{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **!!!_10_Training errors for different N**"
      ],
      "metadata": {
        "id": "OGJEMe57dgqi"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "UQRhYr-UcUZt",
        "outputId": "fb1b28ef-6062-4bc8-e7f5-5b79d80a98af"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pyod\n",
            "  Downloading pyod-2.1.0-py3-none-any.whl.metadata (41 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/41.7 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.7/41.7 kB\u001b[0m \u001b[31m1.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: joblib in /usr/local/lib/python3.12/dist-packages (from pyod) (1.5.3)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.12/dist-packages (from pyod) (3.10.0)\n",
            "Requirement already satisfied: numpy>=1.19 in /usr/local/lib/python3.12/dist-packages (from pyod) (2.0.2)\n",
            "Requirement already satisfied: numba>=0.51 in /usr/local/lib/python3.12/dist-packages (from pyod) (0.60.0)\n",
            "Requirement already satisfied: scipy>=1.5.1 in /usr/local/lib/python3.12/dist-packages (from pyod) (1.16.3)\n",
            "Requirement already satisfied: scikit-learn>=0.22.0 in /usr/local/lib/python3.12/dist-packages (from pyod) (1.6.1)\n",
            "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.12/dist-packages (from numba>=0.51->pyod) (0.43.0)\n",
            "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn>=0.22.0->pyod) (3.6.0)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (1.3.3)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (4.62.1)\n",
            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (1.5.0)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (26.0)\n",
            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (11.3.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (3.3.2)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.12/dist-packages (from matplotlib->pyod) (2.9.0.post0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.7->matplotlib->pyod) (1.17.0)\n",
            "Downloading pyod-2.1.0-py3-none-any.whl (238 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m238.4/238.4 kB\u001b[0m \u001b[31m5.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: pyod\n",
            "Successfully installed pyod-2.1.0\n",
            "================================================================================\n",
            "FULL DATASET (441 points, one outlier)\n",
            "================================================================================\n",
            "Removed normal points: 396\n",
            "Remaining points: 45 (outliers: 1)\n",
            "Outlier percentage: 2.22%\n",
            "The true outlier is at index 24 (zero-based index 23)\n",
            "\n",
            "Q = 45, N_x = 2, N_y = 1\n",
            "N_min = 2.3106, N_max = 31.6667\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x2800 with 28 Axes>"
            ],
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AXqSmSrGx1a9PSZFGjGi59gAtKFhzRXl5udq1a6e33npLiYmJ5vK77rpLp06d0t/+9jeP5/Tp00fz58/XvHnzzGVLlizR5s2bzRMy6cdO8W+//VYffvihunbtWmNb/v3vf2vw4ME6ePCgBgwYUKf2B+txAZoU+RutHLnC/3BMgDogf6OVC9ZckZWVpV69emnXrl0aPXq0uXzhwoXauXOn9uzZ4/Gc0NBQrVu3TpMmTTKXvfjii3r00UeVm5urXbt26corr1RWVpZ69Ohh1rnttttksVi0ceNGSdKKFSs0YsQIdenSRbt27dKDDz6oadOmacWKFV7bWlZW5nbhemFhoXr37q38/Hx16tRJDodDkrNjv2rZbrfLYrHUWrZa/z97fx4fVX33//+PM5MVkEXSbAgSaZBYJAEiKUjFtlwNVStcFVAuK0i94XJJK+VbqVgWC/SDC1oU0IgtFfqTC8SP5bLVYhGXz3VJjCaBIDWsBUMJCQRC9nXm/P6YzCFDVsgyC8/77Ta3vHPmPTPv17zPzHvOeS/HhmEYHun6+nprcKM7DeBwODzSQUFBmKbpkXY6ndjtdo+00+nENM02083FoZgU02XFlJ2NPTkZp82Gabdjr6vzTNvtmBkZ2EePbjaOvXv3kpKSwiMb/0ZsQhKG6cQEMGycyt3L2vtS+eKLL0hMTOySmPbt28dNN93E3D+9T0xCEpgmBiamYSM/dy9p99/GZ599RlJSkn/XUyDuez4SU1lZWbvb76BW7xURERHpAiEhIYwePZpdu3ZZHeNOp5Ndu3Yxd+7cZh8zduxYdu3a5dExvnPnTo+Denen+OHDh/noo4/a7BQH149/m81GZGRkh2ISEREREREREU/z58+30iNGjCAkJISHHnqIlStXEhoa2iR/aGhos9sbr+xz8TbA6si5nLR7JaL2pNu7clFzZbzUtGJSTO2OqdGKbbg7GRunHQ5w52khjvr6ekxceUzjwnYnhtVx2ZUxOZ1OnA2vj2FcKAsGde6V5/y9ngJx3/OhmNpLHeMiIiLiFfPnz2fWrFkkJyczZswYVq9eTUVFBbNnzwZg5syZDBgwgJUrVwLw2GOPMWHCBJ5//nluv/12tmzZQmZmJuvXrwdcneJTp04lOzubv/71rzgcDgoKCgC4+uqrCQkJIT09nYyMDL773e9y1VVXkZ6ezi9+8Qt+8pOf0K9fP++8ESIiIiIiIiJdKCIiArvdbi1P61ZYWNjipUGjo6Nbze/+W1hY6DFjvLCwkKSkpBbLkpKSQn19PcePH2/3qm0iIiKdJWCuMS4iIiL+5e6772bVqlUsWbKEpKQk9u7dy44dO4iKigIgLy+PU6dOWfnHjRvH5s2bWb9+PYmJibz11lts376d4cOHA3Dy5Eneeecd/vWvf5GUlERMTIx12717N+Aaeb5lyxYmTJjAt771LX7729/yi1/8wupcFxEREREREQk0jVdtc3Ov2tZ4FbbG3Ku2NdZ41ba4uDiio6M98pSWlpKRkdHic4JWbRMREe/SjHERERHxmrlz57a4dPrHH3/cZNu0adOYNm1as/kHDx6MaZqtvt6oUaP47LPPLrmcIiIiIiIiIv6ss1dtMwyDefPmsWLFCuLj44mLi2Px4sXExsZal0zTqm0iIuJr1DEuIiIiIiIiIiIiIhLA7r77bs6cOcOSJUsoKCggKSmpyaptja/z6l61bdGiRTz55JPEx8d7rNoGsGDBAioqKnjwwQc5f/4848ePZ8eOHYSFhQEXVm176qmnqKmpIS4ujl/84hce1x0XERHpTuoYFxEREREREREREREJcJ25ahu4Zo0vW7aMZcuWNXu/Vm0TERFfo2uMi4iIiIiIiIiIiIiIiIhIQFPHuIiIiIiIiIiIiIiIiIiIBDR1jIuIiIiIiIiIiIiIiIiISEBTx7iIiIiIiIiIiIiIiIiIiAQ0dYyLiIiIiIiIiIiIiIiIiEhAU8e4iIiIiIiIiLTbunXrGDx4MGFhYaSkpPD555+3mn/btm0MGzaMsLAwbrzxRt577z2P+03TZMmSJcTExBAeHs7EiRM5fPiwR55Dhw4xefJkIiIi6N27N+PHj+ejjz7q9NhEREREREQkcKljXERERERERETaZevWrcyfP5+lS5eSnZ1NYmIiqampnD59utn8u3fvZsaMGTzwwAPs2bOHKVOmMGXKFPbv32/lefbZZ3nppZdIS0sjIyODnj17kpqaSnV1tZXnjjvuoL6+ng8//JCsrCwSExO54447KCgo6PKYRUREREREJDCoY1xERERERERE2uWFF15gzpw5zJ49mxtuuIG0tDR69OjBhg0bms3/4osvMmnSJB5//HESEhJYvnw5o0aNYu3atYBrtvjq1atZtGgRkydPZsSIEWzatIn8/Hy2b98OQFFREYcPH+aJJ55gxIgRxMfH8/TTT1NZWenRwX6xmpoaSktLPW4ATqfT+ttc2uFwtCttmmaTdH19fZO0aZpN0u7YG6cdDkeTtNPpbFdaMSmmToup4TmcNhuO4OCm6Yvi9ouYArGeFFOXxiQiIiKBSx3jIiIiIiIiItKm2tpasrKymDhxorXNZrMxceJE0tPTm31Menq6R36A1NRUK/+xY8coKCjwyNOnTx9SUlKsPP379+f6669n06ZNVFRUUF9fz6uvvkpkZCSjR49usbwrV66kT58+1m3gwIEAHD9+HIATJ05w4sQJqxz5+fkAHD16lMLCQsC1hHtRUREAubm5FBcXA7B//35KSkoAyMnJoby8HIA9e/ZQVVUFQGZmJrW1tTgcDjIzM3E4HNTW1pKZmQlAVVUVe/bsAaC8vJycnBwASkpKrA7/4uJicnNzAdcAgUOHDgFQWFjI0aNHAcjPz+fYsWOKSTF1TkwNr1N8/fXk3nuvK6YRIzg0daorpqoq/4spEOtJMXVpTCIiIhK4DFND4bymtLSUPn36UFJSQu/evb1dHBHflZ0NrZzwIisLRo3qvvKIdCO1Fb5J9SLSDmq/5QoXiG1Ffn4+AwYMYPfu3YwdO9bavmDBAj755BMyMjKaPCYkJISNGzcyY8YMa9vLL7/Mb37zGwoLC9m9ezc333wz+fn5xMTEWHmmT5+OYRhs3boVgH/9619MmTKF7OxsbDYbkZGRvPvuu4wcObLF8tbU1FBTU2P9X1paysCBAykuLqZv377WjEGbzeaRdjgcGIbRZtpms2EYhke6vr4eu93ukQbXTMTG6aCgIGuGpDvtdDqx2+0eaafTiWmabaabi0MxKabLiik7G3tyMk6bDdNux15X55nOzMRMSvKvmAKxnhRTl8VUVlYWcO23vwvE31Qina6t429o9Rg8Ozub0aNHM/eNDxiQkOhx38ncHNbeO5GsrCxGddExvLdfX/zfpbQVQd1UJhERERERERGRS2aaJo8++iiRkZH8z//8D+Hh4fz+97/nRz/6EV988YVHh3pjoaGhhIaGNtlus9k8/l6cdnfkXE46KCio3WnDMDzS7udpnG6pjJeaVkyKqd0xGYarXE4nuDsZG6cNAy4hbp+IKRDrSTF1aUwiIiISuLSUuoiIiIiIiIi0KSIiArvdbi1N61ZYWEh0dHSzj4mOjm41v/tva3k+/PBD/vrXv7JlyxZuvvlmRo0axcsvv0x4eDgbN27slNhEREREREQk8KljXERERERERETaFBISwujRo9m1a5e1zel0smvXLo+l1RsbO3asR36AnTt3Wvnj4uKIjo72yFNaWkpGRoaVp7KyEvCcCej+371sroiIiIiIiEhbtJS6iIiIiIiIiLTL/PnzmTVrFsnJyYwZM4bVq1dTUVHB7NmzAZg5cyYDBgxg5cqVADz22GNMmDCB559/nttvv50tW7aQmZnJ+vXrAdfyufPmzWPFihXEx8cTFxfH4sWLiY2NZcqUKYCrc71fv37MmjWLJUuWEB4ezmuvvcaxY8e4/fbbvfI+iIiIiIiIiP9Rx7iIiIiIiIiItMvdd9/NmTNnWLJkCQUFBSQlJbFjxw6ioqIAyMvL85jZPW7cODZv3syiRYt48skniY+PZ/v27QwfPtzKs2DBAioqKnjwwQc5f/4848ePZ8eOHYSFhQGuJdx37NjBr3/9a773ve9RV1fHt771Lf77v/+bxMTE7n0DRERERERExG+pY1xERERERERE2m3u3LnMnTu32fs+/vjjJtumTZvGtGnTWnw+wzBYtmwZy5YtazFPcnIy77///iWXVURERERERMRN1xgXEREREREREREREREREZGApo5xEREREREREREREREREREJaOoYFxERERERERERERERERGRgKaOcRERERERERERERERERERCWjqGBcRERERERERERERERERkYCmjnEREREREREREREREREREQlo6hgXEREREREREREREREREZGApo5xEREREREREREREREREREJaF7pGH/22Wepqqqy/v/000+pqamx/i8rK+M///M/L+k5161bx+DBgwkLCyMlJYXPP/+81fzbtm1j2LBhhIWFceONN/Lee+953G+aJkuWLCEmJobw8HAmTpzI4cOHPfIcOnSIyZMnExERQe/evRk/fjwfffTRJZVbRETEX3RF+y0iIiJdS+23iIiIf1IbLiIi0vm80jG+cOFCysrKrP9/+MMfcvLkSev/yspKXn311XY/39atW5k/fz5Lly4lOzubxMREUlNTOX36dLP5d+/ezYwZM3jggQfYs2cPU6ZMYcqUKezfv9/K8+yzz/LSSy+RlpZGRkYGPXv2JDU1lerqaivPHXfcQX19PR9++CFZWVkkJiZyxx13UFBQcClvh4iIiF/o7PZbREREup7abxEREf+kNlyke+Xl5ZGdnd3sLS8vz9vFE5FOEuSNFzVNs9X/L9ULL7zAnDlzmD17NgBpaWm8++67bNiwgSeeeKJJ/hdffJFJkybx+OOPA7B8+XJ27tzJ2rVrSUtLwzRNVq9ezaJFi5g8eTIAmzZtIioqiu3bt3PPPfdQVFTE4cOH+cMf/sCIESMAePrpp3n55ZfZv38/0dHRTV63pqbGY1RfaWkpAE6n0+OvzWbzSDscDgzDaDNts9kwDMMjXV9fj91u90gDOBwOj3RQUBCmaXqknU4ndrvdI+10OjFNs810c3EoJsV02TEBTpsN027HXlfnmW7IZ2/lM+STMQViPflwTHl5eZw5cwbDMABXu2Oz2ejfvz8DBgzw6Zh8SWe33yIiItL11H6LiIj4J7XhIt0nLy+PYQkJVFVWNnt/eI8eHMjNZdCgQd1cMhHpbL51xv0y1NbWkpWVxcSJE61tNpuNiRMnkp6e3uxj0tPTPfIDpKamWvmPHTtGQUGBR54+ffqQkpJi5enfvz/XX389mzZtoqKigvr6el599VUiIyMZPXp0s6+7cuVK+vTpY90GDhwIwPHjxwE4ceIEJ06csMqQn58PwNGjRyksLARcy7cXFRUBkJubS3FxMQD79++npKQEgJycHMrLywHYs2ePteROZmYmtbW1OBwOMjMzcTgc1NbWkpmZCUBVVRV79uwBoLy8nJycHABKSkqs2fTFxcXk5uYCUFRUxKFDhwAoLCzk6NGjAOTn53Ps2DHFpJg6N6brryf33ntdMY0YwaGpU10xJSdztGH0rN/FFIj15IMxHTt2jMSkJLZv3864ceP47ne/y/bt2xk9ejTjv/MdPv30U5+PKZB15qVQ6urq+NWvfsWNN95Iz549iY2NZebMmVYduJ07d457772X3r1707dvXx544IEr4r0WEREREREREZGmioqKqKqsZPqKV5j7xgcet+krXqGqstI6lyci/s0wvTDUzGazUVBQQGRkJABXXXUVOTk5XHfddYCrsyE2NhaHw9Hmc+Xn5zNgwAB2797N2LFjre0LFizgk08+ISMjo8ljQkJC2LhxIzNmzLC2vfzyy/zmN7+hsLCQ3bt3c/PNN5Ofn09MTIyVZ/r06RiGwdatWwH417/+xZQpU8jOzsZmsxEZGcm7777LyJEjmy1rczPGBw4cSHFxMX379tVsUMWkmFqKKScH5003tTxjPCMD++jR/hVTINaTj8aUk5NDcnIyM377Cv0Hf9P1GkDBsSNsW/yffP755yQnJ/tsTGVlZfTp04eSkhJ69+6NN3Vm+w2uS6HMnDmTtLQ0UlJSWL16Ndu2bePgwYPWazS2e/dubrnlFlauXMkdd9zB5s2beeaZZ8jOzmb48OGUlJQwdepU5syZQ2JiIsXFxTz22GPWYA+3H/7wh5w6dYpXX32Vuro6Zs+ezU033cTmzZvb/V6Ulpb6TL2I+KzsbGhhwCgAWVkwalT3lUekm/lKW9HZ7bc/85U6EfFpar/lCudLbYXacBdfqhMJXNnZ2YwePZq5b3zAgIREj/tO5uaw9t6JZGVlMcpX28C22m9otQ33dvzefn3xf5fSVnhlKXWA3//+9/Tq1QuA+vp6Xn/9dSIiIgA8rp3iq0zT5NFHHyUyMpL/+Z//ITw8nN///vf86Ec/4osvvvDoUHcLDQ0lNDS0yXb3UrmNl8xtnHZ3Tl1OOigoqN1pwzA80u7naZxuqYyXmlZMiumSY3I6wd3J2DjtcEDD8th+F1Mg1pMPxuRePr3/4HiPH1ZODGtJdV+PyZd0Zvvd2ZdC6dOnDzt37vR4zNq1axkzZgx5eXkMGjSI3NxcduzYwRdffEFycjIAa9as4bbbbmPVqlXExsZe2hsiIiLiB/z9+FtERORK1dlt+Lp163juuecoKCggMTGRNWvWMGbMmBbzb9u2jcWLF3P8+HHi4+N55plnuO2226z7TdNk6dKlvPbaa5w/f56bb76ZV155hfj4+CbPVVNTQ0pKCjk5OezZs4ekpKRLLr+IiEhHeaVjfNCgQbz22mvW/9HR0fzpT39qkqc9IiIisNvt1vK0boWFhc1e59v9eq3ld/8tLCz06OAuLCy0GuwPP/yQv/71rxQXF1ujD15++WV27tzJxo0bmz2hLyIi4s86s/12Xwpl4cKF1rb2XApl/vz5HttSU1PZvn17i69TUlKCYRj07dvXeo6+fftaneIAEydOxGazkZGRwb//+783+zzNrfoCWKsCaEUHxaSYmonJNLGD50ovjdOmidnwnH4TUyDWk2Lqsph8RWe23yIiItJ9OrsN37p1K/Pnz/dYtS01NbXVVdtmzJjhsWqbe/XU4cOHA/Dss8/y0ksvsXHjRuLi4li8eDGpqal89dVXhIWFeTzfggULiI2NtS5jJyIi4g1eOVo/fvw4x44da/PWHiEhIYwePZpdu3ZZ25xOJ7t27fJYWr2xsWPHeuQH2Llzp5U/Li6O6OhojzylpaVkZGRYeSorKwGanPBofBJFREQkkHRm+11UVITD4SAqKspje1RUFAUFBc0+pqCg4JLyV1dX86tf/YoZM2ZYg9gaL0PnFhQUxNVXX93i8wCsXLmSPn36WLeBAwcCrvcEuuba8nv27KGqqgqAzMxMamtrrWXhHQ4HtbW11hLxVVVV7NmzB4Dy8nLrRENJSQn79+8HoLi4mNzcXMD1/h86dAhwDfw7evQo4LpEjbsOFZNi6nBMDa9TfP315N57ryumESM4NHWqK6aqKv+LKRDrSTF1aUy+oDPbbxEREek+nd2GN1617YYbbiAtLY0ePXqwYcOGZvM3XrUtISGB5cuXM2rUKNauXQu4ZouvXr2aRYsWMXnyZEaMGMGmTZvIz89vMoD9b3/7G3//+99ZtWpVm+WsqamhtLTU4waeA9ObSzscjnal3VeWbZyur69vkjZNs0naHXfjtHsp+8Zpp9PZrrRi8p2YTNMkODgY1z9ODNN5IY1p5fHZmBqew2mz4WiIwyNtt1/I00LdBAUFWbEaphMa3gMbF1bc7MqYbDYbtobXxzStOjC4UDeBuO8pps6Lqd3MALBlyxYzNDTUfP31182vvvrKfPDBB82+ffuaBQUFpmma5n333Wc+8cQTVv5PP/3UDAoKMletWmXm5uaaS5cuNYODg80vv/zSyvP000+bffv2Nf/7v//b3Ldvnzl58mQzLi7OrKqqMk3TNM+cOWP279/f/PGPf2zu3bvXPHjwoPnLX/7SDA4ONvfu3duucpeUlJiAWVJS0onvhkgAysoyTWj5lpXl7RKKD8vKyjIBc+4bH5grs89Yt7lvfGACZpaP7z+B2lacPHnSBMzdu3d7bH/88cfNMWPGNPuY4OBgc/PmzR7b1q1bZ0ZGRjbJW1tba/7oRz8yR44c6fHe/fa3vzWHDh3aJP83vvEN8+WXX26xvNXV1WZJSYl1O3HihAmYxcXFpmmapsPhMB0OR5N0fX19u9JOp7NJuq6urkna6XQ2SZum2SRdX1/fJO1wONqVbi4OxaSYLiumzEzTBNNhs5n1wcFN05mZ/hdTINaTYuqymAK1DfdnqhORdtDxt1zhArWtqKmpMe12u/nnP//ZY/vMmTPNO++8s9nHDBw40Pzd737nsW3JkiXmiBEjTNM0zaNHj5qAuWfPHo88t9xyi/nzn//c+r+goMAcMGCA+cUXX5jHjh1r9jGNLV261ASa3NyPOX78uHn8+HHTNE3zyJEj5okTJ0zTNM2DBw+a+fn5pmma5ldffWUWFhaapmmaX375pVlUVGSapmnu3bvXOo7PysoyS0tLTdM0zc8//9ysqKgwTdM009PTzerqarOurs5MT0836+rqzOrqajM9Pd00TdOsqKgwP//8c9M0TbO0tNQ6r1RcXGz1CxQVFVl9DYWFheZXX31lmqZp5ufnmwcPHjRN0zRPnDhhHjlyRDH5SEyffvqpOWPGDHPuGx+Ya/73gLn+oz3myuwz5rr/+cp8Zut7JmB+8sknvhvTzp2mCWZRQoL55f33myaYhUlJ5lczZpgmmPkpKebBjz5qsZ6ysrLM22+/3Vy+5W/myuwz5vqP9phr/veAuTL7jPnCm++aSUlJZlZWVpfFlJWVZQ4YMMB8edtfzZXZZ8zffXbM/OMHn5krs8+Yv/6v983777/fzMrKCsh9TzF1TkyX0n57pWN89+7d5l/+8hePbRs3bjQHDx5sfuMb3zDnzJljVldXX9Jzrlmzxhw0aJAZEhJijhkzxvzss8+s+yZMmGDOmjXLI/+bb75pDh061AwJCTG/9a1vme+++67H/U6n01y8eLEZFRVlhoaGmt///vetynP74osvzB/84Afm1VdfbV511VXmt7/9bfO9995rd5kD9YeWSKfTgbl0gDrGO09ntt9dcVDuVltba06ZMsUcMWKE9YPJ7Q9/+IPZt29fj211dXWm3W4333777XaV3TR9q15EfJbab7nC+Upb0RXH3/7KV+pExKep/ZYrnC+1FZ3ZhnfF4PRPP/3UBKwODLdp06aZ06dPN03TdY590qRJ5vLly03TNNvVMa6B6YrJGzFlZmaawcHBrvOHWYXm01mFrnOIWYXmz97YaQJmZmam78bU1sB0u92Vp4W6ycrKMoOCgsyfvbHTXJl9xhV/w3vw8zd2mjabzczKyuqymLKyskybzWb+vOH1V2adturgZ2/sNIODg82srKyA3PcUU/cPTPfKUurLli3jH//4h/X/l19+yQMPPMDEiRN54okn+Mtf/sLKlSsv6Tnnzp3L119/TU1NDRkZGaSkpFj3ffzxx7z++use+adNm8bBgwepqalh//793HbbbR73G4bBsmXLKCgooLq6mg8++IChQ4d65ElOTub999/n7NmzlJaWkp6ezg9/+MNLKreIiIi/6Mz2uysuhQJQV1fH9OnTOXz4MB988AH9+/dv8hznz58nKyvL2vbhhx/idDo9fjuIiIgEiq44/hYREZGuFwht+Jo1aygrK2PhwoXtfkxoaCi9e/f2uMGFS5rabLZm03a7vV1pwzCapIOCgpqkDcNokgaapO12e5O0zWZrV1ox+U5MhmFQV1eH6x8bpmG7kMaw8vhsTA3PYXM6sTfE4ZF2OC7kaaFu6uvrrVhNwwYN74ETw1rCuitjcjqdOBteH8Ow6sDkQt0E4r6nmDovpvbySsf43r17+f73v2/9v2XLFlJSUnjttdeYP38+L730Em+++aY3iiYiIiIt6Oz2e/78+bz22mts3LiR3NxcHnnkESoqKpg9ezYAM2fO9Dh4fuyxx9ixYwfPP/88Bw4c4KmnniIzM5O5c+cCrk7xqVOnkpmZyRtvvIHD4aCgoICCggJqa2sBSEhIYNKkScyZM4fPP/+cTz/9lLlz53LPPfcQGxvbGW+TiIiIT9Hxt4iIiH/qzDY8IiICu91OYWGhx/bCwkKio6ObfUx0dHSr+d1/W8vz4Ycfkp6eTmhoKEFBQXzzm98EXBPOZs2a1a6yi4iIdCavdIwXFxcTFRVl/f/JJ594zLS+6aabOHHihDeKJiIiIi3o7Pb77rvvZtWqVSxZsoSkpCT27t3Ljh07rNfIy8vj1KlTVv5x48axefNm1q9fT2JiIm+99Rbbt29n+PDhAJw8eZJ33nmHf/3rXyQlJRETE2Pddu/ebT3PG2+8wbBhw/j+97/Pbbfdxvjx41m/fv1lvy8iIiK+TMffIiIi/qkz2/CuWLUtLi6O6OhojzylpaVkZGRYeV566SVycnLYu3cve/fu5b333gNg69at/Pa3v21X2UVERDpTkDdeNCoqimPHjjFw4EBqa2vJzs7mN7/5jXV/WVkZwcHB3iiaiIiItKAr2u+5c+daM74v9vHHHzfZNm3aNKZNm9Zs/sGDB2OaZpuvefXVV7N58+ZLKqeIiIi/0vG3iIiIf+rsNnz+/PnMmjWL5ORkxowZw+rVq5us2jZgwABrefbHHnuMCRMm8Pzzz3P77bezZcsWMjMzrYHlhmEwb948VqxYQXx8PHFxcSxevJjY2FimTJkCwKBBgzzK0KtXLwCGDBnCNddcc9nvjYiIyOXySsf4bbfdxhNPPMEzzzzD9u3b6dGjB9/5znes+/ft28eQIUO8UTQRERFpgdpvERER/6P2W0RExD91dht+9913c+bMGZYsWUJBQQFJSUlNVm1zX78VLqzatmjRIp588kni4+M9Vm0DWLBgARUVFTz44IOcP3+e8ePHs2PHDsLCwjrhHRAREel8XukYX758OT/+8Y+ZMGECvXr14vXXXyckJMS6f8OGDfzgBz/wRtFERESkBWq/RURE/I/abxEREf/UFW14Z67aBq5Z48uWLWPZsmXtev32rvQmIiLSVbzSMR4REcH/+3//j5KSEnr16oXdbve4f9u2bVx11VXeKJqIiIi0QO23iIiI/1H7LSIi4p/UhouIiHQ+r3SM//SnP21Xvg0bNnRxSURERKS91H6LiIj4H7XfIiIi/kltuIiISOfzSsf466+/zrXXXsvIkSO1dIqIiIifUPstIiLif9R+i4iI+Ce14SIiIp3PKx3jjzzyCP/1X//FsWPHmD17Nj/5yU+4+uqrvVEUERERaSe13yIiIv5H7beIiIh/UhsuIiLS+WzeeNF169Zx6tQpFixYwF/+8hcGDhzI9OnTef/99zX6TURExEep/RYREfE/ar9FRET8k9pwERGRzueVjnGA0NBQZsyYwc6dO/nqq6/41re+xX/+538yePBgysvLvVUsERERaYXabxEREf+j9ltERMQ/qQ0XERHpXF7rGG/MZrNhGAamaeJwOLxdHBEREWkHtd8iIiL+R+23iIiIf1IbLiIi0nFe6xivqanhv/7rv/i3f/s3hg4dypdffsnatWvJy8ujV69e3iqWiIiItELtt4iIiP9R+y0iIuKf1IaLiIh0riBvvOh//ud/smXLFgYOHMhPf/pT/uu//ouIiAhvFEVERETaSe23iIiI/1H7LSIi4p/UhouIiHQ+r3SMp6WlMWjQIK677jo++eQTPvnkk2bzvf32291cMhEREWmJ2m8RERH/o/ZbRETEP6kNFxER6Xxe6RifOXMmhmF446VFRETkMqn9FhER8T9qv0VERPyT2nAREZHO55WO8ddff90bLysiIiIdoPZbRETE/3RF+71u3Tqee+45CgoKSExMZM2aNYwZM6bF/Nu2bWPx4sUcP36c+Ph4nnnmGW677TbrftM0Wbp0Ka+99hrnz5/n5ptv5pVXXiE+Pt7jed59912WLVvGvn37CAsLY8KECWzfvr3T4xMREfEFOgYXERHpfDZvF0BERERERERE/MPWrVuZP38+S5cuJTs7m8TERFJTUzl9+nSz+Xfv3s2MGTN44IEH2LNnD1OmTGHKlCns37/fyvPss8/y0ksvkZaWRkZGBj179iQ1NZXq6morz//9v/+X++67j9mzZ5OTk8Onn37Kf/zHf3R5vCIiIiIiIhI41DEuIiIiIiIiIu3ywgsvMGfOHGbPns0NN9xAWloaPXr0YMOGDc3mf/HFF5k0aRKPP/44CQkJLF++nFGjRrF27VrANVt89erVLFq0iMmTJzNixAg2bdpEfn6+NRu8vr6exx57jOeee46HH36YoUOHcsMNNzB9+vRWy1pTU0NpaanHDcDpdFp/m0s7HI52pU3TbJKur69vkjZNs0naHXvjtMPhaJJ2Op3tSismxdRpMTU8h9NmwxEc3DR9Udx+EVMg1pNi6tKYREREJHCpY1xERERERERE2lRbW0tWVhYTJ060ttlsNiZOnEh6enqzj0lPT/fID5CammrlP3bsGAUFBR55+vTpQ0pKipUnOzubkydPYrPZGDlyJDExMfzwhz/0mHXenJUrV9KnTx/rNnDgQACOHz8OwIkTJzhx4oRVjvz8fACOHj1KYWEhAIcOHaKoqAiA3NxciouLAdi/fz8lJSUA5OTkUF5eDsCePXuoqqoCIDMzk9raWhwOB5mZmTgcDmpra8nMzASgqqqKPXv2AFBeXk5OTg4AJSUlVmzFxcXk5uYCUFRUxKFDhwAoLCzk6NGjAOTn53Ps2DHFpJg6J6aG1ym+/npy773XFdOIERyaOtUVU1WV/8UUiPWkmLo0JhEREQlchqmhcF5TWlpKnz59KCkpoXfv3t4ujojvys6G0aNbvj8rC0aNavUp8vLyrIOgxiIiIhg0aFBHSyg+LDs7m9GjRzP3jQ8YkJBobT+Zm8PaeyeSlZXFqDb2H29SW+GbVC8i7dAJ7beIPwvEtiI/P58BAwawe/duxo4da21fsGABn3zyCRkZGU0eExISwsaNG5kxY4a17eWXX+Y3v/kNhYWF7N69m5tvvpn8/HxiYmKsPNOnT8cwDLZu3cqWLVuYMWMGgwYN4oUXXmDw4ME8//zz/P3vf+fQoUNcffXVzZa3pqaGmpoa6//S0lIGDhxIcXExffv2tWYM2mw2j7TD4cAwjDbTNpsNwzA80vX19djtdo80uGYiNk4HBQVZMyTdaafTid1u90g7nU5M02wz3VwcikkxXVZM2dnYk5Nx2myYdjv2ujrPdGYmZlKSf8UUiPWkmLosprKysoBrv/1dIP6mEt/T0vlD8JNziG0df0Orx+Dejt/bry/+71LaiqBuKpOIiNfk5eUxLCGBqsrKJveF9+jBgdxcdY6LiIiIiPgod0fHr3/9a+666y4A/vjHP3LNNdewbds2HnrooWYfFxoaSmhoaJPtNpvN4+/FaXdHzuWkg4KC2p02DMMj7X6exumWynipacWkmNodk2G4yuV0gruTsXHaMOAS4vaJmAKxnhRTl8YkIiIigUsd4yIS8IqKiqiqrGT6ileIjIu3tp8+dpg3Fz1CUVGROsZFRERERNoQERGB3W63lqZ1KywsJDo6utnHREdHt5rf/bewsNBjxnhhYSFJSUkA1vYbbrjBuj80NJTrrruOvLy8jgUlIiIiIiIiVwxdY1xErhiRcfEMSEi0bo07yUVEREREpHUhISGMHj2aXbt2WducTie7du3yWFq9sbFjx3rkB9i5c6eVPy4ujujoaI88paWlZGRkWHlGjx5NaGgoBw8etPLU1dVx/Phxrr322k6LT0RERERERAKbZoyLiIiIiIiISLvMnz+fWbNmkZyczJgxY1i9ejUVFRXMnj0bgJkzZzJgwABWrlwJwGOPPcaECRN4/vnnuf3229myZQuZmZmsX78ecC2fO2/ePFasWEF8fDxxcXEsXryY2NhYpkyZAkDv3r15+OGHWbp0KQMHDuTaa6/lueeeA2DatGnd/yaIiIiIiIiIX1LHuIiIiIiIiIi0y913382ZM2dYsmQJBQUFJCUlsWPHDqKiogDIy8vzuMbruHHj2Lx5M4sWLeLJJ58kPj6e7du3M3z4cCvPggULqKio4MEHH+T8+fOMHz+eHTt2EBYWZuV57rnnCAoK4r777qOqqoqUlBQ+/PBD+vXr133Bi4iIiIiIiF9Tx7iIiIiIiIiItNvcuXOZO3dus/d9/PHHTbZNmzat1ZndhmGwbNkyli1b1mKe4OBgVq1axapVqy65vCIiIiIiIiKga4yLiIiIiIiIiIiIiIiIiEiAU8e4iIiIiIiIiIiIiIiIiIgENHWMi4iIiIiIiIiIiIiIiIhIQAuYjvF169YxePBgwsLCSElJ4fPPP281/7Zt2xg2bBhhYWHceOONvPfeex73m6bJkiVLiImJITw8nIkTJ3L48OEmz/Puu++SkpJCeHg4/fr1Y8qUKZ0ZloiIiIiIiIiIiIiIiIiIdFBAdIxv3bqV+fPns3TpUrKzs0lMTCQ1NZXTp083m3/37t3MmDGDBx54gD179jBlyhSmTJnC/v37rTzPPvssL730EmlpaWRkZNCzZ09SU1Oprq628vzf//t/ue+++5g9ezY5OTl8+umn/Md//EeXxysiIiIiIiIiIiIiIiIiIu0XEB3jL7zwAnPmzGH27NnccMMNpKWl0aNHDzZs2NBs/hdffJFJkybx+OOPk5CQwPLlyxk1ahRr164FXLPFV69ezaJFi5g8eTIjRoxg06ZN5Ofns337dgDq6+t57LHHeO6553j44YcZOnQoN9xwA9OnT++usEVEREREREREREREREREpB38vmO8traWrKwsJk6caG2z2WxMnDiR9PT0Zh+Tnp7ukR8gNTXVyn/s2DEKCgo88vTp04eUlBQrT3Z2NidPnsRmszFy5EhiYmL44Q9/6DHr/GI1NTWUlpZ63ACcTqf1t7m0w+FoV9o0zSbp+vr6JmnTNJukgSZph8PRJO10OtuVVkyKqdNjstlwBAc3TdvtOBpep6U4TNPEbrcDYJhOMF3bbZjYbDbV0xUQk7u+MV03w+kqi2EYHvuJr8YUyDr7Uihvv/02P/jBD+jfvz+GYbB3794mz3HrrbdiGIbH7eGHH+7MsERERERERERERETEx/h9x3hRUREOh4OoqCiP7VFRURQUFDT7mIKCglbzu/+2luef//wnAE899RSLFi3ir3/9K/369ePWW2/l3Llzzb7uypUr6dOnj3UbOHAgAMePHwfgxIkTnDhxAnB1zufn5wNw9OhRCgsLATh06BBFRUUA5ObmUlxcDMD+/fspKSkBICcnh/LycgD27NlDVVUVAJmZmdTW1uJwOMjMzMThcFBbW0tmZiYAVVVV7NmzB4Dy8nJycnIAKCkpsTr8i4uLyc3NBVzv/aFDhwAoLCzk6NGjAOTn53Ps2DHFpJg6N6brryf33ntdMY0YwaGpU10xJSdztKys1ZjKy8u5+eabAbi6NJ9eVa6yDw6uZcSIEaqnAI/J6XQSEhLCjaHVGKYTu7OeAUUHAejfv7/1ne3LMQWqrrgUSkVFBePHj+eZZ55p9bXnzJnDqVOnrNuzzz7bqbGJiIiIiIiI+JrOHpxumiZLliwhJiaG8PBwJk6cyOHDhz3y3HnnnQwaNIiwsDBiYmK47777rHMlIiIi3c0w/Xw6Wn5+PgMGDGD37t2MHTvW2r5gwQI++eQTMjIymjwmJCSEjRs3MmPGDGvbyy+/zG9+8xsKCwvZvXs3N998M/n5+cTExFh5pk+fjmEYbN26lc2bN3Pvvffy6quv8uCDDwKuGeHXXHMNK1as4KGHHmryujU1NdTU1Fj/l5aWMnDgQIqLi+nbt681Y9Bms3mkHQ4HhmG0mbbZbBiG4ZGur6/Hbrd7pME1E7FxOigoyJoh6U47nU7sdrtH2ul0WrNvW0s3F4diUkyXHVNODs6bbsK027HX1eG02S6k7XbMjAzso0e3GEdWVhYpKSk8sul9rhl2IyaAYeNU7l7W3pfKF198QWJiouopQGPKyckhOTmZn7+xk5hhiYBr5YB/HdzPup/8G59//jnJyck+G1NZWRl9+vShpKSE3r17X9y0+LWUlBRuuukm61ImTqeTgQMH8rOf/YwnnniiSf67776biooK/vrXv1rbvv3tb5OUlERaWppH3uPHjxMXF8eePXtISkryuO/WW28lKSmJ1atXt7usasMVk2K6jJiys7EnJ3u2243TmZmYSUn+FVMg1pNi6rKYArkN91elpaWqE5G2ZGfD6NEt35+VBaNGdV95RLpZILcVW7duZebMmaSlpZGSksLq1avZtm0bBw8eJDIyskn+3bt3c8stt7By5UruuOMONm/ezDPPPEN2djbDhw8H4JlnnmHlypVs3LiRuLg4Fi9ezJdffslXX31FWFgYAL/73e8YO3YsMTExnDx5kl/+8pfW87dHINeJ+I7s7GxGjx7N3Dc+YEBCosd9J3NzWHvvRLKyshjlq21gW+03tNqGezt+b7+++L9LaSv8fsZ4REQEdrvdmoXnVlhYSHR0dLOPiY6ObjW/+29redwd5jfccIN1f2hoKNdddx15eXnNvm5oaCi9e/f2uAHWUs42m63ZtN1ub1faMIwm6aCgoCZpwzCapIEmaWvp6UZpm83WrrRiUkydHpPTib2urmna4cDe8DotxeE+QQlgGjYwXNudXFhGW/UU2DG56xvDdTNtrrKYpumxn/hqTIGoKy6FcineeOMNIiIiGD58OAsXLqSysrLV/Fr1RTEppsuIqeF1Wlz1parK/2IKxHpSTFr1RURERK4IL7zwAnPmzGH27NnccMMNpKWl0aNHDzZs2NBs/hdffJFJkybx+OOPk5CQwPLlyxk1apQ1uN00TVavXs2iRYuYPHkyI0aMYNOmTeTn57N9+3breX7xi1/w7W9/m2uvvZZx48bxxBNP8Nlnn1HXcG5PRESkO/n9jHFwzTgbM2YMa9asAVwzzgYNGsTcuXNbnHFWWVnJX/7yF2vbuHHjGDFiBGlpaZimSWxsLL/85S/5//6//w9wjTaIjIzk9ddf55577rH+X7duHQ888AAAdXV1XHPNNSxfvtyaRd4ajXYTaacOjlhvacSZRptdGfy9/gO1reiKFV8aa23G+Pr167n22muJjY1l3759/OpXv2LMmDG8/fbbLZZXM8YVk2LSjPGArSfF1GUxaca47wnU31UinUozxuUKF6htRW1tLT169OCtt95iypQp1vZZs2Zx/vx5/vu//7vJYwYNGsT8+fOZN2+etW3p0qVs376dnJwc/vnPfzJkyJAmx90TJkwgKSmJF198sclznjt3jkceeYSTJ0/yv//7v82WVcffiskbMWVlZTF27Fgeev1vDBh2IwYNE6xMJ/kH9rHm3n8jMzOTkSNH+mZMbR1/21tfdXXv3r2uFVc3/o3YhCQM09mtq67u27ePm266ibl/ep+YhCQwTQxMTMNGfu5e0u6/jc8++4ykpKSA2/cC8fPk68fffj9jHGD+/Pm89tprbNy4kdzcXB555BEqKiqYPXs2ADNnzmThwoVW/scee4wdO3bw/PPPc+DAAZ566ikyMzOZO3cu4JopOG/ePFasWME777zDl19+ycyZM4mNjbV+OPTu3ZuHH36YpUuX8ve//52DBw/yyCOPADBt2rTufQNERESk3R588EFSU1O58cYbuffee9m0aRN//vOfrdmDzdGqL4pJMV1GTA3P0eKqLxfF7RcxBWI9KaYujUlErkx5eXlkZ2c3ubW0wqCISFcrKirC4XAQFRXlsT0qKoqCgoJmH1NQUNBqfvff9jznr371K3r27En//v3Jy8trtiPeTSu2KSZvxFRTU8PUhtXNelUVc3Wpq7y9K89yTZDrGLaiosJ3Y2prxbbkZI6WlbVaT6mpqUTa6wG4ujSfXlWu5xwcXMuIESO6PKaYmBiGhbgGxYTVVRBV7Cpjb5uTe90xBeC+p5i6f8W2gJgxDrB27Vqee+45CgoKSEpK4qWXXiIlJQVwXUt08ODBvP7661b+bdu2sWjRIo4fP058fDzPPvsst912m3W/aZosXbqU9evXc/78ecaPH8/LL7/M0KFDrTx1dXUsXLiQP/3pT1RVVVnXZvnWt77VrjIH6ghEkU6nGePSAf5e/4HaVnTFaPXGWpsxfrGKigp69erFjh07SE1NbVf5A7VeRDqVZpzJFU5the9RnUh3yMvLY1hCAlXNXKonvEcPDuTmMmjQIC+UrJ3UfssVLlDbiq5YtW337t3cfPPN5OfnW5cdBZg+fTqGYbB161ZrW1FREefOnePrr7/mN7/5DX369OGvf/1rs4MJNWNcMWnGuGaMa8a4YrrUmC5lxnhQq/f6kblz51ozvi/28ccfN9k2bdq0Vmd2G4bBsmXLWLZsWYt5goODWbVqFatWrbrk8oqIiFzJQkJCGD16NLt27bI6xp1OJ7t27WqxPR87diy7du3y6BjfuXOnx0H95di7dy+Ax4G8iIiIiMjlKCoqoqqykukrXiEyLt7afvrYYd5c9AhFRUW+3TEuIgEpIiICu93e5DJkhYWFREdHN/uY6OjoVvO7/xYWFnocTxcWFjYZoB4REUFERARDhw4lISGBgQMH8tlnnzV7PB8aGkpoaGiT7Y1X9rl4G2B15FxO2r0SUXvS7V25qLkyXmpaMXVfTIZhXLjuvWHDmk1q2DAxrDzN7Yc+EVOjFdtwdzI2Tjsc4M7TQt3U19dbsZrGhe1ODKvjsitjcjqdOBteH8O4UBYu1E0g7nuKqfNiaq+AWEpdRERE/E9nXwoFXNcr27t3L1999RUABw8eZO/evdYybkePHmX58uVkZWVx/Phx3nnnHWbOnMktt9xiLQslIiIiItJRkXHxDEhItG6NO8lFRLpb48Hpbu7B6S0NNncPTm+s8eD0uLg4oqOjPfKUlpaSkZHR6gB2dwdb41nhIiIi3SVgZoyLiIiIf7n77rs5c+YMS5YssS6FsmPHDuv6ZHl5eR4jBseNG8fmzZtZtGgRTz75JPHx8Wzfvp3hw4dbed555x2rYx3gnnvuAVxLrj/11FOEhITwwQcfsHr1aioqKhg4cCB33XUXixYt6qaoRURERERERLrf/PnzmTVrFsnJyYwZM8Y6Lm48OH3AgAGsXLkScA1OnzBhAs8//zy33347W7ZsITMzk/Xr1wOumYLz5s1jxYoVxMfHExcXx+LFi4mNjbVWhsvIyOCLL75g/Pjx9OvXj6NHj7J48WKGDBnS4dXfRERELoc6xkVERMRrOvtSKPfffz/3339/i/cPHDiQTz755FKLKSIiIiIiIuLXumJw+oIFC6ioqODBBx/k/PnzjB8/nh07dhAWFgZAjx49ePvtt1m6dCkVFRXExMQwadIkFi1a1Oxy6SIiIl1NHeMiIiIiIiIiIiIiIgGuswenG4bBsmXLWLZsWbP333jjjXz44YeXVVYREZGuoGuMi4iIiIiIiIiIiIiIiIhIQFPHuIiIiIiIiIiIiIiIiIiIBDR1jIuIiIiIiIiIiIiIiIiISEBTx7iIiIiIiIiIiIiIiIiIiAQ0dYyLiIiIiIiIiIiIiIiIiEhAC/J2AUREREREREREREREREREAlVeXh5FRUVNtkdERDBo0CAvlOjKpI5xEREREREREREREREREekSLXUKA5w6daqbS9P98vLyGJaQQFVlZZP7wnv04EBurjrHu4k6xkVEREREREREpN0020VERERE2qu1TmGA0LCwbi5R9ysqKqKqspLpK14hMi7e2n762GHeXPQIRUVF+h3dTdQxLiIiIiIiIiIi7aLZLiIiIiJyKVrqFIYLHcNXisi4eAYkJHq7GFc0dYyLiIiIiIiIiEi7aLaLiIiIiFwOdQqLL1DHuIiIiIiIiIiIXBKd2BQREREREX9j83YBREREREREREREREREREREupJmjItcAfLy8igqKmr2voiICC1zJyIiIiIiIiIiIiIiIgFNHeMiAS4vL49hCQlUVVY2e394jx4cyM1V57iIiIiIiIiIiIiIiIgELHWMiwS4oqIiqiormb7iFSLj4j3uO33sMG8ueoSioiJ1jIuIiIiIiIiIiIiIiEjAUse4yBUiMi6eAQmJ3i6GiIiIiIiIiIiIiIiISLezebsAIiIiIiIiIiIiIiIiIiIiXUkd4yIiIiIiIiJySdatW8fgwYMJCwsjJSWFzz//vNX827ZtY9iwYYSFhXHjjTfy3nvvedxvmiZLliwhJiaG8PBwJk6cyOHDh5t9rpqaGpKSkjAMg71793ZWSCIiIiIiInKZ8vLyyM7ObnLLy8vzdtE8qGNcRERERERERNpt69atzJ8/n6VLl5KdnU1iYiKpqamcPn262fy7d+9mxowZPPDAA+zZs4cpU6YwZcoU9u/fb+V59tlneemll0hLSyMjI4OePXuSmppKdXV1k+dbsGABsbGxXRafiIiIiIiItF9eXh7DEhIYPXp0k9uwhASf6hxXx7iIiIiIiIiItNsLL7zAnDlzmD17NjfccANpaWn06NGDDRs2NJv/xRdfZNKkSTz++OMkJCSwfPlyRo0axdq1awHXbPHVq1ezaNEiJk+ezIgRI9i0aRP5+fls377d47n+9re/8fe//51Vq1Z1dZgiIiIiIiLSDkVFRVRVVjJ9xSvMfeMD6zZ9xStUVVZSVFTk7SJa1DEuIiIiIiIiIu1SW1tLVlYWEydOtLbZbDYmTpxIenp6s49JT0/3yA+Qmppq5T927BgFBQUeefr06UNKSorHcxYWFjJnzhz+9Kc/0aNHjzbLWlNTQ2lpqccNwOl0Wn+bSzscjnalTdNskq6vr2+SNk2zSRpoknY4HE3STqezXenujgnAhgmm62Y4XWUxDMN6Pn+LqbPqyTRNgoODcf3jxDBdZTEwCQoK8v2YGp7DabPhaIjDI31R3P5aT4G47ymmzotJRERELk9kXDwDEhKtW2RcvLeL1IQ6xkVERERERESkXYqKinA4HERFRXlsj4qKoqCgoNnHFBQUtJrf/be1PKZpcv/99/Pwww+TnJzcrrKuXLmSPn36WLeBAwcCcPz4cQBOnDjBiRMnAFfnfH5+PgBHjx6lsLAQgEOHDlmzG3JzcykuLgZg//79lJSUAJCTk0N5eTkAe/bsoaqqCoDMzExqa2txOBxkZmbicDiora0lMzMTgKqqKvbs2QNAeXk5OTk5AJSUlFjLzBcXF5Obmwu43vtDhw4BrkECR48eBSA/P59jx451W0xOp5OQkBBuDK3GMJ3YnfUMKDoIQP/+/Tl37pzfxdSZ9VRTU8PUqVMB6FVVzNWlrvJG2utJTU31/ZgaXqf4+uvJvfdeVz2NGMGhhpgKq6oCop4Ccd9TTJ0Xk4iIiASuIG8XQEREfF9eXl6zy51EREQwaNAgL5RIRERERK4ka9asoaysjIULF7b7MQsXLmT+/PnW/6WlpQwcOJDBgwcDWB3lAHFxcVZ6yJAhGIYBwNChQ610QkKClR4+fDg2m2uuQWJiopUeOXIkdrsdgOTk5CZpu91udeyHh4czcuRIAHr16kViYiLgmi0/fPhwAPr160ffvn0B12/v/v37A65BA5GRkQAe11vvjphycnKora3ly5owYgwbDsPGyYjr4ex+zp49y9VXX+13MXVmPYWGhvLWW2/x0B0PUB7ej4rwfgCcdgTx/vvvs2zZMt+OqZ+rvP0OHqTvkSOuetq3j/7/+IernsLDiRwyxO/rKRD3PcXUOTGVlZUhIiIigUsd4yIi0qq8vDyGJSRQVVnZ5L7wHj04kJurznERERGRK0RERAR2u92ahedWWFhIdHR0s4+Jjo5uNb/7b2FhITExMR55kpKSAPjwww9JT08nNDTU43mSk5O599572bhxY5PXDQ0NbZIfsDpB3H8vTrs7dS4n7V4quz1pwzA80u7naZxuqYyXmu7MmNwdSk4MaEibhiu/aZrW6/pTTK2lL7WeDMOgrq6u4R8b7oWZTQxrCWmfjqmhTm1OJzQsN+2RNgy4hLr0iZiukH1PMXVeTCLin1qa2AOa3CMiF6hjXEREWlVUVERVZSXTV7zicU2Q08cO8+aiRygqKtIPSxEREZErREhICKNHj2bXrl1MmTIFcF3TddeuXcydO7fZx4wdO5Zdu3Yxb948a9vOnTsZO3Ys4JrhFx0dza5du6yO8NLSUjIyMnjkkUcAeOmll1ixYoX1+Pz8fFJTU9m6dSspKSmdH6iIiIiI+I3WJvaAJvdIYNCqrp1DHeMiItIukXHxDEhI9HYxRERERMTL5s+fz6xZs0hOTmbMmDGsXr2aiooKZs+eDcDMmTMZMGAAK1euBOCxxx5jwoQJPP/889x+++1s2bKFzMxM1q9fD7hmCs6bN48VK1YQHx9PXFwcixcvJjY21up8v/hET69evQDXUrnXXHNNN0UuIiIiIr6opYk9oMk94uLvKwpoVdfOo45xEREREREREWm3u+++mzNnzrBkyRIKCgpISkpix44dREVFAa6TNo2Xsx03bhybN29m0aJFPPnkk8THx7N9+3brerIACxYsoKKiggcffJDz588zfvx4duzYQVhYWLfHJyIiIiL+SRN7pDmBsKKAVnXtPLa2s/iHdevWMXjwYMLCwkhJSeHzzz9vNf+2bdsYNmwYYWFh3Hjjjbz33nse95umyZIlS4iJiSE8PJyJEydy+PDhZp+rpqaGpKQkDMNg7969nRWSiIiIiIiIiE+aO3cuX3/9NTU1NWRkZHgsZ/7xxx/z+uuve+SfNm0aBw8epKamhv3793Pbbbd53G8YBsuWLaOgoIDq6mo++OADhg4d2uLrDx48GNM0raXXRUREREREmtO4U3nuGx943KaveIWqysoWZ5P7GvfgD/ft4hUSpG0B0TG+detW5s+fz9KlS8nOziYxMZHU1FROnz7dbP7du3czY8YMHnjgAfbs2cOUKVOYMmUK+/fvt/I8++yzvPTSS6SlpZGRkUHPnj1JTU2lurq6yfMtWLCA2NjYLotPREQkUHX2wLa3336bH/zgB/Tv37/FAWvV1dU8+uij9O/fn169enHXXXdRWFjYmWGJiIiIiIiIiIiID7m4U1kdy1emgOgYf+GFF5gzZw6zZ8/mhhtuIC0tjR49erBhw4Zm87/44otMmjSJxx9/nISEBJYvX86oUaNYu3Yt4Jotvnr1ahYtWsTkyZMZMWIEmzZtIj8/n+3bt3s819/+9jf+/ve/s2rVqjbLWVNTQ2lpqccNwOl0Wn+bSzscjnalTdNskq6vr2+SNk2zSdodd+O0w+FoknY6ne1KKybfick0TYKDg3H948QwnRfSmFYen4/JZsPREIdH2m7H0fA6LdWNaZrY7XYAV/wN74EN01ri0dv15Mv7nvs5wMRwOhqSJrZG+4+vx+Sub0zXzR2HYRge+4mv1lOg6oqBbRUVFYwfP55nnnmmxdf9xS9+wV/+8he2bdvGJ598Qn5+Pj/+8Y87PT4RERERERERX9Ldq64eP36cBx54gLi4OMLDwxkyZAhLly6ltra2S+ITERFpi993jNfW1pKVlcXEiROtbTabjYkTJ5Kent7sY9LT0z3yA6Smplr5jx07RkFBgUeePn36kJKS4vGchYWFzJkzhz/96U/06NGjzbKuXLmSPn36WLeBAwcCrh8IACdOnODEiRNWGfLz8wE4evSoNZPt0KFD1pIOubm5FBcXA7B//35KSkoAyMnJoby8HIA9e/ZQVVUFQGZmJrW1tTgcDjIzM3E4HNTW1pKZmQlAVVUVe/bsAaC8vJycnBwASkpKrE6H4uJicnNzAdfyE4cOHbLei6NHjwKQn5/PsWPHFJOPxFRTU8PUqVMB6FVVzNWlrvL2rjzLNUF1gKsjyedjuv56cu+911VPI0ZwqCGmwuRkjpaVtVpP5eXl3HzzzQBcXZpPrypX2QcH1zJixAifqCdf3vfOnj0LQKhhEnvOdXATUl/FsJAaAOrq6nw6JqfTSUhICDeGVmOYTuzOegYUHQSgf//+nDt3zufrKVB19sA2gPvuu48lS5Y0aefdSkpK+MMf/sALL7zA9773PUaPHs0f//hHdu/ezWeffdYlcYqIiIiIiIh4mzdWXT1w4ABOp5NXX32Vf/zjH/zud78jLS2NJ598sltiFhERuViQtwvQUUVFRTgcDqKiojy2R0VFceDAgWYfU1BQ0Gz+goIC6373tpbymKbJ/fffz8MPP0xycrLVud2ahQsXMn/+fOv/0tJSBg4cyODBgwGsjnKAuLg4Kz1kyBAMwwBg6NChVjohIcFKDx8+3Jr5mpiYaKVHjhxpzZRNTk5ukrbb7SQnJwMQHh7OyJEjAejVqxeJiYmAa1DA8OHDAejXrx99+/YFICIigv79+1vvTWRkJIDHsvKKyfsxhYaG8tZbb/HQHQ9QHt6PivB+AJT26E9+/UkAevbsacXlkzHl5NDv4EH6Hjniqqd9++j/j3+46ikzk8irrmq1nnr16sWnn37KiIfgXO9Y3HNwj9eFsG/fPp+oJ1/e99zlqjEN8q92LS1TGxTO17WhAAQHB/t0TDk5OdTW1vJlTRgxhg2HYeNkxPVwdj9nz57l6quv9ul6KmsY+BFo3APbFi5caG1rz8C2xu0ouAa2XbyaS2uysrKoq6vz6DgfNmwYgwYNIj09nW9/+9vNPq6mpoaamhrr/+ZWfXHH0DjtcDgwDKPNtM1mwzAMj3R9fT12u90jDa7VBBqng4KCrFUO3Gmn04ndbvdIO51OawWN1tLNxaGYFNNlxWSa2HGt9GLa7djr6jzTponZ8Jx+E1Mg1pNi6rKYRERERHxJ48HpAGlpabz77rts2LCBJ554okn+xoPTAZYvX87OnTtZu3YtaWlpTVZdBdi0aRNRUVFs376de+65h0mTJjFp0iTrOa+77joOHjzIK6+80q4VWEVERDqbjtYv05o1aygrK/M4od+W0NBQevfu7XEDrJMmNput2bTdbm9X2t2x0jgdFBTUJG0YRpM00CRtLT3dKG2z2dqVVky+E5NhGNTVuWaGY9gwDduFNIaVx+djcjqxN8ThkXY4sDe8Tkt14z5BCbjib3gPnFxYRtvb9eTL+96FE7sGps3ekDRwNtp/fD0md31juG7uOEzT9NhPfLWeAlFrA9vcg9Au1tbAtvYoKCggJCTEGuzQ3ufRqi+KSTFdRkwNr9Piqi9VVf4XUyDWk2LSqi8iIiIS8Ly56urFSkpKrEkKzdHlSBXT5cYEWJd+bHwpRTAJCQlpNSa/vxyp+1Kjtsu/HGlQUJAVa1dcjtRVB56XuWx8uU6bzeZZfw2vb3Chbjqy7zWN78I+0zi+rqynC/tY++JrHIf79Q1Mq26MFvZPb3xHtBafu5/EVy5H6vcd4xEREdjtdutEhVthYSHR0dHNPiY6OrrV/O6/reX58MMPSU9PJzQ0lKCgIL75zW8CrtmJs2bN6nhgIiIi4jMWLlxISUmJdXN3nDRe9aXxyhvuVQSGDBlideYPHTqUiIgIwLVSQL9+rhU8hg8fTp8+fQDXSgG9evUCXKsfhIeHA67fFyEhIdbKFHa7nZCQkEtepSIhIQFw/X4aOnQo4BoUMGTIEMC1+oF7pQPFpJg6HFPD6/Q7eJCEN95wxbRvH0PfessVU8M1Bv0qpkCsJ8XUpTGJiIiI+IKuGJzenlVXL3bkyBHWrFnDQw891GJZNTBdMV1OTKZpctVVV3FjqGsZ/yBHrXVJyB6GycMPP9xqTH5/OdK2Bqa343KkqampRNpdnZ+dfTlS0zR5/PHHsYHHZS6DHLV8K9S1QmNMTIx16c6wugqiil1l7G1zcq87pg7se3feeScRdlcnbv+SE/SsPg/AkJBarr/++i6vp7q6On76058CEF5TxjfOfw1AP7vD2vdai6miogKAa4Lq6F151qond0ylpaVe/Y6ora216qln9Xn6l7jqIMLu4M4772x3PXXHwHS/X0o9JCSE0aNHs2vXLqZMmQK4Rhfs2rWLuXPnNvuYsWPHsmvXLubNm2dt27lzJ2PHjgVcJ0Gio6PZtWsXSUlJgGunysjI4JFHHgHgpZdeYsWKFdbj8/PzSU1NZevWraSkpHR+oCIiIgGkKwa2tUd0dDS1tbWcP3/eY9Z4W88TGhpKaGhok+2NVwe4eBtgrSpwOWn3aMr2pNu7SkVzZbzUtGJSTO2Oyb2ii9MJ7mWpG6cNAy4hbp+IKRDrSTF1aUwiIiIi4nLy5EkmTZrEtGnTmDNnTov5dDlSxXQ5MeXk5FBWVua6lCJQbw+xLglZaRqsT0tj1qxZgXs50kYD0y/ncqRnz57l/fff57r/mEcsnX85UsMweO6553jwj7fisAW5LnPZUE//qHGdbzt16hQHakOJAaqDe1LYz/UelzptvPHGG/zsZz+77H3v9OnTvPPOOwy46xFigbN9Blqr6R6tDeHgwYNdXk/BwcFs2LCBh26ZRlXoVVSHugZTFzvsvPXWW/zyl79sNSZ3B/G/6oOJ7eF6D871jqUo37W9d+/eHoO4u/s7IiQkhDfeeIOH/u0nVIT1pTLMNXC8yGHnnXfe4de//rXPXI7U7zvGAebPn8+sWbNITk5mzJgxrF69moqKCut6KTNnzmTAgAGsXLkSgMcee4wJEybw/PPPc/vtt7NlyxYyMzNZv3494DqZMm/ePFasWEF8fDxxcXEsXryY2NhYq/N90KBBHmVwzwgYMmQI11xzTTdFLiIi4p+6YmBbe4wePZrg4GB27drFXXfdBcDBgwfJy8u7pOcRERERERER8RddvepqTEyMRx73ZDO3/Px8vvvd7zJu3DjrHHxLNDBdMV1OTB6XUnQVHtNwP9agtra21ZiaXI7UuqPly5F2dUwXpzs0MN3hcF1ikpbrpr6+3orVuhwrTS9HejkxGYa7DgzPuml0uU6n0+lZf+6ycKFuOrLvdSS+zqqnC/vYpcfn3sdNDOtSsWYL+6c3viNai8+9DLuvDEz3+6XUAe6++25WrVrFkiVLSEpKYu/evezYscNaxiUvL49Tp05Z+ceNG8fmzZtZv349iYmJvPXWW2zfvt0a2QCwYMECfvazn/Hggw9y0003UV5ezo4dOwgLC+v2+ERERALR/Pnzee2119i4cSO5ubk88sgjTQa2LVy40Mr/2GOPsWPHDp5//nkOHDjAU089RWZmpkdH+rlz59i7dy9fffUV4Or03rt3r7WMW58+fXjggQeYP38+H330EVlZWcyePZuxY8fy7W9/uxujFxEREREREekejQenu7kHp7c0SNw9OL2xllZddXOvutr4OU+ePMmtt97K6NGj+eMf/+jRASIiItLdAmLGOMDcuXNbnGH28ccfN9k2bdo0pk2b1uLzGYbBsmXLWLZsWbtef/DgwZd8gXcREZEr2d13382ZM2dYsmQJBQUFJCUlNRnY1viA2T2wbdGiRTz55JPEx8c3Gdj2zjvvWB3rAPfccw8AS5cu5amnngLgd7/7HTabjbvuuouamhpSU1N5+eWXuyFiEREREREREe/wxqqr7k7xa6+9llWrVnHmzBmrPJdyWTQREZHOEjAd4yIiIuJ/Ontg2/3338/999/f6muGhYWxbt061q1bdylFFREREREREfFbXTE4fcGCBVRUVPDggw9y/vx5xo8f77Hq6s6dOzly5AhHjhxpcvlRTTITERFvUMe4iIiIiIiIiIiIiEiA6+5VV9szeF1ERKQ76YIeIiIiIiIiIiIiIiIiIiIS0NQxLiIiIiIiIiIiIiIiIiIiAU1LqYuIiIiIiIiIiIiIiIj4qLy8PIqKipq9L+bUKWK6uTwi/kod4yIiIiIiIiIiIiIiIiI+KC8vj2EJCVRVVjZ7/9iwMHZ3c5lE/JU6xkVERERERERERERERER8UFFREVWVlUxf8QqRcfEe950+dpjDix7xUslE/I86xkVERERERERERERERER8WGRcPAMSEptsP+yFsoj4K3WMi0i7tHQNk4iICAYNGuSFEomIiIiIiFyZdHwmIiIiIiJy6dQxLiJtau0aJuE9enAgN1cnX0RERERERLqBjs9EREREREQujzrGRaRNLV3D5PSxw7y56BGKiop04kVERERERKQb6PhMRERERKRznTp1iuzs7Gbv06pMgUUd4yLSbi1dw0RERERERES6l47PREREREQ6x9Sp06iurmr2Pq3KFFjUMS4iIiIiIiIiIiKdIi8vj6Kiombv04wrERER8UXV1VVNVmQCrcoUiNQxLiIiIiIiIiIiIh2Wl5fHsIQEqiorm71fM65ERETEV2lFpiuDOsZFRERERERERESkw4qKiqiqrNSMKxERERHxSeoYFxERERERERERkU6jGVciIiIi4ots3i6AiIiIiIiIiIiIiIiIiIhIV1LHuIiIiIiIiIiIiIiIiIiIBDQtpS4iIiIi4qPy8vIoKipqsj0iIkLX5hQREblC6feBiIiIiMjlUce4iIhIG3TiSUS8IS8vj2EJCVRVVja5L7xHDw7k5uo7SERE5Aqj3wciIiIivqm1c8jiO9QxLiIi0gqdeBIRbykqKqKqspLpK14hMi7e2n762GHeXPQIRUVF+v4RERG5wuj3gYiI92jihIi0pK1zyNvefNMLpZLmqGNcRESkFTrxJCLeFhkXz4CExGbv04kZERGRK1Nrvw9ERKTzaeKEiLSmrXPI58+f917hxIM6xkVERNpBJ55ExNecOnWK8d/5jk7MiIiIiIiIdDFNnBCR9tA5ZN+njnERERERET90/vx5nZgRERERERHpRur0EhHxb+oYFxERERHxYzoxIyIiIiIiIiIi0jabtwsgIiIiIhKo8vLyyM7ObnLLy8vzdtFERDpk3bp1DB48mLCwMFJSUvj8889bzb9t2zaGDRtGWFgYN954I++9957H/aZpsmTJEmJiYggPD2fixIkcPnzYuv/48eM88MADxMXFER4ezpAhQ1i6dCm1tbVdEp9IV9LvAxERERER79CMcRERERGRLpCXl8ewhARdA1xEAs7WrVuZP38+aWlppKSksHr1alJTUzl48CCRkZFN8u/evZsZM2awcuVK7rjjDjZv3syUKVPIzs5m+PDhADz77LO89NJLbNy4kbi4OBYvXkxqaipfffUVYWFhHDhwAKfTyauvvso3v/lN9u/fz5w5c6ioqGDVqlXd/RaIXLZTp04x/jvf0e8DEREREREvUMe4iIiIiEgXKCoq0jXARSQgvfDCC8yZM4fZs2cDkJaWxrvvvsuGDRt44oknmuR/8cUXmTRpEo8//jgAy5cvZ+fOnaxdu5a0tDRM02T16tUsWrSIyZMnA7Bp0yaioqLYvn0799xzD5MmTWLSpEnWc1533XUcPHiQV155RR3j4lfOnz+v3wciIiIiIl6ijnEREfG6vLw8ioqKmmyPiIjQSSGRLqbPX9fTNcBFJJDU1taSlZXFwoULrW02m42JEyeSnp7e7GPS09OZP3++x7bU1FS2b98OwLFjxygoKGDixInW/X369CElJYX09HTuueeeZp+3pKSEq6++usWy1tTUUFNTY/1fWloKgNPp9Phrs9k80g6HA8Mw2kzbbDYMw/BI19fXY7fbPdIADofDIx0UFIRpmh5pp9OJ3W73SDudTkzT9EgDrtfAlcZ0WjG6n+vi+DozJvfz2zChIW00lMEwDOt1LyWm5tLN1Y0/1JNpmgQHB1t1YwCmYcPAJCgoyKqnqLhvEpuQ2GL9tRSTaZrYbK4rIxpOB6ZhA8PAholhGAAdi8k0sQNOmw3TbsdeV+eZNk3Mhudsrm7ccbj3T8N0ulKGDRsXyu7tegrEfU8xdU5MIiIiEtjU2ouIiFe5lxoePXp0k9uwhARdZ0+kC+nzJyIil6qoqAiHw0FUVJTH9qioKAoKCpp9TEFBQav53X8v5TmPHDnCmjVreOihh1os68qVK+nTp491GzhwIOC6XjnAiRMnOHHiBODqnM/Pzwfg6NGjFBYWAnDo0CFrAFlubi7FxcUA7N+/n5KSEgBycnIoLy8HYM+ePVRVVQGQmZlJbW0tDoeDzMxMHA4HtbW1ZGZmAlBVVcWePXsAKC8vJycnB3B1+O/fvx+A4uJicnNzAdd7f+jQIQCSk5MZFFwHQO/Ks/Qrd71Pt956KxUVFV0ak9PpJCQkhBtDqzFMJ3ZnPQOKDgLQv39/zp07d1kxFRYWcvToUQDy8/M5duyYX9ZTTU0NU6dOBaBXVTFXl7rKG2mvJzU11aqnmKB6APqVF9C78iwAd955p1WulmIqLi5m8ODBAEQX/5OQelf+b4XW0L9//47H5H6d668n9957XfU0YgSHGmIqrKpqs55SU1OJtLviu7o0n15VruccHFzLiBEjfKKeAnHfU0ydF5OIiDR16tQpsrOzm73p/JF/yMvLU/0RQDPG161bx3PPPUdBQQGJiYmsWbOGMWPGtJh/27ZtLF68mOPHjxMfH88zzzzDbbfdZt1vmiZLly7ltdde4/z589x888288sorxMe7lrk6fvw4y5cv58MPP6SgoIDY2Fh+8pOf8Otf/5qQkJAuj1dEJFBoqWER79HnT0RE/NHJkyeZNGkS06ZNY86cOS3mW7hwocdM9dLSUgYOHGh1Kro7ygHi4uKs9JAhQ6yZt0OHDrXSCQkJVnr48OHWzMLExEQrPXLkSGuGZHJycpO03W4nOTkZgPDwcEaOHAlAr169SEx0rS7Sp08f69rr/fr1o2/fvoBrNZf+/fuTk5NDZmYmY+qCiQVKe/RvKPkZPv74Y55++ukujSknJ4fa2lq+rAkjxrDhMGycjLgezu7n7Nmz1iz+S4kJXAMh3Neoj42Ntcrub/UUGhrKW2+9xUN3PEB5eD8qwvsBcNoRxPvvv8+MGTP4+OOPSZj9K2KB4l7RDRHl88477/Dkk0+2GlO/fv2swR0F/a5zzRgH/lETytmzZzseUz9XefsdPEjfI0dc9bRvH/3/8Q9XPYWHEzlkSIv1dPbsWd5//32u+495xALnese61zbgeF0I+/bt84l6CsR9TzF1TkxlZWWIiEhTU6dOo7q6qtn7wnv04EBurs4h+TD35Jiqysom911p9RcQM8a3bt3K/PnzWbp0KdnZ2SQmJpKamsrp06ebzb97925mzJjBAw88wJ49e5gyZQpTpkyxRiYCPPvss7z00kukpaWRkZFBz549SU1Npbq6GoADBw7gdDp59dVX+cc//sHvfvc70tLSrAMYf9PSSJErcbSIiD8KhNFe7qWG3bfGnXQSuNatW8fgwYMJCwsjJSWFzz//vNX827ZtY9iwYYSFhXHjjTfy3nvvedxvmiZLliwhJiaG8PBwJk6cyOHDhz3yDB48GMMwPG7uE8hXKn3+RESkvSIiIrDb7dYsPLfCwkKio6ObfUx0dHSr+d1/2/Oc+fn5fPe732XcuHGsX7++1bKGhobSu3dvjxtgdYLYbLZm03a7vV1pd8dK43RQUFCTtGEYTdJAk7S7M6lx2mazNZt2OByYuF4Hw+a64VpC2/36XRkTgBMDDNfNtLnK5bHM9yXGdHHaX+vJMAzq6uqsunF3XJu4lpl211Nb9ddSTB7L1dvsrjpoqA/3Muwdism9/zid2Bvi8EhfFHdzddM4PrNRfE4ulN3b9RSI+55i6ryYApk3jsF/+9vfMm7cOHr06GENehAR/1NdXcX0Fa8w940PPG7TV7xCVWVls5fpE9/ReHLMlV5/AdEx/sILLzBnzhxmz57NDTfcQFpaGj169GDDhg3N5n/xxReZNGkSjz/+OAkJCSxfvpxRo0axdu1awNWgr169mkWLFjF58mRGjBjBpk2byM/Pt66BNmnSJP74xz/ygx/8gOuuu44777yTX/7yl7z99tvdFXanaW0ZVS2lKuL7tBSy+CtvDGxzW7ZsGadOnbJuP/vZz7o0VhERkUAREhLC6NGj2bVrl7XN6XSya9cuxo4d2+xjxo4d65EfYOfOnVb+uLg4oqOjPfKUlpaSkZHh8ZwnT57k1ltvZfTo0fzxj3/UtWBFREQugbeOwWtra5k2bRqPPPJIl8coIl3r4okVmlzhfzQ5JgCWUq+trSUrK4uFCxda22w2GxMnTiQ9Pb3Zx6Snp3sspwau6x+5O72PHTtGQUEBEydOtO7v06cPKSkppKenc8899zT7vCUlJdaSYc2pqamhpqbG+r+0tBTAGi3r/muz2TzSDocDwzDaTNtsNgzD8EjX19dbIx7daXCNLnenT58+bY0UiY77pmvUNyY2oODYEd5a8ihnzpxh0KBBOJ1OTNPEbre3mm4uju6MyeFwEBQUhGmaHmmn04ndbvdIB3pMpmkSHBzs2unMhto1bA1p12hy92NbigkgODjYym+YTmv0d3BwsDUqvctiApw2G6bdjr2uzjPdkM/eymfI/V5cKDtg2LBxYTZDV9fT119/zblz56z3yjBco/n79+/P4MGDO7TvnTlzhtqaGuszbOKajVB0/DBvLn6UoqIiBgwYcNkxuV8LTAynwzUrwTSxNdp/3Pkv5/NkvSeYYDrBsGG0sH9eTj25n9+GCeaFfdhdD9ZsixY+T56fIRMDE9OwYWBaI9278jsikDUe2AaQlpbGu+++y4YNG3jiiSea5G88sA1g+fLl7Ny5k7Vr15KWltZkYBvApk2biIqKYvv27R7t91VXXdXirDYRERFp3fz585k1axbJycmMGTOG1atXU1FRYbXpM2fOZMCAAaxcuRKAxx57jAkTJvD8889z++23s2XLFjIzM60Z34ZhMG/ePFasWEF8fDxxcXEsXryY2NhYpkyZAlzoFL/22mtZtWoVZ86cscqjNl1ERKRt3joG/81vfgPA66+/3g1RioiItM7vz7gXFRXhcDiIiory2B4VFUVBQUGzjykoKGg1v/vvpTznkSNHWLNmDQ899FCLZV25ciV9+vSxbu5r4LivDXXixAlOnDgBuDrn8/PzATh69Ki1pNyhQ4esJQ1yc3MpLi4GYP/+/ZSUlACQk5NDeXk5AHv27KGqynXdh8zMTGpra3E4HGRmZuJwOKitrbWuQTXwuiEkfyOMAQmJxH1zKKMiexIZF8/gwYOt1ykuLiY3NxdwvfeHDh0CXEvcHT16FHAtbXfs2DGvxpSZmQlAVVUVe/bsAaC8vJycnBzANYjBPbox0GOqqalh6tSpAPSqKubqUld5e1ee5Zog11JoFRUVbcY0depU+tkdAHzj/NeE17iuufTTn/7UWiauS2O6/npy773XVU8jRnCoIabC5GSONlz/qaV6Ki8v5+abbwbg6tJ8elW56mNwcC0jRozo8no6fPgwL730EqNHj2b69Om89tprjB49mvvuu4/f/va35OXldWjfKysrIzk5mci4eG6M6Uf84GsZkJDI2KGDuP766zsck/s7ItQwiT3nWg4rpL6KYSGugT51dXUd+jxVVFQAcE1QHb0rz1r1FNGwv5WWlnbo8+R0OgkJCeHG0GoM04ndWc+AooMA9O/fn3Pnzln7SXP7Xm1tLfc27Hs9q8/Tv8RVBxF2B3feeWe766kj3xGByD2wrfEgtPYMbGucH1wD29z52xrY1tjTTz9N//79GTlyJM8995y1rGVLampqKC0t9biB5+C25tIOh6Nd6cYDjNzpxgM73GnTNJukgSZph8PRJO10OptN2+12ayAKptN1A2tgjz/GdHHam/UEWAOJMF0DjMBz8ExLMTUZ3OYe1NNoYE5QUFCb9ee1enLvPzYbjoY4PNIXxR0Inydf2vcUk2/EFKjuvvtuVq1axZIlS0hKSmLv3r3s2LHDOobOy8vj1KlTVv5x48axefNm1q9fT2JiIm+99Rbbt2+3ricLsGDBAn72s5/x4IMPctNNN1FeXs6OHTsICwsDXDPMjxw5wq5du7jmmmuIiYmxbiIi0n66nOKVydvH4JfCV4+/L5444ko2nTjiLpe3f4cG4m/ryz3+BpOQkJBWY2rp+Lu5yWXeqifDMFqMz97cMXfjtN1+4Ri9hbppfH7BaHR+ofHksiYTjxrSISEhbcbkqgPTs+yNPkM2m80zvkbnQNx105F9r2l8F/aZZuNzOlqN71K/IwDPyVftiK9xHE0mlzXE0dz+2dK+Z9VBC/F15DuiyeSyZs5h+crxt993jPuCkydPMmnSJKZNm8acOXNazLdw4UJKSkqsm7vjZPDgwQAMHDjQ6iyPi4sjNjYWgCFDhlgnGIYOHUpERAQACQkJ9OvXD4Dhw4fTp08fABITE+nVqxcAI0eOJDw8HIDk5GRCQkKw2+0kJydjt9sJCQmhf//+ANSYBvlXu5ZNqA0Kp6DfdYCr4979Ov369SMhIQFwXVtu6NChgGvQwJAhQwCIjY0lLi7OqzElJycDEB4ezsiRIwHo1asXiYmJgOtHmvskTKDHFBoayltvvQVAeXg/zvV2lbe0R3/+Ve/6ourZs2ebMb311lsUO1wziM/0vZaq0KsA2LBhg/WF16UxHTxIwhtvuOpp3z6GNsQUlZnJkKuuarWeevXqxaeffgrAud6xlIe76uN4XQj79u3r8noqKytj3bp1TF/xCrctf5XQW6Yy940PGHHvz9m4cSNFRUUd2veuuuoqq0P+bJ+BVIT1BeBobQgHDx7scEwtfUccqA0FXA16Rz5PPXv2BOBf9cGU9uhv1VNRw/7Wu3fvDn2ebDYbtbW1fFkThmnYcNiCOBnhGjBw9uxZa6WPlva9kJAQ3mjY9yrC+nK2j6sOihx23nnnnXbXU0e+IwKRNwe2/fznP2fLli189NFHPPTQQ/yf//N/WLBgQavl9dXBbZ0xECw5OZlBwa4BTr0rz9Kv3PVe3XrrrdbAFX+LyVcGt5mmyVVXXcWNoa5lBIMctdYAo5iYGOu5L3VwW6S9ntTUVKueYoJcByf9ygusAUZ33nmnVS6v1ZN7YGVLg9uqqnyingJx31NMvhNTIJs7dy5ff/01NTU1ZGRkkJKSYt338ccfN5kVNm3aNA4ePEhNTQ379+/ntttu87jfMAyWLVtGQUEB1dXVfPDBB9ZvSYD777/fOkFz8U1ERNpHl1O8cvnK5LL28NXj766eOKLf1l13/N3DMHn44YdbjamzJpd1ZT3179+fb4W69reQ+iqii/8JwFU2J6k//akrpg5MLktNTSXS7jq/0NLksiEhtdaEuajiY4TVuc4bPfzww1bHaXMxmabJ448/jg08Ji0FOWqtmGJiYqzPU1hdBVHFrjL2tjmtSUsd2ffuvPNOayJW/5IT9Kw+b8XknlwWH1JjxRRd/E9C6l1xPPbYY1YH8OV+R9hsNn7aUE/hNWV84/zXAPSzO6x9r6snlz388MP0MFzHT7HnDhPkqAXg8ccftzrlL/c7wp8ml/n9UuoRERHY7XbrjXIrLCxscTm16OjoVvO7/xYWFnqMPi8sLCQpKcnjcfn5+Xz3u99l3Lhx1jJwLQkNDSU0NLTJdms0SqMlcxun3csZX07aPRKjtfSF1zJcSyQDGAamcWEZZfdy2i2V8VLTXR2TO20YhkfaWk67UTrQYzIMw5rRjdFofJJhs5ZDdy/j3FpMdXV1Vn7TsHlsd+8fXRqT0wkNI4I80g4HtLF/upelvrjsTi4so93V9VRbW2tdv6Mxd910ZN/rSHwd+Y5wNtp/OvJ5cu8/JgY0lN9sYf9sKY6TJ09ajWRjERER1vM7Max9xf39ZpoXRgS2tO95foaMC58DDOsHX1d/R0jnanw5lREjRhASEsJDDz3EypUrm22nwTW4rfHjSktLGThwoMfgNjf3IAlwDYhw74NDhw610gkJCVZ6+PDh1r6SmJhopUeOHGntB+7BKo3T7kEs0P5BU3379gVcn43+/fuTk5NDZmYmY+qCiQVrcAqc4eOPP+bpp5/2u5jAdSImMjISwBqc4o16ysnJoaysjC9rwogB6u0hrgFGZ/Zz6tQpa1BMSzG5B7c9dMcDlIf3o6JhYNdpRxDvv/8+M2bM4OOPPyZh9q+IBYp7uX/75vPOO+/w5JNPeree3AMrDx6k75Ejrnrat4/+//iHq57Cw4lsNGjqcuopLy+Pmpoajh8/ztdff41pmhw9epRvfOMbV/S+p5h8I6ayhhNPIiIivqKoqMi6nOLF1xQ9fewwby56hKKiIgYNGuSlEor47vF3SxNHvm5h4oh+W/vI8TdQaRqsT0tj1qxZl3z8XdqjP/n1J4Gmk8u6s5727dvH2bNn+UdNKDF4Tmwsc9r4bMMGVtDK8XdmJpGNJpddXE9nz57l/fff57r/mEcsrklL7n6ExpPLjtaGENMwYa6wX5x1njQtLY2ZM2e2GJNhGDz33HM8+MdbPSYt1dtD+EeN6zN06tQpDtS64qsO7klhP9d7XOq08cYbb/Czn/3ssve906dP88477zDgrkeIxTW5zF32xpPLDteGEhPsmsRV0O8661z7iy++yN13391qPbX1HeF0OtmwYQMP3TKNqtCrqA51TYgqdth56623+OUvf9lqTO5z3/+qDya28eSyfNf2iyeXNbfvpaWl8WDKj+gH5F8db8X33HPP8e///u8eE+Yu9TvCPbnsoX/7CRVhfakMc03+ck8u+/Wvf+0zx99+3zEeEhLC6NGj2bVrl3XtMafTya5du5g7d26zjxk7diy7du1i3rx51radO3cyduxYwFUJ0dHR7Nq1y+oILy0tJSMjg0ceecR6zMmTJ/nud7/L6NGj+eMf/xjw14IVEfFF7hHvVZWVTe4L79GDbW++6YVSSVu8PbCtsZSUFOrr6zl+/Lg1QvRivjq4rTMGgjkcDutggEaDa+rr65sdGOcPMfnK4DaPgTmuwnsMPGxuYE57Brc1HphTX1/fZv15rZ7c+09Lg9sMAy6hLi8ub1vf/wdyc62TulfavqeYfCcmERGRi7kvp9aciIiIbumUbm7gvgQ2XzoGb4uvHn939cQRb8Tkb7+tL/f4G1yTllqLqbMml3VlPZmm2WJ8Dvfkqw5MLmt8fqGlyVeeE48u5KmtrbXqoKV9zFUHhmfZG32GnE6nZ3yNJid1xuSyS47PdqGe2orP87Wa/44AWpx81Z74OmNymVUHLcTX+LugcXzt+Y7wp8llft8xDq6ZX7NmzSI5OZkxY8awevVqKioqmD17NgAzZ85kwIABrFy5EnAtezBhwgSef/55br/9drZs2UJmZqY149swDObNm8eKFSuIj48nLi6OxYsXExsba3W+nzx5kltvvZVrr72WVatWcebMGas8Lf2YEBGRztfSiHf3aPfz5897r3DSIm8ObLvY3r17sdls1ohMEfEPbX3/a7aTiIhcrpY6Lrur01ICV2sD+6Dp4D6RzuJLx+AiIiLeFBAd43fffTdnzpxhyZIlFBQUkJSUxI4dO6zrm+Tl5XmMOBg3bhybN29m0aJFPPnkk8THx7N9+3Zryj/AggULqKio4MEHH+T8+fOMHz+eHTt2EBYWBrh+BBw5coQjR45wzTXXeJRH1zgTEel+GvHuf7wxsC09PZ2MjAy++93vctVVV5Gens4vfvELfvKTn1jLWouIf9H3v4iIdKZLWZFE5FJpKXPxJm8cg4Pre/XcuXPk5eXhcDjYu3cvAN/85jfp1atXt74HIiIiAdExDjB37twWR7d9/PHHTbZNmzaNadOmtfh8hmGwbNkyli1b1uz9999/P/fff//lFFVERETwzsC20NBQtmzZwlNPPUVNTQ1xcXH84he/8Lh+mYiIiIhcubQiiXQHDewTb/DGMTjAkiVL2Lhxo/W/+zq1H330EbfeemsXRy0iIuIpYDrGRURExP9098C2UaNG8dlnn11WWUVERETkyqGOSxEJRN19DA7w+uuv8/rrr19qUUVERLqEOsZFREREREREREREREQ6IC8vj6KioibbIyIitNqIiIiPUMe4iIiIiIiIiIiIiIjIZTp16hTjv/Mdqiorm9wX3qMHB3Jz1TkuIuID1DEuIp1CIyJFRERE/It+v4mIv9L3l4iI+Jrz589TVVnJ9BWvEBkXb20/fewwby56hKKiog63UWr/REQ6Th3jEhBa+lEA+mHQHTQiUkRERMS/5OXlMSwhQb/fRMTv6PvL/506dYrs7Oxm79M5HBHxd5Fx8QxISOz05+2M9k/n0EVE1DEuAaC1HwWgA+Pu0B0jIkVEpHldPWJcI9LFm1rb/6RjioqK2vz95s53MX3+RcSb2vP9pe8o3zZ16jSqq6uavU/ncEREmtfR9k/n0EVEXNQxLu3iy6N5W/pRADow7m5dNSJSRESa19UzprpjRRB1vEtL2tq/t735phdKFXha+v2mFYFExNfp+NN/VVdX6RyOiMhlutz2T+fQRXyfJgd0D3WMS7v4w2heHRSLiMiVpqtnTHX1iiBaCrXr+fPAg7b27/Pnz3uvcFcArQgkIt6kk4KBT+dwRES8Q9+/Ir6prcHpvjA5IFB+o6tjXNpFo3lFRER8V1cf2HbV82sp1K4VKDN+deLGu/T+i0h304ohIiIiInKlaWtwurcnBwTSb3R1jEu76aSYiIiIdAX9xugamvErIiL+SCuGiIiIiMiVylfPkQXSb3R1jIu0Q0tLRIB/LEUqIiIiVy5fPagSERFpjdovERERERHfEgi/0dUxLtKG1paIAP9airQlp06dIjs7u9n7/O36EN4SKNfXEBERERER8XetHZ/587G7iIiIiEhXuVL6ONQxLtKGlpaIgMBZinTq1GlUV1c1e5+/XR/icnXkxEkgXV9DRERERETEn506dYrx3/lOi8dnB3JzAa6Ik34iIiIiIu3R1m/oQOrjUMe4SDsFwhIRLamurmq149+frg9xOdpz4qS1zvFAur6GiIiIiIiIPzt//nyrx2dffvkl06ZPD+iTfpoxLyIiIiKXoq3f0IHUx6GOcfEJuoa39wVyx39b2vrSb++KAFfye9jVrpRlXEREREREOoM6Rls+Pgv0k34dHfgtIiIiIleuK6GPQx3j4nVXwjW8xT9cCV/6/uhKWsZFRORK09UDn9Qx5NtUPyIt68j3ozpG2ydQj/86a+C3iIiIiEggUse4eN2VcA1vEbl8gT6jQ0TkSpV36hTDunDgkzqGfFtrg2NVP3Kla+vz0db3oy90jGrgi/cFase/iIiIt5w6dYrs7Oxm79NvHBH/oY5x8Rk6aGuZlpoX0XeEiEigKerigU+d0TGkjp2u09LgWA2MFWn789He70dv/X7WwCQREREJRFOnTqO6uqrZ+/QbR8R/qGNcxMdpqXnxB+o4EBGRy9XVHTeX+/ya0dw9NPBNpGX++vnwhRnrIiIiIp2turpKq95ewdpaMUD8hzrGRXyclpoXX6cZISIiEog0o1lEulJHriHuL/y1Y19ERESkJa39vtFS64GtrRUDOno5uCuBr0yuU8e4iJ/QSQXxVZoRIiLe5Cs/qiVw6TeYiHS2jl5DXERERER8j5ZaD2xtrRjQ0cvBBTpfmlynjnG5Imi0llzpuqPjSB0HItLdfGGp6ythxp+IiHSuzrqGuIgEJp3DEhHxT1pqPfDp/Pfl86XJdeoYlytCW6O1dn3wAaGhoc3ef+rUqa4s2hVDM/q8x5dGY4mIdCZvL3WtGX8iItIROrHmvzQwTrqSZhyKiPgv/b4TaZ0vfEbUMS5XhLZGa33ve99v8aAjNCysO4oY0NQx612+NBpLRKQrdOWP6tZOfGvGn4iIyJWnreNbDYyTjurojMOWfr+CJn+IiIgEMg3ebB91jMsVo7WT5m0ddEjHqGPWN/jCaCwREX/S3hnh+n4VERG5crR1fHslDIzTSdeud7m/L1v7/Qqa/CEivq21gT3uNkYDf0Sap8Gb7aeOcZEGOqnd9fQeS6DSpQJEApNmhIuIyJVKHZ9t89aKNd6Wd+oUw3TS1We19PsVNPlDpD18+fs30LVnYI9hGFRXXf6qr6dOnSI7O7vF+0T8mQZvtp86xkVERDpAlwoQCXwa2CWXq6sHTrX1/DqxJ9J1AnlgZHtXTJGu0R2zfVrdf9t4bJFOunpdezp29PtV5NKp/fOu9g7s6cjAn6lTp+lyqhLw9BugbeoYFxGRK15HOg50qQAREWlOWyfWOjpwqq3n3/XBB3x/4kSd2BPpAl39+fY2rZjiXV0926etjvejb75JTDuex5dPura1FK8/fz4h8Dt2Ar3+xHep/fMNbbUvHWl/rvTLqeadOkWRZsyLqGP8StHaj0p96YnIlayzZmT48okhERHpfm2dWHP/Nr/cGadtPf8///lPvz+xpxPj4qva8/kOhP1Tv2+9q6ve//Z0vLenY9xXtbUUbyAMXgnkjp0rof7E96n9C2xXav3mAcOmTqMqgAdWibSXOsavAO25Poev0/U/RKSr6PorIlc2LTUtXa2lEy+ddSmOrpxR4U2tvT+gE+PiG/z18yUCgbv/tmcp3kAYvKL68+/6E+/x9eM/Xy+f+K8ioCqAB1aJXAp1jF8B2nt9Dl/m78tEabaL//P2D1Nvv/6VIFBPLIhIy3QNOfEmXYqjdS29P6D3SERE2taVx3c6x9P1dHwuXcHXj/86o3wdPX/Y2uS0zvh+06q23hfI36/av6S9AqZjfN26dTz33HMUFBSQmJjImjVrGDNmTIv5t23bxuLFizl+/Djx8fE888wz3Hbbbdb9pmmydOlSXnvtNc6fP8/NN9/MK6+8Qnz8hZMy586d42c/+xl/+ctfsNls3HXXXbz44ov06tWrS2O9XF35pdfVjaY/LxPVnmWgdn3wAaGhoc3ery9t7+uspbYvl6//cBfpCLXf/q+1A29fPymoa8iJL7gST0xcysC+QH5//J3acBG5Emmp77a1NXAAmr+UDOgcWHe4kttvXz/+62j5OuP8ZWuT09rz/dba57+mpobvT5zo16vaiu8KhFWTpfsERMf41q1bmT9/PmlpaaSkpLB69WpSU1M5ePAgkZGRTfLv3r2bGTNmsHLlSu644w42b97MlClTyM7OZvjw4QA8++yzvPTSS2zcuJG4uDgWL15MamoqX331FWENH6J7772XU6dOsXPnTurq6pg9ezYPPvggmzdv7tb4fUFHG8328OWTYm0t9d7WbJfvfe/7fj0jvjO02rHihfI01h1LbbcWf3f8cO/qGema8S7NUfvdtvacVLrc5+iMz19nLQXtbb78G6Or+fPAhs6g9qlj2nr/vD2wryMn5q+Uz8DlUhveNn2/iHSdjs4Ia2tyB7TecdvWOZ4vv/zyiu34bU/HhGEYVFdd/jmwrp6cE8jUfrv4+vHf5ZavM85ftjU5rbXvt/Z0fNdUV/vt5LfuoBnPretoH4yIW0B0jL/wwgvMmTOH2bNnA5CWlsa7777Lhg0beOKJJ5rkf/HFF5k0aRKPP/44AMuXL2fnzp2sXbuWtLQ0TNNk9erVLFq0iMmTJwOwadMmoqKi2L59O/fccw+5ubns2LGDL774guTkZADWrFnDbbfdxqpVq4iNjW3yujU1NdTU1Fj/l5SUAFiNktPpBMBms3mkHQ4HhmG0ms7Pz6ewsBDDMHA6nRiGYaXPnj0LQMGBfdRWlgNgACZw5ut/EhwcTF1dHSdz91FXWY7ZcK8BnP76nxiGgd1ut+6n4V4Dk6K8fwJQW1vDrffP5arIWAzAMMBpQmlhPv/7/3uFzMxMjh075nptw8A0TSt95swZDMNo9vnPfO16/uDgYPJz91FbWYGBScOjOZd31Ho/m8ZncObro1Z8+R2Iz2azcerAhdd35zmbd7RhpONU6uvrME0Tp9NJUFAQDocD0zTp2asXhmFQV13V8PquEhqY1Dd0hjsc9Xxn5qP0jR6A3TBwNLw/5adP8dHraxrFV2GV3cSgqCG+48ePU1ZW1uL7GxQU1Gp8dru91fgqKysJCgryqAMa3r+goCAqG37wXKgD1/Ofbqg/9/0X9jGXcw2vf+TIEb77ve9RWlKCYRgEBQVRV1eHYRj0uuoqMn//eyINA9Nux15fj7Nx2mbDLCvjzKFD1g+Exu9BTEwMZWVl2Gy2Ju/B2byjGIbRbHyNPx/u8jtrqjziq2uov6bxuWrIHV9lZSXBwcGczHW9P43rLygoiKNHj/KdW26htqaG+vp6bDYbhmHgcDjo2asXG/7wB9d+UlNlPX/j/aeysrJD8R05coSbx4/HUV9PXV2d9Zmrq6sjLDycja+/3mZ8ze1jjeO7ZcIEqquqcDgcLcZ36sA+j/jONNp/mvuOaBxfc98RF9ffxd8RF++fF39HnG1HfHa73Xr/L/4Mnf76n9jtdsrKyigtLW3Xd/nF74/NZrM+2+59OpD4S/sNXdeGnz592uO7q3EbXl9fzx0/+hFVDfv45Xw+jxw5wq3f/S5lpaVWe1dfX299v/7h979vdf91fz5a+nzm5+dTXVXFd2Y+ytUx12Cars9f2el8Ptm4juPHj1NZWdnsb5RvfOMb1v7d0ueztLSUQw3f76ZpYrPZmny/t/b5LC8v58CBA9brN24fIyMjrddv7/dP498fjb9/Trbr++dCG+7+/dE4Pne5LiW+ysrKZtvw9tbfkSNHrIENwcHB1NfXY5omwcHBBAUH88Xnn2Oz2Th9+rTrtU0TwzAAiIyMZMCAAZw6dYpTp05ZdeOup6ioKCLLyrCDZ7vdKF3WUP7mvt8bx9fW74/LqT93/O7fH40/WwC9+/Th96+9hmEYLdZfWVlZm/XXUnzu31etxdfc87s/QzExMZSWll70+Xdpz+8P9/5pGEaz+497/wbP9rHx78cjR45wy4QJVJSXY7fbrd/BdrudsPBw/rhhA3W1tdwy61H6RA3A1vD+FBecJH3zq+Tn51/0+W/f78fG3xHHjh2jvLzcY99z14HT6eSOH/3I+n3V+DvQZrMRFh6Ow+GgrrbWanftdjuA9Rvls/R0Bg0apDa8Gf7ShndV+11eXu7V39dt/f5s6/uxrKyMgwcPUlhY6NE2mqZJdHQ05eXlXfr7uqysjAMHDnD69Okmrx8VFUV5eXmH4uvq9rut78f2HD90pP1uq31r/vv/En6fVFZSSue3342P4UzTbBJf4zK6v98vPr/l/o799x//uNn2Ozg4GKPhu7ilcyhBQUHcdddUamtrPNoF93OH9+jhqueKCo92wd3WBQUHux5XXdUkPkdNFYZhcNddU3E46q3zQo1/Z/W66qqLPv80+Qw11343/o5orv1uHF99fX2T/bPxPtb49d2PbbyPHTt2jLKysia/n93fEYZhkJ+f36Ru3Oegqior+c7MR+kfc411fstuGJw99S/+Z9M6goOD+c7MR+kX7fp94DBdEZaezufj19e2Gp/dbueuu6ZSV6f2+3Ko/W69/W5v+3a57XdnH5+6n//i82ONv59MoK66qtX4Lj6HXl9d5RGf0fAchmFwzz0zKC8va/Lb2jAM7EFB1NfVMWHWXHpHxWJzHTpafQT/86eXgabnN2l4fvf59Ivbt4v7CC5uv+HCMdCF+Jo/h35xH8HFx0Bt9RG0dQ7d6XQ2qT/38wcFBbXavjmdTqb8+7+32r61Fh9BQZRefN68cftts2FvoQ+mcXxd1X4XFRW1q33rSPttt9utPpjG8bnPobc3vsbHpy33odHp3xEd/Y2vc+iX0H6bfq6mpsa02+3mn//8Z4/tM2fONO+8885mHzNw4EDzd7/7nce2JUuWmCNGjDBN0zSPHj1qAuaePXs88txyyy3mz3/+c9M0TfMPf/iD2bdvX4/76+rqTLvdbr799tvNvu7SpUtNXMcjuummm2666XZJtxMnTrSzZfQP/tR+m6bacN1000033S7/pjZcx+C66aabbrr5303tt9pv3XTTTTfd/O/Wnvbb72eMFxUV4XA4iIqK8tgeFRXFgQMHmn1MQUFBs/kLCgqs+93bWstz8RIzQUFBXH311Vaeiy1cuJD58+db/zudTs6dO0f//v2t2TcdVVpaysCBAzlx4gS9e/fulOfsbL5eRpWvY1S+jlH5OsbXy3c5TNOkrKysxZnM/sqf2m9QGw4qX0epfB2j8nWMyucdasMv0DG496h8HaPydYzK1zG+Xj7wjzJeKrXfF6j99h6Vr2NUvo7z9TKqfB3j6+W7HJfSfvt9x7g/CQ0NJTQ01GNb3759u+S1evfu7fM7tK+XUeXrGJWvY1S+jvH18l2qPn36eLsIVzy14ReofB2j8nWMytcxKl/3UxvuXWq/L1D5Okbl6xiVr2N8vXzgH2W8FGq/vUvt9wUqX8eofB3n62VU+TrG18t3qdrbftu6uBxdLiIiArvdTmFhocf2wsJCoqOjm31MdHR0q/ndf9vK477eolt9fT3nzp1r8XVFRETERe23iIiIf1IbLiIi4n/UfouIiLj4fcd4SEgIo0ePZteuXdY2p9PJrl27GDt2bLOPGTt2rEd+gJ07d1r54+LiiI6O9shTWlpKRkaGlWfs2LGcP3+erKwsK8+HH36I0+kkJSWl0+ITEREJRGq/RURE/JPacBEREf+j9ltERKRBm1ch9wNbtmwxQ0NDzddff9386quvzAcffNDs27evWVBQYJqmad53333mE088YeX/9NNPzaCgIHPVqlVmbm6uuXTpUjM4ONj88ssvrTxPP/202bdvX/O///u/zX379pmTJ0824+LizKqqKivPpEmTzJEjR5oZGRnm//7v/5rx8fHmjBkzui/wZlRXV5tLly41q6urvVqO1vh6GVW+jlH5Okbl6xhfL594Uvvtydf3X5WvY1S+jlH5Okblk86mNvwCX99/Vb6OUfk6RuXrGF8vn2n6RxnlArXfF/j6vqvydYzK13G+XkaVr2N8vXxdLSA6xk3TNNesWWMOGjTIDAkJMceMGWN+9tln1n0TJkwwZ82a5ZH/zTffNIcOHWqGhISY3/rWt8x3333X436n02kuXrzYjIqKMkNDQ83vf//75sGDBz3ynD171pwxY4bZq1cvs3fv3ub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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x600 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Average error for the true outlier (sample 24): 0.043461\n",
            "Maximum average error: 0.043461 at sample 24\n"
          ]
        }
      ],
      "source": [
        "import sys\n",
        "!{sys.executable} -m pip install --upgrade pyod\n",
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "import math\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 1. Generation of the full elliptic paraboloid dataset with an outlier\n",
        "#    Features: x1, x2 ; target variable: y = x1^2 - x2^2\n",
        "# ------------------------------------------------------------\n",
        "x1 = np.arange(-1.0, 1.05, 0.1)\n",
        "x2 = np.arange(-1.0, 1.05, 0.1)\n",
        "X1grid, X2grid = np.meshgrid(x1, x2)\n",
        "Ygrid = X1grid**2 - X2grid**2\n",
        "\n",
        "# Inject outlier at point (x1=0, x2=0) with value y = 0.45\n",
        "mask_out = (np.abs(X1grid) < 1e-10) & (np.abs(X2grid) < 1e-10)\n",
        "Ygrid[mask_out] = 0.45\n",
        "\n",
        "points_full = np.column_stack((X1grid.ravel(), X2grid.ravel(), Ygrid.ravel()))\n",
        "labels_full = np.zeros(len(points_full), dtype=int)\n",
        "labels_full[np.where(mask_out.ravel())[0]] = 1\n",
        "\n",
        "print(\"=\"*80)\n",
        "print(\"FULL DATASET (441 points, one outlier)\")\n",
        "print(\"=\"*80)\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 2. Random removal of 90% of normal points\n",
        "# ------------------------------------------------------------\n",
        "np.random.seed(42)\n",
        "normal_indices = np.where(labels_full == 0)[0]\n",
        "n_remove = int(0.90 * len(normal_indices))\n",
        "remove_idx = np.random.choice(normal_indices, size=n_remove, replace=False)\n",
        "keep_mask = np.ones(len(points_full), dtype=bool)\n",
        "keep_mask[remove_idx] = False\n",
        "points = points_full[keep_mask]\n",
        "labels_true = labels_full[keep_mask]\n",
        "\n",
        "print(f\"Removed normal points: {n_remove}\")\n",
        "print(f\"Remaining points: {len(points)} (outliers: {labels_true.sum()})\")\n",
        "print(f\"Outlier percentage: {labels_true.sum()/len(points)*100:.2f}%\")\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 3. Data preparation for NNF: inputs (x1,x2) -> output (y)\n",
        "# ------------------------------------------------------------\n",
        "X_nnf = points[:, :2]   # x1, x2\n",
        "y_nnf = points[:, 2]    # y\n",
        "\n",
        "Q = X_nnf.shape[0]\n",
        "N_x = X_nnf.shape[1]   # 2\n",
        "N_y = 1\n",
        "\n",
        "# Scaling to [-1, 1]\n",
        "def scale_to_minus1_1(data):\n",
        "    min_val = data.min(axis=0)\n",
        "    max_val = data.max(axis=0)\n",
        "    range_val = max_val - min_val\n",
        "    range_val[range_val == 0] = 1.0\n",
        "    scaled = 2.0 * (data - min_val) / range_val - 1.0\n",
        "    return scaled, min_val, max_val\n",
        "\n",
        "X_scaled_nnf, x_min, x_max = scale_to_minus1_1(X_nnf)\n",
        "y_scaled_nnf, y_min, y_max = scale_to_minus1_1(y_nnf.reshape(-1, 1))\n",
        "\n",
        "X_tensor = torch.tensor(X_scaled_nnf, dtype=torch.float32)\n",
        "y_tensor = torch.tensor(y_scaled_nnf, dtype=torch.float32)\n",
        "\n",
        "# Index of the true outlier (zero-based)\n",
        "true_outlier_idx = np.where(labels_true == 1)[0][0]\n",
        "print(f\"The true outlier is at index {true_outlier_idx+1} (zero-based index {true_outlier_idx})\")\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 4. Calculation of hidden layer neuron count bounds (empirical formulas)\n",
        "# ------------------------------------------------------------\n",
        "log2q = math.log2(Q)\n",
        "N_min = (N_y * Q) / ((1 + log2q) * (N_x + N_y))\n",
        "N_max = (N_y / (N_x + N_y)) * ((Q / N_x + 1) * (N_x + N_y + 1) + 1)\n",
        "print(f\"\\nQ = {Q}, N_x = {N_x}, N_y = {N_y}\")\n",
        "print(f\"N_min = {N_min:.4f}, N_max = {N_max:.4f}\")\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 5. Training for N from 3 to 30 and building all histograms\n",
        "# ------------------------------------------------------------\n",
        "N_range = range(3, 31)          # 3..30 inclusive\n",
        "n_N = len(N_range)\n",
        "sum_errors = np.zeros(Q)        # for accumulating error sums\n",
        "\n",
        "# Create a grid of subplots 7x4\n",
        "n_rows, n_cols = 7, 4\n",
        "fig_all, axes_all = plt.subplots(n_rows, n_cols, figsize=(20, 28))\n",
        "\n",
        "for idx, N in enumerate(N_range):\n",
        "    row = idx // n_cols\n",
        "    col = idx % n_cols\n",
        "    ax = axes_all[row, col]\n",
        "\n",
        "    torch.manual_seed(42)\n",
        "\n",
        "    # Two-layer network with tanh\n",
        "    model = nn.Sequential(\n",
        "        nn.Linear(N_x, N),\n",
        "        nn.Tanh(),\n",
        "        nn.Linear(N, N_y)\n",
        "    )\n",
        "    criterion = nn.MSELoss()\n",
        "    optimizer = optim.Rprop(model.parameters(), lr=0.01)\n",
        "\n",
        "    # Training for 1000 epochs\n",
        "    model.train()\n",
        "    for epoch in range(1000):\n",
        "        optimizer.zero_grad()\n",
        "        outputs = model(X_tensor)\n",
        "        loss = criterion(outputs, y_tensor)\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "\n",
        "    # Compute MSE for each sample\n",
        "    model.eval()\n",
        "    with torch.no_grad():\n",
        "        predictions = model(X_tensor).numpy().flatten()\n",
        "        errors = (predictions - y_scaled_nnf.flatten()) ** 2\n",
        "\n",
        "    # Accumulate sums\n",
        "    sum_errors += errors\n",
        "\n",
        "    # Histogram\n",
        "    examples = np.arange(1, Q+1)\n",
        "    bars = ax.bar(examples, errors, color='skyblue', edgecolor='black')\n",
        "    bars[true_outlier_idx].set_color('red')\n",
        "    ax.set_title(f'N = {N}')\n",
        "    ax.set_xlabel('Sample number')\n",
        "    ax.set_ylabel('MSE')\n",
        "    ax.set_xticks(examples[::5])\n",
        "    ax.grid(axis='y', linestyle=':', alpha=0.7)\n",
        "\n",
        "# Hide extra subplots (if any)\n",
        "total_plots = n_rows * n_cols\n",
        "if n_N < total_plots:\n",
        "    for i in range(n_N, total_plots):\n",
        "        axes_all.flat[i].set_visible(False)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 6. Calculation of average errors for each sample over all N\n",
        "# ------------------------------------------------------------\n",
        "mean_errors = sum_errors / n_N\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 7. Histogram of average errors\n",
        "# ------------------------------------------------------------\n",
        "print(\"\\n\\n\")\n",
        "plt.figure(figsize=(14, 6))\n",
        "examples = np.arange(1, Q+1)\n",
        "colors = ['red' if i == true_outlier_idx else 'skyblue' for i in range(Q)]\n",
        "bars = plt.bar(examples, mean_errors, color=colors, edgecolor='black')\n",
        "plt.xlabel('Sample number')\n",
        "plt.ylabel('Average MSE (over N = 3..30)')\n",
        "plt.title('Average MSE errors for each sample (averaged over N = 3..30)')\n",
        "plt.xticks(examples[::5])\n",
        "plt.grid(axis='y', linestyle=':', alpha=0.7)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# ------------------------------------------------------------\n",
        "# 8. Additional information\n",
        "# ------------------------------------------------------------\n",
        "print(f\"\\nAverage error for the true outlier (sample {true_outlier_idx+1}): {mean_errors[true_outlier_idx]:.6f}\")\n",
        "print(f\"Maximum average error: {np.max(mean_errors):.6f} at sample {np.argmax(mean_errors)+1}\")"
      ]
    }
  ]
}