{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Cards Image Dataset-Classification\n", "[Kaggle page](https://www.kaggle.com/datasets/gpiosenka/cards-image-datasetclassification/data)\n", "\n", "The data is in E:\\Data_and_Models\\Kaggle_Cards (53 classes 7624 train, 265 test, 265 validation images 224 X 224 X 3).\n", "The train, test and validation directories are partitioned into 53 sub directories, one for each of the 53 types of cards. The dataset also includes a csv file which can be used to load the datasets.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plan:\n", "\n", "* Fine-tune a pretrained image classification model\n", "* Extract outputs from the feature extraction layers and try completing the task with gradient boosting\n", "* Compare results\n", "\n", "\n", "[Nets in torchvision](https://pytorch.org/vision/stable/models.html), though could look at those through timm or directly on huggingface.\n", "\n", "The image resolution (224x224) matches many standard nets (e.g. [EfficientNet](https://pytorch.org/vision/stable/models/efficientnet.html) B0, [ResNet](https://pytorch.org/vision/stable/models/resnet.html)(s) 34 and 50).\n", "The [RexNet family](https://github.com/clovaai/rexnet) is also all of that resolution, and although less common, supposedly more efficient in training than EfficientNet.\n", "\n", "EfficientNet B0 and RexNet 1.0 have around 5M parameters, and EfficientNet B2 and RexNet 1.5 have around 10M.\n", "If venturing farther, then [EfficientNetV2](https://pytorch.org/vision/stable/models/efficientnetv2.html) (the small one, which would still upscale to 384x384) would be even more efficient, but at around 20M parameters (between those of EfficientNet B4 and B5)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# import sys\n", "# sys.path.append('..')\n", "from pytorch_utils import *\n", "from lightning_utils import *\n", "from pytorch_vision_utils import *\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_path = r'E:\\Data_and_Models\\Kaggle_Cards'\n", "device = 'cuda' if torch.cuda.is_available() else 'cpu'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Classification with NN\n", "\n", "### Model Creation" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import timm\n", "\n", "# The HWC -> CHW permutation seems to happen on its own (or the data info on Kaggle is wrong)\n", "# dataloaders 0, 1, 2 are train, test and valid\n", "\n", "# # EfficientNet B0 - 5.3M parameters\n", "# dataloaders, classes = image_dataloaders(data_path, (transforms := (weights := tv.models.EfficientNet_B0_Weights.DEFAULT).transforms()), batch_size = 32)\n", "# model = tv.models.efficientnet_b0(weights = weights).to(device)\n", "\n", "# # EfficientNet B2 - 9.2M parameters\n", "# dataloaders, classes = image_dataloaders(data_path, (transforms := (weights := tv.models.EfficientNet_B2_Weights.DEFAULT).transforms()), batch_size = 32)\n", "# model = tv.models.efficientnet_b2(weights = weights).to(device)\n", "\n", "# RexNet 1.0 - 4.8M parameters - https://huggingface.co/timm/rexnet_100.nav_in1k\n", "model = timm.create_model('rexnet_100.nav_in1k', pretrained = True, num_classes = 53).eval().to(device) # Cannot use len(classes) yet\n", "dataloaders, classes = image_dataloaders(data_path, (transforms := timm.data.create_transform(**timm.data.resolve_model_data_config(model), is_training = False)), batch_size = 32)\n", "\n", "# # RexNet 1.5 - 9.7M parameters - https://huggingface.co/timm/rexnet_150.nav_in1k\n", "# model = timm.create_model('rexnet_150.nav_in1k', pretrained = True, num_classes = 53).eval().to(device) # Cannot use len(classes) yet\n", "# dataloaders, classes = image_dataloaders(data_path, (transforms := timm.data.create_transform(**timm.data.resolve_model_data_config(model), is_training = False)), batch_size = 32)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "=============================================================================================================================\n", "Layer (type (var_name)) Input Shape Output Shape Param # Trainable\n", "=============================================================================================================================\n", "RexNet (RexNet) [32, 3, 224, 224] [32, 53] -- True\n", "├─ConvNormAct (stem) [32, 3, 224, 224] [32, 32, 112, 112] -- True\n", "│ └─Conv2d (conv) [32, 3, 224, 224] [32, 32, 112, 112] 864 True\n", "│ └─BatchNormAct2d (bn) [32, 32, 112, 112] [32, 32, 112, 112] 64 True\n", "│ │ └─Identity (drop) [32, 32, 112, 112] [32, 32, 112, 112] -- --\n", "│ │ └─SiLU (act) [32, 32, 112, 112] [32, 32, 112, 112] -- --\n", "├─Sequential (features) [32, 32, 112, 112] [32, 1280, 7, 7] -- True\n", "│ └─LinearBottleneck (0) [32, 32, 112, 112] [32, 16, 112, 112] -- True\n", "│ │ └─ConvNormAct (conv_dw) [32, 32, 112, 112] [32, 32, 112, 112] 352 True\n", "│ │ └─ReLU6 (act_dw) [32, 32, 112, 112] [32, 32, 112, 112] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 32, 112, 112] [32, 16, 112, 112] 544 True\n", "│ └─LinearBottleneck (1) [32, 16, 112, 112] [32, 27, 56, 56] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 16, 112, 112] [32, 96, 112, 112] 1,728 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 96, 112, 112] [32, 96, 56, 56] 1,056 True\n", "│ │ └─ReLU6 (act_dw) [32, 96, 56, 56] [32, 96, 56, 56] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 96, 56, 56] [32, 27, 56, 56] 2,646 True\n", "│ └─LinearBottleneck (2) [32, 27, 56, 56] [32, 38, 56, 56] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 27, 56, 56] [32, 162, 56, 56] 4,698 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 162, 56, 56] [32, 162, 56, 56] 1,782 True\n", "│ │ └─ReLU6 (act_dw) [32, 162, 56, 56] [32, 162, 56, 56] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 162, 56, 56] [32, 38, 56, 56] 6,232 True\n", "│ └─LinearBottleneck (3) [32, 38, 56, 56] [32, 50, 28, 28] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 38, 56, 56] [32, 228, 56, 56] 9,120 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 228, 56, 56] [32, 228, 28, 28] 2,508 True\n", "│ │ └─SEModule (se) [32, 228, 28, 28] [32, 228, 28, 28] 8,949 True\n", "│ │ └─ReLU6 (act_dw) [32, 228, 28, 28] [32, 228, 28, 28] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 228, 28, 28] [32, 50, 28, 28] 11,500 True\n", "│ └─LinearBottleneck (4) [32, 50, 28, 28] [32, 61, 28, 28] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 50, 28, 28] [32, 300, 28, 28] 15,600 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 300, 28, 28] [32, 300, 28, 28] 3,300 True\n", "│ │ └─SEModule (se) [32, 300, 28, 28] [32, 300, 28, 28] 15,375 True\n", "│ │ └─ReLU6 (act_dw) [32, 300, 28, 28] [32, 300, 28, 28] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 300, 28, 28] [32, 61, 28, 28] 18,422 True\n", "│ └─LinearBottleneck (5) [32, 61, 28, 28] [32, 72, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 61, 28, 28] [32, 366, 28, 28] 23,058 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 366, 28, 28] [32, 366, 14, 14] 4,026 True\n", "│ │ └─SEModule (se) [32, 366, 14, 14] [32, 366, 14, 14] 22,416 True\n", "│ │ └─ReLU6 (act_dw) [32, 366, 14, 14] [32, 366, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 366, 14, 14] [32, 72, 14, 14] 26,496 True\n", "│ └─LinearBottleneck (6) [32, 72, 14, 14] [32, 84, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 72, 14, 14] [32, 432, 14, 14] 31,968 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 432, 14, 14] [32, 432, 14, 14] 4,752 True\n", "│ │ └─SEModule (se) [32, 432, 14, 14] [32, 432, 14, 14] 31,644 True\n", "│ │ └─ReLU6 (act_dw) [32, 432, 14, 14] [32, 432, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 432, 14, 14] [32, 84, 14, 14] 36,456 True\n", "│ └─LinearBottleneck (7) [32, 84, 14, 14] [32, 95, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 84, 14, 14] [32, 504, 14, 14] 43,344 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 504, 14, 14] [32, 504, 14, 14] 5,544 True\n", "│ │ └─SEModule (se) [32, 504, 14, 14] [32, 504, 14, 14] 42,966 True\n", "│ │ └─ReLU6 (act_dw) [32, 504, 14, 14] [32, 504, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 504, 14, 14] [32, 95, 14, 14] 48,070 True\n", "│ └─LinearBottleneck (8) [32, 95, 14, 14] [32, 106, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 95, 14, 14] [32, 570, 14, 14] 55,290 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 570, 14, 14] [32, 570, 14, 14] 6,270 True\n", "│ │ └─SEModule (se) [32, 570, 14, 14] [32, 570, 14, 14] 54,291 True\n", "│ │ └─ReLU6 (act_dw) [32, 570, 14, 14] [32, 570, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 570, 14, 14] [32, 106, 14, 14] 60,632 True\n", "│ └─LinearBottleneck (9) [32, 106, 14, 14] [32, 117, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 106, 14, 14] [32, 636, 14, 14] 68,688 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 636, 14, 14] [32, 636, 14, 14] 6,996 True\n", "│ │ └─SEModule (se) [32, 636, 14, 14] [32, 636, 14, 14] 68,211 True\n", "│ │ └─ReLU6 (act_dw) [32, 636, 14, 14] [32, 636, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 636, 14, 14] [32, 117, 14, 14] 74,646 True\n", "│ └─LinearBottleneck (10) [32, 117, 14, 14] [32, 128, 14, 14] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 117, 14, 14] [32, 702, 14, 14] 83,538 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 702, 14, 14] [32, 702, 14, 14] 7,722 True\n", "│ │ └─SEModule (se) [32, 702, 14, 14] [32, 702, 14, 14] 82,308 True\n", "│ │ └─ReLU6 (act_dw) [32, 702, 14, 14] [32, 702, 14, 14] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 702, 14, 14] [32, 128, 14, 14] 90,112 True\n", "│ └─LinearBottleneck (11) [32, 128, 14, 14] [32, 140, 7, 7] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 128, 14, 14] [32, 768, 14, 14] 99,840 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 768, 14, 14] [32, 768, 7, 7] 8,448 True\n", "│ │ └─SEModule (se) [32, 768, 7, 7] [32, 768, 7, 7] 99,264 True\n", "│ │ └─ReLU6 (act_dw) [32, 768, 7, 7] [32, 768, 7, 7] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 768, 7, 7] [32, 140, 7, 7] 107,800 True\n", "│ └─LinearBottleneck (12) [32, 140, 7, 7] [32, 151, 7, 7] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 140, 7, 7] [32, 840, 7, 7] 119,280 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 840, 7, 7] [32, 840, 7, 7] 9,240 True\n", "│ │ └─SEModule (se) [32, 840, 7, 7] [32, 840, 7, 7] 118,650 True\n", "│ │ └─ReLU6 (act_dw) [32, 840, 7, 7] [32, 840, 7, 7] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 840, 7, 7] [32, 151, 7, 7] 127,142 True\n", "│ └─LinearBottleneck (13) [32, 151, 7, 7] [32, 162, 7, 7] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 151, 7, 7] [32, 906, 7, 7] 138,618 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 906, 7, 7] [32, 906, 7, 7] 9,966 True\n", "│ │ └─SEModule (se) [32, 906, 7, 7] [32, 906, 7, 7] 137,031 True\n", "│ │ └─ReLU6 (act_dw) [32, 906, 7, 7] [32, 906, 7, 7] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 906, 7, 7] [32, 162, 7, 7] 147,096 True\n", "│ └─LinearBottleneck (14) [32, 162, 7, 7] [32, 174, 7, 7] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 162, 7, 7] [32, 972, 7, 7] 159,408 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 972, 7, 7] [32, 972, 7, 7] 10,692 True\n", "│ │ └─SEModule (se) [32, 972, 7, 7] [32, 972, 7, 7] 158,679 True\n", "│ │ └─ReLU6 (act_dw) [32, 972, 7, 7] [32, 972, 7, 7] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 972, 7, 7] [32, 174, 7, 7] 169,476 True\n", "│ └─LinearBottleneck (15) [32, 174, 7, 7] [32, 185, 7, 7] -- True\n", "│ │ └─ConvNormAct (conv_exp) [32, 174, 7, 7] [32, 1044, 7, 7] 183,744 True\n", "│ │ └─ConvNormAct (conv_dw) [32, 1044, 7, 7] [32, 1044, 7, 7] 11,484 True\n", "│ │ └─SEModule (se) [32, 1044, 7, 7] [32, 1044, 7, 7] 182,961 True\n", "│ │ └─ReLU6 (act_dw) [32, 1044, 7, 7] [32, 1044, 7, 7] -- --\n", "│ │ └─ConvNormAct (conv_pwl) [32, 1044, 7, 7] [32, 185, 7, 7] 193,510 True\n", "│ └─ConvNormAct (16) [32, 185, 7, 7] [32, 1280, 7, 7] -- True\n", "│ │ └─Conv2d (conv) [32, 185, 7, 7] [32, 1280, 7, 7] 236,800 True\n", "│ │ └─BatchNormAct2d (bn) [32, 1280, 7, 7] [32, 1280, 7, 7] 2,560 True\n", "├─ClassifierHead (head) [32, 1280, 7, 7] [32, 53] -- True\n", "│ └─SelectAdaptivePool2d (global_pool) [32, 1280, 7, 7] [32, 1280] -- --\n", "│ │ └─AdaptiveAvgPool2d (pool) [32, 1280, 7, 7] [32, 1280, 1, 1] -- --\n", "│ │ └─Flatten (flatten) [32, 1280, 1, 1] [32, 1280] -- --\n", "│ └─Dropout (drop) [32, 1280] [32, 1280] -- --\n", "│ └─Linear (fc) [32, 1280] [32, 53] 67,893 True\n", "│ └─Identity (flatten) [32, 53] [32, 53] -- --\n", "=============================================================================================================================\n", "Total params: 3,583,766\n", "Trainable params: 3,583,766\n", "Non-trainable params: 0\n", "Total mult-adds (Units.GIGABYTES): 12.71\n", "=============================================================================================================================\n", "Input size (MB): 19.27\n", "Forward/backward pass size (MB): 1904.75\n", "Params size (MB): 14.18\n", "Estimated Total Size (MB): 1938.20\n", "=============================================================================================================================" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summ(model, input_size = (32, 3, 224, 224))" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "# Make the feature extractor layers (\"features\" in the summary) non-trainable (re-run summary above to check)\n", "for param in model.features.parameters(): param.requires_grad = False\n", "\n", "# # This as well for RexNet models\n", "for param in model.stem.parameters(): param.requires_grad = False" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Classifier Layers Replacement (not for RexNets)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Sequential(\n", " (0): Dropout(p=0.2, inplace=True)\n", " (1): Linear(in_features=1280, out_features=1000, bias=True)\n", ")" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# NOT NEEDED FOR REXNETS\n", "# Inspect the classifier layers to replicate its structure\n", "model.classifier" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# NOT NEEDED FOR REXNETS\n", "\n", "# Set the number of classes to the card ones (and reset the other parameters in the classifier layer)\n", "model.classifier = torch.nn.Sequential(\n", " # EfficientNet B0\n", " torch.nn.Dropout(p = 0.2, inplace = True),\n", " torch.nn.Linear(in_features = 1280, out_features = len(classes), bias = True)\n", " # # EfficientNet B2\n", " # torch.nn.Dropout(p = 0.3, inplace = True),\n", " # torch.nn.Linear(in_features = 1408, out_features = len(classes), bias = True)\n", ").to(device)\n", "\n", "\n", "# The following simpler option does not complain but fails to replace the actual parameter tensor:\n", "# model.classifier[1].out_features = len(classes)\n", "# And replacing just the linear layer might be biased by the pretrained dropout one\n", "# model.classifier[1] = torch.nn.Linear(in_features = 1280, out_features = len(classes), bias = True).to(device)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Training" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Model pipeline functions\n", "\n", "loss_fn = nn.CrossEntropyLoss()\n", "\n", "# Define an extra metric beside the loss\n", "f1_fn = torchmetrics.F1Score(task = 'multiclass', num_classes = len(classes)).to(device)\n", "accuracy_fn = torchmetrics.Accuracy(task = 'multiclass', num_classes = len(classes)).to(device)\n", "\n", "def prediction_fn(img):\n", " with torch.inference_mode(): pred_logit = model(transforms(img).unsqueeze(dim = 0).to(device)) # Prepend \"batch\" dimension (-> [batch_size, color_channels, height, width])\n", " pred_prob = torch.softmax(pred_logit, dim = 1)\n", " return torch.argmax(pred_prob, dim = 1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Custom Pure PyTorch Version" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training RexNet10_0_FullRetrain_Adam001_10_epochs\n", "[INFO] Created SummaryWriter, saving to: runs\\2024-04-08\\Cards\\RexNet10\\0_FullRetrain_Adam001_10_epochs...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f931c6d1562a48a0ae83b80c633a789f", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/10 [00:00 8\u001b[0m \u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlmod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mldata\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;66;03m# NOTE: trainer will prevent from re-fitting, so if the model changed need to re-declare trainer above in order to train again\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:544\u001b[0m, in \u001b[0;36mTrainer.fit\u001b[1;34m(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)\u001b[0m\n\u001b[0;32m 542\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mstatus \u001b[38;5;241m=\u001b[39m TrainerStatus\u001b[38;5;241m.\u001b[39mRUNNING\n\u001b[0;32m 543\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtraining \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m--> 544\u001b[0m \u001b[43mcall\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_and_handle_interrupt\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 545\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fit_impl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_dataloaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mval_dataloaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdatamodule\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mckpt_path\u001b[49m\n\u001b[0;32m 546\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\call.py:44\u001b[0m, in \u001b[0;36m_call_and_handle_interrupt\u001b[1;34m(trainer, trainer_fn, *args, **kwargs)\u001b[0m\n\u001b[0;32m 42\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mstrategy\u001b[38;5;241m.\u001b[39mlauncher \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 43\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mstrategy\u001b[38;5;241m.\u001b[39mlauncher\u001b[38;5;241m.\u001b[39mlaunch(trainer_fn, \u001b[38;5;241m*\u001b[39margs, trainer\u001b[38;5;241m=\u001b[39mtrainer, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m---> 44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtrainer_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m _TunerExitException:\n\u001b[0;32m 47\u001b[0m _call_teardown_hook(trainer)\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:580\u001b[0m, in \u001b[0;36mTrainer._fit_impl\u001b[1;34m(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)\u001b[0m\n\u001b[0;32m 573\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mfn \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 574\u001b[0m ckpt_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_checkpoint_connector\u001b[38;5;241m.\u001b[39m_select_ckpt_path(\n\u001b[0;32m 575\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mfn,\n\u001b[0;32m 576\u001b[0m ckpt_path,\n\u001b[0;32m 577\u001b[0m model_provided\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[0;32m 578\u001b[0m model_connected\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlightning_module \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m 579\u001b[0m )\n\u001b[1;32m--> 580\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mckpt_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mckpt_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 582\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mstopped\n\u001b[0;32m 583\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtraining \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:989\u001b[0m, in \u001b[0;36mTrainer._run\u001b[1;34m(self, model, ckpt_path)\u001b[0m\n\u001b[0;32m 984\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_signal_connector\u001b[38;5;241m.\u001b[39mregister_signal_handlers()\n\u001b[0;32m 986\u001b[0m \u001b[38;5;66;03m# ----------------------------\u001b[39;00m\n\u001b[0;32m 987\u001b[0m \u001b[38;5;66;03m# RUN THE TRAINER\u001b[39;00m\n\u001b[0;32m 988\u001b[0m \u001b[38;5;66;03m# ----------------------------\u001b[39;00m\n\u001b[1;32m--> 989\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run_stage\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 991\u001b[0m \u001b[38;5;66;03m# ----------------------------\u001b[39;00m\n\u001b[0;32m 992\u001b[0m \u001b[38;5;66;03m# POST-Training CLEAN UP\u001b[39;00m\n\u001b[0;32m 993\u001b[0m \u001b[38;5;66;03m# ----------------------------\u001b[39;00m\n\u001b[0;32m 994\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: trainer tearing down\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:1035\u001b[0m, in \u001b[0;36mTrainer._run_stage\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 1033\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_run_sanity_check()\n\u001b[0;32m 1034\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mautograd\u001b[38;5;241m.\u001b[39mset_detect_anomaly(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_detect_anomaly):\n\u001b[1;32m-> 1035\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit_loop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1036\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1037\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnexpected state \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\loops\\fit_loop.py:203\u001b[0m, in \u001b[0;36m_FitLoop.run\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 201\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mon_advance_start()\n\u001b[0;32m 202\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39madvance()\n\u001b[1;32m--> 203\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mon_advance_end\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 204\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_restarting \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m 205\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m:\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\loops\\fit_loop.py:374\u001b[0m, in \u001b[0;36m_FitLoop.on_advance_end\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 372\u001b[0m call\u001b[38;5;241m.\u001b[39m_call_callback_hooks(trainer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mon_train_epoch_end\u001b[39m\u001b[38;5;124m\"\u001b[39m, monitoring_callbacks\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m 373\u001b[0m call\u001b[38;5;241m.\u001b[39m_call_lightning_module_hook(trainer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mon_train_epoch_end\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m--> 374\u001b[0m \u001b[43mcall\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_callback_hooks\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mon_train_epoch_end\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmonitoring_callbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[0;32m 376\u001b[0m trainer\u001b[38;5;241m.\u001b[39m_logger_connector\u001b[38;5;241m.\u001b[39mon_epoch_end()\n\u001b[0;32m 378\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mepoch_loop\u001b[38;5;241m.\u001b[39m_num_ready_batches_reached():\n\u001b[0;32m 379\u001b[0m \u001b[38;5;66;03m# if we are restarting and the above condition holds, it's because we are reloading an epoch-end checkpoint.\u001b[39;00m\n\u001b[0;32m 380\u001b[0m \u001b[38;5;66;03m# since metric-based schedulers require access to metrics and those are not currently saved in the\u001b[39;00m\n\u001b[0;32m 381\u001b[0m \u001b[38;5;66;03m# checkpoint, the plateau schedulers shouldn't be updated\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\call.py:208\u001b[0m, in \u001b[0;36m_call_callback_hooks\u001b[1;34m(trainer, hook_name, monitoring_callbacks, *args, **kwargs)\u001b[0m\n\u001b[0;32m 206\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(fn):\n\u001b[0;32m 207\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mprofiler\u001b[38;5;241m.\u001b[39mprofile(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[Callback]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcallback\u001b[38;5;241m.\u001b[39mstate_key\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mhook_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m--> 208\u001b[0m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlightning_module\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 210\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m pl_module:\n\u001b[0;32m 211\u001b[0m \u001b[38;5;66;03m# restore current_fx when nested context\u001b[39;00m\n\u001b[0;32m 212\u001b[0m pl_module\u001b[38;5;241m.\u001b[39m_current_fx_name \u001b[38;5;241m=\u001b[39m prev_fx_name\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\callbacks\\early_stopping.py:183\u001b[0m, in \u001b[0;36mEarlyStopping.on_train_epoch_end\u001b[1;34m(self, trainer, pl_module)\u001b[0m\n\u001b[0;32m 181\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_on_train_epoch_end \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_skip_check(trainer):\n\u001b[0;32m 182\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m--> 183\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run_early_stopping_check\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\callbacks\\early_stopping.py:194\u001b[0m, in \u001b[0;36mEarlyStopping._run_early_stopping_check\u001b[1;34m(self, trainer)\u001b[0m\n\u001b[0;32m 191\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Checks whether the early stopping condition is met and if so tells the trainer to stop the training.\"\"\"\u001b[39;00m\n\u001b[0;32m 192\u001b[0m logs \u001b[38;5;241m=\u001b[39m trainer\u001b[38;5;241m.\u001b[39mcallback_metrics\n\u001b[1;32m--> 194\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mfast_dev_run \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_condition_metric\u001b[49m\u001b[43m(\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# disable early_stopping with fast_dev_run\u001b[39;49;00m\n\u001b[0;32m 195\u001b[0m \u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\n\u001b[0;32m 196\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m: \u001b[38;5;66;03m# short circuit if metric not present\u001b[39;00m\n\u001b[0;32m 197\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[0;32m 199\u001b[0m current \u001b[38;5;241m=\u001b[39m logs[\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmonitor]\u001b[38;5;241m.\u001b[39msqueeze()\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\callbacks\\early_stopping.py:149\u001b[0m, in \u001b[0;36mEarlyStopping._validate_condition_metric\u001b[1;34m(self, logs)\u001b[0m\n\u001b[0;32m 147\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m monitor_val \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 148\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstrict:\n\u001b[1;32m--> 149\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(error_msg)\n\u001b[0;32m 150\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 151\u001b[0m rank_zero_warn(error_msg, category\u001b[38;5;241m=\u001b[39m\u001b[38;5;167;01mRuntimeWarning\u001b[39;00m)\n", "\u001b[1;31mRuntimeError\u001b[0m: Early stopping conditioned on metric `val_loss` which is not available. Pass in or modify your `EarlyStopping` callback to use any of the following: `lr-Adam`, `train_loss`, `train_F1`" ] } ], "source": [ "model_name = 'LightningRexNet10'\n", "# extra = '0_FullRetrain_Adam001_3_epochs' # Mimicking the train_combination function format\n", "extra = '0_ClassRetrain_Adam001_max10_epochs' # Mimicking the train_combination function format\n", "print(f'Training {model_name}_{extra}')\n", "\n", "set_seeds(42)\n", "# trainer.fit(lmod, dataloaders[0], dataloaders[2])\n", "trainer.fit(lmod, ldata)\n", "\n", "# NOTE: trainer will prevent from re-fitting, so if the model changed need to re-declare trainer above in order to train again" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "ename": "RuntimeError", "evalue": "CUDA error: unknown error\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mRuntimeError\u001b[0m Traceback (most recent call last)", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\call.py:44\u001b[0m, in \u001b[0;36m_call_and_handle_interrupt\u001b[1;34m(trainer, trainer_fn, *args, **kwargs)\u001b[0m\n\u001b[0;32m 43\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mstrategy\u001b[38;5;241m.\u001b[39mlauncher\u001b[38;5;241m.\u001b[39mlaunch(trainer_fn, \u001b[38;5;241m*\u001b[39margs, trainer\u001b[38;5;241m=\u001b[39mtrainer, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m---> 44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtrainer_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m _TunerExitException:\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:685\u001b[0m, in \u001b[0;36mTrainer._validate_impl\u001b[1;34m(self, model, dataloaders, ckpt_path, verbose, datamodule)\u001b[0m\n\u001b[0;32m 682\u001b[0m ckpt_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_checkpoint_connector\u001b[38;5;241m.\u001b[39m_select_ckpt_path(\n\u001b[0;32m 683\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mfn, ckpt_path, model_provided\u001b[38;5;241m=\u001b[39mmodel_provided, model_connected\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlightning_module \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 684\u001b[0m )\n\u001b[1;32m--> 685\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mckpt_path\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mckpt_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 686\u001b[0m \u001b[38;5;66;03m# remove the tensors from the validation results\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:965\u001b[0m, in \u001b[0;36mTrainer._run\u001b[1;34m(self, model, ckpt_path)\u001b[0m\n\u001b[0;32m 964\u001b[0m \u001b[38;5;66;03m# strategy will configure model and move it to the device\u001b[39;00m\n\u001b[1;32m--> 965\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrategy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msetup\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 967\u001b[0m \u001b[38;5;66;03m# hook\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\strategies\\single_device.py:77\u001b[0m, in \u001b[0;36mSingleDeviceStrategy.setup\u001b[1;34m(self, trainer)\u001b[0m\n\u001b[0;32m 76\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msetup\u001b[39m(\u001b[38;5;28mself\u001b[39m, trainer: pl\u001b[38;5;241m.\u001b[39mTrainer) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m---> 77\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel_to_device\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 78\u001b[0m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39msetup(trainer)\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\strategies\\single_device.py:74\u001b[0m, in \u001b[0;36mSingleDeviceStrategy.model_to_device\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 73\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mself.model must be set before self.model.to()\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m---> 74\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mroot_device\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\lightning_fabric\\utilities\\device_dtype_mixin.py:54\u001b[0m, in \u001b[0;36m_DeviceDtypeModuleMixin.to\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 53\u001b[0m _update_properties(\u001b[38;5;28mself\u001b[39m, device\u001b[38;5;241m=\u001b[39mdevice, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[1;32m---> 54\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1152\u001b[0m, in \u001b[0;36mModule.to\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1150\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mto(device, dtype \u001b[38;5;28;01mif\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_floating_point() \u001b[38;5;129;01mor\u001b[39;00m t\u001b[38;5;241m.\u001b[39mis_complex() \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, non_blocking)\n\u001b[1;32m-> 1152\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[1;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torchmetrics\\metric.py:811\u001b[0m, in \u001b[0;36mMetric._apply\u001b[1;34m(self, fn, exclude_state)\u001b[0m\n\u001b[0;32m 809\u001b[0m \u001b[38;5;66;03m# make sure to update the device attribute\u001b[39;00m\n\u001b[0;32m 810\u001b[0m \u001b[38;5;66;03m# if the dummy tensor moves device by fn function we should also update the attribute\u001b[39;00m\n\u001b[1;32m--> 811\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_device \u001b[38;5;241m=\u001b[39m fn(\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mzeros\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m)\u001b[38;5;241m.\u001b[39mdevice\n\u001b[0;32m 813\u001b[0m \u001b[38;5;66;03m# Additional apply to forward cache and computed attributes (may be nested)\u001b[39;00m\n", "\u001b[1;31mRuntimeError\u001b[0m: CUDA error: unknown error\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[1;31mRuntimeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[48], line 4\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# trainer.validate(lmod, dataloaders[0])\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m# trainer.test(lmod, dataloaders[1])\u001b[39;00m\n\u001b[1;32m----> 4\u001b[0m \u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalidate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlmod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mldata\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 5\u001b[0m trainer\u001b[38;5;241m.\u001b[39mtest(lmod, ldata)\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:645\u001b[0m, in \u001b[0;36mTrainer.validate\u001b[1;34m(self, model, dataloaders, ckpt_path, verbose, datamodule)\u001b[0m\n\u001b[0;32m 643\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mstatus \u001b[38;5;241m=\u001b[39m TrainerStatus\u001b[38;5;241m.\u001b[39mRUNNING\n\u001b[0;32m 644\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvalidating \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m--> 645\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcall\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_and_handle_interrupt\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 646\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_impl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataloaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mckpt_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdatamodule\u001b[49m\n\u001b[0;32m 647\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\call.py:68\u001b[0m, in \u001b[0;36m_call_and_handle_interrupt\u001b[1;34m(trainer, trainer_fn, *args, **kwargs)\u001b[0m\n\u001b[0;32m 66\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m logger \u001b[38;5;129;01min\u001b[39;00m trainer\u001b[38;5;241m.\u001b[39mloggers:\n\u001b[0;32m 67\u001b[0m logger\u001b[38;5;241m.\u001b[39mfinalize(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfailed\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m---> 68\u001b[0m \u001b[43mtrainer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_teardown\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 69\u001b[0m \u001b[38;5;66;03m# teardown might access the stage so we reset it after\u001b[39;00m\n\u001b[0;32m 70\u001b[0m trainer\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39mstage \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:1012\u001b[0m, in \u001b[0;36mTrainer._teardown\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 1009\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_teardown\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 1010\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"This is the Trainer's internal teardown, unrelated to the `teardown` hooks in LightningModule and Callback;\u001b[39;00m\n\u001b[0;32m 1011\u001b[0m \u001b[38;5;124;03m those are handled by :meth:`_call_teardown_hook`.\"\"\"\u001b[39;00m\n\u001b[1;32m-> 1012\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrategy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mteardown\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1013\u001b[0m loop \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_active_loop\n\u001b[0;32m 1014\u001b[0m \u001b[38;5;66;03m# loop should never be `None` here but it can because we don't know the trainer stage with `ddp_spawn`\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\pytorch_lightning\\strategies\\strategy.py:528\u001b[0m, in \u001b[0;36mStrategy.teardown\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 526\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlightning_module \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 527\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: moving model to CPU\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m--> 528\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlightning_module\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcpu\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 529\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprecision_plugin\u001b[38;5;241m.\u001b[39mteardown()\n\u001b[0;32m 530\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maccelerator \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\lightning_fabric\\utilities\\device_dtype_mixin.py:79\u001b[0m, in \u001b[0;36m_DeviceDtypeModuleMixin.cpu\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 77\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"See :meth:`torch.nn.Module.cpu`.\"\"\"\u001b[39;00m\n\u001b[0;32m 78\u001b[0m _update_properties(\u001b[38;5;28mself\u001b[39m, device\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mdevice(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcpu\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n\u001b[1;32m---> 79\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcpu\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:960\u001b[0m, in \u001b[0;36mModule.cpu\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 951\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcpu\u001b[39m(\u001b[38;5;28mself\u001b[39m: T) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[0;32m 952\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Move all model parameters and buffers to the CPU.\u001b[39;00m\n\u001b[0;32m 953\u001b[0m \n\u001b[0;32m 954\u001b[0m \u001b[38;5;124;03m .. note::\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 958\u001b[0m \u001b[38;5;124;03m Module: self\u001b[39;00m\n\u001b[0;32m 959\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 960\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcpu\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[0;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[1;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[0;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[1;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:802\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recurse:\n\u001b[0;32m 801\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mchildren():\n\u001b[1;32m--> 802\u001b[0m \u001b[43mmodule\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_apply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 805\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m torch\u001b[38;5;241m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 806\u001b[0m \u001b[38;5;66;03m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 807\u001b[0m \u001b[38;5;66;03m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 812\u001b[0m \u001b[38;5;66;03m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 813\u001b[0m \u001b[38;5;66;03m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:825\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 821\u001b[0m \u001b[38;5;66;03m# Tensors stored in modules are graph leaves, and we don't want to\u001b[39;00m\n\u001b[0;32m 822\u001b[0m \u001b[38;5;66;03m# track autograd history of `param_applied`, so we have to use\u001b[39;00m\n\u001b[0;32m 823\u001b[0m \u001b[38;5;66;03m# `with torch.no_grad():`\u001b[39;00m\n\u001b[0;32m 824\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[1;32m--> 825\u001b[0m param_applied \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparam\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 826\u001b[0m should_use_set_data \u001b[38;5;241m=\u001b[39m compute_should_use_set_data(param, param_applied)\n\u001b[0;32m 827\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m should_use_set_data:\n", "File \u001b[1;32mc:\\Users\\Dr-Lo\\miniconda3\\envs\\ML11\\Lib\\site-packages\\torch\\nn\\modules\\module.py:960\u001b[0m, in \u001b[0;36mModule.cpu..\u001b[1;34m(t)\u001b[0m\n\u001b[0;32m 951\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcpu\u001b[39m(\u001b[38;5;28mself\u001b[39m: T) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T:\n\u001b[0;32m 952\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Move all model parameters and buffers to the CPU.\u001b[39;00m\n\u001b[0;32m 953\u001b[0m \n\u001b[0;32m 954\u001b[0m \u001b[38;5;124;03m .. note::\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 958\u001b[0m \u001b[38;5;124;03m Module: self\u001b[39;00m\n\u001b[0;32m 959\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 960\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_apply(\u001b[38;5;28;01mlambda\u001b[39;00m t: \u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcpu\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m)\n", "\u001b[1;31mRuntimeError\u001b[0m: CUDA error: unknown error\nCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.\nCompile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n" ] } ], "source": [ "# trainer.validate(lmod, dataloaders[0])\n", "# trainer.test(lmod, dataloaders[1])\n", "\n", "trainer.validate(lmod, ldata)\n", "trainer.test(lmod, ldata)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "save_model(model, fr'{data_path}\\Models', f'{model_name}_{extra}.pth')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Post Training\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Recreate the model and load the saved parameters\n", "\n", "# # EfficientNet B0\n", "# model_name, extra = 'EffNetB0', '0_First_Adam001_10_epochs'\n", "# model = tv.models.efficientnet_b0(weights = (weights := tv.models.EfficientNet_B0_Weights.DEFAULT)).to(device)\n", "# transforms = weights.transforms()\n", "# for param in model.features.parameters(): param.requires_grad = False\n", "# model.classifier = torch.nn.Sequential(\n", "# torch.nn.Dropout(p = 0.2, inplace = True),\n", "# torch.nn.Linear(in_features = 1280, out_features = len(classes), bias = True)\n", "# ).to(device)\n", "\n", "# # EfficientNet B2\n", "# model_name, extra = 'EffNetB2', '0_First_Adam001_10_epochs'\n", "# model = tv.models.efficientnet_b0(weights = (weights := tv.models.EfficientNet_B2_Weights.DEFAULT)).to(device)\n", "# transforms = weights.transforms()\n", "# for param in model.features.parameters(): param.requires_grad = False\n", "# model.classifier = torch.nn.Sequential(\n", "# torch.nn.Dropout(p = 0.3, inplace = True),\n", "# torch.nn.Linear(in_features = 1408, out_features = len(classes), bias = True)\n", "# ).to(device)\n", "\n", "# RexNet 1.0\n", "model_name, extra = 'RexNet10', '0_First_Adam001_10_epochs'\n", "model = timm.create_model('rexnet_100.nav_in1k', pretrained = True, num_classes = 53).eval().to(device) # Cannot use len(classes) yet\n", "transforms = timm.data.create_transform(**timm.data.resolve_model_data_config(model), is_training = False)\n", "for param in model.features.parameters(): param.requires_grad = False\n", "for param in model.stem.parameters(): param.requires_grad = False\n", "\n", "# # RexNet 1.5\n", "# model_name, extra = 'RexNet15', '0_First_Adam001_10_epochs'\n", "# model = timm.create_model('rexnet_150.nav_in1k', pretrained = True, num_classes = 53).eval().to(device) # Cannot use len(classes) yet\n", "# transforms = timm.data.create_transform(**timm.data.resolve_model_data_config(model), is_training = False)\n", "# for param in model.features.parameters(): param.requires_grad = False\n", "# for param in model.stem.parameters(): param.requires_grad = False\n", "\n", "# model.classifier\n", "model.load_state_dict(torch.load(fr'{data_path}\\Models\\{model_name}_{extra}.pth'))" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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P8sIXvpAXvehF3HLLLbzsZS/jP/2n/0QQBDz3uc/lM5/5DG984xu3QVJANUiv5Ff49//+3/Pud7+bZz/72bzmNa+h2Wzye7/3e/R6vW3b/tAP/RC/+qu/ymte8xqe8Yxn8NnPfpb/9t/+27bQu//wH/4D73//+/mmb/omfvqnf5qbbrqJ4XDI8ePHee9738ub3vQmDhw4cNX3/nDp5S9/Ob/3e7/HK17xCo4fP85tt93Ghz/8YX7zN3+T7/iO7+C5z33uNR/zyJEj/Lt/9+/4jd/4DQaDAT/4gz/I7Owsn/3sZ7l48SKvfe1rd9xPCMHLXvayKjnuCU94Av/4j//I29/+9kue68///M/RWvO85z2Pu+66i1/91V/lCU94At/3fd8HwJve9CY+8IEP8J3f+Z0cOnSI4XBYheo+lHv7UpCUkje84Q289KUv5fnPfz6vetWrSJKE3/md32F9fZ3Xv/712/a50n2DF+z/6l/9K9785jdf0a/w2te+lm/8xm/k+c9/Pr/0S79UJa8tLS3x6le/emxbrTXPeMYzKn/TP//zP/NzP/dzfM/3fA/XXXcdUkruvPNOfvd3f5fFxUX+7b/9t9W+P/VTP8Xb3vY2nve85/FLv/RLHDx4kM985jO87nWvY3l5ecxX0u/3ee973wv40HDwPreLFy/SarUqP9yjjr7Snu4vJV0qeW2SXvGKV7hWq7XjuizL3Bvf+Eb3hCc8wcVx7Nrttrv55pvdq171KnfPPfdU2yVJ4l796le73bt3uziO3VOf+lT30Y9+dMfktcOHD1910tRHPvIR99SnPtVFUeT27NnjfuEXfsH9j//xP7ZFpSRJ4n7xF3/RHTx40DUaDfeMZzzD3XHHHTue/8KFC+6nf/qn3dGjR10QBG5hYcF9/dd/vfuVX/kV1+12r/ned0qccs5HCz3jGc+44j2urKy4n/iJn3B79+51Wmt3+PBh98u//MvbokGuNvqopLe+9a3uG7/xG6trf+ITnzgWWbRT8trGxob70R/9Ube8vOxarZZ7wQte4I4fP37J6KNPfvKT7gUveIFrt9tuZmbG/eAP/qA7d+5ctd1HP/pR96IXvcgdPnzYRVHkFhcX3TOe8Qz37ne/+4rX/3CT1yapjD76nd/5nR3Xv/Od73RPecpTXBzHrtVquec85znuIx/5yNg2V3vfzo3m307RXDvRJz7xCfec5zzHNZtN1+l03Hd/93e7e++9d9t2wNi4Onv2rHvZy17mjh075prNpgvD0F133XXuJ37iJ9yJEye27f9P//RP7kUvepE7cOCAi6LIXXfdde5Hf/RHt21bPq+dPg816fFrgYRzNXtxSl8T9Ja3vIUf/uEf5v7773/ItXum9NVPf/d3f8eznvWs6Xue0peVpj6FKU1pSlOaUkVToTClKU1pSlOqaCoUvgbpla98Jc65KaQwpSlN6RGnqU9hSlOa0pSmVNHUUpjSlKY0pSlVNBUKU5rSlKY0pYquOnlNXkVBqsuRqP1/pe1KSeUYIVtlgHB5iDrm5ZePr7j0mUZHHz/KlKY0pSk9uslae8VtrlooPFT2WTJnx9WIhO3nmjzvlI1PaUpTmtKXjr7kZS6ulYkLtgsFNyFNHrJgcBN7PzzjZ0pTmtKUHnX0VVf7qDJudoCJHhly4z+ngmFKU5rSlCq6eqFwKeZ5NVz7Egy+fsgdD3MtfoyrlB51OGtKU5rSlKY0Tl/66KOpJj6lKU1pSl8z9PDho6tl+nWt/0pq+k7HvArVXlxqm2s49ZSmNKUpPZbpkfUp7MRxL4nXCHbm/rWQqR2Od0nGP3G6S55ySlOa0pSmdEn60sNHj6BqfiWBMKUpTWlKU3p4dPWWwiPAkLcz9dGCsdyzetToIxBBerlLnxoPU5rSlKY0oi9PSGrFla8cwnQpa+BSYNPljzalKU1pSlO6FvqK5ym4stzEJcpTXIsm7ya+J3/vtMNUgExpSlOa0oiuWig8fOim/CVqS7az5PqSyXNeat01C4Or2mBKU5rSlB579LCFwrXwVoebOM6V976SP+BS5Z0my2VMaUpTmtKUrkwPGz66NPPdORbV4S5vdtQMCncJSGly04ndRr+m4UpTmtKUpnRN9BX3KWyjugSQ28WBGMtEczv/ntKUpjSlKT0kuvrS2dsU//EOCeX6UjkfVTYdbbfdv1A7wI6GhQMhJsJUiyp2rn60kUkxCVBtP+aUpjSlKU3pUnQNloIY+yrJiRq7d+Xf5TIPFZViQZTsu471XDHWdBJ+qh27TjtYFdM+OlOa0pSmdG308KukXmYHv4ur/QLh3LjSP/l9WSEhqiw3IcZhpCnvn9KUpjSlh0/XAB9dWiqIEs6pGQ2i9PM6MTIyLpedXOYMTPihtzuTd2qC4E8syhNDISimMUhTmtKUpnQt9Ig5moUYCQYxybidX1Z4B0ao0UT10m0WBJNCwY0JhrpvWYgJJ3QpEITATTihpz0VpjSlKU1pZ3poQqGEcMq/Xanmi4rhy2oLN6b9l9+y9nflYqhlGO/k17Y1pl/+HuUpiLH/XWGWOOcQNcFQF0bTgKUpTWlKUxqna/ApjEM249D/iPlLvNUgCw+zmKhwN+ZbnoCKJCOLoV6+tWTnDoFzI2FgyzOL4shjkkfUApVc4YOYsBhEtbE/z1RKTOlRRuJauhfuQJeaE5c77pXmUX3fhzrnHup9Tef4lemqhULJpCcjRsuPLJi1FCBd8Y0suLbFY/7WCw1AVrFIrhASAiW9EBFuBAXZ8hQOLBIHGOGwCL+ucDLb2hix1EJjd7iXHcNWpzSlRxk9XIEwpccmXVOZCx89VC5xhSOZKilB4KOLhChhJFdZCqKIQlJCIAUoIQrjwqGkRAiBVhLlBIpyHVhnsdbhnCN3YPHfBs/8DSUMZHGFEKrDUKPIppoHfJKqNIcySmqqTUzpq50E24zfK8iAK2v9YoftJg5awrJM+vBqaMAOfrzx82xfdq0a/FTj/9LRQ+qnUGrzfvl4MkAlGJBIVwoDiwI0klBJlJRoqTzMJCVaa5RShEFArCMCqXHG4qwhz1KyLMMYQ5Kl5NaSGkPmLAZLisPgyFxpVfiwVQtY57ZdX/06L3OLU5rSV5h2irC7FF155F6OiY7g1VJ3ukzUXi2GZDycZPL6prPpa5WuwdFsC1hnJBRkBQCN/AQeNqISBAoIEERKEWlNu9Ui1AFRFAHOD0IhkVIShiGBDNBSI50Da3B5DtaCtaTJgDzPGWYpvWzIMM/ZylKy4txGeBgpLZ3bboeJVMeVnNdUhBBYV7quBUL4O3CucGNfQvPZdryvCroU8/iqucAvC40FF1yjNjq577botStowle1fT18e/Szpn3LSQ9YsaFfKoUcLXbGn7fadBRkUR1ViJoFLLYNh5EwqDABxsdSOWFG1yOqcBLhFbB6wpHwHkIxdqLJuVJfWz/32EY70GXC48X4878a/8W4CLxUQPxjh665Sqp0rhIOpWPY4pm/EDXhgCusA4iloqE1rTBkrtkiCkMajQbGWYy1GAtCSIIgREmNkgrtHMJZRG4IhUABeaDJ8oxhOmRj4OhJMHnG0DkMfogZSqElJsxb6tjXhCAbhbeOzOLyLopd6xO7Gmh2Rwf8V5YmJzM89MF9pf2+vHd7tZDE5LorMesrCY3J9Zf6+0rrqnPWpMHIf+bKRVCBrXX+WTD2QlER1Zbgx6mtQsJdCdlWpy5zdsTID3iJdyeKc5fnLPffaUu/dX0bMfG9fY/6X46SiZcPoyas6klNbny/S1678BtfSiHYUcBf4toeyyDyNTuagbFh4GrrSyeyloJQChoIIqmZb7ZohhGNMEIJCbmlt7lJkuekWUY/ScmNITMWLRRSeKGghaChNQszbdqNBrNRhIwjBE06g5B+MiTSkq00Y3WYMHCO1DmMk1gEpnRGIzDYyk9RjguJQArvz5BCYp3PhHDOIpDYbZrNlL6SdCkN/VJUbruT5jh5rJ2Y9yRJKa+4Tf18OwmLbdtWgmHSMrj8sHOuZN0jBuzKAb7jqWpWwiRVPkBZaP2jZbZkzqL4r7RWnMNZUwiviVbvI2fjzmcsLlmWFrkYMeDRVarqGEKOGPu1uhKsLYToJRSE8nGVlpetWTGP1Yl/DZbCeGG60iVbl7Sl9aCBUEiaShPrgE6zRSMIiYOQLMvITM4wSRhmGUmW008TcuN9BVoolFBIZ9FCkOeKIPA2SSQcoVZEgSIOAiSOQRYDgiQ3WGPAOnIgx+HESOsRTowmDaOBOsYYavdaOsvZYbuvfvpautYr06S2d7ltyu3KZZezLnYSDJ7xbLceLnX88u9t+TCVZu8ufd0Foy21c6/obmeP1eQaQ1hKm9ZdWg5MnqqCa7br7GI0w8dYvIeIXWVr1Jl9ZW3XnM+j9eMxfmO3XxM6FFuOry6vcuKu3OhOR8/z6sb65DsYe3fVOeuC4MpW8LUqKV8rdG0F8Uqz1GchULp2JSNfgnIQCUlbaeYbLVpRzN65RUKt0UqzsrHGME3Z6PYZZBnDPCN1BoNn5gGgnQNnEM4xsI50M2Nj0CVNmrTjmMXODKEOiHWARBDrIRiQwyF9m5OXprPwV+tDVP2CmiEN+EHh/QnltPHObyFkpRyBd1qXWsdXNz36BulDpZIxl+ScG9P2d7IkLkVXEhT1bcqPlBJr7djxR9CRKBijKPh+cV1FpJ3fZuJTYPqV8uLG/5Y1Fj72HIr/BQI3Nvjrp3FQ+tAQfr4IwFkcrtKghfSblVVthAAlfezf6HnWzzt+K2Nr3M6jVVAYG+UErAJGykWTEmaHYxShWfVE1UmBXTJ1ay3W1bYdw0Aee3RNQkEIVyWPiWJAe+zeod3Ih9BUik4YsdBs0gwiZJaTJil9Y1nfWKeXJvTSAYm1JM6SMwovNc4icCgsEoEVAukMNnes98FYQ6gV840modZ04iZKKD9QLWhShnlaDCrnByv+N4XJXbnHpMQ6O1EuQxSToJjMQhQ+h2Jg1gdkPSawgAEeXXRlbemrkeoa+uTfpWCXRRj0JCRUbl/SJCOZ3OZqcwFE6XBzjOqIOWoMt6ZwVFyx2qjGQAtubMtiMjXtuWCCbkKDLRTz0R/179ohyz9k8S2ggFRH/FmW1yHAFEpi5c+o7Te678nzldqa/xbls0GMEl1F/TjCHx+fm1QK0jKGZJLZT1I5ZUshcbntryZRb+y5PgqtBLgW+GgHR6tAIoVDFgJBASHesdwKQzpRTKwDyA1JmtIfJvR6ffpZSmIzEiCjyDUQAourcH0NKBxCSFLncMbQtQlSQGs4pBNESB0QBSEgMLmlHyQYYwny1AsZ5we4rWkMuFKgVXdWLgZAycK3UGMqbuQNm9BUakJiQl5M6ZGnKzHgnSb55MTdydk8ua4UFHXmcSnhsTMjugRkVarW1BCgiknVGVXBGMeO40ZjTNSW+b2qIA9XMMBSxIzDJmIsOme0dFKrd9WlWjd+usLAAaidw1bHGf8xdvUTf4ja+UsB63mKjwY0E5DS6LyiMuEnbKJCAuwcMVbbx42/o6uBgR6tUNFOdA1CAZACZ0sEToxFIWm8QJgVgqUoYt9Mh+VOB4VgZWWVYbfHRrdHLx8ycJYM7wy2wuP/Fh85JKV/qZmzGIeHlZwjAJy1mKFD5IYmEm0trZkOgQ6Imm2SYYK0lvVkgMBigbQyc0eTWkkJwjvUtFIIKcnz3N9nkUAnJ27eTTAKKAfzDrYy41bDTpGxU/rSkRACrTVZlpHnOc45lFJorStBYYzZxhistdV25X7lOqVUBQWVQqL+XR6vDknV/QnltlJKj8EIgcmLfayt0CFkyXlLn1gpQPyxtFJIIbC59RzbWoQYKT2ijPbw0gEdBKU+jjEOZwtryfnfsig6oKqx7MCWoaSF5eGKQBIlUVpT2touz7DWYaylmFJQExolOQOFCVM+bMBfvm/P6+Fb54RPZFUSlxmvzCEqRVGKkUI3Eij+Bpxz5WMtnr+PZKd4rkIKpPTvYPRu/fuWUpGm6VVFt12tEvC1TNcAH5XwyQhPhMKPUBxIA5GUNJSiqTWBEB73tD4RzRhD7qy3CBCYQhCUdYxcqeEUUQbl7zKyyQC5tWS5IctzTO4dy1JAqCSxVkRaoYX3bchSIJTXXzNtve9AgJQIKRByhC+We4liUmKrOKSJAXAZ7NHt+HNKXyaqM32l1DbHb90aqC8rhQMwYuIwJhDCMKzGSn3/SbqUleKhSL+stLkprIVqnXAV/i8K9VwKgVISKUQxJgvrgVoAq6sHhLhCixe1c1BiLhVK5TV0V11DZbXgfYV1i8JPflvByNW91bYZQ1lr1zMBaPnrY7zAvROl0lluWZ9jk7ZDeb5LwT71W/Y/JqORdgoEqI+DS/md6pbjpN/oa52uvp+Cc7UXVA5lH0hXWgmxELSUoq01nTAkKASBy3OsNVhnPGPHWwcpXpOvDFYBeXUeqsFSCgXvd3Ck1pLlXjhYY9BKEkpoaC+MwuLYJaRlykFfmZD+S4chld0jJdYY8jz3TuYiVLWOQ2+nyzue64N9Sl962infoLQa6u/SOUcQBNU2WZZhrSWKIowxpGmK1hopJVEUkWUZw+GwEhKtVos0TRkMBlcUCpPXZG1ZtqW4vlJlcdZ/6pBIKRS0LDL/JYHWvsmgzbwiZQu9vc68ihBP58BlaYXZl3zf2Zqy5Eqr1laolX9ufp0qcKlynlibUxamFIVAoriOwjgZc7WVrrjtj8fW5mR5Us9bXCXVdoKASrhqFK3lnEcahC3PL8b2cQ6M8cfzFs04ZGiMGbPmynefpmk1XurCREqJUqra/1oCFr4W6KqFQl5qT4IqMUwh0EgCIAYaQjIThLS0JhYC8gyTZWTZkCxPSV1OhiWDAj6CUrQIUWoFxpurcjRwraOqd+Q/zh/HWXIMCpBSEQWaRqgJpSSwhsD5GzSMJoArjieL92dMjrGWXbt2EUYRWvtHUmpC5YDYyWwUOwzcat1XDD661MB8KBdxuX2++iZA3fmrtcYYs23C15n4pIVQQkR1K6MOOZXjoC5QjDEFo7fbfAwlbCVr8KRSqmDOoigHg2f8BXd2lZXsGR2igIQAhCMKlLea04QyukIVkIq1I25vXFEoEhBC4bNyAq+5G1HBvmUtMl05iz2s5Bm59TkCQuCk9/kZa72PTUiEUJSFbIw1fv5Kf0PlGVxpKWyjcva7mkU+goZK1VNIt11IOG/ZCyEQthBWpSIpyqPW7Y1CMBVSURbvxGv7Hp1IhkOGwyHnz5/HZq4aKzuNsbrVWb7nR4tAgGsQCqXTtuTWwo00eAUEQhIVmcuxUoRSkGcGZ3KsyTHOYLAVY6+qnFYDCA81ue36dd2oLfczznkoylmcUEgpCk1KoaVAW4FiBD2VRfLKI1uoJrO1lsWlRWY7s7Q7M1XI3SQuPEmXEgrVljWr98s3ZC5lvWx3lF6Z6ujtJF1aIH4laNL8D8MiJybLqvdXh5HyPK/efRAE1bqS+Ze4c8k8pJTbhEUQBJWVUVccym9rbVXXK01ToBQKxZivtE835sD149wVjL34qxjrkfbBHTZLkDiksGhVEwqFILHOx+wYC4haGIiTYGTBsgVaeEUvwFVCxhmHtQ5rDUIVG2g1EgrSCwUlQxASh8TY3Ef6Vda4rD6uXFSS82y8jJaqYC+H91k6V/j9PLspd7Y2LxS7wj9ThI1vFwDFU6uhDnXGXQoFrXWlJG5sbLC+vs75Cxc8TzGTUVSj7PdJ6OnRRlcPH0GhIZR/+e8SPmooRUsHzDWbdOKYZhjQTxOkMb6GkfMCoWLuomDwhQkqagwUMeqVIGxRQgNQwmc5Zs6SmIxhlpDYHI1CakUUBsQmJ1CSwFq08VFR0o1KcpQTBmvJ0wSlFHEc87znPY+bbr6ZJz7xid55hai0zNJU3E52Z5ZZQQO1P78s1sLlGPXlGPzlaCdh8tUlECZpEj8u36PWmmazSRiGKKV8kcUkqSZ7u92ulpUCoO4gLq0CYwxRFBHHcSVcSkugPH8pXKIoIggCBoMB4IWJkhopJOlwgLUesgy1RmtF3Gx46SAFSZqQZTnDpE+ep+TZkCiQaAXSpgRKEAWSRqxREpzNPRMUhbVhHUme45zCOUWWhVgjyTKvYQuL97/hCLFI60vLYPICRhuiAo0MFFG7gdQSAonQISiN0k1cGTBii8DRopqAc96hLhAgC6hFlLaLF0BetoiCP/gRlRfFL+MgRkiJUKAKKDfJUqyx2MyiwwCpFKHSlRC1zjvts8L6z/O8KKNj6PV61VwuQ82jKEJIiUPwqU99is997nOcOnWKwWBAmqR+hLvSAhlZm+U7LpWBR5tguObOa6O8xuJhUbMYBARSeE1d+JpCHs4cMZGROHHVQBBiXJWu5EONuUpElSDj8PkMubPk1lamMiUmKCVKCqQZXdvYwcXI+VW+2E6nw/z8PM1mk263R3erx8WLF8nz/NKm5FcdfPRIC4XL7fPVl8hXdw4aYyotPQgCms0mu3btIooiWq0W1lr6/T5bW1tV1NHs7CxZlrG5uUkYhhWUmOeeSTabTQBOnz7N/Pw8s7OzFTRUFwrgBdFgMCCOY5rNJisrK9U4i+OAKIxREgaDAf3NTQY4pBC08owojmi12si4QRxZlIJ+39DbGrB+cR1sxr7ds8TNkGYU0Qj9NtbmVE4C5xm1JMOYnDwXbG11GQwMq6t9TGqwmSGSEi2gKR2NQBMqReC8lZBlQ6JmTBiHRE0IVEjYbEAgQSqE1pVamGYGY8E65eEqqT1EJiRSBzgsxhnyPAXn0Fr4OSqFt06cw1kY4P2MzTj2ypgqi2/4qMHcGHJygsi/n1AHnh9YU4WSa6vJ0gxnLGsba2x1u5w9e8bzhiAgL8bG8vIyndlZOp1Z5ufmmO10xpi8N3pGcNGlclUebXQNndc8c6u7gevwUWWgSkkgfOUSJSjwzkmBQOFU80xHFMLD2h0YrxBIV5jHhbVh8Q7p1FlS5yOaDF76CykIdYA2Fln4G7br+SMd3jqvWbTabZrNJlmWcerkKY4ff4BPfvKT9Hq9StOsyI3dyc7Py9WS92sy70oJM5dKlLl6unb46FLw2CMBH10q63ena7jUfjslG+20fR0WyrKMVqtFo9FgcXGRPXv28PVf//UEQYDWmn6/z4ULF/jc5z6HMYYg8JV719bWuPvuu1leXqbdbiOEYDgc0uv1OHLkCEIIPv7xj3P06FHiOGY4HJKmKRsbG9V1WGtJkoTz589z/fXXEwQBd911F8YYDh48yPLyHubm5ukNBqytrHDPF77AcDjAmJy5uTnm5+c5ePAgzXYTpRVpOmBt9SL33/sFvvC5T5MOuzzr6U9i1+IsevcsdghSOiDxmLnw+T3WWvq9IcOhZTCw3HvfChcvbvH5z59i0B2QDBIaUhNLyWwo2TXbYa7dpK00YDEmYXZhhlanhcj205qbIVSLuDzCqQAr+zgRYAnp9XKyzOIIUCpEB3EBXQnCuIGxOVme0e9v4pyl2YrRBdRbCgVrYWtzi35/gLaOIAhHfiBrSfOUNM8ZDhPiRkwQhsRhhLGWLM+qYBjrYDAYsrm5xR2f/jQnT53kzjvvRChJEIakWUaj0eAbvuEbuP7667nhhhtoNRu0W80qjNn7eURlXUzmqdShZWPMFefB1xJdvVDwIQ6FA8w/MFuxe4GxOcaAswbhrLcWlPSNc6QPoyutCSUEuogysK6c4EVmZK2Oihcevl+CYNSFzYewllEHZZhqjnEOK8YdW1L4xj6xVOQIcmBojI8AwfrY6yI2XSlFlmWsrq5y4sQJPv3pT7O+vk6WpvXQh9rRr+BTmNgSLq1dTEbMTC77ytClhIKb+L7MER6iUKjvu9Ozmdxvp21LLf0Zz3gGeZ5z9uxZzp8/XwkQrTW7du2qhMj73vc+tNbMzMxw/vx5Lly4QBRFzMzMsGfPHhYWFrDWMjc3x8WLF/nQhz7EDTfcQBiGrK+vk6YpeZ6zuLhIlmWsrKwAsLq6SrPZJM9zHnzwQS5cXCGOGyzvXiKMQm5/0u0kSUKaJmxtbZEkQ+745zv8fUmYm20jXM7SQoeV+Rb9XorLu7gcbFbOG4O1AwQGK3xBR2MceW+AScAmsLlylgtnVjl+zz2sr3TZ2ujTEJKGVuxqBGzMzrDQajAXBmjpUMJgd3cwC20WZjICM49r5rgoxgURMprDyQihGkibI61/D4EIiLTy6onw8z+xkDsLtlDrrEEhCXVhWThHnhmUAGEtwnp/YKi1t+aFIMtAWIc1BuFAIdFKo5TzOQjCl/no9fv0ul1OPXiSz332s9x//Dj//OlPY6wF6fMeOrMdlpeXWVhYIMuybWOrDE0vx0rpM6o7lx+N0BFcq6VQ3H/dseOjDwoG7ewodAtv7ikpUUL6KAdGNZJkETEh3OhokzCLm/gw8V06iazzcFLVZGcHktKbob5tqK2OVMeMy5c+TIZsbW1x4cIFVldXvVDYkS4DH01stW39FSyGrw7aSSh85f0JVxKa5TsNixLtpfY3GAyqhk2lf6HRaOCcI89zVlZWaDYbzMy06fcHFSPQWjM/P+/LvRtTCYUzZ86wvLxMq9WqwlaHwyFxHBc+Cdja2iJNM+bm5gA8889yur0eYaiZabdptReRWhJGIWmekWYpg+Gg8HdYnEkINYTKgsuRGGw+wGQCm0kMOQgDtg+lgHA+y98MB9hMYVNJOthk2Ntka32VtZVN1tf6NBE0tUI3Q6JkiGo3COOQQDq0zEmChFQOsFvzuIaAYRMnMhwpQoeFk1whi1a7Sji0hEAJrPB+BakkxgqywmftCh+fKhRHqaQvu2RH0VBC+LwMrRRWCEw5T4WoqhsrKdGFv08W53HOsWW7DAcDVldWOHf2HGfPnOH8+fPkxhQRXYI0S+ludQv/ka2g7DElw42Yfz3HpRx7j3lHc4U+lB7gIrPG4vMOMufDRnNL0TZTEOiAOHA0dUgsMwK8c8tbHKY4rPBFtvzigsEzyk4UYhSfZMsAOMpSRpQxyj4ZDgyi+lghyJ3PiM6yHCckSE0gFdJJjDAopSpLoYQQtNIIwOQ51pixCJRx7eDhM8hHyipwrh7HtdOJHsKV7riPP4OszlRLjtrhmi4NW40/u3EhOVo3anh0aUuqbn3Usd9SAJw6dYooirjhhhtYWlqi1WqxsbHBysoKn/jEJ1hdXUUIwQ/90EvZ2tri7rvvRghHoxHxdV93M8vLezhw4CDD4ZA8z/n//r//j7vvvptPfepTfOELXyAIAg4cOFAxiTvuuIM4jnna076ZU6dOcvr0Gc6fv0Cn0+HW226jPxzQHwz4f//wMYYDn32/vLyLhfl5brjhBg4dOcSTnvRE1tZW2djY4M47/pFzZ07wwP13Y5NVGhEc3SNoqAZbOibXGVoZQp0ghEUKS783IEsNw60c4xrktoGyPbQbooSh3nIH6xC5RaQZYiCZiQMCm+OSLnojRbCFWu+g44ygF5CaCBuEGGlQapYwDogSX+peaQgiSdjSoKJiIitk4pDS4kyEc5ZGIyCOI+I4AqVw1hGKjGEUkycZrUZMGDcIm02fqOd81nQaaqRSNBsNwjCk2WgUzmI/ArMso9/tcf7cOe655x6++MX7ePDkyWKMUCTrKZQMCIMIrUKkVBhjyYsMc6WUj15Ls0oTLpXdes7So1EgwENpx1nEzglJJV1L2MYKyHBk1pIZSxl2U7bfDKUkdD6LOdwBQrD4VHVVxLyKMkyteOXeh1H4KEqnj5AIqZA6wKQpmbUM85zU2rFs6XqvBFdIoFILKOPZS2zQy6KJomK1aIPxh3L5gXG1NVMeCaFwxW0eynEvsdziRpL8sltebvnl1/kgkZEZX517h2TCnRLWFhYWmJ2d5dChQywsLFQRKN1uF4AgCNi/fz8zMzPkec59930RY3KUUuzevZtOp8OuXbsqx3QJMTrn2Lt3L1mWceLECZIkodvtVsJpfn4eISRnz54lSdLKQR0EAWfPnsU4S2YMC4uLuAJqbTZigiBgbW2Nrc1Nzpw+TZIMSZOEMAyYm5vF7N/LxTM9hB0ghQGX4Qw4meLIsQyLcAwDJkXiiENFZjzTbzdC2s2IKFAoVeZA+6idNCvK2QuHSUNC5YikIDAGlaZkmxtkTUXe7SDUDCqQWDvEZZpsEJInkGc+ykkqgctDfGad771oTeY/NveRiLkkyxKvVkrlS94PM4aJ99GkaYaQCqF8xKGzljzPyNKMZDD0fVkcBEHm4Z2i/lKapfR7PXrdHt2tLQb9AVmSEuqA3ORkxp/fWh9J5sqSH64oAWL8uiphze3cnOfRTFcvFKx34kohfKpCoalbW5SqED5zOHWO1FiSzBAUJpgXCIpYKmJrcECqVBHdWuzv/OAUSqKVGOFCdmTWFW5pfw1ViJhCKo0MvFBIjKGfZgxNTubqZTRKIVAKBz8hcmcQMiNN0yqmva70lgxoUkAUa6tlV+MrmPz7kRhsY9eFq2nwk9txzcFHl9zHjTJyyzNf5iiXOsi2/UbPsH58/2Oy5HX9vqswQ0ZWQxAEHD58mKNHj3LbbbehtWZtba3C+ffu3VsJjDRN6fV6/O3fvp92u811113HsWPH2Lt3L51OB/BWR1xExOR5zqFDhzh48CDOOc6dO8fKygphGBLHMQcPeqvi7rvvZnFxkcXFRaIoYjAYcM899xDEEVEj5uh1R2k2GjSbMb2tTQb9HmfPnWNjfZ0zZ04TRQGNKOLG6w8xO7OPg3tn+VRyke5GglYWKfPiXQxxLsPkPYQz1UcLRdiaIU0lgwTmZhp0OzmNhibQsqoSkDvLMLP0+5Y4z0laIXGkaMUBkctRScpw9SJhYEmWWsTNAEVIkvex+ECNpC/Jc40x3mYPtESoBkgNIiLPPCyW5wnWWVQGzubkaQJInHVkSUqv16XfHzAYDLDO50UI4eesh+cSet0uOFdUM/AhqaZg5GmasrW5xdbmJpubmwz6fbI09eGnmSA3tlIEy6iyMjfCFcecjCSbpLpV+mgUFtdmKfjGBFV0fl7giBmOxIG2ll6WE2c5zTSjE8egQ4IwJkxzQp2iU4uyFuHGH7wUgkBpn6kIRTk7f+IyT8HnKuBDTpVCaY2QCgP0soytJGFrmDCwlsQ5Mjy0ZYqg1rK2Uu7Kktqu4k1lW0QlZNWN7XKYtas45pUGhRj7FqLUgP0yP8AmmezV0jjDFdWyna752i2FS+5TXPPkyp0F4/ZCgg+FJh3U9WSiMkKl1OZLjb6EBJMkodVqcfvttxMEAVJKBgPPeL7whS9U5Sq+/du/nfn5eZaXl5mbmyOOY8oSEZU/zbmq2F6aptxyyy0cOnSI48ePs7q6yurqKoPBACEE+/fvp9lsEkUR/X6fLM9ZWlrybWid4/7770dKQRQqZjsdmo0GBw/sZ9/ePRw9eoRGHKGVxJo+W2sXOHfqFP3hAIvXmqOwya5d84SyixYpWoY4m+JMikAinMSZBltdR5IZ5uZn6Q0dcSPwmr7A+x7wfc0TJxg4X20gd5LcONKBgdQwXB0QBj2S1S2CmTZSCZJ0gA0ibNwiHSqM1Ugtijp9AYgcXAjS+UAUm2GdZ97GOR+IEgQIIXHG4XJHGETkkfUhp1VSISD8cw8DSxyGhEFAoDWB9j6F3BRT2VhfVK/47YzFGkueW58TVfg3dQEbV0mLD2MsPtrompvs1CsgldE/lgI2co7EGJI8Z5DntBxF5mBAoAMfKpplviS2sxWjL1mrEKN6KmWcvxT1wnZFZmrhYFJKIZWPckjyjEGWMcgz70egKMldZROUGdQ7MLrSucSlNf4r0aVDKidxdVEFMo22uRrhshONjlVcxEM4xkOn8Ud1+ed2Ocf6jtniOwR77RSaOvm7npcwMzPD7OwsYRgShiGtVosgCCp/QxlVUma3Hj58mPn5eebn5ytm4SHF8dIG9XPOzc3RbDbp9XpVKKqvuAlaB5UVUzorm80maZaR5hlb3S7OWZKBI45C4ihEB43KQR4Gvs7R1kahNRtDGIVo2SA3eSWgQh2iBWhlfFKywTfJcRKbSaT0yaNRHNBohoShQilZNMwRVTXi1DlS68iMI7MOY4vKAcaS9VPSXkKyNaDRT9CNkKK/IU4LcBoIkCJFiBRkBiLEJwt5bV9W1Vx9fkKp2EmhsMKhta9JFQQ5gfahw0rrylLQWmGNf79aqSqQBSGK8vZgtPVKY6HYFd7iAipy1eAaNdN69DL3h0rX0KNZeSzO2FKtrhrj5AKGDijKVkvlC3c1wohYB0TNGdpCkStNN7cYl6BsOlboTjiHzbKKNfooJYEW0mcl49NkFIJQauIoptloEMQRuTFs9vus9rpsDocMfGwEPk6jrJXkIzKs8KV5BWWVgfGiZaXfoF4KudRGyzj4EV2aCY8zsJ0hlPLYXw4TdOSb2Zkmnbf+urhmyGmHM1/iIFcnCEsmMilE6gmFdTgpjmPm5+e5+eab+aZv+iZuvfVWWq0WSZJw3333VRFIs7OzLCws8JSnPIXdu3cXfoO8sjTK8hVe0Oiq3lEJUSilmJmZIcsypJRcf/31HD58uPIzrKyscPfdX6gCFObn56tyGkkBVTaiEGMysnSAzXK6m1usr66hpCKOosKxnaFERqjh8HXH2LO7RZas0988zvrmJmsbIYtzChkIMuPrIKkgYNgfYnKQtnC45zntmYDZmZi52QatliYIIR16m3wAaGMRDla6A1we0BJhWaqYzZUexjpUoIlaLQIpiXc3i7pkDhHEOC1odRw6FuiWBKW9YFARYpijfLwpzgkazRZRFBFGkU90s45IZVgrEELTarTQYYgMdRUO76ttaKSVlcDQYYRQikB6yFnpgGajSTNu+J7wRTa1yXypHevrePty5YWyKQshshP0erncmEcjdATX2KMZamZWaU4X8L8BMucY5IZemrI1HDLbTEFI4jAmdDFNHHGvTyIgHOaYglGJAtaRCHwFRId0RalgB9KNymmEUhFHIVEYEoQhTkBmDYMspZsm9NLEazx468UU8Uoja8EVrurLYNoFlFSPqXGFV33knnv49IhrKZfDiERx35e0aLb/PX64iQPX0KOdbmN0nnHmP8Jjy3Xb9py88B0F52TMeLlMa00cxywuLmKM4eLFi2xubgK+xMTS0hJhGDI3N8fMzAyLi4tF6YuAJPGKgK+UW09aGpU8qZ+zXgqjhKW01iwuLhIEIUmSsbGxwdbWFqdOnar8U81mkziOaLYa4AJSVSRv5oaN1XV0oKEzSxRFNJtNAmlwdojJu1xcWaO3dR7SDWZaisxAkhqs9c5lJRxKWrLUdyu0Q8NgkJOkhsCkSGloNgMaTU3clCSpxZgighAPI22mKaGEYR4QCOV9g9aQJ9DbGNBb20I3ApoLAcI4bO6Q2vsXrenjTAhZA5xCSAcEOGMwWYZJUxwCk0dYrX1xJud7Q5jcYHJDnuXkuUHIIolM+XFh8hyT55WVJ6UsIpN8LpMzlizxVWGVVkRRVHVNFKKc00WWtZDVuL1cuYpLKW6PVoEA1yIUXFEuF+mhn5p5X4alCqBnDDrNCOWQrSRFyIBGKyCSAqcUzV6fDGikCa6qUS+rQne+fopvuiFd0X2tsBICJKFSNOOYOI4Iw9DjodbQSxO6if+UHd0yLAZFCVSNMrLLFzrunKx+Q+HMlhUjLX0IBUujEGfsxIUrVifq209utDMEsuNxdqBL8v7JY7n6ldZCN3e4jhKrqR97W6To5dbveGHjlkJdnD5UkVgvNzAJKQVBUGUxD4dDTp48iVKKVqvFvn372L9/P4uLi3Q6HR/S2GxWVpEPnPA1c0qt3tdIsmRZXjm7SyZRNWYSo1wXpRQLCwu0Wm2iKOb++++n1+tx//330+/3sdZyYN8+du/excJ8ByUloRSkaUKSJmysrRNGIVEUF4KrjZaWfm+d9ZVNzpw5x+rFB2mGXRbmGhgrGSQpaZZjsxQlLFqByy02MyRbKb2BYTh0NEyCxNJuR7TaAc22Zn0zwxjvf0sFDHFsJikhgn7Dl75ACbAZJoHeWp/uxQ10KGkfaENgsXmGFBYnDCbvIlOFFgEikDhlIAixmSFLc7IkwSEIgxirNFblSClwxpGlOWmSkSYZWZIV1XFcUTrJ+YrLaUqaptWzdsaXt8jyDJNb0iIRTSuvHJR9UnzQpECiEEoiJwogXi7n4GoEwFdPwunDp2uIPip7twqkUD4JpShzXQoFgB6AyXGDPnJ9g60kgyDy+GrYYGFhgbDVwgQBG/0+ajigV9QtGSUsAIx8DkEBI80328w0myzMzRGGAQbB2vo6W4MBK1ubrCcpQ+twRUtNH31kihwGL16EKGEHByiPdRbQkE9YqVVGdd56MUwyS7dtyY5U4S/1EEpRyJTCdmV7XaUyceaqaLsMmLwIRp6gHTaqvN4TjuO6vBN4k7Dme6mfdye5cHlw6OpvbjLSoy4Q6o1vyk+p3WdZxrFjxzhy5AgH9u0njEJUAQsNBgPOnTtXRR1prYmiiK//+ifRKEJDjTETfRR0dd48z8eclMYY1tbWOHnyJA8++CD33HMP/f4AISSzs7PMzMzwpCc9iV6vx4kTJzh1+hSf+9xnCQPF7GyHY0ePsHt5N/Ozcxz4lgNY6xgOhjx44kE2NtcxWcJcp8G+PfN8/Tc8hV73GO//q//J8q45nPDWMlISRi20cmjloVirDCaF2HnopRlrQLB/7yIX1wasb2Wcv3iR3OQkBSpsHaxlFkFGu9dHNZsoIqJYk+cp6Waf1bMr5DZh1/WLaBURRposH2BsQjaQ5GnCcDBEhUOkbhHFlnRgGPZyBr0UhyoK+GUYk+GcxOSWXjdlc3OTfq9PGIZeMGuFUJ41DAYDsjRl0O2TDIv3lGdFljLFu7CEYUi73WZxcZFdu3bT7fW5uLZaTLmy7I7FmMxXd7W+9+PDabL+aBAGJV0DfFQyhDLjkIqPlILB4DX0xFp6zhGlCVZIWoMBjdgRS4EOQmIEM40mubHkxmDSpFYPXUBR66iEPEIpCYu+z40gIFAaYx2ZM3QHQ7rDIf00I7XWJ87JMjdhxBJLVlVBRztUqRNU7pIaWDba1+NHRfrcJaKPdvAcbD/P2OlL8TJ6vtWxdxxnrjqRmzz8paD74kU56gluNY29sgBG1tAIJqxVrirfS32n8qprVoTfv36cunTZ9gBG9+WKbcT45tVZxLiQqJv1UkoCHdBuzzA3N8/evXvZu3cfe/fsZX5+HmstG1ubdLe6DIYDer0eaZLQ6/cBb2E88MADzMy0mZnpEEU+qWmU12K3CShjfPXN4XDIxYsXuXDhAmtra1WV1TDUtFotFhcXieOYwWBQlGMAnCNLhoV+UPZEFqP+DG6UdV+OOY8+CYyFXj9hOMzIcostCs8pqVHSoqQrHLzeOWu0wxqHUhAEkk67wUy7QasVo5S3oKskVCBx0DeWrTSjH1paGqxQ3q+YO9LekOGmIN3qIQKHajVQWmCFw5gUxxBLgMv7KATODQtr3/j8CvBO5yKCxBXdGMuSB74TIlUvBwSV4PN5SSMlbtTYx1v2CLyjvtmgM9thbm6OTqfDxfXVEfRXcoVaY6Nynj/CgO7XJF2DUPDvxGvVAA6MAiymVq8I5wdW1znSZEic52yYjE6zxWyzzXynQxhF7F5YIA5C2kHIxtamr19vDAVARVljXgrhIzGiiDiMEUqTJyndJGGYZVzY2mKQZ/QyQ4IjF6NmPKNr96LAN3YS4IoiW5R1133vaWddVaNJOotzvmFoqRm7IjyxnMgj8VH+b7fl7475JYr/x8XJhBVR/hoTTiPyQ7dIuCmX1aGoUuhBTXK76iC+SRJFZnn9qKO2J+XGrrxPV19eC+WtnaJcMOLnomon6XmqG91U+RxG8m07iWqr2rlG5Yvr39ZaojCmM9Ph8bc+nttvv51XvepV6KJuzhc+dzcPnDjBRz76/wCHUpJjx47RbDVpt9tsbm5y4cIFXve6/8ji4iKPf/xtPPnJT2H//v20222sdb5iaBRV2a6DwYBut8uHP/xhzp49y+rqKrt27WLv3r08+9nPptPpVB28Sl8DeOtmc3OLbrfH+XNn6XU3WVk9T5YmrG2s8nfv+RDNZpMbbriBG264iV1Lu4lDxcrFc3zx3rv5+D/8HWdO3c/W6oD1jSEra1s0wrhISFNIHMIahMmRWOJGiLVFr2qbomTIrsUOSwttFueb6CLoovQN5kAXsMYie0MiFSGkptOOiQUERGT9hJ5LOHfPCWb3zbEQ7KYx3yQONUOVY3WK1UNQPS+IGjkykIShJI5jIKDZbqEabVSjSZ77oI/WnCRqxQz6A5aXdhOEETIIoYg+SpIBeZqS9gbEYUSgNboRIjxjKpLPDChFanL6yZAbb74RlOCBkyeqng84W1gHoywmIVyl6JR1We0YF3ns0NULBVn2uptAHwqoo+QNTriqf0HXGhLnMENf+iLNfUXTQPtSE6ZocDLX6QAOJUA6g3SWOFBFfROBVP4lDZOMLEno5X16aeYzl7OMzBpyirwEV3SdEkAx4D3nLxjdtkqsBfRQ3k/t/1qBje2QiBjBKeWek8xNUDT4mdi35KFjekvFIEttfvvxyu1LMSSKBrtjx66gsXrCV2UyFeHAoyDZ+rXZ6mqKvx2VBQdlaYtCay2kimNkRZbPbOwey5uQpaU1fkP1P0uRUw6y0Z262r2xDQP2+PII0y+jxLa2tuj1epw8fYphMuTmm2+i3W7TbDbYtXtXAU/4iqn9fh/nHIPBgLNnz3HixAmstdx4440+7LMopS2EYDAYcPr0aY4fP85gMKDVarF7926WlpbYvXs3MzMzVR/nsooqUDnChRDVPvnCHLuXF8mylDRJCOIIY/y86HV79HsPoCVgc+Zm57nt1idwYN8y990taLU7bG71yBcjQBEEEcIKhDW+JDU+uTNVGQKDVg6lJe12QGemQWemSbMlSFIYJKN3kRlvLQwcdPOczSxjYAxSCyIVYfOUbJCzfnYNoaA52yIMVTElHEZbjLKI0CtfaX8F50KcDVEyQEiBCnzynbMpCO21f+eQSiALx7uoRmVt9DuKWkXF2Belb6BIpLV+BCmtaTSbLC4usbi6Vmzrh1aZF4soEnKVrNmyNcXnMUpX32RHWBByNMnLCV98iwJCsBSmofNF6pSzmNSQGsMwy8hsThQEtMIYLSRaK5qNGK0kcahRJkc6Q6fRQCtJIAVZ5iMOzg1WSZOEfrdL31iG1hZRRj5i2vd+BmMdKIHQsqp9V7btc0Wck4cpCsY6dqPjiWSCwrtRmgvlcBnj2F4bn0Q9SqEgGTFeN7nb6Gf1fzlE/bl3Qoj8/7KmiZfWSyVchPcPVocthYLbLqxkNf1GbQ3L6Whqlo0vOFBaALJ6nqUhUpYaBlGY5YwuTpTBxzUBIsf+HD1358asHxgJBNjuS1BKVQmH5fr+oM/qik8mO3vuHHEc8bjHfR3Ly8s+dyGOKmdx2aFt9+7dfOELX+Dv//7vefDBB7HWcvToUYIgqBrzWGsZDAacOXOGu+66i7m5OWZnZ7nppptYWFgoSlyIKnR1a2uLzc3Nqi9Hq9Wi1WrTaDRZWFxASUEYepjKGMPRY9exsbHBqZOnuffe+1hZWcGZnIW5WQ4f3MuuxdtJBhvkg/M0Y8PmZo80m8M5RRBoKOCksoGN7y3iEOQEGqQSGBEyMxPTmW3Qain6Q0jy0VDJjH9lA6BrDI00o59bQikRYYRN++RZysa5dZSWzC7MojoRSkscBpvlZCpHCY3DkvYDhGwiZBMpm0itUMrgSHFWFAPZj3wKhKCEdoQzo+FbOIWzLMdGo4HuijFTJqkZ6xBSETWaLCwusrS25q0JIVBKVIlsiEKRKLq8FXKCkWr02KSrFgpWOITwTltRMEknPVdzBcMV+ESzkg+UNAAykzOwlm6eooQgVAqNr4rYDCNCpZmJQmajkJkwBJMjUQQopLVI4wjznDDLCPOcwFlyvBO6dHLX/RpS4J1ZBbuSFJisb/U24lOAz9IeVXm1ZZvPQoQApeQbJ8+J/bGE8D13i83KJkNSCGTh3CiT8KBkyqOhVxcYI629TMAbffv7dKMNcTVLR3j4oHgP2o6KB1Yx2ROf8njl+UtbgCJMuIQU/BlNVYnWiur0FfSgS1UMQRn1XT6/4lGNnWe0onY7OzwRV9t2Mm68ZBSbZpP+oM99999LoxVz5uwZZmbaHLnuCHv2LTPoD7h48QKrn1/DGkOjGVeRSpubW1hruOGGmzh06BC33XYbzjk2Nja47777WF5erkpXlKGphw8fZm5ujlbLx9vPzc1VHfp6vV7lzD537txYs6ZGo8Hc7Bwz7Q779u2h0YxptVu+FpFSNJsdwrDJzMwCR4/eQJqkrK1cYG1thbNnTjLoXSQZbIAIGA5Tzp7d4OiBBdrNEOtipNQoHaKkBZvj0gxMgssHKJeiZUy7GbC02GZfd4G9e+cwwFq35/sfVAUtIQQ2shzp4EK3j40CGi5CmxBpHd3zW0i3RRSex4aKRmII986iAoFWAmcznBHk6Qa565MTEEbzSNcg7zpk0EIELTI7JDeCpG8Z9IYkw5yGiohCn8dgnMFYw1avT5ZmDPpDpFIYJ9CmsE6sIc29j7LfH5BmhiCIOHDoMEjFoUOHWFldZXNrk7LVqW8fKqrua27CMn6s0jVYCtWvsUnqoXVX8lpgxGxG2qb/yzqLyX0bvsTkXigAxlpCpcEaAhzaORpKgFYEOgDjUM4RCkEkFbFSRX12h3Jlgx83ppWPoRRVhA21K6v/rtVDqqva1T6jI47Wj44wyWwF/sGWMJoujNJRuQ6383VOPDODZ8h2Yr2r71D8KLtTIUYCIHBF0l9NIFStTWvnrh938t35bPVaYUEoSq4Vz0Mw5nMu4brS0TzWZrX8e0K4VhbF5WhSINf3L5y+1lq2trZYW1vj7LkzNJrX0Z5pI5UkNzlp7guu5XmO0rJy7BqTV4lqcRyza9cuXzI9y+h2u8zOzlbnAZ/v0G63iaLIV9UtymmUSY9lCYzhcFiV3qhHSJVhrz4+vhxP3oEqpSAIJEoFNOIWJjdVdm6vu4nNu5hsgApCsmGP4WBItzek349JUo3C+xM0OcLmuDwlS4dk6YA8HSJkCCIj0IJmw1sMzY0IRM+PAeHHnKJ0OlsGxtBNMmIhGOiAplAINC6TZH1Lf61Pb7WH05LZ+RZSKAIti3pmxpfecAbrcqz1VU2tHYLVSBPgnMQZgc2t9wkYgzU+98LVPibPqndl3AgGcq5o/1kMMK/xez/O7OwswyTh4MGDIKA/6JNVOSeloiLGFJZSaXwUBRRdE11TO85tmmrx9MpQNtx4JzafuyBwwtdZkThSaysYo9wuTYYEUpJmCWnSZ0tr0kGTVhCQNxo0goBQSGaaTUKtfYr+MEHnOWmWYvH+BEMVwOBfsPUOs1IDqK6/qKhYMqjKmSoAWU5OWUU0WGombq05esnUvQDwjF4X9xU4L6gUjoYQBIgiM7v8uDFt3T9XfxklDJYBSfF7SF3AjrYtBYAS2+Gq2Fp0cX1B8awDRttV118+r5rGnheFDsvr8PVxRn/jnC+CiH9m5UVNTqTKGikiZ/xzdw+5RelkWCowFoW0trbGAyce4MMf+Qhz8/PceOONnDp9io2NDYZJQhiFtGdaLC8vF/Vzgqo382AwQCnFkSNHGAwGbGxs0O12q7j4IAgm/BiqKqo2GAyqSrtlNrTWmoMHD9JoNKpyF1mW+XlSCKAwCFEqQOsAqSSDbADOY+W+qijMzS4w2+lw5PBBzp25n5WLp/mH7mkuDja4sLLF6TMXwKY0o0WUGyBMj0AMkC5DuZT1jXXW1zfQwQxRPCRoCrCWVkOye9csW/0cKVe99ed8HSGsHytdY8FYLg581nWUOfa0Q2aCFoG02EHO2slNUmlprrWIWk2iRUkUt7zj1xpSmeJ7OadgQ5y1KN1AyAAhNKEIfGG7QEKgUVYUzbm8b00KcNL3XzBSVHkGUmmCIPTVVKX2yooxGOPQeYYONHMLc8zNz/Jt3/ZtfPwTH2dtfZ289Lk4gbMCa0aBJpTDVMBj1M/8EHo0bzP1C5eoKBOkRu6hiumq0bKRoi0q5p05z6itcRhnSfIc4RwDHeKsY67ZwIVhEWuukFphlEanKalzaGt82jqOAF+czxiqwmO+CF7BRAscu9IIRFmHRVafev+EEpopg43K8DefCFNkWhc5HEHx0UCj+B0BTbwpHisfWhsp3wu37GXtrLeiUmMwRTG/oTMMraVnHQk+/6Ms8JcyCiEcPVP//JWjEgQzxTXExXUE4AWUlIRaEirt712M3m1RMJLEWlLrGFrLwFlS5+hbywDvgFSUJU5k8W4LuEn4ird11d7L3HFzQrjRGKohSLWBVtu8xvTBjVtz1Tn8sl6vy8ULF/jc5z7L4259HIePHqbRbBBEAZ25DlEQEAQBnU7HZ7vaWolkqRkMBqyvr1f+huFwSJIkVTmLsZwWqKrrDgaDqsnOmTNnWFlZqVpw1ktw7FpaYs/yHpYWF5FSMhwOWdtYJ4gidOBDapVUSKnQgUAqL9id80lmu5f30Ok0kDyd++69kzuzLTIj6fYT+oOUZiRpRs0i+kgQCEkUN4gbma8EEIVEccQ8ChnA/j1L9Po5jRiGCZhsVKEgdV4ZUXjfQigEm1nGrA2JhSLUETjIhinDtSEA3TPrYAVhECE6MSJUSGfRUmGVIk23kDan0ZpFaYMIPRxtc3CZxAUCZyVBqNCBQkUB0lmkUwRZihOC3IIONCrQSK19pWSpPc8RRVIbFicsrVaTRivm9ic+gf6gz4kHT/DF4w+gdVDUptLVRxYlMR6rFkJJ19xPoW5ijVENanGlz6GQvL46aSE0atC8K+KMc+MxvtT5UrkpIKwj0cXADjRaK2aCsDLVc+fjsgdphswlxnqQQxeXljvIjE+AM6JgnoIqJru85hIlkkUTcan8d6WJlsC4KDVELySkEGjnneolDBbimW+IZ8ghngnPIIiEoK0kcRDQCiKaYeSZsxQV7DBIUzJr6FtD32T0bM5GbhlaXym2zNQO8AIhoRZ+W0FV/rwh0EYQAS28kIoEzEhJrDWNUNOIwsIROYLGCsWQofGwQT83bJqcobVsWFv1u9bOV59NhahKn+cFdy/z3EZsvD6IRiu2BXBdBY2Jmx127vf7gOO+++7lwQdPcPbcWRYXFmm0Gh6jDjRaaaIwxFpLmqQ+dFT4+P/SiV2WVi6d0Hme+7IJtQ599TyFJEkYDof0+30eeOABHnzwQT70oQ+xublJr9fDOUen0+Fxt3wdj7/1VoRzdGZnEULQ7fcIGw2iuEGz1UFL36JSaV/mJfCKPUIYmguLSNFhflYjZc7pU/fi6DEY5gyTjEYYEEYNbDpEOh/tFMUpjUZOGIWEYUAchaAjdKTZs2uetfU+rViS55Y0pco78mUv/JjqO0tkDFtZxtD6SqqoEGdy8tSSbPr+0N3zGwRK0261vEAAJBYVaAIFg7SHtQZJglI5KijgWwFOQ64EVguUlqhAIQNvX0tnCULP+JW1qEChdGExSF8cTyKrwIOyiW+jGROEATfffBMXL17g7s8fYXV9E2OtFwZS4cteFCVN6pjqY5SuIaN5HG+rmD+U6PEIvhBlM5xCA8vMGFRRwR3WVgOwxLkdnsn1TU5ujc/MzBMGUYxrtYiDkGYUsdRqMddsMddq001SVvo91pIh/TxnPUtJ8FqtURIjBANnRvCLKPpMqyIAtMB5y1rq5ccY4wsA4mvPe+HhY8GVc2gc2o2EQQuYFYKmkCw3mrS0ZjbQzAcBsZQ0hSOSikhqYqVQQhIV2onAd4gzQIKja3K6ec6F4YBunnF2MGArz+jlhg3nBcKguB+L91tIIMRVlsGSULSlZE4HzIeallYsRBGhEsRaoEUBeYkSKhPYwjsztDCwlr41bBjDwBjOJ0M20pSNLGM99xZN1xiGeOZRwkseHLNFNJMfCZ6RlrZkMaSucuLtlPEti8b0Jcki4clDOUMuXLjAHXd8CgCtPeMItCYMPFRRwj9BEW7qK3aGdLtdzp07V0FJu3fvZmFhoWrFWXZzO3v2LCdOnOBd73oX6+vr3Hzzzdx6663ceuutxHHMwsICn/zkJzl//jynTp2qrIK9y3vodn0f5kAJGq0W80uLBI2YIIiIG5GHXC3eKgawFik1cdDAmQHWQqM9x9Hrb0aqnC/e/XGS/iqDxDE7ExI3OljtEC4lkClRlpPnliDQ+J41Q6LAF5M7enA3xsAt1+/nvuNrnEm6DGrCOivG2WaWg4TQGeayHJlpIqVRRCCa2GFCalJW7ztPtpWQ9VMW072Ecw2C+QCTJhjhx4bVKd2104TDAUHUR4dLCBpImkhhimqqWWHWq8KPZYvENoAcKS1Kg9YUEYQ+Wsk648Pni5pK0vmOcDOtFjffeCP5t38bSZKxsrqKzY0X5v0BWZZicgO2RJEFxjw2JcM1WQo1FLe2QpRFDMecmSV+vg2/rvwOrtImS+3Pa9yi0EY9TJA74512DvpCQJh7fFxqQqFo66CIc/E1lKI8w0nJ0Fm0M2RK+ugZW4StOgqnYgmVlF2XbFUYy7rx4liicCn4ekxFtVZnCVzhFMdr4rNCsKg0baXZE0a0tWYuCOgoSSwEsbAECK/JW4sSjqCKXhpBMImAhpS0tCYIQ7pSop1jM1N0VU6UWx/JZU2F9ytGVkJbSBpSsieIaSvFnNbMaUVTCea0IpDealAl/FW7BvBCJhWCRCkGUtKUmoGyBALaStFWGj1M6VuDsKCKZ1I+MVOBiMV7hFrpjpEqtiNstCMJxMSWlcVaubRLRiaqDUxmyNKUQDdxxtIddove4MJXIM1y0iQpIJWYI0ePsbW1xcWLF2k0GjSbPrktjuPROCl8GmWJ7uFwyObmJqdPn2b37t2sra3RaPhyLkePHq1gJecc83NzLO9ZZnFpkfm5WZrNBnGjQdBooMMIVZT19lnkozsswzSF8Bg4CKTUtFozLC/v5+TxzzIcbDJMjfcHCI1SYWHcGhDK+8oECGHB5Z75Kku7GTLXabBn1xznz/e4KL3CAYwltA0dBM7St5atLCdKMzo6IEIQCo0zKc5Z0q0hw1DTbwS0F9tI5dDtNlKBko4oUD5q0fqIKCsjDD3AFEmChiR1pNkAKxyqiIIzDl9yPEtJs4QsS9C6FrrhBNY68tz4JLcsJcsz0nToO8FZy0y7xaGDBzly+BDNZpO52VlajaZXGoS8BH977NE1CoVamYPSU1g5OP3k9IzdoZ1FU5a7HjGtgKoSbqW5l0LBO2NFhc+rYlIkaYpIU2SvR19r8kaTdqNFFMa04phWGLLYbDHXSujnOZ1sSN8YesYUCXSWIE9Ii14PAkPmLP0yXhlDVrMQbNGdqfQ3COG1aYmo2hwGQOy8Rr4AdIRkWSr2xk3mgoj9jSZtpZhVitAkKJMROeMjkhwoY6okslGJCN9XOhaC2SDAhQG7g5AkCNlsNOlaS89YzvT6bCUp5/tdBliK3lXeZwAshRGzYcSR2XnaWtGRkihP0cYQ28yb31gCfCSYrkQ2iOIN5UKSK0WmNEkYkgnBZiOmax2b1nLv6hrracb5LGXdpGxawzoeg/Z54OURvbbgyrjYCV9CscUE1adnPYGwEAPO1coTFMvtyAGttabZaDA/N8fe5T1cf/31pGnqk82KRLWTDz7I6VOnuPPT/0zcbDC/uMjP/dyrEUKwurrKDTfcwPLyMrt37/Y9EIoENCklURSxf/9+du3axWc+8xnuueceHnjgAZRSdLtdnvnMZ7J3715e8pKXcNNNN/H5z3+efr/Pwvw8T3vaUzh25Aj79u6hMzuLVBqrNK4Ii7QlFoiPyrNYtCy1Yeed+lZhnaDZ6hA3jvDPd7RJc8n61oC5jiXLFbFqIFGYPMU4313NVtk8vhy3lClz7ZC9S20ed+NhLpzd5NzpVdKkCAyQvue6dbABZNYhbU7UH5LkBmUjOqFgMYwQeYrILdn6kH5usMmQKJKYwRxznZgglqhIMNOKsUHAgAzcAGckSe6wNiDJG2xsZvQHFislYdQkiGcwzvd86Hb7ZFnCcNADZxgmDZQKfEJb7jDGYoyl2+2S5xl5nhEE0Gg20VozM9PkcfM3s762zurKKjqM2bd/Pwtzs6yv+5LllRU7lvH/2KJrKHNRwByOGgvxkSSlli9xBMJDKhpfiCsQgqaShEIQFizHO5lHse6JyTG2SDopjh3hsfoIaEuvaXeEIFKShrWESYrOLS5NsVJhVODNcSHoFE04pLWkyZA8t0iDVzeM82+8iBbyWixj5QiULpp/lE04itA6gY8q0ggiHC2gKWCXDphXAQeCiL1RzJwO2I2iYRwtkxGYDOVyQkwVpup5pEPa8vmWyWOQO4Gxxlef1IqGlDR0QEcoBkoRBiFdB600pG8NifXXFkpJW2vmw5CZIGCPhIZzNE1OkGUokxNZX/5AYZFYbymIonZRISAdglyo6rmGgSWXEi0hdBA5GIYxHam9XyQVBHlKZnMEhSO88N+Uh7XO1lj9lXUxMbbFZDKRKIIGvK0xqmkDQRjQaDbZvXs3119/PbfdeiuNRoP19Q1sltNsNGg3W8zOdDh04CC7l3bRaLVotpqsr6+T5zn79+/n6NGj7N27t6pbVI88KktsaK259dZbmZ+fp91uI6Wk2+1y//3302q1kFKyb98+Op0OxhgajdgLmVbTjzflP0jpo72cRUifIJdnGTZPwRq0BKWk71SmHFIpnNMIESJFzNKufZgsZePCfayvDzkhL7BrXhOFXiEbDHN6vT6R0NjQIIQmyy2IIYNBiMly5joRM21FqwG9QRHUUEDGTvhgkARHF8NKOiQzGZHLyRsBDR0zIyMCoXwiZArpZsr6qVXSQULQiQkWmgQLLVx/iAtyXznVSGzuQCukatBstLBOowKYnY0JoiYqbHqhYH19pzQN0BraMy3iRoMwiADhS9UYLxiCUJGmKUkypNlq0mi2CMOQMjHpuuuOsnfPXlCKVqtNGAWU8FOZhPvYBI48XYNQ8Cx0HA5y1XcZ8RK5ou+BgFZN642FIJYSbf2kUlJWTKOXOlIjGFjfyckLhVEUz4yUNJRiRnjHbANBmOeo3GJT37PBKY2OI0SgaSiFU5JceGhD2ELdMc63/XOlMChqLBW/Za2bW1V0C296esbkm/xUUUUCZoRgQQcsBSHLUYPlIGJOKRaMh4jiPCNwPks7EN5xPpbEVgPWfQJd0TXOGvJcoGyAVZqG1DSlJJUCqTQ9ZQl1QD/3JQkAIqnoBCEdrWkqySIQOUNkLSrPUXlOQI50FuG8UBDCeqFQJCH4DGWP2TupccpDXLkqWqDiw2tTHdAQqogX9xNqq2i12Mc7940oHOFuZCGIK4qDyXE3GZ00+ksUUQKuptaVXdeWlpY4eOAg1113Hf1+n2Q4BAeNKCaOY9rtNsu7dzPb6dBot1Bas7q6ThAE7Nmzh3379lU9msuktLoPoxQMR48eZXZ2liRJWF9fZ2Njg/Pnz1dVOhcXF9m/f38BOUmiMPD9gosAB2Tpb7FVF7jc5AyGfUw6xJrcR6kpHxLbiBVaSx+G6TRCRMzP7yZLBqxfOEG3l3E2WyMOZnFNSRRAluYkw5QkTLxiE0RYDNYmDAchNhfMNDXtpqbVkGhtya3Xn3xwhtfUMxwDHJt5hskzZrAEEuabMc1Ag5AILDbPcb2M7oUt8jRlZtcMTeEImzE2SHyNM+G7pVnjkDJGKkUUQe4UKEGrFaKj0GdQW4mx3rmvtUBIQ6Pl32MUxQhfPQ8MmNz7FZJEo5Qgjhs+9DeOfUBHbti7Zw/GWGyRbFkWbHHOPtaRI+BahIIo3MDO636lIFAIQhxhAV/MAJ0oYCGOWVCKltbsabdoKk1TKUizIjTFxxs7ARv9AYNkyNrWJnnuscVQes13JgyZjZu0wpA2otDSJa6wa1ObkyIYCNhKB/QTy2Yy9HCGsaxbS985es6ROkgRVWinq5VZ8KWRS5RdMCqXN7pXH97pHbmzCPYGEYtBwHWNJotac1CHLDpBKze0+wNC52jgUC7zTLioEOm5Y3lsAA9RVVo1EovFWshTixEZJkvJpcJIRewcKZblKCALNXkJ3UlBU0oiCQGWxqCHdo7QWbR1FfYvitjTCoKxxgsrysovAmVznDQ4kxPYDCslgRLEStOWCuU0s1LSiJu0A8VcHCGGPVbyjEGSVmGN9byKOmpbQ8xrY8yrHLJSO0bhv854haEuIWzpQ1Aa8Pjz8t69HDp4kGc+89nccMONzM0usDS/RKvRYmtji7W1dS8kkhRjLY1Wm83NLYZJgnOOhYUFbrvtNvbv389sER00KQzKyLSyd8LMzAwLCwt0u90qm7kMRS0T18oWklEUIoQgyw3JMEVqB0XAg7Pw4IMnWFtb4/TJB0n6PUzmGblWijDSLC0t0OnMcOzYUaJQE2jNwcM3MdPucPHMKXrr5zh97hzznRbSheiGQtiQQEUEyuf4IIoaANIhhUUrRasZcuTwAkl+iM3hSexWTq/rrTEnJUYpUmuxxu+bAc08ww0FckMgZxrYQCNlXJSqEQxWhiRbKUKcYH69D8OccF8H0Y48SBmCCSV53sM4QyI0zkZoFSF1ipAJkCCF7+McaI9JGBuiA43UEmtzhFBIJfycwUcmhYSAJIpjgjACHWCzjNxmvsQJHp7LjS/LURRg9dBkMScfq/bCtWU0TzwjiUAXwqAKxRSCOaVYDAOWtKatFLu09hBIEYKKYxTvrySxVgxMQBQEZHjoJJKSUCtmwoiZQvtvOIF2PhQUIbASUqFIBSghyZ3DWh+Bo6zF5ZnPqqSqhVhF69RdoQClp9XhB4Zl5IQuM5DrIZ8xgpb0TteO1sxIRROIjSG2ltgZAucInfOaOV47r56nq3vux3VoKWyVrSmcQFE2OvcQg0QQOUcoKKrCFjWAgBjrE+ech3qU85q+z6UoOlUXqZxV2KgbDwqoxKGzYMFa4YEtJ6vn0CrEyFBK+lKSIGkrxcBaIorwWeevzzE6PmM5B6O7r2wCIUa/J7YpfU+ujGWtbVaGKi8sLLBnzx6OHj3K/PyCL3onJc1Gk+XlPYRh5MtmpylpniEGA7Ki3PWBAwdYXl5maWmJZoFDl++qDh2VlkPJ9EuYMYoi2u023W63yrBWSnlIsrBCw8BHPAWFNeqdpI5hktAbDLjnnnsZ9HtkSYKSwmvLUDnIt7Z6ZFlOe6ZDZ6bJ/GyLMGrRbM3RnlkgHw4Y9jYxRmOMKqKsPKNVOkAHGh0orJNYJ4gihZOKhlHs3j3HMIfP3XuRzA7oJqaA/hx5YcU6igZWAvrOERnDZprTzSyB8HPZs2OLMDlkhmR9wKDRpdeMoKnRzqEaMVIYnDQIcp+HIVOkCpBa+sgQLAhbZDRDlmUkacpgMCQzxoejFvPYWofJvU8hSTOscVjj53zUaBC3Wj6YJPd9rqWSRSQhSLtDsU8hHqsy4RpqH9V+10s5BLgKX28IWA4Uu8KQPVHMbi1pScGCs4S5ITS2shSklGgXIJ0iEZI00PQaDVKdYmxOrENCpWlFMZGUaARBjvcH5BZZ2N+Z1qRS0Je+3k5oFV0JdjhkM0uL1jrjZRpc/aYmgO6ixJsvyeEsvnfb6L4jvEBoC8GslMwrzaIKmANaeU4zy4iNoS0s2lkC66M9tpe2Yyyr15Xe5oLhFfzYJy4x6v7mpA+xtfjkIl+/ZeTsl0UWs3SgrM+0VsXyEQ912BI4dRQ2gn8AAm/FSQrhKCxYg3MChSF3EDiBEYJAKp8vIX0S26xWJNYwI0f1c4reZMW9FvVligk37iko68OOmD/lNdhRDn0lTFUtphxHFEfMzMxw9OhRbrnlFp785CeztLhEEIbYLKPVanHzzTeTJAlpmnJxdZX1jXVOnjpFdvJBhmnCNz75G1nevcyuXbuKVzHqzGWMqZZpravs5ZLpSylpNpsopciyrBIY5f6+Yq3Dmrwq4OfwVT2z3HFxZYUzZ8/yvvf8FTMzbZ54+xM4sG8vs50WqigKOegPOXXqFCsX11hd2+Tggb3cctP1tKIWzTbsXj6Kct6KdihyqwjDgDwcYMIBURwSxYq4GeKcxDpJ2Ihp5AoVa8LWIfYeOsDnv3gaFa7Rz7bo9h3DxM8HBcTCR6ZJYN06bO5zDlqDgNwKokZEUygCqYikQriMdHWDjXyFtN9nlxI0dnVox02kUeAUNtA+dNwkhDNtwihCWG+lighs5lt0bnW36Pb7rK6u0+31SYq2nGma0u12ydIca13hHwwIdESnM0uz2WL3nuWqLElnrkMoQ+9nUBLnY+jHBcJjmK5eKBRzULhRTR9ZJFWV2H8bwYIKWFSaXdJj2i0Hc3lOaAzaGESWIZxDSYWyxmOouU9aGxqLQWKFJkASIGlYgciKeOMC38+zFKEUTgqf/YnHJ1MpEVqxGDVJBaylCZt5Tm69NWMKjV8UDMqTKDDJggHUPqXGXGrQPipKFFaC14xnlKKjFG1rfVkJm6MK56DE4FxO2SV6sgDeqGZQwSQFZVylZ5DOazrlEmcdOIuUAosYhYG68p5cFTIr8AKhdGgLVzQqLzXrMTO5TjUUX5TCwVYSTIocZ0BLQYAjVoKmcAyFoC0VfaWIhSB0rnDKe+ZvGIFl9dNOTsTKGqhlMCN8nwvvULRjwqD8ajWb7FraxbFjxzh69KjvxRyE5CZHlQED1hLGDVQQ4lbXGAxTzq+scODgIVqtFvv3HyCKIgaDQZW7AKMghJLB9/v9KiQ1KWCn0sdQCoDy77Eevw60Cqprdk6QZ4atbp8Hjj/AiQcf5Ou+7nEszM9x7NgxZmeaxFHgwzKtw3QsWgesrq7xD//4cUxm2L9nH9HiDDpos3ffUUyasrpykbvu/iwzseDYgaeQ6B7OBUUOigKlvAXqBCb3CosSjplWTBQ3uOmGAygdcH61S5o5koyiyrC3/JJi7ChAWIfMDfEgJckhlgELgaahQyLhYUaXDjAbjl4yQEbnaW4MCcMWekmjRRPpAowOyESAzCQ2sZy5cJpuYlnZyrl4cZP19S4PnDrL5laPlZV1Nrd6JElKECjy3DAcJkUmPSilEUIihELrkEAHzM7P0Wo1menMsP/AfuYX5rnpphuYm5tndnYWhysCF0pl5bErGK4ePpIeyhCiZDSjMg9lNm9DCGaUpiMVs1LSwdFwjrYxBMagTe7T751DW4sshILNBdY5mtYVAIdEOYGyEBuwuQHj+zBY48tgIByuiCZwTpA7QSQlTik6YchWlhErRWgMgfCF80aVSetY2DhUURcKTGxRwkeBEERC0hCKpvTRQRGOAIuy1veEwDvdHPk25+pYr5kajSVziRGg5N04rgjrrFkF23hs4S8oBJAs8SFbCqVSEImqJtF2bF9UpdCrI7vRsT2mblGFBRU4Syh83kMsJbHwkWZBMS6qaCsmJtuEhVZ9j12Mq5bLcsLammitICRBHMXMzc6yd88elpeXabValYavdOAPLUHJAKl9ZmySZWxudbnxxhvZt28vc/NzOGvpbnXH+jLU+zSAbwvpncViDCYqqfQjANW3LS01Iave5CAxxjEcJpw/f4EzZ85w2223smvXInv27EEJhyxi9UVR5tn3i7acP3+RpYVFhoMcYyRBqOl0FojiGRwBJ0+dpxXhwV2nR/FmQuKErMa0cyNANQogCDUH9i/RG6bM3KPZ6hnU0FZKTFmFGOejzErlcC3NcFawEDsiJZgjGEGTJsAMfN/l7rlNbG4Z7u7R0E105LzQdpLcQU5GlvQ5+eBFVjb6HD+9xsnTFzh3cZ37T5xkc6vP6upGJRSiUFf5DaXGVwreMndBCOkbKs20mZvrcPS6oyzvWUZpxaFDB4niyFdcKCCkamw9Rukaah9Z75gtNGuvhY7i7htK0daKuUbEfBwxH0Z0soSGtbSsJXKGEDsqyOYMIjNFqcOybK0YQTx5ikCipcEZg7OOOI59jwZ8dUmLwAmDld7X0Ah90xQxM0PPWlrdLWJrGOYgjB/YOT4axhbMZCeqnImVU9FVSXkBHstvKEUrCGgHIS0d0Mi9s11iwOUY63FVKYseBzWs6FI6SL04Xlk3qmwpasEzE0DaAv+sXf+ouY7zMe3Cv5fSiqgLop34MZRaug/Lq0qk46NQCieDFzZYlMvROEK0z9ZWipZztKyhKRWR9QKjrJFUAlST4d8j6HYkpMuSKOCK8iMKKf08NeXFFH4RIQVhqFmam+Pw/gPcctONHDl0yJewKOoSicYIL/bl0R3DNGGYeiip2WwyNzdPnhuCQLOwsMDFixfp9XpsbW0RhiGtli+iF0URrVarKnFRlr4oxw2MRymVCZG+9AIkWYooWtIpJXHOY+Xnz53j1MmTPP87vo3l5d0sLs5z6uQDbG5uIIBG3GBmZpa1tU02NrbYt+8Ai0u7CcOYPDMM8pSV1S3OXVjn9Lk1VjcG9FXOp+/8PKEeopWjTUDuBINh6ptXCW95ZWlOd913SkM1efzjjtCZaXP+3BqBvkCou2z2HbmBLPPfDjBBSGotLs+RxjBwKc1k6P1ezpErR0sIFoJZED7nvXexz+bWOg+k99HZ36Ozb8jMYUkepJwdbvCFk2e578x5PnbXFzm/PuDEhYR+bkmMJbV5qdpgnK9VlWQ+I8YLej/XstyPZD+2vJW2sbXF5tYWZ86e5cSpUywuLRBEEcM0o9nuMBimpHnOlK5VKLgSl5eUJZRLb33dWViykzIeX1qHsA5hrO8K5Vy1DOuqSeKQ2AIv9/PKoZypaigp59mjwlVMShUOVsUo21gW0EtZ3W0UR1R8RPldgyhKJlNqxNXwc9s02NLxp0TRxISyrEflr8KWwE/hMyt15AozHynBxXl3prI/RcUsa5DTyOrZQbGpCQEvy0V1rhGQM+rK7Ip7LRmbpGSk3qooz+1czRoR/iOFL1uihKia3dTtr9Hvibsck1I7WXDl1ZXPy1WCs1wr8T28m2FEp9Vitt2m1YiL9+k14LIqrr8f/y8IAxpxTLvdIk0S1tfWaMYhjTimETequkcrKyuVf6B0Ppd+g8FgUFkF9eqtk/2j/eOvm3Wi0kodRQvJcttiHPrkSYkUkixN6dsBWWbZ3NwkSVIOHjjIrqVdhGFElmX00wFnzp5lfXOT3FgWd+1G2QH3HX+A2RnJbEfSnFNYIYuEOG/JWWMxmQGTkhuBE5aZpqPTCtm7PMeFlT69bkp3kELVr9orcJnzmcQGbxkKZ9nIMkJ81F0zDlBaYKRGFYEWIveQWrLWpx9sIUWM0zMkMuDc1pAH7z/N8VPnuHhyhfVeSm/TMHRF0UxdRgYWlVKFIDe2UhycLdo+2cJZWMDC5cs3zmIzg+v1CAuYMEuzApatW8cTQ/ExRtcgFIrBShkB4zXu0vj0WZOjMMQR6xGV198WfZids1USmc/qFZ71SIUTCosgryALi6KoSiq82a0KYYQDLRRWCFIkwoIwDpvlxflskeU4ikAq0JNKcfd9FGzBue1IsLgiUmd099tcxUpJAiUrGK3MbUAIclc2KBfekVXsWGrvZa/k4nJ2EApu7GSy/rcTNT5aauBlhgfjAkGUkNkOx8fVWO9I+NSziIvEVnACWUA3TjiEGgkGKSgEgyx6XI+EwtUgs+PzbySw/Jd/D97ScUXBwxH8JRE0labTaLA402Gh02Gm2QSTF9cHxuYeL5ZFjX8s7XaLhYU59u1ZZnNjja3NddJBn5mZGebn5yuhcPLkSTY3N9nc3GTXrl1F57QWWZaxublZdWWrl7+oQ0tA5V+o/xYFhOOcxeQ5WisaUchwMKDf69GIfQ/iZqPB6mDA1laPjc0u3W4PKRS3P+GJdGZavknQ+jnWVy/wmc9+lv7WKk5Ivu62J5AMVvl/H/wLDu2f5+jhJcI2tFoBTQNaGLQzSAM2t0hnMUlOZoZ0ZvvMNAQ3HN3H6uqAQT/j7IVVXDGxbaEcDvIRfAw+a/p80ifPJDZRtPQsUofMS+1Doq1F5gEuy0nODXHDDbINx/qqrwb8hQvrfP74Be45s04Xz0diRtayE7pq6xsWeTMmMwiKKqnWz+E8L4r2F9UIvDUZkBuDsRlpmjEcJuS5Vzh9HF3VkWSkpEyFwuWpmrimFAyjErsGGFpL3+RsJSkzStENA9pSEQqByTXK+kgeY3OwDlVYCBLPTAR+opSwxVjYYgFKW5NTtoysa/9W+E9qDf00ZXWrz3pvSDfLGVpHymTnshp/rf3wsFYNaikTuibGh3WOzHimkaqUDJ+oJijr7EtsXnNsT2ohOz3fbQNwVGfH71pzLFcMXRTasE+IczUpI+o3WDYkrz/T2gnrFsfIrV04l0XZgKQUi7J6+tU/V+RUWN8hK7emKnUxivpy9auevNVLUKHxWQ+1iMJa8hPWQ1OBFMyEEZ0ophPHRFIR+MGCFgIZaFQY4ApNURba99LCAo0oohFEDIYDkiRhddW37zx+/Dh79+4liiIWFxfJ85yLFy9y9913s7Kywq5du6omOr4RPbRareqqS2FQdmmrV1YFsNbPGu8nELTaTQ4fOoizhg984G/ZvXsXT7z9CSwuzhc9pZvkxpIkvrCdFJL5uTn6vS4nThznvns/y+bmCgjH0vIS7eYeIjVk0A05ev2NaJWyujVkv4hQcZvZhQYhBk1O3u+RpznCpgSBDzDXIqPdCLnh2H42N3OUjDh7vsfqRsLq5igSzMqi5pCDoR8xrFuDwFc2uGhyXCZpSoidIXYgrEQ4TSQl9C1J3oNMkQtFK4FFqek1QmySoW05Arw13s9N5ddzWU6WmyJKz1s7xnhfoCit1UorcUVAQFHJQEiUUGgZoISmLK4jyhAkV4c1H3t0TUKhDJWsa83l7wxHYh2D3PiPsWRakiOx0ju4bMlgip093CKqzGHf0rLUBEV1fH8BhQN4jB2JQiAIrBSkzjI00B0m9JKMYW5J3XjnsOp4rmYt1FCkevE+MXYBtft1jtwU9ZJMjrG6gChG0EGl6FIAMHXtvk71k48tHy2rmGh1gO3bikKzEdKNr6gsrtpi4bYJIYefTOX2rpgZzsnijOUy/xk9x1GhOGutr9dj7Ui7m/iM3c8OgrCErMafT6nNFThxYcApKGLjA2KtiZX2BRdtAQEW5dCVLCptWi+SpBA0Gg2fECYUvaIe0urKKv1+n62tLWZmZpBSVnkHURSxvr5e+QtKOKjsoFYPP60/j3rUUun4dsV78aGsgkYjYmlpgcGgx+c+eyfd7iaLC3MoJVBqnmazRSQUzabEFXXJ8yyn293i7NmznD13luFgi6XFFrNzLRYX2mTDFQQJu/fsY2vzPFu9FTKrcDIkjGeIRE7gctI8RziB0QYtAhABQvoEsKg5y57lBbq9jLlOTJIa1rbSSkkq54/FO50dPnchdJauE2zkOVoINiVFO19BgM+K1yjyzGGyFOf6WKWJRMCs0iw1YjaNh5tT66EqnCCxOQ6vRBprqzErnIfBPM93FS+RshrJRZSVH3we/vXlsoUoBcLIOt6uoD226OqFQk6B/Ts0JY4OIDBIhvis2FVjCHNDnOU00eRCoIsyFFKDTA1OGKSzuAKXd0pVgIMUEulEUSCsaCQvKbp8+fh6K8BqhVGSRMJQCfpKsWFh3VhODnucSxLWHGwh6OE1mVI4VKhQafeKIq7fgcZXJNXWjiwGRoLClxNzDG1OP0/ppYo8iEaho06CU2gVIq3xMEZhCUk3EnWihs2PqMY+awVYRsVFSoutxHZHGr5fWeCoNXy6tH5GplHthhjh2gJR94V77d+BE9ZrhIBVPjTZefMOpMd3fb0mS2JzUuuLDRrHWKIgtXuA8WcLIytnlFVS+ja8baKcP2VdWLZVRBxEzIUxTaHQuSHvDzHDhCAOsdZnx+cFvuWVDq/V5GmGQjDfmWWm2cJYy/79+zl95jR3fuYzVVby0tISs7Oz3HTTTWxsbGCModls0mq1KqgpDMPi8YsiQshbClEUVRnOZZe2brdLFEdEccjs7CxhpAmCNtcfO8rC/CwPnvgi586d5U//9B3s2rXE3Nwct956G7Oz88wvLNHtdtnc3OQfP/YPWJuhFTzucdeze/dRjhxeJs96JMNNznXP4qTk5lufyGc+/XG+eP/9nLvYRQYxu5YCnHBYcpSM0UoiRILHhwSdVogMIggijh7eRRjFnDy7xn0PXGC9e4L+0DtzRa01WWmNlwUvpXO4jU0uKEHWbLCn1WBvu+mbPBmDKvwo2jmS9S5SaWZnOkRzc+xfXKK9ts7KYMgDW13Wc0PXWlzmG071C2jWCkEzjnHge0Hgj+lEObdEEcoMrsgTca6mYBTKmjOetwnnQaRaTcLHJF1DldSCwRR5ARIfRlrWREnxjuCuMWzmGetpypwUCClpSZ89qBQIparWnYH08AS1blbOisoaKR1ypZZf9S0WAiMVRkoSKRkIQR9Bzzm6zrGRZ2wZw4BRYxpTA0nKUE4z4Z0dWS7lHdZwcenXWVPUJiqOaYXwCTDO9y02zkfnxKooVexGWnlpfXiFv9RKRMWf6yOxGNOMwUXlhkUoZl0wjPyYIwkwcpYXeNIOYXbF3uMCAa9xlc2RvNQs3kfxTpH+3q0QlQDILWTOVb6lSWuysssZ18YmRFu1VLqi4i6grfctaWfRRQe7TtQgCkNagEwS0q0thhvrJK0m8WwbrK+Do8MQKuipfKfFk3W2yEPwTKLRaDA/Pw9QOZd90lNMo9HEmJxms0kcxzQaDcoyGMYYr9DIEasso45KoTFMhly4cL4QChFxHPl8CKFoNBssMMfXfd3XsbS0SLvd9lqvFJw5e4aV1XXiM+eKYnk57Zk2jThidrbFoUMHmZ+fodGIGJAwHDqEkj6Xxwk6c/McOHSEXj/j4sUNzs+1mYsF7RBklmMyj7MjJEJYkqQPuSUf5DhriELLrqU2G90+szMh1uaUPrgy+ARGLVuHztG1vrS8c4KVNCMMNI0sRwoNSqFcWnRU8zCgc2CSlLCAfhaCAOEc/TxHJikyyzx8VOhKmRRYIdH4eeyspSx06edxOcb8XBHFfCk/Xtcc2QilJV+3GMbm47bx+eilq09ecz6eWCmFxpc7sLklL1j2EP/g1vIcmXgJ3dYKqzVNpUFLlJBYHfj+zc55DVRKnFYo6ZE9m5cGH5XAsM4nt2UIjIBECoxSGK3pSUFXSNYdrDvHunVczBPWrKWLbxAyRFC4HSuzEsCQVwOkgq8qKKvmeIKKEebGFNaC8LCYUhBoXLncWYS1qFhXWcQ2t2U41ZjmLiaBsjGIZxIo8ulq5WMZ8VdBTSJUcE4xF7xlUTd3Sok8AlyLVePx/6UfwdUjahTeqpM+GMAKUcStC19XykJqBakTZIyEZ1lO0J9n3KswltVcCNHSnvAwg69MGxhblQZva81M3GC+3UEXvY9lr8dw5SKb587SiENm9+wuehwbX3yx6HBX+lWkBKwPQlBKgRCYLCWKQ/bv30uSpICg0+nQarWZmemwtLQLcASBnzb1sFdjDGEQoGQwJihKR3SWZWxubXL8xHHCMCx6LswhaCPDmFarQbvd5JnPfAabm5ucOXOGe++9l3PnzvHAgyfo94f0e0NmZ2fpdDo88Qm3s7xnFwcO7GVhroHWjl73AoMh5M6gQo21imE3Y/fe/exaXuKOT/8jG1tbBNJyYNcsYq4FyQCTJaT9YVG1VWE2V8idYpAKMtsiUAH7984yTBKOLzUxeQ+sJUlGMCHFWB0WQ8wU7zFzjmCY4JRE6oCo1UZIn4ekXYYg990HcZh+D2kNoTHsDgOaRW5IKHoEzjFIcsJCSUiLekyZ9XkizuS4qhKvqpJs/QRw1dD38LVPBBXVDCy6trlR1OSkDf9Yoqu3FAoncO68qS8QKAnWCYz1QYs5PuPXWUueJGgh2Ag0eRixICWLUrLYbhFZS2BysiwlNxnSpigniJRCa/+SfLVDh8mNLyUtwOgAozQ2DBgoxVAIzjnfBexcnnIqTVnPc86kKVvOsQn0KR3NtcxgN+mv8MKHsnJrCVeJwrWqCubn/LESys5nggHeSlFCEiqJlgLhBL0s9TkN2CJ0s8gwHtkelZbu/yixLFutqQBQf5HU/RKVW1hskyUjqVH9X9PZq2SIIsO68PNMvGykUFX5jFK7stZDeLm1GKUxUpKrwBcktIKuyegZXwfJQ3X+fKPmNMWxy+t2NZEgR+cp+2+0hfR1tZyjia+pNK8lc6FiPtbsasdIIdno9mh0N0nPnuXiA8cJlWTf4QMEzSa6GeNsirNQ9SRwDpxBSN9tTRbvvhGE6FASxyEl3BUEEQJJlubF9f3/7P1pkyzZed8J/s7mS6y53f3e2rEUAAIEBZIiu0mpTWxZt43NB5h38wHms828mJbN9IzaxNa0jOrWSNxACIVCrXfPPWN3P9u8OMc9IvPeKlSx2dMAiuda3siM8PDl+PFnf/7/yGa96K1RbRRGZyrHmLrtlVYopfE+9PmE1jYslnOePXuGkpKiKHn04CHxEOqjYVpwQlAWA/b2C+rBkMPDW6zWa5brNc55bOuoyoqiLLh1dEhZGurKIIUlxhZdFGhj0FqzaRps2zIaDdkb14yHJetmzuzyjNOTF4i2ZTNfcP9ojFQCx5JKa8pCMxiWIDWTqGlcQeMU1g9Q8pBN8y5/8b98zHp1gU2PfcLokkmAR+8IAqwQzPPzQoB21bJoZzgL+6bgXlVQK0kpFGXwSCJDLWlai900DOoBhTYMh2MOTMXVyDEuZlw0beIT8ZF1sH0erOPvSNSwoTe36JLVUfQGQQpLB6xrccHhY66IvGGwfFOVw9dQCmmyOlJ2kcMZ6bcUr4dkKchskZ1ZiwuBSkBUqZO0LgwIKINOwrL1iOAyRpEAqVAihSK8TwLIyVRf7aXGK41TBSuRcgWX3nHuAqet47RpufKOeQgsSQxmNnYE99tg+k0kxNhf31ZZbHsZyLzO27BIl1doY0qub0KkAJyUOCmRIVVCQeyABa6HRzpflnSAuCPEO6WRjr37rWzX3Fihr1uwYuf/7bLuNcmr37kZu+m9JfoqjBizBRjAS/BC4KXACkETBE0UbAI0IXtRJDm3neYdtz5fpY/d6mHn7nSd44l/owIqIRgBtYRDo9kvDPuF4ajQec0IhG3wiytmxy8ZTUY0izmmNChVpnBHvn4fHCF6oo8oaVDK4IInhuTTCCLGKIwuEVJhbcRaR9skPKMYAuv1ki6cNxzVfe9COneBigWIFOfuPIb5csZ8Pmez2SAQCctnvqCuBvh9DySoZ6kUZUZTretBQvGMCegxZK9GKUVVmjx3PlfeJDa2jnfY+8RPoosCU1ZUdc3h4S1E9Fy8fMZi2aCJ3D3aS/zGusyEUpLCKKTSoAyyFUgL05GmPRjwxoNDPjw45vJyRWub5IH7HJIVKc7vRYbDIK0ZBeA90Qf2TUsMqWIMEs+6IWbazIjzFm8thSkopGZoNFpqBiawah0GyXpjidEjdhgSO3SxboULUkVe2PGYRSe3+q2yVy24sQrJc7tdn9+k8TX6FNKIkMhA8h8dN0Ak0V0GIpsYWUewa8dACOYbyZE23CoM68mYPWN4UJUYJVBGI9YrZAhYETFSoAR4lUDXrJBgCqLWrKWmEZIF8LJpuHSOp85y6Swv7IYT71nEyAXQCtiI9Opz3LOTsV0svhfFMVU2ebrqpu21JkGYlF4kh0qABZHTpkEGOCwMrU6ctdEYHIGwaXDZUu5c3l146k4xeBKlZScwk0uhue4xbM+nm3fgVWHevf2aVfy6hR13dnQtkCSSotrtu4giVZA4IWiloC0K1kJy5jzHNvDSRU43LZfesiIRsrhI7oKn4zcBQOqMKQQ4l0I80XfVRDAUkgLBIHiGQjIWkltlybQwvL0/ZlwVTMqCIifAR9MhF65hdrHg53/17zm/eM703j63336L/Xt30cNBKk7wjqvZFav1GqUMpqwZDPc4P7tgtVpD7oPxIbC/d4QxFefnV1xeXnFyfJooPJ2jtatE92gtt24dMRwMmIwnDDKFpwuJ7GW1Waf9ec/nTz5jvV4zmUww2mC05uXzl7SbFqNLDg8P+v4HREykOlqjjcF5l7zbsC1rtdanmD4JFSBGgZAGKQu0rtCmIkaPNCUn5xc8efqYw/0pt7Th8uwS7IrF2tKGxAt9ZzplMTtlvZmzryRFqTCFwgeL857xwKBkQVndQ0R47+3b/D//33/NfOXYNF05cjLCREzPnSXd0y7c6pBUjWPuBcgNt0pNLDXGaGT0BLtJZcQyeYgyQaMy0AUHukRPJtwuK6am5LjZcGktL9oVixCQPrCCLSx+7oVSiJ3Aa3q+ZEbULYqCojAYkzrmU1Xdtkbxm+glwNfiU9iajGInKdPFxtNIQtWSKkYWpNyB8YGAxcaIXi2ZG4MIgTpG6igolUGrvNhjaliLUhOEwCmB0wavJLOYKg8uneV5s+bSOp4Hzyx4zkLgKsbryWWR44iCG+Iv9Inc7Xs7JWl9bmEnfEJXepuSny2wjJ6Zt5y3DSp6JqJAKYkUBSFWW6TVXEob/I6pHjuAvC3KaS+mOy9iN3TUzXCXT+j2s7NLsfN6PZErdn2i9Lvoftt6Jv32MTf7dclzkTyDoCReJW+o0Zo1gnnrmTnHZetY+pZ18DjCtR6Fngch29Jh54wEsW/k6zgrihgTiRGRkYjsScGtsmCvKjisE6FLrTX40MOelCoy0AIlLd7OefHklwTtaP2K24/eBKUT1tH5JVfzOSFKTFkzmnoeP37C1dUVZVngg6dtG6aTC7QpWS7WLJcrrq5mVFWJUoqBGTBfONbzNU+ePEErlbicy0ToEmJaP7owCRFVSqaTPfb29inLBNCmlaauBgwGQwaZpc0Hn1NEaUICaeFJ2cHAQAeQ1SlrKRRIQ4wCGQNFMaAqxwyH01SAsVpCAGVKhCxQOjKeHrCeCdr1nOfHF6xGFQ/u7hExSF1noyTnYERAyQChQQpFoeHhg33KquLnHzzh+HTBy9Mlyw3EQMrfkI2svDbbmLG6CFx6SyAybCRSGKSImCLBziuZPBQDaAEieMJmjdIOIzXjGBBKEAclRguGTsM6MLMtomlRIT37G7YmVd98KbYFACI/fz2ta4ypyo5tyfs3uVHhKyuFno+ms2rpkjK7HbAxkzlu25WSCxlZOc/MedpgmWpFax37pmCqNHu6oBAZ5sI2BO+QyhClwCpFIyWNEJw6y8xbjpsNz9dJKRwDK2AOLEiLoqOD9Pm1A5qLWYldl7k7/4sdhSC24ZN82RCTBQwJAHAeAgrL8XpFDAUjlXB4tDQEKQgZXtlHjyAgQyDkiou+Yb8/RtxWE8VuUcrdE73GRdGNXWsmKYR4/cMdld39tlWSnVLIm+fjp0qvmENFoq+y8lrjjcZpzcYYliFyES1nruWsbZmFlmXsmIBTorlXygKESKLBQy4N7bCUOgTaTPdJgkkYA3sCDhXcrwr264rbgxojBVrAxia6SoWnLgSq0IgByLDg8Sd/x8rOmC3OmEzGqLJitbGcn5xycnrBunUU1ZDJQcvPfvYBJyen7O9PsbZlsZwzqMdobVLOLN/HR48eUQ9qxpMhPnjOTk959uwZbdPkvocCrROJTlVV3Ll3l7qqqeqK9779LpPJhMPDfYwyGcmz4ztQeJ96XhKrmkCImEpqY0Cr9JhKGfswqBRdU1x3HxPCVHCO6DyT8SEiwsvnpwxqw2g4BpG4CvYO7uJtYLna8PFnz9mb1EzGI4ws0IVCyCIJSGsReLQMBL8hBo0WkbfevMv9+4pf/vIJ9acvWSyXrNsURlI6dRa74PqG0c44cERMsDTRozYeF0tcDJSixCtBJXUC5dMKDYTg8KsmJaaVYlqU1EozqipGzjBzDqMD52sBrkVFWMXsgeYZ8blCrpdRubRRhOTBJR7sxFeSKHq6sOd1jfA6p/y3VWd8jZJUdurqO3s0NTZtFyYJC0V0iyEJB4SgjZF1jLQuMPSRpV2wbwx72nCnrBloxdRoinKAriRRJeGxjoHT9YqrtuHYtsyd56Rtucru4iXJMljnV8uW2CXSdTLvRBTF1vLvZHA682wn9NZD6BOfovM4AJQixMg6BK6ix/lAsVmx8haCJ4yHNEUBZUVjHU3YMJSJnY6YYJw7WA2RFUQ6uujj7RCvT/OXDPHKZvHGpzu/33QnYNs5nkNXXbotSomXEisUrdE4JWmMZqM1a6N5EQLn1vG03fDCNpx4yyz6PrHfPZQuz2EQOa8jIlrnJrncC6IijGRSCFUkcVNIwf2q4qgquVuXHJSaSgHrJUGCk7BeL3AE5Kjg1p19hnf2uf2dd1CjAW5Y8+z8ko9/8ZyTs+dM9o54+M63uL0/5t7tI9Y2EqVBFUOKwrBYrNg0GxaLJaenpwkCIUaMKfoS1IPDfYaDAYNBxei9d3jn3bdpNw3OOVzrmM+XzOcL2tYyGA753ve+z3gyYjgcYErdl6dKkfkUuqkXCR4jRpHRYNPNF1IkfgRC9gpyYyS5vyeS8xwplCSEQKuK4WCP27ceMhlNGVYF6/WM9XrOZrVBECiGe4z2PUjDs88bXp6v+bf//q94dP+IO0cThBRoFZCiJbKt7gm2pVmtKMuaSo/44z98n/29IYvVgiiWXC0ca5uyi1J2+cbk/Xeh2CsimxhwzrIOnkXbQnAcFAYzGDAQmioGSu9S+XYAERzSOcqYINTdesVBJvAa7U24Gg64VVe8WDfMbMotbkJkFQLrGLAhGYpdb1UIMSE22wacJXiHEGEbXv6C5+ybMr4e9hGvFz79b71VLYhCpgWVhV1nLYgIbYyo4LA5USukYRQFXkZqpSm0Tl5CDCx94Ng5LpqWU9ey8J4z51MimaQM2vxzvQSyC07cOPMcL+/KNrlx7tevN776Tl+GmZSQIHIVPNLBqJVMbIGUiqowVEISpELLdCZGxW0tdcheSbh5XBDxNedNvCHP47XtxXaz14wb4aFXriq9dCi4kVRu63PivJUSKyUrkWhPVxHOnePcWS6cYxY8i+DZZIXQVW3tmhBdiWuv8Ehvqhw2KvNPDYyEYCxVonStCvbrkloEjAiIkNn0QsDHFrSgHCrG+zUHd8bcvjtGDio2WnE6t3h3xfHzlvVqRj2qObr7iLquKAdDoiyIssKFPaqq4vzikhQ2ibRtm5RCkYhZEpLqHnVdphBQYSiLkrZpsa1ldjlLBpEPjEaa8XjM7du3e6XQ2ib7YDt3RXDNG92JZ+aXFFfccgeLa15i8i63PBtJcWiELpOnoxSEVGoaYqQJKwQBU2rqUUIcrYZnrBaCi/kJ43lDVbYMK0OhI1pt81xSJOyx1KpqKVTg4b0DFssVj+4fMl8GfFjTXLn+2rrV1fUYCQFNjiOoGNE+3c9Jk3JMh0Xow5qCxPeguxB1DCifmODKkAo4CgFGFZRCIGPqGRk0icRr5TzGgfA+VUCxRSvwEVQMuSAm45518/6lz9E3Y3yt8FFnTW4t2i19ZTe6RdTl7UUMNDGR3BRS0AgwMbLycOw9tfe8dDDUhsNAqjIRAm8DrfdctRteLhZcrdfMRSKpXwKtEslaDDFZAnGrEDpcpj5MIgQIua0oUiqbr76H1ejwUqLcCtDtQ9s9uaJnPcv1LLR5Wjbe065XbGJg36xZjMfsKc2toiYKj/WeKMB4l7glZErSa9V1gNJ7Yx3nwU7mhk6k9k5ZdnP6TMiXmDe9YP4yc6erLsvX2EjJRmk2SjFTkrWAc++YB89MWD5cLrmwjmdty7kPzGLOIYlE1ZhKA7fH3x3BB1RMnNEVSRlMItQRhsA9Y9gvS751eMBQwUgG/GYNMaCGBY1v2Ng1elxSTWruf/seh28csffgADlZ4eSKGD0P7gv2bx/w058/5ezkJZ989nc8ePPb3Ln3Jj/+wz9lUO2ja8V80eLaJevlnMl0j+9//wcpHGQ0EfoQT1mXScAGh7cO27Z8enrC6ek5H/znD5BCY0zJH/7hH3J0dMTh4SHapBBRYRTew2azQWmN0oqqHPS5ug4GQ8otL0PXPhmyB4vIwaOYkqcxZPgM64ghpOoloTL96B5VOaAsDAeH94g45lfntO2G1WrBcHxE8C17+3dYzC55/vgjFrNTPvj4lOl0H6kNhQoUJqBkxOiWovBoZalKQVEG7t09Ym8y4Ohgn8m/+St+8dFz/upvXmB9Qh2wMTe3xmQoeClA6YxNlTiSV8HTLpccbxraVnC7KjksDUeqoJIwCAHpLTI4tIdCRAbAZr3GrdfEENgzBbcHNfeqmoUPPJ4vuGwaTlcbztYNK++ZszUibYyMAwwQVDGVPOvssf7j+JrQ2UAvKXdr2BGxd4U7CZSKa7KtG9Mi8TEpCh3T3rqkEMGx8NA0DVVwmM06JaxDYGFbLq1jCSxjLnUTggZwIdKEbafzNrG5DWVtpWi2VvuT3imR7MwacT3mHvO1ih1X33chDyROpH2sc7mlAYy1NDFSrNc0RYmuNUom4iAdJUEooowp/hpTU1tHmCN3MaEQPeVoOjeJiJloZ2fxXq80itvzF9292bl7Ytursd1BtkZF8hCclDghabWmUYq11syAZQycWJcaBGPkpGm5cp5LH1jkBH8r0sPf5RL6Q8A19SYyGm3q40iKoc4hpD0pOaxL9quKkZZUMqBFROqU+FxslkTlkRU8ePcuo/0x4/sTZO1ZNOeYtgQjkUpSGoXQgoOppiwEdS3w7SXHLxwf/N2Qw9sPePPdHzAeGIhDHj9+wtPHV3z2yadU9YCiLNk/OKAoC8qyxJQGRGQ+n3Nxfs7JyQm2TSRKB4eHKZk8PWB//4C6rlFK5zLPdPVSSsqySFVdUuRS2e3tUGoLnBcyeN/u+r1O/JR7X6RAKJXKcmU20/obr9C6QqQYDExStVc1GCFiKq7em+6zWswojOGDn/4Vpy/OuJw5tCqZjMYgWkK0OOsgQGkkhdZoBcGvKU3kztGYh3f3WK82PH92wWJlWax9h5pBWerU9R4CbfYURF57QirmwUEIvGybdC1aY4SgzV59qTSFSqRVMgZUSB6DDgkKW4cWGQLjTuHUA/ZNyV5Zs1etWbSW4/WGpffMQ2q0HRApfaDIkBsJL6uDVREJwqVr9PyGja/e0RxC7y7Ijr4yS7CeUyFbrzcjL5HUd+BEshwUKfxi8o+NntJFFlEgN4mtoUtMbYJjQ26fJ1uyUtKEgAtbIK50nC3p5XWGgiwhe4Ww87obEIt9gINM8ZB7BUSv5JwPKbkuFT6roFWu1hEkZMyF90iRSlfLskILCEpiUPjQ7TzXniMyQ1kqW0XsJPDzsftTFOw04KT9XAe6o08d9OdPzEou3a94/ZI7MZ3CYlLSSoWTKuUPlGalFLPgufLw0jnOnOPceV40bYIUIXluXflv56l166Hbf/eggUicGiTvsSKFjGpgIiVHheL2sGKvqhjp1NGsCGAErYfZfE45UgwGJW999xHTW1P8IHDVXHK1PmcwqNHCYIoaqQxaKG4daKbW0PqKxy8uOXnxktlszhtvf5f7Dx4xHuxRlgW2XfP5p5/zt3/zM3Su7f/Wt7/NaDxiNB6jjMIHz4sXL/j000/58MMPeXT/EXfv3uNf/Is/4+GDN3h4/1GCvMhouR2kSoeLVBRVZvYLeG/TMgxgjEEp2d/bECLIjoY0M1r09zqCyIB/SFKreddJlhKpKQcmUKpCqoiUMUF8k44rZGJ1Izia1ZJBOeSXv/iE06sN51eWqpLcL/YJbo73a6xd9z0Mxmi0Eth2hVGaWwcDHt0/wLWWZ8+ec3IGzvq8DgSqKmisZ2NzmDem/JIQqelzETwuBnS7QWgD2mCEZChJa0ZrlAARHTJ4NBHhcxbQuqSwNg3jqmZQFEzqARuRYG+ON2tmTUtxes5V21K2LfO83iqfuqe1c8gQenrhKFJOLWTl8+r47Y4xfWWl4KFPCvjo6YvroVcCMW+zlWFbKLQuxNE1mXTIiorkMSgipz411KidY1q2XsCaLLh9wMbdiuLUv9gJ9LBzBtds49AdOZ92jnP7GHAZ8tl6lxrmQsT5SPBdAip5Q1IouhYYG8kUgttwkiUJyaZpOPOei6bhnbLiUGtaY5jkfElQMvE5NxEZPTp4hFaJhlSLxBTnsyiPIMRWYWWg0l7gbn9if32xmzeR56kDnBPboFTnEQUgSImTik1R0krFhdHMhOAywmPnuXSOx03LuXNcOs95jGzIFV9ZITi5hRLoPJ5dBKmEMBoZCEmFYERkHFM44J6W3B4OeGNvwp3BgForsCtav8a6JboCVUkePTjkwTv3efitR4wfHaJqBapFWUflgCKiC8loXBCkwkfB4rIlFIZ6OOT24ZhVC0+P17TzZ/yP/6//K9//0R9x+96b/LM//gk/eP/b/Oh3fsAvP/qEk9MzPvjZT1MNfoTp3pThaMTb777D7//+7/Mnf/InvPnGW0yne9y+fZeqqCgKg3VbiJTYmSqdxxZ9Lwx7sDaS0oik0BoIlCo6Jy7Nm5AoSW/MdGuyi9inIoncuxA8PsM+SAne+owBJXE+cHV1xXw+Y7lcYJsleI/wjvtvfod6uM/HH/2MZy9nvDyecf/OlP1JjZH7xGhZbTaYyiB1gXMOHxzeNty7VVGoI2z7Lp89PaM0L/n05Qa/CQRvt/IzX6eLgXVI5dpRKCxJrqw3C07aNcdCMtGKe4OKW2XBfmHYQ1AJxVABLhWYah+RMRlWftXgVg2ryxkoidSaqizwVcGbjx5x0TScrleceo8eT3hzOOK2KRhFQRkiJgRUTA2aMd4M3L46+ijuNQP05vjNUxxfq3ktXvslvvrBTgz5i6apW8a7Ajw9BunhSZbhdlu3853eK8j1851472zrXbaBLknXewnXNNeNc+prlnd+bl5avP7FbjF0W9p8fuRzJkaic6gYGAtBjIFRhtHQUhGFwAiJkQqdd22QGbduq8p6hbpz7n2/QeyQhMS1rbvPUz1VUgxdOKzjX5akUr0owIukEKxSrKRkIwVXRC584DxETq3lKnsIVz4w3+kH6RP8QpBBoZPy3Lk3N42EIv9UwEAIRkIwNYapMUwKQ60khYi0viX4FhdbTGEwQ8XBnQmH9/c5enAA05KoM+mTBK1TDE4r0DqF2lSEQnkQimElKMqCgU95hMW64fL0GacvH6O14faj7/Tgd8476rrE2pbGOawPTKfTPoG8N52yt7/P/fsPGQyGVGWdAPGQiSEwbiN/sQvn9II8z4fYrl66sFHIYSFS3utmg+H18F9utuqUQfea73wIAWstzic4mcIbvLcsVytmiwWL+RzXblACamOYHtxmUI+4OD0h2A2zpWcwsxAVwxKETKvNeYEOCTbc+4BzkUJHhgPNnaMJrfUsli3ny3NcaFn5HHIVGZQwe7CeiI0BK+T2KrNxJhE0QWG0RCWmKIxOz00hUj+DjAKCzFzksQfX8z5V+UkfqLQiSsmw7jqnU6hI1RXTwjCQiiLGRAIUQXY9WHFXjl3va369n/A6ifflCuHX1d/4GjAXr3nvV1zNq1/phFYSWD6/1Qm+rjtaXPvutuuh6yoGEDKVRoTuAcxxkd3H5drx465f8eoldKGnkOPx3YbXK0MioQuUxi0mOwgcKbbe4fZsSGiRjfMQVpw3ksZaDo1hXhTsC0EtYGKKPoTSZq5b27QpEUtmdBNb4Sp3QlXbOP12eW2VbeznLdVrd9eVKsMQCVQwCEEoChopWQnJWYzMg+PJxnJqHcfW8ay1LELgnOQddB6CQ7BhN8HfKeDtA7XtZ4kYEqrlIAYGpD6E28awbzRvTIZMS8NIAnaFjY7WLgjKoqvI5O6Q6dGEb/3wbQZHIxgFqB1eOGbzi+RRhIay1EQizq0QQkEUFNoipKBUDUok9NN7t0ouZy3NZsF//Pf/A1H+Bf+n//P/hfHeEfuHb/Dojft4DwGN0gW6qJAqUW9anyp3AiR4C7EFKpSCPgzU8UrDttQ0xA4QPuNBkSqGyHPlvUuzFUWPx9PjKgW/kwPrzsAToiWGjtYo5mMnKI1nz5+wWq9YbdaMpyMgslzOaJoNrbVU5YDCGCajMcOqojKG97/3I85PXvKzv/6PvDh7zqePTxnVgum44t7dCWYVaF2LbWepXDUEbLtBxsDDexP29sY8fPgI1N/w2dMzfv7xHCUFlVa03qc5yZhYDljiUBFaUsh1SaQhMgiB1TpwYTfsK4XdnzI1BqELBkpT+EjYOHCpXLYqDFoqhlJjY2DjHHaxxGuFtQ4hwEgYVBVqOOBuWbCvJXXwVDFSxmSYufwc/SP20a8Yr0zMr5ip103mlpD99dvexM+8+dn17WI2nruwyO4O85FFFk07J7IbWHrdhfRVVWL76essgq6be0vUs4VmjiQrutv6PCYMp9LaxATnIhutGEqJLzSjDi2WzHXsBDok4aFiV0oXUR3nrM/EISTrC5Fr2cneQJ4b0XEIyG4aEuR4wpGSOKUTJ4U2KT8QAi+dY+Y8T9qWC+c5dZ7TEFgT++bABCUgkxcnujBU3LniNGudYlCkhVaQ8gipU1mwryS36pKDsuBoOKCWYKLHh5aII5qAqQ1mVLJ3a8roYIhTLW1cI2wkrCReOBq3orHrhMXjJFopgmtRyiCEZLWY9RAQmAFBFmilKQpHVXra5pJVc8WHH/4tt++9yf033kPpCq1T1ktog9Imxe77+b6+Lvq+FrZloz0x0XaV0vXC7K7vEHy/qpTSfeitBxLMsOVSKGL0xOhTbb0EJbuV4PG+7UutvbUs10teHL/AeZcS1xq0VpRlCnOFOKTQhqIo2ZtMqcuKwhSItkWqku+4yONPf8nZ8XPOXn7KulngguO99x4wrIcgAzE4YrCUjUUJwXg8ZOIN+wcF51dL9vemzJcfcrWyzNdJ+McIXQ5dkMI1nQETRPI8ZUyvIgS8i2xCwKxW7BuDK2umUjJAMFAqGZPSIwOEGBLVB5FS5LBSCOicE03p9WRsVcFTeIf2HhVSNVzXSLn1ym7Ki+vj5nZfdXxZwOl/7/H1sI++6tV38VN2Ln4n9LHrBezu86bw7cJGsLVy+21j7x58wcnF3m1/vSKK/TG2RxSZSGhXGe0qs+tFovlE6DoItttffy1iKoNTrWUtA60IWGMYa41SBi8VKAUxYIgYLdOTIugVgIrsWPo71rhMVUpd2Gb3PJJCEH0sJ8GGKFwOF7XGYJVkoQyXznEWHI9by8w5njUNlyFyEVIyuSvn6/InCfSuc6V25zlee1K6h0xnhdD1IoylYF8rjqqSw7ricFCjggO7ZhMsAQdVpBgaRocD9u7sUU9KWrFBhAjWY/F44WljQ9NukvXbCrSSRGcxpkAIyXq5AKGRukRXAWkqtK4pjKeuIsHPWSwafvnhT2mdZe/wiPHkEKMMMRFpZCGdLqsrtECww7SWmb/U1r1MTkKX40n/Qtyu6lSOGntGOCFkCi3GlGjOTd85FJW8jRB8QiF2LUqL7JV4Ag7rmv4km7ZhsZpzfPISpRXaGJQSlFXJ/v4+Wiu07splC6bTA4qyQhsDq4ayGjGZ7BOiIlDw6aefMV+t2bQbHrz5EFEMKaRPCLS+oWwajPKMJ0OQA6IY0jrY35vy6efPkMdL1iuXIV9yzUEuPLAhrVknkkfbgWu2JAhu61OzqFitmJuCgGJTFEyUwiuVoNWVRvrUAV7plOBPcPzpeC7xdqbquBxqKoJPCsF7VAxZKcQbUuGLh/jKW/6q/fx6eSNfGxDv646bF/s6AX2zf6v/jrj5/esi/Pp7u1P7daY4BTfEzsPXhbJ2j9rZerJXD9uj7HoI/Wdiq1TOY0o+W5I1PsMxDzC0KYE70YqpUdwpJEMp2K8rSu8pnEPbFukDysdEMCNkTlKm44QM4rUVTh46zgMl00MmBFZnUiJjMjGRZIZgFQKPlzOuvOfMWl7YhDJ74gNrkiJI574FG3PdvIgciiLsPB7pQZdsSd01EU3sq4wOjeTQGO5XFXfqkmmhkZsVUgaUirREhBZM7x9y69Eh99+5y/hODdpzPH+KqEqqSUFdC4IIrK1CGzAmWYWFMRzu7ffCdTweI1XBZH8PXQ2QumTlJKYQFOWQIApOL9Z88J//isVyyXjvkPsPHJPxAdVQIaKE4HOuSSaY6Iwo6rOQBnrQP3ltkXe5rrizLFPpaQipSk3rhPYao6BtUkukFCpBXghBiJ7gPdZ6TJHsBx9iLj4IXM0uWK2WHB+/wOVqnKJIcBuP3njUU6SOx1MGdc3h4SFFUaAzJEV/8iKjT1UG4TxSlLzxrR9y6/5bHN29y+XZc54//oD/+T99wH/4y7/lv/mX/5S6LNGUjFBElxLKWoMpNA/vH1DXJf/FH/yIx89O+fTpCR9+esJi1dJY+go5aVJznQux7wESWiaoehdpIiwibBrHoPWcbFru1gP2i5JH1ZCh0kyHiZSHGNF4RPBEZ3HBEXzAty02pSDAFIhcadTVe8UcBgs5tPel7c3/AKPzon8dx9eCufha44bMvim6O1vqdWI87v7yZTMXd/bW1z/ekOa9YtmxrvPX4rUT3QktxQ4nJW+345Hs7IVt+ul6MKH3GLIr3JKqcgxbT0lmPulAasXfRI9WBa2QFEr3eENFiCh8InvfqXdPkMDpSILYJ5NTIiRxYicBLrBC4aTGaUWjNGshmCM4d56597xoW66859J7zrxnGRMXxS53RAcZ3uUPeN0z07tX20yHyMohhY+gFJkkpzBMy4KhVlRSQGuJMhA1KCMRlWZ8OGVytMfk1j7lWOBEQ1zRx6OUSUJTozBeE6JBOo8pDEVVJvhoFzBFiZC670eJxCyMJVWlGY8HNE7g3Uvads1ms8LbhN56bWHsWiu7v2Wvod97jNfKiUXcNXx2cbW2WZfk6e3kvUSW0zm+EqMnREcIAiEjzjUICSFKVqsli8Wc+XyeOKMzZHdZluztH/SNccPhmLKoqKphLoFVhBzjT8+FyndMECUIVVANJ+ii5J7dUNUVzm1Yrmasluc8fXnOeFAwqhXCekRI8NdKi5RDKA2jYcXd24cJQyrC2cUKADdvt+jFmYMkRt+/5/r+nNgT98iY0BB8cChlsVFQyoKJVkStETIZQVIIhAdiIgELGZTSSZl7j+RWg3c3Nna+XCpQSKgHXy72/tfqi068/Tp5CfC1PIVfpdd2xf7u369uddOmj1+49a/64IZKee22sT+trggkdqe5s31XkSNDrkAI21ASO9uHBNxBV0nT8aaJnc1gGzoCWMsM0hUSRMQSWBAo8Lz0kZEXTFrFXEr2MbjSMDaGEZGRMGjnKURLiMkrUVGkEIpPYlqQatYTQHDRYw6tbMgMdQpXVlijuRAw86kR7clqzYW1fLJcsSSBCnahoiVbReB2rmcb/OiUpd+GOXbmoMslqOwlJNRTmCC4W1fcrisejkZMJRTRs9os8TLiC0G5P6I+HPHou28zubdH/XCPyBXRNshSpoojHFrJVHWEoEQjVUn0AVMU6OEAGkvAYqoaH2C53oANCNWiqwkChVGKujQMB4GDw31GowEEhxQx7V9pkIouMSNi4jyIxL4DuSNRSrDbKYSBEJljYTeUJBIIXp4nJXuYSbx3mb5TZHpQ6NxX4SypE8ymMmnrOL84QylJUWhOTo6Zza6YzWYoqdDKAIKiKHn7rXfQxqQkOQn9NLUzxIyCahLGks4J+hDxNiCERBYVQmi0rrj/Zs3tew954623uXX3Hk8ef8T/7b/7v3OwN+Q77z5iaAS1UdzeP2Qsoa4lWnoGpebtR/fY39/n3r37bFp48uKU5uNnrNqAtaCMThxXCKzzeB/RMvXOBJUiqY2PbEghyBkw22wYNg3nbcvUFNyua+7XFROtOTAlOiiUEnibSL8iEI0hFoZYVVAUOCFTMW/2EDpAvFTgG75cLmWlcrMq8TUb7vz+6ra/bgoBvpZSkNf+2onuE6+Jxe7tX60Df6VC+IqjE0K/6lhfxV977SZixxPZsSBkFtLdo33zu5EUwxQ5VhqzFRRyHsIg2BBZE1nFxEU7D6mwc08r9pTiSGkqoRgIhXUpBuqDTwJXpkZCISKh88VJeEteSJoYsErRas0yRNbW88JZrpznxDmebjZcec8pCWk2/aQKkEaIjBy5rRLbvaWB0Pv/u7QlXW5hi3wa+/LTkRJMtGSsU2NSFQPah74hyQbPpvVMRreYHEwZH0woBwZiS+MbGtcQRMB6y7pZE0yCmm7sJpVeOocUkoBkudgQXPIUGgvOJyRMVYDUAi+TZW6dZb22tDZw5849XJT89O9+BnJI08KjwRFKAEImEDshess7hIDSaT1Y16bwQ+Z8Roi+iU2KxOx2rRkxxl6gJBiLhMEjpSQGS2NdMlNEYjgEj7MNp+cnrFYL5otLpBQYk4T5aDRmMBgiSBVx48mEwWCYeBUAawPONoCk1AUIhRQG5xNDjowqBU6yVZ1upQSZ0Fy9j6ArisGUR+9+j+mtO6Cg3cwJ7YKzq0uiX3J15RiPluxNNwipCVESgPFkwmh6mx9vFHeOz4n6A45Przg5n7HatInNL+bGUJUSxjZkOk8kWkhC9D1hlidxtgRnmQXPyltWbcPEKI7KklJALQVGqazEQRqDKEpaU+CNwSqdiy10KvQQMlUf5mf0i3FhvnrW4bo0+M0Yf09P4XVVu9c+5ssm4aaX8GVH+vI9ffF3vvR0RPffq9963btdo9fNg/XN0XQhyFdhJDoLMfUDxN7aj9luSyWeSTFI27L0iXN4VRiaokBXmoGWIA0mtuhcYaGBUqUabiFSo13XpxC0JkidAOqkYK0kFyGy8JZnmw0XWSm8sC3zELjozyMBlnkh+u7k0Gm7TtLH2KNzZtV4w+PqKjhi9hJy2AgYasHYpLzJQCQPQYeACiGZHNFjXUtRlwynIwaTIaqMhNjQuib1LYiIC46mjdCkbu2mTUrBOo8xBSF65KohRkkMIisFgQugRUIeVSSyqKYNrDcWayMHB0ccn8358Jcfsbd/H6Vr7j20CFH29xe2kOhdU1mMgfVqRcjY/EWRKD4j9ExpWsrtRHbrpqsuokPlTXFt5y3NZo2QCikU9aAkRpeUwukxF5fnbDbLhGaqJXdu3WY4HFJVNZkNien+AWVVoZTBOodzns3GI5CoukRLjZCJ75AAIaq+gipkAD4RMsCeSJ6MkAWmGnFnPOJWfMhgUPHy2Wd89IufsjibsVlaZleXDOctVwvHcDhCmwIlK4bDIaPpEd+RI/aOrjidWaJ8xqoJLJuLlFgn5WOkEAS/RSlOBkmC4pMxcXW0pFyV8wkiZ21b1m3LSCmWdcvAaCZFwbAoMJmUPWFOaaxSGKVplcIpTdSaoFSPe7b18rem3jWZkMPUv9JJ+A0df49E89ex7a/HXm/6Dq9zpgTXBXP8wm2/4hnk+LYnvnL864eO11zBnUe4XxbXE1CxL2SOO1vko+48/xGfFzwxcxwTsSIT08dMTk9kHQOVD5ytLUe+4paXXEXNWMEtrRkXFcOyYhIDOnha3yKig+jxKhJRBFkSipKgNZfOsQiOC2t53jRcOsuTpmERAjPgNDehrdk231kSGXvGuszh185LDH03+vbWxgSTnCE3urCRISmDGhgK2JeCI204MpoDKZgAAx+pJKgMhW29IARQhUIVgqVfIhpH8BucWNH6DavNkoEeUOkaKct0liJXqDSOxka0AWE0dT3FmJowO6N1jk0bUaFCKsO6tVgbWG88s3WgDZJaRRZrz2zV8NGnnzNbOaSeMpocMJkcUVZDpNIpcRsDPgRms0uWyyXPnz9H6wSN/fbb7yQhXVdJ0MSsUaPIiiDNm21bYkwc3t5tsK7h5fPnWNtg2w3D4YiiLBmPRwlqer2E4CmNQYi6VypGV1TlkIP9A7QqUMqgdQFC4pwA0t/jcZn8uJj6IHyQOdQUc6FCUlTGlDlJ71O4SwpCLJGiwMgaZEAJz91H73Nw6w3eeveHnJ+8ZDG74slnH7NYzLmYXXF2bhHRopVjvNZMWoOnphxOefDm2wRdI6sh5YuXLBdLzs/OCc4SfbpGAG9TOW2by3YFuRckpnXmSR7uErjwjjJ4njnLQCvGxjCuKgqtMUqhnEc5Dz4wMCV7UjEuCnxV45TGio5bnFcF0DdofG3o7C/+e3d8eUDntd/skrl/z5vwiiPwyhm9hm31NVoiPa+vaWwX3T7yn0K8EjO6eQ431WckGXIJRriD6RCJ8pMtOYiIEek90aba76VSBB9otcbq5A4XUmQoaRAxx0aFwkuNk2lxn3rP3DtOreXYWq6848x71qTmsyU7HBQ7r8l9BkTHdRt77yp5Pq9e+DaQdD18lDwFQa0kQ6UYKs1ASUohkpeQr5cQU3LSGKqqoKwLlJagJUInIEEpFEqlngGlDFIaEAJtJMZJXFCEqBGqRJoRrdc0LjBbepo24LzECIkMChcyTaMW1CNNKQzVeB9LycM11IMRMQouLmc0FjabAEITIjRti1QSpTXr9ZKmaViv11RVlctgM+ruDgVVZ3DEzvyNGRnVO5xrWG8WbNZLnj97gvcWKcF5R1VWWNcQgsfaFmM0IzlktUkJa6kkg8GAuq4piqrnnRYyEcCGHDcVomuSkxlqOykrkUOiYsedTmGybCR1yzznThJZUgAkuhyjVElR1AhZUo8WeDTz2SWXF+c06xXBeyQKUw9Bl0hZUgjD7bt3kUXNaO+Ayf4+F+cXhBBYLxY063UGodzxu3PHd8IlSvPYJZ87y94DTUxhwpVLa3slJMZ5Cq1S6WkIyAijsmHuPesQU25BpMKOnjflGzz+nkrhZhHp7vhiZfBl33rdUV7391f5zu5ZfN2cRVdHvbX5t+7jzbyB2FEqPWpsPmjc3Si/2YcgRGqgESTOYxlB5QaeJKQF6wwrcbZZMRSSO6rgzqDmqK5pByWVkNQSEuJ8IEqBFxKLZmYjq9bxZDFn5iyntuUiBJYhcsYWnbbjtE0QFal+e5ctC5LA9rFjiLuZTu/GdpZT+Ejm8FFICWYpmBrNYVVwVCQcmzokmlYRfA//XA41o8MxR0d77B/sMZoMoQxEU7H2GuUMNjjKuqYoByl5qhSmLjG1o7SOdRvRumQwvc3zF2ccn5zz+eNzQlAMBhNKLzGloahGlMOKST2hHu9RlEPU4IAgND/+A8WzZ2fM52tOzi6Ip5eE8ISXx2fMl0tOz84Yj8ccHBwwnU6o64qDgwP29vY4ODhgNJpQlom6U8lEqBNCzNVF5PLHJHSbtuXi4oST4+dcXpzys5/9NUYrjm4dMV7OKYsS51xP0PPWO28xHA45PT2lKEuG4xF7kymFKZCiQKAQQmdKzRQmi0gSYF7uvM41s32Pp8g0mlEAYbtk80YxRJTUQCSIgIgZ0UqZ1DSmBkxuT5hEz4O3v0O7WbNeLbg4P6VZr2k2G5yLWBdoXKREcnD/DUw5QJuKJ0+e8vjzx/w//tW/4vFnn3P84gXeusSNHiJSaZSU2FyBp5TEBZ8wngAdReI3yWWmS8CEQNEGVGtRQKFS6EgbjS42TBA8WK6Ytpa7EaxQ+Aw/8/oW22/O+PrQ2b9i3MQo/crhn/jqr52Y2RXRX7SnL1ImXXIvvmL9530JIFtAMVtNfVI1v6Z4t3hFFt6ErQ59iGn37Wwr7ljT13IOcUu9YrMv03HM2px7WMeA8w2rdeDctqz8gLExHNYVhZEoKXF4Ns5zubZcNi1La3nWJLjgy+CZR1iTGtH6iiKles3WxZOvTU8gl7722QN64pcu6hpiH2qT/U+GAydjHAnBWCecmYGQiZcbMFEkbpgYcqVPrhhxjrbZsFkXBOdx2hJ0wEVJFAbnFZsGjKiQwiBizWy14GK+4cnzM1yAsp6ljIaouP/29zHFgMFomhLFCBoXUyLU1Mh6jB5OODh6gFCGgGE4uUPTeFZrj7OB1jrKesTp2RnPnj/j5cslz58/4403HrG/v89kMulLYJeLFW1rU/+BSFb6crnEeYdzjs16TdNsmM0u2TQrFvPzfB/hzTffoCwLptMJwQeCD6xWbU80L2VSDrdv30YqhdYGrUukMtlAyDVfId+nmNa0yHF6EEiVFnai/EwWTAfDsQ2hxgTLnZNp/XOUXYfAlvcDJfowqhcRUdRUyrCnK7xLsNgxpDCqdak0QxclKE0Uimo84PD2Icoo/vPPfsZHH/6S//x3H7BarYhNS0eX6buu/RCzUk3HTyFNkWFhunwDPY6aAGQmwuqa1NabDaebhivrWPmIz6sWRE9yxc5cbGURvGoe/naNv3/z2hfE3F4XOHpdKOaLP/zSt7mmGL7gHF733bhr/vT3dOem7yiCax2p/fbxhhJ4/TFj3IapUiNcfgCjyEsuVZl0oaReReSwUqdTPBGbr7Uh4mJkYwNza0EIplWEekCtDEZrGm8TVHDbct5sWLSWl23bw1MsSQ/LnO0xZcb1TzWlgl0SBNHNR+f1xHRtXXcv4noORlz76cp1M6uaENRKUYkUNiogk7OnCqcYUyVVKqtNmP+2bbFNi/OeVllknXsvggIvwSowBiEKQtRcLSKnF5YnLxe0NqLLwHT/iMl0xK2H71EPRgxGU9ZNw8a2uPmSgCTIgmBKMBWjvQOULgHDeJpIcVZrT9taNpsWHxJ3QVEYlssFl5eXTKcTjDFsNhtWyyVaapz1KKVRRuc1EZnNZjhnCcGxXC5Zr1ecnR/TthuazYLbt/aZTkfcunWLqioYDgcs50s2m6aH3dZao5VG64LhcNQ350mlQXSoWzK9xnxbEb3l3/ExSERv0XwRPAnEHfrP63f5OhqAIBFYpZ6OKDxCl+iiYlgMEJCS7HkRWZdRYI1J4BwR6uGAvYM9BqMR9XBANRjw4vgczi8IYkHrbILqCKL3XLqCh6SjRA4fpQCvoyuH3q7JGCPCe2RISiG0DTNrWbpAGzqulxTyg3Dj4d+5/L/X+M0KSP2DdjT/w+jO12cEXv37q030q1vF1x6ib2wSN/6Okev+9Bef3u4jtXtwETqF8MXBrC4mGrJsVmLbLKZiCvUsCFQE1psVA2d57j1VUWAy0NjaWs7XK2a2ZR0cV8S+Aa1DM90FFVSwDQsltvJXYqpdyOs68B4538A176LbolMGhtSsVmnJuCiopaSIEeEcSkgKKbF5J1JKVuuG+XrB+O27FNMR+2aMLgXSBBrhWbdrPnv2gv2DAUe3DzlbwOV8wd/8/K9YtxEbBO+9/3sc3r7Le99+n7IaUJQV5XgPIRKp/bMXz1k3F6ycQmnDYDDhyfE53l9w98F30ULR2pAJcjTDUc0gCkIQHN26g3OOn/zkJxwfv+Tp0yfM53Nmsxl//ud/zrNnz3j+7FleN+B8h3MkuHXriMPDA773/e9w9/YdDg8P+O533mU4qNibjtk0S5pmw8nJS+bzGc+fO44Oj9jbP+B73/8hxhQYYyjLGqk0IXha27LaNAwpMBqM6fopci6j7zhPQ2u1ExpMglWqzgAKO67vjo+eO7mRN/1B6DC3QnRIqSEmkIi0aCRCZZQy2SOKoeX2KVFCJTyvARRFQV0NuHf/Pn/yz/85b739LT74+Qf863/9rzk+PWE1a0h1R7k3KJ9qoIMmlxnWQiJUPtdcPhxjxHq3vWafFEQjJV4l4yJKlf3b7sq38/C/bnzdAPb//uPrK4Uvma/OAP+iUM4Xv/G6vXyF8avmut/Nl5xR/jXelG79r6LHqLm+zQ3e43j9y6L7bu8hvHoG8TW/7zgqvYUedrZzJFd47QRt0yRAL6Vog6fxjpmzrIKniZEV1xPIu/zVXe9F4orOTsJr1u+14F1vmcVXtrt2/vT2an6VGG0SUJkAogeR2eZkTscKSfDQWM9i3lBcbZiuIlIaRGmI0abwnBwzXwvsyYqVFazbSDm8Tb0/xFRDHrz9ffYPb7F36xFapaYtXQ1SY5loUKbGmA1KNwkKJErqepgA83SRO58jUialIJUmRpkaBqXoSyeFSEJ2uVywWCzw3rG/P+Xo6CB7VzHnEdLM7O/vM51OefPNRxzu7zOdjDk4nFBXJaPhAO8bmk0SYN4H2tYihKIoylTaqVPoKHkFKTQklcEYUNLkRPBWIVxbnzdsmm5diWufR3qgpZvjZlGFYPtHzE2TUWYPMSO8dj0ZQMpzpP0LcXO1k4iClKAqFWVRMRgM+d7332cwrJkv53z88cc8e/6c09NjbNviGt8nm+PO09EpvEgkZC89ZMXld+RWzP03QqVEvVQyG4Ox9zp21/R24rYRgC8ev1kK4HXjHxz76BoIHn/fKfqHnNjXKITXvdXVjOe4SVdGKIVES5mSobvVEP1Xt8B7CNljIxGSM6q6cEvvlKeY9m4t9O4i7Oaug7FIdR6JBMfGxPK2JKBDS7lxdMAELbHvQO6IiXY7kT03AAbJMeawvVsxSl5Z7jvXvNu73V1y15R708PokFETjr6k0AVGpOQzLp1N1zVM7vKNVmJbOH4xY42hvN8wvDNgONrDYQnSUo0Vz45PefaLz8EMGE8P+MHv/dfcefAmt+48oD44RCgNIeBdwgxKFe0pIl3VE0ZBst74RKbkAo8evcXe3iFlNQRUgiQxZYJn73y8/iZ5nHeMpxP2Dvao6xKtFP/Nf/svCSHBkUjZNZ3Jfl1536XwI85ucLbBhzb1PDhHs1mzXCxT1VKGMVGmpMjJWClTnsCHvM6kpqxqqlpuw5TdT+/ZpjDR6wVd3CqD7u8bQq83Hrj5s91ROnIHwyuQ6NwE123Qfc7Oqu/Kw3NOKSTDQZs099oY/ss//S/4vZ/8Hv/0j/+If/c//U/87V//DX/+5/+Gy4sLZlfzhGkUPD64NMepAYhIxMWAJPUdpDYaSegsn7DVaabQmEJiikT1ucW0vT5T/9uMXc/718ub+MpKocNw78aXXcKvy+W9go8qroc7dt7uPQIhctxcdOGU9EDHGw9MYox69Vq7BNx1xXh9we3CgO9stI1/9scR+Oj7yiAZUyLNkkTVJqfGchQ0J6dFH4bqjyegI+7ZHnd7jT5XxexWWvUe1M4syh2/oc+HZIUgd66r2yqBm0Ucgig16G0JpI+RTQyp0xgQ9ZCiKBlUFUsrmJ8uefkf/g69P6I4miCnA6JSrJ1nML3F9378XQ7uPGQwnnJ47w0G433K4ZSIIQaRAAOlQ5BgJ5arJc+ePWa+mLPZrAkRirJKnbajCUVZ43xAiBRW8t4TXSLnAZLwytZ3VRY93aZWKjtdGZsoOkRUhBixrUXIxLDmQ8A5y3IxZzG/Yr1aslov+kqk4XDE7dt3uLyagRAUpuTo6Baj0Tg3kMkUhhHbMM6ud9rN+26FW/fZrujpxf2OF91/3nXu0ymZyLZctQsAQYdtxe6Kll0fRuI9VD0qYF53odtv5hqPoT83rZIYCgJiJtmJKJSGo8M9/uAnv8fbbzzgwb0jnj97zgc//4Dnz59ycXXB1ewK5zzWZaXQpccIWYHH/lkVQqRYLMllDSHgQsj8GNsnU/RP699viJ25/U1scPuansJW1G17uH59r/qmIL85xGv+2K7/btnH3kO4rmRyB3HvSos+DpPKu3cfm/R/18m8y6f2im/ffyvtL+TEdcwKQYnc5xC3dKbb1jKRvAOxUyu2YzR26AXbC96x+vNbN/2a7dY71x5vhLi4Jh6u/Z3IflI3apQqQUvHgPee1ofcLCSRRYmgQBeGuY+sl5bZkxPkbIlarJjcv4Wua2RRcjS5zaN3vsO9R+9QDsfowRhpaqQu8dYnz6WjLRaCEC1t6zg7u2C5WtC2LYPRCKU0w8GYsqwxukhJWxlRSmK9I/iYE/FJ80WVFITRCilV4mCWAgh4n7qRY1dEEAPWNX3OJsZA0zQs5hdcXV1kALukFIQQjMdjptMpPgi0NoxGY0ajMWVZ9YogNRF22amd/oe4VVjpZnUaXeyusuv1g70CYOeucd0ziDdXfKfwezch65cU00fENGciwa/0a2Cn9V9k1NgYthSlqS8CelrR4AkiJbrHo5rqrYfcv3NEpQVPHj+m0IKqEFQvJDG0rDcNcdXsUAx1xw34kJ7fbYiIa+eVwPIyJZXozulVvypNzZeFjV4/dntdf1PG/+bQ2b+uY1csSyEhpsVjXeJo9qRGmS2SJXmb0C8VmZVHX9u8E//ZZXGL3cNLfqCylN4+fulLW/i00K9cKRP4mg8etCAqSfSpVlSE3Qc17duzXYCia/ihU5Ci+2B7Log+3LG76GPoSlR3V3N3HVs3XIgUQhLdaccufyEyQqxhg2IR4Mqnq1WqQomAihovCoIUBF2zDIHLIFkUEldoRneOGN46ZPLgLu/98Pvs3brF7QcPMeMJZjShbduUHFRDXFREl5uPYiB6jzYCpRUEhyOyahs2zuGCp2bXs1FImbgtEAoBGKVAgtR66zmJJEhssyWDFST+A2dbpAKtJErl7TWcnR1zfnmGEEkRbtYNzqWcSlEUeT4Ug9GY8XTK4dEdYgTvAyKzuvkYcjPc9dGFO7s1tRv2ubZtvoUdTPR1/b5j6OU13BkPvd8odne0ux5uuMTIVE0WMre57GBeUxhVyi2InMvrSIhAcA0IUBoKLSiVYd2sECJSGkNRwEAV/P7vfo8ffvdt/suf/IBnTx7z8uUL/vv/4V/z6Wef89Of/ZzZlaNtk/fsQwL3Myahp6JU8ihsS4yk0tiQFmw3h+mp9yDze/43SJL/A46vrRR+nT2DrzLEF/0uxLWfNGJvZYtsqSXaQ7IFnqR+Kt3cWvdpe5m/38Hx9rvc2bfojTpx48x2H9V8gnSQvyFL5I69ausOxBveQE6+xd2/xA2p8er97OLg7JzbNryWryv6ne13vktWiKQwlgXWPnCx2TCQNVoZKqnQInUzNy4RoNjWJc6HwYDx0QFmMmb/rTcY3jpicu82tx++xWhvj9HBHURZIcoKH1RKPouuJDNV23R+mfcdppDPzGMJp8g5h8vAgjGCkBIlk/DvOCm6fgyxa1+LdFdlRl6W/eeJIxq6/EEgBMdms2S5SuEiIUM/Vx0MRVkMctVMSigLITHGpHMSIfM2yNx5LLjuxbGzVrf3Z3cZdcrsWunwDnLAtYKBrsruxkrst92NDNxYO50f3SupvmxZ9ufZnU/X0S063yW+yqkoBGiRqoViCARvCc7RbtbYzRrfLlDCUhVw62BMcLeJ3nJ1uWG9tqyWa9Yby3LVYH1IiLDExM0cu3JV0fMvENI59NA23dzsjK/jJWwjFF/5K79W46vTcf6GK4PtEDv/dw9I6BODWuvecu5GBKRKLFWdNSxIcf4Qt1ZzrxSkSD29MSQL/4tGb5FFbiqFrUSW24dQJkkUunMTMfNEZwsvxORF5F1sQzg3DtrtP+4u4Js16d1uOogEkbpzpQARcS70jU8hnQpSdMcTiceB3DDnWh5fXWKMhqJAaYMhorRm4QON88yXK4rpmNH+IY9+50ccPXzA2z/6IYP9fQZHB1AUoBVUNTGHUVShkFEQpdp5ApMEEyFgXUtoGyB5B0VVEmYz2ralaTZUVZXhqhMzWXAxdcnGgJYyxfHDjmcYk+JRuvOsSLMrElpqSjQ7vG9pbcPs6pSLy1MuLk9QGrQ2DAcj6rqkLIbU1RgpNQLJoB7QdR1LKdEFGZZbErpYeW93ZOHdW9/yFYWx/b3D3Qq7qypLvm4NdG+9ugb6fYStoBQisu1zSP913OVCadR1VdoL2wiQrfPUupBWi8qSOAaPkAkLqpAuhZGsTcqgaTh7+YLlYs7V6SnL5Zz1Zs3twxFH+yN+57vf4uJizmK+4tNPnnF+fsXz56ccn12x3rQk3zUpAyVS74wMIHwkOp+UfVb6fQ8EX64MOk/8+vjNl5Pf2PDRrpUTIQvX68og4dqn+ucQUkiiDztJ2cfy+1p+IROE9U4NqcidpWmjnFzbeai7/clrakH0QseL/PDIhAEklEwNpCESvSN07v2O8NruqKuaed3Cvb6gr1Vf7V5XF5YQSRnQCSIhQXZsb/kIUhGjwIXIGp8T4jK58m1De37Gk/mM/aqgVJJSKYbjEfX+hDffe4fDe/e4/8473HrnbQb7+wzv3kaVJVQVlGWiHFNbVFalDZGknLt/nUUdhaAwhqgFl5fHrJZL2s2GsjCo8Yi6KhFEFosZzjbEaFmvWwQKlUtTZb7PHfeA9z6HOUyS0iEQRSQEx3o5Y71Zsd6s2GyWeG/xdsN8dsHs6hKpBMPBkFtHd9jfO2Iy3kfIMuFeOZ96KkyRSWA6PubcnCZ1gpMOaf7TPdrlAHxVcHWr+3U5ItGtKSJb1sBtpktKtd1JjOw2ZKa10i2QnfdEXmsZLDB0/Q3EPizaI+gKEEpAcBAcQkZidHi7xvoG51rmlyesFjNOjp+zWc5pmzXetkghKIxiPCnZP9jjwf1DUlGzxrfg2sj58YyrqyWnJ1d89NHnnJxe8NEnn7JcrlmuVgkqJQRKHyhCxMSICiCzkdM/rt/Q8Q1WCtfH1vLbPmKdJSal6Jt4yqJMFoVMsd6usSd9X+XEcBoxdkQmXQIrF+wKmaNM3T+2FUt9qCo9/G0mbXE5ERYhJxwDwYtrXdHXIDa6h7Q7l2vX+sWeX6cYOsC/3UqK7jXmcELkBjtV9mpCSF2lUUTaDGzmfcCtV1y1klWsGJQl02JAvb9HeXTInfff586DB7zx3nuM79zBjIYwHCSCGylBl0khCHIyP2bQNzLZUHfvOgWWPJsUskiCSpD4B7RK8x+8Z7Na0bYbnG0zEF1EodO96pOxyVTvqCuV1oAnxo4v2bJaLVgu5yyWc5pmmaxeEfHeIWU6F20MVTVgOBwxHI4JaLwPWOGSh5oT2ckoUFmwkjwWYo7GbI0KOoNg9/5Grt3srv6++/8aW2AOe+6I9p2f69VqabmIbfhpd3RGSux+Qg6zJq8geZI5PCMAmVd9dOAtPji8a1ktLmjtGtuuuTx/yXJ+yfHTz2nWC5xtKI2mrEoG1Zi6klRVybAcIqIkeIH0mugEU1UxH67ZL4aERcMgSq6ev6RoHVIqNjFQC0mBwJCLNWLMFLy74bFv5vjGK4XezsoJsuh9crVjYsHSWmGkAqVQUvA773+fsiiIIWCdI3iPLgqMNlRVnTpIu4Rf7KqGugcpC5pkjuUkbYekmc6mq1YJISW156sl682ak7MzTs/OuJxdbk8+ZPYuIfA5cbALdhZzbPTLHNprYbIbiqLzFJIwTMnDLu7cJdylFBn3XyK0SaEslYDJlAAnE3jZ0rYs8RQioidjDh495Ps/+hF/8Ad/yKM33+D2W2+hyxJZFAitkwLQmp6Tsqu8EYIospAP6SSNNviQcgRSpJBL+lrKDdw+vM1kOGRQFZyeHHN1dcnJyQlCSKqiotAFq/mCh2+8jZQ6l0vaZO372AvFLlkv2s4adqyWC5arBZ8//pT1ekXTrBhPRgmPylkePXyLH//uEePxGJXhKEI0WC8wOnkAstRY62hbl4hycn5ESE1X3CBI3kO3ar/onr4SC+8Ux45y6D6B655hJw173mbSOrzpaYpeH22/27oG7wNSpb6essylvDGFgDp+jXTYAOuG4FuCa3j58hlnZyf83U//Cteu8a5lWGmqQrM/HjI9uM+wrjg42EPL1NOyXCzYrDcsXj5jNV9ycXLB4mzBer7h5bNT5pcrLk/nnJ/P2axbitayFyIjKaEcMxntca8esq8LqpAEYccp3pV4f1PHN14p9COv+20lDime7H0SHmXBcDDg93/yT9ibTilzQhBIfLdaUxRlqonuYr/Zau1qn3snXQCqUwBdY8+uldsJocDF5SWXV1f84he/4IMPf8FmtcT6jkQ+147kEkDy753b/kXqYLcQqdvHbnihzzl2qqo7n/xhpLNAU2JX5KvrsXVECicEAV6BUApZVIwnY6ajEd/93vu8/eZbfP93f5f73/42e0dHFJMxogPokzLlDbqwlbwRIulDKLG/dymgIiF4YvbMnHPE0KKUwJiC0XDEYj5jvTLZixBopWjaTW/ha21SOCKHUHxH9oJIgHfes1qtsK7FOUvTrlOXrbOpRl9IQq5aUbLEmJqiGFKYUWIAiwLnZUqQZ5BFKVVicAtxK3HhWnK5n4t8vfH6LzvzszMv/eTsJA6ujdxd0u02GxEdNtcroztEb0xvjyViQOJy4ZwkhtQQJmJAhDb3H7jslTWs5pdsVgs2qzmX56dsVksGKiArgxSaUVVSGsOoqjBeEJctl4uXeOdplmuuLi5ZLZZcHF+yWWxYXC5wiwa3sWxmK/yqRc0bpo1nFCEU1bahsygZ1QMOyoqRNlRSoiLZU7j+fPxDjd05/nUf/6gUuhGTcNQy4bFIRILvdQ6kZDSYcvfObf6P/4f/lkcPH3G4t5e4gLWm0KaPuydBlIVjZt3KB0gv3ero0LqujZ0HXyRBe/L8Bc+fP+d//Lf/Ft82nB0fM1+tcd5n3JekTBIcQ/qqz3XXX+wjXLf+Xt0qxZEhJZi3UyTomWuzYE7VPkl0Oe9SklSqpNgERJmUZjmsuP/OOzx8+JB//i//jHffeosf/c4PMUWVwiY2oTIlC63ztjJkd1fKKLb3SSi17QuInZ4VOJeqgYKEdtPQtmtGoxKtNNPJlMXsis1ySVUUSdlXFW3bMJtdsJhfUBRlguQw6XPrXO91WevZbDZ88umnbJo1TbNOt1Kl/WitUSoB6REFZT1EyhooCaFE5CY0dcMUFUpSZF7lNPtJYUhxcz10n3fKuw/ub/e1m3DvDJHY153t3OvO3N9dhKEPtXXKZFcx9Rwifcf/9nsyN4vF2OaCHpGKEmIkhoZgG1zbcHl+zGox4+XzJ5yfHXN5doxvGwZlwdsP7zOsagZlybCoUQAuMDu/ZHE148XnT1lczjl9fszFyRmLqxknT8/wmwANVAJKKZhUNSYIpl5QVwN0VSBMiRMCKwS2KKgnE+4Mag7KkpHSGBKEfWf8bIV33F77N2R845VCiuRsY+jOOmIISAFaghFgJBQiUUrWEYZEhoBsW0Tbggu9Rat6T6EryxPbJ7Fz4bvqjZvx+n67LVqSWSwo1mtMa5HrhrjaUCDQUmE7ALKYUCdjBB/cK3Hlv89IuYV00l2OoSsnDDFkSzo99ELkxqruSZICZTRFaXj45hvcu3+PH/zwB3z7vfe4d/cu77zzFpPRGFFW2BDB2hSiuz4byWMARMgds51QzA+vzD0FoUv6xpA7aQUxOsqyoCwlUqbyRkHkYH+PQV0wHo9o25bNpmW9XtM0DZ999hmDesB0ukdjHa21XF3Nsg6U1IMhCPC+BVLVUllWFEWCuq7KOv9doZTG6ApjSkympCSKTJuaL0+lnIx3Ea1lTvBuzdQQt2BvvzoEeDMM1PkS3b98L9kqk1cFXdy+im4bek+332OHaZJhdCMeLX1mvAl47/CNZb6a027WXJ2esFzMWS6ucOsVMVhU9BxUhtsP76XQTYiojWN+/JyTxZLN5Zx23bC8uGJ+ccVqvmJ1viI2lrhpEdZR+8DbFJhaU49KBkpTCIkOmXzKC6qqRmqNlQorJa2WrLXBFIZRjJTeQWtRGT1VkSqQvqRm8Ld+fKOUQv8wdH+zE27t3buQH0T6DmItMkuY9/jVCrdY4pRC+CSMROPyjrYVRT3JfUdyHMkPWn7gZPeIhe7A+aw6ZMskBNvVEnc1IyxX0LRI59FK4UmlqVtEHQHXkoBfw7L5FQrkWkUSSbT0gmqnbr1LzBeFYTQZMxqPePudd3jjrTf50Y9/zDtvvsWtoyP29qcYrUEpYsiW+GtLIUXvMcnO9bgWG89/h/7mbXVwzglJqfC+IUZHjBatU4JyPB6yXiusdYQQsNYym83xPlAUFcv1mk3TcH5+DohEMiMFxiSBkpjXFIPBkLIoGQ7HDAZDBvWQshwk6GxZJIs6CoTQ2YL2ea4geURb7Kxtjc52FrYGa2ft5+qqnA+41pS4O3+7lq64vo9rG+16FnF3+y6pvKMoOm3cr1nS7zHDLQqHt5sMB75ifnXJZrXk4vQlq8Wc1WKO9Cm/UBuF0YpSK1SIhNaxPL1kdnrG/PyS+fEZzWLN/OyC1XxJu9wQVwEVoAqCUkhKKRkVBZU2DMuKgdQYIaFtEbkj2qgED9+IiJXQSpkaDKWgiBHlA8L7FObamd9O3W2n6nXP1pc/ONem9zdo/NYrhde5fbu3MuEKbbGMpFJJsIdIkRfeUApUs8Gdn/PhX/wFs7199osC1Tqk95QuIEJaXIXWKJHI3WPXGJMPGILPvA0xy/yYAL2yIJPKEIWgjYKoNVEpLq3jbL7g6S8+xJ2cMUGw8JmxTRmaEGhDxG5aehCNPuZ+w975Cgu0+65Sqset797z3meHaKcuXkgIqRu0qioGwwF37t7mJz/5Cd/5znf4p3/8xxwcHnD79hFVWWKUTp5YENAGCmUQSuDdzrmqrjNsi4gf4lbhdsn0NKnZa0AglcL5Lblo8C3BW1o7p23XLBdXuZcgstk0rJZrzs8vWa0tzgUKM0RKz2xhWa8bmqah2fjEY1ApyrJmNBrx1lsHtNay3rQMBkO01hhdZrhtQ6LtlIiocq9BLi/tMKZy3ijkRLnW5oY30ImnnTWb4/3bRrDdMtGkGBLoHv29gtzaIkVmf9u+1/kQXWejEDIpgZg7/HPoKHiXPbFc5y8TFEhSxoEYHME1rBczms2Ss9OXzK8uuTg7Yb1cEJ3DyMiorDjcn1IqSbCOq5NTzk9ecnlyxtmTF6yuFlw9e0lcN8TGUtqAChHtImOpKKRirx5RC8VYaIoQ0TEyMAYlBDpElG0QIaK87b1aQkOQkkYKrDa0RQFigPQlxm2QroG2AR/Sd6/N/JeFX7/oYbqZ0/nNG7/1SuGLRrzxe+yqgvJIBmkEH4jWpTLLCCeff048u6BRisI6tPNULpN3eE+hFEoIvLNJoEb6Wv7OCut43CHi8fTJVaEIQmCFxGuD05pLH7hYrZmfnuJWK1TYJpeD2MIzd5Z1jLEPh8W4Ren8WnPTldKyDRt1+1BSIVXqPegs17KqKMuShw8fcnh0yLe+/R4/+tGPePfdd3nw4AHD4ZDRcJQEd3ajuhyAQCSmq5jOX0iZ7NAdprvdTl0hUnMckKqPuvCISH3UMVic37DZXLCcn7NaXXJx9RznmtQZG1MV1fn5FZt1w3yx4cGDtzg6PMSYEVU1ZDzZYzgY4pxjPNlLVJhlwXS6R1VX1IMR2jqkaqnKOnsFOldhJb6vrkT5RutWv7i2wIs3DZcbyeVrqzR7CDsKQbDtRem4A2KMKbeV10Ii5ulOISaYje5oIoWnZO7FCSFkPoLYV50Jug72XDARU/6gWa9YLxZcXZ5xdXHCZrOkWS8JziGdY6+qUUSU98TWspqf8fLsnPViyenTl2xmczazJc3lnLBpqVYOE1K138CAjmBUMs4MgpEwFAiGQaB9QEeoRUCJFLaV2eKXwSevKIYMjieztyaIXqJ96o+QIT23grgT0e38tS+u8OrW5G9PQ+/18Y1VCrujb90X3UOSV0juEA6hJUiBs46XH31MW1SsgIH1FN5T2xSTLIKnkImf2LZtyleQEDJjzMiRncAWSZBFAiJzDbcRvJA4rWm1oVWaSwRXbcvV6Sl2uUTlRCsxKRSfW/i7ZGzqiE2dxzH6LODjNkwF3HR/X1eW6r1HSZUTpz4LGIlSCmMMjW3zvEnG4zH7+/v8+Mc/5o03HvH7v/8TvvWdb3P//n2UMSgpMUrhvSN6j1Qic1zJPj6dXO1UhhljyIqhS9Vky0xkKPCsZFN0o8PoT8l1HzY0zZzL8+c8efIRx8dP+PzznxOjYziscww/8Pnnz2gaj3WCRw/f5P69exgzpawGDEeTXsD6GLasZybxMxijMcajtc08BxIhUjRaCEVP4bdbPcTWC+tzMDff64OZr7FCu7DkToag+37MoG+dMnDO0bYtMYQMoVEgKFEqCTJrbbfL7ElIlEod2d57tDLpHniXWkMkeOsQImSlYAnOsro65vTkJZ998jEvXjxls1oyrComgwEH4ym3J1NKrQmrDaez57z4/Cm/+Jufcn58ystPniJDEvxjNJXUHBQ1Y1MyLAwjoTARjPeokCAqihBRISYvwifU4Dp0pE4xNcLFLumde0tkVxyRnRspUNqCy0ohZqThrQi44aO9bojt3P8WKoZvsFLYvfG5a9UHfAz4EPBx2+0JIEJE4mkur7DFGiElZYRBiAzaBhMCZQwUAlRMTUtKSIzWOOdTD4TsEnQRH1N3bFEVGU9HcrVpaWJkrRReaVCajfMsm4b55SXOJgJ3jcjUg8nlFzFuY/LZbU4vuzwA2VrtjG4BHc59+lrsBf/u3977RECvFGVZ9tZkDIHBYMB7777H9773Pd771rf4p3/0RxwdHXHv3l2U1lhncyFRsp5jSHNrrUVLTWFKkrpK/L1JngraGBOuvhRJIYiIEh1wt8hcxz5/LrIVbAl+w+XFM45ffs5/+F/+NcOBZFBLfvTDh5SFZjio0boCoXj+7BEXF3OePj1ls7zk6eNP+eHv/glVPcKUw34qA1s4CZF7JgQSrSKqSmGXrUXx6tq6JmBiYhvrS2rjq4rjC8duPkxs9xvpMJjS74v5jJOTE54+eYaQgu9+57tImaqjunSBkooOD8o5RwQ2zZqiKNBFaswTIqIUxGAheLT2eLthcXnFRx/+jJPjZ5w8f4oWUJcF7z24w6CqqHWJ8hFlI6efPGN+dsHHf/szLp6fcv7sBHu1RDjPA1EwUIaBNoylopKKidSUQVKESB0tKkSMD8gcglU+NcCZkJ5HEWJi8gOUyCCRMXkyXcc2uXpQS4WT2ZtwHrzP+82eDx4RE9BhwvTtb9m1169wo77ylr+u4xusFOCaYohba+sVa4zsWsZIaNvM2mRQgIlQOE8RAzWRgtSk471DSUkRSOWjIfaNQCJGXEhKofQKKTxCOFbO4UPXQJMEumtb2qahbRs60MYtVQm5OkT01n58jdX/anXKje/sbHctlJFDX9vO7q3CmE4m7O8f8N577/Hd736X73znO7z37rtMphNGoxGtbbHOJQUVwjb8EFP1SqDret1aXdskq6Dr3qa/xhS6CIhtaGBHGHvXYu2Kxfycy8tjTo6fYO7vsT+dcutwRFkaysKgdYUQmuD20UqxnG9omjWXF2epUdGY1GSW952UgtzOYRfmEiLH5ndyAbuJ3Btyvhf8XVdy9iR6q/OrKIad+7J19rbr1HtHs9mwmM+5urpEa91/IQSfu+STEvF5Dn3YcoWkpr0MIx3zOm03eLshuDXtZslqds7Zy6ecHT9nfnHCqK7ZHxwwKQsGZYVoA3a5YXO15OSTJ1y8OOX5zz9heTZjdT6n9pJSCg7qgpEsGKqCkZSUCEak3IAOkTIkD0GHmDCKYqpQkiT8IvLzqELyJGWXQ+i9yHwvRBL6UihEViA9EF43f7t/73gV12/k1xf21x6l3yBd8Q1XCtsRMmRFCB01ZaKL7ErFU+RHZLwWhVJZIcTIAKikZCwFBSGXpbpkgbgW2zp8CD1khpQCR1681uKso10lFiqkRBVFLyTWtmXZNqxsywpYk/iaLQIrDVEkspfUpxAJIsELBO8JYRv66NRI16160yvYTSZ3o0vsdtU51lqqqmI4HPIv/uy/4t133+Wf/bN/xv17DzIhzAhyr4bRmrIssG0L3tN6h1Gp4kRnVrTNfEYxGKJMgVIaHyPOp+9GKfG4ZAWSwNJCloZSJIhlpQQQsG7D7OqE2eUxH330d1ycP6MoLAd7JffuTbl9NCQGx3x+wdonSIQYCspCcrA/4fHTY16enPMntqEMHhECyKQYOnmRmgPVznxdx8mC1zd89Yqt+5dN/a8rJG4q8Ju5Iucc5+fnXFxccHl5SVkWjEYjbt06wvmWxXLGsK5RKnV7R+9xNuEMSSUZDgeE0NKsV0iVGy6D4+T5Yy5Oj/n0Fz9js5qzWV4yrgyTQvOt7367DxVdPD/j8vExH/zVf+bkyXOef/I5s6dzwtIy8oH9quKd4ZSDakAlFbUP1Cp5CMY5lA8Yb1Heo4LHeJ/DSzmoJkSvfgMi3SMS6mliONwaSolUiowrFYkSlFGoLsSHgCj7vM7NEqGvoZ5/K8c3VymkwHy2umK/WLYFaVvsl65CqY2Rq9UK4zzLWjCSilIIvJB4Ii6Q3NIY+oRwx0PcMWXFnAOIsbPqJS6CjRC0JmqNN4ZNCMys5appmduWNdCQiHUC6btC7sSZc2VJd1nsXkkfWsphhtjF8eN2q7gjaLLC6LyJLo9wcHDAw4cPefjwIX/0x3/MgwcPePDgAZPxNHMDdAdPnpL3KQTUWXUyZJjpkKFEBEhvs/ueFKYSqbOr67RWXXIzW69xe8WpIikFn/qfEC1KwcHeHpPxiEFdslmtEhZRJFU/KU2z8Djr2DQNZV1R6wEpH5kCWpKULyGH6egrrrZJ8a1M3kn050TwTQ0Rt0Stacu/p+R5nVfnvcday/n5OVdXV2w2G/b395hMJ4TYImWgKBLZEF7kXExAK5kT4xHbrIGETLq4mtNuVixnF8zOEzCdiS1lqTiqDhgaRSElem25Oj/mePYJZ49PWFzMePHRU9aXM8TZgn0X0FpxWJTslSX7RclUSgqSMWWcRUeLcR4VQ58/UN3zExNnSB/rF9tu+t6nFDsrXXRxfkFQcusZZMh5RKoEE0JBrgoTUqXPMinIV9HVoj/Obllw/ym/6SGkb65SuHYjO0tZ0ieaRIIi8DEpBAu0RC4WS2ThOBCacVFSKYWVyfptg8dZjwwJ40eJRAyeEnqJD7gTyF50EBEyk9FEvCkIxuCLgtVmw4VtuWgbrqxlDWxISiE1zIq++SmFvjoLfxvm6K5FXL/UPq/R4/PlhR1yAxjd97Lg0VozHA556623+PGPf8yPfvQj/snv/x77+/tMJpNcoir7eZUC2tYSgqcc1MnD8hF8qgoRzqVqESGg2aRHSGqE1uiyTDHhkBLzqTIkwSWkNqnEYtZ1MsdebQeESDDWxigODw6YjMfUVcXVxQUiRsqiwJgCoUquLmc0TctytWEw3Gc4Psw5jZCyjjtcFdvwW6ckXhcOyGJKdMQ9u9t1RkYXKutvwtdcslvvQMrr+SBrLaenp8zniW704PBt9vf38KFBa0VhFK61uBCRMZ2dVgKhNN5b1usFSqaqosuTZ8wuz3nx5FN8swJv2a9LRsOao/EY4yPROU6fPOf082f88qcfcP74mPXlEnexxoRAHeHAFAyN4U5RMTYFY22oY0SHgIkerAPnMCGiYkyvZMbMbn6yyS9IJeNBpJLYrjitZ32Tu0pX9rOdgH2zUhcSIXUqZhAqeYMiAy6K3Y7xXzW2Ic/XJZqvd5X/5o1vrlJ4Zew8pFEgQmLxSgI7CWQBzBDIEHjeNgigMQZpCgZa4ZAUghQeEQ6FwMoE4BZjROhtmVsbQ1IMpmATI6sYmcXIum14uV5xYi0n1vJivebKexbQh49cXy7RIU8mJRZjxOcQVJL7SVGk6qHrPNMq80Mk8L1t/bwSqv/OcDhkMpnkqqI3+NM//VPefPNNHj16xHA8RGuVH4wUflO5FFNLha4qYgi08wUyeEyMCO8JbcuLTz9jdnnJ6fEJdVVR1TUP33mXajyh3NvvaTQxhigjQYDKDFopSep2av7T9UqlkMogZYF1cHxyxnQ8Ym+yx3hwO1fTBE5PV8yXF3z+5JSmhdYb3n30Le4/eIuyHCC7sFFIKiiEDmojGQ3ELw79CMGOQsgquXPS/gHkw81O5K4QwDmHtZamaYgxUpYVR0dHHBxMAUuMHu8tRneK26OkRApYLeds1gvOTl4wuzpntZjRLK8QwTPRMB7uURnFIIJbrbn8+DGfffBLzl4cc/zZE+xiQzvbUFvBYZBMBlNqIRgIyShCGWESoWwdVeMogkfFSC0FwmfgyZxIlj70EyW7CcuxWwGEXCLU5dQ68yVkPz89wde5HGznyUuNExqHwgkFQiV/sCeukq80UH5Txz8qBejDGyJb8V1YqQ8fCYnN8ctVBBUil85SZZdzqFILfRSCgVaYKPGkhJjOHL5EcploWsxNCAQhCFqzibCOgbnzLHzgtNlw7h2XPv29jpGW5K04IPalrVkEdRUUHaeu2IYXOuuyT3KLbTVNh8sU47a+vVMWpjAcHR1x985d3n//fd566y3ef//9LGwOUgMeO924vUBMk9YVWuE8wVlc29DM5jSLBS8+/CVX5+ecvHjJYDCgGgwwUTA+PGRqLcVggCxMsrRzI1vitxH05Z6QQwIRSDkVrUuqesR6tcR5xXLpuLxYY9QW+nq+sCyWjhALdFFQV1P2D+4y3b+NkAWgISrijmDfXSd9IlJ0Aj9e+3jbUtGphyTn+vdufOe1y/FGpVEKVXVzHbcKpk+spmR+p9xTV3nyirxzhJjS4V1JaQwObz0ueGaXJ6yWMy7OXiTegs0SbIuWUBuDiQHZBtazJaurGedPXnD8yRPOX5wwe3GCaAPawkCWDKTgUGsqIRkIQe1TGekwBEwIGB/QwaOIaKVSw2fMKMJxZ6b7C+zi/V1bJpnnjh66vetDDl14NqXJs4AXPTWsR+KQ+ff0mY8dB7rYUupuj7x707/y+G3QK/+oFMhuaC5xEyGAT92mPkocqicWt0Ra77j0gcXKcuUde84wj56RVOxrzWFdMdSaMngMAiNlhuVNgsSFiPU+oTVKSSxL1iGyCIHPzs+52Gx4ulhyET1XMXBO8lK6nIKFLLhFDmZkgedCsnpk0ZPgSCn7sFCHxpqUQfrpqlN8SAifIQYKbRiNhnz3u9/l/fe/xw9/50f8wR/8AXfu3OHBgwcpfu2SpS6EQGqVAOSkwjZN6uQOgZgTzKVQ2GbJ7PFTfvGf/pIXn3zCR3/7t9jVmthYtDEoY/i70b/j7puPePcH3+Pd3/kdJrduIQ8PEUUJZYF3EHwkKp+Fb+f+J0FZlGOYaB6+8V2Gg32WV0uePrvi44+OcXaNUoq6rigHY4pqyNvf/h0me4fcvvsmo/EBRTkgBkMMGmTRh8OkAHGDie+6MtiGgrpw0/aznS7ta8Liq0qOnWPEHfhyQCmBkKCFpGlTqW8MSUQqJVO3sQ+ICFpKpDB4tyF4i7crZldnzGbn/PLnP2M5v2I1v+T+nTvcPthnUk6RIRDXLS8+fcz585d89Jc/ZXl2yez5GWUUGCR35IiygFpHpkhqIdgXYIKn8JHSgQ6RKoB0qRRUhsxypuN2HrOyTSGhHNvfmW8fI56AC/l9pQgZC8tFSURCVKluKsZUxJEVShtTxVoQio2QrJGsY2qYbKKkjRIXZK8cvs7d+W0d31il8KtufGowSz8JTi099kVR4ENk4SzaubTovGeoFDOtaY1mrBSisYiQHoJSqURRGCPOe6zzOJGwi1opWYfIynuer1esQsSOxwyHAwajAW8cHiHKijioWDQty6bh7OKU1WrJ1cUFvm3xIeTkdSRER/D0YSFBQn7trEwgKb647bIWLlCbgnJccffeXY5u3eJP/uRPee+9b/Ht73yHe/fuMRwOCd7jXWpAU1oiOgIi77E+eQQC0CrHaZ1HbDa055ecffIps88+Z/nkCcXVnMI6VAhoUhhhvlxzYS2ftA2V0jQPZ9xWGjkapXixMVtPS+Ru7Z5tTiJlQVEIJuMjjCyQ70OzWWCbFW2zQoh07+rhmKIeMj28S1ENqUd7ICusk8SQeyN6wvk8YpdnivQJmtjZrzvb7SqLPt/RvX+tjY3rKKPZ04pbi7mPnvSKIUNRvyaO7Z3DO4vWKlWiZS7x4C0pMJLq75fzc5bzK549+YTV8opmNUeFDQejkocHDzmcTBnXNfOTM+bnV7z85DEvP3nC1ctz5k9fwsYydpKBkJRCsa8rigi1jIxCpCIyIeUHlPdoG5A+pnUQUtmoUXpLH0uy+EOfd9nG/6PY9QxyL0umonU5ZBiRhKjy9qrvLbIxZIQCSRN8CtOqklYq1lKxkgYhNRskLaJ/Frtjvi7j81VQUq/Buf8Gj2+sUnjdrevf27n/If/dLxRT4Lxn6SwiBJoINgRGIWCloJCSVmsatyQ6i7AtdVGihUhlnc7TWktQCg+sQ2QTAusQOI8ebwpGhwdM79xmfPs29771berJmHp/n8v5nKvFgp9/8DNOT04IzrFaLGhjxPtkJQV871+HEJAigX/Rh5J8egojfVJZ+shgWHF4cMi33nmXR2+8wZ/+yZ/y6I03eOPNN/sHwlnbN64lnJ+kGKx1qZQ192YolWCnI8BqQ3t+wdnHnzB7/Jj1sxdUyxU6Rioh0dITvGd+ccl8sWB1ecFkOMJvNuwd3cIAsigTif0OemwkcR0kgzApBSU1o9EBw3rM4fQQbzd439Ksl0QiUinq4YSyGqCqARGFQ2HbTN4WBEIJjE6hiF1LtmMwu048thPm6BZJfm+LKdrpkW6HuzkJsVU+O+GTGHe+04ewYvZe4nYjuryCTX0xKnk3WkuInugtUnkIlhAt88szzk5f8POf/TVusyTahrcf3WN/PObRndvUukBFOD495+TTJ/z8P/wlp5++ZHk6Y+BgoAx7Zc0ASSUUR6qijFAGz4DUqzP0DhEC0geEc+AConXJqxQCbZLS8j55fCHKvjybjsdCyg6MO9WU5ahhUBpPKspIvNyKEHUS5lJiY2p6tNFngy4rBSDKAisVG6lYSo3MnkMrJDYrhYB4rUL4IhPy9RAyon+uflPHN1Yp7I5Ian9P1Q3dQgzbSrVsxbkYma/XqVICePDoDR7dvct/9Ud/xKN793j/rXcopaRdr/nv/9V/x954zHfeeZthXRJD4PGnn7FcLlkslty6e496OKQYjRBFAUWJH1SoumJ89y7VdEo5naDLCqEUQhs2TUPbtgTvWC2XPHv2lJ/+3U/5+JOP+Yv/+d9zdnbGy5PjhDwKaJV4hiUJroOQSi2zjYWJBqM0k4N93nn3Hb7/w9/hT//sz3j46E3eeudddFUQIxmwLYmlJNcEuTEXhEAaRVTZSvIBFnNYb2C1Zv3LD7n8xQd8/u//gubZc/RsxhRBJRUjpfHWEYDpaMxawHzT8OH/59/xi//0l3z88cfcee89Hv7ge9z51nuU0wmYIVpIlJS0PgkTpdW2l6RQEDxBVZRVsjOH4xRQ8CGA0nipEKJACIUWCWQnSDCyRAmJyuHCFKbaSutURrzrHezmHOI1SdLnIwQ720LuXtvmX15ZiHnbmHIlfaKii6r3eYS074RHGPDB0jTLDAgYiXGDEArbzPj041/w6ccf8PLFE6QI3D/aZ29wyLiqKIngHJefPeYvf/4hTz95zMd/+QntbE24WjMKkYNYcKseUQlBDVQeCi+YzJNyNyGifSorjTF1CqsARgik1hhd9NdqQyA4T+OTYI9SEqQiCkkQmpCTvlZKghR4KXsPwcrk87RR4EX3nQKPwCKxIeAAF3O+Tgja6AkCgtF4rfFGMRcRrQr2lGSkFa3WtEpilaBB4EROQMewc0/jtRsV405o8Nr7X9VT+PUNUv2jUtgd2YVMRl/fKM+uV+hC10IlqKdT9u/d463vfY83HjzgzbffIbaO1XxGcfs2ejhEHh5CVSS44LZFtZa6tdx/400G4zHVcIgsK2RVwaBCVSWDowP0YICuBz3DGVJj2xZrLYXWtG3L3t4UpGQwGnF8dko9qFk3G9bLFW3b9tSCIgRkhgbulIICKiGojOH+4QFv3r3Lt958k7fuP+DOnduMBgOiTPFcQVdRk19vuMkd6B/Bg7Ow2tBcXNBeXnHx8UdcfvYZ7vwcvV5ROMdQqmRhxuS0BATKpPluY+BiuaRpGp5+/DFOSeR4wPT+HYphncpTxe4ZdUZzF2hJ2krK0DcfKh22nAt09ziVIwqhkDL3RHRQFtvl0FvyOxEOrgv73Q9fFfW7QaMuZNSlkWM++W24aFf77Ow6R7vjNceiUw4BqUBpENITnSN4R9MsWC0t84unnJ084/L8JcGtKYxmVBUMC8NAKpqrK5rFkovnL3n2wac8+/gx86fHiCYwcIKJKRgrw6EqKBCUwVOSFEGdK4l0iKgQkDGFjnJhXFovqai/rwjyOfnrpCQqTZQaJ5MycELjkXghaKXCC4FTCifACUErBC6KFPKJCo9MPNdZUdgocTHiRCoU8IBFpia2kNjgQpCsCBgPSwQbsrIRAp+9hdCvpd37/Hphv60u2ykA+BVjWz321bb///f4R6WQRwIpSz/dnQ65Nj6S348iww+nuPPe3Xs8+u77fPf3f5/Dw0PUeEwzX9BKMPfvc9Ws+Y/PnlIYRWEMBwf77E2mHB4ecfett6mHw7TWigLKimzWE7TExyQgQ0x12IWgrxyy1iKl5M6dewwnU97//vfZ29/nww9/QVn+Gz768EPOjk8oEDnh6KhRGASKdNMNkklZsjcZ809/8H3e/8EP+L3f/RF3phMqJVG+JcaERS+jhyhyg1xM1qza4U52LiuDBXG9IZ5fcvyzv+Pk44/58N/8Of7yimq+YBIilTGUPiCdA9tgjCYoRbNcIrSmrAoOBgMWRD76xc95Mbvg0/Njjt59i3IyphoOuhuGFPnBtz5XVCULO02jyefXvyRLtrvfUqf5RNJrz666pxMGuz/pWztCPt4Q/19hxA56YSsUtrmDPvWwTU10DGg7USQpO3PF4b0jBEtdCWI0DGoB0bFxK05ffs6Jb/jZX/8FKlqMiHz/3bcYVBUDIXFXC65mJ3z+s19w/uKYT/72A5Yna5pZyy0NA6U5MCWHZshIlexJnfoLgkMTUAQK73IPSew7OBIybJrHJIwDLV1FkMQrnar5hAZT5JJshY2CVZS0QmERbKTGCcFGSDYx0MbAyqUmzyYK2pASxG2MKaQktpVGQane63cx5/KaCNojDDRYBtJwy8I0Sm4LhZUaLzReqAR3w/a+fNPGN1YpbAHFtrHZjj8A2FEQ9N68ECBNATHQes9steT86oLTq0tMXTHam6AHFbWY8vb73+H05ISXz55RjUZUwyF3336byXSPvYODFDbSJsNUKqKSiVshkFZzVgCpKzNZhEhQWiaLMyalVRSGsRjxzjvvoKTk8uyc2ck5V8dnSO8zm1RiiyuAgkgpU+nsfmUYaUE4fcnVJyWfGYG2DZOjW4z9PWRdI+tBsrJFVxVCsm77eECLsBZsy/r0mNXJKS9/9nOe/u3fcv7JJ4izUwatZRwDA2ICDMzx9ag1QesUJhASqyKb4Fh5z0ZKhvtT9u7e4vabj6hGQ1RhdrgWYNNscD7gcwhJZdhyIQRKa3oUqxyf72Lyr0SBO2lMJLXQ7tj3Ofl4Pc+YcwP06VH6nMFOXuH6b91fsTf5t5DneU95bpMpkmxWyPwHyc0j+tR3EEJ6JTqkcChajLQ0q3NOXryA5oxSCw4nAyaDikldoQL4+ZpnL06ZPz9h8fKMk48+Z3M1R5yu2bcCY2oOpaQWkj1VMI2K2kcG1qJjKimVISSo+ODpYad3UPk6bywRQUEQCi9TxZBTBi8UrTJYobAolghaIVlEySZKWiSLoGiEYIXsO/k3QvYKxYusmqTJVn4qG/fkQgQRCSJmiPeE8SSVQBmJjQ2iHGDLIb4cEMqaoE1WJh2b4Y62/pLxjyipv2XjWgSgSxr1+UDR/3QPfwSU1gkLyDnm6xVnl5ecXJxRjwbcDrdRpaHUkgdvv0VQkuenp8i6xkzGTO/eYbS3z2BvH+FTAkwY05+LtY7QWV0qJXG3EBQ5qaokkoRH5J1Ha4XWiof376MQXJ2e89P/719iokQFiwYqYACURAZEaqWYFIbDUlMbibg8Y6HgmbPsDQfQrKmqArO3l67XSaKUyML0teCpgiSCbYltQ2w2LE+OOf/8MR//1X/i2d/+lNnnn/OWKaikYiwklUgLLgBRCqJSOJVixk5KrIAGTxMFXkkmh/sc3L3DnUcPqEYDRKFB5cqUrBRa54hCYGKBwSCUTnwSKsWEQ7hp820byoidisjty7m8VcibuQKxI9138gmCG4qh28fOd19RENtEcdzdpvMeROZJpoMtiT07a4ratT2xDT0VvUf4NZIWu55xdf6csD5lPKj41pv3OJpOOZhMOHv8kqvLJS8+eszZp8+4fPKS5dNjxMZSt5F9kzqP91DUSCZCM4yCMsQeikIH33sHBN+HQjo1mumpCQicUCksJDVearxKysAJRaML1kGwCTAnlYfOomKdQzozNE0ULEjKwSJphCZIjZcFKEOUCqHLhJMlE1yMz4ohiqxaO0wz7xJemRa4oFFFjSsGeFMTTUVQhiAV1xbHrxi/jQoBvtFK4bqL2MFDS5mSe8FnUDnvc7ds+kyXRWoUioHHz5+xWK/Qdck7b7/FP/knv8e33nuXw/0DRod73NcSNaj55Sef8Mtnz/n/sfefTZJlZ34n+DviKtehRcrKUkChoMFpTcz0kDYfYW2/375aYZyd3eVSDdkahGgUCoWSqUXoCNd+5RH74lyPzCyg2b00ri27qk9ZVHpEeHh4XHEe9RfPLq/o9fuMRiNu3jyk1+3SSTOiKCaKI148O6IsS7yAwWDAYDhkMBoSRTFaRxhrQsYjZbCDVArngp3kaNDHNw1v373LweYmT9MMvzIk3tMDBsLTEZKdrMOok7LT6zPqd4ij4IRWj68YX1zwyWzGcG+Xb/7BjM1bt9m4dRu5sYmIYqhD5ucBYcFbQ7NacPH8KVcvXvDRf/z3zI+PWd5/wMhaDpOYbm3IhCeL4xa66mjaEt/GMZO6pjCeVZZgkhiTJezeOKSzvcXtH3yfwc0bjO7cprO1DVEMUmGsozE1Z2cXrIqcyhh6vR69Xo+DvT2kUjSmlcJw/qX7mFTrRvd1EuAd7Qbsr1Fa6+vj5Zxind3/9lX0uxPJL28Wr2ed6/aQfD2+vHx228py3gCBbxCGngZ8kLI2psDbGmdrTl48YzadcPTkIb6pub27we39PQadDrv9HpPTcz796As+/+XHTM6uOPnsGVHZENeWPZ3Rz3rsjXroskY3DQMniD10jCW2LgyTWfsOBMVV5x3Gtu24NYRUBnMoJ1VgEKsYKxWFiKkQFF6wcJLKwbKWlF5QIplZQelh4SS1Cj4iVdLFqIg6iqlFG0hE1HJxNMa3EjQitKW8lHilwkFtUViOABfHOYS3aBmEFK1ZoJOEOu5S64RaaioHtXt9o//t6vCrGQS+vL7GQeFLa71JvMom9a9+O3ziXEAkKK1J0oSs2yFJU4RUrIqSi6sryqoC51nlOauqRChNlKQIKTHWsSoKLscTVnlBEkeYpgk6PIsVAsFgNMQ5/5rtZXBYa99Lm+0KSbtZeXSkSOKIfiejE0WBbY0gBQZCsKEkPaXYSxIGUcx2pOn5gBqx1lFZi7IOMxmz8pbzx48CWkcqhlFC1AUi2co9CHxjqIucy6MTXjx8zNnjR1y8OKIZj9GNJVWSbqyITXDGQki8CoS9yoUecGktZRLj4pidu3fwWYLJUvo3DulubbL7xht0trfpbGwh0yy021pG8zVj20GRFyip0EpjXdisXG1omhpjTAjsQqCjiCjSKK3RkWZN/8N/aUD8d+zp6xW2h/Uw+LWy47d/6BUM68uZZQtVuP61r4eW69mC8C2p0CDwSBG0iZxvqMsl+XLOYnbF1dkpxWpF5B3dNCGNegzilMh6Lp+dcPb0BadPnnH+8Ih8skAucjIv6aLYUBFdoek6h3YO7TyZc8HgxgWdIu3bEdJ6KN4mVGsYZ0D6KLxUNDLCqDA8rlRMIxRLInIvyBHMvaDyggWCGkUtFAsVWkYrJI2KaVREHXWwSlPpmEbEWKFppL5mHlvfMpUFATgg28AgxUtxO98GfBEkVnyri+dEkLywUoUZQgt/fbUYXN93rw6Svy7r6xsUXrZwAbDG4szr+kCv+hCsdWaCM5UmTmLuvvEGb731Jn/0J39Mp9NBKcVn9++T5zl4T103FHnJ3btvsLO3T5Z1qOqavFjx7MURdR0sIh89fMjnn33Ot775LW4c3uAP//AP6fV6DAbDIIntoKqaMPRV8jUi2hrmobQkiTX9JKGvNQMl0ULQEYItJTjMMkZRxK1el0wput6jVvnaKBiVJMgs42yxoFgs+Gg8YevuG+w9P+H7UUq0uw8DhYii4Ma2XDI/O+MX/+kvefjRhxw/+IJOsWQgJHe2d+k7S2YNygaBs0ZKSFOsVCyqilndcJbnDO/cYuPmDf6n/+P/Adnt0kQxathDZinRaBPSFLIM0izc+CbIgccqoj8YYb3g7OISQSCfVWWDVY7lYsF8NmO1XDGfLhBCkKYpGxsjev0u2zs7RJEM+k1ehvacWwv3/x2N5OsuzxqW+np76B+cSb5aOFzHEn8dQAThLTjZylfYGq0EUSSxjcOYiun4hCcPH/DJrz8kU4pOmnDv1i02en02egPy8ZSrkwv+4v/577l4esT4xSl6BR2puDPI2EwyRnHCwIFuDEyu6LZJROKDw5lyLoAThESi2402GDo5EVp8hhYiGqVYHVGomEoqSqGZoSm85MqGecHCSRZeUiHIhcbpGKdjapVglcJGMY2KMTKiQmOQlCisjHEiAqVxuGCr2lZ1QrUtHylC+8i/OjMSIIJ+FtZiCPMaJ2JiEVGjMVJh17hzIUAppA+zEu/+cfMN/mvX1zcofCmxu24fidedx9bwwHWG7Jyj0+3w1ltv8aMf/ZD33nuP73//+6RpihCCoiio64rlcolAoJRmOBghpebs7AxjclarFbt7u2RZyqDXZXt7h9Fog7qsmS8X3L//kDyvaGrL7v4eUZKgWx18KQSspS3cS/co5RzaNERNhSpWqHzFUMAo0tzoZBykKUOt2dCaBEgDNKR1QwMhDVIbEhuaKXlRcnl0zDgvWHrB1o2bvPvPfh90hAX+9mc/4+jZU371s5+SX55TT6fsRRIbRVgEy6qmqGo6SJQQlFJSNoaKhpVSiK1N9re2ufeD77N95zbRrduILEW0wYkowsdJwKlbj1kVITs1NkhjaI2pG8pVzunxMdYEVvf56Tlaa5qmDnaiUtHvDehkGaPRBr1elyxL0SoKBLvX0sP1xyuw1Fcvklf6Cb+LvOrXc5bffbmtf0v7um0oEOGxW4MJRMhZZatTJIXHSY8zFcu8ZDkbs5xP+fjDv6XOc7b6fW5ub9NLUhIvmD8/4+jqUx7/5gGzszHn918gioIto7i5vUVHafre0vGCrLbETUNkHalSdAQkCGQTOPxroxrjXdupl4FHEGmclDQ6okZQesFKaGrRzgWMZAlMfZBnGaMppCbXmlLFNEJT6ihk60LRqAgnJVbHOBVhpQ7VAaGCsL4dKq8TNqWw3raqvi89zt2aHNh6MoPAWQ8OhBNhdNRyPBof/i7jAv/ItRUIzrViiP718/U7Tu0/2XF+xdZvI1DENesSvtRbXH+030uShL29PW7fvsO9e/e4ffs2SZJc/5y1jvH4iiiK6Ha7SBFRVzUXFxdYa6mqiuFoxMbmBjubG8Gs3jseP3xMUwcJ5DTN6GRdNrd3iJLW+Uy0KA8ffo+wHrwLEgLWIJsGVVboqiKqawaRZjOO2MkytpOEvlL0CG2B2K0tO6Fpvai9eYlW8nXDcjxhOV8wt4KtyzFbN+7ilaKyll/8/Gc8ffKEz3/zaxJjSL1j1O9RS0XtPVVjEVUDUYSSAikkc9tQeI/LMnpbW+x8411uf/977Ny+Dds7kMToNIE4aVmtAusdjXXUxgT3OmPQ1hFFjrqsKPOC+XRGXpTUVU1VVGgd4Kb9fp9ut8fudka/32dzc5M0TYlayYz1iNTj23MrXw8KHloSxvVA+Rpjjv/tgYLndyttvhJZvtSoCl9rf0d4gXVgCK0i0dpEmqpkOZ8wvjhjNr7k+NkzeknC7mjE/sYWXR0xP7lkfnTGk88f8JuffMjqak5aCIZaMYojbvcGdLVGrHK0MWhjiKqaGE9XKFIJcfu3rakSrv3c+KBN5IUOSB2tqXVMhaRAMDdBLHLqJCsvmPt1UJBMtaaSEZVKqKMUqyJqHQfCmQ9cBCckXkW4NXdBaBwS4yXWS6wP14IQBHUA59vAEMo34dU1TFrwMti3ii4oRDBxag+z9cHoyuJbgn/LZv5yC/nVTeC/0frvPY58bYPCy15huPitX/szB9THWlZ6vQk4GzbfTpbhjOXh/Qfs7+7hrGM02GA4HNLr9dCRRknFaLjRSj7o9iJz1HWJc8Fn2VrLfD7j008/pqlrTN3wp3/6p6RJymK+QgqF8cEr2tqX5CvhHXESXVsRUhloaphOMGdnrB48YKsseLuTcnc4YBTF7KUpmbVExiBr04riaXTcRcgA+Su8o2gsS2cppIBuFpA8SvH06IiHZ+d8+OQZ09WKyXLJ8/MTiiKnWCzIgIwgg3GVpNQGhnFMp5+Rt7BKD6xkYJW++8/+GTe/8S7v/fM/IR6N2vZQCkrhtb4eKMtIoa1HtOqazhiK5YrJ5RWTyYTnL55RlSWHOztsbG4x3Nxkb3+fJM1I0xQpFVIq0igK50K3aHqx9j5okwMvvwQ7eHUHENeBYc1G/hKO6Hq91pd+2ZV+7TnBjXPddgoto7DZroNC4B6YuqTO55iqpF7NmY4vOXrxlLOjZ5i64vvvvscwzRilGS8+u8+Do1M++ov/zPJ8xup8wYZ33FQpB1tdNtOMUZIhVyXS5kTWEeHReLz1RHhSLZAmKK06G26KsDlLLKEqcCrCximl0lRSMvUhICyRnDvL0sJcBwBBYQABAABJREFUagqhyYUmjzJqFVOkfYyOaXRCrUJbqEYFopn3OLWWDgjSL85bGlcGEpkPVEuPbAnentqFwCmlR6sgqS6kAh/Oq3UhYHsnEa0lW9CNCmdNtPIsnragkOIaTCLWZKH/mrbg/1frd6UH/32sr21QuF5f2gP+ztPvwwXprKMqKyaTCSfHx/S6XZ7efcrW1hY72zskaYLWGtmqlEolwXvKqqKpg+Z9UeScnZ0ipOT8/Ixup8NoMGQ0GtHJumRpt/WLFtfy1usLOqT2TWg/1DUuL3B5zuLFMbOTY66ePkVVFaM4ZhTHdJVGt+qv3vu2zJaBAdqWyY1SwdMBWFpLbjwLAbmSrKTisqgpgWa+YF6WzIuSabHAGIP1jlbmnkXdILzgQuWYjqeKoZOEGYTUimzQJxn02X/nbTbv3iHd3sInSRsIdAgKKrBb15h/Yy1N3ZDnK+qyZD6ekOc5Rb4iSxKyJKHb6zIYjugPR4xGI6IkIU0z1gFA0W7Rr7QAwssHvsVLb26HdGvbzJdb+rqierWFELbw14OD9+KV68e/knmwfge85MkHy9ZgoRqMfdotDWdrmnLFajahWC1Yja/Il3NskdOLYoRSxNZTTuccr8548dkDJsdnLE8u8MuGbuNCZag1O1FMD0m3scG/wHoi3/L1PCBka3fqsLZVW20zZ6SiEQojJLWKsTqiURFLBIUTXDhHKSQrCVOpyIVgLiMqoShkRBmF51exDsNnpahlSzj0PiQ83uOkDdWRcIHw1h47Qdi8Q7i91ptpIbshBIt2viNauXN8qEq9l61EiWxvG4eQwYhJSI9YGz8TWlDXScHvmvcI/984Lvz3GxDgaxwU/q720asGJteEtvUN7jxlUVDkObPplE/TT5lNZ6RJyuHhIW+99RbdbpcoiqiqKvgStDwEYwyrfMV8Puf8/Iynz5+2VYnnG+++y61btxgMBnQ6XXb39q83omD519pjupbMVlRBwa0sMVcT6smUx7/4JVfPn/H0ww+QizkH3Q5baYa2DlfVmPVuFifUzlMbR2UrrBCQdMPwD8F53TBvas6mJStgBYyNJbeOWWMwSIwQGEVAdSgVvCGcZ1JXlLWhKhs2yi79LONgf5c0y+gM+rzxve9wePcO3/jhD0hGQxj0w2BQCGQSqgN3nS16TF1TFSXlKuf5s6fMplPOjo/ppin9bpc7d+4wGAzY2d0KyBMhoRXqW4vDXWOD1nvx9Qm/jjt42iqxRSmh20oRXiv11/aLvPKa60rzy7XDq3aNrz2fYDeJt1hT4bA44VBatGiyClfnFIsx50dPmV1ecvb8GYmSjLod3rh5h0Rrzp8959n9h3z2yw+ZPT7CLnJ6NWxGGTuDIQdxh66UDDyIskJUK3pJihYKgcM7G9oqOsI7R1NXrRlTqIgCvDOmUppGSsooo5ERpYy4NIaFtZzUhlIpykSximJqqVipKEA8VUytY4zS1JHESGiEoyGwm40PbGcn/Et3a986XQuQUree5gp5reDFtVSIcaYNYB5vwa9NcoRAkCCFQsgI2pTAehOkT6RD0LQ+1IZg2NS0ATrIoPyW6OG6jfg1WV/boPDaastSR1vK84qwVXtPSyFC79+8FMnqd/vsbu9y59YdDg4OONw/vPYwED4wonUULm7nHJtbG+hYE2cJZVlS1RWXlxd4D8vlCtsKvDnn2t42QKt+2hgiH+QFMDXNcsXqxRHnDx8zeXHEsw8/pJpOkKuCnlCIJEW0cwOjFBZPCUytoXGe0nnmdU3tHGVeUXlLbg3juiS3holz1z4OS+ep8YQtzGO9CMQhIcC2BigiaNfDWgsn9GpHacLoYJ9vfv+73H33bbYO94n3t4PWUxxklB3QWNOCPyT5akVelJxfnLNarljMF8RakXUS3n73LTppSi/L2NzYIEmSgMhqTY5U1OoXtTex9y+rBCHWs6J1qybAPoX0KAFK6vaQu9aqtJ0mX8NguZ7nXIMQxCsaTNepZVuFyOBg56wNm5sIFqPO1eAaoEG0rGRT1FhTcfbiKav5jOnlGSZf4ZuGm1sjYqnIlGL89DnL8ZTPf/khi/Mxq5ML+rklIWYrjRhFKVtxFtzOjCGqA+NcGhOaMDKICTofRse0ME6vItAxIALHQEoqqSlkUBOde0lhHQtjGBvD0jkuURgVYaKEOtI0SlJIaHCU1JQ0GCeo6hwr5DVs1RMg1kIGqfLXOOZhcINUYTP3wWm1RfGGqts415rrhO+Jdb3QalcJlSKERooERFsnaocUHiEs3ixwNgZKpKhRIsxthDfINmitz+L1I//651/l9U9B4dUKf71+x7lfu5WFRCUEhiiKSNOMXrdHr9sjyzKcDXMJJdW1heP6Z6MoIutkDHGkVUpZlizmC7yD1SoPmPprBu6r/QqHt03bG/XYsqSaz5keHXP26BHnj59w8eQpoq7IvCUSEh3FeGNDz5bANLXes2gMlfMUzjNtagpjWVlH5Sy5tSxsTeU9S4KpT0Uw+QniYiGTswTIpBfr7ms4iJZgcNIATmtIE6LhkP7eHjffeZudu3cY7myiBz2EUteBRQDOWoSz4ATL1ZL5YsH5+Rl5vmK1ytnf3SXtpOxsbr5sG2VZIKRdO9EF/SMhaNsL4nrw+7KxEzb0lyLJsFZCVYRNx9lXygr/ivVKuzF49+owUnwpeLySUHh/TYAU4Re1+5rFeYN3Dd4ZjCmpigVVseLi6Dn5YsZifEksIZGSfn+Ich5ZGyZHJ1y8OOH5J1/gliVyVdOLEvoyYidKGeiYodRkxgTl0qZGmiBNIYwJHhiR5iWotvURULpVLQ0bfYMI7UQRWMZjB7n3zKxlYj0rYKZku9kLGgVWeSoFBocV4bpz6z6+EMECVOmA+sKHbD0QIK5VBIQMMiah6xrOhbPhmDtaLSVjQ1WIuB4kW+dba00RrlavgYZ181AKGRBdwuF8gfcWIWqEMMg2KOAd4rdu/q9HIHh1/VNQ+B0rlKmv3PgqeABrpciyBGsMqzxnPJ3y9PkzPvnsUy4nYybzGVEUoZUizbLwWt6RlwV1XTKejKnrmrKuSdMEKQQb/QFVXvDowUP2d/bQSjLod9uf9dhWdCwChKnxZcWTD37J5dNnPPj5L1idnFFOpkRVTQTEWoOUGOdYlRVlVbPIVyydpXSWcV1TOk/uubb5LH0QS1hv6JaXLm+m/Xi1g4sA0xikCMJ6ou3zSgSxVPTSjO98533e+ca7/P6P/4jN3R22bxwQbQ5RnbRlnSrQOgQ674mVZrlaMT475ZPPPmM2nxOnCVvbO3zjvffoZClJFNHLOug22xWvnKNwosC4NURR8WVDTYfnWmTulc1cXctZBymR4EfwsjUE4T1aE9jjzjlUFKGj6DpQrKUTvfdIFXr0dVWhpSDWEqkIR9Y2SGGQyrBcjlnMphw9f8bRk4dMry7YzDoMuhnvHh4imgZbVpx+8ZCLo2Oefnaf+fEFZlnQqz19GbE56LEbp3SlZugVVDXMFgFF5l3wRCY4telXHOSCQEaQj3BSBCixjrEqaBHl1nFR1Uxsw9J5ZkKGWYGOKbOERilyYGUaZssxTWFxClQ3pdPv0RuN2N8YkXQyesMw54njmG6vRxxFLRBAhHjeVtMqDoAA0bbuQCC9wJrAD5rNZtRNQ17XlFVN3Rjqqma5WnFxFcigVdUwX00oyob5ogShkUrT7QwCz0d4Ikpi2SHRDbEyaGXRwtI2LmnVj171zftarX8KCsCrQ59XPYzXCKS1hoq1gAhGM1JJirJgNptxeXVFmmU474mThDRNSNM0BBfnUVrTmAQlJVVVU5Ql4NFasbWxyXQ6ZTwe46zBNgbs2kU2bGLCWkRjWF1dsrq85MlvPmZyfMz84gJfFGgfPG89ntJ7irJqSXIFRdOwqGsWzlI6x8xaKh/aQutgUPK6GbpD0Ii1DeIrN4d4ZQjrDdKDEgG9EgMZgkwqupEilYJEeLJIkUaKOFIt0bTNqFuehGiPUVEWTC4vefb8OU1ZkeiI7a1tNjY3GIyGJJFGqYAyce3PBIvT1v2tPWLOrbPSNhy8NuxtT/UrxdirhINQQYiXRQG8kvW/vD6kUi102V8rxwq5Hlq2ukA4lLCtvIZHOAPeYW1FXa2o65zj509YzCacHx/jq4phmrK/uUmiJL6omJyes5xMefbpA+bnl8xfXCJXJV3j2IkyekIxlIq+g9R7Um8DtNgFZJEWgkirlrcdjJjWCU8jguNYFUCv1MhWsE5xWdUsjeHSNsy8YyVgIT0ljpU11KLBigg1HDCIuwyTmHiQEqUx6aBL2u3QHfTpDPrhfuh0UC2TPI7iFoChrgc9AQ0kUDp6/T5EoIUCF5KOYSfCOEtlmmBp24IQirJiNt+mKCvq2jBbrFguS8aTJWVtsMZhLOH+Mg3G5PgGfFOArZDOIETbXmqFs8VrF8rXa31tg4JAcO2I+EqfONz0EqkDYkao0H/11mA8+DoMkLUOma3znhfHR3T7vZDZ7mwzGAyuUUPer7crwDvKvGS5WDKZXBHFEb/3z/4H7t//go8++jXeOkxd4+oa1bZmpDVBmnqVc3n/Ic8//ZSf/7v/QDWf0wEGUUyaxOA8tbFMq4qT2ZzZYkHpDJW1LE3DgrD5VxIaGQJCI8LAr26v/TDOCyW4F2BFIPe49ojJ1oBGANaJ4MvgHSkBkjpE0ZGKjUgRNyVuMcMtZ/hBB4kFY/CNBB0FIrYNJb+3lunFJU8fPeaDDz/kjTfeYG9nh7fffoekkxF3s+tWmq2bQFSzjkRH1y0JfPCiNi6gGzXqGkFyfc5F2/N69Rvt8Pd6jvSyS3Q96F9XQar1vl5r6+Ad1tSAQ0cSf61NFMaiiYZraFZV4q3Bm4rZxSnjqws+/ODnLGdzyvmCb775Frdv3uPe4U2WkwkPP/6Ez3/2AS8ePeX5J0+QtSWzcLOfspFm3MqGJNaT1oastkTOkrTHFAKWX0lI4mvmAXlRYZwP8hBaYZUiJ/gT5A68VFiteTSdMDeGKY5cCUolWGlJbgzTsqJuBMLF3NveY+/wgLtvvcmtN24z3Bgy2BwGcmEcPoQEY5oww/COqmowjSEvC0xjMI3F+vXQIDj4BU/xcLy10kRtlT7a20EqgRUWFQUoqrPrCVFoJRnrmM+WTKcLTs/HnF+Mmc+XPH3+gsViyXxeslzNsLKiWU1x1RLhSpS34RptdbDCgPolP+XrtL6WQeEaEfI7WCTOBRSKMeYajaFU0NWRUlJWJUJKojj4I2xsbHJ4eMjW9jZxmhCnKXGaXLOjlZTXfQjT1DS1QQCx0vjG8vknn/LkyWOOnz1HOst4YwNVlgw7Gf0spZpOWV6NefjBhzz+5BOOHz7EzRekHjpxhPeesmmYLhcsq4qLZc44X7Gqa0of2MlGSspIUQvB3NRBk562LSTabBsRBo7rjNs7rBetP27INANs0yIQxHg00AUGQtKXkoNOl16SsNXL0IsZs8cP+bN/dcn2jUO++cMfsHv3Dfrb2yQ7u0HlUmnKqmKxWvGTv/prhFK889Zb3HnjDYajIWkSI2Twj1CRehnIpQjSFK3Msb2e/QuiVl32JdL8FQZCu+m/dqf7lr16jRTyGGdbQIFHSXVdNXoX+s62bl2DfTDyQaznFA4lLbi24eYdtqowdcVifEW+WjG+OGe5mFKslmxnKYfdLv27bxJ5qC4n/Os//wmT03OOHzxmdT6hWeXc0JpekrIZpYykIEPQWRYkXpB6QWoJnBVjUUKhVXSNLqpdaKk1zlIicVrikjSY10jFSghya7moShaznBzHaVVQSihije9mkCZs7u9w0OvT29xic2+P7nDIzsEBOo5QUYRQkqIumTyfUlUleVGwWCwoqoLJZBx0wFY5i9WKpjFUtcUYj2lCBQOgtAizA+fbMZFAt8MrgaDbjdCxJErDbC5OIiKd0Ov32d3dpdvtkSQJSZyhdcK9m7vcOdzDGMf4m+/QNEEP6/LyHLzj1q0b7GyOAqPcB5G/0Ap8ya159d+vy/paBoXfWq8Eh2so6isf19VD206SShGnKRubm+zt7bOzt8tgOAQhWvXI4D+r5HpIGQZlxti2L22RCKx1TC6vKJYrpPfUqxW5lMwuLhCdcDMWl5dMTs548tFvOHrwgIsXLxilKZGOUEJibYMxhkmRMy9KzpdL5k1D4SwlBJ0aKTFSYpSgcpLGB31603Ih9CtM3vWRcG7titYel/WxaT/TBPZrAnSlpK80m2lCP0nYiCNUU2FnFSeTM6r5jGG3g/ZAWYGKg9tcnFCsVizmM8YXF2xsb7O3t8vW1gbdXg+hWltM78DL1oZAEOLsmoQmruUPQFyfo1fe9ctzez0SX8eGNki49cA5vJZzNsCFfUAL+bbA8K16jvM2YNu9Rei1lLlBtCN9Z9by1g11vqTKV0wuL8iXS67OzqiLHNvUbPb6dOKEUdZhfjlmfjXhi199xPT0gunzE+JGkHjBZj9mGMfspBld64itRzclsRckQhFZgfQerA8ubEisaGG9HmovggihVEGdVgeYaS0lSzxL5xjbhqltWDnDQnlspPH9lGjUJ+r12Lx9QH9zk93Dm+weHtIbDEm73dDjzwtmiwV5WTKeXLFcLpnPZ1xdXrHKV1xcnrNYLpnPF8yXS+rGBl8mC621N4LgHrcGdYXWYAtoCKMekhR0rEg7Md1elySJSZKMjdGIW7duMRwO6XQ6bIw2GfSHbG7u0sm6yEyTJmkYNivJ5WiAMQ29fpdOll2DDtZ1wfqzr+v6WgaFL+PHRYtNFh6UkGiliFrhNyEExhiMMay1cfrdLm/cu8ef/Mmf8I1vfIN79+5hjWU2HZMv50FHSUbX8wnnTMi8qya8vpTBx1YIumnK99//Fv/zH/8h0jaUyyUPfvMbnpyfs7y8wExm1LM5V0+eEiO4M9gI78VBWdVMVwvmRc7RbM6iMVzVNSvCANmLYIpeWYutPV5JZKcb/j6laZomEJbqJigz+2BKgm+p/791X7Q6S7QeDUKwG2n2k5SdJOHuoE8/ihjFGrzFe0ejEprJjEf/8c84+tVvSEYb3PveD+nvbDM8POTp1SWrpuH3f/gD+lsjNvZ3EbHCSYOUoJQmiTS2dX+TOkIQoIfWBJkD02bISsqwwbfZu2g3/fVt7rxteSe08MWXwcO1cwDrDbWrkSIMQZ1oW4dVE1p6EuJEv4IgqrHO0FQ5pqmxTUOxmlPmOZenp4zPz5ldXREpSRbH7Aw36GYbJFIzv7hi/PyUn/7mM06fPmd+MSbKDamXvNndYFPFdISiZxpS4+ktagZKEwuFlnHYVWtDrGOU0sgoXY9qQMUgoKI9B5EP1aKElRTMrWHZ1JxVK1a2YdJUyH6G7PbZ3NmguzFk9+5tdm7fZLC9RW9/Hy8klYWT80uePjjh8eNnLJc589mCo+MTZvMF4/FVaAkZR2NcSC6sQyqP0pAX7WxOEkxvpERHoUVbG8Ma+rtOQqwDrcJx9xYoHcu6ZLJowr1lHVIK4r/9GEGQSO91M7rdHqPhBhsbW3S7fba39oPj4d4BUkuiSJPoFC3igFQSGiF1y6x+1Zv567e+lkEBXhkgtut1kpFvxbZeqRTaTcQB1hiWiwXHR0ckcUwURURK4awNaqlSvZwltNmtEhKVxERSEkvdCtkRmMZNgysrquWC1WzK4vyc6fExs7MzzGSKL6sgYSzDgLM2hsZaSmcY5yvmZcGkacitpRBQi2BYY9o+sdA6DGs7HYY722HIJyVX4yvy5YrxxRW+ldR4WQ20bz7kweGGw6N86LYmQCZCldCVkp6Q9GXQVsoaE8SIhaNuh5rSS+xiQdVYjr/4nOT8jPTinJmzkCa8/d336PQyokjglQdpw4YhHUq84mPcKli2USxYQYprM7aXcFMvwvtep52hpmh1htrqg8CalQEC1bYNXNsGCkJ+Sgb2rFa2HUR6mrrAmIq6LimLBaapKfIFpq4xdYWpSkxVU81nRN4x6nZIlEILCWXNfDXHrEpOnzxjdjnh/NFz6umcKK/ZUhkdoRigGAhF5gU9L4m9J7OOyFo0lij4W4bax4dY6EXoihsRZK2tCG5ltYRawRxH4TwT07CwhpU3LDSYNCHrDBjs79DbGjE82CPpd+lubxF1u9RC8PToiFVRcTVbcHZxyXS24OTFGUVRka8qrqZTiqJktcrbYTftvCZUA9KFYCWEQCmu51Qvnb/X86z1xedeXoLth2sfehfaTC+5KJ7SNgGU4T2mMRR5Tb4qmc0WJEnK2ckFw+EGL7aOSNKETifjzbfeQmpNfzi8Jjf6l9vA13Z9pYPCqxv9P/T5ITtx1zr866CwNuAxxlBXFSfHx3jneP7sGbPplK2tLQ73D+hkHeIoIhjCC7R+KVMRR5pIhKAgjAtaPvMwaJwsVyzOz1hNx4yfPWN6fMz05JRmMiESgt3B6BoJtapLVlXFVZEzKQrmdcXEOWoBpZIYqYK/bW1QWpP1+xzcucvW7i53772J1AqP44vPPufs7IzxxVUYpr/i2QBrhne78batF+UhAroCekIwuP6QjISg4yGtKnQ7jy1sg9OKvk6ZFgV5XvJ4PMakKXbQo3Owz+jGAZvDDnEvwUkbNPGVQGuNkg6FwYuArrLO4bzAuSCVTYtQCcgmdx3Uwn7Rsir8Oji/bBO4NcFQqDA7BnywjUcLR6TCoDYECIeXDoHBOcNqMSXPl6yWMyZX5xRFzmI+w1QVpqqC3LQXREhGvT7DrU1ioWiKkqujc04ePuXi2REPfv0J5aLALRs205SNJOZOZxhQXI0haYLJzQBJ5D2Rc4i6QTqHbpE6XqrgLdDOag2ibQ2F4FAhqJSgUnBuapa24bRescSQC4sY9EgHPXbeuMPtt99k7/YNdm/eRESa0jtOxxMuZzP+9tcfcXZxyePnR0xnC/KiIp+XuHUbyL8c1axTiZaCgPEBK+ENpGk43o199dnhPK7nb/6VABBEINsXvAYBqOD1AcRx3FaCAXXlvCfPG4qiYb5YAuchaNaQpBmdbj+0mDY2cB50HAcFAcdLmZL/wszx67C+0kEBXgaG36oMXslS5LXQWXi+lopIB2E7QSh/a1e3QcPhjAXnOTk65ur8ksuzCzqdjNEgiOIlSUKQzQ6vI6Rfd56CXL8D5VzQoikrEgSpEMRVhWwa/HKBrCpUU9PrdAIDVUFeleR1zbP5lGVdc1WVrJynAGYEFFFlA2JeRxFvf+ub7O4f8OZb79DpD1FKc3Z5wXQ+4+LinPOzMxbzRUDzrFVTW0imeAWhs364niMEzX3oINiQEZsyZkNFZI0JbSVjUSIEEiVcMGExBuNDdVQIj3UCJzO2+jG9FD746V/gY0UTC7YPduj0uvQGA9IkI0u7JEkPqSKEjvE+lPhOikAq9mtnMh+sIkV4185bHLbdVARSvfzbwpxC4DFhR8OjJCgsWlp8U9KYhsXsijyfs5iNubo8Jc8XzOdXxJEmSyOyJKjAjhLQaUYkenR1BtZTTHOWV3OePDzi5NkRq+mC8YszmukKuygYlIId2WUw1AwjTVcphmVF7D2pdaQEuG/UWJTzaBdaYUIIXNPCrJQK/AIpKZWgElAKTyGh8p65sSzrhpVrOHcFlfSUXU002mS00efOt95jtLPNjTfeIOr0IIr42/uPuBpPeHp0wvnVlOl8ydH5OcuiZLIsWy9xBwFli2s3fk9IfKQQKCGwTROAGhqiSBMnCd/53vsMRyPSThZ4BnXD1eUV0+mM+188AAJy6q237zHaGHJw45AkjVFaka8KVsuci7Mxz54+Zzye4FzF1vYmb797j+GgS5JojGmw1tIYw9nZBfP5khdPzyjriqqxLJYramMpihJrXGgTh13i2uVO8Ns0tq/L+soHhfX6reAgrv/HqxnLSwlteY2V9t691lZxIlQSpjEU5OSrFUkUcdHpkCZBEC8EBUmkozYohE1XtBPctRREbOx1f36IJBGCvoBMSRIpiLVGSEFlGpZ1xbwsmVQly6Zh2jSULda8AIwQWKXoDjr0ej1u37vLzu4+e4eHWAtV3TCbzbm6vOT09JT5dEZZltfzA09bPotXfIzxrZRAm/0JiDzECBIkHanJWqP3yDo0IaNVLd7bi+BzYJUIcxQ8sVagQKUxm4MOnV5GMR/TKKiUI4odTdmhKRekSZcq69HpDtFxiu70UDJCySiwmdfEs2voaPvHuJD5+5Z9HoROX0pSXBttuoBfDxarFmtqmrrE1CWmrpjPLilWISiML07I8yV5PqXbyYjpoeMesYyIhCISCi0UsfPY2tDMV8xPLrk8veD5/cfkswWr8wlR5YgN9KMOXaXZiiL6SpIJQdpURN6ROkciWuE6Z5AuVB/rd+6cb9naAUVklKRQISDkwrEk8AomvmFlG5auYSoMRkviUZfuwQ6Dgx0O3rnHYGOT/t4uy7JhUZQ8ePqCk7MLHj1+xtVkwXJZMM2X1NZTGH+d5CgXevg6UiQ6QemITicMboVzLOYLmroGZ0nSmMGwz+GNQza3g4R53RiquiFLY6JI8fC+vx7u725vsru3w+27N1uRScVyUTCfLVFWcnl6zqw9r70s49bhIcONHkmiaUwZZmXWXUvNnBxdYmtLY2oaY0iLAmPMy/nil9rHLz/9+vWTvrJB4Vrl8u+oFADWCHx3jU3meuB8rW58vV7KVXjvMcahWlp9VZY0ZUm1zF/+XnwgLikFzoSmhQ1DWi0g9SHrHikFrZWk7g3oJAk7g/BvGkesyoJFWfJifMmkLJlVFadVHUhqQOmDLlENJGnC9u4m/+Jf/ku++d57HB7e4vjohJ/+9Bfcv/+Ay8sriqKgaWqquqSu68DOXUtyAELJdgZCC0EKG5NGEAlBIgSZEPRRwbQnSRkoFdpGLmS3sfNBownHKl9iBDSxonCOSgj6+3sMtrY4+MY73P72+/R2t5lrQ+UNK1txcn7M+dFTpstFaEt4Qbe/Qafb58ade2xsb7O5vUvWG6JUBEK/hKtcY97bzF8AWLyzWNO8lB2JVFAGrWpWyxVlnnN+cszF2SkPH9ynqYIUwmjUpZvFDHspd/e26KSH9DsJSRSRxBHe2OA9vaqZXU2YXlzy8acPmF6MOX7wjMn5gvnlitQ7Mq250+uxOejQ1ymdBmLr6FpL2hgiZ0lNg/aOeF354MN1Fiaz1DZwMRqhcTLCqphSRzRKMI8FS98wd4arqggaVk2NjRUuU5SdIZ3NIe/+8Lvc/eY73Lh3F93rMluu+M+ffsavPvyYLx4+5tGD5+R5TVm6IB/hwKswm+p2NWVZtkN+GI263Djc5pvvvc/u7h4HN25SrFZMx1f84he/4Oz0nJOjc3b29vjWt7/BjZuHRFHE1dUVSgVZ8/e+8Q6bgwG//MnPENqTxpK3795mtDEE01AtKko8kU7oJzH7W1s8yzKmkSbrdjjc2+Pdt99hkc+o6oK6tmSdjI2NDbq9IePxhGdPj8lXFWXZYJpWGbXNdNacoi/vDi//lb/j+1/d9ZULCv/QOcKXIWdr+FsY3b0cYIV+tGQt8RBii7j+WgC4iOshZ9voDvuTpd10QRGG1xGQiIDvTxB0rKWnNKMoYqfXpZdmpEkSdIqKkqvVimVVcpGXFHiqKMK41njGOUQUkcUxNw/22Nze5t47b3FwcIhzjp/+559yfnHJs+dPmc6mlFVwhTPWtIiQlg3s/TUzOKByaN1JgjNbaB+1Wja0CM7WIUwpQawVqVahsvEehUWuhcjUmhjQyjN7z+JqxtJ6xo3laDwl2xzSO9wk7mdkwy6bUcpwqNnudsPfaS1eaRCGyfkL5pNznj99gFBJaDgL1QrOqQDVVZJI61YTCSBATI2p29ZCy0FpW3iunR/ZqsJWNXsbfSI1RCtBt5MQa0kaSVI0qnbU5YraeRbWMR9PKVY5V8cXLMYLFuMF89NzquWK6nxKsqrYMoaNJKIba3a0DsN4a0lNqBgzY4ldkLROPEgvUO6lpIjzIgyRhaLSGqMlNsqoRRCrm+EorOWqMCx9zcLVTG1F6S1LGpI0Id3o8857bzPc3eb2u++QDPrMq4aj5w84Pb/kZx98xLPnJ5yfX7LKK5omzG6CfLUIyBwAY9ESkkxz984tdne3uHPnBmncQWHIF1PAM+h32NvbxmOZTK4Yjnoc7O/ibMMiX3H07BndTpder8co66K8JxLQ6WQMBj22NzbQkebF0fNwP0nBzvYu0jmkd0jviZXivfe+ycHhAc55Li/HzBYznDNsbGzQ7wXHQyWja6kM7z1bW5vs7u6xvb1Jv99DR6r1VXoFvvw7kHf/bZf/Ox7//3995YLCl9dvVQi/I2asdfXFdVBoiU7tx3UAQATE41q4y61bFvK6vbLeANe5h3eOSGm0CPqLCS37V0pSoGs9G1KxkyQcjkZ00hTjYZ7nzJZLTuZz5lXFaV4iOik+STE++EU3jSHrdOj0e3z7u9/l7r03+B9+//c5OT3h9PSM//v/9v9gtVy1Vo+h5RAkhy0OTxSF019VVVCsjAIXAx8E6lz4oetDZnyrgY/ACQ8otIYkUXSiiEwItLMoHyoqaJnhuNbUxGKN5eL0gtXJBbPPHuI6MVGvw7d+7zsc3DrkjXfeYP/WHp1+B53FVKYhryumxZJlWfDs9CmT2ZzxfM6qbEImiyDSCVEU0+n2iOOEXrcb5gcytPustdR1Rb5cUJYF+XKB8KClvK7Kdje32doY8fatQzZHA9IkRuLxxmCrimK+pM5LplczqmVBsVjx4tFzxpdj7v/mM4pZTbloGLQOZj0Lwwj6ERxmKd04YhhpIuNQTYVuQgsmscELWXtB5F6SHdfkvAqPQQUbyyh4E4jeBrn3TBvDaV2wMIaTasnSNSx9Ta4sjXBUwrLVi+ntb/K9H/8Ru4eH9Hd2Ob644OT8gr/8yS949OQ5f/2fP8SGURlxFIKBaqWrA2hCBvObpibWnk4n4fd/731u3LzBvXt3+eKT+0zGU85P5gwGfTY3tzg83EFH8OLFY7a2B9y8ccDx0RFXF5c8un+f7c0tdrd32R9tIRpLLAQb/T57u7vsbm5TlDlHT56hZICQbvWGob9pDMJZkkjzz370Q5JORlXVHB+fcnp+RhRFWCvZ2toPRjso6qqhaQzOwcHhPrdu3eLgcJ/RxpA4iZDtIPv647Vt4/9XXs3/fQWD9frKB4X/4nrl5AdSUtDVX5uuCFpZAyFe+mxcIyBCQAiOTgIZnn1d8kftTRVJifYW7R0drUgIA9rNOKKrNQfdPoOsw6CT4euKVVNhpCLuhcxqr9NlUpSYB/c5mU25WC4wUqI7XW5ubXL77l329vc5OLyBx/Pnf/bn/PrXv+H5ixdMp1PqpqGqa5RuORdNa+xiXTunVPT7fZy1mKYJEhGRZjgaoDxI5ynmc2zdQN2g25pJKxX0hbzD2oZaeAoXHNJk07AOjrVtcG3bbZCmZJkk7SuW1nJVNyyNoclrjj/4iItPP+fTv/prhlsDsm7G1v42cTcj7nWIeh1kFHGYZuzvdHB7h8g4CcFGqdDpciGrDqfBX8MLhWrZsUpcB3tnGmjNh1SLWo3a8WL94pRHnz+grkry2ZymKqnzgtVkRrUqmV/OaHJDkxsoa7wxDHPDllPoTDOKIzpKsRnFdBV0JKS2RtUWXSxI0MQopA2Cb9q1LUcPzrUoKxRGBFP5QggapanjhCpKqITiqnEsrWFqGsbekUvBLEuC7aVMMQlEWcSN2/vce+ct3nznbboHh8yd4JMPP+az+w948OgpH3z4KbP54po7oKQgShPSOGHQG3Lz8BYbG5t0OhmrfMXZ+QlHJ8/wGG7fvoUQnt989Cs++/gB08mMKErY2NygKAuyLGVne5Nhv8eg36M/6DL7eMrlxQVVXuB6DdJ7Eh0x6g/45lvvsLu7ze7ONlQNzSJH1YZ8taSpK0Re4z0URY2oKrZ7PXb7fVZlwf37X3D69DlX0yk7uzu4qsGWdai0GktdeXrdHts7m7zz7psc3rzJ9s4WcRpT1lWbXLzcD1pVla/l+noHhVdW2zBiPUpYl+6vlRa+xTaum09irdL58muvJhyKkDFqH4azPSXIpKQjJMMoph/HbPe6ZHFCGkWUVRnE57Sm0+/R39sj2z9gVNdcSiifP2dxBqWzJJ2Mja1NNjY3GQ43sMayWC548uwZT5485eT0FKlVEA2zDb416nFrcXrh24GyCLwKF9691jFZmrC9vY32Aukcl01D7T2mbsKwGYh0QFbJ1tbQOkdtg/GJ8rbNdkOARQTv61RpEqVRUhMZi/eCCEHtLNUip1kuybFUV5fEWUI9nZH0umSDPumoj05TsuEQmcSoNCHuSqTWoAXWeYxtnbxcqKRYnz4Z2g+y5QooIUPGaT2+sbgmzAXKqsLWDXVZMJtMKYqc1XSKrWpMUVLMFjRFxWq8wFUeW3p6WpNISaZiYi1JpGSgFalSbCUxmYAUj2xqhA3y17GESHiEkW3rMXgMeC+CFDWCBkHTSlEUUlErRalicqEpkJw1NStnWXjHXEApJaWMqJWj0Z5omNIZdrnx1j32795h68YhK2OZzZd88fAJXzx8yqPHz7i4mFBWNRACp1SS4XAQNtDNLfYPd9kYbdLtdsmLHJ0IlvmUsspJ05SqypnPZkxnU6bTOUmSEscxZVkwGg3RSrO5uUG320EKSVmWFHkRLGitwTuLVpIsTdnb2WFve5vtzU1MUVIvV4jG4KsaW1aUszkeQVMbUiGIkpRECFZ1zXI8plwuMUWBtC60mZwLLPjWH6ObZezvbdMf9MiyFC8Ce90Y81oEEOtb+mu6/ikoXK/Qt3WtPrxriWrri+NluLjuM4VWU9vKWffb115PeIeyjthJet6RCtgVmn6UMEpTtjoZnThmp9/DNEEOwUuBThIGh3scvPM2h++8w90f/ggfx/xoPOZvfvlLPvj4Yz774gFSaW7cuom3ntOTUx4+eMh0NuPk7BwnQKmIqqnwwqNjHXqmwgV1Ty/AibCpC0m+qlBKEccpO9u7bG1u8KMffA/tA7Huw5/+hMnFBfMyJ/GBtLbZ67GZJHTTDtJZamdZNE2QayaoggrvWp9kgRaCRCqUUNQehkiGKkJ2e3glWZoytIqaKvS0lzmziyc0XoSP8JaxAog1JBFpv4NKInSWILRGRIo4ydpZiXpJOPRhhuIag3Qe6cFbGxBCeUG5XFEXFcvpMoABvG917HyQI5c+mNp7SeJhaCESijiSbPeGZHHCIOuivENaiy1KpLN0yiYgsbxrPQ08kVcI085rWkFAoxOsUOFxFB5XMqKKYhqpmOuY3MPMe87KmoWpOClKbCRxaUSdaKyCJnJYabHacuubb3Pj9g1+/C9+jHOesqr5y7/5G54+ec7Pf/4rxuMl80VOHAUkl7cGrTVpJ+EP/+j32N3dZm9vj8V8QVnVRJlkZ7TJ7Xs3sNRcXZ1TVTVVbXAojBfU1lMvC3r9Bik025s7pGmKQNDr9oL20SJ4ZSxWOau8oChLtJQM+h3ef/dd9ra3GPX7fPiLn3N5fo6fLeki6CcZPR2FVq5KkT1FnCb4yYTq8oL87BSxyElrSw9HTzgyESr/2DdkGm7s7/CjH3yPZVUxm094+uwJHuh0+620xkvJ7jX58eu4vnJB4dUZwt87dH6tPAz5/Rrj/hpqSbwcluJfBgZx/TuCjLMmBIWIlvGLoCdgQ2q6UrKbZvTjmFGSMoxTEqWCVaK1SGvZ290nGQzo3jgkzlIWZc6T58+IBwP6u7u8881vkm6MGG7tsFzllGXF1fkl08mEy4sr8qLAO7A+KE8K1f4dMpihO+fwNgzGlZA4665FQ3vdLttb27zzzluMhgNipcnnUxbjK4rlAlOVaA+pEnSUIol0gNtq1apTAkoinKeyDamWRFIHxjaBJ2yMw0uLkpoY2b6/UFsJ60m8IBGajhbYlgntkFhUqFS8o7QGa0Iglr5ERA0yr/FS4KSg1upamnntfeCsbRFlnkjI4J/gHMI4dNXQqRsyY+kRIZQPLR2xRl1BLAWpksRChVaTsSgfKsABgsQ60rIMAcc5fGOQ3pEKEQLCmigXDgRrJJvXAifCrKBG0nhJ5SVGahqdskJReMll5Vg6z8Q5JtZTeEXVG2A0NBoaZXHaozox/WFGb7PHW9/6Jtu729TW8eLomCfPnvHxZ59zfn7JIs9pnEMqTWNdO3sR15C7Xq9LnMTk+ZLzi1Om0xl1bel2e+zt7nFwcMjNWzcYjjaYziahZeeDbPlqWZCMp5wcnzLo9el0MhazBfPJDO8dF2dnLGdzcJ6qKJhOxrx49pRhr09Xx1R5wbSqmV5NKJYr0ihByWCepNverfc+HFNjuTw9ZToZ06xWKGuI8cS+hXxbi9aKbhyzPeqyNeqzMegzeT6jsTn5cok1hjgKEPKXoJFQXr5MBL9e6ysXFF5dX9Y4+u316kTp5ZTptR9Z89/XYPf111yw22ydfNuedAgGEWGY3BXQk5ItpRkozX6a0YtjhklCL46RCKp8RdDeF+zt7NDf2Sa5cchCwGy15PTxA/rbu3zv3j3e/Ma73HjrTUbbe5wcn/LrDz9itco5Oz1nMp5gnUMoha1rGmdIoqS1GnVYG+YIzvogDCbBtSqfWmo2BkPu3rnD+9/6Fv1uh4vTY5bzGSdHz1nNZpgiD54JStFLIpIoQkc69PNFYM96p/HGY41DRkE9U7b6RN44sBZnPGmiUUIQq1b51IE3QYLbCoXTcZBpkAohNUJGlM7ROMuqKqlMTW0aTGFwpcGrBoPFeIfB4gjEwbquaUyDM0FnKtYKLaPwmu28RDnQSLQQpEnGuqGTyLVnlycWilRpYqkC87mqEM4hnCV1HuUNqm4QziNdaJspIBbrOVOgSNKK7QmpEFKB0jgkNZKVE5ResHISqzSNSpg6ycrCUVWzcI4rY8mlwGhNMhjQyGB7WfsKoTy9bspwf4/b927yzvvv0et3mS8WfPHoMT/9+c95+PAZq2VBUdV4FDqOyYscgFgp1lalnU6KVpL5YsrJyTGnp6ecn48ZDkas7r3J7/3B73Hz5g0QDWVVte5noYU3X+a0fy2x1nS7HZqmYTmfM5tOODs5pchLhIcyz5lcwZNHj9jZ2OTdu/fI5wvmVc30akxdlmRxSqRCtWmbmpe+6UGX6vzkmOliTpPnaBuEJqOWK6OtJU5iSGL2t4fsbPQZ9brU+YplUZIvFzhjiKO4VQtog0ILARb+VWPOr09w+EoHBVifzDVf8bVvEHLBoMCJFwgfBn/Se6RvfVuvNViCCJvzrc24C3gkKcSXqoPw74CAMNqJNHe6PTbihL2sQyYVHSkxeYltDPVqRRRrRBJz+eKYvKp54/CQzc1NNkcjHk4mXFyN+T//X/6vvPv+t7n79lt85zvf4523K95+6xvc//Qznj5+wl/99V9zcXnBi9NTdBwj0a3Uc/hjY6lAKYQHayymtnSyjOFgxJ/88T/nxuENbt+6yf0vPuPhJ+c8/PQ3lIsZ1WKGKisSZxko2M4Stvpd0m4wETrP54w6HUbdLjdv3CPRCuktx8+ecXx5yTDukihNJjV1UUNjWBZ12IS1IrJBe0iVNVoEMlQU9LxpWi84R01vrZgaaayWWBcHsToRKgjjZRsYWtFsK5Bxhkq7RCoK/XJAmICowrRmKiKQwiSg7RpFJoiFbr0jHMIRjI58Dc4FvwsZZJ0jfItQCtAd8cqmhVQ4AmQ2jlOCzLen9ALjBYVvZwYqpowSKqk5qz0rJ5ivHBMHOZJVOqRUipVS1FpipWciGhwG1wbOrBNx5923eOPeLd58+w2QkpPTc/7yb/6Kjz/9nM8++4L5vA6ELgHO2YCebneAxtpWgrzm6ZMn7O5ssbe7y6g3pMgKni2OaYpLbO3o9QesVjnf+d63UFHCqqhY5TlFUYD1rBY5R0XN5GqCbnk91lhsY6mqBm/DMa1XFcvK8LR4wEWccPrgCZ04JY1iIhkjIkm+WDKpF9RNjTF1y7y3RHGE1ppuUSCl5GB3j8VyibGWXhTTjQKQY39rhyRLubm/T+M8zapkeXHFfJVT7d2gXubUeXjfykskqoVff32CwJfX1yAo8Hrmfx38W7byumBcow54yVW4rh3aB2up5vVQSl6jVl4JCgJSIRgqxSiK2EgSNtKUUZzQ0xGx98Rti4GmIbrW4JGUqxyfLMhXOb3NTbI0YzQCX5ZcXY4RUhHFCcPhiG7HIrxkMZlRLHM6nQ46joMm/Pq9+vX7b3WMCINxLRVRErGzFSCBb969S7fTxdYNV+fnnB2/YHx+jq8KqMtAWFOKYaLppwmdJAYpaKylbioiGxGToPo9sl6HXidlVpUsrSEvbNv6AVqMlvOBCBfY4kFPSQh13YJTjms9fe8JuX87GA+DbYGT6hoxZrzAeoEN4Nfrc65E4C7ESoff7AERBtBrgEBQwFgnBO1c2oO2PjimQdjkvQtBdm3HiQhDa9cyt1sFOO9fthzDd8L7lSLCS4mRYUZSe8GK4Hi2QpJ7SeklV86z8pI5iqlQFCgqlVBrTRVHNBqsDGRF2/okDHsp3VGP/cMDNre36fW7XI0vOTs/5+HDJ5ycnDOb51RVuMaD7ESM1jH9fj+o5kpFURRY0zAZj0kixeH+PmmUkKUZUkia2jCdzjl6cYzHM9joc3Z6yvhqSpGXmMYQqaBWq1Ro0XkBsY4QOkIkoPqhVSOdB9sE3WxjqV3JyktEZhGpQ6mIpjasipK8KqiaCmOCn4XHEVmH0gaDIEkTev0OcZKgXSCVusZSLnMWkylNmRHFijzPuZxMWU1nVFUTZGasQ7TilK/uAF+v2uD19ZUPCr97rU88vFRpXAu/re341plkkNMOyqICGq5v9cgLtA8Q0wRPD9jSmoHW3BoOGSUJe50uWzqiKySZsfiywuYFsgl2lp1OFxdF2DhitlyxshZ3/wE3s4yb+wf84Ic/gjTloqrojjbpDIYoFWMay3DDEacJTgjyuqKoKmprWrXPQCyTUhJpFQhaxlGXFaPhiBt7h/zRH/4ht2/d5q17b/HRrz/k3/5v/4nnTx9TrpZEzgQ7TSnZan0S7mxvkmhNrCR5XVI1FdPVnCWOKY4bcURvZ4fb3/4GyY0Dto5O+A//+t9TzFfI2tPRCYmM6EYdEiWptQwYfe/pdzKEC+L61tR4PJ00vVasda3BjfS2JdmJoMbpHdbboH4qBEoHRy4pRPg545B1iVxv4j5s+s69ZK6rNkBdiwJaB81vO/Q6bCt30gYT2hcCpFShDSaCpIcXCqETKgeNBy0TvIowKqZREY3UnFc1C2O5rGvGZc3S1UyFxsQZtjtgJWIqoVhpjY00Nokw0uCVJ+sklAvD1dWcd95/nzffuMnv/cHvIaXFmIJf//rXPHj4kJ/85BeUlaUxQTVXiPD3b+9scXBwwB/90R+xvbXJ7tYmn3z8Gx4+fMCHv/w5+XLBW2+8SafTZWtrh+FgwHS25PJyxvgnP0cowf/73/2/sNbTVA7lPVpKtjZ79LpdRoM+/V7wKzjY2w3XjVZsDkZoqbClYXxxxfjikhdPn2NrQyfOyLIOURTz5OkLlqsVs8WchiBYItvWrlISqio4Ra1yut0OO0qRJimpUjgnGV9OmY2nzGYzjLUMNkbMVysuJxMmeUHW75PJiExFpCoKbWD3dQ0Dr6+vfFAQr55n/+UHvt3g1zls+622EliznKV8+VpRy0mIpCD2EHtPh9A2GkjYihOGScxWJ6MXRSRKQNNQOwdVg6gN1CZsUFqRZV0aKamkIIkz6PTY2tph0B+SZR2U1sg4YdTtodIMIQXj6ZTZdMbjR4/4xQe/5LNPP+P5yTGz+TRIdrRS0876QLAzjkgq0jjm1sEt9vb2uXfnDXa2dvDW8hf/6X/n+dOnjE+PEWVB4i2pgF4U0U9itrsdOlFEpCKss6xMw6IqKeqKqTU0tqExNcf5ElWuOHANYnuDQZrQuXOb8nzM5HzKwmm0U6RIEi/pOk1HQCrAyIgIR+wMWmqkM5i2xSPXEtnr8Y7zCOGuM3uFCvBgCMps7TFYy3zLVihPehtaQT5Udi8rxLCxq7VKZjjb7TXwkuMugMAtC0qrxrUglTaNsAR0lJUxXmtE2qOwntI6rEoxQlGgKYygcI4LA7mXzGTMXIjQKooyXJzisg45mlpIciFwWmClRWgP0jIrlujIc3hzlzffvM2dW/t4VzMeX3J+fswXn3/Os+dHmCaEMK0kWSem2824c/uQ/f19drZ3kN6xmE4pF3OyJObtN99kOR3T7wd/5U4vUDG3trZwHhbLFQiPFJ4sjul0Ogz6IzYGQ7rdLjcPDul1MwbdLloFccl+ll6fg16SIZxnfjWl0IpYSgbdLiYyeK+YLpYUVcXlck7dGBqlcSLchEnWodPN2NraZDgaorXig1/+LUtraSZTsiQm1ppeHBNrRaI1Wico5VjOl1RVjXBti9jJABH2QWVXiTaR4Nqc9b/F9vOPcn3lgwK8Djn2rz1yr7SL1rL7r6KXrtGngG+zyqADlBAYybEPFUJHCIZSsJEkjLKUjSwjlZIYjzPBhtMWFdJ4lPXoWKGUJk06eO+pvQvlb7fP5tYOg+GINOsgpUZGEb3hCAs0znE1vuLo+IS//dWv+NsPf8Xnn3/O8fkpTVOBcNftLt94QlwQpFlCJ+ly7403uXXjFu+8/TbCWRazGX/9F3/BajalXM5JvCMWgXA1SGI2uj02e10SrVFAaRrKpmbZNBTWsCCwpBvbcJIviIolV7ZhuDGkt7VJdvsmAs1sVuIqwAoSVAgKXtGXiizQqYP5vLIkSKRtENUqCOwJj3Ytmt+Ll+iT9pxFrQm8x2OtCQKG2NZTWlxn9N46hPUtk1m1IITglhd6bS0osWV1B4SZvJZy9kK1BjChCjHeBdaxEFgEpv1wOoMoRqQDVsaRGxfaQAgWXjJvLEvjuHJQCUmuY1ZCUEpFk/ZxcYLPOhQ+uOQVeJx0OGGJdAh6y+WUrY0uhwe73L17gxv725im4PLyjIf3v+Dxwwecno9xBoRUaK3pdztsb2/y7fe+xc7uDqPRiIuzM6azGavlnDt3bnPzxiGTqzeCR0ickPnAaB6ORhRlSaSDdImOJKN+h+3tbW7fvs2Nw5tsjDZ54849OllKN00wVYkzBmEMtq6xdU0iJLZqqMSMqEVwddOMWhny0jBdLrm4GrNqGhwCGcUIFSF1RHdzm43NDe7cu8PhzRtEccSvPv+c1WzKZL6gE0UkWtN0O2RRTD+Bbpoi8CwuLzHWoYVGo1FIhG0lRdrzvpamd19T1NF6fS2Cwu9a7XZAQBv5l1r74hprdN2LB4JTiIMYGdBF3tJDkiHZTjN6kWYjDWS0XhrTSTOwhrKu0EIgtSLqZEjjcMYjVEQtJMt8idUaG0XEW1t0d3fYOLzJ4OAG3f0DZL+H05pivuBqPudyOuNf/9t/x8NHj/jZz37O5eUF8/kc6wwykmitMHWNNQYtI9I4ZdAb8O5b77K3u8vd27fBWU5ePOfTjz7k4uyUy+NnRHh6StJRmlQrdgZ9ht0uw24P6T2mrnl+foFXEiLNuz/8EU5LHh+/4Oz8ghezKe7Zc6ZKcLj6Jm/u7rAxGhEd7uHKivGLU2rvcQ2kskMkFKlUdJwgdnA8K4mdJXWGrVTTUSmDbkLsHbG3aBM4Bol3aMJmop1FeE/lzHXwFi3cU8ngX23xrX6TaPWRwuzAtX1jQZCTgHbjb7/qCLMEIX2YVwgRAqwQiChuzWwCpNQhcVLTeInxgpWXNEjKGpbGszKeUksqJFPrWThNLgTLWOOiCHpdcg+VENiki5WauoWLGu+obI33wVTe2xrnSpbLC24d9njvm2+wu7NBEmseP3zAZ599zq9//WtOzycslzVaxzQmsNX7+z22Rpvs7+0hBcwnE379wS8ZX425vLxka2uTjY0N3n7nLQaDAVprLs4vubwcMx5f4Lzhxs197ty+yc7OFu9/+xv0+z0Ggz5lUdNUDY8f3CdfLlnMZozPzijznGaxDIN4Y+klCZFUaKGx1mGMZbZcUVQN01XOsqwovKFR6pozdLi/z87uLu+9/x06vS5pJ+XBwwecHB9zucyprcdLjXCCpnHU02WAhwvPqNsjSxI2NnYQSiGkJF7MibOMTqeHVJqqqamtwVh73Xr9HVoXX5v1FQsK65rgv3wyxWv/hudeS2MLcR0U1q8SBpGhhRHhiBFBt0gJulKxmWV044hRllxjnitriZUmGaTEPkAVfVnjakNd1nihESK0HHSWEPX69PZ26e3t0tncIO73kVmGRVDVDZezOU+Pjnh+fMKnn37Ks+fPOTk9oShymqZGqPUWJ65L3yiOGQyH3Lpxk8PDAzY3NsE5VosFl2dnnJ0cM728xNUVOoroRJpepEgjTTdLiaOgCVMWFWVZsaiqwCTWmu7mJl4rotkUI8csG8s4LxisVlytFhx4Sz/SqH4H0cmolaSUDiPbTVVoLAorBJHzFMISEVpyzik6UlB7H3yIHcQeNJ4ETwxEIgRoiWt173z7OFQGXqznROH76ypvPQ/48no1GfBCtHLioWqwBPOataOZF+F9G0SA0CKxRDRCUiNYWE/tBIXwLNqgUCtBLSQzIciVpEBR6ggfxYgoCw51CKyKcEJh2woF2sKlJR9614CrSRPNcNBlb3cLrSV1U3FxecXF1RUX4ylF2WBaq0olJMhgK9pUJYv5jCSOkVKSxEHqvSwrrq4mFEXJ1vYmxjQ0xnBxccFsNkco6A+6DPoD7r1xh52dLbY2t5BCUOYF46spq+WK05NTlrMl88mM+fiSpigwyxxFYK+bTkakI5Ioaa1DHcu8oKwbFkVBZS0NHiNAxZrhcMTW3g47e/tkvS5IyWS+4PzyitOLi6AaG25cas81o115R4NHqxrrBVnHhZatDJauKo5RceDZCCnxLZLtpc7Fq9vI1ys4/CMOCr+Lf/B6o+i1TP9Lz3gNkOQdjbcYHF6Ktk3jMS54FUcIFKF90cXTEbAhJVudlGGScmdnmyxJ6KYZs9mUZVkwLXMODg5447336LQl7NXpKYvJjOXFGN1i9I1zbN+4we6du+y98w69nW223noTuTGCTpeiKrmazfjbjz/hJz/7Gb/68Nf85uOPWa5WlHUVKpAkomnqoF8EeBcUUIejIW++9SZ/+uP/kVQluMbw0QcfcPLiOY8ffIErcoQ1JEA/1uz0OwzSmCTS9LoZ1rggynd5SVFV5I2h38sY9nukW9s4AbWMWDnBrDb4ZU40mXH/xQt27tyit7tDur1BdDWmjARLJWisRHV7SDTCagpU4AqILsoalGm4chVRY+jUDZGDxAsGIiIGOi0pLBXQwREJTyaDf4NqP5c4pDctgqllJ3uPbA14XqYO7bzgGmJGK5XbtpC+1BaqCSiqilARGASND7+59praCUoLk6qmQlAbx8I6ltbiI4nTmiqJqVRKo+LQL1caHyWU1odKyqpr57l1ZaNRCBmGIUWZAzV3b+3xzpu3ee+bb7OcTbi8uuSzz+/z4NFznp9cUVUGnCDGhd66UszGl5T5HFOvePPNt7h9+w4/+MEPubi4YLnIGU8mTKZnLFYLtNZoLdGRIoo0N2/c5NbNm3z/e9/ncH+PLE15/PARL14857NPPubk9Iz5Ysl8MsWUjrrwdFRL/nMw6GSkvS7duI/WGusceZGzLArmZUVpDNO6ChWZEBgsm8Me3/1nP+DWzdtsbmxyfnHF+cUln352n8vxFavVskWdKazzNK14Y0wAD0QIfGVYGceyPgtqsVmGiDVaR8gsQ3cyok6KiILHx0vdfPgnRvM/yvXbgeFlDHj9e2u/5fV3PK8HiFcZzOvPlScwI3Gh107gHgziiINul42sQy9JUHisaVjlHqKIbrfD2+9/i92DA26/cQ8dK7x3DM7PWc7mzK8mYMPvMt6zc3DAwe079G/fDBXCqE+Jp5hN+eLZU56+eMG/+d//Iw8ePebF0RGr1QprTCtI5/Gu9Q8WAi0l2we7bIxGvP/NbzPsD6jznJOzp8wnUx5/8QXL2QRXFUTeESvFzqjPRr/L9rCPckFrfr5YBMipdeheh+HGkBtbW2zs7LKxs4vMMparJePFgkVZUTQeX5REkyn3nzzlG+9/izs4+sMu3UEHnQhUCcY6jGtC795LEBonJSKVWBM2RONBO411ktg5amfb4OwpjCXxntQH/4YIT+YsyluUc0TSogUkOlQMwvuWhLau+HiNr7jGo6+vDW9DNYCzeEK1YoGG4GxngNJLDBLjJY1XGCSVrbFSY4WmjGOMVDRxHFoSzlG3UNJGeUw7HzCu9YVuAsItRWBs8N1wxrdtTYcjx1PhKekpQ5pqvv32G9y7uc+wk3L2fMr52SknZ6dM5nPK2qJUTJLE7G5usb25wdbGiPlySlWXrPIlZ6cnNE3DnTtv0Ov1+YM//mN+9atf8fDhQ/KiRsoGrQV37tzkYH+PH/3wBwwHQ3qdDl989jnT8YSnj59wdTXm5PgM2xTgHXujDYQTCAPFfAHWsdnt00lTOmmGlBpjHLNVzrIsWJYlK9NQOUflQCURSZbw/e98l83NLfYPb1CbhufHL3j08DHjyYyz81OKsqRpgqZXQDtLlAqkSCVAtK2pyofELk0SKu/JV0vsylN4z7zIKZs6zIbaToGQop0b+b+3QFjb937V1j/yoPD3r+ub/ZWT9+WAAC/nB+vnrTHzAewRAkIGDJRi1GoWDdMOWRS1+vyG2hjiXo/Oxgbv/fBHbO3vs314CCrITGQ726wWS4bTGbYyQcrae7b39ti7eRO9s41IE1ykyZcrrhYLPn/wgM/u3+cv/+qvmExnLFer8P6kQGsZVF2tDz7DUhJHEQf7+9y8cZPvfec7mLrm6vSc50+fcHFyyvnzF/imRpiaRAXJ673RkEGvw8agR10W1FUVbjofyvjuaIvOYMDBG2+wubvHcGubvDX/ma5WrOqGynlsWaMWS14cn7BYLbHe0e1ldHspOhYo7ZHK47wJlppeIkQY1qooCtpG3uKJsD54MBtrMVYGLwrvqYQn8cFVLPYe7R0ZDuUsylliYYIPgopCZcArQcH7V4JCuOldmyH4ln4SFEpb0rr3VN63FDqovbgOChaJuZbfgMJ40AlCS3yc4rWmiSOMC3IbjQi6REbY1odaBg9wG8QDdaQRUiGtv4bZShmQRtatcFQ4X9DpwSDr8M6dG9zY2aQTK1aLGePLC67GYxbLFY0NsuhplrG3u8OdWze4eXjA+eUZ09mEh48esFwuMNayf3CD0cYG7926zfOjIx49eUJVVwgBiVBsbG5y585tvv3+t5BIFrM5jx485NGDhxw9PyJflSwXJaN+TK8TDHAiIVEOTpsGWxu2NzaIo4RIx1RlTW0si1XJoqpYVhWlcBg8VkrSLKM/GvCt73yHwWAIQvDi+XPOzs54/PQxi8WK2WzxEj3amkIJKVFaB7lvH86iMw7bclviboeyKlmtCoqmxmrFqg56W9b765ogYA/+/oDwVV7/yILC72oZ/UOe9/fPGNYtBuUsCdATioEQSAFdDwMp6CvJjV6HYafDXn8Q3LxsTdlYZBwT9/t0d/cY7e1x49vfJR30cWmCzKLQzjnYp29s6/EcBpm2qtDdLlE/+OPWTcPRxTkfffopH33yKf/hP/0ZJyenHB8fk6Qpo0Gf1SpvPYYdOIvwAVUxHPS5c/sOf/rjH/PmvTc5f37M8ydP+dXPf8788oo6z+l6RxJrOp2U3Y0Rg07G7vYm+WrJ6fEJRVUiI83Nt99k6+CQnZs3kJ0OjfOcTabcPz7i7Ne/4ujomFWeM5svaIwjyVJMU1FXhsV0xmI6oZhP2eyl7I863NrocF7NWDUNwi2wRtLUCmPD5hoNhoGM5SuUCjenxSMdWK+oDBjnqIWn9MGQRkuCpakPEEkhg1GL9BbyAtXCWVUbHIT31zyF9eTo1Sujce1X2wrCAQ1hY3EIjFQ4KallaBlZofFa4YWiiSVCaaSWWNXghKG2FbV3GG8pqhIvJVGnQxKlqCgm8w7bWJpFQ5pmRDrGN2Ew7pwB7fHS0fgVXhmErtnsDNjZSvjhWzdQieTixQMefvoR9x89ZnJ1QV0aYi3pdFK2dzb5wz/8H+hlwS9iZ3cIAv74n/8hZWOoGxsqE+BqOmG2XJJXFTjPwcEOf/xHP+KH3/8+t2/dIl/mgTn/53/Fi6cvmE1mFLkh0ZLtfsIf/PB73L5xwDt37lIsCyaXEz4ykmJVcOPwNmVZs1gVnE4XLPKcq8WSyodMXiQxcZays7vD7//hH/Dt736Xqq45Pz/npz/9KUdHR1xdXrZ8FY+QFiUk3kPdlEHMMUquTbKMDQAEIsXO7g47Ozv86b/4n3ny9Am/+vADTi8v8LGm9i7Mctb6ZkLg2krt67z+kQUF+PsCw5erud8lffSSurZ+jvhSYPBo50iEwElJX0pGUcQg0gw7HXppgpYSJwKGe9AfkvR69HZ30b0+8WDA49NT+nXFcGeHLIuJogilUtp5YXivzuOaBrTGxjGL1YrZfM5Hn33GR598ykeffMLzoyOmkynGGLRpsFIiRZvZeE8SR0SxZntrm63NLd669yaR1Myuxjx99IizoyMWkwm2yJGmIdGKTCt6SUw3DhA+2zTUdU1ZVZRNQ6QVSa9H3O2g0pTJasWyLHlxds7p+TmnlxdcXF1QVyHr816u/YgCL8IGm0tTlkSJIpWQaYJqpWiQvsai0FgaJEJqBl2F8wE9gm3AWZxpgvqsEFhhg9+zNNfn0AvfGgGFCkA4jxVB02gNV5Xeo1o+wprrIPGI30FUskpcgw1se4zNGoIqJK5FxHilAQVCgQqeG1IEpzcvPRYTKhAZWlgKR4JDaklvEJFlKUmSUBcNdV6zKJZ00CSEgYeXDusbHME32kiDbzkK252I3X7GzqDDqi65urpkNrliMZ1i6gYQxFFMr9tjOByys7PNYjrhxfkpXghUpOmP+ggVgVThnJcVk+mM+WKOB/Z2t7l96ybvvvMOG6MRwsPxi2OOnr3g9PiY5XxBU9VoIRkNety9scedG4cc7GwTC0FhGqo8RwuJVpoiL1kWJbPlikVRsqqDnawVKsjED4f0h0PeePNNNrZ2kDri5OlTjo9PODk5ZTKZsCoKtGqF6a/RgrT8lFBdOWtABLJmlmYMen3u3b3D1tZWAAw417YvLY0Lsu7Wh2to/d8azv0PqRS+iq0j+EcZFP7r1vXA2b8eFAQCKRTKB7arMg7dWKLG0EOS6Jj9Tsp2r8soS9nudINiknWIOCJOU954/3029/c5fOttTmdzLucL/k//6l9x8403+P1//ifcSG/Tb2Wm1x7B6yURNE1DXVd8+ugxj5485v/2v/6vPHj4kCdPn1HWFb5lzZZlQVkVZHGCkmC9Y2Nji63tLf7w9/+Ag/193rx7j7/+87/kJ3/+l3z2wYdgGrpaEztLJGEYKbpJHAZ/SiKs4ezshKppKJqGkgDT0YMBOVCMr/jrn/+c86srLqZTqqahNub6/QehvRAQdHs8NQJbVlTLBXEvIqWhJxsKSqQviYTES43VEUYJZCS4e3OAF4LaNFxdXVLkJaty1m7uEu9tILLpVq9ISPD2elYkvUe4UF0EpEsM11Skthp0FrseL7c6Ra9cIAgVXxNThAwzZw3XXASlFE4IIqlxUgeFU9vSH3Xc2qQanGnwgI41Wgq8hI5UZJ2Uw8MtRoMRvaxLNc1Zjme8WE3ox5ZMOXQksdZTN46aGiMMPvH4CFyquL0z5GB/i9tbIx6+eM7Jk8dcHB8zubjE1AatM9JOl8P9Q27fuMGNwxv8x08/5t/923/DZF4QRRE3b+9y49YddvcOqI1hPB7zqw9+zWqVEynF7/3e9/nmN9/lxz/+MSfPX3D0/Dl//Rd/yfnJKVen52A8sRB0+ynvvX2P/+VP/yd2+0E6/OGnn3JyfMqzp0cgY/Dw4PFjFkXFvKhYWRNacVIhk4QoSbh5721u3LzJH/3zP2E8vuKzzx/w7//tv+Hq6pLJZIJQAqkCAGRNNg2BAaQKKDPnDJVxKKHY2N3h7q27fPv9b/O9732XJIn5t//+3/Hk2TOuxhMWqxwrRWi9Onutpuu9R0kZKsOv6Ib/D1lfqaDwZUDqevMXr4T/lpN0TYISUqJUUL9UDrQNQ+UOsJkmeAGHoxHDToCdeufIq5rZfIFIE3TTkC1XSOu40R9w6+Yt9oUkz7pYBA+fPcdoxcaq4OBQkaYpSZrhWp/kuq44OTvl+fPn/MXf/DVPnj3ji/v3GU+mGOPQWuOdw1RN8AlQkiiJSdOUre1Nbt25xd7eHv1ej9lkyp8/+I988fGnnB8dI5uaWAg6UtBLElKt2Op26KQp/U6HKI7C8YoE5WzGfF6wMI7IwLPTczb3dtno9fjGt97ndllyNZuyWC5ZrFY0pqFpGmazOfmypCoqZNvKslWNrSp8WaJtQ1d4drIYmWlWpUQbhxdBzxQdkXYVP3pnFxXHWAmPH3umE8k4KYKhjxRIp0LWLwSRUkHgr9UdUmvbNevAm6DQqVRgG4iwiVzzGMQabPDSZjTE6AA1XRsPXbcT1rmED9LcoWoI3gdeSpzXAcIqZBsUbNBqkoI4i7HOhvmA8mRpysFuws6wwyDrsZKGSSWoXM7ICTrSEzuFdY7SVZTUNNLSeBfQUJHioNdhrxeQWuV8ztnRMfPJnHxZ0FSQKk0WZ2xtbDEcblLVjiTrs3d4i6y3xJiGxSznQfGIJ4+OcN5R1RXFaoUSnk435s17d9nf3WG5mPHi+TOePnrCk0fPKZdLEq3Z39tpgQzvsD0a0dGC8xcvKBYLXjx7xnIRlFeXeU5eGc7mc2oHjYAC8EqRjYZs7+2zs7/Pm2+/TZqlPHr0mEePHvL8+TPOLy4pqwLZQkaFaOXfCbBThURIicO3hEMYDob0ez2+/d632N/d5+Bgn0cPHzCbTfjwg18ync3Il0tcY5EuyJ5ESgfFXylRiMBN8dBePXy5xfh1WF+ZoCD+C4/Fq3XBKxPmIBjXisX50GrQzgceQmsfKZRkoz+gm0QkKohqFcYwyXOwBuUs/eWCrCgpgIOdXdJ+n3tFxfnVFS+OTxhMFwgds7nVoKMksDodNMYyWyx5cXTCx59+xgcf/poXR0ecnJ5R1Q3WOSKtW/5BEzJkpUjSlMFwwM2bN7l96zY7O9u4xjCeTPnkw19zcXTMcjojsZZYazpK0U8Ssjhi2OuQJQmdThZkhaWENGZWlRSmYVGGG+ZsPEZ0O2Sbm2zv7eGB/mKT6WzKbD7HOENZlq1X9RTbGGhCL9cZg69rXN2grCURjkGsMJEk0gLtXejZe4eMFd3Mc2+vT9zNIFb44pJLXRHbFCUgVqIdGgeUjtaaWOn2Bg5VgrchKHhnEAQDIdFqWqzbgwFZEkpF0ZaMQgRJRESYXQhaSfQ2KPi2lbDuNoV5gwrnREoQUWA0e2jatoRQIJUkzWIaG9Q9tRKkSczuRszeIGGYJcyXEpk4LnzJyGu6TpA43QYFQyEaam8pWzlToTSbaWDMC2up8pzp5RX5MqcqG6wJb1BLTRJnRDohLyp0nLK1s0eSZhR5wcXFBYurGUVRYb0FAlCh04npdVIO9ncZDvuslgsuzs85Pjrm6mKMcJbNbsqN/T1uHhzwg2+/j/KeOl8xvbxgejXm6vKKprFY58nLkkVZMy+LIGCoY6xSyCSmt7nJ7uEht+7eZf/wkKap+eTjT3j46BFPHj+mLAvAoyN13QP2rRiea+Hmcn0Pa0mcxIw2Rmy1g/HRYESWpXzx2Se8ePGcF0+fUpvgDLiuHBUyBAOpkOsK/rqCFP/QLtJXbn0lgsI/dPz8u5cDa3BNhTANmVRsdnscbm1ztX9AU5Z00g5FsWJaLriaTsnrilmRs1jMqYD7Rc7oyRN+9uQJf/DjH/PmO+/w7vvf5XZVc3cyJo5j4jim0x8gtaY2lvF8ztXVFX/2Z3/GL3/1AT//+c+5Go8py5LlqrguZyMn2w3MtyqR8MPvfY8bhwfce/Me08mYy9NTPvnwI2ZXYy6Pz5HGoK0jU4pBlrK7NWLUyUgjhXQG6w2resUb773F9t4e/e0dfvLzX/B4fIk1OXld8ZvP7/PF02cknQ84vHWTrNulM+iBEERJzPe+9X0AHj16xKP7j3jx7Dnzy3HI3AVY09CUOdJUqKYmqgqyukCZgtRrhA+NANNUJLWhZyckvgYZc7gVMeyMuHd7RBIHe9BrOHEbFLSOruHDWsjWxEYgWnihc+46AfDStxUALYRxDfcUrSNduwG48PqidW27hrDyav/4JZ7JA14GK03jfZDylh6pZECDKU/TlJimJsKFWUdjSB3EZklmF3TqOZ18Qs809FRK1IS++UAKishSScd5scLLGGUFW72MnWEPW5YspnNOT8+YL2qKCqwnbPRuyke//g3Pnj1nPLmk0+3wzje+FZjc1lEWBZeXl4yvxjx6dJ+iXGFMyc3DPW7dusHNvV0E8PD+fZ49eszJsxdkCjaGI96+8wb/8n/8MXdu3eT42UPGFxccv3hOuSyoy4plUTNfFUznOSvrAipNK0rnKOqSt957j939Q7713e+j4wghJX/9k7/h/Pycx48eYk0DuCB696UtOdI6cIps0x5jCaJhe2eb7373u7z71ttsjEaspnOePn3Cnz/6T7x4+ox8tWLYGwT0UZ4jBSRSIgn+zU1eBi8M1srJ/Nbv/jqtf2RB4fUa4HdVB3/XCX0JN/WvfC1Az7z3rWmKRwtJooM8hNYJRjQUdcMiL8nzFZMipzSGlXfk3lF6R75akcsryugx6a83uJwvaERMb9Cn2+/T6XSI45CVl3VNVZbcf/iQo+MjPvjwQ+4/eMjp+QV1XQVv4TU8lrZfLiW9bpfN0Qabow1uHhwy6PVYTedcnZ1zdXnB7OKS1WKJqwPUNIljNjop/Sylm6UoFTR+8nKFijSRStDdlGzUpzsaEnU7WCkQkUIrSdzpECcxcZKEYy0ESZIiVYD+dbs9nLWBBCRfzknWe6czBtOsPZ09ylsiH9o8qbfh7HlP5SyR1WhXo7wG7+kkEqkSdJwQJylp1sGuGecyeEpLFTJq4SGS4XYO3IdX3gQvB9KtOdj1QBFaIpt45Try7eevZI7C+zV69ZWrrvVURrQM58C29kFZsQ00HikssY1w1pAI8I2hns+RtYdrUKsh8obINURCEZk2MAkVcmLvELZGOIkUjjjRxElM3TQUZcUyLymNpXYBXmu8w5uGyWzakhs9g8GAQb9PEsVopcnSlOFgSBzF5PmCxWLKeHzG9uYGtw4PSLSiLAsWkwnFfEG1ypHGI4zHVZbldMkkHXN+dMJsOmE1X1KWDVXdsKwMy8qwqBtKBA3QCEE2GLIxHHD7jTfY2NpGKMF8PmO+XHB0/ILx1RWr1byt3Nf3cJAily2sVGqB9METPNIROorZ391nf/+AGzdvorRmlRf8f9j7ryfJsju/E/wccZVr99CROrN0FQqqIdhNspukzdoMx0izmR0z/mtra7bPu7Zvy90xDskmbamaBBpAo1G6UlTKyJCu3a86Yh7O9YgoAN3LmZ2HLhYPEBkRHsrL77nnp77i6Og1pycnHB8fs1qtMHVNLIM0exxFWO+JpGqsWUNigWvmTF87R76d6xsWFK7W10PCb6/fGiA2B5a4HCA1csfN9zpnwVmkd8RSNRryLYSMqAxM8wXj6YT5csG8yqmFp1aSQomgcVPm+Lri5WzGw1dHdLp9fvnRZ3z/Bz/kv/vv/yHd/oAsy8iLgslszqtXr/jn//Jf8sXDh/ybf/dvWa1WFEVBFIUMVUU6IClsGIDFUcT+zjY//dGP+fCD7xBrxXQ85i9/9Stev3rJ5OKCfLHEW0uMp5ckdLOMO/s7pJEm0YKiWJGXOafnp8TtjH48QnRS4mEPOhk2jigF6DQiiWIOb90iy1qkrRYqiUnSlN29/SBLLSVJnFIUBVVRYWqDNbY5i0OWXtcVdVmghSASQacocRbtLG0PwgWCmHQVUQ2RXaMsWGtotxSZiIh7A6K0TZR1qAi8gSBMJ0LLpq5DVSBVsNhslhSCSF1t7Q341G2QJg2OnQ1vgSuU2iXjWajws5sgc73vGFy4r353M7ISClACjwEfkEOxzIikIJMKU+SY9RpvKiw1QlQoUZNIQ+INqa1QxoU9IKOGK2ERtgQv0dKRtlKSdsZ5UTBdrxgvliwrS27BarDCgalYnJ/hvefFq6dkaUKapPQ7PQb9Pu+8/Q6j4YiD/UPa7ZTzs2M+/mjK/ds3+e777xBLWCyXjF8fs7yYUM6WUFhqXzE9nvDxLz/ieSfj/OQZeIeQkkVpyKua81XBsqiYGkvdDG0L4OadW3zne9/njbffQUjJl48e8ujRIx4/fsz5+Tl1XeGtvbxzI914GjpPrBv5GK0CoEHFxGlCu9PhT/7+32Nra4udnR0efvYFx0dHfPrxJ+SLBfl8EQ5/IVivV0RRRCfLqKwl0VGoDrwgkiqg0Zy/do2vnzXfrrnCNy4oXB7w/joF7fq6niWG3vB1YlpoWzS6ODLwVKQA1YhlGe9YVxWz9ZrjyYTJeMw6X5LXFaWAhXfUzlO6IEtgCAO0JEsZbI347vd/yNbOHs+fv+Q3H/+G0tR873vfZWtrxGq95unTp3z00Uf8x5/9jNfHx6zX69AmiqJL34DGtRitIoaDPvu7u/zdP/oj+p0OdVnw8a8+4eLsjGePH1OsVtRFEfxohSRJEvqtlE4rJUsTTF1yej5luVpRViVFbegALtbYSGG0wGqJjxUyjXhw7x6DwYj7b74VYJYIJos5ta2ZTqdheJiv+fzLLymKgqOXr1hMZ6xXSyQuOJJpSSuN6WQpWIOva0RtkLXFG0tM43XcXC3lPZF3aO+QOAbtDiLO0IMtZNpGZm0yAgLIK9X08iXO1CG7l3JTJ1z2hOW1Q9yLTf147fbeVBOXyAPCAdeEkEvhoesHhWz8e4W63GVeyjCfEq7BwBKMY3DgbchyhUCZGkFEFk/xNXhM87WQpEjpUNKT6NDJtrbEGY9XjlgDkSRO1CX5b7pcslivKJ3B4nECakP4u8KjtSLSmmG/y6AfgsHO1g69Xo87t+7QabdJkoTp9JRISyKl6HXabA8G6Eanq5otoKiIGgtX4Rz5OmcxWyCcI0s7rNYrxuMpk3WQQZmXJrDAg5MP7Xab733wAffeeIMHb73FV0+fcXZ+zseffMJisSDPc9rtFt6l1FVBVdcYY1BKkaUpOzs7PLh3j/29fZI0ZTqb8/DhY2pr0FHEoDdgtVjx+aef8/rFS2aTCYvxGFcblA8+zRsjLGktqqrYHQzY2trmcLTFqN0mlRK9mTP9/lOHb1Pt8I0JClcwzuvR/Hqfd/O1zdumDP2twCF+TygR4WBBSSyewhqWZclktWS8WpIX68C4xFN4qL2n8kH6wAJoTdLKGG1vc/vePbZ3dvn4009ZFznL1QqlBTs7O+T5mkePHvOrv/gLHj56yHQ2vyyNlQysXVwYgEZRRJwk7GzvcHhwyBsPHrCczZhPJjx78oTx2Rnj01Ok2/gBS2IlaSUJ7TShncZEWlFXnuV6zXy5oqwqfASplIg4wimJlYLKGQwWlGC4PWJvd59bt25hjAtktCKnqEomyynT2ZzpfMZyuaYsCubTGb42+MY0XQmBkhBHmjSJL41zaFyupPVoubHA9EHt1AcSmtqIDuoIGSfoJIMkRcQJgRcQJLZprhV1g4WVDX4d0SCQfBgQbC5201W6Ovw3/4Q5xFXPwDUOau6aZKq/+t0bVNI1sbrAUyD8jICAm1fQqJrS2Lj62iOcQnoVeB1NGAtJi7/07dAKnPPUzoS5kvAoDUIHuWohwXtLXgQ3Mruxh202stIarTWdVossSdkeDRgN+gyHA3a2d2m3O3Q6HaJI43HUdRnafEKQxRGdLEVah69rTJ4jaoN2oJVGyyD2uGldZbGkMo75cs00r8hry9p5iCJkkpB22vSGQx689Qa7+we02i1Oz054/uIFz58/v5zTtFppuL7YgNaykMQxvV6P27dv8/77H3D/3j2yLOP07BxrPJPplNoacJ7FbM7jR4+ZnJ5SrFbBLrUhOKpG5iTVOgRn7xlkGaNOm2G7RTuJA7oN2OyisDuuXtVvTzgI6xsTFMK6ujzua2JVoaN8dSdf+4nmcNgYo/z2150PjlQ20phIs1KSC1Pxar3k2XzCdDnFO0ftHNa7YCavY9I0QToLUvLgnbe4ees2H37veyBCr/TxVw9ZLVdYa/nTf/W/IGUwOqlqQ1lWeAKeHw++ttSuJk0TVKzQSnP79i3u3r3DT37yI+Io4vXr1/zyZz/js49+gygrpAtG94N2m3ackkWKKFK0soRer0uaJuBD/z1L2yzyAmdqRKTRrRbtrRFRK6XG8vjLT3j+6hnrYkFRrlkXa6bTKdP5grOLCR998gnj2YTpcoKxFuscskH/1FWNqD2i9igJXnli6em1E0b9FsJWuLLEFUVAJ5mAoBIenLVEOiLWMbJ26FoiXUo5q/HLJeQaGa1QURymqAiQOgQHqQje2s1F3HQFL70RNvvFb4wyYDOXaH5GeIH34hJ8uJk2e2vxJvwe4UKFQePP7TZ/zodZRTiUGw1+7wJ82NY4ZzGuJo5idKQpqwpTV5TLOZ1YkcoI4WOEiFFxgowihIow1mAbhU/b/F6tJCpSpKlCCIP1FcaWeG9pChW0UmyN+ty6eYv79x/wnfffp91qs16tMM3fNsZRVRVffPkJx8dHnJ2ecnbyGuEN/XYU5KY9+NUaM19STRcoY8gixdb+Hu12l9FoJ1SL6zWff/oo8FasJReCWiqsVgy2RuzfOOQPfvoTtnZ3iFopf/mbj/i//z//H4wvppRlSVmG+ZlzjrzxWY6UxhgQIuKdd97n7bff4h//43/M22++weHBAXEcs17n/Lf/p3/In/7Lf8lvfvMb/tk//aes12uqssKWBco6Imsv7XFTJIlU7HTatLOMbrtF1unSb7fY0oqBknSVJJVhLnTFbPntE+fbs/5mBoX/zdOeyxPhd3/F1whKNMljcxhvBkuBBYOXCiOg9I61rVnZmpUxoekgRPDY9QFdI7Vmp79Fu9fjjQdv0B8Osc7x/Plzjk9PQ7+9roKsNQHJEqoBj3UOraIw4zABaqmlJNYRrVbGwcEhN28ccniwT7FeMSsKvvz0U05fH1GslqQE0luiBLGUxErQbiUkcUTWSuh2W7TaLQb9LWaLBQbPpFghnUGlMVm3Q380Iu10kFHEyfk589USj2c2XyBlTLt9irEerTX7+3t0+x36yy6L1bJpRdVYE9pFQgqkCiqkSkqSJCbLUrJWhjV5mDlYj3cCvMR5GYKC36CCNN4KsAJhBbPplLw0GHcaMlQdB8ipB8S1oOBE06XxjY+yb+wxPVIKmglEk9UH1qu/DCDhvfCiqSo284YQFGh6zKGSCBunqSHYqCD4ze9uRNl8gxhz3uIbeQupFFJJSlMDoLWEQQfZSqmtoHaCwjoK5YmkQwvwSuJkhFUWqxxGhMDmpbgcmItGxTXs8bC1Ix2RJgmtLCOONHjH+dkpVVFQlQVlWVGWJePpmPHFBdPphHy9JpIgUomwwfPAVwZlHa0opkozlFekSYKUkmWxZjybslyuyGtDZS2ldZg4RkYRO9s77OzvcfPObVrtNtZYnn75kBfPnzO5GLNa5VhjrwJ5M5SRQhLHCYPBkHa7zQ9/8EPeePMN7t27z3A4IklStFJkiWc0GPD2m2+hlWJ8ccb4/ILx+RkrazCm4akIQSYEbalpRRHbnU4Q5WtlSKWIfFATcHUdyIbNvtlY8F6eGt/CqPA3Myj8Z1yI31Uo/P0/FDJDf/kzounx4sNQczOIFkrjlQ4EG2dZ2pq5qZnbOkDYkqA7X+cFnhAUHrzxJnfu3eOtd95mXRQ8P3rJv/m3/5bHjx+TtrLmb0ISRUjZDC6da8zew/N3pg6tojiilSZsj0b84U9/wmg4oNvt8Ju//CVHL17wi5/9DLUxmAEiJckiTaw8Wjj6nYw0Tcg6KcNRn/5gwPe+/2OOT8/IneV8NSf3hrTXpr+1xf7Nm/S2t5Ba8ezVKy6mU7xSvD45ZTJdUhnP9vYOO7t73L5zE6Rgtprx7MUznr96wdHRKeW6pLIOJUApoK6ItKLTbtHrdul2u1SnC4qyxtQeZyXCa4xV0Mz1lNAImeCswhmBNPD66REnp2OOj0+JkCQiavyYYdNGEkLiLc2bx1mLsw4awx2tZJPzOS5zeR/c17zzTQ7RyF00baPamGuaUjQARXn53iIaotrVcFmpAA4I2yzsM6nC4W3xGB+McgrnSLOUw5uHcOcQubeFrWFde2ZlTSwMHk0sQGqFjCJqaioMBYZYCBIlcUEPHNWAEtwmUnlBpKOAzAKW8zllWfKLn/+cqiyoq5KiURYti7xh8trQ0kMga4MoDb6o8XmJNjBq99BWUyQ1Ks1Y1zWvXx9xfHrGapWTpimVUKy9RWpN1unw5vvvcePGDe7cu8tyteL1yQn/8//nf2ad55RlSVVWOO8RqMYMSaOUItIRnU6XBw8ecO/ePf6H/+F/5ObNm9y4cQNnDVVVU/kabx2R0vzkRz/i+x9+SDtOePzwS379i5/zuq5YVRVSCFIhaGvNMEnppCm3t7aD1IxWFNairKVarajWa6q8CEAJ13hvfK3B/O2LCn8zg8L/Qctfe3+lLLEx3wSkxPmgVFp6RyUcVgtqBbUEGylcJBu7TIv3gsPbt9ja2uLNN96kPxiSpCm//MWvOD0748vHjzg+OQEPVdUgYxzUdVC8VCoMQ5UKKArhIU4D6WZ7e4vvfudDBoM+rVbMyesXfP7xOZ99/AnL2YyuAkzQ9dnpt2mlMYNOi0gItBQkrYjuoMPhrZvsHBzQanf4+NEXPH/5kt988SnHF1Mqa3jj/g2G+zvs3DhgVVbML1Z8+fgZk/GUvPAsygWCFdPpinb7KZ1Om8GwT6vdYntvmzs3b/Deu2/z5ZdfcX52zqPPv2A1W1OuCzqxp9WK2drapdXuoXTGdF2xyCtWNSgRo1REGVR+Qs/cgbMaLzKEzJAyw9XgSousQBiPcBZp/GYwcCkpHSoPmoO90T/yMshT2M3MaTNc3mTV4UTfQE0va0oh8FqygatK3wQDoRDB4QbXDLudvPYzzSaTSgUtHedANBaezSHuhGBeFkQ6oa3bxLqNVC18KvBphzLOWKgIKxWRUGiliNOYlVeUGHLAqBjpJEQZOu2gtUPKCOEkkbJY71guV5ydXRCpCK0UaZrw7nvvBDJhM3D11lGWObPJmPlsyvHLl7iqwq9rnn72kCivUZWhykt8FWQjtILJbM48zzmZz1lbi4kUc2dQSUJ3OODBe++ytbvL/o2bVGXJp599ztOvnnIxvmAxXlySxhQqJBE6DgABpRgNh2xtb/HDH/yA733/e7z77ru8/dZbtFotoiiiMDVlWfLi2XMW8wXj0wtu3rjBsD/gT/7W3+KD+/d49+Yhn/7ylxy/eMHJ40cIU5M4x+6wTydLSSWYqmSVG8brNTrL2Fsu2Skrah+urUPjvbp2YGxa1N+uwPCNCQr+Wra/WVd6Rv8/LpqAjaPa1yOFbGSKQ1Zn8Y3JB0EQTYVSPmjuaHScsHewz97uLjdv3cQYR1mWPH/2nKPjY7766qvLlohzV/ML54PypZRXSCghQEpJK22zvT3i4GCPmzcPaGUtJpNzLs5PefH0KadHR9iyoJdIROOi1ctS2q2EfrcdbjApaHUy2r0O/a0haacNWvPs6CXPjl5yfHHGqnLB63nQpzvs0+71WBclF5MpZxcT1qsCY5rui3OsVivKcs18PmE+n9LtdohTzcHhPvfu3GG5yME5nkcROeGAjyJFliV0+33iNAOhWBc1q8JQWkEsIoQSGBLwoX9rvAUrqYmIiYmI8V7hnAhqdEZADcI0AeAamowmsAbS2kYAL0yXtLy69Nffb6596CiJa/pHDSpNhAAixSYoBAQWXl4GBS+vBs+m6SVJobDeY3G4ZpDshMRfKqv6EBSbWs8R2kNGJ9Q6IVcRXii0CDOlREesvaf0UHgVBASdwMoIVPAtFkI3rZeAYqrKiuViybm+oNvr0ut2GHTboZxyjnacIhvNqPM4JpWSxckplTFIY5iejXnpBSm6mfk0Qdt71nnOcp2zWK+DWqxSoBRxp8NgZ4e9mzfY2tkhTlNm8wVHR695+vQp0+mMsqiaFq1oXtPAIo6TmChJONjf5/DGId/54H0+/OAD3n3nHbq9LkIE8IVo7vHVcsl0MuHk+JgsilDO89bd27SkQBc51ckJaVVhTo6hLNCmpp8lZGmC9MHzpCgKFqsV2nmKug7CeMggcRKkEkPSuCkFLw+Lb8/6xgSFv35tKOnXB0QbTZSvY42894Eg1tz4DfQo3MQeahN8ESpTY50FKWi1OxweHLC3u8sf/9HfQUnFeDzmi8+/5NWrI7569pyyrkMrgaZlfQmbVw1BKgw1rXPUdU2n02FrtMV/8w/+AcPhgH6vy5NHj3h4espnn3zMYjpnNV+SCUeqILKOfrtNr9VmdzQkTWOyLGEw6NHtdjm4fZMoy1BZyn/69a948vQpX375FeuiIi8t+7e22Nnb4ns//j47+/tk3S4fffGQx0++4vxsAd4TRzHvvvOAXrdLpDXT6QUX4zPG4wmT6ZjZekJv0OPO3bvkqzXr5Yr1eo11Bh0J9g73uXVznzfefodWb0hu4dnJlPPxmoVPyOKEWEZ4H+Otp64N62pNVGqOC82wnTKSfYweYFXB2qyIrUQSBbw5EqXCdZNCBGST28wADPgwIPaXDmu2kcu2za3ezJ4alNPVY+HNN835cHC5MPNhA1QIh0Twb94gkSTxhtFcmkYpVmClwwlBXSpcBFaBJca7mGUpiNces7SUBi7qmFVri5LGPN6BQKJcRGGDtPPCSrJaMDSSmVVkTmFlgpXBuhNhQjWbF5zmBSfHJ3z15BFpknC4t4W3BmzNg5t32Nna4jtvv0vLOHpSMvnqOUXtiZSnnK85zg0H2zsIJGW18U0uOFssWNU1pQ9GQzKKeev997hx8xZvvPMOeVGwWq/4+S+D5/PZyRnz+QJTG2RzuFtriaI4kPOAvZ0dbt2+xX//D/877t69w4fvf0C7lZFJgWgkVLRStKOIrN3hrbt3mfX7dJXmxZOvePSXv+bs8JB2EtONI7aiCHpdzNYIZ2qUc2gd2rbLMmeR50xWa85XaxKCFDpxgm61ELM5XilcMzv6djETvr6+uUHhf8M1u+6qdjWHCIPFjZ4QvtFRt0FlU0sFLshpJzpiezTi5uEhq+WSPC949vw5r14fcTEeU5ka5x1CqWsVDVxKK1wSpjxxHJGmXe7evs3u7i6HBwcURc6rFy95/tXThoi2wteGREgSKUm1YtRu0+906LZaocMtIvr9LXZ2d+kP+jihuJjMefHwEV8+fs7R8RmLvERIQXeYcefeLW7cusHO7h5SaV4fnfDVk6c8/eo5VWXZGg25dfOQO7fv0Om0SeKIreWAnfk209kMBAy2Boy2t6lqw/lF8APOi4AiEQKiOCJtZfRHI9ARq9JwdD5jPF0xt4rSKrSVxE6FtpoVFC5BG8mj0yWDWjGsFa+mFRdLx3kuiCyk3hNZGwr8RvNGioA7F94hnUX65s3WgYToHbLhPSjvkD7YdF4PBkFo4yooXCpjbuZOIgSADTJ1c2C4zU8LcclZqB1BXhuJ0xFWhOqgNDbMqTz40hBJxQRNsqyovGUxn3NWStQm0KECMMFqSueoPSyMoG0k0irWQlPJGJU6VJIiowioGsmPK8FH4T1KeNIkphV3aMURh7u7DDrdADktK+y6IEGiokB2TKOYSGvKylKbkuVqzSzPWVUVy6qiRqDimMHOLt3RiPc+/C5Zq0VtLa9PjhmPx5ycnIQhdFmE11MGUIDf+If4YAB08+YN3n7rLd55603efnCf/f19+p02kQ7uacIahBXBL8RapLW0I41stxF7u4jlkomA5dkpubPMvGNy/Jr1dBoY9A3JsmrMr85mC5ZlybwoWdQ1xpoQdBujq99GHV2bgv/vPaG+seubGxT4Xb6BuLwtvr5+W/dcNL3gjYSE1jpc+0ZUTSNIlEba0I5IlOZwb4/7d+/w6OETjk9O+OSzz1ivcsqqDpmjCpvQbQaiDUJECIGzJiBhvCfNMvb39vjB93/AjcMDbtw44JOPPuYvf/krnj56TLFeEwtFIgRRkqKdp5Ok3Ny7Qa/dJktTzs7OgJjt7UNu3LzDcGvEl08f8eT5K/75v/s3zJYFeWVQGnr9lN3DHh987z3uP3iT3cMbHB+f8eXnD/nNrz/h+YtX1KVjZ3uPH//4R+yMRqRJQprGWGsxxlyqVW7t7WCsI68qnr96xatXRyxWRfDhlZIojsjaLUY7O3gdMV2XPDo6Y34+xxiNqiWylkincBYqK7E2HMDm2YTuuGIwLjl+vWQ5rZguPdqGgKBs4DFoCB7MBKc1hSfGEoWOMJE3KO9QrkY7h3Yu6A754NK2CQQb9SJ5rZ94yae9Rm/2gBPh0LANwKmhpuERWB8CR72By6oI4hZWKnIhWVrL2jrW3mOkwCxy5MUKkWYYJaiNYbVuEFxSIqIkDLetCj7QTjIvFb06BIolCaVO0a2YKGuj4xRE3iCQfFD8VYpWGtFtZ+yORhxsb7O/vcXBcAuNpFquqRdLivGMxAtaSYuD7X3SNEUpxYsXL5gvl5xPpyzritxaFoCMY5JWi7tvvsGte3f5W3/3j7kYj/n8i8/5/MsvOX79mtlkgrUOa0NAkDJUVJvX0uCJ0oR333uXH//wB/zB97/He2++RafdJs0SLiGCZc4lk9xasI6OUnQ6HXZbLUYCxp0Wf/av/pTlZMJ6MsGsA0dBGBOY91qxKtbM1znPz89Zm3AtVt5T1cG7OTeWytomMDT3rbjaE/+leib8desbHRR+37qOHLiOPIIQDIJOT4MEsgFCWFdVI9GsSHVEqiIypRl1WsxsTT6f8+f/4c/46Fd/wWy5xrlN5hmysbBxJFJIfKPPnrVbGGupqgohPHEc8+DeXe7dvct777zLqD+gWOf83/4v/1dm4zHzyRRbFGjrkD5oCiVRxLDbIY0i6rJi4Tzr9ZrTiwvkdMqiyPnFRx8jpODF2SnzfMl0kVM5h4gE+wd93n7nDf7Bf/Mn3Lh5iyTN+OSzL/n880f8x//4C05Pz3G1ZdDL2B512d4aYeqSs8WEL7/4gtoYrLXcuHWL3qCPSjOOXr/m5asjTs/PKKqCViehHUd00pjbd25x+85t9g4PyVdrJrM5F7lnVgqqWqN8hpQxuDgIyUmJUUGlc3pRoSYV+tUEs1rja0uku0QSrBRoGTJ+5z3aWxQWSY1vSGJhbhxaR84FdMmmKpB4tAgEPy0aU/cNYampPII6qrw8kzbkNNuglxwO23DajHPX4KkSR7DqrJ2gcmHO5JRGJe3Q+44lWRRjpKRUmkpGGKcxHgQxSZZSWkfhPV7GoBRSRTgRxAvzMgejiVc1ayuwKqbTbTHa2WX/cJ/5ssA6y2ptabdTtoYDvv/hd9jb2ebe4SGL8ZjZ+Tm/+vQh5XrNejxvZMdhqzckSRLStMV0PmexXHI2mVGamkpqjHI4Kej3ewx2drj9xht88MMfMtre4ee/+AUvXr7k888/Z3JxRlGsgzWt81jnG9SpaDglHqkUf//v/zFvvvGA//bv/z1uHRxwY2+XTqRRVYEfXzA5O2M+noC1TY0m6PS6ZO022XAY7u6igOkEphPseEx1MWZ9cUGkZPCv0DGlNSyXa47GU2brnPMqMK1L7ykIVLlKeGo8dYMQsw2Uy3+NEPjtW9+4oOCbls9fu8TmH7/5f3h4A0ndQAibzetdgOWFw0IRK0WiNO04ptKasiyZnJ1jraW0Hh1FdDvtIKfARkPpEt/C5i9u/l6WpbRbbQ4ODtjf32d3d5dqnTObTPjys8+xZYVwlkyq8ByECA5pUUw7y4iUxJgaY2vAs8zXOO/JbU1tDLU1nK8CH8HHilY7JckSbt054M69O9y7/wClNGVZ8erFES9fvOT1qyNq26iMKhEgmWWJtRVlWTCdTcmLnKKsiNKUoq7xMubFiyOev3jBcrmirmu0EmStmF63w/bOFsPRkCTNOL+YcjqesagcKyup0UiRIESMFzEIBSIKjmreIY3BuxpnSrTxaC/pyCic0c4jhSFwoG2oBr27fO0loIRv2KuBR6KlDONcDzESDSQieDMoEfgdUoSPJaHNp6T6WlDwNEHBuxAUPA1azWHZBIVQKUReUFqQDcnaEp6DlME32KgII2VoN3mJMzSQTAkqpsYinMPKBCEVVkZ4qXG+xoqI2kvyylLUlso4OnFCq91mOOiTtRLW65wcS6I13VbGjf099rd36KYZi8qwuJhw+uo1xXJFuVjSSjNaWdaI5EVUtWG5WjOZL1gUBcaFykYkMYlW9Hd32NrbZ//GDVrtDh7B06fPgtT762NMVeCcaVRqaYJmONSjSJOlGZ1Omw/ef59333mL9955i2G7TS/LcMsFbp1Tn5wxf/6c8+NjvGleSARmZxs7HKCa+83nBauTExYnJ5jFErde48sS4hi0wuDIq5p5njPLS2ZFRe5CAKiACqgJqLCNoOEVsfXb2TK6vr5xQQGats/vNI/+iu/92mfhjhcE1Il1wZ5RIUILRAjaOmKQtdju9djqdtB1TR3HVFVFXdesygpjLavpFKGCPEUUx1gvMNagRWgFLGdTslbGztaIt99+h73dXd584wF1WfLk4SP+/D/8GWfHJ8hGo0V6T+IcaRTmF91Om267RZJElFXF0fHrcEhXBavShWxsNQ+VuYSkFxRRu4M+7334Prfv3uanP/4hUgrW65xf/vJnPHv6nI8++oTlqiCONHEksc6zmOd8/ukXzCYX/PAPvsdwOOBHP/khL1+95umz5/zFr3/DKi8oa5rWgMNZh5SeVgK9w13u3L7Fh9/7kJ2dbeZ5zS8//oLffPQ5z8Yl3mek3R2qIsIahZcJCIVojHIknl4rAVNBEWxDpbPYumxenyooRjiLcDXKB2XRxJXEWNrKEUtPLAUJgkhoWlGC9qGllHhQHiKCV4ZugsNGMUmKUDUofyWN4huAgvW2scV0lwxj21QK1oMRG5hq1GieKgoPBkkpE3LryY1jWiyovMAKFdBJXuKiFKII0dJEMsFoRRWlOK3wOqKmovYVUiZ476gqz+npOcPRgNHOiNGwxztv3efs5BRf1dSrim6sGGQxbSEoJxP+l3/2L5icnDE7P6cVxWRxzM3dA7qdDlmWMV/lXMzHvDo7DzaaxjCrCpwQyCjm5v277B4e8OEPv0+UZnil+Pf//j/w9PlLHn/1PCjVChFY4M5ifPC2Q4SAGMcxB7dv8uM/+AP+zh/9IX/44z9gdzRiu5MhV2s4P2fx5Anr8zNOPv2C02fPuTg6YjWZBdkXpdja2aU/HHH7wX1kpLHW8Itf/ILnz5+H2YnWDFttcmPIi5JX0ymzsuQiz5lUNYVzFCqi9I7SW4wXpEIhdIKKYqI4RikZxh/4S22E33+G/Je/vpFBAbhiJvP1mcHv+wiuD5sb5unlzzXZ/gao5C3eGZwxQVMoChWDMYEtqRfLYF1Z1YH06jy+QVjEUhFFGmQw5hltb3Hr9m0ODg5ptdrMLsZMxhecHB0xPjujXC2JhEA1UNN+2iJNYrpZQqIDdHC1LimqktKWeA1ax7RbQRROxRHtdos0SwMUtd2iNxxy8/ZNhltDLsYTptMZz5495fHjx4zHEzq9PqPtPVqtDqvVmjwvePHqGCE84/GYZ8+esVwuOLx5g36/x82bt5jOlhjrWa7Wl6+1kp5YS7rdlN3dHW7eukl/METqhLOLGcdnM16fzSidBhHjjcKicWhsk4ZLD5EIEEVnbCOD4VDWoZxFW0vsDCmWDEMkHJn0xB5SBG0lSQR0tCRWnliGqkDhiAi6StJD3FzjyHs0Ptiu2pAihMCwgaiGjSUb+GRACYSg5b1FiZD9Ohf6zxbQ3jdENUskBFZKNBKDIMKRKElLRiRCUnkopGLtBIWDlfQYb6jLAiEVlZTY2iK0wsURWjmgpiVCuyPGUS4WrKYTMDVZpNke9OlmCa0ozKFSKcm0JnJhEF8vc6gMsZD0WmEm1coyEIKiqpitVyzWOYuyDINtHD6KaXXa7B4ccHjnFsPtbUpjmFycc3p+wdNnzzg+PaPIi0Dg07p56YKWlFIaHSWMtrYYjrb4yR/+Ie+/+w7vv/suu1tbdNMEWVVUsxnV2QWnTx6xPD7l/NEj8vMLxGxGVpYNGkxiL8YsVmuerVegFA4opzNSIYnTBOM9RVkxy9csq4rpOmdR1yzqmty5UBkIgUEQ4AoNGV6G4O8aIqy/5K58W8GoYX0jg8Jvt4+uo4vCB3xtCn39+4MMwVUeEA6GRrpCBKlia2pMXSG8D6Vzp4N3gTUrPeRFgfSeygSnrdrWSK2JdYROYnQcM9re4ebt23zw4XeIopi6qvn04494+fw5jx9+iSuDaFcr0mil0EiGvQ6tJCicIjzO1cyXU4q6onQlUZaQJRm6lRLF4cbd2d1hOBiy15T1veGQOInxwKMvH/LVV1/x53/+56zXOVIKPvzwe+zvH3Dv7n1evz5hMgl6RpPpmIuLCx49esRkMmLvYJ9+f8BguMXxyTnGwHhSNGelQAlHlmq2hn0Obxxy9/59esMRde04Ojnh1cmE12dzVLqLEAmmVuA1Xmgqt0HHWLQKbmeuqJGmRlU12lVE3hKZitQa2r6mJQwxjo70pEAqBD2pSKWkoyFREEtP1IjR+aposr4wVJYEVz3ZVGWSBpZ6jbfiGx5E8GPehIrNzMgFjkKADFz2y60Ijxvn8SoY8MQi8F4Sb/GRxquIvtYYBAWCpYPceebOUzjLvKyQIng41L7AKoVIImQsUMrTESCFJ/aecj5jeXEBVUlLK3ZHA/qtlHGsSSRkStJWEdo6MA5R1MReoKKUrf6ALE2J05R1GSw4x/M5i6IM6CIR5jeq1aK3s8Pb3/2Q7b1dsk6b45NjXr1+zW8+/pjziwmrVYF1EqnCfO7SrEiKsDdbbe7fv8fd+/f5n/7P/yMHe7sc7O7QiTXKGriYU15cMHv1gqPPPmPx+pjpl4/RtUFbSweFINyP+XjM0lqOnzzGCglRRNxp008zkm6XRZ5zPr7gfDZnVhSMq4qVsyycZQ0YBIZQ1RkI7UARYONOhusdzoVvMxD1an3jgsJfN08IhCZ/OSQMS16pJPtNv7CxSlHNpxKEkngJpa1YVzmLfMHZ+JxivaIo1rTjmCSK2Bp0saZFP29TFCVVXVPUBuOC2FikNJ1M83d/9COiOKYcT/jq9WumkynPvvqKfLUisQ6lgkfsIE1JIkWqNf1ORpYmDEcDuv0e3UGXpJvhBCxMSZTG6CymPxoRJUFTfuMUtVrnrFZLnn/8jJOzc6bTOS9fvGS5WjGdLuj3+/R6PbZ39xiMtoizDBlpsk6bP/77f8Lr10d89eQJvX6PbrdDlnYw1lGsSopVQbUuiRw4Z/He0+ppRsMe7737Nm+88YAbt2+zrjxn5zN+8ZtHnFwUWNEhS4cIH2PqCAwIa0mNIxaSTCoyUxI5g1pNUaYiqguGGjLh6QtDSzo6WNrakuDpSk/sLTGO1NVE3hLXFlVbpHBIZxoegg1zBSEvGc9YixKycUNwV0CEDU/p8lAQWCv52vJXMNVNheERqCa5jKRsNJgqKuvwQtJJUqo8SIFkMsJJiRGSgRRUQlAmmhrBGkGOpfSeBVDYmnm5YJ1XVBhiXSOSMCwvjp4xFQXV+XtkAm5vb3F3dwc7X7I8nSLKgvHREZ8XlghF6iXddp+or0jiFOs8pxdjpusV8zxnvM4pnWMtBSKOiFoZf/vv/T1G29ts7+5yfHzEVy+e8/EnHzOfzxlPptTN/o3iJLC4m6G+0pLRaMjNm7d56623+Tt/94+5e+cO33nnXRKtSKRAVjVUJW4xpxyPWZ+cUF1c4GczWrYmdsGMSTuLcwElFIvQ4lVxjNMal2SUCIqy5mR9yqwoOJ7POctXLE3N3HtKPCVBydgAta0v50BeNJWCCKZEtXOXZDzfXF1JmCd9G4PENy4oXF9/1dA5tIXF1x757RbT5ZevDxYFWO8wzlJbQ1lXFFVJVkVBYjeO0FJjVRD00ghqrYm0oapryAtUo20UIzBFyXQ25fzoiOl0xno6xVlDhCeSklgpuq0WsZYkOjieKSWIk4h2t8VgOKC91QMtaZkKEStkpGj3ukil8FJQlSVlWTGejJnN5hy9es3xyRnT6Yyjo5PGL5dGZkAgtUbIAMTMi4K8LNja3mI02qKqSrIsI04SyqoO2vnzJfkqpy7rJrMO9K1Ou8No2Ofw8IDhaESWtVmsCi4mC45PJqwLCyJGEiHQKCeCs5XzKGtIhKDlHS1fh6BQF0S2InUVIy9oSRgqS+ocLWHoCEssQtYcCUuMJfYW5S3KVohGCEl4G/wxaN4EgabtwzBR4ZsDPewER9ChQgh8453jhb+GWhOX/9vIo/jrG4fLeEIgxhFc/IQj8hZna2xt0NqBVzgl0V6GVo8AI4IBT+EFJZ7Uw9pbFBWRKyl9TSwbXafKY2dTypamns+Is4xeHLPd7TLv9eklMc546nXOSs5IVEysNEkUk0QxxjsqYxpmch4k0a3FSkmUZrSHAzrDAbuHh2TtNmVdcTGdcHxyzNn5Gfm6oCrLxkNCXQE6RBgmJ2nMwcEN7t+/z/vvv8/bb73N4UGYX2BqXFXivYGqolqvKRcL8tmUerXCFjkRYe6jnQvCfNbhjUEqHZI2pbAqtNmMdeTWMMnXzMqSWVmwNIaVs+SEYLAJCJtZ0EYy0xE8NjaPBY5CUzFcXtcGqPItDAvfuKBw/XAX1w773xXIa75HyGsfi2vvPdYHRUUvJAZH7S21sxgcTnisCO9RMNgesbezzfx8QpkXlMLR67bRKsJ5WOdF8Fiua6r5jH//r/6UsiyZTqeNAJgn05oNziGRklaa8satm3hvMaZmuZpT1h4ZSVQSodKY0lmcsdQ4FtMFyzzn9OKC5WrFxcU5y2VwbSuKAmcdzlqSLEVKRV46nAuIwPF0Rl7WjCczhIzQccqnn3/OxcUF5xdjbt++zd/+u3/COl8zXyz4za//kpPXx7w+es18tsYah0SipUdrwXtvPeDu/dv85Ed/QNYe4on59PMvefb8mCdfHeNchBYZFA7lLYn1JK7xTqhzImvJnKGLJcPSpaKtHYNEMkoULSUYCIGocsjXJLZCe0cqBIkI8wNpDMJZXFXgXRh0yoaM2EozrLVYE7gWQsgQEFUwgq9tEGYzeIRqeAJJgsdjnW0UuEXQF2r8n10jordJRkRTOYCnbmSgL0XxhMSFHBXp64ZAJxFoIg/OCeq6wCmFlzG1UhgkS1tSac+ehBxJiWZua1a2ZD5f492aslixfPwVW3u7jHb3+M7hbYY+Zv7Va6azJYvZmiyDTCtavTYQ2PrnF2csi5zxasnCVKxtDVmLrNNh+/Ytvv+jH3H/rbeYzOccHb/mZz//GednJyzn8wDTFKC1pjQW6yq88ygdKtb9vR329nb4R//oH/Hee+/zgx/8kE67jVYKW9cUiwX5fMZ2GoVq5vUxJy+ec/zkMZOT18g8Z0crqGtcXbFeLrHW44RAt1oorRGxxiJZ1IbTdcGsKnm1nLMwNWNbsgJKYM3Xg8LmVLgMCt4316pBlW2CQsOACYkCl0nAty0wfOOCwvV1VexfBYTLy9fcuF+rEPyG4HbFOHY+kJLqBjkhtAyWihLiLCFJY9568w3u3LzJ7vY27q5htVhy9OIVi9mCYl1Q10FWYTDoUZQVxljy+Zy6rhHWor1FAJGEWGuSVkqn1SKONMv5lKqpSNZlAUKwNI70+Jys08bFQVzN4MjrmrKumC3XlFXFahV05I0xSO1J04jR1oA33nyD4XDIx58+ZDKZcXp2Rl056tqwWuUMBp5W1mZnew9rPU+fPmOxWDKZTFmslqzzNa9evmK1WJKXJVJttIA83XaLfq/Ndz98j9t3brGztcP5eMX5+IKHXz7l7HyGJkLKBOkjktqhXElUWTLniJ0jqyoS7+gKT196Mjx9ZWkJS0dYuqYkNY7MVWhXo6nR3iBdaCvIprMfmN0Q6ZgrqYrwUV5uqGgKogiExGtF3QyLC6ewQmA27jZKIrRseAgiBAU2gngC6a/E78LWaeQ2lESIrx801tQIoJYuWGR6gVNhLiCFC3LaQjRsbIMzHtUov7Z8mJd0tKRqeuBtocnxDBAUOFRecf7Zl4jpkiS36OmSdl4zkholYyJt6UdJ87oIFuuceb7mYrEgNxVLU2GkREcZ2zduMtrb453vf5dWrxcSgo8/5uz8jPFkTFEUWOuo6iAvLbwPGlxKg9J4/KW3uLMeZz2mtlRVjWgHwPBqlfPy+XOePfySG/0OHSXpOke73WZvb5/61RG1daxmSyhLqCusUnglkZHGpzF1FLH0jqW1nFaGs6JgWtVcmGZ+ABSEQFASQACG0CK6vGibOfKmO3AdlnIJY/+2hYDfXX8Dg8JVWf77yrf/LCDq1wbN1z752iApqJZa5zA+OF0ZZxFNQPASklZGO0t5+4P3ubG3x9ZoRD9rM5tM0VHE4y8fs1guKcqSKIoY9HuUZU1ZlLx8+Sr4K8sr5mzkDO0oZdDrMhwOEQJevXpFXhasi5zcOGrvyc8mWMAKcKp5+kqEnqgXBDn6EMxc4wnR7Ue028FH+Yc//CF37t4mSmKePn3OYjmnrguMcUHP3jqyrMPe3gHGOP7i17/m1dFrnnz1lNliQVXXWGsa/L8k1oE/gbMMh21uHO7xve9+wI0bN+h0Rzx/fsZXT57y6MuvWK8Nse4RkaCFRhcWZWqioqBlalJn6TlLW8BQCwZC0pKCAZYEQ+Yq0qpCO0Nc58QSMiUQ3oCzeFM3VYFDNJLkcZw2pERB7YKm0ipfI5VGKoXWKSiJV5LKW4xzrHFYGcxsvBLNmwq2lq6pCi77y6JRSt1cCnnJd9GRQjZsZNcQF00ZiJEb8W5kEFmUBCOXWAUOg6iCZpF3Jjx/KWghEFKhVNQ8H0VLKCohKVTMrC6oCsP5x18ip2s6tUAUhnRVMESjVUQSObpRgtQxSydYrNccX1wwrwpKb1l7S9TKSFptDm/f5ua9e/z4p3+Lpy9e8PzVK/7iL/6C2WKOMRXOGpx3FGWNIBgpyShqWjqaujaUVUld1ZjakK9L1quc5WJFv9tHCsl6tebF8xf88pe/5GI0YKfb4Xu3btDpdOnuHzLvP2FeFCyOzxB1hTQGHSVIrZFpitEaoyTzsmZa1xyvC86Kknldc2ErCmAFzTA58BAufS+uHSf+8p9rR8U1aZPrs8hvc2D4GxgU/o9e4nc/brKdKI4QJhDCnLUNGzMYkas4YbSzTbfTZrS7zWePHnJ2esIHb79HpDQyjZFZjI81r5+/QgpBt9Nmd3uH0daQLAnYcik8WIPEkyURSgUVTGQgwf3wD36AjCOINKeTMZPFnM8eP2axLinzChVJslbGweEN+oMh3W4XqSJWqzXPXrzk4uKC5WpJEie0sxaj0YBur0231+G9994Nvf5lwYsXx6xXBbPpjJPjU572nhPHCaPRFnhBvi4oyorahGJaSlBKopvDLooVh4fb/ORHP+THf/B9bt04wDnLr3/5Sz755AmPHr9E5CWZlaQCMulCz79YENU1raqi60pazrKrJV0t2Yo0PWXJgJav0NYQ2QptKqQzaBc4HNqFWYCQApklbMToTIMYmdsaazzGbw4Cieh1AjkJ0fSULbUNhjVWeOpUY/FUWEosNZayMkHquhG5C7Pp6lK3J+wdGsTSplUUBtVSNtBiKUkjhY4kiVIIp5HeE7mgqRULhbAOYeyVdr/wSBlUdJUD6RxUNd6Htk/sbZg1aUnkJaXzzF6fc3Qy5cWvv0AmGUhNWygSGdPvpOS1ZZkveHIxZlqVLOqKHIdMEw73d7l19x4Ht25zeP8elTH883/xp/zm04958vwpi+UK6yzO28uKu9trXyrHrovgjYCsEEISx5rZdEK5zvl//7/+Kb+5c5uP/vI3/OQnP+LmjRu8/dab/OFPf8KHbz7gy1/9gmIy4dEXX7KlNVtKsbd/SOIFpw+/IlEaFaeINMUphVGaWVWyKHJerwsmVcXLdcHUBemQJVfVQZgfgJWykSXxl4BjIUKAvmw3N5cuKOvS6GRdg6J9i9c3Kij8nuP96w/461/cDAHF1z7316uI3/olm36jVIokTuj0erRaGUIpLqZTnr14yeH+DVpZhhIhczc+aAEpKUmtIWll9Hp9cB7nwvBTuaCemsSNvEZTsUgt2TnYA6WxUkCWoOcZz85OWBuHzSviKOgJ7R8c0O/36XQ6pGmLxXLFar2mLAvqukJK1WTFGtcosRrjiKKY7e0d8nXNIl4TaQ3eU5UlWZaitQ42iLXBVOZSMVg2B12kBVkSbAzv3bnJnds3ODw8oCpLFosVr56/ZHx2Tj5fEDcon7iuSCSkKGJbEXtDVxj6wtFWji0FHeEZ4Ok6SPCkrgpaRs6gvEX6DZT0unduY3spJF4JjAPjofRQe4Hx4WAQjQlN1bCPg7ZNyCANrlHkFlgctXBNUAgy1Z6GDdiw3m2jk+XsNeSb93jfwBgbiXQpg7m9Ep5MCrT0wTBHhOG89g7lBYkMw3bpGsYz4U9FTVCJNvIpYTOGQxlQDoT1JCJULevaYU1OUS+JWjUqTsi6fYyQaKFYViVlVbHIV6ytpXAWpxVxmjLa2WW4s8NgawvjHLPFkidPnvDy5UtOT05RUQSN1ajaqAA00GGa6tQ1TnhCEljZzuOMYb1cMh2POT56xZNHQ8p8zWjQpR1FbA2HbA+HLI2hXq8oTcHCBY5BVdsgfaI0XkdYpbFCUjjPrKqZlRWTsmRWG5bWsOaqXXQ1UN4wqa+0b6/f7JfHQ/OayibAS7/5ePNT3+7g8I0KCpslvhYBaML+9fJPXhsqy6th8+XXg8m6rR3O+ibL0yihccaRJS22trYo8ltICbPlipevT3j09AVvv/s+VkriKGJRl8yrgpXzwSO50+LG3VvsbO/wl7/8FdW6pq5KUh00WWxVUdeGqqxp97pk/S633nyD8XzO8fkZ+3dv0yt3eT6+YF55ysmKUbfL7sEhP/7xjxtWtWF/f588z4OFoHcI4anqNaLRbRmPL3De8qtffkIUZ7zzznvs7txgvcpZL9d0Ol1aSRz0b6yl1+qBE6zWK+JIBmCJcCQaWqnie995i1u3DvnjP/pDRoMh3U6Hn/3Zf+L10TGff/qEau2g9GypFG89ZnZBR0a0pWLoDB0JW5lgKCRdBCNvSZwhs5a4kThOnG3abE0QECDUpjUjKGyNcZZ1VWFlIIm5KMIpSZ3EWCGxQgasPSFYr6qKdVWxrHJq76kIZko1gdBkN1h1LfFSINIEoQUyAhVF4SCU6koeRelG9tk184PgV+2dw7sK58LjwrnQ6qrWYGwwAa8CxyVusvlYRqQqRktBrCSpkkRSkIogzZERmNfKB91UgUdZR4okRhIlbUplKYRBpW1EkiCTjLVxLGrDcjJhXBQsqpw5jiWObmeH/t4eb3/3u8RJSuUcf/bv/j3HJyc8fPSIyprQGpNNj90GYppSKlSQLswLamMvTaK8cRhf0dnuM+j2uHv3Fq1WC1uV/Pt/86+JtObhx3/J+2+8wXffeZv33ngDbt7k5W9+w/HDh3z68BHT5y9x65yo1QcpqaWgFpLcGE4XC85XK6Zlwak15HjmiGao7C/nBzWXZnohaSB8YglHhSZYwAqCeq52EmUF2oC2HunCm7gMLd/e9Y0MCr9DMfnaDKF5aDNoDp98XT6bkBU4AfiN8YdqVE0laatFtz8gPjtluVzw6Wefcz6eBIJSI2tgXBAK80qhEolONXGW0hsOGYyGrKuSvMgxdQU+QktBVeWAQCjJ9uEBw60tTicTnr96xeNnT/lBr4vQiqxRjIwTRa/fYzAIvIVHjx7x8sXLxqxHkqYxrVZKO0vxlGgt0UrgnKPICx4/+Yos6yBVQqQTev0+aZzhXWAvn56eMp3OWCyW1HUV+sV4lBC0Oym72yMO97b58Q9/wOH+Hofb28zGU46/esbzLx4zPptgxgtULYisJHMebUELSxdBm1AVtAQMpaPnHZl3tG1N7AyJMU2ryKJ8EwjYZHsBSrjBlFslAhwxUtQSKgE5HoMhNy445zlP7jzGQeHC14xw0JLISKFbGVkS0dI6HKJao5IYlSToOCLrD5A6DFBpoLuboIAUjZBieIbeBemLYOXpwZvGozkgwLy1uKLEVjWuqikWK2xlcGWFKx2utizKCmdqbJUTQwgG1pFJTT+KaaFCALAh0AjX/G5nqW2N1hH9rAU6wglJWVVh2FtbgKv932ih5KZmslzw+NmzS8LdV8+eMV8uAiyzcSqSzfBdaY0ggDFEEwQiHbScnHdYZ2i12mwNR7x57z5bgyH9fo+yKIKw3uvX1GXB8vSU6YvnLI5e8d6tW6TA5MVLzk9OmU1n4fc3YIDSWGprmeUFq7rmbJ0zrisWzrIkiNkVUobr7a8Uazf8A65VCeFo3+geNP/6DRpRBv9tfj9q8du8vlFB4fec/X/td2405rmGQrryNgj3ygaRFNQyFQhFkqR0ul2UjsiLgi8ePuJiOsV4gja8kFjv8SIc8DqWRE1QaPe6tHq9wBitCry1xFEwq1+WZaN+GjPa22MwGnEynvD01Us+f/SQN7/zHdq9LnHaIk6boNDr0e33yNotJtMpDx8/Ynt7m067TZLEtLKUdiujtiuiSKO1wjsbHOFevKDd6tHtjtjbO6DdzohVwmI+5+LigsePH3NxMWa5WiIl6KDQQawVw26HW4d7vP3Gfb73wfvsbI3oRJrXj5/y+JPPeP34Gav5CjevSdAkaDrOkXhBB0lXGFpItrUiw9PF0faWxFtariIyhqiukKYK/dwNvFOElpAFygYyWgOoBK8kNtaUwlPgmZmK0lmWriK3NYU1rAxUTpBbkIlAxoJ2LyNpZbS2hiTdDlGWkrQ7RElC2m6TZC3iNGWwvRc8MaQMcwUhkFpeHqobDPumQnPeXWs5NN7OeGxtcNZg8wJTVtRFyeJiQlUU5IsV6/mKfJmzGk8ocseqLNGNvEdWe9o6wkmBFYIMSIwNmax1wTrTGKyriVqaTpxgtcYIEUQLrceaRti7eU29AC8lRV1hlguePH9GVVvKuub49ITamgDVpTH5EQIpFSrS1HXDkSAgpCKlEDocG7WrGQ0H3L93h3ffeZut4RBvLaenp5yfnTI5O2U+mfAiL1idHFOcnSHefZdeklCfnTM/PWcxW5AhEFrjpKKwBWtrOV3nLOuKszxn7g1r71gR5CpKNqJ2Vy2jEPwaD+0NCs370CVo+AdX2KJrTcm/Kh78VjPi27S+UUHhf8/yDeRANPDTMGwKOYSrfUMY0ygdoXSEjhNq45gvVjx98YKXL1/w+Mlz6tqgpAqIHwIxytogTLe1vcNoOOLBG28wW6+ZPv2Kl+en9Hs93nn3HfqdNlIIjo6OEEoRJQnt3V2s1vzsz/4j4+mUEkleG2RpKCtDkmXs7O6xs7NDp9PhfDLmbHzO6cUJZ9NTUNvs7e5y684B29s9jLlH1k7YPdymrEouzsfUteX8Ysyvfv0XtLJHQQ2zMlRVRZkXOFvhsSgNqgkK7717n4O9Hb73nfe4sb/Lzf09RG14/fARv/5PP2d6csHsbIya1/RKh157BlrQU5ItrYOoX1UyiBLakUQWq9Ae8o7I2cbjIJDOtK+R0oS2V6NBY6WkUopaSNZSBb0gBKUSGCFYecPKVKxMxbiuqLBUkSfttUg7fbZ2hsStlGzQpd1v0+q2Ge7vkLQyOv0+sqkQKhMgukVRUjYtkWeLk1AJNnDLAFNtnMKURoimfSQ2Hs++aR05TFUGLL93GFPhrUOYIJCoWgmD0V2SKKKbZUE0Ec9sMmG1XDE+O2M1nlLMFpw9fEa5zHk5W5FVS2ILAxSpkLSlpCWD3k8rboMU+CrHOEMtGmKXdRTGsizyMFz2BtMkSGXtWBnD+OlTUBInJau6BAGpjokaldi8KnHGIkwdYLfN/3Ce2hharZRut8sf/8nfYTAYMBj0OXv9modffs6zJ0+YT6dMLyb4IieyhgzP6viYL2dz/ItX9NOUYZIEjStgWRbUxrDMc+ZFwbKqOM0L1s4ya6QqSgSV0hg8ubWEndusppoMMds3zINw3zeskeaObc6E5s1C2HNCBgveBnV4KXu8+eZv2fpGBIX/vOrgr/iJ6x9uov9l5eAvmatXyp+Ssq5ZLJacnp1zMZ6EstwFH95N9hFpTRQlxHFCrGO6vR69Xp/Ves1yuSSvKnpSknU7pJ0OUgjSTgekRMcJRBG1c5xdjFmuV5S1Ce0pQCpNmmR0ul063S5JmrJerynKgqqumc3npGnKntgla2XEkaYocqQSrFZrptMZk+kMZ8PBN5/PydcVQqgm87OYuibWMng9RIJup8Vo2OXtN+5x42CPN+/doZulpEJw8vqYi5NTTp8+p5ytcMuCpFREVtASiqFQ9KViS0AMJN7Rc4bMenAG0ZjdhGHrFUVIiIZJjsA0N6WRUEhBJQW5kuTes3awdEEPf+EcBYYCS92JEbGmO2jRHfboDLr09kYk7ZT2qEu71yFtt0h7HYRWGKGw3mFtRW2DT4LVChFptINYKpAKGSXB0UypEBRkmC1IGV3OqERDiLhs5zRBAe+o6zKohhoT5NW9xyuJkZJcQKR8QB51M9JEMUw0vdEQuy5IVUoxmbE6OsNdLLDrkrJ2aEl4nkoTSYmUTSXQtDxFI+DnIMxPnKNyzX8jQe/H+qADVHkHvskEGt9wL4L/weUp2CC7hGy+5jyRUqRJzO3bt9nb2+XmjZsIPKvlgvPTU8bn55weH1Ou11SrFQke7T0RoK1FlCV2vca4QOsTQqIaobrSOWZlybysWFQVc2vIvWOFJwcqBDUBYVYjrlUHgYF+aal8PfkX4b/He3c1Z+CqCNi0mPy1//3X9Q0JCn/VujTU+VoVuBkwhx0iGxXO6zMF59zlBvAe6tqyXuXkeYmUitl8zrOXL/j408+ZTSdEWuBqH0xWrEdJTX+4xWg0wRmHUorRcMhwe5tf//rXvHjxgtLaMG9IU2SaIaUkHfbDc1Ka2sO6KHh5ckxRVqHH64P3bafbwwtJnGXsH9wgiiMuJhPWeeAaPH/+groy3Lxxi06nTRxFvHr1gslkyvHnRxyfnDKbzbFNOyEvClauuMJpN1A8b0Er6Hc0H7x3l5/++If86AffZ2drxDBrcfriJS8fPeHn//rfMj4+pbyYEjtB20m6NqYtI/azNgOl6QpJz1kiLAkOlS+ROCIZRM69C9o9my6RbMbKlgANXWOppaASkpWSVFKyVLCwjpk3nK+XrGrDtAbdksRdza237zHa2+bBB+8w3B3R2x4Sd1N0rIk6KUIrUJKT8QXj6ZSHT55wfjFmuVyjVUKn3WN//5C9vX16vT4H/S3iNCVtdYizDKWj4KQmFUJolNQNaEE2FYK/ZFLXZQHCIwRUZYGta8oiZ7mYs1osOHrxnNVsxsX5Gc6U4Gq2RgO6nS4HN/a5ubPHqN3DjVfMjs94+fGXPP3VR0xeHGFPzxFxQrvbpas1kffkkwlxHJNmGagI0QxSja0pvGGFIyf4SzsfzGVqAppK6hivAsIqyVK891gXVICttcRxjBQKYwMfxOLx1tJutbh18xb/5J/8E957712OX73k048/5l//qz9lcnpCsV5hqkbCRAlaUhIJQYxjGMdsd7ocDAa04pgIwkEtBLWOWNeG4zwEhWVdMcZSAjkBZVThqawBBEpsVFl9c+87NoaaAX4quCSnNegw1xBIm+9oQoALApj+ykrpv66/kUHhOiTs+vrdeiEk/b9Ndvutn/BB9vg6Y1GIAKNLohRjahDBYEVKeek25hrnKOvBG09INhwvXh1hrKPV7nJweIv9/ZtYY3DWcnYx4fXJGa9PzlkXhlVRMV0t6Q4HtDsdOoNeY3FpOTk94ez8nKKyGOcREl69PsJ4x3Bnh539g8B8lZLZfM7HH3/OyfGYsvCMLxYUhWWdG6I4QinJYrGgqkry9YrlMqcqgwwBgoB8avqscSxI04hOO+P+nZvsbI14/+0H7G1vcbi3S4ZndnzMF4+fcvbiFafPXjB/9gq5LhgZT4akJRTbaUJbRWxFko73ZN4SVznaGhJbEyuBFhsr0s1wP7z+QaFSIpUm95bKe1YyplKSSkdMrGXtHBemZGENU1tDLyZq93nvzl229rbYPthisLdF3E7Jhl1krCkjmOdL6qVhdVxQmODPW9QGIRX9nUP2b79FnLTIsh5xktJudUmTlDhKSFphjqSjGKkCMc7LptcuZNM+2gwnaarMIBCokg6bvFOnFd5ZWsbQHmxTlyWj/ZvUVUWZLzFVgalK8tWcMi94cTrh5GRCjGAnapNfTDk+PmZZl/hY0R72SGXQvdqI/cdJDEJSVDVL4SiEZCkUK2NZOSi9okRRYAKZS2wQrgE66p0NnhFKNexsQRxFwd8BgdKafpKys7vLYDDgxo2btLIW3XaHs4sz/r//5pjPPvqYi5MTxqdn2HWJMp4EQeIhdZ6uhEwpdoYdBu0Ow26HllboZj+sy4JVVXO2WLEsKybGkQtJoRNUJIkE1N6SiKBhlcigXOUJpFPfiBk6bzG2vvTYlo0XBlJhjQUPsY4aEIAL0OFIoSKF1HLjFnoJub0cXn5LC4e/gUHhd1fT8fkrvvb72QubDdN8cnmBr7uvxVEcymRnUSqU4IG0sxlEh7TWNrhm5z0np2coqdjb3Wdvd59up0uZF0wnE45PnnI+njCezChqy7qomCwW7FuL1JrBYEBtDEWe8+Wjh7x8+YraBKcqKeDk7AyhFdtN5trpdHn58iWT2Zwnj58ym84xNSwWOYtFztHri8uSuTn/g/x3M31LIlBaEMeSjRJ0p6Xp9Vps7wz47nfe5N6tW/zRT39ELCTSOo6fv2R6csrHP/8Fk1fHTF4ekxlH5gV9FdGVko5U7MURbaXpS0itI3EeUZdIa4idJW3aHGVtLpEh/pJMFu5CqxpvAe9ZaEWlFGUUcWFLlt5zZixLLHPp6I96dHZGPPjRe9y8c4sbd28SZTFWeFZ1TmEq8jpo6q+LgvPZlOVqzbqs0Dqh1x9y7/A+N2/dZWt7j25vCyE1guBh4B2oOG2GyhuUkYBLSpNAoK6CwuWJEeDNCppBs0PboLgjhKfVsK93ZSPJ6w2myKnLnOdPn3B2esqLV2esJhPsuuD+aIdyOudsPA7sXi2JOy2iRmbDA156VBQFZV5jKPDkQpBLyK0jd54SQY0MSqFNz33z887awNiW4Q7acFxUk4QIIElShv0hd2/f5fDGIe9/5wO00jhr+Itf/IKnT77iL37+57iqIvIEcyOghSARkAIdIWnriP1el36nw6DTxZkQRA2Qm5pZUXC+zsmtpY4TvJQoqWgl4doqb7CNxLVQGofAeBEStwY0Yq2hrAqMMcGYZ5Pxe0AEpVOtZNBFdC7ItiiBVBKpQlUhrvoO186Sb2dU+EYEhd+/vn4JrwvjXX9sEwCUUlctpCAbynI5RQBxHJHEijRWaAVxrEizmK2tPkoFGGCxLqjKmhevXvD6+IhPPvkkHBKNmAF4vHCsV2tqXyMiOJmcc/EfZ3z06SdkSUyr1QrYbueYTibk6xJrQ2/dOc/nn3/Ow0eP+A//6efhRhWSug4qm+vVGq0U7XZGKIcdZV1jmoomSVUYFjf8C+88nSwhjjRpGnN4uMdoNOCtN+6wt7PFrVsH7A36ZFqxennEs6NjXn31lKefPWR5MSU/HZNauCliRrGmJSTbQgXzdKlpGYOuDbE1JNYTO1CmRjiLr2sqW1ELQS0CSito2ShcYyZTC0khBKtIkwNHVc48rxlXJXUWQ5rQvn3I7d0h/RvbHNy/SXfYY+/wAKEkE29YXEwpqoLpckHdtDnSdptWb4vvv/shUdJCRymtdpcoSkiyDkqlKBnh5SYAaLwOh0vdoFIECikastbvJB2btyalbPrWtambajP06n0DaqhMGVoqaYySEqnCHETLlMN777J38wFvvfNd8vmcYr7g4S//kvVkzUVRISuLqgN8tRQieFq74KuQRFGDrAlDVO9hVRpmznBeVYxdzZT6Shwu9OzCc27gvw4aGC0457DGoLXmBx9+j92dHe7cuUOUpQgp+fUvf8F4PObV8+ecHR+zmi+QVUXqBSmKFEuMp681nShmkCZstTNakWaQpbTTlHakmZY5hbGsnMNnGf3RiBs/vklntMWtN99BZS1kkmAauRmUQEYKoSW1tVjnKStHHMcIIZhOp8znc05Pj3n16hXj8ZjHTx6zXCyYzaZEUYT3nrzIgYCuCx7SNdaFLkEURWitL70haBLHb+uM4RsXFL6mkvpb5cPv91poasFNj9FzORB0zjSlpgotJh8IVK0sYXsrQO2WyxHOGmbTGcvFiiIvsMZS1jlVZbEmlLFCCpSWGBOsGqUG4yxlYXE+DHWT+XJzhlDkBcY0+Immz15VJb4qqf2qOXNCeheOIQFeXiKn8IF0J5v0L1KSOJKkcTOMVBE7oyGtNKXbDXpFw2Gf24f79DoZvTilnC3Ii5Lxi5dMjk85e/GS1aszzGJNq/J0haavIkZS0RKSEYLMCzLriJ1HeYcyJpB+XJMtC4FTEicbeKmUGCGoG5ink4pCSgrvWVoTDGdwTIVhFXlKregcbJEOOgxvHdDe6tPdG9LdGZG2M0rvcI1/hREi9Np7unHRkrS6PVrtDsOtA+KkhY4z0rQV2kE6Aa8aiIlmI7AdJBA2eeEGfip/qzUZrscVmmUzpgwBQjSDTO82FLww4BRIhNRch0AKoZFKksQCp1PiKEN6DU7jVYJu9dg6vIVLJvjFCjedURrDoumpmzCmR0qFUJrKCwrrWTvPyllW1lB4R0XIyG0Dp/ViIxgYEgnX7MUgKb75b3QU+ZrlfM752RnIICcf1HJnXJyekM8XuKIk9YIYQcqmQhB0tWaQJGy12wyy4BWSKIUzhuV6hdeKKI7pphlRv0/U67Nz/wHdrW1uPHgTryOcUhQusOvlpsWjmtau8xgDaZIgpSRLU3rdDp12i36/z2w2Q2vFyckJzlnW63UQprx+Gb27JBpuguKl65r/7XTz27e+cUHhavlr78WVlPHm0WuqqQ4f2LuEgae3gfKiGrE6vKUqV1TlGukN+zsjEv0WO8MOdV3ivOPFixccHx/z6uURq9Wa2WzOarUOkMZG2CzIJgS0RxpLsL6BAlrqypJTX4KqXXO2y0ZRQeorHqW8nI8FDSIpJFopnLXUpgZCENEyKLt4D61Y024ljEZd9vZ2GA2GvPvgbUbDAQf7e4z6PdI4xtc1q9mE8evXPPnoEy5eH3P8xWNEUaFLQ8cqulKxl/XoyYAq6hPaAT3vUHWNqs2Vt4J3yEbyQCZJaMnEGiMDhDRHUAErPLWOMVKxhAApLQvGJicXlrIboTop8XDAO3/4fXZvHrB16yBwE4DKOXJjOH79io0MxeGt23S6PbZ3Dy4d76K0jZQRUsV4AqcEGj9oERHaQU1byEtU4wsgQglH2BGiycC/HhSugxk2HgybpZXAWoOxNrQkACxoGaHjqLno4TCWIgpwVxdhMVhKKrsmrzW1atE/uMPbb37A/MVLVmfnvProY/LZlMV4TBWnZEoRe4cSGqki5tazxHJuKi7qknGVs/KWgoA2cpd4L3Ai+IVsZkxCBEl0RFCcFc7x8PPPLpspta2DsKOO0DL4fiTWkQkVOBRAiqMnBZmU7GYJW90O+8MRrShGCqhMxXgx42I25ea7bzPY3mb73n06u7t0d3fZv/+AtNsj7g+ZrYI9aL5ehhmBlqH15RzGBWXcJNKkcYSSkiyOyOIhB7u7tDodvPd88ulbfPLJJ/y7f+d5+PAh+XpNnCRBrLBpMRlrMTZAkY2xGBO8xy8v9LeY0PaNCQp/HetQXBsiXz0mvvbeNUEBT4DhNRM735TRbOQwhMQYT1HWVJVFqpi97S263SH377/FerWmKEvmiwXT6ZTlasVsNqeqa8qyZrlaU1QVVR2UI4u8gNrQQJfCXnPN6NWHbPIyT5UisGibIaeUCh1FSCHQUiFV6Ld2WoG41u12ydKMJEnY3h6QtVL6/RbDfo92lhJ5hfJQzpe8PDnHlCXzkxNW0wnTkxOKswvsKmdYeWKnA5NWKTKp2dUpLSFoAS1jiL2j4xs5ALisWIQQAdNPGB47AYUPOkIVsGpkC3KtWDpHbitO1ksK71hhiXf6dPtt3nj3LtmwR2t7QDLqYLKI03wezCCEIsnaRO2MWzv7JGlGmrXo9kdESUqSdhBKhYCkIrzQeJlwNRNoAOheX2X7Plxv75us34urfbRpM17fT1+382t+h2h62D70qBv2s29IbFKrEGjcJuCEOZVvPKprB3lRc3Ex5tWLl8wmU/Zu36MbJ2y3O+xt7WGXSw53D1icnnD+9CmL4xOm6zWxDzBTk5csnGdlLcdFwUVdscA1iJ2A2rkia4bqRwkRKmW/cREgQIWtv/SsDnsTIh+UhCJjUEKga0PkHJGDLppMSrpa040kWaTY7ffopCmxDK+N8Y5FWdLf3ePm++9z5zvv09neontw0KifKo7G59Tn5+TWo5IEFScQhb2ftTsNszyIDSqhiJW+BJFEUcR6vWYymXB+cc5yueSTTz7h6dOnTKdTamNw3lPX9abJ27SHJFLKS3VdKWUj+PdbF/5buL4xQeGvWxuCGvxuMNgs12QZ4trXrkaFmyGiwhN0XvK8YrUuieOYKMoYjTpIFTL2uimFp7Mpq+WKyWRMUZSs1jmzxZw8L5gtFpRFQb5eYfMSZwzO1CG4OX8Jo3MbpJNzYfAlFTpJ0DpG6Yg4Thq1Uk0URURxxKg/pN1qMRqN6HW6tNsttnZGpElMqx3TShMiKRgfn1Mt16ymc2anZ+SzOWfPnpJPZyzPz0hrS+I8fRRtoegoyUBqMqnYVprEexIfPBAi58h8EHMT3l/SgzawQidCy6gGCg+FUFRSsBQBZloIwcRblrbmtC4wWuDSmM7uiP7+Frfef5vWsEe21WdWLSldTelCl18rRRolJO022/sHtDs92u0uUdJCSI1HX6JSHBIvFI7QcxZNReAR4NVVcuGbSkAGeCkEkewrlJrg61rKv9VUEJu91wR0Ly4PG9doNgupQiIgHbgm996Ix3lHVVtWecnZeMbZZMpivuDBnQf0W20GaUY0GCHKkn6ny+ToCB3FFLUl5wJnLGVVkpc1c2sDKa0qmVnDqmkdbRi/zTNt4MAS2QydN9Wz9I28CQKFRzVCfM77S/c63RDNlA9VYwJ0gLZS9OOIXqLJYk2/lZHoKNhZeov1HqsUvd1d7r37Hrc/+ID2aEiyPWJRlMzynNcnJ8xXay6mc4Y7O/SHI+IoAyXRcRzIpUoSxzFaKiIhLxF/URQ1iD7D6ckJZ+dnfPXVVxwfH7NarbA2vALW2g3EqAkCV92Fq7evD5y/rbHhGx0Uruw4Nxiyq8euv7+Stmgcs9hUCgFlIkWEiHqgepQm4dXxik8+fcHPf/4zrDHs7u2RpglZmnD/jbu0WxmtdovR6JBbt1q02llDjAvkN4B1vqYqS9Z5TrlaY+qaslhjTE1dB8jiFXbq625eQgc9faU17W4vKLZ2upfiZLGKA6xOKkxZYaqa8SyQ4J4dvWJ8fspyOmP67Bi3KhDLHJ0XyKomXq9InOMQ6HlJCmxJSa/pBXd80OCJq2vWojaQzqKG1eobxJbFY6UMpDABlYhxUYTP2pDEeC05H58zKda8nsyZOk8lBVv3trl59ybv/MF32b17k9agRx1JzhdTPnv9EpmlRFnK/s17jIZb7GztE8cZSmmiKA4VgdSgM5ARQqVBZcITZjwuBHmtoiCq1yiaBhx+6CWrpupSDeqm2TyXe4hLjZzft8TlO6UDwNJcP35lqASsv5pVSLlp0QhqG+xbn7x4xsnZGV88fMSDe/e5/9Y7bO8dkEURqVIIYxHW0t/ZovvmA258/0NuP37C9OSUzz/6iJOTUyavjnh2esJ0teZ1vmLtXcMADoJ/WoQhtPNNz7J56qpRat1oXWVakUhFJASU1aWSaCIEGojxSB/umBaQIthOI9pJwqCVMeh1SJOYKImpjWVZVyxqQ9Lt8bf/0T/i4P49Dh48INnfQWYZIkmhKBD5moXUMJlytlhy4/Zt3nz7bZ4+e0FlDPP5kna7Q5qmGOMobUWxWlHXjbGPsRhr0GnE05fP+eKLL/jFL35BnudUZRlmN1lKnhdorYiSGG89SkfNwLnhLVl3KY9+Zb9qv5WB4RsdFOB6YPj6Y7/98dfnDYSMQarQ6kVi/eZNY73GuIi8hKK0iIslWudoram9IkkTsixhOOzR7rQbW87gr9ztdIiTuBEVi8kyTRxleBcsN52zuA1kER80fzbyG85dlri+YXlFUYJUGuMFVVHjXImtFmG+UFYUq5xynTOZjinKgsVqwXI6pVwusZMlsqiJ1iW6skTG0ao9LSHoSc1QC1pCsB0pWlLSASJrUNYR1SEz1B60DwfCpuXg/ZVUce0dtZTB3EQFZnLlLfNizco5jvOctTPYVky/30N32tx87zbbN/bYunWAjRXzqmBdWkoH7cGQzmiLtN1me++AXqdPqzck0ilSNP7SPvT9LRESjfDqiuHa9MdF03a6GqEG6KX3IvTRN8Jv1/dI852hVeSvP/L1/XX5qcdf+54rfa3wO501l20J6xy+yWjn8xmLxYLziwvKqmJ7Z4fR1hb94ZA0axE1iYUQQVtLCR+ydSkYHB4i4pjoxXPq8ZiLYs1FWTCvStbeXeoCOdl4DjeBCd+I2iGaPcflHtRA7FwQ5RMiXG9AI0gIQSERgkgKYqnoxpqW1uy0uqRxRCuOSZIYqSR5WWKFwGrF1t4+g91dDt56i+HhIenuHqrTgSiGOCKWipaOaHVXrMoa61xQEjg94/Xr11RVDUrRbnfJsowojhr2eIFUTQIF1NZQlAXWXQvM3mOsRagrhWRPYGZ7F6ogmrZUcM8Tlwnj9fVtrBq+8UHhr1qb6mCzNhm8bw41CFmesx7nJZWF0gqMj0B30OkAEQ+w1ZLJ0lGWOVVV8dnjo2YOYEjTmCSJ6LRT4igiTWNu3ThgNBqyv79Pq9Wi1+uQZQk61rQ6ISuNlGp60AHUCoEZW1UV1ob3ZV1R1jWzvKCq1qyWOfPZjOV8yfRiTL5aM70Ys5rNKVc5VZEH1nQaBwIRgj2ZkjpFh5SONKTS0hKOtoSBlmwnmo6W7KURsq6hLDDrHIxBO0+sNLGOLhGY1obqwAnf4N/9Jdu0FlBpQSEc03LFi8mU89WaMyDuZezc3eaN773P/r1bPPjuu8g0xkaSTx495HQ8ofCwd3jIm++9z+Hde7R7fXTcDr1+L1EqZSOBbq3HWI/1CutkqASQl8FeConSMdAM7AkHrFaSoOXW9PibjeBswM7rRujtEnEqNvvn+sDZb67YpUTC9R/a+DQ7ZynLgixJieKEqg6Z62I+58mTxxwdvSIvK0Zb2/z0pz+llbVJ4oRWmiGcx9d16Eg1ZDVijRAZvVuH6F6b+PPPWD39iienJ7xeLsmNoWYzRwh7Wwhw5aaXDpH3KCTxZrjeVAPKe1JrSawlBtpAjKBFIJppoKUkaRTRTVK2Bz06rRZ7g8GlptiqKlnXFaezCTprkQ2GfPiHf4ubb7zJ/R//BNHpQLvTSGoEhFqctoilZFAZ1pWhNJbHT77ixcsjnr0IemNCKjqdLmmW0e500ZFEa8loNKDVbpFlGaYsGE8maKXp9XoMh0OccywWCyTqsm1kXSMo6KC2FqU1OorC3E4FCPjl+fGtCgNfX/9FBIXm1r4mZXH1tU0GcNkioCmlEVhX42kGWLFGpwlRq4OIMqxMKF1M6VKiOENmniQlZBwNnFVIMMIzLz2yArmGZTkjeblGfvw67EUJWgeyTBSrhjMhG1VWmkwSZDOg9M5folisbbgIxlCVJVVeUlcVqdIoD8pERHTRcUZfWRSeyDt0WaJqgyoWzU0u2dGKrlLsdLqkOFo+MG6jusYsVyhn0c6SWJDooLWDDM+naRlZbFDvVJJCpxgpKSLBynvW3jOu16ydZWxqFpGhHmpu3Nhn63CPN7/7Lrv3btHZGrB0FavpgvFiiZMRuwc3uP3gbXqDEYPtXdKshxYJ0mVsFC2dbSx3mp6/UhuWcYPTD1f7EkHirQ1Z4LW2onMW58MsR4nGd1oGn+WrY36zca72T+hNXcu6r339av+Fh5RUjZWpJI0TrDEsypKT42MWizknJ8dYZ+h22ty6dYvBIBjPKKnC4Luq2di3io09mK0olyvW52MefvYpr14851/8s3/Bq+NTJqsVOIcWArN5Ps08QAhBpFWYmThPjCfCkRKqP4UnJuhVdaUkRZAAmfNkKmIra5M1kNJLEyAlaamIGIGqK4z3FNYyq2tKIdi5/4DtGze48eAN3vjRT+jvHyDaHdAJ3gkq50IFI2RoXwlBu9tjd9/xnQ+/y1dPn/Lq9RG7e7u0Wx22tnfIshZxktLqtEOQxKLj4GJoa0OaZAz7w+AXfn5OXRkePXzI+dk5knDPRa043Ed13SQEm+AdEEmhtWi4xKX+16DwN2v9Dk7490BNv778tX8v7+bm3dfhquJau8ZeHgIqlJJKIxu9GycijI8wxEiZBUE0EUxfNloxwZPXUtuq0cIx5FWFoCLPc6ytqU2FkC4Eh0hcIh4umfhSoqQILlxNWe+cvdqwNvj+2rrGNSim7V6XVGvaKkL5BCUiWhEoa9F1FQJCaUjWdTCBVzpAS5ViJ5LEzhI7T1Q7pDFQFZeZc6Q0UghUQ8rb4NmtCGJ1wddAUkURlZLkkWTlAoZ+bEpWzjLzBt+OiVope/cP2L11yM2379HeHqGzlOn0gmVZMluv6W/t0OuPuHvvraA5lLZxMnAIhI+bVFnivGhaPwFFs2nLbCCkoQfcQEsJgVt4yWXy58Nw17tgzhkk0P21rXJFVrrectxwWy5bfNeiwl9FcAqaSKGOKMuSYr3m4vyCxWLGZDym1+/S7XTY39ul2+3TypqZSFMhNACZMKS2BlusKWYTJsdHPPn8U548fsyjL79gvi4o6zrYxzatFHH5BD3Ch4Rng3SLBUQiDIpjCZETtIUgFYK+1rQIzOTMelo6YjtJ6CQxqQ57AoLngpYB1UZtsN5RWYMRApKY7Zs3Obz/gHvvv8/WnbukgyEkKV6o0PLzQczucmNJiJKEVqfD7v4+z1++ZLFccuvmLYbDAbs7O6RZiyRJyDrtML+xVWOo47G1JY5iknYn+FMnKaPhiHa7g2i4JlJItI6amYG5PO8399jl27XX7uqjb9/6GxkU/v9amx7C5af+8uJDgzxQasNnu4SIGmOpKkNRWUojqL3GyqyBWbaxLkg04K7aUEIQFBFU8LLFGWyzsaIOTVbmCCL1HpQLVcE1bd7LG3kDWfSg5Sa8+WCu4h0itUhjENbSEaCNQxeG2AZkUMsYImtpVRUdL2iRMGgpekqxG0dsKU9LOOL1CmkrlCnRtkZ5T6ZjaIxhtA/mI54gKWykgDRuzOdtI6kAMylY4zgv18xMwdJWLJRDtGOSrW3uf/Aeh3fvcOvtB6A1K2M4On7FuqrQ7Q7dwZDvvfNddvdv0G73ECpBygjnYqROA8zV69D1Fg2fALEB+VxeY+8bHkpz+yq1afVc18/feChHhC3vL/eJ4Fqi8VvZyNWMwH2tHSnENXb8te+vqpKqrKjKkrIsmVyMmYwvmM2mVEVJK8v48IMPGQz6dLptOt1eqHaMa0xsmmhga0SZ45ZzzHLBiy8/4/XzZzz85BM+/+RTxhcXHLRSukLQ8jCvLUUTtBSCVITZCYQgIAjyJz2lyJRiGEW0haQlJDtxTEdrdtKEFpJECDo+DKK1DUmCFgGVFcAEja2ptSzXhkoKCi259f67DG7c5J2f/pTu7h69gxuoXg90DELjhMQgiFoZXkBlDMY7sB7rAneiLEuUVLRbLfLVmjIveP78Od1en1ar0Q7zjlW+vhRWpLaoxgnx1fOXnJ2e8eUXX3B+ekas4kuwyXq5wgtCdYEPqLlr11SqQJBDXJn0fBsDAvwNDwrXy/LN+n2sZf87H1x2GS4Har/zm3wzUPTN40Gcp8GtN0qYXuFQOILmimtgjeHHN0xj2Bw0TugQAJohpRCNyc+1wOB+63nIJgt1l2SwcGBJgoGLwgbzemRoGXlomRplDbqqSJ0j9p6udaTe0UXQE5IMz1Bq2hL63tJ2jgSLsmXQybdVYCRDYEWLYEkZ/hsJ+jJKNuzZoDefC8kKx9o7zk3NylvObEkhHWUiae2MSAc9du7c4ODNe2wd7FMIT20q1sYikpQ0bdEebtMbjOiP9sg6I+K0hXNhMIzU4U0oGsAkVy7NV2PAq21wXf3KXwsE4nf2Dtd/w+UvuNwkX9tEG6jpps98vSLYcBGsbYDFzlEUJfl6zWq5Yr1eUdeGuqwQUtLpdIn6A1pZxnA4ImulAUAgZKhwGh9J4TxYC8ZAVTM/PmZ5esyLTz5hfPya9dERrapESIVvJcxRqMohfI22jspZjJBh8N/UT6nWpCol0SrsCykYSElHCDpCsK01baXY1orU07SPQhDB2UBoEwonZWMqpfBSYPCcrxakwwHbt29x4623GN28Sf/wgLQ3QGcpaB3UWDcHbdOCtDb0+y0O6z1SePJ8zXq9JtKKQb9Pu93COUdZl5ee291+FyEErXaLSGukFJiianaJoBwVCCfY3d6lWBecZefkVYGtA+pMSBHekI16srjkKWzmDtdYQ9/a9Tc6KGzW70MYXV+/L0yE6/y75f0GsQDhQLZOgFMIrxBoBCoc/F4FFqiXWK9wIgSIgDK5/DPX/roLMgLN+81XQghpFOp8eMxde0rah+pANi0H7z3CWURjRBMLgcaTIYisJbKCJK/RpiIuC1LnGlipoC0F20rSQZAJx0BJYm9ITU4LR+Qt1Dm4GqwhkqG09q4RRdOSqrZY10AakRipKb2gcrCSgoV3LJzhqFqzdIYLXyE6EbqbcOO9B+z8r+z915Mk2ZXmCf4uUWLcefBIhkwkgAKqqlGFJjPdQ5rIiqzIvu1/uDK7TyMyD92z0zNdvT09XQxVXUCCJ0FmRmaEh3s4Nabksn24V9XMPSIBVHU9JJCtKZ7hbqampnrJId855zsP7vHO7/8ek4NdskHJj3/+AY11BJWxf+cBk5199u48YDCcMpntk+VDhMxQqKiYYif4+Hti0pO9UqAfwxvzfGvuu/noIJ5bi2lrzkR/TkjKmFTQ1bVw6WiYhd9cR0gi1UkTq8uNMZydXXB5ecnl5SVXV1cIRKRT35kxm03Z390jzzKyTCXBE/DOI4JAOJH6OntoW4JpoWk4+fADnr3/c376p/8Js1wQ1mvu5gXZdAYy50KtGLQeHWrmJnJONVJQK0njPUJIJvmQvcmY3fGYSXAUITD1jmnwjAnshtgudV8I8tQIKfcQnMe5BJFKSZPlsShQKZzWNMHx6dWc1x/c52vf+x5f+94fsXP/LnJvD6E0qIygVJrLBNmGCP00TcvJi+e0xmCcZVDmtE3D/OqaIs+5d/cOk9EoJVw0DEcDprtTHr/+mCIvkER6C6001WKJNQbTGg5nB1xfXbO4vkYKxcnxC+rT55jW4AnIIBEClEhxxEQAGNOFScrrqxxijsdvhVL4ux63U1N7+dAJZx82qXmdcCYFIIVKFc4x3hA9hMg50/uuyaRIrXHoXtiInM7mUEng+F7wyJT5kQWRioICeRCoEOmHY9N2UE0TrfpmSWEbcmfYCY6SwEzGeMFQwq6AoQjM8AyDpUjUA8I2+GaFNDXBW3LhI2dSrukI37xQ2BCb3bcixg2MUhitaHWMG6yD4+lqztwZFt7SDBVyPOLBgzfZf3yX3QdHPHjnTbJBQZ0rnj59yqqu2T28y85kxv7hXYaTPYrBmHK0i9IFMhviRSo867qkCFCprlZIkgfH38J0E7f+vf3eFxgXgtS+Kx7excB0bSqapmG9XrNcLaMgs5a2aamblizLMcby9Okxpm2x1vLw4UNmsxkP7j+gyDPyPGNYltE6xXUc1kiXYCPjk4fg4OKC+ckxT37yIz79wX/m8vMn6IuL2LsZReZBBofFRO91OEQXQ+bOE5ZL1sBaSh6+9SaHR3f47nf/AcM8o5SSF7/8iOrykvXnn1HWFUVTkwdH5gPSO3TwaB/A+UgLWGRYqbBSRqPAGi7alpOm4cq0PK9q7hVD9t54k+LwCDndhXIAKlKOBx0VQkRco2p3JvYuMM6wWi9Zr1Y8r9Y0dcPV5QWPHz/m/v17DIdDFosFq6ahKGMBZ1kUFEWJEoJgPcY2sZ9EUeKdZzaesX9wwPHzYxbzFT+f/YKLqwtU2zIYFClGFjCmxTuHS0kc1tqe9gLoPQpvv5r9Fb6USuHvW1P3ZFfp6i85HVuQcle4silyuynmCSLx6Ug6ejRCJ7USVUKf976xPON5InIFhYDCI0OnFAI6QBFip6oyxDiB9hZlWoRtUPWawhlKb5gpwUjAnhKRs14KdoSnDI6JtxTekuMYBUnwMdiNaaL3kaXmikLeDCITO1oZHTthtVrSSKhFYCk8S2950TashKeWUO5MGO5NufPmY+688Yj9h3eZ3TvE4DlfLZi3Lcum4cHOLjt7hxzce0heTlBZicpGIDSIvK827pwukQLHm6ODe7Zf/SKv8dbnxCvW0qs8zvTlYvtvD8EFrLFRKazWzOcLmrahaVraNiqFwWCItZ7FfNFXz5blgMlkyu7uHqrP2onU2d66CNf52GJI+BBpUIwltC316SnXT55w/NOfcf3pp9RnpxR1GxMGpEK5AMJTe8MAmBUlJkiE80ycI1OaQZ7z9ptf4+Hrr/G97/1DciVRwfNLAdfHxzy/vop9sa1BJhJIkQykFE6GVEQZpMIJGftfO8dV2/JiteKybVlYh9EZxc4uajhGlINYg9ATekXIKUg2sKmMQldnMWXWWsPF+QXr9ZrF/Iq7d+/E9FClUFpTDMpYyax1TNc2LcE62iq2DB0OhpEAUuexjiEEynJAXhRIpfoMNaVUfK6OdCykeGNHjHdrGf0KYOJ3/vhSKoW/1yN5ANEhSH8kAZ5KhOiSGhUhtYuM0E3v0jvbF0fF5oLpSCT1wm2CeYKYShhDC77nwRHEfaKBLP1oArm3aG/JnKUwFcpZCtuiTY2yLZPQUuAYYxjrwEjAYS4YCJjKwMC72BfZNijXousVOjg0HlVLhHdo26AziRQxH9t4R1O3rJ3DADYvEUWOHBSY1AT+ylnmznBla47nKxbWcGItuw+P2H90l3/w3/wR+/eOePDWGzQq0ATPh59/zqppWFrDW++8y72HD7l79xFZXqKzIdZ35GzR6woBlNLJM+vgoYBD9HMm8ag+hWijIOjjDX+PR+9JikR50XHtZAyKAqZTrPdImdrEBNjd30cIyZtvvMl8vmSxWDIcjlEqQyuNVir26sATnMW3JrUl9eAMGAdVA9dzzOUlf/k//89cfPYZZx99xATLUXBMlUY6B1WN1BkOwWrdMJxO2Tk4wKzWBOt4MB6z9/ARd772Nf7Jv/wXHN6/x96dw8i3RGA2G3P+2WeEds3is8+onKFuYuzKSYnxm4C6T3GlFYEqWI5tzVVrOF5VvGhaFs5xBSyUpi2G+MEIBiMYFr1D5pwjVvTEvskuBHSRMSrHvDv9Os+fHfNMKX7y3o84eX7Cs2fP+OUvP2UyHTMYj9nd2+Pr33iX3YN9huMxH3z4IZeXlzz5+BPWyxVt21LmOXfu3OWb734LIQRNXfPez97j/Y8/5Pn5C6q2wQSPr6utGIJESp2yCWPtkFYK1dUypTTsr+rxu60UbgWeu3jCdt5IZ5dKYsBVBpdyuD0ZniwpCJXO9LgIaYgN5AQhfdanszrLy6esolS97CJLTxYivq+Dp3CGzBkybyhMHTuX2ZrCWwpvmKnAQAZmAsYiJIjIUPjA0FtyG+sLctegnCHzLSq4aAkG0X83Kce+dS728EVgdYaTAltk+FzjlWDpGmrvOGtbFt6x8I66VGSDIW/fv8/Raw84fHyfvUcPKMZDltawqBqWbUMbIB+NebS7x9H9R+zuH6GKIUJleKEj5QQxmBzoyOhu5gKEQEp/FNuRhM0kpl+EuPnib7qFX3WeuH1COkkKQZbnsd5BKwo7iBxaUqWMtkBZlLF/sY5KQEnZUzJrpeKz+JjCHKwlGEtdLXHrFRdPP6e6uubq82fo5QqWK45/+lPcfM7YGkZ4CjxZSFloRA4vhCQrclrvWc2vCXnBaDTi8PHrHL3+Bvfefpv9wwOGkzGqLGOcyztGB/sg4Z3v/iEXOzPmsymLjz+mqSou6pqCaKxIKXFC0Aa4MoaFNTxdrVlYy4U1rISgUYraeRoCbQh4EanLw9Y8ChlbhMbOh10ldRwLUxtM24Lz3Dk6Yjwa8drjx5TDAUVZUrcNWZ7jjOX5s2Oc86xWC6SQPLx7L8UCItQrheT84gXPj59zfn7O3/zwh3z+2ecslnNc8H0dSgf7blcvi5TocaO46St+/G4ohe35FC+/th1sjIsh9KdE8RMSIVhABYcOjjx4CmEpcSgfi7ZCF2QO20BT+nwISG9j0VFSEPgYNO4Eswo+Xj95Bio4SluTO0PuWkrXoL1hYGtGMjCWgj2lGCrBnhaJc8ZTmhblLbmpkdYirSPzLRpHIWKQWtB5MHEjhBBwIVCHEBulS4krcnymsUWsOaiV4PlyxaJtOFnXEZ8WMD7YZ/f+Hf74X/733Hv9NY4ePeBqvWTd1Dy7uuRiuWReVQx3dtjbO+Sbv/+HTGa7lMMRjQFHzNrSuogNblB9rno/psnyjpMS2WK7au+XRLmA0Pt5f/elso0b9sXLYROLEkJSlBmFKBklTKkrYHMuJB4laFuzCXgHYraLdWSZigFb67DGEKyBtmV5ds7ixQk//Y//kdNPPuGD7/8Vw9aSG0s+n7NTFLy2u0PhPdp7hG1jsaNS1N7jJZSjCcu65unpCeXrbzA7OOAP/vE/4u6bb3Hv7bdplSLkGRQFzjQ4ZxjdOWC8v8OduwecPrjPi/ff5wfzBcvTF8yvFpRKkEtJpjReCOoAJ9ZwUVV8Mp9Tec9KCGxWYKRm7RqqALX3OCKsGlzHPBwzhqQEb2NhqZCCYB2mbbm8vGK9XOKt4WtvvkFZlty//5CsKJBa8dHHv2SxWHB+fs6nn3zCi5NTlJK89vgR/+R//OccHB0xnowxxvDpkyf8+Z//OX/2Z/+Jjz76JT/7+S9YryuqqiLLMpSWN7nFbtUuBb/hRxPblshXVE/8biiF7SPcxAO3AYbOSwgpA6XPUU5iSmN74Tx0NWNbg6mQzuMTEydCJzklUi5SjAn0SsFHK12nYLIGhHOIEGMEOkTLvvSGLDiGwVAES4FlJC25cAxFy0jCKMUMihAYtp7MGbR3aNsig4+c+sGjZEBJIstlkHgRA2rex9xCoRUWgRMCqzKszvBZzkpCjeeFaVm1jmWwLIXBlgK5N+PO3i6TowPe+P1vMD064PDN12iF4PPrU07Pr7lervn8+Sl7hwcc3n3It/7BHzOaTinHY5CaxgSEiBTWzgtM6yK0JmPXMEEUFP0sJamqOgvuFd7AbW6av48Fc0PtpGZmskscEBFzdj6ycgKRkE/EVqcqRIt1b3eX0WDIwd4OwQeKPI+xAh9J7ZSzrOZznvzspzz/xc84/+SXXPziF7j5nAdSMtGKUggmk0mMH9RNjAUI8FnWx3wqKamF5LJtCbMZd19/nbvf/g47Dx7w+NvfYri3D6MBWVHglcS4Bi88Pov8VFIpRDlg5403Ge7to8oRL558xk/+9C9ZLuY01RrjHI2Lldhn1Yp5W3MSQk/F7UJk9m2U4LJa8dGTJ0zu3IE8pxwl9SkCUunoZfmNhy6CRMmcvfGUWVbidg9S1b9mOJlEjFUIvvbmG5i2xVQV33r8GvPLaz779BOsMfzFn/x73v3mN7j34D4HR0c8PDjgn//Tf8qd/X0+efKE//V/+7d88mkkxxMpk821bZy7rezDIssp84IyL1BderDjK6sMuuN3RinchgC2FcPN97o3E2sqsZ5AEQWs9pbMW3JvGPgW6xqUBx+6bly6N147paAhwjU+bn7RCWwhyARI55Dek/vohWTBMwiGDM8oGAochbCMcWTCM8QxlIGhgGEIZCFQOIuyBuksKnkkOZHWWIr4b3SHBSEoBD6mPkYuDYyIxWgmj0qhzTJW3rLygTNjWGNZC0sYZcgyY3K0w969Oxw+esDDd16n3JkSSk1V1VytK1atoTKOdevY0wXlaMrewR0GoxEmBFyI6b6ZjpWscchjTn5Xzd0TkG1nhW1DfClDq8tz7wLHr1IM26/coKP4dQvlNsYIaVVEDzAlj0YIhNilS6VSXCnjclJBRoZQpaL35Rwq0WbjHYRYmdysVxx//hnHn3zC+ccf48/OyduWmZSMZeqDnWm092hrkago1FQMxrcBWqVopcIVJcP9fWavv87dt95kevce44N99HiMyDNEHgsOrW+jYSA0wXucjMJaT6dkZcnRW19D5CVPn55Qf/6UtXVcr1dUreGqrrlsW5bGsiBgBVgRO7EFwEnBoq74/PgZDy8uKEYjVBHbdyI3AG2EWUXqzhfnW2Q5QmVQduSEEpXnafwD09EQXxT4LKM0njGK5ckJV3XD6dkLLnd3GCjJ4e4uwyxjcHhI9fpr5JnmB3fvcHl5kWRAnOOu7sT7jlJm4zl0fam3vcX/2o7zd/h4lV15s4I1BoYzPHmCc0amYtZW7LcrynaJ8ivwEeaQqJSdkhj8Q8JhO6XgY7FZKSPjZCElhRRkCAocuYBCxuriTHiGwpLhyIOjCG2MM3gTvQpj+7aX2hqkj0HBXEYyPR3bssVnImZ42CAQeY6QEmMaLNAiaLXGSkWb51TA3DU8r9dcm5ZPFyvUOKPcLXjwzmN27+zzzh98i4N7dzi4f49awtV6xX/+yXvUDiyKR699ncFBjt69w3S2QzGeUdeOIAxBa5TKU8ZHzAXXWiNSDwMpo8TwfcZfNx8iZcCIm1x0dFkxf4tjq1q1XwsvxaWjoBDpG0K/NjYJAhGDCygdU2W7G+rpNFJL1bxQiFwjfGS1BcA0PSvuerXg5Pkz/vLP/pTlJx/TnJzwel4wUYodBIV15N5RihAr49sal9IRXDagFpIFknVREIZDHnzr93j0jW/wzvf+GHH3DmI4RORFzP7JcsiySAIYZPQOtKSuKry1oAOZVGR5we677zJ59JiDx2/wJ//H/8Hzv/orPv7gkuvlkhfXV1Qh9mUIeeqbgcA4j/cOnec8eX7Mv/m3/xarM75+fc0f/aN/yHA4pMhKXIDgHD4EdBBooZDeIZBkeRHTcJ0DayA4sC0kuvBcCGxTszo95/rzZ1y9OMOevCBra/YRHP/k51x89DFvHt6lmE6gKLgz3UFaz/39fZ6NRpGZuKmByDfmfZxf5yKc17YtJqWlBr+JK3TK4lc19vpdPn4nlUJnZW7zHwFJBmzxmogOUvKoYMmCIfeGoW+ZhIZ9YRgJQy6iVSi8QAl3M7ic8pEkASVT1k8IFCKghSAXgkJItIAiwUoZntLHc3MsGocOlizYCAv5GG9Q3scc8q6uoa94Bjw4fIxlp5RSL8Ak6emBJZKWQCMEjRAYEVi6lqWzXBrDNYa2ENx5+IjxwZSduzvcee0e490ps/v7uFxyOr/kbLVm1bZ4XTDb3WE43eXBo7ewLrA0z/Ao6tZhvSBHo3UZW2LKWJAWG7soto8UOiCI24WJIglcQV9otqUYuk+L2/v1lR7AVgCx8zLCtnK5fZFUuJayxuKP2VxrO9Dd93De/NuRrHV5baGrgxeBYpAz25nyxpuvc+kdK6XQixW2bVjWFQrIdYa1LUiJyzQhy/BasxYCk2WYYsjBm28wPDzk8Pe+ze7DB6i9PcJgSMhzvI6pnGyRPwqhYtO/1kX1pxQiz/HG0VpL3bRUqzWn19ccX895Pl9yVlUsW0MtRGTDJcTGQSmdNJZiBry1zFdLnp4c895PfsT1aonIMw6ODjm6c4fpzowsyxIQt+UBeo83Bte2uKahXS0jCaS1DDJNrjTVcsl6vuD0yedU8wXtumYvy/BaYbKCz54+ZXlxRXt+iTaOUGTMLy+5PD9jdXmFWVfkiKiYRIQkpRB46XEhESWmvRQ6D3UroPAV1QfA76hSgE384KUjdMARqRlKlLAKiw6G0jeMfcPMNxzRYoRhqCTagxYC3fFuCo/yITGTJqXgPVrEtNacyFyZCchlLEbT3sUYgPfo4GKmk4+54jKkbrrBR2+D1PUq0SbRWzKhF/rBRVI/D7QixgxapfAhptTNhaBFUAlBRaS7vjA1c9NwVleYgaIYDvn2d9/m6OFd7r52n53DGdkghyLj/GrO6ekxn7+4wATJ5PAehw9e4/7jNzi885jVquLzk2uc9axrg3WSgCbTg6gQZCecUuX0DbgmCtmu49VmeqIyjzxA8LLgvj3L3aTe8gqScN+e9z5OsZUiE2GpbT8kCnIfLMG7yKQbPH2mvei+tyPly+govUMXiPbpmUSMSQgRGA5LDg73+b1v/x7PdcZlWXL9/ofYtuV6vWYwGDDMM4w3oAROZLgixynNVYCQ5YjZjHvf/g533nyLg299EzkaEkajqBCUwiUGXp0qdCM8qnHO0lqD1AIhY19n7xuscZwvVlxfXPHLZ8d8/OKMJ5eXnKzWtNbglKbxFuMjVbkMoEUcCR/AWYtdLlkZQ/ib/8ynn39OEzyvv/kG73zjXV6TrzGZTGInNiHwQiCcB2sxqxXNakmzWrE4P8NUFdV8wd50wnQ45PzpM67OzvnoF+9TqIwyy7n/1ptoleFc4Hj+ARdnZ9TPX0BV4zLN2ckxJy9ecH16SrtYUCBo6TrIRePCC4nwscqoz06nU+5di9a/tV/6O3X8ziqFLzoSwtj/3WcOOYuyLZmpGNo1U7fmiAYnWnaQFCIOlvIbD0EJUjC5Cyr7VOcQK0O72gfRRttKBRerlAkpZTRyG0WnPCqTDgzqOJASHWRs2dnFQaQCKfBaEmTMFHFa0wDLAGsCjQiYQUErYC0Cp+sli6rlwjvkqKC4c8g3/+Ab7D+4w6NvvkU5GVJOh6xdS7Ve8skHT1NdgeLt73yX6e4++/dew8uCIHNcKPACRrNDmqrGGsvF9RKHIh9M0Im2OpJNJAHVC1R691yIjfoOW7Oz/fqvns0v+jsqIkIct206DIHAd/AQpPvoFK6H4JChJQQHtAgRWW6FTIKlD3BIYncuiUg0HVIJGlshgEJneBew3qF0xnA24Z3f/33u7Owyf/waH2UlV58/5WS55NRa5qbiwWyGd5blakEVoPWeqigpZlMmD+4z/da32P36O4jDI8gyyDQiiyym1rtYnd6NXwDrIqF2nuUIFUfAe8+8qplfXvLX7/2QD37+C/7N//K/cHFxwWI+Z902IAQ6yyJjbQi41uB8wBqHyhRCCWxjkImv6emzZ5xdnHO9WnBw5w73v/+Qe/fuMRlPONjZZVSWTIoS2dS4uokZT2enzF+8YH5yjK9qZFMzkIqBkszyAt+2zM/PGRQlRZZz9d4PQER69MU6JoD8+//p/0XlLKfzOc/mV1xWaz6/uuZqvaZwDikEDhG7HZKK1kOkrddak2WxZ8h2v5WvskKA3yKlcAti/rXvR4QnteRkEzjqqZBJvWmTlR+FtEd5iw6WPDgGwRGCZYKkCIHcg3JJgNMVuhHbVgbQ6RoyRK+hu27wkUVV4uL56TtFeq1LkdVsYeeda9vBHgkP9wiQkazVK0FQkiAlJtPRK/CBpbdUIdAERwusg2cpA3UuUYMBw70pu/cPePDOG+zfv8P06ICgoCE2WV/XDZUL6HzAYDhh/+4DdvaO2Dl6QG08dRsIIovwiMwJwuFFwIXorncCPcrOQBey3YSIO8XQ/X5j1uJv2y8lGGlT37at1G+vgC5gKLYC069aKV2LVr/lPURGWoKlqZeYtma9vsQ7g3OGLpxkfSDPS8piSDmYonSOkmVq6JJYWImMrqlZBl4IpNaMZjO4c4dcKubHp2ilqa8usVdXNFXFQmp8EKyzgrWUWKWRO7sUR0fsvvaIwZ1D9O4OocgJSkV+oVQ5TIgd+0I/gHENSRlTfH2ILUmXyyXPnz/n+fExP33/fT744H3e/+Tj2PfYO2wIKf9fpJ7Xoe/iRkj1OSJ1dhMChIz4vDUcHx+zXK+5ns85PTmJ9RM7e4yLgnFeoJqGUDdUZ+eszs9YX5zTXpyjjGEUPC2RdyubjCNT63qFygtkllGtFgBY51E6tiydf/Ypy6bhYj7ncrlg3jZY55DOMZCpMxsxHburqu74rKJXl2jOe2UQ+nX1VVUNX26l8OsMxVcc3bSKrX+3oOD+JAGRa4hIShcFe8T3i+AYeMskWPAtk9Yx8DGjKPfJu8Al/qJIUaFCiN5BcAn7d5uv7BrDiw01Rs+L5Da8qZlUCESkS5AyZXHI6AlIgQseHxwVASvBagi5ImhNU+RUCM594LLxLI3lZH5B5TwrB3uP9pke7vAPvvt7HD28x6O332ByZx9VZlzVFccvTnny9HPWrUPnJa+9+wcc3X3InXuPKcf7SF2AKilyRTZUWCOwfs58bjDGE5AMRlOG4xlZUeKDwwWH6nLBSZ5BetqoODatMrvZ2kBJN63+VymO7U18c7F0v8utkEQU+n02EXEsnW8RMt1XiJlCIrR89uRnnJx8zns/+AsuLk45OzvGeocLnqqxvP76W7z7jW/zne/8I/b2j5hOD9GyREtBUZYAWOtBZWiV01iLCIJM5Qzu3GO0f8j+0X2qi0tefPeP+eCH7/Hsl5/w01/8AiEkw517tFoiy4J3vvv7PP76O3z7H/1D9P4elCUWh/MxjiNDFtcK3ZpRPeVGpmIGk5CCxWLJxeUFf/ODv+Gv/ur7vPfee/zlX/4li8UC61qUjG1MvXORKl2B9wLvwXeFX8QCyOAcSit0npOXZVQoznF1ecnF+Tkff/BBLFaUknFeor1HOcvAegofmAYYA+MAj4cjdgclbx4cMBaxRWzhTWwCVMzQCU5crK+xIeCVRKoSyKjWNVZKHuxMeKoll3XNJ4trFgrGQnHWtKx8ZEi1QmBEKlcVnnW1ZF0tWa0XWNMQnEWxabX0X5XCl+n42yqDWxbktuDZLlJJZ0UooQsu3YBs6AvPYhA4Wo5liIHhIjiy5ClEqz9+RofoNUTGU58ancTzItwd70sm5v/OgwF6TwY6WKLj54x2tSXgRWxw0wJGKBoV+xw0WmCkwOCYNxUr7zmzjmVwNHjsuGQ8HnH/6Ig7b9xndrTLva+9xmA6wpWa0/kV7ZXj5OoK6z2D6S6Hs30Gowl3H77BaLpHMdpF6pIgdYSTXKqqDRqCwBgHiOiK5zlKqwTNkAjgOvUXkmsg2NQqvzzRN6bqlp0fDdVt8vFNTGDjgWyfvylK6oMKsVFxDCKzqTZHeKrlnPn1OSfPn3D+4jNWyytmE81kdMDjR1O63tlBaKyXXF2d8OzZJ9R1jVYDhqVEF0UUyEIiVdZXPvt0C1IKhMoQmUbMPLlS7Hp4Ky/Ye/wapihYLVfUTc3+vSOmB/u88Qd/wP79u8jJGIoiQkZpFCWp9iAphUBI3x8xc2tj9XDbtrz/4Qd89vln/If/8z/w/vvv88mnn7CuKnzwKB1hIp8s6hACwjn6wvw+YN+NcXwm5zzGWIJz0SN2np740VmEFzgfkhceyR6HCHaUYi/L2dcZj0cjZlnGAYLCWnLnKLxJ9T4upn4LkN7iiG01hTMQAtp6DJJGWnasRQIrlZF5h/OWOu1/E7qOiyQW44DWKsJHed4zpnbr7quqEODLqhRuz8iNgONm028L+xuMqOmslyoXu2yWLYy5q0qOhmSIhHVsgsWSSDRXBkfhYzWyTJXJ3TVUUgrZFuvqdvRio6wijOJ9oGvUIpLl4tOiDSFmEnXISisCVgSMVLQiKoG2yDFSsFaBtfNU3nHeNiyc5UVrMLnCZ4rBbMzO/Tu88+1vcu+t15ke7DI6mNEGx9o1nFxcMl+tefbiBTt7B9x98JDX3vw609kes727oAqCLGLXrCCxLlbyehfQMqboGmPJMoVSWaoeVXifcs+358eHLcEVR75vlfnSZIebf25N7HYc4maHtO5jvYWQOHx86rgVENJvXWoTU4i36Vmvrnl+/IT3fviXeLNACsO9OxOmsz32Dyax+55UZIMJ73/4CT947+c8e/aEujYc7D8gVyWijB6CEIK8zHHOErzFJzjHKxkZRGVUjDovmJYjZnfu0iyXvKgaXpye8OzZUw6//g73Hj/izd//DvloBINBjCNo3dMxyhB64jeIeLt1Dq0jP5NpW5bLJdfzOT967z3e/+B9/t2/+3ecvnjB5dVlzA6SsV2tcy6yh3aGknM9A0Sf178ZtdQ61vdFeqSUaZHgURVSrw4Xex7oACOdMVGK/Sznbjng7mDI48GQsZTs4pHGIJuaMsRCUOFM6ukAgyzCZDYIsIYgPLJ1GAQKxU6IlCCVzlAWWmepZVwrS+uxCYoMEgieTCuyLOuVgthK7/6vSuHLftxGEn6TI533Ep++iDBODIJKRHC9+PYJZxbEYjCNSA3TYlGadFEpqLAJNkcQJPTxif6WO9kEfRpptKK7yEaizRAqgRlRgXgpsIl7xgtwZY6VkrUK1FLQCsG5M6yN48I0LKyl9h5TZuTTEXfvH7Fz74jJ/g5v/9675MMSVRYsTM2LesEnTy5xIlJP6MGQnTt7/ME/+ReUwzHlaILWQ4TQGJcRXMSTUUnoesi0QuWKqqppzRLTzsn0kDzLGA5yBkWOlpuuVr5XxALhO0ryV01Vr565vS2TfYcApNws2SgIb27fwKbTXhR2KVWUaMB2uawiyKRUZMwyMoann33Ci+efYVYXPHiww2xasreTk+WQ6xZVZDHgrBoOdoe8+7XXcL5E4alXK0wxRQwhUzlCKHDgbcBbT55rEJExNUBsgpMJhM6QZQ6mINsZ8o//n/+PaN1bGwvisoxyMoqZXFJGL9J6ZJ4RkpUuHDEA6330EISkbiOz6wc/+zk//clP+PFPfsIPf/g3nJ+f8/z0BGMNWRY9GWc91tgk9Ls2p7ClN5MC344IJWXhPC7Y3kPuDCqAXEQBkwcYAEPgqNDsZprXioJ9JdnHMm1WDEIgaxu0MWhrmZYaJeN8d21vsXE9SefQ2iGkpnACKxRGCqZZSZMpxoXgzBqGbUXWVpwbw9pUsYUo0ePWCLzzOOcwLsZRUteT3vP8r3UKvyXHDevwCybtC/WG2IQ6u3T/lz8obngZUtDXBwi/ISYToRPr9DDR9gU7WIOkAFIyyEYZyMgV40XM+3YiJUMKgVUy0hqIiIO2IrAMnspDI+DctVTecy0CpswJWjPcmzLam0Ua6/tRKUzv7IOSNMFjvKDxAa81QmnyLGc022U0mXFw5yFZXqLyEmsEPgicT3wPQtJxPcW+x/F563pN06xRCvJcURYZSolULdoNpoDge2ETf+JA3FQMW97fLY9wkxhwM1S9/dnee+gDxreVSsRAQvAkaDx+UojUfS82vFnMr2jriiLXDIqo5IpCo5RHypQlJlKfZx+t6g4qCR0PeSASwaXMpxhrln2Vb5fw4AOpCxiJiiFDas1sUPaWeJ86K7daRIYun0smA0clhRcSHUf8ubq65vLikp/85Cf8+Cc/5ic//gmfPnnCarWiaZo4lmkPhdB5chuiuG4Rd6O9XevTKeltryw+p4iGUSKLVCSlsPUzUoKxlkwyxUgIBgQyZ2PMwRq0i1QwKkg0cf+5NAyh8+S9RzqPDI7goxJTqVZECclEalohmBEYOUvlPHnolEE0iPp+esmA6IyJ8NL6+uodv3VKoTt+XTe2bs1un9fBN51nILYER8+aKES/yFQSIAKiMvCJTnvjQCN7mbWJBSAiHNTj3UoSABMgIAlK4DOFT1inFQGDwCkdKYwlNEQ66oU31M5x6VqW3rEKjis8PtOonTFHjx6xe+cOj9/9GtODXe68dp/hbIzQip+9/z6VaWmCQ5cl2WDI/YePGI6nTKa7jHf2yYsBUELqLGe9jc2HRIZSGVLphKwFcCl/3wlOj5+xWC6Yzsbs7e6ys7OLEhLvYjWdUhopVV/5K8WGQfPvNN8bUfkr51+INMMieoDOg3cmCT+HFprIrx9brwrAuxZrW85PniNoePzoAcNBtHyDd7GeBYmznmAMLghenJzx4fsfcXTnXbSakekcpXTyhCI1OJCosxVO+F6Wd4qsXzfBofPYCznqL493DpkVCCkJNs6J9yH18oiVNVpnZFlJY1qcizGu6/mcF2dn/MVf/AUf//Jj/u3/+r9xdnbGxcVFSrGNlBJ9clIfb0lCPdUTdHEvsRnY3vMTnWEmN9BsrnUUzM4lKNb1FPEDCcMAowAzJdnNFHt5ziwEJt5TNLG/eOY9uQhkSoB1kXlVpB7cISZaEDpG49itUFgXe1YoepaBsRL4LMeVBZfW0FhHgcAQ+Zs8Ilani1jL4rueCsmr/Yo6CP3xW6sU4GX37raQ8MH3yLWUW5ZOl1Z342I3/+4tT4gehkqhPSe3rNFtLBu6KupAhH66dFIXImdOxJIVaBW9ASGo8BgErQCjNT6ll66sYWUN53VD5SwLHDaTuCzn4NH9yHb5xiMOHtxjur9HNh3hpOB4fsX85CmNtYx3dignU4ZlznA8JR+M2Dk4pCxHDIZTdDEEleF9EmRCIrVChJQwtW1WJzioTd3Fzs/PaJqG8WjMbLrDzmyXPCuSMkgwUfIKNhtN9OO5GcPtAewG3PeKuxvjbtO6zvMQW1QYaS2E4GOQO4ReGaXKP0KIpHbCJj6oPp4ggOhBzHZnrJaXnF1eciRHZHlBMZiiZABhaY2laQxPj0+5OF8RQs7e7hGHR/fZ2T2gHI5T6mdixpXR04oOo9+2raOhIbuOfPGVzqiIjWliJbLwgRBS6qdKqzmlgbqQ0imFwDjLBx9+yKeffspHH33I3/zN33B8fMzzk2Oqqiak2ANbY9nvn+iCRKI7Nt0Bu/W87bWFDorrpzEqD+tiEWWsvo9Cu9OBilj0lkvIlSKTsWpZe7+BXEXiSwoxWN4mr5QgUlovkc0rhBjfSvflJQnu8TQ+7iXjPS4p5zzLKZwjVzIyzvbP5lO6g+gTIrjxs70uv1rHb41SeJVV+Cr46GZQGW4i0t36Dz2Esb0EujXQwwtsr+y0cMLWtk67I4jogm/yuuPG9snKMTbmSQspQSvIIlW1EbDC0whoELRa4ZSkzTPmOOYucOoMjXfUWqAHOdl4yNHX3+DwwV3e/s432DncZzgdc1lXXC4WnD59zqdPn7KsKv7Rf/vPGEynDKcTJrMDisGI4WSKzkryfEggBpDjcESlFwPFIXoE275UGhRrLVVVMb+e473n8OCI8XjMdDIl08WmEfpLCqG7TNhCHm5DPVs02v28RZ+uE2QxVpA6aaVGKFJKfMo28T4mAOiOQz9A6i+H9zYqaB8VgUwpmIQICU5mM+pmwfmzK0bDjGJQpNRHj3eStvGsVp6nT89ZV5ZMj9ndPWL/4A6T6S5alxHqcVFwSpGCl0JEfLB7zgS3iKQwQqIQ77LPEKmuIBUusqUIovcl8IRYUWwtiEBVVXz40Uf89Cc/5r0f/oCf/vSnXF5ecXFxmZrJyKQUAs67LcuYPpoTs8roc8MCHVwXNi9szVanEKKyjqOsotUVFYPYVgqCXInIuZSa2nT9PryQeOGj0USEi7yzvVISouvilgyDqD2SQSb6GEAbAiYEjPd4FddhpnOKzJFJGYtDO6XgAyIVscle8W393ORD+UodvzVK4VXHb0Ja9UrFEeJPt2gFxI3sYqe14H3s5ZosqDZECmwpIpVEV/DWiUwXNpZXRJ5jCmkURWARMbc616iyQA8HMWhM4NobagE1gfOmYlkZjk8rGjytCJR7Aya7M37/W9/krW++w6M3X2d694DWW44vXvDBR+9zOb9i0dTkgxG7Rw/4x//y/8b+wSHFYIzUGSov0PkwdgPLB0ipcWhEKpdz3qWxApUsbKV0rwi6MczzHCklWZbx+uPX8T6wt7/PoBwBMsJOBJSKqashbDozQgezdf/rfrb74Iabv3VzJzbnR+M7AO4GEIhwCOkJ3uCcpapaiiJmREnVpWq2sbqZgFaR9RahWK2vqKsVO7sznj//jJ/+/APef/8XZFpweLCDUpH7armo8EGwf/iIN978Bt/4xu+zu/+AohgRUNjU11npIgpvGRMLfIjWPAGcDak5zE3PNf4ea1REEv5aJwXgidXEzmNcbPOX5ZrluuL09JS/+Ms/59NPP+Ev/vzPeH58zPHxUxaLBcbYnnzQOU9eiJg9lWU9EZx3HilE5F1yXZwk9GMfve2N6dSlwm4rBgCdZygpY2tZICNQCBGZfI2lLHMmgwHZcEDQmoWPlBNOZxgE2nlW1qOJXgU6dTgUItK2AF665LXrHurJpIYQu/kZYuvQlVLUSrKSgmxnytAO4PKC4Nub6y0pB3zXaGsDIX9F9QHwW6AUuqV4w/fefv83UAzQWTU3ryuSQSAg4scpYLhlTMQU0e4nuZqdMumAWZusbU+IWUMIrIp0aBawQsXXlYwQR9tQCWgFLIWlJlATuMbQZAGxO2Q4yJkMSmZ3d5juzbjztUfM7h9R7M9olWDtPEvrqANYmTGcjVLQ+AGHdx+yt3+IDxIhFULnSJUn3pucLsO98xIi30vokYLOOgxbgy5I+fAispzu7OwSfGA0HEUKhZ5MTHBjR/Uewe2/XwUfbfRAN2f03lzo7y3CRNuCC0jEcyFYvLd4b3A2xRhCTM2cL64TlbUnyzOUilxBV1fnVNWCer3GA9OdXZTwKCnIyzEqeT+j8Qilc+4/fIu7997g8OgRRTlFqjwpWZVgkA302KUgd0/Re0rJiwkJIulCn50nms5mkxgRvSTjHM5Zrq5qnj9/zi8//pj33nuPJ0+e8MnHH3N9fcV8voi0DiGmPndkdCF0MNtW/UaPo/c38/Le2fp/zxAAfRV195x9WWBIf4sYS3OALgaMd3YZjScMtSaDTRZfiAkcwbjekEpfFr3vzitQKS6jNnMvZBbhNS8gxBaqMsVxsjxjkGe0bYvXCu+SsZIG+EbDnW1o8yt+fKmVwkvz83dQDC8Xr/Vv0JGx9YBQCMSGaYkvJQi8F1SB1KcgoKROjKjRtQ0iLmIvwEkZF58UWJWa2khoZYYBLquKebXi4nLB0kVG0zAU1ASqANluwWhnzNe/803uPHrA0YP77N+/gypyjIBl1fDhxTHHL86wHlQxZLZ3l6M3dnj73W8xHE8ZjXdBKPp2l1IhVc7GJ0opsMHjXYx16IQ1d7DaRjJ3uHMcK6VicFMgefhwkJCOTbxACtWPpbzVS9N7n5TObcHzKjf9Nu31Zp6EAOsM1rYp5BG3s4rJODhb45xF4DCtoW0Ci8WC1WrJyckJ1jR4bxkOS5RWZJni9PQ5y9Uc7w15kfPP/vm/YGcypswL8qzA+4A1nslkl+Fwwp1HbyJFFrlGYkJywvpTthadyvOpO1tcN9EDELFXs3X9OEsVWWQjX1Eq/POdIhQ46/pg6HKxYL5Y8KMf/Ygf//hH/Omf/SkffPALrq6uqFbLlBkV+kwwIVPitIgQnHM+UUX7ftxdcGA2WTjq10jGTiGItI9CCFhnsS6uMpfgJKljJbT3kM92ufu1r/Po6C6TImfgfWwY5T2FUrG23ZhtwLI3QHQyCLIiAxFSS9wY+8iUxjtoW4cNce9mSjPUmkme02SafLHA/ORHGGtwNlW5p97MUkZoTYmA3Io/fWWxI76kSuEV0YPN/ztE4Zag/6K/X3odUg+CuFE6EMgThbrTGqs1Vmc0WYbLMpSNTJmWyHgqRECIGNT0BBpvsSHQeouxMQe9EQGXvIEqCNoQqLzH5eAHE4qioMw1xe6IYjKmnE0ZH+1QjgdM7+yTDweEYcnpeomvBVZIXBB4ITl4+BpZUTKe7jHd2Wc4mjLa2UPrgkCOD7F7lVRZElJqQ7KKTxaY7Bu6d0JXChlx+ljuvTXm6XdPj5GLBEt08ESAXkjHgb4p+ON7Nz2GVyvym6/16YJEIRoDxgbvDR0hgVSCumpo24bLi8sYDG9NjBmIGG9oTYQOpIpN25WWZJliUBaMx0OEDFhnyPOMwXDAaDJjNBgyGc1SeqlCigylC4TXMQsoREbNaOxvK67et0n3IFJT+M6LioLJ921T43qCRPwRkoHiHCE41qsV1/MFz1+84Bfvv8/x82P++q//Mycnz/n8889ZL1cEF3m1YsV110AmejjBB5x1hM4Z6TKLkqLoxnnjiXXzuQUfbntwJNBOqCRgBVInreyjYeWcx+IRId7DYHeXe2++xbvvfoPd6ZRhplO3Qo/SSQ2lOIIgxEwHIeIaTV5M/x1sWGul1DEd1yYPRQi8ihTbIctZNDXPTk/I/93/jgge7yzGOYz3yUvewEU9t1M3f8HxVTy+dErhi2yU2+Lj16ak8rJi2C7V7z7ZKQQvYiqeVwqnFEZrWqUwWiGUwiOxBKySUbgJh/GRoroKnjZ4au9ovMMSqHGRn0gIVh4M4DNFPhpQTicMpiOyQcn4aI/ZwT57d4/YuXuAHhQ4LWm9pXGW69Ua6wNBaXRRkuU5e3cfMBpN2T04YjTZpRyM8U4QQmQ1DSGmWyqZEYXTFuTS2bWdUrgRbBQgYh682Db1k0xwXbphN6Zi+99ukroA4E0lsJmq8OoJ3Zqzno4gdAVwlhhDiMVG3huct5GkjoB0gvV6xXq14vziBU3d0NZtT11QlmXKvpGR30cEMq3Js4yyKBgOhwgJjWnj63lBUQwpBiPGkx20ztEqo218hNy8pMPaeoNbif75OyptQeiz3noCBZ9glz6m0FXU+01GXHqrCyTPr684OTnlg48+4vvf/z6ffPIJf/3Xf03T1Jg2UXunrKw4dxvSt3jpLk62ufZ2CnaXHrupML85OVt+4+bv/lmTQSHj93rhe8jMJZNLSkE2HrN79x4P33mbg719xqMRPX6mYwA8RtY7igyXDDgJHWFdj/VCHxuQqRNi1AjRK8p07CmhNZdXV9hBiZ6MEdUav17jUtX2FgJ5MxuLbQ/4q3d86ZTCFyBE9DLn73LNG5lIod8EtYxtLUHRZhpT5JjBgGWec6EUTwm0eAolYnGNd/i2IgSL9YbWGoyz1BacDHgFTkGQoCeacjRkvDvj8b0jhtMpu3fuUI6GDCYjysmYrCgop2NWTcOirjitK9pqSeM8eTkiHwzZObpDORyxd3iXwWhCORiiixFCalAZUmWYoGK3ryDwrgsLCpzdhmq6NE0B+K50k66wrIf4vYp7cnvsk3cQM182HkEIAedNamco6fsJ4HuhQ38HYevvzUxu9HS/23G2xQeXBE1Ai6iQgrcYU1HXFXW95np+hTFt7DDXGoyx8bwQC7GsNYDg/r37KUge71IKyMsYU8i0YjAYsK7WXC8WWGswbcvpyQu0umC9VzMcjpmMp2hVRjoEIaLQ85YQooJVWQx+OudSQoygq5sPIfL1EETE+EPycVRSHp1Qw8c8f6KQf/rZZ5ycnvAf//TP+OWnn/Kjn/2UJ599zvX1gtVqjVYx5TKOaew0HoPnHmNtxOJFHEel5Q166O1m9d0G62dlYwts3tvefF16N6FPYXU2Zn0prUB6ggSDxwsQKufKtny+uOLEtAgCajRAb/V+iGuAHhbqb2B749/AetP/RFLQUiW6DY/DY72ndY6FECyVIgxGiHKILCqCsbgAjXU0xtA0TTREkmUTOo6yr+jxpVMKv+roMMzf9Lit+W//7jshhMBLiZMKqxQVgoV3nDU1VV2TNTU6+JhZoSLjoshyQpnFrk5Sk2UKPciQhUbmmnJWUI6HTPd2mB7uM5iMmOzuIRP/vVeaRgmMM9TBUQMhL1AIRjqPtBPDCZPpLsVg1KeU5sUAoQtA4oWkI9sIoWsOwsYT2naHxNY+6sehO2kTiOyVAxthcVtNb7y0LcEiuk5lnVKQN7//18xPPC0kGdBdi2gFi+QdOIsxDev1gvn8mrqpsNZQVesIZSEZDYdReSFxyXocDccURSTrS2ntZDp6SlJKRkOPUhnGeKpqTV1VVE3k68l0CUgG5ZAsk0gV4aiQFKpPzy+63qKi97nom/wkIzeO7UbdihRkxfkYaHUOW62pqzVXlxd88OEHPH32jF/8+Ed8fnzM8ZPPmF9d0dRN7CSWrtEHiVMcovf9eojuVRxgrx7/WzNEx821mZ1b5/c2RyfIfb9+fHq9dY6r5ZLPTp7zi48/5mK55PT6Cq1kgtXC5ruD76msu8K6HuJPiiuESEy4dZcEBM6Y2P4ziXUXAsvVipPTU67XK9ZtG2GjDv7sYKM0XpsxuAmXfdWO3yql8F963Aw6C0jWrUPgpMIpTas01yFw0rR8cHnF/OIM6opMCnIt2d+bMChLJtMR49mQwbBgvDNhOB6ws7/DdG+HcjRgtDehGJSU4yHkGi9jgdFyXXE1X3B6fkbVNKyNoSgHlKMxR3cfMZ7MOLh7j7IcUZYjlC4RMkOqAqWy2OxcakKyRFNGHTZ0T0SiWdg8ZVzgG+ungw3oMoa6KrutjdCTfAtx4/WQPI7tZiQ+OHA3X4syQm3uYXse2L65dN20833wxAREF2M23uBcQwgO5wxVveDF2QnHx8dMp2NCCMznc0aDEYPRgEePHlPkJRvARjAeTdBKo7VOLUIFeNMLniIf4JyN2Sk2cF6dcXl5hTEmelsBdma7qEyjs5ymblFKo3SObeN9ujagM43OMmRK2nTexLEOctOg08cUTxWIsQTnoDFgDKFtWb044fMnT/irv/orfvDj93jy9CkfPHnCoqq4qmqQkkIp8mKQOuy5JDQj5BIIeBFQUiY5GvpxvqkEQr8nbpBJ3jakti2I8CphGV+TnaHtNgHsjnG1MS2fPH1K4xxPT84Yj8eMpqO+piXWTMTiwuCiUrCpt4N3lmBDT+PhQ8C4TY1FF4C31lI3NTbRzmdaU5SRMqRuaj767DPapsG0JgbgtUZlOqYrd9liPaR3+xm/WseXUin8yjkJm8W8/e/m7Zc/va0IOutYpDQ2ESRaZAiR4VFU1nNZNTxfrPhsvWbZtJRCMh0PUaMh07deY29/h8eP77O3N2M8GTKZjsgKTTnI0XnsSiWyWJa/MJbTFy9YVmuuV0ukytBZwe1wJCAAALTYSURBVGT/LvvlgPHOXvQKxlMG5Qid5ZSjCVJplNQgMwQKKTR09AlBRkI3RN8b0bvE2qplb3fJZOXF/dwV/Gxw4b7ol4Rzdwnot5yEm0McK4k9buMVbI1zV5DVdf7yoWOkFQmG6ARLuOG1dDEDCOgEwTlnaZsVq9U1z58fU9dVymISHOzt90HSO4d3mYynjEdjxqMpOotptzKxmioRFYHzkUWUIFIWVVRPTbPG2sBsso8IiqZuYg+EtiGEwGKx4rPPnyFUzngMWRaVTggenenkqaUiqJR8cNO0TY20ifCRSBTTwhhC1eAuLqmvrlleXvLv/vW/5vT5c549e8bZxRntckG+WjN0liBSv2TvwbR0npoUKhb+SrmpmUmFfT4lFsRE6S1P4dcB5psQycta/cb6iF6EDCDczVOzLCrhoAXGGE5fvOB6vkApFYPLfZC344/aQEfd3Ibg+zBDx9MUkw/YPEu6J+tcgsziWCit8SGyxq7W60SsF+sybPCJCM8nQ6SjR2GjIPxXUzt8KZXCb3L8JoHmV3wqbt604mPcKhG1iRhMbgOsjeW6bbloW1bWMk4WYD4YEGYz9P4Bowf32TncYzabMJuN0VqiM5EyYyytb2lNy7ptOJ8vuV4suFwuGIzGzHaGjHcPme3scef+I4rRhHI0TZtNgMzS3UIgSshouUdFIOigIhkLbxKFfZ/qns4KdHs2AbNJUPd569zcxFvoUzq2IbfNGHbjv/EMxA0lfYMyO23kbaPzpoveXcP1/3b9DZxvaduK1XLByfNj1uslWmfs7Oyyu7tHVTUIIZhMJozHU0bDMWU53CgDlSGlxlrXY+jeRYEYeYrieDgrcVYwGo1x1jOd7OB8QFVrlqsFdd3gueaorinLIWUxxIcYV1AqERumrK2OCiKOXo93dElfUQg6B8bi1ivsYkn7/Dnzk1Mun5/wk//rP3F1ccm6WmOcQXnH0LlYMCkl6xAwwWOc3age1fUXTgR/ceB79R/1UtgEkn+FQugI+7rpD2xiQS95fEkhCLoUWjZ9sAUoEeMYQmqstVzP5xhzfqOaOl4nPYkPt67d/wVsJUWELszc5c5tmF1DB1slwd7De10fjW46QkhNqzYMxemL/1YQ9e/i8VurFH7d8SqF4X0HUXSiNT6+CyE2J0fgdIYvSvxgSC018yC4ag0vzi/Jr6740dNjMi0ZDjWPHhxx53CPb37z60wnQ2bTESYFSYWCfFAymow5fPw2b05nHN1/QFaUZMUApXOkylD5KGYNeRFL+YkQhpBywyHUZZV0tm3YUEmoxGKaZTG+4bGQ2Dc7uuM4FCnD48YW72CmKLE3je3pBfmvGt94Dx0m3J0ff3fW4rynbbsiKmK/BaXQWkbIxRmMaQjeMxzmOGdo24a2rTBty2JxRVWtWa9WONtC2PSiyLKCO0f3KYoBo9E4jVMsXhJComX0qgLQNg0CQZYV6CJy4gTrsC7gbKAoJwwEENZonTEaTri4vKBuGtZVw3icMRqNGAyHFIOy93601piUNkoqACSlOkohyGQetbX3qbTdQVNjFwva5YKPf/BDzj77nI//8w+4fvqc+mrOm+UAcXCAtZaGQEvgMlgum5pnyyWfXc+5blsMBpme03mfxtP3IGHo/2NjfX+BMnhVOvftM7sVuH1+xx0koumS3vU9pNnUsdezUBoXIntrx9WkdUwl7VOAbsc3/CaGsemF1n2fQmzBoYHQG4nd/fRQ6bY3khZ2jDckD0pJtNaRnkSwdS9fXcXwW60Ufh119jbdb4eHhvS5KAujSx3J67qesxLftcAUIioKiDhnAN86hIR5BU4IrpYVbRCMRwNmswGj8ZDBoOTegzuU4xk7B4fsHNxnMt1hsnMnKgOdEbNEJIi8t9q7nPf4DH1frf6JuhzyGwBb1x+gh+m3zf1kYXUSP4hb73dqIgmSRHlMB/98EZDXb5qtzdP/2uEOUVnINK6yUxjBpbTSyFXU0VHX9Yq6rlgs51SrJda0GNMmrN8xHI7I88jmOhgMU9rogKIYoLOiT1rpuro53z2iTD0YOmhL9UHwWBvg2MaxROrB0Ck452Pby41A3cpp95YupTTmtHeFT0AqdnStxbcGW1tsXbM+O2P14pT1xTmf/ehHLE5PWT1/Rri6Jl83TLO8r+JtpMCk3h8ox0przoSgBup055H5OwliXtGV7jc4NpXjonfpbtvpMr0ot9ZZ9Ay2ws8hgJD935skhNTRbUvYdunR9J/f+saw+Y5Xo1edj7TxYrbXaqcIww0X9RXj0VGF9zwsYeu7v3D1/84fv9VKAb4YRtqqv0rnsUEskg0VLT6FFAGvBEEJgooVyVEhyKQUomBzMjYNFw4aB9XxNZ8/v+bnHz2lKBTTac43v/V1Hr/2iG999x9y9/49Hr72OsPhLlk2QGUFiET4lWAcGRJZmZT4Lp0y5ZbEIOX2w9Lf/Qa2CZuYKvFX32dXyW7rdt70KxZ66NsTEvyG76//VPxt+4ObX7sUx/S6T8pEdMVwxJRJETmLQojKoGnqlF3kKXONEPDi7IzLywuOj58xv77COct0OiXPCoqi5GD/CKU0zsNwOGY0HJMVQ1SWE1BReLuI8RME1vq+LkHng43gScF1oRKLq/SJJM8jZfxRGqQWoATOW6wztKbFuZQJo5InZB1ZXiCEwDmbMLyOfTPgXKBZrKiXFavLBcvLKz77+c84/fADLj97wuLjT1GNYerhICiGZc6sbZEhdjQzKmbDxZotSSU1p0LQEJVCK2L6gPd+05i+s4y3KaVeggVfMszja69ATiTxepLUW4QUP9heDyEqpgAJxukuEl/zKeOnK9qDmLp7w5u9cbubvzrRv736OpL6G7cqwg2xH7r4WWCTqXTr2UTqg96n6r7i+7+Kx2+FUtgW+r+KzuIlKu1X2EzbFkCEIT1BOHywuK5AKsR0NkvACggkuEYKgkwCVKQiIQQeR+sCy7XjZ794wpNn57y4qnjt9df41re/wxtvfJ3dvUPu3r1PXhQxPTJhoNZ2JT6x1SWkep0QkB19NdvFSJ0pc3PhblzpToDf3khi67VuRDYu9augot5z6AcubNJe00h2hVrbaY4dT0+XUdSnTRKIqasOZw3WNFRrQwiuZ6/0ffaKRKAoyyGz2S6z6Ywsz9FZkfoI5ChdgJA4D4hYqxFSNbdSKpHIGXKdJWEpE4+Oj9XbKgpbGVJlsYwCx9gG56OQz3NNXuSUZYkQAe8tilihrIoMEVzk8Q8xlkSweGuwbcvq8oLTZ885PzlleX7N6vKK4w8+pDo5ob24YNBWDJHs5wUjFyi9Z+JtnzjQdsHQLMMEwY7OmQjJirhxbddfIMVxJAkr99uZZreWw9byubFdxCZt9Qaldvpcd/0uDXYD+yR/VMSolw9b353ekyKty74j39Y+7tdd53F2wr1LF+28gc0CFenmtw287YcUXe1DWkrJSU6OrNikvHZFfenv7cQLgcB9RX2FL79S+Nsq7a3d8JICEb1sS0ZjSBsjZTZvZSF4kci9IC4kkbJ9ZKwcjskkMn1PhCsaE6jOrpCXcyrjubiu8KLEupI7dw1ZMWY8mSBkTp4s5C67wncbZ+sRwtYGpt/E4sZG2naab1o6rxq4beXYbb6w+extSwqS5xC2Phr6925qkg2ktJ0psqlz8iAiaZ13BmNqqvWK1lSE4BkUJSJEHqYsy1E+kOclZTlkNJowGk3I84KsKPtYhvORwsEn5dRbqSFagCE1DOpqCro14VMHttA5Dr1CsrF4zbax/SMhNXaPfXxjD98Y1ZdSIrSMqaTegTcE22BtTbNe0VZrLl8cc3b8OafPjmnmK+r5gur6BFtdIcyaXHgKESiEp5CCkkDmPMIn4eoCCEWhFSUwlIpCCApihEgGYvMnqW5UI2/HDsJLv7z6iIJ9k4Bw4/wtFKZjGO6WTje9XXyh6xsh40jF8r0+0Cv76EDYdkkRGw/1hjf88m2L/vzQL8ubT5sSHUL3V+gVQ9w6W3umg5S3g96by3xljy+3UuiMh7/DR18FK3ULvmdwECBFiLCBcCjhUNKjFJFQTEYCs6gY4oe0Kkl5cXT1SkrFXrd17QhCIaTk7KJhsf6Ejz895T/8n3/FbHeHP/rjP+btr32Nb3/nOzx69CjSK5DgFgRSxU3lvI+9haXoeZo60R1I7Qk7Ns0UiL7FP9eNwtbvvv+321jbXlPgVeN8y5HvdE2AvkgpQQp0t4pIaZJReSrZUWx4RCpCm8/POT97wZMnH1MUBXmesb+zT1GUvPX6W7FVpZAMyxE6L8nzMlr5DubXa5qmoa7rGDdQktF4TJblEWoqBxHO8fS04SJECmhr2r4A1gUb89udIdfRLnx+/Bl1tWK9XmCaBilgNp0ym+1wsD9jWGTkKrWcDC4Gjm1NsC2mmnNxccL52XM++ehnrBdXrK8vUN6REfi9t15nlO1S/OEj1i+uqc8WfPaDn1GdX3H57CmD6R55PsRVa6SHDJ34iByZFxRCMBQwEoqhUBTB4YgtJmWIlBI2BXn7Nc5Nb+CLZF2fORaSYghbBkYIESTsMoNCaksLqN786LqxhVSZEg2c6HfHroJdn2WZQtKdhwnRIIqfCT3z6qvMjc4J9lvYWBcPCH3xICnjqDtDdqZK3AJio9hkUiBKSBSx22LUJ+Flg/IrdHy5lUJ3dOb9K+bppTqF3pIVL70fbu+QLTnXU+OFTdtNhY/0vkIgE6+8SA0+NlZSMjn7/oZRGFob8JWhNQuqpuXy+gqlFZeXlyxTn9yjO3e4d/cOIQSsdejUGKSjau7Mll5wp6Ix0bUSTD5y6GoWevc33YvYJprY8gxuwFBb39APj7jxz+3jRm3rVsAw9DEGvwm84lMswSSlYGnbmqpesVhc07YlZVmyv3OAVhllMaRpDNY6zs6uqJuWqm5ZLJbUTcNiMaeqa+q6xgM6y9jZ3WU8njAeTTg4PKIsB4zHU/IyckWVRR6FnZLRkk2WqxABKXzyEgzz+SVtU8VMJxxKBgZFRpFLMgkyGPAKVGQ6DcZwefac9fKa0+dPmF+fM79+Qb26BNcyG4F0Hh08g7xlkAkGWqHHiqLNuZ6WiCqjxmLbisYHBl3/Au9SYFxumLhDXJ+dT9lZ7p0w7cSf66ZlW4lvLftu7m7O4RY8s/VX1ztEpliJTkpCEDqy8NREJ3KCbZAnQZMUl6LrK5K6p23tun77pDX0ihXWC+rOc+35mkInGra95M3NhyBeXsLbXkF/XqCrxt/2fr6qauG3Qyl8wexsGDm7iQ033ns5AC02mwvAxYUR2wdGqgLhLMI7pLNkwZMTC4+CI62iLYupizWkimARVG/ZWwfBWmxlsVeXhOD59MknHN25y3s//jF12/LNb3yD+/fu4JyjbVvUoEj59ZsCtKgEouD1ohP0ibSu22Ah4L1MOerRQRZi4zJ3GSBdDKFLyrgtMF7aQluy4rbLvRnnsFVo1DXr8T2JnfDxd2trpIqYfNOsWa+XzOfX5HlN245Qj3OyrCTPB6xWhsWi4pcffcKz4xM+ffIZH/7yY66uLjk5eU5V11RNjUhkd3fv3uXo6A6Hh0d8/d1vcHh4yNe+9g7T2Q6jyYT9/V2yLENrHfs1e9dnQwkREMFgTcX5+QneGvJMApZMC4YDzSCX5NIhfB0rdnMI7Rq7mvPpBz/g+bPP+eEPvo9pF3i75q3X7rEzG/HwaAdbrXFNxUAvyWWDRiMLTzYR7O2NkNWKuQo01YqlrxkW41Sp7hINR/RY6ap8gyNstZLcLOeAStojQmZp0vouUrd2wm0bq1Pu6bqdwlFEKg4dQt9Ap+tAnRPIEBRISqXi9/vIVuoIrJzHEjBAS6SI77yHuLZSUWEX2+rMk14JpOfrM+XSupYq1nqQGhi9JB/kzettnXAzvTVdNaRWpL4Lft9a8y8P35fkeMXE/j0cX26lcMOAETc0+5ZhHBfwlgLoAkYdjPHSNdNyU0IiQkA7ibKgHZQoRkgmSEYhtvYTIqaleg9BRszU+VjLGyDx6nc4Zkw19SmVsXEtWtB375rPr/jwow/4f/9//ifu3r3D+x/8jHfefpt33/063g7JMk1RRMprkeCrOAYekWIeneiPkJZMXC4bdtQOI+mKs0hwk0BCFyhPZaLRsuruPaXW9OZW9+O3Bi9ts06xdB8PMUgriNxkMjh8MDRNxXI15+T5M66uL6iqNVIK8iznu9/9Y4p8QAiSJ58dc3X5c05PzwipZ/RoNGYy2+O733vIP/0f/gVa61hBnAwA56OA9N5TVRXrdcWLFy/46MOP+NM//XOGozGj8YR/9t/9M46ODnnw4C5Fpsi0wLYGESwiGKT05DLw+MFdVqs5i+tLpKtABApRkAWQFq5Oj2nrmpPTE67OXnB+cszi+gy84Z3XRkzH+0wnBaNSoGVAh4bKrKjbJVJopCrIsgFa5ogyw92doE3N9XRMtvZkTVxLnYUblCJoSeUNK+dZWkvlAw0RNnIQ10m/ErdhE7bmcWtT9Hvg5gxHWKUj7UvVACHEZjgICmKfhZxACWTArMgYKM04y5gVOZlUBOMwztNYz3XTUjvHtbdUeNZARfQYDJEexbuYQbchw+65Grf8hWgEhc6g6QLpAkRKLBBhyzP2Ww+4sWZuiIG45JMnK0KMESnZq6dtb6mr8bmZ1Pr3JZC3DFlu7rbNq1903KIgeMU1/y7Hl1spQIeC3Dj64ppXvN77lP3nO+unP2mTFUH8XYZYkam8QCPIEQyEYCgErZRIAjZEt9wmVzW6w3ExyxCXb2BLIaWCouB9pL1Iz9I0DVXbslwuOX5+zGQyxlrDbDbB7e8xGJSEMIxsnFKlAF1n5ScaiGQ9Khl5/TcNEgWxwU63rDcI701oaIMBd1kZIY2VSKkaQXSFcttT0SmRkBAjsTU3sQYhEJA+4ENL8AbrGup6zeXVOWcvTlmvVkxnU/Q0YzqdoWSOaT3z+Yqz80uOj08pihGDYsje3iE7e/scHB1x7/59xuMxk8mk58yxzmCMYT6/5vT0lBcvXnB5cUFdV3z66acIqSjKAa89fow1hkGZMRoWFLlGBYMUnkw4hA4ILKNBgTealXBILASHNyuMaFm7isX1BdV6yYunT7m6eMH56QnB1wwKzdHejP29Cfu7Y2SoCc5gqxanLVYalLIopdEqkIlYnTwcZ9SjnLIsoG4huK2pEqnPt6ANnsY7KmdjH+K0/vzGPOin+daOYDO7L+NIvVUstiBHUu9iYnxAp5+cqAgKYASUUrCvM0aZZlYU7JQFhVQE7WiMpxaWwgbWQYD3JDIQAlEh0D9DbMjTG3y37nTbxu9/6zXf5vn7znWvGoIvUAxbFtPGiNo66yagdvu6v4pa+1cJ5RvC6car27Dey1d4lXJIe/ml9141ar/58eVXCr/B0S+k2wrg1iFS9W+3AH3wCRNV5EJSCBg4x44UHBYZb0zGzJ0F56hNS2sNlYs92IMSWB+wARo6SydyqrgQaE2DklBmEm8NznqMI1VOCmzmaFvDv/7X/4af/uQn/MWf/xn/6n/473nw4B6PHj1I5G2SqlrhvQEMUgaUgN3ZhLIoGI3GkRtJRitUSIVQBdbGIHiRDVOhVqK3C4FgHYiQ0nE7N35rxNIG3U7n9X7LjhPpdBlxWNdRPuOxrsGahrpaYEyD84bBoMCYmqZpyIsy0kuguTi/5rMnJ1xeLrDGcXR4nzff/Dr/5J/8j9y7cz8ymw4GdE2epY4KLlJjJ2EWYj5+21jwkCnNwwcPmYynlMWQ9z/4gKfHz/n+97/PRx99yEcf3GE8KhmUOUd7Q0Zlzt50yKhUaB1YLc9wpmKc+dgwydQcf/yE9fKa+eU5TbVES8Ebrz/k4dcO2P3u63hbQbBkwqKkQ7kLBlqgNWSjAXlYoq1gNsrJs5xcZbD2BFMjtSArNOPRkKuzmmZRMxoWaBWVfRMCjfesgLl3XLYNS++pAIfs/YMuuIzovGa4gduz6e/QeYk9bPqKXOQC3xtHsW0TDJOHMAb2Ms0409wbDZOXULBbFBRSEqyntZ7aeM6lYmkMx2uYe8uVt1wRGYGXROVg2Xg9nbKLxhdbPI0vuT/9Wg14xFZR5rZAj7/ftLtvHluiWLy8Fbo3ukyqKGc2ysNv3dsGxdi6uVt38qut/pfv7Ferll+lQv7LvJgvpVL4zYcuHWFr4bxi/MVtM2TrddGZ996Bs2hnGUrYzTUPJmOm3oKxVI2iaRVLYzE+9lloiT2YK0LsxUy30FO7y5Agp9SNSombiyuESAXw4vQFEtgZj7nz6SGPH91nMCwZlEW8YrB4V5HryNS63pmlNMkSlcWK3p29I4rBkHI8pev84l1XwduRECRyAO+x3vUBbWctELuxbfJfuRGnESlIEZL3E7Z570VUCnW1oqqWnL14nnoNeEajAcZYRqPIS+Sdx7QOKQ3WSvZ2C4TQvPbam0ynO+zu7TMaTyjyWI/QKdHOO+yCjNZ7qtWaqlpzdnbGcrlgvV6T5zm7u7uUgyEHh4cslksOj44oy4LRoMCaGmcbnnzyKRJHITx3DqeMhhnL+XO8rfF2RaYcUniUXVOIhknhGSlFphUHs4JBASpUOLMkOIMTJrqb0uO6JjxGYKo1bbWmbWrwMbVZGoVwkrY11HXDcrmO7J5KIrQmKI0XCitV7ONtbPyxhjr4XnjatNY2VIIbD7hPb/Zpfd+wJ9N7ImwEHfQB5IzoFZQEhkAJ7ErFUEp2lWI/zxhnmkOdM5SKSYCJtWRCInz0plsBOlOMCYgiZ+QEpYsQ7Tp4RIgwWJPuyG7ZJyLdY1xV27xEG36jl8ocuvNuGTg3n/glEGnrp1/2t46QYKo0tsnl3zQnenVV9Rcf2zcVXv1O92xi67nSzW0/74bQ49VK8++qFr6USuG/9OihEEhu3kaw9WRlqZhJpPz54AzCGrRtmUiip7A7Za2AtmW91tR1zdW6praWhfHUQmACFAhaYpVpQ3Lvg8MmSmPnY2GM6uH69N1IgnOcv7jg6vyS+eUVs+mYRw+O2N2bsbs7ZWeSI4XD1FeMyoxhmXE5m6GUwgdBMZhQDia89fVvMtvdpSwFwoMIIrnlOuLZMoeukXqXiplHio2miVTQeRbpIELkTogBy+CRKnHKCI91HmdbQnC9VSpEjCesV3MuL8/55NNfxsweKRmPxxRFyc7OLlJoQhBcXy/IcovWI4aDKcPhmLfffocsyxFKE1wskrPeI5AItaV/hOipkq+vr5nPr3n69Clt2+CsYWdnh52dEfsHh4wnEwbDQWx4b1rWqwXHTz/l7PQ5P/3gA5bXl6yvz3n37Ucc7I5ZXH5GcBUyVBzsDhkNc3anJYPcsZvnSJlR5JoHB0NMW1NV11TXl3jbkmtPpiV5JjBGxVaszrNeXFMt51SjKS5zGOHI/QDlcqqqYbmsuLy6RltBlmnIc5AaLwRGSRrg2lRcty3Xbcs6eGqS8SEChtBb151U7ai6eyQ19P/r4wWdOPMh3ICKFBEiypNCmAIjBPd1xjTTHJVlVApKsaM0BVA6T+F8/Hyq53EIhlpRS8FABK6sYGIhawMLB8J5VgRWac92kJJlY/V3/qkX3Z5JnpHfZjdKVO4bF7c/ugZHr4RYwkYNvmSGis2QbfsE/dkp4URucNf+Xm6gtGy/d/v3V9zO9me3FMDmHm5DWl2nixtXivf/CoX4m1Zq/+4pBbFRwAFeWa9Aet2HFLwVIINHBodyhtIZRt6yAwyFIJOCUBR4pVlmJbWxzOuapXVULrBwgbX3XDvDkkBDrEZugTq56Q4wvqs+lSl25pMlF12Iy4tL1ssFzWrO/fuHBHvEmw++yd7umMOdt1gtLqlX1wwyh3ctVVWxWFxw5eH4s/cZjMYc3rvP4zfe5uDwLrO9e0hVRAgm2LishUIokChaE7diUQ56QWGNIYS0uTtPwacsHRnAW0RwtG2N96n61xmstSwW11TVij4wGAJtaylLze7OfuwPoTJ2ZjXGOEzrmUx3yPMS6wJBODKpIuMoMRVSBI/w4kaVbsdpM5lNKQclw+GQECKYMpvN0DpDKd0zZOq8IBQFw7JgNiqpHz2gkI7nzz7jw5+/R1lk5JlgdzKgzAqmo12mY0WZCwrt8dZi24amWWEsrOcKgkc6QyYanDB406bx1bE3tg/YxiB8fCYRBArFIBuiTE4wimZlqBYtq4Vjr5wwGg0QWYkJsDSei9Zy7R3H6xXnrWVuHSsfolKQnZewJZJ6Szf0bKkb1H17i2ziBzIJuy6AnJNiBsAucJRl7OiMR8MhU51xmOdMCBQhUDYNynm0s+QhpErvDYdYLgVGCIaZZE9nHATFWCvmzjE2lkvruLaOOfGZ5gRMiIpOEI0a2z2RCElwitSvolNsW2a18J3VtbG2b0AH3XNvKYQgewVxOy7R2+Bb0JCAWLvR11NshE1fNc2vEv9/X0fY+vni42+NuvBboRR+xWO9YjxiVs7m7ZvIXjeBWx/svIgQomLwDuU92nlK71HeU6ZFIKRioGN63cgHFtJROc/ABlbOxQ3mLetA6k8bC8265ejC1gbuMj3Y8Bu1dYM3LVfeMkxeQb2uCJMB09EYzIrQKgodNx4Z1K7F21gQVq9LvG8oigxnW5TOycsJxSCJBaH6QRFiw1kvpUr3FCkgeusnRKHcf8g7CA6Bp21rjGlp2tj9zFmLsS0IGA6HvWAvigFlOaAsRwwGI7TOkaLA2oA1nvFkhtIZy+UqwgNCIsRtBswtKEt2EBfkeY7WijzLUs2BYDwex74CLtCaFmsdWZZFWERLhqViPCq5d+8e3ja8OJ6hlMQ7S1lkjAeC3Z2MURnItUfR4AWYEPDGpnGIhW1Sxt4PsTguxnu0jIWPBIEToFPDFy0VSmq0yqCVeOtpqpa2NjiXOLh0RtAa56AVhqXzLKxh0RqW1lF73+PwrlMI27mlop+2/s+e/UpsIgrboEmMqcW4QQF93GAkBHtCcKgzdvOcO3nORCn2pGTgLXnwZDambitryUIUqUrSKwWlBLmUKB3rPHIkbaYpZIRdu0SP4D06REbYbrd31Qx9RlLYunex+b0jBbzZv/kWlHzj2HgG23GXTm50Gea9aOj+Djf8gJcs8Zuexc3v7inpX3pvu5L7N1Aj4uZUp5t6+UFvwEw3vvk3Or6ESuG2H7V9/O317+1PdAVq3V8d+qoJaO/RzqCNITOGvK5Q1ZqJseQ+kKX2jkIq5GTC2gVqH7hwnoVznFrDcbXi2hhOXMsyQBZgTfQaBGCCj4FgojusdRHvMniC9TETp2kxVc2LZydUlxc8fniE+md/hJYtWjj2dqcMy4zJ8C6r1YKqWnMxXyUP5ow/+5NfsKotf/hH/x0PHr3Ju9/8QwazfVQ+wDRN2rQKZPSiXLDIVCgVISQSv00cKpEqrYNrkQkqOj15ynK1ZL1ep1x6wc7OjL3dXd588w3m8wVN03L3zn3yfEBZDGNfaaEYjIYEH3Auhj+six4DIrFn6lRQ1iuEKNSkUpERNfhYISsAFNlgGAOnAqSSSTA6yiKHApRKtOEhgiS+0Dx+/IhhqRCu4vln7/Pi7JR3Xp8y3SnYPyhRYY0MLdI7ZAZykDMqh0gR2J3kKBV7Niy0x7Qt3ueUhWZYZqgsBw9WNWhZUGSG2WgHrQYoSqrVmvWLNRdPz1lezCm0xIVAZTyyzGkUrJGcrlecrCuOG8PCB66Ja6kBmhDwnaCX2+u7+7/shb4UMjKvdo2RQldvECiI8YNR+hkCD5RiR2seliX3ygG7ecYdpSi8p2wbtGlRzlF4hwpRiGSdLeYcLsQeyU6Al4JBoRkrTZtpBlqxUoodnXGReS6c57hpWThHZlqWxMB6RoSUJNyIoXQ03SlshtsyADfPv/XCDQG5UQabErxfcaTULN85Fr2x1FH93Rz3bWl1491t5OI2UvWrbuDX2sNfGIJ/+UKvQEu+6PgSKgXY0oN0v7yUlvqrP/rSEdi6aoKYYqVyl8lCP2sxo1+QCYkSMmZheI92DuWjhZgrRU5kqlRKMJAKJUExZJoZMqe4to68NVwnl7/Dgg0CJ2Si7iU1gd8EboMHaxx1CJyfXSGD5wc//Cl3DsYc7A5Rd/cpioKy1IiQkymHDy2OnD0ZYZL5quHF8cc01ZKmqXjw2ttMdw8ZTveQMkvrpMtJ9xhjsK1FKxUbvSMhFUrZtsWYhquLU6SKtRNVtaJtauq6QmtNlmmU0mQ6J89KZtMM5wNFMYw0IEisjQFqITSR0lr282Wd7X+XScJLRK8UOq/m5pyGrW2efkvSoos9AFhrk8IQsd2jdRRlyXA4YjKZ8nFdc3lxiX7ngDyPvZx10Eg8mSjABoJp8LaNPSKqNVmWk2VZso5TC6SOHysJZCk0wsuYaWpCzOFvK+anV1w/u2Z9tcQ3jsl4RqaGCFmwdBGSvGxbrozhyhpWIbDeWj/RU0j14uKmRxzp10XvIaRKlkTrEBLVtScjbv5hUgwzBDtKMVWSR0XOjtLcz3MOtGIqBGNjyJwjN4YsVWkX6fqamJZNqgyW6ccRLXxlu6rngBGKjEhNr7WmUHFnjmxMx712jjJ45rg+CK3Sc8d2zgIZYo2QJyoFv/38W2Lg1QI3cRd0MNPW6113vFunv7zubmFE4tapgS+WTy8VDfaf3Wj2lwV+uH3yK19+6T5vfeQ3Nam/lErhvwyPe9k3uPmn6JVMZH4MPfNjVw4gQsT9M6kIUlMITx4smXNo69BKM1CaUkQ3OJOSEYJCSUqtWPqC0mZcNDXaO6TxrJN1ZhC0QuCUxAuJE2DwOH+TDtiZQGMd5+fX1Os1TTXnW19/jeyth0iVkeUFRS5QZOTagsjQWclodsDdowOuFxX/9t//Oacnn/Ps+DPqpuLBozd5fVwi1SBWy5KwDxzWVCyXK8qiQCsVm9QED8GxrhasVgs+/vhDsjwjLzLaxmBaQ9PUQIHWCp3l6KxEq4LBoETpDG+7Gg6FMS3WenQmUUqSadXTNNRN7KIWi4hU8lziJvWpa1pgC0bayoyKPkXyEHoOnBgT6dhapZTkSuOdw1lLmZcMByMm4ynrqubs8hKVZeg8Q6rY/lSJQKkCrrEYGzBtgzOGWmlCYRE+8mDJWGYb7zWtodgtLwMv8SYQmthUyM5brp6dcfrpGavLBdIqJpNdAjk+KK4ax8JazpuGi9ZwZSzLACti4VeXvulCCsIGSI/+ErVFD46EkBJYY9wlI2YY5cCE6B0cCMlhlrGXZ7wxHDBTiiOpmQnBKATKNnoHum0phECLyMckRYyZdYyjCfAjEGt7vE+JfUTW4aCgECCkplSKUaq3mVuH8oIBhtIaBJ4qCcaG6AWqLjPOx1hDp/QQ0Vvq/f8vECDd1LxSLnQQUgdpfZFx2XlE3CTl63XMS9DN9jd0526M3u7vl+osetbB7uK38KpbL924x5e+9dd4RLeOL6VS+OLjCx20W8dtzbqheO4u0zU97yYqJAUQZI4TGusV1seceqUgyyAXklJapPeIZoVKu3CoFDqxdA60ptWK/WzItc65owqO64YrYzluayoCVQisbcAIgemEL5ugYXdPPggWK0dVe+ra4OynnJ3P2T/Y5f69HcKDKd6s8W6F9RVYS1vBICso9zT/93/1PV5czPnlp8d8/P5f8vmTn3I9P+bg6D73Hr6BygYIqQmhINeCnZ0Bq8WCtokKyrYtbVNxfvGCqlqxXF0h69ip6vXXvkZRDkAqlNJIpRkOOmK6ISDxXiJVXGIhQJZJlIpd5YSQW+IDyjKnW8AbhRC9KG4ohcgJpHSGVtGnF0SB5JzH2hg81zrrlYbSkZHWWodUmkxL8IoJngePX+fbv/9ddnbG/Olf/Gf2dwq+9sYhuxNNmYFyC0K7wtcLmuUcERyFzPHGYRvLuq5ib2BC7D2caQpVksmMAQNoM3I3oHpRUc8bnn94wvnnV1yfLmmuLYoCmTeETOGk5Nl8wbWxnJiWk7bh0juuoE/f3NQnuB7N8GnRdHW/kdcpxQy8RxFS3CAaJmMEIxF/doGxUjwoCu4MSvbznEMhGIbAxBqGzpF7T9Y2MdbmPbmQKJHA15Coul3ilErer1IqemYiWuUOsN5DsOTCo5VniGYiNINMstaaHS25aDXXRvN5AwvneOEdS6AKUNmudWbkg3JET8GJV0uDjezcxFM6eYDYtO0Um5ci82wC7zt6GKG2hWrM4BMpsL3FKBavIzql9GrVsAGstyGnzqi4cZe3YK9bT7h16hdLwm3P57cePnrV8XeNL2zEbE/7cOsKcXxjcAypCELjhcalTl1ehqQ0PELGHGu8o+tvk/sEA0mQ3pOLmCGhpULkOd5BgaJ2ltxH19onVz74WDvgeNWSEBjn8T5QycD51RqAz5+9QEjPZKJQ1EgMuFgXoBtJLgIqK9iblVhTMywDV8tLqmrO6fEeYGOHuNEOWV4iZAz7BSTVekHbtlFpGoNpG+p6RdvWidsoPmtRloxGY/KyRAidBHUe004jqAIhtscE6BrMCxm2mrlsskdisFtsrN1bh+zqFEgbr0tRTIN2O07XUaF04+hDIDgPKl5LiBifGI4n3L3/EO9qPvnobxAYruZjynwUK8Z9VCDex/ERgJaxIX2E3iLNhHcJxBCRnC4kXm7hJBhJs2hZX665Pr2mul5jK4PyGikk1oGTsffyojVcG8O1bVl5TxUCLRtcvcPCO9Hi06rpxqFzGYQIPXSkk2fQZReNgamQTJXiUAomWnEnzzjKMna1ZuYdhQ8MnaNwjsw7dPDpWl2m3vYGut2PIE5wJPTrbiugfCDr6NPTmRLwWpMLSdAqKi8JjbfkIhJLxiSQm0wCnWDdNJndIn0I24b2q+TGy6Z2LzoDKXNrS+LeutY259r2FTslvXXmS9cPvUeyfUdi69RXJY7e2hRbXxRunfUrj98wrvBbpBR+/XEz9fTXDVHHux4Xm0VihSJkJT4vsUVJrXKCylgB1jsKERn0tJJkQqGlRAsgxLhDFqAyEVbJg2CsNHt5yWxUMHeekdJctg0v6poXWFYE5olEzrHhoLe37rNr23lxZbi6vuBP/uNf8/jhHlX9Dod7BdOJQocaLQJttWYwKNGZpmot3jgeHpUIauarFb/82V9ycfop1xfPee3NdxlP90BGZtJ11XJ5dUXTtjTGkmeaIssYDAZoPUQQGAxHDIcjysGQrCgpB+N450HG/HoPVe0oypxM5ynFNcI4UqVWmLib9Me3FmsXC+gEv1KKTGbxvaRGfHDgXe8NyBSIzjK9iUGkZg6mjTTZPjhiWXmgUCCEYjiZ8e0//CNef+N1/uav/xRPy2ItuKumlKMR+5MjQrPCri6o5mfIYDk8OogtO6VgYhzGWuaLJUIqlMqYDmfooBGVxLQeN685f3LJ6nzJ4nSJaCQTPaTY3cF6xaKGpQ0sveF5XXNpWp7blosUS7BSpG59ISkjhYrhVlywvRcVV0sMxGbBokJXjSwZCsEUQRECM+Aw0+znBa8NB0yV4kiJCCV5x6CLHyQvQYdAphTS+xjhda5XBFKIqNDlljXewzwbpS9SwZpKhpRUHi0smRRkRYlVmqnO2cszVnnGRCuurWVWVZyZlitrOQvRW6oI1ElZpr5UMb7Atvh8lYW8bQZGf6uDjaOX0ANSN2zs28jNy6L+lmJ4xTfHQ77ybr5YVm2uKG5fPcFWnSL8zfmSfv3xW6wUtiakN5Nuvh+tlI0ZuaHB6Io+omsbIWCFlwojJUvvuTSG46qCukZkipHWDCKwSeYjx732HhXoXWktJUXwaBfQqfmLtR4nJYVS2HLASElyIaCtKH0U/4q4MCM8cNMwEYlJ0rgNgd2zkwXWBkaDj3n98T53jyY8OBqiM0GRB7JMonXMksq0QGkQYkrVjJivLF4Yrk6fsF4sKAYT7j74GsgMjyL4yAmklaTIcwbDITuzXZTSmB1Lnhex2U1eIqTG98E5gUhpGlmmUcnyF1KB9zes+x6/7SpteyiCWBPRYa7JIhKdJUwHq0U4qaMciNlIAYLHmEgfcn09Z7lasV6vuby6xlobCfS8AQI7kxHj0YDD/RmzcUE5nPFH3/unLK5fsF6ecr2wECpKPSILOTKbgF4RfEtQOUGl9SVigZQzLsFUGkGBCBpqy+p8zennZ1w8vaBZNrHAwCtCUJggMAgaqbiuDZdNjCFcO88qQCNiDMF0UEkiq4u1LpoQXOxOIFJNc4gKoSOy67KKxnjGSHalZCQVR5nmKMvZzzLua81YCHaCp3SOwntya9HBk6X1vem2thG43dhHb2Tb207/Jvilt2eT0O0tex9hGUXcRw6LhpgBJ2Jb3LEQ5EIwahUzY8iNYeU9V36TTOpFJOyDmJEVAiBTK1spUmr0tsgOaQzjvpViu3/4NundlkW/lVMaoaVuHb+c/NA5p/1VOsMzQFREYmsfROOlYwvY5vHrNkDnE8mtz5Be9X1x3jYM1e2bDhfb8mp+Q13xO6EUeldqC0O40UchvXdb83cQTlQKEq8UrRQsveeibTlerxF1TaaHGBn75SIh85bCgTIW5X0kCxOCQkjyJCiyZCV550FIBkoiy5Khit6FCYbcRshAJuHntwVfXHuxBwCC1vrYEEgETl6sWa9bRGhicM9L7h/uobWmLAJZ7lDKU0iJdZ7MBCajGc4LLq4rLq4qnp0+4+LqY1AFBMVgNKMczRIeHK3uclAwGo/Y3dsnz+N5UkWBH1JNQacUOkBDConOsh4OklJ1WyEphgQadLzeaa5uOvTdZtxEHWQ3Z34TcO4arMSmOh5nDU3TsFqt+PzpMaenp5yfn/P02TGtMTjnca6B4Ll795A7hwd8/WtvkukjpuMR3/3j/5anTz7iRz/8c+aLGE+ZDYcMc80wH+FliUDgpE5B8UQT7QPWOGSIGUjCZ+AUvjIszlacfnbO/PgS3wa0yyFElN8HQesFDZKr1nBWVVxZyyJ41iJSTbdiO9uo2+ARmpECpN8qoIpqHU1XlRyhogkwwbOvFFOteDQYcKQ1+1nGkVQMQmDsQlzP1pCF2Eck5oh1IdDQQ0SRHiaVkCXdLqDP6HFpfnyawy0zoJ9jGUCFGA/Rqce08h4lFYVUaJ0xVYphphlKwVRFmO7aQvAO2+1rolD3xOJQF0gV+PHOffK7eySRjXzselhtKpO3Ac2btnkfCO6fv6v878VMx8LRNynqV3iqgO69Wtj0hQ6ASIaQ6GDWjUHUX5tOecW/OnUROpehN4K77xObB+0e+gs4A28fv8VKYfu47bj96mP7zK6U3imBVYJaSa6D58S0fLi4op3Peb7QjAgMROBOnjHJM+6MSsZZTolAN23cUE1DESRZEIyLARDzPaSAMniCd+QyMCwLykxwZQ1ZteLSWnLryATUAZaByJCpZCLYizT+fUGPgMXS8unnC6Q4ZTk37M1mvPZonzdee4h3cwg1WQ51XdFUC5SKlbWPjqYc7U55eOeQn390zPnliu//X/87b3/j2/yD7/03FONJ7INcjinLEeVwhBJ5FGB1iCmnxSBZVQJEx64vIv4Oqfo4LlIpZcrpl73R4nuKjI1H4LyPcQmlUuoqSCn6TCNnTZo31W/czsoSQnJ+ccnpyXP++q++z8XFJWfnF4nmYkRWDCiGY8qioG4qTNtwebVkuVxzevqCw/0d9nYm/PEffotHb32L2e4BP/nhX3B28pS/PPuIyVCyP8sZZJ4y05xeGTLp0TiwFm88wua4VlCvWtT1nGbR8ssf/JL56TXL8zWh1ggXk0GDyAhScV23rGzgtHIcr2rOm5azYFkTCeMqITDECt9OUFnvkd72sZqYWh13gI6tHijYZBUdStiRkplS3CsLplpzP8/YAabOMmtbihAYOYeyNhZvhk6ehF5hR4gl9N8p6NJQN1tQhBhPidl7G6G9jZKr9GoI4G3MiFLpc5kU5DiMkOQeWikZaMUwU+yrgpGSXFrPsDGMXPSoTr2lSrfRNfRprEsGiIzkgoTUXjXt/2RcieBjH5VA/LsTzimYfFumdMqN/qytOBebTCiEwHkbqW2CSPWWnVeVqiRSL/KuFife18bIieyxvld+EW6NvVZI3qKWEmMszrm+XzfbBtaWZ/GbegnwpVQKrxLuN3X2S++KV7/+hVdOl+tcs84y9wJMstDWwXFpDFXbYJxhQGBAzFiaBY/IM1od6bUHUkX+fOniRYQkpCIqfKSS1gJyUsGVEjQyZjXNraZreO58DA62IaXwbW26rplPSB6FdbCqPJeXFblUHD+/YjwsadqQipV04nnqmro7JIIyl+SZosg1R3sTgg989uyUenVFU10zmo4oconOJVqnRSzorUIpYn2BtZEmW4iNh9Z9381Mig4i2pqfPtJ8w0S7ac6FEN307ire9xtIyPj5bQ6kk+fPOXn+nKqO2e2TyZSdvV0mkylIjdaawWBI08RK7MX8kuBjdzUfoGkdjQ0U2ZC9w/vsHz3CusDZ8Zr5uqFprpmNYDxQ7M6mSBx4SzCeYAMyFGAF3gjmiznryzUvnp5jlgZXB4RPvFJCY4XCCcnCtSyMS7CRYeEca2JNS5vSnbs8/G5cogW+BVsEeu6ijHCjKnksYE9JdrVmL9McFjljqdiRkrF3DJyPxoiPnq1yUUjKrmOZSPMgRI+7d5Tr3RxtzqOv/O32o+x32O0jXb+zkn1MPohF/vGLvHRRyci4pbQUtHmGVoFGKJxpkdaxrKMn0JFRQiTXI63N/hu3RUh6jtg/4gbl3mact9dmL2i31qbYvPISg1IIff2TIkTFIELfnEgHuqakMSkhfZMLaRyCwIVwI17QJfv64BOlfvTCpYzte/v6h7Ch9XlJkt7OxviC40uoFODlx9nWx190vAwn/abf1GU0tBJqFekrLrEcu5aFbTmzm8yN09YwrhueGcdBUTLLc+6VAwZFxljlGGspfCCTEuGi4PA+NvMohSNTkqFSlFqyR0YuhryoGyYCssYyT1xMqxBw1kGyMnQiwOvI6pyHdQ2fP1twebaiyCTz6yWHB1MO9zPGY4VqI7yUZTl4g8CSSYPWmtmwpPz6Y+7fWfLs+ClmfcZHP/trBkNNpvdpQ0u10rig2d+/R5aVZDpDyQDBUlc1AUFWllF+p/ijlIosj0JbSJEyllIKauhI9kgB5Pg8vZzxyYX2IaaYhoj7KhEt5Ejk58jyjCzPWa/XnJ6e8id/8ifMr6+pqzXf+973ODo64vHj1yPGryRN4xBSUpQlEO+hblaYpqJaLVgt57Rtw8n5nJ3phAf37vMP/9t/RbW65j/+//6/fPLLn/Lee3/F/izj6GDKu9/4NhoPpma9OoOmZSwzvLG4RcsHf/1zrk6vOP3knEE2ZJANImQkJF7lVEKwDoGnTctl1fJsWXHhYQFcE+MILWAFfZFWB2C4BMaRYioxqBzI8AyIMYQJcCRgpgRvlDlHZcFhWXJYlJQhFaIZh25aSht5iwoUyvtU05CESiewOthlSzGIsCVhb8Ac6QNC9vGDG5DgFoYhk3J3zscgeohUIUJA8A1KCpSX5Fox0ZLxcMBSSKZeMq0azpoG2zZce99Lh6bb0yHRrHe3k4R8IPKSSRcXbPDpp7Om5UZQ9xQ4W7IlSqJYpPcSOhPdV0hKuvvJU4B905MiGpKZkCgpe0LDyraY4KmDwwpwqSeWCSnemFADlQwvlShfOsXUjbVMmXcibIobtxXZrzu+pErhb3v8HRSCoMfkAuCSZWYFGCKpXUWkFei43jMRtfnSOuqq4ro1jJVmPbSRQTLL2ckLvJAsA4g2EFqHDA4hQuy+JkB5hwsOgeBAKbKypMxygm4YWYerY054zI5I1qKSGOtis59khWghsCHSI3x+fA0ERiP4zrdf5+H9XTK1Jrga1y5Q0qBEoFqvkTJDyhIncmzree3BPtfLmk9/+RNqs2Y03WPv6CFZOSIvxlxfXSBlEVlNR1OGwylZOUSpPOXERwUAaUP3fYRD9JpCl1G0HWQTBL/ZfDJ9PvhYIRySade3FpWxsbrOMgKBtm15//33ubi4YDgcsruzw6AsuHfvHpPJBCEEdV1jrGFVtbStYbVe0zQNbdtSN2sij5MjUwqtJMNBzro2XP//2/uzJ8uy67wT/O3hDHf0KcJjzDmRiYkQUBRBI6rU7FKXZJSq2vpJpoe2+tvaqh/a2vQqtbWpuk1SUV3USBIgQALICTnEHD5ev8MZ9tAPe+9zjntEZEaCFAVk3pXm6R73numeu88av/WtZcUoA5GNeedb32d//4DDw0Me3vuAulnxn3/yITf2d7lzbZ+ivI6zFUefPmLx8JjFw2PO753RrFoKOSFXY7QqETLDCkEFnLchMnhat5y3hnPXN6fVDCaTkRRyVKTxyfedQQhw0wJHjmcG7AjBrhDc1JJdrbhbhN6Dfa3ZBTIchTGhEc07iq4oHe+1TzWKoE1cTFSndMoliiH614fPYUg3ORyyT8n4Tp32e/sQGQjXczQpAq2E8HGglWkR3iK9xGUKZIaJlBka2MymnDQNom4QzrHs7p+LXEqqu8YYuHdXnBohQ/TlI7+S73L8XTKp+7CehFYMkXMfRUtS4Tp8usxH+g/oqESmIowtneqMWZ5TKEWmM1rnaKzjbLNiYwzntqXxwTEAIsKxb1rEhhG3FhHGkg4NeXepMUJPr4nhu58vv4VG4dlQ7+UkeQqDI8Uwd0jRa0kzZUMYvyEoZQOxIxky51jXDQsaxkJineegLJE6Q2UZQmkyYxHW4KUPtAD4wJYpkhcc8uF7eUGhM0ZCUaHJm4ZlY/HeYL0NTJG+TyOkTlYI3rb1UBnPk6MlTVvhxQU7u5PAHlo0YGtMs6bQFiUs3raEUZ+arJgiZMatG3M29ZKnjz/m5PyEcjzntW8sme0cMJsf0LinQEZezNmZHzDf2efajbsoHWCRCbOvuuRoCMtTkJy88zDbQXShvBt4YiJW15z3Hb4d0nFSbkKQaU3dNlRVxccff8xisWA+n3Pj8JDD69cYj8dorWnbltVqyXqzYbluWC5XPHj4kOXygs1mQ1WvUdEQHOztMp1MQv1DtyxWG/wop9AZd1/7BgcH17l56xZ/0hgeP/yUn3/wAPOq5GDnBnOZA5qjJ2uefPyUJx9+RraRaK8p1JhMjlCqBJ2FgTLWcGFqjuuWk7blwoTmrMRplGgs2pR2SznslMqJkjrxNQF2WkJnFA6k5JrO2M80N/OCXa3ZVYoxsZnNBoBEgqxmRMUTLA4peTJM71196vpM3yU1HzdI155SgMNE7SBy8L7rvBP0zoCPxxXOR+fJIb3AG43QAq9LGqXQQlAzJleS2pjABxWhqpAYVpMx6vmKPEm/+8FPiiN8v8fAMenTYPHqRX8fAr9UpB4XoYBeimAYUjovB/alZKIzdoqSvdGIMtOUOqO2jk1rKI1hCWBbNoT6YkBXxdR2vAIXKXHCvBZ/ySjAYAaF76/15XMnv3VG4dcxCOLK735hpH4AIQVWxu5IfKwviA77nB5WCVQijOxcecEFjsx7Ttcr5k3Nw7rmznTKfllwW5dMi4Kd8QjaGpyhNgZpW4Q1Ac4qBKXzIc+rM3wh2JMZwsCRaThuW56Yho33LJsW5/0gvxi8oUQaeuHArAz23oqdn33C+brhH/2D36fILLY+IZcVmTCUpSfPFKMyp6oNjbHkq5bRuzd47dUDPvjkAavaUC8fMCk9mSyY71wHNMvlOY8eHvPxrzxvf/N7zHcO2L92i7woybLgawoBWmUIwuJ1sYCsdRbguc6RZdF7u6JNAm1AyJuGvlWBaVuauuJscc6mqrlYLmkaQ920rNYVdWN4+PAhjx4+ROCxtkVJRVmOYwpLce3aDYx1NE1NXYefzWYTSOKMYTIaoaTk4aMHzKZTljdvYJsK4RzTUc5sOuZg/xZ/77//v7BZnvPez/6UerHgP/2nT5FnC9xyzfmv7uPPaqhmTMopCoVvJUZkWK+pWlhbw/31ms9WS55sNjyoDJX3HWFiS9+k5nxSleJybpw+V53hyXERXSS4oxTX85ybec6rec6uUtzVmtJZ8nWNatrQQOYtmYdMKgpkx1t0uXYXvqCuIe3K4zb0vj2X4ZJJWfbZ8jT5b3j0VMwVaNlHkBaPjflIKaBQMtQVpEA2LdqC8iF1OSbQvu8pRe5Br9YctS0y3tNApue7SD+dPGQqBSjd/XiZ4OnpCeudnEuon45DI1J8QDeLoiSm8nyo6YwIhnpPaSZKcassmWU5u0XJTpaRS0WmNa2CWmcc4Vk2BfcFnJmWU2M49sExLUQPUa6iQ2Wt6dJGMkaTfY81vdUafPaXkd8yo/Bl5cWGo1NKxGUc8ZIhnzj4W0R4aAzfQmQhYq5OhhDXO6wxKBqk3rBxFll4dvMCVYwYo3FOxCKeRYvQ8SwJXoXwoRg9RWCkZC/L4jQtz8YHWo3W+S6a6RBT8TlOTW+tg03jePR0QZ5nHJ2u2ZkoCp0hlQ8EZKUn15I81xhncN6TKctkpCjKnLOLKfmqZt1WtPWSar1gMtuNmO8qenaei4szEJLxNAz8ybXuRzvGnGYft/adypcTfTE/LhIKI9zL9XpN2za0dUMbu6rPLy7CkKPzRewWFmRZxmg8wraKtqlpm4ZqUyFE8KCU0midUdd1iECAyWTMaFSyY2chzeVsGFjkHEoptNbkeUHVtjgXp6jJnKyYMRlNmE73WF2sOL5/j6eLlvPFMc3pmvWioWgkpRzjRaCK80pihcI6wXnbcmEajjcVZzFttHZ9t7IRgWq7x/YP71Sffkk9NqG43Hcqj4RgpjQ7WrOX5ezqjB0pGCPIrEcbi2gNIubfQ8pDXNIbEPPvg4fjeU9QMv6+MyRX3DUvruznUzaq/zzCh87h9OjFdeN9qL9BoMxQ8ROruIak83hjKOOUwEYpWhGemdMso43p3RQxpLTQcyWOekUOLyJ9wv73cD7L1ddTpJBSRaXvOaUmCHZj1DbTmhtZwVRr5kIy8T40BlqLQdACQmnGuceanFwEw2+tI4t3Tnk6+K2J5+7naXSJo/7/V7+8lzQMX3Gj8HwJaz7esZCwBqFAhGKglxIvVYwFZZ+LdBFiSlgIRgQvp7EtG+9YthUnZxUTITgux9yczWhHOQdaM0ZhgVxA4R2ZCJ2iyvnQZWth5kJhyZUFYy2ZtIqAzTbYpu2nY0lJ42HlwpAeH9e2E9A4eP9XRzx8vOD27Ru8cnuPb7x+jXy3pMxBZwYhLMY0eNcgaFGiQcmMQmnefu0WF6uGv3zvU1bnR1RVFQbhFBPaesVkMmfvYM7T48dcLJcU5RStFOPRCC0U3kucsYFUTgm0CEva2jjBrRupGB7+xIHknOkKzPfvf8bJyQkPHjzA2WCK29ZiWsNiuWI2mzHf2WH/4IAs0xSZZrVcsl5dcHpygrU2TJLLc7TOAkUHgixTvHrrFfb29tnb26Wu1jx5/IDj4yOqas3d23fY39/nzp07nJ+c0tQ1RZaH6XHj3UCLLQX7h69y75e/IHNj/uKDp5ydn1ItHHu6ZDYuaVpHi0BlBRtnWVvLp2cLzuqK+6sFJ85yQZ//tlJiZHA0XEScyYG/HRzuoSfueyVE4DLakZIbZcGtvOB2UXJDyoBAMhbVOmRrsXUbC6H9uveCDrrY6YyrjHKXLXn/chrElEKAVCsabjfMZfc5J8CHKLfzHkLXu4vU214ASiCljiy0kgyJcR7Z1CBCoda6UNPyeUnjoFCazXqFiszDLYGILzlO3bUH2twwACJ2pwshI2lJiJy6+kmKcETqtI+ovDjTJ5ELloRJdWPgBoIdFeqMN0dhQNGNIqfAUzhH1rQoH6YTIhVeaWZaUuucXT3nuK45qivKzYaFtTy1Yb2sfIqAwlyX8PlChDPMIgy/uheR+71IfmuMwqVZwYN/P1+SJxP/lRzYZ7ZLwLDUoiODUvOhKSuxUCbOJBE9FhHPbxkUqQbHr72Hpma19Cyd4c5oxE6muZlnzDLNXI9xTROI1FqHkCF/WsZcugWkVuRS4HFMTYuxljPnWXgfn+uYO40ejvOC1npcFSgcvDf82U/e5/T0OpkSmKZgd6axM0uReUZ5IJBzLozXRAZYW67GjIuC3fmc5cayvlhx+uSY6dxx8/oNlpuWxdkZ1ijISvAGaxqaqsILh0AjZQE+3Mu+4CU6yGFiepKS7m8hfLDLMhKp4Tg9O8G0Bmcdb7zxFtPZjHI0CR3VRUFR5MHwSIGzBmsMm/USYwymaQPEz4MXoRlqNBkzm84pyxFZrrBmxHRccuf2Law1TMZj8jynLAsypbEmRBFFnpMVJcioBI1lvnONt979HS7unfC0mHN/FZTuWWsZ6Qw8rJuKRVWxqGseblZctA1HzsaisgwIEyFwUnZT00T0qgV9OUVGZTpMy6QooSAQ2s21ZjfL2NGamZSUNnQkS2PQzqO9wAkdOrBNr0ZchPsoJcN3I+GSaum8eEF3Fektlyi642yHS5mngecqQr9JmJ7mO7vgffR1XXzBhX6BTAqciPUFD8KErjShgnLPPBQqOBRTGRsktWKhNQ7P40phvGEZ71E/iyFlAEI6ygjfpasS5DOBO4YF9XTPU6SQiPOSYZ4QUkW7SK4rzY7U3M4ydrXmRl5woDMmSrJLAJko2yKtIfRoSLyTOBMMVB7npmc6YyQkAsXCWMq25cw5FpGUsAZWQsQhWK6ro6SEXTD2XI7QXtI4/NYYhSS9Mfj8TzhEYHX7iKuGQXT/pbF8cVkEoxANg+oeyMSXFBaQ831hKj1GIdcPzho2G8u6qTB2xn5RkmVTvNaUOg8PUivwTR0eWhmIwBL7Y4CcCVpyMgkXtcIaS2s9TUwxZOm8QobOWg/WhNXqvePDXz3EW8utwz3KbA4+J1PgClAifFLnPc62gV7CS1QOhdbsTKa0zYpFs2JxdoYUOa++OmezOWGzWuLUBE8siJuWtmkgDtsRQmCtB2dp22YQ2MYHSzq0luR5+ARpZGpo8BEorRBSsNmsaeoWayyz+Zybt25xeHgTIRU+QlqT16ZkuF+mrTFty2a1pm5bWmMRUlMUBTu7u4HRVcowJc7nzCZj4mgL8jzHWUvbtuRZQRr7mXiVvA+q1BsYj3cY3y148uqnoQb0yQOas3PqzQXkBc57Tpqak82a082Gp3XF2hkWOGokDQKDCMq0w6oPKT6SpzpIs9A78WmOQSFgrCQTrZhpzUSqkDKKqQlhQqe1inTwIeoVses2NBmGyLivEnTKO6VJojcvfN87nVJE3f8v5SsG33i3g+h6EHpxPRw5arB+lkYwlAFtE3sOvIsp15C3F8pjImOAETDXihqYKMnaiU5pm+7KYqQqwzNjfTII8TkeZJGu/qQ0l4zfgaSPEMaEVNEOkusqZ19n3ClG7GbBKOyIEEWMXYtwDqwJEHHvQrUlOqLCa6xUqCxHK00uFdZLJtrhRU1mTEg3ecPap9ncoYO8i7iSzhsYhaT7vrJG4cvLFyTSuiIbQODzDyRfMub9Vfgte8ic9x5ne2PgordkCDw1muCJ1B7W1rFZXDBVKy7aijuzGXZvl+uzOYW1bJojtLVkrWGsRxRSInyCGnrIJGOZY+2EbL1B2xoX0wfBAAmME6xdwGRLpSPTK5wuaj767BTrfkJdvcnrr1xjZ34N0bSYdkmRh3kJm1WFUhl5LjB2jZAFr926waRckusFn9z7hJOnR+wfHLJYVDRVTT4ZI72nqWrM2OAcjMox3kvqquH+w894+vSYX/78l5wvFhyfnCAkZHnGu+++w91X7vDt73yrI+9zBH4XJT3Xrl0jz3IePXxMtalp25Zbt25y/fohk8m4S3uYJvAYaa06KKCUkjwvwtzpmHcOEaDHWst6vaSqa5YXS5QUFEVOWeRkme4ou7XO0FlYFk2MOExrungyywukzpHFmFfe/TZ5OeH99z/itKo5OjphxBpjDU/Oz1i2Dau25ci2NN6xQdAQupRtHAIQ9J7v0DFAP/kOEeYIxEENMlJZ5IT54TMp2c1y9vKcvSxnLiRjPJkxKGNR1vakb5EzSGZZ6ORNroxIvD/PJiD6DHUwCM9nSrhcQxA8+4+eGO856QyZdFavuZJfrpAdnYS1AdodhiUZcIJRpPtwVrKvNUJrbrZjbFVxYkxAD8brDqWD6NTZwFdlmhBVeheIRIYX/zzjoEXIKhcOxj5ECLdkxlxqbqmcO3nJvs54dTRmJgV7QqLrCmValNkgvUV6g/SxV1mAECo8swichBbDWEpmUjIpR2yE5HA652nTcNQ2jJYrzk2LMA2pi8UBRoZUWEJd2UHCTGnVUWt8kfwWG4Uvrpr4FPJeiRhE9EY6157gWfc/nsQC2RVNo3S3OYa26RCJm8TH3HATG0fwcOEcBs+oqgOTp9a4omAqJJOiAGMQxtB6i4zMn1pAqQQzqZBKsrQ5G2tonGUVO0+N7z+XSDhwF+CfVoRmsnVlOTlfc3K2ZnenorWaslCUpULLGm8btMrC/GAhUVojdUZWllgL1kvOLjbUxvPh+++TjXYoyxlIHXPKAuvCrIKz8wXrTc3DB0c8eXLE2fkC07ZoJZlOxhgbGD3v37/PcnnB2dkZN27dYGdnh7uv3EXowHCa6ZzRaMy1g0PqOhiFyWRKUeSkwrSUwctO36fovueU75BsqoqmaSMcNrCtVnVFXTcsLy5wziKE4NbNQ8qy6NONMqqAOIdDRMXZK4eICBKScmfOaG8POZ1S64wzZ7moNxhjOTEtG2PYOMfGD+crJ45OejhkV2C+kqqA2DvQp42SB6zjT6EC/l0L0LjYNBUMSIp98X3PR6JaGOrmIdV4QgqlTuZ0VSnUvtrMlf66dLzBeyJ+OTHRFAyDd4PPK/rhNT69wuWjeQY0G3EkJ6FRSzqHdI5MenIhKKWkEII83p/USZx+eiMZ0kBXey9SRsEPXg+uRYw+vKcEJiLMsj7IMnal5prKONCKPSWZe8/YQYlFOYtwFmFMNOqBx0zgU346WErh8F4gMIHUT0hcJkM6TUqskninWGQaCaycjdFOSB95HwrQiWaeFOGRIruXCxV+i40CfLFhiH7OYLPUHt4VxVxYFc5brDMY0+JsizMmFj9t+MJkeJRsut1SRgMSbrsUAhELVl4ECm2Fx8iAClpaz2ZVcbSpeXR2zpuzOddHI75z/TqibRD1htVmhbSB+VLnGXmWUxQZUy8QWqOUoNAKu65ZWAfWIXygMQ5hssc4S2tcaqxkUzlOzxvuP7kgL0q+12bslVNu3J7Sbo4w9RK7acKCV4rpdIrOS2QxYjIdc+3wAF2O+PTeU/7F//tf8Lu//4f87g//HmcVCKHxKFrjWVctn9y7z2ef3eff/vH/jjGh2Pt/+u//Pnu7u8znc87Ozjk9PePf/PEf8+jxYz679xm/9/s/5N133+V//p//r+hxhvMSrQrGo4y333o3jAm1Lbu7uxRFgbWhkUmi0CoiUhhAIoWMdRLD/UiK1zQNRVFw/fp10pjOo6MjVqsV5+fn7Mx/xOHhja7BbhiDK6UCeFL0jUkdV7/zjK9fY9K2sL/HclTwwLZsViuMsbTWURtDYy0b+hkCrqOYSxxO0dnovOqgPntF5ju0Ud8VC4X35N4x1opJpsgJ/TBhsE7oSxER5ovvDYSIVzF8TkRnEAaKw8teUXda/nmu/lWD4HqsPKC6vhMI5BehloUYkLgRCrxCDK7BE667S5nF2oQL9WEPtM4irUDaYBQKAWMEExGmIV7gqYnRu/eBSsYTobkBXp4JiUKEXggZ6yqeBDcM544po8JHokEf+g52teLN6YQ9oThEckNq5kh2TUPuoUSg2jYwG9hgFLRw6KSCPHGErAjhi/QoYwJ7rJAo52iVIsvykD1QCluWzLTBCY9qBMK21IQmNmPBKxVSamn6koCuaPUS8ltuFL5YnleYTgs40eomAJKUQQkopdBKoSIaAQKhlkd0zJzJIHSBsfcYa/vAInl+Iiw0E3NN1gU6bblacWFaJqOcHSXZzSRTUXQehVACgYUWNILd2MXpbcZ5VaOcp41ZBU/fBVsD1npaF0JdY2C1go8/OWW9anjt7jXa5gb7uyO0z0COyIsJ3rRY29K2YcCOaw1kBVIXTEeS3XnO9YMdms2SX330PuXObcbTHO88jx4+ZrW+x8efPqI1ju/+zve4eeMm+/v73Do8DPOki4Lr165T1zUHBwc8fvqUjz7+mCdPn/CrX/2Kn/3sr7hx4wY3b9xiVJYUecZ8Nsf5MAdBax2UfUQjDRlS0/frvadpWjabDU+fHnFycsJyGQrPi8WCzz77jIODA6bTaQdDPTk54aOPfsWmqjjYP6AockbliARRVplCiWR0YjnSxrBfClRZoiZjxLik0Yqlc5w1daTqjnUnkRI/dE1SLipBR083TZcWTiFLjEtE6NkINNO2ixRyIShkiBIKpdBSBP4i55DOht8+0h7ENRn/iM+B79avd4NzdpvFGDgZgQEEVQwhnMnwxIdLdNdO7E+73O8gEHFudzKLfVwU7o9DpjB7UMfogpUIuRPElJgIBHNKObQM1Ns5AemnfbhXvYF1KEQEFoZBWFqpSE0d739MM2nCDHfhghmXPkRppQisrdfLksOi4NZoxJ6U3PCCXQtj5xm3scBvHZgmPNcuRAhKCnTUN6HuIuLYUoOLGFMpA+EdhjCbQwUroqXElgUTn+OKHH9xgV2Hcb8yrScbOdYiF5mQAvFCXO6z8pU3Ci8SQVxc0fULdYRQS1DxR3aeTLi5Q1y2S+RvURKMLaUl0zupt8HGsD14hp68abDe8mi9wo3DjIKRztHeQZOUXCRbE5JRljFTEpNp5jF1sha+m9vbxnMaYtdzTABbC20LxydrTNvy6b0n7MwKLpY3meYSLTKkzDDCRqXb4nEY34QHSApyDeNCsbszwbQbHj+6z53RQSjKNjVnpwuOji84OT5lPJnx9tvv8tabb3Ljxg1MXSNl6ESejCc4DwfXrnF8csrewTX+7f/vjzk6esqnn36KEJK93QNGRYnSirIsSVCQhIvvflzv6YqEbvEB113XDaenp1RV1RWx67rm3r17pIE/k8kErTXee05OTyH2jozH4+CJZjo4B1kWo8tIieIJ1AzEiD/TiDyDPMNISe09a2NpzJCyOXodPhaqY4KoIzljoGCH7lxUvH36gljXiNw6UUlkUpJFJaYAGQfahIll6RYO0UvDVM2Vcw6BHFFfD9M8/R6J7jluJK5ctww3SOA7gyMG7wshuwjmUt4mntB3hiQal5iCAt85Y4JE1Nd/1sQ3pEXM//tB2miQVBGE+lOqIQ6jkw6PKETcr4/ckkEeSclOUbA/GrObZ+wIyY6HiTeU3pP7aJQj/xnWIrzruLykjFTYMkQ+0HcqE4HvColwYfQpzuKkAgW10ighWGcZZ5uKhRCUPhSda0LqGp/ICiNQIeqml5GvvFFISgF45rf3NjyoVlKUBePxiKIIWHTvbdctnBqbpFQxaxAWV6LEDQ+86z1I+mck1AfDWEqbKazwtMJy1FouGkv79Jg3DncQuzm7u7uhGHRxQXW+pF0sKVWOQiFNxYHOmI8ybG04qRv0ehMGqMfrqeh9rtSBHZ1NNg24heUvf/EpzhrGZcFbr+4yGwmqxQpBgxYGoTZIGQjoXL3CCs2mEUhh+cYbN/jw06e8/8tPufvGO5h2yY///D/jfIGUJf/HP/xDDq4dcufuq1RVzeJ8yS/+6qcIATvzOaPxhKIomUwm7O7u8HuHv8utWzd4/OQx/9sf/zFt23Lnzm3KsghcR5kiDdBJ09iUUp0RkINooUMvSUmWZUwmE+7evct8Psc5x2effcZnn4X+h7qu+f3f/31u3brFO++8w4MHDzg/P+c//ac/pShy5vMdXnv9Vfb299B5FiZy2XC+qJZCPhsReZRqWhPw9TZomzBcaKjsRRgJ2tjeMzbxdzIwacEk9tlIQI6LCikdr6OuFiHFkEtFKXWYoeBFoNB2gsyLMASKVGhVsT6RtEN//niRfZBwKVoZ/E7evQfrbYyIfYymUkkgYvpitNVxH8X6SegBuNQ1wKXhS3gGFxWer1gH9LjozInuJ9FSZ1KSC0UuZUi9CBEpsi9phNB4KhMEOgDNcQJhBdLJUGsQEmGD0Up9SQoopWKiNHtlwa3ZjFemE/bqlqm1FLYlt5bMWpRrwthSHELYADv3fa9ccg8sLtBV+J68zuHiZ5YoEaIY6VvwHuUCk7MSkkYoFkJSCckFodnNIGLfQlguIToN+cmX7Vf4yhuFJFcNwlXxkZIh5X/SHAClEtY+3NwOzyw8InoZ6eHyybMQxEKS6LwZCAUhKz1OeVSuyJVkOh+xd/sa11+7ycF8zsh57BPBBouzNa6KNQMBmQ/n2y1yEIKlNdRtiAZWJjxkDUSIWtd8jHNhMVrnOTuveHq05MHDE25em1HmJdYrlNCkVSsUKJkeT0emFWUu2ZmPuHYwp3GCoycPEXrBYqPZ27/N7t4eNw6vM9/ZRQjB0dERT58cUTdNgJ5KgbEW0dTkRY7KMibjMXt7uzRNQxPpJ5LyRxBTRe65hv1FfStKKfI8Zz6fM459B0AoZt+9G9FJeejuLgryPKdtW4qiQHhJVVU8fvyY3f0dirJg/+AA78G6NOUsQDuTx7qpKparFRfLwLNUN01ovkrmeZhGJGVnkgIMH1SELq5uu+7zDJZqckZSQXqo5zoAXVqKXnRpmkuuvu/TRenFzth0q7h7YtLld1v06R4GkUEqug+vdcAf1H1KLm2U0mjDy37myRS9cgsptnQvw/8uQy5Ft0937cN7lO5huD2XIOR+uMEw9+57M5UiNeEjxYinS90pVyFMizdNeBhdIMgReGQ0BkLS/Q41zPBpbPw+k0HoaDSSzfPhAfbWhGa5yJwaIsRQVJ9kGYVrqb1D+1hXItD2QJjF4q8Ec58nXxmj8HJNbb1X6aEvFuMDrULbBNgbcS5wlnUphjDj13c+VvBKg/LEh4K1lz30LYz5C0vKxTC5dQahQGcw3h+zPxvxxpu3eef11/ju229xN8/RVc3ZB4KLEqS2rO4/RbSOUhA9BcfhpGRUZBjpEJUga1uqdYMKmScCfkGw8S5A7+I1ee95elxRZmfsTB7w1ut3mc8KhBojREjz6EyhNQgZPqtxEpVpskxgnGY0mXP3FcH/+r/9BatacnDjHV579W2+8fab3L1zB6Eyzi/W/NXPf87773/At775LsVozGgywbahZrGpa/KyDEX06Yz1eoOxBmsDN6gMdTKaOBtBCEGe58jUPBZ/kgz/nWVZ992l97TW7O3t8cMf/pCqqrA21CiUUkwmE6bTKdZYHuw95Fe/+hW/eO+X7B3sURQFr7z2Ks47WmtweJQMKSXi0KSzxTlHx0c8fvKYk9NTlqslrTHRkNGjiuIDKmWP/ZFJFYqQ9+2i0G6HPnXiXCiSduSN9EbCOhciO9E7Al1Ikf7pu64EILGhXn52hPe9UUo/fnCPU5qoS+WIzmFPEQPpXCkNMmh6G8YCg1ikq8N1vQLp43eGIxpCn5rfAh9SNxdaJOqZAbll8r59bwwsQ36zYeNaQoCJLqMV70x3IQEe4IP370JtpxCCkZSItsY3Dbauuk8lU4QhBFKJgZsePoON98gOTzN0GJIV8hacx7UOhwVhkdoipUIpz0QrdscjJqahsQbtDZkI/SteikCmiU90Ti8lXxmj8CJ5noeZipXDvHQSrRWHN67z7rvf4N697/Po0SM+++wz6jrAG+um6WCr3hqsEx1ULimAVPRHeLQSHF6fM52UXD/cYWd3wrXrc165vcvebMxbN/e4MZtwcz6hrGpUbTmQB4x3BLN9xSO/pF6s2SwuwIbuR/yMQkgOyhyrBFmbsXKgjaNtAutmRchVt97ThCgfY8IaOzpp+PjTU97/4DGmcbz16oxM5SFUlQYpPVkRHhDtwDcWg8W2G6bjPea7O0xKidY5b79xl1fv3ODm4QFaeRrTsFwuOT4+5snRU/7u9L9hf3+f6zeuU603mNZQFAVaK+q65vT0hKPjpxjThglSxoSivnfoTHde2/MigmSsjTHddLcEFFBKdd9p0zRIKdnb2+tI+hLPUTIeAJvB9SUDZK0NBWWpY2NeSCeGq5GcnJ7x6PFTHj1+ytnigsqYLm2CCDOCne/TX877cK0iNZAFRel9BOt30YAj1RtEdPOsiA2KRGCBd9Q2EC3WStFqHajfpaCJSibVQsLN65ZlX1hNmiJpfxfdUWLEK4cet7gMYkl/D18QgAhF9dTsJrvnIRat405i0N3cXSBRf3aRkghd2KTmN0CJqNQdFtnBfI0PfTu1c1TOUQ+4payIPzLdwzAK1xJGgToZlGhiEhvGMOFVQWKmVfhQb/OBFl/jQyQvJcIZvOtp6YI5SaYwNg/isbGR0Pe3LMx/8L5DMiql+iY747FYrPCgNUIKpJaB1FCBEAHzZUhRGMFRTd+MeHGW5Kp8ZYzC50UIXXRwxcPsd6bz7LJMs7e3S3vnDt/85rvs7u6gtWK1WlFVFavVCmtt9wUO8a4JkCEI1AtaSbJM8MrNA3Z3p7zy6nX2r805vLXP3Vu77ExLbu2MmCjPWDjkRY3UMPJjFDVaNZw/HoFoWa/XuCYode1ypMoYZzlzkeGkYqdusRguTCDPs4T8YlIqCVnbeFiuDMcnax4+PGVcZLz12l5M27YgHEK4Lm0mACkMwhuwNUUmGM8K5tOS2uTMpyPGZU6hI2tMVKQm3iMAqULKBu+xmY0K3bFcLjk5PuL05ITxaExZlh1k1DkbJkwNyNWSEZCRCiAp+PTa8LvuZ+D6rv4wGo2672p4nLTdYnFOVdeUZYnWofPZWosSOtCDD/ZNj/nFxZLTszPOLxasqypAHmV/zcl7Tx5rWm+XFHL6q8OS9x6+875rqemORa8EjXO03tI6ixU6EOtJEeeDCHQYqhz0vOvTIMNF263jPizoIoZLU7wGc7WTQgt/D9JEIgJfBQgXP03KbYngjXdHSAXpEBJcMl6Xopx0btGnjHrlSogQhMSI4Bm3LgymSX0hKcfekVt299LF9I3v+J+Gd39oDNN0BZl8+RhSBGRSyAqoiJPto5tBaVuEUrXHdxGLB5IvkNgFUhe9kAqk7q7EedNFN+F9iVQy1ih8Z6y7QJH+6xSD/7+MfGWMwovkeV18ASNN6IyMT6t3Fq0kN27c4MbhIf7b3+EP/uAPOgNwcXHBcrnkwYMHbDYbVqsVTV13Hi7xK88yjdaK/d1dJuMROztT5pOMMpfMdwtUBjr3SCpwDWb5FFddsF6vkKzRumW6A1k2IpvD6/pNVk/PuKc/5OJpRXXWglgjRcE0z5F5ztgLGiGY1g1ObhBVg4jjMmVckEZGSCSW1dpwv7X8h//8Cx4/fsL3/843gtemcrwIIaqILGAygimlsEhlKHLPbKz50e9/n5Ozhs/u/wolM1arDd//4S66mLK3N+db33qX8WTMex98wNPjI1rbcnj9OpPZlM1qxePHT3n//Q/5i7/4CzZVxT/9p/+Uvf19dvd2Mc5ysV6R5zmZzsh1TlOH1F7btpGfqAwT7WJ6KEUHbdt2NYhhSgmCcurnRQej0rYtbdtyfn7Ov/yX/5LJZMq3v/1tDq9fZ74zp2kaMu8DBYaPjYHOdHQnv/rkY9774AOOjo9Zb9ZhfXX9K/2PkKLrlPfOY7pogy6FefXBdT51NtD9Tpz6dfypPKysY+UclZSUQoRIIU4dI87+zkSAYOJ9gCxGb907G2kb+vTPUBmGf3e9z30uXhD5iaKiVZGuI2onEY2Z8GEYVILGdgq3y0SJnmZicMdSRiWy5tEXmvuZJwaB0xqrM1xe0EjNBsHSC9a+H1o0nFPRiU/ptzCwJticFD31Xn663mAQ+sY/DzStYdM07MbIT2kFDTjThjy+SGwHodTvle7mo7Qi1ktk/MzegVRdJ7uK9tJ7cF5S6TwwwkpJlec0eY6Yz7DVhrrymCyM3xWxtjj8rhB9Ku1l5CttFJJieG7Y5FPucAg3DF5urjN0locZAdGDGo9G7OzMmU2nbKqKxWKBbVucs9GrFLHPIcBZy1yTaUWeZ8zGOUWuGE0UQjmEsmBXuHaD8acIkaF0gcxzhAJnKmQBEkW+P8YLy/6r17D+hNos4jPiABMbmiQzBUZLdrRiJUXXt+DxtIgupZXyrab1LFc1p2crPvn0ITeuj7hxkOF8g/MOY2w/hSv+VlLgbEtdr5mOMurKYds1m9U5F+fH1JslUmUU2Yjr167hPdy7fw/nHA8ePGBxfk6WZTRVxXK54uLigoODA5TWHBwcMJ5MggcUvpZgbF2gI6g3FcaYrihsjMHEVM3VNNDV7zsZgaGxCD0NTWfoHz9+zMnJKXXd8OjRI4QUnC8WLC6WjEcjJtMJs/k81iw0y4sLTk9O+ehXH/PJp5+yWFxQ101M3Yo+FcTQ708pxqhyBKS5235w7aJTrtFvTd434ERAq3QpJKCylo2xrK2jEIFGO4vpM2nDkHoZI8aEPPI+zK2IlEfITgvThby9ih7k5gWRUl7glQpeuhS0Ml6T6wnlNKEfIJcRBeU8SqQxlpGAzyd6jyGtZK+KQ3gjIpFimnHicULihMRKhZWSRogwm8J5NtZROWgJlA82Xf9gnG0itUtNaZLECtB/G2maIF501+kIlCStMWyammWlqHwYdtQIgRcKJ3s0Vvic4QxWKlrvqZ2ndi4QarqwrUr9EqQuax8KzCKYoVZJGqVopGKTadZScFJVPF6tebxZc2EMK+e6mRwpOnLx+0yIsZeRr7RRuCrPKIYY6ss49ctaS13XKCnJY8ESHxrXlJownU64fetWh4MXMf+3s7MToIuZBhw4R726oK4qNus10+mYPM/QuYjpmRbvw/B2YxSagizzSNEijMRUG7QAqQXZ4Qg9UeSZpPGWVbtEVSEx6toK6TSZU+woAVqwzjVVHTy4Kq6D1ofCmvepmBke4NXacHy64sc/eY9vf/MO1/dfx/qa1hl81aJVSIERce+ZFpi2Ynlxxig/YFxKXLtivTxFZyNWF6foLKecTbl75xb7+we0puX09JQPP/yQzXodPHlryfOCyWTGu+++y+HhIXu7+wglcd6jMwUi1ALatsW0hs0q7GuMIcuy4LnHFFBZlpRlifeeLPYVDNOEWvfL3FrbpZw2mw1HR0f86Z/+KR9++GHX7Na2LY+ePGY6nXJ44wY7O3OuXT/g7bffJt/ZIctyTs/O+elf/iU//slf8P5773F0cho+GwPtKkTyPAb1JtvR9/ukfB0E5U+EsgbMfYI+J43tfVCdhn5wTA0sjaUQLQtj0EpRSEmmApeOVCC86yCgMpI8Cu+72Qohp52oQlLRO0z1CzWRlMoK3DxpDoFXGqckVinWBKLG2gd1JHzA8msRZjpoB9o7stgTFLi7LM7bqLajJQldGwNDGou/ERziEBF2KbBCYbSilYoKwdI5LqxjYS0r56kQYdY1ce5ADGtC+ic0AyoIZIHed1FAlxDTgVfJWxe4zmJh2DjPxhnO1xsK59gtC5AyUJlLTYaKjk0wCE4EwpEGQeUcK29Yu3Aci6PIFCOlGWeBakYDrrU4ExpmvZT4IqPVmkZpzgUsrOXjxYJPF+c8Wq146h0bQnRU0aMQU7pNdFHPF8tX2ij0UNJnMe3pb+8d1oYuY2uDkrHGsnGbLjedZ+E2haKmxRqDbU3IHUuJsxbTeKRpkSpw5YRB9p6qbslzCyikzCMviQej8UZjTYZSIAuN1C1YgZAVwsg4uRtELsm841p9Cz0uefTeQ5pli20r8BrlFYWVTBFcKzRNm4f5tVWYQhUeiODDRtovWg+rysNZw1/85YcgDLu7JXduCMaFJRMNUjiUDJ6TiXOplRVo68PoUQE3rk9x0mHbCx7e+5C6qXl9ts+oyMnynO9+9zs0TcO62mBNi3cuKAWlKfIRk/E0ENgVo86j8RKcszR1qKWsLpa0g/RR27Y0TdNRWFhr2dvbY29vj7feeovpdMpsNuu+4zD9rY8QnHM8fvyYo6MjPvroI87Pz8mynB/96EddBHHn7l0m0wlVXbNarVheLDg4OOhGff785z/nn//zf85H0Zi0xnRKvPc0A/Nul6OPD2jq8JXRULsU4/uAaOs3THnnWBsSAidCuicZhDVw2oZZFI90hclzyAuQirHUZMUIYQyYFtM08bwSrQXKa7Tqr8sk3q9EzkZPimGjYjNSdNPhaoLD0TjHadNQO4dBkEtJmWl2ipJSapQXGGOQxpC1DSrSsgR0niTMKYhue8rxJyNKxO8LsCJEJkYqaqFohGQlgkE6MS2PW8txazmuG86tjeSDMqaNUteHQOFCHwM99Xdgo43cZzGass7gBWhn+9SaCPWAxsOibdHeMxeCjRBUPs5hlpJCpJ6W0Exm8CytZ20Mi6Zl0TQ0zmKxZJG7amcypswyZnmByCRSZ3gChbhRkpXzrGzDk7ZhYS0P64YHxnDkXTfOtYbuGe+gt4OC88vIV9ooAJcig6sGIRQSE8Qx5u+cozJ15COJNYLZrKstgKBtDaZtQ35YycCgaUO4qHSciWDCUJimbmgKgxSKPOtraN6AaQXGCLRUMV+aIUSGtxovLE5YZKEQQiOmOaODGd4LTh6dYp3HVjXChWKuxlMIxVRJ5pnC2IxRZTDErmcPNnXi+rBYGgOydjw5uuDoZMnpYsO1/RFFplBSxQ0tIk0Ojx5noKp25Jlkb3fMqhLUpuL87Cl5OcG7FqlzCpWxv78boHfe4a0D71BSoaQm03nnynRRjOjzy855mrphtVp16aP007YtFxcXrNdrzs/POTs74/j4mPF4HFJR4/GltFFaC4kq4/z8nOPjYx48eBC4kWKdoq7r2AkdjJd3jrZpqOuK1XLFeDSmyYNB+vDDDzk9O6OqqlhHuJyT7wp8l7JZ/Ta9T9rv1F9r3DchlETKcQfkjfPBA24QrJ1DA+dtSyYlhdYUKnjzszzri8Ym1g+k7a5RqsRLFKhYbCRoCykiCSJgbayUWCFohaT2Lkw4s4bGQeUMx8awsRYvFYUQTESgG7dKobzsiOm8s6iYFpPCB1p6EYoPQiTnxXdRkSUUk70Ag8RJiZGKSigaodhIwdLBuTWct4bz1rK0hrVzNIiOWjq1/4W7GusDInUs00UI3RchBokkEetBIkCSIztF6GAHNsTOauvwMgy+qYXroO8VwXieW8uytZy3DeempbEB1ZdbSa4s6yxjBGy0RhGMVloTrXVcWMvSWR7XNUtrOWnbEBXBpYjIXv4kPRbmJWvNX3mjAP2DdhWFlH6EEEil8QjOFwERc3YWaBJ25nO+993foW1bbMxhV5sNTx8/QSuNVgpTNyglO8gieIwxrFYrzs7OcM4zGo0jj73FmRZnNrRtxdnSMBkBSpKJDEmOFxkSgxSSMpMImUGkuih2pjS1YflkwdMPH2EWDXbdMKYkdwJlQJYjptpzsqrRiWyNgJtO0DzjQsFrY+DoHE4uYLER6NEek92CcTZFuBrsBmNrpGqZTwzT+T6z+R6oGcYp9vY0H9875eHTJY8efIj1jjfe+Q7lVJBpGUcqSpTMcRG/r6WKOGuNaQzOObTOgy/ne5rfRE9xenrKp598yjoiv27dusUrr7zCq6++ynK55E/+5E/41a9+xaNHj3j//fd5++23+Sf/5J9QFAVZlkXK5eAEtG3LarXik08+4eOPP+bHP/4x3/ve95jNZvwv/7f/O0+ePOHo6Ii/+3f/Lq+++irf+s63GY/HTCYzHj54xPHRCQjPh+9/wNPHT1heXLDZbLpagaefiRDgrIFKwVmbsiGdJNLCIEE1OTNgYRNBacfFG4IHKfAu0BmkfTUBgslqzbkxnBvDajRiJwtpl5HWlFKSI5HWImpJ5mzgUYpoICc8xkfCx0AEhpMSZAYyFHONFNRCsGhb1tbypKmD52tazoyhdg6vJKVRjHXGgRRMdcYNHScJ6oJJpkPh3rWoyG6qZSq6R6i3d1gRIgQrRPdT4TFC0EhFpTJqKVmIjNO64bP1inuV4dRYnvgwpWwJ1IhB+ijctHCnQxOiRMRUXZ9/R4b7FmChklJrJkoz1or90YixlOwQZkRngMtyGmM531RcNDWybpDGdumuVYTIntiGlfcsnOMcusE4Kn4Xo+U5uZRMVgVKhK5sGZNajfesrWXtHAtj2XjHqWupiIADkpMwQFul7KOMn21bU7gsw+JjMhLWxjxrxLcLIWlbw/HJCfc++4yzs1P29/e5ffMW0+mU0WiEaQ1aacqiiEZBk+kMpUP3czIKSmmMCbnzLMu7n4AykNgYMmf5hKwQZIUkkx7pM5AtGIVoJba2eGGQGYjCIx1MD/eQUtMsG9ZyQUNFu7QIIEcxlgoyyeFsimpaNtWGdUw5KOhQCGmhNBbOlxvuPzzi9HyXUakZl2VAIGHwpsbFUZkpUvAYlBSUhWBUSMpcsFmvqNbnXJwfobKSrCgRaDwhJysECCF7D96lyW+Oul5hbGgS8wJa03L//j0++/RTPvzgfd775XssLy4QQvDaa6+xWq34wQ9+wHw+5zvf+c4lhX92dsZqtQpT04riklOwXq85PT3l4uICYwzz+bzrbH711VfZ3d3lzp073L17l729PbIITQXYbDYReXbB6WmoIaT1M4TIDuVqgU+koGu4Nv3lPS5ZDg/40O/gO/sgMAkuTEghOaAgdL66Njg/KxsQdVMRf7KMTKtAxews1tlAPy48ToYmOOc9KIWXMnDtyAyPYiMktXMsreXUWJZtw+OmYWUtF86y9AER5Jwnw1H6sO4mqqXNHVOpmCvNjhCx6UuH7lvv0MJ33ETJuNqY+rBS0Iqg2DexbrH0jpUxVAjOvOGsaXnc1JxYxyIahJBOkRgZFPOwwN8bb7rUWaIiSOSEoYYS2IaNtWH8pfBsTKwbOY8loP7GKhjd8WgUml2NxcbJiq0xLJxlYw0L59h4zxo6zjI7OP3KeZR3lL5BDtJbnkCJUjlP7T1L52i8H0QIscaS1tulBdf/2tJcfI6kdFFAgEiEUB0uvW0NT5485f33P+DBg/scHl7n7Tfe5K233mI2nbJercA6ppMpmQpQyLIcoSLSKAVuNjKm1nXDaDSmLEeU5Si4hy7H6nDOcrxDOZKUY4WWGuk3kINvMlwtMW0VCPSUxOeAEMxuHVCMRvjaoXxYTM1qBd5ToEFmZEJzd38XtVpz2lQsXUghKR+nWRGJ81yY63x8vuKDj+/zrXdvMB7lHB7MQ1GcAK+zxmKNjcNNDIgGITx5ljMqYVIKjs5XVKtTzo4fMJ7uMJnNEUIShk2FInAgGgx4bmttqMcYw/liRd201G1Daw2bquL999/nvfd+yU9/8mP+4sc/YbFYkGUZb731FsfHx7z77rvcvXuXH/7whyilMMbw0UcfsVgsWCwWXQrJmB6MuFgsePr0Kefn5zjnuHHjBqPRiKIo+MEPfhCouSN/ktaasizj1DXPZrOhbRoePLzPyclJh35KjXRXGVu77uABdYeIdRMxsB1f9Kwmjy9028cHnB7KKUid7D40s3lPYyxTpXACdrOc3Tznel5QCskoz9DOoZzFxqK3k6ldDpxU3Zxyh8YiWbSWZdtyXDc8rRsWTc2jqmaD44JewbXeo61FW8uZNUykZG0Nc52zq3Ou5zkjKZlJRS4kGT7WFwJ01XW1BBHrB4nw0bPGs7KG43rDeRvQVqfWc9G2PKlrToEVsCAYhAqPi+SR3XgUItQz3VtiVJAgr5H6HkJdy3pHYy1SK7wLtb0NgnVj2QjBWErKLGeW52TjEdIF1gFTVTR1zXq9ZlFbVtZwDjHd1BuFutMYxJnPHmVN9z2r+N4ltBl96tDFFFnfi5GQCzEdJ9J6eXn5WhiF9OBCHyUkjyy9lzpcgxKxrFYr/vIv/4qPPiyRXvIP/8E/YFSMmIzGiFKFiEGG/cajURhOk2f9sa3FWaiKijIrKbIcpXQopjmFioiALJ+iconMdEgTUYPOEbJEyQLXOJxYs94sQi4+k+hZhpaSnVevYZzBK9isG+za45eGDItAcb0cYYzlqVbUNqBNWhe56AWYkDJGF4J1XXPv0QmPji+Y7Uy4Xc8otabQJUU5RgpBvV4hnMXUa6wyeJnhpaXMHft7JRe1p3Er/uLH/5GsnDDb2UEXuwghsQLatqHx4IwP0VZeRrSQZLM5xsV6Q56HcYSj0Ygizzu20kSffXR0xC9+8Qv+5E/+hLt37/LKK68wm834wz/8Q/7hP/yHTCYTXnnlFbIswznXQYvbtuXs7IwnT55QVRWz2Yzvfe97vPbaa+zu7LJZb7raUYj6UuTXP1lt2/Dg4QOq9Yb/8O//Q+BtappubV2iaO+i02gIgvt5OeHLAAk6+H+/SfRuB6WHQLMdvMeUgw8EIbD2ngtrOXWW0gpOzi27ec5OnnNYjhhJxYQwEyAnDOgJDVARbUSgYXDW0RpHYxoa4zmtK1at4biqOTU1K2s4xV1KXbj4OxHInTpP4S1PNhtmsmauFddMwViFedJljBpKKdFSUugwUEpIiUViCdDNVaxXnNuWtTWcNA3nbcvaWC6MZ+McC3pFuyQYkQaPkJ5USPPxfoVSssMKF4xGjIqckNioaPGJqiMY3Vp4LKFnQjtP1lqWzpN7aKxnkmXslSN2y5JxljGbTtDTCbsHe2SbDVVToxYLlnWgw4h0iV1zXUpxXV0T6TvviseAjTTsPew0NsqJ8L4TgzqCf/kIIcnXwigM5TKGvffsLiOSwmyEs7MzFkLy0Ucfcf/+A1579TXK22WsTcjuR8W8cYdPJ4TkoTglO4Xi4zjEkD6IvoBQ+ICHQJLHayhBNiAbhB6BcbT+AoRC6Nj44zKy+YhiZ0KzqcmmC4QzmI1DuNB+X0jBWAkmWjPG0gC57x/czmMSULeW84ULU9rOV1ysdvClQxZhI+ccpjW0TU2jFU47vDQ46QGFVhIlLe1mxePTNa8+fcj+9VtMdrLQFIfuivk9j05AwigFWoX7IJVCaoUQMJ1MQ/ru1i0uFhdcLBY45xiNRoGvKEKIm6Zhf3+f3d1d9vf3w/yGsrz0nSeFbYyhaRqcc+R5zv7+Pjs7O+zszJnP5/hYiE7rIW2bogLnCu6IOxweHrIzn7O4WITZCWnOwxU4bF+3DIvAP8cgPMsKlMxIOsTAIoQcXJ/iQHQT+Gr64mzrYeM9vmmo8Kx9QAaVUjIRMjCqIiizALuUSvQ8QFJhfYgs69bRGMdZU7E2lrO25dwaNt5yDh0uPhU3bfeZwuvaQxNz4StvaQSMlWXtHaUUFBGtkwlJ4T1ShnpSKhDX1rE0DWtrODctaxeKyYs2GIq1hdpzqdja4fTTdLPuHiaj3aeQQjuI6J6D/up9F1k4AcaH9GllLCrC140L9/msrqitDRExUHuHyhSF1oy0phACmWVMGoNFsDaGLE5jTLMuUiRwlXgnLRczWDbJVKV0UUcaOFhwMRHSpSuhC1y/UL7yRmFIqwxcfmChe+ATfj3tI6Wkbho26zU//elP2dvdZb1c8j/9j/8To7Jks9mQSYWWikJnSGMRou6O672j2myoqgohFcbYHgHlPc4ZWtOyqSKBspRkMijJXOaItoB2BHKO05JKXIAGpaGlDcr0YMbMOopxidk4Nkcrls0Zbm2gtUibMVKWG7MRzcohW886jvmqHbQ2kDpaDcvac3bq+OlffcJyec44b7m+l3N9V+PqY9rqgpOHD5lNJ8zmE0RZ4qWidRpLSWszFqenPHxywZ///AG1cXz62X2+8Z0fsrN3yLUbdynKEZnOUSoPvDguFGW11ty9e7ejGlht1rRtw7fefZdvvfMN/sc/+iNWq1WnmIeS+hS01l0/gjGGuq5DR3SWdemj9G+tdceUqpTi6OiIs7Mziizv3ksG5NGjR1xcXHByckJRFMxmM373d3+X73//+/zRH/0R//rf/BsePnrI2dlZd03JkFyVtPSe92yK57wjBiMrQ23Ch9BOBGcivOG6hqqgFB2NtygXjP4CT9k0lE3DZLUiQ3RRQi7CwBgpQm05kLQFAIIj/G4IacYqRiOpsNkQ8vbJy5WdSYuXJWBNqBUsfBhhmRvPQ1NRCJjJMCQoIzgqMqY2kxK0KBLXaIWjwbGKnzFh8YfRSYJiJuUaWhI82DYY0UEUdylgG7zmPR03kyBBZsO9b50P8Ns2jDvNRSgyZ4T6V2ZaTqsNo4szSqm4vbvDTllybTJlNiop85wbSjPebMJkw/WKZdtiTd1BjD29UUi9i12zqe8jBUectyDlpa6ObqUMWpcHWcyXlq+8UUgyhCVCUvyq+3cqEnaMqC70LTRNKF5+9NGvkELyd37ne2HugRAUOiNTms1mE7sf3cD4ODbVhqqukJnGS48yMnaWgvNh9GfTtCgJbaZA+TiAQ4LT4DOsy7A+Bz3Ga4dTHqE83luEtqjZmALF7HCJ8JLNyQpnAr+/czVaCualZsdmWAnnvsVZT9UG8qzGg2uiQnCwWrVcrFqsz9D5mPFsjMtaGgWjctyxiqpRETxKkeMoMT7n1lriRcbBowuq9QX3P/uYcnrI+WLFqjLs7OwxHk+ZzXZDKkxEBngvUVLHBe9p6ioUhM9OaZqautp0XFPDDubd3V3KsgwjRGPqLz38HSJo0KMyrBc456iqiuPjYw4PD5FS8uDhAyA0u7VN6Ic4PT3tFPze3h7z+RxrLfP5nLe/8Q1++rOfcrEMhedES/EiHq7eoA0e2sGPiLF+XxDttxWDfwsfyeSSe+t9bOrykc4toIjCiox9KQRFrvD9fOeorGOtuVOUrX82ZZGigZbQhBU8ct8p4tBQE/p+gjLr2/gSKqaOf2ceNo6OSE5Hg9BTGIKLY+ctggYfawqXETY2Rk2WwCBrIRbO4/MNPYFfcvsvRW4DYuzuixgM9xF0KIAuNROVc/psiPA8exK1dogozjcbvHVoG8aojvOCMgsQbO8jL1VTU689RJZbuvuZILnDGnisjcTvt7/EQQ+C993rQzvRGYbnL8tn5GtrFCAo39TYdNUoBMZOS9uaaBQ+5PzsjL/33/533L55k93dXXxW4FLns4AwmCchUSybasOmrtFFBtKjdI8oSJFC2xq0kpjWIRx4GfDdWA0+p3U51htENgFlcdLilQ2t8Fqhp2N0PmJ2c4P3cP7kBLfeYKoa7yuUzJiPcnZdDlKycB7XWDbGUUfns2181+yyWres1gYnCrJyxmx3F7s2NFpST0+ZzWbszmeocQ5K41SBlyO8zzFMkdmIe4+WLDYrHtz/hGx0jenZBefLhsMbt9jZ2UWKjCIvKPIidNsSJrO5kKeiqjZcXCx48uQJ5+dnnJ2edFOyhBCMRiMmkwn7+/uMRiN2dna691erFU0TehvSdzoejzvPPyGSUkfz48ePOTg4IMsy7j94QNu2CCFC93XTUlUV0+mUg4MDrl27xu5umP8wnU555513uH79Ok+PjsKacS72K7jLKaIrfTL+0joMnrgQ/aSskF4cmItgMTqPL0waC94iSUF433vsaZ6C951BEISHPeX7+2lk4RQJAZUMQP+U0BmXRCCdPPSWRFXtwxwOInup990sc0Tk8YnRQB3Pm0UjoHx/Xdml8/nOMCXjU8Xz2pQ/F7F51HsMLijNlJWNXn5iAnpGH3qIgNRwv7qf7o72d0GEBrtEbNj1NohoWDqjEBrhvPcsqgrXGlTdUCqJ9jDfGZNFtKLxBIeytXhjMPFuGjyNS93vfVeylrEzWhDrHmHGR2r0S+JeVvN/jnzljcIwEkj/TnlFE3HzyTg4Z3HOhvGRkS7BOsembuB8gXeee/fuUWQ5h9cPmc1mjCNyRSmJ0hKZZWFOQ9uwXq/JspzJdExe5IxGo5g+IqBu2gZrHKNRyXQyDnht6ZDagl2DXeOEQZiMDEmmDEq0rNs2cLKrsCgy6Rjd2kMWAQ5nhKeVBrOuUN6SAzu5RkrNWeNpTcPCG0p6jzCFz2enK4pccO/RCdOp5mB/xFjlyGxMOR6TlwU6z2LxKmQ2vQskdIWG+bTgtVdv8eDJmouN4NvfehcnCp4cX/De2QKE5GD/Y6bTGQd7B1zbv8Z0MmU6Tb0LgmvXrjGfz5nMxqyWK5YXF90cBO898/mcvb09Dg8Pu9TRarXq+g/Oz895/Pgx3/rWt3j99dc7MEGWZdy6dYvxeByGAD19yp/92Z91sNTvf//73fCduqpxMbJIdYiPP/6Yuq65du0a5WjErdu3eO3111muVnz66aesNyEyBKIXJ55Zi8+op6SM/VB1DVzaq15e7Ez3njgWVHbrOanAMNwlKK1mkEpIxiAVORn87kT0kOWhxJYyQok2XevgKPG6DD1HUDqMJRgpKUKDnPD9NYgr13X11vi4f4haRP+Teox8uK9dv7IH63v6jnQdl6aFcrmJtYvg4rWJqNydi1GUCkeTxGltcb+E3EvP0CDeY+0c3jcI26LPQ79NJjN0nqOzgvnOLtnE4kZjJm3DqG7YeIdxlrpuaExLYw2NbbHeY6yLPUah6z1ER7Z7brsIQaTP0KeitumjF8izkcKV14S49PSlQigEWoKQp644PT1hcXCAiR5lymUHSKpGaB14YQTkxpBnGVmWkenwIyJXvRcGHGiZoVWG1jlKBnZSoS0IgxcGoXIEFikMUhmU1LiI+rHK4ERYLNkkJzMjJtdmlI9HFKsc29QIaxDOkEvFSCnGSjOSlkJIMh/a79sYbzqgri2bdcvFcsNq3bBpLMVIIqVG6AypdDB6JAMbEwg+pGVGZc7OfMKDJ0uqdUVdV4Gyu6lpbEBJBC8+rGRnLBejC3Z36kBCmGeBBMwHEsJMacajEev1ujMKk8mE2WzWKey6rjk/P+f8/JyTk5NL216lTC+Kgul0yt7eHpvNBucc5+fnPH36lOvXr6MzHec4+ADDdYEGfLVec7Fc0jYNu3u7SCkoioLRaMRoNCLPc+qmrym9eCHS69KXdOqerUUMIgh6Q5P+P1T4idMzmQxB8NzT+583jWtgmvpc96ULT416iYEzcmx1503XH7dJipjeAKb00tAo+G6bIH0aqyOk6I3OoCYgIDK1Xr53V295dx+vaktx+crT55eDf3TpHPrzpPuajNfwxyBonKMyhnXbUkgJOqxxoUBlGbkQjKVCOYd1lgJFozSNaamMDIbC+a6A3vpgnCWXDfjwc3fprUvvvZx1+MobhRcVmBOCKL2us6DcvQjNKk3TgPBIFReFsLSm4YMPPkAiuHPrNqOiZFSWFHngNBJSxZjPBIXn4pAWC9IJhI9Bu5d443AGvAFvRNCrECy9CQ+S9Qori7CQpUDmDqksoljgY4NaY2qMaVA6R+eCuXTsr8/x2tLWj2hWLXZlyWWIFK4VI5xTrBswkYdGaUXlLd5Z6g1cXFiePl1wfDjnfNkwHWkymeFFhheaMEQlpEraukVlEqU1u/MJOoPVJuN///c/48c/+YCNm7Kzf4vD229xcHiL6WyHshxTVRX373/GT378Y+qqYW93n9l8zv7BAZPJLHjit24xm806pBGEYnFVVVRVxenpKcvlkk8++YTT01MWiwWTyYSdnR1++MMfsr+/T1mWHRw50Wrnec53vvMdDg8PKYqCTz75hL/6q7/i9p1bzHfmXLt2DW89TdPyySefdFFIIu+7E8d6DoEJeVmgqk2/wC55/leke3n4kL6cpbhsGEIW2l952FMDVujUDzUH70INCeEvQx+jZymHO0dxA9Xt48ZJ2STFmfieLqUthBhm6/uF7X33uh/8pP8r+k8/NAp91OFI426ee2dielEM3Oeeg7W/eyna6GCcwsVBPhGOG6+s4yn0viu4ZKK/ZymqSHfP42kjud9E5SitKPIMtKbVilNTo4VD49gYS+McK2NBa6aTCZN4zXLscNZibahL1qblfLNhZVo2tmHpTIAgx9vg/QDO2vmyfePblzEI8DUwCtDndIf/hj6VJESgF+hghZHoLolSikSb9fjRY8blmHv37zGdTsnykGbSbYNqqoA8ifQG6/WK09NTjDGURcG4acLwdCRN3dA2NWdn5xGtYpDKIqVDaIe1FcZuqKsNzjUoWVMXUGhP67KgDIRFqbAKjDMop1DTkp2bByghWR8vWcmKtq5DBOJhVuTUXrBjPOeupTEhh6l8KPhhoW0cZ6crzk7XnJ1v2J2U5LQsVxu0tGhpccrhhQ+dta1HyBYnYFNLnBMo4ShzxdtvvMZs7ybldI/zs1MeP36CdWHgze7uLm+8+SZaaZq6Zblc8Ytf/ILjkxOsddy+HaCft27dIsuyrpCcmtPOz8/x3lOWJePxmGvXrrG3t8dkMuHg4CA0nsVu9eH3LqVkOp12Refbt2+zXC5p2hqpZJihoDKKouC1117r1sHt27eZTCahKP3gAR9++CG/fO+XfHbvHhcXFzRNM2ha81+g368mcF4ybOhkGBf4K6+GvxIEGHyEXfaqtbuKgRK5qji6gia+SxcSaxXPizL6yKCPAlIskcyEv7L98FqGhkV22/iB7351lGcfc6TegpTTFxAmqdl0fxK53+eJ787YOWjpPqXfnsiwKklRhU6pJTyFyiiVZD4eM80z5kWB9g7vPGdNjatrHCvWxtL64P17IUGpwJAqJWOdUyhNmReM8wxjLUWec1FvuKgltBsa70OtxgXgQdNdvew+SbruNPh129Ec5Wr/weCdy8U+63D2MiQVn/KPfRfu4ydPKIqC+w8ecO3adabTKWVRBorpyrNarWiNQWcZ6/Was/OArS+LEmtc5FuR1HVD3TRhLoNtQy1B2dBsoxzGVrTthratwbcI0WKMpM3A+9g5LSxCeYQG0zrIFWpaMDvco8gyjj99jLOwPq/BOaT3TPOM2kt2DIw2Syoc2gUyCk2AqZracX664uxsxfnZhvWOxkjDarUhUxatLEITnD8pQtRAQ2ssjc1wbozWMBlpXn/tFabzQ4wYc//BI+49fMxy1XLj5k0ODq7x2muvMZ/NuXfvPueLBR999BF/8dOfcnFxwc1bt7l75y5vvvkm8/m8G6JzcnLCyckJFxcXjEYjfud3focbN27w+uuvc3h42M1pTpL+HtJRJBTVzZs3Wa1WrNcr3v/wfaqqCvTpWlPkBbdv36YsSyaTSTe57ezsjPv37/Mf/+N/5P0PPuDJkycBMtu2dFAPIS7F85cj1kuB/Uuv5eGDnl4ZnCGdiMAhxLPn61Pn3R/9u32fRDpyD48cGJ60zzC6iO/6Kx8rqeKrEVFnaNJ+lxI2w2sU3d+XlVzPL5UMiyeksJ5JE3X2+bLx9VeO2x/cP/NaN3zHp2E7MhqFSEYZkU7Ce0ZaM8kLdmYzJkXOrCxpq5q2bThfLKjiYJ6NdRjvQQXorXdQ6oxCZ6jxhHw0piwzijzD48hzTbYKzpbxLZWz/Rch4khR0iTp5CoM7qLo7/wXyVfeKLwIHnhVUiOaRCJ8+AmcM+AsAS3kHUf2mLIseXp0RFVvQHj2D/fJsxzw7DkXGqB8QLdMd2ZMJxOKPGc8nSIJxsXUYaGMpxmjUcFkMkZqglGQoY/BWcNytcC5NnjeI01ZSLy/QLgK7DltdUxbL0LHpAutS3pSkAvBrbfukuVHXJytadcW2orM50yk4CDTnOocYRyta3H4DnXijeXh/RMmZcZYKW7tvMvOVCFkhrGOqq7ICRj/TGuQGi81UmuUy0BnvHL3kE1t+X/+P/4X9q7d5e/8N/8Hvv3OO/zB7/+3GJGzWq85Oj7mf/3//H+5iIXkW7du8w//0R/x9/+Hf0DdNNy/f5/TkxN+9atfYa1lMpnwox/9iHfeeYe9vT1msxl5njOZTCiKIs5+1s+kDIdrIBmG4US+LMsYjyd8+5vfQUqB1lnXu9I0ATBw//593nvvPY6Ojnj8+DGj0Yg33niD9957j/PTs5SOjlrm8pp71iH5slHB5T2TwrusSP2lX3zhe5e3cgOf/WqB/POu5Xl/P7vNsMA+VM6X1NZLHHtIORj+sx1MIinvNDAr0FT0h493zqeXHPgwC3zITGtjJ1ii1e+3l2Fwjg8Di7SIc0bwFDgKrZiWEw4mE2ZlybXZTvDgTcvxxZLVZs3xekUTeYs6igpjutpG1lh0W7OqN8zWBTurksPdOWWRsTPJyNWYeSHJhGFZNxyta6QXKFRHddGmtJEQWJ/ihzikfWsUvkiS73A1r/uCByK+bEyAkjZNHYqZwvfFScINDVS3LcYasjwjy8NsgTzPw4E8YeiJ8PH9jCzXSB09EuXxVmOlJdMtzmVIGeZHZ3nEbbgMjMG0a5AVxiu8D52gWmtEKRjtTBmdbyimJc6EphaFI1OSkRaMtWKjFbppO1ig8OAtbNaGzbJhvaxwViCFJs9LdGZR2pNpjVIyNIxJDSq0RSmX42TGZFIynY5R8jw0YUXeHilkpB+WXXrDQ6AJidDe8XRCaUds1hucdVSbUEPIsizSWnuKouj6FIqi6CCpw9nM6XeCmV5NI6X30+vJoAghOvqKFJGk+kUiwXPO0TTNpW7mwdLql01SVC/pnLys/M0e7bInfrlw/fyTXX3pWVv4RVfon/n/553lckQUPeHovX/ekZ85lhgkoeICHAIRnmE8EFeju97QJlivFp5CCaZFzmxUMitLMilpTUtV16zrmlXThJQRPvZrpCly4VhCBC4r5z0b41AiPKuzOkMKx7jQFFqifMasKBAeVpUJ/Rneo2KKyMTr7qs6lwcHvYx8LY2C9334GV/oQsRh8XD4o5TupjABtKbBONMxS/pBLO6F7zh0rLUBuw7RWQlFv552wfaKRYhIvx3y8s5KnNV4F7EZPqdDcwsNosWxwrqKlgInPJnwZIVCZZ7JtX2a2rF3awFuSUULtaUUgpnU7I5zrHA8aTY08cjGhzp5tYR64zG1J9MjxuMRk/w6o8Iwzi1FEagovABUDjJHZnOMz8ianNl0zN7OlH/8j/4Anc8R2R73PrvPe+99SuMFo/GE3YNr/J2/8wPKUUHbNjx+8oQ//fM/pSwmFEXJ9f3rvPHGm3zrm9/s5mInb/3p06ddWunatWtdt/JoNOpqDzaS7a3Xa5RSTKfT7vsckuQlY1JVVTef4fHjx5ydnfHRRx+xXq/ZbDZ873vf4xvf+Abj8Zif/vSn/Mmf/AmPHz9msVh00GZ/Rcn8tsmXueqX3dZ/zr++/LFjUqoLzS6/84xBe44MI8W0RtL3pZTqjHzaxtlUmk69Dw7rGzSBKmQkBbNcczibcG0+Y5wXVKs169WKJ6dnnK4rNsbEiWiCGn/JKAQab4FUYRRtbQy0NW1bkQtLMy6ZlJpCKSajAunnLPMGawRUa0zbkEdMVBrB672PtNs9Od7Llpq/lkahqzN0dYVBdvOSp5CWmcO5eFd9INWy1nbMoW3ThE7GDh7nA0Jms6HaVGRax1mssmujN21L2zSsV5vOW9WZCkZBSdomNM6tV6F4mWegpA3pJ1yg7jVQbyR1pbAmB0uYkBURFRQFejJmuj9nfd5iGkvdhmWjhWRUCMZOkUtB7j05YGI63BAGrrTG0rQtTZtRiEBNYYyjyAM0VQiwLjZnZQGJIYRkVE6YTCo++/QeebnLwY0xo9GU8bREZmN0nlOMRtRNTVVvMCYgg64fHIR7jWS9WdE0FetIWCil5ObNm4zHY7Is47PPPiPPc05PT9nb22N3d7ejsejp0MUlYzBcA6lRMSn9jz/+mNUqzI5O277++uvddkopTk9P+eUvf8nPf/5zPvjgAxaLBU3TvLB29dtqHH6zxT8vQPhcuWqwrzp/8bBD/ot+RjOXC84SQWDqCl3Z0yJnXpbsjqeMsoxMCBZ1TV3VbKoNjbW0uEjy10Nsh70cnsAqIOPv1HC4ahqkgIvlCl+UqCJnVJRIqdkYT+UcdWvCfA18TCOlZtQ4VjV80Je2Cl8rozB8YLuw3qV85+XXu33wED1954IhcX4QCRhz2SjEQmZT1RFh1NBUNXjIpA7ehheYOFKyqmqkFOR5hoszo4WUNI2hrluqqo2LVYYibyyAewemhaYWtI3C2RzpBV5JEjJJZAV6NGK0M6OYLKnWDX4VrkVJRZELRk6SK8hd4KBpVDidcUSmTEvdGJrWUOQJZutIg+UTLtx6j3Spu1aQFyWjcsLDR59QjhsmO6+wd3CN8XSPfLwDMnhKp+dnbKoKa1u01uzt7rFe1xhjqeuKOuaXJpMJWZZx7dq1zrN/9OgRidLCGNOhitLMZgjKYMhlBM+mllKPwwcffBCLzmv29/eZzWbcuXOnMzSffPIJJycnnUG4d+9el1L6PH6tq8i3raH4WxYRiCk9/pku4Evf26DCMfyGhugpGdNGYb6zQwnBOM+YlgWz0YhSKYT3tE0bHJ6m6foLemMQEzqdLYo1EBG624ekglXbooDVak2GpIzswVpl7FpYrDdcrBR5vOaWvnFQMByp2pUuvlC+VkYhSVoIqeiYiNFU55GGNA709Zmucu9cQPIgMG1DXW3YrNf42FmrlEJJiZYCLeiGtId8er+4umvxod1eC42WefROAkmZUh4pwwxPKXKkKAgUYqmVZ4yWc7yWZCNJrgzT0iHrFb6p8LlDzwW7dyTVhUOIgmr9FGqPrVvGmcR6xU6hAvVF0/P8W2BdNZycn/Pw0RMEM+Q1g80dLvOwrkEEj0uoPNQU2iXGZ6ybmvUm4KvD6MzQEbzZbLBec/74ODT8pDqAUoyn4+7+F8UI72GzqWjqhjr2JTRNg1KKi4sLFosFr776KuNx2O/x48c8fPiQDz/8kP39fb773e92heeUHkjcR957zs7OODo64sMPP+T+/fssl0vu3LnDbDajLEuWyyVVVfGTn/wEpVTXH5Ea49K8aDdIBSZ6lC9ae2FdbQ3D37QE1omeUqS7xwOHoN+259AKjATqEvggcCfJjncoApMQeLQUjJRG25YMOJhO2RtPmGiFaQKqsK4q2tb0BoDI3iroPXegRwo5jA0Oaur21gQGWNEaTs6XYBzCGMosI9cZB9MZF6s11aaiaWpk5H9KTq5NUFTSuns5q/C1MQrPLSSJy++HSUvBk7icRYpN/SIRsilGoxFlUYZctg5jOXVMV4BHSRkLsSpOZwvNcd2ocOfwzpLFhZllGTpSZOBDwcn5MHcAT6hpxB/hs5BTdSVWlfjYAa0yhx7FCNgLnFrjM4cuJ+TjCfmoDrTUjQHnyKWi1IppnlPZloxQcLaErldvLU3TslxVrNYZrVVoK9BS0BjTw/RkwEp7a2mdoI3BjYwjSp13bDZrRpOGrHCMRyMQEhG584WU5FmGMS0X6zVS6jhcPgzlKfI8QH3btqO7KMuSpmmQUjKbzbp0wMXFBd57Hj58yPXr19nZ2bmU2kkF5DR28/j4GGstWmvW6zXe+47iJCmJRHNxfn7OxcUFT548iVBi2/ErJePQLa0rxexn1t6vIb/O/r+O8fnrXud/aXneZ3peanDo8w8dwZSuFaJ30JLKTD0OJJgpAiUFqQci9WgoPFoEFy1ASTVaCIxzoefJ2VBvpE8VWRJpX7AJMUsV9I33AUzqUyThu5pD6z21MbRxPrlzPpAZqjCDosw0uq1jSqufYvdMvCOe1/T3rHzljcKLFlD4UmLNQDgaU9O0NXVbD7jxB2iMAFQgzzWT8ZibN29weHid69evszvfIct0yMXHorFWijzLGRclk1EwHuNxSaIiy5QiU5L1eMx0MmE6myHynFjtRrctWdviY75e65y8KOJ0NwW+wMdQtUFDlqELkDsaJzKsWNBkG4RVqLEin+9QbgyqeIqsHbiaUVaipeL6dIr1a5ZVSyJqcBKwjmrTcHq2ZDxS3Lo+C8ZOKqxvkNKH6xEhjdR6SxsZWKVSjEaBK6m1lqPjp4xnB0x39vnWO++S5yVSaZabNXXTsN4sefToER988AECRVmWfOMb7zLf22VnZ4f333+fzWbDgwcPeOWVV3jttdf4yU9+AsC3v/1t5vM5eZ7z6aefslwuefr0KT/84Q/Z2dm5hDo6Ojri6OiIn/zkJ12n8ptvvsl0OuXf/bt/h9aa/f199vb2mE6nzOdzFotAzvfee+/x8OFDfvazn9G2IQpK3/eQej1FoC9af+la/jbkN13Bf1kZork6PE3ndT+LJUy3X6qQRszzHG8dZV5AHDHrbWgu865PK4X0UIjulVQBnupsJCME6R2FgLFSTIuccRb4ySrrQ0rZGIyzYbYFae6ED4OMhAxhB4FbLSGZEl1GoAMP7mMTocK1s9TWBvZjE0gxtZKMtGJaZOQbTytsRzAY6NRdCp/oKNdfQr7yRmH4cF6Fm0kZZ99634WSeZ6jZE9/IWTwjF0ckHNwsM+164EtM8/zLjSVUgbMfpShB9m2DUIGnn0pQpt+0za0bRvSEMZQNw2a8CV652jbQN3c2jDVS3iJ9RrrVdd2bx20VtDa8KULJ3E+x6sx5B41qhCyRlORzTbkG8jGT6irwMeopUKiKPOCImvJlUDY3gBa62kaT91AaxUq30EXnqxwFMUYpSEvQo+CFxphMpRTiKLESQfKsrd/Tjna4423v09rMqwx/Pmf/zlSabKiZG9/n/FkzI3DG1w7uMY33n6HqqrZbCru3bvPo0ePaNuWW7ducefOHXZ2dmiahk8++YTbt293ij7VEa5fv85ms+HDDz/kgw8+wBjDm2++iZSS9XrNp59+yqNHj1itVgghODw85NNPP6VtW775zW+GAS9xwFJd1x2UdTwe8/bbbzOfz/n5z3/OJs7KSBxL0Bczr3bMp/fSuhiuy638+iLoR2cOFZ4QAc1DRBOm76BL+ZnQf1LXdfS8XTd5MbAXgJISYVOzWswcyNDJnBGMwijPmRehJyhAuiPE1XmMsxjnXlhUjpUEHCEVLUSIRnysK0gizfgApeR8mI6H9wjnUd5TKMk41+RSUDuB8ilS6E/2bLn88+UrbxSSDFMIlyTe5GQUtNYIOSxIxwfaB4rtvb099mPjVJZlIVcYjYKWKnoc0SBED9JYg2hDDSLRXLRtS2PabshP0zYgwjmsC8ijtm0xNuAQpFaBnM1ZlA/HD4PuPa0FoSTSK6zTOFnitUMWs1CLcBl6PCebGPRoiswMXqxCCkcosiykwDIlEc5FhFVEH1lPY6B1CqkmqAx04cnLEp158lLhUDgkVmqE10gmVK2haFrKcsTO7h5vvPEGjx4vODlbcv/ePZwQZEUYY5rnOUVZMp1MmM12WC7XnJ2d8eGHH3F8fMzJyQm3bt1iPp+zs7PDZ599xsOHD7l9+zZKKT766KPOc79x40YYkFTXPHr0CGst165dQynVjeJ8/PgxdV13FNwffvgh5+fn/N7v/R4QOpYTNDUVr/f29jg4OOiiyNTYNoQtp/U1ZOYdvv+bUEd4njH6TbiuoVy9xhcW7mONLvUSXGI+JWYDBvt2A7UiDDxFeWnfrs8lwouFjWVan2qDAi2i4vWQK80ozwcdzZD6HqxLXca9Ueg+HwNeqSGsKew+2Edc2t8xrHFGunEpyLUiSzVM+vcgzbQQnaP3MvKVNwpX0USXulx9pLMSsmuCSjQIPVKF6EnIjl75jdde5/btO4xGY6xxnJydopUiUzp6Jo62NRhraE2DEyEd5F1KLSiapsW0LVXb4CtwwqNziZBhwdR1HUZNtiZAPP0Y61tqk4EN5HXW1NTVirap0Jmg8QKnLJIMyZRirBFZC7JG7YI2JXL3GLdW1FlFQ4bzCp9r1MiQz1r0YoU0JjDDOkFrJLXRNKbAyX1EppCFoBUXwUi1Di80HonxGuMUjZHce3TCp/eO+I9/9hPmOw+xcs6Nm69x6/Yt7r7+Nq1xrKuaugn9Cf/u3/978jxnNptx9+4r7Ozs8vf//v/AarXk9PSE9957j0ePHvGtb32r4znabDYURcE777zT3a+HDx8yGo34x//4H/PjH/+YP/uzP2M6nWKM4b333usYTcfjMZvNhl/84hd885vfZD6f85Of/KQrSu/t7XH79m329/dZLpccHR3xr/7Vv+Kjjz7iyZMnQGBcHSqVJMNU0nDd/aYp39968Vzi2vDOgwgjPdNzP5yRAiG9q+LIz9SsOAQLeGtx1oJ1kSGAwE0U51inOkLmPbmUZFIFir6orJ0LA38iaA4gRhshkvDdOgmaXeqARsQlFR7BhoShOoEmPPVGeIx3pPhDCtBKkmuFVgJtBdJeZsntaiW4l7YKX2mjcNWLGxoEIeiayIA+n+ihLANZ2+HhIWURBsEUec5kPOb119/glVde4fr168xnszBcvixQUpJJHYesBII45TTKarIsUkIURVywCiEVSmmMdeR5Rl4U6FwgJKGIHMNVoQLcMS9ysiLQb3snwSmkFjgsQkm0luhcoYsciUV6h9IFUrUIX6EnNVkN5e41yo2nOK+RMsMhMcYzK0r2y5LNeEXRGjJnyMYZo1lBXs6QekRrM2oj0W0otSE80vRem/GBJqCxnroVODJu33mVyeyAshzjvKdqWsY5FKOS6c5uF8anEZahiaxGqSUHB9cZj8cURehFWK1WnJ2doZTi5s2b1HXdFZ1TX8Jms0EpFSK6/f2ONM85R5ZllGUZvrOi6EZ1TqfTbtbFaDRib2+vm9NQ1zXr9brrR4AwgS1BXZ83djMZimQsfpOjhCS/6deXZHhfAZADavT42CSgQGpSvAoC0Eqxu7PL7u5uh16LByd1OUNfCHYEVJ6QPmDBPTGFG8AiqSB9iSCwq3M8+5me9yl93DZmkboy8fDvGBQx4J/trvsquijVVyIg60t9v19powDPRgr9sJ2BcfCetgk9Bc479vf3eeutt/jBD37AYrGgbRpm0wm78zm/9/s/5OaNm9y6cYOyKMh0bJYSYWZqyhVWdYNzIUxNBG15ngd6bSFxbfBIxtMNWivyPENlffxnTEPbNmzqCoQgz0uKLAtoJIgpKktTTTGmDUZBK/JRHsmaLLgW2gayFYUJHce7r7Uw2sPoWRyBKSjblrGx7LaGnc2GVdtyampEJlG5Znf/kHw8Y9VmuLVn0yY+S094WgjwVGSYJ+ugdSXj6TX+8f/5vyPLJ0g54dGTUx49ecJ43XLz5i2+8frrTCYTtNb8wR/8AWdnZxFW+hFHR0fkecnNmzd49dVXmU6nPH36lH/9r/813/zmN/nud7/Lj3/84w6mOpvNEELwJBIWzufzjuo6KYc33nijm82c+hheeeWVCJtt2d3d5datW/zgBz/g/v37HB8f87Of/YyzszOOj48ZjUbcuXOHvb29bpbzkHgvSQ9U6Nfe8LWt/PVFJBQIgb7bOdcZhTzPu/uc6NKHDqJWitl0xptvvtl1w6fjDMX7QD0RDIHDu77XAMAag63bMFUOQleAuOqM9sf08X/PZrBDBBG2FjgRrsX6FBOImOqN0wcHVQMfU8nhpvTn6YyCYBAtbCOFZ0L2IX5ZCBGUuAhwz4uLFet1xXw658033uTw+iG3bt2haWq8dWRakWcZb739DSbjMVleggwditgQyjkfwtcUcvpY9HcEnh/hPNI7pBCBs8SBFwrrBY1xKBlDSRE8bodE56NQ11Aah6TtqSvxToDKAoOrCAyJ1uowBMuJqK8lMpeImUZnUw7eyZjd3nDtzWUg/xMCo1Q3+3ZpHbXzrJwJi1N4JpOCotAc7I3JtCfTHmuXEWCXCL1EqC14Qeske4eh03ln9xY6G5FlYw5uVNSNIctKRuMxWusuVed9oMC+ceMGZTHCtIYispNKKdnZ2SHPc370ox919Njf+MY3cM51BkEI0aGQUqPbfD7vIoUEYU2pg/R6qkdcu3atO9/169eZz+fM5/OOYiPBYq21XU/F1bV1Ka99xRn5vAa3rXw5SffRRc8+KXQBPdxU9FHEpfvvAuz45s2bHZniarViuVyG+dwubK/jiFGcC4p5oFY9YK2hbRucD6pbyZBe0hIyKftaQ7quqLX7+XhxultU86FmEIzQkNU1NbeFk8sAjnE+PGvGU7cW40Kk3jIwWsTZ6zi8FC/tkHyljQJ8Pqa5Y3oXkvPzc05PTmPqQjOf75BlOT6ijhIjotYZbWtp6ovuWDIdSYrOC7C+92BE3C5EFGFgvbUW63yc4Bb2VRmxeS32THg78DqGmALRoRy8D8MPhfcR26/xzuKdQ/qQRpI4aFpoHW0+ws9yinIS8pxCIvIcpyROSuZCYRDUPgwTN84GWm8BUodxhF56vBPdw5AknCl4OlmRkSuNUCOELJAqpxwpdOYQMvBuLxaLZ+CbzjnKssTnodmsrmvcueuG2iQvfb1ed53K6YGHQGoHsFgsLimGdP+7a43eVUKIAYzHY4QQXYpKSsnu7i7T6ZSdnZ2uWW1IvjdMFaXPclUppc/2m5RK+qrIcMxukvQ9DPsShk2F3gUeo7R+Li4uOD4+5uzsrP+OoE8Bidg71MfHIe/vHNaZAFeNqB8l+h8pUi2hHw3kYtGXrvgbjynockWpCC06DdUzOoV50L5LLRnnaa3DRCfTDq+PnlaceMqXka+NUbj6gOI9bVQmzln+X//iX/Bv/+2/5Z/9s3/23NBTRkSDc5GG1vfKsOuE9JdjQ+/jAHMf9g3NbaFP0kZrb6yNISfdwJw0BSpceDqYuPS398QumFiw8nEZeRGHuhOVeZjpmlBFGBve94ECOBxOgpB4pfAyjAsJ6j56YNEgSmEiYR8dV1G4tzFvKUW3UFOOVOoCIRRSaazxuDCl/lKI/UzNJ+L3nAv9DkqrzigkcrtEXDZUxqlomJTB82pJz1sfw6lu6bUhguiqpO97mLNO/776/tVz/tcwCl8mZfWbfG3Pk+chk563tobfoxI9PDj1mJyfn7O8uMAYE2DoKsM04VnXQoIIg7YsParIi0BJE+qIsd9AglaBAkPjQlEa0SlnH/WBEqFp0zvZ1TJC93QwDAGu6lEINIFriehoCqVBaQyCyjhWtWHTWupBs1xX5BYgw7DHbfpoKFeVQqfMUmDnBU+fHrG4uODp06Pg8SOw1gQ9L0UcjkOX6hCx1SRFASFfODAKsVbhOqMQmmAEiQW194xTMlSq4BU44S7ZgvBHOKgXBGPgQ84z1ZdksiEuwdBipzH0jYxRwYccaLdswssxBRUuIkLhfFrEPhoFGxV64EUKDUS9UUhOUEh9xfekJs2qcDYu6i5SS0rhmSRr50XJ2PWcjEJd152X/jxG2+cRnb3IGFz9O0USHRJlYByupobS72GfQpLPO/fftlH4dZTub/r1Dfd73vf4vBTe0ChIEYgcA2w8RIqJRqWrK3RrO6CAJGGIT+ImMoAhTB4MTMgWhA8pJKlCc6qUkbKiH0Pa5fc7V37oJAXnTmJRhPGkiWdJCxlZEzRKZyAVtbXUraFqWxrvMT51Tg/mWgtCMZ7Lk+0+T77yRuHzvESBjAtE8OTJ0/6WpYWaFpmUxPJDLGgNjcrgXJ13fzlaSHZb+EEaKNagus5MMdzNXTpOR8tNr3mHwDMhZMfLgk9oiL7j0w12hcTB1H/EwSyR8JnEsEk++vyDfaI/3F1/0Ou+Mwodnrq7L8+R57w45IUS/YuX7ufw4R4q2JfF37/Ie7+a/7+6zZAX50Uy3Oc3qXbwVYoUXvb7fh4U/Xn7htQwuNiHpJUO9BTOo0VwaFLPgCB0JQugAmrvQ6exaWltDgIypSi1Zpzn1MaSSYFywalS6ThCErvQ8D5Ew1qrYEC8RzsfYa9E4yDIpabICspy1NUz16sly7rmoqrZOEfdV/loSRxLwakNqeyXu8dfeaPwYhl4EKLXUUqpZ5SCdw73As2WlNhwttTViCG94eMiQPTNNf2Ze2qs/jjpMFcfgKHPkQxL8ioUQoQjueivP4OqGP7hQagwZc4Too/wViqH9ZsKiEPhCfEoYRRnSnAKAV70dyJdem+ABp/jykcawvmuftqr+eKrD/gzMMV0nCsG4IsU0HPplJ8jn6eYtvK3I1e/7xc2uEV5kYFIaWE5SClJIZFagBNYP3CKhOz7BYCN80hjeXK+oGlapIBMBUr56WhM42FUt6zbFu0c46zACEkrBJWxWO86wkxwCBei+ExKcgQFoKwN0wDzAp3lqCxnY1qMdRwvlpxVFUtnqAhzmlshsb5PI+FBOMeXsfVfO6PQLQ4/UL++f+9FxcD0TyEZaNUXeMHdyRho097zFlGFBwXruayl0479ebuIZHC8S1mleAw/NBRxhwB3G37+gRmKf8gu93N536GBGti2wfuXh6GnfGnnfl1V/MODXPmcDHYbih9+T3y+Iv48Zf15+1316p9nFD4v4nyZc3yZbf5rym/69V2S9Gy9pFxK86ZDhBdIENcU+Uohsfjg5Pj+yUqQUes9rYfaepZVjRKCWVUxGY3JtabIc0pjybOMzFoaD5lQAUgiJEY48KFWGS4hsC8LD0qoUKxGIkUCkGTILENoTW0tTWu4qGrWxlB5G9NZdBDWRKiH71PLL5k9+voZhRdJehiGFLsi5Yzo0S2Bx6rPXV/Kc3SW42quRYQd3WD7Z76pZ1MnlzzuwWm694bFZ4CIa+6//BApdGn7K5uLdMnDytTVEyWzE0+X6uupvhAezJT+evGq8ym9deUcV5JFMXh5yTi3+xxfnKf/vPevFoqvQpmH731ZpTlEP23lry8vuotftAassz0AYZAKTHU9mWoPPqSOJA4hA4jU2z7aNjFyaKAbYbvyoJ1naTyZF2ipGU8LrC64jqQ+OcNXFUvTdOlZ7VyYzaB659B5kM6jMaGGIKDMCkZZzmxnh7wcYfOcs6ZiVVU8Wi85axuWwIZAolcDVsQ5Cr7vyfoy8vU1CtFrTdwpPG9RdUp+4EUyQDENt3lmv97TvqQMo3JN21zefZCO8gyOERNLnf1Ix3cDb2lwTcOTDT7u1Zf98Pdwx86g+cuvX/oYPmn6wS7+6gVc/txXr6PPjw3uw7PG8tIen1NYHPahfBl5XoTxomN8meO/aNvfhDrDb7OI4Vr5nO/DD57fuPVzIoXLBvuyY2AHaV66aDywmAb2UwmsrUU2htFqjZIa56EoRkipmIwmzCctSElbbcCH3gTwpGGOAX4eaK+FIDCdCkEmFaNyxLgoKMoRKEXjPMumYd00rK2h9o6Gvo5gfGiE8yL2PKXPyNUn6cXytTIKz3prsZNw4AVe0oE+Kj7Zu8iO/kZ/7nkG3uYwfXNZIfvBa1cBY+KSmr9iO/pXBikZP1jAV/P63YORdPmzB+RZBfzMmfstvH+2mPwSYeowLuqu59KOlx/kq4Zm+BB/2dz+y27/eYr8yyj05xmwrfz15JkMpHueM3RFBkbEOcewQHg1VZgMeRc9ElCDMv1DiNA05l2AiQILY2lshW0N3kta49gVGVJp5pM5rYc8L9hYizAtzpuQNoqenvGBQC8hjjSQC0WhM2azKeNyRDmZYI2hMi3ndcWqrljZlo331EBNMFQNkDqnhFQxLeWfyRJ8nnytjMJVCd6u7Quggm7yGRAItjolNXQ3nq8oX7gwP2/FDt7rQWuelE5KkUZqYPmCJMkzp7vqgD8TFVzadvjmlQ0HujrGKJcf0Bccs+uFuFwZ+LwP8YVy1bsbIpJeRvl+oWf5EvKbhC76Osmz0eavIcOFKwRCSVyCFosw9TDR6gej4AKE3F1e9218GmoAL1AOTjY1rQXIGJUlk2nBfDKnLCdYpVg3NRf1hso0GGtorAn6xweWZSUUudAUWU6ZlWQ6x3k4X63C3Pe65vjijNq0ocDsPRWDiW6dkyUgXn/H4PqS8rU1Cpcf5qu5kxe7vJ+n2jrj8EWK4oVviyu/X3yO7lBXnPznHtp/sfLuzclVw/DiK33RXXvRHuKZPb7goj5Htsr46yu/lmF40YP0nAcq8RAN3MPBeRNcu59z0EYHTntYGwNeUGYVXkiy0iC0Jsskk/EEmWnQEt1IGmvQbROP5tEiUNbkMiNTOXmWB+NjHW1ds6kqNnXNsqlpnKWhTx1ZcSWz4P3gebv67H3BrfIv+XR9FQplz4MsAh2k87LbLjpu9UtdrZc8++fLszf02bTVc69vyAN8Kf7oI4UvPtcLLsw/f5M+yTTYSbwgnPA9U/HQbHze6a72cjzvIp8bA10Jv7ae+VaG8nJP1PN3SIXmLj0MHY+Vdf2oex+5HrWC1J6kZNjOu36YTQ5hLCdQIsgRzFROmRfMRmNm8yl5WZBNRwG5JDytswEyntgHPDjjIvdeiFKccZwuLqjqmvPVEuMD7UztDQZHDZ1RcJkOT5GLHmBMkSWajfCEe2r/xSCOr22kAM+JFi6trDAsJ7313P3j7y/2koeq88Vb9p0KSdK//Evs/ZwL+1KbvShyuvxS+iRXt37R9flL715+pz/Oi8/X/XNrDLYykF9rNXSejL/8myvr64oqcIN/O1xfwI2vJlaltMqtEDhnWLewxrMQlqzK0NUqFoEJ9QTRD/DyzmONjWmqUIy21rPabGiMoRZEgkqJsQLjJSZ0CQWX0Q0e0OHnGvy8bHz1tYoUfrvkS5mBrWxlK7+mPA+A0r13abv+7SFZnfR0uftCKJQI+fxEUaGU7Lm44kG01v1MDmvjFDgX2U9DDSMMugrhisx0QFoJ2LQNxjmaK1xHz88aXAGPOPO8rS7J1zpS+M2WrTHYylb+68jLRfXdu3HzwDXkY4o1ZBkkhLGebsh9ALKVSCFQVdVpdOtT57GPGSCPibBz2QT6ay+gtWEyor2Ugv2bk61R2MpWtrIVrkQMVxMogmeMABBbeYbl6MvEcymaEL4nsfGA9IFNSVpH4vyycc8+aRyMQtg+1BoQAuPTGbrqx9/MDYiyNQpb2cpWvvby/PT4F6fMPaGmkNJH1l2GbiRWnMt4Qj+AtsYhOPQ1CtlxGPsuNdQZGu/xL3FdL/8JnpWtUdjKVrbytZarFCapX2EoX0SsmGgqnn29jyKuYPw6Q3C5GEwXLyTMYQfG8HTX1ZkeEX7/TVZ8t0ZhK1vZytdansdN5Z/5Y7h9/GOo5a+g84KuFrExto8e/JWd/OCvoWHot7gMRu/g8y9rBX6NzNLWKGxlK1vZynNlWBq+hEN6jk6OtBX4SN1yuXXs6lFEfN0OtPZgYGi33+Uo4vM1/N9UtLA1ClvZyla+1vJcIsVLufvnpYvC/7oIYxgxiOep72FV4XJhGuh4kC7tJ/qxtpcK3925rhbDX2wWvozB2BqFrWxlK197uUq02Hvmv57//bzmzvRbwYBKQ/SDqYS83Hj2vCaJq7w2/wVkaxS2spWtbIVnu5qv/PFcT/z5Y34v73kVNGrx9LTzIQpw+K4Y8cJ24mf42qKZScd5ngg6MryXbUDeGoWtbGUrX3t5PrroWTDp1W0viXg2LZRSScN9L9sbH7cZbPWyQYB49hqfu8kXXfcV2RqFrWxlK1v5m5DnKd2r3rm4Ego8O6P2b/ySvmyiaWsUtrKVrWxlIN4/P/FzdUris/IcBd8Vni/TXPR7xHrCs1hUYiX78sn9lW1StOBfxKP85WVLiLeVrWxlK39b8l82MPhCeRl1v40UtrKVrWzlBXK1A/nrIPKLN9nKVrayla1cpan4teS3wLJsjcJWtrKVrWylk236aCtb2cpWvoR8XrTw6wYCXzYC+cLz/DVCmm2ksJWtbGUrW+lkGylsZStb2coL5G+rBPA3fp6/xgG3kcJWtrKVrWylk61R2MpWtrKVrXSyNQpb2cpWtrKVTrY1ha1sZStbea78bbI4/OY0MGyNwla2spWtvFD+NgzDS7LW/S3ZjW36aCtb2cpWttLJS0cKL8vFvZWtbGUrW/ntlW2ksJWtbGUrW+lkaxS2spWtbGUrnWyNwla2spWtbKWTrVHYyla2spWtdLI1ClvZyla2spVOtkZhK1vZyla20snWKGxlK1vZylY62RqFrWxlK1vZSidbo7CVrWxlK1vp5P8P09MEbjPZwe8AAAAASUVORK5CYII=", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import random\n", "\n", "test_image_path_list = list(Path(fr'{data_path}\\train').glob(\"*/*.jpg\"))\n", "\n", "for image_path in random.sample(population = test_image_path_list, k = 3):\n", " plot_img_preds(model = model, image_path = image_path, class_names = classes, transform = transforms)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "69424d4c415048f68e41e193f343039a", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/265 [00:00\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
pathtrue_classpred_classpred_probcorrect
0E:\\Data_and_Models\\Kaggle_Cards\\test\\ace of cl...ace of clubsace of spades0.926314False
253E:\\Data_and_Models\\Kaggle_Cards\\test\\two of di...two of diamondsfour of diamonds0.836523False
76E:\\Data_and_Models\\Kaggle_Cards\\test\\four of s...four of spadesace of spades0.804189False
217E:\\Data_and_Models\\Kaggle_Cards\\test\\ten of he...ten of heartsnine of hearts0.804065False
56E:\\Data_and_Models\\Kaggle_Cards\\test\\five of s...five of spadesnine of spades0.792117False
..................
1E:\\Data_and_Models\\Kaggle_Cards\\test\\ace of cl...ace of clubsace of clubs0.223088True
149E:\\Data_and_Models\\Kaggle_Cards\\test\\queen of ...queen of clubsqueen of clubs0.214851True
143E:\\Data_and_Models\\Kaggle_Cards\\test\\nine of s...nine of spadesnine of spades0.201521True
69E:\\Data_and_Models\\Kaggle_Cards\\test\\four of d...four of diamondsfour of diamonds0.113845True
22E:\\Data_and_Models\\Kaggle_Cards\\test\\eight of ...eight of clubseight of clubs0.102740True
\n", "

265 rows × 5 columns

\n", "" ], "text/plain": [ " path true_class \\\n", "0 E:\\Data_and_Models\\Kaggle_Cards\\test\\ace of cl... ace of clubs \n", "253 E:\\Data_and_Models\\Kaggle_Cards\\test\\two of di... two of diamonds \n", "76 E:\\Data_and_Models\\Kaggle_Cards\\test\\four of s... four of spades \n", "217 E:\\Data_and_Models\\Kaggle_Cards\\test\\ten of he... ten of hearts \n", "56 E:\\Data_and_Models\\Kaggle_Cards\\test\\five of s... five of spades \n", ".. ... ... \n", "1 E:\\Data_and_Models\\Kaggle_Cards\\test\\ace of cl... ace of clubs \n", "149 E:\\Data_and_Models\\Kaggle_Cards\\test\\queen of ... queen of clubs \n", "143 E:\\Data_and_Models\\Kaggle_Cards\\test\\nine of s... nine of spades \n", "69 E:\\Data_and_Models\\Kaggle_Cards\\test\\four of d... four of diamonds \n", "22 E:\\Data_and_Models\\Kaggle_Cards\\test\\eight of ... eight of clubs \n", "\n", " pred_class pred_prob correct \n", "0 ace of spades 0.926314 False \n", "253 four of diamonds 0.836523 False \n", "76 ace of spades 0.804189 False \n", "217 nine of hearts 0.804065 False \n", "56 nine of spades 0.792117 False \n", ".. ... ... ... \n", "1 ace of clubs 0.223088 True \n", "149 queen of clubs 0.214851 True \n", "143 nine of spades 0.201521 True \n", "69 four of diamonds 0.113845 True \n", "22 eight of clubs 0.102740 True \n", "\n", "[265 rows x 5 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "image_paths = list(Path(fr'{data_path}\\test').glob('*/*.jpg')) \n", "\n", "image_df = record_image_preds(image_paths = image_paths, model = model, transform = transforms, class_names = classes)\n", "image_df" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.VConcatChart(...)" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "image_pred_grid(image_df.iloc[:5,:].copy(), ncols = 4, img_width = 200, img_height = 200, allow_1_col_reduction = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Add initial EDA\n", "* Try different hyperparams\n", "* Replace all plotting with Altair\n", "* Try Lightning\n", "* Use LightGBM instead of the classifier layers\n", "* Visualise wrong outputs" ] } ], "metadata": { "kernelspec": { "display_name": "ML11", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.7" } }, "nbformat": 4, "nbformat_minor": 2 }