{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Policy_cost.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VZGPwGDeCrdZ"
      },
      "source": [
        "# Simulation\n",
        "\n",
        "![image.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UUo_5G9_JfNw"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import matplotlib.cm as cm\n",
        "import pandas as pd\n",
        "import matplotlib.ticker as mticker\n",
        "import matplotlib\n",
        "from matplotlib.pyplot import figure\n",
        "from matplotlib.ticker import FormatStrFormatter\n",
        "import numpy as np\n",
        "from pathlib import Path\n",
        "Path(\"./content/sample_data\").mkdir(parents=True, exist_ok=True)\n"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Y_WcH8D54EB"
      },
      "source": [
        "## Lockdown only delays the virus spread"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1lliA-gEyv_0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "f8ad4040-9510-4088-96fc-83ef1559068b"
      },
      "source": [
        "# Set policy efficiencies\n",
        "test_cap = 0.001\n",
        "hygiene = 0.30 \n",
        "distancing = 0.74 \n",
        "lockdown = 0.96\n",
        "quarantine = 0.96 \n",
        "\n",
        "# ASSUMPTIONS:\n",
        "\n",
        "# Virus parameters\n",
        "transmission_days = 16.33/2.40 \n",
        "exposed_days = 5.27 \n",
        "recovery_days = 16.33 \n",
        "r0 = 2.64\n",
        "\n",
        "transmission_rate = (1/ transmission_days)\n",
        "incubation_rate = (1/  exposed_days)\n",
        "recovery_rate = (1/ recovery_days)\n",
        "\n",
        "# Country parameters\n",
        "hospital_cap = 6/10000\n",
        "death_rate_with_med = 0.6 # 60% chance to die with ICU treatment\n",
        "death_rate_without_med = 1 # 100% chance to die without ICU treatment\n",
        "general_dr = 0.02 # 2% death rate\n",
        "icu_case_rate = 0.06 # 6% need ICU treatment\n",
        "ser_case_rate = 0.15 # 15% of serious cases\n",
        "\n",
        "\n",
        "# Initialize\n",
        "susceptible0 = 0.99\n",
        "infected0 = 0.01\n",
        "exposed0 = 0\n",
        "recovered0 = 0\n",
        "population = 1000000\n",
        "policy_start = 30\n",
        "policy_end = 60\n",
        "days = 300\n",
        "\n",
        "\n",
        "def virus_model(days,policy):\n",
        "\n",
        "  if policy == \"hygiene\":\n",
        "    pol = hygiene\n",
        "  elif policy == \"distancing\":\n",
        "    pol = distancing\n",
        "  elif policy == \"lockdown\":\n",
        "    pol = lockdown\n",
        "  elif policy == \"quarantine\":\n",
        "    pol = quarantine\n",
        "  elif policy == \"None\":\n",
        "    pol = None\n",
        "\n",
        "  # set values for the first date of the simulation\n",
        "  susceptible =  susceptible0\n",
        "  infected = infected0\n",
        "  exposed = exposed0\n",
        "  recovered = recovered0\n",
        "  dead = 0\n",
        "\n",
        "  # Scale to population size\n",
        "  susc= [population * susceptible0]\n",
        "  exp = [population * exposed0]\n",
        "  inf = [population * infected0]\n",
        "  rec = [population * recovered0]\n",
        "  re = [r0]\n",
        "  d = [0]\n",
        "  \n",
        "  for day in range(days):\n",
        "    if policy_start < day < policy_end  and pol != None:\n",
        "      transmission_rate = (1/ transmission_days) * (1-pol)\n",
        "    else:\n",
        "      transmission_rate = (1/ transmission_days)\n",
        "\n",
        "    # Simulate flow between compartments\n",
        "    S2E = susceptible * infected * transmission_rate\n",
        "    E2I = exposed * incubation_rate\n",
        "    I2D = general_dr*infected/recovery_days\n",
        "\n",
        "    # Account different death rates depending on condition\n",
        "    if (icu_case_rate*infected < hospital_cap):\n",
        "      I2D += icu_case_rate*infected*death_rate_with_med/recovery_days\n",
        "    else:\n",
        "      I2D += hospital_cap*death_rate_with_med/recovery_days + (icu_case_rate*infected - hospital_cap) * death_rate_without_med/recovery_days\n",
        "    I2R = (1-general_dr)*infected*recovery_rate\n",
        "\n",
        "    # Update the compartments\n",
        "    exposed +=  S2E\n",
        "    susceptible -= S2E\n",
        "    infected += E2I\n",
        "    exposed -= E2I\n",
        "    recovered += I2R\n",
        "    infected -= I2R\n",
        "    infected -= I2D\n",
        "    dead += I2D\n",
        "\n",
        "    re.append((transmission_rate/ recovery_rate)*susceptible)\n",
        "    susc.append(population* susceptible)\n",
        "    exp.append(population* exposed)\n",
        "    inf.append(population* infected)\n",
        "    rec.append(population* recovered)\n",
        "    d.append(population* dead)\n",
        "  \n",
        "  return susc, exp, inf, rec, d, re\n",
        "\n",
        "result_h = virus_model(days,'hygiene')\n",
        "result_d = virus_model(days,'distancing')\n",
        "result_l = virus_model(days,'lockdown')\n",
        "result_q = virus_model(days,'quarantine')\n",
        "result_0 = virus_model(days,'None')\n",
        "\n",
        "m = [m for m in range(days+1)]\n",
        "\n",
        "# Plot the graphs\n",
        "# Here we plot only lockdown\n",
        "sns.set_style(\"ticks\")\n",
        "matplotlib.rcParams['figure.figsize'] = 8, 6\n",
        "sns.despine()\n",
        "formatter = mticker.ScalarFormatter(useMathText=True)\n",
        "f = mticker.ScalarFormatter(useOffset=False, useMathText=True)\n",
        "g = lambda x,pos : \"${}$\".format(f._formatSciNotation('%10e' % x))\n",
        "\n",
        "plots = ['Susceptible','Exposed', 'Infected','Recovered','Death cases']\n",
        "abbrev = ['S','E', 'I','R','D']\n",
        "\n",
        "for num,policy in enumerate(plots):\n",
        "  plt.plot(m, result_0[num], label=\"No policy\", color ='grey',linewidth=2.5)\n",
        "  plt.plot(m, result_l[num], label=\"Lockdown\", color ='green',linewidth=2.5)\n",
        "  plt.axvline(x=policy_start,linestyle='--', linewidth=1.5,  label='Policy start')\n",
        "  plt.axvline(x=policy_end,linestyle='--', linewidth=1.5, color='red', label='Policy end')\n",
        "  plt.tick_params(labelsize=22)\n",
        "  plt.ylabel(policy, fontsize=22)\n",
        "  plt.xlabel('Days', fontsize=22)\n",
        "  plt.legend(fontsize=22)\n",
        "  sns.despine()\n",
        "  plt.gca().yaxis.set_major_formatter(mticker.FuncFormatter(g))\n",
        "  plt.savefig('./content/sample_data/{}.pdf'.format(abbrev[num]),bbox_inches='tight')\n",
        "  plt.show()\n"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KlyP4s8qGV+/YsYPvv/+euLg41Go1bdq0YdSoUYwZM6ZGWmfqW0ETuOMiAB8MN9CZlGfM0O5XrFA2h6hxN27cIDw8XNfhH7QjMQcNGkTDhg0VTCYeV2Z+Jvt+38fu+N3sTthNQnpCheeZqkzxdvbG181Xt3Vy6UQDC1mHT0kGV9CI6qlvBc3otdp5XrZM7qVwkkr076/dHzigZApRg0pKSjh48CCHDh2i9GPTwcGBYcOG0aZNG4XTiUcVfzeebZe2sf3Sdo5dP1Zh3xc7Czv8mvvRu3lverfoTY8nekjxYoAMpg+NEEIYqrS0NLZt26abosHExIQ+ffrQt29fzMzkY7Qu0Wg0nE89z7aYbYRdCiMqJarcOZamlvRt2Zdn2zzLoDaD6OTSCVMT6Q9l6OR/ohBCVEKj0XDy5El2795NcXExoF1qZeTIkbi6uiqcTjyMm9k32Ri1ke/OfUf07ehyx590eJIR7Ufw3JPP0bdFX6zN9TvNh6h5UtAIIUQFCgsL2bFjBxcuXNA916tXLwYMGCCtMnVEXlEeP8b+yHfnvmN3/G7UGnWZ411cu+Dv4c/IDiPxcvKqV3O2GCP5XynqhDZOBr50RPv2SicQepSWlkZoaKhuJeyGDRsycuTIcqMshWFKSE9g9YnVfHPmm3LDqjs4dmB85/GM9hpN68atFUooaoIUNKJOWOJf8ZB8g/HVV0onEHoSExPD9u3bKSwsBKBNmzb4+/vLemwGTqPRsCdhD/+K/Bc/x/2Mhv8b79LYqjFjvMcwocsEujXtJi0xRkoKGiGEQPsD8fDhw+zbt0/3XN++fenfv79MjGnAStQlbI3Zyj8P/5MzyWfKHOvfqj/vdHuHEe4jsDSTuYGMnRQ0ok54P0w7EsFgW2omTdLupaWmTiopKeHnn3/mzBntD0RLS0tGjhyJu7u7wslEZYpKivju3Hd8cuQTrty9onvextyG8Z3GM7XHVLydyy+VI4yXFDSiTki4rZ/VZ2tMXOUziArDlp+fT2hoKL///jugXUxy7NixODk5KZxMVEStUbP5wmYW7l9IfHq87nlHG0em95zOO93fwcG64klYhXGTgkYIUW9lZ2cTHBys6/zbtGlTxowZo9f13oR+aDQadsTtYN6+eVxI/b+RZ80bNmeW3ywm+kzE1kL6OdVnUtAIIeqljIwMNmzYQHq6dhSMh4cH/v7+mJubK5xM/Nn5lPPM+GUG+37/v/5NLrYuzO83n7d835L+MQKQgkYIUQ/duXOHDRs2kJWVBUDXrl0ZOnSodP41MHfu3eGDAx+w+uRq3Rwy9lb2zO49m7/2+Ku0yIgypKARdYJnUwNf9K9LF6UTiGpKTU0lODiYnJwcQDtZ3uDBg2UorwHRaDR8d+47Zu6eyd28u4B2Qci3u71N4DOB0kdGVEgKGlEnGOwq26Vkle06ITU1le+++4579+4B0K9fP/r37y/FjAFJSE9gcvhkfk34VffcgNYD+GLIFzJqSVRJChohRL1w9+5dgoODdcXMwIED6dOnj8KpRKkSdQkrjq1gwf4F5BXnAeDWwI0vn/+SUR1GSdEpHkgKGlEnzNisnR9kxf/zUThJJV5/XbvfuFHZHKJCWVlZZW4zSTFjWBIzEhm3bRyHrh3SPTfJdxKfDP4Eeyt7BZOJukQKGlEn3MrMVzpC1a5fVzqBqERubi7BwcFkZGQA0KdPHylmDMim85t4++e3ySrQdtB+0uFJvh7+NU+3elrhZKKukYJGCGG0CgoK2LhxI2lpaQB0796dAQMGKJxKAGQVZPHOz+/w/fnvdc9N6TqFz577DBtzGwWTibpKChohhFEqKSnhv//9L8nJyQB07tyZ559/XvpiGICLqRfxD/Un7o52hm1HG0fWj1jPcPfhCicTdZkUNEIIo6PRaNi5cyfx8dqp8du3b8+IESOkmDEAmy9sZuJPE7lXpO2c/Vzb5/j2pW9xbeCqcDJR10lBI+oE35aNlY5QtV69lE4g7hMREcGpU6cAcHV1ZdSoUTJpnsKKSop4b897rDiuneJAhYpF/Rcxv998TFTydyMenxQ0ok6YPcRD6QhVW7JE6QTiD5cuXWLPnj0A2NnZMWbMGCwsLBROVb9l5GfwcujL7P19LwCNrRrzvf/3PN/ueYWTCWMiBY0QwmjcunWLrVu3AmBhYcFrr71Gw4YGPsu0kUtIT2DYpmFcSrsEgI+rD1tf3Urrxq0VTiaMjRQ0ok6YEqy9fbBmXFeFk1Ri1Cjt/o8fpqL25eXlERoaSnFxMSqVipdffhlXV+mXoaSIpAhe3Pwit+9pVzMf6TGSjf4bZRSTqBFS0Ig6If1eodIRqnbnjtIJ6jWNRkNYWJhurpmBAwfSrl07hVPVb1ujtzI2bCwFJQUA/MPvH/xz0D+lv4yoMVLQCCHqvN9++40rV64A0KFDB/z8/BROVL+tP7Oet3a8hVqjxlRlyuphq3mr61tKxxJGTgoaIUSddvnyZX777TcAmjRpwosvvijDsxW0PGI5f9/9dwBszG0IezWM5558TuFUoj6Qtj+F5ebm0q9fP9zd3Tl//rzScYSoUzIyMggLCwPA3NycV199FUtLS4VT1U8ajYaF+xfqihl7K3v2jNsjxYyoNdJCo7CVK1dSUlKidAyD1/tJR6UjVG3gQKUT1DtqtZqtW7eSn69d52vEiBE4OzsrnKp+0mg0zNo9i8+PfQ6As60zu1/fTWfXzgonE/WJFDQKiouLY/PmzcyZM4eFCxcqHcegTRto4B08FyxQOkG9c/DgQa7/sShot27d8Pb2VjhR/aTRaJjz6xxdMdOiUQt+Hfcr7ZoY+P9ZYXSkoFFQUFAQY8eOpVWrVkpHEaJOSUpK4uDBgwA4OTnx7LPPKpyoftJoNCzYv4BPj34KQCv7Vvw24TdaNGqhcDJRHxlMQTNnzhy2bdtW6fHWrVuza9euGnv/hIQEDh06xPnz57lw4QJXr15Fo9HwxRdfMGTIkAdev2PHDkJCQoiNjUWtVtO6dWtGjRrFmDFjKpxyffv27SQmJrJ27VouXLhQE9+SUQlYHwnAd3/poXCSSjz/x4ynO3cqm6MeKCgoICwsDI1Gg6mpKaNGjcLc3FzpWPVS0G9BfHzoYwCaN2zO/oD9UswIxRhMQVPK19eXli1blnveycmpRt83JCSEDRs2PNK1gYGBbNq0CUtLS3r16oWZmRkREREEBQURERHBl19+Waaoyc7OZunSpcyePRtbW1t9fQtGLb/IwPsZ5eUpnaDe+N///qebb2bQoEG4uLgonKh++ufhf7Lot0UAPGH3BPsD9tPKvpWimUT9ZnAFzSuvvIK/v3+tv2/79u2ZOHEi3t7eeHt7M2/ePCIjIx943S+//MKmTZtwcnJi48aNuttHaWlpjB8/nj179hAcHExAQIDumhUrVtCyZUtGjBhRU9+OEEbpwoULREVFAdC2bVt69uypcKL6af2Z9by/930A3Bq4sS9gH20d2iqcStR3dX7Y9s2bN1m7du0Dz4uOjmbLli2VHn/llVd47733GDp0KC1aVL/JtPS9Z82aVaYvjKOjI4sWLQJg3bp1qNVqQDtnxubNm5k+fTpZWVlkZWVx7949AO7du0dOTk6131uI+iQ3N5edf9zSs7GxkflmFBIeF86kHZMA7SKTv47/lfZN2iucSggDbKF5WPPmzePo0aOkpqYyf/78Cj/goqKimDhxItnZ2XTp0gV3d3e9vHdycjIXL17E3Ny8wn42PXr0wMXFhZSUFM6ePYuvry+JiYkUFxczfvz4cuePHz8eDw8PfvzxR73kE8KY7Nq1S1f8Dx06FDs7O4UT1T9Hk47y6n9fpURTgrWZNeGvhePp5Kl0LCEAAyxojh8/TmxsLPfu3aNJkyZ07dqV3r17V9ixFmDJkiUEBASwceNGCgsLCQoKKlPUnDp1ikmTJpGbm8uiRYv0VsyAttUHoF27dlhZWVV4TseOHUlJSSEmJgZfX198fX3L9dWJiYlhyZIlBAYG4uXlpbd8xmRgBwOfX+SFF5ROYNQuXbqk6zzv4eGBp6f8EK1t0bejeWHTC+QV52GqMmXLy1vway5LTAjDYXAFzfbt28s99+STT/L5559XWIy4urrq+qiEhoZSVFTE4sWLMTEx4fjx40yZMoX8/Hw++ugjXn75Zb1mLZ0Do2nTppWe4+bmVuZcBweHSu/7e3l50bFjR71mNBaT+hn4/flZs5ROYLTy8vL4+eefAbCysmLo0KFyq6mWpeamMvT7oaTnpwOw9oW1DHcfrnAqIcoymILGw8OD+fPn4+fnh5ubGzk5OURHR7N8+XIuXbrEG2+8wbZt2yoc0eDs7ExwcDATJkxg27ZtFBUVMWLECKZNm0ZRURFLlizhpZde0nvm0uZva2vrSs8pHcWUm5v72O+3ZcsWXT+g9PT0x349IeqC3bt36/qWPffcc3KrqZYVFBfgv8WfxMxEAIL6BzHRd6LCqYQoz2AKmgkTJpT52sbGBmdnZ/z8/Bg3bhxnz55l7dq1lc6o6+joyIYNG3jjjTcIDw8nPDwcMzMzli5dyrBhw2rhO3h0PXv2JDY29oHnjR49mtGjRwMoMhJMSaPXRgCwZXIvhZNUon9/7f7AASVTGJ34+HjOnj0LaFtqO3eWqfRrk0ajYcrPUziSdASA1zu9zvx+8xVOJUTFDH6Uk4WFBZMmaXvUl66oWxkHB4cyw6M9PT0ZPHhwjWWzsbEBtE3ilSltmZH5ZoR4OMXFxbpbTRYWFrzwwgtyq6mWLTu6jG/PfgvAU82eYt3wdfJ3IAyWwRc0AG3atAEgJSWlyvN27tzJggULsLCwwN3dnaioKKZOnUpBQUGN5HriiScA7dDxyiQnJ5c5VwhRPUeOHNHdWn3mmWdo1KiRwonqlx2xO5j962xAOwvw9tHbsTKrePCDEIagThQ0pbOCVtXK8dNPPzFz5kzMzMxYvXo1ISEhdO/enYMHDzJ58uQqW1EeVelIi8uXL+tW/P2z8+fPA9ChQwe9v78Qxio9PZ3Dhw8D4OLiQo8eBrrkhZGKuxPH2LCxaNBga27LjjE7cGkgMzILw1YnCprSybQqW003LCyM2bNnY2lpydq1a+nTpw+2trasW7cOPz8/IiIidEO39cnNzQ0vLy+KiooqXGcqMjKS5ORknJyc8PHx0et7C2GsNBoNO3fupLi4GIBhw4ZVOm2D0L/cwlxGhY4iuzAbgOCRwXR2lb5LwvAZxKdETEwM+/fvp6Sk7Ho9xcXFrF+/nuDgYKB8x2GA0NBQ5s6di7W1NV9//TVPPfWU7pi1tTVr1qyhX79+REZG8uabb+p9Jt7S/j3Lli0jMTFR9/ydO3cIDAwE4K233pIP5Mf0Qic3XujkpnSMyr36qnYTjy0uLo7Lly8D0KVLF5o3b65wovqjtBPwhVTtnD9zes9hZIeRCqcSonoMYpTTjRs3mDp1Kvb29nh6euLg4EBGRgZxcXGkpqZiYmLCP/7xD/r27Vvu2vj4eOzs7Pjmm2/o1KlTueOWlpasWrWKGTNmcOnSJbKysmjQoEG58y5evKgrQACuXLkCwPLly1m/fr3u+dDQ0DLXDRkyhDFjxhASEsLw4cPx8/PTLU6Zk5PDoEGDeP311x/5z0ZojevVSukIVXvnHaUTGIWioiJdi6yVlRWDBg1SOFH9subkGjZGbQTgmVbP8OGADxVOJET1qTQajUbpEElJSWzYsIHz589z48YNMjIyUKlUuLq60rVrV8aOHVvp7SbQdsqtanI70Lb23L17F2fnimecPX78eIXLEfxZZcOrd+zYwffff09cXBxqtZo2bdowatQoxowZUyOtM/7+/oSFhen9dQ1VXqG29c7awlThJJX4Y04i/hj5Jh7N/v37OXjwIKBd3qB79+4KJ6o/Im9E0md9H4rURTS1a8rpSael34yoUwyioBEPr74VNDIPjfHLzMxk5cqVFBcX4+bmxptvvim3amtJRn4Gndd05lrmNcxMzDgQcIDeLXorHUuIhyKfFkIIg7Bv3z5dR+DnnntOiplaotFomBw+mWuZ1wBYOnipFDOiTpJPDCGE4m7evElUVBSgneKgZcuWCieqP749+y2hF7V9A4e1G8b0ntMVTiTEo5GCRq0hTMoAACAASURBVAihKI1Gw+7duwEwMTGRjsC1KO5OHH/d+VcAXBu48p8X/yMzAYs6SwoaIYSiYmNjdVMe9OjRAwcHB4UT1Q+FJYWM2TqG3CLt/FwbXtqAk62TwqmEeHQGMWxbiAd5uWszpSNUrYI5ksSDlZSUsGfPHkA7TLtfv34KJ6o/5u2dx+lbpwH4h98/GNy25ta9E6I2SEEj6oRXuhn45GpS0DySEydOcPfuXQCefvpprK2tFU5UPxxMPMhnEZ8B0NWtKx8N+EjhREI8PrnlJOqEu7mF3M0tVDpG5dLStJuotoKCAg4dOgSAg4ODzDlTS3IKc3jjxzfQoMHKzIrv/b/HwtRC6VhCPDZpoRF1wtsbTwEGPA/Nyy9r9zIPTbUdO3aMe39MSDhgwABMTQ100kQjM3vPbBLSEwBYMnAJ7o7uCicSQj+khUYIUevy8vKIiNBOlujq6qpbuV7UrL0Je/n3yX8D0K9lP6b1nKZwIiH0RwoaIUStO3LkCAUFBYC2dUaGCte8rIIs/vLTXwCwNbflPy/+BxOV/AgQxkP+NQshalV2djbHjx8HoHnz5jz55JMKJ6ofZv4ys8xswG0at1E4kRD6JQWNEKJWHTp0SLfEwcCBA6V1phbsTdjL12e+BmBQm0FM6TZF4URC6J90ChZ1wutPGfhU+G+/rXSCOiE9PZ1Tp7QdvNu2bStLHNSCvKI8JodPBrS3mr4e/rUUkcIoSUEj6oThnZsqHaFqo0crnaBOOHjwIGq1GtD2nRE178ODHxKfHg/ARwM+oqW9FJHCOOmloDl69CiXLl2iadOmDB48WIZfCr27mZEHQFN7A514LSlJu29u4BMAKig9PZ1z584B4OHhQdOmBl6kGoGolCiWHl0KQLem3fhrj78qnEiImlPtgiY0NJRvv/2WoKAgunXrpnt+/vz5bN26Vfd1t27dWL9+Pebm5vpNKuq1v205CxjwPDTjxmn3Mg9NpQ4dOoRGowG0swKLmlWiLuGtHW9RrC7GVGXKuuHrMDWRXzaF8ap2p+Ddu3eTlpZG586ddc+dOXOGH374ARsbG4YPH06zZs04efIk4eHhNRJWCFE3ZWRk6Fpn3N3dcXV1VTiR8Vt1YhWRNyIBmNlrJl1cuyicSIiaVe2CJj4+nnbt2pVpefn5559RqVR8/vnnfPrpp4SGhmJlZUVYWFiNhBVC1E1HjhzR9Z2RBShr3vWs68zbNw+ANo3b8EH/DxROJETNq3ZBk56ejouLS5nnTp48ScOGDXXNx40bN6Zbt25cu3ZNvymFEHVWVlYWZ86cAaBdu3bSd6YWzNo9i5zCHADWDFuDjbmNwomEqHnVLmjUajWFhf+3OGBeXh6XL1/G19e3zHn29vakp6frL6EQok47cuQIJSUlgLTO1Ia9CXvZcnELAK96vcrgtoMVTiRE7ah2p2BXV1diYmJ0X5d+SP25oMnOzqZhw4b6SygE8FZfA5/VdOZMpRMYpOzsbE6fPg1AmzZtaNasmcKJjFthSSF/3akdyWRrbstnz36mcCIhak+1C5o+ffoQEhJCYGAgffr0YdmyZahUKp555pky58XExEiTstC7QZ4uDz5JScOHK53AIB09elQ3K7CMbKp5Xxz7gpg07S+eC59eSLOGUkCK+qPat5ymTJlCkyZNCAkJ4d133+Xq1au88MILZdZhiY6OJiUlBR8fnxoJK+qv+Ns5xN/OUTpG5WJjtZvQycvL080K3KpVK1q0aKFwIuN2Pes6gb8FAuDh6MGMp2YonEiI2lXtFhpnZ2e2bdtGaGgod+7coVOnTrz44otlzomLi2PgwIE8++yzeg8q6re5YecBA56HZrJ2anmZh+b/nDhxgqKiIkDbwitq1qzds8gtygXgX8//CwtTC4UTCVG7HmqmYCcnJ6ZOnVrp8ZdeeomXXnrpsUMJIeq2oqIi3Yrarq6utGlj4H2g6riDiQfLdAQe1GaQwomEqH2y2rYQQu/Onj3LvXv3AOjdu7cshliD1Bo1f/vlbwBYm1mzbPAyhRMJoYyHLmgiIyOZNm0a/fr1w9vbm7lz5+qOHTlyhM8//5zbt2/rNaQQou5Qq9VEREQA2mkcPD09FU5k3Dac28DpW9qRZO/1fo/mjWQ9MVE/PVRB869//YuAgAB2795NamoqxcXFurVZAOzs7Fi3bh27d+/We1BjlZubS79+/XB3d+f8+fNKxxHisUVHR+vmourVqxcmJtIQXFNyCnOYu1f7S2VTu6b8w+8fCicSQjnV/qTZt28fq1atwtXVlS+++IKjR4+WO6dTp044ODiwf/9+vYY0ZitXrtRNOiYq99cB7fjrgHZKx6jc/PnarZ7TaDQcOXIEABsbGxnxWMM+PfIpt3JuAbB4wGJsLWwVTiSEcqrdKTg4OBgLCwu+/vpr2rZtW+l5Hh4esvRBNcXFxbF582bmzJnDwoULlY5j0Pq0c1Q6QtUGSSdMgN9//53k5GQAevToUWbtN6FfSZlJLDuq7S/T1a0r4zqPUziREMqqdgvNxYsX6dy5c5XFDICDg4P0oammoKAgxo4dS6tWrZSOYvAu3szk4s1MpWNU7uxZ7VbPlbbOmJub0717d4XTGLe5++aSV5wHwPLnlmOiklt7on6r9v+A/Px8HBwcHnheZqb+fuh8/vnnuLu74+7uzjfffKO3161IQkIC3333HbNmzWLIkCF4eHjg7u7Orl27qnX9jh07eO211+jatSs+Pj74+/vz/fff61YY/rPt27eTmJjI22+/rc9vw2gF7YgmaEe00jEqN2OGdqvHUlNTSUhIAMDHxwcbG1kQsaZE3ohkY9RGAEZ1GEXfln0VTiSE8qp9y8nJyUn3YVWVK1eu8MQTTzxWKICoqCi+/vprVCpVmY7HNSUkJIQNGzY80rWBgYFs2rQJS0tLevXqhZmZGREREQQFBREREcGXX35ZpmNkdnY2S5cuZfbs2djayj1vYRyOHTume/zUU08pmMS4aTQa/v7L3wGwMLXgk0GfKJxICMNQ7Raanj17cuXKFQ4fPlzpOf/73/+4efMmfn5+jxWqsLCQOXPm0KRJEwYOHPhYr1Vd7du3Z+LEiSxfvpw9e/bQo0ePal33yy+/sGnTJpycnPjpp59Yu3Ytq1atYvfu3bRt25Y9e/YQHBxc5poVK1bQsmVLRowYURPfihC1Ljc3l6ioKEDbj65x48YKJzJeP0T/wJEk7a29aT2m0dah6m4AQtQX1S5oJk6ciJmZGdOnT2fLli26YZmgXbNl+/btLFy4EGtra8aNe7zOaV988QXx8fEEBgZiZ2dX5bk3b95k7dq1D3zN6OhotmzZUunxV155hffee4+hQ4c+1Jozpe89a9asMn1hHB0dWbRoEQDr1q3T3Xq6fPkymzdvZvr06WRlZZGVlaWbgOzevXvk5BjwekVCVOLUqVO60Xo9e/ZUOI3xKiopYu4+7TBtRxtH5veTkXVClKr2Lae2bdvyz3/+kzlz5rBo0SICAwNRqVTs2LGD7du3A2Bqasqnn35K8+aPPrHTuXPn+M9//sMLL7zAgAEDHjinzbx58zh69CipqanMnz+/whlJo6KimDhxItnZ2XTp0gV3d/dHzne/5ORkLl68iLm5OUOGDCl3vEePHri4uJCSksLZs2fx9fUlMTGR4uJixo8fX+788ePH4+HhwY8//qiXfELUhpKSEk6cOAFolzlo2bKlwomM19env+bK3SsALOi3gEZWjRROJITheKi1nIYNG8aTTz7J6tWrOXz4MDk5ORQXF2NlZUWvXr2YOnUq3t7ejxymoKCA2bNn06hRI+bNm1eta5YsWUJAQAAbN26ksLCQoKCgMkXNqVOnmDRpErm5uSxatEhvxQxoW30A2rVrh5WVVYXndOzYkZSUFGJiYvD19cXX17dcX52YmBiWLFlCYGAgXl5eestnTN4bor+/txqxeLHSCRRz8eJFXctiz549ZZmDGpJbmEvQwSAAWtm3YnLXyQonEsKwPFRBA+Du7s6KFSvQaDSkp6ejVqtp3Lgxpqamjx1m+fLl/P777yxfvrxaI6pA+xthcHAwAQEBhIaGUlRUxOLFizExMeH48eNMmTKF/Px8PvroI15++eXHzni/69evA9C0adNKz3FzcytzroODQ6VN8l5eXnTs2LHS19qyZYvuttn9t/zqg64tq/fvQTGP2W+srtJoNLpFKG1tbR/rFxpRtRXHVpCco53j58NnPsTSzFLhREIYlocuaEqpVKpqFx3Vcfr0ab777jsGDRrE0KFDH+paZ2dngoODmTBhAtu2baOoqIgRI0Ywbdo0ioqKWLJkSY2sAl7a98Xa2rrSc0pHMeXm5j72+40ePZrRo0cD4O/v/9ivV5ecSrwLGHBhUzpzdj0rbJKSkrh58yYA3bp1w8zskT9SRBXu3LvDp0c/BaCTSyde6/iawomEMDx6+fQ5evQoly5domnTpgwePPihW2vy8/N5//33adCgAR988MEjZXB0dGTDhg288cYbhIeHEx4ejpmZGUuXLmXYsGGP9Jq1pWfPnsTGxiodw6B9ukv757Nlci+Fk1SidJHWAwcUjVHbSltnTE1N6datm8JpjNfiQ4vJKsgCYMnAJTKJnhAVqPb/itDQUIYOHcrJkyfLPD9//nwmTpzI0qVL+dvf/saECRMoKip6qBCff/45V69eZc6cOTg7Oz/UtfdzcHAgICBA97WnpyeDBw9+5Nd7kNKJw/Ly8io9p7RlRuabEcYmIyODmJgYQNtXrEGDBgonMk7XMq+x6sQqAPq26MvzTz6vcCIhDFO1W2h2795NWloanTt31j135swZfvjhB2xtbRk4cCBnzpzh5MmThIeHM3LkyGqH+PXXXzExMWH79u26EVOlSifzCwkJ4cCBA7Ro0YKPP/64wtfZuXMnCxYswMLCgtatWxMVFcXUqVNZuXIllpb6v99cOoFgaZN7RUrXtdHHZINCGJLIyEjdpJcyVLvmLDqwiIKSAgA+GfSJdLoWohLVLmji4+Np165dmcXmfv75Z1QqFZ9//jlPP/006enpDBgwgLCwsIcqaADUajWRkZGVHk9KSiIpKYmsrKwKj//000/MmTMHc3NzVq1ahY+PD5MnT+bgwYNMnjyZ1atXV9nX5VF4enoC2rll8vPzKxzpdP78eQA6dOig1/cWQkmFhYWcPn0agFatWuHq6qpwIuMUfTua7859B8CL7i/Sq7mB3nIVwgBU+5ZTeno6Li4uZZ47efIkDRs25OmnnwagcePGdOvW7aFX2963bx+xsbEVbqWF0XvvvUdsbGyFc7SEhYUxe/ZsLC0tWbt2LX369MHW1pZ169bh5+dHRESEbui2Prm5ueHl5UVRUVGFaz5FRkaSnJyMk5MTPj4+en1vIZR07tw5Cgq0rQbSOlNz5u6di1qjxkRlwuKB9XdqACGqo9oFjVqtprCwUPd1Xl4ely9fxtfXt8x59vb2tTqkODQ0lLlz52Jtbc3XX39dZg0Za2tr1qxZQ79+/YiMjOTNN9/U+0y8kyZNAmDZsmUkJibqnr9z5w6BgYEAvPXWW2XWchIPb+FwTxYO91Q6RuVWrNBu9YBGo9H1pWvUqBHt27dXOJFxOnHjBD/Gan+BC+gcgKeTAf/7F8IAVPuWk6urq64DIMCRI0coKSkpV9BkZ2fTsGFD/SV8gPj4eOzs7Pjmm2/o1KlTueOWlpasWrWKGTNmcOnSJbKysirsvHjx4kVdAQLaRTZBOzfO+vXrdc+HhoaWuW7IkCGMGTOGkJAQhg8fjp+fn25xypycHAYNGsTrr7+ur2+33vJqauAzonbponSCWnPt2jVSU1MB7VBtKdZrxgcHtCM+zU3M+eDpRxv9KUR9Uu2Cpk+fPoSEhBAYGEifPn1YtmwZKpWKZ555psx5MTExVU40p2/vv/8+AQEBVb6nhYUFX375JXfv3q10FFVOTg7nzp0r9/zVq1cfmGHRokV07dqV77//nsjISNRqNW3atGHUqFGMGTNGPvD14PDlNAD6tHNUOEklfv1Vux80SNkctaC0dcbU1FRupdaQiKQIdl7ZCcCbvm/S0l6WkxDiQVSa0mEKD5Camoq/vz9paWmoVCo0Gg3Dhw9n6dKlunOio6Px9/cnICCA999/v8ZCC+3EemFhYUrHqDWj10YABjwPTf/+2r2Rz0OTk5PD8uXLUavVdOzYsd5N8FhbBgcP5teEX7EwtSB+WjzNGjZTOpIQBq/aLTTOzs5s27aN0NBQ7ty5Q6dOnXjxxRfLnBMXF8fAgQN59tln9R5UCKG806dP61aO7969u8JpjNPBxIP8mqBt8ZvcdbIUM0JU00PNFOzk5MTUqVMrPf7SSy/VyBIDQgjlqdVqTp06BWj71DVrJj9oa0Jp3xkrMyve7yMt3UJUl3TuEEJUS1xcnG4eqG7duskEbzVg/+/7OXD1AADvdHsHNzs3ZQMJUYc88lpO2dnZ5OTkUFkXnNrsGCyEqHknTpwAtCMHq1oVXjwajUbDgv0LALAxt+G93u8pnEiIuuWhCpqMjAy++OILdu/ezd27dys9T6VSER0d/djhhCi12N/Af4CuXat0ghp1584d3TIknTt3xsLCQuFExmdPwh6OJB0B4N3u7+LSwOUBVwgh7lftgiYzM5NXX32VpKQkTE1NsbKyIi8vDycnJ9LS0tBoNKhUKtzcpIlU6F9bJwNf+NDdXekENaq0dQakM3BN0Gg0LNy/EIAGFg34R+9/KJxIiLqn2n1o1q1bx7Vr1/D39+fkyZM899xzqFQqDh06xOnTpwkKCqJRo0Z07dqVffv21WRmUQ/9Gp3Cr9EpSseo3I4d2s0IFRYWcvbsWQBat26No6OBzgVUh+28spPjN44DML3ndBxt5M9YiIdV7Raa/fv34+DgwAcffICFhUWZDoHW1ta8+uqrdOjQgdGjR9OlSxfGjh1bI4FF/bTukPZ2xyBPA22G/+wz7X74cGVz1IALFy7o1m2S1hn9u791pqFlQ/7e6+8KJxKibqp2C82NGzfw9vYud++8pKRE97hjx4507dqVrVu36i+hEEJRpUO17ezscDfyW2tK+Cn2J07d0v4Z/+2pv+Fg7aBwIiHqpmoXNCYmJmXWQLKxsQEotxCls7NztZYLEEIYvuTkZG7evAmAj4+PLOOhZxqNhkW/LQLA3sqeGU/NUDaQEHVYtT+dnJ2duXXrlu7rJ554AtAu6ni/+Ph4GQEhhJE4ffq07rGs26R/4XHhnE3W9k/621N/w97KXuFEQtRd1S5ovLy8SEhI0N1i6tWrFxqNhmXLlhEfH09OTg5fffUVly5dwsPDo8YCCyFqR1FREefPnwegbdu22NvLD1t90mg0fHjwQ0Dbd2Zaz2kKJxKibqt2p+C+ffvy888/c+jQIfr370+HDh145pln2L9/Py+88ILuPJVKVeXyCEI8iuWjuygdoWrBwUon0LuYmBjy8/MB8PX1VTiN8dkdv5sTN7XD4af1mCatM0I8pmoXNC+88AK9evUq04/ms88+47PPPuOXX34hIyODNm3aMHXqVBkJIfSuqb210hGq1ry50gn0rvR2k42NjXQG1rP7W2caWDSQvjNC6EG1CxozMzNcXMoOmbWxsWHBggUsWLBA78GEuN+Oc9qOqcM7G+iSGlu2aPejRyubQ0/u3LlDYmIioJ0Z2NTUVOFExuXA1QO6WYHf6fYOTWyaKJxIiLrvkddyEqI2bTym/eFqsAXN6tXavZEUNPd3BpbbTfpX2jpjbWbNTL+ZCqcRwjhUu1NwZmYmJ06cICWl8tlaU1JSOHHihG5FXiFE3VNSUsK5c+cAaNGihcwMrGdHrh1h/9X9AEzuOhlnW2eFEwlhHKpd0GzYsIHx48dz+/btSs+5ffs248ePZ+PGjXoJJ4SofXFxceTm5gLSOlMTSltnLE0tZc0mIfSo2gXNgQMHaNGiBd7e3pWe4+3tTYsWLThw4IA+sgkhFFB6u8nS0hJPT0+F0xiXyBuR/BL/CwBv+r5JUzsDvYUqRB30UEsftG7d+oHntW7dmuvXrz9WKCGEMjIzM7ly5QqgXcrE3Nxc4UTGpbR1xtzEnNm9ZyucRgjjUu1Owbm5udja2j7wPFtbW7Kzsx8rlBB/tvr1rkpHqNoPPyidQC/OnDmjeyy3m/TrzK0zhMeFAzChywSaNzK+of5CKKnaBY2TkxNxcXEPPO/y5cs0btz4sUIJ8WcOtga+nIYRdJxVq9WcPaudht/NzQ03NzeFExmXjw59BICpypQ5feYonEYI41PtW04+Pj5cuXKF3377rdJzfvvtN+Li4uja1cB/mxZ1zn9PJvHfk0lKx6jct99qtzosISGBzMxMQFpn9O1C6gXCYsIAeL3T67Rp3EbhREIYn2oXNAEBAQD8/e9/JzQ0lMLCQt2xwsJCQkNDmTlzJiqVinHjxuk/qajXfjh1nR9OGXDfLCMoaEo7A5ubm9OxY0eF0xiXjw99DICJyoS5fecqnEYI41TtW06dOnVixowZLF++nA8++IAPP/yQpk21PfRv3bpFUVERGo2GadOmyW93QtQxubm5xMbGAtqFaC0tLRVOZDxi02LZckE7k/Ror9G0b9Je4URCGKeHmil48uTJtGnThpUrVxIbG6ubGh3A3d2dd999l8GDB+s9pBCiZp09exa1Wg1oby8L/Vl8eDEaNADM6ztP4TRCGK+HXvpg8ODBDB48mLS0NG7e1K6v07RpU5lNVIg6SqPR6EY3OTo60twIF9pUSkJ6At9HfQ/AqA6j8HL2UjiREMbrkddycnR0lCJGD3Jzc3n++edJSUnhhx9+kL4LotZdu3aNO3fuANrOwCqVSuFExuOTw59QoikBYH6/+QqnEcK4yeKUClu5ciUlJSVKxzB4377RQ+kIVfvf/5RO8MhKOwObmJjQqVMnhdMYj+tZ1/n23LcAvND+Bbq4dlE2kBBGrtqjnIT+xcXFsXnzZqZNm6Z0FINnbWGKtYWp0jEqZ2Oj3eqY/Px8oqOjAejQoUO1Js8U1bPs6DIKS7SjQaXvjBA1TwoaBQUFBTF27FhatWqldBSDFxxxleCIqwqnqMK//63d6pioqCiKi4sB6QysT6m5qXx16isABrYeyFPNnlI4kRDGz2BuOQUHB3Py5Eni4uK4e/cuOTk52NnZ4eHhwciRIxkxYkSN3ttPSEjg0KFDnD9/ngsXLnD16lU0Gg1ffPEFQ4YMeeD1O3bsICQkhNjYWNRqNa1bt2bUqFGMGTMGE5PydeP27dtJTExk7dq1XLhwoSa+JaMSHnULgHG9WikbpDKhodr9O+8om+MhaDQa3e0me3t72rSRyd70ZXnEcvKK8wBpnRGithhMQbNu3Tru3r1Lu3bt8PHxwdramps3b3Ls2DEiIiL45ZdfWLlyZYXFgT6EhISwYcOGR7o2MDCQTZs2YWlpSa9evTAzMyMiIoKgoCAiIiL48ssvy+TOzs5m6dKlzJ49W5r4hWJu3bpFSkoKoG2dkc7A+pGel86qE6sA8GvuR/9W/ZUNJEQ9YTAFzeeff46npyc2f+qHcPnyZSZMmMDevXvZtm0bo0aNqpH3b9++PRMnTsTb2xtvb2/mzZtHZGTkA6/75Zdf2LRpE05OTmzcuFF3+ygtLY3x48ezZ88egoODdTMtA6xYsYKWLVsyYsSIGvlehKiO0tYZlUpFly7SYVVf/hX5L7ILtQv0zu87XwpFIWqJwfSh6datW7liBqBdu3a89tprABw9erTc8Zs3b7J27doHvn50dDRbtmyp9Pgrr7zCe++9x9ChQ2nRokW1c5e+96xZs8r0hXF0dGTRokWAtvWpdNKyy5cvs3nzZqZPn05WVhZZWVncu3cPgHv37pGTk1Pt9xbiURUWFnL+/HlA+3+sYcOGCicyDtkF2aw4tgIAXzdfhjz54NvVQgj9MJgWmqqYmWljWliUX3F53rx5HD16lNTUVObPr/i3oaioKCZOnEh2djZdunTB3d1dL7mSk5O5ePEi5ubmFfaz6dGjBy4uLqSkpHD27Fl8fX1JTEykuLiY8ePHlzt//PjxeHh48OOPP+olnxCViY6O1q3HJp2B9WfNyTWk56cD2r4z0jojRO156ILmzJkzREREkJqaSkFBQYXnqFQqFi9e/NjhAJKSkti8eTMAAwYMKHd8yZIlBAQEsHHjRgoLCwkKCirzIXLq1CkmTZpEbm4uixYt0lsxA+iGu7Zr1w4rK6sKz+nYsSMpKSnExMTg6+uLr69vub46MTExLFmyhMDAQLy8ZCbRimyZ3EvpCFU7cEDpBA+l9HZTgwYNaNeuncJpjENeUR6fRXwGgKeTJy95vKRwIiHql2oXNIWFhcyYMYP9+/cD2hESlXmcgmbr1q2cOHGCoqIiUlJSOHPmDGq1milTplS4TpSrq6uuj0poaChFRUUsXrwYExMTjh8/zpQpU8jPz+ejjz7i5ZdffqRMlbl+Xbv6c+kinRVxc3Mrc66DgwM9e/as8FwvL68qZwresmWL7rZZenr6I2UW4vbt2yQlJQHQpUsXTE0NeH6fOuSbM9+QkqvtZD23z1xMVAZzR1+IeqHaBc2//vUv9u3bh42NDS+++CJt2rShQYMGeg90+vRptm3b9n8BzcyYPn06b7zxRqXXODs7ExwczIQJE9i2bRtFRUWMGDGCadOmUVRUxJIlS3jpJf3/tlTa98Xa2rrSc0pHMeXm5j72+40ePZrRo0cD4O/v/9ivV5d8dTAegEn92iqcpBLLlmn3s2Ypm6MaSltnQG436UthSSGfHPkEgLaN2zLae7TCiYSof6pd0Pzvf//D2tqaH374oUbnq/j444/5+OOPyc/P5/r162zdupWVK1eyc+dOvvrqK1xcXCq8ztHRkQ0bNvDGG28QHh5OeHg4ZmZmLF26lGHDhtVYXn3o2bMnsbGxSscwaHtjUgEDLmjCw7V7Ay9oiouLGpASwwAAIABJREFUOXfuHACtWrXCwcFB4UTGYcO5DVzP0rbCzukzBzOTOtE9UQijUu020dTUVLp27Vprk29ZWVnx5JNPMnv2bP7+979z6dIlPvzwwyqvcXBwKDM82tPTs8LbVPpSOiorLy+v0nNKW2ZkvhlhCGJjY3X/Xn19fRVOYxyK1cX88/A/AWjWsBnjO5fv8C+EqHnVLmgcHBxq5BZTdYwcORKA/fv3U1RUVOl5O3fuZMGCBVhYWODu7k5UVBRTp06ttPPy43riiScA7dDxyiQnJ5c5Vwglld5usrKyokOHDgqnMQ5bLmwhPl17S/Q9v/ewMC0/GlMIUfOqXdA8/fTTnDlzRrfuS21q1KgRZmZmFBcXk5mZWeE5P/30EzNnzsTMzIzVq1cTEhJC9+7dOXjwIJMnT66yFeVReXp6Atq5ZfLz8ys8p3SuD/nhIZSWnp5OQkICAJ06ddJNhyAenVqjZvFh7QAIZ1tn3vR9U+FEQtRf1S5opk+fDmgXVCydv6K2nDhxguLiYho2bEjjxo3LHQ8LC2P27NlYWlqydu1a+vTpg62tLevWrcPPz4+IiAjd0G19cnNzw8vLi6KiInbt2lXueGRkJMnJyTg5OUnny8dkZW6KlbkBj8axttZuBuzMmTO6x3K7ST+2X9pO9G3t9A2zes3C2tyw/w0IYcwq/RVt5cqV5Z7r06cP//3vfzl8+DA9e/akadOmFU4cpVKpmDp1arVDnDx5kuzsbPr27Vvut8ZTp04xb552cbeXX3653BDT0NBQFi5ciI2NDevWraNr1666Y9bW1qxZs4Z3332XgwcP8uabb7Ju3Tq93jqbNGkS06dPZ9myZfj4+NCyZUsA7ty5Q2BgIABvvfVWja1BVV9895ceSkeo2s6dSieoklqt5uzZs4D29mdlnetF9Wk0Gj46+BEAja0aM6XbFIUTCVG/VVnQqFSqMvPNlH598+bNMkOr/3z8YQuaa9eu8f7779OwYUM8PT1xdHQkNzeXpKQkrly5AkD//v11rUT3i4+Px87Ojm+++YZOnTqVO25pacmqVauYMWMGly5dIisrq8KC5uLFi7oCBNC97/Lly1m/fr3u+dDSVZX/MGTIEMaMGUNISAjDhw/Hz89PtzhlTk4OgwYN4vXXX6/2n4UQNeHKlStkZ2vXF5LWGf3YdWUXZ5K1rV4znpqBnaWdwomEqN9UmkpmyKuoheZhvPvuu9U+NykpibCwME6ePElSUhJ3795Fo9Hg5OSEt7c3I0aMYNCgQZVef/PmzSontwPtcNW7d+/i7Oxc4fHjx49XuBzBn1U2vHrHjh18//33xMXFoVaradOmDaNGjWLMmDE10jrj7+9PWFiY3l/XUH259zIA0wYa6Ky2pSPwFixQNkclNm/eTGxsLBYWFsycObPCZURE9Wk0Gvr8pw9Hk45iZ2FH4oxEGluXvx0uhKg9lRY0wrDVt4Jm9NoIwICXQOjfX7s3wCUQsrOzWb58ORqNBh8fH1nlXQ8OXD3AM989A8Cc3nNYMmiJwomEENKxQwgjd/bsWd2t4/v7mIlHV9p3xtrMmr/1+pvCaYQQ8BAFTYcOHZg7d+4Dz5s/f75uOLMQQlkajUY3usnZ2fmBt2bFgx27foy9v+8FYFLXSTjbVnwbWwhRu6pd0Gg0mioXpPzzuUII5V29elW3kKmvr2+FoxLFw/n40McAWJhaMMvPsJe6EKI+0fvMWvfu3ZMJu4TeNbYx8E6sTZoonaBCpTMDm5qaVjgKUDyc07dOEx6nXbdrQucJNGvYTOFEQohSeqs81Go18fHxHDt2DFdXV329rBAArBln4H0/tm5VOkE59+7dIyYmBtDOal3VqvCieoJ+CwLAzMSMOX3mKJxGCHG/KguaP0/Xv337drZv3/7AF33xxRcfL5UQ4rFFRUVRUlICyNwz+nDm1hl+jP0RgIDOAbRu3Lpa15VOGZGZmanI0jFCGBozMzMaNWqEg4PD/2fvzuNizv8Ajr+6JSnpEJErg4gcJeeKtdjNrmO1jsJvV3atXXbXuY7FHqzddZ+bxTrKfeUKsYiUIxIhZ4ku6UKmmvn9MTuz0pROU/k8H495xHyvd0PTez7f9+f9KdE7OvmeSV1TvfwCtLKy4t1332XcuHElFqAgAPx66DoAk3o21nAkeZgyRfF1TtmYvvtyMbCZmZmqg7VQdLNPKkZndLR0+L7T6ydIgGLkOjo6GgMDA+rUqYO+vr6oYxLeanK5HKlUyuPHj4mOjsbW1rbEerXlm9Bcv35d9efGjRvTt29f5pSRN2zh7XLx/hNNh5C/oCBNR5BDTEwM8fHxADg6OopfosV0OfYyu68rRqc9W3hSv1r9Ah335MkTdHV1sba2Fv8GgoBicMTAwABra2sePHjAkydPqF5CNYgFTovGjBmTb7deQRDKjgsXLgCKN4+WLVtqOJry7+XRmamdphb4uPT0dExNTUUyIwiv0NLSwtTUtEQXjS7wzavCLGUgCILmvHjxgqtXrwIgkUhKdDHWt1FYXBg7IxRduT1aeNDArEGBj83IyKBy5cqlFZoglGuVK1fm4cOHJXY+0SlYECqYK1eukJmZCYhi4JKgnNlU2NEZUNTQlMZaboJQEWhrayOTyUrsfIUuLz548CD+/v7cu3eP9PR0tYXCWlpaHD16tEQCFAQAa5NKmg4hfzZlox+JXC5X3W4yMTGhQYOCjyYIuV2Ju8KOCMWU/CEOQ2ho1rDQ5xC3mwRBvZL+2ShwQiOTyfj6668JCAjIc7aTciaU+AEWStrCTxw1HUL+Nm7UdAQAPHr0iNjYWEBRDCxGB4pHWTujraXNtE7TNByNIAj5KfC7na+vL0ePHqVx48asWbOGHj16oKWlxaFDh1i1ahXvv/8+AKNGjRKjM4KgIS8XAzs6lvEksIwLjw9n+7XtAAxpPgS76nYajkgQhPwUeIRm7969GBgY4O3tjbm5OX5+fgDUrVuXunXr0qVLF9q3b8+0adNwcnKiVq1apRa08PaZ5acocv3BzV7DkeRB2Xtp4UKNhfDixQuuXLkCQKNGjahatarGYqkIfjz5I/Dv6ExnMTojCGVdgUdobt++TcuWLTE3N8/x/Mu3n/r370/Dhg3566+/Si5CQQCuPUzl2sNUTYeRt0uXFA8NCg8PF8XAJeRq/FW2Xd0GwODmg2lUvZGGI6qYXF1dkUgkSCQSjh8/nud+H3zwARKJhODg4DcYXelbsmQJEomEJUuW5Hg+ODgYiUSCh4eHhiIrnwqc0Eil0hzJjIGBAQBpaWk59mvUqJFqyqggCG+O8nZT1apVadiw8MWrwn9+PPkjcuSiduYNmj9/fonOeBHePgVOaCwsLHj8+LHq78rk5s6dOzn2S0xMVH1KFAThzXj48CGPHj0CRDFwcYXFhbHl6hYAPmn2CRJziYYjqvgMDQ25efMme/fu1XQoZYKDgwMHDhzg119/1XQo5UqB3/Xq1avH/fv3VX93dHRELpezevVq1W2n8+fPc+7cOerWrVvigQqCkLeLFy8Cohi4JEw/Ph1Q9J2Z2WWmZoN5SyhvrSxZsgSpVKrhaDTP0NCQBg0aULNmTU2HUq4UOKHp1KkTjx49IiwsDIB27dpRv359AgIC6NSpE/369WP48OHI5XIGDRpUagELb6f6FkbUtzDSdBh5a9RI8dAAqVSqKga2s7PDxMREI3FUBMEPgtl7QzFKMLzlcDGz6Q3p0aMHDg4OPHjwgM2bNxfq2MzMTDZu3MjHH39Mq1atcHBwoFevXvz+++88eVK4NeAePHiARCLB1dWVrKws/vzzT3r16kXz5s1p3749kyZNyrezbWRkJBMnTqRLly40a9YMZ2dnRo4cyYkTJwoVx+tqaJ48ecKiRYv46KOPaNWqFS1btqRHjx5MnjxZ9eHmwYMHNGnSBCcnJzIyMtSeJzMzk44dOyKRSIiMjCxUjGVRgRMaNzc35s2bp2qjrqOjw/Lly2nYsCGJiYlcu3YNmUzGkCFD+Pjjj0stYOHtNKefA3P6OWg6jLz9+afioQHh4eGqT7WiGLh4ph1X1Mvo6+gzo8sMDUfzdvn2228BWLlyZYHX93nx4gX/+9//+PHHH4mMjKRt27Z07dqVtLQ0vL296d+/P9HR0UWK55tvvmHx4sXUrFmT7t27o6+vz+7duxkwYECuUguAgIAA+vXrx549ezA2Nua9996jYcOGBAYG4uXlxcISmgF57do13NzcWL58OY8ePcLJyYkuXbpgYmLCvn372Lp1KwA2NjZ07dqVlJQU9u3bp/Zchw8fJiEhAScnJ+zsyn/yXuBp22ZmZvTp0yfHc3Xr1sXPz487d+6QkpKCra0tZmZmJR6kIAh5UxYDGxsbV4g3JU35594/HL2j6KHl1cqLOiZ1Sv2aMTExnDx5khcvXpT6tUqKgYEBnTt3LvHWHC4uLnTs2JHAwEDWrl1boPUDFy1aREhICPXr12fdunVYWVkBijW0Jk6ciL+/P+PHj2fLli2FiiUmJoaMjAx2796tKrCXSqVMnTqVvXv3MnHiRLZv367aPyEhgYkTJyKVSpk8eTIjRoxQbQsODmbUqFGsWLGC1q1b06lTp0LF8rKnT5/yxRdfkJCQwCeffMKUKVOoVOm/LupJSUk5ki0PDw8CAgLw9fVlwIABuc7n4+MDwJAhQ4ocU1lS6KUP1Klfv35JnEYQ8jRlp+JWZ5kdpfHyUnx9w6M0jx49Ug2Bi2LgopPL5Uw7phidMdQ1ZGrnwq3ZVFRnz57l5s2bb+RaJcnAwIB+/fqV+Hm//fZbTp8+zZo1axg8eHC+H5AzMjLw9fUFYNq0aapkBqBSpUrMnDmTU6dOcenSJS5cuEDr1q0LFcvo0aNzzBbU19dn+vTpHDt2jCtXruQ459atW0lPT6dVq1Y5khkAZ2dnhg4dire3N2vWrClWQrNt2zZiY2NxdHRk5syZubrym5mZ5XjNXFxcaNiwIeHh4YSFheHg8N/7540bNzh//jyWlpZ07969yDGVJUVOaO7fv09SUhKmpqbUq1evJGMShFzuJJTcEvOlQkO/lJT3y0HcbiqOQ7cOcTr6NABfOX1FjSo13sh127Vrh1QqLXcjNM7OzqVybnt7e3r16sWBAwdYsWIFU6fmnViGh4fz7NkzLC0t6dChQ67tZmZmuLq6sm/fPkJCQgqd0Lx6RwIULRG6du2Kn59fjnOeO3cOgL59+6o9V//+/fH29ubChQtkZ2ejo6NTqFiUTp06pTpfQZcYGjJkCLNmzcLHxydHQqMcnXF3d0dXt0TGNjSuUN9FVlYWK1euxMfHR1Vs9dFHHzFnzhxA0U3Yx8eH2bNn00hDBZKC8LaQSqWqIn1RDFx0crlcVTtjrG/MxA4T39i1a9WqJSZRvGLcuHEcPnyYzZs3M3z48DxvbcXHxwOKWpG8KLfFxcUVKoaqVavm2WlbGY9yzbSXz59XLLVq1UJbW5sXL16QnJxM9erVCxWPknI0tjCDCB999BHz58/nwIEDTJ48GVNTU9LT09m7dy96enoMHDiwSLGURQUen87KysLLy4tly5aRmppKgwYNci1S2apVKy5dusThw4dLPFBBEHISxcAlY9f1XVx8pBjp+tblW6pXLtovG6Fk2NraMmDAAKRSKYsXL37t/mVpMeTSjqUo569cuTL9+/fnxYsX7NihWDl+9+7dPHv2jG7dumFpaVnSYWpMgROajRs3cubMGVxcXDh27JjaqmkbGxtsbW0JDAws0SAFQchJLperhrmNjY3FiGgRZcuyVX1nzAzN+NblWw1HJAB8+eWXGBoasnfv3jxrjJS/iB88eJDneZTbXq6vKYjU1NRcXfCVYmJicp1T+ee8ZlTFxMQgk8kwMDAo1kiqtbU1AHfv3i3UcUOGDEFbW5vNmzcjk8lUtUcVpRhYqcAJzd69ezE1NWXhwoX5ZnT169fPMRQn5O/p06d07twZiUSi6iUi5Na0ZlWa1izDiy22bKl4vCExMTGqn7PWrVuLYuAi2hi2kWsJ1wCY1GESVQ3K8P+xt4ilpSWenp7IZDLmz5+vdp9mzZpRuXJl4uLiCAoKyrX9yZMnHDt2DAAnJ6dCx6Cua3FaWhr//PNPrnO2bdsWUIx8qLNz505A8bNanHoVZUHxjh07ct0hyU+dOnXo3LkzUVFRzJ8/n1u3bmFnZ1ek16UsK/C74N27d2nRosVrV/A1MjIiKSmp2IG9LZYuXUp2dramwyjzfnCzL7srbYNile03uNK2cnRGW1tb3G4qoueZz1W1MzWNazLG6fXThIU357PPPsPExITjx4+rHYWpVKkSn3zyCQA///yzqqYGFP1pZs6cybNnz2jZsmWhC4IBli9fzu3bt1V/z8zM5OeffyYtLQ17e3vatGmj2jZw4ECMjIy4cOEC69evz3Gec+fOsXHjRoBcM6AKa8CAAVhaWhIaGsqPP/6Yq5g8KSmJ8+fPqz126NChAHh7ewNUyNqtQqWKBbl/Fx8fr1q4UsjfzZs32bx5M5MnT2bGDNHESyiYp0+fqhaAbdKkCcbGxhqOqHxaHLyYB6mKX5Q/dv2RynqVNRyR8LKqVavi5eXFb7/9xvPnz9XuM27cOMLDwwkJCeG9997D2dmZSpUqcf78eRISEqhZsya///57oa9ds2ZN7O3t+fDDD2nXrh3GxsaEhoby6NEjqlWrxrx583Lsb2Fhwbx58/jmm2/4+eef2bZtG40aNSI+Pp7z588jk8n44osv6Ny5c5FeC6UqVaqwfPlyRo0axaZNm9i/fz+tWrXCwMCAhw8fcu3aNT744IMcyZZSx44dqVevHnfv3sXIyIgPP/ywWLGURQUeobGxseHGjRv5roaakZHBjRs3aNCgQYkEV9HNnj2bIUOGiLWvCmDc5lDGbQ7VdBh5GzpU8XgDQkNDVaN6yqFuoXASnyXyS+AvANhb2DOsxTANRySo4+HhQY0aeU+hNzAwYM2aNUybNo0GDRoQHBxMQEAAVapU4bPPPmPnzp3Url270NfV0tJi4cKFjB49mujoaI4ePcqLFy/o06cP27dvV7uafffu3dmxYwd9+vQhOTkZf39/bt68SYcOHfjzzz8ZN25coeNQp3nz5vj5+eHl5YWFhQVnzpzhxIkTpKSk4Obmphq1Uvc9tW/fHlDMfFJ2/a9ICjxC4+rqyp9//smaNWv47LPP1O6zevVqUlNTcXV1LVQQmZmZnD9/nhMnThASEsK9e/eQSqVUq1YNR0dHhgwZUmp9D5Tu3LnDqVOnuHLlCuHh4dy7dw+5XM6iRYvo2bPna4/38/PD19dXlfTVq1eP/v37M2jQILX1Dbt37+b+/fusWrWK8PDw0viWKpRHKerXIikz8ilMLEkymUw1pGxhYUGdOqXfzbYi+vnkz6S+SAVg3rvz0NEuWl8QoXiUNS55MTAweO06SHp6enh4eOS57lFR6erqMnr0aEaPHl3gYxo1asRvv/1W4P2/+uorvvrqq1zPOzs7c+PGjTyPq169Ot999x3fffddga8llUrx9/cHYPDgwQU+rjwpcEIzYsQIdu7cyR9//EFERATvvfceoCi8OnHiBIcOHWL37t1YW1sX+sU6d+6c6t6ihYUFbdu2xdDQkNu3b+Pv74+/vz+jR49m7NixhTpvYfj6+ua691lQyqZFBgYGuLi4oKurS1BQELNnzyYoKIjFixfnSGrS0tL47bffmDRpEkZGZXjBRaHMiYyMJCUlBVCMzpSlKavlxe2k2yw7twyArnW70qthLw1HJAilz8fHh8TERDp16qR2hKkiKHBCY2pqyurVqxk9ejT79+/nwIEDaGlpceLECU6cOIFcLsfa2pqVK1cWeihLS0uL9957D09Pz1z3/g4cOMD48eNZvnw5zs7OtGvXrlDnLqhGjRrx6aef0qxZM5o1a8bUqVMJCQl57XH+/v74+PhgYWHBxo0bVbePEhMT8fT05MiRI2zYsIFhw/4b0l64cCG2trZqO1EKQn6UozP6+vo5un4KBTf12FQyZZmAYnRGJIVCRXXnzh3++usv4uPjCQwMRE9Pj/Hjx2s6rFJTqKJgiUTCgQMH2LFjBydPnuTBgwdkZ2djbW1N586dGThwIJUrF76wzsXFBRcXF7XbevfuzenTp9m+fTt79+7NldA8fPgQPz8/Ro0ale81rl27xpUrV3B3d1e7vagrhK9atQqA8ePH56iFMTc3Z+bMmXh4eODt7Y2Hhwfa2tpERkayefNm1qxZQ2qqYsj72bNnqq/p6ekV8t6mUHxJSUncunULgBYtWoji+yIIiQlhy1XFQoWDmg2iTc3cxZOCUFEkJCSwfft29PX1ady4MePGjaNx48aaDqvUFHpCvIGBAYMHD36j9+CaNm0KqG9fPXXqVM6cOUN8fDzTpk1T+2krLCyMTz/9lLS0NFq2bIlEIimRuGJjY7l69Sp6enpq62ycnJywsrIiLi6OS5cu0apVK+7fv09WVhaenp659vf09KRx48bs2bOnROKrSFrZVtN0CPnLIyEvSS9Px1Q3i0HIn1wuZ+IRxbIG+jr6/Oz6s4YjEsoa5eSXiuJ1tTgVTblYkerevXuAor7mVXPmzGHYsGFs3LgRqVTK7NmzcyQ1Fy5cwMvLi6dPnzJz5swSS2ZAMeoDinV0Xl7C/WXNmzcnLi6OiIgIWrVqRatWrXLV6kRERDBnzhxmzZqFvX0Z7rWiQZN6lvFPFf+uZ1ZaMjMzCQ1VzPKqW7duhWpX/qbsj9zPifuKAtMxbcdQr5pYVFcQKpICJzSPHz8mODiYyMhIkpOT0dbWxsTEhEaNGuHk5JTvMu/FkZCQwK5duwDo0aNHru01atRQ1ahs3bqVzMxMfvnlF7S1tQkODubzzz8nIyODn376iQEDBpRobMpmTzVr1sxzH2WrauW+ZmZmec7Ysre3p3nz5nmea8uWLWzZohguVy4OKrwdwsPDychQzPQSozOFJ82WMv6wonbAtJIpUzvnvYqzIAjl02sTmpSUFObOnYufn1+eHW11dXXp27cvEyZMKNEmX1lZWUyYMIG0tDRcXFzynA5uaWnJhg0bGD58OLt27SIzM5M+ffrw9ddfk5mZyZw5c/joo49KLC4lZe2LoaFhnvsoZzE9ffq02Ndzd3dX1QD169ev2OcrTz7fcAGAlR6F7/j5RvTvr/j67+JvJenldZuqVKlSoe+Bl5alIUu58Vgx9D6983TMDEvnA5ggCJqTb0KTmJiIh4eHqieLiYkJ9vb2VKtWDZlMxpMnT4iIiCAlJYVt27Zx8eJF1q9fX2KjNT/88ANBQUFYW1u/dm6/ubk569evZ8SIEezbt499+/ahq6vLb7/9xvvvv18i8ZSWt+0+Z1E8eSbVdAj5e/y41E4dFRXFo0ePAMVaMDo6omdKYcQ/jWfWiVkASKpLxBIHglBB5ZvQTJ8+nbt372Jra8v3339Ply5d1O53/Phx5syZw+3bt5k5c2aBlnx/nZ9++ont27djYWHBunXr1NbPvMrMzIxhw4YxZcoUQFFM/O677xY7lrwoZ3Tl1ZYb/huZEf1mhKIKDg4GQEdHR3QGLoKpAVNVTfQWvLcAfR19DUckCEJpyHPpgxs3bnD8+HHq1KnD9u3b80xmALp27cq2bduwsbHhyJEjqqmlRTV37lw2bNiAmZkZ69atK/DSAAcPHmT69Ono6+sjkUgICwvjyy+/zLWAV0mpVasWoJg6nhflisjKfQWhMJ48ecL169cBRYG5SIwL5+Kji/wV+hcA79u9Ty870URPECqqPBOa/fv3o6WlxeTJkwtUF2NiYsLkyZORy+Xs27evyAHNmzePtWvXYmpqytq1awvc0XDv3r1899136OrqsmLFCnx9fWnbti0nT55k1KhR+Y6iFJVyOnlkZKSqYPNVV65cARSLCApCYYWEhCCXywFKffmPikYul/P1wa+RI0dXW5f5783XdEiCIJSiPBOaK1euYGxsXKh1mVxdXalatSphYWFFCub333/nr7/+wsTEhLVr1xa4+HHnzp1MmjQJAwMDVq1aRceOHTEyMsLb25v27dsTFBSkmrpdkqytrbG3tyczM5NDhw7l2h4SEkJsbCwWFhY4OjqW6LXfNh0amtOhobmmw8hbt26KRwl68eJFjqna+S3SJ+S25eoWTkefBmCs81gaVW+k4YgEQShNeSY0d+/eLfSogpaWFk2bNuXu3buFDmTBggV4e3tTtWpV1qxZoxr9eJ2tW7fy/fffY2hoyOrVq3N0EjY0NGTlypV07tyZkJAQPvvsM9LT0wsdW368vLwARTJ2//591fOPHz9m1ixFIeLIkSPVLlApFNzX3ez4upudpsPI2/TpikcJunTpkup2aWkt+VFRpb5I5Vv/bwGwNLJkeueS/bcRBKHsybMoODU1tUizlczMzFS3WQoqICCAlStXAlCnTh02btyodr/69eurEgil27dvY2xszF9//aV2bRsDAwOWLVvGuHHjuH79OqmpqWqXFrh69aoqAQFUdUALFixgzZo1que3bt2a47iePXsyaNAgfH19cXNzo3379qrFKdPT0+nevTtDhw4t4CshCApyuVxVDFytWjUaNRKjC4Ux4/gMHqUrZobN6z4Pk0omGo5IEITSlmdC8/z58zy73+bHwMCg0PUqytWDQdFALDw8XO1+Tk5OuRKaKVOmMGzYsHyb2+nr67N48WKSkpLy7LCanp7O5cuXcz2v7FKcn5kzZ9K6dWs2bdpESEgIMpmM+vXr079/fwYNGiRGZ0rAsDWKhUL//p+ThiPJQ69/i00PHiyR0928eVPVPNHZ2VksoFgIoY9CWRKyBIDOtp3xbJF7mRGhbHB1dSUmJob169eXiRqxJUuWsHTpUsaMGcNXX31VIuf08PAgJCSkzHyPFVmeCY2yELEoCntsv379itUoLr9kRklXVzffdvHF7QXj5uaGm5tbkY8X8peRqb7YnSBOAAAgAElEQVSpY5lRwkXnytEZAwMDWrZsWaLnrsiyZdl8vv9zZHIZutq6LO+9XCSDgvCWeG1jPWWH0oJKSEgoVkCC8LZ7+PChqg7N0dFRrKpdCN4XvQmJUYzmfefyHfaWYm00QXhb5JvQBAYGEhgY+KZiEQQBOHPmDADa2tqiGLgQ4tLjmBKgaKppa2IrCoEF4S2TZ0JTkNs4giCUrKSkJNUq7s2bN8fERBSzFtR3h78jOSMZgMW9FmOkL5oQVjSRkZF4e3sTHBzM48ePMTIywsHBgaFDh+bb/PXUqVNs2bKFS5cukZycjImJCbVr18bV1RVPT88C1YuGhIQwZswYnj17xo8//kjfvn1V25KSkli6dClHjx4lKSkJKysrevfuzejRo/M957Nnz/j77785ePAgUVFRANja2tKrVy+GDRuWY53Aq1ev0q9fPxwcHNi2bVuO88yZM4d169ahq6tLcHBwjokvJ06cwMvLi65du6om3wQHB+Pp6YmTkxNr1qxh9erV7Nmzh5iYGKpUqUKHDh349ttvy10ekGdCc+zYsTcZhyDkq1uTvOufyoQPPiiR0wQFBalq0FxcXErknG+DfTf3senKJgD6SPrQR9JHwxEJJS0gIIBx48YhlUqxs7OjTZs2xMbGEhgYyMmTJ/niiy8YN25cjmPkcjkzZ85k8+bNADRr1gwnJydSUlK4ffs2f/zxB71798bGxibfa+/fv5/Jkyejp6fHqlWr6NChg2pbQkICgwYNIjo6GjMzM1xdXZFKpWzcuJGQkJA8a7iSkpIYNmwYN2/exMTEhI4dOwKKZGPBggUcPHiQv//+G1NTU0DRnNXU1JSrV6+SmppK1apVVecKCgoCFAs6h4SE5Ogfp9zWvn37XDFkZmYycuRILl++jJOTEw0aNODSpUv4+flx/vx59u7dm+M6Zd1rV9sWhLLAq3MDTYeQv/Hji32Kp0+fcunSJQDs7OywsrIq9jnfBikZKXy+73MAqhpUZXnv5RqOqOBCYkL48eSPpL1I03QoBWZsYMz0ztNxqvXmZhwmJCQwceJEpFIpkydPZsSIEaptwcHBjBo1ihUrVtC6dWs6deqk2vb333+zefNmzM3NWbZsWY4Ce7lcztmzZ187Curt7c0ff/yBhYUF3t7euRq+zp49m+joaNq3b8+SJUtUoyNxcXF4enrmOVN21qxZ3Lx5kzZt2rBixQpV4pCSksKoUaMIDQ1l9uzZzJ+v6HCtra2Ns7Mz/v7+hISE0L17d0CRGN28eZNGjRpx8+ZNzpw5ozahUfcBKTQ0lGbNmnH06FGqV68OQFpaGsOGDePq1ats2rSJL774It/XpywRCY0glBEhISFkZWUB6j9NCepNODKBmLQYAOb3mE+tquVn3bSFZxey72bRl4rRlKoGVdnUb9Mbu97WrVtJT0+nVatWOZIZUMxQHTp0KN7e3qxZs0aV0GRlZaluscyZMyfXbEEtLa18R0Gzs7P56aef8PHxwc7ODm9vb6ytrXPs8/DhQ44cOYKOjg6zZs3KcavHysqKSZMmqU0IYmJi8Pf3R1tbmx9//DHHKIiJiQk//fQTbm5uHDx4kAkTJqiu6+Ligr+/P2fOnFElNGfPnkUulzN06FCWLFmiSmBAkezcuHEDCwsL7OxyNybV0tLil19+USUzAMbGxnz22Wd88803BAUFiYRGEEqa+yrFD+mWUWX0Nsw77yi+/vNPkQ6XSqWqGYW1atXC1ta2ZOKq4I7eOYr3RW8Autfvzv8c/6fhiApnXLtxpEnTyt0IzTjnca/fsQQpfzZerlt5Wf/+/fH29ubChQtkZ2ejo6NDeHg4T548oUaNGnTu3LlQ13v+/Dljxozh2LFjODs7s2zZMrVrGp47dw65XE6LFi2oU6dOru3K5YBSU1NzPH/+/HnkcjktW7akfv36uY5r2LAhLVq0IDQ0lHPnztGnj+IWqjIBezlpefmWkvI2UXx8PJaWlqpkJ6/JBTVr1kQikeR6XhlTfHy82uPKKpHQCEIZEBoaqmpI2b59e9E7pQDSpemM9BsJgJGeEd5u3uXudXOq5YTfID9Nh1HmxcXFAeRZ61KrVi20tbV58eIFycnJVK9enYcPHwJQr169Ql/v77//JisriyZNmrB69Wr09fWLFBcokoZXE5qCHGdjY0NoaKhqX1Cs6WZtbc2dO3eIi4vDysqKoKAgbGxsqF27Nu3bt2fv3r2cOXOGjz76iLNnzwJ51+O9OuKkpBxpkkqlecZXFokWtoKgYdnZ2apPWWZmZgVelPVtN+XoFO4l3wNgbve51DWtq9F4hNL3phLWLl26YGpqSkREBOvWrSu16xTl+3l5lObBgwdER0ernnt1BCe/+hmgwnWxr1jfjSCUQ5cvX1Yt/9G+ffsK9yZTGvxv+bP03FIAOtbpyOi2+U+PFco3ZYF8dHS02u0xMTHIZDIMDAxURb7KKcdFWSy5SZMmrF+/HnNzc/744w8WL16sdj9l9/mYmJg8z6UcKXrZ674fgAcPHuTYV0mZnJw5cybXDKYaNWpQr149goKCiImJISoqirp165a76ddFJd45BUGDZDKZqnll1apVadGihYYjKvsSnyUyfM9wAKroV2Hdh+vQ1hJvZRVZ27ZtAdi9e7fa7Tt37gSgdevW6OoqKins7e2pVq0asbGxnDp1qtDXlEgkbNiwgRo1arBs2TJ+/fXXXPu0adMGLS0tLl26pDY5+eeff3Ldbnr5uMuXL6tNuG7fvs3ly5fR1tZWfe9KL4/CnD17Fi0trRw1Mi4uLsTFxakWeX6bmnOKdwGhXPjAwZoPHNTf7y0TBg5UPArpypUrqkUoO3TooHozFtSTy+V4+XkRmx4LwOKei2lgVsan9AvFNnDgQIyMjLhw4QLr16/Pse3cuXOqX94vz4DS09Nj1KhRgGIR47CwsBzHKadtp6XlXZBdv359Nm7ciI2NDWvWrGH27Nk51iq0sbHB1dWV7OxsZs6cybNnz1Tb4uLi1CZBoKj56dGjBzKZjBkzZuSIITU1lRkzZiCTyejVq1euOhfljKX4+HiOHDmCRCLBzMxMtV05WrNpk2IW2tvUz0q8ewrlgodLXU2HkL/XdARVRyaTcfLkSUBRhNeqVauSjqrCWXtpLbuu7wKgX5N+DG85XLMBCSXi1SnPr1q6dCnz5s3jm2++4eeff2bbtm00atSI+Ph4zp8/j0wm44svvsg1m2n48OHcvn2bbdu2MXDgQJo1a4atrS3Jycncvn2bR48eERAQoHYGk1Lt2rXx8fFh2LBhbNq0iYyMDH766SfVreEffviB69evExgYSLdu3Wjbti1SqZTg4GDs7OxwdHQkNDQ013lnzpzJ3bt3VT1lnJwUfX2Cg4NJSUmhcePGzJgxQ21M7dq1IzIykhcvXuRKWJydnVUF0m/b8ikioRHKhedSxWrbhvo6Go4kD8pPZpUrF/iQq1evkpSUBIjRmYK4nXSbrw9+DYB1FWv+/ODPcjerSVDv9u3b+W6XSqV0796dHTt24O3tzdmzZ/H398fIyIgOHTrg4eGhdukDLS0tfvrpJ7p168bmzZsJCwvj+vXrmJqaUqdOHYYOHYqFhcVr47OysmLjxo2MGDGCHTt28OLFC3799Vd0dXWxsrJi+/btLF68mICAAI4dO4alpSWDBg1izJgxqlGiV5mZmbF582bV0gfKDze2trb873//w9PTk8p5vJ+4uLiwYcMG1Z9fVrVqVezt7bly5Yqqu/DbQkv+8viZUG7069dPdd/4bVDR+tDI5XKWL19OYmIiRkZGjB07Fj09vVILr7yTZkvptLaTaiVt/6H+9GjQQ8NRvV5ERARNmjTRdBiCUGaV5M+IqKERBA24du0aiYmJgOKet0hm8jfh8ARVMjPWeWy5SGYEQXizREIjCG+YXC5XDS9XrlyZNm3aaDiism3b1W0sDlFMm21bsy2/dldfaCkIwttNJDSC8IaFh4erWoq7uLjk2YVUgJuPb/Lp3k8BqFapGls/3oqBroGGoxIEoSwSCY0gvEHZ2dkcP34cACMjI9XMBiG355nP+Xjbx6RJFVNa1/ddL7oBC4KQJzGtQigXBrTOe82TMmH48ALtdvHiRVXfmc6dO4vRmTzI5XK+PPAlYXGK3iGTOkzig0YfaDgqQRDKMpHQCOXCx21qazqE/BUgocnMzFTVzpiamtK6detSDqr8Why8mLWX1gLQ2bYzP7n+pOGIBEEo68QtJ6FcSHoqJelpGV75NTFR8chHcHAw6enpALzzzjvo6JTRnjoadujWIb49/C0ANlVt2Nx/M7ra4rOXIAj5E+8SQrnwxcYLQBnuQzNggOJrHn1oMjIyOH36NKBoXd68efM3FFj5cj3xOu7b3ZHJZRjqGrLnkz1YG5fhJS8EQSgzxAiNILwBp0+fJiMjAwBXV1exorYaSc+TcPN1I/WFYjG/vz/6m1bWYjkIQRAKRryrCkIpS01NJTg4GFAsZieRSDQcUdnzIusFA7YO4FbSLQBmdpnJx/YfazgqQRDKE5HQCEIpCwgIIDMzE4Bu3bqJ9YdeIZPL8NztyfF7iunsHzf9mOldpms4KkEQyhuR0JQBT58+pXPnzkgkEq5cuaLpcIQS9ODBA8LCFFOPmzRpQt26dTUbUBkjl8sZe3AsW69uBaB97fas+2gd2lrirUkQhMIRRcFlwNKlS8nOztZ0GGXa0Ha2mg4hf198kespuVyOv78/ADo6Orz77rtvOqoy75dTv7D03FIAmlo0xW+QH5X1Cr5iuSAIgpL4GKRhN2/eZPPmzXz99deaDqVMc2tRE7cWNTUdRt7c3RWPl4SHh/PgwQMA2rVrR7Vq1TQRWZm1+uJqph2fBkDtqrXxH+qPmaGZhqMSBKG8EgmNhs2ePZshQ4aIWxGv8TD5OQ+Tn2s6jLxFRyse/8rMzOTo0aOAYomDTp06aSqyMmnD5Q14+XkBYGZohv9Qf2yqlvFu0EKJc3V1RSKR5Hg0b94cV1dXJk6cSERERIleR/kBQ2ny5MlIJBJ27txZItcRNEskNC+5c+cOf//9N+PHj6dnz540btwYiUTCoUOHXnusn58fgwcPpnXr1jg6OtKvXz82bdqETCbL85jdu3dz//59vlBzu0LI6Zstl/hmyyVNh5E3Dw/F419nzpwhNVUx/djV1RUDA7GgotKGyxsYtnsYcuQY6Rmxf/B+mlg00XRYggZ17NiRvn370rdvXzp06IBUKmXPnj0MGDCA/fv3azq8Ms/DwwOJRKKaTfkmLVmyBIlEwpIlS974tV8lamhe4uvry/r16wt93KxZs/Dx8cHAwAAXFxd0dXUJCgpi9uzZBAUFsXjx4lx9R9LS0vjtt9+YNGkSRkZGJfUtCGVAcnKyqolejRo1aNmypYYjKjteTWYODT1EO5t2mg5L0DAvLy+cnZ1Vf8/IyGDatGn4+fkxY8YMOnTogKmpaYlf99tvv2XkyJFYWlqW+LmFN0+M0LykUaNGfPrppyxYsIAjR44UaCVkf39/fHx8sLCwYO/evaxatYply5Zx+PBhGjRowJEjR9iwYUOu4xYuXIitrS19+vQpjW9F0BC5XM6BAwdU07Tfe+890UTvX+qSmY51Omo6LKEMqlSpEjNnzqRy5cqkp6cTGBhYKtextLSkQYMGGBsbl8r5hTdLvNO+5OOPP2bixIn07t2bOnXqFOiYVatWATB+/PgcdTDm5ubMnDkTAG9v7xy3niIjI9m8eTNjx44lNTWV1NRUnj17BsCzZ89U6/0I5U9ERASRkZEAtGzZUtRG/Wtx8GKRzAiFUqVKFdXPz8OHD1XPy+Vydu/ejYeHB23btqV58+Z0796dWbNm8ejRo0Jd43U1NJcvX+a7776ja9euNGvWDGdnZ/r168fixYt58uQJAMuWLUMikTBjxow8r3Ps2DEkEgkDlEukFMD+/fvx9PTEyckJe3t7nJ2dcXNzY9asWURFRQGK9eEkEgkhISEAeHp65qhHevkWlL+/P1OmTOH999+nTZs2NG/enHfffTff1+3lW1nnzp1TjaQ1btyYo0ePIpFIWLpUMUtx6dKlOa6tiVtQ4pZTMcTGxnL16lX09PTo2bNnru1OTk5YWVkRFxfHpUuXaNVK0cb9/v37ZGVl4enpmesYT09PGjduzJ49e0o9fqFkyWQyDh48CIChoaGYpo3il8/3Ad8z9/RcAIz1jdk/eL9IZoQCUX6409fXBxT/n8aPH8++ffvQ09PDyckJExMTwsLC8PHx4cCBA3h7e+Pg4FDsa69atYoFCxYgl8uxs7OjZcuWPH36lHv37rFs2TKcnZ1xdnbG3d2dFStW4Ofnx8SJE6lSpUquc23atAmAIUOGFOjaS5YsYenSpejp6eHo6IilpSWpqanExMTg4+NDmzZtqFOnDubm5vTt25dTp06RmJhIx44dsbCwUJ3H3Nxc9edvvvkGAwMDGjRoQPv27ZFKpURERODj48PBgwfx9fWlXr16auM5dOgQmzdvpmHDhnTo0IEnT56gq6tL3759iYiI4Pr16zRu3JgmTf6rhXv5z2+KSGiK4dq1awDY2dlRqVIltfs0b96cuLg4IiIiVAlNq1atctXqREREMGfOHGbNmoW9vX3pBl4OjexUX9Mh5O+777h4/rzqDbhHjx5Urvx291PJkmXh5efF2ktrAbA0suTgkINifaZXuK8KyvXcBw7WeLjU5bk0m+FrQ3JtH9Daho/b1CbpqVS1cOvLhrazxa1FTR4mP1dbTD+yU326N7XidkI63+/M3czzK1c7OtqZc/VhCrP9ruXY9qYWiI2IiFDNSmrcuDEAPj4+7Nu3D3Nzc9atW4ednR0A2dnZzJkzhw0bNjBu3DgOHTqkSoKK4siRI8yfP5/KlSvzxx9/4OrqmmN7WFiYqu7G3NycXr16sXfvXnbv3s3QoUNz7Hv//n1Onz6NqakpvXv3fu21pVIpq1evpnLlyuzcuTNXknHv3j10dHQAaNCgAXPnzsXDw4PExMRctUgv+/333+natSuGhoaq57Kysli6dCkrVqzg559/ZvXq1WqP9fHxYfbs2bi/0prinXfeYcmSJVy/fp3u3bvz1Vdfvfb7K00ioSkG5Q9bzZp590extrbOsS+AmZlZnv/p7O3t81yJecuWLWzZsgVANdz5tuje1ErTIeQrplUr9l+8CICtrS0tWrTQcESalfoilcE7BrM/UjFDpUG1BvgP9aeBWQMNRyaUdSkpKZw/f55ffvkFmUxGkyZNVPWMa9cqkuOxY8eqkhlQNK6cOHEiAQEBxMTEcOjQoWLVJypvo0ycODFXMgPkGgHy8PBg7969+Pr65kpofH19kcvl9O/fv0CzHdPT08nIyKBx48ZqR0yKehtbXTKlq6vLuHHj2LFjB6dPnyY9PV3tCFOHDh1yJTNlkUhoikFZ9/Jyxvsq5Qymp0+fFvt67u7uqv9U/fr1K/b5ypPbCYqRjwYWuX/YNC07O5tTq1dTPTGRZCsrPvjgg7d6vaZbSbf4cPOHXEtQfLJvZd2KA4MPYFWlbCelmpLfiIehvk6+282M9PPdXtPUMN/tDSyq5LvdvqbJGxmRUXf7HRQf8JYsWYK2tjaxsbFER0ejra3Nhx9+mGtffX193NzcWLVqFSEhIUVOaBISErh+/Tp6enr07du3QMc4ODjg4OBAWFgYwcHBqg+sGRkZ7Nq1C21tbQYNGlSgc5mZmVGrVi2uX7/O3Llz+fjjj2nQoGQ+CNy9e5dTp04RFRXF06dPkcvlgOI9TCaTERUVRdOmTXMdV15un4uEpoxwdnbmxo0bmg6jzFIOi7+p4e7CCAwMpN2/nxzvrVuX47712+bw7cO4b3cnOSMZgF4Ne7F5wGaqGlTVcGRCWfZy7Ye+vj6Wlpa0bt2adu3aqT4cxMXFAWBhYZHnSEft2rVz7FsUygJka2vrPEsJ1PHw8GDChAn4+PioEpr9+/eTnJzMO++8o4qtIObNm8fXX3/N2rVrWbt2LWZmZrRo0YJOnTrRp0+fQs/KysrKYtasWWzbtk2VxKiT14SU/O5ClCUioSkGZY3E8+d5d7BVjsyIXjMVU2xsLCdPnsQD0NPXp2PHt7PYVS6XMz9oPhOPTkQmV8zom9RhEj+7/oyOto6GoxPKuvxqP15V2qOfRT1/z549+fXXXwkICCA+Ph5LS0t8fHwAGDx4cKHO1aZNGwICAjh+/DghISGEhobyzz//cPz4cZYsWcKaNWvUjqTkZf369WzduhVLS0umTJmCo6Mj1atXV9UZffLJJ4SGhuaZ7BQmsdMkMW27GGrVqgXknFL4qtjY2Bz7ChVHdnY2u3fvVkzJ19LC3NwcXd237zNC4rNEPtz8IeOPjEcml1FJtxI+/XyY232uSGaEEmNlpbhlGR8fj1QqVbtP9L/Ljyj3LQpl3eOjR4/IyMgo8HH6+vq4u7uTmZnJ1q1bCQsLIzw8nNq1axdp6RNDQ0N69+7NzJkz2bNnDydPnqR37948efKE2bNnF+pcym73s2fPpnfv3lhbW+comr5//36h4yuLREJTDMoMOTIyMs//+FeuKG6VaGIKm1C6/vnnH9XQtomJCQbFmFVRXh2/e5wWK1vgd9MPgDomdQgcEcig5gWrFxCEgqpRowa1a9dGJpOpbWuRmZmJn5/i/2FBmqLmxcLCAolEQmZmJrt37y7UsZ988gl6enps3bpVNZN10KBBJdJc09LSkm+++QaA69ev59imp6cHKD5kqZOSkgL8l6y97PTp0yQlJRU5LuW1s7KyinyOkiISmmKwtrbG3t6ezMxMtes9hYSEEBsbi4WFBY6OjhqIUCgtyqmYoHijNTUx0XBEb5Y0W8rUgKl0W9+Nh2mKEcr+TfpzadQlWtdsreHohIpqxIgRACxatIjbt2+rns/Ozua3337j4cOH1KpVS21fsMIYM2YMoKhlOXHiRK7tV65cUY2+v8zS0pIePXoQFxeHn58fBgYG9O/fv1DXjomJYdu2bWrrWY4dOwbkrmlRjki9/Jq8TDlbysfHJ0eT16ioKH744YdCxfcq5bXv3LlTrPOUhLdvfLyEeXl5MXbsWH7//XccHR2xtbUF4PHjx8yaNQuAkSNHivb3xfSVq93rd3pDnj9/zs6dO5HL5armUlolNAuhPAh+EMynez/lasJVAAx1DVnUcxGftfrsrZ7dJZS+wYMHc/HiRfbt28eHH36Is7OzqrFedHQ0JiYmLFy4sFg9aEDRR+qrr75iyZIleHl50ahRI+zs7Hj69Cl3797l/v37rF+/nho1auQ61sPDQ7Wg5vvvv1/oNahSU1OZNm0as2bNokmTJtjY2CCTybh9+zaRkZHo6ekxYcKEHMd0796dnTt3Mm/ePE6fPk316tUB+PTTT6lfvz6jRo0iMDCQLVu2EBwcTNOmTUlJSSEkJARHR0fMzc0JDQ0t0mvVsWNHDA0NOXz4MEOGDKFOnTpoa2vj6upKt27dinTOohIJzUuuXr2qSkIAbt26BcCCBQtYs2aN6vmtW7eq/tyzZ08GDRqEr68vbm5utG/fXrU4ZXp6Ot27d8/Vl0AovI52ZWPmkFwux8/PT7WSdo8ePRQNtrp313Bkpe+p9CnTj09n4dmFyFEUDzpYOeDb35emFgUvUBSEotLS0uL333+nU6dObNu2jcuXL5ORkYGlpSWDBg1i1KhRam+rFMWYMWNo164dGzZs4MKFCxw+fJgqVapgY2PDV199hUQiUXucg4MDVapUIT09vdDFwKCYqTVlyhRCQkK4desWt27dQktLCysrK9zd3fH09KRhw4Y5junWrRs//PADW7ZsISgoSFUC0adPH+rXr4+joyPbt29nwYIFhIeHExAQgI2NDZ9//jleXl58+umnhX+B/mVhYcHKlStZtmwZERERXLhwAblcTo0aNd54QqMlz28O11smODg4z34IL1M3vdrPz49NmzZx8+ZNZDIZ9evXp3///iV2//RV/fr1y3P9kYro6kPFPWD7mpq9tXP+/HnVpy+JRIK7u7tiVOLSv91YK+DK2nK5nF3Xd/Hd4e+4l3wPAH0dfWZ0nsHEDhPR09HTbIBlWEREhKife8scPXqUL7/8EgcHB7Zt26bpcMq8kvwZESM0LylOLxg3Nzfc3NxKOCJBSdl+XZN9aJQdSAGMjY3p06fPf7dYxo1TfP3nH80EV0oux15mnP84/rn3j+q59rXbs9ptNU0sxC9qQXhZVlYWy5cvB/6r9xHeHJHQCEIBPHv2jG3btpGdnY22tjYDBgyo0Gs1xaTGMPvEbFaHrlb1lTEzNOPHrj/yeZvP0dYSNWGCoLRjxw7Onz9PWFgYt27dokWLFvTq1UvTYb11REIjCK8hk8nYuXOnaurju+++S506dTQcVel4mPaQuYFz+fPCn7zIfgGAjpYOX7b9kh/e+QEzQzMNRygIZc+5c+fYtWsXJiYm9OrVi++//14UyGuASGgE4TWOHj2qmg5pb29f4I6m5UlUShQLghaw8sJKMrL+66nU2643v7/7u7i9JAj5mDt3LnPnztV0GG89kdAIQj5CQ0MJCgoCFNX8bm5uFeqT17mYc8w/O59tV7eRLf+vKVf3+t2Z9c4s2tdur8HoBEEQCk4kNEK5MLGn+imSpen+/fvs27cPULQhHzRoUJ6L4vHLL28wsuJ5nvmcHRE7WHVhFYFRgTm2da3blVnvzKKTbeFbtQuCIGiSSGiEcqG17Zut3UhMTGTLli3IZDK0tbVxd3enWrVqeR/QvmyPZMjlci7FXmL1xdVsurKJlBcpqm262roMtB/IN+2+oU3NNhqMUhAEoehEQiOUCxfuK9YaeROJTVpaGhs3blStov7BBx+oOkDn6cwZxdcylthcS7jGlvAtbL22leuJOdd/Ma9szqeOnzLGaQw2VW00FKEgCELJEAmNUC7MO6ToD1TafWgyMjLYuHGjakZTlwnICAUAACAASURBVC5dCrYO1/ffK75quA9NliyLoOggDkQeYF/kPsLjw3Ns10KL9xq+x2eOn+EmcUNf5+1bUFMQhIpJJDSC8C+pVIqPjw/x8fEAtG7dmi5dumg4qteLTonm6J2jHLx1kMO3D+e4naTUyroVA5sOZFDzQdQxqZhTzgVBeLuJhEYQgMzMTHx9fYmOjgagcePG9O7du8zNaJLJZVxLuEZgVCCBUYGcijpFVEqU2n3b1GzDR5KPGGg/ELvqZWdxT0EQhNIgEhrhrZeVlcXmzZu5d+8eAA0bNqR///4aXyE9MzuTiMQIQh+Fcin2EqGxiq/qRmAAqlWqxnsN36N3w9681/A9LI0s33DEgiAImiMSGuGtJpVK8fX1VSUz9evXZ+DAgejqvpkfDblczuPnj7mVdIsbiTe4+fgmNx7f4MZjxZ+l2dI8jzUzNKNjnY50rN2RjnU60rZWW3S1xY+0IAhvJ/HuJ5QLM9yalvg5nz9/jo+PDw8ePACgbt26uLu7o6dXhNWjFy5U+/RT6VOiU6OJTokmKiWK6NRXvqZE8zzr+WtPr6+jT3PL5jjWcKRtrbZ0qtMJiblErKkkCILwL5HQCOWCfU2TEj1famoqPj4+xMXFAWBnZ8fHH39cqGRGLpfzKP0RUSlRROlFEZUSxf0DfxGVqvhzVEoUSc+TChWXtpY29UzrITGXIKkuoWWNljjWcKSxeWP0dIqQaAlCGebq6kpMTEyO5/T19bGwsKBNmzaMGDGCJk2Kv+yG8joBAQHY2PzXomDy5Mns2rWLOXPm0K9fv2Jfp6LK6/Ura0RCI5QLgZGJAHS0My/2ueLi4vDx8SE1NRWApk2b0q9fP3R0dNTuL5fLuZd8jyvxV4hIiOBa4jUiEiKISIwgXZoOQDfFUk8ENHj99WtUqUEdkzrUrlpb9bVetXpIqkuoX60+Brp5dCMWhAqqY8eOWFhYAJCcnEx4eDh79uxh//79zJs3j/fff1/DEQrlgUhohHJhybFIoPgJza1bt9i2bRtSqaI2pU2bNvTq1StHAXDaizQCowI5++As5x6e49zDcyQ+S8z3vNNOKr4GN6mCrYmtKlGxNbX9L3ExqU0t41oiYRGEV3h5eeVY9DUjI4Np06bh5+fHjBkz6NChA6ampiV+3W+//ZaRI0diaSkK6CsCkdAIbwW5XM6ZM2cICAhALpcD8O677+Li4kKmLJNTd04RcDeA4/eOcy7mXI6FGl9lZWRFE4smNDVvSmPzxtQ1rUsb/9lU0jUgdfKpMjfVWxDKm0qVKjFz5kwCAgJIT08nMDCQDz74oMSvY2lpKZKZCkQkNEKFJ5VK2bt3L1evXgVAV1eXbu93457uPZbsXMLByIN5ToWWVJfQtlZb2tZsi2MNR5paNKV65eq5d9T/Q/FVJDOCUCKqVKlC3bp1uXbtGg8fPlQ9L5fL2bNnDzt27OD69etkZGRgZWVFp06d8PLywtrausDXeF0NzeXLl1m/fj0XL14kISEBIyMjatWqxTvvvIOHhwfVqlVj2bJlLF68GHd3d2bPnq32OseOHeOLL76gefPmbN++vcDx3b59m7/++ouzZ8+SkJBApUqVsLe3x8PDg27duuXa/+Val/v37/Pnn38SHh5OVlYWEomEUaNGqT0OICYmhkWLFhEYGEh6ejo2Njb07duX//3vfwWOV9NEQiNUaDExMezcuZOkpCSyyCLWKJZHlo+YvW92rinRWmjRskZLutbtims9VzrU6YBppZIf5hYEoWDS0xU1avr6iiU65HI548ePZ9++fejp6eHk5ISJiQlhYWH4+Phw4MABvL29cXBwKPa1V61axYIFC5DL5djZ2dGyZUuePn3KvXv3WLZsGc7Ozjg7O+Pu7s6KFSvw8/Nj4sSJVKlSJde5Nm3aBMCQIUMKfP39+/czadIkMjMzsbOzo2vXriQlJXH+/HmCgoIYPXo0Y8eOVXvs9u3bWblyJc2bN6dLly7cvXuXy5cv8+WXX7Jw4UJ69uyZY/9bt24xdOhQnjx5grW1Nd26dSM1NZVFixYRFhZWiFdNs0RCI1RIMpmMM2fOcPz4cWJlsZznPBHaEaQ9TYO7/+1nrG9ML7te9GnUh54Ne6offRGE0vTOO7mfGzgQRo+GZ8+gd+/c24cPVzwSE2HAgNzbv/gC3N0hOho8PHJv/+47cHODGzdg1Kjc26dNg+7d4dIlGDcu57Y3tF5ZRESEqqVC48aNAfDx8WHfvn2Ym5uzbt067OwUHbCzs7OZM2cOGzZsYNy4cRw6dEiVBBXFkSNHmD9/PpUrV+aPP/7A1dU1x/awsDDVrSpzc3N69erF3r172b17N0OHDs2x7/379zl9+jSmpqb0Vvdvqcb169eZNGkSenp6LFu2LMcSLJGRkYwcOZLly5fj7OxMu3btch2/evVq/vzzTzp37qx6bvny5SxatIj58+fnSmgmTpzIkydP+PDDD/npp59Ur11kZCSenp4kJRVutqamiCYWQrnwS7/m/NKveYH2TU5O5u/1f7MsYBlrZWtZznJCCCFNlgaAkZ4Rw1oM4+CQgyRMSGDLgC0McRhSvGRm1SrFQxCEYklJSSEgIIAxY8Ygk8lo0qQJTk5OAKxduxaAsWPHqpIZAB0dHSZOnEjNmjWJiYnh0KFDxYph6dKlgOIX/avJDICDgwM1atRQ/d3j36TR19c3176+vr7I5XL69++PgUHBJgSsXLmSzMxMJkyYkGs9OTs7OyZPngz8N/LzKg8PjxzJDMBnn32GsbEx9+/fz3EL7/z581y9ehVjY2OmT5+eIxG0s7Nj9OjRBYq5LBAjNEK50MAi9zDuq7Kzszl55iQL/lnAKdkpkknOsb17/e4MazGMvo37YqRvVLIBSiQlez7h7ZHfiEflyvlvNzfPf3vt2vlvl0jy396y5RsZkfH09FT7vL29PUuWLEFbW5vY2Fiio6PR1tbmww8/zLWvvr4+bm5urFq1ipCQEPr06VOkWBISErh+/Tp6enr07du3QMc4ODjg4OBAWFgYwcHBqhlbGRkZ7Nq1C21tbQYNGlSgc8lkMk6dUkwueHUkRUmZ4IWGhqrd/o6aUT99fX1q167NtWvXiI+Pp2bNmgCEhISojjE2Ns51nHLUpjwQCY1QLhy9pmiA172pldrtkfcimbpzKofSDpFGmur5qgZVGdFyBF+2/bJ0F2j081N8dXMrvWsIQgX1ch8afX19LC0tad26Ne3atVPNGlQ2wbSwsMhzpKN27do59i0K5eiFtbU1lSpVKvBxHh4eTJgwAR8fH1VCs3//fpKTk3nnnXdUsb1OcnKyqnbIxcUl332fPHmi9nllsvIqZX3PixcvVM/FxsYC5Nkwr2rVqhgbG5OWlqZ2e1kiEhqhXPA+dQfIndA8THzI1J1T2fZoG095qnq+dpXaTOo0iWEth1FF//WjO8X2x7+znERCIwiF9mofmvyUdluEop6/Z8+e/PrrrwQEBBAfH4+lpSU+Pj4ADB48uMDnyc5WtIzQ0dEp8ijT29o6QiQ0QrkUnxzPlF1T2By1mWc8Uz1fy7AWs7rNwrOlp1gqQBAqECsrxYeZ+Ph4pFKp2qLf6OjoHPsWhXLa96NHj8jIyCjwKI2+vj7u7u4sW7aMrVu30rlzZ8LDw6lduzadOnUq8PWrVatGpUqVyMjIYPr06RgZlfDt8VcoX6tXl6BQSk1NLRejMyCKgoVyJioxiuHrhlN3UV3WRK1RJTM19Wuy4t0V3Bt/j09bfyqSGUGoYGrUqEHt2rWRyWTs2bMn1/bMzEz8/r31q6wxKQoLCwskEgmZmZns3r27UMd+8skn6OnpsXXrVtavXw/AoEGDcnQifx1dXV3VrSZ/f/9CXb8olK/VP//8o7rV9TLla1oeiIRGKBeevnhK+MNwGi5ryN/3/+Y5ihWqa+nVYtk7y4iaFMXn7T9HV1sMOgpCRTVixAgAFi1axP/bu/OgqK58geNfNhFFFsdW0ZAgkWZXiVtwTFyC+zZKMgYUnZTLpFye9XzJWDpTI5owUYMxIU5mouNoxOCGkGiokNG4jQURcAFEAoqAGJYh4AYqAn3fH6R7RMAFG5qmf58qCzz3nHvPlZ/cX9977jk5OTm68traWj788EMKCwvp3bt3k4Npn9SSJUsA2LBhAydOnGiwPT09XTf25EHdu3dn7NixlJSUcOjQIaytrQkMDHzq4y9evBgrKyvCwsKIi4vTzW6upSgKaWlpnDp16qn3/bBBgwbh6enJrVu3CAsLo7q6WrctJyeHzz777JmP0Vrkt79os2o1tUQlRvFZ0mfklta91VBtXfef7QWrF/i/If/HotGLsDBvfFFJIUT7EhwczNmzZ/nmm2+YNm0aQ4cO1U2sV1BQgL29PR9//PEzzUEDMHbsWJYuXcqnn37KwoULUavVuLm5UVlZSW5uLvn5+ezcubPeq9taISEhxMXFATBp0qRmrUHl6+vL+vXrWbVqFcuXL2fjxo28+OKL2Nvbc/36dTIzMykrK2PBggUMHz78mc7VzMyMDRs2EBISQkxMDD/88AMDBgzg1q1bnD59mlGjRpGRkdHkI6m2RBIa0eZkF2Xz8dGP2X9lPz9r6haFtLC6DIC3jTcrfr2CWf6znuo2bouLjDR0D4Ro98zMzAgPD+eVV15h//79pKamcu/ePbp3705QUBC///3vn2rpg0dZsmQJL7/8MpGRkZw5c4Z//etf2Nra8txzz7F06VLcm5iqoV+/ftja2lJRUfFUg4EfNmnSJHx9fdm5cycJCQkkJycDdRP5eXp6MmLECMaNG9fs/T9IrVYTHR1NREQEp06d4siRI/Tu3ZslS5Ywf/58xo4dq5fjtDQz5eF7WcIozJgxg5iYGEN3Q2/ySvP4/OTnxF6KJasqq942SywZ7jicFSNWML7/s91KFqI1ZWZm4unpaehuiFZ05MgRFi9eTL9+/di/f7+hu9Pm6fP/iNyhMYBDhw6xe/dusrKy0Gg09OnTh8DAwKcePGbMNBoNp7JPsffMXo5eO0r2vWw0aOrV6WnRkyC3IN4Z+w5nrkJ1E/tqE/burfs6c6Zh+yGEMJiamhrdmBPteB/ReiShaWVr1qwhKioKa2tr/P39sbS0JDExkbVr15KYmEhERES7TGo0Gg3n8s8Rlx7HyfyTnL1+lutKw0mh7M3sea3na7w1+C0m9p+o+7f4332JAEzp3/iEUQb3t7/VfZWERgiTc+DAAVJSUkhLS+Py5cv079+fCRMmGLpbJkcSmlb03XffERUVhUqlYteuXbi4uADw888/M2fOHA4fPkxkZCRz5841bEf1oPRWKcd/PE5ibiI/FP5Axu0Mbim3Gq3bzbwbw1TDmP3SbGYMmiGDfIUQRiU5OZnY2Fjs7e2ZMGECq1atMtnJ7QxJEppW9Pkvixe+8847umQG6gZ5hYaGEhISwtatWwkJCTGKuzS1mlqulFwhozCDrJIsskuzySjLIKcyRzeYtzEd6IC7jTujnx9N0KAghvZ9shlChRCiLVq3bh3r1q0zdDdMniQ0raS4uJiMjAysrKwanSNhyJAh9OjRg5KSEs6fP89LL71kgF7WV6up5VLxJTILM8n6TxZXyq6QfzOfwjuFlFSVUK4pp5bax+6nM53x7uKNfy9/xnuOZ7T3aDpYPttrlUIIIcSDJKFpJRcvXgTqlmNvaiptX19fSkpKyMzMbNWEJu1qGnHpcXUJy626hOU/Vf954oTlQV3Nu/Jipxfx6ebDYOfBvOL2Cl69vYzijpMQQgjjJQlNK7l27RrQ9Cqo8N81RLR1W0Pa1TRe2v7SEycunelMN6tuOHV04jnb53BxdMGtmxseTh74POdDV9uuLdLPv80e2CL71ZvoaEP3QLRRiqLIeAohGqHvWWMkoWkld+7UrTlkY2PTZB3tImSVlZWNbt+7dy97f3k9uKll45+WuZk5Zvz3l21nOqOyUtHTpifOts70cexD32598XTyxLu3N462jno57tPq2rmNP6Lq1s3QPRBtkLm5ORqNBgsLGeguxMM0Go1e795LQmNEZs6cycxfXgueMWOGXvbp4+xD/v/kc+U/VwyasDzO/pS6VXTfGORs4J40YceOuq+/+50heyHamI4dO3Lnzh26dOli6K4I0ebcuXPnkR/yn5YkNK2kU6dOANy9e7fJOto7My29XPzDejn2opdjG53f5RfRZ+oew0lCI4yJra0tN27cwNbWVh47CfEARVG4ceOGXq93MlKzlfTu3RuAwsLCJutoV2/V1hVCGDdHR0dqamooKiqiqqpK72MGhDA2iqJQVVVFUVERNTU1ODrq76mA3KFpJV5eXgBcunSJe/fuNfqmU3p6OoCs/SJEO2Fubo6zszPl5eVcvXqVmpoaQ3dJCIOztLTE3t6e7t27yxgaY+Tk5IS3tzcZGRnEx8fzm9/8pt72pKQkiouLUalU+Pn5GaiXQgh9s7S0pHv37nTv3t3QXRGiXZNHTq1o4cKFAISHh5Ofn68rLysrY82aNQAsWLBA5mwRQgghnpKZIg91W1VoaCi7d+/G2tqaYcOG6RanrKioICAggIiIiCd6xXPGjBnExMS0Qo/bhrv36+bJsenQRl9//eW1fH4Z/C2EEKJ1ySOnVhYaGsrAgQP58ssvSUpKQqPR4OrqSmBgIEFBQXJ3pgltNpHRkkRGCCEMShIaA5gyZQpTpkwxdDeMSmRiHgAh/i6G7EbTPvus7uuiRYbthxBCmCi5HSCMwjdpRXyTVmTobjRt3766P0IIIQxCEhohhBBCGD1JaIQQQghh9CShEUIIIYTRk4RGCCGEEEZP5qExUkOHDtXrmk/Xr1/X65oaov2Q2BBNkdgQj6Lv+HB0dGTbtm1NbpeERgCmN1GfeHISG6IpEhviUVo7PuSRkxBCCCGMniQ0QgghhDB6FqGhoaGG7oRoG3x8fAzdBdFGSWyIpkhsiEdpzfiQMTRCCCGEMHryyEkIIYQQRk8WpzRhhw4dYvfu3WRlZaHRaOjTp4+s+t2OXLlyhX//+9+kp6dz4cIF8vLyUBSFTz75hPHjxz+ybXNj4+TJk+zYsYMLFy5QVVWFs7MzkyZNYt68eXTo0EHfpyiaobq6mpSUFE6cOEFSUhJ5eXncv38fR0dH/Pz8mDVrFkOHDm2yvcRG+xYZGUlKSgrZ2dmUl5dTUVFBly5d8PDwYPr06UydOhUzM7MG7TQaDbt37+bAgQPk5uZibm6Ou7s7wcHBTJ48+ZHH1Ne1SB45mag1a9YQFRWFtbU1/v7+WFpakpiYSGVlJWPGjCEiIkKSGiMXFhbGzp07G5Q/LqFpbmxs3bqV8PBwLCwsGDJkCHZ2diQnJ1NeXs6AAQPYsWMHNjY2ej1H8fQSEhJ46623AFCpVHh7e2NjY0NOTg7Z2dkALFq0iGXLljVoK7HR/r366quUl5fj5uZGjx49sLGxobCwkNTUVBRF4bXXXmPz5s31fs61tbUsWbKEo0ePYmtri7+/P/fv3ycxMZH79+8TEhLCn/70p0aPp9drkSJMTnx8vKJWq5Vf//rXSm5urq68tLRUmTBhgqJWq5UdO3YYroNCL/bt26esX79eiYuLU/Lz85XZs2crarVa+fbbb5ts09zYSEtLU9zd3ZX+/fsr58+f15VXVFQos2bNUtRqtRIWFqbX8xPNk5CQoCxdulRJTk5usC0uLk7x9PRU1Gq1kpiYWG+bxIZpSE5OViorKxuUZ2dnK8OGDVPUarUSHR1db9u2bdsUtVqtTJw4USktLdWV5+bm6tocPny4wT71fS2ShMYETZ8+XVGr1UpsbGyDbadPn9YFWG1trQF6J1rKkyQ0zY2NpUuXKmq1Wvn0008btLt69ari4eGheHt7Kzdv3nz2ExEtatWqVYparVZWrlxZr1xiQ2zevFlRq9XK8uXLdWU1NTWKv7+/olarlaSkpAZtYmJiFLVarQQGBjbYpu9rkTxTMDHFxcVkZGRgZWXV6GOHIUOG0KNHD0pLSzl//rwBeigMpbmxcf/+fU6ePAnA1KlTG7RzdnZmwIABVFdXc+LEiZY7AaEXXl5eAJSUlOjKJDYEgKVl3bDbB8c8nTt3jrKyMnr27MngwYMbtBk/fjxWVlakp6frJaYeRRIaE3Px4kUA3Nzc6NixY6N1fH19AcjMzGy1fgnDa25s5ObmcvfuXRwcHHj++ecf2U57DNF25eXlAXXja7QkNkRBQQF79uwBYPTo0bpy7c9b+3N8mI2NDX379q1XF1rmWiRvOZmYa9euAdCrV68m6zg5OdWrK0xDc2ND+712W2O0+/zpp5+euZ+i5ZSWlhIbGwvA2LFjdeUSG6bnwIEDJCcnU11dTUlJCefOnUOj0fD2228zZswYXb0njY3MzMxGY0Of1yJJaEzMnTt3AB75RkHnzp0BqKysbJU+ibahubHxJO06derUoJ1oW2pqanj33Xe5ffs2/v7+9T6FS2yYnrNnz+qSW6h73LRs2TLdG3Jazf0Zt8S1SB45CSGEYPXq1SQmJuLk5MSHH35o6O4IAwsLCyMrK4vU1FTi4uKYM2cOmzdv5re//W29sTBtiSQ0JkabKd+9e7fJOtpsWJsdC9PQ3Nh4knbaT2MSU23T+++/T3R0NCqVih07dtQbPwMSG6asY8eO9O3blxUrVrB8+XJ+/PFH3nvvPd325v6MW+JaJAmNienduzcAhYWFTdYpLi6uV1eYhubGhvb7oqKiJttpt0lMtT3r1q0jMjKSrl27smPHDlxcXBrUkdgQANOnTwfg2LFjVFdXA88eG/q8FklCY2K0r2ReunSJe/fuNVonPT0dAE9Pz1brlzC85saGq6srHTt25MaNG1y9erXRdmlpaQ3aCcPbsGED27dvx8HBge3bt+veRnmYxIYAsLe3x9LSkpqaGm7evAn8Nza0P/+H3b17l0uXLtWr++D3+rwWSUJjYpycnPD29qa6upr4+PgG25OSkiguLkalUuHn52eAHgpDaW5sdOjQgVdffRWAgwcPNmhXUFDA+fPnsbKyYuTIkS3Wf/F0wsPD2bZtG/b29mzfvh0PD48m60psCIDk5GRqamqws7PD0dERAD8/P7p27UpxcTHJyckN2sTHx1NdXY2vry89evTQlbfEtUgSGhO0cOFCoO4XWn5+vq68rKyMNWvWALBgwQJZy8kENTc2FixYgJmZGf/4xz90n7ih7hn4qlWr0Gg0BAcHY2dn1wpnIR5n06ZNbN26FTs7O/75z3/W++TcFImN9i8lJYVjx45RU1PTYNuZM2f44x//CMDrr7+OhYUFABYWFsyfPx+A0NBQysrKdG3y8vLYuHEjAG+//XaDfer7WiSLU5qo0NBQdu/ejbW1NcOGDdMtCFZRUUFAQAARERG6gBXGKSMjQ/dLAeDy5ctUVlbi4uKCvb29rnzfvn312jU3Nh5cgPDll1+mS5cuJCcnU1ZWRv/+/fniiy9kAcI24Pvvv2fRokUA+Pj44Obm1mg9V1dX3QVHS2KjfYuJiWHlypXY2dnh5eVFt27dqKyspKCggMuXLwMwcuRIPvnkk3qT4dXW1rJ48WKOHTumW5yypqaGhIQEqqqqHrk4pT6vRZLQmLBDhw7x5Zdfkp2djUajwdXVtVlLtou26fTp08yZM+ex9bKyshqUNTc2Tp48yfbt27lw4QJVVVU4OzszefJk5s2bV2+6dGE42ovW4wwZMoTIyMgG5RIb7VdBQQExMTGkpKRQUFBAeXk5iqKgUqnw8fFh6tSpBAQENNpWo9EQFRVFTEwMV65cwdzcHHd3d4KDg5kyZcojj6uva5EkNEIIIYQwevIxXAghhBBGTxIaIYQQQhg9SWiEEEIIYfQkoRFCCCGE0ZOERgghhBBGTxIaIYQQQhg9SWiEEEIIYfQsDd0BIYTQl9GjR/PTTz/p/m5mZoaNjQ12dnb06dMHX19fJk2a9Mh1i4QQxkkm1hNCtBvahGb48OGoVCqgbrXf8vJyMjMzuX37NgCjRo3ivffe09URQhg/SWiEEO2GNqHZuXMnQ4cOrbdNo9Fw9OhR1q1bR0FBAS4uLuzZs0e3arAQwrjJGBohhEkwNzcnICCAAwcO8MILL5CXl8f69esN3S0hhJ5IQiOEMCn29vasWrUKgIMHD1JaWqrblpCQwJo1a5g6dSpDhw7Fx8eHUaNGsWLFCnJychrsa+7cubi7uxMXF9fk8datW4e7uzsbNmzQlVVVVbFlyxamT5+On58fPj4+DB8+nJkzZ7Jp0yaqqqr0eMZCmAZJaIQQJmfEiBE4ODhQW1vL6dOndeWrV68mOjoaS0tLBg0axIgRI7CysuKrr74iMDCQlJSUevsJCQkBICoqqtHj3Lt3j5iYGMzNzQkKCgLqHn0tXLiQjRs3UlBQwODBgxk3bhwvvvgiRUVF/P3vf+fWrVstdOZCtF/ylpMQwuSYmZnh5eVFQkICly5d0pWvWLGCIUOGYGdnpytTFIW9e/eyevVq/vznPxMXF4eZmRlQN7i4d+/epKSkkJ2djVqtrnecb775hps3bzJy5EicnZ0BOHPmDD/88APe3t7s2rWLTp061TvW2bNnsbW1bcnTF6Jdkjs0QgiTpB0MfOPGDV1ZQEBAvWQG6pKfN998Ez8/P3Jycrh8+bJum4WFhe7OS2N3abRlwcHBurKff/4ZgIEDB9ZLZrTHGjhwIDY2Ns9yakKYJLlDI4QwSRqNBqgbLPyg4uJijh8/zpUrV6ioqNDV0yYieXl5uLm56eq/8cYbbN68mYMHD/LOO+/o7q6kpqaSkZGBs7Mzr7zyiq6+t7c3FhYWREdH4+Liwrhx4+jWrVuLnqsQpkASGiGESbp+/TpQN0hYKyIigs8//5yampom21VUVNT7u4ODA1OmTGH//v18/fXXzJo1C/jv3ZmgoKB6SdPzzz/PypUrWb9+PWvXrmXt2rU4Ozvj5+fHa6+9xpgxyuq7JgAAA0JJREFUY7CwsNDbeQphKuSRkxDC5CiKQmZmJoBu3Mt3333HX//6V6ytrXn//fc5cuQIqampZGVlkZWVxeTJk3VtHzZ79mwA9uzZA9QlS99++y3W1tYEBgY2qB8SEsKxY8cIDQ1lypQpaDQaDh48yLJlywgMDGyQNAkhHk8SGiGEyTl+/Dg3b97EyspKNwFffHw8AMuXL+eNN97A2dmZjh076trk5+c3uT8PDw8GDx5MdnY2ycnJREdHU1VVxaRJk3BwcGi0jUqlIigoiPDwcI4ePcrXX3+NWq0mMzOTLVu26PFshTANktAIIUzKzZs3+eCDDwCYNm0av/rVr3TlAD179mzQJicnR3dHpynauzS7du3S3al5cDDw43h4eDBnzhwAfvzxxyduJ4SoIwmNEMIkaDQavv/+e15//XXy8/NxdXXlD3/4g267q6srAPv37+f+/fu68rKyMlasWPHIcTVQ94aUk5MT8fHxXLt2DV9fX3x9fRvUS0xM5MSJEw32V1tby8mTJwHo1atXs89TCFMlg4KFEO3Oli1biI2NBepm5S0vL+fixYu6CesCAgJYu3ZtvQHBc+fO5auvvuL48eOMHTuWfv36UVVVRVJSEk5OTgQEBHDkyJEmj2lpaUlQUBAfffQRgG5w8MOysrL44IMP6NKlC15eXqhUKu7du0dqaiqlpaWoVCoWLFigr38KIUyGJDRCiHbn1KlTQN28LjY2NtjZ2eHt7U2/fv2YPHlygwnwAJydnYmNjWXTpk2cOXOGY8eO0aNHD2bOnMnixYsJCwt77HGHDRvGRx99hIODAxMnTmy0zujRo7l9+zbJyclcvXqVc+fO0alTJ3r16sWbb75JcHAwXbt2fbZ/ACFMkKy2LYQQevKXv/yFL774gvnz5/Puu+8aujtCmBRJaIQQQg+KioqYOHEi1dXVHD58GCcnJ0N3SQiTIo+chBDiGYSHh1NcXExCQgJ37txh3rx5kswIYQByh0YIIZ7B6NGjKSwsRKVSMW3aNJYtW4aVlZWhuyWEyZGERgghhBBGT+ahEUIIIYTRk4RGCCGEEEZPEhohhBBCGD1JaIQQQghh9CShEUIIIYTRk4RGCCGEEEbv/wEyFCPAo2npsgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1jGB4rJUKM35"
      },
      "source": [
        "## Policy Efficacy check\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wBNJZ5q6Ngf1"
      },
      "source": [
        "### Find optimal policy"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TZhAfGXVDI9Z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c50d312f-7de8-42cf-94c3-580fd6979b09"
      },
      "source": [
        "# Set policy efficiencies\n",
        "test_cap = 0.001\n",
        "hygiene = 0.30 \n",
        "distancing = 0.74 \n",
        "lockdown = 0.96\n",
        "quarantine = 0.96 \n",
        "\n",
        "# ASSUMPTIONS:\n",
        "\n",
        "# Virus parameters\n",
        "transmission_days = 16.33/2.40 \n",
        "exposed_days = 5.27 \n",
        "recovery_days = 16.33 \n",
        "r0 = 2.64\n",
        "\n",
        "transmission_rate0 = (1/ transmission_days)\n",
        "incubation_rate = (1/  exposed_days)\n",
        "recovery_rate = (1/ recovery_days)\n",
        "\n",
        "# Country parameters\n",
        "hospital_cap = 6/10000\n",
        "death_rate_with_med = 0.6 # 60% chance to die with ICU treatment\n",
        "death_rate_without_med = 1 # 100% chance to die without ICU treatment\n",
        "general_dr = 0.02 # 2% death rate\n",
        "icu_case_rate = 0.06 # 6% need ICU treatment\n",
        "ser_case_rate = 0.15 # 15% of serious cases\n",
        "\n",
        "# Initialize\n",
        "susceptible0 = 0.99\n",
        "infected0 = 0.01\n",
        "exposed0 = 0\n",
        "recovered0 = 0\n",
        "population = 1000000\n",
        "\n",
        "# Policy costs: \n",
        "lockdown_cost = 0.1 # 10% of yearly GDP\n",
        "quarantine_cost = 0.05 # 5% of  yearly GDP\n",
        "mask_cost = 0.002 # 2$\n",
        "distancing_cost = 0.05 # 5% of yearly GDP\n",
        "\n",
        "def evaluate(inf, rec, d, policy, cont_tracing):\n",
        "  ''' Calculate penalty points '''\n",
        "  dd_point = -7000 # death\n",
        "  inf_point = -0.3 # infection\n",
        "  ct_point = -6.4 # contact_tracing\n",
        "  result = sum(inf)*inf_point + d[-1]*dd_point + sum(policy) + sum(cont_tracing)*ct_point\n",
        "  return result\n",
        "\n",
        "def virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list):\n",
        "\n",
        "  assert len(hygiene_list) == len(distancing_list) == len(lockdown_list) == len(quarantine_list)\n",
        "  duration = len(hygiene_list)\n",
        "\n",
        "  susceptible =  susceptible0\n",
        "  infected = infected0\n",
        "  exposed = exposed0\n",
        "  recovered = recovered0\n",
        "  dead = 0\n",
        "\n",
        "  susc= [population * susceptible0]\n",
        "  exp = [population * exposed0]\n",
        "  inf = [population * infected0]\n",
        "  rec = [population * recovered0]\n",
        "  cont_tracing = [] #for calculating contact tracing price\n",
        "  re = [r0]\n",
        "  d = [0]\n",
        "  policy = []\n",
        "  \n",
        "\n",
        "  for day in range(duration):\n",
        "    # mitigate transmission rate (Re) by applying policies:\n",
        "    transmission_rate = transmission_rate0 * (1- hygiene_list[day]*hygiene) * (1- distancing_list[day]*distancing) * (1- lockdown_list[day]*lockdown) * (1- quarantine_list[day]*quarantine)\n",
        "    \n",
        "    # calculate loss per day for each policy\n",
        "    ld_point = - population * lockdown_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    qr_point =  - population * quarantine_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    hg_point = - population * mask_cost\n",
        "    dst_point = - population * distancing_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    policy_point = hg_point * hygiene_list[day] + dst_point * distancing_list[day] + ld_point*lockdown_list[day] + qr_point*quarantine_list[day]\n",
        "\n",
        "    # Simulate the flow between compartments\n",
        "    S2E = susceptible * infected * transmission_rate\n",
        "    E2I = exposed * incubation_rate\n",
        "    I2D = general_dr*infected/recovery_days\n",
        "\n",
        "    # Account different death rates depending on condition\n",
        "    if (icu_case_rate*infected < hospital_cap):\n",
        "      I2D += icu_case_rate*infected*death_rate_with_med/recovery_days\n",
        "    else:\n",
        "      I2D += hospital_cap*death_rate_with_med/recovery_days + (icu_case_rate*infected - hospital_cap) * death_rate_without_med/recovery_days\n",
        "    I2R = (1-general_dr)*infected*recovery_rate\n",
        "\n",
        "    # Update the compartments\n",
        "    exposed +=  S2E\n",
        "    susceptible -= S2E\n",
        "    infected += E2I\n",
        "    exposed -= E2I\n",
        "    recovered += I2R\n",
        "    infected -= I2R\n",
        "    infected -= I2D\n",
        "    dead += I2D\n",
        "\n",
        "    re.append((transmission_rate/ recovery_rate)*susceptible)\n",
        "    susc.append(population* susceptible)\n",
        "    exp.append(population* exposed)\n",
        "    inf.append(population* infected)\n",
        "    rec.append(population* recovered)\n",
        "    d.append(population* dead)\n",
        "    policy.append(policy_point)\n",
        "\n",
        "    # Append number of exposed people for each date for contact-tracing loss estimation in evaluate()\n",
        "    cont_tracing.append(S2E*quarantine_list[day]*population)\n",
        "\n",
        "  return susc, exp, inf, rec, d, re, policy, cont_tracing\n",
        "\n",
        "# h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3\n",
        "# numbers indicate month. Ex: l2 = 0.5 -> half lockdown is applied in 2nd month\n",
        "result = np.zeros((3,3,3,3,3,3,3,3,3,3,3,3), dtype = float)\n",
        "\n",
        "for index, value in np.ndenumerate(result):\n",
        "  h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3 = index\n",
        "\n",
        "  # Filter out unreasonable cases: Lockdown and social distancing in the same month \n",
        "  # OR Distacing and (distabncing + tracing) in the same month\n",
        "  if (d1!=0 and q1!=0) or (d2!=0 and q2!=0) or (d3!=0 and q3!=0) or \\\n",
        "  (l1!=0 and (q1!=0 or d1!=0)) or (l2!=0 and (d2!=0 or q2!=0)) or (l3!=0 and (d3!=0 or q3!=0)):\n",
        "    result[h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3] = None\n",
        "    continue\n",
        "\n",
        "  # Divide by two to get the policy strength: 0, 50%, 100%\n",
        "  hygiene_list = [h1/2]*30 + [h2/2]*30 + [h3/2]*30\n",
        "  distancing_list = [d1/2]*30 + [d2/2]*30 + [d3/2]*30\n",
        "  lockdown_list = [l1/2]*30 + [l2/2]*30 + [l3/2]*30\n",
        "  quarantine_list = [q1/2]*30 + [q2/2]*30 + [q3/2]*30\n",
        "\n",
        "  # Get the compartments\n",
        "  susc, exp, inf, rec, d, re, policy,cont_tracing = virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list)        \n",
        "  # Evaluate the loss\n",
        "  point = evaluate(inf, rec, d, policy,cont_tracing)\n",
        "  result[h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3] = point\n",
        "  \n",
        "#no policy case\n",
        "print(result[0,0,0,0,0,0,0,0,0,0,0,0]) \n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-197972647.11065745\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r5swxQHrYBbP",
        "outputId": "2dc721e3-16dc-4c04-db80-a417bef69373"
      },
      "source": [
        "# Optimal policy loss\n",
        "loss = np.nanmax(result)\n",
        "arg =  np.unravel_index(np.nanargmax(result), result.shape)\n",
        "print(loss, arg)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-4525982.639901729 (2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mg1kTzMwN9RL"
      },
      "source": [
        "### Plot outcomes of different combinations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4ZVRO3LkyAQ4"
      },
      "source": [
        "index = []\n",
        "index.append([0,0,0,0,0,0,0,0,0,0,0,0])\n",
        "index.append([2,2,2,0,0,0,0,0,0,0,0,0]) # hygiene\n",
        "index.append([0,0,0,2,2,2,0,0,0,0,0,0]) # distancing\n",
        "index.append([0,0,0,0,0,0,2,2,2,0,0,0]) # lockdown\n",
        "index.append([0,0,0,0,0,0,0,0,0,2,2,2]) # quarantine\n",
        "index.append([2,0,0,0,0,0,0,0,0,2,2,2]) # optimal combination"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XDXjDDq0EUUt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "79341a09-b48d-4681-8b21-9f109ff231f2"
      },
      "source": [
        "ind = np.unique(np.asarray(index), axis = 0)\n",
        "ind.shape"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(6, 12)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "drfuHGi1HTIE"
      },
      "source": [
        "# Set policy efficiencies\n",
        "test_cap = 0.001\n",
        "hygiene = 0.30 \n",
        "distancing = 0.74 \n",
        "lockdown = 0.96\n",
        "quarantine = 0.96 \n",
        "\n",
        "# ASSUMPTIONS:\n",
        "\n",
        "# Virus parameters\n",
        "transmission_days = 16.33/2.40 \n",
        "exposed_days = 5.27 \n",
        "recovery_days = 16.33 \n",
        "r0 = 2.64\n",
        "\n",
        "transmission_rate0 = (1/ transmission_days)\n",
        "incubation_rate = (1/  exposed_days)\n",
        "recovery_rate = (1/ recovery_days)\n",
        "\n",
        "# Country parameters\n",
        "hospital_cap = 6/10000\n",
        "death_rate_with_med = 0.6 # 60% chance to die with ICU treatment\n",
        "death_rate_without_med = 1 # 100% chance to die without ICU treatment\n",
        "general_dr = 0.02 # 2% death rate\n",
        "icu_case_rate = 0.06 # 6% need ICU treatment\n",
        "ser_case_rate = 0.15 # 15% of serious cases\n",
        "\n",
        "# Initialize\n",
        "susceptible0 = 0.99\n",
        "infected0 = 0.01\n",
        "exposed0 = 0\n",
        "recovered0 = 0\n",
        "population = 1000000\n",
        "\n",
        "# Policy costs: \n",
        "lockdown_cost = 0.1 # 10% of yearly GDP\n",
        "quarantine_cost = 0.05 # 5% of  yearly GDP\n",
        "mask_cost = 0.002 # 2$\n",
        "distancing_cost = 0.05 # 5% of yearly GDP\n",
        "\n",
        "def evaluate(inf, rec, d, policy, cont_tracing):\n",
        "  ''' Calculate penalty points '''\n",
        "  dd_point = -7000\n",
        "  inf_point = -0.3\n",
        "  contact_tracing_point = -6.4\n",
        "  result = [-1000*(sum(inf[:i])*inf_point + d[i]*dd_point + sum(policy[:i])+ contact_tracing_point*sum(cont_tracing[:i])) for i in range(len(d))]\n",
        "  return result\n",
        "\n",
        "def virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list):\n",
        "\n",
        "  assert len(hygiene_list) == len(distancing_list) == len(lockdown_list) == len(quarantine_list)\n",
        "\n",
        "  duration = len(hygiene_list)\n",
        "\n",
        "  susceptible =  susceptible0\n",
        "  infected = infected0\n",
        "  exposed = exposed0\n",
        "  recovered = recovered0\n",
        "  dead = 0\n",
        "\n",
        "  susc= [population * susceptible0]\n",
        "  exp = [population * exposed0]\n",
        "  inf = [population * infected0]\n",
        "  rec = [population * recovered0]\n",
        "  cont_tracing = []\n",
        "  re = [r0]\n",
        "  d = [0]\n",
        "  policy = []\n",
        "  \n",
        "  testing = 0\n",
        "\n",
        "\n",
        "  for day in range(duration):\n",
        "     # mitigate transmission rate (Re) by applying policies:\n",
        "    transmission_rate = transmission_rate0 * (1- hygiene_list[day]*hygiene) * (1- distancing_list[day]*distancing) * (1- lockdown_list[day]*lockdown) * (1- quarantine_list[day]*quarantine)\n",
        "    \n",
        "    # calculate loss per day for each policy\n",
        "    ld_point = - population * lockdown_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    qr_point =  - population * quarantine_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    hg_point = - population * mask_cost\n",
        "    dst_point = - population * distancing_cost * 30 /365 # account for 30k$ of yearly GDP\n",
        "    policy_point = hg_point * hygiene_list[day] + dst_point * distancing_list[day] + ld_point*lockdown_list[day] + qr_point*quarantine_list[day]\n",
        "\n",
        "    # Simulate the flow between compartments\n",
        "    S2E = susceptible * infected * transmission_rate\n",
        "    E2I = exposed * incubation_rate\n",
        "    I2D = general_dr*infected/recovery_days\n",
        "\n",
        "    # Account different death rates depending on condition\n",
        "    if (icu_case_rate*infected < hospital_cap):\n",
        "      I2D += icu_case_rate*infected*death_rate_with_med/recovery_days\n",
        "    else:\n",
        "      I2D += hospital_cap*death_rate_with_med/recovery_days + (icu_case_rate*infected - hospital_cap) * death_rate_without_med/recovery_days\n",
        "    I2R = (1-general_dr)*infected*recovery_rate\n",
        "\n",
        "    # Update the compartments\n",
        "    exposed +=  S2E\n",
        "    susceptible -= S2E\n",
        "    infected += E2I\n",
        "    exposed -= E2I\n",
        "    recovered += I2R\n",
        "    infected -= I2R\n",
        "    infected -= I2D\n",
        "    dead += I2D\n",
        "\n",
        "    # Append number of exposed people for each date for contact-tracing loss estimation in evaluate()\n",
        "    re.append((transmission_rate/ recovery_rate)*susceptible)\n",
        "    susc.append(population* susceptible)\n",
        "    exp.append(population* exposed)\n",
        "    inf.append(population* infected)\n",
        "    rec.append(population* recovered)\n",
        "    d.append(population* dead)\n",
        "    policy.append(policy_point)\n",
        "    cont_tracing.append(S2E*quarantine_list[day]*population)\n",
        "  \n",
        "  return susc, exp, inf, rec, d, re, policy, cont_tracing"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k1O6Sq-Wz7tE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "db9d51df-7a38-42ab-b996-1854d373bfc2"
      },
      "source": [
        "# Plot\n",
        "figure(figsize=(10, 6), dpi=80)\n",
        "legends = ['No policy (worst)', 'Hygiene & Mask', 'Distancing', 'Lockdown', 'Distancing + tracing', 'Optimal policy']\n",
        "al = [0.7]*5+[1]\n",
        "col = cm.rainbow(np.linspace(0, 1, 6))\n",
        "plt.yscale('log')\n",
        "for i,indice in enumerate(index):\n",
        "  h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3 = indice\n",
        "  hygiene_list = [h1/2]*30 + [h2/2]*30 + [h3/2]*30\n",
        "  distancing_list = [d1/2]*30 + [d2/2]*30 + [d3/2]*30\n",
        "  lockdown_list = [l1/2]*30 + [l2/2]*30 + [l3/2]*30\n",
        "  quarantine_list = [q1/2]*30 + [q2/2]*30 + [q3/2]*30\n",
        "  susc, exp, inf, rec, d, re, policy,cont_tracing = virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list)        \n",
        "  point = evaluate(inf, rec, d, policy,cont_tracing)\n",
        "  m = [m for m in range(91)]\n",
        "  plt.plot(m, point, label=legends[i], alpha = al[i], color = col[i])\n",
        "  plt.plot()\n",
        "\n",
        "plt.legend(loc = 'upper left', fontsize = 20)\n",
        "plt.ylim([10**9, 10**12])\n",
        "plt.xlim([0, 91])\n",
        "plt.xlabel('Day(s) from start', fontsize = 20)\n",
        "plt.ylabel('Loss ($)', fontsize = 20)\n",
        "sns.despine()\n",
        "plt.rcParams[\"figure.figsize\"] = (10, 10)\n",
        "plt.tick_params(labelsize=20)\n",
        "plt.savefig('./content/sample_data/loss.pdf')\n"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 800x480 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "04_OdXai26la"
      },
      "source": [
        "### Make table"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N26AEli5h0o1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "33a70983-5b79-4a9e-f14d-406229194b8d"
      },
      "source": [
        "# Code abbreviations\n",
        "res = []\n",
        "keys = ['M', 'D', 'L', 'T']\n",
        "for i,indice in enumerate(index):\n",
        "  h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3 = indice\n",
        "  hygiene_list = [h1/2]*30 + [h2/2]*30 + [h3/2]*30\n",
        "  distancing_list = [d1/2]*30 + [d2/2]*30 + [d3/2]*30\n",
        "  lockdown_list = [l1/2]*30 + [l2/2]*30 + [l3/2]*30\n",
        "  quarantine_list = [q1/2]*30 + [q2/2]*30 + [q3/2]*30\n",
        "  susc, exp, inf, rec, d, re, policy,cont_tracing = virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list)        \n",
        "  point = evaluate(inf, rec, d, policy,cont_tracing)\n",
        "  print(point)\n",
        "  label = ''\n",
        "  for i in [0, 3, 6, 9]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [0, 3, 6, 9]]) == 0:\n",
        "      label += '-'\n",
        "  label += ' | '\n",
        "  for i in [1, 4, 7, 10]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [1, 4, 7, 10]]) == 0:\n",
        "      label += '-'\n",
        "  label += ' | '\n",
        "  for i in [2, 5, 8, 11]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [2, 5, 8, 11]]) == 0:\n",
        "      label += '-'\n",
        "  res.append([label, int(1000000-susc[-1]), int(d[-1]), point[-1]/1000000000])\n",
        "\n",
        "\n"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-0.0, 243048989.58971217, 470678582.1668743, 690577331.1735109, 908237760.8551673, 1127633311.3754811, 1351688723.9838376, 1582607088.6732883, 1822097374.9588842, 2074236122.0474293, 2342150151.2319617, 2627239907.0491276, 2930770376.0273614, 3253924474.7595596, 3597840495.176862, 3963638463.533936, 4352438784.206866, 4765375507.530481, 5203605843.889663, 5668317047.890548, 6160731449.867514, 6682110170.847734, 7233755889.18961, 7817014910.067934, 8433278707.264355, 9083985049.549042, 9770618783.818312, 10494712318.882685, 11257845833.772503, 12061647220.14198, 12907791758.07521, 13798001517.133377, 14734044469.007896, 15717733294.09704, 16750923861.323364, 17835513358.30278, 18973438047.40031, 20166670622.162304, 21417217138.044987, 22727113491.241478, 24098421419.742825, 25533224001.568817, 27033620626.39734, 28601721418.640667, 30239641092.40032, 31949492221.718967, 33733377913.174995, 35593383872.168655, 37531569859.25571, 39549960538.61687, 41650535727.21853, 43835220060.41985, 46105872097.69389, 48464272900.72205, 50912114125.33215, 53450985678.5054, 56082363001.872955, 58807594053.63102, 61627886071.472855, 64544292209.78891, 67557698154.818344, 70668808831.42566, 73878135324.47755, 77185982146.15268, 80592434987.66104, 84097349099.51114, 87700338448.37553, 91400765800.51762, 95197733881.4246, 99090077758.5454, 103076358588.70189, 107154858863.72156, 111323579277.08357, 115580237320.89357, 119922267706.4011, 124346824682.70491, 128850786307.49924, 133430760701.00723, 138083094290.00644, 142803882023.51147, 147588979515.73682, 152434017045.93054, 157334415319.1069, 162285402867.15317, 167282034946.788, 172319213769.91507, 177391709883.50772, 182494184500.68335, 187621212572.41122, 192767306380.5876, 197926939428.16144]\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DyiAWep25AhV"
      },
      "source": [
        "Table represents loss regarding applied policies. The most effective policy combination is listed at the top. The meaning of policy notatioin is as follows:\n",
        "\n",
        "*   None: Doing nothing\n",
        "*   Uppercase: full efficacy\n",
        "*   Lowercase: half efficacy\n",
        "\n",
        "\n",
        "*   L/l: Lockdown\n",
        "*   T/t: Tracing with distancing\n",
        "*   D/d: Distancing\n",
        "*   M/m: Masks and Hygiene\n",
        "\n",
        "*Example: L | l | D denotes the consecutive policy execution of full lockdown (1st month), half lockdown (2nd month) and full distancing (3rd month).*\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "57Np49ZUVcES",
        "outputId": "108b4eb9-ff5f-4006-e611-fab6b39e29e9"
      },
      "source": [
        "df = pd.DataFrame(res, columns = ['Policy combination', 'Cases', 'Deaths', 'Loss'])\n",
        "df = df.set_index('Policy combination')\n",
        "df.sort_values(by='Loss')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Cases</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Loss</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Policy combination</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>MT | T | T</th>\n",
              "      <td>10734</td>\n",
              "      <td>577</td>\n",
              "      <td>4.525967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>T | T | T</th>\n",
              "      <td>11003</td>\n",
              "      <td>591</td>\n",
              "      <td>4.569165</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L | L | L</th>\n",
              "      <td>11003</td>\n",
              "      <td>591</td>\n",
              "      <td>4.932606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D | D | D</th>\n",
              "      <td>22478</td>\n",
              "      <td>1138</td>\n",
              "      <td>8.436941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>M | M | M</th>\n",
              "      <td>201929</td>\n",
              "      <td>8941</td>\n",
              "      <td>63.400395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | -</th>\n",
              "      <td>592136</td>\n",
              "      <td>28018</td>\n",
              "      <td>197.926939</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Cases  Deaths        Loss\n",
              "Policy combination                            \n",
              "MT | T | T           10734     577    4.525967\n",
              "T | T | T            11003     591    4.569165\n",
              "L | L | L            11003     591    4.932606\n",
              "D | D | D            22478    1138    8.436941\n",
              "M | M | M           201929    8941   63.400395\n",
              "- | - | -           592136   28018  197.926939"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "swtj_irH4gCv"
      },
      "source": [
        "# More results"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m_cFJnMzBDVP"
      },
      "source": [
        "# For more results:\n",
        "def k_largest_index_argsort(a, k):\n",
        "    idx = np.argsort(a.ravel())[-k:]\n",
        "    return np.column_stack(np.unravel_index(idx, a.shape))\n",
        "\n",
        "def k_smallest_index_argsort(a, k):\n",
        "    idx = np.argsort(a.ravel())[:k]\n",
        "    return np.column_stack(np.unravel_index(idx, a.shape))\n",
        "\n",
        "x = result\n",
        "# Choose bottom k combinations\n",
        "k = 5\n",
        "idx = k_smallest_index_argsort(x, k)\n",
        "index.extend(idx.tolist())\n",
        "\n",
        "# Choose top n combinations\n",
        "n = 5\n",
        "idx = k_largest_index_argsort(x, n)\n",
        "index.extend(idx.tolist())"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "98qyxcTO4sHi",
        "outputId": "b4a6089d-349f-4ac1-a835-d37a337d7d84"
      },
      "source": [
        "res = []\n",
        "keys = ['M', 'D', 'L', 'T']\n",
        "for i,indice in enumerate(index):\n",
        "  h1, h2, h3, d1, d2, d3, l1, l2, l3, q1, q2, q3 = indice\n",
        "  hygiene_list = [h1/2]*30 + [h2/2]*30 + [h3/2]*30\n",
        "  distancing_list = [d1/2]*30 + [d2/2]*30 + [d3/2]*30\n",
        "  lockdown_list = [l1/2]*30 + [l2/2]*30 + [l3/2]*30\n",
        "  quarantine_list = [q1/2]*30 + [q2/2]*30 + [q3/2]*30\n",
        "  susc, exp, inf, rec, d, re, policy,cont_tracing = virus_model(hygiene_list, distancing_list,lockdown_list,quarantine_list)        \n",
        "  point = evaluate(inf, rec, d, policy,cont_tracing)\n",
        "  print(point)\n",
        "  label = ''\n",
        "  for i in [0, 3, 6, 9]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [0, 3, 6, 9]]) == 0:\n",
        "      label += '-'\n",
        "  label += ' | '\n",
        "  for i in [1, 4, 7, 10]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [1, 4, 7, 10]]) == 0:\n",
        "      label += '-'\n",
        "  label += ' | '\n",
        "  for i in [2, 5, 8, 11]:\n",
        "    if indice[i] == 2:\n",
        "      label += keys[i//3]\n",
        "    if indice[i] == 1:\n",
        "      label += keys[i//3].lower()\n",
        "  if sum([indice[i] for i in [2, 5, 8, 11]]) == 0:\n",
        "      label += '-'\n",
        "  res.append([label, int(1000000-susc[-1]), int(d[-1]), point[-1]/1000000000])\n",
        "\n",
        "\n"
      ],
      "execution_count": 12,
      "outputs": [
        {
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 576
        },
        "id": "lcacXdor4fdo",
        "outputId": "11eb5d22-20c5-47e7-e880-1bfccdad15fe"
      },
      "source": [
        "df = pd.DataFrame(res, columns = ['Policy combination', 'Cases', 'Deaths', 'Loss'])\n",
        "df = df.set_index('Policy combination')\n",
        "df.sort_values(by='Loss')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Cases</th>\n",
              "      <th>Deaths</th>\n",
              "      <th>Loss</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Policy combination</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>MT | T | T</th>\n",
              "      <td>10734</td>\n",
              "      <td>577</td>\n",
              "      <td>4.525967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>T | T | T</th>\n",
              "      <td>11003</td>\n",
              "      <td>591</td>\n",
              "      <td>4.569165</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>L | L | L</th>\n",
              "      <td>11003</td>\n",
              "      <td>591</td>\n",
              "      <td>4.932606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MDLT | MDLT | MDLT</th>\n",
              "      <td>10006</td>\n",
              "      <td>539</td>\n",
              "      <td>5.482550</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D | D | D</th>\n",
              "      <td>22478</td>\n",
              "      <td>1138</td>\n",
              "      <td>8.436941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mt | Lt | Dl</th>\n",
              "      <td>26023</td>\n",
              "      <td>1378</td>\n",
              "      <td>10.463221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mt | Lt | Dlt</th>\n",
              "      <td>25736</td>\n",
              "      <td>1370</td>\n",
              "      <td>10.472406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mt | L | DlT</th>\n",
              "      <td>25887</td>\n",
              "      <td>1383</td>\n",
              "      <td>10.561816</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>m | L | DT</th>\n",
              "      <td>59338</td>\n",
              "      <td>3502</td>\n",
              "      <td>25.313706</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>M | M | M</th>\n",
              "      <td>201929</td>\n",
              "      <td>8941</td>\n",
              "      <td>63.400395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | m | -</th>\n",
              "      <td>515900</td>\n",
              "      <td>23447</td>\n",
              "      <td>165.681432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | d</th>\n",
              "      <td>453512</td>\n",
              "      <td>23862</td>\n",
              "      <td>168.641122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | M</th>\n",
              "      <td>478792</td>\n",
              "      <td>24620</td>\n",
              "      <td>173.993851</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | m</th>\n",
              "      <td>534917</td>\n",
              "      <td>26295</td>\n",
              "      <td>185.788009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | -</th>\n",
              "      <td>592136</td>\n",
              "      <td>28018</td>\n",
              "      <td>197.926939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>- | - | -</th>\n",
              "      <td>592136</td>\n",
              "      <td>28018</td>\n",
              "      <td>197.926939</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     Cases  Deaths        Loss\n",
              "Policy combination                            \n",
              "MT | T | T           10734     577    4.525967\n",
              "T | T | T            11003     591    4.569165\n",
              "L | L | L            11003     591    4.932606\n",
              "MDLT | MDLT | MDLT   10006     539    5.482550\n",
              "D | D | D            22478    1138    8.436941\n",
              "mt | Lt | Dl         26023    1378   10.463221\n",
              "mt | Lt | Dlt        25736    1370   10.472406\n",
              "mt | L | DlT         25887    1383   10.561816\n",
              "m | L | DT           59338    3502   25.313706\n",
              "M | M | M           201929    8941   63.400395\n",
              "- | m | -           515900   23447  165.681432\n",
              "- | - | d           453512   23862  168.641122\n",
              "- | - | M           478792   24620  173.993851\n",
              "- | - | m           534917   26295  185.788009\n",
              "- | - | -           592136   28018  197.926939\n",
              "- | - | -           592136   28018  197.926939"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    }
  ]
}