diff --git "a/upside_down.ipynb" "b/upside_down.ipynb"
deleted file mode 100644--- "a/upside_down.ipynb"
+++ /dev/null
@@ -1,584 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "ecbad93e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>.container { width:70% !important; }</style>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from IPython.core.display import display, HTML\n",
-    "display(HTML(\"<style>.container { width:70% !important; }</style>\"))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "4dcdbbd1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import random\n",
-    "import numpy as np\n",
-    "\n",
-    "import matplotlib\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "41ab7c5a",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2022-04-07 17:01:47.622995: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.1\n"
-     ]
-    }
-   ],
-   "source": [
-    "import tensorflow as tf\n",
-    "from tensorflow.keras.datasets import cifar10\n",
-    "from tensorflow.keras.models import Sequential\n",
-    "from tensorflow.keras import regularizers, optimizers\n",
-    "from tensorflow.keras.layers import Conv2D, MaxPooling2D, BatchNormalization\n",
-    "from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten, InputLayer\n",
-    "from tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping, ModelCheckpoint\n",
-    "\n",
-    "from sklearn.model_selection import train_test_split"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "d5483db1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def rot_dataset(dataset, seed=0):\n",
-    "    \"\"\"\n",
-    "    creats a new dataset where some randomly chosen images are filpped upside down\n",
-    "    \"\"\"\n",
-    "    (X_train, _), (X_test, _) = dataset\n",
-    "    train = np.concatenate((X_train, X_test))    \n",
-    "    random.seed(seed)\n",
-    "    size = train.shape[0]\n",
-    "    rsample = (random.sample(range(size), size//2))\n",
-    "    label = np.zeros(size)\n",
-    "    \n",
-    "    for rnum in rsample:\n",
-    "        train[rnum] = np.rot90(np.rot90(train[rnum]))\n",
-    "        label[rnum] = 1\n",
-    "    \n",
-    "    return train, label"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "4252e56f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X, y = rot_dataset(cifar10.load_data(), seed=2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "45b82858",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "x_train, x_test, y_train, y_test = train_test_split(X, y, test_size=0.10, random_state=0)\n",
-    "\n",
-    "x_train = x_train.astype('float32')\n",
-    "x_test = x_test.astype('float32')\n",
-    "x_train /= 255\n",
-    "x_test /= 255"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "80f62322",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "class ConvBlock(tf.keras.Model):\n",
-    "    def __init__(self, dr, num_filters=16):\n",
-    "        super().__init__()\n",
-    "        self.conv1 = Conv2D(num_filters, (3, 3), padding='same', kernel_initializer='he_uniform',\n",
-    "                            kernel_regularizer=regularizers.l2(1e-4))\n",
-    "        self.bn1   = BatchNormalization()\n",
-    "        self.conv2 = Conv2D(num_filters, (3, 3), padding='same', kernel_initializer='he_uniform',\n",
-    "                            kernel_regularizer=regularizers.l2(1e-4),)\n",
-    "        self.bn2   = BatchNormalization()\n",
-    "        self.pool  = MaxPooling2D()\n",
-    "        self.dr    = Dropout(dr)\n",
-    "\n",
-    "    def call(self, inputs):\n",
-    "        x = tf.keras.activations.relu(self.bn1(self.conv1(inputs)))\n",
-    "        x = tf.keras.activations.relu(self.bn2(self.conv2(x)))\n",
-    "        return self.dr(self.pool(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "d282a04d",
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Model: \"sequential_1\"\n",
-      "_________________________________________________________________\n",
-      "Layer (type)                 Output Shape              Param #   \n",
-      "=================================================================\n",
-      "conv2d_9 (Conv2D)            (None, 32, 32, 16)        448       \n",
-      "_________________________________________________________________\n",
-      "batch_normalization_10 (Batc (None, 32, 32, 16)        64        \n",
-      "_________________________________________________________________\n",
-      "activation_1 (Activation)    (None, 32, 32, 16)        0         \n",
-      "_________________________________________________________________\n",
-      "conv_block_4 (ConvBlock)     (None, 16, 16, 16)        4768      \n",
-      "_________________________________________________________________\n",
-      "conv_block_5 (ConvBlock)     (None, 8, 8, 32)          14144     \n",
-      "_________________________________________________________________\n",
-      "conv_block_6 (ConvBlock)     (None, 4, 4, 64)          55936     \n",
-      "_________________________________________________________________\n",
-      "conv_block_7 (ConvBlock)     (None, 2, 2, 128)         222464    \n",
-      "_________________________________________________________________\n",
-      "flatten_1 (Flatten)          (None, 512)               0         \n",
-      "_________________________________________________________________\n",
-      "dense_2 (Dense)              (None, 64)                32832     \n",
-      "_________________________________________________________________\n",
-      "batch_normalization_19 (Batc (None, 64)                256       \n",
-      "_________________________________________________________________\n",
-      "dense_3 (Dense)              (None, 1)                 65        \n",
-      "=================================================================\n",
-      "Total params: 330,977\n",
-      "Trainable params: 329,857\n",
-      "Non-trainable params: 1,120\n",
-      "_________________________________________________________________\n"
-     ]
-    }
-   ],
-   "source": [
-    "model = Sequential([\n",
-    "    InputLayer(input_shape=(32, 32, 3)),\n",
-    "    Conv2D(16, (3, 3), padding='same'),\n",
-    "    BatchNormalization(),\n",
-    "    Activation('relu'),\n",
-    "    ConvBlock(num_filters=16, dr=0.2),\n",
-    "    ConvBlock(num_filters=32, dr=0.3),\n",
-    "    ConvBlock(num_filters=64, dr=0.4),\n",
-    "    ConvBlock(num_filters=128, dr=0.5),\n",
-    "    Flatten(),\n",
-    "    Dense(64),\n",
-    "    BatchNormalization(),\n",
-    "    Dense(1)])\n",
-    "model.summary()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "92f8bcaa",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "rlr = ReduceLROnPlateau(monitor='val_loss', factor=0.5, min_lr=1e-7, verbose = 1, patience=5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "61bf2320",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2022-04-07 17:02:31.286126: W tensorflow/core/framework/cpu_allocator_impl.cc:80] Allocation of 663552000 exceeds 10% of free system memory.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch 1/75\n",
-      "900/900 [==============================] - 12s 11ms/step - loss: 0.7201 - accuracy: 0.6386 - val_loss: 0.5794 - val_accuracy: 0.7038\n",
-      "Epoch 2/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.5827 - accuracy: 0.7278 - val_loss: 0.5684 - val_accuracy: 0.7212\n",
-      "Epoch 3/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.5314 - accuracy: 0.7534 - val_loss: 0.4859 - val_accuracy: 0.7485\n",
-      "Epoch 4/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4952 - accuracy: 0.7694 - val_loss: 0.4914 - val_accuracy: 0.7550\n",
-      "Epoch 5/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4632 - accuracy: 0.7895 - val_loss: 0.4530 - val_accuracy: 0.8190\n",
-      "Epoch 6/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4425 - accuracy: 0.8002 - val_loss: 0.4586 - val_accuracy: 0.7978\n",
-      "Epoch 7/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4260 - accuracy: 0.8124 - val_loss: 0.4095 - val_accuracy: 0.8152\n",
-      "Epoch 8/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4150 - accuracy: 0.8179 - val_loss: 0.4177 - val_accuracy: 0.8173\n",
-      "Epoch 9/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.4012 - accuracy: 0.8266 - val_loss: 0.4256 - val_accuracy: 0.8295\n",
-      "Epoch 10/75\n",
-      "900/900 [==============================] - 9s 11ms/step - loss: 0.4003 - accuracy: 0.8262 - val_loss: 0.4128 - val_accuracy: 0.8350\n",
-      "Epoch 11/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.3882 - accuracy: 0.8371 - val_loss: 0.3916 - val_accuracy: 0.8233\n",
-      "Epoch 12/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3750 - accuracy: 0.8448 - val_loss: 0.4057 - val_accuracy: 0.8193\n",
-      "Epoch 13/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3744 - accuracy: 0.8452 - val_loss: 0.3588 - val_accuracy: 0.8483\n",
-      "Epoch 14/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3691 - accuracy: 0.8460 - val_loss: 0.3667 - val_accuracy: 0.8485\n",
-      "Epoch 15/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3617 - accuracy: 0.8505 - val_loss: 0.3909 - val_accuracy: 0.8490\n",
-      "Epoch 16/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3566 - accuracy: 0.8559 - val_loss: 0.3555 - val_accuracy: 0.8352\n",
-      "Epoch 17/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3465 - accuracy: 0.8621 - val_loss: 0.3707 - val_accuracy: 0.8625\n",
-      "Epoch 18/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3468 - accuracy: 0.8635 - val_loss: 0.3676 - val_accuracy: 0.8440\n",
-      "Epoch 19/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3386 - accuracy: 0.8674 - val_loss: 0.3507 - val_accuracy: 0.8692\n",
-      "Epoch 20/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3389 - accuracy: 0.8661 - val_loss: 0.3685 - val_accuracy: 0.8437\n",
-      "Epoch 21/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3410 - accuracy: 0.8638 - val_loss: 0.3232 - val_accuracy: 0.8723\n",
-      "Epoch 22/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3362 - accuracy: 0.8711 - val_loss: 0.4032 - val_accuracy: 0.8580\n",
-      "Epoch 23/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3293 - accuracy: 0.8719 - val_loss: 0.3253 - val_accuracy: 0.8872\n",
-      "Epoch 24/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3244 - accuracy: 0.8772 - val_loss: 0.3471 - val_accuracy: 0.8487\n",
-      "Epoch 25/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3204 - accuracy: 0.8740 - val_loss: 0.3744 - val_accuracy: 0.8580\n",
-      "Epoch 26/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.3200 - accuracy: 0.8783 - val_loss: 0.3349 - val_accuracy: 0.8760\n",
-      "\n",
-      "Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257.\n",
-      "Epoch 27/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2986 - accuracy: 0.8876 - val_loss: 0.3046 - val_accuracy: 0.8935\n",
-      "Epoch 28/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2890 - accuracy: 0.8921 - val_loss: 0.3049 - val_accuracy: 0.8837\n",
-      "Epoch 29/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2839 - accuracy: 0.8942 - val_loss: 0.3107 - val_accuracy: 0.8910\n",
-      "Epoch 30/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2794 - accuracy: 0.8966 - val_loss: 0.2916 - val_accuracy: 0.8912\n",
-      "Epoch 31/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2780 - accuracy: 0.8986 - val_loss: 0.2982 - val_accuracy: 0.8838\n",
-      "Epoch 32/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2752 - accuracy: 0.8979 - val_loss: 0.2953 - val_accuracy: 0.8848\n",
-      "Epoch 33/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2721 - accuracy: 0.9002 - val_loss: 0.3392 - val_accuracy: 0.8798\n",
-      "Epoch 34/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2668 - accuracy: 0.9017 - val_loss: 0.2969 - val_accuracy: 0.8935\n",
-      "Epoch 35/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2631 - accuracy: 0.9035 - val_loss: 0.3140 - val_accuracy: 0.8897\n",
-      "\n",
-      "Epoch 00035: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628.\n",
-      "Epoch 36/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2599 - accuracy: 0.9064 - val_loss: 0.2850 - val_accuracy: 0.8898\n",
-      "Epoch 37/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2502 - accuracy: 0.9112 - val_loss: 0.2803 - val_accuracy: 0.8948\n",
-      "Epoch 38/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2443 - accuracy: 0.9136 - val_loss: 0.2810 - val_accuracy: 0.8973\n",
-      "Epoch 39/75\n",
-      "900/900 [==============================] - 9s 10ms/step - loss: 0.2398 - accuracy: 0.9144 - val_loss: 0.2828 - val_accuracy: 0.8880\n",
-      "Epoch 40/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2393 - accuracy: 0.9144 - val_loss: 0.2792 - val_accuracy: 0.8968\n",
-      "Epoch 41/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2335 - accuracy: 0.9191 - val_loss: 0.2849 - val_accuracy: 0.8958\n",
-      "Epoch 42/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2354 - accuracy: 0.9175 - val_loss: 0.2837 - val_accuracy: 0.8987\n",
-      "Epoch 43/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2312 - accuracy: 0.9192 - val_loss: 0.2827 - val_accuracy: 0.9013\n",
-      "Epoch 44/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2329 - accuracy: 0.9166 - val_loss: 0.2870 - val_accuracy: 0.8975\n",
-      "Epoch 45/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2344 - accuracy: 0.9149 - val_loss: 0.2920 - val_accuracy: 0.8898\n",
-      "\n",
-      "Epoch 00045: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814.\n",
-      "Epoch 46/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2252 - accuracy: 0.9203 - val_loss: 0.2784 - val_accuracy: 0.8968\n",
-      "Epoch 47/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2193 - accuracy: 0.9243 - val_loss: 0.2787 - val_accuracy: 0.8995\n",
-      "Epoch 48/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2155 - accuracy: 0.9247 - val_loss: 0.2808 - val_accuracy: 0.9013\n",
-      "Epoch 49/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2171 - accuracy: 0.9241 - val_loss: 0.2791 - val_accuracy: 0.9008\n",
-      "Epoch 50/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2147 - accuracy: 0.9251 - val_loss: 0.2797 - val_accuracy: 0.8935\n",
-      "Epoch 51/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2116 - accuracy: 0.9259 - val_loss: 0.2808 - val_accuracy: 0.8995\n",
-      "\n",
-      "Epoch 00051: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05.\n",
-      "Epoch 52/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2084 - accuracy: 0.9281 - val_loss: 0.2759 - val_accuracy: 0.9030\n",
-      "Epoch 53/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2030 - accuracy: 0.9308 - val_loss: 0.2768 - val_accuracy: 0.9003\n",
-      "Epoch 54/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2055 - accuracy: 0.9318 - val_loss: 0.2776 - val_accuracy: 0.9033\n",
-      "Epoch 55/75\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2056 - accuracy: 0.9292 - val_loss: 0.2760 - val_accuracy: 0.9010\n",
-      "Epoch 56/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2000 - accuracy: 0.9322 - val_loss: 0.2773 - val_accuracy: 0.9010\n",
-      "Epoch 57/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2026 - accuracy: 0.9303 - val_loss: 0.2796 - val_accuracy: 0.9022\n",
-      "\n",
-      "Epoch 00057: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05.\n",
-      "Epoch 58/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2038 - accuracy: 0.9308 - val_loss: 0.2761 - val_accuracy: 0.9007\n",
-      "Epoch 59/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1991 - accuracy: 0.9319 - val_loss: 0.2773 - val_accuracy: 0.9025\n",
-      "Epoch 60/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1979 - accuracy: 0.9341 - val_loss: 0.2777 - val_accuracy: 0.9007\n",
-      "Epoch 61/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2016 - accuracy: 0.9306 - val_loss: 0.2769 - val_accuracy: 0.9043\n",
-      "Epoch 62/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1989 - accuracy: 0.9335 - val_loss: 0.2776 - val_accuracy: 0.9018\n",
-      "\n",
-      "Epoch 00062: ReduceLROnPlateau reducing learning rate to 1.5625000742147677e-05.\n",
-      "Epoch 63/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1929 - accuracy: 0.9340 - val_loss: 0.2780 - val_accuracy: 0.9042\n",
-      "Epoch 64/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1916 - accuracy: 0.9342 - val_loss: 0.2782 - val_accuracy: 0.9020\n",
-      "Epoch 65/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1920 - accuracy: 0.9331 - val_loss: 0.2779 - val_accuracy: 0.9043\n",
-      "Epoch 66/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1937 - accuracy: 0.9353 - val_loss: 0.2782 - val_accuracy: 0.9017\n",
-      "Epoch 67/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1932 - accuracy: 0.9348 - val_loss: 0.2775 - val_accuracy: 0.9030\n",
-      "\n",
-      "Epoch 00067: ReduceLROnPlateau reducing learning rate to 7.812500371073838e-06.\n",
-      "Epoch 68/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.2003 - accuracy: 0.9303 - val_loss: 0.2765 - val_accuracy: 0.9037\n",
-      "Epoch 69/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1894 - accuracy: 0.9365 - val_loss: 0.2779 - val_accuracy: 0.9043\n",
-      "Epoch 70/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1918 - accuracy: 0.9341 - val_loss: 0.2780 - val_accuracy: 0.9023\n",
-      "Epoch 71/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1948 - accuracy: 0.9340 - val_loss: 0.2782 - val_accuracy: 0.9027\n",
-      "Epoch 72/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1934 - accuracy: 0.9356 - val_loss: 0.2776 - val_accuracy: 0.9043\n",
-      "\n",
-      "Epoch 00072: ReduceLROnPlateau reducing learning rate to 3.906250185536919e-06.\n",
-      "Epoch 73/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1925 - accuracy: 0.9358 - val_loss: 0.2772 - val_accuracy: 0.9040\n",
-      "Epoch 74/75\n",
-      "900/900 [==============================] - 10s 12ms/step - loss: 0.1982 - accuracy: 0.9332 - val_loss: 0.2766 - val_accuracy: 0.9047\n",
-      "Epoch 75/75\n",
-      "900/900 [==============================] - 10s 11ms/step - loss: 0.1963 - accuracy: 0.9320 - val_loss: 0.2771 - val_accuracy: 0.9052\n"
-     ]
-    }
-   ],
-   "source": [
-    "# initiate RMSprop optimizer\n",
-    "opt = optimizers.Nadam(learning_rate=0.001, decay=1e-6)\n",
-    "\n",
-    "# Let's train the model using RMSprop\n",
-    "model.compile(loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
-    "              optimizer =opt,\n",
-    "              metrics = ['accuracy'])\n",
-    "\n",
-    "history = model.fit(x_train, y_train, epochs=75, batch_size=60, validation_data=(x_test, y_test), callbacks = [rlr])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "9a7fc0e3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA34AAAFNCAYAAABfWL0+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAACDMklEQVR4nOzdZ3jcxdX38e/sqnery5bce2+4U2x6qKGXhNBC4CZAOsmTSpL7DgmBBEIIIYQaegu9N2NswL33KlmW1azetfO8mJUt25It21qtyu9zXXvt7r+elcvo7MycMdZaREREREREpPvyBDsAERERERERCSwlfiIiIiIiIt2cEj8REREREZFuTomfiIiIiIhIN6fET0REREREpJtT4iciIiIiItLNKfETCSBjTH9jjDXGhLTh2KuNMfM6Ii4REZGuSO2qyNFT4ifiZ4zZZoypM8YkH7B9mb+R6R+k0JrHEm2MqTDGvBXsWERERA6lM7erR5JAinQXSvxE9rcVuLzpjTFmDBAZvHAOchFQC5xmjMnoyBurcRQRkaPQ2dtVkR5DiZ/I/p4Ermr2/lvAE80PMMbEG2OeMMYUGGO2G2N+YYzx+Pd5jTF/NsYUGmO2AGe1cO6/jTG7jDE7jTG/N8Z4jyC+bwEPAiuAKw+49ixjzHxjTIkxJtsYc7V/e6Qx5m5/rKXGmHn+bScZY3IOuMY2Y8wp/te/Mca8aIz5jzGmDLjaGDPFGLPAf49dxpj7jTFhzc4fZYx53xhTbIzZbYz5f8aYdGNMlTEmqdlxk/w/v9Aj+OwiItL1dPZ29SDGmN7GmNf8bdkmY8y3m+2bYoxZZIwp87dz9/i3R/jbyyJ/G7nQGJN2LHGItDclfiL7+wKIM8aM8DcclwL/OeCYvwHxwEDgRFyDdo1/37eBs4EJwGRcD11zjwMNwGD/MacB17clMGNMX+Ak4Cn/46oD9r3tjy0FGA8s8+/+MzAJmAEkAj8BfG25J3Ae8CKQ4L9nI/B9IBmYDpwM/I8/hljgA+AdoLf/M35orc0DPgEuaXbdbwDPWmvr2xiHiIh0TZ22XT2EZ4AcXFt2EfB/xpiT/fvuBe611sYBg4Dn/du/5f8MWUAScCNQfYxxiLQrJX4iB2v6dvJUYB2ws2lHs0brZ9bacmvtNuBu4Jv+Qy4B/mqtzbbWFgN/aHZuGnAm8D1rbaW1Nh/4C3BZG+O6ClhhrV2Da5RGGWMm+PddCXxgrX3GWltvrS2y1i7zf2N6LXCbtXantbbRWjvfWlvbxnsusNb+11rrs9ZWW2sXW2u/sNY2+D/7P3GNNLiGOc9ae7e1tsb/8/nSv+9xXLLX9DO8HPdzFhGR7q+ztqsHMcZkAbOA2/1t2TLg4Wbx1AODjTHJ1toKa+0XzbYnAYP9be1ia23Z0cYhEgiasyNysCeBucAADhiOguvpCgO2N9u2Hejjf90byD5gX5N+QCiwyxjTtM1zwPGHchXwLwBrba4x5lPcN4xLcd8wbm7hnGQgopV9bbFfbMaYocA9uG9do3D/hyz2724tBoBXgQeNMQOBoUCptfaro4xJRES6ls7arrakN1BsrS0/4J6T/a+vA34LrDPGbAXusNa+gfuMWcCzxpgEXK/mzzWyRToT9fiJHMBaux03Gf1rwMsH7C7EfavXr9m2vuz79nIX7j/+5vuaZOMKsyRbaxP8jzhr7ajDxWSMmQEMAX5mjMkzxuQBU4HL/UVXsnFDTg5UCNS0sq8Sl7w13cOLGybanD3g/T9w39YO8Q9z+X9AU2vbWgxYa2tww2GuxH1rqt4+EZEeojO2q4eQCyT6py8cFI+1dqO19nIgFfgj8KIxJto/2uYOa+1I3NSKs9l/bqNI0CnxE2nZdcAca21l843W2kZcAvO/xphYY0w/4Afsm6/wPHCrMSbTGNML+Gmzc3cB7wF3G2PijDEeY8wgY8yJHN63gPeBkbj5e+OB0bjE7Uzc/LtTjDGXGGNCjDFJxpjx1lof8Ahwj3+yutcYM90YEw5sACKMMWf5i6z8Agg/TByxQBlQYYwZDtzUbN8bQLox5nvGmHD/z2dqs/1PAFcD53Lw/A4REeneOlu72iTcX5glwhgTgUvw5gN/8G8b64/9KQBjzDeMMSn+9rXEf41GY8xsY8wY/5eoZbhktvEI4hAJOCV+Ii2w1m621i5qZfctuN6yLcA84GlccgVuKOa7wHJgCQd/s3kVbkjLGmAPrnDKIZdl8DdElwB/s9bmNXtsxfWcfctauwP3TeoPgWJcYZdx/kv8CFgJLPTv+yPgsdaW4gqzPIxr6Cpxk9kP5UfAFUC5/7M+17TDPyzmVOAcIA/YCMxutv9zXFGZJf45HCIi0kN0pnb1ABW4IixNjzm4eej9cb1/rwC/tta+7z/+DGC1MaYCV+jlMv+olnT/vcuAtcCn6EtO6WSMtQeO5BIRCQxjzEfA09bah4Mdi4iIiEhPosRPRDqEMeY43HDVrAMmzYuIiIhIgGmop4gEnDHmcdwaf99T0iciIiLS8dTjJyIiIiIi0s2px09ERERERKSbU+InIiIiIiLSzYUEO4D2lJycbPv37x/sMEREJMAWL15caK1NCXYcXYXaRxGRnqO1NrJbJX79+/dn0aLWlogREZHuwhizPdgxdCVqH0VEeo7W2kgN9RQREREREenmlPiJiIiIiIh0c0r8REREREREurluNcevJfX19eTk5FBTUxPsUDq9iIgIMjMzCQ0NDXYoIiISYGof207to4h0B90+8cvJySE2Npb+/ftjjAl2OJ2WtZaioiJycnIYMGBAsMMREZEAU/vYNmofRaS76PZDPWtqakhKSlKjdhjGGJKSkvTNr4hID6H2sW3UPopId9HtEz9AjVob6eckItKz6P/9ttHPSUS6gx6R+AVTSUkJDzzwwBGf97WvfY2SkpL2D0hERKQTUPsoItKxlPgFWGsNW2Nj4yHPe+utt0hISAhQVCIiIsGl9lFEpGN1++IuwfbTn/6UzZs3M378eEJDQ4mJiSEjI4Nly5axZs0azj//fLKzs6mpqeG2227jhhtuAKB///4sWrSIiooKzjzzTGbNmsX8+fPp06cPr776KpGRkUH+ZCLSGVTVNbApv4LNBRWEeb0kxYSRHBNGUnQ48ZGheDyHHqK2uaCCxKgwekWHHVMc1lpqG3w0+iw+a/FZwILxQESIl1Cv0XC5Lqy2oZGKmgYSosLwHubvVFupfRQR6VhK/ALszjvvZNWqVSxbtoxPPvmEs846i1WrVu2tDPbII4+QmJhIdXU1xx13HBdeeCFJSUn7XWPjxo0888wz/Otf/+KSSy7hpZde4hvf+EYwPo6IBFBtQyNvrtjFrtIayqrrKatpoKymnuq6RkK9hjB/AhUe4qGooo71u8vZUVyFtS1fLzYihBtPHMS1MwcQGebdb9/Okmr+9801vLUyD2NgTJ94Zg1O5vghKUzom4DPWiprG6mqa6CytpGymnqKK+soqqxjT2UdxZV1FJTXkl9eQ355LflltVTXt95T4zEQHuIlItTDzbMHc/3xA9vzRycBVlPXyM6SaqLCQg76u3S01D6KiHSsHpX43fH6atbklrXrNUf2juPX54xq8/FTpkzZrxz0fffdxyuvvAJAdnY2GzduPKhhGzBgAOPHjwdg0qRJbNu27ZjjFpHAqKlvZHdZDUWVdQxKjiE+6vDrfllreXtVHne+vY4dxVUAhIV4iIsIJS4yhMhQLw2NlrpGH3UNPmobfMRFhjCqdxwXTMhkWHosg1NjaPD5KKpwyVlRRS2fbyrirnfX8/j8bXz/1KFcPCmTRmt5+LOt3P/RJiyWW08egtcYPttYwD/nbuGBTza36XPGRoSQEhtOamw4YzMTSI0NJzE6jFCvwePv2fMYg89aauobqan3UVPfSG2Dj0EpMUf/A5aAOFz76LOW6rpGIkK9be7xU/soItK59KjErzOIjo7e+/qTTz7hgw8+YMGCBURFRXHSSSe1WC46PDx872uv10t1dXWHxCoih+bzWRZsKeKlxTmszi1jd3kNJVX1e/cbA8PSYpkyIJHj+icyPiuBpJgwIkO9e4c9Lssu4fdvrGHR9j0MS4vlsWuOY9rAJCJCj71X5ZqZA1i4rZg7317Hz15eycOfbaHRZ9lWVMUZo9L5xdkjyOwVBcBtpwyhvKaeL7YUsya3jPBQD9FhXqLCQogK8xIXGUpidBiJ0WH0igojLERTxHuSplTPYpu9a19qH0VEAqtHJX5H8s1je4mNjaW8vLzFfaWlpfTq1YuoqCjWrVvHF1980cHRifQMq3aW8tSX2xmREcfXxmSQHBN+0DHFlXXM3VBATX0jfZOi6JcUTXpcRIu9G9nFVbywOIeXFuews6Sa2IgQpg5I5LgBvUiPiyA1LoJeUWGs21XGV9uKeXFxDk8s2L73/FCvIT4yjLiIELYUVpIcE8YfLhjDxZMyCfG2b0J1XP9EXrxxOu+t2c09720g1AtPXDuFE4amHHRsbEQop45M49SRae0ag3R+h2sffdayamcpaXERpMVFtMs91T6KiHSsHpX4BUNSUhIzZ85k9OjRREZGkpa27xeqM844gwcffJCxY8cybNgwpk2bFsRIRbqfwopa/vzuep5blE2o10NdQzZ3vL6GGYOSOHdcb0ZkxDF3YwEfrc1nyY49riBJM2FeDxkJ7pfcpmGKTcMWjYFZg5P5yRnDOH1Ueos9dE0JVEOjj9W5ZazdVUZJdT0lVfWUVtdTWl3HOeN68+0TBhITHrj/jo0xnD4qndNHpQfsHtK9eYwhxOOhvtHXbtdU+ygi0rGMba0qQBc0efJku2jRov22rV27lhEjRgQpoq5HPy/paqrqGli7q4zI0BBiI0KIiwglPNTDf77Yzr0fbqS6rpGrZ/TnlpOHkFdaw2vLd/La8lyyi/cNCRvTJ545w1OZMzyVxOgwdhRXsb2oih3FVewsqcZjXGXKiFAPEaFekmPC+drYDPokqHpgsBhjFltrJwc7jq6iPdrHDbvLCfN66J8cffiDuyG1jyLSVbTWRqrHT0S6rHdX5/Gb11azq/TguT8AJw5N4Zdnj2RwqismEh8Zyo/Th/Oj04axLLuEbUWVzBiUfNDQtazEKGYODnj4Il1KqLd9e/xERKRjKfETkS4nZ08Vv3ltDR+s3c3w9Fh+efZIDFDuX/6goraB8VkJnDQstcXzjTFM6NuLCX17dWzgIl1YqMdQXd99RgmJiPQ0SvxEpFOqrG1gw+5ySqrraWi0NDT6qPdZthZU8uCnbsmB//e14VwzcwCh7VwQRUQOFhLioaHKh7V2b1VaERHpOpT4iUjA7Siqwhg3hLIl1lq+2lrM3I0FrM8rZ/3u8v3m4B3olBFp3HHeKM2xE+lAof4Ktw2NltAQJX4iIl2NEj8RCZj6Rh/3fbiRv3+8CZ+F8VkJnD02g7PGZpARH0l2cRUvL9nJS0ty2FFcRYjHMDAlmnGZCVwyKYuh6bGkxIYT6vEQ4jWEeg2RYSFK+ESCoKlnvd7nIxT1souIdDVK/EQkIDblV/D955axcmcpF0zsw5DUWN5Ykcvv31zL799cy6CUaDYXVAIwc3AS3z91CKePSicqTP8tiXRGoV7Xy1ffqHl+IiJdkb6y62RiYlz1wdzcXC666KIWjznppJM4sCz3gf76179SVVXV7vGJHI61lsfnb+Os+z4jZ08V/7hyIvdcMp6bThrEm7cez0c/PJEfnjqU9PgIfnDqUObdPpunrp/G1ydkKukT6cRC/D1+DUGq7Kn2UUTk2Cjx66R69+7Niy++eNTnq2GTYGho9HHbs8v49WurmT4oiXe/dwJnjsnY75iBKTHccvIQnrp+GreePITMXi3P+xORziXEYzCYoC/poPZRROToKPELsNtvv50HHnhg7/vf/OY33HHHHZx88slMnDiRMWPG8Oqrrx503rZt2xg9ejQA1dXVXHbZZYwdO5ZLL72U6up9RS9uuukmJk+ezKhRo/j1r38NwH333Udubi6zZ89m9uzZALz33ntMnz6diRMncvHFF1NRURHIjy09UH2jj1ueWcpry3P58enDePTq40g9YH08Eem6jDGEeE27DfVU+ygi0sGstd3mMWnSJHugNWvWHLStIy1ZssSecMIJe9+PGDHCbt++3ZaWllprrS0oKLCDBg2yPp/PWmttdHS0tdbarVu32lGjRllrrb377rvtNddcY621dvny5dbr9dqFCxdaa60tKiqy1lrb0NBgTzzxRLt8+XJrrbX9+vWzBQUFe+9x/PHH24qKCmuttXfeeae94447Wow32D8v6Zpq6xvttx9faPvd/ob919zNwQ5HegBgke0E7U5XebRX+7hxd7ndnF9+xOe1RO2jiEhgtNZG9qwJNW//FPJWtu8108fAmXe2unvChAnk5+eTm5tLQUEBvXr1IiMjg+9///vMnTsXj8fDzp072b17N+np6S1eY+7cudx6660AjB07lrFjx+7d9/zzz/PQQw/R0NDArl27WLNmzX77Ab744gvWrFnDzJkzAairq2P69OnH+slFAKhtaOTmp5bwwdp8fnPOSK6eOSDYIYnIkWpj+5hZ34gPC6Ft+PVB7aOISKfSsxK/ILnooot48cUXycvL47LLLuOpp56ioKCAxYsXExoaSv/+/ampqTnkNVpaLHfr1q38+c9/ZuHChfTq1Yurr766xetYazn11FN55pln2u0zSddVVdfA3A2F7CqtpqbeR3V9IzX1jVTVNVBR00C5/1FWU4/PWnpFhblHdBiJ0aFEhHjxeAzGgMcYPttYwOebivj9+aP5xrR+wf54IhJAxoBtxyl+ah9FRDpOz0r8DvHNYyBddtllfPvb36awsJBPP/2U559/ntTUVEJDQ/n444/Zvn37Ic8/4YQTeOqpp5g9ezarVq1ixYoVAJSVlREdHU18fDy7d+/m7bff5qSTTgIgNjaW8vJykpOTmTZtGjfffDObNm1i8ODBVFVVkZOTw9ChQwP90aWTqK5r5JP1+byxchcfrc2nur5xv/0RoR4iQ73ERIQQGx5KbEQImb2i8HpgT1U9mwsq2LO9jj1V9TT69p/fE+b1cOcFY7hsSt+O/Egi0p7a2D6WltWQV1bD6N7xeDzHvoi72kcRkY7TsxK/IBk1ahTl5eX06dOHjIwMrrzySs455xwmT57M+PHjGT58+CHPv+mmm7jmmmsYO3Ys48ePZ8qUKQCMGzeOCRMmMGrUKAYOHLh3qArADTfcwJlnnklGRgYff/wxjz32GJdffjm1tbUA/P73v1fD1k1Za8krq2FlTikrd7rHV1uLqaprJCk6jAsm9uGssRmMSI8jMsxLeIinxW/MW7t2o8/is+CzFmvB44HwEG+AP5WIdAYhzRZxD/cc+797tY8iIh3HuPl/3cPkyZPtgev3rF27lhEjRgQpoq5HP6+uZVN+BWt3lbG9qJJtRVXsKKpiS2EFhRV1AHg9hiGpMUzs14uzxmQwdUDi3l/cRLoyY8xia+3kYMfRVbRX+1heU8/WwkoGpcQQHd6zvjtW+ygiXUVrbWTP+l9bpBsora7nteW5vLAomxU5pXu3p8WF0y8xmtnDUhndJ57RfeIZmeF69URE2kNoU49fkNfyExGRI6fET6SLWJZdwqOfb+WdVXnUNvgYnh7LL88eyczBSfRNjCIqTP+cRSSwQvzz+tprLT8REek4+k1RpJPbXlTJn95Zz5srdxEXEcKlx2VxyeQsRvWOa/PcPBGR9uD1GDzG0KAePxGRLqdHJH7WWv2C3Abdab5nd1BcWcd9H27kqS+3E+LxcNvJQ/j2CQOJ6WHzakQkcI60fTTGEOI1Pa7HT+2jiHQH3f43yIiICIqKikhKSlLydwjWWoqKioiIiAh2KAIszy7hG//+ksraBi49LovvnzKU1Dj92YhI+zna9jHU46He13N6/NQ+ikh30e0Tv8zMTHJycigoKAh2KJ1eREQEmZmZwQ6jx6ttaORHLywnJjyEl26awdC02GCHJCIdyBhzBnAv4AUettYetMieMeYk4K9AKFBorT3xSO9ztO1jcWUddQ0+6gp7TiKk9lFEuoNun/iFhoYyYMCAYIch0mZ//3gzG/MreOTqyUr6RHoYY4wX+DtwKpADLDTGvGatXdPsmATgAeAMa+0OY0zq0dzraNvH37+xhv98uZ21vz1DI2lERLqQbp/4iXQla3eV8cDHmzh/fG/mDE8LdjjS3qyFzvaLss8HnqNY29HXCMbT8udpqIOSHVC8BUp3QNkuKM+D8lz3esq34bjrjj327mkKsMlauwXAGPMscB6wptkxVwAvW2t3AFhr8zsywLS4CGrqfZTVNBAfGdqRtxYRkWOgxE+kk2ho9HH7SyuIjwzlV+eMCnY40p7qquDtH8Oa12HajTD9ZoiI3/+YhlpY9rR7ZE6GaTdBQt8DjqmD5c/A/PvAEwon/xKGfe3wyWRdJRRvdYlY8RbY0/R6G5TlQNY0mHI9DD8HQsJav05DLWz6AFa+CBvegcY6iEiAyF7uERIOJduhNAdsszlgxgsxaRCbDkmDIDrlSH56PU0fILvZ+xxg6gHHDAVCjTGfALHAvdbaJzomPEiLd0M888tqlPiJiHQhAU38DjdPwRjTC3gEGATUANdaa1e15VyR7uaRz7eyIqeUv10+gcToQ/zyLftYC8ufha1zYdb3IWXowcfUV8PcP8OXD0L/WXDCTyBzUvvGUboTPCEQ20IvbdFmeP4q2L0K+k6HT/8IXz0EM78HU25wSduSJ+Hzv0LZTkga4vZ/+U8YdT5M/y6kjoSlT8K8v7pErfcEl8w9ewX0Px5O+53bBi45zP4SNn8IO76E4s1QsXv/mKKSIHEg9J0GMamw7g148VqXnE38Foy9xPXo1ZRA9R732P45rH0dakrd+WMvdcle0/7qPS4xzJoK4y6HXgPcPRL6unt4vO37M+++WsriDywpGQJMAk4GIoEFxpgvrLUb9ruQMTcANwD07XvAlwjHIC02HIC8shqGaDi6iEiXEbDEry3zFID/Byyz1n7dGDPcf/zJbTxXpNvYVljJ3e9t4NSRaZw9NiPY4Tg+n+vRCQ1QAYfqEgiLBu9R9hjUlMGbP4CVL7ghhyueg8nXwEk/g+hkd8zmj+GN77seriGnuYTo4TkwaI5LAPtNP/i6Ph/kr4bt82HbPNi1HDLGwvCzYejpLtkB14u39nWXkG37zMUw+FSY8A0YeobrOVvzKvz3ZvCGwJUvwpBTIXcZfPR7+ODX8MUD7loVu11SeO7fXGxlO12iuvhxWPUShMdBbZnrmTv3Xhh0MvgaYPFj8Mkf4KGTYNTXXeK1dS7UVbhEtPdEd8+mJCxxgHsdmbD/Zz71dy5R/OpfMPcumPung38uYTHuZzDmYhh44tH/ucnh5ABZzd5nArktHFNora0EKo0xc4FxwH6Jn7X2IeAhgMmTJ7fbegRp/grDu8tq2+uSIiLSAQLZ49eWeQojgT8AWGvXGWP6G2PSgIFtOFekS9pTWce6vHLyy2vIK60hr6yGeRsLCQvx8PvzRwe/WIK1bjjfe7+Eijy46BGXjLSH2gpY819Y+h/YsQAwbthfbDrE9YZ+M2DGrYcfurhzMbx4nRtWOPvnrpdq7p9g0aOw/DmY9T0o3OCSwcRBcNVrLlmpLYeF/4YF98OjZ7ietLDo/T970UbXqwWutyp9LOQsckme8bpew/gsWPuaS8Z69XcxNNS4YZrPf9P1iGUe54ZD9pkEFz8OCf7f5XuPh2+86BLLuXe5hHHmv911mz53fCac9nuXnC55AnYtg4lXud69pmO8oW6u3NhLYN5f4It/uB67sZfC4JPdsRFxbftz8XhcgjjkVDckdOtcCI/ZfxhnbEbgvgSQ5hYCQ4wxA4CdwGW4OX3NvQrcb4wJAcJwQ0H/0lEB7kv8ajrqliIi0g4Cmfi1ZZ7CcuACYJ4xZgrQD/ftZlvOFekSauobWbRtD59tKuDzTYWszi2j+VrA0WFe0uMjuOuicXt/oQqavJUu4dvyseshikmD/1wIp9wBM245+sIkOxfDokdg1StQX+mGM570M5doNRX8KN7iEqXY3jD24pavY61L2j74jUtErnnbDVcEOOtumPIdeP9X8NHv3By4E34Cx/9wX8ISHuuSwik3uN6yzR/uPxcNYOR50G+WS0KbkjWfD3KXuiGR696E7K/cMMwJ34C+M/YVR5n9c9j8kesF3Pyxi+e037c8b67fDPjmK4f+uUXEwYzvHuaYeDjlNzDnl60XWzkSiQPcQ4LCWttgjPku8C5uqsMj1trVxpgb/fsftNauNca8A6wAfLjpEKs6KsbIMC9xESFK/EREuphAJn5tmadwJ3CvMWYZsBJYCjS08Vx3kwDNYRBpC2stO4qrWJZdwrLsElbmlFJSXU9dg4/ahkZqG3xU1DTQ4LOEeg0T+/biB6cMZULfXqTHR5AWF05sRCcYMle+Gz76LSx9yg0DPONOmHydG+r56v/A+790Qx7P/RuERbX9usVbXZK25r9uqODoC2DCNyFrysEJiq8R/n0avP0TGHgSxLRQAGTB/fDeL2DEOS6WpmGXTVKGwhXPuuGUEXEueW1JWBRM/x/3aAuPx80LzJwEp/y69eqcHu++nrOOpjl03Ya19i3grQO2PXjA+7uAuzoyrubS4iKU+ImIdDGBTPwOO0/BWlsGXANg3Pi2rf5H1OHObXaNgMxhEDmU0up67n5vPa8vz2VPVT0AEaEeRveOZ2haDOEhXsJDPISHeIiJCGFy/0Sm9E8kOryd/8lV5LvheIeqxHgojfWuiMgnd7qhitNvhhN+tC+hCglzwxTn/QU+/C0UrIfLnz642uSBqvf4C6r80w1JPOln7trhhygE4fHCeffDg8e75O/iR/ffv/lj15s38jwX06F6tnqPb9PHP2rBHo4rEmTp8RGa4yci0sUEMvE77DwF/yK0VdbaOuB6YK61tswY05Y5DiIdzlrLa8tz+d0baymurOXccb2ZMiCJ8VkJDE2LIcR7FOuhHY092111yOXPuOGG5/6t9WPXvQWrX3Zz1fpMgoxxbv7W5o/h7duhcL0rSnLmH12p/QMZA8f/wJ3/4rXw/Lfg+g9a72Fa/w688h03T27CN2DOL9wcvrZIHQEn3g4f/x7GXATDz/J/3m3w4jWQPAzOe0CJl0iQpcZGsCm/MNhhiIjIEQhY4teWeQrACOAJY0wjrnDLdYc6N1CxirTF1sJKfvnfVczbVMi4zHgeu+Y4RveJP/yJ7ak8z/WkLX7MzedKG+0Kpcy4DZIHH3x8bTm8fqurgLnyBbfNeFyP3Z5trjDJ5c+6KpSHS6aGnAJn3wMvXecKpEy94eBjynLhlRvc9c9/E9JHH/lnnPU9Vw3zjR9Av5ngDYPnvuHm4l32lEtaRSSo0uLCyS+vxeezeDz6IkZEpCsI6Dp+h5unYK1dAAxp67kiwZBfVsODn27hP19uJ9zr4XfnjeKKqf3wdvQvO1/9yxVe8dW7eXIn/NglRfeOhU/vhAsfPvic+fdDZQFc/yEk9IPcJbBzCeStcNeY/t0jq9Q4+kJXufLD38KIs10lzibWwqvfdcNHL3685d7DtvCGuiGf/5oD7/4cGmshbxVc8fzRX1NE2lV6fASNPktRZR0p/nX9RESkcwto4ifS6dRWuMqRoy7YV4mxFfllNfzj0808/eUOGnyWCyb04cenDyP1WCtvFm2G0hy3vEBbLXwY3vpRy0Myp37HLew96weQNnLf9op8mP83Nycuc7LbNvR09zhaxrjqmQ9Mc8NEL31y375Fj7gqmV/787EnaL3Hw8zbYN497v2cX8DQ047tmiJy9Hw+2DbXFV7CDfUEt6SDEj8Rka6hgyYkiXQSix9zQxXXvd7qITl7qvjNa6uZ9aePeWLBds4b35uPfngid1087tiTPoBXb4YnzoV3/h80Nhz++GVPw5s/dMMxL3v64KRqxq2uYuYnf9h/+6d/dL1lJ//62GNuLnEAnPgTt47d+rfdtuItrjdy4Gw47vr2uc+Jt0PvCW5duuN/1D7XFJGjs+RxeOI8WPUy4IZ6gtbyExHpStTjJz3L5o/c89y7YMS5+81rW5dXxj8/3cJry3Px4OOycUl8Z0YfMmOB+p1QFgtxGcd2/5IdbuHylBHwxd/dkMuLH4Po5JaPX/WySxQHnuSGT7ZUvTMq0S1L8Okf3ZILGeNcr+Lix2DS1YEZHjn9FljxArz1YzcP75WbwBMC5/29/QqvhEbAtz9WIReRzmD8la6Y1KvfhZThpMe7tR5V2VNEpOtQ4ic9R30NbP/czXXLW0nlqjfYlHA8WworeHVZLp+sLyAqzMvNx8Vx69abCFm7A9Y2O9944RsvwqA5Rx/Dqpfc8xXPwvYF8Ppt8NBJcOl/Dl6CYP3b8PK3IWuq6+k71Fy8af/jlk74+P/giufgwzvAG+56zQIhJAzO+Ss8cjo8fDIUboCvPwTxfdr3Pkr6RDqHpqVdHjoRnruS5Os+whjIU4+fiEiXocRPeo4dC6Chhj+aq7mSf1D4wq84v+53gCEpOowfnjqUb07vR8Ib34bKPDj5VxAeByEREBrphlK+dhv8z4Kjryy58kXInOKqafbqDynDXMXKR06HPpOhodolqA01rncwfawrahIWfejrRibAjFvgo9+5BHDNq3DiTyEm9ejibIu+01yP4uLH3ILqYy8J3L1EJPjiMlzy9/jZhL56I8lR15GvxE9EpMtQ4ic9x+YPaTChPJ0/gCH9v8UFO+/ixVNriB99Ov2SogkL8cCa12DNf2HOL+H4H+5/flwfePRMV9Hya3868vvnr4Xdq+DMZuf2mQg3fArv3A5luyAiHmLSXe/ekNPcXLqIuLZdf+qN8MUDbvHz6BSY8d0jj/FInfpbiM+Eydepd06kJ+g3Hc64E976Ed+P7MX7ZdcGOyIREWkjJX7SNRRthvislue4tZHd/BFLGc6UYVlccMXX4L6nmbz9YZhzoUtaqopdEZX0sa6i5IH6TYcpN8BXD8HoC1yP15FY+aJbQ2/U1/ffHpMCFz1y1J9rr/AYmPV9eO8XbohneOyxX/NwIuLdshIi0nMcdz3sXMIVy59mfeFgYEqwIxIRkTZQVU/p/KqK3fIBSx4/+muU52F2r+bDulF8bUw6hITDzO+54Z/b5rlj3v05VBe7AiXe0Javc/KvICHLFVypr277/a11C6gPPCmwwy+n3ujmA07Wt/AiEiDGwNn3kB85kCsrHqWh0RfsiEREpA2U+EnnV7AOGutcAZGjteUTABYwjpNHpLltE78J0akw90+w8QNY/rRLBjPGtn6d8Bg4514o2gSf3Nn2++csgpLtMPqio/4IbeINheFngccb2PuISM8WGklp+gz6UMDWgopgRyMiIm2goZ7S+RWsc88lO476Enbzh5QQR8rgScRF+HvzQiNh5q1uaGTeSkge5ubUHc6gOTDhG25x9L7Toa4CcpfCzsVuHt+kb8Epd+w/523lC67K5oizj/oziIh0JnGp/YjeWsuG7FyGpLdxLrKIiASNevyk8ytY756PNvHz+WjY+DGfNo7mjLEHLDcw+VqISoLqEjfEMyS8bdc87X9dAZVnLnULwn/1L/A1Qp9J8Pm9rrpmk8YGWP0KDD3dzYkTEekGkjL6A5C7Y0twAxERkTZRj590fs17/Kw98uqR+asJrS5gvr2QnzcN82wSFg0XPgyVRZB1XNuvGZkAV74AuUug9wRIHemGWVrr1ub77G7Xo3jCj2HbXKjMhzEXH1ncIiKdWEiC+yKtOG97kCMREZG2UOInnV/BesC4IZXVeyAq8YhOt5s+wgB1/U4kPqqFoi1HuyB7xtiD5wMaA2f/xRV++ej3EBrtlnAIj3PLM4iIdBdxGQDUFGcHORAREWkLJX7SuVWXQPkuyDwOcha6AilHmPhVrHmPnb4sZowfE5gYD+Txwvn/cIuwv/sz8Ia53r7QiI65v4hIR4h1iV9UTQGFFbUkx7RxqLyIiASF5vhJ59ZUybOpt+xI5/nVVRG56yvm2TGcOjLt8Me3F28IXPhvF3djnYZ5ikj3ExpJfVgC6aaYtbvKgh2NiIgchhI/6dya5vcNOdU9lxzZkCK7fT4hto7itFn0ij76xd+PSkgYXPIkXPMODJrdsfcWEekAJq436WaPEj8RkS5AiZ90bgXrISQS0se6eXJH2ONXtOIdam0o/SedEqAADyM0AvpND869RUQCLCShN5khJazdVR7sUERE5DCU+EnnVrAOkoe4eXMJfY848bObPmKhHcbJY/oHJj4RkZ4sNoMMj3r8RES6AiV+0rkVrIeU4e51s8Tv+YXZnPCnj3n4sy3U1De2eGr+zm2kVG8mu9dUklR0QESk/cX1Jr5xD9vyS6htaPn/YhER6RyU+EnnVVsOpdmQMsy9j8+Ckh28ujSH219eQU19I79/cy0n3/0pLy3OodFnAViXV8YPn1/On/7xTwD6Tj4rWJ9ARKR7i+uNwdLLV8Km/IpgRyMiIoeg5Ryk8yrwV/Rs3uNXV84dL8xn6oAsHrtmCou37+HOt9fxwxeW89DcLaTGhfPZxkKiwrw8nbqVxqpEZs5UYRURkYCI7Q1Ahili7a5yRvWOD3JAIiLSGvX4SXDtWgHPX+UWPPfbUlDB55sKqc9b4zb4E7/V1QkAzE6r5uFvHUdEqJeZg5N59eaZ3H/FBOobfazPK+fHpw9j/u2zGV+/DO+gk8Cjv+YiIgHhX8TdFXjRPD8Rkc5MPX4SXGtfgzWvwugLYeR5FFXUcsk/v6CwopZfhr3LVZ5QnlkHSXG7ePjjMl4Jgd+eGE90+L6/uh6P4eyxvTl7bO99181f5xZ+H3hSx38mEZGewt/jNyauio+V+ImIdGrqCpHgyl/rnlf/F2st/++VlZRV13PnBWOYlVDEDtObX72xnpufXgK9+gIQXb3z8Nfd8ol7VuInIhI4UYngDWdIZDlrd5VhrQ12RCIi0gr1+EngLHsGjIFxl7V+TMF697zhHf771SbeXb2bn505nMum9IX5O2HkJD6ZfRJfbS1m9rAUuD+2bUs6bPkEeg2AXv3a45OIiEhLjIHYdLJCSthTVc/uslrS4yOCHZWIiLRAPX4SOHP/BHPvan1/Qy0Ub4GsqVBfxadvPc2UAYlcf/xAqKt0CV7KcPonR3PJcVmkxEW0bS2/xnrYNk+9fSIiHSGuNym2GEDz/EREOjElfhIYNWUuqSvaDLWtlPgu3Ai2Ed+kayn1xHM6X3D3xePweozbh923lEOTtiR+O5dAXTkMUjVPEZGAi80gui4fgDVK/EREOi0lfhIYu1f5X1jIX9PyMQXrAHhpZzyv103m1JClZMU07fMPAW1ayqFJglvLj0PNI9nyCWCg//FHGbyIiLRZXG+85Xn0iY9Qj5+ISCemOX4SGLtW7Hudt4KylAnsKKoiu7iK4qo6SqvrGbfhM6bh5Tfz67m+75mE7PoQNr0PI89zSaEnBBIH7n/dhL5QWwY1JRDZq+V7b/kYeo93RQdERCSwYjOgoZpJvT2sVuInItJpKfGTgGjIXU5taCK+hjreffNtfvRSxkHHPBS2mmxPGqP7pvCtK06BB/8Iq1/xJ37rIXEQhITtf1KCq+xJSXbLiV9tOeQshBm3BOBTiYjIQeLckg6TelXzxkZLTX0jEaHeIAclIiIHUuInR6dsF8Smu4puB/hgzW76rlzAroZMkiINU0N28rPZw+mXFEVWYhTJMeHER4YS/uCvMKmTeO7S6e7EEefA8mehrsr1+KWNOvi+exO/HZAx9uD92+eDr0GFXUREOoo/8RsZU4HPRrM+r5xxWQnBjUlERA6iOX5y5Cry4d6xsOyp/TbnllTznScXcdMTXzDAZjN03AxGT5xFVt1WvjOrH2eMzmBU73jS4iKIoB5TvAVSRuy7wKivQ30VrHsD9mw9eH4fQIJ/eYbWCrxs+QRCIiBrWvt8VhERObRYN6JjQHgpoMqeIiKdlXr85MjtWg6NddgN77Im7RwWb9/Dwm17+HDtbnzW8n+zQghd1EDG8CnQUAcNNVC8ef8KnUUbwfr239ZvJkSnwGd3H7yvSWQvCIs5dOLXdzqEah0pEZEO4U/8EhuLiI3oy/KcErcWq4iIdCpK/OSIVeesIBIoXfMRZy+di8VDelwEZ4xO5/unDCVr+8uwCEgf55I+gLyV+ydyTVU7U5v1+Hm8MOJcWPRv976lHj9jWl/SoXy3qyA69tL2+JgiItIWIWEQlYynYhfH9T+ZL7cUBzsiERFpgRI/OSLVdY18+eU8TgISTAWPnBHJkHEz6JMQiWma7/fFCgiNdhU5bSN4w1wv4ZiL9l0ofy0YLyQN3v8Go77uEj/jOXhfk9YSvy2fuGfN7xMR6VhxGVC2i6kDEvloXT755TWkxmrkhYhIZ6I5ftJm9Y0+/uepxaRUbaY8figAs8PWktkral/SB5C3AtJHg8cD3lDXq5e3cv+LFayDpEEQEr7/9n4zIDoVeg1ofbhma4nfpg/cUND0Foq+iIhI4MT2hvJcpg5MAuCrrer1ExHpbJT4SZv4fJafvLiCuevzGB6yi9hRp0PyUNg698ADXZLXPPlKH+O2NV90PX9ty0M5PV4480446WetBxOfBbWlUF2yb1vJDrcUxKgLXMIpIiIdx9/jN6p3HFFhXg33FBHphPQbshyWtZb/fWstryzdye9mReL11UHqKBhwgls+obF+38F7tkJdxf5LLaSPhapCKM9z7+trWq/aCTD6Qhh7cesBNS3pUJq9b9unf3LDQ4//4dF9SBEROXqxvaGqkFBbz6R+vfhya1GwIxIRkQMo8ZNDavRZ/vL+Bv49bytXz+jP5f3L3Y60kS7xq6uA3KX7Tshb4Z7Tx+zb1vS6abhnU0XP1FYSv8NpvpYfQNFmWPY0TL4W4vsc3TVFROToxbnKnpTnMW1gEht2V1BcWRfcmEREZD9K/KRV2cVVXP6vL7jvo01cNCmTX509EpO/xvWsJQ+D/scDBrZ8uu+kXSvAEwKpI/dta1qIvSkpzF/nnpuv4XckDlzL79M/ugIys75/dNcTEZFjE+sWcafcFXgBzfMTEelsApr4GWPOMMasN8ZsMsb8tIX98caY140xy40xq40x1zTbt80Ys9IYs8wYsyiQccr+rLW8tDiHM+/9jDW5Zfz54nHcddFYPB4Du9dA4iBXeCUq0fXmbW2W+OWtcEM4mxdtiYiHXv339fgVrHXJYWtVOw8nKtFVDS3Z4ZaFWPE8TPk2xKYd9WcWEeks2tB2nmSMKfW3j8uMMb8KRpz7ifMnfmW5jMmMJzzEo+GeIiKdTMCWczDGeIG/A6cCOcBCY8xr1to1zQ67GVhjrT3HGJMCrDfGPGWtbRofMttaWxioGOVgeyrr+H+vrOTtVXlM6Z/I3ZeMIysxat8B+Wv2n7834AT46l9QXw2hkS65GzTn4As3FXgBl6wlDnJrPx2N5mv5ffIHCIuGmd87umuJiHQibWw7AT6z1p7d4QG2Zu9Qz12Eh3iZ2LeXevxERDqZQPb4TQE2WWu3+BO5Z4HzDjjGArHGrQUQAxQDDQGMSQ5hdW4p59w/jw/W7uanZw7nmRum7Z/01VXCnm2usEuTASdCYy1kf+kWUK/Y3fJyCuljoXgL1Jb7K3oOO/iYI5HQF3YscJU8p90E0UnHdj0Rkc6hLW1n5xORACGRUJYLwNSBiazZVUZpdf2hzxMRkQ4TyMSvD9Cs7CI5/m3N3Q+MAHKBlcBt1lqff58F3jPGLDbG3BDAOAV4ddlOLvzHfBoafLxww1RuPHEQXo/Z/6D8dYB1hV2a9Jvuhm1unbtvDl9GS4nfGHfuziWuomfqUc7va5LQF6qKIDwept98bNcSEek82tJ2Akz3T5N42xgzqoX9HcsY/5IO/sRvQBLWwqJt6vUTEeksAjbUEzAtbLMHvD8dWAbMAQYB7xtjPrPWlgEzrbW5xphU//Z11toDFo0Df1J4A0Dfvn3bM/7uJ28VZH/hllNoqIaGWny1lazZuJH0wmw+CSslzZZgno+BWxa7uXnN5a92z80Lt4THQp9JLvEL9fcOpo0++N5NlT1XveQqera2lENbJWS55xm3uEXbRUS6h7a0nUuAftbaCmPM14D/AkMOulBHt4+xvaF8FwAT+iYQ5vXw5dZiTh6h+dciIp1BIBO/HCCr2ftMXM9ec9cAd1prLbDJGLMVGA58Za3NBbDW5htjXsENfzko8bPWPgQ8BDB58uQDG0dp7uUb9iVvgDUe6ggjtjGO2LgMUvtNx4RGwbL/wLo3YfwV+5+/e41L7noN2H/7gBPgs3sgPM5V3IxMOPjecX1cgrbmv+79sfb4DTndLSMx7cZju46ISOdy2LbT/+Vo0+u3jDEPGGOSD5wT3+HtY1wGZH8FQESol3FZ8XypeX4iIp1GIId6LgSGGGMGGGPCgMuA1w44ZgdwMoAxJg0YBmwxxkQbY2L926OB04BVAYy1+2ush8L1MO1/WHf1am4e+C4Dqp/kON8TLDzvY/r9aC6eix+F8+53wyhXvXTwNfJXu546zwF/bQacALYRNn/Y8jBPcMOA0sdCTakbGpo46Ng+T+pwuPgx1+MoItJ9HLbtNMak++fGY4yZgmvLg19CMzYDyvPAuhxz6oAkVu0spaJWU/dFRDqDgCV+1toG4LvAu8Ba4Hlr7WpjzI3GmKZumt8BM4wxK4EPgdv931imAfOMMcuBr4A3rbXvBCrWHqF4C/gaeGRLHGc8uJy5m0u57eShzLt9DhdNytx3nDEw+kLY/DFUHlBQNX/t/vP7mmROgZAI9zp9XOsxNA33PJaKniIi3Vgb286LgFX+NvI+4DL/yJngiuvtin1VuV6+KQMSafRZFmuen4hIpxDIoZ5Ya98C3jpg24PNXufievMOPG8LcIgMQo7UV1/NZwrwTn4Ct508hGtnDiA+KrTlg0dfCPP+4oZlHne921ZRAJUF+8/vaxIaAVlT3Xp+TcldS5qqfaYe4/w+EZFurA1t5/244midS2zTkg65EJ3EpJRG/hL6D6Y/dx3c8oVbz1VERIImoAu4S/D5fJY/vbOOefPn4cPwwG2X8f1Th7ae9IErzpI8DFa9vG9bS4Vdmhs0B4wHMtrQ45dyjPP7RESk82m2iDvLniH6oemc6/2cMF81bPk0uLGJiIgSv+6svKaeG55cxAOfbOaUlD2YhH4k92pDBUxjYMxFsH0+lO5023b71w5Oa6Vq+LSb4PoP9y3i25KU4XDCj2HcZUf2QUREpPNrSvxeuwX+eyMkDeaRMU9SbGNo2P5FcGMTERElft3V1sJKLnhgPh+vL+B3549mbFge5kiGWI6+ELBugXRwPX5RyRCT2vLxIeHQZ+Khr+nxwJxfQOKAQx8nIiJdT0yam+9dXw1n3Q3XvsvQMVNZ7BtK7dYFwY5ORKTHU+LXDb22PJez7/uMwopanrxuCt88rg8UbYSUYW2/SNIgyBgPq15073evabmwi4iICIA3FK57D7670M0P93iYMSiJtSEjiC7fCpXBLzwqItKTKfHrRmrqG/nZyyu59ZmljMiI481bj2fGoGTYsxUa6458bt2Yi9xaeYWboGAdpLYyzFNERATcPO/Y9L1vQ70eogfPAKBKvX4iIkGlxK+b2FxQwfl//5xnvtrBTScN4pkbptE7IdLtLFjnno+kxw9g1Nfd87x7oL5KPX4iInLEJk6fQ731sn3Zx8EORUSkRwvocg7SMbYVVnLu3+YRHurlsWuO46RhB8zDy/cnfslDj+zC8ZnQdwYsf8a9V4+fiIgcofEDMljnHQg7vgx2KCIiPZp6/LqBP7y9Fgu89t2ZByd94Hr8EvpCeMyRX3zMhWB97vWR9hiKiEiPZ4yhKm0yA2rXsXtPebDDERHpsZT4dUUFG9w6ScCCzUW8u3o3/3PSIDJ7RbVy/Hq3lMLRGHk+GK9bePdoEkcREenxMseeSISpZ/7nnwQ7FBGRHkuJX1eTswj+eTw8ewU+n+X3b66hd3wE1x8/sOXjfY1QuOHoe+uik2HCN2DEuUcfs4iI9GhpI08AIH+NFnIXEQkWzfHrSoq3wNOXuqGXuUv56KO3WZ1rufey8USEels+Z882aKw9+h4/gHPvO/pzRURE4vtQEZFBn/KVbNxdzpC02GBHJCLS46jHr6uoKoanLgbbCNe+iw2NpurzfzE+K4Fzx/Vu/by9FT2PcCkHERGRdhTSbxqTPBv477KdwQ5FRKRHUuLXFdTXwLNXQEk2XPYM9JnIysTTONU3j9+c2htjTOvn7k38jrCip4iISDuKGDidDFPM/CUr8PlssMMREelxlPh1dj4f/Pcm2LEAvv4P6DedXaXV/Cp3KpGmjvFFbx/6/Px1EJcJ4RpWIyIiQZQ1BYA+5StYtH1PkIMREel5lPh1dgsfhtUvwym/gdEX0uiz3PHaGtbY/tSmT4JF/wZ7iG9OC9ZB6jHM7xMREWkPaaOxoVFMCdmk4Z4iIkFw2MTPGHO2MUYJYjBYC189BJlTYOb3qGvwcduzS3lndR7fP2Uo4dO+DUWbYGsrVdL2VvRU4iciIkHmDcX0mcRJUVt4fVkuZTX1wY5IRKRHaUtCdxmw0RjzJ2OMKoR0pO3zoWgjTLqa6nof33lyEW+s2MVPzxzOTScNglFfh8hesPDfLZ9fsgMaarTwuoiIdA5ZU8iq3URDbQVPfbHDbWtsgJUvQmlOcGMTEenmDpv4WWu/AUwANgOPGmMWGGNuMMZo0ligLXkcwuMoG3QW33rkKz7ZUMD/fX0MN544yO0PjXBr7K17E8p2HXz+3sIu6vETEZFOIGsaxjbyjaxi/j1vK7XZy+DhOfDSdfDZPcGOTkSkW2vTEE5rbRnwEvAskAF8HVhijLklgLH1bNV7YM2r1Iy4kCseX8mSHXu477IJXDG17/7HTbrGLfGw5ImDr7E38VOPn4iIdAKZkwG4Kn0719Q8Tugjc9wXl/F9YffqIAcnItK9tWWO3znGmFeAj4BQYIq19kxgHPCjAMfXc614ARpq+MWOiWzcXcG/rprMOS2t15c0CAbNgcWPueEyzRWsh9jeEBHfISGLiIgcUlQiJA8ja+XfuDnkNd71nkjj/3wJQ0+D/DWHLlYmIiLHpC09fhcDf7HWjrXW3mWtzQew1lYB1wY0up7KWuySx8iJHMaLuUncfck4Zg9Pbf34yddBeS7M/dP+jWb+WvX2iYhI5zLyPEgawsJZD3NTxfW8s7kWUkdCbRmUZgc7OhGRbqstid+vga+a3hhjIo0x/QGstR8GKK6ebecSzO7V/KNsJt+dPZizx7bQ09fcsDNhzCXw6R/h5Rvcgu8+n6vomap6PCIi0onM+TncsoiJcy5iQHI0//h0EzZtlNun4Z4iIgHTlsTvBcDX7H2jf5sEyO5P/kmVDad08Hn84NShhz/B44ULHoI5v4CVz8PjZ0PuEqivUo+fiIh0Sl6P4TsnDGTVzjIWVPhHtSjxExEJmLYkfiHW2rqmN/7XYYELqWfLycsndtN/mRs2iz9cPhOPx7TtRGPghB/DJU+4hvOxs912VfQUEZFO6usT+5AaG87f5+dDggq8iIgEUlsSvwJjzLlNb4wx5wGFgQupG6irhJeuP+I1iWrqG3nx8XuJopax595GbETokd975HlwzdtufT/jVY+fiIh0WuEhXq6bNYDPNxVRGjfMFXgREZGAaEvidyPw/4wxO4wx2cDtwHcCG1YXl7cSVr4Aq185otP+u3QnJ1W+TUXcYHqPPuHo7997PHxn7r4EUEREpJO6Ympf4iJC+LQkBQo3QkNtsEMSEemW2rKA+2Zr7TRgJDDSWjvDWrsp8KF1YVXF7jn7y7Ydby1200cMfu8qxns2Ez39Ojd081jEpEDfqcd2DRERkQCLjQjlu3MG825hsluXtmB9sEMSEemWQtpykDHmLGAUEGH8CYm19rcBjKtrq25K/L5yyyu0lsQ11MGql2DB/Zjdq+hrE1g54nuMmfLtjotVREQCwhgTDVRba33GmKHAcOBta219kEPrdK6a3p9r5w2GOvDlrcKTMTbYIYmIdDttWcD9QeBS4BbA4Nb16xfguLq2ph6/it1Qsr31456+BP57I/gaeCTpR5wX8iBDL/oVeI9ibp+IiHQ2c3FfmPYBPgSuAR4LakSdVESol8vOOIlaG8rGVV8d/gQRETlibZnjN8NaexWwx1p7BzAdyApsWF1cU48fQPbClo+pyIctH8OMW9hy8Qf8dudELps+mPAQb8fEKCIigWastVXABcDfrLVfx02bkBacPb4vOSF92bNlKdV1jcEOR0Sk22lL4lfjf64yxvQG6oEBgQupG6gqgqhkCItpfZ7f5o/d86gLeHT+dsK8Hq6c1rfjYhQRkUAzxpjpwJXAm/5tbZpi0RN5PIa4/uMZ4NvGI59vDXY4IiLdTlsSv9eNMQnAXcASYBvwTABj6vqqiiE6BfpMOkTi9yFEJVGaMIoXF+dw3vjeJMeEd2ycIiISSN8Dfga8Yq1dbYwZCHwc3JA6t5RBE0gzJTzzyVIKK1TdU0SkPR0y8TPGeIAPrbUl1tqXcHP7hltrf9Uh0XVV1XsgKhGypsLuVVBbsf9+nw82fwQDZ/Psohyq6xu5ZqY6UUVEuhNr7afW2nOttX/0t6eF1tpbgx1Xp5Y2CoB+Ddu494ONQQ5GRKR7OWTiZ631AXc3e19rrS0NeFRdXVWxWz8vaypYH+xcvP/+3SuhsoDGgXN4fP42pg9MYmTvuODEKiIiAWGMedoYE+ev7rkGWG+M+XGw4+rUUl3id0X/cp7+agfr88qDHJCISPfRlqGe7xljLjTmWBeW60GqiyEqCTInu/fZB1Qo2/wRAB/Xjya3tIbrZqm3T0SkGxpprS0DzgfeAvoC3wxqRJ1dTCpEJXNyYiHxkaH85MXlNDT6Wj62sgievRKWP9uxMYqIdFFtSfx+ALwA1Bpjyowx5caYsgDH1XVZ63r8ohIhMgFSRhw8z2/Th9jUkdy3sJx+SVHMGZ4alFBFRCSgQo0xobjE71X/+n02uCF1csZA2kgiitbym3NHsTyntOVCLyU74JHTYd0b8PptUKhhoSIih3PYxM9aG2ut9Vhrw6y1cf73GpfYmtpy8NVDZKJ7nzUFcr5y8/rAzffb8QXrY6awIqeUW+YMweNRZ6qISDf0T1xBtGhgrjGmH6AvTg8nbTQUrOOc0amcOjKNu9/bwNbCyn37d6+Bf58Glflw8eMQGgmv3AiNDcGLWUSkC2jLAu4ntPToiOC6pKY1/KKaEr+pUFMKhRvc+23zwFfPX7dmcVz/Xlw4sU9w4hQRkYCy1t5nre1jrf2adbYDs4MdV6eXOhLqqzAl2/n9+aMJD/Fw+4sr8PksbF8Aj57hjrvmbRh1Ppx1N+xcBPPvDWrYIiKdXVuGev642eOXwOvAbwIYU9dW5U/8IpslfuB6/QA2f0SdCefT2sH87vzRaOqkiEj3ZIyJN8bcY4xZ5H/cjev9k0PxV/Zk92rS4iL45dkj+WpbMZ+8/jg8eb5bLum69/YdN/pCGHUBfPwHyFsZtLBFRDq7tgz1PKfZ41RgNLA78KF1UQf2+CUNckmgf55fzfr3md84nCtmDGV4ukbMioh0Y48A5cAl/kcZ8GhQI+oKUoYDBnavBuCiSZnc3mcFJyz5PnWJw+DadyGh7/7nnHW3q6b9yo3QUNfxMYuIdAFt6fE7UA4u+TssY8wZxpj1xphNxpiftrA/3hjzujFmuTFmtTHmmrae22lV7XHPUUnu2RjX65f9FY3F24go3cKSkIl875QhwYtRREQ6wiBr7a+ttVv8jzuAgcEOqtMLi3Jfmua7xM8sfJgbi/7IEoZzg+fX1IUnHnxOVCKc+ze3du6nf+zggEVEuoa2zPH7mzHmPv/jfuAzYHkbzvMCfwfOBEYClxtjRh5w2M3AGmvtOOAk4G5jTFgbz+2cqg8Y6gmuwEvhBla8/W8Axs++kNiI0CAEJyIiHajaGDOr6Y0xZiZQHcR4uo7Uka7H77O74a0fYYaeQe7ZT/LJthp++MJyN9/vQMPOgAnfgHn3QP7ajo9ZRKSTC2nDMYuavW4AnrHWft6G86YAm6y1WwCMMc8C5+EWsW1igVj/GoExQLH/HlPbcG7nVFUMGLeUQxP/PL/+Gx+l0JvC7JkzgxKaiIh0qBuBJ4wx8f73e4BvBTGeriNtNKx9DT78LYy5GM7/B+d7Q8mrMtz59joSIkP57XmjDp4nf+rvYOWL8NW/4Ox7ghO7iEgn1ZbE70WgxlrbCK4nzxgTZa2tOsx5fYDsZu9zcAldc/cDrwG5QCxwqbXWZ4xpy7mdU1URRMSDx7tvW+8JNOKlF+WUDj0H4zmaEbYiItKVWGuXA+OMMXH+92XGmO8BK4IaWFeQOck9T74WvnY3+NvNG08cxJ7KOv45dwu9osP4walD9z8vKtEVelnxHJx6B4THdnDgIiKdV1sykA+ByGbvI4EP2nBeS+UqDxybcTqwDOgNjAfu9zeQbTnX3cSYG5oqphUUFLQhrACrLt5X2MWvzBfKGtsfgPjRpwUhKBERCRZrbZm1tmn9vh8ENZiuYvApcPNXcNY9e5O+Jj89cziXTM7kvg838mhLi7sfdz3UVbjkrzVVxSoCIyI9TlsSvwhrbUXTG//rqDaclwNkNXufievZa+4a4GX/+kabgK3A8Dae2xTPQ9baydbaySkpKW0IK8Cqivef3we8uCiHLxuHYk0IDDgxSIGJiEgncNg1fNpa3MwYc5wxptEYc1H7hthJpAxzBdIOYIzh/74+htNHpXHH62t4YVH2/gf0mQgZ42DhI2Bb+M64Ih/+Ngk+/n2AAhcR6ZzakvhVGmMmNr0xxkyibZPTFwJDjDEDjDFhwGW4YZ3N7QBO9l83DRgGbGnjuZ1TdfG+ip5Ao8/y+IJtfJZxDebadw7qDRQRkR6lxdErTdpa3Mx/3B+BdwMRZGcX4vVw72UTmDU4mZ+8tIJnv9qxb6cxMPk6VxXUv5TSft77hWurs7/quIDbS00ZPH0p7Nke7EhEpAtqS+L3PeAFY8xnxpjPgOeA7x7uJGttg/+4d4G1wPPW2tXGmBuNMTf6D/sdMMMYsxI3pPR2a21ha+ce4WcLjqo9+yV3n6zPZ3tRFRfNGgNZxwUxMBER6QjGmHJjTFkLj3Lc1IZD2VsYzVpbBzQVNzvQLcBLQH77Rt91RIR6efhbkzlhSAo/fXklTyzYtm/nmIsgPB4W/nv/k7Z86oaAhsdB3irw+To05mO2axlseAe2fhrsSESkCzpscRdr7UJjzHBcb5wB1llr69tycWvtW8BbB2x7sNnrXKDFSW8tndslVO8/1PPRz7eRHhfBGaPTgxiUiIh0FGvtsVQUOWxxM38BtK8Dc4Ae/Y1iRKiXh66axM1PLeVXr66mrsHH9ccPhLBoGHcZLH4UzvgDRCdDQy28+QPo1R+m3gTv3A4l2yFxQLA/RtuV5e7/LCJyBNqyjt/NQLS1dpW1diUQY4z5n8CH1gU11LoJ5VG9ANi4u5x5mwr55vR+hHpVyVNERA6rLcXN/oobIdN4yAt1tuJnARIe4uWBKyfytTHp/P7NtTzwySa347jroLEOlj7p3n9+HxRtclVCm0bg5K0MTtBHq2yney7NCW4cItIltSUb+ba1tqTpjbV2D/DtgEXUlVXtv3j7o/O3ERbi4fIpfYMYlIiIdCFtKW42GXjWGLMNuAh4wBhz/oEX6nTFzwIoLMTDfZdN4LzxvfnTO+v5+8ebXHGY/sfDokehaDPMvQtGng9DTnELxBsP7F4V7NCPzN4ev53BjUNEuqS2rOPnMcYYa11pLP+E8rDAhtVFVfsTv6hESqrqeHlJDueP701itH5cIiLSJnuLmwE7ccXNrmh+gLV279hEY8xjwBvW2v92YIydUojXwz2XjMcAd727Hq/HcOPka+HFa+CJ88Eb5oZ9AoRGQtKQLtjjp6GeInL02pL4vQs8b4x5EDfc5Ebg7YBG1VU19fhFJfHcwmxq6n1cPaMLzR0QEZGgstY2GGOaipt5gUeaCqP59z94yAv0cF6P4c8Xj6PRwp1vryPszFFcG50KpTvgjD9CXLPaOuljjryyZ2Whmz8YGnn4YwNh71BP9fiJyJFrS+J3O3ADcBNu7sFSICOQQXVZ/h6/hvAEnliwnakDEhnZOy7IQYmISFdyuMJoB2y/uiNi6kpCvB7+csk4fD7Lb9/exPDx1zPDLncLuzeXPhpWvQjVeyCy1+Ev3FgPD86C4WfDWX8OTPCHU7bLPdeVQ00pRMQHJw4R6ZIOO8fPWusDvsCtrzcZt+7e2gDH1TX5e/y+2GXZWVLN1TP6BzceERGRHijE6+Gvl43njFHpXLFsNI9k/S94D/iuO32Me85r4zy/TR9A+S73HAwNdVCZD8nD3HsN9xSRI9Rq4meMGWqM+ZUxZi1wP/7y0tba2dba+zsqwC7F3+P3/JoqkqLDOGVkWpADEhER6ZlCvR7uu3wCp41M47dvrOEnLy6npr5ZIdQ0f+LX1gIvK55zz3u2BifpKvf39mX6K5JquKeIHKFD9fitw/XunWOtnWWt/RtwyNLRPV5VMTY0infWlXDu+N5awkFERCSIwkI8/OMbk/ju7ME8vyiHrz8wn22FlW5nbBpEp7atwEtNKax7C7KmuffbPg9c0K1pSjablqIo05IOInJkDpWZXAjkAR8bY/5ljDmZltcXkiZVxVR546hr9HHRpMxgRyMiItLjeT2GH50+jEevPo7ckmrO+ds83lmV53amj25b4rfmVWishdN+B+FxsH1eYINuSVNhlz6TAKOhniJyxFpN/Ky1r1hrLwWGA58A3wfSjDH/MMac1kHxdS3VxeTVRzMiI45RvTXhWkREpLOYPTyVN2+dxcCUaG78z2J+/spKapNHQcE6N3/uUFY8D0mD3TDLvtOC2+OX0A9i0jTUU0SOWFuKu1Raa5+y1p6NW0h2GfDTQAfWFVWXFpBbF6nePhERkU4os1cUz984netmDeCZr3bw24VeaKzDFq5v/aSSbNj2GYy9FIyB/rOgaCOU7+64wMElfmGxEBEH8X001FNEjtgRTUKz1hZba/9prZ0TqIC6sqrSAkqJ5bzxvQ9/sIiIiHS48BAvvzx7JK99dxal8cMB+Mdzr7Ipv6LlE1a+4J7HXOye+81yzx093LNs5751COP6aKiniBwxVR9pJw2NPrw1e4hKSCE5JjzY4YiIiMghjO4Tz703X0SDJ5zoPWs58965PPr5Vqy1+w6y1lXzzJoGiQPctoxxEBbT8cM9y3L3T/xKd7r42sJaV5ymoTZw8YlIp6fEr518tmE3cbaCvpka5ikiItIVeENCCUkfyeV9SzlhSAp3vL6GW55ZSkVtgzsgb4WbAzj2kuYnQdZU2B6MxK+Pex3fB+oroaakbedunQvPXr5vSQoR6ZGU+LWTtxetw2Ms/bOygh2KiIiItFX6GMIKVvOvb07ix6cP462Vuzjv/nls3F0Oy58DTyiM+vr+5/Sf6RLCysKDr1e601UBrW1l6OjRaGyAirz9e/yg7cM9177unrO/bL+YRKTLUeLXDkqr6lm2bgsAITHJQY5GRERE2ixtDFQX46nYxc2zB/Of66dSWl3PBX+fS83S57BDT4OoxP3P2TvP74BeP2vhxWvh+avgz0PgpW/Dxg9c4nY4DbWukExLKnaD9R2c+LWlsqfPB+vecK+zFx7+eBHptpT4tYPXV+QS4ytzbyITD32wiIiIdB7pY9zz7lUAzBiUzBu3HM8liVuIqC3kwT3HkV9Ws/85vSdASOTB8/xWvwzZX8DM77kqoBvfg6cuhHuGw+pXDh3Hmz+AB2e2nCQ29ew1H+oJbavsuXMxlO+ClOFQuB6qSw5/joh0S0r82sHLS3IYndjo3kT1Cm4wIiIi0nZpo9xz3oq9m9J9efzC8yjVoQncv3MQp9zzKc8vyt5X+CUkDLKm7N/jV18N7//a9SCe/Cs456/wow1w6VMQkw5v/hBqy1uOoXgrLHsGakqhcMPB+5sWb2/q8YtJB+Np21DPda+DJwRO+pl7v3PR4c8RkW5Jid8x2lNZx9LsEmb29v8o1eMnIiLSdUTEQa/+kOd6/MhbCf8+DVNVROQ3n+P12+YwLD2Wn7y4gqse+Yrs4ip3XP9ZsHs1VBW79/Pvh9JsOPNO8HjdtpBwGHE2nHMvVBXBFw+2HMO8v7ihnAC7lh+8v3yXe25K/LwhLvk73FBPa938vgEnwqA5gIEcJX4iPZUSv2O0YEsR1sLIBP/QjAPnAYiIiEjnlj7GJXzb5sGjX3M9ZNe+A32nMTAlhudumM5vzxvFku17OO0vc3nw08009J0BWNixwPW8zbsHRpzrEsIDZU6CYWfB/L9B9Z7995XsgGVPw6Sr3fDRZj2Pe5XtdPsim40qiu+zryewNflroHiLSz4j4iB1BGR/daQ/HRHpJpT4HaPPNhYSEx5Cn7Aq11CExwU7JBERETkSaWOgeDM8eQHEZsB177kkyc/jMVw1vT/v/eBEZg1J5s631/H1/9bi84a7eX4f3AG+Bjj1t63fY87PobYMPr9v/+3z/uqej/8hpI+GXS0lfrkQlwHG7NsW14bEb+3rgHFJJ0DmcW6op8936PNEpFtS4neMPt9UyLSBSXhq9rhv4pr/pywiIiKdX8Y4//NY19MX3/KavH0SIvnXVZN56JuTKKyBL+sHUb7oGVjxLEy/ed8i7y1JGwWjL4QvH4SKAretLBeWPgnjr4CELEgf63r8DkzMmq/h16Qti7ivfQP6ToPYNPc+8zg3j7Bo4yF+GCLSXSnxOwY7iqrYUVzFrMFJbox/VFKwQxIREZEjNeQ0uPhxuOrVNk3ZOG1UOu//4ETq+0wntqGYYpPAlhE3Hv4+J/3MLdsw7x73/vN7wdcIx//Avc8Y53oFS7btf17Zzn3z+5rE94GG6oOHjjYp3gK7V8Lws/dty5rinnO0rINIT6TE7xh8vtkt3DprSIr7j1eFXURERLoejwdGnQ9h0W0+JSY8hBPOvBSA+7iCcx9azjur8g59UvJgGH85LPw37FwCix+DcZe74jLgehxh/+GePh+U7To48Wt639pwz7X+tftGNEv8koZARLzm+Yn0UEr8jsG8jYWkx0UwKCXa3+OnxE9ERKTH6DsVblnCDbf9ikEp0dz4n8X86Z11NPoOMfzyxNtdBc8nzofGun29fQCpI129gOaVPasKwVffwlBP/3DU1ip7rn3dDR1tSirBJbh9Jquyp0gPFRLsALoqn8/y+eZCTh6ehjEGqoshcmKwwxIREZGOlDSI3sBz35nOHa+v5oFPNvPx+gJGZsTRJyGC3gmR9E6IZGK/XsSEh0BCX5h8DXz1kFvkPWnQvmuFhEPKiP0rex64hl+TvYu4t5D4ledBzlcw+xcH78uaAp/cCTVlrtKniPQYSvyO0ppdZZRU1XP8kGQ3sbqqSD1+IiIiPVREqJc/XDCWiX178dzCbBZsLiSvrIamzr/MXpH8/YqJjMtKgBN+7Nbma1pUvbmMsbDxPfe7hTH7Fmk/MPGLSQPjbTnxW9fCMM8mmZMBC7lLYOBJR/lpRaQrUuJ3lOZtcvP7ZgxOgrpKN1xDc/xERER6tIsnZ3Hx5CwAGhp97C6vZd2uMn716mouenA+vzhrJFdN74e59D8tXyB9LCx7yvXaxWU0S/wOGOrp8bqlJ1oa6rnmNUgaDCnDD97XZ7J7zl6oxE+kh9Ecv6M0b2Mhw9JiSY2NcMM8QVU9RUREZK8Qr4c+CZGcPCKNN2+dxQlDUvj1a6v57tNLKa+pb/mkpqUlmoZ7lu0ETyhEJR98bEuLuO/ZDlvnwqgLWl5iKjIBkoepsqdID6Qev6NQU9/IV9uK+ea0fm5DVVPipx4/EREROVhCVJhbA/CzLdz17npW7CxhRHocln1L8SVGh/K1oamciMHsWg5DT9+3eLunhe/q43rvXwgG3LqAABOvaj2YrONg3Vv7hpOKSI+gHr+jsHj7HuoafMwa7P/2ranHT0M9RUREpBUej+HGEwfxzLenkRobwY7iKrKLq9hZUk1uSTXvrt7N1U+vYzvprFw0l4/X5+Mr3XnwMM8mcX1cYtiUOTY2wJInYcipbkH41mQe5353Kd7S/h9SRDot9fgdhc82FhLqNUwZ4E/01OMnIiIibTRlQCIv3TTjoO31jT7mbSpkz5sjSClbyTmPLuTzqM3EDDiO+JYuFJ8JDTXu95DoJNj4LlTkwaR7Dh1AZrOF3JtXFe1oWz4Fbyj0O/hnISLtTz1+R+HzTYVM6NuL6HB/3ly9xz2rx09ERESOUqjXw+xhqUyYcgKZFPDghQNI8hXxwgYf//hk88HrA+5dxD3HPS961BV8GXL6oW+UMgzCYoO/kPsb34e3bw9uDCI9iBK/I7Snso5VuaX7hnmCW8oBILJXcIISERGR7iN9LABnRG0ggjri0vrxx3fWcdlDC9hRVLXvuOaLuJfsgE0fwIRvgvcwA7o8XsicFNwCLzWlULwZ8tdAfU3w4hDpQZT4HaEFW4qwFmbul/gVQ0T84f+jFRERETmcpsqeG94B4OLZU7jnknGs21XOGffO5acvreDTDQXUx2S448p2url9ABO/2bZ7ZE6B3auhuqR9Y2+rXf6qpb4G2L0qODGI9DBK/I7QF1uKiA7zMi6z2Wj76mIN8xQREZH2EZ3sCrdseBcAE5/JBRMzeef7J3D6qHReX57Ltx75iqn3LqcRL9lb12GXPgmDT4GEvm27x6A5YBthyyeB+xyHsmvZvtc7lwQnBpEeRl1UR2hZdgnjshII8TbLmauKVdhFRERE2k/6WNjwtnsd63r2+iRE8pdLx1NT38jcDQW8vSqPvDWJRKx5AWNK+WTw7UypayAqrA2/3mUe50YrbXofRp0fuM/RmtxlLrn1NUCuEj+RjqAevyNQU9/I2l1ljMtK2H+HevxERESkPTUN9zQeiEnbb1dEqJfTRqXzl0vHk9F3ECmmlCJPItcvSGTa/33IH95ey6b8Cqy1LVzYzxviev02vr9vOYiOtGs5ZIyH3hPV4yfSQdTjdwTW7iqjvtEyLjNh38aizVCwHsaOC1pcIiIi0s1kuAIvxKQfsoaAJ74PZEPizGt5dtDxPPr5Nv41dwv//HQLveMjmDUkmVlDUpg6IJGSqnq2FFSwuaCCLQWVTK8YycUVr0Dein2JZkeoLYeiTTD2Epd0bnjHbQuP7bgYRHogJX5HYFl2CQDjm3r8GmrhxWsgJBxO+HHQ4hIREZFuxl/Zc++SDa1J6AcYzMSrmNwrkcn9E9lVWs1H6/KZt7GQd1bl8fyinINOi48MZW51JhdH4Hr9OjLx27UCsK7Hzxj3etdy6D+r42IQ6YECmvgZY84A7gW8wMPW2jsP2P9j4MpmsYwAUqy1xcaYbUA50Ag0WGsnBzLWtlieXUJ6XATp8RFuw/u/cv9RXfaMW0RVREREpD3EZ0JUEsT3OfRx07/rirr06rd3U0Z8JFdO7ceVU/vR6LOs3FnK4u17SI4JY1BKDAOSo6msa2DK/35IfswIUje+Dyf8KMAfqJmmwi69x4Pxutc7lyjxEwmwgCV+xhgv8HfgVCAHWGiMec1au6bpGGvtXcBd/uPPAb5vrS1udpnZ1trCQMV4pJbnlDIuy1/Nc91b8OWDMPUmGP614AYmIiIi3YsxcPFjB83vO0h0EkTPbHW312MYn5Wwb7RS02nhIYzNjOeTqvFckvNcxxaqy13mCtbEpLr3CX1V4EWkAwSyuMsUYJO1dou1tg54FjjvEMdfDjwTwHiOSUlVHVsLK11hl9IcePV/3LCIU+8IdmgiIiLSHQ04AVKGBezys4el8mzJMLA+2PJxwO5zkF3L3DDPJr0nqMCLSAcIZOLXB8hu9j7Hv+0gxpgo4AzgpWabLfCeMWaxMeaG1m5ijLnBGLPIGLOooKCgHcJu2fKcUgDG946BF6+Dxnq46FE3v09ERESki5kzPJVlvsHUhca7eX4dobYcCje6YZ5Nek+Eku2u11FEAiaQiZ9pYVtr9YLPAT4/YJjnTGvtROBM4GZjzAktnWitfchaO9laOzklJeXYIj6E5dklGAMT81+C7C/g7L9A0qCA3U9EREQkkMb0iScxJpLlEce5xM/nC/xN81ayt7BLkz4T3XNrwz2DsdyESDcUyMQvB8hq9j4TyG3l2Ms4YJintTbX/5wPvIIbOho0y7NLGJwSQ8TOBZA40JUgFhEREemiPB7DScNSeLl8OFQV7iu6Eki5/ns07/FrSgJ3Lj34+CVPwp8GQvWeAAcm0v0FMvFbCAwxxgwwxoThkrvXDjzIGBMPnAi82mxbtDEmtuk1cBqwKoCxHpK1lmXZJW5+3+41kDYqWKGIiIiItJs5w1N5t2Y0FtO24Z61FVC46ehvuGu5W5swNn3ftog4SBpycI9ffTV89HuoLoaNHxz9PUUECGDiZ61tAL4LvAusBZ631q42xtxojLmx2aFfB96z1lY225YGzDPGLAe+At601r4TqFgPJ2dPNUWVdUzqHQ7FWyBViZ+IiIh0fbOGJFPmiSc3eiRsfO/QB2/+GB6YDg9Mdb8PHY1dy/bv7WvSZyLkHtDjt+hRqMiDkAjY8PbR3U9E9gpkjx/W2restUOttYOstf/r3/agtfbBZsc8Zq297IDztlhrx/kfo5rODZblOSUAHBedD1hIHRHMcERERETaRVxEKMf1T+TDhrGwczFUFh18UE0pvHYLPHk+hISB8cCCvx/5zeoqoXDD/vP7mvSeCOW7oGzXvmPn3QP9j4fRF7kev8b6I7+niOwV0MSvu1i2o4SwEA/9G7e7DRrqKSIiAWKMOcMYs94Ys8kY89MW9p9njFlhjFnmr2qtVa/lmJw8IpUXy0YC1vWsVRVDSTYUrIc1r7pevqX/gZm3wY3zXJ2DpU+1nCQeSt5Kt3REaz1+sG+458KHobIAZv8chp0BtaWwY8GxfEyRHi9gC7h3J8tzShjdO46QwnluuEHiwGCHJCIi3ZAxxgv8HTgVVyRtoTHmNWvtmmaHfQi8Zq21xpixwPPA8I6PVrqL2cNT+d83B1AT1ouIV28++ICU4XDJE5A52b2ffotLBBf+C0466LuJ1jUVdmmpxy9tNBivW89vwAkw768waA70m+7mFXrDYP07bp+IHBUlfofR0Ohj5c5SrpjSD3avdguperzBDktERLqnKcAma+0WAGPMs8B5wN7Ez1pb0ez4aFpfKkmkTQYmR9M3KYa/Rf+UH4+phNBoCI2EsGgIj3PJVmjEvhNSh8OQ0+Grh2DGrRAW1bYb7VoGMWkQl3HwvrAoSB3p5vl9+U9X0GX2z92+8BgXw4a34fT/BdPSimEicjga6nkY63eXU1PvY1xWPOSvUWEXEREJpD5AdrP3Of5t+zHGfN0Ysw54E7i2g2KTbsoYw+xhqTyc24/qqd+DaTfCpG/BmItg6Gn7J31NZt4KVUWw/JmD97UmdxlkjGt9f58JsHMRzP+bSyybehgBhp7hCsoUbmz7/URkP0r8DmN5dikAE5MboWI3pI0MckQiItKNtdSVcVCPnrX2FWvtcOB84HctXsiYG/xzABcVFBS0b5TS7cwZnkptg48FWwrbdkK/ma4gy4L7wde4/76qYvj4/2D5s64wDPgLu6xveZhnk94T3fE1JTD7Z/vvG3qGe1Z1T5GjpsTvMJZnl9ArKpTMuq1uQ6oSPxERCZgcIKvZ+0wgt7WDrbVzgUHGmOQW9j1krZ1srZ2ckpLS/pFKtzJ1YCJRYV4en7+ditqGw59gjOv1K94C697ctz1nMfzzBPj0j/DKd+CuwfD0ZTDvL60XdmnSe4J7Hn72vtdNErIgbYyb5yciR0WJ32Esz3ELt5v8tW6DKnqKiEjgLASGGGMGGGPCgMuA15ofYIwZbIyb5GSMmQiEAUdYXlFkf+EhXm6ZM4S5Gws4/S9zmbuhDb3EI86FhH4w/z6w1s3Ne+R0wMC3P4LrPoApN0DeCph7lzvnUD1+6WPhxJ/C6f/X8v5hZ0D2F65HUUSOmBK/Q6isbWDD7nLGZSZA/mqI7OUmJYuIiASAtbYB+C7wLrAWeN5au9oYc6Mx5kb/YRcCq4wxy3AVQC+11qrAixyzm04axIs3ziAi1MNVj3zFT15cTmn1IdbO83hh+nchZyE8dja8/RMYfDJ851PoMwmyjnPFWL63Cq57Hy57GuIPmrLa7HoeN8SzV7+W9w890/Uabnz/2D5oRynb5ZbFEOkkVNXzEDbsLsdnYXSfeJi/1hV2USUpEREJIGvtW8BbB2x7sNnrPwJ/7Oi4pGeY1K8Xb956PPd+uJGH5m7h0w0FfHNaP742JoOBKTEHnzDhSvjk/9wae6f8Bmbc5hK45jweyJpy7MH1nuC+gN/wNoy79NivFyi1FW5o6/y/QXgsfHchRCUGOyoRJX6HUlBeC0B6bBjkr4XxVwQ5IhEREZHAigj1cvsZwzlzdDq/f3Mtf35vA39+bwMjMuI4e2wG54ztTd8k/xIOYdHwjZfdF+MHzstrbx4PDDnNLSrfUAchYYG935Hy+WDFs/DBHVCR5+YqbngH3vsFnP9AsKMT0VDPQymqrAMgze6GugoVdhEREZEeY2xmAs9/ZzoLfjaHX549kshQD3e9u545d3/CfR9upKHR5w7sMzHwSV+TYWdCbRnsmN8x92sLa2HLp/DwyfDfm9xw1us+gMuecuscLnsKNn8c7ChFlPgdSqG/x69XxSa3QYVdREREpIfJiI/kulkDePl/ZvL5T+dw1tgM7nl/Axc9uICthZUdG8zAk8AbDiuedz1s7a0kG774B6x+BXatcMM2W2MtbPkEHj0TnjgXyvPg/Add0pd1nDvmxJ9A4kB443tQV9X+8YocAQ31PITCilriIkIILVzhNqSOCG5AIiIiIkHUJyGSey+bwCkj0vjFf1fxtXs/4+dnjeDKqX0xHVEHISwaxlwMy/7jErNTfwODTj58DYaaMti13M25yxh38PE+Hyx+BN7/tRvl1VxMuis4E9fH9ebFZUJEHCx+3FUZje0NX/szTPjmwYvdh0bCOffC4+fAp3fCqb895h+ByNFS4ncIhZV1JMeGw+41kNDX/WchIiIi0sOdM643x/VP5McvLucX/13FS0tyuGp6P84cnUFEqDewNz/3bzBoNnz4W/jPhdD/eDjlDkgcAFVF7lFZCKU5kLsUcpdA4UbAX/w2YxxMvg7GXOQSyaLN8NqtsH2e61E844/QWAfFm92+4i1QssNda92b0OhGhBHXxyV8E6+CkPDW4x1wAkz4Bsy/H0Zf6O7fGmtdrE1TjA5MJFs7p6oYSra5CvSJA9v4g5SexnSnCtCTJ0+2ixYtarfrXfrPBVgLzzd+D3oNgCuebbdri4jI0TPGLLbWTg52HF1Fe7ePIk2stTy7MJuH5m5ha2ElidFhXDwpkyum9qVfUnRgb95QB4sfdYvFV7WylGVMGvSe6J+HOBH2bIVFj0D+GgiPh6Gnwdo3wBvqlp6Y8M1D9x5a6+5VsRuSBh864Wuuqhj+PhXiMuD6D11iWVcF9VVQWQA7vnCVUXcs2PdZPCGQMsIlihnjwBsC1Xv2PSqLoGS7S0qbeimNxyWZs38BsQFagszXCLuWuWGu9TUw7jJIGhSYe8lRaa2NVOJ3CKfc8ykjU8K4b8tZMPM2OOXX7XZtERE5ekr8jowSPwk0n88yf3MR//liO++v3U2jzzIyI45ZQ5KZOTiZKf0TiQwLUE9gTRksfxZsI0Ql7XvEprvE78BEzlqXaC18GNa+DoPmwNn3QFzvwMTXZNXL8OI1re/v1R/6zoB+0yEi3g1NzV3mkqzmiW1IpOvZi0p0I9IS+kJCPzccddvn8NVD4A2D47/v1lkMjdx3bkOtS1or8t2j0v+MgbSRrp5FfN99S3L4fFC+y/V+5q+FrXNh22dQU+r2G49bW3HgSTDpGhh+lkuifY2ux7V4i0tOa8qgrtIlqHUV7n4xaS45jc1wr30Nrqe2ssA9qoqhrtzNs6yrdI/6KmisB1+9S54bG9x6kqFRrnc0JNIl44117tj6avdsrfs7EZ3c7O9HBsRnQkKW+8xRSVCeCwXroGCDey7LdXHZRvez8DW4ezfUuZ7fhlq3LTzWf91EiEx0fz5hMa5HOSzKvQ6PhYgEiExwf77hcdBQ44oV1ZRBbbl7DD39mJePU+J3FMb/9j2uH1LFd9d/Cy78txsSICIiQafE78go8ZOOlFdaw0tLcvhsYwFLtpdQ1+gjzOthfN8Ejuvfi8n9EpnYtxfxUaHBDtUlBB21RrO1sOxplwiFRrlHWJRLAvpMdr2BrZ1XnudeRybsn8i1pGgzvP8rWPeGG46aPNQle+W7XE/h4YTFQMpwl5QUbYaG6n37Evq6JG/Aie7ha4Cl/4HFj0FZDkSnuhj3bHPJ14FCo10yhHVJHofIQ0Kj3VzKMP85YbEuufOGud5Qb5g/yWzwJ3jVLuaGGgiJcD+n0Ej3c27qqW0+FLj554J9SWyTSH9i7Q0F43UJpvG4+4aE73v2hEJtqUtUq4rd9WtKWv78bfHzvMP/GR9Ga22k5vi1or7RR0lVPYPtDrdBSzmIiIiIHFZ6fAQ3zx7MzbMHU1XXwMJte5i/qZAFW4p48NMtNPo2AzA0LYYTh6ZwyeQshqQFqY5CRyV9TfeacOXRnddaUtiSpEFuKYlt8+CTO10vUuJA6DfDFaqJTXM9bNEp+54b61wP1+5VsHu1692LSnLJXdJAN6w1aYgrbnOgE38Mx/8ANn3glq7wNbplNxIHQuIg15MZmeASME+zXt/Gen/PY55LbL1hrkcuOgWikts2v/FoWeuSs5JsKM12zxW7XQ9gyjCX+EYnH9s9GuqgvtIN6a2rcH8O1SXuvjUlrpcvNMr1BIbHuiQ3PNYlkgGixK8Vxf41/DLrt7o/gOQhQY5IREREpGuJCgvhxKEpnDg0BYCqugaWZZeweNseFm7fw2Pzt/Gvz7YyoW8Cl07O4uxxvYkJ16+n7aL/LLj6jbYdGxIGmZPd42h4vG6I4tDT236ON9Qlki0lk4FmjBuOGdkLMsYG5h4hYe4R2Ssw1z8K+pfVigL/Gn6p1ZtdF7m3EwxHEBEREenCosJCmDEomRmDXG9KUUUtryzdyXMLs/npyyu54/U1nDA0mTnDU5k9LJXUuAD2+oj0MEr8WlHk7/GLL98IA2cGORoRERGR7icpJpzrjx/IdbMGsDS7hJcW5/Dh2nzeXb0bgNF94jh7bG9uOH4gHk8HDssU6YaU+LWisLyWOCoJr8zV/D4RERGRADLGMLFvLyb27cXvz7es3VXOx+vz+WDtbu58ex2NPsvNswcHO0yRLs0T7AA6q6LKWkZ5trk3aaODGouIiIhIT2GMYWTvOG6ePZiXb5rBOeN6c/d76/liSytr9YlImyjxa0VhRR2zQ1ZiPSHQd1qwwxERERHpcYwx/OGCMfRPiuaWZ5burcEgIkdOiV8rCitqOcm7EpM11ZVXFREREZEOFxMewt+vnEhZdT3fe24pjb7uswa1SEdS4teKutLdDLVbYdCcYIciIiIi0qONyIjjd+eN5vNNRdz34cZghyPSJSnxa0W/PV+6F4NPDm4gIiIiIsLFkzO5cGIm9320kbkbCoIdjkiXo8SvFaNrFlLhjYf0ccEORURERKTHM8bwu/NHMSQ1huufWMTTX+7AWg37FGkrJX4t8DU2MrlxOTsSpoJHPyIRERGRziAqLIRnvj2NqQMS+X+vrOSHzy+nqq4h2GGJdAnKalpQuWMZKaaUgrRZwQ5FRERERJpJignnsWum8L1ThvDKsp2c//fP2ZRfEeywRDo9JX4tqF3/PgDVfU8MciQiIiIiciCvx/C9U4byxLVTKKyo47z75/HwZ1uoqW8MdmginZYSvxaEbvuEtb4s4pIzgx2KiIiIiLTi+CEpvHnrLCb268Xv31zL7D9/wjNf7aC+0Rfs0EQ6HSV+B6qrJHb3Iub6xpIUEx7saERERETkEDLiI3nyuqk8/e2pZMRH8LOXV3LKPZ/y8pIcahvUAyjSRInfgbbNw2PrmesbS3JMWLCjEREREZE2mDEomZdumsEjV08mKiyEHzy/nGn/9yF3vL6adXllwQ5PJOhCgh1Ap7PpQ+o94Sy2w0iIUuInIiIi0lUYY5gzPI2Thqby2aZCnl+YzX++2M6jn29jbGY8F0/K5GtjMjSqS3okJX4H2vwhW6InEOOJxesxwY5GRERERI6Qx2M4cWgKJw5Nobiyjv8u3cnzi7L55aur+c3ra5g1OJlzx/XmtFFpxEaEBjtckQ6hxK+5PduhaBNLk04j2avePhEREZGuLjE6jGtnDeCamf1Zl1fOa8tzeW1ZLj98YTnhr3gY0yeekb3jGNU7jpEZ8QxKjSbkgHWcQ70GY9QhIF2bEr/mNn8EwOd2LMkaAiAiIiLSbRhjGJERx4iMOH5y+jCW7CjhrZW7WJFTwkuLc3hiQeuFYJJjwjltVBpnjEpn+qAkQr0qkyFdjxK/5jZ/CHGZLKtOZWKqevxEREREuiNjDJP69WJSv14A+HyW7D1VrMktY0th5X7HWmtZm1fOf5fu5OkvdxAXEcLJI9JIjQunsdHSaC2NPktdg489VXUUV7rHnqp6RvWO4/4rJhIfqeGkEnwBTfyMMWcA9wJe4GFr7Z0H7P8xcGWzWEYAKdba4sOd2+58Ptg+H4afRdGievX4iYiIiPQQHo+hX1I0/ZKiWz2mpr6ReRsLeWd1Hh+ty6eytgGvx+x9hHo99IoKJTE6jGHpscSEh/DK0p1c+fAXPHntVHpFq1NBgitgiZ8xxgv8HTgVyAEWGmNes9auaTrGWnsXcJf/+HOA7/uTvsOe2+48Hrh1KdWVZVTNX6HET0RERET2igj1csrINE4Zmdbmc84cncF3/rOYy//1Bf+5fqp+v5SgCuQA5SnAJmvtFmttHfAscN4hjr8ceOYoz20fEfEUmiQAkrSGn4iIiIgcg9nDU3nkW8exraiSyx76gvyymmCHJD1YIBO/PkB2s/c5/m0HMcZEAWcALx3pue2toKIWgBR9IyMiIiIix2jWkGQev2YKu0qqueSfC8gtqQ52SNJDBTLxa6nmrW3l2HOAz621xUd6rjHmBmPMImPMooKCgqMIc39FFXWAevxEREREpH1MHZjEE9dNpaiijosfXMDWAwrIiHSEQCZ+OUBWs/eZQG4rx17GvmGeR3SutfYha+1ka+3klJSUYwjXKfT3+GkMtoiIiIi0l0n9evHMDdOorm/k4gcXsHZXWbBDkh4mkInfQmCIMWaAMSYMl9y9duBBxph44ETg1SM9NxAKy13il6jKSyIiIiLSjkb3ief570wn1Gu49J8LWLx9z377N+VX8NcPNvC3DzdSUdsQpCiluwpYVU9rbYMx5rvAu7glGR6x1q42xtzo3/+g/9CvA+9ZaysPd26gYm2uqLKO2IgQIkK9HXE7EREREelBBqfG8MKN0/nGw1/yjYe/5I8XjWXnnmpeW57L2l1lGAPWwhNfbOenZwzn6xP64PG0NAtK5MgYa1ubdtf1TJ482S5atOiYrnHz00tYk1vGxz86qX2CEhGRdmeMWWytnRzsOLqK9mgfRaR95ZfXcNW/v2JdXjkAE/omcO643pw1JoOdJdX85vU1LM8uYULfBH5zzijGZSUEN2DpMlprIwO6gHtXVFRRS7IKu4iIiIhIAKXGRvDcDdN5e9UuZg5OJisxat++uAheuWkGLy3J4Y/vrOf8Bz5nbGYCE7ISGO9/9EuKwhj1BErbKfE7QGFFHYNTYoIdhoiIiIh0c/FRoVw2pW+L+zwew8WTszhjdDqPzNvG/M2FPL8om8fmbwMgOsyLx2Pw+SyN1uLzwdD0GO6/fCL9k6M78FNIV6HE7wBFFbVMG5gY7DBERERERIiNCOW2U4Zw2ylDaGj0sTG/gmXZJWzYXY61EOIxeP1zAJ9blM2598/j/ismcsLQY692L92LEr9m6ht97Kmq11IOIiIiItLphHg9jMiIY0RGXIv7r5zajxueXMTVj37Fz84cwfXHD9BwUNlLiV8zxZVNi7cr8RMRERGRrqVvUhQv3TSDH72wnP99ay1rdpVx8aRMCivrKKqopbiyjsraRoZnxDKxbwIDk2NUMbQHUeLXTNPi7Skq7iIiIiIiXVB0eAh/v2Ii93+8iXve38ArS3fu3ecxEBbioabeB0BsRAjjsxIYlhZLQlQocZGhxEWEEhcZwtC0WDJ7RbV2G+mClPg1U1ihHj8REQkuY8wZwL24dWwfttbeecD+K4Hb/W8rgJustcs7NkoR6cw8HsOtJw/h1JFplFTVkxwTRlJMOPGRoRhgS2ElS3fsYWl2CUu272HhtuK9yWBzWYmRTB+YxPRBSRzXP5HkmHCtdd2FKfFrpsjf46c5fiIiEgzGGC/wd+BUIAdYaIx5zVq7ptlhW4ETrbV7jDFnAg8BUzs+WhHp7FqbCzg4NYbBqTFcPDlr77a6Bh/lNfWU1TSwp6qO5dklLNhcxLurd/P8opy9x4V5PcREhBAbEUJCZCjp8RGkx0WQHh9Jenw4Q9NiGZYWS4jXE/DPJ0dGiV8zTUM9kzTUU0REgmMKsMlauwXAGPMscB6wN/Gz1s5vdvwXQGaHRigi3VJYiIekmHCSYsIZQDQT+/bimpkDaPRZ1u4qY2l2CWXV9ZTXNFBeU09FbQPFlXVsKahk/uYiymsa9l4rMtTLmMx4JvRNYHxmAlmJUfRJiCQhKnRvsZm6Bh9bCytZl1fGxt0V5JXVsKeyjj1VdeypqqeuwccPTxvKBRP1X1x7UeLXTFFFHWEhHmLD9WMREZGg6ANkN3ufw6F7864D3g5oRCLSo3k9htF94hndJ/6Qx1XWNrCrtJrVuWUs3VHCsuwSHpm3lfpGu/eYiFAPvRMi8RrD1sJKGnx27z1SY8PpFRVGYnQYfXpFkV1cxQ+eX86y7BJ+cdZIwkIC04NYU9/II59v5akvdvDt4wfwrRn9u20lVGU4zRRU1JIcHdZt/7BFRKTTa6kBsi1swxgzG5f4zWpl/w3ADQB9+7a8QLSISHuJDg9hcGosg1NjOW98H8AlVRt3V7CzpIrckhpyS6rZVVpDbYOPU0emMSw9lmHpsQxIjiY8ZP+5gw2NPv74zjr+9dlWVu0s5YErJ5EeH9Fu8fp8ltdX5PKnd9azs6SafklR/Ob1NSzNLuEPF4whKqz7pUnd7xMdg8KKOpJjNb9PRESCJgfIavY+E8g98CBjzFjgYeBMa21RSxey1j6Em//H5MmTW0weRUQCKcI/5HNM5qF7C1sS4vXw87NGMj6rFz9+cTln/20evzpnJMkxYRgMxoDHGJJiwuibGEXoAXMKd5ZU89mGAuZuLGB7URWpseGkx0eQFhdBUkw4Ly7KZnlOKaN6x3HXxWOZNiCJBz7ZxN3vb2DdrnIe/OYkBiRH771eRW0DK3NKqaxtIDo8hOhwL1FhIYSHeNhZUs22wkq2FlaypbCSvNIaqusbqW1opLbeR019I16PceeFuXNjIkLpkxDJgOQo+idFMyA5mqzEqIAWz1Hi10xRRS1pce33TYKIiMgRWggMMcYMAHYClwFXND/AGNMXeBn4prV2Q8eHKCLScc4am8HQtBi+8+Ribn1maYvHeD2GvolRDEiOJiUmnMU79rApvwKA9LgIhqXHkl9ey4qcUor863anx0Vw98Xj+PqEPnvXMvzunCGMzUzgtmeXcu7f5nHjSYPI2VPF0h0lbNhdju8wX6GFhXjon+TmM0aGeQkP8RIR6iHM66HRWqpqG6mobaCqrpGSqjpW5pSwp6p+7/nGwLJfnUZ8ZGg7/OQOpsSvmcKKWka2Uv1IREQk0Ky1DcaY7wLv4pZzeMRau9oYc6N//4PAr4Ak4AH/1IQGa+3kYMUsIhJoQ9JiefPW41mVW0qjz2ItWGvxWdhdVsO2ItfTtrWgkmXZJYzuE89lx2VxwtAUhqTG7DeNq7ahkYLy2laXpjhhaAqv3zKL/3lqCXe9u564iBDG9+3F6aPSGd83gaToMCprG6msbaCyroHaeh8ZCREMSI4mIz4Sr+fIpoyVVtWztaiSbYWV7CypDljSB2Cs7T6jPyZPnmwXLVp01Odvyi8nzOulb5IWqxQR6cyMMYuV7LTdsbaPIiI9TUOjj7yyGnrHR+7tEewqWmsj1ePXzODU2GCHICIiIiIiQRbi9ZDZq3t1BmllRRERERERkW5OiZ+IiIiIiEg3p8RPRERERESkm1PiJyIiIiIi0s0p8RMREREREenmlPiJiIiIiIh0c0r8REREREREujklfiIiIiIiIt2cEj8REREREZFuTomfiIiIiIhIN2estcGOod0YYwqA7cd4mWSgsB3CCYauGntXjRsUe7B01di7atzQ+WLvZ61NCXYQXYXaR8UeJF019q4aNyj2YOlssbfYRnarxK89GGMWWWsnBzuOo9FVY++qcYNiD5auGntXjRu6duzSPrry3wHFHhxdNfauGjco9mDpKrFrqKeIiIiIiEg3p8RPRERERESkm1Pid7CHgh3AMeiqsXfVuEGxB0tXjb2rxg1dO3ZpH13574BiD46uGntXjRsUe7B0idg1x09ERERERKSbU4+fiIiIiIhIN6fEz88Yc4YxZr0xZpMx5qfBjudQjDGPGGPyjTGrmm1LNMa8b4zZ6H/uFcwYW2OMyTLGfGyMWWuMWW2Muc2/vVPHb4yJMMZ8ZYxZ7o/7Dv/2Th13c8YYrzFmqTHmDf/7LhG7MWabMWalMWaZMWaRf1tXiT3BGPOiMWad/+/89M4euzFmmP9n3fQoM8Z8r7PHLYGlNjLwumr7CF2/jeyq7SN03TayK7aP0PXbSCV+uH/wwN+BM4GRwOXGmJHBjeqQHgPOOGDbT4EPrbVDgA/97zujBuCH1toRwDTgZv/PurPHXwvMsdaOA8YDZxhjptH5427uNmBts/ddKfbZ1trxzUold5XY7wXesdYOB8bhfv6dOnZr7Xr/z3o8MAmoAl6hk8ctgaM2ssN01fYRun4b2ZXbR+iabWSXax+hG7SR1toe/wCmA+82e/8z4GfBjuswMfcHVjV7vx7I8L/OANYHO8Y2fo5XgVO7UvxAFLAEmNpV4gYycf8RzQHe6Ep/Z4BtQPIB2zp97EAcsBX/XOquFHuzWE/7/+3dTahd1R2G8edtjBI/SsEvpFHTYHCgWA2SQS0i6qiIExEjFkSEghS0Az9aJ4LUQScliKVg1aLUKrZVcSSKYmlVVJRYtTqSUIMxiYiKpYjEfwd7pR4kF2/Sc+8+a/P84LDXXjcc3hMOvFl7r30DPN9bbl9z/x7YkeN8hu76sWXsqiN77seWr7uOnEI/tozddaR3/AbfBd6bOd/Z5npyYlXtAmjHE0bO842SbADOAV6ig/xtK8h2YA/wdFV1kbvZBtwMfDkz10v2Ap5K8mqSn7S5HrJvBPYCv29biO5JchR9ZN9vK/BQG/eUW/NlR66y3voRuu7IbfTbj9BnR06hH6HDjnThN8gB5vx1pysoydHAX4CfVdWnY+dZjqraV8Ot/fXAliRnjhxpWZJcAuypqlfHznKIzquqzQzbzH6a5PyxAy3TYcBm4LdVdQ7wbxZ168cBJDkcuBT409hZNDo7chX12I/QZ0dOoB+hz47suh+h34504TfYCZw8c74eeH+kLIdqd5KTANpxz8h5lpRkLUOpPVhVj7bpbvJX1cfAcwzPkPSQ+zzg0iQ7gIeBC5P8gT6yU1Xvt+Mehn30W+gj+05gZ7vqDfBnhqLrITsM/4h4rap2t/Necmv+7MhV0ns/Qncd2XU/Qrcd2Xs/Qqcd6cJv8AqwKcn32gp+K/DEyJkO1hPA1W18NcOzAQsnSYB7gber6tczP1ro/EmOT/KdNl4HXAy8w4LnBqiqX1TV+qrawPDdfraqfkwH2ZMcleSY/WOG/fRv0kH2qvoAeC/J6W3qIuCfdJC9uZKvtrBAP7k1f3bkKui1H6Hfjuy5H6HfjpxAP0KnHel/4N4k+RHDPu81wH1Vdce4iZaW5CHgAuA4YDdwG/A48AhwCvAv4PKq+mikiEtK8kPgb8AbfLWf/laG5xgWNn+Ss4D7Gb4f3wIeqarbkxzLAuf+uiQXADdW1SU9ZE+ykeEKJgxbQ/5YVXf0kB0gydnAPcDhwLvANbTvDwucPcmRDM90bayqT9pcF3/nWhl25MrrtR9hGh3ZWz9C3x3Zaz9C3x3pwk+SJEmSJs6tnpIkSZI0cS78JEmSJGniXPhJkiRJ0sS58JMkSZKkiXPhJ0mSJEkT58JPWhBJ9iXZPvP6+Rzfe0OSN+f1fpIkrRb7UZqPw8YOIOl//lNVZ48dQpKkBWM/SnPgHT9pwSXZkeRXSV5ur9Pa/KlJnknyj3Y8pc2fmOSxJK+31w/aW61J8rskbyV5Ksm60T6UJEn/J/tROjgu/KTFse5rW1mumPnZp1W1BbgL2Nbm7gIeqKqzgAeBO9v8ncBfq+r7wGbgrTa/CfhNVZ0BfAxctqKfRpKk+bAfpTlIVY2dQRKQ5LOqOvoA8zuAC6vq3SRrgQ+q6tgkHwInVdUXbX5XVR2XZC+wvqo+n3mPDcDTVbWpnd8CrK2qX67CR5Mk6ZDZj9J8eMdP6kMtMV7qzxzI5zPjffiMrySpf/ajtEwu/KQ+XDFzfLGNXwC2tvFVwN/b+BngOoAka5J8e7VCSpK0yuxHaZm8oiEtjnVJts+cP1lV+39l9RFJXmK4WHNlm7seuC/JTcBe4Jo2fwNwd5JrGa5cXgfsWunwkiStEPtRmgOf8ZMWXHuG4dyq+nDsLJIkLQr7UTo4bvWUJEmSpInzjp8kSZIkTZx3/CRJkiRp4lz4SZIkSdLEufCTJEmSpIlz4SdJkiRJE+fCT5IkSZImzoWfJEmSJE3cfwFushOGTCrLfgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 1080x360 with 2 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "def plotmodelhistory(history): \n",
-    "    fig, axs = plt.subplots(1,2,figsize=(15,5)) \n",
-    "    \n",
-    "    # summarize history for accuracy\n",
-    "    axs[0].plot(history.history['accuracy']) \n",
-    "    axs[0].plot(history.history['val_accuracy']) \n",
-    "    axs[0].set_title('Model Accuracy')\n",
-    "    axs[0].set_ylabel('Accuracy') \n",
-    "    axs[0].set_xlabel('Epoch')\n",
-    "    axs[0].legend(['train', 'validate'], loc='upper left')\n",
-    "    \n",
-    "    # summarize history for loss\n",
-    "    axs[1].plot(history.history['loss']) \n",
-    "    axs[1].plot(history.history['val_loss']) \n",
-    "    axs[1].set_title('Model Loss')\n",
-    "    axs[1].set_ylabel('Loss') \n",
-    "    axs[1].set_xlabel('Epoch')\n",
-    "    axs[1].legend(['train', 'validate'], loc='upper left')\n",
-    "    plt.show()\n",
-    "\n",
-    "\n",
-    "plotmodelhistory(history)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "5ca0c9f5",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "100/100 [==============================] - 0s 3ms/step - loss: 0.2771 - accuracy: 0.9052\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[0.27708700299263, 0.9051666855812073]"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "model.evaluate(x_test, y_test, batch_size=60)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "c9c73c11",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def sample_incorrect(model, test, labels, num_points=5):\n",
-    "    \"\"\"\n",
-    "    Takes the model, test, labels and randomly samples some examples from incorrectly classified data\n",
-    "    \"\"\"\n",
-    "    \n",
-    "    incorrects = np.nonzero((model.predict(x_test) > 0.5).astype(\"int32\").reshape((-1,)) != y_test)[0]  \n",
-    "    rsample = random.sample(list(incorrects), num_points)\n",
-    "    output = []\n",
-    "    for choice in rsample:\n",
-    "        output.append(test[choice])\n",
-    "    return output"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "e90bbe6d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 1080x1080 with 25 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "rows=5\n",
-    "columns=5\n",
-    "fig=plt.figure(figsize=(15,15))\n",
-    "\n",
-    "\n",
-    "final = sample_incorrect(model, x_test, y_test, num_points=rows*columns)\n",
-    "\n",
-    "for i in range(1, columns*rows+1):\n",
-    "    img=final[i-1]\n",
-    "    fig.add_subplot(rows,columns,i)\n",
-    "    plt.imshow(img)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a30139de",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b0441be0",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.9.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}