Project proposal

project-proposal.ipynb

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      "name": "Project proposal",
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      "display_name": "Python 3",
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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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        "<a href=\"https://colab.research.google.com/gist/itamardavidyan/b378ba06afc857cdfbc68e302f775ba1/project-proposal.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nywd0PJ5dPKU"
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      "source": [
        "# Project Proposal\n",
        "\n",
        "At this project we, Itamar Davidyan (316463918) and Rotem Shai (204630115) decided to research the factors affecting happiness in world countries. For this goal we found dataset of the World Happiness Report and we got some more datasets from the UNdata website.\n",
        "\n",
        "<br>\n",
        "\n",
        "## Problem Description\n",
        "\n",
        "The world economy has been growing consistently for many years and the world's population is in a state of \"wealth\" in relation to the past - but there are many countries where significant sections of the population are not happy with their life in the country. The purpose of this project is to find the factors of the increase in the happiness score among populations in different countries, and thus allow countries to invest their resources in the same factors which will cause to raise the happiness score of the citizens of the country.\n",
        "\n",
        "<br>\n",
        "\n",
        "## Data Collection\n",
        "\n",
        "We collected our data from public websites:\n",
        "* [World Happiness Report (via Kaggle)](https://www.kaggle.com/mathurinache/world-happiness-report) - Kaggle is the world's largest data science community with powerful tools and resources and a wide variety of datasets. For this project we downloaded the dataset of the 'World Happiness Report - 2020'.\n",
        "\n",
        "  The yearly report is the product of a world-wide survey aimed to measure people's happiness by country.\n",
        "\n",
        "  The report includes an overall happiness score, and provides 6 parameters that might have a certain relation to the score:\n",
        "  1. GDP per capita\n",
        "  2. Healthy Life Expectancy\n",
        "  3. Social support\n",
        "  4. Freedom to make life choices\n",
        "  5. Generosity\n",
        "  6. Corruption Perception\n",
        "\n",
        "  According to [the report's official website](https://worldhappiness.report/), these parameters \"reflect what has been broadly found in the research literature to be important in explaining national-level differences in life evaluations\".\n",
        "\n",
        "  The report indcludes 153 countries.\n",
        "* [UNdata](http://data.un.org/Default.aspx) - an online data source, that includes data series from statistical databases provided by the UN System.\n",
        "\n",
        "  We retreived data from several databases provided by UNdata:\n",
        "  \n",
        "  - Labour force and unemployment\n",
        "  - Seats held by women in national parliament\n",
        "  - Population, surface area and density\n",
        "\n",
        "  Each database includes several data series. For this project we chose the following series, for each corresponding database:\n",
        "\n",
        "  - Unemployment rate - Total (%)\n",
        "  - Seats held by women in national parliament (%)\n",
        "  - Population aged 0 to 14 years old (%), Population aged 60+ years old (%)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hp2GleAmZWq1"
      },
      "source": [
        "Let's upload the Kaggle dataset:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mcRTjTGadaLx"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import os\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "import sklearn as skl\n",
        "from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score, r2_score\n",
        "from matplotlib import patches as mpatches"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 484
        },
        "id": "F8APtG5PdzH1",
        "outputId": "ebca911d-d4e9-49be-b911-db14db93d6e4"
      },
      "source": [
        "happiness_df = pd.read_csv('https://github.com/rotemsha/sadna_data/blob/main/2020.csv?raw=true',error_bad_lines=False)\n",
        "happiness_df = happiness_df.set_index('Country name')\n",
        "happiness_df = happiness_df.filter(items=['Regional indicator', 'Ladder score', \n",
        "                                          'Logged GDP per capita', 'Social support',\n",
        "                                          'Healthy life expectancy', 'Freedom to make life choices',\n",
        "                                          'Generosity', 'Perceptions of corruption']) # keep only relevant columns\n",
        "happiness_df = happiness_df.rename(columns={'Ladder score':'Happiness Score'})\n",
        "happiness_df"
      ],
      "execution_count": 2,
      "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",
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              "    }\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>Regional indicator</th>\n",
              "      <th>Happiness Score</th>\n",
              "      <th>Logged GDP per capita</th>\n",
              "      <th>Social support</th>\n",
              "      <th>Healthy life expectancy</th>\n",
              "      <th>Freedom to make life choices</th>\n",
              "      <th>Generosity</th>\n",
              "      <th>Perceptions of corruption</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Country name</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>Finland</th>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.8087</td>\n",
              "      <td>10.639267</td>\n",
              "      <td>0.954330</td>\n",
              "      <td>71.900825</td>\n",
              "      <td>0.949172</td>\n",
              "      <td>-0.059482</td>\n",
              "      <td>0.195445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Denmark</th>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.6456</td>\n",
              "      <td>10.774001</td>\n",
              "      <td>0.955991</td>\n",
              "      <td>72.402504</td>\n",
              "      <td>0.951444</td>\n",
              "      <td>0.066202</td>\n",
              "      <td>0.168489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Switzerland</th>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.5599</td>\n",
              "      <td>10.979933</td>\n",
              "      <td>0.942847</td>\n",
              "      <td>74.102448</td>\n",
              "      <td>0.921337</td>\n",
              "      <td>0.105911</td>\n",
              "      <td>0.303728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Iceland</th>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.5045</td>\n",
              "      <td>10.772559</td>\n",
              "      <td>0.974670</td>\n",
              "      <td>73.000000</td>\n",
              "      <td>0.948892</td>\n",
              "      <td>0.246944</td>\n",
              "      <td>0.711710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Norway</th>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.4880</td>\n",
              "      <td>11.087804</td>\n",
              "      <td>0.952487</td>\n",
              "      <td>73.200783</td>\n",
              "      <td>0.955750</td>\n",
              "      <td>0.134533</td>\n",
              "      <td>0.263218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Central African Republic</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.4759</td>\n",
              "      <td>6.625160</td>\n",
              "      <td>0.319460</td>\n",
              "      <td>45.200001</td>\n",
              "      <td>0.640881</td>\n",
              "      <td>0.082410</td>\n",
              "      <td>0.891807</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rwanda</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.3123</td>\n",
              "      <td>7.600104</td>\n",
              "      <td>0.540835</td>\n",
              "      <td>61.098846</td>\n",
              "      <td>0.900589</td>\n",
              "      <td>0.055484</td>\n",
              "      <td>0.183541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.2992</td>\n",
              "      <td>7.865712</td>\n",
              "      <td>0.763093</td>\n",
              "      <td>55.617260</td>\n",
              "      <td>0.711458</td>\n",
              "      <td>-0.072064</td>\n",
              "      <td>0.810237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>South Sudan</th>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>2.8166</td>\n",
              "      <td>7.425360</td>\n",
              "      <td>0.553707</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>0.451314</td>\n",
              "      <td>0.016519</td>\n",
              "      <td>0.763417</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Afghanistan</th>\n",
              "      <td>South Asia</td>\n",
              "      <td>2.5669</td>\n",
              "      <td>7.462861</td>\n",
              "      <td>0.470367</td>\n",
              "      <td>52.590000</td>\n",
              "      <td>0.396573</td>\n",
              "      <td>-0.096429</td>\n",
              "      <td>0.933687</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>153 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                          Regional indicator  ...  Perceptions of corruption\n",
              "Country name                                  ...                           \n",
              "Finland                       Western Europe  ...                   0.195445\n",
              "Denmark                       Western Europe  ...                   0.168489\n",
              "Switzerland                   Western Europe  ...                   0.303728\n",
              "Iceland                       Western Europe  ...                   0.711710\n",
              "Norway                        Western Europe  ...                   0.263218\n",
              "...                                      ...  ...                        ...\n",
              "Central African Republic  Sub-Saharan Africa  ...                   0.891807\n",
              "Rwanda                    Sub-Saharan Africa  ...                   0.183541\n",
              "Zimbabwe                  Sub-Saharan Africa  ...                   0.810237\n",
              "South Sudan               Sub-Saharan Africa  ...                   0.763417\n",
              "Afghanistan                       South Asia  ...                   0.933687\n",
              "\n",
              "[153 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cxcg_9Aa1ed6"
      },
      "source": [
        "Let's upload the UN datasets and perform some basic cleaning:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7630Aynb1hzo"
      },
      "source": [
        "labourforce_df = pd.read_csv('https://github.com/rotemsha/sadna_data/blob/main/un_laborforce.csv?raw=true',error_bad_lines=False)\n",
        "labourforce_df.columns = labourforce_df.iloc[0]\n",
        "labourforce_df.columns = labourforce_df.columns.fillna('Name')\n",
        "labourforce_df = labourforce_df.drop(labourforce_df.index[0])\n",
        "labourforce_df = labourforce_df[labourforce_df['Year'] == '2020'] # use only data from 2020\n",
        "labourforce_df = labourforce_df.loc[labourforce_df['Series'] == 'Unemployment rate - Total'] # use only total unemployment rate\n",
        "labourforce_df = labourforce_df.set_index('Name')\n",
        "labourforce_col_name = 'Unemployment rate (%)'\n",
        "\n",
        "labourforce_df = labourforce_df.rename(columns={'Value': labourforce_col_name})\n",
        "labourforce_df = labourforce_df.filter(items=[labourforce_col_name])"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yY-D7jj0Wd9C"
      },
      "source": [
        "We can now perform a similar process with the rest of the un data:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wuo5Jl3dRo-T"
      },
      "source": [
        "un_women_par_df = pd.read_csv('https://github.com/rotemsha/sadna_data/blob/main/un_women_parliament.csv?raw=true',error_bad_lines=False)\n",
        "un_women_par_df.columns = un_women_par_df.iloc[0]\n",
        "un_women_par_df.columns = un_women_par_df.columns.fillna('Name')\n",
        "un_women_par_df = un_women_par_df.drop(un_women_par_df.index[0])\n",
        "un_women_par_df = un_women_par_df[un_women_par_df['Year'] == '2020']\n",
        "un_women_par_df = un_women_par_df.set_index('Name')\n",
        "\n",
        "un_women_par_col_name = 'Seats held by women in national parliament (%)'\n",
        "un_women_par_df = un_women_par_df.rename(columns={'Value':\n",
        "                                                  un_women_par_col_name})\n",
        "un_women_par_df = un_women_par_df.filter(items=[un_women_par_col_name])\n",
        "un_women_par_df[un_women_par_col_name] = pd.to_numeric(un_women_par_df[un_women_par_col_name])\n"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b7FGjp-yU5Nk"
      },
      "source": [
        "un_population_df = pd.read_csv('https://github.com/rotemsha/sadna_data/blob/main/un_population.csv?raw=true',error_bad_lines=False)\n",
        "un_population_df.columns = un_population_df.iloc[0]\n",
        "un_population_df.columns = un_population_df.columns.fillna('Name')\n",
        "un_population_df = un_population_df.drop(un_population_df.index[0])\n",
        "un_population_df = un_population_df[un_population_df['Year'] == '2020']\n",
        "un_population_df = un_population_df.set_index('Name')\n",
        "\n",
        "un_population_kids_col_name = 'Population aged 0 to 14 years old (percentage)'\n",
        "un_population_df_kids = un_population_df.loc[un_population_df['Series'] == un_population_kids_col_name]\n",
        "un_population_df_kids = un_population_df_kids.rename(columns={'Value':\n",
        "                                                  un_population_kids_col_name})\n",
        "un_population_df_kids = un_population_df_kids.filter(items=[un_population_kids_col_name])\n",
        "un_population_df_kids[un_population_kids_col_name] = pd.to_numeric(un_population_df_kids[un_population_kids_col_name])\n",
        "un_population_df_kids = un_population_df_kids.rename(columns={un_population_kids_col_name: un_population_kids_col_name.replace('percentage', '%')})\n",
        "\n",
        "un_population_old_col_name = 'Population aged 60+ years old (percentage)'\n",
        "un_population_df_old = un_population_df.loc[un_population_df['Series'] == un_population_old_col_name]\n",
        "un_population_df_old = un_population_df_old.rename(columns={'Value':\n",
        "                                                  un_population_old_col_name})\n",
        "un_population_df_old = un_population_df_old.filter(items=[un_population_old_col_name])\n",
        "un_population_df_old = un_population_df_old.rename(columns={un_population_old_col_name: un_population_old_col_name.replace('percentage', '%')})\n",
        "\n",
        "old_population_col_name = 'Population aged 60+ years old (%)'\n",
        "un_population_df_old[old_population_col_name] = pd.to_numeric(un_population_df_old[old_population_col_name])\n"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jn0kmL9r6zl1"
      },
      "source": [
        "Notice that un-DataFrames contains different countries regions than happiness_df.\n",
        "\n",
        "We would want to merge the dfs, so we'll see what is the symetric difference between the lists:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S7w-5E067T0l",
        "outputId": "b7a781e9-205e-4079-bb2b-57126a73fc59"
      },
      "source": [
        "def handle_countries_diff(main_df, secondary_df):\n",
        "  main_countries = set(main_df.index.tolist())\n",
        "  secondary_countries_list = secondary_df.index.tolist()\n",
        "  secondary_countries = set(secondary_countries_list)\n",
        "  missing_in_main = main_countries - secondary_countries\n",
        "  # print(f'missing in main df: {missing_in_main}')\n",
        "  missing_in_secondary = secondary_countries - main_countries\n",
        "  # print(f'missing in secondary df: {missing_in_secondary}')\n",
        "  return missing_in_main, missing_in_secondary\n",
        "\n",
        "missing_in_kaggle_data, missing_in_labour_data = \\\n",
        " handle_countries_diff(happiness_df, labourforce_df)\n",
        "missing_in_kaggle_data"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Bolivia',\n",
              " 'Congo (Brazzaville)',\n",
              " 'Congo (Kinshasa)',\n",
              " 'Czech Republic',\n",
              " 'Hong Kong S.A.R. of China',\n",
              " 'Iran',\n",
              " 'Ivory Coast',\n",
              " 'Kosovo',\n",
              " 'Laos',\n",
              " 'Macedonia',\n",
              " 'Moldova',\n",
              " 'North Cyprus',\n",
              " 'Palestinian Territories',\n",
              " 'Russia',\n",
              " 'South Korea',\n",
              " 'Swaziland',\n",
              " 'Taiwan Province of China',\n",
              " 'Tanzania',\n",
              " 'United States',\n",
              " 'Venezuela',\n",
              " 'Vietnam'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wqgNSR9zEI6m",
        "outputId": "46ca15a4-6a04-49f9-b5d7-bbeeac892bd1"
      },
      "source": [
        "missing_in_labour_data"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Africa',\n",
              " 'Americas',\n",
              " 'Angola',\n",
              " 'Bahamas',\n",
              " 'Barbados',\n",
              " 'Belize',\n",
              " 'Bhutan',\n",
              " 'Bolivia (Plurin. State of)',\n",
              " 'Brunei Darussalam',\n",
              " 'Cabo Verde',\n",
              " 'Caribbean',\n",
              " 'Caucasus',\n",
              " 'Central America',\n",
              " 'Central Asia',\n",
              " 'Channel Islands',\n",
              " 'China, Hong Kong SAR',\n",
              " 'China, Macao SAR',\n",
              " 'Congo',\n",
              " 'Cuba',\n",
              " 'Czechia',\n",
              " 'Côte d’Ivoire',\n",
              " \"Dem. People's Rep. Korea\",\n",
              " 'Dem. Rep. of the Congo',\n",
              " 'Djibouti',\n",
              " 'Eastern Africa',\n",
              " 'Eastern Asia',\n",
              " 'Eastern Europe',\n",
              " 'Equatorial Guinea',\n",
              " 'Eritrea',\n",
              " 'Eswatini',\n",
              " 'European Union (EU)',\n",
              " 'Fiji',\n",
              " 'French Polynesia',\n",
              " 'Guam',\n",
              " 'Guinea-Bissau',\n",
              " 'Guyana',\n",
              " 'Iran (Islamic Republic of)',\n",
              " \"Lao People's Dem. Rep.\",\n",
              " 'Latin America & the Caribbean',\n",
              " 'Middle Africa',\n",
              " 'New Caledonia',\n",
              " 'North Macedonia',\n",
              " 'Northern Africa',\n",
              " 'Northern America',\n",
              " 'Oceania',\n",
              " 'Oman',\n",
              " 'Papua New Guinea',\n",
              " 'Puerto Rico',\n",
              " 'Qatar',\n",
              " 'Republic of Korea',\n",
              " 'Republic of Moldova',\n",
              " 'Russian Federation',\n",
              " 'Saint Lucia',\n",
              " 'Saint Vincent & Grenadines',\n",
              " 'Samoa',\n",
              " 'Sao Tome and Principe',\n",
              " 'Solomon Islands',\n",
              " 'Somalia',\n",
              " 'South America',\n",
              " 'South-eastern Asia',\n",
              " 'Southern Africa',\n",
              " 'Southern Asia',\n",
              " 'Southern Europe',\n",
              " 'State of Palestine',\n",
              " 'Sub-Saharan Africa',\n",
              " 'Sudan',\n",
              " 'Suriname',\n",
              " 'Syrian Arab Republic',\n",
              " 'Timor-Leste',\n",
              " 'Tonga',\n",
              " 'Total, all countries or areas',\n",
              " 'United Rep. of Tanzania',\n",
              " 'United States Virgin Islands',\n",
              " 'United States of America',\n",
              " 'Vanuatu',\n",
              " 'Venezuela (Boliv. Rep. of)',\n",
              " 'Viet Nam',\n",
              " 'Western Africa',\n",
              " 'Western Asia',\n",
              " 'Western Europe',\n",
              " 'Western Sahara'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "umbD-ajpCm2Y"
      },
      "source": [
        "We can see that some of the differences are a result of slightly different \n",
        "names.\n",
        "Since not much data is missing in the UN database, we'll update it manually:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HUNReaUpC3uR"
      },
      "source": [
        "updated_names = {'Bolivia (Plurin. State of)': 'Bolivia',\n",
        "                 'Czechia': 'Czech Republic',\n",
        "                 'China, Hong Kong SAR': 'Hong Kong S.A.R. of China',\n",
        "                 'Iran (Islamic Republic of)': 'Iran',\n",
        "                 'Côte d’Ivoire': 'Ivory Coast',\n",
        "                 \"Lao People's Dem. Rep.\": 'Laos',\n",
        "                 'North Macedonia': 'Macedonia',\n",
        "                 'Republic of Moldova': 'Moldova',\n",
        "                 'Russian Federation': 'Russia',\n",
        "                 'South Korea': 'Republic of Korea',\n",
        "                 'Eswatini': 'Swaziland',\n",
        "                 'United Rep. of Tanzania': 'Tanzania',\n",
        "                 'United States of America': 'United States',\n",
        "                 'Venezuela (Boliv. Rep. of)' :'Venezuela',\n",
        "                 'Viet Nam': 'Vietnam',\n",
        "                 'Republic of Korea': 'South Korea',\n",
        "                 'State of Palestine': 'Palestinian Territories'}\n",
        "labourforce_df = labourforce_df.rename(index=updated_names)\n"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5ByMflps8QsH"
      },
      "source": [
        "Let's see the countries that remains lost:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mBcpwoJxJMlC",
        "outputId": "0edc0fa6-9b01-4e5c-bf29-c3e0479c8815"
      },
      "source": [
        "missing_in_kaggle_data, _ = handle_countries_diff(happiness_df, labourforce_df)\n",
        "missing_in_kaggle_data"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Congo (Brazzaville)',\n",
              " 'Congo (Kinshasa)',\n",
              " 'Kosovo',\n",
              " 'North Cyprus',\n",
              " 'Taiwan Province of China'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5i1wrrJkE53X"
      },
      "source": [
        "We'll rename the index in the rest of the UN DataFrames as well:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MHF7Mox0FAWQ"
      },
      "source": [
        "un_women_par_df = un_women_par_df.rename(index=updated_names)\n",
        "un_population_df_kids = un_population_df_kids.rename(index=updated_names)\n",
        "un_population_df_old = un_population_df_old.rename(index=updated_names)\n",
        "un_women_par_df = un_women_par_df.rename(index=updated_names)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U6kTjFXe9SEh"
      },
      "source": [
        "Yay! we can now merge the Dataframe to a one big happy DataFrame.\n",
        "\n",
        "We'll do so with in 'inner' merge so we don't get null values. We'll do the merge and check how much data is lost from the original DataFrame:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        },
        "id": "nfB7uftT9ON7",
        "outputId": "121b5872-0a56-4df8-cbd5-ac58e31391d7"
      },
      "source": [
        "print(f'size of original df is: {len(happiness_df)}')\n",
        "df = happiness_df.merge(labourforce_df, how='inner', left_index=True, right_index=True)\n",
        "df = df.merge(un_women_par_df, how='inner', left_index=True, right_index=True)\n",
        "df = df.merge(un_population_df_kids, how='inner', left_index=True, right_index=True)\n",
        "df = df.merge(un_population_df_old, how='inner', left_index=True, right_index=True)\n",
        "df = df.rename_axis('Name').reset_index()\n",
        "print(f'size of merged df is: {len(df)}')\n",
        "df"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "size of original df is: 153\n",
            "size of merged df is: 145\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Regional indicator</th>\n",
              "      <th>Happiness Score</th>\n",
              "      <th>Logged GDP per capita</th>\n",
              "      <th>Social support</th>\n",
              "      <th>Healthy life expectancy</th>\n",
              "      <th>Freedom to make life choices</th>\n",
              "      <th>Generosity</th>\n",
              "      <th>Perceptions of corruption</th>\n",
              "      <th>Unemployment rate (%)</th>\n",
              "      <th>Seats held by women in national parliament (%)</th>\n",
              "      <th>Population aged 0 to 14 years old (%)</th>\n",
              "      <th>Population aged 60+ years old (%)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Finland</td>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.8087</td>\n",
              "      <td>10.639267</td>\n",
              "      <td>0.954330</td>\n",
              "      <td>71.900825</td>\n",
              "      <td>0.949172</td>\n",
              "      <td>-0.059482</td>\n",
              "      <td>0.195445</td>\n",
              "      <td>6.6600</td>\n",
              "      <td>46.00</td>\n",
              "      <td>15.8651</td>\n",
              "      <td>28.9914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Denmark</td>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.6456</td>\n",
              "      <td>10.774001</td>\n",
              "      <td>0.955991</td>\n",
              "      <td>72.402504</td>\n",
              "      <td>0.951444</td>\n",
              "      <td>0.066202</td>\n",
              "      <td>0.168489</td>\n",
              "      <td>4.8500</td>\n",
              "      <td>39.66</td>\n",
              "      <td>16.2817</td>\n",
              "      <td>26.1324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Switzerland</td>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.5599</td>\n",
              "      <td>10.979933</td>\n",
              "      <td>0.942847</td>\n",
              "      <td>74.102448</td>\n",
              "      <td>0.921337</td>\n",
              "      <td>0.105911</td>\n",
              "      <td>0.303728</td>\n",
              "      <td>4.8500</td>\n",
              "      <td>41.50</td>\n",
              "      <td>14.9586</td>\n",
              "      <td>25.2887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Iceland</td>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.5045</td>\n",
              "      <td>10.772559</td>\n",
              "      <td>0.974670</td>\n",
              "      <td>73.000000</td>\n",
              "      <td>0.948892</td>\n",
              "      <td>0.246944</td>\n",
              "      <td>0.711710</td>\n",
              "      <td>3.2200</td>\n",
              "      <td>38.10</td>\n",
              "      <td>19.4243</td>\n",
              "      <td>21.6034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Norway</td>\n",
              "      <td>Western Europe</td>\n",
              "      <td>7.4880</td>\n",
              "      <td>11.087804</td>\n",
              "      <td>0.952487</td>\n",
              "      <td>73.200783</td>\n",
              "      <td>0.955750</td>\n",
              "      <td>0.134533</td>\n",
              "      <td>0.263218</td>\n",
              "      <td>3.3100</td>\n",
              "      <td>41.42</td>\n",
              "      <td>17.2571</td>\n",
              "      <td>23.2666</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>Central African Republic</td>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.4759</td>\n",
              "      <td>6.625160</td>\n",
              "      <td>0.319460</td>\n",
              "      <td>45.200001</td>\n",
              "      <td>0.640881</td>\n",
              "      <td>0.082410</td>\n",
              "      <td>0.891807</td>\n",
              "      <td>3.7000</td>\n",
              "      <td>8.57</td>\n",
              "      <td>43.5417</td>\n",
              "      <td>4.4743</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>Rwanda</td>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.3123</td>\n",
              "      <td>7.600104</td>\n",
              "      <td>0.540835</td>\n",
              "      <td>61.098846</td>\n",
              "      <td>0.900589</td>\n",
              "      <td>0.055484</td>\n",
              "      <td>0.183541</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>61.25</td>\n",
              "      <td>39.4742</td>\n",
              "      <td>5.1208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>3.2992</td>\n",
              "      <td>7.865712</td>\n",
              "      <td>0.763093</td>\n",
              "      <td>55.617260</td>\n",
              "      <td>0.711458</td>\n",
              "      <td>-0.072064</td>\n",
              "      <td>0.810237</td>\n",
              "      <td>4.9900</td>\n",
              "      <td>31.85</td>\n",
              "      <td>41.9111</td>\n",
              "      <td>4.6319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>South Sudan</td>\n",
              "      <td>Sub-Saharan Africa</td>\n",
              "      <td>2.8166</td>\n",
              "      <td>7.425360</td>\n",
              "      <td>0.553707</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>0.451314</td>\n",
              "      <td>0.016519</td>\n",
              "      <td>0.763417</td>\n",
              "      <td>12.2600</td>\n",
              "      <td>28.46</td>\n",
              "      <td>41.3278</td>\n",
              "      <td>5.1518</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>South Asia</td>\n",
              "      <td>2.5669</td>\n",
              "      <td>7.462861</td>\n",
              "      <td>0.470367</td>\n",
              "      <td>52.590000</td>\n",
              "      <td>0.396573</td>\n",
              "      <td>-0.096429</td>\n",
              "      <td>0.933687</td>\n",
              "      <td>11.1600</td>\n",
              "      <td>27.02</td>\n",
              "      <td>41.8226</td>\n",
              "      <td>4.2228</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>145 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                         Name  ... Population aged 60+ years old (%)\n",
              "0                     Finland  ...                           28.9914\n",
              "1                     Denmark  ...                           26.1324\n",
              "2                 Switzerland  ...                           25.2887\n",
              "3                     Iceland  ...                           21.6034\n",
              "4                      Norway  ...                           23.2666\n",
              "..                        ...  ...                               ...\n",
              "140  Central African Republic  ...                            4.4743\n",
              "141                    Rwanda  ...                            5.1208\n",
              "142                  Zimbabwe  ...                            4.6319\n",
              "143               South Sudan  ...                            5.1518\n",
              "144               Afghanistan  ...                            4.2228\n",
              "\n",
              "[145 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "btuefp6ljUSR"
      },
      "source": [
        "We lost 8 countries. It's a bummer, but we can live with it.\n",
        "\n",
        "We can also see that there are no null values in the table:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VIhSnYpbjIai",
        "outputId": "6ce56d24-dc2c-4511-9ec8-600f0f92a665"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name                                              0\n",
              "Regional indicator                                0\n",
              "Happiness Score                                   0\n",
              "Logged GDP per capita                             0\n",
              "Social support                                    0\n",
              "Healthy life expectancy                           0\n",
              "Freedom to make life choices                      0\n",
              "Generosity                                        0\n",
              "Perceptions of corruption                         0\n",
              "Unemployment rate (%)                             0\n",
              "Seats held by women in national parliament (%)    0\n",
              "Population aged 0 to 14 years old (%)             0\n",
              "Population aged 60+ years old (%)                 0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "50bFkVgIIlIZ"
      },
      "source": [
        "## Initial Data Analysis\n",
        "\n",
        "Let's perform some basic analysis of our data.\n",
        "\n",
        "We'll start by looking at the happiest countries and regions.\n",
        "\n",
        "In all plots, we'll dedicate a different color for each region.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pIXGJGnnLNXO"
      },
      "source": [
        "def get_regions_colors(df):\n",
        "  import matplotlib.colors as mcolors\n",
        "  colors = list(mcolors.TABLEAU_COLORS.keys())\n",
        "  regions = list(df['Regional indicator'].unique())\n",
        "  zip_iterator = zip(regions, colors)\n",
        "  region_colors = dict(zip_iterator)\n",
        "  return region_colors\n",
        "\n",
        "\n",
        "def show_plot(df):\n",
        "  region_colors = get_regions_colors(df)\n",
        "  x = 'Name' if 'Name' in df else 'Regional indicator'\n",
        "  df.plot(kind='barh', x=x, y='Happiness Score',\n",
        "                  figsize=(15,7),\n",
        "                  color=[region_colors[i] for i in df['Regional indicator']])\n",
        "\n",
        "  handles = [mpatches.Patch(color=region_colors[i]) for i in region_colors]\n",
        "  region_labels = [i for i in region_colors]\n",
        "  plt.legend(handles, region_labels)\n",
        "  for index, value in enumerate(df['Happiness Score']):\n",
        "      plt.text(value, index, f'{value:.02f}')"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "uEEk74lzKtuU",
        "outputId": "df8ac588-f050-4e05-9a31-6148cacce5e9"
      },
      "source": [
        "happiest = df.nlargest(10, 'Happiness Score')\n",
        "happiest = happiest.sort_values(by=['Happiness Score'])\n",
        "show_plot(happiest)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KhtlMKjdLXzL"
      },
      "source": [
        "10 unhappiest countries:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "VMQhR6LJLfHl",
        "outputId": "43a91b59-7145-4a9b-a533-3c7e656a096f"
      },
      "source": [
        "unhappiest = df.nsmallest(10, 'Happiness Score')\n",
        "unhappiest = unhappiest.sort_values(by=['Happiness Score'])\n",
        "show_plot(unhappiest)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ncAGHO-Sds9R"
      },
      "source": [
        "Let's look at the happiest\\unhappiest regions:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qqnNpnM2spTc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 794
        },
        "outputId": "d2d710e4-7938-4991-bcc4-657d8ec59b1b"
      },
      "source": [
        "sns.set(rc={'figure.figsize':(12,9)})\n",
        "data = pd.melt(df, id_vars='Regional indicator', value_vars='Happiness Score', value_name='Happiness-Score')\n",
        "sns.violinplot(x=\"Regional indicator\", y=\"Happiness-Score\", data=data, split=True, inner=\"quart\")\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),\n",
              " <a list of 10 Text major ticklabel objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ghJCoodDsa5xSZX22KEjhDU2PPXYMn/3s3Thx4nFkYwpecukIrj2YgCoH11MsMYYrJuN4ykQMJ9fr+NbZEu6661P48pfuxa0veyVuuumX9kXbBg+Hkh+aRQ+Llr+RRxhfB8PGHwPRnxOEEBI1FJp9/FQqQ7+Bkm25fxisr+fw93////D97/8nMjEFt1zmhWVFCs8EPMYYLhmL4YmjOk7nDXz9dBGf+tTH8fUHv4rf+u3X49JLnxT0EHe0vadZ7D5WHhBFfxwAeiwIISSqKDT7XNcPvf2u7MDCFZofeuj7+MQn7oRRq+J5F6Xx7KNJaHJ4K7eMMVw8quP1WQ2PrNTwtVML+MAH3ocXvehW3Hbb7ZDlvZucuJcaPc0qhWaguT1D7McBoFYVQgiJKgrN58tfVioMy6g9+OBXcdddf4fDGQ2vfNpkzxuThAFjDE89EMelYzq+erKAL33pXszPz+Itb/n9xgYiYdKoNFNPMwDANLz2DNux4TjOvmixGRQKzYQQEk3ifrK1YMx/KHa9uGqwofnRR3+Gu+76Ozx5Iob/fs34vgrMzXRFwq1PyuKFl2TwX//1EL7whc8GPaS2WtszRA9Iht/TDACGYexwy+ij0EwIIdG0P5PVAMh+C4OLfkOz498/2DaCL33xHsgMqJgO/t9P1nDTBSlcOh4DACwUTXzlxEbjtrc/ZRRp3Rvvfy1U8KPFCgAgpUn49SvGGrf7yuMbWCh5H/yXjum46cJ043uf+NFq49+D+l3zRRMP3P9l3HLLbYjFYuf7EO0p3oYgUU8zAC8gygBseKE5bP9fw8QPGgwj3MtQEkII6Q+FZp8s+w+F22dvshOO0LywMA8XwKIfPL92soB/O+dt7Z3ROp9QOLtRb4RVWWJbwnBG7/w38fsM8nc9cVTHj5eqyOVWcejQkY4/NwiNdgxFApjYVUXHcWBaFpKShLLjwDRFrzQb/ldxnxOEEBJFFJp9jb5Zt79NKvgEwqA36Dhy9AJs5HOYSiqQWvqrk5qMVzZVdZtdOKIjV23/N994NIXpdPu/azrV/vq9/F3H12rQdR0TEwfa3idIjYmAEgOTJKErzTwcxpmEMpzQb/QzaFRp3vTDH/4AH//4X+Otb30nrrzy6qCHQwgh54VCs0+SJMiyAtfpc2c31wtLQW/Mccstt+GnP/0JEqqMX79itOfl5a6bTuC66UTfv+93r53o+z79/K7/mCnhkZUaXvayVwb+2LbT6GmWGCSZCT0RkFdWY5IE2BQW+d8vem83ADz++GOo1WqYmTlLoZkQsu/RRMAmqqbBdfqrGPKQrWn6IIbUs0svfRJe+9rfwfG1Gj79cA4lY39u62w7Lu4/uYGvnizg+uuejpe85GVBD6mtRkiWvUqzyKfieWU57p/hED0s1ut+pbku9uPQzN31BGtCCAkPCs1NYnoM6Ds0e2EpDBOfnv/8m/E//sdbMVuy8dEfruHna7Wgh9SXtYqFT/5kDd+eKeN5z/tlvOWtvx94r3gnze0ZkJnQ7Rm1mvc8i/vLzPHLouLL7xmC93Y3C8s69oSQ8KpWqzh16kSoD7KpPaNJLB5HudxfxZBXpsMQmgHgWc96Do4cuQD/986/wmd+OoeUKmEsLkNiLNQrajx5IoavnylBUTW88Y2/h2c+89l7+rjstUZIlhmYxASvNHshOSHJ/mXB2zNM6mnm+Iefbe/PM1+EkOH51Kc+ju997z/w/vf/OS688KKgh9MWheYmyUQCi0tnUDz14LbvyfFRJKaftu161/Y+IBOJ5MDH16sLLrgQf/z+P8d9930eX/ziPahYDsbjyi6W0xu8jbqN+ZKJMxsGrr76Wvz2b78BY2PtJxKGSXNPMySxe5p5ZTnZqDRXgxxO4HhYdhwHlmWFcnOeYeEVZpHPxBBCenPq1EkAQLVaCXgknYn7bt5GMpkE+gyWru2vHBDvfzLdIKmqile84jfw9Kf/Aj75yf+LM2dO4wfzVUynNKR1GdNpteNkvp0m7L3w0pGOv7PTz2v3uyzHxb+eLeLfzpWRTCbxu699HW644Vmh2FmxF40QwABIYocCHpIpNHvPA8dxIMsabNuAYRhCh2bbtrZ8JYSQbtx+l/4dInHfzdtIJpNQ1DhSF/9yz/dxbQNgDIlEuEIzd+GFF+F97/sA7r//K/jC5/8R/+eHq7j1shFcPhFcO8laxcJnj+UxXzTwzGfeiNe85reRSqW73zFETNMEkyUv5Etir8lbrfJKs+xfFjc080mQmhJD1Q/NYX1vGAZ+MMnnABBCSDeOE76z4hyF5ibJZAqO3V8fomvXEY/FIUnhnVMpyzJe+MKX4JprrsWdd/5v3P2zs7jpghSe/4T0tjWdB+2x1Ro+dzwPRYvhbW97G572tGcM9ffvFcsywWT/sZMYTIHbM/iptLgkQWZM6NDM+7tVJYZqvdC4LCp+MCnymRhCSH/CPHE4vEkvAMlkCo5l9HVqwLXrSCZTAxzV3jl06Aje+94/xU03PQ//dq6ELxzPwx7iEd1/LVRw9yM5TB++AH/ypx/et4EZ8CpnzD9QYrLYEwErlTIAQGcMuiSHuh9t0HilWVXiAGhSJA/LIvf8E0L6I/zqGbOzs3jLW97SuFwsFlEqlfD9739/GL++Z+m01yLg2gaY0lv7gmvVkRnPDHJYe0rTNLzudW/AxMQEvvCFz0KTGF5y2cjAe4kfWani3sfyuOKKK/F7b38XdD0cq43s1rZKs8ChuVqtQGEMMmPQJdYI0SJqrjQDtILGZqVZ3NcHIaQ/Ya40DyU0HzlyBPfdd1/j8gc+8IFQLkGUSnnh17XqQI+hGY6BdHr/hGYAYIzhpS99Oer1Or785ftwdETDtQcH13e5VrHwheMbuPiJl+Dt73h3KHf465dlmY0DDSaJvU5zqVRCzF9PWwNQLoscmr2QzEMztWcY/lcKzYSQ3oQ5NA+9PcMwDHzxi1/Ey1/+8mH/6q4yGV5p7v2DzrXrjQr1fvOKV/wGLrv0Mnz1ZBFVc3BP0q+c2ICsanjrW98ZicAM+BOb+L4rgi85Vy6XoPsHEDEwFIuFgEcUnO2hWexKM29XEX2XSEJI7yg0N/nmN7+JqakpXHHFFcP+1V2l095yao7V2wed67pwrBoymf1VaeYkScJrXvs6VE0b358fTHVwrmjg57k6XnLLbRgbGx/I7wiCZZmA5FeaBe9pLpVK4JvIxyQJpWIx0PEEia9ZrarU0ww07Y5IoZkQ0pXXy0xLzjX5/Oc/v6sq8/j44CfbyfIhAIBr9Vhpdiy4jo1Dh6YwObk/q82Tk1fhmmuuxkOPPYLnXJDa89U0HpqvQNc03H77bZFaekuS4K3RDK89w3HsffscOF+VchFx5h1/x5iEcrkk7GOh696Tgk8EVFUI+1gAgO2vY+/YptCPAyGkO1n2PkeSSS207xdDDc1LS0v4wQ9+gDvuuKPv+66tlQa+dp9te/9hTo+h2bG8pbUY07Cysn+ra894xnPw4x//BDMFAxeO6N3v0CPLcfHIah3XPe2ZKJdtlMv79zFqVS5XG5VmSAymYe7r58D5WF9fx0X+SiJxSUKtUsHc3FpkWnH6sbKSBwBofqV5dTUv7PMCACr+8oPlSlXox4EQ0p1texXmjY1KYO8XksR2LNIOtT3jnnvuwXOf+1yMjo4O89f2TJZlJBKpnnuaeUV6ZKTzLnn7wXXXXQ9FUfCz5b2dtHRyvY6qaeOGG561pz83DEzLbLx6RJ4IaNs2yuVKo9Kc8MNzobAR5LACw9szNL/SLPKa1QBg1L22DNEnRBJCekc9zb577rknlBMAm2UymZ7bM3hFOpPZ36E5Hk/gmmuux09XarD2sJr/48UKkokErrzy6j37mWFhWdaWJeds2w712pKDUihswIXbCMv868ZGPshhBYZvIS7LGiRJFr6nue4vucfDMyGEdBPG1dW4oYbm+++/HzfddNMwf2Xfstlsz6GZV6T3e2gGgF/8xeejbNj46fLeVMY2ajYeXa3jxuf8EhQlehtPWpYJ1jQREAj3C31Q8nkvHCdbQvP6+npgYwpSrVaDLKtgjEGRtUaIFpHruo0JgHXB16sGvMdD1DMwhPSDKs37SCYzAjg9rp7hr7Kx39ZpbuepT70KR49cgG+dLe9JtflbZ4tgkoRf+ZVf24PRhY9pWlt6mgExtwre2PDCcULy1t/j4TmfFzM0V6sVKLLXyy3LqtCh2TTNxtkXwzCEPBPT7Gtf+xLe9rY34Mc//mHQQyEklPg7RJgLUBSaW4yMjPQ1ETCeSEaiksoYwytv/03kqia+M1M6r581VzDww4UKnv/8X8HExOQejTBctlSaJX6deKF5bW0NAJDilWYmQWIMudxakMMKTLVahSKrAABZUoXuaeb93boqw3VdoZdlBIDZ2RkAwPp6LuCREBJOfO0uqjTvI5nMCBzLgOt0P9JxrTpGItCawV199bV42tOegX85W8JiaXcfcKbt4guPbSCbzeJlL7t9j0cYHrZtb67TLPH2DPFCcy63BomxRlsGYwwpWRE4NFcgSZuhuVKpBDyi4PDJf5riPTdErro3E/HgmpBe8Eqz00P+CgqF5ha8P7mXvmbXru37lTNa/dZvvR6pVBqfPZZH3er/aO8rJzawXDbxu//9zZFal7mVbVuNsCxye0Yut4aULG9Z3zvFgLW11QBHFZxKpQJZ4u0ZmtBbivMqu67KWy6LTsT3CUL6Qe0Z+wjf3c+xe+hrtuuRmATYLJPJ4I1vejtWKxbufSzfVx/iDxcqeGihghe/+NZIrpjRzLK2V5pF/DBcWV5CqmVDnLQkY2V5KaARBatUKjV6mhVZR6UibmjmlWUemqnS7BHxfYKQXvC8QaF5H9msNHd/g9/PW2jv5ClPeSpe+cpX4WcrNXxnprcP/dmCgS8+voErnvJUvPzlvz7gEQavXaVZxPaMleUlZPxJgFxGkpHP54UMB5VKuSk0U6UZAGKqsuWyqHifpui93YR0Qz3N+whfCYOvjNGJ6zpwrHokVs5o54UvvAVPe9oNeOB0AafWd34syoaNf3w0j9HRMbz5Le+AJEX/aWVb9pbNTQDxKkiGYSBf2EBGbgnNsgwXLlZXVwIaWTAcx0G5XIKqxAAAqqLDMOrChqTWSrPooZk/D0yT1qwmpB2qNO9DvbZn8FAdxUoz4E3oev3r34zpg4fw2WN5FOvtn8SO6+Lzx/MoW8Dbfu9dSKXCuV/8XnIcB67rgvG2BP+LaKF52W/ByLaEZn55aWlx6GMKUrVageu6UBRvK3rFD8/FopjbR/NJkDGNh2ZxJ0UCm6GZr11NCNmKh+Uwf5ZSaG4Ri8Uhy0rXiYBR2tikk1gshre89Z0wHNaxv/l7c2U8nqvjN3/zt3DRRRcHMMrha7yg5db2jPAeHQ8CD8Uj0tYlF0f80Ly8LFZoLhQKANBUaeahuRDYmILE+7l5e4bIK4kAgMF3R6TQjJWVZXz605+gx4JswT9DqT1jH2GMIZlKdW3PcPzvR72yeuTIUdz+66/Bz3N1PNyyW2C+ZuHB0yVcdeXVeN7zfjmgEQ4ff2HzSrOo7RmLi/MAtlea40yCJklYXFwIYliB4eG4NTSLugtctVoFY5vtGSJPigQAo06hmbvnns/hG994AMeOPRL0UEiI8M/WMM8PotDcRjqV7t6eYYsRmgHgBS+4GRdd9AQ8cKoE096sNj9wqghIMn77d96w2aoggEZFedtEQLEqzYuLC0jKCvSWHnbGGEZlGQvzcwGNLBgbG96W4pqa2PKVXy+aSqUMVVEgSwyyJAnfnlH3QzP/KrJSydtAy3XDW1Ekw7cZmsP7WUqhuY10JgP02NOcTkc/NEuShFe96r+hULfw0IJXLVopm/jZchU33/wijI9PBDzC4WocBfOJgEzM0Dw/P4tsh0mfWUnG/PzskEcULL51uKrEAQCa/1XU0Fwul6HI3vNDVSShVxIBNjd74V8JIPjO6qSF43+2hvmsLYXmNtKpFODsfAqNV5qTydQwhhS4yy9/Cp74xEtw/8kCHlmp4gvH85AVBTff/KKghzZ0re0Z/FUU5lNKe811XczPzW1rzeBGZQXr+bxQ1cX19XVITG60ZciyCkXRhN02uVwuw98MEIpMoWOkyIEAACAASURBVLlWq/tfKTRzAp2gJD2gSvM+lUym4NrdQrMBTdOhquqQRhW8F7zgV2G7wD8+so7ZoomnP/0XIrt6yE5a2zOYgO0Z+fw6KtUKxmSl7ffH/DA9NydOtTmXW4WuJ7e0KulqUtgtxcvlIhT/tSFLDOVyKeARBatW9+aE1ARfes9DJWayFV+VCgh3Aar9J57gUqk0bKu+dVmxFo5tIJlIDnlkwXrmM2/ERRdd3Dh1cvDgdMAjCgZ/QTN+yClgewZvvRjvFJoVxb/dHC655LKhjStIq6ur0JStW8drahIrK2KtV82VSiWofqlZlcUOzY7jNCYA0s6IhGzX3JJhmhSa95VkMgW4DuBYgNy+kuzadaSy0e9nbsYYw6FDh4MeRuAsyw/H29ozxAnNs7MzADbDcauMJENhUuN2IlhZWYaujW+5TtdSWF0V5zFoVi6XMBrjoVlCqSTmetXA1o1dqhSam1B/BvE0V5fD/FlK7RltJJNeBdndaTKgbSCVEqOfmWzlOH5PM2/PELDSPDs7g4QsI9FhIqDEGMYUGbMzZ4c8smAYhoGNjTxi2tYD6ZiWRqVSFm6NYsdxUKlUoPhtOoosoVwSt6eZV5fTehK1Wi3U69ASEoTmSjNNBNxnNkPzDtvfOiZSSbHaM4jHtv0PPF4kEbCneebcWYxJ7ScBcmOSjBlBQvPq6gpc10VMbwnN/mXRNnqpVqtwXXezPUORUDfqof4wHCR+0JSNZ+C6Lq2g4b95ttswi4ipuSXDsnbIXgGj0NxGwu9VLs/+B4qnHoRZnG98z6rmUDz1IFzHQDye6PQjSITxSjNvz+BdGqKEZsdxMDc307GfmZtQFBSKRSE29+AbucT1rRNj+WXRthTnrRiqLG35ytfnFQ3f2CUbz/iXxTrz0AmtnkG45vYMvuV8GFFobiOR4GG481GwYxmNijQRS2PJOf7q8SvNopxyXV5egmGaGO/Qz8zxUD0zc24YwwoU3x0xro9suT7mh+Z5wTZ64ZP+NicCyluuFw1fbm8skd1ymRDiaQ7KZojPSFFoboNXmmMTT0H64l+Gmj7U+J4SH0PqCc+H61iN2xGxNMIxL5Mwfr0YlWYegie6hOYJRd1y+yhbWJiHpiWgKPqW62VJQVxPY2FhvsM9o4lXlNWmzU2868WcDMgrzWOJkS2XRUfdGYRrbsmwqNK8v/BKs9thgxPe60ztGWJqtGEwMScCzsycBQM6rtHMxSUJSVkRoq95dnYGca39muUxfUSo9aqBpvYMhdozgM0K+3hy1L9MoRmg9gyyic93YIoKK8TrNFNobiMW87a/7TQRkIfpzTYOIpLG6hn8Db9RaRajPWNm5hyyigqlh0+8MUnCzLloh2bXdTE3N4tEbLTt9xOxUSwszAtzUAVs72nW/PBcLBYCG1OQyuUyGBhG/UqzqBX3VlRpJhwPzbKmU0/zfqMoClRV7Rya/et5uCZicRz/nV7i7Rli9TTPnD2N8Q5LzbUaVxTMz89GOjCurq6gXq8hEe8UmrOwbQtLSwtDHllwtrVn+F9F7WkulYqIazEkNe8zQ9THoZXrivGeSbozTa8YKWkaheb9KBZLwHU6/Mf511OlWUyb7RnY8jXKwZCr1WpYWVvtOgmQG5cVmJaF5eWlAY8sOLxnOxkfa/t9fr0Ivd1cqVSEpiqN1iVJYpAkJmyFtVQqIqHFockaZElCsSjm47DJKzw0ChBEeHzJOUnTQ700JYXmDuLxOFx7557mWCw2zCGRkNi+5BwDmBiV5rk5b3e7bsvNcTxcz85GNzDynu3O7RlZMCbh7NkzQxxVsEqlYqO6DHivEU1RhA2LxWIRCTUGxhgSWkLYg4dWVGkmHJ8IKKk6TQTcj+LxBFyn/dGOS5VmofFw3NzSyxgTIjTzbbF7rTSPyQoYol1lPXv2DOKxDBRZbft9SZKRiGdx7tyZ4Q4sQMViEYq8teddlZmwEwG90Oy1ZiS1OIVmnwjvmTtxHAd/8zcfxR13/CkefPBrQQ8nULwlQ9Z02txkP0ok4h3bM/j11NMspm1Lzvn/FqFqMjc3C4VJSHfZDZBTGMOIomJ+PrqrR5w9exqJWPvWDC4ZGxOq0lwobEBtCc2KzISdCFgqFpDUvSJLUo2jUBDzcWglenvG+noO3/72v+KRR36Kb37z/qCHEygemiU9Btd1Q9vuSKG5g1gsDuZ2qDT7y6FQaBbTZmjevI4J054xi1FFhtTHWlGjkoQ5v0IdNZVKBaurK0jFx3e8XTI+jkJhA/l8fkgjC1ZrewbgTQYUMTS7rotisYikX2lOaHEhH4etxJo83Qk/eEolVOEPpPhEQFmL+ZfDWW2m0NxBLBYDdmrPYAy6rrf9Pom2dqEZgrRnzM/NYLTHKjM3KstYXFoM9eSO3eItF50mAXKphBeqz549PeghhUK5XIaqbH2eaIokZFtCrVaFZVublWYtgaLgAYkT4ezcTjY2vIPoyfEESqVSJN8je9WoNGterjKM9nPKgkahuYNYbOf2DF3TGzPDiVg2e5o3//9F6Gmu1+vIrecwKvcXmsdkBY7jYHV1eUAjC86ZM14ITiUmdrwdD9UihGbDMGCaJrRtlWYZlUol8q+TVo1qoh+aU3oClWpF6IDEifZcaJXPrwMADk56z41CYSPI4QSKh2RZ55VmCs37Sjweh9NhnWbYFrVmCMzlK/JvqTRH/wNgaWkRAJDtceUMLuuH7MXF6K1TfPbsaehaEpq68/uBImuIxzJCTAbk1WRF2frxoigSXNdFtVoJYliB4a0YSW0zNDdfL7Kov2d2s76eAwAcnExuuSwir9LMIGmaf5lC874Si8XgOjZcZ3szuuuY0Gm5OWG1mwgoQqWZb86R7bPSzEP2wsL8no8paGfOdJ8EyCViY43KdJS17gbIibqVNq8epjTenpH0r6fQHPX3zG5yuTWkEhqyI7HGZVEZhgFJUSD5nxeGEc6e5v5KRgLhazC7jgXW0sPpOibicao0i6pTpdmN+J6wfIOSfysVwQBcn0jiQr//bMUy8e9N/ao3Z0aQ9F83p406GICVlWi1ZxiGgcXFeRyevLKn26fiYzi7cAbVagXxeHSXq+S73aktlWa+lXapVMLU1NCHFRgejpP61kpzoSDGpND2+OYmYofm1dUVZNIaRtJa47KoTNOEpChgfmimSvM+02i/aNfX7FiIU6VZWI2e5uYrGRMiNEto+bt7pDAWudA8NzcLx3G6TgLkkv4KG1FesxoASqUygO2VZqVRaRZrMiCf7LVZaeahWeRKM62eAQArK0sYSWuI6Qp0XYnce2Q/TNOAJCtgCq80hzM0U6W5g+ZK8zYu9TSLrDHje8s6zdH/AFhdXcGEouK27PaQONnhegB4ciyO00Ydy35PdFTwnQB7D82jjftddtnlAxtX0BqV5g7tGZVKeehjClKxWEBM1aH4FbS07rVnbGyIO+mLE3n1DMuysLa2hkuOeqddRjM6lpaWAh5VcAzDANvSnhHO0EyV5g54KG4bmh0L8ThVmkXVtj0D0Q/Na6srSEm7e8tISzLW13ORqsbPzs5AlhTE9HRPt9fUJBRFw8xMNNes5rqF5nJZrNC8sbGBlB+UAUBXNMiSjGJR5NDsvQ9E6f2gX6ury3AcB6NZL0uMjuhYWorevI9eeaFZBVO8nVWpPWOf2aw0b2/PcB2qNIus0+YmUf8AWF9f33VoTkoS6oaBarW6x6MKztzcLOKxETDW22PCGENCH8XcXNRDcxkSY5Cklh0BFR6axZoIuLGRb7RmAN7zIB1LUqUZ0S807GRhwZtYPe6H5rFsDKurq6GtsA6aaRpg8maluV4P5+NAobmDndozHNuErlOlWVSNrV+3baMd3dBcq9VQq9cak/v6lfKrjFFaUmlubgZxPdvXfeKxEczNRXdLccALxaoib1vHXmIMiiyJV2nO57dUmgEgpSUbvc5i8p4bUX7P7GZ+3nsfGB+NN766rhvJpTl7Ua/XwZp6mqnSvM80KsktazW7ruNXmik0i4r34W2dCBjt/jy+bFZil5XmBJO3/Jz9rl6vYX09h3hspK/7JWJZlMulSE+GK5fLjUl/rbwNTgQLzYV8o4+ZS+sJqjRD7Erz7OwM0kkdMd0LiRNjXuaI+kF1J/V63etp9tszwlpxp9DcAa8kb6s0++s2U2gWl4g9zXwjhvguQ3PMP1UflQ0d+EYvCb2/0BzXMwCiudELV6mUocjt11iRZSZUpdnwW5JaQ3NKT2IjL3Kl2RPl98xuZmfPYWJsM0eMZ2OQJIbZ2WivrtNJ3ah7S841QnM94BG1R6G5Az7Rr7WnmV+m0CyudpubRH2d5mLRq4zGeuzfbcXDdlRCM1+zutdJgFzMD838/lFUKZehSO1DsyIxoSrN/MzK9kpzEsVSQejQCET7PXMnlmVhfn4WB8Y350bJsoTx0TjOnTsb4MiC400E1MBkGQALbaWZlpzrQNN0r0+1pdLML9NEQHG139yEbfY6RxDf+lhnu1mlGdD9sB2ViYB8PdWTs/8JxiQcnboKo5kjAIBSZQ2n5r7XuO3lF/0iNNWbCLZRWtxy/ygq71BpViSGikCV5nx+HQC29zTrKbiui0JhA9nsaBBDCwVRDxrm5+dgWTYOTGzd5OjAeBxnz54KaFTBMgwDiqKAMQZJVUMbmqnS3AFjDLqmA9tCs1dppomA4ur0Rh/lDwAedrUOFcRuZAASWGRCs7fdLet55QxOYjI0NR7p7XKr1QqUDm08iiyhLFClOe+3YKRj2yvNAISdDBjl+R+9OHv2NADg4OTW58XBSW9VlbyArTt8yTkAkBUltO0ZVGnegR6LodbanmF7IZrWaRYXrzSzlvYMvvZoFPFKs7rLSjNjDJosRSg055CIj+CqS1+47XupxHjb6wFgavxSLKw+ilwuOquItKpWqxjrcCZOkRmKEXkO9GJjw6s0p/XUluszMe/y+vo6LrzwCUMfV9D4e2iUCw07OXPmFDRVxlh2a46Ymkz43z+Ja665PoihBcJ1XZhGvbHcHFNU1OvhDM1Uad5BTI+1mQhIlWbROY7Tdi/pKH8AWJb3OlB2tYm2R2EMltVmW/p9aCOfhyrvrkVLVeKN0/ZRY1kWLMuC3Kk9Q5ZQrVWF6WXN5/NgjCGlbz0Nz0NzVJ8H3fD/f1GeB61OnTqBqcnEtmUZpyaSYABOnxarRcM0TbiuC0n1Ks1SiEMzVZp3EIvH4Va3/sdRTzNxXRdwgfVveUsDJS4fjfxEQNP0wu69G9s/5CcVFc9JtZ8Qd6xWxbGaV1mUwBo/Z7/bKOShKonuN2xDVeIobKzu8YjCoeb/X3dqz5AlCY7jwDRNaJo2zKEFIp9fR0pPQmpp4+E9zlFat7wfIodmy7Jw7twZXHfF5Lbv6ZqM8bEETp06EcDIgsP7l3l7BpPD255BleYdxGOxRjsGtxmaqdIsqrZv9CzalWbbbrOdfJ9ktjc/JwzKpTJURd/VfVVFj2xfL2+/6bROM58gyMN11OVyuUZVuZkiyUjqCao0Cxiaz507A8uycWhq+/MCAKYPJHDy5ONCPTb1eg0AGms0Q1FRq9UCHFFnVGneQSwWB3PbTwSkSrO4XNcBkyWM/uKRxnWVR3ORf5NTGMNt2bG+7vPkWBxP9l8rd29Eo6rmui6qtQpG07urlCqyBtM0YFkWFCVab8E8NMsdJozK0uYqKplMf2tc70fr62sY0duHo4yeEjY0bxYYov2e2c7Jk14VeXoq2fb7h6dS+OnxVSwvL2Fq6uAwhxaY1kqzpCihbc+gSvMOYrEY4Lb2NHuXdX13VSay/zmOi23z4RiLdKUZYOf98eYdU+y+JzosTNOE4ziQJXVX95f8+4W1knI+Gu0ZXSrNvLIUdevr68jE2rcuZWIp5Naiu4pKLyJeZ2jr5MnHkUpqyKTaH3TzCvSJE48Pc1iBaq00S6qKOrVn7D+x2PaJgK5jQlFUyLIc0KhI0LyJgC3hL+LtGYydf2jmP2e/4712srS7KjG/XxSDIz8Q6FZpjuIBQ6t6vY5KpYyRePvQPBJLU0+zgEvPnTzxcxw6kOz4XjgxFoeqyjh5UpzQzCvNfCIgU7TQVpqHdm6wXq/jgx/8IL773e9C13Vcc801+JM/+ZNh/fpd0fX2Pc069TMLzXWdNpVmwInwB4CqqnBcF67r7jr4WnChqrurzoYJn8zIpN0dOPO1nfmKJFHCDwR22hEQECM087W4RzpUmkfiaRRLRRiGIcSkyGaboTnggQxZoVDA8soyrrjkaMfbSBLD9IEkTp74+RBHFiz+vsH8djVaPQPAhz/8Yei6jvvvvx+MMayuhn/2eCwWg2MbW4KC61i03JzgHMdtU2mOdnsGD7s2dv+mYbtuJMIB/3/ud2MTjq+kYNv2no0pLPgHndRx9QxxJgLmct5nXOdKs7el+vp6TpjeVU7UiYCnTnnV4079zNzhqSS+9+OzqNfrQrSCNt43FM3/KvjqGeVyGffeey/e/va3N8LnxMTEMH71eWmskOE2fbjZJq2cIbh26zQzBrgR3kabh13zPD7kLNeFqu7/0NzY3Ga3PyACLSqd8Apyp0ozb88IaxVpL635/cpZPxy3yvphem0t/AWkvbYZlqP7ntnOiROPQ2IM05M7h+ZDB1NwHKexc2DUbYZmvz1DVWEaRigLUUMJzTMzM8hms/jrv/5r3HbbbXjta1+Lhx56aBi/+rzwcNzc1+w6FmICHPmRzhzHadui4DjRqxxyfLWY3YZmx3VhOg7i8eisOrPrj/sIV9f4adaHz6zioRPLWC1sVpSLVQM/O+cFSRHaM1ZXV8DAkOlQac7GM43biUbUSvOJEz/H5EQCqrpza9ehA2JNBmyE5sbmJn6RxjQCG1MnQ2nPsG0bMzMzeMpTnoL3vOc9+MlPfoI3vvGNePDBB5FKtV+Op9X4eG+320sTE1kAW0MzXBsjI2lMTrZ/IyTRp+ty2/YMJrHIPi+mp70zQ3XXAdB/L6/hfzhOTo7u+8dIkrw38tmlh7Gc27oJQSo+houP/ELb+y2tPY6l3OMwTS9IHjgwsu8fi1aNFfQ6FNP51aqKyP3trcrlDWTiKSgdet9H4hkwMFSrhcg/Fq34jpGxmCrM3+44Ds6cOYXLL+7+9yYTKrKZGGZnTwvx+PCpLptLznlfk0kFo6Ph+vuHEpqnp6ehKApe/OIXAwCuvvpqjI6O4vTp07jyyit7+hlrayWvl3SIDH6Q4zTtYuZaYEzBykpxqGMh4VGp1Le3Z0jeDOCoPi8sy18qbJevwbo/SdJx5H3/GBWLfpV0l1Uy169Rb2zUoCj7+7FolcsVIEsSnnbJ1LbvpeMarr/kAL7x8CxyucK+fx50Mzs737E1A/A2OMnEUzh3bi7yj0Ur0/TOylUqdWH+9vn5WVSrVUz32L8+fSCBY8eOCfH4rK7mAWxtzwCA+fk1WNZw17KXJLZjkXYooxkbG8MNN9yA73znO7jxxhtx+vRprK2t4cILLxzGr9+1WMxrw9hSaXYs6mkWnNee0XIlY3Ds8PVf7ZV02vvwr+1yhZCqH7ajsKEF7+8+OHE5jkz1dtAPAFPjl2Jq/FLMrzyKU7P/GYlJka0Mow65wxrNgLfkoCxJQvQ0r64s43B8+1bJzbKxDFZWloc0ojARrz3j1KmTAIDpAzv3M3MHDyRx7MQMNjbyGBnJDnJogTOMOiRZAfPnPPDwHMb3iaGt0/zHf/zH+NjHPoaXvOQleOc734k77rgDmUzno/Aw4KtkbO1pNmn1DMF1Wqc5iqshcDzsVnY5MaPq3y/sr/le8MmMdvMZqD44/vuJpkVvbkS9Xu+4RjMny1JoZ8bvFdu2kVvPYSyxc9gZTYxgdUW8nmZ+1lik0HzmzCmoqozxbG/zOni4PnMm+pMB6/V6o58ZaA7N4Zv7MLS699GjR/GZz3xmWL9uT7QLzY5tCbEEDOnMtu3tPZsRX3IulUqDMbbr0FzxV6CJQqVZkiToug7b3l1otmwDkiRFttIsdVkdRJZYKCtIeymXW4PjOBhN7HyQOJYYwU/mj0VyS/Wd8LA87JbLIJ06dRJTEwlIXQ4quakJHppP4eqrrx3k0AJXr9cbQRnYnBAYxvcJ2hFwB41w7Idm13W91TOoPUNojmMDLW98LOI7AkqShEw6jfIuVwgpOw4YWGROM8ZiCVj27mZ227aJmB6LxO6IrQzD6F5pllhjB7Co4i0X3SvNWbiuK9yyc/y9UpQdAR3HwczMWUxNJHq+j67JGMvGBak01yA1LUfKV8+g0LzP8NDcqDT7X6nSLDa7Xe+yxCLdngEAY2MTKO3ywKBkO0inUpGppiWTSdi7DM2WXUciOfzVgIbBMIzW48ltJIbIh+bl5SUA3UPzWMI78yJaXzMPy6K0ZywtLcIwjL5CMwBMTcRxToC1muv1emM3QGBzIiCF5n2mtT3DdSk0E15pbrky4pVmABgbH0d5lx9yJcfG6Pj4Ho8oOOl0Gqa9uzd006oj3eNSm/tNvV7rWmmWGIt8T/PKyjIkJnXcDZDjoZqHbFHw98qov2dyMzNnAQAH+gzNB8YTWF1bRaVSGcSwQqNerwPK/uhpptC8g23tGRGewEN6Z9vbJwIyxuBEvNI8MXEABdveVXWo6Lo4cGD7MmT7VTqdhmXv7g3dsutIR2BCZDuGYXTt2RSl0jyaHGlsmd5JJpaCLMnCVZr52TpxQvM5SIxhYrS/zZ0mx73bz83NDGJYoVGr1bb2NPv/DuPBNYXmHciyDEmWqT2DbOE4bSYCSgx2xD8AJicnYbkOqn32Ibqui4JtYWLiwIBGNnzpdAaWtdvQXGss4Rc19XodcpdebUlioawg7aXl5SWMxrpPepWYhNHEiHCVZrexbnu0Cw3c3NwMRrMxKEp/kWtizKtMz85GPDS3TASk9ox9TNP0zfYM/wVOS86JzbKtba8cxhD5SvPkpBd6N/r8O8uOA9t1MTGx85q1+8nISBaGWet7IpPrujCMKkZG9v8qIu0YRr1rpVmWor/k3MryEsaTvU16HYuPYEWw0Mznf7SdHxJBc3MzGM/2nxtG0hpURcb8/OwARhUe3kTAptAsyWAsnOu5R2NWzgDpmo6qH5ZdqjQTALZlbV/5QICJgAcOeDtZfaNYQEKScH0iiQv9VqUVy8S/lzZ3rro5M4Kkv33wwzWvH2+qx52w9gO+Cohh1aCrvfcp2rYBx7UjsfReO6ZhQkrsXIuRGEO1Ht32jEqlgnKljNF4b//HY4ksHl5+bMCjChf+XilCpdmyLCwvL+MJ1/TfnsYYw/hoDPPz8wMYWXgYRh2asrl6BmMMkqqG8owUVZq70HStMQEQjZ7m6K2vSnpnWta2Jecgees0R3k2OO9JttHf38jXdj54cHrPxxQUHppNs78JOoZVBQBks6N7PqYwMMwel5wzoxuae11ujhtNjKBSraBcLg1yWKGyWWmOfmheWVmG4zgY20WlGQDGsjoWF+b2eFThYrS0ZwDwQzNVmvedmB6DW/UrzS61ZxDAti20zu/hlWfbtiOzrForRVEwOT6BbLGImzNbA8GkouK27Fjb+8UlCYosY3x8YhjDHIps1q809xua/dvz+0eJ4ziwLKuH9gwG09zdxjD7weqqt8Nft41NOB6uV1aWkYzoUoStLMva8jXKlpYWAWDXoTk7EsOxEwuR3QCn8b6htoRmJZyhmSrNXei63mb1DKo0i8yytm9uwl9JUa+cTB8+gvU++3jXbQsHDhyEJEXn7YZXincbmkdH2x9g7Gc8CHddcs4PzVE9K7O66lWaR3uuNGf8+4mzwYlte5+lUT544vgkz2xmd6F5NBOD67qN51XU8BYM1lJpZhSa9ydd16k9g2zhVZpblpzzL0e9cjI9fRh5q79l5zYcF4cOHxngqIZvZCQLxhjqfYbmulEGAGQ7VOX3Mz65r+s22v73oxqYVldXoSkqEmpvISnr9z7ncuKEZv4+GdXnQLOVlSWoqoxEfHdV4mzGmzeyvBzV0Oy1arW2Z3ihmXqa9x1N08Fcas8gm6wOPc3AZgUlqqanD8FyHRR7XF7Pdl3kLRPT04cGPLLhUhQF6XSm/0qzVUUsFkcsFr33EL72ci+V5ubbR00ut4qReKbnbdITagyqrApTabYsq3HQbUa4t51bXV1BNqP3/HxoNeKH5rW1lb0cVmjwYLw9NCtUad6PNE0D/LAMf6YvVZrFZrVZPYNXmqNeOTnsV4xzPR4c5G1v2uDhw0cHOKpgjI6ONSrHvTKMciRbM4DNENx1c5Ooh+a1NWRjO+8E2IwxhpF4GuvruQGOKjyag3JUnwPNVldXkEmq3W/YQSqhQpJYZA+q+HOAbetp1lAP4dKUFJq70DStsT6z61iQZSVSvZmkf7ZtAXL7SnPU2zMOHfJDc49/Jw/Xhw8fHtiYgjI+Pg7T6rfSXMF4hLYTb9aoNHdrz2iE5vB9IO6FXG4NmT5CMwCM6Cnk1qIZilo1B2URQnMut4Z0aveFNkliSCd15HJreziq8NisNG9tX5FCWmmO3lTMPeaFZn8ioGtDVXd/xEiiwbIsaK09zbIYoTmVSiGTziDX44ddzq/KHzwYrfYMwKs0G+ZP+7qPYVYiW2nmFcTu22hHt9LsOA42ChvITD65r/ulYynM5qPZs9qKByFZliN74MSZpolSqYTTMwbuvvcYnnndNC6+wJsgurRaxte/fa5x25f+yhORSnjh+uHjK/jpce8gKpVQkUoqkT0T0ThDpWw9sGCKCiOEoZlKpl14OwLy9gyLWjMI7DarZ4gyERAAjhy9ALkeVwlZsy0cmJiM5OtmdHQMplWH7fT2f+66DupGBWNjEa8097DkHBDNftZisQDXdZHSk33dL60nsbGxEdkVRZrx0KxpWigriXspn18H4O2CeT5SSRXr69GsNPMDJ7at0qyG8sCaKs1d8Eqz67pwHRtqBD/8dwY9IAAAIABJREFUSe9s21s5onX1DEQ4CLQ6fPgoHj/+qPc4dDkVv+44eMLRC4c0suHi4dcwyojHuu/+ZphVAC5GRyO6sQn1NKNYLAAAUnrvu0Ty25uWiVqthng8PoihhQY/Ha9pGqrVamTXHwaAjY08AOB5z74Al1y0dQnCqYkkXn1r+zMSV10+iasun2xcfvDfz+Lc/MbgBhogfuDUbvWMMG6CRJXmLhoVMtcGXBu6Rltoi6wx0U8WuNJ85ChMp/sKGnzljMMRW26OGxvz2ix6XXbOML1Jg6OjUa00+6fde1xyLpqh2dtKPqn1F3yTWsK/f2HPxxQ21ar3etF177O0VqsGOZyBKhS8oJtKnF9bZzKuolqtRvI1w0Mzk7f3NNuWFbq9Dyg0d8FDs+vYcKk9Q3iW5YXmbZVmWYzVM4DNFTTWuqygsW5bcOGF7Cjivck8DHdTj/DGJsDmc7/XSnMUz8rwrbATfYbmuL+mc7nc32os+1G16oVkvuwivxxFhYJ3ELTbNZo5fv9SqXjeYwqbxhkqdXulufn7YUGhuQuNV5ZdG65jN46OiZgMww/NHSrNIoTmXlfQ4CtnRDU08w1Kel2r2TB4pTmaoZnaM4BKxXsuxJT+Pid4aK5Uoh+a+WPEP0uj/DfzMwfx2PmFZn5/fiYjShpLzrWpNHvfD1ffezQbifaQqvJKswXm2lRpFlyjOtZx9Yzoh+ZkMonsSBa52s67NeUsG5IkRXLlDMCrlMVi8T7aMyqQZRnpdH/Lke0XjdUzBG7P4K0H//SjL0FiEp57yQ140oGLAQDzG0v40iPfbNz2Vde9BOlYCgBwas1bRaHW5TUVBTwk897tKIfmcrkMRZGgqvJ5/RwemqNZae7c0+x9P1zvEz1Xmg3DwF/+5V/i+c9/Pq6//noAwLe//W3cddddAxtcGLT2NPMQTcTEK8mtlWaR2jMA4MiRC5Bzdu41y9kWpg5MRXaSDwBks9meK811s9LYfjuK+t0RMIrtGY3+zD7/j2Um+/ePfmgul8tgjDXaM6LcklIulxDTz3+Z2pjuvYdG8QDDMAwwSQZrWWFEkpXG98Ok50+zD37wg1haWsJf/MVf4PWvfz0A4NJLL8Wf/dmf4TWvec3ABhi05p5muDZ0nUKzyDqFZpHaMwDg8JGjOP7oz+C4bsfKYs5xcMmRC4Y8suEaHR3Dzx/7OR5+/CsAgKNTV2E047WvlCprODX3vcZtGRgmDkSzNQNo6mnuEhijvE5z41QzvL/xX098D/96wnsOTI8cwBue9aq295Mlecv9o6xcLkFVtcaeB6VSKeARDU6lUkFMO78qMwDoutz4eVFjmsa2jU2AzSXowvaa6Dk0f/3rX8cDDzyARCLR2BFvamoKS0tLAxtcGGia98L2lp2jSrPoOrdneK+JsL3AB+XQocOwXAdFx8aIvP1txHJdbER45Qwumx2F6+68ighn2lWMjkWzvxvwQrMksa5VVinCK83YPW4v3yrKj0mrYrEITVObQnP0Wg64arUKTTv/qWO6394RxUmThtE+NPNKc9jOSPUcmlVV3bb0Ry6XQzab7XCPaGiEZJdWzyDNleatb4Qi9TQDXmgGgHW7fWjO+ytnTE9Hb/vsZtnsKMCAKy/5tW1hMZUYx1WXvrBx+Xs/vRsjI9F9vzQMAxLrHhAk5gXrKB5g2rYDXdE6VpQ7ue7wU/GlR76569C9nxSLBSiKAlmWIctypJfZq9eq0NTzD82q/zOiuDyfYRjbJgECEehp/tVf/VW85z3vwczMDABgeXkZ73//+/GiF71oYIMLg61LztFEQNHxo95OPc1he4EPCg/NnVbQWPcPsA8diuYkQG5kZASOY8N2dj5YchwbplWPdGi2LLNrPzMnSyySB5i9bPjTVjTb3Nva2NhoVJk1TWssyxZFdaMORTn/0CzLEiQpmgeapmlumwQINFeaw/U+0fP/5u///u/jyJEjuOWWW1AoFHDzzTfjwIEDeMtb3jLI8QWuEZIdy9sRkNozhNaxp5kxsIi+qbWTSqWRSiaR77DwfN6vmB08OD3MYQ0dD8HdJgMaVnXL7aOIt2f0QpKk0H0Y7hUXu9gKO/q7ZzcUChuNz1VVVSMdmg2jDnUPQjMAqIocyc8X0zQBeXvfN/Ov25ftGbZt484778S73vUu/OEf/iFyuRxGR0cjOwu82eaSc95/HFWaxdZ402qtNMNr2YhqEGhnevow8mfPtP1e3rYxmh2FrseGO6ghGxnxts82rZ1XPTBNLzRnMt23296vTNPsOgmQkxiL5GtFlmU4Tv8J2Pb74uU2p6mjxLIsVCplTE0dAOB9nvKtpqNobW0NxQJw973Htlw/NZHAC268sO19Hj6+gp8eX912vSxLkTw7Y5qd2jPCORGwp0MgWZbx93//942lo8bGxoQIzMBmSHYsCs2keSH27S8dSZZCd1Q8SNOHDiPfYSvtdcdutHBEWSbjVY55KO6Eh+pMJjPwMQXFti30+rEgsWhOepNlGXaXpRjbcVzbv3+09xvjAZlvbKJpGvL59SCHNFCu6+5Z540ssdBtKb0XDNNbcq4VC2l7Rs+Htbfeeiv+4R/+Aa9+9asHOZ7Q2exp9sIQtWeIrWNPMwAo4rRnAMDU1EFUbAuG40BrWWOz4Dh4asRbMwAgnfZCcNdKswDtGZZl9VxpZoxFMjSrqgrHdeC4Tk+TIjnLD0NR/3zJ57eGZl3XsbCwAMuyIrmeezKZxBOO6Pi1X3xCz/e56vJJXHX55LbrP/qZn8DpUKTYz0zTarRiNOPXha263vOz9OGHH8Zdd92FT3ziEzh48OCWSvPdd989kMGFQaM9w/IWradKs9g2K81t2jME6mkGvNAMABuOjcmm0FxzHNRsu/H9KOO7+/Ge5U54qOYhO4osq79KcxRXitA0LwyatgVd6f2zwrC9YBD90OxVlfnnqKZpcF0XhcIGxsbGgxzawIhxTn73TMMAU7a38YV1ImDPofn222/H7bffPsixhJIkSZBlhXqaCYCm/qp2E55kJlR7xoEDfmi2bUw2zX7e8KtmBw5MBTKuYZJlGYl4AlbXSnMNiqI2KmxRZFlWzwGBMcCyoneqmf//1i1jV6GZ75IXVevrOQCbjxP/e9fXc5EMzYwxuHs1ydNFY4+MKDEtE0xPbrt+cyLgPg3NL3vZywY5jlBTVAWWzdszzn9LTLJ/eZMWpPY9/VL4Ji0M0uSkN5mn0NJnV/B7Oicnox+aASCVzsA06jvexrTqSKVSkZ4L0k9PM0M0K82xWBwAULfqAFI936/mn8mMx+ODGFZo5HJrkCSpUXzi4TmXy+GJTwxyZIPh9bjvTWp2XBesj5af/cKyrLYTAcEkAOFr4+qriejzn/887rvvPiwtLWFqagovfelL8fKXv3xQYwsNVdVgGtTTTIB63YDUabKOzFCv7xyeoiSRSCART6DYMvGJh+iJie19eVGUTqexurTzVsCWVUN6JLqtGYC3ylKxYuChE8vbvpeOq3jS4dHGZcaiOakpkUgAAGp9nnGqmzw0J/Z8TGGSy61B12ONg0deaV5b275aRBQoigLH2ZvQZ9kuVDV6fd+maUJq19PMGCRZ3r89zXfeeSfuvfdevO51r8OhQ4cwPz+Pv/3bv8Xy8jLe9KY3DXKMgdNUDeWq96FIlWaxeZXm9uU0JkswulQco2ZiYhKFxYUt1xUdG8lEIvJVMy6dTmNpIbfjbSy7jnT6wJBGFAzbtvtq4IzipKZk0jvNXDV3btdpxW+fTPZend6P1tZWoeubhSe+M2AutxbgqAZH0zSYexT6LCuam6vZtgW5zeoZgNeisW8rzZ/73Ofwmc98BocPby4jdeONN+I1r3lN9EOzpsG1qaeZ8C0/21eamSzWREAAGJ+YxLmF+S3XFW0b45PRnwTIpVJpWPbOB0uWYyCVSg9pRMFwHAfZpI5rntD9DANj3i6JUZNKeaG30mUJwlaVRmje3tsZJaurK1v6thljiMVika00x/Q4zPr5b97iOC4sy4nkuveWaUFvU2kGAEmWYZrhCs09N8hUq1WMjY1tuS6bzaJW6++Iej9SVRXwF5+n9gyxmabRdmMTwA/NAk0EBICxsXGUWiqGJbgYGxejNQPwqoOW1SU0W/XIByJvTdoel5wD4NjRqzSnUl4LTsXo73OxYlShqVqkJ4rato18fn3bZEdd17G6ur2lJwriiSTqxvk/z+uGd4DJ23+ixLYtsA4THJkkh27uQ8+V5uc85zl417vehT/4gz/AoUOHMDc3h4985CO48cYbBzm+UGiuLlOlWWyGYQLtD4qF2xEQAMbHx1F37C1rNZcdB+Pj0ZsJ30kymYRlm3AcG1Kb04yu68K06pE/9e44Ts/tGYyx3W03HXJ8smfZ2Hlb9VZlo9qoUkdVPr8Ox3G2heZYLIbV1WhWmpPJJI6tVRo7Aj7zumlcfIG3VvvSahlf//a5xm1f+itPRCrh5YvmXQFTCRU33XDE/3nReo64rgvbtttubgIAkKTQtWf0XGl+3/veh2QyiVtuuQXXXnstbr31VsTjcbz3ve8d5PhCoTkoU6VZbIZRb7/cHOAtOSdYe0Y26519KvtnYizXRc22MTo6ttPdIoV/kPEVdlrZjgXXdQSpNPdx+z1aVSBMJElCMpHqOzSX6pVIb7EOACsrXjW5NTTH43GUSkXU69E7a51Op2HvQe9+peoVY6LW4sXnNXQKzUyWQzdhuOdKcyqVwh133IEPfehDWF9fx+joaCTXDGxna2iO3uxV0juvp7lze4ZoleZs1qualG0HozJQ9vtUo7zzXSt+ytSyDWjq9smPvN85kYh2aCaedCaNUr3fSnMF49PRngewuroCYPuyejxEr6ys4MiRo0Mf1yCNjGThusDtL34SVGVrXpqaSOLVtz657f1adwV87FTO/3nROrDiVeSO7RlMCl17Rs+p995778Xx48chSRLGx8chSRKOHz+Oe++9d5DjC4Xm7T2p0iw2o0tPs+M4oTsyHqRs1ltGrOJ6f3PZrxzw60WwWWlu39ds+xXoqFea+xXF9gzAC0qlermv+5SMstCVZgCR7Gvm74Ol8vmdgSyVvWJM1M7g8cnAnUIzJBl2yOY+9Bya/+qv/grT09Nbrjt48CD+f/buPDyq8uwf+HfO7BsJCSGyr6JYQRQX7NtqxVq3IuD2Wnm1rVb62vrT4laXulRbEXC3tta99qV1YRNFS6uodUFblBZccENFVCAkIetkZs7y++PMcyaTzGQm1Mw5Oc/3c11ekJmJuY0z59znPvdzP7fffvtXHpTTdE6UOyfQJJ9UKtnjyDnzNfK0aIjKRyJzqz2RSZplqjSLZLjQYkDRtuH2SnNvN25x40YNgPmZaOvF9AzDMKRozxCTM7reoc5Wmt2XNItdDpta/rNzQnNrCj6fF/G4u2a9WwWmggsBPf230tza2tptoUI8Hkdz838+TsXpxGxmr9cnTUsK5ZdOpwuOnBMVaKcNY+9LkUgUiqKgPZMsi6R5wAB3Hdx7ItozND3//3dVkkpzb7YMNgyUvHtgfzNgQO8qzR3pJDRdc/2F5o4d2/NuEx4IBOD1elFXV2dDVH1L7Jra1Pyfze9vak6iumqQ6/IPkTQXrDR7lP5baR43bhxWr16d89jf/vY3jHPj3pdd+Hz+zJ+sMsvOTJoLVJozCwRl6mtWFAWxaAyJzG229syCQLdVRHoiKsgFK82qHLu99W4ihpF30ogbVFRUoCOdRFor7TjQkmqzvs/NCiXNHo8H4XDYlZXm6moz0W1s+s8WOTY2J1G7x5DiL+xnREJc8K6T4rye5pKzwIsvvhhz587FM888gxEjRmDLli1Yu3Yt7rnnnr6MzxHE4j8mzZROp+FV8r8PRDItU3sGYN5x6siMjOrQdYRDIak+K1bSXGB6RrbS7K5xUV0pioJSc2bDgOuqZoJos2hNtmNgpHgiLKrSbm7PSKfTaGrahYEDR+d9PhgMYseObeUNqgy8Xi8GDx6Mhv8gaTYMAw2NHdhvf/clzaKnuX7jP9H00Tuo3m8aYiPGAgA66rcj2VAHfYCzjpslH7UOPPBAPPXUU5g0aRISiQQmT56Mp556ClOnTu3L+BwhW2nmFtqy01S1YKVZxvYMAIgPqEBHpsLcYRiIuTw57Mrv98Pr9RUeOZd53O3binu9vl7UmQ3XJs2iYtxSYouGmLTh5kpzfX0dDMMo+BkwK83ma9xm6NARqG/c/aS5qSWFtKph6NBhxV/cz1gj50p4jVP0qhw0dOhQzJ07FwDQ1NTk6g95Z6Kn2cdxc1ITkzE8BeY0y9ieAZizQ8WN1Q5dR9Rls0SL8Xg8iEQiVnLclaolEQqF4S2wVaxb+Hxe6CUmPYbh3jt32UpzqUmz+yvNhSZnCOFwGMlkB9raWl03i3j48BH41/p1UFUdPl/vLxR3NpgXVcOGuWscH5CtNFcf8HVUjP9aznOh6lqEBw913DSqov8HV6xYgZdeesn6+q233sLhhx+OadOm4eijj8bmzZv7NEAnEAf33q4OJ3exdibqYeQcIF/SHIlEkMxMz0jCQNTlO5vlE4lEC46cU7WU66vMQKbSXGp7Rub1biSS37ZUaRM0WlPt8Hg8rksWOxOL/HqqNJuvc19f84gRI6EbBnY2lD5RpbPtO9utf4/bWJXmQrmVx+O4SnPRpPn+++9HTU12yPYvfvELfP3rX8fKlSvx9a9/HQsXLuzTAJ1AtGUwaZabSIYLVZrF2BzZkuZoNIZk5sCWMtzfu5tPLBor3NMswRbagHlHrtRN/nTDvRtFiUWwpe4K2JZsRywac227CmAmw4qiIBgM5n3ezWPnRo0aAwDYtrN3s7uF7TvbMXjwYFcuJNbFAaPAQkCPRyn57lW5FP2Ubtu2DRMmTAAAfPnll/jggw/w85//HHvuuScuuugibNiwoc+DtJt1G9FZ/++ozKxVvAXbM8w/rYq0JMLhMFRDh2YYSBqGNYJNJtFYtMeFgF3HdbqRz+cvuSfVbM9w5xqRYDCIQCBQctLcnkq4ftqMmNFcqPAkkmaxa6CbDB5ci0g4jG07di9p3lbXjjFjxn/FUTmDdbzoodJsGP2s0uz1eq3K2fr16zF27Fhr69xwOIyODvftF99Vtj3D5kDIVsUrzebjThuR09dEkpwyDKR0Xc6kORqDphdYCKinXD+jGehlpVk3rLUibhSLxUtuz2hLJRB3+VzzurodBfuZAfO94/f7XZk0ezwejBk7Hl/u6N3W6gDQ2p5Cc0sSY8e6c7SvSIgLplYObM8oen/s4IMPxq233opZs2bhj3/8I4444gjruc2bN+e0briV2xfwUGlEBbn9/UZ0bGnJec5XGUR4jHniS6flSprFbcMOXYdq6AiF3N+/21U0Gu1xR0B52jNKy5o1w91JczwWR3tHaUlzu9qBgdE9+jgie+3cWYd4vOfPQCgUcmXSDADjx0/Au++8hVRaQ8Bfej7xxTazOj1u3J59FZqtilaagZLXSZRL0UrzlVdeiXfeeQff+973EA6Hcc4551jPPfHEE/jmN79Z0g+aPn06jjnmGMycORMzZ87MWVzodG5d5U29U7SCLGmlWSTJbZmKQE8VJbeKRmNIq8lutxINw0Ba7ZCiPSMQCGZ7FIvQNB2BQKCPI7JPLB5HIl3aXdj2VMLV749UKoWWluaix4VgMOjKXQEBM2nWDQNfbO9di8bWbS3w+bxWX7TbFEuazXYeZ2XNRbPB2tpaPPzww3mfu/jii3v1w+644w6rP7o/EZVmLgSUm6qao2+i+1YjNLz7SnetzWzfcNqInL4mToZtmfFBMlaaxeQDVUvB78smB7qhQdc1KSrNwWAAWgm3Ug3DgKbrCAbde3EVjcawI/15Sa9NpBKufn80NNQDKH4xbVaad5YjpLIbP34CPB4Ptn7ZgtHDS2/F2fplK0aPHuvaC8zsGojCuVWpF+Llslsl1GuvvRbXXnvtVxyKc4nRSG4cvE6lE8lw8Z5mOZPmdqvSLF/SLJIeVU3mJM2qalYb3TxOTAgGQ1A1HYZh9FhgEC0cbk0EALPPv75tF+559c8AgMPHH4K9Bps7nX3RtB1Pvb0GgLnJi6prru55r683E+FCkzOEUCiEjo4OtLe3u25dRCQSwfDhI/DZF7tK/p50WsP2ujYcc+A+fRiZvURO1VNPc7+rNOezcuXK3UqaL774YhiGgalTp+LCCy/EgF4sfqiutu9KvKrK/Nk+nxc1Ne4/+VF+9fWZg37BW0nmn6GQXO+T1tYqAEB7pjVh8OBKqf77AWD48MEAgLTagTCym1SkM33OQ4fWuP53UlVlHs91w4C3h6RZ08yT4KBB7n2fDBo0EHoJq/7FIqeamoGu/V2k02ZLQimVZgAwjARqamr7PK5y23//KXjm6VXQNB1eb/Hxgp9vb4WmGzj44ANc+95obMxcLPZwvPB6FUf99+9W0rw7FdfFixdjyJAhSKVS+PWvf43rrrsON910U8nfX1/faluZvrXVXBWvqhrq6lqKvJrcqr7e/H9frNLc3JyQ6n3S3m5W1hOZBKCjQ5fqvx8AdN08lKa7bHAiKs2G4Xf970RVxZ0WAz3lBGrmOJ5Ow7W/E8MwW/rOOuQU+Lps4jK0ohZzv/49AEBdawNueeE+6LrXtb+LLVu+AFC80iye37z5M0Sj1X0eV7mNHDkeaVXDlzvaMHxI8SRwyxct8Hg8qK0d6dr3RmNj8R5vTSvv+URRPD0WaXdrmvr//u//9vp7hgwZAsC8JXf66afjzTff3J0fbQv2NBPQqe2i0Nsg87jYGlQWgYB5shNJs/haJqL9Iq3mLv4SSbQM7RmiUqgWKW5oErTxiB3ukgVmdwvJzJ0IN25cITQ2NiAQCBSdQiWS5sbGxnKEVXZ77z0RgJkMl2LL5y0YNWq0q98b/dFuJc0//vGP8dlnn2Hr1q0lvb69vR0tLeYbxTAMPP3005g4ceLu/GhblHIrhdzPmhfZ40pfOG6uZF8LBs3e1I7M7WjxtUxEq5naNWnOfO32zSuAbBKsaj2//0V7hpunrIhEJ6kWS5pTmde79wJi167GolVmoHPS3NDXIdkiHh+AYcOGY8vnzUVfm05r+HJ7K/bZZ98yROZsTltLVnI2eOGFF1rV4aVLl+L444/Hd7/7XTz++ONFv7e+vh5nnHEGZsyYge9+97v4+OOPcc011+x+1GWmKOYVstP+51F5ZZPmAi/IPC7bQkC/P5M062KBl3yV5kAgCL/f373SnE7A4/G4eqSYIBK/YhM01Mzzbk4UxQVBqUmzmyeJ7NrVWNJMbkVR4Pf70dTUVIao7LHPPvti67ZWaEUuLEU/8957f61Mkdmsh9zKaXf4S+5pXrt2LW688UYAwEMPPYQHH3wQAwYMwE9/+lOccsopPX7viBEjsGLFiv8sUhspCivN1Gmlb8Gk2ZPzOln4fD4oimJVmmVMms3EeED3pFntQDQak+IYIiYeqFrP73/xvNsmJHQmkuBiSXNKM8dUurnqvmvXrpInpQSDQTQ1lT5hor/Ze++v4W9/+0vRvuYtn7dAURRMmLBXGaMrP5EQFzxiGAZ6Gkdnh5KT5nQ6jUAggO3bt2PXrl2YOnUqALh2rmJn2UqzzYGQrYruXuTp8jqJBPx+dCTN/kw37/TWk4qKCuyqz90FLq12SNGaAWQrxx98uQuf1rVg9OA4Bg0wH2tJpPDe52YylExrmde7OWk2LxxFUlxIyqo0u/NC0zAMNDc3Y+jQISW93ufzuTxpzvQ1f97Sc9L8hSz9zOJc2lOluTyRlKrk8sfEiRPx+9//HnfddRe+9a1vAQC2b98uxW1HUSVy2v88Kq+uu70VIltPMwD4fdlE2c3zd3tSUVEBVeteaa6srLQpovKKRMzxUcUuGg2ISrN7ZxOLSnNaLZI0Z5JqtybNqVQSqpou+ZgQCATQ0lK857e/isXiGD58BLZ8Ufi/UfQzT5zo/n5mRUyiKlxqhsfjrLt0JUfz61//Gu+//z6SySR+9rOfAQDWr1+PGTNm9FlwTiGSZgkLiNRJsc2LnNZ7VU7+TidFWbedHzCgIs/0jESv5tH3ZyIJHlIVxYHjB1tVZgCIhwM4cPxgHDh+MPaojEBRFFdfXJVaaU5raub17mzPaG42k8NS7z75/X5XJ80AsPfe++Dz7W0F+5o/396W6Wd276YmgnXOLJBcGQagOOy8WvLZbeTIkbj55ptzHjvmmGNwzDHHfOVBOQ0rzQTI2XZRKnFS9Pl80l48DBhQgVQ6kbMjXjrdgQED5Kg0+3w++P3+oj3NaU1HJBJx9ftE9PUXbc/Q0lAUr2svNFtbWwH0Lmlub2+HruuuXQew114T8eyzq7F9ZzuG1na/U7/1S3M+8557urufGYBVRa5b93c0vL0u57lQ9WDAMArvi2CTkt+VTz31FD766CMAwObNmzFnzhycccYZ1mNuJuZLDh06zOZIiJxJnBT9Lj35l6KiogKGoUPNzObVdBWqlkJFRUWR73SPaCRadOScmkma3UxUmtMlJM1BF1fc29vNzSs2b96MN954A/X19dZzLS0teOONN6x/kskk/H4/DMNAR0dHoX9lvzdhgtnX/NmX+ec1b/2yBcOGDXf9ZwQo4e6sYcDTXxcC3nbbbXjkkUcAAAsXLsTkyZMRiUTwy1/+Eg8//HCfBegEQ4YMxQ9+8CNMnry/3aFQPyBjRVqMnfP55FwECMCqKKfVBPy+INLpROZxeZLmSDSKdFvPc3bTqoHKKndv9lJye4aadvW0mfb2dgClt66JintbW6trk8bKykrU1NTg8y9bgSm5z+m6gS+2t+Gbh02zJ7gyEz3Ngw74LwwY133vjs/+ssRxdxxKTpobGhowaNAgJJNJvPHGG7jjjjvg8/kwbZr7/+d6PB4cccRRdodBNit24M+OpHPWlXE5WJVmSSdnALAqyql0ApEFbjXoAAAgAElEQVRQJdJqIudxGcTjcWxv6nmikqobrt8h0RzD6LV6lgtJaWnXLgIEgETCTJonTZrUbS53PB63pnAJIml2c6UZAMaP3wsb//2PnFYuAKhrSCCV1jB+/AQboysf0Z5RsNBk6PA4LGkuOZqqqip8+umn+Pvf/45JkyYhEAggmUxKWVUjOXmKT8fJvE6+pNnXqadZVqKiLJLlVGZRYEWFHD3NABCNxqAV2UZb1XREo+6dnCEEAwGkikzPSLs8aRbJb6nHBdEK2dGRKPLK/m3cuD3R2p5Cc2vuHO8vtrdaz8vAqiIXTJqN/ltp/slPfoITTzwRXq8Xt956KwDg1Vdfxd57791nwRE5iTX6plBOYI1xljBpzpwUfV4mzaItQ8b2jGg0VtJCQLdXmgGzRaOknua4OydnAEAyaSbNIhkuRp6keTwA4MsdbaiIZy+avtzRhmg0isGDa+0KrayszU0KjHM1DKP/Ts848cQTceyxxwLIDrGfMmUKbrnllr6JjMhhPMVKzZmrZaddGZeDlTRL3J4Ri5k7/6UylWZRcZZlcxPATJpTauFt5HXDQFrVEI26f75/MBRCUiu+I2A86N6LqmQyCY/HU/IxUSTN6XTPFxv93YgRo6AoCrbtaMPe46qsx7fVtWPMmHHSFF6si6kCexsYhl7yBVe59Ors3tHRgdWrV+Pee+8FAKiqCk0rfIAkcpOi87qN3NfJxOsVSbO8lWZFURCLxa1ZzSm1A6FQ2NXziLuKxWLQdB1agZOgmKwhw6ZYoWCo6DbaSS2NUMi97RnpdLpXSY84dqZSPf/e+ju/34/hw0dg+8526zFV07GzoR2jRo2xMbLyyt69LXBS1Z3XnlFyNP/4xz9wzDHH4Mknn8Rvf/tbAMCnn36Ka6+9tq9iI3KUYv1X2V22nfUhLwer0izx9Awgd4OTdDohVWsGAKvtIq3mT5rF4zJUmkPhsLVNdiEpNYVQKNzja/qzdDrdq6RHvNbtlWYAGDlyNOrqs20o9Y0J6LqBUaNG2xdUmXm9ohBVYEyl4bx53SVHc8MNN+C2227D/fffb50g99tvP2zYsKHPgiNyEuvDW2gMLdszpF4ICJiTMtJWe0YHKmRNmgvMak5blWb39zSHw2Eki/Q0J12eNGua2qtWA/FaGe5gjxgxEq3tKbQnzPeISKCHDx9pZ1hlJe5CGIUWD/fn9ozPP/8chx56KIDsG9vv90vx5iYCsh/wln/XofGFrUhua7OeS+9KYtfLX+S8Tibiv9kr8UJAABgwYABULQkAULUODKiQp58ZyLZdFEyaVXnaM8LhCDrUZMHnDcNARzrp2nnEAKDreq/uvMmUNA8bNhwAsLMhYf3p9XpRW7uHnWGVlaJkzpWFFgLqRvY1DlHyu3ncuHF46aWXch579dVXMWGCHPMEiaxkuEhPs8/nrA95OYhkWcYLhs7icXMrbcCsNMu0CBAooT1DokpzJBJBR7pw0pzS0tANvdv8Yjcxk+bSXy+SZl13f9I8dKiZNNc3mu1c9bsSGDy4Vqq7dVZ7RoE1EDB0x51PS/6/c9lll+HHP/4xvvWtb6GjowNXX3011qxZY/U3E7mdSAxj+1YjOCy3UuavDKLi0D1Qv+oTx10Zl4NIlp12gCu3eDwOTUtD01Upk+Z4vEh7Rmayhnidm0UiUXSkk902sBBEQh2JuH9mde+5f3rEwIFV8Pv9aGgyL7Ibd6Uwcsx4m6MqL3GuLJQ0G7ruuPNpyZXmKVOmYOXKlRg/fjxOOukkDB8+HEuWLMHkyZP7Mj4ixxAVgEL9V+JxmSoFgkianXaAKzeRDHYkm2EYhhTJYWelVJoVRXF1H68QjUahG3rBCRqJdIf1OpKPoigYXDMYjU3mhVVjcwdqa4fYHVZZZUfOFbizoDuvp7lXZ/fa2lqcc845fRULkaMVS5phJc3yTZAQix/F7TZZxWJmZTmRbM58LVfS7PP5EAwErYpyV2nV3A1Qhjm0YkJIezqBkL/7WLm2lDluTLYLq1LI8P4AgMG1Q7B1yztobU9D03TU1Ay2O6SyUhQFHo+ncKXZgQsBS06ad+3ahQceeADvvvsu2tvbc55bvHjxVx4YkdNYFeRClWaNlWbZK81igVuiowmAHKPVuorGokhpHXmfS2k6YjE5JoqIC6a2VAJVke5bqbenRKXZvUmz1+uFUXCwfXfitbJcfA8aNAhvv51CU3My83WNzRGVn9fr7aE9Q+u/SfNFF12EVCqFY4891tULF4gKsSrNhbYJlrg9Q1SaZakQFSKS5I5UCwA5pkR0FY8PQGtDe97n0qqOqgFy9HkPyPx3tqfybwndnm7PeZ0bKcruJc2yXHxXVVUjlVKxs9F8j1RXV9scUfkpXh+MAu0Zhua8nuaSz+7r16/Ha6+9JtXuVkSd+f2Z936RnuZAQL72DKdVA+wi+lM7Mu0ZMlaa4/EBaKz7Iu9zqm5I07IiFoG2JvNfQIjH3fz78Pl80AtNRshDvFaW48nAgWaS/OX2tszXVT293JWKVZqdVoQq+R7IXnvthW3btvVlLESO5vebyXChSrN43EquJcJKsylbaW7NfC3fIq9YLI4C6wCR1nRXJ4mdid0gW5NteZ9vTbYjEok6Lin4Kvn9u5c0y1Kcq6w03yPbd7bB5/NJOUnF5/MBPUzPcNrno+Ropk2bhh/96Ec48cQTMWjQoJznTj755K88MCKnKboQUOKeZhl3QcwnGAxCURQkM0lzOOzejSsKicVieRcCGoaBdFqTJmkOhUIIBAJoTeVPmluSbaiocHd/t98fgKZpBcfudSWSZlkWU1dUmL3udQ0JVFQMlLLoYFaaC7Rn9Oee5nXr1qG2thavvPJKzuMej4dJM0nB4/HA5/dZyXFXIpmWudLcm/5FN/J4PAgFQ2hPtMPn81t3J2QSi8WRVjXohgGlUxKg6QZ0w5Cmz9vj8aBiQCWaO1rzPt+abEPlHgPLHFV5ife/XuLoMJE0B4NyHEOrq2tQW1uLXbt2YZ99Jtkdji18Xh9SeSrNhmH070rzH//4x76Mg6hf8PsDMAps3GCoct1a7ExUSGSslHQVDkfQnmiXYhZxPiIpVjUdgU6b3WS30Jaj0gwAAwcOREt9/kpzc7IVwwaOLXNE5RUMhgCY22KXkjSL7bPF97ldMBjEwoV32B2Grby+ApVm666Ds5LmHu+pdq4a6bpe8B8iWfj9/qI9zXImzWzPEEKZ6UKyThkqtMGJTFtoC5UDq9CSpz3DMAw0d7SistLdleZg0JxPLZLhYsTrAoHuc63JnXxeH4w87w+RSIudeJ2ix2imTp2KN998EwCwzz77dKsiiT6ld999t+8iJHKQYCCIpJp/NTykTprNY4Ps7RlANlkOheSolnUlKs1dt9IWfc6ytGcA5jSEpkRLt57etlQCmq65flqC+CyUmjSrqprzfeR+Pl/+kXMikfb5+lFP86pVq6y/P/fcc30eDJHTBYJBGFr+262ibUPGKgnbM7JEsizrib94pVmepLmqqgppLY2OdBLhQPYiqrnDnOPt9qRZtCi9/fbb3W6zx+NxTJgwIecxkVzL+tmRkc/ng9HRfat5kUg7bVFoj0nzkCHZfdCHDRsGwKwkNTY2YuBAOVd6ktyCwSCM1gLtGaoBr9fruNW+5cBDQZa4JS3+lI0Yu9et0ixhe4aYw9vU0ZKTNDdlkuaqKndvZiGS31LvQIlKs6zrAWTk8/lg5NlB1HBoT3PJ0TQ3N+P666/HM888A1VV4ff7ccwxx+DKK69EZWX3LUKJ3CgUDAFNhXqadfglbM0wsT1DEHcaZE2as5Xm3FuuovIs0yxascPbrkQz9hiQ3SJ5V0Ikze6uNIs55aNHj8Yee+xR9PWqqiIQCDguUaK+4/f7gR7aM5zW01zy6p3LL78cyWQSTzzxBNavX48VK1YglUrhiiuu6Mv4iBwlGAwBauFKs4z9zADbMzoTSbOMbTqAWV1UFCVvpTkUCkmVEFVVmXsa7Eo05zzelGiG1+u15vS6lbhAEhXkYlRVlXK2ucwK9jTr/bCnubPXXnsNr7zyitWvN27cONx444345je/2WfBETlNMBgsPKdZ0xEKyVNFo/zEhZOM87oB88IpEonkTZqjElWZAaCyshKK4rXaMYRdiWYMrBzo+k2Beps0p9NpRCJMmmXi8/mAfNMzNGf2NJf8iR07diw+//zznMe++OILjBkz5isPisipgsGgNY+5K0PVpZkvWgjbM7JJcyDgrIN9OUWjse4LAVUdUYkWAQLmpj8DKwd2rzR3tKB6UE2B73KPQCAAv9+PdDpd0uvT6TTi8QF9HBU5ic/nt/qXO8tWmp11Z6rkaA499FCcddZZmDlzJvbYYw9s27YNK1euxMyZM7FkyRLrddwdkNwsGAxBL5g0GwjH5VzAIpJltmdkd0GTcTdAIRaLo7GtMecxVTekTIiqBw1C087cpHlXRzP2qZaj4BSNRktOmjVNk2q6CpUycq6fJs3r16/HyJEjsX79euuxESNG4M0337RmOXNLbXK7UCgEXdW6zV0FAKiG9JVmyh7kZS66x2Jx1H2Z+wtQNUOqRYBCdfUgbNr6pfW1buhoTrS6fnKGEI3GkEx2n46QTzqdtqavkBzM6RmFe5qdVnzgNtpEvRAKhQADgG4A3i5Js2ZIu6GF+UthewYAq09V5qJ7NBqFqnVNmnUpq4hVVdVo7miFbuhQPApaOtqgGzoGDRpkd2hlEY8PQFtba0mvTafTUo0kJJE0d+957/eVZsAcO/fCCy9gx44dGDx4MA4//HBUVFT0VWxEjiMqyYaqw+PNXRJgqPImzSJXZntGlszXD9FoLGchoGEYSKmapJXmami6htZkGwaE4tjVYbZqiMkabheLxUtaCKhpGtszJOTz+aHnXQioZp53VtJc8kLAtWvXYvr06fjjH/+IjRs34v/+7/9w5JFHYu3atX0ZH5GjiKTYSHfPiAxVkzhpzt/nLTO3T0boSTQaRTrTxgQAmm7AMAwpEyKRHDclWjN/yrGxiRCPx0vqaRavYaVZLsXaM5w2PaPkFP7666/Hddddh+OOO8567JlnnsEvf/lL/OUvf+mT4IicpnOluTPDMKCldWl3shJVVbZnAPvttz82bvw3Dj54mt2h2EZsaqFqOvw+L1RNvo1NBLGBSVNHM0ZgiDV+zu1baAuxWBypVCr/OpBORNIs42JRmfl8PhiG3u39IRJpp/U0l1wK2bFjB44++uicx4466ijs3LnzKw+KyKlCIXPDim4TNHQDMAxpd4HTMyOD2J4BDB8+EpdddjVGjx5rdyi2EclxOtPXLFo1RDItk+xW2tlKcyAQkOZ3EYvFYRhG0RaNVCqVeb18dyNkJpLirn3N/X5HwJkzZ2Lx4sU5j/35z3/GrFmzvvKgiJxKVJK7VZozX8tbaWbSTFnWphaZZFnmSnM8HofP60Nzpi2juaMFAyurpPmsxOOZbdWLtGhkK81sz5CJNW2oS4uGblWanZU0lxzNO++8g0ceeQT33XcfamtrsX37djQ0NGDy5MmYM2eO9bquiTWRmxRsz8j0OMva0ywqzWzPICBbURYVZlFxljFp9ng8qKysRHPSrDS3JNswcLAcrRlAtke51KQ5FmN7hkxEz3LXpLnfb25y6qmn4tRTT+3LWIgcLxzOVJrTuUmzaNcQz8uGyTJ1VqjSLEtLQleVA6vQ0mgmzc3JVuxROcrmiMqnt0mzrO8RWVmV5i4bnDh1G+2Sk+bZs2f3ZRxE/YKVNKu5SaLs7Rl6nm1QSV6RSAQA2zOEysqB+HT7hzAMAy0draisrLQ7pLIRPcqlJM3hcBher7ccYZFDZHuau1aanTlyrlfR7Ny5Exs2bEBjY2NOZYm7AJIsCvY0p0XSzPYMosJJc8S2mOxUUVGJ1mQbkmoKaU1FRcVAu0Mqm95UmjluTj7Z9ozuCwG9Pp/jev9LTpqfffZZXHLJJRg1ahQ+/PBDjB8/Hh988AEOOOAAJs0kDZ/PB6/X2609g5VmVpopKxgMwePx5EzPCAaC0s6urqioQCLVYY2bk2lTsEgkAkVRSkqaKyrkqcCTKdue0eWcqmmOm5wB9CJpvu2223DDDTfg2GOPxUEHHYQVK1Zg6dKl+PDDD/syPiLHCYZCBadnyNrTLJJmJs8EmBu7hEKhTpVmQ9rPBgAMGGAubtvRsjPnaxl4PB6Ew+GiSbOqqlwEKKHs9IwulWZdc1xrBtCLkXNffPEFjj322JzHZs+ejRUrVnzlQRE5WShf0sz2jJw/iSLhCNTM+0HVdUQkXuAlNuzYnkmaZdvAIxqNlZg0y/sekZXV05yn0uzvz0lzdXW1tZHJsGHDsH79emzZsoUnSZJOOBSGXqA9Q4ykk42WWcTB4wEJ4UjEqjRrmo5wWM5+ZiDb11vX1gBAzqS52OYmqqpKu1BUZgUrzZmeZqcpOWk+5ZRT8MYbbwAAfvCDH+DMM8/EzJkzcdppp/VZcEROFA5H8rRnGPD5fY68nVQOIlnWtJ5PjCSPSCQKLdPTrOryTs4AsknyzlYzaZZt17toNGpdWOdjGAbS6bTU7xFZFdrcxNA1x22hDfSip3nu3LnW32fNmoWDDz4YiUQC48aN65PAiJwqHA4DDV1GzqV1aavMAKDrotLM6RlkikQiyOTM0HS5e5rF7OGG9ib4vD4EAkGbIyqvaDTaY6VZ0zQYhiHtdBWZWdMz8sxpdtqMZqCEpPn0008vOvKjN7sA/uY3v8Gdd96JJ598EhMmTCj5+4icIhQKAV3mNOuqjoik/cyAefsdYHsGZYXDYWi6qDTL3Z4hKqgdahLx+ADHjdHqa+FwpMekWTzHSrN8eqw0O/DObdGITjnlFOvvhmHguuuuwzXXXLNbP+ztt9/Gv/71LwwbNmy3vp/ICYLBUN7NTWQdNwdkK81szyAhFMr2NKuqjnBY3ovKQCAAn8+X6duV7+Kh1KRZ5rsRshItGHqeSrPfgYWooklz150Ab7zxxt3aHTCVSuG6667DzTffjDPPPLPX30/kFOFwOO/IuXCFvAd8LgSkrsJhc+ScbhjQJK80A2bi2NLSjKiE1dRQKARN06Dret5Z3eL4IXPhQVbWLOaulWatn/c0/6duv/12nHDCCRg+fPhufX91tVwLJ8i5qqoqoKXNHjzrNqtqoGJAHDU1cu5oFQiYW996vR5pfweUq6qqApquW9XmQYMqpX5vxGNRtLQ0Iz4gJt3vYdAgc9MSTdN6TJr32KNKut+N7AKBzG6yXSrNMDSEw0HHvR/KkjSvX78eb731Fi6++OLd/nfU17dykRE5gq4rgGEAugF4s0mzovhQV9dib3A2aW9PAgA6EklpfweUS9fN5CiZNk+GquqR+r3h85uL/7zegHS/B1U1j5NageqhSJo7OnTpfjeySyQ6AOTpadZ0GEb5jxmK4umxSFs0aV67dm3O16qq4rXXXoNhZBPYQw89tMd/xz//+U989NFHOPLIIwEA27Ztw9lnn4358+fjG9/4RrEQiBxFTMkwVB0er5L5uyH1rUVubkJdic+DSJpl71cVGx/JuAGSOGYWGjsnepplnkAkK9Ge0fjOm2jZ8iGq95uG2IixgK7B6/XaHF13RZPmK6+8MufryspKXHHFFdbXHo8Hzz33XI//jrlz5+aMrJs+fTruvvtuTs+gfkmc/A3VADKTowxVkzxpZk8z5RKfh5RqvjdkT4jEf7+Mv4dg0DxQFkqaxXFDvI7kYU3PMLosru+vI+fWrFlTjjiI+g2r0pzZFdAwDGhpXcoKkpDd3KTwBgYkF/F5SEq+xbwgEsJAIGBzJOUXDJr/zYUuqsVxQ7b51QQoigJF8aJi/NdQc9Bh1uOGrjlyszBbImIiTv1ZKGQe2HUxQUM3AMOQukrCOc3Ulfg8sNJsEsmyjEmz32/+NxerNMv4uyHA6/N230bboe0ZJW+jTUSmzj3N5p/mbSWZK2nZnmZWmskkPg+ptJbztazGjh2HgD+A0aPH2B1K2YmkuVil2YmVRep7Pq8PRpf3hvQj54jcQpz8RbIskmeZK2lcCEhdic9DUmW/KgAcddSxOOqoY+0OwxbZDSzyHx90XYfP55dup0QyeX2+biPndF3PznB2EFaaiXqpe6WZSbNhZPu7iYBskpy22jPkTpplVlrS7Lxb8VQePp8vz8g5Z/Y0M2km6iW2Z3THSjN1ZfU0a7yolF2hCQmCYRiOnJRA5WG2Z2STZsMw2NNM5BZWe4aWac/QePtZnAyZNJMgJiGkVR0ej8eRJ0AqD5E0s9JM+Xh93tye5szfndjTzKSZqJfECm+2Z2RZBzy2Z1CGz+ezelQDgQD7VSUmelMLJc2GYTiyf5XKw+fNbc8QVWcnvieYNBP1kqIo5hVwl/YMVpoBnUkzZXg8HgQyUxPEnyQncZehUHuGUxd9UXn4fLnTM8Tf2dNM5BKBYDDbnsHpAFayzIWA1Jk/YN5e5fxduYmkeevWrXjjjTdQX19vPdfS0oLGxkZ4vUxHZOXrMj1DVJ2d2NLFdynRbggEAtn2DC50IspLzOf1M2mWWrHkh+0ZcvP5fFYfM5Btz3Bipdl5ERH1A8FgEO1qCkC2PUPqapqoMLPSTJ3IvAseZSmKWZ8bMmQIxo4dm/NcPB5HRUUFFwJKrFulOZNAs9JM5BLBYMiqMBuaOR3AiSt9y80Ak2bKEsmyzK1LZPa3K4rS40JAkViTfMxKMxcCErlWKKen2YCf0wEAAB7wd0BZYgGgnwsBpacohauGbM+Qm9ebO3LOcPC26kyaiXZDMBgC1OycZt5+JupO9DIzaSavV+lxcxMn3oqn8vB6vTk9zWB7BpG7BAJBQM+cADSDSTNRHqJlye93XsWIyovtGVSIt+uOgDqnZxC5SiAQADq1Z4jdz6QlWlPYokKdiK2RuUUyKYq3SKWZF1ay6taeYc1pZtJM5ArmyLlse4bsC51EPzdTZupMnPSc2JtI5cX2DCqkUNLsxAspJs1EuyEQCEC3pmcYCEpeaVZYaaY8RIWZk2XI6/UVSZqZjsjK6y00PcN5F1J8lxLtBr8/u7kJe5oBT6YfkX2J1JmoMDvx5Efl5fP1nDTzboS8fL7cSjMXAhK5TCAQgGEYMHQD0Ll5g9WewUozdSISIfY0k9fr7XEhoBNvxVN5mO+NTpVmg0kzkauIJNnQDEAzpB+pJSrMTJqpM3HSc+LJj8rL5/MVTJp1XWelWWKK4s1OowJ3BCRyHStJ1nQYbM+wkmW2Z1Bn2UozEyLZ+f3+gu0Zuq6z711i3SrNXAhI5C5WpVk3uLkJsskyk2bqzOMx3w9OrBhRefl8/iKVZibNsvJ6vYBhZC+qMu8TJ55PnBcRUT8gqiKGZibNsldJmDRTT5g0UyAQ6DFplv0YKjPr+JB5f4jpGU68Q8UzHNFusCrLmgGdPc1WRZFJM+XD9wX5/fmTZsMwmDRLTiTNYgGgqDg78WKbRzKi3SCSZF3VAcOQ/oAvZqwqDjzIEZH9ClWaNU2znic5WUmzeH9Y7RnOO58waSbaDVZ7RlrP+VpWopLoZUWR8uJUFdkFAgFoWk9Js9wbRMnMSo67tGc48Q6V8yIi6geySbOW87WsxEFPceBqZ3KC/FMTSB7BYChnQoIgqs/BIJNmWYk7laLS7OQ5zTzDEe0GsdJbz1SaZV/5nZ3Hy+twyjrooGn46KMPsO++k+0OhWwWDAahqmq3x0WlmUmzvETRRSTLYmYzk2Yil2B7Rq7s9AznHeTIPuPGjceVV/7S7jDIAUKhEHRdh67rObfdRdIcCoXtCo1s1n16hnMrzSwLEe0GJs25uPMbEfUkFAoByCbJgqg+i+dJPuIiqmt7BnuaiVxCzI80VLZnANkKM5NmIsonHI4AQLcWDVaaqevIOWTuRoidZp2ESTPRbuhaaXbiEPZyEr3MYl4zEVFn4bCZFHdNmsXXkUik7DGRM1htfZn5zIahO7LKDDBpJtotXRcCyt6eIQ56Ph8rzUTUXaFKs/haPE/y6To9A7oOD5NmIvfo3p4he6WZ7RlEVJioJBfqaRaVaJJPttKc7Wl26qJyJs1Eu8FKmtmeAaDz9AweUoiou2g0BgBIp9M5j6uqilAozGOHxLruCGjohmPHlzozKiKHUxQFiqKw0pwh/vu93NyEiPIQleau7RnpdJpVZskpirngz1oIaOhQHLo+xplREfUDXp8PhmouXOD0DLEQ0HmrnYnIfpFIFED+SnMsFrcjJHKI7DbamYWA7Gkmch+v12tVmmVfCJgdGcTtkomoO6/Xi2AwlLfSHIvFbIqKnKDbyDnDcOz6GCbNRLvJ5/NZPc2ytyWw0kxExUSj0W6VZk3TEI1GbYqInMDqZ++0I6BTe9ydGRVRP9D5Slj2nmanVgWIyDlisVjeSnM0yvYMmVk7Aoo7law0E7lP50RZ9qSZlWYiKiYWi+dUmg3DYHsGda80c3MTIvfpvPjPqVfF5SIWcrCnmYgKicXiOZVmTdOg6zrbMyTXbU0M5zQTuY+vU6Ise9Js7ejEpJmICohGYzmVZvF3Ts+Qm8cjzh/ZOc2sNBO5TOeWDNmTZnHQY3sGERUSi5lJs7i4ZtJMQKfzJ9sziNzLa23o4ZU+WXTqAY6InCMWi8EwDKtFQ/zJ9gy5dVsIqOuOLUTxTEe0m3zebNJMJrZnEFEhoqIsKsysNBPQqegi2jMMtmcQuY5oz1CYNFtkr7gTUWFiSoaoMDNpJqDAyDkmzUTuIirMrDQTERUXjZpJc9dKM9sz5MbNTYgkwKS5O7ZnEFEhXZNmVVURCATg9/t7+jZyue6VZvY0E7mOmCPp1A+3HdieQUSF5OtpFok0yatrTzMMw5rI5DTOjIqoH2ClmYiodJFIBEBuTzOTZrIqzXq2p9mp7Rll2/v3Jz/5CbZu3QpFURCJRHDVVVdh4sSJ5frxRF85n08kzXJvod0Z2zOIqCmOmVgAACAASURBVBCfz4dgMJjTnsEttKn79Azn9jSX7Wy/YMECxOPmrZlnn30WV1xxBZYvX16uH0/0lfNaI+ec+eG2A9sziKgnkUg0Z04zFwFS3ukZDj2vli0qkTADQGtrK0+u1O+JD7pXYXsGEVEpIpFIp6RZY3sGdao0Zzc3kb7SDABXXnklXnnlFRiGgfvuu69X31tdzQ8WOUssFgYABENB1NTIPWd0yJBBAIBRo4ZL/7sgosIqKyvw+eefAwBUNY3q6koeMySXTocAmKPmTAZCoYAj3xdlTZp//etfAwBWrFiBhQsX4t577y35e+vrW6Hr7Jck50ilNABmG1ZdXYvN0dhrzJiJOO+8CzF58n7S/y6IqDC/PwhN06Dreqbi7OMxQ3KaZp5LrZ5m3UA6rdvyvlAUT49FWlvq37NmzcLrr7+OxsZGO3480VdCjJxTHNp7VU4+nw8HHXQIgsGQ3aEQkYOFwxFommYlSmKiBslLtOt2ntPs1PaMskTV1taGL7/80vp6zZo1qKioQGVlZTl+PFGfEKPmfJyeQURUEtHTLPqaw2EmzbLrPj1D8pFziUQCF1xwARKJBBRFQUVFBe6++24uBqR+TXyoFS4EJCIqSTgcQTqd7pQ0h22OiJxAUbzZhYCyJ82DBg3CY489Vo4fRVQ21vQMtmcQEZUkFArBMAxrVnMoxKSZzF5isbmJk+c0OzMqon4gW2nmx4iIqBQiSU4mk5mvuQ6CAI+iZLfR1p1baXZmVET9QHb7bLYZERGVQrRjZJNmVprJLD6JhYCsNBO5kFM/1ERETiUm7KRSKQCsNJNJUbzZOc0O7ml2ZlRE/UD2Q8354UREpQiFggCyleZgMGhnOOQQiqJYCwENXXfsAnsmzUS7yalXwkRETiUqzWIhIGe7EyCSZuePnHNmVET9gFM/1ERETiUqy6lUCh6PB36/3+aIyAkUj4c9zURu5tQPNRGRUwUC2aQ5EAhwvwYCwOkZRK4nPtQGW5qJiEoSCAQAAKqqWn8nUhQFhm7AMAxWmoncSHyoWSghIiqNaM8wDMOqOhNZCwEzVSgmzUQu4/Hw40NE1Bt+fyDv30lu5pxmnUkzkVuxPYOIqHc6L/xjewYJXq8XMHQzcUbnzcOchUkz0W5iewYRUe8oimIlRJzRTILV05zZ4MSpd3KdGRVRP+DUDzURkZOJajPHzZGgKF62ZxC5mVM/1ERETubzMWmmXFwISORyimL2ZbCnmYiodCJZ9vl8NkdCTuH1egG9c0+zM9NTZ0ZF1A+Iofwczk9EVDqRLIuKM5FXUcwZzZmeZlaaiVyGPc1ERL3HnmbqquvIOaeeX50ZFVE/wAozEVHviQoz2zNIyLZnsKeZyJVETzPApmYiolKx0kxdeTyZhYA65zQTuZSny59ERFSMqDB7vaw0k8nrNZNmsRBQUZg0ExERkeREe4ZTq4lUflZPMxcCErkd2zOIiErl83kzf7LSTCZF8WYqzeb5lCPniFyL7RlERKUzj5msNJOgKIpZZWZ7BhEREZFgVhNZaSbB682d0+zUCyomzURERFR2Tk2MqPwUxQvoWqeFgM68g8ukmeg/xp5mIqLSsT2DcimZHQGhiznNznxvMGkm+o8584qYiMjJnJoYUfl5vd4uI+ecmZ46MyoiIiJyNVaaSVAUxexnZk8zkduxPYOIqLecmhhR+Xm9Xhi6xm20idyP7RlERL3l1MSIyk/MaWalmYiIiMgiNrBwZmJE5SfaM9jTTERERJTh9FvwVH5er0iazfeGx+PM94YzoyLqByorKwEAEybsZXMkRET9h8djtrQxaSZBUbyZkXNmpVlste403I6HaDeNGTMO8+ffjNraIXaHQkTUjzBpplzmQsDO7RlMmolcxePxYOjQ4XaHQUTULzn1FjyVn3kBZcDQNADO7XfnO5aIiIjKzsPBQ5QhkmRDUwE49y6EM6MiIiIiIimIJNlQzaSZlWYiIiKiDIP7QlGGSJJ1tmcQERER5WJ7Bgli4V+2PYNJMxERERFRDq83057BnmYiIiKiXGzPICFbaWZ7BhEREVEOtmeQkO1p5kJAIiIiIqK8uk7PYHsGERERUQbbM0joPKdZURRrq3WnYdJMREREZWRmyw7Ni8gGoqdZzyTNTuXcyIiIiMh1/P5A5m/MmsmUW2l2Zj8zAPjsDoCIiIjkMXPmSUin05gwYW+7QyGHsJJmVYXHwZVmJs1ERERUNiNHjsKFF/7c7jDIQayFgJrm2MkZANsziIiIiMhGndszmDQTEREREeUhdgTkQkAiIiIiogKsHQFVZ1eay9LT3NjYiEsvvRRbtmxBIBDAqFGjcN1116GqqqocP56IiIiIHKrzjoBOTprLUmn2eDz40Y9+hNWrV+PJJ5/EiBEjcNNNN5XjRxMRERGRg2V7mjVHj5wrS9JcWVmJQw45xPp6ypQp+OKLL8rxo4mIiIjIwaz2DIf3NJd95Jyu6/jzn/+M6dOn9+r7qqtjfRQREREREdmlrS1u/sUwEAr6UVMTtzegAsqeNF9//fWIRCL4n//5n159X319K3SdG9UTERERuUlTU4f1d93woK6uxZY4FMXTY5G2rEnzggUL8Omnn+Luu+92dPmdiIiIiMqj8+I/Jy8ELFvSfMstt+Ctt97CPffcg0AgUPwbiIiIiMj1OhdSvQ4uqpYlaf7ggw/w+9//HqNHj8Zpp50GABg+fDjuuuuucvx4IiIiInIoVpo72XPPPfHee++V40cRERERUT/Secyck5Nm59bAiYiIiMj1OrdnSD+nmYiIiIgoH6+3c9Ls3NTUuZERERERkeuxPYOIiIiIqIjchYDOTU2dGxkRERERuV5uT7NzU1PnRkZERERErte50syFgEREREREeXg8Hng8HgDsaSYiIiIiKki0ZbA9g4iIiIioANGWwaSZiIiIiKgAJTM1g+0ZREREREQFKB7RnsGkmYiIiIgoL8XL9gwiIiIioh5xISARERERURFMmomIiIiIimDSTERERERUBJNmIiIiIqIiPDB3BGTSTERERERUiJkzc04zEREREVExrDQTERERERXh8Tg3NXVuZEREREQkFVaaiYiIiIgKyLQ0M2kmIiIiIiqGSTMRERERURFMmomIiIiIimDSTERERERUEDc3ISIiIiIqwgDApJmIiIiIqCjOaSYiIiIiKoKVZiIiIiKiIhTFU/xFNmHSTEREREQ2M5Nlj4dJMxERERFRAVwISERERERUEi4EJCIiIiIqiHOaiYiIiIhKwp5mIiIiIqKC2NNMRERERFQSVpqJiIiIiIrgnGYiIiIioqKYNBMRERER9Yg9zURERERERbCnmYiIiIioCCbNRERERERFMGkmIiIiIiqIOwISEREREZWElWYiIiIioqKYNBMRERER9YibmxARERERFcWkmYiIiIgoL1FhdnBLM5NmIiIiIrLXd787C1VV1aiqGmR3KAV5DMMw7A6iFPX1rdD1fhEqEREREfUziuJBdXWs8PPlCGLBggWYPn069tprL7z//vvl+JFERERERF+ZsiTNRx55JBYvXoxhw4aV48cREREREX2lfOX4IQceeGA5fgwRERERUZ/gQkAiIiIioiLKUmn+KvTUmE1ERERE1Jf6TdLM6RlERERE1FccMT2DiIiIiKg/K8uc5l/96lf461//ip07d2LgwIGorKzEqlWrevXvYKWZiIiIiPpKsUozNzchIiIiIumxPYOIiIiI6D/EpJmIiIiIqAgmzURERERERTBpJiIiIiIqgkkzEREREVERTJqJiIiIiIpg0kxEREREVASTZiIiIiKiIpg0ExEREREVwaSZiIiIiKgIn90BlEpRPHaHQEREREQuVSzX9BiGYZQpFiIiIiKifontGURERERERTBpJiIiIiIqgkkzEREREVERTJqJiIiIiIpg0kxEREREVASTZiIiIiKiIpg0ExEREREVwaSZiIiIiKgIJs1EREREREUwaSYiIiIiKsJndwBO1traik8//RRf+9rX7A7FFhdddBF+9rOfYcSIEd2eu/DCC3HLLbfYEBU5SSKRwLZt26BpmvXY+PHjbYyInGDz5s3YtGkTUqmU9disWbNsjMgeTz/9NA477DDEYjHcfvvt2LBhA+bNm4d9993X7tDIZi+//DLeffddJJNJ67HzzjvPxoioFEyaC3jxxRdx9dVXw+v1Ys2aNdi4cSPuuusu3H333XaHVjbPP/881q5di/nz5+Pwww/Pee7jjz+2KSp7bdq0Cddcc023hODdd9+1MSp7LF68GDfddBMqKyvh8XgAAB6PB88995zNkZXfJ598gssvvxzbt2/HmjVr8Pbbb2PNmjX4f//v/9kdWtk9/PDDePTRR1FXV4dJkyZh3bp1OOigg6RMmn/3u9/huOOOw4YNG/Dyyy/jzDPPxK9+9Ss88sgjdodWdjx2Zt10003YuHEjPvzwQxx55JF47rnncOihh9odli1UVcXSpUu7XUDMnz/fxqgKY3tGAXfccQeWLFmCAQMGAAAmTZqELVu22BxVeY0cORJ33nknrrrqKvzmN7+xOxxHuPbaa/Gzn/0Mo0aNwosvvoi5c+di3rx5dodliwceeABPPfUUnn/+eaxZswZr1qyRMmEGzPfFueeei3g8DgCYOHEi/vKXv9gclT0ee+wxPP744xgyZAjuv/9+PP7444hGo3aHZQufz6xLvfLKKzjllFMwY8aMnMRAJjx2Zr344ou4//77UV1djeuuuw7Lli1DU1OT3WHZ4uqrr8abb76JF154AaNHj8Zbb72FUChkd1gFMWnuQU1NTc7XgUDApkjs4fF4MHXqVCxZsgSvvvoq5s6di9bWVrvDslUqlcKhhx4KwzAwePBgzJs3D6tXr7Y7LFvU1NRg2LBhdofhCC0tLTjssMOsiruiKPD7/TZHZY9AIIBIJAJd12EYBiZMmIBPPvnE7rBs4fF48PTTT+Ppp5+2KonpdNrmqOzBY2dWIBCAz+eDx+NBOp1GbW0ttm3bZndYtti4cSMWLFiAeDyOH//4x/jTn/6EDz/80O6wCmJ7RgHRaBQ7d+60ToKvv/66VUWSzeDBg/Hwww9j/vz5OPHEE3HHHXfYHZJtvF4vAKCiogKbNm1CbW0tGhsbbY7KHl//+texcOFCHH/88QgGg9bjMvY0e71epNNp63ixfft2KIqcNYlwOIx0Oo29994bixYtwpAhQ6Drut1h2eKqq67Cvffei5NPPhkjRozAJ598gkMOOcTusGzBY2dWNBpFIpHA/vvvj8suuww1NTWOrq72JXHu8Hq9SCQSiMfjqK+vtzmqwjyGYRh2B+FEGzZswDXXXIOtW7di7733xieffILf/e53Ui3gmDVrFlasWJHz2BNPPIH58+dD13X84x//sCky+zz44IOYNWsWNm7ciAsuuAC6ruP888/H2WefbXdoZTd9+vRuj8na07xixQo888wzeO+993DSSSdhxYoVmDdvHr773e/aHVrZvf/++xg+fDgSiQRuueUWtLS04Nxzz8XEiRPtDo1sxGNn1s6dOzFgwABomoYHH3wQLS0tOOOMMzB06FC7Qyu7s88+G7fccgvuu+8+rF+/HgMHDkRraysefPBBu0PLi0lzD1paWvDmm28CAPbff3+rv1kWd9xxB84///xuj7/77ru4+eabcd9999kQlXOk02kkk0nEYjG7QyEHWLduHZ5//nkYhoHp06fjwAMPtDskshkXiObHYycJmqbB6/VC13WsXLkSra2tmDVrlmPfG0yae9DQ0IB///vfAID99tsPVVVVNkdEdluxYgWOOOIIVFRUAAB27dqFv//97zjhhBNsjsw+9fX1OYubZKyWCG1tbQAg5cK3P/zhD/j+97+PhQsX5n3+0ksvLXNE9vvBD36As846CzfffDOeeOIJ6LqOGTNmYNWqVXaHVnY8dgKLFi3CJZdcgvPPP99q5ers9ttvtyEq6g32NBfw17/+FVdddRX23XdfGIaBK664Atdffz2+/e1v2x1a2RT6YAPmbfjbbrutzBHZ74EHHsgZnVVZWYkHHnhAqgO/sHbtWlx22WWor6+HoihIp9OorKzE2rVr7Q6t7D766CNceuml+OCDDwAAEyZMwIIFCzBu3DibIysf0ZsYiURsjsQ5xAJRMdNe5gWiPHYCU6dOBQAcccQRNkdiv0suuQSLFi3CSSedlDfPWLJkiQ1RFcekuYBbb70VjzzyCMaMGQPAvM127rnnSpU05/tgt7S04A9/+IO0Czjy6byxh0wWLVqEhx56CPPmzcPy5cuxZMkSbN261e6wbHH55ZfjjDPOwMyZMwEAK1euxOWXX47HHnvM5sjK57TTTgPADRo64wLRnsl27BTrQGbPnm1zJPb7/ve/DwD4+c9/bnMkvcNPbwHBYNBKmAFg9OjR0q1unT17tvXP8ccfj/r6etxzzz341re+hb/97W92h2eLmpoa/PWvf7W+Xr16Naqrq22MyF5jxoyBqqrweDw45ZRT8NJLL9kdki3a29sxa9YseDweeDwezJw5E4lEwu6wbCEWNgFmNemYY47Byy+/bHNU9jj99NNx3nnnobGxEXfeeSdOP/10nHXWWXaHZQseO7NuvPFGtLS0QFVVnH766ZgyZQqeeOIJu8MqKzFU4eCDD7b+mTJlCsaMGYODDz7Y5ugKY9JcwJFHHonf/e53qKurw44dO3D33XfjyCOPREdHh1QnQ13X8eijj+I73/kO3n//fTzyyCO46qqrpD3YXXHFFbj55ptx1FFH4aijjsKtt96Kq6++2u6wbCE2bqitrcWaNWvw3nvvSTug/2tf+xrWrVtnff3GG29INWmns2XLliEej+O1115DQ0MDbrjhBqs9QTazZs3COeecg+OPPx6JRAILFiyQcqIKwGNnZ6+++iri8Thefvll1NbWYvXq1XjggQfsDssW8+bNQ0tLCzo6OjBjxgwcf/zxuP/+++0OqyC2ZxRw1113AejemP+b3/wGHo9Hiq0/n3nmGdx+++0YM2YM7r33Xuy55552h2S7cePG4emnn7a2ER8zZow1f1Q2Z555JpqamnDBBRfgoosuQktLCy6//HK7w7LFpk2bcMYZZ2DkyJEAgM8++wwTJkzAySefDMC5/Xl9QXweXn/9dcyYMQMHHHAAZF1v/sQTT2DmzJk5k1TEY7LhsbO7f/7znzjqqKNQW1tbcP2Q23388ceIx+P4y1/+gkMOOQSXX345Tj31VMeOImTSXMCmTZvsDsF28+bNw9ChQ+H3+/Nuoy3TSt9UKoVAIGDdZRA74aVSKQDmhg6yERWzyZMnS9uuI1x55ZV2h+AYoVAI99xzD1atWoXFixfDMAxpd8F76KGHuiXI+R5zMx47u6uursY111yDl156CXPnzoWqqtL1dwuqqgIwLyAOP/xwhMNhR/f9M2nuQWNjozVybsqUKaisrLQ5ovKaP3++3SE4xn//939j+fLl2H///XMqAoZhSHPnoatEIoG7774bW7duxc0334yPPvoIH3/8sVSLZQXRg9fe3g5A7gkS8+fPx5/+9CdcfPHFqKmpwZYtWzBjxgy7wyqrjRs3YsOGDWhsbMTixYutx1tbW6W7gOCxs7ubb74ZK1euxOzZs1FRUYGtW7fihz/8od1h2WLcuHH40Y9+hM2bN+Oiiy5CR0eH3SH1iHOaC3jppZdwySWXWLtYvffee1i0aBH+67/+y+bInGHdunXcvEFyP//5z1FTU4Pnn38eq1atQltbG+bMmdNtF0kZfPbZZ7jooovw7rvvwuPxYJ999sGiRYswYsQIu0Oz3bZt27B06VL89Kc/tTuUsnn22Wfx3HPPYc2aNTk7Z0ajUcycOROTJk2yMTpymjfeeANLly7FDTfcYHcoZdfR0YGXX34Ze+21F0aMGIHt27fj/fffxze/+U27Q8uLleYCbr31VixevNias/rRRx/hkksukTpp3rFjB5YvX45ly5bBMIycldAy0DQNJ598MpYvX253KI7w3nvvYcGCBdZkhGg0Cl3XbY7KHldffTVOPfVUnHTSSQDMxXBXX321Y7eC7WupVArPPvssli5dirfeeku6uw/f/va38e1vfxsvv/wyvvGNb9gdju147Oyurq7OOp96PB7p7sYIoVDIOj6kUim89tprWLZsGZPm/kZV1ZyNCcaNG2f13shEVVU899xzWLJkCTZs2ABVVXH//fdjypQpdodWdl6vF5FIBMlk0trIQWaBQCDn62QyKe2Cr4aGBmvRHwCcdNJJePjhh22MyB7vvPMOlixZgmeeeQYTJ07Epk2b8NJLL3V7r8jiG9/4BjZv3oxNmzZZPbwAcjb5kAGPnSZN07BmzRosWbIE//rXv/Cd73wHbW1t0o7qFDZs2IAlS5Zg9erVmDRpkqPnWDNpLqCqqgrLli3DiSeeCABYvny5dNto33DDDVi1ahX22msvzJ49G3feeSeOO+44KRNmYcyYMZgzZw6OPvronL7VOXPm2BiVPQ488EDcfffdSKVSeP311/Hggw/m3IqWiaIo2Lx5M8aOHQvAXBEu22SA2bNno729HbNnz8by5cuxxx57YPr06dImzADw8MMP49FHH0VdXR0mTZqEdevW4aCDDpIuaQZ47ATMi6hRo0Zhzpw5uP322xEKhXDkkUfaHZYtGhoasHLlSixduhTpdBqzZs1COBzGfffdZ3doPWLSXMB1112Hiy++GNdeey0AYOLEibjpppvsDarMHn30UUyZMgVz587FtGnTAEDasTiCpmnYc889sXnzZrtDsd28efNw3333IRqNYtGiRZg+fTrmzp1rd1i2mDdvHubMmWOtgdi0aRMWLlxoc1Tl5fP5kE6nkUqlrLtysh8vHnvsMTz++OP43ve+h/vvvx/vv/++Nc5UNjx2AocccgjWrl1rzWd28iYefe2www7DgQceiF/+8pc44IADAACPP/64zVEVx6Q5D03TsHbtWjz22GNoa2sDYPZryuall17Ck08+iYULF6KpqQmzZs2SdizOAw88gLPOOgsnn3wypk6danc4juD3+3Huuefi3HPPtTsUW+m6jsGDB2PVqlXWtJ399ttPujtTjz/+OD788EMsXboUp512GsaMGYP29nYkEgkpx4oBZgtTJBKBruswDAMTJkzAJ598YndYZcVjZ9Ztt92GpqYmPPnkk5g/fz6amprQ2tqKzz77TLpFw9///vexcuVK3HLLLTjppJNw9NFH2x1SSTg9o4ATTzwRy5YtszsMx9i0aROWLl2Kp556CmPHjsWMGTNw2mmn2R1W2YhbzuJPMsdn/fa3v8Vrr70GADj00ENx7rnnIhaL2RxZ+c2YMQNPPvmk3WE4hqqqeOGFF7BkyRKsW7cOhx12mJS7As6ZMwcPPfQQrrjiCtTU1GDIkCF47LHHpHqv8NhZ2DvvvGOdV0ePHo1HH33U7pDKStd1vPjii1i6dCn+8Y9/QFVV/Pa3v7XubDsRk+YCFixYgP322w/HHHOM3aE4SjqdxrPPPotly5bh3nvvtTucsjnttNNQWVmJN998E4ceemi352Xa6EU4//zzEYvFrAVwy5YtQ3NzM+644w6bIyu/8847D5dddhmGDx9udyiOU1dXhxUrVuCcc86xO5Sye//99zF8+HAkEgnccsstaGlpwbnnnmu18ciAx87ixLSZ4447zu5QbNPQ0IAVK1Zg+fLlaGpqwt///ne7Q8qLSXMB06ZNw65duxAKhRAOh61B7GvXrrU7NLLBrl278Oqrr2LRokU4//zzuz3v5NW+feXYY4/FM888U/QxGfzwhz/Ev//9b0ydOjVnkRMTArmtXbu2W6KY7zE347GTemvDhg2YPHmy3WHkxZ7mApYuXWp3COQglZWVOO6441BdXY1DDjnEelxs3CCjwYMHo6GhwerdbWxsRG1trc1R2eOEE07ACSecYHcY5DALFy7s1pKQ7zE347GTesupCTPApLmgYcOG2R0COdAhhxwi/cYNYirEwIEDMXPmTBxxxBEAgBdeeEHaXSJZLaPOPv30U3zyySdobW3Fiy++aD3e0tKCRCJhY2T24bGT3IBJcwHTpk3LOy6J7Rny4sYNJtF+MH78eIwfP956/NRTT7UrJNudf/75eY8XMrZnPPHEE5g5c2bRx9zszTffxLJly7Bz586cubOxWAyXXXaZjZHZg8fOXPfee2+3Hv98j5HzsKe5gM8//9z6ezKZxJNPPgmfz4ef/vSnNkZVXsXmzF566aVlisR+nTdumDVrlrVxw5o1a+wOjRyg8+32ZDKJ1atXY9y4cfjFL35hY1T2yDclQdbJCZ03yJIVj53d8TPSXSqVyhlp69Qxlaw0F9C1PeOCCy7AqaeeKlXSLCqKW7ZswT//+U8cddRRAIBnn30WBx10kJ2hlR03buiu68i5adOm4Sc/+YmUI+e6tmeceOKJOPvss22Kxh4bN27Ehg0b0NjYiMWLF1uPt7a2Ip1O2xhZ+TU0NCAcDlsJ87p167B69WqMGDECc+bMkWq3SB47s1555RW8/PLL2LFjR05RqrW1FbLWL//2t7/h+uuvR11dHQBYQxfeffddmyPLj0lziT777DPU19fbHUZZnXfe/2/v3uNyvP8/gL/u7kqp1kTkEJrDYg5FopGS/EakFCNmfGfOh+Y0W0iYNcvMYYeGzfB1GqWT0zaHZtNKDivU2LCaaHSgm453/f7o26VbJUx97lyv5+Phsbou7JUHd+/7c70/788MAMCbb76J0NBQNGjQAAAwdepU+Pr6ioxW63hwQ0V+fn4wNjaWVlNDQ0Ph5+cny5FzD1MoFEhPTxcdo1alp6fj/PnzyM3Nxfnz56XrRkZGCAwMFJis9k2fPh0rV65Ey5YtceXKFUycOBEeHh744Ycf8Pfff8PPz090xFrD184H9PT0YGRkBIVCoTFlp3HjxrI9TfXjjz/GmjVrCwonZwAAIABJREFUYGNjAx0dHdFxqsX2jCqU72kuLi5GUVERFi5cKMtHbW5ubjhw4EC11+SCBzeU4si5B8r3NJeUlOD333+Hg4MDAgICxAYT4Oeff0afPn1ExxBq8ODB2L9/PwBg/fr1SEtLQ2BgIPLz8+Ht7Y2oqCjBCcXga2epS5cuoX379qJjaIXhw4dj7969omM8Nq40V6H8KBxdXV00atRIVo/Uymvbti0WLlyocYhF+Q1gcqOrqwtXV1e4urpKBzfIEUfOPVA2QQQAlEolJkyYgK5duwpMJM7du3ehUqlgbGyMtWvXIiEhAbNnz0anTp1ER6s15Te4nTt3Dp6engCAevXqQVdXvt92+dpZ6pdffkHTpk1hYmKC+fPnIzExEYsWLZLVm82yKTIDBgzAjh074Obmhnr16kn3tfUpBFeaH5KWloZmzZpVeu/ChQt45ZVXajmReCqVCp9//jliY2MBlI4Omj59uix7V+nBBtG0tDScPn26wsg5Oa4c0QNlR4onJCRg+fLlePPNN7F9+3bs2rVLdLRaM3bsWLz99tto0qQJfHx88P3338Pc3BzFxcUYPHiwLJ/G0ANl/0Z+/fVXbNy4EdOnT8cHH3yA0NBQ0dFqjbW1NRQKhUYvd9nn7GmuQ6ZPny7tYH34scGiRYtkubvV2NgYCxYsEB2DtARHzj3w1ltv4ZtvvgEABAQEaLRjyHU3fNlK6i+//IIRI0bA3d1d+jOSi4ULF2LevHlIT0/H9OnTYW5uDgA4duyYrFbcqXJlT61jY2Ph7u6Obt26yW4jYHJysugIT4VF80PK/8Ut2+lb2T05yc/PR0REBFJTUzX+TOQ0co4eKNsgSqVTEsr89ttvGvfk+nqhUChw4MABHDhwAF988QUAyG56hrW1daV9y/3790f//v0FJCJtYmBggA0bNmD//v3Yvn07SkpKZPdvpMyKFSuwcOHCaq9pCxbNDyk/CufhsThyHZPj6+uLwsJCdOnSRbbD6OmBgwcPYtCgQRpjxcobM2ZMLSfSDg8XyXJ9vVi8eDE2btyI4cOHw9LSEteuXdM4PplI7gIDA7Fjxw7MmzcP5ubmSElJgbu7u+hYQsTHx1e4durUKQFJHg+L5ofk5+fjzz//RElJicbHZffk6K+//mIP3v9cuXIFX375ZYVV97q0+/ffunz5MgYNGqQxVkyuHvUmW65sbW2lFWYAaN26NRYvXiwwEWkDvnY+YGVlpbGS2rJlS0yePFlgotp38OBBHDx4ENevX9cYYatSqWBgYCAw2aOxaH5IXl6exlGW5T+W6zdFS0tLaTe83M2ZMwcDBw6El5eXbKepzJo1C8XFxRg4cCCcnJxExxHq0qVLcHBwAFA6NaLs45KSEqhUKpHRhCkqKkJISAiSkpI0FhrkNquZNPG184GcnBxs3Lixwr+RrVu3CkxVu6ysrODs7IzExEQ4OztL142NjaXXUW3Eovkhcj7asyomJibw9vaGo6OjRnuGHHuai4uLMWXKFNExhNPR0cGaNWtkXzR///33oiNoHX9/f6jVasTGxsLHxwdRUVGws7MTHUuI8PBweHh4VHtNDvja+YCfnx/atGmDa9euwdfXFyEhIbKbzGVtbQ1ra2u4uLjgxRdfFB3nsbFopmpZWVnByspKdAytYGNjg+TkZFhbW4uOIpy1tTUSEhLQpUsX0VGEad68uegIWicxMRGRkZFwd3fH5MmTMXr0aEybNk10LCG+/fbbCgVyZdfkgK+dD/z1119Yv349jhw5giFDhuD//u//8Oabb4qOJYS/v3+lT/HXrl0rIE31WDRTtTgtAfD29oZCoUBRURFCQ0NhZWWlMYhdjn15Fy5cgI+PD1q1aqVxJKwc/yzogbJ/F0qlErm5uTAxMUFGRobgVLUrMTERCQkJyMrK0tgwq1KpZDslISEhga+d/1P2xFZPTw/Z2dkwNTXVmMQjJ+UPhsrPz8fhw4fRpk0bgYkejUUzPZaff/65Qv+VnIppzqmuaNGiRaIjkBYyNTXFnTt34OjoiIkTJ6JBgwayOykyPT0d58+fR25ursaGWSMjI9n2dvv5+YmOoDVat26N7OxsuLu7Y+TIkTAxMZFde0aZYcOGaXzu5eWFCRMmCEpTPZ4ISNVatWoVEhMT8ccff6B///44cuQIHBwcsGrVKtHRah17FIkeTa1WQ6lUori4GJGRkcjJyYGnp6csNxL//PPPsjoamZ5cfHw8cnJy4OjoKOsj1ssUFhZi8ODBWrtfhEVzFXigxwPu7u7Yt28fvLy8EBERgfT0dCxatAgbN24UHa3WVXbKm1xPfuMOcE0pKSlISUmBWq2Wrsl1o6RKpcJff/0l29Wz8mJiYpCSkqLxfUSOs8z5egGkpaWhWbNmld67cOGCLP+9zJo1S+ppLikpwe+//w4HBweN01W1Cd/WVIEHejygr68PXV1dKBQKFBYWokmTJrh586boWLWKPYoVcQf4A5988gn27NmDNm3aQEdHB0DpiEo5Fs3R0dHw9/eHUqnE0aNHkZiYiM8//xzBwcGio9W69957D+fPn0fHjh1lP2aNrxfA9OnTpQWW4cOHa/RzL1q0SJaLL+V7mpVKJSZMmICuXbsKTPRoLJqrwAM9HjAyMkJubi5sbW3x3nvvwdzcXKuHj9cE9ihWxB3gDxw6dAg//vijLFsQHrZu3Trs3btXmnHfuXNnpKSkCE4lxtmzZxEVFQU9PT3RUYTj64XmqaHlnzw8fE9Oynqa79+/DwAam8q1EYvmKvBAjwdWr14NpVKJBQsWYPPmzcjJydHacTA1xdXVFS4uLjh27Bj69+8vOo5W4A7wB8zNzflaUY65ubnG53J9WmdhYSE6gtbg68WjTxCV6+FpqampmDt3LpKTkwEAHTt2RFBQECwtLQUnqxyL5irwQI8HGjVqJH0s13mrQOmBHp999hmL5v/hDvAHbGxspBPPyo/TkmN7hpGREW7fvi0VAbGxsTAxMRGcSozWrVtj/PjxcHV11fg+IseeZr5elO6V+vPPP1FSUqLxcdk9OfL398frr78Ob29vAEBoaCj8/f2xefNmwckqx42AVfjss88qvS6nMWtU0fvvvw8fHx9ZH+hRGbnvAB87dmyFawqFQlabnMokJCRgyZIl+Pvvv2FtbY1r167hyy+/RKdOnURHq3Xvv/9+pdfl2tJVRq6vFy4uLlXeUygUOHLkSC2m0Q4eHh4IDw+v9pq2kM/f1iegVqtx8+ZNfPDBB6KjkJbhgR7A5cuXcevWLbz66qvSNTs7O/zyyy+4du0a2rZtKzBd7VOr1RgyZAhGjhwpOopW6NKlC7Zu3YozZ84AAGxtbfHCCy8ITiWG3IvjMmq1GsOHD5c2usn1WPWjR4+KjqB1dHR0cOXKFbz00ksAgKtXr2r1plkWzZVQKpX4/fffRccgLcQDPUonRbzzzjsVrjdq1AirVq2S3ZQEpVKJ3bt3s2gux8TEBA4ODtL4vdzcXBgaGgpOVftyc3Px1VdfITU1FZ988gn+/PNPXL16Fa6urqKj1SqlUon69esjPz9fo32JaPbs2RgzZgw6dOggjZz7+OOPRceqEovmKvTq1QvLli2Dp6enxoqi3FbRyuTk5ODq1asafVc9evQQmEgMe3t7AHVnp29NuH37NqytrStcf/nll3H9+nUBicTr2bMnDh06hIEDB4qOItz333+PDz74ALdu3QJQOhVAoVAgKSlJcLLaFxAQAHNzc2mTk4WFBebOnSu7ohkArKysMGbMGLz22msar5ty7O+mB/r27Yv9+/fjt99+AwB07doVZmZmglNVjUVzFfbv3w8AOH78uHRNrj1HBw4cwMqVK3H37l00btwYKSkpsLa2luVMybKdvklJSVAoFFq/07cm5OTkVHlPrjOr9+3bh82bN8PAwACGhoZSoRgTEyM6Wq0LCgrCmjVrYGNjI82slqvff/8dK1euxM8//wygdJNkcXGx4FRiqNVqtGvXDleuXBEdhbSMmZkZunfvjri4OPzzzz8smusi9h49EBwcjNDQUEyYMAFhYWH45ZdfcPjwYdGxhKhrO31rgpmZGS5evIiOHTtqXL948SJefPFFQanECgkJER1Ba5iamqJbt26iY2iFh0ft5efny3YeL/u7qbx58+bh7bffhrW1NbKzs+Hh4QFjY2NkZWVh9uzZGDFihOiIlZL3MkA1YmJi8N///hcAkJGRgatXrwpOJIauri4aNmwo9Sf27t0biYmJglOJkZmZieHDh0OhUEChUMDb21t2s0anTZuGadOmYc+ePUhOTkZycjL27NmD6dOny3YkYfPmzWFqaors7Gw0b95c+iEnubm5yM3NxYABA7Bjxw5kZ2dL13Jzc0XHE8LOzg7BwcEoKChAbGwsfH19HzlB4Xl35coVHDhwAGFhYdIPkqeLFy9KbX7h4eFo06YN9u/fj9DQUKnu0kZcaa7Chg0bEB0djVu3buGNN95AYWEh/Pz8sHPnTtHRap2+vj5KSkrQqlUrbNu2Dc2bN5d6euWmru30rQmOjo744IMP8MUXX2DFihUAgFdeeQXLli2Do6Oj4HRi8Ojo0ikZCoVCWkldtmyZ9Llce5pnz56NTZs2wcjICEFBQXBxccGkSZNExxJi69at2L17N27duoXOnTsjPj4ePXr0gKenp+hoJED5DaGnT5+W+vwtLCy0+qAXFs1ViIqKQkhIiPSIwMLCAiqVSnAqMXx9faFSqTBv3jwEBAQgJycHS5YsER1LiPI7fQEgOTlZq3f61pQ+ffqgT58+omNoDR4dDWmzGz2gp6eHqVOnYurUqaKjCPfdd99hz5498PHxwddff41Lly7h888/Fx2LBEpPT4epqSni4uIwa9Ys6bo2H/TCorkKBgYG0NPT07imze9+apKDgwOA0jFS3377rdgwgvXt2xdRUVFISEgAoP07fan28OjoUitWrMDChQurvfY8q+6NtBxPltXX10f9+vVRXFyMkpIStG/fHteuXRMdiwSZNGkSPD09oaenh+7du0uTyc6dO4dmzZoJTlc1Fs1VsLCwQHx8PBQKBYqLixEcHIx27dqJjiXEBx98gBkzZkibvLKysvDFF1/I6ptgeQ0bNkS/fv1ExyAtwqOjH4iPj69w7dSpUwKSiFM2Ui0lJQWnTp3CgAEDAAA//vijLEd1AoChoSEKCwthbW2NoKAgNG3aVLaTRAgYNGgQ7OzsKowwbdq0KZYvXy4w2aPxGO0q3Lp1CwsWLEBcXBwUCgXs7OwQFBSERo0aiY5W6zw9PSts2Kjs2vOsV69eVT5pUCgUOHnyZC0nIm3y22+/ISAgQNZHRx88eBAHDx7Er7/+Kj2dAgCVSoV79+5h165dAtOJ8eabb2Lt2rVo0KABgNIFB19fX1ker37p0iW0aNECubm5WL16NXJycjB16lSp1Y2oLuBKcxXMzc3xzTffIDc3F8XFxTAyMhIdSZiyqRnlFRUVCUgiTmUjxeLj47Fu3TrpGyLJV9euXWV/dLSVlRWcnZ2RmJgIZ2dn6bqxsbFGES0nt2/f1nh9aNCgAW7fvi0wkTjt27cHULoKX7aBmKiu4UpzFXx8fCpMyqjsmhz4+fmhfv36mDhxIkpKSrBp0ybcu3dPtnM3k5OTsXr1avz9999455138H//93+iI9WqR626A5DlgR7s430gOztbtvO6HzZr1iyYmJhg+PDhAErnut+5cwfr1q0TnKz2ZWRkYNu2bUhNTdVYdFm7dq3AVERPhivNVcjLy9P4XK1W486dO4LSiOXn54cVK1bA09MTCoUCzs7O8PPzEx2r1qWmpmLNmjU4e/Yspk6dCm9vb1meeFa26r53715kZ2dj5MiRKCkpwd69e2Fqaio4nRjs433A39+/0jdVciyOPvzwQ3z++edSj2bPnj2xYMECwanEmDlzJtq0aQMHBwfZjemk5wdXmh+yadMmbNq0CSqVSmMjT15eHtzd3bFs2TKB6UiUpUuX4scff8SECRMwevRo2U5GKM/LywuhoaEa17y9vWV1Oh77eCvat2+f9HF+fj4OHz6MNm3aYNGiRQJTkWhDhgxBVFSU6BhE/wpXmh8ycuRIDBw4EMuXL4e/v7903djYWHaraKdPn0b37t0RHR1d6X0nJ6daTiTOzp07Ub9+fQQHB+Orr76Srpcd3CDHlgSVSoXMzExp5F5mZqbsZpmzj7eiYcOGaXzu5eWFCRMmCEojVn5+PiIiIiq0JMhx5Fy7du2Qnp6OJk2aiI5C9NRYND/ExMQEJiYmGoVR2RHaNjY2ApPVvn379qF79+7YtGlThXsKhUJWRfORI0dER9A648aNg6enp1QsRkdHY/LkyWJD1TJra2tYW1vDxcWFfbxVUCgUSE9PFx1DCF9fXxQWFqJLly6yfTo1a9YsKBQKqFQqDB06FLa2thqnwcmxbYfqLrZnVGH06NH46quvUFJSgsGDB+OFF15A3759ZdePVlxcjEuXLmnMUSQqk5ycLPXu2tvb4+WXXxacSIyPPvoI06dPh6GhId58801cvHgRS5cuhYeHh+hota6sSAJKn8T8/vvvcHBwQEBAgNhgAgwaNAgHDx4UHUOo8u06lXn4yQSRNuNKcxXu378PExMThIeHw93dHfPmzYOHh4fsimYdHR3Mnz8fkZGRoqOQFipbaZW7kydP4r333sPx48fRpEkTfPrpp5g0aZIsi+byB/8olUpMmDABXbt2FZhIHEtLS6hUKhgbG4uOIgyLYnqesGiuQkFBAYDSk70GDx4MHR0d2e74bdWqFf7++2+0aNFCdBTSImfOnEFQUBBSU1OhVqtl3d9dpuz0tyZNmjxyLN/zrKxIun//PoAHp+PJkYmJCby9veHo6KjRniHHnuaioiKEhIQgKSkJ+fn50nW5ji6luolFcxXs7e3h5uYGtVqNpUuX4u7du7IcLwYA9+7dw9ChQ9G9e3eNb4DsRZO3hQsXYtq0abCxsZHtv40yDRs2xJIlS3DixAlMmjQJRUVFlR4KJAepqamYO3cukpOTAQAdO3ZEUFAQLC0tBSerfVZWVrCyshIdQyv4+/tDrVYjNjYWPj4+iIqKgp2dnehYRE+EPc1VKCkpQXJyMiwtLWFsbIzMzEzcvHkTHTt2FB2t1lXVkyanx25VTRApI6dNkWWGDRtWbb+iXGRmZiIiIgI2NjawsbHB33//jbi4OHh5eYmOVuv+85//YPDgwfD29gZQeqBHVFQUNm/eLDgZieTu7o7IyEjpvzk5OZg2bRq2bdsmOhrRY+NKcxUUCgWys7Nx+vRpvPHGGyguLoahoaHoWELIqTiuStkEkYKCAiQmJkpHwl66dAldunSRZdHct29fREdHy/Jrf5iZmRnGjx8vfd6iRQvZtjNlZmZKJ+ABpbO7t27dKjCROBkZGQgMDMSNGzewfft2JCcn4+zZs/Dx8REdrdaVTcxQKpXIzc2FiYkJMjIyBKciejIsmquwYcMGREdH49atW3jjjTdQVFQEPz8/WR6jfe3aNbz//vtIT0/H0aNHceHCBRw9ehQzZ84UHa3WlK2GzJkzB35+ftLGpoSEBGzZskVkNGF2796Nr776CkZGRtDX15d1T/ONGzcQFBSE5ORkjX5NOY4q1NHRwZUrV/DSSy8BAK5evSrb/SCLFi1C3759sWPHDgDASy+9hPnz58uyaDY1NcWdO3fg6OiIiRMnokGDBpzZTHUOi+YqREVFISQkBCNGjAAAWFhYyO7ghjIBAQGYOnUqPvnkEwBAhw4d8O6778qqaC5z+fJljUkAXbp0waVLlwQmEkdOJ/9Vx8/PD25ubkhKSsKqVauwc+dOtGzZUnQsIWbPno0xY8agQ4cO0si5jz/+WHQsIdLT0+Hj44Pdu3cDAPT19WXb/79hwwYolUrMnj1bas/w9PQUHYvoibBoroKBgQH09PQ0rsl1N3xOTg769u2L1atXAyhdSXr4z0YuDA0NER4eLo0Si4iIkG3bTvPmzUVH0BpZWVkYMWIEtm7dCltbW3Tt2hUjR47EjBkzREerdX379sX+/fvx22+/AQC6du0qnRopN7q6mt9i7969C7luIyp72lBcXIz27dujSZMmsh7FR3UTi+YqWFhYID4+HgqFAsXFxQgODka7du1ExxJCqVSisLBQetOQnp4u29WSwMBAzJ8/H4sWLYJCoUD79u2xcuVK0bGEYEvCA2VvIuvXr4+0tDQ0atQImZmZglOJY2Zmhu7duyMuLg7//POPbIvmAQMGwN/fH/fu3UNoaCh27NghbZCUi48//hienp5o37498vLyMHLkSKSlpaGoqAhBQUFwdXUVHZHosbForsLixYuxYMEC6XG8nZ0dVq1aJTqWEKNHj8aMGTOQlZWF9evXIywsDLNnzxYdS4g2bdogNDRUatWR80oJWxIesLOzQ3Z2Nnx8fODl5QV9fX289tpromPVqnnz5uHtt9+GtbU1srOz4eHhAWNjY2RlZWH27NlSq5ucTJw4EREREbh79y6io6MxduxY2R14c/z4ccyfPx9A6ZM5fX19nDx5EleuXIGfnx+LZqpTOHLuISEhIbC3t5dmiubm5qK4uBhGRkaCk4kVHx+PY8eOoaSkBC4uLrKer5mSkoKUlBSNObxynCDh6emJsLAwaYRUcXExRo4ciT179oiOJlRaWhpUKpU0YUUu3NzccODAAQDAli1bEB0djW+++QY3b97E5MmTER4eLjghiVD2OgEAc+fORefOnaVJM+XvEdUFXGl+yA8//ICPPvoIJiYmsLe3R8+ePWFvby/7otnOzk7WhXKZTz75BHv27EGbNm2kFhWFQiHLopktCcC5c+dgY2MDoHTUmpmZGZo1awYAOHbsmMaR0s+7spFiAHD69GlpBdHCwkK2+0H++ecffPDBB4iNjQUA9OrVCwsXLkTjxo0FJ6s9arUaKpUKhoaGiI+Px3/+8x/pXtnJu0R1BYvmhwQHB6O4uBgXLlzAqVOncPjwYQQGBsLExAQ9e/bEhx9+KDpirbty5QqCg4ORkpKCoqIi6frevXsFphLj0KFD+PHHH2XdllGmspaEgQMHio5Vq5YuXSod8DJhwgSNw17WrVsnq6IZKN3vYGpqiri4OMyaNUu6Xr7nXU7effdd2NnZYeHChQBKn2S+++67+Pbbb8UGq0WjRo2Ct7c3TExMYGFhgU6dOgEonUQk1153qrtYNFdCR0cHnTt3RufOndG3b1/ExMTgv//9Lw4ePCjLotnX1xceHh4YNmyYbOetljE3N2fB/D8LFiwAUPqI1d7eXpYtCeW72x7udJNb59ukSZPg6ekJPT09dO/eHW3btgVQuhpftvouN7du3dKYoDJt2jTs379fYKLaN2bMGHTp0gXp6eno3bu3dF2pVMLPz09gMqInx6L5IX/++SdiY2MRGxuL5ORktG7dGnZ2dvjoo4/QuXNn0fGE0NXVxdtvvy06hlawsbHBnDlzMHDgQI3H0XJszyhPrkVR+baDh1sQ5NaSMGjQINjZ2eH27duwtraWrjdt2hTLly8XmEycli1b4q+//kKrVq0AlO6HaN26tdhQApQtQpWJi4uDvb29wERET4dF80MGDx4MGxsbTJ06FX379pXdN77KODo68rjk/0lMTATw4IRAQL49zVQ6wzw6OhoAoFKppI/LPpcbc3NzmJuba1yT86lv+fn58PDwQPfu3QEAZ86cQbdu3eDr6wsAWLt2rch4wgQGBmq0MhHVFZye8ZBjx47h1KlTOHXqFPLy8tCtWzfY29vD3t6+wjcDuYiJicG0adOgo6Mj++OSicobO3bsI++Xf3NF8lNdYThs2LBaSqJdODWD6ioWzY9w7949nD59GqdOncL3338PhUKBQ4cOiY5V6wYMGIC5c+filVde0TjURK4nwuXk5ODq1asam5t69OghMBERUd0RHByMKVOmiI5B9MTYnlGFzMxMxMbGIi4uDrGxsbh58ya6dOkiOpYQpqamspuKUJUDBw5g5cqVuHv3Lho3boyUlBRYW1vL8lFjUVERQkJCkJSUpPEGIjAwUGAqIu1x7do1vP/++0hPT8fRo0dx4cIFHD16FDNnzhQdTYjCwkJcvXoVLi4uKCoqqnDMOJG2k+dZyI8QEBCAwYMHo1+/fti+fTsaNGiAJUuW4NSpU7J91Orq6oqdO3ciOzsbubm50g85Cg4ORmhoKFq1aoXDhw9j06ZNst0g6u/vjzNnzuD48eNo3bo1zp8/DwMDA9GxiLRGQEAApk6dChMTEwBAhw4dZPm0Eig9IMvV1RUzZ87EzJkz4erqijNnzoiORfRE+DbvIS+++CIWLVqEbt26aUxHkLM1a9YAKJ1Jq1AopJ7mpKQkwclqn66uLho2bCidBti7d2/ZHq+emJiIyMhIuLu7Y/LkyRg9ejSmTZsmOhaR1sjJyUHfvn2xevVqAKXjTMsOBZKbZcuWISgoSJqaER8fj4CAAERERAhORvT4WDQ/5J133hEdQeskJyeLjqA1yjZCtmrVCtu2bUPz5s1x//590bGEKHtTqVQqkZubCxMTE2RkZAhORaQ9lEolCgsLpSlM6enpGvtC5Kb8mDmeMEt1EYtmeiIFBQU4dOgQQkJCsGXLFtFxap2vry9UKhXmzZuHgIAA5OTkYMmSJaJjCWFqaoo7d+7A0dEREydORIMGDWQ3XmzWrFmPHEsp15FiVGr06NGYMWMGsrKysH79eoSFhWH27NmiYwnRu3dvREREYOjQoQCAyMhI9OnTR3AqoifD6Rn0WBISErB3714cPnwYnTt3xpAhQ+Dp6Sk6FgmkVquhVCpRXFyMyMhI5OTkwNPTU1YnJpZtAE1ISEBCQoJUEERFRaFLly5YvHixyHikBeLj43Hs2DGUlJTAxcVFdiusvXr1ktr6srOzoa+vD6B0AaZBgwYcXUp1CotmqlJmZiYiIiIQEhKCwsJCeHp6YteuXTjpoQH1AAAgAElEQVR+/LjoaKQFMjMzYWxsrPFNUKVSwczMTHCy2jdq1Ch8++230kbIvLw8jB8/Hrt27RKcjEis69evP/K+XEeXUt3E9gyqUt++fWFnZ4elS5eiW7duAIA9e/YITkXaYvLkydi6dav0eVFREaZMmYLvvvtOYCoxsrKypDcPAKCnp4esrCyBiUgkb2/vR7bt7N27txbTiMWimJ4nLJqpSuPGjUNERARWr14Nb29vvPbaa6IjkRYpKCiAoaGh9Hn9+vU15jXLSc+ePTFx4kTphLfw8HD07NlTcCoSZcGCBQCA48eP48qVKxg+fDgAIDQ0FFZWViKjCVPWpvEwtmdQXcL2DHqk4uJiREdHIyQkBHFxcSgqKsIXX3yBXr16iY4mxIoVK7Bw4cJqr8mBh4cHNm/eLLVjZGRkYPz48YiMjBScrPYVFhZi165diIuLA1BaILz++uuyHS9GpUaMGIHvvvtOKhbVajVGjRolyyd25ds08vPzERkZCV1dXUyfPl1gKqInw5VmeiQdHR3069cP/fr1Q2ZmJsLCwrBixQrcuXMHP/30k+h4tS4+Pr7CtVOnTglIIt7YsWPh4+MDDw8PAKWrq5MmTRKcSgw9PT2MHTsWY8eOFR2FtMidO3eQn58v9boXFBTgzp07glOJ8XCbhq+vL15//XUWzVSnsGimx2ZmZoa33noLb731FhISEkTHqVUHDx7EwYMHcf36dfj6+krXVSqVbE/BGz58OCwtLREdHQ0AWL58ucYcVjnJyMjAtm3bkJqaiqKiIuk6R87J26BBgzBy5Ei4ubkBKH0dKftY7lJTUznXneoctmcQPYbk5GRcvHgR69evx6xZs6TrxsbGcHBwkNWYNapo9OjRaNOmDbp27QqlUildL+txJvk6evSoRtuOs7Oz2ECClO9pLi4uRlFRERYuXAgvLy/ByYgeH4tmoieQnZ2NF198UXQMoYKCgjB//vwqD/aQ4+rqkCFDEBUVJToGkdYq39Osq6uLRo0aabzBJKoL2J5B9ASCg4Mxffp0GBoa4s0338TFixexdOlSqa9XDrp37w4A6Nevn+Ak2qNdu3ZIT0+X3YmI9GhXrlzBl19+WaFtR04j58qU9TTfvXsXcXFxaNGiBaytrQWnInoyLJrpsRUUFECtVkuflx83JhcnT57Ee++9h+PHj6NJkyb49NNPMWnSJFkVzS4uLlCr1UhNTdVoVZGzu3fvYujQobC1tUW9evWk63JcdacH5syZg4EDB8LLy0u2q6rz5s3D22+/DWtra2RnZ8PDwwPGxsbIysrC7NmzMWLECNERiR4bi2aq1g8//IDly5fj1q1bAICSkhIoFAokJSUJTibOqVOnMGDAADRp0uSRhxg8r5RKJX766ScWzf8zZMgQDBkyRHQM0jLFxcWYMmWK6BhCXbx4UVpRDg8PR5s2bfDNN9/g5s2bmDx5MotmqlNYNFO1Pv74Y6xZswY2NjbQ0dERHUeohg0bYsmSJThx4gQmTZqEoqIijdV3OXF2dsbXX38NT09P1K9fX7ouxycQ3PBHlbGxsUFycrKs2xDKP3k5ffo0XF1dAQAWFhayXHCguo1FM1XL1NRUOkZb7j755BNERERg2LBhMDU1xd9//43//Oc/omMJ8dlnnwEo3RioUChk/QSiqKgIISEhSEpK0jgVMTAwUGAqEi0hIUE6BbB88Si3nub09HSYmpoiLi5O4+mUXE8QpbqLRTNVKTc3FwAwYMAA7NixA25ubhov/HJcUTQzM8P48eOlz1u0aIEWLVqICyRQcnKy6Ahaw9/fH2q1GrGxsfDx8UFUVBTs7OxExyLB/Pz8REcQbtKkSfD09ISenh66d++Otm3bAgDOnTuHZs2aCU5H9GQ4co6qZG1tLa0glpH7iuKNGzcQFBSE5ORkjVWSI0eOCEwlztWrV/Hnn3/C1dUV9+7dQ2FhoSxH8rm7uyMyMlL6b05ODqZNm4Zt27aJjkYk3K1bt3D79m3pewpQuvqsVqtZOFOdwpVmqhJXEivy8/ODm5sbkpKSsGrVKuzcuRMtW7YUHUuI0NBQbNiwAYWFhXB1dUV6ejqWLVuGb7/9VnS0Wlf2BEapVCI3NxcmJiY87UzGqpphXkZuU1XMzc1hbm6ucY3jGakuYtFM1VqxYgUWLlxY7TU5yMrKwogRI7B161bY2tqia9euGDlyJGbMmCE6Wq3bunUrQkJCMGbMGADASy+9hNu3bwtOJYapqSnu3LkDR0dHTJw4EQ0aNGBRIGOcYU70fGLRTNWKj4+vcO3UqVMCkoinp6cHAKhfvz7S0tLQqFEjZGZmCk4lhp6eHoyMjDSuyXUW7YYNG6BUKjF79mypPcPT01N0LBKE01SInk8smqlKBw8exMGDB3H9+nX4+vpK11UqFQwMDAQmE8fOzg7Z2dnw8fGBl5cX9PX18dprr4mOJcSLL76Iq1evSo+hw8PDYWFhITiVGGVvFnR0dGR10A0RkZxwIyBVKTk5GRcvXsT69es1xgQZGxvDwcEBxsbGAtOJl5aWBpVKhfbt24uOIsTVq1cxd+5cXLlyBWZmZjAwMEBwcLBse7yJiOj5xqKZHkmtViMwMBCLFi0SHUWoc+fOwcbGBgCQmZkJMzMz6d6xY8dk28OoVqtx7do1lJSUwMrKSrbtGUTlXbt2Da1btxYdg4ieMXkf70bVUiqVOHfunOgYwi1dulT6eMKECRr31q1bV9txtEZBQYF0SuTVq1fxxx9/CE5EJN6cOXMAAOPGjROchIieJfY0U7V4XDI0ZlU//HBGrg9rtm7dik8//RQvvvii1NesUChkNbM6Ojr6kfednJxqKQlpk7y8PBw+fBhpaWmV/h3h3wuiuolFM1Wr/HHJZeR2uEn5masPz1991DzW59mWLVtw6NAhWY9W27RpU5X3FAoFiyOZmjNnDnbv3o3bt29X+DvCvxdEdReLZqoWDzkBcnJypBUjlUqlsXqkUqlExRLKwsJC1gUzAJ74R5VydXWFq6srAgMD8f7774uOQ0TPCDcC0mPJysrCb7/9BgCwsbGR3VHJY8eOfeR9ORZPv/76KyIjI+Hk5CSdiAfI99FzTk4Orl69qnG8eo8ePQQmIm1Q/rWza9euaNCggeBERPS0WDRTtU6cOIH58+ejQ4cOAIDff/8dQUFB6N27t+BkJFJgYCAiIyNhZWUlbQZUKBTYunWr4GS178CBA1i5ciXu3r2Lxo0bIyUlBdbW1ti3b5/oaCRQ2Wtnx44dUVJSwtdOojqO7RlUrU8//RTbt29HmzZtAAB//vkn5s+fzxd+mfvhhx9w9OhR2R50U15wcDBCQ0MxYcIEhIWF4ZdffsHhw4dFxyLB+NpJ9HzhyDmqVlFRkfSiDwBt2rRBUVGRwESkDSwtLaGry/fdAKCrq4uGDRtCrVYDAHr37o3ExETBqUg0vnYSPV/4HY+qZWZmhtDQUHh5eQEA9u3bp3G4B8lTq1atMG7cOLi6ukJfX1+6PmbMGIGpxNDX10dJSQlatWqFbdu2oXnz5rh//77oWCQYXzuJni/saaZqpaSkYN68eUhKSoJCoUCHDh0QFBTE45JlrqqpAIGBgbWcRLyYmBh06tQJGRkZCAgIQE5ODubOnYtXX31VdDQSqOy1s2wCUYcOHbBq1SpYWloKTkZET4NFMz22e/fuAQCMjIwEJxHn2rVreP/995Geno6jR4/iwoULOHr0KGbOnCk6mlZIS0tDs2bNRMeoVWq1Gnv37sXIkSNFRyEtxddOoucDe5qpSn/88YfGjxs3buDGjRvS53IUEBCAqVOnwsTEBEDpytGhQ4cEpxKroKAAUVFRGD9+PDw8PETHqXVKpRK7d+8WHYO0mJGREQtmoucAe5qpSpMmTapwTaFQ4N69e7hz546sTgQsk5OTg759+2L16tUAAB0dHejp6QlOJcb58+exd+9eHDx4EPn5+VixYgWCg4NFxxKiZ8+eOHToEAYOHCg6ChER1RAWzVSlo0ePanx+//59bN68GTt27MD48ePFhBJMqVSisLBQOjo7PT1dmlEsF1u2bEFoaCjy8vLg5eWFsLAwjBkzBoMHDxYdTZh9+/Zh8+bNMDAwgKGhIUpKSqBQKBATEyM6GhERPSMsmqlaRUVF2LlzJzZu3AgnJyeEhobK9vjk0aNHY8aMGcjKysL69esRFhaG2bNni45VqwIDA+Hg4IBly5ZJG5rK3kTIVUhIiOgIRERUw1g00yOFhYXhs88+Q6dOnbBlyxZYWVmJjiSUp6cnWrRogWPHjiE3NxcrV66EnZ2d6Fi1av/+/QgJCYGPjw+srKwwbNgwyH0/8YEDBzBx4kSNaxs3bqxwjeTlypUr+PLLL5Gamqoxn3nv3r0CUxHR0+L0DKqSu7s77t+/j5kzZ6JTp04V7rdt21ZAKtIWarUax48fR0hICH7++WcMHDgQ7u7ucHR0FB2t1g0bNqzCkdmVXSN58fT0xMCBA9G1a1colUrpur29vcBURPS0WDRTlVxcXKSPFQqFxmqiQqHAkSNHRMQSYtasWY9sQVi7dm0tptE+GRkZ2LdvH8LCwhAVFSU6Tq355Zdf8PPPPyMiIkJjcohKpUJCQgLCwsIEpiPRhg4dioiICNExiOgZYXsGVenhjYBy1q9fP9ERtFrDhg3x9ttv4+233xYdpVbp6enByMgICoUC9evXl643bty40ukzJC82NjZITk6GtbW16ChE9AxwpZmI6F+6dOkS2rdvLzoGaQlvb28oFAoUFRXhjz/+gJWVFerVqyfdZ08zUd3EopnoMbA9gx4lPz8fERERFTZ8vfvuuwJTkShxcXGPvM+eZqK6ie0ZRI+hrD0jISEBCQkJGDp0KAAgKioKXbp0ERmNtICvry8KCwvRpUsX6Ovri45DgpUVxeHh4RVOyQwPDxcRiYieAa40Ez2BUaNG4dtvv4WBgQEAIC8vD+PHj8euXbsEJxMjJiYGKSkpGqurY8aMEZhIjEGDBuHgwYOiY5CW4VQVoucLV5qJnkBWVpbGSqKenh6ysrIEJhLnvffew/nz59GxY0eNcVpyZGlpCZVKBWNjY9FRSAskJiYiISEBWVlZ2L59u3RdpVKhsLBQYDIi+jdYNBM9gZ49e2LixIkYNmwYgNJHrT179hScSoyzZ88iKioKenp6oqMIZ2JiAm9vbzg6Omq8qWJPszylp6fj/PnzyM3Nxfnz56XrRkZGCAwMFJiMiP4NFs1ET2Dx4sXYtWsXDh8+DABwdnbG66+/LjiVGBYWFqIjaA0rKyvZn5ZJD7i6usLV1RU///wz+vTpIzoOET0j7GkmoqeyZMkS/PHHH3B1ddVYXZVjTzNRedHR0Y+87+TkVEtJiOhZ4koz0WPgyLmKCgoK0LJlS1y6dEl0FOEyMjIQGBiIGzduYPv27UhOTsbZs2fh4+MjOhoJsGnTpirvKRQKFs1EdRRXmokeQ9lu96pGzi1evFhkPBJs6tSp6Nu3L3bs2IHIyEgUFBTA29sbkZGRoqMREdEzwpVmosdQtvFv9+7d2L59uzRybuTIkRg/frzAZLXv9OnT6N69e5WPoOW4ipaeng4fHx/s3r0bAKCvrw8dHR3BqUgb5OTk4OrVq8jPz5eu9ejRQ2AiInpaLJqJngBHzpWuunfv3r3SR9ByffSsq6v5Unr37l3wIR4dOHAAK1euxN27d9G4cWOkpKTA2tqac5qJ6igWzURPgCPngA8++AAAsG3bNsFJtMeAAQPg7++Pe/fuITQ0FDt27IC3t7foWCRYcHAwQkNDMWHCBISFheGXX36RJu8QUd3D54dET2Dx4sVwdnbG4cOHcfjwYTg7O8u2n7myTW5y3fg2ceJE2NnZ4ZVXXkF0dDTGjh2LcePGiY5Fgunq6qJhw4ZQq9UAgN69eyMxMVFwKiJ6WlxpJnoCenp6GDt2LMaOHSs6inB5eXkan6vVaty5c0dQGjHUajUKCgpgaGiIoUOHShtEc3NzoVarZX9Sotzp6+ujpKQErVq1wrZt29C8eXPcv39fdCwiekosmokew5YtWzBu3DisXLmy0tFzcjr5bdOmTdi0aRNUKhUcHByk63l5eXB3dxeYrPatWrUKL730EkaMGKFxPSoqClevXpXV3wuqyNfXFyqVCvPmzUNAQABycnKwZMkS0bGI6Clx5BzRY9i1axdGjRqFzz77rNL7M2bMqOVE4uTk5ODOnTtYvnw5/P39pevGxsYwNTUVmKz2eXl5Ye/evRUmZajVanh4eCAqKkpQMiIietZYNBMRPSUPDw+Eh4dXes/d3Z1zmmWOh94QPV/YnkH0GLZv3/7I+3I8OvrGjRsICgpCcnKyxgzaI0eOCExVu/Ly8pCbmwtDQ0ON6/fu3UNBQYGgVKQtFi1aJB16AwAvvfQS5s+fz6KZqI5i0Uz0GJYvX45XXnkF7du3Fx1Fa/j5+cHNzQ1JSUlYtWoVdu7ciZYtW4qOVavc3NywYMECfPjhhzA2NgZQ2r7i7++PgQMHCk5HovHQG6LnC4tmosfw4YcfYt++fbh8+TKGDRuGIUOGyK5/92FZWVkYMWIEtm7dCltbW3Tt2hUjR46UVX/39OnT8d5778HR0RGtW7cGAFy7dg0uLi6YOXOm2HAkHA+9IXq+sGgmegxeXl7w8vJCamoqwsLCMGrUKLRv3x5Tp06FtbW16HhC6OnpAQDq16+PtLQ0NGrUCJmZmYJT1S5dXV2sWrUKf/31Fy5evAgA6NixI1q1aiU4GWkDHnpD9Hxh0Uz0BCwtLTF+/Hg0atQI69atQ58+fWRbNNvZ2SE7Oxs+Pj7w8vKCvr4+XnvtNdGxhGjVqhULZapg4sSJiIiIwN27d6VDbzw8PETHIqKnxOkZRI+hpKQEJ06cQGhoKC5fvoxBgwbBw8MDlpaWoqNphbS0NKhUKjRt2hQmJiai4xBphby8PBgYGIiOQUTPCItmosfg6OiIxo0bw8vLC/b29hUOOGnbtq2gZNrF2dkZx48fFx2DSCv06tULbdu2Ra9evdCrVy/Y2NhU6HMmorqDRTPRY3BxcZE+VigUGpt5FAqFrMasPYqTkxOio6NFxyDSCmq1GomJiTh58iRiYmJw6dIldOnSBRs3bhQdjYieAt/yEj2Go0ePio5QJ1R2xDiRXCmVSrRo0UL68c8//3DkHFEdxqKZiJ7IH3/8UeW9oqKiWkxCpN2GDBkCAwMDODs7Y/jw4Vi+fDnbM4jqMP7rJaInMmnSpCrv1atXrxaTEGk3Ozs7nDlzBnFxcdDV1YWenh46d+7MJzJEdRR7momIiGrQzZs3cfz4cWzYsAE5OTk4deqU6EhE9BS40kxERFQDzp8/j5iYGJw8eRIXL15Ex44d4eDgIDoWET0lrjQTERHVgFGjRqFXr15wcHCAra0t9PX1RUcion+BRTMRERERUTXYnkFERFQDMjIysG3bNqSmpmpMllm7dq3AVET0tFg0ExER1YCZM2eiTZs2cHBwgFKpFB2HiP4lFs1EREQ14O7du1i+fLnoGET0jPBoIiIiohrQrl07pKeni45BRM8IV5qJiIhqwN27dzF06FDY2tpqHPzDnmaiuolFMxERUQ0YMmQIhgwZIjoGET0jHDlHRERERFQN9jQTERHVgMzMTMyePRu9evVCr169MHfuXGRmZoqORURPiSvNRERENWDmzJlo27YtRo0ahZKSEnz33Xe4dOkSPvvsM9HRiOgpsGgmIiKqAR4eHggPD6/2GhHVDWzPICIiqgHFxcXIyMiQPs/IyEBxcbHARET0b3B6BhERUQ2YMGECPD094ezsDACIjo7G3LlzxYYioqfG9gwiIqIacunSJcTFxQEAevbsiXbt2glORERPi0UzEREREVE12J5BRERUA+Lj47F69WqkpKRArVajpKQECoUCMTExoqMR0VPgSjMREVENeO211/DOO++gU6dO0NF5sO++efPmAlMR0dPiSjMREVENeOGFFzBo0CDRMYjoGeFKMxERUQ3YsmUL9PX1MWjQINSrV0+6bmhoKDAVET0tFs1EREQ1ICoqCosXL0ZeXh4ASD3NSUlJgpMR0dNg0UxERFQDXFxcsHbtWrzyyisaPc1EVDexp5mIiKgGNG7cGJ07dxYdg4ieEa40ExER1YA1a9agsLAQbm5uGj3Nbdu2FZiKiJ4Wi2YiIqIa4OLiUuGaQqHAkSNHBKQhon+LRTMRERERUTXY00xERFRDcnNzcfPmTajVauka2zOI6iYWzURERDVg69at+PTTT2FqaipNz2B7BlHdxfYMIiKiGtC/f3/s2LEDTZo0ER2FiJ4BDo4kIiKqARYWFiyYiZ4jXGkmIiKqAb/++isiIyPh5OSkMXLOyclJYCoielrsaSYiIqoBx44dw7Fjx3Dt2jWNnmYWzUR1E4tmIiKiGvDDDz/g6NGjMDAwEB2FiJ4B9jQTERHVAEtLS+jqcm2K6HnBf81EREQ1oFWrVhg3bhxcXV2hr68vXR8zZozAVET0tFg0ExER1YDCwkK0bNkSly5dEh2FiJ4BTs8gIiIiIqoGV5qJiIhqQElJCXbv3o2TJ08CAPr06YMRI0ZAoVAITkZET4NFMxERUQ34+OOPkZSUBC8vLwBAWFgYrl27hnfffVdwMiJ6GmzPICIiqgHu7u7Yt2+fNEGjsLAQXl5eiIyMFJyMiJ4GR84RERHVkPKtGGzLIKrb2J5BRERUA/r06YOJEydi2LBhAErbM/r06SM4FRE9LbZnEBER1YDi4mLs3r0bMTExAAAHBweMHDlSOlKbiOoWFs1ERETPkFqtRkFBAQwNDTWu5+bmQl9fH0qlUlAyIvo3+HaXiIjoGVq1ahWioqIqXI+KisInn3wiIBERPQssmomIiJ6h2NhYeHt7V7ju5eWFn376SUAiInoWWDQTERE9Q2q1utK+ZaVSyQkaRHUYi2YiIqJnKC8vD7m5uRWu37t3DwUFBQISEdGzwKKZiIjoGXJzc8OCBQugUqmkazk5OVi0aBEGDhwoMBkR/RucnkFERPQMFRUV4b333sORI0fQunVrAMC1a9fg4uKClStXSicEElHdwqKZiIioBvz111+4ePEiAKBjx45o1aqV4ERE9G+waCYiIiIiqgZ7momIiIiIqsGimYiIiIioGiyaiYhqSFpaGmxtbaFWq2v0/xMaGgofH58ayeDi4oKTJ08CAIKDg7Fw4cKnzklEVJdxCy8RyZ6Liwtu374NpVKJ+vXrw9HREYsXL4aRkdG/+n2bNWuGs2fPPqOU4jNMmTLlX/8ef//9N/r3748LFy5wigQR1SlcaSYiQukq6tmzZxEWFoaLFy9iw4YNoiNRJYqKikRHICKZYtFMRFSOubk5+vTpg6SkJOnauXPnMGrUKNjZ2WHo0KGIjY2V7qWmpmLMmDGwtbXF+PHjsXTpUsybNw9A6arqyy+/LBV66enpmDJlCuzt7TFgwAB899130u+zfv16+Pr64t1334WtrS0GDx6MxMRE6f6GDRvg6uoKW1tbuLm54Ycffnisr+fhDGPHjsWaNWswatQo2Nra4q233kJmZqb088PCwtCvXz/07NkTX375pcbvtX79eulrA4D4+Hjpz8XJyQmhoaEAgOPHj8PT0xPdunWDk5MT1q9fL/2aN954AwDQo0cP2Nra4uzZsyguLsYXX3yBfv36wcHBAe+++y5ycnI08u/ZswfOzs4YN27cY33dRETPGotmIqJybt68iRMnTqBly5YASgvdyZMnY+rUqYiLi8OCBQswa9YsqdCcN28eunTpgtjYWMyYMQPh4eFV/t5z5syBhYUFTpw4gXXr1mH16tWIiYmR7h89ehSDBw9GfHw8XFxcsHz5cumepaUltm/fjtOnT2PGjBmYP38+/vnnn6f6GqOiohAYGIiYmBgUFhbim2++AQD88ccfWLp0KT7++GOcOHEC2dnZuHnzZqW/x/Xr1zFx4kS88cYbiImJQVhYGDp06AAAMDQ0xMqVKxEfH4+vvvoKO3fuxI8//ggA+O9//wsAOHXqFM6ePQtbW1uEhoZi37592Lp1K3788Ufcv38fy5Yt0/j/nTp1CgcOHMDXX3/9VF8zEdG/xaKZiAjA9OnTYWtrCycnJ5iZmWHWrFkAgPDwcPTt2xdOTk7Q0dFB79690alTJ0RHRyMtLQ2JiYmYNWsW9PX1YWdnBxcXl0p//xs3buDMmTOYN28e6tWrhw4dOmDEiBEaRXb37t3h5OQEpVIJDw8PJCcnS/cGDRqEJk2aQEdHB25ubmjVqhUSEhKe6mv18vKClZUVDAwMMHDgQGlV/dChQ3B2dkaPHj2gr68PX19f6OhU/m0iKioKr776KoYMGQI9PT00aNBAKpp79uyJl19+GTo6OrC2tsbgwYMRFxdXZZ7IyEiMHz8elpaWMDIywpw5c3DgwAGNVoyZM2eifv36MDAweKqvmYjo3+IuDCIiAJ9//jleffVVxMXFYe7cucjKysILL7yAtLQ0HDp0CMeOHZN+blFREXr27Il//vkHpqamMDQ0lO41bdoUN27cqPD7l/1cY2Nj6VqzZs1w/vx56fNGjRpJHxsYGCA/Px9FRUXQ1dVFWFgYNm/ejOvXrwMA7t+/j6ysrKf6Ws3NzaWPDQ0Ncf/+fSmjhYWFdK9+/fp48cUXK/09bty4Ia3GP+y3337DqlWrcPnyZRQWFqKgoAADBw6sMs8///yD5s2bS583b94cRUVFyMjIkK6Vz0VEJAJXmomIyrG3t4eXlxdWrlwJoLQI9vDwQHx8vPTj3LlzmDRpEszNzXHnzh3k5uZKv76yghkAGjdujDt37kClUmn83CZNmlSb6fr161i0aBEWL16M2NhYxMfHo127dv/yK608Y/l2jNzcXGRnZ1f6c5s2bYqUlJRK782dOxf9+/dHdHQ0Tp8+jVGjRqHs8FmFQlHp/7fszQBQOiZPV1cXDRs2lK5V9uuIiF4SAsQAAAJWSURBVGoTi2YiooeMGzcOJ0+eRHJyMoYOHYpjx47hxIkTUKvVyM/PR2xsLG7evInmzZujU6dOWL9+PQoKCnD27FmNFenymjZtCltbW6xevRr5+flITk7G3r17MXTo0Grz5ObmQqFQwMzMDAAQEhKCy5cvP9OvGQBee+01HD9+HPHx8SgoKMC6detQXFxc6c91d3fHyZMnpTaKrKwsqc3j3r17MDU1Rb169ZCQkICoqCjp15mZmUFHRwepqanStSFDhmDLli1ITU3FvXv38Omnn2LQoEEcSUdEWoVFMxHRQ8zMzODh4YHPP/8cTZs2xRdffIGvvvoKDg4OcHJywtdffy0Vk6tWrcK5c+fQs2dPrFmzBm5ubtDX16/09129ejWuX78OR0dHzJgxAzNnzsSrr75abZ62bdvirbfewqhRo/Dqq6/i0qVL6Nat2zP9mgGgXbt28Pf3x7x58+Do6IgXXnihyraIZs2aYePGjdi8eTPs7e3h6ekp9WAvWbIE69atg62tLT7//HMMGjRI+nWGhoaYMmUKfHx8YGdnh3PnzsHb2xtDhw7FG2+8gf79+0NfXx+LFy9+5l8fEdG/oSgpe2ZGRET/2jvvvIOXXnpJ2khIRETPB640ExH9CwkJCUhJSUFxcTF++uknHDlyBK6urqJjERHRM8aGMSKif+H27duYOXMmsrOzYWFhgYCAAHTs2FF0LCIiesbYnkFEREREVA22ZxARERERVYNFMxERERFRNVg0ExERERFVg0UzEREREVE1WDQTEREREVWDRTMRERERUTX+H4jOLGo6oRUFAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dlFB3C3Ud1V6"
      },
      "source": [
        "From the above graph we can conclude conclusions:\n",
        "\n",
        "*   At North America and ANZ all the countries get happines score between 6 to 8\n",
        "*   At South Asia there is the biggest diffrence between countries.\n",
        "*   At Westren Europe there is the country with highest happines score.\n",
        "*   At South Asis there is the country with the lowest happines score."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pf3wgA6weuW-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "1eb6961e-9635-4003-8650-5e4a6cb72c00"
      },
      "source": [
        "hover_data = df[[\"Happiness Score\"]]\n",
        "\n",
        "fig = px.choropleth(df,\n",
        "                    locations=df[\"Name\"],\n",
        "                    locationmode=\"country names\",\n",
        "                    projection=\"natural earth\",\n",
        "                    hover_data=hover_data,\n",
        "                    hover_name=df[\"Name\"],\n",
        "                    color=\"Happiness Score\",\n",
        "                    color_continuous_scale=px.colors.sequential.Plasma,\n",
        "                    scope=\"world\")\n",
        "fig.show()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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          "metadata": {
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    {
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        "sns.jointplot(x = df.loc[:,'Seats held by women in national parliament (%)'], y = df.loc[:,'Happiness Score'], kind=\"reg\")"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7f2e401d1d90>"
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\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g02L5OE7-Ueq"
      },
      "source": [
        "From the 2 above graphs we can't conclude unambiguous conclusion because there is no correlation between the columns values."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zU9DTJ-hgVdW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "outputId": "55c8bcc8-4c79-41c1-9b38-ae266b2db772"
      },
      "source": [
        "sns.jointplot(x = df.loc[:,'Population aged 0 to 14 years old (%)'], y = df.loc[:,'Happiness Score'], kind=\"reg\")"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7f2e37659390>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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8xDhlu8qzLItoNAoAiEajaGxsrJjIEARBEOWjLCsahmHw6KOP4r777oPD4UA8Hse3v/3tcpyaIAiCqDBlcW9WVRV/+qd/ir/4i7/A9u3b8cYbb+Azn/kMnn76aTidzlKfniAIgqggZVnRnDp1CkNDQ9i+fTsAYPv27bDb7ejt7cXmzZstHaPYRbOGBjeGh6NFO14pqPYYKb6FQfEtjGqNj5oBplKWIklzczOuXbuG8+fPAwB6e3sxMjKCjo6OcpyeIAiCqCBlWdE0NDTgwQcfxKc+9SkwDAMAePjhh1FXV1eO0xMEQRAVpGxzNO9973vx3ve+t1ynIwiCIKoE6i8mCIIgSgoJDUEQBFFSypY6qwW6e4N45tU+BMdSCHht2HNTBzZ3BiodFkEQRE1DQpOhuzeIx5/tAcexcNh4jMZlPP5sDwCQ2BAEQSwASp1leObVPnAcC0ngwDAMJIEDx7F45tW+SodGEMQS4+mXL6K7d6TSYRQNWtFkCI6l4LBN/HaIPIvgWKpCEREEsdipr3dN+/jpy2N4oyeI3TevmPZ5WdEwNlp9ztUzQUKTIeC1YTQuQxLGHWFlVUfAa6tgVARBLGZ++MxJxBLKlMcZw8DFqxF8+T9eg8cpTnl+396ucoRXNCh1lmHPTR3QNB1pRYNhGEgrGjRNx56byL2AIIjy0howPSD7g/EKR1IcSGgybO4M4CPvXIs6p4hESkWdU8RH3rmWGgEIgig7NpFDQ50N/cNxlMH3uORQ6iyPzZ0BEhaCIKqCtgYXjp0NIhxLw++u7RQ+rWgIgiCqkBa/AywD9A/XfvqMVjSzQAOcBEFUCoFn0eR3oD8Yx3Ur/WAzhsS1CK1oZiA7wDkalycMcHb3BisdGkEQS4S2BidkRa/5MQsSmhmgAU6CICpNk88OnmNqPn1GQjMDwbEURH7it4cGOAmCKCccy6Kl3omrI3Foul7pcObNkqvRZOsuoZgMv0ucse5CA5wEQVQDbQEnLg/FMBROoqXeWelw5sWSWtHk113c9tnrLjTASRBENRDw2iDyLAaCtWM5M5klJTSF1F1ogJMgiGqAZRm01DtwLZSAqtVm+mxJpc4KNc4sxwAntVATBDEXrQEnLg2a6bOsPU0tsaSEpph1l2IIBO2BQxCEFeq9NogCi4FgvCaFZkmlzopVdynWjA21UBMEYQWWYdBa78RgOFmT6bMltaLJrhKeebUP4ZgMX17XWSErlHyBAABJ4JDOPF7ISoT2wCEIwiqtAScuXotiMJysdCgFs6SEBhivuzQ0uDE8HAVQeAqrWAJBLdQEQVil3iNB5FlcC9Ve99mSSp3NRKEprIDXBlmduHydj0BQCzVBEFZhGAaNPjuGwkloNZY+I6FB4S4AxRIIaqEmCKIQmv0OKKqO05fClQ6lIJZc6mw6Ck1h5dd6FtqWTHvgEARhlYY6OxgGeO3kNby7hjIfJDQwVyiPP9uDNMyVjKzqc65Q8gUi20jwn7/poVkYgiBKhsCzqPfYcJiEpvZYyAqFZmEIgignTX473roQRnAsiYDXXulwLEFCk2G+KaxitToTBEFYocFrBxDG6UujuHUzCU1VUGqLl4W2OpMFDUEQheB2CPA4RZzuC+PWzS2VDscSi1poZktr7W5wF+UcC5mFobQbQRCFwjAMNnUGcOriCAzDAFMDWzwv6vbmcli8LKTVmSxoCIKYD5tWBxCKpDE8WhsuAYt6RWM1rbWQ9NVCGgnIgoYgiPmwqbMeAHC6bxSNPkeFo5mbRS00VtJa+ekrwMD5gQi+9kQ3WgNO/P7OTkuCMd9GApvA4tpIAppugOdZeBwCOI4lCxqCWCJ8aM/Geb1PVTW4HQIGQkk0TCoDyIqGsdHqsqlZ1EJjZT4mm77SNB3hmAwGZg50KJwsab2kuzeISFLN7APOQNN0hCJpOG08/mDX6qKfjyCI6uOHz5xELKHM6702kcMrJ67Cxk+s0ezb21WM0IrKoq7RWLF4ydrPRBIKGJh23BzLQDeMktZLnnm1Dw4bj3qvHULG/oZjGXicIjUCEAQxJ3UuCdGEXBO+Z4t6RQPMndbKptdUVQebuTHQDYDn2JK2KWfrMwzDwC6ZH4NhGEikVOtfHEEQS5Y6lwjDACIJBT63VOlwZmVRr2iskO0a41gGBkyRAQx4nGLBbcqFbIRWLAdogiCWJl6XKS6jsXSFI5mbRb+imYvsquOJ353DwEgCPMfA65LAssy82pQBa+4A8/FXW+zDnYv96yOIYmIXOYgCi9GYXOlQ5mTJCw0wnl7Lv9DVOcWStikX2ha92Ic7F/vXRxDFhmEY1LkkWtHUGvNtU56vO0Ah53vm1T4oqo5IQoGq6uB5FnaRWzSeauQZRxCFU+cUMRROQtV08Fz1VkIWndBUIv0ynzRYofQH40ik1UxnHKBpOqJJHVowXrRzVBIaXiWIwqnL1GkicRl+T/XWdxeV0FQq/VLMjdBmQtMMwADYTGscA0DTDfPxRcBCPOMIYqlS5xIBAKMxEpqyUcn0S6l3yuQ5BmnFgG4wYJnx7jieq35DPSuUY1VIEIsNm8RDEriqr9OURWiuXLmCP//zP8/9fzQaRSwWw+HDh4t6nsWcfmkNODEYTiKZVnP5WLskoclXG/tRzEU5VoUEsRipc4kYq/LOs7IITXt7O37+85/n/v8LX/gCNE0r+nkWc/ole8df55YW7R1/qVeFBLEYqXNJGAwnc01C1UjZo5JlGU899RQ+8IEPFP3YC7Hsr3as2OkQBLH0qHNn6jTx6l3VlL1Gc/DgQTQ1NeG6664r+rEXe/qF7vgJgphMtvNsNJqu2uxN2YXmJz/5ybxWM/X1Lkuv293gxu6bV1p67WR77WLz+qlBPPncOQyGEmjyO7B352rs2NBU0DFKHeNCofgWBsW3MKo9vrlw2CUYzMISS04ATruAaEqB02mKTrV9X8oqNIODg3jttdfwyCOPFPzekZEYdL14rbwNDW4MD0eLdrzJ5Lda2wQWw+EEHnviWEHprlLHuFAovoVB8S2Mao2vkIt8IplGfJ7bBOTjdQoIjiYRj5vdZ5X4vsz2dZdVaH7605/i9ttvh8/nK+dpLVHsQU+adCcIolz4XBIGggmk5OI3WRWDsjYD/PSnPy1JE8BCmY/78lxk97nJZ7G0WhMEUV1ktwkIRavz+lLWFc2vf/3rcp7OMoWuPqysfhZzqzVBENVFnUsCxzIYqdIb2epsui4zhaw+rK5+FnOrNUEQ1QXLMvB7pKrNmJDQoLBNyPJXPwzDQBK4abd8prkXgiDKScBrQzShYKwK7WgWldfZfCnEZ6sQmxuaeyEIolwEvHYAozjWM4yNy7yVDmcCS0po8msrLQ0u7N7aOkEMrHSdUe2FIIhqpM4lQhRYHD55jYSmnOQLi03kEInLcNgFOGw8wpHkhC0ErK4+yGWYIIhqhGEYNPkceOPUIP7wHWuqaiO06omkyEwu2g+Fk4inVGiaDoZhYBP5aWsrc0G1F4IgqpVmvx3xlIqzV8YqHcoEamZFo+s6zO2+rDG5ZVk3DDAMEEkocNgEAPOfa6HaC0EQ1UhDnR0Cz+LImWFsWF49g/E1s6IJx2TE06rl109uWeY5FoYBqHndZVRbIQhiMcFzLG7c2IzDpwehavrcbygTNbSiMRCNy0imFbjsImx5xfjpmFy09zhFjIwlwbEsDMNASlaptkIQREX50J6NRT/mS90DONQ9gJMXw9jcWV/048+HmhGaLKpqYDSahihwcNkFSIK5UpnM5KI9yzJw2kV47DwSKXVC1xlBEEQl+OEzJxErgqlmPrpuwO0Q8Mpb10hoFoqsaAirGmwiD5edB8dOzAJO17L8B7tW5x4vtvNrsU05CYIg5gPLMri1qw0HXu9DIjVek64kNSs0AGAYQDKtIi1rsNt4OG08WGa8YaBcRfv8LQHybWmyMRAEQZSTd928HL96+SKePz6Au25aXulwaqcZYDZ0w0A8qWBkLIVEWp02lVZKrNrSEARBlIPO9jqs76jDb1+/UhVNAYtCaLJouoFIXMZINIm0ogEoj+LQlgAEQVQb77qxA+FoGq+dHqp0KItLaLKoqoFwNI1wVIas6mCsj9/Mi0JMOQmCIMrBps56tNQ78OvDfTDKneaZxKIUmixpRUM4msJoTM4MfJYG2hKAIIhqg2UY3HnDMvQNxnC6b7SysVT07AUwXz3ONgwEx9KIpRToJVB2sqUhCKIaedv1zXA7BPz6cGXrxTXTdfaDZ3uwdU0Aq9u8YOaRC9MNA7GEglRKhcMhQNeLKzhkS0MQRLUh8Bx2bWvHz1+8gIFgHK0BZ0XiqJkVzUAwju//8jS+vf8kzl0Zm3fOUdUNRGIyhsMJyIpW8voNQRBEJbljWxsEnsVvXrtcsRhqRmiWNboAAJcGo/jeL08VRXDCsTTC0TTUEtZvCIIgKonHIeJt1zfjpRPXEInLFYmhZlJnf7B7DbauCeC3b1zBxavRnOAsb3Zj9/Z2dLZ6Ck6pGQaQkjXIig6H3Rz4ZApwiCYmQu4IBFGd3HnDMjx/bAAHj1zB+25bVfbz18yKBgBWtXrxZ3dfhz99zwasaHEDAC5di+J7T5/Cd546id7++a1wsvWbkbFUWedvFhOT9//JuiN09wYrHRpBLHla6p3o6qzHwSP9kBWt7OevKaHJsqrVi33v2Yh737MBK5pNwbl4LYrvPn0K3/nFSfQOzE9wVM2cvwmVaf5mLl4/NYhHfnAED3zjJTzygyNVfdEmdwSCqG7edWMHYkkFL711reznrpnU2WQYhkFnqxer7vbg/NUIDrx+BRevRXHxahTf/cUprGgxU2qrWgpPqWUNOyWBg8sugufKrzjdvUH86MA5gEFV+KdNlxbb3eDOPR8cS8Fhm/jjRO4IBFE9rOuow/ImN35z+DJ+r6t1gi9kqak5oTnTF8YLxwcQjqbhc0u4rasV6zp8puAMRPDbN67gUp7gNPnsYBmzFpP/+rnI1m/SShJ2iYfLxoNly7cAfObVPvA8k3OllgQO6czj5RaamUxDvV4HlgccAKbu/wMsDXcEqksRtQLDMHjXjcvw7adOort3BFtWl+/ntGZSZ/914CwOvnEZ+w9dQCSpwCbxiCQV7D90AWf6wuYKp82LP7t7I+599wYsz6TUBsNJXA0lEU+pCEZSuddbxTCAREpFMFK6gc/pCI6lJly0EykF4UgaPZdHy55Gmykt9uRz53KvWYruCFSXImqNHesb4XNL+E2ZBzhrZkUTTSk4djYIu42HXTIvwCLPQQbwwvGB3ColKzirWj34l590Y3gsBVUzIKs6ZFUHzzHY/+J5vHxyCMOhuOVVjq6bDQPJlAqnXYBd5Etawwl4bYilFHAsi0RKQSiaBgxA4Nmyp9FmSosNhRK5/59u/5/FfnefL8BAZVedBGEFnmPxzh3L8OPfncOla9HcDXnJz1uWsxQBkeegGwZSsga3Y/xxgWMRjqanvJ5hGKRkDQGvDYpqIJKQoai6WfCPKYilxuB2CLlV0XsBSym1rEN0Iq3AbRchCSxQgpboPTd14EcHzkFlNETiCmAADAN4XVLZL2gzpcUa/Y4Jr5vJHWGxppeoLkXUIr/X1Yr9hy7gN6/1Yd/d15XlnDWTOgMAjmOm7K2gaDp8bmna1/vcElTdgCRyCHhtqPfYcpKgqDpCkTQicRm6Ya6KCiG7pXSpHKI3dwbwsb2bUecUoagaeI6B32ODXTIvbOW8oM2UFtu7c/Wc713M6SVy7SZqEYeNx62bWnD41BDGYlNv0ktBzQgNwzCwSzw4loGsmhc8WTUveLd1tU77ntu6WqFpOmTV7BtnWHNCxmXnIQrmly4rOsZiMvqGYrhwNVJQTAZK6xC9Y0MTHvjwNqxdVgdfnsgA5b2gzWQaumND05zvfebVPiiqjnA0jf7hOMLRNBRVXxRtz0uxLkUsDnZvb4emG3juWGE32POlZlJnHqeAeo+EWzY24eyVsSldZ9OxrsOH9wITutQ4hoFmGPC5OcRTGqJ5KbXvPHUSNpHD7VtacfuWNsux5W8p7bDzcEh8UVsH99zUgcef7UEa5kpGVvWyX9DmaxraH4wjkVbBAGAZQNN0RJM6tGC8+EGWmaVYlyIWB01+B5O9CmIAACAASURBVDatqsdzR/vx7luWg+dKu+aoGaHRNR17b+/EmnYfEkkFaVWztGXzug7fBCE60xfG/kMXIKsMJIGFLLBQVB0cy0DTzRrQrw9fxvFzI7j77SuwssVjPcZJDtF2oTgNA7V8QdM0AzAAljW/EQzMOpemFd69V421HnLtJmqVd+xox1d+fByvnxnCzRubS3qumhGaP3vv9Tlrf8kjQVENJNIKUrJWkOV/dpWT7TpTVQMepwCnTUBa0RBNKFBUHddCCXznqZPobPNg9/Z2rGi2LjhZh+gEr8BlF2ErQsNArV7QeI5BWjGgGwxYBjA/KqPgIdiZZnmAygywEkStc91KP+o9Nhx68xoJzXQYhnkB8zhEOG0GUrKKZEqFalFw1nX4cMuWdoRCcXzpB0dgk3gwDAObyJsdXbKGsbgMTTfQ2x9Bb//8BOet8yEcevMqVN1Ak9+BWzc147oV9QCq8+68FLQGnBgMJ5FMq1A1HTzHwi5JaPLZCzoOtRITRHFhGQa3XN+Mp1++mCstlIqaFJp8OJaB0ybAYeORkjXEUwpU1foKRxRYBEeT0HQDHM/CZePBcSw6Gp24fWs7fvv6ZVwZjucEZ3WbF7u3t8/Zf55N0XEcC4FjcelaFCNjKQAMDMNYMnfn2fpSnVtaUH2JWokJovi8/fpm/OKli3j5rWv4f25eXrLz1LzQZGHAwC7ysIk8FEVDIqVCVvUZJ/lP9Abx37/twWB4/ELFaGYHml3i8e6bl2Ptsjqsafei5/IoDrxxBVeG4zjXP4Zz/WNzCs4LxwfAcSxEnsvEB4zG0nj6pYtwO0TUe225JoTJd+fZ1U4oJsPvEmt6tVOs+tJStbghiFLS5HdgdbsXh968SkJTCAwAUeAgiRxUTUdS1pCalFY70xfG0y9fwlgsjUyNGroB6LqZknPZhQlOA+s6fFi7rK4gwQlH07BJE7+9AsdiMJTAYCgBn8cGj0OEquuIJ9Xc3Xl+LcJtn/9qp5pSc8WoL1VD5x1BFJsP7dlYkuNqmo6GBmtT/7tv6MC3fvomZDBoa3BN+xpZ0TA2mpj2OSssOqHJYhgAx7Jw2Vg4JQGyml3laJnVBgPdMMBlu6EMAyzHIuCxIZVWJxwr38izziVi9/Y2nO4bRX+e4KxpNwWno8n8cH1uCZGkklvRABOHSyMJOdMOLcDrlhCJp9HgtU3rK1ZoLWIxFs5rufOOIGbih8+cRCyhVDSGRMo8/9d/dASdbd5pX7Nvb9eCzrFohSYfhjGLxzaRQ1rRAZaB08YjzLHQNAOGYUA3AE3XERxNwu8ZL4rl11psEo9oSsWRnmHc/bYVAMPgwBtX0D8cx9krYzh7ZVxwbsvYPMgwVzKKpk8YLt1/6ALSAPSEgUg8DYfE467bluPHB85B5Cf2tBdai1ishfOlZnFDEOXAYRPgdggYDCdnFJqFsiSEJothmBdtj12AZhhY3uzGlcEYkvL4jnOabiCW0nCmL4x1Hb4ptZaskeeL3Vfxp3dfh3XL6nDm8igOvH4F/cFxwVm7zItbrmvG6UvhaYdLJw+S3tbVigavHU1+BxJpFUqetUmhtYilVDifbfW222LqgCCWOk0+O3oHIlBUHQJf/OHNJSU0WXZubcOPDpyDJHHwuiW4dQPxpAJZ1eB2iGBZJucInV9rSaYVxFIqNFXHaCSdE6P1HT5TcPrMGk5/MI6ey2PouWwKzh+8Yw2WNU686E0eJAVMIbx+pR+/ea0PdR4bJJ7F8Ghq1lrEdHfzS6lwPtvqbffNKysbHEHUCI0+O871RxCKpNA0ySy3GCxJodncGYDX68B//eY0Ll+Lwmnj0RpwwukQkEypiCeVnCN0ttaiaTrG4nJu7JJhMMH1mWEYrF/uw7qOmQSnDru3t00RnMlkxeeF4wOI60B7gxO3bW7Bxsz8TT4z3c2//fpmHDpxbUkUzpfS6o0gSkWdSwIDIBRNk9AUkx0bmrA84MAjPziC0bjpwKxGZdgyq5xGnx0Mg1ytJZZQkDVRYRgDbufElU+WfME5nRGcgWAcPZdH0XN5NCM47VjWOH13BzC+2vH7nQiF4qZYKDokkZ1guzPT3fzpvlF85J1rF3XdIruSG4uZDtxelwiHTQCweFdvBFEqeI6F1yUiFCnNDZploQmHw3j++ecxPDyMffv2YXBwEIZhoLm5tNYFpWZy22w4qkLTdPzRnnWo99qwbV0jBJ7Fv/3qlOlIwDOmrYzIwzCMaffCAUzB2bDch/UddTh9KWwKzkgiJzjrltVh1xyCk0VWdYRj5o6bLruYs2+Z7W6+Vi1rrJC/kqtzSwhFUghF0jAMAzzPLdrVG0GUEq9LwsBwHIZhgCnyvieWqj6HDx/Gnj178NRTT+Gxxx4DAFy6dAkPPvhgUYOpBDNZ4F+3oh48y+LS1QiOnQ2iye+E3y3B4xBgE82L+2x74WRhGAYbVvjx53s34f+9cy1a681l6ZnLo/jGz07g3351GleGYnPGaRhAStYwEkkikjDtcZr99iW5H0r+Ss5hE1DvtYNjGYzFlNznt1hFliBKhcchQNF0pPKao4qFpRXNww8/jEcffRS33HILbrjhBgBAV1cXuru7LZ8onU7j4YcfxssvvwxJkrBlyxb8wz/8w/yiLgArra+ztc0+/mwPFNUc/DQvbDxYJtMOPcteOJPJCs765T6cyqxwro4kcObyKM5cHsW6jjrs3taO9jlWOIYBJFIqUrKG3duX4elXLiIl62AZLOpaTD6TV3J2iYdN5JBIqXjgw9vQ3RvEIz84siicFQiiXLgdIgAgmlAm7H1VDCwdrb+/H7fccgsA5JZUgiBA06wr35e+9CVIkoRf//rXYBgGwWDpd1hcaOtrdtOuaNKsz8RVc/8ah8RjVasbO7d1oi3gKsg9mmEYbFzhx4bJgtM3ijN9o1jfYabU2meY0M2iZ4w6b9/ShhPnRxAcTcFtF/DOG5YV9aJajTMqs3XVFctZgSCWGo5cd606xysLx5LQdHZ24oUXXsBtt92We+yll17C2rVrLZ0kHo/jZz/7GZ5//vmcUAUCpf+lX2jra3AshWRay2zaxQAMAw5ASlahqAa2rm6AbhhIyhqSScWyezQwLjjrl/tw6mIYB4+YgnO6bxSnM4Lz/jvWwC1xsx6ns9WLzlavaS5qF3I/LMWgWh0GZrOjKYazAkEsRWyiea2pWOrsc5/7HD72sY9h586dSKVS+PznP4+DBw/m6jVzcfnyZdTV1eFf/uVf8Oqrr8LpdOJTn/oUduzYYTnQ+vq5i+aTCcVkuO38hMIWzzEIx2QAmNMLqKXBhZFzQYABVMNARmsg8hzCMXnC+zVNRzypIJ5SUIDeAABuq3fh7dvacbxnGL948QL6h2M43TeK//Nvr2Hz6gDefetKLLe4PYHGAk67CKdNyG02Nl8OPNENSeRyNSlR4JCSVRw4OpATaqt+SsVkd4MbXq8DTz53DkOhBBr9DuzduRo7NjThBwfOTfjMBZ4FzzG4GkrgK090YzCUQFPe6ytNJb5/hUDxlRaHXYLBlHZ3y0KwiRxU3YDTObX2vJDvtSWh2bx5M/bv34/9+/fjAx/4AFpaWvDEE09Y7jjTNA2XL1/Gxo0b8dnPfhbHjx/Hxz/+cTz77LNwuawJyMhIrKAUFQD4XeKUFEta0eBzmbnI4eHorO/vbHbhzXNBIHNaw8h6qDHwucRp388DSCka4kkZqmqgkIiXNzjxifddh1MXzZTatVAC3eeC6D4XxPoOH3Zvb5vR9C6fYcQh8CxcdgHSAjZduzocg8PGT3ApYBkGV4djGB6OoqHBPef3cC7mm5pbHnDg/t/fPOGx4eHohM9c4M3dU8diaSSSKobDCdgEFsPhBB574ljFmwaK8f0rJRTf/CjkgpxIphGvsNdZPpLAIZqQEY9P7aad63s929c9p9BomoatW7fi9ddfx759+yyEOpWWlhbwPI/3vOc9AMxGAp/PhwsXLmDTpk0FH8/qxWmhjr+n+0bhsvOIJ1UYMFczDMx6wGzHsAkcbIIdsqIjkVaQVqxtOw2YF/LrVvqxYYUPl4MJ/Pz5XlwLJXC6L4zTfWFsWO7Dru3taAs4Zz2OouoIR9MQBS4nOFZjyFJqh4FSpObyP3Nzd08N8ZQKl0NYdN5vBFFsxMzW9sVmTqHhOA4rVqxAOBxGU9P8Ug1+vx833XQTDh06hFtvvRUXLlzAyMgIli8vfP+DQi5OC3X8DY6l4PfY4LBpiMRlqJoOjjXz/laOIQosJFGCoulIpjUk06rlVRnLMNi6rhHLAg6cvBjGwcwK59SlME5dsi44sqIhrGpTZnCAuQW71Nb8pTD/zP/MwzEZPpeIRFKB2yFMeB25BxDEVDjWvDkrNpZSZ3fffTc+/vGP44/+6I+mpMuy3Whz8dBDD+Fv/uZv8MUvfhE8z+ORRx6Bx2N9W+T/859vgAEQS8gFXZwWMriYvaO3S3yu3S+taKhzipaPYRgAz7Jw21k4bbx5h51UoGrWBef6lX5sXOHDyQshHDzSP0Vwdm9vR+ssgpOdwUkrSdglHk6bgFMXQ3MKdqmt+UtlH5P9zLOplaz7w1LwfiOIhcCxpqN9sbEkND/84Q8BAF//+tcnPM4wDA4cOGDpRMuWLcN//Md/FBjeOHaJx7VQAkOhBPweacJFo1R3p8W+o2cZcxdQu8gjIatIFCo4q+qxcaUfJy+EcOCNKxgMJwsWnOwMzqETV1HnlqCqBnRj6i6fWUrpMFAu80/aNI0grMGxDLRCu5ksYEloDh48WPQTF0q2VZXnWETiCpz28VVFqe5OS3lH7xB5OEQeqcy204pqrY6TLzhvXQjh4CTB2bjCh13bZhccXTdw9vIo6uvs8LolpNIKkmmt7OmkcgkAbZpGENZgGMAotJhrActDF6qq4ujRoxgcHERzczO2bNkCni+/J6fXJWJkLIW0opXl7rTUnmFm4wALWTXMxgHZuuBsWlWP6zKCc+CNKxgKJ3HyYhgnL84tOHUuCeFoGqm0BpdDgM8tYSwulzWdVE4BWMzebwRRLHTDWPBYxHRYUore3l584hOfQCqVQktLC65evQpJkvDNb34TnZ2dRQ9qNjiORWvACZddWER3pwxEnoEkSJBVcx7HakHOiuDs3t6OlvqJgpN1pU7KKlRNhwHAZRfwnretyNzVTDzPdI0DxdhYjASAIKoHTTfM4fQiY0loHnroIXzwgx/EvffemxuE++53v4sHH3xwQXWXQjAMA2lFg6bp+INdxZl/qDZ7FcMwt332uSUoqgFJ5MGyjKVOtXzBOXE+hINHJgrOdSv82LW9LSc46zp8U3b5fPv1zaj32jAWl+G08eBYc5Bspk4/r9eB5YHi711BEERl0HWzTlNsLAnN6dOn8f3vf3/ChP0f//Ef45vf/GbRA5qJZNp0Vi6WGLx+arAq7VWATKcax8DvtUFOyUjJKpIp1ZLFDcsw2NxZj+tXTRScty6G8NbF0ATBmWmXz0RKRSqtwSaZJqK/O9I/baffk8+dmzI0WS109wZx4IluXB2OVcVNBEHUArpewdRZY2MjDh8+PKGV+fXXX0djY2PRA5qJ//2H2wt2BpiNJ587V/QZjlLAsQycNgEOG4+UbDYOqJo+Zx0nJzgr/ThxYQQHj/RPFJyVfuza1jYlpZZFNwwkUiqSaRWxlIomnx0pWcv5IIk8i6FQothfblHIrsAkkau6mwiCqGa0SgrN/fffj/vuuw87d+5Ea2srBgYG8Nxzz+FLX/pS0QMqF4Mh044kn2oe4mMw3hotqzqSaRVpWYM+h+KwLIPNnQFcv7IeJy6M4MAb/RgeTeKtCyG8dSGE61f6sWt7O5pn2L7VMABD1zE0moTfY4NPMgVvNJZGYwm2fC0G2UFQm2ja51TrTQRBVBu6YUwY6i4WloRm9+7dePLJJ/GrX/0KQ0NDWLNmDf7yL/8SK1fO7YBcrTT5HRgOJ2pyiE/kWUiCCFXTkbDoOJAvOG+eH8HBI1cwPJrCiQshnJhDcLKNA4OhBOwiD0niUOcScc+uNaX6EmfESl2tVIOgxSA//pYGF3ZvbSXxI6oGXTfA8sU3+bQkNLIso729Hffdd1/uMUVRIMsyRNH6lHylmO7itHfnajz2xLGaHeIzzT3HHQeSaWt1HJZl0LU6gE2rZhCcVX7s2jZRcCY3DgichFu2tqG90Q05Jc/LRy1LIQ0ZVu2HsoOgYpXdREyOPxxJUkqPqCpKVaNhDAvTOR/5yEfw13/919iyZUvusWPHjuHLX/5y2brO5uPeDEz85c4XlPt+fwvGxhJV1XU2mULdaQ0YSMka4ikFqmrte6XrBrrPj+DgG1dyd/wMkBOcplnSY36/E+FwPOejJvBMQYIz02czk6vydFYyWUugBz68bcpxJZEDyzBzHrdcTI5f4FnEksqU+KuFanVHzlKt8dXy1gX7Hn4W61f48ZkPb5/wuKxoGBudvSa7IPdmAOjp6UFXV9eExzZv3ozTp09beXtFmcm4MdsxVU3CslCydRybyEPOuBbP5TjAsgy2rA5g86r6CYLz5vkQTpwPzSk4+T5qNpGH0y6At3hHVKipptWUWPa9B44OVFXXWTWn9IjK8MNnTiJWwW0C9u3tmiDWqbQKTdGKLuCWhMbtdiMYDKKhoSH3WDAYhN1uL2owpWCmX+5q7ZgqBgzMi7aUdRxIKkgvWHDqsWt7G5p8MwtOMq0iJasZ487xOZyZKPTCW4g32ubOAHbfvLKq7njL5e1GEPNF1QwIJajRWDrinXfeic985jPo6elBMpnEmTNn8NnPfhZ33XVX0QMqNgGvDfKk/RVkVZ+xY6q7N4hHfnAED3zjJTzygyPo7g2WI8wSwUDkWfg8EvweG+wSj7mGfrOC8//d04UP3rEaAa8NBoA3z4/ga//djR8dOIvB8MwinZ3DGRlLI5pUZjXom+mzmenCu+emDmiantnfZ3yAt1bqapPjT8lqTcVPLH4UVQfPVUho7r//fnR2duKee+7Btm3b8MEPfhArV67EZz7zmaIHVGxmujjt3bl6ymuzuf3RuDyh2FzbYjPuOFDnElHvtcFh4+cs+LEsgy1rAvjUPV24545O1GcEp7t3XHAGgrEZ368bBuJJBSORVGZ766mCU6hwbO4M4CPvXIs6p4hEyhzgrXTdpRAmx+/z2GsqfmLxo6h6SVY0llJnkiTh7//+7/H5z38e4XAYPp9vgktANTOTceOODU1T0iql2IirmsjujeNxiHDarLVGcyyDrWsasLkzgO5zQRw82o+RsRS6e0fwZu8INnXWY9e2djT6pk+j6rqBaEJBIqXCYRdgzxTogfmZata6N1p+/NVazCaWJpquQzdKkzqbVWgSCTNF4nCMp5l++9vfoqenB1u3bsW73/3uogdUCqxenAqpGczWlpt9rj8Yh6aZA1CtAWdVFKSzFNoazbEMtq5twObVGcE50o+RyLjgbF5djzu2taOxbnrB0XQD0biMZJIxBUfiwICpGeGoNl+8ao2JqF2ye2OVInU2q9Dcf//9uOuuu/C+970PAPDFL34RP/3pT3HTTTfhH//xHzE4OIiPfvSjRQ+qUlgt1s42zwEAjz/bA0XVkUirgAGkFQOD4eqcmWCZcYubpKwhMUdrdL7g9F6N4qkXzmMkksLxcyPoPje34Ki6gUhcRiLFwGkXYBPmrhtVmkK2D1/KMRG1TTazUXb35rfeeitnMyPLMn784x/jsccew80334zu7m488MADVSM0VlYYc1ncW92Ia7YUG2BuZRBJKGBg1jp0gzFNQd1S1abhGDBwZCxu0tnN2BQNM0kOxzK4eVMLOlvcOH4uiINHriAUSVsXHM3AWExGnFfgsouQBA7VqjfVmFKtxpiI2iZbRy2711kymYTH4wEAnDhxAjzP4+abbwZgztEMDw8XPaD5YGWFYcXi3mrNYK4Um8PGQ1V1ZD8vlgFUTa+JmQkGeZuxKQbiKQXyLK3RHMtg29oGdK0OTBWc3hF0dQZwx7Y2NMwkOKqB0WgaAs9iIBjH/xzvx5WhOHxuqWpSQdU4/1KNMRG1zfiKpvjHnlVoGhsbcfr0aaxfvx6HDh3C9u3j06KRSKRq7GesrDCsWtxbqRnMlWIbjcvgeRaapoMBoBtm3rO2ZiYYiAIDSZSQVnQkUkqmO2z6V+cLzrGzw/jd0X6EImkcOxfE8d7gnIJz4vwInnrpAjxOCc0BJxIpBT/87VkAlU8FVeP8SzXGRNQ2WaEp+340H/3oR3Hvvfdi69atePHFF/H1r38999yLL76IdevWFT2g+WBlhTH5uYUMbM6VYnv82R7YRQ7RpJ6ZIzFgl6SanJkwjIyJp9vc/TORMocyZxOc7esasWVNgyk4R/oRis4tOC8cHwDLspAVHcHRJJw2AQGfHc8fGyiJ0BRSSLeaUi0n1RgTUdtke4GYcgvNPffcg+XLl+PEiRP4kz/5E+zYsSP3nCRJ+OQnP1n0gOaDlRXG5OcWYnFvJcX2zKt90PK6zpp89qpJBc2H/FkcRRMQTyqz1lTGBSeAY2fNLrXwJMHZta0NgYzghKNp2CQ+d65YUgGTNDeAkxUNosACRariFFpIn08bdqmpxpiI2qZizQAAcOONN+LGG2+c8vju3buLHsx8sbLCmPzcdAObhTBbiq1WWnbngzmLw6DOJcLttiERT8+xwmFzgnO0J4jfHZ0oOFtWB3DH1jb43BIiSQUin2eYqWqQBAHhaBqiwMFpFxbkFJ1lPoX0avxMqzEmonYxMq0/pWjKsTSwWe1YXWHMNbBJWMcwAEnicyucREpBKj3zRmwcy2LH+kZsXTtRcI6eDeLYuSBWtXggK+bunQLHQtHMG4LbulphwHRpllVt3k7R+VAhnSCmImTmZ1RNn+OVhbMohAZYuiuMhbLQob/sCifrNhBPqfMSnN6BCBgGcNoMyAyDgNeG27pasa7DN+FcWadou8TDIQnzEhwqpBPEVIRMNmGy/2AxWDRCQxRGd28QTzzXi4FgHDzHwuMUFjz0x+XZ28RTKpLp2VNq0wlOLKmCZYDV7XUIeKfvUMsadybTKiSBg8NWWEqNCukEMRUxs7V91QjN5cuXwTAM2tvbix0PUQayxfCxmAyGYaAbBsIxGX63BI5jFzz0lxUch41HPDlXl5opOFvWBHD0bBC/O3IFozEZR3qGcezsMLasacAdW9tQP81qY3yFY6bUnHYBIj+34FAhnSCmwrEMGACKqhX92JaE5tOf/jT+8A//ENu2bcNPfvITPPTQQ2BZFn/7t3+Le+65p+hBEaUlWwzXDSPXM68bBiIJBU0+e9FqFTxrdqnJKo94cvY5HJ5jccP6RmydTXC2taHeM7fgZFc4s0HpVIKYCMMwEAQWSglWNJbc015++WVcf/31AIB//dd/xfe//33893//N77zne8UPSCi9ATHUhB5FjzHjvfOA1BVvei1imxbtM8twee2wSZws3qbZQXn0/9rC95/20rUuUToBnCkZxhf+a9j+MlzvRiJTC+EWcEJR1MIRdJIpBRgRhMdgiAmI/Jc5VJniqJAFEUMDg5idHQ05xAQDNb2Pi1LlWwx3OMUEYqkoBvmlZ9jmQXXKmZqLsgNfnoyTgNz7PrJcyxu2NCErWsbcLTHdBoYjcl4o2cYR88OY+taM6Xmn2GFk1Y0s+YTleG08RCr2EuNIKoFgWehKBUSmg0bNuBb3/oW+vv7sXPnTgDA4OAgXC5X0QMiSk+2GM5lVhpjMRmqZqC53o7fv2P1vFNKVgYhJwtOPKlAnsW8M19wjvQM47ms4JwZxtGe2QUHAGRFg6xoEHgGDpsAu0j9LwQxE2ZzTIVqNF/4whfw1a9+FTzP44EHHgAAHD16FHfffXfRAyJKz+Ri+KpWT1GK4YUMQmYFR3SLSCs6Ykll1twwz7G4cUMTtq1twBtnTMEZi2cFJ4htawPYOYvgKGrGLZpVYJ+0ARtBECYCz5WkRmNJaDo6OvDlL395wmN79uzBnj17ih4QUR5KUQyf3yAkA0ngIAocUrKKeEKZdQM2nmNx08YmbF83UXBePzOMIz1BbFvXgJ1bWmcUHDWzAVs8ycBhM7dFKIWJ4FKCNmBbPIgCW7kazS9+8Qts2LABnZ2dOH/+PP7u7/4OLMviwQcfRGdnZ9GDImqThQxCMgDsIg+byCGR1hBPKrNuMT2j4JwewpEzw9i2rgHv27l6xm4XXTcQy2wxbQ5/cuC5hdvbLDWmS5d+7+lT8DhFpGSNhKfGEDgWilKh1Nmjjz6KH/3oRwCARx55BJs3b4bD4cBDDz2Ef//3fy96UEuNxXJHWIxBSAYMnBIPu8ghkVaRSKmWBef1M0N4/ujAuOD0DGPb2gbcsbUVPvf0YqfrBuJJBcmUCknkYJf4ovipLRUmp0s1LeMOIWtornfQzp81hiCwiCWUoh/XktCEQiEEAgGk02m88cYb+NrXvjZhEzRi/sxWQJ9uF9BSxVAMoSvmICTLMHDZhIzgaEim1BltbQBTcG7e2Iwd6xqnCs6ZYWxf14CdswmOYSCZNodLBZ6jTjWLTE6XRhIKGMb8fjIMQzt/1hgiz0HR0kU/riWh8fv9uHTpEnp6erBp0yaIoohkMgljkd/2lWOlMVsBfffNK4t6ruko9t7zxa79cCwLt52FU+IQm8NHDZgoOCcvj+GXhy4gEpfx2ukhvJETHNMtejoMY7xTjecZOG0CbCIHpsokp1pWwZPTpWomvy/w40lLMiytHcRKtjffd9992Lt3LziOw1e+8hUAwEsvvYT169cXPaBqodgX4JmotJPwdKmPsZiM//vkm+hs81ZNGo9lWfQNRnGo+ypGomnwLHDTxuYJppv58ByLndvasXGZF6+fHsJzxwZygpNNqc0mOIC5zbTZqcZUVadauX42rTA5XcqxDDRdh8c5vvsuGZbOzIf2bKzo+TVNR0Ne5sTllKADEx6bsCsWtAAAIABJREFUDVnRMDY69yaSloRm7969uOuuuwAAdrtpdLhlyxb88z//s6VgapFC9yyZ7x1mpZ2E84UukVIQiqbBADAMo6ry6/kXV7dDAMOxOHTiGliWwZr2uhnfx3Msbr6uGTvWN+Lply7i9TPD0HQjs8IZwo71jdi5tQ11rlkEZ0qnGgeOtWSqURLms59OqZicLm2ssyGSVMGyDAzDIMPSOfjhMydLUhOZL2f7QojG0/jOk8ctvX7f3i5Lr7M8vZZKpfD8889jeHgY+/btg6qqNZU6mywE/+vO9VgemHmXzUJWGgu5w6y0k3C+0EUS2V0zGQg8W/QL2ELSPfkXV1nRISs6GAY4dTGMTavqZ/VRA4De/jH0XBlFnVuEouqIJRToBnD41MSU2myCk+tUS6qwSdy8tylYKJVeBU9mcrq0WtJ6ROGwLAO9+Jkza15nhw8fxp49e/DUU0/hscceAwBcunQJDz74YPEjKgFZIRiNyzkh+NaT3ejundlCJ+C1Teknn2mlkX8RzBZAsy7Ic7G5M4CPvHMt6pwiEikVdU4RH3nn2rL9Yu65qQOapiOtaFBVPXPRNHKpj2JdwKb7DB5/tmfWzyCfrD9bPrpu4Fz/WM5HTZrFR+2F4wOZz4iHyy6iye+A085nUj0GDp8awpd/dAw/e+E8RmOzF0N1w0AipWIkkkQ4ks78nJRPbQr52awEmzsD2HNTBwJeG4JjKTzzap/lz5moLGzGzb3YWFrRPPzww3j00Udxyy234IYbbgAAdHV1obu7u+gBlYLpUg2ars96p17ISmOhd5iVdBLOT32MjKbAMECdW4JdMr+eYl3ApvsMxtIqvr3/JBw2fs4739lSjPkuA7JiIJZScrt1ZglH07BJ458Rw5ibtQmsglu72vD8sX5EE0puhbNjfSNu39I66wrHMICUoiGtahB4Dg4bb4rdQr5RFqj0KnguqqmGRBQGy1ZQaPr7+3HLLbcAMH9BAUAQBGha8Qd7SsF0QiAJ3KxCUEirbqXrLAslK3TZC0Qp8uuTP4NESkE0qQCGgUCdbc6LkbWLKwNRYOAXJKQUDXzexL/PLSGSVCDy45+Rounwe2x42/XNuGF9I147PYjnjw0gmlDw6slBvH56yLLgTO5UK6WnWrXvp1NNNSSicEqRCrb029DZ2YkXXngBt912W+6xl156CWvXri1+RCVgOiFIK9qcQmB1pVHtd5hWKeUFbPJnEEkogGF6K1mZtyg0NpvAwe9zIJ2SEU8ouK2rFfsPXYCMzPSzZn5Gt3W1AjDbcd92fQtuWN80o+Ds3NIK7yyCA+R3qpXWU62a99OpthoSYR3DMFAKRyZLQvO5z30OH/vYx7Bz506kUil8/vOfx8GDB3P1Givs2rULoihCksxf1L/6q7+aIFylZDohgIGiCUG132EWQqkuYJM/A0XVweTVgoC5L0aFxsaxTM7WZseGJgRHkzh4pB8p2dwg7dbNU9uj8wXn8KlB/M+xAUST44JzQ2aFM6fg5HWq2SUedomDsEQsbmp9hb+U0Y3xrFUxsSQ0W7Zswf79+7F//3584AMfQEtLC5544gk0NzcXdLKvfe1rFVkFTScEc3WdzecctSgs5WLyZ2ATuJzlS5ZSXYwYMDjfP4rTl0exss2LtKyazs89w2hrcE07iyPwLN6+qQU3bpgoOK+cHMRrBQhO1uImkVIm7P65mAVnuhu7RFIBzzJ44Bsv1fSN2GLHXNFUSGgAoKmpCfv27St6AOVishA0NLgxPBytYERLj/zPIFsPSitaWdKNv3qlD/GUCgBw2Hi47SJGoim8cHxgxqFPwKLgbG2DN29lNh0TtpvmOTjsQlG/vmpi6k0FCzAMVN2g5oAqR9cNlGJEjDEsDMOMjo7ie9/7Hk6dOoVEYuIU6OOPP27pRLt27YLL5YJhGNi+fTs+/elPw+PxzC9qYlHw+qlBPPncOQyFEmj0O7B352rs2NBUknPd+4Vn4bbzubQAz7GwSyySsoH7P7TV8gpDVjS8cKwfv37lEiJxOXMsBrd2teFdtyyf0UttOgSOhdNhNg6wi3irgr/5xiGEI0nY8hokwtEUUrIOp11AU4k/+2rm58/3Ip6qnoHNF4+ZLujvfrs1+6sPv8uaO4wlobn33nshyzLuuuuunDNAlve///2WTnT16lW0tLRAlmV84QtfQDwexz/90z9Zei8AjIzEZnXxLZRaWNFUe4y1FN8jPzgyfUOIx4ZP3dOFRFqd07gzH1nVcPjkEP7n+ABiSfNCwXMMbljfhNu3tE6oPc2E3+9EKBTP7f5ZbZ5qxfp8H/jGS3DYxkU+60ABw0Bbgyu3mi10fqxaf/6s2rcA1ecM8NKJa9B1A7dubrH0+n17u3KfwWxft6XU2dGjR/HKK69AFOf+5ZmJlhYzcFEU8eEPfxif+MQn5n0sgiiUmToD37GjHRzLwG0X4JA4xJKmg/NceiPyHG7d3IIbNzZOEJyX37qG104P4oYNTbi9y5rgKFXqqVYsFtpxWCtkHRFCMRnf/dt3VjqceSGrGhxS8VvzLR1x3bp1uHbtGjo65pc/TyQS0DQNbrcbhmHgl7/8JTZs2DCvY1ULZLNRW1jpDORYFleGonjx/2/vzOObqNM//sl99EjvkxuWm0IFbKEUpIACslB1ZQFFXXHxRDzQRRRlUXdFfoorouyux++ny8K6ogWUS26oLYcUSgXkECg0PeiZ5s4k8/sjzZj0TNock/Z5v16+pNNJ5slkOp95nu9zFJWhokYPsUCAscMSW13DaSw4B0+roTNYkFdUhuPnPBOczpqp5o2MQ77j0otP4bsaKl9jMtugChG1vaOHuHVG0tPT8cgjj+Duu+9GTIzrzfR3v/tdm6+vqqrCokWLYLVaYbPZ0LdvX7z22mvts5gHUOVzcNJWZqDz96oKkUAsFuHAqRIAaFVsACfBGRSHo2fLcaiw1EVwbh0Uj/EjkhCubFtwOlumWiAzDv1F4zZUwQjT0IoqRB4gj+bEiROIj49Hbm6uy3aBQOCW0HTv3h05OTnts5CHUOVz8NKaJ+r8vRrNNggsNkjEIpwvrsGQXlFg3FgjlEpEyByehLTB8TjakKWmMzL4oagMx86VI21QPDLdFBznTDWp0zC2YCSQGYf+oLki1WBD75SV6W3cescvvvjC6wcOZqjyuX0EOtzYlifa+Ht1tJa5WlqPKJUcOqP7CQNSiQiZKUlIGxSP/LPlOHzaLji5RWU42iA4M2/r55bdLGtPXDBZrJCIBQhRSCGXiHDml0rsyA++8G1nKnB20FyRarDhSP8PkXs/9b5FoWEbRrECgK2VvtHCAM7lCBRU+ew53gg3dlSo2vJEW/peI8NkEAo8TxgA7IIzfngS0gfbBefQaTX0DYJz7HwFbh0Uh/HDkxDmhocD2BMHautNuFJah8OFpWAFgCpUGnTh285W4Oy8DiUWBWfoTNeQPenX0NnIkSNx8uRJAMDgwYObxB0dQnTu3DmvG8V3OktvM3/S0XCjN4SqLU/Une9VJBQiIlQKCyOB1miGydz6HBzuOA2CkzY43r6G4xCcM2U4erYcaYPjPRKcvSduQGOwIDxEihC5BKEKKTR6M3ZR+DYgOHtpNVpzgK1pH7VaExQykU/Csy0KzXfffcf9e+/evV4/cDDTGV1/T3BO44wKlbr12TsabvTGulhbnqi73yvL2p9aI0NlMFns7VVMjHuCI3MSnMIrNdiVf5UTnGNnK5A2OB6ZwxPbFBzH2AOjyQqjyQqJWAihEKg3WPDnz44hRC7G7bcG/zUZ6HCrJzi8NE/qaPhEjdaEyDZaKrWXFoXGUfcCAMnJyQDsXkxNTQ0iIyODNrPCW3Q2199dGqdxuutZdDTc6I11MXc8Fk++V8ccHFm4XXB0BvscHHeSw2QSEe5I74mU3pHI/6kMhwtLoTcyOHKm1O7hDIlHZkrLgtN47IFGZ0Kd1gypWIgeCWEQiITYmnsFQoEAQ/tEu/V5+IJDXNSVOhjM9iyo8JDgCw8GE0azFQaTFb0TfSM0bi2waDQavPDCCxg2bBjGjh2LlJQUvPDCC6itrfWJUQR/ae80UedJnizLwmSxehRu9MZUSV9NM3UITmSYFJFhMo9CDzKJCBNGJOOFuam449buUMrEsFhtOFJYiv/ZeArb86+hXt80FJM5PAlWqw1mxn4+HdXlSoUEWgOD2noTrDbgyJlSWG22FieP8g3nSawmixU2G4t6gwUGE+PR5FrCM2rq7VNlI8P87NE489JLL0EkEmHLli1ISkqCWq3G+++/j2XLlnk0KoAIftrrWXQ03OitdTHfeqICSCUiRElEMFqs0OrNYKzuFb84BCd9cALyz5bh8OlS6E0MjhSW4uhPdg9n/PAkhDY04xzQIxIzYR9RXVNvAsuyUIVKuX5ijoy5i9drUVVnglQihFIugVQsAHjU5gZwDY/pjQxnq9XGQtQw8VGjtzTY3/HszmAKx/mLm7UGiIQCRIS2v/tLa7glNPn5+cjNzYVcbn967Nu3L9566y2/zZMh+ENHQmAduckH27qYXCKCXKWAzsRAZ7C43adPJv1VcPIaQmoGh+CcLUf64HhkNgjOgB6RXCHpx9t+gsbg2jPLYrVnzNlYlqvHkTjV4/BBbhonedTUG2FiBJCIhRCLhGCsLAQAmAZvtqPZnVRs3RSWZVFRY0CMSg6Rj7KI3RKaPn36oKSkBH379uW2qdVq9O7tXodPwjvw4UmscRqnpyGwjhCM62IhMjEUUpG9BsfEeCQ4t6UmY8wQV8E5XFiK/EaCA6DNCaJA05HTSrm9r1ogG3k2TvKQiEWwMDZo9BaoQqSo1hhhY+3dtr1xrVGxdVO0Bgv0Jgb9kn3XTd8toRkzZgwefvhhzJo1CwkJCSgrK8PWrVsxa9YsfPXVV9x+7nQJINyj8HIl9n5ViNKbWsSo5BjYIwK5RWUBfRJzCJ3JbAVjtd84E6OUvPYs+IBzDY5DcNxtJ+Ou4DQOpUWGybjtzcEwLDSORp5yMRRSMUQBGFXQOBQbHiJFVZ0BFsYGuVSEMKUUWr0FUokQESHuZTh6cjyAiq0ragwAgLhI7w2CbIzb3Zt79OiBgoICblv37t1x8uRJrtbG3XY0RNs43HuZVMSJynd5xQhRiKFsqNr195OYc8ghIkzmMg6bRMY9REIhwpVSKGUSaA2e1Vo4BCd9SDzyispx5IwaBpOVE5wxQ+IxLiUJj/x2iEfva7XZEwn0RgZyqQhKmQQSscBvfdUah2IVMjHCQ2Qwma3QGxnERyrw4NQBXrvGqNi6KepKHcJDJD5toUMtaHiIw72XS8WwMDbIJCLYWBsMJitUob/u588nseZCDlabrcuFHLwRvhSLBIgMk0ERKkO9Rg8L4/5dXS4VY+ItyRgz1FVwDp0uRf5P5UgfkoBxKYlcSM1dbDYW+gZvSya2N/J0Y1RVh2kuyUMsEmDC6G44X1yLyjojl2XmjeuMiq1d0RosqNGaMbhX601jO4rbEqbRaHDgwAFUVFQgLi4OEyZMgEql8qVtXZbm3HtxQ9zdGX8+iTVnk0wi6lIhB28uJLOsvadUVJgCBjMDrQcJA4Cr4PxQVIbcM6UNgqNG/k9lSB+SgMzhiR73rWJZwNjQV00sE8NssULuw/5dzSV5+DJMzLekkrlTBwfkuA427DwPgQB48YHRiFYp2n5BI8wWq1v7uSU0eXl5WLRoEXr37o2kpCSUlpZi5cqVWLt2LcaMGeOxcUTrONx753oMpVwCrcESsI63zYUcTBZrlwo5+GIhWSAAlDIx5FIRtA31Ip44EnKpGFm3dMPYoQn4oagMRwpLYTT/Kjhjhto9nBsVWrfXbwCAhX0+Tm29CWIfD2RrnOTx9r9P+nTBnk9JJYGYsOmYismyLPYev4ZBPSNhMzM+nVbqltC8/vrrWLlyJaZPn85t27FjB/785z9j586dPjMuEPAps8toZiAUCLhwwp3pPbhwgr9tay7k4Fij6Sr4ciFZKBC4rN/YC1ub7vdzcU2zgtGS4Bw8pUbumVKIRQ3jomViaAwWbM29gploe84O4P+BbLRg7x/OF9fiZq0RMzN8nz3sltBUVFTgjjvucNk2ZcoULF++3CdGBQq+5Ng7jrW3QM1lnTlEZabfrGjeJmcR/v3tA9EzxneZKnzDHwvJjvUbk8UGbUNLGwc/F9dga+4V+/pdC4LhEJwxQxK4kJrRbAVjZWGymBoacNrDaYdPq9sUmuaEbWDPSG4gmy8KQGnB3j/s+/EGQhUSjB4Y5/NjuSU0s2bNwoYNG/DAAw9w2zZu3Ijs7GyfGRYI+JRjn9I3BpPSe/vUnfWUxiGH2NgwXtnna/y1kOxoaRMVJoPJYkW9wQyGYXH4tBoikZDrbyYVi2BG84KhkIkxaaTdw1m9sYDzkLQGC3RGC5RyMSxtxNeLLlc2K2yAXdgcBaBKudir6zi0YO97quqMOHnxJqam9fDLMD23hObs2bPYtGkTPv74Y8THx6O8vBzV1dVISUnBfffdx+23YcMGnxnqD8hlJ1ojEAvJMokIMokCehNjv7GLXCu3JSIh16eqORQyMZKilajVmWFh7F4SywI6AwOBANh9/DrGDUvg0uad2d3w4NWSsLkUgDbU48i9UI/DtwX7zohjRPnEEcl+OZ5bQjN79mzMnj3b17YEHHLZibYI1EKyUiZGUkwI6g0WGM1WmC32DERHm5nWcHQNkElFUMrE9iaVRnvSwYGCEuQVNSQNNBKcyjoDZGL3hI2xsajXW6AzMJDLRJBLxZBJ2r+Ow6cF+86GwcTg4Ck1RvSLQUyE55lm7cEtobnrrrt8bQcvIJed4DMZwxLx3wOXoQqVQSljUaUxNmkz0xyNuwYkRCqQNjgeFbVGbg3HVXASoZSLEaNSoFpj4DwaoG1hs7G/1uM4wmoysShoukd3BXbmXYXWYMG09J5+O6bbdTSVlZUoLCxETU2NSyFXZ+oGQC47wWecr0+d0YLeiWEY3jcGPRPa7lHl3IDTGUeWWmPBGTs0AeNTk7B538VW+6e1hEtYzZHx5qP0aMJ9rFYbvj5wCYN6RqJfsv/qIN0Smj179uCFF15Az549cenSJfTr1w8XL17ELbfc0qmEBiCXneA3ja9PlgUMFgY6vQVWDwo+HTgnDeSeKUXumTKYLFbsLyhB3k9l6N89AnVaEzQ6s1v1N83BWFlodGZo/ZQezYcSBb5SXKFFbb0Jj/7Wv4WibgnNe++9h7/85S+YNm0aRo8ejZycHGzevBmXLl3ytX0EQbSCQAAopfasL52RgcHIwNaOO7hCJsbkUd2RMSyRExyj2YrCy1WQSUQYO8weUlPI2t8Py2ZjoTNYoDdafJYe3VyJwqffnUN4iBRGs7VLC4/NxuLijToM7h2F/t0j/Hpst64atVqNadOmuWy76667kJGRgT/96U8+MYwIPPRkGDw4d4jWGhgYzZ51GHDgLDgnL1Vhz7Fiu4dzsgQ/nClDxrAEZHRQcFgWTebjyLyUYtu4RMFqtUFnZGA0W5HQkH3XVefPXK/Qwmi24veTB0Dg5xCmW1dLdHQ0KisrERMTg+TkZBQUFCAyMhI2m63tFxNBCV+KVwnPEAmFiAiVwmQRNyn4bIvGxZnTx/XBC3NTkVtUih8aQmr7TpYg14uC41jHkYiFCFFI7CPC2/2OTUsUNHoLBAJ7koJj9HhXnD9jY+3eTESoFKkDYlFZqfXr8d0ap3bvvffixx9/BAA89NBDeOCBBzBr1izMnTvXp8YRgcP5ydDxB0rz2oMD54LPyDAZJOK2b92OrgMag4Urzty0+2dcr6jHlFHd8cLcVExMTbbfqBsEZ/XGAuw5cR0GE9Nhmy2MDbX1JlRpDDCY2/9+MSq5vT1SAwxjA9swOM1BV6yNK7mpg97EoH+3CL97M4CbHs3ChQu5f2dnZ+PWW2+FwWBwmbhJdC6oeLVzIJOIIJUoYDTbEwaYFhIGmus6YLXZuOJMpVyMKaN/XcP5oci+hrPvZAl+KCpDxrBEjB2a0CEPB7APZKvTmqETWqBUeJ6p1rhEQSQUwGqzITxEyu3T1WrjWJbFxRu1CA+RID7KP3UzjWnXVZGU1HZ6IxFcNF6PkUvsdURUvBr8CAAopPZ1EL2Jgd7QNGGgpt4Euazpg0Xj4sxfBScBR86U4Ycie1r03h9vIPdMqfcEx9YoU00qdmsgW+MShbgIOTQGBkKhACzLdsnaOHWVHloDg1EDYgPizQBtCM28efPaNCzY284Qza/H6I0MHH/VbRWvUtJAYHH3/AsFAoQ21LNo9RaYzFY47tuRYTJoDBaX4kwz03JxplIuwe2ju2PcsAQcKSzFDz+VNRGcjGEJkEs7JjjOmWpSscje5qaNxIHGKeBd+fpkWRYXrtciVCFBYnTgGuC2ehXce++93L9ZlsXKlSvx2muv+dwowr8010wUAMRCAUIVklb/QClpILC05/yfvVKN/QUlXO+0W/rHcm1qnIszwaLN4kylXILbb+2BcSmJzQrOuBS7h9NRwWFZ+/wjU0NfNblcjDCzvV+bO15OV70Wy6oNqNdbkPqbmIB5M0AbQtO49cxbb73VZdrRdCVaWo/RGxmsXJDW6mv51PG6K+Lp+XcWJplECKtEhKPnyjFuWCJmZvRuknWWFOleTN8hOBkNgpPXsIaz58QNHCn0nuAA9rCaVm9BdZ0RunoTlHIxJB3MVuuMONZmlHIxkmNDAmpLx791IujpSDNRShoILJ6e/8bCZLbYYLXZUHi5CvOm9MfAnpGchxAVFYLqap1H9oTIJbjDycNxFhznNRxvCA4L+9hpo8UKsbihzY2E2tw4uFlrRK3WjOH9ogN+TtxKbyY6N1PTesBqtTXMLGFhsljdXjBtnE4KUNKAP/H0/FfWGSFt1JFZKBDgF7UG4UoposLlkHvBO3AIzgvzUjFhRBKkYiEMJrvgrN5YgP0nS2DsQBpzYxiGhUZrRmWdEVqjBVabrcs38rxwoxYKqQjdY0MDbUrrHk1eXp7LzwzDID8/36Wp5pgxY3xjGeE3OtJMlDpeBxZPz39b3qtEJEREmBQmiw3iDs6VAX4VnIxhdg8n/6cyGExWfH/iOo6cUWPcsCSMGRrvFQ8HsCcPaPUW6A0MZFIRFDKxT6aA8p0qjRHVGhOG9o6C0AvfY0dp9dt9+eWXXX6OiIjAsmXLuJ8FAgH27t3rG8sIv9LeBVPqeB1YPD3/bQmTI0OrSmNEn24RGDM4HolRSpy9Wt1kpLMnzTVDFRJMTXOE1NTI+6ncSXBKkZmSiDFDEiCTeqcVjY1lYTDZW/F0xXEFl27UQSoWokd84L0ZoA2h2bdvn7/sIIKYrpzVwwc8Of+tCZNzogDLsjj1cwUKzpeje3wYbDZ7DYrzSOeZgMednO2C0xPjUpKcBIfB7uPXcbjQ+4LTFccV1OnMKK8xYGCPCJeOCIGEkgEIwosEQ81GS8LkSBSwWm2o0ZohhAA2FvilRAO5TIwe8SGQiEXQ6MzQmxiua0B7cBacw6fVyD/rW8EBXMcVyKX2KaCdMax26UYdREIBeiWGBdoUDn7IHUF0AhweQa3O7FLTUni5MtCmuYUjUUCjt0AAQCgUQCQUgAVgYay4WqaFhbEhWqVAVJgMtdqmI509JVQhwbT0nnhhbioyUxIhEQk5wVm9sQAHT5XAZHa/Mag72Gz2KaA19UZUaUzQm9s3WoGP6IwWlFTq0CshzKX4NtCQ0BCElwj2RqSODDaGsXHP+DYWEDYURTKMDUazFTX1RthY4DfdI7y20OwQnCVzR3CCozcx2HXMSXA86ETtDixrb+bpyFbT6M1NMviCjSul9RAIgD5JbU9d9SckNAThJZpLHQ6mmiJHmrvDi7E/5bMNDSlZ+3aWhdFsRZ3WhLFDExAdLodSLvbaInuYUsoJzrjGgvNv3wgO4OrlVGoM0JuCz8thrDYUl9cjMVrZ4V5z3oZf1hBEENORwlc+4Fi3+Wr/Jair9JCIhQgPlUIkEsLGAuEKMfRGhlt7GtbHvr8qRAq51PP5N60RppRienpPZKYk4vDpUhw9W84JzuHCUoxPScLUcb29cixn7J4bCw3jn9HTc6d6b6Tyjh+ugMkvxjNzRmJQ76gW9/PWd+QJJDQE4SU6Q02RI1Gg8HIl9haoUXpTi4gQKeZk9WsxqcEx/yYyTNbmOAJPCVNKMX1MT2QOtwtO/tky6I0Mdh4rxpEzpRg3LBFpQ+K9NqHTGX+Mnt648yy0ekuzv/vj3cNx82a9W+/DsixyDl5Gz/gwRIeI3X6dvyChIQgv0ZlqilL6xmBSem+PbljO4wh0RgYGo/fCT86Cc+i0GkfPlkNrsGDnsWIcKlRj/PAkpA+Oh9QHgtPc6Gkpz3qrXbxRB3WlDn+YPjCgzTNbgoSGILwI1RTZW9qEKSRQykSoNzSMI/BS2ClMKcWdY3ph/PAkHD1/E4cKbtg9nKPFOHxajUwfCw5Xk9PQW00hFUHAA8k5XKiGTCrCrQPjA21Ks/g9GeCDDz7AgAEDcOHCBX8fmiAIPyISChEZKkNkqLxJkkRHCVNKMXtyfyyZm4qMoQkQiwTQNQjO6o0FOHRa7dO1CEdvtapaI3RGC6xeChW2B6OZwYnzN3HrwDiv1h15E796ND/99BNOnTqF5ORkfx6WIIgAwbKAVCJEpEQOQ8P6jTdvyuFKKe4c2wuZI5Jw+JQaR8+Vc4Jz+LQ9pJbmIw8HsI8sqNdboDMyXOKAvzl+vgImixXjUhL9fmx38ZtHYzabsXLlSqxYscJfhyQIgicIACilYkR5OR3agUNwlsxNxVgnD2fH0WKs3nQKhwvVMDO+83AciQPVGhOMJu91pXaHvKIyxEcq0C9Z5dfjeoLfPJq//e1vmDlzJrp169au10dHe785XGwsf1o0tATfbST7OkZXtU9vtKBeZ+5wdlpUVEiTn3t1i8Ss2/phZ97HCPT6AAAgAElEQVRVHD6lhs5gwY78YhwpLMUd6b0wPjXZZx6OpygVMrCClp/32zr/tfUmXLhei3sn90dcHL+KNJ3xi9AUFBSgqKgIS5Ysafd7VFVpYfOiyx0bG8a7FMDG8N1Gsq9jBIN9e/Ov+CyLTgCA6UA4ra3BbFNGdkPawDgcPK3G8XPlqNdb8NW+i9iRdxUThifh1sFxXm/TIhAA0eHu103pDSboWkhvBtDm9bG/oAQ2FhjSPSLg11JrouiX0Nnx48dx+fJlTJo0CVlZWSgrK8OCBQtw5MgRfxyeIIh2cOJcuU97tznCadEqOUIUEp+08A8PkeK3Y3thyZxUjBnSEFIzWLA9/xpWbzyFI4WlPg2p+ZoT5yuQEKUM+KjmtvCLR7Nw4UIsXLiQ+zkrKwvr169H//79/XF4giDawdcHLrmMfZZJRDDBXifkzRRuRzq0QiqG1mC2p0N77d3thIdI8duMXhg/IgmHTqlx/Hw5JziHGpIGfOHh+BKtwYLzxTW4c0xPXtbOOEO9zgiCaJbyar1fe7eJRQJEhEoRGSaDROybG6eqQXCen5OK9CHxEIsE0DYIzjsbTyH3TCksQdJY86cr1WBZYES/2ECb0iYBKdikgWoEwX/io5S4WaP3c+82AaQSEaLECns6tME3NSqqEClmZvTGhBHJOHiqBMfPVaDeYMF3eddw6JQa40ck4dZB8ZB4uf7HmxT9UoUQuRi9EvidUAKQR0MQRAvcfVs/WK02mCxWsCwLk8Xqt95tAgGglP26fuOriZgOwVkyZwTSB8dDJBRwgvM/Gwt46+HYWBZnrlRjSO8or41q8CUkNARBNMuoQfG4b0p/RIRIoTcyiAiR4r4p/f3aYsexfhOtkkEh8379jQNVqAwzx9kFJ62x4GwqwA9F/BKcGxVaaHRmDOsTHWhT3IJ6nREE0SJ86d0mEgoRESqFySKGzovjCBqjCpVh1rjemDAiCQdPqXHifAXq9RZ8+8M1HDylxoQRSRg9MPAhtaIr1QCAIa2MA+ATJDQEQQQFjnEE0jApzBYbLhbXYMuBS6jSGBEZJkPm8CQM6BHplWNFtCk4yRg9MC5ggnPuajW6xYYgIlQWkON7CgkNQRC8ovByZRtFogKcL67BttyrkMvFiBEqUKs1YWvuFcwEvCY2gKvgHCgowY8/32wQnKs4dKoEE0YkY5SfBcdqs+GSWoOxQxP8dsyOQms0BEHwhsLLlW4Vie48WgwTY4XewEAmFSE5NhRhIVIcPq32iV0RoTJkZ/bB83NG4NZBcRAJBdDoLdj2w1W8s6kAeUVlflvDuVGhg8lsxW+68be3WWPIoyGINmj7CZvwFjuPFrtVJFpZZ4QqVArGau+eLBYJEK6UwmSxQSgQeG3gWmMcguNIi/7x55uc4Bw8rcZtI5LQr6dvF+gv3KgFAPTvFuHT43gT8mgIohXcfcImvENlndGtItEYlRwmp4QAxsqiss4IuUTo8ww1AIgMswvOc78fgdEDGzwcnRlbc6/67qANXLxRh+hwGaI86KkWaEhoCKIVnJ+wBQIBZBIRRCIhdh4tDrRpnZIYlRzmRiGo5opEp6b1AMOwTWp8Jo3sxmWoRYbJXYpNfUFkmAx3jf9VcHxd08KyLC7eqMVvgsibAUhoCKJV3H3CJrzD1LQebhWJpvSNwaN3p7RY4+PIUIsMs7e0EfuopY0Dh+D8+eHRPj3OzToj6rTmoFqfAWiNhiBapPByJfRGBtX1JkjEQoQrJVDKJX5ow9J1cQiFO2tiowbFo2eMso13tHuhUrECBgsDvd7S4Rk4rSEW+fbZ/fKNOgBAXx4POWsOEhqCaAbH2oxMKoLJwoBhbKiuN8HC2CARC/3ShqWr4osiUYHAPpJALhFBb2KgNzJenW/lLy6r6yCTiNAt1vuDIH0JCQ1BNINjbUYpF0EiFkKjM8PCWGG22PDQtIGUdRakCAUChMolUEhF0BkZGEwMfJSg5hN+UWvQOzEsKPqbOUNrNATRDM5rMwqZGPFRSiTHhkIpF5PIdAJEQiHClVJEhysgl4p8mqHmLcwWK65XaNEnKbjCZgB5NISPCPbakxiVHLU6s59b5BP+RiwSIDJMBpPZBq3Rdz3UvMG18npYbSz6JoUH2hSPIaEhvI5jfcMeevq19gRA0IjN1LQe2PD9BZhgz14yMza/tcgn/AvLAlKJEFESGYwWK7R6Mxirf+Jpc6cObvF3VqsNsbG/zpo58lM5AKAPCQ1BuF/dzWc8yX4KJvjgafLBhpaQS0SQqxTQm3w3dM2ZjTvPQqu3uLXvifMViItUQBUkjTSdIaEhvE5lnRFKueulFYy1J3xpke8t+OBp8sEGd1DKxJA7EgaMjM9a2nhCTb0JowYHTyNNZygZgPA67lZ3E/6FD10O+GCDuziGrkWpZJDLApswYDQxMJitGNDTe52p/Ql5NITX6UrrG3wOAzWGD55mSzZcLdPgqTWHYDQzkEvFuH10N8wc18dvdrWGWChEZKgMJosNWh8OXWuNGq0JgHdHIPgT8mgIr5PSNybgI4D9QbA13OSDp9mcDZW1BhjN9rYzIqEAJosVW3+4iq1HfvGbXW3haGkTFSZDRJgMYpF/3ZuaehMEAqBPkHUEcEAeDeETOtv6RnMEW9IDHzzN5mwwmK0QCgBRQxGiSABYbcDu4zd449U4I5eIIFPJoTdZoTNY/NJhoKbeBFWIFFIfNwn1FSQ0BNFO+BCK8gQ+ZNI1Z0N5tZ4TGQdCAWA0M36zy1MEECBEZm9pozNafNphwMayqNWa0SM+uNrOOENCQxDtJBiLOvngaTa24ak1h+xhMyetsbGAXMr/25NIaB+4ppRJoNWbYbZ6f8pmndYMq41FVBh/r6u2oDUagmgn7ra0J1rn9tHdwIKF1caCZRv+Dxa3j+4WaNPcRiwSICJMiogQKQRe7kNWpbF7yNHhwVc/44D/jwwEwVP4EIrqDDjWYXYfv8HLrDP3EUAqEXl92Fq1xogQuRhyWfDeroPXcoLgAXwIRXUGZo7rE4TC4ntYlkWVxoSEqLbm7vAbCp0RBEHwlHq9BRbGFtRhM4A8GoLo8niz6DSYCliDAW59hscJJu5AQkMQXZjWeo9Ncuoc3NH3IrFpH9UaE+RSEZRBvD4DUOiMILo03uw9Fkx9zIIB+/qMEdHhcgiCYTJbK5DQEEQXxnmSqIP2Fp16870IQG9iYDRbERXk6zMACQ1BdGm82f+MD73UOhNVdY76meA/fyQ0BNGF8WbRKRWwepdqjQkSsRBhSkmgTekwwb3CRBBEh/Bm0SkVsHoX+/qMLOjXZwASGoLo8niz6JQKWL2D0cxAZ2TQK8GzzD++QqEzgiAInlGlsQ86i+oE6zMACQ1BEATvqKozQiQUQBUqDbQpXoGEhiAIgmdUaYyICpdB2AnWZwASGoIgCF5htlhRr7d0irRmByQ0BEEQPKK6YX2GhIYgCILwCVUaI4QCICKsc6zPACQ0BEEQvKJKY0REmAwiYee5PVMdDUEQRICYO3Wwy89GE4Nv867hnon98MD0wU32N1us/jLNq/hNaJ544gncuHEDQqEQSqUSy5cvx6BBg/x1eIIgCN6xcedZaPUW/PHu4bh5sx4/F9fAZmORFKnAzZv1gTbPa/hNaFatWoWwMHuV6549e7Bs2TJ88803/jo8QRAE77lSaheX3onhAbbEu/gtCOgQGQDQarWdon8PQRCEN7lSqkGMSo7wkM6TCAD4eY3m5ZdfRm5uLliWxccff+zRa6OjQ71uT6yHEwQDAd9tJPs6BtnXMfhuX1soFTKwAvvzfmxsGK5VaDGwV1TQf67G+FVo3nzzTQBATk4O3n77bfzzn/90+7VVVVrYbKzXbImNDeN9DJTvNpJ9HYPs6xh8tc8TkdAbTNDpLQCAy1erUFGtx23Dk3j5udqitc8dkPy57OxsHD16FDU1NYE4PEEQBO+4UqoBAPRO7FzeDOAnodHpdCgtLeV+3rdvH1QqFSIiIvxxeIIgCN5zpVQDgQDo2UlGAzjjl9CZwWDA4sWLYTAYIBQKoVKpsH79ekoIIAiCaOB6hRbxkUrIpZ2vvNEvnygmJgZffvmlPw5FEAQRlJTc1KFHvPeTnvhA5+lxQBAEEaQYTQxu1hrQLbZzCk3n89EIgvAbhZcrsfNoMSrrjIhRyTE1rQeNcm4HxeX1YAEkk9AQBEH8SuHlSmz4/gJEIiGUcjFqdWZs+P4CAJDYeMjVhoyzbnEhAbbEN1DojCCIdrHzaDFEIiFkEhEEAgFkEhFEIiF2Hi0OtGlBR3FZPSRiIWIjFIE2xSeQ0BAE0S4q64yQil1vIVKxEJV1xgBZFLyUVuoQF6noNKObG0NCQxBEu4hRyWFmbC7bzIwNMarOMxnSX5RW6RDXSb0ZgISGIIh2MjWtB6xWG0wWK1iWhclihdVqw9S0HoE2LahgWRZlVTrERyoDbYrPoGQAgiDahWPBn7LOOobRbIWFsSEusvN6NCQ0BEG0m5S+MSQsHURnsDfV7MxCQ6EzgiCIAKIzMgBIaAiCIAgfoTMyEIsEiArrvEkUJDQEQRABxGhmEKVSQCjsnKnNAAkNQRBEQDGYrIgO77zeDEBCQxAEEVCMZgYxnbiGBqCsM4IgvAg12fQMlrWnN0d38iJXEhqCILwCNdn0HIaxwWpjEa3q3B4Nhc4IgvAK1GTTc0wWKwAgJqJzezQkNARBeAVqsuk5M8b3hUgoQFJM55xD44CEhiAIr0BNNj1HKgA+en4CwqSd+1bcuT8dQRB+g5pstg+xqPPfhikZgCAIr0BNNomWIKEhCMJrUJNNojk6v89GEARBBBQSGoIgCMKnkNAQBEEQPoWEhiAIgvApJDQEQRCETyGhIQiCIHwKCQ1BEAThU0hoCIIgCJ8SNAWbvhhzGgyjU/luI9nXMci+jsF3+wg7ApZl2UAbQRAEQXReKHRGEARB+BQSGoIgCMKnkNAQBEEQPoWEhiAIgvApJDQEQRCETyGhIQiCIHwKCQ1BEAThU0hoCIIgCJ9CQkMQBEH4lKBpQdMRVq1ahV27dqGkpATbtm1D//79AQBZWVmQSqWQyWQAgCVLliAzM9OvttXU1ODFF19EcXExpFIpevbsiZUrVyIqKgqnTp3Cq6++CpPJhOTkZKxevRrR0dF+ta8tGwcMGID+/ftDKLQ/s7z99tsYMGCA32184okncOPGDQiFQiiVSixfvhyDBg3ClStXsHTpUtTW1iIiIgKrVq1Cr169eGMfH65BZz744AOsXbuW+zvhyzXYkn18uf6INmC7AMePH2fVajU7ceJE9ueff+a2N/45ENTU1LD5+fncz2+99Rb70ksvsVarlZ08eTJ7/PhxlmVZdt26dezSpUt5ZSPLsmz//v1ZrVYbELuc0Wg03L+///57Njs7m2VZlp0/fz6bk5PDsizL5uTksPPnz+eVfXy4Bh0UFRWxCxYs4Gzi0zXYnH0sy5/rj2idLhE6GzVqFBITEwNtRrNEREQgLS2N+3nEiBFQq9UoKiqCTCbDqFGjAABz5szBzp07eWUjnwgLC+P+rdVqIRAIUFVVhbNnz2LGjBkAgBkzZuDs2bOorq7mhX18wmw2Y+XKlVixYgW3jU/XYHP2EcFDlwidtcaSJUvAsixGjhyJ5557DuHh4QGzxWazYePGjcjKykJpaSmSkpK430VFRcFms3EhID7Y6GD+/PmwWq0YP348Fi1aBKlUGhDbXn75ZeTm5oJlWXz88ccoLS1FfHw8RCIRAEAkEiEuLg6lpaWIiooKuH0O+HAN/u1vf8PMmTPRrVs3bhufrsHm7HPAl+uPaJku4dG0xIYNG7B161Zs3rwZLMti5cqVAbXn9ddfh1KpxP333x9QO1qjsY0HDhzA119/jQ0bNuDSpUtYt25dwGx78803ceDAATz77LN4++23A2ZHSzRnHx+uwYKCAhQVFWHevHl+P7Y7tGYfn64/omW6tNA4wmlSqRTz5s3DyZMnA2bLqlWrcO3aNbz33nsQCoVITEx0CU9VV1dDKBQG1JtpbCPw6zkMDQ3FvffeG9Bz6CA7OxtHjx5FQkICysvLYbVaAQBWqxUVFRUBD6M67KupqeHFNXj8+HFcvnwZkyZNQlZWFsrKyrBgwQJcu3aNF9dgS/YdOXKEl9cf0ZQuKzR6vR719fUAAJZlsX37dgwaNCggtrz77rsoKirCunXrOLd/6NChMBqNOHHiBABg06ZNmDp1akDsa8nGuro6GI1GAADDMNi1a1dAzqFOp0NpaSn38759+6BSqRAdHY1Bgwbh22+/BQB8++23GDRokN/DZi3ZJ5PJeHENLly4EEeOHMG+ffuwb98+JCQk4JNPPsEjjzzCi2uwJfuGDRvGi+uPaJsuMfjsjTfewO7du1FZWYnIyEhERERg/fr1WLRoEaxWK2w2G/r27YtXXnkFcXFxfrXt4sWLmDFjBnr16gW5XA4A6NatG9atW4eTJ0/itddec0ktjYmJ8at9rdn4yCOP4NVXX4VAIADDMEhNTcWyZcsQEhLiV/sqKyvxxBNPwGAwQCgUQqVS4U9/+hOGDBmCy5cvY+nSpdBoNAgPD8eqVavQp08fXtgXHh7Oi2uwMVlZWVi/fj369+/Pm2uwOft0Oh0vrj+ibbqE0BAEQRCBo8uGzgiCIAj/QEJDEARB+BQSGoIgCMKnkNAQBEEQPoWEhiAIgvApJDRBxNKlS7FmzZp2vz41NRXXr1/3okX+5caNGxgwYAAYhgm0KV2atr6HtWvXYsmSJS2+3mw2Y/r06aioqPD42OfPn8ecOXM8fh0RWEho2klWVhZSUlKQmpqKsWPHYunSpdDpdIE2i2P+/Pn473//67KtoKAA3bt3D5BFvqe2thZPPvkkRowYgYkTJ2Lbtm0t7tvWzbAt8vPzMX/+fIwcOdKl71tjjh07hgEDBnToAaGz8Z///AejRo3i6oW2bduGcePGISsrC/n5+dx+xcXFmDNnDtfZAQAGDhyIsLAw7Nu3z+92E+2HhKYDrF+/HgUFBfjmm29QVFSEjz76KNAmdWlWrlwJiUSC3NxcrF69GitWrMDFixd9ciylUol77rkHL774Yov7WCwWvPnmmxg+fLhPbPAU5xt2INm0aRNmzZoFwF7R/8477+Drr7/G8uXL8cYbb3D7vfHGG3jppZe4pqgOfvvb3+I///mPX20mOgYJjReIj49HZmYmd1Pbu3cv7rzzTowaNQrz58/H5cuXuX2zsrLw97//HdOnT8fo0aPx0ksvwWQyAQC+/vprzJ071+W9BwwYgGvXrjU5Zl1dHR599FGkp6dj9OjRePTRR1FWVgYAWLNmDU6cOIGVK1ciNTWVa9To/F719fV48cUXkZ6ejokTJ+LDDz+EzWZzsWPVqlUYPXo0srKycPDgwRY//z/+8Q9MnjwZqampmD59Or7//nvud1arFW+99RbS0tKQlZWFf/3rXy5hl/r6eixbtgzjxo1DZmYm1qxZ49KbbNWqVUhLS8OkSZNatUGv12P37t1YvHgxQkJCMGrUKGRlZWHLli1N9j106BD+/ve/Y8eOHUhNTcXMmTMBAOXl5Xjsscdw6623YsqUKfjyyy9bPF5KSgqys7Nb9RA/++wzZGRktNqJoLCwEGPHjnURgd27d3M22Ww27vympaVh8eLFqK2t5fZ9+umnkZGRgZEjR+K+++5zEdalS5fitddewx//+EeMGDECR48excGDBzF9+nSkpqYiMzMTn3zySbN22Ww2fPjhh5g4cSLGjBmDF198kWuX05jr16/j/vvvR2pqKv7whz+gpqamxc+rVqtx/fp1Tnxra2sRHx+PuLg4jB07lgvt7ty5E/Hx8c2KdFpaGvLy8mA2m1s8DsEvSGi8QGlpKQ4dOsRNdHz++eexbNky5OXlYfz48Xjsscdc/ii2bduGTz75BN9//z2uXLmCDz/80ONj2mw23H333di/fz/2798PmUzGCcqzzz6LUaNG4dVXX0VBQQFeffXVJq9//fXXUV9fjz179uCLL77Ali1bsHnzZu73hYWF6N27N/Lz8/HII4/g5ZdfRktNJLp3744NGzbgxx9/xFNPPYUXXniBi79/+eWXOHToELZs2YJvvvkGe/bscXnt0qVLIRaLsXv3buTk5CA3N5cL+X355ZfYv38/cnJysHnz5lZnoVy9ehUikQi9e/fmtg0cOBCXLl1qsu/48ePx6KOPYtq0aSgoKMDWrVsBAM899xwSEhJw+PBhvP/++3j33XeRl5fX4jFbo6SkBJs3b8aTTz7Z6n4pKSmIiIjAkSNHuG1btmxBdnY2AOCLL77Anj178K9//QuHDx+GSqVy6fA8fvx47Nq1C3l5eRg8eHCTcOC3336Lxx57DCdPnsTIkSPx8ssvY+XKlSgoKMC3336L9PT0Zu36+uuv8c033+Dzzz/Hnj17oNfrW+wsvWTJEgwZMgRHjx7FE088gW+++abFz3vhwgV0794dYrF9QklUVBRqa2tRVlaG3Nxc9OvXD1qtFh999BGee+65Zt8jPj4eYrEYv/zyS4vHIfgFCU0HePLJJzFq1CjMmzcPo0ePxmOPPYbt27djwoQJyMjIgEQiwYIFC2A0GlFQUMC97r777kNiYiIiIiLw+OOP47vvvvP42JGRkbjjjjugUCgQGhqKxx9/HMePH3frtVarFdu3b8fzzz+P0NBQdOvWDX/4wx+4Gy4AJCUlYfbs2RCJRLjrrrtw8+ZNVFZWNvt+06ZNQ3x8PIRCIaZPn46ePXuisLAQALBjxw488MADSEhIgEqlwsKFC7nXVVZW4uDBg1i2bBmUSiWio6Px0EMPcedjx44dePDBB7lz9eijj7b4mfR6PUJDQ122hYWFub1uVlpaipMnT2LJkiWQyWQYNGgQ7r333mY9Ind44403OO+qLbKzs7lzX1tbiyNHjnDD2jZt2oRnn30WCQkJkEqleOqpp7Br1y7OI/zd736H0NBQSKVSLFq0COfPn3fxPCZNmoSRI0dCKBRCJpNBLBbj0qVL0Gq1UKlUGDJkSLM2bdu2DQ899BC6d++OkJAQPPfcc9i+fXuTBAC1Wo0zZ85g8eLFkEqlnAfcEhqNxuWcCIVCrFixAk8//TQ+/fRTvPHGG1i7di3uv/9+/Pzzz5g/fz4WLFiACxcuuLxPSEhIix4WwT+6/OCzjrBu3TqMHTvWZVtFRYXLsChHy//y8nJum3Ob+qSkpHZl3xgMBvz1r3/F4cOHUVdXB8DeJdhqtTaJaTempqYGFovFxc6kpCQXG50bJyoUCgD2m3lz5OTk4LPPPkNJSQm3nyN80rgtf0JCAvdvtVoNhmEwbtw4bpvNZuP2b/xaZ3sbo1QqodVqXbZptVq3GyxWVFRApVK5iFVSUhKKiorcer0z+/btg06nw/Tp093af9asWZg2bRr0ej127NjhslCuVqvx5JNPcmMZAPs1VVVVhZiYGKxZswY7d+7kWvgD9u/XMdGz8UiE999/Hx999BHeeecdDBgwAM8//zxSU1Ob2FRRUYHk5GTu5+TkZDAMg6qqqib7hYeHQ6lUctuSkpJculU7o1Kpmoj/mDFjMGbMGAD2rLKioiK8+OKLyMrKwr///W+UlpbilVdecQll6nQ6l6mlBL8hofEycXFxLk9fLMtykx4dOP8RqtVq7qaiUCi4tucAcPPmzRaP8+mnn+LKlSv48ssvERsbi3PnziE7O7vF8JYzkZGRkEgkUKvV6NevH2eTs43uUlJSgldeeQX/+7//i9TUVIhEIm6hFwBiY2O5tSMALv92PKXn5+dzoRRnYmNjXc5VSzcvAOjVqxesViuuXr2KXr16AbDftByfrzGNRynHxcWhrq4OWq2WE5v2npO8vDwUFRUhIyMDgH0dSiQS4cKFC80mjMTHxyM1NRW7d+/Gli1bXNbpEhIS8Je//AUjR45s8rqcnBzs3bsXn332Gbp164b6+nqMHj261WsgJSUFH330ESwWCzZs2IBnnnmm2bWvuLg47sEBsF+nYrEY0dHRLt9hbGwsNBoN9Ho9JzZqtbrFUdUDBgzAjRs3wDBMk+/cMfht+fLlqKmpgdVqRXJyMmJjY/Hzzz9z+5WXl8Nisfi9CzfRfih05mWmTZuGgwcPIi8vDxaLBZ9++imkUqnLU+O///1vlJWVoba2FuvXr+eefAcOHIiLFy/i3LlzMJlMWLt2bYvH0el0kMlkCA8PR21tLT744AOX38fExLRYMyMSiTB16lSsWbMGWq0WJSUl+Oyzz7gFaE8wGAwQCATcjJfNmze7LEhPmzYNn3/+OcrLy6HRaPDPf/6T+11cXBwyMjLw1ltvQavVwmazobi4GMeOHeNe+8UXX6CsrAx1dXX4xz/+0aIdSqUSU6ZMwfvvvw+9Xo8ff/wRe/fudRE9Z6Kjo1FSUsIlQCQmJiI1NRXvvvsuTCYTzp8/j6+++qrFc2Kz2WAymWCxWMCyLEwmE7cOt3jxYuzatQs5OTnIyclBVlYW7r33Xvz1r39t0f5Zs2bhk08+wYULF3D77bdz2+fOnYv33nuPu+lXV1dz61w6nQ5SqRSRkZEwGAx49913W3x/wF6/snXrVtTX10MikSAkJMTFU3JmxowZ+L//+z9cv34dOp0Oa9aswbRp05qIQ3JyMoYOHYq1a9fCbDbjxIkT2L9/f4s2JCQkoEePHlxo1Zn//ve/GDx4MAYNGoSIiAiYTCZcunQJ+fn5LkkXx44dQ3p6Oo1sDiJIaLxMnz59sHr1arz++utIT0/H/v37sX79epc/ihkzZuDhhx/G5MmT0aNHDzz++OMAgN69e+PJJ5/EQw89hNtvv73Zp1gHDz74IEwmE9LT0/H73/8emZmZLr9/4IEHsGvXLowePdolZdTB8uXLoVAoMHnyZMybNw8zZszAPffc4/Hn7devHx5++GHMmTMHY8eOxYULF3DLLbdwv9SdN48AAAIhSURBVJ89ezYyMjIwc+ZMZGdnY8KECRCLxVx47+2334bFYuGy8J5++mnOk5s9ezbGjRuHWbNm4a677nK5ATfHa6+9BqPRiLFjx+L555/HihUr8Jvf/KbZfR0DvNLS0nDXXXcBsA93KykpQWZmJp566iksWrSoSWjUwfHjx5GSkoKFCxdCrVYjJSUFCxYsAGCf9hgbG8v9J5fLoVAoWp1MOWXKFJSUlGDKlClcqBKwf49ZWVl4+OGHkZqaitmzZ3M36ezsbCQlJSEzMxN33nknRowY0er5AeyJBllZWbjllluwadMmrF69utn97rnnHsycORP3338/Jk2aBKlUiuXLlze77zvvvIPTp08jLS0N69at4xIZWmLOnDlN1r6qq6vx+eef45lnngEAiMViLF++HA8++CBWrFiBV155hdt327ZtVLQZbLCEX5k4cSKbm5sbaDMCxoEDB9jbbrst0GbwkkmTJnWJa8NkMrHTpk1jy8vLPX7tuXPn2NmzZ/vAKsKXkEdD+BSj0YiDBw+CYRiUl5dj3bp1mDx5cqDN4h27du2CQCBoMd24MyGVSrF9+/Z2TRIdOHAgFWsGIZQMQPgUlmXx/vvv45lnnoFcLsdtt92GxYsXB9osXjF//nxcunQJb7/9dotrJgQRzNAoZ4IgCMKn0OMTQRAE4VNIaAiCIAifQkJDEARB+BQSGoIgCMKnkNAQBEEQPoWEhiAIgvAp/w98qFkYdz4NBwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K2RR3-yDglcw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 454
        },
        "outputId": "4b5ffa1a-2699-41a9-fb06-1e185f7a4b44"
      },
      "source": [
        "sns.jointplot(x = df.loc[:,'Population aged 60+ years old (%)'], y = df.loc[:,'Happiness Score'], kind=\"reg\")"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x7f2e36638550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "32_3C07-73SJ"
      },
      "source": [
        "From the 2 above graphs we can conclude conclusions:\n",
        "*   The more the child population occupies a wider share of the country’s population - the happiness score is lower.\n",
        "*   The more the 60+ population occupies a wider share of the country’s population - the happiness score is higher."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2SweJM53HZqH"
      },
      "source": [
        "Now let's find correlation between Happiness Score to other columns\n",
        "If the value is near to 1 or -1 it's show that there is correlation between the params\n",
        "(For convenient analysis of the data we absolute the correlation value and arrange in descending order)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ulTpOc9gDAj4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 831
        },
        "outputId": "ef667dca-c9da-49b2-d099-76d002628098"
      },
      "source": [
        "corr_data = df.corr()['Happiness Score'].drop('Happiness Score')\n",
        "corr_data = corr_data.to_frame(name='Correlation').abs().sort_values(by='Correlation', ascending=False)\n",
        "sns.barplot(x=corr_data.index, y=\"Correlation\", data=corr_data)\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 1, 2, 3, 4, 5, 6, 7, 8]),\n",
              " <a list of 9 Text major ticklabel objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yc5dhpOCtlKP"
      },
      "source": [
        "## PCA\n",
        "\n",
        "At first, we tried to visualize our data a bit. To do that, we needed to reduce the dimensions of the data. we did so by using PCA."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dl34J0xwQpPE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 816
        },
        "outputId": "dd3ad776-5144-4419-ec3e-aa6b953a6900"
      },
      "source": [
        "sns.set(style=\"white\")\n",
        "\n",
        "# Compute the correlation matrix\n",
        "new_all = df.drop(['Name', 'Regional indicator'],axis=1)\n",
        "corr = new_all.corr()\n",
        "\n",
        "# Generate a mask for the upper triangle\n",
        "mask = np.zeros_like(corr, dtype=np.bool)\n",
        "mask[np.triu_indices_from(mask)] = True\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(11, 11))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(50, 250, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=1, vmin=-1, \n",
        "           square=True, linewidths=0.5, cbar_kws={\"shrink\": .5}, annot=True)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2e400d2b50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x792 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FIBsVtHI5Fj4"
      },
      "source": [
        "num_of_trains = 1000"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mRlg1L_-dtpC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "597d7b44-b018-483e-9d10-49d2ce5d3ae8"
      },
      "source": [
        "def train_decision_tree_classifier():\n",
        "  x = df.drop(columns=['Happiness Score', 'Name', 'Regional indicator'])\n",
        "  y = df['Happiness Score'].apply(np.round)\n",
        "  x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2)\n",
        "\n",
        "  model = DecisionTreeClassifier()\n",
        "  model.fit(x_train, y_train)\n",
        "  predictions = model.predict(x_test)\n",
        "\n",
        "  return accuracy_score(y_test, predictions)\n",
        "\n",
        "scores = pd.Series([train_decision_tree_classifier() for i in range(num_of_trains)])\n",
        "scores.mean()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.49958620689655164"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TmiKj0x41DcN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1454fcc4-dd3b-4d35-8466-251ae19152df"
      },
      "source": [
        "def train_decision_tree_regressor():\n",
        "  x = df.drop(columns=['Happiness Score', 'Name', 'Regional indicator'])\n",
        "  y = df['Happiness Score']\n",
        "  x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2)\n",
        "\n",
        "  model = DecisionTreeRegressor()\n",
        "  model.fit(x_train, y_train)\n",
        "  predictions = model.predict(x_test)\n",
        "\n",
        "  return r2_score(y_test, predictions)\n",
        "\n",
        "scores = pd.Series([train_decision_tree_regressor() for i in range(num_of_trains)])\n",
        "scores.mean()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.5307158930825181"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a-YfyEuHzgwQ"
      },
      "source": [
        "From the above 2 decision trees we didn't get satisfactory score (around 0.5 from 1)\n",
        "\n",
        "Thoughts for future work:\n",
        "*   Collect more relevant data (like `un_population_df`)\n",
        "*   Merge with data from previous years.\n",
        "*   Try using different models."
      ]
    }
  ]
}