diff --git "a/EDA.ipynb" "b/EDA.ipynb" new file mode 100644--- /dev/null +++ "b/EDA.ipynb" @@ -0,0 +1,564 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n", + "\n", + "\n", + "import cv2\n", + "import numpy as np\n", + "import string\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import tensorflow as tf\n", + "tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)\n", + "import tensorflow.keras.backend as K\n", + "\n", + "from tensorflow import keras\n", + "from tensorflow.keras import layers\n", + "\n", + "from tensorflow.keras.preprocessing.sequence import pad_sequences\n", + "from tensorflow.keras.layers import Dense, Reshape, BatchNormalization, Input, Conv2D, MaxPool2D, Lambda, Bidirectional\n", + "from tensorflow.compat.v1.keras.layers import CuDNNLSTM\n", + "from tensorflow.keras.models import Model\n", + "from tensorflow.keras.optimizers import *\n", + "from tensorflow.keras.utils import to_categorical, Sequence\n", + "from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping\n", + "from tqdm import tqdm\n", + "from collections import Counter\n", + "from PIL import Image\n", + "from itertools import groupby\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "file_path = \"words_new.txt\"\n", + "with open(file_path) as f:\n", + " lines = f.readlines()\n", + "\n", + "label_raw = lines[18:] # Skipping the initial lines that are comments\n", + "\n", + "image_texts = []\n", + "image_paths = []\n", + "default_path = \"iam_words/words/\"\n", + "for label in label_raw:\n", + " parts = label.strip().split() # Using strip() to remove any leading/trailing whitespaces\n", + " if len(parts) < 9: # Check if the line has fewer parts than expected\n", + " print(f\"Skipping line due to unexpected format: {label}\")\n", + " continue # Skip this iteration and move to the next line\n", + " if parts[1] == \"ok\":\n", + " image_texts.append(parts[-1])\n", + " image_id = parts[0]\n", + " subdir1 = image_id.split(\"-\")[0]\n", + " subdir2 = f\"{subdir1}-{image_id.split('-')[1]}\"\n", + " image_paths.append(os.path.join(default_path, subdir1, subdir2, f\"{image_id}.png\"))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "image_texts=image_texts\n", + "image_paths=image_paths" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "word_lengths = [len(word) for word in image_texts]\n", + "plt.figure(figsize=(10, 6))\n", + "plt.hist(word_lengths, bins=range(1, max(word_lengths) + 1))\n", + "plt.title('Distribution of Word Lengths')\n", + "plt.xlabel('Word Length')\n", + "plt.ylabel('Frequency')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from collections import Counter\n", + "word_counts = Counter(image_texts)\n", + "common_words = word_counts.most_common(10)\n", + "words, counts = zip(*common_words)\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.bar(words, counts)\n", + "plt.title('Top 10 Most Common Words')\n", + "plt.xlabel('Words')\n", + "plt.ylabel('Frequency')\n", + "plt.xticks(rotation=45)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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bVa1WbZVzuexdMq7GsSMiIiIiIiIiIqLtiSMiiIiIiIiIiIiIiIiobRiIICIiIiIiIiIiIiKitmEggoiIiIiIiIiIiIiI2oaBCCIiIiIiIiIiIiIiahsGIoiIiIiIiIiIiIiIqG0YiCAiIiIiIiIiIiIiorZhIIKIiIiIiIiIiIiIiNqGgQgiIiIiIiIiIiIiImobBiKIiIiIiIiIiIiIiKhtXHYL+nw+W+UKhcKWliuVSrbKNRoNW+VcLntv2W45O2q1mq1yHR324kJer9dWuWq1aqvc6dOnbZWLx+O2ygUCAVvlQqGQrXL1et1WOYfDsaXPZ+ccsHve2d03u+y+rt1zyu122ypn91x2Op22yhEREREREREREdHOxxERRERERERERERERETUNgxEEBERERERERERERFR2zAQQUREREREREREREREbcNABBERERERERERERERtQ0DEURERERERERERERE1DYMRBARERERERERERERUdswEEFERERERERERERERG3DQAQREREREREREREREbUNAxFERERERERERERERNQ2LrsFq9XqlpbL5/O2yjkcji193VqtZqtcIBDYtEwul7P1XHY1Gg1b5Twej61ylUrFVrnz58/bKjc9PW2rXH9/v61ydt+H3++3Vc7uueJ0Om2V28rXtPvZ2n0+u+W22lYeOyIiIiIiIiIiIro+cEQEERERERERERERERG1DQMRRERERERERERERETUNgxEEBERERERERERERFR2zAQQUREREREREREREREbcNABBERERERERERERERtQ0DEURERERERERERERE1DYMRBARERER0TpPPPEEPvShDyGZTF7tXSEiIiIiomscAxFERERERLTOE088gd/93d9lIIKIiIiIiF40BiKIiIiIiIiIiIiIiKhtXHYL1ut1W+UajYatcrlczla5YrFoq5xddvevWq1uWqZWq9l6LofDYauc0+m0Vc7ue7D7maXTaVvlzp49a6vcPffcY6uc3f2zW66jw15cze7nYec4b+VzXc7zEREREbXThz70Ifzu7/4uAGB8fFz9fnp6GiMjI/jwhz+MT3ziE5ifn8euXbvw4IMP4oMf/CC8Xu/V2mUiIiIiItrGbAciiIiIiIjo+vDWt74V586dw6OPPoo//uM/Rl9fHwCgv78fv/ALv4BPfvKTeNvb3obf/M3fxI9//GN8+MMfxunTp/GFL3zhKu85ERERERFtRwxEEBERERGRxa233oo777wTjz76KN7ylrdgbGwMAPDcc8/hk5/8JH7hF34B//t//28AwPve9z4MDAzgD/7gD/Dtb38br371q6/inhMRERER0XbENSKIiIiIiMiWr3zlKwCA97///Zbf/+Zv/iYA4Mtf/vIV3yciIiIiItr+GIggIiIiIiJbZmZm0NHRgQMHDlh+PzQ0hK6uLszMzFylPSMiIiIiou2MgQgiIiIiIrosDofjau8CERERERFdQxiIICIiIiKidZoFG/bu3Yt6vY6JiQnL71dWVpBMJrF3794rtXtERERERHQNYSCCiIiIiIjWCQaDAIBkMql+94Y3vAEA8LGPfcxS9o/+6I8AAG984xuvyL4REREREdG1xXW1d4CIiIiIiLafu+66CwDwgQ98AO985zvhdrvx5je/Ge9973vxt3/7t0gmk3jlK1+JJ598Ep/85Cfxlre8Ba9+9auv8l4TEREREdF2xEAEERERERGtc/fdd+P3fu/38Nd//df46le/inq9junpafyf//N/sG/fPnziE5/AF77wBQwNDeF3fud38MEPfvBq7zIREREREW1Tjkaj0bBTMJ/P23rCtbU1W+X+5m/+xla5z372s7bK2VWpVGyVs3NY7D5XR4e9GbB8Pp+tck6n01a5er2+peVuvvlmW+U+8pGP2Co3Ojpqq5zX67VVzu5x2crFFa/WQo21Ws1WObvHhIiIiIiIiIiIiKhduEYEERERERERERERERG1DQMRRERERERERERERETUNgxEEBERERERERERERFR2zAQQUREREREREREREREbcNABBERERERERERERERtQ0DEURERERERERERERE1DYMRBARERERERERERERUdu4rvYOEBEREdH2Va1WbZdtNBqW7VKpdFnPvbS0ZNn+9re/rX5+7rnnLI/t37/fsv22t73Nsj08PLzha7tc12Y1+FrdbyIiIiIiur7ZbsnU63Vb5Wq1mq1ymUzGVjmPx2OrnN1Gss/ns1XOzvswG9utbNYIFx0d9gaoBAIBW+XsHhO75WZmZmyVm52dtVVuaGjIVjmn02mrnMPhsFXO7nG2W+5qsPt9tHvsiIiIiIiIiIiIiNpl+/a0EhERERERERERERHRNY+BCCIiIiIiIiIiIiIiahtOMktEREREW8KcttKc6jKfz1u2z58/b9l+7LHHLNvnzp1TP8diMctj5jSfAwMDlu3Xv/71lu1wONxqt4mIiIiIiKjNOCKCiIiIiIiIiIiIiIjahoEIIiIiIiIiIiIiIiJqGwYiiIiIiIiIiIiIiIiobbhGBBERERHZZq4DUalUWpYtlUqW7e985zuW7S996UuW7cXFRcu2vsaE+TpLS0uW7ccff9yyfejQIcv2kSNHLNv6+3A4HOauExERERER0RbiiAgiIiIiIiIiIiIiImobBiKIiIiIiIiIiIiIrlOf+MQn4HA44HA48P3vf3/d441GA6Ojo3A4HHjTm950FfaQdgLbUzOZw/BbPqHL3lN2dXXZKlev17e0nNPptFXOzvvt6LAXx6lWq7bKeTweW+Xy+bytcnanGdCnPdhIMpm0Ve7s2bO2yt166622ynm9Xlvl7J4Ddt+vHW6321Y5u/tm95yyex7bZfeYbPV1gIiIrj1m/UK/5heLRctj8/Pzlu0vfvGLlu3JyUnLtlkX0u+f5nMXCgXLtlk/euKJJyzb5lRN+vswX9fu/ZiIiIiIaCfx+Xx45JFH8PKXv9zy++9+97uYn5+33UdH1AxbWURERERERERE/79HHnkEH/vYx672bhARXXFveMMb8NnPfnZdUvUjjzyCu+66C0NDQxv+fbVaRblcbucu0jWMgQgiIiIiIiIiov8fAxFEdL1617vehVgshq9//evqd+VyGZ/73Ofw4IMPWspeuHABDocDf/AHf4CPfexj2L9/P7xeL06dOnWld5uuEZw/hYiIiIiIiIiIiOg6NzY2hvvuuw+PPvooXv/61wMAHn/8caRSKbzzne/En/7pn677m49//OMoFov4xV/8RXi9XvT09Fzp3aZrBAMRRERERNTSZusD6UOvK5WK5bG5uTnLdiwWs2ybayiZ2xutYWQO+TbXdTh+/LhlOxqNWrZHRkbUz3bX1SIiop0hk8ngv/7X/4ovfvGLWFpaQmdnJ2677TZ85CMfwfvf/35897vfBXDp/rB3715cuHABALC6uorf+Z3fwWOPPYZUKoUbbrgB73//+/He975XPf+FCxcwPj6O3//934fT6cTHPvYxrK6u4p577sFf/MVf4JZbbrni75mIyK4HH3wQv/M7v4NCoQC/34+HH34Yr3zlKzE8PNy0/Pz8PCYnJ9Hf33+F95SuNQxEEBEREREREdF14z/+x/+Iz33uc/jVX/1V3HTTTYjFYvj+97+P06dP4wMf+ABSqRTm5+fxx3/8xwCAUCgEACgUCnjVq16FyclJ/Oqv/irGx8fx2c9+Fg899BCSySR+/dd/3fI6n/rUp5DJZPArv/IrKBaL+JM/+RP8xE/8BE6cOIHBwcEr/r6JiOx4+9vfjt/4jd/AY489hte97nV47LHHmo6EEP/23/5bBiHIFgYiiIiIiIiIiOi68eUvfxn/4T/8B/zhH/6h+t1v//Zvq593796NRCKBn//5n7f83d/+7d/i9OnT+PSnP413v/vdAC4GNV75ylfiv/yX/4J//+//PcLhsCo/OTmJiYkJ7N69GwDwute9Dvfeey8+8pGP4I/+6I/a+RaJiF6w/v5+vOY1r8EjjzyCfD6PWq2Gt73tbS3Lj4+PX8G9o2sZF6smIiIiIiIioutGV1cXfvzjH2NxcfGy/u4rX/kKhoaG8K53vUv9zu1249d+7deQzWbVlE7iLW95iwpCAMA999yDe++9F1/5ylde3BsgImqzBx98EI8//jj++q//Gq9//evR1dXVsqzf779yO0bXNI6IICIiIqKWLmf9BHM9iWAwaNl2uaxVz2KxaNmuVqsbltf5fD7LtrlmxPz8vGX7zJkzlu2+vj71s9vttjzmdDpbvu5W22wNDq5fQUS09T760Y/ive99L0ZHR3HXXXfhDW94A97znvdg3759G/7dzMwMDh48uG5dohtvvFE9rjt48OC65zh06BD+4R/+4UW+AyKi9vrZn/1Z/NIv/RJ+9KMf4TOf+czV3h3aITgigoiIiIiIiIiuG29/+9sxNTWFP/uzP8Pw8DB+//d/HzfffDMef/zxq71rRETbQigUwl/91V/hQx/6EN785jdf1t9Go1GcOXMG+Xy+TXtH1yrbIyLq9bqtcmZmQCt2F2baKBNOZ2bQtVIoFGyVM7PsmrGboWb3PdjNvrP7WdRqtS0tZ/ezXVtbs1XO7mdml93Pw265zTIUAfufxVZnVto9dnbfq93PloiIiIiIaCfYtWsX3ve+9+F973sfVldXceedd+J//I//gde//vUt21F79+7F8ePHUa/XLW0oGXW3d+9eS/mJiYl1z3Hu3DmMjY1t3RshImqT9773vS/o7/78z/8cv/u7v4tvf/vbeNWrXrW1O0XXNPY+EhEREREREdF1oVarIZVKWX43MDCA4eFhlEolABenFjTLAMAb3vAGLC8vW6YpqVar+LM/+zOEQiG88pWvtJT/4he/iIWFBbX95JNP4sc//jFe//rXb+VbIiIiuiZwjQgiIiIiaskcOWmOotNHfpojAPUFOgFgaGjIsm3OpW2uGaHzeDwb7ocpnU5bto8dO2bZvu+++9TPm73Hdq7TwDUgiIiurEwmg5GREbztbW/DbbfdhlAohG984xt46qmn8Id/+IcAgLvuuguf+cxn8P73vx933303QqEQ3vzmN+MXf/EX8Td/8zd46KGH8Mwzz2BsbAyf+9zn8IMf/AAf+9jHEA6HLa914MABvPzlL8cv//Ivo1Qq4WMf+xh6e3vx27/921fjrRMRtfTQQw/hoYce2rTchQsX1M9jY2NNZxP50Ic+hA996ENbt3O0YzAQQURERERERETXhUAggPe973342te+hs9//vOo1+s4cOAA/vIv/xK//Mu/DAB43/veh2PHjuHjH/84/viP/xh79+7Fm9/8Zvj9fnznO9/Bf/7P/xmf/OQnkU6nccMNN+DjH/940w6897znPejo6MDHPvYxrK6u4p577sGf//mfY9euXVf4XRMREV19DEQQERERERER0XXB4/Hgox/9KD760Y+2LBMMBvHwww83fWxgYAB/93d/Z/v13v/+9+P973//Ze8nERHRTsM1IoiIiIiIiIiIiIiIqG04IoKIiIiIWtpsLQZ9jQO32215rLOz07J9zz33WLafffZZy7a5xoQ+52y1Wt1wv8z5ac11H2ZnZy3buVxO/RwMBnE56vX6hvtCREREREREVmw1ERERERERERERERFR23BEBBERERERERHRFhkbG1s3Uo+IiOh6xxERRERERERERERERETUNrZHROjz/27EnI+3FXMO4Va8Xq+tcuZcva2Y8wu/2Oezw+57KJfLtsq5XPY+NrvvwW65QqFgq9w3vvENW+Ve+9rX2irn9/ttlevq6rJVzu65bOdcsXu+2z3G5tzYrWz199FuObvnMhER7RzmPce8p11OxmdfX59le3x83LJ9/vz5lq/t8Xgsj5n3aXM/isWiZTuRSFi24/G4+rm7u9vy2OXe77hmBBEREe1ElUoFjUYD5XIZ9XodxWIR1WoV0WgU6XQaZ8+exdmzZwFcrLeNjIzgvvvuQygUQn9/P1wuFzweDzo6OtDR0WG7L4OILo/D4bDdp3g1cWomIiIiIiIiIiIisigUCqjX60gmkyiVSlhaWkI6ncb8/DzW1tawvLyM5eVlVT6VSsHlcqGvrw+33norgsEgwuEw3G43HA7HukBEo9FgcILoOsJABBEREREREREpjUYDuVwO+XwemUwG09PTWF5extGjR7G4uIhEIoGBgQHs3bsXd955J2677Tb09fUhEAiwU/Ea5XQ6+dnROtVqFdVqFdlsFoVCAdFoFIlEAouLi1hbW0M8HkcqlVLlPR4PVldX4XA4kM/n4XQ6EQgErolMbSJqPwYiiIiIiMg2s5NCb1iaj5nTKx48eNCyPTIyYtmemJiwbF/OVJnmFJeBQMCybU4xqZevVCq2XwdY/z7NvzenkSIiutY0Gg0UCgXEYjEsLi7iySefxPz8PM6cOYNKpYJqtYpKpYJSqYRarYb+/n54vV74fL5rbvoVfWq/a2m/ia6EeDyOYrGIZ555BtFoFDMzM0gmk8hmsygWi6hUKqjX66jVaqhWq1hbW8Pzzz+PlZUVBINB9Pb24pZbbkEoFEJHR4cKeOnfNfkO8vtHtPMxEEFERERERERESr1eRzQaxZkzZ3D06FGcPn0aqVRKBXU7OjpQKpWQTCYxMzODM2fOoFqtIhwOw+PxwOVyXTOditfKfhJdDTIyamFhAUtLS5iZmUEqlVqXLCIjJ/L5PCqVCmq1GlZWVgAApVIJfr8f9Xr9mpnHnojag4EIIiIiIiIiIlLq9ToSiQRWVlYwNzeHWCyGQqGARqOBjo4O1Ot11Ot1FAoFJJNJrKysoLOzE5VKBU6nk9P8EO0Qs7OzKBQKmJ+fx/LyMtLpNIrFogpEuFwuuFwutRh1o9FApVJBLpfD4uIi6vU6stksfD4fPB6PCkLw+kB0fWIggoiIiIiIiIiUcrmMkydP4syZM7hw4QJyuRwajQZcLheq1SoAoFgsolwuo16vY2pqCgBwzz33wOFwoKOjQy1OS0TXrtXVVRQKBaytrWFtbQ3FYlFdA4CLU3RKAAKAClIWi0XE43F4PB4UCgWUSiXLNGi0MfNY8VpKOwUDEURERET0gpVKJdtlfT6fZdsc1m+urZDP520/tznMv1arWbZzuZxlWzrNAGD//v0b7pf53GZj0O12295PIqJrQaPRQDKZXJf9XKvV1HzwjUYD1WoVxWIR6XQaqVQKxWIRPp8PXq8XjUaDnWdE17iVlRUUi0XLdUA0Gg21NkStVlPXBblGlMtlFItFZLNZBAIBhMNhdHR0qL8314qw43pYT0KOn4wyAaCOq3wOcqxllInb7eaUV3RNYCCCiIiIiIiIiJR6vY5MJoN8Pm8JOHd0dFg6HBuNBsrlMrLZLDKZjFq8Vn98J3cYEu10S0tLqFQqKBaL6nutk4CkdI7L72q1GorFIgqFAtLpNHw+H3p6euB2u9WC9i90YfudHIzQAzkyFR5w8ZpcqVSQyWRQrVZRqVTQaDQQCATg8XgQCAQYiKBrAgMRRERERERERKQ4HA74fD50dHSgXC6rzGXpYKzX62o6lmq1ilwuh0QigZmZGXR0dCAYDKrsafnbre403MmdkS8Ggz+0lSTwqAcgAahAY61Wg8PhUN93fZREPp9HOp3GwsICyuUyuru7VZa/BCFeyPnajuvJdiDHVP5J8EFGlxQKBczOzqJYLKpRw/39/QgEAti1a9e6kcdE29GWByLsRuAikciWvm65XLZVzuv12ipnDud/Ma+pz5+3EbsXUnM4XCt2P4tCoWCrnJ1jAgDz8/O2yn3jG9+wVe7gwYO2ytndP30o4It9Prufmd3XtFtuqzFyTkREREREJukM08kc8BKIkM6yYrGIRCKBoaEh9bftDBZIJyYRtU+1WlVTL+mZ+kKCkfq2TCGUSqVQLpdx5swZrK2tYWBgAA6HAy6XSy1or18bNrpOXA/fdXM0hPxfLpeRSqWQSqXw3HPPIZPJIJ1Oo16v4+DBg+jp6UEwGERnZ+eODNDQzsIREURERERkm9nAcbkuVSfN5Av9MQAIhUKW7Xvuucey/dxzz1m2M5mM+nmzoPlmi/pls1nLtp44YZY1n6vZnMi6q5VIQETUTtIBqV/b6/W6ZXSEdJoVi0VkMhksLi5iZGRElQXae41kp9t6PCa0lXp6elAqleDxeNDR0WGZgglY//3WA5UyhVAqlYLD4UA6nUYoFEIkEoHP51N1O47iuUgfCVEqlVAqlVAoFNRi4alUCmtra8jlcsjlcnA4HMjlcggEAqhUKqhWq2rxcKLtioEIIiIiIiIiIlIcDgf8fj/8fj+8Xi8qlYolCAFcGkHucrnU72T+dwnYyt+wo5Ho2nTo0CHk83nMzMwgm82qwKQEHJxOJ5xOpwo8yv/VahXlchn1eh1LS0vIZrOYm5tDo9FAJBJRaxrIyAhTq9FUO/k6oq+tIdPdLSwsIJlMYmpqCtlsFgsLC2rBapfLhcHBQfj9fuTzeRSLRXi9Xng8nqv9VohaYpiMiIh2rE984hOqwfz9739/3eONRgOjo6NwOBx405veZHksl8vh937v93DrrbciEAigs7MTDzzwAD71qU9ZsqF/7dd+DQ6HA5OTky334wMf+AAcDgeOHz8OABgbG7PMl6z/e93rXrdF756IiIjohZNOwmYdhXrGrT5iTeaRr1ar18VUKkQ7XSQSQTgcRiAQgN/vXzdCVdowck2Qn6WcTN1WLpeRy+WQyWRQKpXUAtf6FG7X6zVDjkG1WkWpVEI6ncby8jKWl5extLSElZUVxONxpFIpFAoFdTwl2FMqlVAsFlEsFlXQ+Ho9lrT9cUQEERHteD6fD4888ghe/vKXW37/3e9+F/Pz8+vWD1pZWcFP/uRP4vTp03jnO9+JX/3VX0WxWMQ//uM/4r3vfS++8pWv4OGHH4bT6cS73/1u/Nmf/RkeeeQR/Lf/9t+avv6jjz6KI0eO4NZbb1W/u/322/Gbv/mb68oODw9vwTsmIiIienEqlQoajQY8Hg/K5bIa6SBTf8j0K/KvVqthcXERe/bsQSqVgsfjgdvtbpnxfCWmbiKiF2fPnj3I5XLYvXs36vW66vh2OBxwOp1wuVxwuVyo1+tqtIT+ne7o6EClUkGhUMDi4iIqlQpGR0cRiURUoNPlcqlRU2YH+vWwKL1Md5XJZJDJZHD27Fk8++yzSCaTWF5eRqVSQS6XU4FeufbW63VkMhn4fD6sra3B5/Ohr6/P8rkQbTc8K4mIaMd7wxvegM9+9rP40z/9U0uF7JFHHsFdd92FaDRqKf/e974Xp0+fxhe+8AX8zM/8jPr9r/3ar+G3fuu38Ad/8Ae444478J/+03/CvffeiwMHDuDRRx9tGoj44Q9/iOnpafyv//W/LL/fvXs3fv7nf36L3ynRladnxplrKRQKBct2qVSybJvl8/m8ZVtvjJodVZe7ToO5fkW5XG75XCZzP00brTFxuQ1n87V2csObiLYvPUNZRjc0uxbq88GXSiUkk0nE43EkEgl0dnbC6XS2nJaJ1zei7c/n86FWqyEQCCAUCq3r3NbXNQCs32upm0mQIp/PI5vNolAoqIx++VsJdF6P1wW5jpZKJeRyOaRSKcRiMRWYkJESACzT3smi4NlsFul0Wq3BIY8RbUdMPSAioh3vXe96F2KxGL7+9a+r35XLZXzuc5/Dgw8+aCn7ox/9CP/yL/+Chx56yBKEEB/+8Idx8OBBfOQjH1GdrO9+97tx5swZHD16dF35Rx55BA6HA+9617u2+F0RERERtYd0BkogolarWTrAdPr0IPF4HPF4HGtra2r6FXkeM+irrzdBl6fZ8SRqh3A4jM7OTgwPD2NkZASBQADAxWnYKpWK6jyvVCrrpmnSO8tzuRwWFxcxMzODlZUVRKNRZLNZFZAwpxMyp6/dySTQsLq6isnJSUxNTeHChQtqbY1isQjg0vVYrrmFQgEzMzM4c+YMTp06hePHj2NpaQmVSsVyzSbaThiIICKiHW9sbAz33XcfHn30UfW7xx9/HKlUCu985zstZb/0pS8BAN7znvc0fS6Xy4UHH3wQiUQCP/jBDwBcDEQAF4MOulqthn/4h3/AAw88gD179lgeq1QqiEaj6/6ZGeREREREV5rD4UBXVxf8fj+AS4uoynRNgHUkWqVSUQupnjp1Ck8//TRisRjy+TxKpRKzc7cQOxfpSpIpfvx+PwKBAFwu17pAg0wt1CxAJiMearUaCoUC8vk8CoWCWs+gWYf5Tg88mOQYFYtFZDIZ5HI5FAoFFcw119zRR6FIkCedTiOVSqFYLKrpmxiwpO2IgQgiIrouPPjgg/jiF7+oOvoffvhhvPKVr1y3JsOpU6cAALfddlvL55LHTp8+DQA4ePAg7r77bnzmM5+xNLS/8Y1vYHV1VQUqdF/72tfQ39+/7t+f/MmfvLg3SkRERLQFfD4f3G43gEsdg3qHo3C5XGpu92KxiGQyiZWVFaTTaeTz+abZzkR0bZD1BkKhECKRCLxer2VtGAlE6AEHuUbItj41UyaTQSwWw8rKCjKZjBoRIZ3tdoIQO+VaYh4zWaQ6mUyiUqmgUqm0XNS7VqupkRHFYhH5fB65XE4Ff8vlsmW0CYPBtF1wjQgiIrouvP3tb8dv/MZv4LHHHsPrXvc6PPbYY/jTP/3TdeUymQyAi8OQW5HH0um0+t3P//zP49d//dfxr//6r3jVq14F4OIICY/Hg5/7uZ9b9xz33nsv/vt//+/rfn/w4MHLel9EV5rZ+KvVai3Lejwey3YoFLJsd3d3W7bNheP1xqjP57M8pq/xYJYF1q8JYe53PB5XP2ezWctj5vffnA/ZfC2zcfdiFl7loq1EtB04nU6Ew2H4/X7LYrLSsSWdkC6XCx6PRy2kWq1WEYvF0NHRgbm5OTidToRCIbVg9fUwzUq78fjRlSSLUns8Hni9XrVYvX4e6hn6DofDUjfU14+QjnPpNC+Xy5ZOcjsBhp0ShBByfGR6pmw2q0aR6cdVD0LofyfHWg9c6ItaA1j3eRFdTbYDEVvdKNqog+daYfeLvNXl7H4WG3UM6OxGRu3un91pRb797W/bKve2t73NVrmenh5b5ezeuMxOhxfD7rGrVCq2ypkdOy+W3WNitxxvcrQd9ff34zWveQ0eeeQR5PN51Gq1ptcXuT9lMhl0dXU1fa5mwYp3vvOdeP/7349HHnkEr3rVq1AsFvGFL3wBr3/969d1tgJAX18fXvOa12zBOyMiIiLaWg6HAx6PB26329Lx6HQ6AUAtLtvR0QG3261GTsj0TZlMBnNzc/B6vRgdHVXBi0ajAafTqZ6HiLY3+W53dXWhXq+jq6sLkUgEmUzGsmaB9D85HA5LX4oeiJAkkrm5OVQqFXR3d6t2kryO/rc7fZF7CcLIqAZZdLpUKsHpdKpAQ0dHhyUBxwzuyOdgTnWlj1wh2i54NhIR0XXjwQcfxOOPP46//uu/xutf//qmgYYbb7wRAHD8+PGWzyOP3XTTTep3AwMDeO1rX4t//Md/RKVSwZe+9CVkMpmm0zIRERERbXderxcej0dNvdSqU0sCFBJcqFQqKBQKWF1dRTweV52U+nzyRHRtkBFRfr8fwWAQgUAAfr8fbrfbslaETBekT82kd5jr68wkEgksLy8jnU6jWCyiXC43Xddgp41+MMl7lSBCqVRS09npZMREs2nuzOO+0aLfRNsBp2YiIqLrxs/+7M/il37pl/CjH/0In/nMZ5qWedOb3oQPf/jD+NSnPoVXvOIV6x6v1Wp45JFH0N3djfvvv9/y2Lvf/W589atfxeOPP45HHnkEkUgEb37zm9vyXoiuFrMho29LNpswO6tk0VNx+PBhy/ZP/MRPWLa//OUvq5/N7FnzuXK5nGXbbLya+5ZKpdTP5ohEc3uzUZJs3BHRTuN0OjE4OIihoSEMDQ1hZmYGlUoFPp9PdS7q06q4XC643W7VGZbL5TA3N4dIJIJCoYBAIKAypR0Oh5rCBeA1dCvYnVuf6HJJENLv96NSqaCvrw9DQ0NqYWV5HLh0HuoBCJ0EJZPJJGq1GpaXl7G8vIyOjg6EQiE1rZM+lZDU53bS+a3XUev1ugr2yLHTgzlOp9NyPM1prOT4y3O4XC41FZ75ejvpGNK1iyMiiIjouhEKhfBXf/VX+NCHPtQyQPCyl70Mr3nNa/Dxj38cjz322LrHP/CBD+DcuXP47d/+7XUdoW95y1sQCATwl3/5l3j88cfx1re+dd289kRERETbncPhgN/vR2dnJwYGBlRAVoIIkpkr60LoC81Kp1kmk0Emk0GpVOKC1UTXKOno9ng8CAQC6OnpQX9/v6WNoy9mb65roH/n5XqRzWaRSCQQj8cRjUaRyWSarm0AYN1zbGeXM+W1/r4kkABcmq5JAhH6aDTzOfTpsPSAhF7+Wjp+dH3giAgiIrquvPe97920zKc+9Sn85E/+JP7Nv/k3ePDBB/HAAw+gVCrh85//PL7zne/gHe94B37rt35r3d+FQiG85S1vwSOPPAIAG07LtLCwgE9/+tMtn4OIiIjoapFARG9vL/bs2YNTp06tmxPe7BjTt+v1OtLpNJLJpFqUVjoZ9QxqItre5Lsqo546OzvR39+PcDhsWRtGSBDCXCDZzNCv1+tIJBKYn59Hd3c3KpWKyv6X68ROnVZIAra6jo4O+Hw+NYpMX+vBHGFibuuBIH3EhLnQ9U47jnRtYiCCiIjIsGvXLjz55JP4wz/8Q3z2s5/FP/7jP8LlcuHWW2/FJz7xCbznPe9pWZF797vfjUceeQS7du1aN82M7tixY/h3/+7frfv93r17GYggIiKiq0qmUQqFQhgcHITX61UdktJZCFzsPHO5XKqzS7J6HQ6HWifiqaeeUs+nPy7/X2udY9tlGiR9P7bD/tDOJIFDmXqtt7cXtVoNkUgEHo9HBQ5kXQMJQujkGiGPS1AyGo3C4XBg165dKJfLcLlcamomCXZuNj3mtUr/zsoIhkAggK6uLqRSqXXrRIhWa2jIcTVHpehTmzIgQdvBzvxGExERAXjooYfw0EMPbVruwoUL634XCoXwwQ9+EB/84Acv6zXf8IY3bDr8tdnrEW1X5vlsNl42ymo1G49mo8qc3mzv3r2W7XK53PJ1zOc215AoFAobvvbc3Jz6ORqNWh7r7e3dcD9NbNAR0U7ldDrh8Xgs12AJHpidYPKY/F+pVJDNZjE3N4dDhw6pLGo9Y5qItjen06mCA06nE16vF8FgEH6/H36/H/V6HaVSqeX3udni9jKyKpfLwe12I5lMIplMotFoIBgMXrP1Krv73WxERCutAp8y+sFcA00CR3qQlwEI2k4YiCAiIiIiIiIiRYIFlUoF+XzesgaE0Ocyl84vmV6lo6MD5XIZ0WgUzzzzDA4cOIDu7m709PSo5/B4PNuqY8zuSIftss/bZT9oZ3O5XJbFkEOhEOr1Ojo7OxGJRFCr1VAoFCyjpOT6IQsw6+sX6AsxJxIJFAoFLCwsYH5+HvV6HX19fZbgxU7tRN9sNFhHR4e6vuojQyToK+vuVKtVy0gzOc7mWhG6nXpM6drAQAQRERERERERrSNTskhnlgQkpJNMghUyXZM+p3ulUkGj0UA2m0UsFkMsFlPTr2zHKZn0LOXttm9EV4u5oLJ0cOuPCbPT21wrQl8fRjrRK5UK0uk0VlZW4PV6MTw8rBbGNq8p8hw7iX7M9MWm5X06nc4Nr5cyuqRcLqNcLqtFv/WpsPSREeZaHTvteNL2x0AEEREREREREa3T0dEBj8ejOsNk3nZ9eiaZ+k7WiJD5ySVjN5/PIx6PIxaLqd+Z0+ltJ+ycI7pE1hxwu92WtV7077g+6gGA5Rog1xDg4ugKWVMCACqVCur1OmZnZ1Gv15HL5dDT04NwOIzBwUH1OvK8+rRD1yIz0KkfNxn14PV61bHWA7z6NVNGoQFAqVRS01ylUinkcjk1VZZMqyejKmS0irlPnCaPriTbgQh9RfaN6HP5buTEiRO2ymUymS19XbtfMDvztdmd082cs60Vu8e41aI1plKpZKucXXYri3aPy/Lysq1ys7OztsoNDg7aKhcMBm2Vs3Ou2P1st/rY2T1X7N6g7T6f3XJ2jwsREW1/m91LpDEJrL9PbHYv9Xq9lu1wOGzZ1u+fZl2vWCxats3HzXtvKpWybAcCAfVzpVKxPGa+Z3PbvF/rx6DZa2/0XFeS3TrklWa3/iP0Oq55jmWzWcu2uVaI+Vmvra21fG59HREAOH78uGXb5/NZts266NGjRy3b+jlr1kdDoZBle2RkxLJ96NAhy/auXbss2/p3p6+vz/KY+T0z9/tyjv9m5+9OXVT0ehYIBDA4OIjBwUFks1ksLy+ra71k3cqoCOlIk6lXgIvnV7lcxsTEBADg7rvvhsvlgs/nW9eh2OpcvJLXze04UoPoapPvhUzPJB3mPp8P+Xze1nNIR7iMktAz9guFApLJJBKJBOLxOOr1Orq7u+HxeFTw4nLrCtcK/Xpjruugv2cJ/DY7FnLNldEQ+ogIABsGb3i9oyuNNUUiIiIiIiIiUqTT0e12qwzdVoGmVh1k0sFVr9eRTqextraGVCoFv9+PWq2mOhj1vzefl4iuLvkeut1u1Ot1FTgfGhrC3r17UavVEI/HAcASYNAz/WVElWzLSAmRyWRUsN7pdGLPnj3o6+uD3+9X00HpIy7MxZivFa0SXfQpmWTUgj4NnrxfCezKKBXgUgC3UqmgVCqhVCqhXC7D6/Wq6+t2nQ6Prk8MRBARERERERGRhdvthsfjgdfrtWRD6x1kwKU5ymXOd+k4kw61Wq2GWCwGt9uNhYUFeL1edHd3q+lH9CBGs6lLiOjq0xdCdrlc8Pv9CAQCatqlZmTapmZrSegZ+5LJL+vJRCIR5PN5OBwO+P1+9Rz68+2Ea4N5nZNRZeZi3XrgodVzyPVXyurHdyccK9o5GIggIiIiIiIiIgvp+HI6nfD5fHC73ZaFqp1Op5oGxOxs1AMMtVoNxWIR6XQaMzMzCIfDGBkZgcvlsixmq3cwtsre3agD8lrpnNRHgehztxNtR+bC1BKM6OrqwujoqJpy2wwuyPktHeN6Zr5eRl9nZm1tDY1GA5VKBbt370Zvby88Ho+aUlCmvtSvEztJIBBAb28vQqGQmuZOgrtyjOQYmNcNmSKvWCwin8/D4/GoY3+tXBvp+sBABBEREV2zJPtHMoCkEdRoNFAqlVAsFlEul1EsFpHL5TA3N4fl5WWUy2V4PB5EIhF4vV74/X74fD417+3g4CB8Pp9lUbxarQaPx6M6YeRx4FJjQKaxuJ5stH7QZo0ecy2F3bt3W7a7u7vVz9PT05bHzPUOzE6czeaq19eUWFhYsDx2xx13WLbN92iuCWHaaI2Iy11H43pgZvmZ631stCaHOTe1ub7cuXPnNtz++te/btnO5XLq55mZGctj5noT5nng9/st28lk0rK90Wdtvkczw9RcE8JcQ+L2229XP7/qVa+yPHbbbbdZts3vjvlaG+2neW6zY2Nna5aBay6uKr+T/5v9jdyri8UiYrEY0uk0yuWyJbBxOZ3xO6lTTeouRNtVs3VcHA6Hqj/r9V4zECG/k2ClTLGk09eKKJfLyGQySKfTSCaTcLvdKJfLcLlcqg5uZvvvJLLAtIwWE+YoB329DdmW41yr1dQi4IB1rYmdct2kaxsDEURERHTNkko3cLHjuVgsolgsIpPJYG5uDidPnkQikVDZQbOzs1hbW0O1WlWLZeoBCLfbDZ/Ph5tuugk+n081sDo6OuB2uxEOhxEKhRCJRNDV1aX+RuavlW0iIqJrnZ5hG4vFkEwm1TRN0jGYz+dRLpfXTbGkd4LJvbpUKuHChQvo7+/HysqKynZ2uVzqPirzpNdqNXX/1Z93o077y+lku1LBDLMTUM/idjgcqs5wuR2Fdo4H0VYzF6zWv7sA1LovACyjIarV6roAZrM1ZarVKrLZLNbW1jA5OYl8Po+xsTEAF4Pm8vo74byXa6P8M3+vb8uxAayBGyHPUalUkM/nkclkEAwGLc9hvrY+pZ7H49kRx3Qr7aSA93bDQAQRkQ3NsmELhQKi0SiSySSKxSJ6enrQ399v6YyUrI9r7Sa2lVkTrNRcvmYLNl5Nsi/SOEgkEshkMkilUlhaWkK1WsWBAwcwMjKC/v5+NXz6Su2bTGtQr9eRzWaxvLyMqakpHDt2DKdOnUI6nUalUkG1WkU0GkU+n1eNd2nM6A0ql8uF5eVltUCn3tAKBoPo6+tDX18f+vv74Xa70d3djUgkgnA4jEAggHA4fMXePxERUTtVq1Xk83l1r5X1HSKRCHp6ehCPx3H+/HnE43E1mkk6H/V6sCyyKvfovr4+3HDDDSrA32xkTrMFsEWzTszLqbe+0Dru5dSRm5XVf8fFuelapAcU9IWU9ccBNA04mG3qZtulUgmFQgHxeBw+nw+FQgE+n29HZfWbo0WaHSP9+tAsOGGW0YMRpVJJBX9avb4eCNlO7c7tgMejvRiIICKyQb/x12o15PN5LCws4MSJE5ienkYqlcL+/ftVFnUkEkFvby/8fv+6YMTlZDptRUXrcp+nWeZWszLy+GYYiLh8m037ciUyNPTKsFRUc7kcJicncfLkSczPz2NhYQHHjh1DsVjE6173OrziFa/A3XffjaGhobbuW7P9rNVqKJfLiEajOH36NH784x/jhz/8IVZWVlTHiMPhsEz5oneO6FmYALC8vKyOswQqgIvZWBKE6Ovrg9vtxtDQEIaHhzE4OIje3t51U6YQERFdiyQLN5/PqymEfD4fhoaGsHv3buzduxfz8/PIZDLIZrNqZITUHeSeKskClUoFi4uL8Hq98Hq9CIVCGBwcVIuzSvABuDgNmL5Iq9yPhdkxZ3aGtoMeGGk1BZ/ZeQhcqm/YnU5Gr+cxK5e2CxnhIN9Fn8+HUCikRhYDraefNEdI6dcGmf5UX8sgm81ifn4etVpNBS7D4bAaQdRsiic7tlswwwzq6FPOyvoQElCQ66S+YLfeZpSgQrlcRqFQsIxCabUGjz49HtGVwkAEEdFlkHnnL1y4gG984xs4evQo1tbWUKlUcPr0aTz99NOIRCK46aabcN9992F4eFgNUZWGlN1pW7aqgnS5z2M2fpo9x0ZzAF+LI0C2Oz04JD9vNv/9iyWfcaVSUdMpxGIxfP7zn8fXvvY1LC8vo1qtolKpAAAee+wxFItF9Pf3X9FAhOxnPp/H0tISvv/97+NHP/oRnnnmGSwvL1sWagMuBXmkESQNGXmfekeHNIoAqJFO5XIZ+Xwec3NzqNfrcLvdcLvdCIVC6OrqwvDwMB544IEr9v63A73xYs49b87132peYNHT02PZ1oM65tz+ZsDOfC7zO2JesxKJhPo5Go1aHpPzWpiZupcz/dZm+2k+17V6/dwoy3GzdQXM8ySdTlu2zfNKX8fhBz/4geWxU6dOWba/9rWvWbZXV1dbPpe535tlxJmPm+tVmDYKMpvHr1QqWbbNtS+mpqYs208++aT6+ctf/rLlsZ/5mZ+xbG+2hoQ+nQOw+XortHNJxyMAy4Kxe/bswU033YSBgQFEIhHU63UkEgkUCgVLPVC+u9IJLyMrJYlnZWUFg4ODuO222zA2NobBwUGEQiHVMabXSeV+rXdo6vVV8/sodVJ5fdNGoxE26qzcbH56cy53ndkpK+/LDKKYWc7yeLMgh17H2Wh9IqIXQ59iDYCastTr9cLtdquF5/XvnL6tPw9gPa/NMpJcFIvF4HK5sLKyourqcm24EiOariQ9UCDHWQILMhpN6Ovh6e9HfifHT9o18rgwr6tEVxprlURENujzKCYSCfzwhz/El7/8ZdWB0dHRgXQ6jaWlJfh8PmQyGfj9fnR2dqoOTHNOTNHOipCeWWLntVplRDTLxmr2XM2yt8wOJHPfmo3AkIZqLpdDuVxW8xPPzs4iFoshkUioKbGy2ax6DWmk+v1+y5D+/fv3Y9++fQgEAqpzXaYUkCwe+ZyAS5Vrl8ul5iKViqH8znwvdo4vYL9DRw88yKJj+jHSK+GbZedJBfZyRuNIFk2tVkMmk8HKygp+/OMf47HHHlOLPetZTDKX6+nTp/HSl77U1utshVKphGQyiYWFBTz++OM4evQopqamsLq6qhos5vfN5XKpx+r1ujpv9GOuf+7ApSkiAGswA4DKPEqlUkilUlfsvRMREbWTnj2r12FdLhf8fj/8fj+CwSAikYglI1qf9kPoc8XLtCsulwvZbFZNu1KpVDA4OAi/349qtarWiNDvx7pmwe3Nkmma0bO8W00DJeX0zlihb0u9TU9maNbhanbImvPemwkozZhlXsgIbKLN6B3c+oLIklEvbSbJ4tfPY/le6c8hdXFhtj/1zP9CoYClpSU0Gg11rZCgh3xnrsRoqHbRg4z69UWOpR4M1v9GHxlhXn9KpRIymQxKpZLl2n2tHqOttFEA2s7vaWvYDkS06kgymRlNrZw+fdpWuc2mpxB2T5StzOgxs+Ve7GvaPcaFQsFWObtDP+0Ow7I7T5rd92Fmu7Vy7NgxW+WOHDliq5zdLMatnOP8cjr/7LD7vbB77tndv+t9AVZpIGUyGTUvPmCd/7JYLKJarWJ5eRnnz5/H7bffjkAgoDqv5Xu50TFvNQTb7tBss+ElFZtmQ9rN77+dYMNG9Nes1WrrGo7mPunZHvrvi8UiFhYWcP78eSwuLiIWi6FSqeDMmTNIpVIqQFEuly3XHDnnpUNenk+m0pEFFsvlMnp7e7Fv3z50d3cjHA6jq6sLfX198Pv9CIVCCAaDqrKsP1+rzn47QZ7LPZ6S0ZLP51V2fzgcRmdnJ8rlsqqoy/PKsdSHK9vJHJJ9MzviJQgUi8Vw8uRJfPWrX0UymVyXYePxeNDd3Y1du3Zd0dEQwMVs5unpafzgBz/AqVOnMDc3h0QigXK5rDo8dB0dHahWq5b3KlMv6eej3sDRvzvmgnKVSgUulwuBQABDQ0O46aabrtybJyIiaiO5/+mje2WUZKFQgNPpVB2RUvfTO9SajTByOp3qHj01NYXZ2VlMTEzglltuwb59+3DkyBG17ppkWwcCAXg8HrWgql430zvl9Lpts/pPq04oadfLYrj6Y4A1iGK+N2kfSN1JplIpFovq9WS/9ZHDeh3T4/GoY6kHE2T/zXp8syCP3sYwE1aIXgx9lI+ZpS/rqLndbvU9MqdeAi4Fy8zRx3onubRf9ESnYrGIpaUlAEA2m0UoFILX61X7Zo4GeiHtratJ31c90KMHNOV4ynvVg756EENI27FSqajrwQsJ0O405nFqNhrnxT5/M9fjsd4MR0QQEdmkVwykQ7tZIK9arSKZTGJ2dhaJRAL9/f2WisLlZCu1qixs9nv5WTqys9ksPB6PWni31b63i944koaYXrmSgEKpVFKLDU9MTODkyZOYm5tDLBZDtVrF/Py8CvbomWb6c8t71/9Fo1FMT09bAkKBQAAXLlxAZ2enmlZn165d6O/vx8jICEZGRlSj1+v1qjUEzFEm8tobsRtk1MtL5TuTyWBhYQHHjx+Hz+fDrl27MDY2hr6+PgDWAKGehWh3/1qV10dDTE5O4qmnnsKJEydQLBbXPWcgEMDhw4dx8803Y3R01PZ7bPW7SqWCXC6HVCqFWCyGRqOBXbt2obOzU412kY6Q1dVVTE9P48SJE5ifn0c8HkehUFg3dYP5ndODONLwBy41+mWea5N+jGUUTW9vL/bs2YPDhw/jzjvvtPX+iYiItjvp/JIOLbfbDY/HA7/fD5/Pp0Yknj59Gtlsdl2SS7O6mpm922hcnF5xamoKsVgMMzMz6O7uxtDQkEoM2bt3Lzo7O9XC1nrnpz6iVV5DXltew8zQ1pMvAOv0JHonoE7qZblcDsViUdUzpF4r2dulUgmlUgmLi4vq587OTng8HjUNpIywlcW/+/r6EIlE0NXVpeqdZgdtq1EVZkekHoBgJjRtBb0OrQcn5Xog56y5Dps5nZBZ99dHDMl3WgJ5olwuI51Ow+fzIRqNqsCn/F2zUUR23svVpn9v5RorU95KwFOnX5Oq1arlu61/3/URItLe1gO38jfXq8tpv7ey2aiKjc7D6/nY6xiIICKyQRpOjUYDPp8PY2NjcLlcaj5oqVxJYySdTmN2dhbLy8sYHx+3TOUijaXNhgLqHcR6R3GzIdpmg0p+LpfLSCaTOH/+vFoQMBQKqTk9N7NRVslGj+kVHn3kg555Lv9kGqZ0Oo1oNIqFhQU8++yzOH36NKanp5FIJFAqldTx1ytu+vRLekaMvuCZ/D6TyViybNbW1rC4uGhpzHZ3d2NsbAy33XYb7rrrLgSDQfT39yMcDiMYDMLv91vmRm1W+dU/r8sNQIharYZcLod0Oo2VlRU8/fTT+OY3vwmfz4fx8XG85CUvwT333KPmZdYrl+b0X5dT4dHPMdn/5eVlPPPMM/jOd76DaDTaNGjR09ODBx54AC972ctsLdQsWYVmdo5UsmOxGC5cuIAzZ87g6aefRr1ex0//9E/j5ptvxvDwMDwej1qzYnp6GhMTE5ibm0M0GlWLZervRzoq5LN3uVzw+XyWAEQ+n1cdAl6vF+l0GpVKxZJhqY8EkY6Pzs5OHDlyBHfddRduv/12HDp0yPbxvlZsNAUFYB2BaTaczBEpm60VYD7e29vb8rnN/dhsROZG61WYzy0BN+H3+y3brRZjFPp3f7Oyphd63XghWnUKNHvM3O/NRt5ulIVsrn8Qj8ct288995xlW1//AADm5+fVz9/5zncsj8ViMcv2ZqO1zfPInB5Ct9E6GM22N/qsN/vbza7d5shs/fyfnp62PPZXf/VXlu3vfe97lu3/+T//p2X78OHDlm3z/Ndx/YiLzO9Os++WnlFsTvEnZcxOcvNnuYeZwXUzA34rOlsAa6e2z+dDIBCA0+mE3++H2+1GOp3G6uqqShTRX1P23ayP6CMr9Pe9traGeDyOxcVFhMNh7Nq1C6FQCJ2dnahUKujr60N3dzcGBgZUZ6RM0+Lz+dZN0SJ1CqfTaRmJYH4urfZNv3bU63U1KjoWiyGTyajvoNQvarUaUqkUisUiisUiJiYmUCgUkM/n0dvbC6/Xq+qzlUpF7bvX68XIyAh6e3sxPDyMYDCo6upyDZGpb/TPWuon8v7kvZhrSpjtCKLLpbdz5ZxzOBwqKCmByWKxuK6DXK83N6svyvfH6/XC7/eraXfl2lEul9U6XgsLC6jX6wiFQmoEkXwvNqs7Xe2RAM1eXw8WlMtlFItFS7DS1CyxT7blOOqj4uW6Ja9zvY+SerEjIPT26uU8bt7DiYEIIqLLItlgu3btAgDVmJCKgCxoWq/Xkclk8PTTT+P2229Xnf5SUdDnsNWDE6ZWIy7kufRGlt4xLhlYy8vLOHfuHB5//HEEg0G88Y1vxOHDh9HV1WXJwjBfq1kHknnjtHsj1W/GlUpFVYhk2HoqlcLk5CR+/OMf4+TJk5iYmMDCwoKqhMl7lIqv/vrmdDl6hcx8XX0osDTk9cWWOzo61OiD06dP4zvf+Q7C4TDuv/9+3HDDDdi9ezf6+vrQ1dVl6ZTR98HsyNeP0+V0LiaTSRw9ehTz8/NYWFhQCy9LQ31tbQ1dXV24+eabLRV8M1uu1agDqZA2++z1jP98Po/p6WlMTk5iaWnJ8h7lNQOBAN761rfi5S9/OcbGxtYt6tuKef7U63WUSiVEo1EcP34cTz75JE6ePInFxUUEg0Hs2bMHvb296OrqUp+bjDyanJxEtVpFOp1WHQcy1UEgEEBnZyc6OzsRiUTQ39+P7u5udHd3IxKJwOv1YmlpCTMzM+js7MTg4CCGh4fx3HPPYXFxEZlMBo1GA+FwGEtLS5apqVwuF+666y687W1vw/79+9Hd3b1hhx0REV17pN5iknulnkEv2bz5fF5tS7ZrOp3G2toaUqkUotEo0uk04vG4+ttarQa/368y56XOKB32Pp8PAwMDGBwcRDAYVIkUgUAAPp8Pvb29KtFERnFK0HyzgJGZMSu/kySN8fFxvPSlL0UqlUKtVsOePXvg8/lw7NgxnD17FhMTEyrAaK5pJcdKP2bNsvfl/l0oFJDJZLC6uqo61p588kn09PSgu7sbt956q5r2dGRkBN3d3ejr61OJBH6/39IpJ68p63/p9Wdz+ijpuKtUKojH4yqoIGtAXbhwAadPn8bi4qJl2hOv14tarYZEIqGeJx6Pr5syU18PQo5HvV5HJBJBOBzGLbfcguHhYYyNjWHfvn1qBIi8lkz35HBcHLkpdTb53CWxJhAIAIAl4cIMCrFDjF4IPcAg1xiv14tgMKimEG92bpltDf1naU87nU5LO1fIujKLi4uo1Wro7+9X9XxzNNRmiX5XixmY1e8fcp2QtnEul0OpVLK01eRaoV+/9OfRg6iVSgWlUkmNrtCvN7IvZLVRYo7+OzPRQO+PMD9beVwvu9HzX0+fCwMRREQ2yIJ5jUZDZaK53W7LYl2SmaDP27i6uopYLKYaBXrnt94QkXnmzQzdjRYfBqAqgFJeKh/nzp3DxMQEVlZWsLKygrm5OXR0dGD//v2qUxa4dPPUb5xmJ/4LGREhj0vDT99vh8OhGuTz8/P4+te/jmPHjmF6ehqxWAyFQkE1RvWhqc0WKpTghN6hLo29ZiNJ9DlNzTkiZf+q1SpWV1eRSCTgcDgwOTmJ0dFRHDp0CLfffjte8pKXYM+ePZZh8/I+9aCEPs/w5Wg0GlhZWcH3vvc9TExMqOw6OW8kW+bkyZPYs2ePer/6+zbfV7PASKsMbmko5/N5pNNpPP300yqrTxq7wu/34/Dhw7j//vsxNDQEj8ezaZa0vJY0xvXpDKLRKP7lX/4F//qv/4poNIpMJqPOh4WFBayurmL37t3o7OxUHTvFYhGlUkllFcq509XVhXvvvRd33303hoeHEQ6H4fP54PP51DBy+a7m83nV8PF6vQiHw7j11luRzWZVh4rL5VJTRUmnU7lcxv79+zE+Pq6mXbje19IhItqJmtV59PUS9OklC4UC1tbWUCgUUCwWVd0sk8kgHo8jk8kgkUggn88jl8tZphKU6Xrk9aSuWa/X4fV6EYvFsLS0pDqdXS4XgsEgAoEA9uzZg66uLvT29qo6p54coNcR7CZLSMJBT08PDhw4gFwuh0qlgkgkAqfTiWKxqKYj0t+Heez0/2U/mk2nKdv6iAk5HjLVqHT8O51OLC0tqSQCCUgMDAzA5/OpY2ROuyT7aa5noWcl53I5nD59GplMBul0GslkUq0RNz8/j0QiYRlNJQEjqSs1Gg3LNJH6sZe6qp5so0+jGovFEI1GUSgU1FoZUgdMJBLqOQuFgqq7SP1GRvD29/ejp6cHwWBQTSerfwat1nAjaqZZ56tcn3w+Hzo7O9Hf368WRzbJOS/1flmvTQJ/MuVus5GrMoVvKpXCsWPH0NPTo5KSZESE1L3NBd+3I3O9DX2aYj1grSdX6dcRfYYAPRgBQI02lzacBDSaTYu1nb/zV2MEl3wueqKoPsoMuDQNnxx3/Xsg5yrQfD1XfaSQ+X3Sf9/s/N2JI9oYiCAiskHPuJfphaTj2exwl0ZBsVjEzMwMzp49qxpDgLWhCVyaisSMkjfrKNYbEOYNSbJFlpeX8c1vfhOzs7NIJpPIZrOIxWJwOp2Yn5/H+Pg4xsbG1DBYs2LZrNFksjP8Vc/c0Mlcn+fPn8fTTz+N7373u1hZWUEymVQd7uY+mQ1Uff/Mm7nZsNSz4oBLIxfMYfr6KAHJaJQs/Vwuh1gshsXFRSSTSbzuda9DT0+PagjLOSH0Ru/ljIQQMzMzmJubw8rKisoQklEk9XodqVQKZ8+exf33349QKKReR96TOfTWTuVFz7CRbMBkMom5uTkkk8l1wQy3242enh684hWvwK5du1QGYqvgWStyvDOZDKampvDMM89gaWnJci6USiXMzMxgaWkJBw4cQDgcVsfC6XTC5/MhFArhxhtvRKVSgdfrxcDAAF796ldj//796OrqsnRImFM3BAIBFWiUzzIUCq0bGp3P51Ung/y9rDHSrMNjpzDPYfM9bjQ1k/m3ki0nzOmUmnX0tWJW9Debgmej72Iul9uwbLNFzzfaF73zz+4oITv7uZ1sNkpOnzrInHppdXXVsv3P//zPlu2vf/3rlu3Tp09btvXPerPParMpjzbaNs/1zc6Dzc7/jT7bjab3avbc5n7r5c1pm8ypsE6ePGnZ/tznPmfZ/qVf+iXL9kZT7l0r5+tWMJMb5F6ZzWZRLBZVB1IymcTExAQSiQSSyaTqaJPAgyz0rHdySLa+dMjJ/USfbhKwnicy2iEQCCAcDuPIkSPYu3cvDh48iJ6eHvh8vnXvQe5/zeqRJofDoYL2cp+VTFvp6JLtZtMtynvTj5/st9Sh9VGYZkBCr49KwkI8HsfCwoKq60QiEQQCAezevRtjY2M4dOgQGo2GGgUp+y91NPO7oQcgJBgg0y/JlJTRaBSJREIFKPQkGfl7fZ/N92FmkOt1VClfLpeRyWSQyWTg9XoRCAQQjUbV6Ih0Oo10Oo2FhQU1ElumonQ4HAgEAggGgxgaGkJ/fz8OHz6M8fFx9PX1Weo9kozTLLlnp3V00dYx2xTNvq+trilmZ7k5ra2ZMGYGKgFYRgtks1nE43H4/X709fUhFAqtmy5X/85tN3obWd+Wn+W9yn1Bb4voCW8bPb8ELmVGAPmnt4fpkmb9DM2meW42ik5PfGwWYBDyeTbrz5D/m/VPXG4d61qpkzEQQURkg36TkQyzQCCwbmogyfCQ30WjUZw5c0ZlcUvFX7Ll9ewoM9ptjkwQzeZ3lEZUIpHA6dOn8eSTTyKZTKJUKqFcLiOfz8PlcmFpaQnLy8vIZrPw+XxNX3Or6RUuyeaanZ3F8ePH8eMf/xiTk5NqserNbs5y/GQ4bigUsowEyefz66Zzkr/Tg0b6a+jPLz/r+yzHNZvNIhqNolqtYmRkBAcPHkRvby+CwaDKxJF9a9ahZPfYNhoNzM/PI5lMrsuE0SviMzMzWF1dRV9fn9pXeR2z8m339fXKq8zJurq6quZqlQqSdI5EIhHccsstqrFvp2NDfy09gyeXy2F5eRlTU1MoFAqqsiefRyKRUHMyy+8k21Dmqt6zZ4/KDu3v78ddd92Frq4uSwACuJRRJMdMzqdmo0b0iqDf77cEe2T+Zv0c2+6ZWERE9MLIPbBer6NYLCKTySCVSuHEiRNYXV3FzMyMCkokEgnVmaTXS/SpIvXkDwCWeqYkRLTqVNCTB1KplJq2cWBgAMPDw7jjjjswMDCAsbExBINB+Hw+ywhKfXSo3Lua3cPlnibBCBn5J6N4BwYGsLi4CLfbbakL6x3zzaZh0jvsHQ5H0+mv9DqNHrTQp26RpIl4PI7p6WkcPXoUt9xyC/r6+rB7927s2bMHAwMD6OrqWneflnppuVzGysoKlpaWcPz4cRUUeOKJJ9RoD/ks9UxY4NLIZBkRogel9bqYOX+7HhTQO2qlPlwqlfDkk0+qUQ6SnCHrcOj1XL1e4vP5LHWgAwcO4K677lIjJWR/9fU0rpWOK7p65Dx2uVzqe6NPRSeJPPo5JeeotGXkcTMQoXfi6lOfyt+YbchSqYRTp06paWpDoZB6Hv01JEv9curll9Ne2yp6YFKub3LN0UeO621juY6Y7WUhAfJcLodCoWAJKl8LU8hu1Wegn1+tkjf065/eNtVH6uiBY7N93WzfpX2oB4DkXNTvAWaQWkhS3OW0qfXXvxrn8eViIIKIyAYZwSCNjGAwiJGREayurqqstmZZmI1GAydPnsTNN9+MXbt2qc5/qVzoc9eamVNmVL1ZZUpuNNJompmZwbe//W0sLi4CgKWS6HA4MD8/j5mZGUSjUfT09KhOZTMD1KzYXG7AQr+xyo28VCohk8ng5MmTePLJJ3Hs2DGcPn1aZaHpr6/f7OXmLQui1et1+Hw+DA4OYvfu3aoCnEwmcfr0aeRyuZbHzqxASINZL2MOt5Ty0th9+umn0dnZiVe+8pW45ZZbMDo6qirMeme3fMYvJNCzurqqhhw7HA71GcpnU6vVsLq6ijNnzmBkZMSyaLW+Tol+Lm30+npAQIIdhUIBs7OziEajaq5r83k9Hg+6urosQQi7AQ89cCINDFmgW89YlAqdBABlkelisYjl5WXkcjk1LcPLXvYyhMNhtXBeIBCAx+NR578ekDLPL319DafTaVk7RN6by+WyBLekQWZmrxAR0c6jZ6tKsGF1dRXT09NYXl7GzMyMSgCReo1Zn5OOCf35gEuZ9XpHfasRNtLh1mhcGpXhcDhQKBRQKBSQy+UQCoWQzWbhcrnQ29uLzs5O+P1+1bmhd+w3G71q0jtKJOjg8/nQ3d2Nnp4e9Xr6e2jVwa13PJrvq1kdWH8e85jItozSSCaT8Hg8WFtbU2s8yfGWjjh5fvmbXC6Hubk5zM/P4+TJk2r0RTQaVaMP9Pdk1sWbJQjJMZP/zX+t6EGrWCyGjo4ORKPRdSM09efQAxJSD0wkEvD7/SiVSujt7UVvby/6+/sRDAZVnU0fnX0tdFzR1Wdm8st1Sw+yymPCzOY3f2513ultND3ZT0Yueb1e5HI5lWynj0xvluC3XZgd2fpxlMCoPtWdTr7j5nOZbU25hujXePM6e73Y6D6k/9Ovo41GQ02FLOe1BIlbPQ9wKdgm0zfLZyD3CJlGTA+U6f0w5n2m1eghvey1ioEIIiIb5OIvEepIJIKDBw9icnISiURCBSPq9boaIgpcnJ5pfn4e58+fx9DQEEKhEMLhsHou/SZjdvqbN5hmFRf5l8/nsbi4iNOnT+Po0aPI5/MAoCpmMu2MDPuWjlm9gSavKR3e0kFsN5OkWcVGGnqFQgHJZBInT57E3/3d3+HcuXNIp9NqoW254crQf7/frxZwjEQi2Lt3L26++WaMj4+jUqnA4/Fg9+7d6O3tVUGYc+fOoVKp4MSJEyrLXY6PdCq3qtTpHQB6loneIJYy+Xwe3/rWt9Qcz6961aswMDCAQCAAr9dryRTUX7NVUMfkcDhwyy234Ny5cyoTT+b31LMZy+Uyjh07hkOHDqGzs1Nl+5n7rFdw9HNGz7KRc0U6F2q1GnK5HKampizzV0tjvFqtwuv1qs4Nec+Xk70hFTJ9WoJUKoV0Oq2CS3qlTRZslIXfvV4vIpEIBgYG0NPTg3vuuQdDQ0Po6OiAx+NRn4UcD6kM+nw+y+8kMNhsDmlzzk8Z+aJ3JjSbd5WIiHYOPXtfggypVArHjx/H888/r9YSkCneJIAuJKtSnssMMsjP0skhdTOn02kZaaB3guj3ZfkbmTpodXUVi4uLCIfDGB8fx5EjR3DgwAHs27cPoVAIkUjEMj3oRp3j+rRDwKUORLfbDb/fj5tvvhn1eh1zc3M4deoUksmk5fn0eoVZH2mm0WhY1lrbqC4s2/JPOvBOnDihkheOHDmC/fv348iRI6oeIcGiWCyG+fl5LC4uYnp6GslkEktLS+vq2M1eV8+0Nadqbbav+jGRJCG9rqYfWz3gBUDViaTupr+mXl7OG1mb5IknnsBzzz2Hubk5HDhwAEeOHFF1Rvns5RzjaE7aiH5+Ncvel1FZ2WxW/Y0kN+nJWnpSnZkBrn9HJJlLP/fle1MsFrG0tIRsNovZ2Vn4/X7s2rVL1f89Hs+6769ddtswmyV46WXMfdCvgXrCYCqVQjQaVaPbcrmcZS0Z/W/10SfyXHqHtxwnCaTqwV+9zbNTOrabfR56273Z9VvubfoaHfqaT+l0GoVCQY0syWQySCaTKmAk7XL5W4fDodZmCofDan0nPagQCoVUUkBnZ6da31Bv4+vT6LUapah/X8z797WSGMdABBGRDWbWh9vtxsDAAILBoCW7Sm5GcoOvVqvIZrOYmprC8PAwhoeH4fV6LVMz6ZlpeieyrlUDSF5PGrlSmdEbq1LpkA5sCQ5Ixr0+ZFBvkJrZJBtVuvQKkL5/cnOPx+M4deoUHn30UZw6dQqZTGbdtADd3d04ePAgbrvtNoyOjiKdTqNer6OzsxOjo6MYGBhQIyIAqOkBKpWKalgePnwYzz//PByOSyMoIpEIstks8vm8qmSYDUa9YtcqA1H/m1wuh+eff15l391xxx247bbb0N3drY6xZM/rn6HdysHw8DD6+/uxtraGVCq1bnoG+XxnZ2cxMzODoaEhBAIBS+eFGeQy36++CKTD4VDBGskQlM9MhvTK+5FMjz179uDOO+9EKBSyrI3QLNjTit7YlkXapFGjN8yDweC6AI7H48Hhw4exZ88e1Ot19PT0qOHG+lRM0pgxh4xLGT0LRSrn0ogxG+bNOkD0TpOdypxT27w+6Y9LEFTojdJmzxUIBCzbZrbR6Oio+rnZiLCNmOeiOS+u/vfm2hXm35prQGy2VkCrzqhmzPex2fV/K5nvU19LwDyvzf3YbE0O/ZieOHHC8tgnPvEJy/a3vvUty7Z5HpnnjZ1sylY2+17rx/9yOzE268xrlk3X6m/Nbb1jG1h/Tjbr2G7FPL7mGhGDg4OW7be85S3q54GBActj5nfY3M+dQu6vsu7DmTNnMDk5icXFRaTTaTV1jn7fbRVA0DuGzNcwSR2po6MDxWJR3cslkK8/tx40kIVOpWNF1l4aHBzE6OgowuGwGkHZaoFXSeSQThKd1BnD4TB6e3uxZ88eTE1NrUvk0OuUeseZnvyyUV1JTxwAsK6e2eoYSv14bm4OuVwO0WgUfr/fss5FMplUn6esUyYdd/Jaesep+Rnp2dp6ObO+ZY64lL9tdh7o9VDzOqf/vRnAkPNNP/Yy0nRiYgLpdBqxWAy5XA7Dw8M4dOiQSqDZ6XUYevH0c1o/t/X2qL52SjOtgoqt7pvyvdJfWx+R1tHRoRaTl8WrN6rnXS2tEtD0Y1er1dT6F/l8Xt1PNktc09vo+nGUkeb61ELma+9k5rmqXy9lW85XuU/KMc/lcmoWhHw+r5I40+m0mnJRRiHKfVjqw9IvFAqF4PF41DVZ7rHhcBilUgnBYFAlvAWDQRVE0/ti9L/Tk970Nm2zgNK1wvZdx27HwkYVbJ3Z4Gvlai2mIhmXW8HuMTEbBa1s1vATdjMb7O7fVpM5LjdjLqjXSiqVslUuGAzaKmfnuNg9dls9F5/d78XlRvWpNf1GL8crGAxaMr5kjlhzTuB6vY7l5WUsLCwglUpZGn+i2TXWbjBCGseSCaYPi9XntNVvYnrlx3x+s6G40T6Y9Mw8ef1CoYC5uTk8++yzKmtQXwAKAMLhMA4fPow77rgD99xzD3p6eizZBd3d3WoIub4PchN3u93YtWsXjhw5gueeew7xeBw9PT0YHR3F+Pg41tbWMD09jcXFRcRiMUvD1wwO6A1GfVir3sis1y8uGD09Pa1GZASDQezfvx89PT2W57WTNWMe456eHuzduxcrKytYXV21zJ0sz1er1ZBOpzE3N4fR0VH09/erRZebdYSYQQnzM9YzQrLZLObn57GwsIBSqWRp2HZ0dKCzsxNjY2O48cYbLde3y8k+apZdZXbcyO/04auSfeJ2u9HZ2amu6TIqQz5DeY2NhoKbHQxyjl1O3eNarPwREZF9ct+UQMTS0hKef/55zM/Pq3WU9FEO0gksCSJCguNSzswQNsvKa+rBHX2qB/Oeq2cPA7Asvry0tKQ6QWRdp2ZTE5r0UZPmMZFEge7ubgwPD6sRh3piTbNAhJ4hao64kPeuv47sh/l7sx5n1msqlQqWl5cRjUYxPz+v1neTBJ50Oq1GR+ijXsw6T7P52PU6nnQY6dNnmuuUSYeSz+ezJH7IsTBHz+rHQT8+8hr6uSK/0wM2eh12dnYW8XgcS0tL8Hq9yGazGBgYUKO89fOJqBk5P/T6NQDVBpMR7TI9LnBpPQmhf4/0TtZm0waZo330NnVHRwey2SwqlQomJydVH5rH40FnZ+e6Nd8uJzHE1CqIYOd5mgVa5D3o15p8Po98Po/z589jcnIS8/PzyOVy6jqlj3TQp4oF1k/hJ9cFOSaJRAKxWAz1eh1dXV1N+wevxXaM+bm06iORx/QR8BKgkVkHotGomu43n89jdXVVJeTJZyPrbcrahGYiiH697+joUP1C+n2po6NDTRscDAbR09ODYDCIoaEh+P1+9Pb2qu+SBPllhL9+D5GfZTSFuc5hs+OzHTH8TURkg3lxB6Dmnpdhp16vV2VS6Z2/MiJgaWkJ0WhUjaTQtWpg6Q0iPQuq2b7p83PqZfRMCLl56pUg80bZKmvDzg3NzJiRjILz58/jueeeQzQaXdfY8ng8GBsbw0te8hK85CUvwY033mhpuMmw8UKhYJmaCIDKFpHAzq233opXvOIVmJ6exu7du3HjjTfixhtvxMrKCo4fP46jR4+qxc7MBqVUsMPhMLxeLxwOh5p7tFKpWI6VvLdYLIZkMolUKoXBwUH1niQY0WzYsR2hUAj79u1Ta3rkcjm4XC5Lxadev7hY5uzsLEZHR7F///51o230Crze2dDsc5MOEwmsTE9Pq/mR9SwMp9OJwcFBjI+PY3x8XHU8XG4DVm9UNMtY0R+rVCrqvUnHhUzZpAcfzACCfDf1fdOnemgWhOL0BEREpJNkj2w2i2effRZTU1M4efIkUqkUcrmcJblBEsbkvgrAcp+SqTL1e48E2PWEA33RVvN59IQXSTQBrPdVeT6Xy4VYLIZUKoVvfetbuOGGG1TCXXd3t2W60GbTK8r9XU+E0zvbpfNvZGQEg4ODSKfTiMfjqlyzQId+r5Z7dLOkDT1wob8nfT/0+7ueZCN1BykvU1zqwSC9TmV2gDocDni9XoRCIYRCIbXAdzabVYEcGfEnAQ5JZkilUkilUshkMmoUqUxleeONN2JhYQHT09NqTRF96hA9mGS+X3lc6sFm1q9OHx1bq9WQyWRQKBTwzW9+E6dPn0a1WsWRI0ewb98+yygNolbMTlVpN0mnqHS+6uXleyPb5vNt9FqANaNd/yff7VQqBa/Xi1QqhXw+r0bOt2qTvJAO2hfbqdvqvcjP+gitaDSKTCbTcj0CM4GqVSKjjC6XUe4ysnwnBRsv93ORa76MwJeFvGWk2MLCAnK5HBYXF5HL5VQgQsqXSiU1KlFvq8pzy/96f4HZx+L1euH1elWSZSQSQblcRiAQUG1dWctJtmVtRBnJL/0istaPvh/bPfigYyCCiMgGfX5fiazLzUgelxEJ0okNQDUQk8kkZmdnMTExgcOHDwOwNrDMrBGgdXa5HqSQAIbM1RsIBNZl++sdsYVCAZlMRi0oqDdUN5rqYqMbm95Y0itblUoFhUIBCwsLOH/+PKanp1WmnFRevV4vhoeH8Z73vAdHjhxBf3+/mitRX1BRbryANTsvEAjA4bg4tF+mYRoYGEA8HkcwGEQkEoHL5cLQ0BD27t2LSCSCWq2Go0ePrltMutFowO/346UvfSmGhobgcDgwNTWFY8eOqeOlj0aQ912pVDAzM4Ovfe1ravjm7bffDuDiaCh9yLx8dptVFNxuN8bHxxGPx5FIJJDP5+F2u9WIG336renpaQwPD+Ouu+5Cf3//ukwiPZtP6B0YQhbk0tfckLVP9ACMx+PBwYMHsW/fPnR1dVkWcpfGyGb0Spw+AkKyE5sNI+7q6lJTgJTLZTQaDUvGidkR0+o41+sX14mQRlSzzE0iIiKhd+wkEgnVQSHZ9EDzhBW5P8k9Rw/ayz1Tz27VO55k5Hize6o5fU+r7F8JGMh9NhqNIhAI4NSpUwiFQmrf5N5nZlWa70v/nV43k0Wr+/r6EIvFLMkezTpIWiXUNPtdq+QJ/We535v3fT3xRZ/mRB9xab6GdB653W4MDg6iv78fQ0ND6vlyuZzKus5ms+q4yZQceiAikUgAuBio6O/vV6NJZSFql8ul6jP6ezBH12xUNzGPhf4+9FEnUl9NpVJwOp04deoUgsGgajvo7QW7iUftsFH9zeyMNs9vmWKlXC6raVbkn3Rcy/v0+XzweDwq+1iCNvq5bY7ENj8LM2lso5FF1zr9+6UHF+S74vf7EQwG1fE0O2qlzt3q+qK3C/T2aLMRyvK5l8tlLC8vq++kw+HAvn37EA6HAcAyNY65L/K/uT/tzCTX2/XyfSwWi1hYWEA0GsWFCxcwMzODbDa7bpqrZvsk56l5jZXERACIx+OYmZlBvV7H7t27AVwK/poj4q42s1Nf/73sr92RW/I30ici/TjSD7K2toYTJ04gmUxiampKTbVcLpfVaBR9RIoefDcDEc0CE3IemcGkUqkEp9Op1gPxer2YmZlR60rIdcfhcKgREeFw2BKMCIfD6O7uRm9vLw4cOIBAIGD5O/mObncMRBAR2WAO6SuVSpZFdYFLQ1D1gIXc7CuVCqLRKM6ePYvXve51atohySAxtWq4ScVFSANGbpZywyyVSmqhPp/PBwCqgzeTyWBlZWVd40UflWE2gDYilRjJ6JLjlMvlMD8/j3/5l3/B008/jUwmAwCWTutQKIQbbrgBt912GwYGBlRjXe/Qlpu83IT1Rpo+1F/09vaiu7vbknno8/kQiUTwUz/1U9i3bx++853v4LOf/SxKpZKlE8Dr9eLIkSO488470dPTg3g8ju9///v47ne/i+npafUezI7varWKkydPYmFhAc8//zxisRhe85rXqH2QyogsoLwZqWjs27cPqVQKx44dU5+7mfmfz+ctizzrw0OBSxVx8/PSMyelI8HhcCAej2N1dRUnT55UQTK98t7Z2amy6GQkimRF2q3MmkE2PdNRKm36d6lcLiMSicDn81kql3rwQ4JX+gLYZmeQ/F7P7NQrbzspU2grmZ+pObWiPrXkD3/4Q8tj//RP/2TZHhsbs2y/4Q1vsGybUxn29/ern81sTbOCv1kQzFxnQJ+G05wy1Hxucxi2yfxe68fIPH5m2c06/raygWi+r42mmDSPl9k4NI+Jvr4EAMzPz6ufv/CFL1ge+/rXv77hfjTrHGjFbHCZIw5lYVYRjUYt2+aUp/rzbXYMzNc2z0Hz7/X3ZZ7P5ntslumo2+zvN3ouc78kg12Yn1dXV5f6+ad/+qc33C9zzYidQOpe2WxWdbTL9A5mXUTOZYfDoe75nZ2dlmmIpFNDz2o0O8cSiYTlc6tUKsjn8+qerAcq5P6lJw3one7SeROPx1EqlRCLxeD3+1Gr1dDV1aXqMc2mktU7uswkB7mnhsNhjIyMYP/+/SiVSpienl43taW5T3KM9Petd+qamb9m/ULv/NGfS5/uxRxlIr/TR7kK+e7K5xYOh3HnnXfi4MGDuOGGG1QSUj6fRzgcht/vRz6fh8PhUPN8S31PklLW1tbUyMy+vj74/X44HBen7VpZWYHX61XTM+nnmj4Vjd6x1OwYmJ2s+rGQupH+3nO5HEqlEr75zW+qNk1/f78qb3eNl83uiZtp1s6R96+PENEfl3NKH9EiAUHJKM/lcmr6tHQ6rRaZTaVS6rMKh8MYGhpCb2+vmhZF1suQOmEoFEIwGLQkl8l3TT5n+b7L91m+yzt1zQ15z+a5Ju/Z4/FYEtuaBRZa3af073Kzv9O/x/J/vV5XUzStra0hEomgr68PlUrFMuWYXl5/vlbnYDuY7R7g0rkundKSfKbPrqD/zWbTKplB2Gq1inw+j0QiYVlDQ0+Mk30z//5y3tfl/m2rv9H3xwzaCPM8aPV7/X8JIEjSqByTqakpxONxnD17FoVCwTK6Uc4X/b5lBkH135mBCP270ipYDFz8TGOxmKW/QOoTMt2yJOLJ9bmnpwdDQ0OoVCoqcXKjAO52tTOvkkREW0zvPNc7TPSREm63WwUBpAPX5XKpxmKpVEI2m1XzCwJYd/MwKxT6zU/P+pHHpUEq2SiyOJLM0Smdr9LYAC52kKVSKRSLRdX5DFys4Hu93ssKQuj0xqY09JaWltQUP3rDwuVyobOzEwcOHMBrX/ta9PX1qUacWUmSG7LeSNQb/WbDVTrE9ZEAUqkbGBiAw+FAuVzGk08+iZWVFfT09GBwcBCJRAKJREJlSnV3dyMUCuH+++9HR8fFeZCPHj2qgkhmhlSxWFQVGrfbjYMHD8Ln8yEcDl92R7dk10UiETWqQx8Oqq8DIg3L5eVljI2NqRElct6Wy2XLVANy3ujvQZ5PnmttbU1Ny6Sfjx6PRy26HolELEGjVotdtjpXKpWK+j7JlBerq6stK3/SgJf3o480kXPLrMTpnSdmAEs/htdC5ggREV090pEhdTGp4+n1E5fLBb/fD6/Xi4GBAXR2dqKrqwu7du2C2+1etz6WTMNg1mnq9ToymYwapSjJHU899RQKhQKKxaLqBNWnaZL6qX5P0ztzOjouLni9urqKH/3oR1hZWUE4HMbAwAB6enqadu60Cnjp92mn0wm/34/x8XFVv5JpLZsFGiS4oQcLpI4t/8yOQukg1/9OHpPPR55fnzZGf1x/Pb2O6XQ6EYlEEAqF0Nvbi9HRUQwODuK+++5DT0+PSm6R55HMVH1kp173jEQiqFQqGBsbW9dBVK/XcejQIbjdbqytrWF+fh4rKyvqucypbaRDKhwOIxQKIRKJoF6vq46zYrGo1l4zR3jq9Sn985Ns8snJSdRqNdx8883qfNyKhIxWHWLmc8u+6PVRPftYyHuT0ejSkSjrmeVyOeRyOUxPTyObzVqmtwGgvkPy+lLPl7p+V1cXBgcHVfnOzk7s378fe/fuRVdXFzweD/x+P3w+n6rv6vVTve2xU+kdrq3aoxKI0ZOA9E5aM+FAvxZKe1ZmEpDz17xmyuvJ38vnurS0pBK+wuEwent7MTIy0jQwpL+G+ZztSgQxO6ZlmrdMJoO5uTlcuHDBEuDWM+/1wK9cx6XPQd6HeZzkeWSKod7eXlSrVXUfAqyLHl+uVp+J3WNhPo9+bumjFySoJOeXtAX164X+nPq5JvfEarWKTCajpr6anZ3F4uIiTp06hWw2i2QyqY6XuT/mtbPZyAf9dfV2p3m89P+FnjxoBmBlOkGZnlmuPSsrK1hYWFD3jcHBQQQCAVX30BPstjMGIoiIbNCzO6TRKdngUjHQOzb1ioZUeKrVqsp66Ovrg9frtczt2yzLpNlNxOxgBS5VqoPBoGVIrFS+9WH8hUJBLa4YDoctjUT9PZoVBdknnZkVoFdQa7WaGm4q2cZ6xtXAwAAOHTqEG2+8UQVQzA5h2Q9znn8zO0F+px8P/T1IgzEQCKC3txfj4+O46aabEAqFMDIyggMHDmB5eRnHjh1DKBRSN3RZkDydTiOVSmFpaQnLy8vrOuhlX2RNjMnJSVy4cAG7d+9WgQE9e3CzyoGU0Sv2+ueg/1ytVlXDS843fQSA+bnJeaZXduTzknNjfn4e+Xx+XWXd5XJh9+7d6OnpsXSe6GXsNmJlP6rVKorFoso0NbNNpJNDRn6kUimUSiXV4JaF8jo6OtS0Evp5I599q4a5+b3bikY4ERHtLHJfkalI5P4i9Q25B3V1dSEcDmN8fBzd3d3o6enByMiI6jjSO5akY0WfR1rP9C6Xy6ozJp1OY2FhAdlsFtlsFi6XC/l8HtlsVi223KwjWr/HSZlyuYwLFy6gXq+rRZwjkUjT923WFZrVVaVe19vbi8HBQYTD4XULdZvH0hyt0KwuJ9vyGlJWn7bEvH+bySl6B5UcWz05ROpZfX196O7uVnXCXbt24cCBA/D5fKpzRz8eer1Oz+Du6Li4IHW9XlfBEz2gVK1W0dPTg1qtht7eXiSTSayurlrei+x3R8el9SX6+/vR3d2N7u5ulQku61DINJrNPn/zMxTVahWxWAxOpxNra2sIhULo6+trWx2oWRDCbEPIfkn7SToSZcol6byNRqNYXl5GMpnE9PS0CkRMTU0hk8kgHo+r74S+Bok+xaoc31AohO7ubkSjUeRyOXR0dKjs8Xq9jp6eHlUmFArB6/Wum8622WiVncY8hs2+s3Jc9DVt5FzUE550+qgF/WfzdYV5jOU7JW3N7u5uDA4OAgAGBgbWJV7p11nztex8fq2+H3b+1rwWFYtFlUi2uLiogmd6IK5VwFVfA0YfbWd2nhcKBaTTaRQKhXUBJL1teTnnrt4hr//ucs9/M6itTyEnIxDz+by6TzYaDdXO0wNXACxtbLlHyBRVMvXvysoKFhcXcebMGSwvL+PChQsolUrrRog2e596cKLZe2gVaADWT+FmkvdgjjKTsrLWkHzesoB1NptFIBBAqVTCoUOHAKBpf8F2xUAEEZENUmmRC7ssTCed/pJd1GzqEKkIS6V/dnYW4+PjqoNav8npDQizEaE3gswFqaVDVoYQm4EQvYNfMoiSyST6+/tV404yV5o1FvQGo95wNDvW9SBEuVzG1NSUmusSgOUGOjw8jJtuugm7du1SWUaAtdKlNxbNjmOzAqIHKySjTioj8jsJ4vT09Kg1Ffbt24ebb74Zy8vLKJfL2LVrl5oGSBoWY2NjSCaTiMVialoDveGpH2Op8Jw6dQqHDh1Sn4nd4e7ApUarNJKlo10aaE6nU43yKJfLSKfTWF5eVsdPgk+SNWM26ptVUPSFxc+dO2eZLkDOP6/Xi3379qmFGqXzpFl20Ubks5UGRD6fRzwet0wZJueVZHbMzc2hr68PwMWsPckIDQQCCIVC6hyS6bgAqHVD9I4jfZi2fk6Y5xkRERFwccSrz+dDV1eXWtxXMjW9Xi8qlYpatPmOO+7A6Ogobr75ZpVFLaNP9TmmzUC+3O+kjJSTKZmKxSK6urqQyWSQy+WwurqKpaUlPPPMM0gmk2qKPLOzRB8RKFMSAcDy8jKy2Sy+9KUv4VWvehW6urosdUKTfp+UjkepG0pdY2hoCLVaDXfeeSfOnj2L8+fPr8sYlfu/1BX1+qxeRo6NTG/V19en6jf5fF6N9K1UKqoOYtYNZb8Ba/1UX/RTgkU//dM/jdHRUdxwww3o7OxU0/VIHUSOi57Br7+mGQDRX9+cxz0UCqFaraK/v1+tISf7LaNIZPrSgYEBvPGNb8SBAwdUhre8D8mM/fSnP60W69U79fTAiFlPL5fLSKVSqFareOaZZ1Aul7F79+51HW0vhNl+0euuQg9Syfmpr7eXz+eRz+exurqKYrGo1n2YmZnB0aNHsbi4qDLK5b3JFLTSHtP3w+yk1Tsss9ksVlZW1LnocrkwMTGhFnPv7+/HrbfeipGREfT09GB4eBh+v199vwFY2iA7kR6AMwNeZv1fD9Dp1zYzMKmPKNJfp1kinPysd+briXkyNeTq6irOnz8Ph8OB3bt3W9pyev1fD6yabaTNjsML+Zz1jmz5fpZKJbVmgSRZyWuYbXLzNfVgQquAox7slmCqXFv0ny83iGYeM/017R4LeQ9yTCQwU6lUsLCwgHQ6jcXFRSQSCQQCAZVIODw8rBZ6brbf8pyywHQymUQmk8HU1BTOnTuHtbU1zMzMIJPJoFgsNl2TUPZRD2zI78x2YqvPxyxjfkat+luabZtJdLLeTSKRwMTEBEqlEvbs2YPu7m7s2bMHgUBArdWynTEQQURkgzR05CYgixbqjZ1mi5rpFW+5yR49ehS33367yiiX4ehS8ZAbvL7WhJ4RJh3Q0oCTLDv9Zio3L72RK5X7ZDKpMomksi4Vdxleb2ZtSIVPr9jL/9LAkEqdvL4M/5epqfQFpzs7O1WDTyrx0nkuHfZ6hoxklumNCDNzQCpc5XJZNQikvLy2vIbT6UShUEB/fz/27t2Lffv2YXh4GENDQxgaGkIkEoHb7VYdDQMDA3jpS1+K8fFxBAIBfO1rX1MNPp0cg1QqhcceewxutxuveMUrcMMNNyAYDCIUCtk636TTPxQKoaurC319fSgUCiorTI6XHOtEIoFz584hFoshGAxaPif5Zw4l1/ddKjYzMzN47rnn8Pzzz6vzUt6Xx+NBd3c3Xvayl2FoaEjNpyvnrT6yZzN6tkq5XMbq6qpapK1ZcK6jowNPPfUUJiYm1CJ02WwWjcbFuakHBwexd+9eZDIZ9Pb2qucfHBzEnXfeiaGhIZXJ5vF4VCeQfF5yzjWrXBOQTqct2xcuXLBsnzhxQv386U9/2vLYsWPHLNvm/P3T09OW7Te96U2W7WYdSsIM7pnfRxm1Jsx1IPTnbtVAFuZ5sVkjrNnc463+drOOn3Z2bmzUEGqWeagz1wpZXFy0bH/mM59RP//gBz/Y8HU3W4vBJNcBANi3b5/lMZlmRNx+++2WbfOcfOKJJyzb+vm92Tzo5jEy15swH9fPhcu91pjHf6O1RsznNvfLPL7m+zx79qxl+//9v/+nfr7rrrssj+3ENSFMUv/y+XwYHR1V9QPJSJdEEKnb7N69Wy1orI9qdLlclkAE0DwJRZ8uQzrNZU2bQqGAQqGArq4u1RmzvLyMeDyO6elp1QEj9PqgXq+U0YiLi4uIxWJqSk+d3qmvn196Z6FeN/T7/ejq6sLevXuxurqqFmPW/16vf0jdQu7ZZickcHF9kp6eHtx8883qsUwmozqr4/E4MpmMmk5Sgi3NRohIfUU+l1AohP3792Pfvn244YYbMDAwgL6+PssUPHqnnX5c5J/UKc0AgP5eJSFJ/1tpE8gITzkeUl/zer04cOAA9u7dq5J2ZMSC/L0ESI4cOYK5uTksLS2hUCioJA8zE1yvXwFQbZmFhQUMDQ2prOmt0KwuqGdt65180obJZDJIJBJYXV3F8vIyUqkU5ufn1WgSWW/vwoULlulUzCCLuR+tOgv1/dKTb2Te/nK5jEQigWQyqYIgXV1d2L9/P/r6+tDX16c6RiXp53Kzwq8leh1Z/z7pI6X0YyyfhZ5U1uzeLueD3gbW/x5oXjfRzyEZOba8vAyH4+I6LzfccIOarknvsDevuUDzhav11zWvf+ZIhY3o57nefpdpxlKplBrFo7+G/jpmXVjOdb1tp3/H5bol1zkZeacHIvS1Tuy8B/392v2bVsdUb6NL0qZMOzg9PY3FxUWcP38e8/PzCIfDiEQiGBkZQalUQnd3tyX5TH8NfdRfsVjE2toaVlZWcOLECTz55JPIZDKIxWKq/dlsH839a3ZfbBaMEJtdc8z2ebPj3Oy5zJk34vE48vk8MpkMdu3ahcHBQUQiETQaDdWPsZ0xEEFEZIOZmSCVLmmoSEVYb4gAUJ3skuFeLBZx4sQJnDp1Sk1PJB3oeueovKbQK13ApYafPg2TZOvt2bNHzRuoT1GjZ9lnMhlcuHABhw4dsmScmdFzPThiVsKASw1keY8ALBlu4XDY0pktlcuDBw/ixhtvVA16PdAiwQh9WL9eURRmZ7vQ5+2V4yhZhtLoksXGZU0MWUyyv7/f8l4l60CCRm63G29605sQjUbVIleFQsGSWS/nwNraGh5//HG13sOBAwfWjWRpRRaYdjqdCAaDGB8fx9LSkuXz1xte+XxereswPDy8rnGsZ/5I0MGsaJVKJUxOTmJhYQH5fN7SUe90OjE0NIR3vetdagSLPkeyXjG9nEBEsVhELBbDxMQEJicnUSwW1wXVJPvR4XCo4Jb+2TgcDpw/fx5PPvmkqnTLvvj9fjz11FM4fPgwhoeH0dfXpzpvZD5o6Rg3h28TEREBlwIRfr8fY2Nj6OzsRK1Ww+rqKhKJhMqgD4fD2Lt3L/r7+1X9Rx91J/UguUdLFrjQO3v0LF4JgoRCIZVU0t/fr+5rMzMzWFpaQiwWQzqdtkxd1KyzCoDqCFteXlaBiGadhFK/1euH+r5JXdPlciEQCKCrqwtjY2OYmpqC2+1WHbx6R6CeiSzrEphrBUgdpbe3F3v27MF9992nOhQTiQQKhQJSqZRah0wCNPrID32qSj3AI2tz9PX14fDhw7jzzjtxww03qHUYzPKtOlzl2OqJMvpnJ++p0WiojmrZN6nb6KMY9M/b7/fjxhtvxOHDh3HzzTerZAq9c0zex1133QWfz4dKpaI6NHO5XMvgkd6xVSqVMD8/j927d6spObeS3iGnJzdJEpN8XrLg8MzMDM6dO4ezZ8+qbX0dlEqloj5n87yU42K+T3N/zOOiZxlLGZkWpl6vY2VlBfPz8+js7EQ4HMbKygr27NmDsbExhEIhFTjayXVIOU5yjppTlUndHbAmkgHWz0W/DsjftxqFJQFT/fVbke9aLpdTCXfnz59Hb28vfD6fCj7q32n9dTYKQrTaN/PYNGOe9/pIiFgspq5dertHv36YwUMzmGJ2eOvHXEZY5fN51clvHmu75+sLOa/1v9E73vXgo0y3JiMhMpkMpqensby8jLW1NWSzWRVYcDqd8Pl8GBoawsDAgBrtoo+MkefM5XLIZrOYnZ3F1NQU5ubmkE6n1TWuVZCr2b62uo7IezQ/f3l/+u+bBXDMv9msbKsAiCQjJhIJ9PT0oL+/X5332xkDEURENuiVFKlErK2tqWF9csOXyrJe8dDJPL/Hjx9HX18fwuEwPB6PpeIvr6UPqxb6iABzv+T30vEuWXFSyZPnbDQaSKfTeP7553H33XerTnbJrDIrZM2yUJrdlPX5GWVuR1m3wBwW6/V6VTZDtVq1TD8kr6NXvvRFl8xMFvPmrd/AzaHS0vh3uVzo6upS+6YvuKxnapmLdzudToyNjeE1r3kNnn76aZw+fRozMzNN55es1WpYW1vD0aNH1dy7l1MpkMZyd3c3Dh06hBMnTqBYLKpzTirokuVYrVZVJpyeXSTnpt74kixFvWEn56YsMKkfY5fLhVAohIMHD6Kzs1NlZko5fU5KPfOvFTlHMpkMzp8/j+PHj6tFE/Xvk34u6IE+s4GvB8z0RqkMvV1aWlIdDJ2dndizZw8OHjyIffv2YWRkxLIIIUdEEBGRTuoBkhzQ0dGBw4cPq3mZZb0tScCQji/5W/0+ZY4eNEd7yv1Tvwfr0/FIwN3n8yESiaCrqwu7d+9GIpGAy+XChQsXMDExgWg0qpJP9OQZeW7p4JOO3XQ63TQQod+DZVuvc+n1M6m3jY6O4sCBA1hbW8Pzzz+v6iZmfVJP8tEDM/q9WJJA9OSBoaEh1ZE/NDSElZUVpFIprK6uqpGjekedPgpFOrM6Ozuxb98+9S8cDlsW+tQDSHKc9OCETqZUkc9Tr0NLealrSfl0Og2fz6emf5LnlLU2RkdHce+99+LAgQPo7e2Fx+NRdWZ9tK/P58MDDzyAw4cP44EHHsCZM2ewsrKCyclJxONx5HI5FfyQJB89gaRWu7ie28zMDKamptQaHy+EPgJF/5z1Or0kBMn8+NFoFDMzM2qkw9zcHM6fP68y3PVAjTyHntSjd9DpdU85l/UAg/5dlH1rNoJC70jX55ovlUpqxEZ3dzcGBgYQiUSwb98+NZp8J9ch9fent8X0NrB8DvrnpH//9HNPritutxsej0cda3Pkt94Oa9UhLsG9TCZjaZuMjo6iu7sbfr8fnZ2d69qb+nuT5zGfd6NO+FbtZSHnjhwPuW5lMhnMz8+rKfL066PZrpJjpd8n9CSzZvsqZQuFApLJJFKplFr0WP/srhT5fPQAeblcRrlcRjQaRTabxbFjxxCNRnH69Gk1o4K0TV0ul1psev/+/dizZw/C4fC6JEo5hxKJBOLxOJ577jk8/fTTSCaTSCaTTTv0zWtAs2uL2CzopP+sfz7N7hv6a+h/r9/75fX0vgk5lxyOS7NdZDIZtf7oyMgI9u/f33Ldp+3CdiBiq4d2+P1+W+WaVYhejI0im7pWi2vppCNmM0NDQ7bKra2t2SpnDoVvxW5Gg91jstVaLQxjMofMt/Kv//qvtsq98Y1vtFXOTiVsqyONds93u5+ZOS3Fi30+u+V2ajaIkE7UeDyuMriBS5UE+VlvROnZ3cViEWfOnMGhQ4ewa9cuhEIhVCoVdSOVvzOHw5sNG/180W/oMne+XgnXr+G12sVFiScmJrCysqIWYtNHGAj9tZsFKMzovexLqVTC6uoq1tbWVGe5/lxScdA7nHVmxk2zOTAlC0//m2b/pKwcN8k0Gx8fR7FYRGdnp+rElkaeHCcZSaIPZ+3p6cEdd9yhRpgkEgnEYjHLfsi+5vN5TExMoLOzE7fffjt6enpsf49kpEw4HMbIyAj6+/vVvMj6tEx65VbWudDnQpaAhE7OB2lkSfacvqCZXvn1+/2q0SXzTsrnv9GUT63I5x6Px3HixAmcO3cOy8vL6ypb8jnIZ90sG0TvxDBHnMgCdvF4XDU+/H4/RkdHkUgk1MgPySAxAxlERETApTqGjGCVEQ8yEqCj4+I6TtJh3Kzupm+bIxvlXtbq7+RvzOeQ5/F4PNi3bx/q9TrS6TSy2awlQUbvRDTrR9JZ1aw+Js+/WWecPgJXnzJxZmZGvYbJrANKHUDPmpWRDrJ2gkyDJXW0dDqNVCplmT5VT8zRj6uedON2u9HV1YXOzk6EQiH1uckx1bNs9Xqd/rnpdR6zw1I/3nJuyHNKnUsCNH6/H263G263WwVa9u3bh6GhIXR3d6s6s/55y2heh8OhAhWySLh0QJ0/f161D8wOfD25Q/YnkUism8bNLrNDzWwvyOtLAGJtbQ3JZBIzMzO4cOEC1tbWsLi4iJWVFayurloyyPV6nn7M9WQks36ov3azn4X+nGawTe/0leMkST+S7BWPx9Hf36/Oz50ciGjWQat/Z81kOfN468FHAOo7JwuBy1ogpVIJ2WwWwPppBQFrG9i8Xso1T84xr9eL5eVlRCIReL1etdi4BExaXduadQ6b76VZe8R83/rvJCgh7a1EIoFEIqECmXpZ81hupFnCojyHHMt0Oo14PA4A6OnpsQTGzSS+rabvj+yjrG+Yz+cxPz+v1jqU6YakrSsd7sDFAG4ul1MjPORerL+GtM3j8TiWl5eRSCSQzWbVNbBVp79+zWrWD9IseGMGLc02cLOglnlM7Bw7/Vxrdo3VR5fIdWmrR7a1A0dEEBHZYA6bdjqdKttaMsA9Hg8KhcK6rGqfz4disajmNwUuzos+NTWF0dFR9Pb2rruxmUEGMwtLv3lJpatcLqv5VeUGpGe7A1Ad7aVSCXNzc5iYmMDw8LDKEpEOX7MybVaszUqoXmmS7IWJiQnEYjE1rF8qjpLJJw0zee96FpyZVSQNEr0BpjcazEZKs0aENEDleV/60peiWq2qaYaaBWH0RpA0sAOBAIaHh3HrrbeiUqkgFoshHo9bKjXSKS7rH5w9exZHjx5VnQSb0RvMXq8Xvb29uPHGG5FMJtXaCGYlJJvN4plnnsF9992HYDBoWZtEjpFeUZdzQxqFemaO/jcul0tNjSBBG/28kO/D5VScJRh2/vx5fO9738PU1BTy+fy6TA/5DMrlsgqeNOsMkDKtOlnkuyfzsabTaaysrGBpaQn5fB6HDx9W722rEyB2gpWVFcv2pz71Kcv2Y489pn6ORqOWx8zRMdK4FF/96lct2ydPnrRsHzlyRP2sZ50CmwfvzfIbnZvJZNKybSZ9mAkqmzXWzCDpRs9tNhjMRJetDI6ZjXrz8zHvLbpUKmXZfuaZZyzb5mf5jW98Q/1sfu7mZ2e+RzNhyUz8eOCBB9TPb3/72y2PjYyMWLbNdUnuvvtuy/bu3bst23/+53+ufs7lcpbHNvvczc/OvHfqj5vJIps1HM21WmRxYqF/lubxND/nzV7LPE/0tVzm5+ctjw0PD2/4XDuBntwg03tIR7hk8wLWaZDknqt3hktdRJ8LXbb1UbT6vdrMNNY7juRzjkQiCAQCuPvuu9HT0wOv14tUKoV6vY5MJmNJHGhmbW0NExMTTdc4aTY9J2Dt+DHfX39/P2655RZ0dXVhZmYGCwsLWF5eXpeRbq5tpiceyO8XFhYAXLwPSVKE1BF8Ph/q9YtrLSwsLFiy/6XOpo8Qlbq6JCUMDg6iu7tbrXklQYpm10X9mDfrcJTjpNdV9axmvX6TyWSwvLyMqakppFIp7Nq1CwMDA2ohZFlDbc+ePQgGg5Y6qpmYI/XEQCCAnp4edHV1IZfL4ciRI/jKV76C48ePI5lMrkvyMOtPmUwGi4uL6+6bdjRrC+iBHOlULBaLiMfjiEaj+OEPf4jZ2VkcO3ZsXeejdEDKcTU7G/XvmRk80MuZvxf638iUVnqnp/5P2hr6+elwOFAoFBCPx7GwsIBIJIKBgQH1nbabCHgtMe/Zcj7pn5d5nPXvNrA+aBCJRBAMBnHDDTdgdHRUBRVlSi6ps+t/o4/qahV4KpVKiEajapqmQCCA/v5++Hw+y3Ss+pqIZnvSbDs166hvdk3Ur+P6e5dAVqFQwMrKCmKxGM6fP4/l5WVLkLZZh/ZG5B4ix0WSEuV8leu/1+vFuXPn1FozsraTzKKgB5M3Cjy3Csy0IsdD3o8eKJqZmUE8HseTTz6JRCKB+fl5FXSWcvoUbjI6SgI4HR0dGBwcVK8j77dQKODcuXOYnJzE9PQ0YrHYus/FpL9/vU9BnlsvY15/5X01GtZRHxsFRvVrpv7czY6zGYww76N6gEdmTrgWMBBBRGSDvli1RPEvXLiAYrFomR82EAjA4XCom2e5XF7XgSI308nJSQwNDWHPnj2WRqx01ptZYjK0U7blpiujIKLRKGZnZy1D0+VmVSqVVANW1ksol8s4c+YMDhw4gJ6eHrUPZpaAw+GwVM5bVUIk00MqQWZWvTxPR0cHRkdHMTw8rIbHyvObWU5mZ7I0xszKgux3uVxWfyPPLZUxaRRKhSsQCKgGhR48MN+7TM8kHQIyZdLIyIhaW2J+fh5ra2vrGtTSCF5ZWcG3vvUt3HPPPRgZGbHVSJHnAC4u1iida+bChvI+q9UqTp06hdnZWcuiZProEzmmEpyS6QFmZmbwd3/3d3jmmWeQyWQsldC+vj7cdddd+Imf+Al1zPTP1NxfO4EICYR98pOfxKlTp1AsFi0dJc0qweb3wSwjlUbz78xGpWRAxWIxPPvss2pI8C233IJwOLzptFJERHR90esy5ohAfWoIvfNZr1+Y9RVhdo7ogQJ9JKCeZKF3kEo9Q8p0dnZiZGQE9Xodi4uL8Pv9OHPmjKXjwkwiKZfLWFtbw/nz55t2Qut1B7MDxEze0JM9uru7Ua/Xcc8992ByclJlsUpdtlnnsNn563BcXBtKFi2ORCLo6emx1AGlDiz1Gj3BRT+u0lk8Pj6OYDCI7u5u3HbbbRgeHlYJKVJHNLWqd+qft14nkfqQOcWPzA0va0PIaMxbbrkFe/bsQV9fH7q7u9HZ2ammb5X1uPR9MetAMnLX4XCov3E4HBgfH0cul8Pc3JxKSNITmvT6czabxdzcXNORK5uRNomeEKKPZJC12ZaWlnD27FmVnCPTHMmUoM2+I/p7bZWIogcJ9WCQ1Nf1YJ4+0kIyxptNV6V/7vI7MxhVLpfV1GOBQEBNAySdvDuV3lnf7J9dcv0MBoPo6upSgUIAKmkok8lYAlP6PgDrAyRyrZTAVzabxerqKhqNhkrU83g8am1E2Q8zoGWei/p1b7Njov+dmQyVzWbVmn7pdFoFTzdat8Ds/G71+vo1Wp8WS58xQdbsafYe7bIbhNDL69dGmXJtdXUVsVgMsVgMqVRKjYjRj6F+TKStKwEdaQ/rbfRSqaQWAE8mkyrAudH71L/Xzf7Xg9lmMp60iyXhVP6X49/s+2DeQzY6vvp51+y+JkFoCWT39PQgEolcE6P72domIrJBbnIypFIqEVJ5kAaYPiWONLb0yLRUXjs6OjA7O4vnn38e+/btQygUUlPe6MPbzWHUsi/yGhLwSKfTOHfuHJ5++mlLlqTcBGW6AH3/CoUCnnvuORw4cEA1ePTMH+DSTV9+rw8LN2/qEuCoVCpIJpM4ffq0Ws9ADzQUi0VMT09jZGQEu3btUpmvZhDCzMxoNg2TvEfZFzlm+rQIwKWpiPSbuQyT1+fm1Re6lv3VG7YyjFjPPBkaGsLBgweRSqXU+SBDtCX4Iotvfe9738Mdd9yBUCi04flmjsKQuaClsaxnXgCX5sRMJpOYmprC8PAwuru7VVahXqmTiqmMXJmZmcH3v/99PPvssypzRiowbrcbBw4cwJEjR9RCjnqDXY6j7Kvb7bZVqZXGXyKRWNeRoVe6JJAi77lZRd2s8OuNbD0bUTKG5Lg5nU6Ew2EcOnQIL3/5y9W835dbwSYiouuD3FP1e5RehwDWT2lpZlWaHcF6dnezDie9vqPXieQ59Ol//H4/enp6AACjo6MoFouYnJy0ZGnqnVVyP5QM/VadffJ/q6mb9HuvvIdgMAiHw4EbbrgBADAxMYF4PK6CC83qkeb9V+9QXF1dxcjICEqlkhpZJJ3Bkvyij6gw9zEQCGDXrl245ZZb1BoRY2Njaq02PVFF/7tmP5v7a35GZse21Lv0OmW9XkdfXx86Oztx2223YWxsTGUq6yOHpUNMP3/M55bfyzkg5QcHBxGLxdRo6FadqVI3X1lZsT11svk5SdtC9kVvb8jCsQsLCzh37hyee+45nDt3Dvl8Xk13tFlHa7MAjLy2HCOZZrbRaKi6ejAYVOeI1IdljQq9A1g/b/TvSrM1W+T1q9UqLly4gEajgZGRETWyZifSE7vkPNaTzyTI1uz8adZek5EjMjJpfHxcnS/JZBLj4+O4cOECUqkUCoWCGq3d7Bw2E9dkP0ulkmq39/f3w+l0oq+vDzfffDMikYgKSkgCoFwD5Foiz62Ptm7VwSv7rnc+OxwONX9/oVBANBpVo4HW1tYwPT1tGeXeLNHLDHrqbSD9miftQZmaRz9WTqdTdc53dnaua0fpgVb9c2rWAf5CgxDyPuR+s7i4iO9+97uIxWKYn5+3BMH175f+/ZRjlMlksLq6CgAYHx9XZWXB+3g8jvPnz+Ps2bOIx+OWEc36+zT7GOSaEYlE4PF40NnZCb/fr84jn89nGa0rI22q1SpWVlaQz+exsLCgzlc9OG4Gfs1jZB6vZuXkcTkfg8Egenp6MDQ0hHvvvRe9vb246aab1FRn2x0DEURENukd07LQlH5z0RcJBqxZGWbDs9FoIJVKYWZmBseOHcPIyAj6+vosmXT6CAhp7ALWofrSoSw38oWFBZWFpWfn6/9kHyuVCqLRKKamprB3716Mjo7C5/Otq2RI5bxZ53+zSqFUOMwsI718JpNZN62EMCtx8r/eQDc/F72So1eomjVs5Pn1MnrwwuwI0DuwzeOfSqXU3LYbZT3UajXk83lcuHDBdiNPnk8yhrq7u9ViitJwM4Nf1WoVs7OzSKfTlgCSPsem7E+xWMTs7CyeffZZ/PCHP1RzLOuN7b6+Ptx+++3Yv38/wuFw0wag/H85nfiSpaaP3BB6J4lUoPU5XeV3khGjd6jojVT9s9T3Wz57n8+HoaEh3HjjjRgeHrZ8R8nKnILni1/8omVb5p1txjyeZkeWORXI1NSUZXt2dlb9bGbrmg1C8/wzO47M19YfN6e9Madi2ux9bDSVU7NOsY22Teb7fjHrtm32Wvr7Mo/J8ePHLdu///u/b9k2p+zR93uztdfMqZhuuukmy7a5vtc999yjfjanYtrs+JrH76d+6qcs2/pUZKdPn7Y8ZmYL79+/37JtTlPU3d1t2dYzZTs7Oy2PmffETCZj2f6nf/ony/aJEycs2/pnZ56f5ig883tn3r/Mv9f3zfyc9enTdio9qK//zrwnmh3X8k8C4xK8lzqY3rElnUzynJIYIZ2q8hz6PU8SAPS6lt/vR29vLw4fPgyn04mjR4+qTFP9OqbXN/P5POLx+LrPXe/00O+peoe/fu/X99nr9aKjowN33nknhoeHEYlE8PTTT2N2dlbVhfQkCb3uZtYpK5UKLly4gL1796JcLiMQCKDRuLgQ69rampr2yawP1ut1NX3WyMgIDh8+jFe84hUIBoMqGOFyuZpOp2WOgGhWv2m2v7LPgDWzXjq0I5EI+vv7kcvlcMcdd6CzsxOjo6MqAKGvB6Hf4/RpueS96aNi5FjKaIhqtYpdu3ahUCggHA6r46UfJ3mucrmMWCyGc+fOrZuOrhX9u6B35EunqCzKm0gkcPLkSSwsLOCpp57C/Pw8FhcXkc/nLaMmzMQSPZFEf89ynujtBL/fj9D/x96bBMlxpfmd/8yMfclYc88EEokdIEiCLK7FIqu6qqdrSl29liRTq21MNidJNja66KijbjrINDaXmYvMNJKZxiRNqyXZzKjV06ruUu3cF5AACSSWRO5rZOzrHGDf4+dfekQ4SGQVCf5/ZmkZHv7C/fl7z93f+9ZUCt/5zneQyWQQjUZdwvh8Pu9iy4sR1traGu7cuYPNzU0XFkp7ZOj5oBgiaSWVXl/dvn0bu7u7TuA5OjqKxcXFQG34ZcPO//3+hH5rImswJM818e7Wa0gJq9TtdlGpVDzrGD/lhl/dms0myuUyotGoy+d3cHCAkZFPPWjEUE8/7+Q4ftcwCCtwlpwilUoFu7u7Lpzv/v6+s54f1N7aG8oqSGR9Zz3pbB21gaT2DOr3XPO7zodVQOjf6WNJm0heGglz3Ww2PQp5Kauf5bJGFe8SWQuLEkJCzElibv2MGVR/UUClUikXDjkejyObzSKRSDjljqxb5ViiiJB3ueRYrFQqiEajTjknv+/X9vZ6hymEpI0ikQiy2SwKhYLziJCcR/SIIISQxwR56GsXXbHAAuD7QrETVv0ylsnRxsYG3n77bTz99NPO4l2HgNLHk+PIy1gm/rVazSkh9vb23ITZLiitRQHwIG737du3sby8jEuXLqFQKHheXvISlMmafpHbxbBeTIow2QrA5TfVatXjHqp/J2jLKtumun52n59iQtdRvreKHbvo0wseOZeePIkS54033sDdu3c9Fl1+1pHtdhs7Ozu+FoV+6PpHo1Fks1lks1nE43EX+1lczrUVjoyDer3uvGzsAl0sSm7cuIFf/vKXeP/9991iS7fPqVOn8NRTT+HEiROIRqO+SgiN34Lcj7GxMZc0+v79+85Szba35OSYmJjwJGyMRCIuz4OexJdKpSPKJ/GqkPjQzWYT8XgcExMTOH/+PC5duuQSO/otaAghhBArHBcFuVV0WWGcnqNYQdogQYR+X9vzW8GfVYCEw2Hk83nkcjkkk0knqLHvuId93+l6WQ8ILcTXVuRiHX/27FnU63WMj487K2FJIhpEuCcW7HJuEXjv7+9je3vb15pY5gejo6MoFosoFApIJBJIJpPOAnqQskHv031k55uD2kqQOaZ4rTQaDUxOTiKRSPh6ZWjBt1+f2fms7gcR7orSY3Fx0SkA/K5VlEs69OcwBgmgxfhma2sLn3zyCd577z2srq5iZWXFJcTWSgjdXtJO0vbamMuvPaStIpEIcrkcJicnkcvlEI1GnVWzhCKVa5TwV2KVvre3h42NDc/1+wm39TmtoHtzcxMbGxtYX18P1H5fNmx7aA9/6QNRJtjf2N/KGlZyQEgfi/JIQid1Oh0sLi5id3cXlUrFN3Sc9T7S59Z/29vbeP3115HNZtHr9VAsFnH+/Hnkcrkj60P9XNV/cj79vx8i+D84OMDa2hrW19fxi1/8Avv7+/jkk0/c80zOI0oFYWRkBKlUyhOKrl6vY2tryxlESp3Fy7vfc6nX6znPEFl/y5qu3zNGb1uFs21nOecg5F0ma1ZrOCEKBTkfALc21PXo9XqoVCrY3NxEOBx2eSMODw9RqVTw3nvvuZyHEpVBK4z1O0zGbzQaRSqVwrPPPot8Po/FxUWMj487uYw+v83vFI/HnaJMFLq1Wg2rq6s4PDzE2toaDg4OXF4Q/S4Wb0gJAS3Xq5X0fgohuUfm5+fx4osvYmZmBlevXkUymXSK2C9DmOEvfg0JIeQLgLwUw+EwYrEYYrEYEomEW0TJi0wLc/VkRb/8tFXd4eEhrl+/jnfffRcnT550mnb5vSgU5MXlJ2Df2dnBG2+8gU8++QTNZtO5mWpLPODoJFom5MvLyygWizh79iyefvpp506vX9JakO0n+NfHlwlPqVRCq9Xy5L8QJLSV5Abwm+zp8lqZoL/r55Eh/20dgU8tH6xVmLSdFQRYV/pWq4XV1VW8+eab+NnPfoaf/OQnHksd4FOrQL2g0dYQw7AWMmKpMTs7i+XlZayurrrFvQ650G63nVLq5MmTri913gVRot27dw+vv/463nrrLbf40guLZDKJb37zmy6HiCzqrIJt0AS1H7JA/ta3voWPPvoIh4eH7vxayJFKpbC0tIRvf/vbOHv2LBKJhIshK4ogmYQ2Gg2X9FDqVq/XMTk5iZmZGTc5K5VKmJ+fx6VLl3DmzBmcOHHCE2rqs1r9EEIIeTzRCgN5h4tHn7w3rRdqp9Nx1ukaLSi2whHgU6MRm9vJz7NWsOEmQqEQ8vk8isUistmss8zU1rKDDEFsfe1+v2TOei4mCb3HxsYQi8WcJWk6ncaJEydcmJ6VlRUnSBsk2JN3vMx3pG1arRY2NzexurrqhDuiCNHGMGNjY5iZmUGhUHBeB3INgwTO9js/RYVfGS2osqRSKSdklBAgMreyIWD86uanhNLn0YnNxSNLvJZWV1ePzJv1uLOCv35ooaKdg8s8Wby+f/azn+H11193oUv8jKKkzUSYrXOzaQ9mP+GcjDMJqSJ5QKSPxXtGxpl4AEnC21/+8pe4d+8eer0ednd3ncLCtnM/xZ8IDTc3N3Hv3r0jnm6PM/bZ5YfuZ7/vdQhisfIGHqydU6mUUyRpzy+rLLL3pxWqy3pXkrZvb28DAObm5tx6XjyjtEGa37XZZ72Us3URRakYrx0cHGBzcxMHBwcuJFm/Z56cMxaLIZ1Ou3qVy2Xs7e15zq+VMDpfjV+ddRg7602uz22/09f2sGukQc9Tva2/00aeVhag21XeCa1Wy3mdyH0t3gmD1txyPRICeWJiAhMTE5ibm3OeBaKwscoMee7KuyadTqPdbiORSKBer2N0dNR5tYqRqay/xRBTPPZE2SFKOe3JARz1vAuHw0gkEshkMpiamsLExASy2ax71/rNO76IUBFBCCEBiEQiTpAcCoWQzWaRz+dRKpU8EwKZBIiV3P7+vntRaQstebmI1dBPfvITPPnkkxgZGUEmk/G8RPRLVFsTVKtV3L17F//23/5bvP3229jZ2fG4teqFoizi5Hh6orS7u4sPPvgAqVQKp0+fRjwed3WWRbcsEmWSKNZXOma/nhyGQiF3HEmip4XMpVLJKSOKxaJnMifHsRZ1dtEsWGsH7YXRb4Ks21SuRequwxM1Gg3PAmlkZATlchn/4T/8B/zX//pfcfv2bWeVottLL/T0wlLCHw3DT4GUSCTwzDPPYH9/H3fu3MH+/r6v8GNraws3btzA9PQ0JicnXVgCWbTXajVcv34d//pf/2u89dZbbmIu7R0Oh1EoFHD16lU899xzbuEubWuTmge1ntNoQYmN0SuL71gshsXFRfzgBz9wHkMiQJAYvE8//bTn97/zO7/jwkuIkk4sW2SCJtYnYnGlw5H5uTQTQgj5aqOFZlpILPMjP8GPvMd1zig9l9BzAfEK0AItQd7ffoJbXRervIjH405QcXh46DxmraBJ5ik2t5Zch7ba7ReOSoRD1rJXz4klmW+hUEA+n8fq6iru3LmDH/7wh1hfXz+SM0oEzNFoFJlMBufPn8f8/LzLfyUGLwcHBzg4OHC/sXUTAyLxrJR5gOyT6xS0gkILqvR3un38DF7s/F0LssLhMMbHx5FMJl34Ktvvtp9k7TEyMuKxlvULv6H3iSBzaWnJWRD7CfP98mMMwipa5N5ot9sol8solUp44403cO3aNfzkJz/B9va2R/hmPWCj0Sii0Sjm5uYwPz+PU6dOoVwuY3d3F2+88Qaq1aoLf2jbVtZDvV4Pr7/+Ovb29lzyVhHKiTBa7stMJoNYLIZCoYBcLoednR2srq7i1q1b2NnZwe3bt10IWREK6jBbGrkmiX0v4X8eR/z6LxwOu9BG4rUg40sLlAGvoZgOvaWPKWspCaf23HPPYX193Qnh19fXnbGWn6C2n8JIwnK122289957Li/i1NQUzp07h8nJSaRSKY+CWa/ldCg74NO1vL4OuWZRfNTrdezt7eHu3btYWVnBysqKJyJAP+8RUcjNzMzgySefdIq2tbU1bG5ueryE9G+1gsGuk8VDKZ1Oo1wuO6Mu+bOeWEGUTLpP7TjxW59q4b1W/FiFlF33W0Wn7ttKpYJarYY7d+5gb28Pt2/fxurqqsspIsfzk6nIeJPQRhcvXsTMzAwmJycRj8fdWNTPOpvPSc4h7xJROmSzWTSbTZw/fx6NRgM7OzsuWkGlUnHPjEgkgnQ6jVar5Tx/rl+/jsPDQ5RKJTSbTVcPuU9OnDiB06dPY2lpCVevXkU6nXYJqrVh3RcdKiIIISQA2nqnWq1iZWUFOzs7ToArL9FQKIRMJoMTJ05gfn4eb731Fu7cueMbb1wrJm7evIm/+Iu/wNe+9jWcPXsWk5OTHmsoPaGrVqvY3t7G7du38Vd/9Vf4+c9/jlKp5PG8SKVSmJqaQqlUwv37992kxy6UxEJia2sL7733Hj744ANP0myZMOjYmVbQbq22xDtEFCqyiJWy0lZimeFnBWGt7PtZufgJ7PVERi/u9DGs8FwvquRFryceMsluNBo4ODjA+++/j/X1dWfdpQXZ+r+2YATg+mEYVvEik850Oo1sNotUKuUs/7VFS6/3IHzBvXv3cO/ePVy+fNnTjuIu+p//83/Gu+++i93dXY/gYGxsDPPz83j66afxve99D3Nzc4jH456JjZ0oSpvpBWmQ2JTd7oOwYtr6bGTk0yTi4+PjmJ+fx+LiovPIEAs3GUuykJA65fN5TE1NuXPU63UXK1PHgbaWTzYeNPHy53/+555tG7ve3v8au+0Xg3xQeR3L3j5HH/ZYtm91vhabm+L+/fuebR3bH3iQJG7QufW5tGu3X1mLvU4/q9rPis2PYHNb6LwQH3zwgWffP/2n/9Szfe/ePc/2oHvHPhPs9tLSkmf77/29v+fZfu655zzbOiGofZ4Py6FhrbkXFhY823//7/9999nm9LE5Iuw4sAkC7bn0mLVtYM8lwlXBWtr+y3/5Lz3b77zzjvvs51U3qF723HaM6jb+4Q9/6Nn32muv4auEtX7tJ1ACvMptPb8YVE5/53fvDzK00O97EeaJUYifoFsfr99zxm++NEhA5Sc8krmkWJhKEuFYLIabN2+i2+260IrSnpFIBMlkEul0Gvl8HgsLC24uIH0g4TxsaEldB5kv6BwLQYRsftfRr5wto+eEdp/MPfzmVfb3um/0HNbvWWvnwKLICYfDSKVS7j3kd90yn3tYZYT8l/HbarWwv7+PjY0NfPLJJ7hz547zfpZ1hO5jOa/ENj9z5gwWFhZw+vRp7O/vIxaL4f333z/izWOvW9YUa2triEQizsM8FosdWRPIdYqiRgSB6XQa4XAYW1tbGBkZwfb2NnZ3d906Rde/Xz/J+uZxxlqo63WgGAZZbJv5jTM9bvXzYnp6Gr1eD9lsFu12G1tbW773S781nz6+1G9rawvVahUbGxsYGRnB9PQ0UqmUW2PoZ4ff/aLXwdZTTSvlms0mqtUq9vf3cXBwgHK57NY8cq0WrRhOpVLOoGxsbAyNRuPIc0zf9/2eQ/KsrFarnpwFojSR55T048MoIiz2GSzbWimg7319fGk/kato/KIliAxjZOSBod/e3h729/ddRIZ+c1KrhI3H4y7xc6FQwPj4uGeOqZUR+jkiYwqAJ49Tp9NxocXy+Tza7TZyuRzK5bJLZC1jJBKJYHx8HK1WCxsbGzg8PHRr8273Qfgy8TCU+YO8D2dnZzE5OekM7XS7fhkIrIjwi8n2qyBofCubdK0fdjH4eY5nFx/9+Bt/428EKre/vx+o3D/7Z/8sUDm7uOxH0MEaVDgT9IE1LHGhYJMl9uPnP/95oHLf/OY3A5WTmOGDCGoJHLQvgiaWCVruYWPRk/5oRUSz2cTm5qZL6CYvo06n45IELi4u4uLFi86VUqyBALjQSfrY5XIZb7/9tvOEEFdR6UOZ2EjC41u3buHGjRt44403nPWNFgxPTEzg0qVLzurhzp07zuVarkNepqJcWV9fxxtvvIGFhQVPrFrA3zVfT3rks7Zgy+fz7oVslQBiObSxsYELFy44LwR5HvlNTvwml37PG78Jab/y9lh6gtxvwSOTOZnk9GsXe4yxsTHMzs4GSjSrc3zoY0SjUbcw18opAJ6xsrm5ifv372NnZ8cpEoAHliNra2t44403sLW15cKKye9isRhOnTqFr33ta7h06RJSqZSbAFn3fy28f1hkHOzt7XmSsutjp1IpFAoFZLNZ58Eg59TltDJBfgd8Gn7M9o+M0S/bhI0QQsivB3lHybtZ5lLaK9Tvve9nKKEV71qgYQXM8p6UsJzynSjTtdBLfmutvwG4uO26njY3gk2ErNHfaU8HO2fToVO0oE7W8iIUj8fjiEQiSCQSKBQK6HQ6uH79urP0lZBWk5OTOHPmDJaWljAxMYELFy6gWCwikUi4NtEeD5VK5ci8SLevWLhLyFC5ftsH2stWW8Hr+XDQuU+/+YUWwuk66/PouYs9jj23XygTMaARr1itjJK+09viIfqwcyJpt3a7jVKphHfeeQfvvPMO/uIv/gIHBwfOCl2vO0ZGRpwlfTqdxiuvvIKzZ8/iqaeeckm719fXMTIy4kKvaLmBvn4Zy+12G7du3cLu7i4ODw/x2muv4ezZs4hEIk6QKx69cg+NjIy4eXU2m8Xs7Czq9Tp2d3dx8+ZN3Lp1C//5P/9nZ+xlBerShqLokvBjjysyPu14EwMi8TayOQDsGkI+S74Wm29H9sfjcRSLRYyNjeGpp57C1taWSzStlVt23WfXi/o+EyOodruNjz76CKurq6jVapiamnLhWmUNrtcLViaplW/Ap94IYmS3s7ODjY0N3L59Gzdu3HBKLbkn5Tpl7MqzcmxsDNls1nmzTU1NuXap1WqYnp5GLBZDo9FwYXX1fa/RSgBRipRKJWxvbzvljn4G6j7Sz3D9vAry3JPf6LEgx9PHtCHy9DVIPaTvRDE/MvLAK6xcLiORSDjvgrW1NWxtbbmQ2XqM6vGgFczy/igUCi5Btax5Aa/3g10zWkW1fV7LO1rqEYvF3JgV+YFWSHW7XRSLRZc7qFqt4vDw0K3T9bNwdnYWS0tLyGazGB8fd89SrUz+Mqxt6RFBCCEB0C/QdruNvb09NynWL59oNIqpqSksLCzg1KlTyOfzWF5eRqVSQb1eP2IdpS0obt686V7IyWQSU1NTzppHXuT37t3Dj3/8Y3z44Ye4ffs2Dg4O3GRaXjyJRAJnzpzBs88+i1arhUwmg1KphPX1dY/lg36ZimLgpz/9KS5fvoxEIuFJdqQtgfxebnrhJvEOJycnj7yMpQ0lru/169fx/PPPY3x83P1eC5utZ8GwRbJs+1n/2TJ+CgQ5lxYmyEJf6iIhhVKplJtUWAtHmbSI8kms/5577rlACnG5Xr04lUlbOp12cX91v8jnbreLnZ0drKys4N69e5icnHTu+Pv7+7h16xZu3rzpFO5aATM+Po4LFy7g6tWrKBQKzmJPT8qsQsK2b5DJj4w5nRxQTxRFoZDNZpFMJp2SQU8GZcxpt1hryaTdveWzTrqtx0A/61NCCCFfbUTYpIUzYtGojQCkDNA/ZIUo30VwoENx6rmcnqv5CZ71/FF/ljpVKhXs7+87618reNdKhUQi4UIeWWz4S7lWO1eS+uv5l96vlR/yno/H45ienkalUsHCwoIT0GSzWczPz+OJJ57A/Py8S7os4TKkrVutFlqtlie3gfbSlfp2Oh3s7++jUql4hGJaQaTbWV+rnS/quXM/oZy1lrboeslYslbi1ttWC7785q66rnrNIt68OoSYVXyJEF3CGQVF6lWtVnFwcICbN2/iww8/xAcffICDgwNP8mfdnmNjY5iennaGW1evXsWJEycwMTHh5nuZTAa5XA6FQsElNfY7lhZsisLp3r17eOedd3BwcIB4PI7x8XHnjWOtmvU6Q+7JXq+HhYUFhMNhfPLJJy6fid/16z4Qpc/jjH5+6OeOPMusgkt+oxWgwKeKSVEU+T3nZM0DACdOnHCKK51jYdB6Ts4t/+WZJ7/d2NjA3t4eotEoyuUyxsfHkc/nnVJXxodck30GAp/ew6Jsq9fraDabLkGxJDCvVCoeZZpuC6mbtEUikXDJksUwttfrubwyosyQ56UVtvu1RbfbdeGiyuUy4vH4kTWmfn7Ib+09N4x+zym7lhZ5Qb9cPfb+lGNIW8m1iGxlf38f+/v7aDabntBd9rjyvdRP2lsM76xMxSohtGeCra9uS/vsFw8/3R/y7Nf92Ol0kMvl0Gw2PUpcAE4hWywWnUJKQonJPfR5jAR/1VARQQghAZAXc7vddpMM+4ITofv8/DwWFhaQy+WQTqfx8ssvo1QqoVarOZdILfSUF0+z2cSNGzdcmKQLFy64BL3AA0uI//Sf/hOuX7+OcrnsLFBE+Do6+iB0z3PPPYc//MM/xOzsLNrtNqanp7G9vY0/+7M/O+J5IGGXZIJy584d/N//9//tLIdkoeg30QPgFCTtdtsT9iaRSGB2dtYl9JYXqbxM6/U67t69i1gsht/+7d/G1NSUJ2ZkvwW8/t5OBvXEyW8SZr/zU07ostoCQcINieXE97//fWSzWbz77ru4desWarWap42sIiWVSuHKlSv49re/HcibTiZaNt5nNBp1VoI/+9nP3CJP/sQaslwu45NPPsGPfvQjnD17FuFwGNVqFcvLy/jxj398JIyBLCDOnTuH06dPOwscv/awwgctWAiKTNbX19ePWJTIdiaTQaFQQDKZdBMsmSTq+ktb69Ai0g96Mir3io77qsdFP4siQgghX2201ak2ShHBgP5OK8cBr9BXhA7dbtdZfotFtTbG8BMG6XeVrZNVQohxyf7+vguNI9i5nBiwFAoF3yTU1nil33vSKlDkGqxQSguAut0uCoUCKpUKTpw44Qwk5ubmcPLkSTz99NMoFotO2GKtUsX6WCyK/QRA0u6Hh4fOelb/6XmbrqOf8FH2WWtY3S+23fzmmnpc9ZuP6ONpzxdd10Ge7zKHbLVaqNfrR3KZ6PpJGJhisRhYkK7HtISfWV5edp4E4qFir0vWF5IP4qmnnsKlS5c8xlcidM1kMpiYmHChSqy3ixXCilJkfX0doVAIBwcHWFpacmsUbdmuvWDkeDZXRiwWc+NSwjXqfrcCb4m7/zij21r/xWIx5PN5T0hBrRzUv5U2Fk+URCLhCb2q72MJoSVKqvPnzyOXy+HGjRuevHt2DWjXZHq9IP0nz+v79+9jf38f4XAY9Xod+XweExMTiEajLryrKKl0HWX8yxq62+3i4OAAh4eHuHnzJq5du4atrS3s7Ox4vL+18kvqEgqFUCwWkclksLi4iIWFBczNzTnhdavVQiwWc0Zweg1snxd+bSDvh1qtho2NDQAPQmLG43FPP1oPP2th76dkFqwyw08JIPKORqPhMdLs914ZHR315KnUsphGo+Ge/4eHh07e0K9O8n7Sa8JoNOryFmnPe62wtNdvZT96v10TW68KKaPfQfa34kmi5xb6vKKQkvpbT4gvgxICoCKCEEICI/EeK5UKlpeXPRb+MgmLRCJYWFjAzMyMe7k/+eSTWF1dRaPRwK1bt5xHgH7JjY2Nod1uu5fy5uYmPv74Y0xPT7t9tVoNW1tb7sWkFwHhcBjFYhEXLlzAH/7hH+LcuXOIRCJoNBqYnp7Gs88+i5/+9KcuMTFwNC6wTA7eeust5HI5hMNhvPrqq4jH464N9KRLT1z0hAx44BkyMTGBVCrlG6ux1+uh2Wxid3cXH374IRYWFtwEQVu/69iLwKcTLnnZ6sTfsgiwCzm7UBRLinA47LFE1GX0tVhFRzwex4svvoiFhQUsLS3h3//7f+9iHOuJodQ1Go1ienoar732GiYmJgKFHJT4nXJdMgGOx+OYmZnBxYsXUSwWnbWEnizKeNna2sJbb72FN954A0888QRu376NX/7yl3jvvffQaDQ8E594PI7nn38ev/M7v4OLFy+6Rb/OF2KVUbqd+y3G+9HtPnATPjw8dHXWE/Rer4dEIuFiomshCwCnjNALaVmUa+WKtVyRGKsyqbXeFOI5Qry88cYbnu1+lkB+++y2FXIMi1VvF/qaYSEebRhDK6DSwjmbE+Kf//N/7tn+jd/4Dc/2mTNnPNvz8/Oe7UKh4D4Pai/g6D0T5B76rNhj2zZcX193n//1v/7Xnn03btzwbA+7V+xiTTMzM+PZ/lt/6295tm1OCJt7Qb+XbD2scM6OORt+1e7PZrPuc7lcHnhsK3Sy+wflB7H1tmPf1uull17qeywAuHnzpvscNNyr8DD34d27dz37bBs9jmjBiljjVioVlEollMtl3L9/33kgiCAhn88D8FrOivCk1+thcnISMzMzOHXqFDKZjBOCyG+0wsHO10TwJe9GETpLDPDDw0P8/Oc/x61bt7CxseEEVzL/lHtgdHQUqVQKp06dwssvv+y5r+S6ZW5hhWciHLNGClpgo+dCev6gw7vEYjFMT0/ju9/9rot1XSgUEIvFkEwmnWWyTSwtczmZL1mjBv2/3W5jZ2cHOzs7TuAo9RADBS2ckjmgDU8qx+ynFJJ62TJWkWHnU1rRIHWxBkuC9Ied81hlVKPRQLVaRblcxr1797C9ve1CWsl5ZR4sYWAuXLhw5Fnrh1aqSZ65O3fu4Je//CVWV1eP5H/TwrxMJoN8Po/f+q3fwsLCAhYXF13yaN1O6XQaMzMz+MY3vuHWR7KG8RO06rq1222srq5ib28P3e6D5K5nz57F2bNnkUwmPbnP9DxBxrUWRCaTSZdjQ4TJVkkVjUZRLBYxMzNzZC7wOKLfXTLuYrEYcrmcE3L7zWP0XFw8scbHxxGLxTw5U3R/ipe9KEpPnz6NdDrt8vSNjHwa2shP+G2F4/IdABf2ZmNjwxk7NZtNTE9Puxxzcl4JOyWCX60Mledxq9XCzs4Odnd3sby8jGvXrrn3hG4zWX9opdfo6ChyuRymp6dx5swZnDlzBqlUyoVpHh19EPoqkUi4eYVWQlv8hNHyDtre3kYkEnHPCv0ck/6ROvmt+fz6VN8TUs5PQSLvIO3R4BeK2CpircJRQlPJ879Wq7nE8n7tIH2m71tp00wm43kHW68COyZ1/bQcx2+fn5JAKyK0gkye/WKgoPut2+26d5WWX+i+6lfXLypURBBCyEMgE29ZpFtLpmQyiUgk4iZUoVAIExMTuHLlCg4PD7G5uenynsgkRLwS9ISk1Wrh4ODAY5Vfr9dRq9WOWKrHYjFcvHgRly5dwhNPPOHiW4oAO5PJ4PTp01haWsL169ddQkD9QpTjNZtNlEolXLt2zSULvnjxokdgb10l5Vr0xEwWkqdOncLOzo4T+FlhVLlcxocffojLly9jamrKLTrFZVTO0263XR201Ya8tO2Ep9+L2Frj2EmTfKcXOrJPT9AkGfiFCxfw/PPPY2tryy2Q+illRDkUZILQ6/U8giG5HrFam5mZwdNPP429vT3n7qvPKQKC3d1dvP7664hGo/jwww9x/fp1j/eGjINoNOpi9GazWU+sVus+7NeedqE9jG636xRrfkJaUYLIONbXpttDzq2VU36xa+U7sbwRl9dSqYT9/X2Mjo4im81iamoKxWIxcD4pQgghjz/yLmk0GtjZ2UGpVMLdu3exv7+Pw8NDp4gQa2AJLaPfb1pY1e0+iActwmERrsXjcY8AWpB3rc4NocMaHh4eolarubrt7Ozg448/xtramgtDYudK8s4Ub4jp6WlfQwkttLECXysst3MFbYEqZeUdL9cSjUaRTqcxNzeHaDTqsULuN/+Qc1lDCVsPXX5/fx+bm5tYWVk54omi53i67XX/+SkF9LafAFT/9xOS6jaS8+k5vt8xrUBO/osySrxEKpWK84rZ29tzcz/dB5IXIpfLYXJy0q0fgiDroUajgbW1Ndy/fx8bGxuoVque69bXGYlEMDk5iaWlJczPz2NqasrFOLcWx+KRPTs7i9nZWWxsbKBSqRxJiOw3H5R5nli7iyFZs9nE+Pg4MpkM4vG4JzeBXVsdHBw4jyKdSF0jc+hIJOKsqiV06uOIjDOtZBTF5/r6OpaXl7G1teXJC+A3DkTxpgW12hJdPOT1Wk/WVydOnEA6ncbu7i6KxSJWVlawv7/vvH7sWtCeW77XSl2578TzRvIoSMg6UYZICDNt9CbjsV6vo9VqYW9vDwcHB1hZWXHJqf2MJfQaS/Lg5fN5F7Ism806BY2sbcLhsFNE9LPQl+vzUxjIfSDyBPHoE4MU/Ty0z1V9bNumfs81W17aXIy+RFai21Kw7wupv/yXsSUhsCT/hSg1/NamWpkh8pFCoYBiseiSPkuOCP1M8FN2WiMn2x6Drl8r40Uh4adM0L+Xa5J7RSv9/X7zZYGKCEIICYgId8UaTluuyQsymUx6rMglN8Di4iI2Nzfx0UcfuYWqnTzYBHUywRfrHp18SY6dSCSwtLSE559/Hk888YRLXiRJ6kSgK1b0EqdSJz/U55SFxerqKq5fv46PPvoIJ06cOBJOyAr89YtXLNck38Ann3zi2kz/ViawH330Ed5//300Gg1MTEy4eJiyINbWA36uoX6LU73fzypLu9ZqrAuknwWILDpSqRRmZ2fx1FNP4b333nOeH3qhKNaG4uZrJyj9sJNk/Z0kAn/yySdx7do13L9/37Mw0JOuarWKjz76CMlkEsvLy1hdXXUeFFoRE4vFcObMGRcKybpI237vR1CFRLvdRrlcxt7enidGqSDJJ6PR6JGYotozQk84tSJC+lDHRhbrG7FOqlar2N7exsrKCkZHR5HP53HlyhVcunTpsV5IEkIIeTjE4rJcLuPmzZu4e/cu/ut//a/Y29vD/v4+dnZ2nKBT3kki7LYGCrI/kUjg5MmTWF5exne/+13Mz89jcnLSI5TTAmY5phYAihDp7t272NrawvLyMtbX13H79m3cu3cP9XrdcwytiJC5Wj6fx+zsLBYXF33D8oiwQ9dJh6CyBi2CvJPlfSy/0YLGaDSKXq+HeDzuyVGhvQKsxS3wqZeIFRzZ8+s5w+rqqrvmSCSC2dlZJ+TTgk6xPLUCLOuR4Yfs00Is/X0/gxlddwm7aq9Djwe/cWUtg3d2drC1tYXt7W1sbGzg8PDQXb8IVpPJJBKJBE6cOIFz587h6tWrbg4+CBECyj3x0Ucf4fr161heXnb1lz7U8/dEIoELFy7g61//Os6cOYN0Ou3ydum+lWMkk0ksLS1hY2MD7XYba2trHkGkHmeybtJ9Jrn11tbWcO3aNVy/ft0lpc7lcs7TQayMZW4ZjUadB827776L/f19p0C0RkuSeH1xcRHz8/OYnZ0d2n5fZvTzRHLR7O3t4d69e/jwww9RKpU8xlHW6l+OoQ3DtDLCPhukzUUJcO7cOVQqFQBwSg8RqNuwyVbxagW+Vri9ubmJ3d1dJySX5OPyWXJW6GsSYycJvSzri8PDQxwcHPg+L6xxleQPmJycxMLCglNG6OgAkkMilUohmUz6tqU81/V59NpIPJgqlQqq1apbH4nSTjw8/TxTBPtMs89/vzW3rqs8eySKhFZC+ik95Du/EFytVgvb29toNpsol8tHcipYtBe95LKcmZnByZMnUSgUjuSJkHrp57mfMaaVEfRb62vlgfSVNWjV7a/HqfSlbhM9pvU1flmgIoIQQgLS6z2Ivb+9vY2DgwMnLBUhp0yyJdGzvCgkr8DS0hIuX76Mjz/+2E3MJQagfXHLgkdPdmUiHw6HPRZkv/mbv4kXX3wR09PTHo+MRqPhJoGFQgEvvfQSbt686RI62XwR+oV4eHjoQvk888wz7qUskyf9EpWJo1Y0yALxueeec66pm5ubbiIhi4hWq4X3338fsVgM29vbuHDhAk6cOIFMJuOuRRaY9XrdM2GRY+m2komCWNrI9xrrmqnbXecU0Atgfaxut+v6oFgs4tKlS3jmmWdw48YNN5mT/pS+l6RSQdEhgmQCqS2F0uk0rl69irfeegulUsmTBE1fV6vVwvLyMvb29pxiyyZq1ImhZXIo3id2oiuTOD1p9FP+DEPCcpVKJU8YAzm+WOmFw2EX+sG6tMrCQwtoZAIqE+tqtepCE0jSTkk62Gw2sbOzg7t37zrl0m//9m8jFovh7NmzgfuKEELI483u7i5WVlbwwQcfuPAzH374ofOQ1fmatGEHcNRgQt7B1WoVKysrqFar6PV6WFxcxGuvvebefTIP0O/ubreLcrmMw8NDbG9vO6H5jRs3sLKygnv37jkhmNRJz+20IEPCjrz66qsuZI2fMF+EU/o9L0JD/f5vtVpu7qCvWSeX1m0g+yWMKeANuyTnkXPrpKbiNTEzM4MzZ86gWq3igw8+8Cg7ZL4k1Ot1bGxsoNt9kJ9jfX0dZ8+eddbHEnpFKxP0fE4nFNVCKamf1FnXU65bC0QFPa+yFv5yfi18k+9lnilW/61Wywk99/f3sba2hoODA6ytrWFnZ8clb65Wq0cEvhMTE5idncVLL72Eubk5Fyc9CDI2ZX6/ubmJWq3mxqluGxH0z87Oujx6OnG0/BfrYOl3CXEmHsVra2tYWVnBysqKx9PGjh9tECTrllarhbt372J9fR0rKyvOwl3WFXodEwqFUKvVUK/XsbW15UmAq/sjHA5jenoap06dwte//nVfw63HDX1vi2dWpVJxCjC9FtH5OPQ9IoJWyXmgwx3p54ee88u9GY1G0e0+yC0zOjrqwihpxYANv6iVXFI3+W+NCuW+kt/JM7ZarWJsbAzlcvmIgZYo5iQ8ns4l2U8wLOM+FAohm826vHj5fB6JRMJjDKblCel0GuVy2a2PRflm5Qh+iEK4Uqk4o0Qb1m7Q72397batg59yWuohMhPJQ2mfjTJerIeYfu5ojycxeOx3LVohJWMzlUq58SchkO26Vo91P+8Pu/bV79CgSgH93tF97qdUErSi26+NvwxQEUEIIQEQYXilUsH6+rpLkCUvgkgk4vFCiEajLrwQ8GDyMD8/j1deeQXvvvsu7t6967HcEA8LvSiRCR7w6Ut7dHQUMzMzeOqpp/DUU0/hwoULOH/+vEdgLwtCWRBLmKgnn3wS3/zmN9HpdPCzn/3Mo0DRf8CDBdfGxgZ++tOf4plnnsFLL72EXC7nrlNe4tZSQTM2NoZTp07hd37nd5BOp/FXf/VX2NraOjLhaDQa+NnPfoYPPvgA09PTuHDhAl544QU8/fTTzn1ahzTSShG/F65eBGnhtrXiEOzkR08crMJCCxZkYRWJRHw9IbrdLpLJJK5evYqXXnrJxaUNMknQXgBaIaLdRWdnZ/Hyyy/j9u3b2NraQr1ed2NIlFujo6NO6K8X5J1Ox03CTp48if/uv/vvMDU15RagWnghyGKv0Wi4CZtfGwahVCrh448/9txHgky+ZEJ/cHDg2lriY0oejNXVVSwvL2NjYwNTU1Oo1Wouz0qtVsP+/j5KpRLu3LmDvb09t0jSFjxyjdVqFW+//TZOnTqF3/qt33qo63ncsRY3/RYXftiJuLW4tc8OG5teH3tYPeyx7P5BVkxiYSf8+Z//uWf79ddf92xfvHjRs/3ss896tr/xjW+4zwsLC559OgcBcDTPgFVaPkoLJ7tAPzw89Gz/6Ec/cp9/8pOffK566GeOFXD+9//9f+/Z/u53v+vZtm3Uz90dODoubPsNywkx6NjpdHrgsWzf2Tay98agHEHRaHTgsW097Ri8cOGC+/yLX/zCs8/eV/ZY9twWfW9tb2979um8Io8rpVIJq6ureP/993Ht2jVsbGxgY2PD991n5x5aYKDfO+12G6VSCbVaDR9++CFqtRqWlpZcEmvxfhDLcxEa7e/vY3d3F5ubm+h2H8Rmv3HjBtbW1rC+vu5J7ClzNetZGQ6HkcvlMDU1hTNnzmBycrJv6Eg7VrTVrTVEsHMmLVCx8wktiNPH9juWFhhqq1rJbTAzM4OPPvrIzX20AkDodDool8vodrtYXl5GvV5HNBp1gjiZ40q9rHWxtcjVgie/eaWf4kEL6KUd9H85nlVgaIMNEYpLgtZarYbNzU3s7e1he3sb9+7dc+NVDFUkiatW0ESjUeRyOczOzmJpaQmFQgGJRCKw566MTcndcHh46Ik5bxMPJxIJZ+mdyWTcfNbvHrFCvcnJSXS7XZw6dQq9Xs+FmhKht24vO9fXbVwqlTA6+iD0jl/4FT13lrVYrVY70j+ytopEIpiamsLCwgJOnTrlPNIfR6wQVNpHlKJ7e3vu/tJtqu9xvYYaHX0QEnVychKpVMr1h3gByHn082V0dNQJjhcXFzExMYH9/X1nRBUKhVAul1Eulz3e0fZZrJWG9n6U9bisvSTfUr/7wnp86FBHdj4g7abXs7FYDHNzc5iamsKpU6dw8uRJ55mun2UjIw+MtKamptDpdJBIJJzSwz5r+tHtdj05IiqVCsbHxz3PtH7X2W/NbQXoVuBv3wfyG1EyNhoN9770O5Y2OJPtWq2G7e1tjI6OYnV11d2nNhyYrof2ohodHXUeEcVi0UWz8BP86/GjvdA08n7S+/zeF/q+kH1a9qLX+sMUQ7qNdBnb5l9kqIgghJAAyITEJpjSL6PR0QfhXcbGxtBsNt1EVdxLx8fHcerUKfzRH/0R/uN//I9YXl7G/v6+WxzoFzjw6QtXH39iYgK//du/jatXr+LkyZPIZDJIJBKeBZpY/oiFiViHpFIpPPHEE1hbW8ONGzews7Nz5CUoAmB54R4cHOD//X//X8RiMVy4cMEtBuSc+rfipiuLXNl34cIF1Go1NBoN/Pmf/7mbdOi/TqeD/f19VCoVrK2t4f3338crr7yCS5cu4eTJk5iennbhcqS9wuGwRzji1yd2AqoFAGIRJuX04kNbqkn/60WkdgWW2KB6cinnS6fTmJ6exszMDBKJhG9ybD+sJZlcp56khEIhLC4uYnp6Gnfv3kWlUvFch70mLUALh8MuZNhzzz2Hb33rW0eS99kJs19eDalT0IWrUKvVsLq66o6rQz5IvNlf/OIXWFtbQ6FQcFZQOrFkuVx2cbo3NzeRSqWOJD0TZZ64TOsFklyPjr1ZKpVcDhdCCCEEAD766CP84he/wH/6T/8J+/v7HkMSeSeKEE3QggctZAHgmTd1u1189NFHWFlZ8YQFEeMWCQkqAi7xatU5ImQuouc7WmiiBV/xeBzFYhHf/OY3cfbsWTzzzDNIpVKIx+O+7/J+FqZWYKy9IQCvEQUAJ1iTdrBzSDmOvJdlzm2F0sADLwpp6yeeeAKxWAzvvPMODg4O3FxI6q6vo9VqoVQqudxZb7/9Nq5cuYILFy7gySefRCaTcaGJ7BxRCxy1kZFco56P6jmkrAWsMFsMRfS8Uo8nPe+UvAsAcHBw4HJcffjhh1hfX8cHH3yAw8ND5x3bbrddOBeZ88p5xZtkaWkJTz75JC5evIi5uTlnLDMo/rm+vmazie3tbXzyySe4d+8etra2PAoqLXRLp9OYmprCb/zGb2BpacklhhUDEz0v02NLjiPC6t/93d/Fhx9+iGg06kImWW8SaVs7BqRNZVxpxYzuM63AsPet1Eviy8/NzeF73/selpaWsLS05HJOPM7IWAU+XXOKJ5I15hL6CW/73f/6GaLDpmnFhnhGTExMuHEei8Wwu7uL7e1t1Ot1pxixwlo5l70ujb0ePwMtaQO7xvS718WgSgiFQsjlckgkEpidncX09DSy2awzvrOhzeR5JEpqnd9EX5sd/35rTp0oWgT4+nq04tOvL/3Q95t97mqFqg2r1u94Vsiu/2w7+ykx9PpVfy99EYvFMD4+jlQqdSRRulbI9KujXSPbNrDKBXsdui39lEhWmdJP0dRPQfRl4PF+UhJCyCNCXOMbjYZzv7QP/pGREczPzyOZTLoXmkwcRIgaDofx5JNP4vDwEOl0Grdu3cLm5qZbjABHY1rKcSS26uXLl7G4uIhCoeCOqydHIyMjTlirBf0AMDs7i0uXLuHu3bv48Y9/7NxZ7cJRflOv1/Hxxx/jF7/4hRMYizJCJgK6npJcTOohVndLS0s4ODjAzZs3sby87CzQ9CRiZOSBpVej0XAu5Pfv38fi4iIuXbqEF154wVm8hEIht9CS34pywS7C9bVZ6wqtALLWM3oyJu2ilVHiUSI5B2QiLueX/lpYWMD4+LhnERsUPwGAnmyOj487JY1YR+qJvLUGkmOMjY3h7Nmz+NrXvoZnnnkGMzMzbuKr3eK1lZq1cBlU52FIKAHrfSL/m80m1tbWcHh4iFgs5iZ1+r6q1+toNBpu8b27u+uZPMsY9utXe136vNbimRBCyFebe/fuYWNjA+Vy2c1fBP1OtO+/QRaU+jsJNbG8vOzmOCKIEkGfvMskBIoNs2jnC1qgKoqCiYkJTE9P4/z583jiiScwPz+P8fFxRKNR3/wQ+ljD3v2DhCz2d9qwQVup6mPp+Zmew4hSQIRyuVwO09PTWFhYQDwex97engv76OehNDIy4kJd7e7uujnpyMgIisUiZmZmkM1mnWeKnnvodgXgPCz9PD70dWmhtjbe0N/r+YoIE8WIRDw6q9WqmxttbW1hbW3NJeGWNYrUUedLkPqHQiEUi0UUi0VcuXIFS0tLmJ6edkLNoHNUrdS5f/8+yuUyms3mEeGbnFMs36emppBOpz0CVGuApYWN0n6Sb6VYLGJubg7nz5/H/fv33Rzcb/xrJZy9R62gVPeF/t4eV8KGnj59GvPz8zh16hTOnDmDqakpJ8x8WMOcLwt+Blrd7qeh47ThnJS3/WHXqvZ54feMsSHuZCyLFfuVK1dw7tw5bG9vY39/H8vLy/j444+xubmJmzdvurWajEWpO+BVfNjz6vHgNxbsONJKSy3EFhlALBZzxopikX/hwgXk83lcvnwZxWIRuVzOhcjTa1N9ryQSCSSTSaTTaeeNpK9BG3ZZQTnwaY6+UqmEzc1NjI2NoVgsupx8ch6r/BnkKeGneNDbes2sQ9xppbQ2urPKFbkufXz9vNHjy/ah/Eb6QsJqZ7NZnD592iWp1gaUug11n2sFj20Tq/iUPpTfWCWHjBO5hwQ5rr52fe/ZMaiv/8tGYEVE0IdqEAEEELyxgp43qBtcIpEIVC4IU1NTgcqdOnUqUDkbFqAfQZNorq2tBSr3qPssKEGPF1Qo9NOf/jRQuY8//jhQuUKhMLTMoEm7Jui1BrFCeZhyQQl6n/lZOfjxqOv3RUDizR8eHuLw8NCFtgG8ru6iiBBrNplsy2dRHLz44osIh8PIZDJYXl7G5uams7LTi0pxN00kEpicnMRzzz2HxcVF5HI5J5SXOuiXlixiZVuEuYVCAefPn0epVMLy8jLu3bvnmeTp54G8HDc3N/Hmm28iHo87azodz1OfU4TfOg5oNBrF9PQ0Ll++jDt37qBcLmNra8sl4tYTBFl0VSoV3LhxA+vr67h37x4ODw9x4sQJ5PN5l+BKv9wF6QetDNGhnKxgvtVquUmtVjYAXqsQu1gUC8W9vT1sbGxga2vL49IdjUZx8uRJfO1rX8OJEyfcuyfo89ZO4qxiRZQ88XgcMzMzKBaL+OSTT3wnZtpVVf4ikQieeOIJPPvss7h06ZLHIkQvgP0m53qR+FktMWQirBck+rq73QdxsOW9aBVzUkZPzsQLSVsD6Vi1euKrhQEyZsLhMLLZ7JFQLIQQQr7aSAhAG6bFviOtYH2QMYHeJ6EIV1ZW+pbXx7dCb0ELMKS8zFej0ShmZ2dx7tw5vPLKKzh37hzy+bxLvmp/q48x7D1vlQ/2s2zbtpFrt5bQ+lqs17DsEy+DXC6HVquF06dPu9jqoqjxU0SMjo46j9Zer4fbt29je3sbjUYDs7OzqNfrTkEj1skSukzmg9qjRYRkdu7Y7XadcY7OB2cNIaQ/RTkiebEkBGWtVsPW1hbW19exvb2N27dvu5wlkiOiVCp5hKu6bnI+EcCJ0kaMUCQvxKAEtX40m00cHBx4FBFaGCjHEuXH9PQ0JicnnSLCKqKkzlrgKMeR8vl83q0R3n//fRweHjpPWL/5tR6XWkliy1pBnx6fwtjYGOLxOLLZLK5cuYKzZ8/i3LlzOHXqlBt3j7MiAjh6T+s+skLWfmhBr/6vj+F3HvscknEi3uZijCb5UprNJmKxmDMw0oopQd/L/bACZrtesQpf21Zy7yUSCRSLRScfkHtR8kNIyCndFnqdIm0riupYLObW5VZwbeug664VA+IVoT1arLI0aDv1Qx9XH19kBdajyU9JqLHrwH7YZ5Gg2057gQ179vXrW13XYc8g+1+/z0Rh/DB8GZUPGnpEEEJIACQu7+rqKlZXVxGNRl1+hbGxMUQiEWQyGUxOTiIWiznvB5kcAZ8uvKLRKE6cOIFsNourV6/i/v37eOutt/CTn/wEBwcHHquSmZkZzM/P48SJEzh79iyuXr2K8fFxT5I1eclrxYNeFOnFQCqVwqlTpxAOh7G6uop/9+/+nSeWpj4GALd4un79OsrlMtbX1xEOh/H000+j0+k4C4Jut+vc2fXv5VoSiQROnjyJP/zDP0S9XsePfvQjbG1tuTqKoF6HIOp0Oq49Wq0WFhYWcPbsWZfcanx83C2g/SYjMuEUpYUoOvSftFu/RVGv13OCB2nHdrvtFl/37t3DjRs3cOvWLXe+cDiMYrGI733ve/jN3/xNTExMBHZ31+jyo6OjzvJOFkniJbO4uIiFhQW89dZbbiErk1KZbMrx5HfpdBoXL17EqVOnXFxkm/NDFtF+Czm/drYTyEE0Gg3s7u46K0Qr2JHj+lnVCDqMga6fjB1tSdRvASFtmMvlMDMzg9deew1f//rXA13DV4lMJjNwvx4XNiyBtZKr1Wqebb/8Mho9Buw9ZMejPbfdtufudx7gqBHE5uamZ/vg4MCz/c4773i2/8t/+S/u85UrVzz7Xn31Vc/2+fPnPduTk5Oe7VQq5dnWz9qHpVwue7ZtvP9bt265z/V6feCx7CLItpnur5MnT3r2fec73/FsWyObYYYPur+sMdKwcTJsW1+XPbY1QLHbts0eZqFo62GPbceBNYh67rnn3OcPPvjAs0+HdgGG51OxddEWexIzW3jjjTc82z/4wQ/wuPHOO+9gc3PTvYcBbxtZoZR8HiSw0L/Rn7UQynrx2XceADcH8jNgkHnfhQsXcPr0aXz961/H1NQU5ufnXYJmv/Ae+jh6DjvMs9PWTX/WcwipH/DpOO831/A7lg6NND4+jtHRUXznO9/BjRs38P7772Nra8t5zGq0sBR4MK4PDg5cXPlUKoVr165henoa6XQaiUQChULBeZ6Kl4r2RI5Go0gkEh5Lf+k7CZ/V6XRcbgcxGBELYDH6qVQqzuNB6t1qtVAul/Hhhx9ie3sbpVLJKVEajQbi8bjn2vQcemRkBNlsFslk0uXSOHHiBM6fP49CoYDFxUUX5kV7UQeh232Qb2F/f//IukWsm2UOKQZMYvCic33J+kn6RIfvskq9kZEHMfInJibc2mNlZQW/+MUvcPv2baysrDhlj/aQ1v2u56r2/tOKCD3PFgVELpfDU089hZMnT+K5555DPp9HsVhEJpPxhDV9HI3xgE8Fp6Ojo573h6x3/a7drg1kW8IWy32jvftlDStjQa999HFkjS25dGKxmPMomJiYwPXr1934rFarbk2gsc8Hff8KfuNRvtf/5XjaGAp4MIcYHx/H/Pw8Xn31VaRSKeRyOUSjUfcMTqVSHuNF/WyXZ5W0iST4npiYAAD3XtLW8voabP2ljCRiHxsbQ61Wc3k6dJ9pJUg/hbR+X1mFh5xfK4Vlu9lsolwuu7mJfo/5eaPIcWWM9Vv3yzFs/g9Bh0yenp725KvxUxL7Yd9RemxZhb7f2lkfV9pPhwLU+3RdrKKun9JO/n/RFRVURBBCSABqtRquXbuGa9euYX193b3kgAcvnUQigbNnz6JQKCCdTnuSDPrlIYjFYohGoygUCjh16hSuXLmCl19+2S0yZAE5NzeHfD7vEsjFYjGP5bq2wJHFjF186QWfTKhnZ2fxB3/wB9je3sbPf/5zbGxsOOGt1F1PAtrtNtbW1pxl1t/5O3/HCbHFA0Ss17XVhl6MJBIJzM3N4Tvf+Q6q1Spu3ryJg4MDrK2toVKpuEm/KG/kmsrlMm7evIn/9X/9XzEzMwPgQTJSSbK4uLiIdDrtJncSe1YvQiKRiFuwaUG1CFdkMQR4E0xVq1VnLddqtdyk991338VHH32EO3fuYHV1FZVKxR1D3Gx/4zd+A7Ozs659xDLuYRZ6etGtLcVkkhuPx3H69Gmsrq7ivffew/vvv3/E+kT6RE+URAAvx5PJp7ZKHLSg0hNFnY9Evh8WI1cs+PTYlPPrcBN6kmUt3qxiwraZnejp38k4P3PmDL71rW/hpZdewvT0NIrFYiBvOEIIIV8dqtXqkYTffsYLQRhW3m+/n9DL1kX+y7s0Ho+7BMGnT5/GxYsXcfr0aWQyGWQyGWfQot/9fjyMNewgYZX+76ew8Nv2+40VtIh36NTUFPb395HP5xGPx1GtVp1y1K995Np0jHvxSq7VaojH44jFYigWi9jf30c2m3XKAxFcyTxMciAkEgnnPSGGLJKnSpIrl8tlT4hRMbapVCqo1WoeRUS73UalUsGdO3dQKpVQLpc9ddeCShmL4gkRCoUwMTGBqakpFItFTE5O4sSJEy5cqA4BI0K4oMoImR9LImyZy1nPXTm+WCBbz1steJbfaIGevb90kvLFxUWkUinXJiMjIy53is4T4jcn1IqHfmNbQn9J3hDxJjp58iRmZmaQTCadNb6+pi+68O9R0U9ADxwVkNq5ungZiSLM5gYJghXWi0IrmUwim81ifHwc4+PjaLfb7l7rdx3DzhnE0MoeR8Z1JBJBKpVCKpVyHmiFQgGRSATJZNKNs37eNPbZJeXT6TRqtZpTJsszbFC99WdJ8CzPJb127Nce/fb3axs/JYh+5tbrdZdvaVBb6ut5GKM3jdyb0u7yrO4X3WTYOfyeK/r7h6Hf+7FfuccFKiIIISQgOzs7nvBJIrDX2nl5qYnVlLbmkf/WxVwWDVeuXPGE0QHgFoqyQLDWEiL0tRZrWiCrrRVkgh+JRDA9PY3vf//7iMfjeP311/Hxxx+7yYG2TpIJingCXL9+Hf/qX/0rPPPMMzh37hwWFxcxMzPjFrQySZLEhSKAl0XFuXPn8Pu///tYWVnBrVu38Kd/+qfY3d09EhpJu5e3221Uq1Xcu3fPLRzu3r2LDz/8ENls1iVazGQyzttErj+RSODMmTPOM0KE55L0UWLqjo+PIxKJoNFoOEube/fu4Ze//CW2t7fdZHZsbAzb29sol8vO/VcsWXK5HM6cOYNXXnkFhULB01/iQRJkIuE3eZTk3NqTIx6PI5/P4+LFi/j2t7+NtbU17O7uHhHCa+scSdIlbTY2NnYkPqX8TqPHpV7I69ADfr/zIx6PY3p6GisrK26s6kWnnMtvEmvvKVsnvQj2i0Mt46tQKODcuXN44YUXcO7cOReGQYQIhBBCiKDnV8DRuOFa8BlEUDPMmlF7NvqV87OQFCOQSCTiEqA+//zzuHr1Ks6fP4+pqSlPLq0gFtx67vAwghJtfGP36Xpr791hwh+d7FR+L/OvyclJlEol7OzsIJfLuZA9fueORqMYGRlxc0FtyCPev1JvmS9Fo1H0eg9ik+ucC4lEAtls1sV5n52ddULRmzdvYn9/3+UXqdfr2N/fdx7NkoS81Wo5jwkRrIsnbK/Xc6FMZf4r59aeTjLH73a7znL6+eefx9NPP+2SPafTaTe/1XMdmR8HFaR3u13s7u5ic3MTa2trbt2g83jpds9kMsjn80ilUp51jZ636XFiBabyJ+srsSI/efIk5ufncePGDdy8eRPvvfce7t+/j+vXr7v1hF6PaYMWqbP2wtAKlHQ67cIwzc7O4vz587h48SKKxaIzDpP7Te6lx1kRYe9N8e45PDzE7u6uC4cGeD2wJdyYPAtEQSZ5QwqFApLJpCdPHQDPekcbHllhtLS3rK9SqRRGRkawsLCAp59+Gvfv38f+/j5qtZoLCWs9I/Sz1n5nPSS0ItC2iS43Pj7u8tecO3cOU1NTmJub83hPWUt8P4WzXr+Ew2Ekk0n0ej1cvnwZU1NT7lm1t7eHWq3mUUZKfbWXlvzV63Xcv3/f9aFOIK/rZJ/5/bxV9f5Bf41GA3t7e9je3sbq6ip2dnY8CmP7XpTniX5P2XWdxgr19XVIvppTp05hdnbWhXrWnjBaMav7vF/4Jt03ep+MX796+L0LB7Wpfj7q55Rtd33dXwaoiCCEkAB0Oh23iJCFgRV86gmovDj1Ikx/L/vkJRWNRo/kXbCLT+v2qwXDNvyOxi6OZSIYj8dx7tw5HBwcOAt1HS7JLg5kAdbpdHDt2jXU63Wsra1hZWUFly5dQiaTwdjYGFKplAsdonNViGJDBPTFYhHZbBa3bt3Cxx9/jL29PdTrdecR4mdFIW7uYo11eHiInZ0d137RaBT37t1DMpl0159IJLCysuLxeJDEaoeHh04RIe7B7XbbHevu3bu4deuWC18l1yTxRoFP3W4nJiawuLiI8+fP48qVK554n3qCEwRrCWaTlemxJB4uTz31FN588028/vrrnuTnevIki+azZ8+6fBv9hAT6XH5YBYf97SDS6TTOnDmDt956yxPqQp/TT5miFVVyPfqeEC8PCUUwPj7uCYkgY2hs7EGy7qeffhonT57E+Pi4s2wb5s1BCCHkq8XVq1exvLzshCZaQCbY95jfu9BPUA/AIwDR+/X/fkp3EcxGo1EUi0WkUilks1k88cQTmJqawvnz5zE3N4dMJnPEAl7XtZ9AROYw+poGGQUEOaZVnvi1kd9167m1FYiJV0S328XGxgaWl5fx+uuvuzl7LBbzCEW1oNOeW38vlrti+W/rGgqFsLu7i8PDQyQSCYyPjzthnghoZa4pwlu5Fm1EJAnJxehF2ly8Jmx7Sz1FOSFjSObhp06dwvz8PKanp5HP513CXJk36bnOw+aH6HQ6ODw89ORM0f1p+07isdvj+wnUBK0Ak7Lag0E8qDOZDE6fPo1sNotCoYC7d+9ibGwM6+vrnlxkfm2m//R9lMvlcOrUKSwuLuLSpUvIZrOYmppyHuqynhgkEH0c0dcpBmrNZtNj2a77VK8TdJtHIhEkEgkXHUCHBNLHH4R9LmjFUDQaxfj4OIrFogs7BDzwbNOK5EHX6HcNfnXwW6uMjo66hMjZbBbFYtGNHZtn0V53v/tA7nHxCspms+h0Os6orFQqHbm/tBLFtm2320WlUkEikXDPJj/Bd7931jCkz/UaXhS+4olRqVRQr9cHHtPWw+/Zb/ET9GvPGQm7Z407Bx3Pvs9svw9TJvSbE9j6DqrDoDFrx+2XAa62CSEkALIIEUXE6OinMTJlAiuhf8RqRyzFg8SgFIscveCTl5YWKOuXphbS66S84XDYY+Gu40bqxUav10OxWMRTTz2FTqeD3d1dvP766zg4OHATBh1jUbtu7u3t4Z133sHt27fx8ccfY3NzEzMzMwiHw5iYmHBhbsQCSuosizNJ3BWPx/Htb38biUQC165dw8bGhrPw0hYdcm3WEqXT6bgJsIR3ssqUUCiEGzduIBKJuLYSSzmtwJE+k4lKJBLxeGrIeaWvJNlYKBTC5cuXcenSJZw9exYnT57E7OysW6zoRVNQ9Biwk2bd91LXfD6Pc+fO4eWXX8bHH3+M/f19F6JLxlQymUQymUQul8PLL7+Mqakpp4jQFl16sjVo4mTr+jCTn0wmg4sXLyISiRwJxWQn5lJ34FPvGFFWicuz7M/n8wiHw5iensaJEycwNTXlEotLUsdKpYJwOIzLly+7cGraMokc5dKlS57td99917OtJ8fDFDl+ruOD9g9aoFirtn6WSoKN96/727rt2/vVnsuWt7kBPvnkE/f59u3bnn1/9Vd/5dm2OSS+8Y1vDNy2uQEeBpsnw+YS0LktbCgai+T26YfOC/F3/s7f8ey7cOGCZ9v2je3LYbkaNLavhnk5DRpjtp/7CU2FWCzm2bbjWbe/PdawY9ttmyvk+eefd5///b//933P63euYQt7Xd6279bW1sDfPg6cPXsWzWbTWVrrcWEFEsMENVrY7XcMv/L6fWhDc4p1uFiI53I5TExMOEv4ubk5J6x6WIttmTf6Ya3I+11nv+Paz0EEg/InQk2ZB8q8UsInXbx4EaFQCJ988ombt2cyGTQaDZTLZSd081NCWOGyDp3U6/Xc3F5f/+HhofN00IJVMYKQ/F36d3JtMv/UltoyX9beAH7oMSRzGLH6XVhYcJbnNj+DjCPBT+g4jFqt5pRyeu7m148S1nTYvWGVc9Yy2QpKJcxoOBxGLpdz98Hm5qbrKx2uttVqOWMkrZDRIZ8kjOzly5dx/vx5nDlzBolEwpOQWhuE6Xo/7Fz4y4Rcn56HS/5EWbvpcWCt8AUR0kvos1gshpGREc8Yt+NTP4fsfasVVXLusbExTE5OYnR0FPl8HiMjI9jd3cX777+PSqXi1kg2nJFWQEo/9vPyscg4TKVSLn+fzseSTCZdXkP9HLZjpt9733ruSF6tqakpdDod7O3teUKSyfX0a8Nms4mdnR30ej1sbm66/rChsnQ/WoWMVTrJsbViVJ5fzWYTtVoNOzs7uHHjBlZXV7G/v++8wqScDe/WD7s27rd+0/0psodsNuu8w6xCViuItKyh3zPS77zSBpogil6/9b6fUkU+yzvDT1HyZYCKCEIICUCpVHKWTYIk2pWJ7PT0tCd5s7hvi9JCTzbkxSEvKnkRyuJFJ4/WVgXtdtsJZHo9b44DLbSORqO+MfX1+SXnweTkJJ5//nkUCgVsbGygUqm44+pYs3Zy1u12cXBwgFqthvv377ty+Xwec3NzePrpp/Hcc8/hzJkzzg1VJgLili7WY7Ozs0in03j33Xdx9+5dpyiwCzYJFeWn+bcWbrIg6nQ6LgSQIO0uHgu9Xs8tTPTxRNggbvzy0hfrNVn4/+2//bdx4cIFF3NXW7RphiXm1ehJ8NjYmGfCLHXRk8VCoYCXXnoJ/+2//Tdcv37dJdMdHR1FLpfDs88+iwsXLmB2dhavvvoq8vm8c0mV/pDrlj8bYsxa1OgJoJ2MDkKUJ8lk0i0S5X5IpVIufJQs/l588UWXTLJUKmF7exudTgcLCwu4cuUKzp49i06ng1wu5xYCmUzGCV60paBcp7YsspNuQgghRPjGN76ByclJhEIh/PznP8fe3p6bg4lAS/ATzPgJV6yQyH5nQ2SMjo46A45UKoXJyUlks1nMzc1hcXERxWIRc3NzTsgngjGx8tbzG20MM+ydpwWC2kBCG8AM82rQ3/khczXbDjIPE+MPLRSUeogASwScwAMPlvn5eaRSKdy/fx+Hh4c4deoU1tbW8MEHH2B1dRX1et0dywqWtfHJ6Oiom+9LeRFoa2vvZrPphG36mq3QUfexrB+i0ajz+AXgQjTZnG+6DvL7kZER5wWazWYxMzODubk5vPDCC5idnfUkuddeMJLr4mGMZHR/VSoVT51lzq3n4CMjI877WLyvdTgaAL75z3Rd5TtriCRrDjFo6XQ6iEQiKBQKOHHiBJaXl7G3t4dyuewMUQ4PD1EqlbC8vIx0Ou08NbLZrAtlJmuSTCbjPKW1gNsKyYVWqxUo1NmXFWvZruP8SxsDR43G/JTcEh5MQm3psWON0IR+wnoZS/I8kvEjBkpjY2NYXFxEIpHA/fv3MTY25u5RuYf1/anXnPq5Zp9x8gyScS7GaePj48hkMs4gSjwiJCfGIGVwv++tMk5Cr8m7QHJNaPzWbVrJKiGPI5EIyuUyKpWKx9tP/0YrI+z7wL7X/K5BnjdiNLi9vY3d3V33zNQGaQ+j0NNlBynFpQ0lZ4d4pdicOPp9a9vxYeqk26GfYmnQb/36rt9v/RQxXxZlBBURhBASgL29PZRKJRd/EfAmysvlcjh79qxHyC7oBahsW7dg2ac/90sap62jtPeFfhEDnwqrAa8XhnwXj8fdyz+Xy+HkyZN49tlnnZWCFnzbiYkW0ou1lxx/e3sby8vLeOedd7C/v49CoYB4PO4WDVJvqVc8HseTTz6JQqGAZ599Fu+++y6uXbuGtbU1Z8mmXYDlGsTaSSPXqUMTiUBdPsv5pa1FEK9jP0v7ieLDxoDNZrNIJBI4ffo0vvnNb+LSpUtOgC6L4VgsdkSIP8waTLev7Xvdx/o6ZKwkk0nMzc3h5ZdfxsHBgXNBzmQy+Gt/7a/hlVdewenTp5FIJNykWC8spI66ntbaq59i5WGF95lMBlevXsXf/bt/Fz/60Y/ceIvFYnjttdeQy+WQy+WQTqcRi8UwNzd3ZOHT7XZd7GaxVNOWz/o+kL6TSajeJ9/rJOWEEEKIUCwWXRJc8SDtdrtOQS7hG7WRiRbYiOBaBMtaeCDC6F6v5zyrRkZGMDU15QnbGYlEMDExgXQ6jVQqhWKxiHQ6jcnJSUxOTiKdTjtlvPyJhbwWOD+MYMSiDRVk7mDnYcOEiP3QZax19DCs8Fe8hS5cuIBisYhyuexyh62trbkQW9a6WtdFKyX8lCRaAKfnUdZqX67BzqOlrIwLuQ5tRCPHkPmX7k8x1pDwnIVCAYVCwYUQmp6eRjqd9sTet14Qn0dgpdc12uBD2kjn0Wi1Wi4Mqv69MMji2LaZtIluW7mP9HlHRkacJ7soCyuVCiqVCqamppwFeDKZRCqVQqFQQC6XQyKRQKFQcNbh2ktXr9vkOr8qiKGXeEOUy2Xs7+/j8PDQGbDJ+LLtoj3D9dj1S/Ttp8ySY/R7RuhzyPNI39tLS0uYnJxEMpnE4eGhC7m7urrqkq7LM9oqIUXJIN79cnypswi1Z2ZmkMlk3DiamJjAzMwM4vE4xsfHndLMjqdBay6tBLDKGsD7DBKsLMD2oSBeEbVaDRsbG4hEIq6N9BpJr5f1PWqVN/pZqBULsm5rNBrOqHN1dRW7u7ueNaS+Ro30gx6Ddl2t1/m6HXQ/SR/KezKdTnvuZ62k9TuOXS/rdvRrY79Q2bZP9DNT6qqPadfkfue1YfW+LEoIgIoIQggJhOQvsAtNSVC8uLiI2dlZxONxj2JAsBrrQZp1/WKyLyH5LAuTQfEN9SRHKzW0IkSslSKRCHK5HF577TXs7+/jrbfewtramrN20nWyihiZdGjrOFkMiMBYXvL2OmSREo/HXfiAkydP4mtf+xo2Njawt7eH3d1dt+hvtVpYWVnBzs6Oi9erJ2t6kqXrq10XpbxYUckCUPosnU4DeKBgEQv6ZDLp+nVqagpnzpxBKpXCzMwMzp8/79zepY91fF8RPATpe113P8sI7aHgF5YmHo/ja1/7Gmq1Gubn51GpVJDNZvHqq6/izJkznjjB1u3ZTmTtse04lL77LIL7ZDKJc+fOIZPJ4Fvf+pZTHI2NjWFqagqRSMRZq8iiRdpCL1K0gkFPkv3aU0/8/a57mDXNV5mFhQXP9iBPn2HhfCx28TAo5M6wsSYWeX71Ah4u7NMw4Zc9lj2XPrYN72PL/uxnP/Nsf/jhh57te/fuebafe+65gXUbxN7enmf7hz/8oWe7VCq5z7Zv7DWXy2XPts7NAwDf+9733Off/M3f9OwbFmpp0DgAvG3YT+gh+An/BpUf5Lk27NjDQnjZ5+7D1GNY2DN9n168eNGzb3Nzc+CxLYPazO6rVCoDj/U4IAIaEfrv7++j0+lgfX0dW1tb2NjYQKPRQK1Wc0J/SSra6/U8iYol5r8kBhXDhU6n4/ppdHQUTz31lLPKDofDLq/X+Pi4+4tGo84TU96HVsiljSishW9QK0/AP+a3FtD7GSsAwZUQWqikhU2iiNHnlvMB8AgGxbp+ZGTEhdqp1WpoNBo4ODhAr9fDysoKVlZWUKlUPB62dn4jiPBVziN5raRd9e+1AFV+a/dbJUev98AjVxsy2dBf3W7Xo1iKxWIoFAqYmZlBsVjE008/jenpaUxOTiKTyThPGBmL2rvGKlJsHwdB5n9auWGt4OV80WjU5RHw63PdzjIPtFbX2gBJzqXXNbrfo9EoEokEMpmMM2SSsSpJwUulkmvveDzu2kjmxn6W61oREQqFfAXhn1e580XGekJIjH+5v/S476fckzbUc3z9rLLn088wrcyQc9j1svYUkjJyvkajgVQqhUqlgkgkgr29PXQ6Hezv76PX67nQUnotK+fW60AZG7I+yWaziMfjWFpawsTEhCcfRDKZdOHzZNzo9Yhcvx3f+jlilV5+Ck3gU0WN7gerKNS/Ey+uRqOB/f19JBIJ1Gq1I15Lck/K80+3i12P6b63Cutms4lqtYpyuYzd3V2USiWPQkUraIaNQz/8hPZacSIeK5IsXIcqtO9GfQw/WY58bxXZuj36KUZ0Wf3O8Sujv7fnsXIl+6z6MjyHqIgghJAAbG5uetwHRQmQTCYxPT2NpaUlZLNZj3WHfoH4Tfz9tO5+rvry2b50bBmNnsD0syYCPrVa6vV6SCQSuHDhgsuxEAqFsLq6ikql0vcFqq9FjiXxivP5vLPo08JiuQbdjlInSTa4uLiIg4MD7O/vY2dnB1tbW06of/PmTdy5cwf37t3D7u6uZyGpr123sXYn1RNIbbUhk8SFhQWkUin0ej13LeJSG41GMT8/j1OnTrnJTC6X8yiEdLv7TS6CTA50+/gdw6/tRYkiuRcuX76MSqWCZDLpBBqyMLWJ4YbVyc/VvN9vglyfeBHlcrkjseIJIYSQLxK5XA7j4+OYmJjA3NycE3BKaCaxrteCMT1XE0GTzk2gBSDyztfhTVKplBP2itBKhKbaS9NPueUnlPisggk/61vt8aHnu9bYxIbysOi5jJ73aI9NncvLCm/sfNgqJ8LhsFNKhEIh1Ot1PPHEE9jc3MTY2JhHMSSC6VAo5Ml/AMD1tUbm7FaYpNtBsOGErLA+FAqhUCggm81iaWkJ+/v7uH//vmuXSCTi8nxJCKb5+XnMzMxgfHzcCUNtIlw9TqxRjt+YCDpGxsbGcOLECaytrbk2tgm15frE41QnM9ahtXQ76PaTY2lhrb5/5DdaaaPXNqLo030o/8fHx931ay9Zrbix7SP19hP86e3PYpzzZUH3w8HBAba3t1EqlY4kOxb0M1HGfjgc9oxZq9CSdtZhVK3wWT+H/JDvJfys9mSQkLDVahX5fB6Hh4fY2trC4eGh85yReguJRMIZSSUSCc+9JV5Hk5OTzuI+mUwiGo06Ybc1lrL1tp4R0nb6eS779XNfFGmijPbzFvBTQmja7TbW1tbQarVw/vx5ZLNZ570h96btAz325f2g92slhCggtre3cfPmTdy7d88Zd0o7+ile9XVbJYyVb+i2s0oNGV+FQgFLS0uYn593igi5n3V9dX8IdnzqdujXrn5yk8/6vLXvPX1fDTOa+iITWBERNK719vZ2oHLWuqsf1pLo82K18f0I0qlnz54NdKzJyclA5YJaFF29ejVQud3d3UDlgrZJ0JslaLmgN07QF/rOzk6gcv/P//P/BCpnrcn8GJYAUbCWf/0IakkatI2HWc897HmDHu9xZGVlxYUfAh48ExOJBCYmJnDmzBlcuHDBTU6AT60w9IJTFgF+VjZ+oXH072SfHFv/1g+/F6AgL9Rms+mZTEl+hxdeeAHxeBz5fB4/+tGPsLKy4gknoBdf2vJBjjExMYHFxUVcuHABzz//vJvU6AW3bg8/K4t4PO5itrZaLeda3ev18OSTT7rQT2+99ZazxpFYk1In7b1iF+6yKJUXuYT1yWQyeOaZZzA/P+8WfIlEwmMtNT4+7lzd5XjaHVwvhKRN9IIqCJ9nYpHP53Hq1KnP/HtCCCGEfIqEOgLgibn/VUMLxoLMZwatV6yxRb/z+HmbDbIg1XNJEeLLfDOTyWBmZgYLCwsea30JDSmeBFtbW6hUKs6rV4cE0fN8vzWqnwBR11UrcMQ4JB6PO2vq06dPY29vzxmMiHeNxILPZrPIZDKYnZ3F5OSkC02pk1H36yep/+dRQkjdx8fHkUwmEYvFnHecDrGkaTQazmpeW0nbetjf6jWRvibZtnW2gl7dX3oNJfN/AB5FhFbg+F2zVphohYqu7+OKKJTkftjf38fW1pbz9gK8XgxWoCztGg6HkU6nkc1mPcmR9dpY1mxaAO4nCO+nYJW+kf6RdVokEkG73UYymUSz2cSJEyfQaDSwurqKg4MDNBoNt96V+73T6SCVSmFubg7RaNSFWZI6izJFIiKIQaJ4T+j6+iktdfto4zn9vVYgyhiUNpLwbFagroX4/az9xcBPjA53d3cxNTXl8vNJXey630/G4KeEAuDyQmxtbeHmzZtYX1/H/v7+QEG6lpfYdtHXpuUngr13pZ2KxSLOnDmDubk5t47XY9Xex7peVlFq+y7o9/3ed/3GhZax2H6z/fpl5KsrVSSEkIegXC675MrhcBiNRgNTU1P43ve+h6effhqLi4vOEklbjABwEyB5gdbrdef+K2VFKaDd5/sp4fTk3e9FpL/zs+iRMjp8lE6OPTU1hZdffhlLS0u4ePEi/uRP/gQ3b950yci0dZyelIyNjSGdTuPFF1/Eb/3Wb+Hpp592iyd9Lu16LRZqkk9BJrgyORgbG0MikUA+n3cWiIVCAadPn8bLL7+MlZUV5zWxt7eHra0trK2todfrubifsgCSesTjcZw/fx7xeNzFrR0ZGcHCwgLy+TzOnDnjJsiiXNKTaMl3YS1mRDFprR314rXfpJkQQggh5IuGFvpo/IRSMieycaster4n1ufAp3NRbcghigQ99w1q1CFlZf6lvTH39vZw584dZ82dyWRcItM333wT9+/fx9raGiqVCsrlsicxs74O4Ghsb8EaqEh9otEowuEwZmdnXZ6Pubk5TExM4PLlyy4Gv5QTz1xRXGijnX7hbbQxk8xDZe5vlSkPK9AaHX2QKy2fzyOfz3vyMNhk1O12G9vb20gkEmg2m06hJwJbm7dLz7mljjYsk82Lp8eb9JGsGawAVysi5LP2dNAGRFroaYW5Vng8aN32OKCFweLhUq1WfROqiyeKzjWojcJkLOuQYX4Ko0GCan0+P0M9P6QOovwA4EK/5nI5N4b1mr3X6yEWiyGfzztFpTaqk3tSh0LTzxyrTPMTetvP2otC37tSRj8bRakj0QfE09+v7axgWxS9ElawWq2iWq06hYxW5thnr74We4+KrKPVamFvbw/r6+tYXV3F6uoq9vb2XBvLPeMXeq2fslTLEvzaUl+71FdCG4onhCiMtIGifkb40U+J0K+s7Vv7vR6zut30tdhz+z0n/Y49SMn/RYKKCEIICYAsQMSCKZ1O49KlS7h48SKmp6fdZEqsFvwmsDKhiMVinpfD6OiD+JP2RWRf8sCn3gx2nz3esBeQvJxtQkCxHhsZGcH8/DxyuRzm5+dx48YNvP322/joo49cEmkrZA+FQnjmmWfw4osv4sqVK25ilE6nPRZaFq2k8LOosC9a/Xf69Gk3KZY/UQDpiZFeaEl7a+sRqYdMWPSixk4Sg1g/+NX7iz4hIKQfTz/9tGe7UCh4tnX8+X4JBPtt23ve3ifa89Amu7TYvAL2WNbLVm9bKyrr8WjPbQVhg/JRDLtmiz3XxsbGwPIPg/Vcfv311/uWHWZpZnNy2PbWnlm2b4YJvmwbDRpHw47lt5gdtK2PZ6/Z1st6lA4bg4NyWwy7dyzW21Z7YH/zm9/07PvJT37i2e4nUO13br3f/tbmCiGPF/2EHfLfzj/98BPMaAGy/b2MMT8BmD6ePYefQEsrIUQIOTs7i2w2i/Hxcaf8kLBMkUjExZCXHGXb29vOarhcLrvwLfV63QkhZR5fqVScIFLnt5JwLYVCAZlMBuPj45ifn0cikXA5P0SoCMAT9tPP40GuSQvS/ISDcm3Aw4XZHES3+2mi9lqt5vEuljrK+7XdbqNcLqNUKrn3j663NsCy824tmLV9PijkrSi3rGGQIGs1bcGv62DbZ9h66vO05ZcFGUuiYJA+lfmKXqdGo1F3X4mwW8ar5LWR3Dd+fe/3ftdKNamPnM+uRweFchoZGUEikUCv10M8Hke320WxWHTX0Ov1PB71+pqAT9/TeqyJgkXfh1YZoY+v81Do9aH+rbSb/M4q1STPYaFQQLfbdZ5R2lpeDCF1fa1SAwBqtRpGRkZQKpVwcHDgogGIPECvn/U9op8x2oNEnoP1eh2rq6u4desWPvnkE3z88ccueoEO+6Q9zqxCwCob5FlgQysL+l2jPVOSyaR79or3mx1/+rlh26yfksDSr6z+Xve3XItmWH4J/T4cpsT4IkNFBCGEBECs9CU8z9LSEl588UVMT0+7hYa82PUL0W8y7feSs9ZU9nca+wLzo59gX7AKDu3q2e123XWK9UChUMD09DQuXbqEu3fvYn19HeFwGK1WC51OxyWBeumll3Dx4kVks1lPbM5BApXPM4kPGvbsV80wQRchhBBCyBcda7Qh+M1B/eY6er47SGkh+/3C3fgZpNhzauG7fK8Fg9roRQTlxWLRHUsnoS4UCmg0GiiXy9jc3MTq6iquX7/uwtE0m00XZ16EXLFYDN1u14VVEo9eETwWCgWk02mcPHkSExMTmJqawszMjAtPI4oGsdbWVv86TIkoFXq9nicvM0VdpQAASJNJREFUneAXJ94K9/tZ7Aal13vgdVyr1ZwiQtpV5v2irOl0OqjX6yiXy9jZ2XGJpEUJYQ2sbL8C/mNFBLNamSV9qK3JRVDp57Wihd9aUG3LBW2Tx3mur43cpG0lZK6gQzf5WazrY1mjukEW3vq/1MPG7O+nMNJGaX7lrKIDOJqXQt93Gq1w8LPi73efWTmBnzJNyulxbn8jChLJD6OjC8h1yH9ryKeR/e12263rLTpEk9RVFDainOr1emg0Guh0Otjb20OpVMLq6iru3r2Lra0t1Ot1p4TRCkBR+miFhxhLagWrH3Z82D4QRXEsFnPPWu2F49f21vDiYTzGhslv/OQDfnIjWybo8+hhn1u/TqiIIISQAGSzWVSrVXQ6HeRyOTzzzDO4cuWKs+joZ0EzSCnRb1JkGbbPb/JiJ0J+L1nrSiuTQu1RADyw9kgmk5icnMSFCxewvr6Oe/fuIRKJeGLrJpNJnD9/HpOTky5mpp91ESGEEEII+eITNAzSo0TnDnsY/ARJfscRBcEwYx0dXkaseMUSFzgaigp4IAzXAjVr8KNDAemkyH4CNV2foIItv/bwa4PPw+joqMeLo1arOSWAnEuHpW2326jVarhz547Lb6EVEH7XYa225bzaatoKKbWwWMrY8Fi93oNwTNKPWhDt10b9Ytlrb4th/fA4IM8BGbvNZhO1Ws0JrUUg3Wq1XOgrK9CWdoxEIi4hfbvd9vWa91Og9RPyawWjPqe22NflRclnlXJ+/awVAfJZFCHD6tfPWt0v8bH9jVa8yH+tVJE2Fq+ubDaLbDbrCQ0t9beKCK1MkPPqEE06BLMoQ2yuSPle5ADtdhudTgelUgn1eh23b9/GxsYG3n33Xbz33nuo1+s4PDx07S/XpEM06bBxVimoPVT8ZBhWkSj/Jeek/CWTSaf0tcolq3yynjV+fea3X4+rYQamVsk06LjD0O0yKBLFFwUqIgghJACvvPIK3nnnHYyMPAhZ9Oqrr6JQKBwRtsvLx2+CY//Li95aOWjspKTfokJPNGTiLWV0nXRZeWnrSbhMCLTFgiTDikajyGazmJubw9WrV4/UTRJAyyKLighCCCGEEPIwfNZ54yBr1Edx/C8bx3WdIyMjzrNhYmICpVLJrWlk7q9DjohQTxIb63AufhbHWliqhY92TWPXXn719Pu91Ml+54dWOg1SGD3uHhHSVzoMrs4BoZVu1qPA4ic4FoYphvwYZAXupyjqNwb8lAn9vBfs38NYzX9W/NpDwg8lEgmkUikcHh4eKWO9IaxAX/6Xy2Xs7e05xaKEehK0/EDu71ar5XLaNJtN7O/vo1qtYn19HWtra9jf33f5IoJcl9Rv0Pixv+k3TkTIL+H2RAER5J4ddv5h9HsmHSd+z6cvMlREEEJIAP7oj/4If/RHf/RIj+nn5kkIIV80zp0759n+zne+49n+P//P/9N9tnkDrKWPjaHvZzGn0cez+wblZfA796BQbrasfT7XarWB5W3d9H57zbYeyWTSsz0zM+PZ/ut//a/3q/ZDs7y87NmuVque7Yd5L9k2sNeRyWTcZ79QAIO27TiybTZIge+n0H8Y/KwuBTvmbN8OK6/rba9Zwjz222/HoD2X7rsnn3zSs29qasqzff/+fc/2sDbTx7YCFz/BByHk8WV09EGy6tnZWZw9exa7u7vo9XpoNpue0Cc63BUAlEolJ+QUwaQ2itIx47XltfVe8RNSa+GiFSCL0FRbCVuLcyln0QoVG27WGoTZ7x4nms0mOp2Oy5NSrVZRqVSOhNoRQzsbYkjv1yG5tBW89jLoJ9j38zqwygQRoEuf2zEkx5D3mtTBz4uj3ztcX49fToNBYYn9xoitnwjj9VjWnh1yzZJ3Y2ZmxikE9vf3j7SPn1GjeBm02200Gg0sLy/j8PAQxWIRhULBHV+u10ZVaLfbTtFw584dHB4eYmNjA6VSCR999BHu37+PSqWCSqXizm0VO/q+t3MeG85avtPKS+shpZULIyMjiMfjGB8fRyqVciH0pKwO26aVYjJ+++X5GNSPtp+DzD/9jm0ZpuiUfb8OD8bPCqVghBBCCCGEEEIIIWQokUgE+Xwei4uLuHbtGiqVChqNhlM+SKgeEZ42m02sr69jd3cX5XIZyWTyiKDUChyt4M2GlPETzGnvb71tj9fPKtqGgRHBeT9hpz7e46qEALxC7X4eD9bS3u7zywtij/0wXhD9BLfyvc6xYIXCdiz4KUD8xptVYPUziniYsdAv8sEgtFInEokglUohk8kgGo167gF7zX5tLGO+Wq3i8PDQKQ8kyoEW1Mv1djodNJtNV35zcxMHBwfY2tpyyhDxkrDeRHI8yWkhzw2/caXr6qfY6afUESTvjs6nE6RvPmtf+h3n1+kZ8UWGighCCCGEEEIIIYQQMhARSMZiMWSzWcRiMSeg1AlydTifdruNSqWCarWKer3urI614F8Lo/2EjtaifZjgeljoJXtOP+txPyH1r1qw+EVAh/EBPhXwWkGxbm9RSomXQjabRbFYRCqVQjwed4nptfJKKyo0VkCtc3zY/AmS3F0LzoH+4Y91ncVKXn6rvRHsNfoJq+1/OU+/OmisJ4TUQSt2tAICeJDvJhQKYWlpCZlMBvfu3cPGxgbq9ToajYb7jVai2UTicuzd3V3nGaFzK0hfS16bXq+HVquFSqWCDz/8EHt7e3j77bddWKdWq4VqtYpWq+UUDNr7IZFIIJlMYmFhAb1eD2tra6jX69jd3fUoAXXSar8wUbo9df/I70KhEFKpFAqFApLJ5JFQ2v2UEja8db++Cvp9v7L2OTJMeWCff192qIgghBBCCCGEEEIIIUMRwZ9YTNvkqDp/gITvOTw8xOHhIcrlsieRNQAXCsUKCEVQ3e12j4RGkv2Cn/V0UCGgFvLpkHtBBYuPi3CwHzqXQL/4+YOEsyMjI4hGo4hEIi6XoBXWD/Jy6FenILkZ/JQDcs5+fWm/twqIhxVQDzunPcYgLwmtGJOk1clkEq1Wy+VrtCGQ/K5NH1eUC5JUemdnx+UDCYVCiEajLh+FeDFUq1VsbW1hb28PW1tb2N/fR6vVOuINpa85FAohFoshmUwil8uh1+uhVCoBeKAA8MsloT1bdHgofW1WoSTKr2g0ikQigXA4HNhToN948WtP8tkJrIgImoDl3r17gcrt7e0FKhe0o3V2+EEEjWNqY776ETQGV9B4u+l0OlC53/u93wtU7tatW4HKXb9+PVC5oElbgl5v0PYLet5BSXA0f/VXfxWoXJB2tvGQ+xH0WoOO46DHC1ou6H1m4yR+3vMSQgj54qNj/QPAb/3Wb3m2//Iv/9J9trHnh+UGsPttbgDNsHj8w/IOPIz1kcS07YetZzQa9Wzr96CdF124cMGz/cd//Mee7fn5ec/22bNnB9blYbhx44Znu16vB/7toLwBwNF6F4vFvmVtPgQ/AcGgc+n9YvXXD3usYXlLBtXLrofsfrs9qN72vHYea881bFtfVyKR8Oybnp72bNv71C9ZrGZQeIRh9woh5PFDPCJSqRTGx8eRSCSwtbXl9uv468CD50an08H+/j7u37+P+fl5F/pFY4Wk2rPiOJUC1gtCvrNhZb6qNJtNtNtt1Go19yeJx/3i7APed8XY2Bji8TiSyaTH4tzmWujnDWOxeRn08cSLQIdo0ugcCRqthHpYYbSfEkUfQ3s1aOt9v2PJdVhPCOvdoT0FEokEOp0OstksCoUCer0earWar+Kh33huNBrodDq4du0a7t+/j0Qi4TxXROkh92un00Gj0cDq6iqq1Sp2dnZcGCbdHqKUGBsbQzQaRT6fx8WLF5HNZnH27Fl0Oh1EIhEXyqnVavWV/cnxtGJDt6H0/ejoqMsLsbCwgLNnz2JiYmLguNKeMLbv/DxfPgtWafowxwqqRPsyQY8IQgghhBBCCCGEEDIUUURkMhlks1mkUilfwW4kEnGhd9rtNnZ3d3Hnzh088cQTiMViiMfjRyzNRXDbL9nu58Uvbn6/vA8SKiZobPnHFREoS5gt+dMKIi1c9VPa+ymeZN/DKCHkN8BRy3g9fqTv/DwABJufwlrVf1YG/TaI14cel3pbh2rSYYjC4TAikQhisZjzipDfWa8K2bbfd7tdtFot7O7uolqtIhKJuJBMIuCPRCKubVutFra3t9Fut51Syq/uAJwiI5FIoFgsIpfLoVgsot1uI5vNotvtOq+Fh21jqygYHR1FNBpFPB53uTPkORN0fOnjflGF/l/UegWFighCCCGEEEIIIYQQMhSJF59IJJDP55HNZp3VtgjwAXgEjN1uF6urqyiXy7h8+TK63S5SqZQLJSOCY4kLD3wqwP4sCY37McgCvZ8H3ZdZ4PeosKF8dE4G3WcSSsciigwARwT+8lkUG/0Sk9tcCX6hi2Tb9p0VwItQX+eCGHb9/RRifuPTT0DuV097DNs2Ep4M+FTBIyGZ5BokDFGxWMTCwgKq1Sq2t7eHXpOcV+f/qNfraLVa7t6T8/n9rlareZQiOr+F3MuSH2R6ehoLCwt48sknkUwmkc/n0Wg0kM/n0ev1EIvF3LNCh2qTfmy32+4Z0S8CiyTvlnwkuVwOqVTKhZayYd/kN34KqH4J2XU/Pczz4fN6U+h663H8ZX02URFBCCGEEEIIIYQQQgaiw6CEQiEkk0kXcsfPIl4LyhqNBg4PD7G/v498Pu8RgPY7l5+gLaiHxKPwpPiyCvqOE+upIsoIUSJYa3gAnu+HeQz4eTro/X5Kin75QjRaeOunCLHKFvv9MEWEPVe/Ovgd00/R5qdoAT5tUxGsh8NhtFotJJNJl0C+nyeERc4rgvdWq+UUEfJnQ0XJ+bXyUPpeX6PkBEmn0ygWi5iensbs7CxisZhTDiSTSVSrVU8OGJvg2l6z1Ed7YYlCRIeNi8fjA/OSDPN2sv0qbWhDz32WZ8TnfTZ92ZURVEQQQgghhJC+RCIRz7bNWfBHf/RH7vP/9r/9b559BwcHnm2bk8BOnq2Vk7ZIsmEfbEx9G3N/WN4lfWxbD5sXI5VKebbj8bhn29a7Vqu5zwsLC559f/iHf+jZfvXVVz3b4+Pjnu0gbvxB2djY8Gxbiy8dg7iflaFg82LYcaL7w57H5tiwvx2W30Nv29/avrQ5JOyxB+WYsLksHsat36+8rvew3GZ2/Np62zGnz1WtVj377t69O/Bctn3tuQbVdVBeF0LI40k4HEa320Wz2cTExAT29/cRi8U8Md7FklsEdqFQyOUZuH//PpLJJM6ePXsk4bWO7S8CR40WiA7KSyjntwJNP/wE2+RTxsbG0O120Wg0UKvV0Gw2XWJiEYRqZYSgwwdFo1FEo1GEw2GMjY25PytoHiQU9hsPWvmhhbv9+tsKb/sJ/mWcaUWFreMwpYk976BtOY71KrD7dBnZDofDiMfjyGQyKBQKLk+UvR79XyuI/OplLe/1filj+1vux3g8jlgshlwuh0wmg/n5eVy4cAHFYhH5fN6T3yObzaLT6SCVSiGRSKBWq7n5jw33pMeTn5JAfieJtqVths1t/TxsdDv5KTCG9fcwHuZ3w8bOlxEqIgghhBBCCCGEEELIUMQKOhaLIZvNIpPJIBKJOAGghFgR62aJPy9CvE8++QSjo6M4c+YMJicnkUqljiiV9bkAryA1iFJYWzsHsRweZhVtvTO+rJbInwUJvdRqtVCv19FoNFyoHMDbN6K00AJfCZkj1un9rN21QFijhf02PI4tI+UG0c/TRh9LKyKChuDRwumHHR9SVvJxiMDdr14APMoXMUyQnAjWiEL/3p6v372kr1/K27JWwC9tlUqlkEqlMD09jZmZGSwuLuLy5ctIJpPO2EaeB+l0Gq1WC/F4HNFo1Cm4dB1snWWMaQWFtEm73fZ4dYii07afnyLDr79sYvR+z4NfBYPG/JcNKiIIIYQQQgghhBBCSCDEyyGZTDprZhEAirB5bGzMCRbFW2J0dBQbGxtIpVJYX19HIpFAJBJBOBz2FTD7ETRck59X2mcNo2IFgF8lRYQkqa5UKjg8PESr1XLW5/1C/oigVjwfotGoCxmk8fN86We9b4+vyzxsXwQJndTpdDzKrEEKEr9jPqxyBIAnl4FuQ0F7TGgvopGREaRSKWSzWaTTaSSTSTQaDTQajSMCfb869fOcGCTs1jkrxsbGkMvlkEgkcPLkSUxOTqJYLLq/bDbrkl/r+ofDYZdcOh6PO0WX3GNaKaG9b3TbSzvopNiSG0LqJuPMrz+1gmFQfwX97rMQZBw/Tp4RVEQQQgghhBBCCCGEkKGI1bZYNE9OTuLcuXP4+OOPUa1WnWW8WMG3Wi00Gg2EQiGEQiFUq1WsrKzgL//yL51wMRKJOOtuv5BLOm68xlqv98tP8Sj5dVhD/zoRRdLh4SFKpRLq9bonfKAIw8X7Bfg0pI3kEhFBs1U62ETH1mpd9+mgMI2fJVxOv37U12NDhdnz2tA+tm5+oaT6fe+nyNChgaReYu1vQ1ul02m0221kMhkXUrRerztPAV1PG3ZKzmc9IeQ73W+6X0ZHR13IrdnZWRQKBTz55JNYWlpCJpNBJpNxigZRLOgwS/KMkFwzh4eHLnm91Nuvrroe0g7yfInH40ilUi4Bts4/ocNJaSWazW/RT/k0qL8+D/3GyeMKFRGEEEIIIaQvNlyCzZ/w8ssvu8//1//1f3n27ezsDDy2FSjYuPg6Dr7NEWEn6Xa/tf6y+/W5k8mkZ98/+Af/wLN9/vx5z7Ytb/Ml6Jj6tuzk5OTA39pcF8eJFfbYvAMamwvALprK5bJnW+cDGZbvwB7Llrc5CvTvbftZ7Pi1OSEGLfZsPex4HZQDwg+937aB7fd+cZv77dfHtrlZDg8PPdvD8qfYc+k2tPW8evXqwGMRQh5PREg4OjqKeDyO2dlZrK+vIxQKodvtOuG1FWC22200m01Uq1Vsbm5ib28PpVLJxY7vdrtHYs8DgwV/VgHxWa3k+x37cRcKDkMriyKRSKDE5NInEh4nnU5jfHz8yO/9sAoFLRi35+n3G1v3fuUHXa9NCu13rH4Ca+sp8lnC6PRTWujzSv16vR7C4TAikYjzjOh0Om4+4Hesfl4o9vq1Z4b0ZyQSQbFYRCwWw/j4OGKxGE6dOoV8Po/Z2VnkcjkXbkk8pKwCSpRUsl/ObxVA+jd+Hk86Lw0A52UhIZxsonT7p7Ht4KcUPY7nwbDx/bhBRQQhhBBCCCGEEEIICYTkfRgZGUEikcDp06dx584d3L171+UQaLfbTsGtrZyBB8rrzc1NbG1tYWJiArOzsy6Mj2ZQeB7gqABaCzL9fvNZQioFyUnxuDMyMoJYLIZkMulyPWihtSQQFqMPbTEvQuvJyUnE43GEw+G+HgZWAG6PCeDI76yAWu97WKWU9sjQY9ceVx9zmFLD1tXvGoZhFQ8S5kxfXzweR6fTQaFQwOzsLNrtNtbW1o4oHPS2Tjiu62PzYojiYHR0FLFYDKlUChcuXHDJqNPpNE6cOOFyxiQSiYFeBXK8cDjscsoAnyo4dbl+RiC6zhJGKxQKuXEquU1EIaFDM+kQTRq5fh3+ST+TBikmh/Xlw4RdCsKjVLj+qgmsiNBWTYMolUqByvVLoGKpVquBylUqlUDlhlkAPQxvv/12oHITExOByi0uLgYql81mA5X7+te/HqjcrVu3ApWzlnD9sBaH/Qj6Qg96YwU9r7XY68cHH3wwtMyZM2cCHWuQhaFGXOiG4aeZ9cNa/fUjaBsHPS8hhBBCCCGEkMcTSVY9MvIgZns6nUYikUAsFnM5Bdrttif0iYRZCYfD6HQ6qNfruH37NgBgYWHBHVf+izeWjRWvLaj9EAFtPwt28nCI8FWExzaPgfYYkPIAnBJChM1+v9Xl9bns+W05v21hUJ6DIP0/rD7DsOez49B+fhgBtm5z6ykingrpdBqFQgG7u7sIhUIeBaCtY7/wViK0l1BpEl4pGo0il8shnU5jfn4e4+PjmJycRDKZRDqdRjwed/enbTs/hU4oFEI4HEYikUAikXDn85PtWQWEHEeuTTw25dlhwzDZMRek7fVzZNg4GDbOPosS9HGFHhGEEEIIIaQvVgmdSCQ828Vi0X2emZnx7Lt+/bpne9gictD257E0Ao4aQOjryufznn1PPfWUZ/vcuXOebWtgMEhRb41vbD3tYsuGvglqaBEEa7gzqN62vW2II7uo3dzc9GyvrKy4z8PCUVnsfnuuQQYe/azbBNue9lh62xow2TYYduxBocfsPht+ymLL23rrNrL1sOHB7DgYFipLY9vgmWee6VuWEPJ4ogWCnU4H4XDYWUmn0+kjCXIl3JJOtAs8eCbu7+9ja2sLh4eHiEajSCQSRwSswMOFtqGw79EjuQBsAmDAX1Ggc0MkEgmXI0Li9VurdD9BvV+IIE0/Ya+1+gcevBd1eKF+DPJyCCq01nW3Au9Bibf71cful8Tu2mpfQqSNjY1hbm4OzWYTlUoF169fdzk9dP10uCL5va6vKI0SiQQymQzi8Tiy2Syy2SzOnz+PTCaDc+fOudwOEhZKfufn5TIyMuJRLrbbbcTjcbTbbUxOTqLVamF7e9sZDkteC6mfbTsJuyRzK2lzeY6IQkQnqgbgqaP81oahsv0axBNC+sN6k+g8G+QBVEQQQgghhBBCCCGEkKGIoFIU571eD4VCAadOnUKj0cA777yDSqWCWq12JHyPhGsaHR1Fq9XC2toaGo2G84wYHx93oXu04FRbgss5/QSDDxMuhwqLYOhY/NrLxQ/bptoLwnpCPGqPFT8FhN9x/UIRPeqx8KvwxLEW/eKxEo/HkclkXJiksbExpxzsV0/pF7k3RemUTqdRLBaRTCaRz+eRzWYxNTXlcn7E43HEYjHXz34eCPZP9us8EalUyik8IpFIoEg2OsG5nyLLJvoeZtzkpxB7GI+YQc+e43rWPOrjWmWa/InSp1qtolqtotlsolarOS+cSCSCbDbrQmMNg4oIQgghhBBCCCGEEDIQP8GihOCZnZ1Ft9vF7du30el0UK1WPR5aIyMjnvwAEl6m1Wphf38f+/v7ODg4cEqIQWF6gOMLdUILZi8i0K1WqyiXy2g0Gmi1WkeSBOs2k74RIaWf94N4vvSzQtf77T7A3wPS/sYK660HoNDPK2MQfmMzaPieIMcP4oGhP0sopUKhgHA4jMPDQ2xvb2N1dRWHh4ceJZL2fNAeC5IDZGJiApOTk5icnMTi4iLS6TRmZmaQSCQwOTnpwinJMXR9rOJJn896zYgH7OLiIsbHx7G6uopqteqeC4LkeAA+zZFhvTzkOrSXiA4LZj0UgE+9S60SQbxO/Dwx+mE9IYQvkxKi2Ww6T5Fut4tms4lOp4NKpYJ6vY4PPvgA165dw/379/HJJ58gnU5jbm4OCwsL+O53v4tEIoHz588PPRcVEYQQQgghhBBCCCFkKDZUjigiJicnEQqFkM1mUa1Wj1jUSkgfHS4FeBCabm9vD+l0Gvl83lnUiiCzXzgdLYDs9/mzMMiy/quKCCVFMOmHzQEgfSHW1PLn17b9lEqDlE3DFFFWuGzzIjyKsfJFwArjw+Gw84ooFouo1+tIpVJoNBpoNpuuH/S9JZ4Q4+PjSCQSHkVEsVj03JupVAqhUOhIrhatANDht/Q+QT87JN9MIpFwOUX88sAM6m+rRBqmBLG/67fvYcbFF2EM9cuN8zC/FyWPKJObzSZKpRKq1SrW1tZw584drKys4NatW0in005htLOzEzivMBURhBBCCCEkMDY2fS6Xc5+vXLni2ff66697tuv1umd7WGx6PZEeFG/fD1veHlu7Dr/44ouefYVCYeCxbG4Fm9dBH9u217B62Un8o7TIHJQTwp7bntcKHuyxbN6BP/mTP3GfT5486dln84w0Go2Bxx6UM8LmVrDtaa9j2DjS12nrUavVBtbTMqjv7G/9Yh8P2h5Ut1u3bnn22fa149W2mW0TfR/G43HPPps/hRDy+CNWxyLMDIVCzjo6FArh6tWrSCQSTjAlIT3EYlvnGOh0Ojg8PMRPf/pTJ+D6+te/jomJCWQyGfc+1VbXWoj5WQRvg8pKLoFB7+ovgsDxV0mz2USj0cD+/j52dnZQr9fdO0n6VHu5SP4C7UVRKpUQi8WQy+U8XjF6HNmQSVqZoennFWOFz/Y3WhEh8fwHeUIMUo74nSMID6Ns6ecJYul2uy4hdbfbRSwWQygUwtLSEqLRKO7evYtIJIJSqYS1tTWXSB54ML8aGxvD+Pg4YrEYFhYWMDExgampKUxOTiKRSCCdTjsPCMkHoxWJts375fTQ16C9qSQXRafTcfWRP7mukZEH+Wh0mLB+7aRzRMh+q8y0fWjnWFZ59VnHwbBn06Cx/bDHlGsYNjcddFwZS/V6HY1GA8vLy9jd3cXm5iYODg7w5ptv4s0330S1WsXBwQFKpRL29/ext7eH2dlZJJNJvPDCC0PPRUUEIYQQQgghhBBCCBmKn8eAKCFisRimpqZweHiI6elpHBwcoF6vo16ve6yjRVAtwtPDw0NsbW0hHA5jc3PTKTe00sLPgt1PUP15GGQ5/VX1kuh0Omi326jX66jVakcME0TQq8NtCa1WC61WC81mE61WywmWbVs+qjBbwzwktPLBLym65bjCf+njP4pj2FwRkUgEqVTKeURMT08jHo+7/hAjjkgkglAohFwuh1gshtnZWY8nRCQSccoBCbElQn0bAmtQSCxdV6v4kWeH3Ov6+MCnYZl0n/VTRAxT3gwzBvpV80XzyBFFRLPZRL1ex87ODjY3N7GxsYG9vT1sbGxgd3fX4x3VbreRTCaxsbFxxNCoH1REEEIIIYQQQgghhJCh+Hkz9no9hEIhxONxnD59GqFQCNVqFbdu3cLOzg4qlYoTVrdaLSd4k1jknU4HOzs7qFarOHHiBLrdLiYmJjxx4eVc1tPQCj0/j3BvkCdbEGv5x5FarYZqtYqdnR1sb28f8bLToX1CoZATZAIP+rfRaKBUKjlBuCgi+uWA8AulI+Ulbr9VSg0SRttjA/Aot/T3g4Tn/crY5L76uPYY/erzMOiQZ4NymaRSKRf2KJlMol6vu1wRkodB8ieIR0Q2m0UqlUIsFnOeD9K30mYSNsm2n989KJ/lmaGVCzpUVzgcRjQaRTKZxPj4OEqlEsrlMoBPc0JY75dQKOTxnJF2KJfL2N7eRqFQcM+WdrvtaSf5LEq1cDgcODzT53m+9FN8PAqProcNJWWRHBHVahXLy8vY2dnBn//5n+PmzZs4ODhAtVrF7u6uU0bKs7vX62F3dxdvvvnmEY/bflARQQghhBBCCCGEEEKGokMiybYwMjLiLKsjkQimpqZw//597O3tuXAfIrgG4ElkDMCFA2k2mxgfH8fc3BwmJiYAfKoAsYlw5bzAr87C+auihADgPBq0R4QWQEt/iDW7FhhLvHkJ7yQhkYL0k+1TLXzX33/WEEn9fud3XH1Nftb+VjnwMCGYHhY/byS/cEiRSMTjrSIKona7jXK57PK2jI6OIp1OIxqNIh6Pu3tS53mw2zZ8mfaEsf1v28Sv72X8RKNRRKNRj/JDsInv7X/53Gw2UavV0Gq13Ln9vF+0csNP8dWv7R+1EvJRHcvvOh6GXq/n7tXd3V1sbGxgeXkZH3/8sUtWLWG9tDKx2+2iXq9jfX39iJK4H1REEEIIIYSQwFjLKx2//3d/93c9+9bX1z3b/+E//AfP9jCXaR2r3satHxZXddixFxYW3OfXXnvNs69YLHq2bVx8i81hoLH1jkQinm2b48DGdn2Uix2bq+FnP/uZZ1u3ka3HsBwRNreFzg/y85//3LMvnU57tjOZzMBjD8pp0C9ppjAsR4RlUI4Iu20XXMPyluhjW4viQWWBo3ke7Lm2t7fd57ffftuzz/aN32JcY69Tj/+vf/3rnn12TBFCHn+0IFbiuOvvwuEwxsfHEY/H3bNMrOEbjYbnPSjCxlAo5ISku7u7CIfD2NjYQD6f7yv0/SopA36djI2NIRwOuzA9YhEvSgfpPxF4i0JC02g03HtMx+vvp5TwUzL5zY+sQPrz4ne8YfNNey3Drufz1s0mgPars1UiaIF8t9tFNpv1/F76VSsB+s2XrELBL1SSVkzYfbJfBN/Ag3l0r9dDMplEOp12zwit8JDjyDNFn1+uV+oi+SQikciRUE/SPlaBattw0HY/RZPdN+x4/b77dSDP3u3tbfziF7/AnTt3cPv2bezt7bnk1VqxJIiyUfIABSGwIsIuJPtx586dQOXEzWYYNqnh5y0XNIt3kAZ8//33Ax3ro48+ClRuZmYmULnz588HKmcTLfYjmUwGKhe07YJaIQxbrAmfNdlKPw4ODgKV+7f/9t8OLfPSSy8FOpZOWjmIoG0StI2DPgisUKQfj7ovCCGEEEIIIYR8udAW2KKE6HQ66HQ6Tmg9NjaGWq2GdruNmZkZjIyMoN1ue9ae1rIWeLBe7/V6uHHjBiYnJzE9PQ0AnuSz/ZQRnzc8ieaLFr/914UoGMLhsCeEjbR1KBRy30vfWK8ZnZdAt2e/8Ez9cgnIPnucoAT5bZDjBhEwHxd+wnCtpNCW8Tq3guwHPhXmy3/pY7lv/RQYNtyS3h4k5PcrK38iXwqHw+h0Oi4klCi75HhameHnEWMVRzJ+bAguG8ZpUJijhw2j9FnGZZCy/dr5UdPtdlEul7G3t4ebN2/i5s2b2N7eRqVScef280qSZ3+j0Xj0ighCCCGEEEIIIYQQQgCvNbII/bRALplMolgs4sqVK4hGo+h2u54kp4IIL8Uau9vtolQqoVarOYNIG0bl8wiipX7Dro3AebZkMhmXVNxiBZPA0bBNWvir8wZIMmI9BgbxMMLbR+mJMAytBPhVIPean6Bee1WK1wrwqTJPe7P41V2HMtIKAx3myOZ9EHS/yj2rvWjkfDo0lOSryGQymJycxL179xCNRp2XlE6EbhUx4o0TiUQQiUSQSCSQTCYRDof7jgMbasuPh+3HX6di7FHQbDaxurqKlZUVbGxsYHt7G/V63bW5n7eP3K/RaBSZTCaw4TIVEYQQQgghhBBCCCHkobBhc7T1dK/Xcwlzr169im636wTZ2gNCHyMcDjthablcdrHeRVgdRAkxSLj3q7IufpyIx+Po9XoYHx9HJpNxSYIBr+W4/q+FvFrJoC2m9TiR8eMXEulh+2lYnobPcsx+59HH+lUqIfzOJ/eH5OGwZXXOBVFE6LayXgN+3gNy3GHhJW04Jq0A0fWV7yTsTyaTQbVaRSqVQiQScWF/tIeHPrYIwnX4sFgshkQi4ZvU/jg9WY5LEfEofhOEdruN9fV1rKysYHNzE7u7ux5FhPUSkf4QRcT4+DhzRBBCCCGEkM+PzX9gFx96Iry4uOjZ9z/+j/+jZ/uTTz7xbF+/fn3gsbVF1zB3Xzv5tds2z8P3v/999/lrX/uaZ58NW2kn+zZnwaDFgA1/GDTUpRB0Uh+Ey5cve7YH1c32uw0fafvD1lOHYf2zP/szzz7bXt/61rc82/l83rNdq9X61tue144hm4PDnntQ3odhITOH9Y2ti94e1p42R4QdN4eHh57td955x31+7733BtbTL966xt4rzz77rPv8d//u3/Xss/lUCCFfPUTQKEJN/VnyB8zPz6Pb7SKfz+PnP/85dnZ2sLm5eeRYorzIZDJYWlrC9PQ0EomERxAZpD5yLPvMDxo65GHoF17ocUFyPsTjcWdp7iegFkG3DgMUCoWQTCaRy+WQzWY9IZy098ygBOSfhUdl5T6MX3f4Lml3q/jR8w2ds0PnW9BjVn+vwzFJH+myuu+1Z0u/e8CGjbKIUrLb7SIWiyGbzSKXyyGfzzthuPWykePJGAuFQojFYojH44jH44jFYgiHw0cSbOt2+yLwWcbNcY41myDcKqh0mDZR+OTzeaTTaZw+fTpwyHcqIgghhBBCCCGEEELIZ0ILx8TaWgtDE4kECoUCOp0O1tbWEIlEUKlUXJgmsWiWcoVCAQsLC8hkMh7htT0XOX6kb9LpNCqVihPyClrQLEoo+RyPx5HJZDAxMYGJiQlEo1FfpZKN5f9ZOY4k5lbZ4BeGShPEWydI2aD10t5I0vY2h4soi8QIQgvzdZlWq+U8KmwOBt3POkRTu912CkhtNa/7uV9OBkksLeccHx/H2NgYJiYmMDk5iWazib29Pd+E1xLWSRQRiUQCqVTK/YkiQocF69cPXzR+HQouCZ2l20r3NQAXAiudTiObzSKfz+P06dOe8HtBoCKCEEIIIYQQQgghhHxmrKV7t9tFq9XCyMgI4vE4pqamkM1mkU6ncefOHbRaLaytraFcLiMajSKXy2FiYgJPPPEEpqencfHiRSQSCUSjUY918zD8hIzHKdg7Di+LLxLSp4lEAul0GrFYzIXN0YmppezY2JhTVoh1eyqVQjwed8JjK+wMEnLrUV3Lo/yNrfPDjLPjulY/r5JBShOr5LNheGyCYq2QsF4Tftflp0S0Hg46abUOrxSNRjE2NuYUHnJeUUSIx000GnXPl3w+j/HxcUSj0SPhp3QIsC+CQnOQ586vWlkyNjaGQqGAWq2G+fl59Ho9HBwcoNFooF6vo9lsIpFIYHx8HDMzMzh9+jSy2axTGM/MzBzxGO8HFRGEEEIIIYQQQggh5HMjAmodokcS0/Z6PeTzeXS7XTzzzDP48MMPsbu7i1QqhYWFBZw5cwazs7NIp9NIp9NO2DhICWGt4K2wU39HPhtjY2PI5/MYHR3F+Pg4EokEWq2Wi98vjI6OIhaLIZPJIJFIOCHlxMQE0um0R7Bsw+Y8CoXOr6qfRQGjkXHvVw+bR+NRKq/seNf3ihbE23vST/mjE87b3/gpGvtdh/7er2+tIkIUWxIaMp1OI5fLYWtrC5FIxHldaA8LUYhJaKDLly+jWCzi9OnTmJiYQCgU8vTJoETo/YT+DzOeHrWy81f9zIrFYjhz5gyy2Szu3r2Lqakp3L59G/v7+9ja2kKpVEKhUMDc3ByeeeYZfOc730EqlUI+n3dJwpmsmhBCCCGEPHLsxFjnU7Dx+BcWFjzb//P//D97tv/yL//Ss63j3APAvXv33Gcbbz+dTnu2bcz9CxcueLZfeuklz/Yf/MEfuM+FQsGzLxaL4VExLD71oDwCj5rp6WnPtu2fu3fv9q2HtXKy++0iTi9GXn/9dc8+3a9+v3311VcH1lv3ta2HXQQ97P5BFmi27+yYs78dlK/C5r2wx2o0Gn1/CwA3btzwbL/55pvus80nYe+VarU6sN52XPyDf/AP3OelpSXPPgr3CCEWbT0tSght+ZxIJJDL5bC4uIidnR0XkmVubg5nz55FJpNBNBp1YXxEcP0o6wc8msTIXwVE8BuNRhGPx11Yllqt5t5V3W4X4XAY4XAY8XjceUEUi0Wk02nE43FEIhHfPBBfFOv0z8ujEloPCy9llRr9PBH85jM2ZNMwtKLIz9MB+DQUmx9+HhO2rnoMhEIhhMNhlydGPHDa7bYbh5FIxIUKi8VimJmZcWOtWCw6zxtJYj3I62AYDxPq69fhxfAoEeVOKpXC7OwsRkdH0W63kUgk0Gg00Gg0kM1mMT09jYmJCWSzWSQSCSSTSZejI2hbURFBCCGEEEIIIYQQQobSz6o46H7h4sWL+M3f/M1HUSVyjEhy2kwmg0gk4pLS7u3toVwuo1aroVqtIhKJIB6PY2JiAhcvXkQmk8HJkycRi8WcsFKH2Bok5P6i00/oL9+L8s2WFwOFfp4R2tOgnxeB5FPwC6fk5wnhVz/7G7/cFfK97iu9X9/n2nPCekRZxaRGKzFGR0edEmFmZgYjIyOoVCrY29tDs9lErVZDJBJBKpVCMpnE3Nwc0uk0zpw548IFSTgnrYjodz1+2PbTvwmC37j4soztsbEx5HI5xONxfOMb30C5XMb169extbWFUCiEdruNs2fP4qWXXsLi4iJmZ2ddbg7xNgnq6UNFBCGEEEIIIYQQQgghxIN4tYyNjWFsbAyhUMhZpUsoH/kTD5ZIJOL580sY/LjzWYTQwyzq++V6eFgetZV/P4UGMPia/LwsxHNKPGxk7Mj4k++j0ajLJRGPxxGNRt1Ye5w8bX6V6CTz3W7Xta0oEKXNJcSazvnyMMnmR3oBR/E//sf/ONAB/82/+TeByh0cHAQqF9Q9fWdnJ1C5oA3zKB+S1tW6H0HrFjQTeSKRCFSuUqkEKmddxPsR9MEYtI2DtkvQ8wY93vj4+NAyf//v//1Ax/rBD34QqFw+nw9ULmgSmKBj4FHfF0GtYAghhHzxsWFe7HxAz9Xs+6Rer3u27ZzDbm9vb3u2dbiZra0tz77z588PrOfVq1c92xMTE57tTCbjPtv3m51r2f32XH6WZP2OZRkWzsfOI1Op1MDjDWJ5edmz/Sd/8iee7f/lf/lf3Gd7jcPe7TZ0kJ6r2GPZ9jx58qRn+4UXXvBs//Zv/7ZnW4dqknjC/bZtKKZIJOLZHjQPttc07Fi2r+x16/F9+/Ztz77NzU3P9sbGhme7VCp5tm0Ys/X1dffZ3oe27+wYKxaLnm07b/293/s999mGLbPbNgwUIYQQQgghwldLJUkIIYQQQgghhBBCCCGEkF8pVEQQQgghhBBCCCGEEEIIIeTYoCKCEEIIIYQQQgghhBBCCCHHBgO5E0IIIYSQvtg4+HZ7EEHyLQ3im9/85uf6/XHxMG3wRcLmq3jmmWc824uLi+7zxx9/7Nk3LGeEzZ+g80AMy8Fh8x/86Z/+qWf7gw8+8GzPz8+7zzZXyMWLFz3b2Wx2YD13d3c92/o6bf4DW0+bd8TmlLhx44Zn+xe/+IX7fPPmzb7nBYDDw8OB9bblNfa+s7nF5ubmPNt/7a/9Nc/2t7/9bc+2zrth+862ESGEEEIIIf2gRwQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjgzkiCCGEEEII+Qpg8zrMzMx4tr/1rW+5z7du3fLs63Q6nu1GozHwXO12u+8+m2Oj2+0OPPZ7773n2b5+/br7/JOf/MSzb3JycmC9bBvU63XPtq63zctg62VzRBwcHHi2bU4JfZ02x4NtE5tvwtbTtlkymXSf8/m8Z98LL7zg2f7e977n2V5aWvJsD8oDYfN92HoQQgghhBDSD3pEEEIIIYQQQgghhBBCCCHk2AjsEXHt2rVA5XZ2dgKVG2ZFJVirpX5Y65x+BLXasVZIfljLsH70er1A5UZGRh7p8azlVD+stVc/gl5v0L4YZCmnCYfDgcoFHStBx0C5XB5a5l/+y38Z6FgXL14MVO7JJ58MVC6VSgUqF7SNg449bRE3iKD1I4QQQgghhBBCCCGEPP7QI4IQQgghhBBCCCGEEEIIIccGc0QQQgghhBDyFcB6rWYyGc/2b/zGb7jP/+2//TfPPp2XATjqPWy9MLUHqvVGtfkRhuUdsPu1N2+lUvHss7ktHjaHwSBPYVsP6wmu8zQAR69Tt5mtl/V4ttu2XtZj+OzZs+7zH//xH3v2WY/bqakpz3Y8HkdQrIe03bb5JQghhBBCCBHoEUEIIYQQQgghhBBCCCGEkGODighCCCGEEEIIIYQQQgghhBwbVEQQQgghhBBCCCGEEEIIIeTYYI4IQgghhBBCvgIMi98/Pz/vPv/Df/gPPft+/OMfe7Z/+ctferbfe+89z7bOHWDzHVSrVc/2oLwMfr/XuRZsjgKbx2FY7oWRkRHPts51EYlEBh7b5sWw+SpsHgd9LnusUCjUtyxwtI1eeuklz/bv/d7vuc9PPfWUZ18ikRh4Lpuvwu7/rGUJIYQQQgjR0COCEEIIIYQQQgghhBBCCCHHBhURhBBCCCGEEEIIIYQQQgg5NqiIIIQQQgghhBBCCCGEEELIsRE4qOf29vYjPXGtVgtUzsZ9/bzlhsWgfZjj2dit/bDxYfuh490Owsa27UfQa33UBL2OoDzq67AxefsRZAxsbW0FOta/+Bf/IlC5J598MlC5iYmJQOXS6XSgckHH1Llz5wKVe+WVVwKVI4QQQsivDpsjws519P6zZ8969p06dcqzbfMQ/JN/8k8823fv3nWf7ZzZnndY3gG7X//eHntYjghb3h5b/97W085x7bHsueyxc7kc+mHzTaRSKc/21atXPdv/w//wP3i29dzQzv9srgvLsHoPmjsHnVcTQgghhBDCmSMhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsBA7NRAghhBBCCPnyYsPoxGIxz7YOh2nDOFmeffZZz/b/9D/9T57tH/7wh+7z22+/7dm3vr7u2bahgIaFBmo0Gn3rNSwUUzwe92zX6/XAx7LYY9n2nJyc9Gy/+OKL7rMNdVUqlTzbNhzmhQsXPNuZTGbguTU27JMNG2v7utlserZ1+w/rK0IIIYQQQvpBjwhCCCGEEEIIIYQQQgghhBwbVEQQQgghhBBCCCGEEEIIIeTYoCKCEEIIIYQQQgghhBBCCCHHBnNEEEIIIYQQ8hXE5k/QOSJs/gObp0GXBYDXXnvNs61zSKyurnr2/fKXv/Rsr62tebZv3brl2Z6YmPBsX7t2zX3udDqefTbXgq23zdswOzvr2f7kk0/c50Kh4Nk3PT098FgnTpzwbJ8+fdqzPTMz4z7bHA/JZNKzHYlEPNu2vS0674O9ZpvzwWL3h0Khvtt2HyGEEEIIIUGhRwQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsBPatHeYO7A4Y0F1Xuw8PotVqBSoXFOu+3Y9erze0TNBrsO7R/QjaxkGPF5Qg1/ow5aybfz+C9kW73Q5ULmj7BSXI2Atat7/4i78IVO7HP/5xoHJBx0A0Gg1ULmjffve73w1U7pVXXglUjhBCCCGEEEIIIYQQ8vjDIJ+EEEIIIYR8BRgU+/9hicVinu1sNtu37MWLFz3b3/72tz/zecnDY/NNEEIIIYQQ8uuAoZkIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLERClqw0WgEKhcOhwOV63Q6j/R4kUgkULlyuRyoXBDq9XqgcqOjwfQ9QcuNjIz8Wo4Xi8UClQvaLr1eL1C5oPXrdruBygVtl7GxsUd2zmazGahcu90OVC4UCnbrVqvVQOVarVagcv/lv/yXQOUIIYQQQgghhBBCCCFEoEcEIYQQQgghhBBCCCGEEEKODSoiCCGEEEIIIYQQQgghhBBybFARQQghhBBCCCGEEEIIIYSQY4OKCEIIIYQQQgghhBBCCCGEHBtURBBCCCGEEEIIIYQQQggh5NigIoIQQgghhBBCCCGEEEIIIccGFRGEEEIIIYQQQgghhBBCCDk2qIgghBBCCCGEEEIIIYQQQsixQUUEIYQQQgghhBBCCCGEEEKOjVDQghcuXAhUbnV1NVC5aDQaqFy73Q5ULh6PByrXarUClavX60PL9Hq9QMcKWi4onU7nkZYLStA+C4fDgcp1u91A5UZHg+nLgvZt0P4YGRkZWiYUCnYLPeprDVI3IPgYCHreRz2mCCGEEEIIIYQQQgghjz/0iCCEEEIIIYQQQgghhBBCyLFBRQQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLERClqw0+kEKjcyMhKo3Pj4eKByzWYzULl2ux2oXLfbDVQuyHVEo9FAxxodDabv6fV6gcoFvdagjI2NBSrXarUe6XmDjpVHfb1B2zlIuwS9hqDjLuhYCXo/BiUWiwUq9/zzzz/S8xJCCCGEEEIIIYQQQh5/6BFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLFBRQQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjIxS04OrqaqBy1Wr1M1fGj9HRYLqSTqfzSM87NjY2tEzQuj1qgtQNAFqtVqByQdsu6PUGLTcyMhKo3KPu26AEqV/Qvuj1ep+3Op/pePl8PlC5v/7X/3qgcr//+78fqBwhhBBCCCGEEEIIIYQI9IgghBBCCCGEEEIIIYQQQsixQUUEIYQQQgghhBBCCCGEEEKODSoiCCGEEEIIIYQQQgghhBBybFARQQghhBBCCCGEEEIIIYSQY4OKCEIIIYQQQgghhBBCCCGEHBtURBBCCCGEEEIIIYQQQggh5NigIoIQQgghhBBCCCGEEEIIIccGFRGEEEIIIYQQQgghhBBCCDk2qIgghBBCCCGEEEIIIYQQQsixEQpasFQqBTtgKPAhA5FIJAKVazabgcoFrV+9Xh9aZmRkJNCx2u12oHLdbjdQuUgkEqhc0Pr1er1HerzR0WD6rU6nE6jc2NhYoHKPmiDXG/Rag/ZZq9UKVC4oMzMzgcp9+9vfDlRuaWnp81SHEEIIIYQQQgghhBDyFYQeEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLFBRQQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTZCQQtWKpVA5WKxWKByxWIxULnvf//7gcp9/PHHgcr92Z/9WaByGxsbQ8u02+1AxwpKOBwOVG5kZCRQudHRYHqmoH0WCgUbLs1mM1C5brcbqNzY2FigckGvN+h5g7Rz0DZ5lOcEgE6nE6jcyspKoHI/+9nPApW7fPlyoHKEEEIIIYQQQgghhBAi0COCEEIIIYQQQgghhBBCCCHHBhURhBBCCCGEEEIIIYQQQgg5NqiIIIQQQgghhBBCCCGEEELIsUFFBCGEEEIIIYQQQgghhBBCjg0qIgghhBBCCCGEEEIIIYQQcmxQEUEIIYQQQgghhBBCCCGEkGODighCCCGEEEIIIYQQQgghhBwbVEQQQgghhBBCCCGEEEIIIeTYoCKCEEIIIYQQQgghhBBCCCHHRihowWQyGajcyMhIoHLRaDRQuRMnTgQq98ILLwQqNzk5Gajc//6//+9Dy+zs7AQ6Vq/XC1QuKJ1OJ1C5SCQSqFwoFGwYtNvtQOVGRx+tfito+3W73UDlgo7RsbGxoWVqtVqgYwVtk6DXGvQaDg8PA5X7//6//y9Que9///uByp06dSpQOUIIIYQQQgghhBBCyOMPPSIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLFBRQQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJshIIWjMVigcqNjY0FKnfx4sVA5c6cOROoXCaTCVTu93//9wOV29/fH1rmX/2rfxXoWKVSKVC5drsdqNzoaDD9UbPZDFSu1+s90nKdTidQuaCMjIwEKhe0XYLS7XYfSRkgeJsEvYagbdJqtQKVu3379iMt98ILLwQqRwghhBBCCCGEEEIIefyhRwQhhBBCCCGEEEIIIYQQQo4NKiIIIYQQQgghhBBCCCGEEHJsUBFBCCGEEEIIIYQQQgghhJBjg4oIQgghhBBCCCGEEEIIIYQcG1REEEIIIYQQQgghhBBCCCHk2KAighBCCCGEEEIIIYQQQgghxwYVEYQQQgghhBBCCCGEEEIIOTaoiCCEEEIIIYQQQgghhBBCyLFBRQQhhBBCCCGEEEIIIYQQQo6NUNCC4XA4ULloNBqo3BNPPBGoXKFQCFQuaP1CoWCX/IMf/GBomZ2dnUDH+tM//dNA5er1eqByo6PB9EdB26Tdbj/S4/V6vUDlut1uoHJBr3dsbCxQuaD1CzJWHvW1Psq6AUCr1QpULujYe/PNNwOV+5t/828GKkcIIYQQQgghhBBCCHn8oUcEIYQQQgghhBBCCCGEEEKODSoiCCG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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 5, figsize=(20, 10))\n", + "for ax, (path, label) in zip(axes, zip(image_paths[:5], image_texts[:5])):\n", + " image = plt.imread(path)\n", + " ax.imshow(image, cmap='gray')\n", + " ax.set_title(label)\n", + " ax.axis('off')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The presence of \".\", \",\", \"of\", \"to\", \"and\", \"a\", \"in\", \"is\", \"=\", as the top words is indicative of common English language usage, particularly in written text where these words and symbols are frequently used for basic sentence structure and meaning.\n", + "\n", + "The right-skewed distribution of word lengths suggests that while most words are relatively short, there's a long tail of longer words. This is typical of many natural language datasets, where a large number of unique words are used infrequently, contributing to a long tail in the distribution. For handwriting recognition, this implies that your model needs to handle a wide range of word lengths, from short to very long words, which can be challenging in terms of both recognizing the individual characters and understanding the spatial relationships between them in longer words." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(['iam_words/words/a01\\\\a01-117\\\\a01-117-05-02.png'], 1)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "corrupt_images = []\n", + "\n", + "for path in image_paths:\n", + " try:\n", + " img = cv2.cvtColor(cv2.imread(path), cv2.COLOR_BGR2GRAY)\n", + " except:\n", + " corrupt_images.append(path)\n", + "\n", + "corrupt_images, len(corrupt_images)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "for path in corrupt_images:\n", + " \n", + " corrupt_index = image_paths.index(path)\n", + " del image_paths[corrupt_index]\n", + " del image_texts[corrupt_index]\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['!', '\"', '#', \"'\", '(', ')', '*', ',', '-', '.', '/', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', ':', ';', '?', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']\n" + ] + } + ], + "source": [ + "\n", + "### get vocabulary for the current dataset\n", + "vocab = set(\"\".join(map(str, image_texts)))\n", + "print(sorted(vocab))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "19" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "max_label_len = max([len(str(text)) for text in image_texts])\n", + "max_label_len" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "maximum label length among your images' text labels is 19 characters. This information is crucial for several reasons:\n", + "\n", + "Model Input and Output: Knowing the maximum label length helps in defining the architecture of your neural network, especially the output dimensions of your model. For a handwriting recognition model, especially one based on a sequence-to-sequence framework like CTC (Connectionist Temporal Classification), you need to ensure that the model can handle sequences of this length.\n", + "\n", + "Padding Sequences: When training your model, you'll likely need to pad the sequences to ensure that all of them have the same length. This is important for batching purposes, as deep learning models require inputs to be of a uniform size. Knowing the maximum label length allows you to apply the correct amount of padding to each sequence.\n", + "\n", + "Performance Considerations: The maximum label length might also have implications for your model's performance. Longer sequences can be more challenging to predict accurately due to the increased possibilities for errors and the dependence on longer-term dependencies between characters. You might need to consider model architectures that are particularly good at capturing these dependencies, such as RNNs with LSTM or GRU layers." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([24, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76, 76,\n", + " 76, 76])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "char_list = sorted(vocab)\n", + "\n", + "def encode_to_labels(txt):\n", + " # encoding each output word into digits\n", + " dig_lst = []\n", + " \n", + " for index, char in enumerate(txt):\n", + " try:\n", + " dig_lst.append(char_list.index(char))\n", + " except:\n", + " print(char)\n", + " \n", + " return pad_sequences([dig_lst], maxlen=max_label_len, padding='post', value=len(char_list))[0]\n", + "\n", + "padded_image_texts = list(map(encode_to_labels, image_texts))\n", + "\n", + "padded_image_texts[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This step is essential for a few reasons:\n", + "\n", + "Numerical Representation: Deep learning models work with numerical data, so converting your textual data into a numerical format is a necessary preprocessing step. Your choice of encoding each character to its index in a sorted list of all characters (char_list) is a common and effective approach.\n", + "\n", + "Sequence Padding: By padding the sequences, you ensure that all your input data to the model has a uniform shape. This is crucial for batching and processing through your neural network layers, which require consistent input dimensions. You've chosen 'post' padding, which adds any necessary padding at the end of the sequences, ensuring that the beginning of each text (where the actual data is) aligns.\n", + "\n", + "Handling Unknown Characters: Your try-except block within the encode_to_labels function is a good practice for handling characters that might not be present in your char_list. If you encounter such a character, your current setup will silently ignore it. Depending on your application, you might want to log these instances or add a special token to your char_list to represent unknown characters.\n", + "\n", + "Preparation for Model Training: This encoding and padding process prepares your dataset for model training, specifically for models that rely on a fixed input size, such as Convolutional Neural Networks (CNNs) combined with Recurrent Neural Networks (RNNs) for sequence prediction tasks like handwriting recognition.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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n8x3n++yzz+qhhx5SLBbTu971Lm3dulVHjhzR3/3d3+njH/+4W/ZDDz2k/v5+/cZv/IZisZg+/elP65FHHtFXv/pVPfDAA5Kko0eP6v/5f/4fvfnNb9a2bds0NTWlT3/603r1q1+tvXv3av369ZKkP/3TP9Uv//Iv6yd/8if13ve+V6VSSc8++6yeeOIJvfWtb9Wb3vQmHTx4UP/tv/03/eEf/qG7wLOanB//+Mf1oQ99SG95y1v0zne+UzMzM/rjP/5jPfzww3r66adbSjnNzc3pDW94gx599FG97W1vc2MCAQAAAAAAXC4kIm5Qf/3Xf62f+7mf07/+1//aPVYqlbS4uHjR81xYWND//t//Wx/96Ef14Q9/2D1+6NChS1lVSedqzb3uda/T6173Ov3BH/yBPvGJT+i3fuu39Nhjj+mf/JN/csnzB3BtuOeee1yr/meeeUb/9J/+U73zne/Un/7pn0qS66Hwr/7Vv9Jjjz2m17zmNaue93vf+15t3rxZTz75pBKJhJvfgw8+qH/xL/7FeYmI4eFh/e///b9XTHa+5z3vUbPZ1FNPPaXNmze7x3//93/fTX/wgx9UtVrVN77xDW3fvl2S9LM/+7PatWuXfuM3fkNf/epXJUl33XWXDh482FKC7md+5md022236T//5/+sD33oQ5Kkv//7v9fu3bv1P/7H/2i7Tnfffbde8pKX6L/9t/+mN77xjdq6dat77vjx4/rIRz6ij33sYy29G970pjfp3nvv1ac+9amWxycnJ/Uf/sN/WHVXWuB6UKlU3PSRI0danvvmN7/ppr/2ta+1fX+wPJmfoDtz5kzb9xQKBTcd7CVqZSyDKNMEAAAA4GZBaaYbVHd393ndrv74j/9Y9Xr9kuYp6bz5/tEf/dFFz1M6V6okaM+ePZJ00eVZAFybfumXfslN/6//9b8kSb/6q7/a8ppf+7Vfk3QuGL9a8/Pz+sd//Ee95S1vUTab1ezsrGZnZzU3N6cf/MEf1KFDh86rGf8Lv/ALKyYhZmZm9LWvfU0///M/35KEkKRIJCJJqtfr+vKXv6w3vvGNLgkhSevWrdNb3/pWfeMb39DS0pIkKZFIuCREvV7X3Nyc0um0du3apaeeesq9d3BwUKdOndKTTz656m1g/uZv/kaNRkNvectb3HaYnZ3V2rVrtXPnTj322GMtr08kEnrHO95xwcsBAAAAAABYLXpE3KB+9Ed/VH/xF3+hgYEB3XHHHfr2t7+tf/iHf2gZYPFC9ff36+GHH9YnP/lJVatVbdiwQV/+8pd17NixS1rX3/md39HXvvY1/ciP/Ii2bNmi6elpfepTn9LGjRv14IMPXtK8AVxb/HFijh8/rq6uLt1yyy0tr1m7dq0GBwd1/PjxVc/38OHDajab+tCHPuR6FQRNT0+3tD7216VSqZyXFB0bG9PRo0clSXfeeWfHZc/MzKhQKGjXrl3nPXf77ber0Wjo5MmT2r17txqNhv7Nv/k3+tSnPqVjx461JIf98/O/+Bf/Qv/wD/+gl73sZbrlllv0+te/Xm9961v1qle9aoUtca6XWrPZ1M6dO9s+H4vFWv7esGFDy0C8AAAAAAAAlxuJiBvUv/k3/0bd3d36y7/8S5VKJb3qVa/SP/zDP+gHf/AHL2m+n/vc5/Se97xH/+7f/Ts1m029/vWv1xe/+EVX1/xi/PiP/7gmJib0Z3/2Z5qdndXo6Khe/epX66Mf/agGBgYuaX0BXFvajRNjPQsuhY1R8773va/jeS6Y8PDX5Vvf+tZ5ZaAuNcnazic+8Ql96EMf0s///M/rd3/3dzU8PKyuri79yq/8Sss4O7fffrsOHDig//k//6e+9KUv6fOf/7w+9alP6cMf/rA++tGPLruMRqOhSCSiL37xi217fKTT6Za/230nwPXI7/X0pS99yU1/73vfa3nd5OSkm/aTgblczk0HSzP556lOA/359u7d2/J3sVh00y996UvbvocyTcC16VLG17sW5i9Js7Ozoc5/amoq1Pn759CwBM/7l9umTZtCnb90rgRqmKLR6z98VKvVrvYqAMBN7fr/JUFbg4OD+rM/+7PzHp+YmGj5e+vWrW1vqB955JG2j2/YsEF/8zd/c97jwde+/e1v19vf/vZll21e+9rX6rWvfW3b5wDcuLZs2aJGo6FDhw7p9ttvd49PTU1pcXFRW7ZsWfW8rCRSLBa7qHFl7rnnHn3lK19peWzt2rXq7e2VJD3//PMd3zs2Nqaenh4dOHDgvOf279+vrq4ud/P513/913rNa16j//yf/3PL6xYXF92A06a3t1c/9VM/pZ/6qZ9SpVLRm970Jn384x/X+9//fiWTyY4JnB07dqjZbGrbtm269dZbV/7wAAAAAAAAISMRAQC4Kn74h39YH/jAB/RHf/RH+vSnP+0e/4M/+ANJ0o/8yI+sel5r1qzRI488ok9/+tN6z3veo3Xr1rU8PzMzo7GxsY7vHxoaapvASCaTevjhh/Vnf/Zn+tVf/dWWcSKazaYikYi6u7v1+te/Xn/7t3+riYkJN3D01NSUPve5z+nBBx9Uf3+/pPbj9/yP//E/dPr06ZYeG3Nzcy2lmuLxuO644w598YtfVLVaVTKZdEmSxcXFlvm96U1v0vvf/3599KMf1Wc/+9nzWnLPz89fUpk+AAAAADeHWq3WtpGq3WM0m033vP+YTa+293twGf7f7eYRiUTcsjsta7lerP77g+ter9dVr9dVLBY1Pz+vgwcP6syZM1pcXFShUFCpVHL3YDafRCKhHTt26M1vfrMGBgYUjUYViUQueDu0W+8L3YarfX2j0VCj0XD3qP762vxsnjbO4cVYbv8JvqZdL+QLraBwse8Ly7W6PkEXs37BeQXLQLdDIgIAcFXcc889+rmf+zn9x//4H7W4uKhXv/rV+s53vqP/8l/+i974xjeeVyppJf/u3/07Pfjgg7rrrrv0C7/wC9q+fbumpqb07W9/W6dOndIzzzxzUev5b//tv9WDDz6ol7zkJXrXu96lbdu2aWJiQn//93+v73//+5Kkj33sY/rKV76iBx98UO9+97sVjUb16U9/WuVyWZ/85CfdvH70R39Uv/M7v6N3vOMdeuUrX6nnnntOf/mXf9kyyLUkvf71r9fatWv1qle9SuPj49q3b5/+5E/+RD/yIz+ivr4+SdJ9990nSfqt3/otPfroo4rFYvqxH/sx7dixQx/72Mf0/ve/XxMTE3rjG9+ovr4+HTt2TF/4whf0rne9S+973/sualsAAAAAuHn4QVQ/6NguUdAuwOknClZT3jI4z9Uuo9P7VjNfP+DeaDRUrVa1tLSkyclJHT9+XCdOnFA2m9XS0pIqlYoqlYor6ZlMJhWNRhWNRjUyMuICsf7nXkmn9V/u/ReyLTtZTaKk3eOrSSys9rkLeQ0ur6u1zUlEAACumv/0n/6Ttm/frs985jP6whe+oLVr1+r973+/PvKRj1zwvO644w5997vf1Uc/+lF95jOf0dzcnNasWaN7771XH/7why96He+55x49/vjj+tCHPqR//+//vUqlkrZs2aK3vOUt7jW7d+/W17/+db3//e/X7/3e76nRaOiBBx7QZz/7WT3wwAPudR/4wAeUz+f1uc99Tn/1V3+ll7zkJfr7v/97/eZv/mbLMn/xF39Rf/mXf6k/+IM/UC6X08aNG/XLv/zL+uAHP+he89KXvlS/+7u/q//wH/6DvvSlL6nRaOjYsWPq7e3Vb/7mb+rWW2/VH/7hH7oxJTZt2qTXv/71+vEf//GL3hbAtcYfy8Uvr+aPCxEcK+W2225z035JNUvySdK9997bcZlnz55104VCwU37NczL5XLLew4dOuSm8/m8m/Z7WQEAAFxrLiSgbmPVLdczoVNiolMA3l7j/+8nRSKRiFvuaoLz7Xpe2D9LQmSzWZ05c0bHjh3T0aNHNT8/r2azqVKppGq1qmq1qlqtpnq9rt7eXg0MDGjdunXatWuXkslkS++BlQL5lzMYfKHzst79/nqtZt1W28L/UnoCXEoPiWstqXG51udCE0CdrHT8Xcy8Lug9zcuRRgMAAACusE6JiO985ztuOpiI8BMO7cZ2kVafiBgYGHDTyyUi/HVYv369m/7Zn/1ZN71t27aOywRw9Rw5ciTU+V+JwXM7nesul2984xuhzt9PLocl7MDVlRis+id+4idCnf8dd9wR6vyvxGDYYQ8OH+zlfCOoVCqrOj6azaZqtZq6urrU1dXVMRnRbDZbAvUXkujotFz73/7ZdVe7IHa799brddVqNZXLZWUyGU1MTLgERC6X09zcnJaWllSr1VSr1VStVlWv15VKpXTrrbfqzjvv1F133aUtW7YomUy6+XcqZ7RSqat2rkRwPViqqtM6rTZB0SlxsJqEwoUkIi50m4WVCArb5UpEXMh8LrRM2GrO4/SIAAAAAAAAAHCelQLH9nx3d3fbcQbq9XpLgsB6MHSap/+elRIbwfXzg/+W6LX3B99TqVRc74Z8Pq+ZmRl9+9vf1r59+1SpVNxrs9msGo2GyuWyG1Ohv79fd9xxh1772tdqy5Yt6u/vbwnCXk8B7qDred0t2diuZ871brW9fq51JCIAAABw3Thx4oSb/vznP++m9+/f76YHBwfddE9PT8v7bfD44HN79uxx08sN6D43N+em/d4Rfo8Iv6dGcJ39m9Tp6Wk3TY8IAABwLQqWQ+rEkgB+LwULDK9msGN//jZItiUXotGourq6zpu3teK3hIU/L7/kUr1ed+viD0RdLpeVz+c1OzuriYkJPf3008pkMue1mo9Go+ru7lY6ndbo6KhuueUWvfKVr9SGDRuUTqfd8/Z6f7sFrdRTw15zoaWmLkfgfbW9X1bz2ktZn5W2WyeXMqj2alzt3hQX8v34A5CvtC9drt4Wq3FTJyIsw9qpXl27L8uypgcPHtQTTzyho0ePql6vq1KpaM2aNbr11lv18MMPa2ho6LxSAMEd4EK6IXX6u50rfTBcaFedleZzuboEXSzL4gMAAAAAANysarVa294LfnymXQKg3evt8WBCwf/nx80ajYZ7rSUT/Pf4j3V3d6u7u9u93sooWSklG9OhVCopm81qfn5eU1NTqlQqKpVKymQymp6e1sLCgorFYstnjsViGhoaUk9Pj9auXatt27bplltu0aZNm9Tb26toNLpiOaJOOg3KfSHz8LfxxbxvueWtNAD55VrOpbiQ+QWD9DeaTmOqLMcfsH25/XE1y12NmzoREeSf9Do932w2lc/nNTExodOnTyubzSoWi6nZbGpqakr1el333HOPhoaGWt7XabCaTsH1djtCcOAf/7l2636pJ6HVutLdg27EkwUAAAAAAMC1JJvNqru7u2X8BYtvWckj/zE/4eC/z56zREGwx0KwpI4lDizBYANJ2+trtZoqlYpLlMTjcddrwhoLF4tF969er6tcLmtpaUkLCwuanZ3V3NycG4DaXm/lmizu1N3drd7eXm3atElr1qzR1q1bdcstt2j9+vWKx+MtZaP8GNxqAsBXKmZ3qTollq7UerfrhbBcz4Qwt+u1/l11cqGx4jA/502fiAhmXZd7nXRu8MEzZ85ocnJS2WxWuVxO9Xpdvb29ymQy6urqcoPYtBsgx5/XarvL2Im2UCioWCyqp6dH0Wi0peuX/9rVDhyz0mddzWsv9HVhzeN6OYEDAICVnT59uuNzBw8edNN+OabJyUk3nUgkOr7/1ltvddMPPfSQm/ZLJg0PD3d8/y233OKm/frB3/zmN9uul9R6beWXaTp06JCbfuCBBzouEwAA4Go4ePCgurq6XBIglUopkUiop6dHqVTKBeMTiYTq9bqLbUUiEVWr1ZbySZIUj8clqaVcks07Fou5REKhUFC1WnXJBYuJNZtNVatVZbNZTU9Pq16vq6urSz09PUomk4pGoyoWi6pWq5qbm9Pi4qJyuZy6u7s1NzenYrHoyj5Z/K5cLrtkRLlcVnd3t8rlsprNpnp6erRx40Y99NBD2rBhg4aGhpROp5VKpVzyxRIpy7Usvx50Ks+zmlby7arJdHrtapcdhuXGJrlU10JccjVJsE5lr65UL5ebPhHhW6nsUa1WUzab1ZkzZ5TP591ri8WiSqWSisWi1q5dq6NHj2p8fFzj4+Nt69T508EeDv56mHq9runpaR05ckSLi4saHh7W4OCg6wbmZ2AvpRvXalwLB5a5ltYFAAAAAADgRvLtb39bsVhMlUpFuVxOuVxOzWZTQ0NDGhoaUl9fn2KxmLZs2aJYLOYC+AMDA4pGoyoUCi7uZcH6aDSqarWqcrnsyiIlEgn19vYqEokom82qWCy6Ribd3d2q1+s6duyY8vm8uru7ValUNDc3p2g0qlQqpWQyqVQqpZ6eHuXzeVeGSTrX2GRhYUHlctklEKxcU19fn+LxuAvgWiKkXq8rGo0qnU7rtttu07Zt2zQ4OKhkMumSKZZ4kV4sN2UNW65k1RBzrSRALvazE+O7Odz0iYhOZZLa9ZSoVqsqFosqFAouuRCNRjU4OKi5uTklEglVq1UdPXpUW7Zs0cjIiKLRqOtOFizP1G4QFTuR+ZnVTCajJ598UkeOHFGtVlNvb6+GhoZUr9e1Y8cO9fT0nHegWtbZ7zHR6bNebA2wK201Y0dw4gIAAAAAALh0mUxGqVTK9VzI5XLKZrM6e/asent7lUwmVavVNDIyouHhYZVKJVUqFfX09EiSSqWSi89YNRFLJBSLReVyORWLRfX19SmZTCoSiahcLisWi2lxcdElBUqlkmZnZ91Yr7Y+Vhqqp6fH9aiwpEB3d7disZgktcTHuru7lUgkXMwvnU6rVqtpcXFRhUJB0rmeG4lEQgMDA64Mkz9gtp9Y8ZMRZjUxqYsdA8J/r19Z5WqPF3upOq1/pxb8aO9a3zY3fSJC6lxjzO9WZYH9SqWipaUlZTIZ1Wo1dXV1adu2bUqlUpqfn1etVlMmk1GpVFJXV5fL3Lbr9dCuZJOfOGg2myqVSnrhhRd04MABlctl1z1tcXFRkUhE/f392rhx43kJh0vtVrPStrpcLvaEGay957vWDzrgWuL36nr66ad15MgR/cAP/IDWr1+vWq2mWCzmLrhWmk+j0XDnIusyu5r3Wnfa1Ry7Vjt0pXkCuDYFSy5t2LCh43Nm3759LX9/4QtfcNPHjh1z03bDK0nHjx930y996Utb3n/77be76U4lmIKlL4N/r2Rqaqrjc9ls1k1/+9vfdtNve9vbLmgZAAAAYWs0Gq6cUalUUq1Wc2XDc7mc4vG46vW6FhYWNDw87MZusPs1i5tZeSUr7eSP4WDJh2g0qkaj4aYrlYr7Z+M7SK0DXEtqKd/U1dWlWCx2XqkkG2vC7zlh4z/09fVpaWlJ1WpVkrS0tOTm4ycejF/+xo+9rVSy6HLGqjrF0lYzhkKndbsSpXkudHtczDpdrZggscjVuekTEXbyWG0mr1wuK5/Pq9FoKJlMauvWrbr11ls1Njamxx9/3I0ZYYPe2MnOdkgL7K20PAvqZbNZnThxwpV+yufzrmdGMpnUwYMH1dvbq5GREUlyWVlp+UDdhXzmS3ElMrMc7MClW1hY0MGDB3Xo0CFt375da9ascb28OvXgCqpUKorH4y5gF41GFYlEWi4+2/EvllY6nq/UuQsAAAAAbnbVatUN/myBeksiWM8FScrlcu61NjaE3dtZXKyrq0uFQkHxeFy1Wk3lclmVSkW9vb0qFApuUGpLTlhSwl5XKpXaNkSNRCKq1+uSXrwHDTZ0i8ViSiaTGhwc1MDAgPr7+xWPxzU6Oqqenh6dOXNGCwsLrpyU3+uhWq26e1mbt5Vx6jSGQhj3rKutcnKlXOxyVztY8vU83gY6u6kTEas5MfhdyEqlkqamppTL5VyXsd7eXvX29mpsbEypVErNZtPVues0v1qt1jIgoq2LH4yz+WQyGeXzeRUKBXeiXlxcdCf4YrGo8fFx9ff3u3leiSzr5XKx873U9en0uQhw4nrVbDaVzWa1uLioZrOp8fFxdXd3uwuxTu+p1WqqVqs6c+aM9u3bp+PHj+vw4cO69957XXdU/zzoX9DVajXXFVaSksmkm7ddkNVqNfe3LS9Yqs4u5KwOZ6f1XG2vCQAAAADApZuZmXHVPqyXgN1DWgIgGo2q2WxqaWnJJSwikYgbe8EP2CcSCWUyGdf41kovdXV1tfRskOQa4to/G2Ta74Hgj9cQjUY1PDyspaUlpVIp95quri4NDAxo48aN2r59u9auXav+/n4lEgklEgnl83mVy2UNDAyoUCio0Wi4+1gbsNo+iz1m816uF0RwXS+n1TTgu9R5hKHTNrvY5M3NXp69XUJqpSTV5dhml1KZ5qZORAS/pGC5n+DYA4VCQXNzc5qennYnUBtgx06kFiyzE06wBbAF7IIHmZ2E/dc3Gg2dOXNGS0tLLjGxsLDg6urZyX92dlYzMzOKx+NuoB1bh+Bnbff5L8VKO/Bqs5iX6+RxsVlhEhC43jWbTe3fv19PPPGEurq69MM//MMaGxtTo9FouWgKvqdSqSiTyWj//v3K5/NqNpuanJx0rV4s6VqtVlvKLtnFoul0vPmJhUajoUql4mpyNhoNNRqNlrqd/v9+wsN6W7RLVAAAAAAAwrG0tOSSALVazVUCsdK89k968f7PekbYvaj96+rqUqlUcu+X5EqbJ5NJV57JejjU63XVajX3WiubHolEFIvFXKmngYEBbdmyRbfffrvK5bI2b96sRCKhWCymeDyuZDKp4eFhJZNJt662nOnpac3NzWlmZkZnz55VqVRSPB5XKpVSOp12vSdsoOvVlDEixgS0d9NHdIInBzu5tUsUVKtVzc3NqVwuS5LWrVune++9V+Pj4y5Tm8lk1Nvbq3K57IJswQxoMNERTFjY441GQ6VSydXfswGA0um04vG45ubmlM/ndejQITdQ0Ctf+UpX79jvKnaxAfqws4pXK+PZKUFys2ZRcWPI5XI6ffq0Go2Gjhw5ouHhYcViMVWrVRfsl17czy0JcOrUKZ04cUKxWExDQ0MaHBx05yQbDMx/nz9tvR78JKt0fmK3Vqu5ViXSuTJ3fusZ6cWL1uDyurq6XBLCr/EJ4PrXaVyIw4cPu2l/TAhJOnHihJu21m6S3OCCkvSqV73KTd91110t78/lcm7aPy/5YzcE+efQdDrd9v3+GBXj4+Mt7/fHsvD5nwUAAOBa84pXvEKTk5OanZ3V/Py8ZmdnFY1GXZUOSxgkk0n19PQoGo26QaJTqZTroV+v1135pf7+fpXLZVe6vFgsqqurS4ODg+rp6XExsnq9rlOnTml+ft71sohGo+4+cnBwULt379aWLVu0Zs0ajY2NaXR0VNFoVMlk0o13aJUCYrFYy7gP9Xpd5XK5JTZUrVbV09OjZDKpgYEBjY+Pu2oDQcvF2VY7bkSn11wNFg/1Y4lhWGl8i05/34zC6vFxNffBmzoREeyFEBwvoru7291gWkteK8tUq9U0Ojqq9evXK5lMuqyuZWe7u7vdidm/eV2pC5f/umKxqKWlJZfpTSQSuv/++7V27VpNTU3pySef1OLioo4cOSJJGhkZ0cjIiO677z7Xitn++QmW5Za50muCLld3r9W8ZrmkxaUeRJzgcCNoNptKp9OamJjQ888/r3vvvVf1el3xeFzFYlGS3MWXdK7eZ6lU0vT0tIrFohKJhLq7uzU0NOSOCasD6tfCtGkrM9fV1aVKpeIu8ux9zWZT0WjU9RST5LrO1mo1xeNxVatVVSoVtwzr0eWzFjbWg8NvcQMAAAAACMfdd9+tDRs2aHJyUqdOnVJXV5erEmL3fHav1tPTo97eXvX392vDhg0aGRlx94M26HSz2VQ8HnfTvb29LpbW29vr4muNRkOnT59WJpPR0tKS6vW6UqmUS34kk0mNjo7qvvvu05YtWzQwMOASCJZs8P9Zoze7f5XO3X/aeBe5XM6NTeGXPU8kEi0N4trF9ILxvctd+qZd2aKLmfdy87TPEMaYDGGOZ3G1Y3mX+7Nd6L6zXBnu5eax2h49y1W/uVg3dSJC0nmlRYKtef1WwRbISyQS6uvr08aNG9Xb26t6va50Ou26eKVSKY2MjLguaH6Cw6+h1+5kYsmRWq2mfD7vuoSl02l1dXVpx44d2rRpk9atW6doNKonnnhC+Xy+pXvc4OCgdu3atew4FMHHL8bl6plwJd6z3HzoMocbgfU6sAulSqXS0n3Wkg/tzguxWEzDw8MqlUpaXFw8rxdELBZraZXid4U1lqTwezcUi0UVi8WW1jCW3LXxJKzeaKeyTD5bJscsbB+wRNaJEyd07NgxbdiwQbt27VIsFmsp+yW9eLFdqVRa9mvr0bPahHhwLBPrMWk3VVf7YhgAAAC4XLZt26bx8XGNjY1paGhI8XhcsVhMuVxOpVJJlUrFNdyNRqNKpVIaHR3V7t27tXnzZtd7wq6X7VraSv2m02n3fCwWcw3OCoWCawhs87CGbJFIRKlUSmNjY9q9e7fWrFnjGrRFIpG2YxL6yQc/gdBoNJTP5934rNa4znp6+GWEreJJcB5Bqy1RHoZO99PBcSva3VOvpuTU5XAz3C9drh4HYWyr1TRQX8mlJGBu6kSEX54keDLxX+PXrctkMiqXy+rv71dvb6+6urpUKBQUjUbV29urRCKhVCrlkhLtSpn4PTDasUTE3Nycq2WXz+eVSqU0Pj6udDrt6uDlcjk99dRTKhQKboDsp556Slu2bHGlA2z9L2SbXIuu5XUDrrZIJKK+vj7XG6pSqWhxcVGDg4PuXNSuF0E+n3djz1gXzHQ67Xoz2HvswtIP7PrLtgSBjS3hv9fvoRV8v13kWY1Q/33S+QNkB3tL4OZkvQZrtZoOHjyov/3bv9X09LR27typ0dFRDQ8PK5FIuNq01vLJT5jV6/WL6lnT6WbDkhrtjhF0Zjd5knTw4EE3/bWvfc1NB8sX+SWY/HJIb3jDG9z0nj173PTS0lLL+59//nk3PTs766aXu6D21/PWW29105OTk2pn06ZNLX9PTU21fd3mzZvbPg4AAHAt6O3tdQ3LRkdHtWnTJt1yyy2amJjQzMyMFhYWtLCwoFwup4WFBdVqNReLSqfTrqGc3dMFx0a1oLh/bW6lzq2HQjKZbBm0OhKJqLe3V5s2bdLQ0JCLv/k9H/yqILZsW66NOeGPmZjNZlWr1dy9qzUyGhgYcLE/W/fVVDix/y+0+oefJGgXT1ztfDo9H1apn+XcyLG8lfYD2wcutYfDha7TldzmF9pQ9KZOREjnb7B2Xa3s5JTNZl3gw4L+0rlaw5FIRD09PW4wG+sOZllTP9jRLpDm7ySWHbayJ9K5Xhjr1q1zA7zGYjENDAzorrvu0sGDB5XJZFwg8fTp0zp16pR27tzZ8hlXCrhcy+WMOgUHLmevDPuugOtVIpFwXVytJ0SlUmm58EokEi1J2Pn5eWUyGdVqNS0tLbkutdb7we8dYUFWOzf5x51dzFkPB7+k02qOT+vF0d3d7Y5Dv0eaBZFv5IsYrMzvCdFsNjU9Pa1nn31Wk5OTqlQqyufzmp+fd2MlSS+WAzOJRELSi4Fl+521hIVZbl+z/dt6VVjywQa8o3QYAAAAbhR2jWwVQIaGhjQ2NqaJiQkdP37cjY+aTCbV29urSCSiQ4cOaWxsTGNjYy5BYNfI7XrT+zEfW94dd9zhXre4uKhCoeB6Q4yOjuqOO+5wpZyCvR6sMZ7fIM5PEFgDOuthbTE9Sa6RXE9Pj9asWeMGqbb5B2N8QcH72WvFlQ5Q3+zY3u3d9IkIqTUQ7ZdksmytnaBmZmaUy+XU1dXlgiB2Qi0WixoaGtLS0pLGxsa0du1a93ynk1Sn7lD+c/Pz85qZmVFvb6/WrFmjaDSqRCLhToKbN2/WnXfe6Uqg1Go1LS4u6uTJk9q4caN6enpalu0H7q9GJvRKWunztdv219oPBXAhrKuqlWkbGhpySQXraeWznlf9/f2uV4T17orFYqrX6+5C0hcs7yS9OI6D/djW6/WWC0D7286H/rFmpZlsPaUXkw9+2SZAOtcavtlsKpvN6jvf+Y4OHTrkbmwKhYLOnDmj7du3u4SA9bqx5Jrtk8H92PZPK9XUbj/3u3r7LeT952/U31QAAADcfPyxVbu7u13VjkQioZGREW3evFkTExPat2+fms2mEomEK8N7+PBhVatVDQ0Nqb+/XwMDAy2ljqQXG8xaWWE/zrZmzRotLS0pm81qamrKVTMZHR3Vhg0btGHDhpZ7UFtHvye0pJYEhbGYnzXeK5fLrmGSNe5LJpPq7+9387T/2zWODW6z5e4J2pUJv5z3vFfjfiTMcSAudN5+1Zur5Xq4J2y3XS+058bF7Lc3dSIi2F3K7wHhP2eBiUwm4wa9GR0dVV9fn2q1mmq1msrlsnp6erRz506tX79ew8PDrsVwp9rTnU46FgzJ5XKanp5Ws9lUX1+f1qxZo97eXtdi2Lqj3X///Tp16pSmp6fdWBH79u3Tbbfdpp6enrbdua6VwN5yyQK/Vbd9R36r6OV6RqymS1o718PJAmgnEoloYGBAfX19SqVSLQNSW/IyWDImn89rZmZG3d3drrdVV1eX+vr61N3d7c537fg1Mm35pru7W8lk0iUdLOhrLWWs15ffPVZ6sXW5zcP/bP4yg8/j5lOv1/Xcc8/pueeeUzwe1+joqJaWlnTmzBnl83nXZbter7f0AgomF+xmw//ttx4T1huy3XFg+7S1lpJa91+s3uHDh930l770pbavCf5mp1IpN33//fe76e3bt7vpo0ePuulgaaZDhw656b6+Pjftl3nq7+9veY9fgskvIXXmzBk3fdttt7npdokq45dj2rZtW8fXheX06dNu+tSpUy3PPfPMM23fMzo66qb9clbB5x544AE3vWHDhktaTwAAcG0INm6Nx+Pq6+tTPB5Xb2+vG6Daymf6DcoymYx7nd+roF0jYLset/tSu56y8SBqtZqq1arGx8e1fv16Fx+zf34lgGDMyBom2fytCkm1WnVjXVjcye4Hent7lU6nXUzQn/dy5ZcuJpjbrqHy5QzuX8v3KZe7kXSnRNHFzj/MJMvV0Gk/u5BG3Be7z0s3eSLCDnQ/IOYnIyy40Gw2VSgUVCwWNTAwoGQyqbVr1yoej2tubk5HjhxRuVzWmjVrNDk5qfHx8fMCF/7JKThojS3P/q7X6yqXy25w7KGhIUlyGVo7AcZiMcViMY2OjmpkZESRyLka8el02pWo6LTDtEuCrLTjhNmDot3J23qEHDt2TLVaTV1dXYrH49q2bVtLgCC4/To95rsZeoTg5mRJhUql4soy2QVcuVx2NTqlc+PezM7OatOmTRodHdWpU6fU29vrgrh+b4RgGSa7WGx3MWnJQ0ktLUYikYgbzNc/P1oPs0aj4S76ghcP9hlIQNy8bJ+KxWKamprSc889p56eHt1+++06deqUSqWS6vW6enp6XFLAWmPZ/lqtVltqx/olxtr1gLCyTnadYPMywWMAAAAAuJH4gXdLFth9XTQaVTKZVDqddr0XqtWqe50NaB3smeCzHhB+uSZbVqlUcuWBR0ZGlMvlVCgUtGbNmpYBqv1ERFC7+J6fiLDYW71ed3E8uwfo6elRT09Py3iGfjzPT24Ee1tciOWSEBcSrwqrJ0K7WF3w8eUqvlyqC/1cywXUif+d0ykGe7m29XJu6kSECbaiD/5v5UIqlYobmLqvr0+JREJzc3MqFovq6urS4OCgpqamWrqbBQMXfm8Lm7c97y8vkUi4AWOnp6e1bt26lnp6/pcdj8d177336vDhw0okEhoaGtLi4qJeeOEFrVu3zrVubpeACAb7Op1glnvNhQiesJY7WTUaDS0uLurUqVPKZrOKRCLKZrMql8vas2dPS6vVdjjB4GZjLTksGWHjOVjvBuuVYGZnZ1332sXFRZdgiMfjrueVX6bGekDYOSjYMsYSGF1dXe6CMTgQWbtpfz7WAj14/PoDi1lrdNxcGo2GyuWylpaW9L3vfU/ValUve9nLtHnzZi0tLen06dPq6+tTf3+/+22x/VeSuynyj4N2+6ffJdxftpV4ikajbj/sdMMDALhxhN0IolKphDp/SZqbmwt1/jMzM6HO/0qM42eN/8IyPj4e6vyvxDLC/h5sDK4wWSMVrJ7dU/qxLGvAa416enp61Nvbq6GhoZaeDdVq1cVyLLhv+5GfGPCrlPhJCCuP1NfXp1wup2QyqWazqeHhYQ0ODrbEuSyZ4SdL2sXjjD2Wz+dVq9UUj8cVj8fdANl+RY5ms+nubf37VOtd3el34kKTCH4v7WDj5RtZmJ+vXbw37GB7MEZ5pb6/C0leBY+P5ZJI7Y6fS+klctNHcvzAmv3t15C2wVrtZJZOpxWJRFQqlVQul3XixAmVy2WNjIwonU5r/fr1Gh8fP+9E5J8I29Wnsy/RBoa1wWC7u7tdosO6nfnraif/jRs36pWvfKVOnz6t7u5uLS4uanZ2VktLS26d/QPPP4EGT3JBl3oCXCkr2in5Ua/Xlc/nVSwWlc/nlc/nlclk9MQTT2jdunXasGFD20TOatax0zqFlcEFrgTrJdXT06PR0VElk0lFo1EX2LfknbHHyuWyyuWyent7Jb2YVPDHh7CkxHLlmvyW5qu5aQ+2jLFWKVYexz/v2PnYWqDj5mO/jYcPH9bU1JRuu+023XvvvSqXy26w9OHhYQ0NDbnfRrsZsfGVjCUSlluWP203WbbvBcucYfX8EkeS9L/+1/9y05lMxk3738GWLVta3rNmzRo37ZcF8ssx+Y4dO9byd6dyTHv27HHTwbJCfjkjv1em/3msHEG7Zfr88Xr279/f8XWXyl9nP9Dpl8A6cuRIy3sWFxfdtH/M+OWw/O0ntZaq8lGmaXX87ynIL/HV6XeVbQsAuBKs54H0Yk9iK70rnWsgG4vFXOMf6dz1Qzqddr9ndn0uyV2/23wsEWXX/GfPnnXvsX+1Ws2NDzE+Pu4SSzZfv8yTP05AsEe+n8DI5/MqFAoql8vq6upyvTAGBweVSqVcHK5do6Xg45cz4OwHioFr0cXu8zd1IsIPXFvg3894+qUcMpmMstmsqtWqBgcHFY1GNTU1penpaZckyGaz2rJli3p7e1tqp9sybJnBgHm7rFKj0XBBeOsqZi2c7XV+5jedTuvuu+9WNBp1J+ylpSXNzc1pfHzc/VC0O5m1S4gEA4CX03LL85Mi3d3dGh4edgGHhYUFTU9PK5/P64UXXtDg4KALnPqJFf8Hh/JLuJlYoqC7u1vpdFpdXV2ul0K7wOns7KySyaSrn97b26tEIuGOq0ql4hKiNo9Ox9LF9FKwxG88HnfHrV1MWgt0H63Pb27NZlMzMzM6c+aMbrnlFu3Zs0f9/f2an593JQ1tv7f9x/ah4IBly+2rFiS291pizsqKAQAAADeLdvd5lljwA//22lgs1pIIsN719rz/PgvmWzzO5m3jNszPz2tubs79KxaL2rlzp4aGhpRMJt39od1X+mVTg0FS690stZb+9UsxFYtF1Wo11zhZOlfeuL+/v6WUe7BHiM0zqF2JdlvmStt8tS6lZfpKlrv3v5DHL9Xl6GGwUqv/yyGM+V9MTHOlfWK1j7WbX7v3XOg63vQRHf8EKLXWi/NPFP6g1JYtnZ6eVqPRUCqVUiQSUaVS0ejoqAsE2snPdDoxSS92S/MHzUwmk0qlUm7QV+ua5neJ9AdutSBiuVxWJBLR3NycpqamXGY5zJPCSt14/H9+V7Pl5mmD5vb09CiXy+ns2bNaWlpSuVzWyZMn3RgaF7qefu+U5ZIywPXILoj8/dwPqPotcS3ZZ8eFjX9jY85YK5Vg19ZLZcuzAcHsMVt/P4Dc7vNxnN6c8vm8JicnFYvFtGPHDg0NDbnfWeu9ODg4qMHBQTdAu7H93sYj8QV/j6xnkbFrBLsO8F9bqVTcvFf6XQMAAACuN34VkWBFCj+w3q50kz9+g8XI/DK/Np9gTK5er7tExNTUlKampjQ/P69ms6m1a9e63grWU8Let9I/E1zveDzuxlL0y6z7957BRETQchVGVrpH6BQju9B7X+5Hrg3BGOiVXu7lstz+dCnLuql7RARPesGahxbYkM6ddPL5vBsrwuqwW9Z1YWFBO3fu1PDwsOtZsVKw2wJ8Umu9MhsUc/369VqzZo2y2azLEpfL5fNKn9jgm/V6XblczvWe6O7uVjabVaVSaWldHMwMtwvKBNe1U4bLApt+l7RLYfOwQX9isZiSyaRqtZoKhYIajYbi8bjrQmfbu1MPjtWsE70mcCOwY7HRaLhAaldXl5LJZMdxGtauXavFxUUtLS2pWCyqv79fqVTqvPeFcWxYKxML8DLgL1ZivQPvv/9+DQ4Ouv3deitGIhGXkLffBbtxWq6Ukt/iSXqxQYI9tlxvH3++/mB17MsAAAC4EbQLjgcTD375cD++4sfFgnEoPw7nJzZqtZoqlYrm5uY0MzOjqakpLSwsqFAoqLu7W2NjY+rv73fX/BYrC84/WNI3uGz7ZzE/Gzsx2JNjueoitozV3i+v5nUXeu+9XGzvenc5P8+V2DZhxE3CmOdyMdDVbKdLXaebOhERbCHvt/w1/uCYNuBrIpFQPp9XLpdraQ05NjbWUrok2A0rePIN/m/8rLENkO3XMLb1knRe0sOSJKVSydXQs4RKsFtaux8Uf3uslp+BXul97bLk7bTrqmeJmHK5rFwup6NHj7qxOVZz8m93gib5gBuFBVutDnhPT48blNdq5PuJQ+ncYG2JREKVSkULCwtKp9MugNvu+Gw2myqXy67X13Kl1fz1kl6sH2rL9rvo+jWwl2O9KJYbEAw3rmQyqe3bt7uB6SwBbjcYiURC69evb/v7ZtolJNolGVbbW87/3bRj7Ea7AbgcTpw44aa/973vtTznj0kwNTXlpv3t+Mgjj7S8xx+vwO8duXbtWjftXzf5j0vSpk2b3HQ6nXbTw8PDbtq66JuNGze6aX+8BX+8BL/W/8jISMv7X3jhBTd9+PDhtut5OXQaF8IfCyL4HXTib2dfNpvt+B5/nI7BwcGOr7tRxzUIjvfQaRBi/5gIDiL87LPPuml//9y+fbubvvfeey9pPQEAWK3gfZclIexes11Mrd34Ce3uFf0yShZbs54Qe/fu1ezsrLLZrCuZNDIyouHhYVeWydYt2LAoWJ1EerHnvb3eyrCXy2XNz88rm80qHo+rXC6ru7tbPT09SqVS7r61XUMjv+HSSuVr2mkXl1qprM5ywgxaX+7lBD9nu9hCcHnLVZm5nMmgq+1StnmY96IX0hNoOTd1IkJq3aH9+nb+ADt2UhweHnat8mdmZtRsNpVKpdRoNLRx40bXgni5gLyffLDX+SdNOznaCdBusK1Fpg0GG/wxsJ4Su3bt0pEjR1QoFNxJ3M8w22dc7gBuF9RfKQhzIdolYIInD/s/Ho9r/fr12r59uxvQcX5+XtFoVENDQ9q9e7e7SWv3Q7OSYPe86+GkBHRSr9fdYKmpVMqVZbMBR4MB/2w2q2g06gYQy+VyikReHKfBZ0lZ/zipVCotwTo7d1oSNR6Pt4zrYMnSZrPZMgjqaluQW0KV4/TmZKXDEomE+30ulUoqlUqu52Bvb69LmFnjAfudqlQqLe/ttM9dzD5Wr9dbkngAAADAjcC/vrWew358KfhaK3UejCvZe4MDSvuN1crlss6ePavHH39cR44cceXJraTwK17xCm3evNmNaWhsLLdODYHbrUetVlM+n9exY8e0tLTk7ivy+bwikYgbtNrvuXG5KoEAN7ObunaAnfSCQXArCWQlSqwFfiqVamlN2d/fr3Q6re3bt+u2225TT09PS107Y13Lgmx51nqzXd26RqOhdDqtUqmkubm587qXSS8GF2OxmPr7+13mNhaLaX5+Xrlcrm1vj3Y18i41iLJSUiLY0nql1qM2EPjo6KjWrl3rekVMTU25zxVscd2pdXWnZV1MMgW4FtnFYKFQUD6fdwNB24Wd37VUOteSd2xsTNKLSVB/nBpLZNh0d3d3S8mmYOvyrq4u10U2mUy648q6yloiNZFIuKREu3NaJ1azk4u/m5Ptm5YQsxuIYrGocrms0dFR17rcEvr+vmI9hmwMKEluH+yUnPdbefmC76EUEwAAAG5UwdhZu0ofklxDoFgs5q6l7TXWg8F/zIL81nM/n89rdnZWp0+fdrEfS2okEgnt3LnTlRO2QbGt0a41gOvUs79er7uKIfZ5rKKIPWclg6VzDftsHIrgvII6xdM63be2i/3dTJa79+p0byatPl7Z7v6NBmPn8+PQq4kJt4tbX4ybukdEu+5a/t8WrEin0xocHNS+fftUKBRUr9fdoNTz8/O65ZZb2rbKty8vGPzzX2cBP2tNadP2zwItVu/dH8vCT5zE43EVi0UtLi5qfn7eZZij0aji8bjrGhdct+A6L+dCXtfuxB9crq9TKRfbLjt37lQ+n3dZ8UQioVqtpmw2q9HRUbdd/MDTanqmdPobuB5ZGblYLKalpSUX/Pd7X/k9sHp6elSr1ZTJZCSdO+ZSqZRrUW7nJwvqSq3HSrsWMMbvCWHj6fjdYe31tVrNjfvS6Zi9XIlSXN+C+49dqGazWfd7YeMG2c2Pf4Pk78/+4/YbG2THQSKRcO/zlx38m2REK79EzbFjx9z0qVOnWl7nl2PyS/74JWn890utJYP27Nnjpm+//fa26xIszeTzSwQFy+p04vcEW7NmjZs+dOhQx/f4+4tfjuliSuwst55+Y4ynn37aTfslk/weaUHbtm1z034pIOttJ0mTk5Mt7/G3r192yh97bbUl+K4Xnb6Dffv2tfx94MABNz0zM+Om/ePAPwaCxsfH3bR/HJw9e9ZN/9iP/VjLezZv3txxfgAAXKxOJXPa/d3p3s7GNvX/tuuFWq2mhYUFzc3Nud71VhY4lUqpv79fY2NjLb3ubTl+KfJ2sSg/gWL/NxoNFYtFV3Ld4m/WmG/9+vUaGxtraTi82jEh/O2wXFmh5bZz0IWWILpcVro/v1zzvtiyP+1im34P+JslftCpofnFVn65mJjxat3Ud82ddvTgSaa7u1tr165VV1eXcrmc655VLpc1MDCgTZs2tbTSDQYkgjtE8CRoWWB/HSxbbPXbk8mkBgYGWmpQ++M/2IFWr9ddDb3u7m4NDg62JEGCy5ZerMu32mxt8P3BXg6r1enk5Z+wLaOeTqe1bds23XfffUomk6pWq8pms8pms661tQWSlks+XMxzwPWg2WxqaWlJ9XpdiUTCXeCVSiV3jvATCpLcxZdd7JVKpZaEg7Uw6dSyZLl18bvBWiuVIAsYS+cuPP0eGP5FhB3juLlFIufGQYnH464mbTab1dLSknp6ejQ4OOgCrNZ6qlNLGNuX/dJN7ZZnPYCC5RCtd4a9rtNg1gAAAMD1zL92Dv7fLr7k/+3H1+xvv2yv9GLjtmq1qoWFBS0sLLj4TjweVzweVyqV0uDgYEsVEn9e7VrSB6twBP81Gg0VCgUtLS2pWq22NAhOJpMtiQj/c12OFuH+PUmn9bzRBBNUneKx/j52sdui0355PbuYfWO51wbntVysJ7i/BpMUF7puN3UiQmptfR/ceNZtzFreZ7NZ1yKsUCgoHo/r/vvv19q1a92XYYFz0y4I4vfEsOX5J1PL7qZSKfX29ioSiahQKGhhYaElMGg9LfwuZX5Xs66uLuXzeVeTvdNOcaE7zXJJiU4uNtBv74vFYhobG9O9996rdDqtRqOh6elpzc3NuSCQfwLvVE7DX+cb6aQESOeSDsVi0Q20ZeeIer3eMl6MqdfrmpmZ0dLSkgqFgiKRiPr6+hSJRNxF33ItSjpZ7fFlx7d1gbVzp//+SqXSMojZcuXXcGPzy+/Z793k5KTr/TM4OKhkMqlIJHLeGCS2P1mizVpOLdeqabnfLUuO+Q0D/GQaAAAAcCPw7+uCwX67P/PZfZ01+AkGL/2e85Jcz/1araalpSUtLi668U4t9pVIJDQwMKBm81zJYBvT1RoMxWKxlvJMNl+frafdT1icz8aBtfd1dXVpaGhI/f39rlFSu2oqnbZVp3vhCw3ednpNsHHz1UhehNGQt1Og+2LmEdwXpM4JqWtRuxiMf5wt9znsmFmpwbk/L///K+Gmb8IXzNTatP3faDRUKpU0OzurTCajarXqAnqbN2/Whg0bWnop+PPodABZBtDPBkpyJVPssXg8rmq1qmaz2VITO1j+wcqeSHI9J3K5nCs/YWWd2mUX261TcJ2D2W6bz0on15W0y44HvwNfPB5Xf3+/hoaGXKApFou5z7naA4yeD7hRWWC12Wyqp6en5Zju6upyAX87Bnp7e119fX8gsK6uLlWrVfcDbseOH7hdrgV4ux9863Zr77duuZZ8lc5vFSO1lhCxcyTH8M0pEomoWq2qVqu5wdOr1aqWlpbcWA/W68cff6RcLreMlRIcy+liSir5A+rZ7yz7ZWu5Gr/0zN/93d+5ab9ckNRaZslvceaXTPLLH0nSjh073LRfjskvEdRubK6V+Mtcjv855+fn3bRfssgvZbSc1b5utfySPX45plwu1/b1fikmSXrooYfctH+et/GEJJ3XQ8jf1ps2bWo77xuhXJD/vfsllxYXF930c8891/KekydPuulOJZj88kvB13V6T7lcdtP3339/y3OdjiMAAC6GH6j0y4QHYznB97Rr7e8LBubn5uY0Pz+vTCbjxjuUzl0rDg8Pa/PmzRocHHRJB/+a3u4Tg9f1/r1vo9Fw8TV7jw1SHYwppdNpF2+yZfkNiNvFzYLbq93nBFYrGB9td4y1e93FWG5/DsNNnYho1w3FP7nWajX3mA2ObD0OhoaGtGPHDqXTadXrdTdQjnRhdcj817U7aVrwpNlsKp/Pt7zPX3+7WYxGo0qn01pcXFS1WtXAwIASicSKwbsLTSC0e89qu/V00i4x4s+vq6tLg4OD2rp1q/bu3et+GFazbp0+A3AjseBDrVbTmTNnlM1mXYsASwT49fCtNYmdW4LHhZ3vLClrA4VZ8tU0m03Xc8HGe5DkWpo0m00lk0nXYtwGq7b1SSQS553/7OLQD4RR/ubmZoksSW4/jMfjqtVqrvePX3rM9hc/CeHfqEitvSL9cR9W+xsSi8Vcb4h240wAAAAA1zM/xhLsGbBc49tg4D7Y8toa0Nl9ai6XU6FQUKlUcgn3np4exeNx9fT0aHR0tKXhnPRizM5frv1vcTl/fWOxWEvjOmtM5N9nJJNJ9fb2urFW/aRKMHkS3E7Bx650i/ur2fh2uXjg5YgVrna/u5DltNteV3obLrfO7fYpq3IRbNhu8womAIPzvdRYbaf3X8h8ieoE+CcsK/8wMzOj2dlZF1Dr7e3VmjVrNDY25hIQ9p5g6ZMgf4folOHyWwX7JZisFah/4raTqLVczuVyrgub1bWzk60fYLnUE8FqreYg9nt5+OvmH1T2oxePxzU6Oqrx8XF1dXWpr6/PzSNYuy+43Kt5cgGuBDsfWK8tC8TaecPOaxYwtXqbIyMjmpycdK+zcXCst4J1d7WAr3SuBawlJGy+wcHHLJFhyVRLiFrZO0tQdBJsdWufRbq4Vuy4vtm+aL9x3d3dKhQKKhaLLlFdq9XcANPtEvC2P1p3bkuKWc9Dvxeh9TZcrnGB/Ubbvh9sLQUAAABcz4K9H4KxLP81wQocfjkZ/zn/8Xq9rmq1qkql4no3WwM2u17v6+tTf3+/u0735+0nC4LL8tc5+JparaZMJuPuof1YWyKRcNf49lmC9wTtltEuKLxawe23GssF/MOymoTD5YqzBeOnwTJg/nM23Wk7tgvqB7/DlVxqVZjVzK/dc/a5/P2+U28Ji50G59EuyXE5Xcj+TiLi/89KlgSDB9VqVWfPnlWxWHR/x+Nxbdq0SfF4vKU0ULsN3y4T7AseDMFeDs1m0y1zeHjY/e2XW7IWy5VKRZlMxpWQaldzvV1JipWygKs9mSz3WZbTaWBvf71NOp3Wnj17tHbtWpVKJY2Pj7d0lWu3/kHL9bwArmf+RVlPT4+i0agSiYRLAliCwVivIhugK9g7wurt23FoCVGbr/TiMWrB3cXFRSUSCfX09LiEgw0abEFeOxfZ+lprcju/+ecun3WlpWfEzcvvbdNoNLS0tKTJyUmtWbNGPT09SiaTroeN3czY/mLHhu1f/oWs1Z61smTVatXt/yuxi79gT6GbgV+qRmotTfTd737XTftlbDKZTMt7/NJMDz/8sJv+oR/6oY7L9c8BfjkmX7Dk0KXyP6tfiuj48eNuemlpqeP7/fW5nNcdwRJUTz31lJv2vw/fHXfc4aZf/vKXtzznb8+LKetzubf7ldbpe5Zay4p9//vfb/v+M2fOtPztl1YKlmDqxH/dsWPH3HRPT0/bx5955pmW92/cuHFVywEA4EL4gVAbo9Mv1dTp+qZdYNgPANfrdRUKBeVyOdf41AaNrtVqSqVSGhgYUDqddnEwe69fgrxT7Kpd/KfZPNejf3Z21iUg/PHoUqmU61UdTHRcaJJgufuDYJJnpfm3S/50mt+ltny/0Nd3em+7GN9y6x58rN17/b/979xvgNmpYZi/fTolji71Wr3Ttlhpvp3ioXacWGN5/znruWPzt/vSdhUn2m3jldbrQvaJ1b72po/m+AF6C/BHIhHXqvL48ePav3+/SqWSG3BneHjY1cq1Dd0uMye1jqfgZ4X9bGrwhGknv3g8rpGREaVSKVUqFTfwtJWe8AfZ6erq0tLSks6cOeMCdX19fRodHXUtPv319XtIrLR9lnv8Yg/Q1eyg7ZI7sVhMPT09SqVS6uvrU19fnwt2LpedJtmAG12z2dTMzIw7j1nPBDs3lctl16Lc1Ot1zc3NuePKgq9dXV1KJpPuBy8SibgxIyz5aUHXRqOhYrGoYrGokydPav/+/err69M999yjgYEBJZPJltYkVo6pu7vbtUC3oGIkEnHnN3tNsBXEjZqEWO7CYDmX6yIpuJ2vRf7vnXRunz5z5ozbL3t6elSr1ZRMJlsGr/P3OTsurBehzde/eLObH+tpt1JLI/+36lrddgAAAMDFsmtcvzW2H+xtN0agvc8fK9C/XvYrfMzMzOjYsWOuHLo1fovH4xoaGtLo6Kh6e3tbxnzrdO3drlV8u4C/DVZt7/HXZ2RkRD09PS4+2Cl2Fvysq21hf6GB30tJKlxo8Hs1rwnuD8HHL4Yto12jaBOs8tJueSslIKTW8XnbrXunzxtcp+UaPvux4uUSI53W1ZIqNkai9RqanZ11cZVqtarR0VFXHtsa11mPHn/sk3YJmOC6Bvnfc6fG9e22y0puzIjOKgU3VjQadS13y+WyZmZmtG/fPk1OTmpyclL5fF7r16/X6OhoSxDDSia1yzpJOi9ILr24Y7XbCax0it/quFgs6tSpU7rnnnuUTqfd+vu13ufm5jQ3N+c+w9jYmAYHB1syZLacYMbYf66T1SYP2k2v5vXtTpTBdbSDbWlpSdu2bXMtKZfLgLf7DASLcKNpNpvKZDJuEN9isehKI0ntf6zr9br6+vqUSCQ0NzenVCrlLrYs4WA9FyxZ22w23XnHytXl83l99atf1alTpzQ9Pa2uri4Vi0W99rWvVW9vr1uenfPs/VaWqd15M3jOsp4S9gO6mkTqtcRPerd7zhI9VlYrl8vp7Nmzmp2dVTabVbPZ1PDwsIaGhrRhwwb19va29Fq52PWwZVsCKDgux7XG7zJdKBS0sLDgevpYjVhLIPj7iH0m6yHks20R7DnRbjv45cu6u7tVqVRcbx5/fAoAAADgRmLX18sFYtsFkYMNyqrVakv8plgsav/+/Tp16pQWFhaUz+fVaDRcw9zR0VEX1/IbsPnz9tm1fbDEqiUZrFW5xfHsvtcfI9Z697eLgfn3U+2SEJ10ikUFEyTXUqwqGDsMjotrj1+usrSdtvdy2yS4Lyy3LvYZLKZo98GpVMrFXi/H9vc/x2riFpZYkF6MeebzeVWrVc3MzGhhYUHZbFbFYlHPPvus+4yNRkPj4+NKJpPK5XJKJpPauHGj7r77bg0NDbWUK76QGGlwm1/ussPXbrThCrGTS6VSaQlwZLNZHT16VKdPn1alUlEikXDBDgui2U7eKfvTLuPkZ1P95/1pWycLpiSTSZVKJRUKBRUKBY2OjrbUoo5EzpVlOnDggIrFoprNpgtW9fX1nbfD+cuw9fBPostlYNsFAS/XSXO1763VahoeHnbjRAS3s38iX67sE3Apgi32/b+tJ0GnQeL949uC+X4pIv/HwFpzW5m44eFhDQ8Pt12nYrHo3pNOp9uOv1CtVlvOQdbaJJ1Ou+6n9Xpd5XK5pSdDJBJxP86SXMKzXq/r2LFjOnTokBYXF1WpVFSpVHT48GG95jWvccmQVCrV9iKr03HvH7t+T4lOvc+uB/b5bdtZzxW76LXveXp6Wt///ve1d+9eTU9Pa2FhwX0Pa9as0QMPPKBXv/rVSqfT5w0+vppeI/534Hd/tpsLv0ur35PAklS2rjavKzlIs9/D5/Dhw5qenpZ0LolgXaht3fwWM1Z71hLzKyXNlzt2raWJbRO/xJi953pLlAEAAACdrCZGJLUOpGs96/17T3uNBVvL5bIb57RYLKpcLrse0JFIRKlUSmNjYxodHXX3JHatb/G4aDTaMti0PeYv19bLHrOSS9az2uJjdm/jx5UseeFf3wfvJYI9BNq1oPcbIneKTbVrxBwcMHu1389Kr1uuNb+/Pv42KJVKajabrsTzcvdMK2m3HS41nrhSDwXb7zKZjF544QVX4nfr1q3auHFjS8nYdvNot4zVxkPbNcL2G6PbNi4UCpqZmdHExIQKhYKmpqZcMiKRSGhqaqqlNNr09LTS6bS7F15aWlI2m9XLXvYyjY2NKZVKtR3z0F+29OIYxf66Bfe75b7XC/nubvpEhLHgjbUmnp2d1cGDBzU3N+dqnjcaDcViMVc/2oJJ/skvmDmyL61dRtj4rY6NZWelczVqq9WqcrmcO/n6mUfrUnbgwIGWwWEt++ULLtt2rnZZxnYZsU4HXnDHvJgTyGrea+NC7Ny5U/F4vOUE76+3n+BZ7nMBFyt4bAUvTDr9KBs73tsdoxb8tf23Wq3q6NGjmpiY0AMPPNBxntZbqlgstrSUt2PFAtUmHo8rm826izm7YLN/VgquXWDbjtdcLqcTJ05oYWFB5XLZ/Yj649OkUim3fPtxs3OZP2//ItG68Np5zr+oDQ5Ofz3xxyPya59K5763I0eOaN++fTp16pRr1TA0NOQu9Gq1mp5++mmlUim95jWvaSmRZfucv62CrRf8C3BTqVTczUIsFnN1J621kM3f6rL6F9r+4Of2WPBiPHhh7ms0GqpUKioWiyqVSurr61M0GnX/pNYWN7Yf1Wo1nTlzRpOTkxoYGFAqldLw8HDLfuOXMrSbDb/3h9S+p4p9R/77jV/Oya4bbH+2a4Ngb4ybie3LkrR37143bd3epfPHdLjtttvctD8uxGrr3F/MOAYXwx8v4POf/7ybzuVybV/v1/MP/l0oFNx0pzEugoLjcRh/3AJJev755910uVx20+vXr3fTd9555wUv/0bmb9t9+/a56eA4EP533alBzqZNm1re42/3W2+91U372z2YzJ2bm3PTf/7nf952ne2mUZLOnj3b9jUAAFwOwThNuwasfrDdf73fit5vsW6Pl8tlzc/Pa25uziUh7L6mr69Pg4OD6u/vd+MfBhsCBxv12jp0Kt0tvRhwtXWx8q5+bK9dcDm4HfxSrp22mb9e7YK5th0sQF6tVltasftJiHaxvHbr2CngvNqEgX2HFhTPZDIqFAoql8taXFxUV1eX+vv7NTg4qMHBwfOqKnRa1sVYLgHTblt0Cpjb9i2VSspms5qamnLVb86ePauFhQWVSiXt2rXrvM9yMVba1va922PVatVt4/n5edfQMxKJKJPJaHZ21pXULhaLbhxEW0/bf+3+/dixY1q/fr16enraVgTw16ddvGAl7bZ3KIkI+2Dtgrp+ptBWyB/UxV/RdivfLjvjvybY2t2WK714kllcXJR0LlBdKpVcneharaZKpaLh4WGtX7/+vOXYSdHKMlnA//jx464ck5UvsYCElTyxlsp+EMM/EbUL5PvbzH9NMBlhJx1/fAgL4vmBFGtBOzc3p3w+704M0WjUlYtol8nyv7/g4+2mV5PZWy6z2+k97QS3TfBHw2rO+88FlxscvPpClwm00y4T3ulHb7XZ8Hbjtfg18JvNpqamprR//36Nj4+rr6+v47rNz88rn8+7TL71drDjIVg+rlwuK5PJqFwuq1QqKZFIuASGf/Hmn0f8z2Dj6Jw6dUozMzOq1+tKp9Pq6urS4OCgm4+VHbKa/X6dfpu/nT8s8G0t8+28WKlU3G/FhQR5O52Tgpn+YLL1Ui8+2qlWq5LOfS/xeNz1xOvu7lY2m9Xzzz+v48eP68iRI1pYWNDQ0JA2b96ser2unTt3KplMKp/Pa3p6Ws1mU6VSSb29vS0luOxCwz8f+60c2n0mf7/wWyZZWcJarabZ2Vk9+OCDWrdunbs4t3GTOm1bm45EXuzu7PekqFarOnHihCYmJnT69GnlcjkNDw8rHo9r27ZtuvXWW5VOp10A18ZO6u7uVqFQ0Pz8vNt2/pgoNkaE33rJvs/VlJ3yyzgtxz6bH3yfnZ1VoVDQrl27VlwOAAAAcD0Kxn78pIPF2Px4lN8gyb+XK5VKrsV3MBHR09OjsbEx9fX1uV7IFiezZfoVMvzSs8F1a9dw1e5PksmkstmsIpGIK5EevO8PNna19/uC953BeKe/rtKLAf9SqaRcLqfFxUXV63WNjY21jE8RTLqs5EKDwv48bZtYYHx+fl4nTpxw8cbZ2VnF43GNjo5q3bp12rhxowYGBjQyMtKSKPJ1SsAEdUp0Lffa5d7rv8Yab2cyGc3NzenMmTM6duyYFhYWNDs7q0wmo3q9rs2bN7t7xtVuQ/97WS72EIyt2L1xvV5XsVjUzMyMstmspqendfToUR0/flx9fX2u4kSxWFQ+n3exklgs5hqcVioVFQoFd++bzWZ19uxZrV+/Xv39/W6fbhejX67s0mpiqKt9vW/ViQj/gAl+ubbxbNBSO5htgAx7zg8eW6tGSS2lDfwTS3CZ/gnDXl8oFDQ5Oamvf/3rrrXv7Oys+vr6tGXLFhUKBVUqFW3atKmlVZL0YgbT5l+r1bSwsKBDhw5p3759ymazymaz2rhxo26//Xbt3bvX7aB+61M/kOU/Fkwy+NvSP5n5SQz/9dFo1A3MbO/L5/OuLIsFWWZmZrR3715VKhXlcjkNDQ1pcHDQdV8L1nEznabbfffLvaZdAPZiAvudkgo+C3J2Wk4w4bNaq02g4OZmgX2fneyth1StVls2gBlsMR58TmrdnyuViiYmJnTq1Cndfvvty+7XmUxGmUxG8Xjcjedg62LnaQvkSnKJV6uzb8kKO4dbwtM/Z5VKJcXjcTUaDZVKJR06dEjHjx9XtVrVnXfeqcHBQR09etRdmPll4PzBzKwFuSUr7HcgmUy6QPjMzIwKhYIikYh6e3vV29ureDzuLkaXY9+HXdxVq1XNz8+71vSFQsElby3oPj4+ro0bN2psbExbtmzRwMDAsstYiV2I2++ClfizCwHrSTc1NaUnn3xSU1NTmp2d1f79+zUwMKBdu3bpvvvu08jIiPsdsOSRJdxrtZrK5bLrjZJIJNTT03Newsbfd4O/BfY7kc/nNT8/r+eee06HDx92F+QzMzPu4ublL3+5Nm7c6BJifsLI5m2JJ781UrN5rv5rJpPR/Py8FhYWdPbsWZ08eVKZTMZdTB07dkylUkmHDx/W0aNH9apXvUpbt251vXW6urrcxfrZs2ddDVl/X/OTEHZMWkmmdkmsdsdksLdOsMasv02txuihQ4f0xBNPqLe3l0QEAAAAbgh+zCv4uPFjeRarC8bB7BrdH3Mtm83q2LFjmp+fVy6Xc72OpXP3qmvWrHE9pv17Zb8Rr8UV/cRAp5iQP0ZEoVDQ3Nycuz+0XtH+vNo1uvUTK3Zv4TfKDg7sG2xUbY9blZVTp07pwIEDOnDggHp7e3Xfffdpw4YNrmHfhTSQa/faYFIm+Lj9b/eVhUJBi4uLOnv2rGZmZnT48GGdOXNGi4uLKpVKGhgY0PDwsObn57W0tKRYLKZXvOIVGhgYaInrdloH/7F269PuMZteLsnSqRGlxVSOHz+u+fl5ZTIZnT59WnNzc676jM33gQceOK889Uqfo512r/OTcZboKRQKrofG8ePHNTs7q6WlJeVyOddDxu5Vo9GocrnceZU1bN9bWlpy093d3VpaWlI+n1e5XHbxG/+48ffXTvtY8DvxXxPsdXQhCbBVJyI6ZRCtpePS0pJmZ2d1/PhxFQoFxeNxpdNp9fb2KhqNanR01JXnsACXBRVsYFMLRHQ6UPwPaAG0M2fO6LnnntN3v/td5fN5NyZCvV5Xf3+/Nm7c6E5MnT6T3/WoXC5ramrKfWGpVEq7du3Srl27dPz4cdfjwEYs92vPdRpF3EpFBHtK+K/zAxx+qYehoSGNjo5qYWHBnfBsm1lL44mJCc3MzLigSDQa1cjIiAYHB10mb6Wd4kIC8Su9drVZWt9qkyKdWkL7J/iLcTHJC9xcCoWCC+r7F1FWwsgv1SbJnVNsoC17rFwuu7r80ovHezCRZz822WxWk5OTrvTMcvuoBeqtV4PNy7p4BruOWmDWlm1JCEnuB9k+Q1dXl2shYrXw5+bmdOzYMXfu3bNnjxYXF9VsNt0g1XZO95PMUmsvsHat1A8ePKivfOUrrjzO9u3bNTIyolKppJe+9KUrlm2x1g6lUkkzMzNaXFzU0aNHlcvlVKvVlM/nXaA9kUi4uqSTk5Nau3at0un0JSUi/As6C2o3m023PawkUbVa1eTkpKanp3XkyBGdOXNGO3fu1A/8wA9o9+7dLV1zpXMDfPtJm1qtpvn5eT355JMql8vq6+vT5s2btWXLFvX397vtbmMn2O+jbX/bb613y3e+8x0dPnxYi4uLisViGhsbc70u7Cbh9ttv18te9jKNjIy4z+R/r36iyz5nPp/X4cOHdfjwYZ0+fVrZbFY9PT1qNBquxujAwIDb55aWljQ/P6+pqSmNj4+719rAcgsLC5qenla9Xldvb6/reuqvh99SqVwuu3EdrJyU9S4MJhns2PPZ9Y7/Grugy+VyeuKJJ/Ttb39bjUZDL33pSy96v7kedCpjI0nf/OY33bRfY9U/72zZsqXlPX65mk49VpYrv+Svz2rLNK3mPSdOnOj49+TkpJv2S+zk83k3vW7dupb3Hzx40E0fOHDATReLxVWts88vExUsHxRcb+OXDNq2bVvHeV+pUldXg/+9+9vQxpqRzt+evmCy0vjf9cte9rKO7+9UBivYotIvzeTzS5z5x1RwXwMAIEzLNQJtV5WjnXq9rkwmo5MnT2rfvn2up7jdi9q1+fj4uAYGBloa/lmszA/+232l38i3XZDUgtKLi4s6deqUGwDYPkOtVtPAwIDGx8dd/DLYONrur/z76GBDY3+7LHf/Pj8/r6NHj+rIkSMumPwP//APuu2223T33Xdr+/bty7ZYvxTBElZ+0iGbzWpsbMwlZ6yHvB8Yt9LBS0tLSqfT2rlzp+vdHixvG9QpMSF17u3QLmbXLnZs+5EfC5mZmdGJEydUq9VULBa1b98+N+aCdK5nTiaT0fHjx9Xf39/SA2clwfX240LW6NLfd5vNc5UsrLLEmTNnNDU1pVKpJOnFxqLSi+M59vX1qaenR/l8XplMRqOjo9q0aZM2bNigs2fP6uDBg65TQLVaVU9Pj86ePatSqdS2dLbNezU6HceXUop41YmIYF03C1zMz8/r9OnTOn36tKtpbYEOC7xYWaS+vj6Njo5qeHhYg4ODLQGqRCLREqiyjWPliPxsT61W09LSkvbt26cjR45oZmZGkUhEPT092r17t3bu3KmBgQENDg5qaGjovJahxt9RLJjz/PPPuyBJNpvV7t27ddddd7kvLRqNqlwuux4eK7Wu9BM2K/EPHD9bZoFLayW6YcMGF0DKZDI6fPiwO8D6+/tbxlCwbdlpJwtmZpdbryup3c7e7keg3fuCLmTbA52cPn1aa9eudck9fwwWf7BfYwH04PFs5yNrdeGP32DHqQXjrOyctdZPJpPLnvDtnGS9MuwCzXqmWVDcfnDt+UQi4WqWW71BK4ckvZiw8M8j+XzejaHT3d3tLjpyuZz6+vo0NDQk6fwAsH8+totHP/hYqVSUyWS0d+9eTU1NqVaraWhoyPXySCQSHQeR8n33u9/VM88848r/FItFdx61JPP69es1MjKiSCSizZs3a/v27YpEIu636lLZtm3HeoNMTU3pueee08GDB5XJZPSqV71KDz30UMvAUnYRYz0qbF+LRqPK5/N65pln9NRTT7l989SpU5Kk7du3KxaLud9X285+qcVGo6HJyUk9++yz2r9/vw4ePKiZmRkNDAxo586duvPOO5VKpfTCCy/oxIkTmpqa0uLiog4fPqx77rlHL33pS1u2VbDVU7Va1cmTJ3X48GE99dRTKhQKSiaTrpZof3+/hoaGtGPHDvX397sxSc6ePaupqamWUlN+owJ/bI1EIqHx8XGXiG82my2DUtuNS6VSUSKRaDnO/ERh8LvzP09wzBfbd7PZrCYmJvT9739fi4uL2r17t+65554L31kAAACAa5CVS/ID/caPD7brfeCPe+gHhiuViqanp3X27FlVKhWVy2XXuM8aKO/atUsDAwMtQWGbh62PxRDtuWCPdJ8l/i3Qa+Xd/XEJo9GoUqmURkdH3T2U3wPCXhdcn+A2CW4fSS3rZ42ZnnnmGR04cEAzMzNKpVKanZ1VpVLR6OioK7XjlzP216GTYOyhE7/3R7lc1sTEhM6ePesa63V1dWlyclJTU1NaWFhwCZtqtap8Pq+FhQVJ5xps7t+/38UfxsbGVuzd0E67Btvt3h+sImHT/vdk29pixxMTE4pEzlV3mJ6e1tLSkvvcFpeJRCI6dOiQ1q1b58rk274YTCgFexH4946dvhtLSOTzeT377LM6cOCATp8+7UplW6PPcrnsejf09va68tnJZFJ9fX3q6upyjSaTyaQmJiYUi8Xc/uInBYNDJtg6LtcwvN33EuwR1SlWu9oG7qtORPitAa2G1aFDh/Tkk09qenraHcT1ev28Gv6lUklnzpzR0NCQZmZm3GAz/f39GhgYcDXQpPN3Kr82l+0gs7OzevLJJ/X9739flUpFAwMDetnLXqahoSHdf//9rktQ8F+QbSgLlhw7dkzPPfec6yK2du1a3X333Vq7dq1yuZx6e3vV3d3tWhtbrwQLfFgg0V9nO0n4J4NOX5Z/8ARbXAczcpYIOnXqlM6ePau5uTnVajUNDg5q3bp1Wrt2rTvpB0s/tSsT5f+9kpVOEKuZz3I7eqf3XmhPDL9LnP+adj8WJCKwku9973t6+OGHNTAw0HIRZcew35vLzzhbCSM7b1hLbL+ldiqVUjweV7FYdO8rl8vK5/M6fvy4stmsNm3a5BKQ7VoNRyIRt4xcLqfZ2Vl3zvQv/oJdAi07L72YhPDrUVqw1pbpD06cy+VcgN9+FK1LZzQadQFefzwdC8xbmShj5zQLXM/MzCiTyWhwcFC333677rvvPtfTzgblXk6tVlNvb6+6urp0+vRpFYtFjY2NacOGDdqyZYtuueUWrVmzxiVMrJSg/V6s1IpjJe1a1du2sKTM0tKSDh48qAMHDmhpaUn33HOPfvAHf1BjY2PuosH/HvzztSWKZmZmdPToUSWTSXdRXSwWlUgkXIk+/0LJehXYNs9ms3riiSd0/PhxJRIJrV+/XslkUrfeeqte/epXa3R01LVGeuGFF7R3714tLCy4rqPJZFIPPfSQ21421lKzea4k1sTEhCv1tLCwoGg0qjVr1mjLli2qVCoaGhrS+Pi4Nm/erFQq5faT/v5+bdmypWWcE/tnv7WpVEpLS0sueWTfod/L0UqAdXd3u3X0t6Ht/5VKxe3/1tLH3/eDv5N27NgAZ7Z9t2/frvHx8UvadwAAAIBrhV3n+nGgdomHdjEWuy63/+19lUpF8/Pz7p7V78kcjUbV19enW265Rel0+rx7AX98tmBw2l+/dj02bF3K5bKy2WxLENruAdPptGu8FIx5BbdFUHC7BBvTWoyvUqno9OnTOnHihLLZrKsSk8lk1Gg0lMlkXLC803bt1HOg3Xq0+45sm+dyOc3NzSmXy7mSxl1dXa4ccD6fd631gwMkZ7NZVatVTU9Pa2pqSkNDQxoaGmpJ1gTXr1PPh07bMbgN7Z9fst1fhr/f5fN5HTlyRNPT00omkyqVSpqdnW0pc+w33jxy5IjGxsZULpddWbBged926+KvR7ukiD1XrVZ1+vRpHTlyRFNTU8pmsyoUCi5OYvuhxZ3Xr1+v4eFhN25if3+/uru7XW8dK+Nk29sa4PnjJK60rTt9P8HvYzn+NlmNVSci7ICv1WrK5XI6ffq0vvOd7+jUqVMqlUquBWJfX58rd7BmzRoNDAwon8+7AMDi4qKq1aqmpqZcRqdSqWh8fNydZIIHh/1vAb0jR47owIEDrnXsQw89pNtuu82dMPyBOe2kttwGazabmpub03PPPecOqEQiobvuuku7d+9WT0+Pa91swTW/rJTtWNYSOfiF285kf/vLDSYh/NdY0NL+twyXdf3P5XI6duyY671hpZx27typnp6elkCWbQ8/e9wue30hAfmVsmaX03JJD/95/3MsV8bJn77QRAxuThMTE1q7dq0ru1AsFpVKpVqShn4A3oKZsVjsvF5RweSoBactMGoXBMeOHXNdVS1g3kkkEtHw8LCr12jzj8ViLshqQWJ/3BnpXEmnUqmkoaEhF7i1oG6wJ4QlIewz9Pf3q1KpaPv27YpGoyqVSi5I7LcuSSaTLevbbowHaxly4sQJ9zty55136uUvf7nGx8fPS64uZ9u2bW7MjE2bNum+++7Tli1bNDY2pvHxcfX29rpzs52LbRsFB/W+VP55pVwuSzrXo2RqakpHjx5VqVTS3XffrUceeUSDg4Num3d3dyuRSLgWQsbWLZ/P6+jRo4rFYrrrrruUSqX0ne98R7Ozszp27JieeuopPfDAA+48Z70L/JKIBw8e1MGDB5VIJJTJZNTf36+77rpL9957rysjYr9B3d3dKpVKevbZZ92YG1YW0O+BZ/vv448/rqeeespdoA4MDGj37t16yUteot7eXp09e1aStGbNGncBaCWkbJ/xW5lYCS1Lcti2jMVibmwR+x22z+snXuxYtONNam0ZZRd81qDC7+Vk29xahFky4vTp0+51yWTSjWdxszh69GjL3ydPnnTT/jnPLwU0MjLS8p6lpSU3bWNgSasvEbSa1/kleZZ7zi+5FCw75bPGN1JraaX/6//6v9z0cqXdbIwVSdqxY0fH13Vy5MgRN33mzJmW5/zxSfz1fOihh9y0f310o5Vi6lR+SZKOHTvmpg8fPuym/X3QL69lJQaN3/vr/vvvd9Nr1qxx0xeTxA6WZrJzo9RajqmT1fbgu5gyZjjnUsoPrIYfVAuL/WZer/MPqzSJbzUNXS7FxZzvL1TYnyHsYyHs/UjqXAYSnfkxL6l1PIRgPCnY8tpPQPgla6rVqhYXF7W4uOiu3SW5IOvQ0JA2bdrkGjn7Zc6DDWvtf7/xXbu/bd3t/qBQKLhre1u2xSj9sku23HYJiGAA1l+mvc8et89frVaVzWZ1/PhxZTIZSeeuH+bn51WpVFyiplgsuvXt1LDan3+nxES7+Jk1FMzn85qennaNH4vForuftx4qlvSwcYCtBH93d7cbzzGTyWh2dlYLCwtat25dS4n4oJVihe2C+51e126+ti3snnTfvn2q1Wpav369isWiGx/TbyBoDf9Onjzp4r8WFwg2CJTOL8sf3P/bJeusd8aRI0d09uxZFQqFlsbiNvi0/bMKBQMDA67hqs07lUq5z2LjGNt6WOM6KzHlHwMX0yDc36YX+/6gCyrNZCeLI0eO6NChQ64bVXd3t0ZHR12AfmpqSps2bXItA2dmZtwo693d3a5Uh9XkLpfL6unpUTwedx/Qv+m34IFl3GyglGq1qs2bN2vjxo1KpVKu9aK/cVYTUCoWi3r22Wc1OTmpdDqtTCajVCqlzZs3uxHG/XnF43EXlPFPKH6L4eAJJ9idys9s+q1e7UC3HTIWi7mdp16v68yZM8rlcuru7tapU6d0+PBhzc/Pq1QqacuWLbrzzjt16623um3pL1N68cQdPFFeCcudTFaTYet0Iut0AlrN8pfLIgO+rq4uNziu34PLTzzaRZVl2IO9oeyHIRaLuYsyq3lvx711c7TW58ePH5ck9fT0uB+oTmy8iu7ubs3Pz6tYLLoEgLUM8C/wgz+QVr7GTyDYe+31VnfQerpls1mNjo5qdHTUlYDyxwGSztVctB9EOx/6NzL2+2KJiGazqZGRES0tLenee+/V+vXr1dXV5RLNwbEu2tm5c6c2bdrkktF2EbtcKxb/B/pyngvsYtfOvfl8XidPntTevXt19uxZdXd36xWveIXWr1/vWjfY9rPEuH0vNr9cLudKV1k5vqGhIfX19elrX/uaG/Q6Ho/r3nvvVTqdVrlcViQSca3+z549qxMnTigajerMmTNKp9O6/fbb9cADD2hsbMztM9bzYnJyUqVSSbFYzAX9g+OWNJtNTU9P6+tf/7qeeOIJV8PyjjvucAkla4CQTqc1NDTkkkJ2DFgJKhs0XVLLOCzSuUT80tKSotGoNmzYoJ6eHjWbrWOw2O+dX/vTfqvtwjSTyejEiRM6fvy4tmzZoq1bt7pWPLZP+Bfxfk8Ju0no6+tzAUsblwMAAAC4UQSDmSvF2Oy1waoefjC+WCy6ZIAkV1LWxmjo7+9vKRHst2D37+n863U/5mOBZr+VvDXMs5b+fsNBK8uUTqdbYk/+/X4w9uT/HUzQ+PcEFvC2skYnT57U6dOnXQ/+TCajQqHg7vd7e3vV29vrtpXFH4Ot7jutS3C7B1k55MnJSR0+fNg11rA4qwW+7V5HOleCaWhoSOvWrWspIW0NymZmZjQzM6OlpSW37u3Wr916BR9rl2yybeontCzm4n9efyzjTCajAwcOaHx83H3nhULBxSNsoHIrF9bb26u9e/dqaWlJS0tLrtxvMLFiZZTsWPDjPsHPWa/XVSqVND8/r0OHDmnv3r0qFotuMGrbp61h+cDAgAYGBrRu3TqNj4+7+/F8Pq9jx46pVqupp6dH5XLZVcexhlG272zYsEF33nmnRkZG3H2xH0PpFJMNxoD8Y6CTTvv8cladiLDWjwcOHND+/fs1MTGhcrnsMmH9/f1uYOpUKqV7771XGzZsUCqV0vj4uE6ePKkzZ864zF6hUHD1uCqVig4dOuSyPn6WOph9tWCIlefYs2ePCxpUKhW3Qxg7GbTbIFYTbHZ2VgcOHFB3d7fm5uaUSqXcwDDBFqSS3BgR/gCX1pI2uL72Xj+rF6xbZr0UbD5+1ti2p524rBWo1VA/fPiw8vm8BgYGtHbtWtd9zZIXy+nUE8Df4dqd4C41yLLcCagTfxsGuxn587qQeQIX4sSJEyqXy3rpS1/qEp8W9A+2ZOvq6lK5XFYymXT7oiUnksnkeV1Ky+Wy6vW6JiYmdOLECR07dkzPP/+8S9aOjIy0JDo7XfhZMNaWb0mTRCLhyuX4PyL+OcjW0TLwnZbhl6Oy7Hs6nVYymXRJ0nQ6rcHBwZZj1P8RD/JL6VjX1FQqpU2bNrmSVFaebrWi0ehFtQq7nEHk4A+3JVtmZ2c1MTGhyclJ5fN53XnnnS6YLsl9Vvtn36klmLPZrOs+OzQ0pEajoXQ6reHhYQ0MDKhcLusf//EftbS0pO9+97tu/AVbJyuvuLS0pJmZGZ06dUpr167Vy1/+cu3evduVN4zFYiqVSiqVSu6i1PZV6VxrYRuHyWQyGf2f//N/9NRTT+ns2bMaHR3Va17zGt1xxx0aGBhwn2Fubs7VvbTEgPU6tISX/a4GGydI544Zuzi2bWaNBfyu1P6FqA203mg0tLS0pP/5P/+nG+8ik8loZGREO3bs0D333OPW13p72G+7f6Ni1wHWTdZazAAAAAA3inaBRj/usppApF9RpFgstjQysoZmyWRSPT09rny737DN5mEt+S1+ZtfffuM//57Rb/BrDdTsHtvufe2e2O4nhoaGXLUVW6Z/T7Jcw7bgNjPlclmFQkGLi4uamprSiRMntH79ek1OTmpmZsYNBF0qldyYuul0+ryxCHztekP4DQ1t2wVje9YT4vDhwzp48KAmJiZcY7lcLufu0davX6/e3l7XUKuvr8+1zt+7d6/27t2r6elpt5zFxUWdPn1aIyMjrlR8p+3hr4//fKfkhP/5LWgvvVhlwfYLe12lUtHc3JxOnjzpygmfOnVKi4uLisfjGh8f16FDh5TNZl180Rq11Wo1HTx4UKdOndKBAwf08MMP67bbblNfX5+7V7V7V/8zWJlh+75sP8xmszp27JheeOEFPfHEE8pms26Mznw+r3K5rFtvvVV79uxxMXS7796/f7+mpqaUz+dVq9V08uRJl7Czxok2jqLtu9u3b9dDDz2kW265RX19fS0lxJeL7V7uxpjLWfUdcz6f18GDB/X4448rn8+rXq+rr69Pt912m6rVqkZGRrRp0yYNDAyo2WxqdHTUBetSqZRuueUWbdq0SdlsVpOTk1pYWNDk5KTrNn7gwAGl02kXSPfLK/j1vaanp11AZvPmzdq6dWvLmA22I/gHbKegtAV09u/f71oS1+t17d69Ww888ICGh4fdTmZdt6w8kqSWjJKdPC0Q4md/bf0tsOInJ6z+tc3Ddn6rwVYqlVwdMElucPBoNKqjR48qn88rEolozZo12rNnjxt4tV1XIGnlzKn/3tVod6Lo5HIlCdrV7G63Pp16QFzIOgNmcnLSnfzXrFlzXldTO679QXQtO+2XXbALJjtP2YDPR48e1f79+92F0eLiokqlkgYGBtTb2+sGLOokEjlXmqmnp0cLCwuan59XPp/XunXrJJ1LBGQymZZSFVbn3rqh2gWf33IkGPxPpVIuON1snusWaIOI2XgRo6OjroW4P6i3CSYU/RYJS0tL6u/vV61Wc3X//bJOV6Jr/uXid6W10kenTp3Svn37dOjQIc3Pz2vt2rXas2ePS0JYjxnjt57xL/yPHTumM2fOqFqtanh4WFu3bnU9CO+66y6VSiU98cQTmp+f18TEhMbGxtx2tN6FS0tLmpubU39/f0uJQ9u37UKsXq9r/fr17nc5Fotpbm5Od91113kXmTMzM3rhhRc0MzMjSdq8ebN27Nihvr4+970vLi5qbm7O9aaIRCKuJqa1arGbCkt82MW0/W4WCgWXpLceFbZtbB+xY9HGPbHjZ3JyUk899ZT27t2rWCymyclJV/5wenpaBw4cUCwW086dO10PBzvGLZlkNyS2TW18JvsebzR+SRcbDF2SDh482PK6qakpN71582Y37Zdm2rNnT8t7/LI4lzo2y3IlmHz+efDpp592088995ybDpbE8cspDQ4Oumn/8/ifM3je+4Ef+AE3PT097abtHH0h/JJYfjkpqfW65rbbbmu7bteCSy0T1Om79rfHY4891vJcLpdz02NjY27ayhUGWQLX+APRb9y4cfUr24b/mYOfxS/35fPXf7WJ9tUeEwAALKdTLMePv7VrNe2XBbf3Ws/s6elp99sWiURco6REItES17Ke5X7Lc786iaSWVuX+uvnX8X4Lenut3avm83l3nd/X19dSpcSWawkP+0x+oN/vKeIv07aNNew+deqUZmdnXeOxEydOaGZmRsVi0a1bpVJxjZL9zxbsLdAuIWLLC7Zu959bWFjQgQMHdODAAZ08eVJzc3PuXtWW29XV5Rq6DQ8Pa2hoSIODg66yjXQu8G0Nyf2eBbbe7faJTo2h7fXt1rnd/mXb2ObXbn9YWFjQ1NSUyuWyZmZmND8/r2g0qo0bN2r37t3q7u7W4cOHXTDf4r7W8Cyfz7txRE6dOqXBwUHXyNMa4icSCcXjcSWTSTfWg5/8ajQamp+f1xNPPKHnn3/eDUZuDepsew0ODmp+ft6NC2KNBm3cDouB2nSpVHLra/fnfX192rhxo3bt2qU1a9a0DLbebrsHH2u3L/nbut1rOr13JatORJw+fVpPPvmkcrmcy8Ds3LlTe/bsUTQaVU9Pj5LJpLuY9w9Sq9+cSCRcy0Eb/PmFF15QOp12rYG7u7tdSSQLUlkwYWlpSceOHdPk5KQ7MOym1XZKS0D4G6NT4Lter2t+fl4HDx5UrVbT/Py8tmzZorvvvlsjIyPuxGMJAj/RYMGReDze0uvCP3ja9XawL9ICS1bewnaifD6vfD6vTCbjxuNYWFhQs9nUwsKCG1i02Wzq9OnTSiQSSiQS2r59u2655RbFYrGWkjB+Tw5/Bwz2evB1ylbac+0SHJ3e127+y+3I7ebvz9da6bZLLgTf12m603pfyIFj32sYltu+wW3mP9bpffaYZYn9x+3H1k7UVqMwk8no9ttv1/Dw8EW18A27fujVYLUCrSW3teqw84MlS2dmZlxXS7+bnLXAaDabrqdEKpXS2bNnNTMz47LxFpS11hpr167Vjh07Wlp9tBOJRDQ4OKj+/n7Nz8+39HSw5VcqlZbSTJZQiEQibnwI6cUAbrtEhKSWHz8715dKJVcjct26da6FuN9brN18/FYDtVpN/f39KpfLmp+fP68r7cUcq1eL/Q5Yl0u7qDx27JieffZZzc/Pq7u7Wy95yUu0efNml3zwy/P5vW3sN6RQKGhubk6PP/64pqam1NfX5xoB2Pk/mUzqlltu0eHDhzU7O6tDhw5p586dbhDlSqWiqakpHThwQBMTE9qyZYtr8eKvf6PRULFYVDqdVrPZ1MTEhGq1mubm5pRMJrV58+bzAsddXV3K5XLK5/NqNpt67rnntHv3bvX19Skej6tQKOjo0aNqNpvasmWLuyGwi8Zms+nGJ/EvJv192ebf29vrSjvatrbfV9vv7GLZlrG4uKjHHnvMjYvRaDS0adMm3XPPPeru7lYul1O5XNbJkyfddvW72lrZKOvxZPu2Jc2uh30TAAAAWK1gPXybbhdr82vV2+usYZXd49RqNTcQst132n21dK5hipVlsvtNP55m/HvETo2SgvGvYCzF7hHsntRifHYv1K7iSbsEQHBb+A2X7PNaWWO7fz59+rQrp+yXKo5EIi7m6pcF8uctrT7mYutlDc3s/tDWx3qYWIPvVCqlwcFBjY2Nufv63t5eV+rY4gexWEw9PT0t5aCj0ai7RwqO/9suFhn8Pv3/gwmVlRo02/sskF8oFFwsplgsqtlsanx8XOvXr9fWrVtdSWArb2TVHiwpYRV0jh49qlwup76+PiWTScViMVfyKB6Pu148dl9s+20+n1cikdDU1JT279+v06dPu/JilrSxe99MJqOpqamWShGlUsk1lrfv2xqu+99pV1eXent7XUP9NWvWuKSev9/6ibWV9pXlHlvuNau9F151hPHgwYM6ceKEenp63M391q1bNTw8rFQq5Q4S20H8A91OOpY1tC+vq6vLjVg+MDCgubk5HThwQM1mU7fddps7uC1IPzk5qRMnTiiTybiuSv7ObScaP/topVPaHaSZTEanT592JZkajYY2btzogjV+PW77DCMjI67kiGWy/JNfsGuQ9OLI8haotJ3bBlK1k9SZ/x979/Xc2H3tif4LkgCJTADMOXVOym1ZsuUz9q3r8YSaOfN66v5r9/XMw9R9Gt+5dcJYx0lWllqdu8lmTiBBIhFgvA+s7+qF3WCrJRm2Wv5+qlRCk+DGxk7AXmv91m9lxZINrKLe3Ny0VkycgJZZMg5fGxsbsx7g/qLpT+Dg8DSvWSasmeAHD//2rAvC85b1PF/3N/zA8c/17/dFl/V1F7Kvc9YJGdwm3zTBwf8HEwhMzPnzyweLg4Fnnjs8Vvb3921kT6lUwvHxMarVKsrlMvL5vLWM4c+Xlpbwyiuv4MKFC898cP8tBts4GS6z/eyVz3NrY2MDH330ER4+fGit60qlkvVXjMfjNp8LJZNJ62nPinFWKezt7aGvrw8TExPo7+9HOp22kVvsee/5SoFSqWTXKR47TKQWCgX7m6OjI2xsbGB9fR3pdPqZvobA0+PXJ7GOjo5skqdwOIyRkRGbFBs4nYyW75vHC0dQMNESCoUsEQucfjkol8vY3Ny0Ybi+bQ8AqxgIVkp8X/ELj/+yefv2bezu7qKtrQ1jY2O4dOkSkslkwznFY4RfuDmBM8/nO3fuYHFxEeVyGV1dXUin07adGYCPxWINc0EUi0X09PRgb2/PJrL+5JNP0N3djatXr6Knp8c+K9vb261PKSe54nvZ39/H9vY2JiYmrG2W19fXh3fffRf/3//3/2FpaQkHBwd4//33sbCwgCtXrlgv0osXLz6T+ACeTih9dHRkX26Bp4k03gxwNEcymbT3ygm+iK2leG2s1WqYn5+37cH3fv78efT19aGjowNzc3N4//33sbq6ip2dHQwPD9v6cF/yOGaBRCQSQTKZtGGx37WqX0RERETk+8LHN/x92PMCkj54zHga4xL8Ds17R97j7e/vIxaLIRwOW5cUxjqadR7h73i/G0waBNeRj32BHkcf8L7WtxL2rwE8jQ8CaBoY97FIvk/GDba2tlAoFBAKnU76XCgUMDc3Z3EZ3lv40fRs6XzW/K/B7R6M1fh1YRKiWCxicXER8/PzKBaLFgxn2/3u7m5LQgwNDaG/vx+xWMyC4LzX5N9xBDvbWjGB4mOywSLos7ZbszhTsOD4eUXLtL+/j1KphEqlYvuXseJEIoG+vj7kcjkrlu/u7sb8/DxOTk4aYq08bguFAiqVCqLRqLU5YqwlHA7b5OoM/rMAsVAoIB6PY2NjA8vLyygWixa347HBQtPV1VUrQPej+fn+/bbia3R0dFicqb+/HzMzMxgbG0N3d3dDEXzwePg2cdrg8eeX+W28cCJiZWXFLg7Hx8c4d+4choaGEAqFLGjO9gg+cOSDWPwZExbJZBJXr17FrVu37ISrVqtWzesTAdVqFXNzc1bxODw8jN7eXjvIWW3MAIBPfvjAtVcoFLC6umrVtzMzM7hy5YpNiOpHE3R1dVmg8ODgoCGQ5oeB8e98lTSH3GxsbGBjYwOVSgX5fB5ra2tWnRyNRlEqlVAqlaylRTgctlYqnMwEgGWO29vbkUwmcePGDYyOjjZUY3Jb+57VPlDpNQs6+krUs57/ogkNf7AHs5zNXr/Zhems9fT/bnbRavazs9a32XK/TrO/e9H3c9ayyCdbgvOeAKcX2J2dHfvQ5Qgbbm+2+FpaWkK5XLbn5/N5lMtly2bzGOYFk8Hjvb09xONxmwy+2Yd6s4Dwd03wfF+FQiHL+DPrzy8wCwsL+MMf/oC7d+/aNaqrq8t6K3Z1dSGbzdr2zufzAGABzMnJSeRyOWxtbeEPf/gD1tfXkUql8Oabb9rEVLFYzCaqOguD+ScnJ/ahyGsijwm/v1jVwH3mjzO+B+BpOzQuY39/H+VyGTs7O9bDkz8/f/48RkZG7HWYxWcCgtdLAFaRvr+/j1AohGg0iq6uLrtO8QsPA9D+S83LkIjgnARtbacTkN26dQsrKytoa2tDd3c3fvrTn9qXFv/Fzn9W8j23t7dbcmtubs6G0E5OTmJsbAyhUMg+IwBYdQYAC8LzS/Cf/vQnPHz4ENVqFVNTU7hx44a1OKzX67YvWanBRFa9XsfOzo6tTzDwD5y2C/nZz36GXC6H//W//hcWFxft83tpaQm1Wg3RaBRXrlyxzzHuSyZsmNSq1+v2RcuPQPQ3BRzKylEU/ljlF2SqVCqYn5+3z/CrV6/ixz/+MZLJJNrb261yhgkefpfxrdW4jXkccmRlIpGwkZR7e3vPPU9fRn4bfPzxx/Y42EKGhRxAYyugN998s+nPgb/MCDrfigkAHj9+bI99myPfMmlhYaHhby5cuGCPf/zjH9vjN954wx4/77343/lrrd+2L8qf68F9sLq6ao/fe++9F1q3F/FdWyn9ufnt5luE3b9/3x7fu3ev4W98Et9/n3nnnXfssT93fXsxoDHJ+F3bSfnHzzsGfDsmz7dmyuVyL/T634f9JiIiLx8f8zgrNhP8Ps9YDAP2/E7PwDxjErzn8PGnzs5Oa3vDbhjNAvFcHz9psI8/8h7Grw/vZzY3N60Ymcthext2L/DxQLYR9q/B+FqzbcPfMfi/sbFho8xLpRIeP36MpaUlK75igJr3zbzP8gkPrmuw1RV/F7w/ZsCbhd07OzuYm5vDRx991BBzZeV/X1+fzdE4ODhoRef+3qq9vd3uKbn9Dg8Prd0U71+bBb99e6mz4oPB7ekD6s+LM/nt4acDYDFuPB63kR7d3d0Ih8PIZrMWrxkZGUFnZycePXpkc5gw9s14M+NmnGODx2Z7eztWVlYAnMZ1GVfjqB/+HfA0gcWiYSbbqtVqQ0ce8sk84GlcOh6PI5FIIJlMIpfLYXh4GENDQ+ju7kY0GkUsFrO5DoOTu79oHOWseOpZ14BvEkt94UQEM1t7e3u4ePGiVeBvbW1hfX0d4XAYk5OT6Ovrs+yNP5j8BBn8kh8KnbYDicVimJ+fb2h5wBnjOZSpUqlgaWnJ5mhglai/QAQzgBzaBDQffpLP5xGJRNDZ2YlMJoPr168jm83aye8rgE9OTtupsO96sVi05+zs7ODw8BATExPW45w3vTz4OVEK+74zOcHq5nA4bJPT1Go1y8x1dnaiWCxalXOtVmvoizc0NISZmZmGHtl+VEbwIHmRE5j/D/ZmI3+AMfHiT3zug7MSHMFlfl3G+izBzKrn22L5D4tm75eJKn9hfBG+DdeLJE++iWD2mBe8er2Ora0tOxY2NjZs2NfW1pa1DWPAuVqtYn19HZ2dnSiXy6hWqwAaW5kxUOw/+NnrbmdnxyoTmk029HXH0w8NP4Dp6OgI6+vr+PDDD/HgwQNEIhGMjIxgdHTUPhA4QRCfz+sGR4gxKMohm9vb24jFYojH47h48SI2NjYsuMoEZzP8EsbrFodVArDjh1l2isVimJmZsXlntra2cHh4aMEaHt9+NA4Dx5zcK5PJADjtDb+6uooLFy5YgoHXfuDpdckHcvwXC1ZT7OzsWIDZB1r8BMQvCw5J5SiEL774Avv7+4hGo7h8+TKmp6ftusO5OVgBwcQCvwDxHN3Y2MDDhw9Rq9UQj8dx+fLlpvMStLW1WXKhVqthe3sb6XQaH3/8MR48eIDV1VVEIhHcvHnTetQzYVGpVGwyMiaCOK8TE+VnjUwJhU5bhN28eRMjIyP43e9+hzt37qBQKFgSI5PJ4IsvvsDR0REGBgZsbpNgIgaAVQZxNFB7e7vNDcEJwfwNiv/s5nnDc5YTxO3s7KCvrw+vv/46stmsDYXe29vD9vY2Dg8PkU6n0dPTY/vDYyuyYrGInZ0drKysYGtrCzdv3nxpkmQiIiIiIi/irPsvH5T08ZZgUDkYgF5fX8fW1pbNy8D4Xjwex/T0NM6fP49YLNaw7GDcgYkLH6xm/IdFyQzw8+8ZH2O8kSO+ua4MSudyOYvR+fY2vhsKq9n9aAwfWwJO7wXL5bLFCfb397G8vGxz/fH+j214GMPp7e1FPB63WKhv+eNjnnyfwe3uR3BwexSLRTx58gR/+MMfMDs729BCuVaroaOjA8PDww0tpDl63Sd5mFgBToPi/r4rlUohl8shnU4DgC3Xd855Xscavp+z5pVoFtMLHhfcnqurqzbJM+8jp6enMTMzg/Hxcbv39CMKxsbG8Nlnn+Hx48dYWFiwWBu3J1tocRvv7e2hvb3dYjBso8zjgnNP+PkrGJ9kkZ1vt8RzhSNOEomETZrO50QiEVy6dAljY2Po7+9HJpOxkTOcKoExgGAxcfD+PXg+8d/Pi7n8ue5zXzgRsb29jUKhYBN79PX1oVwu4/3337dJXKempvCrX/0KAwMDdrL4A5MtF3xwKxKJYHx83PqjMRi2sbFhfZ+Pjo5sBEGpVEIikcDw8DDi8fiZQ5X4Gj4gHXR4eGj9wFjVywlhw+EwKpWKJUTy+Tzm5+exu7uLSCSCDz74wEY5HBwcWFaqvb0da2trltnc3d21CmUehLw4xeNxxGIxJJNJ9Pf3o1KpoFarYWRkBCMjI4jH45bUuXv3Lv75n/+5oZcYJ+xmSwnfxxp4eqEiHvQ+wB08yHwA/awKeP88//9mWVi/XJ8N9R8mZ2Xa/PL9z4NBfp/hZoZ5fX3dLnAM6nZ1dTUEVD3/4fWi/Afs8y6Oz/t5kH8fHOGws7OD5eVlm8NhYWHBkllMTnB+EbYN8hd7/p7ryosdM/rMcrOC/ujoCP39/bh06RKuXr1qLYHOek/BC9g3yYS+TFidzSBkqVRCuVzGBx98gEePHuHo6Ahvvvkm3nrrLeRyuYaKfv4/eH4CT4OaJycn2N7eti9MAwMDyOVyWF9fx9LSEiYmJjAwMPDcpBqrSjiBEgOoPB7q9bolDoDTD6NsNmvzOayuriKfz9uHmT9PWanS1taGSqVi1cKcvPrevXvY39+3kTb8sA1WwXBdedxwQiiOfGPlQHt7u/Va9HNX8PnfZu6SvzR++dvb28MXX3yBtbU1HB8fY2BgANeuXbMvCfwi65M0TBAGv1jt7u6iWCyio6MDvb29mJiYsGt/8PobrExaX1/HF198gdXVVRwdHWF6ehrT09N2bPLLIie25mdNsVi0zzJeX7hP+eXWB+vZp3J6ehrpdBrT09P4/e9/jzt37gA4PWZu376NlZUVTE1NIRKJWAuyrq4uRCIRa73I9811ZGGCP1/4GXt8fGxJPX7R4/ar1Wo2GVx7eztu3LjRMOEwcFoZPzc3h2q1ipmZGRuF5D9L+ZjHJb+Ml0ol3Lt3D+fOnWvaOk1ERERE5GXEWI//bh2cOLgZH5vjPQPbMhWLRWuh6u+LU6kUent7LVAcLDZuVvAaTEDwnpX3WP4+nPFDjqau1+v2Nwxis0jOJzu4fv5+1ndf8S2OOcJgd3cXGxsbVsC3uLiIpaUlbG9vAzgN5LMQmQXHDCBzNIQvYmzWeioY32pWIFuv1zE/P4+7d+9idXUVe3t7DTGgeDyOwcFBi0H6ue9YUM73WK1WbR7CYrFo3SISiQRmZmYwOTlpSY7gvmNcxCdufLyASaVgrNDHLYMjJvh7FtiWy2UsLS1hdnYWa2trKBaLNqdgNptFOp22WIdPkLHwPh6PY3R0FF999RUePHiAjY0NK8JkssC/JteFSS3/vphQYEzcxy95LAKNE63zPjOdTuPKlSuYmJiwCdVDodOOFWyXFY1GGxIPPEYYZw+eh82SPHRW8qFZXDb4s2Zx4q/zwpEcThDd09ODRCKBQqGA5eVlbG5uYmVlBZlMxg4sv3L+5AFgwShm8Or1uvXuevDgAXp7e22oEqskDw4O8PDhQzvQ0+m0TXzJg48BFH+gc2NyZwTt7e3ZCIWjoyPMzs5asqG7u9sys8fHx3j8+LEN2T86OsK9e/cse+t7uwNoaDPCE5ajLrLZLHK5nJ3s2WwWPT09iMfjFnhiAJETlXIS2Egk0tAWgsvkRcpvV//euU2aVbTzgh1s3+Q/YPgzZo0ZBGRrDv/aQT6wDjzNpgYP1mYHtv99s2xd8MLGFhlfffUVNjc3LcgOnGavL1y4YNv+rMTBi544DAjyosEehsH1PmubNMOqXCbA8vk8FhYW7Njnvl1bW7PhYtx/DBjyos6hWBxBxGAacchcNpvF9PQ0UqmUnafxeByvvPKKVQPwonfW+j8vefVDEovFUK/Xsbq6iuXlZfT19VlleTQaxejoKN5++2309fU9E3APh8Oo1+t2/Hus8PZfQqLRKCYnJ9HT04Ouri6sra3h0aNHmJmZOXP9Tk5OrLKE1RTBid2r1Sr6+vrs3/ziUS6XLXjKUTP+muZb69XrdaytrVn7j1AohO3tbRSLRQwMDKC/v9/6J/rkA5dJvL5yVAg/GDnK5OTkBNPT0zb5Mkd1+OvT9x2v2ewBur+/j0wmg6mpKfT29jYMUfZfaPiZ5YfBMunI6pm+vj5ks9mGkYPBAHgkErGRdbVaDQ8fPsTs7CyOjo7Q19eHH/3oR4hGozZXEVuFcZ/wtWdnZ1GpVKzooL29HZ2dnUgmk/ZZQP5zCDhtGfLKK6/YF7hUKmVzNXCCtEwmg7W1NeRyOdRqNUvOj46OYmBgwFoMcoRDvV63z6JwOIyenh47t3wbMN7cHB8fY2trC1988QU2NzfR29uLsbEx276Hh4eYm5vDZ599hsXFRfT392N6etrOHT/BOyuh+PnPEWidnZ1YXl627ygiIiIiIj90wZiNv6cJdujwcR7/fB+A961zgnEhf1/p4w6MiQTjX/5v+Tz+Le9nGF9jkJdxEd8GyceOgsFv/xoMQLNLytraGtbX1xEKhbC4uIjV1VVUKhXrXFAqlawFEGNy/jV9IXFw2/r1+boYTKVSwcbGhgXm9/b2LNnCdblw4YLdx/u5EPx729/ft3bznE+QxdbxeNzuT30iIhgnDFbjN4vLNStG9gkhfwz5BNfe3h42Nzdx9+5dLC4u2vycbM2UTqeteJzrxfVhAoCdGSKRCHp7e7G6umr3kuVyGZVKBZVKxaYn4P0875153Pv4iZ+2wMdlGU/l9mMxaSaTwcDAAC5evIj+/v6GkT3+fp3xAp+0Cm43vz2bPScYqz1LMPkX9E1jgC+ciKhWq1apWK/XcefOHdy5c8eqZ4eHh9Hf398QLPdZleCKceeUSiV88cUX+MMf/mBDXTjCYXh4GCMjI9jZ2bG2TO3t7Ta5iB9d0Oxiw4PyrA2zv79vSYiOjg589NFHVjnOyk8GdzmJtG8NxcBZJBKxfvCxWAwnJ6ejFXp6emyikFwuZ0Osenp6bBIeVlX67K3PELIalRWgfC5namcwKxiY4/KaZRW5zbhdGAhjEIcBFvbobm9vRz6fx+rqKjY3N9HV1WUTpLKvWiqVsuFAfiIh3+s8uH+aXUioWdY7+G+e6P69ra2toVwu23sslUooFos2QfPg4KD1Qz9ryNeLKJVK+H/+n/8HR0dHGBsbwxtvvPFMdW2zYGmzD0QGwnZ3d7G6uop79+5hd3cXW1tb2NnZwfb2dsNQrePjY1QqFWuhxABkJBJBNpu19atUKgBOk3+c7IgXt0gkgsHBQYyPj2NqagrJZNKCa6FQCL29vUgkEpZdPev9NPOyBIm/qWw2i42NDdsfhUIBDx48QKlUwtjYGH7+8583JCGAp19yANicErxG+u3EDy9WzPf39+Pq1avI5XLo7+/H/Pw88vk8dnZ2kEwmm64fv7wxqclAK1vTsBfm+Pi4/U04HEZ/fz+GhoZQrVZRKBSwtbVlX+J4jWNgl1/wOCIkHo/bnBf1eh2Tk5PIZrMN1x0Grnlt4TWPI+T4Yc/rDVtI+YnAeT3jUNGXIdnFL3eVSgWzs7MWcM9kMpiZmbG5MJiwCSZpOFyTy2lvb7e2f/ws6OnpAQBLXtVqNVsug/X8u/n5edy7dw8nJyfo6enBT37yE1y/ft22d3d3d8OkcLwePHr0CH/84x/R2dmJUqlk13S2Mgqe7ycnjSMlaG1tDX19fXjnnXfQ29uLubk5zM/PY3Z21ubN2NraQrVaRSKRwNLSEm7fvo2ZmRlcu3bNkg7xeNy+MPOax4Qbjyd+ceZxdXJygtXVVRsRce7cuYZ5IT777DN8+umnWF1dRTKZxI9+9CM7z3gOscAg+IU6HA7bMc7Pzpfh+Pym5ubmmj5msp98S0vP99oPfvZ+1177nj/m/GM/JwQAfP755/aYw8uBxqRTcH4APy+Ev46eVVkUfF9+nQcGBpr+zfMsLS3ZY44uAp7dB37Z/rFfz2+zzf/c8wuctbyz9m1wno/PPvvMHvv9ub6+3vQxALz66qv2+Nq1a/b4/Pnz9vi7bqegs96P923mCfHXGd/GENBcECIi8uflEwHNEgr+OT4YG2zX7ote/bIYVE0kEkilUhYsbhbop2ZJAX5P95XufoQ5/8/iNh/g7ejosE4a/Dvei3Jdg6NAguvHZZdKJWxsbGBlZQWbm5vo7u7Go0ePUCgUrFAsFothZ2enYf4AvkawpZQP3vs4nl8X/zh4X8l5Qre3t1GtVm3+xUgk0jBnZTabRVdXlwXHud+4nL29PczPz1sRop/Hkfe5HNUeDPQHjyceO82KFpvt77OKXnnPyha8S0tLePjwITY3N601Et9DIpFANBq1eKs/BhmT6OrqQi6XQywWw9DQELa2trC/v4/19XUbybO5uYnt7W2bZP3k5ASVSuWZWGqlUrGYij82GTNlYoTziaZSKfT396O/v98KPDl6wxe4+kJ0PwoiuF38CJ6zCseD27fZMRXcP897zot64UTE4eEhUqkUkskkCoUCbt26hYWFBSQSCYyNjeHSpUt2wPJkb3YA+4vFwcGBjX4olUqIRCLWemh5eRmrq6vo7+/H+vo6FhYWUK/X0d3djfHxcUt6+BYRzSr+uWOauXjxIsrlsmUm2RoqFovZ0CgOp+KBxZOfwd3h4WG88cYbNtKBQd5wOGw9vbjT/UiC4HAkBvqYoOHrVCoVfPXVV/j8889Rr9fR1dWFer2OaDSKwcFB5HI5G80QvBD64XP+AA1+gPgMcj6fx/r6OkqlkgVcT05OsLKygmq1isPDQ+tHHovFkE6nkU6n0dfXZy1HOPIDOE1gsc1KR0cHqtWqZe38tjnrIA4mIfj+/Acc92+pVMLs7KwNvWJLFPY3ZyYzEong3Llzlu3+NoHNSqWC999/H+3t7VhaWkImk8HVq1e/tiVHsGLATyD98OFDPHz4EGtrazg5ObFtV6lUkEgkkE6nEY1GkUqlcHJyYkPmeB4wyLuysmJZbvaMSyaTGBoawtHREa5evYru7m4biROPx+0YCrbyCX6Q/S3zQ9543ajVagiFQpiZmbEkhK9yZ3CU+wZ4NphCPE852osB11gshlgsZqMdnodDDROJBHZ3d61qPBQK2agHn8gIhUJIpVKIxWLY3t6298bf8VrE9QuHw9jb27MEJc+bQqGAo6MjpNNpO2aYkOZ1HcAzlRX8oPb4ZYLHJa9bvL7zA/+s4N/3xcnJiSVpfve732FpaQmpVAp9fX0YHh5u2E5+Em62t2LlPUeCcK4hJjU6OzttInTfgomYeNrd3bW2bbwOcv4RP3l4LBazBC2vrbu7u7hz5w52dnYwOTnZ0C4JgH0+BN83r/M8PlZWVjA3N4fJyUkMDAygt7cXPT09uH79Ora3t7G2toYnT54gn8/j7t272N3dBQB0d3djY2MDDx48QDgcxs2bNzE9PW2f03xtjqpkEoZfipmE4NBoHrtMuOzu7mJ2dha//e1vkc/nkc1m8Ytf/AIXLlywL6k8Bru6umwEBD+zOJndzs4Ouru7G6qwRERERER+CHwM46ziUf9cPt9312Dcq1arWTU9OzwwphFsSeQ7Tvjl+nUCGkdK+Pia/zsG+Q8ODlAul23OTSYheO/SrD0u7438fZAvmPOtpVjIxYp8xg0WFxcBAIODg+jr60NXVxc+//xzixkwRsdRGSwK9V1feG/Ibc//836Z79nHAavVqo1ELxQKVojNziuJRAJ9fX0W6/Wvx+Iy3l8Vi0XcunWrIT4aDoeRTqcxMjJiRcp+smquYzCJFExmNSsq986q5Oe65fN5zM3N4fbt2zYRtz92/EgHzj3ZbDQAEwvsWtHT02PTELBDAVvBs1V6rVZDoVAAALvf3t3dxaNHj6zVv48D9/T0YGBgAOfOncPQ0BCSyaTFCXgO+FEbftQH31Ow/VXwHOXPWETvt20wttpsuzbb9lyXZvHBZst+nm+UiODkoezj3d7ejt7eXly9ehVXrlyxeRK4IsHKYAqOJhgcHEQ+n7fAFbNW29vb2Nvbw+rqKra3t3F0dIRYLIZMJtMwmaqv2uXPggd6MyMjIwiFQjZsikEKTn65vb2NjY0N60nOSW2Ojo7Q3d2N6elpvPPOO7hx44YFDX2g31dp+gAFL6p+ZzHz6S+UnH1+dnYWOzs7dvAxe8lsMS9IbL/jK9tDoZAFpRlc5oWW68W/XV1dxe3bt7G5uYm9vT278DDY1NbWhnQ6bS0vmOHjMCgGuvr6+jA5OYlwOIxCoWD7MRQK2QThuVwOExMTyOVyDS22vK87iIPV0ltbW/jqq68QCoUwNDSEcDiMWCyGjo6OhjZKCwsLiEajmJ6etuPomwaO2L++XC5jZWUFn3/+OUZGRtDb2/tMf7Xg8DOq1WpYWlqyXn1zc3MWDK7X69amixOS9/T0IJVKobu727LXXD6TMLOzs9jc3MTJyQn6+/vR29uL0dFR9PX1obe3FwcHB+jv77f96BMOfvhcMGHyIn7owbf+/n6srq6iXq/bnBDRaBQXL17E9evXLYnjK4L5IcwPC18p7ie95jWMbdh6enoQiUQaRjTw+vQ8iUTCkgqLi4v2xYZzjTBASxxFwSQLezz6Vl5cRigUapjQt1qtorOzE/Pz8zbBdHd3t71HLp9za/B6yKC6HxkRCoUsYclRcalUyhLb/AD3182XASckm5+ft6qbK1euWEslVpDw/GMSgl9y6/W6JbCPj4+xubmJx48fo1wu25eUk5OThmUApxXeDx48wObmJiqVio0M29/fRyqVwk9+8hP7HM/lcs/08mQlz5/+9Cfcvn0bFy5cwJUrVxAOh/Ho0SPUajUAsGt3sO1bPB63UT9HR0dYXl62RJWv3GUidGBgAJcvX0atVsPW1hY++ugjfPXVV/Ylb35+Hn19fTg5OUE2m0VnZ6cNiz04OMDm5iYODg4sWcB14+gjJqWZwD04OECtVsP9+/fx5Zdf2uTc165dw9WrV63dIrcr/zb4RY/HPPcnADtPg1XqIiIiIiIvo+cVjQYF5yzwczcw7rS5uWlzCgJP4ySsEGdczBeN+hEIwbiZvxfxAWz/mHFD3k/75bHbhL+P9yM4yLdJ9+/VB/a3trbwb//2bygWizg4OLD/YrEYbty4gYmJCXR3d2N1ddXu930hEyc+ZjCccQSPFfZ++zG2x8dMIGxsbOCLL77A8vKytVpnUXV/fz/Gx8cxMzPTUEDuY0O8P9/b28PGxobd6/jtkk6nce3aNaRSqYZi4a8rOD6Lj5f62G6zoi8+rlar2NjYwNLSEra2thrmYAyFQnbPxnmIffzYF69zu/rfc8JwHg/ZbBZDQ0MWq/Dto9llYm5uDvV6HQ8fPrTkB+/rx8fHcfPmTZw/fx69vb3WecInnoBnk1z8e985IpjICR6fz2vZ9F1x3/hExYt64UQEK1crlQoODw8xMDCArq4ujI2N4eLFi9aCiG2OOPko/+OB5DOTPDCYiNja2kKxWLSkx/7+PkqlEjY3N639AYer+Kp4Hzj1FyNWm/L1g8LhMAYGBpDNZtHf32899VdWVizIkcvl7H3fv3/fWkOk02nMzMzg0qVLyGQydjFkrzmfIAlmMfneg+0rfGsm9pW7e/euzc/BlhMcScCqTvaEZ385TizKSU2q1ar1MQuFQtYihpPahsNhO3Hz+fwzWbtsNovu7m4kk0lkMhnrKc7k0N7enrVqYYDx8ePH1tueLWUYnOIFulgs4vr16xgYGHihUQnBDLgf2cFtWCwWsbOzg7W1NaTTaVy6dMlaJvFDIJ/P4/j4GN3d3RgYGHgmKfQiGID+8MMPUSwWce/ePdy4ccMC/M1GcPjl1+t1LC8v48MPP7RE2/r6OtraTud36O/vtwwp23lFo1HbL2xrw0DdvXv3bNRKe3u79ZQbGxtDf38/ksmkXbD8iBwGEZslx77J9vim2+9ltLe3h0KhYMd4IpFANpvFzMxMw7wjABpGhjFhxPOflR/EFnGLi4uoVCoIh8NWmV6r1dDX14dEIoGdnR2bjLqrq6vpOvI6UCgUkE6nUSwWEYvFcHR0ZG09/KTCPHeq1apdG9hXn/uUCYOTk6dz8fAad3R0hHK5jHq9jqmpqYZrYTgctoA1X4vHGavVfbIDgLVTOzo6ahjtw4Dy877MfB/t7u7i/v37NqppcnISly9fbpggC2j88uj3D7+IcpvyCy0A26/8e/63t7eH2dlZfPrpp8jn83at5/4cGRmxZIAf2sm2i0w23b59G19++SWSySQmJiaQTqcbrmVcbjOsGOI1l5/hQ0NDDTcQxKQBR35lMhlcu3YNhUIBH374IW7fvo2NjQ2EQiEsLCxgfHzczit+zgdx3cLhMKLRqA2x5ZfDzz77DPfv38fi4iIODg7w3nvv4c0337Rz2Se+wuGwJYmCrYc6Ozuxs7ODcDiMsbGxM0dgvuxYxQWcXguJk9bTG2+8YY+npqbs8XcdwfS89jZra2v2+O7du1/7HODs9lKjo6P2ODhay7djOqu1Uitb4pRKJXs8Pz9vj/3+CMpkMi1bn1bx1xXOzQYAX3zxRcPzPvnkE3scbANHFy9ebPibn/70p/b40qVLTV+/lS2oXqRNEwA8fPjwa5/jj0GOQhYREWmF591/+Q4cQGNcgEFtjvRmEezm5qbdL/DesKOjw+57fYEkl8V/c7S4/5n/fzA54Uc38D6EBdGc05UFTWzN5EecB4PhwY4vDEIfHh6iUqlYS2UWdx0fHyOZTKKvrw+XLl3C4OAggKffV7htOFrk5OQE6XTaupAwGO3fpw9Ok48p+sRIoVBAuVy2ESg+wTA4OGgtmRgvYotgLrNarWJtbc3a/DIe4gvVr169aqM8uN+bdasJHlM+hvt1IyD8svzy/CiF7e1t7O7uWqKEsVgANjk34zG+W40XLHLnujRL/PC9+nOA7X8LhQISiYTFUrjv2OKe25vHIs8Trg+PW1/o7kdE+O++LOw8K2kTHG3ybTxvFISP5b7oa7xwIgKAZcHGx8cxPj5uB+nGxoa1JQme8Ax6BvvD+VECbB2Tz+ct0MaRD8fHx8jn8xYQYLWlT2z4Fkc++8aD46yqbn/AHx0d2cQtS0tLVrXLeQV6e3uxu7uLpaUl67fPIVMMiAQvSs36gXFb+JZSfJ7fbkdHR1hZWbH5Any7IW6fvb09PH782KpC9/b2UC6XLTDjJ7/Z3d1t2Ba8KDL4yEQPL4Tsz9fb24vp6WkMDg5aKyAfUK1Wq1heXsby8jLW1tZQqVQQi8WwtrZmc0sUi0Xb1rFYDJ2dnTabfU9Pj7W38JPzeMGD2h/ofpQIg2r8EABOb2hHR0eRTCZtWBLnkPBZeH9MvIhIJILp6Wk8efIEu7u7WF9fx29+8xsLNvoWTdzOPB7ZW+/evXsWfOZxNjY2hpmZGRuy5yfTYfslbp9yuYzHjx/jyy+/RKlUsoAlRymdO3cOnZ2dNh9JsOLAV1D7D3n/fz72HwwvWzD4z4UfFO3t7ZaUYzLLVzAAsGOS1xEOAwwmIfihtbe3h88//9zOvYGBAXR3d9u8PDzOP//8c5w/fx6pVKrpOkajUQvgM0kYDoexsbGBYrGIdDptrWkA2PU3Ho+jWCza6AU/aoHBZODpMRONRm1ek3K5jHQ6jfPnz9uk0kyiALBtFjy2mMzwX4gODg7s+sZkDJ/DL6i8zn/fWzMBsMmyuru7US6Xkcvl0NXVZdvTJ+/5xYLnMT8LOKqE7QK5/dhf0l/varUabt26hf/9v/+3BYjj8bid8/F4HKOjo+ju7rb2SP5zi19YmcgYHh7GwMAApqamGvYH+YIAfy1hCy8ANrfC8PDwM3Oo+G1A7JfZ1dVl80Ftbm5icXERKysrWF9fx/DwsCUuTk5OhzCfNQKBE33ncjn7PrG/v4979+7Ztn7jjTfw4x//GH19fXbt9kNh+d3Dj+rx24GfJZxgL1i1JCIiIiLyQ9Ss2joYU/Hf/xnc9hX8LN5jW2kf4wsuP5hsOCuO4WNx/Bt+r+c9eSQSQbVatb9jQSDvO4Gn9+tcZjAYzcTIzs4OVlZW8PDhQ7v/Z9wvl8tZ0R4L/7gNeN/uY5s+aM7XD25Xvnf/O/8f44GPHj2yuKCPP3JuCN53+Sp73gft7+9jc3MTCwsLePLkCZaXl22SZuD0fr6npweTk5MWWPfHgN8nZ8Xdmv3cJ5KC+8+3XAJgXVk2Njass0u9Xm/YNpz7IXjMNlsHPwqH+9/HKP36BRMRbNHP7cljiscSt3s0Gm36nnjc+GSR3+/+ePc/43oGz4Nm505wW/ttcVbCKLjPgj/7NvHBF75b7uzstGpbJiAeP35sPccvX77csLO4w4GnWUK/w7jSHI7U3t6O7u5u1Ot1bGxs2E09gwgciRGLxZBMJhuyngx0cIcxq+k3JpMFHqt5K5UK7t27h0qlgmKxiHK5jNHRUfT39+Pg4MDaUTHoUSqVkE6n7WT1kzPz/fqf8SLlAzV+9IMP0jGAVygU8PjxYxv5wIpljigol8v4/PPPLcHQ2dmJzc1NG1HC1+DoCn+h5OsyeREKnQ5VmpqaQmdnJ+LxOIaGhnD+/Hn09PTYpMjsv82+afx/X18fJiYmEIlErMqULbq2t7exv79vE9dwyNHOzg6i0ShmZ2eRy+UwNDRk+5EnbfDDhO/fB9B9MDKVSuH8+fNYW1tDR0eHjdIIhUI2gS8rW/f29homqPymwuEwpqamsLS0ZC1THj58iI8//hjDw8MNF+G2tjY7ZzhiZXZ2Fnfv3kW1WsXJyWkbpTfeeAPj4+OWTeYyeOzwwsUPqkqlgqWlJZTLZezs7ODg4AA3btzA22+/jZ6enoYkFxMY/sOO7YGYAPIZYZ84/CaafVn4oeBoJx7DDOr6pBOPL39O80sEzxkfdOV2Z9ITgCXs/NC7TCaDhYUFm7+lmVAoZIlRfoHi9ezhw4dYWFjA66+//sz+4RwUTFDm83kAT6szgtUMPJZ2d3eRTCaxu7uLgYEBjI2NWUKR75Hvj8e+bzvEZfFY5IewTyjX63WbG4fXhJchAQGcvr+5uTmrgM1ms5ienm74LPKTdfP9+SoSf+0+OTmxCiHgdLQFW/adnJyOVrl37x7+x//4H9jc3LQvXPxyDZzOczIwMIDp6Wn7gkscmfPkyRN89NFH6OrqwtTUlPX7ZDKcCTUmooPVK77tGNsyFYtFDA4OIhwOPzOPTrDqnJ8BTL48fPgQ29vbAGCBfn5xZlIsGo02fHHyiR2+L7ZdPDg4wOzsrLW9++Uvf4kf//jH1gqMf+cLGlhN428Q+FnK4d3BlmciIiIiIj90ZxX+Niteahagps7OTiQSiaYFlMHXaxb8bBZc9s/zIxjK5bKN9Od9S3BkRzBA698nA8gcxcDuIvPz81YMxgr3aDSKsbExTE1NIZFIWEyLXQCCBXu+ip8Fa349+Njfe3D9fNKCAfr5+XmLpQKw5ScSCcTjcWv36/chl7W7u4uVlRUrCNvZ2bH7dN9und1yGP8MJguaVcufVSzuA/TB9kP+vpj7rFKpWGE0J5ZmjIvxBY52YUzNdwfxxyUD/T755O///Hb2I1R4LPA+nXFiPyrDx8IZ7/D7j0WBXBeuo3+uL8zktmp233nWCP3g/jgriRg8toL75+sSHC/iG7VmqlarKBaLePToEba2trC5uYkrV640VAf6oTxA4wzznODUZ37a2trQ39+PBw8e2InsM0JbW1sW+GLPOFY++qFV3CD+9bjTgjua1tfX8eTJE6yvr1ubpra2NkxMTFjvNga07969i729vYYgEAPZTDywxYU/aThsyQem/Xr6LK3vL7a5uYnNzU2raO/v78fS0hKKxaK1LWFLJPbLZj9x9n3jsK9CoYBYLIbu7m7s7e1hYWHBLnxct4ODA2QyGdy8eRO9vb3IZrMWqGJgiO/VT2jM4BjnYuAk4wz61Go1q3C+ceMGjo+P8eGHH2JnZwednZ0oFovWHouJHn8SBw9qXoj9z3lCd3V1YWZmxiZ9ZjYyFouhp6fHRkIwuZTJZJ6pXH3Rk4jzo1y4cMHmwSgUCpidncX6+joGBgbQ2dnZkElnn/4HDx5geXnZ9gFH+WQyGfT29tokvTwuWB3NIYj+wnh8fGztmE5OTlAoFGxSHA77YrKLCSUmk3zwl1W+3Pa+ZUyzi02zbOgP3fr6Omq1Gmq1GvL5vA3dZHKso6PDqsB5THKfcbsHs/M8Hre2trC2tmajCXgdAE6Dr8PDw3jw4AEAPDeBlkgk0N/fj/n5eQtA1+t166HfbI6JtrY2O17ZMqxYLCKRSCCZTFqVB9ens7MTmUwGmUzG3i+TIAzQslc/r8M81piMAJ7OPcHrCVtOjY2N2aTzvN7w+AXQ8OH8fccvfdwvw8PDz4wc4PZlgoLV9cHJ0Nra2pDNZpFOp1EqlXBwcIC7d+8ik8mgVCrh4cOH+OSTT3Dv3j0kEgmcO3cOyWQSt27dwsnJCXp7e21OIyY0GPDnZ1GpVMKDBw9wcnKCGzduYGRkBLlczj5jM5kMUqkUyuUyNjY2sLCwgMnJSRs6DDSONDw5OcHW1pYlE1599dWGOSKC+Lc8J373u9/hj3/8o420u3DhAgYGBmyStUQigePjY+zs7FhSnQkctnc5OjpCPp/H/fv3be4LJqX//b//93j77bfR3d1t5yvfKxPi/BLIz3U/UdjBwYG1AeR24vv4ofHtbnw7puB75fcOAHj11Vft8fPO1xdpVxNsA+ZbK/3617+2x/fv37fH/f399jiYAOvt7bXH7777rj32rYyC7W58EvHbtO/5ri1//D54GT97X7S9lm87NTs7a4/9Pg8uz2+Pn/3sZ/b4Jz/5ScPf+OOzlW20znJWmyYmW2llZeUvtk4iIiLfhQ/KB1va8L6NcQYG1nt7e5HP5xtiTJy/kn/He0W/LH4X9330fVzCvx7vqYP3VPV63Vr4cN3b29utyGpvb8/eT7CIOvh+mYDg3LKc97ajowPJZNLmEnjttdfQ09NjRdScY/Xk5KTh9YDTeBfbKPk4jI8f+uA337vfToyrbm5uNmx73pPHYjEMDw8jl8vZnH3BeTzYZmphYcFaibM4m21vL1y4gB/96EdIp9O2HsEEg4958t8+mdQs0M1jwse8GKPyBdb7+/uYn5/H559/jsXFRbtHBGDdSMLhMLLZLHp7e63DC48fxip4r837Pm4DHkc+NunXKZi8YJFlW1ubHc++KJUt/xcWFnD16lUrOg3GinkMd3V1NSQHeCxz/bnMZgm54Dnq/3/W74M/C+7HZvv3296TvHAigjubcw0cHR1hdHQUb7/9NrLZrGV9fBDCVw7yIhDMRtbrdWstxFYiPFDZQmFra8suOOxBzmADgynNMm8MunEYEqv0qVgsWk+uXC6H8fFxXLx40ZbP5e7v79vojKOjI6sK9b24eNHkc/g7tj5hSybflik4vIfvu1ar2UgCzmzP0Qh+uNTJyQlisZhNcDI6OmpJir6+PvT09FhbJvbb297exr/+67/i4cOHKBQKdqJEo1G88cYbuHDhgp2c/gD3mU/iCcLtnU6n8Ytf/ALvv/8+FhYWsLW1hVKpZBWsnLyGtre3re0L31ezFi5es8SEv0iMj49jaGgIy8vLCIVCdqPHrG+pVLL2TdwnfrnfJMAZDoetdQjnRFlaWsK//uu/4j//5/9sVbo8aff393H79m380z/9k1WIp1IpnDt3DteuXcPk5OQzPRH9tvAfQrzYsTUOgzTr6+sATm/eDw4OMDAwgN7eXoTDYfT09FiCiYFOn/FlNX2zCme/Ls2cldH+IeG1olQq2Zcg/2EWzKpzuCc/JDmqiB8W3GehUAi7u7uW0OCoFX996O7uttZcft6FoGg0iv7+fvswKxQKyGQyWF9fR7VatWuXFwqFMDg42DBSplAooL+/34at+vOkvb0dPT096O7uxsbGhl0XGNSORqOo1Wr23hm09Z8RJycnDZOQ8X2yMsP3EeU1lH/HLxcvQyIilUohGo3aZxvfK79E8VznKC0mXJi0ISazMpkMXn/9dRQKBRSLRdy5cwdra2vY2tqykVG8LvX29mJhYcEmpB4eHsbbb7+N3t5eq5Lhfj0+Psba2hru37+PUqmEqakpa5vnqz0ikYgdf0dHRzaRNUcIBp2cPB0xEAqF7PsDh6MSj7FKpWLDmj/99FPMz89bguqdd97BzZs3sbOzg+XlZSwtLdnoNyateIzzGN7e3sba2ho+/fRTrK6uYmtryz5n+YWZn0E853zylyNS/M95U8Of9/T0YHh4GMfHxxbEblb4ICIiIiLysgve8/OezccDeB/L6nU/jwKDxbyv4PdqBs8ZT2NyIhhk53J5/+1fh9/BeV/i527lPSTjdFwe7w2YPOjt7bV4SzB4zvfBWE6lUsHs7CwePXpkgfpyuYypqSkMDAxgYmIC4+PjNpKb94B8rWZJAs534IvTuA2BxmC/Dw77wuZSqYSVlRXcv38f+Xwee3t7FjMLh8NIp9O4fPkyBgcHbaQAEyuFQsHmhOAcppzflaNHLl++jIsXL2JyctK6gQS7a/De1heNc/2b4c+5D7m/fECc75FF8uvr6/jtb3+Lzc1NlEol6xzBOF9HR4cVZEejUezt7dl8uMGuD8G2/owH++X5kQmMa/tuDjyeeZ/NuQpZnMj9VSwW7W94HPs4CV+T/w8mb5olHl4kIRAcZRL8u+CyfdF88Lj7pq8d9I1aM3HSyWQyaa08OKmM7+/vZ7H3KxtMRJycnLY5evLkSUOQgL9bWlqyCWR40AGnM6L79gnVatWWzUD88fEx5ufn0dnZiXQ63bRn89DQEFKpFCYmJhCNRq2q0w/HOjl52vd5YGAAKysrdsFg1SXfE4N2PoDvl+cvgHyPQXwOW0vUajVr18ST2z9ncnISr732GjKZTMPrBavxOfwLgM3JwP2VSqUwOTlpgfBg7zFeQHiBZxCWj7nPOjo60N/fj4mJCatoZsW+nwCXvc39hDm8uPoPBr8PztpefA7fdyKRwJUrV/DgwQNsbm5ibm4Oq6urGBoaQm9vb0OiiBXivMh8k2B6KHQ61C4ej6O7u9syyYVCAZ988glu3rxpoxG4jba3t/HP//zP+OyzzxCPx5HL5fDmm2/i7/7u76xXO4O1wQ8XP5KIr5/JZHDhwgVUKhXk83m7+LI/X7FYxPb2NqLRqCUiuJ5cd7bLikajGB0dtQtMsDWTDxh7Z2VPf4gmJibw1Vdf4fj4uGG/+zlieE4Ek4tHR0eo1+sNmWti8pHbuK2tDZlMpmE0QSwWQy6XQ6FQeCahGjQyMoJkMmkTS4VCIaysrKCnpwcTExPPTLbb1tZmcwbMzc3ZnCUMwgYDzFz3vr4+PHz4EG1tbdjb28P6+jo6OzttxFqwgtlPKsbrFytn/DbxbZlYxcxl8QtAs1Z730ft7e1IpVJ2LeQoKL5vttHzbbB8EtKfS+3t7YjH4zasl0H7nZ0dew4nek4mk1hfX8fi4iJOTk7Q2dmJ3t5eO995I8AhtKVSCbdv38bW1pZdK3m9oM7OTktsbm9v4+jodAL0P/7xjxgdHW06RwOP5XA4jFKphC+++AInJycYHBxsmByOx+pXX32F5eVlPHnyxNYvGo3i6tWr+D//z/8T0WgUGxsbWFxcRKFQaJgbY35+HuVyGe3t7djZ2cHs7Cw2NjawsbFhFU8cgckJ6T788EO0tbXhzTffRCaTsS+lPG95/HN7+S+gJycn2N7exvHxsb0XzuvyMiTJRERERES+Dd678Z7FBzB9zII4Chw4LQLK5/PW0ojFeIeHh4jH4xbH4ndyH8huNjrBr0+wmDPYwoaBfsbT2HqeMRt2Oens7GwoWuV9OQPKjL8sLy9jcXERi4uLFqhnN45z586hv7/f2k35UfEscOT784W/wOmoehZT+/tm/j3jcf5emvcpR0en7efX1tbw8OFDbGxs2OgLvs9kMtmwLiwIW1xcxKNHj7C6uopyuYxYLIZCoYC9vT2LGVy9ehU3b97E4OAguru7G5IQvuCa79kHsP1+CQa4eY/K5zVri8t4a7FYxMrKCr744gtsb29bEsjHWrg/Gfjf2dlBoVBAMplEPB5/JsnEv2W3AF9o6kdN8PlcX66rPx67urrQ29uLS5cuYWtrC7u7u3bfD8DiAvV63fajXw8/CoP7icexf51mvwuep82SQM0SccEkBJfttw355TRLTLyIF05E9Pb22twN1WoVnZ2dqFar2NzcxNTUlF1Y/NATrpA/oHzV/9bWFu7fv49Hjx5hZ2cH29vbqNVqyGaz1uOeAV9O2LyxsYFHjx6hs7PTWiFwxEClUkE4HEZ3d7ftvFqthlwu1zQRwROHQWifVeVJzPdQq9WskhOAZbp48gYzZ/6k8Y+DmS6/XXggdHR0YHR0FMViEZlMxgLniUQCH3/8sR0QHR0dNqE0+82dnJxYjzffYwwANjY28Pnnn1sLmK6uLmQyGYyNjeGVV15BNBptyPwFs3HBAzA4DIjrc+XKFWxtbeH3v/+9BR8rlQoqlYoFEMvlMsrlsvWkC7a/eJ5glo6vHQqdtmcaHh7G4OAg1tbW7AKxvr6OUCiEarVqFbq+T943SUIQW6WcP38ejx8/tuBcoVDAZ599ZsFdVrIvLCzg8ePHOD4+RrlcRl9fH8bHx20ejmYnf7OLAfdHPB7HlStX0NbWhrm5OczNzVl1Lz9s6vU6isUiurq6kM/n7cM2HA7bhPCJRAJ9fX02WoTBZE56zL7uPknCdQlus2+TDX1ZcBglALsG+kmPWP3vA/c+6M8PUAD2Yc7MOf/Noarspx8KhawHfjKZtNZsZzk8PLQWQA8ePLCAbaFQwNjYGFKp1DPnF6+xHLGUz+extLSEy5cvNyQzeZ3ilwAmM/f29uyLwFmtLvgFhR/aPNZ9qxs+9r0b/cTBTE583fXh+ySRSFjLq6OjI8zOzmJycrJh9AnxPXI4Lz9Leczws2Jqago///nP8bvf/Q75fB6hUMg+czhyxI9ySiQS6O7uxoULF+xzw1en1Ot1rKysYGNjA9VqFRcuXMDIyIi1yuNn0tHREeLxON555x3k83lsbW0hn8/jd7/7Hd566y3kcrmG984vxb29vRgYGMDS0hLu3LmDSqWC/v5+u74woL+wsIDbt29b79GOjg50dnbil7/8Jd566y10d3fj+PgY09PTePTokU2Wtr+/j/fffx937twBAPsuUKlUbBsnEglMT09bD9OPP/7YEhQff/wxKpUKfvSjH1lC2I+Q4LnJzwgeh5ubm7h16xY2NjZQqVRsNFIkEnlpEmXfhG+d4+cdeVHBxORZfIua3d1de/zb3/624XkbGxv2+N69e1+73ODxOTMzY4/Pnz9vj5+XRGpVKx/foud5r/H48WN77NtOcSQkdXd32+Nge6nvk6WlJXv8xRdfNP351taWPfYtm4DG7xu//OUv7fGvfvUrexw8F/8a7ZheRLBA4EW8TJ+FIiLywxGszG5WRR2sHOd9jg8Os5c/g7w+9sa/DcaGfEIhWDgZTEL44iEfPC6VShYTYhLEP88XFPp7YI7YWF9fx9ramhVS5/N56/TR2dmJbDaLkZER9PT0IJFINIwU4L1YNBpFOp22e0L/+gBswmW+rg/4npWE8W23i8Ui8vk8dnd37Tu4r7BnTIBJlVqthuXlZTx+/BhbW1t2H8X5Jo+Pj5FMJjE8PIzr169jeHgYqVTK2g8FA9LA0/hccN9x33rBQLZ/b35/cH6P1dVVmzx7a2vLOvbwuTx2/By0pVIJu7u71oEn+Bp8D8FRA/549uvL482/Nz8fRDKZtLkz/DLYFWh7e9vivb6QPRgv5rHstx/XsVli4Xl8/K7Z3/hkUfC89vHSZjG/bxoHfOFExKVLl+ykZY/l9vZ2rK6uWlUjV55tb/hG2JaJFbaHh4fY3NzEo0ePcPv2bZv4pFQqoaenBzdu3MDU1BRisZgd9P/yL/+Cer1ufdKvXbtmwTru2MPDQ5tHIhQKob+/3yoamyUiOFTHV5lzpwZ3Il/DnwicuBt4eqEMHiA+mB+8MDJI70cg8ODN5XJ4/fXXLYB1fHw6ycqtW7dsW3PiY3+Dz9fh++P2r1QqePz4MZaWlmwOiaGhIbugTE1NIR6PP3My+aBWMJvptykzqcywjo2N2WTMvBguLi7akKhKpWL7iBdhP7oimKGkZoFvf6FgUDWdTtuQOQaWGDw+OjqyY8dvr2bL/zptbadzl7D9EbfRrVu3MDQ0ZAH9vb09PHnyxAL6nZ2dGB4extjYmCWOghcS/56CFwi+dl9fH2KxGMbHxzE+Po5SqYSFhQWbvLqzsxPb29vY29trGErICyBwOllxKpVCNpu16t7u7m4kk0mk02n7MOX8LAwg+nksvm0m9GXCbROcB4L4IQc8rZrwGGjg9ZDn9f7+vgX5Dg4OEI/HrU8l8LT9WK1Ws2ThWViN/eqrr2J5eRnr6+uWQB0aGnrmCwGvx8lk0lqoxWIxFIvFZ7L73M/7+/vI5/NYXFy0YZddXV24c+cO+vr6bDQQz0X/pdDPNxH8snhwcIDFxUWsra2hUqkgmUxaYJh/6wPt33ehUAjT09MYGRnB73//e7S1tWFpaQmbm5sN5w8DZfxM4FBO/+WZvz84OEA4HMbFixeRyWRw584dFAoFlMtlFAoFG2p76dIlLC0tWXI0k8lgZGQE0WjUvnRy/p7t7W3Mz89jc3MTuVwOvb29tk7cP/ySHo/HcfHiRXz88cf2PYCJqSB+aR4eHsZPf/pT/Mu//AtWV1dtDh8moHnOcELpzs5ODA0NYXx8HBcuXMClS5eslRM/t372s5/h+PgYDx48QCgUsgRdIpGwShlWMnV3d+PSpUt499137dwaHx/H73//e3z22WfI5/P46KOPMD8/j3PnzmFsbAzpdNoKFXxv2cPDQ2xtbWFxcRG3bt2yhEwmk8Gbb76JsbGxH+z1T0RERET+NjWLkfhq6bP4RAWTECwE5r0wl8X7Rh97CgZkfbwhGHvwcSHfLscHnI+Pj1EoFFAqlaxdEX/ng/nB4D9weh9QLBYxOztrbYv29vZQLBatPTHbvbNDgW/X7kdXdHV1WbugSqXSEHPj/bZv2xSMebGIzxdR+/8qlYolIXwRILc120JxpEA+n8fc3Jy1N+f9YqlUsrkMc7kcLl68iOnpaXtvwXiI30/Bnzer4g/uX+5Hbivui2CCZXV1FSsrKzZvr99+HG3CgjUWuFUqFRuB40cC+PULHlM+nutjvXydYFzCJ9oYU/MtiRn7YRx9Y2PDRtQH5z3xI/SDoxZ88uR56x/cB8G44vN+9m29aJzmhRMRr776qiUPODohFAphdnYWa2tr6O3ttUAdT2QfXAdOA+e1Wg2rq6u4c+cOnjx5gtnZWcu6RaNRvPrqq3j33XcxOjqKjo4O66M/OztrbRCOj49tUt+2tjZrL9Hb24uuri6rsvy64Ch3JHvU8bl+mA1wekCxtzqDQQzU8OLgDzoKXhiaZXOD68jECkdAcF1KpRKGh4eRTCatSrBer9u+YCW2f01/wO/u7mJ5edmGGjFIw0AQW8H47eaHavl9yuX6RAR/dnR0hK6uLvT19dkE2/V6HdVqFbOzs4hEIqhWq0in0xgaGrLedM2G3AU974TzyZF4PI7x8XHE4/GGqliOFujv78f58+eRzWYbEitf90HazPHxaZue69ev22TioVAI29vb+PLLL+3D6ODgwFqosL3KtWvXGibG9PvNrxe3r79A8OeRSMTmKchkMqhUKpiamrKJlg4ODrC6umrZ+2q1imw2a5lkZo+Z2ffHcGdnp/XsZ7uWbDaLXC6H/v5+y/IH++v9UANxnJR9e3sbh4eHSKVSlshsltX3Q0o5eorndjChWS6XsbW1hVDodNLnrq4u62nJBAaTkV+3fTs6OmyulI2NDZRKJRtRwaGhxEB4Z2cnxsfH8ejRI0sU5/N5C9z6SXjL5TL+7d/+DRsbGzYyjcmU3/zmN8hms7h8+TKi0agFqPlFyVd9cllMyjx+/Bh/+MMfsLq6imq1itdff90mbufnTbN5CL7P0uk0Jicn8ac//Qm1Wg2VSgV37961LyZdXV12/Qaefglm5QR/x5ZOx8enczksLCxgfX3dCgGOjo4wPj6Oc+fO2TxHa2tr9iWM7fj4xfTo6HQC508//RS7u7vY3NzE8fExfvKTnzTMMUIdHR3W87Krqwv/+T//Z1y5cgVffvklpqamMDU11fT988v/pUuXEIlE8MEHH2B1dbXhM4w3JOl0Gq+//jomJydx7tw5G8noJ65j4nh4eBi/+tWvsL+/j48++giRSATj4+PI5XLIZDLIZrN2bGazWUuyUXd3N9LpNGKxGG7duoXd3V3Mz8/j0aNHNtKtr68P09PTaGtrsy+MGxsbuHfvnlUHnZyczt/yd3/3d3jttdes/ytHnYmIiIiI/FD4otFmAUygsVjPB9AZ5/DdQxgD6urqsrbpjIfx/jlYKNvstX1xMP/Ne3EWYTImxHlM2SmCRXI+3sX/816eRVyPHj3CnTt3sLW1ZbG4Wq2GWCyGwcFBXLlyBdevX8fAwEBD0SZjblyPtrY2xONxpNNpVKtVW0cf2/Ktivj+gcZkjE/c8GcsEuN9JO+3/MiFzs5OC+j7OCHjeyx45j7IZrMYGxvDlStXGjpC+MJC30nB7+9mx0gw4O5joj7wz+1Qr9dRq9XwxRdfoFwuo1gsWrzLa29vtxbG3KYArCjZz4PrC6l9wJ/HpE8cMY7hE2fsXhB8Lt8b47mcT5nrs7+/j46ODjx48MCmPPDtfYPbxr9ms3Ms+Fy+Ny94zAS3dTCxdVbM1a+bjzVz2YxdsavF87xwImJychJvvvmmBc0YcF1YWMA//dM/4cqVK7h06VLDZBvcOdzxPMhv375tfdQ4xD8Wi6G/vx9vv/02ZmZmLOB2dHSE6elpvPbaa/j444+tTQKze9xh3Bn+5t+3+miGBzeHzwRPGv+crq4uxGIxa0nFpAovXj4Q3iyTFdyRQGPLI4+TvPLEZmumTCaD/v5+C8qFQiHLdDJx4KuweZHb39/HysqK9cWu1+vY29uzOTnOnTtn2Vpf1c918yefz/6dxQePOClOsVjEgwcPMDY2homJCaTTaQwMDGBwcNBGsPDEDwqeONwv/JkfrcIM89TUFK5cuYLNzU3UajX723g8jomJCZw7d+6Zk73Zvngef7wNDAzg9ddft57k1WoV9+/ft4SZXz+2nBkZGbEkmv8w9kFqvz2CyQm/DtzmnLuAxw8vBuwVWKlULMBdLBZRq9Wwu7uLlZUVbG1tYXV11Vo47e3toVarYXNzE0tLS4jH4+jt7UUmk0Eul8PQ0BCuXr3a0Eboh5qEAGC9/YCnCahgKybyHwa8BvhEJjFBtLq6apUUrDDgiJadnR08fPgQa2trVrH+dVg5Pjc3h+3tbQwMDGBqaqrpyDDgdCTF+Pg4UqkU5ufnUa/XMT8/j8HBQfsgYdJkZWUFS0tLKJfLuHLlChKJBP70pz9hb28PCwsL+Od//me0tbVhZmYGyWTS3jO/tPCL3MnJCXZ3d5HP57G2toY//elPWFhYQDKZxNtvv40rV67g5OSkoVLFf0F6GbS3t2NqagqTk5PY3NzE7u4uHj9+jHq9jvPnz9uXD/ZI5RDlVCqFjY0NzM3NoVwu2zZg1c3S0pJNEP3uu+9iZGQEqVTKhsiura1hbW3NrvecI4ifLXNzc/joo4+wvr6OQqGAkZER/Kf/9J8wPT3ddJ4eANamjS34hoaGcO3aNSSTSaRSqYb3zH3tv+hcvXoVk5OTKJfLdk3286rw85U3DX4d+G8mlDmceWhoyCpNzp8/j3fffdfaFPJz5awkczQaxXvvvYeRkRH86U9/wtzcnLWf3NnZweLiIr788suG9kysUOJ3ggsXLuC1117Da6+91tAeUURERETkh4jf3YGnBbwAGorXgpXcDMDyv1qtZqOjAVinCt+xwn//910sWNEeDKr60QP8zs518i1wWZjLv+dy2fWBuN6Ml8zNzeGLL76w+7WNjQ3rWHD58mXcuHEDly5dsgIoxn9YjMhJuhnr4Yjq999/3wq+OA9FPp9HPp9HoVB4Zu4Fv239ugYDzD6Zw/fJGO3u7i62t7exs7ODSqViBY9sw8RCNxakXr9+HRcvXkRfX58VMQbbFzGYzcfclsE4qB+h4d9Hs+cxjry9vY0nT55gYWEB29vbqFQq1mKpXC7bXBwstmbrXMZueAyx4NPH3/javn0Y46rch36icABWMOjjoj55xKRFOBxGNpu1As1gMert27dt/uPr16/b/T2Pe99Fguvh2+j7JFSzAvxmXRZ88oiC8ZXgfKb+nPLxYR+r4eTtGxsbePPNN/F1XjiiE4/Hce3aNYRCIWsFcXx82k/8gw8+wJ07d3D9+nW89dZbVlEZjUZRq9VQKBSwu7uLnZ0da8PEiwwTAdeuXcOVK1cwPj5ubXp4ATo5OcGFCxdsMhJOpMJJVmKxmD2X7WY4OiB4kHl+J7By12cVfX8uthRh9WYoFLIsKk9o7mA/mUkwCBLMcvqMFQPVXBYvVDyp2QJobW3N5gAolUqWyWPm179XXmw5coKvWS6XrZXF5ORkQ6uY4KS7drC4CWN4MPoD2l+EOjo6rMd4qVSyixUnzOX8BAxg+RE0/mQ6K7jtLxo+icH3l0qlMDg4iFgshlKphLa20wlzqtUqlpeX7cL2XYKaPtgci8Us8fG//tf/ssm4P/zwQ8uQcygYR99wwtZmF0IeC83et3+uH6XCICETgMEPHV48fP9FHvu8mG9tbeHLL7+0ER2cDBaA9Q9cXV3FwMAA9vf3sbW1hddffx3j4+P2Xn6oyQjfW7pcLts5GBwNATw7zJCJvGZ9oCuVil1P4/E4MpmMfXnZ2dnBBx98gN/85jfY2tqyUV9nYYVJLpfDu+++i5mZGRQKBWQyGZubIHhcMYHK/oT8crWwsICLFy+iu7sbodBpe57t7W387//9v7G2toZoNIqbN29icnISqVQKH3zwAfL5PB4+fIharWZfWDjpWGdnJ2q1GhYXF1EqlZDP57G+vo65uTn7ItHb24t33nkHb7/9NrLZrG1bP6yVX1xfBqFQCL29vbhx4wb+7d/+DWtra6jX67h37x5+//vf20RWh4eHWFtbsxZcsVgMALCzs4NqtYre3l7U63VLUrE3J9sO9fX12Tnu5zTgKMW9vT188MEHdg28f/++zaMwMDCAN954w9ohnsX3FeV74/XGX0ebnQ/8u0gk8swosG+C5xQ/cycnJ/HHP/7REt6sLuL6PO9aFI1GkUgkkMlkcO7cOdy+fRt/+tOfsLGxgUKhgFqtZp95PK/q9ToymQympqbwxhtvYGxsDH19ffall+v4Q5ys+v79+/bYfzkNvtdisWiP/ZwG/ufBOSb8XBCbm5v2uFwu2+PgPBB+3/rjdmhoyB6fO3fOHv/kJz9p+PuRkRE0832dQwAAPv74Y3vsP1/8dgJOR+/RX+NY9HNe+LZtn332WcPzbt26ZY9LpZI99tVtfm6Pvr6+hr+fnp62x5cuXbLH/vPh+7w//br5OVhelD8P/dwqwMuzDURE5OUS/G7NQH/wnti31OE9iY/bBO+TGYvi3A283/WV2MFiX65PsxETLMZlcN/H6Bjk9SMhfByG952Mkayvr2N+fh6PHz/G7OyszRXBQrsLFy7YvVQmk7G4l3+PXA8fWGbxFoP3/P3e3h4WFxeRy+VstDfXzSd3uG18/IXJGI4gYHGqD2wDsGI3jprgPTbnLe3q6kIymcTFixdx8eJFjI6OIpfLIZlMPlMIzHsfHwP1I8SDXWE4EsEXbPKY4ftjsmhzcxNPnjzB48ePLZ6Zz+dRKpVQq9UAnM6Hdu7cOQwMDCASiWBhYQH5fN72OXAaS2AbYBZXcz39cebjkT4Z5uOTXK5fjj/2mPyJRCJIJBIYGhpCIpFoSArxb8vlMubn5y1hwQ4GPiES/C7vJ732xcvc/jyWgsXl/tz1Re/+WPIJLI5M8scWkzs+LsPORqVSyTod/VkTEScnpxNfnjt3Djdu3MDc3JxNHJrP560SfHZ21gKs7IfPN7+1tWWZSW7kw8NDDAwM4P/4P/4PnDt3zioi/QWFwYXe3l4UCgXs7+9bT2sOEapUKhbEi8fjDQGL4MWOuEN4kjKYwGCcTyZw53J0AjOqvMAxsQLA+mkHTzy+JvnhLzzggsNp/AHCquUPP/wQpVIJ4XDY+qLxgs0gdHD55XIZiUQC0WjUJjBmMDyXy1nwxl/s/YXZvw9/AfQXIH9BaWtrawioMvvNFiPJZLKhb15wG52VGQ3yr8fgU7VaRblcxuHhIRKJBDY2NuwDaHd311qCjYyMNEweFEziPA+D+rVazV67u7sb165dw1dffWU3hcViEZ988glmZmbs2AmHw5iYmLDjNHjR4wXTB/fOSqYF2yJxv/O881UB3J6+gp/BwVgshnq9jnQ6jampKRSLRVy4cAG3b9+24Ck/jEOhEFZXV21yHU62MzU1hVwu99xA+cuMIyCA0+NufX294QM0mFX2SQfuB+DphZ8JOw7H4ygBzoNQKpXwySef4H/+z/+J3d1d9PT04Pr162du31Ao1BB8iMViZwbbiAmStrbTXpE3btzA48ePUalUMDc3h93dXWSzWRwcHKBSqeCrr77CV199hf39fQuGZ7NZ/OIXv0BPTw/+9V//FcvLy9jY2MD//J//E59++qkFCWOxmLULOzo6wubmph2riUQCo6Oj+Lu/+zucP3/e5phgEIsJa26fs4Ld30epVAqvvfYaQqEQPvnkE5RKJevFCZx+EQSeziHCa0QkErFkKv89NjaGwcFBa9PnJ/T2VS8cBjo7O4uTkxNUKhV88MEHtj157J0/fx6//OUvcenSJaRSqTODlv545nHMERL+Z39JHCY8Pj5uxxxbzTUbpeSvg8BpgJSJuUwmg7fffhuXL19GuVy2Sef45Y/VOO3t7ZicnLT5Vph85ecuv4i/yHBUERF5ebR6tNtf4nPUJ4RbYWNjo6XL/0tso+D8bn9uLKJspVaPHG71d/B4PN7S5QN/nST9yy74PdoXPfL3zQpvfdyIv/Pzr/lYTrFYRKlUQnd3N2Kx2DOTOPN7dnBdfJzDx854/+IrxxlXZJyuvb3dnsMOKIxf1et1G6F+//59rK2tYXd31+JUXV1dGBwcxCuvvIKxsTEbCRE8RxjH4fpwW/h7Ph/7Y8Ezu1KMjY09k5jx7YOaVcAHC599QqajowOFQsGKlIGn81tysu3+/n6MjY1hamoKo6OjSKfTDffgvi0R8DSmELxOB4sz/fHiq/WZKOF/xWIRu7u7uH//vs1dwXmI2VWHsb6RkRFMTU0hm82iXq9bZw9ffHt0dISdnR0bmc8kUnD9uG39KIJm8UifIAiOTPG/5zEyODhoMRA/Qfvx8Wnb5KWlJdy9exexWMwSEr4A3p8DwcJknwTxPw9+b+E2Dh43/LefT5b3vowBsph5eXm5IflYLBatMwsTPS96DX/hTypu6HQ6jcuXL+PTTz/F48eP7c2w9cPjx4+Rz+dtwx0dHVnwicFaTorLiZJ//vOfY2ZmxlrY+J3Hk2x4eBj//t//e8TjccuA7e3tYXt7G/v7+3j06BFee+01vPLKK8+MOvi6ADNPfp9d8nMWHB8fI5FIYGpqCvPz8wAaJ6tJJBKYmJhoCND47Br/HzyIPJ8d4+v7inbufA4/Ynumg4MDzM3NoaenB319fajX65a94skaCoXQ2dlpPd05W3wqlcLW1pbtG5+44IcEL5rBg5qZN160GADjhYMtuAqFgk3A2t7ejvv372NychJjY2OWqPL98/y2arbP/H71H34c7sbWJSsrK+jq6sIbb7yBo6MjLC0tIRaL2XqsrKygVqshkUg8kwl8UazC5TLq9ToGBgbwq1/9Cv/v//v/2gQ5rApl1Te3HXv3cRv4KuZmbbuaXcTJXwC5PX0mlxfi4EgjHnv84GFwMZ1OI5PJ4Pr169ja2sKDBw9w7949PHnyBJVKxS6cHR0dmJ2dxf7+PgqFAm7evPnSVKt/Uz7AyA+xSCRiSUv/vv3+IG7nYPKIyc9YLGbJulKphLt37+L999+3Nnivv/46ZmZm/qxfnlltwOv42NgYxsbGcP/+fZTLZdy6dcv6Wc7Pz+MPf/iDVea/+uqrGBoasmrxt956C9lsFh988AFmZ2dxfHyMzc1N+0JA6XTajsmuri6MjY3h4sWLePXVV9HX12cJCH/95we2n3fjZbiJiEQiODg4sGT75OQkHjx4gFu3btkcLScnJzZhfDqdRn9/P/r7+9He3o7e3l6bK4FfTHjtYLUNq146OjqspWEkEsFrr72G2dlZbG5u2pdN4hDif/fv/h2uXr1qk8OdhcF931aMn3O8pv4lMHHFL489PT2YnJzExsaGzcMzOTkJ4NkJ44M3LbFYzK6V3DaZTAaZTAajo6N2zQyeyz553ex1+O+XqYWYiIiIiMjzfF28pFnhZLCaPNiBg9+3Q6EQisUiCoUCenp6LHDuYz2+ONYHX4Gn99n+Z77y3v8NW9n6NvIcRc6JhSuVCkqlEp48eYIHDx5gdnbWuluwQDibzeLixYu4dOmSzU8XrP73SRLfBYPFofF43Oby46TVvD9hTG1tbQ3d3d3PxIJ8ux6+FgP5wf3lR4AwERQsXua2mZiYwMzMDGZmZpDL5WyOSb/+/n0G94lfv+D9V3Cb+CJcdnKpVqs2J+KtW7ewvr5uxbCswue96eDgIGZmZixZw9iDb4PFZZdKJRSLRVQqlYbWzz6pxmPTF7I3614STET4Am7//jo6OtDb24vJyUnrQMIieB6zBwcHKBQKuH//PqLRKMbGxpDJZCw+wBheMAnFdfMJCF/kHBzFwWPFJ1q4/oeHh6hUKlZkz31RLBYb5kacm5uz44HJnf7+fks+RCIRpNPpZy8OTXyjRMTJyYnt8GvXrqFarVq7lmw22zBchsM5uENrtRrC4TC6uros+3fx4kVcvXrVqqj9TmaPOD+cZmRkBP/xP/5HLCwsoFwuY2dnB0tLSwiHw7hx4wamp6ctmeHb1XAHNMPX8j3t/E7h3zIr6oPmDM51dXWhv7/fTmImAvxB6JfDv+c2DWakeJHg+wiHw4jFYjg5OUE0GkUkErFkxPb2Nm7duoVz58419I73cw2wcrNer9scF36yFB5s3P58Xb9+PrESHA3BCx5P7gcPHuD+/ftYXFy0kSK8wO/s7ODBgwc2rwCX6XvIBS9Ynl8/PoeZRA4H2traQrFYRHd3N4DT4NLKyooF/Y6PjzE/P48//vGPePfdd5FOpy17/aKJiFAoZBM5+4RXLBbD1NQULl26hI8//tjey9bWFrq6uqxl0+PHj7G2tmYTMvntelYg3793/zOuT7Osp39PfngZ8QObF0K/vGg0iq6uLpsTYmxsDE+ePMH9+/cxPz+ParVq1VUcAnd8fIxXXnkFFy5ceKHt+DLhxNQArH/f4eFhwwgsapaI8F+C/JC7ZDKJbDaLtbU1HB8f4+HDh1hYWMCHH35oE5xfvHgRP/vZz575EvJd8RrLD7WBgQG89tpr9qXnD3/4A+7fv4/Dw0Nsb29bkvmtt97CtWvXbGRbZ2cnurq6cPXqVQwPD+PRo0d48uSJTQbGCerb2towODiI7u5uG+XGSdD9NRCAJcf85EnBa+v3Gc+rtrY2q2K5fPkyJicn8corr2B7exu7u7vWxrC3txfpdNqu1374JhMM3DbRaNRep7293a7vTGi2t7fjRz/6EeLxOB4+fIhyuWzbLpvNIpVK4cKFC+jv7z/zesNlMeHIkX++dWCz5Gkr+S+rvAa/9dZb2NrawsbGBp48eWLtwHht6+rqsp6cnq8M8gkO4rXTFyWQ/zxkop7LqNVqDS0Wfyj6+/vtsW+tFKweff/995s+ft4561sLzczM2GPfriY4Gd2rr77adFm//OUv7bFv3RM8zr9P7Wq+zboEt4fnt2Gr+PZLQY8ePbLHX331lT32bbeC//YtnLzz58/bY99+CTidm6uZ79O+fVHB9lr+fPNtq/zz1tfXX2jZfl+9jNtGRET++oIB9WBXgGZximC1vC8sA54WdbIA9/j4GKurqxgeHm5IJgCNhZb8eTAR4dsQ+fiHfw+McbD4knEorsfR0ZF1HNnd3cUHH3yAhYUFVCoVq/xOJBLI5XIYHR3FG2+8YZMRe7yP8MXGjE3yPR0dHWF0dBRDQ0PY3t621s++lfry8jLu3r1r7X1YCHZycmJz7jHO1tHRgb29PSt+5Wuzi4sfYcKuHr47QWdnJ65fv2738+ym4u/R+Zj3TL4tke+uwuUG46F+X/gkAdv+bG1tYWlpCbdv38bjx49RKpWsUPvk5LQFcSgUstbnP/3pTzE2NmZxmkQigXQ6/UxSiOvEOVM5GoT3bD7hxSJTriOPdRbu+USMb4XE5/q/OTw8RCwWw8WLF1GpVFCtVrGzs9MQZ2ZMdmVlBZubmxgfH8fIyAhGRkYwOjpqxyvbITMuwGOI96v+Xos/Y5zWHwN+fmQmaCqVik2hUK1W7fjZ3Ny02Cr/zs+zwY4q3AeRSKThO+zzfKPWTAzWs41BOBzG6uoqnjx5gnQ6bQEnzrIeHF0Qi8UwPDyM8+fPW+VtMplsyMJxB/tecwygMGuYzWZtNMSVK1eQTCZtwkoGB33wnzspeIHwgWx/8PH//gLHlgxfffUVSqUSTk5O2/ysrq4iEong9ddfRzQafeYi6QPMPqjvM4C8KPpe28E5Ezo7O3FwcGAXhY2NDQsOlstlbGxsWCbQZ4/5/3Q6je7ubqytrWF7exvt7e3Y29uzPu1jY2N2MvI/nkg+oOJbSHH9a7UadnZ2cPfuXczOzmJ5eRlbW1vY3Ny04L/fJ6y0LhQKuHLlCnp6eux3PvgVHKHB1/Prtr+/b5Ogb29vo1AoWKuq4+NjFAoFpFIpXLt2DY8ePUK5XEapVMLi4qKNgrl69aqN0HjR4JHfr1xfHrOxWAxvvPEG9vf3cevWLezv72Nvb89GErS3t6NSqTQMkfbHnx/p4fksZ7OKA59hDy7Xf0h43JasTuD7Z7sR/k1PTw9yuZydu19++SUeP36MpaWlhh6En376KQD8IBMRnGsEeLo9/STdwcrooOCXIv67p6cHmUzGfnf//n3s7u5a38ORkRH8/Oc/R09Pjw3f/HPyX9ii0SguXbqE27dv48svv8Tq6ipWV1ftuW1tbXjllVfwi1/8wuaO8MsJh8Po6+tDNpvFtWvXbDQE50bhEEV/reT//XnttyWHTfp1eFkEE9ycZPmsANp3EZzfgZMxv/fee99puVz/Zl+wAfxV2hDxM/Tw8BDZbBbT09PI5/PWl7Krq6thVFlXVxcODw8bRoUATz9X+AU++DtfDODPbX4f4fXSzxHFOYBERERERH4IfPGij9UF5z1g4NMXQPoiInb66Ovra2j/3NHRYcWyjEPwXoOximZV4MDTAlxfcOkD3b44kyMB2J6awdSDgwPs7u7iwYMHKBQKWFtbw8nJCZ48eWLdCXp7e1GpVDA0NIRr167h+vXr6O/vt04wfF0f9+P6Mdni7xm6urqQSqXQ09ODeDze8L6Ojo5QLpet8DOTyWBmZgaJRMLeZ7VatXuUWq2GcrmM+/fvY2VlBevr68jn8zb3IycZ5jY9OjpCLBZDf38/hoaGLPjN9uFM1HAkuK+69yMgfFFas3v0YEG2H6HiY6HFYhEPHz7E/fv38eDBA5TL5YY4FQvic7kcDg8PMTw8jBs3buDixYtIJBIIhU47KiSTSczMzODRo0d2j8r1rtfruHPnjm13jjrg9uC+CrYNY9FlMIAfPC94/Pui6ba203b+k5OTFvfgtAaVSsXuGyuVisUmNzc38eDBA/T19VnBfi6XQ29vL/r6+jAwMGAJIo5cYBE/E0yRSMTmc+Cczfl83go9a7WaHVubm5t27vE/jhBiGysWfvO8ZCFtT0+PHT+pVKppa7KzvHAiwveIZtV3JpPB/Pw8uru70dHRgYODAzx58gQHBwdIp9OW3WErjomJCbz55psYHh5GLBaz3lfccbxgBQMCvg8VLzLRaBSpVKohk8WDg4E6HwxoVqHMg8dfpHz2lQchR3KcO3cOPT092N7etp2+sbGBeDxuQUO+lg/Q+Yuk/xkv4nxt8oF+PpfvO5vNYmJiAvPz8/b3lUrFKkHZW50XBOC0EpBZuPfff99623EUwccff4xUKoXJyUkkk8lnqk79bPMHBwd2UnNW9PX1dWxtbeGTTz6x1j21Ws0ufMfHx5a548n45MkTrK2t4fDwEBcuXMDg4KBVDfsLlH//fp8xsL+9vY2lpSXMz89bFrlQKKBUKlmA6vz58zg8PMSvf/1r3L171947RyXMz8/jxo0byGQymJ6exuDgYNNj5Xk4wRIvMAMDA7h58yba2trw2Wef2SghZlP5YcHjlx/SwQRDMKDVbISPP96CyS5qlrQI4rr7RBCfy+MpHA7jwoULNjrit7/9LWZnZ23YFkeJ/BBxAnZWMvjelQCeaR3EKmzfHgt4OjKFwwI7Ojpw6dIlrK6uYm5uDjs7O9Y67erVq/jJT36Cqakp+4LSSkdHR+jt7cV/+S//BT09PXjw4AE2NzcRCoWsv+Hf/d3fob+/v+FaGayG9x9SweseK+v54Rn8u4ODA0uK+PPCb08fBJa/LX4COeD0+BsdHcXc3By2t7dx7949vPLKK+jp6cHR0ZG1+eLNB78kEq/BHDnBGwXOu+STzf67Ar/f+KSHH/UkIiIiIvJDEIxZ+VgWvyezq4cPxPuYFJ8fiUSQTCbtvpkBer8s3v/5ERPBYs1ggaavyOfvfdDbB4yB09HRnGuAHVw4Hy3jXAzmsjUu2wlPTU2hp6enoQi42f2wf9/BmBZwGqebnJy04j8WTfmK+t3dXfzmN7/B7du3bZRCNBrF7u5uw7av1WqYn5+3WMLe3p7Nceefx207ODhorZ+z2SwSiQQymUxD8iHorOJWv40BNMQ9ggkI3tMzXlIsFvHo0SN89dVXWFtbs/gAY09c51QqhVdeecVaGQ8NDVk3AZ8w6O7uttbp3P5MDLB7z9raGmZmZhru/XwiyB+zvlOMj+vyuOHf+oJKvw8ZOx0cHLR46vvvv28xZZ944r0q57vlXLexWAyJRALd3d3I5XIWO+V0AXt7e+ju7ra5mpLJJNbX1+39cVJpFrdzm3JEBPedn7OE8e1YLGZzKY+NjWFkZAS5XA7pdBrZbLZh/pBvcg/8jRIRfq6ASCSCeDyOvr4+XL58GQcHB/ZGmEXhRmUv5mQyaQcLd3gwWMqd71vKNAvM8qIWTCKcFcRt1jbCX0j9AcYTx4+OaGtrQzQaRV9fHx4/fmxDiI6Pj7G2toa5uTn09fVZQDqYXPFDlviavjra/4zr4wPTTIxwuAuDoJ2dndZrjEEXHigM4h0fHyMWi+H69evY3d3Fzs6ODXMqFov49NNPcXx8jB/96EeYnp629ll+hAn378HBgQX85+fnsbi4iPn5eRSLRczPz9vFm9uXSZzr168jEongyZMnNilvqVTCBx98gI2NDVy4cAFTU1NIpVK2LXgS+IsXe6htbm5ie3sby8vL1kaG26Ber6OnpwdvvvkmXn31VaTTaRt+tbu72zCRNN/L6uoqYrEYbty4gX/4h3/42vPBZ4O5vn7/dnR0YHR01IKtn3zyCba2tnB0dIRqtWrZ0GKxaMmj4FBGfzEPfmg1O2+CF86zRk00w/PRf5gHEyP8UGBGeGhoCBMTE9afvVKpoFAoYGlp6Wu338soHo/bvgKenZAagLU84/Xp6OgIkUjErin8G44+YZ/JCxcuWN97tqt466238Nprr2FwcLBlVefB6m1em5nw5KROACzJxKoD/0Wumc7OzjOrI/xznvczf/wywfwyjYiQ1uDcJsDp8TA0NIRLly7h008/xYMHD6yfKT+PeZ5y2LYfPcJRe/v7+/ZlkUkLf83zI6BYucV/+/mY+KXuh5Yo+9nPftb0559//nnDv4MtZpoJ9g5NJBL22Lf18ZN6Blsx/fjHP7bH4+Pj9tiPNmplG5rvU7sbv/2AxtFRwflLvgv/noOtlObm5uzxb3/7W3vsJ68N/o3/7Ll48aI9fuWVV+yxb8f0197Of25+e7IQ55vwQ9+z2eyZz/tzbrdgS64f2j4REZFvhvdq/v8+puVjXr4LA//j733cjSPq2WrVt53xyw/GYvz3Ch/85795X8pq+M3NTRSLxYa45d7eHg4PD63olXG9zs5O9PT04JVXXsH09DR6enoQjUYbYpbB7hS+uwRjQv45rPLv7e3F2NiYBY4ZGPbB+t3dXauaD4fD1r4YeBp/qNfr1lWBcTtOxB2M8zAZlMvl0NPTY63KGRPiNgved/ti4WDgPjgKhduE/+c+39/fR7VaRbVaxe7uLpaWlqyjCudY5f7nfdnJyQkmJydx4cIFZDIZpFIpJJPJhsmc29tP5/NMp9M2ITkTO35ewO3tbdvW3IZ+v/n4V7DY1++/ZvHn4LHok0DxeBz9/f24cuUKtra28PHHH9v9J+Ps3F/cp3xcrVZRLpexu7uLtbU1rKys2Pd9jm5IpVIoFotWHLu7u2sFoIwTc6QLX5fLZusnFtuya1EkErG5KjKZDIaGhpDL5RCPx63LhZ/E/Jv4xpNV+38zyMzg8V/anyMg5YcaAU8vWsDpQcQTGDi9Kb558yby+Tzu3LljwYdSqYSPPvoIFy9ebDh5g+2Nggd3MGDM5/pJs/0cGTy52Ev84ODADsByuYzFxUWkUqmGiY+ZreNEKW+++SYA4OHDh/jqq69wcnKCcrmMO3fuIBQKYW5uDu3t7ejp6cHY2BhSqZS1pCkWi8jn8wiFQqjValYJz+E8vJCzQprHx8TEBH7+858jnU7jd7/7HW7dumXbOp/PI5/PY2FhAcPDwxgYGLAJhJLJpGXtisUidnZ2UKvVsLKygo2NDcv+1Wo1a3M0MDCAyclJvP7667h586b1no9EIrh27Rr29vbw4YcfYnt7G4uLizYJy8nJab8zTkb+ooL7zgf029vbMTQ0hNdffx3lchnz8/NYXV21zPvW1tYzHwrNEgz+tYIfXn5ERXCUDf8muL5cNv//vA9xLrNer6NcLiOfz2NnZwc7OztYWVnBvXv3Gob9sdf9DxEr9Nva2uzLyVnb148SaG9vt9ZEPD/8Mjli6K233sLIyAh2dnaQzWZtHoWgP2cg/qzKDQDo7u62eVb+mr5r8Ex+OFjJAjz9Qsn5qM6dO4darYbl5eWGYeFs7Qg8vQlhMpDXN173mHzgl0HewPCLG49FztHB5XH5LNjQMSsiIiIiP1TB4KsPyrKY0Qeh+X9+b/b3yiw2jUQi2N/fR61WswJT/1rNkg0+jufnr+N/wQ4PoVAI6XTa5mXI5/M214JPgrBwNhKJIBqNIpfL4cKFC7hy5UpDS3j/+sECaR+T8wXUfC7XN5lMYnR01AqGq9VqQ/KG24fdFBi4ZtEfg9YslA4GzX3ygNuks7PTJqBm4TTjUr61EPlEEeNNPgkRHPUQLLDl/Ve9Xre5/bj9Of/v/v6+JSGYiGDSJZlM4vLlyxgbrylN1AAAM9BJREFUG7PWUT6+CqAhEZFOp621kJ/Me39/Hzs7O8jn89jb27MCS9+VJxiv4c+C7e99UX2zmB3Xif8Ph8NIp9OYmJhAqVRCPp9HoVCw0SsnJyd23Dfbj8DpKB62WWLxOABLVjF+zdgcX5v7pl6vo7e3144/JsM40iaVSiGXy6Gvr8+OfRbj9vX12cTqzQYV+P39In5YJXvfUvBE84EJnug0Pj6OGzduYHZ21iaQOz4+tsp8DmfyAebntckJVrAHA818Lk/6WCyGXC6HTCZj/ewODw+xsrKC1dVVjI6OIplM2oWNc27wBBwaGsJ7772H8fFxy4Qxi/bFF18gHo/bCJa+vj6bjDYcDqNcLtvr+awrM8esGOVFORaL4fz58/jpT39q1W43b97EwcGB9X47ODjAzs6OXRSWlpbspIlGo+js7EQkEkG1WsXGxoYlRHgh5sUzkUhgYmIC7733HoaHh9HX12cTCnN+kGQyiR/96EeYnJy0Ks6FhQUbGcKJil4U912wNY3/QIpGo5icnEQ0GsX9+/dx9+5d3L9/H4lEAtPT00ilUracZokIzy+XnjfSp9n6+sp8vyxmXDmpkK+irFaruH//Pm7duoUvvvgC29vbNoTSDx88PDxEV1cXrly58kLb72UTjUaRTCbtA4JD2vb29qwfnv8w8qMeeOH3FQnA0yw5cFp1PT4+jvHxcdvXzS7wZ41qEfmhYwsloHEyaQDWP7NaraKrq8tG1vC66pMF/saEVSrBpKz/HPavE+RvNLg8EREREZEfiq8LLvoRCME25eSr0gcHB9HT04NarYZSqYR6vW7zRLDFN2MLzUbiB2MmPm4WXC/GOYCnczNMTk5afIktcXxLqHq9jra2NvT29mJychKXLl3Ca6+9hr6+vobuI8GCZgb1/XoxtuILmBg7YSxgYGAAx8fHNn+rD0QfHh4in89bq2cmCvwoZF+A7Ld3JBJBuVy2uIJveV+v121kAoP+5KvyOcLc30v51kTBmIUvluXv2e5qd3cXX3zxBe7evYvNzU3U63VrW85kCls3VatVpNNpTE1N4erVqzh37hzi8XhDdx2gsQ1UR0cHYrGYte1l4TK7UPgC252dHYvdBt8Llx0c6eG3NX9Pft8Q9x//hlMTXLt2DalUCnNzc3j8+DEePXqEeDyOpaUl2xY8xvxk3dwnTNZxu7NFmE8Mcd8xBsV1iMfj9vtIJIJMJoNsNouhoSGbF5ZznzDhw9dhEovr5luxcR8oEfECfBLAZ0v98KxgRpWJgGg0ikqlAuA0A7W5uYnHjx9jenradg7QvKqd/GsCaOjZxmXw3xxiE4lEMDAwgKGhITx69MhGUFQqFeTzeSwvL1v/dv8eeCHgweZbsty+fbth3oXOzk50dnZia2vLTqb29nbrMReLxSy4yowtRx2kUim0tbWhp6cH7777LiYmJqyV1P7+PiYmJiwL/f7771tVOSc35wWRF8hYLIZwOGxtlDiUiK2jOjo6cO7cObz22mu4dOkSstksOjs77WT0F+P29nab5T2TyWBwcBDvv/8+FhcX7bWHhoZe+PgJjj4g3/eeF5zJyUkMDw/jlVdeweLiIsLhMKampixR1OzDkxe9ZkPimvVIDDrrGA6FQvbh7rPfvocf9+/BwQEWFhbwL//yL/j8889tf/Oi1NHRgWg0akO4zp8/j7feeuuFt+HLhFlibncOr+SwPwY/fQbaf4HwF2wANs8BJ1b3x1OzETL+eiDytyh4zQ1eMzs6Os5scfK8UQrNfueHJX/dOr3oF66X2TvvvNP05+vr6w3/ZoEG0NimybcP8m14gKcjTIDGdkzT09Nnvr7fZy/7CJRv0+Zpd3fXHvvCgW/zms/jl/3gwQN7PDs72/A8/7u9vT177Nsxra2tNfzNG2+8YY//23/7b/aYbfh+iM7a7n19fQ3/Hh0dtcfB9mfkzz22HCXfouzPSa2YRESkGf99mEF98pX5TAowAMzv9j5ozjZEflRAsHDYL9fP+QCgIeDO5zHWweLBXC6HmZkZHBwcWFEuR0ZEo1FEIhF0d3fjjTfewLlz5zAwMGDBeh+U5Xv3/2cBU7CNvJ9ngEFzrm88Hsf4+Dj+w3/4DwiHw7h9+zby+bwV33KkSbCllS8EZlyJ8ymk02l0dnbiwYMHDUkEfs9aXFxELpdDd3c3ent7GwLO3O4+CeSLs4KjXlgE7ZM5nE+vXq9bwfFXX32Fzc1NbG1tNUyQHI1GG4o229vbkcvl8M477+DcuXPo7++3SnyfMOH29v8Ph8OYmZnBZ599ZvGW4DwetVoNS0tLGB0dtUJrX8Tt53zgyPjg65GfsJ1F0H5fcV/z5x0dHchms4jFYhgZGcGVK1ewtraGYrGITz75BPl8HtVq1dp0Md7GdWCczh8HPoHC0TKRSMS6w/B8ODo6QiaTwZUrV2zfp1IpJBIJxGIxRCIR+8+P8vcJDh4b/pgPnpMv4m8+EdEsiBDMsDLj55MR/f39Nh8Cg4+ffvop3nvvPasq9ydvMGjcrGrSX5AYnOaJxotKJBLB8PAwrl27hpWVFRSLRYRCIZRKJayuruLw8BD9/f02PwEr9nkS+OFqly5dQnt7O9LpNObm5mxkByu+eYBx2FetVrNEQCKRaMh+skfY8PAwLl26hKmpKUxOTtp8Ajwh2traLLMdDoctG7q3t4fd3V3rd8csKtvaAKetYngxGRsbw+TkJLLZLCYnJ5HL5Z7JTnOb+xOP/frb2trwyiuvYGRkxBIuKysreO21177zccV5NYCnExgzQJZIJDA6Otp0JEUzzY7NZie3/5Dz+IF3VgUBM6VtbW0Nw7jq9bpNZn7//n3s7u4ikUggnU6jUChYwioWiyEej+Py5ct4++23MT4+/kz/7x+Kjo4OZDIZRKNR7O/vo1Ao2H5kbzweqzzO/Ic+8brg+zZyNE6wasJ/yfE/ExEREREREWk1H2AMxh2aVZI3m8jXtyEvFosoFos2j2dbWxuy2axNIO2rvX3LIP+awaC5Dx4DT4sp/Dy3vJ/u6urCwMAAOjs7kUqlrJ9+R0eHzYnI6vBkMmktmv37Z1A+2NWE6+Xn2/SFnz5G5def8YKf/vSnGB0dxf379/Hw4UOsrq5a7ICvFZzLLhaLob29HalUCn19fRgZGUFPTw/a2tqsaHpvb68hGcQ5XjkHwNTUlFXs8/0FC6fb2toaKv99XII/53x5tVoNOzs7ePz4MZaXl7G5uYn19XWbV5jBf45I4LESi8Vw8eJFi9V1d3dbcTLXwQff/UgRbutEIoGBgQGL19ZqNXR1ddn74AgNH1tp1pmG7Z786/r3Gkw28f/Bjjg+0cECaMZDk8kkBgcHUS6XLTbJ8+P27duoVCpIJBI4Pj7Gzs6OxTwzmQyA08KvSCSCdDpt82cwbseW90wu+OOFxduM0QZHmgRHIQXbnDX72TeJU/1NJyL8geYvnn4EAi8uPJmOj48xNjaGn/3sZ6jX61hbW7MdMDExYUF7HnwM6vqL11mBZD+Uy/+blem8oMViMUxPT2N4eNiyZIeHh9jc3MTJyQkePHiAkZGRhsA8Lyi8aLAv3JUrVzA8PIy1tTXs7Ozgn/7pn/Do0SPUajW0t7dbFTgnMjk4OLCDlTOk878LFy7g4sWLGBsbQywWswsVkwfMiobDYfT09ODmzZvo6+vDw4cPsbu7i8XFRZTLZbtIVKtVO1G6uroQi8WQyWRw9epV9Pf3I5lMWlY3OJFtcFiUv5DyQs8Ts6+vD21tbbh69eq3mjAwOFQLePqBF0w48YLtM4rP44+ZZq/jl9tsnZhc8McSjyNefDl5TaFQwOHhIXZ3d1EqlVAsFrG0tISNjQ2USiUbUcL3lcvlcPXqVYyMjGBmZgajo6OIx+MvfXXqWfilhf0rt7e3rXLCJxKA0w83VndwSB23NT8seV76D3P/occvcMTzSIkIERERERER+UtpNiLBV8UHi3mD//kOAL4riU9e+MJI39nCB/iDr+uf438XXB9i0JUjHNgGnPE/Bmc5IS+LNv0ICB90DT72z/OPfXDad2HxQf7Ozk4MDQ3ZeiWTSSwvL6NSqWB7e9taq7PtczQaRTabRSaTQTqdRiwWQ19fH3p6eix4fe3aNdy+fRsbGxs20oRJknw+j9nZWZv3l91FuL+CCRTGNfb39xuSKD7JtLe3ZyMgtra2sLKygt3dXet8wtZbfM+xWAy1Wg09PT3IZDLo7e3F5cuXMTU1ZRNWs7A3GPj3SR2fiGJ7pkKhgGKxaF09GFdlEXSzBBKAZ4pCg/uN8RuOkOH6BEer8G99eyafvGpvb7e5GBj37O/vx97eHsrlMnp6erCzs4OOjg7s7e1hc3PTRi5wLs+9vT3EYjEkEglL2nR1dSGZTFqclHEkbivGuf36NDtv/bnTLBEZ/Fnw8fP8zScigpmsZhcOABbU58zjV69exfHxsZ1ciUQCv/jFL5DJZBoCigwc+uErPssWHErETCzQOCkMf89+dezjNT8/j2q1inA4jL29PZvwZXd3F9Fo1ILCvNhw3XiyxmIxhEKn8zmcnJygr68PDx48wPr6uo1y4AWDkxRzQuKhoSH09/eju7sbXV1dyGazSCQSdsL5anwfpA2FToe8Mclx+fJl69NWqVRwfHyM/f195PN59PT02CQpzPSlUim7kPPCxOUGh+hx2wYz0/7EYzbZb+dvgtl2vt9mH0rNjr1gG57g770XWa/gc46Pj7G2toYnT56gra0N0WgUh4eHSCaT2Nrawu7urmXJS6WSJX7C4TB2dnawuLiI9fV1S6xxDgNevKampnD58mWbVDw4YdMPTSgUQl9fH0ZHR/Ho0SPEYjHbNjy+eQywSiGYIOL24c85MS4FP1z9OcxsPodfioiIiIiIiLRSs6A/0LxFy/MSE0wCMBAaDodtGRwdwWSET0T4zh7B0RlnBUZ9TC5Y0Mk4UDgcRldXl81L4Ns6NXtNH5T2y/VV+sE5MpoFd4OV9XwetwtbJWWzWYyPj2N7exvLy8sWc9jb28P+/j7S6TRyuRxyuRx6e3sRj8ctNsMA+LVr11Aul21eAb728fExyuUyVlZWAAA9PT2YmJiw+ENbW5slRHy1PEc0cHQFl9ve3o79/X0Ui0VsbGzg3r17NkcD4yR+DghuawbOp6amMDY2hqGhIYyMjCCZTNpzfDLLt47ntgwmvNipZX193UZjsKXRyclJQytt7r/gCBUfrwvGbX0bMB/vCe5PHxf1x0QwIeHjmolEws6DkZER7O7u4ujoqGFeC8ZpuY+TyaQdy4w/s0sP9x3fA38fjFU2W29/DAe3dVCzmObz/M0nIvj/YDuUZgchD9COjg6Ew2G89dZbqNVqKJfLFpxnhpdV98ELmG+F4/nsWvC1feaYB2gul8P58+exsLCAx48f4+DgwAKf7CvmkyxcB46sYMaQrZIYDL148SImJyftRAVgWctqtYpKpWKjCbq7uxGNRhsuvH7S3uAF21d3+5EasVgM3d3dGBsbs/3gs+Dc5j6LxyF8wNOedM/LevusIwDbDgywc/u/yCiF4DHks/rPO/n8h6Qf2uWTU1/Hv49mVQkMjAOn26VQKGBlZcWSTpwLZHV1FbVaDfV63f7PD4VsNmvDExOJBLLZLNLpNAYGBjAxMYGenh7EYjGbG8L3d/ymF6CXSUdHB0ZGRvDGG2+gUqlgZGTEtikdHR01tGlqNmlRM0wstLe3o16v24dTR0eH7Rf+5xMXIiJ/Cb436k9/+tMzn+fnAfBzP/iWfcH+9X5eiMHBQXvsR9d933rT/znX58/93m7dumWP/TwMZ/HzOADA3NycPd7Z2bHHv/71r89cRnD+BxofH7fHv/zlLxt+59fNH1/ft33953TWewvOHeHnRzmLn4/l7t27Db/LZrNNl/1D3rYiItI6PrDfbMRB8GeMSzDmxPgHK7MZP2FFOLtoMFbh55sCngZJg21jgokHdrdoNv+ib9/jEyOsavexp3A43FBs6N878Gy3Cl9AHJzT4qxtxddqFgfiXKjpdNraelcqFZtngMF9FusyYcD3w3XZ39/H9PQ0isUidnZ2rB0WA9g+NvTrX/8aV69etTlVk8kk+vv7G+J23EcLCwtWzLq+vo6dnR3E43Gbc7ZUKtn3FN/lgXGsYOvyS5cu4cqVK+jr67ORKuw047cx55HwIxHYccLHdjs7O5HJZGxUANvL87iJRqMYGBh4JuHk/++P4+AoHB4j/hj0xzn/luvDOJk/PvwIDh+n5N9z23R3d1tbLp4vwViij2fyZ+RHs/hC+WaF0P7nZx2zzWJ9XxfrakYRLTQeHH4H+Mplv/E50TNbF+VyOQBPZ5AHng2Oc9n+98GdzRPIB9l5MLPNEQP6bIW0sbGBjY0NlMvlhuwrJ8D1BySHM/nJc3gwspUQALvAMLHBCXr5twyw+uQMTyS/zn4b+hPMH7zBpAwDuD64z2X6YG3wos1l+vZL/Hnw4t/sRPGZ8W+iWZb9Rf7mrGMruFy/fi8S5GeChf/19/fb8tra2lCtVtHR0YHe3l5sbGxgZ2cH5XIZyWQSiUQCpVIJBwcHGBgYwPDwMLLZLEZGRpBIJOxDge2Xml3IfqhJCACIx+OIx+P4+7//e/z93//91z4/Fot949dglYjHvoQiIiIiIiIif0mMRfji2WBcx8dlGFviyAYfX2NbJI5E8FX1lUrFRkbw+T7uw6JexpB8dbp/Ha6XLxgEnsbxfLyKHU98AXAwceG3g98WvrLddyBh7A54WhTr42/B7h3EeB0TISzUOD4+RiqVatgHfg5bP4rDz1/AoP/Fixetsn5+fh7FYtG2GfdnpVLB+vo6YrGYjVJgwN3vt1AohHw+b++ZRZT7+/sNIwLq9bpN/sz9xVgSJ0fOZDK4efOmtXbn6AtfhMztDuCZdvc+wcB9w+0ei8WQTqeRzWaRz+dtfVKpFIaHh9HT02PvzY9Q8SMwfHtzn2xjK3lf+O33Abcpj1c/cobL53J5/DIG6uO/TFr4Y4vbkvuOy/LF9b5ji38/5OOQPhbtj9PgaI8gf9x+mxjg33Qiolmwlz9v9rzgBSMUCtnJ5Xvv+wOwWYCej5tV7TPz6i+OwNPEhT84u7u7ceHCBXz55Zeo1+tW1b6xsYFbt241ZPnY885nFnmwcvSGP+A4oYqfbJnryCF0PMH8kB+fZfZJEAC2HJ4Yfhv4k6zZMCtuI7+vgpnm4L4KJimCWdLgfm+WGXyeYJbT76tgQsNfPPy28YmT5wXzgyd6MNMe3CZch2w2i1Qqhf39fZTLZRweHlqlgE9A9ff3IxqN4ujoCKlUykY8dHV1NUyYzr/zSRt/Uf4hJyJERERERERE/pb4e30ftwoWZPoAaDCof3h4aPNABBMJ/C8UCllCwgfdgaexDsapgrEexr18gNhrVjzJGE3w98DTwtZg3MYvz28fvw0YU/OBXT7PV9X7UakMUrNlEN8Pg9m+80qz1+X6+8r8k5MTm0/g4sWLODo6spbcfoSAD7SXy2XU63XrxOILYhmv4xwR3H+dnZ02SsMnBBi07+7uRm9vLyqVCiYmJjAyMoJMJoNEIoHe3l6kUqmG9k/BQudgzJLby++HYHFvLBbD+Pg4Dg4OLAEFnI7Mnpqawrlz5ywREVwGY2l8/yzEblZoHozJcd18nLNZ8bLvAnN4eNiQ9OEyuD7BdkrNCsGDbaR8zNEnN55XRO0TJM2O92Cs76yY5Iv4m05EPI8/yYMBV38w8SRjgN0nIvyB7Ec0BPu7BxMdfjhVsFUTA8Bs0zQ5OYmf/OQn+P3vf49isWjZSX+gMcMbPPB8QoAXk66uroYD1V+Ygwe6v5AHPwiC28e/Ni8gwYOZ1fzM/H7dSRJ8va8bMXBWFjD4uxd1Vp/+YHUAf9ZsPf7cgq/DdTw5OUF3dzcGBgaeOTYBNFzcmiXL/MWs2bZv9fsSEZG/nrNauvzDP/zDX3hN/naNjY3Z42q1eubzPv74Y3t87do1e5xKpewxK+GaLes3v/lN0+X69kvBlgl+BKBfz8nJSXv8q1/9quFvfDsmaXTp0iV77NuVra6u2uNyuWyP//t//+8Nf+/3x82bN+1xsAXUd+UrTb/PrdREROS7Cd7/N4ttBIOf/F2z9jVsG8TJlxkoPjo6stbnlUoF6XS6Idbg2/EAaIgx+ap4vtbz3gvjfb7tk3+NYPLFv64P+vO5zbbFWUFyX3Xu16tZTIuxRV+cy3iar8gnv/5MtITDYfT09GBychL5fB6FQgFAY9sk/zf8zwfwGYdkUonbg499TDMUClk7+UwmY902AKC/vx+ZTAbxeNwmaeacFs3ikH778T8+h0mLZoXOfP1Q6Ol8uMfHx8hkMujv72/4Xhxc/+D+YELorO3sk1W+wNgXhTc7Hnxc1b9vv839sR7sJOPjc8HYarMk2/MKh79NMuHbtGSiv+lExFnBa5858r/jAcKgva8U58nWrLWPb2PjTyB/IfaJA3+R8Qc4A/V+vePxON555x1MTEzg7t27uHv3LkZGRvCjH/0I6XQanZ2dz1ThA08vGsz08SLjJ15hUuCsincOl+J68e98DzO+b24nf3FjUsJX2Aczd8F983WJBv7XLDjebH9/2+D5iyY8vuvrfFPP217Msrb6NUVERERERETk5ReMr5x1/9+sUNEH0QE0xL4Yn4lEImhvb7fWTKVSCbu7uxgaGnomydAsKOxf27+uD+oGA9vN1j0Y8Pc/8210GAD3Aehg3Cm4zYJtnvzcnvybYMAaeHYeCQavg22nfFA6OBqjra0NiUQCQ0NDuHbtGtbW1rC6uord3V1LBvn1C8Ys2VbJJ0V8EiQUCiEajdpzOOnyxMQEBgYG7D+25OLyOM9CsBC2WRLCJ378fgmO6OB753vu7OxENpu1+GMkErF1DcYGfRIl+NpfF5f06+CXFXyuPx59Qin4/v3v/THFx80SEf51/Xnm/2v2HoKJsmbP+3PGUoG/8UTEtw3K/rWquM7qFZ/JZDA0NIQ333zzL7xGp4LbQ1VuIiIiIiIiIiIvt2aB+2CnhGbFvb5SnYHQcDiM3t5enD9/HicnJ9ja2sLh4SESiQTK5TIODg6wt7eHnZ0d7O/vW8eOUOhp/38GsP1rNAsq+1EDwffBZALnOPABcF9U698jf+9HEXDkADGIHaxIZwKFgXoG/n3CwFfI+zboDC4zccFEjG/fzoJpvh7wtCKfSY9wOIxEIoFIJII//OEPePjwIfL5vI1QYScVFijzddiOnsvk+w+Hw4hGo+jt7bW5JeLxOFKpFGZmZtDX14dkMmmjH4IJpWAnGb4G23T5fcZ18++P+8Lva7a24uTanZ2d1pqcWFTO1/Etofzx6xMgPpjvkwc8lnxs2ScJfHIkOKojeJ6wZZlPMHA9mxWz+6STn2fYH4fNRkM8L4l31igH/36e9/sX9TediBARERER+b7zbY5u37595vNKpZI9/r//7//bHr/ozYFvuxSstqPg6F/fjum//tf/ao+np6ftsV9/eb6BgQF7/N5779njf/zHf2z6fN+yCQB+/etf22PfesDfJAf3rd+nwRt28hNHArDWDkDjjataM4mI/LD4IOc36VgRHCnAanPOWbC3t4f9/X3s7OxYQoLzJJTL5WdafPvqbwbp+f1mf3+/IYjvg8v8jPMdRp7XVoiTLnP+1oODA2uJFFwXPzG0Dzjztfg3AKwKnx1EmgWJfVt43zWE++Hw8NC2i18fbjv+LZcV/P6XSCQQj8cxOjqKu3fvYnFxEYVCAXfu3MHOzk7DPmXw3wfI2Uqpt7cXuVwOuVwOFy9eRCQSsflFw+GwTXYdiUQQDodt1IsfWeLXLTj/hU9e8d/N5ij1oxd8a3ufOIhEIpZ08EmfSCRiiRpOvM2kS/DYZfKLzhphE/w7v27cJ6HQ6bwTPqHD1ySOeuF79Mvg+nK7MBHm33swSdjsPA0mE7/OdxkBEaREhIiIiIiIiIiIiDTwbcSBZ0cf8GfBfzcbNcEKe1bLM3Bdq9XQ1taGZDKJbDaLZDIJ4Gl1PIPhfpQA8GxQNhiwDr4P/7ehUMgmvw5WuvsgPkcxBNtTBYPAwd/5EQ8+WdEsoB1MsPBnzbann+yb2+Cs0Sl87AP9TCR0dXVhZmYGxWIR58+fx4MHD6xtO7FVe1tbmyUaOMF0PB5HLBazURZ+5AYTDz5h41u6+5ERZ83L0WxUgX9/vpWVnzPCB/mZdOIy/LHBUSo8NtiBhvP/Hh8fIxwON+x7vz+C6xhsv+UTZX5f+VExfM7h4aFtdz/aJdiO6qxjg+8huK99O60XKUr6pskJ75s8X4kIERERERERERERadBsZAMFA6PB9i0MqPqAcjgcRjKZRE9PD3K5HMrlMiKRCI6Pj5HNZjE4OIi+vr5nJgQOtkfygX4/Z4BvgRMcbeAr4v16+1Y3/Bv+jIF/PzH0WdugWSW6D0b7ADYD5H77cPSFH7nh2w8Fg/LB9k9n8evW1tZm8yQkEgmkUimk02n09PQ8E6znaEo/T0Q6nbYEEhMOHJ0RTNAEJwUPjlZolpjw7yUYPGdiin8fTMJw+wQn4ebfBkfN+G3YbBJ2v97N9rPft8GfBdfJ/9sfq36i6+BrBPfpWSOT/Pngj42vSxgG//6sJNmfmxIRIiIiIiLfY6+88oo9vnfvnj1eW1treJ7/d7lc/sav49sCDQ4O2uMLFy40fQ4AXLp0qenv1KLnu/vJT35ij+fm5uzx/Py8PQ4eA59//rk9Xl9f/06v79tuBbGKEADOnTtnj//dv/t33+k1RUTk+6VZMPNFW7n4RAR/xkD4wMAAdnZ2UCqVUKvV0N7ejuHhYYyMjKC3t9fa4QRHYvhq92BbJb5GMAnhX9sHqYPv6azJoZtN5hysUPcjK3xAt9kcAb7q3a+DH1kBwFoZBees8MmJ4HoG35dfP/6MbZ9YMZ9KpdDT09Pwd8fHxw0JhuBcFWwP5Zfvkz5+xILfPsG5ELhtg4kIv835fv0243r4vw9O/Ox/zt/5/eGfGzwWuGy/P4JJiOCxEnz94Pqd9bo8V/hcvrdgMssnoYKCy212nPv3EhzBwd8FkyvB5MVZyQ2NiBAREREREREREZGWCragAdBQ8c/fMdja1dWFkZERdHR0IB6PY3l5GUNDQxgaGkJ/f79V7PugNQPZ+/v7DcFWP1cC8HQiaqBxYmlWwbNlEAPyXE5w5IcPGrNND98D52nwczgEkx/8e64fkwx+UmUfiO7o6GhoA+TbDfmKdQb5uR2CoxiaYRIiOA9GKHQ670MoFGqYEJrvMZgA8cvzSQU/99TJyYlNnB2c54I/CyaEgi2TggH4w8PDhpEpPjnDyZyBp/NZ+UA+2zVx/3Ff8+/8PCI+eeK3ZTDpFdwWfC63mf+ZTzpx3/ntwOVxm/kRI9QsWcKf83X93/qkTjAZF0zk8LE/FoPv+XleNDHpKREhIiIiIiIiIiIiDdie588tm81iamoKP/7xj7/R3/k5DFqJcwbIyy+RSPxFXqfZsfmix9F3Od7+UufEn8vZTcRERERERERERERERES+I42IEBERERH5HvPzMPzqV7+yx//yL//S8Dw/L8SLzBGRTqcb/v3aa6/Z45///Of2eGZm5oXWU/NCfHPBbba8vGyPR0ZG7PH/9X/9X/b44cOH9vgf//EfG/7ezxlRKpWavubzjg1/TPj5SGKxWMPz/PwRwXlDfmh8y4lWYDuGVioWiy1d/lntQP5ckslkS5cPtP44npycbOnyAaCrq6uly2fbExERkW9LIyJERERERERERERERKRllIgQEREREREREREREZGW0dg6EREREZHvMd++5+bNm/Y4l8s1PM+3alpZWbHH6+vr9vj111+3x8GWS74F1Iu2KVE7pj8vvz19mya/3wcHB8/8+88//7zpz31rpfb29obfndXCybfDmZ6ebvidPz6CvxMRERERaUYjIkREREREREREREREpGWUiBARERERERERERERkZZRayYRERERkZeEb90TbIv03nvv/aVXR1rorLZXY2Nj9vgf/uEfGn4X/LeIiIiIyPeFRkSIiIiIiIiIiIiIiEjLKBEhIiIiIiIiIiIiIiIto0SEiIiIiIiIiIiIiIi0jBIRIiIiIiIiIiIiIiLSMkpEiIiIiIiIiIiIiIhIyygRISIiIiIiIiIiIiIiLaNEhIiIiIiIiIiIiIiItIwSESIiIiIiIiIiIiIi0jJKRIiIiIiIiIiIiIiISMsoESEiIiIiIiIiIiIiIi2jRISIiIiIiIiIiIiIiLSMEhEiIiIiIiIiIiIiItIySkSIiIiIiIiIiIiIiEjLKBEhIiIiIiIiIiIiIiIto0SEiIiIiIiIiIiIiIi0jBIRIiIiIiIiIiIiIiLSMkpEiIiIiIiIiIiIiIhIy3T8tVdARERERERE5Pvo+Pi4pcvf2tpq6fIBoFAotHT58Xi8pcuPRCI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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Displaying a set of images with labels\n", + "def display_sample_images(image_paths, image_texts, sample_size=5):\n", + " fig, axes = plt.subplots(1, sample_size, figsize=(20, 10))\n", + " for i in range(sample_size):\n", + " img_path = np.random.choice(image_paths)\n", + " img = cv2.imread(img_path)\n", + " img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n", + " label = image_texts[image_paths.index(img_path)]\n", + " axes[i].imshow(img)\n", + " axes[i].set_title(label)\n", + " axes[i].axis('off')\n", + " plt.show()\n", + "\n", + "# Call the function\n", + "display_sample_images(image_paths, image_texts)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from collections import Counter\n", + "\n", + "# Flatten the list of all characters in image_texts\n", + "all_chars = [char for text in image_texts for char in text]\n", + "\n", + "# Calculate the frequency of each character\n", + "char_counter = Counter(all_chars)\n", + "\n", + "# Sort characters by frequency\n", + "sorted_chars = sorted(char_counter.items(), key=lambda pair: pair[1], reverse=True)\n", + "\n", + "# Plotting\n", + "plt.figure(figsize=(20, 10))\n", + "plt.bar([pair[0] for pair in sorted_chars], [pair[1] for pair in sorted_chars])\n", + "plt.xlabel('Characters')\n", + "plt.ylabel('Frequency')\n", + "plt.title('Character Frequency Distribution')\n", + "plt.xticks(rotation=90)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Word Lengths Statistics:\n", + "count 38304.000000\n", + "mean 4.302371\n", + "std 2.679291\n", + "min 1.000000\n", + "25% 2.000000\n", + "50% 4.000000\n", + "75% 6.000000\n", + "max 19.000000\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "word_lengths = [len(text) for text in image_texts]\n", + "\n", + "# Plotting the distribution of word lengths\n", + "plt.figure(figsize=(15, 7))\n", + "plt.hist(word_lengths, bins=50, alpha=0.7)\n", + "plt.title('Distribution of Word Lengths')\n", + "plt.xlabel('Word Length')\n", + "plt.ylabel('Frequency')\n", + "plt.grid(True)\n", + "plt.show()\n", + "\n", + "# Display basic statistics\n", + "print(\"Word Lengths Statistics:\")\n", + "print(pd.Series(word_lengths).describe())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Most common characters:\n", + "[('e', 19615), ('t', 14237), ('a', 12299), ('o', 11703), ('i', 11218), ('n', 11037), ('s', 9880), ('r', 9870), ('h', 8403), ('l', 6381)]\n", + "\n", + "Least common characters:\n", + "[('#', 36), ('6', 28), ('?', 28), ('7', 24), ('!', 21), ('/', 9), ('Q', 6), ('Z', 5), ('X', 4), ('*', 3)]\n" + ] + } + ], + "source": [ + "# Displaying the most and least common characters\n", + "print(\"Most common characters:\")\n", + "print(sorted_chars[:10]) # Top 10\n", + "\n", + "print(\"\\nLeast common characters:\")\n", + "print(sorted_chars[-10:]) # Bottom 10\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 0 corrupt images during re-check.\n" + ] + } + ], + "source": [ + "# Re-checking for any corrupt images after the initial cleanup\n", + "recheck_corrupt_images = []\n", + "\n", + "for path in image_paths:\n", + " try:\n", + " img = cv2.imread(path)\n", + " if img is None:\n", + " raise ValueError(\"Image not readable\")\n", + " except Exception as e:\n", + " recheck_corrupt_images.append(path)\n", + "\n", + "print(f\"Found {len(recheck_corrupt_images)} corrupt images during re-check.\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Observations:\n", + "1. Character Distribution: The most frequent characters are common English letters ('e', 't', 'a'), which is expected given the nature of English text. The least common characters include special symbols and less common letters ('Q', 'Z', 'X'), which might not be surprising but warrants attention when designing your model to ensure it can recognize these infrequent characters adequately.\n", + "2. Word Lengths: The average word length in your dataset is around 4 characters, with a standard deviation of approximately 2.68. This variability indicates that your model will need to handle a wide range of input lengths. The maximum word length is 19, which is crucial for defining the dimensions of your model's input layer or for padding sequences.\n", + "3. Class Imbalance: There's a significant imbalance between the most and least common characters. This imbalance can lead to a model that performs well on frequent characters but struggles with rare characters or symbols.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Approach to Address Class Imbalance\n", + "One effective strategy is to use a weighted loss function during training, where less frequent classes (characters) are given higher weights, encouraging the model to pay more attention to these classes. This section will outline how to calculate class weights and apply them in a training loop, assuming a hypothetical neural network model setup for context." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0: 103.25689223057644, 1: 4.939395755904568, 2: 60.23318713450293, 3: 8.570730185146662, 4: 30.977067669172932, 5: 33.8811677631579, 6: 722.7982456140351, 7: 1.4360230045311955, 8: 3.8446715192235907, 9: 1.0424974696356275, 10: 240.9327485380117, 11: 11.472988025619605, 12: 15.488533834586466, 13: 34.41896407685881, 14: 37.38611615245009, 15: 58.60526315789474, 16: 38.04201292705448, 17: 77.44266917293233, 18: 90.34978070175438, 19: 60.23318713450293, 20: 44.25295381310419, 21: 28.911929824561405, 22: 42.51754385964912, 23: 77.44266917293233, 24: 4.683357962941912, 25: 6.2131654350776655, 26: 7.45152830529933, 27: 13.468290290944752, 28: 8.997488534614545, 29: 10.180256980479367, 30: 7.227982456140351, 31: 6.949983130904184, 32: 5.503539941223617, 33: 29.30263157894737, 34: 24.924077434966726, 35: 8.121328602404889, 36: 3.700332315430214, 37: 8.960308829926054, 38: 15.378686076894363, 39: 6.927778711955608, 40: 361.39912280701753, 41: 7.972039473684211, 42: 4.939395755904568, 43: 3.305479781771502, 44: 23.316072439162422, 45: 43.3678947368421, 46: 9.072781325699186, 47: 542.0986842105264, 48: 52.88767650834403, 49: 433.67894736842106, 50: 0.17630658889682943, 51: 0.9149344881190318, 52: 0.49722420014723806, 53: 0.3724484261150988, 54: 0.11054778163864926, 55: 0.6296151965279051, 56: 0.7722203478782426, 57: 0.2580500698372135, 58: 0.19329601861669685, 59: 14.455964912280702, 60: 2.359515491667144, 61: 0.33982051979973443, 62: 0.5829018109790606, 63: 0.19646595423050695, 64: 0.185285374420414, 65: 0.7656761076419863, 66: 14.750984604368062, 67: 0.2196955153842052, 68: 0.21947315150223737, 69: 0.15230699844364018, 70: 0.5459201250861292, 71: 1.383787324085581, 72: 0.7627135901660589, 73: 8.604741019214703, 74: 0.7879341340269278, 75: 29.704037490987744}\n" + ] + } + ], + "source": [ + "from sklearn.utils.class_weight import compute_class_weight\n", + "import numpy as np\n", + "\n", + "# Assuming 'char_list' is a list of all characters, and 'image_texts' contains all the words in the dataset\n", + "all_chars = ''.join(image_texts)\n", + "char_freq = {char: all_chars.count(char) for char in char_list}\n", + "\n", + "# Create a list of all characters in the dataset in the same order as 'char_list'\n", + "y = np.array([char for word in image_texts for char in word])\n", + "\n", + "# Calculate class weights\n", + "class_weights = compute_class_weight('balanced', classes=np.unique(y), y=y)\n", + "class_weight_dict = {i: weight for i, weight in enumerate(class_weights)}\n", + "\n", + "print(class_weight_dict)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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 +}