Tips_Tricks_23_COVID_vaccine_analysis.ipynb

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  "metadata": {
    "colab": {
      "name": "Tips_Tricks_23_COVID_vaccine_analysis.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "mount_file_id": "1EOWf1bv3_LN07ux_9FLD60w2RECidWrW",
      "authorship_tag": "ABX9TyNLQPh+FowD+k2A4TDpctiX",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bnsreenu/python_for_microscopists/blob/master/Tips_Tricks_23_COVID_vaccine_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xdgfevvUK-hi"
      },
      "source": [
        "https://youtu.be/n0ehFY8jWvs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2NeAF3cTyFVI"
      },
      "source": [
        "Download data from https://www.kaggle.com/gpreda/covid-world-vaccination-progress"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h7_l4Oegs68S"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd "
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mSwpGyEQuYzL"
      },
      "source": [
        "#!pip install plotly  #No need for colab as it may already come with this pre-installed."
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eaEIQDGouUwf"
      },
      "source": [
        "#Import plotting libraries. \n",
        "# Plotly can be useful for Choropleth, display of data on maps. \n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "%matplotlib inline\n"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZWYFvzeKtbtP"
      },
      "source": [
        "#Load the data into a pandas dataframe. \n",
        "df=pd.read_csv(\"/content/drive/MyDrive/Colab Notebooks/data/COVID_data/country_vaccinations_26Oct2021.csv\")"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1N4MEcSitgMQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "aa50f983-3b59-4023-9a9c-11a4158ffed6"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>people_fully_vaccinated</th>\n",
              "      <th>daily_vaccinations_raw</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "      <th>people_vaccinated_per_hundred</th>\n",
              "      <th>people_fully_vaccinated_per_hundred</th>\n",
              "      <th>daily_vaccinations_per_million</th>\n",
              "      <th>vaccines</th>\n",
              "      <th>source_name</th>\n",
              "      <th>source_website</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>2021-02-22</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>World Health Organization</td>\n",
              "      <td>https://covid19.who.int/</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>2021-02-23</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1367.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.0</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>World Health Organization</td>\n",
              "      <td>https://covid19.who.int/</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>2021-02-24</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1367.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.0</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>World Health Organization</td>\n",
              "      <td>https://covid19.who.int/</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>2021-02-25</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1367.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.0</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>World Health Organization</td>\n",
              "      <td>https://covid19.who.int/</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>AFG</td>\n",
              "      <td>2021-02-26</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1367.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>34.0</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>World Health Organization</td>\n",
              "      <td>https://covid19.who.int/</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "       country iso_code  ...                source_name            source_website\n",
              "0  Afghanistan      AFG  ...  World Health Organization  https://covid19.who.int/\n",
              "1  Afghanistan      AFG  ...  World Health Organization  https://covid19.who.int/\n",
              "2  Afghanistan      AFG  ...  World Health Organization  https://covid19.who.int/\n",
              "3  Afghanistan      AFG  ...  World Health Organization  https://covid19.who.int/\n",
              "4  Afghanistan      AFG  ...  World Health Organization  https://covid19.who.int/\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UsVNoK35whSt"
      },
      "source": [
        "Above, we see a lot of NaNs that we need to fill with some values, zeros make the most sense here. \n",
        "\n",
        "Let us check how many NaNs for each column. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ehxNSSmpzDym",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c4cb461e-f660-4925-86a2-da6a4c8f98a3"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "country                                0\n",
              "iso_code                               0\n",
              "date                                   0\n",
              "total_vaccinations                     0\n",
              "people_vaccinated                      0\n",
              "people_fully_vaccinated                0\n",
              "daily_vaccinations_raw                 0\n",
              "daily_vaccinations                     0\n",
              "total_vaccinations_per_hundred         0\n",
              "people_vaccinated_per_hundred          0\n",
              "people_fully_vaccinated_per_hundred    0\n",
              "daily_vaccinations_per_million         0\n",
              "vaccines                               0\n",
              "source_name                            0\n",
              "source_website                         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1uOvvk-4tvkv"
      },
      "source": [
        "#Fill NaNs with 0 and then drop all countries with iso_code = 0. This is key information that we need so dropping unknowns is the best way to handle. \n",
        "df.fillna(0, inplace = True)\n",
        "df.drop(df.index[df['iso_code'] == 0], inplace = True)"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "63ElW_nRzey9"
      },
      "source": [
        "#Check how many nulls we have. SHould be none. \n",
        "df.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g4HRTvSPtlEP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e38d3f28-fd1c-4ddd-effb-7f86403661dd"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 53595 entries, 0 to 53594\n",
            "Data columns (total 15 columns):\n",
            " #   Column                               Non-Null Count  Dtype         \n",
            "---  ------                               --------------  -----         \n",
            " 0   country                              53595 non-null  object        \n",
            " 1   iso_code                             53595 non-null  object        \n",
            " 2   date                                 53595 non-null  datetime64[ns]\n",
            " 3   total_vaccinations                   53595 non-null  float64       \n",
            " 4   people_vaccinated                    53595 non-null  float64       \n",
            " 5   people_fully_vaccinated              53595 non-null  float64       \n",
            " 6   daily_vaccinations_raw               53595 non-null  float64       \n",
            " 7   daily_vaccinations                   53595 non-null  float64       \n",
            " 8   total_vaccinations_per_hundred       53595 non-null  float64       \n",
            " 9   people_vaccinated_per_hundred        53595 non-null  float64       \n",
            " 10  people_fully_vaccinated_per_hundred  53595 non-null  float64       \n",
            " 11  daily_vaccinations_per_million       53595 non-null  float64       \n",
            " 12  vaccines                             53595 non-null  object        \n",
            " 13  source_name                          53595 non-null  object        \n",
            " 14  source_website                       53595 non-null  object        \n",
            "dtypes: datetime64[ns](1), float64(9), object(5)\n",
            "memory usage: 6.5+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qUTyOBmjz2t6"
      },
      "source": [
        "The date is in the 'object' format. Let us change it to Datetime format for easy handling and plotting. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ywbTncAyn5HB"
      },
      "source": [
        "df['date'] =  pd.to_datetime(df['date'], format='%Y-%m-%d')"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hwSjhMaXtrYL",
        "outputId": "465ec759-475a-4313-d70f-757d40e1cc80"
      },
      "source": [
        "#Print column names and drop the ones we don't intend to use. \n",
        "df.columns"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['country', 'iso_code', 'date', 'total_vaccinations',\n",
              "       'people_vaccinated', 'people_fully_vaccinated',\n",
              "       'daily_vaccinations_raw', 'daily_vaccinations',\n",
              "       'total_vaccinations_per_hundred', 'people_vaccinated_per_hundred',\n",
              "       'people_fully_vaccinated_per_hundred', 'daily_vaccinations_per_million',\n",
              "       'vaccines', 'source_name', 'source_website'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T82-CYxBt1Xi"
      },
      "source": [
        "df.drop([\"people_fully_vaccinated\",\"daily_vaccinations_raw\",\"people_fully_vaccinated_per_hundred\",\n",
        "         \"daily_vaccinations_per_million\",\"people_vaccinated_per_hundred\", \"source_name\",\"source_website\"],axis=1, inplace=True)"
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C_E_qHMHuBIR"
      },
      "source": [
        "Now, let us try to undersatnad the data. I am picking US and India for my study. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WKa398eK1Wge"
      },
      "source": [
        "**USA**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GT78rGZduEZH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "ddacd210-d07e-49f5-93f9-6b783df8a106"
      },
      "source": [
        "#Save USA data into a separate dataframe\n",
        "df_USA = df[df[\"iso_code\"] == 'USA'].copy()\n",
        "df_USA\n"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>123.19</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51437</th>\n",
              "      <td>United States</td>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>415012026.0</td>\n",
              "      <td>220648845.0</td>\n",
              "      <td>796148.0</td>\n",
              "      <td>123.40</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>311 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             country  ...                                   vaccines\n",
              "51127  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51128  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51129  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51130  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51131  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "...              ...  ...                                        ...\n",
              "51433  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51434  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51435  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51436  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "51437  United States  ...  Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "\n",
              "[311 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_cRs1fWKkBDG"
      },
      "source": [
        "# Use white grid plot background from seaborn\n",
        "#sns.set(font_scale=1.5, style=\"whitegrid\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T7ARL5o50qe5"
      },
      "source": [
        "#Drop the dates with missing values, previously NaN that we filled with 0. \n",
        "df_USA.drop(df_USA.index[df_USA['total_vaccinations'] == 0], inplace = True)"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Bh5aZxQwVKi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 431
        },
        "outputId": "83da7ac3-e800-4a69-910d-d1108a345ebb"
      },
      "source": [
        "#Plot total vaccinations as a function of date\n",
        "plt.figure(figsize=(18,6))\n",
        "sns.lineplot(data=df_USA, x=\"date\", y=\"total_vaccinations\")\n",
        "plt.title(\"Total vaccinations in the USA\")\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8q-m5I17wgfq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "outputId": "89350bbb-4ea9-4d1b-9e70-a85666ad3fb3"
      },
      "source": [
        "#Plot daily vaccinations as a function of date\n",
        "plt.figure(figsize=(18,6))\n",
        "sns.lineplot(data=df_USA, x=\"date\", y=\"daily_vaccinations\")\n",
        "\n",
        "plt.xticks(rotation=90)\n",
        "plt.title(\"Daily vaccinations in the USA\")"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Daily vaccinations in the USA')"
            ]
          },
          "metadata": {},
          "execution_count": 53
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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IN4/reULnpyZE84crBvP+3RNY/Ktv0T4yjEc/39y4IUVERETkhKgAISIizUJeURmvL9nBpcNSSY6LOun+EtpFcPPpPflwzR6NghARERFpBlSAEBGRZuGF+VmUVVbzvTN6N1qft4zvpVEQIiIiIs2EChAiIuK5nPzDvDg/k3NO7UxGcmyj9atRECIiIiLNhwoQIiLiqY17DnH5E/Ooqnbce07fRu+/ZhTE3z7TKAgRERERL6kAISIinlmSeYArn5xHtXP8+46xnNI1rtGvkdAuguvHpvHxuj3kFZU1ev8iIiIi0jAqQIiIiCdyi8q48dlFJMZG8ub3x9G/S+MXH2pcOLArzsHMjfuDdg0REREROT4VIERExBPTFmZTUl7FUzeOoHvHdkG91sDUODrHRfLFhr1BvY6IiIiI1C3M6wAiItJyVFU7FmzL470Vu+gYG8GPz+1HaIgF3E9FVTUvLchiQp9EMpLbByHp0cyMSf07M33lLsorq4kIU/1dREREpKmpACEiIg3ywerdPDB9LXsLy4gKD6G0opqsvGIeuXookWGhAfX14Zo97DtUxu8vHxSktN90dv9kpi3KZuH2PCb0SWqy64qIiIiIj74CEhGRelVWVfPA9LXER4fz2LXDWPHbc/n1Rafwweo93PL8YorKKgPq74V5maR1asfEvslBSvxNp2ckEhkWwufr9zXZNUVERETkP1SAEBGRes3cuJ+9hWXcd24/Jg9OISo8lNsm9ObPVw5hwbYDfP/lpTjnGtTXqp35LM06yE1jexJyAtM3TlR0RCjjMxL5bP3eBmcVERERkcajKRgiIlKvaYuySW4fyaT+R49YuHxEN4rKKvnde2uZvmo3lwxJOer5orJKNuwuZP3uQqodJLQLZ/rKXcREhHLFyG5N+RIAOPuUzny+YR+b9hbRr0vw154QERERkf8IagHCzKKAr4BI/7XecM79rlabSOBFYASQB1ztnMsMZi4REWm4nPzDfLlxHz+YmEF46DcHzl0/Jo03l+3koRnrmNgvibiocA4Ul3PXq8uYvy2PYw02+O64nsRFhTdB+qPVFFA+37CXtE7tWLEjn4R24UHdAlREREREfII9AqIMmOScKzKzcGCOmX3onFtwRJtbgYPOuQwz+w7wB+DqIOcSEZEGen3xDhxw9Wndj/l8aIjxP98eyJTH5/KXTzZx6/he3PTsInLyD/PDszIY0j2BU1PiCA8NIb+kgsLSCk7t6s0H/i7xUQxMjePxL7bwyKebqKhyxEWFMf8XZxMTqUGBIiIiIsEU1HdbzjfJtsj/MNx/q/1d2BTgfv/9N4DHzMycJuiKiHiuqtrx+pIdTOiTRPeO7epsN7hbAjeMSePF+ZnMWLWb8soqXr5tNKf17HhUu8TYyCAnrt/3JvTmtUU7GNojgaTYSB6csY43lu7kpnE9vY4mIiIi0qoF/eseMwsFlgIZwOPOuYW1mqQCOwCcc5VmVgB0AnJr9XM7cDtAjx49gh1bRESAWZv2sbuglN9dfGq9be87tx8frtlDqBmv3DGu2a6xMGVoKlOGpn79ePqqXTw7dzvXj0kjtAkXxRQRERFpa4K+C4Zzrso5NxToBowys4En2M9TzrmRzrmRSUnav11EpCm8unAHibGRnH1K53rbxkeH8/4Px/Pxf5/RbIsPx3Lb+N5k5ZXw+fq9XkcRERERadWabBtO51w+MBM4v9ZTOUB3ADMLA+LxLUYpIiIe2lNQyhcb9nLVyG7HXHzyWJLjooiPbvrFJU/GeQM6k5oQzTNztnsdRURERKRVC2oBwsySzCzBfz8aOAfYUKvZe8BN/vtXAF9o/QcREe+9vmQH1Q6+c1rrnvYWFhrCzaf3ZNH2A6zeWeB1HBEREZFWK9gjILoCM81sFbAY+NQ5N8PMHjSzS/xtpgKdzGwLcC/w8yBnEhGRelRVO/61eAcT+iTSo1Pdi0+2Fled1p3YyDCmztnmdRQRERGRVivYu2CsAoYd4/hvj7hfClwZzBwiIhKYrzbvJyf/ML+66BSvozSJuKhwrhjRjVcXZvObyWV0aga7dYiIiIi0Nk22BoSIiLQc0xZmkxgbwbcasPhka3HNqB6UV1Xz1rIcr6OIiIiItEoqQIiIyFH2Fpby+YZ9XDGiOxFhbeefiX5d2jMirQPTFmWjpYhEREREGl/beWcpIiIN8q/FO6iqdlwzqrvXUZrcNaN6sC23mIXbD3gdRURERKTVUQFCRES+VlZZxUsLsjijbxJpnWK8jtPkLhrUlfZRYUxblO11FBEREZFWRwUIERH52nsrdrH/UBnfm9DL6yieiI4I5bJhqXy4eg8Hi8u9jiMiIiLSqqgAISIiADjnmDpnO/27tGd8RqLXcTxzzWjfYpRvLtvpdRQRERGRVkUFCBERAWDOllw27DnEreN7YWZex/FM/y5xjEzrwOMzt7A9t9jrOCIiIiKthgoQIiICwDOzt5PUPpJLhqZ4HcVzf7pyCGbGzc8t4oCmYoiIiIg0ChUgRESETXsPMWvTfm4am0ZkWKjXcTzXMzGGp28cya6CUm57YTGlFVVeRxIRERFp8VSAEBER/vb5ZqLDQ7l2dJrXUZqNEWkd+OvVQ1m+I58HZ6zzOo6IiIhIi6cChIhIG7c48wDvr9rNf53Zm44xEV7HaVYuHNSVG8ak8friHewuOOx1HBEREZEWTQUIEZE2rLra8dCMdXSJi+L2M3p7HadZ+t6E3jjgubmZXkcRERERadFUgBARacPeXp7Dqp0F/OyCfrSLCPM6TrPUvWM7LhzUlVcXZlNYWuF1HBEREZEWSwUIEZE2qqS8koc/3sCQbvFMGZLqdZxm7b/O6E1RWSWvLsz2OoqIiIhIi6Wvu0RE2pjl2Qd5d8UuZqzaTW5RGY9fO5yQEPM6VrM2MDWe0zM68dzc7dxyei8iwlS/FxEREQmU3kGJiLQhT3y5hUufmMeri7IZmdaB528+jZE9O3odq0W4/Yx09haW8bfPN7H/UJnXcURERERaHI2AEBFpI5ZmHeDPn2ziwkFd+P3lg4mLCvc6UotyRp9ExvbuxOMzt/L4zK0MSo3nlvE9+fbQVMw0gkRERESkPuac8zpDwEaOHOmWLFnidQwRkRajoKSCCx+dTUgIvH/3BBUfTlB1tWPd7kJmbdrP+6t2s253IZMHd+V/Lx1EfLR+pyIiIiIAZrbUOTey9nGNgBARaeWcc/z8rVXsLSzlje+PU/HhJISEGANT4xmYGs8dZ6bz5KytPPLpJpZn5/PPG0YwMDXe64giIiIizZbWgBARaeUe+2ILH67Zw4/P68fQ7glex2k1QkOMO8/K4I3vj8M5xx0vL9U2nSIiIiLHoQKEiEgr9tRXW/nzp5u4dFgqt0/o7XWcVmlo9wT+fu1wdheUcv+7a72OIyIiItJsqQAhItJKPTd3O//3wQYuGtyVP14xWFttBtGItA7cdVYGby3P4b2Vu7yOIyIiItIsqQAhItIKfbZuLw9MX8d5Azrz16uHEhaq/90H2w8nZTCsRwK/ens1Ow+WeB1HREREpNnRO1IRkVbmUGkFv35nDf27tOfRa4YRruJDkwgLDeFvVw/DObj9xaUUl1V6HUlERESkWdG7UhGRVubhjzay91Ap/++yQUSGhXodp03p0akdj107jI17D3H3tOVUVbe8ra5FREREgkUFCBGRVmRJ5gFeWpDFd8f1ZFiPDl7HaZMm9kvm/ksG8PmGfTw0Y53XcURERESajTCvA4iISOMoq6zi52+tJjUhmh+f28/rOG3aDWPSyMot5pk52xnZswOTB6d4HUlERETEcxoBISLSSszcsI8t+4r47cWnEhOp+rLXfnHhKaQnxTB1znavo4iIiIg0CypAiIi0Ep+v30dcVBiT+id7HUWA0BDjutFpLM/OZ+2uAq/jiIiIiHhOBQgRkVagutoxc+N+zuibpF0vmpHLh3cjKjyElxdkex1FRERExHN6lyoi0gqszikgt6iMs0/R6IfmJL5dOBcPTuHdFTkcKq3wOo6IiIiIp1SAEBFpBT7fsI8QgzP7qgDR3Fw/Jo2S8ireWZ7jdRQRERERT6kAISLSCszcsI/hPTrQMSbC6yhSy+Bu8QxMjePlBdk457yOIyIiIuIZFSBERAJUUVXNweJyr2N8bW9hKatzCpik6RfNkplx/eg0Nu49xDVPL+DOV5bx23fXNKu/QyIiIiJNQQUIEZEATZ2znUl//pLyymqvowC+0Q+Adr9oxqYMTWXy4K6UVVazfk8hL87P4r2Vu7yOJSIiItKkglqAMLPuZjbTzNaZ2Voz+9Ex2kw0swIzW+G//TaYmURETtaanAIOllSwYU+h11EA+GLDPlITounXub3XUaQO0RGhPHbtcN7+wel8cd9EuneMZu6WXK9jiYiIiDSpsCD3Xwnc55xbZmbtgaVm9qlzbl2tdrOdc5ODnEVEpFFk5ZUAsDw7n8HdEjzNkl9SzpwtuVw+vBtm5mkWabjT0xP5YPVuqqodoSH6cxMREZG2IagjIJxzu51zy/z3DwHrgdRgXlNEJJicc2TmFgOwPPtgQOcWl1Vyz2vL+cNHGwK+bmFpBQu25bFl3yEqq6qpqnZMW5TNpD/PorSiiilDUwLuU7wzNr0ThaWVrN1V4HUUERERkSYT7BEQXzOznsAwYOExnh5rZiuBXcCPnXNrj3H+7cDtAD169AheUBGR4zhQXM6hskoAVuzIb/B5uUVl3PL8Ylbt9H3gHNY9gXMHdDlm29cWZbM6p4DyympKKqrYuOcQW/cXUbOBQmRYCB1jIthdUMppPTtw/yWjGJASf3IvTJrUuPREAOZtzfN8FI2IiIhIU2mSAoSZxQJvAvc452pPml4GpDnniszsQuAdoE/tPpxzTwFPAYwcOVL7mImIJzL90y9G9erIou0HOFBcXu/Wl5m5xdz03CL2Fpbyj+uG89jMLfzirdUMT+tAYmzkUW3LK6v51TtriAoLIS46nMiwENKTYpkyJIWB3eI5UFTO+t2FZB0o4Wfn92fK0BRNvWiBktpH0rdzLHO35HLHmelexxERERFpEkEvQJhZOL7iwyvOubdqP39kQcI594GZPWFmic45rc4lIs1OVp5v+sW3h6ayaPsBVuw4yKT+netsv7ewlGufXsDhiipe/d4YhvfoQHpyLJP/Poefv7map28ccVQBISf/MFXVjgemDOSKEd2C/nrEO+PSE3ltcTZllVVEhoV6HUdEREQk6IK9C4YBU4H1zrm/1NGmi78dZjbKnykvmLlERE5UZl4JIQYXDupCiMGK7LqnYRSVVXLzc4spOFzBy7eNZniPDgD07dyen57Xj8/W7+XNZTm1+vcVOHp2ahe8FyHNwrj0TpRWVB/375CIiIhIaxLUAgRwOnADMOmIbTYvNLM7zOwOf5srgDX+NSAeBb7jnNMUCxFplrLyiklJiCahXQT9u8SxvI51ICqrqvnhq8vYuPcQj103/BtrNNxyei8ykmN5Z/nRBYgs/wKXaZ1igvMCpNkY3bsTIQZzt6rmLiIiIm1DUKdgOOfmAMednOycewx4LJg5REQaS2ZeCT39xYGhPRKYvmIX1dWOkBCjtKKKOZtzWZp9kLlbclm1s4D/u3QQZ/VL/kY/ISHGoNR45tf68JmZV0JMRCiJscdfV0JavvjocP/fgVw4p6/XcURERESCLtgjIEREWpWsvGJ6JvqmRwzrnsChskq27i+itKKKa59ewG0vLuHpr7ZhZjw4ZQDXjq57156M5Fj2FJZyqLTi62PZB0pI6xSjhSXbiHEZiSzPzqfYv7OKiIiISGvWZNtwioi0dPkl5eSXVHw9AmKYf02H5dn5PPHlVpZl5/Pw5YO5ZGgKUeH1LyrYJzkWgC37ir7uKzOvmH6d2wfpFUhzMy69E//4ciuLMw8w8RgjZURERERaE42AEBFpoCz/Fpw16zP0ToyhfVQYf/pkI28vz+G+c/py1WndG1R8AN8ICIDN+4oAqKp27PCPgJC2YWRaRyJCQ5indSBERESkDVABQkSkgWrvUBESYgztnsC+Q2VcPCSFuyZlBNRfj47tiAgNYau/ALEr/zAVVU47YLQh0RGhDOuRwLyt2nlaREREWj8VIEREGigrr+0dc04AACAASURBVAQz6N7xPwWCK0Z04/wBXfjjFYMDXrchLDSE3kkxX4+AqD3CQtqG0zMSWburkPyScq+jiIiIiASVChAiIg2UmVdM17ioo6ZYTBmaypM3jGjwtIva0pNj2VJTgDjgH2GRqBEQbcm49E44Bwu2aRqGiIiItG4qQIiINFBWXuOvz9AnOZYdB0soragiK6+EiLAQOrePatRrSPM2pHsCMRGhzN2iAoSIiIi0bipAiIg00JFbcDaWPsntcQ627i8iM7eYtI7tCAnRFpxtSXhoCKN6ddQ6ECIiItLqqQAhItIAh0oryC0qb/QREBlHbMUZjBEW0jKMS09k6/5i9hSUeh1FREREJGhUgBARaYCaBSIbe4eKnontCA0xNu09RNaBYu2A0UaNy+gEwPxtGgUhIiIirZcKECIiDRCsHSoiw0JJ69SOeVvzKK2oJi1RIyDaolO6xNGhXbjWgRAREZFWTQUIEZEGWJx5gLAQIy0IIxQykmJZsSMfaPwRFtIyhIQYY9M7MX9rHs45r+OIiIiIBIUKECIi9cgtKuO1xdlMGZpKu4iwRu+/T+dYaj5zpnXUCIi2amx6Ijn5h9meW+x1FBEREZGgUAFCRKQez87ZTlllNT84Kz0o/fdJbg9AWIiRkqAtONuqs/snYwbTV+72OoqIiIhIUKgAISJyHAUlFbw4P4sLB3UlPSk2KNeo2Qmje8d2hIXqf8ttVUpCNGN6deLt5Ts1DUNERERaJb3TFRE5jhfmZ1JUVsmdEzOCdo30pFjMCMr6EtKyXDo8lcy8kq/XBBERERFpTVSAEBGpQ3FZJc/O3c7Z/ZM5NSUuaNeJjghlQp8kxmckBu0a0jJcMLALkWEhvL08x+soIiIiIo1OBQgRkTq8tCCL/JIK7pwUvNEPNV68ZRS3Tegd9OtI89Y+KpxzTu3M9JW7qKiq9jqOiIiISKNSAUJE5BgKSyt4ctZWJvZLYniPDl7HkTbk0mGpHCypYNbG/V5HEREREWlUKkCIiBzDM7O3k19SwY/P7ed1FGljzuibRKeYCE3DEBERkVZHBQgRkVryisqYOnsbFw3qysDUeK/jSBsTHhrCxUNS+HT9XvJLyhut32dmb+P3H26gulo7bIiIiIg3GlyAMLMYMwvx3+9rZpeYWXjwoomIeOMfX27lcEUV/31OX6+jSBt1zageVFRV848vtzZKf3lFZTz88UaenLWV+6ev1TafIiIi4olARkB8BUSZWSrwCXAD8HwwQomIBFNBSQVvLdvJ/e+tZWWt7Q7X7irgxQVZXDa8GxnJsR4llLauX5f2XDasG8/NyyQn//BJ9zdtUTblldVcPCSFF+dn8adPNjZCShEREZHAhAXQ1pxzJWZ2K/CEc+5hM1sRrGAiIo2hoqqaRz7dxJ7CUg6XV5FXVM6y7INUVjtCDJ6fl8nkwV25ZlQPpi3K5v3Vu4mPDudHZ/fxOrq0cfee25fpq3bxl0828eerhpxwPxVV1by0IIsJfRJ59DtDiY0M5fGZW+kUE8kt43s1YmIRERGR4wuoAGFmY4HrgFv9x0IbP5KISOP5YPVunvhyKynxUcREhhEbFcb3zujNeQO60Dsphqe/2sbTs7cxY9Vu2kWE8oOJ6XxvQm8S2kV4HV3auNSEaL47ridPz97GbRN6cUrXuBPq58M1e9hbWMbvLxuMmfE/3x7EnoJSHvl0E5eP6EZ8tGZTioiISNMIpADxI+AXwNvOubVm1huYGZxYIiKN44V5mfRKjOHze88kJMS+8fx95/bj+jFpfLVpP5P6J9MpNtKDlCLH9oOJ6by2KJs/fLSB528edUJ9PDd3O70SYzizbxIAoSHGj8/rx0WPzuGl+ZncNUmjfURERKRpNHgNCOfcV865S5xzf/A/3uacuzt40URETs6qnfksy87nhjFpxyw+1OgcF8WVI7ur+CDNTkK7CO6alMGXG/fz9vKdAZ+/Ykc+y7PzuWns0f8NDEiJZ1L/ZKbO2U5JeWVjRhYRERGpUyC7YPQ1s6fM7BMz+6LmFsxwIiIn4/l5mbSLCOWKkd28jiJywm45vRejenbkV2+vYcu+ooDOfXF+JrGRYVwxsvs3nrvzrHQOllTw6sLsRkoqIiIicnyB7ILxb2A58GvgJ0fcRESandyiMmas3M0VI7oRF6U57tJyhYWG8Og1w4gKD+XOV5ZxuLyqQeeVVlTx8Zo9TB7cldjIb864HJHWkTG9O/L07G2UVTasTxEREZGTEUgBotI59w/n3CLn3NKaW9CSiYichNcWZVNeVc2NY3t6HUXkpHWJj+IvVw1h495D3P3acp6ctZVHP9/MO8tz6jzny437KS6vYvLglDrb3HlWBnsLy3hzad39iIiIiDSWQBahnG5mPwDeBspqDjrnDjR6KhGRk1BcVsnLC7KZ0CeRjORYr+OINIqJ/ZK551t9+Otnm/l03d6vj4/u3ZGu8dHfaD9j1S46xUQwpnfHOvscn5FI/y7teWdFDteO7hGU3CIiIiI1AilA3OT/eeS0Cwf0brw4IiInp6yyijteXsq+Q6U8cvVQr+OINKp7vtWXW8f3IjTE2HnwMOc+8hWfrN3LTeN6HtWupLySz9fv47LhqYSF1j3Y0cw4PSORlxZkUVpRRVS4dtcWERGR4AlkF4xex7ip+CAizUZVtePe11cye3Muf7h8MGPTO3kdSaTRtY8Kp11EGH07tycjOZaP1uz5RpsvNuzjcMXxp1/UGN2rI+WV1azaWRCMuCIiIiJfC2QXjHAzu9vM3vDf7jIzrewmIs2Cc47fvLuG91ft5tcXncKVx1j1X6S1OX9AFxZlHuBAcflRx2es3E1S+0hG9ap7+kWN03r62izclheUjCIiIiI1AlmE8h/ACOAJ/22E/1idzKy7mc00s3VmttbMfnSMNmZmj5rZFjNbZWbDA3kBIiJV1Y5fvLWaVxdm84OJ6dw2QYOzpG04f2AXqqodn63/z5oQRWWVzNy4j4sGdSU0xOrto0NMBP27tGdRppZ0EhERkeAKZA2I05xzQ454/IWZraznnErgPufcMjNrDyw1s0+dc+uOaHMB0Md/G42vqDE6gFwi0oZVVFXz3/9awYxVu7l7Ugb/fU5fryOJNJkBKXGkJkTz8Zo9XOUf9fPZur2UVVZz0eCuDe5ndK+O/HvpTiqqqgk/zpoRIiIiIicjkHcZVWaWXvPAzHoDx9043Dm32zm3zH//ELAeSK3VbArwovNZACSYWcPfNYlIm+Wc465XlzFj1W5+cUF/7j23H2b1f+Mr0lqYGecP7MLszbkUlVWy82AJf/x4I6kJ0Yzo0aHB/Yzq1YmS8irW5GgdCBEREQmeQAoQPwFmmtmXZjYL+AK4r6Enm1lPYBiwsNZTqcCOIx7v5JtFChGRb5i1aT8fr93LT8/vx3+dmV7/CSKt0HkDulBeVc1ri7K59umFHCqt4J83jCCkAdMvatSsFbFwu6ZhiIiISPA0eAqGc+5zM+sD9PMf2uicK2vIuWYWC7wJ3OOcKww8JpjZ7cDtAD16aK9ykbbOOcffPt9MakI0t43Xmg/Sdo1I60BibAT/8/56YiPDePm20QxMjQ+oj6T2kfROimHR9gPcoWKeiIiIBEm9IyDMbJL/52XARUCG/3aR/1h954fjKz684px76xhNcoAjl6vv5j92FOfcU865kc65kUlJSfVdVkRauTlbclmenc/3J6YTEaY569J2hYYYFw9JoV1EKM/ffBpDuyecUD+je3ViceYBqqpdIycUERER8WnICIgz8U23uPgYzzngWEUFwLfDBTAVWO+c+0sdzd4D7jKz1/AtPlngnNvdgFwi0kY55/jbZ5vpGh/FlSO7eR1HxHO/vPAU7vlWX+KjT3x37NG9OjJtUTbrdxcGPIJCREREpCHqLUA4537nv/ugc277kc+ZWa96Tj8duAFYbWYr/Md+CfTw9/0k8AFwIbAFKAFubnB6EWmT5m/NY0nWQR6cMoDIsFCv44h4Ljw0hPjokxsJNLq3bx2IeVtzVYAQERGRoAhkG843geG1jr0BjKjrBOfcHOC4q2A55xxwZwA5RKSN+/sXW+gcF/n1toMicvK6xkczuFs8D3+0EcO4dXyvgBayFBEREalPvQUIM+sPDADia635EAdEBSuYiMix5BaVMX9bHvee05eocI1+EGlML90ymp++uZL//WA987fl8ecrh9AhJsLrWCIiItJKNGS8Zj9gMpCAbx2Imttw4HvBiyYi8k3ztuYBcEZfLUYr0tji24Xz5PUjeOCSAczZnMt3n1vE4fIqr2OJiIhIK9GQNSDeBd41s7HOuflNkElEpE5zNu8nLiqMQZqjLhIUZsZN43qSkhDN7S8t4d7XV/D4tcM1HUNEREROWiArVi03szvN7Akze7bmFrRkIiK1OOeYszmXcemJhOrDkEhQnXNqZ3514Sl8uGYPf/pko9dxREREpBUIpADxEtAFOA+YBXQDDgUjlIjIsWzPLWZXQSnj+yR6HUWkTbh1fC+uG92DJ77cynsrd51QH9l5JZRVahqHiIiIBLYLRoZz7kozm+Kce8HMXgVmByuYiEhtc7bkAjBBBQiRJmFm3H/JANbuKuTB6es4q18S7aPCG3z+vxZn87M3VxMeavTvEseoXh358bn9iI7QArIiIiJtUSAjICr8P/PNbCAQDyQ3fiQRkWObvTmXbh2i6dGxnddRRNqM8NAQHrhkALlFZTz2xZYGn5eTf5iHZqxneI8Ebh3fm/ZRYUyds53731sbxLQiIiLSnAUyAuIpM+sA/AZ4D4gFfhuUVCIitVRWVbNgax6Th3TFTOs/iDSlId0TuHJEN56du52rT+tO76TY47Z3zvGLt1ZT7Rx/+84wuvuLhg9/tIEnvtzK2PROfHtYalNEFxERkWakwSMgnHPPOOcOOudmOed6O+eSnXNPBjOciEiNlTsLOFRWyfgMbb8p4oWfnt+fqLBQHpqxrt62/166k6827edn5/f/uvgAcO85fTmtZwd++fZqtu4vCmZcERERaYYaXIAws0gzu9bMfmlmv625BTOciEiNOZtzMYNx6Z28jiLSJiW1j+Tus/swc+N+vtiwt852G/YU8tCMdYzq1ZEbxqQd9VxYaAiPXjOMyLAQ7nxlGaUVWpxSRESkLQlkDYh3gSlAJVB8xE1EJOhmb97PwJR4OsREeB1FpM26aVxPeifF8NCM9ZRXVn/j+Y/W7OGyJ+YRHR7KH68YTMgxtsvtGh/NX64eyoY9h3hgev2jKURERKT1CKQA0c05d7Vz7mHn3J9rbkFLJiLil5lbzJKsg5xzamevo4i0aRFhIfx28qlszy3mubnbvz7unOOvn23ijpeX0rdze6b/cDxpnWLq7OesfsnccWY60xZl8+6KnKaILiIiIs1AIAWIeWY2KGhJRETqMG1RNqEhxtWndfc6ikibN7FfMt86JZlHP9/MvsJSyiqruOdfK/jrZ5u5fHg3Xrt9DJ3jourt575z+zIyrQO/fGs127QehIiISJsQSAFiPLDUzDaa2SozW21mq4IVTEQEoLSiiteX7ODcUzs36EONiATfry86lYoqxwPT13HTs4t4d8UufnJeP/505WCiwkMb1Ee4fz2I8LAQfvDKMgoOV9R/koiIiLRogRQgLgD6AOcCFwOT/T9FRILmozV7OFhSwXWj0+pvLCJNomdiDLeM78X7q3ezNOsgj1w9hDvPygh4i9yUhGj+evVQtu4v4rpnFnCguDxIiUVERKQ5qLcAYWZx/ruH6riJiATNKwuz6NmpnXa/EGlm7pqUwVUju/HCLaO4dFi3E+5nYr9knrphJJv2FvGdp+az71BpI6YUERGR5qQhIyBe9f9cCizx/1x6xGMRkaDYsKeQxZkHuW502jFX0xcR78RGhvHwFUMYl5540n2d1T+Z5797GjsPHuY7Ty3gUKmmY4iIiLRG9RYgnHOT/T97Oed6+3/W3HoHP6KItFWvLswmIiyEK0ac+LerItIyjMtIZOpNp5GZW8z972l7ThERkdaowWtAmNmlZhZ/xOMEM/t2cGKJSFtXWlHF28tzuHBgFzrERHgdR0SawNj0Ttx1VgZvLtvJjFW7vI4jIiIijSyQRSh/55wrqHngnMsHftf4kUTEKzM37mPK43NZsSPf6yh8vn4fh0oruWKEtt4UaUt+eHYfhnRP4JdvrWZX/mGv44iIiEgjCqQAcay2YY0VRES8U1ZZxUMz1nHzc4tZuSOfP3+y0etIvLlsJ13iohirxSdF2pTw0BD+dvVQKqsdP3ljpddxREREpBEFUoBYYmZ/MbN0/+0v+BaiFJEWbOv+Ii57Yh5T52znprFp3POtPszenMvqnQX1nxwk+w+VMWvTfi4dnkqoFp8UaXN6JsZw7zl9mbslz9P/F4mIiEjjCqQA8UOgHPgX8BpQCtwZjFAiEnzOOf61OJvJj85hV/5hnr5xJA9MGcgt43vRPjKMJ2dt9SzbuytyqKp2XDYs1bMMIuKtK0d2JzIshGmLs72OIiIiIo2kwVMonHPFwM+DmEVEmkBJeSVzNufy76U7+XTdXsb27sQjVw+lS3wUAHFR4Vw/No0nZ21le24xvRJjmjzjW8tyGNwtnj6d2zf5tUWkeYiPDueiwV15b8UufnXhKcREataniIhIS9fgf83N7FPgSv/ik5hZB+A159x5wQonIifv5QVZLM48QHFZJfklFazKKaC8sprYyDB+cl4/7jgz/RvTHG4+vSdT52znqa+28v8uG9ykedfvLmTd7kIeuGRAk15XRJqfa0f14K1lOby/ajdXnaYFaUVERFq6QL5OSKwpPgA45w6aWXIQMolII5m3JZdfv7OGLnFRdIyJIDYyjBvGpHF2/2RG9uxIRNixZ2Elt4/iyhHd+PeSndw6vhcZyU03EuGtZTsJDzUuHpLSZNcUkeZpRFoHMpJjeXVRtgoQIiIirUAgBYhqM+vhnMsGMLM0wAUnloicrMqqah6Yvo7uHaP59L/PJCo8NKDz7zgznfdX7+aSx+Zy/yUDuHJEN8yCuyBkZVU176zYxVn9kukYExHUa4lI82dmXDOqBw/NWMeGPYX07xLndSQRERE5CYEsQvkrYI6ZvWRmLwNfAb8ITiwROVmvLMxm495D/OrCUwMuPgB079iOD+6ewOBu8fz0jVXcNW05BSUVQUj6H7O35LL/UBmXDe8W1OuISMtx2bBUIkJDeG3RDq+jiIiIyElqcAHCOfcRMJz/7IIxwjn3cbCCiciJO1hczl8+3cTpGZ04b0DnE+4nJSGaV24bw0/O68fHa/Zwwd++YtH2A42Y9GhvLcshoV04k/prdpeI+HSIieC8gV14x787joiIiLRcgYyAAKgC9gGFwKlmdkbjRxKRk/WnTzZSVFbJbycPOOlpE6Ehxp1nZfDm98cRERbCd56az18+2YhzjftBoLC0gk/W7uGSISl1rk0hIm3Tuad2Jr+kghU78utvLCIiIs1Wg9/lm9lt+KZdfAw84P95f3BiiciJ+mD1bl5ZmM2NY9Po16XxFo8c0j2BGXdP4NtDU3n0iy18sm5vo/UN8MGq3ZRVVmv6hYh8w4Q+iYQYzNq4z+soIiIichIC+ZrxR8BpQJZz7ixgGKCvIkSakU17D/Hjf69kWI8Efn5B/0bvPzYyjIevGEy3DtFMnb29Uft+a1kO6UkxDOkW36j9ikjLl9AugmE9OvDlpv1eRxEREZGTEEgBotQ5VwpgZpHOuQ1Av+DEEpFAFRyu4PYXlxATGcaT148gMizwhScbIiw0hJtP78WizAOsbKTh0Nl5JSzKPMBlw4O/04aItExn9Uti1c4CcovKvI4iIiIiJyiQAsROM0sA3gE+NbN3gazgxBKRQP3sjVXk5B/mH9cNp3NcVFCvddXIbrSPDOOZOY0zCuLNZTsxg0uHpTZKfyLS+kzs51uc9iuNghAREWmxAtkF41LnXL5z7n7gN8BU4NvBCiYiDbc06yAfrd3Dj87uw8ieHYN+vfZR4VwzugcfrN5NTv7hk+orM7eYp2dvY1K/ZFISohspoYi0Nqd2jSMxNpKZG1WAEBERaakCWYTyUTMbB+Ccm+Wce885V17POc+a2T4zW1PH8xPNrMDMVvhvvw0svogA/PWzTXSMieDm03s12TVvGtcTgOfnnvgoiIqqau751wrCQoyHvj2wkZKJSGsUEmKc2TeJ2Zv3aztOERGRFiqQKRhLgV+b2VYz+5OZjWzAOc8D59fTZrZzbqj/9mAAeUQEWJJ5gNmbc7njzN7ERIY12XVTE6K5cFBXpi3aQcHhihPq4+9fbGHFjnz+77JBGv0gIvWa2C9J23GKiIi0YIFMwXjBOXchvp0wNgJ/MLPN9ZzzFXDg5CKKyPE88tkmEmMjuH5MWpNf+44ze1NUVsnTX20L+NylWQd47IvNXD68G5MHpwQhnYi0Nmf0SdJ2nCIiIi1YICMgamQA/YE0YEMjZBhrZivN7EMzG9AI/Ym0GYu2H2DuljzuODOddhFNN/qhxoCUeC4eksLUOdvZV1ja4PMOl1dx3+srSe0Qzf2XnBrEhCLSmsS3C2d4jw5aB0JERKSFCmQNiIf9Ix4eBFYDI51zF5/k9ZcBac65IcDf8e2wUdf1bzezJWa2ZP9+vfEQKSip4P731pIYG8l1o5t+9EON+87pS0VVNX//YkuDz3n44w1k5pXw8OVDaB8VHsR0ItLanH1KZ1bnFJz0ArgiIiLS9AIZAbEVGOucO98597xz7qgJmCcyesE5V+icK/Lf/wAIN7PEOto+5Zwb6ZwbmZSUFOilRFqVg8XlXDd1AVv2FfHwFYOIjgj1LEvPxBi+M6o70xZlk5lbXG/7RdsP8Py8TG4am8bY9E5NkFBEWpPzBnQG4JO1ezxOIiIiIoEKZA2Ifzrnco/T5KVAL25mXczM/PdH+fPkBdqPSFuSV1TGNU8vYNPeIv554wgm9e/sdSTuntSH8NAQ/vjxxuOuTn+4vIqfvrGSbh2i+en5/ZswoYi0Fr2TYunbOZaPVYAQERFpcRpz0rh944DZNGAikGhmO4HfAeEAzrkngSuA75tZJXAY+I5zTntriRxDXlEZL8zP4qX5mZSUVzH1ppFM6NM8RgMlx0Vx24Re/P2LLSzOPMDkwSlcMaIbp6bEHdXuT59sJDOvhGnfG9OkO3aISOty3oAuPD5zC3lFZXSKjfQ6joiIiDRQY34C+EbhwDl3zXFPcO4x4LFGzCDSKr2+eAe/eXcNZZXVfOuUztzzrT4MTI33OtZR7vlWX/p2bs/0lbt4eUEWL8zP5PX/GsOItI4ArNqZz3Nzt3Pd6B6aeiEiJ+W8AV34+xdb+Hz9Pq46rbvXcURERKSBTmQXDBFpQpVV1fzxk42c0jWOz+49k2duGtnsig8AoSHGxUNSeOrGkSz45dmkJkRz16vLOVhcTmVVNT9/czWJsZH87AJNvRCRkzMgJY7UhGhNwxAREWlhGrMAUd6IfYmI3+zNuew/VMb3J6aTkRzrdZwG6RgTwRPXDSevqJz7/r2SZ+ZsZ93uQh6cMoA47XohIifJzDhvQBdmb86lqKzS6zgiIiLSQIFsw/mWmV1kZsc8xzk3pvFiiUiNN5bupGNMBGf1S/Y6SkAGpsbzm8mn8MWGffzhow2cc2pnzhvQxetYItJKnD+wC+VV1Xy5cZ/XUURERKSBAhkB8QRwLbDZzH5vZv2ClElE/PJLyvl03V6mDE0hIqzlzZi6fkwaFw9JIS4qnAenDMC/6Y2IyEkbkdaBTjERfLRG0zBERERaigYvQumc+wz4zMzigWv893cATwMvO+cqgpRR/j979x1eZX3/f/z5yV5kkEVCCJCEvSFsBDfg1uJAcdfROlqtWlvbqv21Wmu/DlpH3RNx4sQBCgLKCnuTMEIGZBGy9/n8/kiggCAEzsh4Pa4rF8m573PnlTeHQ877fIa0W5+tyaW2wcGUYQmejnJCjDFMv2Iw5TX1dNDUCxFxIm8vw7kD45i5PEu7YYiIiLQSzXpL1RgTCVwH/BJYBTwNDAXmOD2ZiPDBimz6xIXSL77lLTp5vIwxaj6IiEtcM7ortfUOZi7P8nQUEREROQ7NWQNiFrAQCALOt9ZeYK1911p7B9A6VsYTcbP6Bgdb9pSd0H235pWxJruk1Y5+EBFxtZSYDoxNieTtJZnUNzg8HcdlqusauH3GSp6em+7pKCIiIielOSMgpltr+1prH7XW7j74gLU21cm5RFq9qtoGbnlzBROfWsAz8zKaff/307Lw8TJcODjeBelERNqGa0d3I7ekmrmb8jwdxSUaHJbfzlzN52t388z8DArLazwdSURE5IQdswFhjLnEGHMJELH/84M/3JBRpNXZV1nLtJeX8t2WfIYkhvP411t49Ycdx33/8pp6Zi7PYmL/TkRpXrOIyFGd0SeWzuGBvP5jpqejOJ21lj99vJ6vNuzh+rHdqK138NaStvdziohI+3E8i1Ce/zPHLPCRk7KItAl5pdVMe2kpmUWVPHvlUM7qG8uv317Jw59txMfLcFbfTnQI8CHIz/uou0K8tzyLsup6bjolyc3pRURaF28vw7RRXXnsq81s2VNGr04dPB3JaZ77fhvvLNvFbaclc+/E3uwsrOCtJZncOiGZAF9vT8cTERFpNmOt9XSGZktNTbVpaWmejiHyE3ml1VzxwhLyS6t58dpUxiRHAVBT38AvX09jYXrhgXNjOvjzwjWpDO4Sfsg16hscnPqv+XQKDeCDX41xa34RkdaouKKWUY9+y3kD4/m/ywZ5Oo7TnPLP7+gWGcwbN4zAGMOi9EKmvbyUf04ZyGWpXTwdT0RE5KiMMSuOtFTDMUdAGGOmWWvfMsbcfaTj1tonnBFQpLXbU1LN1Bcbmw9v3DiCYV07Hjjm7+PNi9ekMn9LPnsr6iipquOdZbu48sUlPD9tGON7Rh849+sNSaKgnQAAIABJREFUeWQXV/Gnc/t64scQEWl1IoL9uG5MN/67YDvje0Zx4eDOno500orKa8jaW8W0kV0PjJYbmxJJ704deGXRDi4dlnDUUXQiIiIt1fEsQhnc9GeHo3yItHv5ZY3Nh4Kymp80H/YL8PVmUv84rhyZyK9OTeaDX42ma2QwN76+nPfTsg6s4P7Sou10jQzirL6x7v4xRERarXsm9mJE9478/sO1bMgt8XSck7Y2p/FnGHTQKDljDDeM7c7mPWUs3lbkqWgiIiInTFMwRE5SWXUdl/93CTuLKnjzKM2HoympquOmN9JYtmMvEUG+jEqK5Mv1e3j4gn5cO6ab60KLiLRBBWU1nP/vRfj6GD69bRwRwX6ejnTCnpq7lenfprPuoYkE+/9vwGp1XQPjHvuOrpHBvH/LaLy8NApCRERanqNNwTjubTiNMQHGmNuMMc8aY17Z/+HcmCKtS229g1vfWsHWvDKevWpos5oPAGGBvrx140ievWoo43tGsyi9kKgQP6YMS3BRYhGRtiu6gz/PXz2MvJIa7py5igZH63uTZb81WftIiQk5pPkAjaPpfj+pNysyi3lTO2KIiEgrc9wNCOBNoBMwEfgeSADKXBFKpDWoqW/g3g/W8ENGEf/4xUBO7RVzQtfx8/HinAFxPH3FENL+fCbz7jn1J79wiojI8RncJZy/XtiPhemF/OubLZ6Oc0KstazJLmFQQvgRj08ZlsD4ntE89tVmsvZWujmdiIjIiWtOAyLFWvtnoMJa+zpwLjDSNbFEWi5rLZ+tyeXMJ77nk9W53Duxl9NGLPj7eNMhwNcp1xIRaa+uGJHI1BGJPDd/G7PX7fZ0nGbLLq5ib0XtIes/HMwYwyMX98cAf5y1jtY4nVZERNqn5jQg6pr+3GeM6Q+EASf2lq9IK1VZW8+lzy/mjndWEeznw+s3jOC201I8HUtERA7z0AV9GZIYzj3vr2FrXusasLkmex/AT7ZpPlhCRBC/n9ybhemFzFqV465oIiIiJ6U5DYgXjDERwJ+AT4GNwGMuSSXSQr2flk1aZjH/78J+fHHnKUw4aPtMERFpOfx9vHnuqmH4+Xjx1Nytno7TLGuy9uHn40WvTj+/2di0kV3p3akDb2ktCBERaSWOOdHcGHP3QV9e3/TnM01/BiPSTjQ4LC8v2sHQxHCuHt3N03FEROQYOoUFcGafWL7dlIfDYVvNjhFrskroFx+Kr/fPv0/k5WU4f1A8j3+9hdx9VcSHB7opoYiIyIk5nhEQHZo+UoFfAZ2BeOAWYKjroom0LN9s2MOuvZXcPD7J01FEROQ4jU6KpLiyjs17Wsc0jPoGB+tyjr4A5eEm9+8EwFfr97gyloiIiFMcswFhrX3YWvswjbteDLXW/s5a+ztgGJDo6oAiLYG1lv8u2E7XyCDO6tvJ03FEROQ4jU6OBODHbYUeTnJ8MgrKqapr+Nn1Hw6WFB1C704dWuVimyIi0v40Zw2IWKD2oK9rm24TafNWZBazOmsfN47rjncrGcIrIiIQHx5I96hgFm8r8nSU47Imq3EByqPtgHEk5wyIIy2zmD0l1a6KJSIi4hTNaUC8ASwzxjxkjHkIWAq85opQIi3NCwu2Ex7k67TtNkVExH1GJ0eydMde6hscno7ys6y1LMooIjTAh26RQcd9v3MGxAHw1XqNghARkZbtuBsQ1tq/07gIZXHTx/XW2kddFUykpZi3JZ85m/K4elRXgvyOuW6riIi0MGOSIymvqWddTomnoxxVXYODP85ax2drcrloSGeMOf7RdikxIfSMDWG21oEQEZEWrlmvpqy1K4GVLsoi0uLsLKzgN++sonenUH59aoqn44iIyAkYldS4DsTi7UUMSYxwyfeoa3Cwp6SaLh2Pf+TCfiWVdfzq7RX8uK2I205L5ndn9Wr2Nc4ZEMfT36aTX1ZNTIeAZt9fRETEHZozBUOkTSuvqSc9r4x9lbUHvr75zTS8vAwvXD2MQD9vDycUEZETERXiT6/YDi5ZB8Jayxdrd3P2kwuY8Pg8NuaWNuv+KzL3cs70hSzfuZf/u3QQ907sfULbhZ4zIA5rtRuGiIi0bBpPLu2atZZ7P1jLnI15lFTVHbi9e1Qw/j5eZOSX88YNI0/oHS0REWk5RidHMnP5LmrqG/D3cU5DOWdfFb9+awVrskvoGRuCr7cXby/N5O8XDzhwztrsfXywIpvbT0shJvR/IxPqGxw8M28bT3+7lYSIIN67ZfRJjc7oGduB3p068H5aNteM7nYyP5ZTvJ+WRV5pNbef3sPTUUREpAXRCAhp177dlM8HK7IZkxzJ7yf15qnLB3PfpF70iAmhrLqev5zXl3E9ojwdU0RETtKY5Eiq6xys3rXPKderb3Bwx4yVbC+o4F+XDuLL34znvIHxfLwqh/KaegAcDssfPlrHG4szOfupBXy2JpfaegfvpWUx8akFPDl3KxcN7swXd45zytSQqSMSWZdTwnoPr3Xx+o87ufeDtfzrm63sKKzwaBYREWlZNAJC2i2Hw/Kvb7bQLTKI6VOH4OutfpyISFs1MikSLwM/ZBQysmlNiJMx/bsMVu7ax/SpQ7hgUDwA00Yl8uHKbD5elcO0UV35asMeNuSWcteZPZm3JZ873llFaIAPpdX19IkL5flpQ5nUP+6ks+x30eDOPDJ7E+8s23XIKAx3emPxTh78dAMTekbzQ0YhM5Zm8sC5fT2SRUREWh694pJ264t1u9m8p4y7zuqp5oOISBsXFujLsK4RfL0h76SvtWzHXv7zXTq/GJpwoPkAMLhLOH3jQnl76S4aHJYn5mwlJSaE209P4YNbR3P/5N6MTYni9RtGMPvOcU5tPgCEBfly7sA4PlmdS0XTKAx3qalv4Ik5W/nLJxs4q28sL16TysT+nXgvLZvquga3ZhERkZZLr7qkXapvcPDknK30iu3A+QPjj30HERFp9c4dEMeWvDIy8stO+BolVXXc9e5qunQM4uEL+x1yzBjDVaMS2bS7lIc+3UBGfjl3n9UTby+Dj7cXt05I5rlpw5jQM7pZ22w2x9QRiZTX1PPF2t0uuf6R/JhRyOSnFjL923QuHtKZZ64cip+PF1eP6kpJVR2frcl1WxYREWnZ1ICQdmnWqhy2F1Zw99k9T2i1cRERaX0mD4jDGPhi7YntFGGt5Y+z1pFXWs3TVwwhxP+nM1kvHNyZYD9v3lySSd+4UCb163SysZsltWsEKTEhzFi2yy3f7720LK58aSkN1vL6DSN48vLB+Pk0/no5sntHesSE8NZS92QREZGWTw0IaXccDst/5mUwMCGMs/vGejqOiIi4SWxoAMO7duSLdSf2jvwHK7L5Yu1u7j67J4O7hB/xnBB/Hy4e2hmAeya6v8ltjOGK4V1YnbWPTbubtyXoifhgRTY9YkL4+rfjmdAz+idZpo3qypqsfazL9uzCmCIi0jKoASHtzvfpBWQWVXLTKUkuGwIrIiIt07kD49iaV056XvOmYeworODBTzcwOimSW8Yn/+y5d53ZkycuG8RpvWJOJuoJ+8XQBAJ8vXh6brpLv09JVR0rMos5u18sAb5H3tr04qGdCfLz5s0lO12aRUREWgeXNiCMMa8YY/KNMeuPctwYY6YbYzKMMWuNMUNdmUcE4O0lmUSF+DPRzcNiRUTE8yb379Q4DWPd8a+RUNfg4DczV+Hr7cUTlw/C+xijGiJD/LlkaILHmtwRwX7ccXoPvtqwh+82n/yim0ezKL2QBof92UZLaIAvFw6O57M1uymrrnNZFhERaR1cPQLiNWDSzxyfDPRo+rgZeM7FeaSdy9lXxXeb87l8eMKBOaoiItJ+xIQGMLxbR2Y3owHxflo2a7NLePSSAcSFBbownfPcdEoSKTEh/PnjDVTVumYXinlb8gkL9D3qdJT9Lh+eSFVdA5+7cWFMEWm/ymvq+eOsdfyQUejpKHIELn0FZq1dAOz9mVMuBN6wjZYA4cYY5+5JJXKQd5buwtK4SriIiLRP5zVNw/h2Ux7fby1g1qpsSiqP/O58bb2DZ+ZlMLhLOJP7t56Rc34+Xvz9ov7k7Kti+nfOn4rhcFjmbylgfM9ofI6xlfWghDB6xXZg5vIsp+cQETlYUXkNU19Ywoylu7j3/TXaBrgF8vRbwJ2Bg/83ym66TcTpausdzFy+i9N7xZAQEeTpOCIi4iGT+nfCy8CNr6dx7SvLuOvdNTz8+YYjnvvRymxy9lXxmzN7tLp1g0YmRXLpsAReXLC92WteHMvG3aUUltdw6mELTx6JMYbLhndhTdY+tuxxbg4Rkf2yiyu59PnFpOeXcefpKeSWVPPKDzs8HUsO4+kGxHEzxtxsjEkzxqQVFBR4Oo60Ql9v2ENheS3TRnX1dBQREfGgmA4BvHHDSP5z5RDev3U0V41M5ONVOWTklx9yXl2Dg2fmN+6adDwvtFui+yf3xmGt06c/zNucD8CEXsdXl4uHdMbX2/CuRkGIiAvklVZz+X+XUFhew1s3juTus3txZp9Ynp23jaLyGk/Hk4N4ugGRA3Q56OuEptt+wlr7grU21VqbGh3dOn8JEM+x1vLajztJiAhkfCv9JVJERJxnXI8ozhsYz/BuHbnrrJ4E+Hrz9LeHTlWYtSqHrL1V/OaM1jf6Yb/IEH+6RwWz0clbcs7bks+ghDCiQvyP6/yOwX6c3bcTs1ZlU1OvIdEi4jzlNfVc/+py9lXWMuOmUaR26wg0NmCr6hp4ysU7AknzeLoB8SlwTdNuGKOAEmutVigSp5u7KZ8VmcXcMj7pmKuXi4hI+xIV4s/1Y7vx2ZpcNjW9UC+truOZeRn07xzK6b09s52ms/SLD2NjrvMaEHsralmVtY9Tm7nN6GXDu1BcWcfcjflOyyLiblW1DTgc1tMx2rXaeseBUQ31DQ5ue3slW/LKeOaqofTvHHbgvJSYEK4amciMZbt+MsJNPMfHlRc3xrwDnApEGWOygQcBXwBr7fPAbOAcIAOoBK53ZR5pn+obHDz21WaSooK5QotPiojIEdx8SjJvLM7kyTlbOX9QPH/9fCNF5TW8ct3wVjv6Yb++8aF8uiaXfZW1hAf5nfT1FqYXYC2c1szGzLiUKOLDAng3LYtzB2rNcWl9MosqOP/fi4gK8efaMd34xbAEQvxd+nJKDlNUXsPFz/7Irr2VRAb7ERHsR0Z+OY9eMuCITdHfnNGDj1bm8I8vN/PStakeSCyHc/UuGFOttXHWWl9rbYK19mVr7fNNzQeadr+4zVqbbK0dYK1Nc2UeaZ/eX5FNRn45903qje8xVuoWEZH2KSzIl1+OS+KbjXnc8c4qOoUG8Mlt45r9Ln9L1C8+FMBpoyC+3rCHqBB/Bhz0TuPx8PYyXJrahYXpBWQXVzoli4i71DU4+M3M1QCEBvry4KcbGP3It83a0ldOTn2Dg9tnrGJPaTW/O6snZ/aJJSzQlwfO6XPUHe4iQ/z59WnJzN2Ux+JtRW5OLEeilp20aZW19Tw5ZyvDukYwsV+sp+OIiEgLdsO4bqzLKWFsSiTXjO7WZqbs9Y1rbEBsyC1lTErUSV2rqraBeZsL+MWwzidUn0tTE5j+XTofrMjmt2f2PKksIq7U0DTNYv/jfPq36azO2sczVw7l3IFxrNpVzMOfbeS3M1cTEeTH6ORIT8ZtFx6ZvZnF24v4v0sH8YthCcd9vxvGduftJbv4++yNfHrbOLzayHN7a6W3g6VNyNpbybIdew+5zeGwPDlnK/llNfzxnN6tfgitiIi4VocAX166NpXrx3ZvM80HaHwHsFNogFMWovx+az5VdQ2c0//EplAkRAQxLiWK99OyNY9eWqQGh+XNxTsZ+v/mMOYf3/KPLzcza1U2z8zL4NJhCQemDw1JjOC164eTGBnEzW+maYtZF7LW8uaSTF75YQfXNU19aY4AX2/undiL9TmlfLLmiPsdiBtpBIS0egu2FnDbjJWUVdczvmc0fzq3D14G/vDROpbvLGbKsASGde3o6ZgiIiIe0y8+lA25JSd9ndnr9hAR5MuI7if+/+plqV24451V/LCtkFN6aGcq8azs4kp2FVVSU++grKaeFxZsY31OKaOTIgny8+bFhdtpcFi6Rgbx4AX9DrlveJAfr98wgkue/YFrX1nGR78eQ3x4oId+krZpfU4Jf/18I8t27GVsSiQPnNvnhK5zwaB4Xl60g8e/2sLk/nEE+Ho7OakcLzUgpFV7Y/FOHv5sIz1iQjh/UDzPf7+NyU8vxNsYAv28eXzKQKY0s0sqIiLS1vSND2X+1gKq6xpO+Bfv6roGvt2Ux/mD4vE5iTWVzu4XS3iQL+8uz1IDQo6poqaeHzIKOaNP7FFHJv2QUcicjXlMGZZwyC4IpdV1ZOSXk19aQ0FZNfUOS2SIP1EhjQsXfrI6lxWZxYdcKzbUn39PHcJ5A+MwxpBfVs3X6/cwOjnqiAtOdg4P5LXrR3DZ84u57tVlvH/rGMICfZ1bhHbq2fkZPP71FiKC/PjbRf25YniXE37u8fIyPHBuH654YQkvL9rBbaelODmtHC81IKRVqm9w8NfPN/LG4kzO6B3D01OHEOLvw9QRiUz/Np2Kmnrum9Sb6A7Htz+5iIhIW9YvPpQGh2XLnjIGdQk/oWssSi+koraByQNObgcLfx9vLhrcmRlLd1FcUUtE8MnvzCFtk7WWu95dzTcb87hyZCJ/v6j/T6bUfrluN3fOXEVdg+W1H3cyJDGcoYkRpO3cy7qcEn5upk/vTh24b1IvhnSJIMDXCz8fL5KjQw5p0sV0CODq0d1+NmefuFD+e/Uwrn11GTe/kcYbN47A30fvsJ+MXUWVPDlnK2f2ieVflw5ySlNnVFIkZ/WN5bn527h8eBeiQvQ6wRPUgJBWp6SqjttnrGRheiE3ndKd+yf3OdAR7xjsx0OHDY8TERFp7/rFN74rvHF36Qk3IGav301ogA+jk05+sb3Lh3fhtR938vHqHK4f2/2krydt08uLdvDNxjyGdY1gxtJdhPj78IfJ/1vX6/20LH7/4VqGJEbw9BWD+WZDHm8tyeSNxTsZ3CWc209LYVCXcGJDA4gJ9cfHy4vC8hoKy2qI6uBPz9gOTss6JiWKf106iN/MXM3d763h31cM0WKHJ+Ff32zB28vwt4v6O3VEyf2Te3P2kwt4au5W/nbRAKddV46fGhDSquwsrODG15eTWVTJY78YwOXDj7zljoiIiPxPQkQgHQJ8TngdiNp6B3M25nF23074+Zz8GuZ94kLp3zmUz9fuVgNCjiht514e/XIzk/p14rlpQ3nw0w28sGA7FTX1BPh6sz6nhKU79jIuJYoXrhlGkJ8PN4zrzvVju1HvsEfder1jsJ9TGw8Hu3BwZ/JKq3lk9mY6hQbw5/P6uuT7tHXrskv4dE0ut52WTGxogFOvnRwdwlUjE3l76S6uG9ONlBjXPBbk6NSAkFZjyfYibn1rBQBv/XIko5zwDoyIiEh7YIyhb1woG3KbvxNGflk1Ly/aQVl1PecM6OS0TKf0iObFBduprK0nyE+/kkqjvNJqlmwv4tHZm0mICOSflw7EGMND5/ejsraBt5fuIsDXi96dQrllQhJ3ndnzkCkTxhh8vT038uCmU5LYXdL4byYuLIBfnpLksSyt1WNfbSYiyJdbJiS75Pq/OaMHs1bm8Ojszbx83fBDjllrScssZm9F7YE1c878mfVHpPn0bC+twnvLs3jg43Ukdgzi5WuH0y0q2NORREREWpW+8aHMXJZFg8Me1y/T+WXVPDBrPd9tzqfBYTm1VzTjekQ5Lc/opEiem7+NtJ3FjO+pxSjbsz0l1byflsXHq3PYVlABQFSIHy9flUpoQOPwey8vw+NTBnLP2b2ICvE7qYVQXckYw5/P7UteaTV/+2ITMaEBXDAo3tOxWo0FWwtYlFHIX87re+Dv3tkiQ/z59WkpPPbVZl77YQfXjumGMYbqugbueX8Nn6/dfcj5N47rfsholk9W5/DSwh2kxIQwrGsE8eEBrNq1j+U795JfWkPP2A70iQtlfM8ohiRGuORnaM3UgJAWrcFheeyrzbywYDun9IjiP1cO1crCIiIiJ6BffBhVdTvZUVhBSkzIMc//19db+H5LAb88pTuXpXYhOfrY92mOYV0j8PEyLNlepAZEO1VaXce9769hzsY8HBZGJXXk8uFdGJ0URd/40J80yowxdApz7pB8V/DyMjxx2WAKy5Zxz3tr2JBbwg1juzt9OkFbY63liTlbSYgI5KpRrp1mff3Ybvy4rZCHPtvI/K0F3HN2Lx6YtY61OSXcO7EXp/aKJtDXmzcWZ/Lyoh10jQzimtHd+GBFNvd+sIbukcEsTC9k1qocALxM43Nsj9gQtuSV8fXGPUz/Lp1nrxrKxH7OGznWFqgBIS1WeU09v525irmb8rl6VFcePL9vi+12i4iItHT94kMBWJlZfMwGRNbeSj5amcO0UV35w+Q+LskT7O/DoC7hLN5e5JLrS8v3jy83M2djHjePT+aK4V3a1AjXAF9vXrwmlT9/sp4XF2znlUU7uHhIZ+6b1Fu7LxzFku17WZ21j79d1N/lu4gE+Hrz+vUjeGPxTh79cjPn/XsRwX7evHB1Kmf1jT1w3p/P60t2cRUPfbqBjPxy3lySydjkKF68JpUAXy+y9laxu6SKfp3DDtmmtaSyjuteW8YdM1bx2vXDGZPivNFjrZ1ezUmLlF9azZTnfmTelgL+emE//t9F/dV8EBEROQm9YjuQFBXMzOW7jnnus/O34WUMt0xw7fz1UUkdWZtdQkVNvUu/j7Q8y3bsZcbSXdwwtjv3T+7dppoP+4UF+TJ96hDm33MaV45I5OPVuUx+eiELthZ4OlqL9Nz324gK8WPKsAS3fD8vL8N1Y7vzxZ2nMHVEFz741ZhDmg8A3l6G6VMH0zc+lDcWZzIuJYqXrk0l0M8bYwyJkUGMTIo8pPkAjX/3r143nO5RwfzyjTRWZ+1rdj6Hw7I6ax+bdjd/7Z6WTK/opMWx1nLPB2vJLKrk1euGc80x9l4WERGRY/PyMlw1qisrd+1jfc7Rd8PI2VfFByuyuHx4F+LCAl2aaXRSFA0Oy/Kde136faRlqalv4A8frSUhIpC7z+7p6TgulxgZxMMX9ueT28YSHujLNa8s45HZm3A4rKejtRgbcktYsLWA68d2P2RRUXdIiQnh0UsG0icu9IjHg/x8ePW6ETx4ft+mkQ/Hly88yI83bxxBVIg/V724hI+bpmv8HGst87bk87v31jDikblc9MwP/Pf7bc36eVo6TcGQFufDlTks2FrAwxf005xQERERJ5oyNIHHv97M20szefSSgUc85/n5jb/s3nqqa1agP9iwrhH4ehuWbN/Lqb1iXP79pGV4Zt42thVU8PoNI9rVDih94kL57I5xPPzZRl5YsJ2+caFcNKTzcd8/u7iSZ+dvo6CshhvHdT+wI5y1ls17ykjPL6eypp6K2gYqa+opr62nsqaB5OhgLh6SQFjQ/9ZRy91XRXiQb4up//PfbyfE34dpo7p6OsoRRXfwP6Etg2NCA3jvltHc+c4qfvvuan7IKOT+yb2pqmtgX2Udvt5eJEQEEuzvw9LtRTz21WZW7tpHWKAvE3pGc3rvmDb3eqhlPOJEmuSXVfP/Pt9IatcIrm6hT0AiIiKtVViQLxcN7szHq3K5f3KfnyzsnLuvineXZzFlWBc6h7t29ANAoJ83g7UORJvkcFheXrSDvNJqQgN9CfLzJiO/nNVZ+9iSV8bFQzozoY29sDoeAb7e/P2i/qzO2seTc7dy7sA4fI8xzTizqIIXF27n3eVZGAyhgT5c8UIeo5MiGZAQxtcb9pBZVPmT+/n5eBHo601JVR3/+Goz5w2Mx8fLsCijkOziKgJ8vTi9dwznDojnjD4xbh95sF9mUQVfrM3lpvFJbXKx+U5hAcy4aSRPf5vOf+Zl8P6K7J+cExrgQ2l1PbGh/jx6yQCmDEs45uOitVIDQlqUBz/ZQFVdA49NGYiX9tsVERFxummjujJzeRYfrsjmhnH/e0fPWsufP16PMfBrN4x+2G9UUiTPzt9GWXUdHVy07Z6430uLtvPI7M0E+HpRXecAIDzIl0EJ4UzuH8cN47p5NqAHeXkZfndWT375RhofrMhm6oif7vhQXdfAx6ty+HBlNst3FuPrbbh8eBduOy2FiCA/ZizdxXPfb2P5zr2MTo7klvHJpHaLIMTfh2A/H4L8vQ+8gF2fU8KMZbv4ZFUOXl6G0UmR3DC2OzsKK/hy/R5mr9tD5/BA7pnYkwsHdXbb7+DWWuZvLeDR2Zvw8fLixhMYYdBa+Hh78buzG3fXWJFZTHigH2FBvtTWO8guriK7uJLuUcFMG9XVY40gdzHWtr65R6mpqTYtLc3TMcTJ3l2+i99/uI77JvXi16emeDqOiIhIm3Xxsz9QUlnHt7+bgDGNLzZmrcrmrnfX8Kdz+/DLU1y7+OTBfswo5MqXlvLqdcM5rbemYbQEReU1FFXU0iMm5MDjoznWZZdwyXM/cEbvWJ6bNpR6h6Wipp6wQN8Tul5bZK3l4md/JK+0mnn3nHrIi866Bgc3vLachemFJEUHM2VYApcMSfjJFqS19Q7qGhwE+x/fe8q19Q68vcwh25s2OCyLMgp5/OvNrM8ppW9cKNOnDjmurXpPlLWWZTv28tTcdBZvLyKxYxAPnt+XM/rEHvvO0moYY1ZYa1MPv10jIKRFmLsxjz/OWs8pPaK42Y2/9IiIiLRHV4/qyt3vreGvn2/knrN7UVFbz0OfbmRoYvgJzXM+GUO7RuDn7cWS7UVqQHiYtZZZq3J48JMNlNXU0zk8kNN7x3D58C707xx2xPtszC3lsa82ExHky03jk+gWGcydM1cRFeLPP34xAGMMvt6G8CA/N/80LZsxhvsm9uLKl5Y27gbSNBrJWsv9H65jYXohj1w8gKkjuhwZ/3dVAAAgAElEQVS1aePn44Wfz/EP0z/Sud5ehgk9ozklJYrP1uby4Kcb+MNHa3nvltFObxbVNzj4aFUOr/2wk427S+kY7MdD5/flypFdm/VzSOumBoR43PKde7ltxkr6x4fy3LRh2m5TRETExc4fFM/yncW8+sNOvl6/h/jwQKrqGvjnlEGHvDvqDgG+3gxO1DoQnpZfVs3Dn23ki7W7Gd4tggsHd2b+lgLeX5HFu2lZTL9iMJP6xx04v7qugenfpvPfBdsJD/RtnDKwOpfO4YHkllTxzk2j1HQ4hjEpUYxJjuTf36VTU+/gjD4xfL52Nx+uzOY3Z/TgypE/nZrhKl5ehgsHd6aipoE/zlrHl+v3cM6AuGPfsRmmf5fB9G/T6RXbgUcvGcBFgzsT6Ne2pxvIT2kKhnhUZlEF5/97EVEd/Hn/ltFEhvh7OpKIiEi7kbZzLw/MWs+WvDLun9ybWye4b+2Hgz0xZyv/+S6d1Q+eTajWgXCZzKIK/vXNVlZmFpMcE0KfTh3AwKL0QjbkluLjZbj77J7cMj75QCNqb0UtN76+nNVZ+3jo/H6cMyCOd5fvYsbSXeSWVHPpsAQeOLcPxhjeXprJW4szuWpUV247TdNpj8fWvDLufm8163NKD9x26bAE/jlloEemqzQ4LOdOX0hFbT1z7prgtPUI6hocjH70OwYmhPHytamaitMOHG0KhhoQ4lF3v7ua2et3M+euCXTpGOTpOCIiIu1OXYOD1Vn7GJYY4bEFoBdvK2Lqi0t4+dpUzQN3AofDMnN5Fp+vzSU+PJCk6GDySqqZsWwXPl5enNY7msyiStLzynFYy7CuEYzvGc3Efp2OOPe/qraBO95ZxdxNeXh7GRoclrEpkdx2agpjUqI88BO2PbtLqpi3uYD8smpuOy3FozsgLEovZNrLS53alPxy3W5+9fZKXrkuldN76994e6A1IKTFySyq4JM1uVw/ppuaDyIiIh7i6+3F8G4dPZphSGI4fj6N60CoAdE8VbUNbCsoJ7qDP9Eh/mQVV3L/h+tYvL2IpOhgMvLL+WBFNt5ehstSu3DXmT2ICW1czLCuwUGDwx7zXe5AP2+enzaUp+amU13XwNSRiSRHu26RwvYoLizQrVMufs64HlGc0TuG/3yXwS+GJhDd4eRHKM9Ytou4sAAm9NQ6L+2dGhDiMc/O24a3l+Hm8Vp0UkREpD0L8PVmqNaBOC4Oh2XlrmK+3ZzP0u1FrM0uod7ROKLZr+ldc38fLx69ZABXDG9cwLCsuo7aesdPprr6entxvCPsfby9uGdiL6f+LNJy/fHcPkx+eiHTXlrKazcMJy4s8ISvlbW3koXphfz2zB5uX2NGWh41IMQjsosr+XBlNleNTDzQhRcREZH2a1RSJE9/m05JVR1hgVoHAhp3RMgrrWFbQTnbCsrZmFvK3E35FJbX4ONlGNQlnJvGJ9EvPpTiilqy91VRV2+5aXz3Q14wdtC6GtJMydEhvHbdcG5+cwWXPPsjr98wgp6xHU7oWu8s24WXgcuHd3FySmmN1IAQj3j++20YA7d4aLErERERaVlGJ0Xy1Nx0lu3Yy1l92+80jMraeh6ZvYk1WSVsLyinorbhwLEOAT6M7xHNxP6dOK1XtBoL4lJjUqJ495ZRXPfqcqY89yP3TerNlGEJB6bs1Dc4yNlXRWLHoKMuKlnX4OC9tGxO7x1zUqMopO1QA0LcxuGwbNxdyvdbC3hveTZThnUhPlxPRCIiIgKDE8Pxb1oHor02IGrrHdz61koWpRcwNiWKS1O7kBwTQnJ0MMnRIcR08NfuAeJW/eLD+OhXY7hz5ir+9PF6npqbzmWpCewsqmBheiFl1fX0iAnhurHduGhwZ0qr69heUMH2gnK2FVSwMbeUwvIapo5oGetbiOepASFukbOvisv/u5js4ioABncJ584ztD2TiIiINPL38WZY1wgWb2uf60A4HJZ73l/Dgq0FPPaLAVw+XC/YpGXo0jGIj341hsXbi3hu/jaenb+N2FB/zukfR4/YEGatyuGBWev508frOXiDxSA/b5Kig7nplO6c2kuLT0ojNSDELZ6fv4280mr+OWUgp/aKJqaD1n0QERGRQ41KiuTJuVvZV1lLeJCfp+O4RU19A5t3l/HWkkw+XZPL7yf1VvNBWhxjDGOSoxiTHMW+ylrCAn0PjMa5cVx3VmQW893mfOLCA0mOCiYpOoTYUI3YkZ9SA0JcLr+smnfTsrhkSAKXpWrxGRERETmy0cmRPDEHlu7Yy8R+nTwdx6XW55TwyOxNpO0sprbBAcAtE5K4dYJ2B5OW7fDmoDGG1G4dSfXwdr7SOqgBIS73yqKd1Dc4uPVULTgpIiIiRzcwIYwAXy/ueX8NLy7YTnJ0CLeemkz3qGBPR3Oaipp6npyzlVd+2EHHYH+uH9eNwQnhDOwSTmetjSUibZwaEOJSJVV1vLUkk3MGxLWpXx5ERETE+fx9vJl+xRDmbSlgW0E5n6zJIau4khk3jfJ0tGb7ZHUO9Q2WCwbH4+vtBcDcjXn85ZP15JZUc9XIRO6b1FtbjopIu6IGhLjUm4t3Ul5Tz680+kFERESOw9n9OnF20/SLZ+Zl8PjXW8jILyMlpoOHkx2/z9bk8puZqwF4Ys5WbjqlO0u27+WrDXvoFduBD68cwrCuGq4uIu2Pl6cDSNtVWVvPKz/s5LRe0fSLD/N0HBEREWllLh/eBT9vL95cnOnpKMdt5a5ifvf+GoZ3i+Cla1KJDfXnoc82Mn9rPr+f1JvP7xyn5oOItFsaASEuM3NZFnsrarntNG23KSIiIs0XFeLPuQPj+HBlDvdO6k2I//H96pqRX868zfmc1TeWbm6cApq1t5Kb30ijU2gA/706lY7BfpzRJ4b1OaVEhvgRrzUeRKSdUwNCXKK23sGLC7czortWxBUREZETd/XorsxalcOsVTlcParrUc+rqm1gTfY+Xl60gzkb8wB47KvNXDkykTtO70F0B3+n5iqtrmNN1j5W7drHhtwStuaVk1lUQbC/DzNvHk7H4MadAowxDEjQSFAREXBDA8IYMwl4GvAGXrLW/uOw49cBjwM5TTf9x1r7kqtziWt9vCqH3SXVPHrJAE9HERERkVZsSJdw+ncO5Y0fdzJtZCLGmAPHNuaW8tTcrWzILSW3pAprITzIlzvP6MG5A+J4Y/FO3l66i/fTsjm1VzRn9ollRPeO7CmtZntBOSVVdZzZJ5ak6JAD16yua6C8pp6okJ82LKpqG/hi3W5mLtvFil3FWAvGQPfIYHp36sAFg+I5Z0AcKTEhP7mviIiAsda67uLGeANbgbOAbGA5MNVau/Ggc64DUq21tx/vdVNTU21aWpqT04qzNDgsZz7xPUF+3nx+x7hDflEQERERaa73lmdx34druW9SL07tGUPn8ECmf5fOaz/uJCzQl3EpUSRHh5ASE8JpvaMJ8vvfe2zbC8p5edEO5m7KI6+05ojXH9QlnOFdI1iTvY81WSXUORxM6BnN1aO6MqhLOD9uK+L7LQV8s3EPZdX1JEUFc8HgeFK7dmRglzBCA7SThYjIwYwxK6y1qT+53cUNiNHAQ9baiU1f/wHAWvvoQedchxoQbcrna3O5fcYqnr1qKOcMiPN0HBEREWnlqusaOO/fi8jILz9wmzEwdUQi903sRXiQ3zGv4XBY1ueWsDa7hM4RgSRHheDjbfh8bS4frcwhPb+c/p3DGNW9I34+XryXlnVIwyI8yJfTesVw+fAujOzeUW+wiIj8DE81IKYAk6y1v2z6+mpg5MHNhqYGxKNAAY2jJe6y1mYd4Vo3AzcDJCYmDsvMbD2rIbcn1lrOmb6ImvoG5tw1AW8v/ecsIiIiJ8/hsOwoqmB9TgnpeeWc0SeGIYkRTrt+fYMDH+//bRBX1+Bg7sY8thdWMCY5koEJ4fq9RkTkOB2tAdESFqH8DHjHWltjjLkFeB04/fCTrLUvAC9A4wgI90aU4zV/awGbdpfyzykD9Z+0iIiIOI2XlyE5OoTkaNesr3Bw8wHA19uLyRrJKSLiVF7HPuWk5ABdDvo6gf8tNgmAtbbIWrt/fNtLwDAXZxIXenZeBvFhAVw0uLOno4iIiIiIiEgL4uoGxHKghzGmuzHGD7gC+PTgE4wxB7eWLwA2uTiTuMiyHXtZvrOYm8cn4efj6oeWiIiIiIiItCYunYJhra03xtwOfE3jNpyvWGs3GGP+CqRZaz8F7jTGXADUA3uB61yZSVznmXkZRAb7cfnwRE9HERERERERkRbG5WtAWGtnA7MPu+0vB33+B+APrs4hrrU+p4TvtxZw78ReBPp5ezqOiIiIiIiItDAaJy9O8dz8bXTw92HaqK6ejiIiIiIiIiItkBoQctLmbMzji3W7uWZMV8ICfT0dR0RERERERFogNSDkpGTkl3HXu6sZmBDGHaf38HQcERERERERaaHUgJATVlJVx01vrCDA14vnpw0jwFdrP4iIiIiIiMiRuXwRSmmb8kurueu91WTtrWTGTaOIDw/0dCQRERERERFpwdSAkGaprmvglR928Mx3GdQ2OHjkkgGM6N7R07FERERERESkhVMDQo6LtZZvNubx9y82sWtvJWf1jeWBc/rQLSrY09FERERERESkFVADQg6ob3CwbOdevly3h6837AFgdHIkw7t15Mv1u/kho4geMSG8eeMITukR7eG0IiIiIiIi0pqoAdHO1Tc4WLJ9L1+s2803G/ZQVFFLgK8Xp/WKwcfbix8yivhkdS5hgb48fEE/rhqZiI+31i4VERERERGR5lEDoh3bmFvKb99dxda8coL8vDm9dwznDIjj1F7RBPk1PjSsteworCCqgz+hAb4eTiwiIiIiIiKtlRoQ7VCDw/Liwu383zdbCA/yY/rUIZzdN/aI22gaY0iKDvFAShEREREREWlL1IBoZ7KLK/nde2tYumMvk/p14pFLBtAx2M/TsURERERERKSNUwOinbDW8vHqHP7y8QYc1vL4lIFMGZaAMcbT0URERERERKQdUAOiHSiprOOBj9fx+drdpHaN4InLBpMYGeTpWCIiIiIiItKOqAHRxv2QUcjv3ltDYXkN907sxa0TkvH20qgHERERERERcS81INqovRW1/OubLcxYuouk6GBmXTOWAQlhno4lIiIiIiIi7ZQaEG1MXYODt5Zk8uScrVTUNnDD2O7cO7EXgX4/3eFCRERERERExF3UgGhFFmwt4MWF2+keFcywrhEMTYwgISLwwEKSi9ILefizDaTnlzMuJYq/nN+XnrEdPJxaRERERERERA2IVsFay/Pfb+fxrzcT0yGAlZnFvLE4E4DYUH+GdY2gps7Bt5vzSewYxAtXD+OsvrHa4UJERERERERaDDUgWrjK2nru/WAtX6zdzXkD4/jnlIH4eXuxJa+MlZnFrMgsZsWuYoor6rh3Yi9uHNedAF9NtxAREREREZGWRQ2IFmxXUSU3v5nG1rwy7p/cm1vGJx0Y1dAvPox+8WFcPbob0DhKQiMeREREREREpKVSA6KFWphewO0zVgHw2vUjGN8z+mfPV/NBREREREREWjI1IFoYay3/XbCdf361mZ6xHXjh6lQSI4M8HUtERERERETkpKgB0YJU1tZz3wdr+Xztbs4dGMfjUwYS5Ke/IhEREREREWn99Oq2hdhXWcvUF5eyeU8pv5/Um1snJGlahYiIiIiIiLQZakC0ANZa7v9wHel5Zbxy3XBO6xXj6UgiIiIiIiIiTuXl6QAC7yzL4qsNe7h3Yi81H0RERERERKRNUgPCw7bmlfHwZxs4pUcUN52S5Ok4IiIiIiIiIi6hBoQHVdc1cOc7qwjx9+H/LhuEl5fWfBAREREREZG2SWtAeNCjszexeU8Zr14/nJgOAZ6OIyIiIiIiIuIyGgHhIXM25vH64kxuHNdd6z6IiIiIiIhIm6cGhAfsKanm3g/W0C8+lPsm9fJ0HBERERERERGXUwPCzRwOy13vrqamzsH0qUPw9/H2dCQRERERERERl1MDws1mrcph8fYi/nJ+X5KjQzwdR0RERERERMQt1IBwo/Kaev7x1WYGdQnn8tQuno4jIiIiIiIi4jYub0AYYyYZY7YYYzKMMfcf4bi/MebdpuNLjTHdXJ3JU56Zl0FBWQ0Pnd9XW26KiIiIiIhIu+LSBoQxxht4BpgM9AWmGmP6HnbajUCxtTYFeBJ4zJWZPGVnYQUvL9zBJUM7MyQxwtNxRERERERERNzK1SMgRgAZ1trt1tpaYCZw4WHnXAi83vT5B8AZxpg2Nzzgb19swtfbcP+k3p6OIiIiIiIiIuJ2rm5AdAayDvo6u+m2I55jra0HSoDIwy9kjLnZGJNmjEkrKChwUVzXKCqvYW32Pm4/vQcxoQGejiMiIiIiIiLidj6eDnC8rLUvAC8ApKamWg/HaZbIEH/m3XMqPt5tbmCHiIiIiIiIyHFx9QiIHODg7R4Smm474jnGGB8gDChycS63C/b3wd/H29MxRERERERERDzC1Q2I5UAPY0x3Y4wfcAXw6WHnfApc2/T5FOA7a22rGuEgIiIiIiIiIj/PpVMwrLX1xpjbga8Bb+AVa+0GY8xfgTRr7afAy8CbxpgMYC+NTQoRERERERERaUNcvgaEtXY2MPuw2/5y0OfVwKWuziEiIiIiIiIinuPqKRgiIiIiIiIiImpAiIiIiIiIiIjrqQEhIiIiIiIiIi6nBoSIiIiIiIiIuJwaECIiIiIiIiLicmpAiIiIiIiIiIjLqQEhIiIiIiIiIi6nBoSIiIiIiIiIuJwaECIiIiIiIiLicsZa6+kMzWaMKQAyPZ2jlYsCCj0dop1QrZ1HtXQf1dr1VGP3Ua1dS/V1L9XbfVRr11J93cvd9e5qrY0+/MZW2YCQk2eMSbPWpno6R3ugWjuPauk+qrXrqcbuo1q7lurrXqq3+6jWrqX6uldLqbemYIiIiIiIiIiIy6kBISIiIiIiIiIupwZE+/WCpwO0I6q186iW7qNau55q7D6qtWupvu6leruPau1aqq97tYh6aw0IEREREREREXE5jYAQEREREREREZdTA0JEREREREREXE4NCBERERERERFxOTUgRERERERERMTl1IBo54wxLWI11LbCGONtjLnFGPP/jDFjDzv2J0/lao2MMUHGmPuMMfcaYwKMMdcZYz41xvzTGBPi6XxtnTFmq6cztBXGmIEHfe5rjPlT02P5EWNMkCeztUXGmNuNMVFNn6cYYxYYY/YZY5YaYwZ4Ol9rZ4z5yBgzTc/DrmeMSTLGvGKM+ZsxJsQY86IxZr0x5n1jTDdP52trjDFexpgbjDFfGGPWGGNWGmNmGmNO9XS2tsAYE2aM+YcxZrMxZq8xpsgYs6nptnBP52svjDFfejyDdsFo+4wxHY92CFhjrU1wZ562zBjzEhAELAOuBr631t7ddGyltXaoJ/O1JsaY94AsIBDoBWwC3gUuADpZa6/2YLw2xRhTBuz/z8A0/RkEVALWWhvqkWBtxMH/9o0x/wdEAq8CFwGR1tprPJmvrTHGbLDW9mv6/AvgJWvtrKYXEX+31o792QvIzzLG5ACLgdOBucA7wBfW2lqPBmuDjDELaKxvGDCNxueN94Czgaustad7MF6bY4x5Fcik8XE9BSgFFgK/Bz6x1v7bg/FaPWPM18B3wOvW2j1Nt3UCrgXOsNae7cl8bYkx5mivNwzwubU2zp15fhJCDYi2zxjTQOMTqjnoZtv0dWdrrZ9HgrVBxpi11tqBTZ/7AM8CUcBUYIm1dogn87UmxpjV1trBxhgD7AbirLW26es1++ssJ88YMx0IB+611uY13bbDWtvds8naBmPMqv3/9o0xq4Hh1to6PZZdwxizxVrbq+nz5dba4QcdW6t6n5z9j2djTChwIY3/vw0HPgfesdZ+49GAbchhzx27rLWJRzomznH484MxZom1dpQxxh9Yba3t48F4rd7Bz83NOSbN1/Ta73sOfe233yhrbaCbIx3Cx5PfXNxmO42dxV2HHzDGZHkgT1t2oJljra0HbjbG/IXGjq+Gq56ApqbDbNvULW36Wp1TJ7LW3mmMGQa8Y4z5GPgP/xsRIScvzBhzMY3THv2ttXWgx7ILfWCMeQ34KzDLGPNbYBaN79j/5P9Babb9z8WlwJvAm8aYSOBS4H5ADQjncRhjetI4AiLIGJNqrU0zxqQA3h7O1hbVGWOSrbXbmt5BrgWw1tboudopMo0x99E4AmL/mx2xwHU0jngV59kE3GKtTT/8QEt47acGRPvwFBDBkX/x+qebs7R1acaYSdbar/bfYK39qzEmF3jOg7laozRjTIi1ttxae8P+G40xyUCZB3O1SdbaFcaYM4HbaeyaB3g4UlvyPY1ThwCWGGNirbV5TUNPCz2Yq02y1j5gjLmOxqHryYA/cDPwMXCVB6O1FeWH32CtLQKeb/oQ57kP+Axw0Dhl6w/GmEFAKHCTJ4O1UfcC84wxtTQ2eK4AMMZE0zjCR07O5TQ2Kb83xsQ03ZYHfApc5rFUbdNDHH2txzvcmOOINAVDRFodY4yxevJyGWNMHDDEWjvb01lEROR/mhZYLbbWNng6S1vUNDUu0lqr5rCIi2gERDthjOlN41zNzk035QCfWms3eS5V26RaO49q6T5HqnXTOhCqtRPosexeqrdrqb7uc5RafwJs9liotq0XcKExRo9tNzLGXG+tfdXTOdqDllBrbcPZDhhjfg/MpHEhkmVNH4bG+d73ezJbW6NaO49q6T6qtWupvu6leruW6us+P1Prmaq18+mx7VEPezpAO+LxWmsKRjtgjNkK9Nu/8NlBt/sBG6y1PTyTrO1RrZ1HtXQf1dq1VF/3Ur1dS/V1H9XavVRv1zLGrD3aIaCntdbfnXnaspZea03BaB8cQDyNW3EeLK7pmDiPau08qqX7qNaupfq6l+rtWqqv+6jW7qV6u1YsMBEoPux2A/zo/jhtWouutRoQ7cNvgW+NMen8b5ubRCCFxhXvxXlUa+dRLd1HtXYt1de9VG/XUn3dR7V2L9XbtT4HQqy1qw8/YIyZ7/44bVqLrrWmYLQTxhgvYASHLmK0XKsoO59q7Tyqpfuo1q6l+rqX6u1aqq/7qNbupXqLuJ4aEO2UMeZma+0Lns7RHqjWzqNauo9q7Vqqr3up3q6l+rqPau1eqrdrqb7u05JqrV0w2q9bPR2gHVGtnUe1dB/V2rVUX/dSvV1L9XUf1dq9VG/XUn3dp8XUWg2I9st4OkA7olo7j2rpPqq1a6m+7qV6u5bq6z6qtXup3q6l+rpPi6m1pmC0U8aYBGtttqdztAeqtfOolu6jWruW6uteqrdrqb7uo1q7l+rtWqqv+7SkWmsERDu1/wFojLne01naOtXaeVRL91GtXUv1dS/V27VUX/dRrd1L9XYt1dd9WlKtNQKinTPG7LLWJno6R3ugWjuPauk+qrVrqb7upXq7lurrPqq1e6nerqX6uk9LqLWPJ7+5uIcxZu3RDgGx7szS1qnWzqNauo9q7Vqqr3up3q6l+rqPau1eqrdrqb7u09JrrQZE+xALTASKD7vdAD+6P06bplo7j2rpPqq1a6m+7qV6u5bq6z6qtXup3q6l+rpPi661GhDtw+dAiLV29eEHjDHz3R+nTVOtnef/t3c/IZfWZRzGr6+MhuCgaeJGSHBhRdaACyEJxty0MByQahFSIIaLaNWfRQguQhPcSCjixlnmn4pCcFyEKQmWqEwkmQYVsygDtUlxJdwt5gy8hAjCc9/n4Zzrs5r3+Z335Z6Ls7p5znNsOcfWvew7y9697DvH1rPs3cu+c1bd2mdASJIkSZKkdn4LhiRJkiRJaucCYg8k+VyS55OcSvJQko8fOPvDNmfbNbZeji3n2LqXfWfZu5d959h6lr172XfO2lu7gNgPDwB3AlcDrwG/S3Ll5uzcbQ21o2y9HFvOsXUv+86ydy/7zrH1LHv3su+cVbf2IZT74XBVndj8+94kLwInktwC+BCQZdl6ObacY+te9p1l7172nWPrWfbuZd85q27tAmJPJLmwqk4DVNXTSW4Gfg5cvN3Jdo+tl2PLObbuZd9Z9u5l3zm2nmXvXvads+bWfgRjP9wDfPrghar6I3AD8IutTLS7bL0cW86xdS/7zrJ3L/vOsfUse/ey75xVt/ZrOCVJkiRJUjvvgNgDSS5M8pMkryZ5K8mbSf68uXbRtufbJbZeji3n2LqXfWfZu5d959h6lr172XfO2lu7gNgPjwJvA0er6uKqugS4fnPt0a1OtntsvRxbzrF1L/vOsncv+86x9Sx797LvnFW39iMYeyDJX6rqqo96po/O1sux5Rxb97LvLHv3su8cW8+ydy/7zll7a++A2A//SPKDJJedvZDksiQ/BE5tca5dZOvl2HKOrXvZd5a9e9l3jq1n2buXfeesurULiP3wdeAS4Jkkbyd5C/gtZ76G5WvbHGwH2Xo5tpxj6172nWXvXvadY+tZ9u5l3zmrbu1HMPZEkk8BlwPPV9W7B65/uapObG+y3WPr5dhyjq172XeWvXvZd46tZ9m7l33nrLm1d0DsgSTfBX4FfAf4U5KbDhzftZ2pdpOtl2PLObbuZd9Z9u5l3zm2nmXvXvads/bWh7Y9gEbcBlxTVe8muQJ4PMkVVXUfkK1OtntsvRxbzrF1L/vOsncv+86x9Sx797LvnFW3dgGxH845e+tNVf09yVHOvBE/yQrehDvG1sux5Rxb97LvLHv3su8cW8+ydy/7zll1az+CsR/eSHLk7A+bN+SNwCeAq7c21W6y9XJsOcfWvew7y9697DvH1rPs3cu+c1bd2odQ7oEklwPvV9W/PuDsuqp6bgtj7SRbL8eWc2zdy76z7N3LvnNsPcvevew7Z+2tXUBIkiRJkqR2fgRDkiRJkiS1cwEhSZIkSZLauYCQJEkjktyZ5Hsfcn4syebvFyMAAAGWSURBVGcmZ5IkSXNcQEiSpLU4BriAkCRpR/kQSkmS1CbJj4BvAv8GTgEvAqeBbwPnAX8FbgGOAE9szk4DN2/+xP3ApcB7wG1V9erk/JIkaTkuICRJUosk1wDHgWuBQ8BLwIPAw1X15uY1PwbeqKqfJjkOPFFVj2/OfgPcXlWvJ7kWuLuqvjT/P5EkSUs4tO0BJEnSzvoi8Muqeg8gya831z+7WTxcBFwAPPX/v5jkAuALwGNJzl7+WPvEkiSpjQsISZI07ThwrKpOJvkWcPQDXnMO8J+qOjI4lyRJauRDKCVJUpdngWNJzk9yGPjK5vph4J9JzgW+ceD172zOqKr/An9L8lWAnPH5udElSdLSXEBIkqQWVfUS8AhwEngSeGFzdAfwe+A54OBDJX8GfD/Jy0mu5Mxy4tYkJ4FXgJumZpckScvzIZSSJEmSJKmdd0BIkiRJkqR2LiAkSZIkSVI7FxCSJEmSJKmdCwhJkiRJktTOBYQkSZIkSWrnAkKSJEmSJLVzASFJkiRJktq5gJAkSZIkSe3+B8AfX6UUExb5AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_WmVvif71bPo"
      },
      "source": [
        "**India**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XiSNAEuD1hJo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "da8a2e22-8973-4e50-94aa-526f32948142"
      },
      "source": [
        "#Save USA data into a separate dataframe\n",
        "df_India = df[df[\"iso_code\"] == 'IND'].copy()\n",
        "df_India"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "      <th>vaccines</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>21866</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-01-15</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21867</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-01-16</td>\n",
              "      <td>1.911810e+05</td>\n",
              "      <td>191181.0</td>\n",
              "      <td>191181.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21868</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-01-17</td>\n",
              "      <td>2.243010e+05</td>\n",
              "      <td>224301.0</td>\n",
              "      <td>112150.0</td>\n",
              "      <td>0.02</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21869</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-01-18</td>\n",
              "      <td>4.540490e+05</td>\n",
              "      <td>454049.0</td>\n",
              "      <td>151350.0</td>\n",
              "      <td>0.03</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21870</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-01-19</td>\n",
              "      <td>6.748350e+05</td>\n",
              "      <td>674835.0</td>\n",
              "      <td>168709.0</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22146</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-22</td>\n",
              "      <td>1.009946e+09</td>\n",
              "      <td>712404590.0</td>\n",
              "      <td>5540317.0</td>\n",
              "      <td>72.48</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22147</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-23</td>\n",
              "      <td>1.013637e+09</td>\n",
              "      <td>714084133.0</td>\n",
              "      <td>5850184.0</td>\n",
              "      <td>72.75</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22148</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.022268e+09</td>\n",
              "      <td>717676310.0</td>\n",
              "      <td>6560451.0</td>\n",
              "      <td>73.36</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22149</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.024150e+09</td>\n",
              "      <td>718444141.0</td>\n",
              "      <td>6456459.0</td>\n",
              "      <td>73.50</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22150</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>721149084.0</td>\n",
              "      <td>6248147.0</td>\n",
              "      <td>73.98</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>285 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      country  ...                                vaccines\n",
              "21866   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "21867   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "21868   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "21869   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "21870   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "...       ...  ...                                     ...\n",
              "22146   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "22147   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "22148   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "22149   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "22150   India  ...  Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "\n",
              "[285 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "579u-YDyuKv_"
      },
      "source": [
        "#Drop the dates with missing values, previously NaN that we filled with 0. \n",
        "df_India.drop(df_India.index[df_India['total_vaccinations'] == 0], inplace = True)"
      ],
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wERcd8sS2AmN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 431
        },
        "outputId": "f18e93b5-34c3-46d9-9cf1-c0c70fb8b61d"
      },
      "source": [
        "#Plot total vaccinations as a function of date\n",
        "plt.figure(figsize=(18,6))\n",
        "sns.lineplot(data=df_India, x=\"date\", y=\"total_vaccinations\")\n",
        "plt.title(\"Total vaccinations in India\")\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ITtuH2vzukdW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "outputId": "43bc8d6a-7a9e-4087-ae7a-e31460592444"
      },
      "source": [
        "#Plot daily vaccinations as a function of date\n",
        "plt.figure(figsize=(18,6))\n",
        "sns.lineplot(data=df_India, x=\"date\", y=\"daily_vaccinations\")\n",
        "\n",
        "plt.xticks(rotation=90)\n",
        "plt.title(\"Daily vaccinations in India\")"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Daily vaccinations in India')"
            ]
          },
          "metadata": {},
          "execution_count": 57
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u4FziWWiwt2P"
      },
      "source": [
        "Top 10 countries with highest amount of vaccinated people per 100 of the population.(First sorted by total vaccinations deployed to make sure the data is not skewed by small countires with low populations)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BprBBKS7wtO7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "7a7b9838-439a-490c-f5a4-74e1cb009186"
      },
      "source": [
        "#Group by total vaccinations given by country and sort descending to identify the top 10 countries. \n",
        "vacc_by_country = df.groupby('country').max().sort_values('total_vaccinations', ascending=False)\n",
        "vacc_by_country = vacc_by_country.iloc[:10]\n",
        "vacc_by_country\n"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "      <th>vaccines</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>country</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>China</th>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "      <td>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>India</th>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>United States</th>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>123.40</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brazil</th>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>JPN</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>147.54</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Indonesia</th>\n",
              "      <td>IDN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.834772e+08</td>\n",
              "      <td>1.143471e+08</td>\n",
              "      <td>1897011.0</td>\n",
              "      <td>66.39</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Turkey</th>\n",
              "      <td>TUR</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.156746e+08</td>\n",
              "      <td>5.525654e+07</td>\n",
              "      <td>1264431.0</td>\n",
              "      <td>136.02</td>\n",
              "      <td>Pfizer/BioNTech, Sinovac</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mexico</th>\n",
              "      <td>MEX</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.156246e+08</td>\n",
              "      <td>7.004907e+07</td>\n",
              "      <td>1088095.0</td>\n",
              "      <td>88.76</td>\n",
              "      <td>CanSino, Johnson&amp;Johnson, Moderna, Oxford/Astr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>DEU</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.109504e+08</td>\n",
              "      <td>5.751572e+07</td>\n",
              "      <td>874929.0</td>\n",
              "      <td>132.24</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pakistan</th>\n",
              "      <td>PAK</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.020679e+08</td>\n",
              "      <td>6.934111e+07</td>\n",
              "      <td>1280906.0</td>\n",
              "      <td>45.32</td>\n",
              "      <td>CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              iso_code  ...                                           vaccines\n",
              "country                 ...                                                   \n",
              "China              CHN  ...  CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...\n",
              "India              IND  ...             Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "United States      USA  ...          Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "Brazil             BRA  ...  Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bi...\n",
              "Japan              JPN  ...       Moderna, Oxford/AstraZeneca, Pfizer/BioNTech\n",
              "Indonesia          IDN  ...  Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...\n",
              "Turkey             TUR  ...                           Pfizer/BioNTech, Sinovac\n",
              "Mexico             MEX  ...  CanSino, Johnson&Johnson, Moderna, Oxford/Astr...\n",
              "Germany            DEU  ...  Johnson&Johnson, Moderna, Oxford/AstraZeneca, ...\n",
              "Pakistan           PAK  ...  CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m74Zdlm43VBz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "7c475fdb-e50f-401c-9017-dd6b0c7f6170"
      },
      "source": [
        "#Now sort by total vaccinations per 100\n",
        "vacc_by_country = vacc_by_country.sort_values('total_vaccinations_per_hundred', ascending=False)\n",
        "vacc_by_country"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "      <th>vaccines</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>country</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>China</th>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "      <td>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>JPN</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>147.54</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Turkey</th>\n",
              "      <td>TUR</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.156746e+08</td>\n",
              "      <td>5.525654e+07</td>\n",
              "      <td>1264431.0</td>\n",
              "      <td>136.02</td>\n",
              "      <td>Pfizer/BioNTech, Sinovac</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>DEU</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.109504e+08</td>\n",
              "      <td>5.751572e+07</td>\n",
              "      <td>874929.0</td>\n",
              "      <td>132.24</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brazil</th>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>United States</th>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>123.40</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mexico</th>\n",
              "      <td>MEX</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.156246e+08</td>\n",
              "      <td>7.004907e+07</td>\n",
              "      <td>1088095.0</td>\n",
              "      <td>88.76</td>\n",
              "      <td>CanSino, Johnson&amp;Johnson, Moderna, Oxford/Astr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>India</th>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Indonesia</th>\n",
              "      <td>IDN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.834772e+08</td>\n",
              "      <td>1.143471e+08</td>\n",
              "      <td>1897011.0</td>\n",
              "      <td>66.39</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pakistan</th>\n",
              "      <td>PAK</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.020679e+08</td>\n",
              "      <td>6.934111e+07</td>\n",
              "      <td>1280906.0</td>\n",
              "      <td>45.32</td>\n",
              "      <td>CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              iso_code  ...                                           vaccines\n",
              "country                 ...                                                   \n",
              "China              CHN  ...  CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...\n",
              "Japan              JPN  ...       Moderna, Oxford/AstraZeneca, Pfizer/BioNTech\n",
              "Turkey             TUR  ...                           Pfizer/BioNTech, Sinovac\n",
              "Germany            DEU  ...  Johnson&Johnson, Moderna, Oxford/AstraZeneca, ...\n",
              "Brazil             BRA  ...  Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bi...\n",
              "United States      USA  ...          Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "Mexico             MEX  ...  CanSino, Johnson&Johnson, Moderna, Oxford/Astr...\n",
              "India              IND  ...             Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "Indonesia          IDN  ...  Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...\n",
              "Pakistan           PAK  ...  CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qXupbNoCxHhO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "outputId": "60baa396-05ea-404f-9912-c7bc2723b722"
      },
      "source": [
        "plt.figure(figsize=(18, 6))\n",
        "plt.bar(vacc_by_country.index, vacc_by_country.total_vaccinations_per_hundred)\n",
        "\n",
        "plt.xticks(rotation = 90)\n",
        "plt.ylabel('Vaccinations per 100')\n",
        "plt.xlabel('Country')\n",
        "plt.show()"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wMiotxhhzmmV"
      },
      "source": [
        "Country with most vaccinated people. Obviously, this will be skewed towards highest populated countries that effectively depoyed vaccinations to bulk of its population. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FkVFje3r5CXK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "fc2a0405-e8e8-4fb3-d00b-5954a82d90e9"
      },
      "source": [
        "total_vacc_by_country = df.groupby('country').max().sort_values('total_vaccinations', ascending=False)\n",
        "total_vacc_by_country = total_vacc_by_country.iloc[:10]\n",
        "total_vacc_by_country\n"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "      <th>vaccines</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>country</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>China</th>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "      <td>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>India</th>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>United States</th>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>123.40</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brazil</th>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>JPN</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>147.54</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Indonesia</th>\n",
              "      <td>IDN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.834772e+08</td>\n",
              "      <td>1.143471e+08</td>\n",
              "      <td>1897011.0</td>\n",
              "      <td>66.39</td>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Turkey</th>\n",
              "      <td>TUR</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.156746e+08</td>\n",
              "      <td>5.525654e+07</td>\n",
              "      <td>1264431.0</td>\n",
              "      <td>136.02</td>\n",
              "      <td>Pfizer/BioNTech, Sinovac</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mexico</th>\n",
              "      <td>MEX</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.156246e+08</td>\n",
              "      <td>7.004907e+07</td>\n",
              "      <td>1088095.0</td>\n",
              "      <td>88.76</td>\n",
              "      <td>CanSino, Johnson&amp;Johnson, Moderna, Oxford/Astr...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Germany</th>\n",
              "      <td>DEU</td>\n",
              "      <td>2021-10-25</td>\n",
              "      <td>1.109504e+08</td>\n",
              "      <td>5.751572e+07</td>\n",
              "      <td>874929.0</td>\n",
              "      <td>132.24</td>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pakistan</th>\n",
              "      <td>PAK</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.020679e+08</td>\n",
              "      <td>6.934111e+07</td>\n",
              "      <td>1280906.0</td>\n",
              "      <td>45.32</td>\n",
              "      <td>CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              iso_code  ...                                           vaccines\n",
              "country                 ...                                                   \n",
              "China              CHN  ...  CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...\n",
              "India              IND  ...             Covaxin, Oxford/AstraZeneca, Sputnik V\n",
              "United States      USA  ...          Johnson&Johnson, Moderna, Pfizer/BioNTech\n",
              "Brazil             BRA  ...  Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bi...\n",
              "Japan              JPN  ...       Moderna, Oxford/AstraZeneca, Pfizer/BioNTech\n",
              "Indonesia          IDN  ...  Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...\n",
              "Turkey             TUR  ...                           Pfizer/BioNTech, Sinovac\n",
              "Mexico             MEX  ...  CanSino, Johnson&Johnson, Moderna, Oxford/Astr...\n",
              "Germany            DEU  ...  Johnson&Johnson, Moderna, Oxford/AstraZeneca, ...\n",
              "Pakistan           PAK  ...  CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wO4CZSfuzonF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "outputId": "4bcb3763-f68d-4fa8-c91c-0a980ea072b7"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(16, 7))\n",
        "plt.bar(total_vacc_by_country.index, total_vacc_by_country.total_vaccinations)\n",
        "\n",
        "plt.title('Total vaccinations per country')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.ylabel('Total vaccinations')\n",
        "plt.xlabel('Country')\n",
        "plt.show()"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ClkrLIU5zAO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "90780692-fcf4-42d5-9b8b-62810e7181bc"
      },
      "source": [
        "#Sort by total vaccinations delivered by countries and group by vaccines. \n",
        "vacc_names_by_country = df.groupby('vaccines').max().sort_values('total_vaccinations', ascending=False)\n",
        "vacc_names_by_country.head()\n"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>vaccines</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, Sinovac, ZF2001</th>\n",
              "      <td>China</td>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Covaxin, Oxford/AstraZeneca, Sputnik V</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</th>\n",
              "      <td>United States</td>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>151.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinovac</th>\n",
              "      <td>Brazil</td>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</th>\n",
              "      <td>Wales</td>\n",
              "      <td>SXM</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>165.14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                          country  ... total_vaccinations_per_hundred\n",
              "vaccines                                                           ...                               \n",
              "CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, Si...          China  ...                         155.89\n",
              "Covaxin, Oxford/AstraZeneca, Sputnik V                      India  ...                          73.98\n",
              "Johnson&Johnson, Moderna, Pfizer/BioNTech           United States  ...                         151.96\n",
              "Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bio...         Brazil  ...                         126.22\n",
              "Moderna, Oxford/AstraZeneca, Pfizer/BioNTech                Wales  ...                         165.14\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qltzBJnE6a4Y",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "ebb33cfa-a1e8-4710-85b6-53a71712ac1c"
      },
      "source": [
        "#Get the top 10 vaccines by country for easy plotting\n",
        "vacc_names_by_country = vacc_names_by_country.iloc[:10]\n",
        "vacc_names_by_country"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>vaccines</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, Sinovac, ZF2001</th>\n",
              "      <td>China</td>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Covaxin, Oxford/AstraZeneca, Sputnik V</th>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</th>\n",
              "      <td>United States</td>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>151.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/BioNTech, Sinovac</th>\n",
              "      <td>Brazil</td>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</th>\n",
              "      <td>Wales</td>\n",
              "      <td>SXM</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>165.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing, Sinovac</th>\n",
              "      <td>Indonesia</td>\n",
              "      <td>IDN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.834772e+08</td>\n",
              "      <td>1.143471e+08</td>\n",
              "      <td>1897011.0</td>\n",
              "      <td>66.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pfizer/BioNTech, Sinovac</th>\n",
              "      <td>Turkey</td>\n",
              "      <td>TUR</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.156746e+08</td>\n",
              "      <td>5.525654e+07</td>\n",
              "      <td>1264431.0</td>\n",
              "      <td>136.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CanSino, Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, Sinovac, Sputnik V</th>\n",
              "      <td>Mexico</td>\n",
              "      <td>MEX</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.156246e+08</td>\n",
              "      <td>7.004907e+07</td>\n",
              "      <td>1088095.0</td>\n",
              "      <td>88.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</th>\n",
              "      <td>Spain</td>\n",
              "      <td>ROU</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.109504e+08</td>\n",
              "      <td>5.751572e+07</td>\n",
              "      <td>874929.0</td>\n",
              "      <td>169.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CanSino, Covaxin, Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing, Sinovac, Sputnik V</th>\n",
              "      <td>Pakistan</td>\n",
              "      <td>PAK</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.020679e+08</td>\n",
              "      <td>6.934111e+07</td>\n",
              "      <td>1280906.0</td>\n",
              "      <td>45.32</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                          country  ... total_vaccinations_per_hundred\n",
              "vaccines                                                           ...                               \n",
              "CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, Si...          China  ...                         155.89\n",
              "Covaxin, Oxford/AstraZeneca, Sputnik V                      India  ...                          73.98\n",
              "Johnson&Johnson, Moderna, Pfizer/BioNTech           United States  ...                         151.96\n",
              "Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bio...         Brazil  ...                         126.22\n",
              "Moderna, Oxford/AstraZeneca, Pfizer/BioNTech                Wales  ...                         165.14\n",
              "Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, S...      Indonesia  ...                          66.39\n",
              "Pfizer/BioNTech, Sinovac                                   Turkey  ...                         136.02\n",
              "CanSino, Johnson&Johnson, Moderna, Oxford/Astra...         Mexico  ...                          88.76\n",
              "Johnson&Johnson, Moderna, Oxford/AstraZeneca, P...          Spain  ...                         169.02\n",
              "CanSino, Covaxin, Moderna, Oxford/AstraZeneca, ...       Pakistan  ...                          45.32\n",
              "\n",
              "[10 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4FN9-Rcp8HD0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "outputId": "a0c2c59d-3272-404f-a3e6-d48fcccd763d"
      },
      "source": [
        "#Reset index to move vaccines from being index to a column. \n",
        "#This makes it easy for us to plot using Seaborn, especially if we want to sort by country. \n",
        "vacc_names_by_country=vacc_names_by_country.reset_index()\n",
        "vacc_names_by_country"
      ],
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>vaccines</th>\n",
              "      <th>country</th>\n",
              "      <th>iso_code</th>\n",
              "      <th>date</th>\n",
              "      <th>total_vaccinations</th>\n",
              "      <th>people_vaccinated</th>\n",
              "      <th>daily_vaccinations</th>\n",
              "      <th>total_vaccinations_per_hundred</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...</td>\n",
              "      <td>China</td>\n",
              "      <td>CHN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.251339e+09</td>\n",
              "      <td>1.100842e+09</td>\n",
              "      <td>22424286.0</td>\n",
              "      <td>155.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Covaxin, Oxford/AstraZeneca, Sputnik V</td>\n",
              "      <td>India</td>\n",
              "      <td>IND</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.030850e+09</td>\n",
              "      <td>7.211491e+08</td>\n",
              "      <td>10037995.0</td>\n",
              "      <td>73.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Pfizer/BioNTech</td>\n",
              "      <td>United States</td>\n",
              "      <td>USA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>4.150120e+08</td>\n",
              "      <td>2.206488e+08</td>\n",
              "      <td>3384387.0</td>\n",
              "      <td>151.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Johnson&amp;Johnson, Oxford/AstraZeneca, Pfizer/Bi...</td>\n",
              "      <td>Brazil</td>\n",
              "      <td>BRA</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>2.701074e+08</td>\n",
              "      <td>1.587227e+08</td>\n",
              "      <td>2045834.0</td>\n",
              "      <td>126.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech</td>\n",
              "      <td>Wales</td>\n",
              "      <td>SXM</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.859792e+08</td>\n",
              "      <td>9.718129e+07</td>\n",
              "      <td>1997542.0</td>\n",
              "      <td>165.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...</td>\n",
              "      <td>Indonesia</td>\n",
              "      <td>IDN</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.834772e+08</td>\n",
              "      <td>1.143471e+08</td>\n",
              "      <td>1897011.0</td>\n",
              "      <td>66.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Pfizer/BioNTech, Sinovac</td>\n",
              "      <td>Turkey</td>\n",
              "      <td>TUR</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.156746e+08</td>\n",
              "      <td>5.525654e+07</td>\n",
              "      <td>1264431.0</td>\n",
              "      <td>136.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>CanSino, Johnson&amp;Johnson, Moderna, Oxford/Astr...</td>\n",
              "      <td>Mexico</td>\n",
              "      <td>MEX</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>1.156246e+08</td>\n",
              "      <td>7.004907e+07</td>\n",
              "      <td>1088095.0</td>\n",
              "      <td>88.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Johnson&amp;Johnson, Moderna, Oxford/AstraZeneca, ...</td>\n",
              "      <td>Spain</td>\n",
              "      <td>ROU</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.109504e+08</td>\n",
              "      <td>5.751572e+07</td>\n",
              "      <td>874929.0</td>\n",
              "      <td>169.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...</td>\n",
              "      <td>Pakistan</td>\n",
              "      <td>PAK</td>\n",
              "      <td>2021-10-26</td>\n",
              "      <td>1.020679e+08</td>\n",
              "      <td>6.934111e+07</td>\n",
              "      <td>1280906.0</td>\n",
              "      <td>45.32</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                            vaccines  ... total_vaccinations_per_hundred\n",
              "0  CanSino, Sinopharm/Beijing, Sinopharm/Wuhan, S...  ...                         155.89\n",
              "1             Covaxin, Oxford/AstraZeneca, Sputnik V  ...                          73.98\n",
              "2          Johnson&Johnson, Moderna, Pfizer/BioNTech  ...                         151.96\n",
              "3  Johnson&Johnson, Oxford/AstraZeneca, Pfizer/Bi...  ...                         126.22\n",
              "4       Moderna, Oxford/AstraZeneca, Pfizer/BioNTech  ...                         165.14\n",
              "5  Moderna, Oxford/AstraZeneca, Pfizer/BioNTech, ...  ...                          66.39\n",
              "6                           Pfizer/BioNTech, Sinovac  ...                         136.02\n",
              "7  CanSino, Johnson&Johnson, Moderna, Oxford/Astr...  ...                          88.76\n",
              "8  Johnson&Johnson, Moderna, Oxford/AstraZeneca, ...  ...                         169.02\n",
              "9  CanSino, Covaxin, Moderna, Oxford/AstraZeneca,...  ...                          45.32\n",
              "\n",
              "[10 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ofxjusd7z3Ol",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "8ccdc3aa-d1b6-487a-a82d-15c33aa94c11"
      },
      "source": [
        "plt.figure(figsize=(12,8))\n",
        "\n",
        "sns.barplot(data = vacc_names_by_country, x='vaccines', y = 'total_vaccinations', hue = 'country', dodge=False)\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),\n",
              " <a list of 10 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 66
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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RRRfRpEkTZs6cydChQ2nXrh377rsvnTp1qjrGlu0mTpzIiBEjWL58OWvXruXSSy/lkEMO4eyzz2b58uXEGBkxYgR77LHHD7qOobo7JbNdUVFRLC4urnZb4cgJtVxN+pXccG6mS5AkSTWgtLSU1q1bZ7oMfYfqvp8QQkmMsWjLtmkdzhFCOCCEMC2E8GYIYWEI4VfVtAkhhLEhhHdCCPNCCIelsyZJkiTph0r3cI61wG9ijG+EEJoBJSGE52KMb27S5mfAwZWvLsD/VP4pSZIkZaW09kTHGBfHGN+ofL8CKAX236LZqcCEWOE1YI8Qwn7prEuSJEn6IWrt6RwhhJZAR+BfW2zaH/hwk+VFbB20JUmSpKxRKyE6hNAUeAS4NMb41fc8xoUhhOIQQvGGOdUlSZKkTEh7iA4hNKQiQN8fY3y0miYfAQdsstyict1mYozjY4xFMcaiffbZJz3FSpIkSSlI99M5AnAXUBpj/PN3NJsEnFv5lI7DgeUxxsXprEuSJKm+ysnJoaCggA4dOnDYYYcxY8aMGjnukCFDqqb/btmyJUuXLq2R42ardD+doxtwDjA/hDCnct3/A/wEIMY4DngKOAl4B/gGGJzmmiRJkrLCi0ceVaPHO+qlF7fbpkmTJlWzCj777LNcccUVvPji5vutXbs28ZTYd955Z6L2dV26n87xSowxxBjzY4wFla+nYozjKgM0lU/luCTGeFCMsX2MsfpZVCRJklSjvvrqK/bcc08Apk+fTo8ePejTpw9t2rQBoG/fvhQWFtK2bVvGjx8PwKRJkygoKKCgoIBDDz2UvLw8AHr27Ml3TYa3I3Lab0mSpHpk1apVFBQUUF5ezuLFi3nhhReqtr3xxhssWLCgKhjffffd7LXXXqxatYpOnTpx+umn06dPH/r06QPAL37xC446qmZ70+sKQ7QkSVI9sulwjpkzZ3LuueeyYMECADp37lwVoAHGjh3LY489BsCHH37Iv//9b/bee28AxowZQ5MmTbjkkktq+QyygyFakiSpnjriiCNYunQpGx4fvOuuu1Ztmz59OlOnTmXmzJnssssu9OzZk/LycgCmTp3Kww8/zEsvvZSRurOBIVqSJKmeeuutt1i3bl1V7/Kmli9fzp577skuu+zCW2+9xWuvvQbA+++/zyWXXMKzzz5LkyZNarvkrGGIliRJqkc2jIkGiDFy3333kZOTs1W7E088kXHjxtG6dWsOPfRQDj/8cADuvfdeli1bRt++fQFo3rw5Tz31VO2dQJYIMcZM15BYUVFR/K67PwtHTqjlatKv5IZzM12CJEmqAaWlpbRu3TrTZeg7VPf9hBBKYoxFW7atlWm/JUmSpB2JIVqSJElKyBAtSZIkJWSIliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJ9cRll13GLbfcUrV8wgknMGTIkKrl3/zmN/z5z3+udt9BgwYxceLEtNdYVzjZiiRJUobc9pvJNXq8YTedss3t3bp14x//+AeXXnop69evZ+nSpXz11VdV22fMmMHNN99cozXtqOyJliRJqie6du3KzJkzAVi4cCHt2rWjWbNmfPHFF3z77beUlpbyz3/+k06dOtGuXTsuvPBCqpuYr6SkhKOOOorCwkJOOOEEFi9eDMDYsWNp06YN+fn5DBgwoFbPrbYZoiVJkuqJ5s2b06BBAz744ANmzJjBEUccQZcuXZg5cybFxcW0b9+eYcOGMWvWLBYsWMCqVauYMmXKZsdYs2YNw4cPZ+LEiZSUlHD++edz5ZVXAnD99dcze/Zs5s2bx7hx4zJxirXG4RySJEn1SNeuXZkxYwYzZszg17/+NR999BEzZsxg9913p1u3bkybNo0xY8bwzTff8Pnnn9O2bVtOOWXjMJG3336bBQsWcNxxxwGwbt069ttvPwDy8/MZOHAgffv2pW/fvhk5v9piiJYkSapHunXrxowZM5g/fz7t2rXjgAMO4KabbmK33XZj8ODBDB06lOLiYg444ABGjRpFeXn5ZvvHGGnbtm3VsJBNPfnkk7z00ktMnjyZ0aNHM3/+fBo02DHjpsM5JEmS6pGuXbsyZcoU9tprL3Jycthrr7348ssvmTlzJl27dgUgNzeXlStXVvs0jkMPPZQlS5ZUheg1a9awcOFC1q9fz4cffsjRRx/Nn/70J5YvX87KlStr9dxq0475vwaSJEmqVvv27Vm6dClnnXXWZutWrlxJbm4uQ4cOpV27duy777506tRpq/133nlnJk6cyIgRI1i+fDlr167l0ksv5ZBDDuHss89m+fLlxBgZMWIEe+yxR22eWq0K1d1xme2KiopicXFxtdsKR06o5WrSr+SGczNdgiRJqgGlpaW0bt0602XoO1T3/YQQSmKMRVu2dTiHJEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJEn1SNOmTRO1nz59Or17905TNZu76qqrmDp1aq181g/lZCuSJEkZMvrsfjV6vCv/tvUMg3XJtddem+kSUmZPtCRJUj00ffp0evbsSb9+/WjVqhUDBw5kwyR8zzzzDK1ateKwww7j0Ucfrdrn888/p2/fvuTn53P44Yczb948AEaNGsX5559Pz549OfDAAxk7dmzVPn/729/o3LkzBQUF/PKXv2TdunWsW7eOQYMG0a5dO9q3b8/NN98MwKBBg6qmGr/22mvp1KkT7dq148ILLyTbJgg0REuSJNVTs2fP5pZbbuHNN9/kvffe49VXX6W8vJyhQ4cyefJkSkpK+OSTT6raX3311XTs2JF58+bx3//935x77sZZld966y2effZZXn/9da655hrWrFlDaWkpDz30EK+++ipz5swhJyeH+++/nzlz5vDRRx+xYMEC5s+fz+DBg7eqbdiwYcyaNYsFCxawatUqpkyZUivXJFWGaEmSpHqqc+fOtGjRgp122omCggLKysp46623yMvL4+CDDyaEwNlnn13V/pVXXuGcc84BoFevXixbtoyvvvoKgJNPPplGjRqRm5vLj370Iz799FOef/55SkpK6NSpEwUFBTz//PO89957HHjggbz33nsMHz6cZ555ht12222r2qZNm0aXLl1o3749L7zwAgsXLqydi5Iix0RLkiTVU40aNap6n5OTw9q1a2v0WDFGzjvvPP74xz9u1X7u3Lk8++yzjBs3jn/84x/cfffdVdvKy8u5+OKLKS4u5oADDmDUqFGUl5d/79rSwZ5oSZIkVWnVqhVlZWW8++67ADzwwANV23r06MH9998PVIypzs3NrbYXeYNjjjmGiRMn8tlnnwEVY6rff/99li5dyvr16zn99NO57rrreOONNzbbb0Ngzs3NZeXKlVXjpLOJPdGSJEmq0rhxY8aPH8/JJ5/MLrvsQo8ePVixYgWw8QbC/Px8dtllF+67775tHqtNmzZcd911HH/88axfv56GDRvyl7/8hSZNmjB48GDWr18PsFVP9R577MHQoUNp164d++67L506dUrPyf4AIdvudExFUVFRLC4urnZb4cgJtVxN+pXccO72G0mSpKxXWlpK69atM12GvkN1308IoSTGWLRlW4dzSJIkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKyBAtSZJUTyxbtoyCggIKCgrYd9992X///auWV69evc19y8rKaNeuXS1Vmv2cbEWSJClDSke/UKPHa31lr21u33vvvZkzZw5QMXFK06ZNufzyy7d73B8yHfiOyp5oSZKkemzQoEGbTavdtGlToGJa7x49etCnTx/atGmz2T7vvfceHTt2ZNasWbz77ruceOKJFBYW0qNHD9566y1WrFhBXl4ea9asAeCrr77abHlHYE+0JEmSqvXGG2+wYMEC8vLyKCsrA+Dtt99mwIAB3HvvvXTo0IFjjjmGcePGcfDBB/Ovf/2Liy++mBdeeIGePXvy5JNP0rdvXx588EF+/vOf07Bhw8yeUA0yREuSJKlanTt3Ji8vr2p5yZIlnHrqqTz66KO0adOGlStXMmPGDPr371/V5ttvvwVgyJAhjBkzhr59+3LPPfdwxx131Hr96WSIliRJqscaNGjA+vXrAVi/fv1mNxjuuuuum7Xdfffd+clPfsIrr7xCmzZtWL9+PXvssUfVOOtNdevWjbKyMqZPn866det2uJsSHRMtSZJUj7Vs2ZKSkhIAJk2atM1xyzvvvDOPPfYYEyZM4O9//zu77bYbeXl5PPzwwwDEGJk7d25V+3PPPZezzjqLwYMHp/ckMsAQLUmSVI8NHTqUF198kQ4dOjBz5sytep+3tOuuuzJlyhRuvvlmJk2axP33389dd91Fhw4daNu2LU888URV24EDB/LFF19w5plnpvs0al2IMWa6hsSKiopicXFxtdsKR06o5WrSr+SGczNdgiRJqgGlpaW0bt0602XUmokTJ/LEE0/w17/+NdOlpKS67yeEUBJjLNqyrWOiJUmSVOOGDx/O008/zVNPPZXpUtLCEC1JkqQad+utt2a6hLRyTLQkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiTVIyEEzj777KrltWvXss8++9C7d+/vdbxx48YxYcKO94jh7fHpHJIkSRkyatSoWj/errvuyoIFC1i1ahVNmjThueeeY//99//en3nRRRd9733rMnuiJUmS6pmTTjqJJ598EoAHHnhgsxkFv/76a84//3w6d+5Mx44dq2Yg/NWvfsW1114LwLPPPsuRRx7J+vXrGTVqFDfeeCMA77zzDsceeywdOnTgsMMO49133yXGyMiRI2nXrh3t27fnoYcequWzTQ9DtCRJUj0zYMAAHnzwQcrLy5k3bx5dunSp2jZ69Gh69erF66+/zrRp0xg5ciRff/01f/zjH3nooYeYNm0aI0aM4J577mGnnTaPkgMHDuSSSy5h7ty5zJgxg/32249HH32UOXPmMHfuXKZOncrIkSNZvHhxbZ9yjTNES5Ik1TP5+fmUlZXxwAMPcNJJJ2227Z///CfXX389BQUF9OzZk/Lycj744AN22WUX7rjjDo477jiGDRvGQQcdtNl+K1as4KOPPuK0004DoHHjxuyyyy688sornHnmmeTk5PDjH/+Yo446ilmzZtXauaaLY6IlSZLqoT59+nD55Zczffp0li1bVrU+xsgjjzzCoYceutU+8+fPZ++99+bjjz+uzVKzkj3RkiRJ9dD555/P1VdfTfv27Tdbf8IJJ3DrrbcSYwRg9uzZALz//vvcdNNNzJ49m6effpp//etfm+3XrFkzWrRoweOPPw7At99+yzfffEOPHj146KGHWLduHUuWLOGll16ic+fOtXCG6WWIliRJqodatGjBiBEjtlr/hz/8gTVr1pCfn0/btm35wx/+QIyRCy64gBtvvJHmzZtz1113MWTIEMrLyzfb969//Stjx44lPz+frl278sknn3DaaaeRn59Phw4d6NWrF2PGjGHfffetrdNMm7Dh/zLqkqKiolhcXFzttsKRO95zCktuODfTJUiSpBpQWlpK69atM12GvkN1308IoSTGWLRlW3uiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmqZ0aPHk3btm3Jz8+noKBgq4lTUjFp0iSuv/76NFRXNzjttyRJUob84+GanbnvF/1f326bmTNnMmXKFN544w0aNWrE0qVLWb16deLP6tOnD3369Pk+Ze4Q7ImWJEmqRxYvXkxubi6NGjUCIDc3l+bNm9OyZUv+z//5P7Rv357OnTvzzjvvADB58mS6dOlCx44dOfbYY/n0008BuPfeexk2bBgAgwYNYsSIEXTt2pUDDzyQiRMnZubkapEhWpIkqR45/vjj+fDDDznkkEO4+OKLefHFF6u27b777syfP59hw4Zx6aWXAtC9e3dee+01Zs+ezYABAxgzZky1x128eDGvvPIKU6ZM4Xe/+12tnEsmOZxDkiSpHmnatCklJSW8/PLLTJs2jTPOOKNqbPOZZ55Z9edll10GwKJFizjjjDNYvHgxq1evJi8vr9rj9u3bl5122ok2bdpU9VbvyOyJliRJqmdycnLo2dgTX3oAACAASURBVLMn11xzDbfddhuPPPIIACGEqjYb3g8fPpxhw4Yxf/58br/9dsrLy6s95obhIQAxxjRWnx0M0ZIkSfXI22+/zb///e+q5Tlz5vDTn/4UgIceeqjqzyOOOAKA5cuXs//++wNw33331XK12cvhHJIkSfXIypUrGT58OF9++SUNGjTgP/7jPxg/fjxTpkzhiy++ID8/n0aNGvHAAw8AMGrUKPr378+ee+5Jr169+N///d8Mn0F2CHWxu72oqCgWFxdXu61w5IRarib9Sm44N9MlSJKkGlBaWkrr1q0zXUa1WrZsSXFxMbm5uZkuJWOq+35CCCUxxqIt2zqcQ5IkSUrI4RySJEmirKws0yXUKWntiQ4h3B1C+CyEsOA7tvcMISwPIcypfF2VznokSZKkmpDunuh7gduAbQ1UfjnG2DvNdUiSJEk1Jq090THGl4DP0/kZkiRJUm3LhhsLjwghzA0hPB1CaJvpYiRJkqTtyXSIfgP4aYyxA3Ar8Ph3NQwhXBhCKA4hFC9ZsqTWCpQkSdqR5OTkUFBQQLt27ejfvz/ffPPNd7YdNWoUN95441brr7rqKqZOnfqd+z3++OO8+eabNVJvtsro0zlijF9t8v6pEML/DSHkxhiXVtN2PDAeKp4TXYtlSpIkpUWHic/W6PHm9jthu22aNGnCnDlzABg4cCDjxo3j17/+daLPufbaa7e5/fHHH6d37960adMm0XHrkoz2RIcQ9g2VE7OHEDpX1rMskzVJkiTVFz169OCdd95h8uTJdOnShY4dO3Lsscfy6aefbtX2jjvu4Gc/+xmrVq1i0KBBTJw4EYDf/e53tGnThvz8fC6//HJmzJjBpEmTGDlyJAUFBbz77rvccccddOrUiQ4dOnD66adX9X4PGjSIESNG0LVrVw488MCqY9YFae2JDiE8APQEckMIi4CrgYYAMcZxQD/gP0MIa4FVwIBYF6dQlCRJqmPWrl3L008/zYknnkj37t157bXXCCFw5513MmbMGG666aaqtrfddhvPPfccjz/+OI0aNapav2zZMh577DHeeustQgh8+eWX7LHHHvTp04fevXvTr18/APbYYw+GDh0KwO9//3vuuusuhg8fDsDixYt55ZVXeOutt+jTp0/VPtkurSE6xnjmdrbfRsUj8CRJklQLVq1aRUFBAVDRE33BBRfw9ttvc8YZZ7B48WJWr15NXl5eVfsJEyZwwAEH8Pjjj9OwYcPNjrX77rvTuHFjLrjgAnr37k3v3tU/tXjBggX8/ve/58svv2TlypWccMLGYSd9+/Zlp512ok2bNtX2gGerTN9YKEmSpFq0YUz0nDlzuPXWW9l5550ZPnw4w4YNY/78+dx+++2Ul5dXtW/fvj1lZWUsWrRoq2M1aNCA119/nX79+jFlyhROPPHEaj9z0KBB3HbbbcyfP5+rr756s+Nv2rNdlwYkGKIlSZLqueXLl7P//vsDcN999222rWPHjtx+++306dOHjz/+eLNtK1euZPny5Zx00kncfPPNzJ07F4BmzZqxYsWKqnYrVqxgv/32Y82aNdx///1pPpvaYYiWJEmq50aNGkX//v0pLCwkNzd3q+3du3fnxhtv5OSTT2bp0o0PUVuxYgW9e/cmPz+f7t278+c//xmAAQMGcMMNN9CxY0feffdd/uu//osuXbrQrVs3WrVqVWvnlU6hLnWbb1BUVBSLi4ur3VY4clszjNdNJTecm+kSJElSDSgtLaV169aZLkPfobrvJ4RQEmMs2rKtPdGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJKkW1cX70eqDpN+LIVqSJKmWNG7cmGXLlhmks0yMkWXLltG4ceOU90nrjIWSJEnaqEWLFixatIglS5ZkuhRtoXHjxrRo0SLl9oZoSZKkWtKwYcPNptRW3ZXScI4QwpgQwm4hhIYhhOdDCEtCCGenuzhJkiQpG6U6Jvr4GONXQG+gDPgPYGS6ipIkSZKyWaohesOwj5OBh2OMy9NUjyRJkpT1Uh0TPSWE8BawCvjPEMI+QHn6ypIkSZKyV0o90THG3wFdgaIY4xrga+DUdBYmSZIkZaskT+doBbQMIWy6z4QarkeSJEnKeimF6BDCX4GDgDnAusrVEUO0JEmS6qFUe6KLgDbR6XUkSZKklJ/OsQDYN52FSJIkSXVFqj3RucCbIYTXgW83rIwx9klLVZIkSVIWSzVEj0pnEZIkSVJdklKIjjG+GEL4MdCpctXrMcbP0leWJEmSlL1SGhMdQvgF8DrQH/gF8K8QQr90FiZJkiRlq1SHc1wJdNrQ+1w5Y+FUYGK6CpMkSZKyVapP59hpi+EbyxLsK0mSJO1QUu2JfiaE8CzwQOXyGcBT6SlJkiRJym6p3lg4MoRwOtCtctX4GONj6StLkiRJyl6p9kQTY3wEeCSNtUiSJEl1wjZDdAjhlRhj9xDCCmDTKb8DEGOMu6W1OkmSJCkLbTNExxi7V/7ZrHbKkSRJkrJfqs+J/msq6yRJkqT6INXH1LXddCGE0AAorPlyJEmSpOy3zRAdQriicjx0fgjhq8rXCuBT4IlaqVCSJEnKMtsM0THGP1aOh74hxrhb5atZjHHvGOMVtVSjJEmSlFVSfU70FSGEPYGDgcabrH8pXYVJkiRJ2SqlEB1CGAL8CmgBzAEOB2YCvdJXmiRJkpSdUr2x8FdAJ+D9GOPRQEfgy7RVJUmSJGWxVEN0eYyxHCCE0CjG+BZwaPrKkiRJkrJXqtN+Lwoh7AE8DjwXQvgCeD99ZUmSJEnZK9UbC0+rfDsqhDAN2B14Jm1VSZIkSVks1Z5oQgg5wI+B/61ctS/wQTqKkiRJkrJZqk/nGA5cTcUkK+srV0cgP011SZIkSVkr1Z7oXwGHxhiXpbMYSZIkqS5I9ekcHwLL01mIJEmSVFek2hP9HjA9hPAk8O2GlTHGP6elKkmSJCmLpRqiP6h87Vz5kiRJkuqtVB9xd026C5EkSZLqim2G6BDCLTHGS0MIk6l4GsdmYox90laZJEmSlKW21xP918o/b0x3IZIkSVJdsc0QHWMsqXxbDKyKMa6HqolXGqW5NkmSJCkrpfqIu+eBXTZZbgJMrflyJEmSpOyXaohuHGNcuWGh8v0u22gvSZIk7bBSDdFfhxAO27AQQigEVqWnJEmSJCm7pfqc6EuBh0MIHwMB2Bc4I21VSZIkSVks1edEzwohtAIOrVz1doxxTfrKkiRJkrJXSsM5QgiXALvGGBfEGBcATUMIF6e3NEmSJCk7pTomemiM8csNCzHGL4Ch6SlJkiRJym6phuicEELYsFD5nOid01OSJEmSlN1SvbHwGeChEMLtlcu/rFwnSZIk1TuphujfUhGc/7Ny+TngzrRUJEmSJGW5VJ/OsR74n8qXJEmSVK+lFKJDCAcDfwTaAI03rI8xHpimuiRJkqSsleqNhfdQ0Qu9FjgamAD8LV1FSZIkSdks1RDdJMb4PBBijO/HGEcBJ6evLEmSJCl7pXpj4bchhJ2Af4cQhgEfAU3TV5YkSZKUvVLtif4VsAswAigEzgbOS1dRkiRJUjZLtSd6XYxxJbASGJzGeiRJkqSsl2pP9E0hhNIQwn+FENqltSJJkiQpy6UUomOMR1PxVI4lwO0hhPkhhN+ntTJJkiQpS6XaE02M8ZMY41jgImAOcFXaqpIkSZKyWEohOoTQOoQwKoQwH7gVmAG0SGtlkiRJUpZK9cbCu4EHgRNijB+nsR5JkiQp66UUomOMR2xrewjhkRjj6TVTkiRJkpTdUh4TvR0H1tBxJEmSpKxXUyE61tBxJEmSpKxXUyFakiRJqjdqKkSHGjqOJEmSlPVqKkT/toaOI0mSJGW9bT6do/K50NWNdw5AjDHmU/Hmn2moTZIkScpK23vEXe9aqUKSJEmqQ7YZomOM79dWIap5H1zbPtMl1LifXDU/0yVIkiSlPO334SGEWSGElSGE1SGEdSGEr9JdnCRJkpSNUr2x8DbgTODfQBNgCPCX7e0UQrg7hPBZCGHBd2wPIYSxIYR3QgjzQgiHpVq4JEmSlCkpP50jxvgOkBNjXBdjvAc4MYXd7t1Ou58BB1e+LgT+J9V6JEmSpEzZ3o2FG3wTQtgZmBNCGAMsJoUAHmN8KYTQchtNTgUmxBgj8FoIYY8Qwn4xxsUp1iVJkiTVulR7os+pbDsM+Bo4APh5DXz+/sCHmywvqlwnSZIkZa1UQ3TfGGN5jPGrGOM1McZfU8uPvwshXBhCKA4hFC9ZsqQ2P1qSJEnaTKoh+rxq1g2qgc//iIpe7Q1aVK7bSoxxfIyxKMZYtM8++9TAR0uSJEnfz/ZmLDwTOAvICyFM2mTTbsDnNfD5k4BhIYQHgS7AcsdDS5IkKdtt78bCGVTcRJgL3LTJ+hXAvO0dPITwANATyA0hLAKuBhoCxBjHAU8BJwHvAN8Ag5OVL0mSJNW+VGYsfB84IoTwY6BT5abSGOPa7R08xnjmdrZH4JIUa5UkSZKyQqozFvYHXgf6A78A/hVC6JfOwiRJkqRslepzon8PdIoxfgYQQtgHmApMTFdhkiRJUrZK9ekcO20I0JWWJdhXkiRJ2qGk2hP9dAjhWeCByuUzqLgpUJIkSap3Uu1NjsDtQH7la3zaKpIkSZKyXKo90cfFGH8LPLphRQjhGuC3aalKkiRJymLbm2zlP4GLgQNDCJs+F7oZ8Go6C5MkSZKy1fZ6ov8OPA38EfjdJutXxBhrYsZCSZIkqc7Z3mQry4HlwDYnTZEkSZLqEx9TJ0mSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKyBAtSZIkJWSIliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKyBAtSZIkJWSIliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKyBAtSZIkJWSIliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISSnuIDiGcGEJ4O4TwTgjhd9VsHxRCWBJCmFP5GpLumiRJkqQfokE6Dx5CyAH+AhwHLAJmhRAmxRjf3KLpQzHGYemsRZIkSaop6e6J7gy8E2N8L8a4GngQODXNnylJkiSlVbpD9P7Ah5ssL6pct6XTQwjzQggTQwgHpLkmSZIk6QfJhhsLJwMtY4z5wHPAfdU1CiFcGEIoDiEUL1mypFYLlCRJkjaV7hD9EbBpz3KLynVVYozLYozfVi7eCRRWd6AY4/gYY1GMsWifffZJS7GSJElSKtIdomcBB4cQ8kIIOwMDgEmbNggh7LfJYh+gNM01SZIkST9IWp/OEWNcG0IYBjwL5AB3xxgXhhCuBYpjjJOAESGEPsBa4HNgUDprkiRJkn6otIZogBjjU8BTW6y7apP3VwBXpLsOSZIkqaZkw42FkiRJUp1iiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQk1yHQBUm3odmu3TJdQ414d/mqmS5Akqd6yJ1qSJElKyBAtSZIkJWSIliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKqEGmC5BUu1488qhMl1DjjnrpxUyXIEmqZ+yJliRJkhIyREuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUqoQaYLkKRMue03kzNdQo0bdtMp32u/0Wf3q+FKMu/Kv03MdAmSdmD2REuSJEkJGaIlSZKkhAzRkiRJUkKGaEmSJCkhQ7QkSZKUkCFakiRJSsgQLUmSJCVkiJYkSZISMkRLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpoQaZLkCSpGxSOvqFTJdQ41pf2et77Tdq1KiaLSQL7IjnpMwwREuSJG3DPx7unOkS0uIX/V/PdAl1miFakiRJKekw8dlMl5AWc/udkHgfx0RLkiRJCRmiJUmSpIQM0ZIkSVJChmhJkiQpIUO0JEmSlJAhWpIkSUrIEC1JkiQlZIiWJEmSEjJES5IkSQkZoiVJkqSEDNGSJElSQoZoSZIkKSFDtCRJkpSQIVqSJElKKO0hOoRwYgjh7RDCOyGE31WzvVEI4aHK7f8KIbRMd02SJEnSD5HWEB1CyAH+AvwMaAOcGUJos0WzC4AvYoz/AdwM/CmdNUmSJEk/VLp7ojsD78QY34sxrgYeBE7dos2pwH2V7ycCx4QQQprrkiRJkr63dIfo/YEPN1leVLmu2jYxxrXAcmDvNNclSZIkfW8hxpi+g4fQDzgxxjikcvkcoEuMcdgmbRZUtllUufxuZZulWxzrQuDCysVDgbfTVnjqcoGl221VP3gtNvJaVPA6bOS12MhrsZHXYiOvxUZei42y5Vr8NMa4z5YrG6T5Qz8CDthkuUXluuraLAohNAB2B5ZteaAY43hgfJrq/F5CCMUxxqJM15ENvBYbeS0qeB028lps5LXYyGuxkddiI6/FRtl+LdI9nGMWcHAIIS+EsDMwAJi0RZtJwHmV7/sBL8R0do9LkiRJP1Bae6JjjGtDCMOAZ4Ec4O4Y48IQwrVAcYxxEnAX8NcQwjvA51QEbUmSJClrpXs4BzHGp4Cntlh31Sbvy4H+6a4jTbJqeEmGeS028lpU8Dps5LXYyGuxkddiI6/FRl6LjbL6WqT1xkJJkiRpR+S035IkSVJChmhJklQrQggNM12DVFMM0T9QCGFwpmuoTSGE/iGExpmuI5uEELqGEM4KIZy74ZXpmjIhhHBJCGGPTZb3DCFcnMmaMsnfRYUQwn9X87u4LpM1ZUoI4fAQQrNNlncLIXTJZE0Z8FEI4c4QgrMTq0oIYWQIoUWm60jKMdE/UAjhgxjjTzJdR20JITwGdKPiiSsPAM/GGNdltqrMCSH8FTgImANsuA4xxjgic1VlRghhToyxYIt1s2OMHTNVU6b4u9iout9ACOGNGONhmaopU0IIs4HDNjzGNYSwExVPqqo31yKEsDcVj7MdABwMPAI8EGN8LaOFZVAI4efAn4AfAaHyFWOMu2W0sFoUQriZit9FGRXZ4uEY45KMFpUCQ3QKQgjzvmsTcEiMsVFt1pNpIYTdgNOo+EuwAHiCir8EX8xoYRkQQigF2vhscwghzAfyNwkIOcC8GGPbzFZW+/xdbFT592enGOO3lctNqAiO9fF3Ud3/aM6LMeZnqqZMCiE0p+LpXAOoCJAPxhivzGxVta/yEb+nxBhLM11LJlX+y8SRVPwe+gJzqQjUj8YYV2Sytu9iiE5BCOFT4ATgiy03ATNijM1rv6rssEmvwsXAXjHGA7azyw4lhPAwMCLGuDjTtWRaCOEG4KfA7ZWrfgl8GGP8Teaqygx/FxuFEH4LnALcU7lqMDApxjgmc1VlRgjhUWA68D+Vqy4Gjo4x9s1YURkWQmgK/Bz4NbBfjPHHGS6p1oUQXo0xdst0HdmkshPmWOB64NAY4y4ZLqlahugUhBDuAu6JMb5Szba/xxjPykBZGRdC2JOKAH0mFf8sNzHGeFlmq6odIYTJQASaUdEb/zrw7YbtMcY+GSotYyr/afqXwDGVq54D7qxPw338XVQvhPAzNvldxBifzWQ9mRJC+BEwFuhFxe/keeDSGONnGS2sllXeV3MKFf/t6Ao8AzxIxW+jPv198fPKt0cB+wKPs/nfF49moq5MCyG0p6I3+gxgKRX/0v3/Zraq6hmilUhlr8FpVPzl15GKadsfBKbXp3+6DiEcta3t9XFoi/xdSNsTQvg7FT2ML1Lx344nKyddq3dCCPdsY3OM/z975x1lWVF94W8z5DDkIAgIQxzJOSpBkpJUggSJYvzJEBQVAwiCAgaCKChZQLIgKEGGnGEGGLIgSRBBJIOkmf3749Sbft39uqcbnVevp+pb661+995p16ate++pqnP2sfdom5jMSFqcCJw/R9SRnEOk9zyeVdgkqEH0AEm5OqsBC6RTzwJ3lBQ4Akh6ka5Vgyttv5dZUlYkLQI813gJpHzPeW0/mVVYBtJD8MfASGCig4vtRbOJykQdF11IWgM4DlgamBYYBrxZUtFUg7QCuyfwUbrfIyUFS7sAf+jUHNdKHiT9jch/Psf2/bn1DJRqcTcAJG0MPAocDHwyfX4IPJqulcSCtne2fVnpAXTifGBC0/H4dK5ETiVyPd8H1gfOAM7MqigfdVx08Uti5+pRYAbgC8DxWRXl43fEtv0mxErsh4GigknbZ9QAujuSTm9hA3lKTk3txvYI298bSgE0wNS5BQwRjgE+0XMVKa02/ZlYYSkC2//JraHDmNr2u40D2+9KmjanoIzMYHu0JNl+CjhY0hjgB7mFZaCOiyZsPyZpWMp3PTVZvX0nt64MLGZ7W0lb2T49pTbcmFtUJTvL2X6lcWD7ZUnFWYMORepK9MCYGnimxflngdp9qWz+JWlisZikrYhCiBJ5JxUXPirp/yR9Gpg5t6hM1HHRxVtpAnGPpCMl7Uu5757G7t0rkpYBZiWs3YqjVaMVSUXZxTYxVSrUB0DSHNRFziFB/T9pYJwC3CnpHODv6dyCRAL8ydlUZUTSIraf6HFuVdt35tKUiS8DZ0k6nqi2fwYosjMdMAqYEdgbOJRI6dg1q6J81HHRxeeJoPn/gH2JZ+dnsyrKx29SsPR9oih75vS9RE4GJuaCp6L1S+hycSmJnwG3JmtMCO/swzLqyYaklW2P6XFuc9uX5dLUH7WwcIBIGglsSffCwj/afjCfqnxIGkuYwz+bjj8O/NL2snmV5SG9ALD9Rm4tuZC0ku2xuXV0EnVcTLTx+lOj2UrJNKW0FI+kQ4C5bH81TSz+BPzWdn+OFVMsKcbYIB1eU3hssUsjN1rSDoQN5Op5lbWmBtGDJG2zYPul3FpyImlV4FeE1+dKhCvD5rb/3u8vTmFImhc4HJjf9mbpQbim7eJ2KCRdSxRNXQCcO9QKRP6X1HHRRbLx2gC4ATgXuML2+3lV5UHS04S70blEoFT0C1jSkcBwYGXgJ7YvzCwpG5LWARa3faqkuYGZe+72loCkRYl3yI7AusQO3ua2X80qrA9qED0AJC0EHEm8CF4lOhUOB64Bvl2ibRWApDWJ7nRvA58aCn3u/9dIupxwpfiu7eUlTQ3cXfCK/HzAdoRJ/nAimP5RXlXtp46L7kiaBtiMGBfrEE01vpBXVfuRNCOwOZEKuDJwKWHp1auR15RKU4MRiHfp94mmRFdAmQ1GJB0ErEJ05lsitUM/v9QuhpKWIBrPPA18upMNDWoQPQAk3QocTXTkG5/ODSPylvaxvUZOfe2kqSNbg5HAc6SW6KV1ZJN0p+1VJd1te8V07h7bK+TWlpPUceoAYHvbxblS1HHRmxRIb0q0/f6Y7bkyS8pKSmE4BtjJ9rDcetpFbTDSG0n3EM3LxjY9L8bZXi6vsvYh6T66xxbzEIuW7wB06t+iFhYOjLlsn9t8IgXT50g6NJOmXPw0t4BOQNLUaUv6TUlzkm7+1FiiI7edJjeSliZWGrchnCjOBfbPKqrN1HHRG0XL7+2B9YDrgJOI3YoiSfUj2xMTirso7G9he/fcGjqQd21bUuN5MVNuQRnYPLeAD0INogfGGEm/Ak6nuzvHrsDd2VRloLYtnsgdRC74/kSV/QhJNwNzE0FkiZxCdLLc2PY/covJRB0XvdmFmFB9qfTiQklPEu+M84Bv2n4zr6L2I+kA20dKOo7uK48A2N47g6wsSDrc9oHAeZJOBGaTtBfhWvLbvOrazsu2X2vUnQ0VajrHAEgep3sCW9HlzvEMkc92ckkvBkk32V5H0ut0fwCK2IoropVvj236qYElib/BIyV3ckz3yhLpsLi/RR0XrUmFlqumwztsv5BTTy4kDbf9Wm4dOZG0he1LJbW0v7R9ers15ULSWNsrpe8bARsTz4srbf8lq7g2I+ky25tLeoKILZp9xG170UzS+qUG0ZXKB0DSM8DP+7puu89rUyppm/oM4EniAbggsKvtG3Lqaid1XPRG0rZEGth1xLhYl1iFvSCnrhxI+jBwHNAoGLsRGGW7VTOvyhSOpHuJNKdejWeguoANBWo6xwCRtAnwYeDq1NK4cX4P20X1uG+QiivnpWkc2X46n6K2MoxolNDy4VcoPydSOR6BiRXWvydcCEqhjovefA9YtbH6nOy7riZsrErjVOBsoigdYOd0bqNsijKRng/fAD5C93fIBn39zhTIUsAY0k5ubP0chAAAIABJREFU0/nGcUeuvk5uJC0ALEz3cdGRizF1JXoASDqcsGUaS/giH237uHRt4nZMSUj6OnAQ8DwwIZ12p1bQ/q8p9f/3/mhVTV5ghXkdFz2QdF+ztZ+iNfy9Jdr9tXJoKdW1Ja3CnkAEkRMb0PTsVjcl05z+VQkkHUEU3j5I17hwpzp/1ZXogbEFsKLt9yUdDJwtaVHb+1LuitMowtPy37mFZKLU/9/74y5JJwFnpuOdCPeBkqjjojdXSLqS2JWAeEH+OaOenPxb0s50/S12AEp9hr5v+9e5RVQ6jq2J2GJI1JrVlegBIOkh20s3HQ8DfkM0kxhp+6PZxGUidafbqODOY7Pbfjm3jk5C0nTA14hdG4h8z18NlYfh/4I6Lloj6bM05QHb/kNOPbmQtDCRE70msV1/C7B3QWlwE0kLUi8AfyB5AUNZecCSdrN9Wm4dnURqVLWt7TdyaxkINYgeAJIuA47qae8m6UfAgbanyqMsH5JOJpwH/kT3B2ARhVM93Ekaq48mdnemtV13eQqkjotKZWAkF4aedKwLw+QgNZ7pKwiz7T3bqacTkHQhsDwwmu6xRUdaH9YH+sDYttVJ29+TVOp21NPpM236QN8PgykO27M0H0uamViF/RKxslIcktYGDqZ3QUgxL8U6LnqT2jwfQXQgE4XZYTaTiir3oncxXXFd+oClbb/dfELS9LnEZOKyFucWBPYlipRL5I/p00zHxhY1iB4Ye9r+JYCkj9p+oHHB9rP5ZGXlQdvnN59IVlZFIWk2YB+iocTZhAtBqTmOJxMP/26FQiVSx0U3jgS2sP1QbiEdwCVEmtPVFH6PEKksPYtwW52bYrF9YeO7pEWBA4GPAT8hnqclMpvtY5pPSBqVS8ykqOkcA6CHIXqtvqf136Gkv42kuYiudNsTnfqOs11kW+cGkm63vXpuHTmp46I3km62vfak/+WUT6lOHM1Imo9oWnYmsCNdaU/DgRNsL5VLWw4kLUXYQK4IHAWcWWqtEfQZW3Ssi0ldiR48RVffS9oM+CSwgKRjmy4NB0q68Z8C/kV4vL4F7Cl1DY1ScsN7cK2ko4CL6J7LNjafpLZTx0Vv7pJ0LnAx3cfFRfkkZeMySZ+0Xao7CcAmwG5E34Xm++F1YiW2GCSdT/jo/4zYxRsPDG88MworstyBmFQtIqk5nWMWoGP/DjWIHhizSfo0MBUxwD/TfLGwl8E/CNuyLYlt+wavEw+BUjiKrjytWfr7hwXRWIVepemcgZKaJ9Rx0ZvhxIRi46ZzJiZbpTEKOFDSO8B7FJgfntp6ny7ps83pDIWyKnEvfIPYwerW6pqymq3cAjwHzEVMKhq8DozLomgA1HSOASDpNPqvoC2uKETS1CVvOVUqlUrlgyPpIFq8V20fkkFOpfKBqCvRA8D2brk1dCCPSmr1ACxp5oykDxO+rxM9cIFRtp/Jp6q9SNrZ9pmS9mt1vcQUhjouQNIBto+UdBytg6WOtKyaHEhayvbDklrWjBSW8tSg2Qd4emBzoNjiU0lbEkWFANfZbuXcMcXTwyZ0WmAa4M1O3a2pQfQAkHQr8F3b17S4Ntr2hhlk5aZ5y356wgZwjkxacnIq4b7QcCbZOZ3bKJui9jNT+lnTF7qo46IrICqta2Ur9gO+SPdt6galpTwBYLvb30LST4ErM8nJiqSfEKkdZ6VToyStZbuoHHHobhOqSA7fClgjn6L+qekcA0DSs8CrRKva79h+r+lax1aNthtJY2yvnFtHO2lVbV8r8Ct1XLRG0uzAK64vnkoP0ti40/ZiubW0G0njgBVsT0jHw4C7bS+XV1ln0MlxVnGd9j4gzxMrr7MBt0tasulakS8DSSs1fVaR9GXK3Nn4t6SdJQ1Ln52BovyAJe0lafH0XZJOkfSqpHGSOvLB1wbquJB+kOy7kDSdpGuAvwHPS/pEXnXtRdKqydqtcbyLpEskHSupxB08JN2XnhHjJD0APAIcnVtXRmZr+j5rNhWZkfSZps82aZX+7Un+YiZKDHo+ELbfAr6QnDn+Iulw2ydQruVd81bc+8CTwHZ5pGRlDyL39RfEhOoWYPesitrPKOC09H0HomXrooTv6bHAunlkZaWOi/DKPjR935V4Vs4NLAGcTjQcKYUTgU8ASGo00/g6sALwG2CbfNKysXnT9/eB5wsuVv8xcLeka4n75GPAt/NKysYWTd8bscVWeaRMmprOMQB6mn9LWoAIGv5DtC5dPJe2SiU3zWkKks4Gbm90nCqpAU+lO81bsJIuBK6yfWI6LmpcSLrX9vLp+/HAv2wfnI6LTfNJhZbrEBPNm2zfnVlSNiR9iMiLBrjD9j9z6qkMjLoSPTBeaD5Irb43kvRNunufFoOkOYGDaHoAAoeU0tq4Og90Y0J6AbwMbAgc1nRthjyS8lDHRTfekbQMkQ63PuGF22DGPJKyMazJFnRDosiwQZHvYUk/IApvG37hp0k63/aPMspqKy1cWxruPfNLmr9E1xZF+/NjiGJCA7cC+9p+PKuwPijy5h0stjft4/xRRHOFEjkHuAH4bDreCTiXtGVZANV5oIsfEH+HYcAfbT8AIOnjQEc++CYjdVx0MQq4gEjh+IXtJwAkfRIobcXx98D1kl4kdjBvBJC0GFG0XiI7AcvbfhsmOlTcAxQTRFNdW1pxNnA88Ol0/Dni/lm9z9/ISE3nqHwgJN1ve5ke5+6zvWwuTZV8SJoamMX2y03nZiKeMW/0/ZuVShlIWgP4EJHW8mY6twQwc6ErjtcCn7b9SjqeDbjIdomBYyUhaVxPV5LmdKhOowbRlQ+EpJ8DdwDnpVPbAKvZ/kbfvzXlIGku4GtECsMpxI7EuoT7wP62H8sor5KJOi4qlYEh6WIiB/gvxKrrRsQ75RkoJ/VJ0sJEM5EX00RrHeAx2xdnlpYFSUcQz89ziHGxPTA7adff9kv51PWmBtGVD0TqKjQTMCGdmgp4M313p3YX+l8h6Spiy34WIsfxVOBSImDayfZ6+dRVclHHRaUyMCTt2t9126e3S0suUl74rkSweA6RDnkdkbpwr+198qnLg6Qn+rnsTuuKXIPo/wJJWwH/tH17bi2V9tLYXkodlZ6yvVDTtWKr7UunjotKZXBImgZYBnjW9guT+vdTEpIeJGwOZwSeBuaz/VZKj7unZ8pkpfOozVb+O1YHvifp8txC2oWkhSXN2nS8vqRjJO0radqc2trMeIhpMfBij2sTev/z8pD0IUnT5dbRZuq4mASpOdP8uXVU8iDpBEkfTd9nBe4FziB8knfIKq79vG373ZQX/rfUj4Lk4vJuXmntZag2JKor0ZVBIel2ohjkH5JWIBom/BhYDnjP9heyCmwTkl4h3ElEbNXf0LgErGN79lzaOgVJVwMjgAsLypWv42ISSDqdeF781fb2ufXkJN0j7wHH274st552IOkB240geh9gPdtbpwDq8k5t7zw5kPQ4Yf0o4Ejgm41LwJG2R+TS1m4kjQU+Yful1JDoHLoaEi1tuyMbEtUgehBI+hpwVlM18ezADrZ/lVdZ+2iunJX0U2CC7QMkTUVsPy3X///ClEGyb+sT29e3S0snk9IaRjZs76Z06rgYOJJmsf16bh05SSvyHwLWsH18bj3toEcTnj8B59s+ree1EpB0an/XbRfT5XSoNiSqPtGDY6/mB53tlyXtBRQTRNO9zfkGwHcAbE+IeKkYdgIuB64uPRBoRtIwYF6ani2lBNCJOi560NRIoplXgafaraXTsP0P4B/AmNxa2sgrkjYHngXWBvaEiTaZRTVnIlq+3+a6mglDtCFRxwrrUIZJUmPAp4ChpDxggGsknQc8R9jOXAMTW5aWlMN1MrAZsJ+kd4GrgCts35tXVj4kfZ3oYvk8Xfm/JrbuS6GOi978ClgJGEdMwpcF7gdmlfQV21flFNdOJK0NHAwsTLx/RQc6DkxmvgQcC8wH7NPU3npD4E/ZVOVhF+B4SX8FriCeFaW2+x6SDYlqOscgkHQU8fA7MZ36EvB32/vnU9Ve0vb89sQW5HmpBTqSVgTmsX1lTn05ULRA35gInpYlurFdYfu8fn9xCkPSY8DqpbR+nxR1XASSLgK+39TJciRwCHAA0VyjI7dpJweSHgb2JVaexzfO13umbCQtRTwnNgFmBa4lguqbbY/v73enJIZiQ6IaRA+ClPf7JWLGDGESf1JJg7zSRRoP2/QMiiStDGxq+7A8yvKQOpBtlLbjiqWOi+700d30ftvLdHKu4+RA0u22O7J9caUzkDQDsD4RVK9pe5XMkir9UIPoSuW/QNJdpT/kJO2Xvn4UWJLYkn2ncd32z3PoykkdF11IOhd4iai2h9jJmgv4PHCT7VVzaWsXTXnh2wHDgIvofo905CpbZfKT0kIfsL1Ubi2VwVOD6EEgaXHCzm0kMH3jfGH5bJUmJP2E8AM+l66OjR3XmnRyIumg/q7b/mG7tHQKdVx0kVbWvkq0Mwa4mciTfhuY0fYbubS1i7RL0xe2vUHbxFQ6DkmXAF+3/XRuLZXBUYPoQSDpJqJw6hfAFsDuwFS2f5BVWCUbfbQoLa1QqNKDOi4qlcFRcgdgSTcAKwJ30H3SvWU2UZUBUYPoQSBpjO2VJd1ne9nmc7m15SY1UHiLaBpwf249lfYj6S/Atj181M+xvUleZZWctHCkAMrcwZN0ONFEo/ke2d/29/Iqy0/62ywLTG17s9x62klf/vLVV77zGxLVIHoQSLqF2JK8gLB2exb4ie0lswrrACStCiwErGb7W7n1tAtJMwL7AQvZ/mJK+VmyE2/2yU2rIrHSmic0qOOii+pI0UWr+0HSWNutvLQrBSFpYWBx21en58ew6jXf+Q2JpsotYIgxCpgR2BtYGdgZ2DWrog7B9p22LywpgE6cSvhjr5WOnwV+lE9OVsZLWqhxkF4Kpc7S67jo4lXbl9t+wfa/G5/cojIxTNJ0jYOULz5dP/9+ikXS1yTN1nQ8u6Sv5tSUi9S07QK67HMXAC7OpygfkmZKDkcN/gk81IkBNNRmK4NlfCqCeYPIhy4WSXMD36J3kWVpBTIjbG8vaQcA22+psNaNTXwXuEnS9UQTiXXp3nWqJOq46OLa5LFfHSngLGB0U7vn3YHTM+rJSe0A3MXXgNWA2wFsPyppnrySsjEa+AQRZ0EsXF5F14JER1GD6MHxM0nzETPGcwvP/T2LcB74FPBlYkX+X1kV5eHdtJrU6GI5gqZAoSRsX5GsvNZIp/ax/WJOTRmp46KLhi9ys+WfgdIm3Ng+QtK9RJAAcGiJDaoStQNwF+/Yfrcxz04t0EvdxZu+2bHH9hspvaUjqUH0ILC9fgqitwNOlDScCKZL3Kad0/bJkkal4ofrJd2ZW1QGDiY6Sy0o6SxgbWC3nIJykVZaNwUWtX2IpIUkrWb7jtzaMnAwdVwA8dzMraHDeAh4v5H7KmmWQnNfrwDOldTcAfiKjHpycr2kA4EZJG1EWEJemllTLt6UtFJjpyo1qfpPZk19UgsLPyCSliXa1m5vu7jZs6TbbK8h6UrgWOAfwAW2R2SW1nZSe+c1iBSG20pdfZX0a2ACsIHtpZPzwFUlNNNoRenjQtLOts9sasbTjUKb8OxFpDjNYXtEKjg9wfaGk/jVKY7aAbiL9LfYE9iYeF5cafu3eVXlIZkUnEPEFALmI+KsMVmF9UFdiR4EkpYmum1tQ1cjhf2zisrHjyTNSvz3HwcMJyrwi0LSaOBntv/UdO43tkvMBV7d9kqS7oaJOY7FTTChjovETOnnLFlVdBY19zVhewLw6/QpnZ0IO9CJgbOkzUt087F9p6SliO63AI/Yfi+npv6oK9GDQNKtxAzpfNv/yK2nkh9JjwN/B65pdOYr1bJK0u1E8cedKZiem1iJLtHiro6LSi8k3W579YbVXcp9HWt7udza2o1qB+CJSHoFeBLYwfZD6VyxzwtJy9B7XJyRT1HfVIu7QWB7TWLWPIekZSRNk1tTLiSd3sKe6JScmjLxCrEdOa+kS9PqfFFIOi19PRb4AzCPpMOAm4DDc+nKTB0X0gHp53GSju3xOUbSQangcopH0v+lrz1zX8+n3NzXU4n36fvA+sAZwJlZFeXjCWAP4AJJ26ZzRbr5SDqI2N0+jhgXRwId27mxpnMMAkVXoTOIGaOIoqFdbd+QVVgelmt03YKJW/fFrTgSuznvA1+VtBsROM6eV1LbWQ7A9lmSxhDBo4CtG6sqBVLHRRTQAdzVx/U5Cdu75dsjJyt7AL8Evk3kvt5H5AP/GTgpo66czGB7dHLoeAo4OD0/fpBbWAZse2yKMX4vaXVgWG5RmdiGeCbcbXt3SfPSwZOrGkQPjp8DG9t+BEDSEsDvicYrpTGVpNltvwwgaQ7KHE8nNL7YPk3SfUTeY0nMmCZQjZWTW9PPGZqrrAuj+HFh+9L0s08fZElvtk9RflIe8G/Tp3TeSQV1j6aV+meBmTNrysVzALZflLQJcASwTF5J2fiP7QmS3k8OaC8AC+YW1Rc1J3oQSBrXM3et1bkSkLQLcCCxHQmwLXCY7d/lU9U+JA23/VqaPPTC9kvt1pQLSa8Dd9J6+9ElNeCp46ILSUfb3kfSpbTwvLXdsVu0/2skvQ+81eoScY8Mb7Ok7CQXhoeA2YBDieL0o2zfllVYJSuSfkXEFp8jjAveAO6x3ZEN7moQPQhSzu8EurYWdiL62++RT1U+JI2kq2HCNbYfzKmnnUi6zPbmkp4gAoTmANIlFcc0iqRy6+gE6rjoQtLKtsekLepeJH/5Iqj3SG8K3qWaSJ1o9o+kjwDDbY/LLKVPahA9CCRNR2zJrpNO3Qj8ynaRncgkrQMsbvvU5MQws+0ncutqB5LWsX2TpOltv51bT05qgNBFHRetUXRvXKiRClca9R7pjaRrCQ/gYjsANyYSdaLZhaQ/Ei5ol9ju+HSvGkRXPhCpgnYVYEnbS0ian7D+WzuztLYgaYztlUu2IWogaSPbf8mtoxOo46I3krYAfgpMa3sRSSsAh5S0yibpQNulOtX0ibo6AG9PpHMU1QFY0mjbG0o6wva3cuvpBNKEYnvgU0Sa4DnAZZ26KFGD6EEgaW2ine/CNBXRlbRF20DSPcCKhMfpiulcMfnhkm4DxgFbEzd5N2zv3XZRmUgrSn09SFxSN7Y6LnqTHBc2AK5relbcZ3vZvMraR1p06O8eObSdejoNFdoBWNKDwBeAk4Ed6VFXUnK6i6RhxHNjL2DTTq0bKNFN4b/hZKIr3xiguNakPXjXtiUZQNJMk/qFKYzNgU8AmxDjoWS+0eLcGsRL8YU2a8lNHRe9ec/2q1L3+CCXmEy80eLcjEQANSdRWFcUqh2AIez8vg98mHD/asZ01RwVRUr/2oIYHysBfTr85KauRA8CpW5TuXV0ApK+ASwObER0ndoDONv2cVmFtRlJq9juywe3ONJW3PeJTlOH2b48s6Qs1HHRhaSTgdGER/Jngb2BaWx/OauwTEiaBRhF+EWfR7SHL22yWTsANyHp+6XvRjSQdB6wGnAFMbG6PllDdiQ1iB4Ekn5CGKBfBEwsJix1yyV13NqY2IK6sqS82JTneQrRbWs8sJ3tW/KqykfyNv0ecV8cZvvazJKyUMdFbyTNCHyXpmcFcGin5jhOLpLt4X6Eq9PpwDENn/1SkTQtsEQ6fMT2ezn1tBtJ8xB2bosRaWA/sf1aXlV5Se+Sq20Pid3+GkQPgpT72ZOifHArgaRxRID0cOoudaTtlhXWUzqS7gTmBo6iq9HKREqaZNZxUWmFpKOAzwC/AY633Sq9oyhadQAGdnVBHYAlXUGkfd1ApILNYnu3rKIyI2ka4CvAx9Kp64ETOnWCVYPoygdC0meIrkrzEA/AopoG9HRfKNmNQdJ19F80Vcwks46LLiTNRViCvkyszh8FrAv8Ddjf9mMZ5bUVSROIXZr36bpXGknixTw3m0kFpzu6Rwdg28V0AJZ0r+3lm46LfV40kHQSMA1dedCfB8bb/kI+VX1TCwsHgKSdbZ8pab9W1233LAgogSOBLWw/lFtIJubpMR66HZc0Jmyvl1tDB1HHRRdnA3cRtRN3AKcBxxCB9EnAermEtRvbU+XW0IFM0+wbbvuvaRWyKCTNTteEaljzsQvqcNrEqs0TC+AaSfdmUzMJahA9MBrOE7NkVdFZPF9wAA3wW7qPh57HxdFiG+464MRO3YabTNRx0cW8tg9U2HI8ZfvIdP5hSV/LKSwnkpYnJhIAN3RyN7bJzF1p1bG5A3BpxbizEukczdY1jfQ3A8XZ5wLjJY2w/TcASYvSwW5oNZ2j8oGQdAzRbepiuhdZXpRNVCUrQ20brjJ5ad6armkugaRRhO9t4zn5aeA3pbkaQe0AXGmNpA2BU4HHicnFwsDunVqsXoPoASBpL6JRwKNpVeVkwqrpKaIQ4u6sAjMg6dQWp217j7aLqXQEPfP7+jpXKQNJrxAFUyJWXhsFYwLWsT17Lm25SIWnazbaGSd//VtLaVJVqQyENMFaMh0+0skTq5rOMTBGEfl8ADsAyxPbLCsCx9K1NVcMtnfPraHScQypbbjKZGerpu8/7XGt53EpiO73xHh6dKkrhdoBuNIPKwMfIcbFCpKwfUZeSa2pQfTAeL8pr3Nz4Azb/waulnRkP783xZIqqX9N5D0uI2k5YEvbP8osrZKPbwLXSuq2DZdXUiUjOwGXE56vr+cW0yGcCtwu6Q/peGtiZ7NEagfgSi8k/Q4YAdxD17gwYYfYcdR0jgEgaSzwKcKq6SlgA9sPpGsP2V46p74cSLqeCJpOtL1iOne/7WXyKsuLpK2Af9q+PbeWHAylbbh2UuK4SD7ZmwEbAu8CVwFX2O7YSvt2IGklmvKAS0wHhNoBuNIaSQ8BIz1EgtO6Ej0wfkBUDQ8D/tgUQH+cSH4vkRlt3xEp4hN5P5eYDmJ1YFlJU9veLLeYdiBpA9vXJO/wZhZL23C12LTAcZEmDLcDB0uak+hYuH/atRpLBNTn5dTYLiQNt/1a6lr4ZPo0rs1RqJXZtakJTe0A3IMUSEI05vllVjHt537CtOC53EIGQg2iB4DtyyQtTHQTam7TehewfSZZuXlR0ghS4wBJ2zBEBv3kxPaBuTVk4OPANcAWLa6ZLieCYil0XEwkpb/9Pn2QtDKwaVZR7eVsIhVwDN0bE4lyrcwaq9CrNJ0zUExzpr6wvXRqVlTiSv1cwIOS7qD75GrLfJL6pqZzVD4QqWjsN8BaRJrLE8DOtp/MqSsHkpYBRgLTN851ahFEpX3UcRFImg3Yha5CIQBs751LU6VS6UzSDn8vbF/fbi0DoQbRlf+KZNE0VamFQ5IOIjqvjQT+TOSA3mR7m5y62k168L1se5yk7YiGK3+jUN/XOi66kHQLcBtwHzChcd726X3+0hSIpKkJ33RLWpBYZXzM9j2ZpbWV2gG4N5LWAI4DlgamJVJH3yyxHfxQo6ZzVAaFpFuB79q+BqDhd5qujba9YTZxediGsDy82/bukualqwNXEUg6HlgOmF7SI8DMwBXA2sAphEtDaRQ/LpqY3nbLgKkUUq+BI4A3JB1KFGWPBVaUdIrtI7IKbC+1A3Bvfgl8DjifSG/ZBVgiq6I2I+km2+tIep0WKU+dOqGoK9H/BZI+BLxU0kqbpGeBV4nVte80t3SWdHfDqaMUJN1hezVJY4D1gdeBh2wvlVla25D0oO2RkqYHngXmsT0+NSYaZ3vZzBLbTh0XXUjaF3gDuIzuOY7FFNNJeoBw5JgFeAhY2PaLkmYE7rT90awCK1mRdJftVSSNazTeKfF9OhSZKreAIc7vgIclldQ44Hlipjwb4Xe6ZNO1Emdkd6Wcz98SRUNjgVvzSmo7bwPYfht4yvb4dGzgvf5+cQqmjosu3gWOIv77x6TPXVkVtZ93bb9s+2kiheNFANtvEX+fYpC0l6TF03dJOkXSq5LGSSo1aHxL0rTAPZKOTBPPouIzSTNKmqbpeElJ+0r6dE5dk6KuRP+XpNW2kQ3buykdSWNtr5S+fwY4Gjjc9gmlz5wlfQQYbntcZiltRdIzwM+Jbbd903fS8T62F8ylrRModVw0SM13VmsEjiUi6WGi2+1URFrPjsT9IeDMknoNSLofWNH2e5J2BPYn7A9XBA6yXVwH4OT+9TyRD70vMCtRT/JYVmFtRNINwJ62H5W0GHAHcBZRV3Kn7W9nFdgHNYgeJJKGAfPSvcr86XyK2ktzEJ2OFyBaov8HWNr24rm05SL9DXq2rr0hn6L2koro+sT2D9ulpVNIqyfX2H41Hc8GrGf74rzK2o+kq4Ct06prkUi6tr/rttdvl5bcSLrH9grp+9nA7baPScfd3i+lkAr0/2N7QjoeBkxX0j0j6b5G6l+qG5jD9tfSCv2YTk0LrIWFg0DS14GDiBljo8rcRFFVKbzQfGD7WWAjSd8kVhOKQtIRhFf4g3RvUVpMEA38FbgqeQFXgoNsN1o7Y/uVNNkoLogG3iS2qa+le050SRZ3O9n+R24RHcKEVE/0MtHN8rCmazPkkZSd0cAniNoBiL/DVYSFbCk0r+huQKSAYftdSRNa/0p+ahA9OEYBS5YcLNhu2SDB9lGkQV8YWxNjopji0hYsBJyf8tlGA5cDdwyVtq2TiVb5jKU+by+mzMlDMyelboXXEc41N9kutcNr7QDcm+ltNwJobL+Rik5LYlyqL3sWWIyYRDR28TqWms4xCNJKykYFP/wmkpwY9gQ+SvdmEntkE5UBSZcD2zY/AEtF0izEasqmwGqEC8EVwJW2n8+prd1IOgV4BTg+nfoasT25WzZRGUjb0leXlK7QF+mZuR7hGb428DRxf1xRUkogTPTM7tYBOKU0qMRnqaSbga83Wp6njp6/tL1mXmXtQ9IMxELlh4BTbN+bzq8FjLD9u5z6+qIG0YNA0snAksCf6L4tWaI5/PnAw0SBzCGEF/DHv5wuAAAgAElEQVRDtkdlFdZmJF1I+AGPptytagAkLWj7703HI4mAYWPbm+RT1n5SQPB9YlJh4C/AYc2+6qUgaTTwmUZ+eCWQtAhxf2wKzGd7tcySKpmQtCpwDvAPoth0PmB722OyCqtMkhpED4K+CqgKLZy62/aKDV/LtJV/o+01cmtrJ5J2bXW+tG5s0L0wpBJImqnEwLkZSZcQzgt/IfKjgfImmv2tykua1nZRVneV7qR3aMMy9pHmHgyVzqXUHL0PRInBcj80bvBXJC0D/BOYJ6OetpNeirvVreqJjJW0qu07cwvJTdqCPIno3riQpOWBL9n+al5lWbgofYomNSCaIGnWnqvyNYAum5T/vB/RhGcvSYtLWtL2Zbm1VfqnBtGDQNLcwAH0zgPeIJuofPxG0uzA94A/EsHC9/NKai/9vRQLZXVgJ0lPESuOjXatJbnXNPgFsAlxb2D7XkkfyyspDyXuyvTDG8B9kopelW+FCuwA3MSpRBOiRg70s0QL8BpEdzg1iB4cZwHnApsDXwZ2Bf6VVVEGJE0FvJaKQm4AFs0sKSf1pdhFUXnPk8L236MX00TG9/Vvp2RSd7ofE00TmhcfSnxu1FX5vvkdMELShba/kVtMmxlhe3tJO0B0slSPh0epSDoceBU4qROd0WoQPTjmtH2ypFG2rweul1Tc1rXtCZIOAM7LraUDqC/FhO2nJK0DLG771LRzM3NuXZn4e0rpcMp1HEW4lZTIqYS//i+A9YHdKaylcQPbpycXgoVsP5JbTydh+xONDsC5tWTg3TQuDCBpBE2F6oVzBzCCeH7skllLL2ph4SCQdJvtNSRdCRxLVNJeYHtEZmltR9JPgBeJlfnmFdiXsonKRH0pBqnwdhXCN3sJSfMD59teO7O0tiNpLuAYwp1DhOfpqE5cSZncSBpje+UeHcnG2F45t7Z2I2kL4KfAtLYXkbQCcIjtLTNLy0LpHYAbSNqISI0cSTwr1ibqba7LqasyaWoQPQgkbQ7cCCwIHAcMB35o+49ZhWVA0hMtTru0Ldr6UuxC0j2EC8NY2yumc+MKzYmuJCTdAqwDXABcQ+R7/sT2kv3+4hSIpDFEN7brmu6R+20vk1dZ++mrA3CpzwtJcwJrEJPu22y/mFlSFiQd2+L0q8Bdti9pt55JUdM5BkFTpeyrxLZkySxt++3mE6mZQGkcTDQWuQ7A9j2SippINPGubUtqbEnOlFtQLlIqy17AR+i+ylZUM6LEKGBGYG/gUCKIbGkNWQDv2X61R7prx7Y0nswU3wG4B9MTrdCnBkZKwvYNmTXlYHpgKaKwEuCzwBPA8pLWt71PNmUtqEH0IKgvxm7cAqw0gHNTOvWl2MV5kk4EZpO0F7AHYfNWIpcQu1ZXU2hBYYMmy8M3iHzoknlA0o7AsFRwuTfx3CyRvxMLUsUj6Qhge+ABmlblicL90lgOWNv2eABJvyaepesA9+UU1ooaRA+O4l+MkuYDFgBmkLQisfUEkdoyYzZh+agvxYTtn6bcvteIpgE/sP2XzLJyMaPtb+UW0QlIWgL4JrAw3RcfSrQG/TrwXaJo7GzgSuBHWRW1GUn7pa+PA9dJKr4DMLA1sSpfiwlhdqIgvTHBmgmYI1nKdtzfpwbRg6O+GMPGbDfgw8DP6AqiXwcOzKQpJ80vxd8TL8VDsyrKhKTvA6c1B86Svmj7Nxll5eIySZ+0/efcQjqA84ETgN9S6OJDEysTk8vvNk5IWgkYm09S25kl/Xw6faZNn5J5HJiG6sgBcCRwj6TriPjiY8DhKT3w6pzCWlELCweBpB8Bt9QXI0j6rO0Lc+uodA6SXiB80//P9rXp3FjbpaX4IOl1YgXl3fRpNJ4ZnlVYBkp14miFpLeAO4Ftbb+QzhV5j1S6kHQhsDwwmu6r8iX2G2g03lktHd5p+x859fRHXYkeAOmFaOJFeGDaUniPgl+MwIclDSdWoH9L5EJ/2/ZVeWW1B0mXkjw9W1GiOwfhurAVcL6kC2wfRddORVHYnmXS/2rKRtIc6eulkr4K/IHuAUJxdpjAI8BRRI+BPW3fQqH3SGpQta3tV9Lx7MA5tkts2vTH9KkEUxELMlMDi0larFOLLGsQPQDqC7Ele9g+RtImwJzA54mOU0UE0YStHcBngPmAM9PxDoRlU5HYflrSx4FfSzofmCG3phykphE7AYvYPlTSgsCHbN+RWVo7GUPX4gNEXnQDU2anU9u+TNIjwLmSTqGfyfgUztyNABrA9suS5skpKBe1CU8XQ63IsgbRg0DSx1qd79QZ0mSm8WL8JHCG7QdKalOaOlYi6We2V2m6dKmkuzLJys1dAMn6cHdJXyNyQEvkV8QLYAMiR/4N4Hhg1Zyi2ontRXJr6EAEYPvR9D45hXAjKJHxkhZqNFeRtDCFTiia+w0ARfcbYIgVWdYgenA0r6RMT+TsNMzzS2OMpKuARYDvSJqFMq3dZpK0qO3HASQtQuTCFoftvXocH08EjiWyuu2VJN0NE1fZiiyeSv7xXyUsqkw4HJ3Q02e+BBoNVtL3N4DtJC2UUVJOvgvcJOl6YnKxLvDFvJKycTC130CDIVVkWYPoQWB7i+bjtEV7dCY5udkTWAF43PZbKf9xt7ySsrAvYdP0OPEiWJjCXgSSzrO9naT7aLGSVGgHsvdSS+NG45m5KXOSCXAGUTtxXDrekUj92jabojYj6QDbR0o6jtarrcUVkNm+IjmTrJFO7VNqlz5qv4Fm3iLcOYZEkWUNov87ngGWzi0iB7YnkGyZJI0gXoyfAz6aU1e7SS+CxYkOSwAPD5VtqP8hjQ5Sm2dV0VkcSxTSzSPpMGAb4Ht5JWVjGdsjm46vlfRgNjV5aPz3lprq1YuU/rcpsKjtQyQtJGm1wuoGGtR+A10MqSLLGkQPgh6rCFMRK7El+XtORNL8RPL/jsCywI+JILooJE0DfInwsoRYlT7R9nsZZbWbywh3lh/Z/nxuMZ2A7bMkjQE2JHYotrb9UGZZuRgraQ3btwFIWp3ygsntiftkNtvH5BbTITTXDRxC7FZcSEF1A00U34Snge3Tc2sYDNUnehBI2rXp8H3gSds359KTA0lfJBwoFgDOS59LSi0iknQSkb/VuPE/D4y3/YV8qtqLpPuBw4kCum/2vG77oraLyoSkLwGnt8r3lTSqxABK0kNEB8un06mFCKu39wm3iik+3SetvH8CuBxYjx62diXa/TX8sSXd3cgVl3Sv7eVza2sXkma0/VYf1xax/US7NeViqKYF1pXoASDpEuDm9LnT9ruZJeXkl8CtwI627wKQVPJMbNUeD/1rJN2bTU0evkzYuc0GbNHjmoFigmiiRmJvSTvZvqfHtV2B4oJoYsu+dE4gGmksSu/dy1Lt/mrdALwq6XDghylFspkLiR2+UhiVfg6ptMAaRA+M3wJrAYcBy6eVlVuIoPoW2yX5An+IKAj6maT5iJXoafJKysp4SSNs/w0gVVQX1drY9k1Elf2dtk/JrSczDwPfAi6W9EvbP226VowFZDO2n5K0POG+AHCj7aImmraPBY6V9GvbX8mtJyeSTrO9G7VuAMKJYgRws6Qde6w8F/W8sP1c+vlUbi2DYarcAoYCti+zfaDt9YC5iKT/fxKdpzq2HeXkwPa/bZ9g++NEvucrwPOSHkoz6tL4JlEodV2yaroG2D+zprYiaXFJFwP7S/q9pAVya8qIU9fOVYB1JI1OLWyhXA/cUcBZwDzpc6akr+dV1V4kTS9pH2LS/UVJJS9gLQdRNwAcQNTTPEfUDZyfU1gG3rS9M2EFeoOkXZquFfW8kHRT+vm6pNd6fF6V9ISi82lHUXOiB4ikuYjV6LUIS57pgXuAW4daIvx/g6T5W/Wxl7QE8Dnbh2SQlRVJ0xE5nwCPlObOIelGwsbsBmBLYE3bn8mrKg+NPM+m4y8DBxJWiN9tvlYKksYRY+LNdDwT8dzsyBzHyYGkc4H3CI/szYCnbI/q/7emTCQ9TNTVtFxptV1MsX7z80LSRwjrx2eJYvVrS3xe9IWkOYmd/yUn+Y/bSA2iB4CkR4FXiRyl24i86DfyqsqDpD8DcxCm8FcAN9l+P6uoDEjqN0gsrJjuHtsrNB2PLfXh31wk1XRuKWIldhnb0+VRlo9UKLRqo9gyNV+50/ayeZW1D0n3Nf570yr0HQXfI68Dd9I6iLbtYpqX9XxeSJoK+D5RPzGD7Q/1+ctTGJKG234t9Zzohe2XJH2okfbRKZS8pTQYTiFWnz9L2LktI+lW4G7bpeW/fjK9BNcDPg38VNLTREB9RaOFawFcQOxENIrHml8IpRXTTS9pRbr+BjM0H5e0skSsIHXD9sOSGs+PEjkVuF3SH9Lx1sDJGfXkYKLlpe33ezTVKI3HSgqUJ8Gfmg9SceEPJV1JdDEsibOJosIxLa6Z8BPvqAAa6kr0oElpC2sBaxJtbF9M+cHFomh1vRlRhT+f7dUyS5rsSNqa8MVeDLgE+L3tx/KqyoOka/u5XNTKUjOSZgcWJ1K/ALB9Qz5F+ZC0MrB2OrzR9t059bQbSeOBNxuHwAxEZzYR98jwXNraTavdmkplqFKD6EGQnBfWIl4GawHzA7fbHlKWLJMTSdOWZAGY8ju3IpopzEnkvV6fV1UlN5K+QFg2fZjYrViDyAMudUIxDJiXpt3PgnatKk1I2sj2X3Lr6CRSl8IfAyPpPukuzvpQsU2zE7CI7UMlLUQsznVkJ8uazjEA0jbkGsBrJFs74NgSO5ClfLa+Zl62PWs79XQAbxP58q8BC9P0AKwUzSii89ptttdPedEluteQnDgOAp4n7B9FPEOKKSysdONASd/p45ptb9hWNZ3BqcQ98gtgfWB3ynVPa+5keSgd3smyBtED4w/AF2z/O7eQ3NieBUDSoYQt0e+Il+JOhId0EUjagEjnWA24Gjim0XymUgHetv22JCRNl/KiO6qqvI2MApasz89K4hstzq1B2N290GYtncIMtkdLUvJJPljSGOAHuYVlYPVGJ0sA2y9Lmja3qL6oQfTA+BzwVUnXUbAjRQ+27NGp79epU18pN/3VwDjgJmA6YJdmj0/be+cSVukInpE0G3Ax8BdJLwNDqonA/5C/E7s1lQq2JxaOSfo44UYxPfBl25dnE5aXd5Izx6OS/o+wuZs5s6ZcDKlOljUneoA0OVJsRuREl+hIMRFJtxAG8ecQg30H4Gu218oqrE1I2rW/6yV5h/dFajLyUmm+2T1JgcKsxLOimHqBBpJOJnzU/wRMHAu2f55NVCUrkjYhuhO+Axxmu7/i5CkeSasCDwGzESkMw4GjbN+WVVgGJO1E1BitBJxO6mTZqY14ahD9ASnRkaKZZAx/DDGhMJErvo/tJ/OpqnQSkq4mWtpeaLvVFu4USVpFecD2Urm1dAKSDmp13vYP262lkh9JdwJzEx1/b+15vTBLzMbz4oiSnpGTItWQbEikio7u5PqzGkR/ACQNp3sqzBslrTDVm74yUFKl9UjbD+TW0k4kXQJ8vcRdqkqlP1JaZH/F6cU52Ei6zfYauXV0EpJmJNxKnrL9r9x6+qLmRA8CSV8Cfkg4MjQeAi7Nhsb2eEnr5NZR6UwkzUN3m6aiAujE7MADku6gyx8Y21vmk9ReJB1tex9Jl9IiaCrpb1HpwvZ6uTV0IHdL+iNwPt2fF8U07ZK0JXAs8BKR6nM84ejzEUnf6tQUyboSPQhS++81bb+YW0tuJP0aWICCb/pKd9JD8GeEf/oLhOXfQ7Y/mlVYBlIedC9K8hCXtLLtMfVvUWmFpGmArwAfS6euA060/V6fvzSFIunUFqdte4+2i8lEMibYlqgfuRZYzvbjaVFmtO1lswrsg7oSPTj+RnSZqsRK478JL8cGpbW77oWkrxJ/lwsLdHA5lLCqutr2ipLWB3bOrCkXn7T9reYTko4AigkcGy4MjWA5BU3LAM/aLtXKrNLFr4FpCF9ggM+nc1/IpigfJ9m+ufmEpLX7+sdTKBNs/xVA0hO2Hwew/YKkjn2X1iB6cHwHuEXS7XSvMi/Ozsz27rk1dCgi2sHvBJS2Xf2e7X9LmkrSVLavlXR0blGZ2Aj4Vo9zm7U4N8Ui6QTgONsPSJqVKCIbD8wh6Ru2f59XYSUzq/awSb0mrUaWyHGEG8Wkzk3JTCVpdqLJzIT0XY1r+WT1Tw2iB8eJwDXAfXSwb2E7kPRh4iZvzJZvBEbZfiafqvzYPj63hoy8Imlm4AbgLEkv0JTqUwKSvgJ8FRghaVzTpVkIB5uSWNf2l9P33YG/2t5a0nzA5UANostmvKQRtv8GIGlRYpJVDJLWBNYC5pa0X9Ol4cCwPKqyMSvQ7MzS/L1j845rED04prG936T/WRGcCpxN5DBBbNufSqzAFYOk6YDPAh+h6X6yfUguTRnZCvgPsC+xEj8rUNrf4WwiQPwx8O2m86/bfimPpGw0OxZtRNRPYPufYdpSKZxvAtdKepxYcVyYmGyVxLREU5WpiYl2g9cIf+SSWHwo5sPXwsJBIOlw4EngUrqnc5T2ckTSPbZXmNS5KR1JVxDd2MbQtIpi+2fZRGUieac/Z/vtdDwDMG+J3uGSRgDP2H5H0nrAcsAZtl/Jq6x9SLqWKDR9ligUWioF0FMD91cf7UpahFgyHT5SamMmSQundt+kzoUz234ts6y2Iuku4Bm6mtg9mVfRwKhB9CCQ9ESL08VZ3AFIGk2sPDe2ZHcAdre9YT5V7UfS/baXya2jE0gPwbUanumSpgVutr1qXmXtR9I9wCrEDsWfgUuAj9r+ZE5d7UTSEoRl1XzA0bZPS+c3ATa2vX9GeZVMSNrA9jWSPtPqeokOT5LOBr5MLMTcSaRzHGP7qKzC2kxq4rZp+iwA3ETs7F3fqROsGkQPkDQ73Nb2ubm1dAKSFiZyotck8pVuAfYurbmEpN8QxVP35daSmz52J+7tUTxUBJLG2l5J0gHAf2wfJ+lu2yvm1lap5ETSD20fVG3dumg8O1PL65WIVLAxtpfLLC0byc1nXSKgXg/4l+1PZRXVgpoTPUBsT5D0TaDoIFrSEcm6a7XaLAEIJ47d0i7FO0Runwt9+P1L0pa2/wggaSugVE/19yTtAOwCbJHOTZNRT6XSEdg+KP0sLf+5P6ZJQePWwC9tv1d63UDKj74mfZC0QF5Frakr0YNA0k+IoOBcujcYKSYnWtJ9RH7nGNsl2e+0JK3I96KR31YSKQ/4LGIbzkR+2y62H8sqLAOSRhLbs7fa/n3KF9/O9hGZpVUq2UkNeF62PU7SdkTDlb8Bv+rUbfvJiaS9CfvLe4FPAQsBZ9peN6uwDEjanOg58BHCoaSxMDU8p66+qEH0IKg50SDpKGAvoqL4LdIAp8MH+uRE0vLEthPAjbZL9ToFINncYfuN3Fo6BUkLAp8rLcexUumJpOOJhZjpgUeId8kVhF3qVLZ3yiivY5C0gO1nc+toN5IeAz4D3OchEKDWILrygZB0ie2tcuvIjaRRxKSiUQzzaeA3to/LpyoPkuYFDgfmt71ZWo1d0/bJmaVlQdLchAXkDkQr9D/Y/kZeVflJaT7/tH17bi2V9iPpQdsjJU1POLfMY3u8In9hXKe2d24HkmYjLFN3BJa2PX9mSW0nufpsaHtI9OKoOdGDRNIywEhiFg2A7TPyKcrGd3qekLSe7esyaMnJnsDqtt+Eia2dbyWKLkvjNMKx5bvp+K9E6lMxQbSkWYhVlB2BJYjJ1SK2P5xVWGexOrCspKltb5ZbTKXtvA1g+21JT9ken44tacj5BP+3JCvQrYhnxoqEX/TWRNOqEjkA+LOk6+luJfzzfJL6pgbRg0DSQUSV6EjCtmozwoKlxCD6PEm/A44kJhRHEpZea2ZV1X5E9y5b4+lqVVoac9k+T9J3AGy/L6moDmTAC8AdwPeAm1Jg8OnMmjoK2wfm1lDJyjypO5+avpOO584nq/0ka7t1gauIhZdrgMcKXIxq5jDgDSKumDazlklSg+jBsQ2wPHC37d3T9vWZmTXlYnXgCMLabhaioGztfn9jyuRU4HZJfyBeAltR0MprD96UNCepRaukNYhGNCXxHeBzwK+A30sq2s2ngaS16N3Vs8TFhwr8lq7ufM3fAU5qv5ysjAReBh4CHkppLaXn2M4/lHov1CB6cPwnWd29L2k4seq0YG5RmXiPaPE8AzFjfGKo5DD9L7H9c0nXEVZ3EA1n7s4oKSf7AX8ERki6mVhVKqp1re2jgaMlLUoE0xcD80v6FpET/desAjOQdqxGAPfQtWtjytzBq0Sa11W2/51bSG6SN/RSRN3E1ZJeBGaRNK/t5zPLy8WfJW1s+6rcQgZCLSwcBJJ+BRxIvBz3J7Yc7inR71LSvUQXtkOBuYATgHdtb5tVWJvp0d55fWBZCmvv3Exq6bwksSr/SPL6LJpUR7EDsL3txXLraTeSHgJGDoVK+8rkJ00oNyF800cTHenuqOMDJK1MPCu2I94ra2WW1HYkvQ7MRORDv0eHO3/VIPoDktpTDrc9LrOULEhaxfZdPc593vbvcmnKQY/2zn8iVmKLau/cTOnb9pKuJOy6Lrf9cG49nYCk84lups/l1lLpHFIR7ieIjnSrESkNVwBXlrIKmxoy9VqVT04l69ouqrgwdYZe0/bNubUMlBpED5LUNWdhugcJRQ10gLTq+tF0+IDta3PqyUVt79xFX9v2tvfOp6q9SJqPCAo2Jdw5bicCg6sbDi6lIOlSIm1jFmAFouCyudq+djwtGEkL2v570/FIolh/Y9ub5FPWPuqqfG+G2vuzBtGDINmXbQ88SPcgoZiXQZpEXETYFI1Jp1cmcqM/XZo5vKTbgaMJW7ctbD8h6f6hVBjxv6Ju23cnraqsTgQGGxI1BFfZPjKrsDaRutL1ie3r26Wl0nlIuq9kT+hm6qp8F5J+StjEXjQU3iU1iB4Ekh4BliuxLWmD5EJxie3TepzfBfhsaQ1YanvnLuq2ff9ImgvYxPZZubW0k3RPPGf77XQ8AzCv7SezCqtkRdLpwC9t35lbS6dR4qp8g6ac6PeJxbqaEz2lIOlyYNuS2xlLesT2koO9VpnySZ2mit62l3QcyeKvFSWltjSQdBewlu130/G0wM22V82rrJITSQ8DiwFPAW/SFSwtl1VYG5G0Un/XbY9tl5bKB6Na3A2AphfjW8A9kkbTPUgo6cU4VauTaet6WJu1ZEfS2sDBdOXJN14Ei+bUlYmDcwvoABrFtmsTHrANn+htiTSwEpm6EUAD2H43BdKVsilqhbUPfpZ+Tk8UqN9LvEOWI54lpTUvA0DS7MDidO8M3ZG1ZzWIHhiNF+MYwn2hZC6T9Ftgn6ZW1zMBvyC6OJbGycC+xNgorTtfN2xfL2lhYHHbV0uakcImVrZPB/h/9u472s6qWv/490kQqaEoICJNpEhHadKkiAoKKCBcROlF4SfYkKuICFYEvSIoCChNhCsCAhakQygSagihXBUEC4rSRDrJ8/tjrc3ZOTknORtlz/fknZ8xzkj2u3PGeDgke6+93rnmlPRRYAPbL9bHJwDjI7MF+rukrW1fCCBpG+AfwZlSMNsPSNqA8npxiqSFgHmic/WT7U0AJJ0HvMX2pPp4ZVq6KSFpL+BA4A2UQ+rrUmqkN43MNZws5+hR3UFZgbIzfW/3DksbSHoV8DVgN8ptOIAlgNOAz7Xw53Gj7XWiczSBpL2BfYAFbS8jaVngBNubBUfru3p+4m22H62PFwB+08Zyp9pL/UxgMcrr5p+AXWz/LjRYCiXpMMru6/K2l5P0euAc262bfCtpsu2VZnatDSRNAtaivF52htF81fa2wdGGlDvRPZC0JfB94PeUWy5LS9rX9q9ik/VPHZ7xaUmHUurZAH5v++nAWJGulHQUpWNJd4lPG2vZ9qecLL8RwPZvJS0cGynM14Hbap24gI1o6c6S7d8D60qapz5u7ZmSNI33A2sAtwLY/kvtUtFGkySdDPyoPt4ZaOUMCuBZ289KQtKrbd8jqbGbD7mI7s23gE06Oyh1h+UXlN6OrWL7GWBSdI4G6OxCr9l1zTT01tMr7Lla7wq8NL2wdbe66vmAeyl/Nzp/Pw62/de4VHEkLQJ8FXi97S1q54G32f5BcLQU63nblmR4qSywrXYDPkopYwC4Bjg+LE2sP0maH/gZcKmkxxi46904Wc7RA0k3dZ8or1OFJuQp85RA0jeAx4FdgI8B+wF32T4kNFiA0TYw4JVUuxqdAhxie7X64eq27BHcbpI+TTk8tjmlRHAP4Czb3wkN1meSxlKGMW0SnaVpaq/5+YCLm1oqmovoHkg6ntKF4SeUHbYPAA8ClwHYPi8uXYog6dXAdkw/6vqIqExR6g7snsA7KSUMvwZOHg0N8//TRtvAgFdSZ/Oh+4OFpNttrx6dLcWStDldrxe2Lw2OFKJ2/NrW9hPRWZqgfrBYhGnfUx+MSzS8LOfozRzA34DOJK6/Uyb1bUVZVLd2ES1pUeDRFg6iuQB4gtKdo23/7QBIWt72vbanAifVr85z6wPXhYWLsy/wSWCKpGfrtcYODHglSJqtdid5StJrqKU9ktal/JtJLVbP1ZzavXCWtI/tEwNjRfkXpS76UkrPbKB17XMBkPQx4DDKWmtqvWxK27/GyZ3o9B8h6TJgGeBc25+OztMvbR3x3U3SVOAMYP/Bh8Yk3Wp7hgMF0qyp8/9e0luB7wArA3cCCwHb227rwakESHqYshH1/2xfWa+18vVC0q5DXe+0zGwTSb8D1rH9SHSWkcid6B5IegNwLGWQApS+rwfa/lNcqmaw/Y5aI75idJY+u17SKp3+ni01mdK27FZJu9j+TddzCsoUTtLWlK4cAFfZ/nlkngACsH1LrW1cvl67t3b5Se32Z2Ab4BxJP7V9FC19vbB9Wm2fu1y91OZ/I39kFN2pyp3oHtRbLT+m7LoBfAjY2fbmcanijKa6pf+02t0rTWgAACAASURBVMvSlP/2ZYH7KOUcbRxd29lx3IhygOw04Mu2p7Z4Z+nrlF6nZ9ZLOwE32/5sXKr+kvQnSkejIdke9rk06+vUyEuag9KJYh5gFdsrBEfrO0kbU143/0B5D1kc2LWpU/peCZI+WX+7EuUD9y+Ytm1sI18vcie6NwvZPqXr8amSPh6WJtBoq1t6Bbw3OkDT2L6m3ro/HhgvaefoTIG2BFavdeJIOg24DWjNIpoyrXIeWrq7mGbqZgDbzwK7S9ofeGtspDDfBN5p+14AScsBZ9Gun0enR/iD9Wv2+tVouYjuzSOSPkT5yw1ld2lU1O28Ag6kTJpq5X+/7Zf6VkpaDdiwPhxve2JMqjAvLZJsPw7sVGv8rqUcvG2r+YFH6+/niwwS5KE2dqlJI2N770GPvwt8NyhOtFd1FtAAtv+vTgduDduHdz+WNK5c9pNBkUZkTHSAUWYPYAfgr8BDwPbA7qGJ4oyquqVXiqQDKbfsF65fP6q79G1y0uAL9UDMRsA5/Y/TCF+jTCw8te5C3wJ8JThTv+UOdJqOpJ/UXydJumPwV3S+IDdLOlnSxvXrJOpOfdtIWrOWS95B6Vgysd7hbKSsiU4vi6QfMIrqll4p9UX/bbafqo/nBm5oU010GiBpfdvX1f7hC1LqoqEMZWrVxEJJC9h+LDpHahZJr68jvpcc6vnuu3xtUV8v9gc2qJfGA99rYcvYznvq/rbH18cbUH4WjXxPzXKOHkhaCNib6Qdr7BGVKdCoqlt6BQmY0vV4Ci3dgav9f48F3kz5OzEW+JftNpUyfIdSx3hDPVB5YXCeSA92Rjoz8G+icxh3dtv5/tNOPwfeQjl8/OHoMJEkXW57M+AI2wczg4O4LTKls4AGsH2tpBcjA81Ivoj15gLKJ8TLmHbh1DqD65da7BTgRknn18fvA34QmCfSccB/UUo41qSM/15uht8x63lB0onAGyRNN764TcMTbM/b/VjSPJTdtn2B84f8ptQGs0v6ILCepG0HP9myyb+LSloP2FrS2QzagLF9a0ysUFdL+j7l7JmBHYGrJL0FmvczyXKOHuSoWpD0bdsfl3QRdQJZN9tbB8QKVf9xv3QbzvZtkXmiSLrZ9pqS7ujceuse9dwGkl4LvAM4EvjC4OdbOjxhfuDjlA9VPwb+p60HktNLt+d3ppwvGnynxm26sytpe2BPyvvH4Bpo2960/6liSbpyBk837meSi+geSPoycL3tX0ZniSLprV3DE6Zj++p+Z4ogacEZPP1cp0a6TSRdQ1lAnszA4dvdbK8WGiyApDUGf5iSNLvt56My9Vv9QPEpyk7SD4Fjbbf+MHIqJO1h+4fROZpA0qG2vxSdI/UuF9E9kPQkMDflIN0LDAzWGBcaLICkhW0/POja8t1temZlku6n7MR3337rPO6USf237TMHf++sqh4U+hulHvoTlLZu37P9u9BgASRdRfkA8Yf6eG3gpDZ9oJD0FGWs8ynAdG2q2nYIORWSlgWOogypugP4tO0/x6aKJWlP2z/oejwW+HwbyyYlzUeZQdGZ9no1pWa8kR/AcxGdXhZJ9wKH2u60K/oUsKftto39HlI9hHp1W34e9UX/dNttHrDyEknvAo6hHDRcDNgC2Ktp9XyvJElfZIiSr442LhASSBoPnA5cA2xN6W40XW10m0j6MaWv/J7AaygfPK+2/enQYAEknQvcSZngCPBhYLWm/h3JRfQISFrB9j2dwvbB2vTG2CFpUeBE4FnK6O+7gU/Z/ldosCCStgSutP2MpG1tnydpK9sXRWfrF0nXApu2qWRhRuoo30uBfwBrtK3FXUpDGXy2SNKttZNNq0nakTJs5ingg7avC44UYqizZ00+j5bdOUbmk8A+lNGcgxloVKF7P9h+SNLFlDHGUymlC61cQFdbAl+QdCuwLnBemxbQ1X3AdZIupLwRAO28bS/pUMrBqY2AVSmnyz9l+xexyfpP0hsorQ/Xr5fGAwfa/lNcqhRoDklrMFAKN2f345ZuSi1LmQJ8LqVF6IfroeynY5OFeEbSBravhdJ7H3gmONOwcic6vSySLgP+AhwALE5p63ZNW24/SVoHuM/237uufYHyQri/7bPDwgWRdNgQl93G0c+Svg181vYz9fGSwMm2N49N1n+SLqV05TijXvoQsHMbfxZp9HVf6AdJ9wD/z/ZlkkTZuNvD9krB0fpO0mqUcp/5KB+sHqWcL5kYGmwYuYgeAUlrAX/s3I6VtAuwHfAA8EXbj0bmiyDpfbZ/1vV4NsqioRUnjCVNBNbuTJSS9C3KEJ59gfNtbzCDb58lSfqA7XNmdq0tal9kWn6HZtTdnk2p3ySNs/3PQdeWs/1/UZmiSRoHMPjn0jS5iB6Beov+HbYflbQRcDbwMWB14M22tw8NmPpO0mTbK9UPD6dSbjfta3tqW2v8hvrvbuPPQtJ+wH9TOvmI0pniSNvfCw0WRNLllINSZ9VLOwG710ltKbWapIUpQ4g6u86TKV2N/haXKk4dgb4d00+GbuQdzayJHpmxXbvNOwIn2j4XOFfS7YG5wuSIZ66ti4PXAfMAG9UF9NtpcP3WK0HSFpSa8MUGTekbBzR2XOsrQdLngfWAjW3fV6+9EThG0oK2vxwaMMYelNeK/6GcIbke2D00UUoNUOt9f0zZiDm9Xn4rZQruzi09XHgB8ARwC6WdcKPlTvQISLoTWN32i7V2aR/b13Ses71ybML+k3QzQ4x4tv3Z0GB9VCdvPU/pjfxT4LX1qe3adDim1rCtDhzBtFP6nqR0LHksJFiA2vpxNdvPDro+JzDRdtvGoKeUhiHpN8BHhxjMtDrwfdvrxCSLM9rWVLkTPTJnUea5/4OyyzgeQNKbKJ+YWsn27ySNtT0FOEXSbZRuHa3QOT1crSVpoe6Dhm1RD3xMlPRj2y8ASFoAWLxNC+jKgxfQ9eIzkqZGBIoi6TO2vyHpWIboF237gIBYqaFq29RHO+dMWmLc4AU0gO3bJc0bEagBrpe0iu1J0UFGIhfRI2D7K/XW/aLAJR7Yvh9DqY1uo6clzQ7cLukblBHPY4IzhZC0HrV+qxysBtunz+h7ZlGXStqa8rpyC/CwpOttfyI4Vz/9WdJmti/vvihpU8q/kTa5u/56c2iKNFqcASwj6dy2dHkCJGmBwZsNkhakpe+nwAbAbipTgZ9jYDL0qrGxhpblHOllUY54BkDSGcAywO3AlHrZbdxlq31N15C0F2UX+jBJdzT1xe+VIGklSk3ftZQPElDKndYHtrE9OSpbSk1X27ut2JZ/J5L2AfYGPg10SgDfChwJ/ND296OyRalri+nYfqDfWUYiF9HpZZG0LfCLlt16m46kuykv+q3/hyRpEvBOyrjWQ2zf1LZFNICkOYAPMnDa/i7gzKHKPGZlkl5L6TrwGPBD4ChgQ+D3lOmmrfrAnYZWu1PM0Xls+8HAOH0n6b3AZyivF6a8XhzVtmFdnTZ/dRd+Ok1tJZyL6PSySDqFMqnxGuB/gYttt6oTA4Ckc4ADbLftVv10JH0AOBS41vZ+tSvFUba3C46WAki6hFLKMS+wGaXN3UWUhfTOtjeOS5ei1dKvbwKvBx4GlgTubuOAkQSSfm77vbWMwwxMtIRyd/eNQdFmKBfR6WWT9CpgC0rbvw2AS23vFZuqv+r0rdWBCXS147G9dVioBpG0lu2bonOk/pM00fZq9Rb9A7aX6Houh620XB1YtSlwWS0D2wT4kO09g6OlNGJ5sPDfUEdfvwB81/bPo/P0m+0XJP2K8qlxTuB9QKsW0cAXowM0jaQVKQM1dgIep9QEp/aZAmULqXY26taqTiVpSC/YfkTSGEljbF8p6dvRoVKMWgv9uO0n6uNNKGuKP1DWWM8HxhtWLqL/PbtQOnasGx2k3+qAjR2BjYGrgJOBHQIjhbB9taRFgLXqpQm2H47MFEHSUgwsnF+g3Jpd0/Yf4lKlYG+UdCHltmzn99THS8fFSg3xuKR5KCWBZ0p6GHgqOFOK8xPg/cATtU/2OcDXKHd6v0dDN+iynCO9LJLOotRC/6rNhwsl7UA5MHUVZXGwIXCQ7Z9G5uonSTdQphOeDZxt+7eS7redC6VK0mnA05QdlTuj8/RDnd45LNtX9ytLah5Jc1PmLowBdqZ0eDrT9iOhwRpA0jbAX23fGJ2lX7oPoUs6Gphq+zOSxgC3N/WAeu5E96B2Hxj8qeMJyuGZL7fpH7/tneoO7Oa1N3Ird2CBQ4C1Ov/tkhYCLqNMMGyLvwGLAYsACwG/ZYjhGi13HLAE8GHg4OAs/bIz8CtKzeuT0WFS4ywMPFS71pxWp3ouArTmfXQG1gFWkTSb7S2iw/RJ90HCTamD22xP7cxfaKLcie5BHSoyhTLrHsrY67mAvwIb2N4qKlu/1U4MR9PiHVgoH6xsr9L1eAxlvPMqM/i2WY6k+YBtKeUcywLzA++yPSE0WAojaR3KwePNgOeBSyhdfCaGBkuNIOlmYL1OrWsd3nWd7bVm/J1pViTpGEp57EPA1sBy9dzVosBFtht5tiYX0T2QdKvttwx1bfBialZXT1ZvPngH1vZqscn6S9JRwKqU0fBQ6sTvsN2W3cbp1L6vO1AW1EvYXjw4Ut/Vfw8HAysybQ/cTcNCBZL0GkoP8S2AVYDbKAvqn4QGS2GG6tDS6egSlSmSpJWZ/vWiNZNvaxefHSkL6Z/Y/nO9vgawsO1fR+YbTpZz9GaspLU7u2uS1gLG1ufa1iN5zKDyjUdo4ZhS2wfVwTMb1Esn2j4/MlO/SfosZUF0G0D9e3EccNxw06da4EzKmYH3AB8BdgX+HpooQL0zs31dLJ9Vv5D0VuDdkdlSuL9L2tr2hfBSHfDgLi6tIOkwyiH9FYFfUj5sXgu0ZhFdB5adPcT12wLijFjuRPegLpp/CMxDKWH4J+XE6GTgPW3aVRlmB3aS7c/Epeq/ejjmWdtTJC0PLE85bPlCcLS+kbQj5UV/NWAipQ72EtuPhQYLJOkW228ddFjmpjbeqpZ0c1NvxaY4kpahfNhcjHKG4k/ALm2cZFnPW60G3FZ7qy8C/Mj25sHR0kzkIvplqPWfdPoZttWgHdjxbduBhbJYotSDL0DZObgZeN72zqHBgtRbb++m3LofSzlkeXHbaqMl/cb2upJ+DXwH+AvwU9vLBEfrO0lfp+ww/i9dLcyaOsY39Vdtc4ftf0VniSJpgu216/vJJsCTlOmNKwRHSzORi+geSHo1sB2wFF2lMLaPiMrUb5LeBCxi+7pB1zegnLT+fUyyGF018R8D5rT9jZzGVkgaB2xOOWC4T3SefpL0XmA8sDhwLKUF4OGdW9dtUsf4DtbYMb6pP+pu61eB19veog5pepvtHwRH6ztJ3wM+R2lW8CngX5S2bruHBkszlYvoHki6mNLS7hbqNC4A298MC9Vnkn4OfNb2pEHXVwG+2qYOJQCSbgP2A/4H2NP25BYeMt12Rs/bPq9fWVJKo0OddnsKcEgtYZiNUs7QmtfOodTBVeNs3xEcpRGa3mM/Dxb25g22234YZpHBC2gA25PqP/62OZDSz/L8uoB+I3BlcKZ+63xwWhhYD7iiPt4EuB5o3SK6dufYm+nvWu0RlSmKpLmAT1I6tewjaVlgeds/D46WYr3W9k/qwWRsvyhpysy+aVYlaTHKpNfZ6uONbF8Tm6oRGt1jPxfRvble0ipDLSJbZP4ZPDdn31I0RH2Ru6br8X3AAXGJ+q9zy1HSJcCKth+qjxcFTg2MFukCSjnHZXTdtWqpUyh379arj/9MGembi+h2e6q2PjSApHUpd3pbR9KRlMP5dzHwemG63lvayvZNwE3AudFZhpKL6N5sAOxWa/yeo3TocFPHUb5Cbpa0t+2Tui9K2ovyRtkqkpYDPs30O45t7Ae8eGcBXf2NsoPQRnO1uVf4IMvY3lHSTgC2n1aTR5ClfvkkcCGwjKTrKNNOt4+NFOZ9lLszz0UHiVbfUw+ia1cemvuemovo3rRl/OaMfBw4X9LODCya1wRmB94flirOOcAJwMnkjuPltRtFd9vDywLzRPq5pC1t/zI6SAM8X0c6d3Ycl6FsQqQWs32rpLdT2oIKuLdNrUEHuQ94FfnvAgbeU09iFLyn5sHCEZA0zvY/JS041PNtbNUkaRNg5fpwsu0rZvTnZ1WdfsDROZpC0vuBjerDa9rY9hBA0pPA3JQ3xRcYuGs1LjRYAEnvBA6hDJK4BFgf2M32VZG5UjxJ6zH9XbzWDBjpkHQupU/05XQtpG23qjQQRt97ai6iR0DSz22/t5ZxmPKG2JGtmlpM0heBh4HzmfbFr1UfrCSNpXyYan1f0zql722D20C2Wa19XZfy2vkb262cTJcGSDoDWAa4na464JYuHHcd6rrt0/qdJUrXJuUBjKL31FxEp/RvyB64AyRdAHzM9oPRWaJJus32GtE5mkDS5cA3u0tbJJ3Ytt7haVqS7qYcRG71IqRuQFxme5PoLJGG2aTsaOx7atZEj4CkFWzfI+ktQzxt4FHbD/Q7V4pne+noDA2yADBZ0gSmnUy3dVykMJdL2g44r+2LBGBp4GBJa9k+vF7LMeDpTuB1wEMz+4OzMttTJE2VNF+bpyCP1vfS3IkeAUkn2d5b0nD9f18DTLT94X7mSs2QdX1FPSQ0HdtX9ztLtK6a6CnAM7S7JvpWYG3K+PPFgQ8BV9oealMitUR9P10dmMC0t+1b96G73sVbA7iUaTcg2ljasj9wpu3H6+MFgJ1sfy822dByEf0fIukS2++MzpH6K+v6plVH+a5VH06w/XBknhSvu7RF0m6UscYL2H5DaLAUKj90D8ia6AGSbre9+qBrjS2Py3KOEZC0qe0rhhtvbPu8XEC31ppkXR8AknYAjgKuouy8HivpINs/DQ0WoPZB3hlY2vaXJC0OLGp7QnC0CCd0fmP7VEmTgP0D86QGsH21pCWBZW1fVidbjo3OFcH2abUN5BK2743OE2ysJHXeU2vN+OzBmYaVO9EjIOlw24dJOmWIp93GUb6pkHQOcMCgISOtJGkisHln97mOvr7M9mqxyfpP0vHAVGBT22+utyQvsb3WTL51lpGtQdOMSNob2AdY0PYydRz8CbY3C47Wd5K2Ao4GZre9tKTVgSNaWtpyFGXQyvfrpX2BP9r+VFyq4eUiOqWXQdJFlEOl85J1fQBImmR7la7HYyhnBVaZwbfNkiTdavstg0oZJrbpA0W2Bk0zIul2Sq38jV3/Ria19PXiFmBT4Kqun8Wdtlee8XfOeur7xr5A58PUpcDJths5eCXLOXpQ6z2/Crze9haSVqT0g/1BcLTUf0dHB2igi4eYWNjWiX0v1NuQnVuSC1F2ptvk6/XXN9t+NjRJaqLnbD/fmQAvaTbqv5cWesH2E52fRdW21wsAbE+VdCpwxWgobRkTHWCUORX4NfD6+vj/KGOwU8vYvrrzBdxD2ZGeF7i7bQdjJL0awPZBlFtwq9avE20fHJkt0HcowwIWlvQV4FrKB/A2Oab+en1oitRUV0v6HDCnpM0p454vCs4UZbKkD1LqgZeVdCwt/XcjaWvKQf2L6+PVJV0Ym2p4Wc7RA0k32V5r0C3a6U6SpvYY4jDdhkCrDtN1lS6ckW0eB0hagXJLUsDltu8OjtRXkn4D3AG8Dzh78PNt7WCTinrbfk/gnZR/I7+m3LZv3aKkHqo8hGl/Fl9q4x2cYUpbGlvmk+UcvXmqjq/t3KJdF2htc/QElBe+tQYfpgNas4gGZq+7KOsN1cHG9nkBmUIMOkT3MAOlLUhasGWH6d4LvAN4F3BLcJbUEJKWt32v7anASfWr89z6wHVh4YLYfpryXnJIdJYGGKq0pbEfrHIR3ZtPAhcCy0i6DlgI2D42Ugo2ZlAv5EdoX5nURyjt3OYHthr0nIHWLKIpi8XOIbolgMfq7+cHHqRM72sF2/8Azpb0O9s3R+dJjXF37a+/v+1/DXruWKA1Q3i6DqgPqU0H1CVtWzdcpiltAQ6gwaUtuYjuge1ba4P45SlvjPfafiE4Voo1+DDdfwG/CszTd7avBa6VdHPbD9l2RtdKOgk43/Yv6+MtKGUNrVHbdv0QeFHSFGAH2419M0x9Mxn4E3CrpF1s/6brOQ3zPbOqzgH1bSkj0H9UH+8E/C0kUZzPUzZcPkbZkX+O8r76a+BLgblmKGuiR6g2hX/K9j9qGccGwO9s/yw4WgpWSxjWrw/Ht/XvhKQvAV/stCKSNA44xvbuscn6b6gavibX9b0SJN1BWTjfI2kd4Bu2h5xSl9qj6wzFRsApwGnAl2tXhlvbOA6+bkCsObNrs7LR+v8+d6JHQNKhwG6AJZ1NqfO7CniPpI1tZ4eOlpH0JAO34bp3T/aR9Czwe+AQ25f3PVycscAESbsDiwDHUW7PttFfJH2egZ2lnYG/BOaJ8KLtewBs3yhp3uhAqTlsXyPprcDxwHhJO0dnCjS3pDfavg9A0tLA3MGZ+m2F+sF7SLZX7WeYkcpF9MjsBLwZmItS1/g620/Xvpa3hyZLIWwPuyCo/YFXBs6sv7aC7c9Juhy4kVILvJHt3wXHirITcBilzR3ANfVamyws6ZPDPbb9rYBMKd5Lmw62Hwd2krQrpQ3knGGpYn0CuErSfZSfz5KUaY5tcj/Tn6lpvFxEj8yztp8Hnpf0+3qSFtsvSno+OFtqmFrOMLH2+myNenv2O8ARwCrAsZL2tN22HdjOSOsD6+6rhzhA1QYnUXqnD/c4tdNJgy/YPk3SeOAzAXnC2b64HqJboV66x/ZzM/qeWdDzth+IDtGrXESPzPy17lXAuK42XgLmi4uVmsz296Mz9NnRwAds3wUv1YpfwcAbQ2tIWgU4HViwPv4HsKvtO0OD9ZHtw6MzpOax/b1hrt9H6fTTOpJeRRl1vVG9dJWk77esccGobG2YBwtHQNIpM3q+jQenUhpM0tjOocKua6+x/UhUpiiSrqfUxF9ZH28MfNX2eqHBUmqIekD/WEqp5OyUMxX/st26jSlJJwOvohyyBPgwMMX2XnGp+quW9Myo3d/pfYwzYrkTPTInAr9p4ySllEZC0srAQZJWqpcmA0fbnhQYK9LcnQU0gO2rJLXtoFBKM3IcpSXoOcCawC7AcqGJ4qxle7Wux1dImhiWJsZwnUi2Bhaj3NlrnLYNhXi5dgFukXS2pN0kvS46UEpNIWkbygG6q4E96tfVwHn1uTa6T9KhkpaqX58H7osOlVKT1IPHY21PsX0K8O7oTEGmSFqm80DSG4EpM/jzsxzbH+t8UQas3AhsDPyGBg/gyXKOHkhaAdiCMsZ2PuBK4GLgusG3sVNqi7pjso3tPwy6vhRwwaAdllaQtABwOKWfPMB4Sg/tx+JSNUP9YPVX2zdGZ0lxJF1DaRd7MvBX4CFgt5a+XmxG6Znd3Z1j9+67WW1QO57tBnyasnj+mu17Q0PNRC6iXyZJcwKbUBbVb2tTU/SUukmabHulYZ67y/aK/c6UmkvSVyndW2azvUV0nhSjDjD7G6Ue+hOUjanvtbUtpqRXU6YhQ5mG3KruHJL2Bw4ELgeOHLwp01S5iO5R3WFanK56ctu3xiVKKVbdid7K9oODri8JXNTUJvmvBEkXzuh521v3K0tKTVV76Z9uu80DVjodjIZl+7x+ZYkmaSrwMPB3pj1gKEqb0Ea+j+TBwh7Usca7UW65TK2XDWwalSmlBjgMuKzuMN5Sr60J/DdwcFiqGG8D/gicRanp04z/eDvUg6crAnN0rjX1tH165dmeImlJSbPXGQxt9VPKwLbO0Lbu1wsDrVlEA0tHB3g5cie6B5LuBVZp+T/6lKYjaTXgU0B3d45v2m7VCfO6w7Y5ZTrhqsAvgLNsTw4NFkjSYZQDQisCv6SUwF1re/vIXCmWpNMp7e0uBJ7qXG/TJEtJ76N0KHkTcAHltaKV5SzdJC0CrFUfTrD9cGSeGclFdA8knQt8tMn/Q1NKzVBrHHcCjgIOt31ccKQQkiYBqwG32V6tvkH+yPbmwdFSoPrhajDbPqLvYYLV9pfbADsCr6H0mL86NlUMSTtQXjOvouzMbwgcZPunkbmGk+UcvfkacJukO4GXiv6zzjGl1FEXz++hLKCXooxCPz8yU7BnbE+V9KKkcZS6x8WjQ6Vwd9k+p/uCpA9EhQn2LPAE8E9KZ445ZvzHZ2mHUPpmPwwgaSHgMkrpS+PkIro3pwFHApMYqIlOKSXgpVvUK1PKFg5v05jvGbhZ0vzASZSa+X8BN8RGSg3wWcqglZldm2VJ2pRSzrE2ZaF4jO2bY1OFGzPobv8jNHimSZZz9EDSTbbXmvmfTCm1UT1h3qnvHOqE+bj+p2qO2jt8nO07gqOkIJK2ALYEdgD+t+upccCKttcOCRagvl7cAVxLeb2YZkFm+4CIXJEkHUU5T3JWvbQjcIftRh5Sz0V0DyR9i1LGcSHTlnNki7uUBpG0H2UX4VzbL0bnSTEkvR+4wvYT9fH8wMa2fxabLEWoh5BXB44AvtD11JPAlW0aSCRp1xk9b/u0fmVpEknbAevXh+NtN7YcLhfRPZA01PQg284WdykNUpvnrwAsmecG2kvS7bZXH3TtNttrRGVK8SS9yvYL9fcLAIvnHYo02mRN9AjV1lUX2v6f6CwpjQa2vxudITXCUPWM+d6TLpW0NeXvwi3Aw5Kut/2J4FwpgKRrbW8g6UlGUSlc7kT3QNKENtVrpdSL2pViO0pHiu6Jnq1rWZUGSPoh8DjQ+VC1P7Cg7d3CQqVwnbsRkvai7EIfJumOpk6mS2kojT3x2FDXSTpO0oaS3tL5ig6VUkNcQOl1+iLlcF3nK7Xbx4DnKYfIzqa089o/NFFqgtkkLUo5YPjz6DCpWSTNJWlNSa+NzjIjuRPdg6yJTml4ku60vXJ0jtRMkua2nR+qEvBST+hDKdMr95P0RuAo29sFRwvXxkPZtbTnO8CjC7FKZAAAIABJREFUwOcpd67+RrmzeXBTD1nmIjql9B8h6UTgWNuTorOk5pC0HnAyMI/tJWp3hn1t7xccLTWMpLVs3xSdI1obD2VLmgh8AJgPuBJY1fZ9khYGLre9SmjAYeQiukeS3gOsRNdEoaz5TAkk3QW8Cbif0gKycyAkaxxbTNKNwPaUg9lr1Gt51yIBIGlFynTPnYDHba8ZHCkF6O7YI2lS96K5yd188oR0DySdAMwFbELZWdkemBAaKqXm2CI6QGom23+U1H1pSlSWFK8O3eksnF+gjLpe0/Yf4lLFyUPZAIyprQ7HAFPr7zsvGo09v5eL6N6sZ3vVeoL4cEnfBH4VHSqlJrD9QL1Vv2G9NN72xMhMqRH+WEs6LOlVwIHA3cGZUhBJN1CmE54NbGf7t5Lub+sCuroAeILS6u+5mfzZWdV8QPfguu7fN7ZkIhfRvXmm/vq0pNdTCv8XDcyTUmNIOhDYGzivXvqRpBNtHxsYK8X7CHAMsBjwZ+ASsjtHm/2N8ndhEWAh4Lc0eJHUJ2+w/e7oEMGW7QzfGU2yJroHkg4FjgU2o5wcNXCy7UNDg6XUAJLuAN7W6cAgaW7ghqyJTil1kzQfsC2lnGNZYH7gXbZbWR6Zh7JB0s3An4CLgYtHy52JXES/TLWGaQ7bT0RnSakJJE0C1rL9bH08B3BTU09Vp/6QtBDlDsVSTFvvuUdUptQctfvCDpQF9RK2Fw+O1Hd5KLuotfLvrl+LAddSSmavtt3IMpdcRPeo1vYtxbRvBqeHBUqpISR9EtgVOJ/yJrANcKrtb4cGS6EkXQ+Mp9R7vnSg0Pa5YaFSGEmfpew03jbEc0vafiAgVihJSw51vY0/i456fmJDyoJ6Y+Dvtt8TGmoIuYjugaQzgGWA2xl4M7DtA+JSpdQcdYLnBvXh+KHeKFO7SLrd9urROVIzSNqR0slnNWAiZafxEtuPhQYLloeyQdJY4HTbOw/x3GK2/xwQa4ZyEd0DSXcDKzp/aClNR9IywJ9sPydpE2AVygvi48HRUiBJXwaut/3L6CypWSStQdlpfCcwFriMskvdqtroIQ5lvx9o5aFsSdcCm9p+PjrLSOQiugeSzgEOsP1QdJaUmkbS7cCalHKnXwAXAivZ3jIyV4ol6UlgbuD5+tWp9xwXGiw1iqRxwOaUA4b7ROfppzyUPUDS6cCbKe8fT3Wu2/5WWKgZyBZ3IyDpIkonjnmBuyRNoKuXY1vGcqY0E1NtvyhpW+A428dKynKOlrM9b3SG1Bz19WE4btsCuhLTDiCawsCgkbb5ff0aQ1lzNVouokfm6OgAKY0CL0jaCdgF2Kpee1VgntQAKqMKdwaWtv0lSYsDi7btln16See1YWFgPeCK+ngT4HoGShra5BTgRkndh7J/EBsphu3DASTNZfvp6Dwzk+UcPZL0OmBtys70Tbb/GhwppUaQtCJlsMYNts+StDSwg+0jg6OlQJKOB6ZS6hzfXMf5XmJ7reBoKZCkS4BdO+WRkhaldPN5V2yyGHkou5D0NsoHiHlsL1EPXO5re7/gaEPKRXQPJO0FfIHyyVnA24EjbP8wNFhKKTWUpFttv0XSbbbXqNcm2l4tOluKI+lu22/uejwGmNx9rS3yUPYASTcC2wMXdr1e3Gl75dhkQ8tyjt4cBKxh+xEASa+h3H7KRXRqPUnrA18ElqS8tnQOkL0xMlcK90JtXWV4afjK1NhIqQEul/Rr4Kz6eEdKd442OhdYU9KbgBMoh+p+DLTyULbtP5YqsJdMGe7PRstFdG8eAZ7sevxkvZZSKrfgPsGgoRqp9b5DGcCzsKSvUHaZPh8bKUWz/f8kvR/YqF460fb5kZkC5aHsAX+sQ+1cB64cCNwdnGlYWc7Rg9p6ZRXgAsquyjbAHfWrsS1YUuoHSTfaXic6R2oeSSsAm1HuTlxuu7FviumVV+9MTLa9QnSWJqglDN8GDgG2sn1/k0sYXkmSXgscA7yD8npxCXBgpwKgaXInujed1isdF9RfG9+GJaU+uFLSUZTT9d0tIG+Ni5SiSNoXOM32s7bvAe7peu5A28fEpUuRbE+RdK+kJWw/GJ2nAXanHMr+Sl1ALw2cEZwpypyDJxbWhg6NlDvRL4OkeQBs/ys6S0pNIenKIS7b9qZ9D5PCSXoGuA/Y2fbtg5671fZbYpKlJpB0DbAGMIFph2rk3IUWk/QicA6wh+1n6rXGvl7kTnQPJK1M+XS4YH38D2AX25NDg6XUALY3ic6QGuUe4GDgZ5KOs93db7+tgyTSgEOjAzRFHsqexiRgPHCdpA/Y/j0Nfr3IRXRvTgQ+aftKAEkbAydRGsan1GqSXg1sRxn7/dJri+0jojKlULZ9iaQ1gZMlbQF8qPYFzlugLWf7akmLAJ1+4RNsPxyZKVAeyh5g29+TNBG4SNLBNPj1Ykx0gFFm7s4CGsD2VcDccXFSapQLKIdtX6Tcnu18pRaz/Q/b76Pcor1R0nbRmVI8STtQSjk+AOxA+buxfWyqME/Y/pXth20/0vmKDhVEALavoxxG/gzQ2AOoWRPdgzqS81YGCv4/BLzV9vvjUqXUDG09TZ6G1j1cpevaCsCZwMq2Xx2TLDVB3WncvLP7XPuHX9bGITySvg6MJQ9lI2nRzhTL+ng2YD3b1wTGGlaWc/RmD+Bwyl90KHU7e8TFSalRrpe0iu1J0UFSI+w7+ILteyStSyn7Se02ZlD5xiO09+54pzXoml3XDLTmULakD9n+EbDToEErHbmIHu1sPwYcEJ0jpSaRNInygj8bsLuk+yi7KZ3DMatG5ksxbE/o/F7SAsCywBz10l9CQqUmuXiIiYW/DMwTJg9lAzBX/XVUtQzORXQPJC0HfJrpD0615tNiSkN4b3SA1FyS9qJMHXsDcDuwLnADLdplSwMkvdr2c7YPqhP6NqhPtXZiYR7KBmCZ+utdts8JTdKDrInuQa3hOoFBJ2ht3xIWKqUGkbQasGF9ON72xMg8KV69U7EW8Bvbq9e66K/a3jY4WgrQ6fkr6QzbH47O0wSSLgaeYPq1xTfDQvVZfZ1YFbilqT2hh5I70b150fbx0SFSaiJJBwJ7M3Bm4EeSTrR9bGCsFO9Z289K6uxC3iNp+ehQKczskj4IrFd3oqdh+7whvmdW9wbb744OEexi4DFgHkn/7LreKQscFxNrxnInugeSvgg8DJzPtCdoH43KlFJTSLoDeJvtp+rjuYEbsia63WpXo92Bj1NKOB4DXmV7y9BgKYSkDYCdKW3tLhz0tG237rC+pBOBY/NQNki6wPY20TlGKhfRPZB0/xCX2zpVKKVpdG7b2362Pp4DuMn2KrHJUlNIejswH3Cx7eej86Q4kva0/YPoHJEGHcpeFmj1oWxJ7wPeBNxh+5LoPCOR5Rw9sL10dIaUGuwUysCEzuGg91EmcaWWkjQWmGx7BShT6oIjpeZYStJY21MAJI0DjrG9e3CufspD2ZWk44EVgeuBL0tax/aXgmPNVC6iR0DSpravGKp+C1pbw5XSNGx/S9JVDJy23932bYGRUjDbUyTdK2kJ2w9G50mNMhaYIGl3YBHgOKBV5ydsP9D5fR7KZkNgtfqaMRdlDkcuomcRbweuALYa4jkzcJAqpdaRtGDXwz/Ur85zc3dqpFNrLQBMljSBrjHwtreOi5Si2f6cpMuBGyl18hvZ/l1wrBB5KBuA5zt3JWw/rWEmrjRN1kSnlP4t9ayAKXV8HZ3HnQ/q/237zH5nS/FqHfR0srSj3SRtBBwP/AhYhfJha0/brRvEk4eyQdLTQOdDlCh9o39Hw+vDcyd6BCRtRSl0f6A+/gKlMfoDwIG2hzpwmFIrzOysgKSFgKuBXES305a2D+6+IOlIyt+J1F5HAx+wfRdALZe8AlghNFUM0dUfuv5+VOzE/ge9OTrAy5E70SNQPyWuW28xvBf4FrATsAblReBdoQFTahBJWwJX2n5G0ra2z5O0le2LorOl/usM1xh07Y6m7iyl/ug+VNh17TW2H4nKFEXSJ4FdKe1zoRzKPtX2t+NSpZHIRfQISJpoe7X6+x8C99o+sj6e7g0ipTaTdBywJnAr5cNn/vtoIUkfBfZj4LZsx7zAdbY/FBIshZO0MnAQsFK9NBk4us19kiW9hYFD2ePzUPbokIvoEag70esBTwP3A9vZvrk+d5ftFSPzpRRJ0jrAfbb/3nXtC8CBwP62zw4Ll8JImo9S5/o14L+7nnoyB1S1l6RtKKUcXwNurpfXBD4LfNr2BVHZ+m3QoezBnstD2c2Xi+gRkLQH8Dngn8DDnfGcktagfHreLDJfSpEkTQTWtv1cffwtYClgX+B82xvM4NvTLE7SMsCfbD8naWNgVeB024/HJksR6uvFNrb/MOj6UsAFnbu+bZCHske/XESPkKTFgIWBiban1muLUsbXZv/T1FqSJtteSdJswKnAM8C+tqdmuVOSdDtlp3Ep4JfABcBKOfa7nTqvF8M8l3d2u3QOZbf5ZyLpNEoVwHdt3xmdZ7Ax0QFGC9t/tn1bZwFdrz2UC+iUuLb2e51IaZj/5bqAfjtlQZ3abartF4FtgWNtHwQsGpwpxXlR0hKDL0paEngxIE9jSNpS0pz199vWErmDZ/Jts7rjgMuAD0cHGUruRKeU/m2SNgCeB/4G/BR4bX1qO9u3hgVL4STdCHwbOATYyvb9ku60vXJwtBRA0vuAbwBfBW6pl9ek1M0fbPtnUdmi5aHs0ScX0Sml/zhJC3UfNEztJWlF4COU4RFnSVoa2KHT4Si1Tx1x/Smm7c7xzbaNus5D2dOrJSwHAysCc3Su2940LNQM5LCVlNJ/jKT1KLWvs3Wmtto+PTJTilWHaRzQdelFYOowfzy1QF0s7xKdowFOBNbuPOg6lL0CpWd06xbRlKFc/wu8h/Lhe1egsRsyuYj+N0i6u/72u7aPCw2TUjBJZ1B6At/OwPQtA7mIbrm6u/QBypCq1zMwVCKlNputdq3pPpS9fT1TMldstDCvsf0DSQfavhq4WtJN0aGGk4vof4PtN0t6DbBudJaUGmBNYEVnjVgCJM1LOUz4QWA54DxgadtvCA2WUnN0DmW/DpgH2CgPZfNC/fUhSe8B/gLMqJ92qKyJ7pGkRYC16sMJth+OzJNSU0g6BzjA9kPRWVI8Sc8AE4DPA9fatqT7bL8xOFpKjZGHsqcl6b3AeGBx4FhgHHC47QtDgw0jF9E9kLQDcBRwFaUZ+obAQbZ/GpkrpSaQdCWwOmXh9Fznuu2tw0KlMJI+DvwXMDdwFqXO8dJcRKehSNoPeAQ4t7ZEbKU8lD265CK6B3XS0uad3eda53dZmyYspTScegtyOrWuLbWUpDdSFtM7AcsCh1EmWf5faLDUKJL2pxyoW7KNH7y7D2V3rrXxUHYdrnJgZ6KppAUonVv2iE02tFxE90DSJNurdD0eQ5lguMoMvi2l1shypzQjklamLKZ3tP2m6DwpNcFwh7JtHzD8d82aJN1me42ZXWuKXET3QNJRwKqUW5MAOwJ32G77RKGUstwpTUPSr4GLgV/Zvic6T2qeenBsJabtB3xEXKIYtdNXHsrmpTv+G9t+rD5ekDL6vJGblbmI7pGk7YD168PxtrNVU0pkuVOalqTXAe+uX8sBN1IW1ZfZfioyW4on6QRgLmAT4GRge8rdqz1DgwXIQ9kDJO0CfA44p176APAV22fEpRpeLqJTSv8RWe6UhlP/LqwDbAFsRmnfdYntb4QGS2Ek3WF71a5f56HctdgwOlu/5aHsadUpp50JhVfUgU2NlH2ieyBpW+BIYGHK7WpR6pbGhQZLqRkurrfwu8udfhmYJzWE7anADfXrC5JeC7wrNlUK1umD/LSk11M6cywamCfSF6MDNMyCwFO2T5G0kKSlbd8fHWoouRPdA0m/A7ayffdM/3BKLVQ/aG5QH2a5U4tJOpYysXJIbTw0lQZIOpTSB3gz4LuUvysn2z40NFiQPJRdSDqMMrhredvL1Q9Y59hefybfGiIX0T2QdF1T/0emFE3S3MCztqdIWh5YnnJ79oWZfGuaBUnatf52fWBFSp9oKDWOd9n+SEiw1DiSXg3MYfuJ6CwR8lD2AEm3A2sAt3Y6cnRKfmKTDS0X0T2QdAxlPOfPmLZu6bywUCk1hKRbKC/+CwDXAjcDz9veOTRYCiXpN8AGnQEakl5FuUuxbmyyFC17Ixd5KHuApAm215Z0q+231M2ZG5q6iM6a6N6MA54G3tl1zUAuolMqH8qflrQncLztb9RdhdRuC1BeOx+tj+ep11KLDdcbGWjdIhoYM6h84xFgTFSYYD+R9H1gfkl7A3sAJwVnGlYuontge/foDCk1mCS9DdgZ6LSpGhuYJzXD14HbagcCARuRB6lSqXvN3shFHsqubB8taXPgn5SSwC/YvjQ41rCynGMEJH2m7qoNeVAmD8ikBJI2Aj4NXGf7yDru+eP576O9amu7dYH7KC3uAG60/de4VKkJsjfytPJQ9uiUi+gRkLSV7Yu6DspMw/Zp/c6UUkqjQZNH9qY42Rt5QB7KHjDaWgnnIvplkrQA8HjeikqpkLQcZSd6KaY9KLTpcN+TZn2Sjqb0hz4vXy9Th6S3D3Xd9tX9zhItD2UPGG2thHMRPQKSvgD8xPY9tRXPryifoF8EPmj7stCAKTVAPWF+AnALAweFsH1LWKgUTtKTwNyUvxPP1suN3VlKrzxJY4HJtleIztIEXZ0oPgbM2TmUbXv16Gz9NtpaCefBwpHZEfhS/f2ulNsLCwHLAacBuYhOCV60fXx0iNQstueNzpCapZYt3CtpCdsPRudpgDyUPeBmSf/LKGklnIvokXm+6zbku4CzbU8B7paUP8OUiosk7Qecz7Qvfo8O/y2pDSRtTenKAXCV7Z9H5kmNsAAwWdIE4KnOxTbWRAMHAp8Fzrc9uR7KvjI4U5RR1Uo4yzlGoA4L2Av4G3Av8NbOHHdJ9+QtqZRA0v1DXLbtN/Y9TGoMSV+njDM+s17aCbjZ9mfjUqVoWROdZgW5iB4BSetQyjYWAr5t+0v1+pbAh23vFJkvpZSaStIdwOq2p9bHY4HbmjqBLPWPpCWBZW1fJmkuYKztJ6Nz9Vseyh5QfxbHA4vYXlnSqsDWtr8cHG1IuYhOKf3H5BjfNFhdRG/cKeuRtCClpCMX0S1Wp9HtAyxoexlJywIn2N4sOFrf5aHsAZKuBg4Cvt9pjSnpTtsrxyYbWtbz9qB25tiO6RcJR0RlSqkpcoxvGsbXmH5i4X/HRkoNsD+wNnAjgO3fSlo4NlKYPJQ9YC7bEyR1X3sxKszM5CK6NxcAT1A+LT43kz+bUtvkGN/0Eknr276OciDoKkpdNMDBObEwAc/Zfr6zWKqH9Nv62pGHsgf8Q9Iy1L8LkrYHGjvVMss5etDkWwopRcsxvqmbpFtsv7XTAzc6T2oWSd8AHgd2AT4G7AfcZfuQ0GAB8lD2gNqZ5ERgPeAx4H7gQ7b/EJlrOLmI7oGkE4FjbU+KzpJSU0i6iLJrMC85xjdVtavRHcD7gLMHP2/7gL6HSo0haQylJ/I7KWU+vwZOzjtZCV4ahT6m6QdNcxHdA0l3AW+ifDJ6joGZ7nlAJrXWcK2qOrJlVTtJei3wDuBI4AuDn7d9Wt9DpdRQbT+ULekG4BDbVwzx3OVNPXCai+ge1HY807H9QL+zpNREkhZhoPZ1gu2HI/OkeJLWsH3boGuz234+KlOKI2kSM6h9buOm1HCHstt0t0bSnylnzn4JfNb2C13P3dbp1NE0ebCwB53Fcj1BPEdwnJQaRdIOwFGUQ2QCjpV0kO2fhgZL0f5H0m6dmkZJawMnAauFpkpR3lt/3b/+ekb99UO092BhHsouw+w2AL4D3ChpJ9v31uca+3PJnege1NG13wReDzwMLAncbXul0GApNUDtdbp5Z/dZ0kLAZbZzsdRikt4FHEN5c1wM2ALYy/atocFSqKF2F9t6CDUPZU/7/17StsC3ga/aPiF3omcdXwLWpSwM1pC0CeXTc0qpHALpLt94BBgTFSY1g+1fS/oIcCnwD2CNbHGXAHW1QezUBLfq9WLQoey7JOWhbMD2eZJuBE6tk6Hnic40nFxE9+YF249IGiNpjO0rJX07OlRKDXGxpF8DZ9XH/wX8KjBPagBJhwI7UIasrApcJelTtn8RmywF2xP4oaT5KOVfjwF7xEbqu6OjAzTINOdnbP8Z2FzSQZQOLo2U5Rw9kHQZpV3T14DXUv6nr2V7vdBgKTVEvQ23fn043vbPIvOkeHWj4bO2n6mPl6S0Mts8NllqgrqIxvYT0Vki5aHs0SkX0T2ofQufodxy2hmYDzjT9iOhwVIKJOlJBg5+aNDTzwK/p7QuuryvwVJjSJoHwPa/orOkZqiL58ModygArgaOaONieohD2RsCrTyULWkOyl2Klehq4GC7kXcpWlV/9HJJelOt3XrK9lTbL9Yep7cC80fnSymS7Xltj6tf83Z/Aa8D9qUcLEstI2k/SQ8CDwAPSnqgjjdO6YfAk5RSnx2AfwKnhCaKcwjlrvautncB1gYODc4U5QzK+8a7KB+s3kD5e9JIuYgemW9T/oEP9kR9LqU0BNtTbE8Ejo3OkvpL0ucp7cw2tv0a2wsCmwBb1OdSuy1j+zDb99Wvw4HWjbmu8lD2gDfZPhR4qm5WvgdYJzjTsPJg4cgsMtSob9uTJC3V/zgpjS62vx+dIfXdh4HVbD/buWD7vnrreiLw5bBkqQmekbSB7WsBJK1PKZdsozyUPaAzZOVxSSsDfwUWDswzQ7mIHpkZlWzM2bcUKaU0erh7Ad118RlJUyMCpUb5KHBaV3eOR4HdQhMFsX3QoEPZJ7T4UPaJkhYAPg9cSGlv19jSllxEj8zNkva2fVL3RUl7AbcEZUoppSb7s6TNBh8olbQp0NqhEqmwfTuwmqRx9fFQJZOztBkcyt5HUusOZUsaA/zT9mPANYyC8p7szjECtfXM+cDzDCya1wRmB96fgwNSSmlaklYCLgCuZdrXzfWBbWxPjsqW4kj65Iyet/2tfmVpMkljgZUpHcBWjs7TL5Jutr1mdI6RykV0D+qEws5f5sm2r/j/7d15kGZVmefx768Q2RdRFrEVUKcXVhdQEUXAHRtQURBxCbfpnm6VHqMVnXZ6WmgXtF3R0NYmsNUKxAWEVkRa9hZlKaFYxYUSRkEYC1kELaB45o97E9IyMyszJO+5ZX4/EW/ke87NrPxVxY2oJ08+95yWeSRpzPrtql5Ot10VwJV0RcHvtXloYehbeS6h6/ldwSrbYvYPGKqX5K8W0jMlSd5Hd7Lp8cAdE/NVdXOzUDOwiJYkSYNIsgtwCPA8ut9QHAecXhYjApIsm2K6qmqUrR0W0ZIkaXBJnkpXUD8LOLyqTm4cSY0lWXfV31RNNTcWC3UfQkmS1EiSzYHHAzsBPwM85loA581ybhTcnUOSJA0iyWvpTihcF/gKcNAqB41oAUqyFfAIYL0kj+f+XvmNgfWbBVsN2zkkSYNJ8u/AncAnqury1nk0rP7BwsvpjoKH+7d46wZV+w8eSs0leTXdPuG7AhdyfxF9O/DZqjqhUbQZWURLkgaTZDfgUcCTqurw1nk0rCTPmOl6VZ09VBaNT5IDq+qrrXPMlkW0JEmSmktyGHAs3Qr0Z4AnAG+vqtOaBpuGRbQkad70D5AdDmxP1wcLQFXt0yyUpFFKsrSqdknyXOCv6Y7//nxVPaFxtCm5O4ckaT4tBq4CtgPeBfyUrudRklY10Qu9L/C5/mTTzPD5TVlES5Lm00Or6hjg7qo6u6peC7gKLWkqS5KcRldEfyvJRsC9jTNNyy3uJEnz6e7+4w1JXgBcD2zWMI9GKMl7gFuBf6uq5a3zqJnXAY8DrqmqO5NsRrdrxyjZEy1JmjdJ/hI4F3gkcDTdvq/v8nQ6TZbkhcBjgF2q6lWt86i9JI8BXg68rKp2aJ1nKhbRkiRJai7J1sDBdMXzTsB7gROq6rKmwaZhES1Jmjf97hxvALZlUgth3xutBcr7QpMl+e/AIXSnFn6pf51UVds1DbYa9kRLkubTSXTtHN8GVjbOovHwvtBkHwe+C7y8qi4CSDL6VV6LaEnSfFrfkwk1Be8LTfZw4KXAB5NsRbcSvXbbSKvnFneSpPn09ST7tg6h0fG+0H2qanlVfaqqngE8E7gFuDHJVf3OLaNkT7Qkad4kuR3YAFhBt91dgKqqjZsGU1OT7ou7uH8bRO+LBSrJ1lV1/RTzf0q3O8cRDWKtlkW0JGleJFkE7F5V32mdRdJ4JTmFbv/4s4BTgf+qqnuahpoFi2hJ0rxJcnFVPb51Do1Pkv2BPfvhWVX19ZZ51FaSdYG9gOcDewDX0RXUp1bVdQ2jTcsiWpI0b5L8C91T9yeU/+Gol+R9wG7A4n7qEOCiqnpHu1QakyTb0RXUzwO2qqonNY70eyyiJUnzZlLv60rgN9gTLSDJpcDjqurefrwWcHFV7dw2mcYoyYOr6q7WOVblFneSpHlTVRu1zqDR2hS4uX+/Scsgaqv/YXu6Vd2qqlHeHxbRkqR5kyTAocB2VXVkkkcCD6+qCxpHU1vvBS5Ocibdbyf2BN7eNpJamfhhO8mRwA3A5+nui0Pp9pAeJds5JEnzJskngXuBfarqL5I8BDitqnZrHE2NJXk4XV80wAVV9YuWedRekqVVtcvq5sbCw1YkSfPpyVX1t8BvAarqV8CD20ZSa0n2AG6rqpOBjYG3JdmmcSy1d0eSQ5OslWRRkkOBO1qHmo5FtCRpPt3dPzRWAEk2p1uZ1sL2SeDOJLsAbwF+AnyubSSNwMuBg4Ab+9dL+7lRsidakjSfPgacCGyR5N3AS4B3to2kEbinqirJAcAnquqYJK9rHUrt9D9sv7GqDmidZbYsoiVJ86aqFidZAjyT7kGhF1bVVY1jqb3bk7wDeAWwZ3+65dqNM6nv8IbNAAAV/ElEQVShqlqZ5Gmtc8yFDxZKkh5wSTab6XpV3TzTdf1xS7IV3a/pL6yqc5M8CtirqmzpWMD6B5EfAXyZSb3QVXVCs1AzsIiWJD3gkiyj64MO8CjgV/37TYHrqmq7hvEkjVCSY6eYrqp67eBhZsEiWpI0b5J8Bjixqk7px8+na+n4q7bJ1FKSFwNHAVvQ/XDlSZZa41hES5LmTZLLqmqn1c1pYUnyY2A/++M1WZI/AY4G9uinzgUOq6qftUs1Pbe4kyTNp+uTvDPJtv3rH4DrW4dSczdaQGsKxwInA1v3r//o50bJlWhJ0rzpHzD8P3THOgOcA7zLBwsXtiQfBbYCvgasmJgf6wNkGkaSS6rqcaubGwu3uJMkzZu+WD4syUbdsH7dOpNGYWPgTuA5k+YKsIhe2JYneQVwXD8+BFjeMM+MXImWJM2bJDvRnUQ3seXdL4FXV9Xl7VJJGqP+6Pejgd3pfqg6D3hzVV3XNNg0XImWJM2nfwXeUlVnAiTZC/g08NSWodRWf/z7G4BtmVSLjHUrM82vJEdV1eHAk6pq/9Z5ZsuVaEnSvEmytKp2Wd2cFpYk59HtvLAEWDkxX1VfbRZKzSS5DNgZWFJVT2idZ7ZciZYkzadrkvxv4PP9+BXANQ3zaBzW71ceJYBT6Q5k2jDJbfT7hjPy/cNdiZYkzZskDwHeBTytnzoX+Keq+lW7VGotyT8D500cwiMBJDmpqg5onWO2LKIlSdIgktzO/SuMGwB3AXf3l0e74qhhJNm+qq5cZW6vqjqrUaQZWURLkh5wSU6e6fqa9PCQpGEkuZyu9ev9wLr9x12ravemwaZhT7QkaT7sDvxfuv1ez6dbeZTuk2R/7j+E56yq+nrLPBqFJwNH0W1ttxGwmPuPAB8di2hJ0nzYCng23WEJLwe+ARxXVVc0TaVRSPI+YDe6Igm6A3n2qKp3NIyl9u4GfgOsR7cSvayq7m0baXq2c0iS5lWSdeiK6Q/QHfn98caR1FiSS4HHTRRISdYCLq6qndsmU0tJlgInAUcCDwM+BdxVVS9tGmwarkRLkuZFXzy/gK6A3hb4GHBiy0walU2Bm/v3m7QMotF4XVVd1L+/ATggyStbBpqJK9GSpAdcks8BOwKnAF/0mG9NluQQ4H3AmXT98nsCb6+q45sGU1NJ9gZ26IdXTJx0OlYW0ZKkB1ySe4E7+uHk/2hGfXiChpPk4XR90QAXVNUvWuZRO0keAZwA/JbuFEuAJ9L1Rr+oqn7eKttMLKIlSdIgksx0pPMK4Lqqun2oPBqHJCcCJ1XVZ1eZfxVw4FgPYLGIliRJg0gy06/nHwQ8CvhEVb1/oEgagSRXV9WfzfVaaz5YKEmSBlFVe890vX8Y9WK6Qza0cCyaajLJImCtgbPM2pShJUmS5luSv0mydf/+76pqBTDa3Rg0b76e5DNJNpiY6N9/iu7h5FGyiJYkSa2sD3w+ySnA8wGqasnMX6I/Qm8DbgWuTbIkyRLgp8BtwN+3DDYTe6IlSdIgkhwAXFhV1/fjAJ8Engl8oKo+3TKf2kqyHvDYfviTqrqzZZ7VsYiWJEmDmHxSYZK1geOAnwOHA2dV1VOaBpTmwHYOSZI0lLUBkmwCnEp31PdhVfVbuj2BpTWGu3NIkqShHA/8ANgIuBE4u2/peCVwU8tg0lzZziFJkgaT5E+Ae+gOVzkGeBawFHh1VV3TMpvGpT/V8uZ+15bRsYiWJEnS6CT5NvAY4KtVNbpdOiyiJUnSoPpDVQ4EtmVSa2lVHdEqk8apb/fZvqquaJ1lVfZES5KkoZ1Ety/wErq2Duk+SbYA1p0Yj7GABleiJUnSwJJcXlU7ts6hcUmyP/BBYGu6B023Aa6qqh2aBpuGW9xJkqShnZdkp9YhNDpHAk8BflhV29EdwvO9tpGmZxEtSZKG9jRgSZKrk1ya5LL+IBYtbHdX1XJgUZJFVXUmsGvrUNOxJ1qSJA3t+a0DaJRuSbIhcA6wOMlNwB2NM03LnmhJkjS4JLsAT++H51bV0pZ51F6SDYDfAgEOBTYBFver06NjES1JkgaV5DDgDcAJ/dSLgE9X1dHtUklzYxEtSZIG1fc/715Vd/TjDYDvVtXObZOppSQvBo4CtqBbjQ5QVbVx02DTsCdakiQNLcDKSeOV/ZwWtvcD+1XVVa2DzIZFtCRJGtqxwPlJTqQrng8AjmkbSSNw45pSQIPtHJIkqYEkT6Db6g66BwsvbplH7SX5KLAV8DUmnWRZVSdM+0UNuRItSZIGleQxwBVV9f0kewNPT7Ksqm5pnU1NbQzcCTxn0lxx/wOoo+JKtCRJGlSSS+gO0dgW+AZwMrBDVe3bMpfaSbIWcFRV/X3rLLPliYWSJGlo91bVPcCLgY9X1VuBhzfOpIaqaiWwR+scc2E7hyRJGtrdSQ4BXgXs18+t3TCPxuGSJCcDX2bSSYX2REuSJHVeA/w18O6qWpZkO+DzjTOpvXWB5cA+k+bsiZYkSZL+WNgTLUmSBpVkjyT/meSHSa5JsizJNa1zqa0kf5rk9CSX9+Odk7yzda7puBItSZIGleQHwP8EljDp5MKqWt4slJpLcjbwVuBfq+rx/dzlVbVj22RTsydakiQN7daq+mbrEBqd9avqguR3ToC/p1WY1bGIliRJQzszyQfoHhibfDLd99tF0gj8sj+IpwCSvAS4oW2k6dnOIUmSBpXkzCmmq6r2mWJeC0SSRwOfBp4K/ApYBryiqn7aMtd0LKIlSZI0Gkk2ABZV1e2ts8zEIlqSJA0qyTrAgXTHft/XWlpVR7TKpHaSvGWm61X1oaGyzIU90ZIkaWgnAbfS7c6xYjWfqz9+G/Uf/wzYDTi5H+8HXNAk0Sy4Ei1JkgY15m3L1E6Sc4AXTLRxJNkI+EZV7dk22dQ8bEWSJA3tvCQ7tQ6h0dkSuGvS+K5+bpRs55AkSYNIchnd9mUPAl7Tn1K4Agjd7hw7t8yn5j4HXJDkRLp74gDgs00TzcB2DkmSNIgk28x0vaquHSqLxinJE4Cn0/2wdW5VXdw40rRciZYkSYOYXCQn2YWuWIKuWFraJpVGZiVwL10RfW/jLDOyJ1qSJA0qyWHAYmCL/vWFJG9qm0qtTbovHsYacF/YziFJkgaV5FJg96q6ox9vAHzXnuiFbU27L1yJliRJQwvdr+0nrOzntLCtUfeFPdGSJGloxwLn97swALwQOKZhHo3DGnVf2M4hSZIG1+/C8LR+OOpdGDScNem+sIiWJEmDSLLZDJdXTPTCamFZzX1BVd08VJa5sIiWJEmDSLKMbuuyiT7XiSIk3N9i+vaqWjx0NrWT5F7gZ8A9E1OTLldVPXr4VKtnES1JkkYhyebA2VW1fessGk6SjwB7A98BjgP+q9aAAtUiWpIkjUaS/arqP1rn0LCSBNgLOAR4EnAa8MmqWtYy10wsoiVJkjQKSTYFXgYcCfyvqvpM40jTcos7SZIkNdMfqnIAcDCwOXAC8MSquq5psNVwJVqSJEnNJLkD+BHwxf7j7xSnVXVCi1yrYxEtSZKaSnJV//YTVfXxpmE0uCSfZZXCeZKqqtcOGGfWLKIlSVJzSR4KPKWqvtE6izQbFtGSJGlwSbYEduuHF1TVTS3zSHO1qHUASZK0sCQ5CLgAeClwEHB+kpe0TSXNjSvRkiRpUEmWAs+eWH3uD1n5dlXt0jaZNHuuREuSpKEtWqV9YznWJFpFkl2TbN06x3TcJ1qSJA3t1CTfojviGbr9gU9pmEfj9CZg5yQ/rKqDW4dZle0ckiRpcEkOBPboh+dW1Ykt82i8kmxUVbe3zrEqi2hJkiSNQpJHANswqVuiqs5pl2h6tnNIkqRBJXkxcBSwBZD+VVW1cdNgairJUXStPVcCK/vpAkZZRLsSLUmSBpXkx8B+VXXVaj9ZC0aSq4Gdq2pF6yyz4ZOwkiRpaDdaQGsK1wBrtw4xW7ZzSJKkoV2U5Hjga8B9q45VdUK7SBqBO4FLkpzO794Xb24XaXoW0ZIkaWgb0xVMz5k0V4BF9MJ2cv9aI9gTLUmSJM2RK9GSJGkQSd5WVe9PcjTdyvPvGOuv7TW/knypqg5KchlT3xc7N4i1WhbRkiRpKBMPE17UNIXG5rD+4182TTFHtnNIkqRmkjwEuKUsSBa8JNtX1ZWrzO1VVWc1ijQjt7iTJEmDSPKPSf68f79OkjOAnwA3JnlW23QagS8lOTyd9fq2n/e2DjUdi2hJkjSUg4Gr+/evpjupcHPgGcB7WoXSaDwZeCRwHnAhcD2wR9NEM7CIliRJQ7lrUtvGc4EvVtXK/uAVn9PS3cBvgPWAdYFlVXVv20jTs4iWJElDWZFkxySbA3sDp026tn6jTBqPC+mK6N2ApwOHJPly20jT86c+SZI0lMOAr9C1cHy4qpYBJNkXuLhlMI3C66pqYueWG4ADkryyZaCZuDuHJEmSRiPJFnTtHABU1XUN40zLlWhJkjSoJOsABwLbMqkWqaojWmVSe0n2Az4EbA3cBGxDt7f4Di1zTceeaEmSNLSTgAOAe4A7Jr20sP0z8BTgh1W1HfBM4HttI03PlWhJkjS0P6mq57UOodG5u6qWJ1mUZFFVnZnkI61DTcciWpIkDe28JDtV1WWtg2hUbkmyIXAOsDjJTYz4NxQ+WChJkgaV5ErgscAyYAXdoStVVTs3DaamkmxAt8XdIuBQYBNgcVUtbxpsGhbRkiRpUEm2mWq+qq4dOovGI8lbgOOr6uets8yGDxZKkqRBVdW1fcH8G6AmvbSwbQScluTcJG9MsmXrQDNxJVqSJA0qyf7AB1llK7OqGuVWZhpWkp2Bg+m2QfxZVT2rcaQpuRItSZKGdiRr0FZmGtxNwC+A5cAWjbNMyyJakiQN7e7+YbH7tjIDdm0dSm0l+ZskZwGnAw8F3jDmh03d4k6SJA1tjdrKTIN5JPB3VXVJ6yCzYU+0JEka1Jq2lZmGk2QX4On98NyqWtoyz0xs55AkSYNI8tgke1TVHVV1b1XdU1X/Dnwf2LR1PrWV5M3AYro+6C2ALyR5U9tU03MlWpIkDSLJ14F3rHpSYZKdgPdU1X5tkmkMklwK7F5Vd/TjDYDvjrUv2pVoSZI0lC2nOuq7n9t2+DgamQArJ41X9nOj5IOFkiRpKDO1bKw3WAqN1bHA+UlO7McvBI5pmGdGtnNIkqRBJDkOOKOqPrPK/OuBZ1fVwW2SaSySPAF4Wj88t6oubplnJhbRkiRpEP0xzicCdwFL+uldgQcDL6qqX7TKpnaS7AY8rKq+ucr8vsCNVbVk6q9syyJakiQNKsnewI798IqqOqNlHrWV5AzgNVV17Srz2wDHVtU+bZLNzCJakiRJzSS5sKp2m+bape7OIUmSJP2+h8xwbf3BUsyRRbQkSZJa+naSdye5bzu7dI4ARtvqYzuHJEmSmukPVfk34EnAJf30LsBFwOur6tetss3EIlqSJEnNJXk0sEM/vKKqrmmZZ3UsoiVJkqQ5sidakiRJmiOLaEmSJGmOLKIlSZKkObKIliRJ0ugkuap/vbF1lqk8qHUASZIkaVVV9RdJHgo8pXWWqbg7hyRJkkYhyZbAxBHgF1TVTS3zzMR2DkmSJDWX5CDgAuClwEHA+Ule0jbV9FyJliRJUnNJlgLPnlh9TrI58O2q2qVtsqm5Ei1JkqQxWLRK+8ZyRlyr+mChJEmSxuDUJN8CjuvHBwOnNMwzI9s5JEmSNApJDgT26IfnVtWJLfPMxCJakiRJmqPR9plIkiRp4Ujy4iQ/SnJrktuS3J7ktta5puNKtCRJkppL8mNgv6q6qnWW2XAlWpIkSWNw45pSQIMr0ZIkSRqBJB8FtgK+BqyYmK+qE5qFmoFb3EmSJGkMNgbuBJ4zaa6AURbRrkRLkiRJc+RKtCRJkppJ8raqen+So+lWnn9HVb25QazVsoiWJElSSxMPE17UNMUc2c4hSZKkUUnyEOCWGnGh6hZ3kiRJaibJPyb58/79OknOAH4C3JjkWW3TTc8iWpIkSS0dDFzdv381EGBz4BnAe1qFWh2LaEmSJLV016S2jecCX6yqlf3BK6N9fs8iWpIkSS2tSLJjks2BvYHTJl1bv1Gm1RptdS9JkqQF4TDgK3QtHB+uqmUASfYFLm4ZbCbuziFJkiTNkSvRkiRJai7JOsCBwLZMqlGr6ohWmWZiES1JkqQxOAm4FVgCrGicZbVs55AkSVJzSS6vqh1b55gtd+eQJEnSGJyXZKfWIWbLlWhJkiQ1l+RK4LHAMrp2jgBVVTs3DTYNi2hJkiQ1l2Sbqear6tqhs8yGDxZKkiSpuYliOckWwLqN46yWPdGSJElqLsn+SX5E185xNvBT4JtNQ83AIlqSJEljcCTwFOCHVbUd8Ezge20jTc8iWpIkSWNwd1UtBxYlWVRVZwK7tg41HXuiJUmSNAa3JNkQOAdYnOQm4I7Gmabl7hySJElqLskGwG/oOiUOBTYBFver06NjES1JkqRmkjwW2LKqvrPK/NOAG6rqJ22SzcyeaEmSJLX0EeC2KeZv7a+NkkW0JEmSWtqyqi5bdbKf23b4OLNjES1JkqSWNp3h2nqDpZgji2hJkiS1dFGSN6w6meT1wJIGeWbFBwslSZLUTJItgROBu7i/aN4VeDDwoqr6RatsM7GIliRJUnNJ9gZ27IdXVNUZLfOsjkW0JEmSNEf2REuSJElzZBEtSZIkzZFFtCQtIEnOa51Bkv4Y2BMtSZIkzZEr0ZI0Mknel+RvJ43/Kck7k5ye5PtJLktywKTrr0pyaZKlST7fz22Z5MR+bmmSp/bzv+4/7pXkrCRfSfKDJIuTpL/2xCRnJ1mS5FtJHt7PvznJlf33+uKQ/yaSNDauREvSyCR5PPCRqnpGP74SeC5wa1XdluRhwPeA/wZsT7e/6lOr6pdJNquqm5McD3y3qj6SZC1gw6q6Ncmvq2rDJHsBJwE7ANcD3wHeCpwPnA0cUFX/L8nBwHOr6rVJrge2q6oVSTatqlsG/GeRpFF5UOsAkqTfVVUXJ9kiydbA5sCvgF8AH06yJ3Av8AhgS2Af4MtV9cv+a2/u/5h9gFf1cyuBW6f4VhdU1c8AklwCbAvcQrdP63/2C9NrATf0n38psDjJ14CvPZB/Z0la01hES9I4fRl4CbAVcDxwKF1B/cSqujvJT4F1/8DvsWLS+5V0/yeE7pCD3af4/BcAewL7Af+QZKequucPzCBJayR7oiVpnI4HXkZXSH8Z2AS4qS+g9wa26T/vDOClSR4KkGSzfv504H/0c2sl2WSW3/dqYPMku/dfu3aSHZIsAh5ZVWcCh/d5NvxD/5KStKayiJakEaqqK4CNgJ9X1Q3AYmDXJJfRtWn8YNLnvRs4O8lS4EP9H3EYsHf/+Uvoeqdn833voivcj+r/vEuAp9K1dXyh//MuBj5mT7SkhcwHCyVJkqQ5ciVakiRJmiOLaEmSJGmOLKIlSZKkObKIliRJkubIIlqSJEmaI4toSZIkaY4soiVJkqQ5soiWJEmS5uj/A04uJzEGDBn2AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vhE7uzOe0QFs"
      },
      "source": [
        "Total vaccinations per hundred, by Country on a map. \n",
        "\n",
        "Warning: This can make your browser very slow. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WD9ET00Q0R3m"
      },
      "source": [
        "fig = px.choropleth(df.reset_index(), locations=\"iso_code\",\n",
        "                    color=\"total_vaccinations_per_hundred\",\n",
        "                    color_continuous_scale=px.colors.sequential.Electric,\n",
        "                   title= \"Total vaccinations per 100\")\n",
        "\n",
        "fig.update_layout(margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0})  #No margin on left, right, top and bottom\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}