Finanças_Quantitativas_Automação_de_Funções.ipynb

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  "metadata": {
    "colab": {
      "name": "Finanças Quantitativas- Automação de Funções.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMdaMZA8/nJbQxX49AOMUWP",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/SamuelSousaFerreira/Mercado-Financeiro/blob/main/Finan%C3%A7as_Quantitativas_Automa%C3%A7%C3%A3o_de_Fun%C3%A7%C3%B5es.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GqM3_8jIJ1Xc"
      },
      "source": [
        "# **Python para Finanças Quantitativa**\n",
        "Curso do canal [**Outspoken Market**](https://youtu.be/o_-YNEKQE_U)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LaaSBF9rfXyS"
      },
      "source": [
        "#Carregando as bibliotecas necessárias\n",
        "\n",
        "from pandas_datareader import data as pdr #suporte para download do yahoofinance\n",
        "from datetime import date\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6128CD-HggxM",
        "outputId": "33aeb8e2-371a-4206-deaf-eb9caebe5596"
      },
      "source": [
        "!pip install yfinance #instalando\n",
        "import yfinance as yf\n",
        "yf.pdr_override()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.59)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.19.5)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.9)\n",
            "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.7/dist-packages (from yfinance) (2.23.0)\n",
            "Requirement already satisfied: pandas>=0.24 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.1.5)\n",
            "Requirement already satisfied: lxml>=4.5.1 in /usr/local/lib/python3.7/dist-packages (from yfinance) (4.6.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2020.12.5)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (1.24.3)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2.8.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24->yfinance) (1.15.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F9adRgoihn3j"
      },
      "source": [
        "# configurações iniciais\n",
        "ticker = \"^BVSP\" #ativo \n",
        "inicio = '2015-01-01'\n",
        "fin = '2021-06-01'"
      ],
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5llV6ElViKt9",
        "outputId": "75aa5be8-cdd3-4cb7-f680-6a43b62e9422"
      },
      "source": [
        "# Coleta de dados\n",
        "df = pdr.get_data_yahoo(ticker, start=inicio, end=fin) #método do pdr"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "13Em6IN3i94E",
        "outputId": "dbc1fb72-a6f3-47bf-e9d6-bf376c8e1ce9"
      },
      "source": [
        "df.tail()"
      ],
      "execution_count": 85,
      "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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2021-05-25</th>\n",
              "      <td>124032.0</td>\n",
              "      <td>124696.0</td>\n",
              "      <td>122701.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>8914500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-26</th>\n",
              "      <td>122988.0</td>\n",
              "      <td>124256.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>123989.0</td>\n",
              "      <td>123989.0</td>\n",
              "      <td>8258400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-27</th>\n",
              "      <td>123989.0</td>\n",
              "      <td>124537.0</td>\n",
              "      <td>123470.0</td>\n",
              "      <td>124367.0</td>\n",
              "      <td>124367.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-28</th>\n",
              "      <td>124367.0</td>\n",
              "      <td>125698.0</td>\n",
              "      <td>124284.0</td>\n",
              "      <td>125561.0</td>\n",
              "      <td>125561.0</td>\n",
              "      <td>8838500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-31</th>\n",
              "      <td>125561.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>125540.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>5946500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                Open      High       Low     Close  Adj Close   Volume\n",
              "Date                                                                  \n",
              "2021-05-25  124032.0  124696.0  122701.0  122988.0   122988.0  8914500\n",
              "2021-05-26  122988.0  124256.0  122988.0  123989.0   123989.0  8258400\n",
              "2021-05-27  123989.0  124537.0  123470.0  124367.0   124367.0        0\n",
              "2021-05-28  124367.0  125698.0  124284.0  125561.0   125561.0  8838500\n",
              "2021-05-31  125561.0  126216.0  125540.0  126216.0   126216.0  5946500"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 841
        },
        "id": "MXUSkLLajE4c",
        "outputId": "1ba7399d-0eae-4780-d690-935a7f25f4cb"
      },
      "source": [
        "# Primeiro gráfico\n",
        "df['Adj Close'].plot(grid=True, figsize=(20,15), linewidth=3, \n",
        "                     fontsize=15, color='darkblue')\n",
        "plt.xlabel('Data', fontsize=15);\n",
        "plt.ylabel('Pontos', fontsize=15);\n",
        "plt.title('Ibovespa - Python Finanças Quantitativas', fontsize=15);\n",
        "plt.legend();\n"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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JwzRoUE7U57lkya6Qxu3Y4b8i7PPPP5ExJpJT6lASPvSS9P8kjZU00bIs/53ZEpRlWU/I1Qz/yCOPtCZNmhTfCUXI/PnzlSzfCzoO7jvEA/cd4oV7D/HAfYd44L5DvDQ0tCziOvro0Zo0aYAkqW/fHdq4sViSdNBBIzRp0kBJ0qpVe/Tqq0sl2VVijz9eqs8//1nU5/nFF19I2iJJSk83amy0/I6rrvbfSeqEE06I1tQ6hIRe3miM+ZXspzdealnWF16HyyR18fO2QrVUXzX/6T2u0Ot4JM8FAAAAAIiA4uJy/eMfy7V16/54TwVJwLIs1dTYLcT37WtpJd6tW0vFVteu/nt6XXPNBx7nWrRou/bu9d88PpKcyxvHjesb9eslm4QNvYwx50h6VNKtlmXN9jNkrVr6bDW/J0vSELX03Wr+02Oca7vUsqzdjnGROhcAAAAAIAKmTn1dV1/9gX7609dlWf4rXIBQNDY2aeLE2Soo+ItmzPhGZWUtC8kOOKCz+3VeXkvj94qKljEff1zsc86//vWrKM22hTN4GzeuT5CRtn798nXmmQcpIyNNjzwyOZpT6xASMvQyxkyS9LykRy3LeijAsLmSjjLGDHTs+6mkbEn/kSTLsr6T3fz+PMe501zbc6N0LgAAAABAO9XVNerLL3dKkpYv3+Wu0AHC8cknxfrkk2LV1zfpl798V/v3N0qS0tKMundvqfTKy8tyv66srNftt3+isWOf93vOO+74VA0N/pcVRooz9DrssG6tju/Zs7Nee+1M7dt3na6//ohoTq1DiHlPL2NMZ0k/dm32lVRgjDnXtf2OpIGSXpddWTXbGHOs4+27Lcv61vV6jqTbJb1qjLlD9rLD/5P0gmVZGxzvuVvSv4wx30v6VNKlkoZKusgxJpLnAgAAAAC0U2WlZ0vniop65eRkBhgNBLdxo79n10ndu+coPb2lHshZ6TVv3ma98soGf29zy8x8WLfddrSystJ12WUjNHCgv85J4du7tyX06tIlW+PG9dFnn/0QcHzzkyg7d+bvihSfRvY9Jb3sta95e7CkY2SHTodL+sxr3LOSpkmSZVn1xphTJf1V0kuSaiW9KLsHmJtlWbOMMXmSfs6groYAACAASURBVCvpDkmrJP3EsqyVjjEROxcAAAAAoP0qKuo8tsvL69SjR+cAo4HgNm/23xeuZ0/Peyo3tyUs8rek0Z/7718sya4m+/DD/wpzhv5t21bhft27d66ee+7HeuSRL3X00b10112f6dtvPcO8Tp3SI3r9ji7moZdlWd9LCva8zJmur1DOVSzpzBDGPSnpyVidCwAAAADQPu+9t9lju7y8LsBIoHVr1pT43e/s5yUF7ukVik8+2aaGhiZlZESuk9SWLS1h3YABBerVK9fdq6u0tEbXX/+hx/isLEIvp4Ts6QUAAAAASF3Llu3Q9Onveuwj9EK4LMvSwoXb/B474IBcj21npVeofeQKC+0nPjY0NAWsKAtHRUWdSkvtJ0RmZaX7VKV17Zrt8x6e9+CJ0AsAAAAAEHPV1fVavbpCjY2+jcCnTHnFZ19bq26AZhs2lGnnziq/x7yDJGcj+1D07Zunww/v4d5ev7607RMMYNOmfe7XAwbkKy3Nc9HcSScNVEGB53ybmki9nAi9AAAAAAAxZVmWxo2bpWuuWetT0bVp016VlFT7vIdKL4RrwYKW3lzjx/fzOFZX1+ix7az0CkV6uvEIzvbti9x9um5dS4B28MGFPsd7987Txo3TPfYRenki9AIAAAAAxNTq1SVavnyXJGnmzFUex7y3mxF6IVzO0OuMM4bo9NOHuLdPPHGAx1hnT69QZGSkuZ+YKEm1taEtiWxNfX2jHnvsa/f2wQcX+R3n/XAHi/WNHgi9AAAAAAAxVV3tGQw4q1O2bi33+x5CL7RFTU2DSkvtikFn6DVhQn8988ypmjy5SNddN1pnnHGgx/tCWd543XWj3a9vvfVor9Cr0d9b2uzKK9/Xhx9ucW8fcohvpZc/VHp5ivnTGwEAAAAAqc07wNq/v1Zdu9rNwAM1D6+spKcXQrN58z6NGvVPVVc36IknTnE3l+/cOUNHHNFTmZnpuuOOIZo0aZLPe1tb3pidna677x6n+vomdemSrV/+8kdauXKP+3hNTWRCr2eeWemxHajSy1uTb4u8lEboBQAAAACIqbKyGp/t5tDLuwqsGaEXQnXNNfO0d2+tJOnSS+e6948b11eZmemB3iap9eWNXbpkq6goR489drJ7X6SXN/qr1qLSKzwsbwQAAAAAxFRZWW3A7UCVXjy9EaF6++3v/O4fP75vq+9trdKrsLCTz75IL29sXpbp1KdPXkjvJfTyROgFAAAAAIgpf5Vekt2Ee+XKEr/vodIL7XX88f1aHdNaT6/CwmyffZ06tSyii0TotXu3b+hljAnpvYRengi9AAAAAAAx5R167dpVJUm66aaPVFzsv5F9RQWN7BGaggL/wVXfvq1XS3XuHLwLVGuVXoEqFdti6dIdbRqfk9My58MO69bu6ycTQi8AAAAAQEx5h15Ll+5QY2OTHnnky4DvodILoUpP9x91OMOhYO8NNi7ayxurqur185/P9dg3c+apQd/z3nvnKjc3U7175+qPf5zQrusnGxrZAwAAAABixrIsn55eixZt18aNe4O+j9ALoQr0MITWqria5eVlBjxH166+yxsjGXqtWLHbY/uyy0bokkuGB33P8cf3044dVys7O73VRv2phtALAAAAABAT118/Ty+9tE47d1Z57F+2bKe+/HJn0PfSyB6hsCwr4BLDzp2DN6lvlpub6bevliR1757js8/Z06u9yxt/+KHCY/upp6aE1M+rtV5kqYrQCwAAAAAQdatW7dGjj37l91htbaPeeWdT0PdT6YVQ1NUFrrRyhlPBBAuQBg4s8NkXyUovZ+h15ZWHh9zAHv7R0wsAAAAAEHXr1pUGPf7aaxuCHif0QihqavyHTjk5GUpLCy1AGj26Z8Bjgwd38dkXidDLsiwtWLBVy5a1VDyG0ngfwRF6AQAAAACiLtBysWathVrBljdalhXWnJB8Ai0vDKWJfbOzzx4a8Ji/0MtZQRZu6HXHHZ9q4sTZmjlzlXtfnz6EXu1F6AUAAAAAiLpNm/a1+T0ffni++7W/UKyurlEnnDBbAwY8oc8+29au+SE5BG5iH1o/L0maMmWQcnP9j+/XL99nn7PSK5SeXpZlqaGhyWPfffct8hnXp09uq+dCcIReAAAAAICo8xd6paeboH2WJk3qr+aWRjU1DVq06AeP43//+3LNn79VxcXlOuWUObr11o916qlztHr1nojOHR1H4Cb2oVd65eRk6vTTh/g9lpHhG6O0ZXljaWm1hg17Rv36/aPVhzdQ6dV+hF4AAAAAgKjzF3oVFmbo4IMLA77HGONRcTN27Avat6/Wvb148Xb368rKej344BK9++73OuecNyM0a3Q0gXp6taXSS5LOOcd3iWOvXv4rr9oSev33f3+idetKtXNnlc4447WgYwm92o/QCwAAAAAQdf5Cr7y8dB10UFe/46dMGSRJPsvM3nrrW/fr9HT/v9KuXRu8aT6SV6BKr7Y+BPHUUwf77OvXz38I5axWbG154+LFO9yvf/ihQk1N/vvRZWamqVu3nFCmiiAIvQAAAAAAUVVRUac9e3wb2XfqlOY39Bo/vp9mzjxNkm/oVVfXqIaGJu3bV6uMjDYmGUh6gUKntj7roKAg22efv35eUtsqvdLTPe/ZWbPW+B3Xu3duyE+bRGChL2oFAAAAACAMgZrYf/tttYYP7+6x77DDumnBggvc23l5WR7Hd+yo1KBBT6ikpEY9elAJA0+BGtkXFXVq97n7929/6OUdZF188Tu66KJhPuNY2hgZhF4AAAAAgKgKFHr17Zut0aN7euzz7pvkXel1++0L3a+3bi2P0AyRLMrL6/zuv/DCQ9t97kmT+vvd71ze2Fro5a8Rvr/3EHpFBssbAQAAAABRtW5dS4+t8eP7uStjLr20jw49tMhjbGGh57Iy79ALCKaiot79evTonjryyAN00UXD9ItfjGjzuQ480HPp7Vln+Ta3lzwrvXbtqtKHH26RFWA9pffyRsl+CIM3Qq/IIPQCAAAAAETVp5/+4H598cXDtGHDL/XNN5dq0qQiZWame4z1rnoh9EJbOCu9jjuur5YsuUTPP396wIceBPPWW2fpmGN669xzD1Zt7U0yAbrhO0MvSTrxxJf03nvf+x3rr0+Xv+o0Qq/IYHkjAAAAACBqLMvSp59uc28ff3xf9e9foP79pfnzfcd792Tq1CnddxAQgLPSKy+vfYHpsGHdtGjRz1odl53tG63cdNNHWr3a9wmQ/iq9Nmwo89nXu3euzz60HZVeAAAAAICoWb++zP3kxsLCTjr00G4+Y5yNvK+66nCPY/56IAH+PPvsSv3+9y093/Lzs4KMjpy0NKPMTM/7NFBVmL9Kr6++2uWzr3t3HtIQCVR6AQAAAACi5rnnVrtfH3dcH7+/9D/00ESlpRn16ZOrs88+2OMYoRdCUVvboF/96gOPfbEKvSR7iWN9fZN7e8CAfK1fX6qLL35HPXt21ssvn6GcnEy/yyxfeGGNz76uXbN99qHtCL0AAAAAAFFRVVWv++5b5N4+/vi+fsf17p2n5577sd9j4YZelmUFrLZB8lmzplRVVZ5LY9u7vLEtsrMzPJZW9uqVq5/97G0tXbpTknTvvYs0depBfhvcf/31bp99hx/e02cf2o7IHAAAAAAQFWvXlnpsT5ni2+OoNeGGXt4N8ZHcVq7c47OvU6fY1fl4957LzEx3B16S9Ic/fKFjjnle77+/Oeh5TjttsD788PyYVqklMyq9AAAAAABRUVpa47E9alTbq1cyMsKr1qqpaYhp6IH42r69wmff0KGFMbu+9xMc/S3jbc2AAfl6++2zqVCMICq9AAAAAABRUVpa7X59zjlDwzoHlV4Ihffnfe+9x2vMmANidn3vXl1NTb7LGFtz8smDCLwijNgbAAAAABAVzkqvoqLwnkYXbuhVU9PQ+iAkjbq6ltDr7rvH6fbbj43p9b0ruxoamgKMDOzQQ4siNR24UOkFAAAAAIiKkpKW0Ktbt05hnSMnJ7xaDWdTcSQ/Z6VXVlZ6kJHRkeaVroQTehUU0Mcr0gi9AAAAAABR4VzeWFQUXuh13XWjw+rNtW9fbVjXQ8dUV9cSMnn314oF72WJ9fVtD726dMmO1HTgQugFAAAAAIiKffvq3K/D/YW+Z89cLVnys5DGOq+xdy+hVyqprW1ZzpqVFfuow7sVF5VeiYHQCwAAAAAQFdXVLUFE586ZYZ9nxIgeuvjiw4KO2bTpcp122mD3dllZTZDRSDaelV6xb18eiZ5eVHpFHqEXAAAAACAqnM3kO3Vq35Kz777bG/R4r165Kiyk0itVORvZx6PSyzv0Cmd5I5VekUfoBQAAAACICmelV7gN6ZutXl0S9HhmZpq6dm3pG0bolRo2bizTww8v1bvvfu/eF49KL++eXsEqvQ45pEi33HKUT6+6ggIqvSKN0AsAAAAAEBWeoVf4yxsl6eqrRwU8ZoyUnp6mrl1bQgOWNya/piZLkye/pJtvnq9du6rc++PRyD7U5Y0TJ/bT2rWX6YEHJvpUP1LpFXmxjz8BAAAAACkhkssbr7/+CH311U5lZaXrjDMO1OWXv+c+lpVlnzs/vyU0qKysb9f1kPh2767S1q3lPvsToZF9oOWNziq0nJwMj4rE9vS9g3+EXgAAAACAqIjk8sZevXI1d+65kqRly3Z4HMvMtEMOZ7DmvDaSU0lJtd/9idzI3hnINYe1zZrvY0QOP1EAAAAAQFREMvRyGjq00GM7Pb059Gq5hrPKDMmppMT/EtZEaGQfKPQKtvTSuy8Y2o/QCwAAAAAQFZ7LGyMXenk3/N63z14i5gzWamoaheS2Z0/iVHqFs7wR0UfoBQAAAACIimhVeknSgAH5Pvuo9EotgZY3xqenl2+lV3q6b+WWc24ZGUQy0cZPGAAAAAAQFdEMvQYN6uKzj55eqSVQ6NW83DWWvJc31tc3qbHR8hnnrPQi9Io+fsIAAAAAgIirrq73CJ4iubxRkgYOLPDZl5PT8vQ7Kr2S3/79dX73V1XF/smd3qFXoNDV2dPLXyUYIovQCwAAAAAQUbNmrVFBwaPuSpe0NBPxJ9P5C72clV709Ep+gUKvQw8tivFMpFGjenhsV1b6D96cFY+EXtFH6AUAAAAAiKjLLnvX4+l1+flZEX8y3U9+cqD79ZAh9lJHZzUZyxuTX3l5S+h1441jNH36j/TGG2eqa9dOMZ/LPfcc71HF5ZybU+fOLG+MJR4bAAAAAACImKYmy2dpYY8eORG/zjHH9NZ99x2v99/frD/8Ybwk70ovQq9k56z0Ou64Pjr33EPiNpcuXbL17bfT1a/f45Kk2lr/lYadO7cswSX0ij5CLwAAAABAxGzbVu6zr3v3yIdekvS73x2r3/3uWPe2c+kYoVfyc1ZT5ednxXEmtqys9FbHOCu9WN4YfcSKAAAAAICI+eGHSp99/p5iFw3O5Y309Ep+ztCroCA7jjOxhRJ65eZS6RVL/IQBAAAAABFTUeHby+ibb/bE5Nr09Eot+/fXul/n52cGGRkbzp5egTiXN95+e0uV4q9/PSYqc0p1LG8EAAAAAERMRYXvU+uuu250TK6dmZkmYyTLkhoamtTQ0EQ1TRIrL2+51zri8sYpUwbpscdO0g8/VOjXvz4ymlNLWYReAAAAAICI8a70Gj++n66//oiYXNsYo5ycDFVV2VVetbUNysiIfxiCyGtqsrRrV5V7u1u36PSNa4u0NKOMjDSPJ5d6c1Z6GWN01VWjYjG1lEXkDQAAAACIGGel1+WXj9SCBReoX7/8mF2fvl6pYefOStXV2Z9vUVEn5eUlRrjZ2hJHZ+iF6CP0AgAAAABETGVlS+iVlxf7X/Dp65UaNm/e7349cGBBHGfiqbUljrm5LLiLJX7aAAAAAIB2syxLq1bt8VhyFp/QqyV0qKkh9EpWxcXl7tcDBiRO6NVapVdODpVesUToBQAAAABot3vu+Vx33fWZx77c3Nj/gp+T41zeSOiVrJr7tklSQUFiLG2UWg+9ioo6xWgmkFjeCAAAAACIgFmz1vrsi0efJZY3pobmfl5SaE9NjJXW5tK1a3aMZgKJ0AsAAAAA0E6WZWnt2lKf/fGowKGRfWrwDL0SJ9pordLLGBOjmUAi9AIAAAAAtFNZWY3f/SNGdI/xTOjplSpKS1vuuUSq9Got9EJs0dMLAAAAANAuW7eW+90/fHjsQy/Pnl5UeiWjiy76t8dy2kQKvRJpLqDSCwAAAADQTmvW+C5t/O1vj45LAODZ06s+5tdHdG3YUObTPy6RgibvSq8+ffLcr2+6aUysp5PyqPQCAAAAALTLN9/sdr++7bajddttx6hLl/g07KanV3Jbv943YE2knl7eAdyYMQfoH/84WevWleryy0fGaVapi9ALAAAAANAuGzaUuV8fdli3uAVekvfyRnp6JZsFC4p99iVypdeAAfk644wDdcYZB8ZpRqktceJQAAAAAECHVFHRsoywqKhTHGfi3cieSq9kYlmWnnlmpc/+RAq9Vq8u8di+7roj4jQTSIReAAAAAIB2qqxsCb1yczPjOBN6eiWz7dsrtXt3tc/+RFreeOKJA9yvzz57qA45pCiOswHLGwEAAAAA7ZJYoReVXslq1ao9fvcnUqXXtdeO1tKlO9W/f75mzjwt3tNJeYReAAAAAAAPlmVpxoyV2rp1v268cYy6dg2+ZDGRQq+cnJbr09MruWzdWu53fyKFXj/6UQ8tW3ZJvKcBF0IvAAAAAICHefO2aPr0dyVJ5eV1+tOfTgg6PpFCL2elV3U1oVcyqa31X7mXSKEXEkviLHwFAAAAACSE++5b5H798MPLWh2fWKGX8+mNLG9MJnV1gUIvog34x50BAAAAAPBQX9/UpvGJFXo5e3pR6ZVMAodeVHrBP0IvAAAAAICHhobQQ6+9e2s8lp05K63igZ5eyauuzv99mZlJtAH/uDMAAAAAAB4aG0MPvR54YInHtjEm0tNpE3p6Ja9AlV7OSkPAidALAAAAAOChLcsbZ81aE8WZtB09vZJXoNBr797aGM8EHQWhFwAAAADAw/r1ZQGPzZ69VgMHPq5rrvlATU2W9u+vcx+79trRsZheUPT0Sl7+Qq+srHRNnXpQHGaDjiC+i60BAAAAAAll5syVQZcF3nPP59qypVx///tyGSOVltZIkgoLO+kvf5kcq2kGRE+v5OXsHXfXXWNVUJCto4/upR49OsdxVkhkhF4AAAAAAC1a9IN+//uFmjdvS9Bxq1aVuF//7W/L3a+POqpX3Pt5SfT0SmbORvZ9+uTpiisOj+Ns0BEQegEAAAAANHbsCwGPbdhQpqFDCyVJxkiW5TvmqKN6RWtqbUJPr+TlXN6YlZUeZCRgo6cXAAAAAKS4V15ZH/T4sGEztHFjmRobm/wGXlIihV709EpWhF5oK0IvAAAAAEhx5577ZtDjjY2WnntutSoq6gOOGT++b6SnFZacnJZKL5Y3JhfP0Is4A63jLgEAAACAFNbQ0NT6INmVNRUVdX6PnXTSQBUV5URyWmHzXN5I6JVMnD29qPRCKAi9AAAAACCFrVq1J6Rx6ekmYKXXiScOiOSU2oWeXsmL5Y1oK0IvAAAAAEhRdXWNevjhpSGNraqqV3m5/0qvXr1yIzmtdsnMTFNamv0UyYaGppAr2ZD4CL3QVoReAAAAAJCirr76ff3zn6tDGltV1RBweWMihV7GGJrZJynP5Y3EGWgddwkAAAAApKBduyo1Y8bKgMf/7/9O8Ni2K738L29MpNBLoq9XsnJWemVnU+mF1hF6AQAAAEAKWrx4R9DjN944Rk8/PcW9XVXVoH37av2OTezQq1E33/yRjjzyOS1cWBzHWSEclZV1OvXUOTr66H9pyZKWe7Zz58w4zgodRUbrQwAAAAAAySZQfy5J6tHDfhJjXl5LsFBZWa+9e2uCjk8UOTktv+rOnbtJDz+8TJI0fvyLsqzfxGtaCMP99y/Wu+9+77GvS5dsHXJIUXwmhA6F0AsAAAAAUlBlpe9SxcGDu2jv3lq99dbZkjyraaqq6rV3r/9Kr/T0xFpE5OzpNX/+1jjOBO318svrffadcEJ/ZWQk1j2HxEToBQAAAAApyDv0uuCCQ/X886ervr5R2dn2r4qeoZf/5Y1XXXV4dCcaBufyxv37/Qd16BiamiyffSefPDAOM0FHROgFAAAAACnIO/R6+OFJSksz7sBLknJzvZc3tgRIf/rTJI0d20dHH90r+pNtI2fo9d13++I4E7SXv9DrpJMIvRAaQi8AAAAASEHO0Ot///c49e6d5zMmP78l9FqyZIe2bi13b/ftm6exY/tEd5Jhcvb0Wr26JI4zQXt5h179++dr6NDCOM0GHQ2LYAEAAAAgBTlDL2dFl1NhYSeP7R07Kt2vu3TJjs7EIsDZ0wsdW2Njk8f2SScNlDEmTrNBR0PoBQAAAAApqKqqwf26c2f/i4C8Qy+nrl0TOfRiUVOyqKjwXIb7i1+MiNNM0BERegEAAABACgql0itYeETohWhraGhSaWmNe/uNN87U+PH94jgjdDSEXgAAAACQgkIJvYJJ5OWNzp5e6Lj27Kl2v+7ePUc//elBcZwNOiJCLwAAAACIgO3bK/TNN7vjPY2Q7d/f8iTGcEKvxK70oqdXMti1q8r9umfPznGcCToqQi8AAAAAaKfNm/dp0KAnNXLks3r++dXxnk5INm/e737dr19+wHGB+n0l8hLCRJ4bQrd7N6EX2ofQCwAAAADa6fe//1R1dY2SpIsvfifOs2ldQ0OTR+g1eHCXgGPnzj1Hw4d386kGS+Qn6FHp1aKiok633DJft922QLW1Da2/IYE4K7169MiJ40zQURF/AwAAAEA7OQOkRFdf36iZM1epsdGSJPXunavOnQMvb5wwob9WrvyFPvpoiyZPfilW02yXnJy2L9dMVo89tlwPPbRUklRYmK3f/vaYOM8odCxvRHtR6QUAAAAA7WRZVrynIEmqrW3Q3/72lZ57blXAOU2b9h9dccV77u0hQ7qGdO5Jk/pr/Ph+MkZ66KGJEZlvtFDp1eLWWxe4X9922ydxnEnoqqvrdeWV7+nGGz9y7yP0Qjio9AIAAACAdkqQzEtPP/2Nrr12niSpoCBbU6f6Pu3uhRfWeGwPGRJ4aaOTMUYff/xfKi2tUbduib3ULFBPr3Aa9nd0eXmZqqiob31gAnn00a/0xBMrPPYReiEcVHoBAAAAQDs1NDQF3Y4VZyXPmWe+7nPcX/VXqKGXZAdfiR54SVJOjv/Qq3lJZyrp0iVxn7IZyN/+9pXPvh49CL3QdoReAAAAANBOJSXVHttlZTVxmYf3sr6qKs8Kn8pK34qfAw8MbXljRxKo0quxMT5hZDx1xNDL3+dHpRfCQegFAAAAAO20c2eVx3ZlZb2ammJXVfTYY8s1depr2r3bM3z7+9+Xe2zv3Vvr895Qe3p1JIF6eqVipVdHXNJJ6IVIIfQCAAAAgHaorq5XeXmdx74HH1yiwsJHdd1186J+/Y8/3qpf/eoDvfnmtz7H7r9/sWpqGtzbe/f6VqC1ZXljRxGo0qupyUqYhw7ESizD10jxF1r26JH4y2qReAi9AAAAAKAdvKu8JLvCav/+Ov31r19py5b9Ubv24sXbNWnS7IDHS0qqtXp1iXvbX6VXr165UZlbPAXq6SV1zBCoPeK11LY9srM9P7+MjDR17dopTrNBR8bTGwEAAACgHb7/fl/Q4/v2+QZN7dXY2KS5czdpxoyVrY7dvbsllCsr85zL7Nk/kTEm4vOLt0CVXpL9kIH09OSt/6iqqtcvf/mu9u2r1f/8zzh9953n/dnUZCktLbE/c+9Krx49chJ+zkhMhF4AAAAA0A4vvLA26PFoPMnx8ce/1jXXhLZ0cteultBrwYKt7tfTp/9I559/aMTnlggC9fSSkr+v18svr9OLL9r35Ny5m3yO19U1Bg0FE1F+fla8p4AOKnnjbQAAAACIsoqKOs2atSbomNde26BHH/3Sp+/X/v21+tvfvtKSJdvbfN1QAy9J7ub2TU2WXnxxnXv/WWcNbfN1O4pgoU6yh16ffvpD0OOLF2/XXXd9qvXrS2M0o7arqmrw2E7GakTERseKdwEAAAAggcyZs14VFfVBx9xzzyJJ0rZtFbr//gnu/ddcM0//+tdqdeqUoRUrLtXQoYVRmWPz8saFC4tVXFwuSerWLUcnnzwwKtdLBMF6ejU2Rr7yLpFUVzcEPT5xot0Dbs6c9Vq16hexmFKbVVUF/zsFhIpKLwAAAAAI0xdfhF6l9cc/LvbY/te/VkuSamoadP310XvKY0mJ3cjcuQzzvPMOVmZm4CWAHV0qL2/cujW0Byc4H3CQaLwrvYBwEXoBAAAAQJg2bWppEj5mzAFhn6e4uKLdc+nePcfv/vr6RjU1WZozZ71730UXDWv39RJZa43sk9nWreUhj62vb4ziTMJXWUmlFyKD0AsAAAAAwuQMvX7726MDBk+ticRyrhkzTlVmZpqMkX7+88Pc++vrm1RaWq2SEru3V35+lo47rm+7r5fIUrWnV1OT1aYANVHDpf37I//EU6QmQi8AAAAACJOzquaUUwZp3brLdP31RwQcf955b/ptXN+W8MGyfEObnJwMTZrUX8XFV2rTpst12mlD3Mfq65tUW9tS0ZOXl6m0tORuDJ6ZGfhX3WTu6bVnT5Xq6kKv3poxY2XCVXs1NVk+D30AwkXoBQAAAABhaGxs8mgaXlCQpaKiHD3yyGRdcMGhft8zZ856XXvtPDU1eQZXO3dWadOmvSFd11+j8rvvHqf8/Cz17JmrgQO7KCOjJdSqr29STU1LsBGsCipZBHvaXzJXerVlaaMk3XzzfN1//+LWB8ZQZWW9/OS6QFgIvQAAAAAgDM7wqXPnDI+gZdq04QHft3jxDlVX+1Z2DRnylL7/fp+fd3j65ps9Htv3135CGwAAIABJREFU3Xe8br31aI99zib19fWNqq1tmWt2dvI2sA8FoZenO+/8NAozCR9LGxFJhF4AAAAAEAZnH66cnEyPY6ecMkj/+c85euGF0/2+d8eOKr/7b7ttQdBrlpfX6dhjn3dvjxrVU7/73bE+45zL+7yXN6Z66JXMjezDCb0Szf79LG1E5BB6AQAAAEAYvCu9nIwxmjJlsM4//xC/712/vtTv/tZ6e91444ce24ECLO/QK9WWNwaTzD29iovbHnr16ZMXhZmEb98+Kr0QOYReAAAAABCGqipn6JXpd0x6uv9fudavL/O737ks0du33+7VjBkrPfZdfvnIAOfxrvRieWMzljd6ys/PisJMwkelFyKJ0AsAAAAAwuBc3uhd6dWaG2/8yO/+rKzAv6KtXVvisf3AAxN0ySWH+R3rDM8aGlJzeeNrr01V//75uuqqwzVyZA/3/mQOvfbsqW7ze9ry5NBYoKcXIonQCwAAAADC4FzemJMTmSWDwQKpXbta+oBdfPFhuuWWo5WV1fryxs8//0ELFhS7t1NleeOZZw7Vli1X6rHHTlZ6estDBpJ5eWNdXaPf/TfdNEbDh3fze6yiIrEqq/xVegV5GCcQFKEXAAAAAIQhlOWNknT22UNDPmew5Y27d7dU8fTokdPKeTx/1fvDH75wv06VSi+njIyWn0dDQ/JWejkr+pz69s3TAw9M9HusoiLRKr18Qy8reT8yRBmhFwAAAACEIdTljTNnnqZnnjlV5513cKvnDLa8cffulkqvHj06Bz2Pd+jllIqhV+pUevn/3nr06BzwHm1oaHJXiFmWpf/+7wWaPHm2li/fFbV5BsPyRkRSatS1AgAAAEAEWK6SE2OMR6VXsOWN+flZmjZthHbsqNTLL68Pev5AyxUlz+WNPXu2FnoFPk+qLG90cj5QIJl7ejkfWOA0cmSPgFVgkv3ExC5dsrV48Xbdf/9iSdLo0f/U1KkHadeuKp144gDdc8/xUZmzv7kAkZJ6/9oBAAAAQBuVldXot79doFdf3aCqqnq98spPPXp6BVve2CyUp+QFq9AqK2sJA4qKOgU9j3M5nzcqvVKj0qtnz87atatK1147WqNG9dSKFbsDvu+MM17TihW7Pe5pSXrjjY2S7L5wxx/fV1OmDI7OxB38LW8cO7Z31K+L5MTyRgAAAABoxcMPL9WTT65QSUm1qqsb9NRT37T56Y25ua0HY8F6FzmXfXXpkh30PCxv9OQZeqVGpdfChRdqy5Yr9Je/TJbkW43o/Jl88cV2n8DL27PProrYPBcv3q5DDnlaP/3pa2po8AwhvUOvQw4p0kMPTYrYtZFaCL0AAAAAoBUbNpR5bJeX13mFXq0HWs7liYF4BwBOzjCgoCB41Viw0CsVlzd6NrJPzkqv1av3aMuWcvd2bm6m+vcvkHE9+tA79DrttLZVba1eXdL+Sbqce+6bWr++TG+99a0ee2y5xzFnuPvGG2dqzZpfqFu34A9uAAIh9AIAAACAVjiXFkpSTU1jyD29mk2ePKDVMfX1oYVe7an0CqUqLdmkQqXXhRe+7bHt/VAE73u0e/e2BUmVlZF7yuPWrS3h3AcfbPY45rzPi4o6uUM7IByEXgAAAADQirKyGo/t2toGr55erQdJRx7ZS3ffPc5n/6WXDne/Dh56tQRvrVd6BV7C2KdPXtD3JqNUaGTv3bMrO9vznmxv6BWsEX57eIdpzkb2BQXBw12gNYReAAAAANAK79CrpqZRM2eudG+HsrxRku66a5yGD+/msS8vr+W99fXBnrAXmeWNvXvntjbNpJMqjeydvCu9vJe1FhYGfxiCt9raRpWX12njxrLWB7dBRYVn6NWWZbxAawi9AAAAAKAV3ssbV6zYrd27q93boYZeklRU5Flh42xwX1/fpE8+KdY993yubdvsJWCWZamiok51dXYglpGR1mpfrmChF5VeyVnp5c272i8tzXOZYCgPVnDatatKBQV/0dChT+u55yLX1L683LNxPaEXIonQCwAAAACCsCxLe/fWBB0TSk+vZoWFnku28vJafrHfvbtaJ5wwW3fe+ammT39XdXWNOvbY55Wf/xf3mIKCrFb7HDkbt3tLxUqvjIyWn1eyNrL35h1yeevaNfylgz//+dyw3+tt9eoSrVljN8m3LMtjGW9+PqEX2ofQCwAA4P+zd+fhUZVn/8C/TzLZJgtJIAlhCRAQXNgEUcSq4I77jtpqbd3F3S5vrf7U9q31bV2qdaVaRWtVrAuKVkUQEVGRTQHZ9wAJ2fdkMsnz+2MyZ846SzLLycz3c11cnvOcM2eemJlJzp37vh8iIj8aG10Bs4NCaQ6vLytTlzd++uku5bk+/ngXPvtsN1asKLc834q/oFigJvjxKBEzvcz84hdjAQBTpxZj3LiCmM1D/xq+9tpPAHj6e8nub4/T6fDbm44oGAx6ERERERER+aHv52UmlPJGfdDLXzbLrl31PX6ukpJsw5jDkYTU1MQLJCRiTy8zL7xwOlatuhJffHFZSNmJ4dbWpu1dt3z5ftTXt7OJPYUdg15ERERERER+6Pt5mVEHVQLxV96op25e7xVs0Os//zkXN944QTMmpQxYGhmPtEGvxM30SkoSmDSpCKmpyTELerlcnaYlpk1NLvzjHz8o++znReHAoBcREREREZEfwWR6tba6g76ev/JGPW8ze7VgSymnTCnGs8+equntlKgBH5Y3GlkFvW655ciIPm9Njfn7qaXFjd27G5T9RAzOUvhFPeglhBglhHheCPGDEKJTCLHE5BwhhLhHCLFXCNEqhFgqhJhoct7hQohFQogWIcR+IcQfhBDJsb4WERERERHFj2CCXocckhf09fQNxP2tord9e51hLNRG7KGu0heP1I39E6WRfSBmQa/i4kycfXZpRJ/3xRfXmY43N3fA5fJ9b+6++6iIzoMSQywyvY4AcCaAzQC2WJzzPwDuA/B/AM4B0ATgMyHEQO8JQog8AJ8BkADOA/AHAHcDeDCW1yIiIiIiovhiVd44c+YIHH30QPzhD8dhzJj8oK+nL2f012Nr374mw5g6MBAMBr0So6dXWprvdTR7duDcDLMy2YYGF049dTj++MfjAj7+nHPewe9//yWkDC1zrqKi2XS8paUDHR2+Xl8sb6RwiEXQ6wMp5VAp5SUANugPCiHS4Qku/VlK+ZSU8jMAl8ATkLpFdeqNADIAXCilXCilfA6eINVdQoicGF6LiIiIiIjiiFWm18UXj8a33/4M9913bEjX05cnqrOQ9Kqrjc+tDgwEg0Gv+O/pJaVEe7vvdfHkkycHfIzDkYRHHjlRM9bc3IGkJIF77z0WJ51U4vfxCxbswEMPfYsvvtgb0lz1TezVz93R4QtIpqSwGxP1XtRfRVLKQGH1aQByAMxTPaYZwAcAZqrOmwngEyllg2rsDXiCV953biyuRUREREREIWhoaMecOd9j5cryWE/FlFXQS9+bK1j6DBt/DcXN+h+pgxvBYNArvnt6bdxYjbPPfkfZT0tL1vRx8+fuu6dgwIAM02PBvm5mzJgXUvZce7t5/7uWFrcu6JV4q4xS+NkxdHoogE4AW3XjG7uPqc/bpD5BSrkHQIvqvFhci4iIiIiIQnDXXUtwww0LccIJb6C83Lz0KZasgl5Tpxb36Hrjxg1QtocMyfbbyL6tzRggcLlCC3r5u36iiOfyxptv/gwffbRT2Q92dU8vq6BXsAsmAMDKlRVBn8tML4qm2KxR6l8egCYppf6dUAvAKYRIlVK6us8zdnX0nOftIhmLaymEENcDuB4AioqKsGTJEtMvuK9pamqKm6+F+g6+7igW+LqjWOFrj2IhVq87KaXS2Lq11Y2//vUjnHNOQdTn4c/mzb7yrYsvLkJtbQemTcvF5s0rsXlzz6750EOjsGxZHS64oBDff/9dSI9tamoN6Xt1xRU5WL58PwDgmmsG2+rzJVqvu/37y5TtLVu2YckS+wVXe6Ky0oUlS7TlhcnJnSH9P3U4NLexymMbGqo147/61TA88shu02usXbsara2ZQT1fWZkvQJaTk4yGBs8t9po161FZWaMc27BhHdLTzZ8vHPizNjHYMegVN6SUcwDMAYCjjjpKTp8+PbYTCpMlS5YgXr4W6jv4uqNY4OuOYoWvPYqFWL3uysoaAaxS9ouKhmH69KOjPg9/Hn64CoDnZvzqq6fhrLNG9vqa6v/Vra0dAL4P+rFCOEL6Xk2fDhQWHoKyskZcf/14ZGbap0F4tF53n3yyFIAn2DJs2AhMnz414s8ZDVdcscAwlpubGdL/09LSWqxf71swwfvYd95ZBKBKGb/vvnPxyCN/N73GuHETMW3a4KCeLyurCt6ck8LCbDQ0eLaHDh2JzEw3gEYAwJQpR+KEE4YG/XWEij9rE4Mdg161ALKEEMm6rKo8AC2qbKpaAP1MHp/XfSxW1yIiIiIioiDp+3ht325WgBFbdXW+1Rt72sfLn/T00G7LbrxxQsjPccklY0J+TDyJ155er7++yTAWanljUZF5hpa+p5e/VUatShbNz/WV7Pbvn4Ft2zzveWN5I3t6Ue/ZsUh2E4BkAKN04/q+W5ug66UlhBgKwKk6LxbXIiIiIiKiIK1ape0FVFXVGqOZWFP39IpE0EuI4JqOT51ajJ/97HD85jf2yoTrC+K5p5eev4URzNx771Slf9Y99xyjjOuDZ/56bJn1ntNbu/YgHn98Jfbs8a0fl5Pjyzp0uTrZ04vCzo6ZXssBNAC4BMD/AoAQwgngHHSXCnb7L4BfCyGypZSN3WOzALQC+CKG1yIiIiIioiDpM71aWjpiNBNr9fW+TK/c3LSYzeO99863zMoh/7RBr/jJ9DITSgN6ACgpycGyZZdj06YaXHLJaGV8+PAczXnJyUlITham//8CBb2amlyYPv1NzXsJALKyfEGvzs4udHT4MsYY9KJwiHrQqztQdGb37mAAOUKIi7v3P5JStgghHgZwnxCiFp4sqrvgyUpTFxA/B+A2AO8IIf4PQCmABwA8JqVsAAApZVsMrkVEREREREGQUhoyvZqbA2eMRFtrq29OoZaOhZO/8jLyz+HwBVDc7vjO9FJ/rcE6+uhiHH20djXSyy8/DH/963dYv74KTz99CgDPa1D9fvAKVN74ww+VhoAXoC2hdLulJtOrJ18HkV4sMr0KAbylG/PujwCwC8DD8ASTfgegP4CVAE6VUio/EaWUtUKIkwE8BeADeDrhPQ5PsEotqtciIiIiIqLglJc3o7JSW85ol0yvb77Zj+ee+x6XXXao5oY+PT12gae0NAa9eioeM726usy/Dv17qqccjiSsWXMVqqpalQxD66CX/2C12WMAbdDLk+nF8kYKr6gHvaSUuwD4LVqXUkoAf+r+5++8HwGcZLdrERERERFRYNOnv2kYs0vQ66yz3kFNTRvmzt2gGY9UttUNN0zA889/j7S0ZIwfX4Dvvis3nMNMr57TNrKPj0yv+fO3mY5XVDSH7TmSk5M0JbVWgbZAQa+amjbT8cxMX0jC7WZ5I4WfHXt6ERERERFRAtiypdYw1txsj6CX2U16eroj6KbzoXr44eNxxBH9MXlyERYs2GEIegmhzVai0MRjptcll7xvOl5eHr6gl15jo8t0PFB5o3oxCDVtTy/J1Rsp7Bg6JSIiIiKiHpkz53uMGfMinnhiVciPteqr1NIS+55eVplAkSxtzM1Nx623TsK0aYORmmq8TUtLi1zALRFoM73iI+hl9XWMGZMf5ZlYly96WWd6qXt6sbyRwo+vIiIiIiIiCllrawduuGEhtmypxR13fI6GBmOTan+sMkbsUN5odQOfkRGdQhmzMkazQBgFz+HwBQzjuZG9w5GEOXNOi9j1rUpse1LeWFTkRFaWuqeXPtOLr3nqPZY3EhERERFRyPTld6tXV2D69JKgH28VJGtpcaOrSyIpKXZZTVaBt/T06Nw+mTWsZz+v3onHTC+99euvRl5eOgYNyorYc6SnJ8PlMpYyBgp6mZUy3377ZMOqmtqeXnzNU+8xdEpERERERCH78st9mv0ffqgK6fENDb5Mr8MP768JKAW6gY40q0yvaK3caJ7pxQBAb2h7esVnptfAgZkRDXgBwB//+BNlOzvb14/LX1mylBLLl+8zjM+ePdEQjGSmF4UbM72IiIiIiChky5aVafZbWjrQ0NCOZ59di5KSHFx++WF+H79qVYWynZOTiszMFCXY1dzcAaczxeqhEWd1Ax+tTC+zAJdZ9hcFLx4b2etFIyh7440TsHNnPVpaOjBpUhFuvHEhAGDfvibLx+zYUY/KylbN2Isvno6cnDRD2SmDXhRuDHoREREREVFIOju7sHz5fs2Y292Fv/1tFe6/fzkAYPDgLDQ3d+Dzz/di9uyJGDasn+b8a6/9RNneu7cRTqcD1dWe/Vj39TpwwHz1u+j19DLe7PfrlxaV545X8VbeqC4D9EpLi/zrMzU1GY8/PgMA8N13B5TxHTvqTM9fseIAjjnmNWV/+vShePvtc5GfnwFA+31pb/d9TZ7VShn0ot5j0IuIiIiIiILidnfB4UjCunVVmvJE77EHH/xa2b/mmk+wZ08jXK5OfPddOT7/fJbmfHXgYd++Js2Kc7FcwXH+/G04//z3TI9FK9vKLHiRl8egV2/oe0f1ddXVxsbw6q8xGkpLc5XtHTvqIaU0rDB65ZUfafZPOqlECXgB2jmry5rZz4vChaFTIiIiIiIK6IMPtmPAgKdx8snzsG5dpeG4263Nntm2rU5peL1kyV4888way15KV111ODIzfeWMzc2xy/R6/vnvLY+pSzIjySzTKy8vPSrPHa/UZXR27elVVtaIiy6aj1tu+SxgYK6qqiVKs7KWn5+OnBxPX6/m5g5UVhrnpG9gP23aIM2+uuxU3UuPpY0ULnwlERERERFRQOee+y7q69uxePEePPDAcsPxQDfps2cvwj//uR6Ap7G12oMPHgen05fdFO3yxvLyZrz33lY0N7vw3//utDxvyJDsqMzHrHdYbi4zvXpDXSqnD9DaxezZn+Gdd7bi6afX4p//XOf33KoqbY+sK67w30MvEoQQhmyvQI4+ulizr870Umd4socdhQuDXkREREREFBKzm1u3uyvgjer1138KAGhs9JVGZmamYPjwfprG9WbljWVljbjyyo/wwANfoasrfEELl6sTRx31Ki64YD6Ki58zHE9PdyAryzO3226bFLbn9aekJMcwxkyv3ukL5Y3vv79d2Z47d4Pfc9WN4YcNy8Grr54ZsXn5U1rq69W3cWN1wPPVKz4C2kwvdbCbQS8KF/b0IiIiIiKiXnO7uzB8eD9s3lwT8NzaWl8/Im8wx195o9vdhZNOmoetWz2lUiedVIITThgajmlj5cpyZeU5dTDO68EHp2HWrDE4eLAFU6YUG45HwsiR/QxjDHr1Tl8ob1QLFNhVZ3qdfvpwJCUJP2dHjjro9ctffoKLLx6jCWxlZDiUssWrrz7C8HirTC+zFUyJeoKZXkRERERE1Gtudxeys1MCntfVJVFX167se8v2/JU3PvLId0rACwiujCpY/lbye+mlM3DnnZMxbFi/qAW8ACAzMxXFxZmaMTay7x1tppc9yxvVQgl6DRiQ4efMyFKXNwLA3LnrNfsDB/pex7/73TGGxzPTiyKNQS8iIiIiIuo1t1uivb0z4Hnt7W7TTC9/5Y2PPbZSs9/UZMzI6qn6+nbTcYcjCVdfPTZmq8iNGpWn2c/NZaZXb2h7evX9TC910/jYBr20WYm33rpYs9CFdzELQPse92JPL4o0Br2IiIiIiKjX3O6uoIJera1u00wvq/LG1tYOTf8iAGhsDF+je3UATi1W5WJeo0ZpM2iY6dU7fa28UQZIRlNnehUUOCM8G2vDhxtLcf/4x6+VbXXQy2xVUqtML5Y3Urgw6EVERERERH6pb1ytBBv0amvr1GV6+S9vrK42BqUaGsyzs3qittb8WrEOeo0cqQ96MdOrN1jeGBljxuQbxn780dfQ3uXyBRjNAlnq74u39xfATC8KHwa9iIiIiIjIL31jeTNud1dQwbHWVrcm0OQt27Mqb6yu1mZ5AUBDg7G88d13t+LPf/4WdXXmmVtWrM5PivGdkjHTi0Gv3rB7eWNHh/a9453j6tUVuPzyBfjXv37UHK+o8JU3FhTELugFAL/97dGafXXwW71tFvRSf1/UGPSicOHqjURERERE5FewQS+rTK+Skmzs2dMIAGhrc2sCTd5Mr5QU382vOnhWU2OW6aUNem3cWI0LL5wPACgra8Sjj05HenpwtzoHDjSbjgthr/JGbxko9Yzdyxv1r2lvhtQvfvExfvihEm+8sQkzZgzF4MHZADyvc68hQ7KjN1ET6ixNwJPN6aUtbzTL9DJ/n7G8kcKFmV5ERERERORXb4JeRx89EAMG+HoO6TO9vBlM6qBXR4cvKGGW6dXYqA0QvP76RmX7mWfWIivrCTzxxKqAcwaAjz7aYToe45gXyxvDzO7ljfoFFdrb3ZBS4ocffE3hv/pqHwBP+a83GJySkhTTnl4ADAFmb3lyZ2eXUqYphLZ/lxczvSjSGPQiIiIiIiJLzc0u7N3baHosI8N3s9vQ4NIEx047bTiuuOIwfPjhhUhP993AtrVpV2/0ZjBpg17+M730JYlFRZma/c5OiTvu+Nzv1wV4slC8GWj6IFese3rl5qbjtNOGAwDOOGM4M196ye7ljcagV6dhzNvfbv78bcrYoEFZMX+tSl3X/bq6dnR1SU2WV1qawzR7Uh2MVOPrncKF5Y1ERERERGSqqqoF48fPtSwB7NcvTWk+vXDhbs2xjz++SLnJVQfH9Ks3+jK9fDe53kyvH3+swg03LDQ877ZtdZp9q5v+FSsO4Oiji82/OGgb5mdlpWoyyGIdSACADz64AKtXV2Dy5KJYT6XPU5fR2THopS9vbGvrNASbX3ttI445phj//e9OZay4WBvwjYWuLv2+RH19O2644VNlzGzlRsA8+wtgpheFDzO9iIiIiIjI1Kef7rYMeAGeoJcVdVaHuvxJv3qjWaaXNyhxwQXzTa+9b1+TJtvrvvu+Mj3vmGNe89vYXr1anL4vkR2CXqmpyZg6dZAmIEg9o84o6uzsG+WN6r5dgKe8cfLkV/Hqq76m9meeWRqV+fljttLk9u11eOutLcq+VUaX1TiDXhQuDHoREREREZGpqipjPy21fv1Sg7qONtOrwyLTS9vTq63NjS1bai2vuWNHPQBg06Zq075fXh9+aN6zC9CuEul0pmDu3JnK/quvnmn5OOp7tD297JfpZVbeaFVWrHb88YMjNaWgmQW9Nm6s1uyrA91qVpleLG+kcGF5IxERERERmbK6UfXyl+ml5i/Ty6q8cdmyfX6v6S1FXLeuyu95L720HpMmFeGww/objqnLGzMyHLj88kPR1SWRnu7AzJkj/F6X+hZ1cKUvBL06OyV27WoI+LisrOACz5Gk7+kFAJs21ejOMX8sM70o0pjpRUREREREpsyayKvl5JjfcN900wTNvr6nl3r1RvNG9l1YuHCX3+duavIEvQJlhCxatAfjx8/Fnj3GAIK+vDElJRlXXz0Wl112qGnTbeq77F7eqO/pBXhKBAPJzo590Ov66ycY3ocPPfRtUI9lTy+KNAa9iIiIiIjIVKBMrwkTCk3Hp08fqtlX98uqqWlDW5sn2ORwJCEzMwWANujV1OTCyy9v8PvcjY2eLC19bGr8+ALDuW53F+6/39j3S53p5XSm+H0+6tv6WnkjAOzeHTjTyw5Br4EDM/H555ca3otqRx5p/llhVhoJ2OProvjAoBcREREREZnyF/TKyHDgpJNKLI5pA0jqMkj1jXxubpqSUaUOei1cuBsHD7YYrqtuLu/N9FL35QKAyy47FCNG9DM81qw/mfqx6mw0ij/2L280Znqpe99ZsUtwaNq0wbjvvmMtj1933XjTcauyx5Ejc8MxLSIGvYiIiIiIyJxVeeMVVxyGBQsuVLK09NLTtaVJ6qCXuszQW9oIIKgVCgcMyFC2m5o8WVrNzR2ac6SU2L79WkO/MZfLGOjQljcy0yue2b280SzTy2xMz+o9GAv9+2eYjv/xj8fhppsmmh4bNizHdHzUKAa9KDwY9CIiIiIiIlNmmV6zZo3Ba6+dhZNOKoHDYV7PpG5cD1gHvXJy1EGvwLcmBQXqoJdL81+v9vZOCCEweXKRblybEQboyxuZ6RXP7F7e2NBgDHCZjempsx9jrX//dNPxkhLzwBYACCHwt7/NMIyPGpUXtnlRYmPQi4iIiIiITKkbzgOe5tJ/+cuJyr7VymvGTC9fCdbevY3KtroRfjBBL3Wml3f1Rn2m1/nnjwIAHHGEdrXGQJleLG+Mb32xvFFfuqs3btyASE2nR6wyvQoLnX4fp89W698/Q1nVlai3+MlOREREREQGUkpNeePatVdh0KAsFBT4bmCtgl76AJI600u9Sp16PNSgl1l548CBmTjySE+G19Ch2ZrHtrd3Gq6nngvLG+Ob3TO9gill1HvjjbMjMJOes8r0UmdomtGv/MjSRgonBr2IiIiIiMigtdUNl8sTKEpLS8b48QVK03kv60wv66CXmjrTy+paaurAVGOjCw899A0eeuhbZexXvzpK2S4qytQ81qz3186d9cp+SYk2SEbxJTlZ29NLSml4PcdSMKWMahMmFODww+Mj04tBL4okBr2IiIiIiMjg9tsXK9t5eemmAYKsLKtG9trbDKub4VAzvdQWLdqDV1/9UTOm7hGWn6/NOqms9K0G+atfLcHTT69FW5uvfIw9hOJbUpKAEL7VAru6pKbkMdaCWalRzeo9FUv695yXOjvUjP69z6AXhRN7ehERERERkcbevQ144YV1yn5ennmm1oAB5jez+p5epaX9cOqpwwznaXt6BV69Ud2na//+Js2xwkInzj13pLJ0fb3DAAAgAElEQVSvD8jV1LShtbUDbW1uPProSk3AC+CNdiKwa4ljR0enptQ2GOqVT+0iKyvVdFwfBNczZnoxAE3hw6AXERERERFpfPdduWbfX0Dq17+eotkfOTIX+fnaLBQhBD788ELcdddkzbg6A8Qq02vcuAGYPLkIDzwwDRMmFJqec8wxxdi9+3pNSeOkSUWG8/bvb9Y0r1crLe1nOk7xQx306uyUMZyJVjBZXieeOESzb8egVzAlymZSU5npRZHD8kYiIiIiItLQB730mVtqDzwwDcOH5yAzMwUuVxdOP304kpKMZWMpKcl49NEZOO64wbj77iXIyHBg1qwxquPmN8xnnVWKP//5BADAkiV7TM854YQhhmySnJw0LFx4CU499S1l7ODBFtOSzMGDs5CRwUb28c6umV7qBSOsvPLKmRg2bI6yb8egV0/pg2UMelE4MehFREREREQaK1Zog17HHTfY8lynMwU333xk0Ne+8MLRuOCCQwBA0yfMKptMXfpkVSaVmWkesDrllGE47bTh+PTTXQCA2to2dHQYG9bzJjsxqHt49aWgV3q6AyUlOZqxvDzz/ll9UW2t9uu3Y78y6rsY9CIiIiIiIsWCBduxeLE2o+qee44J63OYNcW3yvQKJuhl1VAf0DbXrqlpU1akVGMPocRg1/LGmppWv8fT0owB4b6S6fXXv54Y8Bx9QM9Oq2pS38eeXkREREREBACQUuKcc97VjLW332nZsD6crINevnGrMkuzoICXugl/ba150GvIkKxgp0l9WF8tb/S+vtUB3BNOGBrROYXLbbdNCnjOlCkDcf314zF6dB4+/fTiKMyKEgkzvYiIiIiICACwbVudZv+oo4oMK6tFSlZWKgoLnTh4sEUzrn5+q+BWl5/4hbqpvifTy3iyvvE+xae+UN44fHgOdu1q0Bz3vu4/+OAC3HvvMpxxxgiMH18Q1Tn2xBlnDA/q80MIgeefPy0KM6JExEwvIiIiIiICAOzerb3Z/uMffxK1505K8qzweMQR/TXjwZQ3dnVZl6rpM706OrSZXpmZKbjssjH6h1Ec6guZXqWlxv5y3qDXtGmDsXjxLPzmN0dHbW6huvRS33vpuuvGx3AmRB7M9CIiIiIiIgBAa6tb2Z42bRDOOGNEVJ//qKMGYunSy9C//9PKWDBBr85O6wCGsaeX9tx1636OwsLMnk6Z+hD79vTyBb1GjOhnOJ6VlRrN6fTK3/42A1lZKRg2LEdZsIIolhj0IiIiIiIiAEBLS4eyPXhwbPpcqQMTQHA9vcaNsy71Upcu6nt6nXDCEIwYwZUbE0VfKG8sLTUGvbKz+07Qq7g4Cy++eEasp0GkYHkjEREREREB0GZ6ZWTE5u/j+ob22p5e5nM69dRhltdTlzfqV2+0ap5P8cm+5Y2+1RvNMr2ys61XJyUi//gpT0REREREALRBL6czNjfa+kwvdWAqKUnoT8eqVVdCCOO4l7q8UZ/pFa0m/WQPdi1vrK1tV7ZLSnIMr/O+lOlFZDcMehEREREREQBteWOsMr2MQS9tYKp/f1+54g03TMCkSUV+r5eXp+3p1dHhy/Bh0Cux2DXTq63NF2zOzExBTo42yNWXenoR2Q2DXkREREREBMAe5Y36rC11HyYAuP32SQCAK644DE89dXLA62kzvdrR3q7O9OLtUCLR9vSyT6aX/jU5dGi25jgzvYh6jp/yREREREQEwB7ljXr6Uq/77jsWXV1347XXzjJkhZnJyEhBWpono8vl6kR9va+UjJleiUVb3mifTC910CstzYGf/vQwzXH29CLqOQa9iIiIiIgIgD0yvfTM2nX56+FlRp3tVVHRomyzkX1isWt5o7rPXFpaMn75y3Ga4+qeX0QUGn7KExERERERAKClxX5BL7Pm9aFS9/WqqGhWtpnplVjU5Y0zZ76t6aUVS/ryxoICJ6ZPH6qMHXfc4FhMiyguMOhFREREREQAgNZWXyN7pzN+gl7qTK+nn16rbDPolVjUmV4tLW488sh3MZyNj768EQDmzTsHF110CK69dhzOO29krKZG1Ocx6EVEREREROjo6MLBg77SP7tkeoVaymhGncGmxkb2icXh0L6WFi3aE6OZaGmDXp5AbEGBE//5z3n4xz9OR0YGe3oR9ZQ9fpIREREREVHM7NvXiFmzfkBtrS84NHBgZgxn5BOOwJQ6mKe9NjO9Eklysv2CnFJKTU8vviaJwst+73oiIiIiIoqquXM3aAJeADB27IAYzQa4+uojAAAjR+bi2GMH9fp6VVWtpuMDBmT0+trUdwSz2me0dXT4Guo7HElhKeclIh/7veuJiIiIiCiqvvuuXLM/bFgO8vNjFxCaM+c0fPLJxfjuu5+FJTvnySdPMh0vLHT2+trUd+jLG8NQOdtrZqWNRBQ+DHoRERERESW49eurNPuPPz4jRjPxSElJxmmnDdesutgbP/vZYabjRUX2KOGk6LBjppe6tJFBL6Lws9+7noiIiIiIourAgWZlu67uVlxwwSExnE34ZWSk4KabJhjGi4qY6ZVI9FmD4VgkobfUmV7s50UUfgx6ERERERElsKYmF5qbOwAA6ekO5OSkxnhGkWG2GiXLGxOLvrzRDtrbfb30mOlFFH4MehERERERJbDycl+W18CBTltkv0RCRkaKZl8IoKCAQa9EYsfyRvb0Ioos+73riYiIiIgoarRBr/jtcaXP9OrfP8OWQRCKHGN5Y4wmouJy+VZvZNCLKPz4KU9ERERElMASJejldGqDXixtTDx2L29kTy+i8GPQi4iIiIgogSVK0Euf6cUm9onHjpl9LG8kiiz7veuJiIiIiChqystblO1ECnox0yvx6Msb7YDljUSRZb93PRERERERRU3iZnrF79dK5ljeSJR4GPQiIiIiIkpgiRP00q7eyPLGxKMvb7TDSqUsbySKLAa9iIiIiIgSWKIEvdjIntjTiyjx2O9dT0REREREUaMNesVvIIjljZScrM3sskGiF1wuddDL4edMIuoJBr2IiIiIiOJEXV0bLr98AY444iUsX74v4PldXRIVFb5G9vEcCBo1KlcT5BgzJi92k6GYsHumV2qq/eZH1NcxlExEREREZGNVVS1oaurA8OH9/J53yy2f4emn1yr7jzyyEu+8M9jvY2pqWuF2e1aPy8pKRnp6/N4eFBZmYtGiS/H8899j2rTBGD06P9ZToiize9CL5Y1E4Re/P9WIiIiIiPq4rVtrMW7cy3C5OvHhhxdi5sxS0/Oam12agBcAvPvu1oDXV5c25uen+DkzPsyYUYIZM0piPQ2KEWN5Y+zrG1neSBRZ9gt1ExERERERAOCaaz5Be3snpARuvXWx5Xm7dzcYxg47LHAmU3m5r7QxEYJelNjsnunF8kai8OO7ioiIiIjIpr78skzZ3r69zvK8nTvrDWPqm2kriZbpRYlNH/SyQaIXyxuJIoxBLyIiIiKiPmDQoCzLY2aZXg0NroDXPHCgSdnOz2dpFcU3fXmjlDGaiIo26MX3IFG4MehFRERERGRDFRXNmv2BA61XVqyrazeMVVW1YvXqCr/PwUwvSiR2LG9U9/RieSNR+PFdRURERERkQ2vWHNTsNzVZZ241N3eYjl944Xy/z8GeXpRI7F/eyEwvonBj0IuIiIiIyIb0WVpm2VxeVkGv3bsb0NVlXcPFTC9KJHbM9GJPL6LIst+7noiIiIiI/Aa9Wlo6IFUNiayCXp7HtVkeY9CLEom+p5cdMr3U5Y0MehGFH4NeREREREQ2tHq1trzR5epEW5sbixbtRlHRMxg9+kXU1LQC8B/0qqpqtTzGoBclEjtmeqnfuwx6EYWf/d71REREREQJrra2DTt31hvG6+ra8fvfL0NTUwe2bavDXXctAaC9cT733JGax1RWmge92tvdqKnxZIElJwvk5LCfEMU3Owa9duzwvc9LSnJiOBOi+GS/dz0RERERUYIrK2s0Ha+ra8O33x5Q9ufO3QBAG/SaPftIzJw5Qtm3yvQ6eNDXxL6w0Gko/SKKN8byxti+5qWU2LatVtkfNSo3hrMhik8MehERERER2Ux9vXnT+vp6F0aO1N4YNze7NEGvzMwUFBU5lX2roJe6tHHgwMzeTJeoT7BbpldVVSsaGjyrsmZlpaCw0BngEUQUKnu964mIiIiIyDLoVVfXhry8NM3YF1+UoaXFrew7nQ4MGJCh7FdVtWia3nuVl/syvRj0okSgD3rFMtHr66/3Y8SIfyj7hxySF/PMM6J4xKAXEREREZHNeLM/9Orq2g1N6z/5ZJch00sd9Lrvvq+Qn/8Ufve7pZrHMdOLEo2+vNEkFhw1p576luZ9y9JGoshg0IuIiIgoQbS0dOD++7/Cc8+tNc38IfuwLm9sR1OTNui1cmU5Wlt9mV4ZGQ4MGOArk+ro6EJdXTsefngFKip8ga66ujZlW589RhSP7FTeqA9ejxqVF6OZEMU3LtFCRERElCBuv30xXnhhHQBgzJh8zJhREuMZkZVQgl7Ll+9Hv36+oFVaWrIm00tt+/Y6FBV5srpcri7VYxwAOns5ayJ7s1N5o94hhzDTiygS7BPqJiIiIqKI2b27Xgl4AcCyZftiOBsKpL7evLyxvb3TkCHiOd8XJEtNtQ56bd3qWynO5fIFudLSkns6VaI+w84rlDLTiygyGPQiIiIiSgCPPLJSs68OeJD9qEsP1QGspqaOgN87f5lemzbVKNvq66SmMuhF8c+Y6WWfIJh+VVYiCg8GvYiIiIgSwLx5mzX7VVWtMZoJBWP/fl/vrWHDcpTtmpo2s9M1/GV6bdxoFfTibQHFPzv19NIrLuZiEkSRYN93PRERERGFRXu7GwcPtmjGGPSyt7KyRmVbnQFSXe3/+5aUJJCcnITc3DQkJRmzWH78sVrZVvf0YqYXJQI7B73slHVGFE/s+64nIiIiorDQB7wAoLLSN7ZrVz0mTpyL4477N2pqGAyzg337mpRtddBLnek1enSeIbDlDV4lJychPz/dcN3t2+vQ1uZZ6ZHljZRo9D29GGciin8MehERERHFufLyZsNYba2v8fnlly/A999XYvny/Xj11R+jOTUy0dnZhYoK3/ds+HBfeaM60yszM8XQB0jdkL6gwFji2NUlsXmzp8SR5Y2UaPRBLyljM4+uLu0T/+Y3U2IzEaIEwJ9uRERERHGuosKY6dXS4lkB0OXqxDffHFDG//OfLVGZU1OTCwcONAU+MQF1dHQpN+NpacnIzExRjqkzvbKyUpGVlaJ5rDp4NWCA0/T61177CQCWN1Li0WdGyhhFvTo6tItR/P73U2MyD6JEwKAXERERUZwzy/RqafGUuC1evEczXlRkHigJRVubG888swbvvbfV9PiBA00YPPg5DB36PD7+eGevny/edHT4glEpKUma7K3qal/QKzPTgaysVM1j1cErq2b2K1dWYOvWWpY3UsLR983SZ1xFizrgnJWVgpyctJjMgygRMOhFREREFOfMg16eTC99ZldZWe+zr37+8/9i9uxFuOCC+XjnHWPm2O23L0ZDgwudnRIzZ77d6+eLN+osEIcjCWlpDmXf248L8GR6ZWY6NI9VB8isgl4A8MMPlQx6UcLR9/Dq7IxV0IvvPaJoYdCLiIiIKM75y/T68ssyzfiOHXW9eq7GRhfmzdus7N9zzzK43V2ac7Zu7d1zxDt/mV5qWVkpPcr0AjwZLu3t7OlFiUVf3hi7TC8GvYiihT/diIiIiOKcWdDL5erE0qV7sWVLrWa8srIVBw8azw9WfX27Zn/z5hr861/a5vj6fjaJpLKyBbNmfYDJk1/FBx9sNz1HG/RKtgx6ZWamICfHOuiVl2ddMlVX184bb0o4+kwvewS9eEtOFEl8hxERERHFuQMHzINYJ574pun4hg3VPX6u5uYOw5g6uFNf367pZ5NonnpqDebN24zVqytwxx2LTc9RBwX9Z3qlYsKEQs2Y+lx96dZdd01Wtuvq2jTfB6vnIIon+uCuHXp6MeBMFFkMehERERHFsY6OTqxdezCkxxw8aFzt0Z/Ozi48+OByTJ36Gt54Y5PheGVlKwDgttsWITf379i6tdZwTqL4/vtKZXvHjnq43V345JOd2LChShn3lp4C/oNemZkpmDFjqGbM4fD9eq+/me7Xz5f5VV/vYqYXJZzBg7M1+10xir/zvUcUPQx6EREREcWxDRuqlSBKSUk2hg/PCfiYxkZXSM/x0kvr8cADy/HttwfwwAPLDcerq1vR1SXx97+vCem68Uhf2nnRRfNxxhlvY9y4l7FuXSX+/e+NGDv2ZeW4p5G9+U1xTk4qjjhigGZMHVC86qrD4XR6Gt3/+tdTkJubrhz705++wa5d9co+b7wpUSxefKmyHatMr337fAuG8L1HFFmOwKcQERERkd0sXboXb721BddcMw4A0N7eiWOOKTacp87aOuSQPM3NlpVQgl5SSmzc6L8csrq6VbPqYCLTl3a+/76n9FNKYPz4uYbzPZle5r+y5+SkIilJIDMzRSkrrapqVY4PGODEmjVXYd26Kpx1VqlmgQHAl4EHsK8QJQ51EDlWQa/77/9K2Q41E5eIQsOgFxEREVEf09HRiYsueh9VVa146ilf9tQHH1yAs88eqTm3ocHXWD4nJw3r1lUhEH3Qa9eueqxaVYGZM0fA6UwB4Al2zZ79Gd56awtaW/0HtKqr20x7fSWiUJv4p6QkY+BAJzIyHIb/zzk5nnLFSy8dg5deWg8AKCx0as4ZPTofo0fnAwCGDNGWdqkx24QShXoFx1gFvb755kBMnpcoEfFPOkRERER9TG1tmyajx+vKKz8yjNXX+wJY/fqlKuVu/qiDXs3NLkyc+Aouvvh93HLLInR0dGLLlhosW7YPzz77PaqqWgMGtNzuLlRU9HxFyHjS3h5q0CsJmZmpePvtcw3HvCs3/vWvJ6K4OBNJSQJPPHGS5bVGjcq1POYNZhLFOzsEvdQGDcqK9RSI4hqDXkRERER9jFXgpK6u3TCmz/T65z/P0Nz0mWls9AWx3nxzM+rrPdd46aX1GDXqBYwZ80+ccMIbIc25rCxwWWUiCDXjzduYfubMUixdepnmmDfTq3//DOzceR3Kym7AZZcdanktf5lexcWZIc2LqK+yQ9Br7FhfL75HH50ekzkQJQoGvYiIiIj6mLY286CXN/NHzRuwAjyZXjNmlOCLL2bhlVdm4pRThplep6qqBa+8sgH/+79f45prPtEc27OnsUdz3ru3Z4+LN01NoQW9UlJ8v64PHKgNTKm/32lpDhQX+88YSUoSuPLKww3jY8bkQwj/gVCieKEOenV2xibo1dTky6Y9+uiBMZkDUaJgTy8iIiKiPsaqKXy/fmmGsYYG382VNzPoJz8Zgp/8ZAi++mo/Pvtst+Exb7+9FW+/vbVHc3M4kuB2dxnG9+5tMD1/5Ejrkrt4pL7ZDYa/oFd2tjHIGchLL52BW289EunpDhx//Buor2/H7NkTQ74OUV+lju9KGZuglzqbNiuLpcVEkcRMLyIiIqI+JpSglzbTS3v83nunKiuZzZw5Iixze/XVMzFpUhEmTizEsccOUsbVmV6DB/sykgKVWsabUMsb1UEvfZDL7PsdSHJyEqZMKca4cQX48cdfYPXqK3HrrZNCvg5RX6XOaoxRzEvTN7EnwWsiCh6DXkRERER9jFV5Y26uNghSUdGMd9/dpuzrM4WGDMnGqlVX4t13z8O7755nWPmvJ4YNy8GqVVdizZqrMGFCgTKuLovs3z9D2Q51NcO+rLOzCy0t/le61EtJ0a6qOGfOaSgpycaf/vSTXt8sDxqUhSOPLOrVNYj6GnWgPRaZXi5XJ1wuz+decrJAejqLr4giie8wIiIioj7GKtNLP37nnZ+jtrYNADBiRD+cckqJ4TFHHDEARxzhaar8y1+OxcMPr+jV3DIyfL9e5uenK9vqTC91hlJHh7EUMl6FGvACPDfFatddNx7XXTc+XFMiSjjq8sZYNLJXlzhnZaWynx5RhIWU6SWEKBRCjFDtCyHE9UKIvwkhzgn/9IiIiIhIzyrTSx1UaWx0Yd68zcr+nDmnISPDf++YceMK/B4PhlXQa/9+3+qN6oy0RAp6hdrPy/OY0Mohicg/bU+v6D8/SxuJoivU8saXAdyp2v8DgGcAnAHgXSHE1eGZFhERERFZscr0amnxBUiWL9+nrEw2fnyB5UqNauPHD+j13NLTfeV4WVm+Gzp1Lyt1ppe3zCcRhNrPCwBqalojMBOixKXt6RWLTC/f50B2NpvYE0VaqEGvSQAWA4AQIgnAjQDukVIeCuBPAO4I7/SIiIiISE8d9DruuMHKtjrTa+PGGmVb3VDenzFj8v0eP/PMwM3u1ZleVquS9evnC4YlVqZXT4JebRGYCVHislOml/oPA0QUGaEGvfoBqO7engwgH8Br3fuLAYwK07yIiIiIyIK6vHHIEN9KiAcPtuDbbw9ASqkpJywpyQ7quvqm6XonnzwMP/74C7/nqEsorW7oErWnV0/KG6urGfQiCqdYr97I8kai6Ao16FUG4PDu7bMAbJJS7uve7weAP5WJiIiIIkyd6dW/f4ZmNbKpU1/Dk0+u1gS9Bg3KQrDUKyvqOZ0OjByZ6/fxTqcv0ysz0yrTSx30Spzyxp5ketXXt0dgJkSJK9arN2rLGxn0Ioq0UINe/wTwFyHEWwB+A2CO6thUABvDNTEiIiIiMvfFF3uVbafToWkYDwB33PF5j4Nef/vbDGX7xRdP1xwbMiQbqanW2WAZGQ4kJ/t+vbQqb8zOTlVKjKQEOjsTI9urJz29eFNMFF6xXr1RW97Inl5EkeYIfIqPlPLPQoh9AKYAuBWeIJhXPoAXwjg3IiIiIjLx9ttble3U1GQMGJCBqiptw/P9+5uV7UGDMoO+9hVXHIaUlCSkpibj/PNH4fnnv8eKFeWYNm0QTj99uN/H6m/grG7onE4HUlKSlSb2HR1dmmBZvOpJeeNrr50VgZkQJS6WNxIllpCCXgAgpXwFwCsm4zeGZUZERERE5Fd2dqpy43TKKcPw5Zf7sGlTjeacnmZ6JSUJzJp1qLK/aNGl+OGHSkyZMjBgzy+nUx/0Mr+hczpTkJmZogS9GhrakZ4e8q+lfY6/8sb/+Z+j8fDDKzRj3333Mxx11MBIT4sooWgb2ceivJFBL6JoCvm3CyGEA8BFAH4CT3ZXDYAvAbwjpTRfP5uIiIiIwkbd/P2YY4oxYICxD5c3KJaWloy8vHTD8WBlZaVi2rTBmrHc3DTU1Rl7TenL96x6ejmdDgwalInaWk872H37mlBYGHw2Wl904EATbrllkeXxtDRtQHHkyFwGvIgiIPaZXr7PSZY3EkVeSHnkQohCACsBvA5PI/vS7v++AeA7IURB2GdIRERERBrq5u8pKUmmQS+vQYOyNDd54XDuuSNNx2tqtGsaWZc3pmDwYN+Kkvv2NZmeF08efPBrv8eLi7XZePogGBGFR6QyvV5/fSOOPPIVPPvsWr/nsbyRKLpCbZ7wGID+AKZKKUullMdKKUsBHNM9/li4J0hEREREPlJKdHb6btQcjsBBr3B77LEZOPTQfAwerL22vil0RkYKDj003/D4zMwUzWPLyhrDPke7ef757y2P5een47LLDtWMJUK5J1EsaFdvDN91r7jiQ6xdexA33/wZWlrMS5nb29148snVyj6DXkSRF2rQ60wAv5VSahoOSCm/A/A7eLK+iIiIiChC3G5faaPDkQQhBAoK/AW9wl822L9/Bn788RfYvfv6gEE1fTAH8JQ3Dh3qy/Tavbsh7HPsS373u2PQr18aZswYqozNmjUmhjMiil/RWL3RaqXW557TBr8Z9CKKvFCDXmkArP4U1wiA71oiIiKiCFL380pJ8fwqF+1ML8DTFyc5OQkjR+b6Pe+668Ybxvr3z0BpaT9l/+GHV2D+/G1hn2NfMXv2RADACy+cjpNOKsEVVxyGO+6YHONZEcUndbl3ZWWrnzODp/5jBGBdNvnii+s0++zpRRR5oQa9vgHwWyGE5k+G3fu/7T5ORERERBFil6CX1zPPnKxkTrz44ummz3/ccdpG+MXFWYZg2fnnv5cQZY5eKSlJGD48B59+ejEyMjw3vqWluVi06FK89tpZSE1lTy+iSFBnerW1ufHee1t7fc22Nu16bi5Xl+l5GRnasmVmehFFXqjNAu4G8DmAvUKITwFUACgEcDoAAWB6WGdHRERERBraJvaewEgsg15jxxZgzZqrUFXVipNOKjE95/HHp2Pq1H+jq0villuOBADTDLEPP9yBG26YENH5xkp6ukNzY/zRRxfhlFOGxXBGRIlJv7DHBRfMh5S/6tU19UEv9ee0mr5XH4NeRJEXUtBLSrlWCHEIgF8BmAJgPIADAJ4D8JiUsir8UyQiIiIiL3Wml8PhuXkrKHBanq9vNh8JEyYU+j0+ZUoxPv30YmzcWI2f/3wsAGDgwEw4nQ60tPhuFtPT4ze7yenUBr28WXpEFF1hXswWANDWpg1yWWV66YNeWVkMehFFWsjLwnQHtv4nAnMhIiIiogC05Y2xz/QK1sknD8PJJ/sym4QQKC3Nxfr1vr+ZxvOKhe3t2ptifQ8gIooO9eqN4RJsphfLG4miL6Q/MQkhdgghTHPOhRBjhRA7wjMtIiIiIjJj1tMrM9O6GbJdgl5mSkqyNfvJyRFIwbAJ9U1xbm4apk0bFMPZECUufXljOPS0pxcb2RNFXqh51cPhWcHRjBPAkF7NhoiIiIj80vb08vwqZ3UTl5WVYutMgv79tRlq+myoeNHR0YnOTt9qbitW/ExpXk9E0RWN8kb1Hyf88fcHCyIKj4A55EKIHADqTqMDhRD6LqXpAC4DsC+McyMiIiIiHbNMLyt2zvICjEEv/Y1jvGht9WWBZGWl4JBD8mI4G6LEFpmglz7Ty/yzTP1Z8Ic/HBeRrDMi0pRVSr0AACAASURBVAqmccKdAO4HILv/vWtxnoBndUciIiIiipBduxqUbW9PLwBwOJIMfaLsHvQ65BDtCo7t7W6LM/s29Y1uPPctI+oLIhFo0mepBhP0mjJlYNjnQURGwZQ3/hvAOQDOgyew9WsA5+r+nQFguJTy8QjNk4iIiIgAXHLJ+8p2VVWrsr106WWGc+0e9Lr66rGa/UTI9NL39CGi6IpGppdVeaP6vHherZbITgIGvaSUW6WUH0opFwCYAeAf3fvqfwullHsiP10iIiKixLV5c40mo6CsrFHZPvbYQXjkkRM15w8alBm1ufWE05mCW245UtnX3zhGw1//ugInnvgGli7dG7Hn0N7oMuhFFEuRWb0x9Ewv9vUjio6QfupKKb/wbgshkmHS1F5K2RKGeRERERGRzssvr/d7PC8vXbNv90wvACgo8PX1inbQq7y8Gb/97VJICZx44ptob78Tqanhz75QZ32kpoa6jhQRhVM0Vm+0yvRqaelQtpnpRRQdIf3UFULkCCGeEkLsB9AOoNHkHxERERGF2RNPrMLDD6/we05RkVOz3xeCXurMp2iXN5aXN0P6FlXE669vjMjzaBcf4I0uUSxFY/VGs0yvRYt2Y8OGamXf6WSmF1E0hJpf/TyAswG8AOBHAK6wz4iIiIiIDO644/OA5xQVacsZ+17QK7qZXvrm048+uhJXXXVE2DNBQllxk4giKxKZXh0dnbp9Y6bXhRfO1+wXFjoN5xBR+IUa9DodwJ1SyhciMRkiIiIiMursNC+V0euLmV5pab7Mp2hneumDbOvWVWHnznqUluZaPKJn1DfEDgeDXkSxFIlML32QyyzTq6FBmy+Sk5Ma/okQkUGoP3WbAZRFYiJEREREZK6lJbgMKH2mV3GxvRvZA9q+Nuomz9Fglll24EBz2J+HmV5E9hHORvZSSuzZ02AIeln19FKLRMYZERmF+lP3UQA3CyH405qIiIgoSpqbOwKfBCA1NRm//OVYAMDPf35En+gZk5PjWxepoaE9qs9tFmSrrAz/mkwMehHZRzhjTb/4xccYNmwO7r57iWbcavVGIoq+UH/qDgYwAcBmIcQcIcRfdP/+L1wTE0JcJoRYLYRoEkLsE0K8IoQYpDtHCCHuEULsFUK0CiGWCiEmmlzrcCHEIiFEixBivxDiD92rT0bkWkREREThZBX0OuWUYYaxF188A/v334iXX54Z6WmFxYABvtUbq6pao/rcZuWUlZXhn4O6vJFBL6LYCleGldvdhblzN5geC5Tpdeedk8MyByIKLNSeXhcD6Op+3KkmxyWA3/Z2UkKIcwG8DuBpAL8GUAzgfwF8KISYLKX0for8D4D7us/ZBOAuAJ8JIcZKKcu7r5UH4DN4Gu+fB2AkPBlrSQDuVT1tOK9FREREFDbqoNdhh+Vj+vSh2Lu3EU8+eZLp+cXF9u/l5RXLoFdNjfH5Ip/pxb+VEsVSuDK96uraLI+1tHg+s6WUSpAtPd2hlFT/4Q/HhWcSRBRQSEEvKeWISE1E5woAq6WUt3gHhBANAOYDGANgoxAiHZ5A1Z+llE91n/M1gF0AboEvCHUjgAwAF0opGwAsFELkAHhACPEXKWVDOK8Vmf8dRERElMjUQa/s7FQ884zZ3x77pv7905Xt6mrrm8hwWbJkD+bN24wDB5rx3nvbDMcjkenldrO8kcguwpXpVVtrXY69e3cDfv/7L/Hcc9/j/vun4eabJyoBLyGAzEz7l54TxQu7/tRNAVCvG6vr/q/3U2oagBwA87wnSCmbAXwAQJ3PPxPAJ7qA1BvwBK9OjMC1iIiIiMJKHfTqC326QpGf78v0qqlpDXqlyp5wuToxY8Y8PPvs96YBLyAyfcVcLga9iOwiXJletbXWQfq1ayvx0EPfoqamDbffvhiNjb6VG7OyUtnEniiKQv6pK4QoFUI8K4RY191ra50Q4hkhRGkY5/VPAMcLIa4SQuQIIUbDU964WEr5Y/c5hwLoBLBV99iN3cegOm+T+gQp5R4ALarzwnktIiIiorDylsoA8Zch4HAkITfX08xeSqCuLnLN7IMpXWxqCm7RgGC4XJ044YQ38NOffqiMsbyRKLZ6u3rjihUH8MUXe1FTYx30+uGHSs3+li21ynZWVnx9hhPZXUjljUKIyQA+B9AGYAGACgBFAC4C8FMhxAwp5ereTkpK+aEQ4moALwKY2z28HMC5qtPyADRJKfUdSGsBOIUQqVJKV/d5dTCq7T4W7msphBDXA7geAIqKirBkyRKTh/Y9TU1NcfO1UN/B1x3FAl93FCv6196KFdXKdnNzbdy9LtPSpLK9cOFSDByY5ufsnisrC1w+uXv3gbD9/50//yC+/LJMM1ZVVWHb7x8/8ygWov266+yUhrFgn3/dukbcdttmAMCMGYbbP4W6pBkA3nzzS2U7OdnN95lN8DMvMYTayP4RAGsAzJRSKn8qE0I4AXzUfdy8o2oIhBAzADwH4AkA/4UnsPYAgHeFEKeYBKdsSUo5B8AcADjqqKPk9OnTYzuhMFmyZAni5WuhvoOvO4oFvu4oVvSvvZdf/q+yPXLkkLh7XfbvvxMVFZ7A3tixkzB2bEFEnmfVqnIA6/2ek5qaE7b/v2+8sRDAHs1YSclg237/+JlHsRDt152nhHqVZizY57/hhheV7c8/r/VzplZzcy68nwWFhbl8n9kEP/MSQ6hBr6MBXKoOeAGAlLJFCPEIgDfDNK9HAbwvpVRWghRCrIWntPA8AO/Ak12VJYRI1gXB8gC0dGdmofu8fibPkdd9zHtOuK5FREREFDZVVS14883Nyv4ZZwyP3WQiJDs7VdlubAxfeaGeuq9Ob84JllkZE3t6EcWWWT+tri4ZVNmjv5JGf9asOahss7yRKLpC/anbCqC/xbF8eMoew+FQAGvVA1LKzd3PP7J7aBOAZACjTB6r7ru1Cbp+W0KIoQCcqvPCeS0iIiKiXmtrc+Ojj3bguus+VVb9mjy5CBddNDrGMws/9U1gU1P4gk56wQTUwvH8H364Hccf/zpee22j4Rh7ehHFllkPeX05Yrgx6EUUO6EGvT4E8LAQ4ifqwe79P8Oz2mE47AYwSfcch8GzSuKu7qHlABoAXKI6xwngHHhKIr3+C+B0IUS2amwWPAG0LyJwLSIiIqJekVJi1qwPcNZZ72hWGbzttklxuepXVpYv0yucjeT1opXpdfbZ72LZsn0oL282HGOmF1FsmX2GBhv06unHr/r66s87Ioq8UMsb7wIwH8BSIUQFgIMACrv/fQ3g7jDN6zkAjwsh9sPX0+v/wRPw+ggApJRtQoiHAdwnhKiFJ9PqLngCeX/XXes2AO8IIf4PQCk8/cEek1I2hPtaRERERL31zTf1eP/97YbxWbPGxGA2kactb4xcpldDQ+CVISMZdAMY9CKyo0hneqkx04souoIKegkhMgCcCWA4gGcBPAXgEADFAA4A+FZK+WkY5/UkABeAmwDcCM+KicsA/E5Kqf6T2cPwBKZ+B0/Z5UoAp0opK7wnSClrhRAnd8/5g+5rPQ5PsAoRuhYRERFRj3R1STz/fJlh/MorD0daWqh/r+wbolfeaH7tiRMLsXatp/youbkDbncXHI6eBae6uowrw6kx6EVkP2YrOpoJR6YtM72Ioivgb05CiFIAn8ET8PJqADBLSvlJJCYlpZTwBNeeDeK8P3X/83fejwiwqmQ4r0VERETUU+vXV2H3bmOb1HPPHWlydnxQZ3pFq7zxrrsmo7KyFa2tbvz97ydj4sS5qKjwrNW0Z08DSktze/Qcra3+58+eXkT2E81ML/XnHRFFXjB/LvwLgC4Ax8OztusIAM/AE5AqjdzUiIiIiBLPtm3mC0LH842SOtMrkuWN6kb2gwdn49FHZyj7Y8bkK0GvLVtqexz0ChS0czjirycbUV/H8kai+BVMfvWxAO6VUn4lpWyTUm4EcAOAYUKI4shOj4iIiCixbN9eZzoezyUxZo3sN2+uwcsvrw+qD1cwGhrasXSpr2xUH0QcPTpP2X766TV45ZUNaG93h/w8zc3+g167d7MNLJHdBAp6LV68B9dc8zEOHmwJeK2xYwf4Pc6gF1F0BZPpVQxgh25sOwABYCA8Pb2IiIiIKAx27qw3HY/nTC9teaMLTU0uHH/866isbMXChbvx2mtn9er6ra0dOOywl7B/f5PpcwJAfn66sr1gwQ4sWLAD9fXtuPVWzYLiAQUKeiUns6cXkd34C3q5XJ04+eR5QV/rscem47TT/mN5PJ7/gEFkR8H+1A2usx8RERER9Up5uXkmQXZ2/GYH6Msb33tvGyorWwEA//73xl5ff+nSMk3ACwBycrQ3nmlpxl5bt922WLM/f/42jB//Mh566BvL59qxwzxoCXia2M+ePTGYKRNRFLnd1re71dWtIV0rUFCLmV5E0RXsEkCfCCHM8rsX6cellIW9nxYRERFRYqqoaDYdj+fsAH15Y1lZY1iv73IZszj0mV6pqYEbzJ9//nsAgHXrluGqq47AkCHZmuPNzS7lHLUzzxyBxx+fgYwMB4YOzQll6kQUBZ2d1pleMsT0j0ArtMbzZzmRHQUT9How4rMgIiIiIgBQmqnrxXd5ozbT68AB88BfT+zb14hzz33X5DkDZ3r5U17ebAh6rVxZYXqu2y0xenR+SNcnougJVN4YikBBr3j+LCeyo4BBLyklg15EREREUVJe7gv4jBjRDzt31mPixMKQgzJ9iT7T68CBJj9nh+bOOz83HTcGvfz/WqxfVdIsM8zq5ritLfSG+EQUPf7KG9vbQwt6ZWWl4oQThmgWztAeZ3kjUTSxkyYRERGRTaxYcUBphJ6WloylSy/DnDmnYcGCCyCEiPHsIkd9E9jUFN5Mr7fe2mI6rm5cDwCpqf5/Lb7ttkWafbMAV0uLeXBrypSBfq9NRLEVzkyv3Nw0vPzyGRg0KMv0OMsbiaKLQS8iIiIim1iwYLuyfc45IzFkSDauu248Bg/O9vOovk+dddXY6MK+fdpMr66unq+p5HAYf929447JyMvTBr0CZdK9/PIGzb5Z9kdLi2/lxvz8dOTkpGLYsBzcc88xoUyZiKLMG/Tavr0OF188H/feuwyyu5lXqJleOTmpGDEiF3v2XI933jnPcJyZXkTRxaAXERERkU1s2lSjbJ91VmkMZxJd6syHurp27NnToDne3t7z8sCMDG3Z4iOPnIjHH59hOC+YRvZqZiWLra2+sfPOG4Xy8puwffu1yM/PCOnaRBRd3qDXpZd+gLff3oo//ekbLFiwA4D/TK+77z5Ks+90OpCS4vksSU5OwqmnDjM8hkEvouhi0IuIiIjIJtRBr0MPTZzG5+qbwNZWNzo7tZldbW2hZVqo6YNeOTlppuf5y/Qyu+kNlOnldDqQkZGC5GT+uk1kd96g1+rVvsUo5s/fBsD4Xl+37udYvPhSrFlzFSZNKtIc69dP+/mSlZWKZcsu14xlZDDoRRRNwazeSEREREQR1tnZhS1bapX9MWMSJ+iVnJyEjAyHJlNKLdTyIjWnU/vrbkGBedaVv0wvs8b6Zple6p5e+mAbEdmXPtAOAElJnj6K6qD34MFZGDu2QNnfvLlG85jcXGNQ/bjjBmP69KFYsmQvzjqrVLkuEUUHfxoTERER2cCePQ1KcCcvz2HoORXvsrJSLINevVn9MDc3HYCvXPKUU4zlRoD/TK/9+42N9c0Ccer5O53M5iDqK8wa2XuDU+r3+pFHFmrO0fcM1Gd6eX388UVYsaIcxxxT3NupElGImG9NRERECU1KicWL9+Drr/crjYtjQV3aOHRoYgW8AG0ze73eZHolJ/uyKh5++HjLldOsMr3c7i7s29cY1Jz05Y1E1DeYB708/1Vneuk/J9SfL4B10CstzYHjjx8Scu9AIuo9/jQmIiKihLVhQxUmT35VCWCccsowzJ0703Kp+UjavNlX2lhSknhBL6tgFNC7TC91IOrss0danmeV6bVgwXZccskHQc1JnenFvj1EfYfbbV3eqA5w6z8ngs30IqLYYaYXERERJZR16ypx440L8fHHO3HzzZ9pbmg++2w3fvWrJTGZV6Jnevlb0aw3jezVfbb8ZV9ZZWBccMF803HzTK/gnouI7MVfeWM4Mr2IKHYY9CIiIqKEct11n+L557/HzJlvY+nSMsPx11/fhJaWDpx88jyMHv0i1q49GJV5bdpUrWwnYqaX//LGnmV6bdhQhd27ff28/PXZ8tfTy8xvfrPUMNbY6ArquYjIXoLt6aX/nNCvzmrWyJ6IYot/giIiIqKE8u23BwKec/jhLynBkjvuWIwlSy6L9LR05Y3mKwzGM3+ZXuoMqmBVVDTjqKP+pRnLzLR+jlB77bhcnSgra0RnZxdqatpQWpqLvXt9vb8GDcoMbcJEFDP+V2/0BcT0nxMsbySyPwa9iIiIiHTU2UFffGHMBgu3r77ah/JyzwqBaWnJKCqyznqKV/56elVUGFdPDGTlynJN361Zs8b4fQ79zWswhg59XtkuKMhAVVWrsj98eL+Qr0dEsWGW6SW6KxfVmabGTC99eWPifXYT2R3LG4mIiCihmGX0hFraFm5PPLFK2R4+vJ/hRioR+CtvLCtrCvl66gDUsGE5+Pe/z/Z7fmlpP5x8cgkA4MgjC0N+vsrKVngX/0xOFhgyJDvkaxBRbPjv6cVML6K+jEEvIiIiSihmNzex7sOydWudsj1z5ogYziR29OWNEyYUKNtlZY360wNSB73OP3+UcgNrRQiBhQsvQXn5TXjqqZMtzxsxInAG19Ch2T3KHCOi2PDf0yv4TK/c3MTrx0hkd/xpTERERHGnvr4ds2Z9AKfzb5gy5VWlPM7t7kJXl7F3S3Z2Ki6+eLTl9Roa2iM2187OLs3KjffeOzViz2Vn+tJDdbbVvn29y/QaMCC4HmlCCBQVZaJ/f+vzt2+/FqecMszvdYIJjBGRffQ004vljUT2x6AXERERxRUpJa655mPMm7cZra1urFxZgblzNwDQLj2vlpWVimeeOQUPPjjN9Pg//vFDxOa7e3eD0nuqsNDpN+ASz/TljerAUUtLR8jX60nQy6u4OBMpKea/JgshkJfnPzOQ/byI+ha327qRvb/VG1neSGR/DHoRERFRXHn11R/x9ttbNWMbN1YDsA56rV17EAUFTvy//zcNxcXGVfe+/np/+CeqmxsAHHZYfsSex+705Y3qnljqTItgVVe3KduhBhJzctLwxBMnWR53Oq1XgQSY6UXU13R2+sv08v3cSE3V3j4nJzPoRWR3DHoRERFRXHnrrc2GMW/PLKug1znnjFS2S0pyDMcPHmw1jIXLypUVyvbhh/eP2PPYnT7TSx30UvfUCVZzsy87zF+TfCs33TQRU6cWmx5zOv0vgM6gF1Hf4nZ3QUpttpdv9UZ1ppf2ve9w6Ht6MehFZDcMehEREVFc+f/s3XeYVOX9/vH7bG9sBZalCCwdRBBEEUQQJRrF2CXWmJ+KJiYxxphoLIk1xpLEaGL92rBhL7EbiqIiiPQivbO99za/P9Y9M2fOzOwOzM7szL5f15Ur5zznzJkH3GV37/08n6e01N5/a926IjU3t1gqhhISYjRmTJYSEmJ0xRVjzfEBA+y77m3dWtopc62vb9Jjj602z6dM6dcp7xMO3BvNuy5JPJhKL9clke2FVN64L1269toJPzzPd6XXoEH24BRA19XU5FBjo/Xfmebm1hDMV6WXYVj/3TqYgB1A5zq47wAAAAC6qMrKBttYeXm9VqzItwQpOTnJWrv2MtXXNyshwfkt0bBhGbbXHzhQrZqaxnbDDn+9+OJG5eVVm/M57zzvzfQjXW2ttZrLtXfOwVR61dQ4X5OcfHD/3dxDrzvumCqJSi8g0jQ1taixsdk2Jvmu9HLvN+i+3BFA6PFZCQAAIorrTouuy9OWLTvg9hv7aBmGYQm8JOk3v5lg6y8lSdu3lwV0ng0Nzbr33mXm+W9/O9H2A1V3MnZsT8u5a+h16JVegQm9UlNbly4lJnp/nmFI2dn2vnAAuq7W0Mv/Si8qu4Cuj9ALAABElMpKZ9gxffoA83j16kLLb+zdf3hp06dPsr766kLNm3eqpk3rb45v3RrY0Ovxx1dry5bWZZM9esTpqqvGBfT54WbcuN66+ebJmjSpjxYuPF9xca6VXp57sXny9df79fTTa3XgQLU5drDLG4cOTfc47ut58fExtrAMQNfW1NRi6/noudLLunvj8OGZuvji0UpIiNEjj5zY+RMF4De+IgMAgIjiurzxuOOcPbLWrCm0VXp5M3ZsL1188WhL9dG2bYENvRYu3GMen332MHb9knTXXcdp2bKLNWPGYW6VXh0LvXbsKNO0aS/r8ss/Vnm5s+LvYCu97rrrOGVlJSo62tDbb5/ZoefV1fm/FBNAaHW80sv+dWPevFNVXv5rXXPNkZ07SQAHpfvW0AMAgIizZ0+F5QeUo4/uYx6vXVtk6RvlK/RqM2SIs9In0KGXazjSnXt5eXMwlV5PP73O/EHV1cFWemVlJWrPnrkqL29Qnz7OJYvuu7wBCG/NzfZG9p4qvbx93ejI1xMAoUGlFwAAiBi33LLEct67d7IZVtTWNmnDhmLzmrflja5cl7f5Wt7Y0uLQ11/v144dHQ/GXEMvXz2iuit/K71qahp1111LPV47lL/fxMRYS+AlSXv3Vh708wB0PW+/vdUWmD/22Gr973+7LP/+uC9vBND1EXoBAICI8fzzG2xj48b1Mo+//TbfPA5kpddjj63SlCkvadSoZ/Tqq5s6NFfXqrOEBH6QcudvpdfGjcVer0VFGQGZU5uzzhrm9dqsWQMD+l4AOt+2bWVasmSvbfzss9+x7ARLRRcQfgi9AABARCgpqbWc33TTMZKkI45whl7vvrvVPO7Ib+xzc9PM4127KlRRUa/77lumO+74SsXFzvebN681bKuvb9acOf/Vvn3tVwLV1TmDnMREOk64i4mJMsOqlhaHmpt97+Do+oNpZzvyyGz9/e8zdNllY7Rly+UaPjzDvEYzayA8XX31Z7axiooGFRbWmOdUegHhh++wAABARPjii33m8dCh6brnnmmSpIkTs83xwkJnUBUb2/4PL4mJserXL0X79lWpudmhtLSHzWu7d1fqqadOVlNTi5YuPWB53TffHNDZZ/fw+WzX5Y0JCXxL5klcXLT591Rf36ykJO+/r62oqPd6rTNcd91R5vHGjf9PFRX1Sk9PCOocAHS+8nLn5ihUegHhh0ovAAAQEdasKTSPTz99iOU4Odne02nKlL4dem5ubrrH8f/7v7WSpO+/L7FdO+ecdzVr1muqqmqwXWvD8sb2+dPXq7Ky0Tw+//wRmjNnhGJjo/TPf57QafNrExVlEHgBYc7bBhWuv6Cg0gsIP4ReAAAgImzdWmoejxyZaR4nJcValp9J0oUXjtL11x+ljhg4MNXn9RUr8j2Of/bZLn300Q6vr6ORfftcNxtor6+Xa6VXamqcXnnldFVW/kbXXjux0+YHoHuh0gsIP4ReAAAgIrjurujagF6SBgywLjW87rqJMoyONTc/2NBLkgoKnL1gmptb9Oabm/XJJzslUenVEfHxzmWf7Vd6OavqevSIs70eAA4V/1YD4YfQCwAARATX0GvoUGvo1b+/NfTq2TOxw8/1J/R6992z1Ldvinnu2qz+pZc26pxz3tXJJ7+uL77Ya7lGTy/PXCu9XP++PKmocIZeqalxnTYnAJHJy+pGi6QkqnKBcEPoBQAAwl5lZYNZVRUXF20Ludwrv/wJvWbOPEzR0Z6rwpqbW7RypTP0OuqobP3854eb59XVzj5Tl176oXl85ZWfWCqX6BPjWWpqvHnsWsnliTX0ivdxJwD4LzraUGwsPz4D4YbPWgAAENZaWhy6//5l5nlubpqio63f4hx9dB/LuafG9t4MGZKu7767VG+/fabt2vffl6impnWZYk5OsnJyUpSU5KzaqqlptL1GkoqKnLtIJiTEdHipZXeTnu4Mr8rKfO/OWF5u7ekFAIGUmMi/1UA4opYeAACEtSeeWK0771xqnrtXdUnS5Ml9dcQRvbRmTaHOOGOo3z+4HHFELx1xRC/b+KpVzh0jJ07MlmRd/lJT06SCgmqtXFlgeZ1rBRg9YrxzDb1KS+t83ltS4ryeldXxSj4AkLzv3tiGpY1AeCL0AgAAYe3BB7+1nLv385KkmJgoLVo0R8uX52n69P4Be+/9+6vM49zc1vd1rSIrLa3T+PHP68CBasvrXHdu5Acp7/yp9HINvTIyWN4IILBcq3gBhA8+cwEAQETJyUn2OJ6RkaAf/WhQQN/rwAFn6NUWtLj+YDRv3oZ2n9GrF1VJ3qSnJ5jHZWXtVXo5l4xmZvJ3CiCw+AUFEJ7o6QUAAMKa+3LGceN6B+299+1zhl5tAY2/PxjRI8Y714qt9iq9ioudoVhmZoKPOwHAf1R6AeGJ0AsAAIQ11/5YsbFROumkgUF77717XUMve6VXR1RV+d6VsDvLyHCGV3fdtVSff77H433z5q1XXp5zCSmhF4BAS0yk0gsIR4ReAAAgrFVVOUOvpUsvUkxM8L692bGj3Dx2hl7+/WBUWUno5c1RR1l33ZwxY762bCm1jK1YkadLL/3QPM/ISFBiIhUZAPzTTh97Kr2AMEXoBQAAwpprpVdKSnB/E+/ayL4t9PJ3DrNnDwnonCLJpEl9lJbmXOLocEgPP/yd5Z5Nm0os5w8/PJMlowACjp5eQHgi9AIAAGHNdXmg686JwdYWzmRldbyJ+qhRmbrzzqmdNaWwFxMTpZkzD7OMtbRYyzFcK+UuumiULrpodFDmBiB8DRuW4fdrqPQCwhOhFwAACGuuyxtTUuJCNo+29+7Z03vodeSRzib7Dz00U+vX/1w5OSmdPrdwNm1aP8t5fHy05byiwhl6edu5EwBcvffeWRo3rpdfr2HZNBCexH/lDQAAIABJREFUCL0AAEDYKi6utVT6dHal1yefnOv1WkJCaxjjvgRm+PAMPfPMKVq27CI98cSPNH58b1144Sj98pfjWYbXAe7LP0tK6vSf/6zUBRf8Vxs3FltCrx49Qhd6AggfI0Zkav780/16DcsbgfBEXA0AAMJSQ0OzzjzzbfM8NTWu05vYz5o1SE888SPNnfuJ7Zq3KoAxY3rqsssON89Xrry00+YXiYYNy9CsWQP16ae7JEmffLJLzz67XpK0eXOppk7ta96bmhrv8RkA4M7frxcsbwTCE5VeAAAgLN177zdasmSfeX7DDZOC8r7nnz9CJ588yDbuLfTydwkN7O64w9n3zHXzgO++y7dU+qWmUukFoGNiYqyVtg6X7RsTEuz/nlPpBYQnQi8AABCWPvhgh3l8xx1TdcstxwblfdPS4vXRR+cqOtr6A5PrD0k33XSMJCkzM0G/+tWRQZlXJOvdO8nrNZY3AjgY7pVeLpmXx19i0NMLCE985gIAgLBUXl5vHp9zzrCgv390dJSam5st523uvHOqTjzxMI0YkenXbo7wrKOhF5VeADrK9d9sd0lJMSottY8BCD985gIAgLDkuqwtFBU+vnrQR0dH6cQTBwZvMhEuOTlWiYkxqq1tsl377LNd5jE9vQB0lPvyRleeqrpY3giEJ5Y3AgCAsPPyyxu1b5+ztxNhR2QzDEPZ2d6rvdr06MEPpQA6xlcje08BF5VeQHgi9AIAAGGjvLxeCxbs1oUXvm8ZT0kh7Ih0vpY4tiH8BNBRvpY3Jifbv6YkJvJ1BghHxNUAACAsVFc3aMSI/1N+fo3tmq8fXjqL4Wt9IwKuY6EXPb0AdIz7P+EtLc5O9vHx0bb7qfQCwhOVXgAAICx8+eV+j4EXuoeOhF7s3gigo1JSvP974XDdyvEH9PQCwhOhFwAACAsFBQRe3VlHQq9QVPwBCF8PPDDd43ifPsm2MSq9gPDEdwYAACAs5OdXexyfPr1/kGfSaurUvubxscf29XEnAqEjoRcA+CMzM8HjeJ8+yerbN8Uy5mlHRwBdH6EXAAAIC66VXjffPFlz5x6hceN66c9/nhKS+dx113EaOjRdgwen6d57p4VkDt3JwIGpoZ4CgAgTFeW5N2N0tKFbbplsGWN5IxCeiKsBAEBYcO3nNWhQqu6667gQzkaaPLmvtmy5IqRz6E6OOKKXz+tnnjk0SDMBECm8hV5RUYZiY631ISxvBMITn7kAACAs7NtXZR576reCyJabm67k5FhVVzdaxvv1S9Fllx2uq68eF6KZAQhX3iu9ohQXZ93BkUovIDyxvBEAAISFnTvLzeNBg1jq1t1ERRkaO7anbXzOnBG6667j1L9/jxDMCkA487W80f1afHy0x3sBdG2EXgAAoMtraXFo9+5K83zgwLQQzgah4mmJY2ZmYghmAiASGIb35Y3NzS0duhdA10boBQAAurzCwho1NDRLkjIyEtSjR1yIZ4RQGDky0zZ24YUjQzATAJEgystPw9HRhhobWzxfBBBWCL0AAECXV1HRYB5nZMSHcCYIpeHDMyzn7713lgYPTg/RbACEO1+N7Am9gMhA6AUAALq8mhpn8/LkZJoJd1fTpw9QRkaCJOm44/pp9uwhIZ4RgHDmq5F9UxOhFxAJ2L0RAAB0ea479hF6dV8pKXH66KNz9P772/Wzn40J9XQAhDlfjewJvYDIQKUXAADo8lxDL7aN796OPjpHt98+Vbm5LGsEcGh8LW/8yU+GmudTp/YL1pQABBiVXgAAoMuj0gsAEGi+Kr2GDEnX/Pmz9dVX+3XddRODPDMAgULoBQBAEK1Ykad58zbopz8dqcmT+4Z6OmGjpqbJPCb0AgAEgq9KL0k6//yROv98dogFwhmhFwAAQeJwODRnzn+1bVuZXntts3bvnqvoaDoNdIR1eSPfvgAADp2vRvYAIgOfzQAABEl5eb22bSuTJO3fX6W9eytDPKPwUVBQYx5T6QUACATvlV5BngiATsOnMwAAQeIecu3aVRGimTgdOFClWbNe0znnvKOqqoZQT8ejm2/+QrfcssQ8J/QCAAQClV5A5OOzGQCAINm7t8pyvnNn6EOvCy74rz77bJfefHOLXn99c6inY/P88+t1zz3fWMbYvREAEAi+GtkDiAyEXgAABMnOneWW8/37q7zcGRx1dU1avHivef7qq9+HcDae/exnH9rGJk7MDsFMAACRxvCSbXkLwwCEH0IvAACCZPnyPMt5ZWVolxPedtuXlvMxY7JCNBPPNm8usY29995Z+vGPB4dgNgCASEOlFxD52P4IAIAgWbr0gOU8lKHX1q2leuCB5ZaxurrmEM3Gs0cfXW0bmz17SAhmAgCIRN4b2RN6AZGC0AsAgE5WX9+kf/xjhTZsKLaMhzL0Wr48Tw6HdSzUlWdtvv++RKmpcfr227z2bwYA4CDRyB6IfIReAAB0siefXKObbvrCNh7KkKmgoMY21hVCrzfe2Kxzz31XhiFbKAcAQCCxvBGIfETYAAB0socfXulxvLKyMcgzceqqoddLL22U5DnwuvXWyUGeDQAgkrG8EYh8VHoBANDJsrISJZXaxkMZMhUW1trGqqpCF8K1WbOm0DY2YEAPPfzwiTSwBwAEVJSXEhAqvYDIQegFAEAn69kz0eM4yxutGhqatWNHuW18zpwROuOMoSGYEQAgklHpBUQ+ljcCANDJqqqcYdLjj88yjysq6kMxHTkcDo9N4mtqQlvptXlziZqb7esax4/vHYLZAAAiHY3sgcjHZzMAAJ3MddnggAE9zOOystCEXlu2lGrfvirbeEtLaDvHv//+do/j48b1CvJMAADdgadftEhUegGRhNALAIBOVl3tDL369esh44fvpSsqGlRRUa+6uqagzqe4uM48zs5OMo+9ffMfDP/85wrdeKN9h0tJGj48M8izAQB0B96+/tLTC4gchF4AAHSi0tI6bdhQbJ6npsYpIyPBPE9Le1h9+z6m9euLgjYn12WV6enOuYSy0uu66xZ6vRYXFx3EmQAAuovaWkIvINIRegEA0Inuv3+55TwlJfaH3RydSkvrdN5573b6XOrqmtTc3KKKCmePsYyMePM41MsbPZk4MTvUUwAARKi6umaP4yxvBCIHoRcAAJ3o3/9eaTlPSYkzlze62rixRB9+6LmnVSAsXLhbPXv+WyNGPK09eyrN8fR0Z+gVquWNnsK2q68ep1NOGaQXXzwtBDMCAHQHJ5wwwOM4jeyByMFnMwAAncj9t8Xx8dEaOjTd472nnvpmp83j5JNfV3V1o7ZtK9Nf//qNOe661DJUlV5FRTWW8z/+8Wg9+ugsffjhuRoxgn5eAIDOkZISp5dfnm0bj+KnZCBi8OkMAEAnyc+vtuzQ+PDDM2UYhs46a5jX1+zbV+n12qFobGwxj4uKas3jrlDplZdnDb3uvvu4kMwDAND9eKr2otILiBx8NgMAcIhaWhyqrGywjX/7bZ55fOyxffWrX02QJF1++VitWnWpnnrqZNtrnn9+gxwOhz7/fI8++GB7QKqvqqvtc2vTFRrZ5+VVm8czZx7GDxsAgKDp0SPONkZPLyBy8F0lAACHoKamURMmPK+MjIf1zDNrLdeWL3eGXpMm9TGPDcPQuHG9lZubZnveN98c0Jdf7tP06fN12mlv6pVXNh3yHNevL/Z6zVrp1eL1vs504ECVedynT3JI5gAA6J4SE2NsIRe7NwKRg9ALAIBD8Morm7R6daGamx26/PKPLcHRd98VmMdHHWXfhdDTb5fz8qp1001fmOcXXfT+Ic9x7doir9d69XLuJNkVKr1ycgi9AADBYxiGUlJiLWOEXkDkIPQCAOAQvPba9+axw2GtqioocPaqGjLE3rw+OTnWNnbgQFXAw6e1awu9XuvdO8k87go9vaj0AgAEW0qK9ZdQLG8EIgehFwAAB2nPngotWLDHMrZ3r7MRvWufL09VXbGx9i/DeXk1liDKm4ULd2vUqKd11VWfyOHwHVatW+e90sv1vYJd6dXc3KKCgmp98cVec6xfv5SgzgEAAHulFz8mA5EiJtQTAAAgXD355Bo1NDRbxg4ccC7Vq6pyhl7u31BLUm5uukaPztKGDc7qMPfnSZLD4ZBhtP7WubGxWU1NLZo581VJ0qZNJbroolE6/nj77lNtfC1vDFWlV0NDs8aPf04bN5aYY/Hx0frRjwYFbQ4AAEj2X0xR6QVEDiJsAAAOkqcG8fv3O5uyV1Y2msfedof64ouf6t13z7L01nr77a2W+9qCsOLiWg0d+pSysv5tue6rkqugoNqyzNJdr17BqfTKy6vWyy9vVFlZnSTpxRc3WAIvSTr//BHKykr09HIAADoNPb2AyEWlFwAAB2nr1jLbWNtOhA6Ho93ljZKUmZmo008fopycFBUW1nq8p6amSfHxMXr00VXavbvSdt1Tb7A2vqq8+vRJVlKS9bUtLY6A/4bb4XDo9NPf1Lff5kuS5swZoczMBNt9v/jF+IC+LwAAHeH+NZrQC4gchF4AABwEh8OhrVtLbeP797cub2xoaF2GKLX27oqP9/0lNzXVcygmSbW1TcrI8ByySVJ9vX1JZJuPPtrh9drDD8+U1PrNfdvSxs4IvXbvrjADL0maP/972z39+qVo8uScgL4vAAAdQSN7IHKxvBEAgIOQl1etmpom23hbpZdrlZf7N9OepKXFe71WW9v6Pjk5nnc2LC+v9zj+3HPr9MAD33q8dvPNk3XuuSMkWb+5b25uaXeu/lq5sqDde448srfZtwwAgGCikT0QufhsBgCEje+/L9Gtty7RypX57d/cyVyrrlz7UC1blqdTT31DN9+8xBzr0cP78sM2viq9li07IMl7uFVR0eBx/LLLPvL6TNedI12/ue+Mvl4dCb2GD88I+PsCANAR9kb2IZoIgIBjeSMAICy09oV6S1u2lOrpp9dp9+65If1NrOvSxmnT+lmaz3/4oXVJoa8qro7cc+GF76uoqFZlZZ5DL29hmC+uoZfrN/edsYNjR0Kvyy47PODvCwBAR1DpBUQuPpsBAGFh7doibdnSGjTt31/lNQAKFtdKr8MP76mMDHtj9jYnnHBYu8/zVeklSb/5zQKVltZ5vPbEE2v0wAPLVVTkfZdGd9OnDzCPO7vSa/16ZzP9v/51mu36k0/+SGPH9gr4+wIA0BH2Si+W2wORgtALABAWPv7YWj3V1ucqVFxDr6FD032GVjNmDPB6rY3rEklvSkudQd+NNx5tHtfXN+uGGxbriis+sdzvvqvjAw9M1/Tp/XXLLZM1dWo/c9za0yvwoVdJiTOsO/fc4ZZrixfP0RVXHBHw9wQAoKPce2+yeyMQOQi9AABh4aOPdlrOQxl6VVc36NVXnTsQDh2a4XOJobcG9K5mz871eT02NkrbtzuDtokTs233fPbZLjU1tai4uFZNTS2qqWk0rw0alKrf/GaCFi36qe688zjL61xDr0BXerW0OCx/N4MGpemii0ZJkk45ZZCmTesf0PcDAMBf9uWNhF5ApCD0AgB0eQUF1Vq0aI9lLFShV2Njs448cp5lbODAVK/N5CUpOzup3eeOHt1T99wzTbm5aXr00ZM0cmSm5Xp6erwKC2sltVZwuVZqtamublT//o+pZ89/69e//p8cLvnV+vU/V2xstMf3dv3mPtC7N1ZU1Jvz6NEjTjExUZo371Rt23aF/vvfs9mxEQAQcixvBCIXoRcAoMtavvyAnnlmra6++jNbBdKBA1W66KL3NWfOeyourg3anFavLjR7i7Xp0ydZP/nJEK+vyc5uv9JLkm666Rht23alrr56vDZtKrFcawu8JGnMmCyvz8zPb+3r9dhjq82xKVP6KinJ+w6S1kovqbS0TqtXF8jhOPSqL9fea+nprc36DcNQbm46jYIBAF2CfXkjX5+ASMHujQCALmn79jIde+xLXntMXXDB+2Zj90mT+uj3v5/U6XMqKanV//63yzYeExOl+++fruXL8yRJ+/ZVWa77Cpy8ueOOqbrtti89XvvxjwcrKsrQxInZWrEiv91ntS0n9Ma10quiol7HH/+K8vNrdOaZQ3XnnVN1+OEH32Tetfl+W+gFAEBX4r68kUovIHIQYQMAuqRPP93ls6m6a5iycOHuTp9PcXGtBg9+Ujfe+IXH60OHZmjnzrnavfsqHXecc+lhbOzBfam9+upxOu00z32+LrvscEnS00+fol/8YpxmzvS+O2RsbJTmzBnp871cv7n/8st9ZrXY229v1dixz+nzz/d4e2m7XCu9fO1wCQBAqLgvb6SnFxA5CL0AAF3Oxo3FuvrqTzt8v/s3q53h2WfXeezbdcklo83jmJgoRUUZuu22Y82xV16ZfVDv16tXkl566TTb+MyZh2nQoDRJ0hFH9NJ//jNLV1wx1utzZs8e0u7OkK7f3BcV2ZeK/v3vKzo6bRtPyxsBAOhKqPQCIhfLGwEAXY63ZX3eVFc3tn/TIWpqsjd47907SXfeOdU2PmvWIH355QVqamrR8ccPOOj3jI+3N56fM2eEbaxnT++h1qWXjvZ6rY3rN/fFxXW264eyaQDLGwEAXR2VXkDkIvQCAHQ5r7++2XL+yCMnatOmEn33Xb6++mq/7f7S0nrbWKClpVkDmzPPHKo33jjD62+Dp0yx767or7g4e+g1YUK2bSw11XuYdOKJA9t9H9eGvZ42BTjssB7tPsMba6UXyxsBAF2PeyN7Kr2AyMHyRgBAl+NeuXTNNUfq4YdP9Bj4SFJZmb06KdDcq53mzz+9078pNgz780ePzrKNpaZ6X97ZkaWf7VV6+VtJ53A4tH17merqmiz/bTIyqPQCAHQ9cXHR6tOndVfkww7roZgYfkwGIgWfzQCALmfMGGewc/75zuV8iYmeC5Rdq4k6S02NM/S66aZjPFZhdbbMzASPO0F6C73GjevYrouuyzjeemuL7XpVVaMKC2v09ttbVFHR/t/1vfcu05AhT2nw4Ce1aNFec5xKLwBAV7Vgwfm6/fYp+vDDczz+0glAeGJ5IwCgy6msdFYW3XDDJPPYW7hTXh6M0Ms5p6Sk0Hz5vP76ozyOe1reOHt2ru6/f3qHnttexVpFRb1OPPFVrV1bpBNOGKAFC+Z4vbekpFZ33fW1JCkvr1p5edXmNXp6AQC6qlGjsnTbbVNCPQ0AAUboBQDociornbskui7P87YLYV1ds9dnORyOgPzG1rXSy1vFWWfz1rA+Odla/XX77VP8+sa9vYa9n3++Vw5H6/HChXtUW9uoxER7xZkkPfbYasvflStCLwAAAAQTyxsBAF2O6xI61+qurCzPy+OamlrU0uKwjb/++vfKzv6PLrnkg0Oek7XSy3Pg09nGjvW8XNG9Uqtv3xS/nuup0is7O8k8drj91W7fXu7xOc3NLXr44ZVe3ycnx795AQAAAIeC0AsA0OV4q/TKzPRc6SRJ9fX26qLzzntPhYW1euGFDVqxIu+Q5uTayD6YyxtfeOFUZWYm6LLLxujYY/t26DUjRmT69R6uuze28RawSdLWrWUex/fvr7IsZ3SVkBCjI4/s7de8AAAAgENB6AUA6FLq6prM5XFRUYZl6Z63Sq/W11mXODrcypM87Uroj1BVel100WgVFV2jZ575sc/7/vznYyVJ06f313HH9fPrPUpKam1jw4dneL1/164Kj+MFBTVeX3PssTkhaf4PAACA7oueXgCALmX9+iLzeMiQdEs/Lm89vSSpvt4aeh04YK04io8/tMDFtU9VsBvZd6Qn2V/+MlVXXTVOffok+93DbOdOe4jlK/Tat6/S47iv0Gv69AF+zQkAAAA4VIReAIAuZfXqQvN43DjrEjtflV7uyxu3b7cuwaur89xcvaNKS52VYqHq6dWeQPbM8tV0ft++Ko/j+fm+Qq/+hzwnAAAAwB8sbwQAdCmrVhWYx+PHW3tAJSXFeq3Ycq/0cm+27muHR19aWhyqqWnU+vXF5pivKqhIkZYWr379PIdonkKvt9/eop///CPzfPbsXPM4Pj5axxyTE/hJAgAAAD4QegEAupRVq7xXehmGocxMz9VerqHW5s0l+uMfP3e77n+lV3V1s0aOfFrJyQ+ZzfWzshL93h0xHKWlxetf/5opw2g9XrDgfPPad9/lq66uSZs3l+jKKz/Wa699r7POesfy+pNOGqhbb52s7Owk/e1vxysxsWtWxwEAACBysbwRANBlOBwOrV7tvdJLag2d3Pt1Sc7ljevXF2nSpBcsuy1K0iOPrNScOSP9ms/8+XnasqXUMjZ6dJbfPbPCUVpavE444TDt3n2V0tPjlZwcq9zcNG3fXq6KigYlJv7TvPfpp9fZXj9jxgCNG9dbd9xxXDCnDQAAAJio9AIAdBmbN5eqoqK1oiozM8Hj8rr2ljd+9tkuW+AlSUuW7LPswNiepqYWzZt3wDY+ZEhah58RztLSWnt69e/fQykpcTIMw2to2NLisI2NHdvLw50AAABA8BB6AQC6hCuv/FgjRz5tno8b18tjRZW3Iqu20Mu14bw7f0KvL7/c53E8Nze9w88IZ2lpcbaxOXNGdPj1UVGRXw0HAACAro3QCwAQchs2FOmpp9ZaxgYP9lxRNWZMT4/jbT27Skvrvb5PU5NDBQXVcjjslUn2e1s8jk+cmN3uayNBW6WXqyOO6GXrs+bJaafltnsPAAAA0NkIvQAAIffee9tsY717J3m89+67j/MYyHSk0uu3v12g7OxH9ZOfvNXunJqbrcFYbm6a7rvveJ1yyuB2Xxtu7rxzqnk8cGCqnnnmFMXG2peRGoahN944Q7/61ZE+n/fvf58Y8DkCAAAA/qKRPQAg5N55xx56ZWcne7y3X78eWrr0Qq1dW6SXX96kt97aIskZepWVea/0mj//e0nSf/+7XXv3Vqp//x5e721ocO4GmZOTrG3brmz/DxKmbrzxGI0d20vDh2do1Kgsn/cOGZKuhx8+UfffP12nnfamFizYbbn+ySfnauDA7tH3DAAAAF0blV4AgJDKz6/W0qX7bePZ2Z4rvSRp5MgsnXfeCKWmOvtOdaTSy1VJie/72p4nScce27dDzwxXMTFROuOMoe0GXq4SEmI0alSmbXzkSPsYAAAAEAqEXgCAkFq4cI88tdjyVYXVxnUnR2dPL2eY1atXotfXFhXV+ny2a6VXXJznHSO7u5QUe7P7fv3a/+8GAAAABAOhFwAgpLZuLbWNTZyYralT+7X7Wmvo1ayNG4u1fXu5OXbuucO9vraoqMbns10rvVzfB04pKbGW85EjM9m1EQAAAF0GoRcAIKS2bSuznP/hD5O0cOGcDoUnrmHUddct1OjRz6i2trXiq2fPRN1333Svr22v0ovQq33JydbQ68MPzwnRTAAAAAA7Qi8AQEi5VmZ9/PG5+tvfpqtHD/uyOU8SErzvxzJyZKZSUuI0c+ZhHq/v21fl89ksb2zfiBHO/l1ZWYnq1y8lhLMBAAAArLps6GUYRoxhGDcahrHFMIx6wzD2GobxD7d7DMMw/mQYxh7DMGoNw/jcMIzxHp412jCM/xmGUWMYxn7DMO4wDCO6s54FAOg410qv3Fz/dv3zVYHV1lA9Ls7zl7oPP9zh89lUerXv5JMH6d57p+m884Zr/vzZio3l7wkAAABdh/dfkYfes5JmSrpd0iZJAySNdrvnRkm3Srrhh3t+J+kzwzAOdzgceZJkGEaGpM8kbZB0hqQhkh5Ua+B3Syc9CwC6rZYWh9asKdSYMVnthiB1dU1mxVVUlKGBA1P9eq+OhF7x8Z6/1K1eXajGxmaPcywpqdXWrc4wjkovz6Kjo/THPx4T6mkAAAAAHnXJ0MswjFMkzZE0zuFwbPByT4Jag6q/OhyOR34Y+1rSTkm/kjOEulpSoqSzHQ5HhaRPDcNIlfQXwzDuczgcFYF8ViD/HgAg3BQV1Wj27Lf0zTcHNGVKXy1ZcoEMw3tvrh07nEsbDzush9+VQt4CLckZerX1+HLX0uLQ7t2VGjIk3TK+e3eFxox5RlVVjS7vQ+gFAAAAhJuuurzx/0la4C3w+sEUSamSXm0bcDgc1ZLek/Rjl/t+LOljt0DqFbWGV20djgP5LADotv70pyX65psDkqSvvtqvwkLfOyTm51ebx/379/D7/RISfFV6ZUlqrdryZvv2MtvYs8+uswReEqEXAAAAEI66auh1jKTNhmE8YhhGxQ/9s940DKOvyz0jJTVL2uL22o0/XHO9b5PrDQ6HY7ekGpf7AvksAOi2Fi/eYzmvq2v2cmersrJ68zgjI8Hv9/MVRg0a1LpU0j3AcuVaadZm50570S7LGwEAAIDw0yWXN0rqI+kySasl/VRSD0n3SXrLMIzJDofDISlDUpXD4XD/iapUUpJhGHEOh6Phh/vsv8pvvS/jh+NAPstkGMZcSXMlKTs7W4sWLfL5hw4XVVVVEfNnQfjg4y487NljDZG++OIr9evnPcz6+usi87i+vszv/8bbtpV4vfbFF59LkoqKKr3es2jRWg0fXmoZ27x5r+2+Xbu2a9Ei37s9AoHEv3kIBT7uEAp83CFU+NjrHrpq6GX88L8zHA5HsSQZhnFA0mK1Nrf/Xwjn1mEOh+MJSU9I0lFHHeWYMWNGaCcUIIsWLVKk/FkQPvi469rq6pr05z9/qdraFsv4+PFHacyYnl5ft3Llt2ptnyiNHDnQ7//GpaVbJG23jR97bF/zWY2Na72+vrk5zfaeNTW7bfeNGTNCM2aM82tuwKHg3zyEAh93CAU+7hAqfOx1D111eWOppLVtgdcPlkhqkHMHx1JJKYZhuK85yZBU80NlVtt9aR7eI+OHa4F+FgB0O888s0733bfcNt7Q4Ht544oV+eZxenq83+/rrafXCy+cah5XVTVYrv3sZ2PMY0/LG12XXLYpLa3ze24AAAAAQqurhl4b1Vrp5c6Q1FZGsElStKShbve4993aJLd8Qlc9AAAgAElEQVR+W4ZhDJCU5HJfIJ8FABHJ4XBowYLdev/9bWpdZe60bZunld9Sfb3n0GvevPW6+upP9eKLG82x1NQ4v+fkvntjenq8amquVW6uc0fGCROyzeOjjsrW3XcfZ56vXVskd5WVDbaxWbMG+T03AAAAAKHVVUOv/0oaaxiG65qY4yXFqrXPlyR9JalC0nltNxiGkSTpdEkfurzuQ0knG4bhui3YHEm1al0uGehnAUBEWrBgt0488VXNnv2WnnlmneVadbXnZvGeQq8NG4p06aUf6vHHV1vGD6ZZvHsj+2uvnaDExFjL2NNPn6y0tHilpcXrpZdmKycnxbxWV9ekF1+0bhRcUeEMva66qr/efvtMS3AGAAAAIDx01dDrCUnFkt4zDON0wzAulDRP0mcOh2OJJDkcjjpJ90r6k2EY1xiGcaKk19T6Z3rY5VmPSaqX9KZhGCf90Fz+L5L+7nA4KgL9LACIRFVVDTrppNfM88sv/1j19U3mubfQy9Pyxpdf9lwYO2vWQL/nFRNj/TJ2ySVjbPccfngv7dt3lfLyfqFhwzIUFWUtJL7zzqXmcX19kznnmJgozZmTrTPOcC8CBgAAABAOumQje4fDUWEYxkxJ/5L0ilp7eb0j6Tq3W+9VazB1k6QsSd9KmuVwOPJdnlX6Q4j1iKT31Lr74j/UGlZ11rMAIKI8+ugq29gbb2zRhReOktSxSq833tisG25Y7LGP1gknDNDIkVl+z2vYsHTFxUWroaFZM2YM0JAh6R7vS062Lp3MyUnWgQPVkqQtW5wtGV2XNqamxskwPK20BwAAABAOumToJUkOh2OrpFPbucch6e4f/ufrvg1q3fUxKM8CgEizaNEe29jatYWSWkOvmhpn6BUfH22GXa6VXued967cWoGZLr54tOcL7cjMTNSHH56jzz/fo6uu6vjuio8//iP95CdvSZLGj+9tjrsubezRw/8eYwAAAAC6ji4begEAuo6iolrbWFvFlsPhUHm5MyzKzEwwq6hcK728BV6SNHJk5kHPbebMwzRz5mF+vWb48AzzuKKi3uXYWukFAAAAIHx11Z5eAIAuoqGhWatXF9rGt28vV0NDs6ZNe0Vff73fHM/ISDCPL7zwfS1cuFvV1fYdEV0dSuh1MFwDLdeg67PPdrncEx/UOQEAAAAILEIvAIBP69cXedyFcceOcn3yyU59+eU+y7hr6CVJf/rTF8rPr/H6/KgoQ5mZiYGZbAe5hl4FBTUqK6uTJL311hZz/KST/KseAwAAANC1EHoBAHy6/favzeOzzx6muLhoSa1LHhcvtvf6ysiwVkgtXXrAZ+jVt29KgGbacUlJsZbzk056TVVVDVq2LM8c++Uvxwd7WgAAAAACiNALAOBVQ0Oz3nlnq3l+9NF9NGhQqnn+xhtbbK9xr/SSpPz8aq/vMXt27iHO0n/uuzKuWJGvDz/coaamFknS2LE91bt3ctDnBQAAACBwCL3Q7d133zJNmfKSpZcPgFZty/7azJkzUrm5aeZ5WzN7V+5LIRMTY5SX5zn0mjatv/785ykBmKn/hg3LsJw//fRa83jGjAHBng4AAACAACP0Qre2dWup/vjHz/X11/s1a9ZroZ4O0OVUVzeax6mpcRo0KE2DB6f5eIVUWWltWl9b26R7713m8d7Fi+eoT5/QVFTdf/90y/lHH+00j084gX5eAAAAQLgj9EK3tnZtUainAHRprqFX//49JKndpvNXXz3ONrZrV4XlPDra0P33T7ctMwymM84Yqt/8ZoLHa8cf3z/IswEAAAAQaIRe6NYaG63LsBwOR4hmAnQtX321T6NHP62xY58zx5KTW5u/uy5vdPf222dq9uwheuONn3i9Z/782aqs/I1+//tJgZvwQfL0Z0lLi1dWVnB3kwQAAAAQeIRe6NYqKxst53V1TSGaCdB1NDW1aM6c/2rjxhLLeFvV109/OtL2mkcfPUm7d8/VGWcMVVSUobPPHq6YGM9fYvr376HExFiP14JtyJB02xj/DgAAAACRISbUEwBCqbCwxnJeXt7QZX4YB0Jh48ZilZXVa+/eStu1mprW0CspKVaNjb/Tffct04YNxZo4MVtz545TVJR1qWLbTojuRozIDPzED5KnSi/3RvwAAAAAwhOhF7q1/Hxr6PXoo6sUHx+thQv36KSTDtMf/3hMiGYGBN9TT63RlVd+4vV6ba2zAiomJkp/+tNkv98jMzOhSy0dbK8pPwAAAIDwReiFbm3NmkLL+R13fG0ef/bZLp188mCNH9872NMCQuIPf/jc53XX0OtgTZ8+4JCfEUieKjvHjesVgpkAAAAACDR6eqHbamlxaMWKfJ/3fPzxjiDNBgiNzz/foyFDntSPf/y6SkvrfN5bV3foy/7+9rfjD/kZne3JJ38U6ikAAAAACABCL3Rb27aVqby83uc9xcW+QwAg3N1111Jt316ujz7a2e69DQ2HFno98MB0DRuWcUjP6AzPP/9jGUZrg/2ioms0aVJOqKcEAAAAIAAIvdBtLV+e1+49W7eWBWEmQGgsXLhbn366y+c9U6b0NY+feurkg36vYcMydP31kw769Z3pkkvG6MCBX2j79iu6VL8xAAAAAIeG0Avdyptvbtb48c/pwQeX69tvnaHX8OEZuvLKI2z3b9hQHMzpAUFTV9ekmTNfbfe+a6+doH/84wQ98MB0XXzxKL/e45ZbWhvdZ2Qk6IsvfnpQ8wyW7OxkxcZGh3oaAAAAAAKIRvboVs45511J0urVizVoUKo5/sADMzR7dq6efHKN5f6tW0tVX9+k+Hg+VRBZlizZ16H7evZM0vnnjzyo97j99qmaPn2Ahg1LV3Z28kE9AwAAAAAOFpVe6LZ27qwwj486KluGYdjuaW52aPPm0mBOCwiKJUv2Ws4XL56j7767RBdfPNoynp4ef9DvERVl6KSTBmrgwLSDfgYAAAAAHCxCL3Qb9fVNHsf79UtRTk6KJLHEEd3GypUF5vFDD83U8ccP0JFHZuv++6db7juU0AsAAAAAQonQC92Gt50ax4/vbR7feutkXXKJtdLl++9LOnVeQCi4hl4nnDDAPO7Vy9rIPTU1LmhzAgAAAIBAIvRCt1Fe3uBxvHfvJPN4wIBUPf/8qXrooZnmWH5+TafPDQim4uJa7dlTKUmKj4/WyJGZ5rXo6CidccZQSdLkyTnsZggAAAAgbNGdG91GRYXnSi9Py7dcg7D8/OpOmxMQCqtWOau8xo7tadu18NVXT9fXX+/X0Uf38djrDgAAAADCAaEXug1vlV4ZGQm2sexsZ+hVUFDbaXMCQsF1aeORR2bbrsfFRWv69AG2cQAAAAAIJyxvRLfhradXWpq90ss19KLSC5Fm6dL95vH48b1COBMAAAAA6DyEXug2vIVeDofDNmZd3khPL0SOwsIavf32VvP86KNzQjgbAAAAAOg8hF7oNryFXlVVjbaxzMxERUcb5uvq65s6dW5AsGzZUqrm5tagd+jQdE2caF/eCAAAAACRgNAL3Yan0MswpAsuGGkbj4oy1KuXs9pr0aI9nTo3IFhKS+vM46FD02lUDwAAACBi0cgeEc3hcOi77/I1bFiGJfS6/vqjFB8frQkTspWbm+7xtXl5zl5eP/vZh8rL+2WnzxfobKWlzs8DT5s4AAAAAECkIPRCRLv55iX661+/0aBBqZo8ua85Pnx4hubOHdfh59DXC5HCtdKL0AsAAABAJGN5IyLaX//6jSRp584KvfLKJnM8NdW+Y6O7888f0WnzAkKlrMxZ6ZWe3v7nAQAAAACEK0IvdEtpaXHt3nPPPdMs52PHPqsdO8o6a0pAUFDpBQAAAKC7IPRCt5Se3v4P+0OGpCslJdY8X7euSM8/v6Ezp4UI9/e/f6u+fR/Vvfd+E7I5FBbWmseEXgAAAAAiGaEXIlZ1dYPXa4MGpXboGVVVjZbzzZtLJUklJbWebpfD4VB+frXHa+jeHA6Hrr9+kQ4cqNZNN32h/furQjKPTZuKzeMhQ9JCMgcAAAAACAZCL0Sk++9fppSUf3m8lpgYoz59kjv0nNNOy7Wcv/TSRp1xxlvKyvq3rrnmM9v9Z531jvr0eVQ33LDI7zkjstXWNlnO33tvW9Dn0NLi0IYNztBrzJieQZ8DAAAAAAQLoRciTlNTi2677Suv13Nz02QYRoeede+90xQVZb333Xdbw4r//GeVGhubzfEDB6r0zjtbJUkPPPCtGhqaNW/een388Q5//wiIQNXV1qrBjRuLvdzZebZsKVVNTWv41rt3knr1Sgr6HAAAAAAgWGJCPQEg0HbvrlBdXZPX67m56R1+1uGH99KCBedrxoz5Hq8XF9dp5cp8JSTEqF+/FMu18eOf08aNJZKkL7+8QFOm9Ovw+yLyuIdeW7cGf1OE5cvzzOOjjsoO+vsDAAAAQDBR6YWI0tTUooce+s7nPUOGdDz0kqS0tHiv1/7975U69dQ3NXPmq5o//3vLtbbAS5Lmzv3Er/dE5CgpqVVhYY2qqqw95lasyFd9vfdwtjO4hl6TJvUJ6nsDAAAAQLAReiGi/OUvX+lf//IdeuXm+te8Oy0tzuu1u+5aah7fdtuXXu8LRVUPQm/dukINHPiEBgx4XK+8Yg1F8/Kq9eyz64M6H0IvAAAAAN0JoRciRl1dkx55ZKVl7JVXZqul5XpddtkYSVJMTJROOWWwX8/t0cN76NVR9fXN7d+EiPPee9tVVdWo+vpm3X33Utv1e+5ZqqamlqDMpbGxWStXFpjnhF4AAAAAIh2hFyLGO+9sVXl5vXl+7LF9ddZZw2QYhp5++hR99tl5Wr36Ug0bluHXc7OyEjVmTNYhz6+2trH9mxBR9u+v8nl99+5KbdoUnIb269cXm73uDjush3r37tgOpgAAAAAQrgi9EDGefXadeXzttRO0ZMkFiouLliQZhqETTxyo0aN7+v1cwzD05ZcXHvL8Nm0qsZzv2lWu3/zmf3rjjc2H/Gx0PQsX7rZVHnpSUdGgxsbWSrC77vra5yYMh4KljQAAAAC6G0IvRIR9+yr1ySe7zPPrrpuoqCgjYM9PS4tXerr3hvbu+vfvYRubMGGeli8/IElyOBw655x39fDDK3Xuue9qzZrCgM0VoffrX/9PM2e+2qF7q6sbde21C3TLLUt0661f6sUXN3bKnAi9AAAAAHQ3hF6ICO+9t00tLQ5J0syZh2ngQP+a1XeEP7295s+f7XF89uy35HA49OWX+7RiRb45Pm7cc+b8Ed7Kyuo6VOHVZs2aQj366Grz/Be/+LQzpqW1a53B6lFHEXoBAAAAiHyEXogIrr2Tpk7t2ynvkZgY4/N6WlprJdg775ypKVP66dVXT7fdU1BQo7Kyer32mn1JY35+dWAmipBy7SvXEQ888K3lvFevpEBOx1RW5pxXTg79vAAAAABEPt8/xQNhoqSkzjzOykrslPfYvLnU5/UdO65Ujx5xiolpzZLPO2+E6uuHKj7+H5b79u+v8tjHq6ioVjk5KYGbMEKiutq/DQsaGqw7e/bs2Tkfv5WVDeZxIHYkBQAAAICujkovRITi4s4PvU47Ldc8njv3CP3sZ2PM8+HDM5SeHm8GXm3i4qJ1441HW8beemuL9u2z7+pXVFQb4BkjFCor/Qu9XANbScrODmylV1NTix58cLnlY47QCwAAAEB3QKUXIoJrcJCZmdAp7/GHP0zStm1lOvLI3vrXv2YqNjZa06b1165d5fr5zw+XYXhunH/jjcfo3nuXmedPPbXW432EXpHBtaJKkk44YYBKS+u1alWBOZadnaT8/BqPr09ICOw/y3fc8ZXuvHOpZSwlhdALAAAAQOQj9EJEKC52BkadVel1/PEDtHHj/7OMXX752HZfl5YWrxtvPNoMvnbtqjCvJSTEqK6uSRKhV6RwD70Mw9Do0VmW0MvhY88Cf5dH+lJYWGMLvBITY2wViQAAAAAQifjJBxEhGJVeh8J1KaSrKVOcTff37KkM1nTQidxDr7/+dZpGjcq0jPkKOGtqAhd6PfDActsYSxsBAAAAdBeEXgg7DodDjY3W5t+uQUNaWtf7oX7kyCxNm9bfNn7OOcPM46+/3h/MKaGTuH4s9u6dpKOPztHo0VmWe66//iivr6+paQrYXN5/f7ttjNALAAAAQHdB6IUuY9WqAn37bV6791166YeKi/uHxo9/Tjff/IWamlosQUNX7Vf04IPTbWNnnDHUPP7mmwO2MA/hp6rK+bF46aWjJckWep155lB5E8hKL099wwi9AAAAAHQXhF7oEr74Yq+OPPJ5TZr0gv7wh8VyeGl6VFxcqxde2CBJWr26UPfc841ych5VfX1rWBQVZSgxsWu2qps0Kcc21q9fDw0enCZJqq1t0sqVBbZ7EF5ce3IlJ8dKkoYMSbfcYxiGzj13uMfXb91apltvXXLI82hubrH0umszdGi6h7sBAAAAIPIQeqFL+OAD5zKs++9frk8+2enxPtfeXW1c+yOlpMR63UWxK5gzZ4RtbOrUfubxkiX7gjkddIK6Ome1XlsAGxsbrdzc1nAzPj5ao0ZlKj093usz7rprqdatK/R6vaSkVg89tEJLl3peEutwOFRSUuexYb6vpZUAAAAAEEkIvdAlHDhQbTl/+eVNHu97771tPp/T1Zdu3XnncYqNbf20e+utMyRJxx3nDL0WL94TknkhcNp245Rad+ds8+67Z2nu3CM0f/7pSk9PaHeXUdddPt39/veL9dvfLtSJJ76qggLn505TU4t+/OPXNWDA43r99c2W10yf3l9vvPETTZ7c1/1xAAAAABCRuuY6MHQ77qHXu+9uU21toxITYy3j11+/yOdzunroNWxYhnbtmquKigaNGNG6o9/06c4G9x98sEP5+dXKzk4O1RRxiFwrvVxDrzFjeurxx39knl988Sj97W/LvD6nrKze67VnnlknqbXp/XPPrdcNNxwtSXr22XX66KOdkqRf/vIz8/4pU/pq0aKf+vcHAQAAAIAwR6UXQuq225YoJeUh23LG0tI6JSU9pDVrvC/x8iQlJbb9m0IsJyfFDLyk1p0dJ0zIltRaqbN6tX9/ZgSPw+Gw9Jt7552tmjv3E61fX2SOWSu9or0+6/DDe+nCC0dZxvr372Eel5d7D71clZY671uxIt/jPX37pnToWQAAAAAQSQi9EDIrV+brzjuXWhp/u7vpps/N44aG9nc23Ly5NCBzC7ZRo5wh2P79VSGcCXy55prPFBPzd9100+datuyAzjzzbT355BrNnfuJeY+35Y2ezJo10HLeu3eSeeyr0stVWZmzz52X/R8sYRoAAAAAdBcsb0TI/P3vK2xjOTnJlqWOH3ywwzz2FY61GTgwNTCTC7J+/ZyVOPv2EXp1RW+9tUWPPrpakvS3vy3TggW7zWtffeVsKO9teaMn06b1t5z37Ons89XRSq/y8oZ27+nfn0ovAAAAAN0PlV4IiX37KvXKK85m9TfcMElbtlyunTvnWu4bOjTdPO5I6HX33dMCN8kgcl1+tn9/lerqmvTLX36qSy/9wFLJg9D4v/9bq7PPfsc8dzikZcvyPN7b0eWNkswdHdv06OFcnustzKqvb7Kcu1ZALlmy1+Nr+vWj0gsAAABA90PohZB45JGVampqkdRa7XLffdM1dGiG4uKiddFFzj5Hrsu93EOvnBxrs/eBA1N1+ulDOnHWnadPH+efJT+/Wm+8sVmPPrpa8+Zt0LXXLgjhzCBJTzyxut17Wlpa1xb6U+llGIbuuGOqJGnw4DTLx29JSa3H11RWWsOw2trWEKy0tE7r1xd7fE1WVkI7swcAAACAyEPohaCrrm7QY485Q4Trrz/Kcv2mm44xj0tK6lxeZw29LrhgpOXctTl8uElNde46WVnZqP/8Z5V5/vzzG0IxJbjwVtXlKi+vdVmuPz29JOmWWyZr48afa926yzRkiLOy0VOA9dxz69S//+OWsbb3c98MwlVaWny78wAAAACASEPohaD77rsCs0n34MFpmj0713I9I8NZleIt9Jo6tZ9SU60/yA8fntEZ0w0K1z9LZWWDLcCrqmq/bxM6T9vumr787ncLJfm3vFFqrfYaOTJLSUmxOvLI3oqKMiRJGzcW26q6fv/7xaqvt27o0Fbp1fb/nhB6AQAAAOiOCL0QdK670o0enaXoaOuHYWamM/QqKKjRrl3lkqzBT3JyrHr1SrS8LpxDrx49nJVeFRX2Bua/+90iS5iC4GpsbH/n0Pnzv9fq1QVau7bIHOtIpZer5OQ48+PY4ZC2bHHuRlpb26iiIvuSx7awq6CgxutzCb0AAAAAdEeEXgg61/AqJSXWdj0hIUZTp/Yzz996a6ska6VXcnKsbafGcF7e6NrAvKCgRs88s85y/ckn1+i2274M9rTwg8bGlg7dN3nyS5bzjlR6uXPdvGHbtjLzuLTU826ObaHXzp3lXp+Zlhbn9RoAAAAARCpCLwRdVZUzvHKtcHJ11llDzeNNm0ok2UOvww6zhl7hXOnluryxsNBzA/P7718erOnATdumC+1xr8bzt9JLkqWvl2voVVzs+eOi7T2XL/fcdyw2Nuqg5gEAAAAA4Y7QCwdl8eI9mj79FT34oP9BjGufopQUz6HXyJHOqq3NmzsWermfhxNv4Z87bzv6oXN1tNLL1eDBaerZM7H9G914C71c+9u53lNb26Ta2katWlXo8XlpafEyDMPveQAAAABAuCP0wkGZMWO+Pv98r37/+8Vmz62Oam95o2RdqrhmTZEcDodb6BWjtLR4/eUvU5SdnaR//Wum2QA8HMXFRSsurv2lcHv3VgVhNnB3MKHX55//1NavriM6Enr165diHtfWNmnlygKv1Wjp6fTzAgAAANA9EXrBbw6Hw3K+bZu/oVf7yxtzc9PNH9aLi2u1fXu5rdJLkv785ynKy/ulfv3rCX7NoStKTfX8d5GY6Fya5muHPgSWw+HQW29t0SOPfOd198zf/W6isrOTbOPnnz9C/fv3OKj3de3ptXWr5+WNrqFXRUWDZs16zevzsrL8rzYDAAAAgEhA6AW/lZVZgxf3lVMNDc22YMyVdXmj50qvqChDxxyTY55/880Bj6FXJOnd2x6e3HPPNMvfg+vfATrXE0+s0dlnv6Nf/3qBKio8h14TJmTrpJMG2sYPpoF9m0GD0syqvz17KnXLLUu0b1+lpdIrJyfZ8pqaGufn5FlnDbNcy8pKEAAAAAB0R4Re8FtBgTUAcA2xXnhhg9LSHtbMma+qudm63MrhcGjlynw99thqc8xbTy9J3S70cq3eaXPssTlKSnJWej3//HrL33dnqKpq0DffHLD99+tufv/7RR7H23YWzchI0CmnDLYFUNLBNbBvExcXrfPOG26e3333Uh199IvavbvCHPNVvfXLX463nLtukgAAAAAA3QmhF/xWUmKtNnINYS655APV1TVp0aI9+uKLveb43LmfKCvr35owYZ7ltd4qvSRr6LV06f6ID7369rWHXpmZiUpKcv5Zn3tuvS655INOm0NjY7OmTn1Zkye/qCuu+LjT3qer+/zzPZZluK4+/vgcrVhxibZsuVxZWYnKybH/d3NdknowrrtuouV8//4qvf76ZvM8MzPB47LK/v17aMaMAZaxvLzqQ5oLAAAAAIQrQi/4rb7eWgHUtvTLtRJFkvLyaiRJGzYU6ckn16i0tE7ufO1aePTRfczjVasKLcu7ukvolZERb/uzvvPOVtXWds4yx4UL92jNmtZdAJ99dr3PZaqR6skn12jGjPler8fHx2jChGyz2irQlV6SNHFiHx1/fH/LWH5+jXmclZVoC8Yk6bTTchUTY/1nvaM7gwIAAABApCH0gt/q6qyhV3FxrS666H0NHfqUZby8vF6StHp1oddn+Vre2LNnkgYNSpXU2ids7doi81okhl7jxvWyjWVkJFiWN7ZZtcr73+mhcK3Ok5z/DbuLb745oLlzP5GvrC862trEznPodfA9vdq88MKpHvu8Sa2VXn/84zF65JETLeMDB7Z+vrz++k/MsZtvnnzIcwEAAACAcEToBb+5V3o98shKvfTSRjU2Wsfz81uXVa1fX+z1Wb6WN0pSdrYzUNi1y1lJFomh16mn5trGkpNjLcsb22zdWtopc/j0012W8z17Kjvlfbqq777L93k9JiZKhtvODX362EOvQ13eKEkDBqRq584rPT4rM7O1OX1amrVf12GHte4YefbZw/TVVxdq1apLLcuEAQAAAKA7IfSC39wrvVyXXbnav7/6h+veewq1t/TK/Yf6NpEYevXoEacpU/paxgzD8FjpVVhY2ylzWLmywHLuvmQ10tXXN/u8Hhtr/yfTU0+vQ13e2CYxMVb/+tdMr++Zmmr9/Gmr9DIMQ8ce21fjxvUOyDwAAAAAIBwResEvdXVNWreuqkP3Pv74al155cdmzy9P2qv08rSDYEpKrEaPzurQHMLNT3860jbmKeAqLPQcNPpSWlqnl1/e6LVKrL6+SQ0N1tBn9+7uVelVX9/k87qn0Ms9eJICF3pJ0hVXHKFLLhltGWtb9ui+1JKQCwAAAACcCL3QYX/4w2IlJz+kJUvKOvyap55aqzff3OL1uq+eXpLnypsHH5yh5OTIbM59xRVjNXZsT0nSHXdMlSTbslFJKijwL/RyOByaPv0VXXjh+xox4mlt327/b+hpt0Iqvayio+3/ZBqGoTPOGGoZC0RPL1fuvb2iolrDrmHDMizjNK0HAAAAACdCL3RYz56Jamnxfze/piZnaNMW6LSJj/cdDtTVWStv5swZoSuvPMLvOYSLxMRYffvtJdq+/QrdeuuxkqRf/epI233+Lm/Mz68xNwJoaXFo0aI9tnsqK+0VeYGo9Nq/v0off7zD8nHQVbmGXjk5ybrwwlGW6952s7z66nGW80Avvx0yJN3j+PDhmbrllsk65pgcLV48J6DvCQAAAADhjl5StiAAACAASURBVNALHeYeWB2MI46w7lDo3hTcnfv1l1+e3e5rwl1cXLQGD3aGHOPH99a3316s22+fYo7t3etfGFVVZQ20qqvtVV3u90iHVulVUlKr559fr379HtMpp7yha6757KCfFSyuoddvfztRL754muW6t+DOvffcoEFpAZ3XZZeNUW5umgxD/7+9O4+TqywTPf570kkn3UlnJyFkIYQQCZvssoR1kGWIMCgIgsrVC6hchhnA0UHcWdSL+zIOKA7ioAIOLqAom7kDIoyACsqWiAhJWAIkZN/f+8eprlR1V6c7obpPVfXv+/mcD3XWekufnDr91PO+L9/61tFl+y69dBb3338Ghx46uarvKUmSJEn1zqSXemz33bfp/qCCbbZpqbj9+OM7z1C4OVdeeVjx9de+dmTDJ7y6ss8+2/KBD+xZXH/qqcVdVh1V0rHrYqWujMuWdd7W3eyNN974BFOnXs0ll9zDqlWbzn/ppRVMnfotzjzztuK2q69+pMftzUtp0qtSFeL69ZX/N+84rldXlVlbq6VlEE888V7mz38/Z53VuJWOkiRJklRNJr3UYxMnDutyNsWOJk1qq7h9//0ncMklB7DjjiP54Q9nd3udQw+dxE03vYWrrz66obs19sTYsS2MGjUEyCq1Fizo2YQC0LnrYk8rvebPX1ZxMgGAJ598lVNPvZW//W0pV1zxAN/85h+L+371q2cqdpesdd0nvSr/bzF69JCy9fb/n6pp0KAmttuu80yRkiRJkqTKTHqpxyKiUxfHSjPXQZYgq2To0EFcdtks5s07i1NP7TxTYaX3PPnkbByvwYOrNyNePYoIZszYNHB5x8HoO868WKpjQqtSgqtSkmrDhsTzz69g48bEj370JN///uPFCrPvf//xsmMvumhO8XWlMcdGjuxZwjRPpbM3bknSa8KEYfzjP+7F8OHNfOMbf9dr7ZMkSZIk9ZxJL22R3XYrT3q9+c3bVzxul13GVNw+bFh1B/jub6ZM2VRBV9r18Kc/ncfYsd/gkEN+UDEx05NKr9deW1PxPZ99dim/+MXTnHLKLZxxxs/59rcfBbKxx7qyaFHn2SVXrVpf4cjaUlrpNWRIlmTtaY/ar37171i8+B8599zOEw9IkiRJkvqeSS9tkZkzy5NZe+45rtMxO+00ijPO2KXi+a2tJr1ej8mTNyW9nn76tWLXw3/4h5+wbNla7r13Ad/5zqOdzuvJmF6//nXnGR0hm8Hxqqs2dV0855zbAXj55fJqrrFjN43jVqnSa82aDV12lawVlbo3bsHQaQwY0D/HnJMkSZKkWmTSS1uktNII4Jxz9ihWbx1xxGQ+/vED+eUv31ZxpsdJk9pMCrxOkycPL77++Md/w667XtupQus3v1nATTc9yR/+8FJxW8ckV8dKrzVr1vOTn8wrrh900HbF15/85H3ceuvTZcc/9NALLFhQPsj9tGmbZiysVOkFsHJlbVd7dTemV1fdeSVJkiRJtad/D5KkLXbMMVPZZptBLFq0jjPP3JVx44by0EPv4rHHXuG443YoG3frAx94Y9ng5rNmTcyjyQ1lv/22LVt/8slXufbaP5Vtu+66x7juuscYNGgATz99NpMmtfHYY6+UHdMx6TVnznPFLpDTpo3grW/difvuW1h8j46++MWHWLhwRdm20i6UTz21uGL7V6xYR1tb7SaOypNenW+PPZ3IQZIkSZKUP5Ne2iItLYP45jdnMnjwjhx1VDae14wZo5kxY3SnYzvOYHfwwdt1OkZb5qCDtuO443bgttv+Wtw2b96SiseuW7eRz3/+d3zpS0dw881Ple1bvHh12frPfvaX4usTTpje5eyb7W688clOY10tW7aOhQuXs3LlOp54IkuUtbQMpK2tmZdeyiq//vjHl9h22x02/yFzZKWXJEmSJDUOuzdqi40Z08zs2TsWB/ruSsek16xZk3qzWf1CRPDVrx5Ztm3UqK6rj1asWMczz7zWaYytRx99uTiDY0qpLOl14ok7Mn5862bbsX79RtatKx+fa/78ZUyc+O/stNM1xW0HHrhdMeEF8OEP//dmr5u37mZvrJTclSRJkiTVJpNe6jUdx5qqNM6Xttz06aM47bSdi+uLF1eedRGyQdgffvilTtvXr9/IvfcuALLZGefPz8bnGjFiMAcfPJHx44dWpa0zZowqW//jHxdV5bq9pVKl1w03zC6uf/nLR+TSLkmSJEnSljPppV5TOrPj0KGDaGoy3Krl2GOnFl8vXryalpbKVXfXXPMoJ5/8s4r7fv3rZ4HyQe63224ogwY1MW5ceaXXzJmjaW5u4tBDt6xab6edRnV/UA2plPR6+9t35s9//l88++w5TJkyvKtTJUmSJEk1xiyEes0JJ+zI7NnTmD59JHff/fa8m9NQRo9uKb6+/vrHWbWqZ7Minn76zOLru+/Okl6l57a0ZDNxduyaevPNJ7Js2fnMmXPqFg3mfsABEzjrrN2L6xMmVKeCrLd0NabXLruMZdy42m67JEmSJKmcSS/1mkGDmrjllrcyd+5Z7L//hLyb01A2N47X5lxwwT4MGJCNQP/wwy+xdOmaDkmvrGJswIDgyCOnADB9+kimTx9Fc3MTEcHEicN69F6HHz6ZAw/cjo985E3Fbc3NTaSUiuOJ1ZruZm+UJEmSJNUPk15SHdprr3HdH1TB3nuPZ7fdsrHVNm5MPProy6xevSnpNWTIpuqmG26YzXe+cwx33fV2Bg7cdKtoayufwXD//bet+F6XXz6LiGDo0EHFbYsXr2avva5j7NhvcOONT2zVZ+hN3c3eKEmSJEmqHya9pDo0dGgzRxwxudvjjj9+WvH10UdPZcCAKJtQ4JFHFlWs9AIYO7aV97xn907jWHVMep188oxO73vppQdz0EETARg2bNPxS5eu5Y9/XMSaNRs49dRbu21/X+tu9kZJkiRJUv0w6SXVqZ13Hr3Z/SNGDOaWW07i0ksPZvbsaVx55WEA7LLLmOIxTz+9pEOlV/dd+oYPL096veENo8uqubbffjgf/eiBxfWWloFEVL7W9Onf5phjfsTatRsqH9DHrPSSJEmSpMZh0kuqUyNHDtns/kGDBhARfPSjB3LLLW9ljz22AWDs2E2D4C9ZUnlMr83pWOk1ceIwPvWpg4rrxx67Q9n+jl0cS/3lL0u4/fZn+MIXHuz2fXvbhg0b2bAhARBBWZdOSZIkSVL9caRmqU6NHLn5weybmiqXV5WeV52kVxsXXrgvu+46lhdeWMFpp+3c6Zxhw5pZvnxdl9f8yU/mcvHFb+pyf1/oOIh9dFWeJkmSJEmqCya9pDrVfdKrcqVSaYXYkiVrWL16U7KnJ90bV64sT16NG9dKRHSq8Co1evQQXnhhRZf7Fy7sel9fsWujJEmSJDUW++9IdWrUqM13b+xZpdfqLa706pi8GjCg+4qo/farPMNju4ULl3d7jd5m0kuSJEmSGotJL6lOdZxVsaOedm8sHci+J0mvc8/ds/j6s589pNvjAQ46aLvN7t+4MfXoOr3JmRslSZIkqbHYvVGqU1Onbj7p9eEP719xe2nSa968JSxbtra4PmRI98me446bxlVXvZmlS9dy/vl796itBx88sdtjfvzjuTz44Auce+6eTJzY1qPrVpOVXpIkSZLUWEx6SXVq3LhWhgwZWFapdfLJMxg/vpXhwwdz1ll7VDxv1KghNDc3sXZtluT5t3/7Q3FfV7MslhowIDjnnDduUVtnzhzDyJGDWbJkTZfHvPWtPwVg7tzF3HjjCVt0/Wow6SVJkiRJjcXujVKdiohO1V4TJgzl618/iiuuOISBAyv/8x40qInZs6cV10uTPW9847heaeuAAdFtF8d2N930VK+0oTsdZ2+UJEmSJNU3k15SHeuY9Gpt7b5SC+D446d12hYB++47virtqmT27B177drVYKWXJEmSJDUWk15SHZs6dUTZek8Goq90HsDIkUNoaelZ0mxrnH125e6WtaJ0FsuejG0mSZIkSaptJr2kOtax0qunSa/p00d22lY6wH1vGDhwAL/5zTvYccfO712qtTWfroWLF68uvh45ckgubZAkSZIkVY9JL6mOdazY6mnCaPLkNkaPLk/sjBjRu0kvgIMOmsi8eWdxxx2nlG2P2PR65cr1bNyYer0tHb3yyqri6zFjTHpJkiRJUr0z6SXVsY5Jr1GjepasiQj22ad8/K7ervQq1TE5t2DB+8vWV61a12dtaffKK5sqvcaMaenz95ckSZIkVZdJL6mOdezeeOihk3p87t5755f02nffbdluu2EAHHPMVCZMGMbYsZsSTStW5JH0stJLkiRJkhqJSS+pjo0b18oBB0wA4NhjpzJ58vBuztgkz0qv5uYm7rzzFL7ylSO59trjABg6dNMg+nPnLuG119b0WXugY9LLSi9JkiRJqnf5jBgtqSoigrvuejv/8z/Ps//+E7bo3I6VXqWVVn1h5swxzJw5prhemvSaNesHtLQM5NvfPobTT5/ZJ+159dVN3Rs7jncmSZIkSao/VnpJda61dRCHHz6F1tZB3R9cYtq08vHADjtscjWbtcVKk14Aq1at54wzfs5nPvMAKfX+wPbLl2/qUtnW1tzr7ydJkiRJ6l0mvaR+KiK45JIDADjwwO049tgdcm3PhAlDK27/yEfu4eqrH+n19y8dR6xjAk6SJEmSVH9Mekn92GWXzWLBgvdz773vYODAfG8Hs2ZN7HLfpz/9216v9jLpJUmSJEmNxTG9pH6ufRbFvG2ue+XChct54YW1vfr+Jr0kSZIkqbFY6SWpJuy117hO2448ckrx9dy5K6v+nosWreT2259h3boNJr0kSZIkqcFY6SWpJgwa1NRp2957j+Puu58F4PHHV1T1/VavXs/ee3+P+fOX8b73vdGklyRJkiQ1GCu9JNWMT3ziwOLriy7al4MP3jTO16OPLqvqe91++zPMn59d86qr/siqVeuL+7Z0JkxJkiRJUu2x0ktSzbjoov34/e9fYtWq9XzoQ/sxYEAU9z355EpWrVpHS0t1ElJLlqypuL21dWDZ+0qSJEmS6pNJL0k1o62tmZ/+9KSybTNnjubxx19l/frEAw88z+GHT+ni7C2zbFnlgfHt2ihJkiRJjcHujZJq2iGHTCq+vueeBVW77vPPVx4jrK2tuWrvIUmSJEnKj0kvSTWtNOn1ne88ysaNqSrXXbhwecXtO+wwoirXlyRJkiTly6SXpJp2yCGbBrN/5pmlHH/8f1Xlul0lvXbaaVRVri9JkiRJypdJL0k1bfvtRzBixODi+i9/+QxLlqx+3dc16SVJkiRJjc2kl6Sa19paPufGiy+ufN3XXLCgctJr+vSRr/vakiRJkqT8mfSSVPM+/vEDy9ZffLHyIPQ9tXr1el59tXK1mJVekiRJktQYTHpJqnnvfe/uZesvvfT6Kr2ef75ylRfAtGkOZC9JkiRJjcCkl6Sa19zcxOzZY4vrr7d740MPvdjlvsGDB3a5T5IkSZJUP0x6SaoLI0cOKr5+5ZVVW32d559fzimn3FKNJkmSJEmSaphJL0l1obV10+1q2bK1W32dn/xkXpf73va2nbb6upIkSZKk2mLSS1JdGDq0qfh66dKtT3otX15+7ne/exyzZk1kt93G8tnPHrrV15UkSZIk1RYHr5FUF1paqpP0Kq0Sa2tr5l3v2oV3v3vX19U2SZIkSVLtsdJLUl0orfR6Pd0bX3lldfH1ZZfNIiJeV7skSZIkSbXJpJekutDauuWVXikl/vrXJWzcmIrbXn550yD4Y8e2VK+BkiRJkqSaYtJLUl0oHch+6dI1PTrn7LNvZ9q0b3PCCT8mpSzxVTrz45gxQ6rbSEmSJElSzTDpJakulHZvfPbZZcUkVlcWL17NNdc8CsDPf/40c+cuBsq7N44ZY6WXJEmSJDWqukh6RcTEiFgeESkihpVsj4j4SEQ8FxGrIuK/I2LPCufvEhF3RcTKiFgYEZ+OiKYOx1TtWpKqb/ToQTQ3Z//UFi9ezZ13/q3LY++44xm22eYbZdvOO+8uFi1aaaWXJEmSJPUTdZH0Aq4EllfY/q/Ax4DPAW8pHHNnRGzbfkBEjALuBBJwIvBp4CLgU714LUlV1tLSxDvfObO4ftttf6143J/+tIijj/4RGzaUV4Ldccff2HPP63juuWXFbVZ6SZIkSVLjqvmkV0QcChwLfL7D9iFkiarPpJS+nlK6EziFLCF1Xsmh7wdagLemlO5IKf07WZLqwogYXu1rSeo9b3vbjOLru+56tuIx3/3un7s8f+HCTbnzgQMH0NbWXL3GSZIkSZJqSk0nvQrdBr9GVlH1cofdBwHDgRvbN6SUVgC3AMeVHHcc8KuU0tKSbT8kS14d1gvXktRLDjlkEgMHZretRx5ZxEsvreh0zGuv9Wxmx7FjW4iIqrZPkiRJklQ7ajrpRVZZNRj4RoV9OwMbgLkdtj9e2Fd63BOlB6SUngVWlhxXzWtJ6iVtbc3sv3+xxzFz5jzX6ZjVq9f36FqO5yVJkiRJjW1g3g3oSkSMAS4F3plSWlehImMUsDyltKHD9sVAa0Q0p5TWFo5bUuEtFhf2VftapZ/hHOAcgPHjxzNnzpyKn7XeLF++vGE+i+pHe9ztuGPivvuybddf/wDjxr1Qdtyzzz7f6dzhw5tYurT8n/eMGU3Gsbrl/U55MfaUB+NOeTDulBdjr3+o2aQXcDlwf0rpF3k3ZGullK4GrgbYd9990+GHH55vg6pkzpw5NMpnUf1oj7vly//C9773YwBWrGjpFIttba+S5aE32X77UTz66KYe0qNGDeGqq05mm21ae7vZqnPe75QXY095MO6UB+NOeTH2+oea7N4YEbsC7wU+HREjI2Ik0P7X6YiIaCH7q3ZYYdyvUqOAlYXKLArHjajwNqPY9JdxNa8lqRftuOPI4uu77nqWlMpnaVy9umPBJkycOKxs/YIL9jHhJUmSJEkNriaTXsBOwCDgt2TJpMVsGtdrPtng9k8ATcD0Dud2HHfrCTqMtxURk8mSaE+UHFOta0nqRVOnlk+UeuaZt5WtVxrTa+LEtrL1mTNHV79hkiRJkqSaUqtJr3uBIzosnyvs+3vgSuA+YClwSvtJEdEKvAUo/Sv4NuCYiCj9q/dUYBXw/wrr1byWpF7U0jKobP1733usbL1S0mvChKFl69ttN6zTMZIkSZKkxlKTY3qllF4G5pRui4iphZf3pJSWF7Z9FvhYRCwmq7S6kCyR97WSU/8dOB+4OSI+B0wDPgl8MaW0tPB+q6t1LUl9b926DQwalPVOXrWqc9Jr6NDyRNmkSW2djpEkSZIkNZZarfTqqc+SDXh/MXArMBx4c0rpxfYDUkqLgb8j6754C/Ap4EvAJ3rxWpL60GuvrSm+rjSmV3NzE1dccQiDBg3g7LP3YMqU4Z2OkSRJkiQ1lpqs9KokpXQtcG2HbYksUXV5N+c+BhzZzTFVu5akvrVkyRrGjs0Gpq/UvbG5eQAXXrgvF164D4MH181tT5IkSZL0OtR7pZekfujcc/csW1+ypPtKL8CElyRJkiT1Iya9JNWdT3/64LL10qTXqlXrOh3fnvSSJEmSJPUfJr0k1Z0xY1o46aSdiuuLF68GsgHtN1fpJUmSJEnqP0x6SapL48e3Fl8/9tgrADzyyCI2bkxlx40YMZi3vGXHPm2bJEmSJCl/Jr0k1aXDDptcfH377c8A8OCDxclWOfroqXzta0cyZ86ptLU193XzJEmSJEk5c1RnSXXpqKOmEAEpwX33LWTOnGeZN29xcf+++47nvPP2zrGFkiRJkqQ8mfSSVJfGjm1lr73G8/DDWXXXEUfcWLZ/1KgheTRLkiRJklQj7N4oqW4dcsjELveZ9JIkSZKk/s2kl6S6deaZu3a5b+TIwX3YEkmSJElSrTHpJalu7bXXeN7whtEV91npJUmSJEn9m0kvSXXtox89oOL2UaOs9JIkSZKk/syB7CXVtXe8Y2eee24Zy5ev5YorHgCgqSmYNKkt55ZJkiRJkvJk0ktSXWtqGsDFF78JgOOPn8all/6WE06YzjbbtObcMkmSJElSnkx6SWoYBx00kdtuOznvZkiSJEmSaoBjekmSJEmSJKnhmPSSJEmSJElSwzHpJUmSJEmSpIZj0kuSJEmSJEkNx6SXJEmSJEmSGo5JL0mSJEmSJDUck16SJEmSJElqOCa9JEmSJEmS1HBMekmSJEmSJKnhmPSSJEmSJElSwzHpJUmSJEmSpIZj0kuSJEmSJEkNx6SXJEmSJEmSGo5JL0mSJEmSJDUck16SJEmSJElqOCa9JEmSJEmS1HBMekmSJEmSJKnhmPSSJEmSJElSwzHpJUmSJEmSpIZj0kuSJEmSJEkNx6SXJEmSJEmSGo5JL0mSJEmSJDUck16SJEmSJElqOCa9JEmSJEmS1HBMekmSJEmSJKnhmPSSJEmSJElSwzHpJUmSJEmSpIZj0kuSJEmSJEkNx6SXJEmSJEmSGo5JL0mSJEmSJDUck16SJEmSJElqOJFSyrsN/UJELAL+lnc7qmQs8HLejVC/Y9wpD8ad8mLsKQ/GnfJg3Ckvxl7j2D6ltE2lHSa9tMUi4sGU0r55t0P9i3GnPBh3youxpzwYd8qDcae8GHv9g90bJUmSJEmS1HBMekmSJEmSJKnhmPTS1rg67waoXzLulAfjTnkx9pQH4055MO6UF2OvH3BML0mSJEmSJDUcK70kSZIkSZLUcEx6SZIkSZIkqeGY9BIAERF5t0GS+pr3PkmSJKlxmfQSETE0Obib+lhEDImIKXm3Q/1PRAyNiH+NiCbvfZIkSVLjMunVz0XEJcCyiDgx77ao/4iIDwN/Bs6PiBl5t0f9R0R8HHgBuAI4LOfmqJ+IiLMj4rKIeG9E7FTY5jOYelVEnBYRfx8Ru5dss7pVvapwvzu/EHtDC9u836nXRcShETGm8Np7nYoG5t0A5aOQ5PoGsBE4D7g73xapP4iIbYDvAW8gmyL4D8DCXBulfiEi/gH4OrAO+HfgfGBwYV9Y8aXeEBEHAP8BtAJPAx8E7o+IM1JKCyJiQEppY66NVMOJiAOB/wSGAmuB8RHxGeCrKaVXC1WuG3JtpBpOROwM/BcwHJgP7Af8PCL+MaX0bK6NU0OLiDeRfddOAd4P/KfPdSpl1r2fKXQpuwb4MXA9cABwdUppWb4tUz9xADAeeDfwxZTSbSml5Tm3SQ0sIkZHxJ/J7nffBw4FPgM8DxzZflhOzVMDK1Q4fAp4kCzWjgXeCYwFzgIw4aVqi4jBZHH3P2T3u/2Az5P9IfhlABNe6iWnAS+T3e8OA04HdgB+GBGteTZMjSsi9ge+SpbgXwacFBHTCvt8vhNg0qvfSSmtBoYATwH3p5QWppTWR8SAiGj25qBe9m5gfkrpnpTSmogYGBH7RcTw9gMsgVcvuJvsj78Pp5SeAxLwN2CXiGg18aBesi9wIHBnSukvKaU1wG1kVfZrwAdy9YqdgX2A21NKT6WUXgQuB24C3hkRJ+faOjWEjveuwvps4K8ppbkppbXAj4Bzgd2BSwoJWel1qfC9uTPZj5fnAf8MHAX8PYDVXmrnH5f9RGSaCqufAVYCJxb2vR/4HXAH8N2ImJlPK9VoSr+YIqKZ7I+9vxbWzyMbW+km4IHC+HJWPqgq2pOnKaVXgfNTSg+1P/yklBYDzwKTgWTiQdXSIZZWk3UvW1SybQDwIvCQEymoWjrE3WCgjWzcTCJiUEppJVkCAuBTpT80SVujwr1rOLCCbJzg9u/fjSmle8mSrv8E7N23rVQjqhB7PweOSindm1K6AXiILMG/D/jjkjImvRpYRBwSEe9pX20vZ08p/Qm4GTgiIhYAHwceIOt/Pxu4ISKOK1zDGNEW6Rh37dsLv/ptAGZExDHARcD/JXsQ+h/gIxHx0cI1jDttsQ6xV1T6gFQSW7cDM4AJKSUTX9pqm7nnPQD8FvhSRHwqIk4H/kRWAfYfwJ0R8Y7CNYw/bZGu4g54hKyS9b2F9faujI8BrwIzgQ8UrtGEtAUKA4VfHhEfjIi3tG9PKb0GvETWnXZ0h9O+SvY3xrmFa3i/0xbrKvaAV1NKS0sqCf+F7D53UqGa32c8mfRqRBHRFhFXAv8P+LeI2CGltDEimkr+4PsmMK9wzJvJKiHOAI4DVgEXRkSzVTfqqR7G3XVk8XY58AvgCymln5I9CH0Z+FhEjCuc5xeUemRzsdfx2JJ72lJgOTCrsN2KG22RHt7zTiO71+0CfKvwehbZPe85surq7QsP5T6TqVs9uN+tJ3vGOycijgaaC9uPAeYC3wHeExGDHdtLPRURYyLi+2RVNXsAFwLXR8QnSg77ClnS66DScwuVhl8ETis845mEUI/1MPYoDJsSKaWHgBvIvn9n9XmDVZN8wGowETGI7GbwbuBnZF3JLoNs4NLCg9GAlNIrwBVkM/n8OaW0vnDMA8CtZLPrHZzHZ1D96UncFQ59hGxMm72B50oeuFeSfUEtovBLoEkI9UR3sVfh+PYH7XvJup4NL2z3+1A9tgXftfNTShcA9wFPAJeklH6fUvoZ2XfwfLIZHSEba07qUk/ud4XnuWvJZtG7Cbg5Im4k+9HpZ2T3vlXA9n3cfNWpiBhDNjTK9mQ9Qk4lq1j9CvDRiNihcOgfyKqoPxYRbR0ucz/ZkBangs946pnNxN6XKcRehx+N2p/xLgaGkSVax5tolQ/5DSaltI5sHJFbyWaHuh44KiKOgqyUvT0BkVK6K6V0f2F7lPxKeCswiWwGDKlbPYi7QYVD5wM/IEtyvSEitimcn4C/kMXc6r5tvepZT+55HY5PJYn/h4CjC9utalWPbcl3bcGxwL0ppVdLYvJpsvG9xhYqq/0jUJvVg7gbWDjuVbIqh08DTWRjfJ2YUvoMWZfbyWSz7Ek9MYWswuY7ZPexlSmlhcAPye5hKMkOfQAACvNJREFUZwAUZuO+HNgN+D8RMaTkGn8j+7vTGbu1JbqKvRvIYu902PQM1171WnjG+wJZouzIyMYV3jcixoFdbPsjk151rlDy2XE2lK+klP53Sullsqqax8nG7SKltKHjP/TCzSEV9jUDJwFLyLr/SJ1sRdytKyQa1gO/BL5L9mvNMSXnzwRGkv0hKFVUjXte4aFoIPAMsF1ETOiDpquObW3clfz6/FfgxML3bXsF4u7ABOCewpiHUpmtiLv17XFXqDj8Almy67iU0i2Fa51Ldu9bW6kLuNQx7lJKvwf+KaV0TYfv1BfI/pZcWnLsvcDngI9RSEgUzGDTRB5SRVsRe8sK55U+57VPWnQl8DxwDvBvwD3ABYV9/sjUz5j0qlMRMToifkA2psPdEfGBiJhY2N3+0BMppYfJytt3imyWRujw/3t7sisiRgMnAO8A/jOl9FQffRzViWrEXeHXl4uAB4FLI+InEfEhsoGdnyHrBiSVqeY9ryQB+zAwnU0DPUtlXm/clVR7/YCs2ubGwjXOAL5NVv16e999ItWDKsYdKaXVhWe88cBbgKOA61JKyx3TS6W6iLtJhd2/KxwzoFAx3QSsI5uVu6xCP6X0SbIfOD8WEXdExIfJ7ndz268jlXq9sVeaxCr8sDmokDz7DXAY8DbgX1JKF/fdp1ItCROd9afw4HIjWb/lHwAHkD3EPAYc3f4Pv3Bz2BgRU4DPA28E9kvZDBfFh6KI2IlsFr3hZON4fQu4oH2cLwmqFndNZN9NGwvXO4ms4mso2ZfaPxe6b0hFvXDPi8KD07FkA4vvkbJZbaWiKsXdwPbv0og4AfgSWRJ2A9kfhRd4z1OpXrjftQBnk3XlPopskPsPmvBSqZ7GXYdzdiYbq3WPlNIThW1NhR/TRwFHks0iOpJsvC+f8dRJtWKvw/4dyH5MP5RsEoWLjb1+LqXkUmcL2QyLi4G9Sra9E1gAfLuLc04mGzPpCyXb2pOeo8iSXlcB0/P+fC61uVQ77krWm4FheX8+l9pdejH2JgIT8v58LrW5VDPuSr5vRwI7AePz/nwutbn0xv2ObCiBj/mM59LVspVxdzawsHBfiy6OaQKG5v35XGp36Y3YI5sx+QpgZt6fz6U2Frs31qeJwCtk/Znb/RdwKfDeQvUCUDYj2Z1kA5++IyL2iIhtgZMjYnRKaTHwsZTS+1JK8/rmI6gOVSvu3hbZbCwApJTWpmzwU6kr1Yy90e3HppQWpJSe7/XWq15VLe6AMQAppSUppbkpJce1UVeqeb8bW9h/e0rpUp/xtBlbEncDCy/3BeYX7mspIkZExBEdvmc3pJRW9EH7Vb+qGXvt37WPpZQ+klJ6vI8+g2rcwO4PUV4iYijZ4HurgOeABwsPyhuBscCoiHghZVZFxA1k4zVcRtZtgrRpNoslEXEzcAhZuWcrMBXYC3g1pbSmTz+calYfxt0rffrBVPP68p7Xpx9MNa0P487Z8lTUl3GXUnIsEwHVibvCsQBvAn5duO6bgc+Qzdzo96w66cPY8+8LdWKlV42KiHOAZ4F3A+eTTQt8XWH3jYX/nlDIbjcBFCq2vgTsGREnFq4zsPDfoUALMJ7shvAbsu4VnfpBq/8y7pQXY095MO6UB+NOeahW3KVsLLntyCbnWBwR3wN+BTxBFndW16iMsafcVbu/pMvrW8j6vp8FPAp8kGw68zbgfcAK4MLCcd8g+9W4tbDePl7IeLIprH/V4brnkWXH7wF2y/tzutTWYty55LUYey55LMadSx6LceeSx9IbcUc2I97GwvIQsE/en9Ol9hZjz6VWFiu9as9G4ATgfuA/UkrPp5SWAT8mG7Ph2MIYDteSzf702dKTU1Ym+jTQHBFtJeM93Aq8O6V0SHKWMnVm3Ckvxp7yYNwpD8ad8lDNuBtR2PwaMAc4MaW0T0rpob74IKo7xp5qgmN61ZiUUoqIc8nG2VoJEBGRUnopItaRzXK3MSIeB64EPhcRPwfuANrHbBhAlhlfWTg2UkrPAM/09edRfTDulBdjT3kw7pQH4055qHLcLS9c8w/AkX39WVRfjD3VCiu9alBKaX5KaWXJL3hR+O9GYHXhmOXA1WSZ8quBMyNibETsDuwDXJ9S2lA41gFM1S3jTnkx9pQH4055MO6Uh2rHndRTxp5qgUmvGpY2zcrTPlPFbsCDkE1TnVJaCpxOVjL6ZeDuwgLwg75trRqFcae8GHvKg3GnPBh3yoNxp7wYe8qT3RvrRERMAqaQ3QgolII2pZTWRsR7gF2BmcCylNKPc2yqGohxp7wYe8qDcac8GHfKg3GnvBh76msmverHTLLKvLmQZcSB3SNifkrpZeB3hUWqJuNOeTH2lAfjTnkw7pQH4055MfbUp+zeWONK+j+/CXgxpTQvIrYHvgg8DJySW+PUsIw75cXYUx6MO+XBuFMejDvlxdhTXsLxL+tDRPwMWAv8GvgEsBQ4P6X0i1wbpoZm3Ckvxp7yYNwpD8ad8mDcKS/GnvqaSa86EBEtwJ+BqcAq4BMppc/n2ig1PONOeTH2lAfjTnkw7pQH4055MfaUB5NedSIivgcsAi5OKa3Juz3qH4w75cXYUx6MO+XBuFMejDvlxdhTXzPpVScKU7lu7P5IqXqMO+XF2FMejDvlwbhTHow75cXYU18z6SVJkiRJkqSG4+yNkiRJkiRJajgmvSRJkiRJktRwTHpJkiRJkiSp4Zj0kiRJkiRJUsMx6SVJkiRJkqSGY9JLkiSpwUTEJyMiFZaNEbE4In4XEZdHxLZbcb0PRcThvdBUSZKkXmPSS5IkqTG9BhwIHAScBtwMvAt4NCL22cJrfQg4vKqtkyRJ6mUD826AJEmSesX6lNL9Jeu/iohvAv8N/DAidk4pbcipbZIkSb3OSi9JkqR+IqW0hKxqazrwZoCI+GxEPBoRyyNifkRcX9oFMiKeAcYAnyjpMnl4Yd9FhW6Tr0XEixFxS0RM7/MPJkmSVIFJL0mSpP5lDrAeOKCwPg64Ajge+GdgGnB3RLQ/J55E1lXyGrLukgcCDxf2TQK+DpwInA00AfdFxIhe/xSSJEndsHujJElSP5JSWh0RLwPjC+vvbd8XEU3Ab4H5wCzgv1NKv4+I9cD8Dt0lSSld0OHcO4CXyJJg1/X2Z5EkSdocK70kSZL6nyi+iDguIu6LiNfIKsDmF3bN6PYiEQdExB0R8Urh3JXAsJ6cK0mS1NtMekmSJPUjETGEbIyuFyNiP+BnZImud5F1XWzv9jikm+tMAW4nS6C9DzgY2I+s0muz50qSJPUFuzdKkiT1L0eQPQP+lmy8rkXAqSmlBBAR2/fwOscCrcCJKaUVhXMHAqOr3mJJkqStYKWXJElSPxERI4HPAfOAO4EWYF17wqvgjAqnrqVz9VYLsJGsW2O7t+OPqpIkqUb4UCJJktSYBkZEe1fFNmAf4ANk1VnHppQ2RMQdwD9HxJeBW4CDgHdWuNYTwPER8UtgOfAkcDfZbI3/ERHXALsCHwSW9OJnkiRJ6jErvSRJkhrTCLIujPcBNwEnA/8J7J5SegggpfQL4MPA28jG9joMmF3hWv8CrAB+DvwO2Cel9Cjwv4A3AbcCpwOnAK/12ieSJEnaAlFezS5JkiRJkiTVPyu9JEmSJEmS1HBMekmSJEmSJKnhmPSSJEmSJElSwzHpJUmSJEmSpIZj0kuSJEmSJEkNx6SXJEmSJEmSGo5JL0mSJEmSJDUck16SJEmSJElqOP8fps/E1+0dQpUAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RbCwpfJYjbkt"
      },
      "source": [
        "# Calculando as bandas de bollinger\n",
        "\n",
        "#Parâmetros iniciais\n",
        "periodo =21\n",
        "desvios = 2\n",
        "\n",
        "df['desvio'] = df['Adj Close'].rolling(periodo).std()\n",
        "df['MM'] = df['Adj Close'].rolling(periodo).mean()\n",
        "df['Band_Sup'] = df['MM'] + (df['desvio']*desvios)\n",
        "df['Band_Inf'] = df['MM'] - (df['desvio']*desvios)"
      ],
      "execution_count": 87,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1m3bY2rMonsV"
      },
      "source": [
        "#filtrando os valores missings, devido a criação de colunas com rolling\n",
        "df = df.dropna(axis=0)"
      ],
      "execution_count": 88,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 841
        },
        "id": "W-LC8Lruoyds",
        "outputId": "322d445e-4d7d-48bd-e1be-68cf75960b5a"
      },
      "source": [
        "# Inserindo tudo no gráfico\n",
        "\n",
        "df[['Adj Close','MM','Band_Sup','Band_Inf']].plot(grid = True,\n",
        "                                                    figsize= (20,15),\n",
        "                                                    linewidth=2,\n",
        "                                                    fontsize=15,\n",
        "                                                    color=['darkblue','orange','green','red'])\n",
        "\n",
        "plt.xlabel('Data', fontsize=15);\n",
        "plt.ylabel('Pontos', fontsize=15);\n",
        "plt.title('Ibovespa - Python Finanças Quantitativas', fontsize=15);\n",
        "plt.legend();"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QO_Ie9YaqcOx"
      },
      "source": [
        "#Construção dos alvos, estratégia\n",
        "periodos = 1\n",
        "\n",
        "#Alvo  - Retorno\n",
        "df.loc[:,'Retorno'] = df['Adj Close'].pct_change(periodos)\n",
        "df.loc[:,'Alvo'] = df['Retorno'].shift(periodos)\n"
      ],
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "Duvmls3YrgG1",
        "outputId": "09543361-5e36-4422-e2c3-bd235e05bd85"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 91,
      "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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>desvio</th>\n",
              "      <th>MM</th>\n",
              "      <th>Band_Sup</th>\n",
              "      <th>Band_Inf</th>\n",
              "      <th>Retorno</th>\n",
              "      <th>Alvo</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-30</th>\n",
              "      <td>47759.0</td>\n",
              "      <td>47759.0</td>\n",
              "      <td>46484.0</td>\n",
              "      <td>46908.0</td>\n",
              "      <td>46908.0</td>\n",
              "      <td>4846600</td>\n",
              "      <td>765.248161</td>\n",
              "      <td>48369.380952</td>\n",
              "      <td>49899.877274</td>\n",
              "      <td>46838.884631</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-02</th>\n",
              "      <td>46933.0</td>\n",
              "      <td>47684.0</td>\n",
              "      <td>46760.0</td>\n",
              "      <td>47651.0</td>\n",
              "      <td>47651.0</td>\n",
              "      <td>3247800</td>\n",
              "      <td>780.145017</td>\n",
              "      <td>48328.380952</td>\n",
              "      <td>49888.670986</td>\n",
              "      <td>46768.090918</td>\n",
              "      <td>0.015840</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-03</th>\n",
              "      <td>47664.0</td>\n",
              "      <td>48993.0</td>\n",
              "      <td>47664.0</td>\n",
              "      <td>48964.0</td>\n",
              "      <td>48964.0</td>\n",
              "      <td>4819800</td>\n",
              "      <td>768.716212</td>\n",
              "      <td>48397.285714</td>\n",
              "      <td>49934.718138</td>\n",
              "      <td>46859.853291</td>\n",
              "      <td>0.027555</td>\n",
              "      <td>0.015840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-04</th>\n",
              "      <td>48965.0</td>\n",
              "      <td>49718.0</td>\n",
              "      <td>48214.0</td>\n",
              "      <td>49301.0</td>\n",
              "      <td>49301.0</td>\n",
              "      <td>4811300</td>\n",
              "      <td>787.326909</td>\n",
              "      <td>48459.190476</td>\n",
              "      <td>50033.844295</td>\n",
              "      <td>46884.536658</td>\n",
              "      <td>0.006883</td>\n",
              "      <td>0.027555</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-05</th>\n",
              "      <td>49299.0</td>\n",
              "      <td>49816.0</td>\n",
              "      <td>49020.0</td>\n",
              "      <td>49234.0</td>\n",
              "      <td>49234.0</td>\n",
              "      <td>4004000</td>\n",
              "      <td>774.205150</td>\n",
              "      <td>48448.285714</td>\n",
              "      <td>49996.696014</td>\n",
              "      <td>46899.875414</td>\n",
              "      <td>-0.001359</td>\n",
              "      <td>0.006883</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Open     High      Low  ...      Band_Inf   Retorno      Alvo\n",
              "Date                                   ...                                  \n",
              "2015-01-30  47759.0  47759.0  46484.0  ...  46838.884631       NaN       NaN\n",
              "2015-02-02  46933.0  47684.0  46760.0  ...  46768.090918  0.015840       NaN\n",
              "2015-02-03  47664.0  48993.0  47664.0  ...  46859.853291  0.027555  0.015840\n",
              "2015-02-04  48965.0  49718.0  48214.0  ...  46884.536658  0.006883  0.027555\n",
              "2015-02-05  49299.0  49816.0  49020.0  ...  46899.875414 -0.001359  0.006883\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "D_xhIIlTrhEu",
        "outputId": "988acdb9-f221-4360-c8b8-72713281f98a"
      },
      "source": [
        "df.tail()"
      ],
      "execution_count": 92,
      "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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>desvio</th>\n",
              "      <th>MM</th>\n",
              "      <th>Band_Sup</th>\n",
              "      <th>Band_Inf</th>\n",
              "      <th>Retorno</th>\n",
              "      <th>Alvo</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2021-05-25</th>\n",
              "      <td>124032.0</td>\n",
              "      <td>124696.0</td>\n",
              "      <td>122701.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>8914500</td>\n",
              "      <td>1749.749257</td>\n",
              "      <td>121232.476190</td>\n",
              "      <td>124731.974704</td>\n",
              "      <td>117732.977677</td>\n",
              "      <td>-0.008417</td>\n",
              "      <td>0.011746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-26</th>\n",
              "      <td>122988.0</td>\n",
              "      <td>124256.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>123989.0</td>\n",
              "      <td>123989.0</td>\n",
              "      <td>8258400</td>\n",
              "      <td>1794.724535</td>\n",
              "      <td>121451.571429</td>\n",
              "      <td>125041.020499</td>\n",
              "      <td>117862.122358</td>\n",
              "      <td>0.008139</td>\n",
              "      <td>-0.008417</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-27</th>\n",
              "      <td>123989.0</td>\n",
              "      <td>124537.0</td>\n",
              "      <td>123470.0</td>\n",
              "      <td>124367.0</td>\n",
              "      <td>124367.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1900.507918</td>\n",
              "      <td>121609.380952</td>\n",
              "      <td>125410.396789</td>\n",
              "      <td>117808.365116</td>\n",
              "      <td>0.003049</td>\n",
              "      <td>0.008139</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-28</th>\n",
              "      <td>124367.0</td>\n",
              "      <td>125698.0</td>\n",
              "      <td>124284.0</td>\n",
              "      <td>125561.0</td>\n",
              "      <td>125561.0</td>\n",
              "      <td>8838500</td>\n",
              "      <td>2049.805076</td>\n",
              "      <td>121871.047619</td>\n",
              "      <td>125970.657770</td>\n",
              "      <td>117771.437468</td>\n",
              "      <td>0.009601</td>\n",
              "      <td>0.003049</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-31</th>\n",
              "      <td>125561.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>125540.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>126216.0</td>\n",
              "      <td>5946500</td>\n",
              "      <td>2138.888476</td>\n",
              "      <td>122219.714286</td>\n",
              "      <td>126497.491238</td>\n",
              "      <td>117941.937333</td>\n",
              "      <td>0.005217</td>\n",
              "      <td>0.009601</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                Open      High       Low  ...       Band_Inf   Retorno      Alvo\n",
              "Date                                      ...                                   \n",
              "2021-05-25  124032.0  124696.0  122701.0  ...  117732.977677 -0.008417  0.011746\n",
              "2021-05-26  122988.0  124256.0  122988.0  ...  117862.122358  0.008139 -0.008417\n",
              "2021-05-27  123989.0  124537.0  123470.0  ...  117808.365116  0.003049  0.008139\n",
              "2021-05-28  124367.0  125698.0  124284.0  ...  117771.437468  0.009601  0.003049\n",
              "2021-05-31  125561.0  126216.0  125540.0  ...  117941.937333  0.005217  0.009601\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_ydFEkRxrqcS"
      },
      "source": [
        "df.dropna(axis=0, inplace=True)"
      ],
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6s3HldwssFM1"
      },
      "source": [
        "#Criando a Regra de Trade\n",
        "df.loc[:,\"Regra\"] = np.where(df.loc[:,'Adj Close'] > df.loc[:,'Band_Sup'],1,0)\n",
        "\n",
        "df.loc[:,\"Regra\"] = np.where(df.loc[:, \"Adj Close\"] < df.loc[:,'Band_Inf'],-1,df.loc[:,'Regra'])"
      ],
      "execution_count": 94,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WHVM6ms2yrbA"
      },
      "source": [
        "# Aplicando a regra no alvo\n",
        "df.loc[:, 'Trade'] = df.loc[:,\"Regra\"]*df.loc[:,'Alvo']"
      ],
      "execution_count": 95,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oAJ4CAm5zdyU"
      },
      "source": [
        "#Calculando o resultado acumulado em juros simples\n",
        "\n",
        "df.loc[:,'Retorno_Trade_BB'] = df['Trade'].cumsum()"
      ],
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 841
        },
        "id": "9P0A6LGhzyMS",
        "outputId": "579168f1-8be9-4620-8248-0d85c191449f"
      },
      "source": [
        "df['Retorno_Trade_BB'].plot(figsize=(20,15), linewidth=3,fontsize=15, color='green')\n",
        "\n",
        "plt.xlabel('Data', fontsize=15);\n",
        "plt.ylabel('Pontos', fontsize=15);\n",
        "plt.title('Ibovespa - Python Finanças Quantitativas', fontsize=15);\n",
        "plt.legend();"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lkyUc8OM0EUj"
      },
      "source": [
        "# **Automação com funções**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ec80J_R1NNek"
      },
      "source": [
        "def om_bolinger(ticker,periodo,desvios,inicio, fim, alvo):\n",
        "\n",
        "  df = pdr.get_data_yahoo(ticker,start=inicio,end=fim)\n",
        "  df['desvio'] =df['Adj Close'].rolling(periodo).std()\n",
        "  df['MM'] = df['Adj Close'].rolling(periodo).mean()\n",
        "  df['Banda_Sup'] = df['MM'] + (df['desvio'] * desvios)\n",
        "  df['Banda_Inf'] = df['MM'] - (df['desvio'] * desvios)\n",
        "\n",
        "  #filtrando valores missing\n",
        "  df = df.dropna(axis=0)\n",
        "\n",
        "  #Construção dos alvos\n",
        "  df.loc[:, 'Retorno'] = df['Adj Close'].pct_change(alvo)\n",
        "  df.loc[:, 'Alvo'] = df.Retorno.shift(alvo)\n",
        "\n",
        "  #filtrando valores missing\n",
        "  df = df.dropna(axis=0)\n",
        "\n",
        "  #Criando as regras de Trade\n",
        "  df.loc[:, \"Regra\"] = np.where(df.loc[:, 'Adj Close'] > df.loc[:, 'Banda_Sup'],1,0)\n",
        "  df.loc[:, \"Regra\"] = np.where(df.loc[:, 'Adj Close'] < df.loc[:, 'Banda_Inf'],-1, df.loc[:,'Regra'])\n",
        "  \n",
        "  #Aplicando a Regra no \n",
        "  df.loc[:,'Trade'] = df.loc[:,'Regra']* df.loc[:,\"Alvo\"]\n",
        "\n",
        "  #Calculando o Resultado acumulado em juros simples\n",
        "  df.loc[:, \"Retorno_Trade_BB\"] = df['Trade'].cumsum()\n",
        "\n",
        "  return(df)"
      ],
      "execution_count": 98,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "99kQGX2YNWiA"
      },
      "source": [
        "#parâmetros da função\n",
        "ticker = '^BVSP'\n",
        "inicio ='2015-01-01'\n",
        "fim = '2021-06-02'\n",
        "periodo = 50\n",
        "desvios =2\n",
        "alvo= 5"
      ],
      "execution_count": 100,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bRCeaIvSt0S7"
      },
      "source": [
        "def om_bollinger(ticker, periodo, desvios, inicio, fim, alvo):\n",
        "    \n",
        "    df = pdr.get_data_yahoo(ticker, start = inicio, end = fim)\n",
        "    df[\"desvio\"] = df[\"Adj Close\"].rolling(periodo).std()\n",
        "    df[\"MM\"] = df[\"Adj Close\"].rolling(periodo).mean()\n",
        "    df[\"Banda_Sup\"] = df[\"MM\"] + (df[\"desvio\"]*desvios)\n",
        "    df[\"Banda_Inf\"] = df[\"MM\"] - (df[\"desvio\"]*desvios)\n",
        "    \n",
        "    # Filtrando os valores missing\n",
        "    df = df.dropna(axis = 0) \n",
        "    \n",
        "    # Construcao dos alvos\n",
        "    df.loc[:, \"Retorno\"] = df[\"Adj Close\"].pct_change(alvo)\n",
        "    df.loc[:, \"Alvo\"] = df[\"Retorno\"].shift(-alvo)\n",
        "    \n",
        "    # Filtrando os valores missing\n",
        "    df = df.dropna(axis = 0) \n",
        "    \n",
        "    # Criando a regra de trade\n",
        "    df.loc[:, \"Regra\"] = np.where(df.loc[:, \"Adj Close\"] > df.loc[:, \"Banda_Sup\"], 1, 0)\n",
        "    df.loc[:, \"Regra\"] = np.where(df.loc[:, \"Adj Close\"] < df.loc[:, \"Banda_Inf\"], -1, df.loc[: , \"Regra\"])\n",
        "\n",
        "    # Aplicando a regra no alvo\n",
        "    df.loc[:, \"Trade\"] = df.loc[:, \"Regra\"]*df.loc[:, \"Alvo\"]\n",
        "    \n",
        "    # Calculando o resultado acumulado em juros simples\n",
        "    df.loc[:, \"Retorno_Trade_BB\"] = df[\"Trade\"].cumsum()\n",
        "    \n",
        "    return(df)"
      ],
      "execution_count": 101,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 674
        },
        "id": "Vbx4Tp6rNYyb",
        "outputId": "0f8e701e-f9fe-417e-aa9c-3260322d6ecb"
      },
      "source": [
        "om_bollinger(ticker,periodo,desvios,inicio,fim,alvo)"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>desvio</th>\n",
              "      <th>MM</th>\n",
              "      <th>Banda_Sup</th>\n",
              "      <th>Banda_Inf</th>\n",
              "      <th>Retorno</th>\n",
              "      <th>Alvo</th>\n",
              "      <th>Regra</th>\n",
              "      <th>Trade</th>\n",
              "      <th>Retorno_Trade_BB</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-03-23</th>\n",
              "      <td>51970.0</td>\n",
              "      <td>52178.0</td>\n",
              "      <td>51516.0</td>\n",
              "      <td>51908.0</td>\n",
              "      <td>51908.0</td>\n",
              "      <td>3397500</td>\n",
              "      <td>1443.133609</td>\n",
              "      <td>49543.40</td>\n",
              "      <td>52429.667217</td>\n",
              "      <td>46657.132783</td>\n",
              "      <td>0.062643</td>\n",
              "      <td>-0.012811</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.0</td>\n",
              "      <td>-0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-24</th>\n",
              "      <td>51908.0</td>\n",
              "      <td>52223.0</td>\n",
              "      <td>51006.0</td>\n",
              "      <td>51506.0</td>\n",
              "      <td>51506.0</td>\n",
              "      <td>3436500</td>\n",
              "      <td>1465.689028</td>\n",
              "      <td>49596.72</td>\n",
              "      <td>52528.098057</td>\n",
              "      <td>46665.341943</td>\n",
              "      <td>0.024282</td>\n",
              "      <td>-0.006912</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.0</td>\n",
              "      <td>-0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-25</th>\n",
              "      <td>51507.0</td>\n",
              "      <td>52319.0</td>\n",
              "      <td>51507.0</td>\n",
              "      <td>51858.0</td>\n",
              "      <td>51858.0</td>\n",
              "      <td>4774600</td>\n",
              "      <td>1484.469641</td>\n",
              "      <td>49671.08</td>\n",
              "      <td>52640.019283</td>\n",
              "      <td>46702.140717</td>\n",
              "      <td>0.006443</td>\n",
              "      <td>0.008948</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-26</th>\n",
              "      <td>51835.0</td>\n",
              "      <td>51835.0</td>\n",
              "      <td>50528.0</td>\n",
              "      <td>50580.0</td>\n",
              "      <td>50580.0</td>\n",
              "      <td>3638500</td>\n",
              "      <td>1470.958737</td>\n",
              "      <td>49721.84</td>\n",
              "      <td>52663.757474</td>\n",
              "      <td>46779.922526</td>\n",
              "      <td>-0.007340</td>\n",
              "      <td>0.050277</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-27</th>\n",
              "      <td>50575.0</td>\n",
              "      <td>50575.0</td>\n",
              "      <td>49909.0</td>\n",
              "      <td>50095.0</td>\n",
              "      <td>50095.0</td>\n",
              "      <td>3927700</td>\n",
              "      <td>1440.892902</td>\n",
              "      <td>49770.82</td>\n",
              "      <td>52652.605804</td>\n",
              "      <td>46889.034196</td>\n",
              "      <td>-0.036023</td>\n",
              "      <td>0.072702</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-19</th>\n",
              "      <td>122976.0</td>\n",
              "      <td>123013.0</td>\n",
              "      <td>121595.0</td>\n",
              "      <td>122636.0</td>\n",
              "      <td>122636.0</td>\n",
              "      <td>8825300</td>\n",
              "      <td>3123.074513</td>\n",
              "      <td>118132.46</td>\n",
              "      <td>124378.609027</td>\n",
              "      <td>111886.310973</td>\n",
              "      <td>0.024442</td>\n",
              "      <td>0.011033</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.864882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-20</th>\n",
              "      <td>122636.0</td>\n",
              "      <td>122734.0</td>\n",
              "      <td>122136.0</td>\n",
              "      <td>122701.0</td>\n",
              "      <td>122701.0</td>\n",
              "      <td>7906400</td>\n",
              "      <td>3030.296975</td>\n",
              "      <td>118359.86</td>\n",
              "      <td>124420.453950</td>\n",
              "      <td>112299.266050</td>\n",
              "      <td>0.016528</td>\n",
              "      <td>0.013578</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.864882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-21</th>\n",
              "      <td>122701.0</td>\n",
              "      <td>122799.0</td>\n",
              "      <td>121760.0</td>\n",
              "      <td>122592.0</td>\n",
              "      <td>122592.0</td>\n",
              "      <td>9493600</td>\n",
              "      <td>2978.688683</td>\n",
              "      <td>118556.18</td>\n",
              "      <td>124513.557367</td>\n",
              "      <td>112598.802633</td>\n",
              "      <td>0.005834</td>\n",
              "      <td>0.024219</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.864882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-24</th>\n",
              "      <td>122592.0</td>\n",
              "      <td>124167.0</td>\n",
              "      <td>122526.0</td>\n",
              "      <td>124032.0</td>\n",
              "      <td>124032.0</td>\n",
              "      <td>8186300</td>\n",
              "      <td>3031.614159</td>\n",
              "      <td>118737.14</td>\n",
              "      <td>124800.368318</td>\n",
              "      <td>112673.911682</td>\n",
              "      <td>0.008899</td>\n",
              "      <td>0.017608</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.864882</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-25</th>\n",
              "      <td>124032.0</td>\n",
              "      <td>124696.0</td>\n",
              "      <td>122701.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>122988.0</td>\n",
              "      <td>8914500</td>\n",
              "      <td>3016.635727</td>\n",
              "      <td>118913.70</td>\n",
              "      <td>124946.971455</td>\n",
              "      <td>112880.428545</td>\n",
              "      <td>0.000065</td>\n",
              "      <td>0.042923</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.864882</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1524 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                Open      High       Low  ...  Regra  Trade  Retorno_Trade_BB\n",
              "Date                                      ...                                \n",
              "2015-03-23   51970.0   52178.0   51516.0  ...      0   -0.0         -0.000000\n",
              "2015-03-24   51908.0   52223.0   51006.0  ...      0   -0.0         -0.000000\n",
              "2015-03-25   51507.0   52319.0   51507.0  ...      0    0.0          0.000000\n",
              "2015-03-26   51835.0   51835.0   50528.0  ...      0    0.0          0.000000\n",
              "2015-03-27   50575.0   50575.0   49909.0  ...      0    0.0          0.000000\n",
              "...              ...       ...       ...  ...    ...    ...               ...\n",
              "2021-05-19  122976.0  123013.0  121595.0  ...      0    0.0          2.864882\n",
              "2021-05-20  122636.0  122734.0  122136.0  ...      0    0.0          2.864882\n",
              "2021-05-21  122701.0  122799.0  121760.0  ...      0    0.0          2.864882\n",
              "2021-05-24  122592.0  124167.0  122526.0  ...      0    0.0          2.864882\n",
              "2021-05-25  124032.0  124696.0  122701.0  ...      0    0.0          2.864882\n",
              "\n",
              "[1524 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TVBAwhLjuxXU",
        "outputId": "346556d8-4f8e-4300-e803-4e49f8986b08"
      },
      "source": [
        "#Pegando apenas o resultado que é a última linha\n",
        "om_bollinger(ticker, periodo, desvios, inicio, fim, alvo).iloc[-1]"
      ],
      "execution_count": 103,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Open                1.240320e+05\n",
              "High                1.246960e+05\n",
              "Low                 1.227010e+05\n",
              "Close               1.229880e+05\n",
              "Adj Close           1.229880e+05\n",
              "Volume              8.914500e+06\n",
              "desvio              3.016636e+03\n",
              "MM                  1.189137e+05\n",
              "Banda_Sup           1.249470e+05\n",
              "Banda_Inf           1.128804e+05\n",
              "Retorno             6.505123e-05\n",
              "Alvo                4.292289e-02\n",
              "Regra               0.000000e+00\n",
              "Trade               0.000000e+00\n",
              "Retorno_Trade_BB    2.864882e+00\n",
              "Name: 2021-05-25 00:00:00, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GPjWg4OPt0TG"
      },
      "source": [
        "def om_bollinger_resultado(ticker, periodos, desvios, inicio, fim, alvo):\n",
        "    \n",
        "    df = pdr.get_data_yahoo(ticker, start = inicio, end = fim)\n",
        "    df[\"desvio\"] = df[\"Adj Close\"].rolling(periodo).std()\n",
        "    df[\"MM\"] = df[\"Adj Close\"].rolling(periodo).mean()\n",
        "    df[\"Banda_Sup\"] = df[\"MM\"] + (df[\"desvio\"]*desvios)\n",
        "    df[\"Banda_Inf\"] = df[\"MM\"] - (df[\"desvio\"]*desvios)\n",
        "    \n",
        "    # Filtrando os valores missing\n",
        "    df = df.dropna(axis = 0) \n",
        "    \n",
        "    # Construcao dos alvos\n",
        "    df.loc[:, \"Retorno\"] = df[\"Adj Close\"].pct_change(alvo)\n",
        "    df.loc[:, \"Alvo\"] = df[\"Retorno\"].shift(-alvo)\n",
        "    \n",
        "    # Filtrando os valores missing\n",
        "    df = df.dropna(axis = 0) \n",
        "    \n",
        "    # Criando a regra de trade\n",
        "    df.loc[:, \"Regra\"] = np.where(df.loc[:, \"Adj Close\"] > df.loc[:, \"Banda_Sup\"], 1, 0)\n",
        "    df.loc[:, \"Regra\"] = np.where(df.loc[:, \"Adj Close\"] < df.loc[:, \"Banda_Inf\"], -1, df.loc[: , \"Regra\"])\n",
        "\n",
        "    # Aplicando a regra no alvo\n",
        "    df.loc[:, \"Trade\"] = df.loc[:, \"Regra\"]*df.loc[:, \"Alvo\"]\n",
        "    \n",
        "    # Calculando o resultado acumulado em juros simples\n",
        "    df.loc[:, \"Retorno_Trade_BB\"] = df[\"Trade\"].cumsum()\n",
        "    \n",
        "    return(df.iloc[-1][-1])"
      ],
      "execution_count": 104,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PtJ0J-hov0jU",
        "outputId": "e7fbe5b1-c892-4bbd-d1dd-9a4ae1cc3c19"
      },
      "source": [
        "om_bollinger_resultado(ticker, periodo, desvios, inicio, fim, alvo)"
      ],
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.8648817092154744"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9se8FlcEt0TL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "outputId": "3fa356a1-526c-457c-af6f-128ff865d4a9"
      },
      "source": [
        "# Com múltiplos resultados\n",
        "display(om_bollinger_resultado(ticker, 20, 1, inicio, fim, 5))\n",
        "display(om_bollinger_resultado(ticker, 20, 3, inicio, fim, 5))"
      ],
      "execution_count": 106,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "2.8625264417980105"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1.338114224136695"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dBURMaB1wHrk"
      },
      "source": [
        "# Funçao para plotar o grafico\n",
        "\n",
        "def plot_resultado(data_frame):\n",
        "    data_frame[\"Retorno_Trade_BB\"].plot(figsize=(20, 15), linewidth = 3, fontsize = 15, color = \"green\")\n",
        "    plt.xlabel(\"Data\"\n",
        "           , fontsize = 15);\n",
        "    plt.ylabel(\"Pontos\"\n",
        "           , fontsize = 15);\n",
        "    plt.title(\"Resultado BB Trading - Python Finanças Quantitativas\"\n",
        "           , fontsize = 25)\n",
        "    plt.legend();"
      ],
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5jIeoM8NwPDY",
        "outputId": "65bc3af7-3c19-4be7-d094-d523e060c6be"
      },
      "source": [
        "dados = om_bollinger(ticker, periodo, desvios, inicio, fim, alvo)"
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "rE5GeASxwUZQ",
        "outputId": "538fa259-9475-4924-9de3-ffea4e64c607"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>desvio</th>\n",
              "      <th>MM</th>\n",
              "      <th>Banda_Sup</th>\n",
              "      <th>Banda_Inf</th>\n",
              "      <th>Retorno</th>\n",
              "      <th>Alvo</th>\n",
              "      <th>Regra</th>\n",
              "      <th>Trade</th>\n",
              "      <th>Retorno_Trade_BB</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-03-23</th>\n",
              "      <td>51970.0</td>\n",
              "      <td>52178.0</td>\n",
              "      <td>51516.0</td>\n",
              "      <td>51908.0</td>\n",
              "      <td>51908.0</td>\n",
              "      <td>3397500</td>\n",
              "      <td>1443.133609</td>\n",
              "      <td>49543.40</td>\n",
              "      <td>52429.667217</td>\n",
              "      <td>46657.132783</td>\n",
              "      <td>0.062643</td>\n",
              "      <td>-0.012811</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.0</td>\n",
              "      <td>-0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-24</th>\n",
              "      <td>51908.0</td>\n",
              "      <td>52223.0</td>\n",
              "      <td>51006.0</td>\n",
              "      <td>51506.0</td>\n",
              "      <td>51506.0</td>\n",
              "      <td>3436500</td>\n",
              "      <td>1465.689028</td>\n",
              "      <td>49596.72</td>\n",
              "      <td>52528.098057</td>\n",
              "      <td>46665.341943</td>\n",
              "      <td>0.024282</td>\n",
              "      <td>-0.006912</td>\n",
              "      <td>0</td>\n",
              "      <td>-0.0</td>\n",
              "      <td>-0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-25</th>\n",
              "      <td>51507.0</td>\n",
              "      <td>52319.0</td>\n",
              "      <td>51507.0</td>\n",
              "      <td>51858.0</td>\n",
              "      <td>51858.0</td>\n",
              "      <td>4774600</td>\n",
              "      <td>1484.469641</td>\n",
              "      <td>49671.08</td>\n",
              "      <td>52640.019283</td>\n",
              "      <td>46702.140717</td>\n",
              "      <td>0.006443</td>\n",
              "      <td>0.008948</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-26</th>\n",
              "      <td>51835.0</td>\n",
              "      <td>51835.0</td>\n",
              "      <td>50528.0</td>\n",
              "      <td>50580.0</td>\n",
              "      <td>50580.0</td>\n",
              "      <td>3638500</td>\n",
              "      <td>1470.958737</td>\n",
              "      <td>49721.84</td>\n",
              "      <td>52663.757474</td>\n",
              "      <td>46779.922526</td>\n",
              "      <td>-0.007340</td>\n",
              "      <td>0.050277</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-27</th>\n",
              "      <td>50575.0</td>\n",
              "      <td>50575.0</td>\n",
              "      <td>49909.0</td>\n",
              "      <td>50095.0</td>\n",
              "      <td>50095.0</td>\n",
              "      <td>3927700</td>\n",
              "      <td>1440.892902</td>\n",
              "      <td>49770.82</td>\n",
              "      <td>52652.605804</td>\n",
              "      <td>46889.034196</td>\n",
              "      <td>-0.036023</td>\n",
              "      <td>0.072702</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Open     High      Low  ...  Regra  Trade  Retorno_Trade_BB\n",
              "Date                                   ...                                \n",
              "2015-03-23  51970.0  52178.0  51516.0  ...      0   -0.0              -0.0\n",
              "2015-03-24  51908.0  52223.0  51006.0  ...      0   -0.0              -0.0\n",
              "2015-03-25  51507.0  52319.0  51507.0  ...      0    0.0               0.0\n",
              "2015-03-26  51835.0  51835.0  50528.0  ...      0    0.0               0.0\n",
              "2015-03-27  50575.0  50575.0  49909.0  ...      0    0.0               0.0\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 848
        },
        "id": "wKiHfVKswVnL",
        "outputId": "b3507705-c1ab-4284-9f55-7a839b0d2ba6"
      },
      "source": [
        "plot_resultado(dados)"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Py3_CtSFwW1h"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}