Analisando_os_Dados_do_Airbnb_Rio_de_Janeiro.ipynb

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      "name": "Analisando os Dados do Airbnb - Rio de Janeiro.ipynb",
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      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/carlosfab/data_science/blob/master/Analisando_os_Dados_do_Airbnb_Rio_de_Janeiro.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",
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        "id": "kLI0gJtzDGuQ",
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      "source": [
        "# Análise dos Dados do Airbnb - Rio de Janeiro\n",
        "\n",
        "O [Airbnb](https://www.airbnb.com.br/) já é considerado como sendo a **maior empresa hoteleira da atualidade**. Ah, o detalhe é que ele **não possui nenhum hotel**!\n",
        "\n",
        "Conectando pessoas que querem viajar (e se hospedar) com anfitriões que querem alugar seus imóveis de maneira prática, o Airbnb fornece uma plataforma inovadora para tornar essa hospedagem alternativa.\n",
        "\n",
        "No final de 2018, a Startup fundada 10 anos atrás, já havia **hospedado mais de 300 milhões** de pessoas ao redor de todo o mundo, desafiando as redes hoteleiras tradicionais.\n",
        "\n",
        "Uma das iniciativas do Airbnb é disponibilizar dados do site, para algumas das principais cidades do mundo. Por meio do portal [Inside Airbnb](http://insideairbnb.com/get-the-data.html), é possível baixar uma grande quantidade de dados para desenvolver projetos e soluções de *Data Science*.\n",
        "\n",
        "<img alt=\"Analisando Airbnb\" width=\"10%\" src=\"https://www.area360.com.au/wp-content/uploads/2017/09/airbnb-logo.jpg\">\n",
        "\n",
        "**Neste *notebook*, iremos analisar os dados referentes à cidade do Rio de Janeiro, e ver quais insights podem ser extraídos a partir de dados brutos.**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0zxQHhIUDF_2",
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      "source": [
        "## Obtenção dos Dados\n",
        "\n",
        "Todos os dados usados aqui foram obtidos a partir do site [Inside Airbnb](http://insideairbnb.com/get-the-data.html).\n",
        "\n",
        "Para esta análise exploratória inicial, será baixado apenas o seguinte arquivo:\n",
        "\n",
        "* `listings.csv` - *Summary information and metrics for listings in Rio de Janeiro (good for visualisations).*\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vhp2wMPgJ6zX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# importar os pacotes necessarios\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tUmoAT8DLQ5T",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# importar o arquivo listings.csv para um DataFrame\n",
        "df = pd.read_csv(\"http://data.insideairbnb.com/brazil/rj/rio-de-janeiro/2019-07-15/visualisations/listings.csv\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qb5By2nIMS6m",
        "colab_type": "text"
      },
      "source": [
        "## Análise dos Dados\n",
        "\n",
        "Esta etapa tem por objetivo criar uma consciência situacional inicial e permitir um entendimento de como os dados estão estruturados.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RYgvuebKNg8-",
        "colab_type": "text"
      },
      "source": [
        "**Dicionário das variáveis**\n",
        "\n",
        "* `id` - número de id gerado para identificar o imóvel\n",
        "* `name` - nome da propriedade anunciada\n",
        "* `host_id` - número de id do proprietário (anfitrião) da propriedade\n",
        "* `host_name` - Nome do anfitrião\n",
        "* `neighbourhood_group` - esta coluna não contém nenhum valor válido\n",
        "* `neighbourhood` - nome do bairro\n",
        "* `latitude` - coordenada da latitude da propriedade\n",
        "* `longitude` - coordenada da longitude da propriedade\n",
        "* `room_type` - informa o tipo de quarto que é oferecido\n",
        "* `price` - preço para alugar o imóvel\n",
        "* `minimum_nights` - quantidade mínima de noites para reservar\n",
        "* `number_of_reviews` - número de reviews que a propriedade possui\n",
        "* `last_review` - data do último review\n",
        "* `reviews_per_month` - quantidade de reviews por mês\n",
        "* `calculated_host_listings_count` - quantidade de imóveis do mesmo anfitrião\n",
        "* `availability_365` - número de dias de disponibilidade dentro de 365 dias\n",
        "\n",
        "Antes de iniciar qualquer análise, vamos verificar a cara do nosso *dataset*, analisando as 5 primeiras entradas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2iS_dae7YQtO",
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        "outputId": "e4e5bacf-0560-4ebf-86a7-27e0bf09e240",
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          "base_uri": "https://localhost:8080/",
          "height": 425
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      },
      "source": [
        "# mostrar as 5 primeiras entradas\n",
        "df.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "        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>id</th>\n",
              "      <th>name</th>\n",
              "      <th>host_id</th>\n",
              "      <th>host_name</th>\n",
              "      <th>neighbourhood_group</th>\n",
              "      <th>neighbourhood</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>room_type</th>\n",
              "      <th>price</th>\n",
              "      <th>minimum_nights</th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>last_review</th>\n",
              "      <th>reviews_per_month</th>\n",
              "      <th>calculated_host_listings_count</th>\n",
              "      <th>availability_365</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>17878</td>\n",
              "      <td>Very Nice 2Br - Copacabana - WiFi</td>\n",
              "      <td>68997</td>\n",
              "      <td>Matthias</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Copacabana</td>\n",
              "      <td>-22.96592</td>\n",
              "      <td>-43.17896</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>296</td>\n",
              "      <td>4</td>\n",
              "      <td>233</td>\n",
              "      <td>2019-06-30</td>\n",
              "      <td>2.13</td>\n",
              "      <td>1</td>\n",
              "      <td>332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>25026</td>\n",
              "      <td>Beautiful Modern Decorated Studio in Copa</td>\n",
              "      <td>102840</td>\n",
              "      <td>Viviane</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Copacabana</td>\n",
              "      <td>-22.97712</td>\n",
              "      <td>-43.19045</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>161</td>\n",
              "      <td>4</td>\n",
              "      <td>232</td>\n",
              "      <td>2019-04-27</td>\n",
              "      <td>2.09</td>\n",
              "      <td>3</td>\n",
              "      <td>352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>31560</td>\n",
              "      <td>NICE &amp; COZY 1BDR - IPANEMA BEACH</td>\n",
              "      <td>135635</td>\n",
              "      <td>Renata</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Ipanema</td>\n",
              "      <td>-22.98302</td>\n",
              "      <td>-43.21427</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>243</td>\n",
              "      <td>2</td>\n",
              "      <td>260</td>\n",
              "      <td>2019-07-08</td>\n",
              "      <td>2.37</td>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>35636</td>\n",
              "      <td>Cosy flat close to Ipanema beach</td>\n",
              "      <td>153232</td>\n",
              "      <td>Patricia</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Ipanema</td>\n",
              "      <td>-22.98816</td>\n",
              "      <td>-43.19359</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>337</td>\n",
              "      <td>2</td>\n",
              "      <td>160</td>\n",
              "      <td>2019-07-04</td>\n",
              "      <td>2.29</td>\n",
              "      <td>1</td>\n",
              "      <td>122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>35764</td>\n",
              "      <td>COPACABANA SEA BREEZE  -  RIO</td>\n",
              "      <td>153691</td>\n",
              "      <td>Patricia Miranda &amp; Paulo</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Copacabana</td>\n",
              "      <td>-22.98127</td>\n",
              "      <td>-43.19046</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>221</td>\n",
              "      <td>3</td>\n",
              "      <td>303</td>\n",
              "      <td>2019-07-12</td>\n",
              "      <td>2.83</td>\n",
              "      <td>1</td>\n",
              "      <td>145</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id  ... availability_365\n",
              "0  17878  ...              332\n",
              "1  25026  ...              352\n",
              "2  31560  ...              125\n",
              "3  35636  ...              122\n",
              "4  35764  ...              145\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6-B_qtEaYEd-",
        "colab_type": "text"
      },
      "source": [
        "### **Q1. Quantos atributos (variáveis) e quantas entradas o nosso conjunto de dados possui? Quais os tipos das variáveis?**\n",
        "\n",
        "Vamos prosseguir e identificar a quantidade de entradas que nosso conjunto de dados possui e ver os tipos de cada coluna.\n",
        "\n",
        "Este *dataset* que baixamos é a versão \"resumida\" do Airbnb. Na mesma página que baixamos o arquivo `listings.csv`. Há uma versão mais completa com 35847 entradas e 106 variáveis (`listings.csv.gz`)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TFRK0tniLV-G",
        "colab_type": "code",
        "outputId": "7ba74ba7-f844-4590-f7da-09480420c410",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        }
      },
      "source": [
        "# identificar o volume de dados do DataFrame\n",
        "print(\"Variáveis:\\t {}\".format(df.shape[0]))\n",
        "print(\"Entradas:\\t {}\\n\".format(df.shape[1]))\n",
        "\n",
        "# verificar as 5 primeiras entradas do dataset\n",
        "display(df.dtypes)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Variáveis:\t 35451\n",
            "Entradas:\t 16\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "id                                  int64\n",
              "name                               object\n",
              "host_id                             int64\n",
              "host_name                          object\n",
              "neighbourhood_group               float64\n",
              "neighbourhood                      object\n",
              "latitude                          float64\n",
              "longitude                         float64\n",
              "room_type                          object\n",
              "price                               int64\n",
              "minimum_nights                      int64\n",
              "number_of_reviews                   int64\n",
              "last_review                        object\n",
              "reviews_per_month                 float64\n",
              "calculated_host_listings_count      int64\n",
              "availability_365                    int64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yz1urSUGW9iE",
        "colab_type": "text"
      },
      "source": [
        "### **Q2. Qual a porcentagem de valores ausentes no *dataset*?**\n",
        "\n",
        "A qualidade de um *dataset* está diretamente relacionada à quantidade de valores ausentes. É importante entender logo no início se esses valores nulos são significativos comparados ao total de entradas.\n",
        "\n",
        "* É possível ver que a coluna `neighbourhood_group` possui 100% dos seus valores faltantes. \n",
        "* As variáveis `reviews_per_month` e `last_review` possuem valores nulos em quase metade das linhas.\n",
        "* As variáveis `name` e `host_name` têm aproximadamente 0,1% dos valores nulos."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "plk2FjbCXOqP",
        "colab_type": "code",
        "outputId": "6bab2f54-7ee0-4b0b-e2fd-b359f58864f8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        }
      },
      "source": [
        "# ordenar em ordem decrescente as variáveis por seus valores ausentes\n",
        "(df.isnull().sum() / df.shape[0]).sort_values(ascending=False)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "neighbourhood_group               1.000000\n",
              "reviews_per_month                 0.464641\n",
              "last_review                       0.464641\n",
              "name                              0.001862\n",
              "host_name                         0.001692\n",
              "availability_365                  0.000000\n",
              "calculated_host_listings_count    0.000000\n",
              "number_of_reviews                 0.000000\n",
              "minimum_nights                    0.000000\n",
              "price                             0.000000\n",
              "room_type                         0.000000\n",
              "longitude                         0.000000\n",
              "latitude                          0.000000\n",
              "neighbourhood                     0.000000\n",
              "host_id                           0.000000\n",
              "id                                0.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iHXvvHIxaoNc",
        "colab_type": "text"
      },
      "source": [
        "### **Q3. Qual o tipo de distribuição das variáveis?** \n",
        "\n",
        "Para identificar a distribuição das variáveis, irei plotar o histograma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q2wWSfeRbmBo",
        "colab_type": "code",
        "outputId": "70d3a1eb-fe3e-48b9-ff84-039095cc0144",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        }
      },
      "source": [
        "# plotar o histograma das variáveis numéricas\n",
        "df.hist(bins=15, figsize=(15,10));"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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0acovBR6zkBglaTaS7Ec32vAqukfSnFZVb0nyKrrH0XynLfryqjq/rfMy4ATg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\n",
            "text/plain": [
              "<Figure size 1080x720 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7x4aw1j5wNmn",
        "colab_type": "text"
      },
      "source": [
        "### **Q4. Há *outliers* presentes?**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ba1xYYTug6bX",
        "colab_type": "text"
      },
      "source": [
        "Pela distribuição do histograma, é possível verificar indícios da presença de *outliers*. Olhe por exemplo as variáveis `price`, `minimum_nights` e `calculated_host_listings_count`.\n",
        "\n",
        "Os valores não seguem uma distruição, e distorcem toda a representação gráfica. Para confirmar, há duas maneiras rápidas que auxiliam a detecção de *outliers*. São elas:\n",
        "\n",
        "* Resumo estatístico por meio do método `describe()`\n",
        "* Plotar `boxplots` para a variável."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ff-8gUahLk-C",
        "colab_type": "code",
        "outputId": "0b6db46d-207a-48a3-bcac-d801a18dfd8b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        }
      },
      "source": [
        "# ver o resumo estatístico das variáveis numéricas\n",
        "df[['price', 'minimum_nights', 'number_of_reviews', 'reviews_per_month',\n",
        "    'calculated_host_listings_count', 'availability_365']].describe()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>price</th>\n",
              "      <th>minimum_nights</th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>reviews_per_month</th>\n",
              "      <th>calculated_host_listings_count</th>\n",
              "      <th>availability_365</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>35451.000000</td>\n",
              "      <td>35451.000000</td>\n",
              "      <td>35451.000000</td>\n",
              "      <td>18979.000000</td>\n",
              "      <td>35451.000000</td>\n",
              "      <td>35451.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>622.242222</td>\n",
              "      <td>4.735833</td>\n",
              "      <td>7.951962</td>\n",
              "      <td>0.607775</td>\n",
              "      <td>7.884827</td>\n",
              "      <td>190.142648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1588.131281</td>\n",
              "      <td>21.958524</td>\n",
              "      <td>22.308053</td>\n",
              "      <td>0.849336</td>\n",
              "      <td>32.626366</td>\n",
              "      <td>151.889963</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>150.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>281.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.230000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>179.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>599.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.790000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>362.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>40000.000000</td>\n",
              "      <td>1123.000000</td>\n",
              "      <td>350.000000</td>\n",
              "      <td>11.250000</td>\n",
              "      <td>265.000000</td>\n",
              "      <td>365.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              price  ...  availability_365\n",
              "count  35451.000000  ...      35451.000000\n",
              "mean     622.242222  ...        190.142648\n",
              "std     1588.131281  ...        151.889963\n",
              "min        0.000000  ...          0.000000\n",
              "25%      150.000000  ...          0.000000\n",
              "50%      281.000000  ...        179.000000\n",
              "75%      599.000000  ...        362.000000\n",
              "max    40000.000000  ...        365.000000\n",
              "\n",
              "[8 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zAx_GIAzhZTn",
        "colab_type": "text"
      },
      "source": [
        "Olhando o resumo estatístico acima, podemos confirmar algumas hipóteses como:\n",
        "\n",
        "* A variável `price` possui 75% do valor abaixo de 599, porém seu valor máximo é 40000.\n",
        "* A quantidade mínima de noites (`minimum_nights`) está acima do limite real de 365 dias no ano.\n",
        "\n",
        "#### Boxplot para minimum_nights\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_-X_Z58of_dC",
        "colab_type": "code",
        "outputId": "a3badde9-7521-4dcd-c2f0-3ebf175d5b44",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        }
      },
      "source": [
        "# minimum_nights\n",
        "df.minimum_nights.plot(kind='box', vert=False, figsize=(15, 3))\n",
        "plt.show()\n",
        "\n",
        "# ver quantidade de valores acima de 30 dias para minimum_nights\n",
        "print(\"minimum_nights: valores acima de 30:\")\n",
        "print(\"{} entradas\".format(len(df[df.minimum_nights > 30])))\n",
        "print(\"{:.4f}%\".format((len(df[df.minimum_nights > 30]) / df.shape[0])*100))"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7EAAADFCAYAAACCeHUTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIRYAAIBmCLEAAAA0Q4gFAACgGf8fQ8Oi7kBBxAEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1080x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "minimum_nights: valores acima de 30:\n",
            "223 entradas\n",
            "0.6290%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R1G8lOfGxfW0",
        "colab_type": "text"
      },
      "source": [
        "#### Boxplot para price"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uQhJ229OkX_o",
        "colab_type": "code",
        "outputId": "f6d72b1d-73a4-4985-887c-23d092158f4e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "# price\n",
        "df.price.plot(kind='box', vert=False, figsize=(15, 3),)\n",
        "plt.show()\n",
        "\n",
        "# ver quantidade de valores acima de 1500 para price\n",
        "print(\"\\nprice: valores acima de 1500\")\n",
        "print(\"{} entradas\".format(len(df[df.price > 1500])))\n",
        "print(\"{:.4f}%\".format((len(df[df.price > 1500]) / df.shape[0])*100))\n",
        "\n",
        "# df.price.plot(kind='box', vert=False, xlim=(0,1300), figsize=(15,3));"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1080x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "price: valores acima de 1500\n",
            "2528 entradas\n",
            "7.1310%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TfxQ1PITFc5Q",
        "colab_type": "text"
      },
      "source": [
        "#### Histogramas sem *outliers*\n",
        "\n",
        "Já que identificamos *outliers* nas variáveis `price` e `minimum_nights`, vamos agora limpar o *DataFrame* delas e plotar novamente o histograma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "67JxJ6n_FrTn",
        "colab_type": "code",
        "outputId": "881e0789-0d14-4503-fefb-3c7e4c39915a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        }
      },
      "source": [
        "# remover os *outliers* em um novo DataFrame\n",
        "df_clean = df.copy()\n",
        "df_clean.drop(df_clean[df_clean.price > 1500].index, axis=0, inplace=True)\n",
        "df_clean.drop(df_clean[df_clean.minimum_nights > 30].index, axis=0, inplace=True)\n",
        "\n",
        "# remover `neighbourhood_group`, pois está vazio\n",
        "df_clean.drop('neighbourhood_group', axis=1, inplace=True)\n",
        "\n",
        "# plotar o histograma para as variáveis numéricas\n",
        "df_clean.hist(bins=15, figsize=(15,10));"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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J2g44FzgcOAA4Juc1MzMza2tuAJpZ14lkMH/cPr8CeDPw7Zy+BDgqT8/Kn8nzD5WknH5J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\nJEmS1BP/AbXrDOZNZgxHAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1080x720 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IXn2oIo5qx-w",
        "colab_type": "text"
      },
      "source": [
        "### **Q4. Qual a correlação existente entre as variáveis**\n",
        "\n",
        "Correlação significa que existe uma relação entre duas coisas. No nosso contexto, estamos buscando relação ou semelhança entre duas variáveis.\n",
        "\n",
        "Essa relação pode ser medida, e é função do coeficiente de correlação estabelecer qual a intensidade dela. Para identificar as correlações existentes entre as variáveis de interesse, vou:\n",
        "\n",
        "* Criar uma matriz de correlação\n",
        "* Gerar um *heatmap* a partir dessa matriz, usando a biblioteca `seaborn`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x2ayzBajqxyd",
        "colab_type": "code",
        "outputId": "022d8acc-8487-4868-f0d4-b654c33a854e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        }
      },
      "source": [
        "# criar uma matriz de correlação\n",
        "corr = df_clean[['price', 'minimum_nights', 'number_of_reviews', 'reviews_per_month',\n",
        "    'calculated_host_listings_count', 'availability_365']].corr()\n",
        "\n",
        "display(corr)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "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>price</th>\n",
              "      <th>minimum_nights</th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>reviews_per_month</th>\n",
              "      <th>calculated_host_listings_count</th>\n",
              "      <th>availability_365</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>price</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.188616</td>\n",
              "      <td>-0.163380</td>\n",
              "      <td>-0.174879</td>\n",
              "      <td>-0.016570</td>\n",
              "      <td>-0.029689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>minimum_nights</th>\n",
              "      <td>0.188616</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.082348</td>\n",
              "      <td>-0.115913</td>\n",
              "      <td>-0.041314</td>\n",
              "      <td>-0.026565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>number_of_reviews</th>\n",
              "      <td>-0.163380</td>\n",
              "      <td>-0.082348</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.627838</td>\n",
              "      <td>-0.036764</td>\n",
              "      <td>0.012013</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>reviews_per_month</th>\n",
              "      <td>-0.174879</td>\n",
              "      <td>-0.115913</td>\n",
              "      <td>0.627838</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.019302</td>\n",
              "      <td>-0.048064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>calculated_host_listings_count</th>\n",
              "      <td>-0.016570</td>\n",
              "      <td>-0.041314</td>\n",
              "      <td>-0.036764</td>\n",
              "      <td>-0.019302</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.073542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>availability_365</th>\n",
              "      <td>-0.029689</td>\n",
              "      <td>-0.026565</td>\n",
              "      <td>0.012013</td>\n",
              "      <td>-0.048064</td>\n",
              "      <td>0.073542</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                   price  ...  availability_365\n",
              "price                           1.000000  ...         -0.029689\n",
              "minimum_nights                  0.188616  ...         -0.026565\n",
              "number_of_reviews              -0.163380  ...          0.012013\n",
              "reviews_per_month              -0.174879  ...         -0.048064\n",
              "calculated_host_listings_count -0.016570  ...          0.073542\n",
              "availability_365               -0.029689  ...          1.000000\n",
              "\n",
              "[6 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "91UujDr6ueqE",
        "colab_type": "code",
        "outputId": "c5dc24b3-bd68-482d-803c-414d053991bf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        }
      },
      "source": [
        "sns.heatmap(corr, cmap='RdBu', fmt='.2f', square=True, linecolor='white', annot=True);"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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094qd4zTJKaWUcl6VMrjv69VUsaNTSilVobmJOPRwhIj0E5EjIvKriEwops4w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\nXDSf5GkAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7b6RMWpuHKN-",
        "colab_type": "text"
      },
      "source": [
        "### **Q5. Qual o tipo de imóvel mais alugado no Airbnb?**\n",
        "\n",
        "A coluna da variável `room_type` indica o tipo de locação que está anunciada no Airbnb. Se você já alugou no site, sabe que existem opções de apartamentos/casas inteiras, apenas o aluguel de um quarto ou mesmo dividir o quarto com outras pessoas.\n",
        "\n",
        "Vamos contar a quantidade de ocorrências de cada tipo de aluguel, usando o método `value_counts()`.*italicized text*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ueLPNWvPHgfB",
        "colab_type": "code",
        "outputId": "dab5a35b-026d-4c16-9a71-1140809c5159",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        }
      },
      "source": [
        "# mostrar a quantidade de cada tipo de imóvel disponível\n",
        "df_clean.room_type.value_counts()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Entire home/apt    22491\n",
              "Private room        9404\n",
              "Shared room          842\n",
              "Name: room_type, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EvwoO-XAHhIm",
        "colab_type": "code",
        "outputId": "2e328d91-87f0-4e17-da5e-8f2e787f140f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        }
      },
      "source": [
        "# mostrar a porcentagem de cada tipo de imóvel disponível\n",
        "df_clean.room_type.value_counts() / df_clean.shape[0]"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Entire home/apt    0.687021\n",
              "Private room       0.287259\n",
              "Shared room        0.025720\n",
              "Name: room_type, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MFa5NbnLJMcd",
        "colab_type": "text"
      },
      "source": [
        "### **Q6. Qual a localidade mais cara do Rio?**\n",
        "\n",
        "Uma maneira de se verificar uma variável em função da outra é usando `groupby()`. No caso, queremos comparar os bairros (*neighbourhoods*) a partir do preço de locação."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MD_xa143JZpi",
        "colab_type": "code",
        "outputId": "4f893c5c-e123-485d-a70b-287907e4a61c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        }
      },
      "source": [
        "df_clean.groupby(['neighbourhood']).price.mean().sort_values(ascending=False)[:10]"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "neighbourhood\n",
              "Vaz Lobo                  967.000000\n",
              "Anchieta                  633.200000\n",
              "Ricardo de Albuquerque    605.750000\n",
              "Jacarepaguá               528.572654\n",
              "Complexo do Alemão        518.750000\n",
              "Vicente de Carvalho       505.000000\n",
              "Barra da Tijuca           503.296127\n",
              "Maracanã                  485.982993\n",
              "Lagoa                     481.692098\n",
              "Leblon                    475.864206\n",
              "Name: price, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wTt-H7G0Q87F",
        "colab_type": "text"
      },
      "source": [
        "Acima, vemos que a comunidade Complexo do Alemão está com média de preço superior a de lugares como Leblon, Barra da Tijuca e Lagoa.\n",
        "\n",
        "Uma pessoa que não conhecesse o Rio poderia apresentar esses resultados sem se questionar. Só para dar um único exemplo de como uma amostra pode ser não-representativa, veja quantas entradas há para o Complexo do Alemão."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "07RIuc0ERlVc",
        "colab_type": "code",
        "outputId": "7c74eec8-1553-4ee4-c246-10aca8b4b297",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 344
        }
      },
      "source": [
        "# ver quantidade de imóveis no Complexo do Alemão\n",
        "print(df[df.neighbourhood == \"Complexo do Alemão\"].shape)\n",
        "\n",
        "# ver as 4 entradas do Complexo do Alemão\n",
        "df[df.neighbourhood == \"Complexo do Alemão\"]"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(4, 16)\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>id</th>\n",
              "      <th>name</th>\n",
              "      <th>host_id</th>\n",
              "      <th>host_name</th>\n",
              "      <th>neighbourhood_group</th>\n",
              "      <th>neighbourhood</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>room_type</th>\n",
              "      <th>price</th>\n",
              "      <th>minimum_nights</th>\n",
              "      <th>number_of_reviews</th>\n",
              "      <th>last_review</th>\n",
              "      <th>reviews_per_month</th>\n",
              "      <th>calculated_host_listings_count</th>\n",
              "      <th>availability_365</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12438</th>\n",
              "      <td>12253055</td>\n",
              "      <td>Triplex House for Olympic Games</td>\n",
              "      <td>65969079</td>\n",
              "      <td>Andrea</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Complexo do Alemão</td>\n",
              "      <td>-22.85729</td>\n",
              "      <td>-43.26518</td>\n",
              "      <td>Entire home/apt</td>\n",
              "      <td>1398</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21543</th>\n",
              "      <td>17148972</td>\n",
              "      <td>Casa Brota</td>\n",
              "      <td>101966262</td>\n",
              "      <td>Thamyra</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Complexo do Alemão</td>\n",
              "      <td>-22.85692</td>\n",
              "      <td>-43.27611</td>\n",
              "      <td>Private room</td>\n",
              "      <td>41</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>2018-10-07</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1</td>\n",
              "      <td>89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23723</th>\n",
              "      <td>21090668</td>\n",
              "      <td>Be a Carioca in our Guesthouse</td>\n",
              "      <td>10459831</td>\n",
              "      <td>Ozomatli</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Complexo do Alemão</td>\n",
              "      <td>-22.86792</td>\n",
              "      <td>-43.27700</td>\n",
              "      <td>Shared room</td>\n",
              "      <td>37</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2018-03-07</td>\n",
              "      <td>0.17</td>\n",
              "      <td>4</td>\n",
              "      <td>88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24008</th>\n",
              "      <td>21448656</td>\n",
              "      <td>Casa 1 quarto alem</td>\n",
              "      <td>155642978</td>\n",
              "      <td>Felipe</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Complexo do Alemão</td>\n",
              "      <td>-22.85954</td>\n",
              "      <td>-43.27623</td>\n",
              "      <td>Shared room</td>\n",
              "      <td>599</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2017-11-28</td>\n",
              "      <td>0.05</td>\n",
              "      <td>1</td>\n",
              "      <td>365</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  ... availability_365\n",
              "12438  12253055  ...                0\n",
              "21543  17148972  ...               89\n",
              "23723  21090668  ...               88\n",
              "24008  21448656  ...              365\n",
              "\n",
              "[4 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4nMyAfrBS3s1",
        "colab_type": "text"
      },
      "source": [
        "Como são fornecidas as Latitudes e Longitudes para os imóveis, é possível plotar cada ponto. Para isso, considera-se `x=longitude` e `y=latitude`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UxVJqJ_3W59I",
        "colab_type": "code",
        "outputId": "77b1e214-c42a-41f0-fe31-4bc4da80f8ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        }
      },
      "source": [
        "# plotar os imóveis pela latitude-longitude\n",
        "df_clean.plot(kind=\"scatter\", x='longitude', y='latitude', alpha=0.4, c=df_clean['price'], s=8,\n",
        "              cmap=plt.get_cmap('jet'), figsize=(12,8));"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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v9+HNcBAPapIkQbmx4pqkO0lV1Se9mzIzAkwoX8Xu9V5KSw1efn4MXsdEJo614XZBVhaY\nJlSOCnHoIMRiUTZt7GfHDhfTpvmG8V0QZ+0CKyUZtuBWKfUvwEogBhwC7tZa9yilrgR+ADgHXvum\n1vrN4xw/E3gEcAMJ4C+01huUUgr4D+AaIATcpbXePBT3JIQQQpwLl11WSGtrgqamTqJRJy5nH20d\nvYRiCfKqsnj819U4jATBQzGUYzSG6UGHLOyOPhbcbGP16kM0NYW48soSps8PYhGhJVhBQ0jRuhe0\nW9NwAKZNhPnz4aab4Iu3u3lvXT2FBQZVVS62bg1JcHs+8pgwWcoShsofgb/VWieUUj8E/hb4G6AD\nWKm1blJKTQVWA6XHOf7/At/TWr+ilLpm4PllwNXAuIGfBcB/D/wphBBCnJdcLhvz52cRDhv8+tf9\n5Of76EWTiIYJRqIcbNDcd0sRxcV9HK7Poi2iaOsM4XBn0LOtkbUNCSZNymDVqnomTB5N8VgfvgKL\n3lpFRmkesahBfwAKCmHLFli6FGbO9HHnndns3RvG5TKYMMFz6oGKkScSgH1SljAktNavHfH0feDm\nge1bjti+C/AopVxa6+inTwFkDDzOBJoGHt8A/FJrrYH3lVJZSqlirfVx5oIKIYQQI9+BAwGeeKIO\nMBg7VpOT76bWFsKBiXe6D93cRU1NP3kFBnnFLtauTdITtVOQ209/LMD2fYr6eotJkxQOw8/skqtZ\nfFWcPRsSbPxDP9s6YuRmFdHT7cA0wTeQoL377nwOHozgdhtUVbmH9T0QZ8ltwiTJ3A6He4BfH2f7\nTcDm4wS2AF8HViul/pVUd5LFA9tLgfoj9msY2HZUcKuU+grwFYCKiorPNHghhBDiXGpvj9Lb66Sm\nPpuO7hhf+KKHhrwknQd78agEn79nLN6Ih8Z+F7lZLpZPamNPcwv27Do8eEj0h+l9P5PKytF4vXa8\nZPDgZZq/e+MQX/mCk56uOKavm/nz85k9W+Fypa7rdBpMnuw9+eDEyDZMmVul1GPAdUCb1nrqwLbj\nlqQOvPa3wJcBC/hLrfXqge0rSJWb2oCfaa1/cKprn9PVgZVSryuldh7n54Yj9nmIVM3sU586dgrw\nQ+CrJzj9nwN/pbUuB/4K+PmZjE1r/ajWeq7Wem5+fv6ZHCqEEEIMqQkTTLbvsrHzQDuu4i7W7Oyl\nzEpCzEmyPsKCCi+9tmymjPMSckbIu6aGP/2bCLPvDTJqtp3yOW4mzitj/vysj8+Z61dMqnISDsQJ\n9EfZe6ib/1xVxw/WBKjuG8abFYNLkQoLB/vn1J4AVnxq2x+BqVrr6cB+UiWpKKUmA7cCUwaOeVgp\nZVNK2YAfkyo5nQzcNrDvSZ3TzK3W+oqTva6UuotUVL9soIzgo+1lwIvAnVrrQyc4/E+BBwce/wb4\n2cDjRqD8iP3KBrYJIYQYBrE4WEnwuIZ7JOevdet6aG3tJ9Drp2arIvPKKHs/cNDfGac1pLj/ng1U\nzigjuqQKlWHHdBpYgEu5KJkewKgtYvzyLGZPP/q8d95ZzPr1PaxbF6DZZsPy2NnxRhdPj/Xx0HSF\nusBm2acltwkThr4sQWu9RilV+altxy1JJVVS+uzAN/WHlVIHgfkDrx3UWlcDKKWeHdh398muPZzd\nElYA3wKWaK1DR2zPAn4PfFtrve4kp2gClgBvA0uBAwPbVwEPDLwBC4BeqbcVQojhUd0Mv3oTEhZ8\nbjHMGTvcIzo/7dnTT1FhiJzKEG2NBtMXGFSvy6anI0A8ZhDuz8BI2qjMb+cb3yqnIGMih2ljMmWU\nObNwj3NhHOfL2mg0SUmpl9Z+2Lk3iDM3wahSG3ZDAtu0EQnAgRE5oezIktRSUsHuRz4qKYVjS01P\n2SRgOGtufwS4gD+munfxvtb6PuABYCzw90qpvx/Yd7nWuk0p9TPgEa31RuBe4D+UUnYgwkD9LPAH\nUm3ADpJqBXb3UN2QEEKIo72xFdxO8DjhDxskuD1bV11VwGuvdWAFEiy91MldSyax7pc1HNgbJWl5\nsdmSJK04Vr+PyRUAfrz4eJkg/0OEJSjmcvSEsP37A/zyl43UNkJ7wM2lM/xs6U4y7+os7qgaltsU\n54LbhPHnJHObp5TaeMSGR7XWj57OkScqSR0sw9kt4bj/xWmtvw98/wSv/dkRj98F5hxnHw3cP0jD\nFEII8RkUZMOhFug3oKJguEdz/po5M4Onn55Fa2uU0aPdPPJIA8lYEL/fRjgYQuPF68ni8sv9bNsZ\nYXNtGGOaorEiSRE23iDEBJz4j8je7t4dwOUyGD3axYF3wsy/qJSyUXa+sRBMaWebPqIBOHROMrcd\nWuu5Z3rQCUpST1ZSesalpiOlW4IQQog0tGIO+D0QT8CiScM9mvNbYaGLwkIX//zPNTz1VCtdXVF8\nHoPSYh8us4DcaVn0V2j+cUcTkbwE0SbF1NwMMn2pgoRPzwEaP97Hhg29xBNhyid7aTFtXD7K4hdP\nxDAMxfXXuygtldqEtHBO2wecvhOVpJIqKX1aKfX/gBJSaxVsIDUdbpxSajSpoPZW4PZTXUeCWyGE\nEOeMywFLZwz3KNLL9u1BKio8mKaN5uYIoyr9bOzNprXBoPrHcWyXxihoTxLN1WRVJsnwGazAixeD\nWEwTiUB9fYy1ay0mTsxHFTpIRr0Eu5M89KsYoTf7yPYr1q3z8tOfmnhk7Ybzm8uEsUM/oUwp9Qyp\nxbXylFINwHdJdUc4piRVa71LKfUcqYliCeB+rbU1cJ4HSC3oZQMe01rvOtXIJLgVQghxWgKBBFu3\npr7KnjXLxG4fIemgC8zKlXk8/HA9hmFw332j2LAlSmB7K3aHn7CZRc4kB/FpUew2zRVxLxcNrHfU\n0pLkscdidHUlaWgIMGeOnfffj+AclcQ2yU1XiyKaSOLPsmNoTUtLnGAQCW7Pd7EAVA/9hDKt9W3H\n2XzCtq1a638C/uk42/9Aaj7VaZPgVgghxGl58slW6uqiJBKavr4Ey5blDPeQzmsNDQnWro2Sn29j\nyRIXDsfplQDcdlsBs2b5icU0Hk+cRx5ZR6TFIGn48GZNZVanjXCDF5/DwWjTBGDPniRPPRVndx0E\ntI2a3ZpRoxLs3RtmoiNBTa/CX+JnvKE51JfA5jVYutRNjvwVn/+GKXM7nCS4FUIIcUrJpKahIUp5\nuYve3gQNDcdbOFKcrlhM88QTIZTSbN0ax+VSXHLJ6TUCVkoxaVJq1bCHHtpIOBzG5cjAMPoYXZRk\n5mWlHESTl23juQM2rvDGePDBPlpaEzR3u5m52IuvwMuhuiB5eQa2JPSt6aR8SoI7VvrR17kpKrKx\nZIlH2oGlg2gADo/IVmDnjAS3QgghTskwFMuWZfP66904HIqLL8469UHihBIJTTisKSkxiEYtAoHk\naR23fXuA/fujzJrlwzQ1hw71k5dnJxgK4fV6WbwwE3+xgzEGJLuDvPO7dnY0WdTXe6gaq2jvjuL3\nO5gy28dd1/v4cG07P/5xD0o5qK+Hp55qZcqUBNu2KdzuPBYulL/n857LhCrJ3AohhBDHuPzybGbO\nNHE6DXy+01t/Uxyf12twzTVuXnklQn6+jYULT561TSY1778f4j8ebqelx4b9VwH+4Ts5VFSYmKaD\n/PwI1143hRs/b8ddAA+vjfDLb28g0ZcgHorjdo9l904v48daXHapi+mTDGZNglmTCnh7jcHeakVv\nDPoagqxYkUkoZLFtW0CC23QQC0CNZG6FEEKI48rOdgz3ENLGRRe5WLjQic126u/+X3ghxK+f62Xd\nhiizF5g0NSX47Wony68oZ9vWdq6+LJt5bS9w+L8hc9nlzAzl8liXwvR5aO0xmDSlG7/f4h+/V8rc\nuUd+9CvKJvjYVx9FKSgbk0l9fQStYdEiCWzTxgU291OCWyGEEGKYnE5gGw5rXn45Qk+3QSxm48P3\nw+QVGQQ6N7PvgJ1lS0fTsnoDqw7ksTcxlsB/dbK1zUdXZyndXd3Y7Am6rWKKKgrwZR+bIS6q9LBi\npYNkEgqKM1m5KIzDYVBZ6T7OaMR5x2XCaClLEEIIIYZNIqFZvbqbQ4fCLF6cycRpJntbwXTBhAIu\nuElOLheEw0nAYOKYDOo6fPhdrTiVk42bY9Qd3AOtPrbs9jAmt4M9hzPYVuNE4UBrk0yzj6uX55FX\n7GbTbpg0JnXezgQ81Qt1CxWJ9Q7yw3DxbBhV6cPlHNZbFoMpFoA6KUsQQggxQllYKBRGGn/PuHt3\niHfe6aWoyMmLL3aQ0eamO2FHa7h5JswbNdwjHFqGobjrLpPnnw/T22cj4nDSmcjkD+uyWbFoAz6v\nDzVmDJ7GBmqiObQ5c1AKDAVaK/ILvWzZHGfuJXDZ/E/O+2YIuiwYkwcdy2H8Jnju90ke+UWM6y9N\ncM1VXlyu9P13dsFwmlApmVshhBAjUC117OcAblzMZhY+fMM9pHPCsjRKKex2RVwbNPfDxFLoCEBd\nF8yt0AQCCbxeGzbbhRF8XXutm8mTHazbCD/+lY0peQ6a20IsvMTFkz8rp7MzjmHkU1Hpp0gZ1B4I\nYllu7PY4C2a7mLPQzjXXwvjKT87pBGIagklQYdh1CJrrghxu0IQ6Y9iVxcqVmcN1y2KwSOZWCCHE\nSJQgwX72Y+InSIgaapnC5OEe1jkxZYqXuXNNDh4MM/8a2BBv5IlXXbgTDhZ8zsmTT7ayd28fJSUe\n7r57HF5ven+UtbQkqalJUl5ucM0Kg9XbINiZydTFmZSU5zNjRoANG3ppbEzi8wU4dDCJy+vD5osw\nbYLJggUe7vuqB8en5gJeYabWOe214LJC+LUXtu+OEgwlMAI9VFdnAxLcpoUL43fAj6X3/whCCDFC\nRYhTTSsGBmMowHGK/44NDJw4CRMmQRwXp9fw/yOJRJIdO3qwLM20aVm4XCOzlde2bRFqaxNcemkm\nV/2Jj9fYTuyxBIVOzeTsPF57wcLhiFBZaXL4cICDB/uYPn3kLKPV0hKiurqPsjKTigrzM5+vq0vz\nyCMx4nEwDPja15x8936DjQehqhCmlhn8z7MGO3ZYJBLQ1WURjsVxzSkkkG1jj9vBjjqD5uY4fr/C\nshx0dUF5Ofg8cFPGJ9e6dUWCt1/tJ2iLY0uEyczMOPHAxPnDaUKFlCUIIYQ4xz7kEG30kkQTJMIc\nqk66v4HBbGZRQy1u3FRyZoWnq1c3sWZNO6A5eLCfW2+t/Pi1zk5oaYHSUsga4u5PkYhFMgler413\n3w3x13/dTjyepLjYwW1/btAyNYrP7cIWDRIlSl62h3A4SktLGICMjJHTmqynJ8pPfrKHeFyjteb+\n+ydTUnL80hGtNe8n4+xPWkw37MyyHf8+uro0sRhUVhrU1lp0dGgmT4bxpR/tYXDJJSZvvhmnv7+f\n/n7w5TuJlmmM5gRZ3hjPvlTP8z/vYdo0F1VjxlJckkNREdz3FXAeMXGstMhg8Ywk4bAmkXAzebJ3\ncN8gMTziAWiUsgQhhBDnSJwEAaJ0EsCPB4skvYRO61g/fqYx9ayuW10doLDQhd1uUF0d+Hh7Rwf8\n+McQjYJpwgMPQMZpJuwSCc2qVT3s3RthwQIfS5f6UWfQyuDAgQBPPtmMZSX5/OcL+f3vwzQ3h/H7\nNRs3xih6yY2/3SRzej9zXJmUR3K4enkBwWCMHTu6GT3aT2Wl/0zfinOmuztGLJZk1Cg/NTX9dHZG\nTxjcHtZJXrFiuPs1a3b1ckeWh0sm+7Hbj/7+uLRUUVSkqK1NkpNjUFFx7PfLCxca5OcbdHW5yM21\nmDoDOicomjMVrRvaCTWHsVluPtgGHcEWHlyUQ20ddHdDYeEn53nzTYPu7jJ6enq57TYnc+dKSUJa\ncJpQLplbIYQQ50CEOG+zixAxoiSIkcCBjVlUnvNrX3JJAc8/X4fWcO21JR9vb2lhIDMItbXQ3n76\nwe3+/RE++CBIebmTN97oZ+JEN6WlJ+8hFQgkcDoNQiGL555rwe1W+HxOXn21A9O0YxiKSMRGMhmh\narQfR3sJ/g8N/vy+go/PkZ/vGlFB7UdKSryUlvqorQ2Qm+uisvLEZQkxND01Cdb/r0aaD4doq3IT\nvKOI667LP2o/j0dx331OOjs12dkKt/vYXx5KS+GGGxT19Q7y8lxYluYv/trPz/8nwk/WJwjGDOJ2\nDU5oxM6GFs20fEV29ifnCAbh3XdhwgQXra0FH5dBiDQQD0CTZG6FEEKcA10ECBIlFz+d9DOPMRST\ndcp628Ewc2YOo0b5SCYhN/ftmBcPAAAgAElEQVSTet2yMvB6oa4OMjOhqOj0z2kYClDEYvqI5yf2\n+uttvP12O5aliccd1NSECAQsZs40GTfOx6xZfurrG+jtVZSXu4hEIB5PcuON58dKWS6XjXvvnUhn\nZ4TsbNdJ65rHKht6fYSe7jiVFW4inZp9+0Jcd92x+zqdiuLik7+311/v48kn+wgGk9xyi58sF3z9\n8y4Kwrk8+PUI/V4HHrsNFfXz6h/bCJYGuWJZIVOm+AbGDn5/6pedSATy8j7TWyFGmgvsFxUJboUQ\nYoiYuFEoOujHhkEO5pAEth/JHlid6oMP+lm7tp+qKhcrV2bzta8ZtLVBcTH4zqC72PjxLpYt87Nv\nX4QbbsiiuPjoutFAEA7VQ6YfinIt3nqrnbIyDxs29BAMRpkxI5MXXmihrk7xp39aSiKhmDw5g7Iy\nJ9dem08yqTAMzqteqw6HQVHRqWtV7UrxuTIvnXleamuDGKbBokVnXwZQWeng29/OQWtwOFKBsM2m\n+NKX8ujtDfPz9+3U7DXoz4D+A1FWH7RQqoknnxyLYSjsdvjyl+HDDyEnB+bNO+uhiJHGYUKplCUI\nIYQYRIkEtLaC3+/h8owpdBMgFz8mQ7+8aWdnnFWruikocPLBBwFGj3Yxa5Z52qUIRzIMxdKlGSxf\nfuzBiQT8/LfQ0g4a+NJKg6wsB83NEZxORSKhWLOmi9JSF1Om+HjhhSZCIQemaePDD4PMn59FWVl6\nL/+6ZIkfv99GfX2YGTN8jB3r+Uzns9uPn929554SRo/t5ruPw/Y1QZLhJAG3pqHZOmq1t7w8uPrq\n45+7rc1i/foo2dkGixe7TngtMQLFA9AsZQlCCCEGSTIJTz8N+/alZqbfe6+PqhNMMhpKWuvPdHwi\nAS/8Hrbthklj4dbPcVQf1UAI2jphdBk0tUF9i+Luu0fx4YfdZGU5KC728vjjtUSjCaLRJB6PA601\nubl2+vstQqHkZ7zDkc9uV8yf72P+/HP778HrtXHtijz2WyF2b+ojGo1jqTglxY7TmgBoWZrHHw8Q\nDqc6KWgNS5ak9y8eacVpQolkboUQQnxGWqdW2erpSQW2o0ZBYyPs3g0lJac+/lzJzXVwww3ZrF3b\nz8KFfqZOPbt2T7UNsHUXVJbDrv1wqAYmjvvk9QwTxo2CA7Vgt8OUsZCX5+Lqqz8p6n3wwSpefbUF\nw1AsW1bA6tXd7NkTYtIkD6NHS/A02K6fauOpS6CrU5HdD7nZBpalsdlOHuDG45r+fgt/lp0t+y1C\nryeZOhNypZnC+SEegBbJ3AohhPgMdu8O8dxzXfh8Bl/4Qh45OU4OHwatUxO4htv8+X7mz/9s3QY8\nblBAdw8oBZ5PfaNuGHDHylTWNsMEpWHr1tRX3x+9Bzk5Tm66qZSXX67nsccOctllhdxySyVO59nV\n2MZiFuvWddDWFmfu3GzGjBn+DPlIMmaUi7+6wuTpp9vJq3CwZEn2KQNbALfb4MorvfzgRyES2HDn\nunhpLXz5OJPfxAjkkMytEEKMOMFggt/+to729ggrVpQwefLInT2vteb557vIzk59vf7OO73ce28+\nBw5AdjZUnXythvNGSRF84QbYsReuHAejjhO02+1QUZKaff+fP0r1VVUKvvJnqdZjANu397BpUxel\npV5WrWpg3Dg/OTlntvoaQH9/nIce2szLL3dhszkYN87Po49OZ9Soz1bHmm6++MUCLr88k0hEM2rU\n6b/PS5a42djoJBJXoBTxxDkcpBhc8QC0XliZ2/NnCqoQ4oL17rtt7NnTC8Czz9YSjVrDPKITU0ph\nmjZ6exOEQhamaSMjA+bMSZ/A9iMzpsAdN8Gc6Sffr60Ndu1JEE1ESMShqRmSSc1770V49NEG3n+/\nk4aGEEqdup3YiRw61Mf27X1YloHTmaSzM0p19ektjnGhKSlxUVXlPq2s7ZG+cIWBz6MwPXDDxedo\ncGLwKVLR3mD/jGCSuRVCjHgfzXnROvX4DBbBGhZ33JHH66/34vMZXHllJoGA5vnn47S2Jlmxws6M\nGRfWf73rN/fSYTXS0hwn051J1ehKVr+R4Oc/a6OhNoJludm6tZvvfW8aWVknXwTiRNrbE2zf3k1f\nnw2bzc6yZZlMmnTiRRTEmSsrgK/fMtyjEGfMYUKRlCUIIcSIctFFBXR0RGlvj3LbbZU4nSdujj8S\nFBQ4uP32T7rgr14dZ926EF6vxTPPeJgwwXbclabOV4lEku3be4nHDebN82N8ammr2vZ2JkyKYFMO\n+kPdrNtdyrO/UxzszSDT340TN7NmaaZPzznrMWzc2IvDYae83E5fX4K77iqnqOjMyxuESDvxALRd\nWGUJEtwKIUY8n8/O7bePHu5hnLVdu7p5661u4vEoubk+vvvd0aS+K0wPP/1pHU88EUEpg+tWBrnl\nK8U4DU1lbirIvewyzeNPQ9LSXLK8l01bbcydDu2tbkKduVSVdXHbbeX4fCf+SAoENH19msJCddyv\n06uqPDgcNsBGVpbx8cpbR9q8uY8DB0LMnOlnwgSZbCYuEA4TCiVzK4QQYhBFIm043X2UjQljZm6n\nviGb8ePOPks5mPr74+ze3U9Ghp2JE/2n1ff0SIlEkscf76KpyUY4HOe//jtOm7MWry/B9QtLWTy7\ninnjqij91iGiVojm3eP49eYOlNPFjFkm1y8pYdnCk7eQaG1N8uijMcJhGD/e4M47HcfU5t54Yyl1\ndUE2berk+utLmTz56IUlqqtDPPdcK36/je3bA3z96xXk559dCYQQ55VEADokcyuEEGIQ+f1eLrr+\nOXKL+snJsXDkFAPLhntYJJOaxx+vpbk5QjKpufnmUubNO7Ogu6UlgmXFaG31kEzasAVjHHgnwNKb\n3ezYupvFs6tQ2Cj1jKe/P8Fjqw5w8SQ3u6oDzK3SLF1w6s4Xu3dbxGIwapTiwIEkXV2avLxPBeGG\nwTe/OfGE5wiFkigFeXkOamoihEIjd1KiEINuhE8AG2wS3AohxCDRWhPq6MDh9eL0ffK1t8PhZP5i\nTUdTIX5fgozc/kG5XrcF60PgM2CRF5xnWOnw7rstrFpVz7hxJoWFPhobw8ybd2bnyMx0UFCQwOns\nxm63YXfEaGh30BWGS4sCR+37UTcEu5GkJDPKmNLkaU0OLCkxaGwM89ZbEXJyFLFYJpDKuiYs+M0u\n2NkKE/Ph1mngOE5J9tixHsaM8XD4cISZM/1pv7SvEB+zm5AvZQlCCCHOwt4XX6Rp40bsbjez7rmH\njIHVCqZP9/PetvmUj99EaakXkzOMIE/gFz3QZUFMQ1TD8jNoDtDREeHVVxsoL3ezZUs3M2cqZs+u\nPOMx+P0O7r13NF1dh6it1eTnmXznzn4untpH+awrjtrXNO3ccksJb73VwYIF2cyZc3pLXI0da+Dz\n9bJggQOHI8577yluvjk1Ya+2F7a3QmUW7GqHQ12pIPfT3G4bX/5yKdFokpqaKDt2BJk40YvbfYGl\ntMSFxwpAl5QlCCGEOAPt7XEaDvdRt24bpeMqCLa10bR588fB7eLFmZSWXkncWkxlpQ87Z5Y1jEY1\nlpWkt1eRna1wuxVJDZ0WFNmhx4L2s2yqP326ic+nuf32cioqzm4p3s9/voSZM7Po6ooydqyfrCzH\ncffr7tbs3u2lqKiCpUttuFynl2pWCkpLwbLiBAIWPt8nAanHPrBSWjj1p/f4lx44j2LjxgCrVnVh\nGKls7p/9WdGJDxAiHdhNyJPMrRBCiNPU1hbn4YdbiUYtevZO4VpjJy4jSkZJyVH7jRrlhjMJapNd\noMOsXZfLr54Ms2ZNgvx8G5dd5uGb33SjlIXvrU7W2+2MXZjNkiyDZFKzdm0nBw8GmT8/m2nTMk54\n+rw8NytXVrBuXSvLlpUwb95x0p2nSSlFVZWPqqqTdyD4zW8sGho0WkM4bHHnnaf3EWQYijvvLOCN\nN3rJzLQxZnwmq1ZDeSnMnAK3ToWdbamMbcVACW8yqXn11VY++KCLGTMyueGGErZs0fzrv4aJxWxc\nfrmdw4cjJBIauz19OlcIcYyEZG6FEEKcgZaWOPG4ZvRoD9XxWWTNK2Hc5CwKpkw5+5PGD0Dkl0Qj\nsPoP17NnTwWBgIHDYbFhQ4wDB+w8/PB+du8OggFL7iml7Mul7NkT4A9/aCM318mzzzZSXOwiL+/E\nvV4XLSpk0aLCsx/nGQoENBkZYFnQ0KP5r87U9psyoORTGdfDhwP09MTIzXVSXu6jpMTFl75UQF8/\n/L+fgGHAug/B54HpY2B68dHHHzwY4Ac/qKW7W/Hmm32Ulfn43e9Mpk71sXZtmPXrLe6+O1MCW5H+\nFDCyW4MPOgluhRDiMygrc+LxKGpro+QXm8y+rgqv9zN+kiQ2g3Jjd+XS1trN4cMltLU56O83AEUi\nEaemJkJFhZuurjg7tqUmqMViSQD8fjvd3XFiMf0Z725w3XCDwbPPJjEM4DIbfcnU5+5v++CB3E/2\n27ixk8ceO8TvftdCJJJk4cICfvzjWZSXewiGIJ6AilKortGsXRuk+oDFggU+srM/+Uhbty7EoUNR\nsrIc1NQk2L8/itfrJx73MmtWCfPna669NhX4d3XFaW2NUVrqIiNDPhZFmrGZkCNlCUIIIU5TTo6d\nv/zLItrbExQXO44KbA+u+YBNr2yhfFIZC29fgWE/zf9ybVUQ34yNfgrzq5g8yYlSmsxMzeLFdgoK\nHEyd6mPjxlRQe9VVqfZdEyeaTJ3qZ9++AJdemkNx8chYoaujI0Ffn0V5uYPvfCf1Hvy0W9FiDSx7\n/6nk6f79fRw6FKSvz8KyFG++2co3vrGP7353LBMnmsyYDFt3QbCnn53dfdRWG+zdG+HBBws+7tOb\nmekiPz+DRCKK328ydqyPK64weOutJHPn2rn8cgPDUHR0xPj3f28gmdRkZtp54IFSTFM+GkUasQLQ\nLWUJQgghzkBGhv2YjF9vcxv/+U876bUKSbzdjbNgF3NXzDi9EzrmgpEJOsTsReV0BZMEgqmlZadM\nsVFaauf73x/L9u0BcnLsTJqUapPgctn40pfK0Vqf8WIMgyIaJbj7LTq9rXgq55HtGs/Wxk5++1wf\nut3DmCo3d9+di82muDEDXuoHDdzgTx2utebgwSgej4dkMlWXm0wqDMOgoyPKli19TJ5s8icr4dor\n4OWXElRX28jJsdPUFMOy4KPfH5Yu9bN9eyHbt0e46io/kya5efnlLrq6LObOzcDtTtU//+Y3jbz4\nYg1aJxkzJpMbb8xj/Hj5aBRpxC6ZWyGEEIOgt9eiM+CmvCxGQ0hzuC7J3NM9WCmwjwdg5UrN+PEx\nens1OTkORo0ycDoVTqediy46/gIIwxLYAok3XuSg9y3ohTb2s3vCVXwQ0wTnxinvKqPmQ0Vfn0V2\ntp08O9yTmaqdBTh4MMpPf9rFwYMRqqoczJ5dSlNTnMOHY9jtTjo7Nb29iYH7A58XLr3UpLo6SlNT\nnCuvzDiqfjaRUOTkZDFrVpIrrnDz7rv97NsXITvbztNPd/HQQ8WEwwk2b+4iFrPQGurqAvT2hgFZ\nmlekESsAvZK5FUII8RkVjy1k9EUVHNrWSmZJKbMvH//xax1BaAlAiR9yTtF9y25XTJkyMsoLTiXR\n3kBiqhcz6MLq66eNDiq8ozncGeBwtIeJhTn4/bbUwgtbYGcLFFsBpmREeOWVGIcPx+jstKisdBIK\nObjmmnI2bOgnkdBMneqnoODo96GszMm3vlVIPK7x+Y6uc/71r0O8/HInkKC6OoObb07NWEsmk/T0\nJOjsjJGd7SAvz0l+voFlgWkaPPtsOw0NSVauzMNulx64Ig3YTMiWzK0QQojPqNZ+mPnfi1BZm82M\n7CrGFKaygV0h+PEGiCXA44AHFkCWZ5gHO0hc85dTsPNx2kt6cJXMZDQTebsnzoGdYzBDJvd80cQw\nFOv2woYayIj08eSLdUwt1BzeF2f27EIaG2M0NcW49dZsSkshN9fJ1q0hwMa4cSYffNBDJKKZM8eP\nadpxOg2czmPHUlvbTzyuyc52UVvbz7x5pXR2Jli9uhu/3+JHP2rgnntKePDBceTm2jl0KEhPj43y\nch/r1/cwbpyXqVPPYFUMIUYqydwKIYQYDI00kufxkzMxSYxmYDSQytjGLBiVDbU90BY8u+BWa3jv\nPdizB2bNgjlzjr9fT0+Mnp4YxcUeXK5z2w9oj65ke99XGF1gZ0ZJFQqDR1+OkWiw0Ze08/DzMH8M\nPP4KNLphamYEu91g/AQPVrgXm01x0005XHONyYQJLgxD4fG46O7uIRqN8s1vHqCiwkFBgYu9e4N8\n9atlJxzLFVcY7N4dwbJsLF6cIDfXwY03ZrFvXw+jRpm0tsbYsSPA9dfn841vTKKlJcp//mc9WmtA\nfVwucSIffhhk794I06Z5mDnz7Ba/EGJISCswIYQQg6GAAmqpIxSy4esaQ3cWZJtQmgGmE+p6INOV\nKk04GwcOwC+fhtxcqK6GkhIo/lSv15aWMD/5yQGiUYuSEi9f/eo4HI7B/6q9MwaNbVGefaoev2ln\ny/4ouaVhxo41SUZcqCQ47dDeDb97Cwq9QFxTW+tiqgldzUGWLs3mi18sxvhU64Tu7iShUJQdO5qp\nr48TCjkYO7aIxsbISSfOLVuWT0aGors7xrx5edhsBl6voqTERXV1mFgMenvd7NwJU6ZAUZGL66/P\n44MP+rj88mwmTDhx3W1NTZTf/raHzEwbe/ZEKCiwU1JynPSxECOBzYRMKUsQQogRQ2sIR8HjSk0k\nOl9MYDzucC6Pv+IlHvKwwQF/cQ3kZsDXFqQytoUm+M4wJopG4XADPPxMhN+9aZH0KCoKPNzeoygu\nhg3bYeMumFgFrkQ/gUCChgZYs6aN3NxsbrutYFDvc08/PNUA3b2KlkyTKzMsentj9PcnCAQs7rja\nxiMvpNp9XbkQ1r4Le6sh0B7AJEjZqExGjXJw++35xwS2AJMnu9iwM8ruugL8zjDhaB+1tWFuu634\npBPnbDaDhQuPvlfDUNx9dwn79oV48SU7e/Z52LkbVlyVxFBRvF43999/6oUdIhGN1pqsLBu9vRaR\nyMjqJyzEUawA9EtZghBCjAixOPxqNVQ3wbhy+OKV4DhP/tcyMNC9+SRDMDofatqgqSsV3Jqu1M+Z\nSibhVy/C7v0Wz7/cRjTuI95lp8OtaOrzkNsOL70BuVnw2jpYscBHS0uC2toIRUVutm6NcNVVCXJy\nTv4mxiwIJSDTeepfKDb1gM8GJQUOWsZls3tjI56SbJ7/fRjCQWbN8vJP92cRTyjGlsOKhfDUy/De\n2xEmVCrKy5y0tiaw2Y6+UCwGVhJ6+5NgZjNmVICOXj+lVXb+9/8eTWHh0W/g9u19vPJKO4WFLm6+\nuQjTtNPZA29sAKcDrlgAphe8XhsTJvixLKgoh/Z2eOaZAPl5CeJx6O/XLF168jqRMWNcTJ3qYc+e\nCLNmeRg1SrK2YgSzmZAhmVshhBgRqpvgYCOMLoZ9dVDbAmNPXGY54hRkgt8Lte3gdkJJzmc7Xyic\nytqWFyfxu5KEbApt0yRDij3bYFJFqm+s2wloKCj0cccdVTzzTAfl5SZ2u4HLdfJotT0MP98LfXGY\nnw83VJ48wB3rgx190BtXXDY9g84ik+rtIQ4d6OWGOU62bAlx6aUmBeWpbgXFhfC5pUH2b+zgnbeT\nZBV4mHlJPgeaYFxJ6px1jfDECxCPw5IFdrIybEQcHmxug9tvyzkmsI1ELJ5/voWcHAcHDgR5771u\nli/P59nVqVKIeCL1i9Ity1P7e70wbx5s+BAcDo3LaVFWZqe7O0ljo3XKvweHQ3HHHblYlj4mKBdi\nxEkGICiZWyGEGBFMT2ouRFt3KsAyz7OuAqYH/uJqaOyCwoGa28/C64GKYk1tk4M507PYsl7jzIW5\ns50k+qGsCJbMhfe2Q+UUKCyFCaNz8XhcNDbGWLTIPKZl1qdt6YSQBRUmfNgOl5VA1kmyzAuyIccJ\nYQucSXiy1aCqyMYBS1PbmKDQZ+D1Hl3n+847XYwZ4yQjT/H2pjjeUpNfvgl/dQPk+OHN9akMfU4W\nrN1o8M/fzmDV61HGVNi4+bpj/xEolSo5SCQ0yWQq4OzrCdPWpsjKdhOOQl/w6GNuuB4uWgwej2LD\nBjdvvBHG4VBccomLSCRJIJAkJ8d23FKJj0hgK84bF1hXOwluhRAjVlkBfHE57KuHyaOgKHe4R3Tm\n/F6YOAiT6ZNJzUsv9XBgS5DsPBf/5+9y2bdb8fbbqQBr3rxUkLdsEfy+G95qhDWvww+XKi69NDVr\nLdUJ4OQK3BBNQFMI/A7wnuBTIh5PYrcrlFKMHwjaI4nUZLHWfDfzV2Sz2Bvnovle4vEEzz1XD8Dy\n5SWUlbnZvz9IT78ir8RDtqnZVxOlq9dBjt9GQS7sOQihCBTlwexpDmZPc5xwzC6XjdtvL+a11zqY\nNSsT3dvI/2fvvePrKO98//czc3rRUe/VliW5Yht3wAVwo5MQ+hICIZBKdlM22bv37v3tZu8re9m7\ne/e+kpDNEloISwiQpeOYZgy4F9mWcZFt9S4d6ej0c2ae3x8jbAvLtmRLsgzzfr3OS+dMeeaZ0Zkz\nn+f7fMt3bvyY3qiT9EuvoPLSyay9bPA+QkBWlvH+yiudzJ1rw2YThEIa//Iv7QSDOrNmObn11rQz\nClwTkwmP4gGP6ZZgYmJiMmGYXma8vug0NsZ55pkeIhENTYtw9Qonq1Z5mDrVEGpFRcZ2u4/AjlYo\ncRnT++8fgbtmSF5+uZMdOwJMn+7hlluyT8maEKaPKEGmZqRzB046ozA7A2yfMfRKKXnzzW4++qiX\n/Hw7X/1qHh6P8ShxWODBGdAZEaTPd+Ma0KO//W0t9fWG6TQc1rj77jJ8PguBoE6N38vrL9XjTIZ5\nMWThoYcmcfVlVlxOiERh8dzhXZ+KCg8VAyr74ZvfwudVSE1LotW/zU9+OfmsvsOpqcaJbt4cJBKR\nlJTY2Ls3wsqVKWRkmI9Kk4sYPQhh0y3BxMTExGSCEQjotLYmyMmx0NaWpLU1gRBQXDx4O58NnEno\nkKAJKHRAQ0OUrVv7KClxUF3dz+zZXqZOPZHqKkgP+3kfHR2H8DAj8yosDG0p7e5O8OGHvRQX22lo\niLJ3b5DFi0+UAbZboPAz6c36+xN4vRZ0HYLBJBaLwqJFaQBUNYSpfj2EYnFz4GCIo0dDzJmTyvJF\n536tiord7NgWQpBk5izfsLNs9PbGaW4O0NwcQ9clXq+CxzN4ENDeHubw4QAFBW7Kys4xj5uJyXii\nmpZbExMTE5MJRmMj/PFFG5rMIRYPUFGhUFnpGHLbKaXwo0tgw2G4dAasqIDWVgUhBIFAEuCUoLIQ\nPUh0UsgkSDcxQlhIHaJ1sNsVrFZBT0+CZPLUsrefpaMjSjQq2Lq1l2nTPNxxRykkghBpAnsmwaCP\nI0dVrJYwkSjE4+efeeDBv1vLa49vRNN0rvva5cPaJ5nU+e1va+npiSOETlmZg5tuysJuPyFuA4E4\nv/nNAWIxHV3XeeihaRQXm1XMTCY4ehAipuV2zBFCPAJcD8SBI8DXpJS9QoiVwM8B28C6H0kp3x1i\n/9nArwEHkAS+JaXcKoRYDrwMHBvY9CUp5d+P9fmYmJiYjCWvvSFxOVWuvtpDY6Od73xbUlU1tLgV\nAtZcbrw+JS/Pzi23ZLN7dz9Ll6ZRVjY4KMtLFgoq/XThIhUHpxdsXq+Fe+/NZ/PmPoqK7GcsUdvV\nFeVb39qO359g6lQfpaUpFOcLOPwoMuYnqdvZsu1BbNZ8yibFsVpdpKefcFBu64ftLZDthnn5nLVq\n2PE+pnu544fXDFoWDktefTVJd7dk7VoLZWWfccsIa/T0xCkudmG1RsnPh8zMwY/Ivr440ahGSYmX\nurp+urujprg1uTgwA8rGhfXAT6WUSSHEPwE/Bf4a6AKul1K2CCFmAOuAgiH2/9/A/yelfFMIcc3A\n5+UD6zZKKa8b8zMwMTExGWM0NPaxlwavir85lyxrBpctsbJgwcjbmjs3hblzU05Z3tWVxGbzMCtl\nFVFCuElDPcujoazMeYpA/pReDd4NgRXoXt9COJzE6VTZv7+X6dN9EOtiR7XklY8WEeiJEnf2YbHq\nvPduD9ddn0phoRNQiCbgtzshoUMkAVYF5uSP/Lw/ZcOGJNXVGqmpgt/9Ls7f/I19ULEGr9fCnDlp\n7Nzpx+lUmT077ZQ2cnNdlJYawjY11c6kSadeTxOTCYfiAef4uyUIIR4HrgM6pJQzBpalA38ASoE6\n4FYppV8YFVn+DbgGCAP3Sil3DuzzVeBvB5r9mZTyqbP17IKIWynln0/6uBm4ZWD5rpOW1wBOIYRd\nShn7bBPAp78qPqBlrPpqYmIyMWlogA0bICcHVqwA6+mD6S9auuminXZWXZfBu/YmSpMubl55+rKw\nn6LrUFMDfX0waxaknEaDrVsX4IMP+lFVwT33pFNefv7Vy/7QB81J0CTEpIXJk50cPRrF47Fw/fV5\nbN8b4FfPV5CT1k1dWxaaU0XQTmmpiqCbmhoX8+alEU1COA5FqdAUgJ7I+fUrGtVQFInVKgiFjMp3\nJyOE4EtfKmb58hxcLguuIdJEWK0KX/taBT09MVJSrDgcpmefyUWADELsgrglPAn8Anj6pGU/Ad6R\nUv5cCPGTgc9/DawFpgy8FgKPAgsHxPDfAfMwtN8OIcQrUkr/mQ48Ee7M+zBU/Gf5MrBzCGEL8H1g\nnRDinzGM7UtOWrdYCFGNIXh/KKWsGeqgQohvAN8AKP5sRIaJycWG1CHWAxY3WC6yZLBAMilJJsHh\nGF7kTywGTz4JFgvs22ck5b98eK6VFxWfWlCtKSGWfjnGIsoZTgjTtm3w0kvG9dmxA7773VOn9DVN\nsnFjP4WFNnp7NTZtClFePrSrw0jw65CmQncQMhfkU+mUzJsXZ9WqArbt6ufJFzrYVp2FDReqasXh\nCCBEgiuvTMFuT5JMGijeUlQAACAASURBVKoz1QmLimBzo/F+Tt659UfTdF54oZFt23ro7HTicBRx\n2212rNZTv2uKIsjMPPM1sFgUsrMvvnvM5AvMBbLcSik/EEKUfmbxjZyYaX8KeB9D3N4IPC2NfIWb\nhRCpQoi8gW3XSyl7AIQQ64E1wH+e6dhjJm6FEG8DuUOs+m9SypcHtvlvGD6zv//MvtOBfwJWnab5\nbwJ/KaV8UQhxK/Bb4GpgJ1AipQwOuCv8F8Yo4BSklL8BfgMwb948szC4ycWL1KH+j+CvBqsHyr8O\njvO3wI0Xra0aTzwRIhyWXHONgyVLzl6XNpk0yrNmZEA4DKHQWXe5KEknnUoq6aaLyUzBOyxpC83N\n4PEYeVwbG43BgPMzekxVBYWFNurr4+i6ZMmSs1uET6ahIcKLL7Zhsylcfm0uW/rtuCxwZQH889Yo\nO/9QR3aXxt9+u4iv3myYjv/rV+30WhzgaSIQgAxXN5m5nTit2VgsDmbNSmX2bN/xY1xfBSvKjBRj\nljPHrZ3hWkSoru5hyhQ3FkuIG24KUDFNIMlETAj7jonJGKMHIT5hAspypJStA+/bgJyB9wVA40nb\nNQ0sO93yMzJmd7aU8uozrRdC3Ivhi3GVPCmzuBCiEPgTcI+U8shpdv8q8PDA+z8Cjw0cM3DS8d8Q\nQvxKCJEppew65xMxMZnoxHsNYesugUgz+PdA3hlvvwnFxo1RNE2Sl6fw5ptRFiywDfKFHAq3G9au\nhbfeMtwSFi4cp86OMwJBCaWUUHrWbevqYuzcGaa42Ma8eS527NDZsSPKkiUWnM6hBwx/8Rfp7NkT\nweVSmDlzZNbIP/6xlWRSEgwm+ce3Isy+1E4kCVYVYk+3UhmOI6wW/uO3DVxz9QwAsqvSaWhowpue\nwOHSUML9hBMaB/alUFjo4I47ihCfydvlOftY54w4nSpCCLq74+gyjHQ9T5AQFkpxcxuCc1TNJiYX\nC4oHHGNiuc0UQmw/acFvBgyHw0JKKYUQY2JcvFDZEtYAPwaWSSnDJy1PBV4HfiKl/OgMTbQAyzDM\n2VcChwf2zwXaBy7YAgyXhe4xOQkTk4mCxQ3WFAg3gp4AR87Z95lApKerBIMJkkmd1FQFdZha47LL\nYPHi4UfQf57p69N4/PFurFbBli0h7rlHITW1m87OGPv2weHDeUyZcmqZNLdbZfHioaP9pTQs4i7X\n0NdYVQXRqE4yKZGKwKYawV9JHQpzBLt2S1SLztTJAiklQgi+vsYHKU7CcSuLCj5g/R962fVhMZMn\np7N/v47fr5GePrqPpawsB/fcU8bu3X6Ky7somRSiqbuKvS1Jpmf0MSs/fVSPZ2Iy4ZBjZrntklLO\nG+E+7UKIPCll64DbQcfA8mag6KTtCgeWNXPCjeHT5e+f7SAXak7mF4AdWD8wSt8spXwI+A5QDvwP\nIcT/GNh2lZSyQwjxGPBrKeV24AHg34QQFiDKgO8sRmDaN4UQSSAC3H6yVdjE5HOJaocpD4B/Hzgy\nwTftQvforEgpqa2NEQ7rLFhgx2KBQEBy2WW2Uyx3p28Ddh6AY80wpxLKv8Cu8+GwITLz8600N8f5\nzW/a2LQpQmpqCvF4gq1bo0OK29ORTMJ//hEOHIbCfLj3rlPdGm6/PZ9XX+3AZhPctMLFO12Q5YTV\nJbDyxwX8x5PQ3hrErmr80z8d4rbbCvF3RbkxtZc57rewaEfJWbyATzZdghCCsjI7DsfYjFQqK31U\nVvpIIGkI7eDpzVlYFAvVx1JIuQxKL8KyziYmI0FOHCPAKxiz7z8f+PvyScu/I4R4DiOgrG9AAK8D\n/pcQ4tP0JaswMmydkQuVLaH8NMt/BvzsNOu+ftL7D4FLh9jmFxjC2cTki4U9A3KXDbkqkYRdh4y/\ncyrAdf4xQ+fN9u1hXnihFyFg0iQ7DzyQMWxR+ymHG+CP6yHFDXsOw1/dDWlf0MxMOTkW5s51sWNH\niIaGKHPnuunujqBp/Xg8diKR4QtbgOYW2H8QykrgWB3UHoWZ0wdvk5tr54EHThha5gwMLnRCxJ27\n+MGPrPy//+3FYrETj+s88shBvF6Y4tyMp+QwM+dXsaJkP//wP5ZR32JjzRofLtfYPoGtlEHsVmIB\nieaHXq2fvrmpwMi+eyYmFxWKB2wXJBXYf2JYXTOFEE0YWQ9+DjwvhLgfqAduHdj8DYw0YLUYqcC+\nBiCl7BFC/AOwbWC7v/80uOxMmN70Jiafc/68BT7YbUwtH26Ee6+90D2CTz6J0NISwumEWEwjkUjH\nZhuZwAhHjYIFGanQ0Gp8/qKKW0UR3HJLGqtXp/DIIy34fCqTJnlQVRtTpqQzZ87Iqn553EamhfaB\nCUPvCOoUhHmZJMeQ6Ni9s/G3T0bTJMFgnPLyFHxWH8G+MMQDKKqVlasywDK2Iy5dl7S0hLHZFPJT\nCujYfICG1jhOSxfhhSVQeMJ0G47DUT+kOqDQN7idtrYIjY0hCgpc5OePbMBgYnLBkEGkNv4BZVLK\nO06z6qohtpXAt0/TzuPA4yM5tiluTUw+5zR2QKYPnHbj/UQgEAhy9GgYIQQVFRo228gtdhXFUJIH\nje0wtwryMsegoxcZXq/K7bdn8Prrvdx4o4OqqnQKCixUVY2snYwM+NpdsG8/TCqD0pLh75ukDZUc\nJFFuuq2HTX+ejdUqWLMmizffbMEvK5i53AruKOQvHXNhC/Daa41s3tyJEHDddYWUueMsWuqiuyNC\nb3cUPRKh99VXiba282zprXS7chDAfXOhfED39vTE+PWvDxGP61gsCt/9biVZWRNgGsTE5GwID1jH\n33J7ITHFrYnJ55yls+G59dAbgmsXX+jeGHi9guXL7dhsKkY2wJHjcsJDt0AsDo4zRNTHE/D2Lmj1\nw4pZMOkc86VeLEyb5mLatPO3Kk4qM14jxclywqxDoJCXvpbbbz/hujBjRiq6LklLm39ih85mCPVB\nXhnYRz9/rK5LtmzppLjYTV9fnAMH+pg716hE5nKpzJ6dTvDjj4ns2kV/egENOw4wbW06rRErdb0n\nxG1XV4xEQlJa6qG+PkRnZ8wUtyYXBZIguj5hUoGNC6a4NTH5nDOtDH50F2g6pA4vTeqYs3JlNq2t\nDUSjSW655awpC0+LEGcWtgDbDsEHNZDmgaffgZ/cCo6RzdJfNDQ3R3jjjVY8HgvXXZeH1zu4bJuU\nkr4+HZdLGbEbyBmRCZARUFKwMxcrlYBAYbDI9vk+c+GbDsObTxjRgVmFcP2Dhj/EKKIogspKH7tr\ne1GScPnlOSxZkj2oEllgnw5C4FOTFOGnvs+oeFcxIGyllAQCMXp7Y0QiSQoKXBQXm24JJhcP+sQJ\nKBsXTHFrYvIFwDuy/PxjTn6+k7/+6wqkNMTH6ejt1YjHIStLGXHA2adEE6AKcDugPwxJ7Vx7PfF5\n4okGqqs1OjuTdHbqfO97pcfXSSl58cUwu3bF8PlUvv51D+npo5DjVe+C8G9BD4B1PjhuRBHD/MI1\nHwGrDTLyoaMBIkHwpp5/nz5D0R0ZHPAL3EJlSmYaQgyuROZesoRESwuJjg6+/qUp1FitZKdA8UBX\n9u/388c/HsPrFYDk/vsn4/F8Dus9m3w+ER6EarolmJiYmIw5QgjOpFcPHozzzDMhNA2WLrWzZs25\nWcoWVMCRVmjphusWgOdzWjlV0yTV1Qm2bUsAGo8/3sf99ydxu42f+Z4enZ0745SUWGhs1Ni7N86y\nZaNwMRK7jTyaahEktoF9OYhhCtTiKtj3EbTVQW4ZuEZ/aiGCzm5rhFnZKXSTZC9hrmKwBVl1u8n4\n6lcBo2zx9u3GrMBdd8G0adDREcVmUygsdFNfH0TTzAyTJhcRMogmP7zQvRhXTHFrYvIF4+jRGJGI\nTnm5Hbt94s5VbdoUw+0W+HwKGzfGWLXKeUYr7+nwuuAba8eggxOEQAB+9ztoaxNYLKlI2U5GhgWr\n1UpXVxy320JdHTz9tGDHDkEkomGzSTIyRul/LzJBxkFvBeEGMQLBnFcKX/4eBPsgp5hhV/AYATYE\nqai0kyCBJIPTW1yTSdi2TWKzRenq0tmyxcm0aQozZqSxeXMHDQ1BZs1KJy3tPMummZiMJ8KLooyF\n5fZ3Y9Dm6GCKWxOTCU5zs04gICkoUKhvE1hUSdWkM1s9T8f27SFeeMEPQGWlg699beKmGCgrs7J/\nf4LeXp3ycss5CduJTlcXNDZCbi7knWOg27Zt0NICeXmSTZucKIokGJRce61KXp4x9f7ii+B0Klx6\nqZdgMMadd6pMn37+jsdJEkhrJVZuBb0DrHNBjFD4pWYZrzFCRXAzGdQQxofKNE4/A2CxgJRB3nqr\nDyEEPl8EyCQry8lf/uUMQqEkaWl2hIDa2iSaBuXlKqr6+ftumnx+kARJcqair58/THFr8sVGSkju\nB90P1hmgjL6/3/lw8GCSp56KA9DqF/hDKu3NOiuvVPnvP7ZgtY7soXroUJSUFAvp6SqHDxvR3yNt\nYzwIhSTFxRZuvdWNlJIZM04IsUAU4hpkTjA/4pHS1wePPgrhsBG89O1vQ845VE52uQyLY319nFgs\nyTe+4ePYsX7uvjv7eIo1lwsaGhJ88kkrXm8Cny+XZEQjHgziysxEnEMN417aOMwmpJCU2eaSdWpd\nnVGnqyvGxo1deL1Wli7NHHYKuVQsXMbwkiBPmRInEjHukXg8hqZJVFXgcFhwOIxH5nvvxXnrrRhC\nwKJFVm66ycyaYDKx0T+HxoEzYYpbky82id0QeQ6EBRJbwP2w8X6CcOiQjsMBubkK6zZopPogL19h\n23aNI0cUqqpGNo07e7aLmpoe+vs15sxxTkhh29en8+ijEfr7dTIyFB56yIXTafTzcBf8rhqSOqwo\ng5VD1jq8OOjuhmgUysqgrg46O89N3M6fD0eOwPvvC1JT/UQikJ5mIU1vg55+SC/m1lvhZz/rRFH6\nmTLFyuO//oQr3evQomGyp09nxu23j1jgNrEfKw4UVBrZSxalI+/8SezZk+Tll5NkZAjuvNNGauqJ\n72Y0qvHii40880wj+flOsrIcaJrO6tW553XMobj8chfHjvmJxTQWL3Zz5IhAVWHSJI7PluzblyAn\nR2CzCfbtS3LTTaPeDROTUUPgwcLlY9DyE2PQ5ugwcZ7iJiYXAr0FFCcoeaA1GOmMxATJlwVUVSls\n3gx1dTqzZynUHALZCyU5YLePXJhOm+bk4YezCYd1ioomTj6seBw+OWBMCycTOoGATmmpSn29RkuL\nRnm58VP1cSO4rOBzwIY6uGqSUXntYiQvD7KyoKEBUlKgqOjs+wxFOAy1RwBi1DfaCIdjPLCygUnN\nH0ETcMkNZExazBVXSLxew4rbfLQDrTCKr7iYjn37iPj9uDIyznKkwbhIoYNjCBR8ZJ9b5wdIJCQv\nvGAI27Y2yYYNSW64wfCNFQKqq/1UV/ciJTQ1hcnOduD3J87rmKejstLJD39oJRqVbNlq4fEnjeWr\nVsKVK4z3c+daee21GCBZunTi3EcmJkOhEyLOpgvdjXHFFLcmX2yscyCxE7T6AX/BEdQZHQemTLHw\nve8p9PdLiooU3v1A4/ABnYULVMrKzk3VZWdPvBRGL/wJqvcaXiLz5ihYrVBXp+F0CrKyTpxnsQ9q\nOqAvBmVpF6+wBXA64aGHoKPDqAjmPkc3i0jEKFTR1t5Pbo6Xygo3vQ1bYFERJMLQVA2TFnPVVdn4\n/Qn6+hLcflse/e/H6auvx+HzYfOM/HtfzCU48KCjkcPkc+s8hlW2piZIb6/A4bCRSEAgAT9/AYQW\n4/bLIqiKQAhBZaWbHTv6sNkUli8fOz/d1FTj0VhTA4UFxuCrpuaEuL3sMhvFRSCCDRSUuID8MeuL\nicn5YlhuLxuDlh8bgzZHB1PcmnyxUfPB8wPQQ6BkcE5RWmNMTo5yfLp67UoLa1de2P6MBYdrobjQ\nEGo9foVvfctFa6tOYaGKz3dCwS4thXQnhBNwyejPSI87DgcUF59fG9nZsGA+7N1rR+pRVFVSUpUD\n/g8ACWWLAPD5rNx/f+nx/bomuQh3dpI1bRoW+8ij/y1YyWeEdX2H4A9/aGH//n7icRW/P5MlS1Ko\nw4In0c7sxG9p3xCiYvZ81IL5xNtD/NMjJSxakD4uQVxz5sAHG433114zeF1R4r8gsAtqBEy6DTIv\nGfP+mJicC5IgMdNya2LyBUO4QDWrDV1ILl8C775vvL/6KsjJUcnJOeFPnOAYUT5GVXKZlbeU7i6V\nTRs1srIEM2eq51zg4fOAEHDTjbB8WRoHDkSw2WDWjJXgnwyqFTJKh9wvs7ISKitPWa7rknBYx+0+\n98IZwyWWSPD+x+2kOBzk5akUFAS5+eYMnnoHRONOEloc3VvE3uptqAVXkVpaQKdr5BnDNE0nkdCP\nB4QNl9WrYGqVMUMwaBCia9BdDd4SiPdCzx5T3JpMWAQebCwZg5Z/MwZtjg6muDUxAfqTsM4PMR1W\npUHWGLvRhWPw/h5I6LB8Bvgu8sj/8+WqFTB9quFzm/mZ7GQ6YUK8gIKdGEdIxFJ57LHphELGdPFd\nd8GsWeZPWWqqwqJFJ32RcipG3EY0qvPkk53UNwaZVBHmzjtycNvOz5/2dCRJ8tsPt9EsezjUDM5P\nMvhfPzMswTctgm16Jnm9YQLJZna0+9glHcyYDP7IyI6zZ0+Y5547jBAJVq8uYOlSI+daS0uEZ59t\nJJGQ3HZbAZMmneqaoShQWjpEo4oKvirorQEJFFw1sk6ZmIwzki+WAcB8IpiYAG/0wN4Q2BT4z074\nXsHYHu+1bbD7iGGBavfDN9aM7fEuBnJP62agIUkgSEfQTzgcJxCAkhJBU5Oko8OsFjUUyaTk2LEE\nTqegsPD0ftbdEVAVSLXDkSNRjtZ3k1Kyno07VWLubnKtt3PTtRVYLKP7cPTTS2NbP5OLvfhzohx5\nx8af/hQGbCxY4Obqqy/FX2/h4w+76S2aQ6DWSmcvfGfZ4HaO9sGHLVDggWUFYDnJD3vzZnjkkXZa\nWxNUVFh45ZUGFi7Mxm5Xee21VuJxHVVVePrZFv72pxVYRmIRLr8dArWgOiClbDQuiYnJmKATIsKW\nC92NccUUtyYmQEgDpwouxXg/1vT0G9ZauxW6ApJwWMPlMm/HoVDw4uRqoryPSjHZqTOZO1dl1y4N\njwcuuWT0q1p9HnjuuX5qaowcybfd5mH27BO5WDuTUBeHpi7Y3mS4NnylHNK8KjGO0dqiE4nYKZhS\nx6EPmqitLaaqanTrFtuxM/0yhfWHYxzbZWfqVDcFBVZef72PBQvcIBTchXPoTYP+flhcAvcth8I0\nI/AwFgdNgac+AYcKNd2QYoX5Jw2Stm4Fp1Nw5EgXNTVQWZmkrq6fyspUXC4Lgf4Ie5olut3GYx/A\n1y437slhoVohbeqoXhMTk7FA4MHO4jFo+Vdj0OboYD5NTUyAtenwuw4IanD72AVhH2fNXHjmfegN\nJBGNdfxjdZRLL03jppvyP5eVuM4XBwtwsMD4IODLX5ZceaUFt/vcUqJ93nmvWvLr5+MUFFqoytbZ\nty9+XNwGNPh3PzTVhvjzE51MS1VZsDqHjS02vnOJnVvvFmzfF2DusgPoqmTDzjJKShWqzj92bBAp\neFlTPIdpP+jg4xftNNbYaW9PUlBwQl3aLPDACjjaAWluKMmCcASe+i9oaoeqKoh7IcMGtT1QUwdz\ns+DoUckvfxmlvl7S3m5HyjTy8hI4nSo7dnRRWZnK9dfn0RYQWMI6y6/MpaEbGnugICVJU1OY9HQ7\nGRlmmV2Tix+doGm5NTH5IpJnhx8XGRah8YhNKs2Bn94CW7cFeOVwlOISFzt2+FmyJIPc3NNXOxrN\n/kkkNYTpIME0XOQy8fN17tiRZN26JPn5CrfeajWF7RAEI/DOHkF5hY1DB+OICNx804n/rV+DsCZp\nfa0dp0ulqTMOH3TzzXsNX9RF05dSNT3K1j2Z/P7pZVSW5bGn1sZVPZCVPrp9dQTT+OiJOE1NcRwO\nnUWLvFx22WDf1xQXzC498fngMahvgdICOPAJzL0afr8Lwl2w+xAU6PDCUxEOHuxH0wTJJFRUONE0\nI/1aaanRvs9n5a47i/C/A706WFRwWTX+4z9qaWuLYrUqPPhgOfn5ZrCpycWNggcHi8ag5V+MQZuj\ngyluTUxOYryC7nUJmoC0VCu6LunsjGG1Krhcp59i374DXn0NMjPg7rsgLe38+lBLlLfw40TlABHu\nJRsXpz++JuHlVtgdgDkpcGMejKeRORiU/OlPSbzeJNu2xcjLc7N69fiVPW1vj9LeHqW42EVq6sQd\nCFgthsVz8qVerJkJrl0omD37hDU01wIFNsEWVSHPpZEjJbNLFFaXGOtVPGTwJfJtkJ8FuZnQ3Wf4\n5Y42hw5F2LEjSl+fBV1Pcs89dlJSzuxm4nIag7zuXsNnfWUJ7NsA2bmGVbe2Ho4cSdDerpCRoZKT\nI3nwwQLefbeNWCxGXV2cSy/VsNtVPKqGu66Hg8cS3Hytm3BdJx3NfkonZ1JfH6KhIWSKW5OLHsPn\nduuF7sa4YopbE5NxpjMGTzRAIAlrsjzcfHMBzc0R5s1LIyVlaIe/WAxefgVysqGjEz78CK6/7vz6\nEUDDgiADC20kiKKfUdweC8G2Xih2wtZemOWDyeOY5UFRIBqNsW3bEXp64iiKlxUrqrDZxt7ntq0t\nwq9+VUsyKfF6LXzvexW43Sd+PnXdEFwjTVE1FtitcO/VsLFGsHiqjWUzPrNegQfSYNH9eWxb30Wa\nV+WaazIGBWIBTCr4NMgMrr0eYo6xmNlQOHhQJy1No69PUlsLk89SD6KiFL68CupaYN50SE2BpfPg\nnc0ggMk5kJvrpKUlTkdHkvvvd7NkiY1Nm9ooLU2hujrAlCke5s9P5+23Q2z/KE5amsKL//oRyoyP\ncR8MUp+4GdWTSmHhFzyNicnnBo2LuOLNOWCKWxOTcebxj/t5ry7JpAyVX+7yUtKZTmE2pA1R/bSx\nMcauXWE6Opw0NTqwWCCRMEqono7DtbBjN5QWw8L5pxcjFTjZR5g2EkzHRdpZfg4+FT+hpPHXOs4e\nAS6XYOHCOG+/3YeiaFRX97NvXx5z5546Vx4MJrHbFazW0flBb22NkkxKSkvd1NeH6O6OHRe3LS3w\n9NNGAYovfxlmzRqVQ54XxVlw1/LTr7cJuLTEzqVfP31akDfegP5WiLng1/UwwwvLMmD1QEGRaFRD\nVcV5XePycifTp6ej63FKShykpJz9kSQELJhlvD7lqkUwo9xIJddUDwUFNmbPTqepSbJqlYoQCYSA\nzm5JW5ckFDG+vO9vFNQ36zTWBVH7LKRfX8Ic5QjehZIpyyrJzh6/mQETk7FC4MbJwgvdjXHFFLcm\nJuNIe3uMPZv9RHK8vLsthNJpY9EVNlo7FaoPwhWXnti2pyfBY4+1s2ePi7a2KFOmWGhvtXDtdXDZ\nQD5uKeWgRPt+Pzz9HDgdsKsaZGqCgxU9RNFZQxqlnHhYe1G5myyi6LjPYLH9lFIXXJ8LewNwWQYU\nX4DZ2hkzbLjdcbxeC8kk1NcHTxG3b73VycaNPXi9Fu67r5C0NCvd3QlSUy04HOdmWi0uduFyqdTX\nh8jOdgwSPe+8A5pmlNB96SWYOXP8C921S41WNPJR6atNUFsbo6rKQVnZuQdEtbUZ53Q0FZIBKHLC\nR35Y5tN49NEjvPdeF5WVHr773XKKz/HLkJIi+O53U9iwQaOoSOHSS4f+/zS0QiBkWJNdp0nakDOQ\nH9nrMgYYhw+rzF8FT1lBS9gouayA5/+jm9S0DDZ94qNyHux3OGnT6gk09OFKqjz5kotr5tpInzUJ\nNdUUtiafD4xc4dsudDfGFVPcmpiMI1JCYTBCW1uMZLeOo0dl2w4n+YVe3J95aAcCGsmkRFFsuN0J\nsrI0Skosx8uArl/fzIYN7ZSWurnzzsm4XBYiUdCSkJ4GgX74OBzChY4ThXX4eZC8QcdQEcMStp+y\nJN14XSjKy72sWJFDe3sEt9tKcbGbrVu7eOeddoqLnaxZU8CHH/ZQWOigvT3Gxx/30taWpLExhs9n\n4cEH8/H5TvzsSSmJRHSczjNX48rIsPO971XQ1RUjL88xSCSnpEAwaFjUfb7xF7bdUuMJGSKBJNKs\nEX0ijM+u8tFHQR5+OJusrKFdXXTdcPU4HatWwXPPgV0H90KoC8PMFPjggy5efLGF1FQb1dV9rF/f\nMais70i55BILl1xy+kfRgWPw1KuAgMJsuP9GnSNHglitgilTPKf832w2o7AHwKM9oOpgB3blpbJw\naSrF+UZAWk0PZC+I88H/ayEe0ggi2ddXSnT6FdR3F2PrgZ+mwaxMyM48pVsmJhcNCm5cn2ab+YJg\nilsTk3EkN9fOdWuy2PUPtSwvdpAxN0xnWOG6ZV4u+Uwl1IICG5Mn2+nsDBIMerDbraxebazr6ory\n/vttFBa6OXIkyJ49PSxalE1uDiyYBxs/1nDYNHyuBCEkcpjW2YmO1arwV381lepqP+npdkpK3Dzy\nyH6ysx3s3dtHYaEbj8dCW1uMSERHSsO1o6TEwbFjEY4dizB7theARELn979v4/DhMJMnO7n77jxs\nttOrvZQU65A+0atWGdPh4TCsWDFmp35autHpaoiQq6u0B3WSUqcqz0FdXYy+Pu0UcRuOwbMboK4d\nrpgOq+cO3e7UqfDTnxrBj/VJiOtQ5YG3dmoDlnOdYFAjI2P4wXV13fCnanDa4CtzIGMYLq1HmsBp\nNwLb6lvh98+1cPiAHynh2mtzWbr09Ln7UhRoSYICTMqAiN0QtiX5UJ4BUgaJh6yAHRSVLcc0Oiz5\n5MSh7yD8zxpYmgdfugbmmdV1TS5SdEIE2X6huzGumOLW5KJA1+Gtd2D3Hpg1Ha5ZdWar00TmiivS\n+dnPKnjllXZUNc5fP+igsvLU7axWhXvvzeHmmzWsVhWrVWAfmGW22RQURdDXF0fTJE6nIVwVBdZc\nrVOzp5P+gMaBL8cjkAAAIABJREFUJyUzv2HDV6pyOSnjeJajSxJJKzEcKGSl21mxwsjU39+fQFEE\nyaQOGNflvvsK2b69j/R0K5WVHnbsCPHmm71EIjo33HCizbq6KAcPhikrc1BbG+bYsQiVlSMPIHI6\n4dprDav8/kNQcxhmVhnW8/Gg/qM+9rzWxlapUzXfx9RCNw0NcSZNslNcPFh4BsKwfjdUH9ZxJ6O8\n9GeF2WV2ctKGNjc7HBAM6igtGsXZKnZV4YorMvnkk3727OnjxhvzWLs2Z9h9fW4nqALaAvDWfrhr\n/tn3mT4ZNu81AsimFMORbX2UlLgJBpMcPBg8o7i93gvOEGjA1RlguQd6A4ZQbm0NkbWzE7CC222k\nL/F5iXZaaMyB2D6YmWNkJXlzG0yZAb6Lf3xo8gVEAroZUGZiMvGob4SNH0NBHny4BaoqoHzS4G2i\n0SSaJnG7h1ti6MKxYEEqU6d6UFVxxvRfiiJISzv1Nk1JsXH33ZPYtKmTBQsymTHjhJLq7dUIhzQm\nTbJTXx+notXF4lLPKW1MBDRNsmNvhE6lk+nlDopdWShD/Aivo4sjRBDAWjIoxxChXq+VJctKWLeu\njdkzM7n00nRsNpVrrsk+vu+0aT4aGiSVlXbWrw8xf74Hi0Xg8agIIenoiAMCt/vclEtLS5jm5hDB\niJu3PnBhtcCWnfD9B4wp8rHmUHU/V2W5SdoFsf0Jbv1uNq/u0OiLquyuF8wvN1wl+kLwyzfgSKvk\ng9f95NjiaBL2LfKRs3xon9lQSOdXvwrS1yex2+Hb3/aQkWHjJz+pPO7v3dYWpa6ul8JCJ4WFZ/a9\nVQRoumENHm5qsdJ8ePgO6A8bbgl/tqTz4YfdCCG4+ursM+6bosKXTh7TucHrhp6eGI89Votb01E9\nNjRdNVJdeDNRNiWoLLSS8CWo+zjGdglVX7Hzr91WvpEG+RP/58XEZBAqbtzMu9DdGFdMcWtyQQmH\nk8Tj+qC8ofG45JNPdKxWqKoyLJSqCgjDrxFOtdoePdrP008bqZpuuKGIBQvOv8xYbz9sqjGmRJfM\nANsoP9S83hO3XzIpEQJUdfgOm5WVqVRWpp6yPDPTQlGRjfr6GA6HwuTJE7fK0vsbEvy5bydqaj/7\ndMkds2dSTNGgbeLoHCVCPjb6SHKEyHFx29ACG/em4i1MpT4IkdhgQanrEpdLpaTERUaGBb9fQ0pj\nXV6enb/4izz27w9RVeWmsHDkAUQdHREeffQAmiZpalXJKZ1KUYmdhmYIhcdH3M6Y4eXNNzvo70+g\nWgU/+XUHDYksNCGoaQCPA6YVQUsPtPXCpBzJ5kSctAIr5VkanW0xurstNDdHyc21k5194vvS0aHT\n16dTUmKhvl5j48YAXm+CGTNSyMlx0NMT59e/PkokouH3x7j77mIuvzzreJW9eDBI7bp1JCMRJq9e\nzV3zsnhlL+T5YM0wKtfquiQclmSkCjIHrMtr1+Yya5YPm00hJ8dBL60cZQdW7JSzCCfes7YbCCQG\nsl94uHI1fLA/hbgzBbtDJXg4zpwUK/2ih9AUC4mkjqc3giSLT2KmuDW5+NAI08/OC92NccUUtyYX\njPq6fl783TaCUSdLVkw+boV54YUE1dUaUgpWr1a56iorRQWw9mqo3gerr4SyksFtvftuK06nittt\n4Y03mkZF3P5+PbT1QCIJ4Shccx6luY+F4JU28Frgy/ngsxoVwgSCmpoQzz/fhdUquOeeHIqLz0+M\nWiyC++7LoL09SWqqitc7cedSG5o0XOUhnHEffR1h/NJPsRgsbq0ISnBQRwSBoJQTkXc9fYY7QFGe\n4UvZ1w8+Lxw+HOTZZ9vZsSNOVpaXnByVaFRy660+rCflMJs61cPUqedu1e7sjKJphkgKR4LoyRj1\nTXZmT4dU3+BtP5vZYrRYujSD7Gw7//7vtTg8Vj7e2oYlVyWtPJOYZlhsAep6YHcjRCIKceGi40AY\nb0xQebuVX/2qgWhUw2pV+M53SsjMNFR5drZCSopCfb1Gf3+cd9/tQAiN//t/67juukLmz3eRSEja\n20NUV/sJh2NommTFCsNV4fAbb9BeXY1qt7P32WdZ9PDDfPOKz1wXJD0ksaHgPckvPBzWefLJMM3N\nGpWVFu6804XFIlAUQVGR6/i+tWzFioMYYZqoYcowKjEVFLiYMsVLbW0/qxY7aYxYqT+WRHQmmVwu\nsGUFeFdvIxmBVIuPgM1LXEKRKWxNLkIUXHhMy62JyTggJc0bnmCBpwZ7pp0NG69n+fKrsFgUDh3S\nKS5WiESgtlZy1VXGtOrSJcZrKPLynNTWBggEEpSUnP8UvJTQ7oecNMNPsbP3/Nr6fZORPL8uAm93\nwuX57dSwHys23nkll7Q0B9GoZN06Pw88kHve/bfZFIqKJlYVLV03TKbKSWXNLl9s46mt+cTymykr\nV08RtgACwVoyaRrwuc3jhPifVASZaQPlWPMhL8s4zrPPtrJ9e4w9e+KkpWmUl3t5/vniQcceDYqL\nPWRk2GloCFFW6uDuu11090Fx/omsCc3NUZ55ppVEQnL77TmUl49OYQBdh/5+8HgERUUOPB6VvDw7\nJe1R2tQEsRjMKIPpxcb2B9ph9QLYsw1aslO4draLzi4FIaIcOhSnsVEhkYiyfHmQ5cuNlBhut8I3\nv+mhpUWjvj7BBx9IDhxIEgxqHDwYRtM0Nm5sZseOHnw+K6mpFnbs6D4ubhPhMBaXC6vLRSJkqOxk\nUrJnTwRNg1mzHGy297OLEApwA+nH09UdOaLR2JikrMzCgQNJmpo0SksHP7IEAhUrSeLoJFGH+Uiz\nWhW++tVJBAIJXG4LLRU6Rz4K0FSXINOj8dQjbWiBKDGrSjJi5W++Vsj8NCgdxVsqHNb5058CtLQk\nWbnSzezZp8lxZmJynuiECbDrQndjXDHFrcmFIdFPgeso2xtz8cW6qMiqOz4lv2SJyvvvawgBV189\nPKvjypX5pKRYicV0Fi48f6utEHDdYnj1Y8MdYcVpIspHipSGtamG/dhxECNGIq2bnpYckkmYPPnz\nkVuzsTGI3x9j8uQU3G4rB/b38+6fqhGKlWvumEPJgEqYMkXlx7nT6UuUkJVuw8HQ529FoYxTH/4p\nHvjOXYbFNt1nZC0wUlwJgkHjelssAr8/QSymHw+8OxM76Wc7/RRh52rSsJ4hEMPrtfLtb1fR3R2j\nucvBzQ+rdPph4SXwzz8yhPfrr3eh6+ByKbz0Uic//vH5i9t4HJ5+Bo7VQ6G3m68t+4RVCzL489YI\nV0x3cPNtGaT6wGM/UTWtKg/ePwR2J2Q5BbGYlYwMsFis7N0r6fLHkQheeinM0qVpxwcCKSmG9TYn\nJ4Xq6m66uwPk5bnweCxs3txOKJTA67UQiWhEIkl8vhPmzfI1a9jzzDPEg0Gm33YbAOvWBdiwIYyi\nSA7WOui6I0ouVgJo7CV8XNx6vcbx29s1wx3We+rApL4+SnfjJdgmHyE/z04h04d9DRVFHHeHqrL0\n8tb2Bpr2qBzVJSFbEiVLxV6hIYI6rZsslA4j+G0kbNsWYd++OFlZKk88EeDHP7ZRUDBxZ1lMLl4k\nAp1xzlF4gTHFrcmFweKmqGISVstREkmVjIXzj0/ZrlxpYeZMFasVMjOHF3Vis6lcccX5WzxPZsE0\nmDnZCHw5H39bIeDuIni51ShXuzJLsAcbMWIkSXD97W7a3vdgtQpWrPCdvcExJBqFDRsMi+CyZZD1\nmXGCrkva26O4XCo+39BmrMOHe3niiQNIaZRB/da3ZnB43bPMS9mPrkt2vtlNyTevOb59ilch5Twy\nOdhtkH1SdTdFEdx9dz7d3U2EQpCd7WDpUg8Ox9m/S34SbKSPTCx8Qphi7EznzDMBDoeFjEwL3/vH\nBAcPRPD6bGzfZ2PjDrj5avB4VBobo8Riguzs0TH91TfA0XooTe+l7p29HIvtYWl+D0v+6juoaRlD\nuj+sng6lmaAthL5G6O6CBfMhHlexejOIB+JYnRbq2nSSSYnNNriNtDQb3//+FFauzOPddwN4PCpO\np4MDBwyR2NmVoKAojWXLTtyHntxclvzwh4PaOXYsQU6Ois0maDiWoFS3sas3hr8brpRWWvLAokJp\nqYW77nJx9KjGjBlWMjJUjnRCfwwqsqG3K8bf/V0djY0x0tMz+MUvpmDLGbi+8e0Q30BLfwm7O26g\nItdGeXYc4luAGFgXgnLCN7d9ewMlDju1vQl0LYluA5sTlDqJ15mNbQzGnEIIdF2ya5fGsWMav/hF\njAcfdFBa+sWKajcZe1RcpDBKFpqLBFPcmowax1rhYCOUFxivM6KoKNPuI7+gFmwpkHIi9YEQgry8\niTHKdI5SLFapCx6efOLzHC7hMLXYsVOeOhnbTRPDheC99+CDD4wUUHV18IMfDC5K8NJLDezc2YPF\nonDffZMpHSILQ319P1arSkGBm/r6fvr7E+S7amn2F2KVIfJTjw55bF03gupGwy+1rMzFv/7rFA4f\njhEK6VRWOobVroJAIEkikUjUYVo7uruTHN3bSaxbEu0S5FZkkZthjIiuuy4Lq1UhmZSsWjU6FTDs\ndkkkImmqjwESX2E6xNuxRAMghq44oCgw9dMaHoUnljc2KnT1eOjv6Ee1SCyLPafN92uzKcyZk8Kc\nOcZgpKcnjYaGMO9+1M+sRTlkV5Thjw5tmQ4Ek2za3InNFqehwYLVqrJmjYe9211sfCuCiCq0aA7e\nXgA5OXBzOcybYWPGDGP/Pc3w7HZAQFEqzBQRDh8OU1hoo74+wrp1ndxySw4ORz97w3/m5f0VNGyx\nkG79hLc9U/nv168nzboRUCF5BNwPHu9bWpodryuO1MGi6MiETmpvF6VT5zB9Rha3feX0/4tkUqep\nKYbHox73VR4OCxY4aGhIsHNnlCuv9GC1KuzerZni1mTU0QjTy+4L3Y1xxRS3JqNChx9++4YxLfzO\nTrhmEcyZDKlnCly2eiBz9rj1cSLhwcMcJt659/aCy2Xk9uzoMKb1P9WE4XCSXbv8lJS46eyMsXNn\nz5DitqoqjY0bW6mrCzBpUgqaBj2W6XjYSk6eg7IVN5yyz86dfl5+uRWv18I99xQPKm97NjRNEg7r\neDyDq4wJIaioGJnJzYeFlaSziyDzSaGcwamtdF1SV2f4DpeViePHi4STXFIlsTjtdHfE+MaXkiya\nbYjblBQLX/nK8HPBno3eXslz/xkjFhLoioeHVtSRH6+FrALIPNuo8lQ6OwVOi6Sk0ktPl0Zvm05X\nV5LMzLM/HtLTHfyff1nAz34tKc4TdPRAS/up2zV0w4/+vY/aYwppQcGSKUkefjiHpk54//k49hoH\nrnyVBheUJSDDAVvaYN5JkzFHu8Bth2wP1Pvhqml2nE5BV1eSvr4wv/99C6+/3sttP7DyqjKNT2ry\niFlDtD0fITf9AJe5O/ny2jQQbtBbicU09u71Y7EIbr21lPT0NvZtaaSn10uKO8ZP1x7i0r9ZS3mh\nwHWaQa6Ukuee66CmJoSqCu69N5fy8uGVInY4FO68M4W+PgeNjZJ4HEpKJsag3uTzhYoLH3MudDfG\nFVPcmpwzkUiSmpo+HA4Va4oPXQo8TnjhfXh7J5TmwP95yKgHP140tkKnH8oKIO3CzvCPGgl0NHQc\n43C7rlgB9fWGsL3hhsEp1xwOlfx8J8eOhZBSUlw8tIWusNDD979/CX19MQoK3Dz2WCNtbQtxyRKm\nWNOZXjy41JOmSV5+uZXMTBt+f4L33uvktttODSwbimBQ4/HHO2lvTzB9upPbbstAVQVbtoRYvz5A\ncbGNr3wlDadz+NawqbiZytDn9vbbSd57TwPgyitVVq40BGxBgY25My0U5sRIS1P5xl22YZfh7egw\n0uHl51uHFfB29KiO3w+zLxHU16t4b7oTUvvAm26MLjHS6bU0tuFzbiUtIwNsi0EM7c+ZmQsF+SoH\nPomjJjVyUxI8+WSC++/PZMMGidUKy5cruN1D983lhMWXCDZVg8MOU2bqHNUlBULBLgTE/Ly3/j28\nvUEsvdM5JieT3Bhn7VrBy6/0428VtLbG8Ca8pOZG2fl2gKP7bDx4Vyqc5O88uxB2NhnCdkYeTCrU\n+Pnfb2bP3ib+7ZeXc+BACpFIlGMqOG/Kxt/qoL1GJSItWLMjvPXRZL60uo6GhiTdoWvYufcYhw/7\nkVKwfHkOd95ZxnWV7Wz83Xoy/3/23jtMjurK+//cCp3T9PTkqAkaZRQGgUASRmRjwORgMA44rb3e\ntdfrtTe83n1/3v29u97k3X1t765tjO0FYZMxskCAjEAIlHOa0eTYM9PTM527q+q+f/QQBEgoIgn3\n53n6menqqntvV1VXnTr3nPP15Ljg0lpoPHoMbDJpsW9fkmnTnAwPZ9m9O3HMxi3kQ2g+9SkbbW0W\nHo+gqangtS1w6jFIMc7OMz2MD5SCcXuWkslIOjtNPB5BdfXZmWTw4INdtLXFsCzJFVdVUVtaxku7\n8vKeixtgMAIvbvvgjNvufvjPX+XVWPwe+Ord+RvvuUj/GPz6FYjkJugc2oNpGHzyxmlcXXdsRt+J\nUl4O3/xmPilLe8fVIX8jbmTfvgm8Xp3p04/sli8qslNUlHd3xWIGfr+NbLaakfi7g5cVBdxujWg0\nRypl4vUee4DzwYNpBgez1Nfb2bEjjmXlWLcuyd69OZYv97BvX4otW+wsXXpqRCx27rQoLxdv/n/F\nFfnlTqfCF75QwtiYQTCoHVN8b76NFA8/PEFIPcgVM19lTmst1H8c9CMbSMFgvv+eHguHA7QSlTUe\nHYixBB8OQ+Fn90/S3bYHXXfyuXvXUtWgg+2Cd7UVScD9r0kyARvSncWZjaHUDzBSleV/nlxAuMOD\nYeRVym6//cjXoY9dChcthKjNZKWWxjCgQih8WnOg9z1PdnA3vX1zccheHJaPmvoqevstFAHXna+y\n3WfwsesMNr4wjvTojI+l8AxqMDMf/iClpNwt+eOPCBJZgWbBdx/oYXtvLdZomsFwmMRkBk0Pku4u\nJXEAlECWTC6AMTpJaizHfmcR69q/zupfRUDobN0a5uqrXViWpLMzDoBv0YVcW1UG2TRUNB7x+76B\n06lQU2OnszMFQGPj8V9w3G7B/Pln5zW+wIcDFSf+s3Cm8HRSMG7PQixL8otfpOjoyHuI7r7bwaxZ\nZ1eBxcEJyeb2HDNrPKTiWfp743zunjIWNMNfTkBPGHQVmqvfv61TxdBo/u+0qnxpqGjs3DVuH98A\nqSxs3tfJ2HCOWfU2fvJgB5d/uwrtFMso5kwYS0CRC+xa3tg8krSx263R2lr83h8egY9/vIyVKwfQ\nNMG11757el4Iwb331vLiiyP4fBorVhx7tQufTyWblaxaleLQoRhr1oxjtytMTAg2b04yf36+Nuqp\nYt48hbVr80IQ76zkYbcrVFYeX+z05s0pinw5lvmfpqfbxexpuxDOUqi+/Ijb1NcrfO5zNvr7LRoa\nBP/QFWaPnmZaiWAykOOSwZfobnNRV7mfvuHzOXionKppk+/Z1v4+6OmWjIYHGY/1gZFj42tprqyF\ncMNO0nsvRNchEjn6OScEFAdgv2FiWlCjqHTnDH72m06sLX1s25mjwtlB34iX4mlzGG50cWiOhdij\nsmatSVWVxoVzVLa+JHAoJm5nGBsC8JHLWTz00BgHDqRparJz/fV+/vPBCM/9bpicVOjdU83s+QcY\n3J9CKEnOqy1j67Zm2joNrLkC5rgoWzjGgjm1bGtTyBmCkhJJSYmLrq44Ho/gttveVji7fNoxH7/8\nA1857e0pPB6V+vpz9IJT4EONSYpxdpzpYXygFIzbs5BUCjo7TerrVYaHLQ4eNM+YcZvLWQwPp/H7\n9Tc9al1j8OMNgkh5Nc90RllkT3DDDdVksybduwZpDUjcM0OsON/JhbM+uLE21IDbmTdsayqgZEqR\ndmwsy6OPhslkLG68sfSElKg+aHQtLx4hMjpSsUhaOexCQznF5VzSOfjJazAwCUE3fGFJvnzUqWT6\ndC9/+ZfTj5osVlbm4M47j98r3dTk4IIL/HR3x2hp0ThwwMTn0/B4TJxOhaVL3SxceOoMjiuu0Ghq\nUhEC6utP/Fi0WznaMJAzFH73uk5pmUJtpR2h5HhTQu0oNDQoNDQoPPpKhqdVA0XXGMiaVDjHuM65\nnVDocrp6qkAdpa4W0Be9q42ODnj0l7C1M0F31xiZuIlNzaC6s4z06vgaMry6IYuqKPzt3x6b0V6j\nqGDl6LFMcuE0BzaO4rctZjC6hUunj+EurSLx0QAXtEK3qRCr8TDPaWFKhc17Ba7yIra+sgcf/aS2\n/5bRxk8STUbZv6uP2vogu/aU0909TFd/ls6dafw1Odx+kyDD1M/opKKmiD/8yhi/0b7Mn/yrJJuw\nUK8OUl5bREBx0uAa54nNfWSzJk3NRdzx6VnUlgriMTu9vZKamuM/pg6Hypw5JzczsO8gPLEKfD64\n80YIFr3/NgUKHA8Wv1+zAwXj9izE5YKmJo22NgMhBDNnnpmT0jAsHnigg87OOA6Hyhe+0ExpqYP2\nEVAFrGj1sK/MweeWlzGt0sbzz4fZti1KMGgj2dNF6ydaUI7kAjwNlAThj+6B8UkoKwZ96nngmWfG\nGBjIS9GuXDnMN75Rd/SGzgJuvgieeh2KFjcyNAg5I8unb2g4pcatZUmeX59g0xaL1oVuBhIqXZF8\nPOOp5lSLJ7ydefNcbNmSQ0qVoaEwHo/kwgt9/OEfVlJVdWqrUAghaGh467tYlsQwLGy2Y/+NDkuT\nlSRxINhSKShbHGAofSfljjUQmAXlR1AqeQ82jwosy42nMUY8p1CVdWOzwec+tYmODo1gxXVU1zeC\nePfvcP16CLng8kZBz4EcjkCWzGgO1W5ROS9NdncJH7trHSP9VWRz0+EYbo61isrnNAfjSBKJDL82\nJbrTjeGdSbdZRNNsPyNzihghb8PrhqC0VGU0InnqSYN9eyCgpIg4qtja00/6mQ20Xr6fTHoGDz2q\n0TnqJxhK86kbPAx1a/QMjFNZN0JJTRyXlWXFRywqqkuZ51Ro+Jqd0W6DhGEx1mZxxfkGP/tJlLTH\nRaDGwf7eNI9t0om2C4qFhaJIbrtNYf78Dzbu1bLgV0+CzwvhEXjhZbj13TmXBQqcMCouiph3pofx\ngVIwbs9ChBDcfbeD7u58zG15+ZkxbsfGMnR2xqmrc9PTk+DgwUlKSx00lcBL7dAdETRX6tRMzTTn\nchaKArouME0LeQweqFONx51/vR0h3nKGnQb109NCyAefuQLAAcdRmP54WLdukueejNA+IAh3JVlw\ndTmhUyOe9YHS0qJzww0eOjpy3HVXgIYGHZ/v9M90jIykeeCBdqLRLFdfXcnSpcdWZzlO/mQsESpW\n1sBZrJLOzGeTMp8rpx/fGFbM1nnhZRcj221MK4MbFzjB+CQefSfzWpvB1nzEbaurYdcuUFQXrUtd\nZN1xxrt1Gqf5UePF7Noap9RVSahijNrmIaD+mMZUoahUAGZLgBeLS3j55RgXXhzkni++htvl5flX\nPOyPOphZ72VLWmPtPmgqkhg5i2G7Qt+hKpqmDaIYUfb2zeJy/y6mzXSy8YBO68U2DnTXsP3AAA0z\nBEO1tfRmS+nv8tLi7mFoXSWLr7mKRU6YP2by5KRBMC3JPpfgX19ysKPPyWDPKHpXirI5HmpLFV59\n2uK2KwSJmGD/fsn8Dzg0UYj8TE0mA7ncydXULlDgvTBIMcruMz2MD5SCcXuWouuCpqYze3j8fht+\nv/5mskVlZX56t74YvrIcoimoC+YLrgMsWxZicDBNOJzh1lursdvPjmmQa68N8fjjYdJpixtuOHn1\nsg8LPT0ZKss0Kms09ran+dyFknLfOWL9vw0hBBdd5OSiiz7YeMdXXw0Tj+eorHSyenU/ra0hHI6j\n/2b37cvw8CMxDjpNtgadpA84GYlo7J8DrU3wxGoYH4TFi2H2MTzTXNYkKPU5GM1aLCoVBIQAvSX/\neh+WLwe/H5JJhc/Pr2WvR2Ei08aqVSGe3wradAeu8ARf/OQBaqvfv713MjxsMDFh56qr3bT3rmew\n38PAQJrNa/djU5p48MkM195ajq8Imnzw2JCguEbQEy8l6Zrk8W3XUz2tmZ8+6GT+/E2s2bKMfkcF\nolnh7k+E2bQjgi9ZjGe4j727QuykGEevi4ceg37NYNMGSfq1NGPZFN5sjHB1CVqwCC1pQ7FbZAMB\n+sYVWmZIBvtBUSSzZ59er200arBpUwKvV6G11YOmCYSAT94Ov30BGurg8uWndQgFfg/RcBIseG4L\nFMjjcKh8/vPNdHTEKS62UVf3VlxZmS//ejsej8ZnPlP/wQ7yGPAXabR+uoQYEp84ebdINGqwdu3k\nlKKYD7f77DDij5clSzz84hcpzFiWuz/up7743DNsTzVRhuhhJ3bcNLAI/QhywAB+v04qZTI6msHj\n0dG0oxtGUkoeeSROwKtS2Q9710muuELn112CS4pgYhh++Sqc3wwPPQRf/zoE30fzQRFwXhlwAkmG\nqgoL3xQt8jKNRjYaWzCzXrxkUDx29KyTcudSbFQeU5vDwxl27pykvNxOWVn+YSOTsUAqqGqWsREV\nr1cQ8Opk9uVIZSSmJaitF1x0pcLLOyVFrU52bZtDyZgkMSHYfXAOl18zk/m323m2z2DOLIPnvSoT\nbp26qi5S5TBxYIzIYBDT8vH3/2QwrqdQNBUyFumMJOR3MT4WJZ3U0DxeyuZptIQEdy6F7AKFJ1dD\nTSU0Tz99vwEpJT/72Qijowa5nCSVst5UJKyuhM/dc9q6LvB7jkGKsYLntkCBtwgEbCxceGpUlc4U\nm2SW1aTRgb0yy314UE4iPuHhh8fo78++KR5w223HVz3gbKG52cU3vlFFNisJhQpzoRYm7byOho0o\ngwxwgDrOO+L6F19chmVJIpEsS5eWvq9xK4TA6RTE4xbSArddIR4V6CpMynwJPWHkQ3ukVMhkTvU3\nPDoKNqqNfwskAAAgAElEQVRcpSyc3svwUAVWxMuNraU0VBybNHIyafLjH/eSyVhkMhaf/nQ1N90U\nYOPGBNdcMZeWGS/jshfxy72VjCSzfPnTRUR0QUs1XDxTsGS2yqwLoK0PKvZZhH0Gg4MJErFe/uN+\niM7x4PWXsf9ljc16HXODAxRnh0kqRcy7O8KrT08nPuAkoFlYUZPJoQyWkCiGSTRrcl6LhT2VprbC\nxZxKQdoFD/VA51rB4jroHoSN22H5uyumnRJME0ZHDaqqbIyNGQwP5w77fHAwwZ13/o729gSzZtXx\niU80c8st/nP24bnA2YNEYJ7iKjtnOwXjtsDZiczk9eGRYGsFceIVDoYw8SIoQmEQEwM4mTSj8XGT\noiKNTEYyPm6cREunl3Q6H2vsPMpsvc9XuAS8GzH1OnrMuK4rrFhxbB7NN7j7bh/PPZdg5kyFe+91\ns28fLF4ORhkc2mrw7IjBE0/AHXdolJef/LGxLMmzz2Z5+ukxqqok990XYscOg/b2HIsXO2htPfx3\nVcllfGr6AJc4bDSVFxMqOvYxJBIGyaRJba2Dnp4Mo6NZli4N0trqBkqJRKp55pF2sOI0z9C45WOe\nd5Wcu6rIYmx1lLFDGVTNjcczgVKm8/B+ldz6GOoVZRSFTEoiDtIswlY9Srkrzu7OGdhqA4y7NMJj\nNtIOBTEZw2lzoqU17GoOzRbAJyV1xQLdBo55UOGBV+IQPcEHCcOwUBRx9IRJmYbUI2hmFyuWXcoL\n62pxOARLlx5eJ/pP/3QTr78eIZ0upb9/gjVruvjGnyv87L/quPbaQvmEAieOhpMQc870MD5QCne2\nAmcn6achNyUkb/WA864TbqpV2GiTBgOYXIQN20lmld1wQ4CHH46g64JrrgmcVFuni/3781PblgW3\n3ALnHdkBeeqREro2wngv1LVCcf0H2PmJo6DSxAV0s4MA5VQy45T3UV6ucf3tfpJmijKnZN7bwuD+\n7jGDq68WZLMAJkKc/OX50CGL++8fZWBgnE2bBN3dcfz+IsrLdR5/PE5trUZpab6ftkPwi18Ltm7x\n01gdo7I8zJe+VHrMD0DFxTbmzvWya1cMv19n1qzDy2Pt3TvBxESWadM8tLVNMjqaOUxm2TThe/+T\nYdV6DZdXYe8LcXSvSrhTIetKo7lceA/Z8I8pqFKh2R7kyuKbeXXPJPsfSZIbGCcRCuKyJvFoDtI1\nHmztY1RV2Fkw38tAH8yZ7SZYrBCqhgEH5FRoWQxiDOZMl9hIsmWLZO5cFzbb0T1dW7ZEeeKJ8JRk\ndBXl5UeooZfbDsZuUKtZsWQV51/4dWyOIuz2w9uPx7MYho18VYo0kGN0QOd7/xJm2TLvST2Ido5B\nxoDGUL7+eIHfLwxShNl7pofxgVIwbgucnZh9oJTmSxiZ/SfVVLXQ+Apeskj8QiGXs9i9O46UMGeO\n531vYu9k5kwXf/VXToQ4vSWuTobnnwevN68ytnr1B2zcDu2DbY+BwwcDu+Gyr4Pz2Ka2zzQByglw\nbFUPToS2KKwNr6HUvYmSVBFLiu9CIR932dSksmWLMSUHe2osEMuCkZEMg4MS01TYsyfNRReB3S5I\nK4K9MVD8ELLDo89ALmsQT1iMJ7x4Jifo788ds1GlKILbb6/gqqtKcLvVd/2uSkocmCb09aVwuVQ8\nnsPb7RmBtjDULt7LwHgKZV8ZCauErEOHGoFZFkCPCr78CUF5cf6UUqM2nvlXG4mJNKmERJEG2YAL\nzZPDFbNRUhHimht0NAvmzdYwTBulpXDT1bA3BXsj8MVLYXE5PPNMlMcejSEEtLVluO22YmIxcLsP\nV+szDAuAJ58MU1b2hmT0GHfeeSQvvpZ/4JNpEApej/6eKil/8zcLWbN+PcZolPysQQLw0D5ondR1\nZmMXPLYDEPkyf3eff8JNFThHKXhuCxQ4W7BdBplf5W8K9huPe3PLkoyMmHg8Cm63glMInFM1Yp95\nZpQNGyYASUeHn1tuebdq1vuhqm/dbHp7U6xZM0owqHPVVSU4nWfeNVJaClu35u+hLcef6H5cDA0Z\ndHUZVFdrVFdrkI7lO/YU5723ufQ5Y9yebrZHolT5NoFVSTg9SMLchVddCsDHP67R3CxQVcGsWScf\nH2dJ6AsosCyI8XiKMqdBQ4OPBQsc7O/MMXmRhzUZjd91wh9MA7cLhoZVYglBeDhLQ6UgFNIYjIDb\nAb4jKwK/iRCCoqK34rf74/DgATAtuKPFx733TmNoKM2cOQFcrsNvP047lE+PkSyL0LPWR3HjJF17\nbOAvwl7mwlaqcUOD4LpLBH+9Bjb8EMLdJpGDGVIpDenzY41EMLJejH0hKjUbETPDD/89QbBSUOJU\nufpKi6/+oQO3W9CcS1KkpKn1eAGdjo4MSU1nIC5oW59mVwISXTCtHD57L3g8sHNnjEcfDaPrTMVb\n50gmLfz+w7/LZAYGk1DuAr9tPmZuGMvoRXddDcrhvwXLyoupOJuLCS6bQfLJA2BpgB3IYi93kkxK\nPCeoE7F70MJKZSnyKOwbsmFZR1YgLPDhJFfw3BYocJZgmwvaNECC4n3f1d+OZUlWrpxkz54MDofg\nvvsCVFS8dcPt7ExRXm5DUXhTE/5EMU3JAw/0o6rQ1pbA6VS56qozX27s+ushFMrfOJcsOX39RKMm\n//mfMTKZ/A3zy1/2UlExG7o3Q6QXpi0G75nfH2cLNW47PVkHglFCzhy64n/zM5tNsGDBqbskvzYE\nDx0UTF/qJlNaR2t/kgXT7dx1l4+uJPy4G0K5DB1Rk/4yJ9ddJfjmd1XKa9yEghluusXP7w7obOvI\nT2V/5gqoKz2+MfymE3IW6Ao82g5/sjDArCOoFpYXwccX62wwNTwX5eivGSUZ0SmfX0QKk1khg+/c\nbaMtCi+sgfEhGElJLBEAfwTsTpQmP/6lAuPndqqrYM+BDNJQmIhAWubYt8/GqlUGF12U4Qc/2EM0\nmiUUcvDtby+gZb6Xh9ZFEHYIt/jp3Aa1DaAMQFs7LJgPjzw5jD+okUlYlJQ4CIU01q41eOwxC7c7\nwSWXuJnMwH/shGQOnBrcWKHxxKprSWfg45fDwrd9/2QG7n8eBiKQVjLE20yETUFmTBAStdHD8gXu\nYxGte09Gxsd58pdb2BmrIhT0ctvyIhTlyMWsh7JZ9o/maAzq1DhOrQBKgTOJwCoklBUocJagnJir\nYnLSYs+eDLW1GgMDBrt2ZQ4zbpcuDfDEEyMAXHdd6KSGaFmSbNYiFNJJpSzSafOk2jsS8QSER6Gs\nJO9hez8cDlix4rQM5TAiEYtsFurrNbq6DMbGLCoqPLD8S2DmQD/FWr7nOBeUOimavJMs26h1l2IX\np0egIxKDnz8Le8ah3KMze47CLct0LpiR/x2U2sAYmOCRRzpQLItdl4X4yMV1TJ8O6YkYmzaO88TT\nLpLlpUwrVwhPwLZDx2/cOjVIG5BVoHQqsTEcztHVlaGy0kZ19eEG1JKaAFW00FseZtuqEg5MjuFq\nb6dhlo//75ONpAfHkdu2Uh+voC/WgpUDshboPtBMhGbhbJEsvFXSv0GSzuiY9iTJrIY/pFE5SyMa\nlfT2xtm9e4JMRrJtW5SPfCTMrPmVXHCjnbRb8kJKJ5bNx6rWSMCf5Fl66KgdIdFhpybn5dKZxUxM\n6OzcmaSoyOQ734nyyCN2IqpG0oBaH3RPwtOv5CegSoPw5AvQVG0yMWFSVqbRNqDQNwb1JfDSrnEc\nTg+5shpSI0kCzR5uvinEJ1d4KCs7/lu1ZUn++m/X89qTE+QabaRzGYZ6JZA3bjvGLB4ayrCr06K+\n085NV0j+cc0E40PgCcK/ft5Pnbdg4H4Y0HBQyhGeKj+kFIzbAu+JlJKengxSQl2dHXGuSHsBLpdC\nUZFKd3cO04TKysNP8/PP99PQkL/TFhef3MVb1xVuvrmcp54apqzMzvLlp74s2MQk/OABSCTB54E/\n+NS7VdjeTjptsn17HF0XnHee531LVJ0MlZUq5eUq3d0GwaBCXd3UvlYUUAqG7TsRAlr8FcBp0DgG\nJicNVq4cYndblpSvhOZGLx1huL5YZdkc9U2FPpcGM4cjZEoUasqcHNgxyg1XVxOPmKxdM0ZllY2R\nwRhOp4suxYclofYEHPDXN8DqLjAlXFUHExMmP/rRKOm0hRDw5S+XUFn51m9QIKijjjpHHbuGO2hd\nYjEazdEcUHnuBY09Dx9AzWnc5HmOiMyyMTIT1Gw+PBWJOqzwnTl29tdEGItLXGEbpuLEkjq2Yp31\nEyCSGma/m7GxDB6PRnGxnd7eBB/5CHxskcbjbXnFsMBCyI7ClQuzbHfvZGfvGI03CyZethGSkqs+\nUsx//3cUTRMEg4KeHot43KK8Ir9/uyfzxn1dCLYP5GXBs6kc//C9UTrTGvaAjVuvdzNsWWQmBOUh\nk/rABG3dxfiKffyvLxXzxS8cXzjP5KTBrl1JfD4F09J5dZ0LrUglVhQkN55kTTdsPphgqNfGt39p\nMpgQ+JsE6auS/OxxjdFxaGxU6eo22d1tUDfHhmXJsza3oMCxYZBmiP1nehgfKAXjtsB7sm7dJKtX\njwNw6aV+rrzy7CpFY1mS3/52jN27Eyxa5OWyy4reNMBttnwowr59GYJBlZaWdxtZJ2vUvp3zzvNx\n3nmnLqZUysNlgvuH8p7bumro7oOBIZjeeOTtf/WrYfbuTSAlhMNZrrnm5LzTR8PhUPjCF7yMjpoE\ngwoOx+/X1NfZxvr1UXp60pSHdHa8PsyFFS5mVKrc2pQ/pwwTVu3PJ24VOT3o6REGOrPU1HhY/VuT\n8X4L1QSbZeF0SG66SKAVgdcJ06uOfzwBO9zxtpjvziGDTMaivt5OV1eG0VGDigobnZ156dnGxreS\nt4bjkl0xG0K18dKARny3xeLUEKanjDFqWdzczv7RaibtMUhrqPhZMcvHNF+KJ55KketzIC2TeJeO\n6lHREhZGSKXlCuga93DZ1Q1sfT2ClCqhkB8h4LIWqC4Bx24IumCiGBLZMf7nL8YZjZvYymDGhSY3\nXRfA5VK59VYvr76aoafHYtkyG4qi4VQsVmgJ+mKweK6T2IjBcK/g5Z02lFSK5w7E8E1zYkupfH9H\nkpYL04yNq9xR7WbzLxLU1cdQhYfNm4AvHHnfSgkHwxBLw8xyGB9J83d/18vAiE7fsJ+BzgliE9Uk\ncynwS0SdmzGvjcefGmfdajdGsIfp5YcY2uZnw8A0asNFDA5D73ZJ40KFGSGdbdvGeeKJQfx+nXvu\nqaWkpPDAei6i4TxjnlshxNeA+8hnSe4CPk3+6X4lUAxsAe6RUmaFEHbg58AiYAy4XUrZdSL9nhHj\nVgjxPeA6IAscAj4tpYwKIa4A/g/5MqRZ4E+llC++x/bnAT8CPEAX8Akp5eTUZ98GPguYwFellM+e\n/m/04WPbtjilpTqqKtiyJX7WGbft7SleeWWCigo7L7wwTnOzi7q6t8oKBQIqS5Ycw/z9acbCwkKi\n8f5JZqYJTzwJ27bB3Llw8035G315Cdhs0NULTgeUvo+t2tWVprraTipl0d19cjHFx4LNJt7lHS9w\nZrDZBKYpUbFYMlPhzksF0yrAMxUS8Fw//P1Y/r17xI87EkEZGWS4u57hRAVDAwpN04PExhP5GrUL\n3YdVCjhZKit1Kit1urszBAIq9fV2Xngxx7/9e4RwGJoafXz9aw5mzxMM1FfSs60Ph5DgqyCY0Dio\nzyeyZ4g501V+HVnOZE8GDAdoOTR3EqfTyQsPjLJvwySDGzUcFQKHW1BaApoOXevC/M3rCcobHHzj\nD2rp7fDjKNN55qCH85ZLqjyCpgAsrYTdo7CiFlb/xxDdWzOEBw1MSyOzxcbmsMHyr0JlpY2VKyt4\n6KEMu3bBD36QIRIZZuvWCKoqKSvz0NDgJBwBu8ePro4S7u1nfMTEVuVGaWykJjLMosV+FMNHbVWQ\ngQGNvj6Drq40GzbYWLLk3TW+4yl46QCsbc/LnxfrOcZfHeC1LSmGTRMj6yU2bqCqec8rKQkhP8NO\nhVXjHgZi0HreDvZv8lNc1UNyY4ytfT5E2o3QndTZiij3BnjgBwOUlNiJRHL87ncj3Hpr9ak7GQp8\nYORIM8SBD7xfIUQV8FVglpQyJYT4FXAH8FHgX6SUK4UQPyJvs/1w6u+4lLJJCHEH8PfA7SfS9zFd\ntoQQ06c6LpNSzhFCzAOul1J+90Q6BdYA35ZSGkKIvwe+DfwZMApcJ6UcEELMAZ4F3stf8GPgG1LK\nl4QQnwH+FPgrIcQs8jtuNlAJPC+EmC6lPD2BkB9i5s51sWbNBADLlp19me5C5D0XliXffH+2ESHO\neg6Qw2Qh06jn6PO63d2weQvU1cK27TD/vHylg2ARfPQyeOAxEDpMxCHwVh4S6bTFU0/F6e/PccUV\nbi69tIjVq8cQQnDNNeemelqBE+PiiwNMTpqMjGS59dYgDQ2He9LXGaBLSGZh59A4ZQM57Ck/bXuj\nUDtEYqSSwYjGnXdWcP31p/6BxW5X+NznQoyOGhQVadjtgh/+sJ3t2yZIJFQOHarAYS/h5s/qjGQV\n1JnVDMY1itKCuJpkMOrCKK6jI1ZLdCeQi+QrC1gJXN4iKmcFeflJC0v3YzYqmBJC01VSoxIRSZKJ\nJcilc8hOg+3bD7JoeZT15RfTPany93tzeFdPMDmS4a67fHx8Sf6698vhNOEOi3jMwmG3CGpu+ruz\nb34nKWH3bnB5Yc3aHHt2RLFrFrpuEo2mcToFA4MZwpE4lXU55tWpJI047SlBsHeE9VmVsmlhbqko\n52tfM/inf5oklzOZuczDV34suWSHxR/fqFA7VdRlbBJ+tBq2DkAGuKjBYOf+NKU5yM11MnowiVqR\nRhmxkR5LgmJBLSjZCdRQOe2/SZHujCMuS6DkHKRGFFITDizLgNwo5IpZv91k3XofbrfGxIRBOm3i\ndhceYM9VdByUnYa63ceIBjiFEDnABQwCK4A3itc/APw1eRvzhqn/AR4B/kMIIaQ8/pTKYz1b/5u8\nAfmfAFLKnUKIB4ETMm6llM+97e1rwC1Ty7e9bfke8jvELqV8p37MdGDd1P9ryBvBf0V+x6ycWr9T\nCNEOLAY2nMg4f59ZsSJAXZ0DKaGx8cTVwU4XjY1OVqwoYs+eBFdfXUxNzemZLrOwUE4wy3Qf+fq8\nXpxsp5s6QgiObIXbbHkjfXIy/97+tq/0ymaor85XP3jm+Sx/cEMX6G5wV7FpU5qtW1OUlmo8/HCM\nb32rmNmzPaiqeFeJogIfbhwOlRtvPHLW16wAtMVhTwRqAhIjmqQ76gLNJNU3hlrpIZtJs3WfnXS6\nAofj1J8/NpvyZpxtJmOiqSnATSZjoSppDh2C5DikIwYlqmAiaSIyE4zsGiXTacPuM0jW+SGZgpw9\nXwtb5piMOtizI0Ons5SRuSmsoEZq3EkwpnL+EsmeH6aIRtNYHhWtLsaOapVwRRFNjqco832GHasm\n6X9ikImhNKtWDfLUUy3Mnu1D+nQMVaA5dbI5STab5tZb3/K5TKRj9IdyrLo/Q7Kvk3R8HF3T0VQb\nNTUahw6lCYU0zq8T1NU7Mfp7OLS7m87ShZgTaRJZJ3N2jSItk2QyySc+4eDXzxg80K6TmZT0PZlm\n6KDGj7+r43IJusJ5z+2iWnhki8mjHUmqlDRiMsfYSBJnNINlH6LlhjL8HQrdvUkG0hZqdSm+AxnC\nu2NYhs6WR5uobDnEwV2ziPuDUKVBbBz2G6SHTBKWxb331vHii2H8fp0VKwpVT85VcqQZPAOeWyll\nvxDiH4EeIAU8Rz4MISqlfEPes4+3nJhVQO/UtoYQYoJ86MLo8fZ9rFcul5Ry4zuSik6V7uhngIff\nY/nNwNb3MGwhb/jeADwB3ArUTC2vIm8sv8Hbd9phCCE+D3weoLa29oQG/mFGCEFT01F0W88wiiK4\n8sogV14ZPC3tHzgAP3l8nKRnmGvviHNpaA4Ojs/Id2FjgBwGFh7sRzVsAaqr4aYbYdcuuGQ51Ne/\n9ZnPA90DeU/1Es+D+QEioPkTSDkNIcSUN1siJQSD+pG6KfB7zM0BCOnQHoTdkSL21lVTyQDR2hIm\nulWsaQraQZPRnn4ee8zgrrumnbaxpNNgs6nceWeI0dFBtm7VKCkJYJoq5X64Z7rkr1cncK2Ik4mD\nvRXqn87R/bpJtdlFu9NLLpcDMwvEMCP97H1dkp3uwXQ5UbpBmaFjD+uwDyIeHavCi6nlMJ02AtVj\n5Cgi5S+lfdBkz8YUo3slmE7Gx+P86Ee9/Pu/zyZwXhn+dWM47QJpt/GzB8opDbl5/AlJb+8or0bb\naYtVEIuO4PBmMQ0XGkkWLgiybJnAspzE4yZOJ1x3bQktdaV88Y9V3EgMQ8E9OsLzT7v4P9/ciMfj\norpasG/QSSZYhtppJ6oqHFIM1q4VXHutTqkfFAGxODSINMX2JOUuhSHTgSMuMBrduDwpKmLD/OLX\nc9myxY3TqTJ3QRHf/JcoP9EkzqDFaH+QaF+adEMReC1IWajXlCHlENaBHPOanZSXO7jrrsL98VxH\nwukqBRYSQmx+2/v/klL+1xtvhBBF5G21aUAU+DVw9ekYyDs5VuN2VAjRyJTYuhDiFvKu5SMihHge\n3lPq5y+klE9OrfMX5I3k/3nHtrPJx1pceYTmPwP8mxDir4CnyMfnHhdTB+C/AFpbW0+wimCBDyNS\nwoO/Mpj0hDFGPbzyfI6mO/popum42plDDToqGQxaOJJ60eG0Lsq/3snN18CaV0AjzWJfG3inQWoE\nxvdz/vkz6e/P0d+f49ZbfXg8haSuAu+NW4GPeuHVPSk2bZikMtSI1MtYvb4XX7lg4tUdlAftlPgV\nurtzHDiQobHRhqadurgfy4InfgNbtkFlBdx7VxVNTSF++lOFQMBGLAYlJXBeK/zfniipBpPkXsh4\nLYzKLJdX7+Sy0l08vbuBZ9MXkkhJEC5UaZDIxdCjEofmIeNV8IxM4ugq5pk+sAwbxcE04xOSxLiD\n0bgflzToWFVPzwtd5HYlsXI6QhhYlp2ODsGmtjQbd6ShQsNRHePeO/biLVvLj/Y28ZOfXMzQtgxZ\nm4/yeVlUv0K8L4NDkXicORYsyHHrrfXU1vrZunWSoiKdBQt8hFOCnvnLCe1+ndz4MEP7Bfd36Vg5\ngaYl2bxZECzxoyfSGEojdicsaNZIJvP7r6YEvvRRCE9AdzH84/+fZZsUjIRKyOiCRMwgaEaYOzeF\n16uzYsVbnvx//CM/fRtjbN6SoWGRE4fuZN2wRc5yYLtFR2uwoNRL7pkkPs+ZF6MpcGrQcVDBaVHz\nGZVSth7l88uBTinlCIAQ4jHgYiAghNCmvLfVwBsypP3knZV9Iq8/7iefWHbcHKtx+2XyhuAMIUQ/\n0AncfbQNpJSXH+1zIcSngI8Bl709nkIIUQ08DnxSSnnoCG3vZ8rwnYoHvnbqozd2zBu8facVKABA\nTFpsllkcCBYJG7Z3BOwKATYdsimNbM5EsRvYOP7qCjoaczg1Xo+AD279KCAdcLAZogfyAy2agdOp\ncOed/vdto0ABkvsh+hwrX21luKQW3aWS3mfH7xL4dYlpAkaaiooyBgfd3H//BPPm2bnrrpM7v5JJ\ni9dfj6Mogtp6N5u3KtTWQHcP7D8oaF3o4J57YMsWmD4dmpthY78Nu02lv9eBr3GSWluG2/RiWr3t\nUD8X0apyiYjzP2ucHGwzEZ4cDfcIhnaamGsHERkVdwKsWh+V9TqDw15yYyM4HQrSUhlaNx1PXQDv\na134NYU+oaDaBKqwcDkdXHJJGT97JIxQ49TOT2KTORrn7uXX0cU8+2o9fX1ZciEdK6vQ22FiW9iM\nzWWj1JZkcZ3OjTfWMH9+fir/8svfygIVAubOtrOubQbdnRHS4UHImYCJYRgYBpgGuAZNqhemKFV9\njPYrINQ31cWqQ/mXjLqZv0BD9Uoe3WvDTIKm6mTSJXzms++WB3e5VJ56vA7TlAgBP/6xRvTnPeyx\ngogyN+YrSVSPQuhCP52DGuXHL95Y4CwkR4Z+2s5E1z3AhUIIF/mwhMuAzcBa8uGoK4F7gSen1n9q\n6v2Gqc9fPJF4WzhG41ZK2QFcLoRwA4qUMnYinb2BEOJq4JvAJVLK5NuWB4BngG9JKdcfZftSKWVY\nCKEAf0m+cgLkd8yDQoh/Jp9Q1gxsPJmxFvjwkMvlZ/N/U5zELDMxkMSkxZXi3eEXn/6kxiOrykl5\nR7j6Cj/V7x3d8sEjBDTdBbGuN2Nu16+fYN26SaZNc3DjjcXY7QXPbYH3wMrAyEOgelGaI4jf+TC1\nIFVLbZRli9i5c4ILzg/w4/87j5deyjE4aOD3K+zZk8lXYFBP3Hv7+ONRdu/OV+5oaTHQtCLGInkv\n7huysgsWQE1jXixi6yF4adDGR5uL6RvfiRgc4c+rd1Jy2e30ivP5tw12EooLx9z5/O/rNcL7h+gO\nKBgrQrQ/lOT5n6S4sAZyxSZjrnECHg9ZxU7KtHHZQpWOAYPhiMLi6TZmXO7kwcfGyRqj2BweqiqD\nfOGzZXzpPjtf+rPttO12kokUIVw2/rnoLlRdY/8rpWQmE1gS8DrRinyIWI5MJE5/doxXJ3U+T8N7\n7osyF1waSLM/N0Yqm6J3MoNEBVRAAxXC4xk0m4MiTaMHN7cuhk2bYfYs3lR4m5jI8dxz/axfHydU\n7kbotaQ0BaEr6IqDqsojH683juV99zVTVlfMd74/zMBBjcR0L3YTlslybPpZmKVb4ITIe26nf+D9\nSilfF0I8AmwlP0u/jbyj9BlgpRDiu1PLfjK1yU+AX0zlS0XIFwg4IY5q3Aohvn6E5W8M/J9PsN//\nIC+cvWaqrdeklF8EvgI0Af9LCPG/pta9csqQ/THwIynlZuBOIcSXpz5/DLh/ajx7pkpN7CW/I79c\nqJRQ4A0efwK2boXNKywWTKhUTZeMYL3nupWV8NX73Lyh5nNWodogkL9QjY3lWLVqnLIyG9u2xWls\ndO909wUAACAASURBVHD++ccnV1zg9wWZfwmV2xd18OuGGkzFzs2NbhZ8LMjAQJrSUjtFRTbmzk2x\nf3+WaNRkwQLHSRm2AAMDWcrKdCxLMjGR41OfyIcl1NVBS3N+nZwBP10DsRRkDfCVw0A6gDOqcHG5\ngyBe9r28nVjDbZBJU19mMJzWyTptLFpUQi0WG1RB9Q0OVvTrOMYtOnSDq24xmPRMsCQuGN8F7b05\nbr7Uxe03BfD7Ydu2AP/4bx34fTplTSbTW7J84xsBtqw5SCbmIDnqRngtFI+DrS/X0Fw5QKwri5AC\noUhcsyWexhSjj3Zj9fdiWlkm0yab2gZY8ZHAe+6PWX6TJZWCiqyT4d02MhlAUfPJcSEnwlJQPQrD\n2zvQfA4mL/ZiE/lygfEkrNsK614cZdNLPXjdFuG+MRZe7GRnfwhjwgK/5LXXJR+5xPGmt/ft7NgP\n+w7B7GbBgvOLETf4ibYnscYs5LMq3lY3571tFltKyebNGXp6cixc6GDatEJM/7lEjjT9tJ+RvqWU\n3wG+847FHeST/d+5bpp8HtVJ836e2zfuki3A+eQ9o5CvUXvCHlEp5XsGL06VFnvPCgxSyvve9v/3\nge8fYb2/Bf72RMdW4MPLvv1QUwOZsJ1DgTQhBMvEuV2UXFEEQggMI59IdipjIwucGJEodPVaJKIZ\nfD7BnDn24zYOs1kIhyEYBNepKtesOCB0G4z/liVakPoZDaC4qBAq2KCl5S2DZcECJ6WlGum0pL5+\nankuAx0bIJeCxovAeeyhClde6eORR6IA3HFHEQ3ToGEqV+0Nr3A6CxNJqAnBwRF4ekeKTGKSq8pH\nucy1iVUv1rO+8zwsj0GqzmCDN47DZrGlY5xfvWIQMywumh/kG/dMY90SJ4+sTtGVzTDcb+CSo4yu\nyxCx2UkoCt6P1GO4FHp7E/zoZ52kc4J4AiYOZPHO6WGAavrHPTQ6uigOeRlMBxAjBkq1Ts9kIwHb\nILZaEPYstsowsS026IkhTBPTtGNNThDdu4n777cjBFx3XTXFxW9da1pavMyc6UWION/6ViP795vs\nOJTmYEaHogBWOEdm0iIzPokeG2P3ejv33Wljxgz49RrY3QEHOiX9wyaqFCSTJqmuPko8DtwznMwI\n5jhwQNI9bOORx5IM9PZT02xy3WfrmVnh4je/BY8Ldh6Ee+6EQIWC8oqGCGbBm2A8bKFp+eNrIXl9\nd4LHHk3i96js2JHhT/6kCL+/EJN7riARWMdQa/3DxFGNWynl3wAIIdYBC98IRxBC/DV5t3KBAucM\nSy6E370EzgE7X5+l0yoEjlNUIHd83EAIQSDwwV5Aioo0brmlmJdfnmTZMh9z556FnubfI3oH4Zv/\nGza/ZqIguOziOB+/3uTKK4/9uGQy8L3vwcAApFJw/vnw0Y8eXj3jRJASDiXnYOhzaApBxfucqlVV\n7/DO7VsDh14BVYdINyz/4jH3fd55Lpqb89VGXK68GzGRMPjFLwbo7U2xfHmQq64qYUkLbDgArw/G\naHv8IFYsw099pTT82TzC4/Mpa6xGqIK9sTjzq1OU+xSefWaUCbuP4T0qe7aOM6OsmL2dAWqnKbzc\npyIPZokrNobjOaJencSBSQ7ujfPQzgRbnuzmqWeHSSe86B4Th81GsMpFZ3aUhRc3sW2Xxbz+YSI5\nBaO0DCFNFi21U1PipKd9kpp5KULTBvnVtkpsRQ5Sgy6QGbJqMQO7DzAZHyAnNGKxHPPnV6CqgtZW\nDw6Hyqc+VX+YtO2Dv2vjU991YXSOwHgur9iiqmgiQcCb5vLLbeh6vs5tkRcWLQ4xPjxOz/5hWlpc\nzGjxUF6eZmzcQgdKyj2sfNJg7UsdJKIJtu4xebkrztJPzMY/pnJxpYPJmCQyYLCoTLKrOUciKXGa\nGUaiCf71+xarBjKsGY6hRGKUEeYrKxZghFWSSYm/EOZ/zmDDTtVxJkSf6xxrQlkZh1ckyE4tK1Dg\nnOGKy/Mxa5oGZWWnLi5148YkK1dOcPCgwcUXe/ja1/zHJEObTJqsXDlBJGJx440+GhtPTBJ4/nwP\n8+d7TmjbAqeWzTuhrxNM02JsQmPfASfzOnLH1cZvfgOrVuXjUaNR8HghPAp//HXYHIFkDpZVQdFx\nlp9+qR1W7wUEnF8LN88/vu2JhcEZALsHJoeOc+O3jNo32LkzRnd3itpaB+vWRVi0yM/HFtsIqRP8\n9pVe0pM5tCJBLAL/9bCXSmOC4VcnmTu7AbPax/ZdglwaSiurOfhClFQEyhbZWbcuxsILfLy8SyG9\ne5zMxABZp2SszWBiPImjwkbsp0PoFXGGhnJUt0i6duRQdBeViy1qFwqq9QDVVYI/+VY1T/zWzeDD\nEps9i5FV+eOFdq77oynDVIbZ8NI2Nnl8DIx7wQyBAlq9necOWXhHxrD0LK/sGmbJ7hzhgQQXXBDg\nz/+8BUURhyV8GR4/rkwfEyNZsCSkM5ASWFoQw6XTMwkjWbj6InhwNaDY+Ld/mcna1V7C4SyKIrjr\nLj9C6OzukfzsRckTz46TG02AZUDaILLP4FDXOMV9Fp3b3GQmsjz3YBTsTnwBjWBxjKQtx66ozusv\nZsje5IE5bqyeMga3Oll7cD93XL6IsrLfLy/guU6WDL28Z37+h5ZjNW5/DmwUQjw+9f7j5FUlCpwj\ndHXl2L49S12dxoIF5/ZU/IkiBFSdhrywtWtjvP66QV+fwa5dUbJZle985/1V3f7hH8L89rdx7HbB\n3r0Zvv/9CrzeQjLYuUxzPRgWTMY1MC1GwgqVVUePKzAxGKadDCnKaaSry4fTaTA4CPG4Qnm5QioF\nz/XAtnHQFeiOwx+ed3xj2zcEIQ84ddg9eALG7YwV8NrPITYM864/zo0PJ5WShMMQi1lEozlUVWC3\nK8RiOR59vgt1SRpzF8gJC58ry9AwFF0pcI2kiTb1UumZgz/q4PXfCWzBcopm9ZHQ46SGnCgeG9NK\nBe6FWXoPjLA3KRnaniCXcqJJk4DixD8k8VXbeWl/hJywMWPJ/2PvvaPtuqt7389vtd3b6f3oSDrq\nXbItd1sy2BiDCyEQQkJxgIT7EkLKg+TljiT35Y6bd28ulyTwMsLlGQwYiIEE04xs44arbFmWbPVy\nej+7l7X2ar/3xzpYMpJl2Vax7PMZY499ztpr7z1X2WvN3/x955weqzaq3PCuHi5bl6FTBGHJcFRS\n2GrgPeVRNV02tkdIz/1GA8e0lYuv/Chr753gifumIaqDB1ZdxTaamSlVUWNRok6de+4t41di7NtX\n4N3vzrJ+/cv7aBfMWTqXTVDZHcPzBDg+IqTTsy7Eki0RvrsTfM+npVpkZYPNpZem6ewMsbi7k+Fh\ni4YGnZYWg1pN8k9/VyNfcHHK49CegkoRbA9RkozeX8GrlvHtDJaVY2RSoGgWiBCJBSHE+jiFmQhs\njAal8xdo0Ckh183zD83QepnPgqxg63xPhwsGnRBd85HbE5FS/lchxL3AlXOLPvZr3cTmeRNTKHh8\n7WsVNE3w5JN14nGF/v75hIAzRWenwfh4lVAIEgmDvXtfPVLnupKBAZtMRiMchtlZl3pdkpjPBbug\nWbUU/vr/hC/8k0p3O8QiIfoXn3rAMslhRtiNik6BCfqXbKX6vQpCKGQaIF9IcOstGoeBhAFxDWZq\ngczglVQ1xToMlKAhDD1z59SGbrhnd5BWdsWi17FxjQvg+s+D74Hx+hu8OI7kq1+1GR8PUyqlWbzY\n5f3vbyCR0CgWHca7JA0b62xMV5kdiZLMx5nYk6JSLNOsCjpW6nTrDt/7OwVFWmT0EOZADx/cVOXo\noM/wZIT/+Y81JqoWiQy4gxKnZCAII/0q5ozDgmaXajXG1mu6mJk4QmPC58t/3EQ4s+BltuaRZGPw\nu5/2GXngOTZGRrgk1Qzy3SAEpumzZ4/KpvVdZJrKlGaqOH4E1BBuXCes+aAKFCVN9klQGaVS0bnn\nnhOd22qkhO90I8JlMC2IKKQ3ZLjuUy3oUWiNw/O/LPHAwxVW9Sg8/HSW//63bUSjKn19EQayFqOm\njV7WwPHJRnTojqE0RlBHqvhaDKNUobJrgv22AMUDauBX8FwPCFOtL8EpxQEBtoAWBTwBR1zQYXYs\nw2P/OEBz6zK2vuPtGSS5ELGxGWbgfJtxTjkt51YI0UMwhvuP45dJKYfPlmHznDmqVYnjSDo6VGo1\nn3L55BUC5nl9vP/9KZ5/3mfbNotIROfmm39tvtizYOYR8ExouhJCjWia4IYbEnz963lmZiQf+UiK\nxsb5qO1bgRuug2gInnlGZdmyoG7rqahTQSNEmDhVCvQvqbF+fZb29iimWeB3fqeHFSuS9JThi8/A\nfQOwRIfDvdB/kt4glgv/+iIULEDAJ1ZCXwouWQBd6SCy3H3yJP5XR3t90pnjKRQkU1OSvj4VTcuw\nfr3G4sXBrSiV0tm8Os49aon08ijJ9T491Rgr3tfH8OARnLSg75IUW2ZstrkFqhWDfbtrLFrTgBKN\n09gCLz6T5cDBw2SnXTzXQCGOrnpoapzmZsHKFR4rV2rs3VsgLEqsWerR2+0Trt4N6b962YghiSAj\nBKHobt6//l5WJBdhFJ4AaxNE2vjCF/L88J4qZStM74JmjkoV041hqzFkKILS2UiieBS7FsPQxlB0\nDc/32fHMM5TG4iTnppJyZRjYt5CWVdNURBp7n8RMp1h7SxMHJzywyixrjfDUgypmPsW9qQhayMX6\nN8l/fpfL5784zlMTVfykzoqPN9C9PsTTj6gY7RreyDBu3UUqKp4ZwvMkYIFfA4rArwoKzaDOajiT\nzfCiCfvysDkKFydgpwZTDszCtKySKNQJCh7Nc6HgnZ0OZW9aTleW8FPmupMBEYJWageAlWfDqHnO\nLO3tKmvXGuze7dDRobFkyXzU9kwSCin8wz808qlPuaiqpK/v135WU/dD9glQDKgNQf9nAPjABzJc\ndVUcTRO0ts4fk7cSV10ZPE6HNvopMEWVAt2sItmZoK9vmmKxSDqt09UVREm7E9BThcYUhFX40dPw\np7ee+HlFO4jcLkjBcBnGqoFzC9D5ep3aM0g6LWhrEwwN+SgK9PW9/Kb7e6u70WojTHseayMlrtVW\nkRIRrJUrmMQmhcZ4rkxvf46JSiPZWpH1n7DZkGrnKalzz0yRUl7BGw+DsPAjy3B9lfY2m2s2Kxw6\nZPL88wZLluh41SnWrZhh61VFJBqOD8ZxctKQEHxUCzMZStOmKCTtAigaqBHqdZ9vfLPErJ+gXB1H\njk5DLYyLC9lhUKFabWNxZ5W+RpVtUQ/X94knCqQ3Z3nmu9/k4j/6HJYv8F1o8JvoUlUGBDS1z1Dq\nqjMyMkZ7r4emhugcnqWzZTnP1n3KuktPPcfOUZ2b/7bOi3sLeN1x9CN1Yk9V8eKSkFfHyuXwZn0U\nPwS5GkKLghcFdIJuqDqBc6sBSaySBbuL4MyCo8LD0/BcNyhRqJigpLDLFousCvDq0qt53hwYhOh5\nhbrLb1VOV5aw+vj/hRAbgE+fFYvmOeMoiuA3fzPGTTdJIhFxQteaec4M/f2v8HNy8qDFQUuCnX1p\nPllRBJ2dbzwSNs+bEynhYBYqdVjWDLGTHOqaD5ZMsVa5ASl8NHSIw3/6T4uYnq7T3BwiHj92Ximu\nw9CQxDNNupoEjhNH11/uHDaGoTcJQyWQ1SLmz37GvsYwi6+/Hv2M1RV7/ei64PbbDYaHfTIZQUvL\ny+2PiBAfjW2ixBQRUiQJxJ1hFBYQzIoUW+IMqwbTYgKry6DUafBoqkBuKMViUeWZShHCgGxA0X1S\n8RBLN2p0dXm8+KLOwECNgWGVL3/jIi7reQRFwlfkbQxPCTZG4JY0/OoymRQKyfQq6L4VqkPQeBEY\nKR74qUvRS5EvFZH5sWCGxpcEjZhCwQlwaIgX+lexr0FBW9GBVsyit6Xo3ZBnYm+E/3HYx7Qk5oOT\n7PrFDCPjFr5iMT5bxXwhjr+pjbEpjd7wNN99XOPgWBHL86A1zaAVpyddw8VEGAImLNy4yuSwoEF1\niaZ9irsN1FgBuyShIYVXi0PGhL5EoFl5eALcNFAHHCACag0WpAPntuRCNQthA1SIxeqk9DIjQ/Pl\n4y8kbGyGGDzfZpxTTjdy+zKklM8JIS4508bMc/YQQhCLzTu154WWrTD4dajPQOctryyUnOctxbMj\n43x/r4GipOlKaXz64pcf+jEH7siDKeHSqMp7EsdChrGYxoIFGr98Gl7cD91t4NctDjySZ/fBCmap\nRmSTwU9+kuHWW9te9r2aAh9dDhMVn31f+gph4TB+tIIWCtF/443navNPSSQiWLr0lTPuIySIcAoB\nekhn/a3LyFFgQOgYioOruBzaNo2nauiWhlevI3WBHjdYfpHOB98nePq+QPOr6yqzZfiv95boue1i\nMhOtjBQiXL4BtnuSjrzDwrhCS8vcLVIo0HIZcBkAu3ZJvvj/Qh0DWSgDxtw0fxlQACuY67QNGvbO\n4jSGcA4r4GnMDEa46/9azI1/2YopH0UfGOGR+1sZe6JEpWwTdCqLAnUYLeDoEQ4bnUji+KU6uKPw\nRAm/3cCoZsksTJG9NI03ZaH3JHB2+hweqFNVPELxFJUpAe9JQEiFw4A0QDUhFYfEAsibQBqoAA2Q\n1MGOQrUKiTZwhyEq6I5M8LFLvk5Ds8n1l2zlDTSPmuccY2DQQ9/5NuOccrqa2+M7lSnABmD8rFg0\nzzznCM+TPPWUx/S05JJLVDo6zrwmqebAfUOdlOufZ2ufT0fq9OQHnidxXTnfSvdNhusG+vVI5FWO\ni/0Mg1MHSYomMrEUByubydlwXB1/njFBCujR4CkTtsbgV9WyxsZ8vv4Nl6eeg1Wrdb79LUEiLKnW\n45hmlpnRGntCNiryBOcWgqn17pjPUbuC3tCAW6/jWtYZ3BPnl644rG5V2ZlP0xWvEknbvEtLYakT\n3D+Wh4JDMhYhEjVZstTir/4ozOWbIO6FeeSRAtPZKs3tL9KyZyeNqka9bQND4+8jd1QQXVGn/myZ\nqAsf+UiKJUuCgyalZGzMZGrK4/Y/N9n9nEDak2DPEjiGytwjDtjgO7T31FndtxcjXKKQUtmxYwmy\nLBjcC//yiSzdH+xg4cosxdFZKmWPQCYA4CH0OLJuA3E8VQFdDyKoFQ2mLZixqC5t4W//uJUf7s7x\nVGeE7HMRzAMRauUjiIqFmlFwHQdSYThchs4ItKdhUAVFgqqA4YGvgRsHokGbZl2AApGESf9VQ/i4\n9E8dJbJM58rLF7GkcTe47wXt/M8EzPPq1LEZYOh8m3FOOd3I7fFDaJdAg/uDM2/OPPOcO3bs8Ljn\nHpd4HPbs8fjzPw8RCp3ZqOpDA7B9DGK6yjdeUPnc5UH0btY2+e7Ts0hb4YOXNNMcPzZnPTvr8aW/\nP8TsRIUbb2vjxvd1nVGbAB58sMwTT9RYujTELbek0Of7yL8q09Mud9yRo1z22LIlztatp4gsuvvZ\n2F5h9+xS7jfDKE0+X84p3N4InQZM43AwVOSAp1BxUrSrKsefenfdZZPPCfKJIi8unkGNRuibbeXH\n9+lIW6XmQtWCUsl/WSOA41E0jRW/8Rvs/+EPiTU3s+Caa878TjlPaAp8eBnc5qpEtCRCJDCxabx4\nmuxXS9h1j1jaoFxSSYY9tv/SYv2KEFu2hPjDP53GrFSJizGmp0IcvTfFje/fSWhqCy8cDaHcnaVl\nNTQujvHCC3WWLAkhpeTLXz7Mo4/O8OyOCsPDGaQbB2YIpvOrBLfTFEHI1iASltRqaZ49sIGFi44g\nlUF6e6bYP9EKeEjHYfw/SlR2X0yoaT8wTRC1lSBMNKOInlapWUUwFTBjoFsgIiBd0HTCegNf+co0\n+WIB19FoYhY1UyWrCmqpTiK5ceycCb/UQI3BlISHC7CyBQpFkHUIKRCNgGlDqQJ5BZptCOtsvOWX\npJY7qNkDhGaqrEmZrG+eRETaQJlPKLtQMAjROx+5PSl7pZTfO36BEOL9wPdeYf155jmv1GqS55/3\nCIVg7Vr1pG1pi0VJOAzNzYLRUUm9DqEzfL2uuUEULRGCrBnc9gTwz/dO8fyTKkJ1GRuc5e9vP5b2\nft8PjnL4iedpSrt85x9HuezKFOmWU9cI832JbUM4/OpO6uSkwwMPVOjo0Hj2WZOlS0OsWfP6Szu9\nXXjyySqW5dPVpfPggxUuuyz2yhFcbTULk3fzyfUF/kfpfSxPKUz58LwZOLf3+FlCEnpjPk2+4HdE\nBt+FuuNx993TbNtWoX95kqabJrF8lciKCtXJEH1H22lvzXB0v6C7XaAlNR590eXy5Tr6cZMCnicZ\nHpYYDatY90er35LdpISA2EvbLKhgMX7U4aqbE+zZWWX6Bcm6S9u44fo4g4M+R496/Ptj+5idUYAk\nhWKS/sVjGA4Upxo5/FANozYClmC7GSEW03nPe4Lf3YEDNb7znVHiqs3EoI3i19GJY+ESJGZJAilB\nDPABG9OJEEk107NwlMlsB6XpJJVCBNJxcIpQG8WdqWCGNbzmPggZUDcBAdLGcz00FzTVwRV1cLPg\nDIO0AAPkQgYPVRganEbRw4TCOlqoDvUMiaZB/Fwar1wCbNgVgqgJjgJuBBIWbDHg6gg8MAMjOfBq\ngBm8PlFEuSlN/EYDMxvHwGRRsoFUx+WILhvSK0GZb+RwoWBTn4/cvgJ/wYmO7MmWzTPPOUdKyQsv\nFJiZqbNmTZrm5jDf/a7DoUM+nieZnZVcf/2JcoCNGzV27/YZHZVcdZVKMnnmo5fXLoDREuQt+I3l\nx5JUpiYg0yBRwz4T4/Kl9afrsD2sMrC4F6NcxajNIusVOIX+sFCQ3HGHTTYrufJKlRtuOLX04VdR\nPtsOvldVX77dNRvu3Q+5Gly/FHoyr3mz35I0NqqYps/UlEsyqZ462m2sA7WFyQM+B77Xwd44rLgV\nOhYFUsbH9krMgkK6XRBqVPjtHeAfdVk3U6ReNLnyyhCPPl5gwUc9jNV1pPSJ5ULcvBK2v9hMplFj\nuljmQCzMn9xV5drlBv/tt6MYejDQ+Yu/8HjgAUmhCNddp/KRjyhcftm521fngzQxujojHHm2wsKV\nYW6+tBPPamZw0ENRBDMzFe77qYXEADzGp5bw+HZYsy5CSu1Hze+jWIkTijSzcJHkYx9LsXZtkMA2\nPFwnFI5Qnc4jhIqmCEK+RV1JIP0cgRzBnHtuAHTww+TLzXgzcdySwHXAj6WhNABWObgYeAq+ZlM9\nDLhJQIBqEoopZPpq1Ish7GwMoYGsFwkcZwmUwM3juTbUaxA38E2B9EOomsS2JH2dKk0LdR5+QgNP\nQs0ADKAAF3VAzQOnDpel4NujYJXmPr8GpPCHi+x6tIeNFx8gHA/x6TWXsqildT5n4AJEIpDzpcCO\nIYR4F3Aj0CmE+KfjXkoSyBPmmeeU7NsH0zOwYjk0v4aONuMV+NZ+cHz4wBJYfJISRlJKnnyywMMP\nz3D0aJ729jDbt2f5kz9ZxuCgT1eXoFoVDA/LE98MNDQI/viPDRzn9CKer4emKHx284kF9z+8tYF/\n/FYBShqfuvlYWO2uUYitbiM+W6QyWuJTWyDV0fLS66bpEQopL5uG3rHDJZeTdHcLfvlLj82bNdLp\nV96elhaN225L8fTTNbZsibBs2cvD1Q8fhR2jkAzDN3bAX2wJpHlvdzZvjgGQy3ls3hx7aTYg58HD\nVQgLuOY43awrO/jWt21WhupkKyEW71VYtwp2vQjJpzMYlxbJjWocnIwjJjwGnzA5Og7RvMb6DbBq\nuU5/qI39/iS9kQhqR4yrOzxWLtGZNBv5s78pM35EA91lW1XlxnWwdR2MjMDjjwdtpqUPU5M+9z9w\ncue2XHbRdUE4fOFH4Qw0Pn3pejbEZvErKhvXpLEslaEhj/Z2lcHBGpm4QaJBpTCtooZascJJPvxH\nC3nuvoPE0xkcv0Y8Vefqa7tZk34Ia9c4jw228Vf/kGFkEHwrydrYYVypkFMkhe4UytEGfLM8VyzT\nI5ApREH6KKE8rhpHD2ep5vzgJPFMECpIDxA0NI5TmAnjGSDtCEiBIy2qRYN6IYpnhkFoBHVlpwgi\nxRBIItTgIJcncLVGVDWEYw9hmx7D3giTUxqEYoH4vz8Ki+NQC0N+EvrSgA3TDlSdoFkDgiD6LOBw\nnYn9rfxs4lIYDfGhj6ZZfOu8Y3shEsJgAb3n24xzyqtFbseBZ4H3AjuOW14GPnu2jHorUrfBrAcJ\nqm+Xge++fXDnN0HX4PEn4LOfgchpzn7/dBBcCRENfnAYPrfpxHUOHKhyzz1TzM5aHDhQZ/nyJLlc\nnWrV5brrNLZtc1FVuPnmVz7NVVWgnoP7+q8f8yv6k2z4fBzfE8Tjx16sutCcinL5u1bTLiy2LI0i\nFAUpJT/+cY6nn67Q0qLzsY+1kEz+qvC9wHFgZiaQWYR/rYfEydi0KcqmTSdPBrEd0NSgTWturhPW\nPKBpgiuuiJ+w/NtFmHHBkVCXcOtc+c/9+0127czhSwiHdRZd04wQgmQC4vkwzQ+GaQG8zTCSs3F8\niEbDTOzzyD/o0NaWwGgymLnYp/1ywfpEhFJF484BKI3blPJ1yrU4TtYkJF2eek5h67oYjY2QTAZO\nrlUPzr2e7hO35/HHC/zsZ7MYhuAjH+lgwYILX5oSUjSuXncswS6Z5KVSY+l0mndeXqQ4bTEW1Qhn\nPK55ZzMf2JrgF/d5lJUqNeGhKwbm5Is8fc9PKFgOX3t0C/l8BCHDJBIOihHGrVfpXGgyMQCmLeac\nVZfAw9UAQSxRoac/x9qbZ8jvEWy7ay00WuDHoVyGugIY5PJR3LiJyNtITwXVx/cilKeawIlCqE4o\nPkx9KkXgOMeD79GVIEOxKqEsQNbwqIDroWsG7W0hpqbj4IeDHbEmGozEWhUYrARlCUU9sL3Xh2EZ\nVARDATyo6fDzCfyIhFQzTz+d4daT1FWe581PHZsjjJxvM84pp3RupZS7gF1CiLuklPOR2tfJDSGl\n8QAAIABJREFUbAG++hMo12DjUrj1qreHgzs9EzhJ3d0wNAyVyqmdW18GEduwBjENBuqwfxYqVfhC\nDtZ2wTXLjkURLctHCFi+PMGRI1WGhmpcdVUTmYzBVVcJVq9W0TRIJN6cOzt6Er3mb3TA98Yhqmu8\npzuOmFslm3V56qkKPT0GIyN1du+uccUVgRe1YYOKbcPkZFD14Y1Goa9eBBNlyJnw/jXBMZznlcm7\n0KBC1Yf8ceU/BwbqbNqkkMvp5Mo28Xaf6YJKby9c/l6YHIPrVkEhDf/kaEQH6szuzNMUVWnubmJ4\nRGFxi0R/opFruxQuW2Wwsy6QQHdK0JCIQa5ItSVJT6NGbrjCo8/F2P6oYHG/Sl+fgyctSOgcKms8\nuB22XBzYJqXkpz+dIZXScF3Jww/n+ehHL3zn9lTE4xp/8tlFfOaPJBMTFq4r6emJ8JUfjnHPtjKV\nozXwBGZ+kP/v+zEWf7CRenSWgaEYM9MxapUQibhNQUnR2BgmURmnXjDBq8xFYbW5h000bNKVyaGO\na7zw3Qwlp43WvjpTrg6ZVohGwfQhP0l9tk40DI6ewK/boKrgaRAugmaBbeGVAeHORYcVIAx6BCoq\npLQ5La3Ggp4w6XgSVc2y50WJZcmgAYPqBoqDqICQB54C6Qg0JCFbh5gdVD6oOwTSBQFIKJngxQkt\nUUgk5i8EFyoGBn3zkdtjCCHullL+JrBTCHFC/EZKueasWfYWYteRILO5pxWePQDXboDMqfOD3hKs\nXAFPPAmDQ7BqJTQ2nnr9Hx+FpyYDKdpNCyRP7/UYHBX4jsK2nGCsAJkYbJj7jS5bFqO/P8bRozX+\n8A8Xcs01GRoaQoi5kUMm8+Z0ak/FsgT8eS8Uy9B43K8zElEIhQQzMw6uC6nUMcdYUQSXXfa6Slaf\nlEwU/uAtrs88k9yShO+XwBDwzuMCu6tWRdi+vUZDs02pJcXPdys8uBcWXQX72sBr88mEXW5KqNyx\nRaWif5nbH1vDc7NL2ft8BDUW5mtfmyDeojByVTv/sya4JBy4HqW4wZZ3N5D7xQylUhHfURkpN/C/\nvgZ+KbjG3H9/loZmi0OH4JrGZh7YHmdNPzRloFTy2L+/xtSUTSql8Yd/+PbpNqWq4qWub+OTdf7m\nL3NURnTwVBBRcFSGR2P82f/eSCZapCjD6GqNWMTC9apUqwqZDptnh3rxkxpqPII/5SPtuXRR3cYV\nCsMzbSRqBZRaE7O5NpSYD01aMCUVzkDIhagDlRi1fDxYLoog7KAcl+NDpA5OCNcOg1EBRwPfAFRo\nVGECaAaSGmvaGrntfT38we+r/M3f7GD3XjVQMng2VHV43oIOYCYPvgfpEEgNYvFA4WDNBuXGnDro\nCkoUhBrFS/ajjtRYs+bCu57OE1DHmY/c/hqfmXu+6Wwb8lamKRVM9Y7NQiIa9J1/O9DUFEgRKhVo\naADlFLpNz4ftU0FnpUId7n6ozvhOC8szkCmDeJOGAEzn2HvCYZXbb+/G8+QJSVEXKqUy/O/vQL4I\nXW3w8Q+AYUAspvLxj7fyzDMVOjsNVq6MnW9T55ljdRiWh+aqnB53Gvb1hfjMZ1rYN+jxsz0Gfa2C\nwWnYPl1nYZ/goYlpHhm3uLuqsvK5JKvHSiQSPlUDqr5LJFanYhtMJ2z2bcthXNpGNgG3NsGHlkHD\n2hjKrVEeeqjI33+pRHXapL3TYKoQJZf3qVVtVm8Mc3jCZWzIondlHG3uin/4cI0FC8L09obJ5RyW\nL3/7nU8+Fn/5f++hMBECKwrUQOqABk6CiXwrE7k0QosjHQFyThKQDjNRLJJc4SPGXXRMnO4Y5rCL\njBigKdiWQyxtU7fj1KaTqCEL3zbQJ6dRGjw8D1w8yE2D1wvCQAn5+F4HUAIjC8Y0FCWIFtAz4Crg\nVwEbiEARaBIQ0wgX4LbbmlGER0uLTj5PMAryXXAqweenbNQDBTzp4DfpQW3bqg5FBUp+4AR7frBz\nnCh+MRVUcHAiuM0aD/2yxE03HQsezHNh4c8nlB1DSjkx9+enpZSfO/41IcT/A3zuxHfN8+usWRQ8\nzxRg7eLgenEhIKXk/vvzPP98mdWr41x/fcNrbt17uhpQVYHFKThQCDSetRGLi7oFTh5G6x5tcY2l\nbbDuJNrBC82x3b27yj335Glo0PjQh5rIZI79DAdGYDYPfV0wNAbjU7Bgbpu7u0N0d79NRkYXGCep\nNAdAU5PGpoTGs2MwNANKaIAberfxgkgxOb2WRY7Oyoe/zZrDOSKKw+FxlRIRZEhSmK1Qr0QIEybc\n4IIIqi/ZPrS8pCAQvLDHJlvVqecLWNkZrn5XP4sWRkikovzsl1VKtsBNxfjg9ZCemzHKZDQMQ0HX\nBQ0NOo2Np9dc5K3EnkMzbNvWiGNnQLEg3RZEMktaIDXwQoCKdLQ5x1aHi7sQ68E6rBJqs2mUOVrC\nLkWvQsFoYdZWCIk6dTNOzcwhCxHwBYrroxk1RNQiWTtEtZzE0ErU7PhceS8N30uA5oJXmhO+18Ft\nAC0E0gQRIxhCOcCv7BSQ17h4cyOOY/De9wbXkvb2RpZdmeXwlIo1qaJ3VxCpKFEh0SbzFO0w9k+b\noKKD6YIbJgjzmsx5xYAN9TQ0+dgixFd+qXHzTpurN8xfgy40Qhgs4iQ3z7cwpzuX+Q5OdGTfdZJl\n85wEIQKn9s2MJSUHcTAQLEFDEYKhIYuHHirQ3m7wyCMF+vsjLF589jrS/NZSOJAPksiOlHUefdRk\nmbT57I1xrrryjemUs1nJI4/4xGKCq68WZ6w6gmm6HDlSIR7XWbDg1aNfriu5++4cnieZnDR56KEi\nt912TK/RmAnUbsPjYOiQeQvWJ73QyVlgKBA/zUFqJASfugFG8yVk8l4ykQZSdpZdmRwtMyadsyMU\n9BWk7HE6lhZJlXPkBwSakSSeqKPbBm3LG7B1WBuC2xa9/PMHbIP8WJ5YRFI1o1y6aAebr97El76p\nkuxM07c6xHBWZWzEZtXiwOiFC6Pcfnsn25+z0JJRSqZK4jip1ORM4F91tZ16xuVCJZ+Hv/4vGZTE\nOH5dol1mEL5NgATrXwq4g8XAofQlSDVIvIqF4HIDnTpeRxzXKxJOWxx9TkPUBLWqhLiG3eRACETW\nREoTMPH9LtwQJGSNci6DVffBT4KsIcIm0hgESwPRAHIKlDSUJUFZrmaw66AKwAIlCf5cTV2ziqLW\n+cgtBd5/e8dL+QWXXpomv0rS3O6y706F7KEierNOfqSLRqWEmvOgGOiDgyvOnNQBg8CBlsHnU4Zi\nCMqS6rTDHT9VuXrDuT5a87xRLGwOMXa+zTinvJrm9g+ATwMLhRC7j3spATx+Ng2b5+yzbxAe3AGd\nzVC5tMYR1UEC1xHhCvGr0bnE9wO59dmejgprsHauXFj/DVGWLzdQFOjpeeNRpW9+0yefD2q72rbk\nPe9548kRvi+5885BhoaqAHzoQ72sXn2SmmXHIQQcPmwxMeFSr/t0db08CtLVDp/8EIxOwuJeSL19\npJAXBA8Mw4OjQaL67y6DRac+3C8RDcHiNoMpwCNHo2PxwVCCUS/J+kgMRykQ0xQ+97v70O9r5D6n\nAU1N0KFH6GjV+Ot36yztnCYiiqD2EjghUPdhclkEV+Sp1MPoukY+V+Pzn59gz2EYL/ukelrpWyz4\nyc+n6Fwxy+LWhYTJEEpE+HEUcg117n7R5UuborQnFZ7bC9+/L5hBuXQtvHfLWdud541DQzAxESPR\nqIJWIXSDhjetgu6htFqoRRcvRzCK8ST0RmF5FNbrCEdF9yVrVynU/26CwSx4XhrfqoHZgqyaaMY0\nrueDDANpcC38rEUx6oM0ICShqqBFfXzHRNrlIClNccEXoJkQaYCqDVRA+CBzkIxBKgW1KpRzIKP4\nYZ1dO7J8/I+PXZ9vvTVDz4DBPUoe5cMeT36xicpDGmhZsmYL1OtzCWpxgiitxTHn1iNwbKtAGcxG\nlJBLSFr86EsO/Of5lrsXGmEMFnHmO12+mXm1yO23gXuB/wZ8/rjlZSll7qxZNc9Zp2rCd+6HZBSe\nfAHKS1w2tWhUkAzicgUhenvDvOMdGXbtqnLddRkWLjwNfcEZQgjBggWv7NTWah6m6aOqGo8/JTAM\nuOLSk1djkFJSKAQa4FIJCoUT13k9mKbHyEiNvr44U1MWR45UXtW5VVVBR0cIVVWCcluaBa4F2rF9\nu6D7mBRhnjcPvoSHR6E7HujCn5g4fecWQCFMI+9jz8RuHniumezMahZ3KKz7/CcRAwdg4VLc3gn+\nZfMvuHvVIrb9dCMdbQaf/GQjS7uOQu0OwAd1IUQ/DkKh4klmnxtANgrqWYf2lhoD5lL2DjsYSYOU\naVMYNKnJHC+Eisw6RzE4SHLmJu7d7jCue/QrEaoMMbx3gvYlS3lubzeZBMSjsP2Ft6Zz29YCbb2C\n8R3NqI0F/JEa6vIQQpNoMYXGhhKzaFTtBNIpwPVd0KQS8at0pkPc0G/Tkk3ztWySRGSEalWnjkLQ\nXUzDSElcSwWnm6BzGUAealNAHKH7KJpGIh2jZjdgywjSiYBdBkcEbXEtBfDBLQfPFKBlaaChVeMQ\ni0DJBiQHSq34/rEou6YJLumPkxmAI/82QeOQTrU3DDUzaLU7LMDVQHWgWgE5G2hwZerYd+EGf0sT\nX4kTVh0Mq8jMbBvNTReWFOztjoXDIcbPtxnnlFfT3BYJZOu/BSCEaAHCQFwIEZdSDp99E+c5G0gJ\nvg+GFlSeWVo2GG+xEcA7CKKJQgi2bGlgy5aG82vsrzE2ZnPHHdNYlqRQyZBpiuO5QenI224+cX0h\nBO99r+CHP5REIrB165mZZ41GVZYtS7J3bxFVFaxadXoaguuvT/PIwyXI7+Hy5t3wggfLPwnh17af\np6fhuZ1Bc4z1696a08dvJhQBXXEYroDrw+a5cqouPhYOUQwUTn3TN2jl4OF3YFegrxUGJqF+zVLC\ni5YCUJjt4667+ti506B/UZpkUqG/XwP7AAgd1HZwB0CWQaT4eaHE3l0lrFgCzVeILGjl58VORs0B\n6ofyaJ5FW2OFgpEmFauj+Qmy+Wnu+pcjZMsaU2WHhndE+VDxzsBRn/w+y1v+lB8N9ZMtwtqlZ3mn\nnid6OuCii8Ecz2Nnbabv11CPVlCkSs/0MJm4Tkezyb5DXeRFhmhSwVuQZE2zwWfXRcj+pMA/f7XG\nOy96iqOpBDuf60JVU9QqFtSLmLkE6G4gNcAmiIhqBDVqQ0hH4KkZSrkwnmtBygxGEzIKjgVZSRBN\n9QlkAirggJ2YK/tVgroLXgzCEq95IXfcB+/YAL0tMFQKztE//+wYzzxTZzZvwqWL4YAE1wz6FmdD\n0GKAVQDHm0umkwQTswLIA2XwJxDmYmzdoLNxmP2Dct65vQDxeXuVcjstza0Q4j3AFwgKiUwDvcA+\nYOXZM22es0k8CjdfCfc/A0t74De6w1SEgYEgIxTMOjx3IKhxun5JoP98s7BjRwUpobvb4PF/d7jx\nRh8pFWZPMZewYYPCmjUSReE1J8W9EkIIfuu3ehgdNYnHNZqaTi/R4p3vTLByYQXt0NO0LWiD8iAU\n9kHb5af93fU6fPUOqFtgWcEAZd3a07ddSnjiIBydhk19sPztNWP1uvnwMtg1G+jC1zaBicMDHKZM\nnXYSXEUf6qtkJa9dALsHYHAGVvdCeE67+x/f3M0Pv/0iQ9l2LKWVjg6DQiGG40BIXQz2LylVhhid\n6KW5XWew2eKfJ+v4qSh+bQa/YjCldKKFJdFFSRaH9lOYsGi1DlKJbSXfl+YweRbNLKSQE2hIVtse\nV8XyXOk7NEaOQnGSyzr+gdZbPoctF9L/Fi6NuX45PPaLDFIro5ZtnF9MIxSbmXiNYasBz29BIkEq\n1P/VJHWJoGUjfOdOi8eeKJOfsnHzXehGgnDMZTZrATNBsLPmgVIHtQZeAnAgYkO6FbJ5sD3wXDxv\nEpRQ4Il6paCcji5gdoogjhQjcHAd0NIwNgKZJLhRMGMgdJYv3kOswWK6uI6v/yLM6uUu9xz2iccV\nntxfwjELuJYL4wKWdYLlwH4ffBXGqkGHISRBMlkEFC0oRUYVCCGEjqFYJKJFCqEItao9Z9s8Fwoh\nDPrpON9mnFNON6Hs74DNwANSyvVCiGuBD589s+Y5F1y0IngECGLHjex+8BDsORpcVqdy8N4rz4eF\nJ6e93eDxxyuMjNhsWqdQLgt0Hd75KtOnmhgH61FQG8G4BsQbL1uhacppJZIdjxCCrgVpKKtQGQm0\ndpGWV3/jcZgmVKvQ3QVj4zA7+5rezoFx+NGOoG7wgXH4k3dDw4nNt+b5NeIGXH7cPWKSMkUsWokz\nTpk8Jk2ceD4MDFg88kiR9naDLVtSfOa9CrU6dDXBYA4euf8w1qP/ykUtHusaDf5t729x5Eia3//9\nFKGQALmYp51P8L/unGB4IEqvcYSGqxoY+nmZ+j4XO++iSpvy84dp3NqNZfiUK5JkU5KmsEMlWiZy\n0QaeHl7Kqh6Tffv3Uqt4aJrCJeE22mcP4RV3c7i0DjW7gEVr9iEiC19xP7gezNQgFYLoa/gZOcxi\nchidRiL0v5Zdf8a59hJ4+OEQg0d9/KrDrIgjvTyFYgbQEaqH9IogongVh9J2i+raIrsOxKm4NRAu\nYyMNeDKC58XAzxJEWedKajW1QCqJqDvIsWFI9gc7zdNBKCBrqKpGKFTGS/jU41G4JgF3DxK0CtOD\nzyKJKuqg+niOGURcZR0awjTHxqgWVTJNeSbCe8iPtjG+bRdSxBh2lhBuV7CnQkgisH8QhudqMppO\n0ATCsnmp+gIexPygzq7XCrRAPYv0beqyTq3TpuMjFg3L68w7txcWFg4HmHj1Fd9CnK5z60gps0II\nRQihSCkfEkJ88axaNs95ZWgS2puCjOmR6fNtzcvZuDFGOCwoFDxWr44SjQqECOqPvyLSgdrXg7/d\n54EQhK4+B9YeI5eDp7cHSWIXXxxFW/4JyO+DSCukjt3oDx+usm3bLM3NBjfd1EI0euJ0UioFF22C\nZ56FROK1RW0hCN4IAekoTE7DM8/DmsXQ3vbq753nGLG5xK4cNTQEEU48CU3T4847p9E0wc6dJrGY\nwqaLU+wehIf3w2NjMPt4livqktlqJw3KKIpbhUSaUFrD9+oo1rf47t4uJg4Kxp1Onn/chAdyiJCF\ndDzUuqCn0eDIRJnZH+fpeY/KOm8cbXSMQ/kesk4f16QEFUp8e9uTzAxWaIhHWLq+h1qlAotX8qMn\nr2L73lb8gVZuuHkN11538m12Pfj6ThgoQMyAT22CxtPIMfIxyfIDfOpIHBq5lTCv7ECfbcIh+Nhv\nCpwCbNtWJ1+o4OPh+8HMjvTmNK/SBVfgmpLndnSQWTxNU2aImT1RqEGuuoDAQfRRNAMjUsQqJ4LE\nMSuKjBmQqYBrQMiH6gygEg77LOytoohZOtqmeLK0mfK+atDKcq6Fb6B7lSQbPMrNOhT8QLbQHoJr\no9iRZrp37MM0wcxHuSj279QqIY5EF+JWZrj+ugxDhs+OnQ65GQVq5UBzq/mAB4oB/q+qI2jQlICZ\n6FzPbXeuMsMsiCJ21URr8Ak114D5Mi4XEmF0lsxHbk9KQQgRBx4F7hJCTBPMWczzFuW6i+DHjwUO\n0LsuPfff7/tw7w549jCs7IFbNh9rA6sogtWrX2vReTco7aO2g2+DrJxxm0+F78PX74R8AWw7mAm8\n9pqWEyK2juNz113jhGIKLx518Z/M88GtTSd8nhBwy82w5dqgjrDxGoPQyzpgSTvsGYCZffDwFDz+\nGPwft0NL8xvZ0rcXLcS5hoXMUqWb9EvO7vG4rqRc8RkYDjE17RFJSiYkPDcAUzXYNeWjTCUoqgky\n+gTT5W7yiU2MvqChfdtHZRS9Msz+72Y4sDPC7CTIUhwlFEKEczQ2FEkYkJsV2NlmdKkxOyF4/jev\nRH45i9bg0WLC5IM5ilqZvd8L46uSas1kenCGfNNGPrnjJg4+1MDvrfoh8Qzs2KEx1lqnMa0jswoH\nh2D9IrhqZRB8HChAT0ry4r4J7ju6l3de3ktj/6kjsR4mPiY67TiM45I/W4fltFm2zODmmy2mp31C\n4TT791dQNY1qtYiUNYQ0kDI8177WxR6q8DuffJSaV6fwVJGv/fO7mOtrS6zB4bLb9xBJmgxsb+CF\nx5sBDeqZwEelCL4FatDeNpPMsXrpPqIRm0ULhtn/rQ2YTgpWNOLuKgIKIpyhIa3TvzbEzrqN60hw\nwnBTF8qwR2RljNYrG2lqzdG/NcaG8UHy+TDe7hy5sQ10XryOpg0WTz/jgdIM/ghY9bkE1iwkdGho\nhSErKMBue4E8QgCOC14dUMDxiPTb6CGHiJWAt3an5rccFg77mTzfZpxTTte5vZlA3f5Z4LcJhm3/\n5WwZNc/555KVgRZXVSBxHpoXjczCY3uDadtnD8GqXlj2RnShIgLhG6F+L4hGMM68x17DI49LAzqR\nX9Ndeh7k8tDRDtkczMyc/DOkBM+TvNAXZdBQyWV01jg+K/ST6ziTr7NUWNiAj18DB3vgznHo7YbB\nEZieffs5t74veeyxGYaGqlx8cSNLl762ndpFiq5TRLISCY1lKzI8vaPAgt4Qk7MRvvoli2hKYdUV\nOo9N2owfNRjL/B4tlUnqtUXYqSiVqTJ7nvT5cdogoSfoWZRjNNfNzKEIvhnGtxRUtwH1UoP//qEu\nvvRlh1xRoq3zsQ4auJdYjJlJjMEamakCGxeGmLBNSqkq+4620BCyWNAX5gtfm2bvjggXJZ+iUMiT\nClskWv+JL9T/gOLOGMmJBFcVJT/7gc/hq8pcvmoa3e3jwECNmf0HUKL72f2NR9j82c8SaXjlpEiN\nNGH6MTmERpIwi15x3XOJoqrkyiqtfRHauzQiaY3HH5zAcEpMZuN4ehTPsQAlqDbgALtt9u9YjCd9\nAgmBpHNdnXDSITcSo+/iHIefyGGWFwStbp0EhExIlsCXKJUyhZLK+NQSmhtnOXgExmcb0DLgjIZA\nbSbRA+1rVN5/UZzvfnMazy6DKaHqQEnBbzWYqijsen4pqc0xjv5A0n7DR2mMPMjOg5s5MruYnz8y\niZOahkYjmL2qJsCrgm+yYHGdxb+7nKndk0wuDDFTFDBrArPgZY51K0MFFPJDHdS+YPHzzjj953bS\na543SBidpbSfbzPOKafl3Eopj4/S3nmWbJnnTUY68errnC00NYhOmvW5CbMzUQnAuAz0SwDlDXWE\nMCnh4hAng5hzYqt4fJdZyngkUPkgTS/TMOs6bN0CDzwAkShcMZc7NjsLTz0dyAwu3QyGoXDLB9r5\ns1GLRUKwoCfMHley4iwl9HW3Q1MjDI1COgk9b8PEsn37SvzkJxM0NOh861uD/OmfLiOdPrNtBK+9\nJsXh0SSGBo89VOfiSwRP7fXZ8ZhLTNOIagrFSZ9QopVMMoopLNyYj5nUGBoPwy1beGqiQm5NCv+H\nWjBaUjykqtF2ZZxbbmnm4KEpNPUgg2qC2voYDjpaXEWVOvValWsuirL9eZ19bYLoWJ32zjDPHEgz\n6GcxjQQN6VnyjkEynCHWdhB3AKxRj7zi85OfSVqbKvzbF3byTPgFUq0Kaz68hfX+dhY1pykOeTi1\n2imdW4FChneR5HIUoigniXKfax56yOXb31c5OJYholVZvKKVll4Xc5uGqyVRQgLbAZCkMgquqXDk\nqaUM7pxi+EiYQBPrgIhTqzahRo6S6rKpV1Wcsht0FzN0SMqg0kGlCpaJgsCWy3j8GTB0iVW36emB\nnv4p1DUOdVGnrcfgLz9xCb0xg/t/lGd8v4IWUrEsG+6ahYUq0o9T1lq4qEdjNg+99dUcTS9krOYy\nW6jjhDxoiUPBhWgFQZIQdQxRI5ftJTpgcFEapnP7+Mk118IPK0ESnG0D3QQ1b+d6npshjJRKcXgC\n32+fr85yAWHiso83mb7wLPP/s/fecXaU973/+5mZM6eX7b1Lq95QAyEE2HQQ4AA2NrhQ3GI7iW9u\nihOn3Ti5iX2TX3yT68Q2iQMGxyVgjDGYXiWKhFBDdVfa1fbds3t6mfr8/hjZVNGMGjrv1+u89px5\npjzz7Jk5n+c73/JWRRxyeNridU2AlFJWUsxXOCq01MCVq2HLAVjZCz3v1aRT/GbpUGYYYT/PInGp\no5MeVgIwgUUOm2b8jGIwiUXXa1KvnHsOrFrpCV1df9lVIZfznhTatrfOsvkRrusM0We7WMDso5jB\nJRiEz38Kpqa96mihUzA/e7FooyiQSOjkcl5xjfeaWd3wqWsFh4YkZhaqInB6LzR0wr1DGuE1LezZ\nViBcZRGJ54g2h+kYADUsmVQk3V2NNByaIBuIQNQEN+BZ1mIKl68IkM9LLr/sKVqaDpIs1vFcoZFN\njy7DGXQpOyZBrcjPfzzOpz8WxFUbSRYMDuTKCMVCGCCLBZ7atZieMzZSmh5iz9giZmIKSruB3u+Q\nKipEm12sF1RC7S2Y5SGef1pnVjmKb7qfReevINr81j59AgWNd5Ac+CgxmoV79sKjGySxgMAScRRi\njE+rVM+H005voO+lURw1RiIUIzVmUy4YrFhT5AufaePPfq+Ozo4CyaJNKesD2cDIQBzxc5dofISh\n54PYZhBkykvhpgS86M1SE4SasVMlcHSgRNkQ+HwugQDU6T2ccfkAl36kSBenEySEYUhWrmxi7940\n+RnLy76Qy8D2ICgZZHuMsckIsSh0t8GszhAbnzE4eBdQVQXuMBRN6G5A6QMjW4UjQ1i2xQM/nOIz\nn22mex1eoFrdLEj5wciAEwDygM/L/GBa1NYafHjyHhTly8f1/1fhneO+RZrC9xtvlef2ONruKpzq\ndFYBtdAU/81K776XTHMIH378hEkySCfLUNGoRkNHYRQTHYWqI1xa4Ve4eNg2pDOHXRWmvRd42RSu\nDyn024KwEHRoR7kyXADaWo7qIU5oFiyIs21bmoMHC5x5Zi319W8vpds7ZV4vzOsVzJtgtiCiAAAg\nAElEQVSt88ADNrNmKaw7VyN7Hzz6kp9IzATfFLq0SI2qzF0TITcpuPT8MOP1OfZ3+An9cAJ/OYap\nRFAjYZqWC0Z/IPjbqEFLZwcLFm2mjSIbvplgvE9gN0WQiXH8hSIzT77AXjfP8vXN/HTbQsYzRSJK\nNb45rSyIOAy8UMV/bplLwG8Q3W+w6qq9HHiug5lJyfyrFNLjAerbixQLY2zxr2HyQD2a/Cjtdpp/\n+lITQlFI5zyXl8DhIZzcsIGZLVtILFhAw7nnHvUqh2+XH+30EgZodYJ9YxB0beqbNToaHWpiPlqv\nPo35585l11aDwhQo9dUEq0t86lsKqxqb+fRnRvj6v7yEDCpQagZXQ7qSoe0LQbRBbhxEFKxpcFQw\nFIg0epVAADTh3QB8fnxama52WLWymtWrY4xsb2DONQHUw6ZRv1/wl3/ZwqpVYb777zl273GYSU8g\nHQUhJAua4eLTYeVy2CzhkaKg9nf8dExnKe4rUp7TCgkHBm2cbA5MiYVXytcsWzyTPEDnynFqD0RI\nlhrAkOCr8wwBUnjiPGpDXHLVqofprj3+vtIV3hkBfMzl1IoWfrs+txUqHFMyGfj2d6BU9jLX/Pbn\n4G0Yho46cRpJMoRJiTgNqIcvoQQaH6WOCUwa0Em8jUtL1+GC8+GBBz3Re+aal9v8QjDfJzBMuO85\nmMrAuUuh/Z1lDKvwNgiFNG6+uQfHcVHVo/+stb1d4dOffvmR/J9cC6tG83zhDwcZ22AzkTNorE5x\n1pX1LLxyDqsbIadqdEUM7ipOsPoSl8c3JmmZaxLK+SkEEnR3+vj+3fO5NGzxyA8VNm8MYs2dJqQI\nMtIBtYhp2OxIhbh0YBdNLT1Mh1qwxjTkmCRZVJBpH+lChLiYJNSSpbNpL0tmh/mvvjaSbSo10TA3\nf3odz9y1hPxwFTNby0TrNcYMnW8/Xub8rGDTpn0EfFPceEWABG2M3Hsv/ro6xh58kHB7O9FZs476\n+L4dXOnFE/TOVpnTILCrXVzXoatL5cLLBZv7BdVLw7RdFeR/f7+Ir6xw2dU+Dihxxm2Vaz7SxkjT\nJv7yD5dQngqBa0PJ9GqIOxLcNMg0IMGt9wRituCl37IlmBZKW4jeT5T42+Vx6upa+MUvXIaHYfFi\n7dfC9lfU1qp84hM1XHBBDV/5qsmdd6UwSnm6Z7ewZkWY+movrODhKWj1wW0bLF4ayWL3ubDdAoRX\n9IGY1ycMwEbTy5jlFDt3d2PEfdArwYnAvixIBYIBCFsQ16EuRnXcwLygvSIcTjLKWOziCIEe71Mq\n39EKJySplPeovrMDDg54vqkngritpws/YRxM4jS8qq0K7YgW2yOx7iwvpZfPB9obbLphFzy53Ssp\nf+uD8MfXgq9y1R4VjoWwfSX5Enz/MTiUcjnQPokmZgiaBnZApyUySPTxEdZe4ZUIq0blvPYq9nXH\nAZtDhzKUpmwySogRVyU2oTPR4PB9ex5DpLAMA6fsx1XLqEs17CegOZLiHN8QvoZFNPU0MnCvjYhZ\n6JaJlEEUS0HzFUBViCeyzBBH7F1CbBeEnzLABxPXh5h9ZZDsn5cpTQkKMxbOHJXxhMYdzyT5QON+\nhmea+fFTfcxqCdDgQOhwKg/pvvfuHu+WDy+EO1+CmF9wzWqVxGUB8nkvQFNRBG2/nkQq/OGXbW6Z\n3IUtCmhWFSGxBIEGDSqOL+SVsHV1yJtQSIIyBk4OFB+4IWASRCtIDaaTQAB0kw9/NcjfX99Ce8hz\nqG9rcymXJT09R/4eNjbCwnmD7O51GBiwsYolTDNHf3+J7XtcnBV1DJQEz/5oD0y6ENa8vlmHBS4u\nMIMncAUEJcm+KNnBCLaZgoANdS7sTHrV0srVXj5IR4PVYUqdc1CaTqyKlRXemgA+5nFqWUYqP5MV\nTkiamrzH9YOHoCoBHSdQpaT4e3yTCL5JWp1S+XA8StgrpuG4vEEm1QonI9sGYGgKqmogJXxEaxWc\n0BjhkkudatI65+XZ3PPPp7jnnnFKJY2lSyNAmPFSgIMZhdSIhTYPWk5LYu6fZLpYT8auJnAgw/KP\n7+Wyjx3i7ukE+Zkuxud8kG2HlvCRc0Jc/GGDux/vY2IQ8nqKvF5NTTBNvDrDrLnjdM5ayPWnOQxu\ndshVK1h5l6e/M8KhaofpUojwOo3SZgPiEGjUsfIwMhWjPy1o6Szyot7FgrnrCI5toW7NGiI9J0Z2\nBIC2OPzemlcuESSO4Ao8S+nnI6HNDMg5LFUfp0o0Aq0sau0g0XyQ9qsyFMfjZA76yQzq4MSAtJd6\nUNdB9aM2xAma05TyGYQraQml+Z/LL/i1sAXo6HjrydVEHv79gRylQJBA3CYSzDA5qfDLX9o0NWmI\nEYP7Bibg2TwUVdB0RFDDlwij5BTKMylABWGDksFWI0yN1EJEYvl8h0v/FkC6QC3YAcCFXAGqLXr9\nDfg57V2Pe4XjQwmbnbzDSj8nORVxW+GExO+HT9/sWWyrqt5cAJ7MOI6L40h0/Y2jxs5cCAfGYTIF\n6894uVRrhZOfkA5TFjwzplDO17Lyc9B0XpS2HZMs6o2x/LeW/3rdBx+cor7ej2H4yOcF69c38pVv\nTmPZDnULE0z5XOLOPrbtn0dxb4KgZiKCMaqqUuw8EOWmrx6ie3gpm58JEkno3P3fkv406DVlQp0l\n9KZpfNkilKIEZ5Vw1zewOr+T+qfv5gZfDU9Z1zNtBphwc5RX6KhbSlgpjVhHmbrzyoz5DG5aU0/f\nlg6qQmP4W88EuwrzzItZNOfi4zjKvzlCreM0fZzTGAcRBuGp4JZMM63Nz1G1JsXkE2mCNfXkp9px\nigr456FERxCuQ6SjHlOYJNxpmsb2UNRqidQuOuI1/2bc8QKUQo0kh4ZxbOiqimGaLrGYQnW1j+e2\nTbHnqTyYAlQJYRAJg9Y1KXx9RfZuqAW35FUhQyBzBnZYQY5poJRB5D33CRrxqq3ZQAS9ZoT6/lEu\nXL4OcQJkuajwzpFvURb8/UZF3FY4YdH1E8MV4WgxNlbi1lv7KRQc1q9vYdWqWmZmXHbtsqirU5gz\nx0ciAl+60st/e4LE4lR4j1jSBY0HIDsNC1uCGOk2vnp5G9qVr1+3tTXIvn15XFfS21vF6tVxPn5T\ngH99FEqWwra/2cecxBB6MoY/G0QL2mQzIfbcH6P4Y0G5N0mtrrD5JYNw/XNQXcWhfAdq6zxMvUh0\nbpZ4s4MVt/CVWpEZneltz/DA1igxc5Rm+Tyrzj+Pe7cYPD+uY7dL/NUuvlFYZj1H9MUoD+XmUtfc\nw66BEP3WOOcueYEPti1//cmcbKjtEPosuOOg9YDi1anuTNTSGUswOjDDzG6H3IiD66qgutAbx10W\nR+g2xt4U3WdMM6vcyn6jja4ajblzqwmH37m4TU5C89wmqpsTZCYtLjvDZuVKjWefnWZy0iTbbWA9\nHwS15GWmdzVEOMxIXxhjWxKEA3otqFnwO6CZyIIEVM8n1yq/8sTx3BjKOGYVHfMO4vefWgLp/UIA\njfmcWgnMK+K2QoXjxOOPj2NZkoaGAPfeO8LChVV85zsFcjkX24ZPfjLE/PmelaQibN9/KApcNB/M\nfihI6I4fOZ/zNdc08fzzKXRdYeXKKgCuPsPPs/1w6Jksk66FEl5OeLofM9qMoUQRikGuUEciOMqh\nwXo2TrQhZICoI+ltniCg1zNTimNNJshvjDI9YyBbINSVId0uuCe9muvk09TXOPQVNM5Ymmf/QIRf\nPjmM29RCvi+P0x/i/rE19PQEyB0MkJ8qkXU1oo1NJOqHKMyMYWqN6PpJ/gXWOoBX+0alUpJFkbk8\ndNsMgZBLbkwiyykINUGvD9JlZIcftT1EdVOQL1zdxe0pk339Co3NGh0dRx6TmYKXKrD2NfmKPjQf\nnt4tyLeF6D4drr4SRg+4EIySdiXPj/pBz0IkDHoIRARnt4tTTntFHGjCF5UEtBS5maKnXX9V5lfx\nARHvPQUgjSdwC4QSUXY+vpbI31Ukw8lICYcdTB/vbhxTKt/UChWOIYbh4PMpKIqgutpPoZDCcSTx\nuI9iUZLNSjo7NYaGHMbHXebPP949rnA0OaMZqgNQtGBezZHXC4c1zj331ZaXaAg+tgb+324/uILp\nKUmwtoaVl47y4K5uAsMuM0Y7eaOaKnOEYknHKCvMZH2sOBOuuKDE9zZVYeYc5CELY9iHPuOyu7+e\nmXUWbdpiHtlzCMOKgEgx+5ZvYo/NRn2pE23TGG5OYPSEIB3mUEalOKKR6ddRIg5W2eHpR9r5k90q\nC7Qsn/pUmNbW98/PjetKbrstwyO/nCS1D0AF83AWAmsKnGaoi0HOoLBJY98WwZ39BeobYpy+BoaH\nBckkNDS8ft9bBuHOLd7TmksWwdpXVDVeMR9OU8HOepW7/3G0xI6fOOzfIkjvzZBPKNDUAIcElB3I\nS1AdCAgIziagSKrtNLWBNGNhi6lcLV6hBhVcFS+bQhkvv20GtBAoAcyUiuHU40iwvFrC+Cvy4aQh\niMZCXl/G/f1M5dtZocIx4pFHkjz22DRVVT5uuKGVc85pQFUF2azFunX1VFerLFjgY9cui1BIsHBh\nJXTs/Y4ijixqy2WX3btNAgHPRUVRXm/pO3sh9P6RxmcnWxmYNuic08S6S4vcuz2BvypDQi/j+HS6\nmvLs+IVJSHNRFAujIc6BM2zi982Q3W5DzAIzhqiF0pif7KCf/XmFTfrHaTX3sCJ1N7pPYZ6ykWgg\nSq7sRwQjmJqBUaMyna3BmXJRVInQJFYK5AREVoVh3Obppw2uvfb983MjJSSzNhsnctAS81K7FBzI\nxkDmEU9MItsaYTxL0NaZu9hhasTGSNjU1/tQFM/t6o3Y0Ac1YfCp8OS+V4tbIaC5FuwaSLsu+6Ys\nRvbCxN4cjnAAHfpL4AtBXnh5ajUFRBX4o1QxhF+WSOa6qQltI1MqYdoaIEAJgyuADJCAgAIo4EoM\nE7A0HnjqDozVnZjBCKtpo5s3mZFVOGEoYbOdmePdjWPK++duU6HCCUw+b/Poo9O0tgYYHTXYtCnD\nhRfWcd55ry699tGPBkkm/UQiglCo4t92KvODH+TYt89CSsn69RHWrn3jqMqxlEtqQYiOaJihnGTX\n1jpaa3z0TeoYZojLPvNTPrj6Mb62q57iTIJyOcYLB21mb+zDmm5FLeRwyhJhTeEoXYQ7c9iESb4o\ncKcVhowO3MQ5XL7l6yTDPTStaKVvRwvWtED4fARneVmu7FENZcSCsoMbcUgOGDxzW57ICj9r6o9i\nmb1jjOXA8wM2Px/OYoYjXqnacAyiLhQUCLr4girKlIkwVapiDomYj64uH0uWeuV8L73EC5R9I7pr\n4Yn9nrPAsvZXt734ok1wn0tyrsr8NoWHD+QYGxzDKkTALIIMQ3MMEjq4ZbAMiAWgXYeyQiFZRaEY\nRhVlGmMhHKcGNB9oJS/QLOyDrIB5MRAKTJRBkdAagAUuzz41xtVqHyNnXctWxivi9iRBAm4loKxC\nhQrvNbquEAqpTE2ZGIZLPP7Gl56iCOrfR0KgwltTdqHPhLACXYeteY4j6e+36OzUSKddDhywjihu\n47UquUOjjO6ZRKkO0XTVLNa2w8IGBVNNctNld6MHxvm9v/0+X/+TL+CGXaZLCXL3RCjvzyOyBmqN\nH70xR+SMcfzVUaRTpLQjROmAj7KrMxFcyHD1x/iZeTZj4zpuKQDnhJAFi7LrI+JI4r0SsTBNZKaP\n5gUp9jwwj/F+P/r5Qdate39E2I9j8j8eGeXRb0yRPKiBGoDmIJg2Qm8g2mMTWVzHZUunmPxpI/Fo\nLT5hs2KFYNkyjZUr1bf0n79wIbRUeYUmFr6icuDwsMv3v2+xdZfDnr02TW0wMlICbRp8eWhvAFmG\nxlbI+70UM3UlGMp61cZCBbKBIFHLJirz7BxfjlOdg5iA7mrYlwS/gJACMgmZAnR1Q08UuhyYpXD3\nwFrOGryV9NoSzSJ2dAe7wntGCI1Fp9hEpCJuTxEKBZvJSZOGBj+hUEU8HU0OHSqwdWuKtrYQS5dW\nIYRA1xVuuKGVZ55JU905RmLpzxkggT14Oo8+UKa+Xueii+oIBCr/m1MJK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TkAACAASURB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            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GkvAg623RjoR",
        "colab_type": "text"
      },
      "source": [
        "## Conclusões\n",
        "\n",
        "Foi feita apenas uma análise superficial na base de dados do Airbnb, porém já se percebeu que existem *outliers* em algumas das variáveis. \n",
        "\n",
        "Também se notou que em algumas localidades há poucos imóveis disponíveis, o que pode distorcer as informações estatísticas de alguns atributos.\n",
        "\n",
        "Por fim, lembra-se que este *dataset* é uma versão resumida, ideal apenas para uma abordagem inicial. Recomenda-se que seja usado, em uma próxima análise exploratória, o conjunto de dados completos, com 106 atributos disponíveis."
      ]
    }
  ]
}