Statistics_lab/labs/Lab7.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yonatanlou/study_projects/blob/main/Statistics_lab/labs/Lab7.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0eSHMq-jm3zC"
      },
      "source": [
        "##Lab 7 - Matan Polke, Eitan Zimmerman, Yonatan Lourie"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zuQB81lf5RJA"
      },
      "source": [
        "# Import modules \n",
        "import numpy as np\n",
        "import pandas as pd \n",
        "from scipy.spatial.distance import mahalanobis\n",
        "import scipy as sp\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.lines import Line2D\n",
        "plt.style.use('bmh')\n",
        "\n",
        "from functools import partialmethod\n",
        "pd.DataFrame.head = partialmethod(pd.DataFrame.head, n=10)\n",
        "pd.options.display.float_format = \"{:,.4f}\".format\n",
        "pd.get_option(\"display.max_columns\")\n",
        "\n",
        "import random\n",
        "random.seed(42)\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "from IPython.display import display"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dw__Cf1eVV11"
      },
      "source": [
        "### Import the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1gyT44YR5VTT"
      },
      "source": [
        "data_ballot_2021 = \"https://raw.githubusercontent.com/yonatanlou/study_projects/main/Statistics_lab/votes_per_ballot_2021.csv\"\n",
        "data_ballot_2020 = \"https://raw.githubusercontent.com/yonatanlou/study_projects/main/Statistics_lab/votes_per_ballot_2020.csv\"\n",
        "ballot_2021 = pd.read_csv(data_ballot_2021,  encoding = 'iso-8859-8', index_col='שם ישוב')\n",
        "ballot_2020 = pd.read_csv(data_ballot_2020,  encoding = 'iso-8859-8', index_col='שם ישוב')\n",
        "\n",
        "\n",
        "\n",
        "ballot_2021 = ballot_2021.iloc[:,:-1]\n",
        "ballot_2020 = ballot_2020.iloc[:,:-1]\n",
        "ballot_2021 = ballot_2021.loc[~ballot_2021.index.str.fullmatch('מעטפות חיצוניות')]\n",
        "ballot_2020 = ballot_2020.loc[~ballot_2020.index.str.fullmatch('מעטפות חיצוניות')]\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W9Afx0TpAJws"
      },
      "source": [
        "parties_dict ={'אמת' : \"עבודה\", 'מרצ' : \"מרצ\",  'ג' : \"יהדות התורה\", 'עם'  : \"רעם\",  'ת'  : \"תקוה חדשה\", 'ודעם'  : \"הרשימה המשותפת\", 'ב'  : \"ימינה\", 'ט'  : \"הציונות הדתית\",\n",
        " 'ל'  : \"ישראל ביתנו\", 'מחל'  : \"הליכוד\",  'פה'  : \"יש עתיד\", 'כן'  : \"כחול לבן\", 'שס'  : \"שס\"}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2qs3ek6iCPJ0"
      },
      "source": [
        "Some cleaning"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "06iCf_LUYB1Y"
      },
      "source": [
        "biggest_2021 = ballot_2021.iloc[:,1:].sum().sort_values(ascending=False)[:13].index.to_list()\n",
        "biggest_2020 = ballot_2020.iloc[:,1:].sum().sort_values(ascending=False)[:13].index.to_list()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WFujX-Q7YlE9"
      },
      "source": [
        "### Q1."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y1ODsM8V2h14"
      },
      "source": [
        "#### a. Matching of the ballots by years."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k5oT8rWkx_UZ"
      },
      "source": [
        "##### Data manipulation\n",
        "First, we will normalize the data:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l0MCyLyXaY_8"
      },
      "source": [
        "ballot_2021_raw = ballot_2021.copy()\n",
        "ballot_2020_raw = ballot_2020.copy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l_MPBc5cO2rx"
      },
      "source": [
        "#normalize the data (only the n_ij)\n",
        "\n",
        "ballot_2021.iloc[:,10:] = ballot_2021.iloc[:,10:].div(ballot_2021.iloc[:,10:].sum(axis=1), axis=0)\n",
        "ballot_2020.iloc[:,10:] = ballot_2020.iloc[:,10:].div(ballot_2020.iloc[:,10:].sum(axis=1), axis=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8Ivt6sm4QX3e"
      },
      "source": [
        "next, we will make the neccesesary matches between 2020 and 2021."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dZH1lQ5n0bag"
      },
      "source": [
        "2021:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eg6FahSOygMY"
      },
      "source": [
        "# Compute votes share only for parties above a certain threshold \n",
        "def parties_votes_percents(df, thresh):\n",
        "    par = df.sum().div(df.sum().sum()).sort_values(ascending=False)\n",
        "    return par[par > thresh]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2-8UhrvRygMZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "948b1eff-8c3f-40e3-e166-ea44cabd6894"
      },
      "source": [
        "# # update the data with the parties above the  threshold\n",
        "total_votes = parties_votes_percents(ballot_2021.iloc[:,10:], 0.0325)  # total votes for each party\n",
        "names = total_votes.keys().to_list()\n",
        "\n",
        "df_2021_a = ballot_2021[names +[\"קלפי\"]]\n",
        "df_2021_a_raw = ballot_2021_raw[names +[\"קלפי\"]]\n",
        "df_2021_a_raw"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>מחל</th>\n",
              "      <th>פה</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>שס</th>\n",
              "      <th>כן</th>\n",
              "      <th>ל</th>\n",
              "      <th>עם</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ב</th>\n",
              "      <th>ג</th>\n",
              "      <th>ט</th>\n",
              "      <th>מרצ</th>\n",
              "      <th>ת</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>אבירים</th>\n",
              "      <td>0.0333</td>\n",
              "      <td>0.1800</td>\n",
              "      <td>0.0200</td>\n",
              "      <td>0.0067</td>\n",
              "      <td>0.1067</td>\n",
              "      <td>0.0133</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.3133</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0133</td>\n",
              "      <td>0.2067</td>\n",
              "      <td>0.0533</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אדירים</th>\n",
              "      <td>0.4667</td>\n",
              "      <td>0.0111</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0056</td>\n",
              "      <td>0.0389</td>\n",
              "      <td>0.0222</td>\n",
              "      <td>0.0500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0333</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אושה</th>\n",
              "      <td>0.0870</td>\n",
              "      <td>0.3116</td>\n",
              "      <td>0.0109</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1341</td>\n",
              "      <td>0.0290</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2609</td>\n",
              "      <td>0.0254</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0725</td>\n",
              "      <td>0.0543</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אחווה</th>\n",
              "      <td>0.1862</td>\n",
              "      <td>0.2552</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0138</td>\n",
              "      <td>0.2483</td>\n",
              "      <td>0.0207</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0966</td>\n",
              "      <td>0.0276</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0276</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>0.0552</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>איבים</th>\n",
              "      <td>0.4250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0250</td>\n",
              "      <td>0.1250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קורנית</th>\n",
              "      <td>0.0652</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>0.0020</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1487</td>\n",
              "      <td>0.0204</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>0.0367</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.1996</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שורשים</th>\n",
              "      <td>0.1103</td>\n",
              "      <td>0.2793</td>\n",
              "      <td>0.0103</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1310</td>\n",
              "      <td>0.0241</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2069</td>\n",
              "      <td>0.0655</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0034</td>\n",
              "      <td>0.0724</td>\n",
              "      <td>0.0862</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שכניה</th>\n",
              "      <td>0.0315</td>\n",
              "      <td>0.2719</td>\n",
              "      <td>0.0067</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.1371</td>\n",
              "      <td>0.0270</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2270</td>\n",
              "      <td>0.0382</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0090</td>\n",
              "      <td>0.1528</td>\n",
              "      <td>0.0809</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שער אפרים</th>\n",
              "      <td>0.3650</td>\n",
              "      <td>0.1728</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0324</td>\n",
              "      <td>0.0972</td>\n",
              "      <td>0.0108</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0734</td>\n",
              "      <td>0.0886</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.0302</td>\n",
              "      <td>0.0626</td>\n",
              "      <td>0.0389</td>\n",
              "      <td>1.1000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שער אפרים</th>\n",
              "      <td>0.2963</td>\n",
              "      <td>0.1961</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0610</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>0.0414</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1046</td>\n",
              "      <td>0.0697</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>0.0327</td>\n",
              "      <td>0.0588</td>\n",
              "      <td>1.2000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12127 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             מחל     פה   ודעם     שס     כן  ...      ג      ט    מרצ      ת   קלפי\n",
              "שם ישוב                                       ...                                   \n",
              "אבירים    0.0333 0.1800 0.0200 0.0067 0.1067  ... 0.0000 0.0133 0.2067 0.0533 1.0000\n",
              "אדירים    0.4667 0.0111 0.0000 0.3389 0.0167  ... 0.0222 0.0500 0.0000 0.0333 1.0000\n",
              "אושה      0.0870 0.3116 0.0109 0.0000 0.1341  ... 0.0000 0.0000 0.0725 0.0543 1.0000\n",
              "אחווה     0.1862 0.2552 0.0000 0.0138 0.2483  ... 0.0000 0.0276 0.0690 0.0552 1.0000\n",
              "איבים     0.4250 0.0000 0.0000 0.0250 0.1250  ... 0.0000 0.2500 0.0000 0.0000 1.0000\n",
              "...          ...    ...    ...    ...    ...  ...    ...    ...    ...    ...    ...\n",
              "קורנית    0.0652 0.3055 0.0020 0.0000 0.1487  ... 0.0000 0.0061 0.1996 0.0305 1.0000\n",
              "שורשים    0.1103 0.2793 0.0103 0.0000 0.1310  ... 0.0000 0.0034 0.0724 0.0862 1.0000\n",
              "שכניה     0.0315 0.2719 0.0067 0.0022 0.1371  ... 0.0000 0.0090 0.1528 0.0809 1.0000\n",
              "שער אפרים 0.3650 0.1728 0.0000 0.0324 0.0972  ... 0.0022 0.0302 0.0626 0.0389 1.1000\n",
              "שער אפרים 0.2963 0.1961 0.0000 0.0610 0.0763  ... 0.0022 0.0305 0.0327 0.0588 1.2000\n",
              "\n",
              "[12127 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ClplbR4LzTw4"
      },
      "source": [
        "#cities that arent in 2020\n",
        "cities_to_remove = ['באר מילכה' , 'מעלה שומרון' , 'עמיחי' , 'פלך' , 'רותם', 'מעטפות חיצוניות']\n",
        "for city in cities_to_remove:\n",
        "  df_2021_a = df_2021_a.loc[~df_2021_a.index.str.fullmatch(city)]\n",
        "  df_2021_a_raw = df_2021_a_raw.loc[~df_2021_a_raw.index.str.fullmatch(city)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_2021_a_raw"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "j6-BnBM7WzZn",
        "outputId": "0cf726e7-49f0-450a-ba9e-5f2ff7de38e4"
      },
      "execution_count": null,
      "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>מחל</th>\n",
              "      <th>פה</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>שס</th>\n",
              "      <th>כן</th>\n",
              "      <th>ל</th>\n",
              "      <th>עם</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ב</th>\n",
              "      <th>ג</th>\n",
              "      <th>ט</th>\n",
              "      <th>מרצ</th>\n",
              "      <th>ת</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <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>אבירים</th>\n",
              "      <td>0.0333</td>\n",
              "      <td>0.1800</td>\n",
              "      <td>0.0200</td>\n",
              "      <td>0.0067</td>\n",
              "      <td>0.1067</td>\n",
              "      <td>0.0133</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.3133</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0133</td>\n",
              "      <td>0.2067</td>\n",
              "      <td>0.0533</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אדירים</th>\n",
              "      <td>0.4667</td>\n",
              "      <td>0.0111</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0056</td>\n",
              "      <td>0.0389</td>\n",
              "      <td>0.0222</td>\n",
              "      <td>0.0500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0333</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אושה</th>\n",
              "      <td>0.0870</td>\n",
              "      <td>0.3116</td>\n",
              "      <td>0.0109</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1341</td>\n",
              "      <td>0.0290</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2609</td>\n",
              "      <td>0.0254</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0725</td>\n",
              "      <td>0.0543</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אחווה</th>\n",
              "      <td>0.1862</td>\n",
              "      <td>0.2552</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0138</td>\n",
              "      <td>0.2483</td>\n",
              "      <td>0.0207</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0966</td>\n",
              "      <td>0.0276</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0276</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>0.0552</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>איבים</th>\n",
              "      <td>0.4250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0250</td>\n",
              "      <td>0.1250</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2500</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קורנית</th>\n",
              "      <td>0.0652</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>0.0020</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1487</td>\n",
              "      <td>0.0204</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>0.0367</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.1996</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שורשים</th>\n",
              "      <td>0.1103</td>\n",
              "      <td>0.2793</td>\n",
              "      <td>0.0103</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1310</td>\n",
              "      <td>0.0241</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2069</td>\n",
              "      <td>0.0655</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0034</td>\n",
              "      <td>0.0724</td>\n",
              "      <td>0.0862</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שכניה</th>\n",
              "      <td>0.0315</td>\n",
              "      <td>0.2719</td>\n",
              "      <td>0.0067</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.1371</td>\n",
              "      <td>0.0270</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2270</td>\n",
              "      <td>0.0382</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0090</td>\n",
              "      <td>0.1528</td>\n",
              "      <td>0.0809</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שער אפרים</th>\n",
              "      <td>0.3650</td>\n",
              "      <td>0.1728</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0324</td>\n",
              "      <td>0.0972</td>\n",
              "      <td>0.0108</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0734</td>\n",
              "      <td>0.0886</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.0302</td>\n",
              "      <td>0.0626</td>\n",
              "      <td>0.0389</td>\n",
              "      <td>1.1000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שער אפרים</th>\n",
              "      <td>0.2963</td>\n",
              "      <td>0.1961</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0610</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>0.0414</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1046</td>\n",
              "      <td>0.0697</td>\n",
              "      <td>0.0022</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>0.0327</td>\n",
              "      <td>0.0588</td>\n",
              "      <td>1.2000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>12124 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             מחל     פה   ודעם     שס     כן  ...      ג      ט    מרצ      ת   קלפי\n",
              "שם ישוב                                       ...                                   \n",
              "אבירים    0.0333 0.1800 0.0200 0.0067 0.1067  ... 0.0000 0.0133 0.2067 0.0533 1.0000\n",
              "אדירים    0.4667 0.0111 0.0000 0.3389 0.0167  ... 0.0222 0.0500 0.0000 0.0333 1.0000\n",
              "אושה      0.0870 0.3116 0.0109 0.0000 0.1341  ... 0.0000 0.0000 0.0725 0.0543 1.0000\n",
              "אחווה     0.1862 0.2552 0.0000 0.0138 0.2483  ... 0.0000 0.0276 0.0690 0.0552 1.0000\n",
              "איבים     0.4250 0.0000 0.0000 0.0250 0.1250  ... 0.0000 0.2500 0.0000 0.0000 1.0000\n",
              "...          ...    ...    ...    ...    ...  ...    ...    ...    ...    ...    ...\n",
              "קורנית    0.0652 0.3055 0.0020 0.0000 0.1487  ... 0.0000 0.0061 0.1996 0.0305 1.0000\n",
              "שורשים    0.1103 0.2793 0.0103 0.0000 0.1310  ... 0.0000 0.0034 0.0724 0.0862 1.0000\n",
              "שכניה     0.0315 0.2719 0.0067 0.0022 0.1371  ... 0.0000 0.0090 0.1528 0.0809 1.0000\n",
              "שער אפרים 0.3650 0.1728 0.0000 0.0324 0.0972  ... 0.0022 0.0302 0.0626 0.0389 1.1000\n",
              "שער אפרים 0.2963 0.1961 0.0000 0.0610 0.0763  ... 0.0022 0.0305 0.0327 0.0588 1.2000\n",
              "\n",
              "[12124 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VB6So3So0dOj"
      },
      "source": [
        "2020:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sxsmNpKSXbe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 629
        },
        "outputId": "379f7141-e647-4938-ef07-3c8365e2a163"
      },
      "source": [
        "total_votes = parties_votes_percents(ballot_2020.iloc[:,10:], 0.0025)  # total votes for each party\n",
        "print(total_votes)\n",
        "names = total_votes.keys().to_list()\n",
        "df_2020B = ballot_2020[names+[\"קלפי\"]]\n",
        "df_2020Bnew = df_2020B\n",
        "\n",
        "df_2020B_raw = ballot_2020_raw[names+[\"קלפי\"]]\n",
        "df_2020Bnew_raw = df_2020B_raw\n",
        "df_2020Bnew"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "מחל    0.3004\n",
            "פה     0.2636\n",
            "ודעם   0.1243\n",
            "שס     0.0756\n",
            "ל      0.0646\n",
            "אמת    0.0591\n",
            "ג      0.0552\n",
            "טב     0.0491\n",
            "נץ     0.0042\n",
            "dtype: float64\n"
          ]
        },
        {
          "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>מחל</th>\n",
              "      <th>פה</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>שס</th>\n",
              "      <th>ל</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ג</th>\n",
              "      <th>טב</th>\n",
              "      <th>נץ</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0081</td>\n",
              "      <td>0.0484</td>\n",
              "      <td>0.9032</td>\n",
              "      <td>0.0161</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0161</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0081</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9514</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0243</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0046</td>\n",
              "      <td>0.0092</td>\n",
              "      <td>0.9495</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0046</td>\n",
              "      <td>0.0229</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>0.1096</td>\n",
              "      <td>0.0377</td>\n",
              "      <td>0.7842</td>\n",
              "      <td>0.0068</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0514</td>\n",
              "      <td>0.0034</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>0.0602</td>\n",
              "      <td>0.0471</td>\n",
              "      <td>0.8639</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0052</td>\n",
              "      <td>0.0157</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>0.4586</td>\n",
              "      <td>0.0545</td>\n",
              "      <td>0.0040</td>\n",
              "      <td>0.0222</td>\n",
              "      <td>0.0303</td>\n",
              "      <td>0.0202</td>\n",
              "      <td>0.0283</td>\n",
              "      <td>0.3515</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>0.3292</td>\n",
              "      <td>0.0438</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0228</td>\n",
              "      <td>0.0175</td>\n",
              "      <td>0.0123</td>\n",
              "      <td>0.0140</td>\n",
              "      <td>0.5271</td>\n",
              "      <td>0.0158</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנע שבט</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0833</td>\n",
              "      <td>0.8958</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנעישוב</th>\n",
              "      <td>0.1942</td>\n",
              "      <td>0.0097</td>\n",
              "      <td>0.7767</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תרום</th>\n",
              "      <td>0.5393</td>\n",
              "      <td>0.1380</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0998</td>\n",
              "      <td>0.0021</td>\n",
              "      <td>0.0191</td>\n",
              "      <td>0.0149</td>\n",
              "      <td>0.1805</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10631 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                    מחל     פה   ודעם     שס  ...      ג     טב     נץ   קלפי\n",
              "שם ישוב                                       ...                            \n",
              "אבו גווייעד שבט  0.0081 0.0484 0.9032 0.0161  ... 0.0000 0.0000 0.0000 1.0000\n",
              "אבו גווייעד שבט  0.0081 0.0000 0.9514 0.0000  ... 0.0000 0.0000 0.0000 2.0000\n",
              "אבו גווייעד שבט  0.0046 0.0092 0.9495 0.0000  ... 0.0000 0.0000 0.0000 3.0000\n",
              "אבו גוש          0.1096 0.0377 0.7842 0.0068  ... 0.0034 0.0000 0.0000 1.0000\n",
              "אבו גוש          0.0602 0.0471 0.8639 0.0000  ... 0.0000 0.0000 0.0000 2.0000\n",
              "...                 ...    ...    ...    ...  ...    ...    ...    ...    ...\n",
              "תקוע             0.4586 0.0545 0.0040 0.0222  ... 0.0283 0.3515 0.0182 2.0000\n",
              "תקוע             0.3292 0.0438 0.0000 0.0228  ... 0.0140 0.5271 0.0158 3.0000\n",
              "תראבין אצאנע שבט 0.0000 0.0833 0.8958 0.0000  ... 0.0000 0.0000 0.0000 1.0000\n",
              "תראבין אצאנעישוב 0.1942 0.0097 0.7767 0.0000  ... 0.0000 0.0000 0.0000 1.0000\n",
              "תרום             0.5393 0.1380 0.0000 0.0998  ... 0.0149 0.1805 0.0042 1.0000\n",
              "\n",
              "[10631 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3-pNIzxAX4KB"
      },
      "source": [
        "#changes needed as specify in  lab 6\n",
        "df_2020Bnew_raw.loc[:,'אמת'] = df_2020B_raw.loc[:,'אמת']/2\n",
        "df_2020Bnew_raw.loc[:,'מרצ'] = df_2020Bnew_raw.loc[:,'אמת']\n",
        "df_2020Bnew_raw.loc[:,'עם'] = df_2020B_raw.loc[:,'ודעם']*0.4\n",
        "df_2020Bnew_raw.loc[:,'ודעם'] = df_2020B_raw.loc[:,'ודעם']*0.6\n",
        "df_2020Bnew_raw.loc[:,'ת'] = df_2020B_raw.loc[:,'מחל']/6\n",
        "df_2020Bnew_raw.loc[:,'מחל'] = df_2020B_raw.loc[:,'מחל']*5/6\n",
        "df_2020Bnew_raw.loc[:,'כן'] = df_2020B_raw.loc[:,'פה']/3\n",
        "df_2020Bnew_raw.loc[:,'פה'] = df_2020B_raw.loc[:,'פה']*2/3\n",
        "df_2020Bnew_raw.loc[:,'ב'] = df_2020B_raw.loc[:,'טב']*0.6\n",
        "df_2020Bnew_raw.loc[:,'ט']= df_2020B_raw.loc[:,'טב']*0.4\n",
        "df_2020Bnew_raw.loc[:,'ט'] =df_2020Bnew_raw.loc[:,'ט'] + df_2020B_raw.loc[:,'נץ']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_2020Bnew"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "SCSxNOPIXQn6",
        "outputId": "8403b7df-2365-4bcf-de2d-564693047d56"
      },
      "execution_count": null,
      "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>מחל</th>\n",
              "      <th>פה</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>שס</th>\n",
              "      <th>ל</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ג</th>\n",
              "      <th>טב</th>\n",
              "      <th>נץ</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0081</td>\n",
              "      <td>0.0484</td>\n",
              "      <td>0.9032</td>\n",
              "      <td>0.0161</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0161</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0081</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.9514</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0243</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>0.0046</td>\n",
              "      <td>0.0092</td>\n",
              "      <td>0.9495</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0046</td>\n",
              "      <td>0.0229</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>0.1096</td>\n",
              "      <td>0.0377</td>\n",
              "      <td>0.7842</td>\n",
              "      <td>0.0068</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0514</td>\n",
              "      <td>0.0034</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>0.0602</td>\n",
              "      <td>0.0471</td>\n",
              "      <td>0.8639</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0052</td>\n",
              "      <td>0.0157</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>0.4586</td>\n",
              "      <td>0.0545</td>\n",
              "      <td>0.0040</td>\n",
              "      <td>0.0222</td>\n",
              "      <td>0.0303</td>\n",
              "      <td>0.0202</td>\n",
              "      <td>0.0283</td>\n",
              "      <td>0.3515</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>0.3292</td>\n",
              "      <td>0.0438</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0228</td>\n",
              "      <td>0.0175</td>\n",
              "      <td>0.0123</td>\n",
              "      <td>0.0140</td>\n",
              "      <td>0.5271</td>\n",
              "      <td>0.0158</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנע שבט</th>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0833</td>\n",
              "      <td>0.8958</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנעישוב</th>\n",
              "      <td>0.1942</td>\n",
              "      <td>0.0097</td>\n",
              "      <td>0.7767</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תרום</th>\n",
              "      <td>0.5393</td>\n",
              "      <td>0.1380</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0998</td>\n",
              "      <td>0.0021</td>\n",
              "      <td>0.0191</td>\n",
              "      <td>0.0149</td>\n",
              "      <td>0.1805</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10631 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                    מחל     פה   ודעם     שס  ...      ג     טב     נץ   קלפי\n",
              "שם ישוב                                       ...                            \n",
              "אבו גווייעד שבט  0.0081 0.0484 0.9032 0.0161  ... 0.0000 0.0000 0.0000 1.0000\n",
              "אבו גווייעד שבט  0.0081 0.0000 0.9514 0.0000  ... 0.0000 0.0000 0.0000 2.0000\n",
              "אבו גווייעד שבט  0.0046 0.0092 0.9495 0.0000  ... 0.0000 0.0000 0.0000 3.0000\n",
              "אבו גוש          0.1096 0.0377 0.7842 0.0068  ... 0.0034 0.0000 0.0000 1.0000\n",
              "אבו גוש          0.0602 0.0471 0.8639 0.0000  ... 0.0000 0.0000 0.0000 2.0000\n",
              "...                 ...    ...    ...    ...  ...    ...    ...    ...    ...\n",
              "תקוע             0.4586 0.0545 0.0040 0.0222  ... 0.0283 0.3515 0.0182 2.0000\n",
              "תקוע             0.3292 0.0438 0.0000 0.0228  ... 0.0140 0.5271 0.0158 3.0000\n",
              "תראבין אצאנע שבט 0.0000 0.0833 0.8958 0.0000  ... 0.0000 0.0000 0.0000 1.0000\n",
              "תראבין אצאנעישוב 0.1942 0.0097 0.7767 0.0000  ... 0.0000 0.0000 0.0000 1.0000\n",
              "תרום             0.5393 0.1380 0.0000 0.0998  ... 0.0149 0.1805 0.0042 1.0000\n",
              "\n",
              "[10631 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RFCrhqPozosa"
      },
      "source": [
        "#changes needed as specify in  lab 6\n",
        "df_2020Bnew.loc[:,'אמת'] = df_2020B.loc[:,'אמת']/2\n",
        "df_2020Bnew.loc[:,'מרצ'] = df_2020Bnew.loc[:,'אמת']\n",
        "df_2020Bnew.loc[:,'עם'] = df_2020B.loc[:,'ודעם']*0.4\n",
        "df_2020Bnew.loc[:,'ודעם'] = df_2020B.loc[:,'ודעם']*0.6\n",
        "df_2020Bnew.loc[:,'ת'] = df_2020B.loc[:,'מחל']/6\n",
        "df_2020Bnew.loc[:,'מחל'] = df_2020B.loc[:,'מחל']*5/6\n",
        "df_2020Bnew.loc[:,'כן'] = df_2020B.loc[:,'פה']/3\n",
        "df_2020Bnew.loc[:,'פה'] = df_2020B.loc[:,'פה']*2/3\n",
        "df_2020Bnew.loc[:,'ב'] = df_2020B.loc[:,'טב']*0.6\n",
        "df_2020Bnew.loc[:,'ט']= df_2020B.loc[:,'טב']*0.4\n",
        "df_2020Bnew.loc[:,'ט'] =df_2020Bnew.loc[:,'ט'] + df_2020B.loc[:,'נץ']\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_2020Bnew_raw"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "MeCgCfLZXrta",
        "outputId": "4ac886b9-1292-44f1-b1d7-61c03c812886"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>מחל</th>\n",
              "      <th>פה</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>שס</th>\n",
              "      <th>ל</th>\n",
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              "      <th>נץ</th>\n",
              "      <th>קלפי</th>\n",
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              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>112</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>235</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גווייעד שבט</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>207</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>32</td>\n",
              "      <td>11</td>\n",
              "      <td>229</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו גוש</th>\n",
              "      <td>23</td>\n",
              "      <td>18</td>\n",
              "      <td>330</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>227</td>\n",
              "      <td>27</td>\n",
              "      <td>2</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>10</td>\n",
              "      <td>14</td>\n",
              "      <td>174</td>\n",
              "      <td>9</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תקוע</th>\n",
              "      <td>188</td>\n",
              "      <td>25</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>301</td>\n",
              "      <td>9</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנע שבט</th>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>43</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תראבין אצאנעישוב</th>\n",
              "      <td>40</td>\n",
              "      <td>2</td>\n",
              "      <td>160</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תרום</th>\n",
              "      <td>254</td>\n",
              "      <td>65</td>\n",
              "      <td>0</td>\n",
              "      <td>47</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>7</td>\n",
              "      <td>85</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10631 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  מחל  פה  ודעם  שס   ל  אמת   ג   טב  נץ   קלפי\n",
              "שם ישוב                                                         \n",
              "אבו גווייעד שבט     1   6   112   2   0    2   0    0   0 1.0000\n",
              "אבו גווייעד שבט     2   0   235   0   0    6   0    0   0 2.0000\n",
              "אבו גווייעד שבט     1   2   207   0   1    5   0    0   0 3.0000\n",
              "אבו גוש            32  11   229   2   0   15   1    0   0 1.0000\n",
              "אבו גוש            23  18   330   0   2    6   0    0   0 2.0000\n",
              "...               ...  ..   ...  ..  ..  ...  ..  ...  ..    ...\n",
              "תקוע              227  27     2  11  15   10  14  174   9 2.0000\n",
              "תקוע              188  25     0  13  10    7   8  301   9 3.0000\n",
              "תראבין אצאנע שבט    0   4    43   0   0    0   0    0   0 1.0000\n",
              "תראבין אצאנעישוב   40   2   160   0   0    0   0    0   0 1.0000\n",
              "תרום              254  65     0  47   1    9   7   85   2 1.0000\n",
              "\n",
              "[10631 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E1y809ppaJ3D",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        },
        "outputId": "2972c830-7009-4c73-d707-e124a75ce26d"
      },
      "source": [
        "df_2020Bnew = df_2020Bnew.drop([ 'נץ','טב'], axis=1)\n",
        "df_2020Bnew_raw = df_2020Bnew_raw.drop([ 'נץ','טב'], axis=1)\n",
        "for city in cities_to_remove:\n",
        "  df_2020Bnew = df_2020Bnew.loc[~df_2020Bnew.index.str.fullmatch(city)]\n",
        "  df_2020Bnew_raw = df_2020Bnew_raw.loc[~df_2020Bnew_raw.index.str.fullmatch(city)]\n",
        "\n",
        "\n",
        "PARTIES_COLUMNS = df_2021_a.columns\n",
        "\n",
        "df_2020_a = df_2020Bnew\n",
        "df_2020_a = df_2020_a[PARTIES_COLUMNS]\n",
        "\n",
        "df_2020_a_raw = df_2020Bnew_raw\n",
        "df_2020_a_raw = df_2020_a_raw[PARTIES_COLUMNS]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-26-5d4741642421>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf_2020Bnew\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_2020Bnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m'נץ'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'טב'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdf_2020Bnew_raw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_2020Bnew_raw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m \u001b[0;34m'נץ'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'טב'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcity\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcities_to_remove\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0mdf_2020Bnew\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_2020Bnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mdf_2020Bnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfullmatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcity\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m   \u001b[0mdf_2020Bnew_raw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_2020Bnew_raw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mdf_2020Bnew_raw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfullmatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcity\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4172\u001b[0m             \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4173\u001b[0m             \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4174\u001b[0;31m             \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4175\u001b[0m         )\n\u001b[1;32m   4176\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   3887\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3888\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3889\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3890\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3891\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   3921\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3922\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3923\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3924\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3925\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   5285\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5286\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5287\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5288\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5289\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: \"['נץ' 'טב'] not found in axis\""
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QhAoLHpeEGjC"
      },
      "source": [
        "#### Utils functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aa77gYhcxlZC"
      },
      "source": [
        "def getByKalpiAndCity(df, KalpyCity):\n",
        "  \"\"\"\n",
        "  Taking the dataframe and indexing the indexes that are in KalpyCity\n",
        "  df = full dataframe\n",
        "  KalpyCity = dataframe (Nx2) that containns only the desirble [\"קלפי\", \"שם ישוב\"]\n",
        "  \"\"\"\n",
        "  results = pd.merge(df, KalpyCity, how='inner', on=[\"קלפי\", \"שם ישוב\"])\n",
        "  return results\n",
        "\n",
        "\n",
        "def compareKalpiWithMean(df, kalpi, city):\n",
        "  top_kalpi = df[(df[\"קלפי\"] ==kalpi)]\n",
        "  top_kalpi = top_kalpi[top_kalpi.index==city]\n",
        "  mean_by_city = df[df.index==city].mean().to_frame().T\n",
        "  results = pd.concat([top_kalpi,mean_by_city]).fillna(0)\n",
        "  results.index = [\"top_kalpi\",\"mean_by_city\"]\n",
        "  return results\n",
        "\n",
        "\n",
        "def bigCitiesFilter(df, amountOfPeople):\n",
        "  \"\"\"\n",
        "  Filtering by amount of people in a certain city.\n",
        "  \"\"\"\n",
        "  votes_per_city = df.groupby(df.index).sum()\n",
        "\n",
        "  only_small_cities = votes_per_city[votes_per_city[\"בזב\"]<=amountOfPeople]\n",
        "  only_small_cities = only_small_cities.iloc[:,[3]+list(range(10,df.shape[1]))]\n",
        "\n",
        "  return only_small_cities\n",
        "\n",
        "def MeanByCity(df):\n",
        "  \"\"\"\n",
        "  Get the mean votes by city.\n",
        "  \"\"\"\n",
        "  \n",
        "  mean_by_city =  df.groupby(df.index).mean()\n",
        "  mean_by_city = mean_by_city.div(mean_by_city.sum(axis=1), axis=0)\n",
        "  return mean_by_city\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PewZo3f3-tvM"
      },
      "source": [
        "##### Intersection\n",
        "Make the same ballot number on each year by intersection:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x720oZ_t2bQv"
      },
      "source": [
        "\n",
        "df_2020_a.reset_index(inplace=True)\n",
        "df_2021_a.reset_index(inplace=True)\n",
        "\n",
        "df_2020_a_raw.reset_index(inplace=True)\n",
        "df_2021_a_raw.reset_index(inplace=True)\n",
        "\n",
        "#getting all the intersect pairs of שם ישוב and קלפי in each year:\n",
        "kalpi_idx = pd.merge(df_2021_a, df_2020_a, how='inner', on=[\"קלפי\", \"שם ישוב\"])[[\"קלפי\", \"שם ישוב\"]]\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "54xjt2BzY28L"
      },
      "source": [
        "#making each year with the same kalpis\n",
        "df_2021_a = getByKalpiAndCity(df_2021_a, kalpi_idx)\n",
        "df_2020_a = getByKalpiAndCity(df_2020_a, kalpi_idx)\n",
        "\n",
        "\n",
        "df_2021_a.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "df_2020_a.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "\n",
        "df_2021_a.set_index(\"שם ישוב\", inplace=True)\n",
        "df_2020_a.set_index(\"שם ישוב\", inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "56xFElY3ZPqX"
      },
      "source": [
        "#making each year with the same kalpis\n",
        "df_2021_a_raw = getByKalpiAndCity(df_2021_a_raw, kalpi_idx)\n",
        "df_2020_a_raw = getByKalpiAndCity(df_2020_a_raw, kalpi_idx)\n",
        "\n",
        "\n",
        "df_2021_a_raw.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "df_2020_a_raw.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "\n",
        "df_2021_a_raw.set_index(\"שם ישוב\", inplace=True)\n",
        "df_2020_a_raw.set_index(\"שם ישוב\", inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SE1B_Ji6eufk"
      },
      "source": [
        "#normalize each kalpi:\n",
        "# kalpi_2021_a = df_2021_a[\"קלפי\"]\n",
        "# kalpi_2020_a = df_2020_a[\"קלפי\"]\n",
        "\n",
        "# df_2021_a = df_2021_a.div(df_2021_a.sum(axis=1), axis=0)\n",
        "# df_2020_a = df_2020_a.div(df_2020_a.sum(axis=1), axis=0)\n",
        "\n",
        "# df_2021_a[\"קלפי\"] = kalpi_2021_a\n",
        "# df_2020_a[\"קלפי\"] = kalpi_2020_a"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lGA1YnlAYqvx"
      },
      "source": [
        "#### b."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iK0Ruz5OcRe4"
      },
      "source": [
        "Filter only the big cities:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8715j082ckU-"
      },
      "source": [
        "$\\sum_{i=1}^{C}\\sum_{b \\in ballot}^{B}\\sum_{j=1}^{K}(n_{bij}-{n}_{i\\bullet})^2$\n",
        "\n",
        "Sort by the biggest"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GRxDmHYjdwcJ"
      },
      "source": [
        "\n",
        "#make the dfs columns [שם ישוב, קלפי, parties]\n",
        "df_2021 = ballot_2021.iloc[:,[3]+list(range(10,ballot_2021.shape[1]))]\n",
        "df_2020 = ballot_2020.iloc[:,[3]+list(range(10,ballot_2020.shape[1]))]\n",
        "\n",
        "df_2021_raw = ballot_2021_raw.iloc[:,[3]+list(range(10,ballot_2021_raw.shape[1]))]\n",
        "df_2020_raw = ballot_2020_raw.iloc[:,[3]+list(range(10,ballot_2020_raw.shape[1]))]\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ilPrj9YGQj5W",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "5a32d122-8781-4934-a6f1-74b072fd963d"
      },
      "source": [
        "\n",
        "\n",
        "only_small_cities = bigCitiesFilter(ballot_2020_raw, 50000)\n",
        "\n",
        "mean_by_city = MeanByCity(only_small_cities)\n",
        "\n",
        "df_2020_big_cities = df_2020[df_2020.index.isin(only_small_cities.index)]\n",
        "\n",
        "diff_squared = (df_2020_big_cities.iloc[:,1:].sub(mean_by_city.iloc[:,1:], axis=0))**2\n",
        "diff_squared.reset_index(inplace=True)\n",
        "diff_squared[\"קלפי\"] = df_2020_big_cities.reset_index()[\"קלפי\"]\n",
        "diff_squared.set_index(\"שם ישוב\", inplace=True)\n",
        "final_ans_b = diff_squared.iloc[:,:-1].sum(axis=1).to_frame(\"SumSquared\")\n",
        "final_ans_b[\"קלפי\"] = diff_squared[\"קלפי\"]\n",
        "\n",
        "\n",
        "final_ans_b.sort_values(by=\"SumSquared\", ascending=False, inplace=True)\n",
        "results_b_2020 = final_ans_b.iloc[:10,:]\n",
        "results_b_2020\n",
        "\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "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>SumSquared</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>צפת</th>\n",
              "      <td>1.0670</td>\n",
              "      <td>40.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>חצור הגלילית</th>\n",
              "      <td>1.0081</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קרית גת</th>\n",
              "      <td>0.8372</td>\n",
              "      <td>74.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.7101</td>\n",
              "      <td>7.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6967</td>\n",
              "      <td>25.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.6951</td>\n",
              "      <td>60.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6607</td>\n",
              "      <td>28.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.6551</td>\n",
              "      <td>46.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6498</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.6427</td>\n",
              "      <td>41.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              SumSquared    קלפי\n",
              "שם ישוב                         \n",
              "צפת               1.0670 40.0000\n",
              "חצור הגלילית      1.0081  3.0000\n",
              "קרית גת           0.8372 74.0000\n",
              "מעלותתרשיחא       0.7101  7.0000\n",
              "מעלותתרשיחא       0.6967 25.0000\n",
              "נוף הגליל         0.6951 60.0000\n",
              "מעלותתרשיחא       0.6607 28.0000\n",
              "עכו               0.6551 46.0000\n",
              "מעלותתרשיחא       0.6498  3.0000\n",
              "עכו               0.6427 41.0000"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "ROmJXobWnzj4",
        "outputId": "8492a2a3-8a7e-451e-d483-8f7ef4f51788"
      },
      "source": [
        "only_small_cities = bigCitiesFilter(ballot_2021_raw, 50000)\n",
        "\n",
        "mean_by_city = MeanByCity(only_small_cities)\n",
        "\n",
        "df_2021_big_cities = df_2021[df_2021.index.isin(only_small_cities.index)]\n",
        "\n",
        "diff_squared = (df_2021_big_cities.iloc[:,1:].sub(mean_by_city.iloc[:,1:], axis=0))**2\n",
        "diff_squared.reset_index(inplace=True)\n",
        "diff_squared[\"קלפי\"] = df_2021_big_cities.reset_index()[\"קלפי\"]\n",
        "diff_squared.set_index(\"שם ישוב\", inplace=True)\n",
        "final_ans_b = diff_squared.iloc[:,:-1].sum(axis=1).to_frame(\"SumSquared\")\n",
        "final_ans_b[\"קלפי\"] = diff_squared[\"קלפי\"]\n",
        "\n",
        "\n",
        "final_ans_b.sort_values(by=\"SumSquared\", ascending=False, inplace=True)\n",
        "results_b_2021 = final_ans_b.iloc[:10,:]\n",
        "results_b_2021\n",
        "\n"
      ],
      "execution_count": null,
      "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>SumSquared</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.6720</td>\n",
              "      <td>1.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.5973</td>\n",
              "      <td>1.2000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.5375</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>טבריה</th>\n",
              "      <td>0.5042</td>\n",
              "      <td>12.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.4947</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מגדל העמק</th>\n",
              "      <td>0.4859</td>\n",
              "      <td>1.1000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.4593</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.4501</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.4485</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קרית גת</th>\n",
              "      <td>0.4350</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             SumSquared    קלפי\n",
              "שם ישוב                        \n",
              "נוף הגליל        0.6720  1.3000\n",
              "מעלותתרשיחא      0.5973  1.2000\n",
              "מעלותתרשיחא      0.5375  1.0000\n",
              "טבריה            0.5042 12.3000\n",
              "נוף הגליל        0.4947  1.0000\n",
              "מגדל העמק        0.4859  1.1000\n",
              "נוף הגליל        0.4593  1.0000\n",
              "מעלותתרשיחא      0.4501  1.0000\n",
              "עכו              0.4485  1.0000\n",
              "קרית גת          0.4350  1.0000"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Vd6J0txAQBt_"
      },
      "source": [
        "#### c.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dl4qkPU9fbWF"
      },
      "source": [
        "$\\sum_{i=1}^{C}\\sum_{b \\in ballot}^{B}\\sum_{j=1}^{K}(n_{bij}^{2020}-n_{bij}^{2021})^2$\n",
        "\n",
        "\n",
        "Sort by biggest"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "IA_QamjOdC8I",
        "outputId": "fdb01106-30fc-4591-f69c-af295d993322"
      },
      "source": [
        "dist = (df_2021_a.iloc[:,:-1] - df_2020_a.iloc[:,:-1])**2\n",
        "results_c = dist.sum(axis=1).to_frame()\n",
        "\n",
        "\n",
        "results_c[\"קלפי\"]= df_2021_a[\"קלפי\"] #both of dfs with same sorting\n",
        "results_c.columns= [\"SumSquared\", \"קלפי\"]\n",
        "results_c =  results_c.sort_values(by=\"SumSquared\", ascending=False).iloc[:10,:]\n",
        "\n",
        "results_c"
      ],
      "execution_count": null,
      "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>SumSquared</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>נווה</th>\n",
              "      <td>1.0091</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>תל שבע</th>\n",
              "      <td>0.5900</td>\n",
              "      <td>12.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ירושלים</th>\n",
              "      <td>0.5843</td>\n",
              "      <td>623.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>בני נצרים</th>\n",
              "      <td>0.5790</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קצר אסר</th>\n",
              "      <td>0.5787</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו תלול</th>\n",
              "      <td>0.5776</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אטרש שבט</th>\n",
              "      <td>0.5621</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שומריה</th>\n",
              "      <td>0.5545</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ערערהבנגב</th>\n",
              "      <td>0.5513</td>\n",
              "      <td>8.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אבו תלול</th>\n",
              "      <td>0.5502</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           SumSquared     קלפי\n",
              "שם ישוב                       \n",
              "נווה           1.0091   1.0000\n",
              "תל שבע         0.5900  12.0000\n",
              "ירושלים        0.5843 623.0000\n",
              "בני נצרים      0.5790   1.0000\n",
              "קצר אסר        0.5787   1.0000\n",
              "אבו תלול       0.5776   1.0000\n",
              "אטרש שבט       0.5621   3.0000\n",
              "שומריה         0.5545   1.0000\n",
              "ערערהבנגב      0.5513   8.0000\n",
              "אבו תלול       0.5502   2.0000"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Mp7fi3nfrIG"
      },
      "source": [
        "#### h. TODO\n",
        "\n",
        "**Top 10**\n",
        "\n",
        "\\\n",
        "\n",
        "$v_{ib} = \\frac{n_{ib\\bullet}}{\\widetilde{n}_{ib}\\bullet}$\n",
        "\n",
        "$ \\ \\ \\frac{\\widetilde{v}^{20}_{ib}\\bullet+\\widetilde{v}^{21}_{ib}\\bullet}{2} \\ \\ \\{b \\in ballot_{ib}\\}$ "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nP-6aGsTfzxF"
      },
      "source": [
        "First, I'll organize the data:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PdvZMY8ggXQZ"
      },
      "source": [
        "def calcVotesRatio(df, numerator,denominator):\n",
        "  df_2021_h = getByKalpiAndCity(df.reset_index(), kalpi_idx)\n",
        "  df_2021_h.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "\n",
        "  df_2021_h1 = df_2021_h[[\"שם ישוב\", \"קלפי\", \"בזב\", \"כשרים\",\"פסולים\", \"מצביעים\"]]\n",
        "  df_2021_h1[\"votes_ratio\"] = df_2021_h1[numerator]/df_2021_h1[denominator]\n",
        "  return df_2021_h1\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j1AKV2nglTsB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "96783d48-2658-4359-afed-e13e752c3e80"
      },
      "source": [
        "columnsToAdd = [\"בזב\", \"כשרים\",\"פסולים\", \"מצביעים\"]\n",
        "\n",
        "#votes ratio per ballot for 2021\n",
        "results_h = calcVotesRatio(ballot_2021_raw, \"מצביעים\",\"בזב\")\n",
        "#votes ratio per ballot for 2021 + votes ratio per ballot for 2020\n",
        "results_h[columnsToAdd+[\"votes_ratio\"]] += calcVotesRatio(ballot_2020_raw, \"מצביעים\",\"בזב\")[columnsToAdd+[\"votes_ratio\"]]\n",
        "results_h[\"votes_ratio\"] = results_h[\"votes_ratio\"]/2\n",
        "results_h.sort_values(by=\"votes_ratio\", ascending=False, inplace=True)\n",
        "results_h = results_h.iloc[:10,:]\n",
        "results_h\n"
      ],
      "execution_count": null,
      "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>שם ישוב</th>\n",
              "      <th>קלפי</th>\n",
              "      <th>בזב</th>\n",
              "      <th>כשרים</th>\n",
              "      <th>פסולים</th>\n",
              "      <th>מצביעים</th>\n",
              "      <th>votes_ratio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3196</th>\n",
              "      <td>תפרח</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>971</td>\n",
              "      <td>827</td>\n",
              "      <td>4</td>\n",
              "      <td>831</td>\n",
              "      <td>0.8548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3832</th>\n",
              "      <td>קרית נטפים</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>963</td>\n",
              "      <td>805</td>\n",
              "      <td>2</td>\n",
              "      <td>807</td>\n",
              "      <td>0.8379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1118</th>\n",
              "      <td>ראשון לציון</td>\n",
              "      <td>177.0000</td>\n",
              "      <td>1136</td>\n",
              "      <td>946</td>\n",
              "      <td>2</td>\n",
              "      <td>948</td>\n",
              "      <td>0.8367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3741</th>\n",
              "      <td>בני נצרים</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>942</td>\n",
              "      <td>776</td>\n",
              "      <td>5</td>\n",
              "      <td>781</td>\n",
              "      <td>0.8326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3415</th>\n",
              "      <td>רמת צבי</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1053</td>\n",
              "      <td>872</td>\n",
              "      <td>1</td>\n",
              "      <td>873</td>\n",
              "      <td>0.8299</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>968</th>\n",
              "      <td>פתח תקווה</td>\n",
              "      <td>312.0000</td>\n",
              "      <td>907</td>\n",
              "      <td>749</td>\n",
              "      <td>0</td>\n",
              "      <td>749</td>\n",
              "      <td>0.8289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2065</th>\n",
              "      <td>בני ברק</td>\n",
              "      <td>53.0000</td>\n",
              "      <td>1261</td>\n",
              "      <td>1030</td>\n",
              "      <td>15</td>\n",
              "      <td>1045</td>\n",
              "      <td>0.8287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2072</th>\n",
              "      <td>בני דרום</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>1012</td>\n",
              "      <td>836</td>\n",
              "      <td>2</td>\n",
              "      <td>838</td>\n",
              "      <td>0.8283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3194</th>\n",
              "      <td>תעוז</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>835</td>\n",
              "      <td>683</td>\n",
              "      <td>4</td>\n",
              "      <td>687</td>\n",
              "      <td>0.8249</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2053</th>\n",
              "      <td>בני ברק</td>\n",
              "      <td>69.0000</td>\n",
              "      <td>1126</td>\n",
              "      <td>922</td>\n",
              "      <td>4</td>\n",
              "      <td>926</td>\n",
              "      <td>0.8239</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          שם ישוב     קלפי   בזב  כשרים  פסולים  מצביעים  votes_ratio\n",
              "3196         תפרח   2.0000   971    827       4      831       0.8548\n",
              "3832   קרית נטפים   1.0000   963    805       2      807       0.8379\n",
              "1118  ראשון לציון 177.0000  1136    946       2      948       0.8367\n",
              "3741    בני נצרים   1.0000   942    776       5      781       0.8326\n",
              "3415      רמת צבי   1.0000  1053    872       1      873       0.8299\n",
              "968     פתח תקווה 312.0000   907    749       0      749       0.8289\n",
              "2065      בני ברק  53.0000  1261   1030      15     1045       0.8287\n",
              "2072     בני דרום   1.0000  1012    836       2      838       0.8283\n",
              "3194         תעוז   1.0000   835    683       4      687       0.8249\n",
              "2053      בני ברק  69.0000  1126    922       4      926       0.8239"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NEpqzrB6qfX1"
      },
      "source": [
        "#### i.\n",
        "\n",
        "$f = False$\n",
        "\n",
        "$F_{ib} = \\frac{f_{ib\\bullet}}{\\widetilde{n}_{ib}\\bullet}$\n",
        "\n",
        "$ \\ \\ \\frac{\\widetilde{F}^{20}_{ib}\\bullet+\\widetilde{F}^{21}_{ib}\\bullet}{2} \\ \\ \\{b \\in ballot_{ib}\\}$ "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mCWdrDOAmsUG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "06e6b88b-009c-4c4b-a365-1ef4896028a2"
      },
      "source": [
        "columnsToAdd = [\"בזב\", \"כשרים\",\"פסולים\", \"מצביעים\"]\n",
        "\n",
        "\n",
        "results_i = calcVotesRatio(ballot_2021_raw, \"כשרים\",\"פסולים\")\n",
        "results_i[columnsToAdd] += calcVotesRatio(ballot_2020_raw, \"מצביעים\",\"בזב\")[columnsToAdd]\n",
        "results_i[\"votes_ratio\"] = results_i[\"פסולים\"]/results_i[\"כשרים\"]\n",
        "results_i.sort_values(by=\"votes_ratio\", ascending=False, inplace=True)\n",
        "results_i = results_i.iloc[:10,:]\n",
        "results_i"
      ],
      "execution_count": null,
      "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>שם ישוב</th>\n",
              "      <th>קלפי</th>\n",
              "      <th>בזב</th>\n",
              "      <th>כשרים</th>\n",
              "      <th>פסולים</th>\n",
              "      <th>מצביעים</th>\n",
              "      <th>votes_ratio</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>521</th>\n",
              "      <td>דימונה</td>\n",
              "      <td>22.0000</td>\n",
              "      <td>1076</td>\n",
              "      <td>461</td>\n",
              "      <td>26</td>\n",
              "      <td>487</td>\n",
              "      <td>0.0564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3165</th>\n",
              "      <td>עין נקובא</td>\n",
              "      <td>3.0000</td>\n",
              "      <td>1148</td>\n",
              "      <td>559</td>\n",
              "      <td>18</td>\n",
              "      <td>577</td>\n",
              "      <td>0.0322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2494</th>\n",
              "      <td>תל אביב  יפו</td>\n",
              "      <td>663.0000</td>\n",
              "      <td>1003</td>\n",
              "      <td>603</td>\n",
              "      <td>19</td>\n",
              "      <td>622</td>\n",
              "      <td>0.0315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>443</th>\n",
              "      <td>באר שבע</td>\n",
              "      <td>143.3000</td>\n",
              "      <td>1080</td>\n",
              "      <td>554</td>\n",
              "      <td>17</td>\n",
              "      <td>571</td>\n",
              "      <td>0.0307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3229</th>\n",
              "      <td>בית שאן</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>1067</td>\n",
              "      <td>647</td>\n",
              "      <td>19</td>\n",
              "      <td>666</td>\n",
              "      <td>0.0294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>506</th>\n",
              "      <td>דימונה</td>\n",
              "      <td>1.2000</td>\n",
              "      <td>1263</td>\n",
              "      <td>624</td>\n",
              "      <td>17</td>\n",
              "      <td>641</td>\n",
              "      <td>0.0272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1425</th>\n",
              "      <td>בת ים</td>\n",
              "      <td>198.0000</td>\n",
              "      <td>962</td>\n",
              "      <td>441</td>\n",
              "      <td>12</td>\n",
              "      <td>453</td>\n",
              "      <td>0.0272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1066</th>\n",
              "      <td>קרית גת</td>\n",
              "      <td>36.0000</td>\n",
              "      <td>1018</td>\n",
              "      <td>590</td>\n",
              "      <td>16</td>\n",
              "      <td>606</td>\n",
              "      <td>0.0271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1280</th>\n",
              "      <td>אבו גוש</td>\n",
              "      <td>5.0000</td>\n",
              "      <td>1100</td>\n",
              "      <td>527</td>\n",
              "      <td>14</td>\n",
              "      <td>541</td>\n",
              "      <td>0.0266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1426</th>\n",
              "      <td>בת ים</td>\n",
              "      <td>203.0000</td>\n",
              "      <td>1178</td>\n",
              "      <td>531</td>\n",
              "      <td>14</td>\n",
              "      <td>545</td>\n",
              "      <td>0.0264</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           שם ישוב     קלפי   בזב  כשרים  פסולים  מצביעים  votes_ratio\n",
              "521         דימונה  22.0000  1076    461      26      487       0.0564\n",
              "3165     עין נקובא   3.0000  1148    559      18      577       0.0322\n",
              "2494  תל אביב  יפו 663.0000  1003    603      19      622       0.0315\n",
              "443        באר שבע 143.3000  1080    554      17      571       0.0307\n",
              "3229       בית שאן   8.0000  1067    647      19      666       0.0294\n",
              "506         דימונה   1.2000  1263    624      17      641       0.0272\n",
              "1425         בת ים 198.0000   962    441      12      453       0.0272\n",
              "1066       קרית גת  36.0000  1018    590      16      606       0.0271\n",
              "1280       אבו גוש   5.0000  1100    527      14      541       0.0266\n",
              "1426         בת ים 203.0000  1178    531      14      545       0.0264"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b9rnUt1wv9sO"
      },
      "source": [
        "#### j."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fC6e0vnZywFt"
      },
      "source": [
        "def plotPreProcessing_c(df, results, ballot_df):\n",
        "  #extract the bzb and the ksherim\n",
        "  KsherimBzb = getByKalpiAndCity(ballot_df, results).reset_index()[[\"בזב\", \"כשרים\",\"שם ישוב\", \"קלפי\"]]\n",
        "\n",
        "\n",
        "  KsherimBzb.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "\n",
        "  #get only the top10 results data\n",
        "  tmp = getByKalpiAndCity(df, results.reset_index()[[\"שם ישוב\", \"קלפי\"]])\n",
        "\n",
        "  \n",
        "  tmp.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "  tmp[[\"כשרים\", \"בזב\"]] = KsherimBzb[[\"כשרים\", \"בזב\"]]\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "  tmp[\"שם ישוב\"] = tmp.loc[:, \"שם ישוב\"].apply(lambda x: x[::-1])\n",
        "\n",
        "  #make a unique index\n",
        "  tmp[\"new_index\"] = tmp[\"שם ישוב\"] + \" \" + tmp[\"קלפי\"].astype(str)\n",
        "  tmp.set_index(\"new_index\", inplace=True)\n",
        "  tmp.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "  tmp.drop([\"שם ישוב\", \"קלפי\"], inplace=True,axis=1)\n",
        "  return tmp\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gfB_bDNhFFbP"
      },
      "source": [
        "def votes_percent_plt(df_2020,df_2021, title):\n",
        "    WIDTH = 0.3  # set column width \n",
        "\n",
        "    fig, ax = plt.subplots(2, 5, figsize=(20,10))\n",
        "    names_r = [n[::-1] for n in df_2020.columns[:-3]]\n",
        "\n",
        "    n = np.arange(len(df_2020.columns)-3)\n",
        "    for ballot in range(len(df_2020.index.to_list())):      \n",
        "        bar_2020 = ax[ballot//5, ballot%5].bar(n, df_2020.iloc[ballot, :-3], \n",
        "                WIDTH, align=\"edge\", color=\"darkblue\", label=\"2020\",alpha=0.7)\n",
        "        bar_2021 = ax[ballot//5, ballot%5].bar(n+WIDTH, df_2021.iloc[ballot, :-3], \n",
        "                WIDTH,align=\"edge\", color= \"orange\",label=\"2021\",alpha=0.7)\n",
        "\n",
        "        tmp_df = pd.DataFrame([df_2020.iloc[ballot,13:].astype(int),\n",
        "            df_2021.iloc[ballot,13:].astype(int)], columns=[\"שנה\",\"בזב\",\"כשרים\"])\n",
        "\n",
        "        ax[ballot//5, ballot%5].legend((bar_2020[0], bar_2021[0]),\n",
        "                                ('2020: ' + 'םירשכ- '+ str(df_2020.iloc[ballot, 13]) +\n",
        "                                  ', בזב- ' + str(df_2020.iloc[ballot, 14]), \n",
        "                                '2021: ' + 'םירשכ- '+ str(df_2021.iloc[ballot, 13]) +\n",
        "                                  ', בזב- ' + str(df_2021.iloc[ballot, 14])))\n",
        "\n",
        "        ax[ballot//5, ballot%5].set_title(df_2020.index.to_list()[ballot], fontsize=18)\n",
        "        # ax[ballot//5, ballot%5].set_title(df_2020.index.to_list()[ballot], fontsize=18, y=0.95, pad=-14)\n",
        "        \n",
        "    for ax in ax.flat:\n",
        "        ax.set_xticks(n)  \n",
        "        ax.set_xticklabels(names_r, rotation=90, fontsize=10)\n",
        "        ax.set_ylabel('percent per party', fontsize=12)\n",
        "\n",
        "\n",
        "\n",
        "    fig.suptitle(title, fontsize=20)\n",
        "    fig.tight_layout(rect=[0, 0.03, 1, 0.92])\n",
        "\n",
        "    plt.show()\n",
        "    return fig, ax\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cofd7CfVMTOA"
      },
      "source": [
        "##### Plot for section c"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "id": "Nf405VG83sAo",
        "outputId": "747fec48-5197-422f-bb7c-4090ddeb26e2"
      },
      "source": [
        "results_c_final_2021 = plotPreProcessing_c(df_2021_a, results_c, ballot_2021_raw)\n",
        "results_c_final_2020 = plotPreProcessing_c(df_2020_a, results_c, ballot_2020_raw)\n",
        "votes_percent_plt(results_c_final_2020, results_c_final_2021, \"Sum of least squared difference between 2020 and 2021 for each ballot (Top 10)\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 10 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<Figure size 1440x720 with 10 Axes>,\n",
              " <matplotlib.axes._subplots.AxesSubplot at 0x7facaa20d810>)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tesYU4JuW9j1"
      },
      "source": [
        "We can see that in most of the parties which are considered as the right side of the politics map (\"Yemanim\"), the main difference is that most of the votes are voted to \"הבית היהודי\". [matan please expand why im not good at politics]\n",
        "\n",
        "As for the Arab settelments its looks more of a change in the arabs party (most of the votes frmo \"ודעם\" moved to \"עם\"). [matan please expand why im not good at politics]\n",
        "\n",
        "So its not that good indicator for detecting fraud ballot - we truly identified anomaly, but probably \"right\" anomaly."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R63a6jiEMoFK"
      },
      "source": [
        "##### Plot for section h"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h3wgfegN5OLW"
      },
      "source": [
        "def plotPreProcessing(df, results, ballot_df):\n",
        "  #extract the bzb and the ksherim\n",
        "  KsherimBzb = getByKalpiAndCity(ballot_df, results).reset_index()[[\"בזב_x\", \"כשרים_x\",\"שם ישוב\", \"קלפי\"]]\n",
        "  # KsherimBzb = getByKalpiAndCity(ballot_df, results).reset_index()\n",
        "  KsherimBzb.columns = [\"בזב\", \"כשרים\",\"שם ישוב\", \"קלפי\"]\n",
        "  KsherimBzb.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "\n",
        "  #get only the top10 results data\n",
        "  tmp = getByKalpiAndCity(df, results.reset_index()[[\"שם ישוב\", \"קלפי\"]])\n",
        "\n",
        "  \n",
        "  tmp.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "  tmp[[\"כשרים\", \"בזב\"]] = KsherimBzb[[\"כשרים\", \"בזב\"]]\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "  tmp[\"שם ישוב\"] = tmp.loc[:, \"שם ישוב\"].apply(lambda x: x[::-1])\n",
        "\n",
        "  #make a unique index\n",
        "  tmp[\"new_index\"] = tmp[\"שם ישוב\"] + \" \" + tmp[\"קלפי\"].astype(str)\n",
        "  tmp.set_index(\"new_index\", inplace=True)\n",
        "  tmp.sort_values(by=[\"שם ישוב\", \"קלפי\"], inplace=True)\n",
        "  tmp.drop([\"שם ישוב\", \"קלפי\"], inplace=True,axis=1)\n",
        "  return tmp\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "id": "Tmc4rpeE4Dnf",
        "outputId": "f4929d97-485d-4208-cdb6-0acdfec578c6"
      },
      "source": [
        "results_h_final_2021 = plotPreProcessing(df_2021_a, results_h, ballot_2021_raw)\n",
        "results_h_final_2020 = plotPreProcessing(df_2020_a, results_h, ballot_2020_raw)\n",
        "\n",
        "votes_percent_plt(results_h_final_2020, results_h_final_2021, \"Highest votes ratio (Avg on 2020-2021)\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 10 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<Figure size 1440x720 with 10 Axes>,\n",
              " <matplotlib.axes._subplots.AxesSubplot at 0x7fac9f579d90>)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_jowuGyJYXQh"
      },
      "source": [
        "The results here seems pretty normal and i dont think we can observed fraud ballot here.\n",
        "\n",
        "The right calculation to do is to check the highest difference in the votes ratio between each year."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x0vcQtaxru1P"
      },
      "source": [
        "##### Plot for section i"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BooAY6mDru1Q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "outputId": "4ecac115-d474-4afe-bd46-da813212dfba"
      },
      "source": [
        "results_i_final_2021 = plotPreProcessing(df_2021_a, results_i, ballot_2021_raw)\n",
        "results_i_final_2020 = plotPreProcessing(df_2020_a, results_i, ballot_2020_raw)\n",
        "\n",
        "votes_percent_plt(results_i_final_2020, results_i_final_2021, \"Highest psulim ratio (Avg on 2020-2021)\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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LpfwwsxMI38lsYN8yGpdT1++fIc6vCI2+M8jQuFsWM/s/QuPyVELv6WyNy2WWgfBgvY2AN9NTz0Qpd14k1JXXrK/GZTNrSkhf85G7Z7yBJCIiIjWbGphFREQkFtGDxR4iDNe+NHWemXUm9OaMw2jCUPDhZrZn+kwzq2NmvVP+3snMMvUsTkxbnjItkVJgGwpTF7g+6nGb2H4H4GxC7777o2kNzaxHhrLXB1pmKNf/CI3XB6atcinQrsCyVjffRe+9UydGvbtvzbJOId/X/YSH5f3JzLZNm/dXQq7n+7PliU4zDfiR0Jhbgpl1J+RN/tTdj3f3wekvQgPyDKC3mW2Xsvq9hLzTJ7HuuBmTYfuJB7b9JTV/d/TAzWtzKH+qOD+XvJlZO+A1ws2V37v7HWUtHzVkjor+vCHtmDuE0Kj6KaHBOnU7JxM+t++BXlnSYqR6ldCo3svMBqXEqQNcH/05Kp+GVTO7jPBQv/cIPZfLe6jno4Qe7MdGPf0TcRqx7oGqI9O2sQlhNMDehAeilqiTY9aVUPdNXI/bEBERkWpMKTJEREQkThcR0k9caGZ7AW8ShtYfTRjefyih4axg7r7QzI4EHgfeNrNXCA19Tujl240wXDuRF7cv8Hcze4swjH0+4cF0h0Rl+XtK+C8IKQWONbM1hMY/B+5z91wedvgRsBfwnpm9SEhfcXT0fqG7T4+WawxMNrOvCY1MM6Ly9iU8nPApd0/tKfoPQu7oJ83sIcIw9O6EofGTyNDrdAP0DvAGcLiZvUl4cN3mhJ6oX7DugYOp3iI0xA8zs1asy+98i7tnTOXg7t9FqQluBd43s4cJjcT7En47nwM59fR0dzezx4EhUUqT1NQSiYf7/aeM9dea2WhCft4hwAXR9B/MbCLQh3Bj4mN3L9X73d1fNbM7onWnmdljhEbigYRUFrPJ8XiL83Mp0CRC/uL3gPZZHow3xt2/S/n7JuC3hDzXU6K6YBtCmpnlhIbq5P6b2X7A3YRONhOBUzOkLVnk7iMSf0S5rE8l9CJ+1MweJTRO9yGkrXiD0BM5J1ED91WE3vevA2dnKMN37j4mpQxLzOw0QkPzJDMbR6gDBhHyVD9KuLmXanxUvulAnSyf5xPuPjWlbJsS6pqExAP7/hM9bBPgOnf/PC1O4sbXY5n2WURERGoBd9dLL7300ksvvWrpi9B46uUs8120XPsM607KsPyWhCH+PxJSZkwlPKTsyGidYWnLT8pWBuCUaJ1TMsxrD/wb+IowdH8JoRHsPuDQlOV+TWiIejcq06ponx4FumeI25WQA3YxoXHOgd45fpaTgLaE3qDzo3K9Dxyftmx9Qk7h5wmNVSujsr0N/BFokCH+oGgfVhJ67o4j9F4ek/79RJ+NExrkUmPkvGx533PKb+O7HH9rZW4nWqYlcFsUdyWhcexaQgqAjNsipA14C1gWxU/uH6HhNuP3R2gUe5GQfmQV8DVwA9Aiz2Ooc7SN61OmNSfkTl4FbFrO+lsTGhvnp37vwO9S9ue8MtavQ3hg5OfR9mYTGombA0uBqXnuT86fCwUeu2X8zsp7ZfoeNyI02H4VlfdH4BGgUxllKuuV8fdMyN3+CKEn8SrCzaorgcZ5fr5X5FCGbMdbD8KNup8JdevH0XdfN8uxWd52Tklbp32+30H0+/sh39+ZXnrppZdeeulVs17mrjRZIiIisv6Z2TXAJUB/d3+hqssTt6iH36vu3ruqyyKVy8xeAHYBfuXuK6q6PABRyo0vgXHuflxVl0dqJjMbCDwFnOju91d1eURERKRqKAeziIiIxMrM2maY9htCHuKfSMuJKlIDnA+0Bs6s7A2b2Rap+YejaRsBiTQPj1d2maR2sJDb40rCyIoHqrg4IiIiUoWUg1lERETi9m6UW/gTQpqA7YCDCTe2T3f3lVVZOJG4ufvHZvZ7YOMq2Pww4DgzmwTMAbYg5AfeipCC5ZEqKJPUDlsQei8/4RoWKyIiUqspRYaIiIjEysyGEx7m157Q4LaIkFv4H+4+qepKtn4pRYZUBTPrQ+hBvSshh3URITXGWGCEu6+pwuKJiIiISC2gBmYRERERERERERERKYhyMIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcwiIiIiIiIiIiIiUhA1MIuIiIiIiIiIiIhIQdTALCIiIiIiIiIiIiIFUQOziIiIiIiIiIiIiBREDcxSq5nZDmb2gJl9ZmaLzWy5mX1uZjeZWZs8Yx1kZm+a2S9m9pOZPWJmHdZX2UWk+jCzNmZ2jZn918x+NDM3szF5xtjdzP5hZu+b2c/R6x0zO9PM6q+nootINWdm+5rZrWb2sZktieqYN8zsODOztGU3MbNzzOxFM/vBzFaY2RdmdoeZbZ3ndncwsyeiuugXM3vdzPaPd+9EpLKY2XdmNrkKtlvPzM6Ozm9+ia653jez07Ms383MnjSzBWa20sy+NbMHzaxByjK6hhPZgOR7rWRmTc3sBjObbmarzGyumY02sy2zLL+TmY2N6rmVZjYjqjc651HG5mZ2i5nNimJMM7Mz0s+1JLt6VV0AkSq2FdAGeByYCRQBvwGGAMea2a7uPr+8IGZ2OPAo8CFwAdAcGAa8YWZd3H32eiq/iFQPOwCXAD8A7wADCohxIXAA8ARwJ1AX+C1wK3CImfV3d4+nuCKyAbmecL7yOPAx0AQ4BhgL7A+clrLsXsCNwCvAv4EFwM7A6cDRZtbd3T8tb4Nm1hF4k3BedAOwONrOC2Y2wN1fjmfXRKQmixqFnwL2Ax4ARhHaILYD2mVY/lTgLmAK8DdgEdAW2Cdab3W0qK7hRDYsOV8rmVlj4FVgN+Be4C2gAzAU6GNme7r73JTlO0fL/AzcQagTOhLOfQ4zs27u/kFZhYvqqpeibd4CfBaV8TZgc+CKvPe4FjJdq4qUZmZHAQ8D/+fuN5SzbH3gO8KJzU7uviyavivwHvAfdx+yfkssIlXJzDYGGrn7j2a2KfAjcI+7n5JHjB7Ae+6+Mm36/cAJwEB3fybGYovIBsDM9gUmu3txyrQ6wESgF/Abd/8kmt4eqOvu09NiHEC4cHrM3Y/MYZsPA0cAe7j71GhaU2AasBLYUTe8RDYsZvYdMNPde1biNv8KXAz0dfeJ5SzbCfgAuA84rZA6RtdwItVTPtdKZjYM+Cdwibv/LWV6d2AycLe7D06Zfjvh5tKu7v5hyvTEuc/N7j6snPKdSejUc7a735Iy/TFgILCdu8/If89rF6XIqAHMbItoCNFXZrZR2rze0fCDwWl/J15LoiFBJ2SJ7VHjRuLv9mnrZ3uNTllnkZktM7OpZva7HPfplCjOASnTksO6ouELa8xsXC7lLkCi8tgkh2X3JdxZvytxYgIQXZBNAo4xDW+XWs7MDs1QTyw1s7fN7MS0ZXeN5i8ws1fMbK+0+SXqh6gO/MXM3or+PtDM/mdmq6M67rH04VRmNiaKUS/6u7w67ZSy9s/dl7r7jxX5jNz9jfTG5chD0fvOFYkvUlPVgvrl1dTG5WjaWkKvO0ipG9z9u/TG5Wj6y8BP5FCPmFkTYBAwKdG4HMVYRuhZuD3Qtbw4IpUly3XDFWnH2Woz+9pCKqqWaeuXOGbz3HbqdootDP1+2sz2zLBsWXXDCgvDsS83s4YZ1h0cLXdteXHL0aOMuqhzFG9ShnlrLaSP+K+Z5dRAHdUl5wBPuvtECzYuY5XzAQMudHc3syYFfCe6hpMaJaV+S339YmYfmdl5Fm44py5fbiqclDoj/bXYzF4zs0FlLF9kZrPNbJyZ7ZDrfuR5rbRf9D46daK7vwl8RRil0ChlVrPoPX3EQeLvX3LY5vHAcsIo0lQjgPqEkWNSDqXIqAHcfa6ZnUG4W3sDcFaGxdZG71NZd8DWAbYEfgfcb2aN3P0/5Wxubsr6mRxKOJF4O2Xabwn/yf8ZuM/MZpV3B7s87r7YzN4E+ppZnehCq2BRBdUUaAR0IgxHBXguh9UTF1lvZZj3NmH46vaEXj8itdVkStcdLYDDgXvNrKG73xVN/zpadkvgWuBFM9vG3RdnChzVgXcC55jZYcA44AXgKGAbQr3YwcJQx2x1RaZ6bSLwMnAN8HmO+7k+bBW9z6vCMohUZ7W1fsm5bjCz5sDGwCc5xN0FaEj28xoI5z7/yyGWSFX7HaGRoQXQDfgjIe1UN3dfEEP8MYTGSIAGwLbA2cBrZraHu5d1/p9aN7SO/h5OSB9R4uaYu98V1UEXmtmT7j4lQ7zyevweS7jWSTeWcMx/Gf09DOhN6EH4D+BZQtquXxH27RULQ9Q/LB2qhH0I9c57ZnYz8HugqZktIDTiXO7uRSnLDyDUh/ua2d8JQ9zXmNnLwDnu/lX6BnQNJ7XI+YSe9RB+8wcAfwe2IKR3ycd1wH+BB4H7gf8Qbu5sTegJ/ISZ/dbdn0tZfkz078aEY+1cQiqZTrmko8lT4ibb8gzzlhNShf2GkGoDwnnZsYS2puGEFBm/ItQHcwipebKKGul3B97P0Nnnf4S6VTfWc6AG5hrC3R8xsweBM83scXd/JZqV+I6XRMstYt1JEABmNhb4iNAwXWYDc3TATco2P7qrvoRQUSXWSfQ6ngZMBw4iXFhV1HOEoaF7kXJiYJZMwp7PsKrBhFw7Cd8Bv3P313NYt230PivDvMS0LdHJidRi0UXcpAyznjCzHQknKXdFyy5LLBv14vkP0JNwgZPNnYSbW2OB14FDEkMrzaw1cBmQGFaVqXylyhZVJfMyzassFoakX0DIf/pkVZVDpDqrjfWLmbUlXAR+k227af5C6IFzTw7L5npeI7IhmOLuX0f/ftzCCMd3CQ0mg7Ovlht3/45w3ZDwopk9BXwbxT+3jHUnpU16JGroGGxmw9x9Ydr8wYQ87PeY2W7uviKaXg/4JX2kQ4btvZ0+zcKQ8zbATYl47j7VzFpEi3yRUs5XzOw5Qi/hP1H+55fo3TiMkDv5QmAhIe3XxYR65OSoHM0JDWUNCJ2m/g28RrjhdTEw2cw6p+ZdjegaTmqLD9PqjGfMbAtgqJldnlIflMvdPzezREPqjNS4FlJCfEfoHPhcYnlK3gx/3szeILTBHAfcnP/ulGka0I9wk+eJlLK1AXaM/tyadQ3M9xByNP+Zkh0d/wfkkkt9E0LDeam6wN1XRTfFdN6TA6XIqFkuJ+SQutvMEsME2kfvpe74JkQnIy8Du6asV6ZMw4XMbBdCz4B73T3TMIRvo/fNctlGDhJ31NITxDeJ3jMNNc/mCaAvcBhwFeGBEpvmuG4iLcmqDPNWpi0jUqtlGer4JvDraChlupzqjaiH0AxCD5a/p+XteyF63z3P4lYpM6tLuFnXATjD3X+q4iKJVGu1pX6xkA7tcUIPplPcfU05yx9J6Pn0X9KGm2ah8xqpCRLXInVTJ7r7R8DzwJHpQ8vj4u4zgU8JHWHy9QKhzN0zxJ0D/IvQcPu3lFntKeNarxx/JHTKGZnLwu4+i9DQtFsOiyfSYbQE+rj7SHd/2N0PIdzoO8nMfp1h2evd/Vx3f9zdr4zKuBmZG+t1DSe12ZuEhtEdy1swV1E7zhTKOUjKUEQAACAASURBVMajG1aLKayeK89IQk/lkWZ2jJm1M7NehOM9Uacnj83ovGwu8AbhQYCHEh7K92vgyegGVlnKqgsg1AeqC3KgBuYawsy6Eu7WfEMYsjkiagQeTBju9FE5IRJDQ1uWuVTY1r8Id5bT/TF6z3iCknJBVjfT/Hy5+8eEp5CmNzC3jt5zfuqvu89095fd/Ql3H064m36DmV2cw+qJoRul8qWxbhhapuEdIrWGmTWLevRclmH2YsKwrFYZ5uVTb8winACkj5BIDB8vt36rLqKL3ruBQ4C/uPuDVVwkkWqrNtUv0XDwJ4AuwKnl9dIzs4OABwjDao/J8aFZOq+RmuCL6P0wM2sRjQhK+BJoTu4NkYVYTOZ6J5f1yLSumV1FSKHxJXC2me1rZrsBe7MuJ3vOLOSiPgp4MaWXd65lbFHuUpDoUfm2u3+RNu/e6L132rKwbih+wgNAccqySbqGk1puSfSey/GYj1yP8SUUVs+VKaqPDibcKBxH6FH9KiH1RSLlWWLfMbOrCTfdTnH329z9yejm1NGE86XyUoiUVRdAqA9UF+RADcw1QJQSYgyhJ84uhIPuVMIQqh0IFyDlXVAk8gbmkjblaMKdstQyNCEMd3rV3T/NufD5+QV4JW3ac8AeZpba+2jX6H0qBYp6N3wAnJnD4omG7EzDJhLTMg29EqlNWhKewJupISdRPzWo4DbaAR+4++q06Yn8fqn1WzGhB1OF8revD1Hj8l3AScCV7l7qgT4iUkKtqF9SGpcPAAa7e5kPMzaz/sB4wlDTA919SVnLp9B5jdQEzxJ6A/8N+JnQoy0h/Rp4fRyzayl9XZXLdjJek1l4IOllhNEI3Qk3tx4k9ASeDNxYQBlPJjSc3Jbnek5uN+ZmRu/paS0g5EWFdQ/j+4l1DTgllo9GaSwghwf36RpOaqnU4zFTm0m+nNzaCjPVc7GI0nZsB+xEeCDnNu5+BOtuDH4OyZH15wOvp6fQcff/Akuj9cvyM+EmV6m6IEqntimqC3KiHMw1w28Iidb/6O6rzezPhIuPjsBO7v5lmWvH43jC0zvzPUHJR5cMuYWeA04n5Oi5L5r2O0Il8WIFt9eY3HokJXL/dCOkGkm1N+HuWmV8ByK1lpm1IpwUPJ7jKmflk6ussqQ0Lp8KXO3uV1RtiUSkOtQvKY3LBwJD3L3MVBdR4/IThAuwA9z95zw29zFhmGi3DPP2jt7fzSOeSKWLUgD2N7NfEdLnTU+Z/WtCD73EQ/4q65ygIts5htBAfbu7LzezIcBThAbmPgU+8Px0QvqfZzLMSzQupd9Uy0fiQaBbZZiXmDYfwkhXM3uXMNx+K1LyvUYNPK0JD2nNha7hpDbL1GaSSRzH+HoVdZJMdl6M6oL9ga9T2rg2JfQ8LnXTK+qIWZdy2j3dfa2ZvQ/sFj0YOjVVxp6EkXA678mBejDXDNtF7zMA3H0poXGiLiEXVWU4nXAnOteLr7xlqShfIVwEDQAwszMIT42/LEse6BKixPiZpu8H7EzJJPGYWRsz2zHKf5jwKmHfB6cOvzOzzoShXI+Ulx9RRCoskSfs/VwWrurG5age6Zg2zQgPEzsVuNbdMw33F5HKV6X1S3RB9TihcfmP7n5XOcsfGC3/BaHhKWv+djNrHtVHyVQB0YMQnwZ6R+cyiWWbElKvfcW6hiORas3dv3H3j919OYCZ/YaQs/exRKNsZZ0TVHA72wELEvvh7k8TRrD2JnS0yUt0rbMDocE6U+N0Ynj8j4UUFsDdvyXkRN3TzJJ56qNnTJxGGAGS2iEo0VnojLRQQwjtFonn7+gaTiSLPOqZCh/jVeBaQkqOa1KmzSM8PLSXmXVIW/5oQu7kxM0kzKx+VBdsk7bsg9GyQ9KmDyPUVQ9VvPg1n3ow1wyJ/xATwzRx90lmdgshP9cT7j4OIHoi8K4ZYrSP3vcys3rRk0JzEuV/3gP4a/p/wlHqjK4570me3P0XM3sN6GdmLxAuvq5291tzDDEyehrpBNY9wGcP4FjCcIrz0pb/G2E42X5ET6F39zVmdg6h0nndzO4k9OY+l1BhDy98D0VqHzPbknU3zjLVV5kklns/irEVsG00LeNFSNzM7NLon4mLl11Spr3m7q+lLP4Zoc5pnzLt78DvgQ+Bz8zsd2mbmO7ub8VbapHaZQOtXx4A+hN62C3PUDd8FA0Lx8y6AE8SetuMBgaEe1frpKXWOCxa7krCA3ESLgb6AC+a2T8JPflOI/TkPjjHXM4iVcbM2rPu/1gj5Fzei9B4+QPhNx73dlK1ABqaWW/g8/Sh29G6vTOsl6hvdjCzvaMHaUG43itKW/YcwnH6HzPbOc+HAf+R0HOxxA2r6IHv+xBudq8mraG2AH8CXgdejp7js5DQG3tP4Cp3/z5l2dGE9GBnRze9XieM1D2dkOrnXynL6hpOapvOZpZeB+T9cL9otOTBrEsb9FoZiyfW2ZHM5zuNgOZRXTbV3ReVEyfnayUze4/w3IuvCD2UDyUcv3e4+5jEclHv4yuAW4ApZjaKkJ5nV8JN8QXAP1KKsSXhOuxVSuZ1T3TyuSmq1z8DDiKcJ13t7t+VtW8SqIG5ZrAs0y8iXJDcamavuftswoGW/oCaVPcD9wCn5LH90wlDtu7IMK9DOdsrWPRQixMI+9SSMPytt7u/mkeYBwknMicShl454STldsKT4r8vY90kd3/EzFYAlxIqsFWE3tX/Fz1tWURydxjhJCEfuxKOu2nR30cC/4yzUDn4a9rfu7Gu5+OVlH8C1yV678y6Xjyp7gHUwCxSMRti/ZKoGw6IXumuZN3DnHdm3cOpspWxzNzNEB6wY2Y9gOsI55MNCA3s/d09fSi5SHV0CiUbCNcQGh3uBq5x94XraTvpJhIaLcZkmZfN+YQH8LWP/i51vefuS8zs94RewLcRGlfLFT275jBCD9303oubEx4Y+BPwpzzT65Ti7h+YWXfgakJPwEaEhptTUxuJomWLzWwAIdf0sYT9/xEYRRiduixlcV3DSW3zj/IXyUl9wk2VX4Ar3H1aOctDOA84Ocu8zQl1WfLmTRnyuVZ6CxhESJlTRHi+1vGZHnzu7v82szmEG1rnEBqwfyQ8IHB4LvVBlGr2AEJddRyhp/T0KGaunRdrPVMHBMmXmc0l3KHqvx63cQrhLnbfTBcyZtaO8DTR+YQTjDHuXvBD/URERERERERERCR/6sEsG6pFhKEdL7p7+lARERERERERERERqQRqYJYNkrsvJuVBDyIiIiIiIiIiIlL51MAshfgHUOpBFSIiIiIiIiIiIlK7KAeziIiIiIiIiIiIiBSkTlUXQERERERERPJnZv3N7Asz+9rMLsow/49m9rGZTTWzyWbWKZre3sxWRNOnmtmoyi+9iIiI1BQ1pgfzpEmTvGHDhjktW1xcTN26dSu8TcWpvFiKU3mx4ixTwvLlyxf06dOndaxBq4Fc652a/D3X1DhxxlKcyo2VoHqn5n7PilN5sRQnP5Vd75hZXeBLoC8wE3gHOM7dP01Zppm7L4n+PQg40937m1l74Bl337msbegaK95YilN5sWpqnHQ18XxH9Y6OqcqME2esmhonXbZ6p8bkYG7YsCE77rhjTsvOmDGDdu3aVXibilN5sRSn8mLFWaaE999/f0asAauJXOudmvw919Q4ccZSnMqNlaB6p+Z+z4pTebEUJz9VUO/sCXzt7t8AmNk44BAg2cCcaFyONAHy6l2ka6x4YylO5cWqqXHS1cTzHdU7OqYqM06csWpqnHTZ6p0a08Ccj0022URxKiFOnLEUp/JixVkmCWry91xT48QZS3EqN5YENfl7VpzKi6U41d6WwA8pf88E9kpfyMyGAn8GGgD7p8zqYGYfAEuAS9399fR158+fzx/+8Afq1atHcXExhx9+OEOHDmXu3Lk0adKEunXrsmTJElq3bk1RURE//PADrVu3Zt68eTRt2hSAZcuWsfnmm/Pjjz9iZrRs2ZIff/yRZs2aUVxczC+//MIWW2zB3LlzqV+/Po0aNWLGjBk0b96c1atXs2LFiuT8Bg0asPHGG7Nw4UI22WQTVqxYwcqVK5PzGzVqROPGjfn5559p2LAhc+bMYfXq1cn5jRs3pkGDBixevJhNN92UxYsXs2bNmuT89H366aefcHeaNGnCjBkzCt6n5s2bs2DBAurXr8/8+fML3qdWrVqxdOlSVq1axapVqyq0T61bt2bVqlUsXLiwQvvUvHlzIDRkVGSfEt/TqlWrmD9/fsH7lPjt1a1blxkzZhS8T4nfXtOmTZkxY0aF9mnu3LkALFq0qEL7lOl7qu2q2/8L1S1OnLFqapw4Y9XUOLmqlQ3MK1asoFmzZoqznuPEGUtxKi9WnGWSoCZ/zzU1TpyxFKdyY1VXZtYfuBmoC9zl7telzT8F+DswK5r0b3e/q9Dt1eTvWXEqL5bi1Azufitwq5kdD1wKnAzMAbZx94VmtgfwhJntlNbjmc0224w33nijVMzUHlGJC9imTZuy+eabl5rfqlUrALbeeuuM62+66aYlps2bNy9jj6vUaYnGttTvMXV+s2bNmDdvHltssUXG+S1atACgSZMmZe7TRhttlLFM+e5TYlvz5s1js802K3ifEsvVqVOHhg0bVmifAJo3b57cl0L3CWDVqlUZv/t89im1TInPqJB9Sv0dbbXVVgXvU0L6d1/IPrVr14558+bRokWLCu0TlP6e5s+fT21W3f5fqG5x4oxVU+PEGaumxslVrWxgXrlypeJUQpw4YylO5cWKs0wS1OTvuabGiTOW4lRurOooypN6Kyl5Us3sqdQ8qZGH3P2sOLZZk79nxam8WIpT7c0Ctk75eyvW3aTKZBwwEsDdVwGron+/Z2bTge2BdwstTHX7fnRMbXhx4oxVU+NISdXt+6luceKMVVPjxBmrpsbJVa1sYE69k72hxnF3li1bRupDGps1a8aSJUvKWCs3ccWJM5biVF6sisQxM5o2barhWmniqivijJVvnEx1DlSP3936iBNnLMVZv7E2kHqn3Dypcatu5zqFxKpt9U51OaYUp3zVqN55B9jOzDoQGpaPBY5PXcDMtnP3r6I/Dwa+iqa3Bn5y92Iz+xWwHfBNRQpT3eqduK6xoPr89mp6nDhj1bQ41ajeqVZqar2jY6ry4sQZq6bFybfeqZUNzHPnzo0l0XVVxlm2bBkNGzakQYMGyWmrVq0i16etliWuOHHGUpzKi1WROKtXr2bZsmVsvPHGFS5HTRJXXRFnrHzjZKpzoHr87tZHnDhjKc76jbWB1Ds55UkFjjCzXsCXwLnu/kP6ArnmQ12zZg2NGjXKKX9jWTkply5dSocOHUrlpCwkz+bq1atp2rRpzvlQ58+fT6tWrWjQoAHFxcXJfS4qKqJRo0asWbMm+WTs4uJi6tevT1FREQB169alqKiIunXr4u6sXbuW+vXrs2bNGsyMunXrsmrVKho0aJB1flFREfXq1WPt2rUl5tepU4c6deok569evZo6deqUmG9mJcrs7mXOB1i7dm1y24XuU2J+YjuF7lOizAmF7lO9evVYs2ZNclsV2Sd3T/6uK7JP9evXZ+XKldSvX7/gfVq+fDnz58+nXr16JY6nyubuRWZ2FvACIf3O3e4+zcyuAt5196eAs8zsAGAN8DMhPQZAL+AqM1sDrAX+6O4/VaQ8NfUaC6rf/501NU6csWpanA3kfKfS1dR6R8dU5cWJM1ZNi5NvvVMrG5gbNWq0wcdx91InPnXq1ImlPHHFiTOW4lRerIrEadCggYZ/ZRBXXRFnrHzjZKpzoHr87tZHnDhjKc76jVWD6p2ngQfdfZWZnQ7cQ8mHcQG550OdN29eMh9m+vx88mzOmzePJk2alMpJmb5OrvlQs5UpU07K5s2bJ3NQ1qsXTlnr1q2LmSXzjyYk5qfWU4mG2lSp69SvXz+5Xqb5ifVT42SaX69ePerXr19qfmqZM62fPn/NmjXJOIXuU2J+oqG00H0qr0y57lNi/po1a6hXr16F9ikh/bvPd58gfPeJ/Spkn5o2bcratWtp1qxZieOpihqZnwOeS5t2ecq/z8my3mPAY3GWpaZeY0H1+7+zpsaJM1ZNi1ODzndiVVPrHR1TlRcnzlg1LU6+9U5838gGpHHjxjUyTnX5Ea6PWIpTebHiLJMEcR3jccaqqfVOTT6mamqcuGNVU+XmSXX3hVFOVIC7gD0qssHqVlfEGau6/YarW5w4YymO5KO61Ttx1l/V7bdXU+PEGaumxpGSqlt9Ud3OdeKMVVPjxBmrpsbJeXuVurVq4ueff66RcRLDDSsjzsyZMxk0aBB777033bp1Y9SoUcl5P//8M4cddhhdunThiCOOYNGiRQA88sgj9OzZkx49etCvXz8++eST5Dovv/wye+65J3vssQcjRowoqEy5iDvOrbfeyt57703Pnj059NBD+eGHdaOZr7jiCrp370737t0ZP358crq7c/XVV9O1a1e6devG7bffHmuZcjV58mTatWtHr1696NWrFzfccEOJOMXFxey7774ce+yxyXVeffVVevfuTa9evRgwYADffFOhVH21RlzHeJyxNrR6p7LrnFzKlKs444wePZoePXokj8HPP/88OX/atGkceOCBdOvWjR49erBy5UqWLl2aPMZ79erFtttuy8UXXxxbefL1+OOPJ7/D0047LTl97NixdOnShS5duvDggw8mp0+dOpUePXqwxx57cNFFF5XKibkBSeZJNbMGhDypT6UuYGZtUv4cBHxWkQ1Wt7oizlg1td6Ja7/ijFVUVFTmuc6mm26arF+OP/74UutfdNFFbL311lVWn44dO5btttsuWcZ77723RJwlS5aw0047ceGFFybXeeyxx+jRowc9e/bkyCOPZOHChbGUvTaobvVOnPWX6p2K7Ve+sbLVOx9//HHyXKdnz54lrrGGDBnCnnvuSffu3TnrrLNYsWJFbOUpxPvvv0/r1q158sknS8RJr3eWL1/OMcccw1577UW3bt248sorYyl3bVHd6ovqdq6TSyzVO2XXOz/88EOyDaRbt26MHj0ayHzsVvW+PfXUU7Rs2ZIPPvggGSfTNSLA1Vdfzc4771xiRGNF1coUGYmhbDUpznHHvYi7x5L0390ZN65fmcvUq1ePv/71r3Tu3JmlS5ey//7707t3b3bccUdGjBjBvvvuy7Bhw7jpppsYMWIEV1xxBdtssw3PPPMMLVq04KWXXmLYsGG8/PLLFBcXc+GFFzJ+/Hjatm1Lnz596N+/PzvuuGOJ7cUh7ji77LILEyZMYKONNuLuu+9m+PDh3H333bz44ot8+OGHvPbaa6xatYpBgwZxwAEH0KxZM8aOHcusWbOYMmUK7s5PP1Uo3V2pMuWjW7dujBs3LmOcUaNGsf3227N06dLkvPPPP5/777+fHXbYgf/85z/ceOON3HrrrRUreC0QV10RZ6yKxjnuuBcBYqt37r+/T5nzK7vOSWwzDnHGOeKIIzj11FMBeP7557n00kt59NFHKSoq4vTTT2fUqFHsvPPO/PTTT9SvX59GjRrx2muvJWPst99+DBw4MLby5GP69OmMGDGC//73v7Ro0SI5lPznn3/mpptuYsKECZgZ++23HwMGDKBFixacf/75jBgxgi5dunD00Ufz8ssv07dv31jKX5lyzJN6tpkNAoqAn4BTKrLN6lJXxBmrptc7cdUVccaqV69e1nMdCD21UuuYVB988EHyQrQq69PDDjsseRM9Pc61115L9+7dk9OLioq4+OKLeeutt2jVqhXDhw/nzjvv5KKLLqpYwWuJ6lbvxHWNBap3yhN3/ZWt3mncuDEjR46kY8eOzJkzh/33358+ffrQvHlzjjrqqGTHndNOO41x48YxePDgWMqTr+LiYq688kr222+/UnHS6x2As846i3322YfVq1dz6KGH8tJLL22Q5ztVoTrVF3HFibNtB1Tv5BorW72z+eab88ILL9CwYUOWLVtGjx496N+/P82bNy917E6aNIl+/cpuS8u1PPlaunQpt99+O3vsUXIQZKZrRIB+/foxePBgunbtWuHyJtTKHsypDWY1KU5cPbtyibPFFlvQuXNnADbeeGO233575syZA4RGj0Sv16OOOornngtp4fbaa69kjsWuXbsml3/vvffo0KED7du3p0GDBhx++OE8//zzJbaXeLBKRcUdZ5999knmh+zSpQuzZ88G4PPPP6d79+7Uq1ePJk2a0KlTJ1555RUARo8ezQUXXECdOnUoLi6mdevWsZYpjjizZs3ipZde4sQTTywxz8ySv9clS5bE9rTdmi6uYzzOWNWt3inv91vZdU4uZYpr3/KJk5rfdvny5ckTz4kTJ7LTTjux8847A9CyZctSeUu//vprfvzxR/bcc8/YypOPe++9lz/84Q/J7yRR902YMIFevXqxySab0KJFC3r37s0rr7ySfMBc165dMTOOPfbY5He7IXL359x9e3fv6O7XRNMujxqXcfeL3X0nd+/s7vu5++dlRyxbdasr4oxVU+uduOqKOGMVFxdnPdcpb73hw4dzxRVXxF6euOJMnTqVH3/8sUQDkLvj7ixfvhx3Z+nSpTrXyUN1q3firL9U71Rsv/KNla3e2XbbbenYsSMAbdq0YdNNN2XBggUA9O3bFzPDzNh9992ZNWtW5g0UUJ583XHHHQwcOLDEdV62emejjTZin332AUK+01122SWnelaC6lZfVLdzHVC9k2usbPVOgwYNks9mWL16NWvXrgUyH7tVWe9ce+21nHPOOSXygL/yyitZrxG7du0a+zlOrWxgXr16dbWK8+CDn3PccS+WeG1Ivv/+ez766KPknZL58+cnf6itW7dm/vz5pda577776NMn3EmbM2cOW265ZXJe27ZtkxXUtddey/PPP1+qgr3uuuvo2rUrgwYNol+/flx++eXJsvTt25fi4mIGDhzIwIED6dOnT/Ju9kcffcSRRx4JhN64b7/9NsuXL2fPPfdk5syZyXX69evHxIkTs+5zpgr//vvv54ADDgBg55135pVXXmH58uUsXLiQyZMnJyubb7/9lscff5z999+f4447junTp5f5+V511VUMHDiQAw88kDPOOIM1a9YAcOyxx9KxY0euueYaxo8fz2GHHcbBBx/MoEGDmDlzZpkxE9555x322WcfjjrqKD777LPkvl1yySVcccUVpXL23HzzzRxzzDHstNNOPPTQQ5xzTsbnxkiaTMd4ocd5dau/4pLPSVRl1DnpZapInZM4KatInZNanrvuuovdd9+d4cOHc9111wGh8djMOOKII+jduzf/+te/Sq2fqCfKM3ToUAYOHMgBBxzAZZddBoSnWw8cOJAOHTpw9913M2rUKA477DAGDBjAcccdx5IlS8qNO336dKZPn07//v3p27cvL7/8MgCzZ8+mTZt12SHatm3L7NmzmTNnDm3bti0xPfE9SfmyHeNN3j2u1KuQOHGWqapUt3onznOduOudhNRzHYCVK1ey//7707dvX5599tnk9DvvvJP+/fsnP6PyPuv1Ve8APP300/Ts2ZOTTz45eX5UXFzMZZddxlVXXVVi2fr16/OPf/yDHj160KlTJ7744otSN9slu/V5bVTIeVN1q3OgZtc7cVxjZfqM0uudhPfee4/Vq1fToUOHEtPXrFnDww8/TO/evcvczvq6xpo9ezbPPvssv//970tMz1bvpFq8eDEvvPAC++67b7nbkSDTcZ7pXKeyzndU79TMemfmzJn07NmT3/zmN5xzzjklrl1g3bHbs2fPMrezvs53PvzwQ2bNmsWBBx5YYvr06dPLvUaMU61MkRFXK31ccaZNiydPi1k89wvyibNs2TJOPvlkrr322hI96xIaNGhQamjH66+/zv3335+xx2C6Sy65BCB5lyjVmWeemRwq/tvf/pbPPvss+fT5unXr8vTTTwOwYsUKevfuTf/+/dlhhx346quvWLNmDVOmTOHcc89l1qxZ7LDDDmy11VbJdebPn0+/fv14++23SzxJPCH1ieoADz/8MB988AHPPPMMAPvvvz8ffPAB/fv3p1WrVnTt2jV5p2j16tU0bNiQCRMm8NRTT/GnP/2pzF55iQoWwvCGCRMm0K9fPy6++GJGjx7NX/7yFwAOPfRQ6tSpw7333svtt9/OX//61zI/21122YUPP/yQpk2bJnsrv/vuu0yYMIHWrVuz6667Mnny5BLrjBw5koceeoguXbrwr3/9i0svvXS9V1I1QVzHOFS/+iuueif9mMqmsuqcTGUqpM7p2LEj06dPr3Cdk1qewYMHM3jwYB599FFuvPFGbrvtNoqKinj77bd55ZVXaNy4MYceeiidO3cucYEyfvx4Ro0aVe5nnZr2ZsCAAXz66ad06tSJIUOG8NVXXyUvmIYMGUKdOnW45ppreOihh0rkVM6kqKiIb775hqeffprZs2dz8MEH88YbbyQ/P4lXdasr4oxVU+uduM511ke9A6XPdSBc0LRt25bvvvuOQw45hE6dOtGoUSOefPLJ5HbS42Syvuqd/v37c8QRR9CwYUPGjBnD0KFDefLJJ7nvvvvo27dviYtgCA1To0eP5tVXX6V9+/b83//9H//85z85//zzy9yOBNXt2ijO+kv1TuVcY0H59Q7A3LlzOeOMM7j11ltLdYg5//zz6datW7JnYTbr6xrrkksuYfjw4aXKla3eSSgqKmLw4MEMGTKE9u3bl7kNWae6ne9Ut3MdUL0TR72z1VZbMXnyZObMmcOJJ57IoEGD2GyzzYCSx+62225b5mewPs531q5dy6WXXpoxdam7l3uNGKda2YN57ty51SrOTjvF087vXvpAXZ9x1qxZw8knn8yRRx5ZIqfnZpttlvxsZs6cWWJo0LRp0zjnnHN44IEHaNmyJRCGN6UOJUjvzZbYVlnatWuXtWdb48aN2X333fnmeclmegAAIABJREFUm29o0KABxcXF/Pa3v+Xoo49myy23ZNKkSaXuNG222Wa0atWKuXPnMnToUHr16sXRRx+dsTyTJk3ixhtvZOzYsSUqrPPOO4/XXnuNxx9/HHdPVjZt27ZNfl4HHngg06ZNK3PfUnXo0CG5n5999hmbbLJJqTL96le/Sn7+V199dfLBNumaNWtG06ZNgTCkbM2aNSxcuJC33nqL559/ns6dOzN48GBef/11Tj/9dBYsWMAnn3xCly5dADj88MP53//+l3PZa7O4jnGofvVXXPVOecd4YpnKqnPKK1OudU6TJk1iqXMylefwww9P9hhs27Yt3bt3p1WrVmy00Ub07duXDz/8MLnsJ598QnFxMbvuumtOn3VCan2Src7p0KFDcplsZU+UsX///tSvX5927dqx7bbbMn36dNq2bVvioWGzZ8+mbdu2tGnTpsQQ0Wzfk2RW3eqKOGPV1HonrnOd9VHvZDvXSYwyaN++PT179uSjjz7i448/5ttvv2WPPfagc+fOLF++PHnukIs4652WLVsmy3viiScydepUAKZMmcKdd95J586dufzyyxk3bhxXXnklH3/8cTK+mXHooYfqXCcP1e3aKM76S/VOaevjGiu1TNnqnSVLlnDsscfyl7/8pVTu0Ouvv56FCxdyzTXX5HW+E+c11tSpUxk8eDCdO3fmqaee4oILLuDZZ5/NWu8kDBs2jI4dO3LGGWfkXG6pfuc71e1cB1TvxFHvJLRp04Ydd9yRt956Kzkt9ditiuusZcuW8dlnnzFw4EA6d+7Mu+++ywknnMAHH3zA5ptvXuY1YtxqZQ/mxo0bV6s4ixbFVXnEkwQ+lzjuztlnn83222/P0KFDS8zr378/48aNY9iwYTzyyCMMGDAACBXSSSedxMiRI0vc2UlUEDNmzKBNmzaMHz+eO+64o0TM9DvAmaxdu5aWLVtm7FGbyHdcp04dOnbsyN/+9jc6derEl19+yT333FPqrviCBQtYsGABW2yxRcY7QYnyfPTRR/z5z3/mkUceKZVja/HixbRs2ZJp06Yxbdq0ZK6tgw46iNdff5127drx9ttvJz+L9957j7vuuouRI0eWuZ+J4Rvpd/5SP6PEvEsvvZRLL700Y5x58+ax2WabYWa89957yc8vdejW5MmT+fe//83tt99OUVERS5Ys4euvv2bbbbdl4sSJbL/99mWWVYL4jvHqV3/FVe+Ud4xXdp2TS5lyqXMgnBhcf/31FapzEjGnT5+ezD344osvJv/dp08fbrnlFpYvX06DBg148803S1ygPPbYYxx++OEl9uuZZ57h/fffL9GDJ9t+pr6nlid9mbIe+nnQQQcxfvx4TjjhBBYuXMjXX39N+/bt6dChA1dddVXyYWATJ07k8ssvZ5NNNmHjjTfmnXfeoUuXLowbN44hQ4aUWVZZp/rVFap3KutcB+Ktd7Kd6yxatIjGjRvTsGFDFi5cyJQpU/jTn/7EjjvuyOefr0shvvXWWzNlyhSg8uuduXPnJnuTPf/888nzltTRHGPHjmXq1KkMHz6cOXPm8MUXX7BgwQI23XRTnevkqbpdG8VZf6neqZxrrETMbPXO6tWrOemkkzjmmGM45JBDSqx37733MmHCBJ544gnq1KmT3LfKvsZK3MiC0CB04IEHcvDBB3PggQdmrHcArrnmGpYsWaKRoQWobuc71e1cB1TvVLTemTVrFi1btqRx48YsWrSIKVOmcOaZZwKlj92quM5q1qwZX3/9dfLvgQMHctVVV7Hbbrux1VZbMXLkyKzXiHGrlQ3MDRo0qFZxfvklngTuMT1kNKc4U6ZM4aGHHqJTp07JO7eXXXYZffv2ZdiwYfz+97/n/vvvZ8stt2TMmDEA3HDDDfz0009ccMEFQHgy5oQJE6hXrx433HADRx55JMXFxZxwwgn8+te/BkKent122y3jU3Rvu+02xo8fD8BXX33FYYcdRtOmTZPrZt43Y9ttt+Xss8+mefPmNGnShDvvvJMWLVowc+bM5MFWVFTETTfdlHUIRWJoyPDhw/nll1+Swzm22morxo4dy5o1azjooIOAkCj/9ttvTz4JdNiwYQwZMoSRI0ey0UYbcfPNNwOhkk5NyJ5w1VVX8c477wAhD1GDBg3o1q1biWXGjx/P3XffjZmxePFi5s6dy6OPPprMSZTJU089xd133029evVo1KgRd911V/LBGJnUq1ePESNGcPLJJ1OnTh1atGjBLbfckjW+rBPXMQ7Vr/6Kr94pO1Bl1zkDBgwoVaZC6hwgljon8RndeeedvPrqq9SvX58WLVokTzRatGjBmWeeSZ8+fTAz+vbtWyIH1xNPPMFDDz1U4rP+9ttv2XjjjUttZ+jQoXz//ffJ/fzwww9LPY141KhRPPPMM5gZ8+fPZ/ny5ey3334Ze/Ik9OnTh4kTJ7L33ntTt25drrzyymRvh/POOy+Zu+2CCy5I3sH/+9//ztChQ1m5ciUHHHBAxhyMkll1qyvijFVT6524znUg3non27nOF198wZ///Gfq1KnD2rVrOef/2Xvz8DiKO3H/LY1OS9ZhHRYWjmzAR2xY2GBwYDnNYQhgiCHfBZYj4QiHCbCwSUwgQAwEwiYEyPqHSUhI2CxHQgIxYJ6EHARiCGvIQhJx2NixsI11C8mWJY00qt8foxlmpBlpjs+0akr1Po8fS9Pdb9enq+uj6uqermuuiZolfqQHvM873//+93n++efJzc2loqIinDPj1f1ee+3FV77yFU455RTy8vKYOXPmmAPYjmhMuzaSzF8u73hzjRVyxcs7Tz/9NK+88godHR089thjQHDQ5YADDuD6669n5syZLF26FAje2F65cqXn11hjxRWLHTt28J3vfIc5c+aE3xt9ySWXcMEFFyS9j8mIaf0d0/o6QZfLO+nknY0bN/L1r38dpRRaa1asWMGCBQtitt2LLrqIz3/+8573d+JRUVER9xrxlltu4cknn2TPnj0sXLiQ888/n5UrVya9j0iU5OyUE8mrr76q43VqR9LY2Eh9fX3a+5Ty3HPPH9iwIfpR+sceOzHO2kG6u7tHvRenv79/zEaTKFIeSddk8Nx8883hCfRMKVMqxDo3//KXv7xx3HHHJf792Cwh0bwTq43D+O08FhOVv2LVK5hz3kl7JF2mei677DLuuOMOqqqqJrQ8Ei6Xd0YTr43HmuSmZ9FjSXtSweUdbzySLlvzjoRnsuSdibjGkuo3pVIel3cm1iPpCnlsucYCl3diEaudx5vQz4v+jlTeMblN2eaRdE32/s6kfII51UrOlGfzZpmJLEJPyJrikXRNBs9YMwon6zLB4/gYqTYO5uUv0847l78S94RmYE7XI4HLO/KYliskXaa2KVM8ki5b847LOZnBtGsjyfxl2rlnq0fSFfK4ayy7Ma2/Y1pfR9Jlq0fSNdn7OxM+yZ9S6iSl1HtKqfeVUqOex1ZKfV4p1aqUenP43yXp7rOrqytdhainrs4n4gm9d88Uj6TLebxzSZbJVLzOO1JtHMzLX6addza3KVs90i5HENNyhaTLtHPYNI+ky3kcyWDatZFk/jLt3LPVI+my1eOI5r77XuOcc34T9S8VTOs3uTblnUfSZasnUSb0NppSygesBk4AtgMblFJrtdZvj1j1Ca31VVL7TWZmRy88hYUyL9iRet2J5GtTTCuTrR5Jly2vzYnHROQdqTYO5uUv0847m9uUrR5plyOIablC0mXaOWyaR9LlPI5kMO3aSDJ/mXbu2eqRdNnqcURjWr4wra8j6bLVI+my1ZMoE/0E86HA+1rrLVprP/A4cPo426RNaDZpUzwNDTJfAwvNSmuKR9LlPN65JMtkKJ7nHak2DublL9POO5vblK0eaZcjiGm5QtJl2jlsmkfS5TyOZDDt2kgyf5l27tnqkXTZ6nFEY1q+MK2vI+my1SPpstWTKBP9IqA6YFvE79uBxTHWO1MpdRSwEfh3rfW2kSu0tLRw8cUXk5ubSyAQYPny5axYsYKmpiaKi4vx+Xx0d3dTXV3N5s2bKS8vp7q6mubmZkpKSgDYvXs306dPp7W1FaUU06ZNo7W1ldLSUgKBAD09PdTW1tLU1EReXh49PT3k5+dTVlaG3++nt7c3vDw/P5+pU6fS3t5ORUUFvb299PX1hZcXFhZSVFREZ2cnhxySS1ubZsoURUPDIAsX5tLS0kJ+fj5dXV1UVVXR1dXFwMBAePuioiKmTJlCIBAIxzw4OEhhYSEDAwP4fMGvlgUCAfLy8hgcDCZen8/H4OAgPp8PrTVDQ0Pk5eUxMDCAUgqfz0d/fz/5+flxlw8ODpKbm8vQ0FDU8pycHHJycsLLR5YpJycHpVRUmbXWUduPXA7B98b09fWFZ2RNJabQ8tB+0okp8i5QOjENDAyE95VOTKHlIVKNKbQ8skypxNTf3097e3tUezIMz/POwQfnsmuXxueDjRsDzJ+fS2vr0Kjj5GXe8fv9lJSU4Pf7o/JKvLzT09NDUVHRqLo3Le/4/f6oNu7yTubyzsDAQLjuXd4xj6amJpHJaqQ8kq6BgQGRiU9s9Ui6nMeRDFJtfOHC3JiT/E1UecC8c89Wj6TLVo8jGtPyhWl9HUmXrR5Jl62eRJnoAeZEeAZ4TGvdr5S6DPgJsGTkSjU1Naxfv37UxpGNu6KiAoC99tor/PL1yOWVlZUAzJw5M+b2I7dpa2uL+RL3yG1Cg9eRsy5GLi8tLWXbtvfZsuXjd6Ns2DDAddfVAFBeXg5AcXFx1Pbd3d3k5uaGX9rt8/lQSpGTkxN1AoWWhwZJQuuOJHKbvLy8US8Dj1we2j7SE2/5WGWKt32s5ZFlSiWm0PLQgEU6MUGwoUbeDUolpoKCAgYGBqLqMZWYQowsU7IxxStTsjEVFBRQWloa1Z6ycLBHNO/s2DG6jUMw50xU3hnpiVweK+8UFxeHzy+T805ubm7MNu7yzsfLJfPOyLp3ecccItuvCR5JV06OzBfwbPVIupzHkQxSbby9fWj8lRJAMn+Zdu7Z6pF02epxRGNavjCtryPpstUj6bLVk/D+PN3baHYAMyN+33v4szBa63atdf/wrw8BB6e701gX0BPpGRiQeS+KUjLvH0rEs337dpYtW8anP/1pDjvsMNasWRNe1tnZyWc/+1kWLVrE5z73OT766CMAfv7zn3PEEUfwL//yLyxdupS///3v4W2uuuoq5s6dy+GHH55ymRJB2hMvprGOz9NPP81hhx1GZWUlb731lkh5IsuULNu3b2fmzJl873vfi/IEAgGOPvpozj777PC6Wmtuv/12DjnkEBYvXpz27KgThOd5R6qNg3n5y6u26XXOSaRMiSLp2bhxIyeeeCK1tbXhNhtizZo1HH744Rx22GE88MAD4c//9re/ccIJJ3DUUUexZMkS/u///k+sPKnwl7/8herqan71q1+FP9trr7046qijOOqoozj33HPDn//gBz/g4IMPZtq0abS3t6dd5smEablC0mVr3pGKS9KllIobU19fH8cffzxHHnkkhx12GHfeeWd4uz/+8Y8cc8wxHHXUUZx88sn84x//ECtPMjz66KPMmTMnnF8eeeSRsOess85i1qxZUf0cgM985jPh9RcsWMB5550nUvbJgGnXRpL5y+WdsZHOX+vWreOII44I913+/Oc/h5fHa7svvfQSxxxzDIcffjhXXnml2ORWUv0dpRTbt29n+fLlLF68mE9/+tN88MEHAHzpS1/iyCOP5IgjjuDCCy9k9+7dImWfDJiWL0zr6yTicnln7P4OBCdvvPDCC1m8eDGLFy/mf//3fwG46KKLwn2GAw88kCVLRj2TlnJ5kuGDDz5gxowZ4bJcd911Yc/tt9/O/vvvH/VAG0B/fz8XXXQRBx98MMcff3w4H6XDRD/BvAGYo5SaTXCA52zg3MgVlFJ7aa13Dv+6DHgn3Z12d3eHn2Y2wVNb62PbtvTuvBW/fg5DQ0MidyiGhoboPfSJMdfJzc3ltttu48ADD2TXrl0sWbKEY445hvnz53Pvvfdy9NFHc+211/Ltb3+be++9l1tvvZVPfOITPPvss5SXl/PCCy9w7bXX8tvf/haAc889l0svvZQrrrgi5v5CX4tOF2lPvJjGOj6f/OQneeSRR7juuuvEZz5NJbYbb7yR4447bpRnzZo1zJ07l127doWXPfroo+zYsYPXXnuNnJycbH1C0PO8I9HGQ5iSv4pfPwdALO90HPDjMc9fr3MOmJl3KioquOuuu1i3bl3UsrfffptHHnmE3/72t+Tn5/O5z32OpUuXss8++3DLLbfwla98hRNOOIEXXniBb3zjGzz33HMi5Uk2rkAgwDe+8Q2OPfbYqM8LCwt56aWXRq2/ePFili5dymmnnZZWWScjpuQKSZfteUcqV0i6AoFA3JgKCgp4+umnKSkpYWBggJNPPpnjjz+eQw45hP/4j//gpz/9KfPmzeOHP/wh99xzT9QFq5dxffazn+Xuu+8e5fnSl75Eb28vP/7xj6OWRebXCy64gM985jMpl3eyYdK1kVR5XN5JDOn8Fbo5pZSioaGBiy66iNdeew0gZtsdGhriyiuv5Omnn2a//fbjm9/8Jo899hhf+MIXRMoj0d8JBAJcccUVXHfddRx77LHs3r07fE7dcccd4W8e3njjjTz00ENce+21aZd9MmBSvpDySI7tgMs7ibrGiumGG27guOOO4yc/+Un4NZUAP/rRj8KOm266SewJ9lRimzVr1qjrqUAgwNKlS7nkkks45JBDopb99Kc/pby8nDfeeINf/OIX3HrrrVHxpMKEPsGstR4ErgJ+TXAA52da6wal1Cql1LLh1a5WSjUopd4CrgY+n+5+q6ur01WIejZtknkxfY7QHZxEPLW1tRx44IEATJ06lblz57JzZ3A87vnnnw/fUT7nnHPCHfXFixeHv3p/yCGHhNcHOPzww8dMxFKJQ9oTL6axjs+8efOYM2eOaHlSdT333HPU19czf/78KM+OHTt44YUXOP/886PWf/jhh/nyl78c/mMn1Qa8ZCLyjlQbB/Pyl1TeGe/89TrnJFKmRJH0VFdX86lPfWqUc+PGjRx88MFMmTKF3NxcDj/8cJ599lkgeOc6dKOou7ubvfbaS6w8yfL973+f0047LeHz75/+6Z/4xCc+kfR+HOblCkmXrXlnovsE8TzxYlJKhV/JNDAwwODgYPiJG5PyTjzP0UcfHS5/LLq7u3n55ZfdAHMSmHZtJJm/XN4ZG+n8VVJSEs4nPT09Uctjtd2Ojg7y8/PZb7/9ADj22GNH3YxPpzzJEqu/s3nzZgYHB8ODziUlJUyZMgX4+LV2Wmv6+vpEn8y0HdPyhWl9HXB5J1FXvJi6u7t55ZVXwmMjofmQItFa8/TTT3PmmWeKlUfKc8ghh8ScfHLdunXhuj399NN56aWXoub9SYWJfkUGWut1Wuu5Wut9tdZ3DH92s9Z67fDPN2itF2qtD9RaH6u1fjfdfXZ0dKSrEPXMmiXzNQqNzNdDkvV88MEH/PWvf+Xgg4NvEWhpaQmfwFVVVbS0tIza5r//+7+jnpqNx8MPP8zDDz886knfRx99lAMOOIBly5ZxyimncPnll4fXCQ2Wfv7zn+e0007juOOO4/bbb0drTXt7O4sXB+dzu//++/n5z38OBAcx+vv7Oe200zjttNM4/vjjw8tiEevJ43gxjTw+43lGsmbNGk477TROPvlkzjnnHLq7uwG4+uqrmTNnDldddRXr169n2bJlnHrqqSxdupS//e1v43p3797Nfffdx1e+8pVRZfra177GrbfeOuqu6T/+8Q+eeuoplixZwuc+9zk2b9487n5MxOu8I9XGwbz8JZV3knma34ucM7JMqeacjz76iMMOOwxIL+eMLM9IPvnJT/LnP/+Zjo4O9uzZwwsvvMCOHcE3v3zzm9/klltuYf/99+fmm2/mhhtuGHM/q1at4rTTTuPEE0/kiiuuYGAg+M7ws88+m3333Zc77riDX/7yl+FjsWzZMrZv3z6mE+DDDz/kueee46KLLhq1rL+/nyVLlnDCCSeIPF3tMC9XSLpszTtSfZ1M5p2RMYWeNJw3bx7HHHMMixYtAuC+++7jX//1X1m4cCFPPPEEV1111Zj7WbFiRbhMX//614FgP+W0005j9uzZ/OhHP2LNmjUsW7ZsVH9oPJ555pnw185DuSqRul+3bh1HHXVU1HwGjrEx7dpIMn+5vOPNNRZ8fIyeffZZFi9ezNlnnz3qtWAjqaysZHBwMPwasF/96lfhflA8vO7vbNq0ibKyMi644AKOPvpobr755qjjv2LFCubPn8+mTZu49NJLx92PI4hp+cK0vg64vJNuf6exsZGqqiquuuoqjj76aK6++upRN75effVVampqmDVr1pj7ydTYDgTr7uijj+bUU0/l1VdfjRlXJDt37qSurg4IDkSXlpamff5O9CsyJoR0R+WlPYKvB/Oc3bt3c+GFF/LNb34zZgdcKTXqDuzLL7/MT3/6U55//vlx/aGvNfn9/lHLzjrrLG655RYArrjiCn73u99x4oknhpeHvjY1NDTE6aefzvr16zn00EPZtWsX/f39vPzyy1x//fXs2bOHqqoqCgoKeOaZZ4DgnfIlS5Zw5JFHxrzbM5J4MY13fBLh8ssv5/LLLweCX5964oknuPTSS7nppptoaWnhv/7rvwB46qmnyM/P58UXX+Tb3/42P/nJT8b0futb3+KKK64Y9QTAb37zG6qrqznooIP405/+FLXM7/dTUFDA73//e5555hm+9KUviT0dYDOSbdy0/OU1XuWcWKSSc4444oiM5JyRzJs3j6uvvpozzzyTKVOmcMABB4RvED388MPccccdLFu2jKeeeorrrrsu6v3HI7n55pvDP1922WX8/ve/Z+nSpdxwww08/PDD3HjjjQCceuqp5Ofn88gjj/Dggw9y2223jVnGr33ta9xyyy0xv+73+uuvU19fz9atWzn99NNZsGABs2fPTvo4OD7GxFzh8k5spPs6mco7sWLy+Xy89NJLdHV1cf755/P222+zYMECHnjgAZ544gkWLVrE/fffzy233BLur8Ri9erV4Z9PPvnksOeLX/wimzZtCg/UXHTRReTn50f1h8bipJNO4swzz6SgoIAf//jHrFixYsz8F8kvfvGLUd/kcoyNaddG2ZpzIPvyTiausU499VROPfVUXnnlFe68806eeuqpuOsqpXjooYe48cYb8fv9HHvsseO+C9fr/s7g4CCvvvoqf/zjH9l777256KKLePTRR8N5ZvXq1QQCAb761a/y1FNP8W//9m9j7scRxLR84fJOfLIh78SKaXBwkLfeeou77rqLRYsWsXLlSu69995wjoBgn2H58uXjujM1tjN9+nT++te/Mm3aNN58803OO+88XnnlFQoLC8ctkyQT/gTzRGDa1x82bpzYCQhS9QwMDHDhhRdy1llnRb0fs6amhqamJgDa2tqijlNDQwPXXHMN//M//8O0adMSLtN4XxGor6/nww8/jLksJyeHww47jM2bN5Obm0t9fT0nnXQS8+fP59Of/jQvv/xy+EmfEMXFxSxcuJBNmzZx++23h1+WHqs88WKKd3wiSXYSgNmzZ4eP7fvvvx/1jp9QmfbZZ5/wOg899FC47JFfWwF44403uPXWWznwwANZs2YN3/3ud/nBD37AG2+8wfPPP8+BBx7IJZdcwssvv8xll10GwIwZM8KxnHrqqTQ0NCRV/smKVBsH8/KXVN5J5GtAXuac8cqUaM6B4Puw0s0545UH4Pzzz+cPf/gDzz33HOXl5eGviT722GPh43XGGWckNcnf7Nmzw7njnXfeifq6W6ycE6/sAG+++SaXXHIJBx54IGvXruXLX/5y+Gnl0KQTs2bN4ogjjuCvf/1rwmV0xMa0XCHpsjXvSPV1QD7vjBdTWVkZRxxxBL/73e9oa2vj73//e/hp5uXLl/P6668ndhCIzinx8k5kf2jFihUcddRR/L//9/9GuaZNm0ZBQQEQzJFvvvlmlCce7e3t/OUvf4m6uHWMj2nXRpL5y+Wd0WTiGitWmQ4//HC2bt067mS/hx56KOvWreO3v/0thx12WLgflAhe9HdmzpzJAQccwKxZs8jNzeWUU04Z1d/x+XwsX748PDDmGB/T8oVpfR1weSfd/s6MGTOYMWNGuF9z+umnR7XdwcFBnn32WT772c8m9WoLybGdgoKCcHkPOuggZs+eHT5G8dhrr73C3/QYHByku7s76evlkUzKAebm5majPPPnyzxIPjQkc7csEY/Wmquvvpq5c+eyYsWKqGUnnXQSjz/+OBD8usPJJ58MBGcnveCCC3jggQeS+oMPhL+yNF6ZIPh1hpHk5OQwNDTEwMAA++67LytXruS2225j586d3HXXXVx88cVR6+/Zs4eGhgbmzJnDTTfdxEsvvRT1wvRQeeLFNNbxiWRw8ON3Rn344YecccYZ48Y5NDQU9f/IMkUuu+SSS8JlH/n+w3Xr1vHWW2/x1ltvcfnll/Pv//7vXHrppaxcuZKGhgbeeustHnroIY488kgefPBBIDiz+ssvvwzA+vXrk67HyYpUGwfz8pdU3hmvjXudcxItE4ydcyDYeUg35yRSntCkm9u3b+fZZ5/lrLPOAoLvVVu/fj0QnGE99GTwG2+8MeYkhyPjTCTnxCs7BC+4Qjln2bJl/Od//iennHIKH330UXi29Pb2dl577TXmzZs3brkcY2NarpB02Zp3pPo6IJt34sXU1tZGV1cXAL29vbz44ovMnTuX8vJyuru7ef/99wH4wx/+EN7u2WefZdWqVePGmUxfZ/Xq1bz00kv87Gc/G+UJXZRB8D2Sc+fOHeWJxdq1a1m6dKnnT/5kO6ZdG0nmL5d3vLnGCpVpy5Yt4f2+9dZb+P3+cQc+Qv2g/v5+7r//fs477zyEZQcpAAAgAElEQVTAnP7O/vvvT1dXF21tbUCwTzZv3jy01mzZsiVchueffz48X49jfEzLF6b1dcDlnXT7O9OnT6euro5NmzYB8Mc//jHqWuXFF19kzpw51NXVhWPzemynra0t/DqMrVu3smXLFmbNmjXmsT755JPDdfurX/2KI488Mu0bG5PyFRljTegxEZ7W1vRnPQVvn2B+7bXXeOKJJ1iwYEH47s/Xv/51TjjhBK699louuugifvrTn1JXVxf+OsPdd99NR0cHX/7yl4HgXZnf//73QLCxrF+/nvb2dhYuXMjKlSs5//zzw+9CjfUVxSeffDL8RMwHH3wQnml35OyYkfh8PubMmcNtt93GD37wA3w+H3feeSf77LMPfr8//FL2/v5+rr/++rhfoQg9eRwvprGOz7PPPstXv/pV2tvbOf/88znggAP4xS9+QXNzc8wnmtesWRN+yq+lpYU9e/Zw7LHHRn3tav369dx5550opejr6+O9995j9erVYw5uj3WM4nHttdfyxS9+kQceeIDi4mLuu+++pP2TEak2DublL6m8M97T/F7nnC984QujypRKzgHYb7/90s45oWPU3NzMkiVL2LVrFzk5OaxZs4ZXX32V0tJSLrzwQjo6OsjLy+Puu+8OTz5x3333ccMNNzA4OEhBQQH33HMPEOwYxho8WbVqFRs2bAjHmZ+fP+pJgF/+8pf86Ec/QilFV1cXTU1NPPnkk+FB7WR47733uO6668KdxWuuuSb8vrUHH3yQ+++/n5aWFo488kiOP/547r///qT3MRkxLVdIumzNO1J9HZDNO/Fiam5u5sorryQQCDA0NMQZZ5zB0qVLAbj33nu58MILycnJoby8nO9+97tAcC6HqVOnjtrPihUr+OCDD4Dge0rfeuutUXNXrFmzhmeffRalVFR/KNYThCG+//3v8/zzz5Obm0tFRUX4VRw+n4/PfOYzbNq0iZ6eHhYuXMj9998fft/iL3/5S6655poxj7FjNKZdG0nmL5d3vLnGCrmeeeYZHn/8cfLy8igsLOSHP/xhuA7itd3vfe97/PrXv0ZrzRe+8AWOPvpowJz+Tn5+PqtWreKMM85Aa81BBx3EBRdcgNaaK6+8kl27dqG1Zv/99+fb3/520v7Jimn5wrS+Dri8k25/B4KvF73sssvw+/3MmjUr6rVfTz31VHhfoWPt9dhO6FVCeXl55OTk8J3vfIeKigoGBwe55ZZbePLJJ9mzZw8LFy7k/PPPZ+XKlZx33nlcfvnlHHzwwVRUVPDQQw/F9SeKyuZ3xETy6quv6tAF6Xi0t7dTWVmZ9j6lPDfc8Du2bo3+asdjj439lbzu7u5R78UZHBwUmW1SyiPpmgyeH/zgB+y9997hu4ImlCkVYp2bf/nLX9447rjjFqVbNtNINO/EauMwfjuPxUTlr1j1Cuacd9IeSZepnptvvjk8CddElkfC5fLOaOK18eLXzxn1Wc+ix5L2pILLO954JF3Snssuu4w77riDqqoqI8qTDpMl70zENZZUvymV8ri8M7EeSZdp/R2XdxInmbwTK1+svf7hmOt60d+RyjsmtynbPJKukMeWsR1ILu9MyldkhL6Ka4qnulqmGpKZHdQLj6RrMnguvfTSlBPQSFc6SNa/I4hUGwfz8pdp553LX4l7Vq1alfLFlmR5pF2OIKblCkmXqW3KFI+kS9rz4IMPpjy4nInyOGQx7dpIMn+Zdu7Z6pF0mdbfmSx5Ryl1klLqPaXU+0qplWOsd6ZSSiul0hocNy1fmNbXkXTZ6pF0hTyTdWxnUr4iY/r06UZ53n13cPyVEiAvL88oj6TLebxzSZbJESReG0/2SUIwL3+Zdt7Z3KZs9Ui7HEFMyxWSLtPOYdM8ki7ncSSDaddGkvnLtHPPVo+ky1aPySilfMBq4ARgO7BBKbVWa/32iPWmAtcAr6W7T9PyhWl9HUmXrR5Jl62eRJmUTzCHJgAwxTN37tjvxEmUyAnjTPBIupzHO5dkmRxBpNo4mJe/TDvvbG5TtnqkXY4gpuUKSZdp57BpHkmX82QH4z0xqJS6XCn1N6XUm0qpPymlFkQsu2F4u/eUUkvTKYdp10aS+cu0c89Wj6TLVo/hHAq8r7XeorX2A48Dp8dY7zbgW0Bfujs0LV+Y1teRdNnqkXTZ6kmUSTnA7OVkeIkwSb4t43BMWiTbuGn5y+FwmImJucLlHYdDnognBk8GFgDnRA4gD/Oo1voArfVBwN3APcPbLgDOBhYCJwH/37Av1bKkumkUUv0ml3McDs+pA7ZF/L59+LMwSqlPATO11s9J7NC0fOHyjmMyMylfkTFt2jSjPLEmsRgPpRR+v5/8/PzwZ+PNDpooUh5Jl/N450rH4/f73R/VGKTSxuMxUfkrVs4BM867THgkXc6TWZfLO7Exra+Timuy5R1T2pTzjI9heSf8xCCAUir0xGD4K+la6+6I9YuB0CzvpwOPa637gX8opd4f9r2aSkEm8tooFqmUx+WdifVIumzzGJZ3UkIplUPwBtfnx1qvpaWFiy++mNzcXAKBAMuXL2fFihU0NTVRXFyMz+eju7ub6upqCgsVBx+cy8aNAebPz6W1dYiWwCy6h6qp873LzqG55BCgOmcrjY2NlJaWEggE6Onpoba2lqamJvLy8igqKqKxsZGysjL8fj+9vb3h5fn5+UydOpX29nYqKiro7e2lr68vvLywsJCioiI6OzspLi5m586d+P3+8PKioiLy8/Pp6uqiqqqKrq4uBgYGwssLCgrIy8sjJycnHLPWmqGhIQYGBsLnTiAQIC8vL/xUqs/nY3BwEJ/PF14/Ly+PgYEBlFLh5Tk5OQwMDMRdnpuby9DQUNTynJwccnJywssDgUB4ndBypRSBQCCqzJHbj1wOhPcViiHVmELHpL+/P62YQmUOxZVqTJH1FCpTKjGFlvt8Pvr7+9OKKeQfHBxMOaZAIEBvby+dnZ1Mnz6d1tbWMfPQpBxgbm1tpb6+3hjPnDm5bNgwkNQ2JSUl7N69m76+j79V0tPTQ3FxcdrlkfJIupzHO1c6HqUUJSUlaZfBNlJp4/GYqPwVK+eAGeddJjySLufJrMvlndiY1tdJxTXZ8o4pbcp5xsewvBPricHFI1dSSq0ArgPygSUR2/55xLZ1pMhEXhtJlcflnYn1SLps8xiWd+KxA5gZ8fvew5+FmArsD7w4PEhVC6xVSi3TWr8eWqmmpob169ePkke254qKCiD4BPMbbwQH8kJ5o8a3lRrfVgD2yXkj5vahCWdDnzU2NsbMF5GfhY5/aWlpzOWlpaWjPJE/l5eXA0SdB/X19Wit2b17N1pr+vv7gfjnS2h5PGItj3TFWh752VjLEynTeP5YnlRiivSkE1Po57HKlEhMiZQpke1HesYq81jOWHWWSkxKKWpqasKDyjNnBpt3S0tLzHJPygHmyIRggqepafRd+liTf8HHE4AppZg6dWrUskAgIFImKY+ky3m8c0mWyREkVhtPlYnKX7FyDph33tncpmz1SLscQUzr66Timmx5x8Q25Tz2oLVeDaxWSp0L3ARcmMh2yTxJ6Pf72bZtG9XV1TQ3N4cHY3bv3h315NO0adNobW2N+yRhT88QhxySx44dAYqLFeXlOTQ0DNLY2JjUk4R5eXlJP0k4MqaOjg601uTn59PZ2ZlyTGVlZbS1teHz+ejr60v56cjKykp27dpFd3c306ZNSyum6upqdu7cGX5aO9WYysrK6OvrizrOqcQU2n7nzp34fL6UYwqdewMDA6OeuksmptBTrKFyphNTU1MTQ0NDFBUVpRVTR0fHqHoyjA3AHKXUbIIDy2cD54YWaq27gKrQ70qpF4H/iBxcThap66yJ7DdlcmxH0mWrR9JlqydRJuUAc+ixb1M8eXlS7yszKy5Jl/N455IskyOIVBsH8+rZVo+ky3m8dTmC2FzPzuOdy3mygvGeGBzJ48ADiW6bzJOEFRUVo54KBKisrAQ+fvJp5PKR2/T1vcPbb0c+wRwYtU0iTxK2tbWF3SOXx3uScGRMU6ZMAaCtrS2tmEL7GqtMicQUWi8vL4+CgoK0YgrFEYol1ZggOJFUrOXJxBRZppArlZhCy7XWYU8qMYUYWfepxFRfX09bWxvl5eVpxQSj6ynek4QTgdZ6UCl1FfBrwAf8SGvdoJRaBbyutV4rvU9bx1Jcn8A7j6TLVk+iTMpJ/np6eozyVFbKVINpcUm6nMc7l2SZHEGk2jiYV8+2eiRdzuOtyxHE5np2Hu9czpMVhJ8YVErlE3xiMGoQRyk1J+LXU4BNwz+vBc5WShUMP3E4B/jfVAti67WRpMt5vHPZ6jEdrfU6rfVcrfW+Wus7hj+7Odbgstb6mHSeXgbz8oVpHkmXrR5Jl62eRJmUTzDX1tYa5WloGBTxmBaXpMt5vHNJlskRRKqNg3n1bKtH0uU83rocQWyuZ+fxzuU85pPgE4NXKaWOBwaAToZfjzG83s8ITgg4CKzQWqf8uJOt10aSLufxzmWrxxGNafnCNI+ky1aPpMtWT6JMyieYm5qajPIsXCgzzm9aXJIu5/HOJVkmRxCpNg7m1bOtHkmX83jrcgSxuZ6dxzuX82QH4z0xqLW+Rmu9UGt9kNb6WK11Q8S2dwxvN09r/Xw65bD12kjS5TzeuWz1OKIxLV+Y5pF02eqRdNnqSZRJOcCcl5dnlKevT4t4TItL0uU83rkky+QIItXGwbx6ttUj6XIeb12OIDbXs/N453IeRzLYem0k6XIe71y2ehzRmJYvTPNIumz1SLps9STKpBxgLisrM8qzY4fMi7dNi0vS5TzeuSTL5Agi1cbBvHq21SPpch5vXY4gNtez83jnch5HMth6bSTpch7vXLZ6HNGYli9M80i6bPVIumz1JMqkHGBua2szyrPvvjJf6zAtLkmX83jnkiyTI4hUGwfz6tlWj6TLebx1OYLYXM/O453LeRzJYOu1kaTLebxz2epxRGNavjDNI+my1SPpstWTKJNygNm0uwG23nWTdDmPdy53d10e9wRz9nkkXc7jrcsRxOZ6dh7vXM7jSAZbr40kXc7jnctWjyMa0/KFaR5Jl60eSZetnkSZlAPMfr/fKE9xsRLxmBaXpMt5vHNJlskRRKqNg3n1bKtH0uU83rocQWyuZ+fxzuU8jmSw9dpI0uU83rls9TiiMS1fmOaRdNnqkXTZ6kmUSTnA3Nvba5SnvFymGkyLS9LlPN65JMvkCCLVxsG8erbVI+lyHm9djiA217PzeOdyHkcy2HptJOlyHu9ctnoc0ZiWL0zzSLps9Ui6bPUkityLQbOI2tpaozwNDYMiHtPiknQ5j3cuyTI5gki1cTCvnm31SLqcx1uXI8iqVRvZs+e9UZ+vvT45j4n17DzeuZzHkQy2XhtJupzHO5etHkc0puUL0zySLls9ki5bPYkyKZ9gbmpqMsqzcKHMOL9pcUm6nMc7l2SZHEGk2jiYV8+2eiRdzuOtyxHEtL6FpMt5vHM5jyMZbL02knQ5j3cuWz2OaEzLF6Z5JF22eiRdtnoSZVIOMOfn5xvl2bNHi3hMi0vS5TzeuSTL5Agi1cbBvHq21SPpch5vXY4gpvUtJF3O453LeRzJYOu1kaTLebxz2epxRGNavjDNI+my1SPpstWTKJNygHnq1KlGeVpaZGY+NS0uSZfzeOeSLJMjiFQbB/Pq2VaPpMt5vHWZilLqJKXUe0qp95VSK8dY70yllFZKLUpnf6b1LSRdzuOdy3kcyWDrtZGky3m8c9nqcURjWr4wzSPpstUj6bLVkyiTcoC5vb3dKM+sWTJf6zAtLkmX83jnkiyTI4hUGwfz6tlWj6TLebx1mYhSygesBk4GFgDnKKUWxFhvKnAN8Fq6+zStbyHpch7vXM7jSAZbr40kXc7jnctWjyMa0/KFaR5Jl60eSZetnkSZlAPMFRUVRnm2bZO562ZaXJIu5/HOJVkmRxCpNg7m1bOtHkmX83jrMpRDgfe11lu01n7gceD0GOvdBnwL6Et3h6b1LSRdzuOdy3kcyWDrtZGky3m8c9nqcURjWr4wzSPpstUj6bLVkyiTcoC5t7fXKE95uRLxmBaXpMt5vHNJlskRRKqNg3n1bKtH0uU83roMpQ7YFvH79uHPwiilPgXM1Fo/J7FD0/oWki7n8c7lPI5ksPXaSNLlPN65bPU4ojEtX5jmkXTZ6pF02epJFLnvbWcRfX1pPxgk6pk6NQdI/86baXFJupzHO5dkmRxBpNo4mFfPtnokXc7jrSsbUUrlAPcAnx9v3ZaWFi6++GJyc3MJBAIsX76cFStW0NTURHFxMT6fj+7ubqqrcygsVPh8sHFjgPnzc2ltHaIlMIvuoWrqfO+yc2guOQQo3rOH1tZWSktLCQQC9PT0UFtbS1NTE7t27aKkpIS2tjbKysrw+/309vaGl+fn5zN16lTa29upqKigt7eXvr6+8PLCwkKKioro7OzE7/czNDSE3+8PLy8qKiI/P5+uri6qqqro6upiYGAgvDw6pmo6Ojro7OykrKyM5uZmSkpKANi9ezfTp0+ntbUVpRTTpk2LG1NeXl54+4KCgrRiqqyspK2tLWp5KjFprfH7/fT19aUVU6ie2tvbo8qUbEy7du3C7/cTCARobGxMOabq6mqam5vp7e0lNzc3rZj8fj/Nzc2Ul5enFVNtbS3Nzc0opdKKKVY9TXZsvTaSdDmPdy5bPY5oTMsXpnkkXbZ6JF22ehJlUg4w19bWGuVpaBgU8ZgWl6TLebxzSZbJEUSqjYN59WyrR9LlPN66DGUHMDPi972HPwsxFdgfeFEpBVALrFVKLdNavx4pqqmpYf369aN2UF9fH/65oqKCN97YGDWz+oYNA8HtfVup8W0FYJ+cNwDomTIlavuqqqqws7+/n4KCAoqLi8fcZ2iwrbS0NOby0tLSsCvW8vLycoCo/YyMCWDKlClUV1dTUFAQtbyyshKAmTNnxtw+MqYQ8+bNiypPKjEB7LfffmFPqjEBo45PKjGF9lVUVBSzTInGFFpvZJmSjSm0PORJJyaAsrKyUXWfbEwQXfepxhQiMqbJPshs67WRpMt5vHPZ6nFEY1q+MM0j6bLVI+my1ZMok/IVGU1NTUZ5Fi6UGec3LS5Jl/N455IskyOIVBsH8+rZVo+ky3m8dRnKBmCOUmq2UiofOBtYG1qote7SWldprWdprWcBfwZGDS4ng2l9C0mX83jnch5HMth6bSTpch7vXLZ6HNGYli9M80i6bPVIumz1JMqkHGAuLCw0yrNr15CIx7S4JF3O451LskyOIFJtHMyrZ1s9ki7n8dZlIlrrQeAq4NfAO8DPtNYNSqlVSqllmdinaX0LSZfzeOdyHkcy2HptJOlyHu9ctnoc0ZiWL0zzSLps9Ui6bPUkyqR8RUZRUZFRno8+0uOvlACmxSXpch7vXJJlcgSRauNgXj3b6pF0OY+3LlPRWq8D1o347OY46x6T7v5M61tIupzHO5fzOJLB1msjSZfzeOey1eOIxrR8YZpH0mWrR9JlqydRJuUTzJ2dnUZ5Zs70iXhMi0vS5TzeuSTL5Agi1cbBvHq21SPpch5vXY4gpvUtJF3O453LeRzJYOu1kaTLebxz2epxRGNavjDNI+my1SPpstWTKJNygDk0GYcpnq1bZV5Mb1pcki7n8c4lWSZHEKk2DubVs60eSZfzeOtyBDGtbyHpch7vXM7jSAZbr40kXc7jnctWjyMa0/KFaR5Jl60eSZetnkSZlAPMu3btMspTUyNz1820uCRdzuOdS7JMjiBSbRzMq2dbPZIu5/HW5QhiWt9C0uU83rmcx5EMtl4bSbqcxzuXrR5HNKblC9M8ki5bPZIuWz2JMikHmP1+v1GeKVOUiMe0uCRdzuOdS7JMjiBSbRzMq2dbPZIu5/HW5QhiWt9C0uU83rmcx5EMtl4bSbqcxzuXrR5HNKblC9M8ki5bPZIuWz2JMuEDzEqpk5RS7yml3ldKrRxjvTOVUloptSjdfdbW1qarEPU0NMh8rcO0uCRdzuOdS7JMpuJ13pFq42BePdvqkXQ5j7cuRxDT+haSLufxzuU8jmSw9dpI0uU83rls9TiiMS1fmOaRdNnqkXTZ6kmUCR1gVkr5gNXAycAC4Byl1IIY600FrgFek9hvU1OThEbMs3BhrojHtLgkXc7jnUuyTCYyEXlHqo2DefVsq0fS5TzeuhxBTOtbSLqcxzuX8ziSwdZrI0mX83jnstXjiMa0fGGaR9Jlq0fSZasnUSb6CeZDgfe11lu01n7gceD0GOvdBnwL6JPYaVFRkYRGzPPRR0MiHtPiknQ5j3cuyTIZiud5R6qNg3n1bKtH0uU83rocQUzrW0i6nMc7l/M4ksHWayNJl/N457LV44jGtHxhmkfSZatH0mWrJ1HkHqtLjTpgW8Tv24HFkSsopT4FzNRaP6eU+nI8UUtLCxdffDG5ubkEAgGWL1/OihUraGpqori4GJ/PR3d3N9XV1XR3d9Pf3091dTXNzc2UlJQAsHv3bqZPn05raytKKaZNm0ZrayulpaUEAgF6enqora2lqamJvLw8cnJyaGxspKysDL/fT29vb3h5fn4+U6dOpb29nYqKCnp7e+nr6wsvLywspKioiM7OTvLygnfepkxRNDQMsnBhLh8G5lBIDx1DdUz3baZjqI4BXci0/v6YMXV0dLBnzx5KS0vTiqmsrIzOzk7y8/PTiqmyspJdu3bR3d1NWVkZTU1NFBUVkZ+fT1dXF1VVVXR1dTEwMBDePlZMWmuqq6vp7OzE5/OlHFNbWxtlZWXs2bOHxsbGtGLy+/1MmTKFxsbGtGJqbm5GKUV7e3taMYXqKVSmVGMKLdda89FHH6UcU6xzzzDE8k6i9PTodBVh8vPznccDj6TLebx1OYJI5R0T69l5vHM5jyMZpI6ry1+T1yPpstXjiMa0fGGaR9Jlq0fSZasnUSZ6gHlMlFI5wD3A58dbt6amhvXr14/6vL6+PvxzRUUFAHl5ecycOXPU8srKSoDwspHLq6qqoj5rbGyMWh5rm9BgW2lpaczlpaWlFBdvYcOGgfBnGzYM8PWjNgEwzfchAFNzOgDoKSiIGVNocLGwsDCtmAAKCwspLy9PK6bQen6/n4IRZQ65i4uLY24fGVNkmUKxpBJTaF9dXV3hz1ONCUbXfSox1dfX09jYSGVlZVoxhRhZpmRjiixTeXl5yjGFiIzJwEHmuCSTdxK9sbXvvj5qanLw+WDjxgDz5+fS2jpES2AW3UPV1PneZefQXHIIULxnz5g3F3p6eujq6kr7xlZo28ibC6ncMOns7KSwsDDtG1sffPABQNo3tnbs2EFXV1daMYVumHzwwQcEAoGUYwrdBPrwww+jypTqTaBAIEBXV1faN7Z6e3sJBAJp39gKHd90Ygot7+npAbD5xpbn1NX5+PDD9J/q6erqGtUnmGiX83jnch5HMkgdV5e/Jq9H0mWrxxGNafnCNI+ky1aPpMtWT6JM9ADzDmBmxO97D38WYiqwP/CiUgqgFlirlFqmtX491Z2GBuvSRcqzebPMi+lNi0vS5TzeuSTLZChieSfRG1sNDRvp6Pj47nrohlKNbys1vq0A7JPzBgA9U6aMeXOhp6dn1M2FkftM5ObCSE+qN0wqKipEbmztu+++o+JK5YbJrFmzwp50bwJFlimdm0B5eXkxy5TsTaCRdZbqTaCQJ90bW8XFxaNuIKZ6YytUpsl6YysTmNa3kHQ5j3cu53Ekg63XRpIu5/HOZavHEY1p+cI0j6TLVo+ky1ZPokz0O5g3AHOUUrOVUvnA2cDa0EKtdZfWukprPUtrPQv4M5DW4DIER/ElkPLU1flEPKbFJelyHu9ckmUyFM/zjlQbB/Pq2VaPpMt5vHU5gpjWt5B0OY93LucxH6XUSUqp95RS7yulVsZYfp1S6m2l1F+VUr9TStVHLAsopd4c/rd25LbJYuu1kaTLebxz2epxRGNavjDNI+my1SPpstWTKBM6wKy1HgSuAn4NvAP8TGvdoJRapZRalqn9DgwMjL+Sh57CQiXiMS0uSZfzeOeSLJOJTETekWrjYF492+qRdDmPty5HENP6FpIu5/HO5Txmo5TyAauBk4EFwDlKqQUjVvs/YJHW+p+AJ4G7I5b1aq0PGv6Xdh/I1msjSZfzeOey1eOIxrR8YZpH0mWrR9JlqydRJvoVGWit1wHrRnx2c5x1j5HYZ21trYRGzNPQIPO1DtPiknQ5j3cuyTKZitd5R6qNg3n1bKtH0uU83rocQUzrW0i6nMc7l/MYz6HA+1rrLQBKqceB04G3Qytorf8Qsf6fgfMyVRhbr40kXc7jnctWjyMa0/KFaR5Jl60eSZetnkSZ8AHmiaCpqSnm5HwT5Vm4MDdqkr+JLo+UR9LlPN65JMvkCCLVxsG8erbVI+lyHm9djiCm9S0kXc7jnct5jKcO2Bbx+3Zg8RjrXww8H/F7oVLqdWAQuEtr/fTIDRKd0Li6uprNmzdTXl4+5gSsiUwqu2hRLr29sGNHgOJiRXl5Dg0NgzQ2NiY9oXFo0vF0J//1+/3k5uamNaFxW1sbfX194XKnM/lva2sr8+bNS3tC440bN1JXV5dWTKEJjYuLi9Oe0Li2tpb33nuP2tratCY0LikpobW1laKiorQmNA5NjOzz+UQmNJ4xY4bohMbD88VMakzr75jmkXTZ6pF02epJlEk5wBxrgqyJ9LS3pz/rKZgXl6TLebxzSZbJEUSqjYN59WyrR9LlPN66HEFM61tIupzHO5fz2INS6jxgEXB0xMf1WusdSql9gN8rpf6mtd4cuV2iExoD7LXXXjEniE12Utnt299hy5ZAxN4Co7ZJZFLZtra2qAmO0pn8d6Qr1YlyxypTMhPl5uXljZpoN5WJcmfMmBGOJZ3JfwcHB2MuT2Xy3xkzZoRd6Uz+q2YfUzQAACAASURBVLUOe1Kd0BhG132qExq3tbVRXl4uOqExBG8CTWZM6++Y5pF02eqRdNnqSZSJnuRvQvD5ZF4EL+UZGNAiHtPiknQ5j3cuyTI5gki1cTCvnm31SLqcx1uXI4hpfQtJl/N453Ie49kBzIz4fe/hz6JQSh0P3Ehw0uL+0Oda6x3D/28BXgT+OZ3C2HptJOlyHu9ctnoc0ZiWL0zzSLps9Ui6bPUkStoDzEqpAyUK4iXd3d1GeWprZSrdtLgkXc7jnUuyTJkgG3OOVBsH8+rZVo+ky3m8dWWCyZx3TKxn5/HO5TyZJ838sgGYo5SarZTKB84G1o7w/zPwIMHB5ZaIzyuUUgXDP1cB/0LEu5tTwdZrI0mX83jnstWTSVx/xz6PpMtWj6TLVk+iSDzB/Ful1FtKqf9QSu0l4Ms41dXVRnk2bZJ5Mb1pcUm6nMc7l2SZMkTW5RypNg7m1bOtHkmX83jryhCTNu+YWM/O453LeTwh5fyitR4ErgJ+DbwD/Exr3aCUWqWUWja82n8CJcDPlVJvKqVCA9CfBF5XSr0F/IHgO5jTGmC29dpI0uU83rls9WQY19+xzCPpstUj6bLVkygSA8x7ATcTnFBik1LqN0qp85RSU8bZbsLo6OgwyjNrlsxdN9PiknQ5j3cuyTJliKzLOVJtHMyrZ1s9ki7n8daVISZt3jGxnp3HO5fzeEJa+UVrvU5rPVdrva/W+o7hz27WWq8d/vl4rfV0rfVBw/+WDX/+itb6AK31gcP//zDdQGy9NpJ0OY93Lls9Gcb1dyzzSLps9Ui6bPUkStoDzFrrQa31r7TWnyM4k/HPgK8AzUqpR5RS/5LuPqTRWuY9PVIeqdeimBaXpMt5vHNJlikTZGPOkXz1kWn1bKtH0uU83roywWTOOybWs/N453KezJON+SUetl4bSbqcxzuXrZ5Mko35yLR8YZpH0mWrR9JlqydRxCb5U0qVAGcQfPfX3sDjwCbgf5RSq6X2I4Fpj5tv3BgYf6UEMC0uSZfzeOfKkq9vZVXOkWrjYF492+qRdDmPt65MMhnzjon17DzeuZzHO7Ipv8TD1msjSZfzeOey1eMF2ZSPTMsXpnkkXbZ6JF22ehJFYpK/U5RSjxOcsfhfgYeAGVrrS7XWtwGfAi5Mdz+SNDc3G+WZPz9XxGNaXJIu5/HOJVmmTJCNOUeqjYN59WyrR9LlPN66MsFkzjsm1rPzeOdynsyTjfklHrZeG0m6nMc7l62eTJKN+ci0fGGaR9Jlq0fSZasnUSRa413AT4B/11rvHLlQa92hlLpWYD9ilJSUGOVpbR0S8ZgWl6TLebxzSZYpQ2RdzpFq42BePdvqkXQ5j7euDDFp846J9ew83rmcxxOyLr/Ew9ZrI0mX83jnstWTYbIuH5mWL0zzSLps9Ui6bPUkisQrMm7TWn97ZAJSSp0V+llr/ZDAfhwOhwNcznE4HN7j8o7D4cgULr84HA5TcPnI4XCkjMQAc7wE830Bd0bYvXu3UZ7qaplXYZsWl6TLebxzSZYpQ2RdzpFq42BePdvqkXQ5j7euDDFp846J9ew83rmcxxOyLr/Ew9ZrI0mX83jnstWTYbIuH5mWL0zzSLps9Ui6bPUkSsqvyFBK7TP8Y45SajagIhbvA/SlU7BMMn36dKM87747KOIxLS5Jl/N455IskyTZnHOk2jiYV8+2eiRdzuOtSxKXd8ysZ+fxzuU8mSOb80s8bL02knQ5j3cuWz2ZIJvzkWn5wjSPpMtWj6TLVk+ipHO7532CM4lOATYP/x769whwa7qFyxStra1GeebO9Yl4TItL0uU83rkkyyRM1uYcqTYO5tWzrR5Jl/N46xJm0ucdE+vZebxzOU9Gydr8Eg9br40kXc7jnctWT4bI2nxkWr4wzSPpstUj6bLVkygpP8Gstc4BUEr9UWt9tFyRMo9SavyVPPQEAiIa4+KSdDmPdy7JMkmSzTlHqo2DefVsq0fS5TzeuiRxecfMenYe71zOkzmyOb/Ew9ZrI0mX83jnstWTCSTzkVLqJOA+wAc8pLW+a8Tyy4EVQADYDXxRa/12qvszLV+Y5pF02eqRdNnqSZSUB5gBlFI+YG+lVIHWul+oTBln2rRpRnm2bpXJiqbFJelyHu9ckmWSJltzjlQbB/Pq2VaPpMt5vHVJM9nzjon17DzeuZwns2RrfolHpq+Nil8/Z9RnPYsey3h5JF3O453LVk+mkMhHw47VwAnAdmCDUmrtiAHkR7XWa4bXXwbcA5yUarlN6++Y5pF02eqRdNnqSZS03oiutQ4QvPNUJFMcbzDtcfM5c9Ia5w9jWlySLufxzmXy17eyNedItXEwr55t9Ui6nMdblzSTPe+YWM/O453LeTJLtuaXeNh6bSTpch7vXLZ6MoVQPjoUeF9rvUVr7QceB04fsZ/uiF+LAZ3G/ozLF6Z5JF22eiRdtnoSRaI13gs8oZT6JsG7VOEEobXeIuAXp7S01ChPU5PMXTfT4pJ0OY93LskyZYisyzlSbRzMq2dbPZIu5/HWlSEmbd4xsZ6dxzuX83hC1uWXeNh6bSTpch7vXLZ6Mky6+agO2Bbx+3Zg8ciVlFIrgOuAfGDJyOUtLS1cfPHF5ObmEggEWL58OStWrKCpqYni4mJ8Ph/d3d1UV1dTXAwHH5zLxo0B5s/PpbV1iJbALLqHqqnzvcvOobnkEKA6ZyuNjY2UlpYSCATo6emhtraWpqYm8vLyyM/Pp7GxkbKyMvx+P729veHl+fn5TJ06lfb2dioqKujt7aWvry+8vLCwkKKiIjo7O8nLy2Pnzp34/f7w8qKiIvLz8+nq6qKqqoquri4GBgbCy0fG1NHRQX9/P319fTQ3N1NSUgLA7t27mT59Oq2trSilmDZtGq2trXFjKisro62tDZ/PR0tLS8oxVVZWsmvXLvr6+ujv7085Jq011dXV9PX10d7enlZMZWVlDA0N0djYmFZMoXrq6+ujpaUl5ZhC9aSUorGxMeWYQudeUVERjY2NacXU1NTE0NAQH330UVoxxaqneEgMMP/X8P8njPhcE3zvjnEEhF7UI+XJy5N6X5lZcUm6nMc7l2SZMkTW5RypNg7m1bOtHkmX83jryhCTNu+YWM/O453LeTwh6/JLPGy9NpJ0OY93Lls9GcaTfKS1Xg2sVkqdC9wEXBi5vKamhvXr14/arr6+PvxzRUUFAB98MMSWLcFju2HDQHB731ZqfFsB2CfnjZjbV1VVRX3W1tbGXnvtNeY+Q4NtkTcLIpeXlpbS1tYWdo9cXl5eDkBxcfGYMU2ZMoW2tjYKCwujlldWVgIwc+bMhGIK7WusMiUSU2i9vLw8CgoKUo4pMo5QLKnGBDA4OBhzeTIxRZYp5EolptByrXXYk0pMIdra2tKOqb6+nra2NsrLy9OKCUbXU0tLC7FI6xUZEHwhfJx/xnaIenp6jPJUVqZdDYB5cUm6Hnnkb5xzzm+i/k1keUzzSLoky5QJsjHnSLVxMK+ebfVIupzHW1cmmMx5x8R6dh7vXM6TebIxv8TD1msjSZfzeOey1ZNJBPLRDmBmxO97D38Wj8eBM1ItL5iXL0zzSLps9Ui6bPUkityoRxZRW1trlKehYVDEY1pcki5bj5GJx1qyTI4gUucvmFfPtnokXc7jrcsRxLS/m5Iu5/HO5TyOZLC13y/pch7vXLZ6DGcDMEcpNVsplQ+cDayNXEEpNSfi11OATens0LR8YZpH0mWrR9JlqydR0h5gVkrlKqWuVkr9Qin1R6XUS6F/EgXMBE1NTUZ5Fi6UeTG9aXFJumw9RiYea8kyZYJszDlS5y+YV8+2eiRdzuOtKxNM5rxjYj07j3cu58k82Zhf4mFrv1/S5TzeuWz1ZJJ085HWehC4Cvg18A7wM611g1JqlVJq2fBqVymlGpRSbxJ8D/OFcXQJYVq+MM0j6bLVI+my1ZMoEk8wfxe4DHgJOBj4BVAD/F7AnRHy8vKM8vT1pTVxahjT4pJ02XqMTDzWkmXKEFmXc6TOXzCvnm31SLqcx1tXhpi0ecfEenYe71zO4wlZl1/iYWu/X9LlPN65bPVkmLTzkdZ6ndZ6rtZ6X631HcOf3ay1Xjv88zVa64Va64O01sdqrRvSKbBp+cI0j6TLVo+ky1ZPokgMMC8HTtZa3wcMDv9/BnCsgDsjlJWVGeXZsUPmhf+mxSXpsvUYmXisJcuUIbIu50idv2BePdvqkXQ5j7euDDFp846J9ew83rmcxxOyLr/Ew9Z+v6TLebxz2erJMFmXj0zLF6Z5JF22eiRdtnoSRWKAeQqwbfjnXqXUFK31u8A/C7gzQltbm1GeffeV+VqHaXFJumw9RiYea8kyZYisyzlS5y+YV8+2eiRdzuOtK0NM2rxjYj07j3cu5/GErMsv8bC13y/pch7vXLZ6MkzW5SPT8oVpHkmXrR5Jl62eRJFoje8AhwD/C7wO3KqU6mbs2UInFNPuBth6103SZesxMvFYZ8Hd9azLOe4J5uzzSLqcx1tXhpi0ecfEenYe71zO4wlZl1/iYWu/X9LlPN65bPVkmKzLR6blC9M8ki5bPZIuWz2JIjHAfA0QatXXAQ8AU4EvCrgzgt/vN8pTXKxEPKbFJemy9RiZeKwly5Qhsi7nSJ2/YF492+qRdDmPt64MMWnzjon17DzeuZzHE7Iuv8TD1n6/pMt5vHPZ6skwWZePTMsXpnkkXbZ6JF22ehIl7QFmrfWGiJ83Acen68w0vb29RnnKy3P4OI+njmlxSbpsPUYmHmvJMmWCbMw5UucvmFfPtnokXc7jrSsTTOa8Y2I9O493LufJPNmYX+Jha79f0uU83rls9WSSbMxHpuUL0zySLls9ki5bPYki8sIapdQS4BxgBvAh8LjW+ncS7kxQW1trlKehYVDEY1pcki5bj5GJx1qyTJki23KO1PkL5tWzrR5Jl/N468oUkzXvmFjPzuOdy3m8IdvySzxs7fdLupzHO5etnkyTbfnItHxhmkfSZatH0mWrJ1HSnuRPKXU98DjQATwHtAOPDn9uJE1NTUZ5Fi6UeTG9aXFJumw9RiYea8kyZYJszDlS5y+YV8+2eiRdzuOtKxNI5B2l1ElKqfeUUu8rpVbGWH65UupvSqk3lVJ/UkotSKfMpv3dlHQ5j3cu58k82diviYet/X5Jl/N457LVk0myMR+Zli9M80i6bPVIumz1JIpEa7wOWKK1/nvoA6XUfwMvAN8R8IuTn59vlGfPHi3iMS0uSZetx8jEYy1ZpgyRdTlH6vwF8+rZVo+ky3m8dWWItPKOUsoHrAZOALYDG5RSa7XWb0es9qjWes3w+suAe4CTUi2waX83JV3O453LeTwh6/o18bC13y/pch7vXLZ6MkzW5SPT8oVpHkmXrR5Jl62eREn7CeZh3h/x+xZAbkRFmKlTpxrlaWmReTeraXFJumw9RiYea8kyZZCsyjlS5y+YV8+2eiRdzuOtK4Okk3cOBd7XWm/RWvsJPh10euQKWuvuiF+Lk3DHxLS/m5Iu5/HO5TyekVX9mnjY2u+XdDmPdy5bPR6QVfnItHxhmkfSZatH0mWrJ1EknmC+FfihUupWgk/lzAS+DtyilAoPYGuthwT2JUJ7ezslJSXGeGbNyqW1dcCY8kh5JF22HiMTj7VkmTLErWRZzpE6f8G8erbVI+lyHm9dGeJW0ss7dcC2iN+3A4tHrqSUWkHw6aF8YEksUUtLCxdffDG5ubkEAgGWL1/OihUraGpqori4GJ/PR3d3N/Pn51JXp/H5YOPGAPPn59LaOkRLYBbdQ9XU+d5l59BccghQvGcPra2tlJaWEggE6Onpoba2lqamJnbt2sXs2bNpa2ujrKwMv99Pb29veHl+fj5Tp06lvb2diooKent76evrCy8vLCykqKiIzs5O/H4/JSUl+P3+8PKioiLy8/Pp6uqiqqqKrq4uBgYGwssjY6qurqajo4POzk7mzJlDc3Nz+LzZvXs306dPp7W1FaUU06ZNixtTXl4eZWVlbNmyhU984hNpxVRZWUljYyMlJSVpxaS1xu/3R7WFVGIK1dOHH35IcXFxyjHt2rULv99PIBCgvb095Ziqq6tpbm6mt7eX6urqtGLy+/00NTUxb968tGKqra1ly5Yt1NbWphVTrHpKkVvJsn5NPGzt90u6nMc7l62eDHMrWZaPTMsXpnkkXbZ6JF22ehJFYoD5weH/zyF4Z0sN//5vw8vU8Oc+gX2JUFFRYZRn2zaZu26mxSXpsvUYmXisJcuUIbIu50idv2BePdvqkXQ5j7euDOFJ3tFarwZWK6XOBW4CLhy5Tk1NDevXrx+1bX19ffjniooKNm3aRFPTx9d/GzYEL75qfFup8W0FYJ+cNwDomTIlavuqqqqws7u7m+LiYoqLi8fcZ6jzWlpaGnN5aWkp3d3dcZeXl5cDRO1nZEwAU6ZMobS0lMLCwqjllZWVAMycOTPm9pExhZg1a1ZUeVKJKbTP0M+pxgSMOj6pxBTaV05OTswyJRpTaL2RZUo2ptDykCedmAAKCwspKChIKyaIrvtUYwoRGVOKg8xZ16+Jh639fkmX83jnstWTYbIuH5mWL0zzSLps9Ui6bPUkisQrMmZH/Nsnzu/7COxHjN7eXqM85eVq/JUSwLS4JF22HiMTj7VkmTJE1uUcqfMXzKtnWz2SLufx1pUh0s07Owg+BRRi7+HP4vE4cEYa5TXu76aky3m8czmPJ6SVXxKYQPQ6pdTbSqm/KqV+p5Sqj1h2oVJq0/C/UTe0ksXWfr+ky3m8c9nqyTCT9jrLtHp2bco7j6TLVk+ipP0Es9a6UaIgXtLX12eUZ+rUHCD9O2+mxSXpsvUYmXisJcuUCbIx50idv2BePdvqkXQ5j7euTCCQdzYAc5RSswkOLJ8NnBu5glJqjtZ60/CvpwCbSAPT/m5KupzHO5fzZJ508kuCE4j+H7BIa71HKXUFcDfwr0qpacAtwCKCTyS+MbxtZ6rlsbXfL+lyHu9ctnoyyWS+zjKtnl2b8s4j6bLVkyhSk/xlFbW1tUZ5GhoGRTymxSXpsvUYmXisJcvkCCJ1/oJ59WyrR9LlPN66TERrPQhcBfwaeAf4mda6QSm1Sim1bHi1q5RSDUqpNwm+hzmtpwlN+7sp6XIe71zOYzyJTCD6B631nuFf/0zwGxQAS4EXtNYdw4PKLwAnpVMYW/v9ki7n8c5lq8cRjWn5wjSPpMtWj6TLVk+iSLyDOetoamqKenfaRHsWLswNvxvRhPJIeSRdth4jE4+1ZJkcQaTOXzCvnm31SLqcx1uXqWit1wHrRnx2c8TP10juz7S/m5Iu5/HO5TzGk9AEohFcDDw/xrZ1IzdIdGLR6upqNm/eTHl5+ZgTISYyueOiRbn09sKOHQGKixXl5Tk0NAzy/sAhFKg9lOa00BqYRaVvG53NzRmfWDQ0CWdubm7ak3D29fWFJ6VMZxLO1tbW8ISX6UzCuXHjRurq6tKKSXJi0draWt577z2RSThbW1spKipKa2LR3t5eAoEAPp8vrZiampro6elhxowZohOLKiX3Gr5sxbT+jmkeSZetHkmXrZ5EmfABZqXUScB9BF8U/5DW+q4Ryy8HVhD83sNu4IsjvvaVNIWFhelsLu7ZtUtmElbT4pJ02XqMTDzWkmVyBJE6f8G8erbVI+lyHm9djiCm/d2UdDmPdy7nsQel1HkEX4dxdDLbJTqxaGjd6dOnj1qe7OSOLS3v8O67kV95D/68X96G8CdlOcEJFfOH9zfSWVpaSnNzc7g8I5cnO7njSFeqE1Y2NzdTU1MTc5tkJqzMyckZNeFlKhNWTp8+PRxLOpNw9vf3x6z7VCbhnD59evgYpTMJ5+DgYLhMqU4sCqPrPpWY6uvraW5upry8XHRiUQjeBJrMmNbfMc0j6bLVI+my1ZMoab0iQynlU0ptVkoVpLo9wfeGnQwsAM5RSi0YsdqjWusDtNYHEXxn2D3plBmgqKgoXYWo56OPtIjHtLgkXbYeIxOPtWSZpEk350R4xpsQ53Kl1N+UUm8qpf4UIy8lhdT5C+bVs60eSZfzeOuSRirveI1pfzclXc7jnct5MotAfkloAlGl1PHAjcAyrXV/Mtsmg639fkmX83jnstWTKVx/x6x6dm3KO4+ky1ZPoqQ1wKy1DhC8pZzqsHgi7w3rjvi1mOAkFGnR2Zny3BUZ8cyc6RPxmBaXpMvWY2TisZYskzQCOWdCbmxJnb9gXj3b6pF0OY+3Lmkk8s5EYNrfTUmX83jncp7MIpBfwhOIKqXyCU4gujZyBaXUPwMPEhxcjnzU8dfAiUqpCqVUBXDi8GcpY2u/X9LlPN65bPVkCtffMaueXZvyziPpstWTKBKvyLgX+JlS6psE390VHgDWWm8ZZ9uE3humlFpBcMKbfGBJugUOfa3EFM/WrTIvpjctLkmXrcfIxGMtWaYMkU7OgYgbWwBKqdCNrfCrd6RvbEmdv2BePdvqkXQ5j7euDJFu3vEc0/5uSrqcxzuX83hCyvlFaz2olApNIOoDfhSaQBR4XWu9FvhPoAT4+fD7Wj/QWi/TWncopW4jOEgNsEpr3ZFOIN/5zkZaW9+L+uyxx05M2uPy1+T1SLps9WQY19+xzCPpstUj6bLVkygSA8z/Nfz/CSM+1wQ7OmmjtV4NrFZKnQvcRIyZ1ZOZgGLbtm2UlJSkPQGF3++nvb09ahKAVCY22GefXGpqNFOmKBoaBlm4MJcPA3MopIeOoTqm+zbTMVTHgC5kWn9/3EkAuru72WeffdKKqaysjMbGRurq6tKKKTSxQUdHB/vtt1/aE1Acemh+eIbY6uoc3n13kG3btiU9WUNLSwsFBQVpT0CRk5NDe3t7WjE1NzczMDBARUVFWpNqhOopVKZ0J6Do7++npqZGdAIKYdLNOWI3thLNO/X1PurqwOeDjRsDzJ+fS2vrEC2BWXQPVVPne5edQ3P/f/bePTyy+6zz/L4qSa37/Wa3O9120o6JIBsm7oSH3TWXEGNgScCbLO4Ml4CHGRhnhx2HgcCQzIyzeTaBsIQZAgkkYcPNJoQAvYzZJDtJmMGBIHfwJshpt7uNCrVbJVVL3WrduiWVfvvHqSrdqlqn6nzP0Xt+9X6eR0+36vLR731/5/etqlNV56AJBXSuriaSO865fXNfz/asLXcuXbqE9vb2yCfzGR4eRjabLZ95N8oa9TV38vl8Od8td/QxMpJBPh/9RdfS0tKu40hqcJknOZd5EiFSvoQ4geh33OK+HwPwsdAjPQBW7lh+Na6H6fLVEzP2fMczD9Plq4fp8tUTlsg7mJ1zUQ6zUeuxv54A8BuVrqjlBBQdHR3lg+JHOQFFNputeEbGWk9ssLX1QnnnKQBMTGzgnfc9DwAYyFwGAHQ3BR8oWNlzMoedNWWzWbS1tUWqqTTm0skH6q2pdLv19XXKCSjm5rYwNRWc4KP0bz0na1hcXCxfHuUEFHvnvt6TNWSzWQwODkY6qUaJvWOq9wQU2WyWfgIK5s6eiJlTy9858I2tsLkj8gKeeWb77MalMx2PZKYwkpkCANzVdBYAsNLRkUjuZLNZ3HbbbRWvr2XuteVOe3t7xTVez/bc1dVFOfGNr7mztra2L98td/TQ0cE5s/z6+jrFw3SZJzmXeeInjflSDVbuWH41rofp8tUTJ2nMI215oc3DdPnqYbp89YSFFiAickxEvqnGu4U5btjJHb9+D4Dno40U5U+kafHs3LkcBW11MV2+9khjr5ljipM6Mweo742t76vj75Rhbb+Avnn21cN0mSdZV5xEyJ3E0fa4yXSZJzmXeZIjTflSDVbuWH41rofp8tWTBGnKI215oc3DdPnqYbp89YQl8g5mEXmJiDwF4ByA/7d42ZtE5CMH3dc5twmgdNywrwH4ROm4YSLyhuLN3iYikyLyDIKvq+/7FGGt5HK5qAqqZ3yccaQSfXUxXb72SGOvmWOKgyiZUyTxN7ZY2y+gb5599TBd5knWFQeE3EkcbY+bTJd5knOZJ37SmC/VYOWO5VfjepguXz1xksY80pYX2jxMl68epstXT1gYn2D+MID/DKAbQOk74J/F/uP2VMQ596Rz7m7n3Eudc+8pXvau4kkp4Jz7KefcuHPuVc65b3POTUYdcHt7e1QF1XPt2hbFo60upsvXHmnsNXNMMRE1cxJ/Y4u1/QL65tlXD9NlnmRdMREpdw4DbY+bTJd5knOZJxFSly/VYOWO5VfjepguXz0xk7o80pYX2jxMl68epstXT1gYb/e8BsD3OOe2RMQBgHNuUUR6Ce5YaG1tVeVZWXEH3ygE2upiunztkcZeM8cUE5EzJ8QJcX6KNViAt/0C+ubZVw/TZZ5kXTGRuuc62h43mS7zJOcyTyKkLl+qwcody6/G9TBdvnpiJnV5pC0vtHmYLl89TJevnrAwPsE8C+BlOy8QkVcA+EeCOxYWFxdVeY4e5ZyQVVtdTJevPdLYa+aYYiJ1mcPafgF98+yrh+kyT7KumGjY3NE4z+ZJzmWeREhdvlSDlTuWX43rYbp89cRM6vJIW15o8zBdvnqYLl89YWHsYH4/gD8XkR8F0CwipwH8IYD3EdyxMDQ0pMpz8SLnwPTa6mK6fO2Rxl4zxxQTqcsc1vYL6JtnXz1Ml3mSdcVEw+aOxnk2T3Iu8yRC6vKlGqzcsfxqXA/T5asnZlKXR9ryQpuH6fLVw3T56glL5B3MzrmPAfg3AN4MYBrBsUrf6Zz7/ajuuND2boCv77oxXb72SGOvtb+7nsbMsU8wp8/DdJknWVccNHLuaJxn8yTnMk/8pDFfqmGfYDaPJpevnjhJYx5pywttHqbLVw/T5asnLJRTbjrn/gzAnzFcSbCxsXHwjRL0tLUJxaOtLqbL1x5p7DVzTHGRtsxhbb+Avnn21cN0mSdZV1w0au5onGfzJOcyTzKkURtKcwAAIABJREFULV+qwcodyy9/PJ1Pn9532cq9jx/qmNLuiZu05ZG2vNDmYbp89TBdvnrCwjhEBkTkx0TksyIyWfz3YRHh7VEhMzY2psozOcn5Woe2upguX3uksdfMMcVF2jKHtf0C+ubZVw/TZZ5kXXHRqLmjcZ7Nk5zLPMmQtnypBit3LL8a18N0+eqJm7Tlkba80OZhunz1MF2+esISeQeziPwigJ8F8CkEX6f4FICfhuLj9ORyOVWe8XHKB8nV1cV0+dojjb1mjikO0pg5rO0X0DfPvnqYLvMk64qDRs4djfNsnuRc5omfNOZLNVi5Y/nVuB6my1dPnKQxj7TlhTYP0+Wrh+ny1RMWxmp8K4B/4py7VLpARP4cwJcB/AzBT6ezs1OVZ35+i+LRVhfT5WuPNPaaOaaYeCtSljms7RfQN8++epgu8yTriom3okFzR+M8myc5l3kS4a1IWb5Ug5U7ll+N62G6fPXEzFuRsjzSlhfaPEyXrx6my1dPWBiHyFgq/uy97DrBHQuZDOdA8CzPxoajeLTVxXT52iONvWaOKSZSlzms7RfQN8++epgu8yTriomGzR2N82ye5FzmSYTU5Us1WLlj+dW4HqbLV0/MpC6PtOWFNg/T5auH6fLVExbGDuYPAPiUiLxeRL5ORO4H8EcAfkVE7ir9EP4OjevXOfnI8oyNcSZdW11Ml6890thr5phiInWZw9p+AX3z7KuH6TJPsq6YaNjc0TjP5knOZZ5ESF2+VIOVO5Zfjethunz1xEzq8khbXmjzMF2+epguXz1hYRwi41eL/37bnstfB+A/Fv/vAKh5y254eFiV5/nnOQem11YX0+VrjzT2mjmmmEhd5rC2X0DfPPvqYbrMk6wrJho2dzTOs3mSc5knEVKXL9Vg5Y7lV+N6mC5fPTGTujzSlhfaPEyXrx6my1dPWCJ/gtk51xTiR00AAcDCwoIqz4kTnPZoq4vp8rVHGnvNHFMcpDFzWNsvoG+effUwXeZJ1hUHjZw7GufZPMm5zBM/acyXarByx/KrcT1Ml6+eOEljHmnLC20epstXD9PlqycsjENkpA7nOMfpYXlYh0XRVhfT5WuPNPaaOSYjgHnoI23z7KuH6TJPsi4jQNvjJtNlnuRc5jFqgZU7ll+N62G6fPUYu9GWF9o8TJevHqbLV09YGnIHs7aPm58/X6B4tNXFdPnaI429TsnXt1IFa/sF9M2zrx6myzzJuowAbY+bTJd5knOZx6gFVu5YfjWuh+ny1WPsRlteaPMwXb56mC5fPWFpyB3Ms7Ozqjz33MM4FLa+upguX3uksdfMMRkBrO0X0DfPvnqYLvMk6zICtD1uMl3mSc5lHqMWWLnjc379+q//NU6f/syun8McjzYP0+Wrx9iNtrzQ5mG6fPUwXb56wtKQO5i7urpUefL5LYpHW11Ml6890thr5piMANb2C+ibZ189TJd5knUZAdoeN5ku8yTnMo9RC6zc8Tm/tNWmzcN0+eoxdmNrKjmXrx6my1dPWCLvYBaRP6ty+aeiug3DMPZimWMYRtJY7hiGEReWL4ZhaMHyyDCMKDA+wfxtVS7/VoI7FpaXl1V5hoc5HyTXVhfT5WuPNPaaOaaYSF3msLZfQN88++phusyTrCsmGjZ3NM6zeZJzmScRUpcv1WDljs/5pa02bR6my1dPzKQuj2xNJefy1cN0+eoJS90HrBGRx4r/bd3x/xJ3AcjWPaqYGR0dVeU5d26T4tFWF9Pla4809po5JiZpzhzW9gvom2dfPUyXeZJ1MbHc0TnP5knOZZ74SHO+VIOVOz7nl7batHmYLl89cZDmPLI1lZzLVw/T5asnLFHe7jlW/Gna8f9jAO4AMA3gzZFHFxP5fF6V5+67MxSPtrqYLl97pLHXzDGRSW3msLZfQN88++phusyTrItMw+eOxnk2T3Iu88RKavOlGqzc8Tm/tNWmzcN0+eqJidTmka2p5Fy+epguXz1hqfsTzM65HwUAEfmic+63eEOKHxFR5SkUKBp1dTFdvvZIY6+ZY2KS5sxhbb+Avnn21cN0mSdZFxPLHZ3zbJ7kXOaJjzTnSzVYueNzfmmrTZuH6fLVEwdpziNbU8m5fPUwXb56wlL3DuYSzrnfEpFeAC8H0LXnus9F9cfBwMCAKs/UFCcVtdXFdPnaI429Zo4pDtKYOaztF9A3z756mC7zJOuKg0bOHY3zbJ7kXOaJnzTmSzVYueNzfmmrTZuH6fLVEydpzCNbU8m5fPUwXb56whL5iOgi8lYAlwH83wA+uuPnI1HdcaHt4+YnT0bezw9AX11Ml6890thr5V/fSmXmsLZfQN88++phusyTrCsOGjl3NM6zeZJzmSd+0pgv1WDljs/5pa02bR6my1dPnKQxj2xNJefy1cN0+eoJC2M1vgfAm5xzf0FwJUJPT48qTy7HeddNW11Ml6890thr5phiInWZw9p+AX3z7KuH6TJPsq6YaNjc0TjP5knOZZ5ESF2+VIOVOz7nl7batHmYLl89MRM5j0TkAQC/CiAD4CPOuffuuf5RAP8MwCaAPIAfc87VfRJBW1PJuXz1MF2+esIS+RPMCHZSf4bgSYwC6UA9LE9LC+uYXrrqYrp87ZHGXjPHFBOpyxzW9gvom2dfPUyXeZJ1xUTD5o7GeTZPci7zJEKkfBGRB0TkORG5ICLvqHD9fSLyZRHZFJE37bmuICLPFH/O1DuGEqzc8Tm/tNWmzcN0+eqJmah5lAHwQQDfBeAVAE6LyCv23OzvANzrnHslgE8C+MV6/x5gaypJl68epstXT1gYO5jfB+AXRIThSoSVlRVVnsFBTuu01cV0+dojjb1mjikmUpc5rO0X0DfPvnqYLvMk64qJhs0djfNsnuRc5kmEuvMl5M6cfwTwVgB/UEGx5px7VfHnDbX+/b2wcsfn/NJWmzYP0+WrJ2aiPt95DYALzrkXnHPrAJ4A8MadN3DOfd45t1r89W8A3FH3aGFrKkmXrx6my1dPWBiHyPjXAMYA/IyIzO+8wjn3EoKfztjYmCrP5OQmxaOtLqbL1x5p7DVzTDGRusxhbb+Avnn21cN0mSdZV0w0bO5onGfzJOcyTyJEyZfyzhwAEJHSzpxndzimitdtEcdcEVbu+Jxf2mrT5mG6fPXETNTnO0cBTO/4/RKA197i9g8D2Hc4jrm5OTz88MNobm5GoVDAgw8+iEceeQS5XA6dnZ3IZDK4fv06hoeHAQCvfnUzzp8v4J57mpHPb2GucALXt4ZxNHMOM1t3owkFDDdNIZvNoqenB4VCASsrKxgbG0Mul0NLSwt6enqQzWbR29uL9fV1rK2tla9vbW1Fd3c35ufn0d/fj7W1Ndy4caN8fVtbG9rb23H16lV0d3djZmYG6+vr5evb29vR2tqKxcVFDA0NYXFxERsbG+Xr99a0sLCAra0t3LhxA7Ozs+jqCs63uLy8jNHRUeTzeYgIBgYGkM/nq9bU29uLK1euoKOjA3Nzc3XXNDg4iKWlJRQKBdy8ebPumpxzGB4eRqFQwPz8fKSaent70dLSgmw2G6mm0jwVCgXMzc3VXVNpntra2pDNZuuuqbTtDQwMIJvNRqqp5L927VqkmirNUzUYO5h/kOBIlFwuh+PHj6vxjI83Y2JiQ814WB6my9ceaew1c0wxkbrMYW2/gL559tXDdJknWVdMNGzuaJxn8yTnMk8iRMmXWnfm7KVNRJ5GcCzU9zrn/nTvDWrZ0fO617Xi8uXCrh098/PzNe9AuPfeZqytAS++WEBnp6CvrwmTk5u4sHEKR2QVPU1zyBdOYDAzjauzs1VfbK+vr6Orqyvyjh7nHNbX19Hc3Bx5R883fVMLpqcL5ZrGx5sxMzNT8w6EfD6Pl7/85ZF39Jw/fx5Hjx6NVFNvby8uX76Mzs7OfTt6ZjZOYTAzjdWtPqy5btzRPIlsNnvLnSLPPfccxsbGIu/oyefzaG9vj7yjp1AoIJPJRN7Rs7Kygttvvz2xHT11ktjzHRH5QQD3AviWvdeNjIzgqaee2nefnbnd399f/v/Zs8EbN6XnPSOZKYxkpgAAdzWdrXj/oaGhXZdls9mKjws7LyvNwc7j2u68vrSTeudlO//f19cHAOjs7LxlTR0dHeV1svP6wcFBAMCxY8dC1VT6W7caU5iaSrfLZrM4cuRI3TWVyGQy5VrqrQkAFhcXy5fXW9POMY2MjNRdU6XtqJ6aSuyds3pqOn78OLLZLPr6+iLVBOyfp7m5OVQi8g5m59xfRnUkTUtLiyrPjRuO4tFWF9Pla4809po5pjhIY+awtl9A3zz76mG6zJOsKw4aOXc0zrN5knOZJ34OOV+OO+deFJG7AHxORL7qnLu48wa17OiZmirgq1/dvaNncHCw5h0IV6+eK3sCgmNIvqxlonxJb1MeANA6OlrR2dPTg8uXL+O2226reH2tL7YvX76M22+/vXx9vTtF8vmLeP75QrmmiYkNPPpoMMZadiA45yg7eoaGhig7elZXV8v92Xn9aHHO+ptyB9a08+8wdvTcvHmzPKYoO3r2zn29O3ouX76c6I6eeiDk0YsAju34/Y7iZbsQke8A8G8BfItz7maUP6jt+Y42D9Plq4fp8tUTlsgHrBGRIyLyHhF5QUQWi5fdLyJviz68eOjt7VXlefFFzoG3tdXFdPnaI429Zo4pDtKYOaztF9A3z756mC7zJOuKg0bOHY3zbJ7kXOaJn4j5EmpnTjWccy8W/30BwBcAfGPogVcaDCl3fM4vbbVp8zBdvnrihPB8ZwLASRG5U0RaATwEYNcJREXkGwF8GMAbnHOR947bmkrO5auH6fLVExbGEdF/BcDXA/inAEpvH00C+EmCOxauXLmiyvPSlzKOVKKvLqbL1x5p7DVzTDGRusxhbb+Avnn21cN0mSdZV0w0bO5onGfzJOcyTyJEyZcDd+ZUQ0T6ReRI8f9DAP577Dh2cz2wcsfn/NJWmzYP0+WrJ2YiPd9xzm0CeBuATwP4GoBPOOcmReQxESmdSPSXAHQB+CMReUZEQmVWNWxNJefy1cN0+eoJC2M1fj+AlznnVkonjyh+1eoowR0L2t4N8PVdN6bL1x5p7HUK3l1PXebYJ5jT52G6zJOsKyYaNnc0zrN5knOZJxHqzhfn3Gbxk4WfBpAB8LHSzhwATzvnzojIKQB/AqAfwPeKyH9wzo0D+DoAHy7+zSYEx2COtIPZPsF8MNpq0+Zhunz1xEzk5zvOuScBPLnnsnft+P93sAYL2JpK0uWrh+ny1RMWxg7m9b0eERkGMF/55ofP+vq6Kk9nJ+fg/NrqYrp87ZHGXjPHFBOpyxzW9gvom2dfPUyXeZJ1xUTD5o7GeTZPci7zJEKkfAmxM2cCwaEz9t7viwC+oY7xVoWVOz7nl7batHmYLl89MWPPdzzzMF2+epguXz1hYRwi448AfFxE7gQAEbkNwK8BeILgjoW1tTVVnr4+xjToq4vp8rVHGnvNHFNMpC5zWNsvoG+effUwXeZJ1hUTkXNHRB4QkedE5IKIvKPC9Y+KyLMi8hUR+S8isv9U5jWg7XGT6TJPci7zJELqntdUg5U7PueXttq0eZguXz0xk7o8sjWVnMtXD9PlqycsjNX48wD+AcBXAfQBeB7AZQCPEdyxMDY2psozObl58I1CoK0upsvXHmnsNXNMMZG6zGFtv4C+efbVw3SZJ1lXTETKHRHJAPgggO8C8AoAp0XkFXtu9ncA7nXOvRLAJwH8YpQBa3vcZLrMk5zLPImQuuc11WDljs/5pa02bR6my1dPzKQuj2xNJefy1cN0+eoJS+QdzM65defcv3bOdQEYBdBd/P1m9OHFQy6XU+UZH+ccmF5bXUyXrz3S2GvmmOIgjZnD2n4BffPsq4fpMk+yrjgg5M5rAFxwzr3gnFtH8EmgN+75G593zq0Wf/0bVPhKey1oe9xkusyTnMs88ZPG5zXVYOWOz/mlrTZtHqbLV0+cpDGPbE0l5/LVw3T56glL5NUoIj8M4Bnn3Fecc/niZf8dgFc65343qj8OWltbVXlWV93BNwqBtrqYLl97pLHXzDHFQRozh7X9Avrm2VcP02WeZF1xQMidowCmd/x+CcBrb3H7hwH8RaUr5ubm8PDDD6O5uRmFQgEPPvggHnnkEeRyOXR2diKTyeD69etwzuFVr2pGJgOcP1/APfc0I5/fwlzhBK5vDeNo5hxmtu5GEwroXF1FPp9HT08PCoUCVlZWMDY2hlwuh7W1NaysrODKlSvo7e3F+vo61tbWyte3traiu7sb8/Pz6O/vx9raGm7cuFG+vq2tDe3t7bh69Sqcc5iZmcH6+nr5+vb2drS2tmJxcRFDQ0NYXFzExsZG+fqdNQ0PD2NhYQErKyu4ceMGZmdn0dXVBQBYXl7G6Ogo8vk8RAQDAwNVa2ppaUFvby+Wl5dx7dq1SDUNDg5ibW0N2Ww2Uk3OOYgIstlspJpK83Tz5s1dY6q1pqWlJayvr6OpqQnZbLbumoaHhzE7O4uNjQ3Mz89Hqml9fR3Ly8u4efNmpJrGxsawvLyMubm5SDVVmqd6SOPzmmqwnu9oe97PdGmrTZuH6fLVEydpzCNbU8m5fPUwXb56wsJ4u+fdAF6157JpAGcAqAyh7u5uVZ65Oc6ZT7XVxXT52iONvWaOKSZSlzms7RfQN8++epgu8yTrionEckdEfhDAvQC+pdL1IyMjeOqpp/Zdfvz49iGb+/v7kc2eRz6//aJrYmIjuH9mCiOZKQDAXU1nAQArHR277j80NFR2Li8vo7OzE52dnbf8m6WdbT09PRWv7+npwfLycvl2e6/v6+sDgF1/Z29NANDR0YHl5WW0tbXtun5wcBAAcOzYsYr331nTzut3jqeemgDgjjvuKN+23poA7OtPPTWV/lZzc3PFMYWtaefO051jqrWm0vUlT5SaSt4jR45Eqql0fen3emsqsbOmOncyp+55TTVYz3e0Pe9nurTVps3DdPnqiZnU5ZGtqeRcvnqYLl89YWEcg7kHwPU9ly0iOGaPSubnOSdBZXlOnOB8rUNbXUyXrz3S2GvmmGIidZnD2n4BffPsq4fpMk+yrpiImjsvAji24/c7ipftQkS+A8C/BfCGqF9H1fa4yXT95m9O4PTpz+z6OczxaPMwXeZJhNQ9r6kGK3d8zi9ttWnzMF2+emImdXlkayo5l68epstXT1gYO5ifBfA/77ns+wF8Lcydkz6rOrD9SQQtnulpzrtu2upiunztkcZeM8cUE5EyB0g+d1jbL6Bvnn31MF3mSdYVE1FzZwLASRG5U0RaATyE4NNAZUTkGwF8GMHO5bmI41X3uMl0aatNm4fpMk8iRH5eowXW2tS2xpkubbVp8zBdvnpiJnV5ZGsqOZevHqbLV09YGDuYfxbAR0Tkj0XkF0XkUwA+CuDtB93xMM6qDgBra2tRFVRPX59QPNrqYrp87ZHGXjPHFBN1Zw5wOLnD2n4BffPsq4fpMk+yrpiIlDvOuU0AbwPwaQQv0j7hnJsUkcdE5A3Fm/0SgC4AfyQiz4jImSq6UGh73GS6tNWmzcN0mScRIuWLJlhrU9saZ7q01abNw3T56omZ1OWRrankXL56mC5fPWFhfJ/giwC+HsBbEHz9828B/JRzbvqW9woon1UdAESkdFb1Z0s3cM59fsft/wbAD0Yd8I0bN6IqqJ7u7iYA0d9501YX0+VrjzT2mjmmmIiSOcAh5A5r+wX0zbOvHqbLPMm6YiJq7sA59ySAJ/dc9q4d//8OzlADtD1uMl3aatPmYbrMkwiR80ULldZm59OnK9525d7Ha/LUg8Y1pa02bR6mKy2eSmvkVusjZlKXR7amknP56mG6fPWEJdIO5uInAZcB9Dnn3luHIvGzqg8PDwMApqenb3kW6DBntu7p6UE2m418VvVcroDx8WZ0dAgmJzcxPt6My4WTaMMKFraOYjRzEQtbR7Hh2jBQPHN2pTNbb21tUc6qXigUKGdVX1paQqFQKJ/tO8oZyFtagBMnMgCA4eEmnDu3ienp6ZrPQN7S0kI5q/rAwADlrOptbW2Us6qvra2VxxTlrOol/7Vr1w79rOqVIGQOQMydsExObka5+y7GxsbMk4CH6TJPsi42pNxJHFbuaJxnbbVp8zBd5omXtOZLNVhrU9saZ7q01abNw3T56omLtOaRrankXL56mC5fPWGJtIPZOVcQkfMABgFc5gypMqyzqpconb06yhnIs9nsrusr3SfMma3Hxl4on90dCM70/s77ngcADGSCtnY3LQAAVvacOXvnma2z2SzlrOqZTKZ8Ru16ayrdLpvN7jvbdz1n697YAKamgncmS//WcwbyxcXF8uVRzkC+d+7rPQN5yRP1rOqVxlTvWdWz2Sz6+vo0nFV9H0lmDnBw7oR9Y+vVr27G0pJDJgOcP1/APfc0I5/fwlzhBK5vDeNo5hxmtu5GEwroXF295ZsLKysraG1tjfzG1vr6Orq6una9uVDPGyZXr17FyZMnI7+xdfHiRbzkJS+J/MZWNptFV1dXpJpKb5icP38eR48erbum0ptAly9fRmdnZ+Q3tgqFAjKZTOQ3ttbW1jA8PBz5ja1cLoeXv/zlkWoqXb+ysoLbb79d5RtbSecOi/Hx5l3PLeoll8tVfK5zmC5ttWnzMF3miZe05ks1WGtT2xpnurTVps3DdPnqiYu05pGtqeRcvnqYLl89YWEcIuP3Afy5iPwqgk8CutIVzrnPHXDfWs+q/i1Rz6oOAG1tbVEVVM/S0hbFo60upsvXHmnsNXNMMRElcwBi7oR9Yyufv4Bz57a/ulV6EjSSmcJIZgoAcFfTWQDASkfHLd9cmJ2dxejo6C3/Zpg3F/Z66n3DpKWlhfLG1ujoKOWNraGhoXJdUd8EGh0dLdcS5U2gmzdvVhxTrW8C7Z2zet8Emp2dxeDgYOQ3tpxz+95ArPeNrdnZWbVvbBWJmjuJo+1xk+nSVps2D9NlnkRIXb5Ug7U2ta1xpktbbdo8TJevnphJXR7ZmkrO5auH6fLVExbGDuafLP777/dc7gDcdcB9y2dVR7CD5yEEx/sps+Os6g8wzqoOAO3t7QwNzXPtmjv4RiHQVhfT5WuPNPaaOaaYiJI5wCHkDmv7BfTNs68epss8ybpiImruJI62x02mS1tt2jxMl3kSIXX5Ug3W2tS2xpkubbVp8zBdvnpiJnV5ZGsqOZevHqbLV09YmqIKnHN3Vvk5MIAO46zqAHD16tWoCqrn2LEMxaOtLqbL1x5p7DVzTHEQJXOK9088d1jbL6Bvnn31MF3mSdYVB1Fz5zDQ9rjJdGmrTZuH6TJP/KQxX6rBWpva1jjTpa02bR6my1dPnKQxj2xNJef6yEfO4vTpz+z6OczxaOyRr56wMD7BDBFpAfBNAG53zv2hiHQCgHNu5aD7Jn1WdWD7K7RaPFNTnAPTa6uL6fK1Rxp7zRxTXETJnOLtEs0d1vYL6JtnXz1Ml3mSdcVF1NxJGm2Pm0yXttq0eZgu8yRD2vKlGqy1qW2NM13aatPmYbp89cRN2vLI1lRyLl97zXT56glL5E8wi8g3ADgP4LcAfLR48bcA+FhUd1wsLS2p8oyMcN5101YX0+VrjzT2mjmmOEhj5rC2X0DfPPvqYbrMk6wrDho5dzTOs7batHmYLvPETxrzpRqstaltjTNd2mrT5mG6fPXESRrzyNZUci5fe810+eoJS+QdzAB+A8C7nHP3ACidvvMvAfwPBHcsrK+vq/J0dAjFo60upsvXHmnsNXNMMZG6zGFtv4C+efbVw3SZJ1lXTDRs7micZ221afMwXeZJhNTlSzVYa1PbGme6tNWmzcN0+eqJmdTlka2p5Fy+9prp8tUTFsYO5nEAv1f8vwPKX59QexT7sbExVZ7JSc5XDbTVxXT52iONvWaOKSZSlzms7RfQN8++epgu8yTriomGzR2N86ytNm0epss8iZC6fKkGa21qW+NMl7batHmYLl89MZO6PLI1lZzL114zXb56wsLYwTwF4NU7LxCR1wC4QHDHQi6XU+UZH6ccCltdXUyXrz3S2GvmmGJiCinLHNb2C+ibZ189TJd5knXFxBQaNHc0zrO22rR5mC7zJMIUUpYv1WCtTW1rnOnSVps2D9PlqydmppCyPLI1lZzL114zXb56wsLYQt4J4D+LyIcAtIrIzwH4CQA/TnDHQns75w04lufatS2KR1tdTJevPdLYa+aYYiJ1mcPafgF98+yrh+kyT7KumGjY3NE4z9pq0+ZhusyTCKnLl2qw1qa2Nc50aatNm4fp8tUTM6nLI1tTybl87TXT5asnLJE/weyc+3MADwAYRnB8nuMAHnTOfSaqOy5aW1tVeVZWHMWjrS6my9ceaew1c0xxkMbMYW2/gL559tXDdJknWVccNHLuaJxnbbVp8zBd5omfNOZLNVhrU9saZ7q01abNw3T56omTNOaRrankXL72muny1RMWxiEy4Jz7O+fcv3TOfY9z7iecc2cZ3rhYXFxU5Tl6lHM2Tm11MV2+9khjr5ljiou0ZQ5r+wX0zbOvHqbLPMm64qJRc0fjPGurTZuH6TJPMqQtX6rBWpva1jjTpa02bR6my1dP3KQtj2xNJefytddMl6+esETewSwirSLymIg8LyIrxX/fLSJtjAHGwdDQkCrPxYucg6Vrq4vp8rVHGnvNHFMcpDFzWNsvoG+effUwXeZJ1hUHjZw7GudZW23aPEyXeeInjflSDdba1LbGmS5ttWnzMF2+euIkjXlkayo5l6+9Zrp89YSF8Qnm3wDw7QD+FYBTxX+/FcCvE9yxoO3dAHsn6GB87ZHGXqfg3fXUZY59gjl9HqbLPMm6YqJhc0fjPGurrZqn8+nT+36SGA/TZZ5ESF2+VMM+wXww2mrT5mG6fPXETOryyNZUci5fe810+eoJC+Mkf98H4KXOuWumF9h9AAAgAElEQVTF358VkS8hONPojxH8dDY2NlR52tqE4tFWF9Pla4809po5pphIXeawtl9A3zz76mG6zJOsKyYaNnc0zrO22rR5mC7zJELq8qUarLWpbY0zXdpq0+Zhunz1xEzq8sjWVHIuX3vNdPnqCQvjE8w5AB17LmsHMENwx8LY2Jgqz+Qk56sG2upiunztkcZeM8cUE6nLHNb2C+ibZ189TJd5knXFRMPmjsZ51labNg/TZZ5ESF2+VIO1NrWtcaZLW23aPEyXr56YSV0e2ZpKzuVrr5kuXz1hYexg/l0A/4+I/LiIfJeI/HMATwL4HRH59tIP4e/QyOVy+y6r9WuM1Tz1MD7O+CA5bzwsD9Pla4809po5pphIXeawtl9A3zz76mG6zJOsKyYaNnc0zrO22rR5mC7zJELq8qUarLWpbY0zXdpq0+Zhunz1xEzq8sjWVHIuX3vNdPnqCQtjC/kXxX9/fs/lP1H8AQAH4C7C36LQ2dmpyjM/v0XxaKuL6fK1Rxp7zRxTTKQuc1jbL6Bvnn31MF3mSdYVEw2bOxrnWVtt2jxMl3kSIVK+iMgDAH4VQAbAR5xz791z/X0APgDglQAecs59csd1PwLgF4q//u/OuY9HqIO2NrWtcaZLW23aPEyXr56Ysec7nnmYLl97zXT56glL5B3Mzrk7GQNJkkyGc3Bylmdjw1E82upiunztkcZeM8cUB2nMHNb2C+ibZ189TJd5knXFQSPnjsZ51labNg/TZZ74iZIvIpIB8EEArwdwCcCEiJxxzj2742b/COCtAH56z30HAPw7APci2GF0tnjfq/WOh7U2ta1xpktbbdo8TJevnjix5zv+eZguX3vNdPnqCQvjEBmp4/r166o8Y2OcSddWF9Pla4809po5JiOAtf0C+ubZVw/T1Wieeg45ZbnDR9vjJtOlrTZtHqbLPOp5DYALzrkXnHPrAJ4A8MadN3DOTTnnvgJg70fPvhPAZ51zC8Wdyp8F8ECUwbDWprY1znRpq02bh+ny1WPsxtZUci5fe810+eoJS0PuYB4eHlblef55zsHStdXFdPnaI429Zo7JCGBtv4C+efbVw3SZJ1mXEaDtcZPp0labNg/TZR71HAUwveP3S8XL4r5vRVhrU9saZ7q01abNw3T56jF2Y2sqOZevvWa6fPWEhXfmqRSxsLCAjo69J0c9PM+JExk880z0xaqtLqbL1x5p7DVzTEYAa/sF9M2zrx6myzzJuowAbY+bTJe22rR5mC7zGHNzc3j44YfR3NyMQqGABx98EI888ghyuRw6OzuRyWRw/fp1DA8P45u/uQWzs1s4f76Ae+5pRj6/hbnCCVzfGsbRzDnMbN2NJhQw3DSFbDaLnp4eFAoFrKysYGxsDLlcDi0tLXjFK5qxsQG8+GIBnZ2Cvr4mTE5u4sLGKRyRVfQ0zSFfOIHBzDSuzs7ixo0b5fu3tbWhvb0dV69exebmJjo6OrC+vl6+vr29Ha2trVhcXMTQ0BAWFxexsbFRvn5vTQsLC3DOYXNzE01NTejq6gIALC8vY3R0FPl8HiKCgYEB5PP5qjX19vbiypUreOUrmzEzs1WuaXy8GTMzM+ju7sb8/Dz6+/uxtrZWtabBwUEsLS3hypUruPvuuyPVNDw8jIsXL+L222+PVFNvb295HKXrW1tb0d3djZmNUxjMTGN1qw9rrht3NE8im81WrKk0TxcvXsTo6GjdNc3OzqKrqwvz8/M4cuRI3TWtr69jbW0NzjmISLmmWuZp57a3traGsbGxfTXd5TpwaXMcXU3zaMYGrm2NoXd1tWJNleap0bHnBMm5fO010+WrJywNuYPZOc6xY1ge1mFRtNXFdPnaI429Zo7JCGAe+kjbPPvqYbrMk6zLCND2uMl0aavtiSfO4+zZZ/ddfubthzMepss86nkRwLEdv99RvCzsfb91z32/sPdGIyMjeOqpp/bd+fjx4+X/9/f3AwBmZ7dw9myw82FiYiO4f2YKI5kpAMBdTWcr3n9oaGjXZTdvnit7AgoAgJe1TJQv6W3KAwBaR0crOnt6ejA9PY3bbrut4vV9fX0Adp8AqVJNpRfm09PTOHZsu9WDg4MAsOuyW9VU+lsrKxfx/POFck0TExt49NFgjKUdiD09PVVrKt1uc3MTR44ciVRT6T6lWuqtCQCWlpbK99t5/WhxzvqbcgfWtHNMIyMjdddUun51dbU8pnpqKrF37muZp53XT09Po6+vb19NbfnVXdv2UGYaKx2PVqwJ2D9Pc3NzaGS0PSfQ5mG6fO010+WrJyx2iAwFnvPnCxSPtrqYLl97pLHX9vUtPqztF9A3z756mC7zJOsyArQ9bjJd2mrTNh6myzzqmQBwUkTuFJFWAA8BOBPyvp8GcL+I9ItIP4D7i5fVDWst+LymtNWmzcN0+eoxdmNrKjmXr71munz1hKUhdzDPzs6q8txzD+eD5NrqYrp87ZHGXjPHZASwtl9A3zz76mG6zJOsywjQ9rjJdFWqrdLJJQ86waSvz1GYLvPoxjm3CeBtCHYMfw3AJ5xzkyLymIi8AQBE5JSIXALwZgAfFpHJ4n0XALwbwU7qCQCPFS+rG9Za8HlNaatNm4fp8tVj7MbWVHIuX3vNdPnqCUtDHiJj59dVNHjy+b0nda4PbXUxXb72SGOvmWMyAljbL6Bvnn31MF3mSdZlBGh73GS6tNWmbTxMl3n045x7EsCTey57147/TyA4/EWl+34MwMdYY2GtBZ/XlLbatHmYLl89xm5Ya+pDH7qAqann9l3++OP31+TRuL1YfiXn8tUTlobcwWz4QbVPJq3c+3jCIzEMwzAMwzAMwzAMwzCMxqQhD5GxvLysyjM8zJkGbXUxXb72SGOvmWMyAljbL6Bvnn31MF3mSdZlBGh73GS6tNWmbTxMl3mMWmCtBZ/XlLbatHmYLl89xm58zR2Na6pSj+o5RJnPPfLVE5aG3ME8uuNswxo8585tHnyjEGiri+nytUcae80ckxHA2n4BffPsq4fpMk+yLiNA2+Mm06WtNm3jYbrMY9QCay34vKa01abNw3T56jF242vuaFxT1qPG9YSlIXcw5/N5VZ67785QPNrqYrp87ZHGXjPHZASwtl9A3zz76mG6zJOsywjQ9rjJdGmrTdt4mC7zGLXAWgs+rylttWnzMF2+eozd+Jo7GteU9ahxPWFpyB3MIqLKUyhQNOrqYrp87ZHGXjPHZASwtl9A3zz76mG6zJOsywjQ9rjJdGmrTdt4mC7zGLXAWgs+rylttWnzMF2+eozd+Jo7GteU9ahxPWFpyB3MAwMDqjxTU5yVqq0upsvXHmnsNXNMRgBr+wX0zbOvHqbLPMm6jABtj5tMl7batI2H6TKPUQusteDzmtJWmzYP0+Wrx9iNr7mjcU1ZjxrXE5aG3MGs7ePmJ082Uzza6mK6fO2Rxl7b17f4sLZfQN88++phusyTrMsI0Pa4yXRpq03beJgu8xi1wFoLPq8pbbVp8zBdvnqM3fiaOxrXlPWocT1hacgdzD09Pao8uRznnSBtdTFdvvZIY6+ZYzICWNsvoG+effUwXeZJ1mUEaHvcZLq01aZtPEyXeYxaYK0Fn9eUttq0eZguXz3GbnzNHY1rynrUuJ6w8D5WlyIKpIPHsDwtLaxj4uiqi+nytUcae80ckxHA2n4BffPsq4fpMk+yLiNA2+Mm06WtNm3jYbrMY9QCay34vKYq1db59OmKt1259/HYx6PNw3T56jF242vuaFxT1qPG9YSlIT/BvLKyosozOMiZBm11MV2+9khjr5ljMgJY2y+gb5599TBd5knWZQRoe9xkurTVpm08TJd5jFpgrQWf15S22rR5mC5fPdoRkQdE5DkRuSAi76hw/X0i8mUR2RSRN0X9e77mjsY1ZT1qXE9YGvITzGNjY6o8k5ObFI+2upguX3uksdfMMRkBrO0X0DfPvnqYLvMk6zICtD1uMl3aatM2HqbLPEYtsNaCz2tKW20sz2OPncfq6nP7Lj/z9tpd2mrT2COtiEgGwAcBvB7AJQATInLGOffsjpv9I4C3Avhpxt/0NXcsv5LzMF2+esLSkJ9gzuVyqjzj45z9/NrqYrp87ZHGXjPHZASwtl9A3zz76mG6zJOsywjQ9rjJdGmrTdt4mC7zGLXAWgs+rylttWmrC9BXm8YeKeY1AC44515wzq0DeALAG3fewDk35Zz7CoAtxh/0NXcsv5LzMF2+esLSECm3l5aWFlWeGzccxaOtLqbL1x5p7DVzTEYAa/sF9M2zrx6myzzJuowAbY+bTJe22rSNh+kyj1ELrLXg85rSVpu2ugB9tWnskWKOApje8fslAK+N8w/GnTuVjpF+q+Oja9vumC5f84vp8tUTlobcwdzb26vK8+KLnANva6uL6fK1Rxp7zRyTEcDafgF98+yrh+kyT7IuI0Db4ybTpa02beNhusxj1AJrLfi8prTVpq0uQF9tGnvkO3Nzc3j44YfR3NyMQqGABx98EI888ghyuRw6OzuRyWRw/fp1DA8Po7tb8OpXN+P8+QLuuacZ+fwW5goncH1rGEcz5zCzdTeaUMBw0xSy2Sx6enpQKBSwsrKCsbEx5HI5tLS0YHl5C6dOteDFFwvo7BT09TVhcnITFzZO4YisoqdpDvnCCQxmpnF1dhY3btwo37+trQ3t7e24evUqOjo6MDMzg/X19fL17e3taG1txeLiIoaGhrC4uIiNjY3y9XtrWlhYwM2bN3Hjxg3Mzs6iq6sLALC8vIzR0VHk83mICAYGBpDP56vW1NvbiytXruDIkSOYm5vD2tpa+frW1lZ0d3djfn4e/f39WFtbq1rT4OAglpaW0N8v6OgQjI8349q1LaysOFzYOIXRzEUsbB3FhmvDHc2TuLQ5jpYrV/bV5JzD8PAwVldXMT8/H6mm3t5eFAoFZLPZSDWV5ml1dRVzc3M1z1Oppp3zlM1m665pfX0da2tr6O3tRTabjVRTLpdDU1MTrl27FrmmvfNUjYbcwXzlyhV0dnaq8bz0pc1YWNhQMx6Wh+nytUcae80ckxHA2n4BffPsq4fpMk+yLq2IyAMAfhVABsBHnHPv3XP9fQA+AOCVAB5yzn0yyt/T9rjJdGmrTdt4mC7zGLXAWgs+rylttWmrC9BXm8YeKeZFAMd2/H5H8bKaGBkZwVNPPbXv8uPHj5f/39/fDwDY2ADOng2ODTwxEfR3JDOFkcwUAOCuprMV7z80NLTrsqGh58r3DwjeEHhZy0T5kt6mPACgdXS0orOnpwfZbHbXZTv/39fXBwC7tqdKNXV0dCCbzaKtrW3X9YODgwCAY8eOVbz/3ppKf+tWYyrtQOzp6alaU+l2a2vnsLrqdvWp1J/upoVdl60MPbqvphItLS3lWuqtCQAWFxfLl9db084xjYyMAKhtnvZev7PX9dRUYu+c1VPT8ePHkc1m0dfXF6kmYP88zc3NoRINuYPZ13cztdXFdPnaI429tk/18LFPdaTPw3SZJ1mXRg7jpDfaHjeZLm21aRsP02UeoxbsE8wHo602bXUBlcdU6TAFwK0PVeBzjxQzAeCkiNyJYMfyQwDeEucf9DV3LL+S8zBdvnrC0pAn+VtfX1fl6eys/hHzWtBWF9Pla4809po5JiOAtf0C+ubZVw/TZZ5kXUpJ/KQ32h43mS5ttWkbD9NlHqMWWGvB5zWlrTZtdQH6atPYI6045zYBvA3ApwF8DcAnnHOTIvKYiLwBAETklIhcAvBmAB8Wkckof9PX3LH8Ss7DdPnqCcuh72AWkQdE5DkRuSAi76hw/X0i8mUR2RSRNzH+5traGkND8/T1caZBW11Ml6890thr5pi0knTusLZfQN88++phusyTrEsplU56czTOP6jtcZPp0labtvEwXeYxaoG1FnxeU9pq01YXoK82jT3SjHPuSefc3c65lzrn3lO87F3OuTPF/0845+5wznU65wadc+NR/p6vuWP5lZyH6fLVE5ZDPUTGYXxlFADGxsZUeSYnNykebXUxXb72SGOvmWPSyGHkDmv7BfTNs68epss8ybp8J+yJb6anC3jVq5qRyeDAE990rq5WPfmIiGBlZWXfyUfqOaFKd3c35cQ3mQzQ3S3lmgDgwsapfSfzmSmcRNvVq1VPqFIoFHDt2rVINQ0ODmJz0+HUqRZMTm4eeOKbbDZb9YQq/f39yGazkU/m09vbi5aWFsqJbwYGBpDNZuuap50niWlra8P8/HykmtbX11EoFHDz5s3IJ/MpFAq0k/nsrKnRYT3f0fa8n+nSVpu2ugB9tWnskbGNr7kTd37Vc9iZRuuReWrnsI/BXP7KKACISOkro+UdPc65qeJ1lK+MAkAul9t1wOrD9oyPN+85oPzhjoflYbp87ZHGXjPHpJTEc4e1/QL65tlXD9NlnmRdSqGc9AYIf+KbY8de2JU7tzrxzUpHR9WTj5R2iFY6wVGtJx9hnfimUHgeS0uVTzKz82Q+L2uawEr/o/tqKpHJZMp/t96aAKC5WcpjOejEN7c6ocre/mg48c3eMdV7kpiSJ0pNQPBJnCNHjkQ+8U0mk6GczAfYPU+NvpOZ9XxH2/N+pktbbdrqAvTVprFHxja+5o7lV3IepstXT1gO+3saiX9lFABaW1tVeVZXHcWjrS6my9ceaew1c0xKSTx3WNsvoG+effUwXeZJ1qWU8klvRKQVwUlvzsT5B7U9bjJd2mrTNh6myzxGLbDWgs9rSltt2uoC9NWmsUfGNr7mjuVXch6my1dPWA77E8w0wn5ldHh4GGtra5ient71FbeVGr8y2tLSUv76YdSvjG5sbGF8vBkdHVL+euXlwkm0YQULW0d3fb1yoPi1wEpf27t58yZu3LhR9Wt7Yb+KuLy8TPnK6NLSEpaXl8tfZYzy9crhYcGJExkAwPBwE86d28QLm6/e9TXYvqYcNtGChR1fCd379crNzU3KV0ZLn8SK+pXR5uZmyldG19bWymOK8pXRXC6HpqYmXLt2zb4yGoKwubO2tkX5qjozd9rb2ylfVdeWOzdv3ty1xqOs0eXlZczPz9ddk++5szPfd9Z029YYVrf6sOa6cUfzJC5tjqNpdrahc8c5tykipZPeZAB8rHTSGwBPO+fOiMgpAH8CoB/A94rIf4hyXMK5Oc6Zvru7uykepktbbdrGw3SZx6gF1lrweU1pq01bXYC+2jT2yNjG19yx/ErOw3T56gnLYe9gTvwro0DwtbjSV/NK13f+Q21fGQX2f22w0t8M87W93t79X2N9533PAwAGMpcBbH+9cmXP1wJ3fm0vm82ira0t8tcrW1tbKV8Z7erqQjab3fdVxnq+iriyAkxNBYFW+veu5t1fgy3RXeEroZq/Mjo4OBj5K6OVxlTPV0ZLY+rr6/P5K6OJ587gIOer6gAvd1hfVdeWO/Pz8xXXeD3bc2tra7kW376qzsidal9V78zn0N+UK1/2spYJrIw+WrGmnWPyPHfgnHsSwJN7LnvXjv9PIMgjCidONCOfj/41xvn5+V3zpcGlrTZt42G6zGPUAmst+LymtNWmrS5AX20ae2Rs42vuWH4l52G6fPWE5bB3MJe/MopgB89DAN4S9x8tvUDV4pme5rwTpK0upsvXHmnsNXNMSkk8d1jbL6Bvnj/wgeeRyz2367LHH7//0Mbj85ry1cN2GQHaHjeZLm21aRsP02UeoxZYa8HnNaWtNm11Afpq09gjYxtfc8fyKzkP0+WrJyyHegxm59wmgNJXRr8G4BOlr4yKyBsAQEROicglAG8G8GERmYz6d9fW1qIqqJ6+PqF4tNXFdPnaI429Zo5JI4eRO6ztF9A3z76uTabLPMm6jABta5Pp0labtvEwXeYxaoG1FnxeU9pq01YXoK82jT0ytvE1dyy/kvMwXb56wnLYn2BO/CujAHDjxg1Vnu7uJgDR3w3SVhfT5WuPNPaaOSatJJ07rO0X0DfPlWrrfPp0xduu3Pt47OPxeU356mG7jABtj5tMl7batI2H6TKPUQusteDzmtJWm7a6AH21aeyRsY2vuWP5lZyH6fLVE5ZD38F8GIyNjanyTE5uUjza6mK6fO2Rxl4zx2QEsLZfQN88+7o2mS7zJOsyArStTaZLW23axsN0mceoBdZa8HlNaatNW12Avto09sjYxtfcsfxKzlPNVelDU7f6wBRzTNo8YTnUQ2QcFrlc7uAbJegZH+fs59dWF9Pla4809rqSp/Pp0xV/jHCwtl9A37bn69pkusyTrMsI0LY2mS5ttWkbD9NlHqMWWGvB5zWlrTZtdQH6atPYI2MbX3Pngx/8Ik6f/sy+n8Mck7Yeacx4Xz1hacgdzG1tbao8S0tbFI+2upguX3uksdfMMRkBrO0X0DfPvq5Npss8ybqMAG1rk+nSVpu28TBd5tGPiDwgIs+JyAUReUeF64+IyB8Wr/+SiJwoXn5CRNZE5Jniz4eijoW1FnxeU9pq01YXoK82jT0ytvE1dzSuKW090pjxvnrC0pBvo7W3t6vyXLvmKB5tdTFdvvZIY6+ZYzICWNsvoG+efV2bTJd5knUZAdrWJtOlrTZt42G6zKMbEckA+CCA1wO4BGBCRM44557dcbOHAVx1zr1MRB4C8D4AP1C87qJz7lWs8bDWgs9rSltt2uoC9NWmsUfGNr7mjsY1pa1HGjPeV09YGvITzFevXlXlOXYsQ/Foq4vp8rVHGnvNHJMRwNp+AX3z7OvaZLrMk6zLCNC2NpkubbVpGw/TZR71vAbABefcC865dQBPAHjjntu8EcDHi///JIDXiYjEMRjWWvB5TWmrTVtdgL7aNPbI2MbX3NG4prT1SGPG++oJS0N+gnlwcFCVZ2qKc7B0bXUxXb72SGOvmWMyAljbL6Bvnn1dm0yXeZJ1GQHa1ibTpa02beNhusyjnqMApnf8fgnAa6vdxjm3KSKLAEoNuFNE/g7AdQC/4Jz7b3v/wNzcHB5++GE0NzejUCjgwQcfxCOPPIJcLofOzk5kMhlcv34dw8PDaG0FXv3qZpw/X8A99zQjn9/CXOEErm8N42jmHGa27kYTChhumkI2m0VPTw8KhQJWVlYwNjaGXC6HlpYWXL1awKlTLXjxxQI6OwV9fU2YnNzEhY1TOCKr6GmaQ75wAoOZaVydncWNGzfK929ra0N7ezuuXr2K9vZ2zMzMYH19vXx9e3s7Wltbsbi4iKGhISwuLmJjY6N8/d6aFhYW4JxDV1cXstksurq6AADLy8sYHR1FPp+HiGBgYAD5fL5qTb29vbhy5QpWVrZw8mSmXNP4eDOmN8d31bS61Yc1142Bmzf31TQ4OIilpSWsr6/jZvH6emsaHh7G+vo65ufnI9XU29uLrS2HU6dayjWtrjrMzRVwYePUrpruaJ5ENputWtPY2BjW19cxNze3q6Yrm9+ADdeGO5oncWlzHF1N82jGBuay2X01zc7OoqurC83Nzchms3XXtL6+jrW1NfT09CCbzaK1tRXd3d2Yn59Hf38/1tbWqm57e2vK5XLY2nK4/fYmHD2awcWLmzh6NIO2NsEN17GrpmtbY+hdXa1YU6V5anRYj8HaHss1vn7U1iN73pScJywNuYN5aWmpHNAaPCMjGeTz0RertrqYLl97pLHXzDEZAaztFwA+8IG/3XcG38cfv79mj63N5FzmSdZlBLDWZqXMASx3NI+H6TKP18wAeIlzbl5EXg3gT0Vk3Dl3feeNRkZG8NRTT+278/Hjx8v/7+/vBxB8fbqUFxMTG8H9M1MYyUwBAO5qOlvx/kNDQ7suO3LkXPn+AQUAwMtaJsqX9DblAQCto6MVnT09PZiZmcFtt91W8fq+vj4AQGdn5y1r6ujoAADMzMzsur70ov3YsWOhair9LZGLeP75zXJNExMbeOd9k7tq6m8KTsq0cuTIvpoAoKurCzMzMziy5/paayq5SrXUWxMA3LgBTE5ulGsqUZqzUk1777+zpp1jGhkZ2VXTSPNX9zkBoL3o2llTyb9zzuqpqcTeuS+NtTT2MDUdP34cN25cxOXLW7h8OTiO7cJCsFba7lvdVdNQZhorHY9WrAnYP09zc3NoZFiPwdoey6uNp/Pp0/suW7n38UMdU61ofCzXNiZtnrA05A7m9fV1VZ6ODs47j9rqYrp87ZHGXjPHZASwtl+my9Zmci7zJOsyAlhrs5qnnhc4vuaOtvEwXeZRz4sAju34/Y7iZZVuc0lEmgH0Aph3zjkANwHAOXdWRC4CuBvA0/UOJu7cqRWNa0pbbdrqAvTVprFHxja+5o7GNaWtRxoz3ldPWBpyB/PY2JgqT6VPBtWDtrqYLl97pLHXzDEZAaztl+lqtLVZz84wbWvKVw/bZQSw1iYzv3zNHW3jYbrMo54JACdF5E4EO5IfAvCWPbc5A+BHAPw1gDcB+JxzzonIMIAF51xBRO4CcBLAC1EGoy13NK4pbbVpqwvQV5vGHhnb+Jo7zO3lscfOY3X1uV2XnXl77R5tPdKY8b56wtKQJ/nL5XIH3yhBz/g4Zz+/trqYLl97pLHXzDEZAaztl+mytZmcyzzJuowA1tpk5pevuaNtPEyXeXTjnNsE8DYAnwbwNQCfcM5NishjIvKG4s0+CmBQRC4AeBTAO4qX3wfgKyLyDIKT//2Ec24hyni05Y7GNaWtNm11Afpq09gjYxtfc0fj60dtPdKY8b56wtKQKdfe3q7Kc+3aFsWjrS6my9ceaew1c0xGAGv7ZbpsbSbnMk+yLiOAtTaZ+eVr7mgbD9NlHv04554E8OSey9614/83ALy5wv3+GMAfM8eiLXc0rilttWmrC9BXm8YeGdv4mjsaXz9q65HGjPfVE5aG/ARza2urKs/KiqN4tNXFdPnaI429Zo7JCGBtv0yXrc3kXOZJ1mUEsNYmM798zR1t42G6zGPUgrbc0bimtNWmrS5AX20ae2Rs42vuaKcsYHYAACAASURBVHz9qK1HGjPeV09YGnIH8+LioirP0aMZikdbXUyXrz3S2GvmmIwA1vbLdNnaTM5lnmRdRgBrbTLzy9fc0TYepss8Ri1oyx2Nayru2jqfPr3vpx5PrWh8rNDmYfbI2MbX3NH4+lFbjzRmvK+esDTkITKGhoZUeS5e5Bwsvdp4aj25FasupivuHqXdw3Qxx2QEsLZfpsvWZnIu8yTrMgJYa5OZX77mjrbxMF3mMWpBW+5oXFPaatNWF6CvNo09MrbxNXc0vn7U1iONGe+rJyz2CWYFHnsn6GB87ZHGXtunevhofAfa1mZyLvMk6zICtH1aBfA3d7SNh+kyj1EL2nJH45rSVpu2ugB9tWnskbGNr7mj8fWjth5pzHhfPWFpyE8wb2xsqPK0tQnFo60upsvXHmnsNXNMRgBr+2W6fF2bTzzxHCYm/n7f5WfeXrtL25ry1cN2GQGstcnML19zR9t4mC7zGLWgLXc0rilttWmrC9BXm8YeGdv4mjsaXz9q65HGjPfVE5aG3ME8NjamyjM5yfmqgba6mC5fe6Sx18wxGQGs7Zfp8nVtMnutbU356mG7jADWWtC4pnzNHY1ryjxGLWjLHeY8P/bYeayuPrfrsscfv79mj7batOUgoK82jT0ytvE1dzS+ftTWI3velJwnLA15iIxcLqfKMz7O2c+vrS6my9ceaew1c0xGAGv7Zbp8XZvMXmtbU7562C4jgLUWNK4pX3NH45oyj1EL2nKHOc++1qYtBwF9tWnskbGNr2tT4+tHbT2y503JecLSkDuYOzs7VXnm57coHm11MV2+9khjr5ljMgJY2y/T5evaZPZa25ry1cN2GQGstaBxTfmaOxrXlHmMWtCWO8x59rU2bTkI6KtNY4+MbXxdmxpfP2rrkT1vSs4TlobcwZzJcA5OzvJsbDiKR1tdTJevPdLYa+aYjADW9st0+bo2mb3WtqZ89bBdRgBrLWhcU77mjsY1ZR6jFrTlDnOefa1NWw4C+mrT2CNjG1/XpsbXj9p6ZM+bkvOEpSF3MF+/fl2VZ2yMM+na6mK6fO2Rxl4zx2QEsLbfaq7Op0/v+zkIX9cms9fa1pSvHrbLCGCtBY1rytfc0bimzGPUgrbcYc6zr7Vpy0FAX20ae2Rs4+vajPv142F6tK1NpitOT6XX/Ae97k/6+U5DHgjove89j2vXdp+k4czba/cMDw9TxvP885yDpbPGw/IwXb72SGOvmWMyAljbL9Pl69pk9lrbmvLVw3YZAay1oHFN+Zo7GteUeYxa0JY7zHn2tTZtOQjoq01jj4xtfF2bGl8/auuRPW9KzhOWhvwE84kTnHdeFhYWKB5t42F5mC5fe6Sx18wxGQGs7Zfp8nVtMnutbU356mG7jADWWtC4pnzNHY1ryjxGLWjLHeY8+1qbthwE9NVWzVPrJwmZPTK28XVtanz9qK1H9rwpOU9YGvITzKzDkDjHOgYNRUMbD8vDdPnaI429Zo7JCGAe+kjbWoh7PJWerK/c+3js4wH0ralKnmovZm7VI211sV1GAGstaFxTjZaDh+kyj1EL2nKHOc++1qYtBwF9tWnskbGNr2tT4+tHbT2y503JecLSkDuYz58vUDysj5trG4/Grxr42iONvbavjfJhbb9Ml7a1+e53n8PS0tf2XV7r4YuYvda2pnz1sF1GAGstaFxTcebO44/ff2jj0bimzGPUgrbcYc6zr7Vpy2VAX20ae2Rs4+va1Pj6UVuP7HlTcp6wNOQhMu65h7NffXZ2luLRNh6Wh+nytUcae80ckxHA2n6ZLm1rU5sH0LemfPWwXUaAz2tKW23acpnpMo9RCz6vKV9r05bLgL7aNPbI2MbXtanx9aO2HtnzpuQ8YWnIlMvntyierq4uikfbeFgepsvXHmnsNXNMRgBr+2W6tK1NbR5A35rS5vnQhy5gauq5fZfXc9Jcyx0+Pq8pbbVpy2WmyzxGLfi8pnytTVsuA/pq09gjYxtf16bG14/aemTPm5LzhKUhdzCzeP/7n8HU1O6vCdTz1UrDMAzDMAzDMAzDMAzDMIw00pCHyBge5pStzbO8vKzKw3T52iONvWaOyQhgbb9Ml7a1qc0D6FtT2jwae21s4/Oa0labtlxmuip5Op8+XfHnsMZzmB5jNz6vKV9r05bLAPDxj38Fp09/ZtdPPfjcI2MbX9emxteP2nqUludNPnjC0pCfYD53btNLz+joqCoP0+VrjzT2mjkmI4C1/TJd2tamNg+gb01p82jstbGNz2tKW23acpnpMo9RCz6vKW21vec957G0FP0wVdpymenSlhfMHhnbaFubGrcXX3tkz5uS84SlId9Gu/vujJeefD6vysN0+dojjb1mjskIYG2/TJe2tanNA+hbU7/2a1+kfKJH29wDljtx4POa0labtlxmusxj1ILPa0pbbdp65PNzXY09MraxNZWcS1uP7HlTcp6wNOQnmAuFg2+TRo+IqPIwXb72SGOvmWMyAljbL9OlbW1q8wD61pSvcw9Y7sSBz2tKW23a1ibTlRZPpUN0rNz7eOzjMXbj85rSVpu2Hvn8XFdjj4xtbE0l59LWI3velJwnLA25g3nvifl88QwMDKjyMF2+9khjr5ljMgJY2y/TpW1tavMA+taUr3MPWO7Egc9rSltt2tYm02UeoxbSsqZqfUOi2piqHXv8Vq609KhWfH6uq7FHxja2ppJzaeuRz8+b3vOer+HatWd3XVbrIZCY4wlLQx4i4+RJzn51bR6NH6NnueLsUT0nq/G51/a1UT6s7Zfp0rY2tXkAfWvK17kHLHfiwOc1pa02bWuT6TKPUQs+rylttWnrkc/PdT/0oS/tO0RZPYcpY/bI2MbWVHIubT3y+XmTtl6HpSFTLpfjvPOizdPT06PKw3T52iONvWaOyQhgbb9Ml7a1qc0D6FtTvs49YLkTBz6vKW21aVubTJd5jFrweU1pq01bj+y5bnIeYzfa5kfbdsd0aetRNU8931LR9vxCW6/D0pA7mFtaOMchqeSp56tSrPEUSAfFef/7v4wXXtjvevzx+2t2scakrUfaPEwXc0xGAGv7Zbq0rU1tHiDeNeXDY4XGXhvb+Lym7Hlcfa56atOWg/ZcRzfacoc5z9pq09Yje66bnMfYjbb50bbdMV3aelRtv1U9h5LQ9vyC1Wvmvr0wNOQO5sHBpopNTrtnZWUFQ0NDasYD6BsTazzaPEwXc0xGAHNNaVsL2nJQY379zu98FRMTG7suq+eJD6u2SuMBan+iwex1pTHF9cSnUfB5TWmrTVsuA7zc0ZaDcY4HsNyJirY1VW2eD/MxWJtHWy4zXdpqY/bI2Ebb/Gjb7pgun3ukbV+KtjkLS0Meg3lyctNLz9jYGMXDGg+gb0ys8WjzMF3MMRkBzDWlbS1oy0Gf88tXD9tlBGicZ1tTt4b5+KttTL6Ox9iNtjWl8XFKm0fjmvK1NsudeNA2P9q2O6bL5x5p25eibc7C0pA7mMfHOR/c1ubJ5XIUD2s8gL4xscZTzVPryQJZ42G6mGMyAphrStta0JaDPudX3J5a80vjdm1so227AxpvTdUK8/FX25hY4/ngB79IOdmWZU48aFtTGh+ntHk0rilf88tyJx60zY+27Y7p8rlHlbKwHrTVlnTuHPoOZhF5QESeE5ELIvKOCtcfEZE/LF7/JRE5EfVvfulL9W0s2j1/+qd/SvGwxgPoGxNrPNo8TBdzTFpJOneYa0rbWtCWgz7nl68etksrac0dW1PJeZiPv6wx/czPfIjygktbr33LnCj5IiI/V7z8ORH5zijj0DY/Gh+nzJOcy9f80k6jP9/R9lyH6bIeHUyl2ip9iOegD/Jom7OwHOoOZhHJAPgggO8C8AoAp0XkFXtu9jCAq865lwH4FQDvi/p3z579bFSFSs+nPvUpiqfaeGpdFEmMqVb+03/6XcoTDVZdLA/TxeqRVg4jd1jbL9OlbW1q8wDWo6Q8bJdG0pw7tqaS8zCfE2irzVePBqLkS/F2DwEYB/AAgF8v+upC2/xofJwyT3IuXz2asec7+p7rMF3Wo4Nh7UvRNmdhOexPML8GwAXn3AvOuXUATwB4457bvBHAx4v//ySA14lIpFMqHjnCOSOjNs/mJuf4KqzxAPrGpK3XLA/TxZx/pSSeO8yeatuGta1Ny6/0edgupaQ2d2xNJedhPifQVpuvHiVEyZc3AnjCOXfTOfcPAC4UfXWhbX40Pk6ZJzmXrx7lNPzzHW3PdZgu61HjesIizrlE/+CuPy7yJgAPOOf+WfH3HwLwWufc23bc5u+Lt7lU/P1i8TZXdrqefPLJpZmZmfIO856envzAwMCu25RYWFgYqnZdLZgnfWPy1aN1TDs4/rrXvW6Y7KyLw8gdn+fZV4/GMfnqYbt2YLnj6TybJ31j8tVTgcRzJ0q+APj3AP7GOfd7xcs/CuAvnHOfLN3XXmPpHJOvHo1j0uapgHfPdyx3bE0l6dE4Jm2eClTMHW+ONP/d3/3d3Yc9BsMwGgvLHcMwksZyxzCMJLHMMQwjaSx3DCOdHPYhMl4EcGzH73cUL6t4GxFpBtALYD6R0RmG4SOWO4ZhJI3ljmEYcRElX8Lc1zAMIyz2fMcwGpjD3sE8AeCkiNwpIq0ITjJxZs9tzgD4keL/3wTgc+4wj+thGEbasdwxDCNpLHcMw4iLKPlyBsBDInJERO4EcBLA3yY0bsMw/MOe7xhGA3Ooh8hwzm2KyNsAfBpABsDHnHOTIvIYgKedc2cAfBTA74rIBQALCELKMAyjLix3DMNIGssdwzDiIkq+FG/3CQDPAtgE8IhzrnAohRiGkXrs+Y5hNDaHepI/w0g7IvKtzrkv1HnfLgAnALwMwGnn3A8Qh2YYhodEyZzi/S13DMOoCXuuYxhG0ljuGIaRNJY70fHmJH9hKR7npwkAnHPrETwC4DYAM/V+pUNE7t57mXPufB2eUefcbD1jqOB6EMA3APh759wf1+n4KoAPA/iIc+4GY1xREJFjAK4555YIrm4APwTgdgTvyp5GECS1ev4tgB8GcAXAywH8uzrH890AfgHAGIAXAPy0c+6ZelxGfDByh5E5RY/lTgKwcoeVOUWX5U4DYblzoMtyp7pH1XOdostyRzmaXmMVPd7ljrbMASx3jMPFx9xhZk7R51Xu+Lxvp+hKde40zA5mEflhAI8BKAXGCIDOOl3/I4DfRnAw+gER+VHn3F/Vofrwnt8dgG+vw3NGRDoBnAPwK865p+pwQETeh+CA+/8VwPeLyGuccz9bh2qj6Pl7EfltAL/mnFusc0wzCL6ytwDgCwAec87VehKATwDoEJG/A/B2AL/jnPueesYD4PcAfAXA88XfV+v0fC+Ar3PObRWD7TMAPliH570AfgDABQD3AviPAO6rVVIM6p8E8BJsP0i/pY7xGDtg5Q4xcwDLnTBj0pQ7rMwBLHcaAsudg7HcORBtz3UAyx21KH2NBfiZO7TMKY7JcufWWO4oxfPcoWQOoC93lGUOYLnDxznXED8AzgLo2/H75yO4/grAHcX/3wHgrw67vuJYvh7A5wH8T3Xe/4t766zT87nivz0Afg7AcxHrEgADAP4XBEHUVqfnlxC8C/SmCGP5b5VqrcPznXt+/+d1ej665/f/UqfnrxAE0LcWf74cZc7sp9xXSu5ozZzieCx3bu2JlDuszCne13KnAX4sd0Ld33Ln1vdX9VyneF/LHaU/rMzZMT+WO9Ud1Mwpuix3qrssd5T+NELuRM2cokNd7mjJnKLDcof804TGoRnA9R2//3UEl3POXRKRH3LOXapXIiJfEJEWEWkt/dTp+TkROQ3gOQDfB+BtdQ7p5p7fN2oYw10icr+I3F+6zDl33Tn3fwB4ZZ3jKXmcc24BwCcBPAXgf63VISL/BsE7P693zn0ywnA296rrkTjnPr3n99+s0/NweSAifQC66vEAaHHO/YZz7gsuOO5Q3Z+GMHbByh1K5gCWO2FRlDuUzAEsdxoIy52Dsdy5Naqe6xTva7mjF3WvsQB/cifOzCm6LHequyx39OJt7hAzB1CYO4oyB7DcodNIO5g/AODTIvLDInKXc+7nI7h6ROQNAP5l8ffQL0z28FoEwVH6OVen5wKCBfYbLvi6wladnskDfr8V34DgmDWnEZw1toxzbm+whUZEbheRHxORP0LwDtU9AN5Uo+NMcXyXEczdvmMj1cCfHPB7oojIX4vIF0VkAsBXAfxynappEfnxHQ+Cb+SMsOFh5Q4rcwDLnQNRljuqMgew3EkBljsHY7lzayx3jFrQ+BoL8Cd3YskcwHLnICx3VONz7rAyB1CWO8oyB7DcoSPFj097j4j8fwD+EcAlBMcyGXPOHavT9dsI3g163Dn3lyLys86599Xh+bxz7tvqGUMF1wkAZwB8CMD/5pyreaGJyF9j+zhGwPY7OM45981Rx1gPIvIVAE8C+AsATznnNkXklwH8gXPubEjHW5xzf1B8B+5fIPg6zeviG3VyiMjx4n83EZyUoK4HIBH5OQDvBLAC4GsA/sY59zOcUTYurNxhZU7RZblzAJY7t8ZyRzeWO6Ecljspw3JHLxpfYxVdljsHYLlzayx39OJ77jAyp+hRlTuWOQeT9txppB3M4865yR2/t7r6z6o+jGBjfgmKJ0p0zv1YHR5WAF0GMI3gXbLzAM475z5Rh+d4teucc9n6R1g/InIHgH+F4MyeTcFQ3D89jLH4jAQnAPhlAHkA4wDudc79X4c6KA9g5Q4rc4ouy50DsNxJBsudeLDcCeWx3GlQLHf4aHyNVXRZ7hyA5U4yWO7w8Tl3WJlTdKnKHcuc5Dis3GmYHcwAICIvwe6zKP7XOj1PInjn5QKK7wi5PcddCel5t3PunfWMYY/nFID3Izgo/bMAfto591xUrwZE5LMAfh/APyB4x+3/dM79kxodAuD12D33dR8XxzBqgZE7rMwpuix3DsByx0g7ljvpw3LHSDPaXmMVXZY7B2C5Y6QZX3PHMudAx//P3rnH2VTuf/z9nRkkknsMQrmXVETDNK6FmlFu53C66DgqUnK6X4SjmzqJUynSj1KhlFSiU6Eo0lVKNymEnFCuE3N7fn88ay979uyZvffMsmfb832/XvPas9fls56196zPfJ/b91HPiWHKTAOziIwDLgI2OpuMMeZvxdRaGkvD8EVkJXAT8CXQFbjNqylhpY2ILDPGdPN7H3GvoIi8DORipwYYYIgx5hRvS3psIyL1gHuBJkAiQGlN14snvPKdWPMcUN8JQ0N9JwTqO0cH9Z1jE/Wd6KC+4z3xXMcC9Z0wNNR3QqC+4z3x7DvqOSE11HPCoLR8J+loXyCGON8Y094jrWKtLllARORXbG6V34H3gAnGmN3FkMo2xnzs/P6WiNzuRflilOL0iCT7P0wi0sW74sQN/we8CEygZAsJKPnxync88RxQ3ykm6jtHB/Wdo4P6TnygvnN0UN/xnpirY4H6TjFR3zk6qO94Tzz7jnpO0ajnhEep+E5ZamAu0Sq7AQiAiPwXOAPbY5YcqYgxpq4zxL8a0AN4RUR6GWMOFbtgIicBxxX3/BikrYiscn4XoGVxRESkpTHmW+ftOE9KFl9UNMbMKu1CxCFe+Y4nngPqO2GivhMd1HeODuo7xybqO9FBfcd7Yq6OBeo7YaK+Ex3Ud7ynTPiOek5w1HPColR8pyw1MNcXkav9N5QgV8tA5/yeJS2UsTlKfneG+rcBrgf+HaGM70EtD9QAri1puWKIMzzQmAR8KiJrgA+AjzzQjDe0N/3o4JXveOY5jo76TtGo70QH9Z2jg/rOsYn6TnRQ3/GemKxjOTrqO0WjvhMd1He8J559Rz2naNRzwqNUfKcsNTDPAep6IWSM2eWFjogkA72A3sA5wGfYZO6RBj6+B/WwMWaHF2WLFYw3q5veClwObAPaYf+JLPZAN56YU9oFiFM88R2vPAfUd8JBfSdqqO8cHdR3jkHUd6KG+o73xFwdC9R3wkF9J2qo73hPPPuOek7RqOeER6n4Tlla5O9rYDowoyRTo7xERNZhH4YlwIfGmBwRmQTMMcZ8Vrqlix9EpA625y8Zm+DcGGOGlm6pYgsR+RnbyzUVeBeYb4xpXrqlOvZR3ym7qO+ERn3n6KC+U3ZR3wmN+o73xKLngPpOtFDfCY36jveo75Rd1HPCo7R8pyw1MH8OvAP0A54BHjfG7C3lMtUHRmEfjgTsw3FpaZYpHhGRt4BFwI84ieSNMf8t1ULFKCLyLlAbyDXGnFXa5TnWUd8pu6jvhI/6jreo75Rd1HfCR33HO2LRc0B9J1qo74SP+o53qO+UXdRzIiPavpNwtC8QQ+wxxtyGHUafB3wc4vhoMAv4BpgBPEUxk5wrISlvjHncGPOWMea/akAFEZHjReQ5YBfQCdhUuiWKG9R3yi7qOyFQ3zlqqO+UXdR3QqC+c1SIRc8B9Z1oob4TAvWdo4L6TtlFPScMSst34joHs4icAjTx3+b0bD0gIo+UTqnykWiMecb3RkRKvdctTkkQkXLYEftZpV2YGGUVMN0Y8ySAXfxWKQ7qO4qD+k5o1Hc8Qn1HcVDfCY36jgccA54D6jvRQn0nNOo7HqC+ozio54RHqfhOXDcwA62BS5zf8/VsGGMOR784ISkb+UqiTwfge0BEJBF4zxhzRSmXKdYYaoz53O/9wlIrybGP+o4C6jvhoL7jHeo7CqjvhIP6jjcca54D6jtHC/Wd0KjveIP6jgLqOeFSKr5TZnIwxyJOj9Z631ugpTGmaikWKS4RkQedKTS+9+8ZY7qUYpEUpdRQ34kO6juKcgT1neigvqMoR1DfiQ7qO4pyBPWdo496TmyjDcyliIg0DNxmjNlcGmVRFKVsoL6jKEq0Ud9RFCXaqO8oihJt1HeUso42MCuKoiiKoiiKoiiKoiiKoijFIqG0C6AoiqIoiqIoiqIoiqIoiqIcm2gDs6IoiqIoiqIoiqIoiqIoilIstIFZURRFURRFURRFURRFURRFKRbawKwoiqIoiqIoiqIoiqIoiqIUC21gVhRFURRFURRFURRFURRFUYqFNjAriqIoiqIoiqIoiqIoiqIoxUIbmBVFURRFURRFURRFURRFUZRioQ3MiqIoiqIoiqIoiqIoiqIoSrHQBmZFURRFURRFURRFURRFURSlWGgDs6IoiqIoiqIoiqIoiqIoilIstIFZiVlEpLOITBWRr0Rkn4jsFJEPRWSwiEgh51woIqtE5KCI/C4i80WkcZDjbhKR90TkVxE57LwuF5G+EZbxRBF5TES2icghEVkvIiMKK5+iKGUPEUkRkddFZKuI/CkiG0VkhoicEoFGsojMdnzwTxH5VEQGHs1yK4qiKIqiFIaIdBERU8jPogh0EkTknyLynVOf+kVEJolIpaNZfkVRFMVbtIFZiWUeBC4G3gNuBu4HEoE5wFOBB4tIP2ARUBG4Bfg3kAZ8KCLJAYe3BzYBk4ERwCTgeGCBiNwdTuFEpDzwDjAceBG4HvgeeAIYF/ZdKooSt4hIL+ADoAXwONYnXgf+BnwqIvXC0KjuaPQDngRuAA4AL4nI349S0RVFiXFE5HwRmSYinziNMkZEuoR57hkiku2cMyBgXzlH9zMR2eV0xP8sIi+KyFkRlM+TznxFUWKep4DLA34ejuD8ycAjwDfYOGk+MAp4Q0S0vUJRFERkiIj81xmwc8gZdLNaRK4UkcRCzjleRMY6gwD/dAYgro4kDgl3AKNiEWNMaZdBUYIiIp2BD4wxuX7bEoDl2Ibj1saYr53t5bANxjnAacaYA872M4HPgP8zxlwd4npJzrGnAFX9r1vI8dcCU4FRxpjH/La/AmQATY0xmyO6aUVR4goR+S/QFUg2xuzy2z4MmAH80xgzJYTGQ9hOsz7GmDecbYnAauBUoKHP8xRFKTuIyDPYzqqvAQHOBLoaY94LcV4C1j9aAZWBgcaYl/32VwLeB1YBPwH7gZOBvwN1gF7GmGVhlO9F4E9so9EuoDowENvJP9YYc0/4d6soSqzhdGgtB/5ujHmmmBqnAV8Brxpj+vttvx54FLjUGDOn5KVVFOVYRkT+A5wEfAn8ho1fLgLOB2YaY/4RcHw1YCnQFJjlnFcJaAl8H6r+5Wj0A152zp0BnAiMBnKBdsaY7Z7cXByhPYJxiNOLEzhN6aCIrHNGkyQEHL9JRD4IoflMIdOf9orIChHpU8TxOSKyXUTmiUjzcO/DGPN+YCOvMSYP+5ADnO63qzOQDDzt39BijFmLHQH9V6cRuqjr5QDbsMZT5LEOfwMysWbjzxTn/L+GoaEocYWf//Tw23a609O8Moj/5DteRHo67y/zO2aUiOQFnPe1iHwaoizBPCtbbEqbZ0Xk5IDjxzvHNHHeb/I777CI/Ch2yuaJEXwkVYBDwB8B230BycEwNP4GbPQ1LgM43vgYtsHmwgjKoyhK/HAXcIIx5mzghQjOux44DTvTqwDGmIPGmHbGmFHGmCnGmP8zxowDOmAbsm8O5yLGmL8aY640xjxkjJlpjHkY6ASsA24tbMSRohwLiEhzJz4Y47etj7PtZL9ti0TEv4PZV0dKct6ni0iuE5v8R0SOC/P6gTph171EpI7Y2QkbROT4gH2+tBfDIvw8KoVb9gAGY30lsLFnBraedVmBMxRFKXMYY24wxgwyxjzgxCX/McZcACwG/i4idQJOeRRoAnRw4pn/M8Y8aowZEWbjcjlsXesX4DxjzBPGmAeAntiG7vFe3l+8oA3M8c3N2JFzXbGNncuwlYkHi6E1ERsAADzvaHbDVlISgIUicmHA8b5rZ2BTUKRi01XULsb1/anvvP7Pb9s5zuvqIMd/hG3kaRa4Q0Sqi0gtEWkpImOBXsByY8yhogrgNJKdDXwR5NiPAeNXJkUp0zgzDe7GesCNhRzma0De6Lz6Tz2qDxwOOL4SdtZCUXQFFdoldwAAIABJREFUnnV+v4wjfvQotsf7vcCKVQCDyO+hrwDXYlPxhMt/gROAZ0WkjYjUE5GeWE/8FphX1MkiUheoh/WxQHzb1GuUYxKx6xhki0jQ58Bp5Hg+4L3v50+xUx7HikiFgPMecI6p77dtgYgs83tf0zmm0GncItIo4JoHReQLEblNbJos/2MTnA73wyJyehCtYt1LURhjthljAr2xSESkAXAvtmK0JZJzsSOGDgHVIjzPpRid+YoSq/yMjV0C4xXIH7OEildWAxdgYxPf7MjiEHbdyxizA5sisAnwUCF6eYVsD8Z/sKm7/hSRH0TkBpGw16M5x7nWxwFlPASsRWMcpQwhwQcKGhHJFDtY8BbxG6wjIpWd/X84cU4jr6/hnOMOSJSCudf3i8hHInJN4HMf5NjCfkqSXnQztpPKHQDkfA5/A2YYY74RkUQRqRyhbokHMJZFkkq7AMpR5cuAaZKLnJ6dkSIy1hjzZ7hCxpjvRMTXkLrZX1dsSohN2Iajxb7jge/8JJaIyIfYIGowNhCJGLG5lK/GTtn0H3Xty7G8Lchpvm31gPUB+34Aaji/53CkASkU1bC5ngtczxhzWOxIhZC5VRWlDDEJ6APcIyKLjTHfONt9/4f2Oa+bsdOO/CtsDYE9vjdO0FMH+/wWijHmPTmSj3SNMeZH5/e3RGQTtnG3H7bTLNj5gY26C0XkD+ABEWljjPmyqOs7PADUBoYCl/ptXwwMNsbsD3F+uN6mKMccxpi9IrIKOF9EEpxZSkXR1e/3Ws77cdjpj5f77fPvqNrq/F4f2O13jG/xqE1FXG9HwDWTsT42ETgDv2faGJMnIldip1HOFpEOxpjsAD3/+wv3XrzmSWwMNYUQIwPFjjCuhvXpBtiBC5VxYr1wEZtHPhGoiU2REVZnvqLEMsaYLBHZSsF4BWCv37Z6QKEzrowxu7HTuJeKSGvgUhEZZYwJZ4aTv05EdS9jzHwRmQtcKyKvGmOWOrsC47KiyMauK7EYOzMrGfgH1l/OxKbVCUUysKuQzrJtQEcRKW+MyQpDS1GOdd7CxgPzgJ3YwXxg44QLsR1CNYHbnO1/OsefjI1N3hKR053OXK+uEchajsQwgo0PLgOmOeW4q5BjgzEcO4gn2ECaoIidSVoOG5/0xNaxfgB+9DusF3YQ5Dci8hzwF6C8iGwDJhljJodxqVADGLthBzAGti+VabSBueyxCvsQtwC+8ELQGHNQRNYAKSGO+0hE9mLzJ0fcwCx2pOGr2MpNn4CKm28UYrDg5FDAMf70A47DBn8DsY3GJ2DNtiiKup7vmkWNjFSUMoXT+DIG2+P7rIikOMFPI+yI/x+d47JFZAtOhc3pCe+Azc/nozn2uf2sBEXyVaTOopAG5kL4L7bROA3bkBSKXGwF6V2sf/2OnSJ+PTBPRC4O0gjlT3G9TVGOFRZjn6cO+AXxfqNg3MVCguQWnu90OA0TkdFOQw3kb2Be6fze0G87HOmYKbSjymkADbzmHBH5HRghIo8aY9b4Hf+TiNwETMfO2hjr3EuBBpsI7sUzROSv2MpjJ2NMThgDDFuS33v3Yv3vgQgvXdzOfEWJdTaSv4E5Bdjg6zwRm8/8VKwnhMNn2I6rZnhQTwuj7jUWGADMFJHWxph92LgMYEMY+h9iF2R3EZEZWF+/UkSedo4piuMpuj7lO0YbmJW4x5ldsMMZ2Lc3IFaYHzBY8LCTMu89ALEzq2YAXbD1Dk+uEeT8PRSMjWaLyJvA7SIy1ZebuJBjccqbCMzG1gHfLqy8QVgKtPUVB3uvwwNSq/pSAz2AXQNiONZDhgOPiEhVJ/VXURR3AGOZRlNklD18lZuqHuvuDVNzH0cqGWEjNqfXQqAddiGJlQGHZDqvwaaWHhdwjIsxZoUx5m1jzCxjzIXYhWw+FJsUviiKup7vmgWupyhlFRG5CFvh+A77HN8pIlWwFamlTgDiYyNwijNj4RFsw9AzfvvbO69rKD6+0UWReqHvvHB97BnsaJ6BTu6vV40xNwM3AL2BISHOL5a3KcoxhG80bO+A7b4RxqFGuf4XOzq2o9+2fKl2ROQU7EwC/8bSNs5rcTqqnnBeg+U/fwb4HrhDRNo52xo5r6EabILdiyc4cc1/sNNFg43GCcbP2MVzLsJ61g/YKahhp/Fw6MeRUUbvcKQzX1GOdTYCDcTmNL4FOI/88Uo7bH073HjFV08rdhqaQjQLxCwicg52FN5P2FGHU5zp3sOwz/q64lzMmYni64S6KIxTMim6PuU7RlEU27haiSCpPzkSz7Q+itcoiiexftczcEchqSQuwo5+nmaMMUH2F8a12NjkCuAljoxm9scXY5TH5k+eZYx5ATvq+EfsOhChfFYH+RQDbWAuu/gvrHKQI6P5ioshvL+nPCIcOe/XuNwDGGaMCTba0LdgVrCp4r5twXqfAnkWO/W+X4jj/sBOSSlwPbH5E2uGeT1FiXuc2QfPYhsWTnNex2BH5yRRcCSbr7KzDZsj8KGAFcQHA98YY7ZSfHyBTGLAtg8ouCCfP74p7iF9TOwiP5cCbwZJSTTfee0cQsYrb1OUmMQY8xV2AZXABuZazmuoFbqDdfpsxY5UaSoiLbEjerLJvxBee+zimcUZKeybhlnXf6OTCmINtuPqAHa2RgWsj+UAr4XQjbQDKxL+jZ3Kenu4JziL/b1rjFlsjHkUWzE7HzsCOWxK0JmvKLHOT9g44ldso+ps8uc0Hox9rsNtYPY1tFbxqoAEqXs5M0SewXYinQE8jU1n8RV25N/fI2zwCWST81ozjGO3AzUleP75etj0GTp6WVEsRQ2Q8aqDqriDcArERiKSJCIvAsFSUgzHNtTOiuQixpiPndjkOWPMIGxH2QoROdXvMF+9a5F/nOfMGp2D7bw6N8SldJBPMdAGZgWgXRhTBODI30vU/sn7NS5fAFxtjCnMgD5xXoOl6TgXa7hF5mt1qOi8Vi/qIKd3/nPgrCABUXtsJa7QfGuKUsbogW0wedJ5doZi/yFXA840xgSO6vONPkwHahlj3BxgItIB28DxdJjXjsS3HjLGnOfh1HRfA3BikH1JAa9BMcb8im1ADhYE+bap1yjHOouBtpJ/Iaoznde1Ic4t0Onj+MwmbAfPN9gGlMuMMZvBjS0uwY4Yjhi/3MGBI1fuBU7BPpvXAa2wqXRuAP5pjNkU6b14gYicjfXdx4EaItJERJpgR3UD1HG2FTky2VnkZgHQM6AiFynhduYrSqzji1eGY+OVIb7cp84iU5cBz4ZIheVPE+f1ZC8LGYTWWH962mm8vRHrmacCHYwxq0qo39R5/V+RR1k+wcZq7f03Oj59JhrjKIo/wQbI+PCqgyrYNcIZkBgsNkrC5j8O7ORqiB3p/KIx5vfiFxWwMcXxwJV+23yDkHYEOf5X5zVUQ7wO8ikG2sCsEMFif75erFD5iT3Bqei8im1cHm6MKapB6X2sWQzzXyFURNpg8xDN9wV3IlIp2CqiTh6gkc7bj/y2lxORFs5oRH/mYs3s6oDto7EjlV4MeZOKUjbwVTQ2Azgjj2/A/mO/Ncjxvgpbrv8ieM5IxHnY6efhrrIetm9FsvBpmHyPzcF8iYgEjgK40nn1dY4hIsc7XlM34Ni5wKkikuF3bCI2j/MeIlxwS1FikMXYjln/aZWXYWcTRJKXz5+N2Lx7zYF6xpiX/PZdj0318H/F1C6AMyLwr8BiY8wmZyrmK871rzLGPO7VtYrBydjPdwI2TYfv50Fn/2PO+3Cm1YbVER8FDUWJBXzxihhj3NlPToqvBdjO9H+FI+RMIU933p7lZSGDEBiX7ceOYE7E+kRYiEiw1BsVgPHO2zcC9p0qIi0CTnkR26A1OmD7Vdh61gsoStkjgcgH9UXaQRXJNcIdkBguVzvXfyLUgWEQLKb42HmtH+R437bfQuh6NYCxTKGL/MU3bUQkcAXRwH/qIXEWnbkIO9oHYEUY57TAjk4J5DjgRBHpAqwNyLsayAvYFUDfBTJFJHC183XGmHXgLgx2AzZIWeksMFEF+Ce2YcnfEJsC74vIy9gGoN+xvVCDsRXBZwNyPNcDvsU2Ynfx2z4DG4w94oxS+Babj7EvcG8YI5UUpazg69Bx/cgY86yI9AVuFpHXAxaB8VXYejn+czI2lUQ/7HTOXqGmSzqj61pivevT4jQei8i5HJkC5cPnaw1FpEuQhbpcjDG/i8gU4CbgC8eXfIv8XYq9T/+Os/bAcmxP/JV+2ydiFyGdIyKPYHvLB2NXNx7m3wivKMcoS7E57noDz4nICOzzfp0x5mAxNTdiY4hf/P3C8Z0JwExjzOclK3Y+qjs/m/22jcDmZL1LRF4qwb2UlI+xHhJIF2zH+iRsx/pGABGpBex2RoK7OAv/DMSm/1jvt/1E7JTYXcaYXc62SthGtwMBGkE78xXlGMUXr3QWkc3Y56AjMAibCub8UKPzROQ0bJ7267Gj7XZjZwkkBD6DIXQiqXsFi8veE5HHgFEistAYMy+My74lItuxuV+3YxfFugxb13rMGPNxwPFLsetquCuMGmO+EpGpwHUisgDb4dgSGIWte81BUcoeJxL5oD7frKBwO6jCvoaXg3CczrShwGdBPKKwc5KAEwuZZXq98+ofU6zAxmMZIlLPGLPN0amEzd28h/wLS9fFfh5bjDG+tBf+Axgn++IZvwGMsyKYnVJm0Abm+OZhj3TKYRtuDwLjjTHhrJR5O4UvXnUSthGlK4WsKurgWxynh/MTyL/wW4DCGDNfRP7E5nZ9GFtZXQrc5jMVh63Ac9hKX19sEvi92Hyw9xBmIGOMyRKRHtgpsYOxKQA2Yk0u3NGVilIWkEK2X4NtbH1WRNr4Nb74Kmw3YEew/IFNSXMdtgMonN72NGCaozUyxLGFMQ9bEQrGZc5PYffm4xZsR9Yw4E7s9LVt2IUwxhu7YnuRGGN2i0gnbEPzSGzF8BtgkDFGZ0ooxzzGmIMisgLbqPJf7Myle40x+f6XOg0kgfhSaTQXkXONMb4Kxkbs8zlYRHZhF6tJx3ZWLaT4vlAYwRpsdorIcOxIxknYafRAxPcSFBE5A+jjvO3kvF4uIqnO748ZY/Y6q7m/HOR8X5k/Msb4778UGC0ir2I79bKwn98Q7MyTYX4VMLCx1CxsXDbe2RZpZ76iHHMYY/aIyO/YBuVLsI0WXwFjgacCO1gKYSg2vvkI+BuQgR3VdwnWO8IlkrpXYbHL7diOuakissLxjqJ42Snn9dgZYwex9alxxpi5EZR9NDZFx9XYgQG7sDMrxkbSyK4oxzoi0hm7CHEVwhvUVxc4HTvIrQ92ANxVItLCGPOdF9c4ClyC7Qy7K4JzKgNbnbjka2z6nTqOVjtsm4/bhmOMyRWRa4HXgdUi8gQ2lvk7dmHBfwR0+j+A9U+3fSrCAYyKg5Qsf7+iKIqiHEFErsQ2NJxvjHm3lIujKEqMIyJnYRs0r8Au7PchcJcx5v0gx4YKWjcbYxo5x2ZgKxZ52BG3v2EbcF4wxrzlQbmNo3WZ874RtjH2PmPMmIBjn8N2SPX2XTuSeymiDFdS9OI4jYuaTeV3/kD/BmYRaYutQHXAjsgsj63MrQL+E5if1U/nX8aY8c62mtjG5vOwlTn/zvxngDklXERMURRFUeIKEVmK/d+7BBgS0JmLiAzDNiJ3dWYdZGBTiv6InTX1P+wMo8eMMaO8uEYEZW9EQBzk5FL/E5hujBnubHsXOBubviyskdEiUh64HzuA6BRsh9Z+517nYjv0CowmdhrTx2FnfSZiY5CJxpjA9D3P4DQwB96ziKRjBzCeQf4BjBtRCqANzIqiKIpnaAOzoijh4izysgnb+DsXeMYYE2pRP0VRFEVRFCXGCdbArMQ3miJDURRFURRFKQ32YKdDv22MCVwzQlEURVEURVGUYwRtYFYURVEURVGijjFmL3ZBJ0VRFEVRFEVRjmE0RYaiKIqiKIqiKIqiKIqiKJ4gIknY/MWfGmMWlXZ5lKOPNjAriqIoiqIoiqIoiqIoiqIoxSJuUmS89957pkKFCmEdm5ubS2JiYomvqTrR01Kd6Gl5WSYfmZmZu7p3717LU9EYIFzfiefvOV51vNRSnehq+VDfid/vWXWip6U6kRGPvqN1LG+1VCd6WvGqE4j6Tmx9P7Gm46VWvOp4qRWvOoEU5jtx08BcoUIFWrRoEdaxmzdvpmHDhiW+pupET0t1oqflZZl8fP7555s9FYwRwvWdeP6e41XHSy3Via6WD/Wd+P2eVSd6WqoTGfHoO1rH8lZLdaKnFa86gajvxNb3E2s6XmrFq46XWvGqE0hhvpPg+ZWOAapVq6Y6UdDxUkt1oqflZZkUSzx/z/Gq46WW6kRXS7HE8/esOtHTUh0lEmLt+9Fn6tjT8VIrXnWU/MTa9xNrOl5qxauOl1rxqhMuZbKB+c8//1SdKOh4qaU60dPyskyKJZ6/53jV8VJLdaKrpVji+XtWnehpqY4SCbH2/egzdezpeKkVrzpKfmLt+4k1HS+14lXHS6141QmXMtnAfOjQIdWJgo6XWqoTPS0vy6RY4vl7jlcdL7VUJ7paiiWev2fViZ6W6iiREGvfjz5Tx56Ol1rxqqPkJ9a+n1jT8VIrXnW81IpXnXCJmxzMkVCnTp1jWscYw4EDBzDG5NtepUoV9u3bV+LyeKXjpZbqRE+rJDoiQuXKlRGREpcjnvDKK7zUilffibdnqizolFRLfSc4sRbrFEerrPlOrDxTqhMa9Z3gxJrvFEdHfad0dbzUijcd9Z3gxKvv6DMVPR0vteJNJ1LfKZMNzDt27PAk0XVp6Rw4cIAKFSpQvnz5fNsPHz5MuKutFoVXOl5qqU70tEqik5WVxYEDBzjhhBNKXI54wiuv8FIrXn0n3p6psqBTUi31neDEWqxTHK2y5jux8kypTmjUd4ITa75THB31ndLV8VIr3nTUd4ITr76jz1T0dLzUijedSH2nTKbIOO64445pHWNMgaAHICHBm6/TKx0vtVQnelol0SlfvnyBER+Kd17hpVa8+k68PVNlQaekWuo7wYm1WKc4WmXNd2LlmVKd0KjvBCfWfKc4Ouo7pavjpVa86ajvBCdefUefqejpeKkVbzqR+k6ZbGCuWLFiXOrEyh/h0dBSnehpeVkmxeLVM+6lVrz6Tjw/U/Gq47WWYok1r/BSK9b+hmNNx0st1VEiIdZ8x0v/irW/vXjV8VIrXnWU/MSaX8RarOOlVrzqeKkVrzphXy+qV4sR/vjjj7jUycnJiYrO1q1b6dOnD+eeey4pKSlMmzbN3ffHH3/Qt29f2rVrR9++fdm1axcA8+fPJzU1lU6dOtGzZ0++/vpr95x3332X9u3b07ZtW6ZMmVKsMoWLlzpTp07l3HPPJTU1lUsuuYRffvnF3T9u3DhSUlLo0KEDt99+u9vrs2DBAlJTU0lJSWH8+PGelcdXpnCZM2cOTZs2JS0tjbS0NGbPng3AV199Ra9evUhJSSE1NZUFCxa451x99dW0b9+ejh07ct1115Gdne1Z2eMdr55xL7Xi1Xf69+/Pnj17gPj0nVmzZtGpUyfS0tLo3bs33333Xb5jtm7dSoMGDXjsscfc94GfW2nf1+OPP0716tXZvXu3u23FihWkpaWRkpJCeno6ABs2bHA9Ki0tjZNPPpknn3zSk7KXBWLNK7zUilffKa2YIJROYb6zZcsWkpOT3Wf0xhtvdM/Lyspi9OjRnHPOOXTo0IGFCxd6Vp5IKCzeycnJKTRWe+WVV+jUqROpqakMGDAgn1cpRRNrvuOlf6nvlOy+ItUqqp61detW+vXrR4cOHTj33HPZsmVLvvNvv/12GjRoUGr3VpTvAOzbt4/TTjuNW2+91T1nwIABnHfeeaSkpHDjjTeSm5vrSdnLArHmF7EW64Sjpb4T2nfGjx9Px44d6dixY742ks2bN9OjRw/atm3L0KFDyczM9Kw8kVCU78ydO5d27drRrl075s6d654TGKu9/vrrJS53mczBXKNGjbjSGTz4bcBOrfAi6f/zz3cvcn9SUhL33HMPbdq0Yf/+/XTr1o0uXbrQokULpkyZQufOnRk9ejRTpkzhiSee4F//+hcnn3wyixYtomrVqrzzzjuMHj2ad999l9zcXG699VYWLFhAcnIy3bt3p1evXrRo0aLANb3AS50zzjiDZcuWcfzxxzNz5kzGjRvHzJkzWbNmDWvWrOGDDz4AoHfv3nz44Ye0atWKcePGsXz5cmrWrMm1117LqlWr6Nq1q2dlioS+ffvy0EMP5dtWsWJFpk6dSrNmzfj111/p1q0b3bt358QTT2TgwIFMnz4dgKuuuornnnuOoUOHelL2eMcrr/BSK15955FHHmHKlCmMHz8+Ln2nf//+/P3vfwdgyZIljBkzhpdfftk95q677qJ79+75zgn83NLS0mjVqpUn5YmUrVu3snz5curXr+9u27t3L3fccQcvv/wy9evXZ+fOnQA0bdqUFStWAJCbm8tpp53mNj4roYkVr/BSK959xyuv8FIrlO80atTIfU79mTRpErVq1eKTTz4hLy/PHXDgRXkiJVi88/nnnweN1c4991zuuOMOVq9eTY0aNRg3bhwzZszg9ttv96T88U6s+Y4XOuo74eG1fxVWzwIYMWIEN954I127duXAgQP5Ruh98cUXbgNYad5bMN/x6dx///107Ngx376ZM2dSpUoVjDEMGTKEhQsX0r9//+IXugwRS37hlc7gwW975jmgvhOuVmG+8/bbb/Pll1+yYsUKDh8+TJ8+fejRowdVqlRh/PjxjBgxgv79+3PjjTfy4osvMmzYME/KEynBfGf//v089NBDLFu2DBGha9eu9O7dm6pVqxaI1bzoHCmTI5j3798flzpe5WQK1WNap04d2rRpA8AJJ5zgNkaCrXgMGjQIgEGDBrF48WIAOnToQNWqVQE455xz3OM/++wzGjduTKNGjShfvjz9+vVjyZIlEZfJq3uLROe8887j+OOPB6Bdu3Zs374dsCttHj58mKysLA4fPkxOTg61atVi06ZNnHrqqdSsWROAzp07e9JL5F+mktKkSRMaNWoEQN26dalZs6ZbKTz//PMREUSEs88+271fJTRePeNeasWr7wwcODCufadKlSru+8zMzHyB55tvvknDhg3zBXDBPrdt27Z5Vp5Iueuuu/jXv/6Vr9wvv/wyF154odvoXKtWrQLnvf/++zRq1IgGDRoUv8BljFjzCi+14tV3vByxFi3fKYwXXniB0aNHA3Z6pu8z8aI8XmCMCRqrGWMwxpCZmYkxhv3791OnTh1PrlkWiDXf8dK/1HdKdl+RahVWz/ruu+/IyclxB+hUrlzZPS43N5dx48Yxfvx4T8vkpc7atWvZuXNngQFGPp/NyckhOzvbs4bFskCs+UWsxTqgvhOuVlG+07FjR5KSkqhUqRKtWrVi6dKlGGNYuXIlF198MZC//cuL8njB0qVL6dKlC9WqVaNq1ap06dKFpUuXAgVjNS86R8pkA/Pcud8xePDb+X6KQ1ZWlifl8UrHKyIxsy1btrBu3Tratm0LwG+//eYG4ieddJI7Es2f5557zh1h9+uvv1KvXj13X3JysmtO999/v2tG/mWaOHEi55xzDn369KFnz56MHTvWLcv5559Pbm4uGRkZZGRk0L17d3fU7bp161xzvPnmm/noo4/IzMykffv2bN261T2nZ8+eLF++PKLP6Pnnn6dHjx4AtG/fntTUVFq2bEnLli3p1q0bzZs355RTTmHDhg1s2bKFnJwc3nzzzZCNtCNHjiQjI4MePXpw9913A3aV2YyMDBo3bszMmTOZNm2aW/bBgwezb9++IjV9vPHGG6SmpjJkyBC2bt1a4N4+++wzsrKyaNy4cb7zsrOzeemll/KNklSKJpjnqO/kxyvfqVWrFr/99luBc+LJd55++mnOPvtsxo0bx8SJEwHrC//5z3/yTbcs7HM766yzirzOwIEDycjIoFu3bjz++OMA/PTTT/Tu3ZumTZuyaNEiJkyYQN++fbngggsYMWJEWClzFi9eTN26dTn99NPzbf/xxx/Zs2cPGRkZdO3alXnz5hU4d8GCBTqSJ0IKe8YrfTq4wE9xdLwsU2kRa74TWJ5Y9x1fWTp37kx6ejqrV68G7KwE33116dKFK6+8Mujn40+48U7fvn3p3bt3ieOdtm3bBo3VypUrx8MPP0ynTp1o1aoV33//PZdffnlY11FiL0bxMv7yinj2nQEDBgBHt561ceNGTjzxRK644go6d+7M2LFj3YaYGTNm0KtXL/czCvVZR9t3cnNzufvuu5kwYULQc/r370+zZs2oXLmy22ClhCaYXwSLdaIV78RarAPqOyX1ndNPP52lS5eSmZnJ7t27+eCDD9i2bRu///47J554ojva2P9eCyPavhPs+9i+fXuxYrVwKJMpMtav9yZXi1cjGrzSEfGmv6BcuXJhHXfgwAGGDBnC/fffn290y5HySIHe15UrV/L8888HHS0YyJ133lloma699lp3umZ6ejrffvstlSpVAiAxMZE33ngDgD///JMuXbrQq1cvTj31VDZu3Eh2djZr1qzhn//8J9u2baN58+bUr1/fPee3336jZ8+efPTRR1SoUCFo2fzL89JLL/HFF1+waNEiwDbE/PDDD24eon79+rF69WpSUlKYNGkSQ4cOJSEhgfbt2/Pzzz8X+RlMnTrV/b1379588803tGrViquvvpoNGza4KSqGDx9OXl4eDzzwAC+++CJXXXVVkbq9evWif//+VKhQgWeeeYaRI0fy2muvufe2Y8cORowYwdSpUwskhr/55ptJSUkhJSWlyGsoR/DKc0B9J5TvlC9fPu59Z9iwYQwbNoyXX36ZSZMm8cQTT/Dggw8yYsQIKleuHPJzq169epGfwfz58wE7iqZDhw5cfvnlnHLKKaSnp3PSSSeRnp5ZIBdyAAAgAElEQVROeno6eXl5JCQkcM0117Bs2TJ69uxZqGZmZiaPPPJIvpxlPnJzc/nqq69YuHAhhw4domfPnrRr144mTZoANlB/66233GBTCY9Y8wovteLVd/Ly8grsi2XfOemkk1i3bh3Vq1dn7dq1XHbZZaxatYqcnBy2b99O+/btue+++5g6dSr33HOPWyEMRrjxztVXX01CQgL33XdfieKdX375JWis1q5dO2bNmuXOmrjtttuYPHkyN998c5HXUSyx5jtexl/qO0X7TvPmzdmwYcNRr2fl5OSwevVq3n//ferXr8/QoUOZM2cOPXr04LXXXnOvE6gTjGj7znPPPcf555+fr7HHn1deeYVDhw5x9dVXs2LFCs/SKMY7seY7sRbrgPpOSX2nW7dufPHFF/Tq1YsaNWpwzjnnkJiYGFQn1OyDaPtOYYv8BYvVxo4dmy//dnEokyOYTzvNm3b1HTt2xJSOMQUf1OIQzki07OxshgwZwoABA8jIyHC3165d272fHTt2uOkgANavX88NN9zACy+84DZw1K1bN9907e3bt1O3bt2IytSwYcNCe4oqVqzI2WefzU8//USlSpXIzc0lPT2dv/zlL9SrV4/33nuP1NTUfOfUrl2bGjVqsGPHDkaOHElaWhp/+ctfgpbnvffeY9KkScyZM8c1q0WLFtGuXTsqV65M5cqV6dGjB5988glgH/x3332Xt99+myZNmhQYHVwUp5xyivvZfvvtt1SrVq1AmRo3buweU1jZAapXr+6W9/LLL2ft2rXuvt9//51BgwZx1113cc455+Q778EHH2T37t3cd999YZdb8c5zQH0nlO9s3bo1X4qFePQdH/369ePNN98E7IyD8ePH06ZNG6ZNm8bkyZOZMWNG0M8t3AU6k5KSSE5OdmeifPvtt/mmuft0Gjdu7H4W/fv3Jy0tjVGjRuXT2rRpE1u2bOG8886jTZs2bN++nS5duvC///2P5ORkOnfuTKVKlahRowYpKSkFFgo544wzqF27dljlViyx5hVeasWr74QqT6z5ToUKFdz7O/PMM2ncuDEbN26kevXqHH/88e7ndfHFF/Pll18WeW/+FBXv+PtOSeKdN954I2is9tVXX7n6IsIll1zCxx9/HHbZyzqx5jtexl/qOwXx953y5ctHpZ6VnJxM69atadSoEUlJSVx00UWsW7eOr776ip9//pm2bdvSpk0bMjMzadeuXZH35k80fGfNmjXMmDGDNm3aMHbsWObNm8e//vWvfOced9xxXHjhhWE11imWWPOdWIt1QH2npL4DcNNNN7FixQpeffVVjDE0adKE6tWrs3fvXndBvu3bt3PSSScVeW/+RMN3ateuXeD7SE5OLnGsVhhlcgTznj3ePKwVK1aMKR3wJldTYb0cPowxjBo1imbNmjFy5Mh8+3r16sW8efMYPXo08+bNo1evXoA1oyuuuIInn3zSHZUGuOawefNm6taty4IFC3jqqaciLlNeXh7Vq1fn0UcfDXqub+pU48aNefDBB2nVqhU//PADzz77rNsz5WPXrl3s2rWLOnXq5OthCtRct24dN954I/Pnz89ntPXr1+e5554jJycHYwyrVq1i+PDhAOzcuZNatWqxZ88eZs6c6d7rokWL+Pzzz0OO0PP19gXr9fN9Rr59hZUd7D8+X+/qkiVLaNasGWBHCg4dOpS//vWvBaZmzZ49m2XLlrFw4cKQ34eSH688B9R3QvnO/Pnz6d27NxCfvrNx40ZOPfVUAN5++233d/98XxMnTqRSpUpcddVVQT833335GqBD9Yj7PCVw6pj/5+Pb98orrwTV8N27jzZt2rBs2TJq1KhB7969ueWWW8jJySErK4vPPvuMESNGuMe+8sormh6jGMSeV6jvhPKdcP63xpLv7Nq1i2rVqpGYmMimTZv46aefaNSoESJCz549+eCDD0hLS2PFihU0b94cKHm84/8ZlSTeqV+/PnPmzCkQq9WtW5fvv/+eXbt2UbNmTZYvX+6eo4Qm1nzHy/hLfado30lISODUU0/lgQceOKr1rLPPPpu9e/e6z+iKFSs466yzuOCCC/juu+/c4xo0aMCaNWuA2PGdadOmuaMk58yZw9q1axk3bhwHDhzgwIED1KlTh5ycHN5++22dKRoBseY7sRbrgPpOSX0nNzeXvXv3Ur16ddavX8/69evp2rUrIkJqaiqvvfYa/fv3Z968ee7nEyu+061bNyZOnOgufrp8+XLGjh1bZKxWEspkA/PBg94kTC9fvnxM6Xi1FkCoYf1r1qzhxRdfpFWrVqSlpQFw9913c/755zN69GiGDh3K888/T4MGDVwzeeihh/j999+55ZZbADsybtmyZSQlJfHQQw8xYMAAcnNzufTSS2nZsiVg88GcddZZ9O7du0CZnnjiCXeq9YYNG+jbty+VK1d2zy2MJk2aMGrUKE488UQqVarEjBkzqFq1Klu3bnUbNHJycnjkkUcKnT7h+4zGjRvHwYMH3akcvsrKxRdfzMqVK+nUqRMi4q6cCnDHHXe4I/NuueUW14x//vlnTjjhhALXGTlyJFu2bHHv88svv3TzIfmYNm0ab775JsYYdu7cSWZmJl27dnW/m2A89dRTLFmyhKSkJKpVq+aa1cKFC/noo4/Ys2cPc+fOBayRtW7dmptuuokGDRq40+DT09OLzPeqHMErzwH1nVC+U69ePZ555hkgPn1nxowZvP/++5QrV46qVasWGWgU9rndeeed9OrViw0bNtChQ4cC5wwcOJBDhw4B8NVXX3HDDTcUGEkzYcIEPv74Y0SELVu2UL58eVJSUvItMBguzZs3p1u3bqSmppKQkMDll19Oq1atADh48CDvvfcekydPjli3rBNrXuGlVrz6zvnnn1+gDLHsO6tWreKBBx6gXLlyJCQkMGnSJHf0zfjx4xk+fDh33nknNWvWZMqUKUDJ451FixYhIvz2228linf69OnDqlWrgsZqt956KxdddBHlypWjQYMGIX1WOUKs+Y6X8Zf6TtG+IyJRqWclJiYyYcIELrnkEowxnHnmmVxxxRWF6kDs+E5h331mZiaXXnophw8fJi8vj/POO8+9byU0seY7sRbrWC31nZL4TnZ2NhdeeCFgF0GcPn26m3d5/PjxDBs2jPvvv5/WrVtz6aWXArHjO9WrV+fmm292c2TfcssthcZqvrV3SoJ4uTplabJ69WoTbsX2kUeW88kn+Yflz517QcTX3Lx5Mw0bNoz4vJLq7Nu3L2hOnMOHDxf50ISLVzpeasW7zjXXXMN9992XL6VIaZepuAT7+/z8888/6969e/jz1I4RwvWdYJ4D6juxrOOlVqzqDBo0iNmzZxc7EI6lz1p9pyCFPePBFrk52G5uxDrFQX0nOjpeasVavBNL91VWfCeSOlZpxSiFUZz4S32ndHW81FLfOXYpqe8UtqBfNOKd4ugE+15j+ZmKNx0vtcq675TJEcwbN3qz4ENJGgOPho6vFyVWdLzUinedoha+iVQrVnSUI3jlOaC+Ey0dL7ViVWfevHme6HiB+o73xJpXeKkVq89UrOh4qRVr8U6s3ZeSn1jzHS/jr1j724tXHS+11HfKBrHmO7EW63ipFa86XmqVdd8pk4lU69ULvuJjpOzduzemdHx592JFx0st1YmelpdlUiyFeU6lTwcX+AmF+k50dLzUUp3oaimWWPMKL7Vi7W841nS81FIdJRJizXe8qvNB7P3txauOl1rxqqPkJ9Z8J9ZiHS+14lXHS6141QmXMtnAfNxx3iS0CWc1zmjqeJXuxMu0KbFWpnjV8VIrXtLmxBJeeQ6o70RLx0st1YmulmKJNa/wUivW/oZjTcdLLdVRIiHWfMfL+CvW/vbiVcdLrXjVUfITa74Ta7GOl1rxquOlVrzqhEuZbGBev96b6VK+VRpjRce3Km2s6HippTrR0/KyTIrFK88B9Z1o6XippTrR1VIsseYVXmrF2t9wrOl4qaU6SiTEmu94GX/F2t9evOp4qRWvOkp+Ys13Yi3W8VIrXnW81IpXnXCJWgOziPQSke9F5EcRuT3I/uEi8pWIrBWRD0Skld++O5zzvheRniUty2mneZOHZMeOHTGlE2u9bl5qqU70tLwsk2LxynNAfSdaOl5qqU50tRRLrHmFl1qx9jccazpeaqmOEgmx5jtexl+x9rcXrzpeasWrjpKfqVNXMXjw2/l+ikOs+Zc+U9HT8VIrXnXCJSoNzCKSCEwFegOtgMH+DcgOc4wxrY0xZwIPAY8457YCBgGnAb2AJxy9YrN7d15JTnepVKlSTOkkJHjzdXql46WW6kRPy8syKRavPAfUd6Kl46WW6kRXS7HEmld4qRVrf8OxpuOlluookRBrvuNl/BVrf3vxquOlVrzqKPnRtp3oacWrjpda8aoT9vWidJ32wI/GmJ+MMVnAPOBi/wOMMfv83lYCfMlCLgbmGWMOG2N+Bn509IpNdrY3eUgSE71ZOMIrHRFv8oyF0tm6dSt9+vTh3HPPJSUlhWnTprn7/vjjD/r27Uu7du3o27evm+R+/vz5pKam0qlTJ3r27MnXX3/tnnPdddfRrFkzOnbsWOwyhYuXOj/88AMXXHABderU4bHHHsu3f9q0aXTs2JGUlBSefPJJd/vXX3/NBRdcQKdOnRg8eDAHDhzwpDy+MoXLli1bSE5OJi0tjbS0NG688cYCOn/729/yfScTJ07ktNNOc8955513PCt7vOOV54D6TijfGThwIHv27AHi03eKc09Dhw51n9s2bdrQrVs3z8oTCcXxnfvuu4/U1FTS0tLo168fv/76qydlLwvEmld4qRWvvuPVfXmpJSIsXrzYfQ67devGRx995O4fMGAAjRo1YtCgQfnOM8Zw7733cs4559ChQweefvppz8oTKR988AFpaWmkpKSQnp7u6rz77ru0b9+etm3bMmXKFPf4q6++mvbt29OxY0euu+46HXUYAbHmO17GX+o7ReO1fxXlO3PnzqVdu3a0a9eOuXPnuttfeeUVOnXqRGpqKgMGDOD333/3rDyRUFidKScnh2uvvZZOnTrRoUMHJk+enO+83NxcOnfuXMBPlaLRtp2Sa6nvhK5ntWnThk6dOrme5M9TTz1Fhw4dSElJYcKECZ6VJxIKq2eJCBkZGbRv397dt3PnTgB++eUXLrnkElJTU8nIyGDbtm0lLrd384aKph7wi9/7rUCHwINEZCRwI1Ae8H1r9YCP/A7b6mzLx2+//cY//vEPkpKSyM3NpV+/fowcOZIdO3ZQqVIlEhMT2bdvH7Vq1eLMM8tRu3YuP/yQS4sWSezcmcfu3bs5cOAAJ510Ejt37kREqF69Ojt37qRKlSrk5uZy8OBB6tSpw44dOyhXrhwHDx5k3759nHjiiWRlZfHnn3+6+8uXL88JJ5zA7t27qVatGn/++SeHDh1y9x933HFUrFiRP/74g6ysLA4dOkRWVpa7v2LFipQvX569e/dSs2ZN9u7dS3Z2NnXq1OHgwYNUrFgRESE3N5fq64ZgMOTlGRITE8jLM+4fpDGGhARxk3sLQp7x7TcYAwkJ4pxj9+88baZ7bl5eHuXKlSM7OxsRITExkby8PMaPH0/r1q3Zt28fPXv2pGPHjrRs2ZLJkyfTqVMn/vnPfzJlyhQmT57MPffcQ926dXn11VepVq0ab7/9NqNHj2bx4sUYYxg0aBBDhgxh1KhR5OTkkJub636PAElJSWRlZbnfdW5uLuXKlSMnx+ZVS0xMJCcnh8TExELL7NufnZ3tnh+4Pykpiby8vHznJyQkkJCQ4O7Pzc11P8tKlSpx77338tZbb5Gbm+v+fPvtt8yePZs333yT4447jkGDBtG1a1eaNm3K9ddfz7hx40hLS2P27Nk8+uij3HXXXSW6J99+32cTzj3l5ubSsGFDli9f7t5TXl4e2dnZ5OXlsWjRIipWrAhAVlYWxhiMMVx11VWMHDnS/dvz/fi+p+zsbA4fPlzgeSrr1KmTyC+/eNO7vm/fPqpVq1bqOpU+HQxAXl6eJz2jv7d+hqSkwv8lJSUlcc8999CmTRv2799Pt27d6NKlCy1atGDKlCl07tyZ0aNH8/DDDzNlyhTGjx/PySefzKJFi6hatSrvvPMOo0eP5t133wVsQ+ZVV13FiBEjCr2mz4tKipc6xbmnmTNnur+PGTPGs5EVxbmvRo0asWLFiqBaS5YsKVC266+/nrvuuguA6dOn8+9//5tHHnmk+IUuQ8SKV3ipFe++45VXeKmVm5tLWloavXv3RkRYv349Q4cOZc2aNYB9Rv/880+eeeaZfOfNmTOHbdu2sWbNGhISEjyptPjKE8l97d27l5tvvpmXX36Z+vXruzFJVlYWt956KwsWLCA5OZnu3bvTq1cvWrRowcCBA5k+fToAV111Fc899xxDhw71pPzxTqz5jhfxl/pOeHjtX4X5zh9//MFDDz3EsmXLEBG6du1K7969qVy5MnfccQerV6+mRo0ajBs3jqefftqNIUpankjvbfjw4Vx//fX5ti1cuJDDhw/z4YcfkpmZSUpKCv379+fkk08G7AClZs2asX///hKXuSzhVT0rlvyr0qeDPfMcUN8JV6uoewJ4/fXXqVGjRr7zVq5cyZIlS1ixYgUVKlQotXgHgtezfG0106dP56yzzsq37+677+avf/0rgwcPZsWKFdxzzz35OheKQ7QamMPCGDMVmCoifwPGAEPCPbd27dp8+OGHBbY3bNjQ/d33oK9cmcWePbaR8JNP7KiEGjVquH8sDRo0CHp+zZo1823LzMzk+OOPL/KalStXBqBKlSpB91epUqWAjv/+qlWrAvmnWlSqVMlN1p2UlAQiCEJiggGEhIQjvR2+hmb/HpAE93fB96v/ORUqVCjQ81ahQgX395NPPtn9R1ijRg2aN2/O7t27KVeuHG+99Ravv/46iYmJXHrppWRkZLgj0Hx07NiRW265hfLlywOQmprKli1bEBGSkpLcB8m/DP5l8u33nR94bLAy+/b7Gl8L2x94zcL25+bmUq9ePerVq8eyZctITEx0f37++Wfatm3r/r2lpqby9ttv06JFC3766Sc6d+6MiNCjRw8GDBjAuHHjSnRPPnJzc/NtK+qeEhMT3c8icP/evXuZPn06kydPZujQoW6ZfMfn+9sLol+hQgWqVKmS73kq643MGzZ4t8hMrVq1YkonwaOe41D/QOvUqeMumnHCCSfQrFkzfv31V1q0aMGSJUt4/fXXARg8eDB9+/Zl/PjxdOhwpB/znHPOyTf6tWPHjmzZsqVEZQoXL3VKck/GGBYuXMiCBQs8K49XHDp0iCeeeML1HR/+/zszMzM9HakQ70yc+AN79nxfYPvrN0Wm45VXeKkVr77j5TPlpe/4xx4HDx7Mt79z58588MEHBc6bNWsWTz31lFs59mrRo0jv6+WXXyYjI4P69esDR/4G161bR+PGjWnUqBEA/fr1Y8mSJbRo0YLzzz/fPf/ss89m+/btnpS9LBBrMYqX8Zf6TtF47V+F+c6yZcvo0qWLW8/q0qULS5cupU+fPhhjyMzMpHr16uzfv5/WrVt7Vh6vdDIzM8nJyeHQoUPugDSAbdu28c4773DjjTfyxBNPeHK9soJXz3ms+ZdXngPqO+FqFXVPhTFz5kxuuOEG17NKK94pjs7333/PvffeC8B5553HZZddVuLrRStFxjaggd/7+s62wpgHXFLMc0PSqJE30xa8mnbjlY7Bm+khvl6OcNiyZQvr1q2jbdu2gB1J7nuoChu9+txzz9G9e/eQ2rNmzWLWrFkFyjRnzhxat25Nnz59uOiiixg+fLi7v0WLFgBceeWVZGRk0L17d+69916MMezZs4eUlBQAHn30UebPnw/AGWecweHDh8nIyCAjI4MePXq4+wqjqM+oZcuWfPTRR/z+++9kZmbyzjvvuD1ZLVq0YPHixQC89tprIXu4pk2bRkZGBr1792bw4MHs22czyYwaNYqmTZty3XXX8eGHH7pl79mzJ1999VWRmj62bNlC586dSU9PZ/Xq1e72Bx54gJEjRwbtPHn66adJTU3luuuuc6fHKKHxynNAfQeK9p2aNWvy22+/FTgnHn0n3HvysXr1amrXru02qBRGuL7Tp08f0tPTj7rv3HvvvZx++unMnz+fO+64I+z7LevEWqzjpVa8+k5geWLJdxYtWkSHDh0YNGhQgbRgwfj555959dVX6datGwMHDmTDhg1FHj9hwgQyMjK44IILGDFihJuWYtCgQZx66qncd999LFiwwP0s+vTpw9atW0OW48cff2TPnj1kZGTQtWtX5s2bB9jGnHr1jkyITE5OLlCRzM7O5qWXXorIZ8s6sRajeBl/qe8U7Tu7d+92G2eOpu9s3769wLO7fft2ypUrx8MPP0ynTp1o1aoV33//fchUEwMHDiQjI4Nu3brx+OOPA/DTTz/Ru3dvmjZtyqJFi5gwYQJ9+vQp4E2hCFZnuvDCCzn++ONp2bIlZ5xxBiNHjnQbyu+8807Gjx+veZqLQazFO7EW64D6jhf1LBGhf//+dO3aNd+srY0bN7J69Wp69OhBeno6n376aZHXiXY9y3df1113HWlpafz73/92Z+SffvrpLFq0CLB+e+DAgRL//UZrBPMnQFMRaYxtHB4E/M3/ABFpaozxRZ8XAb7fXwfmiMgjQDLQFPi4JIXxKp2g74uJFZ1oc+DAAYYMGcL999+fb5SZDxEpMNps5cqVPP/88yxZsiSk/t///vdC9/lG/gKMGDGCpUuXcsEFF7j7fQ99Xl4eF198MR9++CGpqans37+fw4cPs3LlSm666SYyMzOpWbMmFSpU4I033gBsL3m3bt0477zzitUD1bx5c0aNGkX//v05/vjjad26tRssPPbYY9x+++08/PDD9OrVK9+I5WAMHz6c4cOHAzYX6YsvvshVV13FmDFj+O2339xg6I033iArK4tVq1bx8MMP8+yzzxape9JJJ7Fu3TqqV6/O2rVrueyyy1i1ahWbN29m06ZNTJw4sUCv49ChQ7nlllsQEe6//37GjBnjXl8pGg9TmKrvqO9EfE8+XnnlFfr16xfyuHB959VXX6V8+fK89957R813wKb1GDNmDJMnT2bGjBnayBwmsRbreK0VTaLlO/7pwHzEiu+kp6eTnp7OqlWreOCBB3j11VeLPD4rK4sKFSqwbNky3njjDf75z38W+VmMHTvW/f2aa65h2bJl9OzZkzvuuINZs2a509zT09MpX748s2fPZvr06dxzzz1FliM3N5e1a9eycOFCDh06RM+ePWnXrl2R5/i4+eabSUlJcRvrldDEWoziZfwVbY4132nfvn2p+k52djazZs3i/fffp1GjRtx22208+uij3HbbbYWe42twysnJoUOHDlx++eWccsoppKenc9JJJ7nXz8rKonz58vm8qSgKqzN98cUXJCYm8s0337Bnzx4uuugiunTpwvfff++k8Twz6IwQpWhiLd45VmMdUN8p6p4WL15McnIyO3fupF+/fm6O6ZycHPbs2cM777zD559/ztChQ1m7dm2hsy6jXc867rjjmD59OsnJyezfv58hQ4bw4osvMmjQICZMmMBtt93G3LlzSUlJoW7duiXOIR6VLjJjTA5wHfBf4FvgJWPMehGZICJ9nMOuE5H1IrIWm4d5iHPueuAl4BvgLWCkMSb8Lpgg/PBDiU53ibVpFF5NHQ5nOH52djZDhgxhwIABZGRkuNtr167Njh07ANixY4ebVgRg/fr13HDDDbzwwgtUr17dszI1bNiw0OmLCQkJpKSksHHjRsDmpfHl2Dv33HNZuXJlgYpDpUqVOO2009iwYQP33nuvmww93PIAXH755Sxfvpw333yTqlWr0qRJEwCaNWvGggULWL58Of379w85ktCfxo0bu5/tjz/+WCBXaVJSEqeccop7zNNPP+2WPXBUToUKFdzv4Mwzz6Rx48Zs3LiRTz75hC+//JI2bdrQu3dvNm7c6H6/tWvXJjExkYSEBK644go+//zzsMte1vHKc0B9J5Tv7Nq1K9+9xaPvFOeecnJyWLRoEX379o1oylVRvuPTOZq+48/AgQPdQFEJTazFOl5qxavvhCpPLMQ7HTt2ZNOmTezevbvIsiYnJ7ufV3p6Ot98802Rx/vTuHFj1z++/fbbfLksg/lOYWX3laNbt25UqlSJGjVqkJKSwtdff039+vXzzSLbvn07devWdd8/+OCD7N69m/vuuy/sciuxF6N4GX+p7xTE33eSkpJo2LDhUfed5OTkAs9ucnKyO8KvcePGiAiXXHIJn332Wdifga/hCKzv+NJU+pfH35v69+9PWloao0aNKqBXWJ1p4cKFdO/enXLlylGrVi3at2/PF198wZo1a1iyZAlt2rRh2LBhrFy5kmuuuSassiuxF+/EWqwD6jte1LOSk5MB+/1edNFFrr8kJyeTnp6OiNC2bVsSExNDxkg+olHP8vkb2PQnAwYMcD2pbt26zJ49m/fff58xY8YAcOKJJ4ZV9sKI2hwMY8xiY0wzY8ypxpj7nG1jjTGvO7/fYIw5zRhzpjGmq9Ow7Dv3Pue85saY8IdrFUKLFt4M3P7f//4XUzp5ed70loWa+mOMYdSoUTRr1oyRI0fm29erVy93+uG8efPcHt6tW7dyxRVX8OSTT7qNrV6XCexUhkASEhLcRfAaN27M7bffzj333MOvv/7KxIkT+cc//pHv+MzMTNavX0/Tpk0ZM2YMK1asKJAsPVR5fAHK1q1bWbRoEQMGDMi3PS8vj0mTJnH55ZcDNji65JJLgov54bsP32uwMvn2DRs2zC27f6UJ7D8H33SJTZs28dNPP9GoUSO3x+3LL79kyZIlnHrqqW6Djs/YwE6haNmyZcjyKhavPAfUd0L5zpw5c/6fvXuPbuu67sT/3QRBkYT4JiVatGMPvgAAACAASURBVCJZtmTXTDtJY6eTPiaN8xgn6Tgdx1mJ46RJ42lX+3PbuHk1nU5d1/514jpN82j9y8OOZzXTjt08PFO3SVeaJk4fSprKSpO6dGxZ0gh+UOBTpCjwARI8vz8uAQMgSF7g7nuwz8H+rqUliQA+OOce3M3Dy3vPxWtf+1oAftadevv0zW9+E4cPH8bIyEixX1HrTun2iavuFA6WAcGZA4cPHw7d52aPtLkOp+Vr3Qlz6XUj6s7p06eL7/v9738fuVxuxx8kX/e61+Ef/uEfAABHjx7FoUOHAADHjx/f9uaqlf0MU3e2ajsAvPa1r8V3vvMdrK2tYXFxEcePH8eRI0fwwhe+EKdPn0Y6nUYul8NDDz2Ea6+9FgDwuc99Dt/4xjdw77336uXqNUbaHIVz/qV1Z/u6s7q6iksvvTT2unPNNdfgkUcewdzcHObm5vDII4/gmmuuwUUXXYQnn3wS09PTAIBHHnkEl156KQDg3nvvxb333rtjPws1pfIM1NJtVHjsS1/6Ev7+7/8en/jEJzY5W/3MdNFFFxX7ms1m8eijj+LIkSO47bbbMDY2hu9///u477778FM/9VPFG41qdo60+Y60uQ6gdSfqz1nZbLZ4881sNotHHnmkuF+//vWvL853Tp48iVwuh4GBATE/Zy0tLRUPeK+uruKrX/1qse0zMzNF+2Mf+xhuuummHdu7U0Td5M9Wpqai32UUeP4GflIcrt9y7XRa/He+8x38+Z//Oa688srib35++7d/G69+9atx66234l3vehf+9E//FPv378dnPvMZAMDdd9+N2dlZvP/97wcQ/EbmG9/4BoBgRzl69ChmZmYwOjqKD37wg3j7299eXAf153/+5ze16Ytf/GJxfZunn34at956K4BgMfbtctlll+HOO+/Evffei0QigQ996EM4dOgQcrkc3vjGNwIAVlZW8N73vnfbyycSiQQmJiZwzTXXYGFhAS0tLfjUpz6Fb3/72+ju7sY73vEOzM7OIplM4u677y7+JuhLX/oSPvvZzwIIzugp7MQTExNVt/unPvUpfPnLXwYQrH+0uLiIV7ziFWU/8Bw9ehR33XUXjDFYWVnBk08+iXvuuWfTN4fSFC41SyaTaGlpwUc+8pHiGUJbjf/tt9+Oxx57DESEF7zgBfjDP/zDLX1NebhqDqB1Z6e6MzIyUryEyse6U0+fgOAyq8J7FfoVte586EMfAhFheXk5trrzu7/7uzh58iRaWlqwf/9+fOQjH9nS15RH2lyH0/K17hT219JIqDt/+Zd/iQcffBDJZBLt7e347Gc/WxyD173udXjqqaeQzWYxOjqKT3ziE3jlK1+JW2+9Fb/4i7+IT37yk0ilUvjoRz8KIPiBtL29fdP73HHHHTh27Fixn21tbZvOQHrooYdw//33g4gwPz+PTCaDL37xi8Vf4lfL5ZdfjmuuuQY/+ZM/iZaWFrz97W/HlVdeibW1Ndx999244YYbkM/ncdNNNxV/4Hrve9+L/fv3F0+S+Jmf+Rl84AMf2HZ7a4JIm6Nwzr+07mxfdxKJBA4fPhx73enr68P73ve+4tqo73//+4tziQ984AN4/etfj2Qyif379+PjH/84AOCpp54qu3lXIW9605uwvLwMAHjsscfw7ne/e9Nl/nfccQf++Z//GURUVpsK68JWy1Y/M91888249dZb8bKXvQzGGLz1rW/F6Ojolo4mXKTNd6TNdQCtO1F/zpqamiq2eW1tDTfccANe9apXAQBuuukm/Oqv/ip+/Md/HG1tbfijP/ojEJGYn7Pm5+dxww03YHV1Ffl8Hi9/+cvxcz/3cwCAf/zHf8Sdd94JIsLLXvYyfPjDH97SDxtyeY2Y0nz729822xX60vzmb34dZ86UX0rxwAOv2eLZW2dmZgYDAwM1vy6qc/78+apr4qytrbHcbZLL4bR8d+69915cfPHFxd8ISmhTvan2+fzud797/JWvfGW4RQ8dSti6U63mAMDD7/0fm76WveqBbS2tO3YcTkuqE7XuSNrWLtQdIroWwMcBJADcZ4y5a4vnvRHAFwFcbYzZdKcQ23WHq+bUYzVb3ZG0T8Xl3HbbbXjzm99c90EVSf1yoe5wpJafsRo1R9kqW9XB7X7u07rTWIfTKjhvectb8LnPfW7He9/Yak+UaN3ZnGr7ebW5DmBnvlOPU21cJe9TvjmclrSfs2zXnaa87mtoiKfbFy5cEOXUcndQGw6n5bvzC7/wC5EOLpdaUcM5/pogXDUH0Lpjy+G0pDpR647EbS01RJQAcA+A1wK4EsCNRHRlled1AXg3gO9EfU9pcx1OS+o+JcXhtLidO+64I9IZe9L6pSmPtDkK5/xL2mfPV4fTKjgPPvhg3QeX42iPhjfS5jvS5jqclq8OpyXt5yzbdacpDzA/8cQai7N3715RTjKZFOVwWurYszjbpAnCVXMArTu2HE5LHbuW0LwUwEljzGljTA7AgwDeUOV5dwL4fQDLUd9Q2lyH05L2GZbmcFrqaGqJtDkK5/xL2mfPV4fT8tXRlEfafEfaXIfT8tXhtHx1wqYp12A+ciSB48ejF6KpqSns379fjLO2thbpt7PcDqeljj2Ls02aIFw1B9C6Y8vhtNSxawnNCIBnSv7/LICyBSGJ6EcB7DfGfJmI3r8VNDk5iZtvvhmtra3I5/O4/vrrccsttyCTySCVSiGRSOD8+fP4kR9JIJsFEongDutXXNGKqal1TOYP4vz6EEYST+Ds+hG0II/U4iKmpqbQ3d2NfD6PbDaL4eFhZDIZXLhwAQcPHsT09DR6enqQy+WwtLRUfLytrQ1dXV2YmZlBX18flpaWsLy8XHy8vb0dHR0dOHfuHFZXV5FKpZDL5YqPd3R0oK2tDfPz8xgcHMT8/DxWV1cxPDyMbDaLjo4OEBHy+Xyxz/l8Hrt27cLq6mpxfbt8Po9kMom1taDWJhIJrK2tIZFIwBiD9fV1JJNJrK6ugoiQSCSwsrKCtra2LR8vXFa4vr5e9nhLSwtaWlqKj+dyObS0tJQ9XtlmY8y2jwPP39AmSp8Kjxfep94+FdpcSL19am1txerqKowxxa/X2ydjDFZXV9He3h6pT8lkEsvLy0gmk5H6tLKygpmZGVy4cAF79+4t3si5mSNtjsI5/5L2vdNXh9Py1dGUR4/t2LN8dTgtX52wacoDzNXOEk89euOmr+20FirXwuucC7hrNBp54bwyReuORuNfiKgFwB8CeOdOz92zZw+OHj266esHDhwo/ruvrw/Z7Cl873vP/8B17FhwN+o9iTPYkzgDADjUchwAkO3sLHv94OBg0Xz22WeRSqWQSqW2fc/CTW1K12grfby7uxvPPvts2V2vSx/v7e0FgLL3SaVSxTMvCuvHJRKJ4gHdXbt2FZ9beLx0El3t5iqVr6lcl6708cLrS52tHi+8b7U2bfX6ysdzuVxZ++vpU+Hx9fX1qm2qpU/btSlsnwqP53K5su1dT5+A4CB85djX2qdCO6t9tmrp065du9Dd3V1ca3P//v1Nf5BZ2hxFVyTQaOyH654TYcO1n0urXxqNi2nKJTKq3eyhnvT39zfEISLkcrlNX9/p7qBhw+VwWurYs6I4uVxOv6lWCVfNAbTu2HI4LXXitRypO88BKD2d5eKNrxXSBeCFAL5JRGcA/HsADxNR3TftkTbXqcdqtrojZZ9SZ+c4Unesp1FzlK1STx3UutNYh9PyzXGh7jTinhPS5jv1ONXqju5T9hxOyzen1rrTlGcwHz7cWjyTJ0qmpqbKzr6x5ezevRsXLlzA8nL5Eo3ZbLbqGUa1hsvhtNSxZ0VxiKh4Fpvm+XDVHEDrji2H01InXsuRunMMwGEiugTBgeW3AHhr4UFjzDyAwcL/ieibAN4X5YweaXOdeqxmqztS9il1do4jdcd6GjVH2Sr11EGtO411OC3fHEfqTvGeEwBARIV7Tjxe8bzCPSe2XBIsbKTNd+pxqtUd3afsOZyWb06tdacpDzBnMjy/5Sq9DNSmQ0To6ura9PV8Ps/SJi6H01LHnsXZJk0QrpoDaN2x5XBa6ti1JMYYs0ZEvwLgqwguGb3fGDNGRHcAeNQY8zD3e0qb69RjNVvdkbhPqeN2bF+q3qg5ylappw5q3Wmsw2n56ggPyz0nwt5vYmhoCKkU8JKXtO54v4mhljNIp9NV7zeRTCbR1taGdDod+X4TyWQSZ8+eDX2/iWp9mp2dxeLiIvr6+jAxMVE8wFe65j8Rob+/f8t7aCSTSfT09GB6ehqJRALLy8t192lgYAALCws4f/48+vv76+6TMQZDQ0M4e/ZscamsevvU09OD5eXlsu1cT58Krz979mxxybN6+lQYp9XVVZw7d67uPhU+e4V2RulTJpPB+vo6Ojo6IvVpdnZ20zhtlaY8wJxMcq3rxfPDm68Op6WOPYuzTZogXDUHkDfOvjqcljp2LakxxnwFwFcqvnbbFs/96ajvJ22uw2mpY89Sx92UXKr+agQHeY4R0cPGmMcrnsd2qbq08dH5l3sOp+Wr43LC3nMi7P0mAODpp9dx+nSwbbe730Tl60vvNwEA09PTZfeJqPaaMPebmJ6eLtqVj1e730S1PnV2dmJ6ehrt7e1lj5eu+R+mT4X32q5NYfpUeF4ymcSuXbvq7lNpPwp9qbdPQHADu2qP19Kn0jYVrHr6VHjcGFN06ulTIdPT05H7dODAAUxPT6O3tzdSn4DN4zQ5OYlqaco1mAcGeLqdzWbVsWSpY8/ibJMmCFfNAeSNs68Op6WOXUsTRNpch9NSx56ljtMpXqpujMkBKFyqXpnCperLVR6rKdLGR+df7jmclq+O8Fi/54S0+Y40h9Py1eG0fHXCpinPYB4bW9v5SSEyPDysjiVLHXsWZ5s0QbhqDiBvnH11OC117FqaINLmOpyWOvYsdZwOy6XqtUTa+GxVB1OP3rjpa9mrHrDSJnXsWb46wmP9nhPS5jvSHE7LV4fT8tUJm6Y8wDw6yrMQfCaTYVkI3leH01LHnsXZJk0QrpoDyBtnXx1OSx27liaItLkOp6WOPUsdfxP2UvVa1kI9deoUent7y9ZuBGpfYzObzaKtrS3yWqhXX92K6WmDzk7C2NgaRkdbMTe3jtn8Psyuj2Bv4hRm10ewatrRv7Ky7XqUuVwOra2tkddCXV5eLrY7yrqhU1NTuPzyyyOvhXrixAmMjIxE6lNPTw/Gx8eRSqVY1kJ98sknMTw8HHkt1KmpKXR0dEReCzWfzxfXZo2yFmo2m8W+ffsi9anaOElKI+45IW2+I83htHx1OC1fnbBpygPMy8uGxUkmk+pYstSxZ3G2SWps3/SGq+YA8sbZV4fTUseupQkiba7Daaljz1LH6dRyqToADCO4VP260jlPLWuhDgwMYN++fZser3WNzfHx8aKz1XuGWY9ydvZU2dmNhYNQ/Ylx9CfGg43QMgsAyFasK1q5HmVlm+pdN3R8fBx79uypu0+F5xljWNZCHRwcZFkLdXFxserY17Nu6ODgYHEbRVk3dGVlpdimKGuhVo59vWuhjo+PW10LtVGxfc8JafMdaQ6n5avDafnqhE1TrsH83HM8C+z39PSoY8lSx57F2SaJKbnpzWsBXAngRiK6ssrz2G56w1VzAHnj7KvDaalj19IEkTbX4bTUsWep43SKl6oTURuCS9WLZw8aY+aNMYPGmIPGmIMA/gnAdVF+oS5tfHT+5Z7DafnqaMojbb4jzeG0fHU4LV+dsGnKA8yXXspz4vb09LQ6lix17FmcbRIa6ze94ao5gLxx9tXhtNSxa2mCSJvrcFrq2LPUcTfGmDUAhUvVfwDg84VL1YnoujjeU9r46PzLPYfT8tXRlEfafEeaw2n56nBavjph05RLZOhvuew4nJY69qwm+O269Zve6Bk07jmcljp2LU0QaXMdTksde5Y6bsf2perSxkfnX+45nJavjqY80uY70hxOy1eH0/LVCZumPMCcSvEshp/L5dSxZKljz+Jsk4sJe9MboJYb37Rgz54WJBLAiRN5XHFFK6am1jGZP4jz60MYSTyBs+tH0II8UouL2958JJ/PY35+PvKNb4gIS0tLZTcfqecmMQsLC2hvb490M5/CzWEAROrTwMAAJicnMT8/H6lPhRuqjI+PI5/P192nwk1ipqeny9pU701ikskk5ufnI/VpYmIC+Xwe+Xw+Up9yuRymp6fR0dER+WY+mUwGq6vBupicN75p9kib63Ba6tiz1NHUEmnjw1UHAXl989XhtHx1NOWRNt+R5nBavjqclq9O2DTlAebe3hYA0X/TtbS0FL0xHjucljr2LM42CQ3LTW+A8De+aWs7XXZ348K/9yTOYE/iDADgUMtxAEC2s3Pbm4+k0+mqd4Kt9YYq6XQaF110UdXHa7n5SDqdRnt7e6Sb+RTeq/C+9fYJQNkNb6Le+CaVSrHc+GZ+fr5qm2q9SUzl2Nd7k5h0Oo2BgYFIfQKCWlF5g6F6b3yTTqfZb3zT7AeZpc11OC117FnqaGqJtPHhqoOAvL756nBavjqa8kib70hzOC1fHU7LVydsmnIN5tK7CUfJ8PCwOpYsdexZnG0SGus3veGqOYC8cfbV4bTUsWtpgkib63Ba6tiz1NHUEmnjo/Mv9xxOy1dHUx5p8x1pDqflq8Np+eqETVMeYB4d5TlxO5PJqGPJUseexdkmiWnETW+4ag4gb5x9dTgtdexamiDS5jqcljr2LHU0tUTa+Oj8yz2H0/LV0ZRH2nxHmsNp+epwWr46YdOUS2QsLhoWp62tTR1Lljr2LM42SY3tm95w1RxA3jj76nBa6ti1NEGkzXU4LXXsWepoaom08dH5l3sOp+WroymPtPmONIfT8tXhtHx1wqYpz2CenORZi6urq0sdS5Y69izONmmCcNUcQN44++pwWurYtTRBpM11OC117FnqaGqJtPHR+Zd7Dqflq6Mpj7T5jjSH0/LV4bR8dcKmKQ8wHzzIc+L2zMyMOpYsdexZnG3SBOGqOYC8cfbV4bTUsWtpgkib63Ba6tiz1NHUEmnjo/Mv9xxOy1dHUx5p8x1pDqflq8Np+eqETVMeYH7mGZ7fchXuZq9O/JY69izONmmCcNUcQN44++pwWurYtTRBpM11OC117FnqaGqJtPHR+Zd7Dqflq6Mpj7T5jjSH0/LV4bR8dcKmKQ8w9/YSi7O0tKSOJUsdexZnmzRBuGoOIG+cfXU4LXXsWpog0uY6nJY69ix1NLVE2vjo/Ms9h9Py1dGUR9p8R5rDafnqcFq+OmHTlAeYu7p4ur28vKyOJUsdexZnmzRBuGoOIG+cfXU4LXXsWpog0uY6nJY69ix1NLVE2vjo/Ms9h9Py1dGUR9p8R5rDafnqcFq+OmHTlAeYx8bWWJzh4WF1LFnq2LM426QJwlVzAHnj7KvDaalj19IEkTbX4bTUsWepo6kl0sZH51/uOZyWr46mPNLmO9IcTstXh9Py1QmbpjzAPDrKsxB8JpNRx5Kljj2Ls02aIFw1B5A3zr46nJY6di1NEGlzHU5LHXuWOppaIm18dP7lnsNp+epoyiNtviPN4bR8dTgtX52wacoDzAsL6yxOe3u7OpYsdexZnG3SBOGqOYC8cfbV4bTUsWtpgkib63Ba6tiz1NHUEmnjo/Mv9xxOy1dHUx5p8x1pDqflq8Np+eqEjbUDzER0LRE9SUQnieiDVR5/DxE9TkT/SkRfJ6IDJY/lieh7G38ejtqWuTkTlQAAdHR0qGPJUseexdkmTRCumgPIG2dfHU5LHbuWJoi0uQ6npY49Sx1NLZE2Pjr/cs/htHx1NOWRNt+R5nBavjqclq9O2Fg5wExECQD3AHgtgCsB3EhEV1Y87V8AXGWM+REAXwRwd8ljS8aYF238uS5qe/bvT0QlAADnzp1Tx5Kljj2Ls02aIFw1B5A3zr46nJY6di1NEGlzHU5LHXuWOppaIm18dP7lnsNp+epoyiNtviPN4bR8dTgtX52wsXUG80sBnDTGnDbG5AA8COANpU8wxjxijFnc+O8/Abg4rsacOcOzEPzAwIA6lix17FmcbdIE4ao5gLxx9tXhtNSxa2mCSJvrcFrq2LPU0dQSaeOj8y/3HE7LV0dTHmnzHWkOp+Wrw2n56oQN350Pts8IgGdK/v8sgB/b5vk3A/jrkv+3E9GjANYA3GWM+T+VL5icnMTNN9+M1tZW5PN5XH/99bjllluQyWSQSqWQSCRw/vx5DA0N4Ud/NInp6XWcOJHHFVe0YmpqHZP5gzi/PoSRxBM4u34ELcgjtbiIqakpdHd3I5/PI5vNYnh4GJlMBslkErlcDjMzM+jp6UEul8PS0lLx8ba2NnR1dWFmZgZ9fX1YWlrC8vJy8fH29nZ0dHTg3LlzMMZgYWEBuVyu+HhHRwfa2towPz+PwcFBzM/PY3V1tfh4ZZ9mZ2dx/vx5HDp0CBMTE9i9ezcA4MKFC9i7dy+mpqZAROjv79+2Tz09PUin0xgZGYnUp4GBASwsLGB2dhaXXXZZ3X0yxmBoaAjpdLp4B8x6+jQ9PY2enh5MTk5i165dkfqUy+XQ0tKCmZmZSH2amJjA6uoq+vr6IvWpME6FNtXbp8LjKysr2LNnT919qvbZa/bs2ZPA1BTP5GdhYaG4jdWJz+G01LFraYJw1R2J46yOPUsdTS2RNj46/3LP4bR8dTTlkTbfkeZwWr46nJavTtjYOsAcOkT0NgBXAXh5yZcPGGOeI6JDAL5BRI8ZY06Vvm7Pnj04evToJu/AgeJSzujr6wMAzM4aHD8eFKFjx1aD1yfOYE/iDADgUMtxAEC2s7Ps9YODg2VmOp0ue7zaexYGs7u7u+rj3d3dSKfTuOiii6o+3tvbCwBIpVLb9qmzsxPpdBrt7e1ljxd+Y7F///6qr6/sU6HNhfett0+F5+VyOezatavuPpW+Z6Ev9fSp8F7z8/PFr9fbJ2Dz2NfTpwMHDiCdTmNgYCBSnwqpbFOtfSptU29vb919KqS0T81+kLmzk9isXC6njgWH01LHrqUJwlV3JI6zOvYsdTS1RNr46PzLPYfT8tXRlEfafEeaw2n56nBavjphY2uJjOcA7C/5/8UbXysLEb0KwG8BuM4Ys1L4ujHmuY2/TwP4JoAXR2nM2BjPb7ILZ9SqE7+ljj2Ls02aIFw1B5A3zr46nJY6di1NEGlzHU5LHXuWOppaIm18dP7lnsNp+epoyiNtviPN4bR8dTgtX52wsXWA+RiAw0R0CRG1AXgLgIdLn0BELwbwaQQHlydLvt5HRLs2/j0I4CcAPB6lMaOjPCduZzIZdSxZ6tizONukCcJVcwB54+yrw2mpY9fSBJE21+G01LFnqaOpJdLGR+df7jmclq+OpjzS5jvSHE7LV4fT8tUJGytLZBhj1ojoVwB8FUACwP3GmDEiugPAo8aYhwF8GMBuAF8gIgB42hhzHYAfAvBpIlpHcED8LmNMpAPMc3PrUV5eTEdHhzqWLHXsWZxt0gThqjmAvHH21eG01LFraYJIm+twWurYs9TR1BJp46PzL/ccTstXR1MeafMdaQ6n5avDafnqhI21NZiNMV8B8JWKr91W8u9XbfG6bwH4Yc62ZLOGxWlra1PHkqWOPYuzTZogXDUHkDfOvjqcljp2LU0QaXMdTksde5Y6mloibXx0/uWew2n56mjKI22+I83htHx1OC1fnbCxtUSGqIyMJFic+fl5dSxZ6tizONukCcJVcwB54+yrw2mpY9fSBJE21+G01LFnqaOpJdLGR+df7jmclq+OpjzS5jvSHE7LV4fT8tUJm6Y8wHzqFM9C8IODg+pYstSxZ3G2SROEq+YA8sbZV4fTUseupQkiba7Daaljz1JHU0ukjY/Ov9xzOC1fHU15pM13pDmclq8Op+WrEzZNeYBZf8tlx+G01LFn6W/X+aNn0LjncFrq2LU0QaTNdTgtdexZ6mhqibTx0fmXew6n5aujKY+0+Y40h9Py1eG0fHXCpikPMLe3E4uzurqqjiVLHXsWZ5s0QbhqDiBvnH11OC117FqaINLmOpyWOvYsdTS1RNr46PzLPYfT8tXRlEfafEeaw2n56nBavjph05QHmMfGeC6jGB4eVseSpY49i7NNmiBcNQeQN86+OpyWOnYtTRBpcx1OSx17ljqaWiJtfHT+5Z7DafnqaMojbb4jzeG0fHU4LV+dsGnKA8yjo60sTiaTUceSpY49i7NNmiBcNQeQN86+OpyWOnYtTRBpcx1OSx17ljqaWiJtfHT+5Z7DafnqaMojbb4jzeG0fHU4LV+dsGnKA8wzM+ssTiqVUseSpY49i7NNmiBcNQeQN86+OpyWOnYtTRBpcx1OSx17ljqaWiJtfHT+5Z7DafnqaMojbb4jzeG0fHU4LV+dsGnKA8yrq4bFSSR4FpT31eG01LFncbZJE4Sr5gDyxtlXh9NSx66lCSJtrsNpqWPPUkdTS6SNj86/3HM4LV8dTXmkzXekOZyWrw6n5asTNqEOMBPRv4u7ITYzPMyzkc+fP6+OJUsdexZnm+KIi/WIq+YA8sbZV4fTUseuFUeaue5IHGd17FnqNC4u1h1p46PzL/ccTstXJ864WHekzXekOZyWrw6n5asTNmHPYP5bIvo+Eb2PiC6KtUUW8tRTPAvBDw0NqWPJUseexdmmmOJcPeKqOYC8cfbV4bTUsWvFlKatOxLHWR17ljoNjXN1R9r46PzLPYfT8tWJOc7VHWnzHWkOp+Wrw2n56oRN2APMFwG4DcCPAXiKiP6GiN5GRJ3xNS2+HDzI81uu2dlZdSxZ6tizONsUU5yrR1w1B5A3zr46nJY6dq2Y0rR1R+I4q2PPUqehca7uSBsfnX+553Bavjoxx7m6I22+I83htHx1OC1fnbAJdYDZGLNmjPkLY8ybAIwA+DyADwCYIKLPEdFPxNlI7nAtQ2IMz3o/LvG7LAAAIABJREFUvjqcljr2LM42xREX6xHn0kfSxtlXh9NSx64VR5q57kgcZ3XsWeo0Li7WHWnjo/Mv9xxOy1cnzrhYd6TNd6Q5nJavDqflqxM2Nd3kj4h2A/hZAG8BcDGABwE8BeDPiOge/ubFkxMn8iyOtNPWpTmcljr2LEcu33KqHnHVHEDeOPvqcFrq2LXiTDPWHYnjrI49S53Gx6W6I218dP7lnsNp+erYiEt1R9p8R5rDafnqcFq+OmET9iZ/ryeiBwE8B+DNAO4DsM8Y8wvGmDsB/CiAd8TXTN5ccUUrizMxMaGOJUsdexZnm+KIi/WIq+YA8sbZV4fTUseuFUeaue5IHGd17FnqNC4u1h1p46PzL/ccTstXJ864WHekzXekOZyWrw6n5asTNmH3xrsA/AmAXzfGnK180BgzS0S3srYsxkxNrbM4u3fvVseSpY49i7NNMcW5esRVcwB54+yrw2mpY9eKKU1bdySOszr2LHUaGufqjrTx0fmXew6n5asTc5yrO9LmO9IcTstXh9Py1QmbsEtk3GmM+YPKIkNENxT+bYy5j7VlGo1GUz1ajzQaje1o3dFoNLajdUej0diO1h2NRlN3wh5g3qqIfIarITYzNFTT0tNb5sKFC+pYstSxZ3G2KaY4V4+4ag4gb5x9dTgtdexaMaVp647EcVbHnqVOQ+Nc3ZE2Pjr/cs/htHx1Yo5zdUfafEeaw2n56nBavjphs+0SGUR0aOOfLUR0CQAqefgQgOW4GhZnnnhijcXZu3evOpYsdexZnG3ijMv1iKvmAPLG2VeH01LHrsUZrTsyx1kde5Y69uNy3ZE2Pjr/cs/htHx14ojLdUfafEeaw2n56nBavjphs9Ove04iuFtoJ4BTG/8v/PkcgNvjbFxcOXIkweJMTU2pY8lSx57F2SbmOFuPuGoOIG+cfXU4LXXsWsxhqztEdC0RPUlEJ4nog1Ue/yUieoyIvkdE/0hEV0ZpuLS5Dqeljj1LnYbE2fmOtPHR+Zd7DqflqxNTnK070uY70hxOy1eH0/LVCZttz2A2xrQAABH9nTHm5XaaFH/yeR6HiHZ+UhM7nJY69izONnHG5XrEVXMAeePsq8NpqWPX4gxX3SGiBIB7ALwawLMAjhHRw8aYx0ue9r+MMZ/aeP51AP4QwLX1vqe0uQ6npY49Sx37cXm+I218dP7lnsNp+erEEZfrjrT5jjSH0/LV4bR8dcJmxwVrNn4oupiIdlloj5WcOcNThfr7+9WxZKljz+JsE3dcrUdcNQeQN86+OpyWOnYt7jDVnZcCOGmMOW2MyQF4EMAbSp9gjDlf8t8UABPh/cTNdTgtdexZ6jQmrs53pI2Pzr/cczgtX5244mrdkTbfkeZwWr46nJavTthsewYzABhj8kSUB9ABYCX+JsWfw4dbcezYamRnamoKBw4cUMeCpY49i7NN3HG1HnHVHEDeOPvqcFrq2LW4w1R3RgA8U/L/ZwH8WOWTiOgWAO8B0AbgmmrQ5OQkbr75ZrS2tiKfz+P666/HLbfcgkwmg1QqhUQigfPnz+OHf7gVCwsGiQRw4kQeV1zRiqmpdUzmD+L8+hBGEk/g7PoRtCCP1OIipqam0N3djXw+j2w2i+HhYWQyGSwsLOCSSy7B9PQ0enp6kMvlsLS0VHy8ra0NXV1dmJmZQV9fH5aWlrC8vFx8vL29HR0dHTh37hxyuRx2796NXC5XfLyjowNtbW2Yn5/H4OAg5ufnsbq6Wny8tE9DQ0OYnZ3FuXPncPjwYUxMTGD37t0AgpuY7N27F1NTUyAi9Pf3b9mnZDKJnp4enDp1Ci94wQsi9WlgYADpdBq7d++O1CdjDHK5HFpbWyP1qTBO4+PjSKVSdfdpYWEBuVwO+XweiUSi7j4NDQ1hYmICS0tLGBoaitSnXC6HTCaDyy+/PFKfhoeHcfLkSQwPD0fqU7Vx4oqr8x1p3190/uWew2n56sQVrrpDRNcC+DiABID7jDF3VTz+SwBuAZAHcAHAL1Zc0VVT9NiOPctXh9Py1QmbHQ8wb+RjAP6ciP47gh+KimfVGGNOx9GwOJPJ8PyWq7u7Wx1Lljr2LM42xRTn6hFXzQHkjbOvDqeljl0rplipO8aYewDcQ0RvBfDfALyj8jl79uzB0aNHN722dPLY19eHM2eewjPPrBe/Vvjha0/iDPYkzgAADrUcBwBkOzvLXj84OFg0z507h1QqhVQqte17Fg62lY5l6ePd3d04d+4c+vr6qj7e29sLAGXvU9knAOjs7EQqlUJ7e3vZ4wMDAwCA/fv3V319aZ8K2b9/f/F96+0TAOzbt6/Yvnr7BGDT9qmnT4X3MsZUbVPYPhWeV9mmWvtUeLzgROkTACSTSezatStSnwrvX2hrvX0qpLRPzGsdOjffkfb9Redf7jmclq9OzIlUdxqxJJge27Fn+epwWr46YRP2APMfb/z96oqvGwS/mXIqySTXul48xcxXh9NSx57F2aaY4lw94qo5gLxx9tXhtNSxa8WUqHXnOQD7S/5/8cbXtsqDAD4ZunVVIm2uw2mpY89Sp6GJPN+xfSahtPHR+Zd7DqflqxNzotad4pJgAEBEhSXBinWFe0kwafMdaQ6n5avDafnqhE2oA8yFRd99ycBAC06fjr6hs9ls8UwLdeK11LFncbYpjrhYj7hqDiBvnH11OC117FpxhKHuHANwmIguQXBg+S0A3lr6BCI6bIx5auO/r0dwN/e6I22uw2mpY89Sp3GJWncacSahtPHR+dfO+dznHqu6vMADD7ymIe3htHx14gzDfIdlSbCwy4ENDQ1hdLQVfX2043JgQy1nkE6nt1ySKZvNIpvNsiwHtrq6yrIc2O7duyMvBzY9PY3l5WWsr69HWg5sYWEBU1NT6OrqirQc2NDQEMbHx4s3n4uydNbk5GTZ41GWzhofH8f6+nrkpbOmp6eRzWYjLQe2tLRUfF6UPmUyGWSzWbS2trIuB7bdjQPDnsHsVcbG1lic4eFhdeqwUo/euOlr2asesNImXx1Oi7NNmiBcNQeQN86+OpyWOnYtiTHGrBHRrwD4KoIzgO43xowR0R0AHjXGPAzgV4joVQBWAZxDleUxaom0uQ6npY49Sx2nY/1MQmnjo/OvnaPfK9xzfMhOS4KFXQ4MAL7+9RwWF4PStd1yYJWvr1ySaWVlBbt2bb6/Ya1LMlU69S6dNTQ0tGlJqHqXmdquTbUsM9Xf37+pTfUsM3X55ZcX2xNl6ayOjo6iE3XprNI2RVk6a/fu3UWn3uXAgM2fx3r6dODAgaLDuRwYEPwSqFpC/YaKiFqJ6NeI6EtE9HdE9PeFP2FeLy2jozzH1TOZjDqWLHXsWZxtiiMu1iOumgPIG2dfHU5LHbtWHOGoO8aYrxhjjhhjLjXG/N7G127bOLgMY8y7jTGjxpgXGWNeYYwZi9JmaXMdTksde5Y6jQtD3al2JuFIlfe5hYhOAbgbwK9FabO08dH5187R7xXuOXGGoe7UsyTYz9bbXkDeZ1iaw2n56nBavjphE3Zv/CiCSxc+A+D3APwWgF9GUBCcy/JypF/OF5NMJtWxZKljz+JsU0yJXI9sr0nIVXMAeePsq8NpqWPXiinOzYOkzXU4LXXsWeo0NFbqzk5nEtZyqXo2m8Uzzzyz46W1O10ubIxBOp2OfKl6a2tw8KmzkzA2tobR0VbMza1jNr8Ps+sj2Js4hdn1EayadvSvrGx7uTAApNPpyJeqr62tYXJyMvKl6gsLC1jZaHOUS9X37m3BwYPB0rpDQy144ok1HDmSwLPPPlvTZd0rKytIp9Msl6ovLCxgcnIy8qXquVwO6XQ68qXqRIR0Oh35UvWVlRXMzc1Zu1S9zkStO9aXBJM235HmcFq+OpyWr07YhD3AfD2Alxljniai3zXGfJyIvgrg0wBuj611MeW553jW4urp6VHHkqWOPYuzTTElUj1qxJqEXDUHkDfOvjqcljp2rZji3DxI2lyH01LHnqVOQxO17rDcXLSWS9UPHDhQvPw2ymXd2Wx20+XCla8Jc7nwk0+ewOzs8wefCpfP9yfG0Z8YBwB0tcwG71lx2Xfl5cKVbar3su5Kp97Luru7u1kuVf/Wt3LFbXTmTPB94/jxNbzvfReH7hMQHMSoNvb1XNZ9ySWXFK0ol3W3t7cXXxflUvXKMav3UvWCY+tS9ToTqe40YkkwafMdaQ6n5avDafnqhE3YRdw78fwlVktE1GmMeQLAi+NpVry59FKeyyimp6fVsWSpY8/ibFNMiVqPimsSGmNyCH6gekPpE7jXJOSqOYC8cfbV4bTUsWvFFOfmQdLmOpyWOvYsdRqaqHWneCYhEbUhOJPw4dInENHhkv9GPpNQ2vjo/Gvn6PcK95yYE3m+Y3tJMGmfYWkOp+Wrw2n56oRN2L3xBwCuBvDPAB4FcDsRncf2vwUvS4hL0t8D4L8AWAMwBeBdxpj0xmPvQHDJFgD8v8aYPwn7vtWiv+Wy43Ba6tizHDirJ2o9Yrm7cS3RM5jdczgtdexaMSXyPMh2pM11OC117FnqNDSR6k4jziSUNj46/9o5+r3CPSfm6HzHM4fT8tXhtHx1wibsAeZ3I1iLFAgOuHwSQBeAXwzz4pCXpP8LgKuMMYtE9MsIbjTxZiLqB/A7AK5CcBbh8Y3XngvZ9k1JpXjWKsrlcupYstSxZ3G2KaZEqkdhs9OahEAt6xK2YM+eFiQSwIkTeVxxRSumptYxmT+I8+tDGEk8gbPrR9CCPFKLi9uuDZfP5zE/Px95XUIiwtLSUtnacPWs4bewsID29vZIay329PRgfDy4VDVKnwYGBjA5OYn5+flIfSqsdzc+Po58Pl93nwpr+E1PT5e1qd41/JLJJObn5yP1aWJiAvl8Hvl8PlKfcrkcpqen0dHREXmtxUwmg9XV4LJlznUJmWOl7nBG2lyH01LHnqVOQxO57hhjvgLgKxVfu63k3++O3sznI218uOogIK9v0raR1i97TszR+Y5nDqflq8Np+eqETagDzMaYYyX/fgrAq2p8n+Il6QBARIVL0osHmI0xj5Q8/58AvG3j3/8RwNeMMbMbr/0agrVQH6ixDcX09rbg+bpZf5aWliIbPjucljr2LM42xRGGesSyJiEQfl3CtrbTxXX/gOfXANyTOIM9iTMAgEMtxwEA2c7ObdeGS6fTZY9Xe88wa8Ol02lcdNFFVR+vZW24dDqN9vb2SGstFt6r8L719glA2XqEUdclTKVSxb7U2ycgOGharU21ruFXOfb1ruGXTqcxMDAQqU9AUCsq13+sd13CdDqN3t5e1nUJOQ8yM9Qd65E21+G01LFnqdO4uFh3pI0PVx0E5PVN2jbS+mXPiTMu1h1pn2FpDqflq8Np+eqETegFa4joGgA3AtgHYBzAg8aYr4d8eahL0ktyM4C/3ua1I5UvqOUOxwDwkpe0Rj6TsHCQJuqZhF1dXTh79mzkMwnX19exvLwc+UzCfD6Pubm5yGcSLiwsIJ/Pb7rD8dnVq8vu2nxx6xjS6fS2Z6jl83nMzMzU3afCWXfJZJLlDsf9/f1Ip9ORzyRsb2/HzMxM5DMJl5aWim2KeiZhMplkv8MxdyLWI+t3Nx4bW4vy8rIMDw+rY8HhtNSxa8WViHXHerjqjsRxVseepU5j41rdkTY+Ov/aOfq9wj0n7rhWd6R9hqU5nJavDqflqxM2oQ4wE9F7AfwGgP+BYCmLFwD4X0R0tzHmI5wNIqK3IVgO4+W1vK6WOxwDwd1xATlnEpZ+rdFnEiYSCZYzCXfv3o10Or3pDLeRZPCL0cJdm7frU2mbfD2T8MCBA5HPJKzWJl/PJIxajxqxJuHoaGvZGcxRkslkqtYddXgdTksdu1YcsTkP4gpX3ZE4zurYs9RpXFysO9LGR+dfO0e/V7jnxBkX6460z7A0h9Py1eG0fHXCJuwZzO8BcI0x5t8KXyCi/wngawDCFJpQl6RvHND5LQAvN8aslLz2pyte+82Q7a6axUUT5eXFtLW1qWPJUseexdmmmBK1Hllfk5Cr5gDyxtlXh9NSx64VUyLXHduRNtfhtNSxZ6nT0DhXd6SNj86/do5+r3DPiTnO1R1pn2FpDqflq8Np+eqETUsNzz1Z8f/TCG66FybFS9KJqA3BJekPlz6BiF4M4NMArjPGTJY89FUAryGiPiLqA/Caja/VnclJnrW4urq61LFkqWPP4mxTjIlSj6yHq+YA8sbZV4fTUseuFWOasu5IHGd17FnqNDxO1R1p46Pzr52j3yvccyzEqboj7TMszeG0fHU4LV+dsAl7gPl2AJ8losNE1EFERwB8BsDvEFFL4c9WLzbGrAEoXJL+AwCfL1ySTkTXbTztwwB2A/gCEX2PiB7eeO0sgDsRHKQ+BuCOwg3/6s3Bg6GXnt42hTWB1YnfUseexdmmmHI7ItSjRoSr5gDyxtlXh9NSx64VU25Hk9YdieOsjj1LnYbmdjhWd6SNj86/do5+r3DPiTm3w7G6I+0zLM3htHx1OC1fnbAJuzd+euPvGxH89oo2/n/TxmO08fXEVkCIS9K3vEOpMeZ+APeHbOuOeeYZnt9yla7prE68ljr2LM42xZTI9ch2uGoOIG+cfXU4LXXsWjGlaeuOxHFWx56lTkPjXN2RNj46/9o5+r3CPSfmOFd3pH2GpTmclq8Op+WrEzZhf/t0ScmfQ1v8/1AcDYwjvb2085NCZGlpSR1Lljr2LM42xRTn6hFXzQHkjbOvDqeljl0rpjRt3ZE4zurYs9RpaJyrO9LGR+dfO0e/V7jnxBzn6o60z7A0h9Py1eG0fHXCJtQZzMaYdNwNsZmurhYA0X/T9Wd/9jiOHft+2dceeOA1NTvLy8uR2yLR4bTUsWdxtimOuFiPuGoOIG+cfXU4LXXsWnGkmeuOxHFWx56lTuPiYt2RNj46/9o5+r3CPSfOuFh3pH2GpTmclq8Op+WrEzai1s+xlbGxNVHO8PCwlw6npY49i7NNmiBctQKQN86+OpyWOnYtTRBpcxROSx17ljqaWiJtfHT+tXP0e4V7jqY80j7D0hxOy1eH0/LVCZumPMA8OsqzEDyXk8lkvHQ4LXXsWZxt0gThqhWAvHH21eG01LFraYJIm6NwWurYs9TR1BJp46Pzr52j3yvcczTlkfYZluZwWr46nJavTtg05QHmhYV1UU57e7uXDqeljj2Ls02aIFy1ApA3zr46nJY6di1NEGlzFE5LHXuWOppaIm18dP61c/R7hXuOpjzSPsPSHE7LV4fT8tUJmx0PMBNRgohOEdEuGw2ykbk5I8rp6Ojw0uG01LFncbaJO67WI65aAcgbZ18dTksduxZ3mr3uSBxndexZ6jQmrtYdaeOj86+do98r3HPiiqt1R9pnWJrDafnqcFq+OmGz4wFmY0wewarp3vzKbf/+hCjn3LlzXjqcljr2LM42ccfVesRVKwB54+yrw2mpY9fiTrPXHYnjrI49S53GxNW6I218dP61c/R7hXtOXHG17kj7DEtzOC1fHU7LVydswi5Y8zEAnyei/w7gWQDFXxMZY07H0bA4c+YMz0LwXM7AwICXDqeljj2Ls00xxbl6xFUrAHnj7KvDaalj14opTVt3JI6zOvYsdRoa5+qOtPHR+dfO0e8V7jkxx7m6I+0zLM3htHx1OC1fnbAJuwbzHwN4NYBHADwF4OTGn6diales2bOH57dcXM7CwoKXDqeljj2Ls00xxbl6xFUrAHnj7KvDaalj14opTVt3JI6zOvYsdRoa5+qOtPHR+dfO0e8V7jkxx7m6I+0zLM3htHx1OC1fnbAJdQazMcarmwF2dpIoJ5fLeelwWurYszjbFEdcrEdctQKQN86+OpyWOnatONLMdUfiOKtjz1KncXGx7kgbH51/7Rz9XuGeE2dcrDvSPsPSHE7LV4fT8tUJm5oKCBHtJ6J/H1djbGVsjOcyCi5neHjYS4fTUseexdmmOONSPeKqFYC8cfbV4bTUsWvFmWasOxLHWR17ljqNj0t1R9r46Pxr5+j3CvccG3Gp7kj7DEtzOC1fHU7LVydsQh1gJqIXENFRAE8A+NuNr91ARPfF2bi4MjoadulpO04mk/HS4bTUsWdxtimOuFiPuGoFIG+cfXU4LXXsWnGkmeuOxHFWx56lTuPiYt2RNj46/9o5+r3CPSfOuFh3pH2GpTmclq8Op+WrEzZhz2D+NIAvA+gCsLrxta8hWJ/HuczNrYtyOjo6vHQ4LXXsWZxtiinO1SOuWgHIG2dfHU5LHbtWTGnauiNxnNWxZ6nT0DhXd6SNj86/do5+r3DPiTnO1R1pn2FpDqflq8Np+eqETdhf97wUwOuNMetEZADAGDNPRD3xNS2+ZLNm5ydZdNra2rx0OC117FmcbYopztUjrloByBvnak7q0RurPjd71QMNaU+jLXXsWjGlaeuOxHFWx56lTkPjXN2RNj7NNv+qJ/q9wj0n5jhXd6R9hqU5nJavDqflqxM2Yc9gngBwWekXiOhKAE+zt8hCRkZ47jTK5czPz3vpcFrq2LM42xRTnKtHXLUCkDfOvjqcljp2rZjStHVH4jirY89Sp6Fxru5IGx+df+0c/V7hnhNznKs70j7D0hxOy1eH0/LVCZuwZzD/AYC/IqIPAWglohsB/FcAd8XWshhz6hTPQvBczuDgoJcOANx99wnMzj5Z9rWH31u7I61v0hxOi7NNMcW5esRVKwB54+yrw2mpY9eKKU1bdySOszr2LHUaGufqjrTx0fnXztHvFe45Mce5uiPtMyzN4bR8dTgtX52wCXUGszHmfgDvB/AmAM8AeAeA3zbG/FmMbYstegazHQfQbWTL4bSk/3bdxXqkZ9C453Ba6ti14kgz1x2J46yOPUudxsXFuiNtfHT+tXP0e4V7Tpxxse5I+wxLczgtXx1Oy1cnbELfctMY8xcA/iLGtlhLezuJclZXV3d+koMOoNvIlsNpcbYprrhWj7j2A0DeOPvqcFrq2LXiSrPWHYnjrI49S53GxrW6I218dP61c/R7hXtO3HGt7kj7DEtzOC1fHU7LVydswq7BDCJ6FxF9jYjGNv6+mYj4vmtbzNgYz2UUXM7w8LCXDqDbyJbDaXG2Ka64Vo+49gNA3jj76nBa6ti14kqz1h2J46yOPUudxsa1uiNtfHT+tXP0e4V7Ttxxre5I+wxLczgtXx1Oy1cnbEIdYCaiuwH8BoCHEFwy8RCA9wH4/fiaFl9GR0OfuG3FyWQyXjqAbiNbDqfF2aY44mI94toPAHnj7KvDaalj14ojzVx3JI6zOvYsdRoXF+uOtPHR+dfO0e8V7jlxxsW6I+0zLM3htHx1OC1fnbAJuze+E8CPGmOeLXyBiP4KwHcBfCCGdsWamZl1UU4qlfLSAXQb2XI4Lc42xZR3wrF6xLUfAPLG+TOfOYnTp6PfyFNavzgtdexaMeWdaNK6I3Gc1bFnqdPQvBOO1R1p4+Pz/EvaNtL6Zc+JOe+EY3VH2mdYmsNp+epwWr46YRN2iYyFjT+VXzvP2xw7WV01opxEgmdhemkOoNvIlsNpcbYppjhXj7j2A0DeOPu6j3Na6ti1YkrT1h2J46yOPUudhsa5uiNtfHyef0nbRlq/7Dkxx7m6I+0zLM3htHx1OC1fnbAJe4D5YwAeIqJXE9EPEdFrAHwBwEeJ6FDhT3zN5M3wMM9G5nLOn+ep19IcQLeRLYfT4mxTTHGuHnHtB4C8cfZ1H+e01LFrxZSmrTsSx1kde5Y6DY1zdafadk09emPVP7U69cTn+Vfc26hRY8Zp+erEHOfqjrT5jjSH0/LV4bR8dcIm7BIZH9/4+xUVX38lgE9s/NsAcOLXck89xbMQPJczNDTkpQPoNrLlcFqcbYopztUjrv0AkDfOvu7jnJY6dq2Y0rR1R+I4q2PPUqehca7uSBsfn+df0raR1i97Tsxxru5I+wxLczgtXx1Oy1cnbEKdwWyMaQnxR0yR2SkHD/I0lcuZnZ310gF0G9lyOC3ONsURF+sR134AyBtnX/dxTksdu1Ycaea6I3Gc1bFnqdO4uFh3pI2Pz/MvadtI65c9J864WHekfYalOZyWrw6n5asTNmGXyPAqXMuQcDnG8KwbJM0BdBvZcjgtzjZpgnAufSRtnH3dxzktdexamiDS9k1OSx17ljqaWiJtfHyef0nbRlq/7Dma8kj7DEtzOC1fHU7LVydsmvIA84kTeVGOtNPfOU+j121kx+G0HLl8y6lw7QeAvHH2dR/ntNSxa2mCSNs3OS117FnqaGqJtPHxef4lbRtp/bLnaMoj7TMszeG0fHU4LV+dsGnKA8xXXBF26Wk7zsTEhJcOoNvIlsNpcbZJE4RrPwDkjbOv+zinpY5dSxNE2r7Jaaljz1JHU0ukjY/P8y9p20jrlz1HUx5pn2FpDqflq8Np+eqETVMeYJ6aWhfl7N6920sH0G1ky+G0ONukCcK1HwDyxtnXfZzTUseupQkibd/ktNSxZ6mjqSXSxsfn+Ze0baT1y56jKY+0z7A0h9Py1eG0fHXCJtQBZiL6iy2+/hBvczQajWb7aD3SaDS2o3VHo9HYjtYdjUZjO1p3NBpNlIQ9g/kVW3z9p8O+ERFdS0RPEtFJIvpglcf/AxF9l4jWiOiGisfyRPS9jT8Ph33PrTI0xHPiNpdz4cIFLx1At5Eth9PibFNMiVyPbIdrPwDkjbOv+zinpY5dK6Y0bd2ROM7q2LPUaWicqzvSxsfn+Ze0baT1y54Tc5yrO9I+w9IcTstXh9Py1QmbbResIaI7Nv7ZVvLvQg4BSId5EyJKALgHwKsBPAvgGBE9bIx5vORpTwN4J4D3VSGWjDEvCvNeYfLEE2uinL1793rpALqNbDmcFmebOMNVjxoRrv0AkDfOvu7jnJY6di3OaN2ROc7q2LPUsR+X64608fF5/iVtG2n9sufEEZfrjrTZQY0pAAAgAElEQVTPsDSH0/LV4bR8dcJmp1/37N/401Ly7/0ALgbwDIA3hXyflwI4aYw5bYzJAXgQwBtKn2CMOWOM+VcAfItlbZEjRxKinKmpKS8dQLeRLYfT4mwTc7jqkfVw7QeAvHH2dR/ntNSxazGn6euOxHFWx56lTkPibN2RNj4+z7+kbSOtX/acmOJs3ZH2GZbmcFq+OpyWr07YbHsGszHm5wGAiL5ljLk3wvuMIChMhTwL4MdqeH07ET0KYA3AXcaY/1P5hMnJSdx8881obW1FPp/H9ddfj1tuuQWZTAapVAqJRALnz5/H0NAQ9u5twUte0ooTJ/K44opWTE2tYzJ/EOfXhzCSeAJn14+gBXmkFhcxNTWF7u5u5PN5ZLNZDA8PI5PJIJlMYtcuwtVXJ/Hcc3mkUoTe3hasrKwgk8mgra0NXV1dmJmZQV9fH5aWlrC8vFx8fXt7Ozo6OnDu3Dmsra3h7NmzyOVyxcc7OjrQ1taG+fl5DA4OYn5+Hqurq8XHK/s0OzuL+fl5DA0NYWJioriY94ULF7B3715MTU2BiNDf379tn3p6ejA3N4euri7kcjksLS0VH6+lTwMDA1hYWMC+fQn84Ad5jI62Ym5uHdmswcnVq7E3cQqz6yNYNe24uHUM6XS6ap+MMRgaGsLc3Bw6Ozvr7tP09DR6enqQzWaRTqcj9SmXy8EYg3Q6Xdc4Ffo0MTGBlZUVzMzMROpTYZwKbaq3T4XHl5aWMDc3V3efqn32OMJYj6wnn+eziEiUw9U3af3itNSxa3FG647McVbHnqWO/bhcd6SNj8/zL2nbSOuXPSeOuFx3pH2GpTmclq8Op+WrEzbbHmAuxBhzLxH1ALgcwO6Kx74RR8MqcsAY8xwRHQLwDSJ6zBhzqvQJe/bswdGjRze/8MCB4r/7+voAAN/61irm5gwA4Nix1eD1iTPYkzgDADjUchwAkO3sLHv94OBgmfn442NFJ0geu3btKntN4WBbd3d31TZ1d3djcXGxePC08vHe3l4AQCqV2rZPnZ2d6O/vR3t7e9njAwMDAID9+/dXfX1lnwDg0ksvLWtP5eNh+lR43j/8w79hcdEUtzMAXJY8BgDoapndsU/V2lRPnwrbr62trejU2ycAm8aslnEqfbzgROlTIZVtqrVPlW2qt0+FlPaJ8zdnAupRzTlzhu8nnP7+flEOV9+k9YvTUseuFUeaue5IHGd17FnqNC4u1h1p4+Pz/EvaNtL6Zc+JMy7WHWmfYWkOp+Wrw2n56oRNqBXRieidAMYB/CWAz5b8uS/k+zyH4BKLQi7e+FqoGGOe2/j7NIBvAnhx2NdWy+HDoY6rW3Oknf7OeTBQt5Edh9MSfvkWRz2yHq79AJA3zr7u45yWOnatOMJRd0Lc7Pg9RPQ4Ef0rEX2diA5Uc8JG2r7Jaaljz1KncXFxviNtfHyef0nbRlq/7DlxxsW6I+0zLM3htHx1OC1fnbAJuzf+HoAbjDF/Xef7HANwmIguQXBg+S0A3hrmhUTUB2DRGLNCRIMAfgLA3XW2AwCQyfD8lovLKT3D1CcH0G1ky+G0ONsUU6LWI+vh2g8AeePs6z7Oaalj14opkepOyJsd/wuAq4wxi0T0ywjmOm+ut8HS9k1OSx17ljoNjXPzHWnj4/P8S9o20vplz4k5ztUdaZ9haQ6n5avDafnqhE3YA8ytAP6m3jcxxqwR0a8A+CqABID7jTFjG3cofdQY8zARXQ3gfwPoA/CfiOh3jTGjAH4IwKeJaB3BGdd3VfxAVnOSSZ51SLicPNPCQdIcQLeRLYfT4mxTTIlUjxoRrv0AkDfOvu7jnJY6dq2YErXuFG92DABEVLjZcXE+Y4x5pOT5/wTgbRHeT9y+yWn9wR98F6dPl1sPPPCahrVHmsNpqdPQODffkTY+Ps+/pG0jrV/2nJgTue4Q0bUAPo7guM99xpi7Kh5/D4D/guD+WlMA3mWMSdf7ftI+w9IcTstXh9Py1QmbsAeYfx/AfyOiO40x6/W8kTHmKwC+UvG120r+fQzB0hmVr/sWgB+u5z23ysBAy6YfTBrpZLPZ4hq7PjmAbiNbDqfF2aaYErke2Q7XfgDIG2df93FOSx27VkyJWndqvdnxzQCqnj0U9qbGIyMt6O4mJBKIdFPjhYUFdHR0bLqxbD03y83lclhdXY18U+MXvjDoS6FPAJBOp2u+We74+DhaW1sj39R4YmKizK/3BsC5XA7ZbDbSjZoL4zQ5OVn2eL03AC68T9SbGi8tLYGIIt/UOJPJoKurK1KfhoeHMT4+jvX19Uh9iuumxiVxbr4j7fuLz/MvadtI4pzAVyfmRKo7jbhiS9pnWJrDafnqcFq+OmET9gDzrwMYBvABIpopfcAY8wL2VsWcsbE1Uc7w8LCXDqDbyJbDaXG2KaY4V4+49gNA3jj7uo9zWurYtWKKtbpDRG8DcBWAl1d7POxNjY8fP4HFxedvRFzvTY1XVlawa9euTTeWrXzPMDeWLVjVHq/lxrJ/+7c/2HQD4cJza7lZ7uWXX17Wnnr6BACXXXZZ0am3TwA2bZ8oNwDu6Oio2qZabwBc2aZ6bwBccKLe1Linp6euG2qXPg8oH3upNzUGQ92xfSahtO8vPs+/pG0jiXMCX52YE7XuWL9iS9pnWJrDafnqcFq+OmET9gBzpJ1eWkZHW8t+KGm0k8lkyiaqvjiAbiNbDqfF2aaY4lw94toPAHnj7Os+zmmpY9eKKVHrTqibHRPRqwD8FoCXG2NWoryhtH2T05LWN2kOp6VOQxOp7jRm7XdZ4+Pz/EvaNtL6Zc+JOVHnOyxXbIW9WmtoaAivfGUbxsfzO16tNdRyBul0essrZrLZLNra2liu1tq9e3fkq7XOnTuHw4cPb3nFTC1XAS0vLxfbHeXKpqmpKVx++eWRrtYaGhrCiRMnMDIyEqlPhSvRUqlU5Ku1hoeH8eSTT2J4eDjylU1TU1Po6OiIdLXW0tIS8vk8EolEpD5lMhlks1ns27eP9Wotoq2XpQl1gNkY83dhnudKlpfNzk+y6CSTSS8dQLeRLYfT4mxTHOGoR7bP6OHaDwB54+zrPs5pqWPXiiMMdWfHmx0T0YsBfBrAtcaYyYjvJ27f5LSk9U2aw2mp07gw1J0GrP0ua3x8nn9J20Zav+w5ccbmcZ/trtgKe7UWAJw5k8djjwVnMW93tVbl6yuvmBkfH8e+ffu2fc8wV8yMj4/joosuqvp4LVfMtLS0oL29fcsrZsL0qfBe4+Pj2LNnT919KjzPGLPpKqJ6rgIaHBws9iXKlU2Li4vFMYt6ZdPg4GBxG0W5smllZaXYpnqv1gI2fx7r6dOBAwcwPj6O3t5e1qu1gOCXQNUS6gAzEe0CcBuAGwEMGGN6iOg1AI4YY/44jCEpzz3HsxZXNSf16I1Vn5u96oEtnZ6eHpb2SHMAvm0trW/SHE6Ls01xJGo9asQZPVz7ASBvnH3dxzktdexacSRq3Qlzs2MAHwawG8AXNs4MeNoYc129bZa2b3Ja0vomzeG01GlcGH7+sn4m4fLyMp555pmyM5+ydZxJ2NbWhnQ6HflMwsXFdYyOtqKzkzA2tobR0VbMza1jNr8Ps+sj2Js4hdn1EayadvSvrGx7NlcqlUI6nY58JuGuXbswOTkZ+UzCxcVFrGy0OcqZhH19hIMHEwCAoaEWPPHEGo4cSeDM2osw1HIGZ/OH0duSwRqSmE2ntzzrLp/PI13yeJSz7hYXFzE5OcmyRno96/NXnknY09ODdDod+UzClpYWzM3NWTuTsJ4w1B3rV2zpnMCe5avDafnqhE3YJTI+imCSchOen3iMbXzduQPMl17aitnZ6JcCcTnT09NV1zZ03QF0G9lyOC3ONsWUqPXI+hk9XPsBIG+cfd3HOS117FoxJfI8KMTNjl/F0tKNSNs3OS1pfZPmcFrqNDTWfv7iOpMwkUgUz24qPJ76v7WfSZhOp6suJVDrGWr9/afLln8o/Ls/MY7+xDgAoKtlFgCQrTgrr/Jsrso21XvWXaVT71l36XSa5UzCpaXgDFDg+b+PH1/D7/z09wAAl7UcKz63a8Oqdtbd/Px88etRzyRMJpMsZxKWbusoZxJWjlm9ZxKm02mrZxLWmah1x/oVWzonsGf56nBavjphE/YA838GcJkxJktE6wBgjHmOiEbia1p8ifMM5noi7bcTegazew6n5cBZPVHrEcsZPUD4s3rm59fxohe1IpHAjuuDpRYXtz2zYteuXSxn9bS1teHs2bOR1wdLpYCuLir2CQBOrl696Uyls/nDaD93bsuzRZaXlzE3NxepTwMDA5vOoIlyVs/y8jJmZoL7m0RZH8wYw3JWT2dnJ9LpdKQ+TUxMgIgwMzMTqU+5XA7Ly8vFs6eintVjjGE/q4c5zs2DpH3/5bSk9U2aw2mp09BErTvWzySUNj4+X0EmbRtp/bLnxJxIdUev2JLncFq+OpyWr07YhD3AnKt8LhENAZip/nTZSaV4LiXhcnK5nJcOoNvIlsNpcbYpplirR9ud0QOEP6vHmJP43veev8PxduuDZTs7tz2zYnJykuWsnsnJyS3X4qrlzIrnnnsSCwum7Ayhy5LHyvoEBGfAZPveU7VPBbPwvvX2CQjW4ir0K+pZPX19fSzrg+VyuaptqvUMmMqxr/cMmMnJSQwMDETqUyGVZ0/Ve1bP5OQk+1k9zAeZnZsHSfv+y2lJ65s0h9NSp6GJWnesn0kobXy4agUgr2/StpHWL3tOzIk837F9xZa0z7A0h9Py1eG0fHXCpiXk874A4E82JiggoosQXCLxYFwNizO9vWG7bcdZWlry0gF0G9lyOC3ONsWUqPWo1jN6rot6Rg/XfgDIG2df93FOSx27Vkxxbh4kbd/ktKT1TZrDaanT0ESqO8aYNQCFMwl/AODzhTMJiahwtmDpmYTfI6KHozRY2vj4PP+Sto20ftlzYo7OdzxzOC1fHU7LVydswu6N/xXA/wXwGIBeAE8BGAdwR0ztijVjY2s7P8miMzw87KUD6Day5XBanG2KKVHrUfGMHiJqQ3BGT9kPVCVn9FzHcUYP134AyBtnX/dxTksdu1ZMcW4eJG3f5LSk9U2aw2mp09BErjvGmK8YY44YYy41xvzextdu27hMHcaYVxlj9hpjXrTxp+7L1AF54+Pz/EvaNtL6Zc+JOTrf8czhtHx1OC1fnbAJdYDZGJMzxvy6MWY3gL0Aujb+H+msvkZldDTsyiB2nEwm46UD6Day5XBanG2KI1HrUSPO6OHaDwB54+zrPs5pqWPXiiMuzoOk7ZuclrS+SXM4LXUaFxfrjrTx8Xn+JW0baf2y58QZF+uOtM+wNIfT8tXhtHx1wibUAWYi+jki+hEAMMZMGWMMEf07Inp7vM2LJ4uLRpTT1tbmpQPoNrLlcFqcbYojHPXI9hk9XPsBIG+cfd3HOS117FpxxMV5kLR9k9OS1jdpDqelTuPiYt2RNj4+z7+kbSOtX/acOONi3ZH2GZbmcFq+OpyWr07YhP11z50AXlTxtWcQXFb+P1lbZCGTkzx3GuVyurq6vHQA3Ua2HE6Ls00xxbl6xLUfAPLG2dd9nNNSx64VU5q27kgcZ2l9k+ZwWuo0NM7VHWnj4/P8S9o20vplz4k5ztUdaZ9hLudDH/o3TE09tunrDzzwmpotaX2T5nBavjphE3YN5m4A5yu+No9gXR7ncvAgz2UUXM7MDM9N6KU5gG4jWw6nxdmmmOJcPeLaDwB54+zrPs5pqWPXiilNW3ckjrO0vklzOC11Ghrn6o608fF5/iVtG2n9sufEHOfqjrTPsLR9E5DXN2kOp+WrEzZhP7WPA3gjgM+XfO0/I1i/1Lk88wzPb7m4nL6+vlid1KM3bvpa9qoHYm8P4M42ct3htDjbFFOcq0dc+wEgb5x93cc5LXXsWjGlaeuOxHGu1rdqcx3AznxHmsNpqdPQOFd3pI2Pz/MvadtI65c9J+Y4V3ekfYal7ZuAvL5JczgtX52wCXsG828AuI+IvkREdxPRQwA+C+C98TUtvvT2kihnaWnJSwfQbWTL4bQ42xRTnKtHXPsBIG+cfd3HOS117FoxpWnrjsRxltY3aQ6npU5D41zdkTY+Ps+/pG0jrV/2nJjjXN2R9hmWtm8C8vomzeG0fHXCJuwB5m8BeCGAYwBSAP4ZwAuNMUfjalic6eoK2207zvLyspcOoNvIlsNpcbYppjhXj7j2A0DeOPu6j3Na6ti1YkrT1h2J4yytb9IcTkudhsa5uiNtfHyef0nbRlq/7Dkxx7m6I+0zLG3fBOT1TZrDafnqhM2OS2QQUQLABQC9xpi74m9S/BkbWxPlDA8Pe+kAuo1sOZwWZ5u442o94toPAHnj7Os+zmmpY9fiTrPXHYnjLK1v0hxOS53GxNW6I218fJ5/SdtGWr/sOXHF1boj7TMsbd8E5PVNmsNp+eqEzY6/FjHG5AGcADAQf3PsZHSUZ8F0LieTyXjpALqNbDmcFmebuONqPeLaDwB54+zrPs5pqWPX4k6z1x2J4yytb9IcTkudxsTVuiNtfHyef0nbRlq/7DlxxdW6I+0zLG3fBOT1TZrDafnqhE3YT+2fAfgrIvo4gGcBmMIDxphvxNGwOLOwsC7KaW9v99IBdBvZcjgtzjbFFOfqEdd+AMgbZ1/3cU5LHbtWTGnauiNxnKX1TZrDaanT0DhXd6SNj8/zL2nbSOuXPSfmOFd3pH2Gpe2bgLy+SXM4LV+dsAl7gPmXN/6+veLrBsAhttZYytyc2flJFp2Ojg4vHUC3kS2H0+JsU0xxrh5x7QeAvHH2dR/ntNSxa8WUpq07EsdZWt+kOZyWOg2Nc3VH2vj4PP+Sto20ftlzYo5zdUfaZ1javgnI65s0h9Py1QmbUCuHG2Mu2eKPyCKzU/bvT4hyzp0756UD6Day5XBanG2KIy7WI679AJA3zr7u45yWOnatONLMdUfiOEvrmzSH01KncXGx7kgbH5/nX9K2kdYve06ccbHuSPsMS9s3AXl9k+ZwWr46YRP61pRElCSinyKiN2/8P0VEqfiaFl/OnOFZMJ3LGRjgWeZImgPoNrLlcFqcbYorrtUjrv0AkDfOvu7jnJY6dq240qx1R+I4S+ubNIfTUqexca3uSBsfn+df0raR1i97Ttxxre5I+wxL2zcBeX2T5nBavjphE+oAMxH9MIIF3+8F8NmNL78cwP0xtSvW7NnD89sgLmdhYcFLB9BtZMvhtDjbFEdcrEdc+wEgb5x93cc5LXXsWnGkmeuOxHGW1jdpDqelTuPiYt2RNj4+z7+kbSOtX/acOONi3ZH2GZa2bwLy+ibN4bR8dcIm7BnMnwRwmzHmCgCrG1/7OwA/GUurYk5nJ4lycrmclw6g28iWw2lxtimmOFePuPYDQN44+7qPc1rq2LViStPWHYnjLK1v0hxOS52Gxrm6I218fJ5/SdtGWr/sOTHHuboj7TMsbd8E5PVNmsNp+eqETdgDzKMA/nTj3wYAjDFZAE6sVF+ZsTGeyw24nOHhYS8dQLeRLYfT4mxTTHGuHnHtB4C8cfZ1H+e01LFrxZSmrTsSx1la36Q5nJY6DY1zdUfa+Pg8/5K2jbR+2XNijnN1R9pnWNq+CcjrmzSH0/LVCZuwB5jPAHhJ6ReI6KUATnI3yEZGR1tFOZlMxksH0G1ky+G0ONsUU87AsXrEtR8A8sbZ132c01LHrhVTzqBJ647EcZbWN2kOp6VOQ3MGjtUdaePj8/xL2jbS+mXPiTln4FjdkfYZlrZvAvL6Js3htHx1wibsp/a3AXyZiD4FoI2IfhPALwH4hdhaFmPm5tZFOR0dPL8QlOYAuo1sOZwWZ5tiinP1iGs/AOSNs6/7OKeljl0rpjRt3ZE4ztL6Js3htNRpaJyrO9LGx+f5l7RtpPXLnhNznKs70j7D0vZNQF7fpDmclq9O2IQ6g9kY81cArgUwhGANngMArjfG/E2MbYst2awR5bS1tXnpALqNbDmcFmeb4oiL9YhrPwDkjbOv+zinpY5dK440c92ROM7S+ibN4bTUaVxcrDvSxsfn+Ze0baT1y54TZ1ysO9I+w9L2TUBe36Q5nJavTtiEXSIDxph/Mcb8P8aY1xtjfskYczzOhsWZkRGeO3JyOfPz8146gG4jWw6nxdmmuOJaPeLaDwB54+zrPs5pqWPXiivNWnckjrO0vklzOC11GhvX6o608fF5/iVtG2n9sufEHdfqjrTPsLR9E5DXN2kOp+WrEzahDjATURsR3UFETxFRduPvO4moPe4GxpFTp3gWTOdyBgcHvXQA3Ua2HE6Ls01xxMV6xLUfAPLG2dd9nNNSx64VR5q57kgcZ2l9k+ZwWuo0Li7WHWnj4/P8S9o20vplz4kzLtYdaZ/huPfN1KM3bvpjq02+OpyWr07YhD2D+ZMArgHwawCu3vj7pwH8f2HfiIiuJaIniegkEX2wyuP/gYi+S0RrRHRDxWPv2ChuTxHRO8K+51bRM5jtOIBuI1sOp+XAb9cj1yPb8fk30L7u45yWOnatmNK0dUfiOEvrmzSH01KnoXGu7kgbH5/nX9K2kdYve07Mca7uSPsMS9s3AXl9k+ZwWr46YRP2Jn8/C+BSY8zcxv8fJ6LvILib6Lt2ejERJQDcA+DVAJ4FcIyIHjbGPF7ytKcBvBPA+ype2w/gdwBcBcAAOL7x2nMh274p7e1U70tjcVZXV710AN1GthxOi7NNMSVSPWpEuPYDQN44+7qPc1rq2LViStPWHYnjLK1v0hxOS52Gxrm6I218fJ5/SdtGWr/sOTHHuboj7TMsbd8E5PVNmsNp+eqETdgzmDMAOiu+1gHgbMjXvxTASWPMaWNMDsCDAN5Q+gRjzBljzL8CqLxd5n8E8DVj/v/2zj86rrO8899HI8mSxtYPy7IVO46dEIcQLSy7JOSc7dkc2pQ00G3p5tAtpge6S3bbbkM5e0qXH90WtulygBba7oa0gTbQLd2Y0tBSnz0pCS3NtgQCtmkKiMSOnUo4tmX9smRZPyJp9Owfd0bWSCPpzp1n7nz1zvM5R8fWjOaj533f+3x1596ZOzqeP6j8ZUQXnk9Mf7/N2yisPL29vUF6AJ+jtDyWLsuaqkSleZQ6Vn0A8K1zqD1u6XJPuq4qUbe5w7jObGNj81i63FNTtlzusK1PyPtfbHPk+ZWep8psudxh24bZehPgGxubx9IVqicucV/B/FkAXxKRBxC9Ank/gPsA/LGI/FDhh1T1K+s8fh+Asyu+fxHA7TF/d6nH7lv9Q8PDw7j33nvR2NiIXC6He+65B/fddx+GhoaQzWaRyWRw+fJl9PT04M47m3H+fA6nTuVw882NGBlZwnDuIC4v9WBf5jlcWLoJDcghOzODkZERtLe3I5fLYXp6Gr29vRgaGkJTUxNuvbURs7PAuXM5ZLOCzs4GzGkbXlzswzaZQXvDMEZyB9GdOYtLFy9ibm5u+fEtLS1obW3FpUuXMD8/j+3bt2N+fn75/tbWVjQ3N2NychK7du3C5OQkFhYWlu9fPabx8XFcunQJhw4dwsWLF7F9+3YAwJUrV3D90o7lMfU0DOBC7hBaLl0qOaaOjg6cOXMG1113Hebn5zE7O7t8f3NzM3bs2IGxsTF0dXVhdnZ23TF1d3djamoKd93VjCeemEdfXyMmJpYwPa04vXAb9mTOYHxpHxa0Bdc29mNwcLDkmFQVPT09OHXqFPbt27c8pj179mBkZAQigp07d264Th0dHRgdHUVHRwfOnz+PbDZb0Zjm5+eRy+WQyWQSrVNhTBcvXsTs7Cx6enoqGlNhnQo1JR1T4f7p6Wns3bs38ZhWbnuFMRlTaR6lTl9fI44dszl7ODQ0hAMHDtB4rMbGNi5Ll3vSdVWJus0dxnVmGxubx9Llnpqy5XKHbX1C3v9imyPPr/Q8VWbL5Q7bNszWmwDf2Ng8lq5QPXGJe4D55/L//sqq238+/wVEl6+4waKoJOzevRtPPfXUmttXTmZXVxeA6GzQCy/kAGC5aXdnBrA7MwAAuKEh+qDU6ba2oscXLpBduO3FF59d9kTk0HLHDG5sOrZ8S0dDdHCtec+ekjW1t7djdHS06OLbK+/v7OwEAGSz2Q3H1NbWhpaWFrS0tBTd393djdaRqeUxAcCNDccw3fVLJccEAHv37l3+vaV+Z+EAYnt7+7pjKvzct7/9PczMaFE4FuZnR8P4pmNaWVN3d/fymABg//79JR9fakyF+VtcXCx5fzljArBmzcpZp5X3j46Ooru7u6IxFVhdU7ljWllTZ2dn4jEVWDkm44PM9Hm0mrGx1W/MSM7qda+1x2psbOOydLknXVeVqNvcYVxntrGxeSxd7qkpWy532NYn5P0vtjny/ErPU2W2XO6wbcNsvQnwjY3NY+kK1ROXWAeYVfX6Cn/POURnvwpcm78t7mNft+qxT1ZSzMKCVvJwc08mY3MBdzYP4HOUlsfSZVlTNTDIo9Sx6gOAb51D7XFLl3vSdVWDes4dxnVmGxubx9LlntqxFXOHbX1C3v9imyPPr/Q81WQr5g7bNszWmwDf2Ng8lq5QPXGJew3mSjkG4JCIXC8izQDeAuBozMc+DuAuEekSkS4Ad+VvS0xvr80kW3kuX74cpAfwOUrLY+myrMmJsOoDgG+dQ+1xS5d70nU5EWy9aeliGxubx9LlHqcc2NYn5P0vtjny/ErP4xTDtg2z9SbANzY2j6UrVE9c4l4ioyJUdVFE3onowHAGwKdVtV9E7gdwXFWPishtAP4CQBeAHxORX1fVPlUdF5HfQHSQGgDuV9Xxkr8oJs8/b3PBdCtPT08PlecjHzmFiYmTa24/cuSusl2hzhGbx9JlWZMTYdUHAN86h9rjli73pOtyIth609LFNjY2j6XLPU45sK1PyPtfbHPk+ZWexymGbRtm602Ab2xsHktXqPxpSogAACAASURBVJ64pPUKZqjqY6p6k6q+TFU/lL/tA6p6NP//Y6p6rapmVbVbVftWPPbTqnpj/uszldZy8KDN2SArz/h4RcfLl3nggadx+PATa77KxWpcli6rOQrVY+myrMmJsOwptnUOtcctXe5J1+VEsPWmpYttbGweS5d7nHJgW5+Q97/Y5sjzKz2PUwzbNszWmwDf2Ng8lq5QPXFJ7QAzE1aXIbHyqFpdN8hEY+axdFnNUageS5dlTU6EZU+xrXOoPW7pck+6LieCrTctXWxjY/NYutzjlAPb+oS8/8U2R55f6XmcYti2YbbeBPjGxuaxdIXqiUtdHmA+dSpH5bF62TrbuCxdbG8RYPNYuvztW/ZY9hTbOofa45Yu96TrciLYetPSxTY2No+lyz1OObCtT8j7X2xz5PmVnscphm0bZutNgG9sbB5LV6ieuNTlAeabb7a59LSV5+LFiyYetnFZuqzmKFSPpcuyJifCsqfY1jnUHrd0uSddlxPB1puWLraxsXksXe5xyoFtfULe/2KbI8+v9DxOMWzbMFtvAnxjY/NYukL1xKUuDzCPjCxRebZv327iYRuXpctqjkL1WLosa3IiLHuKbZ1D7XFLl3vSdTkRbL1p6WIbG5vH0uUepxzY1ifk/S+2OfL8Ss/jFMO2DbP1JsA3NjaPpStUT1zsTos4juM4juM4juM4dcnHPvYMBgaK39Z99N01KsZxHMdxnFSpy1cw9/TYDNvKc+XKFRMP27gsXVZzFKrH0mVZkxNh2VNs6xxqj1u63JOuy4lg601LF9vY2DyWLvc45cDWmyHvf7HNkedXeh6nGLZtmK03Ab6xsXksXaF64lKXB5ife26RyrNnzx4TD9u4LF1WcxSqx9JlWZMTYdlTbOscao9butyTrsuJYOtNSxfb2Ng8li73OOXA1psh73+xzZHnV3oepxi2bZitNwG+sbF5LF2heuJSlweYb7opQ+UZGRkx8bCNy9JlNUeheixdljU5EZY9xbbOofa4pcs96bqcCLbetHSxjY3NY+lyj1MObL0Z8v4X2xx5fqXncYph24bZehPgGxubx9IVqicudXmAOZfb/GfS9IiIiYdtXJYuqzkK1WPpsqzJibDsKbZ1DrXHLV3uSdflRLD1pqWLbWxsHkuXe5xyYOvNkPe/2ObI8ys9j1MM2zbM1psA39jYPJauUD1xqcsP+Vv94RO19uzcudPEwzYuS5fVHIXqsXRZ1uREWPYU2zqH2uOWLvek63Ii2HrT0sU2tg996FlMTHxvze1HjtxVk3osXe5xyoGtN0Pe/2KbI8+v9DxOMWzbMFtvAnxjY/NYukL1xKUuX8F86JDNcXUrj9XL1tnGZelie4sAm8fS5W/fsseyp9jWOdQet3S5J12XE8HWm5YutrGx1WPpco9TDmy9EPL+F9sceX6l53GKYduG2XoT4Bsbm8fSFaonLnV5gHloyOZskJWnvb3dxMM2LkuX1RyF6rF0WdbkRFj2FNs6h9rjli73pOtyIth609LFNja2eixd7nHKga0XQt7/Ypsjz6/0PE4xbNswW28CfGNj81i6QvXEpS4PMDc12VyHxMqTM7rADtu4LF1WcxSqx9JlWZMTYdlTbOscao9butyTrsuJYOtNSxfb2NjqsXS5xykHtl4Ief+LbY48v9LzOMWwbcNsvQnwjY3NY+kK1ROXujzA3N1tM2wrz/T0tImHbVyWLqs5CtVj6bKsyYmw7Cm2dQ61xy1d7knXxYqI3C0iJ0XktIi8r8T9d4jIt0RkUUTeXOnvY+tNSxfb2NjqsXS5xykHtl4Ief+LbY48v9LzOMWwbcNsvQnwjY3NY+kK1ROXujzA3N+/SOXp7e018bCNy9JlNUeheixdljU5EZY9xbbOofa4pcs96boYEZEMgAcBvAHALQAOi8gtq37s+wD+PYBHLH4nW29autjGxlaPpcs9Tjmw9ULI+19sc+T5lZ6HnbRPqLNtw2y9CfCNjc1j6QrVE5e6PMDc12dzwXQrz9DQkImHbVyWLqs5CtVj6bKsyYmw7Cm2dQ61xy1d7knXRcprAZxW1RdUdR7A5wC8aeUPqOqAqn4bwJLFL2TrTUsX29jY6rF0uWdrk/aBHrZeCHn/i22OPL/S8zBTixPqbNswW28CfGNj81i6QvXExW6r3ULMzSmVp6mpycTDNi5Ll9UcheqxdFnWxIqI3A3gfwLIAPhDVf3IqvvvAPC7AF4F4C2q+mglv8+yp9jWOdQet3S5J10XKfsAnF3x/YsAbk8iGh4exr333ovGxkbkcjncc889uO+++zA0NIRsNotMJoPLly9DRPHqVzcikwFOncrh5psbMTKyhOHcQVxe6sG+zHO4sHQTGpBDdmYGIyMjaG9vRy6Xw/T0NHp7ezE0NISZmRlMT09jdHQUHR0dmJ+fx+zs7PL9zc3N2LFjB8bGxtDV1YXZ2VnMzc0t39/S0oLW1lZcunQJS0tLuHDhAubn55fvb21tRXNzMyYnJ7Fr1y5MTk5iYWFh+f6VY+rp6cH4+Dh6egQ7dsjymADg9MJtRWPqaRjAhdwhtFy6tGZMTU1N6OjowNTUFCYmJioaU3d3N7q6BLfd1oT+/kX09TViYmIJ09OKwcHB2GNSjbJ0cHAQ27dvBwBcuXIFe/bswcjICEQEO3fuXHedCmMqrNNLL72EwcHBxGOamprC/Pw8RASDg4OJ1klV0dPTg4sXL2J+fh5jY2MVjWl+fh5TU1N46aWXKhpTb28vpqamMDw8XNGYSq0TEysO9LweUeYcE5Gjqvq9FT9WONDzyxa/k22fIOT9L7Y5YtwnCNVDzvIJdQAQkcIJ9eXcUdWB/H0mJ9TZtmG23gT4xsbmsXSF6olLXR5gPnfO5kLXVp6Ojg4TD9u4LF1WcxSqx9JlWRMjtXjCZdlTbOscao9butyTrit0du/ejaeeemrN7QcOHFj+f1dXF06fPoXx8atPTo4dW4genxnA7swAAOCGhhMAgOm2tqLH79q1a9k5PT2NbDaLbDa74e8sHGxb+WnVK+9vb29fdpW6v7OzEwDWvb+rqwsA0NbWhqeffhZTU7o8JgC4selY0ZgA4MaGY5ju+qU1Yypw/fXXrxlXuWMCgOPHF5bnemVNhZ+NMyYAa+anu7sbALB///6Sjy81psLjm5qalv+fZEyFn1tdUznrtPL+gqeSMRX+v23btorGBBSvfdIxFVg5JrKDzKkf6GHbJwh5/4ttjhj3CUL1kGNyQj3uyfSenh7s2CF4zWsaNz2Z3tMwgMHBwXVPaDY3N2NwcLDik+ltbW0mJ9M7OtaeTO/pacDs0o6yTqaPjo5i27ZtGB4eruhk+tTUFP7yL0/i+PH+opPp73rXobJP0s7MzGBsbAxAZSfTc7mcycn03t5ezMzMmJ14HhwcrOhk+uzsLDo6OjA4OFjRmIaGhtDQ0ICJiQnTk+ki638AZV0eYH7ZyxoxPr6w+Q+m5BkdHS35xK1W9Vh5LF1WcxSqx9JlWRMpqT/hsuwptnUOtcctXe5J10XKOQD7V3x/bf62qsHWm5YutrGx1WPpcs+WJvUDPT/wA804fz5X8YGe6elpNDc3V3yg55WvbMToqKKtTYreYTCe24vxpX3YkzmD8aV9WNAW7My/Mn69J9vz8/NobGys+B0Gc3Nzy3VXclBkZGQEL3/5yxMfvCocQLjjjmY880x0rdeengY899wibropg4HFVy8fvOpsGMIimjC+4kDO6oMi58+fRzabNTnQc+bMGfT29lZ8oGdkZAStra0VH+jJ5XLIZDIVH+iZnp7G3r17UzvQs5WJezIdABYWgBMnom14o5Ppqx+/+oTm4OBg0f2lHhPnhOZqT9KT6S+99Pyak+kDAzm03jFV1sn0bDa7YU3lnKSdnX0OMzNa0cl0IDoJXjg5W8mJ58nJyeXbKz3x3NTUhN27dwOo7MTzyrlOejJ9tSfpmA4cOIDBwUF0dnaankwHon2DUtTlAWa2V/qynYH2VzBvPY+lqw7Orqf+VvXJySWTt6o3NTVh27ZtJmfXm5ubTc6uZ7Mweav63NycyVvVV5/JruRJ19zcnMnZdVU1Obve1tZm8lZ1ETF5q/rc3JzJW9WHhoagquZn18k4BuCQiFyP6MDyWwC8tZq/kO3vr6WLbWxs9Vi63OOUc6DnxIkFnD8f7QtUcqBnYmJi+cnwer8zzpPt559/frmelTXtzJzHzsx5AMCOhnEAwPSqV8avfrK9uqakB0VWe5IeQGhtbV3zav4kBxC++c2razYwEGXZiROL+ODrngEQHbwqsKPEgZxS73Co9KDIddddt+yq5KBIJpNZfnwlB3pWr1nSAz0FT1oHempE6ifU2f4Gs+1bAHw1sc21pStUT1zq8gBzNmtzps/KMz8/b+JhG5ely2qOQvVYuixrCp24T7pUTy+/OgRI/lZ1INqJtDi7Pjw8vHyWdvX95ez4njt30uSt6l1dXWueTCZ5gjIzM7M8rkqfdHV1dZmcXZ+fny9ZU7lPUFavfdInKMPDw+ju7q74reoATN6qXqjJ+kkX00FmVV0UkXcCeBzRtd8/rar9InI/gOOqelREbgPwFwC6APyYiPy6qvYl/Z1sf38tXWxjY6vH0uWeLU3qB3rYesHyOQ3btsc2R55f6XnISf2EOts2zNabAF9NbHNt6QrVE5e6PMDc2dkAoPKzL1ae2dnZih0A37gsXVZzFKrH0mVZEympP+Gy7Cm2dQ61xy1d7knXxYqqPgbgsVW3fWDF/48hyiMT2HrT0sU2tvXqyR4/vOa26VuPVL0eS5d7tjSpH+jZKr2ZBLZtj22OPL/S8zBTixPqbNswW28CfDWxzbWlK1RPXOryAHN//+LmP5Sip7e318TDNi5Ll9UcheqxdFnWRErqT7gse4ptnUPtcUuXe9J1ORFsvWnpYhsbWz2WLvdsXWpxoIetF0Le/2KbI8+v9DzspH1CnW0bZutNgK8mtrm2dIXqiUtDqr+NhL4+m+PqVp6hoSETT7XHlT1+eM1XWjVZzVG1PeXOkVU9li7LmhhR1UUAhSdczwL4fOEJl4j8OACIyG0i8iKAnwTwSRHpr+R3WvUBwLfOofa4pcs96bqcCLbetHSxjY2tHkuXe7Y2qvqYqt6kqi9T1Q/lb/uAqh7N//+Yql6rqllV7a7k4DLA1wsh73+xzZHnV3oepxi2bZitNwG+mtjm2tIVqicudfkK5pkZpfI0NzebeNjGZemymqNQPZYuy5pYSfvMumVPsa1zqD1u6XJPui4ngq03LV1sY2Orx9LlHqcc2Hoh5P0vtjny/ErP4xTDtg2z9SbAVxPbXFu6QvXEpS4PMA8P21zLxsqzY8cOEw/buCxdVnMUqsfSZVmTE2HZU2zrHGqPW7rck67LiWDrTUsX29jY6rF0uccpB7ZeCHn/i22OPL/S8zjFWG3DH/7wdzEy8p01tx85cldZHrbeBErXtN47rTf6rAi2vPDcSc8Tl7q8RMbBgzbH1a08Y2NjJh62cVm6rOYoVI+ly7ImJ8Kyp9jWOdQet3S5J12XE8HWm5YutrGx1WPpco9TDmy9EPL+F9sceX6l53GKYTsGwtabAF9NjD3FVhObJy51+Qrms2dtzrxYebq6ukw8bOOydFnNUageS5dlTU6EZU+xrXOoPW7pck+6LieCrTctXWxjY6vH0uUepxzYeiHk/S+2OfL8Ss/jFMN2DIStN4Hq1pTkldCMPcVWE5snLnX5CubOTqHyzM7OmnjYxmXpspqjUD2WLsuanAjLnmJb51B73NLlnnRdTgRbb1q62MbGVo+lyz1OObD1Qsj7X2xz5PmVnscphu0YCFtvAnw1MfYUW01snrjU5QHmHTtshm3lmZubM/GwjcvSZTVHoXosXZY1ORGWPcW2zqH2uKXLPem6nAi23rR0sY2NrR5Ll3uccmDrhZD3v9jmyPMrPY9TDNsxELbeBPhqYuwptprYPHFJ7QCziNwtIidF5LSIvK/E/dtE5E/z939DRA7mbz8oIrMi8kz+66FKa+nvX6xUYerp7e018bCNy9JlNUeheixdljU5EZY9xbbOofa4pcs96bqcCLbetHSxjY2tHkuXe5xyYOuFkPe/2ObI8ys9j1MM2zEQtt4E+Gpi7Cm2mtg8cUnlALOIZAA8COANAG4BcFhEbln1Y/cCuKSqNwL4HQAfXXHfGVV9df7r5yutp6/P5tLTVp6hoSETD9u4LF1WcxSqx9JlWZMTYdlTbOscao9butyTrsuJYOtNSxfb2NjqsXS5xykHtl4Ief+LbY48v9LzOMWwHQNh602ArybGnmKric0Tl7RewfxaAKdV9QVVnQfwOQBvWvUzbwLwv/P/fxTAnSJid+GZFUxNLVF5WlpaTDxs47J0Wc1RqB5Ll2VNToRlT7Gtc6g9bulyT7ouJ4KtNy1dbGNjq8fS5R6nHNh6IeT9L7Y58vxKz+MUw3YMhK03Ab6aGHuKrSY2T1zsTotszD4AZ1d8/yKA29f7GVVdFJFJAN35+64XkX8AcBnAr6rq36/+BcPDw7j33nvR2NiIXC6He+65B/fddx+GhoaQzWaRyWRw+fJl9PT0oKenAdms4NSpHG6+uREjI0sYzh3E5aUe7Ms8hwtLN6EBOWRnZjAyMoL29nbkcjlMT0+jt7cXQ0NDaGpqwtIScNttTTh3LodsVtDZ2YA5bcOLi33YJjNobxjGSO4gujNnceniRczNzS0/vqWlBa2trbh06RK2bduGCxcuYH5+fvn+1tZWNDc3Y3JyErt27cLk5CQWFhaW7189pvHxcezZ04Bz55aWxwQAPT0NmF3asTymnoYBXMgdQsulSyXH1NHRgWuuyeDyZV0eU3//Ivr6GnF2sa9oTDNLnZgcHCw5pu7ubkxNTeGaazL4/veX0NfXiImJJUxPK04v3IY9mTMYX9qHBW3BtY39GBwcLDkmVUVPTw8mJyfR2BhtrleuXMGePXswMjICEcHOnTs3XKeOjg6Mjo6io6MDc3NzGFxRc3NzM3bs2IGxsTF0dXVhdnZ23XUqjGl+fh7bt2/H4ODgmnUaXXzl8pheXOzD9oYxLF66VHJMFy9eRCaTwdjYWEVjmp+fx+zs7HJNScdUuB8AJiYmytr2Vo5p+/bta9ap3pmYUDNXa2srlcdqbGzjsnS5J12XE8HWm5YutrGx1WPpco9TDmy9EPL+F9sceX6l53GKsdqG2XqBMb/Y5shzJz1PXNI6wFwJFwBcp6pjIvIaAF8UkT5Vvbzyh3bv3o2nnnpqzYMPHDiw/P+uri4AwNwccOJEdP2YY8cWosdnBrA7MwAAuKHhBABguq2t6PG7du0qcnZ0nFx+fEQOLXfM4MamY8u3dDREB9ea9+wpWVN7ezsGBweLblv5/87OTgBANpvdcExtbW2YmXkeU1NaVNPAQA6td0wtjwkAbmw4humuXyo5JgC4ckVx/nzh7FRueZ5+7Y7+ojF1NQyhM/+41WMCgO3bt+PKlecwM1NcU2F+djSMbzqmAtu2bUN3d3S+ofDv/v37Sz6+1JgK8zc5Obl8+8r7CwdFC7VvNCYAa9assE67G7+zZpzTXV0lx3TgwAEMDg6iu7u7ojEVWF1TuWNaWVNnZ2dZ216p+1eOqd4PMu/fn8HQkM0Z30uXLhWtaa09VmNbr57s8cNrbpu+9UjZHsua3GPrsXY5EdXuzVq62MbGVo+lyz1OObD1Qsj7X2xz5PmVnscpxmobZusFxvximyPPnfQ8cUnrEhnnAOxf8f21+dtK/oyINALoADCmqi+p6hgAqOoJAGcA3FRJMQMDNhcnt/IUDsRVCtu4LF1WcxSqx9JlWZMTYdlTbOscao9butyTrsuJYOtNSxfb2NjqsXS5xykHtl4Ief+LbY48v9LzOMWwHQNh602ArybGnmKric0Tl7QOMB8DcEhErheRZgBvAXB01c8cBfAz+f+/GcBXVFVFpCf/IYEQkRsAHALwQiXF7N6dqeTh5p6pqSkTD9u4LF1WcxSqx9JlWZMTYdlTbOscao9butyTrsuJYOtNSxfb2NjqsXS5xykHtl4Ief+LbY48v9LzOMWwHQNh602ArybGnmKric0Tl1QukZG/pvI7ATwOIAPg06raLyL3AziuqkcBPAzgsyJyGsA4ooPQAHAHgPtFZAHAEoCfV9Xxtb8lPm1tNp8daOWZn5838bCNy9JlNUeheixdljU5EZY9xbbOofa4pcs96bqcCLbetHSxjY2tHkuXe5xyYOuFkPe/2ObI8yu5p9zLwTnFsB0DYetNgK8mtt60dIXqiUtq12BW1ccAPLbqtg+s+P8cgJ8s8bgvAPiCZS39/TYv7bfy9Pb2mnjYxmXpspqjUD2WLsuanAjLnmJb51B73NLlnnRdTgRbb1q62MbGVo+lyz1OObD1Qsj7X2xz5PmVnscphu0YCFtvAnw1MfYUW01snrikdYkMKvr6bI6rW3mGhoZMPGzjsnRZzVGoHkuXZU1OhGVPsa1zqD1u6aqmJ3v8cMmvWtWzXk1JXU5y2HrT0sU2NrZ6LF3uccqBrRdC3v9imyPPr/Q8TjFsx0DYehPgq4mxp9hqYvPEJbVXMDMxMWHzaZxWntbWVhMP27gsXVZzFKrH0mVZkxNh2VMPP3wazz9/sui2I0fuKtvDljuM2y9bTaF6rF1OhFVvlsocwHNnJWz1WLrc45QDWy9Y7n+xbXtsc+T5lZ7HKYbtGAhbbwJ8NTH2FFtNbJ641OUB5ulppfI0NzebeNjGZemymqNQPZYuy5qciJB7iq2ekHsqVI+1y4mo9j5BkmtGhpo7bPVYutzjlANbL1juf7Fte2xz5PmVnscphu0YCFtvAnw1MfYUW01snrjU5SUy9u2z+fRLK8/k5KSJh21cli6rOQrVY+myrMmJCLmn2OoJuadC9Vi7nAjGfYJQc4etHkuXe5xyYOsFxvxi87CtmaUrVI9TDNv+DltvAnw1MfYUW01snrjU5SuYz5yxuTi5lWfXrl0mHrZxWbqs5qiUZ73rg270Sqxq1lNrl2VNTkTIPcVWT8g9FarH2uVEMO4ThJo7bPVYutzjlANbLzDmF5uHbc0sXaF6nGLY9nfYehPgq4mxp9hqYvPExV/BTOBhO6MU8qstQ/VYuvzsuj0h9xRbPSH3VKgea5cTwbhPEGrusNVj6XKPUw5svcCYX2wetjWzdIXqcYph299h602ArybGnmKric0Tl7o8wNzSIlSehYUFEw/buCxdVnMUqsfSZVmTExFyT7HVE3JPheqxdjkRjPsEoeYOWz2WLvc45cDWC4z5xeZhWzNLV6gepxi2/R223gT4amLsKbaa2DxxqcsDzP39Ni/tt/L09vaaeNjGZemymqNQPZYuy5qciJB7iq2ekHsqVI+1y4lg3CcINXfY6rF0uccpB7ZeYMwvNg/bmlm6QvU4xbDt77D1JsBXE2NPsdXE5olLXR5g7uuzufS0lWdoaMjEwzYuS5fVHIXqsXRZ1uREhNxTbPWE3FOheqxdTgTjPkGoucNWj6WrlCd7/HDJr1rVU0uPUwxbLzDmF5uHbc0sXaF6nGKqvb9Tq793jPnFlhf1lju13P+KS11+yN/Y2BKVJ5vNmnjYxmXpspqjUD2WLsuanIiQe4qtnpB7KlSPtcuJYNwnCDV32OqxdLnHKQe2XmDMLzYP25pZukL1OMWw7e+w9SbAVxNjT1m5PvWp03jhhZNFtx05clfN6kk7d+ryAPPCglJ5Mhmbi6WzjcvSZTVHoXosXZY1OREh9xRbPSH3VKgea5cTwbhPEGrusNVj6XKPUw5svcCYX2wetjWzdIXqcYph299h600A+M3ffAZnzxYfHD767vI9bHPEmDshz1Ec6vISGb29NpNs5bl8+bKJh21cli6rOQrVY+myrMmJCLmn2OoJuadC9Vi7nAjGfYJQc4etHkvXVvGU+5ZRz5zqwNYLjPnF5mFbM0tXqB6nGLb9HbbetHSxzRFj7pSaoySXtmCcozjU5QHm55+3uTi5laenp8fEwzYuS5fVHIXqsXRZ1uREhNxTbPWE3FOheqxdTgTjPkGoucNWj6XLPU45sPUCY36xedjWzNIVqscphm1/h603LV1sc8SYOyHPURzq8gDzwYM2Z16sPOPj4yYetnFZuqzmKFSPpcuyJici5J5iqyfkngrVY+1yIhj3CULNHbZ6LF1WngceeBqHDz9R9FXLejxzqgNbLzDmF5uHbc0sXaF6nGLY9nfYetPSxTZHjLkT8hzFoS6vwWx1GRIrj6rVdVpMNGYeS5fVHIXqsXRZ1uREhNxTbPWE3FOheqxdTgTjPkGoucNWj6Ur1DnyzKkO1V7nUm8pnr71SNXrAfi2vVB709IVqscphm1/h603LV1sc8SYOyHPURzq8gDzqVM5Ko/Vy9bZxmXpYnuLAJvH0uVv37In5J5iqyfkngrVY+1yIhj3CULNHbZ6LF2hzpFnTnVgW2fG/GLzsK2ZpStUj1MM2/4OW29autjmqNq5U+5JTSDsOYpDXV4i4+abbY6rW3kuXrxo4mEbl6XLao5C9Vi6LGtyIkLuKbZ6Qu6p3/u9r5u8xZxtXNYuJ4JxnyDU3GGrx9IV6hx55lQHtnVmzC82D9uaWbpC9TjFsO3vsPWmpYttjhhzJ+Q5ikNdvoJ5ZGSJyrN9+3YTD9u4LF1Wc2Tleeih0xgYOLnm9qPvrk09QOmajhy5q2yPZU1ORMg9ZVUPY0+x5Q7b2jPOtXMVxn0Ctl6w+rvJ1puWrmqu2XqfoL7Rq4PYxuUUw9YLjPnF5mFbM0tXqB6nGLb9HbbetHSxzRFj7oQ8R3Goy1cwO47jOI7jOI7jOI7jOI7jOJVTlweYe3pshm3luXLliomHbVyWLqs5Yptrq3oAzpqciJB7ii13LLdfz510PNYuJ4KtNwG+XmDzMPYU25qxjcsphm2dGfOLzcO2wGD/lgAAE7xJREFUZpauUD1OMaH+LWd8/sg2R4y5E/IcxaEuL5Hx3HOLVJ49e/aYeNjGZemymiO2ubaqB+CsyYkIuafYcsdy+/XcScdj7XIi2HoT4OsFNk+1eyrJJSnY1owxv5yrsK0zY36xedjWzNIVqscpJtS/5YzPH9nmiDF3Qp6jONTlK5hvuilD5RkZGTHxsI3L0mU1R2xzbVUPwFmTExFyT7HljuX267mTjsfa5USw9SbA1wtsHsaeYlsztnE5xbCtM2N+sXnY1szSFarHKSbUv+WMzx/Z5ogxd0KeozjU5SuYczkuj4iYeNjGZemymiO2ubaqB+CsyYkIuafYcsdy+7VyPfLI83jmmWeLbkvyQWJsc1RqXED5H8y4nivJHDlXYetNINzcYetNSxfbmrGNyymGbZ0Z84vNYzVH6+0TJPlbzjZHjPtNzlVC/VvO+PyRbY4Y95tCnqM41OUB5oEBm1W38uzcudPEwzYuS5fVHLHNtVU9QHVrSvK2WucqIfcUW+5Y9pTP0cYwbtfOVdi2O4Bv22PzMOYX25qxjcsphm2dGfOLzcOWgwDfHLHNtVMM2zbMuL2EOkeM+00hz1Ec6vISGYcO2RxXt/JYvWydbVyWLra3CLCNC+CsyYkIuafYcofxrVKhzhHjdu1chW27A/i2PTYPY36xrdlDD30Dhw8/searXHxfpzqw9QJjfrF52HIQ4Jsjtrl2imHbhhm3l1DniHG/KeQ5ikNdptzQkM1ZBStPe3u7iYdtXJYuqzlim2uregDOmpyIavdUqVeYb/bqcrZeYNx+fY42hvFvhXMVtu0O4Nv22DyM+RXqmvm+TnWwWp8HH3weZ8+eXHN7uZcSYMwvNk+1e7OW+6hsHt/XqQ6h/n1h3M9mmyPG/aaQ5ygOdXmAuanJ5jokVp6c0YVa2MZl6bKao4997Ft44YViV5LrXrGNC7CryWqOnKuE3FNsuWPZUz5HG8O4XTtXYdvuAL5tj81jmV9Wf8tDXbNS8wP4td8rhW2dGfOLzeNznZ7H93WqA9s2zLi9hDpHIT/vY5yjONTlJTK6u22GbeWZnp428bCNy9IV6hxZjQvgG5tzFe+p9DyWPVXNOcoeP1zyq1xPEtjW3trlRLD1JsC37bF5GPcJfM2ccmBbH8b8YvP4XKfn8dypDmzbMOP2EuocbZXnfUlgnKM41OUrmPv7F6k8vb29Jh62cVm6Qp0jq3EBfGNzruI9lZ7Hsqd8jjaGcbt2rsK23QF8214pT5IPtWXrTYCvJrbtcT1PkrfzO1fZKuucBKteYPP4XKfn8X2d6sC2DTNuL6HOUcjP++6//xRmZoovFZXknWiWcxSHujyN1tdnc1zdyjM0NGTiYRuXpSvUObIaF8A3Nucq3lPpeSx7yudoYxi3a+cqbNsdwLftsXkY9wkefPBrFX+gnmU9bB6nGLb1sVxnq16w8oSap4Dd2Ng8njvVgW0bZtxeQp2jUnl6+PATZb9L1LImtrleb46qRWoHmEXkbhE5KSKnReR9Je7fJiJ/mr//GyJycMV978/fflJEfqTSWr7xDZsJtfJ88YtfNPGwjcvSFeocvec9D5k1fKmakoSr5fqzUkkeJcF7Kj2P1bgsXWxzZJU7jNs1M1s1dyzXJtSeYswvtrGF6mGn3nOH8e8UW16wjQuwG5uVh3G/iZl6zx223rR0hTxHbDWxeeKSygFmEckAeBDAGwDcAuCwiNyy6sfuBXBJVW8E8DsAPpp/7C0A3gKgD8DdAH4v70vMiRNfruTh5p4///M/N/GwjcvSFeocMc61ZU2MVJJHSWFc51B7ympcli62OWLzWLsY2cq5Y7k23lMbs978JDlZzDa2UD3MeO5w/p1i299hGxdgN7aQ54gVzx2+7c7SFfIcPfDAZ01e9Mc21+t5kuxbxiGt92m8FsBpVX0BAETkcwDeBOB7K37mTQD+e/7/jwL4hIhI/vbPqepLAP5JRE7nfV9PWsy2bTaf7GjlWVy0uU4L27gsXaHOEeNcW9ZESuI8UlVN8gsZ1znUnlpvXEmuqxnqHLF5rF2kbNncsVwb76mNsZofgG9soXrIqfvcYfw7xZYXbOMCgNHRmTUHd44cuatsT8hzREzd5w7bdmfp8jmqX09cJGEfl/dLRN4M4G5V/Y/5798G4HZVfeeKn/lu/mdezH9/BsDtiMLnaVX9k/ztDwP4K1V9dOXveOyxx6YuXLiw/Irs9vb2kZ07d46Wqmd8fHzXeveVg3u2Xk2helhrWsGBO++8s8fYmYhK8khVi+Ylbu6EvM6hehhrCtVj7VqB506g6+yerVdTqJ4SBJc7/hyLs6ZQPYw1sXlK4LlDtD5sHsaa2DyMNbF5SlAyd4K50vwb3/jGHbWuwXGc+sJzx3GctPHccRwnTTxzHMdJG88dx9mapPUhf+cA7F/x/bX520r+jIg0AugAMBbzsY7jOHGpJI8cx3GS4LnjOE7aeO44jpM2njuOU8ekdYD5GIBDInK9iDQj+tC+o6t+5iiAn8n//80AvpK/Ds9RAG/Jf9ro9QAOAfhmSnU7jhMeleSR4zhOEjx3HMdJG88dx3HSxnPHceqYVC6RoaqLIvJOAI8DyAD4tKr2i8j9AI6r6lEADwP4bP5D/MYRhRHyP/d5RBeGXwRwn6rm0qjbcZzwqCSPHMdxkuC54zhO2njuOI6TNp47jlPfpPIhf44TKiLyOlV9MuFjtwM4COBGAIdV9acMS3McJ0AqyZz84z13HMcpC9/XcRwnbTx3HMdJG8+dygnmQ/7ikr/OTwMAqOp8BR4BcA2AC0nf0iEiN62+TVVPJfDsUdWLSWoo4boHwCsBfFdVv5DQ8R0AnwTwh6o6Z1FXJYjIfgATqjpl4NoB4G0A9iI6K3sYUZCU6/lvAN4OYBTAywF8MGE9bwTwqwB6AbwA4JdV9ZkkLqd6WOSORebkPZ47KWCVO1aZk3d57tQRnjubujx31vdQ7evkXZ475DA9x8p7gssdtswBPHec2hJi7lhmTt4XVO6EfGwn79rSuVM3B5hF5O0A7gdQCIzdALIJXf8awGcQXYx+p4j8B1X9agLVJ1d9rwB+KIHnqIhkATwH4HdU9akEDojIRxFdcP/vAPxbEXmtqr43gWoh7/muiHwGwCdUdTJhTRcQXRplHMCTAO5X1XI/BODzANpE5B8AvBvAH6vqjyapB8CfAPg2gOfz388k9PwYgFeo6lI+2J4A8GACz0cA/BSA0wBuBfC/ANxRriQf1P8ZwHW4+kf6rQnqcVZglTuGmQN47sSpiSl3rDIH8NypCzx3NsdzZ1PY9nUAzx1aSJ9jAWHmjlnm5Gvy3NkYzx1SAs8dk8wB+HKHLHMAzx17VLUuvgCcANC54vu/rcD1VQDX5v9/LYCv1np8+Vr+GYC/BfBvEj7+a6vHmdDzlfy/7QDeD+BkheMSADsB/DtEQdSS0PNbiM4CvbmCWv6+1FgTeH5k1fc/m9Dz8Krv/yah56uIAuh1+a9vVbJm/rU8rya5w5o5+Xo8dzb2VJQ7VpmTf6znTh18ee7EerznzsaPp9rXyT/Wc4f0yypzVqyP5876DtPMybs8d9Z3ee6QftVD7lSaOXkHXe6wZE7e4blj/NWA+qERwOUV33+9Apeq6osi8jZVfTGpRESeFJEmEWkufCX0vF9EDgM4CeAnALwzYUkvrfp+oYwabhCRu0TkrsJtqnpZVT8M4FUJ6yl4VFXHATwK4CkAv1iuQ0T+K6IzP69X1UcrKGdxtTqJRFUfX/X9pxJ67l0uRKQTwPYkHgBNqvr7qvqkRtcdSvxqCKcIq9wxyRzAcycuRLljkjmA504d4bmzOZ47G0O1r5N/rOcOL3TPsYBwcqeamZN3ee6s7/Lc4SXY3DHMHIAwd4gyB/DcMaeeDjD/LoDHReTtInKDqv5KBa52EflxAL+Q/z72E5NV3I4oOApfzyX0nEbUYL+v0dsVlhJ6+jf5fiNeieiaNYcRfWrsMqq6OthiIyJ7ReQdIvJniM5Q3QzgzWU6jubrO49o7dZcG6kM/mKT71NFRL4uIl8TkWMAvgPg4wlVZ0XkP634I/gmmwrrHqvcscocwHNnU8hyhypzAM+dLYDnzuZ47myM545TDozPsYBwcqcqmQN47myG5w41IeeOVeYAZLlDljmA5445kn/5dPCIyD8C+D6AFxFdy6RXVfcndH0G0dmgI6r6/0Tkvar60QSev1XVH0xSQwnXQQBHATwE4L+oatmNJiJfx9XrGAFXz+Coqv6rSmtMgoh8G8BjAP4KwFOquigiHwfwiKqeiOl4q6o+kj8D93OI3k5zZ/WqTg8ROZD/7yKiDyVI9AdIRN4P4NcATAN4FsDTqvoemyrrF6vcscqcvMtzZxM8dzbGc4cbz51YDs+dLYbnDi+Mz7HyLs+dTfDc2RjPHV5Czx2LzMl7qHLHM2dztnru1NMB5j5V7V/xfbMm/1T1HkQb83XIf1Ciqr4jgccqgM4DOIvoLNkpAKdU9fMJPAfWu09VB5NXmBwRuRbAuxB9smdDVIr+dC1qCRmJPgDg4wBGAPQBuFVV/6imRQWAVe5YZU7e5bmzCZ476eC5Ux08d2J5PHfqFM8dexifY+Vdnjub4LmTDp479oScO1aZk3dR5Y5nTnrUKnfq5gAzAIjIdSj+FMW/S+h5DNGZl9PInxHSVdddien5DVX9tSQ1rPLcBuBjiC5K/z0Av6yqJyv1MiAiXwbwfwD8E6Izbr+tqv+yTIcAeD2K1z7xdXEcpxwscscqc/Iuz51N8NxxtjqeO1sPzx1nK8P2HCvv8tzZBM8dZysTau545mzq8Mwhpm4OMIvIBwH8KIAz+ZtUVd+a0PU3TC/DF5G/B/BuAP8I4AcBvNfqLWG1RkS+oqo/tOL7ss8KisijAHKI3hqgAH5GVW+wrXRrIyL7APwPADcCyABArd6uFxJWucOWOYDnTgyH584meO5UB8+drYnnTjp47tgT8nMswHMnhsNzZxM8d+wJOXc8czZ1eObEoFa501jtX0DE61X1tUauRJ8uuUYicgHRtVXGATwJ4H5VHUugWlDVb+b//yUReZ9FfaQkOSOyd2Uzicjr7MoJhocB/CmA+1HZBwk4xVjljknmAJ47CfHcqQ6eO9XBcycMPHeqg+eOPXTPsQDPnYR47lQHzx17Qs4dz5yN8cyJR01yp54OMFf0KburEAAQkccBvArRGbO95UpU9Zr8S/y7APwwgC+IyN2qOpe4MJE9AFqSPp6Q14jI1/L/FwCvSCIRkVeo6rP5bz9oUllYtKrqZ2pdRIBY5Y5J5gCeOzHx3EkHz53q4LmzNfHcSQfPHXvonmMBnjsx8dxJB88de+oidzxzSuOZE4ua5E49HWC+VkR+duUNFVyr5Sfzj/+RSovS6Bol4/mX+v9zAL8I4LfK1BQatRlAN4BfqLQuIl5l4Pg4gOMi8g0AXwXwtIEzNPxsenWwyh2zzMl7PHc2xnMnHTx3qoPnztbEcycdPHfsoXyOlfd47myM5046eO7YE3LueOZsjGdOPGqSO/V0gPkRANdYiFR11MIjInsB3A3gDQBuA3AC0cXcy93xKTTqS6o6ZFEbC2rz6abvAfA2AOcA3Iroj8hjBt6QeKTWBQSKSe5YZQ7guRMHz53U8NypDp47WxDPndTw3LGH7jkW4LkTB8+d1PDcsSfk3PHM2RjPnHjUJHfq6UP+vgvgkwD+oJK3RlkiIt9G1Ax/BeApVV0UkY8DeERVT9S2unAQkV5EZ/72IrrAuarqO2pbFRci8k+IznI9COCvAfyZqr68tlVtfTx36hfPnc3x3KkOnjv1i+fO5nju2MOYOYDnTlp47myO5449njv1i2dOPGqVO/V0gPlbAL4M4B4AfwTgE6o6WeOargXwLkTN0YCoOX66ljWFiIh8CcD/BXAa+QvJq+rjNS2KFBH5awC7AeRU9V/Uup6tjudO/eK5Ex/PHVs8d+oXz534eO7YwZg5gOdOWnjuxMdzxw7PnfrFM6c80s6dhmr/AiImVPW9iF5GvwTgm5v8fBp8BsD3APwBgE8h4UXOnU1pVtVPqOqXVPVxD6C1iEibiHwWwCiAHwAwUNuKgsFzp37x3NkEz52q4blTv3jubILnTlVgzBzAcyctPHc2wXOnKnju1C+eOTGoVe4EfQ1mEbkBwI0rb8uf2fqwiPx2baoqIqOqf1T4RkRqftYtUBpEpAnRK/bna10MKV8D8ElV/X0AiD781kmC546Tx3Nnczx3jPDccfJ47myO544BWyBzAM+dtPDc2RzPHQM8d5w8njnxqEnuBH2AGcArAfxE/v9FZzZU9aX0y9mU+rheSfrcDuAkABGRDIAnVfXtNa6JjXeo6rdWfP/FmlWy9fHccQDPnTh47tjhueMAnjtx8NyxYatlDuC5Uy08dzbHc8cGzx0H8MyJS01yp26uwcxI/oxWf+FbAK9Q1c4alhQkIvLR/FtoCt8/qaqvq2FJjlMzPHfSwXPHca7iuZMOnjuOcxXPnXTw3HGcq3juVB/PHG78AHMNEZEDq29T1cFa1OI4Tn3gueM4Ttp47jiOkzaeO47jpI3njlPv+AFmx3Ecx3Ecx3Ecx3Ecx3EcJxENtS7AcRzHcRzHcRzHcRzHcRzH2Zr4AWbHcRzHcRzHcRzHcRzHcRwnEX6A2XEcx3Ecx3Ecx3Ecx3Ecx0mEH2B2HMdxHMdxHMdxHMdxHMdxEuEHmB3HcRzHcRzHcRzHcRzHcZxE/H+5NefwMpsmFwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1440x720 with 10 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<Figure size 1440x720 with 10 Axes>,\n",
              " <matplotlib.axes._subplots.AxesSubplot at 0x7fac9ee0edd0>)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9FPrSCs4YrJv"
      },
      "source": [
        "We can see here that in each one of the Jew settelments, the biggest party is Likud, but we cant assume that it tells us somthing about the data.\n",
        "Kolot Psulim is really small part of the data, so to check the top 10 psulim is not that right inspection.\n",
        "\n",
        "The better inspection is to try to predict of which party the Kolot Psulim are coming from. (unsupervised learning when the Y vector is the kolot psulim).\n",
        "\n",
        "In general, when we trying to inference abot fraud kalpies, the data become pretty imbalanced (low share of the fraud data from the whole sample) for classical machine learning classification."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x8AGaippso-k"
      },
      "source": [
        "### Q2."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WqKl8MLxt8__"
      },
      "source": [
        "#### a."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gV6gwW0HwoaE"
      },
      "source": [
        "size_order = (df_2021_a_raw.iloc[:,:-1].sum(axis=0)).sort_values(ascending=False).keys().to_list()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eZo0j2lZxINp"
      },
      "source": [
        "$cov_{x,y}=\\frac{\\sum_{i=1}^{N}(x_{i}-\\bar{x})(y_{i}-\\bar{y})}{N-1}$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sV2jxEDJvVeL"
      },
      "source": [
        "from sklearn.covariance import empirical_covariance\n",
        "\n",
        "cov_2021 = df_2021_a.iloc[:,:-1].cov()\n",
        "# cov_2021 = df_2021_a_raw.iloc[:,:-1].cov()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_efKWDLxwdOo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 784
        },
        "outputId": "98c77fb1-96e8-4eec-af4d-8040c4387c22"
      },
      "source": [
        "# Display heatmap for a correlation matrix \n",
        "# Input: \n",
        "# corr_mat - matrix of correlations \n",
        "# names - vector with names for each row/column\n",
        "def heatmap_corr(corr_mat, names):\n",
        "    rev_names = [parties_dict[name][::-1] for name in list(names)]\n",
        "    fig, ax = plt.subplots()\n",
        "    fig.set_size_inches(17, 12)\n",
        "    im = ax.imshow(corr_mat, cmap=plt.get_cmap('inferno'))\n",
        "    n = corr_mat.shape[0]  # get number of variables \n",
        "    ax.set_xticks(np.arange(n))\n",
        "    ax.set_yticks(np.arange(n))\n",
        "    ax.set_xticklabels(rev_names, fontsize=12, rotation=45)\n",
        "    ax.set_yticklabels(rev_names, fontsize=12)\n",
        "    ax.set_title(\"Parties pairwise correlations\", fontsize=18)\n",
        "    \n",
        "    # Create colorbar\n",
        "    cbar = ax.figure.colorbar(im, ax=ax) #  **cbar_kw)\n",
        "    cbar.ax.set_ylabel('votes correlation', rotation=-90, va=\"bottom\", fontsize=14)\n",
        "\n",
        "heatmap_corr(cov_2021, size_order)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1224x864 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CzmKdWdZyRde"
      },
      "source": [
        "#### b. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kQs3V4pGyTjw"
      },
      "source": [
        "$d(x,y)=(\\boldsymbol{x}-\\boldsymbol{y})^\\top\\Sigma^{-1}(\\boldsymbol{x}-\\boldsymbol{y})$\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wxENyuse6nLu"
      },
      "source": [
        "##### b."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "baw13h-66nLw"
      },
      "source": [
        "\n",
        "\n",
        "df_2021 = ballot_2021.iloc[:,[3]+list(range(10,ballot_2021.shape[1]))]\n",
        "df_2020 = ballot_2020.iloc[:,[3]+list(range(10,ballot_2020.shape[1]))]\n",
        "\n",
        "\n",
        "df_2021_raw = ballot_2021_raw.iloc[:,[3]+list(range(10,ballot_2021.shape[1]))]\n",
        "df_2020_raw = ballot_2020_raw.iloc[:,[3]+list(range(10,ballot_2020.shape[1]))]\n",
        "# df_2021 = ballot_2021[[\"קלפי\"]+ biggest_2021]\n",
        "# df_2020 = ballot_2020[[\"קלפי\"]+ biggest_2020]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7-Q2sTOnAzvM"
      },
      "source": [
        "\n",
        "only_small_cities = bigCitiesFilter(ballot_2020_raw, 50000)\n",
        "\n",
        "mean_by_city = MeanByCity(only_small_cities)\n",
        "df_2020_big_cities = df_2020[df_2020.index.isin(only_small_cities.index)]\n",
        "\n",
        "# df_2020_big_cities = getByKalpiAndCity(df_2020, only_small_cities.reset_index()[[\"קלפי\",\"שם ישוב\"]])\n",
        "# df_2020_big_cities.set_index(\"שם ישוב\", inplace=True)\n",
        "kalpis_order = df_2020_big_cities[\"קלפי\"]\n",
        "df_2020_big_cities_mean = df_2020_big_cities.copy()\n",
        "for col in df_2020_big_cities_mean.columns:\n",
        "    df_2020_big_cities_mean[col].values[:] = 0\n",
        "\n",
        "df_2020_big_cities_mean = df_2020_big_cities_mean.add(mean_by_city, axis=1)\n",
        "cov_2020_b = df_2020_big_cities.iloc[:,1:].cov()\n",
        "\n",
        "\n",
        "cov_inv_2020_b = pd.DataFrame(np.linalg.pinv(cov_2020_b.values), cov_2020_b.columns, cov_2020_b.index)\n",
        "#moor penrose inverse\n",
        "\n",
        "def mahalanobisD_b(X,Y,cov_inv):\n",
        "    kalpi = []\n",
        "    city = []\n",
        "    m = []\n",
        "    for i in range(X.shape[0]):\n",
        "        kalpi.append(X.iloc[i,0])\n",
        "        city.append(X.reset_index().loc[i,\"שם ישוב\"])\n",
        "        m.append(mahalanobis(X.iloc[i,1:],Y.iloc[i,1:],cov_inv))\n",
        "    \n",
        "    results = pd.DataFrame(zip(kalpi, city, m), columns=[\"קלפי\", \"שם ישוב\", \"d\"])\n",
        "    return(results)\n",
        "\n",
        "mD_b_2020 = mahalanobisD_b(df_2020_big_cities ,df_2020_big_cities_mean, cov_inv_2020_b)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1CAPA8w87Dwf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "fc446db4-66eb-48b3-9261-1574da6bf3c6"
      },
      "source": [
        "mD_b_2020.set_index(\"שם ישוב\").sort_values(by=\"d\", ascending=False).iloc[:10,::-1]\n"
      ],
      "execution_count": null,
      "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>d</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.8755</td>\n",
              "      <td>31.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קרית ביאליק</th>\n",
              "      <td>41.7002</td>\n",
              "      <td>12.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.6648</td>\n",
              "      <td>7.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.6596</td>\n",
              "      <td>24.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.6301</td>\n",
              "      <td>41.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.5938</td>\n",
              "      <td>15.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.5609</td>\n",
              "      <td>44.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.5520</td>\n",
              "      <td>28.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.5481</td>\n",
              "      <td>13.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלה אדומים</th>\n",
              "      <td>41.5393</td>\n",
              "      <td>27.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  d    קלפי\n",
              "שם ישוב                    \n",
              "מעלה אדומים 41.8755 31.0000\n",
              "קרית ביאליק 41.7002 12.0000\n",
              "מעלה אדומים 41.6648  7.0000\n",
              "מעלה אדומים 41.6596 24.0000\n",
              "מעלה אדומים 41.6301 41.0000\n",
              "מעלה אדומים 41.5938 15.0000\n",
              "מעלה אדומים 41.5609 44.0000\n",
              "מעלה אדומים 41.5520 28.0000\n",
              "מעלה אדומים 41.5481 13.0000\n",
              "מעלה אדומים 41.5393 27.0000"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zo44hVucH8vC"
      },
      "source": [
        "Example:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4L3qBJZGj9Mh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 132
        },
        "outputId": "f1d7f84b-fb28-4641-b92c-890fe661f671"
      },
      "source": [
        "\n",
        "compareKalpiWithMean(df_2020, 31.0000, \"מעלה אדומים\")"
      ],
      "execution_count": null,
      "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>קלפי</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ג</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>ז</th>\n",
              "      <th>זך</th>\n",
              "      <th>זץ</th>\n",
              "      <th>טב</th>\n",
              "      <th>י</th>\n",
              "      <th>יז</th>\n",
              "      <th>ינ</th>\n",
              "      <th>יף</th>\n",
              "      <th>יק</th>\n",
              "      <th>יר</th>\n",
              "      <th>כ</th>\n",
              "      <th>כן</th>\n",
              "      <th>ל</th>\n",
              "      <th>מחל</th>\n",
              "      <th>נ</th>\n",
              "      <th>נז</th>\n",
              "      <th>ני</th>\n",
              "      <th>נץ</th>\n",
              "      <th>נק</th>\n",
              "      <th>פה</th>\n",
              "      <th>ףז</th>\n",
              "      <th>ץ</th>\n",
              "      <th>ק</th>\n",
              "      <th>קי</th>\n",
              "      <th>קך</th>\n",
              "      <th>קץ</th>\n",
              "      <th>שס</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>top_kalpi</th>\n",
              "      <td>31.0000</td>\n",
              "      <td>0.0186</td>\n",
              "      <td>0.0103</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0639</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1464</td>\n",
              "      <td>0.5856</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0062</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0887</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean_by_city</th>\n",
              "      <td>106.5432</td>\n",
              "      <td>0.0158</td>\n",
              "      <td>0.0189</td>\n",
              "      <td>0.0006</td>\n",
              "      <td>0.0007</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1206</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0592</td>\n",
              "      <td>0.5852</td>\n",
              "      <td>0.0012</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.1096</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0767</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 קלפי    אמת      ג   ודעם  ...     קי     קך     קץ     שס\n",
              "top_kalpi     31.0000 0.0186 0.0103 0.0000  ... 0.0000 0.0000 0.0000 0.0804\n",
              "mean_by_city 106.5432 0.0158 0.0189 0.0006  ... 0.0001 0.0001 0.0004 0.0767\n",
              "\n",
              "[2 rows x 31 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eUTUVRdNK3Qr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "bb4d04ff-905a-44c4-ea65-908b8eeed3a9"
      },
      "source": [
        "results_b_2020"
      ],
      "execution_count": null,
      "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>SumSquared</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>צפת</th>\n",
              "      <td>1.0670</td>\n",
              "      <td>40.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>חצור הגלילית</th>\n",
              "      <td>1.0081</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קרית גת</th>\n",
              "      <td>0.8372</td>\n",
              "      <td>74.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.7101</td>\n",
              "      <td>7.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6967</td>\n",
              "      <td>25.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.6951</td>\n",
              "      <td>60.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6607</td>\n",
              "      <td>28.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.6551</td>\n",
              "      <td>46.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.6498</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.6427</td>\n",
              "      <td>41.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              SumSquared    קלפי\n",
              "שם ישוב                         \n",
              "צפת               1.0670 40.0000\n",
              "חצור הגלילית      1.0081  3.0000\n",
              "קרית גת           0.8372 74.0000\n",
              "מעלותתרשיחא       0.7101  7.0000\n",
              "מעלותתרשיחא       0.6967 25.0000\n",
              "נוף הגליל         0.6951 60.0000\n",
              "מעלותתרשיחא       0.6607 28.0000\n",
              "עכו               0.6551 46.0000\n",
              "מעלותתרשיחא       0.6498  3.0000\n",
              "עכו               0.6427 41.0000"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "52RjnJoAaaN9"
      },
      "source": [
        "We can see that we got a totally different results.\n",
        "It means that Maale adumim have some really diversed neighebrhoods (probably the outliers)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9R6auIwCLKw7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "e062c1a6-4d41-4a09-e873-071321d86832"
      },
      "source": [
        "\n",
        "only_small_cities = bigCitiesFilter(ballot_2021_raw, 50000)\n",
        "\n",
        "mean_by_city = MeanByCity(only_small_cities)\n",
        "df_2021_big_cities = df_2021[df_2021.index.isin(only_small_cities.index)]\n",
        "\n",
        "# df_2021_big_cities = getByKalpiAndCity(df_2021, only_small_cities.reset_index()[[\"קלפי\",\"שם ישוב\"]])\n",
        "# df_2021_big_cities.set_index(\"שם ישוב\", inplace=True)\n",
        "kalpis_order = df_2021_big_cities[\"קלפי\"]\n",
        "df_2021_big_cities_mean = df_2021_big_cities.copy()\n",
        "for col in df_2021_big_cities_mean.columns:\n",
        "    df_2021_big_cities_mean[col].values[:] = 0\n",
        "\n",
        "df_2021_big_cities_mean = df_2021_big_cities_mean.add(mean_by_city, axis=1)\n",
        "cov_2021_b = df_2021_big_cities.iloc[:,1:].cov()\n",
        "\n",
        "\n",
        "cov_inv_2021_b = pd.DataFrame(np.linalg.pinv(cov_2021_b.values), cov_2021_b.columns, cov_2021_b.index)\n",
        "#moor penrose inverse\n",
        "\n",
        "mD_b_2021 = mahalanobisD_b(df_2021_big_cities ,df_2021_big_cities_mean, cov_inv_2021_b)\n",
        "mD_b_2021.set_index(\"שם ישוב\").sort_values(by=\"d\", ascending=False).iloc[:10,::-1]\n"
      ],
      "execution_count": null,
      "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>d</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>רהט</th>\n",
              "      <td>55.2726</td>\n",
              "      <td>21.2000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.2032</td>\n",
              "      <td>3.2000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.1156</td>\n",
              "      <td>30.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0647</td>\n",
              "      <td>32.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0425</td>\n",
              "      <td>35.2000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0318</td>\n",
              "      <td>2.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0218</td>\n",
              "      <td>16.4000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0193</td>\n",
              "      <td>13.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>55.0123</td>\n",
              "      <td>16.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נס ציונה</th>\n",
              "      <td>54.9983</td>\n",
              "      <td>13.5000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               d    קלפי\n",
              "שם ישוב                 \n",
              "רהט      55.2726 21.2000\n",
              "נס ציונה 55.2032  3.2000\n",
              "נס ציונה 55.1156 30.0000\n",
              "נס ציונה 55.0647 32.0000\n",
              "נס ציונה 55.0425 35.2000\n",
              "נס ציונה 55.0318  2.0000\n",
              "נס ציונה 55.0218 16.4000\n",
              "נס ציונה 55.0193 13.3000\n",
              "נס ציונה 55.0123 16.3000\n",
              "נס ציונה 54.9983 13.5000"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2JbfjiRzj2VB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 132
        },
        "outputId": "6e03078c-1441-4cb6-b22b-bfc42a9c54be"
      },
      "source": [
        "\n",
        "compareKalpiWithMean(df_2021, 21.2000, \"רהט\")\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "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>קלפי</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ב</th>\n",
              "      <th>ג</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>ז</th>\n",
              "      <th>זץ</th>\n",
              "      <th>ט</th>\n",
              "      <th>י</th>\n",
              "      <th>יז</th>\n",
              "      <th>ינ</th>\n",
              "      <th>יף</th>\n",
              "      <th>יק</th>\n",
              "      <th>יר</th>\n",
              "      <th>כ</th>\n",
              "      <th>כך</th>\n",
              "      <th>כן</th>\n",
              "      <th>ל</th>\n",
              "      <th>מחל</th>\n",
              "      <th>מרצ</th>\n",
              "      <th>נ</th>\n",
              "      <th>ני</th>\n",
              "      <th>נר</th>\n",
              "      <th>עם</th>\n",
              "      <th>פה</th>\n",
              "      <th>ףז</th>\n",
              "      <th>צי</th>\n",
              "      <th>צכ</th>\n",
              "      <th>צף</th>\n",
              "      <th>ץ</th>\n",
              "      <th>ק</th>\n",
              "      <th>קי</th>\n",
              "      <th>קך</th>\n",
              "      <th>קץ</th>\n",
              "      <th>ר</th>\n",
              "      <th>רנ</th>\n",
              "      <th>רף</th>\n",
              "      <th>רק</th>\n",
              "      <th>שס</th>\n",
              "      <th>ת</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>top_kalpi</th>\n",
              "      <td>21.2000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0035</td>\n",
              "      <td>0.1923</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0035</td>\n",
              "      <td>0.3252</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0070</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1678</td>\n",
              "      <td>0.0070</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.2622</td>\n",
              "      <td>0.0035</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0070</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0210</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean_by_city</th>\n",
              "      <td>31.4077</td>\n",
              "      <td>0.0045</td>\n",
              "      <td>0.0007</td>\n",
              "      <td>0.0006</td>\n",
              "      <td>0.2236</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0290</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>0.0023</td>\n",
              "      <td>0.0006</td>\n",
              "      <td>0.0615</td>\n",
              "      <td>0.0270</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.6289</td>\n",
              "      <td>0.0050</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0007</td>\n",
              "      <td>0.0010</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0007</td>\n",
              "      <td>0.0007</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0009</td>\n",
              "      <td>0.0069</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                קלפי    אמת      ב      ג  ...     רף     רק     שס      ת\n",
              "top_kalpi    21.2000 0.0000 0.0000 0.0035  ... 0.0000 0.0000 0.0000 0.0210\n",
              "mean_by_city 31.4077 0.0045 0.0007 0.0006  ... 0.0007 0.0000 0.0009 0.0069\n",
              "\n",
              "[2 rows x 40 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xs0_xZcuthlE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 132
        },
        "outputId": "10d87be1-2b5c-4cbe-80c1-3fea80d4632b"
      },
      "source": [
        "compareKalpiWithMean(df_2021, 31.1000, \"מעלה אדומים\")"
      ],
      "execution_count": null,
      "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>קלפי</th>\n",
              "      <th>אמת</th>\n",
              "      <th>ב</th>\n",
              "      <th>ג</th>\n",
              "      <th>ודעם</th>\n",
              "      <th>ז</th>\n",
              "      <th>זץ</th>\n",
              "      <th>ט</th>\n",
              "      <th>י</th>\n",
              "      <th>יז</th>\n",
              "      <th>ינ</th>\n",
              "      <th>יף</th>\n",
              "      <th>יק</th>\n",
              "      <th>יר</th>\n",
              "      <th>כ</th>\n",
              "      <th>כך</th>\n",
              "      <th>כן</th>\n",
              "      <th>ל</th>\n",
              "      <th>מחל</th>\n",
              "      <th>מרצ</th>\n",
              "      <th>נ</th>\n",
              "      <th>ני</th>\n",
              "      <th>נר</th>\n",
              "      <th>עם</th>\n",
              "      <th>פה</th>\n",
              "      <th>ףז</th>\n",
              "      <th>צי</th>\n",
              "      <th>צכ</th>\n",
              "      <th>צף</th>\n",
              "      <th>ץ</th>\n",
              "      <th>ק</th>\n",
              "      <th>קי</th>\n",
              "      <th>קך</th>\n",
              "      <th>קץ</th>\n",
              "      <th>ר</th>\n",
              "      <th>רנ</th>\n",
              "      <th>רף</th>\n",
              "      <th>רק</th>\n",
              "      <th>שס</th>\n",
              "      <th>ת</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>top_kalpi</th>\n",
              "      <td>31.1000</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>0.1417</td>\n",
              "      <td>0.0054</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1117</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0109</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0191</td>\n",
              "      <td>0.0300</td>\n",
              "      <td>0.4523</td>\n",
              "      <td>0.0082</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0545</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0027</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0817</td>\n",
              "      <td>0.0681</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean_by_city</th>\n",
              "      <td>148.7635</td>\n",
              "      <td>0.0156</td>\n",
              "      <td>0.1158</td>\n",
              "      <td>0.0097</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1086</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0058</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0009</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0004</td>\n",
              "      <td>0.0296</td>\n",
              "      <td>0.0471</td>\n",
              "      <td>0.4639</td>\n",
              "      <td>0.0056</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0573</td>\n",
              "      <td>0.0002</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0039</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0685</td>\n",
              "      <td>0.0649</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 קלפי    אמת      ב      ג  ...     רף     רק     שס      ת\n",
              "top_kalpi     31.1000 0.0136 0.1417 0.0054  ... 0.0000 0.0000 0.0817 0.0681\n",
              "mean_by_city 148.7635 0.0156 0.1158 0.0097  ... 0.0001 0.0000 0.0685 0.0649\n",
              "\n",
              "[2 rows x 40 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-N1LP3lPNlB-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "48174340-5b7f-403f-8db1-a0f131ca07c2"
      },
      "source": [
        "results_b_2021"
      ],
      "execution_count": null,
      "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>SumSquared</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.6720</td>\n",
              "      <td>1.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.5973</td>\n",
              "      <td>1.2000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.5375</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>טבריה</th>\n",
              "      <td>0.5042</td>\n",
              "      <td>12.3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.4947</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מגדל העמק</th>\n",
              "      <td>0.4859</td>\n",
              "      <td>1.1000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נוף הגליל</th>\n",
              "      <td>0.4593</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>מעלותתרשיחא</th>\n",
              "      <td>0.4501</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עכו</th>\n",
              "      <td>0.4485</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>קרית גת</th>\n",
              "      <td>0.4350</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             SumSquared    קלפי\n",
              "שם ישוב                        \n",
              "נוף הגליל        0.6720  1.3000\n",
              "מעלותתרשיחא      0.5973  1.2000\n",
              "מעלותתרשיחא      0.5375  1.0000\n",
              "טבריה            0.5042 12.3000\n",
              "נוף הגליל        0.4947  1.0000\n",
              "מגדל העמק        0.4859  1.1000\n",
              "נוף הגליל        0.4593  1.0000\n",
              "מעלותתרשיחא      0.4501  1.0000\n",
              "עכו              0.4485  1.0000\n",
              "קרית גת          0.4350  1.0000"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QEqOiNyScYUs"
      },
      "source": [
        "The same here, we can see that the weights of the inverse covariance matrix did a real impact on the results."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wLd4muVKc9ot"
      },
      "source": [
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sgzx_o9y6nLx"
      },
      "source": [
        "##### c.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T5NoonFu6nLx"
      },
      "source": [
        "$\\sum_{i=1}^{C}\\sum_{b \\in ballot}^{B}\\sum_{j=1}^{K}(n_{bij}^{2020}-n_{bij}^{2021})^2$\n",
        "\n",
        "\n",
        "Sort by biggest"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f7uro_SmOOsK"
      },
      "source": [
        "cov_inv_2021 = pd.DataFrame(np.linalg.pinv(cov_2021.values), cov_2021.columns, cov_2021.index)\n",
        "\n",
        "\n",
        "def mahalanobisD(X,Y,cov_inv):\n",
        "    kalpi = []\n",
        "    city = []\n",
        "    m = []\n",
        "    for i in range(X.shape[0]):\n",
        "        kalpi.append(X.iloc[i,-1])\n",
        "        city.append(X.reset_index().loc[i,\"שם ישוב\"])\n",
        "        m.append(mahalanobis(X.iloc[i,:-1],Y.iloc[i,:-1],cov_inv))\n",
        "    \n",
        "    results = pd.DataFrame(zip(kalpi, city, m), columns=[\"קלפי\", \"שם ישוב\", \"d\"])\n",
        "    return(results)\n",
        "mD = mahalanobisD(df_2020_a,df_2021_a,cov_inv_2021)\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gMLXtBhCOdBX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "05a32df4-c119-42a3-fae4-a9babec346be"
      },
      "source": [
        "results_c_md = mD.set_index(\"שם ישוב\").sort_values(by=\"d\", ascending=False).iloc[:10,::-1]\n",
        "results_c_md"
      ],
      "execution_count": null,
      "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>d</th>\n",
              "      <th>קלפי</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שם ישוב</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>כדיתה</th>\n",
              "      <td>13.9224</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>נווה</th>\n",
              "      <td>13.8000</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אלוני יצחק</th>\n",
              "      <td>13.5210</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>בני נצרים</th>\n",
              "      <td>12.7089</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>שומריה</th>\n",
              "      <td>12.7061</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>כרם יבנה ישיבה</th>\n",
              "      <td>11.8919</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>אלון מורה</th>\n",
              "      <td>11.5087</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>משכיות</th>\n",
              "      <td>11.4288</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>פני חבר</th>\n",
              "      <td>11.0996</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>עגר</th>\n",
              "      <td>10.7358</td>\n",
              "      <td>3.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     d   קלפי\n",
              "שם ישוב                      \n",
              "כדיתה          13.9224 1.0000\n",
              "נווה           13.8000 1.0000\n",
              "אלוני יצחק     13.5210 1.0000\n",
              "בני נצרים      12.7089 1.0000\n",
              "שומריה         12.7061 1.0000\n",
              "כרם יבנה ישיבה 11.8919 1.0000\n",
              "אלון מורה      11.5087 1.0000\n",
              "משכיות         11.4288 1.0000\n",
              "פני חבר        11.0996 1.0000\n",
              "עגר            10.7358 3.0000"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Lx254jYtih2O",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 540
        },
        "outputId": "875f18e7-26ce-4f99-f271-cdc3888ec0ef"
      },
      "source": [
        "results_c_final_2021_md = plotPreProcessing_c(df_2021_a, results_c_md, ballot_2021_raw)\n",
        "results_c_final_2020_md = plotPreProcessing_c(df_2020_a, results_c_md, ballot_2020_raw)\n",
        "votes_percent_plt(results_c_final_2020_md, results_c_final_2021_md, \"Mahalanocis distance 2020 - 2021\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 10 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<Figure size 1440x720 with 10 Axes>,\n",
              " <matplotlib.axes._subplots.AxesSubplot at 0x7fac96696810>)"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wEORjjeejHyv"
      },
      "source": [
        "Here we can see an interesting pattern - the results of sum squared was not that informative because of the votes that moved to \"הבית היהודי\" and to \"עם\".\n",
        "Here we dont see Arab settelemnts at all, and we see that the same pattern with \"הבית היהודי\" is happening also here.\n",
        "But if we wil look at Kadita, Alonei Itzhak and Ajar - it looks like a whole different pattern.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OyRsVJEuOYja"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ],
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