Telecom_Churn_EDA.ipynb

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      "authorship_tag": "ABX9TyNM9j40c2WkUj3Tpvy6S28L",
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      "name": "python3",
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      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Harpreetk01/Telecom_CustomerChurn_EDA/blob/main/Telecom_Churn_EDA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "zrz7H3Wzy39c"
      },
      "outputs": [],
      "source": [
        "from google.colab import drive"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drive.mount('/content/drive/')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0RuGWLsvy5tW",
        "outputId": "b74d26aa-dba9-45f4-b4ec-500d7ff4e604"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Improting required libraries**"
      ],
      "metadata": {
        "id": "aT1bu3m7zY6N"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "DLOZ9-GGy5wS"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import warnings \n",
        "warnings.simplefilter('ignore')"
      ],
      "metadata": {
        "id": "EJ1MLaL5IcT1"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv(\"/content/drive/MyDrive/DA Datasets/Telecom Churn (1).csv\")"
      ],
      "metadata": {
        "id": "RsJ57zw6y5zd"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "Rh__jhVSy52h",
        "outputId": "ac1cc933-e05e-4963-da93-7015c6d20f83"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  State  Account length  Area code International plan Voice mail plan  \\\n",
              "0    KS             128        415                 No             Yes   \n",
              "1    OH             107        415                 No             Yes   \n",
              "2    NJ             137        415                 No              No   \n",
              "3    OH              84        408                Yes              No   \n",
              "4    OK              75        415                Yes              No   \n",
              "\n",
              "   Number vmail messages  Total day minutes  Total day calls  \\\n",
              "0                     25              265.1              110   \n",
              "1                     26              161.6              123   \n",
              "2                      0              243.4              114   \n",
              "3                      0              299.4               71   \n",
              "4                      0              166.7              113   \n",
              "\n",
              "   Total day charge  Total eve minutes  Total eve calls  Total eve charge  \\\n",
              "0             45.07              197.4               99             16.78   \n",
              "1             27.47              195.5              103             16.62   \n",
              "2             41.38              121.2              110             10.30   \n",
              "3             50.90               61.9               88              5.26   \n",
              "4             28.34              148.3              122             12.61   \n",
              "\n",
              "   Total night minutes  Total night calls  Total night charge  \\\n",
              "0                244.7                 91               11.01   \n",
              "1                254.4                103               11.45   \n",
              "2                162.6                104                7.32   \n",
              "3                196.9                 89                8.86   \n",
              "4                186.9                121                8.41   \n",
              "\n",
              "   Total intl minutes  Total intl calls  Total intl charge  \\\n",
              "0                10.0                 3               2.70   \n",
              "1                13.7                 3               3.70   \n",
              "2                12.2                 5               3.29   \n",
              "3                 6.6                 7               1.78   \n",
              "4                10.1                 3               2.73   \n",
              "\n",
              "   Customer service calls  Churn  \n",
              "0                       1  False  \n",
              "1                       1  False  \n",
              "2                       0  False  \n",
              "3                       2  False  \n",
              "4                       3  False  "
            ],
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.tail()"
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          "height": 285
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        "id": "wlts6-fcy550",
        "outputId": "ba15c031-b2dc-47ed-b3cf-f882893c1cf4"
      },
      "execution_count": null,
      "outputs": [
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          "data": {
            "text/plain": [
              "     State  Account length  Area code International plan Voice mail plan  \\\n",
              "3328    AZ             192        415                 No             Yes   \n",
              "3329    WV              68        415                 No              No   \n",
              "3330    RI              28        510                 No              No   \n",
              "3331    CT             184        510                Yes              No   \n",
              "3332    TN              74        415                 No             Yes   \n",
              "\n",
              "      Number vmail messages  Total day minutes  Total day calls  \\\n",
              "3328                     36              156.2               77   \n",
              "3329                      0              231.1               57   \n",
              "3330                      0              180.8              109   \n",
              "3331                      0              213.8              105   \n",
              "3332                     25              234.4              113   \n",
              "\n",
              "      Total day charge  Total eve minutes  Total eve calls  Total eve charge  \\\n",
              "3328             26.55              215.5              126             18.32   \n",
              "3329             39.29              153.4               55             13.04   \n",
              "3330             30.74              288.8               58             24.55   \n",
              "3331             36.35              159.6               84             13.57   \n",
              "3332             39.85              265.9               82             22.60   \n",
              "\n",
              "      Total night minutes  Total night calls  Total night charge  \\\n",
              "3328                279.1                 83               12.56   \n",
              "3329                191.3                123                8.61   \n",
              "3330                191.9                 91                8.64   \n",
              "3331                139.2                137                6.26   \n",
              "3332                241.4                 77               10.86   \n",
              "\n",
              "      Total intl minutes  Total intl calls  Total intl charge  \\\n",
              "3328                 9.9                 6               2.67   \n",
              "3329                 9.6                 4               2.59   \n",
              "3330                14.1                 6               3.81   \n",
              "3331                 5.0                10               1.35   \n",
              "3332                13.7                 4               3.70   \n",
              "\n",
              "      Customer service calls  Churn  \n",
              "3328                       2  False  \n",
              "3329                       3  False  \n",
              "3330                       2  False  \n",
              "3331                       2  False  \n",
              "3332                       0  False  "
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              "      <td>180.8</td>\n",
              "      <td>109</td>\n",
              "      <td>30.74</td>\n",
              "      <td>288.8</td>\n",
              "      <td>58</td>\n",
              "      <td>24.55</td>\n",
              "      <td>191.9</td>\n",
              "      <td>91</td>\n",
              "      <td>8.64</td>\n",
              "      <td>14.1</td>\n",
              "      <td>6</td>\n",
              "      <td>3.81</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3331</th>\n",
              "      <td>CT</td>\n",
              "      <td>184</td>\n",
              "      <td>510</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>213.8</td>\n",
              "      <td>105</td>\n",
              "      <td>36.35</td>\n",
              "      <td>159.6</td>\n",
              "      <td>84</td>\n",
              "      <td>13.57</td>\n",
              "      <td>139.2</td>\n",
              "      <td>137</td>\n",
              "      <td>6.26</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3332</th>\n",
              "      <td>TN</td>\n",
              "      <td>74</td>\n",
              "      <td>415</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>25</td>\n",
              "      <td>234.4</td>\n",
              "      <td>113</td>\n",
              "      <td>39.85</td>\n",
              "      <td>265.9</td>\n",
              "      <td>82</td>\n",
              "      <td>22.60</td>\n",
              "      <td>241.4</td>\n",
              "      <td>77</td>\n",
              "      <td>10.86</td>\n",
              "      <td>13.7</td>\n",
              "      <td>4</td>\n",
              "      <td>3.70</td>\n",
              "      <td>0</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3919fd90-5869-4c0e-97fd-e7b31cbd6228')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-3919fd90-5869-4c0e-97fd-e7b31cbd6228 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-3919fd90-5869-4c0e-97fd-e7b31cbd6228');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1r3duThk0wLE",
        "outputId": "e6c5347d-c332-42f4-8737-71ab4d99e40d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 3333 entries, 0 to 3332\n",
            "Data columns (total 20 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   State                   3333 non-null   object \n",
            " 1   Account length          3333 non-null   int64  \n",
            " 2   Area code               3333 non-null   int64  \n",
            " 3   International plan      3333 non-null   object \n",
            " 4   Voice mail plan         3333 non-null   object \n",
            " 5   Number vmail messages   3333 non-null   int64  \n",
            " 6   Total day minutes       3333 non-null   float64\n",
            " 7   Total day calls         3333 non-null   int64  \n",
            " 8   Total day charge        3333 non-null   float64\n",
            " 9   Total eve minutes       3333 non-null   float64\n",
            " 10  Total eve calls         3333 non-null   int64  \n",
            " 11  Total eve charge        3333 non-null   float64\n",
            " 12  Total night minutes     3333 non-null   float64\n",
            " 13  Total night calls       3333 non-null   int64  \n",
            " 14  Total night charge      3333 non-null   float64\n",
            " 15  Total intl minutes      3333 non-null   float64\n",
            " 16  Total intl calls        3333 non-null   int64  \n",
            " 17  Total intl charge       3333 non-null   float64\n",
            " 18  Customer service calls  3333 non-null   int64  \n",
            " 19  Churn                   3333 non-null   bool   \n",
            "dtypes: bool(1), float64(8), int64(8), object(3)\n",
            "memory usage: 498.1+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Shape of the data rows and columns\n",
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oah8lRxhy5_v",
        "outputId": "25f8452a-c36d-4145-8382-c1a4421f1b8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3333, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Getting all the columns \n",
        "data.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AwCAzDk0y6C_",
        "outputId": "cb36afc2-0f1d-4d37-d0d5-a5933598968d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['State', 'Account length', 'Area code', 'International plan',\n",
              "       'Voice mail plan', 'Number vmail messages', 'Total day minutes',\n",
              "       'Total day calls', 'Total day charge', 'Total eve minutes',\n",
              "       'Total eve calls', 'Total eve charge', 'Total night minutes',\n",
              "       'Total night calls', 'Total night charge', 'Total intl minutes',\n",
              "       'Total intl calls', 'Total intl charge', 'Customer service calls',\n",
              "       'Churn'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#unique values for each columns\n",
        "data.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cZ0lVhZfy6GM",
        "outputId": "41e8200d-c165-4a39-b75e-3ef480a88027"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "State                       51\n",
              "Account length             212\n",
              "Area code                    3\n",
              "International plan           2\n",
              "Voice mail plan              2\n",
              "Number vmail messages       46\n",
              "Total day minutes         1667\n",
              "Total day calls            119\n",
              "Total day charge          1667\n",
              "Total eve minutes         1611\n",
              "Total eve calls            123\n",
              "Total eve charge          1440\n",
              "Total night minutes       1591\n",
              "Total night calls          120\n",
              "Total night charge         933\n",
              "Total intl minutes         162\n",
              "Total intl calls            21\n",
              "Total intl charge          162\n",
              "Customer service calls      10\n",
              "Churn                        2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Looking the description of the data to get the insight of the data\n",
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 379
        },
        "id": "kqrmhiezy6JW",
        "outputId": "b59fb71b-1b02-4e34-d785-d2e1f870c02e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Account length    Area code  Number vmail messages  Total day minutes  \\\n",
              "count     3333.000000  3333.000000            3333.000000        3333.000000   \n",
              "mean       101.064806   437.182418               8.099010         179.775098   \n",
              "std         39.822106    42.371290              13.688365          54.467389   \n",
              "min          1.000000   408.000000               0.000000           0.000000   \n",
              "25%         74.000000   408.000000               0.000000         143.700000   \n",
              "50%        101.000000   415.000000               0.000000         179.400000   \n",
              "75%        127.000000   510.000000              20.000000         216.400000   \n",
              "max        243.000000   510.000000              51.000000         350.800000   \n",
              "\n",
              "       Total day calls  Total day charge  Total eve minutes  Total eve calls  \\\n",
              "count      3333.000000       3333.000000        3333.000000      3333.000000   \n",
              "mean        100.435644         30.562307         200.980348       100.114311   \n",
              "std          20.069084          9.259435          50.713844        19.922625   \n",
              "min           0.000000          0.000000           0.000000         0.000000   \n",
              "25%          87.000000         24.430000         166.600000        87.000000   \n",
              "50%         101.000000         30.500000         201.400000       100.000000   \n",
              "75%         114.000000         36.790000         235.300000       114.000000   \n",
              "max         165.000000         59.640000         363.700000       170.000000   \n",
              "\n",
              "       Total eve charge  Total night minutes  Total night calls  \\\n",
              "count       3333.000000          3333.000000        3333.000000   \n",
              "mean          17.083540           200.872037         100.107711   \n",
              "std            4.310668            50.573847          19.568609   \n",
              "min            0.000000            23.200000          33.000000   \n",
              "25%           14.160000           167.000000          87.000000   \n",
              "50%           17.120000           201.200000         100.000000   \n",
              "75%           20.000000           235.300000         113.000000   \n",
              "max           30.910000           395.000000         175.000000   \n",
              "\n",
              "       Total night charge  Total intl minutes  Total intl calls  \\\n",
              "count         3333.000000         3333.000000       3333.000000   \n",
              "mean             9.039325           10.237294          4.479448   \n",
              "std              2.275873            2.791840          2.461214   \n",
              "min              1.040000            0.000000          0.000000   \n",
              "25%              7.520000            8.500000          3.000000   \n",
              "50%              9.050000           10.300000          4.000000   \n",
              "75%             10.590000           12.100000          6.000000   \n",
              "max             17.770000           20.000000         20.000000   \n",
              "\n",
              "       Total intl charge  Customer service calls  \n",
              "count        3333.000000             3333.000000  \n",
              "mean            2.764581                1.562856  \n",
              "std             0.753773                1.315491  \n",
              "min             0.000000                0.000000  \n",
              "25%             2.300000                1.000000  \n",
              "50%             2.780000                1.000000  \n",
              "75%             3.270000                2.000000  \n",
              "max             5.400000                9.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-20293e62-de3c-4717-b361-4ab41d3c8d83\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Account length</th>\n",
              "      <th>Area code</th>\n",
              "      <th>Number vmail messages</th>\n",
              "      <th>Total day minutes</th>\n",
              "      <th>Total day calls</th>\n",
              "      <th>Total day charge</th>\n",
              "      <th>Total eve minutes</th>\n",
              "      <th>Total eve calls</th>\n",
              "      <th>Total eve charge</th>\n",
              "      <th>Total night minutes</th>\n",
              "      <th>Total night calls</th>\n",
              "      <th>Total night charge</th>\n",
              "      <th>Total intl minutes</th>\n",
              "      <th>Total intl calls</th>\n",
              "      <th>Total intl charge</th>\n",
              "      <th>Customer service calls</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "      <td>3333.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>101.064806</td>\n",
              "      <td>437.182418</td>\n",
              "      <td>8.099010</td>\n",
              "      <td>179.775098</td>\n",
              "      <td>100.435644</td>\n",
              "      <td>30.562307</td>\n",
              "      <td>200.980348</td>\n",
              "      <td>100.114311</td>\n",
              "      <td>17.083540</td>\n",
              "      <td>200.872037</td>\n",
              "      <td>100.107711</td>\n",
              "      <td>9.039325</td>\n",
              "      <td>10.237294</td>\n",
              "      <td>4.479448</td>\n",
              "      <td>2.764581</td>\n",
              "      <td>1.562856</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>39.822106</td>\n",
              "      <td>42.371290</td>\n",
              "      <td>13.688365</td>\n",
              "      <td>54.467389</td>\n",
              "      <td>20.069084</td>\n",
              "      <td>9.259435</td>\n",
              "      <td>50.713844</td>\n",
              "      <td>19.922625</td>\n",
              "      <td>4.310668</td>\n",
              "      <td>50.573847</td>\n",
              "      <td>19.568609</td>\n",
              "      <td>2.275873</td>\n",
              "      <td>2.791840</td>\n",
              "      <td>2.461214</td>\n",
              "      <td>0.753773</td>\n",
              "      <td>1.315491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>408.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>23.200000</td>\n",
              "      <td>33.000000</td>\n",
              "      <td>1.040000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>74.000000</td>\n",
              "      <td>408.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>143.700000</td>\n",
              "      <td>87.000000</td>\n",
              "      <td>24.430000</td>\n",
              "      <td>166.600000</td>\n",
              "      <td>87.000000</td>\n",
              "      <td>14.160000</td>\n",
              "      <td>167.000000</td>\n",
              "      <td>87.000000</td>\n",
              "      <td>7.520000</td>\n",
              "      <td>8.500000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>101.000000</td>\n",
              "      <td>415.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>179.400000</td>\n",
              "      <td>101.000000</td>\n",
              "      <td>30.500000</td>\n",
              "      <td>201.400000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>17.120000</td>\n",
              "      <td>201.200000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>9.050000</td>\n",
              "      <td>10.300000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>2.780000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>127.000000</td>\n",
              "      <td>510.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>216.400000</td>\n",
              "      <td>114.000000</td>\n",
              "      <td>36.790000</td>\n",
              "      <td>235.300000</td>\n",
              "      <td>114.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>235.300000</td>\n",
              "      <td>113.000000</td>\n",
              "      <td>10.590000</td>\n",
              "      <td>12.100000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>3.270000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>243.000000</td>\n",
              "      <td>510.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>350.800000</td>\n",
              "      <td>165.000000</td>\n",
              "      <td>59.640000</td>\n",
              "      <td>363.700000</td>\n",
              "      <td>170.000000</td>\n",
              "      <td>30.910000</td>\n",
              "      <td>395.000000</td>\n",
              "      <td>175.000000</td>\n",
              "      <td>17.770000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>5.400000</td>\n",
              "      <td>9.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-20293e62-de3c-4717-b361-4ab41d3c8d83')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-20293e62-de3c-4717-b361-4ab41d3c8d83 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-20293e62-de3c-4717-b361-4ab41d3c8d83');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#total count of the churn \n",
        "data['Churn'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C-F1UGixy6Mb",
        "outputId": "4ebf5a06-9b29-45ed-9194-5f8d8521f7be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False    2850\n",
              "True      483\n",
              "Name: Churn, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There are 483 churning customers and 2850 non-churning customers. So the total count of churning customers is very low as compared to the non-churning customers.**"
      ],
      "metadata": {
        "id": "ThKFxFsP6t-e"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Checking Missing and Duplicate Values**"
      ],
      "metadata": {
        "id": "6Z6QXKvh7e8j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lyIvg9ksy6QD",
        "outputId": "6f01d33b-fc41-45f3-ef45-6ba63856d023"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "State                     0\n",
              "Account length            0\n",
              "Area code                 0\n",
              "International plan        0\n",
              "Voice mail plan           0\n",
              "Number vmail messages     0\n",
              "Total day minutes         0\n",
              "Total day calls           0\n",
              "Total day charge          0\n",
              "Total eve minutes         0\n",
              "Total eve calls           0\n",
              "Total eve charge          0\n",
              "Total night minutes       0\n",
              "Total night calls         0\n",
              "Total night charge        0\n",
              "Total intl minutes        0\n",
              "Total intl calls          0\n",
              "Total intl charge         0\n",
              "Customer service calls    0\n",
              "Churn                     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Percentage of missing values\n",
        "plt.figure(figsize = (16,5))\n",
        "missing_values = pd.DataFrame(data.isnull().sum()*100/data.shape[0]).reset_index()\n",
        "ax = sns.pointplot('index',0,data=missing_values)\n",
        "plt.xticks(rotation =90,fontsize =7)\n",
        "plt.title('Missing Values Percentage')\n",
        "plt.ylabel(\"PERCENTAGE\")\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "Yaa6g_Cey6TY",
        "outputId": "3d3aa009-7896-40c6-af23-f75303edfb0c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1152x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Checking duplicate Values\n",
        "len(data[data.duplicated()])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ncXkH0Kvy6ah",
        "outputId": "6484bda2-8107-4d14-d4bb-6b32cc539526"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There is no missing value in the overall data, and no duplicate values are present. Now we're going to start visualising the data in order to gain more insight from it.**"
      ],
      "metadata": {
        "id": "EzvXdGEn_fbM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Data Visualisation**"
      ],
      "metadata": {
        "id": "KkQMgHyhAOfK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data['Churn'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7om3frjky7Bf",
        "outputId": "0d83c8f5-3d0a-48f8-831c-e954f4350f83"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([False,  True])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Churn Percentage**"
      ],
      "metadata": {
        "id": "RdwR_eOxegbK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (10,8))\n",
        "data['Churn'].value_counts().plot.pie(explode=[0.05,0.05], autopct='%1.1f%%', startangle=100, shadow = True, fontsize = (12), cmap = 'Set3')\n",
        "plt.title('Churn Percentage')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 482
        },
        "id": "CBs5VTCNy7Ev",
        "outputId": "60cbb35d-5211-4b47-b225-de76228fb1bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(data['Churn'], palette = 'Accent')\n",
        "plt.title('Total count of Churn', fontsize = (13))\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "ZIfLfWd_y7If",
        "outputId": "42f766ec-912a-45ae-9b1c-6de833639654"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**According to the pie chart of churn, 15% of the customers are churned and 85% of the customers do not churn. So let's analyse the further columns to find the reason for the churn in customers.**"
      ],
      "metadata": {
        "id": "nSo-V2ZcdnN7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**State Wise Churn Rate**"
      ],
      "metadata": {
        "id": "MNjz3OQ1eoI7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "unique_state = data['State'].unique()"
      ],
      "metadata": {
        "id": "QLsCPAohy7Ln"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(unique_state)"
      ],
      "metadata": {
        "id": "VyG_89kLy7SU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "22a69a99-e0ac-43ae-fa8b-efc0fb8e0031"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (15, 10))\n",
        "sns.set(style = 'darkgrid')\n",
        "sns.countplot(data = data, x = 'State', hue = 'Churn', palette = 'flare')\n",
        "plt.title('State Churn Rate', fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "ngglfVC5y7ZN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 629
        },
        "outputId": "a659ddaa-1551-48ca-c0c7-3d43570c914d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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3WrVqq19/Per08i0Wi3r27CNfX1/5+fnf8/IyG2EQAAAAgJECAgroypXLSkhIsDtN4cKFrf/39/dXXFysw+lvV7BgIfn5+WXa8jIbYRAAAACAkapWra5cuXLp66+33tX8/v7+unnzpvXv6Ohom/EWi+Xui8sGhEEAAAAARsqXL5969uyr6dOnaPv2rbp586YSEhK0c+c3mjNnRrrzP/hgRf3nP+uVmJio7777Vj/8sC8bqs48hEEAAAAAxura9VkNGPCyPvhgvsLCmqtjx8e1YsW/9eijTdOdd9Cgofrmm6/VuvVj+s9/1unRR5tkfcGZiJ+WAAAAAJAj3etPS3gSfloCAAAAAOAUwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIB9XFwBkp0IBfvLx8001PCE2TjFXY11QEQAAAOAahEEYxcfPV/sHDkg1vObMKEmEQQAAAJiDMAgAAADAI9hrBXavPLUVGWEQAAAAgEew1wrsXjnbiqxz53by9fWVr6+fJKlWrYc1cOArdqedMuVtlStXITNLzRDCIAAAAABkkgkTIl0a8DKCMAgAAAAAWWDjxvVatmyJEhLiJUkvvTRYtWvXTTXdggXztGnTBvn6+slikWbOfFf58+fXTz8d1Ny5Ubpx44YkqVevvmrYsFGm1UcYBAAAAIBM8sYbr1mbiXbr9pzmzVski8WiP/44rkGD+mnlyi9tpr969Yr+/e9PtGrVevn5+euvv27I19dP165d07RpkzR16kwVKVJEFy9e1AsvdNfixZ8qf/78mVIrYRAAAAAAMsntzUQPHTqoIUP668KFC/Lx8dGlS9GKjr6owoWLWKfPmzefSpW6T+PHj1bduvXVsOGjypMnrw4e/FFnz57R0KEDrdNaLBadPn1SlSpVyZRaCYMAAAAAkAXGjBmp/v1fVuPGTZWUlKTmzRspLi7OZhpvb2+9++5C/fe/P2rfvj3q2fNZvfVWlJKTpfLlH9Ts2e9lWX1eWbZkAAAAADDY9evXFRRUUpK0du0XqYKgJP311w1dvnxZNWs+rJ49+6hcufL67bdjqlq1uk6d+kP79u2xTvvzzz8pOTk50+rjziAAAAAAj5AQG/f/PwOR+cu9GwMHDtHrrw9V/vz5Va9eQxUoUCDVNNevX9fIkcMUFxerpKQkVaxYSU2aPCY/Pz9Nnjxds2fP0IwZbykhIV4lS5ZSZOTbslgs97pKkiRLcmZGSzcUHX1dSUkevYrIgKJF86f52zM1Z0bpwoVrLqgIAAAAd+vcuRMqUaKMq8twC2ltCy8viwoXzmd3HpqJAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgfmcQAAAAgEcokN9Pvv6+mb7cuJtxunIt1uE0L7zwD8XHxyshIV4nT/6hBx4oL0mqWDFYr78+OtNrygyEQQAAAAAewdffV9ObDcr05Q7ZPENKJwy+994HkqSzZ8+oV69uWrToE5vxCQkJ8vFxr/jlXtUAAAAAgIfo3LmdmjVrqX37vle5chUUElJT3377tSZMmCJJ+vLL1TZ/f/TRIm3btkWJiYkqUqSYXnttpAoXLpJl9fHMIAAAAABkkRs3bui99xZrxIhRDqfbsOFLnT59Wu++u0gLFnysBg0e0axZ/8rS2rgzCAAAAABZpHXrx52abseO7frll5/Vo8ezkqTExATly5cvK0sjDAIAAABAVsmTJ7f1/97e3kpKSrb+HRf3v+cQk5OT9Y9/9FBYWHi21UYzUQAAAADIBqVK3adjx44qLi5O8fHx+uqrLdZxjRo11sqVn+nq1auSpLi4OB09eiRL6+HOIAAAAABkg6pVq6l27brq1u1JFSlSVBUqPKjo6IuSbjUnvXLlsgYM6C1JSkpKUocOT+jBBytmWT2W5OTk5PQny7mio6/b3IqF2YoWza/9AwekGl5zZpQuXLjmgooAAABwt86dO6ESJcpY/3bl7wy62p3bQpK8vCwqXNj+c4fcGQQAAADgEa5ci0339wDxPzwzCAAAAAAGIgwCAAAAgIEIgwAAAAByLA/vAsUpd7sNCIMAAAAAciQfH1/duHHV6ECYnJysGzeuyscn4x3n0IEMAAAAgBypUKGiiom5oOvXL7u6FJfy8fFVoUJFMz5fFtQCAAAAAFnO29tHRYoEubqMHItmogAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIHcIgx+9dVXioiIUHh4uNq3b6+NGzdKkn7//Xc99dRTatWqlZ566ikdP37ctYUCAAAAgIfwcXUBycnJGjZsmD7++GNVrFhRv/zyi7p27armzZtr9OjRevrppxUeHq5Vq1Zp1KhRWrx4satLBgAAAIAczy3uDHp5eenatWuSpGvXrqlYsWKKiYnRoUOHFBYWJkkKCwvToUOHdOnSJVeWCgAAAAAeweV3Bi0Wi/71r3+pX79+ypMnj27cuKF58+bp7NmzKl68uLy9vSVJ3t7eKlasmM6ePavAwEAXVw0AAAAAOZvLw2BCQoLeffddzZkzRw8//LD27t2rwYMHa8qUKZmy/MKF82XKcuD5ihbN7+oSAAAAgGzj8jD4888/688//9TDDz8sSXr44YeVO3du+fn56fz580pMTJS3t7cSExP1559/KigoKEPLj46+rqSk5KwoHTmQo8B34cK1bKwEAAAAyFpeXhaHN8dc/sxgiRIldO7cOf3222+SpGPHjik6OlplypRR5cqVtWbNGknSmjVrVLlyZZqIAgAAAEAmcPmdwaJFi2rMmDEaNGiQLBaLJGnSpEkqWLCgxowZo+HDh2vOnDkKCAhQZGSki6sFAAAAAM9gSU5O9ug2lDQTxe2KFs2v/QMHpBpec2YUzUQBAADgUdy+mSgAAAAAIPsRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQD6uLgDZo1CAn3z8fNMclxAbp5irsdlcEeBa9o4JjgcAAGAKwqAhfPx8tX/ggDTH1ZwZJYkPvzCLvWOC4wEAAJiCZqIAAAAAYCDCIAAAAAAYiDAIAAAAAAbimUEAAOAR6CwNADKGMAgAADwCnaUBQMbQTBQAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAM5OPqAgAAAOBZCgX4ycfPN9XwhNg4xVyNdUFFANJCGAQAAECm8vHz1f6BA1INrzkzShJhEHAXNBMFAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQHMk6gRyzAFscE3An7IwAAd4cw6AR6xAJscUzAnbA/AgBwd2gmCgAAAAAGIgwCAAAAgIEIgwAAAABgIJ4ZBAAA+H90SATAJIRBAACA/0eHRABMQjNRAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMJCPqwsAgLtRKMBPPn6+qYYnxMYp5mqsCyoCAADIWQiDAHIkHz9f7R84INXwmjOjJBEGAQAA0kMzUQAAAAAwEGEQAAAAAAxEGAQAAAAAA/HMIIBsZ6/zF4kOYAAAALILYRBAtrPX+YtEBzAAAADZhWaiAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCAfVxcA5CSFAvzk4+eb5riE2DjFXI3N5ooAALBl71rFdQpwHXc9LgmDQAb4+Plq/8ABaY6rOTNKEhdZAIBr2btWcZ0CXMddj0uaiQIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIHcojfR2NhYTZo0STt37pSfn59q1Kih8ePH6/fff9fw4cN1+fJlFSxYUJGRkSpbtqyrywUAAACAHM8twuDUqVPl5+enDRs2yGKx6OLFi5Kk0aNH6+mnn1Z4eLhWrVqlUaNGafHixS6uFgAAAAByPpc3E71x44Y+//xzDRo0SBaLRZJUpEgRRUdH69ChQwoLC5MkhYWF6dChQ7p06ZIrywUAAAAAj+DyO4MnT55UwYIFNWvWLO3atUt58+bVoEGD5O/vr+LFi8vb21uS5O3trWLFiuns2bMKDAx0cdUAAAAAkLO5PAwmJibq5MmTqlKlil577TX9+OOP6tu3r2bMmJEpyy9cOF+mLMeeokXzZ+nys4unrMe9yIxtwHZ0j+3o6vlzkqT4eHnlyuX08JzGpPcS6ePc4B7r4A41AO7ElceEy8NgUFCQfHx8rM1BQ0JCVKhQIfn7++v8+fNKTEyUt7e3EhMT9eeffyooKChDy4+Ovq6kpOR7qtHRG3ThwrV7WnZ2SW8nyynrca/u9b1kO97iDtsxK2sw5X2Ubm2H/QMHpBpec2ZUjtkOvJdI4Q7nFnfgDuvgDjUA7sRVx4SXl8XhzTGXPzMYGBioevXq6ZtvvpEk/f7774qOjlbZsmVVuXJlrVmzRpK0Zs0aVa5cmSaiAAAAAJAJXH5nUJLGjh2r119/XZGRkfLx8dGUKVMUEBCgMWPGaPjw4ZozZ44CAgIUGRnp6lIBAAAAwCO4RRi877779OGHH6YaXr58eS1btswFFQEAAACAZ3OLMAiYolCAn3z8fNMclxAbp5irsdlcEQAAAExFGASykY+fb5qddUi3OuyQCIMAAADIHi7vQAYAAAAAkP0IgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgXxcXUBWK5DPVz5+vmmOS4iNU8zV2GyuCAAyR6EAP85vgJuxd1xyTGYvzo+Aczw+DPr4+Wr/wAFpjqs5M0oSJwMAORPnN8D92DsuOSazF+dHwDk0EwUAAAAAAxEGAQAAAMBAhEEAAAAAMJDHPzMI98FD9QDuRCcPADwV5zdkpqz6HE0YRLbhoXoAd6KTBwCeivMbMlNWfY6mmSgAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIDqQAQAXoYddAADgSoRBAHARetgFAACuRDNRAAAAADAQYRAAAAAADEQYBAAAAAAD8cwgnGKvowuJzi5yGt7LzMF2BAAAOR1hEE6x19GFRGcXOQ3vZeZgOwIAgJyOZqIAAAAAYCDCIAAAAAAYiDAIAAAAAAZyOgzOnz8/zeELFy7MtGIAAMiJCgX4qWjR/Kn+FQrwc3Vp2cbeNjBtOwBATuJ0BzKzZ89Wz549Uw1/55139Pzzz2dqUQAA5CT2OhQyqTMhOlUCgJwn3TC4c+dOSVJSUpK+++47JScnW8edOnVKefPmzbrqAAAAAABZIt0wOHLkSElSbGysXn/9detwi8WiokWL6o033si66gAAAAAAWSLdMLhlyxZJ0rBhwzRlypQsLwgAAAAAkPWcfmbw9iCYlJRkM87Li05JAQAAACAncToM/vTTTxo3bpwOHz6s2NhbD4EnJyfLYrHo559/zrICcUuhAD/5+PmmGp4QG6eYqzyUDwCAJ7B3vZfMuua7w3Zwh89e7lADPJvTYXD48OF67LHHNGnSJPn7+2dlTUgDPdUBAOD56JX1FnfYDu7w2csdaoBnczoMnj59Wi+//LIsFktW1gMAAAAAyAZOP+zXokUL7dixIytrAQAAAABkE6fvDMbGxqp///56+OGHVaRIEZtx9DIKAAAAADmL02GwQoUKqlChQlbWAgAAAMBNuHNHPtlZgydzOgz2798/K+sAAAAA4EbcuSOf7KzBkzkdBnfu3Gl3XIMGDTKlGAAAAABA9nA6DI4cOdLm75iYGMXHx6t48eLavHlzphcGAAAAAMg6TofBLVu22PydmJiod955R3nz5s30ogAAAAAAWcvpn5a4k7e3t/r27av3338/M+sBAAAAAGQDp+8MpuWbb77hR+idQC9IAOC+OEcDAEzldBhs0qSJTfD7+++/FRcXp9GjR2dJYZ6EXpAAwH1xjgYAmMrpMDh16lSbv3Pnzq0HHnhA+fLly/SiAAAAAABZy+kwWLduXUlSUlKSLl68qCJFisjL664fOQQAAAAAuJDTae769esaNmyYqlevrsaNG6t69ep67bXXdO3ataysDwAAAACQBZy+MzhhwgT9/fffWr16tUqVKqXTp0/r7bff1oQJExQZGZmVNQIAgCxmryMdOtEBci536CCLc4t7czoMfv3119q0aZNy584tSXrggQf05ptvqkWLFllWHAAAyB72OtKhEx0g53KHDrI4t7g3p5uJ+vn56dKlSzbDYmJi5Oub9rcNAAAAAAD35fSdwc6dO6tHjx567rnnVLJkSZ05c0aLFi3SE088kZX1AQAAAACygNNh8MUXX1Tx4sW1evVq/fnnnypWrJh69epFGAQAAACAHMjpMDhx4kS1bdtWixYtsg7bt2+fJk6cqJEjR2ZFbQAAAABwT+jExj6nw+CaNWs0bNgwm2FVq1bVSy+9RBgEAAAA4JboxMY+pzuQsVgsSkpKshmWmJiYahgAAAAAwP05HQZr166tGTNmWMNfUlKSoqKiVLt27SwrDgAAAACQNZxuJjpy5Ej16dNHjRo1UsmSJXX27FkVLVpUc+fOzcr6AAAAAABZwOkwWKJECa1cuVIHDhzQ2bNnFRQUpOrVq8vLy+mbiwAAAAAAN+F0GJQkLy8v1ahRQzVq1MiicgD77PUEJdEbFICcjfMbAMAVMhQGAVey1xOURG9QAHI2zm8AAFegjScAAAAAGIgwCAAAAAAGIgwCAAAAgIF4ZhAAcNfo+MQ98D4AAO4GYRAAcNfo+MQ98D4AAO4GzUQBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQD6uLgAAAECSCgX4ycfPN9XwhNg4xVyNdUFFAODZCIMAAMAt+Pj5av/AAamG15wZJYkwCACZjWaiAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGMjH1QUAyJhCAX7y8fNNNTwhNk4xV2NdUBEAAAByIsIgkMP4+Plq/8ABqYbXnBkliTAIAAAA57hVM9FZs2YpODhYR44ckST98MMPat++vVq1aqUePXooOjraxRUCAAAAgGdwmzD4008/6YcfflCpUqUkSUlJSXr11Vc1atQobdiwQbVr19a0adNcXCUAAAAAeAa3CINxcXEaN26cxowZYx128OBB+fn5qXbt2pKkLl26aP369S6qEAAAAAA8i1uEwRkzZqh9+/YqXbq0ddjZs2dVsmRJ69+BgYFKSkrS5cuXXVAhAAAAAHgWl3cgs3//fh08eFBDhw51yesXLZrfpfNTQ+bMTw2ZMz81ZM781OA+NXjCOrhDDZ6wDu5QgyesQ2bwhO3gCevgDjV4wjpkBleug8vD4Pfff69jx46pWbNmkqRz586pZ8+e6tatm86cOWOd7tKlS/Ly8lLBggUz9fUvXLiW7jSONvC9zp9TavCEdXCHGjxhHUyowRPWIafU4Anr4A41eMI6mFBDTlmHzODq7eAO29ETavCEdciMGjKDq84tXl4WFS6cz/74dF85i/Xu3Vs7duzQli1btGXLFpUoUULz589Xr169dPPmTe3Zs0eStHTpUrVu3drF1QIAAACAZ3D5nUF7vLy8NGXKFI0ePVqxsbEqVaqUpk6d6uqyAAAAAMAjuF0Y3LJli/X/tWrV0urVq11YDQAAAAB4Jpc3EwUAAAAAZD/CIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABvJxdQEAAAAA4K4KBfjJx883zXEJsXGKuRqbzRVlHsIgAAAAANjh4+er/QMHpDmu5swoSTk3DNJMFAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAP5uLoAAAAAuI9CAX7y8fNNc1xCbJxirsZmc0UAsgphEAAAAFY+fr7aP3BAmuNqzoySRBgEPAXNRAEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMJCPqwuIiYnRsGHD9Mcff8jX11dlypTRuHHjFBgYqB9++EGjRo1SbGysSpUqpalTp6pw4cKuLhkAAAAAcjyX3xm0WCzq1auXNmzYoNWrV+u+++7TtGnTlJSUpFdffVWjRo3Shg0bVLt2bU2bNs3V5QIAAACAR3B5GCxYsKDq1atn/btGjRo6c+aMDh48KD8/P9WuXVuS1KVLF61fv95VZQIAAACAR3F5M9HbJSUlacmSJQoNDdXZs2dVsmRJ67jAwEAlJSXp8uXLKliwYKa9ZtGi+V06PzVkzvzUkDnzU0PmzE8N7lODJ6yDO9TgCevgDjV4wjpQQ+bMTw2ZMz813Pv8bhUGx48frzx58ujZZ5/Vf/7zn2x5zQsXrqU7jaMNfK/z55QaPGEd3KEGT1gHE2rwhHXIKTV4wjq4Qw2esA4m1OAJ65BTavCEdXCHGjxhHUyowdH8Xl4WFS6cz+54twmDkZGROnHihObOnSsvLy8FBQXpzJkz1vGXLl2Sl5dXpt4VBAAAAABTufyZQUmaPn26Dh48qNmzZ8vX11eSVLVqVd28eVN79uyRJC1dulStW7d2ZZkAAAAA4DFcfmfw6NGjevfdd1W2bFl16dJFklS6dGnNnj1bU6ZM0ejRo21+WgIAAAAAcO9cHgYffPBBHT58OM1xtWrV0urVq7O5IgAAAADwfG7RTBQAAAAAkL0IgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBXN6bqOkS4uJVtGj+VMPjbsbpyrVYF1QE4F5xXAMAgJyAMOhiPr65NL3ZoFTDh2yeIfGhEciROK4BAEBOQDNRAAAAADAQYRAAAAAADEQYBAAAAAADEQYBAAAAwEB0IAMAALIUPewCgHsiDAIAgCxFD7sA4J5oJgoAAAAABiIMAgAAAICBCIMAAAAAYCCeGQQAAMhi9jrRkehIB4DrEAYBAACymL1OdCQ60gHgOjQTBQAAAAADEQYBAAAAwECEQQAAAAAwEM8MAsg0dJAAAHCE6wTgXgiDADINHSQAABzhOgG4F5qJAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAaiAxkAVvZ6eaOHN9wN9icAnsgdekR1hxrcAdeZe0cYBGBlr5c3enjD3WB/AuCJ3KFHVHeowR1wnbl3NBMFAAAAAAMRBgEAAADAQIRBAAAAADCQ0c8M8tApAAAAkP3oBMc9GB0GeegUAAAAyH50guMeaCYKAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGMjoDmQAAAAAwFVc3asqYRAAAAAAXMDVvarSTBQAAAAADEQYBAAAAAADEQYBAAAAwEA8M4h75uoHXwEAns0drjPuUAMyB+8l8D+EQdwzVz/4CgDwbO5wnXGHGpA5eC+B/6GZKAAAAAAYiDAIAAAAAAYiDAIAAACAgXhm8B7wALLn4L0EAHg6rnUA7kQYvAc8gOw5eC8BAJ6Oax2AO9FMFAAAAAAMRBgEAAAAAAMRBgEAAADAQIRBAAAAADAQHcjkcPQM5j7svRe8DxnDdswcbEfPOT/yXiKFO+wL7lADgMxDGMzh6BnMfdh7L3gfMobtmDnYjp5zfuS9RAp32BfcoQYAmYdmogAAAABgIMIgAAAAABiIMAgAAAAABuKZQfAwODyKJ3Qa4gnrAPfB/gRPw+cW98C55Zacvj8SBsHD4PAontBpiCesA9wH+xM8DZ9b3APnllty+v5IM1EAAAAAMBBhEAAAAAAMRBgEAAAAAAMRBgEAAADAQHQgA5ejNyoAQFbL6T3+AUBWIAzC5eiNCgCQ1XJ6j38AkBVoJgoAAAAABiIMAgAAAICBCIMAAAAAYCCeGQTcBB3pAABgBjo0QmZJ7/PjtRtxDucnDAJugo50AAAwAx0aIbOk+/kxnTBIM1EAAAAAMBBhEAAAAAAMRBgEAAAAAAPxzCAA3IaOfNyHJ7wXnrAOADwTndhwjpYIgwBgg4583IcnvBeesA4APBOd2HCOlmgmCgAAAABGIgwCAAAAgIEIgwAAAABgIMIgAAAAABiIDmTgEegRC8hc9LAGAIDnIwzCI9AjFpC56GENAADPRzNRAAAAADAQYRAAAAAADEQYBAAAAAAD8cwg4CHo8APIfHROxbkFADwZYRDwEHT4AWQ+Oqfi3AIAnoxmogAAAABgIMIgAAAAABiIMAgAAAAABiIMAgAAAICBCIMAAAAAYCDCIAAAAAAYiDAIAAAAAAYiDAIAAACAgQiDAAAAAGAgwiAAAAAAGIgwCAAAAAAGcvsw+Pvvv+upp55Sq1at9NRTT+n48eOuLgkAAAAAcjy3D4OjR4/W008/rQ0bNujpp5/WqFGjXF0SAAAAAOR4Pq4uwJHo6GgdOnRICxculCSFhYVp/PjxunTpkgIDA51ejq+DaQOKpz3Oy8vi1DLszX/nMjyhhruZ39llsB0zpwaTtmNW1uAJ65CTauCYyJwa2I7uX4MnrENOqoFjInNqYDu6fw3Ozp8WS3JycrLDKVzo4MGDeu2117R27VrrsLZt22rq1Kl66KGHXFgZAAAAAORsbt9MFAAAAACQ+dw6DAYFBen8+fNKTEyUJCUmJurPP/9UUFCQiysDAAAAgJzNrcNg4cKFVblyZa1Zs0aStGbNGlWuXDlDzwsCAAAAAFJz62cGJenYsWMaPny4rl69qoCAAEVGRqpcuXKuLgsAAAAAcjS3D4MAAAAAgMzn1s1EAQAAAABZgzAIAAAAAAYiDAIAAACAgQiDAAAAAGAgI8JgaGiojhw5Ikn6+++/1bNnT40YMUK//PKLunXrpvDwcLVt21ZdunTRxYsXbeaNi4vT5MmT1bx5c7Vu3VoRERHatGmTJGnXrl3q2LGjzfRHjhxRaGio3TrCwsKUlJSUqrbhw4fro48+srsOGanjwIEDaty4sb766qtUy7ly5YqqV6+uCRMmWIetWLFCAwcOtPvaKXU2atTI+puPKfMFBwfb1D116lRVrVpV0dHRGZp3z5496tq1q1q1aqVmzZppxIgRunLlSpp1pLyXdxo8eLDq16+v+Ph4m+Fvv/22Ro8ebf37q6++UnBwsI4ePWod1qdPH1WvXl3bt2+3mffGjRuqVauWTp06lWYdw4cPV7Vq1XTmzBnruPTey9uX0bp1a7Vv315t2rTRsmXLJKW9X9mb//Zt8cQTTyg8PNyp+ey9Hx9++KHCw8MVHh6uunXrqnHjxta/f/zxR5tlpLUvz5o1S126dLEZPnv2bA0ePNjhOgwfPlyNGzdWRESEWrZsqa5du+rzzz+3uw69evXSkiVLbIYlJycrODhYwcHB6dZvb/5mzZpp9+7d2rZtm4KDg/Wf//zHbg0p27tt27aqUqWK9XW6deum0NBQXbt2zTptz549tXjxYrvboHXr1tb5J02apKioKEVGRtp97RTx8fGaMWOGWrVqpXbt2ikiIkKTJ09WfHy8jhw5op49e6pFixZq1qyZBg4cqLNnz6a5nLTOCy+88IK1ppR/lSpVSrXdJGndunWKiIhQeHi4WrdurVdeeSXd+m5ff0fnxdvfw/DwcK1fv946nTPHdu/evRUcHKxPPvnEOiwuLk6PP/64tm3bluq9uPP80rFjR+3atcvp9+TO+p09F2Tk2hAZGamoqKhUy4mPj1dUVJRatWqlxx9/XO3bt9fAgQP166+/WqdJ6xx9O2euEV999ZUaN26sAwcO2NTr6Dy/YsUK1a5dWxEREWrTpo3at2+vWbNm6ebNm07XULt2besx17t3b124cCHVvM6e75ctW6bg4GDduHEj1TLSu96GhIQoPDxcYWFhevbZZ3Xs2LFUy3Bme9i77t5+bWjRooVefPFF7du3L9V2SPk3bdq0VMtIa93q1aunU6dO6aWXXrLOGxwcrHbt2ik8PFw9e/a0mT694/eTTz5RcHCwDh06lOF1Dw4O1pdffmkzPq3tYe/c4mgb3V6HveNKkr744gtFRESodevW6tixo15++WXrtTwj+5GU9vU3veP6zuWdPHlSlSpVstkOjq61L7/8cqrtNXz4cM2aNStVHY621YEDB/T888+refPm6tSpk7p3767vv/8+1TLu/BzdrVs3ffzxx9ZpHJ1XnTk3ONqn01vGlStXNGTIEIWFhVn35507d1qndXS9Dg4OtnmvT506pXr16qXatnduy7CwMK1du1bSrV8+CA4O1qJFi9Kc73ZpHVcRERF6/PHHFR4erkceeUQNGjSw1pjyOcSZa6Wzn6Hu5OP0lB7g6tWr6t27t6pVq6bXX39dYWFhGjp0qB577DFJ0vHjx5U7d26becaMGaO//vpLa9eulZ+fn44cOaJevXqpQIECd1XDX3/9pVWrVqlDhw4Zms/ZOnbu3Klhw4bprbfeUt26dVMtZ82aNQoJCdHatWs1bNgw+fr6Ol1DsWLFtGPHDjVp0kSStHLlSj300EPW8YmJiVq1apVq1aqlVatWqUePHk7Ne+LECfXv318zZ85U3bp1lZSUpMmTJ2vQoEFOHViSdPnyZX377bd64IEHtGXLFrVq1co6rn79+ho3bpz17927dyskJES7d+/Wgw8+qMTERO3du1f9+/fXypUr1bhxY+u069evV7Vq1VS6dGm7r120aFFFRUXpzTffdKrW282cOVMVK1bUkSNH1LFjR5vXzoijR4/q4sWLypUrlw4ePKiqVas6nN7e+2GxWLRq1SpJty4qVatW1bPPPpvmMtLal1u2bKmffvpJCxcuVM+ePXX48GEtW7ZMK1euTHcdevfubX2tn3/+WYMHD1ZMTIyef/75VNN26tRJCxcuVNeuXa3Ddu3apfvvv18bN26UxWJxWL+9+b28vFSnTh0NGjRI9evX1/Lly9WiRYs06035EHDq1Cl16tTJut0kadKkSZo0aZLefPNNLV26VHFxcerWrZvddU/ZD1Kk9UE/LSNGjFBsbKyWL1+ufPnyKSEhQcuXL9fFixf1/PPP64033lCbNm0kSYsWLVKPHj30xRdfKFeuXDbLSeu88N5779lMM2/ePHl7e6f6ouLPP//U2LFjtXLlSgUFBSk5OVk///yzw/ri4uJsanB0Xrx9v7iTM8f2vn379OGHH+qVV15R48aNVbp0aUVFRalGjRrW/d8d3O214XYjRozQzZs3tWzZMgUEBCg5OVnbtm3T77//rgoVKjg8R6dI7xqxevVqTZ8+XfPnz9eDDz5oMy69a0TDhg01c+ZMSVJ0dLRGjhypwYMHa+7cuU7VkDJ/cnKyhgwZolmzZmns2LE28zp7vh85cqTd7Zje9bZ8+fJasWKFpFvh+s0339T777+fajnpbQ9Hbj8nbNy4Ub1799b8+fNTbce7MXv2bOv/g4ODtXTpUuXNmzfVdOkdv8uXL7eeJ6tUqWIzb3rrXqpUKc2YMUMtW7aUj0/aH0UdnVsk+9soJCTEOo2942rZsmVauHCh5syZo7Jly0q6dQ24ePGiSpYsmaH9yNH119Fx/dBDD2nlypUaNmyYdRvduR3tLaN+/fqaP3++9WfXpFtfXm/cuFGrV69OtQx728rf3199+vTRlClT9Oijj0qS/vjjD5vtfLvbP0c/99xz6tKli5o0aZLueTUj5wZ7HC3jX//6l4oXL6633npLFotFMTEx+vvvv63z2rtenzp1Su3atdPmzZvVs2dP3X///Q5ruH1bHjp0SF26dFGDBg302WefWY+F5557zuH89o6rsLAw5c2bV1FRUfrrr7/02muvpZrX2Wtlep+h7mTEnUHp1oWne/fuatiwoUaOHCmLxaJz586pePHi1mnKli1rc0I8ffq01q1bpzFjxsjPz0+SVLFiRfXt2zfVNy/O6t+/v2bNmqW4uDin53G2ji1btui1117TnDlz0gyCkrR8+XL169dPwcHB2rx5c4Zq79Chg/UCePLkSf311182H2C3bdum+++/XwMHDrRO58y8c+fOVefOna01e3l56dVXX9Xvv/+uPXv2OFXb6tWr1aRJEz399NNavny5zbiaNWvq1KlT1ru+33//vfr166ddu3ZJkg4dOqR8+fKpY8eO2rp1q80dyRUrVqhTp04OX7tLly765ptvbL59z6iKFSsqICBA58+fv6v5ly9frvDwcEVERKRa/7Sk9146w96+PH78eH3wwQc6cuSIRowYoTfeeEOFChXK0LIrV66skSNH6r333lNav37TrFkznThxwuYb+RUrVqhjx46yWCzpLt/R/JcvX9Z3332nt956S/v370/z7kN6hgwZon379unjjz/WrFmzNGnSJKfqyojjx49r06ZNmjBhgvLlyydJ8vHx0VNPPaXly5erbt261iAoSc8995zy5ctn/SbzdumdF3bu3KlFixYpKirKeg5KcfHiRfn4+KhgwYKSJIvFoipVqjis784PnndzXpScP7br1q2rgQMH6vXXX9eBAwe0bt06jRgxIkOvldXudhukSNneEydOtH44tFgsatq0qfULDUfn6BSO9oUlS5Zo5syZWrx4caogKGXsvFK4cGFFRkZq586dNndH0qshZb3q1KmT5p1uZ/cJex/6Mnrdr1u3rt077plxnpVufcnWpUsXaxjMDukdv0eOHNGlS5c0ceJErV27NtV+m966V61aVQ888IA+++wzuzXYO7ekxd42sndczZo1SyNGjLAGQenWndPq1atLyth+5Oj66+i4bt26tTZv3qzExEQlJydr7dq1CgsLSzVdWssICAhQvXr1tGbNGuuwdevWKSQkRKVKlUpzG6W1rd577z117tzZGgQl6f7777f5Qj3FnZ+jS5Uq5fR5NTOOBUfLSPk8n3KdLVSokEqWLOnUcn19fdWjRw/961//ylA9VapUUd68eXXq1CmtXr1a48aNU2xsrE2LiTtl5LqYFmevE+l9hrqTMWFw8ODBeuyxx2xuv/ft21fPPPOMevTooZkzZ6Zq6nHkyBHdf//91hNRiho1auiXX36RdOvW8O23ttNrblm1alU99NBDaTa1sseZOk6cOKGhQ4dq/vz5qlatWprL+eWXX3T58mXVr19fHTt2dCo03K5u3bo6cuSIrly5opUrVyoiIsJm/PLly9WxY0fVrl1b8fHxNs3yHM17+PBh1ahRw2ZZuXLlUpUqVazrl56U127ZsqV++OEHm1Dl7++v6tWra/fu3bp+/br+/vtvPfroo9Zl7969W3Xr1lWRIkVUv35968n1xIkTOnLkiFq2bOnwtfPkyaM+ffro7bffdqrWtOzdu1eFChVSpUqVMjxvfHy8Vq9erY4dO6pDhw768ssvFRsb63Ce9N5LZ9jbl4sUKaLhw4era9euqlChgpo3b57hZUtSSEiIoqOjdenSpVTjfH191a5dO+s+fP36dW3atMnpuyqO5v/iiy/UtGlTFSlSRC1atHDqruad/P39NXr0aI0bN069e/fWfffd53D6gQMHWs8hX3/9tVOvcejQIZUpUybNVgpHjhyx+XY8RUhIiA4fPmwzLL3zwpkzZzR06FBNnTo1zQ8ZlSpVUvXq1dW0aVMNHDhQixYtUkxMjMP67uTovDhv3jybc+zt31g7e2xLt5oJ+fr6qmfPnho/frz1Qnyn29+L8PDwNJsAZoWMbIO0mv84s70dnaMlx/vCrl27NHv2bH300Ud29+eMnlcKFCigMmXK2IRBZ65TcXFx2r59u9q2bZtqXEb2ibQ4c71NkZSUpM2bN6dZh5Q559kUISEh1i8cv/32W5v9IeWuR2ZKb3/67LPPFBERodKlS6ty5crWZrQpnFn3l19+We+8806aTYUl++cWe27fRinSOq6uXLmic+fOpXmOTOHsfpTe9dfRcZ0nTx7VqFFDO3bs0K5du1SxYsVU+52jZXTq1MnmSx1nvrxOkbKtDh065HA73C6tz9HOnlfT2x+c2acdLaN79+6aPXu2OnfurIkTJ9o0EXXGM888o/3799u9I5qW7777TrGxsTp27JjKlCmjMmXKqEOHDg4/W2fkupiWjGQIR5+h7mRMGGzSpIm+/PJLm5DwwgsvaP369QoPD9eZM2fUqVMnm3bSzqTp8uXLa9WqVdZ/zjTdGDx4sN577700n1VIizN1FC1aVOXLl9fSpUvtTvPZZ58pPDxcFotFLVu21IEDBzJ0J8pisahNmzZau3Ztqm+woqOjtXv3brVu3VqSUn1D5mjee3Xo0CFdvXpV9evXV+7cudWyZctUH5bq1q2rXbt2ae/evXr44Yfl7e1t/RCye/dua/vw20+uK1asUNu2beXv759uDU8++aQOHz6c6sNVegYOHKhWrVrp2Wef1aBBgzLUbDfF1q1bVbZsWd1///0KCgpSlSpVHD7rJmXe+2FvX27btq3y5cuXZjM0Z6W333fu3FlffPGFEhMTtW7dOtWqVUslSpRwevn25l+xYoU1VN7+TWRGbdq0SSVKlHDq4jJz5kzrOeT2b2jvljPnjBSOzgtxcXEaMGCAunfvrkceeSTN+b28vDRnzhx9+OGHqlevnrZt26b27dtnuGZ7+1Lv3r1tzrGVK1e2Ge/ssS3denazVKlSatCggd06bn8vVq1apfLly2d4Xe6Ws9vAmVDx66+/Kjw8XK1atdKECRPSPUdLjveFBx54QLlz57a5E3Gnuzmv3LmvOqoh5QNjgwYNdOnSJZs737fLyD6RXj1pSfkSuGHDhvr222/19NNPpzldZl73bq+rYcOGNvvDE0884fRyMqOFQnx8vNasWWNznrxzX3Jm3YODg1WnTh19+OGHab6OvXPL5cuX05ze3nuX0c9cKZzZj5y5/jp6/Q4dOujzzz/XypUrHX6ZmdYymjZtqjNnzujo0aM6fvy4fv31V7uPNdwpI9eIFGl9jpacO6+mtz84s087WkaDBg301Vdf6cUXX1SuXLk0ePBgzZs3z+l18/PzU79+/TR9+vR0p035wjAqKkpRUVHauHGj9b2LiIjQ+vXr0/1C/l44uz9n5D02Jgz26tVLHTt2VPfu3W125OLFiys8PFyTJ09WeHi4NmzYYB1XsWJF/fHHH6lOPD/88IOCg4PvupZy5cqpSZMmWrhwoVPTO1NHnjx5tGDBAv34448aP358qmXExcVpzZo1Wr58uUJDQ9W2bVvFx8dn+INuhw4drO2lb2/6t2rVKiUkJKh9+/YKDQ3VkiVLtG7dOptv/OzNGxwcrB9++MHmdeLj43Xo0CGntvPy5ct19epVNWvWTKGhodq6dWuq9apXr552796t77//XnXq1JEk1alTRzt37tTevXut3xQ3bdpU586d0y+//KJVq1Y5/S1brly5NGDAAKdOJLebOXOmNmzYoOnTp2vEiBGpOjByxvLly/Xrr78qNDRUoaGh+vnnn51uKprW+5ERjvZlb29veXnd/Snmv//9rwoXLqzChQunOb5SpUoqVqyYtm/fruXLlzv9Xjma/+DBg/r11181cuRIhYaG6tVXX9WpU6e0d+/eDC17165d+vrrr7Vy5Urt378/VcdEmaFKlSo6ceJEmh0tBQcHp/nFxIEDB2yOqfTOC2PHjlVQUJB69+6dbj0VK1bUM888o4ULFyp//vw6deqU3frSktHzYgpnj23p1ofLe9kns9rdbgPpf/vD1atXJUkVKlTQqlWr1K1bN12/fj3dc3R6+0KxYsX04YcfaunSpQ6bK2bkvHLlyhX98ccf1qZe6dWQ8oFx27ZtslgsmjFjRprLzcg+cSdnrrcpXwJv375dlSpV0pgxYzJlezjy3//+N82mufYEBgbarENCQoKuX7+uwMBAp+Z3dH7ZsmWLrl27pueee06hoaGaPn26du3alaq5rDPrntI3wO0dbt3pznPL7t2705zO3ja687gqUKCAihcv7rA5n+TcfuTM9dfRcV2vXj398ssv2rt3r8M+A9JaRq5cudS+fXutWLFCK1eu1OOPP56qGb89KduqSpUq6W6HFPY+Rzt7Xs2MY8HRMvLly6dmzZpp2LBhGj16dJrPTjrSsWNHnTx5Mt3Hk1K+MPz4448VHBysHTt2aNasWQoNDdUzzzyjv//+2yZL3M7RceUsZ68T6X2Gup37XhWzQJ8+fdShQwfrjrxp0yZrz0SxsbH67bffbDoKKV26tFq3bq0xY8ZYU/6RI0c0d+5c9e/f/55qGTBggD755BOnvqlyto78+fNr4cKFaQbCzZs364EHHtD27du1ZcsWbdmyRQsWLMhwE7j77rtPL7/8svr162czfMWKFZo9e7Z12du3b1f16tVtev6zN2/v3r21bNky6wk+KSlJU6dOVZkyZawnYHtu//CQ8to7duyQJJsDumbNmjp9+rQ2btxo/SBQu3ZtffzxxwoICLA2e/Lx8VH79u01cuRI5c+f3/r8gDPatWunS5cu2b1QOdKmTRs98sgjevfddzM039WrV7V7925t3rzZuv7btm3TwYMHbXo4TYu99yOjMrIvO+uXX37RpEmT9MILLzicrlOnToqKitLx48fVrFmzDL/OnfMvX75cvXr1sm7LLVu2aMCAARlqUn3jxg2NHDlSEyZMUGBgoCZNmqQxY8bo+vXrGa7PkbJlyyo0NFSjRo2yLjsxMVHLli2z9oC5bt066/SLFi3S1atX9fjjj1uHOTovfPrpp9q7d68mT57s8G7C+fPntX//fuvf586d06VLl9SoUSO79dnbV+5mX3L22M4p7vZ4Klu2rJo1a6Y33njD5oP1X3/9JSn9c7Qz14gSJUpo8eLFWrJkid1A6Ox55dKlS3r99dfVoEEDVahQwekapFsf+saOHaslS5bozz//TLXse9knMnLd9/X11ZgxY/T111+n6lEzo9vDkU2bNmnJkiUZamnRsGFDffrpp9a/P/30U4WEhKTqJM8eR+eXTz75RKNGjbK+R1u3blXHjh1TfQnrzLrfd999atWqlT744INU4+ydW9Lq0C29bXTncdWvXz9NnjxZf/zxh3Wa77//3iYYpbcf+fv7O339tXdcWywWjRgxQiNGjLDbkY6jZXTq1ElffPGFPv/8c6e/EL19W/Xq1Uv//ve/9e2331rHnzx50m6YufNzdEZkxrFgbxnffPONdT9NTk7WoUOHHHb8lxZvb28NHjw4Q50zff7552rVqpW2bt1q3QcmTZpk9zODo+MqI+f89K4Tzn6GSmFUb6LSrecEk5OT1b17dxUvXlxTp06Vn5+fEhIS1LBhQz3zzDM2048ePVrTp09X27ZtlStXLvn5+WnkyJHW5gN3q0SJEgoPD9eCBQsk3frWztE3Os7WkT9/fi1YsEDPP/+8xo8fr3/+85+Sbt09ateunc0ya9asqaSkJJ05c0bbtm2z+VaqY8eOdn8O4KmnnrL5+/Lly9ZnPG53+zNZ9uaVbjU/ioqK0vTp0xUTE6P4+HjVrVvX7gH5/PPPy9vb2/raQUFBKlOmTJqvXbt2bUm3mgCEhITo/Pnz1k6DqlWrpvPnz1ubTaXo3LmzFixYkOEOJry8vDRkyBD17ds3Q/OleOWVV9SxY0en2+9Lt9qsN27c2Kadvp+fn5o3b64VK1ak+6VFWu9HRt25L9+tefPmadmyZbp586YCAwPVp0+fdJvDhYWFKTIyUk8++eRdNbG9ff6UB/jvbIsfFham9u3b64033lCePHnSXebUqVP16KOPWpui1apVSy1bttTkyZNtuspPz9KlS206e+nXr5+6dOliM83kyZM1e/ZsderUSbly5VJSUpKaNGmiiIgILViwQFOmTNFbb72l5ORkVa5cWfPnz7fpxdPReWHUqFEqXrx4qnNiu3bt1KtXL+vfCQkJioqK0unTp+Xv76+kpCQNHjxYVapUsVufvfcqrX0pZb9I0aVLF5teYDNybLvCjBkzbJorjR8/3mEvpvdyPL355puaM2eOOnfuLB8fHwUEBKhYsWLq0aOHXnrpJbvn6JQmo46uESmCgoL04YcfWnvHvfPnCCT755Vvv/1WERERunnzpnx9fdWiRQubDyvO1iDdurPfunVrvffee6l6Br3XfSIj1/0iRYqoR48emjVrlubMmZPm8u7mPDtw4ED5+vrq77//Vvny5TVv3jyFhITo2LFj1uayKapWraqJEyfazD9y5EhNnDhR7dq1k5eXl4KCgjRlypQM1ZDW8RsSEqIff/wxVY/H7dq104gRI1J9SHdm3fv165fmF9OOzi2S/W2UljuPqy5dusjf318DBw7UzZs35eXlpUqVKunVV1+1zpPefpTS+7i966+j17+ds72Ip7WMBx98UCVLllRsbKzDXsQdbau5c+fq7bff1qhRo5Q7d24VKlTIYf8Xt3+OtveTSfY4Ojekt087Wsbhw4c1efJka9PIMmXKaNSoURmqTZL1nOJsMFuxYkWqXj+bNWum0aNH69SpU2kG0oxeF9Pi6FqZkc9QKSzJd9NwGJkqMTFRHTp00BtvvOGw+QoAAAAAZBajmom6o3379iksLEwhISEEQQAAAADZhjuDAAAAAGAg7gwCAAAAgIEIgwAAAABgIMIgAAAAABiIMAgAAAAABiIMAgCQjj179qhLly56+OGHVbduXXXp0kUHDhzQihUrbH73MD2nTp1ScHCwEhISsrBaAACcY9yPzgMAkBHXr19X3759NWbMGLVp00bx8fHas2dPhn4kGAAAd8SdQQAAHPj9998lSWFhYfL29pa/v78aNWqkXLlyafTo0frhhx9Us2ZN1a5dW5K0detWRUREqFatWmrSpImioqKsy3r22WclSXXq1FHNmjW1f/9+SdJnn32mNm3aqE6dOurZs6dOnz6dzWsJADARvzMIAIAD169fV7NmzdS0aVO1bdtWNWrUUIECBSRJK1as0LJly7RkyRLr9Lt27VLBggX14IMP6siRI+rRo4fGjRun5s2b69SpU2rWrJl++ukn+fjcapyzadMmRUZGau7cuSpTpozmzZun7du3a+nSpS5ZXwCAObgzCACAA/ny5dMnn3wii8Wif/7zn2rQoIH69u2rixcvpjl9vXr1FBwcLC8vL1WqVEmPP/64du/ebXf5S5cuVe/evVW+fHn5+Piob9+++vnnn7k7CADIcjwzCABAOsqXL6/JkydLko4dO6ZXX31VkyZNUqNGjVJN++OPP2ratGk6evSo4uPjFRcXp9atW9td9pkzZzRp0iRFRkZahyUnJ+v8+fMqVapU5q8MAAD/jzAIAEAGlC9fXh07dtSnn36qRx99NNX4V155Rc8++6zef/99+fn5aeLEiYqJiZEkWSyWVNMHBQWpb9++at++fZbXDgDA7WgmCgCAA8eOHdOCBQt07tw5SdLZs2e1Zs0ahYSEqHDhwjp//rzi4uKs09+4cUMFChSQn5+fDhw4oDVr1ljHBQYGysvLSydPnrQO69Kli+bNm6ejR49Kkq5du6Z169Zl09oBAEzGnUEAABzIly+ffvzxRy1cuFDXrl1T/vz59dhjj2nYsGHy9fVVhQoV1KhRI1ksFu3atUujR49WZGSkxo0bp7p166pNmza6evWqJCl37tzq27evunbtqoSEBL3//vtq0aKFbty4oSFDhuj06dPKnz+/GjZsqDZt2rh4zQEAno7eRAEAAADAQDQTBQAAAAADEQYBAAAAwECEQQAAAAAwEGEQAAAAAAxEGAQAAAAAAxEGAQAAAMBAhEEAAAAAMBBhEAAAAAAMRBgEAAAAAAP9H0Oszi7WJz75AAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Average Churn Rate of State**"
      ],
      "metadata": {
        "id": "i0cN-boU0aJ-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "highest_churn_state_1 = (data.groupby('State')['Churn'].mean()*100).sort_values(ascending = False).reset_index()\n",
        "highest_churn_state_1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "BPltGynU9Rul",
        "outputId": "068db072-f943-4413-cec6-36df5d5c4e76"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   State      Churn\n",
              "0     NJ  26.470588\n",
              "1     CA  26.470588\n",
              "2     TX  25.000000\n",
              "3     MD  24.285714\n",
              "4     SC  23.333333\n",
              "5     MI  21.917808\n",
              "6     MS  21.538462\n",
              "7     NV  21.212121\n",
              "8     WA  21.212121\n",
              "9     ME  20.967742\n",
              "10    MT  20.588235\n",
              "11    AR  20.000000\n",
              "12    KS  18.571429\n",
              "13    NY  18.072289\n",
              "14    MN  17.857143\n",
              "15    PA  17.777778\n",
              "16    MA  16.923077\n",
              "17    CT  16.216216\n",
              "18    NC  16.176471\n",
              "19    NH  16.071429\n",
              "20    GA  14.814815\n",
              "21    DE  14.754098\n",
              "22    OK  14.754098\n",
              "23    OR  14.102564\n",
              "24    UT  13.888889\n",
              "25    CO  13.636364\n",
              "26    KY  13.559322\n",
              "27    SD  13.333333\n",
              "28    OH  12.820513\n",
              "29    FL  12.698413\n",
              "30    IN  12.676056\n",
              "31    ID  12.328767\n",
              "32    WY  11.688312\n",
              "33    MO  11.111111\n",
              "34    VT  10.958904\n",
              "35    AL  10.000000\n",
              "36    NM   9.677419\n",
              "37    ND   9.677419\n",
              "38    WV   9.433962\n",
              "39    TN   9.433962\n",
              "40    DC   9.259259\n",
              "41    RI   9.230769\n",
              "42    WI   8.974359\n",
              "43    IL   8.620690\n",
              "44    NE   8.196721\n",
              "45    LA   7.843137\n",
              "46    IA   6.818182\n",
              "47    VA   6.493506\n",
              "48    AZ   6.250000\n",
              "49    AK   5.769231\n",
              "50    HI   5.660377"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7bf68213-b2c4-41c1-877c-4c694050ef26\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>State</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NJ</td>\n",
              "      <td>26.470588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CA</td>\n",
              "      <td>26.470588</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>TX</td>\n",
              "      <td>25.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>MD</td>\n",
              "      <td>24.285714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>SC</td>\n",
              "      <td>23.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>MI</td>\n",
              "      <td>21.917808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>MS</td>\n",
              "      <td>21.538462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>NV</td>\n",
              "      <td>21.212121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>WA</td>\n",
              "      <td>21.212121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>ME</td>\n",
              "      <td>20.967742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>MT</td>\n",
              "      <td>20.588235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>AR</td>\n",
              "      <td>20.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>KS</td>\n",
              "      <td>18.571429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>NY</td>\n",
              "      <td>18.072289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>MN</td>\n",
              "      <td>17.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>PA</td>\n",
              "      <td>17.777778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>MA</td>\n",
              "      <td>16.923077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>CT</td>\n",
              "      <td>16.216216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>NC</td>\n",
              "      <td>16.176471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>NH</td>\n",
              "      <td>16.071429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>GA</td>\n",
              "      <td>14.814815</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>DE</td>\n",
              "      <td>14.754098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>OK</td>\n",
              "      <td>14.754098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>OR</td>\n",
              "      <td>14.102564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>UT</td>\n",
              "      <td>13.888889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>CO</td>\n",
              "      <td>13.636364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>KY</td>\n",
              "      <td>13.559322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>SD</td>\n",
              "      <td>13.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>OH</td>\n",
              "      <td>12.820513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>FL</td>\n",
              "      <td>12.698413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>IN</td>\n",
              "      <td>12.676056</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>ID</td>\n",
              "      <td>12.328767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>WY</td>\n",
              "      <td>11.688312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>MO</td>\n",
              "      <td>11.111111</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>VT</td>\n",
              "      <td>10.958904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>AL</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>NM</td>\n",
              "      <td>9.677419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>ND</td>\n",
              "      <td>9.677419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>WV</td>\n",
              "      <td>9.433962</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>TN</td>\n",
              "      <td>9.433962</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>DC</td>\n",
              "      <td>9.259259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>RI</td>\n",
              "      <td>9.230769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>WI</td>\n",
              "      <td>8.974359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>IL</td>\n",
              "      <td>8.620690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>NE</td>\n",
              "      <td>8.196721</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>LA</td>\n",
              "      <td>7.843137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>IA</td>\n",
              "      <td>6.818182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>VA</td>\n",
              "      <td>6.493506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>AZ</td>\n",
              "      <td>6.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>AK</td>\n",
              "      <td>5.769231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>HI</td>\n",
              "      <td>5.660377</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7bf68213-b2c4-41c1-877c-4c694050ef26')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-convert {\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.rcParams['figure.figsize'] = (18, 12)\n",
        "unique_state = data['State'].unique()\n",
        "churn_rate = data.groupby('State')['Churn'].mean()\n",
        "\n",
        "plt.plot(unique_state,churn_rate, marker = \"o\", linewidth = 2, markersize = 15, color = 'g')\n",
        "plt.title('State Avg_churn Rate', fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "rYT58sYPy7gh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 721
        },
        "outputId": "51d8785f-a028-4969-9fd4-90b295101b2a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "highest_churn_state = (data.groupby('State')['Churn'].mean()*100).sort_values(ascending = False).reset_index().head(5)"
      ],
      "metadata": {
        "id": "0O1uxe-dy7ju"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Top 5 highest Churn state**"
      ],
      "metadata": {
        "id": "b_kgXYPR_eWe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (8,5))\n",
        "sns.barplot(data = data, x = highest_churn_state['State'], y = highest_churn_state['Churn'], palette = 'cool')\n",
        "plt.title('Top 5 highest churn state', fontsize = 14)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "aZMrE3gxy7nG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "c043c7dc-cd92-4a86-937b-2c3398776d61"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "State_count_mean = pd.crosstab(data['State'], data['Churn'])\n",
        "State_count_mean['state_churn_percent'] = data.groupby('State')['Churn'].mean()*100\n",
        "print(State_count_mean)"
      ],
      "metadata": {
        "id": "UWNOOt1ay7qF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7d0774cf-89ef-4238-9bf5-2ea363fab646"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Churn  False  True  state_churn_percent\n",
            "State                                  \n",
            "AK        49     3             5.769231\n",
            "AL        72     8            10.000000\n",
            "AR        44    11            20.000000\n",
            "AZ        60     4             6.250000\n",
            "CA        25     9            26.470588\n",
            "CO        57     9            13.636364\n",
            "CT        62    12            16.216216\n",
            "DC        49     5             9.259259\n",
            "DE        52     9            14.754098\n",
            "FL        55     8            12.698413\n",
            "GA        46     8            14.814815\n",
            "HI        50     3             5.660377\n",
            "IA        41     3             6.818182\n",
            "ID        64     9            12.328767\n",
            "IL        53     5             8.620690\n",
            "IN        62     9            12.676056\n",
            "KS        57    13            18.571429\n",
            "KY        51     8            13.559322\n",
            "LA        47     4             7.843137\n",
            "MA        54    11            16.923077\n",
            "MD        53    17            24.285714\n",
            "ME        49    13            20.967742\n",
            "MI        57    16            21.917808\n",
            "MN        69    15            17.857143\n",
            "MO        56     7            11.111111\n",
            "MS        51    14            21.538462\n",
            "MT        54    14            20.588235\n",
            "NC        57    11            16.176471\n",
            "ND        56     6             9.677419\n",
            "NE        56     5             8.196721\n",
            "NH        47     9            16.071429\n",
            "NJ        50    18            26.470588\n",
            "NM        56     6             9.677419\n",
            "NV        52    14            21.212121\n",
            "NY        68    15            18.072289\n",
            "OH        68    10            12.820513\n",
            "OK        52     9            14.754098\n",
            "OR        67    11            14.102564\n",
            "PA        37     8            17.777778\n",
            "RI        59     6             9.230769\n",
            "SC        46    14            23.333333\n",
            "SD        52     8            13.333333\n",
            "TN        48     5             9.433962\n",
            "TX        54    18            25.000000\n",
            "UT        62    10            13.888889\n",
            "VA        72     5             6.493506\n",
            "VT        65     8            10.958904\n",
            "WA        52    14            21.212121\n",
            "WI        71     7             8.974359\n",
            "WV        96    10             9.433962\n",
            "WY        68     9            11.688312\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Top 5 Lowest Churn State**"
      ],
      "metadata": {
        "id": "WJSF8P4gFnWa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "highest_churn_state_1 = (data.groupby('State')['Churn'].mean()*100).sort_values(ascending = True).reset_index().head(5)"
      ],
      "metadata": {
        "id": "ct04B42Dy7wC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (8,5))\n",
        "sns.barplot(data = data, x = highest_churn_state_1['State'], y = highest_churn_state_1['Churn'], palette = 'cool')\n",
        "plt.title('Top 5 lowest churn state', fontsize = 14)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "kp3it7I2y7zL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "c1281598-f05a-4382-aaaa-6467dda411bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ],
            "image/png": 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MW4L7/PnzWrFihb7++ms5HA5JUp06dewYGgAAn2LLNe6MjAyFhITo7bffVt++ffX4449r+/btdgwNAIBPsWXGXVRUpIyMDDVv3lxjx45Vamqqhg8frnXr1ikoKMijY9Su7dl2AHxb3brB3i7B59HjyleeHtsS3GFhYfL391dsbKwkqVWrVqpVq5YOHTqku+66y6NjZGXlqrjYqswyAa/jF2bZMjNzyrU/PS5beXss0eeyuOuxn5/D7WTVllPloaGhateunTZv3ixJOnTokLKystSgQQM7hgcAwGfYdlf51KlTNWHCBMXHx8vf31+zZs1SjRo17BoeAACfYFtw33bbbfr444/tGg4AAJ/EJ6cBAGAQghsAAIMQ3AAAGMS2a9wwX42QGxVYlfd6JckvLFb2ufPeLgPAdYDghscCq/rpj59meruMa9I7/et6uwQA1wmmTwAAGITgBgDAID5zqjy41g2q5l/F22Vck366WKScs3neLgMAUAF8Jrir+VfRff846u0yrklrO9ZX+T95GABwLeBUOQAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDcAAAYhuAEAMAjBDQCAQQhuAAAMQnADAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADOJv10DdunVTQECAAgMDJUljxoxR586d7RoeAACfYFtwS9Jbb72l8PBwO4cEAMCncKocAACD2DrjHjNmjCzLUlRUlEaPHq0aNWp4vG/t2kGVWJnvq1s32Nsl+Dx6bA/6XPnoceUrT49tC+4lS5YoLCxMBQUFmj59uuLi4vTGG294vH9WVq6Ki61S1/NCcy8zM6fcx6DH7tFje5S3z/S4bLyWK5+7Hvv5OdxOVm07VR4WFiZJCggI0MCBA7Vz5067hgYAwGfYEtx5eXnKybn07sKyLH3++edq1qyZHUMDAOBTbDlVnpWVpZEjR6qoqEjFxcVq3LixJk+ebMfQAAD4FFuC+7bbbtOKFSvsGAoAAJ/Gn4MBAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEIIbAACDENwAABiE4AYAwCAENwAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDcAAAYhuAEAMAjBDQCAQQhuAAAMQnADAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGsT243377bUVEROiHH36we2gAAIxna3Dv2bNH3377rerXr2/nsAAA+AzbgrugoEBxcXGaMmWKXUMCAOBz/O0a6M0339RDDz2kW2+99ar2r107qIIrur7UrRvs7RJ8Hj22B32ufPS48pWnx1cV3MXFxS6P/fzcT9x37dqltLQ0jRkz5mqGkyRlZeWquNgqdT0vNPcyM3PKfQx67B49tkd5+0yPy8ZrufK567Gfn8PtZNXj4N6zZ4/i4uK0f/9+5efnS5Isy5LD4dC+ffvc7rtt2zalp6ere/fukqQTJ07o6aef1syZM9WpUydPSwAA4LrncXCPGzdOXbt21YwZM1StWrUrGmTYsGEaNmyY83G3bt00f/58hYeHX9FxAAC43nkc3EePHtWoUaPkcDgqsx4AAOCGx3eVx8TEaNOmTRUy6Pr165ltAwBwFTyecefn52vEiBGKiopSnTp1XNbNmjWrwgsDAACX8zi4mzRpoiZNmlRmLQAAoAweBXdRUZEyMjI0bdo0BQQEVHZNAACgFB5d465SpYo2b97MjWkAAHiZxzenDRkyRAkJCSosLKzMegAAgBseX+NevHixTp8+rUWLFik0NNRl9r1hw4bKqA0AAPyKx8E9e/bsyqwDAAB4wOPgjo6Orsw6AACABzwO7jfffLPUdS+88EKFFAMAANzzOLhPnDjh8jgzM1Pbtm3TvffeW+FFAQCAknkc3DNnzrxs2caNG7V69eoKLQgAAJTO4z8HK0mnTp305ZdfVlQtAACgDB7PuDMyMlweX7hwQcnJyQoLC6vwogAAQMk8Du6YmBg5HA5ZliVJql69upo1a6bXX3+90ooDAACuPA7u77//vjLrAAAAHvA4uH+puLjY5bGfX7kulQMAAA95HNx79uxRXFyc9u/fr/z8fEmSZVlyOBzat29fpRUIAAD+w+PgHjdunLp27aoZM2aoWrVqlVkTAAAohcfBffToUY0aNYqv9gQAwIs8vjgdExOjTZs2VWYtAACgDG5n3C+99JJzhl1QUKARI0YoKipKderUcdlu1qxZlVchAABwchvcDRo0cHncpEmTSi0GAAC45za4R4wYoR07dmj9+vV66aWXLls/e/ZsxcTEVFpxAADAVZnXuN999121bdu2xHXt2rXT/PnzK7woAABQsjKDe9++fercuXOJ6zp27Ki0tLQKLwoAAJSszODOzc1VYWFhiesuXryo8+fPV3hRAACgZGUGd6NGjUr9M7BNmzapUaNGFV4UAAAoWZnB/cQTT2jy5Mlau3at8zPKi4uLtXbtWk2ZMkVPPvlkpRcJAAAuKfOT03r16qXTp09r7NixKiwsVEhIiM6dO6eqVavq+eefV2xsrB11AgAAefiRp08++aT69++vXbt26dy5cwoJCVFkZKSCgoI8Hui5557TkSNH5OfnpxtuuEGvvPKKmjVrdtWFAwBwPfL4s8qDgoJKvbvcE/Hx8QoODpYkffnll5owYYKWL19+1ccDAOB6ZNsXaf8c2tKlO9X5shIAAK6cxzPuijBx4kRt3rxZlmVp4cKFV7Rv7dqen5bH5erWDS57I5QLPbYHfa589LjylafHtgb39OnTJUkrVqzQrFmz9N5773m8b1ZWroqLrVLX80JzLzMzp9zHoMfu0WN7lLfP9LhsvJYrn7se+/k53E5WbTtV/kt9+vRRSkqKzp49643hAQAwli3Bff78eR0/ftz5eP369apZs6ZCQkLsGB4AAJ9hy6nyCxcu6IUXXtCFCxfk5+enmjVrav78+dygBgDAFbIluOvUqaNPPvnEjqEAAPBpXrnGDQAArg7BDQCAQQhuAAAMQnADAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEIIbAACDENwAABiE4AYAwCAENwAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDcAAAYhuAEAMAjBDQCAQQhuAAAMQnADAGAQghsAAIP42zHI2bNn9fLLL+tf//qXAgIC1KBBA8XFxSk0NNSO4QEA8Bm2zLgdDoeGDh2qNWvWaNWqVbrtttv0xhtv2DE0AAA+xZbgDgkJUbt27ZyPW7durWPHjtkxNAAAPsWWU+W/VFxcrKVLl6pbt25XtF/t2kGVVNH1oW7dYG+X4PPosT3oc+Wjx5WvPD22PbinTZumG264QYMGDbqi/bKyclVcbJW6nheae5mZOeU+Bj12jx7bo7x9psdl47Vc+dz12M/P4Xayamtwx8fH6/Dhw5o/f778/LihHQCAK2VbcM+dO1dpaWlasGCBAgIC7BoWAACfYktwHzhwQO+++65uv/12DRgwQJJ066236p133rFjeAAAfIYtwX3HHXdo//79dgwFAIBP40IzAAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEIIbAACDENwAABiE4AYAwCAENwAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDcAAAYhuAEAMAjBDQCAQQhuAAAMQnADAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEFuCOz4+Xt26dVNERIR++OEHO4YEAMAn2RLc3bt315IlS1S/fn07hgMAwGf52zHIb3/7WzuGAQDA59kS3BWhdu0gb5dgtLp1g71dgs+jx/agz5WPHle+8vTYmODOyspVcbFV6npeaO5lZuaU+xj02D16bI/y9pkel43XcuVz12M/P4fbySp3lQMAYBCCGwAAg9gS3K+99pq6dOmiEydO6Mknn1TPnj3tGBYAAJ9jyzXuSZMmadKkSXYMBQCAT+NUOQAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDcAAAYhuAEAMAjBDQCAQQhuAAAMQnADAGAQghsAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEIIbAACDENwAABiE4AYAwCAENwAABiG4AQAwCMENAIBBCG4AAAxCcAMAYBDbgvvQoUN65JFHdP/99+uRRx7Rjz/+aNfQAAD4DNuCe/LkyRo4cKDWrFmjgQMH6tVXX7VraAAAfIa/HYNkZWVp7969WrRokSQpNjZW06ZN05kzZxQaGurRMfz8HGVuUy+wSrnq9GWe9M8ToTdwdaU0FdXj4Br02J2K6PMNofTYnYp6LQfW43dyadz1uKz+OyzLsiq6oF9LS0vT2LFjtXr1aueyBx98ULNnz1aLFi0qe3gAAHwGbzsBADCILcEdFhamkydPqqioSJJUVFSkU6dOKSwszI7hAQDwGbYEd+3atdWsWTMlJydLkpKTk9WsWTOPr28DAIBLbLnGLUnp6ekaN26csrOzVaNGDcXHx6tRo0Z2DA0AgM+wLbgBAED5cXMaAAAGIbgBADAIwQ0AgEEIbgAADEJwV4Bu3brphx9+cFnWt29fpaSkKCEhQfHx8V6qzDf8+9//VsuWLfXaa685lyUlJen55593Pv7b3/6mLl26aPfu3d4o0Xgl9fgPf/iDevfu7fLTtGlTLV261IuVmmno0KGX9c2yLHXv3l1bt27V119/rYiICK1bt85LFfqWX/9O7t+/v3r37u3FiioWwY1rXnJyslq1aqXVq1eroKDgsvWrVq1SXFyc3n//fbVs2dILFZqvpB6/9957+uyzz5w/PXv2VPPmzdW3b18vV2uefv36afny5S7LUlJS5Ofnp7Zt2yoxMVHt27dXYmKilyr0XQcOHNDp06d14cIFpaWlebucCkFw45qXmJio5557ThEREfrqq69c1i1dulRvvfWWPvroI91xxx1eqtB87nosSVu2bNFf/vIXJSQkKDAw0AsVmq179+46fPiw0tPTncuSkpLUt29fnTt3Tt98843mzJmjXbt2KTMz04uV+p7ExET17t1bffr08Zk3RrZ8O9j14Pnnn3f5hcb3jVeM77//XufOnVP79u2VmZmpxMRE9ejRQ9KlGcvOnTuVmJioevXqeblSc7nrsSQdO3ZMY8aM0ezZs1W/fn0vVmqugIAA9erVS4mJiXr55ZeVm5urL7/8Up9//rlWrlype+65R3Xq1FFMTIyWL1+uYcOGebtkn1BYWKhVq1Zp6dKlqlq1qvr06aNx48YZ/+aTGXcFeeutt1xOKzZu3NjbJfmEZcuWqXfv3nI4HLrvvvu0e/dunTx5UpLUsGFDVa9e3flRurg67npcUFCgkSNHavDgwfqv//ovL1dqtt/97ndauXKlioqK9MUXX6hNmza6+eablZSUpIcffliS9PDDDyspKcnLlfqODRs26Pbbb9dvfvMbhYWFqXnz5j5xHwEzblyzCgoKlJycrICAAH322WeSLr2DTkpKUr169XTTTTdp3rx5evzxxyVJTz/9tDfLNZK7Hj/77LOaOnWqwsLCmAFWgKZNm+qmm27Sxo0blZiYqCFDhigtLU0HDx7UxIkTndudOnVKO3bsUFRUlBer9Q2JiYk6ePCgunXrJknKy8tTYmKiYmNjvVxZ+RDcuGZ99dVXatiwocvduLt27dLYsWM1fPhwSdLNN9+sjz76iPC+Su56HBoaqh07dmjZsmVyOBxerNJ39OvXTwkJCTp27Ji6d++umTNnaujQoRo1apRzm3fffVeJiYkEdzllZ2dr69at2rhxo4KCgiRJ+fn56tSpk44dO6ZbbrnFyxVePU6V45qVmJioXr16uSyLjIxUcXGxjh075lwWFhamjz/+WEuXLtX7779vd5lGc9fjV199VXl5eXrsscdc/iRs4cKFXqrWfLGxsTp48KBiY2NlWZZWr16thx566LJt1qxZo7y8PC9V6Ru++eYbdenSxRnakhQYGKh7773X+MsRfMkIAAAGYcYNAIBBCG4AAAxCcAMAYBCCGwAAgxDcAAAYhOAGAMAgBDdwHdi+fbsGDBigqKgoRUdHa8CAAdq9e7eSkpL06KOPenycI0eOKCIiQhcvXqzEagG4wyenAT4uNzdXw4cP15QpU9SjRw8VFhZq+/btCggI8HZpAK4CM27Axx06dEjSpU/kqlKliqpVq6ZOnTqpatWqmjx5sr799ltFRkbqt7/9raRLX8zQp08ftWnTRnfffbcSEhKcxxo0aJAkqW3btoqMjNSuXbskXfqikh49eqht27Z6+umndfToUZufJXD94JPTAB+Xm5ur7t2765577tGDDz6o1q1bq2bNmpIufSf0p59+6vJZ5SkpKQoJCdEdd9yhH374QU899ZTi4uJ077336siRI+revbv27Nkjf/9LJ+y+/PJLxcfHa/78+WrQoIEWLFigjRs36q9//atXni/g65hxAz4uKChI//M//yOHw6FXXnlFHTp00PDhw3X69OkSt2/Xrp0iIiLk5+enpk2bqmfPntq6dWupx//rX/+qYcOGqXHjxvL399fw4cO1b98+Zt1AJeEaN3AdaNy4sV5//XVJUnp6ul566SXNmDFDnTp1umzb1NRUvfHGGzpw4IAKCwtVUFCgBx54oNRjHzt2TDNmzFB8fLxzmWVZOnnypOrXr1/xTwa4zhHcwHWmcePG6tu3r/73f/9XnTt3vmz9iy++qEGDBmnhwoUKDAzU9OnTdfbsWUkq8es9w8LCNHz48Mu+5QpA5eBUOeDj0tPT9cEHH+jEiROSpOPHjys5OVmtWrVS7dq1dfLkSRUUFDi3P3/+vGrWrKnAwEDt3r1bycnJznWhoaHy8/NTRkaGc9mAAQO0YMECHThwQJKUk5OjL774wqZnB1x/mHEDPi4oKEipqalatGiRcnJyFBwcrK5du+rll19WQECAmjRpok6dOsnhcCglJUWTJ09WfHy84uLiFB0drR49eig7O1uSVL16dQ0fPlyPPvqoLl68qIULFyomJkbnz5/X6NGjdfToUQUHB6tjx47q0aOHl5854Ju4qxwAAINwqhwAAIMQ3AAAGITgBgDAIAQ3AAAGIbgBADAIwQ0AgEEIbgAADEJwAwBgEIIbAACD/D+GihR9ZDmINgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There are 51 unique states in the data, and the top 5 highest churn states are: NJ, CA, TX, MD, and SC, whereas the lowest churn states are: HI, AK, AZ, VA, and IA.**\n",
        "\n",
        "**And the highest churn rate in the state is more than 10 percent which is huge.** "
      ],
      "metadata": {
        "id": "N44ofspdH3vK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**International Plan Churn Rate**"
      ],
      "metadata": {
        "id": "IEaW5a3sNuKD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data['International plan'].value_counts()"
      ],
      "metadata": {
        "id": "6Za0YeVRy72J",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ecd2d89d-4608-44b8-8c6f-c6573728aeb1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "No     3010\n",
              "Yes     323\n",
              "Name: International plan, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plan_churn = data.groupby('International plan')['Churn'].count().sort_values(ascending = False).head(10).reset_index()"
      ],
      "metadata": {
        "id": "xqgNW58Jy78w"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plan_churn"
      ],
      "metadata": {
        "id": "rTGwxFlzy8Ag",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "652b94b0-e124-442c-9038-9e0e96efd36a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  International plan  Churn\n",
              "0                 No   3010\n",
              "1                Yes    323"
            ],
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              "\n",
              "  <div id=\"df-ffbb5dfd-a66d-41bc-b112-036577f9dcc0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>International plan</th>\n",
              "      <th>Churn</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>No</td>\n",
              "      <td>3010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Yes</td>\n",
              "      <td>323</td>\n",
              "    </tr>\n",
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              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffbb5dfd-a66d-41bc-b112-036577f9dcc0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ffbb5dfd-a66d-41bc-b112-036577f9dcc0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ffbb5dfd-a66d-41bc-b112-036577f9dcc0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 155
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "explode = (0, 0.1)\n",
        "plt.pie(plan_churn['Churn'], labels = plan_churn['International plan'], autopct = '%.2f%%', explode = explode, startangle=90,shadow=True)\n",
        "plt.title('International plan Churn Rate Percent', fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "EIcWUXKvy8D3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 701
        },
        "outputId": "d845abdb-7d94-4f0c-e9da-1d98c9a8e5a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1296x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plan_churn = pd.crosstab(data['International plan'], data['Churn'])\n",
        "plan_churn['Avg_churn'] = data.groupby('International plan')['Churn'].mean()*100\n",
        "print(plan_churn)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c1MVEWe8b_yD",
        "outputId": "eed04535-4de8-45dc-e538-cb8cd56b643e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Churn               False  True  Avg_churn\n",
            "International plan                        \n",
            "No                   2664   346  11.495017\n",
            "Yes                   186   137  42.414861\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**There are over 2000 people who do not have an international plan, while there are only 186 customers who do have plan, and the churn ratio of those who have the plan is higher than that of those who do not have an international plan and the reason for that can be the high price of a plan or bad network condition or connectivity.**"
      ],
      "metadata": {
        "id": "47SdwSWoeF6c"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Area Code Churn rate"
      ],
      "metadata": {
        "id": "KEJz1ROceXwR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.columns"
      ],
      "metadata": {
        "id": "nAmmX2DDy8HO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "613a0f10-f6b0-4649-dc19-628789c2c368"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['State', 'Account length', 'Area code', 'International plan',\n",
              "       'Voice mail plan', 'Number vmail messages', 'Total day minutes',\n",
              "       'Total day calls', 'Total day charge', 'Total eve minutes',\n",
              "       'Total eve calls', 'Total eve charge', 'Total night minutes',\n",
              "       'Total night calls', 'Total night charge', 'Total intl minutes',\n",
              "       'Total intl calls', 'Total intl charge', 'Customer service calls',\n",
              "       'Churn'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Analysing Customer Service Calls**"
      ],
      "metadata": {
        "id": "45_7cqMpfZEP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data['Customer service calls'].value_counts()"
      ],
      "metadata": {
        "id": "lzUdt_Bcy8Ko",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5e42c352-0d68-4fba-ed9a-896dac9305f3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    1181\n",
              "2     759\n",
              "0     697\n",
              "3     429\n",
              "4     166\n",
              "5      66\n",
              "6      22\n",
              "7       9\n",
              "9       2\n",
              "8       2\n",
              "Name: Customer service calls, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 144
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "CSC_churn = pd.crosstab(data['Customer service calls'], data['Churn'])\n",
        "CSC_churn['Percent_churn'] = data.groupby('Customer service calls')['Churn'].mean()*100\n",
        "print(CSC_churn)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EOEdrRgDyYzR",
        "outputId": "fff7172a-0948-42da-f056-7d136d3a4d0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Churn                   False  True  Percent_churn\n",
            "Customer service calls                            \n",
            "0                         605    92      13.199426\n",
            "1                        1059   122      10.330229\n",
            "2                         672    87      11.462451\n",
            "3                         385    44      10.256410\n",
            "4                          90    76      45.783133\n",
            "5                          26    40      60.606061\n",
            "6                           8    14      63.636364\n",
            "7                           4     5      55.555556\n",
            "8                           1     1      50.000000\n",
            "9                           0     2     100.000000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (10,8))\n",
        "sns.countplot(data['Customer service calls'], hue = data['Churn'], palette = 'crest')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "C8KCoRuXy8Z_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 557
        },
        "outputId": "c4242386-4976-449c-c7ef-3addf84cb08c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**According to the above analysis, false representation retained customers, and true representation churned customers.**\n",
        "\n",
        "**The person who calls once has a high churn rate, and the person who calls five times has a churn rate of 60%, indicating that the customer is very bad. There is a need for improvement in customer service.**\n",
        "\n",
        "**Generally, after 4–5 calls, the churn rate of customers is more**"
      ],
      "metadata": {
        "id": "IWvYbvdhmIev"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Analysis Area Code**"
      ],
      "metadata": {
        "id": "md0SCujt1z1q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data['Area code'].unique()"
      ],
      "metadata": {
        "id": "YHgJzXBNy8j1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ef615d58-ab8f-4b0e-eb82-db3961f7e9a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([415, 408, 510])"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "area_churn = pd.crosstab(data['Area code'], data['Churn'])\n",
        "area_churn['Percent'] = data.groupby('Area code')['Churn'].mean()*100\n",
        "print(area_churn)"
      ],
      "metadata": {
        "id": "m4N6ZNB1y8nK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7c6de683-80cf-4834-bbd7-ec2cfcc09342"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Churn      False  True    Percent\n",
            "Area code                        \n",
            "408          716   122  14.558473\n",
            "415         1419   236  14.259819\n",
            "510          715   125  14.880952\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**The average churn rate of all three codes is almost the same, which means there is no relation between area code and churn rate.**"
      ],
      "metadata": {
        "id": "4M_TL54RApIi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set(style=\"darkgrid\")\n",
        "plt.figure(figsize = (15,8))\n",
        "sns.countplot(data['Area code'], hue = data['Churn'], palette = 'cool')\n",
        "plt.title('Area code Churn')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "TcNOsJyAy8qG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "6e4b9863-c588-4afc-9d45-7579f9b332a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.columns"
      ],
      "metadata": {
        "id": "HCKjYXecy8tx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ee2edbf6-d5c7-41ae-8006-6103ccce832f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['State', 'Account length', 'Area code', 'International plan',\n",
              "       'Voice mail plan', 'Number vmail messages', 'Total day minutes',\n",
              "       'Total day calls', 'Total day charge', 'Total eve minutes',\n",
              "       'Total eve calls', 'Total eve charge', 'Total night minutes',\n",
              "       'Total night calls', 'Total night charge', 'Total intl minutes',\n",
              "       'Total intl calls', 'Total intl charge', 'Customer service calls',\n",
              "       'Churn'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby(['Total day calls'])['Total day minutes', 'Total day charge'].sum().sort_values(by = 'Total day calls' , ascending = False).head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "3oyRRRIRmCBP",
        "outputId": "dfb47872-4d1f-4198-af65-06f2fe0b2953"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 Total day minutes  Total day charge\n",
              "Total day calls                                     \n",
              "165                          154.4             26.25\n",
              "163                           70.9             12.05\n",
              "160                          198.1             33.68\n",
              "158                          308.8             52.50\n",
              "157                          189.3             32.18\n",
              "156                          239.0             40.63\n",
              "152                          188.5             32.05\n",
              "151                          865.8            147.19\n",
              "150                         1237.9            210.45\n",
              "149                           19.5              3.32"
            ],
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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          "metadata": {},
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    {
      "cell_type": "code",
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        "data.groupby(['Total eve calls'])['Total eve minutes', 'Total eve charge'].sum().sort_values(by = 'Total eve calls' , ascending = False).head(10)"
      ],
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            "text/plain": [
              "                 Total eve minutes  Total eve charge\n",
              "Total eve calls                                     \n",
              "170                          332.8             28.29\n",
              "168                          264.8             22.51\n",
              "164                          246.5             20.95\n",
              "159                          179.5             15.26\n",
              "157                          194.5             16.53\n",
              "156                          119.6             10.17\n",
              "155                          602.3             51.20\n",
              "154                          334.1             28.39\n",
              "153                          196.2             16.68\n",
              "152                         1122.3             95.40"
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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    {
      "cell_type": "code",
      "source": [
        "data.groupby(['Total night calls'])['Total night minutes', 'Total night charge'].sum().sort_values(by = 'Total night calls' , ascending = False).head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   Total night minutes  Total night charge\n",
              "Total night calls                                         \n",
              "175                              263.4               11.85\n",
              "166                              221.2                9.95\n",
              "164                              168.8                7.60\n",
              "158                              141.1                6.35\n",
              "157                              409.8               18.44\n",
              "156                              466.5               20.99\n",
              "155                              374.3               16.85\n",
              "154                              484.2               21.79\n",
              "153                              611.5               27.52\n",
              "152                              626.0               28.17"
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "data.groupby(['Total intl calls'])['Total intl minutes', 'Total intl charge'].sum().sort_values(by = 'Total intl calls' , ascending = False).head(10)"
      ],
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        "id": "srs3sBCuJUmd",
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          "height": 394
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      "execution_count": null,
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          "data": {
            "text/plain": [
              "                  Total intl minutes  Total intl charge\n",
              "Total intl calls                                       \n",
              "20                              13.9               3.75\n",
              "19                               9.5               2.57\n",
              "18                              28.3               7.64\n",
              "17                              13.6               3.67\n",
              "16                              23.1               6.24\n",
              "15                              65.9              17.80\n",
              "14                              50.0              13.50\n",
              "13                             142.5              38.48\n",
              "12                             152.4              41.16\n",
              "11                             293.7              79.31"
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              "      <th>20</th>\n",
              "      <td>13.9</td>\n",
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              "      <th>18</th>\n",
              "      <td>28.3</td>\n",
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              "      <td>65.9</td>\n",
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              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>293.7</td>\n",
              "      <td>79.31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a8c3801e-18bc-421a-9c47-058b157db539')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a8c3801e-18bc-421a-9c47-058b157db539 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a8c3801e-18bc-421a-9c47-058b157db539');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "average_cost_per_minute_day = data['Total day charge'].mean()/ data['Total day minutes'].mean()*100\n",
        "\n",
        "average_cost_per_minute_eve = data['Total eve charge'].mean()/ data['Total eve minutes'].mean()*100\n",
        "\n",
        "average_cost_per_minute_night = data['Total night charge'].mean()/ data['Total night minutes'].mean()*100\n",
        "\n",
        "average_cost_per_minute_intl = night = data['Total intl charge'].mean()/ data['Total intl minutes'].mean()*100\n"
      ],
      "metadata": {
        "id": "k7EJlSbbmB5K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(average_cost_per_minute_day, average_cost_per_minute_eve, average_cost_per_minute_night, average_cost_per_minute_intl)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SXyPaLlPmB1y",
        "outputId": "d5ce8414-c9fb-4779-893c-2db3c98a32bf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "17.000300739130672 8.500104871485778 4.500041448440008 27.005002798871068\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set(style ='darkgrid')\n",
        "plt.figure(figsize = (10, 8))\n",
        "sns.barplot(x = ['Day','Evening','Night','International'], y = [average_cost_per_minute_day, average_cost_per_minute_eve, average_cost_per_minute_night, average_cost_per_minute_intl])\n",
        "plt.title('Average Cost Per Minute', fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "DsQZh1jSmBya",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 503
        },
        "outputId": "35625ecc-d7f5-4770-f743-38ae51db38f1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**As seen in the graph, the charges for day,evening, night are reasonable, but the price of international is high, and it is obvious that the price for international would be high.**\n",
        "\n",
        "**And according to the graph, three time charges would not have any effect on the churn rate but international plan high charges can be a cause for churn rate in the international plan.**"
      ],
      "metadata": {
        "id": "aJyhFXQJRVkp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "correlation = data.corr()"
      ],
      "metadata": {
        "id": "UFkcN7MhHCII"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (15,10))\n",
        "sns.heatmap(correlation, annot = True, cmap = 'gist_stern_r')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 709
        },
        "id": "WCQVM_zoHIAr",
        "outputId": "15857609-8d3d-4b13-d3cf-464400ffd4df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ],
            "image/png": 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SXwhhXcR2bYEwfT0hwH+klIeArcBnUsqGUsrCTussAYZIKRsDI4HFOZ7zQNf57Q7M1C97Q/966gADgZbogv4GuAl0lFJ2LCi2Il7LUys2NpHy5Z0Mj93cnIiNTchVJgF39+wy7u5OJeq07NlznFq1KmFlVfS0uqztGcfkmGd7sbGJ+cSkizs+PtnwpdvFxYH4+GRDvfv2neL111sb1XXtWgx2djaMGbOMt9+ezaJFPxtGrPJuM/vLvJubYz4fYNllLCzMsbW1JjHxHnFxSUbrurs7EBubyK1b8Tg52TJ9+kbeeWchM2du4v799Dzb3r79qGG6ZXHExaXi5pY9e9rV1Y64uFSjMnfuZJcxNzfD1taKpKQHAERERPPee+t4//31DB3aDnNzM1xd7ejVqwH9+6+id+8AbG2taNIk7xTD/Jh67h7XPhcVFUty8j3+97+F/N//fcXOnX/q63eib9+OvP76ZF59dQJ2djY0b1702ePY2GTc3LK/xLi5ORAbm5xPGQcALCzMsLMrQ2Li/QLr9PJy5tq1O9y6lUBmppYDB84TE1P8Ts6Tzl1Ou3cf48UXG5Ug1n/W3hUU63PPebF37wkAzpyJ5PbteGJijOstOrYE3N2zO7y67d7NVeYubm7OOco454k/P+HhV+jbdzL9+3/JqFH9DR3H4sdmWnmLi0vO1Z44EBubuz1JztWelCEx8R6xsUn5tEXJVK1anlOnrpKYeI8HD9IJC7tgdBxs3vwngwd/y8yZm0lOLvh4Ms7Jozle9+07R40aFYo9zb8gT0PedNtxMjzO7/tG3s8TJ8PruHs3GVdXXT5dXOy5ezc73/v2naJv35mMHPkjY8fqxkV8fb1p1Og5Xn11Mq++OpnmzWvj7V342EB+eYyLSy6wjIWFmf7zrHj7TXBwOC+8UKfI6a9Pg3LC7In+lYZnoaPYF8iaR7KW7OmnnYEfpJSZAFLKeKAWcEtK+Zd+WZL++TbAKv2yc8BVoKhvtenANv3/j6LrxBWLfhS0FRAkhDgB/ICuc5hli5RSq7/OMeuIbwME6ZffBvZQsGLFJoR4XwhxRAhxpLixP2suX77J4sU/M2pU6cxqFkIYzhzOn7+Zjz56FTMz48Nao9Fy8uRlPv74NZYtG8HNm3Hs2HH4icSn0Wi5cOEmPXo0Z/nyIdjYWLJ6tfE0yYCAPZibm/HSSw2fSEwAPj7lWbq0N4sW9WTt2mOkp2eSnJxGaGgkgYH9Wbt2IA8eZLJ794WiK3tMTDV3Ofc5jUbL+fNRzJnzPvPmfciKFb9y7VoMSUn32L8/nA0bJrF16xTu309n166/nliMOdnb2zB8uB9ffrmZTz4JoEIFpzzHyJNSnNxlycjI5MCBcMN1xqUZ66BBL5GScp9Bg6azYcNeatasiJmZ6XzJ8/Wtyk8/TWb58jEEBOwiLe3hRhYfBVPNm7e3G/36tWHECH9Gjgzkuec8DLH06NGMn34axvLlH+LiYs+33+56YnFduRLLkiV/MGJE1ye2zZIw1bxB1r6WvT+1b1+fn34azcyZ7/DjjzsBuH49lsjIaDZvnsSWLZM4evQiJ05cfqJx5vbHH2fo1Mm3VGNQiu9ffTMbIUQ54AWgnhBCAuaAFEJ89og2kYlxZzvnKGOGlFLq/6+hZLk2AxKklA0LeD4tx/8f5lOnWLFJKZegG9lEn7+nwoYN+9i69SAAPj5ViI5OMDwXG5tgmDKaxc3Nyegsb0xMAm5uRU+Ti4m5y+jRPzJhwiAqVnQrtOzGjfvZujUUgNq1K+eKKTHP9tzcHPOJSRd3uXL2xMUl4urqSFxcomGa6blz1ww3wUhMTOHQobOYm5vh7u5EjRpeeHm5AtC2bX3OnInklVeMY9RtM/vMZmxsouHMZRZXV10Zd3dHMjM1pKY+wNGxLK6uDkbrxsQk4ebmqP9zoG5d3chchw6+rFqVfSOZHTuOcujQOebPf7dEZxddXW2JjU0xPI6LS8HV1XiaqIuLroybmx0ajZbU1HQcHIwnAlSp4oyNjSVXrsRz+3YyFSo44OSkm97Zpk1Vzp69TefORY90mmLunsQ+5+bmiKNjbWxsymBjU4aGDatz6dINADw9y+HsbKePvT6nT1/Bz69pEXm0NxqRiI1NMhqxyC6ThLu7A5mZWlJS0nB0LPwmSK1a1aRVK937+Msvx4r8sl6auatc2R3QXctUs2ZFypUz3o9ye5TtXUGx2traMH78QEB3M4433phoaE8Kj20PP/98QB+bNzEx2Zcd6LbrbFTezc3ZaJQxJuZunvgLU7WqBzY2Zbh8+YbhZjcFx2a6eXN1tc/VniQZRuVyl8luT9JwdCyLm5tDPm2RLp7u3RvTvbtuUtWSJb/niD97dkb37o0ZPTr/60dz+6fHa0xMEhMmbGDMmFfx8jLeFx6GqeZt48YDbN2qu7GXj0+lIr9v5P08STC8Dmdne+LiknB1dSAuLgknp7z3JWzYsDo3b94hISGFfftOU7duFcqWLQNAixa1OXMmkoYNq+Uba84cZW8/yZCL3GWy3lfd51nRN6O7dOk2Go2WWrVKdjMsU/Us3PX03/4KewGBUsoqUkpvKWUl4ArQFvgd+EAIYQGGTuV5wEMI0VS/zF7//H6gv35ZTaCyvmwk0FB/fWAloFkxYkoGCp0gLqVMAq4IId7Ub1MIIRoUUe9BoKc+lvJAh5Js89+kV6/2BASMJSBgLO3aNWDnzsNIKQkPv4KtrU2ea6VcXR2xtbUmPFw3x37nzsNF3jwiOfkeI0Z8x0cfvUaDBgVeamrQs2dbww0q2rWrx65df+ljisTW1rqQmHTXc+za9Rdt2+rOwLVp48uOHbppajt2/GlYvnHjJDZt0v117NiQkSPfpH37+vj4VCYl5T537+o6VkePXqBq1bzX+tSu7cX163HcvBlPRkYmwcGnaNPGx6hMmza12bVLd1OSvXvDadRIdy1RmzY+BAefIj09k5s347l+PQ4fn4q4uNjj7u7ItWux+m3/jbe37ovw4cMXWLMmhBkzBuZ7zWRhatVy58aNRG7dSiIjQ8PevX/TsqW3UZmWLb357TfdiGBIyGUaNvRECMGtW0mGqbfR0clcu5ZAhQr2uLvbERERzYMHGUgpOX78BpUrF+/Liynm7knsc+3a1ePkycuG6xDPnLlKlSrlKV/emTNnrvLgQTpSSo4cuYC3d959LrdatTy5fj2eW7cSyMjQ8McfZw0dvCytWtVg165TAOzbF0GjRt5FnmS4e1c3LTk5+T5bthylW7eGhZYvzdxl+f33o8Wadvoo27s2beoZZhvs2HGYtm3r6/N2j4wM3fVjW7ceomHD57C1LfpLYa9eHQkMnEBg4ATat2/Ijh1h+tguY2dXUGw2hIfrrhvbsSOMdu0K/+i7eTPOcPOaW7fucPXqbTw8iu6MmXLedO1JPDdv3tW3J6dp3dp46nbr1rXZtesEAPv2naVRI921k61b1yY4+LS+PbnL9evx+Pjo7qqZ9RkQHZ1ASEgEnTvr7jyec1rh/v0RVK3qXmSM8M+O1+TkB4wZs4733+9IvXrFm+JfFFPNW8+ebQw3mtG1J0cM7YmdnXU+JxUdsLUtk6M9OUKbNlntSV127tTNzti5M7uduX49lqzz/+fPXyc9PRNHR1vKl3fmxIm/yczUkJmp4cSJy/nedyG/PN66dVf/vp6hdWvj97V161r8+mvW+3qW55+vWqyTvcHB4Wo08SkjsgeW/n30N2+ZJaXclWPZJ4APMASYDfgBGcCPUspF+k7iQsAG3fWJndGNHH4HNNH/f7iUco/QHRWrgMZABOAMTJZS7hU5foJCf8OZ7lLKwUKI1sCP6EYFe+W8TlHk+HkMIURV/TY9AEtgrZTySyHESmCblHKDfp0UKaWdEMIM3XWMHYAodCONs6SUv+tv1PMxcFNK2bGg2IrI5SPZUdasWUOHDh1wdXUlOjqaSZMmsXz58n9U5507vxf4nJSSOXPWc/jwWcqUsWL8+AGGn7gYNGg6AQFjAYiIuMrUqYGkpWXQokUdRox4CyEEe/eeYO7cIBISUrCzs6FmzYrMn/8xK1bsJCDgNypVyh5JnD9/SL4XietnNxvF9PXXGwgLy7o9dj98fHQXdb/99mz8/T/Xx3TN6Hb7w4f3NNyKffz4FURH36VChXJMnToYBwfj0bSpU1fTqlVdw7S1P/88x8KFW5ASateuxKhRvbG0tECjMb6uLzT0PN98s01/a/HGDBrUkaVLf6d27Yq0aeNDWloGU6cGcfHiTRwcyjJ5ch88PXXXHQUE7GH79qOYm5vxySfdaNFCdxOHixdvMmvWZjIyNHh6OjN2bC/s7W3o02cOGRkaw08F1K1biZEjexjF8+DBtQLf28OHr/Ldd4fQaiUvv1yL/v0bs3LlX9Ss6UarVt6kp2cyc+Yf/P13HPb2ZRg37kU8PBz4/fcLrFt3HHNzM8zMBAMGNKZ1a93PY/j7/8W+fX9jbi6oXt2V4cM7YGWV//VO1tbGF+KbUu7MzY33h8e5z61eHcz27YcRQvDqqy0NP+OwdOkOdu/W5blmzYqMGdPXcA1SerrxnQhzCgu7xKJFv6PVaunSpQEDB7Zh+fJ91KrlQevWNUlLy2T69J+5eDEaBwdrJk58HU9PXYe+d+9F3LuXRkaGBjs7a+bM6Yu3txtffrmZv//WbXPQoDZ06lS3wO1bWRl/2SuN3N2/n8brr09mw4aJ2Nlldyz05zUL9E/bu8TEFMaNW5Yj1ndxdLTl9OnLTJkSiBC6UbuxYwcY/SRPceLTxfYTYWG6n6AYP/5tw6jfwIFTCAycoI8tkilT/ElLS6dlS19GjOijb4uP8/XXa3O0xZVYsGAoO3eGERCwCwsLc4QQvPtud9q3b5jP9jPzLDOVvAFkZNwxehwaeoGFC3ei1Wrp2rURgwa1Z9myYGrV8qJNm9qkpWUwbdomLl68hb29DZMnv5mjPdnHjh3HMDc3Y8iQLrRoofuS//HHS0lMvI+FhRkff+xH48a6k5xTp27k4sVbCCGoUMGJkSNfNRpB0mrTKMjDHq8BAQdYs+aQ0UjinDn9cHa25fvvg9m9+wx37iTj4mJPt24N+b//a5fv9s3Myphs3gDMzY1H/HQ/E7OJsLBzWFtbMnZsX3x8dB3lt9+eg7//SAAiIrJ/HqNFi9oMH/5Gjp9iCdDva876n8ewZdWqYHbuPIKFhTllyljyv/+9QoMG1dBotHz99QZOnLiMEILmzWvzySevAZCZmVDI+3pR//MYkq5dGzJwYFuWLdtD7dqetG5di7S0TKZN28ylS7ext7dh0qSeOdrhBaSmppGZmdUOD8DbW/ddqU+fb5g1qx9VqhR9MqdChf6mM7+9AAttnJ9oJ2rI/btPPCf/6o7is0YIYSelTBFCuAB/Aq311ys+irpNdkcprKNoCgr7glLacncUTU1hHcXSlrujaEpydxRNTWEdxdKWu6NoSorqKJY2U47PlNthyNtRNCWFdRRLW+6OoqnJ3VE0JYV1FE3B09BRXFPW5Yl+N+53784Tz4npturKw9gmhHACrIApj6qTqCiKoiiKoijKs0V1FP9FpJQdSjsGRVEURVEURfm3UzezURRFURRFURRFUZ45akRRURRFURRFURSlBNSIoqIoiqIoiqIoivLMUSOKiqIoiqIoiqIoJaBGFBVFURRFURRFUZRnjhpRVBRFURRFURRFKQEXNaKoKIqiKIqiKIqiPGvUiKKiKIqiKIqiKEoJOKsRRUVRFEVRFEVRFOVZo0YUlWK5c+f30g6hQC4uL5Z2CIWKjd1W2iEUyNzctrRDKJSdXb3SDqFAUmaWdggF0mrTSjuEQpUp41naIRRIo0kt7RAKZGbip3bT06NLO4QCWVq6lHYIhSpTxqu0QyiQEOalHUKBpNSUdgiFSk09W9ohFMjUj4mnQcYTHlG0fKJb0zHxjx1FURRFURRFURTlSVMjioqiKIqiKIqiKCWgRhQVRVEURVEURVGUZ47qKCqKoiiKoiiKoihG1NRTRVEURVEURVGUEnjSU09Lw7//FSqKoiiKoiiKoiglokYUFUVRFEVRFEVRSkCNKCqKoiiKoiiKoijPHDWiqCiKoiiKoiiKUgJqRFFRFEVRFEVRFEV55qgRRUVRFEVRFEVRlBJ4FkYUVUfxERJC9AA2Az5SynOlHE4eQohIoImUMu5R1iulZN68IA4dOoO1tRUTJgykVq3KecqdO3eNKVMCSUtLp1Wrunz66ZsIIQgOPsayZduJjIxm2bLP8PGpAsCff0awePHPZGRosLQ05+OPX6dJk1qPMnQjy5Yto3v37sTExFCvXr3Htp2cpJTMn7+Z0NAIrK2tGDeuL7VqVcxT7ty5KKZN+4m0tAxatvRh2LDXEUKQlJTKhAmB3L4dT4UK5ZgyZRAODmX59dejrF79B1JKypa1ZuTIntSo4VWseObN20Ro6FmsrS0ZP74/tWpVyjeeqVNX6+Opw6efvpEjnpXcuhWPh0c5pkz5PxwcypKScp8vvggkOvouGo2Wvn070r17C27dimfMmGVIKcnM1NCrV1tef71NIbE9/H6WmJjKhAnLuXXrDh4eLkyd+i4ODmVJSrrHtGmruHEjFisrS8aNG0D16p4AJCffY8aM1fz99y2EgHHjBlCvXrWnLndhYedZsOBntFpJ9+7NGDiwo9Hz6emZTJ26lvPnb+DgUJYvv+yPh0c5AAID/2Dbtr8wMxMMG/YazZvXIi0tg48//p709Ew0Gi0dO9bj3XdfMuRhyZJf2bPnFObmZvTo0YI338w/rsfxPj/q9sSUc/e49rljxy4yatRSPD1dAGjfvj7vvOMHwNq1e/jllzAAqlf3ZNy4fpQpY1lkHg8fvsTChb+i1Wrp1u15+vc3fl3p6ZlMn76FCxdu4eBgw6RJvfDwcCIx8R4TJwZx/vxN/PwaMmxYFwDu3UtjyJCVhvVjY5N48cX6DBnycpGxPG25k1Iyd+5PHDp0Wn9MvEPt2lXylIuIiGTKlOWkpWXQqlU9hg/vqz8m/uLHH7cSGXmLFSvG4+PjDUBmZibTpvlz/vxVNBotXbq0ZPDgbsXKX87Yvv56NYcOncLa2oqJE9+jdm3vfGP78sul+uO1PiNG9EcIwTffrGX//hNYWlrg5eXOxInvYm9va1jv9u079O49lv/8pwcDBnQpUWxZ8Zlq7v788wqLFu1Bq5V07epLv37NjZ5PT89k5sydXLgQg4ODNRMndqdCBUeOHInkxx/3k5mpxcLCjA8+aE+jRro2Mjg4gjVr/kQIcHGxY+zYLjg6li1WPIcPX2DBgm1otVq6d2/KgAHt88QzbVqQoa374ou+eHg4AxAYuJft249gZmbG0KHdad68JgDJyfeZNWsTV65EI4Rg9Oie+PpW5ttvd3LoUAQWFhZ4eZVjzJie2NvblCh/ypPx7+8KP1l9gQP6f/MQQvwrO+ahoWeIioolKGgyo0f3Y/bstfmWmz17LWPG9CMoaDJRUbGEhZ0FdB+YM2a8T8OGzxmVd3S046uv/svq1eOYMGEQX3zh/1hfx8qVK/Hz83us28gtNDSC69fjWLduLJ9//iZz5mzIt9ycORsYNeot1q0by/XrcYSF6c5DBAb+QZMmNVi3bixNmtRg1apgADw9y7Fo0f8IDPycwYNfZPbsoGLGc5br12NZv348o0b14auv8l/vq6/WM3p0H9avH8/167GEhUXo49lN48Y1Wb9+Ao0b1yQwcDcAGzfux9u7AgEBo1i0aAgLF/5MRkYmrq4OLFnyKf7+n/Pjj8MJDAwmNjaxgNj+2X4WGPgbTZrUIihoMk2a1CIw8DcA/P13UbOmF6tWjWPixEHMm5f9mufN20CLFnVYt24igYFj8fau8NTlTqPRMnfuZubMeZdVq0awe/cJrlyJNiqzbduf2NvbsG7dKHr3bst33+0A4MqVaHbvPklg4Ai+/vo9vv56MxqNFisrCxYseB9//09ZuXIYYWHnCQ+/CsCOHUeIiUlgzZqRrF49ks6dGxaYs/zzaDrtiann7nHtcwANGlTD3/9z/P0/N3R0YmMTCAoKYfnyEaxePQatVsvu3ceKlcf583cye3Y//P0/Ijj4DJGRsUZltm8/jr29DWvWDOHNN1vwww+6WKysLHj33Y58+OGLRuXLli3DsmUfGP7Kl3eiXbvaRcbytOUO4NCh00RFRbNhw3RGjx7E7NmB+ZabPXsVY8a8zYYN04mKiiY0NByAatW8mDXrfzz/fE2j8sHBR0hPz2DNmi/x95/Ali37uHmzZOeRDx06RVRUNBs3zmLMmMHMmhWQb7lZs/wZO3YwGzfO0sd2GoBmzXz56adprFkzlcqVK7By5Xaj9ebP/4mWLR/+xK2p5k6j0bJgQTAzZ77BihWD+eOP80RG3jEqs3NnOPb21qxa9S69ejVmyZIQABwdbZg27XWWLXub0aO7MGPGTkOd3367h7lz32Tp0repVs2VzZtPFDueuXO3MmfOYAIDh7F798k8bd327Uewt7dh7dqRvPVWa77/fhega+uCg08REDCMOXMGM3fuVjQaLQDffLON5s1rsnr1cFasGEKVKm4ANG36HP7+Q/H3/4RKlVxZtWpfsXNnSjKE2RP9Kw2qo/iICCHsgDbAu0CfHMs7CCH2CyG2AmeFEOZCiK+EEH8JIU4JIT7IWl8IESyEOCaEOC2EeK2A7fjpy5wUQgTrl5UTQmzR1xcmhKivX+4ihPhNCHFGCLEUEDnqGSCE+FMIcUII8YMQwvxhX3tIyCm6dGmOEAJf36qkpNwnLs74C2tcXCKpqQ/w9a2KEIIuXZqzb99JALy9K1ClSvk89daqVQk3NycAqlXzIC0tg/T0jIcNs0j79+8nPj7+sdWfnwMHwvHza6LPnTfJyfeJi0syKhMXl0Rqahq+vt4IIfDza8L+/af1MYfTpUtTALp0aUpIiO7DrV69qjg46M4i1q1bhZiYhGLFs39/OH5+TQ3xFP5eZsXTlJCQ7Hi6dm0GQNeuzQxxCiG4d+8BUkru30/DwaEs5uZmWFpaYGWlO3+SkZGJlNoCY/un+9n+/afo2rW5PrbmhITolkdG3qZxY93Ikrd3BW7fjic+PomUlPucOHGJV15pBYClpQX29gWfmTXV3EVERFGxoiteXi5YWlrQuXMDDhw4Y1TmwIGzdOnSBIAOHepx9OglpJQcOHCGzp0bYGVlgadnOSpWdCUiIgohBGXLlgEgM1ODRqNBCF3zsmVLGP/3f50xM9N9vDg72xWYs/yYUnti6rl7XPtcYTQaLWlpGWRmanjwIB1XV8ci14mIuIGXlzOens5YWprzwgt1OXDgvFGZgwfP8/LL9QFo374Ox45dQUqJjY0V9etXNuzr+YmKusPdu6nUr5935LkgT0vuAEJCTtClSyuEENSrV53k5HvExSXkijWB1NT71KtXXX9MtGLfvuMAVK3qSZUq+Z3kEjx4kE5mpoa0tAwsLCywtbUuVkzZsR2na9fW+tieKyK25xBC0LVra/bt03WSW7TwxcJC9/XD17c6MTHZn8F79x7F09OVatWKng1TcHymmbtz527j5eWEp6eT/pioxaFDl4zKHDx4iZdeqgtA+/Y1OXbsGlJKatQoj6urrm3w9nYhPT2T9PRMpJRICffv6/5/7166oVxRIiKu4+XlgqdnOSwtLejUqT4HDkQYldm/PwI/v0YAdOjgy9Gjf+vbugg6dapvaOu8vFyIiLhOSsoDTp6MpHt3Xfuo+wzVjRo2a1bD8L7XrVupwBPESun7V45wlZLXgF1SygtCiDtCiMZSyqP65xoBvlLKK0KI94FEKWVTIUQZ4KAQ4jcgCnhdSpkkhHAFwoQQW6WUMmsDQgg34Eegnb6ucvqnvgCOSyl7CCFeAAKAhsAk4ICU8kshRDd0nViEED5Ab6C1lDJDCLEY6K9fr8RiYxMpX97J8NjNzYnY2ASjD8HY2ATc3bPLuLs7lahh2LPnOLVqVcLKquhpOk+T2NikfPPi6uqQo0wi7u7ZudTlV9eZvHs32VDWxcWeu3eT82xj27bDtGjhU8x4EnK9l476eHK+l4n5xJwAQHx8sqGsi4sD8fG6eHr2bMuoUT/y6qsTuXfvAV9+OdjwZTg6+i4jR/7A9etxfPzxa7i55f/l6Z/uZwXF9txzXuzde4KGDZ/jzJlIbt+OJyYmATMzgZOTHVOnBnLx4g1q167Mp5/2wsamzFOVu7z7jyNnz0YVWMbCwhxbW2sSE+8RG5tE3bqVjdbNyqdGo+Xddxdw48YdXn+9laHcjRt3CA4+SUhIOE5Odgwb9iqVKrnlm7P882g67Ymp5+5x7XMA4eGRDBo0C1dXRz7++DWqVfPAzc2Jvn078vrrkylTxpJmzWrTvHnRo3hxccm58uhARMSNAstYWJjp83gfJ6eip80FB4fzwgt1DB3u4nhacqeL4y7ly5czPHZ3d9YfE045yiTg7u6cq8zdQuvt1KkxISHH6dZtOA8epDNsWB8cHUt2YicmJm9sMTF3jWKLibmLu3veMrn98ksIL76oO5l3794DAgJ2sGjRZ6xatbNEMeVkqrmLi0vB3d3e8NjV1Z6IiFsFljE3N8PWtgxJSfeNppKGhFykRg13w4mUYcM68957/lhbW+Ll5cQnn3QqVjz5tXUREcZtXVxc/m1dXFwSdepkT9t2d3cgNjaRMmUscHKyZfr0jfz99y1q1vRi6NDu2NhYGdW7fftRXnjhyVzu86g9C9co/vtf4ZPTF8iaI7UW4+mnf0opr+j//xIwSAhxAjgMuAA10I32TRdCnAJ2A15A7tPiLYCQrLqklFmn3toAgfplfwAuQggHoB2wSr98O5DV8nUCGgN/6ePoBOS58EoI8b4Q4ogQ4oi///bcTz8xly/fZPHinxk1Kt8ZvYqeECLPF6WjRy+ybdthPvqoeynFo/v/4cPnqFHDi61bv8Tf/3Pmzt1AauoDAMqXdyYwcDTr109gx44/iY9PKqTWRx/boEEvkZJyn0GDprNhw15q1qyImZlAo9Fy4UIUb7zRloCAMdjYWBEQ8Ntjjy13fKaWuyzm5masXPkpmzaNIyLiGpcv3wZ0o5tWVhYsWzaUV19txowZxZv2/KSYQntiirnLuc/VqlWJTZsmExAwil692jJ69FIAkpLusX9/OBs2TGLr1incv5/Orl1/PbEYC/LHH2fo1Mm31Lb/tObuzJkrmJubsX3712zePIs1a37lxo3Yold8DJYv34q5uTl+fi0B+PHHLfTt+zJly5ZshPNJMYXcXbkSx5IlIXz6qW5admamhq1bT/LDDwMJCvqAatXcWLPmzycaU066z9Cb9OjRnOXLh2BjY8nq1cZTTAMC9mBubsZLLzUsnSCVIqkRxUdAP7L3AlBPCCEBc0AKIT7TF0nNWRwYIqX8NVcdgwE3oLF+lC8SeFwtpAD8pZRjCiskpVwCLAGIj98tcz63YcM+tm49CICPTxWioxMMz8XGJhimeGVxc3Mymv4YE5NQ4MhRTjExdxk9+kcmTBhExYrFH5UwZRs3HmDrVt0NDXx8KhWZFzc3R2JiskdLdPnVjSI6O9sTF5eEq6sDcXFJODlln9G8dOkmM2eu5+uv/4Ojoy0F2bhxP1u3hgJQu3blXO9lYgHx5I7ZCYBy5eyJi9OdlY+LS8TZWXc2dPv2wwwc2BkhBBUruuHh4cLVq9HUqVPFqN5q1Tw4ceIyL7zQEHi0+1lBsdna2jB+/EBAd+ODN96YiJeXKw8epOPm5kTdulUB6NjxecN1jU9D7oy3mXP/STTsP7nLuLs7kZmpITX1AY6OZXFzczCKN7/XZG9vQ6NG1QkLO0+1ahVwc3OkfXvd2eF27XyZPr3ozo6ptiemmLsnsc/lnELXqlVd5szZQEJCCseOXcTTs5xhSmyHDvU5ffoKfn5NC0sjrq72ufKYhKurfb5l3N0dyMzU6vNY9M0tLl26jUajpVYtzyLLPk25Cwr6g59/1l2TVqeON9HR2VMyY2LuFnBM3M1VxpnC/PrrYf3UTwvKlXOgfv3niIiIxMur8GMjKGg3W7bs08dWNU9sOUfnIGsEseAy27bt58CBkyxe/LnhZGd4+GX++OMvFi1aR3LyPczMzLCysuSttzoXGpsuPtPNXRZXVztiYrJHoePiknFzs8u3jJubPRqNltTUNBwcdMdEbGwykyZtZcyYLnh56V7PpUu6jmrW4w4davHTT8XrKObX1uWc2aSLJ6utczRq61xdHYzWjYlJws3NUf/nQN26lfTx+LJqVYih3I4dRzl06Bzz579botkApkSNKCrF1QsIlFJWkVJ6SykrAVeAtvmU/RX4UAhhCSCEqCmEsAUcgRh9J7EjkPe2XBAGtBNCVNWvmzWfYj+6qaMIIToAcVLKJCAE6Kdf3gXIavmCgV5CCPeseoQQ+W2v4Bfcqz0BAWMJCBhLu3YN2LnzMFJKwsOvYGtrk+faC1dXR2xtrQkP1113snPnYdq1q1/oNpKT7zFixHd89NFrNGhQvSThmbSePdvg7z8Sf/+RtGtXj127juhzF4mdnXU+jbMDtrZlCA+PRErJrl1HaNNGd/a8TZu67NypOyu9c+dftG2rW3779l3Gjl3BxIn9qFzZvYh42hpuvKCL5y9DPLa21oW8l1nxZG+3TRtfduzQfTDt2PGnYXmFCs4cOXIBgPj4JK5di8HT04WYmATS0tIB3Rn3U6cuU6VKdryPcj9r06YeO3Yc1sd2mLZtdcuTk++RkZEJwNath2jY8DlsbW1wcXGkfHlnrl7VXdB/5Mj5PDezMeXcZalduyJRUXHcvBlPRkYmu3efpHXrOkZlWreuw86dRwDYu/c0jRrpriVq3boOu3efJD09k5s344mKisPHpxJ376aQnHwfgLS0DP7666LhJgVt29bl2LG/ATh+/DKVKrnmiSk3U21PTDF3T2Kfu3MniayrHs6evYqUWhwdbSlf3pkzZ67y4EE6UkqOHLlQ6A2esvPoxfXr8dy6dZeMDA1//HGG1q2Nbw7SunUtfv31FAD79p3l+eerFuvLY3BweLFHE5+m3L355gusWjWZVasm067d8+zceQgpJadP/42dXVmjqZO6WJ2wtbXh9Om/9cfEIdq1a1hoPipUKMeRI7obo92/n0Z4+OUCrsfLHVtnVq+ewurVU2jfvhE7dhzUx3YJOzubQmLTXb+7Y8dB2rV7HoDQ0FMEBu7k66+HYm2dPa3/xx/H8vPPX/Pzz1/Tp89LDB7cvVidRF18ppu7LLVrV+DGjQRu3UrUHxPnadnSuF1q1ao6v/2muyZ6374LPP98ZYQQpKQ8YMyYzbz3Xlt8fbOv33R1tePq1TskJNwD4OjRq1SpUo7i0B2j2W1dcPAp2rQxvmSlTZva7Nqlu7Z0795wGjWqhhCCNm18CA4+ZWjrrl+Pw8enIi4u9ri7O3LtWqw+nr/x9tZ9Rh0+fIE1a0KYMWMg1tbGU1EV0yJyXAKnPCQhxB5glpRyV45lnwA+wDpgpJSyu365GTAVeAXdyF4s0AOwBH4B7IAj6KaZdpFSRubaVhdgOrpOfoyU8kV9h3E5uumj94D3pZSnhBAuwE/oprEeQjfttbGUMk4I0RsYo68nA/iflDKsoNeYe0QxJyklc+as5/Dhs5QpY8X48QMMt6QfNGg6AQFjAYiIuMrUqYGkpWXQokUdRox4CyEEe/eeYO7cIBISUrCzs6FmzYrMn/8xK1bsJCDgN6NrdObPH0K5csZnol1cjO+G97DWrFlDhw4dcHV1JTo6mkmTJrF8+fJ/XG9s7LYCn9PdunsTYWHnsLa2ZOzYvvj46M6+vf32HPz9RwK6m2pk/TxGixa1GT78jRw/+RBAdPRdKlRw1v88hi0zZqxj375TlC+vOzdgbm7G8uXD82w/9z2MdLc630BYWNbPdfTDx6eyPp7Z+Pt/ro/nmtEt44cP72mIZ/z4Ffp4yjF16mAcHGyJjU1k6tTVhi9RAwd2xs+vKX/+eY6FC7cghEBKSc+e7ejRo1WO+CyMYvsn+1liYgrjxi3LEdu7ODracvr0ZaZMCUQIqFrVg7FjBxhuBHThQhQzZqwhIyMTLy9Xxo0baHhOykyTzZ1Wm2YUW2hoBAsW/KL/aYKmvP12J5Yu/ZXatSvSpk1d0tIymDJlLRcv3sTBoSyTJ/fDy0t3e39//2C2b/8Lc3MzPvnkVVq2rM2lS7eYNm0dWq0WrVbywgv1+b//0x2Hycn3+fLLn4iOTsDGxoqRI9+gRg3j0R5z84JHuEu7PdFoUo0em1LuzMyMr499XPvchg0hbN58EHNzM8qUseSTT16nXj3dyPrSpTvYvfs45uZm1KxZkTFj+ua4qZLxXRtzCgu7qP95DEnXrg0ZOLAty5btoXZtT1q3rkVaWibTpm3m0qXb2NvbMGlSTzw9de1X794LSE1NIzNTg52dNXPmDMDbW/c+9unzDbNm9aNKlcJPSFhauph07szNC76+TUrJV1+tJiws3PATD1k/0zBggK5DpIs1ki+/XKaPtR4jR/bTHxPHmDNnDQkJydjZlaVmzUp8881w7t17wJQpy7ly5RZSSrp3b8PAgXnv/F3Yve50sQUSGnoaa+syTJjwLnXq6F5v//4TWL16CgBnz14x+nmMkSMHIITgjTc+Jz090zDrxde3OmPGDDbaxpIlmylb1jrfn8eQUlNgbKaQu9TUswXGFhZ2mcWL9+p/XsOXAQNasGLFQWrWLE/r1s/pfzJmJ5cuxWBvb82ECd3w9HQiMDCMn346jJdX9qjn7Nm9cHYuy9atJ9m06RgWFma4uzswapRfgSPzuY+J0NDzfPPNNrRaSbdujRk0qCNLl/6ub+t8SEvLYOrUoBxtXR88PXUd0YCAPWzfflTf1nWjRQvdDeIuXrzJrFmbycjQ4OnpzNixvbC3t6FPnzlkZGhy3HSvEiNH9jCKx929p8kPMx7zeP6JdqIa3Tr+xHOiOopKsRTWUSxtj6qj+LgU1lEsbf/gZrdPhCn/okzujqIpyd1RNDWFdRRLW+6OoinJ3VE0NYV1FEtb7i/FpqawjmJpM+XPiaI6iqWtsI5iaTP1Y0J1FPMqjY6imnqqKIqiKIqiKIqiGDHd0/WKoiiKoiiKoigmSN3MRlEURVEURVEURXnmqBFFRVEURVEURVGUElAjioqiKIqiKIqiKMozR40oKoqiKIqiKIqilIAaUVQURVEURVEURVGeOWpEUVEURVEURVEUpQTUiKKiKIqiKIqiKIryzFEjioqiKIqiKIqiKCWgRhQVRVEURVEURVGUZ44aUVSKRcrM0g6hQLGx20o7hEK5uXUv7RAKFBOzpbRDKJS5uek2UVptWmmHUKDMzMTSDqFQZmZlSjuEAply7szNbUs7hEKZmVmXdggF0mhSSzuEQplye6LRpJR2CAUyN7cr7RAKVbZszdIOoUDOzh1KO4SnnhpRVBRFURRFURRFUZ45pnu6XlEURVEURVEUxQSpEUVFURRFURRFURTlmaNGFBVFURRFURRFUUpAjSgqiqIoiqIoiqIozxzVUVQURVEURVEURVGMqKmniqIoiqIoiqIoJaCmniqKoiiKoiiKoijPHDWiqCiKoiiKoiiKUgJqRFFRFEVRFEVRFEV55qgRRUVRFEVRFEVRlBJ4FkYUi+woCiEkMFdKOUL/eCRgJ6Wc/E83LoRYCWyTUm74p3U9LkKIJsAgKeUnQojBQBMp5celHFapk1Iyb94mQkPPYm1tyfjx/alVq1KecufORTF16mrS0jJo2bIOn376BkIIkpJSmTBhJbduxePhUY4pU/4PB4eyhvXOnr3KBx/M54sv3uaFFxoCcPt2PDNmrCUmJgEh4OuvP8DDw6VYsc6fv5nQ0Aisra0YN64vtWpVzDfWadN+0sfqw7Bhr+eINZDbt+OpUKEcU6YMwsGhLL/+epTVq/9ASknZstaMHNmTGjW8Hj6phVi2bBndu3cnJiaGevXqPdK6w8LOs2DBz2i1ku7dmzFwYEej59PTM5k6dS3nz9/AwaEsX37ZHw+PcgAEBv7Btm1/YWYmGDbsNZo3r1VonR99tJh799IAuHs3hTp1KjNjxtukpNznyy/XEh2dgEajpW/fdnTr1tQoDt0+F8ShQ2ewtrZiwoSB1KpVOc/rOXfuGlOmBJKWlk6rVnX59NM3EUKQmJjKhAnLuXXrDh4eLkyd+i4ODmVJSrrHtGmruHEjFisrS8aNG0D16p4AvP76BMqWtcbcXGBubs6KFaOeity9/HLNAt/vw4f/ZtGi39BoJN26NaR//1Z5Yp4xYyvnz9/G0dGGiRNfx8PDicTEe0yatIlz527i51efYcP8DOsEB59h1aqDCCFwcbFj3LjXcHIqm3vTBXpc7cmxYxcZNWopnp66dqJ9+/q8844u7nXr9rJ1aygAr77akt69OxQZp6nl7vDhCyxYsA2tVkv37k0ZMKB9nnimTQsy7H9ffNEXDw9nAAID97J9+xHMzMwYOrQ7zZvX5Nq1WCZNWmtY/+bNeN59tzNvvdWaSZN+4tq1OABSUu5jZ2fDihVDTCa+PXtOs3x5MFevxrJkyYfUrp23jX+acveo25bo6ASmTl3L3bspgODVV5vz1lttALh48SZz5mzi/v10KlRwZtKkvtjaWhcaX3YeL7Fw4a9otVq6dXue/v3b5Ilz+vQtXLhwCwcHGyZN6mU4JiZODOL8+Zv4+TVk2LAueeoeM2Ytt27dZeXKD4sVy9OUN9C1e3PnriM0NJwyZayYMGEwtWvn95l2lSlTVurbPV+GD++NEILg4KMsXfoLkZG3Wb58ND4+3gCcOXOFmTNX6bcB773XnQ4dni92XPnFOW3aNPbt24e1tTUzZ86kbt26ecqFh4czZswYHjx4QPv27Rk3bhxCCM6dO8ekSZO4d+8eXl5ezJkzBzs7u4eOR3myitMVTgPeEEK4Pu5gSkII8URGQ6WUR6SUnzyJbT1NQkPPcv16LOvXj2fUqD589VVQvuW++mo9o0f3Yf368Vy/HktYWAQAgYG7ady4JuvXT6Bx45oEBu42rKPRaFm8+BeaNatlVNeUKavp3/8FfvppLEuXjsDZ2b6YsUZw/Xoc69aN5fPP32TOnPzPS8yZs4FRo95i3bqxXL8eR1jYOX2sf9CkSQ3WrRtLkyY1WLUqGABPz3IsWvQ/AgM/Z/DgF5k9O/8cPAorV67Ez8+v6IIlpNFomTt3M3PmvMuqVSPYvfsEV65EG5XZtu1P7O1tWLduFL17t+W773YAcOVKNLt3nyQwcARff/0eX3+9GY1GW2idixd/xMqVn7Jy5af4+lahXTtfADZtCsXbuzz+/p+ycOEHLFq0jYyMTKM4QkPPEBUVS1DQZEaP7sfs2WvJz+zZaxkzph9BQZOJioolLOwsAIGBv9GkSS2CgibTpEktAgN/A8Dffxc1a3qxatU4Jk4cxLx5xu/jt98OJSBgbJ5OomnnTlPg+71gwS5mzeqDv/8H/PHHGSIjY43K7NhxAjs7a9as+YhevZqxZMkfAFhZWfDOO+358MNORuUzM7UsXPgb8+YNYPny/1C9ujubNx/Jd/sFeZztSYMG1fD3/xx//88NncS//77J1q2hLFs2An//zzl48AzXr8fmu01TzZ1uX9nKnDmDCQwcxu7dJ/Psf9u3H8He3oa1a0fy1lut+f77XYBu/wsOPkVAwDDmzBnM3Llb0Wi0VK7sxooVQ1ixYghLl/4Pa2tL2rWrA8AXX/Q1PNe+va9huanEV7VqeaZN60+DBt7/ktw92rbF3NyMjz/uzqpVI1my5H9s2nTIUOesWRv473+7EBAwnHbtfFmzZl+ROcyKc/78ncye3Q9//48IDs57TGzffhx7exvWrBnCm2+24IcfdMemlZUF777bkQ8/fDHfukNCIrCxsSpWHE9b3rKEhoYTFRVDUNAUxowZwOzZq/MtN3v2GsaMGUhQ0BSiomIIDT0DQLVqnsyc+V8aNqxhVL56dS9WrBhLYOAE5s//hFmzVpOZmf9nQnGEhIQQGRnJb7/9xpQpU5g8eXK+5SZPnsyUKVP47bffiIyMJCQkBIBx48YxYsQIfvnlFzp37szSpUsfOhZTkyHMnuhfaSjOVjOBJcCnuZ8QQqwUQvTK8ThF/28HIcQ+IcTPQojLQoiZQoj+Qog/hRCnhRDVc1TTWQhxRAhxQQjRXb++uRDiKyHEX0KIU0KID3LUu18IsRU4myuW/wohvsrxeLAQYpEQwlsIcU4f6wUhxGohRGchxEEhxEUhRDN9+WZCiFAhxHEhxCEhRK0c29xWWIKEEJOFEP762K4KId4QQszWv9ZdQghLfbnG+rwcFUL8KoTw0C//RAhxVv9a1+qXtRdCnND/HRdC2Ash7IQQwUKIY/q6X8sRwwQhxHkhxAEhxE/6kV+EENX1MRzVx1dbv/xNIUS4EOKkECKk8F0gr/37w/Hza4oQAl9fb1JS7hMXl2hUJi4ukdTUB/j6eiOEwM+vKSEhpw3rd+3aDICuXZuxf/9pw3obNoTQsWMDo47glSu30Wg0NGtWG4CyZctgbV28D5EDB8Lx82tiiDU5+T5xcUm5Yk0iNTUtR6xNDDHt3x9Oly660a0uXZoSEhIOQL16VQ2joHXrViEmJqFY8TyM/fv3Ex8f/8jrjYiIomJFV7y8XLC0tKBz5wYcOHDGqMyBA2fp0qUJAB061OPo0UtIKTlw4AydOzfAysoCT89yVKzoSkREVLHqTE19wNGjf9Oune6spBBw714aUkru30/HwaEs5ubGzVNIyCm6dGmufx+rFrHPVUUIQZcuzdm37yQA+/efomvX5gB07dqckBDd8sjI2zRurDsp4e1dgdu344mPN94/nvbcZTl37iZeXuXw9HTG0tKcF16ow8GDF4zKHDx4ET+/+gC0b+/D0aORSCmxsbGifv1KWFnlPkcnkRIePMhASklqahquriU7W/w425P8XL0aTd26VbC2tsLCwpznn3+OvXtPFbqOqeUuIuI6Xl4ueHqWw9LSgk6d6nPgQIRRmf37I/DzawRAhw6+HD36t37/i6BTp/qG/c/Ly4WIiOtG6x49+jeenuWoUMHZOGIp2bPnNJ07NzCp+Ly93alc2e1fkrtH37a4ujoYZtKULWuNt7e74RiLioqjYcNqADRtWoN9+wo/frLjvIGXl3OOY6IuBw6cNypz8OB5Xn4565iow7FjV3IcE5XzOSbg3r101q8PY9CgtsWKIzuepyNvWUJCTtK1awt9u1etkHbvPr6+1RBC0LVrC0JCTgBQtaoHVapUyFNvVrsGkJ6eUaKY8hMcHEyPHj0QQtCwYUOSkpKIiYkxKhMTE0NKSgoNGzZECEGPHj0IDtadVI+MjKRpU913qNatW/Pbb7/945iUJ6e43dNvgf5CCMcS1N0A+C/gAwwEakopmwFLgZxzLryBZkA34HshhDXwLpAopWwKNAX+I4Soqi/fCBgqpcw9t2oj8HqOx72BrCGH54Cvgdr6v35AG2AkMFZf5hzQVkr5PDARmF6C1wpQHXgBeBVYBeyRUtYD7gPd9J3FhUAvKWVjYDkwTb/uaOB5KWV9dDlDH9v/pJQNgbb6eh4Ar0spGwEdga+FTlOgJ7qcdwGa5IhrCTBEv82RwGL98onAy1LKBvqYSyQ2NoHy5Z0Mj93cHImNTcxVJhF39+wy7u5OxMYmABAfn4yrq253cnFxID4+2VDvvn2neP311kZ1XbsWg52dDWPGLOPtt2ezaNHPaDTaYsaalE8c+cWavXu7uTkRG6vrLNy9m4yrq4M+Vnvu3k3Os41t2w7TooVPseIxJXlft6PhdedXxsLCHFtbaxIT7+XJa9Y+UJw6Q0LO0KTJc4ZpOj17tuLq1Wh69JjK22/PZejQVzEzM26eYmMTc+1z2ftTdpmEAt/rgva5557zYu/eEwCcORPJ7dvxhk6/EIKhQxcxePBMtmw58BTlTpCf2Nhk3NyyT8C4uTkQG5ucTxkHfcxm2NmVITHxfr71Zb2uTz/14513ltCz5wKuXo2ja9eGBZbPP67H054AhIdHMmjQLIYP/57Ll28BUK2aBydPXiYxMZUHD9I5dOgsMTF3i4jRtHKX376S9wRY/vtfXFyS0bru7g558h0cfCrfDs3Jk5E4O9tRqVLhk4xKK77ieBpz90/blpxu3YrnwoWb1Kmjm+ZYtWp59u/Xdaj27DlFdHRCofFliYtLzhWnA3FxyQWWsbAw08dZ8DEBsHz5Ht56qyVlylgWK44sT0vesmNJwN29nOGxrk27m6vMXdzcnHOUcc7zuZef8PAr9O07mf79v2TUqP6GjuPDiI6OpkKF7A5phQoViI6OLnaZGjVqGDqNu3bt4tatWw8di6lRI4p6UsokIAAoyRTMv6SUt6SUacDfQNYphNPoOodZ1ksptVLKi8BldB25l4BBQogTwGHABcgaW/9TSnklnxhjgctCiBZCCBd9PQf1T1+RUp6WUmqBM0CwlFLmisURCBJChAPzgLwTsAu3U0qZoa/THNiV6/XWAnyB3/WvazyQdRHFKWC1EGIAuhFc9LHPFUJ8AjhJKTMBAUwXQpwCdgNeQHmgNfCzlPKBlDIZ+AVACGEHtNK/rhPAD4BHjvpXCiH+o483DyHE+/rR3iP+/jtKmI7iE0Ig9N9r58/fzEcf5e0kaDRaTp68zMcfv8ayZSO4eTOOHTsOP7aYCo/V+Ev40aMX2bbtMB991P2Jx/O02r37BJ07NzQ8Pnz4AjVqeLJly3hWrBjGvHlbSE198Ni2n3OfGzToJVJS7jNo0HQ2bNhLzZoVDR2t778fjr//aObO/R8bN4Zw/PjFxxZTcRUvd2lPLJ7MTA1btx7jxx/fY+PGoVSr5s7q1Yee2PZzy/ne1qpViU2bJhMQMIpevdoyerRuypO3dwUGDOjEsGGL+fTT76lZ0ytPm/MkmFrusmRkZHLwYAQdO/rmeW737pN07ly/FKLKVlh8pc3Uc3fvXhrjxgUydOgrhpNNY8a8yebNobzzzgLu3UvD0rL07nN48eJtbty4S7t2tUsthvyYet5y8/Wtyk8/TWb58jEEBOwiLe2fjyw+rGnTprFmzRreeOMNUlNTsbIq2ZRipXSVZK+eDxwDVuRYlom+symEMANyvvs5v6loczzW5tquzLUdia5DNERK+WvOJ4QQHYDUQmJcC7yFbnRws5RS6r/UFyeWKehGAV8XQngDewvZTn7SAKSUWiFEhr4jmnMbAjgjpWyZz7rdgHbAK8A4IUQ9KeVMIcR2oCtwUAjxMtACcAMaSykzhBCRQGFXTpsBCfpRSSNSyv8KIZrrt31UCNFYSnknV5kl6EYkuXNnl9y4cb/h5g+1a1c2OnsWG5uIm5vxgLObm6PRdMyYmATc3JwAKFfOnri4RFxdHYmLSzRMMz137hoTJ/oDkJiYwqFDZzE3N8Pd3YkaNbzw8tKdiW3btj5nzkTyyiv5v/CNGw+wdWsYAD4+lfKJI79Ys88exsYmGEYGnJ3tiYtLwtXVgbi4JJycsqeGXbp0k5kz1/P11//B0dE2/2BMWN7XnWh43bnLuLs7kZmpITX1AY6OZXFzczDKa859oLA6ExJSiYiIYvr0QYZlO3YcYcCAjgghqFjRFQ+Pcly9GsP58+Fs3ao73+PjUyXXPpe9P2XH6lTge13QPmdra8P48QMB3dSwN96YaNjPss4wlytnT/v2DTh79irPP1/D5HN37VocPj55b6zk5mZvNAoWG5tkNEqWXSYJd3cHMjO1pKSk4ehok6euLJcu6c4ae3npznp37FiHNWuK7uw8ifYk540lWrWqy5w5G0hISMHJyY5XXmnJK6/omuPvv/8lz76UmynlTretvPtf1syHLK6uWfufo9H+5+rqYLRuTEySUb7Dwi5Qs6Yn5coZv77MTA0hIWdYurTo+7mVRnzF9TTm7lG0LZmZGsaPD+Sll56nffvsm6JVqeLOvHn/AeDatVhCQ88VGSOAq6t9rjiTcHW1z7dM1jGhi7PgY+LMmeucP3+T3r0XoNFouXs3laFD/Vmw4O0i43ka8rZhwx5+/lk3O8XHx5uYmOxLSnRtmvF0ZTc3Z6NRxpiYu0W2VTlVreqBjU0ZLl++YbjZTXGsXr2a9evXA1CvXj1u375teO727duUL1/eqHz58uULLFO9enWWL18OwJUrV9i7d2+x4zB1z8JdT4v9CqWU8cB6dNNCs0QCjfX/fxUo2TwBnTeFEGZCd91iNeA88CvwYY5r+2oKIYrzLXwz8BrQl+xpp8XlCNzQ/39wCdctjvOAmxCiJYAQwlIIUVffwa4kpdwDjNLHYSeEqK4fBZ0F/IVuhNQRiNF3EjsCVfR1HwReEUJY60cRu4NhJPiKEOJN/TaFEKKB/v/VpZSHpZQTgVgg7y0Gc+nZs63hphDt2tVj166/kFISHh6Jra21YepXFldXR2xtrQkP112ns2vXX7RtqzvL2qaNLzt2/AnAjh1/GpZv3DiJTZt0fx07NmTkyDdp374+Pj6VSUm5r7/zGBw9eoGqVfPOzc+OtQ3+/iPx9x+pj/WIIVY7O+t8vhQ4YGtbJkesR2jTJivWuuzc+RcAO3dmv4bbt+8yduwKJk7sR+XK7kWlzyTVrl2RqKg4bt6MJyMjk927T9K6tfGNFlq3rsPOnbobbOzde5pGjZ5DCEHr1nXYvfsk6emZ3LwZT1RUHD4+lYqsc+/eU7Rq5WM0rah8eSeOHNGN1sXHJ3PtWiyeni706tWegICxBASMpV27BuzceVj/Pl7B1tamkH1Odx3Mzp2HaddOdwa/TZt6hlHoHTsO07atbnly8j3DjXO2bj1Ew4bPYWtrw/37aYZRzfv30zh8OIJq1TwM2zLl3GXdnTG3WrU8uX49nlu3EsjI0PDHH2dp1cp4Fn+rVjXYtUt3vd6+fRE0auSdZxTdOOf2REbGkpCgO4d35MhlqlQp+t5nT6I9uXMniaxzdmfPXkVKreGETtb01Nu349m79xQvvdSYwphS7gBq1/bi+vXsfSU4+BRt2hhPf2/Tpja7dh0DYO/ecBo10l3n1KaND8HBpwz73/Xrcfj4ZN8ldPfuk3TqlHfq5NGjf1O5spvR9D5Tiq+4TD93j75tkVIyY0YQVaq406dPO6O6sj5XtVot/v7BvPZai2JkMSuP8dy6dVd/TJyhdWvjY6J161r8+mvWMXGW55+vWugx0aNHEzZtGs66dUNZuPD/qFTJpVidRF08pp+3Xr06Ehg4gcDACbRv35AdO8L07d5l7OwK+kyzITz8MlJKduwIo127wvf9mzfjDDevuXXrDlev3sbDo2T3o+zfvz8///wzP//8M507d2bLli1IKTlx4gT29va4uxt/53F3d8fOzo4TJ04gpWTLli106qS7ededO7oxCK1Wy3fffUefPn1KFItSuko6Tv41kPN02I/Az0KIk+imWhY22leQa8CfgAPwXynlAyHEUnTTNY8JXYsSC/QoqiIp5V0hRARQR0r5ZwnjmA34CyHGA9tLuG6RpJTpQnfjn2/013paoBulvQCs0i8TwDdSygQhxBR9ZzBruuxOwB74RQhxGjiCbuQUKeVfQneDn1NANLrprlmn1foD3+lflyW6DvRJ4CshRA39NoP1y4qtVas6hIae5c03p+h/cqKf4bm3356Nv//nAIwc+abR7exbttQ12gMHdmb8+BVs2xZGhQrlmDp1cKHb09157DU++WQRUkLt2pV49dX8BmfzatnSh9DQCN56azrW1paMHds3R6xz8PcfCcCIEb0MP4/RokVtWrb00cfaiQkTAti27TAVKjgzZYpuNGfFit9ISrrHnDkbDTEuXz68WDGV1Jo1a+jQoQOurq5ERUUxadIkwxm6f8LCwpzhw19j+PCl+tubN6VatQosXfortWtXpE2bunTv3pQpU9bSu/csHBzKMnmy7r2uVq0CL7xQnwED5mBubsbw4T0MN1HJr84su3efZMAA41uWDx7ciWnT1jNo0FyklHz4YVecnIzPDbVqVZdDh87w5puTKVPGivHjBxieGzRoOgEBusuNP/usN1OnBurfxzq0bFlXX+Ylxo1bxi+/HNLvc7pzXpGRt5kyJRAhdGdfx47V1Rsfn8zo0UsA0Gg0vPRSU0Ndpp+7/H9ewcLCjKFDX+azz35Cq9XSpUsDqlZ1Y/nyfdSq5UHr1jXp2rUh06f/TL9+i3FwsGbixOxLv3v3XsS9e2lkZGg4cOACc+b0xdvbjbffbssnnwRiYWFO+fIOjB5dwFB/AR5Xe7Jnzwk2bz6IubkZZcpY8uWXgw1fUseNW05iYioWFuaMHNkLe/vCf5LC1HKnu77xVUaMWIFWK+nWrTFVq5Zn6dLf9fufD926NWHq1CD69Jmj3/90X9CqVi3PCy/UY+DA+fr971XD/nf/fjpHjlzis89ez7PN3buLf13gk44vJOQM8+f/QkJCKp9/7s9zz3kyd+7/mURsD5O7R922nDx5hV9/PUb16hUYPHgeAB984EfLlj78/vsJNm3SjWS3b+9Lt25NCozNOE4zhg3rwsiRq9FqJV27NqRqVXeWLdtD7dqetG5di65dn2fatM3067cQe3sbJk3qaVi/d+8FpKamkZmp4cCBc8yZMwBv7+LdkOhpzluWVq18OXToNL16jcfa2orx47M7xAMHTiEwcAIAn33WlylT/ElLS6dlS19attSdCNu79zhff72WhIQUhg9fRM2alViwYCgnT14iIGAXFhbmCCH47LN+RjOhSqp9+/bs27ePF198ERsbG6ZPz76Fx2uvvcbPP/8MwKRJkww/j9GuXTvatdN1rLdt28aaNWsAePHFF+nZs2fejTylnoURRZE9Q1J5mgkh7KSUKUKIskAI8L6U8tijqv/OnV0mu6NI+fC3fX4S3NxM99rFmJgtpR1CoczNTXc6r0bzMOfFnozMzMSiC5UiKyvTHYFPT48pulApMeXjQflnntAvfj0UjSaltEMokLm5af8en4VFSe4B+WQ5O3co7RCKUvDQs4mYUvu1J/rdeMK5n594Tky3ZVJKaokQog66axb9H2UnUVEURVEURVGUbM/CiKLqKP5LSCn7FV1KURRFURRFURSlaP/+rrCiKIqiKIqiKIpSImpEUVEURVEURVEUpQSehamn//5XqCiKoiiKoiiKopSIGlFUFEVRFEVRFEUpATWiqCiKoiiKoiiKojxz1IiioiiKoiiKoihKCagRRUVRFEVRFEVRFOWZo0YUFUVRFEVRFEVRSkCNKCqKoiiKoiiKoijPHDWiqBSLRpNa2iEUyNzctrRDKFRMzJbSDqFA7u49SjuEQkVHbyjtEApUvnyv0g6hQKacN4CMjDulHUKBTL09MWWZmYmlHUKBLCwcSzuEQpnyfidlZmmHUCBTzpup+/33MqUdQqFefDGttEMokhpRVBRFURRFURRFUUyaEMJPCHFeCHFJCDE6n+crCyH2CCGOCyFOCSG6FlWnGlFUFEVRFEVRFEUpAVMaURRCmAPfAi8C14G/hBBbpZRncxQbD6yXUn4nhKgD7AC8C6vXdF6hoiiKoiiKoiiKUlLNgEtSystSynRgLfBarjIScND/3xG4WVSlakRRURRFURRFURSlBJ70iKIQ4n3g/RyLlkgpl+j/7wVE5XjuOtA8VxWTgd+EEEMAW6BzUdtUHUVFURRFURRFURQTpu8ULimyYMH6AiullF8LIVoCgUIIXymltqAVVEdRURRFURRFURSlBEzpGkXgBlApx+OK+mU5vQv4AUgpQ4UQ1oArEFNQpSb1ChVFURRFURRFUZQS+QuoIYSoKoSwAvoAW3OVuQZ0AhBC+ADWQGxhlaoRRUVRFEVRFEVRlBIwpRFFKWWmEOJj4FfAHFgupTwjhPgSOCKl3AqMAH4UQnyK7sY2g6WUsrB6VUdRURRFURRFURTlKSal3IHuJy9yLpuY4/9ngdYlqdN0usKKoiiKoiiKoiiKSVAjioqiKIqiKIqiKCVgSlNPH5enqqMohHABgvUPKwAasi/CbKb/gcmsssPQ/b7IvSLq3AuMlFIeKaRMB32Z7g8be0no5xOHSCl3P8S6TkA/KeXiRx5YDocPX2DBgm1otVq6d2/KgAHtjZ5PT89k2rQgzp+/gYNDWb74oi8eHs4ABAbuZfv2I5iZmTF0aHeaN68JQHLyfWbN2sSVK9EIIRg9uie+vpX59tudHDoUgYWFBV5e5Rgzpif29jYFxialZN68TYSGnsXa2pLx4/tTq1alPOXOnYti6tTVpKVl0LJlHT799A2EECQlpTJhwkpu3YrHw6McU6b8Hw4OZUlJuc8XXwQSHX0XjUZL374d6d69BbduxTNmzDKklGRmaujVqy2vv97GaFthYedZsOBntFpJ9+7NGDiwY558TZ261pCvL7/sj4dHOX2+/mDbtr8wMxMMG/YazZvXKrTOjz5azL17aQDcvZtCnTqVmTHjbVJS7vPll2uJjk7Qx9+uuG93kZYtW0b37t2JiYmhXr16j6ze3J7kfnfx4k3mzPmZ9PRMzM3NGD78VerUybsf/VNPKndZHnUOr12LZdKktYb1b96M5913O/PWWyWa3ZIjvkssXPgrWq2Wbt2ep39/42MpPT2T6dO3cOHCLRwcbJg0qRceHk4kJt5j4sQgzp+/iZ9fQ4YN62JYJyNDw/z5OzlxIhIzM8F7771A+/Y+DxGb6eXucRwTABqNlv/851tcXR2YPfttAGbO3Mi5czeQEipVcmHs2F6ULVumWHH++edlFi0KRqPR0q1bA/r1a5EnzhkztnPhwm39+/oaFSo4cuTIFZYs2UdmpgYLC3P++9+ONGpUBYDPP1/PnTspaDRa6tevxNChL2JuXrwvbk9L3nLTfb4FcejQGaytrZgwYSC1alXOU+7cuWtMmRJIWlo6rVrV5dNP30QIQXDwMZYt205kZDTLln2Gj0+Vh4ojy+PI47p1B9i27QhCQLVqFRgzpidlylj+ozjB9HInpWTu3HWEhoZTpowVEyYMpnbt/OK5ypQpK/XfVXwZPry3Pp6jLF36C5GRt1m+fDQ+Pt4AnDlzhZkzV+m3Ae+9150OHZ5/6DjPnrVhw4ZyaLXQqlUKL72UaPR8cLADoaF2mJmBnZ2GAQPiKFdOA8C335YnMrIM1ao94MMPC7yxpmLCnqqusJTyjpSyoZSyIfA9MC/rcc5Oot4woOyTjvFRkFJOfJhOop4T8NEjDCcPjUbL3LlbmTNnMIGBw9i9+yRXrkQbldm+/Qj29jasXTuSt95qzfff7wLgypVogoNPERAwjDlzBjN37lY0Gt3Pt3zzzTaaN6/J6tXDWbFiCFWquAHQtOlz+PsPxd//EypVcmXVqn2Fxhcaepbr12NZv348o0b14auvgvIt99VX6xk9ug/r14/n+vVYwsIiAAgM3E3jxjVZv34CjRvXJDBQ91Zs3Lgfb+8KBASMYtGiISxc+DMZGZm4ujqwZMmn+Pt/zo8/DicwMJjY2OyGVJevzcyZ8y6rVo1g9+4TefK1bduf2NvbsG7dKHr3bst33+0w5Gv37pMEBo7g66/f4+uvN6PRaAutc/Hij1i58lNWrvwUX98qtGvnC8CmTaF4e5fH3/9TFi78gEWLthXxThffypUr8fPze2T15edJ73fffbeL//u/F1ixYgjvvtuZ777b9Vhe15PIXZbHkcPKld1YsWIIK1YMYenS/2FtbUm7dnUeOr7583cye3Y//P0/Ijj4DJGRxjdk2779OPb2NqxZM4Q332zBDz/ojk8rKwvefbcjH374Yp56AwP34+xcltWrP8bf/yMaNCj5FzxTzN3jOiYAgoIOGY6FLEOGdGPlyk/w9/+E8uWd2LQprNhxLljwOzNnvsnKle8RHHyWyMg4ozI7dpzC3t6a1as/4M03m/DDD3sBcHQsy/TpPVm+/F3GjOnGjBnZ7dakSa+xbNk7rFjxLgkJ99i379y/Km/5CQ09Q1RULEFBkxk9uh+zZ6/Nt9zs2WsZM6YfQUGTiYqKJSzsLADVq3syY8b7NGz43EPHkOVx5DE2NpGNG0NZuvR/BAQMQ6vVEhx86h/HCqaVO1084URFxRAUNIUxYwYwe/bqAuJZw5gxAwkKmkJUVAyhoWcAqFbNk5kz/0vDhjWMylev7sWKFWMJDJzA/PmfMGvWajIzNQ8Vo1YL69eX46OPohk//gZHj9py65Zxp71SpXQ+//wWY8fe5Pnn77FlSznDc507JzJoUKE31XyqZQizJ/pXGp6qjmJ+hBCdhBDHhRCnhRDLhRBlhBCfAJ7AHiHEHn2574QQR4QQZ4QQXxSjXj8hxDkhxDHgjRzLmwkhQvXbPCSEqKVfHiKEaJij3AEhRINcdQ4WQmwRQvwuhIgUQnwshBiurytMCFFOX26lEKKX/v+RQogvhBDH9K+xtn75ZCHEyBx1hwshvIGZQHUhxAkhxFf65z4TQvwlhDiV9dqFELZCiO1CiJP6dXsXN+cREdfx8nLB07MclpYWdOpUnwMHIozK7N8fgZ9fIwA6dPDl6NG/kVJy4EAEnTrVx8rKAk/Pcnh5uRARcZ2UlAecPBlJ9+5NALC0tDCMGjZrVgMLC3MA6tatZNQJy8/+/eH4+TVFCIGvrzcpKfeJizNeJy4ukdTUB/j6eiOEwM+vKSEhpw3rd+3aDICuXZuxf//prBxz794DpJTcv5+Gg0NZzM3NsLS0wMpKNzifkZFJ7t8tjYiIomJFV7y8XLC0tKBz5wYcOHDGqMyBA2fp0qWJPl/1OHr0kj5fZ+jcuYEhXxUruhIREVWsOlNTH3D06N+0a1dXHz/cu5emjz8dB4dHdx5l//79xMfHP7L68vOk9zsQpKbqRmZTUx/g6mr/WF7Xk8hdlseRw5yOHv0bT89yVKjg/JDx3cDLyxlPT2csLc154YW6HDhw3qjMwYPnefnl+gC0b1+HY8euIKXExsaK+vUrG47FnHbsOGEYmTQzEzg5lXzfN8XcPa6YYmISCQ09R/fuTY3qsrW1BnQjIWlpGQhRvDjPnbuFp6cTnp5O+vfVh4MHLxqVOXjwIi+/rDup1b59bY4du4qUkho1yhuOPW9vV9LSMklPz9THoxuV02i0+i/CxQvoaclbfkJCTtGlS3P951vVIj7fqiKEoEuX5uzbdxIAb+8KVKlS/uEDyOFx5VGj0ZKWlkFmpoYHDzJwdXV4JPGaUu508Zyka9cW+niqFRLPfXx9qyGEoGvXFoSEnACgalUPqlSpkKdea2srw3em9PSMfxRjZGQZXF0zcXXNxMICGjVK5dQp4/azZs0HWFnpbpzp7Z1GQoK54blatR5QpkyhN9VUTNzT3lG0BlYCvaWU9dBNpf1QSvkNcBPoKKXMmuM3TkrZBKgPtBdC1C+oUv0PUP4IvAI0RjfNNcs5oK2U8nlgIjBdv3wZMFi/fk3AWkp5Mp/qfdF1PJsC04B7+rpCgUEFhBQnpWwEfAeMLKBMltHA3/pR1s+EEC8BNYBmQEOgsRCiHbof3LwppWwgpfQFij1cEhubiLu7o+Gxm5sjcXFJxgHHZZexsDDH1taaxMR7xMUlGa3r7u5AbGwit27F4+Rky/TpG3nnnYXMnLmJ+/dzDxLD9u1Hjab55B9fAuXLOxnFl7tzqXsN2WXc3Z2IjU0AID4+GVdXXYwuLg7ExycD0LNnW65ejebVVycycOBMhg17AzMz3SEUHX2XgQNn0qPHJAYM6Iybm2OubRnnKzbWOF85y+TMV2xsklGcWa+lOHWGhJyhSZPnDF9SevZsxdWr0fToMZW3357L0KGvFppHU/Ok97tPPunG4sU76dlzFt9+u5MPPnj5CbzKx+tx5DCn4OBTdO5sdH6sROLiknPF50BcXHKBZSwszPTx3S+wzuTkBwAsW7aH995bwsSJQcTHp5Q4NlPM3eOK6ZtvtvHRR10wM8vbo5k+fQOvvTada9di6dmzZbHi1L1n2V/23dzsiYtLyVUmBXd3XYfQ3NwMO7syJCUZv68hIeepUaO80cmAzz5bx+uvL8TGxor27WsVK56nJW8FxW78+Zb92ZVdJiGfz7fCT7A+bCyPOo9ubo706dOGXr1m06PHDOzsrGnWzHjE7J/Eayq5y95W9uibblt3c5W5i5ubc44yznlizk94+BX69p1M//5fMmpUf0PHsaQSE81xds40PHZ2ziQxseC6QkPtqFOn4Pb430aNKJo+c+CKlPKC/rE/UNCFV2/pRwePA3WBwub31NbXe1H/+yKrcjznCAQJIcKBefq6AIKA7kIIS+AddB3Y/OyRUiZLKWOBROAX/fLTgHcB62zS/3u0kDIFeUn/dxw4hu611dBv70UhxCwhRFspZZ6WUAjxvn4U9khAwO8l3GzJaDRaLly4SY8ezVm+fAg2NpasXm08xTQgYA/m5ma89FLDxxpLTkIIw9nfw4fPUaOGF1u3fom//+fMnbuB1FTdl9Dy5Z0JDBzN+vUT2LHjT+Ljkwqp9cnYvfsEnTs3NDw+fPgCNWp4smXLeFasGMa8eVsMHd1nVWH73ZYthxkypBsbN45iyJCuzJy5qYjanm0ZGZkcPBhBx46+pR2KEd10tiR8fSuxdOn71K1bkcWLH297VlKmlLuDB8/h7GxHrVpe+T4/dmwvNm8eQ5Uq7gQHn35icV25EsuSJfsYPtz4hM1XX/Vm48aPycjQcPz41ScWT26mmrenTXLyfQ4ciGDdupFs2TKG+/fT+fXX46Ud1lPH17cqP/00meXLxxAQsIu0tH82slgcf/5py7VrZejU6fF0rJXS8Ux8SxRCVEU3EtdJSlkf2I5uNPJhTEHX2fNFN+JoDaC/ac7vwGvAW0D+k80hLcf/tTkeayn45kJZZTQ5ymRi/P4V9HoEMCPHtZzPSSmX6TvXjdB1GKcKISbmXlFKuURK2URK2WTQoOzrftzcHImJyW4IYmMT80wNcXXNLpOZqSE19QGOjmVxdXUwWjcmJgk3N0f9nwN16+puFtKhgy/nz980lNux4yiHDp1j4sS3EPnM29m4cT9vvz2bt9+ejYuLI9HRCUbx5Rzhy34N2WViYhJwc3MCoFw5e8P0j7i4RJyddWe5t28/TPv2DRBCULGiGx4eLly9Gp2n3mrVPDhx4nKh+XJzc8izXn75cnNzMIoz67UUVWdCQioREVG0bFk7Rw6P0L59PX38rnh4lMPKyipPLk3Vk97vdu06Rvv2uvNAHTvWyzNV8Gn0OHKYJSzsAjVrelKu3MNP0XV1tc8VX1KeKb85y2RmavXxFXxzK0dHG/21f7qb13TsWIeLF2+XODZTzN3jiOn06ascPBjBm2/OZvLktRw7dpkvv1xvVKe5uRmdOtVn377wYsWpe8+yT57Fxibj6mqXq4wdMTG60WONRktKShoODjb68klMnLiZ0aO74eWVd2qulZUFrVvX4ODBS8WK52nJW5YNG/YxaNB0Bg2ajqurQ67Pt+zPruzX55TP55vxZ+Cj8DjyeOTIJTw8nHF2tsPCwpz27esSHn7toWM0tdxt2LCHgQOnMHDgFFxcHImJyb7sQLct4/3bzc3ZaJQxJuZunpgLU7WqBzY2Zbh8+cZDxevoqOHu3eyvpnfvWuDomPd6x3PnrPn1V0c++CAay39+36GnhhpRNH0awFsIkXVl8UAgaxgqGcj61HUAUoFEIUR5oAuFO6evt7r+cd8czzkCWUfc4FzrLQW+Af6SUt7l8YpE19FDCNEIqKpfnvN1A/wKvCOEsNOX9RJCuAshPNFNe10FfJVVV3HUru3F9etx3LwZT0ZGJsHBp2jTxvgOgm3a1GbXrmMA7N0bTqNGuvn1bdr4EBx8ivT0TG7ejOf69Th8fCri4mKPu7sj167pLno+evRvvL3dAd1I2Jo1IcyYMRBr6/w7Nj17tsXf/3P8/T+nXbt67Nr1F1JKwsMjsbW1NkwlzeLq6oitrTXh4ZFIKdm16y/atvXVx+7Ljh1/ArBjx5+G5RUqOHPkiG7wOj4+iWvXYvD0dCEmJoG0NN10xaSke5w6dZkqVdxz5KsiUVHZ+dq9+yStWxsPaLduXYedO4/o83WaRo2eQwhB69Z12L37pCFfUVFx+PhUKrLOvXtP0aqVj9Gd4sqXd+LIkYv6+JO5di2W9PS803tN1ZPe71xdHThx4ophecWKLk/w1T4ejyOHWXbvPkmnTg8/7TQ7vnhu3bpLRoaGP/44Q+vWxlPNW7euxa+/6m5usW/fWZ5/vmq+J4+yCCFo1aomJ05EAnD06BWqVHF9yNhMK3ePI6b//vdlNm0aTVDQ50ye3IdGjaoxceJbSCm5fv0OoLvW7uDBiDw3bSk4Tg9u3LjLrVsJ+vc1glatjG8I0qpVDX79VdeB2rfvHM8/XxkhBCkpDxg9egP/+U976tXLztn9++ncuaObvqrRaAkL+5vKlctRHE9L3rL06tWegICxBASMpV27BuzceVj/+XYFW1ubQj7fdNfv7tx5mHbtCrza5qE9jjy6uztx5kwUDx6kI6Xk6NG/S5yvnEwtd716dSQwcAKBgRNo374hO3aE6eO5jJ1dQfHYEB5+GSklO3aE0a5d4W3FzZtxhpvX3Lp1h6tXb+PhUfI2D6BKlTRiYy2Ii7MgMxOOHbOlfn3jHxOIirJi7VoXPvggBnt7bQE1KU8roZtZ+fQRQkwGUtBNqZyDbqTtL3TXKKYJIYYAH6O7Dq+jEGIl0AqIQjflc6uUcmVBP48hhPAD5gP3gP1AdSlldyFES3RTXFPRjUwOkFJ651jvHDBMSpnnmj8hxGCgiZTyY/3jSP3juJzP6WPdJqXckKtME2COlLKDEMIG+BnwAg4DLYEuUspIIcQadNdi7tRfpzgUeE8fRgowAHgOXQdRC2To81bgT4TExGw02lFCQ8/zzTfb0Gol3bo1ZtCgjixd+ju1a1ekTRsf0tIymDo1iIsXb+LgUJbJk/vg6an7EA8I2MP27UcxNzfjk0+60aKF7rqSixdvMmvWZjIyNHh6OjN2bC/s7W3o02cOGRkaw81X6tatxMiRPQyxmJvbGsUqpeTrrzcQFhaBtbUV48b1w8dHd8vpt9+ejb//5wBERFwz+nmM4cN7IoQgMTGV8eNXEB19lwoVyjF16mAcHGyJjU1k6tTV3LmThJSSgQM74+fXlD//PMfChVsQQiClpGfPdvTo0coQj1abRmhoBAsW/KK/5X9T3n67E0uX/qrPV13S0jKYMmVtjnz1w8tL1zHx9w9m+/a/9Pl61TBKmF+dWT7++HsGDOhoyC3oRkenTVvPnTvJSCkZMKAjAwd+WdBbXiJr1qyhQ4cOuLq6Eh0dzaRJk1i+fPk/rjc6eoPR4ye53506FcmCBdvQaLRYWVkwYsRrRtPKypfv9Y9fHzye3OXOW06PI4f376fTq9cs1q37DDu7oidraLUPCnwuLOyi/ucxJF27NmTgwLYsW7aH2rU9ad26FmlpmUybtplLl25jb2/DpEk98fTUnYXv3XsBqalpZGZqsLOzZs6cAXh7u3H7dgLTpm0hJeUBTk5lGT36NcqXz3+UwMys4PhNIXdPIqYsx49f5qef9jN79ttotVr+978lhhtiPfecByNGvGa4BhogM7PgKWdhYX/z7bfBaLWSLl3qMWBAK5Yv30+tWhVo3bqG/mdPtnHxYjQODjZMmPAqnp5OBAYeYs2aMKORxK++egspYezYDWRkaNBqJc8/X5n//a9TgT+PYWFh/H6bUt7yi68gUkrmzFnP4cNnKVPGivHjBxh+pmHQoOkEBIwFICLiKlOnBpKWlkGLFnUYMUI3G2fv3hPMnRtEQkIKdnY21KxZkfnzPy50m4W9r48jj8uW7eaPP05hbm5GjRqejBr1Rr43qSpJ3kord0IU/Ct0unh+IixM93Md48e/bfiJi4EDpxAYOEEfTyRTpviTlpZOy5a+jBjRRx/Pcb7+em2OeCqxYMFQdu4MIyBgFxYW5gghePfd7rRv3zDP9o8cKd5192fO6H4eQ0po0SIFP79Etm1zonLlNOrXv8/CheW5edMKBwdd59TZOZP//lf3Uxjz5lUgOtqStDSBra2Wfv3iqFOn4PY/pxdfTPsHt316Mlo0H/JEO1Fhhxc+8Zw8tR1FU6QfpdsL1Ja5b335lMvdUTQluTuKpkarTSu6UClxd+9R2iEUqrAOT2l7VB3Fx8GU8waFdxRLW2EdRaVwhXUoSltJOhSlwZTjU+/rwyuso1jaittRLC2qo5hXaXQUTXcPfsoIIQahu4vp8H9bJ1FRFEVRFEVRlGyldd3gk6Q6io+IlDIACCjtOBRFURRFURRFUf4p1VFUFEVRFEVRFEUpgWdhRPHf/woVRVEURVEURVGUElEjioqiKIqiKIqiKCWQqUYUFUVRFEVRFEVRlGeN6igqiqIoiqIoiqIoRtTUU0VRFEVRFEVRlBJQN7NRFEVRFEVRFEVRnjlqRFFRFEVRFEVRFKUE1IiioiiKoiiKoiiK8sxRI4pKsTx4cK20QyiQnV290g6hUObmpnuYRUdvKO0QClW+fK/SDqFAppw7K6vypR1CodLTo0s7hAKZcu7u3btQ2iEUqmzZmqUdQoFMPXeZmYmlHUKBLCwcSzuEApnydxMw7WPC1/fH0g7hqadGFBVFURRFURRFUZRnjukOdSiKoiiKoiiKopggNaKoKIqiKIqiKIqiPHPUiKKiKIqiKIqiKEoJqBFFRVEURVEURVEU5ZmjRhQVRVEURVEURVFKQI0oKoqiKIqiKIqiKM8cNaKoKIqiKIqiKIpSAk3ViKKiKIqiKIqiKIryrFEjioqiKIqiKIqiKCUg1IiioiiKoiiKoiiK8qx55kYUhRAuQLD+YQVAA8TqHzeTUqbnKDsMWCKlvFdEnXuBkVLKI4WU6aAv0/1hY38YQoiVwDYp5YbixPkw/vrrGosXH0SrlXTp4kOfPs8bPZ+ermH27D+4eDEWBwdrxo3rTIUKDpw7F828eSGGcgMHNqFNm6oAbNx4kp07zyEEeHu78NlnHbCyKt7uKqVk3rwgDh06g7W1FRMmDKRWrcp5yp07d40pUwJJS0unVau6fPrpmwghSExMZcKE5dy6dQcPDxemTn0XB4eyJCXdY9q0Vdy4EYuVlSXjxg2genVPAJKT7zFjxmr+/vsWQsC4cQOoV6+aycT3+usTKFvWGnNzgbm5OStWjMo3tsOHL7BgwTa0Wi3duzdlwID2Rs+np2cybVoQ58/fwMGhLF980RcPD2cAAgP3sn37EczMzBg6tDvNm9fU5+Y+s2Zt4sqVaIQQjB7dE1/fyly8eJM5c34mPT0Tc3Mzhg9/lTp1KhXrPS6JZcuW0b17d2JiYqhXr94jrz/L05I7KSVz5/7EoUOn9fvfO9SuXSVPuYiISKZMWU5aWgatWtVj+PC+CCH45pv1HDhwEktLC7y83Jgw4R3s7cuSmJjC6NGLiYiIpFu31nz2WX+TzN3y5bv55ZcjODnZAvD++y/RsmWtpzZ3Of3552UWLQpGo9HSrVsD+vVrkSePM2Zs58KF2zg42DBp0mtUqODIkSNXWLJkH5mZGiwszPnvfzvSqJHudX3++Xru3ElBo9FSv34lhg59EXPzf3aO+XHl8WGZet4edXwPHmQwefIWbt5MwMxM0KrVc7z/fodix/M4jlcAjUbLf/7zLa6uDsye/Tag21d+/PF39uw5jbm5GT16NKdXr1ZPZd5y+6fHQXDwX/z441YiI2+xYsV4fHy8AcjIyGTGjADOnYtECMHw4X1p3Lh2iWI7fPhvFi36DY1G0q1bQ/r3N865LndbOX/+No6ONkyc+DoeHk4kJt5j0qRNnDt3Ez+/+gwb5mdYJzj4DKtWHUQIgYuLHePGvYaT08Mft8qT8cyNKEop70gpG0opGwLfA/OyHufsJOoNA9ReXAiNRsvChQeYPr0bS5f2Zs+eS1y9Gm9UZteuCOzsyuDv34833qjP0qWHAfD2LsfixT354Yc3mT69KwsW7EOj0RIXl8KWLeF8+21PfvyxN1qtlj17LhU7ptDQM0RFxRIUNJnRo/sxe/bafMvNnr2WMWP6ERQ0maioWMLCzgIQGPgbTZrUIihoMk2a1CIw8DcA/P13UbOmF6tWjWPixEHMmxdkqGvevA20aFGHdesmEhg4Fm/vCiYVH8C33w4lIGBsgZ1EjUbL3LlbmTNnMIGBw9i9+yRXrkQbldm+/Qj29jasXTuSt95qzfff7wLgypVogoNPERAwjDlzBjN37lY0Gi0A33yzjebNa7J69XBWrBhClSpuAHz33S7+7/9eYMWKIbz7bme++25XgTn7J1auXImfn1/RBf+Bpyl3hw6dJioqmg0bpjN69CBmzw7Mt9zs2asYM+ZtNmyYTlRUNKGh4QA0a1aHNWu+ZPXqL6hcuTz+/tsBsLKy5IMPXueTT94y6dwBvPVWa1asGMKKFUOK3UkE08tdThqNlgULfmfmzDdZufI9goPPEhkZZ1Rmx45T2Ntbs3r1B7z5ZhN++GEvAI6OZZk+vSfLl7/LmDHdmDFjm2GdSZNeY9myd1ix4l0SEu6xb9+5h44xy+PK48Mw9bw9rvh6925GQMB/+PHH/yM8/AaHD/9d7Hgex/EKEBR0yOg41b22Y8TEJLJ69aesWvUpnTrVfyrzlp9/ehxUq+bFrFn/4/nnaxqV37JFdwJ+zZovWbhwBAsWrEer1eaptyC63O1i1qw++Pt/wB9/nCEyMtaozI4dJ7Czs2bNmo/o1asZS5b8AYCVlQXvvNOeDz/sZFQ+M1PLwoW/MW/eAJYv/w/Vq7uzefMjHbMoFUKYPdG/0vDMdRTzI4ToJIQ4LoQ4LYRYLoQoI4T4BPAE9ggh9ujLfSeEOCKEOCOE+KIY9foJIc4JIY4Bb+RY3kwIEarf5iEhRC398hAhRMMc5Q4IIRrkqtNcCDFHCBEuhDglhBiiXz5RCPGXfvkSIYQoJC5zIcRKfdnTQohPS5axbOfPx+Dp6YCHhwOWluZ06FCdQ4cijcocOhTJSy/pGrJ27apx/PgNpJRYW1sazrCmp2uA7JA1Gi1paZmGf11cbIsdU0jIKbp0aY4QAl/fqqSk3CcuLtGoTFxcIqmpD/D1rYoQgi5dmrNv30kA9u8/RdeuzQHo2rU5ISG65ZGRt2ncWPel0tu7ArdvxxMfn0RKyn1OnLjEK6/ozrhZWloUenb7ScdXXBER1/HycsHTsxyWlhZ06lSfAwcijMrs3x+Bn18jADp08OXo0b+RUnLgQASdOtXHysoCT89yeHm5EBFxnZSUB5w8GUn37k1y5MZGX5sgNTUNgNTUB7i62hc71pLYv38/8fHxRRf8B56m3IWEnKBLl1YIIahXrzrJyfeIi0swKhMXl0Bq6n3q1auu3/9asW/fcQBatPDFwsIcAF/f6sTE3AXAxqYMDRvWKPbIf+nl7uGZWu5yOnfuFp6eTnh6OmFpac4LL/hw8OBFozIHD17k5Zd9AWjfvjbHjl1FSkmNGuUN+5C3tytpaZmkp2cCYGtbBtC1yZmZxu30w3pceXwYpp63xxGftbUlzz+vG7mytDSnRo3yxMYmFyuex3G8AsTEJBIaeo7u3Zsa1fXzz4cZPPgFzMx03xWcne2eyrzl558eB1WrelKlSt6T0leu3KRJE90IYrlyDtjb2xAREVnsuM6du4mXVzk8PZ31uavDwYMXjMocPHgRPz9dp719ex+OHo1ESomNjRX161fKpy2TSAkPHmQgpSQ1NQ1X1+K9l0rpUh1FsAZWAr2llPXQTcf9UEr5DXAT6Cil7KgvO05K2QSoD7QXQhR4aksIYQ38CLwCNEY3zTXLOaCtlPJ5YCIwXb98GTBYv35NwFpKeTJX1e8D3kBDKWV9YLV++SIpZVMppS9gAxQ2xbUh4CWl9NW/5hWFlC1UXFwqbm7ZB7urqx1xcalGZe7cyS5jbm6Gra0VSUkPAIiIiOa999bx/vvrGTq0HebmZri62tGrVwP6919F794B2Npa0aRJ8ackxsYmUr68k+Gxm5sTsbEJucok4O6eXcbd3YnYWF1nLT4+GVdXRwBcXByIj9d9EDz3nBd7954A4MyZSG7fjicmJoGbN+NwcrJj6tRABg2awfTpq7l/P81k4gMQQjB06CIGD57Jli0HCozL3d0xR1yOxMUZdzTj4rLLWFiYY2trTWLiPeLikozWdXd3IDY2kVu34nFysmX69I28885CZs7cxP37uoH7Tz7pxuLFO+nZcxbffruTDz54ucCcmbqnKXexsXcpX75cju05F7D/Oecqk/fL+C+/HKBly382nfdJ5w5g06ZQ3n77G2bM2Ehy8v0SxGpaucspLi4Zd3cHw2M3N3vi4lJylUnB3V33Bdjc3Aw7uzIkJRm//pCQ89SoUd7oi95nn63j9dcXYmNjRfv2xR+BLYgp5dHU8/Y44wNISXlAaOglGjXyLlY8j+N4Bd0MgI8+6oKZmXGH+saNO/zxxynee+9bRo5cSVSU8ahgQUwtb/l5lMdBTjVqVGL//hNkZmq4eTOWc+euEh1d/JOlsbHJuLlln3x0c3PI0yHWldHl18JCl7vExILbUgsLcz791I933llCz54LuHo1jq5dGxY7JlOlRhSfDebAFSll1ukSf6BdAWXf0o8OHgfqAnUKqbe2vt6LUkoJrMrxnCMQJIQIB+bp6wIIAroLISyBd9B1YHPrDPwgpcwEkFJmHf0dhRCHhRCngRdy1Jmfy0A1IcRCIYQfkO+wkxDiff0I6pE1a0ILqe7h+fiUZ+nS3ixa1JO1a4+Rnp5JcnIaoaGRBAb2Z+3agTx4kMnu3ReKruwxEEKQNTY7aNBLpKTcZ9Cg6WzYsJeaNStiZibQaLRcuBDFG2+0JSBgDDY2VgQE/GYy8QF8//1w/P1HM3fu/9i4MYTjxy8WUuujo8vNTXr0aM7y5UOwsbFk9ep9AGzZcpghQ7qxceMohgzpysyZm55ITE8LU8/dihXbMDc3w8+vRdGFn7DCctejR3PWrh3JihUf4+Jiz6JFO554fKaauytXYlmyZB/DhxufePjqq95s3PgxGRkajh+/WkrR5WUqeTT1vBUUn0ajZcqUrbzxRmM8PZ1KJzjg4MFzODvbUauWV57nMjI0WFlZsHTp/3jllSbMnLnxicVl6nkryCuvtMHdvRyDB09h7ty11Kv33D++rvifyszUsHXrMX788T02bhxKtWrurF59qFRjUornmbuZzcMSQlQFRgJNpZR39TeJsX7I6qYAe6SUrwshvIG9AFLKe0KI34HXgLfQjUQWJzZrYDHQREoZJYSYXFhs+vgbAC8D/9Vv6518yi0BlgBcuzZP5leXq6stsbHZZ+ni4lJwdTWeJurioivj5maHRqMlNTUdBwfj8KpUccbGxpIrV+K5fTuZChUccHLSTRVr06YqZ8/epnNn43n4/8/encdFVfUPHP8cQGQHZQABF9QUcc99X9J6cGn7aVqm1pMtT2VlZW655VpqmrabG6CmYlbmVokrCpqYO+4bhrGIIKKyzJzfH3cYGHZMYMzzfr18ycyce+73fu82555z7+S2du1O1q/fA0BAQC3i4pJNnyUkJOPh4WZW3sPDzdTbBhAfn4yHh3als2pVZxITU9DpXElMTKFKFe3KmqOjPePHD8nODf/3fxPx9dVx504GHh5uNGqkPYine/eHTfcNWkJ8gKl3smpVZ7p2bcaJE5d4+OF6eebpSnx8zhDYhIQUdDoXszI6nVbG09OVrCw9aWl3cHV1QKdzMZs2Pv4GHh6uxn8uNGqk9Qh369aY5cu1+ye2bDnIO+/0NeasCZ988iP3K0vPXWjoNn7+WZu2YUM/s6vL8fHXC9n+rucpk3NVe8OGcMLDD/PllyMpYpR7iZR37qpWzblS/vjjrRk9OqjI+Cw5d7npdM7Ex+dc80tISM03tEuncyI+XusJ0OsN3LyZjouLvbH8DSZO/JExY/rg61uFvGxtbejYsR579pylVavapY7PUvNo6Xkry/jmzNmCr29V+vc3H+5ZlLLYX8PDo9mzJ5rIyFNkZGSRlpbOlClrmDhxAB4eLnTpol337tKlETNnlqyhaGl5y3av94OCaL13z5pev/zyDGrUKPy5CXl5eDib9SAmJNww62HMKXMDT08XsrK03Lm6Fj68/+xZ7T7W7Fx2796QlSvv/4ai+nmMB4Me8BNCPGR8PQTYafw7FcjeO1yANCBFCOEF9Cqm3pPGeusaXz+X6zNX4C/j3y/mmW4RsAD4Q0pZ0PiC34HXhBA2AEKIquQ0ChOFEE5A/6ICE0LoACsp5Q/AeKBFMctSKH9/T/76K4WrV2+Qmalnx45ztG/vZ1amfXs/fvtN6xHctes8zZv7IITg6tUbphvZ4+JSuXw5mWrVnPH0dCI6Os40lv3PP/+iZs2iD4z9+3clOHgcwcHj6NKlGZs370NKybFjF3B0tDcN1cym07ni6GjHsWMXkFKyefM+unTRRhJ36tSETZu0B+5s2rSPzp2191NTb5GZqd1/sn79Xpo3fwhHR3vc3V3x8qrCpUvagfDAgVP5HmZTkfHdvp1OWpo21Pf27XT27YumTh3vfDls0MCXK1cSiY1NIjMzi7CwI3TqFGBWplOnBmzZchCAHTuO0aJFHYQQdOoUQFjYETIysoiNTeLKlUQCAqrj7u6Mp6crly9rN8JHRZ3Dz8/TuIwuHDp0wfR+9eruRa5jS2bpuXvmmUdYvnwyy5dPpkuXh9m8eS9SSo4ePYeTkwM6nZtZeZ3ODUdHe44ePWfc/vbSpUtzACIijhISsoU5c97Gzq7yP01duecu9zC5XbuOU7u2V5HxWXLucmvQwJu//rrO1avJZGbq2bYtmg4dHjIr06FDPX79VXsQxs6dJ3n44ZoIIbh58w5jxqzllVe60qRJdVP527czuHZNuxCo1xuIjDxHzZpVuRuWmkdLz1tZxAewePEu0tLSGT7c/KEjxcdz7/fX//3vP6xbN4bQ0FFMnvwsLVrUYeJE7cFOnTs35M8/zwNw6NAFatTQ3Zd5y3Yv94PC3LmTbrr9Zd++41hbW1Gnjk+JY/T39+HKlaRcuTtBhw7mF+o7dKjHli1HANi5M5oWLfyKvGCj0zlz8WICycnarUkHDpynVq2SrUulYgltVOSDydjzdhNtKOkctB7WP9DuUUw3PihmOBArpexu7EXsAMQAKcB6KeWywn52wjis8zPgFrAbqCul7CuEaI82xDUN2AgMllL65ZruJDBCSpnvUYbGBuIsIBDIBL6TUn4hhJiG1hj9GzgNXJJSTi7o5zGM0y0l50LBWCnl5qJyVViPIsC+fZf4+uu9GAyS//zHn+efb8myZX9Qv74HHTr4kZGRxccfb+PcuUScnSvz4YeP4u3twu+/n2b16j+xtrbCykoweHBLOnbUrrgGBf3Bzp3nsLYW1K2r4733umFra13g/J2czO9PkVIyZ84a9u07QeXKtowfP5iAAO0G9KFDZxAcPA6A6OhLTJsWQnp6Ju3aNeT99wcYf37iJh9+uJi4uOtUq1aVadOG4erqyNGj55k6NQQhoHZtb8aNG4yLi/bQmtOnY5g5cyWZmVn4+ur48MMhps/yKu/4/vorkTFjFgKg1+t57LHWvPii9hTQrCzzh+hERJxiwYINGAySPn1aMnRodxYt+p0GDarTqVMA6emZTJsWypkzsbi4ODB58rP4+GhfgIKDt7NxYxTW1la8/XYf2rXT7sk5cyaWTz75kcxMPT4+VRg3rj/OzvYcOXKR+fM3oNcbsLW14f33n8w39MjLq8hrHiWycuVKunXrhk6nIy4ujkmTJrFkyZJ/XG9c3Fqz15aUO1vbwhs/Ukpmz15BZOQx0yPZsx+rPniw9gUGtEeyT5mymPT0TNq3b8LIkYMQQtCv31gyMjJxddWuzjduXIcxY4YC8NRTo0hLu01mph4nJwcWLHivwC8oGRnmT0ksz9xNnbqGs2evAgJvbzdGjnzKrEfEknN361bRQ/AjI8/x5Zdhxp8qasLgwR1YsmQ3/v7V6NixHhkZWcyYsYEzZ+JwcbFnwoQn8PFxIyRkLytXRpr1nMyePQApYdy4tWRm6jEYJA8/XJM33+xR6DA2B4fCR32UVx4LU1TuKjpvxbnX8WVl6Rkw4Gtq1tQeSAPw9NMt6NOnWYHzt7Exv5BZFvtrtj//PM/33+82/TxGauptpkxZQ3x8Mvb2towc+RQPPZRzoTPvOcyS8gZF7xP/dD/YseMgc+asJDk5FScnB+rXr8GCBe8RG5vIO+/MxcrKCg8PNz788EW8vfM3ym7fPl9E7s7yxRe/YzAY6NWrGUOGdGLJkp34+3vTsWN90tOzmDHjZ2Pu7Jg48Wl8fLR8DRz4BbdupRuPZXbMmfMcfn4e/PxzFD/88Ac2NtZ4ebkwZszjuLoW/uA/b++h927IRRl57LHZ5dqI+u23D8o9Jw90Q9ESCSF80IaiNpBSlvx5xmWsqIZiRcvbUFRKrqiTrCW4Fw3FspK3oWhJimrsWIK8DUVLYsm5K66hWNFK2lCsCJaeO0uWt6FoSSz9HGbJ+0RRDUVLoBqK+VVEQ1Hdo2hBhBBDgenAe5bUSFQURVEURVEUJceDcI+iaihaECllMBBc0XEoiqIoiqIoivJgUw1FRVEURVEURVGUUngQehT//UuoKIqiKIqiKIqilIrqUVQURVEURVEURSkF1aOoKIqiKIqiKIqiPHBUj6KiKIqiKIqiKEopqB5FRVEURVEURVEU5YGjGoqKoiiKoiiKoiiKGTX0VFEURVEURVEUpRTU0FNFURRFURRFURTlgaN6FJUSsbOrWdEhFErKrIoOoUgGQ3pFh1AoL6/+FR1CkeLi1lZ0CIWy5NxZct4ADIY7FR1CoTIy4io6hELZ2LhWdAhFunXrdEWHUChLz50lx5eVlVLRIRTKkr+bgGV/Pzl27JWKDqFI3t5DKzqEYqkeRUVRFEVRFEVRFOWBo3oUFUVRFEVRFEVRSkH1KCqKoiiKoiiKoigPHNWjqCiKoiiKoiiKUgqqR1FRFEVRFEVRFEV54KgeRUVRFEVRFEVRlFJQPYqKoiiKoiiKoijKA0f1KCqKoiiKoiiKopSC6lFUFEVRFEVRFEVRHjiqR1FRFEVRFEVRFKUUVI+ioiiKoiiKoiiK8sD5V/QoCiHcgTDjy2qAHkgwvm4jpczIVXYEsFBKeauYOncAI6WUB4oo081Ypu/dxl5MDBeBVlLKxLKo/5/Yt+808+dvwGAw0LdvawYP7mr2eUZGFtOnh3Lq1F+4uDjw0UfP4e1dBYCQkB1s3HgAKysr3nmnL23b1gcgNfU2n3yyjgsX4hBCMGZMPxo3rsmXX25m795obGxs8PWtytix/XB2ti80Nikl8+atIyLiBHZ2lRg//nn8/WvkK3fyZAzTpq0gPT2T9u0b8u67/4cQghs30pgwYRlXrybh7V2VqVP/i4uLAzdv3uajj0KIi7uOXm/guee607dvO65eTWLs2MVIKcnK0tO/f2eefrqT2bwiI08xf/7PGAySvn3bMGRI93z5mjZtlSlfU6Y8j7d3VWO+trFhwx9YWQlGjHiStm39i6zzjTe+4tatdACuX79Jw4Y1mTnzBW7evM2UKauIi0s2xt+lpKu7WIsXL6Zv377Ex8fTpEmTe1ZvXuW53Z05E8ucOT+TkZGFtbUV7733BA0b5t+O/qnyyl22e53Dy5cTmDRplWn62Ngkhg3ryYABHe8yvrN8/vmvGAwG+vR5mOefN9+XMjKymDHjJ06fvoqLiz2TJvXH29uNlJRbTJwYyqlTsQQGNmfEiF6maTIz9Xz22WYOHbqIlZXg5ZcfoWvXgLuIzfJyVxb7BIBeb+CVV75Ep3Nh1qwXAPj44x84efIvpIQaNdwZN64/Dg6VSxTn/v3n+eKLMPR6A336NGPQoHb54pw5cyOnT/9tXK9PUq2aKwcOXGDhwp1kZemxsbHmf//rTosWtQAYNWoN167dRK830LRpDd5551GsrUt2/ft+yVte2vktlL17j2NnZ8uECUPw96+Zr9zJk5eZOjWE9PQMOnRoxLvvPoMQgrCwgyxevJGLF+NYvPgDAgJq3VUc2coij6tXh7NhwwGEgDp1qjF2bD8qV670j+IEy8udlJK5c1cTEXGMypVtmTDhRRo0KCieS0ydusz4XaUx77030BhPFIsW/cLFi3+zZMkYAgL8ADh+/AIff7zcOA94+eW+dOv28F3HeeKEPWvXVsVggA4dbvLYYylmn4eFuRAR4YSVFTg56Rk8OJGqVfUAfPmlFxcvVqZOnTu8/nr8XcdgqVSP4n1CSnlNStlcStkc+AaYl/06dyPRaATgUN4xljchRJldBNDrDcydu545c14kJGQEW7ce5sKFOLMyGzcewNnZnlWrRjJgQEe++WYLABcuxBEWdoTg4BHMmfMic+euR683ALBgwQbatq3PihXvsXTpW9Sq5QFA69YPERT0DkFBb1Ojho7ly3cWGV9ExAmuXElgzZrxjB79LLNnhxZYbvbsNYwZ8yxr1oznypUEIiOjAQgJ2UrLlvVZs2YCLVvWJyRkKwA//LAbP79qBAeP5osv3uLzz38mMzMLnc6FhQvfJShoFN999x4hIWEkJOQcSLV8/cicOcNYvvx9tm49lC9fGzbsx9nZntWrRzNwYGe+/nqTKV9btx4mJOR9Pv30ZT799Ef0ekORdX711RssW/Yuy5a9S+PGtejSpTEA69ZF4OfnRVDQu3z++Wt88cWGYtZ0yS1btozAwMB7Vl9Bynu7+/rrLfz3v4+wdOlbDBvWk6+/3lImy1UeuctWFjmsWdODpUvfYunSt1i06E3s7CrRpUvDu47vs882M2vWIIKC3iAs7DgXLyaYldm48U+cne1ZufItnnmmHd9+q+2ftrY2DBvWnddffzRfvSEhu6lSxYEVK4YTFPQGzZqV/gueJeaurPYJgNDQvaZ9Idtbb/Vh2bK3CQp6Gy8vN9atiyxxnPPn/87HHz/DsmUvExZ2gosXza9/btp0BGdnO1aseI1nnmnFt9/uAMDV1YEZM/qxZMkwxo7tw8yZOcetSZOeZPHil1i6dBjJybfYufPkvypvBYmIOE5MTAKhoZMZM2YQs2atKrDcrFmrGDt2EKGhk4mJSSAy8gQAdev6MHPmqzRv/tBdx5CtLPKYkJDCDz9EsGjRmwQHj8BgMBAWduQfxwqWlTstnmPExMQTGjqVsWMHM2vWikLiWcnYsUMIDZ1KTEw8ERHHAahTx4ePP/4fzZvXMytft64vS5eOIyRkAp999jaffLKCrCz9XcVoMMCaNVV54404xo//i6goR65eNW+016iRwahRVxk3LpaHH77FTz9VNX3Ws2cKQ4cm5K1WuY/8KxqKBRFC9BBC/CmEOCqEWCKEqCyEeBvwAbYLIbYby30thDgghDguhPioBPUGCiFOCiEOAv+X6/02QogI4zz3CiH8je/vEkI0z1UuXAjRLE+d1kKIOUKIY0KII0KIt3J9/JYQ4qBxORoUM68XhRDrhRDbgDAhhIMQYo0Q4oQQ4kchxD4hRCtj2ceMdRwUQoQKIZxKmtvo6Cv4+rrj41OVSpVs6NGjKeHh0WZldu+OJjCwBQDdujUmKuocUkrCw6Pp0aMptrY2+PhUxdfXnejoK9y8eYfDhy/St28rACpVsjH1GrZpUw8bG2sAGjWqYdYIK8ju3ccIDGyNEILGjf24efM2iYnm0yQmppCWdofGjf0QQhAY2Jpdu46apu/duw0AvXu3Yffuo9nriVu37iCl5PbtdFxcHLC2tqJSJRtsbbV2eWZmFlIazOYVHR1D9eo6fH3dqVTJhp49mxEeftysTHj4CXr1amXMVxOios4a83Wcnj2bmfJVvbqO6OiYEtWZlnaHqKhzdOnSyBg/3LqVbow/AxeXe3e9ZPfu3SQlJd2z+gpS3tsdCNLStJ7ZtLQ76HTOZbJc5ZG7bGWRw9yios7h41OVatWq3GV8f+HrWwUfnypUqmTNI480Ijz8lFmZPXtO8Z//NAWga9eGHDx4ASkl9va2NG1a07Qv5rZp0yFTz6SVlcDNrfTbviXmrqxiio9PISLiJH37tjary9HRDtB6QtLTMxGiZHGePHkVHx83fHzcjOs1gD17zpiV2bPnDP/5j3ZRq2vXBhw8eAkpJfXqeZn2PT8/HenpWWRkZBnj0Xrl9HqD8YtwyQK6X/JWkF27jtCrV1vj+a12Mee32ggh6NWrLTt3HgbAz68atWp53X0AuZRVHvV6A+npmWRl6blzJxOdzuWexGtJudPiOUzv3u2M8dQpIp7bNG5cByEEvXu3Y9euQwDUru1NrVrV8tVrZ2dr+s6UkZH5j2K8eLEyOl0WOl0WNjbQokUaR46YHz/r17+Dra0EwM8vneRka9Nn/v53qFxZ/qMYlIr1b20o2gHLgIFSyiZoQ2xfl1IuAGKB7lLK7LF/H0opWwFNga5CiKaFVSqEsAO+Ax4HWqINc812EugspXwYmAjMML6/GHjROH19wE5KeThP1a8CfkBzKWVTIPdlpUQpZQvga2BkMfMCaAH0l1J2Bd4ArkspGwITjDEjhNAB44GexroPAO8Vttx5JSSk4Onpanrt4eFKYuINszKJiTllbGyscXS0IyXlFomJN8ym9fR0ISEhhatXk3Bzc2TGjB946aXP+fjjddy+nbczGDZujDIb5lNwfMl4ebmZxZe3caktQ04ZT083EhKSAUhKSkWn02J0d3chKSkVgH79OnPpUhxPPDGRIUM+ZsSI/8PKStuF4uKuM2TIxzz11CQGD+6Jh4drnnmZ5yshwTxfucvkzldCwg2zOLOXpSR17tp1nFatHjJ9SenXrwOXLsXx1FPTeOGFubzzzhNF5tHSlPd29/bbffjqq8306/cJX365mdde+085LGXZKosc5hYWdoSePc2ug5VKYmJqnvhcSExMLbSMjY2VMb7bhdaZmnoHgMWLt/PyywuZODGUpKSbpY7NEnNXVjEtWLCBN97ohZVV/hbNjBlrefLJGVy+nEC/fu1LFKe2znK+7Ht4OJOYeDNPmZt4emoNQmtrK5ycKnPjhvl63bXrFPXqeZldDPjgg9U8/fTn2Nvb0rWrf4niuV/yVljs5ue3nHNXTpnkAs5vRV9gvdtY7nUePTxcefbZTvTvP4unnpqJk5MdbdqY95j9k3gtJXc588rpfdPmdT1Pmet4eFTJVaZKvpgLcuzYBZ57bjLPPz+F0aOfNzUcSyslxZoqVbJMr6tUySIlpfC6IiKcaNiw8OPxv40QVuX6ryL8WxuK1sAFKeVp4+sgoLAbsgYYewf/BBoBRY37aWCs94yUUgLLc33mCoQKIY4B84x1AYQCfYUQlYCX0BqwefUEvpVSZgFIKXN3L6wz/h+F1pgsal4Av+eavhOwyljnMSB7/EY743LuEUIcAl4A8o3FEkK8auxtPRAc/HuBCblX9HoDp0/H8tRTbVmy5C3s7SuxYoX5ENPg4O1YW1vx2GPNyzSW3IQQpqu/+/adpF49X9avn0JQ0Cjmzl1LWpr2JdTLqwohIWNYs2YCmzbtJynpRhG1lo+tWw/Rs2dz0+t9+05Tr54PP/00nqVLRzBv3k+mhu6Dqqjt7qef9vHWW3344YfRvPVWbz7+eF0xtT3YMjOz2LMnmu7dG1d0KGa04Ww3aNy4BosWvUqjRtX56quyPZ6VliXlbs+ek1Sp4oS/v2+Bn48b158ffxxLrVqehIUdLbe4LlxIYOHCnbz3nvkFm9mzB/LDD8PJzNTz55+Xyi2evCw1b/eb1NTbhIdHs3r1SH76aSy3b2fw669/VnRY953GjWvz/feTWbJkLMHBW0hP/2c9iyWxf78jly9XpkePsmlYKxXjgf6WKISojdZL18PYk7cRrTfybkwFtkspG6P1ONoBGB+a8zvwJDAA897Ckkg3/q8n5+FDBc7LKK0EdQq0BmX2fZwNpZTD8haSUi6UUraSUrYaOjTnvh8PD1fi43MOBAkJKfmGhuh0OWWysvSkpd3B1dUBnc7FbNr4+Bt4eLga/7nQqJH2sJBu3Rpz6lSsqdymTVHs3XuSiRMHIAoYt/PDD7t54YVZvPDCLNzdXYmLSzaLL3cPX84y5JSJj0/Gw8MNgKpVnU3DPxITU6hSRbvKvXHjPrp2bYYQgurVPfD2dufSpbh89dap482hQ+eLzJeHh0u+6QrKl4eHi1mc2ctSXJ3JyWlER8fQvn2DXDk8QNeuTYzx6/D2roqtrW2+XFqq8t7utmw5SNeu2jWY7t2b5BsqeD8qixxmi4w8Tf36PlStevdDdHU65zzx3cg35Dd3mawsgzG+wh9u5epqb7z3T3t4TffuDTlz5u9Sx2aJuSuLmI4evcSePdE888wsJk9excGD55kyZY1ZndbWVvTo0ZSdO4+VKE5tneVcPEtISEWnc8pTxon4eK33WK83cPNmOi4u9sbyN5g48UfGjOmDr2/+obm2tjZ07FiPPXvOliie+yVv2dau3cnQoTMYOnQGOp1LnvNbzrkrZ/ncCji/mZ8D74WyyOOBA2fx9q5ClSpO2NhY07VrI44du3zXMVpa7tau3c6QIVMZMmQq7u6uxMfn9Ato8zLfvj08qpj1MsbHX88Xc1Fq1/bG3r4y58//dVfxurrquX49pwf/+nUbXF3z3+948qQdv/7qymuvxVHpnz936L6hehTvX3rATwiRfcfxECC7eyoVyD4bu6A1rFKEEF5AL4p20lhvXePr53J95gpk74kv5pluEbAA+ENKeZ38fgdey34AjRCiagFlcitqXrntQWucIoRoCGQ/UjES6JidHyGEo3FYbIk0aODLlSuJxMYmkZmZRVjYETp1Mn+CYKdODdiy5SAAO3Yco0ULbXx9p04BhIUdISMji9jYJK5cSSQgoDru7s54erpy+bJ203NU1Dn8/DwBrSds5cpdzJw5BDu7ghs2/fp1JihoFEFBo+jSpQlbtvyBlJJjxy7i6GhnGkqaTadzxdHRjmPHLiKlZMuWP+jcubEx9sZs2rQfgE2b9pver1atCgcOaJ3USUk3uHw5Hh8fd+Ljk0lP14Yr3rhxiyNHzlOrlmeufFUnJiYnX1u3HqZjR/OO644dG7J58wFjvo7SosVDCCHo2LEhW7ceNuUrJiaRgIAaxda5Y8cROnQIMHtSnJeXGwcOnDHGn8rlywlkZOQf3mupynu70+lcOHTogun96tXdy3Fpy0ZZ5DDb1q2H6dHj7oed5sSXxNWr18nM1LNt23E6djQ/NHXs6M+vv2qDI3buPMHDD9cu8OJRNiEEHTrU59ChiwBERV2gVi3dXcZmWbkri5j+97//sG7dGEJDRzF58rO0aFGHiRMHIKXkypVrgHav3Z490fke2lJ4nN789dd1rl5NNq7XaDp0MH8gSIcO9fj1V60BtXPnSR5+uCZCCG7evMOYMWt55ZWuNGmSk7PbtzO4dk0bvqrXG4iMPEfNmsWdOu+vvGXr378rwcHjCA4eR5cuzdi8eZ/x/HYBR0f7Is5v2v27mzfvo0uXQu+quWtlkUdPTzeOH4/hzp0MpJRERZ0rdb5ys7Tc9e/fnZCQCYSETKBr1+Zs2hRpjOc8Tk6FxWPPsWPnkVKyaVMkXboUfayIjU00Pbzm6tVrXLr0N97epT/mAdSqlU5Cgg2JiTZkZcHBg440bWr+owExMbasWuXOa6/F4+xsKKQm5X4ltBGU/x5CiMnATbShpHPQeuH+QLtHMd34oJjhQKyUsrsQYhnQAYgBUoD1Usplhf08hhAiEPgMuAXsBupKKfsKIdqjDXFNQ+uZHCyl9Ms13UlghJQy36MTjQ3EWUAgkAl8J6X8IvfPYxgfQjNHStmtsHkJIV40lh9urNfRWK4hWiO3DvCMlPKMEOIR4BMg+xnd46WU6wvLa3z8D2YbSkTEKRYs2IDBIOnTpyVDh3Zn0aLfadCgOp06BZCensm0aaGcOROLi4sDkyc/i4+PdhIPDt7Oxo1RWFtb8fbbfWjXTruv5MyZWD755EcyM/X4+FRh3Lj+ODvb8+yzc8jM1JsevtKoUQ1GjnzKFIu1taNZrFJKPv10LZGR0djZ2fLhh4MICNAeOf3CC7MIChoFQHT0ZbOfx3jvvX4IIUhJSWP8+KXExV2nWrWqTJv2Ii4ujiQkpDBt2gquXbuBlJIhQ3oSGNia/ftP8vnnPyGEQEpJv35deOqpDqZ4DIZ0IiKimT//F+Mj/1vzwgs9WLToV2O+GpGensnUqaty5WsQvr5awyQoKIyNG/8w5usJUy9hQXVmGz78GwYP7m7KLWi9o9Onr+HatVSklAwe3J0hQ6YUtspLZeXKlXTr1g2dTkdcXByTJk1iyZIl/7jeuLi1Zq/Lc7s7cuQi8+dvQK83YGtrw/vvP2k2rMzLq/8/Xj4om9zlzVtuZZHD27cz6N//E1av/gAnp+IHZRgMdwr9LDLyjPHnMSS9ezdnyJDOLF68nQYNfOjY0Z/09CymT/+Rs2f/xtnZnkmT+uHjo12FHzhwPmlp6WRl6XFysmPOnMH4+Xnw99/JTJ/+Ezdv3sHNzYExY57Ey6vgXgIrq8Ljt4TclUdM2f788zzff7+bWbNewGAw8OabC00PxHroIW/ef/9J0z3QAFlZhQ85i4w8x5dfhmEwSHr1asLgwR1YsmQ3/v7V6NixnvFnTzZw5kwcLi72TJjwBD4+boSE7GXlykiznsTZswcgJYwbt5bMTD0Gg+Thh2vy5ps9Cv15DBsb8/VtSXkrKL7CSCmZM2cN+/adoHJlW8aPH2z6mYahQ2cQHDwOgOjoS0ybFkJ6eibt2jXk/fe10Tg7dhxi7txQkpNv4uRkT/361fnss+FFzrOo9VoWeVy8eCvbth3B2tqKevV8GD36/wp8SFVp8lZRuSvqAfRaPN8TGan9XMf48S+YfuJiyJCphIRMMMZzkalTg0hPz6B9+8a8//6zxnj+5NNPV+WKpwbz57/D5s2RBAdvwcbGGiEEw4b1pWvX5vnmf+BAye67P35c+3kMKaFdu5sEBqawYYMbNWum07TpbT7/3IvYWFtcXLTGaZUqWfzvf9pPYcybV424uEqkpwscHQ0MGpRIw4aFH/9ze/TR9H/w2Kfy8cwzq8u1ERUaOrDcc/KvayhaIiGED7ADaCDzPhKzbOdrDVSSUt4x9oJuBfwL+MmQYuVtKFqSvA1FS2MwpBdfqIJ4ej5V0SEUqagGT0W7Vw3FsmDJeYOiG4oVraiGolK0ohoUFa00DYqKYMnxqfV698rwl8r+sZI2FCuKaijmVxENRcvdgv8lhBBDgenAe+XZSDRyQPspkEpo9yW+cTeNREVRFEVRFEVRclTUfYPlSTUUy5iUMhgIrqB5pwKtKmLeiqIoiqIoiqLcv1RDUVEURVEURVEUpRQehB7Ff/8SKoqiKIqiKIqiKKWiehQVRVEURVEURVFKQfUoKoqiKIqiKIqiKA8c1aOoKIqiKIqiKIpSCqpHUVEURVEURVEURXngqB5FRVEURVEURVGUUlA9ioqiKIqiKIqiKMoDRzUUFUVRFEVRFEVRFDNq6KlSItbWjhUdQqEMhvSKDqFIWVkpFR1CoeLi1lZ0CEWytfWq6BAKZcm58/LqX9EhFOnatd8rOoRCubs/WtEhFMqS82bpbGxcKzqE+5YQ6qvi3ZIyq6JDKJSv7/MVHcJ9Tw09VRRFURRFURRFUR446jKRoiiKoiiKoihKKageRUVRFEVRFEVRFOWBo3oUFUVRFEVRFEVRSkH1KCqKoiiKoiiKoigWTQgRKIQ4JYQ4K4QYU0iZAUKIE0KI40KIlcXVqXoUFUVRFEVRFEVRSsGSehSFENbAl8CjwBXgDyHEeinliVxl6gFjgY5SyutCCM/i6rWcJVQURVEURVEURVFKqw1wVkp5XkqZAawCnsxT5hXgSynldQApZXxxlaoeRUVRFEVRFEVRlFIo7x5FIcSrwKu53loopVxo/NsXiMn12RWgbZ4q6hvr2QNYA5OllFuKmqdqKCqKoiiKoiiKolgwY6NwYbEFC2cD1AO6AdWBXUKIJlLK5KImUBRFURRFURRFUUrIku5RBP4CauR6Xd34Xm5XgH1SykzgghDiNFrD8Y/CKrWoJVQURVEURVEURVFK5Q+gnhCithDCFngWWJ+nzE9ovYkIIXRoQ1HPF1XpfdWjKIRwB8KML6sBeiDB+LqN8ebN7LIj0Mbu3iqmzh3ASCnlgXse8F0SQmwCBhXVFVzEtM0BHynlpnsdV25SSubNW0dExAns7Coxfvzz+PvXyFfu5MkYpk1bQXp6Ju3bN+Tdd/8PIQQ3bqQxYcIyrl5Nwtu7KlOn/hcXFwcADh48w/z5P5KVpcfV1ZGvvnobgFWrtvPLL5EA1K3rw4cfDqJy5Ur55hkZeYr583/GYJD07duGIUO6m32ekZHFtGmrOHXqL1xcHJgy5Xm8vasCEBKyjQ0b/sDKSjBixJO0betPenomw4d/Q0ZGFnq9ge7dmzBs2GOmPCxc+Cvbtx/B2tqKp55qxzPPdCpxHvftO8cXX/yGXi/p06c5zz/fIV+sM2eu59Spv3F1tWfixKfx9nYjJeUWkyat4+TJWAIDmzJiRKBpmrCw4yxfvgchBO7uTnz44ZO4uTmUOKac2E4zf/4GDAYDffu2ZvDgrvlimz491JTHjz56Dm/vKsY87mDjxgNYWVnxzjt9adu2PpcvJzBp0irT9LGxSQwb1pMBAzqWOjbQcj937vfs3XsUOztbJkx4iQYNauUrFx19kalTl5CenkmHDk14773nEEKwYMEawsMPU6mSDb6+HkyY8BLOzg6kpNxkzJiviI6+SJ8+Hfngg+dLHZul566kFi9eTN++fYmPj6dJkyZlOq9s2rEllL17jxvX6xD8/WvmK3fy5GWmTg0hPT2DDh0a8e67zyCEICzsIIsXb+TixTgWL/6AgABtm0hJucm4cYuIjr5E797tGDlyYJkux78pd8ePX+STT1Ya5wHDhvWmW7fmxcZT3vvB2rV7+fHHSKysrGjf3p833uh1X+atvOK7233iXp9j4+KSmTZtFdev3wQETzzRlgEDtPPo4sW/8csv+3FzcwTgtdcCad8+4L7NXXnEdi+2u4MHr7N48XkMBujZ04t+/aqbfZ6ZaWD+/NOcO5eGs7MNI0f64+lpR2amgW++OcfZszexsoJhw+rQuLErAFOmHOf69Qz0eklAgAuvvloXa2tR6rxZEkvqUZRSZgkhhgO/ot1/uERKeVwIMQU4IKVcb/zsMSHECbQ21AdSymtF1Ws5S1gCUsprUsrmUsrmwDfAvOzXuRuJRiOA0n87tgBSyt5300g0ag70vnfRFCwi4gRXriSwZs14Ro9+ltmzQwssN3v2GsaMeZY1a8Zz5UoCkZHRAISEbKVly/qsWTOBli3rExKyFYDU1FvMmRPKJ5+8zIoVY5k27b8AJCQkExq6iyVL3mfFirEYDAa2bj2Yb356vYG5c39kzpxhLF/+Plu3HuLChTizMhs27MfZ2Z7Vq0czcGBnvv5aa1NfuBDH1q2HCQl5n08/fZlPP/0Rvd6Ara0N8+e/SlDQuyxbNoLIyFMcO3YJgE2bDhAfn8zKlSNZsWIkPXs2L3EO9XoD8+dv4ZNPniUo6DW2bTvOxYsJZmU2bTqEk5MdK1e+Qf/+bVi4cBsAtrY2vPRSV15/vYdZ+awsA59//hvz5g1myZJXqFvXkx9/LP01EC2P65kz50VCQkawdevhfHncuPEAzs72rFo1kgEDOvLNN9r90BcuxBEWdoTg4BHMmfMic+euR683ULOmB0uXvsXSpW+xaNGb2NlVokuXhqWOLdvevUeJiYlj7doZjBkzlFmzQgosN2vWcsaOfYG1a2cQExNHRMQxANq0acjKlVNYseIjatb0IihoIwC2tpV47bWnefvtAXcV1/2Qu5JatmwZgYGBxRe8hyIijhMTk0Bo6GTGjBnErFmrCiw3a9Yqxo4dRGjoZGJiEoiM1J4AXreuDzNnvkrz5g+Zlbe1rcSrr/Zl+PD/K/NlgH9X7urW9WHJktEEB49j3rw3mTXre7Ky9EXGUt77wcGD5wgPj2bp0rcJCRnBc891vi/zVp7x3c0+URbnWGtrK4YP78vy5SNZuPBN1q3ba1bngAGdWbbsXZYte7dUjUSwrNyVV2z/dLvT6yULF55nwoRGLFjwMOHhCcTEmPe5bN0ah6OjDV9/3ZLHH/chOPgiAL//rq23+fMfZtKkRixdegGDQQIwcqQ/8+Y9zPz5D3PjRhZ79yaWOCalZKSUm6SU9aWUdaWU043vTTQ2EpGa96SUDaWUTaSUBW90udxXDcWCCCF6CCH+FEIcFUIsEUJUFkK8DfgA24UQ243lvhZCHDD+wORHJai3pRBipxAiSgjxqxDCWwjRQAixP1cZPyHE0cLKF1DnMmMckUKI80KIbsaYo4UQy3KVuyiE0BnrjxZCfGeM+zchhL2xzA4hRCvj3zrjNLbAFGCgEOKQEGKgEMLROI/9xjw9aZymkfG9Q0KII8bfVimx3buPERjYGiEEjRv7cfPmbRITU8zKJCamkJZ2h8aN/RBCEBjYml27jpqm7927DQC9e7dh927t/d9+i6Jr12ZUq6Zdfaxa1dlUn15vID09k6wsPXfuZKDTueaLKzo6hurVdfj6ulOpkg09ezYjPPy4WZnw8BP06tUKgG7dmhAVdRYpJeHhx+nZsxm2tjb4+FSlenUd0dExCCFwcKgMQFaWHr1ejxDaVbCfforkv//tiZWVtitVqeJU4hyePBmLr29VfHyqUKmSNY880pA9e06bldmz5wyBgU0B6No1gKioi0gpsbe3pWnTGtja5h0UIJES7tzJREpJWlo6Ol3JY8oWHX0FX193fHyqUqmSDT16NCU8PNqszO7d0QQGtgCgW7fGREWdM+Yxmh49mpry6OvrTnT0FbNpo6LO4eNTlWrVqpQ6tmy7dh2iV68OCCFo0qQuqam3SExMNiuTmJhMWtptmjSpixCCXr06sHPnnwC0a9cYGxtrABo3rkt8/HUA7O0r07x5vQJyWzL3Q+5Kavfu3SQlJZX5fHLbtesIvXq1NR5bahdzbKltXK9t2bnzMAB+ftWoVcsrX7329pVp1uwhKlcun4E0/6bc2dnZmvaVjIxMoPhegPLeD376aR+DB3c17belORZbUt7KM7672SfK4hyr07ng76/1WDk42OHn55lv+e6WJeWuvGL7p9vdmTOpeHvbUa2aHZUqWdGpkwf795sfy/bvT6J7d+0n+Dp00HHkSApSSmJibtGkifbdzM3NFkdHG86evQmAg4OWK71ekpVlQNzfnYmA1qNYnv8qwv3eULQDlgEDpZRN0IbSvi6lXADEAt2llNljIj6UUrYCmgJdhRBNC6tUCFEJ+BzoL6VsCSwBpkspTwK2QojaxqIDgdWFlS+k+ipAe+BdtLHD84BGQBPjsNG86qH95kkjIBnoV1jcxl7VicBqYy/rauBDYJuUsg3QHZgthHAE/gfMN/bOtkK7wbXEEhKS8fJyM7328HAlISElT5kUPD1zynh6upGQkAxAUlKqqaHn7u5CUlIqADExCaSm3uLNNz/nv/+dzebN+431u/Hcc915+unJPPHEBJyc7GnbtkEBcaXg6ZnTgNTiulFoGRsbaxwd7UhJuUVCwg2zeHMvk15v4MUX5/H441No1ao+jRppw0P++usaYWGHGTZsPu+/v5iYGPMewaIkJKTi4ZHTEPbwcCEhIbWAMi7GWK1wcqpMSsrtQuu0sbHm3XcDeemlhfTrN59LlxLp3bt5iWPKmW/+PCYmmucxMbHgPCYm3jCb1tPTJd+2ERZ2hJ49m5U6LvMYr+PlVTXXfKqYtq+cMsl4elbJU+Z6vrp++SWc9u3vzfDA+yF3liwhISXPscWtkPWaU0Y7ttybL5b3s7LM3fHjFxg0aCqDB09n1KhnTV9Ei4qlPPeDmJhrHD58kVdf/Yrhwxfma1gWF6ul5K2847ubWMriHJvt6tUkTp+OpWHDnCGY69bt5YUX5jJjxhpu3CjybqIC47WU3JVnbP9ku0tKykCnszW9dne35dq1dLMy165loNNpF9CtrQUODjakpmZRu7Yj+/cnoddL4uLucO7cTbNpP/roOC++uB97e2vat9eVOCal4tzvDUVr4IKUMrsbJgjoUkjZAUKIg8CfaA2zosZt+QONgd+FEIeA8WhPDwJYg9ZAxPj/6mLK5/WLlFICR4E4KeVRKaUBOA74FVD+gpTykPHvqELKFOUxYIwxrh1ojeuaQAQwTggxGqglpczX+hBCvGrshT0QFFR2tzwKIUxXlvR6A6dOxTBnzqvMm/c6S5f+yuXL8dy4cYvdu4+xdu0k1q+fyu3bGWzZUuhDmu45a2srli17l3XrPiQ6+jLnz/8NQGZmFra2Nixe/A5PPNGGmTMLHoJbXrKy9Kxff5DvvnuZH354hzp1PFmxYm+FxpRXZmYWe/ZE071744oOBYClSzdgbW1FYGC7ig6lWJaWO+XB0ahRbVaunGAc0vYb6emZFRZLQfuBXq/nxo1bfPvt67zxRi8mTfoe7VRbsSwpb5bu1q10PvwwhHfeeRxHRzsAnn66PatXj2bp0hG4u7vwxRcbKjjK+0NFbXc9enih09kycuRhFi++QIMGLlhZ5XQdTprUiCVL2pCZKTl6VF3cux/cVw+zuVvGHsCRQGsp5XXjME+7oiYBjksp2xfw2WogVAixDm247xkhRJMiyueVfWnFkOvv7NcFrY/cZfSAvfHvLHIa+sUtSz8p5ak870cLIfYBfYBNQojXpJTbchfI/Xst165tkT/8sJv16yMAaNCgJnFxyaayCQkpeHiYDwX18HAlPj6nTHx8Mh4eboA2pDQxMQWdzpXExBSqVHE2TePq2gB7+8rGIYB1OXtWe7qvj09V03Cibt2acvToBQIDWxcwz5yDjxaXS4FlPD3dyMrSk5Z2B1dXBzw8XMziLWiZnJ3tadGiLpGRp6hTpxoeHq507ar1RHXp0pgZM0reUPTwcDbrQUxIuGHWw5hT5gaeni5kZRm4eTMdV1f7vFWZnD2r3R/g66v1onXv3pCVK0vfUCwojzqdeR51uuw8uprlUadzMZs2Pv6GWR4jI09Tv76P2bDikgoN3cbPP+8CoGFDP+LicobDxMdfN21fOcvhZhpSmlMmp4dxw4ZwwsMP8+WXI03Dif8pS82dJVu7difr1+8BICCgVp5jS3Ih6zWnjHZsyT8U/UFQ3rnz86uGg0Nlzp+PNT08oyDlvR9ox+JGCCFo2LAGQgiSk9MKHYJqqXmrqPhKqqzOsVlZesaPD+Gxxx42nVPB/PaTJ55ow6hRS4uN0VJzVxGxlXa7A6ha1ZbExJzHfly7loG7e2WzMu7utiQmpqPTVUavl9y6lYWzsw1CCF56qY6p3JgxR/DxMf/OYmtrRZs2Vdm//xrNm7uVeFkskSU9zKas3O9LqAf8hBDZd/IOAXYa/04Fso8wLkAakCKE8AKKexTaKcBDCNEetKGoQohGAFLKc8b5TkBrNBZZvgxdBFoa/+6f6/3cyw3aE47eEsZvwUKIh43/1wHOG4fp/ow2JLdI/fp1JihoFEFBo+jSpQlbtvyBlJJjxy7i6GiX755Bnc4VR0c7jh3T7qvbsuUPOnfWrgB36tSYTZu0YaWbNu03vd+lSxMOHz5vug/x+PFL1KrlhZdXFY4fv8SdOxlIKTlw4DR+ftXyxdigQXViYhKJjU0iMzOLrVsP07Gjeedxx44N2bxZe8DLjh1HadHiIYQQdOzYkK1bD5ORkUVsbBIxMYkEBNTg+vWbpKZqHa7p6Zn88ccZatXyAKBz50YcPHgOgD//PE+NGiUfSuHv78OVK0lcvZpMZqaebdtO0KFDfbMyHTrUY8uWIwDs3BlNixZ+RTZodDpnLl5MIDk5DYADB85Tq1bph3c0aODLlSs5eQwLO0KnTuYPEejUqQFbtmgPFNqx4xgtWtRBCEGnTgGEhR0x5fHKlUQCAnI62LduPUyPHnc3dPKZZx5h+fLJLF8+mS5dHmbz5r1IKTl69BxOTg7odG5m5XU6Nxwd7Tl6VLv3afPmvXTp0hyAiIijhIRsYc6ct7Gzq5x/ZnfJUnNnyfr370pw8DiCg8fRpUszNm/eZzy2XMDR0b6IY8sF43rdR5cuxR7C/pXKI3exsYmmh2FcvXqNS5fi8PZ2L3Ka8t4POnduyMGD2lPeL1/W4s1+Uub9lLfyjO9ulMU5VkrJzJmh1KrlybPPmg8Kyz1cedeuY9Spk/+8n5el5q68Yvsn2x1AvXrOXL16m7i4O2RmGggPT6B166pmZVq3rsr27fEA7N2bSJMmrgghSE/Xc+eONu9Dh5KxthbUqOHA7dt6kpK0xqdeL4mKSqJ69fvyeZMPHGEJQzPuhhBiMnATbSjpHLTeuD/Q7lFMF0K8BQwHYqWU3Y29iB2AGCAFWC+lXCYK+XkM4/2CCwBXY92fSSm/M342EpgN1JZSXiyufK46lwEbpJRrhRB+xr8bF/DZRbT7Bp3ylBkJOEkpJwshGqANg9UDG4HBUko/IURVtMZhJWAm2n2QnxmX3QptKGtfIcQYtIZ1JvA32s9xFPrkhWvXtphtKFJKPv10LZGR0djZ2fLhh4MICNDuKXjhhVkEBY0CIDr6stnPY7z3Xj+EEKSkpDF+/FLi4q5TrVpVpk17ERcX7aS+YkUYGzfuQwjBE0+0Z+DAbgAsWrSJrVv/xNraivr1qzN27HPY2tpgMJiPnY+IiGb+/F8wGAz06dOaF17owaJFv9KgQXU6dWpEenomU6eu4syZWFxcHJg8eRC+vtpBNCgojI0b/8Da2oq3336C9u0bcPbsVaZPX43BYMBgkDzySFP++99HAUhNvc2UKd8TF5eMvb0tI0f+H/Xq+ZjFk5VV+PCKyMizfPHF7xgMBnr1asaQIZ1YsmQn/v7edOxYn/T0LGbM+JkzZ+JwcbFj4sSn8fHResQGDvyCW7fSyczU4+Rkx5w5z+Hn58HPP0fxww9/YGNjjZeXC2PGPI6ra8EHZGvrwr9IRUScYsGCDRgMkj59WjJ0aHcWLfrdmMcA0tMzmTYtNFcen8XHRzuZBAdvZ+PGKGMe+9CunT8At29n0L//J6xe/QFOTkV1hGtsbfPfqJ9NSsns2SuIjDxm+nmMgAA/AAYP1hqToP08xpQpi43bYBNGjhyEEIJ+/caSkZGJq6vW49C4cR3GjBkKwFNPjSIt7bYxtw4sWPAedeqYr9eMDPMn/VlS7ry8+hf5eUmtXLmSbt26odPpiIuLY9KkSSxZsuQf13vt2u+FfialZM6cNezbd4LKlW0ZP36w6Ur40KEzCA4eB0B09CWmTQshPT2Tdu0a8v77AxBCsGPHIebODSU5+SZOTvbUr1+dzz4bDsDTT08gLe0OWVlZODk5MH/+cGrXNn/umLv7o/94+aBscldU3qDscrd58z5CQn7DxsYaIax46aVedO2a/4JF3mNdee4HmZlZzJy5jrNnY7GxseHNN3vRsmVd0+c2NoX3wlR03opT0fuEXp+WZ73e23Ps4cMXePPNr6lbt5rpQmj2z2Bk1yMEVKtWhQ8+6GfWM13UOcwSclcRsZV0u/v775WFxhYVlcTixRcwGKBHD0+eeaYGK1de4qGHnGjTxp2MDAOffXaaCxfScHKy4f33/alWzY74+Dt89NFx489z2fLmmw/h6WlHcnIG06dHk5lpwGCAJk1ceeml2kX+PEbDhkss/nE3L78cUa6NqEWL2pd7Tu7bhqJSvvI2FC1J3oaipSmqoVjRijvJVrSiGooVraiGYkW7Vw3FslJcg6ci3auGYlmw5LyBZR/rimooKkXL21C0JJZ+DrNkRTUULYFqKOZXEQ3FB+IeRUVRFEVRFEVRlHtF3aOoKIqiKIqiKIqiPHBUj6KiKIqiKIqiKEopqB5FRVEURVEURVEU5YGjehQVRVEURVEURVFKQfUoKoqiKIqiKIqiKA8c1aOoKIqiKIqiKIpSCqpHUVEURVEURVEURXngqB5FRVEURVEURVGUUlA9ioqiKIqiKIqiKMoDR/UoKoqiKIqiKIqilMKD0KOoGopKiWRkxFd0CIWqXNmnokMokpVV5YoOoVCZmdcqOoQiZWTEVXQIhTIY7lR0CIW6du33ig6hSO7uj1Z0CIWy5NwZDOkVHcJ9y9Jzp9ffrOgQCmXJubPk4zCAlZVdRYdQKHf3/1R0CMp94N/fFFYURVEURVEURVFKRfUoKoqiKIqiKIqilMKDMPT037+EiqIoiqIoiqIoSqmoHkVFURRFURRFUZRSUD2KiqIoiqIoiqIoygNH9SgqiqIoiqIoiqKUgupRVBRFURRFURRFUR44qkdRURRFURRFURSlFFSPoqIoiqIoiqIoivLAUT2KiqIoiqIoiqIopaB6FBVFURRFURRFUZQHzgPZoyiEcAfCjC+rAXogwfi6jZQyI1fZEcBCKeWtYurcAYyUUh645wH/Q0KIi0ArKWWiEOKmlNLpXta/b985vvjiN/R6SZ8+zXn++Q5mn2dkZDFz5npOnfobV1d7Jk58Gm9vN1JSbjFp0jpOnowlMLApI0YEmqbZtu0Ey5fvwWAw0L59PV577ZG7ik1Kybx5oezdexw7O1smTBiCv3/NfOVOnrzM1KkhpKdn0KFDI9599xmEEISFHWTx4o1cvBjH4sUfEBBQC4D9+6P56qufyczUU6mSNcOHP02rVv6liGkdEREnsLOrxPjxz+PvX6OAmGKYNm0F6emZtG/fkHff/T+EENy4kcaECcu4ejUJb++qTJ36X1xcHDh48AyjRy/Cx8cdgK5dm/LSS1pOV6/ewfr1EQA88UR7Bg7sVmyc+/ad5fPPf8VgMNCnz8M8/3wns88zMrKYMeMnTp++iouLPZMm9Tet14kTQzl1KpbAwOaMGNHLNE1mpp7PPtvMoUMXsbISvPzyI3TtGlCivO3bd5r58zdgMBjo27c1gwd3zRfP9OmhnDr1Fy4uDnz00XN4e1cBICRkBxs3HsDKyop33ulL27b1AUhNvc0nn6zjwoU4hBCMGdOPxo1rsmTJVn755QBubo4AvPrqY7RvX7L1a4m5y62s9omUlJuMG7eI6OhL9O7djpEjB5Y6ttJYvHgxffv2JT4+niZNmpTpvLJZWu6klHz22Y9ERERjZ2fLhx8+h79/9QLiiWH69O+Nx5IARox4OtexJIS//06iWrWqTJ06FBcXB379NYoVK7YhpcTBwY6RI/tRr54vADNmrGLPnhNUqeLE8uWjiozvXu+zly8nMGnSKtP0sbFJDBvWkwEDOjJp0vdcvpwIwM2bt3Fysmfp0rfu49ydYcGCTRgMkj59WjB4cJcCcreO06djcXGxZ/LkAabcLV++i40bD2JlJXjnnd60aVMPgDVr9rJhQxRCCOrU8WLMmKeoXLkSw4cv4tYt7WvP9etpBAT4MmPGoCLjy4nz3p7/b91K5623gk3TJySk8uijjXnrrcdKGI9l5y0y8hTz5/+MwSDp27cNQ4Z0zxfftGmrTPvElCnP4+1dFYCQkG1s2PAHVlaCESOepG1bf+Likpk2bRXXr98EBE880ZYBA8zPN99/v5Mvv9zIhg2TTOe08spdaGgEGzZEIaWkb9+WDBigbR9fffUre/eewsbGGl/fqowZ8xTOzvZF5s4SqR7Ffykp5TUpZXMpZXPgG2Be9uvcjUSjEYBDecd4v9DrDcyfv4VPPnmWoKDX2LbtOBcvJpiV2bTpEE5Odqxc+Qb9+7dh4cJtANja2vDSS115/fUeZuVTUm7xzTdhzJ07iGXLXiMp6SZRURfuKr6IiOPExCQQGjqZMWMGMWvWqgLLzZq1irFjBxEaOpmYmAQiI08AULeuDzNnvkrz5g+ZlXd1dWL27P+xYsWHTJgwlI8+CipFTCe4ciWBNWvGM3r0s8yeHVpgudmz1zBmzLOsWTOeK1cSiIyMBiAkZCstW9ZnzZoJtGxZn5CQraZpmjWrQ1DQKIKCRpkaiefOxbJ+fQSLF79PUNAo9uw5zpUrCQXOM5teb+CzzzYza9YggoLeICws/3rduPFPnJ3tWbnyLZ55ph3ffqvFYWtrw7Bh3Xn99Ufz1RsSspsqVRxYsWI4QUFv0KxZrRLlTK83MHfueubMeZGQkBFs3XqYCxfi8sRzAGdne1atGsmAAR355pstAFy4EEdY2BGCg0cwZ86LzJ27Hr3eAMCCBRto27Y+K1a8x9Klb1GrloepvgEDOrJ06VssXfpWqRqJlpa7vMpqn7C1rcSrr/Zl+PD/u6u4SmvZsmUEBgYWX/AesrTcRUREc+VKIqtXj2PUqGeYM2dtgeXmzFnL6NEDWL16HFeuJBIZeRLQvni2alWP1avH0apVPZYv166f+vhU5Ysv3iQkZBQvvvgos2blHKN6927N3LmvFhtbWeyzNWt6mPbJRYvexM6uEl26NATgo4+eM33WtWtj0/v3a+7mzdvA7NlDCA4eTljYUS5ejM+Tu4M4O9vx/fcjGDCgA9988zsAFy/GExZ2lKCg4cyePZS5czeg1xtISLjB2rWRfPfd/wgKGo7BYGDbtmMAfPHFyyxZ8gZLlrxBo0Y1is1d7jjv9fnfwaEyixe/YvpXrZorXbo0KHE8lpw3bZ/4kTlzhrF8+fts3Xoo3z6xYcN+nJ3tWb16NAMHdubrrzcB2j6xdethQkLe59NPX+bTT39ErzdgbW3F8OF9Wb58JAsXvsm6dXvN6oyLS+aPP87g5eVW7rk7fz6ODRui+PbbV1my5A0iIk5z5co1AFq1qsuyZW+ybNmbVK/uzvLlu4uMT6k4D2RDsSBCiB5CiD+FEEeFEEuEEJWFEG8DPsB2IcR2Y7mvhRAHhBDHhRAflaDelkKInUKIKCHEr0IIbyFEAyHE/lxl/IQQRwsrX0CdXkKIH4UQh43/Ohjf/8k43XEhRJFnI2Mcu4QQh4QQx4QQnUuXMc3Jk7H4+lbFx6cKlSpZ88gjDdmz57RZmT17zhAY2BSArl0DiIq6iJQSe3tbmjatga2tecf21avJVK9e1XTlq2XL2uzadfJuwmPXriP06tUWIQSNG9fm5s3bJCammJVJTEwhLe0OjRvXRghBr15t2bnzMAB+ftWoVcsrX73+/jXw8HADoE4db9LTM8nIyCxRTLt3HyMwsLUxJr9iYvJDCEFgYGt27Tpqmr537zYA9O7dht27jxY5v0uX4mjUqBZ2drbY2Fjz8MMPsWPHkSKniY7+C1/fKrnWayPCw0+Zldmz5xT/+U/2em3IwYMXcq3XmvnWK2hfGrJ716ysBG5uJbsGEx19BV9fd3x8qlKpkg09ejQlPDzarMzu3dEEBrYAoFu3xkRFnUNKSXh4ND16NMXW1gYfn6r4+roTHX2FmzfvcPjwRfr2bQVApUo29+SKpqXlLq+y2ifs7SvTrNlDVK5cPgNVdu/eTVJSUrnMK5ul5S48/BiBga1Mx5LU1NskJt7IE88N0tLScx1LWpmOGbt3H6NXr9YA9OrVml27tC/ATZrUxsVF274aNapFfHyyqb7mzeuaPitKWeyzuUVFncPHpyrVqlUxe19KyfbtR+nZs9l9nruquXLXhPBw83NgeHg0gYHNgexjyHlj7k7So0cTY+6q4Otb1ZQ7vd5AenomWVl67tzJxN3d2azOtLQ7HDx4ns6dS9YwK4vzf24xMde4fj2Npk3zj7gpiKXnLTo6hurVdfj6ulOpkg09ezYjPPx4nvhO0KuXdk7q1q0JUVFnjfEdp2fPZqZ9onp1HdHRMeh0LqaecAcHO/z8PM2OSZ9//guvv94bIUS55+7SpQQCAqqbvns0b+7Hrl3aRbM2bR7CxsYagEaNqpOQYL7v3S+EsCrXfxVBNRQ1dsAyYKCUsgnakNzXpZQLgFigu5Qye3zAh1LKVkBToKsQomlhlQohKgGfA/2llC2BJcB0KeVJwFYIUdtYdCCwurDyBVS9ANgppWwGtACyjzQvGadrBbxtHGJbmEHAr8Ze1WbAoSLKFiohIRUPj5yDpoeHCwkJqQWUcQHAxsYKJ6fKpKTcLrROX98qXL58jatXk8nKMhAefor4+Ls7iCQkpJhdSfPwcCMhITlPmWQ8PXPKeHq6kZBg/uWvKNu3/4m/fw1sbSuVMKbkPDG55ptfQkJKATFpcSclpaLTuQLg7u5CUlJOvo8du8jQoZ/w3nvfcP78VUBryB4+fJ6UlDTu3Mlg794TxMdfLzLGxMRUPD1dc8XoQmJiaqFlbGyscHS0K3K9pqbeAWDx4u28/PJCJk4MJSnpZpFxZNPykTse1wK+1KXkisfaGM8tEhNvmE3r6elCQkIKV68m4ebmyIwZP/DSS5/z8cfruH07Z0DBunURvPDCAmbO/IHU1MKXKy9Ly11e5bFP/FtZWu4SEm4UO6/8+46b6UvZ9eup6HTasdnd3Znr1823U4ANG/bRrl3phziXxT6bW1jYkQIbg4cPX6RKFSdq1NAVE5/l5q6gY0jeL9LmxxBrHB0rk5Jyy7hcefOunYOffbYjzzwzl6efno2jox1t2pj3bO/efZKWLevg6GhXojjL4vyf27ZtJ+jevWGxjZxslp63gvaJvPHlLpN7n8i7vRb0veHq1SROn46lYcOaxriOo9O5UK+eT5Fx5c2LVv8/z13t2l4cOXKJlJRb3LmTQWTk6QK/y23adJB27eoVG6NSMVRDUWMNXJBSZl8KCwK6FFJ2gBDiIPAn0AgoaqyBP9AY+F0IcQgYD2TfBLEGrYGI8f/VxZTP7RHgawAppV5KmX20eFsIcRiIBGoARe15fwD/FUJMBppIKfOd5YQQrxp7Tw8sX769iKruLWdne957L5ApU37k7beDqVbNDSsry9xUz5+P5auvfmb06OcqZP5CCLLPof7+NVi3bjLBwaPp378zY8YsArRejMGDezBixFe8++431K/vWyH5zB7G07hxDRYtepVGjarz1Ve/l3scueM5fTqWp55qy5Ilb2FvX4kVK3YC8NRTbVm1aiRLlw7H3d2ZL77YVGFxZsdqSblT/n20Y4n5F/KoqDNs2LCPN97oW0FRFSwzM4s9e6Lp3r1xvs+2bj1Mz56FXr8tE/dD7lJTbxMefpLVq9/lxx8/4M6dDH777bBZmbCwI/ToUT73+5bEtm0n6NGjUYXGcL/k7datdD78MIR33nkcR0c77tzJIDh4Gy+/XLJ7O8uCn58HgwZ14v33gxg5MoSHHvLGysp8PwkO3om1tTWPPlq+++y98iD0KD6QD7O5W8YewJFAaynldSHEMrTeyEInAY5LKdsX8NlqIFQIsQ6QUsozQogmRZQvLrZuQE+gvZTylvHhOoXGJqXcJYToAvQBlgkh5kopg/OUWQgsBLh6NVgWVI+Hh7PZFcSEhBtmVxhzytzA09OFrCwDN2+m4+pa9BC/Dh3q06GD9sCRX345mO/gUpS1a3eyfv0eAAICahEXl5wrvmTTkNGc+NzMhgfFxyfj4eFKceLjrzNmzHdMmDCU6tU9iiz7ww+7TQ+TadCgZp6YUvLNz8PDtYCYtLirVnUmMTEFnc6VxMQUqlTR8p37amaHDo2YM2ctyck3cXNz4vHH2/P449pm9c03v+TLQV46nTPx8TlXKxMSbqDTORdYJnu9pqXdKXK9urraG+8p0q6wd+/ekE2bDhUZRzYtH7njSTFdzc+Jx9UYjytZWXpjPA7odC5m08bH38DDw9X4z4VGjbRhTd26NWb58l2AluNsjz/emtGjS34PqqXlDspvn/g3srTc/fBDOOvXRxrjqVHsvPLvO8mmHp4qVZxJTLyBTudCYuIN3NxynnN29mwsH3+8hk8/fQVX18IfgFGYsthns0VGnqZ+fR+z/RQgK0vPrl3HWbRoeIEx3S+5K+gYkj3fvGVycpeOq6sDHh4uBeTdmQMHzuHtXcV0S0eXLg05duwyjz2m9comJ6cRHf0X06aV/KJnWZ3/Ac6ejUOvN+Dvn+/um0JZet4K2ifyxpddxtPTzWyf0OJLzjOttr1mZekZPz6Exx57mK5dtQbrX39d4+rVJF588TNT+Zdems93372Vb+hsWeUOoG/flvTt2xKAhQt/N9vHNm/+k4iIU8yb92KJe42V8meZ3TTlTw/4CSGyxxMMAXYa/04FsvcqFyANSBFCeAG9KNopwEMI0R60oahCiEYAUspzxvlOQGs0Flk+jzDgdWMZayGEK+AKXDc2EhsA7YoKTAhRC4iTUn4HLEIbwlpq/v4+XLmSxNWryWRm6tm27YSpgZetQ4d6bNmi3RO3c2c0LVr4FXtQuH49DdCu5v30UxR9+jQvcUz9+3clOHgcwcHj6NKlGZs370NKybFjF3B0tDcN28ym07ni6GjHsWPafWKbN++jS5eir26lpt7i/fe/5o03nqRZs7rFxtSvX2fTQ2a6dGnCli1/GGO6iKOjXRExafdzbNnyB507a1fPO3VqzKZN2i2umzbtN71/7doNpNTa8ydOXEJKg+lLSvbw1L//TmLHjiM89ljLIuNt0MDXuF6vG9frcTp2NF+vHTv68+uv2ev1BA8/XLvI9SqEoEOH+hw6dBGAqKgL1KpV9PAw83gSiY1NIjMzi7CwI3TqZD6kq1OnBmzZchCAHTuO0aJFHYQQdOoUQFjYETIysoiNTeLKlUQCAqrj7u6Mp6crly8nGOM5h5+fJ4DZELldu45Tu3b++8qKjtVycgfls0/8W1la7vr160RQ0EiCgkYajyUHTMcSJye7AhpjLjg6Vs51LDlAp07Zx5JGbN78BwCbN+ccY/7++zrjxi1l4sRB1KzpeVdxlsU+m23r1sP06JF/2GlU1Dlq1vQwGwZ3/+YuidjY68bcHaVjR/P73zp2bMCWLYcA7RjSooV2DOnYsQFhYUeNubvOlStJBARUx8vLlRMnYrhzJwMpJVFR580e3rVz5wnat/encuWS3UIBZXf+BwgLO06PHiV7qE42S89bgwbViYnJ2Se2bj1Mx47my9ixY0M2b9Yenr9jx1FatHjIGF9Dtm49bNonYmISCQiogZSSmTNDqVXLk2efzRkIV7euNxs2TGLt2rGsXTsWDw9Xlix5p8BGYlnlDjA+jVV7qM6uXdH07Kk1ZPftO8PKleHMnPk8dna2xeZOqTgi+4vlg8o49PIm2lDSOWi9rH+g3aOYLoR4CxgOxEopuxt7ETsAMUAKsF5Kuaywn8cQQjRHu6fQ1Vj3Z8bGGUKIkcBsoLaU8mJx5XPV6YXW01cHrbH5OnAQ+AnwQ2twugGTpZQ7RAE/jyGEeAH4AMg0Lv9QKWWhjxYtrEcRIDLyLF988TsGg4FevZoxZEgnlizZib+/Nx071ic9PYsZM37mzJk4XFzsmDjxaXx8tAcQDBz4BbdupZOZqcfJyY45c57Dz8+DKVN+5Nw57YlbQ4d2KnL4SeXKhY+/l1IyZ84a9u07QeXKtowfP9j0SPqhQ2cQHDwOgOjoS0ybFkJ6eibt2jXk/fcHIIRgx45DzJ0bSnLyTZyc7KlfvzqffTacpUs3Exz8GzVq5JwwPvvsrXxXuLUYsvLF9Omna4mMzH4s+yACArR7Cl54YRZBQaOMMV02+3mM997rhxCClJQ0xo9fSlzcdapVq8q0aS/i4uLI2rW7+PHHPVhbW1G5ciXefvtpmjTRboN9/fX5pKSkYWNjzdtvP2X6KY/MzGuF5i4y8ozxJx4kvXs3Z8iQzixevJ0GDXzo2NGf9PQspk//kbNn/8bZ2Z5Jk/rlWq/zSUtLJysre70Oxs/Pg7//Tmb69J+4efMObm4OjBnzJF5ehfe2WFnl9JJGRJxiwYINxkd3t2To0O4sWvQ7DRpUp1OnANLTM5k2LZQzZ2JxcXFg8uRn8fHRHiseHLydjRujsLa24u23+9Cunbb8Z87E8sknP5KZqcfHpwrjxvXH2dmeqVPXcPbsVUDg7e3GyJFP5fsSaTDcsdjc2doW3rAtq30C4OmnJ5CWdoesrCycnByYP384tWvn7xFwd8//VNfSWrlyJd26dUOn0xEXF8ekSZNYsmTJP6732rXCh/RWdO4MhvR88cydu47IyJPY2VVi3LjnCAjQeshfeGEOQUEjjfHk/MRDu3YNeO+9/zMdSyZMCDYeS6oYf+LBkZkzV7Nz5xG8vLRt0traiiVL3gNg0qQQ/vzzLMnJaVSt6sywYf/h8cfbGeMz3yfKYp+9fTuD/v0/YfXqD3ByMh80M336Who1qsFTT7XNt+5yH0ssMXd6vfk9xxERp/n8880YDAZ6927B0KFdWbw4DH9/Xzp1akB6eibTp6/jzJmrODvbM3nyM7lyt5NNmw5ibW3FW2/1ol07rfG2ZMk2tm07hrW1FfXqeTNq1JOmh8m8/fYSnn++M23b5r9jJe92l1tZnP8BnnvuSz7+eGCxF8SsrCpbbN60+My3u4iIaObP/8X400mteeGFHixa9Ktxn2hEenomU6euyrVPDMLXV3vcRFBQGBs3/mHcJ56gffsGHD58gTff/Jq6dauZGuCvvRZI+/bmF2X695/JokVvm/08Rv799d7nbvjwRaSk3MbGxorhwwNp2bKucf1+RkZGFq6u2sOdGjaszsiRT5jF4+U10OK7Gd9//69ybUR9+qlvuefkgW8oKiVTVEOxohXVULQEeRuKlqSohqIlyHuStSRFNRQrWlENRUtwLxqKZaWohmJFK+oLuyWw5H3Cko8lkL+haEksebvL21C0NJa83Vny/gqqoViQimgoqnsUFUVRFEVRFEVRSqGiHjBTnv79S6goiqIoiqIoiqKUiupRVBRFURRFURRFKQXVo6goiqIoiqIoiqI8cFSPoqIoiqIoiqIoSimoHkVFURRFURRFURTlgaN6FBVFURRFURRFUUpB9SgqiqIoiqIoiqIoDxzVo6goiqIoiqIoilIKqkdRURRFURRFURRFeeCoHkVFURRFURRFUZRSeBB6FFVDUSkRW1vPig6hUHp9WkWHUKSsrJSKDqFQ1taOFR1CkWxtvSo6hEJlZMRVdAiFcnd/tKJDKNK1a79XdAiFsuTcWXLeAAyGOxUdQqGsrCpXdAhFsuT4LPkca+nnMEuWkPBzRYdQJC+vgRUdgoJqKCqKoiiKoiiKopTKg9Cj+O9fQkVRFEVRFEVRFKVUVENRURRFURRFURRFMaOGniqKoiiKoiiKopSCGnqqKIqiKIqiKIqiPHBUj6KiKIqiKIqiKEopqB5FRVEURVEURVEU5YGjehQVRVEURVEURVFKQfUoKoqiKIqiKIqiKA8c1aOoKIqiKIqiKIpSCqpHUVEURVEURVEURXng/Ct6FIUQ7kCY8WU1QA8kGF+3kVJm5Co7AlgopbxVTJ07gJFSygP3POASEEL4ARuklI0rYv7FkVIyb946IiJOYGdXifHjn8ffv0a+cidPxjBt2grS0zNp374h7777fwghuHEjjQkTlnH1ahLe3lWZOvW/uLg4AHDw4Bnmz/+RrCw9rq6OfPXV21y6FMfEiUGmev/6K5FXXunNwIHd8s0zMvIU8+f/jMEg6du3DUOGdDf7PCMji2nTVnHq1F+4uDgwZcrzeHtXBSAkZBsbNvyBlZVgxIgnadvWn/T0TIYP/4aMjCz0egPduzdh2LDHTHlYuPBXtm8/grW1FU891Y5nnulU4jzu23eOL774Db1e0qdPc55/vkO+WGfOXM+pU3/j6mrPxIlP4+3tRkrKLSZNWsfJk7EEBjZlxIhA0zRhYcdZvnwPQgjc3Z348MMncXNzKHFMObGdZv78DRgMBvr2bc3gwV3zxTZ9eqgpjx999Bze3lWMedzBxo0HsLKy4p13+tK2bX0uX05g0qRVpuljY5MYNqwnAwZ0LHVsoOV+7tzv2bv3KHZ2tkyY8BINGtTKVy46+iJTpy4hPT2TDh2a8N57zyGEYMGCNYSHH6ZSJRt8fT2YMOElnJ0dSEm5yZgxXxEdfZE+fTrywQfPlzo2S89dSS1evJi+ffsSHx9PkyZNynRe2bRjSyh79x43rtch+PvXzFfu5MnLTJ0aQnp6Bh06NOLdd59BCEFY2EEWL97IxYtxLF78AQEB2jaRknKTceMWER19id692zFy5MAyXY5/U+6OH7/IJ5+sNM4Dhg3rTbduzYuNp7z3g7Vr9/Ljj5FYWVnRvr0/b7zR677MW3nFd7f7xL0+x8bFJTNt2iquX78JCJ54oi0DBmjn0cWLf+OXX/bj5uYIwGuvBdK+fcB9m7vyiO1ebHcHD15n8eLzGAzQs6cX/fpVN/s8M9PA/PmnOXcuDWdnG0aO9MfT047MTAPffHOOs2dvYmUFw4bVoXFjVwCmTDnO9esZ6PWSgAAXXn21LtbWotR5sySqR/E+IaW8JqVsLqVsDnwDzMt+nbuRaDQCKP235vuMEKJMLwJERJzgypUE1qwZz+jRzzJ7dmiB5WbPXsOYMc+yZs14rlxJIDIyGoCQkK20bFmfNWsm0LJlfUJCtgKQmnqLOXNC+eSTl1mxYizTpv0XgFq1vAgKGkVQ0CiWLBmJnZ0tXbo0zTc/vd7A3Lk/MmfOMJYvf5+tWw9x4UKcWZkNG/bj7GzP6tWjGTiwM19/vQmACxfi2Lr1MCEh7/Pppy/z6ac/otcbsLW1Yf78VwkKepdly0YQGXmKY8cuAbBp0wHi45NZuXIkK1aMpGfP5iXOoV5vYP78LXzyybMEBb3Gtm3HuXgxwazMpk2HcHKyY+XKN+jfvw0LF24DwNbWhpde6srrr/cwK5+VZeDzz39j3rzBLFnyCnXrevLjj6W/1qHlcT1z5rxISMgItm49nC+PGzcewNnZnlWrRjJgQEe++WYLoOUxLOwIwcEjmDPnRebOXY9eb6BmTQ+WLn2LpUvfYtGiN7Gzq0SXLg1LHVu2vXuPEhMTx9q1MxgzZiizZoUUWG7WrOWMHfsCa9fOICYmjoiIYwC0adOQlSunsGLFR9Ss6UVQ0EYAbG0r8dprT/P22wPuKq77IXcltWzZMgIDA4sveA9FRBwnJiaB0NDJjBkziFmzVhVYbtasVYwdO4jQ0MnExCQQGXkCgLp1fZg581WaN3/IrLytbSVefbUvw4f/X5kvA/y7cle3rg9LlowmOHgc8+a9yaxZ35OVpS8ylvLeDw4ePEd4eDRLl75NSMgInnuu832Zt/KM7272ibI4x1pbWzF8eF+WLx/JwoVvsm7dXrM6BwzozLJl77Js2bulaiSCZeWuvGL7p9udXi9ZuPA8EyY0YsGChwkPTyAmxrxvZevWOBwdbfj665Y8/rgPwcEXAfj9d229zZ//MJMmNWLp0gsYDBKAkSP9mTfvYebPf5gbN7LYuzexxDEpFedf0VAsiBCihxDiTyHEUSHEEiFEZSHE24APsF0Isd1Y7mshxAEhxHEhxEclqLelEGKnECJKCPGrEMJbCNFACLE/Vxk/IcTRwsoXUKeXEOJHIcRh47/sbiVrIcR3xth+E0LYG8u/IoT4w1j2ByGEg/H9ZUKIb4QQ+4BZQoi6QohIYw6mCSFu5prnB8Y6jpRkufPavfsYgYGtEULQuLEfN2/eJjExxaxMYmIKaWl3aNzYDyEEgYGt2bXrqGn63r3bANC7dxt279be/+23KLp2bUa1atrVx6pVnfPN+8CB0/j66kxXKHOLjo6henUdvr7uVKpkQ8+ezQgPP25WJjz8BL16tQKgW7cmREWdRUpJePhxevZshq2tDT4+ValeXUd0dAxCCBwcKgOQlaVHr9cjhHYV7KefIvnvf3tiZaXtSlWqOJU4hydPxuLrWxUfnypUqmTNI480ZM+e02Zl9uw5Q2Cg1iDu2jWAqKiLSCmxt7eladMa2NrmvR4gkRLu3MlESklaWjo6XcljyhYdfQVfX3d8fKpSqZINPXo0JTw82qzM7t3RBAa2AKBbt8ZERZ0z5jGaHj2amvLo6+tOdPQVs2mjos7h41OVatWqlDq2bLt2HaJXrw4IIWjSpC6pqbdITEw2K5OYmExa2m2aNKmLEIJevTqwc+efALRr1xgbG2sAGjeuS3z8dQDs7SvTvHm9AnJbMvdD7kpq9+7dJCUllfl8ctu16wi9erU1HltqF3NsqW1cr23ZufMwAH5+1ahVyytfvfb2lWnW7CEqVy6fgTT/ptzZ2dma9pWMjEyg+F6A8t4PfvppH4MHdzXtt6U5FltS3sozvrvZJ8riHKvTueDvr/VYOTjY4efnmW/57pYl5a68Yvun292ZM6l4e9tRrZodlSpZ0amTB/v3mx/L9u9Pont3TwA6dNBx5EgKUkpiYm7RpInWg+jmZoujow1nz2pfPR0ctFzp9ZKsLAPi/u5MBLQexfL8VxH+rQ1FO2AZMFBK2QRtiO3rUsoFQCzQXUqZPVbiQyllK6Ap0FUIkb+bykgIUQn4HOgvpWwJLAGmSylPArZCiNrGogOB1YWVL6DqBcBOKWUzoAWQfdStB3wppWwEJAP9jO+vk1K2NpaPBoblqqs60EFK+R4wH5hvzIHpLCuEeMxYdxugOdBSCNGlsOUuSEJCMl5ebqbXHh6uJCSk5CmTgqdnThlPTzcSEpIBSEpKRafTDibu7i4kJaUCEBOTQGrqLd5883P++9/ZbN68n7y2bj3Io4+2KCSuFDw9XfPEdaPQMjY21jg62pGScouEhBtm8eZeJr3ewIsvzuPxx6fQqlV9GjXShof89dc1wsIOM2zYfN5/fzExMeY9gkVJSEjFwyOnIezh4UJCQmoBZVyMsVrh5FSZlJTbhdZpY2PNu+8G8tJLC+nXbz6XLiXSu3fzEseUM9/8eUxMNM9jYmLBeUxMvGE2raenS75tIyzsCD17Nit1XOYxXsfLK+digadnFdP2lVMmGU/PKnnKXM9X1y+/hNO+/b0ZHng/5M6SJSSk5Dm2uBWyXnPKaMeWe/PF8n5Wlrk7fvwCgwZNZfDg6Ywa9azpi2hRsZTnfhATc43Dhy/y6qtfMXz4wnwNy+JitZS8lXd8dxNLWZxjs129msTp07E0bJgzBHPdur288MJcZsxYw40bRd41VGC8lpK78oztn2x3SUkZ6HS2ptfu7rZcu5ZuVubatQx0Ou0CurW1wMHBhtTULGrXdmT//iT0eklc3B3OnbtpNu1HHx3nxRf3Y29vTfv2uhLHpFScf2tD0Rq4IKXM7p4JAgprCA0QQhwE/gQaAUWN5/IHGgO/CyEOAePRGmYAa9AaiBj/X11M+dweAb4GkFLqpZTZR4ELUspDxr+jAD/j342FELuNvZbPG+POFiqlzB5j0B7IHhO6MleZx4z//gQOAg3QGo5mhBCvGntbDwQFbSog7HtDCGG6sqTXGzh1KoY5c15l3rzXWbr0Vy5fjjeVzczMIjz8GI880rzM4imItbUVy5a9y7p1HxIdfZnz5/82xWNra8Pixe/wxBNtmDmz4CG45SUrS8/69Qf57ruX+eGHd6hTx5MVK/ZWaEx5ZWZmsWdPNN27W8btt0uXbsDa2orAwHYVHUqxLC13yoOjUaParFw5wTik7TfS0zMrLJaC9gO9Xs+NG7f49tvXeeONXkya9D1SygqLMZsl5c3S3bqVzocfhvDOO4/j6GgHwNNPt2f16tEsXToCd3cXvvhiQwVHeX+oqO2uRw8vdDpbRo48zOLFF2jQwAUrq5yuw0mTGrFkSRsyMyVHj97/F/eEkOX6ryL8Kx5mc7eMPYAjgdZSyutCiGVovZGFTgIcl1K2L+Cz1UCoEGIdIKWUZ4QQTYooXxK5L+HoAXvj38uAp6SUh4UQLwLdcpVLK0G9Apgppfy2qEJSyoXAQoBr17bIH37Yzfr1EQA0aFCTuLhkU9mEhBQ8PFzNpvfwcCU+PqdMfHwyHh5ugDakNDExBZ3OlcTEFKpUcTZN4+raAHv7ysYhgHU5e/YvatbUhjhERERTv351qlZ1KTBmbZ45Bx8tLpcCy3h6upGVpSct7Q6urg54eLiYxVvQMjk729OiRV0iI09Rp041PDxc6dpV64nq0qUxM2aUvKHo4eFs1oOYkHDDrIcxp8wNPD1dyMoycPNmOq6u9nmrMjl7Vrs/wNdX60Xr3r0hK1eWvqFYUB51OvM86nTZeXQ1y6NO52I2bXz8DbM8Rkaepn59nwKHFRcnNHQbP/+8C4CGDf2Ii8sZDhMff920feUsh5tpSGlOmZwexg0bwgkPP8yXX440DSf+pyw1d5Zs7dqdrF+/B4CAgFp5ji3JhazXnDLascV8X31QlHfu/Pyq4eBQmfPnY00PzyhIee8H2rG4EUIIGjasgRCC5OS0QoegWmreKiq+kiqrc2xWlp7x40N47LGHTedUML/95Ikn2jBq1NJiY7TU3FVEbKXd7gCqVrUlMTHn8R7XrmXg7l7ZrIy7uy2JienodJXR6yW3bmXh7GyDEIKXXqpjKjdmzBF8fMy/s9jaWtGmTVX2779G8+ZuJV4WpWL8W3sU9YCfECL7Dt8hwE7j36lA9pHHBa1hlSKE8AKKe0TaKcBDCNEetKGoQohGAFLKc8b5TkBrNBZZPo8w4HVjGWshRHFHAWfgqnFoa1GPZIwkZ7jqs7ne/xV4SQjhZJynrxDCs5h50q9fZ9MDZbp0acKWLX8gpeTYsYs4OtqZhpJm0+lccXS049gx7b66LVv+oHNn7Qpwp06N2bRJG1a6adN+0/tdujTh8OHzZGXpuXMng+PHL5mNwf/996hCh50CNGhQnZiYRGJjk8jMzGLr1sN07GjeSdyxY0M2b9Ye8LJjx1FatHgIIQQdOzZk69bDZGRkERubRExMIgEBNbh+/Sapqdpwz/T0TP744wy1ankA0LlzIw4ePAfAn3+ep0aNkg+l8Pf34cqVJK5eTSYzU8+2bSfo0KG+WZkOHeqxZcsRAHbujKZFC78iGzQ6nTMXLyaQnKxdLzhw4Dy1apV+eEeDBr5cuZKTx7CwI3TqZP4QgU6dGrBly0EAduw4RosWdRBC0KlTAGFhR0x5vHIlkYCAnI70rVsP06PH3Q2dfOaZR1i+fDLLl0+mS5eH2bx5L1JKjh49h5OTAzqdm1l5nc4NR0d7jh7V7n3avHkvXbo0ByAi4ighIVuYM+dt7Owq55/ZXbLU3Fmy/v27Ehw8juDgcXTp0ozNm/cZjy0XcHS0L+LYcsG4XvcV+HCrB0F55C42NtH0MIyrV69x6VIc3t7uRU5T3vtB584NOXjwPACXL2vxZj8p837KW3nGdzfK4hwrpWTmzFBq1fLk2WfNB3/lHq68a9cx6tSpVmyMlpq78ortn2x3APXqOXP16m3i4u6QmWkgPDyB1q3NnwnRunVVtm/XRnvt3ZtIkyauCCFIT9dz544270OHkrG2FtSo4cDt23qSkrTGp14viYpKonr1+/+5kkJkleu/CllGSxiacS8JISYDN9GGVc5B6zX9A+0exXQhxFvAcCBWStnd2IvYAYgBUoD1UsplopCfxxBCNEe7p9DVWPdnUsrvjJ+NBGYDtaWUF4srn6tOL7Seuzpojc3Xgavk+nkMY91OUsrJQojXgVFoPwGyD3CWUr5oXJYNUsq1xmnqAcvReiK3AM9LKX2Nn70DvGwM4SYw2NjYLdC1a1vMNhQpJZ9+upbIyGjs7Gz58MNBBARo9xS88MIsgoJGARAdfdns5zHee68fQghSUtIYP34pcXHXqVatKtOmvYiLi3ZSX7EijI0b9yGE4Ikn2pt+AuP27XSefnoya9dOxMkp5wqVwWA+dj4iIpr583/BYDDQp09rXnihB4sW/UqDBtXp1KkR6emZTJ26ijNnYnFxcWDy5EH4+moH0aCgMDZu/ANrayvefvsJ2rdvwNmzV5k+fTUGgwGDQfLII035738fBSA19TZTpnxPXFwy9va2jBz5f9Sr52MWT1ZW4cMrIiPP8sUXv2MwGOjVqxlDhnRiyZKd+Pt707FjfdLTs5gx42fOnInDxcWOiROfxsdH6xEbOPALbt1KJzNTj5OTHXPmPIefnwc//xzFDz/8gY2NNV5eLowZ8ziurgUfkK2tC/8iFRFxigULNmAwSPr0acnQod1ZtOh3Yx4DSE/PZNq00Fx5fBYfH+1kEhy8nY0bo4x57EO7dv7GdZhB//6fsHr1Bzg5FdV5r7G1zX+jfjYpJbNnryAy8pjp5zECAvwAGDxYa0yC9vMYU6YsNm6DTRg5chBCCPr1G0tGRiaurlqPQ+PGdRgzZigATz01irS028bcOrBgwXvUqWO+XjMyzJ/0Z0m58/LqX+TnJbVy5Uq6deuGTqcjLi6OSZMmsWTJkn9c77Vrvxf6mZSSOXPWsG/fCSpXtmX8+MGmK+FDh84gOHgcANHRl5g2LYT09EzatWvI++8PQAjBjh2HmDs3lOTkmzg52VO/fnU++2w4AE8/PYG0tDtkZWXh5OTA/PnDqV3b/Pli7u6P/uPlg7LJXVF5g7LL3ebN+wgJ+Q0bG2uEsOKll3rRtWv+CxZ5j3XluR9kZmYxc+Y6zp6NxcbGhjff7EXLlnVNn9vYFH79taLzVpyK3if0evOBSvf6HHv48AXefPNr6tatZroQmv0zGNn1CAHVqlXhgw/6mfVMF3UOs4TcVURsJd3u/v57Zb73skVFJbF48QUMBujRw5NnnqnBypWXeOghJ9q0cScjw8Bnn53mwoU0nJxseP99f6pVsyM+/g4ffXQcIQTu7ra8+eZDeHrakZycwfTp0WRmGjAYoEkTV156qXaRP4/RsOESi3/czZQpGeXaiJo40bbcc/KvaygqOYxPQ70tpZRCiGeB56SUT95NXXkbipYkb0PR0hTVUKxoxZ1kK1pRDcWKVlRDsaLdq4ZiWSmuwVOR7lVDsSxYct7Aso91RTUUlaLlbShaEks/h1myohqKluB+aChOnZpWrt+NJ0xwLPecPND3KD4AWgJfCO0SXTLwUsWGoyiKoiiKoijK/UA1FP/FpJS7gX/fDU2KoiiKoiiKopQp1VBUFEVRFEVRFEUphYp6wEx5+rc+9VRRFEVRFEVRFEW5S6pHUVEURVEURVEUpRRUj6KiKIqiKIqiKIrywFE9ioqiKIqiKIqiKKWgehQVRVEURVEURVGUB47qUVQURVEURVEURSkFITIrOoQyp3oUFUVRFEVRFEVRFDOqR1FRFEVRFEVRFKUUHoR7FFVDUSkRISx3U7Gy8H5xa2vHig7hvnXr1umKDqFQNjauFR1Coa5d+72iQyiSwZBe0SEUypJz5+7+aEWHUKS//15V0SEUytJzl5S0vaJDKJQln8Ms+bsJgJSW25Bwdn64okNQ7gOWvYcpiqIoiqIoiqJYmAehR9HC+2IURVEURVEURVGU8qZ6FBVFURRFURRFUUpB9SgqiqIoiqIoiqIoDxzVo6goiqIoiqIoilIK6ncUFUVRFEVRFEVRlAeOaigqiqIoiqIoiqIoZtTQU0VRFEVRFEVRlFJQD7NRFEVRFEVRFEVRLJoQIlAIcUoIcVYIMaaIcv2EEFII0aq4OlWPoqIoiqIoiqIoSilYUo+iEMIa+BJ4FLgC/CGEWC+lPJGnnDPwDrCvJPWqHkVFURRFURRFUZT7VxvgrJTyvJQyA1gFPFlAuanAJ8CdklRqUT2KQgh3IMz4shqgBxKMr9sYFzy77AhgoZTyVjF17gBGSikPlDCGJ4CGUsqPiyjTzVhn3wI+K1FcRdTtAyyQUva/y+mfAk7nvYJQlqSUzJsXyt69x7Gzs2XChCH4+9fMV+7kyctMnRpCenoGHTo04t13n0EIQUpKGhMmLOHq1Wt4e7szbdowXFwcuHHjFtOnL+evvxKwta3Ehx8Opm5dnxLGs46IiBPY2VVi/Pjn8fevUUA8MUybtoL09Ezat2/Iu+/+H0IIbtxIY8KEZVy9moS3d1WmTv0vLi4OHDx4htGjF+Hj4w5A165NeemlQABWrdrOL79EAlC3rg8ffjiIypUrFRjfvn2nmT9/AwaDgb59WzN4cFezzzMyspg+PZRTp/7CxcWBjz56Dm/vKgCEhOxg48YDWFlZ8c47fWnbtj6XLycwadIq0/SxsUkMG9aTAQM6MmnS91y+nAjAzZu3cXKyZ+nStwrN3b2OLZteb+CVV75Ep3Nh1qwXAPj44x84efIvpIQaNdwZN64/Dg6VC40tr/37z/PFF2Ho9Qb69GnGoEHt8sU6c+ZGTp/+GxcXeyZNepJq1Vw5cOACCxfuJCtLj42NNf/7X3datKgFwKhRa7h27SZ6vYGmTWvwzjuPYm1dsutp90vu/un+GhZ2kMWLN3LxYhyLF39AQICWu+PHL/LJJyuN84Bhw3rTrVvzEsf02Wc/EhERjZ2dLR9++Bz+/tULiCmG6dO/N+6zAYwY8XSufTaEv/9Oolq1qkydOhQXFwd+/TWKFSu2IaXEwcGOkSP7Ua+eLwAzZqxiz54TVKnixPLlo+7b3N2NxYsX07dvX+Lj42nSpEmZzSe3ffvOsGDBJgwGSZ8+LRg8uIvZ59r+sY7Tp2NxcbFn8uQBeHtXISXlFhMnruLkyVgCA5vz7rs5p93vvtvKli2HuHnzDr/+Or5clqMicielZO7c1UREHKNyZVsmTHiRBg0K2u4uMXXqMuP+0Zj33hto3O6iWLToFy5e/JslS8YQEOAHQGxsIs89N5maNb0AaNy4DqNHP1/q2Mpin9i/P5qvvvqZzEw9lSpZM3z407Rq5V/KzFle7sr7+1J6eiavvz6PzMws9Ho93bs/zCuv5Pvqms/+/Zf46qvdGAySXr0a8txzLc0+z8jQ88knv3PmTAIuLnaMH/8fqlVz4eTJOObN225a1qFD29CpU10Ann8+CHv7SlhbW2FtLfjqq4HFxmHpyrtHUQjxKvBqrrcWSikXGv/2BWJyfXYFaJtn+hZADSnlRiHEByWZp0X1KEopr0kpm0spmwPfAPOyX+duJBqNABzKIIb1RTUSS2AE/yAuKWXs3TYSjZ4CGv6D6UstIuI4MTEJhIZOZsyYQcyatarAcrNmrWLs2EGEhk4mJiaByEitLRsS8hutWvkTGjqZVq38CQn5DYCgoC3Ur+/L8uUfMnHiUObNCy1hPCe4ciWBNWvGM3r0s8yeXfB0s2evYcyYZ1mzZjxXriQQGRltjGcrLVvWZ82aCbRsWZ+QkK2maZo1q0NQ0CiCgkaZGokJCcmEhu5iyZL3WbFiLAaDga1bDxY4T73ewNy565kz50VCQkawdethLlyIMyuzceMBnJ3tWbVqJAMGdOSbb7YAcOFCHGFhRwgOHsGcOS8yd+569HoDNWt6sHTpWyxd+haLFr2JnV0lunTRNoGPPnrO9FnXro1N75dXbNlCQ/dSq5aHWV1vvdWHZcveJijobby83Fi3LrLQ2AqKdf783/n442dYtuxlwsJOcPFiolmZTZuO4Oxsx4oVr/HMM6349tsdALi6OjBjRj+WLBnG2LF9mDlzg2maSZOeZPHil1i6dBjJybfYufNkieO5X3L3T/fXunV9mDnzVZo3f8isfN26PixZMprg4HHMm/cms2Z9T1aWvoQxRXPlSiKrV49j1KhnmDNnbYHl5sxZy+jRA1i9ehxXriQSGamtn5CQbbRqVY/Vq8fRqlU9li/Xrjf6+FTliy/eJCRkFC+++CizZuUcC3r3bs3cua8WOJ/C47S83N2NZcuWERgYWGb156XXG5g3bwOzZw8hOHg4YWFHuXgx3qzMxo0HcXa24/vvRzBgQAe++eZ3AGxtbRg2rAdvvPGffPV26ODPt9++Vi7LkK28cwcQEXGMmJh4QkOnMnbsYGbNWlFguVmzVjJ27BBCQ6cSExNPRMRxAOrU8eHjj/9H8+b18k3j6+tBSMgEQkImlLqRqMVWNvuEq6sTs2f/jxUrPmTChKF89FFQqWPT4rOs3JX39yVbWxu++OJtQkLGERw8jsjIExw7dqHIGPV6A59/vpMZMx5n8eJBbN9+mkuXkszKbN58AmfnygQHD6Ffv2Z8991eAPz8qvLVVwP49ttnmTnzCT77bIfZ+ezTT5/m22+f/Vc0EiuClHKhlLJVrn8Li59KI4SwAuYC75dmnhbVUCyIEKKHEOJPIcRRIcQSIURlIcTbgA+wXQix3VjuayHEASHEcSHERyWo96IQ4iMhxEFj3Q2M778ohPjC+HddIUSk8fNpQoibuapwEkKsFUKcFEKsEJp8cRUwz5lCiEPGWFsIIX4VQpwTQvzPWMZPCHEsVyzrhBBbhBBnhBCzctV1M9ff/YUQy4QQHYAngNnGedQ1/tsihIgSQuzOtZzPCCGOCSEOCyF2lXK1mNm16wi9erVFCEHjxrW5efM2iYkpZmUSE1NIS7tD48a1EULQq1dbdu48DMDu3Ufo3Vu76NG7d1t27dLev3jxb1q21K4g+vlV4++/k0hKulFsPLt3HyMwsLUxHr9i4vFDCEFgYGt27Tpqmr537zbGeNqwe/fRYuep1xtIT88kK0vPnTsZ6HSuBZaLjr6Cr687Pj5VqVTJhh49mhIeHp0n/mgCA1sA0K1bY6KiziGlJDw8mh49mmJra4OPT1V8fd2Jjr5iNm1U1Dl8fKpSrVoVs/ellGzffpSePZsVugxlFVt8fAoRESfp27e1WV2Ojnam2NLTMxGi0NDyOXnyKj4+bvj4uFGpkjWPPBLAnj1nzMrs2XOG//ynMQBduzbg4MFLSCmpV88Lnc4ZAD8/HenpWWRkZBlj0nrl9HqD8Yt6yYK6n3L3T/dXP79q1Krlla9eOztbbGysAcjIyKSkuQMIDz9GYGAr0z6bmnqbxETzfT0x8QZpaem59tlWpn1z9+5j9Oql5ahXr9bs2nUMgCZNauPiol23a9SoFvHxyab6mjeva/qspCwxd3dj9+7dJCUlFV/wHtH2j6q59o8mhIebX4QJD48mMLA5AF27NuTgwfNIKbG3t6Vp01rY2uYfANWoUQ3Tvlxeyjt3ALt2HaZ373bG7a5OEdvdbRo3roMQgt6927Fr1yEAatf2platamUUW9nsE/7+NfDwcAOgTh1v0tMzjftGaeOzrNyV9/clIQQODtr5IitLT1aWodjzxalTcfj4uOLj40qlStZ061aPPXvOm5XZu/c8jz3WAIAuXR7izz+vIKXEzq6SaRRORkbZXeyyFEJkluu/YvwF5B4+V934XjZnoDGwQwhxEWgHrC/ugTaW3lC0A5YBA6WUTdCGyr4upVwAxALdpZTdjWU/lFK2ApoCXYUQTUtQf6KUsgXwNTCygM/nA/ON876S57OH0XoPGwJ1gI6FxJXXZWOP6W7jsvVHW1mFNW6bAwOBJsBAIUT+MZRGUsq9wHrgA2Mv7DlgIfCWlLKlcRm/MhafCPxHStkMrXF51xISUvDycjO99vBwIyEhOU+ZZDw9c8p4erqRkKAdHJOSUk0NK3d3F5KSUgF46CFfduw4BGhDs/7+O8nsi17h8STnicfVNK/cMeePJ7nIeACOHbvI0KGf8N5733D+/FXT8j73XHeefnoyTzwxAScne9q2bVBIbCl4euY0Ij08XAv4QpxTxsbGGkdHO1JSbpGYeMNsWk9Pl3zLFRZ2pMDG4OHDF6lSxYkaNXQFxlWWsS1YsIE33uiFlVX+s9OMGWt58skZXL6cQL9+7QuNLa/ExFQ8PV1yxepMYuLNPGVu4umpfYm0trbCyakyN27cNiuza9cp6tXzMvsS+sEHq3n66c+xt7ela9eSDXW6n3L3T/fXohw/foFBg6YyePB0Ro161tT4KT6mG8XOL3+O3UhI0HJ8/XoqOp22Pbi7O3P9eip5bdiwj3btAkoUT+FxWl7u7gfa/pp73bmY1l1BZbT9ozIpKXd1B8e/jrZNVTW91rap63nKXMfDo0quMlXybZsFiY1NZOjQabz++hwOHTpTbPn8sZXdPpFt+/Y/8fevga1twbdzFB2fZeWuIr4v6fUGhg6dQe/eo2nTpgGNGtUuMsbExDTTuVOL0Ylr19LMyly7loaHR8751dHRlhs3tFveoqP/ZtiwlbzyyveMGNHN1HAUAkaPXs/rr69mw4ZjxWRKuQt/APWEELWFELbAs2htAgCklClSSp2U0k9K6QdEAk8Ud2uepTcUrYELUsrTxtdBQJdCyg4QQhwE/gQaUbLhl+uM/0cBfgV83h7IHqu0Ms9n+6WUV6SUBuBQIdMXJHulHQX2SSlTpZQJQLoQwq2A8mHGlXsHOAHUKuF8EEI4AR2AUCHEIeBbwNv48R5gmRDiFbQ8FzT9q8aezwNBQRtLOtt/RAhhuto1dOhj3Lx5m6FDZ7B27Q7q169e4Bfm8orH378G69ZNJjh4NP37d2bMmEUA3Lhxi927j7F27STWr5/K7dsZbNnyR7nGCZCZmcWePdF0794432dbtx6mZ8+SXDu5t/bsOUmVKk74+/sW+Pm4cf358cex1KrlSVhY8T2399KFCwksXLiT994zH9I2e/ZAfvhhOJmZev7881K5xpSbJeeuMI0a1WblygnGYZS/kZ5e+h6Af0rbZ82PE1FRZ9iwYR9vvFH8vTkVxRJypzxYdDpXfv55JsHB43nnnWeYOHExaWm3i5+wHJ0/H8tXX/3M6NHPVXQoZiwhdyX9vmRtbUVw8Dh+/nk6J05c5Ny52DKNKyCgGosXD+LLL5/h+++jBIIAKwAA+uNJREFUTCN2PvusH998M5AZMx5n/fqjHDnyVzE1WT4hssr1X1GklFnAcOBXIBpYI6U8LoSYYnz+yl2xqIfZ3C0hRG203rLWUsrrQohlaL2RxUk3/q+n9LlIz/V3aabPns6Qpw5DIXUUNh+Z6/3CltUKSDb2YJqRUv5PCNEW6ANECSFaSimv5SmzEK1HkqSkrbnnx9q1O1m/fg8AAQG1iItLNn2WkJBsGjKSzcPDzaw3MD4+GQ8P7apY1arOJCamoNO5kpiYQpUq2lUqR0d7xo8fkh0L//d/E/H1LbhH7IcfdrN+fQQADRrUzBNPimleOfG4FhCPWzHx5KS5Q4dGzJmzluTkmxw8eAYfn6pUqeIEQLduTTl69AKBgebDBXPmm3MlNSEhxdQTkk2n08p4erqSlaUnLe0Orq4O6HQuZtPGx98wW67IyNPUr+9D1armQ7GysvTs2nWcRYuGF5i7sowtPDyaPXuiiYw8RUZGFmlp6UyZsoaJEweYylpbW9GjR1NWrtxFnz7mN8wXRqdzJj4+p0ciISEVnc4pTxkn4uNT8fBwQa83cPNmOi4u9sbyN5g48UfGjOmDr6/5MF3Q7uvo2LEee/acpVWroq++guXn7l7uryXh51cNB4fKnD8fa3o4RV4//BDO+vWRxphqFDu//DlOxsNDy3GVKs4kJt5Ap3MhMfEGbm4528LZs7F8/PEaPv30FVxdHUu8DNksMXf3G21/zb3ubpjWXd4yOftHOq6u9/wxBPeNtWu38/PP4QAEBPgRH58z3FXbpsyPWx4eVcx6yuLjr+fbNvOyta1k6qVr0KAWvr4eXL4cZ3pgS+Gxlc8+ER9/nTFjvmPChKFUr+5RbPmc+Cwrd5byfcnZ2YEWLeoTGXmiyAcD6nSOxMfnjMpISLiJu7v5sdPd3ZGEhFQ8PJzQ6w2kpWXg4mL+VbRWrarY21fiwoVr+Pt7mc7RVao40LFjHU6ejKNp04IvhCp3R0q5CdiU572JhZTtVpI6Lb1HUQ/4CSGy73IeAuw0/p2KNt4WwAVIA1KEEF5Ar3s0/0ign/HvZ0s4Te64ylKcECLAeHPq0wXNX0p5A7gghHgGwHgfZTPj33WllPuMG1AC5uOai9W/f1eCg7Wbo7t0acbmzfuQUnLs2AUcHe3z3aOn07ni6GjHsWMXkFKyefM+unTRerg6dWrCpk3az7ls2rSPzp2191NTb5GZqV1BWb9+L82bP4Sjo32B8fTr19n0kJkuXZqwZcsfxngu4uhoV0Q8F5FSsmXLH3Tu3NgYT2M2bdpvjGe/6f1r124gpdZePnHiElIacHV1xMurCsePX+LOnQyklBw4cBo/v4LvaWjQwJcrVxKJjU0iMzOLsLAjdOpkPhyuU6cGbNmiPQxnx45jtGih3TfRqVMAYWFHyMjIIjY2iStXEgkIyHky5Nath+nRI/+w06ioc9Ss6WE29Ku8Yvvf//7DunVjCA0dxeTJz9KiRR0mThyAlJIrV7TrElJK9uyJzvfAlqJj9eavv65z9WoymZl6tm2LpkMH84chdOhQj19//X/27jssimt94Pj30KSjUkSwYAV7TVTs0ZvYbsqNvcVfTHJTTGLUJDbUxN6j1zQLKqgxwcRobElERVEwsYtii2JQlKLSpe2e3x+7IEtHBdZ4Ps/DI8ucmXn3dWZ2zpyyuu4tQUEXaNWqFkIIkpPTmDhxC2++2ZVmzR7k7/79DO7c0XVf1Wi0hIb+Ra1aVSkJY8/d4zxfCxMVFZczAcutW3e4fj2a6tUdCy3/6qudWL9+AuvXT9Cfs8dyzllbW8sCKtr22NhUynXOHqNTp+xztgm7d+ta8XfvfnAu3759j8mT1zJt2lBq1XIpMv7CGGPunjS68+MuUVH39OfHWTp2NOye37GjF3v2nAIgKOg8rVvXydcy/DTp3797zkQpXbu2ZNeuUP1xdxVb28KOOyvCwnRjO3ftCqVLl8LHpIOuy3b2RCM3b8Zy40YMbm7FX4fL45xISkpl/Piveffdl2jRol6xMRnGZ1y5q8j7pXv3kkhK0nXhTkvL4M8/LxQ4JjQ3T89q3LyZwK1biWRmajhw4DLe3oYPTL296/Dbb7pxxgcPXqFlyxoIIbh1KzEnL9HRiURG3sPV1Z779zNJTdXNSXn/fibHj0fi4fHkX+OMqUWxrBh7i2Ia8H/ouk6aoet/+41+2UpgjxAiSkrZXQhxEriAbmrYw49p/2OBDUKIKcAeoCSd6g3iekxxFGQisANdJe8YkP0IfTOwSj+xTn9gGPC1EGIqYK5ffhrdhDcN0M2aEKj/20Px9m7CkSPnGDBgBpUqWTB16vCcZSNHzsHPbzIAH388iFmz/ElPz6R9+8Z06NBEX+Z5pkxZwy+/HMHVtSqzZo0GdIOzZ870RwjdgPLJk4fn33mB8TQmJOQ8AwbM1E+1PzRn2WuvLWD9et1U+BMmDDD4eowOHXS9lUeM6MnUqWvZsSNUH88oAPbvP8XWrYcxNTWhUiVzPv98FEIImjTxoHv3FowatRBTUxMaNqzBSy95FxibmZkpH330IuPHr9VPE9+GOnWqsXr173h51aBTp0b07duWWbMCGDx4Efb21syYoXtGUadONZ57rhkjRnyBqakJ48a9mNP3//79DI4du8LHH7+Sb5979xY8brG8YiuIlJLZswNITU1HSkn9+tUZP76gr/spmKmpCR988C8++eQH/fTdzahTxxlf30N4errSsWMD+vZtzpw5Oxg27Fvs7a3w8dH1vNi69QRRUfH4+R3Bz083U9vChQOREqZM+ZHMTA1araRVq1q8+GKrEsXzJOXuUc/XAwdOsWRJAPHxyYwf/zUNG9bgiy/GcPr0X/j7/4aZmSlCmDBhwiCDlr2idOjQiJCQcAYOnIOlpTmTJz/oZvbaa4tYv143hHz8+P45X4/Rvr0XHTroKuMjRvTAx8ePHTuO4upahZkzRwKwdu1vJCamsmjRj4DuuPH1HQfA9On+nDx5hfj4FF5++TNGj36Bf//b8CtWnoTcPYxNmzbRrVs3nJyciIyMZPr06fj6+pbZ/szMTBk7ti8TJvih1Wrp06c1deq4sGZNIJ6e7nTq5EXfvq2ZPfsnhgz5Ajs7K2bMGJCz/sCBS0hJSScrS0Nw8AUWLx6Jh4cLX3/9K3v3niUtLZNXX11E376tef3158rsfUD55w7A27spR46cpX//qVhaWjB16ms5y0aMmIm/vw8AH388hJkz15OenkGHDk3p0EH3wOTAgZMsXryZ+Phkxo1bQcOGNVm27ENOnrzMqlXb9ced4JNPhpa61b2szoktW4K4cSMWX99d+PrqGki++OL9fD1mnrTclff90p07iXz+ue68k1Ly3HOt6dSp6K91MTU14f33uzBx4ja0WkmvXo3x8HBk3bqjNGzogrd3HXr3bsy8eb8zcqQ/dnaVmDJFN4QjLCyKzZtPYGZmghCCDz7ohoODFVFRCcyYoft/1Ggkzz3XkGef/Wf0mPinE9ktJEp+Qghr4L6UUgohBgNDpJQlvyP7B8nb9dSY6LplGy+NJqX4QkqBsrJKPuFBeTMzK3l3wvJmzLEBaLXpxReqICYmJf8uz/Lm6Pivig6hSLdvFzzVvzFwdS1pp6CKcfduvonSjYYxf8bq2hCMlzHnLiUlvPhCFahmzfeNvkvB8uW7yvXe+IMP+pR7Toz7DKt4bYAVQtf/JR54vWLDURRFURRFURRFKXuqolgEKeUhoPg+e4qiKIqiKIqiPDVK8N2GTzxjn8xGURRFURRFURRFKWeqoqgoiqIoiqIoiqIYUF1PFUVRFEVRFEVRSqGivrKiPKkWRUVRFEVRFEVRFMWAalFUFEVRFEVRFEUpBdWiqCiKoiiKoiiKojx1VIuioiiKoiiKoihKKagWRUVRFEVRFEVRFOWpo1oUFUVRFEVRFEVRSkGIzIoOocypiqJSIkIY76GSkRFd0SEUycTEsqJDKFRWVkJFh1Aka+uGFR1CoVJTL1V0CEoZ0GrTKjqEQt2+vbmiQyiSq+vgig6hUMaeO2Om0aRUdAiFMjNzqOgQnliVKrlVdAjKE8B47/4VRVEURVEURVGMkBqjqCiKoiiKoiiKojx1VIuioiiKoiiKoihKKagWRUVRFEVRFEVRFOWpo1oUFUVRFEVRFEVRSuFpmPVUtSgqiqIoiqIoiqIoBlSLoqIoiqIoiqIoSimoMYqKoiiKoiiKoijKU0dVFBVFURRFURRFURQDquupoiiKoiiKoihKKaiup4qiKIqiKIqiKMpT5x/ZoiiEcAQC9S9dAQ0Qq3/9rJQyI1fZscBKKWVqMds8AEyQUh4rYQwvAo2llPOKKNNNv81+BSwrUVwliMMD2CGlbFrU/h6FlJIlS74nJCSMSpUs8PEZhZdXrXzlLly4zsyZ60hPz6RDh6aMGzcIIQSBgcdZvfoXIiJu4+s7kUaNPAA4d+4a8+Zt0O8D3nijH926tSpVbEePXuF///sVrVZL376tGDask8HyjIws5sz5mUuXbmFvb8X06f2pXr0yCQmpTJsWwMWLUfTq1ZKxY3sDkJqazvvvr8tZPzY2kX/9qznvv/9CKWK6xLJlO9BqtfTr9wzDh3fNF9Ps2QFcvHgTe3trPvtsCNWrVwHA3/8AO3cew8TEhA8/7Ee7dg35++9Ypk/fnLN+VNRdRo/uycCBHdm//yy+voFcvx7LypXv4OVVo8Rx/vHHVVasCESj0dK3bwuGDm2fL865c3dy6dJtfe5ewtXVgWPHrrFyZRBZWRrMzEx5++3utG5dG4BPPvmBO3eS0Wi0NG9ekw8//Bempo/+vEp3DH7HkSNnsbS0wMfndby8aucrFx4ewcyZvqSnZ+Lt3Yxx44YghGD58h8IDj6NubkZ7u7O+Pi8jp2d9UPHY2y5K89jDmDLliNs3RqKiYkJHTp48u67vY0mvunTv+Pvv+MASE6+j62tFWvXvm8UsT1M7gxjvczy5bvQaiV9+7Zm+PAuBcT6E5cuRWFvb8WMGQOpXr2K/nq3mQsXdNe7jz568BGxatVe9uw5RXJyGr/+OrXEsTysNWvW0K9fP2JiYmjWrFmZ7w+MP29l9Rmb7fbtuwwZMoM33ujHsGHPFxtPaOhFli3bhlYr6dfvWUaM6G6wPCMji1mzNuecE59/Pozq1asC4O+/jx07/sTERDB27Eu0a+dZ5Dbnzg3gwoUbgKRmTWcmTx6ItXWlJzZ3eWNbujSAI0fO6T+3RuDpWVBsfzNzpj/p6Rl4ezfho48G6GM7wZo1O4mIiGbNmo9p1Ej3WXHuXATz52/S7wNGj+5Dt24ti43ncV/rAJKS7jN//k9cuxaNEIKJE1+ladNaj3RvYkxUi+ITSkp5R0rZUkrZEvgGWJr9OnclUW8s8PB3hIXHsL2oSmIJjKUM4ioLISFhREbGEBAwk0mThrNgwcYCyy1YsIlJk0YQEDCTyMgYQkLOAVC3rhvz5r1Ny5YNDMrXq+fO2rWT8ff34YsvPmD+/I1kZWlKHJdGo+WLL3azYMFQ1q9/l8DAc0RExBqU2bnzJHZ2Vmza9D4DBrTn22/3AmBhYcbo0d15551/GZS3tq7EmjX/zfmpVq0yXbp4lSqmJUu2s2jRKPz9x7J372muXYvOE9Mx7Oys2Lx5AgMHduSbb/YAcO1aNIGBZ/DzG8uiRaNYsmQ7Go2WWrWcWbv2fdaufZ/Vq9/D0tKcLl0aA1CnTjVmzx5GixYeJY4xO85ly35n3rwBrFv3BoGB54mIiDMos2vXGezsLNm48b8MGNCWb789AICDgzVz5ryKr+9oJk3qy9y5O3LWmT79JdaseZ21a0cTH59KUNCFUsVVmCNHzhIZGc2WLXOYOHEkCxb4F1huwYINTJr0Glu2zCEyMpqQkDAAnn22MZs2fc7GjZ9Rq1Y11q/f+dCxGFvuyvuYO3HiL4KDw1m79gP8/ccyZEhno4rvs8+G5Czr2rVpzt+NIbbS5i5vrEuX7mDhwhH4+Y0hMPAsERExeWI9gZ2dJd99N5aBA7355pvfgezrXQ/efTf/Ay9vb0++/fa/JY7jUa1bt45evXqV2/6ehLyV1WdstmXLAujQoUmJYtGdE1tZtGg0GzaMZ+/eU/nOiR07/sDOzorvv/+UQYM68/XXuwDdObF372n8/cezePEbLF68FY1GW+Q2P/jg36xf/xHr14+jWrXK/PjjkRLFmc2Ycpc/tnNERsYSEDCDiROHsmDB5gLLLViwmUmThhIQMIPIyFhCQ88DUK+eG3PnvkXLlvUNyter54av76f4+U1m6dL3WLDgu2LvncriWgewfPkO2rVryMaN41i79n1q13YGHv7eRCl//8iKYkGEED2EECeFEGeFEL5CiEpCiA8AN2C/EGK/vtzXQohjQohzQojPSrDdCCHEZ0KIE/pte+n/PkoIsUL/ez0hRKh++SwhRHKuTdgKIbYIIS4IITYKnXxx5dnnM0KII0KI00KIP4QQdkIIDyHEIX0cJ4QQ3sXE3VUIcUr/c1IIYVfiZOZx8OBp+vRpjxCCpk3rkpx8n7i4BIMycXEJpKTcp2nTuggh6NOnPQcPngKgTp3q1K7tmm+7lpYWmJmZApCRUfovNQ0Pv4m7exXc3Kpgbm7Kc881ITj4okGZw4cv8sILzQHo2rUxJ05cQ0qJlZUFzZvXwsKi8Eb3yMg73LuXQvPm+Z8AFh7TDdzdHXFzq4q5uRk9ejQnODjcoMyhQ+H06tUagG7dmnL8+F9IKQkODqdHj+ZYWJjh5lYVd3dHwsNvGKx7/PhfuLlVxdVV95TPw8OFWrWcSxxftgsXbuHmVhk3t8r63DXi8OHLBmUOH77MCy80BaBrVy9OnLiOlJIGDarh5GSn378T6elZZGTonrrZ2OieBGs0Wv0Hlyh1bAU5ePAUvXt7I4SgWbN6JCWlEhcXb1AmLi6elJT7NGtWDyEEvXt7ExR0EoD27ZvmHGtNm9YjJubeQ8dibLkr72Pu55+PMnx415xzp0oVW6OKL5uUkv37z9KzZwujia20ucsfa9VcsTYjONjwYUJwcDi9erUEsq93V3Nd72oXeL1r0qRmzjFZHg4dOsTdu3fLbX9PQt7K6jMWICjoFG5ujtSp41aiWMLDI6lRwwl3d0fMzc3o2bMFwcHnDMoEB5+nd++2AHTr1ozjx6/oz4lz9OzZIuecqFHDifDwyCK3aWNjCejO1/T0TEQpPzKMKXf5YztD797t9LHVKSK2NJo2raP/3GpHUNBpADw8XKldu1q+7ea/dyo+aWVxrUtOTuP06Qj69dMdC+bmZtjZWeljf7h7E2MjRGa5/lSEp6WiaAmsAwZJKZuh63L7jpRyORAFdJdSZvedmCKlbAs0B7oKIZqXYPtxUsrWwNfAhAKWLwOW6fd9I8+yVuhaDxsDdYGOhcQFgBDCAvge+FBK2QLoCdwHYoB/6eMYBCwvJuYJwHv6VtfO+m08lNjYeFxcqua8dnGpTGzsvTxl7uHsXCVXmSrExsYXu+2wsGsMGTKDYcM+59NPh+Vc/EoiLi4JFxeHnNfOzvbExSUVWsbMzAQbG0sSEkqWisDAMJ57rjGiFJ9csbEJeWJyIC4uMU9MCbliMtXHlEpcXKLBui4u9sTGGn6oBAaeKfLGt6R0ebHPFacdcXHJecok4+KiuxEyNTXB1rYSiYmGuTt48CINGlQzuJH6+OPveeWV/2FlZUHXrp6PHCvojq9q1XIfg/mPL91xmvcYzF8h/OWXYDp0ePgub8aWu/I+5iIj73D6dARvvfUVY8aszFc5quj4sp0+HUGVKrbUrOlkNLGVNneGceS/3sXG5o01KU+slUhIeKTRDU+8JyFvZfUZm5qahr//HkaPLvlolILOibz5yl0m9zkRG5uIi0vlPOsmFLvNOXN+4MUXZ3L9egz9+3cscay6WIwnd/ljS6Batco5r52dKxfyufWgjC5+w+tIQc6du8bQoTMZPnw2n3wyuNh7p7K41t26dZfKlW2YM+dHXn/9f8yb9xP37+ft1KcYu6elomgKXJNSXtK/Xg90KaTsQCHECeAk0ARdBa44P+n/PQ54FLC8AxCg/31TnmV/SClvSCm1wKlC1s/NE7glpfwTQEqZKKXMAsyBVUKIs/p9FRf3YWCJvvWysn4bBoQQb+lbV4+tW/dLMZsrG02b1uG772bg6zsJP789pKdXzBOVguzbd44ePZpWdBg5MjOzOHw4nO7djSOma9diWbkyiHHjDLtlLVw4iB9/HENmpoaTJ69XUHQFW7t2B6amJvTq1b74wmXoScldQcecRqMhMTGVb799h3ff7c306d8hpTSa+LLt3Xuanj1L8hywbBh77pR/vtWrdzB4cE+srS0rOpQiTZ48kJ9/nkrt2tUIDDxd0eEAxp+7Jk3qsGmTj74L6m8Vcu+k0Wi5dCmKl19uh6/v+1hZmbNxY1C5x1GWhMgq15+K8I+czOZhCSHqoGtpe0ZKeU8IsQ5da2Rx0vX/aih9TtNz/f4w62f7CIgGWqB7AJBWVGEp5TwhxE6gD3BYCPGClPJCnjIrgZUA9+4dMLhb2bJlP9u2BQPQqJEHMTEPugrFxMQbPJ0DcHY2bL2JibmHs3PlEr+5OnWqY2VViatXb+YbTF4YJyc7YmIePHmLjU3M1xUou4yLiz1ZWVpSUtJwcLAqdttXrtxGo9Hi6Vm6LifOzg55YkrAycneoIyTk4M+JgeysjT6mKxxcrI3WDcmJhFn5wdP8UJDL9GwoRtVqz56dyddXh48TYyNTcLJyTZPGVtiYpJwdrZHo9GSnJyOvb2Vvnwi06ZtZeLEvri7Gx4LoBvb07FjAw4fvkLbtnUeKsaAgH1s23YQgMaNPYiOzn0M5j++nJ0rG3Qp1ZV5ENuOHcEEB5/myy8nlKqVOC9jy115H3POzg507doEIQSNG9dECEF8fEqh3Sgr4pzIytJw8OA5Vq8e80TnzjCO/Nc7Z+e8sdrliTUdB4cnYih8mTHWvJXHZ+y5c9fYt+8EK1b8RHJyKiYmAgsLcwYM6F7oOgWdE3nzlV3GxaWywTnh7GxPTEx8nnUd9PEWvU1TUxN69mzBpk0H6Nv3mSLfl7HmThdbENu3H9bHVpvo6PicZbGx8YV8bj0oo4vfgZLy8HDF2roSV69G5Ux2U5CyuNbpfuxp0qQmoOuuumHDwRLHrhiHp6VFUQN4CCGyR/yOALIfayQB2Z/U9kAKkCCEqAaUfLq5ooUCr+p/H1zCdXLHldtFoLoQ4hkA/fhEM8ABXUujFt37K7KfgRCinpTyrJRyPvAnUPIZWYD+/bvj7++Dv78PXbu2ZNeuUKSUhIVdxdbWCicnwwuZk5MDNjZWhIXpxnbs2hVKly5Fd5GMiorLGYB969Ydrl+/TfXqhXcTy8vLy50bN+5y69Y9MjM17Nt3jo4dGxqU6djRk19/PQNAUNB5WrWqU6JKQmBg2EO1JupiiiMq6i6ZmVkEBp6hU6dGBmU6dfJiz54TABw4EEbr1rpxE506NSIw8AwZGVlERd3lxo04GjV6MFPY3r2n6dHj0bud6uKszs2b97h1K16fu3C8vQ0HzHt7N+DXX3WTwQQFXaBVq1oIIUhOTmPixC28+WZXmjV7EN/9+xncuaPrgqnRaAkN/YtatarysAYMeI4NG2awYcMMunRpxe7dR5BScvbsX9jaWuPkVNmgvJNTZWxsrDh7VjeuYvfuI3Tp0hKAkJCz+PvvYdGiD7C0LPmMegUxttyV9zHXubNuDBfA33/rzuHKlW2MJj7QjQ2sVcvZoLuUMcRW2tzlj/UuUVH39LGepWNHw8t6x45e7NlzCtBd71q3Ltn17p/MWPNWHp+x3377MT//PIeff57DoEE9eO213sVWdLy8ahAZ+eCc2Lv3NB07GnZg6tixMbt36yaIP3DgLK1b10cIQceOjdm793TOOREZGUejRjUL3aaUkhs3dBOB6cbCnadWLZcnNne62Lri5zcZP7/JdOnSgt27j+pju4aNTWGxWRIWdk3/uXWULl2K7gmR/94pmurVHYtcpyyudY6Odri4OPD337pJBI8f/wsPj+L//54kT0OLovind2sRQswAktF1JV2ErsXuT3RjFNOFEO8DY4AoKWV3fSuiNxAJJADbpZTrCvt6DCFEBNBWShknhGgLLJJSdhNCjNL/fYwQogGwAbAC9gDDpJTueb+uQj/5zTH9/gziyrPPZ4D/6bd3H904xerAj4DU7+M9KaVtYV+PIYT4H9Ad0ALngFFSytytmwbytijmJqVk0aLvCA3VTfE8deprOa1+I0bMxN/fB8j+aoL1pKdn0KFDU8aPH4wQggMHTrJ48Wbi45OxtbWiYcOaLFv2Ibt3h+LntwczM1OEEIwe3Y+uXVvm2396+s3CQiM09LL+6zEkffq0ZMSIzqxZsx8vLzc6dvQkPT2L2bO3cuXKbezsrJg+/VXc3HRPGwcNWkZKSjpZWRpsbS1ZtGg4Hh66wdeDBy9n/vyh1K5dfMXVxMSwUTok5CLLl+/QT8XehpEju7N69e94edWgU6dGpKdnMmtWAJcvR2Fvb82MGYNxc9NVCvz89rNz53FMTU344IO+tG+vG6d2/34G/fvP5/vvP8bW9sH+Dh48xxdf/EJ8fAq2tpbUr+/GkiX/l7M8K6vwsQ6hoX/x5ZeBaLWS3r2bMXy4N76+h/D0dKVjxwb6rxbZweXL0djbW+Hj8yJubpXx9z/Cpk2hBq1hCxcOREqYPHkLmZkatFpJq1a1eO+9HkV+xYO1dcNCl+UmpWThwo2EhoblfD1G9jE4fLiuMgm6Y/Dzz9fop0BvxoQJQxFC8Oqrk8jIyMTBQddy07RpXSZOHFnkPlNTLxW6rKJzZ2ZmeLNRnsdcZmYWc+f+xJUrUZiZmfHee71p06Zekbksz/gAZs/eQpMmNXn55XZFxmVsuStghECeWC/xv//tRqvV0qdPa0aO7MqaNYF4errTqZMX6emZzJ79E5cv38LOzooZMwbkxDpw4BKD693ixSPx8HDh669/Ze/es8TFJeHkZEffvq15/fXnCty/q2tJn4MWbtOmTXTr1g0nJyeio6OZPn06vr6+j7zd27cLnlESKj5vABYW+SclyVZWn7G5rVr1C9bWlQr8ioe8nxMhIeEsW/aL/munnuG113qwevWv+nOiCenpmcycuTnXOTEUd3ddRWX9+kB27vxTf068SIcOXoVuU6vV8t57X5OSko6Ukvr1qzNhwn9yJriB/Nc6Y8tdUeesLrYfOHr0PJUqWTB16vCcVr+RI+fg5zdZH9t1Zs3yJz09k/btGzN+/EB9bKdYsiQgV2w1+OKLMezefRR//9/0904mvP56b7p2zV/xzf//+vivdZcvRzF//lYyMzW4uVVh8uT+2NlZFXtvAuDi8qrRP8Vat25yuVaiRo2aU+45+cdXFI2BEMIauC+llEKIwcAQKeVLFR1XaRRVUaxoRVUUjUHeiqIxKaqiaAxKWlGsCEVVFCtacTdPypOpuIpiRXscFcWyUlRF0RgUVVGsaMb8OWHs1zpjPmeN+f8VnoyK4vr1n5TrvfFrry0o95yoMYrlow2wQuj6qsQDr1dsOIqiKIqiKIqiKIVTFcVyIKU8hG6SGUVRFEVRFEVRnnAV9d2G5elpmcxGURRFURRFURRFKSHVoqgoiqIoiqIoilIKFTUTaXlSLYqKoiiKoiiKoiiKAVVRVBRFURRFURRFUQyorqeKoiiKoiiKoiiloLqeKoqiKIqiKIqiKE8d1aKoKIqiKIqiKIpSCqpFUVEURVEURVEURXnqqBZFRVEURVEURVGUUhAis6JDKHOqoqiUiJTG27xubu5Y0SEUSaNJqegQCmVm5lDRIRQpNfVSRYdQKGPOnTHHBqDVpld0CIUyMalU0SEUytHxXxUdQpFu395c0SEUytV1cEWHUKS7d/dXdAiFMjW1qegQlDKQnh5V0SEoTwBVUVQURVEURVEURSkFNUZRURRFURRFURRFeeqoFkVFURRFURRFUZRSUC2KiqIoiqIoiqIoylNHtSgqiqIoiqIoiqKUgmpRVBRFURRFURRFUZ46qkVRURRFURRFURSlFJ6G71FULYqKoiiKoiiKoiiKAdWiqCiKoiiKoiiKUgpqjKKiKIqiKIqiKIry1FEVRUVRFEVRFEVRFMXAE9H1VAjhCATqX7oCGiBW//pZKWVGrrJjgZVSytRitnkAmCClPFbCGF4EGksp5xVRppt+m/0KWFaiuHKVHwW0lVKOKUn5iiSlZOnSAI4cOYelpQU+PiPw9KyVr9yFC38zc6Y/6ekZeHs34aOPBiCEICEhBR8fX27dukP16o7MmjUae3trEhNTmT17AzdvxmJhYc6UKcOpV8+thPH8REjIeSwtzZk6dRienjULiCeSWbM2kp6eSYcOjfnoo/8ghCAxMQUfn3XcunWX6tWrMnPm/2Fvb82JE5f59NPVuLk5AtC1a3Nef70XAJs37+eXX0IBqFfPjSlThlKpknmB8R09eolly3ag1Wrp1+8Zhg/varA8IyOL2bMDuHjxJvb21nz22RCqV68CgL//AXbuPIaJiQkfftiPdu0a8vffsUyfvjln/aiou4we3ZOBAzsyffp3/P13HADJyfextbVi7dr3C83d444tm0aj5c03v8TJyZ4FC14DYN68H7lw4SZSQs2ajkye3B9r60qFxpbXH39cZcWKQDQaLX37tmDo0Pb5Yp07dyeXLt3G3t6K6dNfwtXVgWPHrrFyZRBZWRrMzEx5++3utG5dG4BPPvmBO3eS0Wi0NG9ekw8//BempiV7nvak5O5Rz9fAwBOsWbOTiIho1qz5mEaNdLk7dy6C+fM36fcBo0f3oVu3liWO6YsvthISEo6lpQVTpgzB07NGATFFMnv2d/pzthFjx76S65z15/btu7i6VmXmzJHY21vz66/H2bhxH1JKrK0tmTDhVRo0cAdgzpzNHD58nipVbNmw4ZMnNncPY82aNfTr14+YmBiaNWtWZvvJ7ejRyyxfvgutVtK3b2uGD+9isFx3fvzEpUtR2NtbMWPGQKpXr0JCQirTpm3mwoUoevVqyUcfPfh4XbVqL3v2nCI5OY1ff51aLu+jInInpWTJku8JCQmjUiULfHxG4eVV0HF3nZkz1+nPj6aMGzdIf9wdZ/XqX4iIuI2v70QaNfIAICoqjiFDZlCrVjUAmjaty6efDit1bGVxTvzxRzhffbWNzEwN5uamjBnzCm3bepYyc8aXu/K+X0pPz+Sdd5aSmZmFRqOhe/dWvPlmvlvUfP744zpffXUIrVbSu3djhgxpY7A8I0PD/Pm/c/lyLPb2lkyd+gKurvZcuBDN0qX7c97ryJHP0qlTPQCGDVuPlZU5pqYmmJoKvvpqULFxGDvV9dRISCnvSClbSilbAt8AS7Nf564k6o0FrMsghu1FVRJLYCxlEFdhhBCm5bWvkJBzREbGEhAwg4kTh7JgweYCyy1YsJlJk4YSEDCDyMhYQkPPA+Dv/xtt23oSEDCDtm098ff/DYD16/fQsKE7GzZMYdq0kSxdGlDCeM5z40YsP/wwlU8/HczChQWvt3DhD0ycOJgffpjKjRuxhIaG6+PZS5s2DfnhBx/atGmIv//enHVatKjL+vWfsH79JzmVxNjYeAICDuLrO56NGyeh1WrZu/dEgfvUaLQsWbKdRYtG4e8/lr17T3PtWrRBmZ07j2FnZ8XmzRMYOLAj33yzB4Br16IJDDyDn99YFi0axZIl29FotNSq5czate+zdu37rF79HpaW5nTp0hiAzz4bkrOsa9emOX8vr9iyBQQcoXZtZ4Ntvf9+X9at+4D16z+gWrXK/PRTaKGxFRTrsmW/M2/eANate4PAwPNERMQZlNm16wx2dpZs3PhfBgxoy7ffHgDAwcGaOXNexdd3NJMm9WXu3B0560yf/hJr1rzO2rWjiY9PJSjoQonjeVJy96jna716bsyd+xYtW9Y3KF+vnhu+vp/i5zeZpUvfY8GC78jK0pQwpnBu3Ijj++8n88knA1i0aEuB5RYt2sKnnw7k++8nc+NGHKGhuv8ff/99tG3bgO+/n0zbtg3YsEH3XNHNrSorVryHv/8njBr1LxYseHAt6NPnGZYseatE8T2I0/hy9zDWrVtHr169ymz7eWk0WpYu3cHChSPw8xtDYOBZIiJiDMrs3HkCOztLvvtuLAMHevPNN78DYGFhxujRPXj33Rfybdfb25Nvv/1vubyHbOWdO4CQkDAiI2MICJjJpEnDWbBgY4HlFizYxKRJIwgImElkZAwhIecAqFvXjXnz3qZlywb51nF3d8bf3wd/f59SVxJ1sZXNOeHgYMvChW+zceMUfHxG8tln60sdmy4+48pded8vWViYsWLFB/j7T8bPbzKhoecJC7tWZIwajZb//S+IOXP+zZo1Q9m//xLXr981KLN793ns7Crh5zeCV19twapVRwDw8KjKV18N5NtvBzN37ot88cUBg8+zxYtf4dtvB/8jKolPiyeiolgQIUQPIcRJIcRZIYSvEKKSEOIDwA3YL4TYry/3tRDimBDinBDisxJsN0II8ZkQ4oR+2176v48SQqzQ/15PCBGqXz5LCJGcaxO2QogtQogLQoiNQidfXHn2+YwQ4ogQ4rQQ4g8hhJ1+kZsQYo8Q4rIQYkGu8gW+J33s84UQJ4ABQog++jiOCyGWCyF26MvZ6HP2hz6HL5Uy/QYOHjxD797tEELQtGkdkpPvExeXYFAmLi6BlJQ0mjatgxCC3r3bERR0GoBDh87Qp087APr0acfBg7q/R0Tcpk0b3RNEDw9Xbt++y927icXGc+hQGL16PaOPx6OYeDwQQtCr1zMcPHg2Z/0+fZ7Vx/Mshw6dLXafGo2W9PRMsrI0pKVl4OTkUGC58PAbuLs74uZWFXNzM3r0aE5wcHie+MPp1as1AN26NeX48b+QUhIcHE6PHs2xsDDDza0q7u6OhIffMFj3+PG/cHOriqtrFYO/SynZv/8sPXu2KPQ9lFVsMTEJhIRcoF+/Zwy2ZWNjmRNbenomQhQaWj4XLtzCza0ybm6VMTc35bnnGnH48GWDMocPX+aFF5oC0LWrFydOXEdKSYMG1XBy0p1iHh5OpKdnkZGRpY9J1yqn0Wj1N+olC+pJyt2jnq8eHq7Url0t33YtLS0wM9M9n8rIyKSkuQMIDg6jV6+2OedsUtJ94uIMz/W4uERSUtJznbNtc87NQ4fC6N1bl6PevZ/h4MEwAJo1q4O9ve75XJMmtYmJic/ZXsuW9XKWlZQx5u5hHDp0iLt37xZf8DHRnR9Vc50fzQgONnwIExwcTq9eLQHo2rUxJ05cRUqJlZUFzZvXxsIifweoJk1q5pzL5aW8cwdw8OBp+vRprz/u6hZx3N2nadO6CCHo06c9Bw+eAqBOnerUru1aRrGVzTnh6VkTZ+fKANStW5309Ez9uVHa+Iwrd+V9vySEwNpa93mRlaUhK0tb7OfFxYvRuLk54ObmgLm5Kd26NeDw4asGZY4cucrzz3sB0KVLfU6evIGUEktL85xeOBkZZfewy1gIkVWuPxXhSa0oWgLrgEFSymboutC+I6VcDkQB3aWU3fVlp0gp2wLNga5CiOYl2H6clLI18DUwoYDly4Bl+n3fyLOsFbrWw8ZAXaBjIXEBIISwAL4HPpRStgB6Avf1i1sCg4BmwCAhRHb/yaLe0x197D8D3wK9pZRtgNxNElOAfVLKZ4HuwEIhhE2xWSlEbGwC1apVznnt7FyZ2Nj4PGXicXF5UMbFpTKxsbqL4927STkVK0dHe+7eTQKgfn13Dhw4Bei6Zt2+fdfgRq/weOLzxOOQs6/cMeePJ77IeADCwiIYOXI+48Z9w9Wrt3Le75Ah3XnllRm8+KIPtrZWtGvnVUhsCbi4PKhEOjs7FHBD/KCMmZkpNjaWJCSkEheXaLCui4t9vvcVGHimwMrg6dMRVKliS82aTgXGVZaxLV++g3ff7Y2JSf5PpzlztvDSS3P4++9YXn21Q6Gx5RUXl4SLi32uWO2Ii0vOUyYZFxfdTaSpqQm2tpVITLxvUObgwYs0aFDN4Cb044+/55VX/oeVlQVdu5asq9OTlLtHPV+Lcu7cNYYOncnw4bP55JPBOZWf4mNKLHZ/+XNcmdhYXY7v3UvCyUl3PDg62nHvXhJ57dhxlPbtG5UonsLjNL7cPQl052vu/zv7nP+7gsrozo9KJCSUaKTGP57umKqa81p3TN3LU+Yezs5VcpWpku/YLEhUVBwjR87inXcWcerU5WLL54+t7M6JbPv3n8TTsyYWFgUP5yg6PuPKXUXcL2k0WkaOnEOfPp/y7LNeNGlSp8gY4+JScj47dTHacudOikGZO3dScHZ+8PlqY2NBYmIaAOHhtxk9ehNvvvkdY8d2y6k4CgGffrqdd975nh07worJlGIsntSKoilwTUp5Sf96PdClkLID9S1sJ4Em6CpwxflJ/+9xwKOA5R2A7D5Mm/Is+0NKeUNKqQVOFbJ+bp7ALSnlnwBSykQpZfZjg0ApZYKUMg04D9QuwXv6Xv+vF3BVSpndx+C7XGWeByYKIU4BB9BVvPN1khdCvKVvuTy2fv3OYt7G4yGEyHnaNXLk8yQn32fkyDls2XKAhg1rFHjDXF7xeHrW5KefZuDn9yn9+3dm4sTVACQmpnLoUBhbtkxn+/aZ3L+fwZ49f5ZrnACZmVkcPhxO9+5N8y3bu/c0PXuW5BnJ43X48AWqVLHF09O9wOWTJ/dn69ZJ1K7tQmBg8S23j9O1a7GsXBnEuHGGXdoWLhzEjz+OITNTw8mT18s1ptyMOXeFadKkDps2+ei7Uf5Genr5fxmx7pw1vE4cP36ZHTuO8u67xY/NqSjGkDvl6eLk5MC2bXPx85vKhx8OYNq0NaSk3C9+xXJ09WoUX321jU8/HVLRoRgwhtyV9H7J1NQEP7/JbNs2m/PnI/jrr6gyjatRI1fWrBnKl18O4Lvvjuf02Pnii1f55ptBzJnzb7ZvP8uZMzfLNI7yIERmuf5UhCdiMpuHJYSog65F8Bkp5T0hxDp0laLipOv/1VD6HKXn+v1h1i9yWyV4T4aPfQomgFellBeLKiSlXAmsBLh7d6/MvWzLliC2bz8MQKNGtYmOjs9ZFhsbn9NlJJuzc2WD1sCYmHicnXVPxapWtSMuLgEnJwfi4hKoUkX3lMrGxoqpU0dkx8J//jMNd/eCW8R+/PEQ27eHAODlVStPPAk5+3oQj0MB8VQuJp4Hafb2bsKiRVuIj0/mxInLuLlVpUoVWwC6dWvO2bPX6NXLsLvgg/0+eJIaG5uQ0xKSzclJV8bFxYGsLA0pKWk4OFjj5GRvsG5MTKLB+woNvUTDhm5UrWrYFSsrS8PBg+dYvbroeZHKIrbg4HAOHw4nNPQiGRlZpKSk8/nnPzBt2sCcsqamJvTo0ZxNmw7St6/hgPnCODnZERPzoEUiNjYJJyfbPGVsiYlJwtnZHo1GS3JyOvb2VvryiUybtpWJE/vi7m7YTRd04zo6dmzA4cNXaNu26KevYPy5e5zna0l4eLhibV2Jq1ejcianyOvHH4PZvj1UH1PNYveXP8fxODvrclylih1xcYk4OdkTF5dI5coPjoUrV6KYN+8HFi9+EweH0necMMbcPWl052vu/7vEnP+7vGUenB/pODiU27B+o7Nly362bQsGoFEjD2JiHnR31R1ThtctZ+cqBi1lMTH38h2beVlYmOe00nl51cbd3Zm//47OmbCl8NjK55yIibnHxImr8PEZSY0azsWWfxCfceXOWO6X7Oysad26IaGh54ucGNDJyYaYmAe9MmJjk3F0NLx2OjraEBubhLOzLRqNlpSUDOztDW+va9euipWVOdeu3cHTs1rOZ3SVKtZ07FiXCxeiad684AehivF4UlsUNYCHECJ79PMIIEj/exKQfadsj67ilCCEqAb0fkz7DwVe1f8+uITr5I4rt4tAdSHEMwBCCDshRFGVy5K+p4tAXSGEh/517pHDvwLvC/1jdyFEqxK+hxz9+3fFz083OLpLlxbs3n0UKSVhYdewsbHKN0bPyckBGxtLwsKuIaVk9+6jdOmia+Hq1KkZu3YdBWDXrqN07qz7e1JSKpmZuidR27cfoWXL+tjYWBUYz6uvds6ZZKZLl2bs2fOnPp4IbGwsi4gnAikle/b8SefOTfXxNGXXrj/08fyR8/c7dxKRUldfPn/+OlJqcXCwoVq1Kpw7d520tAyklBw7dgkPj4LHNHh5uXPjRhxRUXfJzMwiMPAMnToZdofr1MmLPXt0k+EcOBBG69a6cROdOjUiMPAMGRlZREXd5caNOBo1ejAz5N69p+nRI3+30+PH/6JWLWeDrl/lFdvbb7/ATz9NJCDgE2bMGEzr1nWZNm0gUkpu3LgD6D7UDh8OzzdhS9GxVufmzXvcuhVPZqaGffvC8fY2nAzB27sBv/6q694SFHSBVq1qIYQgOTmNiRO38OabXWnW7EH+7t/P4M4dXfdVjUZLaOhf1KpVlZIw9tw9zvO1MFFRcTkTsNy6dYfr16OpXt2x0PKvvtqJ9esnsH79BP05eyznnLW1tSygom2PjU2lXOfsMTp1yj5nm7B7t64Vf/fuB+fy7dv3mDx5LdOmDaVWLZci4y+MMebuSaM7P+4SFXVPf36cpWNHw+75HTt6sWfPKQCCgs7TunWdfC3DT5P+/bvnTJTStWtLdu0K1R93V7G1Ley4syIsTDe2c9euULp0KXxMOui6bGdPNHLzZiw3bsTg5lb8dbg8zomkpFTGj/+ad999iRYt6hUbk2F8xpW7irxfuncviaQkXRfutLQM/vzzQoFjQnPz9KzGzZsJ3LqVSGamhgMHLuPtbfjA1Nu7Dr/9phtnfPDgFVq2rIEQglu3EnPyEh2dSGTkPVxd7bl/P5PUVN3ck/fvZ3L8eCQeHk/+Ne5pGKP4pLYopgH/BwToK1V/opsNFXQtYHuEEFFSyu5CiJPABSASOPyY9j8W2CCEmALsAUrS2d4gruw/SikzhBCDgP8JIazQjU/sWdhGpJSnS/KepJT3hRDv6veZgi5H2WYCXwBnhBAmwDXgoftkeXs34ciRcwwYMINKlSyYOnV4zrKRI+fg5zcZgI8/HsSsWf6kp2fSvn1jOnRooi/zPFOmrOGXX47g6lqVWbNGA7rB2TNn+iOEbkD55MnD8++8wHgaExJyngEDZuqn2h+as+y11xawfr1uKvwJEwYYfD1Ghw66HrwjRvRk6tS17NgRqo9nFAD7959i69bDmJqaUKmSOZ9/PgohBE2aeNC9ewtGjVqIqakJDRvW4KWXvAuMzczMlI8+epHx49fqp4lvQ5061Vi9+ne8vGrQqVMj+vZty6xZAQwevAh7e2tmzNA9i6hTpxrPPdeMESO+wNTUhHHjXszp+3//fgbHjl3h449fybfPvXsLHrdYXrEVRErJ7NkBpKamI6Wkfv3qjB9f8jmVTE1N+OCDf/HJJz/op+9uRp06zvj6HsLT05WOHRvQt29z5szZwbBh32Jvb4WPz4sAbN16gqioePz8juDnp5upbeHCgUgJU6b8SGamBq1W0qpVLV58sWTPUJ6k3D3q+XrgwCmWLAkgPj6Z8eO/pmHDGnzxxRhOn/4Lf//fMDMzRQgTJkwYZNCyV5QOHRoREhLOwIFzsLQ0Z/LkB93MXnttEevX64aKjx/fP+frMdq396JDB11lfMSIHvj4+LFjx1FcXaswc+ZIANau/Y3ExFQWLfoR0B03vr7jAJg+3Z+TJ68QH5/Cyy9/xujRL/Dvfxt+xcqTkLuHsWnTJrp164aTkxORkZFMnz4dX1/fMtufmZkpY8f2ZcIEP7RaLX36tKZOHRfWrAnE09OdTp286Nu3NbNn/8SQIV9gZ2fFjBkDctYfOHAJKSnpZGVpCA6+wOLFI/HwcOHrr39l796zpKVl8uqri+jbtzWvv/5cmb0PKP/cAXh7N+XIkbP07z8VS0sLpk59LWfZiBEz8ff3AeDjj4cwc+Z60tMz6NChKR066B6YHDhwksWLNxMfn8y4cSto2LAmy5Z9yMmTl1m1arv+uBN88snQUre6l9U5sWVLEDduxOLruwtf310AfPHF+/l6zDxpuSvv+6U7dxL5/HPdeSel5LnnWtOpU9Ff62JqasL773dh4sRtaLWSXr0a4+HhyLp1R2nY0AVv7zr07t2YefN+Z+RIf+zsKjFlim4IR1hYFJs3n8DMzAQhBB980A0HByuiohKYMUP3/6jRSJ57riHPPvvP6DHxTyeyW0iUkhNCWAP3pZRSCDEYGCKlfKSZQ8uCEMJWSpmsbzn8ErgspVz6MNvK2/XUmDwY0mmcNJqS9AZWCpKVVfIJD8qbmVnJuxOWN2OODUCrTS++UAUxMSn5d3mWN0fHf1V0CEW6fbvgqf6NgatrSTv/VIy7d/NNiG40jPkztugOWBXPmHOXkhJefKEKVLPm+0bfpeDnn58t13vjl1/+o9xzYtxnmPFqA6zQV8DigdcrNpxCvSmEeA2wQDfxzbcVHI+iKIqiKIqiKE8AVVF8CFLKQ0DxffkqmL718KFaEBVFURRFURRFKVhFjRssT0/qZDaKoiiKoiiKoihKGVEtioqiKIqiKIqiKKVQUd9tWJ5Ui6KiKIqiKIqiKIpiQLUoKoqiKIqiKIqilIIao6goiqIoiqIoiqI8dVRFUVEURVEURVEURTGgup4qiqIoiqIoiqKUgup6qiiKoiiKoiiKojx1VIuioiiKoiiKoihKKTwNLYqqoqiUSGbmnYoOoVCVKrlXdAhF0mrTKzqEQpma2lR0CEXKykqo6BAKZWbmUNEhPLE0muSKDqFQJiaVKjqEQt29u7+iQ3hiGXvuqlbtXtEhFCoy8suKDqFQNWu+V9EhFOnOnd8rOoRCpaVdr+gQlCeAqigqiqIoiqIoiqKUghCZFR1CmVNjFBVFURRFURRFURQDqkVRURRFURRFURSlFJ6GMYqqRVFRFEVRFEVRFEUxoFoUFUVRFEVRFEVRSkG1KCqKoiiKoiiKoihPHdWiqCiKoiiKoiiKUgqqRVFRFEVRFEVRFEV56qgWRUVRFEVRFEVRlFJQ36OoKIqiKIqiKIqiPHVUi6KiKIqiKIqiKEopPA1jFJ/IiqIQwhEI1L90BTRArP71s1LKjFxlxwIrpZSpxWzzADBBSnksz99XA0uklOeLWPdl4FJ2GSHEOmCHlHJLyd+VwfaOSCm9H3LdbkCGlPLIw6xfUkePXmb58l1otZK+fVszfHgXg+UZGVnMnv0Tly5FYW9vxYwZA6levQoAGzYcZOfOE5iYCD78sA/PPtsAgICAEHbsOI6Ukn792jBwoC4Fvr772LHjOJUr2wDw5ps96dChYYljlVKyZMl3HDlyFktLC3x8XsfLq3a+cuHhEcyc6Ut6eibe3s0YN24IQggCA/9k1artRETcYu3aqTRq5AFAVlYWs2ev5+LF62g0Wnr37sCoUX2LjSc09CLLlm1Dq5X06/csI0Z0z5e7WbM2c/HiTeztrfn882FUr14VAH//fezY8ScmJoKxY1+iXTtPoqPjmTVrM/fuJQOCF19sx8CBnQC4fDmKRYt+4v79DFxdqzB9+hBsbCxLnLvcOVy6NIAjR87pczgCT89a+cpduPA3M2f6k56egbd3Ez76aIA+hydYs2YnERHRrFnzMY0a5c9/af3xx1VWrAhEo9HSt28Lhg5tb7A8IyOLuXN3cunSbeztrZg+/SVcXR04duwaK1cGkZWlwczMlLff7k7r1rVJS8tkxoyfiYqKx8RE4O1dn7fe6vbIcRpb7soqnoSEZCZPXk14+HX69GnPhAmDShxTWVxPfvjhCDt2HEcIQd261Zg48WUqVTJnzJjVpKbqPiLu3UuhUSN35swZ+sTmLm98S5Z8T0hIGJUqWeDjMwovr4Liu87MmetIT8+kQ4emjBs3SB/fcVav/oWIiNv4+k7MudZFRcUxZMgMatWqBkDTpnX59NNhRhFbttu37zJkyAzeeKMfw4Y9bxSxPY68lcaaNWvo168fMTExNGvWrMz2k9sff0Tw5ZdBaLWSPn2aMGTIMwbLMzKymD//Ny5disHe3hIfnz64utpz4cJtlizR3cZJCa+91o5OneoTE5PEvHm/ce9eKkJA375NefXVVmX+Psord496DUlISMHHx5dbt+5Qvbojs2aNxt7emsTEVGbP3sDNm7FYWJgzZcpw6tVzAyApKZW5czfy11+3EAKmTBlOs2Z1i4zz+PEYVq4MQ6uVPP98LQYMaGCwPDNTw5Ilp7hyJR47Ows+/bQN1apZA3DtWiIrVpzh/v1MhBAsXdoZCwtTgoJu8sMPlxECqla1ZPz4Vjg4VHpMmVUAhBC9gGWAKbBaSjkvz/JxwBtAFrp60+tSyutFbfOJ7HoqpbwjpWwppWwJfAMszX6du5KoNxawfoR9vVFUJVHvZaDxw+6jgH0+VCVRrxvwKOsXS6PRsnTpDhYuHIGf3xgCA88SERFjUGbnzhPY2Vny3XdjGTjQm2+++R2AiIgYAgPPsn79GBYuHMmSJTvQaLRcvRrNjh3H+fbbt/D1fZeQkEvcuHEnZ3sDBnTA1/ddfH3fLVUlEeDIkbNERkazZcscJk4cyYIF/gWWW7BgA5MmvcaWLXOIjIwmJCQMgLp13Zk//z1atTLcb2DgMTIyMtm06XPWr/fh55+DiIqKKzZ3S5ZsZdGi0WzYMJ69e09x7Vq0QZkdO/7Azs6K77//lEGDOvP117sAuHYtmr17T+PvP57Fi99g8eKtaDRaTE1NGDOmHxs2TGDlyvf46acjOducP38Lb7/dGz+/cXTp0pRNm4JKlbtsISHniIyMJSBgBhMnDmXBgs2F5HAzkyYNJSBgBpGRsYSG6k6devXcmDv3LVq2rP9Q+89Lo9GybNnvzJs3gHXr3iAw8DwREYa537XrDHZ2lmzc+F8GDGjLt98eAMDBwZo5c17F13c0kyb1Ze7cHTnrDBr0LH5+b7Jq1f8RFnaTo0f/euRYjS13ZRWPhYU5b73VjzFj/lOqeMriehIbm8iWLaGsWvU269ePQavVsm+f7nxeseKNnGtJkyY16dKl5JduY8td/vjCiIyMISBgJpMmDWfBgo2FxLeJSZNGEBAwk8jIGEJCzgFQt64b8+a9TcuWDfKt4+7ujL+/D/7+Pg9V2SnL2ACWLQugQ4cmpY6rrGN71LyVxrp16+jVq1eZ7iM3jUbL8uUHmDv3ZXx9R7Bv3yUiIu4YlNm9+xy2tpXw9x/Fq6+2YtWqYAA8PBz5+ushrFw5jHnzXmbp0n05n2dvv92ZtWtHsGLFILZtO5Nvm2WhvHL3qNcQf//faNvWk4CAGbRt64m//28ArF+/h4YN3dmwYQrTpo1k6dKAnG0tXbqF9u0b8/330/D3n4yHh2uRMWo0kq+/Pstnn7Xjq6+6ExQUxd9/JxmU+e23SGxszFm1qgcvvVSXdevC9etqWbz4BO+914yvvurO3LnemJqaoNFoWbkyjDlzOrBiRTc8POzZsSPiYdOoFEAIYQp8CfRGVycZIoTI+wF3EmgrpWwObAEWFLfdJ7KiWBAhRA8hxEkhxFkhhK8QopIQ4gPADdgvhNivL/e1EOKYEOKcEOKzEmz3gBCirf73ZCHEbCHEaSFEqBCimhDCG3gRWCiEOCWEqFfMtpbq9x8uhHhGCPGTEOKyEGJWrnLJ+n+76dfZIoS4IITYKIQQ+mURQggn/e9t9eU8gLeBj/SxdBZCOAshfhRC/Kn/6ahfp6u+zCl93uxKmuvw8Bu4u1fFza0q5uZm9OjRjODgCwZlgoPD6dWrJQBduzbmxImrSCkJDr5Ajx7NsLAww82tCu7uVQkPv8H167E0alQDS0sLzMxMadnSg4MHi6ufl8zBg6fo3dsbIQTNmtUjKSmVuLh4gzJxcfGkpNynWbN6CCHo3duboKCTANSp40bt2gVdWAVpaRlkZWlIT8/EzMys2Na68PBIatRwwt3dEXNzM3r2bEFw8DmDMsHB5+nduy0A3bo14/jxK/rcnaNnzxb63FWlRg0nwsMjcXKyx9OzBgDW1pZ4eLgQF5cAQGRkHC1b6p4cPvNMA4KCzpY2fQAcPHiG3r3bIYSgadM6JCffz9lHtri4BFJS0mjatI4+h+0ICjoNgIeHK7VrV3uofRfkwoVbuLlVxs2tMubmpjz3XCMOH75sUObw4cu88EJTALp29eLEietIKWnQoBpOTnb6uJxIT88iIyMLS0tzWrXStfCYm5vSoEE1YmMNPxwfhrHlrqzisbKqRIsW9alUqXQdVcriegK6G5b09EyysjSkpWXi6Gh4iUtJSePEiat07uxV4liNLXf54ztNnz7t9fHVLSK++zRtWhchBH36tOfgwVMA1KlTvZBr3aMry9iCgk7h5uZInTpuRhdbeTp06BB3794tt/1duBCNu7sDbm4OmJub0r17Q44cuWpQ5siRqzz/vO5etWvXBpw4EYmUEktLc0xNdbegGRkPuu85OtrQsKELANbWFtSuXZW4uOQyfy/llbtHvYYcOnSGPn3aAdCnTzsOHtT9PSLiNm3aeAK668zt23e5ezeR5OT7nDp1hX//W9d+YG5uhp1d0W0nly7do3p1G1xdbTA3N6FLFzdCQ28blAkNvU2PHrr7jk6dqnP6dCxSSk6ciMXDw566dR0AsLe3wNRUIKWu5Tg9XYOUktTULBwdS9+7ydgIkVWuP8V4FrgipbyqbzTbDLyUu4CUcn+uHpahQI3iNvpPqShaAuuAQVLKZui61L4jpVwORAHdpZTZ/fumSCnbAs2BrkKI5qXYjw0QKqVsARwE3tR38dwOfKxv0SyuCSJDv/9vgG3Ae0BTYJS+S21erdC1ijYG6gIdC9uwlDICwxbWQ+iaoJdKKZ8BXgVW64tPAN7Tt8p2Bu4XE3eOuLgkXFwccl47O9sTG5tYaBkzM1NsbCqRkJBKbGxinnUdiItLok6dapw5c52EhFTS0jIIDb1ETMyDbW7d+gejRn3JvHlbSUoqcagAxMbeo1q1qjmvXVyqEBsbn6dMPC4uVfKUuVfkdnv0aIOlpQV9+47jxRc/ZtiwF3BwsC0mloR87z9v7nKX0eXOMlfuKudZ1/AD5tatu1y6FEXjxrquLHXqVOPQIV1FdP/+M0RHG77vkoqNTaBatdz7rlxIDh+UcXGpnC++x0V3fNnniscu381EXFwyLi66yoGpqQm2tpVITDQ8dg4evEiDBtWwsDC8QU9OTiMk5AqtW3s8cqzGljtji6csrifOzvYMHtyRAQOW8MorC7GxseTZZw1b8Q4dukCbNnVL1RXb2HKXP754XFxyX+sq57uOxcbew9k577UuvthtR0XFMXLkLN55ZxGnTl0utnx5xZaamoa//x5Gj+5X6pjKOjZ49LwZs7i4ZJydHzyAcXa2LeA6nIKLi+5z0dTUBBubSiQmpgEQHn6b11/35403NvLRR8/lVByz3b6dyJUrMTRqVPGV8MflUa8hd+8m4eSku+Y5Otpz967uYWb9+u4cOHAKgHPnIrh9+y4xMfFERcVRubIts2b5M3LkXObM2cj9++lFxnjnThrOzlY5r52cLLlzJ63QMqamJlhbm5OYmEFUVApCgI9PKB9+GMSWLVcAMDMz4d13m/Hee0GMHPk7kZFJ/Otf+bvcKo/EHYjM9fqG/m+FGQ3sLm6j/5SKoilwTUp5Sf96PdClkLIDhRAn0DW/NqF0XUYzgOx+ascBj9KHynb9v2eBc1LKW1LKdOAqULOA8n9IKW9IKbXAqYfYZ09ghRDilH7f9kIIW+AwsETf6lpZSpnvUYUQ4i196+cxf/+9pdxt6Xh4ODN0aCfGj1/PhAn+1K9fHRMTAcDLLz/Ld9+Nxdf3HRwd7fjyyz1lGktJnTt3DVNTE3buXMzWrfPZtOlXbt6MLX7FMpKams6UKf58+OG/c25+J00awNatIbz++jJSU9MxN38ihyWXiWvXYlm5Mohx414w+LtGo2XmzO385z9tcHOrXDHBKY8kKek+wcEX+P77j9i69WPS0jL47bfTBmUCA8/Qo0f5jON60jk5ObBt21z8/Kby4YcDmDZtDSkppXtgV1ZWr97B4ME9sbY2vtYJY86bMWjUyBVf3xF89dVgNm06ZtCyeP9+BjNm7OTdd7tiY6PGsRVECIGujxmMHPk8ycn3GTlyDlu2HKBhwxqYmAg0Gi2XLkXyn/90xs9vElZWFvj5/VZmMWk0kvPn7zJhQivmz+9ISMhtTp2KJStLy65d11m+vAt+fv/Cw8OegIAn/8GJEOX98+C+XP/z1sPFLYYDbYGFxZV9qu4ahRB10LWkPSOlvKefdKY0ny6ZUkqp/13Dw+Uv+1GONtfv2a8L2l7uMrn3mcWDin5R78EEaC+lTMvz93lCiJ1AH+CwEOIFKaVBfy8p5UpgJUB09PfZ7xsnJztiYh48IY+NTcTZ2T73qjllXFwcyMrSkJKSjoODNc7O9nnWTcjpBtivXxv69WsDwMqVv+PsrHtqVrXqg1a6fv3aMHFiweNHcgsI2Me2bQcBaNzYg+joB11KYmLu4exc2aC8s3NlYmLu5SlThaL8+utR2rdvipmZGVWr2tO8eX3CwyNwd3cudB1nZ4d87z9v7rLLuLhU1ucuLVfu4vOsq8tRVpaGqVP9ef75VnTt+uDmt3ZtF5YufROAv/+OJSTEsEtfUbZsCWL79sMANGpU26A1MjY2vpAcPigTExOfE9/jpju+HrQ6xcYm4eRkm6eMLTExutYljUZLcnI69vZW+vKJTJu2lYkT++Lubvj/vGjRHtzdq9K/v+GkDKVhbLkztnhyK4vrybFjf1G9epWcCbC6dGlMWNjfPP98CwDi41MID7/JrFlDio3PmHOni28/27YF6+PzICYm97UuPt91zNnZsLdEQdfDvCwszLGwMAfAy6s27u7O/P13dL4JZSoitnPnrrFv3wlWrPiJ5ORUTEwEFhbmDBjQvcj1jDlvTwonJ1uD7vmxsckFXIdtiInRtTxqNFpSUtKxtze8ZalduypWVuZcu3YHT89qZGVpmDFjJz16eNK58+MZm12RHuc1pGpVO+LiEnByciAuLoEqVXT3TzY2VkydOgLQTZjzn/9Mw93dibS0DJydK9OkSR0AundvlTOusTCOjpbExj54oBEXl5avm2h2GScnKzQaLampmdjbW+DoaEmTJo45k9S0bevCX38lYG2tOw+qV9ddkzt3diMg4EqxuVMM5b4vL8BNDBucauj/ZkAI0ROYAnTVN1QV6Z/SoqgBPIQQ2VeUEUD2rB1JQHbfCHsgBUgQQlRDN+Dzcci9j/ISAbTR//5qEbH8Bryf/UII0VL/bz0p5Vkp5XzgT6DEA3W8vNy5ceMuUVH3yMzMIjDwLB07Gq7esaMXe/acAiAo6DytW+v62nfs6EVg4FkyMrKIirrHjRt3adRI10VaN2snREfHc/BgOD176io8cXEPPogOHQqnTh2XYmMcMOA5NmyYwYYNM+jSpRW7dx9BSsnZs39ha2uNk1Nlg/JOTpWxsbHi7Nm/kFKye/cRunRpWeQ+XF2rcuyYruJ1/346YWFXix2n4uVVg8jIOKKi7pKZmcXevafp2NGwUbtjx8bs3q2bfPfAgbO0bl1fn7vG7N17Wp+7u0RGxtGoUU2klMydG0Dt2i4MHmzYkJ6dU61Wy/r1gbz0kuHMoEXp378rfn6T8fObTJcuLdi9+yhSSsLCrmFjY5XT/SWbk5MDNjaWhIVd0+fwKF26lKZnd8l5eVXn5s173LoVT2amhn37wvH2Nryh8PZuwK+/6iYwCQq6QKtWtRBCkJycxsSJW3jzza40a2bYPX/NmoOkpKQzZkyPR4rP2HJnbPHkVhbXk2rVHDh/PpK0tAyklBw/fpXatR88wAkKOk+HDp5UqmRebHzGnDtdfN1zJkvp2rUlu3aF6uO7iq1tYfFZERamG+e5a1coXbq0KHIf9+4lodFoAbh5M5YbN2Jwcyv8gVh5xvbttx/z889z+PnnOQwa1IPXXutdbCWxvGJ72Lw9Kby8qnHzZjy3biWQmalh//5LeHsbzqbZoUNdfvtNN99AUNBlWrWqiRCCW7cScnITHZ1IZOQ9XF3tkVKyaNFeatWqyoABrcv9PZWFx3kN6dSpGbt2HQVg166jdO6s+3tSUiqZmboW2e3bj9CyZX1sbKxwdHSgWrUqXL+um+Du2LGLxU5m07BhZaKiUrh9O5XMTC0HD0bRrp3hOu3aVSMwUDcePDj4Fs2bOyGEoE0bZ65fTyQtLQuNRktY2B1q1bLD0dGSyMgkEhJ09ZKTJ2OpWbPooTpPAiHMyvWnGH8CDYQQdYQQFsBgHvRi1McrWgHfAi9KKWMK2Eb+9/iggezJJISYASSj60q6CF2L25/oxiimCyHeB8YAUVLK7vpWRG90/XgTgO1SynWi8K/HyPm7ECJZSmmr/3t/oJ+UcpR+gphV6Fr/+gM+FPD1GHm21U3/e7/C9lNAmRXAMX28nYE1QCJwAN0sRt2EEA3RzWSkRVdBDEc3C1IjfW4OSinfFkL8D+iuL3cOGFXUk4XcLYoAISGX+N//dqPVaunTpzUjR3ZlzZpAPD3d6dTJi/T0TGbP/onLl29hZ2fFjBkDcHPTjQHx8wti164TmJqa8P77vWnfXjeb6Jgxq0lIuI+ZmQljxvSiTRvdvECzZv3I5cu3EELg6lqZCRNezGmFBKhUqagu2LqnawsXbiQ0NCzn6zGyn+gOH66rTILu6zE+/3yNfurzZkyYMBQhBAcOnGDRok3Exydha2tNw4Y1Wb58HKmpacyc6cu1a7f0X+nRiREj8s+alplpOGNbSEg4y5b9glarpW/fZ3jttR6sXv0rXl416NSpCenpmcycuZnLl6Owt7dmxoyhuLvrhq+uXx/Izp1/YmpqwgcfvEiHDl6cPn2N9977mnr1XNHPdcR//9uLDh0a8cMPwfz0k+6bUrp2bcrbb/fOKQNgampTZO5y53DRoh84evQ8lSpZMHXq8Jyp/UeOnIOf32R9Dq8za5Y/6emZtG/fmPHjB+pzeIolSwKIj0/G1taKhg1r8MUXY4rdb1ra34UuCw39iy+/DESrlfTu3Yzhw73x9T2Ep6crHTs2ICMjizlzdnD5cjT29lb4+LyIm1tl/P2PsGlTqEFL4sKFA8nK0jBw4NfUqlU1p4vuK6+0pm/fgm8GLS1LNr6ionJXEfG88ooPKSlpZGVlYWtrzbJlY6hTp3q+GPKfE4//euLru499+8IwNTWhQYPqfPLJSzljUT/4wJdhwzrTrl3+WSrNzQsaKm4cuSvuRkEX33eEhuqm3p869bWca92IETPx9/fRxxfBzJnrSU/PoEOHpowfP1gf30kWL96cK76aLFv2Ifv2nWDVqu2YmZkihODNN/9N585FV5LKK7bcVq36BWvrSg/19RgVnbeqVYuv3BZn06ZNdOvWDScnJ6Kjo5k+fTq+vr6PvN3IyC8LXXb06DW+/PKg/jrcmGHDnmXt2hA8Pavh7V1X/zVFv3LlSix2dpZMndobNzcHfv89nO++O4aZmQlCCEaMaEenTvU4e/YmY8duoU4dx5zhJ6NHe9OuXZ0C91+z5nuP/P6g7HJ3587vBq8f9RqSkJDMlClriI6+h6trVWbNGo2Dgw1nz15l5kx/hNBNrjR58nDs7XWT1ly6FMncuZvIzMzC3d2JKVNGYG9vzZ07hQ/j+fPPaFatOodWK/nXv2oyaFBDNmy4QIMGlWnXzpWMDA2LF5/k6tUEbG0t+PTT1ri66u4n9u+/oe9WKmjb1oXXX9c9DN+1K4Lt269hZiZwdrbmo49aYm9vUWgMDRosEoUuNBL79lUq10rUc8+lF5kTIUQf4At0Q/J8pZSzhRCfo6s7bBdC7AWaAbf0q/wtpXyxyG0+6RVFpXzkrSgak+IqihUt702xMSlpRbGiFFVRrGglrSgq+RnzOVFURbGileCJsvKEehwVxbJSVEWxoj2uimJZyVtRNCZFVRSNwZNQUdy/36Zc7427d08p95z8U7qeKoqiKIqiKIqiKI+JejypKIqiKIqiKIpSCrrvuP9nUy2KiqIoiqIoiqIoigHVoqgoiqIoiqIoilIKT8O4cdWiqCiKoiiKoiiKohj451eFFUVRFEVRFEVRHiPVoqgoiqIoiqIoiqI8df75VWFFURRFURRFUZTHSLUoKoqiKIqiKIqiKE8dVVFUFEVRFEVRFEVRDPzz20wVRVEURVEURVEeo6eh6+k//x0qj4VWm17RIRRKCNOKDqFIGk1yRYdQKCmzKjqEIpmZOVR0CIXKykqo6BAKZewfXsZ8PdFoUio6hEKZmtpUdAhFUrl7eJGRX1Z0CIWqWfO9ig6hUMacNwATE8uKDqFQNWt+UNEhKE8A476bUBRFURRFURRFMTLG3lDxOKgxioqiKIqiKIqiKIoB1aKoKIqiKIqiKIpSCsY+zONxUC2KiqIoiqIoiqIoioF/flVYURRFURRFURTlMVItioqiKIqiKIqiKMpT559fFVYURVEURVEURXmMVIuioiiKoiiKoiiK8tT551eFFUVRFEVRFEVRHiP1PYqKoiiKoiiKoijKU0e1KCqKoiiKoiiKopTC0zBG8Z//DosghHAEAvUvXQENEKt//ayUMiNX2bHASillajHbPABMkFIey/P31cASKeX5ItZ9GbiUXUYIsQ7YIaXcUvJ3VeB2k6WUtkIID/32mj7K9vI6evQvVqz4DY1G0rdvS4YN8zZYnpGRxdy527l48TYODlZMm/YK1atX5tixq6xcuZ/MTA3m5qa8/XYPWrf2AGD16v38+utZkpLS2LPnk0eKT0rJ4sUbOXLkDJaWFkyb9gZeXh75yoWHR/D556tJT8/A27s548cPQwjB8uWbOXToFObmZri7uzBt2mjs7Gxy1rt9+w6DBk3mzTdfZvjw3qWK7ejRK/zvf7+i1Wrp27cVw4Z1MliekZHFnDk/c+nSLeztrZg+vT/Vq1cmISGVadMCuHgxil69WjJ2bP79Tpq0mVu37rFu3TuliulBbJdYtmwHWq2Wfv2eYfjwrvlimz07gIsXb2Jvb81nnw2hevUqAPj7H2DnzmOYmJjw4Yf9aNeuIQDffx/Mjh3HEALq1nVl0qRXqVTJvEJjAtBotLz55pc4OdmzYMFrgO64WbXqd/bvP4upqQkvv9yO/v0Nj+0nJXehoRdZtmwbWq2kX79nGTGie754Zs3anBPP558Po3r1qvp49rFjx5+YmAjGjn2Jdu08iY6OZ9aszdy7lwwIXnyxHQMH6o7dNWt+45df/qByZd058t//9qJDh0YlilOXu4e7niQkpDJ9+k9cuBBFr17NGTu2FwCpqem8/75fzvqxsUn8619Nef/95/9xuZNSsnRpAEeOnMPS0gIfnxF4etbKV+7Chb+ZOdNff61rwkcfDUAIQWDgCdas2UlERDRr1nxMo0a1Afjjj3C++mpbzrV6zJhXaNvWs9xzV9Q2584N4MKFG4CkZk1nJk8eiLV1pScyb3n98UcEX34ZhFYr6dOnCUOGPJMvj/Pn/8alSzHY21vi49MHV1d7Lly4zZIlgfr3CK+91o5OneoTE5PEvHm/ce9eKkJA375NefXVVqWOq7TWrFlDv379iImJoVmzZmW+PzDu3EkpWbLkO44cOas/7l7Hy6t2vnLh4RHMnOlLenom3t7NGDduiP64+5NVq7YTEXGLtWun0qiRBwBZWVnMnr2eixevo9Fo6d27A6NG9S11bPPnf0Vw8B9YWlZi5syPadSoQb5y589fwsdnIenpGXTq9CyffvouQgi+/tqPH3/cRdWqDgC8//7rdO7cjrNnLzBz5lL9PuDtt0fQo0enfNtVjMdT3fVUSnlHStlSStkS+AZYmv06dyVRbyxg/Qj7eqOoSqLey0Djh91HRdBotCxbtof58wezfv1/2bfvHBERsQZldu06ha2tJZs2vUv//s+ycuU+ABwcrJkzZyBr177FxIn/Zs6cbTnrdOjQkG+++b/HEuORI2eIjIzmxx/nM2nSKObP9yuw3Pz565k8eRQ//jifyMhoQkLOAvDss0357rvZbNo0i1q1XFm3bqfBel988R0dOpT+Q0+j0fLFF7tZsGAo69e/S2Bg/tzt3HkSOzsrNm16nwED2vPtt3sBsLAwY/To7rzzzr8K3PbBg+FYWVmUOqbcsS1Zsp1Fi0bh7z+WvXtPc+1adJ7YjmFnZ8XmzRMYOLAj33yzB4Br16IJDDyDn99YFi0axZIl29FotMTGJvDjjyGsXv0efn5j0Wq1BAaeqdCYsgUEHKF2bWeDbe3adYKYmAQ2bvyIDRs+okeP5k9k7nTxbGXRotFs2DCevXtP5Ytnx44/sLOz4vvvP2XQoM58/fWunHj27j2Nv/94Fi9+g8WLt6LRaDE1NWHMmH5s2DCBlSvf46efjhhsc+DAzqxb9xHr1n1UqorOo1xPLCzMeP31rrzzTg+D8tbWlViz5s2cH1dXB7p08frH5Q4gJOQckZGxBATMYOLEoSxYsLnAcgsWbGbSpKEEBMwgMjKW0FDdR1O9em7MnfsWLVvWNyjv4GDLwoVvs3HjFHx8RvLZZ+srJHdFbfODD/7N+vUfsX79OKpVq8yPPx55IvOWl0ajZfnyA8yd+zK+viPYt+8SERF3DMrs3n0OW9tK+PuP4tVXW7FqVTAAHh6OfP31EFauHMa8eS+zdOm+nGPw7bc7s3btCFasGMS2bWfybbMsrFu3jl69epX5frIZe+6OHDlLZGQ0W7bMYeLEkSxY4F9guQULNjBp0mts2TJHf28SBkDduu7Mn/8erVo1NCgfGHiMjIxMNm36nPXrffj55yCiouJKFVtw8B/8/fdNfvllHdOmjWXWrOUFlps1aznTp3/EL7+s4++/b3L48J85y0aMeJUffviWH374ls6d2wFQv74HmzZ9xQ8/fMtXX81h5sxlZGVpShWbMRHCrFx/KsJTXVEsiBCihxDipBDirBDCVwhRSQjxAeAG7BdC7NeX+1oIcUwIcU4I8VkJtntACNFW/3uyEGK2EOK0ECJUCFFNCOENvAgsFEKcEkLUK2Jb9YUQe/XrnxBC1BNC2AohAvWvzwohXiomniZCiD/0+zojhMj/qKgELlyIwt29Km5uVTA3N+W55xpz+PAlgzKHD1+mVy/dTXbXro04fjwCKSUNGrji5GQHQJ06zqSnZ5GRkQVAkybuODraPUxI+Rw8eJI+fToihKBZs/okJaUSFxdvUCYuLp6UlPs0a1YfIQR9+nQkKOgEAO3bN8XMTDdguWnTesTE3M1Z78CB47i5OVG3rnup4woPv4m7e5VcuWtCcPBFgzKHD1/khReyc9eYEyeuIaXEysqC5s1rYWGR/8KRmprBDz+EMnJk51LH9CC2G7i7O+LmVhVzczN69GhOcHC4QZlDh8Lp1as1AN26NeX48b+QUhIcHE6PHs2xsDDDza0q7u6OhIffAHQf3OnpmWRlaUhLy8TJyb7CY4qJSSAk5AL9+hk+ad627SijRj2HiYnuMlmliu0Tmbvw8Ehq1HDC3d0Rc3MzevZsQXDwOYMywcHn6d27rT6eZhw/fkUfzzl69myRE0+NGk6Eh0fi5GSPp2cNAKytLfHwcCEuLqFE8RTlUa4nunOiZoHnRLbIyDvcu5dC8+Y1SxTPk5Q7gIMHz9C7dzuEEDRtWofk5Pv5th0Xl0BKShpNm9ZBCEHv3u0ICjoNgIeHK7VrV8u3XU/Pmjg7Vwagbt3qpKdnkpGRWWQsZZG7orZpY2MJ6FpC0tMzEeLJzFteFy5E4+7ugJubA+bmpnTv3pAjR64alDly5CrPP697xty1awNOnIhESomlpTmmprrrV/ZnK4Cjow0NG7oAYG1tQe3aVYmLSy5VXA/j0KFD3L17t/iCj4mx5+7gwVP07u2tvzepV8y9ST39cedNUNBJAOrUcaN2bdcCtixIS8sgK0tDenomZmZmOedHSe3fH8K//90TIQTNmzcmKSmZ2FjDCnFs7B1SUlJp3rwxQgj+/e+e7NtX9AMaKyvLnPup9PSMUp2nSsVQFUVDlsA6YJCUshm6rrnvSCmXA1FAdylldt+ZKVLKtkBzoKsQomTNDTo2QKiUsgVwEHhTSnkE2A58rG/R/KuI9TcCX+rX9wZuAWnAK1LK1kB3YLEQRZ6CbwPL9K2pbYEbpYg/R2xsEs7ODyp0zs72xMYmFVBGd1NrZmaCrW0lEhLuG5QJCrpAgwauRd7kPayYmHtUq1Y157WLSxViYu7lK+PiUnQZgF9+OYi3t+6/OjU1DT+/XbzxxssPFVdcXBIuLg45r52d7YmLSyq0jJmZCTY2lvlyl5ev734GDuxQqi6decXGJuSJzYG4uMQ8sSXkis1UH1sqcXGJBuu6uNgTG5uAs7MDgwd3on//Bbz88lxsbS159tmSP58oi5gAli/fwbvv9sbExPB0uXnzDvv2neGNN75kwoR1REaW7ImsseWuoHhiYxMLLZM7ntjYRFxcKudZ1/AG+tatu1y6FEXjxg+66v300xFee20Jc+b8QGJikb3188TxeK4nhdm37zzdu+tuakoWz5OTu+xYqlXLvc/KxMbG5ykTbxCXi0vlfHEVZf/+k3h61sTCoujrS1nkrrhtzpnzAy++OJPr12Po379jid+TMeUtr7i45DznhG2+iklcXAouLroHWaamJtjYVCIxMQ2A8PDbvP66P2+8sZGPPnoup/KT7fbtRK5ciaFRo4IqHE82Y89dbGz+e5OCj7sqecrkvzfJrUePNlhaWtC37zhefPFjhg17AQeHkj3ozBYTE0e1ai45r6tVcyImJq6AMk65yjgblNm8eRv9+7/FtGmLSEx8cB0/cyacV155g/7932Lq1A9zKo6KcVIVRUOmwDUpZfYj7PVAl0LKDhRCnABOAk0oXZfRDGCH/vfjgEdJVxRC2AHuUsqtAFLKNP24SQHMEUKcAfYC7kD+R5wPhACThRCfArWllPnutIQQb+lbTY9t2LC/pCGW2rVrsaxcuY/x4/uU2T4eB1/f7ZiamtKrVwcAVq36mSFDXsDaunRP6srS5cu3uXnzXom71pWnpKT7BAeH8/33E/j550ncv5/Br7+erNCYDh++QJUqtnh65m8RzszUYGFhxurV7/Hvf7dl3rwfKyBCHWPMHejG/02Z4s+HH/4754n1K6904PvvP2Xt2rE4OtqzYsWOYrZSfvbtO0+PHk0qOgzgycsdwNWrUXz11TY+/XRIRYdSoMmTB/Lzz1OpXbsagYGnKzqcHBWZt0aNXPH1HcFXXw1m06ZjBq1j9+9nMGPGTt59tys2NiUbz/k0eVJzd+7cNUxNTdi5czFbt85n06ZfuXkztvgVH6OBA//Njh3r+eGHb3B2rsqiRd/mLGvevBFbt65m06YVrFmzmfT0vCO9nhyq66lSICFEHWAC0ENK2RzYia41sqQypZRS/7uGxzOp0DDAGWijbyWMLiomKeUmdF1d7wO7hBDPFVBmpZSyrZSy7fDh3fNtA8DZ2c7giX9sbKLBE7wHZXRPfbOytCQnp+PgYAVATEwiPj5bmDTpRdzdq/C4BATsZdgwH4YN88HJyYHo6AfdXXSth4b70rUgFl5mx45DBAefZubM/+a0RoSFXWXFiu956aXxbN78G+vW7eCHH/aWOEYnJztiYh48kY6NTczpiltQmawsLSkpaTm5K8i5cze4eDGKQYOW8f77a4mMvMOHH5Z+XIyzs0Oe2BLydXV0cnLIFZtGH5s1Tk72BuvGxCTi7OzAsWNXqF69ClWq2GJmZkrXrk0IC/u7QmM6e/Y6hw+HM2DAAmbM2MyJE1f5/PMf9Puzp0sXXaWiS5cm/PXX7QqL81FyV1A82S1yBZXJHY+zsz0xMfF51nXIKTd1qj/PP9+Krl0fjNGtWtUOU1MTTExMePHFZwkPjyxRnLo4Hu16UpQrV6LRaLR4elYvRTzGn7stW4IYOXIOI0fOwcnJnujo3PuMz+n6+CDeygZxxcTE58RVlJiYe0ycuAofn5HUqOFcbPmyyF1JtmlqakLPni0ICjpbZHzGmre8nJxs85wTyTg52eYpY0NMjK6lTKPRkpKSjr294cd/7dpVsbIy59o1XffBrCwNM2bspEcPTzp3Nhxb+U9hjLkLCNjH8OEzGD58RoH3JgUfd/fylCn6XunXX4/qh8yYUbWqPc2b1yc8PKLY2DZv3sbAgf9l4MD/4uxclejomJxl0dFxuLg4GZR3cXEiOjouV5nYnDKOjlUwNTXFxMSE//ynD2FhhsNqAOrWrY21tRVXrlwrNjal4qiKoiEN4CGEyD7zRwBB+t+TgOw7FnsgBUgQQlQDSjfVZeFy76NAUsok4IZ+hlT0YyitAQcgRkqZKYToDuSfOisXIURd4Kq+W+02dF1oS83T040bN+5y61Y8mZka9u07j7e34cBqb+8G7Nmjm3gjKCic1q09EEKQlJTGpEnf89Zb3WnWrGRjhkpqwICebNw4k40bZ9K1a2t27TqMlJKzZ69ga2uFk1Nlg/JOTpWxsbHi7FndGJlduw7TpYtuJrOQkDP4++9m8eIPsbR88ORw1arJbNu2mG3bFjN48POMGtWPgQN7ljhGLy93fe7u6XN3jo4dDXPXsaMnv/6anbvztGpVp8hucy+/3JaffhrH999/yP/+93/UrOnIsmWvlTgmw9jiiIq6S2ZmFoGBZ+jUyXBijU6dvNizRzeO88CBMFq3rosQgk6dGhEYeIaMjCyiou5y40YcjRrVwMWlMufORZKWloGUkuPH/8o3gUx5x/T22y/w008TCQj4hBkzBtO6dV2mTRsIQOfOjTl5Ujee5dSpa9Ssafgh+aTkzsurBpGRD+LZu/c0HTsadoDo2LExu3cf08dzltatdWN1O3ZszN69p3PiiYyMo1GjmkgpmTs3gNq1XRg82LDTRe5utgcPhlG3bsm7ZT3K9aQ4gYHn6NGjdHOFPQm569+/K35+k/Hzm0yXLi3YvfsoUkrCwq5hY2OFk5NhZcbJyQEbG0vCwnTjnXfvPkqXLkVf/pOSUhk//mveffclWrQodPi8gbLIXWHblFJy44buhlU3xvE8tWq55IvpSchbXl5e1bh5M55btxLIzNSwf/8lvL3rGpTp0KEuv/2mm1gnKOgyrVrVRAjBrVsJOZN2RUcnEhl5D1dXe6SULFq0l1q1qjJgQOuHiutJYIy5GzDgOTZsmMGGDTPo0qUVu3cf0d+b/IWtrXUR9yZ/6Y+7I3Tp0rLIfbi6VuXYsQsA3L+fTljY1ULGMhoaPPilnMlnunfvyC+/7EVKyZkz57G1tcHZ2dGgvLOzIzY21pw5cx4pJb/8spfu3XU9rnKPZ9y37zD163sAcOPGrZzJa6KioomI+Bs3tye32/PT0KIoHjRsPd2EEDOAZHRdSReha+X7E90YxXQhxPvAGCBKStld/9UV3kAkkABsl1KuK+LrMXL+nv11Ffq/9wf6SSlHCSE6AquAdKA/4EMBX4+hn3jmW8AJyAQGAInAL4AtcAxoD/SWUkYU9PUYQoiJ6CrCmcBtYKiUstBR5rdu+RV6oISGXmHFit/RarX07t2CESM64esbhKdndTp2bEh6ehZz5mzj8uVo7O0tmTbtFdzcquDnF8ymTUcMWhIXLRpKlSo2fPNNIHv3nuPOnSQcHe3o27cl//d/BfcCtrYueqyWlJKFC/0JCTmLpWUlfHxG07hxHQCGDfNh48aZAJw/f83g6zEmTBiOEIL//OcTMjKycHDQTVnftGk9Jk0aZbCPlSu3Ym1tWeDXY9y/fzXf3x7k7rL+6zEkffq0ZMSIzqxZsx8vLzc6dvQkPT2L2bO3cuXKbezsrJg+/VXc3HT5GjRoGSkp6WRlabC1tWTRouF4eDyoPNy6Fc+kSd8V+fUYJiaFN4SHhFxk+fIdaLWSvn3bMHJkd1av/h0vrxp06tSI9PRMZs0K4PLlKOztrZkxYzBubrrxFn5++9m58zimpiZ88EFf2rfXTQm/Zs1e9u07g6mpCQ0auPHpp/8p1bjUsogp28mTV/nuu0M5X4+RlHSfzz//gZiYeKysLJgw4WXq1y9Za1RF5y7vB0pISDjLlv2i/xqWZ3jttR6sXv2rPp4mpKdnMnPm5lzxDMXdXXdTsH59IDt3/qmP50U6dPDi9OlrvPfe19Sr55pTScv+Kofs7QgBrq5V+PjjV/O1qGZlFT6262GvJwCDBq0gNTWdzMzsc2JIzjkxZMiXzJs3iNq1i67wm5kZVhCMKXempjYURXcT+wNHj56nUiULpk4dnvNVDSNHzsHPbzIA4eHXmTXLn/T0TNq3b8z48QMRQnDgwCmWLAkgPj4ZW1srGjaswRdfjGHt2t34+f1GzZoPri9ffPE+VasaPtfUaFLKNHeFbVOr1fLee1+TkpKOlJL69aszYcJ/DCbwKCp3FZ03gNTUS/n+lu3o0Wt8+eVBtFpJ796NGTbsWdauDcHTsxre3nX1XxnzK1euxGJnZ8nUqb1xc3Pg99/D+e67Y5iZmSCEYMSIdnTqVI+zZ28yduwW6tRxzBmbPXq0N+3a1Slw/zVrvldobKWxadMmunXrhpOTE9HR0UyfPh1fX99H2mZk5JdFLq/o3NnaFv4wQXdvspHQ0LCcr8fI/oqL4cN1lUnI/uquNaSnZ9KhQzMmTBiqP+5OsGjRJuLjk7C1taZhw5osXz6O1NQ0Zs705dq1W0gp6devEyNG5J9t1tIy/1fA5I5t7tz/cfjwMSwtK/H55xNo0kT3WTRw4H/54QddV9Jz5y7i47OI9PR0OnZ8hkmTxiCEYPLkeVy8+BdCCNzcquHjMxZnZ0d++eV3fH2/x9zcFCFM+O9/h/PccwWPJ7a0rGX0U90cP96tXCtRbdocKPecqIqiUiJFVRQrWnEVxYpWVEWxohVVUVSeXMb+JcBFVRQrWt6KojEprqJY0fJWFI2JseeuqIpiRXtcFcWyUFxFsaIVVVGsaEVVFI3Bk1BRPHGiR7neG7duHVjuOVFdTxVFURRFURRFURQDxv3YWVEURVEURVEUxcgYe++dx0G1KCqKoiiKoiiKoigG/vlVYUVRFEVRFEVRlMdItSgqiqIoiqIoiqIoT51/flVYURRFURRFURTlMVItioqiKIqiKIqiKMpT559fFVYURVEURVEURXmMhDCt6BDKnGpRVBRFURRFURRFUQyoFkVFURRFURRFUZRSUGMUFUVRFEVRFEVRlKfOP78qrDwWJiaVKjqEQkmpqegQimRqalvRIRTK1NSmokMoUlra3xUdQqEsLWtVdAhPLK02raJDKJQxnxPG/vTazMyhokN4YtWs+V5Fh1CoyMgvKzqEQhlz3gDu3Pm9okMoVGTk8ooOoUgNGiyq6BCKZezX5MdBtSgqiqIoiqIoiqIoBlRFUVEURVEURVEURTHwz28zVRRFURRFURRFeYxU11NFURRFURRFURTlqfPPrworiqIoiqIoiqI8RqpFUVEURVEURVEURXnq/POrwoqiKIqiKIqiKI+REKYVHUKZUy2KiqIoiqIoiqIoigHVoqgoiqIoiqIoilIKaoyioiiKoiiKoiiK8tT551eFFUVRFEVRFEVRHqOnoUXxH/UOhRCOQKD+pSugAWL1r5+VUmbkKjsWWCmlTC1mmweACVLKY3n+vhpYIqU8X8S6LwOXsssIIdYBO6SUW0rwXrrp99uvuLIV4ejRyyxfvgutVtK3b2uGD+9isDwjI4vZs3/i0qUo7O2tmDFjINWrVwFgw4aD7Nx5AhMTwYcf9uHZZxsAEBAQwo4dx5FS0q9fGwYO9AbA13cfO3Ycp3JlGwDefLMnHTo0LHGsUkqWLPmOI0fOYmlpgY/P63h51c5XLjw8gpkzfUlPz8Tbuxnjxg1BCEFg4J+sWrWdiIhbrF07lUaNPADIyspi9uz1XLx4HY1GS+/eHRg1qm+x8YSGXmTZsm1otZJ+/Z5lxIju+XI3a9ZmLl68ib29NZ9/Pozq1asC4O+/jx07/sTERDB27Eu0a+dJdHQ8s2Zt5t69ZEDw4ovtGDiwEwCXL0exaNFP3L+fgatrFaZPH4KNjWWJc5c7h0uXBnDkyDl9Dkfg6VkrX7kLF/5m5kx/0tMz8PZuwkcfDdDn8ARr1uwkIiKaNWs+plGj/PkvrT/+uMqKFYFoNFr69m3B0KHtDZZnZGQxd+5OLl26jb29FdOnv4SrqwPHjl1j5cogsrI0mJmZ8vbb3WndujZpaZnMmPEzUVHxmJgIvL3r89Zb3R45TmPLXVnFk5CQzOTJqwkPv06fPu2ZMGFQiWMqi+vJDz8cYceO4wghqFu3GhMnvkylSuaMGbOa1FTdR8G9eyk0auTOnDlDn9jc5Y1vyZLvCQkJo1IlC3x8RuHlVVB815k5cx3p6Zl06NCUceMG6eM7zurVvxARcRtf34k517qoqDiGDJlBrVrVAGjatC6ffjrMKGLLdvv2XYYMmcEbb/Rj2LDnjSK2x5G30lizZg39+vUjJiaGZs2aldl+cvvjjwi+/DIIrVbSp08Thgx5xmB5RkYW8+f/xqVLMdjbW+Lj0wdXV3suXLjNkiW62zUp4bXX2tGpU31iYpKYN+837t1LRQjo27cpr77aqszfR3nl7lGvIQkJKfj4+HLr1h2qV3dk1qzR2Ntbk5iYyuzZG7h5MxYLC3OmTBlOvXpuXL8ejY/Pmpzt3rx5hzff7Mvgwc8VGefx4zGsXBmGVit5/vlaDBjQwGB5ZqaGJUtOceVKPHZ2Fnz6aRuqVbMG4Nq1RFasOMP9+5kIIVi6tDMWFqYEBd3khx8uIwRUrWrJ+PGtcHCo9BiyqpSlf1TXUynlHSllSyllS+AbYGn269yVRL2xgPUj7OuNoiqJei8DjR92H49ClOFjDo1Gy9KlO1i4cAR+fmMIDDxLRESMQZmdO09gZ2fJd9+NZeBAb7755ncAIiJiCAw8y/r1Y1i4cCRLluxAo9Fy9Wo0O3Yc59tv38LX911CQi5x48adnO0NGNABX9938fV9t1SVRIAjR84SGRnNli1zmDhxJAsW+BdYbsGCDUya9BpbtswhMjKakJAwAOrWdWf+/Pdo1cpwv4GBx8jIyGTTps9Zv96Hn38OIioqrtjcLVmylUWLRrNhw3j27j3FtWvRBmV27PgDOzsrvv/+UwYN6szXX+8C4Nq1aPbuPY2//3gWL36DxYu3otFoMTU1YcyYfmzYMIGVK9/jp5+O5Gxz/vwtvP12b/z8xtGlS1M2bQoqVe6yhYScIzIyloCAGUycOJQFCzYXksPNTJo0lICAGURGxhIaqjtF6tVzY+7ct2jZsv5D7T8vjUbLsmW/M2/eANate4PAwPNERBjmfteuM9jZWbJx438ZMKAt3357AAAHB2vmzHkVX9/RTJrUl7lzd+SsM2jQs/j5vcmqVf9HWNhNjh7965FjNbbclVU8FhbmvPVWP8aM+U+p4imL60lsbCJbtoSyatXbrF8/Bq1Wy759uvN5xYo3cq4lTZrUpEuXkl+ijS13+eMLIzIyhoCAmUyaNJwFCzYWEt8mJk0aQUDATCIjYwgJOQdA3bpuzJv3Ni1bNsi3jru7M/7+Pvj7+zxUZacsYwNYtiyADh2alDquso7tUfNWGuvWraNXr15luo/cNBoty5cfYO7cl/H1HcG+fZeIiLhjUGb37nPY2lbC338Ur77ailWrggHw8HDk66+HsHLlMObNe5mlS/flfJ69/XZn1q4dwYoVg9i27Uy+bZaF8srdo15D/P1/o21bTwICZtC2rSf+/r8BsH79Hho2dGfDhilMmzaSpUsDAKhduxp+fpPx85vM2rUTsbQ0p2vXFkXGqNFIvv76LJ991o6vvupOUFAUf/+dZFDmt98isbExZ9WqHrz0Ul3WrQvXr6tl8eITvPdeM776qjtz53pjamqCRqNl5cow5szpwIoV3fDwsGfHjohHSaVREMKsXH8qwj+qolgQIUQPIcRJIcRZIYSvEKKSEOIDwA3YL4TYry/3tRDimBDinBDisxJs94AQoq3+92QhxGwhxGkhRKgQopoQwht4EVgohDglhKhXxLbqCyH26tc/kausrRBiixDighBioxBC6MtPE0L8KYQIE0KszPX3A0KIL4QQx4APhRDPCCHO6Pe/UAgRpi9nqn/9p375f0uT0/DwG7i7V8XNrSrm5mb06NGM4OALBmWCg8Pp1aslAF27NubEiatIKQkOvkCPHs2wsDDDza0K7u5VCQ+/wfXrsTRqVANLSwvMzExp2dKDgweLq4eXzMGDp+jd2xshBM2a1SMpKZW4uHiDMnFx8aSk3KdZs3oIIejd25ugoJMA1KnjRu3argVsWZCWlkFWlob09EzMzMyKba0LD4+kRg0n3N0dMTc3o2fPFgQHnzMoExx8nt692wLQrVszjh+/os/dOXr2bKHPXVVq1HAiPDwSJyd7PD1rAGBtbYmHhwtxcQkAREbG0bJlXQCeeaYBQUFnS5s+AA4ePEPv3u0QQtC0aR2Sk+/n7CNbXFwCKSlpNG1aR5/DdgQFnQbAw8OV2rWrPdS+C3Lhwi3c3Crj5lYZc3NTnnuuEYcPXzYoc/jwZV54oSkAXbt6ceLEdaSUNGhQDScnO31cTqSnZ5GRkYWlpTmtWulaeMzNTWnQoBqxsYYfjg/D2HJXVvFYWVWiRYv6VKpUug+zsriegO6GJT09k6wsDWlpmTg62hlsMyUljRMnrtK5s1eJYzW23OWP7zR9+rTXx1e3iPju07RpXYQQ9OnTnoMHTwFQp071Qq51j64sYwsKOoWbmyN16rgZXWzl6dChQ9y9e7fc9nfhQjTu7g64uTlgbm5K9+4NOXLkqkGZI0eu8vzzuocxXbs24MSJSKSUWFqaY2qquwXNyMjKKe/oaEPDhi4AWFtbULt2VeLiksv8vZRX7h71GnLo0Bn69GkHQJ8+7Th4UPf3iIjbtGnjCeiuM7dv3+Xu3USD7R47dhF3d2eqV3csMsZLl+5RvboNrq42mJub0KWLG6Ghtw3KhIbepkcP3X1Hp07VOX06FiklJ07E4uFhT926DgDY21tgaiqQUtdynJ6uQUpJamoWjo6l792klL9/ekXRElgHDJJSNkPX1fYdKeVyIAroLqXM7vc3RUrZFmgOdBVCNC/FfmyAUCllC+Ag8KaU8giwHfhY36JZVNPERuBL/frewC3931uha/lsDNQFOur/vkJK+YyUsilgBeTunmohpWwrpVwMrAX+q29h1eQqMxpIkFI+AzwDvCmEqFPSNxsXl4SLi0POa2dne2JjEwstY2Zmio1NJRISUomNTcyzrgNxcUnUqVONM2euk5CQSlpaBqGhl4iJebDNrVv/YNSoL5k3bytJSfdLGioAsbH3qFatas5rF5cqxMbG5ykTj4tLlTxl7hW53R492mBpaUHfvuN48cWPGTbsBRwcbIuJJSHf+8+bu9xldLmzzJW7ynnWNfyAuXXrLpcuRdG4sa4rS5061Th0SFcR3b//DNHRhu+7pGJjE6hWLfe+KxeSwwdlXFwq54vvcdEdX/a54rHLdzMRF5eMi4uucmBqaoKtbSUSEw2PnYMHL9KgQTUsLAxv0JOT0wgJuULr1h6PHKux5c7Y4imL64mzsz2DB3dkwIAlvPLKQmxsLHn2WcNWvEOHLtCmTd1SdcU2ttzljy8eF5fc17rK+a5jsbH3cHbOe62LL3bbUVFxjBw5i3feWcSpU5eLLV9esaWmpuHvv4fRox9+lIYx582YxcUl4+z84AGMs7NtAdfhFFxcdJ+LpqYm2NhUIjExDYDw8Nu8/ro/b7yxkY8+ei6n4pjt9u1ErlyJoVGjiq+EPy6Peg25ezcJJyfdNc/R0Z67d3UPM+vXd+fAgVMAnDsXwe3bd4mJMdzu778f41//alNsjHfupOHsbJXz2snJkjt30gotY2pqgrW1OYmJGURFpSAE+PiE8uGHQWzZcgUAMzMT3n23Ge+9F8TIkb8TGZnEv/6Vv8vtk0YI03L9qQj/9IqiKXBNSnlJ/3o90KWQsgOFECeAk0ATStdlNAPI7r92HPAo6YpCCDvAXUq5FUBKmZZr3OQfUsobUkotcCrXdrsLIY4KIc4Cz+njzfa9fruVATspZYj+75tylXkeGCmEOAUcBRyBfH1mhBBv6VtZj/n77y3pW3ooHh7ODB3aifHj1zNhgj/161fHxEQA8PLLz/Ldd2Px9X0HR0c7vvxyT5nGUlLnzl3D1NSEnTsXs3XrfDZt+pWbN2OLX7GMpKamM2WKPx9++O+cm99JkwawdWsIr7++jNTUdMzN/1HDkh/JtWuxrFwZxLhxLxj8XaPRMnPmdv7znza4uVWumOCUR5KUdJ/g4At8//1HbN36MWlpGfz222mDMoGBZ+jRo3zGcT3pnJwc2LZtLn5+U/nwwwFMm7aGlJTSPbArK6tX72Dw4J5YWxtf64Qx580YNGrkiq/vCL76ajCbNh0zaFm8fz+DGTN28u67XbGxUePYCiKEQNefDEaOfJ7k5PuMHDmHLVsO0LBhjZx7KIDMzCyCg8/So0frMo1Jo5GcP3+XCRNaMX9+R0JCbnPqVCxZWVp27brO8uVd8PP7Fx4e9gQE/LMenPxTqbtGQN+aNgF4Rkp5Tz/pTGk+dTKllFL/u4bHl9f0XL9rADMhhCXwFdBWShkphJiBYawpJdiuAN6XUv5aVCEp5UpgJUB09PfZ7w8nJztiYh48IY+NTcTZ2d5g3ewyLi4OZGVpSElJx8HBGmdn+zzrJuR0A+zXrw39+umedq1c+TvOzrqnZlWrPmil69evDRMnFjx+JLeAgH1s23YQgMaNPYiOftClJCbmHs7OlQ3KOztXJibmXp4yVSjKr78epX37ppiZmVG1qj3Nm9cnPDwCd3fnQtdxdnbI9/7z5i67jItLZX3u0nLlLj7PurocZWVpmDrVn+efb0XXrg9ufmvXdmHp0jcB+PvvWEJCDLv0FWXLliC2bz8MQKNGtQ1aI2Nj4wvJ4YMyMTHxOfE9brrj60GrU2xsEk5OtnnK2BITo2td0mi0JCenY29vpS+fyLRpW5k4sS/u7ob/z4sW7cHdvSr9+xtOylAaxpY7Y4snt7K4nhw79hfVq1fJmQCrS5fGhIX9zfPP68bmxMenEB5+k1mzhhQbnzHnThfffrZtC9bH50FMTO5rXXy+65izs2FviYKuh3lZWJhjYWEOgJdXbdzdnfn77+h8E8pURGznzl1j374TrFjxE8nJqZiYCCwszBkwoHuR6xlz3p4UTk62Bt3zY2OTC7gO2xATo2t51Gi0pKSkY29veHtVu3ZVrKzMuXbtDp6e1cjK0jBjxk569PCkc+fHMza7Ij3Oa0jVqnbExSXg5ORAXFwCVaro7p9sbKyYOnUEoJsw5z//mYa7u1PONkJCzuHpWZOqVQ2vrQVxdLQkNvbBA424uLR83USzyzg5WaHRaElNzcTe3gJHR0uaNHHMmaSmbVsX/vorAWtr3XlQvbrumty5sxsBAVeKjcXYPQ2znv7TWxQ1gIcQIvtKMwLIns0jCcjuM2GProKVIISoBvR+TPvPvY8CSSmTgBv6GVLRj6EsapKd7LM1TghhC/QvZLvxQJIQop3+T4NzLf4VeEcIYa7fZ0MhhE0x7yWHl5c7N27cJSrqHpmZWQQGnqVjR8NxPh07erFnzykAgoLO07q1rq99x45eBAaeJSMji6ioe9y4cZdGjXT93HWzdkJ0dDwHD4bTs6euwhMX9+CD6NChcOrUcSk2xgEDnmPDhhls2DCDLl1asXv3EaSUnD37F7a21jg5VTYo7+RUGRsbK86e/QspJbt3H6FLl5ZF7sPVtSrHjukqXvfvpxMWdrXYcSpeXjWIjIwjKuoumZlZ7N17mo4dDRuvO3ZszO7dukl2Dxw4S+vW9fW5a8zevaf1ubtLZGQcjRrVRErJ3LkB1K7twuDBhg3m2TnVarWsXx/ISy8ZzgxalP79u+YMgu/SpQW7dx9FSklY2DVsbKxyur9kc3JywMbGkrCwa/ocHqVLl9L04C45L6/q3Lx5j1u34snM1LBvXzje3oY3FN7eDfj1V90EJkFBF2jVqhZCCJKT05g4cQtvvtmVZs1qGKyzZs1BUlLSGTOmxyPFZ2y5M7Z4ciuL60m1ag6cPx9JWloGUkqOH79K7doPHuAEBZ2nQwdPKlUyLzY+Y86dLr7uOZOldO3akl27QvXxXcXWtrD4rAgL043z3LUrlP9v777DoyqzB45/TxIgQBJaAgiCFOmgCNgAK+pasHcRXXXVde1lf1bEFftiwa4ICigWrKigIiiIgAqI0gUpC9Klt9Tz++O9k8yEJASEuW/I+TwPD5k7N5OTezN37nnLeY8+uuTiFuvWbSI3Nw+AP/5YzdKlq6hXr/gGsXjG9sor/+bjjx/h448f4cILu3H55afsNEmMV2y7e9zKipYt6/DHH+tZvnwD2dm5fPPNb3Tu3CRmnyOPbMJXX7l6A2PHzuOQQxogIixfviH/2KxcuZElS9ZRt24aqkrfvl/TsGFNzj9/7/Z+xcuevIZ07dqOESN+AGDEiB846ii3fdOmrWRnux7Z4cMn0L79gVStWjB8dNSoKZx4YqdSxdu8eXWWLdvCihVbyc7OY9y4ZRx+eOy9zeGH12H0aDcffPz45Rx0UDoiQseOGSxevJHt23PIzc1jxow/adgwlVq1klmyZBMbNrj+j59/Xk2DBiVP1TF+kIKOsH1L0NO2GTeUtC+ul+8n3BzFTBG5EbgBWKaqxwW9iJ2BJcAGYLiqvlHC8hj520Vks6qmBNvPA7qr6t9FpAvQH9czeB7QiyKWxxCRZsArQDqQDZwPNCRqeQwReR6YHMT0EHAxsAL4DVisqg8UjjVIEvsDebgEuZOqdhGRBOAh4HRc7+Jq4CxVLXYiTXSPIsDEib/x3HMjycvL49RTO3DZZccwYMBoWrSoT9euLcnMzObhhz9k3rzlpKZW5oEHzqdePTcHZPDgsYwYMZXExARuvPEUjjjCVRO94YbX2LBhG0lJCdxww8l07Ohq+jz00AfMm7ccEaFu3erccccZ+b2QAJUq1S8ubMC1rv33v28xadKM/OUxIi26l17qkklwy2M8+OCAoPR5O+644xJEhG+/nUrfvkNZv34TKSlVaN68Ac8+extbt26nT5+BLFy4PFjSoys9e+5YNS07O7Zi28SJs+nX71Py8vI47bRDufzybrz22pe0bLk/Xbu2ITMzmz593mHevGWkpVXhgQcuoX59N/l80KDRfP75TyQmJnDTTWdw5JEt+eWXhVx//Us0bVqXoK4R1157Mkce2Yr33hvPhx9OAOCYY9ryz3+ekr8PQGJi6doH3If3e/zwwywqVarIffddml/a/7LLHmHw4HuCY7iYhx4aQmZmNkcc0Zrbb78gOIbTeOqpYaxfv5mUlMo0b74/zzxzw05/7vbt/yv2uUmTfueFF0aTl6eccko7Lr20MwMHfkeLFnXp0qUZWVk5PPLIZ8ybt5K0tMr06nUG9epVZ8iQCQwdOimmJ/G//72AnJxcLrjgJRo2rJk/RPfssztw2mlF3wwmJ5dufkVYxy6MeM4+uxdbtmwnJyeHlJQq9Ot3A40b77dDDDu+J/b89WTgwDGMGTODxMQEmjXbj//7vzPz56LedNNAevQ4isMP37FKZYUKxRd6CPvY7az12sX3NpMmudL79913ef61rmfPPgwZ0iuIbxF9+gwiMzOLI49sy+23XxTE9zNPPvlOVHwN6NfvZsaMmUr//sNJSkpERLj66tM56qiSk6R4xRatf/9PqVKl0m4tjxH2catZc+fJ7c4MHTqUY489lvT0dFauXEnv3r0ZOHDgX37dJUteKPa5H35YyAsvjAuuw63p0eMwXn99Ii1a1KFz5ybBMkVfMn/+alJTk7nvvlOoV68ao0bN5u23J5OUlICI0LPn4XTt2pTp0//gllvep3HjWvlDJ6+6qjOHH150GYUGDa7/y78f7L1j9+efo2Ie/9VryIYNm7n33gGsXLmOunVr8tBDV1GtWlWmT19Anz5DEHHFle6551LS0lyfw7ZtmZx1Vi8++OA/pKRUjoqt+Gk8P/20kv79Z5KXp5x4YgMuvLA5b745h2bNqnP44XXJysrlySd/ZsGCDaSkVOTOOztQt667n/jmm6XBsFKhU6faXHmlawwfMWIRw4cvJClJyMiowq23tictrWKxMTRr1leKfdIT8+ffFdck6sADH4v7MdlnE0UDIpKiqpuDr+8C9lPVm3fybUUqnCj6ZGeJYtgK3xT7pLSJYlhKShTDVtpE0ezI5/dESYli2MrDMKfyak8kintLSYli2PZUori3FE4UfVJSouiDspAo/v77fXG9N27a9KG4HxP71Nm3nSYid+PO82Lg7+GGY4wxxhhjjCkLLFHch6nquwRVUI0xxhhjjDF7RnkY5bGvF7MxxhhjjDHGGLOL9v1U2BhjjDHGGGP2IJHEsEPY66xH0RhjjDHGGGNMDOtRNMYYY4wxxphdYHMUjTHGGGOMMcaUO/t+KmyMMcYYY4wxe5D1KBpjjDHGGGOMKXf2/VTYGGOMMcYYY/Yg61E0xhhjjDHGGFPu7PupsNkjEhNTwg6hWFu2zAo7hBJVqdI87BDKLJ+PnWpO2CEUy+fYABISksMOoUzy/bya3ffnn6PCDqFYPr9ffT5uALVqnRh2CMX68ssqYYdQombN+oYdwk5Zj6IxxhhjjDHGmHJn30+FjTHGGGOMMWYPEkkMO4S9znoUjTHGGGOMMcbEsETRGGOMMcYYY0wMG3pqjDHGGGOMMbvAitkYY4wxxhhjjCl39v1U2BhjjDHGGGP2IOtRNMYYY4wxxhhT7uz7qbAxxhhjjDHG7EHWo2iMMcYYY4wxptzZ91NhY4wxxhhjjNmDRBLDDmGv26OJoojUBZ4BDgXWAyuBW1T1t118nbOA31R11p6ML2wi0gm4TFVvivPP3ayqKSLSCPhMVdv+1ddUVZ555iMmTpxNcnJF7r33Ylq02H+H/ebMWcLDD79NZmY2Rx7ZiltuORsRYePGLfTqNYQVK9ZSt25N+vS5jLS0Knz33Qz69x+JiJCYmMDNN5/FwQc3AeCFFz5lwoRZqCqHHto8/7VK8uOPC3n++W/Iy1NOPbUtl1xyeMzzWVk5PPbYSH77bRVpacncf3936tatxuTJi+jf/ztycvJISkrg2muPoUOHhgCMHj2boUN/RARq1UrhnntOoVq1Krt9HJ966l0mTpxBpUoV6dXr77Rs2bCI47iYPn3eCI5jW2677UJEhNGjp/Daa5+yaNEKBg68i1atGgEwc+ZCHnvszeBnwD/+0Z1jjz1kn4mtIL63mTBhOsnJFenV60patjxgh/1mz15Enz4DyczMpnPndtx228VBfD/Rv/9wFi1azuuv35cfX3Z2Do8+Opg5cxYhItx228V07NhyN2Lz89ipKk8/PYwJE2YGx60nLVoUFdv/6NNnCJmZWXTu3IZbbz0/iG0qAwZ8zqJFKxkw4N+0anVAENsiHn98aH5sV111Ksce275UMU2aNJd+/T4hL0/p3v0wevY8Lub5rKwcHnroHebO/YO0tCo8+GAP9tuvJgBDhozhs89+IiFBuOWWMzn88BasXLmehx56h3XrNgPCGWcczgUXdI15zbffHssLL3zOZ5/1pnr1qmXy2P3VeDZs2EKvXgNZvvxP9tuvFg89dBVpaVXYuHErDz/8Jn/8sZqKFStw772X0rRpPTIzs7nuuqfJzs4hNzeX4447hKuv7m7Hbi8cu3jHB7Bp01YeffQtfv99OSJw772X0q5dk50ex71xHc7JyeHhhwcxd+5icnPzOOWUI/n7308rMZYwjtvixSvp1WtA/uv+8cefXH31aVx00fE7jbW0BgwYQPfu3Vm1ahXt2rXbY69bWrNmVeKDD6qTlycceeQWTjppU8zzY8akMHFiVRISlJSUPHr0WEfNmrkAvPhiOosWVaRJk0z++c8/4x67+ev22NBTcXfsHwHfqmpTVe0I3A3U2Y2XOwtovadiKw3ZQ80CUsKAZVWdHO8kcW+ZOHE2S5eu4d137+H//u98+vZ9v8j9+vZ9nzvvvIB3372HpUvXMGnSHMDd3HXq1Ix3372HTp2a8eabowHo2LEZgwbdwaBBd3DPPRfx2GPvATB9+kKmT1/I4MH/ZsiQ/2P27CX8/PPvJcaYm5tHv36jeeyxc3j99b8zZsxcFi2KvVCNHDmD1NRk3nzzKs47ryOvvjoOgGrVKvPww2czYMDl3HXXKTz66Mj813zhhW946qnzee21y2nSJJ2PPpr2F47jDJYsWcWwYX24++5LeeKJt4rc74knhnL33T0ZNqwPS5asYuLEmQA0aVKPxx77J+3bN4vZv2nT+rz++j0MGdKLZ565iccff4ucnNx9JjaACROms2TJSt5//xHuuusynnhiSDHxvcndd1/O++8/wpIlK5k4cUYQX30ef/x6Djmkecz+H3/s/gaGDn2Q5567nX793iMvL2+XYvP52E2cOJMlS1YzbNgD3HXXJTzxxDvFxPYOd999CcOGPcCSJauZNGlWEEM9Hn30Gtq3P7BQbPUYOPBOBg++h6efvp4nnni7VLHl5ubx1FMf0bfvVbz55u18/fU0Fi5cGbPPZ5/9SGpqZd59904uvPAoXnppBAALF67k669/YciQ23nyyX/w5JMfkZubR2JiAjfc0J0337yDV1+9ng8/nBDzmitXruenn+ZRp071XTl03h27vxrPkCFf0alTC4YNe4BOnVowZMhXAAwa9AXNm9fnzTfv5f77L+Ppp4cBULFiEs8/fxNDhtzD4MH3MGnSLGbMWGjHbi8cu3jHB/D00+9zxBGteffd+xky5B4aNaq70+O4t67Do0dPJisrm6FDH2TQoF58/PFYli1bs9N44n3cDjigDoMHu3P6+ut3kZxcgWOOOXince6KN954g5NPPnmPvmZp5eXBsGE1uO66Ndx77wqmTKnM8uWxt7n775/Nv/+9irvvXkX79tv4+ONq+c9167aJnj3XxjvsuBFJiuu/MOzJOYrHAdmq+nJkg6r+oqrficixIvJZZLuIPC8ifw++fkxEZonIryLSV0Q6A2cA/xWRaSLSVETai8ikYJ+PRKRG8L3fisjTIjJZRGaLyKEi8qGIzBORh6J+3qUi8mPweq9EkkIR2SwiT4rIL8CR0b+MiNwUFdc7wbaqIjIweK2fReTMYPvfRWS4iIwBRovIOyJyWtRrvSEi50UfBxFJEZHXRWR68DPODbafJCITRWSqiAwTkZTCB1pEDhSRr0Xkl2C/psHrjQ4eT4/EVhwRaRN1TH4VkWYl7V/Y+PEzOPnkTogIbds2YtOmbaxZszFmnzVrNrJlSyZt2zZCRDj55E589910AL77bgannHIoAKeccijjxrkPjSpVKuX3Em7fnkWkw1BEyMrKIScnh+zsHHJycqlZM7XEGOfMWUH9+tWpV686FSokcvzxLZgwYX7MPt9/P5+TTmoDwDHHNGfq1P+hqjRrVof0dHfoGzWqRVZWDllZOagqqrBtm/t669as/P12x7hxv3DqqUcEx7EJmzdvY82aDYWO4wa2bNlG27ZNEBFOPfUIxo2bBkDjxvtxwAE7fpgnJ1ckKcm1fWRlZe9zsbn4pnHKKZ0REdq1a8qmTVtZs2Z9ofjWs2XLNtq1a4qIcMopnRk79ucgvnpFxrdw4TI6dXI9iDVrppGaWpnZsxftYmz+Hrtx437llFMOD2JrXEJs22nbtnFw3A5n7NhfAGjUqC4HHLBj+9+OsZXc2x8xe/YS9t8/nfr1a1GhQhInnHAw48fPjNln/PhZnHJKJwCOPbYdU6bMR1UZP34mJ5xwMBUrJlGvXk323z+d2bOXkJ6elj/CoUqVZBo1qh3zOz733Kdcd92pOx2RUJhvx+6vxvPdd79y6qlulMWppx7OuHFu+6JFK+jYsUV+zCtWrGXt2o2ICFWqJAOQk5NLTk4epT2Edux27djFO77Nm7cxbdp8Tj+9MwAVKiSRmrrzkTJ76zoMwvbtWeTk5JKZmU1SUhJVqyaXIp74HrdokyfPpX79DPbbr9ZO49wV3333HWvXhpNsLV5ckfT0HNLTc0lKgo4dtzF9euWYfZo3z6RiRQWgUaMs1q8v6Hdp0SKT5GSNa8xmz9qT6WlbYMqufIOI1ALOBlqqqopIdVVdLyLDcUMk3w/2+xW4UVXHisiDQG/gluBlslS1k4jcDHwCdATWAr+LyNNAbeBCoIuqZovIi0APYDBQFfhBVW8vIry7gMaqmiki1YNt9wJjVPXKYNuPIvJ18FwH4CBVXSsiZwMXAJ+LSEWgG3AdED3usRewQVXbBb9jDRFJB+4DTlDVLSJyJ3Ab8GCh2N4CHlPVj0QkGZfwZwFnq+rG4HUmichwVS3uHfpPoJ+qvhXEuEs9qqtXb6R27er5j2vXrs7q1RtIT0+L2mcDtWsXtCxlZFRn9Wp3YV23blP+vrVqpbJuXcFQhrFjf+Xll0ewbt0m+va9GoC2bRvRocOBnHHGA6jCued2pVGjkjur16zZTO3aBclkenoqs2cvL3afxMQEqlatxMaN22KGko4bN49mzWpTsaJ7u9xyywn84x+DSE6uQP361bnppm47P2DFWL16PbVr18x/7I7jOtLTq0Xts46MjBpR+9Rg9er1O33tGTMW8vDDg1ixYi29e1+RfzO1L8QW+dl16kTH5352enr1Qr9D4fjWlfi6zZo14LvvpnHSSYezatVa5sxZzMqVa2nTpuQhWLGx+XvsVq/eENOT5t6X6wvFtr7I9/fOzJy5kIcffpMVK9Zy//2Xlyq2Ha8T1Zg1a0mx+yQlJVK1ajIbNmxl9eqNtGnTMOZ7C8e5fPlafvttGa1bu/2++24m6elpNGtWb6exFRWrb8fur8Szdu2m/H1r1Upj7Vp3HT7wwPp8++002rc/kJkzF7FixVpWrVpPzZpp5ObmccUVj7F06WrOPfcY2rRpvNM490SsJdkXj12840tIEKpXT+Ghh4Ywb94ftGzZkFtvPY/KlSvt5Djunetwt24dGTfuZ0477Ta2b8/illsuolq1nTfKhnFeI0aNmsyJJ3bcaYxlyfr1idSoUdBDX716LosWVSx2/4kTq9K69fZ4hOYFq3q6920AtgMDROQcYGvhHUSkGlBdVccGmwYBR0ftMjz4fzowU1WXq2omsABogEvSOgI/ici04HHkji8X+KCY2H4F3hKRS4GcYNtJwF3B63wLJAORu5RRqhpp8hkJHCcilYBTgHGquq3Q658AvBB5oKrrgCNwQ26/D37G5UDMYH8RSQXqq+pHwfdtV9WtuGbUR4Kk+mugPiUP+50I3BMkowcUER8ick3QWzt58OAvSnipv0ZEYlr2jznmIN5++y4ee+xK+vd3Qz6XLl3NokUr+eij3nz8cW+mTJnHtGkL9lpMEQsXruHVV8dx660nAq4lePjwX3jllZ4MG3YtTZpkMHToj3s9jt3Rtm1j3n77AQYOvJvBg78gM3P3e+/2NJ9jO/30rtSuXZO//70PTz31Du3aHUhiYtiXygI+H7s2bRozdGivYCjgV6HHtnVrJvfeO4Sbbz6dqlWT2b49i8GDx/CPf5wUalxFCfvYueuw+/qyy05i8+ZtXHbZI7z//rc0b74/CQnuycTEBAYPvodPPnmYWbMW8fvvy+IaZ1Hs2P31+HJz8/jttyWcc85RDB58N5UrV2Tw4K/iEl9RZs5cSGJiAp9//iQfffQ4Q4d+yR9/rI5rDKU9r+Dmto8fP51u3TrENUaf/PRTFZYsqUC3bpt2vrPZK0TkZBGZKyLzReSuIp6vJCLvBs//IK52SYn2ZCo8EzivmOdyiE1KkwFUNUdEDsMlb+cBNwC7OgM4M/g/L+rryOMkXAI1SFXvLuJ7t6tqcZMZTsMlpKcD94pIu+C1zlXVudE7isjhwJbIY1XdLiLfAn/D9WYWPUh+R4JLOC8u5f7RegAZQMeg53QRwXEuiqoOFZEfcL/nCBG5VlXHFNrnVeBVgDVrPtcPPhjP8OGTAGjVqgGrVq3P33fVqvVkZFSL/nYyMqqxalVBa/Dq1evJyHCtbzVqpLJmzUbS09NYs2Yj1avv2FLYvn1Tli37k/XrNzN27HTatDmAKlVc6+YRR7Rk5sxFtG9ffC9PenoKq1YVXLDWrNlERkZKkftkZKSSm5vHli2ZpKVVDuLdRO/ew7n77lOoX786APPnuw+qyONjj23B22/vWqL4/vvf8Mkn4wFo1aoRq1YVDClxx7FGzP4ZGbGtr6tWrSMjo3qpf17jxvtRuXIlFiz4I79QQFmMDWDYsDF88ombQ9i6dSNWroyOb8efnZFRnVWrCscX+zsUlpSUyK23XpT/+B//eIQGDXY+V8fnY/f++2MZPvz7ILYDWLlyff5z7n0Z+3PdcSvYp6j3d0kaNapLlSqVWLBgWX7RkeLseJ3YkH+dKLxP7drVycnJZcuW7VSrVoWMjLSYON33ujhzcnK5774hnHTSIRxzjCsA8ccff7J8+Vr+/vdn8ve/8sp+9O9/I7VqFT2U3bdjtyfjqVkzlTVrNpCeXo01azZQo4Y7BlWrVua++3oCrjjIOefcT/366TGvm5pahQ4dmjNp0qz8Yih7M9bSKOvHLsz4tm/PIiOjen4v53HHHZI/P6+weFyHv/zyB444oi1JSUnUrJnGQQcdyOzZi6hfP2OHfX04rxMnzqRFiwYxPYz7gurVc1m3rqCHfv36RKpX3/G2ec6cSnz5ZSo337yaChXiGWG4fOpRFDet7gXgRGAproNseKHCoFcB61T1QBG5CHgcl6cUa082k48BKonINVFBHyQiRwGLgdZBJlsdlxgSzL+rpqojgFuByAzgTUAqgKpuANYFrwPQE4j0LpbGaOA8Eakd/MyaIlLinYuIJAANVPUb4E6gGpACfAncKEH3l4iUVG7wXeAK4CigqO64UcD1UT+zBjAJ6CIiBwbbqopIzAxvVd0ELBVXGTbSOlAliHFVkCQeR6GeyCJ+xybAAlV9Fjdk96CS9gc33DNSaOboo9vxxReTUVVmzFhESkpyzLBTgPT0NKpWrcSMGYtQVb74YjJdu7qCq127tmHkyJ8AGDnyJ446ym1funQ1kdGyc+cuJSsrh2rVqlKnTg2mTfs9mNuRy7RpC4qcrxKtZcu6/PHHepYv30B2di5jxszlyCObxuzTuXNTvvrKzYcaO/Y3DjmkISLC5s3bufvuj/jHP46ibdv6Ub9TCosX/8n69a7ze8qUxRxwQE12xXnnHceQIb0YMqQXxxzTnhEjJgXHcQEpKZVjhsi4n1mNqlUrM2PGAlSVESMmcfTRJU+WX7ZsTX5Bh+XL/2Tx4hXst196id/je2wA559/PG+++QBvvvkARx99CCNHTkBVmT79d1JSqsQMd3LxVadq1cpMn/47qsrIkRM4+uj2Jf6M7dsz2bbNtTn98MNMEhMTaNJk58MUfT525513TH7BhaOPPpiRI38IYltI1arFxZbMjBkLg+P2A0cfXfIlYsfYVpZqrk7LlvuzZMkali1bS3Z2Dl9//QtdusTWMuvSpTUjR04G4Ntvp9Ohw4GICF26tObrr38hKyuHZcvWsmTJGlq1aoCq8uijwzjggNpcdFHBAJSmTffjs8968/77d/P++3eTkVGNgQNvLjZJ9PHY7cl4unZtx4gRPwAwYsQPHHWU275p01ays91AmuHDJ9C+/YFUrVqZdes2sWmTu/Zt357FTz/NKfE6bMdu145dmPHVqlWNOnVqsHixK/o0efLcYovZxOM6XLduTSZPdsXvtm3LZMaMBcXMZQz3uEWMGjWFE0/sVOLvVBY1bJjF6tVJrFmTSE4OTJlSmXbtYgegLVlSgXffrcE11/xJauquFX4ze9RhwHxVXaCqWbhOqsL1Ss7EjcwEeB/oFslpiiPFT2HbdSJSD7c8RkfckNJFuOUx5onIE7j5iAuBzbgho1/ikpRkXG9aX1UdJCJdgP64HsLzcEnjy0AV3JDSK1R1XdBrd4eqThaRY4OvuwexRD93Ia4CawKQDVyvqpMkWDaiiN+jAvANLvkS4E1VfUxEKge/X+fgtRaqandxhXk6qeoNhV5jJfCJql4RbMuPMUiSXwiOVS7wH1X9UESOx2X4kYkB96lqZHht5LWbAa8A6cHvcz6wEfgUl9BOxg1jPUVVF0kRy2MEXdI9g+9fAVwSNXR2B2vWfB7zh+JKYn/IpElzSE6uwD33XEyrVg0AuPzyvgwadAfgClVElsc44oiW3HbbOUh+CerBrFy5jrp1awTLY1TlzTdHM3LkZJKSEqlUqQLXX386Bx/chNzcPJ588n2mTVuAiHD44S256Sb395+Z+UdxYTNp0gJefPHboLx2Wy699Ahef/17mjevQ5cuB5KVlcMjj4xk/vxVpKYm06vXadSrV50hQybx9ts/UL9+QavnE0+cR40aVRg+/Bc+/HAqSUkJ1K6dxp13nky1apWLjaFKlebFPqeq9O37NpMmuVLe9913eX7vUM+efRgypFdwHBfRp88gMjOzOPLIttx++0WICN9++zNPPvkO69dvJiWlMs2bN6Bfv5sZOXISgwd/QVJSIiLCVVd155hj2hcbh6+xldRap6r8979vMWnSjPyy7JH4Lr3U3cRE4nvwwQHBEhTtuOOOS4L4ptK371DWr99ESkoVmjdvwLPP3sayZWu4+eanSEhIICOjOvfe+/cikzHVnB22+XLsdh7be/zwwywqVarIffddmt/7ctlljzB48D1BbIt56KEhwXu3NbfffkEQ2zSeempYVGz788wzNzBy5A8MGfJVEFsCV155SrHV/3Jzt8Q8njhxNv36fUpeXh6nnXYol1/ejdde+5KWLfena9c2ZGZm06fPO8ybt4y0tCo88MAl1K/vkoFBg0bz+ec/kZiYwE03ncGRR7bkl18Wcv31L9G0ad38Ye3XXnsyRx7ZKubnnnfeo7z22k0xy2MkJha/VIYPx25PxrNhw2buvXdAcB2uyUMPXUW1alWZPn0BffoMQcT1XN9zz6WkpVVh/vw/ePDBweTl5aGqHH98B6666tSdxmnHbtePXbzjA/jttyU8+uhQsrNzqF8/nXvv7UlaWhUSEoovIrO3rsNbt26nT5+BLFy4HFWle/eu9Oy5Y+XPvLzY+XBhHLdt2zI566xefPDBf0hJib0XqFXrxGKPXWkNHTqUY489lvT0dFauXEnv3r0ZOHDgX37dL78s3bJeM2cm88EH1VAVjjhiC3/72yY+/zyNhg2zaNduO889l87y5RVIS3MNNjVq5HLtta7C/NNPZ7BqVRKZmQlUrZrLJZeso1WrzJJ+XL6TTtqya9XGQlD43nhvy8jofi1wTdSmV4PRf4jIecDJqvqP4HFP4PBCucmMYJ+lwePfg32KLSm8RxNFs++K95thV5SUKPqgpETRlMynYR2FlZSMhc3n2GDHRNEnJSWKxpRHJSWKYSucKPpmTySKe0tpE8WwWKK4o/T004o9JnsrUfSnQoMxxhhjjDHGmF31B66IZ8T+wbYi9xHXEl8N+JMS+Ntcb4wxxhhjjDEeCpZl98VPQDMRaYxLCC8CLim0z3DcigoTcVP7xpSwjB5giaIxxhhjjDHGlFnBShI34Oq/JAIDVXWmuPXnJwf1TgYAQ0RkPm7N+YuKf0XHEkVjjDHGGGOM2QW+1VEIVpEYUWjb/VFfb8cVwCw1m6NojDHGGGOMMSaGX6mwMcYYY4wxxnjOtx7FvcF6FI0xxhhjjDHGxNj3U2FjjDHGGGOM2YOsR9EYY4wxxhhjTLmz76fCxhhjjDHGGLMHebaO4l5hPYrGGGOMMcYYY2JYj6IplZyc9WGHUKwKFWqFHUKJatQ4NuwQijVqVKWwQyhR27b9ww6hWDNmXB12CMWqX79H2CGUqFatv4UdQrFWr/4k7BCKlZp6SNghlKhSpXphh1CszMxlYYdQou3bF4cdQrEaNLgp7BCKtWTJs2GHUKIvv6wSdgjF+tvftoYdQolUw45g52yOojHGGGOMMcaYcmffT4WNMcYYY4wxZg+yHkVjjDHGGGOMMeXOvp8KG2OMMcYYY8weZD2KxhhjjDHGGGPKHUsUjTHGGGOMMcbE2Pf7TI0xxhhjjDFmDxJJDDuEvc56FI0xxhhjjDHGxLAeRWOMMcYYY4zZBVbMxhhjjDHGGGNMubPvp8LGGGOMMcYYsweVhx7Fff83LKNEpC7wDHAosB5YCXwMnKGq3UMLrAg//DCf5577kry8PE477RB69Oga83xWVg6PPPIxv/22nLS0yvTufR777VedDRu2cv/9w5g7dxknn9yeW245BYCtWzO58cY38r9/9eqNnHjiQdx4499KGc9v9Ov3GXl5eXTvfiiXXnrMDvE8/PAw5s79g7S0KvznPxez3341ABgy5Fs+/3wyCQkJ3Hxzdw4/vDkAmzZt4/HHP2ThwpWICHfddS5t2zbkhRdGMmHCbJKSkqhfvyZ3330uqamVd+s4qioPP/wwY8eOJTk5mccee4w2bdrssN+MGTO4++672b59O8cccwz33nsvIsKcOXPo3bs3W7dupX79+vTt25eUlJTdiqWwWbMq8/77NcnLg86dN3PSSRtinh89Oo2JE1NISICUlFwuvXQNNWvmAvDCC3VYtKgSTZps57rrVu2ReAB++OF3nn/+K3JzldNOa0+PHp1jns/KyuHRR4czd+4KqlWrzP33n53/d9e794fMmbOMk08+iFtuOTnq95jJm29+j4hQq1YK9957JtWrV/lLcfp27KZOXceAAQvIy4MTTqjDuefuH/N8dnYe/fr9xu+/byE1NYk77mhB7drJZGfn8fLLvzN//mYSEuCqq5rQtm01AB58cCbr1mWRm6u0apXGNdc0JTFRSh3TDz/M49lnR5CXp5x2WgcuvfTomOfde/ZDfvttGWlplXnggQvy37NvvjmOzz+fSkKCcPPNp3LYYc0AGDZsIp99NgVVpXv3jlxwgfv7ePHFL5kwYS5JSYnUr1+Tu+46q9TvWR+PXbQff1zMiy9+R16ecsoprbn44o6FjmMujz8+innzVpOWlsx99/2NunXTmDNnJU8//Q3grkOXXXYYXbs2BaBHj0FUrlyBxMQEEhOFF1+8sNTxxPNa/M030xk4cDSLF6/m1Vevo2XL/QuHU2aOW2FTpqzi1VdnkJennHRSQ84/v1nM89nZuTz11DTmz19PampF7ryzI3XquOvWwoUbef75X9m2LRsR4emnj6JixUTGjv2D996bhwjUrJnM7bcfQrVqlXY5NlXl8cdfZPz4H0lOrkSfPv+mVatmO+w3a9Zv9Or1XzIzs+ja9TDuvPNfiAgvvTSYDz4YQc2a7v1w441XctRRhzN9+hz69Hk6+Bnwz3/2pFu3rju87s74fOxij08lPvigOnl5wpFHbuGkkzbFPD9mTAoTJ1YlIUFJScmjR491+Z8TL76YzqJFFWnSJJN//vPPvxTH7hgwYADdu3dn1apVtGvXLu4/3+xdNvTUQyIiwEfAt6raVFU7AncDdf7i6+7xhoHc3DyeeWYkTzxxCYMG/YvRo2eyaNHqmH0+//xnUlMrM3TojZx//hG88srXAFSsmMRVVx3HddedGLN/lSqVGDDg2vx/depU5+ijW5Y6nqeeGk7fvn9nyJBb+PrrX1i4cGWheCaTmlqZd965gwsu6MLLL38BwMKFKxk9+lcGD76Fvn3/zlNPDSc3Nw+AZ5/9jMMPb85bb93G66/fyAEHZABw6KEHMmjQzQwadBMNGqTz5ptjd/0gBsaNG8eiRYv46quv6NOnDw888ECR+z3wwAP06dOHr776ikWLFjFu3DgA7r33Xm6//XY+/fRTTjjhBF577bXdjiVaXh68915N/vWvldx33x9MmVKV5csrxOzToEEW//d/y7nnnmUccshWPv64Zv5zJ5ywgcsuW134Zf+S3Nw8+vX7gscfv4hBg65lzJgd/+5GjJhGSkoyQ4f+i/POO4xXXx0DuL+7K688huuu6xazf05OHs899xVPP30pAwdeTdOmtfnoo8l/KU7fjl1urvLqqwvo1asNzz57COPHr2bJkq0x+3z99UqqVk3ipZc6cvrp9Rg8eBEAo0a591G/fofQu3cbXn99IXl5CsAdd7Tg6acPoV+/Q9i4MYcJE9bsQkx5PP30Z/z3vz0ZPPgGRo+ezqJFsUnx559PJTU1mbffvoULLujMyy+PAmDRolWMHj2dQYNu4L//vYynnvqM3Nw8FixYyWefTeGVV65h4MB/MXHibyxd6m6gOnVqyhtvXM8bb1zP/vvX4s03vyuzx67wcXzuubE88sjpDBhwCd988xuLF6+N2WfkyFmkplZi8OCenHvuwfTvPwGARo1q8uKLF/DKKxfx6KNn8Mwz3+Zf+wCefPJsXnnlol1KduJ9LW7cuA4PP9yDgw9uVKaP247xKS+9NJ3//OdwXnzxOMaOXcb//hebRHz11RKqVq1A//7dOPPMJrzxxuz83+3JJ6dy/fXtePHF43j00c4kJiaQm5vHq6/O4JFHjuT554+lUaM0Pvts0W7FN378j/zvf3/w6advcP/9t/DQQ88Wud9DDz1L79638umnb/C///3B99//lP9cz57n8t57r/Dee69w1FGHA3DggY0YOvRF3nvvFV588RH69OlHTk7uLsXm+7GLyMuDYcNqcN11a7j33hVMmVKZ5ctjb9f23z+bf/97FXffvYr27bfx8cfV8p/r1m0TPXuuLfyycfPGG29w8skn73zHfZBIUlz/hcESRT8dB2Sr6suRDar6C/AdkCIi74vIHBF5K0gqEZFFIpIefN1JRL4Nvn5ARIaIyPfAkODxQBH5VkQWiMhNfyXQ2bP/oH79GtSrV4MKFRI5/vg2jB8/N2af77+fy9/+dhAAxxzTmqlTF6KqVK5ckYMOakjFisX/8S9Z8ifr1m3hoIMaljKepdSvX4t69WpSoUIS3bodxPjxs2P2+e672Zx8cgcAjj22LVOm/I6qMn78bLp1O4iKFZOoV68m9evXYvbspWzevJ1ffllE9+6dAKhQISm/B+Kww5qRlOTKI7dp04DVq2N7i3bF6NGjOeussxAR2rdvz8aNG1m1KvaGedWqVWzevJn27dsjIpx11lmMHj0agEWLFnHooYcC0KVLF7766qvdjiXaokWVSE/PIT09h6Qk6NBhC7/+GtvL1rz5dipWdDe+jRplsn59QcnoFi22U6mS7pFYIubMWUb9+jWj/u5a8/33v8Xs8/338zj55MjfXSumTFkU9XfXoIi/O0UVtm/PRlXZsiWT9PS/1iPr27GbN28T++2XTN26yVSokEDXrhn8+GPsDcaPP67luONqA9C5czq//roBVWXJkq20a+duTqpXr0jVqknMn78ZgCpV3LHMzVVycvKQXegQc+/ZmlHv2XaMHz8nZp/x42dz8sntgcg1ZEHwnp1Dt27tgvdsDerXr8ns2UtZvHg1rVrtT3JyRZKSEmnfvhHjxs0C4LDDDox6z+7P6tUby+yxizZ37krq1atGvXrVqFAhkWOPbcb33y+I2WfChAWcdJJrdDv66AP5+eelqCrJya7nC1zv2Z4Q72txo0a1adgwY5fj9O24Ffbbb+vYb7+q1K1blQoVEjj66HpMmrQiZp9Jk1bQrZvrQe3adT9++WU1qsrUqatp1CiNJk3c315aWkUSEwVV10uXmZmLqrJ1aw61aiXvVnzffDOR008/ARHhoINas2nTZlavju3VWr36T7Zs2cpBB7VGRDj99BMYM2ZCia9buXJy/vs0MzNrt94Xvh+7iMWLKwafE7kkJUHHjtuYPj12lEPz5plRnxNZhT4nMklO3rOfsbviu+++Y+3a8BJVs3fZ0FM/tQWmFPPcIUAbYBnwPdAFGL+T12sNdFXVbSLyANASl4ymAnNF5CVVzd6dQNes2UTt2gUtWxkZacye/Uex+yQlJVC1ajIbNmwr1ZC+0aNncPzx7sOlNFav3lAonmrMnr2kUDwbouJJDOLZypo1G2ndukH+frVrp7F69QYqVUqievWqPPLIB/z++3KaN6/PzTd3p3LlijGv+/nnUzj++N0fdrFy5Urq1q2b/7hu3bqsXLmS2rVr73QfgGbNmjF69GhOOOEEvvjiC5YvX77bsUTbsCGRGjVy8h/XqJHDokXFD7OZODGF1q237ZGfXZzVqzeRkZGa/zgjI41Zs/4oYp80wP3dpaRUKvHvLikpkVtvPZkrr3yV5OQK7L9/zZhhqbvDt2O3dm0W6ekFf7e1alXkt99iW9j//DOL9HQXY2KiUKVKEps25dC4cVV+/HEtRx2VwZo1mfz++2b+/DMTdxmB//xnJvPmbaJDhxoceWR6qWMq6hoya9bSYvdx79lKbNiwldWrN9KmTYOo763GmjWbaNy4Dv37j2bDhq1UqpTEpEm/0aJF/R1+9ogRU0v9nvXx2EVbs2YLtWtHvydSmDMntgfvzz+35L9vEhMTqFq1Ihs3bqdatcrMnr2Cvn3HsHLlJu6664T8BEgE7rxzOCJw2mlt6N69baniCfNavCt8O26F/fnndjIyCpKG9PRk5s5dX+w+iYkJVKlSgY0bs1i2bAsi0KvXJDZuzOSoo+pz3nkHkpSUwL/+1Y7rrx9LcnIi9epV5brrdu+za9WqNdSpU/AZVadOOqtWrSEjo1ahfdKj9slg1aqCnvN33vmETz8dRevWzbnjjmtJS3PH+tdfZ9O795MsX76Shx++Mz9xLC3fj13E+vWJ1KhR0NBQvXouixYV/zc9cWJVWrfe/pd+ptkzysMcRetRLHt+VNWlqpoHTAMaleJ7hqtq9N3n56qaqaprgFUUM6RVRK4RkckiMnnIkDF/Ne7dMmbMTLp1270P2D0lNzeP335bxllnHc7AgTdSuXIF3nordojp4MHfkJiYwEkntQ8nSODhhx9m6NChnHPOOWzZsoWKFXf/5ml3/fhjVf73v0p067b7PathycnJZfjwqfTv/w8++OBmmjSpzVtvldzqvSf5fuy6datDenpF7rjjFwYMWEjLlmkkJBQ04PTu3YaBAw8jO1uZPj3c36FRowwuuaQrt98+iDvuGMKBB+4XEyvA4MFjSUxM5MQTD9rr8ZSFY9eqVV0GDLiEF144n7ffnkJWlmvgeOaZc3n55Qt55JHTGT58Or/++sdOXmnvKc21ON58Pm65ucqsWWu5445DePzxLkycuIJp01aTk5PHiBGLefbZoxk8+EQaNUpj2LB5cY8P4IILTuezzwbx3nsvk5FRk759X8l/7qCDWvHRR68xdOjzDBjwDpmZWXGLy9dj99NPVViypALdum3a+c7G7AGWKPppJtCxmOcyo77OpaBXOIeC81l4HMSWUr5GDFV9VVU7qWqnnj2PLzKY9PRUVq0quLFZvXoj6empxe6Tk5PHli2uJXZn5s9fQW5uHi1a1NvpvhEZGdUKxbOB9PS0QvFUi4onN4inCunpaTHfu2rVRjIyqgX/0vJ7Lo49ti1z5y7L32/EiClMmDCH+++/oNQ9nxFvvfUWZ555JmeeeSYZGRmsWFEwLGbFihXUqRObw9epU6fYfZo2bcrAgQP58MMPOe2002jQoAF7QrVquaxbV/Ansm5dEtWq7TjMas6cZL78shrXXruSChV2eHqPyshIZfXqgg/K1as3xvQwFuzjhhXm5OSxeXNmiX938+e7XoT69WsgIhx3XGtmzlxa7P6l4duxq1mzImvWFNxs/flnFrVqxfZw1qpVkTVr3CUiN9cNrUpNTSIxUbjyyiY8/XR77rmnFVu25FCvXuzxrFgxgcMOq8mPP5a+oEJR15BIT3BR+7j3bCbVqlUhIyOtiPe7+zvo3r0jr712Hc8/fxWpqck0aFDQozFy5M9MnDiXXr3OLfV71sdjFy09vSqrVkW/JzZTq1bVQvFVzX/f5ObmsWVLFmlpsR8XBxxQk8qVK7Bw4Z/B67rh1zVqVKFLlyY79LYVJ4xr8e7w7bgVVqtWMqtXF7TzrlmzfYehjtH75ObmsXVrNmlpFalVK5k2bWpRrVolkpOT6NSpNr//voEFC9x1cb/9qiIiHHVUPWbPXlfqmN555xMuuOBaLrjgWjIyarJyZcEUiZUr11C7dmyveO3a6axcuSZqn9X5+9SqVYPExEQSEhI455xTmTEjduoKQJMmB1ClSmXmz19Y6hjda/t37IpSvXou69YV9JauX59I9epFfU5U4ssvU7nmmj/3+mesKR2RxLj+C4Mlin4aA1QSkWsiG0TkIOCoEr5nEQXJ5bl7L7RYLVvWZ+nStSxfvo7s7FzGjJlJly7NY/bp0qUFX375KwBjx87ikEMal+rmbPToGbvcm+jiWcOyZWvJzs5h9Ohf6dq1Vcw+Xbu25IsvpgLw7bcz6NChCSJC166tGD36V7Kycli2bC1Ll66hVav9qVUrldq1q/G//7miIlOm/E6jRm6ozQ8//MbQoeN49NGeJCfveg9ejx49+OSTT/jkk0844YQT+Pjjj1FVpk2bRmpqasywU4DatWuTkpLCtGnTUFU+/vhjunVzRVn+/NPdoOTl5fHSSy9x0UUX7XI8RTnggExWr05izZokcnJg6tSqHHRQbBGPJUsq8s47tbj22lWkpuYV80p7TosW9YK/u/XB390sOneO/bvr3LkZX3wR+bubTYcOjUr8u0tPT2XRotWsX+/aVSZPXsABB+zeMMAI345ds2apLF++jZUrt5Odncf48as59NCaMfscemhNvvnG3fhNmLCGdu2qISJkZuayfbu7eZk2bT2JiUKDBlXYti2XtWtdApWbq0yZspb99y99pdjINWTZsnXBe3Y6XbrEFq/q0qUlX3wxDXDXkA4d3DWkS5eWjB49PXjPrmPp0rW0auXmG61b5+YArly5nnHjZnPCCW542A8/zGPo0PE8+miPXXrP+njsorVoUYc//tjA8uUbyc7O5dtv59G5c+OYfTp3bsxXX7n5n+PGzad9+/0REZYv35hfhGXlyo0sWbKOunXT2LYtm61bXXzbtmUzZcoSGjWqRWnE+1q8u3w7boU1b16dZcu2sGLFVrKz8xg3bhmHH143Zp/DD6/D6NGuUWv8+OUcdFA6IkLHjhksXryR7dtzyM3NY8aMP2nYMJVatZJZsmQTGza4Ro2ff15Ngwaln4990UVn5hefOe64Lnz66deoKr/+OouUlKoxw04BMjJqUbVqFX79dRaqyqeffs1xxx0JEDOfccyY7znwwEYALF26PL94zbJlK1m06H/Uqxf7e5fFY1eUhg2zgs+JRHJyYMqUyrRrFzsFYcmSCrz7bg2uuebPuHzGGhMhquFNgDXFE5F6uOUxOgLbcYngx8CZkeUxROR5YLKqviEiRwEDgI3At0AnVT02mJO4WVX7Bt9T+PEMoLuqLiopnhUr3ir2D2XSpHnB8hjKqae2p2fPoxgw4BtatqxHly4tyMzM4eGHP2L+/BWkplamd+9zqVfPlUC/8MJ+bNmSSU5OLikpyfTteymNGrmCBBdd9CyPP37JTm/WExJiWwgnTpzLs89+FpTa78hllx3Ha6+NomXL/enatRWZmdk89NAw5s1bRlpaFR544CLq1XM3fIMHf8Pnn08hMTGBm246jSOOaAHAvHnLePzxj8jOzqVevRrcc895pKZW5qKL+pKdnUtamru5a9OmAXfccVZMPLVrly5vV1UefPBBvvvuOypXrswjjzySX2r6zDPP5JNPPgFg+vTp+ctjHH300fTq1QsRYdCgQQwdOhSAE088kdtvv32nCfmoUaUr6T1zplviQRWOOGIzJ5+8gc8+q07DhpkcdNA2nnuuDsuWVSQtzX2w16iRwz//6W6Yn366LitXViAzU6haNY9LLllT6vkVbdv2L/a5SZPm8/zzo8jLy+OUUw6mZ8+uDBw4lhYt9qNLl+ZkZubwyCOfMG/eStLSkrn//rOj/u6eZ+vWTLKzI393F9OoUQaffDKFDz74iaSkROrUSeOuu06nWrWib9xnzLja22NXv36PYp+bMmUtAwYsJC8PunWrzfnnN2Do0MUceGAKhx1Wi6ysPJ555jcWLtxCSkoSt9/egrp1k1m1ajv/+c/MYOmQilx//YHUrp3M+vVZPPzwbLKz88jLg3btqnHllY1LXOKhVq3YpW4mTvyN554bSV5eHqee2oHLLjuGAQNG06JFfbp2bUlmZjYPP/wh8+YtJzW1Mg88cH7Ue3YsI0ZMJTExgRtvPIUjjnANBjfc8BobNmwjKSmBG244mY4d3bIFF1/8DFlZOfnntXXr/bnjjjPyY/nzzy+9PXapqYcUGxvADz8syl/m4eSTW9OjRyfeeOMHmjevTefOjcnKyuGxx0Yxf/4aUlMrce+9f6NevWqMGjWHd96ZSlJSAiJCz56H0qVLE5Yt28ADD4wAXCJ7/PHN6dGjU7E/v1Kl2NEf8bwWjxs3k2ee+ZT167eQkpLMgQfW46mnrsiPJTOz+J7HsI8bwPbti4t97qefVtK//0zy8pQTT2zAhRc2580359CsWXUOP7wuWVm5PPnkzyxYsIGUlIrceWcH6tZ1vaLffLM0GBopdOpUmyuvbA3AiBGLGD58IUlJQkZGFW69tT1paUU3nDRoUHzNO1Xl0Uef4/vvJ5OcXIkHH7yDNm3cubrggmt57z03lHTmzLn06tWXzMxMunQ5lLvvvgER4Z57HmPu3N8REerVq0OvXreQkVGLTz8dxcCB71KhQiIiCVx77aUcf3yXHX7+kiVFV1n15dgtXPhSifFFzJyZzAcfVENVOOKILfztb5v4/PM0GjbMol277Tz3XDrLl1eI+pzI5dprXZL99NMZrFqVRGZmAlWr5nLJJeto1SqzpB8HwN/+tnWn+5TG0KFDOfbYY0lPT2flypX07t2bgQMH/uXXVdXdLO0VP9nZf8Y1iapQoVbcj4kliqZUSkoUw1Y4UfRNaRPFMJQ2UQxLSYli2EqbKIahpETRB4UTRZ+UlCiGbWeJYtgKJ4o+KSlR9EFJiWLYSkoUw7azRDFspU0Uw7CnEsW9xRLFHYWRKO775XqMMcYYY4wxZg+yqqfGGGOMMcYYY8odSxSNMcYYY4wxxsTY9/tMjTHGGGOMMWYPsqGnxhhjjDHGGGPKnX0/FTbGGGOMMcaYPUgkMewQ9jrrUTTGGGOMMcYYE8N6FI0xxhhjjDFmF9gcRWOMMcYYY4wx5c6+nwobY4wxxhhjzB5kPYrGGGOMMcYYY8odUdWwYzDlkIhco6qvhh1HUSy23edzfD7HBn7HZ7HtPp/j8zk28Ds+i233+Ryfxbb7fI/P7B7rUTRhuSbsAEpgse0+n+PzOTbwOz6Lbff5HJ/PsYHf8Vlsu8/n+Cy23ed7fGY3WKJojDHGGGOMMSaGJYrGGGOMMcYYY2JYomjC4vM4dott9/kcn8+xgd/xWWy7z+f4fI4N/I7PYtt9Psdnse0+3+Mzu8GK2RhjjDHGGGOMiWE9isYYY4wxxhhjYliiaIwxxhhjjDEmhiWKxhhjjDHGGGNiWKJo4kJEMkTkHhF5VUQGRv6FHReAOJeKyP3B44YicljYcRUmIjVE5KCw44gmIueLSGrw9X0i8qGIdAg7LgARuVlE0oLzO0BEporISWHHBSAiVUSkl4j0Dx43E5HuYccVISJNRaRS8PWxInKTiFQPOSwARKSLiFQNvr5URJ4SkQPCjiuaiHQVkSuCrzNEpHHYMRXm2/VERKqKSELwdXMROUNEKoQdVzQRqSwiLcKOozDfj53P1xMAETlARE4Ivq4c+UwLm+/HzZQPliiaePkEqAZ8DXwe9c8HLwJHAhcHjzcBL4QXTgER+TZIdmoCU4H+IvJU2HFF6aWqm0SkK3ACMAB4KeSYIq5U1Y3ASUANoCfwWLgh5XsdyMT93QH8ATwUXjg7+ADIFZEDcZXsGgBDww0p30vAVhE5GLgd+B0YHG5IBUSkN3AncHewqQLwZngRFfD8ejIOSBaR+sBXuPfrG6FGFEVETgemAV8Ej9uLyPBQgyrg9bHD4+uJiFwNvA+8EmzaH/g4tIBieXvcIkQkUUTqBQ3sDUWkYdgxmT3LEkUTL1VU9U5VfU9VP4j8CzuowOGqej2wHUBV1wEVww0pX7Ug2TkHGKyqh+MSMl/kBv+fBryqqp/jz7GT4P9TgSGqOjNqW9iaquoTQDaAqm7Fn9gA8lQ1BzgbeE5V/w3sF3JMETnqynWfCTyvqi8AXvQABM4GzgC2AKjqMvyJz+friQTvg3OAF1X1fKBNyDFFewA4DFgPoKrTAF96in0/dj5fT64HugAbAVR1HlA71IgK+HzcEJEbgZXAKAoa/z8LNSizx1miaOLlMxE5NewgipEtIomAghsqBuSFG1K+JBHZD7gAPy/Af4jIK8CFwIhgmIwv15UpIvIVLlH8MhhO5Mt5zRKRyhT8zTXF9TD6IltELgYup+DvzpehbJtE5G7gUuDzYMidL7EBZAWJbOTcVg05nmg+X09ERI4EelAw2iQxxHgKy1bVDYW2+bK+mPfHzuPrSaaqZkUeiEgS/pxXn48bwM1AC1Vto6rtgn/eDGc3e4YvN3RmHyUim0RkI+6C8pmIbBORjVHbffAs8BFQW0QeBsYDj4QbUr4HgS+B31X1JxFpAswLOaZoF+Di+5uqrgdqAv8ONaICVwF3AYcGre0VgSvCDSlfb9wQtgYi8hYwGvi/cEOKcQVuWOzDqrowmGM3JOSYIi7EJdVXqeoK3FCx/4YbUoz3gsaT6sGwtq+B/iHHFOHz9eQW3HDdj1R1ZhDbN+GGFGOmiFwCJAZzip8DJoQdVOAW/D52Pl9PxorIPUBlETkRGAZ8GnJMET4fN4AlQOHGE7OPEdfwaUz5JiItgW644X+jVXV2yCGVGcH8xGaq+nrQG5uiqgtDjKfEYjqqOjVesZRERGoBR+D+5iap6pqQQ4oR9Hg2VNW5YcdS1gQ3nCfhzu2Xqjoq5JDMXyQiVYB7iTqvQB9V3R5qYFFEpErQKGZKKRiRcBWx5/U1tZvjnRKRAUALXC92/ogYVfVl3rPZAyxRNHEhIqNVtdvOtsU5ppolPa+qa+MVS3FEpDmueEcdVW0bVCk8Q1W9KHwSFO7ohBt+0lxE6gHDVLVLiDGV1JKuqnp83IIpRjHJ7AZgcTAnJVRB4Y6+QEVVbSwi7YEHVfWMEGPaRNFDwgR3XtPiHFKZ4+P1REQ+pYShfmH+zZUVwbDTAbhGuoZBoadrVfVfIcc1nZLPrQ1TLEJZOW7B5/8OVPU/8Y7F7D2WKJq9SkSSgarAGOBYCgp2pAFfqGrLkEJDRBbiLsYCNATWBV9XB/6nqqEXKhCRsbihnK+o6iHBthmq2jbcyBwRmQYcAkyNiu9XXz7IfCUik4AOwK+4v7m2wExcZeDrVPWrEMNDRKYAxwPf+vh357NiEtoNwGTgdlVdEP+oHB+vJyJyTEnPq+rYeMVSkmIS2sh5fSXMnkUR+QE4Dxjuy3kNYihx2RpVXRyvWIpTTFIWOa8PqeqfIcRUFo5bIq4gVo+wYzF7V1LYAZh93rW4+RP1cOXYIzYCz4cRUEQkERS3lt1HqjoieHwKcFaIoUWroqo/isQUxAy9xylKlqqqiHhTuENEzinpeVX9MF6xlGAZbo7dTAARaY2bP/Z/wIe4EvdhylbVDYX+7kItBFQWRgAEngGW4srYC3AR0BR3/RuIazALi3fXE18SwVJYAGQAbwePL8QtpdQcNwe1Z0hxAaCqSwqd19zi9o0XHxKaUhiJO1aRZScuAqoAK3BLjJwe74DKwnFT1Vxx609WjC4GZPY9liiavUpV+wH9RORGVX0u7HiKcYSqXh15oKojReSJMAOKsiaoiBlJxM4DlocbUozChTuuBF4LOaaSPtgVl4iFrXkkSQRQ1Vki0lJVFxS62QtLTOEO4CbCL9wxhYIRAIUp0CS+4RTrDFU9OOrxqyIyTVXvDIpmhMm760lZGWYHdFbVQ6MefyoiP6nqoSIys9jvio8lItIZUBGpgCseF/o8+zIyXPwEVY2eCjBdRKaqagcRuTSMgMrIcQPXePK9uPVEt0Q22hzFfYsliiZe/iiip2cDMF1VV4URUJRlInIfBYti98D1+PjgetxCuy1F5A9gIW5ZAC+oat+gcMdG3KT2+8Mu3KGqvlQ2LcksEXkJeCd4fGGwrRLB2oohuxFXuCMT19L+JdAnzIB8GApeSltF5ALcIt7ghgRGhiWGPdejqOtJ2EPHuof880srRUQaqur/AMQtLJ4SPBd2j8o/gX5AfeAP3IiEUOcnAqiqL+uHliRRRA5T1R8BRORQCpYWCaW3vYwcN4Dfg38J+LNWrNnDbI6iiQsR+RxX5jlSaORYXA9BY1yRjNBKPgdD2noDRwebxgH/8WgoW2RIZ4Kqbgo7lmgi8riq3rmzbWERkdNwC08nR7ap6oPhReQEFUX/BXQNNn0PvIhLKKqo6uawYgMQkfNVddjOtoVFRGoAzYg9r+PCi6hAsDRBP9z1ToFJwK24G/iOqjo+xNgaB2X2868nkW1hxVRWBFMSXsHdGAvus+tfwLfA1ar6TIixdVHV73e2LWwiUpvY9+z/QgwHABHpBLxOQdK/CVcFdRZwmqq+F1ZsET4eN1N+WKJo4kLcwuc9VXVl8LgOMBi4GBgX9qR7AHELsmvYN+nRROS2IjZvAKao6rQ4h7ODyBCdQtu8KGYjIi/j5pochxsOex7wo6peFXJcicDXqnpcmHGUpJjzusO2MIjIP3BD6/YHpuGWGJnoSTXbROBxVb0j7FiKUsx5naKqHcOKKSqOI4DngFa4NU8TgS0+DLMTt4TCecAnQKQA29wwC9hE8/n9CiAiZwBP4moVrAIOAGarapuQ40oEblLVp0WkGoCqerMuoK/HLSKoML5DEuHDtdjsOTb01MTL/pEkMbAKaKCqa0Uk1KF2ItIOl7TWDB6vAS5X1RlhxhXoFPyLLADcHVcp858iMkxVQ5lLKSLX4VrTm4jIr1FPpeJ6x3zQWVUPChLX/4jIk7jCBaEKigDkiUg1n25KIL/X5FSgvog8G/VUGv4UUboZOBS39uRx4tZAfSTkmID8c9t153vGV3CM2gDVCk0BSCOqpyJkz+MKiQzDXfMuwxWKCZ2q5onI/wW9S7+EHU+EuGUxOgMZhRoV0ygYPumDPrgGna9V9RAROQ4PplAE79eLgad9uxYHvDxuUaIbxJKBc/Hnc8LsIZYomnj5VkQ+w90EgLugfBsMgVofWlTOK8BtqvoNgIgci5vH0znEmCL2BzpEejnFrVv0OW6Y7BQgrKI7Q3FJ16PAXVHbN3k0ZHdb8P9Wces7/gnsF2I80TbjiiaMIrYIwE3hhQS4ubmTgTNwf18Rm3DDJ32wXVW3iwgiUklV54hIi7CDivJzUNxhGLHnNswiSi1wjUzViS32tAm4uqhvCIOqzheRRFXNBV4XkZ+Bu8OOK/C1iNwBvEvseQ3zelcRN2Qyidg5YhtxPaC+yFbVP0UkQUQSVPUbEXkm7KAC34vI8+x4XqcW/y1x4/NxQ1WnFNr0vYj8GEowZq+xRNHEy/W45DCyEPtg4AN1Y5/DHoJXNZIkAqhqJIH1QW1cQZGIbNxi2dtEJLOY79nrgtbXDSJSeC5iioikeDKH4jMRqQ78F7c0gRJ+RdaID/Gj+moMVf0F+EVE3lJVX1uGlwbn9WNglIisA3wqJ5+Ma5SIHn4VarVdVf0E+EREjlTViWHFsRNbRaQiME1c1enluCIZvrgw+P/6qG2hVtsNlhYZKyJveL6kwnoRScHN/39LRFYRlZSFrH3wf/TcdSX2/RsWn49b4SWLEoCOuLWAzT7E5iiack9EPsIlEpGCOpfiik6cHV5Ujoj0As7GzY0B1xswHDdv4VUNebFbKShtL7gb5Ma4uTtezKGICKqJJns6vMg7IrKQouee+LIEBZC/WHs14Au1tbx2SkRep+jzemUI4cQQt8j4Slwv2a248/qiqs4PNbAywPe5YkHD6zZcMtEDd27f0hAWsy9LfD9uUZ8TghtyuhBXnDC0gl1mz7NE0cRFMC/mcVwPmeDRekBBBcX/4CpQKvAdrurpulADCwTluiPDYL9X1clhxlMSEekA/EtV/+FBLNfjPlTXB49rABer6ouhBuZiaYYbttua2Gp2XiRiIlIr6mEycD5QU1XvDymkfEHRk5mRCsAikga0UtUfwo3MEZFkXNXEwtV2fUjGzo16mIxrhFrmwZDn/JtiVc0LHicClVR1a7iRFRCRtuz4nh0cXkSOiEQXI8qfK6aq/xdSSDFEpDGwPFL8R1zV5zqquijUwALib3Vsr4+bKR8sUTRxISLzgdNVNfRFgMuislQeW0Smq2o7D+KYpqrtC237WVUPCSmk6DjG45ZkeRrXS3wFbrmC0BOx4nhUHfNn3LzdyKLxCcBkjyo8DgPmAJfghrP1wFUqvDnUwIoQHLvxqhr6fGwRmYRb/DwyHzsF+MqH2CB/fvixuERxBHAK7tj5NBcwn4j8qKqHhR0HgIhMxhUXywoeV8Q1eh4abmT+VscGv49bhIh0BhoRNZXNh8YTs+fYHEUTLyt9TRKDgiLnF+p5ekdV/xZqYBRZHrsh7ibUi6GdhSrtJQAdcAVRfJAoIhKVUCTihrX5oLKqjg7iWww8ICJTAC8SxaBnOCIBV4XSl8+L/HMK+RUpfYkN4EBVPV9EzlTVQSIyFDdKwUfNcKM8fJCsUUsTqepmEakSZkCFnAccDPysqleIW+LpzZBjAsrEXLGk6KHhqpoVJD0+8LI6dsDn44aIDAGa4pYpyg02K64GhdlH+PThavZtk0XkXVwBivwiLCFXAoxIjySJAKq6LujB84Hv5bGjK+3l4CqyfhBSLIV9AbwrIq8Ej68NtvkgM+jNmSciN+AWY0/ZyffE05NRX+cAi4ALwgllBwtE5CbgpeDxv4AFIcZTWGS5n/XBUMUVeJKMicgmCuYUKS62wgWpwrJFRDpEqk0Gwym37eR74mlb0CiREwx3XgU0CDuowBR2nCsWeo9YlNUicoaqDgcQkTOBNSHHFOFzdWyfjxu4BsTW0Q13Zt9jiaKJlzRgK3BS1LZQKwFGyRORhpHhnEFRBV8ufL6Xx/5P2DGU4E7gGuC64PEo/Kl6ejNuuNNNuMaA44HLQ40oiqqGXYm4JP8EngXuw71PR+POsy9eDUYl9MIVnkrBk55iVU3d+V6huQUYJiLLcAlPXQoqjfpgclBttz8uMdsMeFFBVlUbhx3DTvwTV7Xz+eDxUqBniPFE87k6ts/HDWAG7n26POxAzN5jcxRNuSciJ+PWTRyLu0E5CrhGVb8MNTBARL4GzsIVPknHtWIf6tG8nea4RXcbETtHwYtqe2b3BFViz2XH8xp6gQfz14hIfeAAYs/ruPAiKiAiFXBrPoKrnpxd0v5hEZFGQJqq/hp2LBFlYa5YMO+U6CHGPvG1OrZvx01EPsUl1Km45UV+JHak2BnhRGb2BksUTVwECcVLuIpdbUXkIOAMVX0o5NAAEJF03BBPgEmq6sXwjjJQHvsX4GVcC3tkjkJRC/GaKMH74d/seMPuRYItIl8AG9jxvD5Z7DcZwO8kW0Qex/XSzSJqTpHd2JWOr0l2cXPFfKhmWxaUhSTbJyJyNVCHHedeH4Wr0jog/lGZvcUSRRMXIjIWd2P8SqTqpIjMUNW24Ubmt+iS8UFy0RIY6UtLuy+VMMsa3xNse2/uPp+TbBGZCxykqpk73dnE8DnJFpHZ2Fyx3WJJ9q4Tkc+Au1V1eqHt7YBHVPX0cCIze4PNUTTxUkVVfxSR6G05YQVThowDjgrmPH0F/IS7WekRalQFPhWRfwEfETv0ZG14ITki0q7wB5lHclT1pZ3vFpoJnh8/n+2vqieHHUQxFgAViHqvmlI7C2jhaZJtc8V2nxVk2XV1ivpsUNXpwbBssw+xRNHEyxoRaUpQJEZEzsM+1EpDVHWriFwFvKiqT4jItLCDihIpwPLvqG0K+LBw/IvBMMA3cMN1Q593ElXG3tsEO9AV+LuILMTFJ7hW9oPCDQuCZQkeAeqp6iki0ho40qPhTj4n2VuBaSIymti/u9B7T0RktKp229m2EPmcZKcDs0TEq7liInJOSc97UvXc2yQ7WB7mdqChql4tIs1wjRWfhRxa9RKeqxyvIEx8WKJo4uV6XMGYliLyB658t0/LPPi6qL2IyJG4HsRIufPEEOOJ4XO1PVU9KvhgvRKYEtxEva6qo0IMK7qMPfiZYINbTNxXbwCvA/cGj38D3gVCTRRFZDruHCYBV4jIAjxLsnFVWIeHHUQ0EUnGVQBOD0ZORN4baUD90AILiMhzuPPqbZINPBB2AMUoaQhiqFXPCxVk8S7JDryO+8w4Mnj8BzAMCDtRnCwiV6tq/+iNIvIPXLxmH2JzFE1cBXPuElR1U9ixRMiOi9ofAMxW1dAXtReRY3Atit+r6uMi0gS4JeybExE5XlXHFNdi7ElLMQAikogbNvYssBF3I3qPTzH6QkTSVHVjoQW88/nQ4ykiP6nqoSLyc9R852mq2j7kuA4o6XlVXRyvWMoSEbkZtzRGPdyNcCRR3Aj0V9Xni/nWuBCREpetUdVB8YqlrBKRxqq6cGfb4hzTMSU9r6pj4xVLcURksqp2KnSt+0VVDw45rjq40TBZFCSGnYCKwNmquiKs2MyeZz2KZq8SkduK2Q6Aqj4V14CK5u2i9sGH1VgAcQu0rwk7SQwcA4yh6BZjL9bHDCrrXgGchltD8XRVnRosqjyRcFuzr8cNh10fPK4BXKyqL4YVU2Ao0J0dez7Bnx7PLSJSi4Jh7EfgiseEKpIIBvHMjDSGiVucvRUQWqIoIu+p6gVRvZ4xwuztVNV+QD8RuVFVnwsrjuJEEsGgkXO7quYGjxOBSmHGJiLjVbWriGwi9rxGerHTQgqtsA+ADoW2vQ+EVggtkgiKSGNcpc7twePKuIqePsgK4olc65riwdBnVV0JdA7ulSJFzz5X1TEhhmX2EutRNHuViPQu6Xn1YMH2qFa7X4BDggqjobfaBbENxS26m4srZJMG9FPV/4YaWBkQVNp9DXhfVbcVeq6nqg4JJ7Kie8CiW41N8USkI653uC1uflEGcJ56sqadiPwMdIgUxwgaeCarauEb5XjGtJ+qLi+u19OX3k6flykQkUnACRqsZSdubbuv1JM1bX0kIi2BNsATxA6zTwP+7cmonclAZ1XNCh5XxI3gOTTcyEBETgTuA1rjitl1Af6uqt+GGZcpX6xH0exVPiSCpbA++ND/DnhLRFYBW0KOKaJ1MBSwBzASuAvX2+NFoigi1YHL2PHmLvReT1UtdmhRmEliIFFEJCqZSMQN2/FG0CPbiNjzGnpPsapOCYaNtcD1nPi2MHv+eQUIGp5C/axV1eXB/5FezzQ8+/wvbpkCwItEEbcQe/6C56q6OSg24oVgVEIDYt+vU8OLCHDv0e644ifRo082AVeHEVARkiJJIoCqZgXJYuhUdZSITMWNeBLgZvVkjWdTfnj1QWFMSM7ELWp/CwWL2oe+OHaggohUwM2xe15Vs0XEp2EAI4BJwHQgL+RYYgSFbB7FtcZGFynyYfjkF8C7IvJK8PjaYJsXRGQgcBAwk4Lz6suQ4l+Bd4B3VfX3sOMpwgIRuQmILH/yL1zFzNCJyLXAf4DtFAxV9GVIse/LFGwRkQ6R5Cvo2d62k++JCxHpA/wd93cW/X49PqyYAFT1E+ATETlSVSeGGUsJVovIGao6HEBEzgS8SMZE5GxgjKp+HjyuLiJnqerH4UZmyhMbemoM+YUomqnq10ErcaIPBXeCG847gV9wc+0aAm+q6lGhBhYQkalhDqkriYiMB3oDT+Nas6/AFVK6P9TAyB+OeA1wQrBpFPBaZP5T2ERklqq2DjuOogTv1QuDf3m4iqfveVKlOFI9+VncTboCo3EFqFaFGhggIvNwS4l4cSMcTUSGATdFej99IyKH4hooluF6d+oCF6pq6FUeRWQu0C66Z8wnIpKB60FsRGyP55VhxRQRzPt7C1dMCWAp0NOHRiibomB8YImiiQsfq55FxXE17qa9pqo2DXqiXlZ/1u+KISJJqpoTdhwAInIrsBlXrtur9QBFZIqqdhSR6araLnpb2LH5TkQGAE+q6qywYylJ8F7tBfRQVW+WjfGViHwBnKOqW8OOJUJilyloD/i4TAEAweiOFsFDb4Y8i8gHwHU+NEYURUQm4KZ2TKFgWDGq+kFoQRUSTD8henhx2ETk18KFpqI/z4yJBxt6auLFu6pnUa4HDgN+AFDVeUGvQOikmMXFCXnNuChZuPmS9+LfULbMoOdunojcgCu9nxJyTGXFYGCiiKzAv7UAC/cq5gL/F25EZcbdwAQR+QF/1gLsG+LP3iVBYjgj7DiK8Cjws4jMwM8ku4qq3hl2ECXxKUGMMllEngJeCB5fj61TaOLMEkWzV0VVPasmsWvupRE1byxkmcEEdsD12FFECfmQvIGHi4tHuR040MehbMDNuIW8b8ItgXI8UOKaaCbfAKAnfs49/QGogFt4+nxV9WL+XxnxCm5ZG2/Oq3qwXt0+YBDwOB6d10I+E5FTVXVE2IGUMTfiRky8GzwehUsWjYkbG3pq9qpgYvhZwBnA8KinNgHvqOqEMOKKJiJPAOtx1TtvxBWfmKWq95b0ffEgni4uHiEiXwFn+TSUrSwQkXaqOj3sOIojIhNV9ciw4yiKiLRQ1blhx1EW+Ty/qYi1AMGtjzkZuN0aBIoX+ZwIO47iBOe2Kq63Mxv/1nk0xhTDehTNXlVGqp7dCfwD1xp7La6S52uhRlTAy8XFo2wBponIN3gylC1qzlORPBmO9aKIVML1GL+lqj6dU3DD2IYCnxJ7XkOveopbzmYAhYZjq6oXvezFDRf3JL6RInINO57X0OcUA8/gCokMxSUSF+GWy5gKDASODSswABEZXXjeelHbQvKdiDyKa4yNPq9hL48BgKqmhh1DYYVGOO0gzGudiDyjqrcU91nmyWeYKSesR9HEha9Vz4L162aqassw4yiOiHQAnsPfxcWLHMqpqoPiHUtEsMYewDm4yoRvBo8vBlaq6q2hBFZIUIjlSuB8XAGP11V1VLhROSLyehGbNez3K4CIjCQYjq2qBwdDxX/2pcCDz/GJSFHFw9SHJWNE5BdVPbjQtmmq2r6o5+IYVzJuCPs3uGRVgqfSgC98+OwIGuoKU1UNdXkMEWmpqnOCz7EdhJnIFnONiwj1WiciHbVgvdgd2HBtE0+WKJq48LnqmYh8AtzoS3n9woIbTV8XF/eWiExW1U472xamoKHiLNxyChtx5/geT3ruvFQGhmN7HZ+vRGQibimb94NN5wG3qeoRYR4/EbkZt8ZuPVxBrEiiuBHor6rPhxFXWSAir6rqNb4msuB9RfZzgM9VNXOnOxuzl9jQUxMvPlc9qwHMFJEfcUMpAT+GdwSJxKkU9MSeJCKo6lOhBlY2VBWRJpG5TSLSGDdPJnQichBuXcfTcAUKTlfVqSJSD5iIBwvbe8z74diex+erHkA/4EXcsZsEXCoilYEbwgpKVfsB/UTkRlV9Lqw4yiJVvSb4/7iwYymBzxXZTweeFpFxuII2X/iyNJYpPyxRNPHic9WzXmEHUIJPge34W83OZ7cC34rIAlwvwAG49TJ98BxuHuw9qrotslFVl4nIfeGFVSbchpuL1VREvicYjh1uSDFux+/4vBQ06JxezNPj4xlLUVT1ORHpzI7TJwaHFpTZbWWhIruqXhGs3XkKburECyIySlX/EXJophyxoacmLspS1TMR6QpcrKqhl6EuasFdn5SB6p2VgMgcojk2hGff4PtwbN/j84mI/J+qPiEiz1F04Y4w13jMJyJDcMV1plEwfUJ9ic/smrJQkT0iSBZPxo1COVpV00MOyZQj1qNo4sLHqmfRROQQ4BJcYZGFuOEoPhgpIiep6ldhB1IMr6t3BonhL2HHUVhQyOZRoDVRrdc+FBUB7yt3Egy/mhl2HEURkV+Bd4B3VfX3sOOJ5mnlztnB/5NDjKE0OgGt1aPWdZ8rd/quLFRkF5FTgAtxRZS+xY1CuSDEkEw5ZImiiQsRObqo7ao6Lt6xRIhIc9xwjouBNbg5AOLZfIpJwEcikoCHPbGqelRU9c4pwTxPb6p3eux1oDeueMdxuJbihFAjivUGQeXO4PFvuPeHF4mi507H3dy9JyJ5uOP2XpjFsqIqd6aLSA1iK3fWDysuAFX9NPg/tErJpTQDV0V5ediBRCluqC643tlQE8Xiqp1GeLJ8x3wRuQfPKrIHegLvAdfaaBgTFht6auIiWA8oIhk4DJgSZtWz4CbuO+AqVZ0fbFvgS68O5JezPxOY7lNLdmFWvXPXiMgUVe0oItMjyyZEtoUdG1jlzj0laETpBfRQ1cQQ4/C+cmfQcHcHO96wh73EQ2Qtu1SgPW4pm+i1Cn0oeuZl5c5iqp1G+FL11MuK7MFn6teeNVybcsh6FE1cqGpMy6eINMAtsBymc3CLOn8jIl/ghotJyd8Sd0uAGb4miT5W7ywjrdiZQS/xPBG5AXfznhJyTNG8q9xZRs4rACJyAK5X8ULczef/hRlPGancOQx4GTe8Lncn+8ZT37ADKAUvK3eWkSTHy4rsqporInkiUs23KR2mfLEeRRMKERHcQvetPYilKq7X7mLgeGAw8JEP8wJF5A2gCTCS2FZsL5bHEJGxuBu796OrdwbP9VTVISHEVBZasQ/Fzc2qDvQBqgFPqOqkMOOKEJGOuN7htrghdxnAear6a4gxeX9eAUTkB6ACLvF5N7I8iy98rdzpU496WRFVufMJ4N9RT6UB/1bVNqEEVgQRacuOc7J9+Lt7CJjgY0V2cWs8H4JrhI1eussKKJm4sUTRxEWhinYJuCE8i1T10tCCKkIwf+d84MKQCzxE4uld1HZV/U+8YzHli1Xu3D0i0kJV54YdR1F8rtwpIg8Aq4CPiG0UWxtWTNGCyt2Fb5g24Irw3B5Gg0BZqdwZfI4di0sUR+CWexivqqEvG+NzRXYRubyo7WVgPq/Zh1iiaOKi0AUvB5ckfh9WPGbPKAPVO71qxY6a71QkH+Y7gd+VO8G/8xrN54qxIjIbzyp3RgTzsQtTj64lfYClwFBcMnERLumeClynqseGGJu3lTsBRGQ6cDDws6oeHLxH3lTVE0MOzXsiUhlo6Gvjk9n32RxFExeqOkhEKgLNg0120ds3eFu9s7hWbNzQ4rBE5judg6ug+Gbw+GJgZSgRFc27yp0Rnp7XaG/gb8VYHyt3AqCqjcOOYSfOUNWDox6/GhR4ujOomhkmnyt3AmxT1TwRyRGRNFzPcYMwAxKRlqo6p7i5zz7MeRaR03GfGRWBxiLSHnjQlwZFUz5YomjiQkSOBQYBi3CtsQ1E5PIwl8cwe0RlVR0tIqKqi4EHRGQKcH/YgQHnUdCKfUWkFTvMgFR1LICIPKmqnaKe+lREvFlHLjiXTwBPRFXufBwIrXJnFO/OayHpqvqeiNwNbs1HEQm1OEuhyp2zgmVsvKrcWQZsFZELcEViwP0dbg++DruH9hNc5c6v8asQUMRkEakO9MdVF92MK3YWptuAa4Ani3hOcfUKwvYArkL8twCqOk1EvOhhN+WHJYomXp4ETooMnwhKob9NyFXZzF/mc/VO71qxo1QVkSaReU0i0hg3T8YbvlXujOLzeQUPK8ZSNip3+q4H0A94EXduJwGXBkMDbwgzMDyt3Bmhqv8Kvnw5qDCeFmZhrCCma4L/fa7Mmq2qG1ztv3x5YQVjyidLFE28VIgeY6+qv4lIhTAD8lmh4j878KH4ROBm3ELeN+Gqdx4PFDkBPwQ+tmJH3Ap8KyILcD3sB+Bat71QqHLn+Z5V7vT5vILrqRgONBWR7wkqxoYZUKQn2+y+4D1Q3AL34+MZSxE+E5FTfazcCSAioyPF4VR1UeFtplgzReQSIDEY2XET4EWBIlN+WDEbExciMhDXEhYZItYDSPRoDoVXiqt2FmFVz3aNiDTCg1bsaCJSCWgZPJyjqpkl7R9PPlfujObjeQV/K8Z6WrnT6/UxReT/VPWJ4hrvfGi087Vyp4gk4xoSv8HNK450jaUBX6hqy2K+1QAiUgU31/kk3LH7EuijqttL/EZj9iBLFE1cBDfF1wNdg03fAS/6dHNsSq8sVO8sqsXaWrFLx/PKnXZed5OPlTt9Xx9TRE5X1U9tqYJdJyI3A7cA9YBlUU9tBPqr6vNhxFUWiUgiUFVVN4YdiylfLFE0cSFuUfvtqpobPE4EKqnq1nAj85OIPKOqtxSXkIWdiInIMcGXRVbvVNVbQwkMa8XeE0RkJEHlzqCcfRKueEy7EGOy8/oXicgvhSp3ElTubF/Uc8ZvZaFyJ4CI3Kiqz4UdRzTfe7IBRGQo8E/cHPGfcNe6fqr631ADM+WKzVE08TIaOAE3nwigMvAV0Dm0iPw2JPjfyyIUnlfvvJaCVuzoD/uNgLVgl453lTux87on+Fy50/f1MZsDd7DjEhRh9niWhcqdAK+IyE3A0cHjb4FXQh6SXdQxi/Dl2LVW1Y0i0gMYCdyFm5dtiaKJG+tRNHERabXe2TZTtgQLeJ9WqHrnCFVtFW5k1or9V4jIt8C5wChV7RBU7nxcVY8p+Tv3Ph/PK5SNcxuU1u8HHElB5c5bcdWKO6pqaEVZilsfU1VDLQQUISK/AC/jbtTzG01UdUpoQZURIvIarjhWZJhuTyBXVf8RXlT+E5GZQHvcUPHnVXWs9fybeLMeRRMvW0SkQ+RmSUQ6AttCjsl7QaWzR9mxld2XtZR8rt5prdi7z7vKnVF8PK9QBs6t55U7fV8fM0dVXwo7iLJERJJUNQc4tFByMyZIvL3gcU/2K7i1p38BxgVLFtkcRRNX1qNo4kJEDgXewU1oF9y8tgutNbZkIjIe6A08jbvBuwJIUFUfFrQH/K3eaa3Yf43HlTvtvO6iMlK580dVPUxEpgDHAZuA2b7MPRWRB3Brdn6Eqy4KgKquDSsm34nI1GBEwlTcMju/B9ubAO+raom98PHge092NHELKiYGybcxcWE9iiYuVPUnEWmJu/EEj248PVdZVUeLiKjqYuCB4EbKm0QxSAx9ah22Vuw9IDiGM8OOI6KsnFfw8tzODv4Pe/5wSXxfHzNS9fTfUdsU8GV0h48iBafuAL4JRp6Am+d5RSgR7cj3nux86np2LEk0cWWJookLEbkeeEtVZwSPa4jIxar6Ysih+S5TRBKAeSJyA24uUUrIMfnuR6ADkCsiTQu1YoddkAUovhUb8CZR9JD35xX8PLeq+mnwv7dLOajqv4IvXxaRL/BsfUxVbRx2DIWVgXmxGSJyW/D1K0Bi8HUucAiugnHYtqlqnojkiEgarte4QdhBGeMLSxRNvFytqi9EHqjqOhG5GrBEsWQ345YEuAnog5vnVOR6XiaftWLvm8rCeQWPz62nlTuB2LUwVXVR4W2mSL7Pi03ENWxKoe1JQGr8wymSlz3ZQQPxEao6IexYTPlmiaKJl8Rg+KRC/jqKFUOOyXuq+lPw5WY8uhn2vCXbWrF3k53XPcLLcxsYhqvc+Rqe9MJGrY+ZLiI1iF0fs35ogZUBqnpc2DHsxHJVfTDsIEria092cA15AXdtMyY0liiaePkCeFdEXgkeXxtsMyUQkU7AvbhqotE9AAeFFpTjc0u2tWLvPjuvf52v5xb8rNxp62PuAR7Oi4Ud36ve8bwne7SInAt8GGlkNyberOqpiYtgGMU1wAnBplFAf1XNCy8q/4nIXFzxhOlA/rEKCtuYIkQq7YUdR2mJSCM8acX2WVk7r+DfufW5cqetj7n7fK3cKSI1ffjbKkpUT/Y3uGMX3ZP9hQ/VdkVkE1AV1/u/DRejqmpaqIGZcsUSRRMKETkKuEhVrw87Fp+JyHhV7Rp2HCXxrSVbRH5WVa+H6xTVYu1RKzZg53V3+XxuRWRhEZvVh3VZRaQi8E88Wx9TREoa0qyezO+cTsG82IMj82JV9cSQQ/OWiNxMQU/2sqinNuIasa032xhs6KmJIxE5BLgYuABYCHwYbkRlQu9g3bjRxPYAeHHsfKzwCIR+Q16csjIfy87rrisL59bHyp1RXsStjxkpcNYTeAkIdX3MMjAPEPyeF+slVe0H9PO1Jxvy103sATRW1T4i0gDYT1V/DDk0U45Yomj2qqDK3sXBvzXAu7ie7LLw4euDK3CL2VegYOip4k+S7V2FR1+HOgXKynwsO6+7rqycW6/Y+ph7hM/zYn33iojchGc92YEXcZ/7x+Oqnm8GXgAODTMoU77Y0FOzV4lIHvAdcJWqzg+2LfBhqFNZICJzVbVF2HEUR0R+VNXDRGQKcBywCZjtw/wOn/ncig12Xv8K38+tbyJzT0VkKnB+ofUx3/dlXqqv8wAL821erO+CETsVgMgaoz2BXFUNtScbYt4b+cPuReSXQg0qxuxV1qNo9rZzgItw6559AbxDGaiE5pEJItJaVWeFHUgxrCV79/jcig12Xv8K38+tb2x9zL/I88qdXiojPdnZwVJikWXFMogqamdMPFiPookLEakKnIkbgno8bq7TR6r6VaiBeU5EZgNNcXM6Mymoehb28hg7sJbs0vO5FbswO6+7xsdz63PlThFZCjwVPKxM7PqY21T1qSK/Mc587GUvC5U7fVUWerJFpAdwIdABdz05D7hPVYeFGpgpV6xH0cSFqm4BhgJDg0IP5wN3ApYoluzksAMoibVk75oy0opt53U3eH5ubX3Mv87HXnabF7v7vO/JVtW3goaJbrh4z1LV2SGHZcoZ61E0xmMi8izwtqqGfUMSw1qyd4/vrdh2Xnef7+fWV7Y+5l9n82J3XRnqya6Bq2Cb37Hjw9qdpvywHkVj/DYF6CUiLXCLZL+jqpNDjgmsJXt3+d6Kbed19/l+bgEvK3eWiTnrnvey27zYXed9T7aI9AH+DvxOME+R8EcAmHLGehSNKQNEpCZwLq4wUENVbRZySIC1ZO+qMtSKbed1F5WFc+tj5U4Rqenz0idloZfdx3mxvisLPdkiMhdop6pZYcdiyi/rUTSmbDgQt57iAYBPcxSsJXvXeN+KHbDzuuvKwrn1rnKnz0liwNteds/nxfquLPRkzwCqA6tCjsOUY9ajaIzHROQJ4Gzc0JN3gI9VdX2oQUWxluxdUxZascHO6+4oC+fWx8qdZYWPvew2L3b3+d6TDSAinYBPcAljZmS7qp4RWlCm3LEeRWP89jtwpKquCTuQaNaSvdu8bsW28/qXeH1uAz5W7iwrfOxlLxPzYn3ke5IYGAQ8DkzH1k80IbEeRWPMLrOW7N3jeyu2ndfd5/u5Lcy3yp2+87GXvSzMizW7T0R+UtVDw47DlG/Wo2iM2R3Wkr0bykAiYed1N5WBc+t75U4ved7LXhbmxZrd952IPAoMJ3boqS2PYeLGEkVjzO7IEJHbgq9fIbYl+xBchUBT9th53QdFVe5MD9Zli67cWT+0wMqGH4EOQK6INC3Uy54bamSwXFUfDDkGs/ccEvx/RNQ2Wx7DxJUlisZ4SkQSgZmeFpqwlux9k53XfZO3lTvLAJ972cvCvFizm1T1uLBjMMbmKBrjMRH5BLhRVf8XdizRykKFR7Pr7Lzu23ys3Ok7n+cBlrV5sWbXiEg1oDcFBZTGAg+q6obwojLljfUoGuO3GsBMEfkR2BLZ6EF5bGvJ3jfZed23+Vi503fe9rJbkrjPG4hbGuOC4HFP4HXgnNAiMuWO9Sga4zEROaao7ao6Nt6xRLOW7H2Tndd9m4+VO31nvewmLCIyTVXb72ybMXuT9Sga4zFVHSsiBwDNVPVrEalCwdCnMOOyZGIfZOd13+R55U7fWS+7Ccs2EemqquMBRKQLsC3kmEw5Y4miMR4TkauBa4CaQFNchcKXAStnb4wpLZ8rd/rOrrUmLP8EBgdzFQHWAZeHGI8phyxRNMZv1wOHAT8AqOo8EakdbkjGmDLG58qdXrNedhOijap6sIikAajqRhFpHHZQpnyxRNEYv2WqapaIu88TkSTcOkrGGFNatj6mMWXPB0AHVd0Yte19oGNI8ZhyyBJFY/w2VkTuASqLyInAv4BPQ47JGFO2eFu50xgTS0RaAm2AaiISXeE0DUgOJypTXlnVU2M8JiIJwFXASbibvC+B19TeuMaYUrLKncaUHSJyJnAWcAYwPOqpTcA7qjohjLhM+WSJojGeE5GKQEvckNO5qpoVckjGmDJERH5W1UPCjsMYU3oicqSqTgw7DlO+JYQdgDGmeCJyGvA78CzwPDBfRE4JNypjTBljlTuNKXvOFpE0EakgIqNFZLWIXBp2UKZ8sR5FYzwmInOA7qo6P3jcFPhcVVuGG5kxxhhj9hYRmaaq7UXkbKA7cBswrtBaqMbsVdajaIzfNkWSxMAC3DwFY4wxxuy7KgT/nwYMU9UNYQZjyieremqMh6IqnU0WkRHAe7g5iucDP4UWmDHGGGPi4dNgVNE24DoRyQC2hxyTKWds6KkxHhKR10t6XlVtkWxjjDFmHyYiNYENqporIlWANFVdEXZcpvywRNEYY4wxxhiPiMhlRW1X1cHxjsWUXzb01BiPiUhj4EagEVHvV1U9I6yYjDHGGLPXHRr1dTKuevFUwBJFEzfWo2iMx0TkF2AAMB3Ii2xX1bGhBWWMMcaYuBKR6sA7qnpy2LGY8sN6FI3x23ZVfTbsIIwxxhgTqi1A47CDMOWLJYrG+K2fiPQGvgIyIxtVdWp4IRljjDFmbxKRT3HVzsEtZ9caVwHdmLixRNEYv7UDegLHUzD0VIPHxhhjjNk39Y36OgdYrKpLwwrGlE82R9EYj4nIfKC1qmaFHYsxxhhj9i4RORCoo6rfF9reBVihqr+HE5kpjxLCDsAYU6IZQPWwgzDGGGNMXDwDbCxi+8bgOWPixoaeGuO36sAcEfmJ2DmKtjyGMcYYs++po6rTC29U1eki0iiEeEw5ZomiMX7rHXYAxhhjjImb6iU8VzleQRgDliga4zVbL9EYY4wpVyaLyNWq2j96o4j8A5gSUkymnLJiNsZ4TEQ2UVAeuyJQAdiiqmnhRWWMMcaYvUFE6gAfAVkUJIadcPcAZ6vqirBiM+WPJYrGlBEiIsCZwBGqelfY8RhjjDFm7xCR44C2wcOZqjomzHhM+WSJojFljIj8rKqHhB2HMcYYY4zZd9kcRWM8JiLnRD1MwA0/2R5SOMYYY4wxppywRNEYv50e9XUOsAg3/NQYY4wxxpi9xoaeGmOMMcYYY4yJYT2KxnhIRO4v4WlV1T5xC8YYY4wxxpQ71qNojIdE5PYiNlcFrgJqqWpKnEMyxhhjjDHliCWKxnhORFKBm3FJ4nvAk6q6KtyojDHGGGPMvsyGnhrjKRGpCdwG9AAGAR1UdV24URljjDHGmPLAEkVjPCQi/wXOAV4F2qnq5pBDMsYYY4wx5YgNPTXGQyKSB2TilsSIfpMKrphNWiiBGWOMMcaYcsESRWOMMcYYY4wxMRLCDsAYY4wxxhhjjF8sUTTGGGOMMcYYE8MSRWOMMcYYY4wxMSxRNMYYY4wxxhgTwxJFY4wxxhhjjDEx/h/dTf6qxWi7DwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Conclusion :**\n",
        "**There is no null value in the data, and the overall churn rate of the customer is 15%, which is huge.**\n",
        "\n",
        "**Area code, account length and day, night, evening charges doesnot play any role in the churn rate.**\n",
        "\n",
        "**There are some states who have higher churn rate and are there are states who very low churn rate. And high churn rate may be vary because of connectivity**\n",
        "\n",
        "**As seen in the heatmap graph, there is no relation between churn rate and account length, voice mail messages, or area code.**\n",
        "\n",
        "**Also, total day call minutes, total day calls, total day charge, total eve minutes, total eve calls, total eve charge, total night minutes, total night calls, total night charge, played no role in influencing the churn rate.**\n",
        "\n",
        "**But for the customers who have an international plan, their churn rate is also quite high, either because of the high price of international calls or\n",
        "network problem**\n",
        "\n",
        "**And the customers who call in the customer service centre their churn rate is also high, which means they didn't find the solution of their issue**\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "ya7EHeNcZl6R"
      }
    }
  ]
}