confusion_matrix.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from tensorflow.keras.models import load_model\n",
    "import numpy as np\n",
    "import cv2\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import itertools\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sn\n",
    "# from matplotlib.pyplot import figure\n",
    "\n",
    "# figure(figsize=(8, 6), dpi=80)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "model_name= \"v4_epoch-10\"\n",
    "model = load_model(model_name+\"/model.h5\")\n",
    "\n",
    "folder_path=r\"C:\\Users\\Raghu\\Desktop\\Gestures\\Confusion Matrix\\all\"\n",
    "\n",
    "real=[]\n",
    "predicted=[]\n",
    "\n",
    "for i in os.listdir(folder_path):\n",
    "\n",
    "    img_path=os.path.join(folder_path, i)\n",
    "\n",
    "    t=cv2.imread(img_path,cv2.IMREAD_UNCHANGED)\n",
    "    t=cv2.resize(t, (128, 128))\n",
    "\n",
    "    preds = model.predict(t.reshape(1, 128, 128, 1))\n",
    "    preds = np.argmax(preds, axis=1)\n",
    "    predicted.append(preds[0])\n",
    "\n",
    "    img_number=int(os.path.splitext(os.path.basename(img_path))[0])\n",
    "\n",
    "    if 0 <= img_number <= 11:\n",
    "        real.append(0)\n",
    "    elif 633 <= img_number <= 658:\n",
    "        real.append(1)\n",
    "    elif 12 <= img_number <= 35:\n",
    "        real.append(2)\n",
    "    elif 36 <= img_number <= 57:\n",
    "        real.append(3)\n",
    "    elif 58 <= img_number <= 80:\n",
    "        real.append(4)\n",
    "    elif 81 <= img_number <= 102:\n",
    "        real.append(5)\n",
    "    elif 103 <= img_number <= 127:\n",
    "        real.append(6)\n",
    "    elif 128 <= img_number <= 149:\n",
    "        real.append(7)\n",
    "    elif 150 <= img_number <= 172:\n",
    "        real.append(8)\n",
    "    elif 173 <= img_number <= 198:\n",
    "        real.append(9)\n",
    "    elif 199 <= img_number <= 223:\n",
    "        real.append(10)\n",
    "    elif 224 <= img_number <= 248:\n",
    "        real.append(11)\n",
    "    elif 249 <= img_number <= 272:\n",
    "        real.append(12)\n",
    "    elif 273 <= img_number <= 298:\n",
    "        real.append(13)\n",
    "    elif 299 <= img_number <= 327:\n",
    "        real.append(14)\n",
    "    elif 328 <= img_number <= 355:\n",
    "        real.append(15)\n",
    "    elif 356 <= img_number <= 380:\n",
    "        real.append(16)\n",
    "    elif 381 <= img_number <= 401:\n",
    "        real.append(17)\n",
    "    elif 402 <= img_number <= 428:\n",
    "        real.append(18)\n",
    "    elif 429 <= img_number <= 455:\n",
    "        real.append(19)\n",
    "    elif 456 <= img_number <= 480:\n",
    "        real.append(20)\n",
    "    elif 481 <= img_number <= 505:\n",
    "        real.append(21)\n",
    "    elif 506 <= img_number <= 531:\n",
    "        real.append(22)\n",
    "    elif 532 <= img_number <= 557:\n",
    "        real.append(23)\n",
    "    elif 558 <= img_number <= 583:\n",
    "        real.append(24)\n",
    "    elif 584 <= img_number <= 608:\n",
    "        real.append(25)\n",
    "    elif 609 <= img_number <= 632:\n",
    "        real.append(26)\n",
    "    else:\n",
    "        real.append(-1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NGdbAhjjz2RCrIcMaZGo4m9kk3t3DHE3RKy0nTpzA2LFjcc899+Cll17Czz//jIceegiff/45hg4dio0bNyrW9vR0Q02N7Qmsrq6DweC4fZrSjcqqKvx9YRqCAgIQEXYH/rV+A7oEdUZYt64OmQ/I8TqxIc58NsRqyLAGNsSZz4ZYDRnWIFODlKfopuX1119HWFgYlixZglatWmHixImYM2cOvv32W8ybNw9z585VrF1VVQcPD53NMYNBj8rKWpdolJSVIfmjj3FzC29MHj8OR3NzkXXkCEYOfsju2Vdy9deJDbHmsyFWQ4Y1sCHOfDbEasiwBpkazmY2m1X7chZFNy2HDx/GSy+9hG7duuGll16C2WxGv379AAA9evRAcXGxYu28PCMCAnxsjgUG+lx1eVDERs6vufjfOR8jIuwOTB7/BNzd3PDz3kycOnMWz7/5NibNeA1bftqNn/fuw+uzPrSr5cqvExvizWdDrIYMa2BDnPlsiNWQYQ0yNUh5ir8RX6v9I+Hm5gZPT0+bnyn5ETEZGUUAgMTEMOh0GsTHByMkxA9btxYI3Sg9fRofLfgHhiYMxMiHH4JGowEAjB81Egs+nIV5s97DvFnvIbZPb/SKjMDMGS8LtwY2xG3IsAY2xJnPhlgNGdbAhjjz2XAtZpNJtS9nUfTDJSMiIrBv3z7r99HR0dizZ0+9P2+sxn64ZHCwL5KS7kNoqB+Ki8sxe/Zu619cR7nRRn0fLrl8zVps3LYdHu7uNsf733cvHh38sPX7ZavXoLKqGhPGjK630dgPlxT5dWLD8Q0Z1sCGOPPZEKshwxrYEGc+G67z4ZL7tm1WrRUR01+11pUU3bR069YNHh4e1u9ramqs31ssFtTW1uLIkSNNntvYTYvI6tu0OFJjNy1EREREdDVX2bRkbN6kWiuqf7xqrSspetuEzZvV2/UREREREZGcFN20dOig/NUEIiIiIiKSG29QTURERETkwpx5K2K1KH73MCIiIiIiInvwSgsRERERkQtz5q2I1cJNi5OocWevqcNLFJ3/yTftFJ1PRERERARw00JERERE5NLMZvmvtPA9LUREREREJDReaSEiIiIicmFmE+8eRkRERERE5FRSX2kJDfVDUtJ9CA31Q2HhRSQnb0d29ik2APgHBiEiJhYtfFuhurICh3/ZjeP798HbxxfRcQPRpv2tMJnq8FtONvZu/dHuu1K46uskY0OGNbAhznw2xGrIsAY2xJnPhuvge1pcmF6vRUrKAKSn5yImZjHS0jKRmpoALy+3Zt/wbNESfYeMQNbunVj50fvYuXY1Ivr2R/vOweg3dCTOnSrDqrkpWL9oIVq3vxV33dtXuDWwIeZ8NsRqyLAGNsSZz4ZYDRnWIFODlOeUTUt5ebnijchIf+j1WqxYcQgmkwWbNuUiL8+IuLjgZt/wvtkH+dkHcfLYUQDAmZIilJwowK0hoagqL0fWrh0wm82oqihH/uGDuKVjR+HWwIaY89kQqyHDGtgQZz4bYjVkWINMDWczm0yqfTmLopsWs9mMWbNmISkpyXrs7Nmz6N27N95//31YLBbF2kFBvsjPN9ocKyg4h5AQv2bfKPv9BH7Z+G/r9+4GA9p27ITi3/Lx49fLUFdba/1Zx9CuOFtq3+e9uOrrJGNDhjWwIc58NsRqyLAGNsSZzwaJRtFNy2effYaMjAyMHz/eeszPzw+rVq3Czz//jPnz5yvW9vR0Q02N7W6wuroOBoPj3sYjQ8PNwwOxw0bhdFGh9crLZT0eGIAWvr44uHunXQ0ZXidZGjKsgQ1x5rMhVkOGNbAhznw2XIvZbFbty1kU3bSsXr0af//73xEaGmpzvGvXrvjwww/xzTffKNauqqqDh4fO5pjBoEdlZW09f6L5NVr4+mHQ2PGoqqzAtjWrrMf17u6IGToS/oFB2LhsCaorK+3quPrrJFNDhjWwIc58NsRqyLAGNsSZzwaJRtFNy/nz53Hrrbde82ehoaE4d+6cYu28PCMCAnxsjgUG+lx1ebC5Nm7p2AkJ457CyeNHsX3NKuvvKN7k5Y1Bjz0Jvd4NG5amoeLCebs6gGu/TrI1ZFgDG+LMZ0OshgxrYEOc+Wy4Fr6nxU4BAQHIycm55s+OHj2Ktm3bKtbOyCgCACQmhkGn0yA+PhghIX7YurWg2Te8fXwRO3w0DuzchsztW6zHNVot+o9MxPkzp7F51XLU1tTY+/QBuO7rJGNDhjWwIc58NsRqyLAGNsSZzwaJRmNR8N3w3377LRYtWoS5c+eiU6dO1uO//fYbpk2bhiFDhmDs2LFNnhsVtaBRjwsO9rXek7u4uByzZ++2/sV1FJEbU4df+w30UbHx6B7dE7WXLtkcv2g8A7+2/qirrbW5SYKxrBQ/fLXoqjmffNNO8TU0BRtizGdDrIYMa2BDnPlsiNWQYQ2iNzIynnHo81DKj/9cplrrgUfHqNa6kqKbFgD4xz/+gU8//RT+/v7w9fXFmTNnUFZWhr/85S945pkb+4vQ2E1Lc1ffpsVRmrJpISIiInI1rrJp2bT8S9Va8YmPq9a6kuK3TXj66acxevRoZGZm4vz58/Dz80N4eDgMBoPSaSIiIiIikoAq93rz8vJCnz591EgRERERETUrzrwVsVoUfSM+ERERERGRveT5VB0iIiIiombImbciVguvtBARERERkdB4pUViSt/dK3mKruEH2emtufL/lwMiIiIie5jN8v/7Eq+0EBERERGR0HilhYiIiIjIhfE9LURERERERE7GKy1ERERERC6sOXxOi9SbltBQPyQl3YfQUD8UFl5EcvJ2ZGefYkOF+a3926NrZA94tmiJS9XVyDuchZPHjsKr5c24/Z5euLl1G5hNJhTl5yFn7x5YHPA/NhnOhRoNGdbAhjjz2RCrIcMa2BBnPhskEml/PUyv1yIlZQDS03MRE7MYaWmZSE1NgJeXGxsKzzd4eiE8pj9+zdqP9BVLsX/HVnSN6IHW7TsgIqY/jKfK8OPKr7Dzu9Vo7e+PwG7dhVyHjA0Z1sCGOPPZEKshwxrYEGc+G67FbDKp9uUs0m5aIiP9oddrsWLFIZhMFmzalIu8PCPi4oLZUHj+Td7eKM7PRemJ3wAA58+cxtmSYvje0ha71q/F8QOZsFgscHP3gFarw6XqaiHXIWNDhjWwIc58NsRqyLAGNsSZzwaJRvFfD8vMzMTChQuxf/9+VFRUoF27dujWrRuefvpphIWFKdYNCvJFfr7R5lhBwTmEhPixofB8Y1kpjGWl1u/d3N3h27YtCvN+te7Qew16CL63tMWZ4iIU/5Z/w63LZDgXajRkWAMb4sxnQ6yGDGtgQ5z5bLgW3j3MTlu2bMHEiRNx99134/PPP8f333+PDz74AN26dcPEiROxZ88exdqenm6oqbE9gdXVdTAYHLdPk6Gh9Hy9mxsiY+Nw/tQp65UXAPhl4wZs/no5NDodwnr1sbsjw7lQoyHDGtgQZz4bYjVkWAMb4sxng0Sj6NmaO3cu5syZgz59/vsvpZ06dcJdd92F0NBQzJ07F0uXLlWkXVVVBw8P209sNxj0qKysZUOl+V4tWyKyXxzKzxuxf8d2m5+ZzSbUVFXh+P59iIjpb3dLhnOhRkOGNbAhznw2xGrIsAY2xJnPBolG0SstBQUFNhuWK8XGxuLYsWOKtfPyjAgI8LE5Fhjoc9XlwebeUGq+b9t26J0wGKUnf8O+bVtgNpug0+vRd8gIeLZoYX2cVqtD3aVLdrUAOc6FGg0Z1sCGOPPZEKshwxrYEGc+G67FbDar9uUsim5aNBpN/WGtFrW1yu1wMzKKAACJiWHQ6TSIjw9GSIgftm4tYEPh+Z4tWiAqNg7H9u/D0X0Z1uOmujpUXryArhFR0Op0MHh6oUt4BE4eP2rvMqQ4F2o0ZFgDG+LMZ0OshgxrYEOc+WyQaDQWi8Wi1PCIiAjs27fvhn9en6ioBY16XHCwr/We3MXF5Zg9e7f1L66jyNC40fnJU3TXPH5b1D3ofPsdqPvTpvS3nCPIP3wQ3e/phdb+7WGqq8PJ40fx68EDQD1/Dd+a2/g3lslwLtRoyLAGNsSZz4ZYDRnWwIY489kAMjKecejzUMrKjz5QrTVq2iuqta6k6KalW7du8PDwuObPLBYLamtrceTIkSbPbeymhZRV36bFkZqyaSEiIiJyJG5aruasTYuib8TfvHmzkuOJiIiIiJo9s1n+/8ir6KalQ4cOSo4nIiIiIqJmgDeoJiIiIiJyYWaT8+7qpRZF7x5GRERERERkL15pISIiIiJyYXxPC9F1qHFnr6nDSxRvfPJNO8UbRERERHTjuGkhIiIiInJhZpP8V1r4nhYiIiIiIhIar7QQEREREbkws5l3DyMiIiIiInIqqa+0hIb6ISnpPoSG+qGw8CKSk7cjO/sUGyrPV6rhHxiEiJhYtPBtherKChz+ZTeO798Hbx9fRMcNRJv2t8JkqsNvOdnYu/VHh/y+p6u+VmrOZ0OshgxrYEOc+WyI1ZBhDTI1nInvaXFher0WKSkDkJ6ei5iYxUhLy0RqagK8vNzYUHG+Ug3PFi3Rd8gIZO3eiZUfvY+da1cjom9/tO8cjH5DR+LcqTKsmpuC9YsWonX7W3HXvX2FXIfaDRnWwIY489kQqyHDGtgQZz4bJBppNy2Rkf7Q67VYseIQTCYLNm3KRV6eEXFxwWyoOF+phvfNPsjPPoiTx44CAM6UFKHkRAFuDQlFVXk5snbtgNlsRlVFOfIPH8QtHTsKuQ61GzKsgQ1x5rMhVkOGNbAhznw2XIvZZFLty1mk/fWwoCBf5OcbbY4VFJxDSIgfGyrOV6pR9vsJlP1+wvq9u8GAth074ecf1mFP+g82j+0Y2hVnS+3/vBdXfa3UnM+GWA0Z1sCGOPPZEKshwxpkapDyFL3SkpOTc92f/+tf/1Ks7enphpoa291gdXUdDAbH7dNkaMiwBjcPD8QOG4XTRYXWKy+X9XhgAFr4+uLg7p12d2R4rWRYAxvizGdDrIYMa2BDnPlskGgU3bQkJibafP/II4/YfD9z5kzF2lVVdfDw0NkcMxj0qKysZUPF+Uo3Wvj6YdDY8aiqrMC2Nausx/Xu7ogZOhL+gUHYuGwJqisr7W65+mulxnw2xGrIsAY2xJnPhlgNGdYgU8PZzGazal/OouimxWKx2HxfVFR03Z87Ul6eEQEBPjbHAgN9rro82NwbrryGWzp2QsK4p3Dy+FFsX7PK+nuWN3l5Y9BjT0Kvd8OGpWmouHDers5lrvxaqTWfDbEaMqyBDXHmsyFWQ4Y1yNQg5Sm6adFoNE363pEyMv7YICUmhkGn0yA+PhghIX7YurWADRXnK9Xw9vFF7PDROLBzGzK3b7Ee12i16D8yEefPnMbmVctRW1Nj79O3ctXXSs35bIjVkGENbIgznw2xGjKsQaaGszWHN+JrLApe7oiIiMC+ffus30dHR2PPnj31/ryxoqIWNOpxwcG+1ntyFxeXY/bs3da/uI4iQ0PkNUwdfu030EfFxqN7dE/UXrpkc/yi8Qz82vqjrrbW5kqesawUP3y16JqzPvmmneLraIrmfL7Z4PlmQ+z5bIjVkGENojcyMp5x6PNQymczpqvWenbWHNVaV1J00xIeHo7Nmzdb/+Vx4MCB2Lhxo/X7Bx54AJmZmU2e29hNC7m++jYtjtSUTQsRERE1H66yaUl95XnVWpM/+Fi11pUUvW1CVVUV7r33Xpv/4t27d2/r/63kr4cREREREZEcFN20NHTLYyIiIiIiso/Z5Ly7eqlF0TfiExERERER2YufqkNERERE5MLMZufd1UstvNJCRERERERC45UWEpoad/ZK/WsHxRuT3yhUvEFE1NyVt1P+/2d4lyh/V0uipnLm56eohVdaiIiIiIhIaLzSQkRERETkwsxm3j2MiIiIiIjIqXilhYiIiIjIhfE9LS4uNNQPaWmPYOfOJ7Fy5XB0796GDSfMd+XGoZyjeOvDOZj4ShJefncmtu7afdVjPlr4BRYuW2F36zKebzZcaT4bYjVkWINajcvCuvhg11cDFJnN8928GqQsaTcter0WKSkDkJ6ei5iYxUhLy0RqagK8vNzYUHG+KzfOGI2Ym7YYg1vBjhAAACAASURBVOMfwLxZMzHp8bFYtW49Dh7JsT5m80+7cOBwtiOWAIDnmw2ebzbEnS9T47Lh8Z3wRXIvuOkd/69DPN/Nq0HKk3bTEhnpD71eixUrDsFksmDTplzk5RkRFxfMhorzXblx+qwRvSIjEHXXndBqtQgK6IRuISE4np8PACgqLcXGrdvRKyrSUcvg+WaD55sNYefL1ACAKWO6YnRCIOb/85hD517G8928Gs5mNplU+3IWaTctQUG+yM832hwrKDiHkBA/NlSc78qNrsFBeOLREdbvyysqcCw3D506dEBdXR3mf7kMY0cMg7fnTTfc+DOebzZ4vtkQdb5MDQD454YCDHthBw79es6hcy/j+W5eDVKeopuWJ554wub7EydOKJmz4enphpoa291gdXUdDAbH3XtAhoYMa1CjUVlVhb8vTENQQAAiwu7Av9ZvQJegzgjr1tUh8y/j+WaD55sNUefL1ACAsrM1Dp33ZzzfzavhbGazWbUvZ1F005KVlWXz/fDhw5XM2aiqqoOHh87mmMGgR2VlLRsqzpehUVJWhuSPPsbNLbwxefw4HM3NRdaRIxg5+CG7Z/8ZzzcbPN9siDpfpoYaeL6bV4OUp+qvh1ksFtVaeXlGBAT42BwLDPS56vJgc2/IsAYlGzm/5uJ/53yMiLA7MHn8E3B3c8PPezNx6sxZPP/m25g04zVs+Wk3ft67D6/P+tCuFsDzzQbPNxvizpepoQae7+bVcDa+p8XBNBqNaq2MjCIAQGJiGHQ6DeLjgxES4oetWwvYUHG+KzdKT5/GRwv+gaEJAzHy4Yesf3/HjxqJBR/OwrxZ72HerPcQ26c3ekVGYOaMl4Vch5rz2RCrIcMa2BBnvkwNNfB8N68GKU9jUfDyR3h4ODZv3my9wjJw4EBs3LjR5opLq1atmjw3KmpBox4XHOyLpKT7EBrqh+Licsyevdv6F9dRZGjIsAZ7Gql/7XDN48vXrMXGbdvh4e5uc7z/fffi0cEPW79ftnoNKquqMWHM6Hobk98obOQqeL7Z4PlmQ9z5ojfK27Vrcis6rBVSX49G9KgNjXq8d0lJo2fzfLt+IyPjGYc+D6Ukj3tUtdZbS/6pWutKim5aunXrBo1GU++vhWk0Ghw5cqTJcxu7aSFqjPo2LY7UlE0LERHdmBvZtDRVUzYt5Pq4abmaszYtit42IScnp+EHERERERHRDbM48a5eapH2c1qIiIiIiMh5tmzZgoSEBERGRmLMmDHIzc0FACxfvhx9+vRBjx49kJKS0qhZ3LQQEREREbkwrU6r2ldjlZSUYMaMGXj33XexZ88e9OvXD88//zyysrIwb948LF++HOvWrcPmzZuxbdu2htdox+tDRERERER0leLiYgwbNgyRkZHQ6XQYPXo0jh8/jnXr1mHw4MHo1KkT2rZti8cffxzffvttg/Pk+ShQIiIiIqJmSKtT72NFLly4gAsXLlx1vGXLlmjZsqX1+/DwcISHh1u/37FjBzp06ICTJ08iNjbWejwgIADLli1rsMtNCzV7atzZa+pw5e8288k3yt81h4hIZLyzF5HylixZgtTU1KuOT548GVOmTLnmn8nJycE777yDd999F8uWLcNNN91k/ZmHhweqq6sb7HLTQkRERETkwrRa9a60jBs3DkOGDLnq+JVXWa6UkZGB5557DtOmTUN8fDxWr16Nmpoa689rampsNjH14aaFiIiIiIga5c+/BnY9O3bswPTp05GcnIyEhAQAQOfOnXHixAnrYwoKChAYGNjgLL4Rn4iIiIiIHOrkyZN44YUX8MEHH1g3LAAwcOBArF69Gvn5+SgrK8PSpUsxaNCgBufxSgsRERERkQtT8434jfXNN9+gsrISL774os3xH3/8Ec8++yyefPJJVFVVYfTo0dy0hIb6ISnpPoSG+qGw8CKSk7cjO/sUGyrPZ+P6/AODEBETixa+rVBdWYHDv+zG8f374O3ji+i4gWjT/laYTHX4LScbe7f+CLPJJNwa2BC3IcMa2BBnPhtiNWRYg0wNsjVt2jRMmzbtmj8bPXo0Ro8e3aR50v56mF6vRUrKAKSn5yImZjHS0jKRmpoALy83NlScz8b1ebZoib5DRiBr906s/Oh97Fy7GhF9+6N952D0GzoS506VYdXcFKxftBCt29+Ku+7tK9wa2BC3IcMa2BBnPhtiNWRYg0wNZ9NqNap9OW2NTisrLDLSH3q9FitWHILJZMGmTbnIyzMiLi6YDRXns3F93jf7ID/7IE4eOwoAOFNShJITBbg1JBRV5eXI2rUDZrMZVRXlyD98ELd07CjcGtgQtyHDGtgQZz4bYjVkWINMDVKe4r8edvLkSZSXl+O2227DW2+9hdraWgBAmzZtMH36dMW6QUG+yM832hwrKDiHkBA/NlScz8b1lf1+AmW///cOGu4GA9p27ISff1iHPek/2Dy2Y2hXnC217zMIXPV1YkPM+WyI1ZBhDWyIM58N1yLie1ocTdErLQcOHMDw4cNx9Ogf/xV53bp1CAoKQufOnbF69Wp89913irU9Pd1QU2P7u//V1XUwGBy3T5OhIcMaZGm4eXggdtgonC4qtF55uazHAwPQwtcXB3fvtKshw+vEhjjz2RCrIcMa2BBnPhskGkXP1ieffIKXX34Z//M///NHTK/HhAkTAAD+/v5Yvnw5Bg8erEi7qqoOHh46m2MGgx6VlbVsqDifjcZp4euHfsMexfkzp7Hzu9XW43p3d/R56H/Q0q8VNi5bgurKSrs6rv46sSHWfDbEasiwBjbEmc+Ga3Hme03UoviVlivvy2yxWKz/94ABA3Ds2DHF2nl5RgQE+NgcCwz0ueryYHNvyLAGV2/c0rETEsY9hZPHj2L7mlXWu4Pd5OWNQY89Cb3eDRuWpqHiwnm7OoBrv05siDefDbEaMqyBDXHms0GiUXTTotFooNX+N7Fjx47/hrVa6PXKXejJyCgCACQmhkGn0yA+PhghIX7YurWADRXns3F93j6+iB0+Ggd2bkPm9i3W4xqtFv1HJuL8mdPYvGo5amtq7H36AFz3dWJDzPlsiNWQYQ1siDOfDdei1WlU+3IWjeXKyx8O9thjj2HChAno2/fq27Ru27YNixcvxuLFi5s8NypqQaMeFxzsa70nd3FxOWbP3m39i+soMjRkWIPojanDr/0G+qjYeHSP7onaS5dsjl80noFfW3/U1dbaXKE0lpXih68WXXPWJ9+0U3QNTcGGOA0Z1sCGOPPZEKshwxpEb2RkPOPQ56GUj6c/rlrr+Tlfqta6kqKbli1btuDdd9/FnDlzEB4ebj2elZWFF154AcnJyejTp0+T5zZ200Ikivo2LY7U2E0LERERNY6rbFrmvjROtdaU2UtUa11J0Tfix8bG4vz585g0aRK8vLzQtm1bnD59GufOncOMGTNuaMNCRERERETNi+L3ehsyZAgefvhhZGZmoqysDH5+foiIiICHh4fSaSIiIiIi6TWHz2lR5QbVer0ePXr0UCNFRERERESS4afqEBERERG5sOZwpUXRWx4TERERERHZi1daiFTw3k93K954bfh+Refz7mRERETkLNy0EBERERG5MK2Wvx5GRERERETkVLzSQkRERETkwvhGfCIiIiIiIieT+kpLaKgfkpLuQ2ioHwoLLyI5eTuys0+xofJ8NpourIsP5r91D+59bKND5vkHBiEiJhYtfFuhurICh3/ZjeP798HbxxfRcQPRpv2tMJnq8FtONvZu/RFmk8muniznQoaGDGtgQ5z5bIjVkGENMjWcSauV/zqEtCvU67VISRmA9PRcxMQsRlpaJlJTE+Dl5caGivPZaLrh8Z3wRXIvuOkd8z9PzxYt0XfICGTt3omVH72PnWtXI6Jvf7TvHIx+Q0fi3KkyrJqbgvWLFqJ1+1tx17197erJci5kaMiwBjbEmc+GWA0Z1iBTg5Qn7aYlMtIfer0WK1YcgslkwaZNucjLMyIuLpgNFeez0TRTxnTF6IRAzP/nMYfN9L7ZB/nZB3Hy2FEAwJmSIpScKMCtIaGoKi9H1q4dMJvNqKooR/7hg7ilY0e7erKcCxkaMqyBDXHmsyFWQ4Y1yNRwNq1Oo9qXs0j762FBQb7IzzfaHCsoOIeQED82VJzPRtP8c0MB5i47iuiwVg6bWfb7CZT9fsL6vbvBgLYdO+HnH9ZhT/oPNo/tGNoVZ0tL7OrJci5kaMiwBjbEmc+GWA0Z1iBTg5Sn6KZl7Nix0GiuvyP78ssvFWl7erqhpsb29/Krq+tgMDhuyTI0ZFiDTI2yszUOm3Utbh4eiB02CqeLCq1XXi7r8cAAtPD1xc7v/mVXQ5ZzIUNDhjWwIc58NsRqyLAGmRrO1hw+p0XRszV69GgAgMViwRtvvIGZM2cqmbNRVVUHDw+dzTGDQY/Kylo2VJzPhjha+Pqh37BHcf7Maez8brX1uN7dHX0e+h+09GuFjcuWoLqy0q6OLOdChoYMa2BDnPlsiNWQYQ0yNUh5ir6nJSEhAQkJCXjwwQfh5uZm/f7KL6Xk5RkREOBjcyww0Oeqy4PNvSHDGmRqKOWWjp2QMO4pnDx+FNvXrLLeHewmL28MeuxJ6PVu2LA0DRUXztvdkuVcyNCQYQ1siDOfDbEaMqxBpoazNYf3tEj7RvyMjCIAQGJiGHQ6DeLjgxES4oetWwvYUHE+G87n7eOL2OGjcWDnNmRu32I9rtFq0X9kIs6fOY3Nq5ajtsYxv5omy7mQoSHDGtgQZz4bYjVkWINMDVKexmKxWNQIRUdHY8+ePQ6ZFRW1oFGPCw72td6Tu7i4HLNn77b+xXUUGRoyrEH0Rnm7dk3qRIe1Qurr0YgetaHRf+a1PvuveTwqNh7do3ui9tIlm+MXjWfg19YfdbW1uPIfA8ayUvzw1aKr5nzyTePXIPK5aG4NGdbAhjjz2RCrIcMaRG9kZDzj0OehlGWzJ6nWGvPSPNVaV1J003LmzBnr/z1w4EBs3LgRf861atX0uyQ1dtNCJIqmblpuRH2bFkdpyqaFiIhIBty0XM1ZmxZF34h/7733QqPRWDcqvXv3tvm5RqPBkSNHlHwKRERERERS493D7JSTk6PkeCIiIiIiagakfSM+ERERERHJQZ5P1SEiIiIiaoaceStitfBKCxERERERCY1XWohU4F1SonhD6bt7rUyLVnQ+AIwa75jbol+PGndyU+N8ExERXdYc3ojPKy1ERERERCQ0XmkhIiIiInJhfE8LERERERGRk/FKCxERERGRC+N7WlxcaKgf0tIewc6dT2LlyuHo3r0NG06Yz4ZYDSXmZx7IwtRXZmD440/g6clTsSE9HQBQXFqKh0aOwrDHHrd+fTxvvt09QJ1zcVlYFx/s+mqAIrNd8XyzIW5DhjWwIc58Nkgk0m5a9HotUlIGID09FzExi5GWlonU1AR4ebmxoeJ8NsRqKDH/1OnTmJkyB6OGDcXXi9PwygtTsXjZCuzdvx+5efnoEhKMf331pfXr+Ul/EXId9Rke3wlfJPeCm97x/7h0xfPNhrgNGdbAhjjz2XAtWp1GtS+nrdFpZYVFRvpDr9dixYpDMJks2LQpF3l5RsTFBbOh4nw2xGooMb/01CnE9LkXve+JhlarRZeQEITd3h3ZOcfwa14eggIDHfLcr6TGuQCAKWO6YnRCIOb/85hD517miuebDXEbMqyBDXHms0GikfY9LUFBvsjPN9ocKyg4h5AQPzZUnM+GWA0l5t9x222447bbrN9fvFiOw0dyEHv//diQno7q6hpMmPoCqqurERV+N556fCy8vbxuuAeocy4A4J8bCjB32VFEh7Vy6NzLXPF8syFuQ4Y1sCHOfDZcS3N4T4uim5asrKwGH3PnnXcq0vb0dENNjcnmWHV1HQwGxy1ZhoYMa2BDnPkVFZVIfv8DdA0NRc8eUdi5ezdu69oFjyQ8iJpLlzAn9VPM/XwBkqZPs6ujxrkAgLKzNQ6d92eufr7ZEKshwxrYEGc+GyQaRc/WCy+8cN2fazQabN68WZF2VVUdPDx0NscMBj0qK2vZUHE+G2I1lJxfWFSE5A8+RKdbb8XLU6dAq9Xi1Wn//WeAl5cnxiWOwstvvg2TyQSdTnedadenxrlQgyufbzbEa8iwBjbEmc+Ga9HqpH3Hh5WiK9yyZct1v5TasABAXp4RAQE+NscCA32uujzY3BsyrIEN588/lJ2Naa+9gV49euC1F6fD3d0d1TU1SFv6FYznzlkfV1tXB51WC63Wvn/0qHEu1OCq55sNMRsyrIENceazQaKRdluWkVEEAEhMDINOp0F8fDBCQvywdWsBGyrOZ0OshhLzi0tK8M6sD/DYoyPwxJhEaDR//F6twcMDmVkHsWT5StTUXMJZoxGLly3HAzEx1seItA5ncMXzzYa4DRnWwIY489lwLc3h7mEai8VicVr9BkVFLWjU44KDfZGUdB9CQ/1QXFyO2bN3W//iOooMDRnWwIby81emRV/z+MLFX+Lb9eth8PCwOf7gwAF4MD4O89MW4XDOUei0WtzfuzeeevwxuLu7X3PWqPF7FF9Hebt2jW5cFh3WCqmvRyN61IZGPd67pKTRs0U932y4ZkOGNbAhznw2gIyMZxz6PJSyYemLqrUGjU1RrXUlqTctROQ49W1aHKkpm5YbdSOblqZqyqaFiIjExU3L1Zy1aeFtE4iIiIiIXFhzuOWxtO9pISIiIiIiOfBKCxERERGRC3PmG+TVwistREREREQkNF5pISIiIiJyYc3hPS3ctBBRo6hxZ6/Uv3ZQvDH5jULFG0RERORY3LQQEREREbkwvqeFiIiIiIjIyXilhYiIiIjIhTWH97TwSgsREREREQlN6istoaF+SEq6D6GhfigsvIjk5O3Izj7Fhsrz2RCr4aprOJRzFF9/vx6lp06hZQtvJMT2Q797e9s85qOFX8Db0xMTxoy2q3WZq75Was5nQ6yGDGtgQ5z5bLgOvqfFhen1WqSkDEB6ei5iYhYjLS0TqakJ8PJyY0PF+WyI1XDVNZwxGjE3bTEGxz+AebNmYtLjY7Fq3XocPJJjfczmn3bhwOFsRywBgOu+VmrOZ0OshgxrYEOc+WyQaKTdtERG+kOv12LFikMwmSzYtCkXeXlGxMUFs6HifDbEarjqGk6fNaJXZASi7roTWq0WQQGd0C0kBMfz8wEARaWl2Lh1O3pFRTpqGS77Wqk5nw2xGjKsgQ1x5rPhWrRajWpfzqLor4cVFRVd87jBYICfn5+SaQQF+SI/32hzrKDgHEJCHNeVoSHDGtgQZ75Sja7BQegaHGT9vryiAsdy89A7KhJ1dXWY/+UyjB0xDFnZ2aisqr7hzpVc9bVScz4bYjVkWAMb4sxng0Sj6KZl4MCB0Gg0sFgsNsfNZjN8fHzw3nvv4f7771ek7enphpoak82x6uo6GAyOW7IMDRnWwIY489VoVFZV4e8L0xAUEICIsDuw6vv16BLUGWHduiIr23G/HibDayXDGtgQZz4bYjVkWINMDWdrDu9pUfRsZWVl1fuz9PR0vPvuu0hPT1ekXVVVBw8Pnc0xg0GPyspaNlScz4ZYDVdfQ0lZGf7+jzR0aNsWEx9/DEdzc5F15AjefnGa3bP/zNVfKzXmsyFWQ4Y1sCHOfDZINE57T0vfvn1hNBobfuANysszIiDAx+ZYYKDPVZcHm3tDhjWwIc58JRs5v+bif+d8jIiwOzB5/BNwd3PDz3szcerMWTz/5tuYNOM1bPlpN37euw+vz/rQrhbg2q+VWvPZEKshwxrYEGc+GyQap2xa1q1bhwkTJqBnz56KNTIy/ng/TWJiGHQ6DeLjgxES4oetWwvYUHE+G2I1XHUNpadP46MF/8DQhIEY+fBD0Gj+uAw+ftRILPhwFubNeg/zZr2H2D690SsyAjNnvCzkOtRuyLAGNsSZz4ZYDRnWIFPD2bQ6jWpfzqKx/PkNJyr49ttvcf78eYwYMQKenp5N/vNRUQsa9bjgYF/rPbmLi8sxe/Zu619cR5GhIcMa2BBnvj2N1L92uObx5WvWYuO27fBwd7c53v++e/Ho4Iet3y9bvQaVVdXX/ZyWyW8UNnIVYr9WosxnQ6yGDGtgQ5z5bAAZGc849Hko5ZdNb6jWuif+r6q1ruSUTYu9GrtpISLXUt+mxZGasmkhIqLmzVU2Lf/vxzdVa/V44F3VWleS9nNaiIiIiIhIDvLc642IiIiIqBlqDrc85pUWIiIiIiISGq+0EBERERG5MK1W/usQ8q+QiIiIiIhcGq+0EJEw1Liz18q0aMUbo8bvUbxBRER0Gd/TQkRERERE5GS80kJERERE5MK0Wl5pISIiIiIicipeaSEiIiIicmHN4T0tUm9aQkP9kJR0H0JD/VBYeBHJyduRnX2KDZXnsyFWQ4Y1KNXIPJCFRcuWo6ikBD4tW2LYIw9jUFwciktLMWHK8/Bwd7c+9v57e+P5SX+xdxk832zwfLMh7Hw2SCTS/nqYXq9FSsoApKfnIiZmMdLSMpGamgAvLzc2VJzPhlgNGdagVOPU6dOYmTIHo4YNxdeL0/DKC1OxeNkK7N2/H7l5+egSEox/ffWl9csRGxaebzZ4vtkQdT4brkWr06j25bQ1Oq2ssMhIf+j1WqxYcQgmkwWbNuUiL8+IuLhgNlScz4ZYDRnWoFSj9NQpxPS5F73viYZWq0WXkBCE3d4d2TnH8GteHoICAx32/C/j+WaD55sNUeezQaJRdNOyadOmen9WWVmJpKQkxdpBQb7IzzfaHCsoOIeQED82VJzPhlgNGdagVOOO227D5GcmWL+/eLEch4/kILhzIHLz8/HbiZOYMPUFjH3mL/h43nyUV1TccOsynm82eL7ZEHU+GyQaRTctSUlJ2Lhx41XH9+/fj0ceeQQHDx5UrO3p6YaaGpPNserqOhgMjnsbjwwNGdbAhjjzZWlUVFQi+f0P0DU0FD17RMHbywvhd4Xh7397Dx+/PwunTp/B3M8X2N3h+WaD55sNUeez4Vq0Wo1qX05bo5LDP/vsM7z55pvWjYvZbEZqairGjh2LuLg4rF69WrF2VVUdPDx0NscMBj0qK2vZUHE+G2I1ZFiD0o3CoiJMf/11+PjcjNdenAatVotXp72AxBEj4OXlCT9fH4xLHIVfMvbCZDI1PPA6eL7Z4PlmQ9T5bJBoFN203HPPPfj888/x9ttvY+nSpUhMTMT333+PL7/8Eq+88grcr7gTj6Pl5RkREOBjcyww0Oeqy4PNvSHDGtgQZ76rNw5lZ2Paa2+gV48eeO3F6XB3d0d1TQ3Sln4F47lz1sfV1tVBp9VCq7XvH6E832zwfLMh6nw2XAvfiO8A4eHh+OKLL/Dpp5/C3d0da9euRXh4uNJZZGQUAQASE8Og02kQHx+MkBA/bN1awIaK89kQqyHDGpRqFJeU4J1ZH+CxR0fgiTGJ0Gj++AezwcMDmVkHsWT5StTUXMJZoxGLly3HAzEx1seItA4157MhVkOGNbAhznw2SDQai8ViUSN0/PhxPP3003j11VeRkJBg16yoqMb9LnlwsK/1ntzFxeWYPXu39S+uo8jQkGENbIgzX/TGyrToax5fuPhLfLt+PQweHjbHHxw4AA/Gx2F+2iIczjkKnVaL+3v3xlOPP1bv1eJR4/covg5R5rMhVkOGNbAhznw2gIyMZxz6PJSSe/BvqrWCw5S7kdb1KLppufPOO23+S2RdXR3MZjPc3d1hsVig0Whw4MCBJs9t7KaFiOjP6tu0OFJTNi1ERCQublqu5qxNi6K3TdiwYYOS44mIiIiImj1nvtdELYpuWjp06KDkeCIiIiIiEtwXX3yB3377DcnJyQCAqVOnYtu2bdDp/rir23333YdPPvnkujPkuUE1EREREVEz5MzPT7me2tpazJs3D/PmzcOIESOsx48ePYrVq1cjJCSk0bO4aSEiIiIiIof729/+ht9//x2PPvoozGYzAKCqqgolJSUIDAxs0ixuWoiIiIiIXJia72m5cOECLly4cNXxli1bomXLljbHJk2ahDZt2mDu3Lk4deoUgD/uKGwwGPDEE08gNzcXEREReOedd9CmTZvrdrlpIaJmRY07eyVP0TX8IDu9NdekeIOIiOjPlixZgtTU1KuOT548GVOmTLE5dq2NSGVlJe6++27MmDED7dq1w9/+9je8+uqrSEtLu26XmxYiIiIiIhem5ntaxo0bhyFDhlx1/M9XWerTs2dP9OzZ0/r99OnT0atXL1RXV8NgMNT75+rdtJSXlzcY9fb2btSTIyIiIiIi13etXwNriu3bt6OiosL6YfOXLl2CTqeDXn/9ayn1/jQqKsrmgyGvdPmDIY8cOXLDT5iIiIiIiOznSp/TYjab8d577+H222/HLbfcgtmzZ2PQoEE3vmnZvHmzw58kERERERE1X/369cO4ceMwduxYXLx4Effffz/++te/Nvjn6t20XPnBkGazGb/88gsKCwvx8MMPo7S0FJ06dXLMM1dQaKgfkpLuQ2ioHwoLLyI5eTuys0+xofJ8NsRqyLAGV2609m+PrpE94NmiJS5VVyPvcBZOHjsKr5Y34/Z7euHm1m1gNplQlJ+HnL17YPnPLSJFWgMb4jZkWAMb4sxngxzlz2/QnzBhAiZMmNCkGdqGHnDy5Ek8+OCDeOWVVzBz5kz8/vvvePDBB/HTTz817dmqTK/XIiVlANLTcxETsxhpaZlITU2Al5cbGyrOZ0OshgxrcOWGwdML4TH98WvWfqSvWIr9O7aia0QPtG7fAREx/WE8VYYfV36Fnd+tRmt/fwR26y7cGtgQtyHDGtgQZz4brkWr06r25bQ1NvSA5ORkDBkyBDt27IBer0dwcDDee+89pKSk2BWura3Fvn377JpxPZGR/tDrtVix4hBMJgs2bcpFXp4RcXHBbKg4nw2xGjKswZUbN3l7ozg/F6UnfgMAUcn49QAAIABJREFUnD9zGmdLiuF7S1vsWr8Wxw9kwmKxwM3dA1qtDpeqq4VbAxviNmRYAxvizGeDRNPgpiUrKwvjx4+HRqOxvjH/4YcfxokTJ+wKnz17FmPGjLFrxvUEBfkiP99oc6yg4BxCQvzYUHE+G2I1ZFiDKzeMZaU49H+7rd+7ubvDt21bXDh7BmaTCbBY0GvQQ+g7ZDiqKytQ/Fv+DbcA132d2BBzPhtiNWRYg0wNZ9NqNap9OW2NDT3A19cXv/76q82x3NxctG7d2u64xWKxe0Z9PD3dUFNj++Fr1dV1MBgc99E0MjRkWAMb4sxno/H0bm6IjI3D+VOnrFdeAOCXjRuw+evl0Oh0COvVx66GDK8TG+LMZ0OshgxrkKlBymvwbI0fPx4TJkzAuHHjUFtbi6+//hppaWkYO3as3fH6bqnsCFVVdfDwsP1UaoNBj8rKWjZUnM+GWA0Z1iBDw6tlS0T2i0P5eSP279hu8zOz2YSaqioc378PETH97eq4+uvEhljz2RCrIcMaZGo4myvd8vhGNXilZeTIkXjzzTfxyy+/oH379tiwYQMmTZqExx57TI3nd8Py8owICPCxORYY6HPV5cHm3pBhDWyIM5+Nhvm2bYfeCYNRevI37Nu2BWazCTq9Hn2HjIBnixbWx2m1OtRdumRXy5VfJzbEm8+GWA0Z1iBTg5TXqFsAxMfHY+HChVi7di0WLVqERx55pFHD77zzTtx1113X/IqLi7PriTckI6MIAJCYGAadToP4+GCEhPhh69YCNlScz4ZYDRnW4MoNzxYtEBUbh2P79+HovgzrcVNdHSovXkDXiChodToYPL3QJTwCJ48fFW4NbIjbkGENbIgznw3X0hze06KxNPDGkqqqKqSkpGDdunU4f/48WrdujeHDh+PZZ5+Fm9v1bxVXWFjY4BO48vNgGisqakGjHhcc7Gu9J3dxcTlmz95t/YvrKDI0ZFgDG+LMZwNInqK75vHbou5B59vvQF2t7a8k/JZzBPmHD6L7Pb3Q2r89THV1OHn8KH49eACo5x/Rb801XfO4o9bQFGyI05BhDWyIM58NICPjGYc+D6UYyz5WreV7y/Oqta7U4KbljTfeQH5+Pp577jm0a9cOhYWF+PTTT3HXXXchKSlJredpo7GbFiIiZ6hv0+JIjd20EBHRjXOVTcv5M5+o1rq51VTVWldq8I34W7ZswQ8//ICWLVsCAIKCgtC9e3cMHjzYaZsWIiIiIiJqPhrctPj6+qKystK6aQEAk8kEd3d3RZ8YERERERE1zJnvNVFLvZuWzZs3AwD69OmDp59+GhMnToS/vz9Onz6NBQsW4KGHHlLtSRIRERERUfNV76Zl5syZNt9/9NFHNt//+9//xosvvqjMsyIiIiIiokZpDp/TUu+mZcuWLWo+DyIiIiIiomtq8D0tAHDo0CGUlZXh8o3Gamtrcfz4cUyZMkXRJ0dE5IrUuLNX6l+bfrv4ppj8RsO3rCd5lNx9t+KNdvv3K94gaq6a9XtaLps9ezYWL16MFi1awGw2w2w2o7y8HL1791bj+RERERERUTPX4KZlzZo1WLFiBaqqqrBq1Sp8+OGHSElJwZkzZ9R4fkRERERE1Mw1uGmpqalBWFgYzp07h+zsbADAs88+i7i4OMWfHBERERERXV9zeCO+tqEHtG/fHvn5+fDx8cHZs2dRXl4OAKisrFT8yRERERERETV4pWXUqFEYNWoU1q5di/j4eDz11FNwc3NDeHi4Gs/PLqGhfkhKug+hoX4oLLyI5OTtyM4+xYbK89kQqyHDGti4vkM5R/H19+tReuoUWrbwRkJsP/S71/Z9iB8t/ALenp6YMGa0XS3AdV8nGRtqrOG+7i2RNKwjOt9iwJmLtZj3QzGW7XCt10mWhgxrkKnhTLzSAiAxMRHz58+Hr68vXn/9dcTGxiI8PBwffvihGs/vhun1WqSkDEB6ei5iYhYjLS0TqakJ8PJyY0PF+WyI1ZBhDWxc3xmjEXPTFmNw/AOYN2smJj0+FqvWrcfBIznWx2z+aRcOHM52xBJc9nWSsaHGGvx93bFgUig+WVeE7lP34rkFuUga1hF9b7/ZYQ0ZzoUaDRnWIFODlNfgpgUAwsPD4eHhAXd3d0ycOBEvvvgi/Pz8GvxzRUVFDX4pJTLSH3q9FitWHILJZMGmTbnIyzMiLi6YDRXnsyFWQ4Y1sHF9p88a0SsyAlF33QmtVouggE7oFhKC4/n5AICi0lJs3LodvaIihV0DG2LOB4COrd3x7S9n8EOmERYLcKCgAj8fvYAeId4Oa8hwLtRoyLAGmRrOptVqVPtylnp/PaxHjx7QaK7/xPbs2XPdn8fGxkKv10On0wGA9XNeLtNoNDhw4EBjn2uTBAX5Ij/faHOsoOAcQkIa3mw1p4YMa2BDnPlsOL/RNTgIXYODrN+XV1TgWG4eekdFoq6uDvO/XIaxI4YhKzsblVXVN9y5zFVfJxkbaqxhz/Fy7Dlebv3ex0uH6NAW+NfPjrujqAznQo2GDGuQqUHKq3fT8umnn9o9fMyYMdixYwe6du2KQYMGoV+/fvD09LR7bmN4erqhpsb2A96qq+tgMDTq8zSbTUOGNbAhznw2xGpUVlXh7wvTEBQQgIiwO7Dq+/XoEtQZYd26IivbMb8eJsPrJEtDjTVcqcVNOqRN7oLMvAps3G9s+A80kgznQo2GDGuQqeFszeE9LfWerejoaLuHv/nmmwCAvXv34ocffsAnn3yCLl26WDcwN910k92N+lRV1cHDQ2dzzGDQo7Kylg0V57MhVkOGNbDROCVlZfj7P9LQoW1bTHz8MRzNzUXWkSN4+8Vpds++kqu/TjI11FjDZZ3bGpA2ORTHi6owZWEu/vSLFHaR4Vyo0ZBhDTI1SHmNek+LvSIjI/H6669j48aNePLJJ3HgwAEMGTIEU6dOVayZl2dEQICPzbHAQJ+rLg8294YMa2BDnPlsiNHI+TUX/zvnY0SE3YHJ45+Au5sbft6biVNnzuL5N9/GpBmvYctPu/Hz3n14fZZ9N1Vx5ddJtoYaawCAe0Jb4PvXumNjphHPzPsVNXUO3LFAjnOhRkOGNcjUcDaLRqPal7Oosmm5rLy8HIWFhSgqKsK5c+cUbWVk/PEm/8TEMOh0GsTHByMkxA9btxawoeJ8NsRqyLAGNq6v9PRpfLTgHxiaMBAjH37I+t7E8aNGYsGHszBv1nuYN+s9xPbpjV6REZg542Xh1sCGmPMBIKCNBxZP7YKUtYWYtfp3h829kgznQo2GDGuQqUHK01j+/O54Bzt79iz+P3t3Hhdluf9//M0wwAhqgLkdK5DFrdwAKTGVk4L7lmvkXpKWa2qJlRanRUvMhb6mJJFlWmZpPz2lSOZeNomYmlYsagi4DSoCEwzz+6Ov83VCZZv7nmsu3s/Hg8fjcDN+XnPNyMGre+YmJSUFO3bswLFjx9C5c2f06tWrRi8PCwlZU6nb+ft7Wa7JnZNTgCVLDlr+4tqKDA0Z1sCGOPPZUKcR/3qz2x7/9Kut2PH9Hri5ulod79G1C0YOHGD5fP2XX6GwqPiOv6dl6svZiq+hKthQdn5uhw6Vmr9gxAOIjmyCG8XW7w/4aHce3tx8901Mk6NHK9UA5Hgu1GjIsAbRG3p9tE3vh1L+Mq9WreXq9IxqrVtVatNy7tw5bN68GXl5eZg3bx52796NwYMHVzh87NixOH36NB599FH07t0b3bt3h+s/fpBWR2U3LUREsrrTpsVWqrJpIcdX2U1LTVRl00IkCm5ayrPXpqXCyyYcOnQIM2bMQNeuXbF7925MnToVixcvRn5+PsaPH3/XP3v48GFotVokJydj165dVl8zm82KXvKYiIiIiKg2KFX2hVNWXO30tpYKNy3vvPMOli1bhrCwMHTq1AnNmjVDYmIinnvuuQo3LSkpKba6n0REREREVEtVuGk5e/YsHnnkEQCwvKGzVatWuHbtWoXDmzVT9uULRERERES1nZpnWuylwquH+fv749tvv7U6tm/fPjRv3lyxO0VERERERHRThWdaXnjhBURHR2PLli0oKirC7NmzsXfvXqxYsUKN+0dERERERHdRG860VLhpCQ4OxrZt27Bt2zY0a9YMjRo1wvTp0+Hj46PG/SMiotsY9kVDRef/qe+n6HyAV4IUCa/sRUSiq3DTAgBNmzbFpEmTlL4vRERERERE5VS4aenUqZPlDfj/dPjwYZvfISIiIiIiqrxSe98BFVS4aXnvvfesPjcYDFi/fj169+6t2J0iIiIiIiK6qcJNS2ho6G2PjRo1ClFRUYrcKSIiIiIiqhy+Ef8OTCYTrly5Yuv7YnOBgd6IiemKwEBvZGdfR2zsHpw8eZENleezIVZDhjWwUXld29RHzND70byRDpevl2DVtzlYv7dm8w8cOIC4uDhkZWWhQYMGeOqpp9CtWzf062f95v2SkhIAwPHjx2vUA+R4LtRoyLAGNsSZzwaJpMLf0/LWW29ZfcTGxmLUqFHo2rWrGvev2rRaDeLieiE5OR3h4UlITExFfHxfeHi4sKHifDbEasiwBjYqr6mXK9ZMCcSKbefRZvrPeG5NOmKG3o/uD95T7Zk5OTmYNm0apkyZAr1ej7i4OCxduhTp6elITU21fOzbtw/NmjXDwoULa7wOGZ4LNRoyrIENceaz4VhKzWbVPuylwk3LtWvXrD6MRiNGjhyJ2NhYNe5ftQUHN4VWq8GGDcdhMpmxc2c6MjIMiIjwZ0PF+WyI1ZBhDWxU3v33umLLj5fxbaoBZjOQlnUDh05fQ6eAutWemZ2djf79+yMiIgIajQbt2rVDaGgojhw5YnW7RYsWoWXLlhg+fHhNlyHFc6FGQ4Y1sCHOfDZINBW+PKxjx44YMGAA6tSpU+XhTz/99B2vPAYATk5OWLNGmev0+/l5ITPTYHUsKysfAQHebKg4nw2xGjKsgY3KO/x7AQ7/XmD53NPDGaGB9bD50OVqzwwJCUFISIjl8/z8fOj1egwaNMhy7MSJE9i+fTt27NhR7c6tZHgu1GjIsAY2xJnPhmPhe1oALFmyBEOHDq3W8H++vvmmH374AVu3bkVwcHC15laGu7sLjEaT1bHi4lLodNV6G4+0DRnWwIY489kQr3FTvTrOSJzaAqkZN7DjqKHiP1AJ169fx5QpU9C+fXv06NHDcnz16tUYOXIkGjVqZJOOLM8Fv7/Z4PMtb4OUV+Gz1atXL6xcuRIDBgxAo0aNrM6c1K1795cYDBkyxOrzgoICLFq0CLt27cLLL7+MJ598spp3u2JFRaVwc3O2OqbTaVFYWMKGivPZEKshwxrYqLrmjXVInBqI388XYVpCOmzxH+QyMzPx7LPPIiAgAEuWLIFG8/erjQ0GA7777jts27at5pH/Jctzwe9vNvh8y9uwt9pwpqXC97Rs27YN77//Pvr164fQ0FB06tQJISEh6NSpU5VCKSkp6NOnDy5cuIBt27Zh9OjRd33pWE1lZBjg4+NpdczX17Pc6cHa3pBhDWyIM58N8RoPB9bD/5vfBjtSDYhe9QeMpTX/wfbTTz9hxIgR6NmzJ1asWAE3NzfL1/bs2YMWLVrA19e3xp2bZHku+P3NBp9veRukvEptWlJSUpCSkoJdu3Zh165dlv9dGVeuXMHMmTPx0ksvYc6cOVizZg2aNm1a4zteEb3+PAAgKqotnJ2dEBnpj4AAb+zencWGivPZEKshwxrYqDyfhm5Imt4CcVuzsejLP20y8+zZs3jmmWcwffp0zJ49u9x/fEpLS0NQUJBNWjfJ8Fyo0ZBhDWyIM58Nx1Kq4oe9OJnNtz+fFB0dXeM3yW/duhVvvfUWwsLC8PLLL8Pb2zZveAoJqdz98vf3slyTOyenAEuWHLT8xbUVGRoyrIENceazoU4jt0OHCm+zYMQDiI5sghvF1q/l/mh3Ht7cfPdNzJ8flP/FwsDfl8FPSkqCu7u71fGoqCjMnTsX0dHRCAkJQXR0dIX3r7L/Xw6I/VyI1JBhDWyIM58NQK+v+P/LRHCyeIVqrTa66aq1bnXHTUtQUFC5S1hWVatWrQAArq6u5f5rnNlshpOTE9LS0qo8tyo/6IiIZFSZTUtN3GnTYkv8/3IiEp2jbFqOFS1XrdWuzgzVWrdS9LIJKSkpSo4nIiIiIqJa4I6blr/++gtvvfXWXf9wTEzMXb/erFmz6t0rIiIiIiKqlNpw9bC7nmm5du2aWveDiIiIiIjotu64aXF1da3wTAsREREREZHS7rhpucP784mIiIiISCC1+uVhISEhat4PIiKqgiZHjyo6PyRE2fmAOlfl4RXKiIjkcMdNS0JCgpr3g4iIiIiIqqE2nGnR2PsOEBERERER3Y2iv6eFiIiIiIiUVWrvO6ACnmkhIiIiIiKhSX2mJTDQGzExXREY6I3s7OuIjd2DkycvsqHyfDbEasiwBjbEma9U48CBA4iLi0NWVhYaNGiAp556Ct26dUO/fv2sbldSUgIAOH78eI16gOM+VmrOZ0OshgxrkKlhT3xPiwPTajWIi+uF5OR0hIcnITExFfHxfeHh4cKGivPZEKshwxrYEGe+Uo2cnBxMmzYNU6ZMgV6vR1xcHJYuXYr09HSkpqZaPvbt24dmzZph4cKFQq5D7YYMa2BDnPlskGik3bQEBzeFVqvBhg3HYTKZsXNnOjIyDIiI8GdDxflsiNWQYQ1siDNfqUZ2djb69++PiIgIaDQatGvXDqGhoThy5IjV7RYtWoSWLVti+PDhNV2Gwz5Was5nQ6yGDGuQqWFvpWazah/2ovjLw4qLi7Fu3Trs3bsXly9fRoMGDdCtWzeMHj0a7u7uinX9/LyQmWmwOpaVlY+AAG82VJzPhlgNGdbAhjjzlWqEhIRY/a6w/Px86PV6DBo0yHLsxIkT2L59O3bs2FHtzq0c9bFScz4bYjVkWINMDVKeopuWq1evYtSoUbjvvvswbNgw3HvvvcjJycH27duxefNmfPbZZ/D09FSk7e7uAqPRZHWsuLgUOp3tlixDQ4Y1sCHOfDbEasiwhuvXr2PKlClo3749evToYTm+evVqjBw5Eo0aNbJJR4bHSoY1sCHOfDYcC9/TUkPLli1Dly5dkJCQgMGDB+PRRx/F8OHDkZSUhM6dO+Pdd99VrF1UVAo3N2erYzqdFoWFJWyoOJ8NsRoyrIENceYr3cjMzMSIESNw7733YsWKFdBo/v6RZTAY8N1332HUqFE1btzk6I+VGvPZEKshwxpkapDyFN20pKSk4Lnnnrvt15599ll89913irUzMgzw8bE+i+Pr61nu9GBtb8iwBjbEmc+GWA1HXsNPP/2EESNGoGfPnlixYgXc3NwsX9uzZw9atGgBX1/fGjVu5ciPlVrz2RCrIcMaZGrYW214T4uim5br16+jXr16t/2al5cXCgsLFWvr9ecBAFFRbeHs7ITISH8EBHhj9+4sNlScz4ZYDRnWwIY485VqnD17Fs888wymT5+O2bNnw8nJyerraWlpCAoKqsndLsdRHys157MhVkOGNcjUIOU5mc3KbZkef/xxzJkzB2FhYeW+dvDgQSxduhRffPFFleeGhKyp1O38/b0s1+TOySnAkiUHLX9xbUWGhgxrYEOc+WyI1RB5DXp99G2Pv/XWW0hKSip3sZaoqCjMnTsX0dHRCAkJQXT07f/8rSr78wIQ+7ESZT4bYjVkWIPojTv9/5Rovsx/W7XW454vqNa6laKblv/+97+Ii4vDqlWr0KJFC8vxtLQ0PP/883jhhRfQq1evKs+tyg8hIiISkxr/GODPCyKqCW5ayrPXpkXRyyb07dsXBoMBUVFRaNCgARo0aIDc3Fxcv34dc+bMqdaGhYiIiIiIahfFr/X25JNPYsiQITh69Kjl97QEBQVBp9MpnSYiIiIikl5tuOSxKheodnd3v+37WoiIiIiIiCoiz2/VISIiIiKqhWrDmRZFL3lMRERERERUUzzTQkREdqHGlb02JoYq3hg18bDiDSKiu+GZFiIiIiIiIjvjmRYiIiIiIgfGMy1ERERERER2xjMtREREREQOrNTed0AFUm9aAgO9ERPTFYGB3sjOvo7Y2D04efIiGyrPZ0OshgxrYEOc+Y7cSE07hg/Xf4rzubnwrF8fQwcNQJ+ICOTk5WHStBlwc3W13LZblzDMmDK5psvg880Gn2+JG6QsaV8eptVqEBfXC8nJ6QgPT0JiYiri4/vCw8OFDRXnsyFWQ4Y1sCHOfEduXLx0CW/ELcWooY/j86REvDBzOpLWb8DPR48iPSMTLQL8sfmTdZYPW2xY+Hyzwedb3oa9lZrNqn3Yi+Kblr179yIxMRFpaWlKp6wEBzeFVqvBhg3HYTKZsXNnOjIyDIiI8GdDxflsiNWQYQ1siDPfkRt5Fy8i/NEuCHs4FBqNBi0CAtD2wTY4eeo3/JGRAT9fX5vd/5v4fLPB51veBilP0ZeHJSUlYe3atQgODsbatWsxffp0jBw5UsmkhZ+fFzIzDVbHsrLyERDgzYaK89kQqyHDGtgQZ74jNx5q3RoPtW5t+fz69QKc+PUUHuvWDd8kJ6O42IhJ02eiuLgYIR074KmxY1DXw6PaPYDPNxt8vmVu2BuvHlZDH330ET799FMsW7YM77//Pj7++GMlc1bc3V1gNJqsjhUXl0Kns90+TYaGDGtgQ5z5bIjVkGENajRu3ChE7OK30TIwEI90CkFdDw90bN8Wy956E8sXL8LFS5excnXNfxEmn282+HzL2yDlKfpsXb16Fffffz8A4KGHHsKFCxeUzFkpKiqFm5uz1TGdTovCwhI2VJzPhlgNGdbAhjjzZWhknz+P2LffwQP33Ye506dBo9HgxVkzLV/38HDHuKhRmPvKQphMJjg7O99l2t3x+WaDz7e8DXvjmRYbcnJyUisFAMjIMMDHx9PqmK+vZ7nTg7W9IcMa2BBnPhtiNWRYg5KN4ydPYtb8l9G5UyfMn/08XF1dUWw0IvHjT2DIz7fcrqS0FM4aDTSamv3I5PPNBp9veRukPGmvHqbXnwcAREW1hbOzEyIj/REQ4I3du7PYUHE+G2I1ZFgDG+LMd+RGTm4uXl30NkaPHI7xT0ZZ/sOazs0Nqcd+wUefboTR+BeuGAxIWv8peoaH1/g/vvH5ZoPPt7wNUp6T2azc+aRWrVrBzc3N8rnRaLR8bjab4eTkVK2rioWEVO61xf7+XpZrcufkFGDJkoOWv7i2IkNDhjWwIc58NsRqyLCGmjQ2Jobe9nhC0jps2b4dult+RgFAv9690C8yAu8nfogTp07DWaNBt7AwPDV2NFxv+b0ttxo18bDi6xBlPhtiNWRYg+gNvT7apvdDKW/nxqrWeqHJAtVat1J005KdnV3hbZo1a1bluZXdtBARUe12p02LLVVl00JEjoWblvLstWlR9I341dmQEBERERFR5ZXa+w6oQNr3tBARERERkRy4aSEiIiIicmClZrNqH9Wxdu1aLFjwfy8r27lzJx577DF07NgRMTExKCmp+PLT3LQQEREREZHNlZSUYMWKFViyZInlWG5uLl5++WWsWLECe/fuxZ9//onPP/+8wlnctBAREREROTBRz7S89dZbOH78OEaOHGk5tmvXLoSFheGhhx5CvXr1EB0djS1btlQ4S9E34hMREdmTGlf2Gt31qOKNT/Z1ULxBRFQZ165dw7Vr18odr1+/PurXr291bMqUKWjYsCFWrlyJixcvAgCysrLg6+truY2Pjw/S09Mr7HLTQkRERETkwKr7XpPq+OijjxAfH1/u+NSpUzFt2jSrYw0bNix3u8LCQqvjbm5uKC4urrDLTQsREREREVXKuHHjMGTIkHLH/3mW5U7q1KkDo9Fo+dxoNKJOnToV/jluWoiIiIiIHJiaZ1pu9zKwqmjevDlSU1Mtn//z5WJ3wjfiExERERGRKnr06IH9+/fj6NGjuH79OhISEtCnT58K/5zUm5bAQG8kJg7Cvn0TsHHjMLRpU/51dWzIsQY2xJnPhlgNGdbgyI0HWrTCE8/Pw5S34jB+/qto2/lRq6/r3D0w4eVYNPzXfTVuAY77OLEh5nw2HEepih811bRpU7zxxhuYO3cu/v3vf8PX1xfjx4+v8M9Ju2nRajWIi+uF5OR0hIcnITExFfHxfeHh4cKGivPZEKshwxrYEGc+G3dX19ML/SZMwuHkb7Bq/hx88/GH6NJvEHxatgYANPMLwIjps3FPg3uFXQMb4jZkWINMDbq7adOmITY21vJ5z549kZycDL1ej//85z/Qait+x4q0m5bg4KbQajXYsOE4TCYzdu5MR0aGARER/myoOJ8NsRoyrIENceazcXf1vb1x+oge6b+kAWYz8s6dwZ/pv6Npc3/cH9gSfcZOxI87vxF6DWyI25BhDTI17E3U39NiS6q8Ef+///0v9uzZg8uXL8PLywvdunVDv3798Omnn6JJkybo2bOnzZt+fl7IzDRYHcvKykdAgDcbKs5nQ6yGDGtgQ5z5bNzd+Yx0nM/4v9894Obujn/5+eNX/Y+4mP0nPvzPAphMpegzZkK1G7dy1MeJDTHns0GiUXTTYjQa8fTTTyM/Px+9e/dGSEgILl26hLVr12L9+vUwGAz47LPPFGm7u7vAaDRZHSsuLoVOZ7sly9CQYQ1siDOfDbEaMqxBloarToeBT01G7pkspB8/BijwXytleJzYEGc+GyQaRZ+t+Ph4NGjQAElJSXB2drYcf/rpp/HYY4+he/fu8PT0VKRdVFQKNzdnq2M6nRaFhSVsqDifDbEaMqyBDXHms1E5ng0bYeBTk3E5NwfffvKhIhsWwPEfJzbEms+GY7Hny7bUouh7WrZv34558+ZZbVgAYNu2bWjSpAn279+vWDsjwwAfH+sNka+vZ7nTg7W9IcMa2BBnPhtiNWRYg6M3mvkFYNTMF5D+Sxq2JyXAVGqLa++JbB7AAAAgAElEQVTcniM/TmyIN58NEo2im5b8/Hw0bty43PGuXbti6dKluHbtmmJtvf48ACAqqi2cnZ0QGemPgABv7N6dxYaK89kQqyHDGtgQZz4bd3dPg3sxcNIUHPp2Gw5s32qje3pnjvo4sSHmfDYcS214I76T2axcfeDAgXj99dfRrl27cl9LS0vDK6+8gq+//rrKc0NC1lTqdv7+XoiJ6YrAQG/k5BRgyZKDlr+4tiJDQ4Y1sCHOfDbEasiwBtEbo7seve3xboOGIii8B/4yFlsdP7Z/L/Zv22L5fOa7/4P177yJi+f/vGPjk30dFF1DVbAhTkOGNYje0OujbXo/lBJ95iXVWmt83lCtdStFNy2ff/451q9fj1WrVuFf//qX5fi5c+fw3HPPYcyYMRg+fHiV51Z200JERKS0O21abKmymxYisi1H2bRMzJqvWivR903VWrdS9I34I0aMQHZ2Nvr164cHH3wQjRs3Rl5eHk6cOIGJEydWa8NCRERERES1i+LXeps1axaioqKwf/9+XL58GZ07d0ZcXNxt3+tCRERERERVo9wlPsShygWqGzdujKFDh6qRIiIiIiIiyfC36hAREREROTD+nhYiIiIiIiI745kWIiKiGlDjyl47tw9UdH5kv6r/+gERFTRponijbm6u4g2iquKZFiIiIiIiIjvjmRYiIiIiIgfGMy1ERERERER2xjMtREREREQOjGdaHFxgoDcSEwdh374J2LhxGNq0aciGHeazIVZDhjWwIc58NuzfOPzTTxj/9CT06N0Hw56Iwldb/35TfWlpKZbHx6PvwEGI7NsPLy1ciIKCghr3HPVxupO2LTxx4JNeiszm93ftapCypN20aLUaxMX1QnJyOsLDk5CYmIr4+L7w8HBhQ8X5bIjVkGENbIgznw37N/LyLiDmlQUYP3YMkv+7HbELXsGqNWvww+HDWLUmAb8cP4FPkj7EV19sQnFRMeJXrRJuDfZo3DQs8gGsje0MF63t/znE7+/a1SDlSbtpCQ5uCq1Wgw0bjsNkMmPnznRkZBgQEeHPhorz2RCrIcMa2BBnPhv2b+Tk5iCyZ0+Ed+sGjUaDNq1bI6hDBxxJPYotX3+Nuc/Pgre3Nzzc3fHy/BhEjRol3Brs0QCAaU+2xBN9ffH+Z7/ZdO5N/P6uXQ17K1Xxw17sumk5cOCAYrP9/LyQmWmwOpaVlY+AAG82VJzPhlgNGdbAhjjz2bB/o0P79nhxzmzL51evXUPasWNwr1MHRqMRWWfOYNToMeg/eAhWJ3yAexs0qHYLcNzH6XY++yYLQ2fuxfE/8m069yZ+f9euBilP0U1Lbm4uZsyYgQEDBiA2NhZGoxEAkJeXh+nTp2PKlCmKtd3dXWA0mqyOFReXQqez3bUHZGjIsAY2xJnPhlgNGdbARuUVFBTghZj5aNOmDdq3awez2YzklBSsfi8e6z5MxNlz57Divfdq1JDhcbrpwhWjTef9E7+/a1fD3krNZtU+7EXRTcu8efPg5OSEmTNn4syZM1ixYgX27duHAQMG4MaNG9i6dati7aKiUri5OVsd0+m0KCwsYUPF+WyI1ZBhDWyIM58NcRpnz53D05OnwNvLC2/GvgY3N1eUlZVh8qRJuOeee+Dt5YUJ48bi+737atRx9MdJTfz+rl0NUp6im5Zjx47hjTfeQI8ePbBkyRJs3boVMTExmD9/PtauXYvmzZsr1s7IMMDHx9PqmK+vZ7nTg7W9IcMa2BBnPhtiNWRYAxsVSz2ahqefmYxuXbvizf/Ews3NDfffdx80Gg2uXb9uuZ3JZLrLlMpx5MdJbfz+rl0Ne+OZFhvw8PAAAHh5eeHq1atYunQpBg8erHQWev15AEBUVFs4OzshMtIfAQHe2L07iw0V57MhVkOGNbAhznw27N/4Mzsbc+bNw6SnJuLZZ6Lh5OQEAKhXrx66d+uKVavX4OrVq8jPz0fSunWI6PGYcGuwR0MN/P6uXQ1SnpPZrNyWKSgoCEeOHLF8HhISAr1eX+O5ISFrKnU7f38vxMR0RWCgN3JyCrBkyUHLX1xbkaEhwxrYEGc+G2I1ZFgDG8DO7QNve3x5fDw2fr4JderUsTo+dPBgTBg3Fu+9vxp79++HsbgY4d274/kZ06HT6crNiez3teJrqIrqNgqaNKlyK7RtA8S/FIrQUd9U6vZ1c3MrPZvf347f0OujbXo/lNLt9OyKb2Qje1vGqda6laKblo4dOyIlJQU3E71798aOHTtwa7JBNa5kUtlNCxERkQzutGmxlapsWkRWnU1LVVVl00KOj5uW8uy1aVH0sglFRUXo0qWL1SYlLCzM8r+dnJzw66+/KnkXiIiIiIikZs/3mqhF0U3LqVOnlBxPRERERES1gDwXqCYiIiIiqoXs+Zvq1aL41cOIiIiIiIhqgmdaiIiIiIgcGN/TUkvx6iNERCQSpa/uFf96M0XnA8D4+Jr/csuK8Gcrkby4aSEiIiIicmC14UwL39NCRERERERC46aFiIiIiIiExpeHERERERE5ML48zMEFBnojMXEQ9u2bgI0bh6FNm4aKtdq28MSBT3opMlvpdajxOLEhTkOGNbAhznw2xGooMf/4qdNY8M5SPPNCDOb+5w3sPnCw3G3eTViLhPUbatz6J0f+2apGQ4Y1yNQgZUm7adFqNYiL64Xk5HSEhychMTEV8fF94eHhYvPWsMgHsDa2M1y0tn84lV6HGo8TG+I0ZFgDG+LMZ0OshhLzLxsMWJmYhIGRPbFq0RuYMnYMNm3bjl9+PWW5Tcr+A0g7cdIWS7DiyD9b1WjIsAaZGvZWajar9mEv0m5agoObQqvVYMOG4zCZzNi5Mx0ZGQZERPjbtDPtyZZ4oq8v3v/sN5vOvUnpdajxOLEhTkOGNbAhznw2xGooMf/SFQM6BwchpH07aDQa+Pk8gFYBAfg9MxMAcD4vDzt270HnkGCbrOEmR//ZqkZDhjXI1CDlKb5pMZlMMBgMls9/+uknrF+/HhkZGYp2/fy8kJlpsDqWlZWPgABvm3Y++yYLQ2fuxfE/8m069yal16HG48SGOA0Z1sCGOPPZEKuhxPyW/n4YP3K45fOCGzfwW3oGHmjWDKWlpXh/3XqMGT4Udd3rVLtxO47+s1WNhgxrkKlhb6UqftiLopuWjIwMREZGYtmyZQCADRs2IDo6Gnv37sWYMWNw6NAhxdru7i4wGq1/kVVxcSl0Ottee+DCFaNN5/2T0utQ43FiQ5yGDGtgQ5z5bIjVUHp+YVERliUkws/HB0FtH8Lm7d+ghV9ztG3V0ibzb+XoP1vVaMiwBpkapDxFn63Fixdj5MiRiI6ORllZGeLj4zFv3jyMHDkSer0eb7/9Njp37qxIu6ioFG5uzlbHdDotCgtLFOkpRel1qPE4sSFOQ4Y1sCHOfDbEaig5P/fCBSz7IBHNGjfGM2NH43R6Oo79+isWzp5V49n2wOebDUf8N+Hd8OphNXTkyBFMmDABAHD8+HFcuXIFkZGRAICOHTvi999/V6ydkWGAj4+n1TFfX89ypwdFp/Q61Hic2BCnIcMa2BBnPhtiNZSaf+qPdLy2dDmC2j6EqRPHw9XFBYd+TsXFy1cw45WFmDJvPr7bfxCHfj6Clxa9U6OWWvh8s+GI/yas7RTdtJSVlcHZ+e+d7Q8//IAWLVrAy8sLAHD16lVotcqd6NHrzwMAoqLawtnZCZGR/ggI8Mbu3VmKNZWg9DrUeJzYEKchwxrYEGc+G2I1lJifd+kS3l3zAR7v2xsjBvSHk5MTAGDiqBFY884irFr0JlYtehOPPRqGzsFBeGPeXFssRXF8vtlwxH8T3k1tuHqYk9msXH3SpEmIjIxEnz59MHLkSPTp0wdTp04FACQkJOCnn37CmjVrqjw3JKRyf8bf3wsxMV0RGOiNnJwCLFly0PIX924KmjSp8n0KbdsA8S+FInTUN5W6fd3c3ErPru46RJnPhlgNGdbAhjjz2RCrUd358a83u+3xT7/aih3f74Gbq6vV8R5du2DkwAGWz9d/+RUKi4ox6ckn7tgYH2+649fuxJF/tqrRkGENojf0+mib3g+l/OvYVNVa59vFq9a6laKblvT0dERHRyMnJwdt27ZFYmIiPDw8MGLECJw5cwbr1q1Dy5ZVfwNfZTct1VWdTUtVVeX/WImIiJR0p02LLVVn01JV/NlKtuYom5ZGac+p1rrQ/j3VWrdS9I34/v7+SE5OhsFgQIMGDSzHx48fj0ceeQTe3vJcao6IiIiIiJSh+LXeNBqN1YYFAPr27at0loiIiIioVuDVw4iIiIiIiOyMv1WHiIiIiMiB2fM31auFZ1qIiIiIiEhoPNNyG7z6CBER1SZqXNlr6fCLijcWrFQ8QUR2wk0LEREREZED4xvxiYiIiIiI7IxnWoiIiIiIHBjPtBAREREREdmZ1GdaAgO9ERPTFYGB3sjOvo7Y2D04edK2bwSUoSHDGtgQZz4bYjVkWAMb4sy/VdsWnnh/wcPoMnpHjWfd2/RfaBncCe716uOv4mJknDiGc7+dhkf9e/Dgw51xz70NUWYy4XxmBk79fBjmsrIaN/l8s6HU94Y98EyLA9NqNYiL64Xk5HSEhychMTEV8fF94eHhwoaK89kQqyHDGtgQZz4bYjXUWMNNwyIfwNrYznDR1vyfETp3D3QM74E/jh1F8oaPcXTvbrQM6oR7/9UMQeE9YLh4Abs2foJ9X3+Je5s2hW+rNjVu8vlmQ6nvDVKOYpuWXDtfNjg4uCm0Wg02bDgOk8mMnTvTkZFhQESEPxsqzmdDrIYMa2BDnPlsiNVQYw0AMO3Jlniiry/e/+w3m8yrU7cucjLTkXf2DADg6uVLuJKbA69GjXFg+1b8npYKs9kMF1c3aDTO+Ku4uMZNPt9sKPG9YU9ms4tqH/ai2MvD+vbtiyNHjig1vkJ+fl7IzDRYHcvKykdAgDcbKs5nQ6yGDGtgQ5z5bIjVUGMNAPDZN1lYuf40Qts2sMk8w4U8GC7kWT53cXWFV+PGyM74A2Wmv39/TOc+/eHVqDEu55xHzpnMGjf5fLOhxPcGKUuxTYvZzq+tc3d3gdFo/cuyiotLodPZbskyNGRYAxvizGdDrIYMa2BDnPk3XbhitOm8W2ldXBD8WASuXrxoOfMCAD/u+AYubq7oGN4DbTs/irT9e2rU4fPNhhLfG3ZV5mrve6A4RTctx44du+tt2rVrp1QeRUWlcHNztjqm02lRWFjChorz2RCrIcMa2BBnPhtiNdRYg5I86tdH8L8jUHDVgKN7rTclZWUmGIuK8PvRIwgK71HjFp9vNhzpe4P+pth7WoxGI2bNmoWZM2fe9mPWrFlKpQEAGRkG+Ph4Wh3z9fUsd3qwtjdkWAMb4sxnQ6yGDGtgQ5z5SvJq3ARhfQci79wZHPn+O5SVmeCs1aL7kOFwr1fPcjuNxhmlf/1V4x6fbzYc5Xuj0spc1fuwE8U2LXXq1EFKSgq+++67236kpKQolQYA6PXnAQBRUW3h7OyEyEh/BAR4Y/fuLDZUnM+GWA0Z1sCGOPPZEKuhxhqU4F6vHkIei8BvR4/g9BG95biptBSF16+hZVAINM7O0Ll7oEXHIJz7/XSNm3y+2XCE7w2y5mRW6M0nHTt2RGpqqhKjERKyplK38/f3slyTOyenAEuWHLT8xbUVGRoyrIENceazIVZDhjWwofz8giZNqtwKbdsA8S+FInTUN5W6/dLht/+dGK1DHkbzBx9CaYn1S3XOnPoVmSd+QZuHO+Pepv+CqbQU534/jT9+SQPu8E+XBStNtz1+O7X5+Waj8g29Ptqm90MpTgcXqNYyh8Wq1rqVYpuWSZMmISEhQYnRld60EBERUcWqs2mpqjttWmypKpsWosrgpqU8e21aFHsjvlIbFiIiIiIiukUtuHqYYu9pISIiIiIisgVuWoiIiIiISGgS/VYdIiIiIqJaiC8PIyIiIiIisi+eaSEiIqrl6ubmKt5YsFLxBDYmhireGDXxsOINoirjmRYiIiIiIiL74pkWIiIiIiJHxjMtRERERERE9sUzLUREREREjqwWnGmRetMSGOiNmJiuCAz0Rnb2dcTG7sHJkxfZUHk+G2I1ZFgDG+LMZ0OshgxrUKqRmnYMH67/FOdzc+FZvz6GDhqAPhERyMnLw6RpM+Dm+n//6OvWJQwzpkyu6TL4fNeyBilL2peHabUaxMX1QnJyOsLDk5CYmIr4+L7w8HBhQ8X5bIjVkGENbIgznw2xGjKsQanGxUuX8EbcUowa+jg+T0rECzOnI2n9Bvx89CjSMzLRIsAfmz9ZZ/mwxYaFz3ftathdmat6H3Yi7aYlOLgptFoNNmw4DpPJjJ0705GRYUBEhD8bKs5nQ6yGDGtgQ5z5bIjVkGENSjXyLl5E+KNdEPZwKDQaDVoEBKDtg21w8tRv+CMjA36+vja7/zfx+a5dDVKetC8P8/PzQmamwepYVlY+AgK82VBxPhtiNWRYAxvizGdDrIYMa1Cq8VDr1niodWvL59evF+DEr6fwWLdu+CY5GcXFRkyaPhPFxcUI6dgBT40dg7oeHtXuAXy+a1vD7kx8T0uNjBkzBk5OTlbHXF1d0bhxY/Tu3Rtdu3ZVrO3u7gKj0WR1rLi4FDqd7ZYsQ0OGNbAhznw2xGrIsAY2xJkvS+PGjULELn4bLQMD8UinEOw7eBCtW7bAoL79YPzrLyyNfw8rV69BzPOzatTh8127GqQ8RZ+tJ554otyx0tJSnD9/HgsXLsRzzz2HoUOHKtIuKiqFm5uz1TGdTovCwhI2VJzPhlgNGdbAhjjz2RCrIcMalG5knz+P2LffwQP33Ye506dBo9HgxVkzLV/38HDHuKhRmPvKQphMJjg7O99l2t3x+a5dDbszy3+mRdH3tPTt27fcx8CBAzF58mQsX74ca9euVaydkWGAj4+n1TFfX89ypwdre0OGNbAhznw2xGrIsAY2xJnv6I3jJ09i1vyX0blTJ8yf/TxcXV1RbDQi8eNPYMjPt9yupLQUzhoNNJqa/ROJz3ftapDy7PZG/Iceegi5ubmKzdfrzwMAoqLawtnZCZGR/ggI8Mbu3VlsqDifDbEaMqyBDXHmsyFWQ4Y1KNXIyc3Fq4vexuiRwzH+ySjLS9d1bm5IPfYLPvp0I4zGv3DFYEDS+k/RMzy83MvbRViHmvPZcDC14OphTmaz2WyP8OXLlzFo0CDs37+/yn82JGRNpW7n7+9luSZ3Tk4Bliw5aPmLaysyNGRYAxvizGdDrIYMa2BDnPmiNzYmht72eELSOmzZvh06Nzer4/1690K/yAi8n/ghTpw6DWeNBt3CwvDU2NFwdb39P85GTTys+DpEmc8GoNdH2/R+KMVp2zbVWub+/VVr3UrRTcvly5fLHSstLcWFCxewfPlyNG/eHC+99FKV51Z200JERES1x502LbZUlU0LOT5uWsqz16ZF0Tfid+nSBU5OTrh1X+Ti4oLGjRujZ8+emDWrZlfmICIiIiKq9ez4si21KLppOXXqlJLjiYiIiIioFuAFqomIiIiIHBnPtBAREREREVXd4sWL8cknn0Cr/XvL4e/vjy+++KJas7hpISIiIiJyZIKeaTl9+jTi4+PRvXv3Gs/ipoWIiIikoMaVvXZuH6h4I7Lf14o3iNRw+vRptGjRwiazuGkhIiIiInJkKp5puXbtGq5du1bueP369VG/fn3L51euXIHBYMCrr76KtLQ0tGzZEq+++iqaN29erS43LUREREREVCkfffQR4uPjyx2fOnUqpk2bZvn8ypUrCA0NxdSpU9GyZUskJCTg2WefxbZt2+Ds7FzlrqK/XFIp/OWSREREZA98eVjt4jC/XPLzY6q1rvb2rdSZln8ym80ICQnBF198Ua2zLTzTQkRERERElVLR5uSmo0eP4tSpUxg1ahQAoKysDCaTCa6u1Xspm6Zaf8pBBAZ6IzFxEPbtm4CNG4ehTZuGbNhhPhtiNWRYAxvizGdDrIYMa3DkxuGffsL4pyehR+8+GPZEFL7a+vcZk9LSUiyPj0ffgYMQ2bcfXlq4EAUFBTXuOerjJGvDrkyu6n1Ukk6nw9tvv41jx46hpKQEy5YtQ+vWrdGsWbNqLVHaTYtWq0FcXC8kJ6cjPDwJiYmpiI/vCw8PFzZUnM+GWA0Z1sCGOPPZEKshwxocuZGXdwExryzA+LFjkPzf7Yhd8ApWrVmDHw4fxqo1Cfjl+Al8kvQhvvpiE4qLihG/apVwa2CDbKlVq1ZYsGABZs2ahdDQUJw8eRJLly6t9jzFNi2jRo3Cpk2bbPJfEqojOLgptFoNNmw4DpPJjJ0705GRYUBEhD8bKs5nQ6yGDGtgQ5z5bIjVkGENjtzIyc1BZM+eCO/WDRqNBm1at0ZQhw44knoUW77+GnOfnwVvb294uLvj5fkxiPrfl8yItAY2HJjZVb2PKhg8eDBSUlKQmpqKtWvXomnTptVeomKblmHDhmH79u3o1q0b5syZg0OHDimVui0/Py9kZhqsjmVl5SMgwJsNFeezIVZDhjWwIc58NsRqyLAGR250aN8eL86Zbfn86rVrSDt2DO516sBoNCLrzBmMGj0G/QcPweqED3BvgwbVbgGO+zjJ2iDlKbppSUpKwrfffos2bdrg7bffxmOPPYbly5fj7NmzSmUt3N1dYDSarI4VF5dCp7PdtQdkaMiwBjbEmc+GWA0Z1sCGOPPZqLyCggK8EDMfbdq0Qft27WA2m5GckoLV78Vj3YeJOHvuHFa8916NGjI8TjI17K7MVb0PO1H8PS2NGjXCxIkT8dVXXyEhIQFmsxnPPfccxowZo2i3qKgUbm7W14DW6bQoLCxhQ8X5bIjVkGENbIgznw2xGjKsQYbG2XPn8PTkKfD28sKbsa/Bzc0VZWVlmDxpEu655x54e3lhwrix+H7vvhp1HP1xkq1BylP1jfglJSUoKytDWVkZSkqU/YuSkWGAj4+n1TFfX89ypwdre0OGNbAhznw2xGrIsAY2xJnPRsVSj6bh6Wcmo1vXrnjzP7Fwc3PD/ffdB41Gg2vXr1tuZzKZ7jKlchz5cZKxYXc801JzmZmZiI+PR58+fTB58mQ4OTlh5cqV2Lhxo6Jdvf48ACAqqi2cnZ0QGemPgABv7N6dxYaK89kQqyHDGtgQZz4bYjVkWIMjN/7MzsacefMw6amJePaZaDg5OQEA6tWrh+7dumLV6jW4evUq8vPzkbRuHSJ6PCbcGtggkTmZzWazEoM/+OADbN++HVlZWejRoweGDBmCsLAwyzdxTYSErKnU7fz9vRAT0xWBgd7IySnAkiUHLX9xbUWGhgxrYEOc+WyI1ZBhDWyIM58NYOf2gbc9vjw+Hhs/34Q6depYHR86eDAmjBuL995fjb3798NYXIzw7t3x/Izp0Ol0t50V2e9rRddQFbW9oddH2/R+KMVp3QXVWuaxjVRr3UqxTcsTTzyBxx9/HH369EHdunVtOruymxYiIiIiW7rTpsWWKrtpIeU5zKblw3zVWuYJnhXfSAGKXTZhw4YNSo0mIiIiIqJaRKJrvRERERER1UJ2fIO8WlS9ehgREREREVFV8UwLEREREZEjM/NMCxERERERkV3xTAsRERFRJbV76azijS9eb6bo/KkvZys6n+zA5Gzve6A4nmkhIiIiIiKh8UwLEREREZED05SVqVizz1kdnmkhIiIiIiKh8UwLEREREZEDczKZVKzZ50yL1JuWwEBvxMR0RWCgN7KzryM2dg9OnrzIhsrz2RCrIcMa2BBnPhtiNWRYgyyNrm3qI2bo/WjeSIfL10uw6tscrN9b8/nHT53G5/9vO/IuXkT9enXR97F/499dwqxu827CWtR1d8ekJ5+ocU+G50KtBilL2peHabUaxMX1QnJyOsLDk5CYmIr4+L7w8HBhQ8X5bIjVkGENbIgznw2xGjKsQZZGUy9XrJkSiBXbzqPN9J/x3Jp0xAy9H90fvKdGcy8bDFiZmISBkT2xatEbmDJ2DDZt245ffj1luU3K/gNIO3GypksAIMdzoVbD3pxMJtU+7EWxTcvZs8pfEvBugoObQqvVYMOG4zCZzNi5Mx0ZGQZERPizoeJ8NsRqyLAGNsSZz4ZYDRnWIEvj/ntdseXHy/g21QCzGUjLuoFDp6+hU0DdGs29dMWAzsFBCGnfDhqNBn4+D6BVQAB+z8wEAJzPy8OO3XvQOSTYFsuQ4rlQq0HKU+zlYQMGDECDBg3QuXNny0eDBg2UypXj5+eFzEyD1bGsrHwEBHizoeJ8NsRqyLAGNsSZz4ZYDRnWIEvj8O8FOPx7geVzTw9nhAbWw+ZDl2s0t6W/H1r6+1k+L7hxA7+lZyAsJBilpaV4f916jBk+FMdOnkRhUXGNWoAcz4VaDXtT9+ph9qHYpkWv1+OXX37Bzz//jG3btuH1119Hw4YNERYWhs6dOyM0NBTu7u5K5eHu7gKj0foUVnFxKXQ62y1ZhoYMa2BDnPlsiNWQYQ1siDOfjeqpV8cZiVNbIDXjBnYcNVT8ByqpsKgIyxIS4efjg6C2D2HT/9uOFn7N0bZVSxw7aZuXh8nyXKj5fJNyFHu2XFxcEBQUhKCgIEyaNAkA8Mcff2DXrl149dVXcenSJRw/flypPIqKSuHmZn11A51Oi8LCEjZUnM+GWA0Z1sCGOPPZEKshwxpkagBA88Y6JE4NxO/nizAtIR1ms23m5l64gGUfJKJZ48Z4ZuxonE5Px7Fff8XC2bNsE/hfsjwXaj3fpCzF34ifl5eHL7/8EnPmzMHkyZOxefNmdOvWDe+8846i3YwMA3x8PK2O+fp6ljs9WNsbMqyBDXHmsyFWQ4Y1sCHOfDaq5uHAevh/89tgR6oB0av+gLHUNjuWU3+k47WlyxHU9iFMnTgeri4uOPRzKi5evoIZryzElHnz8d3+gzj08xG8tKhm/9aS5dF/cgIAACAASURBVLlQo2FvfCN+DSxevBgDBgzA448/jn379uHhhx9GUlISkpOTERsbiz59+iiVBgDo9ecBAFFRbeHs7ITISH8EBHhj9+4sNlScz4ZYDRnWwIY489kQqyHDGmRp+DR0Q9L0Fojbmo1FX/5pk5kAkHfpEt5d8wEe79sbIwb0h5OTEwBg4qgRWPPOIqxa9CZWLXoTjz0ahs7BQXhj3twa9WR4LtRqkPKczGZbnay01qpVK7Rt2xZjxozBo48+Cm9v273ZKSRkTaVu5+/vZbkmd05OAZYsOWj5i2srMjRkWAMb4sxnQ6yGDGtgQ5z5bAC5HTpUeJsFIx5AdGQT3Ci2/q/SH+3Ow5ubK97EfDHs9r8/5NOvtmLH93vg5upqdbxH1y4YOXCA5fP1X36FwqLiO/6elqkvZ1d4H24S+blQo6HXR9v0fiilzmL1zhoVveilWutWim1aLl26hAMHDuDAgQM4dOgQGjRogLCwMHTp0gUhISFwc3Or9uzKblqIiIiIbKkym5aautOmxVaqsmmp7bhpKc9emxbF3oh/7733YtCgQRg0aBAA4NSpUzhw4AA+/vhjvPjiiwgMDMSHH36oVJ6IiIiIqFaoDZc8VvyN+ABw4cIFnD17FpcuXUJBQQHc3NxQr149NdJEREREROTgFDvTsm7dOhw9ehSpqam4ceMGQkJCEBoaikGDBqFVq1ZKZYmIiIiIahV7XtVLLYptWvbu3YtHHnkEEyZMwIMPPgiNRpWTOkREREREJBnFNi0ffPCBUqOJiIiIiOh/8UwLEREREVk0OXpU8cZUhRM7tw9UNgAgst/XijeoduGmhYiIiIjIgfHqYURERERERHbGMy1ERERERA6sNrynhWdaiIiIiIhIaFJvWgIDvZGYOAj79k3Axo3D0KZNQzbsMJ8NsRoyrIENceazIVZDhjWwYd/5h3/6CeOfnoQevftg2BNR+Grr32+oLy0txfL4ePQdOAiRffvhpYULUVBQUOMeIMdzYW9OJpNqH/Yi7aZFq9UgLq4XkpPTER6ehMTEVMTH94WHhwsbKs5nQ6yGDGtgQ5z5bIjVkGENbNh3fl7eBcS8sgDjx45B8n+3I3bBK1i1Zg1+OHwYq9Yk4JfjJ/BJ0of46otNKC4qRvyqVUKuwx4NUp5im5Yvvvjijl8rKCjAiy++qFQaABAc3BRarQYbNhyHyWTGzp3pyMgwICLCnw0V57MhVkOGNbAhznw2xGrIsAY27Ds/JzcHkT17IrxbN2g0GrRp3RpBHTrgSOpRbPn6a8x9fha8vb3h4e6Ol+fHIGrUKCHXYY8GKU+xTcvHH3+MGTNm4Pr161bHDx06hP79++P8+fNKpQEAfn5eyMw0WB3LyspHQIA3GyrOZ0OshgxrYEOc+WyI1ZBhDWzYd36H9u3x4pzZls+vXruGtGPH4F6nDoxGI7LOnMGo0WPQf/AQrE74APc2aFDt1k0yPBci0JSVqfZhtzUqNXjTpk3w9PTEgAED8OOPP8JoNOL111/Hs88+i/Hjx+Pjjz9WKg0AcHd3gdFo/bq74uJS6HS2u2CaDA0Z1sCGOPPZEKshwxrYEGc+G2I1lJ5fUFCAF2Lmo02bNmjfrh3MZjOSU1Kw+r14rPswEWfPncOK996rcUeG54LUodiz5erqitdeew27du3C7NmzodVq0aRJE2zevBl+fn5KZS2Kikrh5uZsdUyn06KwsIQNFeezIVZDhjWwIc58NsRqyLAGNsSYf/bcObwQMx/NfX3x6isvIz0jA2VlZZg8aRLuueceAMCEcWPxyquvYd7cuTVqyfBciICXPK4hk8mEEydOoLCwEA0bNoTRaERJiTp/QTIyDPDx8bQ65uvrWe70YG1vyLAGNsSZz4ZYDRnWwIY489kQq6HU/NSjaXj6mcno1rUr3vxPLNzc3HD/ffdBo9Hg2i0v+TfZ6B/JMjwXpA7FNi2///47hg0bhu+//x4bN27Epk2bMHDgQDzxxBNISEiA2WxWKg0A0Ov/fs9MVFRbODs7ITLSHwEB3ti9O4sNFeezIVZDhjWwIc58NsRqyLAGNuw7/8/sbMyZNw+TnpqIZ5+JhpOTEwCgXr166N6tK1atXoOrV68iPz8fSevWIaLHY0Kuwx4Ne6sNlzx2Miu0e+jYsSPGjRuH5557Di4u/3dJuV9//RWzZ8+Gl5cX1q9fX63ZISFrKnU7f38vxMR0RWCgN3JyCrBkyUHLX1xbkaEhwxrYEGc+G2I1ZFgDG+LMZ0OsRnXn79w+8LbHl8fHY+Pnm1CnTh2r40MHD8aEcWPx3vursXf/fhiLixHevTuenzEdOp3utrMi+32t+DqqoroNvT7apvdDKQ1n/apa6+K7rVVr3UqxTUtaWhrat29/268VFRVh0aJFeO2116o1u7KbFiIiIiKydqdNiy1VZdMiMkfZtDSecUK1Vt7yB1Vr3Uqxl4fdacMCAHXq1Kn2hoWIiIiIiGoXXuuNiIiIiMiB8ephREREREREdsYzLUREREREDoxnWoiIiIiIiOyMZ1qIiIiIahE1ruy1MTFU8caoiYcVbzgKTVmZve+C4nimhYiIiIiIhMYzLUREREREDozvaSEiIiIiIrIzblqIiIiIiEhoUr88LDDQGzExXREY6I3s7OuIjd2DkycvsqHyfDbEasiwBjbEmc+GWA0Z1sCGOPOVaqSmHcOH6z/F+dxceNavj6GDBqBPRARy8vIwadoMuLm6Wm7brUsYZkyZXNNlqPJY2RNfHubAtFoN4uJ6ITk5HeHhSUhMTEV8fF94eLiwoeJ8NsRqyLAGNsSZz4ZYDRnWwIY485VqXLx0CW/ELcWooY/j86REvDBzOpLWb8DPR48iPSMTLQL8sfmTdZYPW2xY1HisSHmKbVpiY2NRXFys1PgKBQc3hVarwYYNx2EymbFzZzoyMgyIiPBnQ8X5bIjVkGENbIgznw2xGjKsgQ1x5ivVyLt4EeGPdkHYw6HQaDRoERCAtg+2wclTv+GPjAz4+fra7P7fpMZjZW+asjLVPuy2RqUGnzlzBv3798ePP/6oVOKu/Py8kJlpsDqWlZWPgABvNlScz4ZYDRnWwIY489kQqyHDGtgQZ75SjYdat8bU6EmWz69fL8CJX0/Bv7kv0jMzcebsOUyaPhNjoidj+ar3UXDjRrVbN6nxWJHyFNu0rF27FtOmTcPzzz+P1157DUVFRUqlbsvd3QVGo/Xr+4qLS6HT2e5tPDI0ZFgDG+LMZ0OshgxrYEOc+WyI1ZBhDTduFCJ28dtoGRiIRzqFoK6HBzq2b4tlb72J5YsX4eKly1i5ek2NO2o8VvbmZDKp9mEvij5bgwYNQvfu3bF8+XIMHjwYQ4cOhZOTk+XrkyZNusufrpmiolK4uTlbHdPptCgsLGFDxflsiNWQYQ1siDOfDbEaMqyBDXHmK93IPn8esW+/gwfuuw9zp0+DRqPBi7NmWr7u4eGOcVGjMPeVhTCZTHB2dr7LtLtT47Ei5Sn+RnyNRgNnZ2fk5+cjPT0dGRkZlg8lZWQY4OPjaXXM19ez3OnB2t6QYQ1siDOfDbEaMqyBDXHmsyFWw5HXcPzkScya/zI6d+qE+bOfh6urK4qNRiR+/AkM+fmW25WUlsJZo4FGU7N/rqrxWNlbbTjTouimZcuWLejVqxf+/PNPbNmyBYsXL8Zbb71l+VCSXn8eABAV1RbOzk6IjPRHQIA3du/OYkPF+WyI1ZBhDWyIM58NsRoyrIENceYr1cjJzcWri97G6JHDMf7JKMsrcHRubkg99gs++nQjjMa/cMVgQNL6T9EzPNzqVTqirIPU52Q2m81KDB43bhz++OMPxMTEoH///jadHRJSudc3+vt7Wa7JnZNTgCVLDlr+4tqKDA0Z1sCGOPPZEKshwxrYEGc+G2I1RF7DxsTQ2x5PSFqHLdu3Q+fmZnW8X+9e6BcZgfcTP8SJU6fhrNGgW1gYnho7Gq63/N6WW42aeFjxdej10ZVu2JP/yBTVWumf9VCtdSvFNi0vvvgiYmJi4OnpWfGNq6iymxYiIiIiUt+dNi22VJVNS3Vx01KevTYtir0Rf/HixUqNJiIiIiKi/2XP95qoRfE34hMREREREdWEPBeoJiIiIiKqhXimhYiIiIiIyM54poWIiIiIyIFpysrsfRcUx00LEREREdmUGlf2in+9meINEgdfHkZERERERELjmRYiIiIiIgfGN+ITERERERHZGc+0EBERERE5MJ5pcXCBgd5ITByEffsmYOPGYWjTpiEbdpjPhlgNGdbAhjjz2RCrIcMa2BBnviM3jp86jQXvLMUzL8Rg7n/ewO4DB8vd5t2EtUhYv6HGLVKHtJsWrVaDuLheSE5OR3h4EhITUxEf3xceHi5sqDifDbEaMqyBDXHmsyFWQ4Y1sCHOfEduXDYYsDIxCQMje2LVojcwZewYbNq2Hb/8espym5T9B5B24qQtliAETVmZah92W6O9wrm5uYrODw5uCq1Wgw0bjsNkMmPnznRkZBgQEeHPhorz2RCrIcMa2BBnPhtiNWRYAxvizHfkxqUrBnQODkJI+3bQaDTw83kArQIC8HtmJgDgfF4eduzeg84hwbZaBqlAsU1L69at8frrr6OkpOS2X+/bt69SaQCAn58XMjMNVseysvIREODNhorz2RCrIcMa2BBnPhtiNWRYAxvizHfkRkt/P4wfOdzyecGNG/gtPQMPNGuG0tJSvL9uPcYMH4q67nWq3RCNk8mk2oe9KLZpcXFxQVpaGqKionD+/PlyXzebzUqlAQDu7i4wGq0f2OLiUuh0trv2gAwNGdbAhjjz2RCrIcMa2BBnPhtiNWRYgxqNwqIiLEtIhJ+PD4LaPoTN279BC7/maNuqpU3mk3oU27RotVqsX78eLVq0wJAhQ/D9999bfd3JyUmpNACgqKgUbm7OVsd0Oi0KC29/5qe2NmRYAxvizGdDrIYMa2BDnPlsiNWQYQ1KN3IvXEDsu8txT726mDpxHE6np+PYr79ixMD+NZ4tGp5pqSFXV1e88cYbiImJwfPPP48lS5agTKU38GRkGODj42l1zNfXs9wpyNrekGENbIgznw2xGjKsgQ1x5rMhVkOGNSjZOPVHOl5buhxBbR/C1Inj4erigkM/p+Li5SuY8cpCTJk3H9/tP4hDPx/BS4veqVGL1KHKG/EHDx6MTZs2Yc+ePRg7diwuXLigeFOv//slaVFRbeHs7ITISH8EBHhj9+4sNlScz4ZYDRnWwIY489kQqyHDGtgQZ74jN/IuXcK7az7A4317Y8SA/pZX90wcNQJr3lmEVYvexKpFb+KxR8PQOTgIb8yba4ul2FVtuHqYk1mhN5d07NgRqampVseKi4vx2muvYd++fcjPz8fx48erNTskZE2lbufv74WYmK4IDPRGTk4Bliw5aPnmsBUZGjKsgQ1x5rMhVkOGNbAhznw2xGrIsIaaNOJfb3bb459+tRU7vt8DN1dXq+M9unbByIEDLJ+v//IrFBYVY9KTT9yx8UjvfpVchX21775etVbanidVa91KsU2LXq9HSEjIbb/21Vdf4csvv8THH39crdmV3bQQERERkZzutGmxJUfZtHR4dJ1qraP7x6rWupXtLv/wD3fasADAkCFDMGTIEKXSREREREQkEcU2LUREREREpDx7XtVLLaq8EZ+IiIiIiKi6uGkhIiIiIiKb0+v16NevHzp06IBnn30WBQUF1Z7FTQsRERERkQMT8ZLHRUVFmD59Ol544QX88MMP0Ol0eO+996q/xmr/SSIiIiIiotv44Ycf0KxZM3Tv3h06nQ5Tp07F1q1bqz3PId+I/803d76eNhERERFRbaLmG/GvXbuGa9eulTtev3591K9f3/L5mTNn4Ovra/n8gQcewOXLl5Gfnw9PT88qdx1y09KwYT173wUiIiIiIiHo9dGqtVauXIn4+Phyx6dOnYpp06ZZPr9x4wbq1Klj+Vyr1cLFxQXFxcXV6jrkpoWIiIiIiNQ3bty42/6+xVvPsgBAnTp1YDQaLZ+XlpaipKTEaiNTFdy0EBERERFRpfzzZWB30rx5c+zcudPy+ZkzZ+Dl5YV77rmnWl2+EZ+IiIiIiGzqkUcewZkzZ5CSkoLi4mL8z//8D/r06VPteU5ms9lsw/tHRERERESEI0eOYOHChcjOzkZYWBgWLVqEunXrVmsWNy1ERERERCQ0vjyMiIiIiIiExk0LEREREREJjZsWIiIiIiISGjctREREREQkNKk3LXq9Hv369UOHDh3w7LPPoqCgQJGO2WxGz549MW7cOJvP/vPPP9GyZUt07NjR8jF69GhkZWXZtLNlyxYMGTIEQUFB+Pe//434+HiYTCabzP7nGjp06IBBgwYhJSXFJvMBoGXLlujQoYPV49SxY0ecPHlS0cbYsWNtNv+m7777Dk8++SRCQkIQFBSEiRP/f3t3HtTkncYB/MspKIiABsTK2NISqaiAlBAOEagropyuKxXdzgB2XZUKKjjYihQshwp13WIpblcqVRGQQ45KxQK61gM0Tq3j0bUrhXKVIKdAON79wyFDBLfd5hcF+nxmnPH9JX6f931j3jdP3iMBuHnzJpNsPp+Pn3/+WWasqKgI69evZ5L/NBcXF2bz/r/Mnz8ftbW1TDNra2sxf/58mbGrV6/CysoKZ8+eVVgNVobed6O9tjExMeDz+UzW2VCdvLw8mfGcnBwEBgbKnT+kuLgYPj4+sLS0hIODA/bs2YPW1lZm+aNta52cnHD06FFmNRTtWduouro6pnUePHiAoKAgWFlZYdGiRdiwYQMePHjALD8oKEg6/3PnzsXChQul06yWRdHbQj8/P6Smpo4Yz87Oxpo1a+TKDgwMRFpamnT6559/Bp/PR1xcnHRMIpFgwYIFcn1WuHnzJiwsLHDv3j3pWG9vLzw9PZGVlfWbc4cLDw8fdT8aGBiIqKgoJjWqqqpGfDaYP38++Hw+k3zyHHET1OPHjzmhUMiVl5dz3d3dXGhoKBcfH6+QWteuXePefvttzt7enquurmaaXVNTw5mbm0un+/r6uPj4eG7dunXMahw5coRbuXIl991333GDg4Pcjz/+yPn6+nIffvghk/ynl2FgYIC7cOECZ21tzVVVVTGpYWpqyjU1NTHJepE1cnJyuMWLF3Pnz5/nurq6uI6ODi4zM5OztrZm8n9rtGUoLCxk+v9pOGdnZ04kEikkezhzc3OupqaGaebT/29v3LjBWVtbc0VFRQqrwVJNTQ33+uuvc9bW1lxzc7N0fHBwkHN1deXMzMyYrLOamhrO1NSUs7Gxkalz+vRpLiAgQO58juO4L774gnN2duYuXLjA9fb2cmKxmIuOjuaWLVvGdXV1Makx2mtRXV3N2dvbc+Xl5UxqcBzHnTp1ilu5ciVnYWHBLVmyhNu/fz/X3d3NJPvp93dHRwf37rvvcsHBwUzyOY7j+vv7OWdnZy4jI4Pr6+vjent7uZSUFM7Z2ZmTSCTM6gxR1DZE0dvCU6dOcZ6eniPG//znP3MnT56UKzs1NZXbunWrdDo3N5fz9fXl3N3dpWNVVVWck5OTXHU4juOSkpI4Ly8v6WsbGRnJbdmyRe7cIS0tLZytrS2Xk5MjHcvLy+OcnZ25zs5OZnWG6+np4VatWsVFRUUpJJ8ozoQ90nLlyhXMmjULTk5O0NDQwJYtW5Cfn6+QWrm5uViyZAnc3d2RnZ2tkBpDVFVV4enpibt37zLJ6+zsRHJyMg4dOoR58+ZBSUkJs2fPRmxsLNrb28Ep4I7YysrKcHR0RFBQEP7xj38wzx+v+vr6EB8fj8TERLi4uGDy5MnQ0tLC6tWrERERgY6Ojhc9i79bt2/fxsaNG/HBBx/A3d39Rc/Orzb0Xht+VPP69evg8/lQUVFhVkddXR1CoRDR0dHMMod0dXUhKSkJhw8fhqOjI9TV1aGnp4fdu3dj1qxZSE9PZ15ziLGxMRYtWoTvv/+eSd5HH32E9PR0xMTEoKqqCsePH0dNTQ2CgoIwODjIpMZwWlpa8PDwYHoU5NGjR6irq4O7uztUVVWhrq6Od955Bw4ODrSNGsbd3R0PHz6UWfeNjY349ttvsWLFCrmyBQKBzBHsS5cuYf369WhpaUFDQwOAJ+9zoVAoVx0A2Lx5MziOQ3JyMkpLS1FWVoaYmBi5c4fo6upi165dSEhIQGtrK1pbW5GQkIAPP/wQU6ZMYVZnuOjoaHAch4iICIXkE8WZsE1LdXU15syZI502NjaGWCxmejoBAPT09KC0tBQrVqyAr68vcnJy0N/fz7TGcH19fcjLy8PixYuZ5IlEIhgYGODll1+WGefz+YiPj4eSkhKTOqMRCoUQiUQKyx9vRCIRpkyZAmtr6xGP+fr6Yt68eUzquLm5wdraWvrnvffeY5I7Ud2/fx8BAQHYtGnTuGpYhixbtgwlJSXS6bNnz8LNzY15nd27d+PKlSsoLS1lmnvz5k3o6+tj7ty5Ix7z8PBARUUF03pDBgcHcevWLVy7dg2LFi2SO6+xsRHHjh3D4cOHYWFhARUVFRgZGSExMRGtra0oLi5mMNeyHj16hJMnT466Tfmtpk+fjvnz52PNmjVITU3Ft99+i8HBQURHR0NPT49ZnfFOS0sLb775pszrWlhYCBcXF2hra8uVPW/ePHR2dqKxsREcx+Hy5ctwcHCAQCDAv/71LwBPftCPRdOirq6Offv24fPPP0dkZCQSEhIwbdo0uXOH8/DwwIIFC/Dxxx/j4MGDWLp0KZN5H01eXh6++uorHDx4EOrq6gqpQRRH9UXPgKJ0dXVBU1NTOq2qqgo1NTX09PQwrXPu3DlYWVlhxowZmDFjBng8HsrLy/Hmm28yqyGRSKQ7ne7ubigpKY16ruxv0dbWBl1dXSZZ/y8dHR10dXUxy3Nzc5NpsmbOnImCggJm+aPVyM7OlmmO5dHU1AQejyedfvz4sbQ5HRgYwIoVK7B3716565w9exYzZsyQThcVFSEjI0Pu3IloYGAAgYGBMDU1RXFxMfz9/aGqOr42m05OTnj//ffR3t4ObW1tVFRUICQkhHkdfX19REREICoqCjY2NsxyxWLxMz8M6+vrQywWM6s1fFsLADweD8HBwbC0tJQ7++LFizAzM8Ps2bNlxlVVVeHm5oaKigqsXLlS7jpubm7gOA4SiQQ6Ojrw9PTEu+++K3fucEePHsXRo0dRUFCAxMRE6OnpITg4GGvXrmVaZ7zz8fHB3r17ERwcDAAoKChAWFiY3LkqKiqwtraGSCTCnDlzoKenh+nTp8POzg6XL1/GqlWrIBKJmB0RMTU1hYmJCZqammBhYcEk82lRUVHw9vaGjo7OiOvjWHnw4AE++OADHDhwYMT7kIwP42vv+3/Q1NREb2+vdLq/vx99fX0yjQwLeXl5uH79OgQCAYAnTUVWVhbTpkVdXR1VVVUAnnz7V15ejs2bN+PMmTNyv/H09fXR0tIy6mMtLS0K/ebs0aNHMDQ0ZJb39IdxRVBkDT09PTQ3N0unJ0+eLH3dU1NT8cMPPyikLnm2wcFB7Ny5E66urvD29sYnn3wi/QAyXmhoaEAoFKKsrAwvvfQSTE1NoaWlpZBa3t7eKCwsREJCApOjE8CTbVRjY+OojzU0NEBfX59JHUB2W8uaWCyGgYHBqI/xeDxmR52HtlFXrlzBtm3bYGtry3y/p6WlheDgYAQHB6OlpQUlJSWIj4+HiYmJdF841qmpqY242Ux/fz/Tb9/t7Ozw+PFj3LlzB2pqamhtbWV2BMHW1hY3b95EbW0t7O3tATw5eyElJQX//ve/pV+kspCWloa+vj7MnDkTBw4cwO7du5nkDmdkZIQlS5bglVdeUchpYd3d3di6dSv8/Pzg6urKPJ88HxP29LCXX34Z1dXV0unq6mro6upCR0eHWY3GxkZcv34deXl5yM/PR35+Pk6dOoVLly49cycrL2VlZbi4uMDY2Bi3bt2SO8/CwgJNTU34z3/+IzN+7949ODk5ob29Xe4az3L58mWYmZkpLH+8sbKyQmtr63O529Z4l5ubK3MUbXBwEBoaGszrqKmpYeXKldDU1ERcXBw+/fRT3Lhxg3kdRXNzc8O5c+dQUlKC5cuXK7RWdHQ0vvzyS1y5coVJnpWVFdrb20f9UF9YWMjsVFlF09PTe+Z+obm5mfkpN7a2tggLC8OOHTtQX1/PLLeoqAirV6+WTuvp6eGtt96CQCDA/fv3mdVRNB6Ph6amJpmxuro6maPd8lJWVoaXlxeKi4tRUFAALy8vKCuz+dglEAikpy/a2dkBAGbPng1lZWWUlpYya47u3LmDQ4cOIT4+HrGxsTh9+jS++eYbJtlPU1ZWZrZ+nhYdHQ1tbW1s375dIfnk+ZiwTYutrS2qq6tx/vx59PT04PDhw8x31mfOnIGtrS3mzJkDQ0NDGBoawszMDJaWlgq9IL+yshI1NTV4/fXX5c7S1NTEX/7yF4SGhuLu3bvgOA7ff/89wsPD8dZbb2Hq1KkM5ljWwMAASktL8fnnnzO9Jep4p6GhgYiICISEhKCsrAx9fX3o7e1FQUEBjh07xvQb5fGura0NmZmZkEgkOHfuHHR0dBS+fqysrLB+/XqEh4czv316Q0ODzB+JRMI0f8mSJaisrERFRQWcnZ2ZZj/NyMgIoaGhzG58oqmpibCwMGzfvh2XLl2CRCJBU1MToqKiUF9fj3Xr1jGpo2iLFy/G7du38eOPPwJ4cpvanJwcSCQSlJSUwNHRkXlNHx8fmJubIzY2llmmra0tHj58iNTUVIjFYvT396Oqqgq3bt2SfngeD5YuXYq//e1vaG5ull6/lJmZyfx6L29vb5w/fx6lpaXw8fFhljt37lzU19fj9u3bMqc0CoVCZGRkMGlauru7sW3bNmzcuBFmZmYwMTFBSEgIIiIiFPqFJmu5ubm4cOECDh48OO5ObZfTbwAACO5JREFU7yWyJuyrp6mpieTkZOzZswdhYWGws7Nj3mHn5+cjKChoxLiHhwdSUlKwadMmJheySyQSmXOqZ86cib179zK7lmLjxo3Q1NREaGgoGhoaoKurC19fX/z1r39lkg/ILoOamhpee+01fPTRR1i4cCGzGkuXLh2xvnft2iXzreBYt2rVKsyYMQOfffYZdu7cib6+PvD5fOzYsQNeXl4vevbGjNWrV6OyshJCoRDTpk1DbGysQm8aMSQkJAQVFRWIiYlBQkICk0yJRAInJyeZsePHjzO9eHry5Ml44403AEBhd+QZzt/fn+mF5X5+ftDR0UFSUhJ++OEHTJkyBS4uLsjIyFDYqW6sGRgYICAgAJs3b0ZMTAz09fVx4sQJJCUlYdasWUyuZxnN7t274enpiYsXLzJpjPT19ZGeno7ExESkpqaiv78fr776Kvbv3w8TExMGc/x8hIaG4sCBA/D29kZXVxcMDAywadOmEe9FeZmYmEBbWxsqKirM9tkAoKSkhHnz5qGtrU3m9D+hUIicnBwm15XFxcVBR0dH5nPO22+/jdLSUsTExGD//v1y13gecnJy0NraOmpDWlRUBCMjoxcwV+S3UOIUcU9bQgghhIyQmZmJ9PR01NbWQltbGw4ODqiqqsK6desU8mO1hBAyUVDTQgghhLxALS0tqKqqwh/+8IcXPSuEEDJmUdNCCCGEEEIIGdMm7IX4hBBCCCGEkImBmhZCCCGEEELImEZNCyGEEEIIIWRMo6aFEEImoJqamhc9C4QQQggz1LQQQogc+Hw+Fi5cCEtLS1haWsLKygqBgYHMfh28trYWfD4f7e3tqKurg6WlJTo6Ov7nv7lz5w7+9Kc//eaafD4fd+7cGTGek5Pzq38v6FkZv+Tq1atMf6OGEELIxEBNCyGEyCkjIwMikQgikQhXr14Fn8/Hhg0bMDAwwLSOkZERRCIRtLW1/+fz2tvb0dfXx7Q2IYQQ8iJR00IIIQypqanBx8cHDQ0NaGtrQ05ODvz8/ODn5weBQIC7d++ira0NERERsLe3h5OTE5KSktDf3w8AGBwcRFJSEgQCAezt7ZGTkyPNHn7UBQBEIhHWrFkDS0tLLFu2DF999RXEYjE2bNiAjo4OWFpaorGxEb29vYiLi4OTkxPs7e0RGRmJx48fS3PT0tLg6OgIGxsbpKSk/Krl5DgOH3/8MZYvXw5LS0ssXrwYaWlpMs/58ssv4erqCgcHB+zbt0/aSA0MDCAlJQWurq4QCATYunUrWlpa5FnthBBCJjhqWgghhKG2tjakp6fjtddeg56eHoAnzcWmTZtw/vx58Pl87Ny5E11dXSgpKUFWVhauXbuGTz/9FABw8uRJFBYWIisrCyUlJbh9+/aodVpaWrBhwwZ4enqisrISUVFR2LFjB3p7e3HkyBFoa2tDJBLBwMAA+/fvx3fffYfTp0/j7NmzEIvF2Lt3LwCgvLwcycnJ+OSTT3Dx4kXU1tb+quUsLCxEfn4+0tLScOPGDezZswf79u1DU1OT9DnXr19HVlYWMjMz8fXXXyM9PR0AcOzYMZw5cwZHjx5FRUUF9PT0EBoa+pvXOSGEkImPmhZCCJHT2rVrYW1tDWtrayxfvhxNTU34+9//Ln1cV1cXixcvhpaWFsRiMcrKyhAZGQktLS3weDxs3rwZGRkZAIDi4mKsW7cOxsbG0NLSQkhIyKg1y8rKYGBgAH9/f6iqqkIoFOLEiRPQ0dGReR7HccjKykJ4eDimT58ObW1tbN++Hbm5uZBIJCguLoanpyfMzc0xadIkhIeH/6pldnZ2xvHjx2FgYIDm5maoqalhYGBA5ohJaGgo9PT0YGRkhICAABQWFgIAMjMzsWXLFhgbG0NDQwNhYWGorKzEw4cP/5/VTggh5HdE9UXPACGEjHcnTpyAmZnZMx/n8XjSv9fV1QEA3NzcpGMcx6Gvrw+9vb1obm6GoaGh9LGXXnpp1EyxWIyZM2fKjJmbm494XktLC3p6ehAQEAAlJSXpuKqqKn766Sc0Nzfj1VdflY5PnToVU6dOfeayDOnv70dcXBy++eYb8Hg8LFiwQLosQ4yMjKR/NzQ0lB6Fqaurw3vvvYfIyMgR86OqSrslQgghI9HegRBCFGx4s8Dj8aCsrIyLFy9CU1MTANDZ2QmxWIxJkyaBx+Php59+kj6/sbFx1EwejzfisbS0NAgEApmxadOmQU1NDVlZWXjllVcAABKJBDU1NTA2NgaPx5M2UgDQ1dX1i3cnA4CkpCT09vaioqICGhoaaGtrQ3Z2tsxzmpubpY1LXV0dZs2aJZ33yMhIODo6Sp97//59zJkzByKR6BdrE0II+f2h08MIIeQ5MjQ0hI2NDeLj49HV1YXOzk5ERETg/fffBwD4+vriiy++wIMHD9DV1YWDBw+OmuPk5ITGxkZkZWVhYGAAly9fxqFDh6ClpQV1dXVIJBL09vZCRUUFnp6eOHDgAB49egSJRIKEhARs3LgRAODj44OCggKIRCJIJBIkJSXJHC15lo6ODkyaNAkqKipoa2tDbGwsAMjctezQoUNoa2tDTU0N/vnPf2LVqlUAAG9vbyQnJ6O+vh4DAwNITU2Fv78/enp65Fq3hBBCJi5qWggh5DlLTExEZ2cnli5dChcXFygpKUmbEx8fH6xduxbr16+Hi4sL5s6dO2qGrq4uUlNTkZ2dDRsbG8TExCAxMRGzZ88Gn8+HmZkZBAIB7t27h127dsHQ0BBeXl6ws7PDw4cPceTIEaioqEAgECAiIgLbtm2DUCiEmpoapk2b9ovLsHXrVtTX18PGxgYeHh7Q1dUFn8+X+X2ahQsXYvny5Vi7di28vb3xxz/+EQDwzjvvQCgUwt/fH2+88Qa+/vprfPbZZ7/qtDRCCCG/T0rcr/lKjRBCCCGEEEJeEDrSQgghhBBCCBnTqGkhhBBCCCGEjGnUtBBCCCGEEELGNGpaCCGEEEIIIWMaNS2EEEIIIYSQMY2aFkIIIYQQQsiYRk0LIYQQQgghZEyjpoUQQgghhBAyplHTQgghhBBCCBnT/gu8QOJX1zg2kAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap=\"terrain\"\n",
    "\n",
    "cm_plot_labels = ['0','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",
    "\n",
    "cm = confusion_matrix(y_true=real, y_pred=predicted)\n",
    "\n",
    "df_cm = pd.DataFrame(cm,cm_plot_labels,cm_plot_labels)\n",
    "sn.set(font_scale=1.1) # for label size\n",
    "plt.figure(figsize = (15,10))\n",
    "s=sn.heatmap(df_cm, annot=True,cmap=cmap) # font size\n",
    "bottom,top=s.get_ylim()\n",
    "s.set_ylim(bottom+0.6,top-0.6)\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "plt.savefig('matrix4.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}