LombaKorona.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "LombaKorona.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNKeN/wguiECxKSQgKeMOF2",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mohripan/Machine-Learning/blob/main/LombaKorona.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6sN0EEPKKQK-"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "import torch.nn.functional as F"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "Tf0Z7DlKK6rI",
        "outputId": "83b9cb0c-74af-47d9-f32d-73f14964207d"
      },
      "source": [
        "covid_per_hari = pd.read_csv('https://raw.githubusercontent.com/mohripan/Machine-Learning/main/Lomba/Dataset/Kabeh/data%20covid%20perhari.csv', skiprows=[1])\n",
        "covid_per_hari.head()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        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>TGL</th>\n",
              "      <th>Perkembangan Kasus</th>\n",
              "      <th>Unnamed: 2</th>\n",
              "      <th>Unnamed: 3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2-Mar-20</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3-Mar-20</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4-Mar-20</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5-Mar-20</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6-Mar-20</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        TGL  Perkembangan Kasus  Unnamed: 2  Unnamed: 3\n",
              "0  2-Mar-20                   2           0           0\n",
              "1  3-Mar-20                   0           0           0\n",
              "2  4-Mar-20                   0           0           0\n",
              "3  5-Mar-20                   0           0           0\n",
              "4  6-Mar-20                   2           0           0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-KHgc-OqLQQV"
      },
      "source": [
        "# Membetulkan Nama Kolom"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q5MJayDELLeV"
      },
      "source": [
        "covid_per_hari['Sembuh'] = covid_per_hari['Unnamed: 2']\n",
        "covid_per_hari['Meninggal'] = covid_per_hari['Unnamed: 3']\n",
        "covid_per_hari = covid_per_hari.drop('Unnamed: 2', axis=1)\n",
        "covid_per_hari = covid_per_hari.drop('Unnamed: 3', axis=1)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "klcuX0VQL_7I"
      },
      "source": [
        "# Mengubah variable TGL menjadi datetime"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TQltN5RXL07G"
      },
      "source": [
        "covid_per_hari['tanggal'] = pd.to_datetime(covid_per_hari['TGL'])\n",
        "covid_per_hari = covid_per_hari.drop('TGL', axis=1)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "QhVHCeu7NEDr",
        "outputId": "08b4b0bb-0a64-4420-f18c-9420d57d8ed7"
      },
      "source": [
        "covid_per_hari.head()"
      ],
      "execution_count": 5,
      "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>Perkembangan Kasus</th>\n",
              "      <th>Sembuh</th>\n",
              "      <th>Meninggal</th>\n",
              "      <th>tanggal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-03-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-03-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-03-04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-03-05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-03-06</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Perkembangan Kasus  Sembuh  Meninggal    tanggal\n",
              "0                   2       0          0 2020-03-02\n",
              "1                   0       0          0 2020-03-03\n",
              "2                   0       0          0 2020-03-04\n",
              "3                   0       0          0 2020-03-05\n",
              "4                   2       0          0 2020-03-06"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8l4VURzxNUZX"
      },
      "source": [
        "# Plot data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nBZ3QMSdSbiQ"
      },
      "source": [
        "sns.set_theme(style=\"whitegrid\")"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "4WTHYNhvNt25",
        "outputId": "9a67abf9-8e01-4c03-a59b-3e9863732ca9"
      },
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['Perkembangan Kasus'],\n",
        "         label='Perkembangan Kasus Per Hari', c='#6D7AB8')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['Sembuh'], label='Sembuh Per Hari', c='#27A08A')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['Meninggal'], label='Meninggal Per Hari', c='#EC4035')\n",
        "plt.xlabel('Tanggal')\n",
        "plt.ylabel('Perkembangan Kasus vs Sembuh vs Meninggal')\n",
        "plt.legend()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fde441d96d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "p1YYHPhWciBc",
        "outputId": "f7c7082d-a64a-4c52-a96e-f182282ca1a3"
      },
      "source": [
        "covid_per_hari['Selisih Kasus dan Sembuh'] = covid_per_hari['Perkembangan Kasus']-covid_per_hari['Sembuh']\n",
        "plt.plot(covid_per_hari['Selisih Kasus dan Sembuh'])"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fde41a5f090>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HP5mPygXriaG"
      },
      "source": [
        "masih_korone = []\n",
        "kalkulasi = 0\n",
        "\n",
        "for i in range(len(covid_per_hari)):\n",
        "  kalkulasi += covid_per_hari['Perkembangan Kasus'].iloc[i] - (covid_per_hari['Sembuh'].iloc[i] + covid_per_hari['Meninggal'].iloc[i])\n",
        "  masih_korone.append(kalkulasi)\n",
        "\n",
        "covid_per_hari['Masih Positif'] = masih_korone"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 535
        },
        "id": "Ket2ezsZsP23",
        "outputId": "fd82ac5e-9631-422e-f3ac-830c85c3e50d"
      },
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['Masih Positif'], label='Pasien Masih Positif')\n",
        "plt.xlabel('Tanggal')\n",
        "plt.title('Masyarakat yang masih positif vs Sembuh')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Masyarakat yang masih positif vs Sembuh')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "Ta9Glb-ROnVh",
        "outputId": "8cf4681f-4f55-4a43-d53b-16789d08e9a2"
      },
      "source": [
        "sns.set_theme(style=\"whitegrid\")\n",
        "\n",
        "fig, ax = plt.subplots(figsize =(13, 8))\n",
        "bar_x = ['Perkembangan Kasus', 'Sembuh', 'Meninggal', 'Pasien Masih Positif']\n",
        "jumlah_kasus = np.sum(covid_per_hari['Perkembangan Kasus'])\n",
        "jumlah_sembuh = np.sum(covid_per_hari['Sembuh'])\n",
        "jumlah_meninggal = np.sum(covid_per_hari['Meninggal'])\n",
        "pasien_masih_positif = jumlah_kasus - (jumlah_sembuh+jumlah_meninggal)\n",
        "persen = jumlah_kasus+jumlah_sembuh+jumlah_meninggal+pasien_masih_positif\n",
        "bar_y = [(jumlah_kasus/persen)*100, (jumlah_sembuh/persen)*100, (jumlah_meninggal/persen)*100, (pasien_masih_positif/persen)*100]\n",
        "\n",
        "sns.barplot(x=bar_y, y=bar_x, orient = 'h')\n",
        "\n",
        "for s in ['top', 'bottom', 'left', 'right']:\n",
        "    ax.spines[s].set_visible(False)\n",
        "\n",
        "ax.xaxis.set_ticks_position('none')\n",
        "ax.yaxis.set_ticks_position('none')\n",
        "\n",
        "ax.xaxis.set_tick_params(pad = 5)\n",
        "ax.yaxis.set_tick_params(pad = 10)\n",
        "\n",
        "ax.grid(b = True, color ='grey',\n",
        "        linestyle ='-.', linewidth = 0.5,\n",
        "        alpha = 0.2)\n",
        "\n",
        "ax.invert_yaxis()\n",
        "\n",
        "for i in ax.patches:\n",
        "    plt.text(i.get_width()+0.2, i.get_y()+0.5,\n",
        "             str(round((i.get_width()), 2))+'%',\n",
        "             fontsize = 10, fontweight ='bold',\n",
        "             color ='grey')\n",
        "    \n",
        "ax.set_title('Perbandingan jumlah kasus vs jumlah sembuh vs meninggal vs Pasien Masih Positif',\n",
        "             loc ='left', )"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.0, 1.0, 'Perbandingan jumlah kasus vs jumlah sembuh vs meninggal vs Pasien Masih Positif')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "wgQ5njvZbxjY",
        "outputId": "f7e640a3-2c9f-4742-f387-bae00a31942b"
      },
      "source": [
        "sns.set_theme(style=\"whitegrid\")\n",
        "\n",
        "fig, ax = plt.subplots(figsize =(13, 8))\n",
        "bar_x = ['Sembuh', 'Meninggal']\n",
        "jumlah_sembuh = np.sum(covid_per_hari['Sembuh'])\n",
        "jumlah_meninggal = np.sum(covid_per_hari['Meninggal'])\n",
        "persen = jumlah_sembuh+jumlah_meninggal\n",
        "bar_y = [(jumlah_sembuh/persen)*100, (jumlah_meninggal/persen)*100]\n",
        "\n",
        "sns.barplot(x=bar_y, y=bar_x, orient = 'h')\n",
        "\n",
        "for s in ['top', 'bottom', 'left', 'right']:\n",
        "    ax.spines[s].set_visible(False)\n",
        "\n",
        "ax.xaxis.set_ticks_position('none')\n",
        "ax.yaxis.set_ticks_position('none')\n",
        "\n",
        "ax.xaxis.set_tick_params(pad = 5)\n",
        "ax.yaxis.set_tick_params(pad = 10)\n",
        "\n",
        "ax.grid(b = True, color ='grey',\n",
        "        linestyle ='-.', linewidth = 0.5,\n",
        "        alpha = 0.2)\n",
        "\n",
        "ax.invert_yaxis()\n",
        "\n",
        "for i in ax.patches:\n",
        "    plt.text(i.get_width()+0.2, i.get_y()+0.5,\n",
        "             str(round((i.get_width()), 2))+'%',\n",
        "             fontsize = 10, fontweight ='bold',\n",
        "             color ='grey')\n",
        "    \n",
        "ax.set_title('Perbandingan jumlah sembuh vs jumlah meninggal',\n",
        "             loc ='left', )"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.0, 1.0, 'Perbandingan jumlah sembuh vs jumlah meninggal')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9jnrmj8KZrva"
      },
      "source": [
        "# Kasus Per Provinsi"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "zoiJ0ENbTGW5",
        "outputId": "387accd3-7393-4209-ef0e-2298ee195dc6"
      },
      "source": [
        "provinsi = pd.read_csv('https://raw.githubusercontent.com/mohripan/Machine-Learning/main/Lomba/Dataset/Kabeh/Data_Harian_Kasus_per_Provinsi_COVID-19_Indonesia.csv')\n",
        "provinsi.head()"
      ],
      "execution_count": 13,
      "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>X</th>\n",
              "      <th>Y</th>\n",
              "      <th>FID</th>\n",
              "      <th>Kode_Provi</th>\n",
              "      <th>Provinsi</th>\n",
              "      <th>Kasus_Posi</th>\n",
              "      <th>Kasus_Semb</th>\n",
              "      <th>Kasus_Meni</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>96.909523</td>\n",
              "      <td>4.225082</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>Aceh</td>\n",
              "      <td>10814</td>\n",
              "      <td>9367</td>\n",
              "      <td>432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>99.057888</td>\n",
              "      <td>2.184779</td>\n",
              "      <td>2</td>\n",
              "      <td>12</td>\n",
              "      <td>Sumatera Utara</td>\n",
              "      <td>29198</td>\n",
              "      <td>25952</td>\n",
              "      <td>965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100.466805</td>\n",
              "      <td>-0.851914</td>\n",
              "      <td>3</td>\n",
              "      <td>13</td>\n",
              "      <td>Sumatera Barat</td>\n",
              "      <td>36268</td>\n",
              "      <td>33058</td>\n",
              "      <td>783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>101.812892</td>\n",
              "      <td>0.510526</td>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>Riau</td>\n",
              "      <td>42698</td>\n",
              "      <td>37374</td>\n",
              "      <td>1050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>103.599320</td>\n",
              "      <td>-1.617750</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>Jambi</td>\n",
              "      <td>7407</td>\n",
              "      <td>5987</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            X         Y  FID  ...  Kasus_Posi Kasus_Semb  Kasus_Meni\n",
              "0   96.909523  4.225082    1  ...       10814       9367         432\n",
              "1   99.057888  2.184779    2  ...       29198      25952         965\n",
              "2  100.466805 -0.851914    3  ...       36268      33058         783\n",
              "3  101.812892  0.510526    4  ...       42698      37374        1050\n",
              "4  103.599320 -1.617750    5  ...        7407       5987         108\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Tq0SkcjaSLx"
      },
      "source": [
        "provinsi = provinsi[provinsi['Provinsi'] !='Indonesia']"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 508
        },
        "id": "KhYy1-oXYwW-",
        "outputId": "24386277-4c70-4058-bc1b-fb11fee44759"
      },
      "source": [
        "sns.set_theme(style=\"whitegrid\")\n",
        "\n",
        "fig, ax = plt.subplots(figsize =(16, 9))\n",
        "\n",
        "sns.barplot(x='Kasus_Posi', y='Provinsi', orient = 'h', data=provinsi)\n",
        "\n",
        "for s in ['top', 'bottom', 'left', 'right']:\n",
        "    ax.spines[s].set_visible(False)\n",
        "\n",
        "ax.xaxis.set_ticks_position('none')\n",
        "ax.yaxis.set_ticks_position('none')\n",
        "\n",
        "ax.xaxis.set_tick_params(pad = 5)\n",
        "ax.yaxis.set_tick_params(pad = 10)\n",
        "\n",
        "ax.grid(b = True, color ='grey',\n",
        "        linestyle ='-.', linewidth = 0.5,\n",
        "        alpha = 0.2)\n",
        "\n",
        "ax.invert_yaxis()\n",
        "\n",
        "for i in ax.patches:\n",
        "    plt.text(i.get_width()+0.2, i.get_y()+0.5,\n",
        "             str(round((i.get_width()), 2)),\n",
        "             fontsize = 10, fontweight ='bold',\n",
        "             color ='grey')\n",
        "    \n",
        "ax.set_title('Jumlah Kasus Per Provinsi',\n",
        "             loc ='left', )"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.0, 1.0, 'Jumlah Kasus Per Provinsi')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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v3p3Bgweze/duHA4HN9xwA4MGDfpV6hZCCCGEEEIIfyUDKn5sx44dWK1WOnbsyIwZM3jiiScAWLp0Ka+88gqvvfYaABcvXqRbt27MmTOHnTt3MmvWLDIyMnzeOywsjIULFxISEoLdbue+++4jKyuLwYMHe73+kUcewWw2c/z4cQYOHMjAgQOBqkGfJUuWYDAYKCgoYNKkSQwcOJDw8HAATpw4wZIlSzAajbjdbl555RUiIyNxu9088cQTLF++nNtvv51HHnmEzMxM5s+f31AfX4NLSkrSZpHU5Tig7fJzudDQUB566CGvbTp27MjcuXOrHRs6dChDhw79Gb0WQgghhBBCCOGNDKj4Ic/gRWhoKAsWLCAsLIzPP/+cJUuWUF5eXuP1mYCAAMaPHw9Av379CAwM5KeffvL5DKfTycsvv8z+/ftxu90UFBRw5MiRWgdU5s+fT2xsLFarlYcffpjFixdzzz33UFhYyFNPPUVeXh4Gg4Hi4mKOHj1Kr169ABg3bpy20KrL5eKDDz4gKysLl8tFcXFxk1kkyWq1YjAYqKioAKpmmAQGBqLT6apNowsODsbhcOByubScTCYTAHq9nsrKSu1rk8mEXq+v0d7lcmGz2XC5XEDVQlKer202GwBGoxG9Xo/RaKzR3u12U1lZqW31HBQUhNPpxO12a6t8BwQEoNPpGrUmg8GA1Wr1q5r8LaeAgABtqz1/qcmfcnI6nVgsFr+qyd9ycrvdWCwWv6rJ33IKCAigrKzMr2ryp5ycTidOp9OvavK3nDz/LfKnmvwtJ09G/lSTp32zZs34pWRAxQ95Bi88Tp06xYsvvsiyZcto3749+/btY/bs2Ve8j8Fg0P6HDtX3IF+0aBElJSUsXboUs9nMM888U6c9ys1mM8nJyWRmZnLPPfcwb948UlJSePPNN9HpdKSmpla7j2d7YIC0tDT27t3Lxx9/TGhoKAsXLuTYsWNXfKYKzGYz4P2H9vJjvhaL9baQr7f2tS346+mHr/ZQNQPmUp5BLW8DWI1Vk8vlwmw2+1VNHv5Sk9Vq1Wrxl5ou1dRrujQfj6ZekzdNuSbP77nLNeWa/C0nh8OhrYd2uaZakz/l5PkHLX+q6dL2/lDTpf8t8peaLm/f1GsKCgqq1ld/qKkhBlI8ZFHa34DS0lICAgKIiorC5XLx6aefVjtvt9tJS0sDYM+ePVRWVtK5c2fat2/PiRMnKC4uxu12k56errWxWCxERUVhNpvJz89nw4YNdeqLy+Vi9+7ddOzYUbtPu3bt0Ol0bN26lby8vFrbWiwWIiMjCQ0NxWKxsGbNGu2c55j47fCMhAt1SUZqk3zUJxmpTzJSm+SjPslIfZKRbzJD5Tega9eujBo1ijFjxhAZGcmQIUPYs2ePdj4iIoIjR47w3nvvAfDqq69iMplo3bo106dPZ9KkSbRs2ZLExERyc3OBqgVjZ86cydixY2ndunWta4B4eF5DstvtxMTEaOt/PPbYYzz77LMsWLCA66+/nq5du9Z6j1tuuYUNGzYwatQoWrRowY033qjNZklKSuKDDz5g/Pjx9O3bV7lFaUXDu9LOT6LxSUZqk3zUJxmpTzJSm+SjPslIfZKRbzr3pe90iN8czy4/O3fubOyuKOfcP1c3yH1aPTS+Qe4jqrNYLA06XU80PMlIbZKP+iQj9UlGapN81CcZqU8y8k1mqAjhBy5cuMCaNWvIz8/H6XQSHR3NzTffTPPmzTly5AhfffUVJSUlREdHM2HCBCIjIzl37hxLly6lqKgIo9FI+/btGTdunLaldWZmJrt378ZutxMXF8fYsWMxGo0UFRWxZs0aTp48CaC18+zMdCmr1cqaNWv47rvvMJlM9O/fn/79+zdIzZ7FpoS6JCO1ST7qk4zUJxmpTfJRn2SkPsnINxlQ+Y2Ljo6W2SleuOyOBptZ4nY40RlrXyipIVgsFtxuN8nJyVy4cIFdu3aRlpbG5MmTWbZsGVFRUYwYMYKNGzfy+eefM336dHQ6HT169CAyMpJjx45x4MABNm/ezLhx48jJyWHz5s3a+a+//prw8HCGDh3Kpk2b+Omnn0hMTMThcLB//34yMzOZMGFCjX5t3LiRw4cPM2TIEPLz81m/fj3XXHMNnTp1uqqfhxBCCCGEEEJcbTKgIoQXTtwNtmLz1R5MgapZIvfcc4/2/aFDhzh37hyHDh3C6XQycOBAevTowenTpzl48CCFhYVERUUxaNAgKisrcTqdHDhwAJ1OB0B2djYAo0ePJiQkhIMHD3LgwAGGDh2q7fzUoUMHbDYb+/fvr3X76uzsbKKiokhOTqaoqIgjR45w4MCBBhlQ0etlTW3VSUZqk3zUJxmpTzJSm+SjPslIfZKRbzKgIoQXBnSN3YU6czucGC4ZtDl9+jQVFRV0796dixcvAmiv8Xj+LCoqonnz5uTm5vLZZ58BaAMfnvN6vV7bCjIsLIyTJ0/idDoZNmwYZ8+eZdmyZQC0adOGoUOH1uhXRUUFVqtVe+fy0mc3hMrKylq3bBNqkIzUJvmoTzJSn2SkNslHfZKR+iQj32RARQgv9AFGzi2o21bQja3Vw8O0rwsKCvjkk0+IiIhg9OjRfP3119WuvXwN6vbt23PnnXfyww8/sHPnTvbu3cuQIUN8Pu/QoUMUFBQwfPhwADIyMti4cSOjRo3y2U7WvxZCCCGEEEL4E5m/I4SfOH/+PIsXL8ZgMHD33XfTrFkzIiIiACgpKQGq1loBiIyMBCAkJIQuXbowcuRIdDod33zzjXbe5XJRVlamtQ8LC8NgMHDo0CH0ej0DBgxgwIAB6PV6fvrpJ6Bqn3qHw4Hb7SYoKAiz2Vzrs38pmX6oPslIbZKP+iQj9UlGapN81CcZqU8y8k1mqIirIiUlBZPJhMlkwuVy8eCDD3LzzTc3drf8VnFxMR9++CHl5eWkpKRw6tQpTp06RXx8PBs2bGDr1q2UlpZy5MgRrr32Wpo3b86WLVuwWq20bNmSo0eP4na7iYqKAqBnz5589913fPHFF0RERFBSUsKgQYOAqgGR8+fPs379eqBqEKVFixYAZGVlsXnzZm699Vbi4uLo2bMnu3btIjMzk/z8fO3eDUFWHFefZKQ2yUd9kpH6JCO1ST7qk4zUJxn5JgMq4qqZP38+sbGxfPvtt9x2220kJSXRvHnzxu6WXyoqKtJmk2zY8N9XlebOncvkyZNZv34969evp127dtpuPCEhIezdu5fS0lICAwOJj4/XXtvp3r07gwcPZvfu3TgcDm644QZtQCU1NRWn08nevXsB6NKlC6mpqV77lZKSQllZGVu3bsVsNjNs2DA6d+7cIDXLaLn6JCO1ST7qk4zUJxmpTfJRn2SkPsnIN51bFjYQV0FKSgoLFy4kNjYWgKSkJGJjYyktLcVutxMZGckLL7xAu3btOHnyJJMnT2bixIls3boVqBoISEhIYOfOnbz00kusWLECoNr358+fZ9asWZSVlWG1WhkyZAiPP/54g9XQFNdQ+S2xWCzagrdCTZKR2iQf9UlG6pOM1Cb5qE8yUp9k5JvMUBFX3Y4dO7Barbz22mvaDJWlS5fyyiuv8NprrwFw8eJFunXrxpw5c9i5cyezZs0iIyPD533DwsJYuHAhISEh2O127rvvPrKyshg8ePBVr0k1nvVJgoODcblc2Gw2XC4XAIGBgdrXNpsNAKPRiF6vx2g0Ul5ert0nODgYt9tNZWWltohsUFAQTqcTt9uN3W4HICAgAJ1Oh8FgoKKiAgCdTkdgYCA6na7GPR0Oh7a+Cvx36qBer6eyslL72mQyodfra7T3VpPNZsNqtfpVTf6Wk91ux2q1+lVN/pRTaWmp39XkbzldesxfavK3nOx2O2VlZX5Vkz/lVFpa6nc1+VtOnv8W+VNN/paTJyN/qsnTviEGimSGirgqPGuomM1mQkND+eMf/8j58+dZsmQJ5eXl2v/Yv/jiC06ePMmoUaM4ePCgNqVs5MiRzJ8/n+Li4lpnqJSXl/PSSy+xf/9+3G43BQUFTJ8+nfvvv79BapAZKmqT0XL1SUZqk3zUJxmpTzJSm+SjPslIfZKRbzJDRVw1njVUAE6dOsWsWbNYtmwZ7du3Z9++fcyePfuK9zAYDNW22/X8azfAokWLKCkpYenSpZjNZp555plq54V/Cw4ObuwuiCuQjNQm+ahPMlKfZKQ2yUd9kpH6JCPfZIUZ8asoLS0lICCAqKgoXC4Xn376abXzdrudtLQ0APbs2UNlZSWdO3emffv2nDhxguLiYtxuN+np6Vobi8VCVFQUZrOZ/Pz8aouxCv/nmVoo1CUZqU3yUZ9kpD7JSG2Sj/okI/VJRr7JDBXxq+jatSujRo1izJgxREZGMmTIEPbs2aOdj4iI4MiRI7z33nsAvPrqq5hMJlq3bs306dOZNGkSLVu2JDExkdzcXACmTp3KzJkzGTt2LK1btyYpKalRahONw2azERAQ0NjdED5IRmqTfNQnGalPMlKb5KM+yUh9kpFvsoaKaHSeXX527tzZ2F2pRtZQUZu8z6k+yUhtko/6JCP1SUZqk3zUJxmpTzLyTWaoCOGFy+6o10CFw+Fg4cKFXLhwgcTERMaMGQOA2+3mww8/JC8vj5iYGO644w4A9u/fz9dff01hYSEBAQE89dRTNe65adMmsrKyaj0PVWvKLFu6lO9zczGZTPTv35/+/fv/jIqFEEIIIYQQQtSHrKEiGl10dLRys1Oc1G/i1ubNmykpKalxfN++fZw+fbrGcYfDQWxsLEFBQV7vd+7cObZt24bR6HvMc+PGjXzz7bf079+f9u3bs379eo4ePVqvvjdVgYGBjd0FcQWSkdokH/VJRuqTjNQm+ahPMlKfZOSbDKgI4UV9Fl/Kz89nx44dJCcnVztusVhYv349Q4cOrdEmMTGR1NRUbY/0S7ndbtLS0ujTpw8hISE+n52dnU1UVBTJycmMHDkSgAMHDtS5702ZLJClPslIbZKP+iQj9UlGapN81CcZqU8y8k0GVITwIkBft7fhXHYnq1evJjExkbZt21Y7t27dOjp37kz37t3r9exdu3ZhsVgYNsz3K0cVFRVYrVbtncawsDAAioqK6vU8IYQQQgghhBD1J2uoCOGFPsBA/htXfg3p1KAALl68yPjx48nPzweq1jU5fPgwubm5TJ06lYsXLwJVW0NfaVGnyspKNm7cyLBhwygtLdVGhAsLC2nevLnPvvzW1pe22WyYzebG7obwQTJSm+SjPslIfZKR2iQf9UlG6pOMfJMZKk1USkoKAwcOxOl0asdWrFhB165d+eijj67YfurUqWzatKnBrqvNihUreOSRR6od27RpE1OnTgWqdvj57LPPfvb9G1tJSQnl5eUsXLiQlStXAnDw4EFWrFiBw+Fg0aJFfPjhhwAcO3ZMu6Y2lZWV2Gw21q1bx4IFC7BYLNjtdt58802gasqdw+HA7XYTFBSE2WzW1m6xWCwAREZGXq1yhRBCCCGEEEL8fzJDpQlr1aoVX3/9NUOGDAFg5cqV9OjRo5F7VT+nTp3is88+Y8qUKfVu63A4rrho69XWo0cPWrVqBVQtJLt582a6dOnCgAEDKC8vB6CsrIy1a9dyzTXXaFmdOXOGM2fOYLPZcLlc7Nu3jxYtWtC2bVtuvfVW7f7p6enYbDYmTZoEQFZWFps3b+bWW28lLi6Onj17smvXLjIzM7UZMj179vw1P4JG09jZiyuTjNQm+ahPMlKfZKQ2yUd9kpH6JCPfZIZKEzZx4kRWrFgBwIkTJygvLyc2NlY7v337dqZMmcItt9zCuHHjSE9P93qfy2eh1DYrJT09ncmTJ3P27FlSUlL4/vvvtXOXf19Xf/3rX/nxxx+ZMGGCNpPlpZdeYvLkyYwfP55p06Zx6tQpoGo2S79+/XjppZeYOHEiS5curXONV0tUVBRxcXHExcXRsWNHoGqGSMeOHbXjMTExAISGhtKhQwcAvvvuO9LS0qioqMDpdJKWlsb+/fsJCAjQ2sXFxREQEIBOp6t1HZaUlBR69OjB1q1bOXHiBMOGDaNz586/Su2NTa+XX1+qk4zUJvmoTzJSn2SkNslHfZKR+iQj32S4qQnr27cvS5Ysobi4mJUrV3LLLY+G5roAACAASURBVLfwzTffaOfj4uJYsmQJBoOBgoICJk2axMCBAwkPD6/3s9599122bt3K4sWLfa4BUl9/+ctfeOmll7SBIYAZM2bwxBNPALB06VJeeeUVXnvtNQAuXrzI9ddfr50vLi5usBp/qY4dOzJ37twaxyMiImocT05OrrErkDePPvqoz3Zms5nf/e53P6u/TZ2MlqtPMlKb5KM+yUh9kpHaJB/1SUbqk4x8k0+nCdPpdIwePZr09HTS09P59NNPqw2oFBYW8tRTT5GXl4fBYKC4uJijR4/Sq1evej1nwYIFtG3blnfeecfrNr9X6mN9ZWVlsWTJEsrLy3E4HNXOmc1mRo8erX3fUDX+EqWlpdqCsEFBQTidTtxuN3a7HUCbZWIwGKioqACqPpfAwEB0Op32ahBAcHAwDodDWysF0D5zvV5PZWWl9rXJZEKv19do73K5tFeJoGrveM/XNpsNqPrFqNfrMRqNNdq73W4qKyuVr6mkpITQ0FC/qsnfcrLb7drW3/5Skz/l5PkZ8qea/C2nwsJCgoOD/aomf8upuLgYs9nsVzX5U06lpaW0atXKr2ryt5xKS0sJDQ31q5r8Ladz584RGhrqVzV52jfERAEZUGniJk6cyK233kpiYmKNxUjnzZtHSkoKb775JjqdjtTUVKxWa417GAyGavuLX35Nr1692Lp1K6dPn9Zea7lSG4/mzZvX2Ma3qKiIFi1aeL3+1KlTvPjiiyxbtoz27duzb98+Zs+erZ0PCgqqNkhT1xqvJs8vGA/PKG5gYGCNa7390F5+zGAw1PqsgICAOrX3dh3gdYVub31qCjWZTCbMZrNf1eThLzVZLBatFn+p6VJNvSaXy1XjXFOvyZumXFNwcLDXZzXlmvwtp4CAAG3g+HJNtSZ/y8lgMPhdTZ72/lKT509/qunS9k29ptDQ0Bo/U029poZ840JeiGri2rdvz5///Gf++Mc/1jhnsVho164dOp2OrVu3kpeX5/Ue1157LYcOHQLghx9+ICcnp9r5QYMGMW/ePO6//35yc3NrtNm+fTsFBQVe73399dfzww8/8N133wFVu9isXLmSAQMGAFU/TKWlpdr1paWlBAQEEBUVhcvl4tNPP/VZf11rFEIIIYQQQgghGpLMUPEDte2Q89hjj/Hss8+yYMECrr/+erp27er1uhkzZjBz5kw2bNigLYZ6uaSkJF588UUefPBB5s+fz8yZM5kzZw4fffQRN910E23btvV67+bNm/Pqq6/yl7/8hcrKSlwuFyNGjGDy5MkAdO3alU6dOjF27Fg6d+7M/PnzGTVqFGPGjCEyMpIhQ4awZ8+eWmuva43C/3imwQt1SUZqk3zUJxmpTzJSm+SjPslIfZKRbzq35+UlIUQ1+W/svOI1rWf2+xV6IrxRYdts4ZtkpDbJR32SkfokI7VJPuqTjNQnGfkmAypCeOGyO9EH1P4unofb4UJn9P7m3IEDB1i1alWN4zNnzuSNN96odqxr167cdtttAPznP//h6NGjVFZWkpiYyJgxY7TrXn/9dYqLi7XvW7duzQMPPOD1+UeOHOGrr76ipKSE6OhoJkyYUGOdnabMs4iZUJdkpDbJR32SkfokI7VJPuqTjNQnGfkmQ01CeFFWWU6zgCsvVlTbYApAhw4dtFebXC4Xq1evJjAwUFsEqXv37trrVWFhYVo7o9FIt27dOHDgQK33TUhIALwv3ARVv/iWLVtGVFQUI0aMYOPGjXz++edMnz79ijU1FTIWrD7JSG2Sj/okI/VJRmqTfNQnGalPMvJNBlSEuEoiIyO1GSHffvstTqeT3r17a6tQR0VFERsbW2Mr6kmTJnHs2LFaB1QiIiKIiYnxuoq2x6FDh3A6nQwcOJAePXpw+vRpDh48SGFhIc2bN2+gCoUQQgghhBDit0sGVITwIiTI+xaIdXX5q0B79+5Fp9Nx4403aseysrLIysoiPDycMWPGEBsbW6d7Z2dnk52dTXBwMMOGDaNPnz41rrl48SLw35kvnj+Lior8ZkAlKCiosbsgrkAyUpvkoz7JSH2SkdokH/VJRuqTjHyTARUhvNAb9Zx99Zuf3b7NrB7a14WFhfz000/ExMQQEREBwIABA4iOjqasrIyvvvqK5cuXM3v27Fr3dPfo06cPLVu2xOFwkJGRwZo1a+jUqdMV10bxx6l6TqdTFshSnGSkNslHfZKR+iQjtUk+6pOM1CcZ+SafjBBX2d69ewG0dU8Ahg8frn39448/kpOTQ3FxMS1btvR5r8GDB2tfnzlzhh07dnDhwgUiIyNxOBzodDoMBoM2cFNSUgKAxWIB8KtFaf1xkMjfSEZqk3zUJxmpTzJSm+SjPslIfZKRb7WvqClEHaSkpDBw4ECcTqd2bMWKFXTt2pWPPvrIZ9upU6eyadOmKz6jrtepyOl0cuDAAcLDw4mJiQEgNzeX5cuXs3fvXr7++mtyc3MJDg7WBjsOHz7M999/D8D58+fZt28fFouF/Px8PvnkE3bt2sXOnTs5ePAgRqOR1q1bA/D888/zr3/9C4D4+HgMBgNbt25l586dHDlyhGuvvdZvXvcBsNvtjd0FcQWSkdokH/VJRuqTjNQm+ahPMlKfZOSbzFARv1irVq34+uuvGTJkCAArV66kR48eV2j125CTk0N5eTlDhw5Fp9MBEB4eTmlpKevXr8ftdtO2bVtGjhypLVabkZGhbY187Ngxjh07xrRp02jRogUul4vMzEzsdjtRUVGkpKRouwZdqlmzZkyePJn169ezfv162rVrx4QJE369woUQQgghhBDCz8mAivjFJk6cyIoVKxgyZAgnTpygvLxcW2B1+/btvP7661itVpxOJw888AA333xzjXtMnTqVe++9l6FDh3r93iM9PZ0PPviAf/7zn9xxxx0sXLhQe1ZKSkq171UQHx9PfHx8tWOtWrVi2rRptbZ59NFHaz1355131npu7ty51b7v3r073bt3r2NPm54rrTcjGp9kpDbJR32SkfokI7VJPuqTjNQnGfkmAyriF+vbty9LliyhuLiYlStXcsstt/DNN1ULusbFxbFkyRIMBgMFBQVMmjSJgQMHEh4eXu/nvPvuu2zdupXFixd7nZWhGs+6JQEBAdraJhUVFQDodDoCAwPR6XSUl5drbYKDg3E4HLhcLhwOB4C2rbJer6eyslL72mQyodfra7R3uVzYbDZcLhcAgYGB2tc2mw0Ao9GIXq/HaDTWaO92u6msrNTelwwKCsLpdOJ2u7UpfyrUZLPZ0Ol0flWTv+Wk0+mwWq1+VZM/5VRRUYHdbvermvwtJ09G/lSTv+XkcDgoKyvzq5r8KSer1UpAQIBf1eRvOVmtVux2u1/V5G85lZaWas/yl5o87Rvi75QyoCJ+MZ1Ox+jRo0lPTyc9PZ1PP/1UG1ApLCzkqaeeIi8vD4PBQHFxMUePHqVXr171esaCBQto27Yt77zzjvYDorraXsW50jHPqz/eeBsh9ta+tpFks9lcpz6FhoZW+96zsndgYGCd2v8aNel0OoxGo1/V5OEvNTkcDq1P/lLTpZp6TWazucaq/U29Jm+ack3NmjXzurNCU67J33IKDAysdfeLplqTP+UUFBSEwWDwq5oube8PNQUFBWnP9ZeaLm/f1GuKiIio9nvOH2pqyH+cl0VpRYOYOHEi8+fPJzY2ttpOMvPmzaNv376kpaWxatUq2rRpo/2L9aUMBoM2sgnUuKZXr17k5uZy+vTpOrcR/s0zWi3UJRmpTfJRn2SkPslIbZKP+iQj9UlGvsmAimgQ7du3589//jN//OMfqx23WCy0a9cOnU7H1q1bycvL89r+2muv5dChQwD88MMP5OTkVDs/aNAg5s2bx/33309ubm6NNtu3b6egoKChyxJCCCGEEEIIIbySARXRYKZMmVJjEdTHHnuMl19+mQkTJrBu3Tq6du3qte2MGTPIyspi3LhxvPvuu8TFxdW4JikpiRdffJEHH3yQb7/9lpkzZ7Jo0SImTJhAZmYmbdu2vSp1CTV5dk0S6pKM1Cb5qE8yUp9kpDbJR32SkfokI990bs9qMEKIas6++s3PbttmlmwbfbVduj6HUJNkpDbJR32SkfokI7VJPuqTjNQnGfkmAypCeOFyuNAb6z+B6/XXX6e4uFj7vnXr1jzwwANA1S+jhQsXcuHCBRITExkzZox2ndvt5sMPPyQvL4+YmBjuuOMOANatW8ehQ4ew2WyEhYWRlJREYmKi12cfP36c9PR0Lly4QFRUFOPHj+eaa66pdw1NhdPp9LkAlWh8kpHaJB/1SUbqk4zUJvmoTzJSn2Tkm7zyI4QXZRVlP7tthw4dmDx5MpMnT2b48OHa8c2bN1NSUuK1zb59+6otuOsRERFBSkoKo0aNwuFwsHbtWq/3cDgc/Oc//8Fms5GamkpZWRn/+c9/qi3a628u3S5NqEkyUpvkoz7JSH2SkdokH/VJRuqTjHyTARUhGlhERAQxMTHEx8fTpUsXAPLz89mxYwfJyck1rrdYLKxfv56hQ4fWOJeUlER8fDydO3cmNDS01ncYc3NzKSsrIyEhgcTERHr37s3Fixc5duxYQ5YmhBBCCCGEEOL/k5ehhPAiODC4Xte7HW50xqrBjuzsbLKzswkODmbYsGH07t2b1atXk5iY6HXh3HXr1tG5c2e6d+/OV199VeP84sWLyc/PR6fTkZqaSlhYWI1rLl68CKCd8/xZVFRUrzqEEEIIIYQQQtSNDKgI4YUhwMCZl0/W+fprHo8GoE+fPrRs2RKHw0FGRgZr1qwBqgY8xo8fT35+PgBWq5WysjLy8/PJzc1l6tSp2qCI3W7HYrHQrFkzAMaOHUtRURGbNm1iy5YtxMfHExIS4rM/v4WlkYKD6zfoJX59kpHaJB/1SUbqk4zUJvmoTzJSn2TkmwyoKGjdunX861//wu12Y7Va6dGjB//4xz98tjl58iSTJ09m586dv1Ivq3vjjTeIiYmpttCqR0pKCiaTCbPZjNVqJSEhgblz5xIQENBgz8/JyeHo0aNen/9rGjx4sPb1mTNn2LFjB/v376e8vJyFCxdq5w4ePIjBYODaa6/F4XCwaNEi7dyxY8dYuXIld999NwDR0dFER0dTUFBAVlYWeXl5xMXF4XA4ADAajURERABo66tYLBYAIiMjr27BjcjhcMgCWYqTjNQm+ahPMlKfZKQ2yUd9kpH6JCPfZEBFMefOnePZZ59l5cqVXHPNNbjdbnJychq7W1c0c+ZMn+fnz59PbGwsTqeTO++8k/Xr19dr8ONK23Xl5OSQmZnZqAMq+fn5bNy4keuuuw63283BgwcxGo2MHDlSG+A4d+4cmzdvpkuXLiQkJBAcHMytt94KQFlZGWvXruWaa65hyJAhVFZWsnz5cmJiYoCqhWsBWrZsCcCbb75JeXk5Tz31FDExMYSEhLBnzx5MJhP79+8nIiKCjh07/vofxK/Enxfc9ReSkdokH/VJRuqTjNQm+ahPMlKfZOSbDKgopqCgoNqMA51OR1xcHFBzFoqvWSmPPfYYR48exW63c+211/LCCy8QHh7OrFmzGDFiBKNHj+bdd99l4cKF7Nq1C4PBwJgxY/jnP/9Jp06dWLlyJUuWLMHpdBIaGsq8efPo3Lkz+/bt47nnnsPlcuFwOHjwwQcZO3Ysc+bMIT4+nrvuustnfVarFavVqq3xsX37dl5//XWsVitOp5MHHniAm2++GYCpU6fSrVs3srOzCQ8P5+233+YPf/gDRUVFWK1WbrjhBp599lnKysqYP38+paWlTJgwgcTERJ5++ukGy6SugoODcblcZGZmYrfbiYqKIiUlhfbt21e7ZvPmzURGRmrrqXiy9rzyExoaSocOHbDb7VitVjZs2IDL5aJ58+aMGDGCVq1a1Xi20Wjk1ltvZe3atXzxxRe0atWKcePGodf777rTnhk6Ql2SkdokH/VJRuqTjNQm+ahPMlKfZOSbDKgoplu3btxwww0kJyfTr18/+vTpw4QJE+r96sb//u//0rx5cwBee+013n33XWbPnk1SUhLbt29n9OjR7Nixg5iYGA4dOkTbtm0pLy+nU6dO7Nmzh3Xr1vHxxx9jMpnYvHkzTz31FJ9++invvvsu9913H2PHjsXtdmszL67kkUcewWw2c/z4cQYOHMjAgQMBiIuLY8mSJRgMBgoKCpg0aRIDBw4kPDwcgBMnTrBkyRKMRiNut5tXXnmFyMhI3G43TzzxBMuXL+f222/nkUceITMzk/nz59frc2poU6ZMwel04na7sdvtAFRWVqLT6TAYDLRo0YJZs2ah0+lwOBzodDptKzKDwcDTTz+Nw+GgoqICh8PBrbfeislkAkCv11NZWYnFYkGv1/PQQw+h1+u1DJo3b87999+Py+XCZrPhcrmwWCwEBgZqI8s2mw2oGoDR6/UYjcZqW6EFBwfjdruprKzU1mEJCgqqUVNAQIBWU0VFBVA1+BcYGFitJs89HQ6HNggH1KjJ87XJZEKv19dof2lNAIGBgdhsNqxWq1/V5G85eQYF/akmf8qptLTU72ryt5wuPeYvNflbTna7nbKyMr+qyZ9yKi0t9bua/C0nz3+L/Kkmf8vJk5E/1eRp71mz8peQARXF6PV63nrrLb7//nt2795NRkYG77//PmlpafW6z6pVq0hLS8Nut1NeXq69+nHTTTfxzjvvYLPZOHv2LPfddx/btm2jbdu29OvXD4CNGzdy5MgR7VUUt9utrc3Rr18/3n77bY4fP86AAQPo2bNnnfrjeeXHarXy8MMPs3jxYu655x4KCwt56qmnyMvLw2AwUFxczNGjR+nVqxcA48aN0171cblcfPDBB2RlZeFyuSguLiYwMLBen8vV5PmB9PTXW9+8/dBefszXO4re1p3x1r629WnMZnOd+hQaGlrtexVrCg0NxWw2+1VNHv5Sk9Vq1Wrxl5ou1dRrMhqNNWpo6jV505RrioiI8Nr/plyTv+UUEhLite/QdGvyp5xMJhMGg8Gvarq0vT/U5Fln0dPeH2q6vH1Tr6l58+bV+uoPNTXEQIqH/74P0MTFxsZy5513smjRIpo1a8auXbu0WRoenn/5vdyePXv45JNPeO+990hLS+PRRx/VRgvbt2+Py+UiPT2dXr16aTNWduzYQVJSElA1gDJ58mRWrVrFqlWrWL16NZmZmQDcc889vP322zRv3pznnnuO1157rV51mc1mkpOT2bZtGwDz5s2jb9++pKWlsWrVKtq0aVOtrktXlU5LS2Pv3r18/PHHpKWlcccdd2h1CSGEEEIIIYQQvyYZUFFMfn4++/fv174/e/YshYWFREdH07JlS+x2O3l5eQDalryXKykpITQ0lIiICGw2G8uXL692/qabbmLBggX079+fa665hosXL/L1119rAyopKSmsWrWKs2fPAuB0Ojl8+DAAR48e5dprr+W2227j7rvv5tChQ/Wqz+VysXv3bm3GjMVioV27duh0OrZu3arV5o3FYiEyMpLQ0FAsFku1+j3HxG+HP68P4y8kI7VJPuqTjNQnGalN8lGfZKQ+ycg3eeVHMQ6HgwULFnDq1CntfbRHH31UW5j2f//3f5k+fTrNmzcnOTnZ6z0GDRrE6tWrSU1NJTIykoSEhGoDH0lJSSxfvpybbroJgBtvvJHt27fTunVrABITE3n00Ud58MEHcTqd2O12Ro0aRXx8PP/+97/ZuXMnAQEBmEymOi/+6llDxW63ExMTw0MPPQRULZ777LPPsmDBAq6//nq6du1a6z1uueUWNmzYwKhRo2jRogU33nijNpslKSmJDz74gPHjx9O3b99GWZRW/LoqKysbdOtt0fAkI7VJPuqTjNQnGalN8lGfZKQ+ycg3nfvSd0iEEJozL5+s87XXPB59FXsivLFYLA36/qNoeJKR2iQf9UlG6pOM1Cb5qE8yUp9k5JvMUBHCC5fdVa9BErfDzRtvvkFxcbF2rHXr1jzwwAO89957nD9/HpfLRVRUFKmpqXTo0AGAZ599ttp9unbtym233XbFc5fbs2cPWVlZVFRUcN111zF+/Phq68/4I5l+qD7JSG2Sj/okI/VJRmqTfNQnGalPMvJNBlSE8MKJE309lhjSGXUAdOjQgYSEBOC/q1RHR0dz4403UlpayqZNm1i9ejUPP/yw1rZ79+7aK11hYWHV7uvrnMeZM2dIT0+nc+fOdO7cmQ0bNvDll18yceLEOve/KfJshybUJRmpTfJRn2SkPslIbZKP+iQj9UlGvsmAihBe/NyR2IiICGJiYqptGZaamkpFRQVFRUVs2bIFnU5XrU1UVBSxsbFef1n5Oudx4MABoGox4Xbt2vH9999z+PDhaltO+yMZLVefZKQ2yUd9kpH6JCO1ST7qk4zUJxn55r9/2xLil3DpoPbtzGte7qhaiig7O5vs7GyCg4MZNmwYffr0wWq18ve//x2omrUyfvz4am2zsrLIysoiPDycMWPGEBsbW6dzHhcvXgT+O4MlLCwMl8tFcXExLVq0qFfZTUl5ebm8z6k4yUhtko/6JCP1SUZqk3zUJxmpTzLyTQZUhPDCEKAn9838Ol8f86fW9OnTh5YtW+JwOMjIyGDNmjV06tSJ8PBw7rrrLgoKCsjIyGDTpk1MmzYNgAEDBhAdHU1ZWRlfffUVy5cvZ/bs2QQEBPg8J4QQQgghhBCiccmAigDAbrezcOFC1qxZg9FoxGAw0LFjRx555BG6dOly1Z+fkZFBq1atuOGGG6547YIFCygvL+eJJ5646v2qj8GDB2tfnzlzhh07dnDhwgUiIyO57rrruO6668jJyeHYsWOUl5cTHBzM8OHDtTY//vgjOTk5FBcX07Jly1rPtWjRAqfTiU6nw2AwEBERAUBJSQnNmjWjpKQEvV5PeHj4r1e8EEIIIYQQQvzGyICKAODJJ5+ksrKSpUuXEhYWhtvtZvPmzRw9erTOAyoOh+Nnr9mRkZFBfHx8nQZUVJSfn8/GjRu57rrrcLvdHDx4EKPRSGlpKatWraJ9+/aUlJRw4sQJQkJCCAoKIjc3l4MHD9KxY0cqKirIzc0lODiYyMhIn+eKi4t54403iImJ4Y477qBnz57s2rWLjRs30rlzZ06cOMH111/v1+unAH6/i5E/kIzUJvmoTzJSn2SkNslHfZKR+iQj3/z7b1yiTo4dO0ZGRgabN2/W1uHQ6XQkJycDUFZWxt/+9jcOHToEwIQJE5gxYwYAU6dOpVu3bmRnZxMeHs7ChQt55ZVX2LJlCwCDBg1i9uzZGAwG5syZg8lk4tixY5w9e5ZevXrx0ksv8fXXX7Nx40a2bdvG0qVLmT59OgMGDGDWrFmUlZVhtVoZMmQIjz/+eI2+O53OWp/3awoODsblcpGZmYndbicqKoqUlBSCgoLYtm0bhw8fxmAwcO211zJ8+HB0Oh3h4eGUlpayfv163G43bdu2ZeTIkRgMBp/nLte2bVvGjBnDli1byMvLIyYmhtTU1F+1/sbgcrl+9ZxF/UhGapN81CcZqU8yUpvkoz7JSH2SkW8yoCL49ttv6dChQ62viLz11lu4XC7S0tIoKytjypQpxMbGMmTIEABOnDjBkiVLMBqNLFmyhJycHFasWAHAjBkz+Oyzz7jjjjsAyM3NZfHixeh0OiZOnMi2bdsYNGgQKSkpxMfHc9dddwFgtVpZuHAhISEh2O127rvvPrKysqq9VgPw2Wef+Xzer6VZs2bceeedXs/98Y9/9Hq8VatW2loq9TkXERHB3Llzqx1LTEwkMTGxHj1u+mw2m6wnozjJSG2Sj/okI/VJRmqTfNQnGalPMvJNBlREDT/88AOPPfYYlZWVDBo0iH379vHUU0+h0+kIDQ3l5ptvZvv27dqAyqXb827fvp2JEydq2/xOmjSJjIwMbYBj+PDh2pbCcXFxHD9+nAEDBtTog9Pp5OWXX2b//v243W4KCgo4cuRIjQGVKz3v12SxWAgKCsLpdOJ2u7Hb7QAEBARo651UVFQAVTOAAgMD0el0lJeXa/cIDg7G4XDgcrlwOBzAf/d+1+v1VFZWal+bTCb0en2N9i6XC5vNhsvlAqp2FvJ8bbPZADAajej1eoxGY432brebyspK3O6qnYtUramyshKj0ehXNflbTna7Xfvd4C81+VNOJSUluFwuv6rJ33IqLS31u5r8LSer1QrgVzX5U06lpaVa//2lJn/LyfN7zp9q8recPP9/wZ9q8rRviN2LZEBFEBcXR15eHiUlJYSFhdGlSxdWrVrFRx99xOHDh6/Yvj7v1XkGUwAMBgNOp9PrdYsWLaKkpISlS5diNpt55plntP/ToirPD6TnL5CBgYG1XuPrmK8pdd5Gh721r20U+dLP31efQkNDq32vYk0mkwmz2exXNXn4S00Wi0WrxV9qulRTr8nlctU419Rr8qYp1xQcHOz1WU25Jn/LKSAggJCQEK/tm2pN/paTwWDwu5o87f2lJs+f/lTTpe2bek2hoaE1fqaaek0NuQ20vsHuJJqsjh07MmzYMJ5++mksFot23DNyl5SUxPLly3G73ZSWlrJ27Vr69+/v9V5JSUl8/vnn2O127HY7n3/+ea3XXio0NLTasy0WC1FRUZjNZvLz89mwYUODPk80fd5+4Qq1SEZqk3zUJxmpTzJSm+SjPslIfZKRbzJDRQDw4osv8tZbb/G73/0Oo9FIWFgYrVq14v7776djx44899xzjBs3DoDx48fXePXGY8qUKRw/fpyJEycCMHDgQH7/+99f8fnjx4/nySef5IsvvmD69OlMnTqVmTNnMnbsWFq3bk1SUlKDPk80fZ6phUJdkpHaJB/1SUbqk4zUJvmoTzJSn2Tkm87teXlJCFFN7pv5db425k+tr2JPhDdWq9XrtEKhDslIbZKP+iQj9UlGapN81CcZqU8y8k1mqAjhhdPuqtcgicvhRm/U1enaQVA4AwAAIABJREFUdevW8c0331BWVkZMTIy2gO758+dZvXo1Z86cISIigtGjR3PdddcB8N5773H+/HlcLhdRUVGkpqbSoUMHALZs2cLu3buprKwkNjaWcePGab/0zp07x7p16zh58iQBAQH07t2bESNGeO1XZmYmu3fvxm63ExcXx9ixY7X3GVVks9nkl7viJCO1ST7qk4zUJxmpTfJRn2SkPsnIN1lDRQgvyivL6nV9XQdTPHr06FHj2PLlyykoKGDkyJHo9XqWLl2qrUodHR3NqFGjGDx4MGfPnmX16tVA1ZbXGzdupF27dgwcOJBvvvlGW2/Gbrfz0UcfkZ+fT3JyMsnJybUuIJWTk8PmzZvp1KkT/fr1Izs7my1bttSrJiGEEEIIIYT4LZEBFSG8uJozM0aPHl1jTZgzZ86Qn59PfHw8ffv2JSkpCavVyrfffgtAamoqXbt2pXPnzhiNRnS6qgGcvLw8oGpx3sGDBxMaGkp2djYAhw8fxmKxMHz4cPr27Uvfvn1JTk722idPm9GjRzNs2DDCwsI4cODA1Si/wag8e0ZUkYzUJvmoTzJSn2SkNslHfZKR+iQj3+TTEcILU8DVmdZW26tBFy9eBCAsLKzan0VFRUDVu4t///vfgaqVtsePHw/8d8vqY8eOYTAYKC8vx+VyUV5ezvnz5wHYvn07aWlpBAcHM2bMGK+zY4qKitDr9drWj2FhYZw8eRKn0+lzG7LGpNfLeLDqJCO1ST7qk4zUJxmpTfJRn2SkPsnINxlQEcILg1HPng/ONfh9E+5tVafrLl8r2mQycdddd1FQUEBGRgabNm1i2rRpJCYmcvjwYTZt2sSmTZswmUzYbDaMRiMOhwOo2mc9JSWFdevW8fnnn9OlSxe/eA9SRsvVJxmpTfJRn2SkPslIbZKP+iQj9UlGvslwkxAKiIiIAKCkpAQAi8UCQGRkJFA1MnzdddfRr18/2rVrx7FjxygvLyc4OJgHHniAGTNm8Kc//YlmzZoRHh6OyWTS2sbFxdG9e3c6dOiAw+HAYrHgdrtxOBzaNmiRkZG4XC7Kysq0foSFhSk7OwWgvLy8sbsgrkAyUpvkoz7JSH2SkdokH/VJRuqTjHyT4aYGsG7dOv71/9i797Cq6rz//8+9N2wOAgKKiAc8DeSBkDyE5DHKFLUwGCfLdCzGyrnvKy39aqPNPTmVTU2N482kTkw1jaNZiobbpDzmIRQkPNGI1GQopiACct7n3x/89hqRDZ4QFvt+P66rS9hrf9Za7/UCjI9rvT9//St2ux2j0cigQYN45513mh1TWFhIYmIimZmZrXSWDa1cuZKwsDAmTZrU4PVp06ZhMpkwm838+OOPhIWFAfW/lL/xxhttcaouJz8/n+Li+rtfKioqyMnJoVevXgQHB5Obm0tQUBDZ2dno9XoGDhzI999/z7fffkvPnj2pqKjg3LlzdOjQAS8vLyorK8nMzKRz5858//33XL58mYkTJwIQERHB7t27OXbsGBqNhh9++AFfX18CAwMpKCjgo48+Yvjw4UyaNInBgwdz+vRpvvjiC/z9/amoqGD06NFteZmEEEIIIYQQQtVkQuU2FRcXs2zZMrZs2UJISAh2u51Tp0619Wld17x585y+vnHjRuA/Ez5paWmteVo3xWazodFolAat7UVGRobSTLaoqAiDwUB8fDwJCQkYDAZ27NhBx44dmTZtGp6ennh5eXH+/Hlyc3PR6XSEhoby4IMPKrWfPn2aw4cP4+XlxdixY7n33nuB+kd9EhMT2blzJ1988QVdu3Zl0qRJTp+DHDBgAGPGjOHIkSNYLBYiIyNlQkUIIYQQQgghmqGxX9usQdyUf/3rXzzzzDPs3LkTLy+vBtuuvQvl6s+v3bZgwQLOnDmD2WwmNDSU5cuX07FjR1588UXGjx9PXFwcKSkprFmzhqysLHQ6HZMmTeLdd9+lT58+bNmyhfXr12O1WvHx8eGVV16hb9++5OTk8Oqrr2Kz2bBYLMydO5cpU6bw0ksvERERwZNPPum0rmvPb9++faxevRqTyYS7uzu/+c1viIqKIjMzk+XLlzN48GCOHj2KRqNhxYoV9OvXD4AVK1awfft2/P39uffeezl06BCbN29udtulS5d48cUXqa6uxmg0MnbsWBYtWgRAcnIy3333HVVVVfz000988sknyjUxm80EBASwfPlyunfvftvZtmUPFXF9am6YK+pJRuom+aifZKR+kpG6ST7qJxmpn2TUPLlD5Tb179+fyMhIxo0bR3R0NEOGDCE+Pl7pX3Gjli5dSmBgIFA/0ZCSksLChQuJiYnh0KFDxMXFcfjwYcLCwjh58iTdunWjpqaGPn36kJ2dTXp6OuvWrUOv17Nv3z6WLFnChg0bSElJISkpiSlTpmC325XeHDfj7NmzrFq1ivfffx8fHx++++475syZw1dffQXA999/zxtvvMHvf/97Vq9ezapVq3jnnXfYs2cPe/fuJS0tDU9PT55//nlln81t8/PzY82aNXTo0AGz2UxSUhL79+9nzJgxAJw4cYLNmzcr12vOnDksXrwYqL/D5u2332bFihU3XWdrqaysRKPR4OnpiUajafBcore3t9LbxNFUVq/XA/V9VOrq6pSP9Xo9Wq220XibzYbJZFL6o3h6eiofm0wmoL65lFarxc3NrdF4u91OXV2d0hjXy8sLq9WK3W7HbDYD4O7ujkajQafTUVtbC9DqNTma77pSTa6Wk+P8XakmV8rJ8T3kSjW5Wk41NTXK95Cr1ORqOTnqcaWaXCkni8WCn5+fS9XkajlZLBbc3NxcqiZXy6miokJpTOsqNTnG+/r6crtkQuU2abVaVq1aRX5+PkeOHGHXrl28//77GAyGm9pPWloaBoMBs9lMTU0NvXv3BmDEiBG89957mEwmLl68SFJSEhkZGXTr1o3o6GigfnIiLy+PadOmAfUrxDiam0ZHR7N69WrOnj3LyJEjGTx48E3XeODAAc6ePcuMGTOU1ywWCyUlJQD06dOHgQMHAhAVFcXevXsByMzMJC4uTlnad+rUqaxateq626xWK2+99RZHjx7FbrdTUlJCXl6eMqEyZswYZTIFYP/+/axfv175oax2137jXvt5czPA7u7u192fTqdz+j7A6eo+zn6Q+Pj4NPjc8UPU09Pzhsa3Rk1GoxEPDw+XqsnBVWqqqqpS7txzlZqu1t5rstvtjc6tvdfkTHuuSafTNTovaN81uVpOjjuDnWmvNblSTlVVVcr3kqvUdPV4V6ipqqpKOQ9Xqena8e29Jnd39wbn4Ao1tcREioNMqLSQ8PBwwsPDmTFjBpMmTSIrK4vIyMgGy98ajUanY7Ozs/n444/ZsGEDgYGBGAwGPv30UwB69uyJzWbj888/JyoqipiYGBYtWkT37t2JiYkB6idQEhMTnfZFmT17NrGxsWRkZPDqq68ycuRIXnjhhZuub/To0bz11luNXv/3v/+tzABC/QTT7U5qfPjhh1RUVLBx40Y8PDz47W9/2+DadejQQfn4/PnzvPHGG2zatImePXuSk5PDwoULb+v4on2QpxXVTzJSN8lH/SQj9ZOM1E3yUT/JSP0ko+bJssm3qaioiKNHjyqfX7x4kdLSUnr06EHnzp0xm81KA9Jt27Y53UdFRQU+Pj74+/tjMplITU1tsH3EiBEkJydz3333ERISQnl5OQcPHlQmVGJjY0lLS+PixYtA/b+W5ObmAnDmzBlCQ0OZPn06s2bN4uTJkzdd48iRIzlw4ADfffed8tqJEyeuO+7ee+/lyy+/pLa2FpvNxtatW29oW2VlJUFBQXh4eFBUVMTu3bubPEZVVRXu7u4EBQVhs9nYsGHDTdcnhBBCCCGEEELcLLlD5TZZLBaSk5M5f/688vzY/PnzlUdgli5dylNPPUVgYCDjxo1zuo/Ro0ezdetWJkyYQEBAAMOGDWsw8RETE0NqaiojRowAYOjQoRw6dIjg4GAAhg8fzvz585k7dy5WqxWz2czEiROJiIhg7dq1ZGZm4u7ujl6v5+WXX77pGnv37s0f//hHli5dSl1dHWazmSFDhhAZGdnsuAceeICjR4/yyCOP0LFjR6Kiorhy5cp1t82cOZN58+YxZcoUgoODlYkjZ+666y4mTpzIpEmTCAgIYOzYsWRnZ990jaL9ubYJtFAfyUjdJB/1k4zUTzJSN8lH/SQj9ZOMmier/Ig7yvFcpM1mY+nSpXTp0kV55Ki5bWogq/yom6OHilAvyUjdJB/1k4zUTzJSN8lH/SQj9ZOMmid3qIg7avHixZw/f566ujoGDRrEnDlzbmhbW7NabHdk8sNmsaN107T4fv8vaq254Lq6OtLT0zl9+jQ2m42QkBCeeuop0tPT+fbbb6muriYsLIwnnnii0fl99NFHFBQUNNh+9OhRDh48SGlpKe7u7ixZskQZU1JSwueff8758+fx8fFh/PjxDBgwwOl5Xbp0ia1bt3LhwgX8/f2Ji4tTlitXC5mvVzfJR/0kI/WTjNRN8lE/yUj9JKPmyYSKuKPefffdW9rW1mpqq1u0+7ODTKa0HLPZ7LQTeEtLS0vj9OnTREdHExQUxLlz55RtgwYNIisry+m4nJwcfvrpp0avWywWwsPDOX78eKMGzhs3bqSsrIzx48dz7NgxUlNTmTdvntOvxdTUVK5cucJDDz1EdnY2GzduZP78+a1yTW5Ua2Ukbo3ko36SkfpJRuom+aifZKR+klHzpCmtEEI0oaysjLy8PCIiInjwwQeJiooiPj4egLi4uCb7+1RWVrJz507uv//+RtuGDx/OhAkTGqyOBVBbW0txcTE9e/Zk+PDh3HPPPQ0aTF/twoULFBUVERERwb333ktMTAxGo5F//etfLVC1EEIIIYQQ4kbIhIoQTnh7dbj+m0SbuhN3EF3NarVz6dIlAH766SeWL1/O8uXL2blz53XHpqen07dv3yYf13FGr9fj5uZGSUkJly9fVu6EKSsra/Te8vJyAPz8/Br86ey9bcnd3b2tT0E0Q/JRP8lI/SQjdZN81E8yUj/JqHnyyI8QTujctOxZd6mtT0O0odgZQcojOSaTiZ///OccOXKEjIwM+vXrR9++fZ2O++GHH/juu++YOXOmMvFhNpuprKxsdhJIp9PxwAMPsGPHDv7yl78od7C4uV3/x7Ran23VaOQRNzWTfNRPMlI/yUjdJB/1k4zUTzJqntyh0krS09OZOnUq8fHxTJw4kQULFlx3TGFhIdHR0a1wds6tXLmS7du3O912J+spLCzkk08+uenzFaKlBQQEANCrVy8GDBigLIdeWlra5JiKigosFgsffvghH330EQA//vgjW7Zsue7xRowYwfz580lKSmLChAkABAUFAWC1WpUJHn9/f+VYUP+I0dXnqxY6na6tT0E0Q/JRP8lI/SQjdZN81E8yUj/JqHlyh0orKC4uZtmyZWzZsoWQkBDsdjunTp1q69O6rnnz5jl9/U7Xc/78eT755BMee+yxFtunELeia9eudOnShR9++IFvvvmGY8eOodFoCA0NJT8/n+Li+qW1KyoqyMnJoVevXvTu3Ztp06YBUF1dzfbt2wkJCWHs2LFAff+TCxcuYDKZsNls5OTk0KlTJ3r16sWRI0fQaDRYLBYOHjyIr68vd999NwBr166loKCA//f//h8hISEEBweTm5tLUFAQ2dnZ6PV6ZcJHLWpra+/4o1ni1kk+6icZqZ9kpG6Sj/pJRuonGTVP7lBpBSUlJbi5uSn/qqzRaJRffK69a6O5uzgWLFhAQkICDz/8MP/1X//FlStXAHjxxRdJT08HICUlhaFDh2K1WgGYNGkSZ86cAWDLli1MmzaNhIQEZs2axQ8//ADUr0by6KOPEh8fz+TJk9m2bRsAL730Ev/85z9vqh6A48ePM3PmTBISEkhISOCrr766qXp+//vf8+9//5v4+Hief/55AN58800SExN55JFH+OUvf8n58+cbXK8VK1YwdepUJkyYQHZ2dtNhCHETNBoNiYmJBAYGkp6eTm1tLY8++ihdunQhIyOD3bt3A1BUVITBYODcuXP4+/szcOBABg4cSFhYGAA+Pj706tULgNOnT2MwGKitrcVqtWIwGDh69ChQ/xfW7t272bVrF507d2bGjBlNPvKTkJBA586d2bFjB1arlWnTpkkHdiGEEEIIIVqR3KHSCvr3709kZCTjxo0jOjqaIUOGEB8ff9O35y9dupTAwEAAVqxYQUpKCgsXLiQmJoZDhw4RFxfH4cOHCQsL4+TJk3Tr1o2amhr69OlDdnY26enprFu3Dr1ez759+1iyZAkbNmwgJSWFpKQkpkyZgt1uVx4fuJV6Kioq+N3vfsd7771Hly5dKC4u5uc//7kySXMj9fzP//wPb775Jps3b1beO2fOHBYvXgzULy379ttvs2LFCqC+QWdUVBQvvPACW7du5e2332bDhg03dW2FcKaqqorAwEBmz55NTU2N8rrVauXxxx/HZrMpj+E4ep6YzWbq6uqA+iZeS5YsQavVKt9XQ4cOZfTo0dhsNuUuFce46OhooqOjMZlMQH3/FKPRiJubG4mJicqxrVYrgYGBPPbYY0r/FC8vL4xGI3a7HbPZrBxfo9Gg0+mora0F6ieJPD090Wg0DWry9vbGYrE4rUmr1So1abVa9Ho9Wq220fhra7JYLBiNRoAGNWm1Wtzc3BqNt9vt1NXVNajJarWqqiZPT0/l4/ZeU3V1tcvV5Go5OY7jSjW5Wk4Wi4Xq6mqXqsmVcqqurna5mlwtJ8ffRa5Uk6vl5MjIlWpyjG+JO29kQqUVaLVaVq1aRX5+PkeOHGHXrl28//77GAyGm9pPWloaBoMBs9lMTU0NvXv3Bur7Lrz33nuYTCYuXrxIUlISGRkZdOvWTbnbZc+ePeTl5SmPItjtdqX/QnR0NKtXr+bs2bOMHDmSwYMH33I9x48fp7CwkDlz5ijv12g0FBQUNJpAaqoeZ/bv38/69eupqalRvlEcvL29leVpo6KiePPNN69/MYW4AT4+PsrH1/7Abe55Umfd0J2Nb6pruoeHx3XHX3t+8J8Gts7uVHE2/k7XZLFYlHNylZqu1t5r8vDwaHQHVHuvyZn2XFNgYKDTu9Tac02ulpOvr2+TdxK215pcKScvLy90Op1L1XT1eFeoycvLSzmuq9R07fj2XlPnzp0b/JxzhZpa8hEmmVBpReHh4YSHhzNjxgwmTZpEVlYWkZGRDVbocPxr7rWys7P5+OOP2bBhA4GBgRgMBj799FMAevbsic1m4/PPPycqKoqYmBgWLVpE9+7diYmJAeonUBITE532RZk9ezaxsbFkZGTw6quvMnLkSF544YVbqkev13PXXXexbt26Ru8vLCy8oXqudf78ed544w02bdpEz549ycnJYeHChcp2xwwk1E/2XDvhIoRoG9IVXt0kH/WTjNRPMlI3yUf9JCP1k4yaJz1UWkFRUZHSIwHg4sWLlJaW0qNHDzp37ozZbKagoADA6aMxUN/00sfHB39/f0wmE6mpqQ22jxgxguTkZO677z5CQkIoLy/n4MGDyoRKbGwsaWlpXLx4Eah/bCA3NxeAM2fOEBoayvTp05k1axYnT5685XruueceCgoKOHz4sLL9xIkTjZZ1ba4eHx8fqqqqlM+rqqpwd3cnKCgIm80mj/MI0U5cfTumUB/JR/0kI/WTjNRN8lE/yUj9JKPmyR0qrcBisZCcnMz58+eVZ8zmz5+vNHJdunQpTz31FIGBgYwbN87pPkaPHs3WrVuZMGECAQEBDBs2rMHER0xMDKmpqYwYMQKo79Nw6NAhgoODARg+fDjz589n7ty5WK1WzGYzEydOJCIigrVr15KZmYm7uzt6vZ6XX375tupZtWoVf/zjH1m+fDlms5mePXuyZs2aG67nrrvuok+fPkyZMoW+ffvyv//7v0ycOJFJkyYREBDA2LFjpfGsEEIIIYQQQog2pbFfe+uAEAKAPesutfUpiDYUOyOorU+h3ausrJRl9lRM8lE/yUj9JCN1k3zUTzJSP8moeTKhIoQTVosdnVvrPC+Ynp7Ot99+S3V1NWFhYTzxxBPU1tayefNmLly4gNFopGvXrsTFxdGtW7cmxwDXHffnP/9ZWZ4aIDg4mOeee87peeXl5bFjxw4qKiro0aPHLa1M1Z5ZrXZ0Onlm9HZYrdZmm4SJtiX5qJ9kpH6SkbpJPuonGamfZNQ86aEihBMWq6lVjzdo0KAGnxuNRiorKxk5ciQjR46ksLCQjRs3NjvmRsf16tWLxMREEhMTefDBB52eT1VVFZs2bcLDw4Px48dz4cIFPvvss9ussmU11cC5pchkyu2TBtHqJvmon2SkfpKRukk+6icZqZ9k1DzpoSKEE4611FtDXFwc5eXlZGVlKa/5+fnx7LPPKl218/PzuXDhAmazGXd3d6djbmQcgL+/P2FhYU6XNXM4efIkVquVUaNGMWjQIH766SdOnDhBaWkpgYGBLX0JbklrZiRujWSkbpKP+klG6icZqZvko36SkfpJRs2TCRUhnHB3b3qyoSU19ViJVvufm8fKy8spKSkhJCSkyTXfb2bc8ePHOX78ON7e3jzwwAMMGTKk0X7Ky8uB+gmaq/8sKytTzYSKzJarn2SkbpKP+klG6icZqZvko36SkfpJRs2TCRUhnHBz07JlU8kdP86jP+/c7PaqqirWr1+PTqdj6tSpN7zfpsYNGTKEzp07Y7FY2LVrF9u2baNPnz7X7Y0irZaEEEIIIYQQoiGZUBFCpSorK/noo4+orq5m5syZdOnS5bbHjRkzRvn4woULHD58mMuXLxMQEIDFYkGj0aDT6fD39wegoqJC2Segqqa0er2+rU9BXIdkpG6Sj/pJRuonGamb5KN+kpH6SUbNkwmVVpaens5f//pX7HY7RqORQYMG8c477zQ7prCwkMTERDIzM1vpLBtauXIlYWFhTJo0qcHr06ZNw2QyYTab+fHHHwkLCwNg4MCBvPHGG61ybsnJydTU1LB48eJWOd6dkJ+fT3FxMVA/gZGTk0P37t359NNPKS0t5b777qO0tJTS0lLCw8PR6/VOx/Tq1QtfX1/+/ve/Ox1XVlbGnj176NevH3a7nRMnTuDm5kZwcDAAr7/+OkFBQfz6178mIiKC3bt38/XXX1NVVUVeXh6hoaGqedxHCCGEEEIIIdqaTKi0ouLiYpYtW8aWLVsICQnBbrdz6tSptj6t65o3b57T1x2rxzgmfNLS0lrztFxGRkYGBQUFABQVFWEwGIiPj6e0tFTZ7jBv3jz0en2TY3r37t3kOG9vb2w2G1999RVms5mgoCBiY2Odrivv6+tLYmIiO3fuZOfOnXTv3p34+Pg7dg1uxdX9YoQ6SUbqJvmon2SkfpKRukk+6icZqZ9k1DyZUGlFJSUluLm5KY9TaDQaBg4cCDS+C6W5u1IWLFjAmTNnMJvNhIaGsnz5cjp27MiLL77I+PHjiYuLIyUlhTVr1pCVlYVOp2PSpEm8++679OnThy1btrB+/XqsVis+Pj688sor9O3bl5ycHF599VVsNhsWi4W5c+cyZcoUXnrpJSIiInjyySdvqM59+/axevVqTCYT7u7u/OY3vyEqKorMzEyWL1/O4MGDOXr0KBqNhhUrVtCvXz8AVqxYwfbt2/H39+fee+/l0KFDbN68mUuXLvHiiy9SXV2N0Whk7NixLFq0SDleUVERc+bM4dy5c4SGhrJy5Uq8vLxuK6vWNHv2bKevR0VF3fQYgN/97ndNbpsxY8YNjxswYAADBgxo8v1tra6u7rpNekXbkozUTfJRP8lI/SQjdZN81E8yUj/JqHkyodKK+vfvT2RkJOPGjSM6OpohQ4YQHx9/030pli5dqjx6sWLFClJSUli4cCExMTEcOnSIuLg4Dh8+TFhYGCdPnqRbt27U1NTQp08fsrOzSU9PZ926dej1evbt28eSJUvYsGEDKSkpJCUlMWXKFOx2u9I342acPXuWVatW8f777+Pj48N3333HnDlz+OqrrwD4/vvveeONN/j973/P6tWrWbVqFe+88w579uxh7969pKWl4enpyfPPP6/s08/PjzVr1tChQwfMZjNJSUns379f6QeSm5vLpk2b8PX1JSkpCYPBwC9+8YubPve2cvV19vb2xmKxKJNa8J/nFrVaLXV1dcrHer0erVZLTU1Ng/E2mw2TyaQscebp6al8bDKZAHBzc0Or1eLm5tZovN1up66uTmlE6+XlhdVqxW63YzabAXB3d1f6rdTW1gL1E4Senp5oNJpG+7wTNZlMJoxGo0vV5Go5mc1mjEajS9XkSjlVVVW5XE2ultPVr7lKTa6Wk9lsprq62qVqcqWcqqqqXK4mV8vJ8XeRK9Xkajk5MnKlmhzjnd2pf7NkQqUVabVaVq1aRX5+PkeOHGHXrl28//77GAyGm9pPWloaBoMBs9lMTU0NvXv3BmDEiBG89957mEwmLl68SFJSEhkZGXTr1o3o6GgA9uzZQ15eHtOmTQPqV29xNB6Njo5m9erVnD17lpEjRzJ48OCbrvHAgQOcPXu2wZ0QFouFkpL6FXP69Omj3JUTFRXF3r17AcjMzCQuLg5vb28Apk6dyqpVqwCwWq289dZbHD16FLvdTklJCXl5ecqEyqhRo5RlfSMjIzl79uxNn3dbuvYbWafTNfleZ7PDzsY3NYvs4dF4OWhnP0h8fHwafO7mVv+jwtPT84bGt0ZNnp6eeHh4uFRNDq5SU3V1tVKLq9R0NVeoqUOHDg22uUJN12rPNfn4+DTKCNp3Ta6Wk4eHh9OMHNtu5JzUVpMr5aTVatHpdC5V09XjXaEmrVarfA+5Sk3Xjm/vNfn5+TX4OecKNbXERIqDTKi0gfDwcMLDw5kxYwaTJk0iKyuLyMjIBkvTOv5V91rZ2dl8/PHHbNiwgcDAQAwGA5+L2Fq4AAAgAElEQVR++ikAPXv2xGaz8fnnnxMVFUVMTAyLFi2ie/fuxMTEAPUTKImJiU77osyePZvY2FgyMjJ49dVXGTlyJC+88MJN1zd69GjeeuutRq//+9//btAlWqvV3tC65h9++CEVFRVs3LgRDw8Pfvvb3za4Pld/4+p0uiavnXAt0nFc/SQjdZN81E8yUj/JSN0kH/WTjNRPMmqedJhpRUVFRRw9elT5/OLFi5SWltKjRw86d+6M2WxWGo1u27bN6T4qKirw8fHB398fk8lEampqg+0jRowgOTmZ++67j5CQEMrLyzl48KAyoRIbG0taWhoXL14E6u/+yM3NBeDMmTOEhoYyffp0Zs2axcmTJ2+6xpEjR3LgwAG+++475bUTJ05cd9y9997Ll19+SW1tLTabja1btyrbKisrCQoKwsPDg6KiInbv3n3T5yVcjzTIUj/JSN0kH/WTjNRPMlI3yUf9JCP1k4yaJ3eotCKLxUJycjLnz59XnjWbP3++8gjM0qVLeeqppwgMDGTcuHFO9zF69Gi2bt3KhAkTCAgIYNiwYQ0mPmJiYkhNTWXEiBEADB06lEOHDilL4w4fPpz58+czd+5crFYrZrOZiRMnEhERwdq1a8nMzMTd3R29Xs/LL7980zX27t2bP/7xjyxdupS6ujrMZjNDhgwhMjKy2XEPPPAAR48e5ZFHHqFjx45ERUVx5coVAGbOnMm8efOYMmUKwcHByuSQ+L+tpqamRW/XEy1PMlI3yUf9JCP1k4zUTfJRP8lI/SSj5mnsVz9nIkQbqqqqwsfHB5vNxtKlS+nSpcstPXLUUrZsKrnjx3j0552b3Z6ens63335LdXU1YWFhPPHEEwD8/e9/V+5mgvrHnl566SWgfuJu586d5ObmYjKZ6Ny5M7/85S/x9PTk008/5YcffsBisSgTd44JvcOHD3P48GGqqqrw9fVlxIgRSu+da+Xl5bFjxw4qKiro0aPHLTVXvl2VlZXyw13lJCN1k3zUTzJSP8lI3SQf9ZOM1E8yap7coSJUY/HixZw/f566ujoGDRrEnDlz2uxcLBbbdSc7WoLVaken0zT7nkGDBpGVldXo9c6dOzN27FigYSOm3bt3k5WVRVRUFKGhoRQWFiqdt4OCgvjZz36G2Wxmz549fPbZZ/Tv35+ysjK+/PJL/P39eeihhzh48CBffPEF/fv3p2PHjg2OW1VVxaZNmwgKCmL8+PHKfp566qnbvRxCCCGEEEII0W7IhIpQjXfffbetT0Gh0bTOjVvXm0yJi4ujvLzc6YRKhw4dCAsLa9CU12w2c+TIEXr27MnDDz+M3W7nnnvuUbbff//91NbWUllZiaenp7IMmeNGNT8/P/r27cuxY8eoqalROm5f7eTJk1itVkaNGsWgQYP46aefOHHiBKWlpcpy3q3BsSKUUC/JSN0kH/WTjNRPMlI3yUf9JCP1k4yaJxMqQjhhs9maXX5LDQoKCvjDH/6AXq9n5MiRjBkzhrKyMqxWK5WVlbzxxhvYbDYiIiKIj49XGkqtXLkSo9GITqcjISEBrVZL586deeCBB9i9ezfvvvsuGo2G+Ph4p0tBlpeXAyhLVTv+LCsra9UJlfaQ0f91kpG6ST7qJxmpn2SkbpKP+klG6icZNU9a9grhjKbtf2hYrE3fJTNgwAASEhKYNm0aHTt2ZO/evRQUFCjLUNfU1BAfH8/AgQM5ceIEx44dU8ZOnz6dRx55BA8PD/bu3YvFYqG6upqsrCy6du3KY489RnBwMNu3b6eiouK659lWbZhMJlObHFfcOMlI3SQf9ZOM1E8yUjfJR/0kI/WTjJond6gI4YS7m5b3Nhe36Tk8k9ClyW1XN4utrKzkiy++4NKlS0qD2S5duhAREYGnpye5ubmUlpYq7+/duze9e/emoKCA48ePU1xcTFlZGZWVlQwbNoz+/ftTXFzM3r17OXfuHIMGDcJisaDRaNDpdPj7+wMoky2VlZUArd6U1tEXRqiXZKRuko/6SUbqJxmpm+SjfpKR+klGzZM7VFQoPT2dqVOnEh8fz8SJE1mwYMF1xxQWFja5IktrWLlyJdu3b3e67a677qK6urrBa9HR0RQWFgL1K9Zcvnz5jp9je5Sfn09ubi5QP4GRk5PDxYsX+fvf/87hw4fJzs4mMzMTjUZD9+7d8fb2Jjw8nIsXL5KVlaX0XunVqxfFxcVs2rSJ7OxsMjIyOHXqFG5ubgQEBCiTISdOnCAnJ0dZirtTp04AvP766/z1r38FICIiAp1Ox9dff01mZiZ5eXmEhoa26uM+QgghhBBCCNHW5A4VlSkuLmbZsmVs2bKFkJAQ7HY7p06dauvTuq558+bd8th//OMf3Hfffcov7zfKYrE4bZrqSjIyMpTlkYuKijAYDEyePBlvb28OHjyI0WgkICCAqVOnEhISAsDkyZPZunUrO3bswMfHh4ceeoiwsDDKy8spLS0lPz8fjUZDUFAQ48aNw8vLCy8vLx566CGysrLYvn07vr6+xMXF0bVr10bn5OvrS2JiIjt37mTnzp10796d+Pj4Vr0uAJ6enq1+THFzJCN1k3zUTzJSP8lI3SQf9ZOM1E8yap5r/zbaDpWUlODm5qY8VqHRaJTHOAoLC0lMTCQzM9Pp51dbsGABZ86cwWw2ExoayvLly+nYsSMvvvgi48ePJy4ujpSUFNasWUNWVhY6nY5Jkybx7rvv0qdPH7Zs2cL69euxWq34+Pjwyiuv0LdvX3Jycnj11Vex2WxYLBbmzp3LlClTeOmll4iIiODJJ5+8qXpXr15NcXExzz//PB4eHrzzzjtcunSJP//5zxiNRqxWK8899xyTJ08GYObMmfTv35/jx4/TsWNHVq9ezbPPPktZWRlGo5HIyEiWLVuGXq+/nRhUY/bs2U5fHzZsWJNj/Pz8nObg7+/PM8880+S4mJgYYmJinG773e9+1+DzAQMGMGDAgCb31Rrk9kP1k4zUTfJRP8lI/SQjdZN81E8yUj/JqHkyoaIy/fv3JzIyknHjxhEdHc2QIUOIj4+/6f4US5cuVR7BWLFiBSkpKSxcuJCYmBgOHTpEXFwchw8fJiwsjJMnT9KtWzdqamro06cP2dnZpKens27dOvR6Pfv27WPJkiVs2LCBlJQUkpKSmDJlCna7Xemfcavmzp3Lxo0b+d///V/Cw8MBCAoKYv369eh0OkpKSkhISGDUqFF07NgRgHPnzrF+/Xrc3Nyw2+28/fbbBAQEYLfbWbx4MampqTz++OO3dV5qUVlZqUwOabVa6urqlI/1ej1arZaamhrl/d7e3thsNkwmk/LDz9PTU/nY0VTKzc0NrVaLm5tbo/F2u526ujql2ayXlxdWqxW73Y7ZbAbA3d1d6aniWHpZo9Hg6emJRqNptE+LxaJMwgEtUpPRaHS5mlwtJ43mP8uCu0pNrpRTbW0tJpPJpWpytZxqamqU83eVmlwtJ7PZrOzDVWpypZyMRiNubm4uVZOr5WQ0GjGZTC5Vk6vlVFlZqZyrq9TkGO/r68vtkgkVldFqtaxatYr8/HyOHDnCrl27eP/99zEYDDe1n7S0NAwGA2azmZqaGnr37g3AiBEjeO+99zCZTFy8eJGkpCQyMjLo1q2b0oNlz5495OXlMW3aNKB+FRdHA9Lo6GhWr17N2bNnGTlyJIMHD77lWq/+ZetqpaWlLFmyhIKCAnQ6HVeuXOHMmTNERUUB8PDDDyuP+thsNj744AP279+PzWbjypUrLnVb2rXf5O7u7td9j06nc/o+AA8Pj+uOB/Dx8WnwueN6O7u2zsY7O6em3GpNdXV1eHh4uFRNDq5SU2VlpVKLq9R0tfZek81ma7StvdfkTHuuyc3Nzemx2nNNrpaT3W5vdE4O7bUmV8tJp9O5XE2O8a5Sk+NPV6rp6vHtvSYPD49G31PtvaaWmEhxkAkVlQoPDyc8PJwZM2YwadIksrKyiIyMbLBEreNf6K+VnZ3Nxx9/zIYNGwgMDMRgMPDpp58C0LNnT2w2G59//jlRUVHExMSwaNEiunfvrjzuYbfbSUxMdNoXZfbs2cTGxpKRkcGrr77KyJEjeeGFF5qtJTAwkPLycjp06ADU9z6pqqpqsonpK6+8QmxsLH/5y1/QaDRMmDChQa3e3t7KxwaDgW+++YZ169bh4+PDmjVr+PHHH5s9HyGEEEIIIYQQ4nbJKj8qU1RUxNGjR5XPL168SGlpKT169KBz586YzWalSem2bduc7qOiogIfHx/8/f0xmUykpqY22D5ixAiSk5O57777CAkJoby8nIMHDyoTKrGxsaSlpXHx4kUArFarstLMmTNnCA0NZfr06cyaNUtZDaY59913H5988ony+SeffMLgwYPx8vICoEOHDg0eHaqsrKR79+5oNBq+/vprpV5nKisrCQgIwMfHh8rKyiaviXA9rt6Q2BVIRuom+aifZKR+kpG6ST7qJxmpn2TUPLk6KmOxWEhOTub8+fPK82jz589XGtMuXbqUp556isDAQMaNG+d0H6NHj2br1q1MmDCBgIAAhg0b1mDiIyYmhtTUVEaMGAHA0KFDOXToEMHBwQAMHz6c+fPnM3fuXKxWK2azmYkTJxIREcHatWvJzMzE3d0dvV7Pyy+/fN2ali5dyuuvv87DDz+MVqslJCSEt956S9k+a9YslixZgqenJ++88w4LFixg2bJlJCcnc/fdd3PXXXc1ue+pU6eye/duJk6cSKdOnRg6dGiTd+4I16LVynyw2klG6ib5qJ9kpH6SkbpJPuonGamfZNQ8jf3qZ0iEEIr3Nhe36fGfSejSpsdXO6vV2uzzkqLtSUbqJvmon2SkfpKRukk+6icZqZ9k1DyZUBHCCbPFhrvbnZ+NTU9P59tvv6W6upqwsDCeeOIJAA4cOEB2djYVFRUEBQXx61//GoDy8nJWrlzZaD/x8fFERUVx6dIltm7dyoULF/D39ycuLo5+/fpx+fJltm3bRlFREVarlR49ejB58uQm+9hkZ2ezf/9+amtr6devH4888kiD3jVqUFlZ2aINpUTLk4zUTfJRP8lI/SQjdZN81E8yUj/JqHly/44QTtTVVrfasQYNGtToNZvNRmRkZKPXvb29SUxMVP4LCgoCICQkBIDU1FRKSkp46KGH0Gq1bNy4kbq6OiorK7Hb7YwbN46oqCh++OGHJleOunDhAp9//jlBQUGMGzeO/Px8vvzyyxasWAghhBBCCCHaP5lQEaINxcXFKc2ArzZ27FgeeOCBRq/r9XoiIiKIiIigd+/eXL58mR49ehAcHMyFCxcoKioiIiKCe++9l5iYGIxGI//617/o2bMns2fP5t577yUuLg4vLy+Ki50/0nTs2DGgvjnxyJEj6dmzJ7m5ucq67kIIIYQQQgghZEJFCKc8vTvc8WOYrbf3tF1OTg42m41hw4YB9Y8DAfj5+TX4s6ysrMFzjz/99BO1tbX06tXL6X6d7cdms3HlypXbOt+WprZHkERjkpG6ST7qJxmpn2SkbpKP+klG6icZNU9W+RHCCXedlpe3nL+jx3jt0e63PNZut5OTk4OXl5fTR4Yc77lWSUkJH3/8sdJfpT2T9k/qJxmpm+SjfpKR+klG6ib5qJ9kpH6SUfPkDpU7KDY2lvz8fABqa2tJSkriN7/5DVartckxmZmZJCQkAFBUVMTMmTNb5Vwdxz548GCL7/fq6+CQkJBAZmYmAJs3b+bMmTMtflxX9v3333PlyhWioqKUteH9/f0BqKioAOobSAEEBAQAcOnSJf7+97+j0+mYNWuW0lzKbrdjsViUr8tr91NRUYFWq6Vjx46tVN2Nqaura+tTENchGamb5KN+kpH6SUbqJvmon2SkfpJR82RCpRVUVFTw1FNP0bdvX5YvX37Dy04FBwezdu3aO3x2/5GVlcXXX3/dasdz2LJlCz/++ONNj3OFnh75+fnk5uYC9V8nOTk5XL58mYKCAnJycoD6H2I5OTlcuHBBGffNN98AMHToUOW1kJAQgoODyc3NJSsri0OHDqHX6xk4cCBXrlzho48+oqamhmHDhnH+/HnluFeuXOH111/nk08+AWDw4MEA7Nmzh6+//ppz584RERGhTNyohcyWq59kpG6Sj/pJRuonGamb5KN+kpH6SUbNU9dvSC7o8uXLLFq0iNjYWJ5//nnl9QULFnDmzBnMZjOhoaEsX7680R0AhYWFJCYmKndy3HXXXcyfP59du3ZRXl7Oa6+9RkZGBgcOHMBisbBy5Ur69evHpUuXePHFF6mursZoNDJ27FgWLVoEQHJyMmfOnKGyspJz584RGhrKypUrOXv2LBs2bMBms5GRkcHkyZN5+umnefbZZykrK8NoNBIZGcmyZcvQ6/Vs3ryZbdu24efnx3fffYevry/JycnKqjM3KjU1ldzcXF577TX+/Oc/s3jxYjp16sSyZcuora3FaDTyi1/8gtmzZwPw0ksvodPpOHPmDNXV1aSlpd3QtVSrjIwMCgoKgPo7kgwGA/Hx8fz4448cP34cqL/TxGAwMHbsWEJCQqioqCA/P58+ffrQqVOnBvtLSEjAYDCwY8cOOnbsyLRp0/D09OTixYtUV9evXLR7927l/REREY3OqVu3bkyaNIkDBw5QUFBAWFgYEyZMuFOXQAghhBBCCCHaJY1dppzumNjYWKqrq3niiSeYN29eg22lpaUEBgYCsGLFCqxWKwsXLiQzM5M333yTzZs3O51Q+Z//+R9mzJhBeno6S5Ys4U9/+hP3338/KSkpnD59mrfffhuj0YjFYqFDhw6YzWaSkpL41a9+xZgxY0hOTsZgMLBp0yZ8fX1JSkpi4sSJ/OIXvyA5OZmamhoWL14M1M9GlpeXExAQgN1uZ/Hixdxzzz08/vjjbN68mTfeeIOtW7cSEhLCyy+/TKdOnXjhhRecXoc1a9YQHh6uvJaQkMDixYuJjo5m5syZPP3009x///0AVFVVodfr0ev1VFdXM23aNJKTk+nXrx8vvfQS+fn5/POf/1QaJDV1LW+XmnuoiPo7lNR214xoSDJSN8lH/SQj9ZOM1E3yUT/JSP0ko+bJlbnDxo4dy/bt25k+fTrBwcHK62lpaRgMBsxmMzU1NfTu3fuG9udoJOpoROqYhIiIiGDnzp0AWK1W3nrrLY4ePYrdbqekpIS8vDzGjBkDwKhRo5QVXCIjIzl79qzTY9lsNj744AP279+vrPLi6empbB8yZAghISFA/WMiGRkZN3pZANBoNE5fr6ur45VXXuH06dNoNBqKi4vJy8ujX79+AEycOLFBt+lbvZZqYLVaqampUT739vbGYrFgs9mUR5r0ej0AWq1WeYZRq9Wi1+vRarWNxttsNkwmEzabDQBPT0/lY5PJBICbmxtarRY3N7dG4+12O3V1dcrtfV5eXlitVux2O2azGQB3d3c0Gg06nY7a2lqgPk9PT080Gk2r1FRbW4uHh4dL1eRqOWk0Gtzd3V2qJlfKyfE95Eo1uVpOVVVVyv/EukpNrpZTXV0dGo3GpWpypZyMRiMBAQEuVZOr5WQ0GvHw8HCpmlwtp/Lycjw8PFyqJsd4R0/J2yETKnfYr371K/bu3cusWbP4xz/+QXBwMNnZ2Xz88cds2LCBwMBADAYDn3766Q3tz/HF7PiCcNBqtcoX0IcffkhFRQUbN27Ew8OD3/72txiNxkb7ANDpdA22Xc1gMPDNN9+wbt06fHx8WLNmTYNeJ9fup6lmu4GBgcpSvA7l5eWNHldx+NOf/kRQUBB/+MMfcHNz4+mnn25wjldPptzOtVQDnU7X6Bu5uR47jl9Or+ZsvLP3QcPMmhoP4OPj0+Dzq/+H/kbGt0ZNVqsVDw8Pl6rJwVVqqqurU2pxlZqu1t5r0ul0jc6hvdfkTHuuycvLy+nx23NNrpaTm5ub02ND+63JlXJy/KxzpZquHu8KNbm7uyvHc5Warh3f3mvy8fFpcCxXqKklJlIcpCltK3j22Wd59NFHmTVrFkVFRVRUVODj44O/vz8mk4nU1NQWPV5lZSVBQUF4eHhQVFTUoGdGc3x8fJSVYRz7CQgIUF7ftm3bLZ3PyJEj2bhxozLhsm/fPrRaLaGhoQB06NCh0XG7du2Km5sb+fn5ZGdnN7nvO30thXo5ZrCFeklG6ib5qJ9kpH6SkbpJPuonGamfZNQ8uUOllTz33HPY7XZmzZrFBx98QGhoKBMmTCAgIIBhw4Zx8uTJFjvWzJkzmTdvHlOmTCE4OJiYmJgbGvfggw/y2WefER8fz+TJk3n88cfZvXs3EydOpFOnTgwdOrTJu1ma89xzz/HWW28xdepUZfndv/zlL8ps4WOPPcYf/vAH3n//fRYvXszcuXNZtGgRmzZtok+fPgwfPrzJfY8ePZqtW7fesWsphBBCCCGEEEI4I01phWiCNKVVt7q6uiZvsxbqIBmpm+SjfpKR+klG6ib5qJ9kpH6SUfPkDhUhnDBbbHd8wsNsteOuc96YV1xfU02N1aKuro709HROnz6NzWYjJCSEp556isOHD3P48GGqqqrw9fVlxIgRREdHA5Cens63335LdXU1YWFhPPHEE8r+Pv30U3744QcsFguBgYGMGzeOgQMHNnssZ/Ly8tixYwcVFRX06NGD+Ph4AgIC7sg1UHtG/9dJPuonGamfZKRuko/6SUbqJxk1T3qoCOGEBtsdP4ZMptye5ppPqUFaWhonT57knnvuYeLEiQQGBnL58mW+/PJLNBoNDz30EFarlS+++IIrV64o4xwreF0rKCiIhx56iPHjx3PlyhU+++wzpaO6s2M5U1VVxaZNm/Dw8GD8+PFcuHCBzz77rOWL//+pPaP/6yQf9ZOM1E8yUjfJR/0kI/WTjJonEypCOOFYnkuol5ozKisrIy8vj4iICB588EGioqKIj49Xlofz8/Ojb9+++Pj4oNPplM7mcXFxTfY8uv/++xkwYAB9+vRpcNtlU8dy5uTJk1itVkaNGkV0dDT9+/fn7NmzlJaWtvAVqKfmjITk0x5IRuonGamb5KN+kpH6SUbNk0d+hHBC7+V9/TeJNtWSy521JJPVxqVLlwD46aefWL58ORqNhujoaMaPH88DDzzA7t27effdd9FoNMTHx9OhQ4cb2vfKlSsxGo3odDoSEhLQarXNHutajuXL/fz8GvxZVlbW5F0tQgghhBBCCOdkQkUIJzzcdDyWmt/WpyHaoU8Sw7FYLACYTCZ+/vOfc+TIETIyMujWrRtZWVl07dqVsWPHsm/fPrZv306fPn2UyY3mTJ8+nbKyMnbt2sXevXsJD2/6WP369aNv377N7u9O9ySXZ27VTfJRP8lI/SQjdZN81E8yUj/JqHnyyI8QQrQwR5PXXr16MWDAAKV5bFlZGZWVlQwYMID+/fszYMAATCYT586du6H99u7dm3vuuYewsDBKSkooLi5u8liOx3gsFgtWqxUAf39/ACoqKgCorKxscL4tTTrCq5vko36SkfpJRuom+aifZKR+klHz5A6VOyQ2NpY1a9YQHh5ObW0t//3f/02XLl147bXXmmzsk5mZyZtvvsnmzZspKipi4cKFrF27tlXONzMzE7PZzKhRo1psn//1X/9FYWEhUL+ySHh4OFqtls6dO/Pggw9iNBqZPXt2ix1PCLXo2rUrXbp04YcffuCbb77h2LFjaDQaQkNDAThx4gQ+Pj6cPHkSgE6dOgGQn59PcXExUD/pkZOTQ69evbBarezfv5/evXtjMpk4deoUbm5uBAQE4Onp2eyxXn/9dYKCgvj1r39NREQEu3fv5uuvv6aqqoq8vDxCQ0Pv2OM+8i8a6ib5qJ9kpH6SkbpJPuonGamfZNQ8mVC5wyoqKnjmmWe4++67WbJkyQ1/QQYHB7faZApAVlYWNTU1LTqh8u677yof33XXXWzYsOGGe0XcLovFojT6FKK1aTQaEhMTMRgMpKen07FjRx599FFCQ0N56KGHyMrKYvv27fj6+hIXF0fXrl0ByMjIoKCgAICioiIMBgPx8fH07t2b0tJS8vPz0Wg0BAUFMW7cOLy8vACcHqtLly6NzsvX15fExER27tzJzp076d69e5MNbFtCTU2NanvdCMmnPZCM1E8yUjfJR/0kI/WTjJonv3HeQZcvX2bRokXExsby/PPPK68vWLCAM2fOYDabCQ0NZfny5XTs2LHB2MLCQhITE8nMzATqJyTmz5/Prl27KC8v57XXXiMjI4MDBw5gsVhYuXIl/fr149KlS7z44otUV1djNBoZO3YsixYtAiA5OZkzZ85QWVnJuXPnCA0NZeXKlZw9e5YNGzZgs9nIyMhg8uTJPP300zz77LOUlZVhNBqJjIxk2bJl6PV6Nm/ezLZt2/Dz8+O7777D19eX5ORkgoKCbvjaJCcnU1NTw+LFi5X9+fr6cvr0aYKDg/ntb3/Lm2++ydmzZ4mIiODtt99Go9Ewc+ZMnn76ae6//36ABp/PnDmT/v37c/z4cTp27EhKSsrtRijELevSpQtJSUmNXo+JiWlyJZ/m7th65plnbvpYAL/73e8afD5gwAAGDBjQ5L6EEEIIIYQQN0YmVO6g+fPn88QTTzSYTAFYunSpcov9ihUrSElJYeHChdfdn5+fH6mpqaSnp/PrX/+aP/3pTyxYsICUlBRWr17N22+/jZ+fH2vWrKFDhw6YzWaSkpLYv38/Y8aMASA3N5dNmzbh6+tLUlISBoOBX/ziF0yfPl2Z4ID6ZpVvv/02AQEB2O12Fi9eTGpqKo8//jhQv/zq1q1bCQkJ4eWXX+af//wnL7zwwi1fq5MnT2IwGOjatSvPPvssCxYsYO3atXh7e/Poo49y6NAh7rvvvuvu59y5c6xfv17uThFtytGbRKvVotfr0Wq11NTUKNu9vb2x2WyYTCZsNhtQ/3yq42OTyQSAm5sbWq0WNze3RuPtdjt1dXVKY1kvLy+sVit2ux2z2Uzg0DAAACAASURBVAyAu7s7Go0GnU6nLHmn0Wjw9PREo9E02qfFYsFmsymNbvV6vVJHXV3dTddkNpsxGo0uVZMr5VRVVeVyNblaTle/5io1uVpOZrOZ6upql6rJlXKqqqpyuZpcLSfH30WuVJOr5eTIyJVqcoxviTtv5LfOO2js2LFs376d6dOnExwcrLyelpaGwWDAbDZTU1ND7969b2h/cXFxAAwaNAhAuUsjIiKCnTt3AmC1Wnnrrbc4evQodrudkpIS8vLylAmVUaNGKauJREZGcvbsWafHstlsfPDBB+zfvx+bzcaVK1caNCQaMmQIISEhAAwePJiMjIwbvSxODRkyRHnsYcCAAXTv3l05z/79+1NQUHBDEyoPP/ywTKaINufsh/O1r+l0Otzd3Z2O9/DwuKF9+vj4NPjc8bXvrHnYjZ5TU5yd6/Vqslqtyj5dpaartfeaPD09G+2rvdfkTHuuqXPnzk73055rcrWcOnbs2OQ+2mtNrpSTt7c3Op3OpWq6erwr1OTIyDHeFWq6dnx7r6lLly4NxrhCTS35CJOs8nMH/epXvyIhIYFZs2ZRVFQEQHZ2Nh9//DF/+9vfMBgMzJ8/X5nJux7HF6hjds1Bq9Uqs3EffvghFRUVbNy4EYPBoDR/vXYfUP+F51j941oGg4FvvvmGdevWYTAYeOKJJxqc543u50Zdu7+m9q/T6ZQZUKBBbVD/F6cQQh0cP5eEOkk+6icZqZ9kpG6Sj/pJRuonGTVPJlTusGeffZZHH31UmVSpqKjAx8cHf39/TCYTqampLXq8yspKgoKC8PDwoKioiN27d9/QOB8fH+UxBcd+AgIClNe3bdvWoud5q0JDQ5WVUb7//ntOnTrVxmckhGjK1ZOfQn0kH/WTjNRPMlI3yUf9JCP1k4yaJ89GtILnnnsOu93OrFmz+OCDDwgNDWXChAkEBAQwbNgwZYKgJcycOZN58+YxZcoUgoODm2x+ea0HH3yQzz77jPj4eCZPnszjjz/O7t27mThxIp06dWLo0KGN7gZpC3PmzGHevHns3r2bgQMHMnDgwLY+JSFEE+RfNNRN8lE/yUj9JCN1k3zUTzJSP8moeRq7oxuMEKKBx1Lz2/oURDv0SWJ4W5+CalRWVsoyeyom+aifZKR+kpG6ST7qJxmpn2TUPJlQEcIJk8WG3k2eiLvW3/72Ny5duoTNZiMoKIgJEyag1WrZsWMHly5dAqBv375MnjyZDh06AFBcXEx6ejqFhYW4u7tzzz33MH78eMxmMx9//DGFhYWYzWbGjx+vNB4+d+5cs/u81ldffcWRI0cwm80MHDiQKVOmtFlzYpPVhl4nXztQ3+PIWXMyoQ6Sj/pJRuonGamb5KN+kpH6SUbNk//rF8IJu9Xc1qegSj169GDixImMGTOGixcvsnXrVi5fvoy3tzcPPvggYWFhnDp1il27dgH1y+b+85//pKioiHHjxjFu3Dil07bdbsfLy4uf/exnjY7T3D4dHI+gnTp1in379tGnTx+io6M5fvw4Bw4cuMNXomkymSKEEEIIIcT/DdJDRQgntFr5pdiZCRMmUFtbS1lZGQcOHECj0XD33XcTFRUFwN13301ubi7FxcUA5ObmUllZycMPP8zdd9/dYNkyvV7PtGnTOHbsWKPmws3t08GR0fHjx4H6ZcU7dOjAiRMnOHbsmLKsuGg78n2kbpKP+klG6icZqZvko36SkfpJRs2TCRUhnLBp5AfHtUxWGzaziT/+8Y9A/TrxjzzySIN13//9738D0KtXLwDlkZ1Dhw5hMBjw9vZm0qRJDBo0qNljNbdPh7q6Otzd3SkrK0Or1SqPA/n5+VFYWIjVam12TXpx5zkyEuok+aifZKR+kpG6ST7qJxmpn2TUPJlQEcIJDzcdialH2vo0VCU1cTg2jZ4nn3ySkpISdu3axd69e/nlL38JwNmzZ0lLSyMkJIRx48YB/+kK7uvrS2xsLOnp6Xz22Wf87Gc/u6FnMZ3tUwghhBBCCCHUQP4Z/ibExsaSn1+/8kttbS1JSUn85je/wWq1NjkmMzOThIQEAIqKipg5c2arnKvj2AcPHmzx/R4+fJhp06YRHx9PXFwcs2bNuqH1ye+66y6qq6ubfU9FRQUpKSktdaqihWm1Wvr160d0dDTdu3fnxx9/pKamhoKCAtatW0dgYCBPPvkker0egICAAAAGDhzIgAED6NWrFxaLhcrKyuseq6l92u32Bsu3BQQEYLPZlK+tiooK/Pz85O4UFZBbRNVN8lE/yUj9JCN1k3zUTzJSP8moeXKHyi2oqKjgmWee4e6772bJkiVoNJobGhccHMzatWvv8Nn9R1ZWFjU1NYwaNarF9mmxWHj++ef5xz/+Qf/+/QH417/+dcPX4HoqKir429/+xpw5c1pkf6LlfP/993z77bf07NmTiooKzp07R4cOHSgvL///2LvzuCrL/P/jr3MOHPblYEhq4kK4kuKCZqOijOYuKdqYpTVpY9PiUv20aRnTcZypaDGnommysdFkTDTApSJ1pCRxwd1cJhXFDBdADtvZf38w5/6CHo+YoDenz/Px6CHc97nu+/qcN2BeXPd1sXz5chwOB927d+f48eN4e3vTvn17YmJi2LhxI3v27EGj0XD8+HGCgoIICwsDIC8vj9OnTwNw5swZ8vLyiImJ4eLFi1e9Zn5+PkuXLqVHjx6MHDmSrl27cuTIEb744gtCQ0MpLS2lX79+t/KtEv/jHAQT6iT5qJ9kpH6SkbpJPuonGamfZOSeDKhcp4sXLzJ79mwSEhKYPn26cvzZZ5/lxIkTWCwWIiMjWbhwISEhIbXaFhQUkJSURG5uLlA9Y2PmzJl8/fXXlJSUsGDBAnJycvjmm2+wWq0sWrSIqKgozp8/zzPPPEN5eTkmk4n4+Hhmz54NwOLFizlx4gRGo5HTp08TGRnJokWLOHXqFKmpqdjtdnJychgxYgSPPvoo06ZNo7i4GJPJRJcuXZg3bx56vZ7Vq1ezdu1agoODOXbsGEFBQSxevJjw8PBaNZSXl1NRUcFtt92mHOvUqZPy8fHjx1m4cCHFxcVYLBYefvhhkpKSrngfX331VbZv347FYsFgMLBw4UJatGjB/PnzMRqNJCYm4ufnR2pqKkuWLGHdunXYbDZ8fHx45ZVX6Nixo/Iezpo1i6ysLEpKSpg9ezZDhgy5wZSFK35+fpw5c4YDBw6g0+mIjIxk0KBBnDt3Doulelek9evXAxASEkL79u0JCgoiKSmJrKwsvvjiC26//XaGDx+ujHRnZmYq1z906BCHDh2ibdu2FBYWXvWaTs5BvI4dO9K/f3927NiB1WqlS5cuMqCiEvIbDXWTfNRPMlI/yUjdJB/1k4zUTzJyT+NwOBy3uhONRUJCAuXl5UycOJEZM2bUOldUVKT81v2tt97CZrPx3HPPkZuby6uvvsrq1atdDqj88Y9/5MEHH2TDhg288MILvPnmmwwcOJAPP/yQI0eOkJycjMlkwmq1EhAQgMViYcqUKUydOpX+/fuzePFiMjMzWbVqFUFBQUyZMoWhQ4dy//33s3jxYioqKpgzZw5Q/ahESUkJBoMBh8PBnDlz6NatGw888ACrV6/mL3/5CxkZGTRr1oyXXnqJJk2aMGvWrCveh/nz5/P555/Tq1cvunfvzqhRo2jWrBlWq5X777+f119/naioKMrKykhKSuK9994jKiqK9u3bk5eXR0BAQK3367PPPiMnJ4e33nrrivfo8vc2JyeHt99+m5UrVyrv4csvv8xDDz3Erl27mDlzZr1tmStrqNSWlhSnPKrj7e2NRqNBp9NRWVkJVA9w+Pr6otFoqKioUNr5+/tjtVqx2+3KozrOkW6tVktVVZXysV6vR6vVXtHebrdjNpuVR8t8fX0pLS0lMDAQs9kMgJeXF1qtFi8vryvaOxwOqqqqcP648/Pzw2az4XA4lIEbNdTk/NhTarJYLMpiwZ5Skyfl5Pwe8qSaPC2noqIi/P39PaomT8vp0qVL+Pj4eFRNnpRTWVkZTZs29aiaPC2nsrIyAgMDPaomT8vp3LlzBAYGelRNzvZBQUHcKJmhcp3i4+NZv349EyZMICIiQjmenp5OZmYmFouFiooKWrduXafrDRs2DEDZ9cS51WtMTAxZWVkA2Gw2XnvtNXbv3o3D4eDChQscPnyY/v37A9C3b1+Cg4MB6NKlC6dOnXJ5L7vdzpIlS8jOzsZut3Pp0iV8fX2V8927d6dZs2YAdO3alZycHJfX+eMf/8hvf/tbtm3bRnZ2Nh988AFpaWlYrVZ++OEHnnnmGeW1FouF48ePExUVVesa2dnZfPrpp1RUVNRaD8OVAwcO8MEHH3Dp0iU0Gg0nT56sdX748OEAxMbGcu7cOUwmU50WPBXXz9UPnbocc7eeiatVw121v/x1er0eHx8fl1m76pPzLwInL6/qH381vwfctb8ZNTl5Sk1Go1GpxVNqqqmx12S3268419hrcqUx1+Tv7+/yXo25Jk/LydvbWxk4vlxjrcnTctLpdB5Xk7O9p9Tk/NOTaqrZvrHXFBgYeMX3VGOvqT4GUpxkQOU6TZ06lc2bNzN58mQ++eQTIiIi2LlzJytWrCA1NZWwsDAyMzOVGRTX4vyic46YOWm1WmWg4eOPP6a0tJTPPvsMHx8fXn75ZUwm0xXXgOovpprnasrMzGTXrl0sX76cwMBAUlJSag1OXH4dd4vttmzZkpYtWzJ+/HjlPenbty8Gg4H09HS3NZ85c4a//OUvrFq1ipYtW5KXl8dzzz3n8rVms5kZM2awbNkyOnfuTGFhoTKQdHm/nd9IVqtVBlSEEEIIIYQQQjQoeSDqZ5g2bRpjxoxh8uTJFBYWKtOmQ0NDMZvNpKWl1ev9jEYj4eHh+Pj4UFhYyMaNG+vULjAwsNZuKkajEYPBoBxfu3btdfelvLycb7/9VpmiVVpaSkFBAXfccQdt2rTB19eXzz//XHn9Dz/8QFlZWa1rlJWV4e3tTXh4OHa7ndTU1Fp9rqqqUgaTzGYzVqtVmTnz6aefXnefhWdyToMX6iUZqZvko36SkfpJRuom+aifZKR+kpF7MkPlZ3r88cdxOBxMnjyZJUuWEBkZyZAhQzAYDPTs2ZP9+/fX270mTZrEjBkzGDlyJBEREfTp06dO7QYNGsTnn39OYmIiI0aM4IEHHmDjxo0MHTqUJk2a0KNHj6vOZrkah8PB8uXL+dOf/oSPjw82m41Ro0YxePBgAFJSUli4cCEfffQRdrudJk2a8Pbbb9e6Rvv27Rk6dCjDhw/HYDAQHx/Pzp07AQgNDWXUqFGMGjWKkJAQUlNTmT59OuPGjSM0NFQWnBUKu90uWyOrnGSkbpKP+klG6icZqZvko36SkfpJRu7JorRCXIUsSltbWlLcre5CLeXl5Vd9bl2og2SkbpKP+klG6icZqZvko36SkfpJRu7JDBUhXDBZbaobQLiaDRs2cPDgQcrLy4mOjmbixIkAHD16lK+//pri4mJuv/12Ro8eTXh4OHv27HG5zs2MGTMICQlh48aN7N27l8rKSkJDQxkwYAAxMTGYbXaOHzvKV199RWlpKXfccQeJiYkYDAaX/frPf/7Djh07sFgsdOrUiZEjRyoLTtUH52riQr0kI3WTfNRPMlI/yUjdJB/1k4zUTzJyT9ZQEcIFc2XFtV+kIs5dopycixgDDBkyhIsXL5KWlobD4aBVq1YkJSWRlJTEmDFj0Ol0BAQEEBQUxPHjx9m6dStBQUEMHjwYo9FIeno6NpsNc2UFq1atwsfHh8GDB3P27Nla6+XU9P3337NlyxbatGlD79692bt3b71tZy2EEEIIIYQQaiADKkK44GrLLrUaNmzYFevqnDlzBqvVSkxMDD179iQqKorCwkJ++uknDAYDMTExxMTE4OXlhc1mo1u3buh0OmWxYYPBQFRUFD4+Puj1ejQaDfv378dms9G3b1969+5Nhw4dOHXqFEVFRVf0ae/evUrffv3rXxMcHMyePXvqte7GlNEvlWSkbpKP+klG6icZqZvko36SkfpJRu7JgIoQLtg1jeNbw3yVra2dq3GfOXOG4uJifvrpJwCKi4trvW7Xrl1oNBp69OgBQFRUFHFxcRw6dIh3332XyspKkpKS0Gq1lJSUABAcHFzrz8uv6Tym1WqV5y2Dg4MpLS11uxX39ZLph+onGamb5KN+kpH6SUbqJvmon2SkfpKRe7KGihAu+HjpGJO2+VZ345rWJA10ebxVq1Z06tSJQ4cOcfToUfR6PUCtNUyKioo4fvw40dHRhIaGAnDx4kX27dtHVFQUPXr04Msvv+Tzzz/nqaeeuuIesp61EEIIIYQQ4pescfwaXoUSEhI4evQoAJWVlUyZMoU//OEPbn8Dn5uby9ixYwEoLCxk0qRJN6Wvznt/++239XrNJ598ksTERBITE2nfvj2jRo0iMTGRKVOm1Ot93Fm9ejXTp0+/afdrTMaPH88TTzzB7373O2WNlfDwcOX8rl27AOjZs6dy7MiRI5hMJrp06ULHjh1p27YtRqOR8+fPK4MupaWlABiNRqD68SCHw4HValVGsA0GA3a7nfLycqVNcHBwvW65Zjab6+1aomFIRuom+aifZKR+kpG6ST7qJxmpn2TknsxQuUGlpaX87ne/46677uKFF15Ao9HUqV1ERAT/+te/Grh3/2f79u1UVFTQt2/fervmu+++q3zcvn17UlNTZUutW+Do0aOcO3cOqP56zMvLo1WrVuzevZsmTZpQVFTE3r176dixo7Ijj81mY8+ePYSEhBAdHa1cy3l+586dWCwWjh49ik6nw2AwEBwczMaNG9m6dStlZWUcPnyYyMhIwsLCOHnyJEuXLiUuLo7hw4fTtWtXjhw5whdffEFoaCilpaX069fv5r85QgghhBBCCNFAZEDlBly8eJHZs2eTkJBQa5bEs88+y4kTJ7BYLERGRrJw4UJCQkJqtS0oKCApKYnc3FygekBi5syZfP3115SUlLBgwQJycnL45ptvsFqtLFq0iKioKM6fP88zzzxDeXk5JpOJ+Ph4Zs+eDcDixYs5ceIERqOR06dPExkZyaJFizh16hSpqanY7XZycnIYMWIEjz76KNOmTaO4uFiZkTBv3jz0ej2rV69m7dq1BAcHc+zYMYKCgli8eHGt2Q3u7N27l+TkZGV2wvTp0xkwYIBS84QJE9iyZQuVlZX8+c9/VmZILFu2jE8++YSgoCDi4+NZvnw5ubm5WK3Wq/YVoKysjJkzZ/6svnqCnJwc8vPzgeqZT5mZmSQmJnLu3Dm2b9+ORqOhc+fODBs2TGnz/fffU1FRwcCBA2sNAnbs2JF77rmH/fv3s2HDBgwGA8OGDVPWZElKSiIrK4usrCxatGhBYmKiyz517NiR/v37s2PHDqxWK126dKn3AZX63IJZNAzJSN0kH/WTjNRPMlI3yUf9JCP1k4zc0zhkIYSfJSEhgfLyciZOnMiMGTNqnSsqKiIsLAyAt956C5vNxnPPPUdubi6vvvoqq1evdjmg8sc//pEHH3yQDRs28MILL/Dmm28ycOBAPvzwQ44cOUJycjImkwmr1UpAQAAWi4UpU6YwdepU+vfvz+LFi8nMzGTVqlUEBQUxZcoUhg4dyv3338/ixYupqKhgzpw5QPX6FyUlJcrjGnPmzKFbt2488MADrF69mr/85S9kZGTQrFkzXnrpJZo0acKsWbOu+n60b9+evLw8bDYbkydP5u9//ztNmzbl3LlzjBs3jrVr11JaWsqvf/1rUlJSGDhwIBkZGXz66aekpqZy+PBhHnvsMdLT0wkLC2PBggVkZmaSm5tb732tq8a8hsovgclkwsfH51Z3Q7ghGamb5KN+kpH6SUbqJvmon2SkfpKRezLcdAPi4+NZv349EyZMICIiQjmenp5OZmYmFouFiooKWrduXafrOWcQONe7GDiw+h/LMTExZGVlAdWParz22mvs3r0bh8PBhQsXOHz4MP379wegb9++yu4rXbp04dSpUy7vZbfbWbJkCdnZ2djtdi5dulRrS6zu3bvTrFkzALp27UpOTk6dati9ezcFBQU89thjyjGNRkN+fj4GgwF/f3+lrtjYWF599VWg+pGk+Ph4ZSBq3LhxZGZmNmhfPYVzLROo3t3HbrdjNpuV9Ux8fX2Vj53PQHp5eaHVavHy8qKioqJWe4fDQVVVlbLorJ+fHzabDYfDgcViAcDb2xuNRoNOp6OyshKoztnX1xeNRnPFNZ3rq1itVgBldpFWq6Wqqkr5WK/Xo9Vqr2jvqiabzYbJZPKomjwtJ29vb0wmk0fV5Ek5WSwWzGazR9XkaTnV/BnnKTV5Wk4Oh4Py8nKPqsmTcrLZbHh5eXlUTZ6Wk81mw2w2e1RNnpZTZWWl0ldPqcnZPigoiBslAyo3YOrUqWzevJnJkyfzySefEBERwc6dO1mxYgWpqamEhYWRmZnJypUr63Q958ifM2wnrVarfHF8/PHHlJaW8tlnn+Hj48PLL7+s/IOl5jUAdDpdrXM1ZWZmsmvXLpYvX05gYCApKSmcPHnyqtep63a3DoeD9u3bs3z58ivOFRQUXLUudxqqr57i8h8EOp0Ob29vl691Nbrs6gdJYGBgrc+dU/1c7UPvqr2rPl2Nq77Wpaaqqir8/f09qiYnT6nJaDQqr/GUmmpq7DXVzMepsdfkSmOuqaqqyuW9GnNNnpZTRUXFVf+HvLHW5Ek5GY1GdDqdR9VUs70n1FTz7yJPqeny9o29Jp1OV+sanlBTfQykOMkuPzdo2rRpjBkzhsmTJ1NYWEhpaSmBgYGEhoZiNptJS0ur1/sZjUbCw8Px8fGhsLCQjRs31qldYGBgrZkMRqMRg8GgHF+7dm299K9bt27k5+ezbds25di+ffuuucVur169yM7OpqioCIA1a9Y0eF+FEEIIIYQQQoifS2ao1IPHH38ch8PB5MmTWbJkCZGRkQwZMgSDwUDPnj3Zv39/vd1r0qRJzJgxg5EjRxIREUGfPn3q1G7QoEF8/vnnJCYmMmLECB544AE2btzI0KFDadKkCT169LjqbJbrERISwnvvvcfrr7/OwoULsVgstGzZkpSUFLftOnTowNSpU5kwYQKBgYHcfffdysjhfffd1yB9FUIIIYQQQgghfi5ZlFaoRllZmTL9a/HixeTn55OcnHzL+iOL0qqbzWZzO71P3HqSkbpJPuonGamfZKRuko/6SUbqJxm5JzNUhGq88cYb5OXlKbNa5s+ff6u7dEPCin8i8szRK44fateLTke31zp2KagJJ1pVL0YcUnqB5j8dx9tiosIvmFN3tMOs98O3qpzWpw+hN1fh0Ggp9w+mtLSHsghxTXa7nQ0bNrB//340Gg3dunVj8ODBtbZIbuxkLFj9JCN1k3zUTzJSP8lI3SQf9ZOM1E8yck9mqAjhgslqxecG91wvLi7mzJkzQPUAR0ZGBr6+vsyaNYsFCxbQsWNHOnXqBEBwcDCRkZGUlZXx9ttvEx4eTmxsLJs2beL222/nt7/9LefPn+fgwYMYDAZOnjzJnj17iO3WjcTRo6+493fffcdXX31FXFwcVquV3bt3M3r0aLp163ZDNalJzRlNQp0kI3WTfNRPMlI/yUjdJB/1k4zUTzJyT2aoCOGCubISnxtc/dlgMGAwGAA4dOgQNpuNbt26KVPmwsPDadeuXa2dj/bv34/NZqNv37507tyZH3/8kX379lFUVER4eDj9+vWjqqoKm83Gnj170Gldryu9d+9e9Ho9Q4cOxW63s2/fPvbs2eNRAyoyFqx+kpG6ST7qJxmpn2SkbpKP+klG6icZuScDKkK4oPfzu6H2ZpsNfY1nDXft2oVGo6FHjx7KsezsbLKzswkJCWH48OG0a9eOkpISAOUxHuefxcXFhIWFcezYMf79738D1QMyAwYMcHn/4uJiAgMD0Wq1aLVa/Pz8KC4uvqGahBBCCCGEEEL8HxlQEcIFHy8vRq9a97PbZ4wboXxcVFTE8ePHiY6OJjQ0FIBf/epX3HHHHZSXl/PVV1+RlpbGc889d8V1Lh8RbtmyJQ8++CD//e9/yc3NZdeuXcTHx//sfjZmfjc46CUanmSkbpKP+klG6icZqZvko36SkfpJRu65fl5ACFFvdu3aBUDPnj2VY4MGDaJDhw706NGDqKgozGYzly5dUgZcSktLATAajQDKo0MBAQHceeed3HvvvWg0Gg4ePAhUr9FitVqx2+3K68vKypTjFRUVyjU8hc1mu9VdENcgGamb5KN+kpH6SUbqJvmon2SkfpKRezKg0oASEhI4erR6l5fKykqmTJnCH/7wB7dflLm5uYwdOxaAwsJCJk2adFP66rz3t99+W+/XnTRpEr/+9a9JTExk+PDhPP3008pAQX0pKChQHoVRE+daJyEhIURHRwNw7Ngx0tLS2LVrF99++y3Hjh3D398fg8FATEwMOp2OrVu3kpuby+HDh4mMjCQsLIxvvvmGr7/+mj179pCeno7D4SA8PByAffv28ec//5lt27YB0LVrV8xmM1988QUbNmzAbrfTtWvXW/Y+NAR5nlP9JCN1k3zUTzJSP8lI3SQf9ZOM1E8yck8GVG6C0tJSfvvb39K2bVsWLlxY5328IyIi+Ne//tXAvfs/27dvZ+vWrQ1y7Zdeeon09HTWrVuHTqdjxYoV19XearW6PX/mzBlVDqh8//33VFRU0L17d2XL4pCQEMrKysjKyuKbb76hefPmTJw4EZ1OR1BQEElJSVRVVZGVlcXtt99OYmIiUD075cCBA6xdu5YffviBmJgYhg8f7vK+vXr1okePHuzbt4+DBw9y9913e9SCtAAWi+VWd0Fcg2SkbpKP+klG6icZqZvko36SkfpJRu7JGioN7OLFi8yePZuEhASmT5+uHH/22Wc5ceIEFouFyMhIFi5cSEhISK22hhUjrQAAIABJREFUBQUFJCUlkZubC0D79u2ZOXMmX3/9NSUlJSxYsICcnBy++eYbrFYrixYtIioqivPnz/PMM89QXl6OyWQiPj6e2bNnA7B48WJOnDiB0Wjk9OnTREZGsmjRIk6dOkVqaip2u52cnBxGjBjBo48+yrRp0yguLsZkMtGlSxfmzZuHXq9n9erVrF27luDgYI4dO0ZQUBCLFy9WZkxcjdVqpaqqSqn1yJEjzJs3j8rKSkwmE/fffz+PPPIIAM8//zw6nY4TJ05QXl5Oenr6Vd+3+fPnU1BQQGJiIq1ateKdd96prwhvSExMDDExMbWONW3alIcffviqbTp27EjHjh2vON69e3e6d+/usk1sbCyxsbHK5zqdjpEjRzJy5Mif2XMhhBBCCCGEEO7IgEoDmzlzJhMnTqw1mALw4osvEhYWBsBbb73Fhx9+6HJR0ssFBweTlpbGhg0beOKJJ3jzzTd59tln+fDDD3n//fdJTk4mODiYlJQUAgICsFgsTJkyhezsbPr37w/AgQMHWLVqFUFBQUyZMoXMzEzuv/9+JkyYQEVFBXPmzAGqp3clJydjMBhwOBzMmTOHtLQ0HnjgAaB6i9+MjAyaNWvGSy+9xLJly5g1a5bLfi9YsIC3336bs2fP0qZNG8aMGQNAixYt+Oc//4ler6e8vJzx48fTr18/oqKigOoZHsuWLcPf39/t+/bHP/6RV199ldWrV19XPg3J+ViTt7c3Go0GnU5HZWUlABqNBl9fXzQaDRUVFUobf39/ZS0U56wc57bKWq2Wqqoq5WO9Xo9Wq72ivd1ux2w2K+up+Pr6Kh+bzWYAvLy80Gq1eHl5XdHe4XBQVVWlTO/z8/PDZrPhcDiUEWq11GQymTyuJk/KCcBkMnlUTZ6Uk/O1nlSTp+VksViUv0s8pSZPywmgvLzco2rypJyqqqo8riZPy8l53JNq8rScnMc8qSZn+6CgIG6UDKg0sPj4eNavX8+ECROIiIhQjqenp5OZmYnFYqGiooLWrVvX6XrDhg0DoHPnzgAMHDgQqJ4JkZWVBVSv2/Haa6+xe/duHA4HFy5c4PDhw8qASt++fZXteLt06cKpU6dc3stut7NkyRKys7Ox2+1cunQJX19f5Xz37t1p1qwZUL1mR05OzlX7/dJLLzFw4EBsNhtz587l9ddf58UXX6SqqopXXnmFI0eOoNFoOHfuHIcPH1YGVIYOHar8D8uNvG+3gqtv0Locc/dImLe3d53au3odgI+PT536FBgYWOtzL6/qHxU183fX/mbU5Ovri4+Pj0fV5OQpNZlMJqUWT6mppsZek5eX1xU1NPaaXGnMNQUEBLjsf2OuydNy0uv1LvsOjbcmT8pJr9ej0+k8qqaa7T2hpprfQ55S0+XtG3tNwcHBtfrqCTXVx0CKk6yh0sCmTp3K2LFjmTx5MoWFhQDs3LmTFStW8I9//IPMzExmzpypjOZdi/OL1DnC5qTVapURuY8//pjS0lI+++wzMjMzGTRokPJb4prXgOovvqstkpuZmcmuXbtYvnw5mZmZTJw4sVY/63qdmnQ6HYMHD1YGX958803Cw8NZs2YNGRkZdOnSpVZfaw6m3Mj7JjxPXdciEreOZKRuko/6SUbqJxmpm+SjfpKR+klG7smAyk0wbdo0xowZowyqlJaWEhgYSGhoKGazmbS0tHq9n9FoJDw8HB8fHwoLC9m4cWOd2gUGBtbafcdoNGIwGJTja9eurZf+5ebmKjNLjEYjt99+O15eXhw9epSdO3detZ279y0wMJCysrJ66Z9oHJzT/4R6SUbqJvmon2SkfpKRukk+6icZqZ9k5J488nOTPP744zgcDiZPnsySJUuIjIxkyJAhGAwGevbsyf79++vtXpMmTWLGjBmMHDmSiIgI+vTpU6d2gwYN4vPPPycxMZERI0bwwAMPsHHjRoYOHUqTJk3o0aNHrdkj18O5horVaqVZs2bMmzcPgN///vfMnj2bVatW0aZNG+Li4q56jX79+pGRkeHyfWvfvj1t2rRh5MiRtG3bVjWL0gohhBBCCCGE8Ewah2wsLYRLo1et+9ltM8aNqMeeCFfKysqueP5SqItkpG6Sj/pJRuonGamb5KN+kpH6SUbuyYCKEC6YrTb0Xj//eUGzzYb+Zz5vuGHDBg4ePEh5eTnR0dFMnDhROedwOFi6dCn5+fm1zv373//mzJkzVFZWEhYWxr333qss7Hv+/HkyMjI4e/YsoaGhDBs2TDl36tQp1q1bx8WLFwkPD2f06NHKQsOX27lzJ9nZ2VRWVhIVFcXo0aNrrXFzs1mtVmUBK6FOkpG6ST7qJxmpn2SkbpKP+klG6icZuSdrqAjhgk5zY+1/7mCKk3MXp8vl5eXx448/XnH8p59+Ii4ujoSEBIqKili5cqWyYG9aWhoXLlzg3nvvRavV8tlnn1FVVYXValVeN2TIEMrLy1m5cmWtLW+dzp49y7p16wgPD2fAgAEcPXqUL7/88oZqvFEazQ2GJBqcZKRuko/6SUbqJxmpm+SjfpKR+klG7smAihAu1Nzb/GYbNmyYy3VvjEYjWVlZylbZNT311FP069ePPn36EB0djdls5tKlS5w9e5bCwkJiYmLo1asXffr0wWQycejQIY4dO0Z5eTk9e/YkLi6Obt26UVJSwsmTJ6+4/p49ewBISEjgV7/6FS1btuTAgQPKzlK3wq3MSNSNZKRuko/6SUbqJxmpm+SjfpKR+klG7smAihAu6P38bsl9zW62nt6wYQNt27alY8eOV5xzbmdWVVVFQUEBgYGBhIWFUVJSAlTvH1/zz+LiYrfnLufqtXa7nUuXLl1/kUIIIYQQQgjhAeRhKCFc8PHyYtSq+t3Oui4yxyW5PH78+HGOHTvGpEmTlMENi8WC0WgkKCgIALPZTGpqKhUVFTz00EMu94x3t2SSLKckhBBCCCGEEHUnAyr/k5CQgL+/PxkZGWi1WuVYSkoK7dq1a7D7PvnkkxQUFABw+PBh2rVrh1ar5bbbbuOjjz5qsPs2tLS0ND755BOgev0NX19fDAYDAC+++CKLFy/mX//6163sYqNSWlqK1Wrl448/Vo6dPHmSNWvWMHnyZEwmE8uXL+fHH3/kN7/5Da1btwYgNDRUaQ/Vjw0BGAwG/P43C8fVOYfDgc1mQ6PRoNPpal0nKCiI0tJStFotISEhDV/8VdzKBXFF3UhG6ib5qJ9kpH6SkbpJPuonGamfZOSeDKjUUFFRQXp6OmPGjLlp93z33XeVj9u3b09qaioBAQE37f7Xy2azuZz5cLmkpCSSkqpnWzz//PPExMTw0EMPKecbejClrv1Uo6NHj3Lu3DmgegAjLy+PsLAwxo8fD0B5eTnr16+nWbNmxMfHA7Bs2TIKCgqIjY3FZDJx4MAB2rRpQ7NmzYiIiODAgQOEh4ezc+dO9Ho9nTp1wsvLi4CAAOXY7t27CQ0NpXXr1ly6dIlFixYpOwl17dqV7du3s2nTJtq2bcvp06e56667bumK31artdFm/EshGamb5KN+kpH6SUbqJvmon2SkfpKRe7KGSg1PPfUUf/vb35TdUWpKSEjg6NGjV3xut9t55ZVXGDp0KKNHj2bChAlA9RfelClTGDt2LCNGjOAPf/iDy+tezd69e5k0aRJjx45l7Nix/Oc//wGgoKCA3r1789Zbb3HfffcxZMgQdu7cqbRbtmwZ9957L0lJSbzzzjv07t37mufc9XX16tU88sgjPPnkk4wcOZKjR4+yZMkSkpKSuO+++/jNb37D999/X/c3uUYNTu3bt+f9998nKSmJX//613z33Xe88cYb3HfffYwcOZIffvhB6cv06dOVdjU/d9XPxionJ4eNGzcCUFhYSGZmJiUlJXTq1IlOnToRHR0NQGBgIK1atQJQZjnt2bOHtLQ00tLSOH/+PABjx47ltttu46uvvsJmszF+/Hh8fX3x8vJi/Pjx6PV6vvjiCwICAhg/frwyQ6um5s2bM3z4cM6fP8/mzZuJjo5myJAhN+PtuCpXuxEJdZGM1E3yUT/JSP0kI3WTfNRPMlI/ycg9maFSQ0xMDJ07d2bFihU8/PDDdWpz+PBhcnNzWb9+PVqtVlmkU6fTkZycrDw+MWfOHNLS0njggQeuec3S0lLmzp3L3//+d5o2bcq5c+cYN24ca9euBaoXCI2NjWXWrFlkZGSQnJxMamoqhw8f5oMPPiA9PZ2wsDAWLFhQq59XO3etvu7du5f09HQiIyMBiIiI4NFHHwWq//E/d+5cVq5cWaf362qCg4NJS0tjw4YNPPHEE7z55ps8++yzfPjhh7z//vskJydf8xqX97OxeuSRR9yeDw0NZe7cubWOXf55TU2bNmXKlCkuz7Vq1Yrf//73dbpHXFwccXFxbvt2M93KHYZE3UhG6ib5qJ9kpH6SkbpJPuonGamfZOSeDKhcZubMmUyePJlx48bV6fUtW7bEarXy4osv0rt3b2VLW7vdzpIlS8jOzlZ2Q/H19a3TNXfv3k1BQQGPPfaYckyj0ZCfn4/BYMDf31+5T2xsLK+++ioA27dvJz4+nrCwMADGjRtHZmbmNc9dq6/du3evNUhx4MABPvjgAy5duoRGo3G5ze71GjZsGACdO3cGUOqLiYkhKyurTte4vJ+Nlclkwm63Kz+89Ho9AFqtlqqqKuVjvV6PVquttZWZv78/drsds9msjCb7+voqHztnHnl5eaHVavHy8rqivcPhoKqqSlmk1s/PD5vNhsPhwGKxAODt7a2sr1JZWQlUf436+vqi0WiuuKbVaq33msxmMyaTyaNq8rScLBYLJpPJo2rypJzKyso8riZPy6nmMU+pydNyslgslJeXe1RNnpRTWVmZx9XkaTk5/y7ypJo8LSdnRp5Uk7O9c3OPGyEDKpdp27Yt8fHxtRb/hOpZHDWnOzn/kRAUFMS6devIzc0lJyeH5ORk1qxZw9atW9m1axfLly8nMDCQlJSUOg88OBwO2rdvz/Lly684V1BQoHyBQPUXxo2OGmZmZrrta801XcxmMzNmzGDZsmV07tyZwsJC+vfvf0P3B/Dx8QH+7wvdqWZ9V8vAVT8bM+d74Yq3t/cVxy7/QaDT6Vy+7mrXdvWDJDAwsNbnzrVSXA0Kumrvqk9X83NrCgwMxMfHx6NqcvKUmkwmk1KLp9RUU2OvycvL64oaGntNrjTmmkJDQ132vzHX5Gk5BQQEXPXv7cZakyflpNfr0el0HlVTzfaeUJNer1f66yk1Xd6+sdcUFhZWq6+eUFN9DKQ4uR1Qefnll/nTn/4EwP/7f/8PjUbj8nWvvfZavXVIDZ5++mnGjh2LzWZTjkVGRrJ//346dOjAd999x4ULFwAoKipCp9PRr18/7rnnHv7zn/9w+vRpjEYjBoOBwMBAjEYja9euJSYmpk7379atG/n5+Wzbto27774bgH379nHXXXe5bderVy/+8Y9/UFRURFhYGGvWrKnTuevpq9lsxmq10qxZMwA+/fTTOtVUH1q1asWRI0eUkc8vv/yS4ODgm3Z/IYQQQgghhBDCye2Ayh133KF87Fz88pfg9ttvJzExkSVLlijHZsyYwfPPP8+yZcu4++67ad68OVC9JfDLL7+M1WrFZrPRv39/YmNjiY6OZuPGjQwdOpQmTZrQo0ePK2ZUXE1ISAjvvfcer7/+OgsXLsRisdCyZUtSUlLctuvQoQNTp05lwoQJBAYGcvfddyujb+7O3XfffXXua2BgINOnT2fcuHGEhobe1IVJY2Nj6dOnDyNGjKBp06Z06NBBWXhV/PK4WjxXqItkpG6Sj/pJRuonGamb5KN+kpH6SUbuaRzOh5eERygrK1OmUC1evJj8/HxlQVd358SVRq1Ku+n3zByXdNPv2VgZjcZ6na4n6p9kpG6Sj/pJRuonGamb5KN+kpH6SUbu1XkNlW3bttGiRQtatmzJ+fPnSU5ORqvV8swzzxAeHt6QfRTX4Y033iAvL0+Z1TJ//vw6nRO1mazWBhvc2LBhAwcPHqS8vJzo6GgmTpwIwPnz5/nHRx/x09mzhIaGMmzYMKKiorh48SJr166lsLAQm83GHXfcwYgRI5QFhr/55ht27NhBVVUV7dq1Y9SoUfj4+GCxWFixYgUFBQVYLBYGDx7MPffcc9V+7dy5k+zsbCorK4mKimL06NH4+/s3yHsghBBCCCGEEI1dnefvzJs3T1ns5a9//StWqxWNRsPLL7/cYJ0T12/u3Lmkp6ezfv16PvjgAyIiIup0TtRmrePjWT+XczejmtLS0rh44QL33nsvWq2Wzz77jKqqKoxGIw6HgwEDBhAbG8vx48eVHZoOHTrEpk2baNGiBX379uXgwYNs3LgRqF7c2M/PjzvvvPOa/Tl79izr1q0jPDycAQMGcPToUb788sv6LbqeyfRD9ZOM1E3yUT/JSP0kI3WTfNRPMlI/yci9Os9QKSwspHnz5litVr799ls2bdqEt7c3/fr1a8j+CXFL1NxpqL4NGzaMkpIStm/frhw7e/YshYWF9OzZk169euHt7U1GRgaHDh2ia9euPPLII8pr9+/fz7lz5wDIz88HoE+fPkRGRrJjxw727t3L8OHD0ev1jB8/nj179vD999+77dOePXsASEhIoEWLFhw9epQDBw4watQoZdVttWnIjET9kIzUTfJRP8lI/SQjdZN81E8yUj/JyL06DzcFBgZy4cIFduzYQVRUlLJF7Y1u2SuEGjm0rne0ulHmGjtH1VRSUgKg7Frk/LO4uLjWNmA//vgjlZWVyiLRzkdyTp48yZkzZ6ioqMBsNtfam70uXN3fbrdz6dKl67rOzSSj5eonGamb5KN+kpH6SUbqJvmon2SkfpKRe3X+1fNDDz3EuHHjsFgsvPDCCwDk5eXRtm3bBuucELeKXufFyFXL6/26a8c9WKfXuVor+sKFC6xYsUJZXwUgLi6OAwcOsHnzZjZv3oxer8dsNqt2Vkl9qqiokAWyVE4yUjfJR/0kI/WTjNRN8lE/yUj9JCP36vyvrt/97ncMHjwYnU5HZGQkABERESxYsKDBOifEL0VoaCgApaWlQPVq2gAGgwGoXrB26dKleHl5MXnyZOWHmr+/P48//jiFhYX4+PiwYsUKrFbrNafmORwObDYbGo0GnU5X6/5BQUGUlpai1WoJCQlpkHqFEEIIIYQQorG7rl9jt2nTBgC73Q6gPHbgSRISEvD39ycjI0OZ3pSQkEBKSgrt2rVrsPs++eSTFBQUAHD48GHatWuHVqvltttu46OPPmqw+94Mq1evZuHChbRo0QKonjY2e/Zs+vTpU6/3+ec//8moUaNo0qRJvV63vh09elRZA6W0tJS8vDxatWpFREQEBw4cIDw8nJ07d6LX6+nUqROXLl1i6dKlVFRUkJCQwJkzZzhz5gwxMTEYjUZyc3O57bbb+O9//8vFixcZOnSocq+8vDxOnz4NwJkzZ8jLyyMmJoaKigoWLVqk7DLUtWtXtm/fzqZNm2jbti2nT5/mrrvu+kXMdBFCCCGEEEKIn6PO/1o6ePAg8+fP58iRI5j+twOKw+FAo9Fcc8HLxqaiooL09HTGjBlz0+757rvvKh+3b9+e1NRUZZ0aNbLZbLXW9riWe+65h3feeQeALVu2MH/+fDZs2FCv9/zkk0+45557VD+gkpOToywmW1hYSGZmJomJiYwdO5bMzEy++uorQkJCGD9+PL6+vvz000+Ul5cDKDv4AMTExKDRaDhy5Ajbtm3Dz8+P+Ph4evXqpbzGuRsQVO8IdOjQIZeP6TVv3pzhw4fzzTffkJ+fT3R0NEOGDGmot6BeyJbO6icZqZvko36SkfpJRuom+aifZKR+kpF7dR5Qef755xk4cCALFy7E19e3Ift0yz311FP87W9/Y8SIEVc8OnH5bBXn53feeSfz589n27Zt6PV6/P39SU1NxWq1Mm3aNIqLizGZTHTp0oV58+bVebXkvXv3kpycrPyDevr06QwYMICCggKSkpKYMGECW7ZsobKykj//+c/07NkTgGXLlvHJJ58QFBREfHw8y5cvJzc31+05d31dvXo1GRkZBAQEkJ+fz+uvv853333HunXrsNls+Pj48Morr9CxY8dr1mQ0Gms9SvLss89y4sQJLBYLkZGRLFy4kJCQEHJzc1mwYAExMTEcOnSImTNnUlZWxieffILFYgFgzpw59OnTh/fff59z584xffp0fHx8eOONN+q0XfCtUHPHnstNmTLlimOtW7dm7ty5Ll8fGBjIk08+edXrXa2dq3NxcXHExcVd9fVqY7fbr2tQT9x8kpG6ST7qJxmpn2SkbpKP+klG6icZuVfnAZUzZ84wa9YsNJqG2f1ETWJiYujcuTMrVqzg4YcfrlObw4cPk5uby/r169FqtcruKDqdjuTkZAwGAw6Hgzlz5pCWlsYDDzxwzWuWlpYyd+5c/v73v9O0aVPOnTvHuHHjWLt2LVC9M0tsbCyzZs0iIyOD5ORkUlNTOXz4MB988AHp6emEhYXVWufG3blr9XXv3r2kp6fXWkPn0UcfBapnXcydO5eVK1e6rCUnJ4fExEQqKiooKirigw8+UM69+OKLhIWFAfDWW2/x4Ycf8txzzwHw3//+l/nz59OtWzegetebkSNHotFoOH78OI888gjZ2dn8/ve/57PPPuOdd95p0Eez6oPRaESj0eDr64tGo6m1I4+/vz9WqxW73a7soOUcfNNqtVRVVSkf6/V6tFrtFe3tdjtms1l5NM/X11f52Gw2A+Dl5YVWq8XLy+uK9g6Hg6qqKmVhXD8/P2w2Gw6HQxnI8vb2VtZfqaysBLjpNZWVleHv7+9RNXlaTjabDT8/P4+qyZNycn4PeVJNnpZTSUmJ8kssT6nJ03IqLy/H29vbo2rypJwqKiq47bbbPKomT8upoqICf39/j6rJ03IqKipSZql4Sk3O9vWx2G6dB1QGDx7Mt99+S79+/W74po3BzJkzmTx5MuPGjavT61u2bInVauXFF1+kd+/eDBw4EKge0VuyZAnZ2dnKNrR1neGze/duCgoKeOyxx5RjGo2G/Px8DAYD/v7+yn1iY2N59dVXAdi+fTvx8fHKIMW4ceOURz/cnbtWX7t3764MpgAcOHCADz74gEuXLqHRaDh58uRVa6n5yE9ubi7PPPMMX375JX5+fqSnp5OZmYnFYqGiooLWrVsr7Vq1aqUMpgCcPn2aZ599lsLCQry8vLhw4QLnz58nPDy8Tu+pGlz+jXv55+5GgL29va95PZ1O5/J1AD4+PtdsD9UzX2pyrqXi6mvXVfubUZOXlxc+Pj4eVZOTp9RkNBqVWjylppoae012u/2Kc429Jlcac02+vr4u79WYa/LEnK72iHZjrsmTctLpdB5Xk7O9p9Tk/NOTaqrZvrHX5O/vf8X3VGOvqT53LarzgIrJZOKpp56iR48e3HbbbbXOvfbaa/XWIbVo27Yt8fHxfPzxx7WO63Q6ZQQOUNaTCQoKYt26deTm5pKTk0NycjJr1qxh69at7Nq1i+XLlxMYGEhKSorbgYeaHA4H7du3Z/nyK7fvLSgoqPXYkFarVUbkfq7MzEy3fa35Pwxms5kZM2awbNkyOnfuTGFhIf3796/TfXr37o3VauXYsWOYzWZWrFhBamoqYWFhZGZm1prlcvkze8888wzPP/88gwYNwm6307VrVyUDIYQQQgghhBDiZtHW9YV33nknjz32mDJLoeZ/nurpp5/m008/VdYvAYiMjGT//v0AfPfdd1y4cAGAoqIiKisr6devH8899xxBQUGcPn0ao9GIwWAgMDAQo9GoPK5TF926dSM/P59t27Ypx/bt26dMj7qaXr16kZ2dTVFREQBr1qyp07nr6avZbMZqtdKsWTMAPv300zrXdeTIEcrLy7njjjsoLS0lMDCQ0NBQzGYzaWlpbtsajUbuuOMOANLS0pRpZVA94OPcblh4Pk9fy8kTSEbqJvmon2SkfpKRukk+6icZqZ9k5F6dZ6g89dRTDdkPVbr99ttJTExkyZIlyrEZM2bw/PPPs2zZMu6++26aN28OwNmzZ3n55ZexWq3YbDb69+9PbGws0dHRbNy4kaFDh9KkSRN69OhR5xkVISEhvPfee7z++ussXLgQi8VCy5YtSUlJcduuQ4cOTJ06lQkTJhAYGMjdd9+tTGtyd+6+++6rc18DAwOZPn0648aNIzQ09Jo7wjjXUHE4HDgcDv7yl78QFhZGv379yMjIYMiQIRgMBnr27KkMWLnyhz/8gSeeeIKQkBD69etHaGiocm7y5Mm88MIL+Pr6qnpRWlE/as4UE+okGamb5KN+kpH6SUbqJvmon2SkfpKRexqHm+kOO3bsUHb9+O677656kT59+tR/z8QNKSsrU55NW7x4Mfn5+SQnJ1/znPg/I1dd+ajVjVo77sF6v+YvlclkcvmcplAPyUjdJB/1k4zUTzJSN8lH/SQj9ZOM3HM7oDJy5EjlsY+EhATXF9Bo2LhxY8P0Tvxs8+bNIy8vT5nVMn/+fCIiIq55TlQzWS34eLlebOlGmG029LLt2DVZrVZSUlK4ePEicXFxDB8+HKheV2jp0qXk5+fTpk0bJk+eDMC///1vzpw5Q2VlJWFhYdx7771ERUUBsHLlSo4fP47VaiUsLIwBAwbQqVMnAKqqqtiwYQNHjhzBbrfTrFkzfvvb37rs0+HDh/nqq68oLS3ljjvuIDExEYPBcBPejcbLaDTW66Jfon5JPuonGamfZKRuko/6SUbqJxm55/aRn5praGzatKnBOyPqz9y5c3/WOVHNXFmFT1D9D6jIYErdbNmyhdLS0iuO5+Xl8eOPP15x/KeffiIuLg4vLy82bdrEypUrefbZZ9Hr9YSHh3PnnXdisVjYtGkTn3/+OR06dECr1ZKens6RI0fo3bs34eHhnD592mV/ysrKWLVqFeHh4Qxr0c9/AAAgAElEQVQePFi5ztUGX4QQQgghhBCer86L0v7zn/9UFmAVwtM5t+4SN19hYSHbtm1jwIABtY4bjUaysrKUrcI1Go1y7qmnnqJfv3706dOH6OhozGYzly5dAmDgwIF07NiRNm3a1FpUq7i4mMOHDxMTE8OgQYOIjY0lMTHRZZ/279+PzWajb9++9O7dmw4dOnDq1CllcWfhmnwfqZvko36SkfpJRuom+aifZKR+kpF7dX53tm/fzltvvUW3bt0YNWoUQ4YMuWL/aCE8hfYqe6uLhmO2WfHW6sjIyCAuLk5Z8Nlpw4YNtG3blo4dO/LVV1/VGlBx7j1fVVVFQUEBgYGBhIWFKecXLVqEyWRCp9MxduxYtFot58+fB+DHH39k4cKFaDQaevfuzeDBg6/oW0lJCQDBwcG1/iwuLq51H1GbVlvnMXtxC0g+6icZqZ9kpG6Sj/pJRuonGblX5wGV9957j9LSUr788kvS09P505/+RL9+/Rg1ahT33ntvQ/ZRiJvOx8uLkWkf3epu/KKsTZpCXl4eJSUljB49msLCQqB6IawDBw5w7NgxJk2apAxuWK3WWs90ms1mUlNTqaio4KGHHlIGWQAmTJhAcXExX3/9NZs3b6Zdu3ZYrVal3bhx49ixYwc5OTlERUXRtm1bt3291tblopr8RkPdJB/1k4zUTzJSN8lH/SQj9ZOM3Luu4abg4GDGjx/PJ598wvr16ykvL2fGjBkN1TfxC5OQkMDQoUNJTExk6NChvPTSS1gsFrdtJk2axObNm4HqWQjr16+/GV0VDaS0tJSKigpSUlJYs2YNAPv27WP16tVYrVY+/vhjli5dCkB+fr7yGpPJxLJlyygoKOA3v/kNrVu3rnXd1q1b061bN6Kjo7lw4QLnzp1TFpRt1aoVHTt2VBaqdT7G49wCHVC253au62I0GgFkUdprqKiouNVdEG5IPuonGamfZKRuko/6SUbqJxm5d93DTTt37mTdunV8+eWXhIaG8vTTTzdEv8Qv1DvvvEO7du2w2Ww8+OCDZGVlKTu8XIsM7jV+nTt3pmnTpgCcO3eOLVu2cOedd/KrX/1K+WFeXl7O+vXriYiIID4+HkAZTImNjVVmtLRp04by8nKys7Np3bo1ZrOZ77//Hi8vLwwGA76+vjRt2pTjx4+za9cu9uzZg0ajITIyEoA///nPhIeH88QTTxATE8PGjRvZunUrZWVlHD58mMjISHncRwghhBBCiF+wOg+ovPrqq3zxxRdoNBqGDRvGRx99RMeOHRuyb+IXzGQyYTKZCA4O5rvvvuPtt9/GZDJhs9l4/PHHGTFixBVtnn/+eWJiYnjooYduQY9FfQgPDyc8PBwAf39/tmzZgsFgqDXjxPnIj7+/P61atQKgoKAAgD179rBnzx4AHn74YUJDQykqKuLo0aNoNBrCw8MZMGAAfn5+ACQlJZGZmcmGDRsICQlhzJgxyoBOTUFBQSQlJZGVlUVWVhYtWrS46gK2QgghhBBCiF8GjaOOiwG88sorjBw5kp49ezZ0n8QvVEJCAnq9Hh8fH06dOkXfvn1ZvHgxly5dIjAwEJ1Ox4ULFxg7diyZmZmEhIQwadIkHn30UQYOHFjvAyqyhsrNtTZpChaLBa1WW2tqob+/P3a7HbPZjN1uB8DX1xeLxYJOp8NsNgPVz3dqtVq8vLyuaO9wOKiqqlLWPvHz88Nms+FwOJTHyry9vdFoNOh0OiorK4HqnYR8fX3RaDRXXNNqtWK325W1WPR6PVC9cFdVVZXysV6vr3NNzo89pSbn/T2pJk/Kyfk95Ek1eVpOlZWVyveQp9TkaTlZLBZsNptH1eRJOdlsNoKCgjyqJk/LyWazodPpPKomT8vJaDQqaxN6Sk3O9s61GG9EnQdUnH788UcKCwuJiIi4YhcOIW5EQkICKSkptGvXDpPJxNNPP80999xDfHw8ycnJ5Ofno9PpOHnyJEuXLiU2NlYGVDzI2qQp1/V6q9Uqi2SpnGSkbpKP+klG6icZqZvko36SkfpJRu7V+Z05f/48s2bNYs+ePYSGhlJSUkLXrl158803iYiIaMg+il8gHx8fBgwYwH/+8x82b95MQkICf/vb39BoNAwZMgSTyXSruyhusaqqKtm6XeUkI3WTfNRPMlI/yUjdJB/1k4zUTzJyr867/MydO5cOHTqwfft2vv32W7Zv307Hjh2ZO3duQ/ZP/ELZ7XZ27NhB69atMRqNtGjRAo1Gw9atW8nPz7/V3RMqIFsXq59kpG6Sj/pJRuonGamb5KN+kpH6SUbu1XmGyq5du1i0aBHe3t5A9bNKs2fPpl+/fg3WOfHLM336dHx8fLBYLERHR/Pkk09y4MAB5s2bx+LFi7nrrrto3779re6mEEIIIYQQQohfuDoPqISEhPDDDz/QoUMH5djx48cJDg5ukI6JX55Nmza5PP6rX/2Kr776yuW5f/3rX8rHf/3rXxukX0KdnDv1CPWSjNRN8lE/yUj9JCN1k3zUTzJSP8nIvToPqEydOpVHHnmEcePG0bx5c3788UdWr17NjBkzGrJ/QtwSJqv1uhdJFTfGbLOi17n/kWS1WklJSeHixYt0796du+66i6VLl17xuocffpjWrVuzYcMGDh48SHl5OdHR0UycOFF5zfnz58nIyODs2bOEhoYybNgwoqKiANy2u9ypU6dYt24dFy9eJDw8nNGjR9OsWbOf+S54FpvNJouYqZjko36SkfpJRuom+aifZKR+kpF7dV5D5f777+ett96iuLiYzZs3U1xczBtvvMFvfvObhuyfELeE439bbomb51qDKQBbtmyhtLRU+Tw8PJykpCTlv4CAAHQ6HeHh4cprOnfu7PJaaWlpXLhwgXvvvRetVstnn32mbKvmrl1NVquVlStXYjabGTJkCOXl5axcuVLZOu6XTp65VTfJR/0kI/WTjNRN8lE/yUj9JCP36jTUZLPZGDJkCOvXr6dPnz4N3SchbjmLxYKvr++t7oaoobCwkG3btjFw4ECysrKw2WwEBAQQExMDVG/pXl5eTkxMDAEBAQAMGzaMkpIStm/fXutaZ8+epbCwkJ49e9KrVy+8vb3JyMjg0KFDdO/e/artLnfs2DHKy8sZNGgQcXFxlJWVkZ2dzcmTJ2nbtm3DvBGNiHwfqZvko36SkfpJRuom+aifZKR+kpF7dZqhotPp0Ol0slWt+MXQ+8kPDbUw26w4HA4yMjKIi4ujefPmLl+3c+dOAHr27HnNa5aUlAAoa0A5/ywuLr6uvtXXdYQQQgghhBCNT50fhpo8eTIzZ85k2rRp3H777Wg0GuVcy5YtG6RzQtwqPl7ejFj97q3uhgDWjX2SvLw8SkpKGD16NIWFhUD14zbl5eUEBARgMpk4cOAA4eHhtGrV6rrvUV9TGWVKZG3OXeGEOkk+6icZqZ9kpG6Sj/pJRuonGblX5wGVP/3pTwBs3bq11nGNRsP3339fv70SjUZCQgJ6vR4fHx9MJhM9e/Zk7ty5P/sbb/Xq1XTr1o02bdrUc09FY1ZaWkpFRQUpKSnKsYMHD6LX6xk9ejT79u3DYrHUaXYKQGhoqHJdAKPRCIDBYLhmW+v/1tfx8vK6oev8EtQceBfqI/mon2SkfpKRukk+6icZqZ9k5N41B1QqKyt5//33GTBgAJ06dWLatGn4+PjcjL6JRuKdd96hXbt22Gw2HnzwQbKyshg+fPjPutaaNWswGAwyoCJq6dy5M02bNgXg3LlzbNmyhbZt2yoDKLt27cLb25suXbrUanf06FHOnTsHVA965OXl0apVK5o1a0ZERIQyq2Xnzp3o9Xo6derktl2TJk3429/+RkVFBS+88ALR0dEEBAQo7Xfv3k1oaCitW/9/9u48rso6////4yycw6aACO6ooJC44AKJ5koqLrlH20edRquppqysrzbO9FGb0mxzEmfGMsul1NxScSszRXMNUJHMJRXNDQRB9rP//uDH9ZE4oiXKxeF1v926Cec613W939cT6Jz3eV+vd4t7dGXUTafTVXcTRCUkH/WTjNRPMlI3yUf9JCP1k4wqd8saKm+++SY7duwgODiYb7/9lnffffdetEvUQCaTCZPJRN26ddm3bx+PPvooI0aMYOjQoWzatEl53tixY5k9ezaPP/44Dz74IO+//z5QuupKWloab731FsOHD2fv3r0AfPLJJzz88MOMHDmSZ599lqtXrwIQHx/PpEmTePrppxk4cCDPPPMMxcXF977j4q4LCAggPDyc8PBwZbCiTp06NG7cmAsXLpCRkUG7du0qFMzau3cv27dvB0qL2iYkJPDrr78CMGrUKOrXr8+3336LzWYjLi5O2b+y/W6k1+uJi4vDYDCwdetWvLy8iIuLQ6u97QXUXJr8Pqqb5KN+kpH6SUbqJvmon2SkfpJR5TSOW9z036NHD9auXUtgYCCXL1/mf/7nf/j+++/vVfuEyt14y8/58+fp0aMH8fHxXL9+HW9vb3Q6HVlZWYwaNYqEhAR8fHwYO3Ys/v7+fPjhh8oKKV999RUtWrRg7NixjB8/nr59+wKwfv16kpKSmDFjBlqtlmXLlpGcnMwHH3xAfHw8CQkJrF69mjp16jBhwgQGDhzII488UiV9kxoq6rBp1F+dPp6fn0+dOnXucWvE7yEZqZvko36SkfpJRuom+aifZKR+klHlbnnLT1FRkTLVvlGjRhQUFNz1RomapeyWH5PJxIsvvsiiRYvo3bs3U6dO5dy5c+h0Oq5fv87Zs2fp2LEjAAMHDkSr1VKnTh1CQkI4f/6809skvv/+e9LS0hg5ciRQuoS3t7e3sr1Hjx7KyiodOnTg/Pnzd7/D4p6zWCyYzWbsdjsA7u7uWCwWTCYTZrMZKJ0totVq0ev1FBUVKft6enricDgoKSlRisZ6eHhgs9lwOBxYLBagtOCWRqNBp9MpI/EajQZ3d3c0Gk2FY1qtVux2u1JTxWAwAKDVaikpKVG+NhgMaLXaCvvb7fYKfSr72lX6ZLValdXhXKVPrpRTYWGhy/XJ1XK68VNBV+mTq+VUViDdlfrkSjkVFha6XJ9cLaey/xe5Up9cLaeyjFypT2X7V8VA0S0HVGw2G/v371c6bLVay30P0K1btztuiKj5jEYjffr0YefOnezYsYOYmBjmzZuHRqMhNja23LLbN9bh0el02Gw2p8d0OBw899xzPPzwwzc9543HkaW9XZObm1uFQsd169ZFr9c7renk7I/jjQNxUPqHHqhwm9DN9v/tY5XdT+qsKLOz/W9WvNlV+mS1WpU2uUqfblTT+2Q0GpW2lKnpfXKmJvepXr16FTKCmt0nV8upTp06TjOCmtsnV8rJw8MDnU7nUn26cX9X6JOHh4dyXlfp02/3r+l9ql+/frm/c67Qp6qccXPLARV/f3+mTp2qfO/r61vue41Go9QaELWb3W7nxx9/pEWLFiQlJdGkSRM0Gg179uzh3Llzt3UMLy8vZaUUKL2laMmSJfTv3x8fHx/MZjNnzpzhvvvuu1vdEDWEVBxXP8lI3SQf9ZOM1E8yUjfJR/0kI/WTjCp3ywEVqZcibmXixIkYjUYsFgutW7fmr3/9K2lpacyYMYP4+Hjat29PWFjYbR3r0Ucf5Z133mHhwoVMmTKFESNGkJuby5gxY4DSGSuPP/64DKgIioqK5H5OlZOM1E3yUT/JSP0kI3WTfNRPMlI/yahytyxKK0RtJUVp1UGK0tZckpG6ST7qJxmpn2SkbpKP+klG6icZVe6WM1SEEEIIUbNt2bKFn376icLCQlq3bs0TTzyhbHM4HCxevJhz586V2+ZwONi1axfJyckUFRXh5+fHY489hr+/P6dPn2bbtm1kZ2djMBi47777GDx4MDqdjvz8fDZs2MDZs2fx9vYmJiaGDh06AHD06FESExPJzc3F09OTjh07EhMT47TN58+fZ9OmTWRnZxMQEMCwYcNo1KjR3b9YQgghhBC3SQZUhHDCbLPedGaEuLfMNisGXcU/VZ6entXQGvF7SEbq0rZtWw4ePKh8X5ZPSkoKly5dqvD8gwcPsnPnTsLCwggLCyMzM1MpIL5+/XoKCwvp378/P//8MykpKQQFBREREcGmTZs4e/YsDz74IMePH2fdunU0bdqUOnXqsG7dOoxGIwMGDCA5OZndu3cTEhJC8+bNy53barWycuVK3NzciI2NZffu3axcuZIXX3wRrVZ7F6+SusjvkPpJRuom+aifZKR+klHlas+rEiF+B4fV+apD4t5zNpgCKMuiCfWSjNRj0KBBFVbks1qt5Ofns23bNvr27Vthn7179+Lj40NcXBzt27cnNjaWwMBAoHT2ipubG8HBwdSvXx8orcxfXFzMiRMnCA4Oplu3bvTp0weHw8Hhw4ex2+1oNBo8PDwIDg7G19dX2e+3Tp06RWFhIZGRkURFRdGpUydyc3NJT0+v4iujbvI7pH6SkbpJPuonGamfZFQ5GVARwhmd/GqonbNl2YS6SEbqYLY5fyFkt9vZsmULwcHBtGnTpvw+ZjN5eXnY7Xbee+89Zs6cyZdffqksTT9y5EgcDgf//e9/SUlJoVOnToSFhZGbmwv833KEdevWBSA3Nxej0ciwYcPIzc3l3//+NydPnqRv3740aNCgQtvKjlO2f9m/OTk5d3o5ahS73V7dTRC3IBmpm+SjfpKR+klGlZNbfoRwwqh3Y/DXs6u7GUIIccc2j5zi9PEzZ85w6tQpxo4dqwxgWCwW8vPz0el0ABQUFPDQQw+RkZHBwYMH2bNnDzExMezduxeNRsPo0aM5deoUhw4dIjQ0FB8fn3LnuLHuvc1mY8+ePdSpU4fY2FiSk5NJTEykVatWNG7cuNI+1Nb6+fKpoPpJRuom+aifZKR+klHl5GN4IYQQohbKz8/HarXy+eefs3jxYgDS09P5+uuv8fT0xGAw4OXlRefOnYmKigJKZ4gUFhZy+vRpGjduTLt27ejSpQsAp0+fVm7jycvLU84B4Ovry5UrV8jMzFRmxHTo0AG73c7Zs2eB0hdsZS/abnYcPz+/u35dhBBCCCFul8xQqUViYmKYP38+oaGhd/1cM2bMICUlBSh9kd20aVNl+v+LL75IcnIyU6Y4/9RUCCFE1Tp58iSZmZlA6SBFSkoK/v7+xMXFAVBYWMjmzZtp1KgRvXv3BiAiIoIff/yRH374gaysLACCgoLw8PDAaDRy4cIFDh48yOnTpwGoX78+Hh4ehIaGcvr0afbt28fx48fRaDRERERgNBrRarWcOnWK5ORkjhw5ouwHMG/ePIqKipg6dSqtW7fGy8uLpKQkDAYDhw4dwtfXlxYtWtzLy1btDAZDdTdB3IJkpG6Sj/pJRuonGVVOBlTEXTFt2jTl65iYGObOnVtuIKdfv3537dxWqxW9Xn60hRCizN69ezl37hwAGRkZJCQkMHjwYGXmSdktP97e3sqKOw8++CBFRUXs2rULo9HIAw88QGRkJBqNhri4OL777ju2bduG0WikS5cuREZGAjBkyBA2bNjA9u3b8fLyYvjw4fj7+wMwfPhwdu3axZYtW/D09KRnz56EhYVVaK9erycuLo7NmzezdetWAgMDGTp0aK1a4UcIIYQQ6qdx1NYbk2uhshkqP/zwA5s2bcJms2E0Gpk+fTpt2rRhxYoVnDhxgmnTppGamkpcXByrVq2iQ4cOynMeffRRXn31Vc6ePYvFYiEoKIiZM2dWuG/e2XnLBlTWrl3Lzp07mTt3LgcOHODtt9+mQ4cOHDlyBL1ez7vvvsu8efM4deoUjRo1Ij4+Hk9PT15//XXatWvHmDFjAMp9//rrr6PT6Th79iyFhYWsX7/+jq+X1FARQriCm9VQsVgsuLm53ePWiN9DMlI/yUjdJB/1k4zUTzKqnHyMXwuNGDGC8ePHA6WfWk6bNo2VK1fSrVs3Fi1aBMC+ffvo1KkT+/fvp0OHDuzbt0/Z5+9//zv16tUDYM6cOSxYsIDXXnvtD7fn9OnTzJ49m7feeosZM2YwYcIEVq5cScOGDXn66afZtGmTMi29Mj///DNffPGFrJUuhBC/UVaDxNPTE7vdrqzi4+3tjbu7u1LB32w2A6UzRLRaLXq9nqKiIuU4np6eOBwOSkpKlEKxHh4e2Gw2HA4HFosFADc3NzQaDTqdjuLiYgA0Gg3u7u5oNJoKx7RardjtdqWGStn0Yq1WS0lJifK1wWBAq9VW2L+sT2X9cJU+Xbt2Tfl/mqv0ydVyys/Px2g0ulSfXCmngoICAgMDXapPrpZTQUEB3t7eLtUnV8spKysLb29vl+pT2f5lqxLeCRlQqYXS0tL4+OOPuX79OhqNhvT0dACaN2+OyWTiypUr7Nu3j1deeYX58+czdOhQZTYKwPr160lISMBisVBUVHTH97S3bNlSWbIzPDycS5cu0bBhQwDatm2rTFO/lYEDB8pgihBCOHHjCwadToebmxt2u73CCwlnS107e7FR9sKqTNltlu7u7re1/28fK1tVyBlnn4o52/9mn57V5D55eno6PVdN7pOr5eTm5oaXl5fT/Wtqn1wtJ51O53J9KtvfVfpU9q8r9enG/Wt6n7y9vZ2+jnCmpvSpKgZSysiASi1jt9t56aWX+OKLL2jbti0ZGRn06tVL2R4dHc2OHTvIzs6ma9eu/POf/2Tnzp107doVgKSkJJYvX86KFSuoV68eCQkJrFy58o7adGOhI51OV+4XUafTYTKZlK9vXAe97PEyMpgihBC3T+qRqJ9kpH6SkbpJPuonGamfZFQ5uTq1kNVqpVGjRgAsW7as3Lbo6GgWLFhAp06dAOjcuTMLFiygW7duAMoUcV9fX8xmM2vWrLln7W7evDlHjx4FIDMzkwMHDtyzcwshhKuRqv3qJxmpn2SkbpKP+klG6icZVU4GVGoRq9WKh4cHEydO5OGHH2bUqFEVZnVER0dz8eJFZQCl7Pvo6GgAevbsSVBQELGxsYwZM4bw8PB71v64uDiuXLnC4MGDmT59Oh06dLhn5xZCCFcjnzipn2SkfpKRukk+6icZqZ9kVDlZ5aeWyMzMZNCgQezZs8fpvWmiIlnlRwjhCm62yk9+fn6V3kMsqp5kpH6SkbpJPuonGamfZFQ5qaFSCyxZsoRly5YxZcoUGUy5TSar5aZvQsTv8+mnn3L16lXsdjsBAQHExsYSFBTE9u3bOXLkCMXFxfj6+tKnTx/atWvHzp07SUxMrHCcadOmAaV1fHbt2kVxcTEhISEMGzYMT09Pzpw5w8aNG8nLy8NgMBASEsJDDz3ktDiWyWRi48aNnDhxAoPBQPfu3enevftdvxZCVAezzYpBJ/+7F0IIIYSoarrp06dPr+5GiLsrIiKCMWPG0LZt2+puSo1RXFjk9I24+P0yMzPp2LEjjRo1Ii0tjfPnz1O/fn02bdqEv78/3bt358SJExw/fpwHHngAb29vmjdvTnh4OC1atOCXX36hYcOGREZGcvnyZVasWEHTpk0JDw/n0KFD5Ofn06ZNG/Ly8vDy8qJ9+/ZYLBZ+/vlnDAYDzZs3r9Cmbdu2cejQIXr27IlOp+PgwYM0b94cPz+/arhCrqtsOVFRvXQ3maprNpslH5WTjNRPMlI3yUf9JCP1k4wqJzdECeGErBhUdWJjYwkLCyM4OBi9Xo9Go1HWnffz8yMkJASj0YjBYECj0RAYGEi7du1o166dspZ8ZGQkAIcPHwYgJiaG3r1706xZM9LS0rBarTRv3pzo6GhCQkKUZbc1Go3TNh05coSAgAD69OnDgAEDyh1bVB35PVI3yUf9JCP1k4zUTfJRP8lI/SSjyskcYCGcsGJHx83XMxe3ZrZZMOjcMJlMvPfee0Dp2vLDhg2jWbNmREVF8eOPP3Ls2DH0ej2PP/54uaJXDoeD5ORkjEYj7du3ByA3NxeAunXrYrfblX+vX7+Ov78/SUlJfPPNN0DpqlD3339/hXYVFxdjMpmUe0Hr1q0LQE5Ozt27GLWU3W5Hp5PfI7WSfNRPMlI/yUjdJB/1k4zUTzKqnAyoCOGEUefG4HV/q+5m1GibR8wCSpdaGzNmDFlZWXz33Xfs2LGDIUOGkJqaSkhICF26dOGbb75h3bp1vPDCC8rSbOnp6Vy7do3IyEiny7WZzeYKj7Vp0wZ/f39SU1NJS0vj2LFjdOzYsdJ2Sl3uu8dsNuPm5lbdzRA3Ifmon2SkfpKRukk+6icZqZ9kVLl7cstPTEwMAwcOZNiwYfTv35/nnnuOlJSUe3FqRXx8PLNn396qLTExMZw8efKWx7vxDd1HH33E5s2b76iNd8vBgwfp378/RUVFymPr1q3jsccew2az3ZM2rF27lokTJ97xcRYtWkR2dnYVtEjcK1qtlpCQELp27UqTJk1IT0/nxIkTmEwmOnToQJs2bQgODiY/P5+rV68q+yUlJQEQFRWlPObr6wtAXl4edrudvLw8tFotPj4+APj4+NC6dWtiYmIAOHbsGFA6sm61WnE4HHh4eGA0GsnLywNK63wAUj/lLrDb7dXdBFEJyUf9JCP1k4zUTfJRP8lI/SSjyt2zGSpz584lNDQUgG+//ZZnnnmGhQsXEhERUSXHt1qt6PX3bsLNvHnzGD9+vPLJ+UsvvXTPzv173X///fTu3Zv333+f//3f/+Xq1at8+OGHLF68uMZM37Lb7Wg0GpYsWUL37t3x9/ev7iaJ2/DLL7/w008/0axZM/Ly8vj111/x8vJSBi+SkpKwWCycPHkSnU6nPF5QUMDx48dp1qwZgYGByvEiIiI4ePAg33//PU2aNOHXX3+lffv26PV6tm7diru7O76+vspASkBAAAC7du0iMTGRuLg4wsPDlePs3LmTjIwM5dhCCCGEEEIIcbuq5ZafAQMGkJqaysKFC5k7dy779u3jX//6FyaTCZvNxrPPPsuQIUOA0hVC3nrrLS5duoTJZGLIkCE8++yzQO1UWfMAACAASURBVOlMksGDB7N//35CQ0N55ZVXmDRpEoWFhZhMJnr37s3kyZOV82ZkZPD000/z66+/EhQUxEcffYSHh0elbZ03bx4bN27EaDQqb+jnzJkDwGOPPYZWq2Xp0qXMnDmTdu3aMWbMGOLj4zlz5gwFBQWkp6fTtm1bnnnmGd555x0uXbpE//79mTJlSqX92717N0uXLuWTTz4hOzubBx54gDlz5jBo0CAWLFhAfn4+kyZNYvbs2Rw8eBCLxYKfnx8zZ86kSZMmFfrx6quvMmLECPbv38+SJUuYMGECQUFBzJ49m927dwPQs2dPXnvtNXQ6HRkZGUyePJmsrCyaNWsGQI8ePejfvz+jR49m+/btSrXnsrwGDRrEX/7yF3JycpTZBzNmzKhwu8bly5f561//ylNPPUVUVNRNM4uPj+fUqVMUFBRw6dIlhg8fTmZmJhMnTsRoNPLBBx9w9erVm/7siOrn4eHBxYsXSUtLQ6fTERQURL9+/WjcuDHdu3fn6NGjbNmyBT8/PwYNGqQUvTp8+DB2u10pRlumcePGDB48mN27d3Pu3Dlat25NbGyscq6kpCSKiorw8vKiS5cu9OnTx2m7YmJiKCwsZM+ePRiNRh588EGCg4Pv6rWojWSZdnWTfNRPMlI/yUjdJB/1k4zUTzKqXLXVUImIiOD7778HIDw8nGXLlqHT6cjKymLUqFH06NEDHx8fpkyZwvPPP09UVBRms5knn3yS9u3b88ADDwCln2SvXr0aAJPJxPz58/Hy8sJisTBhwgR27dpFr169AEhLS2P16tXUqVOHCRMmkJCQwCOPPHLTNubm5rJo0SJ++OEH3N3dKSgowN3dnWnTprFs2TJWrFiBl5eX031/+ukn1qxZg6enJyNHjuSDDz7g008/xWq18uCDD/Loo4/SokWLm/YvMjKS1157DYvFwr59++jYsSP79u1j0KBB7N+/n6eeegqAp59+WhmcWbVqFe+//74y4HMjDw8PZs2axbPPPktYWBjjxo1j+fLl/Pzzz6xdu1Y51ldffcUTTzzBW2+9RdeuXXn++ee5ePEiQ4cOpUePHjRo0ICoqCg2b97MyJEjuXDhAmlpacydOxedTsf777+Pn58fDoeDKVOmsGbNGh5//HGlHcePH+f//b//x7Rp04iMjLxlZqmpqaxdu5Z69eopfbxxtlNAQMBNf3ZE9WvSpAnPP/+80239+/enf//+Trf16NGDHj16ON0WFRVFVFQUJpOp3BJuvXv3pnfv3k736dOnT7nBFaPRyMMPP3ybvRB/lEwRVTfJR/0kI/WTjNRN8lE/yUj9JKPKVduAyo2FIK9du8bUqVM5d+4cOp2O69evc/bsWUJDQzl48CDXrl1TnltYWMjp06eVAZURI0Yo22w2G++++y6HDh3C4XCQlZXF8ePHlTfnPXr0UFb06NChA+fPn6+0jXXq1CEoKIjJkyfTo0cP+vTpg7e39231r0ePHsoqImFhYdx3330YDAYMBgMtW7bk/PnzBAYGVtq/1q1bc+TIEfbu3cvzzz/Pe++9h9ls5ujRo3Tu3BkovZVh2bJlFBUVKUvM3kznzp1p1aoVf/rTn9BoNOzbt4+RI0cqM0hGjRrFd999xxNPPMGBAwf4xz/+AZS+Ke7WrZtynLFjxzJr1ixGjhzJihUrGD16NAaDAZvNxmeffcauXbuUlVduHNE8ceIEL7zwAh9//DEhISHArTPr1auXMpjizM1+dm5ViFTcG/n5+Xh6emK1WpU6JoDyM6fVaikpKVG+NhgMaLXacvV+PD09sdvtmM1m5Q+6u7s7JpMJ+L/itHq9Hq1Wi16vr7C/w+GgpKRE+bvj4eGBzWbD4XBgsVgAcHNzQ6PRoNPpKC4uBkqXXXZ3d0ej0VQ45t3oU9nXrtKnG5etdpU+uVJOxcXFmM1ml+qTq+VUVFSktN9V+uRqOVksFuUYrtInV8rJZDKh1+tdqk+ulpPJZMJsNrtUn1wtp/z8fKWtrtKnsv3L3q/fiWobUDl69CitW7cGYPr06cTExDBv3jw0Gg2xsbGYTCalbsbq1atvWln4xnWxP//8c/Ly8li1ahVGo5E33nhDedMFlPs0W6fTldvmjE6nY+XKlaSkpLB//35GjRrFp59+yn333XfL/v32XL/93maz3bJ/0dHR7N+/nyNHjjB9+nT8/f3ZtGkT9913H0ajkYsXLzJr1ixWr15Ns2bNSElJ4bXXXrtln+60bkrnzp2x2WwkJyfz9ddfKzOEEhISSE5O5ssvv8Tb25v58+eTnp6u7NegQQMKCws5cOCAMqByq8xuNgOozM1+doQ6lP2RquxnztnP/m//uOl0ugrPKykpwWg0lvvdutn+QIXB0LKaS86mMTrb31mbbuaP9qmMq/QpPz9f6Yur9OlGNb1Pdru9wraa3idnanKf9Hq903PV5D65Wk4Oh+OmH7bV1D65Wk5lr31dqU9l+7tKn258vegqfbpx/5reJ6PRWOF3qqb3qSoGUsrck1V+fuu7775j+fLljB8/Hih90d2kSRM0Gg179uzh3LlzQOmF7tKlC5988omy7+XLl8utBHKj/Px8AgICMBqNZGRksH379jtqZ0FBAdeuXeP+++9n4sSJhIaGcurUKaD0jX5BQcEdHf9W/YuOjmbt2rU0bNgQg8FAt27diI+PV2aLFBQU4ObmRkBAAHa7nRUrVvyu83fr1o1169ZhsViwWCysW7eO7t27A6WFbL/++mulTfv37y+379ixY5k0aRKdOnWiUaNGQOn19/Pzw9vbm/z8fDZu3FhuH19fXxYtWsSGDRv4/PPPlX1+T2ZeXl7Kqixl+zv72RFCCCGEEEIIIe6mezZDZeLEiRgMBoqLiwkJCeGTTz5RVtV49dVXmTFjBvHx8bRv356wsDBlv/fff59Zs2YxdOhQoPQN9dtvv62s3nGjsWPH8tJLL/HQQw/RoEGDcrep/BEFBQW8+OKLypSk8PBwBgwYAMD48eMZN24c7u7uLF269A+fo7L+RUREkJOTwxNPPAGUDoB8+OGHREdHA6W3Eg0cOJDBgwfj5+dH7969laVmb8ejjz7K+fPnGTlyJFB6m1JZTZm///3vTJ48mYSEBJo2bUqHDh3KjSQOGTKEN998U2kblN5+tX37dgYOHIi/vz9dunSpMFukTp06LFy4kGeffZaioqLfndm4ceOYOnUq7u7ufPDBB5X+7AjXdi9X9RJ/jGSkbpKP+klG6icZqZvko36SkfpJRpXTOG4sZiLE/6+kpAS9Xo9eryczM5OHH36YRYsWKSuhJCUlMX36dBISEsrVSXAlg9f9rbqbUKNtHjHrrh7/t0VphfpIRuom+aifZKR+kpG6ST7qJxmpn2RUORluEk6lp6czZcoUHA4HVquVF154QRlMmTp1Knv37mX27NkuO5hitlnu+oCAqzPbLBh0zu+vrAoyWq5+kpG6ST43t2XLFn766ScKCwtp3bq1Mhvz6NGjJCYmkpubi6enJx07diQmJgaAlStXcubMGaxWK/Xq1aNPnz6Eh4cDcP78eTZt2kR2djYBAQEMGzaMRo0a8euvv/Ltt98qt/oGBwczZMgQvLy8WLduHUeOHCnXLh8fH15++eUK7bXb7WzZsoWjR4+i0Wjo1KkT/fv3d9n/R6uJ/B6pm+SjfpKR+klGlZOrI5y67777WL9+vdNtM2fOvMetufdMRSUY6ty9wYDa4G4OpgAUFRVVaUEpUfUkI3WTfCrXtm1bDh48qHxfVmvMaDQyYMAAkpOT2b17NyEhITRv3pyAgABatWqFxWLh+++/Z926ddx3333Y7XZWrlyJm5sbsbGx7N69m5UrV/Liiy+SnZ2Np6cn/fr149y5c6SlpWE0Ghk+fDiRkZE0adIEDw8PsrKySExMVGqW/daBAwdISkoiKioKq9XKvn37CAgIoFOnTvfqctVa8nukbpKP+klG6icZVU4GVIQQQgghbjBo0CByc3PLDaiUrczn4eFBcHAwp0+fJjMzU1mRoG/fvhQXF5Ofn4+7u7uyzOOpU6coLCykX79+REVFUVBQwK5du0hPT6d9+/Z07NgRgPbt25OWlkZmZiYATZs2xcfHhzp16rB582YAIiMjnbb3yJEjGAwGBg4ciN1uJzU1lcOHD8uAihBCCHGXyYCKEE4YPAzV3QRxCzJSrn6SkbpJPs6ZbWYMuor/DzAajQwbNoz169fz73//GygdRGnQoIHynI8++giTyYROp2PUqFFotVpyc3MBqFu3brl/c3JylFtpAU6fPg1A8+bNy53XYrGQmppKvXr1yj3/Rjk5OXh7e6PVatFqtXh4eJCTk/NHL4EQQgghbpMMqAjhhFFvZND6x6u7GUIIIe6xLcOXO33cZrOxZ88e6tSpQ2xsLMnJySQmJtKqVSsaN24MwGOPPUZOTg7fffcdO3bsIDQ0tMJxnK0FcP78edavX0+jRo3o06eP8rinpyepqamYTCZ69uwpNVFUyNPTs7qbICoh+aifZKR+klHltNXdACGEEEIItbty5QqZmZkEBwfTpk0bOnTogN1u5+zZs8pzWrRoQadOnWjdujVZWVlkZmbi6+sLQF5eHgD5+fkA+Pn5AXDu3Dm+/PJL6tWrx5gxYzAY/m92jMPhICkpCZ1OV+72HbvdjtVqxW63K8cqKChQHi8qKlKOL+4uWSxT3SQf9ZOM1E8yqpzMUHEhMTExzJ8/3+knYlVtxowZpKSkAKXTlJs2baosp7V27Vp0Ot1db8OBAweYPXs2a9euvevnEkIIUXucPHlSqWWSl5dHSkoK/v7+aLVaTp06RXJysrICT/369cnMzGTXrl20aNECs9nMzz//jF6vx8/Pj8DAQLy8vEhKSsJgMHDo0CF8fX1p0aIFly9f5ssvv8ThcNC5c2fOnDmDm5sbYWFhQOlgy6VLl2jfvn25TwhTU1NZv349/fv3p3v37kRERPDtt9+ydetWbDYbdrudiIiIe3/haqGSkhK8vb2ruxniJiQf9ZOM1E8yqpwMqIg/ZNq0acrXMTExzJ07954M5AghhBB32969ezl37hwAGRkZJCQkMHz4cIYPH86uXbvYsmULnp6e9OzZk7CwMHJzc7l27RonT55Eo9EQEBBAnz598PDwACAuLo7NmzezdetWAgMDGTp0KFqtloyMDCwWC4BSeNbHx0cZUElNTQVuXoy2zP333092drby/OjoaClIe4/IJ7fqJvmon2SkfpJR5TQOuUIuo2yGyg8//MCmTZuw2WwYjUamT59OmzZtWLFiBSdOnGDatGmkpqYSFxfHqlWr6NChg/KcRx99lFdffZWzZ89isVgICgpi5syZ+Pj43PK8oaGhnDlzhpkzZ5KTk4PFYuFPf/oTo0ePBiAsLIxXXnmFbdu2kZuby+TJk4mNjQXgm2++Yc6cObi7uzNw4EDmzJlDSkoKXl5eN23PgQMHmDlzJhERERw6dAiNRsOcOXMICQmpkuspNVSEEKL2uVkNleqQn58vxYNVTjJSN8lH/SQj9ZOMKiczVFzQiBEjGD9+PFD6Kdu0adNYuXIl3bp1Y9GiRQDs27ePTp06sX//fjp06MC+ffuUff7+979Tr149AObMmcOCBQt47bXXbnleq9XKa6+9xnvvvUdISAgFBQWMHj2ajh07KoMc3t7erFmzhuTkZF5++WViY2PJysrif//3f/nqq69o0aKF0sYylbXnl19+YdasWbz55pv897//5T//+Q8ffPDBHV9DIYQQtZfVasVms+FwOJQZJG5ubmg0GnQ6nbIkskajwd3dHY1GQ1FRkbK/p6enUuPEarUCKLVRtFotJSUlytcGgwGtVlthf7vdjt1uV2quuLu7KzVTzGYzAHq9Hq1Wi16vr7C/w+GgpKRE+WTRw8NDFX0ym81KP1yhT3q9nsLCQpfqkyvlVPa77Ep9crWcrFYr+fn5LtUnV8upLCNX6lPZ/lUxUCQDKi4oLS2Njz/+mOvXr6PRaEhPTwdKl2I0mUxcuXKFffv28corrzB//nyGDh2qzP4AWL9+PQkJCVgsFoqKimjRosVtnTc9PZ3Tp08zadIk5TGLxcKZM2eUAZXBgwcD0LFjRzIzMzGZTBw5coTw8HDlPKNHj2bWrFnKMSprT8uWLQkPD1eOuWPHjj9yyYQQQgiFXq9Hry99ieTu7l5hu7MXYL99rLJaYm5ubre1v7u7u1Kf7EbOHnPWpt/e866GPjl7HtTcPpUtU+1MTe2TK+VUtoy5K/Xpxv1doU8mk0lpr6v06bf71/Q+eXp6lmurK/SpKmfcyICKi7Hb7bz00kt88cUXtG3bloyMDHr16qVsj46OZseOHWRnZ9O1a1f++c9/snPnTrp27QpAUlISy5cvZ8WKFdSrV4+EhARWrlx5W+d2OBz4+fmxfv36mz7nxj+YgDKKeDO3as+NqyGUjaAKIYQQrkDuylY/yUjdJB/1k4zUTzKqnCyb7IKsViuNGjUCYNmyZeW2RUdHs2DBAqVYXefOnVmwYAHdunUDSlcz8Pb2xtfXF7PZzJo1a277vC1btsTd3Z1169Ypj50+fZqCgoJK94uIiODYsWOcP38egK+//lrZdiftEUIIIWqysqnPQr0kI3WTfNRPMlI/yahyMqDiQqxWKx4eHkycOJGHH36YUaNGlVtmEUoHVC5evKgMoJR9Hx0dDUDPnj0JCgoiNjaWMWPGKLfT3A69Xs/8+fPZvHkzQ4cOZciQIcyYMUO5l+5m6tevz/Tp03n66acZMWIE165dw83NDQ8PjztqjxBCCCGEEEIIcbfIKj8uIjMzk0GDBrFnzx6n956pXUFBgXIv3Zo1a1i9ejXLl1fvSguyyo8QQtQ+alrlp6SkpEb+P702kYzUTfJRP8lI/SSjykkNFRewZMkSli1bxpQpU2rsD/vSpUvZunUrNpsNHx8f3nrrrWptj8lqVtWLaiGEEPeG2WbGoDPc+on3gEajqe4miFuoLRllZ2ezceNGMjIysNlsNG3alCFDhpCamkpiYmKF50+bNo1169Zx5MiRco/7+Pjw8ssvk56ezuLFi8tti42NJTo6utJtZ86cYePGjeTl5WEwGAgJCeGhhx5yWgjTZDKxYcMGfvnlFwwGA927d6d79+5VcDVEVaotv0M1mWRUORlQcQHjxo1j3Lhx1d2MO/Lcc8/x3HPPVXczFDq5G071rFarUhFcqJNkpG6Sj3NqGUyBylctEOpQWzLKz8/H4XDQp08fsrOzOXjwIAkJCQwaNIj69esDUFRUxJYtW2jYsCEAkZGRtGrVCoCsrCwSExOVGn9levXqRUBAAMBtbdPpdHTu3Jk6derw888/k5aWRmBgID179qzQ5u+//56ff/6Z3r17k5GRwbZt22jUqBEtW7aswisj7lRt+R2qySSjyskrKSGcKC4urtLltETVk4zUTzJSN8lH/SQj9astGTVr1ownn3xS+f7o0aNkZmYSGBhIYGAgAHv37gVKB1IAmjZtStOmTQHYvHlzuW1lgoKCaN68udPBXWfbmjdvTpMmTSgpKSEnJ4cTJ07c9NPzI0eO4O/vT58+fcjJyeH48eMcPnxYBlRUprb8DtVkklHlZEBFCCeMHur5hFI4J3/Y1U8yUjfJR/0kI/WrDRlZbGbcbpi5denSJYqLi2nTpo3ymMPhIDk5GaPRSPv27cvvb7GQmppKvXr1CA4OLrftiy++AKBJkyaMHDkSf3//W25LSkrim2++AUoHWO6///4KbS4uLsZkMimzZerWrQtATk7OH7sIQghxEzKgIoQTBr2RF9cOrO5mCCGEEEJUq/hRW5Wvs7KyWL58Ob6+vgwaNEh5PD09nWvXrhEZGYnBUP5DqbS0NEwmEz179lRmk3h5edGvXz8CAgL49ddf+eGHH9i0aRPjxo2rdBtAmzZt8Pf3JzU1lbS0NI4dO0bHjh0r7YOswaFeUp9D/SSjysmASi0UExPD/PnzCQ0NvSfne/3119m7dy9+fn7Y7Xb8/f2ZNWtWhXtl70ReXh5fffUVTz/9dJUdUwghhBBClLp69SqLFy9Gr9czbty4crNzkpKSAIiKiqqwX1JSEjqdjk6dOimPBQQEKPVRQkNDSU5O5urVq7fcBqWFbX18fKhfv365ARW73Y7dbken0+Hh4YHRaKSwsBAorQED4OfnV5WXRFSBmrqgRm0iGVVOBlTEPfHMM88wZswYAN59913mz5/PjBkzbnt/u92ORqO56QhpXl4en376qQyoCCGEEEJUsevXr7N48WKKioqIiYnh4sWLXLx4kXbt2lFQUMDx48dp1qyZUk+lzOXLl7l06RLt27fH09NTeTwxMZHi4mIaNGig3EIUFhZ2y21bt27F3d0dX19fjh07BqAMvuzatYvExETi4uIIDw8nIiKCgwcPsnPnTjIyMgCIiIi469dK/D4y+0H9JKPKyYBKLfbZZ5+xadMmbDYbRqOR6dOn06ZNG1asWMGJEyeYNm0aqampxMXFsWrVKjp06KA859FHH+XVV1/l7NmzWCwWgoKCmDlzJj4+PpWe0263U1hYqDzv6tWrTJo0icLCQkwmE71792by5MkAxMfHc+rUKQoKCrh06RJfffUV8+fP5+DBg1gsFvz8/Jg5cyZNmjThzTffJD8/n+HDh+Ph4cGKFSvu+vUTQgghhKgNcnJylNke27dvVx5v164dhw8fxm63Vyg4C5CcnAxULEYbEBDArl27SElJQa/X065dO2JjY2+5zcPDg6SkJIqKivDy8qJLly706dPHaZtjYmLIzc1lz549GI1GHnzwwQo1XET1KyoqqhW1iGoyyahyGofcVFjrlN3yU79+ferVqweUVmb/17/+xcqVKzl37hx/+ctf2Lp1Kx9//DE7duwgJiaGZ555htjYWBYsWEBQUBDXrl1T9p8zZw42m43XXnutwvluvOUnKysLb29vli9fTr169TCZTFitVry8vLBYLEyYMIGnnnqKXr16ER8fz5o1a1i7dq1ynhvPuWrVKvbu3cucOXO4cOECo0eP5sCBA1V2naSGihBCCCFqu/hRWzGZTACYzWYA9Ho9Wq0WvV5PUVGR8lxPT08cDgclJSVK3RIPDw9sNhsOhwOLxQKAm5sbGo0GnU5HcXExUPopuLu7OxqNpsIxrVYrdrsdq9UKoNRp0Wq1lJSUKF8bDAa0Wq2yf0FBAYGBgdjtdsxmM3a7HSi9haHs65rWp7L9XaVPBQUFeHt7u1SfXC2nzMxMvL29XapPZftXxUCRzFCpxdLS0vj444+5fv06Go2G9PR0oLRiuslk4sqVK+zbt49XXnmF+fPnM3ToUGU2CsD69etJSEjAYrFQVFREixYtbnquG2/5+fe//80//vEP/vOf/2Cz2Xj33Xc5dOgQDoeDrKwsjh8/Tq9evQDo1auXMoACpdM5ly1bRlFRkfILI4QQQggh7h6j0Vju3xs5e0NS9uarTNnSx85qMTjb/7eP6XS6m7bNzc2t0v11Oh06nc7p86Bm9qlsf1fpU9m/rtSnG/ev6X3y9vau8DtV0/tUlTNuZECllrLb7bz00kt88cUXtG3bloyMDGUQAyA6OpodO3aQnZ1N165d+ec//8nOnTvp2rUrUFpgbPny5axYsYJ69eqRkJDAypUrb+vcAwcOZMGCBQB8/vnn5OXlsWrVKoxGI2+88YbyKQiUVoEvc/HiRWbNmsXq1atp1qwZKSkpTmfECCGEEEIIcWPdFqFOkpH6SUaV01Z3A0T1sVqtyko7y5YtK7ctOjqaBQsWKBXZO3fuzIIFC+jWrRtQWgTW29sbX19fzGYza9asue3z7t+/X5nNkp+fT0BAAEajkYyMjHL35f5WQUEBbm5uBAQEYLfby9VJ8fb2pqSkRGatCCGEEEIIAHldWANIRuonGVVOBlRqIavVioeHBxMnTuThhx9m1KhRFUYeo6OjuXjxojKAUvZ9dHQ0AD179iQoKIjY2FjGjBlDeHh4pef85JNPGD58OEOHDmXjxo288847AIwdO5aUlBQeeughpk6dqpzPmbCwMAYOHMjgwYOJi4ujadOmyjZfX1+GDh3K0KFDeeyxx/7QdRFCCCGEEK6jrK6DUC/JSP0ko8pJUdpaJjMzk0GDBrFnzx5ZU/wWpCitEEIIIWq7+FFbq7sJf1h+fr6sTqJykpH6SUaVkxoqtciSJUtYtmwZU6ZMkcGUWzBbTTX6BYQQQgghRFWw2My46QzV3QwhRA1ktVqZP38+2dnZREVFMXjwYK5evcqGDRu4fPkyvr6+DBo0iJCQEABKSkrYsmULJ06cwG6306hRI/785z+TnZ3Nxo0bycjIwGaz0bRpU4YMGaIsXnL8+HG+/fZb8vLyaNq0KcOHD8fPz4/c3Fw++uijcm3q2rUrAwc6/+B8586d/Pjjj1gsFsLDw3nooYeUgrk3I7f81CLjxo1j69atPPLII9XdFNVz2Kq7BeJWbixeLNRJMlI3yUf9JCP1qw0Z1eTBlLKlU4V6SUbqdycZJSYmkpeXV+6xNWvWkJWVxYABA9BqtaxatUpZ2nj9+vUcPXqUTp06MXDgQGXAJD8/H4fDQZ8+fejYsSNnzpwhISEBKK2zuXr1aoxGI/379+fy5cusW7eu3Dm7dOnC6NGjGT16NBEREU7b+vPPP5OYmEjLli3p2rUrR44cYffu3bfso8xQEUIIIYQQQgghRJXJyMhg//799O3bl23btgFw+fJlMjIyiIyM5P7778fNzY0NGzZw7NgxWrZsyfHjx2nfvj39+vVDo9HQuXNnAJo1a8aTTz6pHPvo0aNkZmYqX9tsNnr06EHbtm25dOkSqampXLt2Da22dP5I48aNCQsLu+lyzwBHjhwBYNCgQXh5eZGamsrhw4fp27dvpf2UARUhnNDefClzoRLO1rkX6iIZqZvko36SkfpJRuom+aifZKR+fyQji9XEhg0biIqKuORpgQAAIABJREFUonHjxsrjubm5ANStW7fcvzk5OXh7ewNw6dIlZs6ciUajoWvXrvTv3x+d7v/enF26dIni4mLatGlzy2P6+/sDkJCQQEJCAgEBAQwbNqzc4iZlcnJy0Gq1eHl5Kce5cOECNput3Pl/SwZUhHDCTW/kra9iq7sZQgghhBBCCFGjDG49i9zcXIYNG0ZGRgZQeoukzVa+rsKN6+OULc9sNpt5+OGH+fHHH9m7dy8hISEEBwcDkJWVxfLly5XaK87ceEw3Nzf69OlDw4YNyc7OZvv27axdu5aJEydWWV+lhkotERMTw8CBAxk2bBj9+/fnueeeIyUlRdn+2x+sHTt20KtXL1JTU7lw4QJdu3Z1etzb/YGMj49n9uzZd9yP+Ph4zGbzHR9HCCGEEEIIIUTVy8vLo6ioiPnz5/P1118DkJqaqrz/LKurkp+fD4Cfnx9+fn4ANG/enDZt2hAeHg7AtWvXALh69SqLFi1Cp9Mxbtw4ZeUhX1/fmx7Ty8uL3r17ExYWRvfu3WnQoAE5OTlYrVYcDgdWq1VZFtrPzw+73U5hYaFyvLp161Y6OwVkhkqtMnfuXEJDQwH49ttveeaZZ1i4cGGFwjwJCQl8+OGHLFy4kNatW3PhwoXqaG45VqsVvV7PvHnzGD9+vBSwEkIIIYQQQggVatu2LYGBgQBkZmaSmJhIq1at6Nu3Lxs2bCAtLY2AgACSkpIwGAyEh4djNBoJDAzkzJkzJCcnc/jwYTQaDUFBQVy/fp3FixdTVFRETEwMFy9e5OLFi7Rr14527dqxfft29uzZQ0FBAcePHycoKIh69eqRnJzMpUuXaNKkCTk5OVy5coUGDRqg1+tJT09n8eLFyupDERERnDhxgq1bt+Lr60teXh49e/a8ZV9lQKWWGjBgAKmpqSxcuJC5c+cqjy9fvpzPPvuMJUuW0KxZs991zKtXrzJp0iQKCwsxmUz07t2byZMnV3jeiRMneO2113jjjTfw8fFhxowZFBcXYzKZeOSRR5SCQ6+//jo6nY6zZ89SWFioFCV67LHH0Gq1LF26lMTERJYsWYLFYgFgypQpdOvW7Q9eFSGEEEIIIYQQdyIgIICAgAAAPD09SUxMxM/Pj8aNGzNq1CgSEhL49ttv8fHxIS4uDnd3dwBGjx5NQkICW7ZswcfHh5EjRxIYGEh6eroyc2T79u3Kedq1a0edOnUYPXo027ZtY9u2bTRp0oThw4cD4O/vz6FDh0hLS0Or1dKqVStiY52XdWjTpg29evXixx9/xGq10qFDh9saUNE4brzJSLismJgY5s+fr8xQAdi2bRtz5sxh8+bNrF27ltmzZ+Pm5saaNWto0KCB8rwLFy4wevRoDhw4UOG4a9euZefOncydOxeTyYTVasXLywuLxcKECRN46qmn6NWrF/Hx8RQVFdGzZ09mzZrFnDlzaNWqFQUFBRgMBgwGA4WFhcTFxREfH09ISAivv/46J0+e5IsvvsDT0xOAsLAwUlJSlGJBOTk5+Pr6otFoOHPmDE8++SS7du2qkmsmNVSEEEIIIYQQ4vf5x6PfVHcT7hmZoVKL/XYsrWXLlmRnZ7Nx40YmTJjwu49ns9l49913OXToEA6Hg6ysLI4fP06vXr0A+OGHH9i9ezcLFy5UBmxKSkqYPn06J06cQKPRkJmZyfHjxwkJCQFg4MCBymCKM7/++iuvvvoqGRkZ6PV6srKyuHr1qjIiKoQQQgghhBDi3jKZTOj1eoqKipTHPD09cTgclJSUKO9FPTw8sNlsOBwO5a4DNzc3NBoNOp2O4uJiADQaDe7u7mg0mgrHLKuFUlbYtqw8hFarpaSkRPnaYDCg1WqV/cvqsNwJGVCpxY4ePUrr1q2V7wMDA/nXv/7F2LFjAX73oMrnn39OXl4eq1atwmg08sYbb2AymZTtLVu25NSpU6SlpSkDKh9++CEBAQG888476PV6xo8fX26fygZTACZNmsTrr79Ov379sNvtRERElNtfCCGEEEIIIcS9VbbcsrNBi7Ilksvo9aXDEmW3/tzI2f6/fayywrFubm63dcw/Slb5qaW+++47li9fzvjx48s93rBhQ5YsWcLy5ctZuHDh7zpmfn4+AQEBGI1GMjIyyt3fBtCkSRM+++wzPvzwQzZv3qzs07BhQ/R6PSdPniQpKanSc3h5eVFQUFDunGXriK9Zs0ZWABJCCCGEEEIIcU/IDJVaZOLEiRgMBoqLiwkJCeGTTz6psMIPQKNGjVi6dKkyU+VmhXug9DafsilVY8eO5aWXXuKhhx6iQYMGTovDNmrUiEWLFjFhwgRKSkp47rnnmDx5MqtXr6Zly5ZERUVV2ofx48czbtw43N3dWbp0KX/72994/vnn8fHxoWfPnsqyWUIIIYQQQgghxN0kRWnFHZkxYwb+/v688MIL1d2UKidFaYUQQgghhBDi96lNRWllQEX8IWazmdGjR+Pn58ecOXPw9/ev7iZVKYvVhJveWOXHPXToELt37yY/P5/mzZszbNgwdDodS5cu5dq1a2g0Gho1asTgwYMJDAzEarWyefNmTpw4gdlspn79+gwYMICWLVtisVhYvnw5Fy5cwGKx0L9/f7p3737TcyclJbFr1y5lhtKwYcNuWaNGCCGEEEIIIX4Pq82MXmeo7mbcE1JDRfwhBoOBhIQElixZ4nKDKQAlxVVfi+XSpUts2LCBOnXq0K9fP9LT09m0aRMArVq1YvDgwURGRnLu3Dm++aZ0VPfIkSMcOnSIhg0b0rdvX65cuUJCQgJQukqTh4cHrVq1uuW5L1++zKZNmwgICKBPnz6cPHlSOUdNlZ+fX91NELcgGamb5KN+kpH6SUbqJvmon2Skfn8ko9oymAIyoCLEPXPu3DkAunTpQteuXWnUqBEnT55Eo9EQExND69atadmyJVC6LBj839LWAQEBBAcHo9frlerXBoOBuLg4QkNDb3nuw4cPAxATE8MDDzxAs2bNSEtLU5YWE0IIIYQQQgjx+0hRWiGc8PCo2lFVq82s3F5z/vx5GjduTHZ2NgC5ublotVo+/vhjoHQZr4EDBwLQsWNHTp8+zYEDBzhw4AAeHh4MHz78d58/NzcXgLp16yr/2u12rl+/XmNnGDlbVk2oi2SkbpKP+klG6icZqZvko36SkfpJRpWTARUhnNDrjcR/WXVFaV/8n29o27YtycnJyn9lqyPp9Xp8fX0ZM2YMFy9eZMeOHezZs4fhw4dz4cIFTp06Rfv27QkNDWXjxo2sX7+ep59+WpnFUlvZ7fbqboK4BclI3SQf9ZOM1E8yUjfJR/0kI/WTjCont/wIcY/o9Xr+/Oc/85e//IXnnnuOpk2botfr8fPzw2AwEBISQq9evfDx8eGnn34C4KeffsJmsxEZGUm7du1o3Lgxly9fpqioqNJzORwOrFYrNpsNQFlOOi8vT/lXq9Xi4+NzF3sshBBCCCGEEK5LBlRUIiYmhpMnTwJQXFzMhAkT+Nvf/qa8Ia5K8fHxzJ49u8qP+3utXbuWyMhIhg8fzuDBg3nmmWe4evWqsv3pp5/m/Pnz1djCqmW329m6dStXrlzhxx9/5MyZM0RGRpKWlsaWLVs4dOgQW7du5fr16wQEBADg5+cHwJ49ezh48CAXLlzAw8NDuX0oJSVFqc1y8eJFUlJSMJvNXL9+nbfffpuvvvoKgIiICAC+//579uzZw6+//kq7du3Q62vuJDWzueoLB4uqJRmpm+SjfpKR+klG6ib5qJ9kpH6SUeVq7rspF5WXl8czzzxD+/btmTp1qsvf1tG9e3fmzp2Lw+Fg0qRJzJs3jxkzZgCwYMGCam5d1dJoNJw7d0653ScqKooHH3yQM2fO8MsvvyiPh4aGMmDAAADuv/9+srKyOHnyJGfOnCEgIID+/fsrPxdlK/4AHDt2jGPHjhEcHFzh3I0bN2bw4MHs3r2bc+fO0bp1a2Jjq+6WJiGEEEIIIYSobWRARUWys7OZPHkyMTExTJw4UXn866+/ZtmyZdhsNry9vZk+fTrBwcGsXbuWhIQEjEYj58+fp379+rz33ns0aNCA+Ph4ioqKmDJlCkCF78ucOHGCGTNmUFxcjMlk4pFHHuHJJ58EYOzYsYwfP56+fftW+P6zzz5j06ZN2Gw2jEYj06dPp02bNgCEhYXxyiuvsG3bNnJzc5k8efIt37xrNBqioqLYuXOn8lhMTAzz588nNDT0pue7cOECo0eP5sCBAwAVvlcTjUbDs88+W+Hx0NDQm67Uo9frGTZs2E2POW3atNveFhUVRVRU1G22Vv1q8uya2kIyUjfJR/0kI/WTjNRN8lE/yUj9JKPKydVRkZdffpknnnii3GBKUlISW7Zs4csvv8RgMJCYmMjUqVNZsWIFAMnJyaxbt47g4GDmzZvH22+/zdy5c2/7nE2aNGHRokUYDAYKCwuJi4ujZ8+ehISEVLrfiBEjGD9+PAB79+5l2rRprFy5Utnu7e3NmjVrSE5O5uWXX77lgIrZbGbXrl0MHjz4D52vJrBarRQXFwOlgyvu7u5oNJpy9VA8PT2xWq3Y7XZlSeOy4rVarZaSkhLla4PBgFarrbC/3W7HbDYrBaTc3d2Vr/8/9u48PKry7v/4+8xM9h0MJOwkBkgIqyKrGMKWIBBl62MLVvSHrVbFSi9RtI/4VK1bWxW1WPV50Cq1LoGwJSCryBICyhIEIoQkgBCWhGQmy+y/P3LNKSFDQAzkzvh9XZcXk5k559zf+ZAgX+5z354peyaTCYPBgMlkanC82+2mtrZW37I5KCgIp9OJ2+3GbrcD4Ofnh6ZpGI3GZqvJbrdjMBh8qiZfy0nTNKxWq0/V5Es51dTU4HA4fKomX8uptrZWP95XavK1nJxOJ1VVVT5Vky/lZLVa8ff396mafC0nq9WKw+HwqZp8Laeqqir9vb5Sk+f4sLAwfippqCjktttuY9WqVfzXf/0Xbdu2BerWvDh48CBTp04F6hYb9SwsCnDTTTfpt3hMnTqVCRMm/Khr1tbWMn/+fA4dOoSmaZw+fZqDBw9etqGSn5/PO++8Q0VFBZqmUVRUVO91T2Okb9++nD59GqvVSkBAQIPzbN26Vd/NJj4+nvT09Ku6XktgMpm8ftNe/JzRaLzkOfz8/K7oeG/vA7xm4G1MoaGh9b72dKa9bZvWXDUZDAaMRqNP1eThKzU5nU79nL5S04Vaek2BgYENztXSa/KmJdcUHh7u9TwtuSZfyykoKOiS52ipNflSTsHBwRiNRp+q6cLjfaEmT0ae432hpouPb+k1RUVF1TvGF2pqikaKhyxKq5D/9//+H5MmTeLuu++mtLQUqGugTJ48maysLLKysli2bFm922IuxWg01tviyvOvxBf761//SnR0NEuWLGHZsmX07t1bf++lzmGz2Zg9ezbz5s1jxYoVvPfeew0WK/J8M3l+c3u6hRcbMmQIWVlZbNq0CU3TeP311xu8p7HrmUwmvbvZWJ3C91xupyPR/CQjtUk+6pOM1CcZqU3yUZ9kpD7JqHHSUFHMb37zG+688069qZKamkpWVhanTp0C6v7FNz8/X3//N998o8/W+OKLLxg0aBAAnTt3Zv/+/bhcLiwWyyWbMGazmZiYGEwmEwUFBezcuVN/rVOnTuzbtw+Aw4cPc+DAAaCuweFwOIiNjQVg8eLFP7nu0NBQnn32Wf71r39x+vTpeq81dr0bbrgBu92u73SzYsWKnzwWIYQQQgghhBDicuSWHwX99re/xe12c/fdd/Phhx/y6KOP8sADD+B0OrHb7aSlpZGcnAxA//79eemllyguLtYXpQUYPXo0q1atIj09nXbt2tGzZ0+v13rggQd4/PHH+fzzz+natWu9RUtnzZrF7NmzWbduHUlJSSQlJQF1zY9HHnmEKVOmEBkZ2WS7xfTo0YO0tDTeffddnnrqKf35xq5nMpl46qmnmDlzJq1atSIlJaVJxiKEEEIIIYQQQjRGc194v4RoUTIzM9m4ceOPWoRWXLkFHzfdtsIP/2p1k51L1LlwfQ6hJslIbZKP+iQj9UlGapN81CcZqU8yapzMUBHCC4fD2qRNEIfThsnor3+dnZ3N/v37qaqqIiEhgV/+8pcAnDlzhmXLlnHy5EkiIyNJT0/XFwjevn0727dvx2KxEBYWxqBBgxg4cCAA7733HmfOnMHlchEdHc3YsWPp3LkzbrebdevWsWfPHmpqaoiMjCQlJUWf4XSxnTt38tVXX1FTU0N8fDwTJ04kODi4yT6HpiS9YPVJRmqTfNQnGalPMlKb5KM+yUh9klHjZA2VFmzSpEkyO+Uaqa21N+n5LmymeHi7DeuLL77g7NmzjBkzBoPBwGeffUZtbS3nzp1j9erVaJrGmDFjcDqd5OTkUFFRAUCHDh1IS0tj+PDhnDp1imXLlgFQWFjIli1bCAsLY/To0ZjNZrKysnA6nQ2uffLkSVauXEl0dDQpKSkUFBSwerW6M2s8W6AJdUlGapN81CcZqU8yUpvkoz7JSH2SUeOkoSKEF9e6E5uens7gwYPrPXfy5ElKS0tJTk7mlltuYfDgwVitVr777jt9POHh4cTFxREaGorRaNS3GBs7dizdu3cnLi4Ok8mEpmn16oiKiiI+Pp6AgAD8/f311y+0e/duAFJTUxk6dCgdO3YkPz//kjs0NTfplqtPMlKb5KM+yUh9kpHaJB/1SUbqk4waJ7f8COFFYKD3vdWbwsW3/3icP38eqGuaXPhreXk5/fv3Z+TIkaxbt4633noLTdPIyMggJCQEqNsu2rMgcWBgIBMnTgQgPj6eAQMGkJeXx3fffYfJZOKuu+7CYGjYS/V2fZfLRUVFBa1bt27Kj0AIIYQQQgghWjxpqAjhhZ9fIP/7wZhrcu57f73mit53YTe4qqqKHTt2EBMTw2233camTZtYtWoVXbt2JTw8HH9/f6ZPn87Zs2dZu3YtGzZs4Ne//jXnzp1j7969xMfHc9NNN7F69WqWLl3KQw89hL9/w6ZOSxIUFNTcQxCXIRmpTfJRn2SkPslIbZKP+iQj9UlGjZNbfkQ9qampFBQUNPcwfpYiIyMBqKysBMBsNgN1t+sUFRVhNptJTEykR48eJCYmYrPZOHbsGAAGg4H4+HgGDhxI+/btKSoqorq6mkOHDmG1WunduzeJiYnExcVhNps5c+YMbrcbh8Ohr6dy8fUrKysxGAxERERc18/hSnlbB0aoRTJSm+SjPslIfZKR2iQf9UlG6pOMGiczVIRoBgUFBZw+fRqoa1x88803dO7cmbZt25Kfn090dDQ7d+7E39+fpKQkysrKANi7dy+hoaHs27cPgNatW3P48GH2799Px44dqays5NixY4SEhBAUFERUVBRQt3uP3W6noKAAo9FIVFQUFRUVvP766/ouQ3369GHHjh2sX7+euLg4jh07Rq9evfR1WlQj93OqTzJSm+SjPslIfZKR2iQf9UlG6pOMGqfm35SEUl566SV27NiB3W4nKiqKF154gfbt23P8+HEmT57MtGnT2Lx5M7W1tbz66qt88skn7Nmzh8DAQN5++22io6PJzMxk+fLlBAQEUFJSwg033MArr7xC27ZtWbBgAdXV1cydOxeg3tcLFizg6NGjmM1mjh07RqdOnXj99dcJCgrCbDYzb948vv/+e9q2bUvbtm1p3bq1fh6Vbd26leLiYgBKS0tZvnw5GRkZTJo0ieXLl7NmzRoiIiKYOnUqgYGBtGvXjjFjxrBjxw5WrVpFWFgY6enpxMTEcOLECU6cOEF+fj5Go5FOnToxatQoNE0jMTGRIUOGsG/fPrKzs4mKiiI9PZ3g4GBsNlu9MbVr145x48axefNmiouLSUhIYOzYsc3x8VwRu91OYGBgcw9DNEIyUpvkoz7JSH2SkdokH/VJRuqTjBonDRVxWbNmzdKbFJ999hmvvvoqf/vb34C6hUxvuukm5syZw3vvvcc999zDP//5T5577jnmz5/PRx99xO9//3sAdu3axdKlS4mLi+PNN9/k+eefv6Jtn/Pz8/n8888JCwvjvvvuY/ny5UybNo233nqL8PBwcnJyOH/+PJMmTVK6AXChKVOmEBgYiKZpVFdX688HBwczffp0XC6XvruO1WoF4OabbyY5ORmou8XH398fp9NJeHg4M2bM0I93uVzYbDb9lqGUlBSGDx8OoDdRampqCAoK4umnn6a6ulp/b//+/enXrx+1tbW43W6cTqd+W5Db7cZur9tO2s/PD03TMBqN1NTUAKBp2iVrcjgc9WryrN9iMBj0rdg8NRkMhgbHe2pyuVxA3cK7NpsNq9Wq12QymTAYDJhMpgbHu91uvSaouxdUxZo8j32lJrvdrv/+9ZWafCkni8XiczX5Wk4XPucrNflaTna7naqqKp+qyZdyslgsPleTr+Xk+bPIl2rytZw8GflSTZ7jw8LC+KmkoSIu66uvvmLx4sVUV1c32EI3ODiYlJQUAHr27ElMTAyJiYn611u3btXfe9NNNxEXFwfA1KlTmTBhwhVdf9iwYfrOM71796akpASA3Nxcnn76aaBu/Y9Ro0ZdfZHXWWhoqP744m9ko9F4yeP8/BruPuTteG/vAwgICLjs8RePD9Bv+/HWnfZ2/PWoKSQkhICAAJ+qycNXaqqtrdVr8ZWaLtTSazIajQ3G0NJr8qYl1xQREeH1+i25Jl/LKTg4+JL/cttSa/KlnDw/63yppguP94Wa/Pz89Ov5Sk0XH9/Sa4qKiqp3LV+oqSkaKR7SUBGNOnHiBH/+85/5/PPP6dixI9988w1/+MMf9Ncv3CnG0/XzMBqNV7SIkdFo1Lua8J8ZGR4XfmMajcYGr4ufJ03TmnsI4jIkI7VJPuqTjNQnGalN8lGfZKQ+yahxssuPaJTFYsHPz4/o6GhcLheffPLJVZ/rm2++oaioCIAvvviCQYMGAdC5c2f279+Py+XCYrGwcePGKzrfLbfcQlZWFlC3sOu6deuuemyi5WmsEy3UIBmpTfJRn2SkPslIbZKP+iQj9UlGjZMZKqKBmTNn1vvGSUtLY9y4cURFRXHbbbexc+fOqzpv//79eemllyguLtYXpQUYPXo0q1atIj09nXbt2tGzZ88rOt/vfvc7nnzySdLS0oiOjiY5ObnB9DHhu2pqapp0up5oepKR2iQf9UlG6pOM1Cb5qE8yUp9k1DjNLfsgiesgMzOTjRs3XtEitFfKbrfjcrkICAjAYrFw11138eSTTzJkyJAmOf//fjCmSc5zsXt/veaanPfnxmw2yw93xUlGapN81CcZqU8yUpvkoz7JSH2SUeNkhoposSorK5k1axZOpxOr1cr48eObrJlit1uvWePD4bRhMvrXey47O5v9+/dTVVVFQkICv/zlL6mpqSEzM5OTJ09itVqJiYnRZ/EAbN++ne3bt2OxWAgLC2PQoEEMHDiQc+fOsWLFCkpLS3E6nXTo0IHbb7+dVq1acezYMdasWcOZM2cAiIuL4/bbbyckJMTrWDdu3EheXh52u52kpCTGjx+vLxrV3OR+TvVJRmqTfNQnGalPMlKb5KM+yUh9klHjZA0VcV1MmjSpSWenALRu3ZrMzEyysrLIycnhoYcearJza9q1u1fw4maKx8W3OlmtVsxmM0OHDmXo0KEcP36czz77DIBz586xevVqNE1jzJgxOJ1OcnJyqKiowGw243a7SUlJoW/fvhQWFrJ8+XL9uODgYEaNGkVCQgIHDhxg7dq1Xsdz4MABNm3aRNeuXRk4cCB79uxh8+bNTfhJ/DSX2lVBqEMyUpvkoz7JSH2SkdokH/VJRuqTjBqnxj81C6GY692JTU9P5/z58+zYsUN/Ljw8nN/85jf6WAoKCjh58iR2u13ftz08PJy4uDh2795NdXU1JpOJjh07cs899+jn2bdvH6dPnwagV69e9O3bV3+cn5+vv3axPXv26GMLCQlh79697N69mxEjRjR5/VdDuuXqk4zUJvmoTzJSn2SkNslHfZKR+iSjxskMFSG8cLsc1+1aTofN6/MGg0H/AXb+/HnOnj1LbGwsfn5+3HDDDYwcOZKSkhLeeustTp06xYQJEwgJCam3oPAPP/xATU0NnTt3Buqv0n3kyBEA/bWLlZeXYzAY9NuBwsPDqaysvKKtsK+H6urq5h6CuAzJSG2Sj/okI/VJRmqTfNQnGalPMmqczFARwguTXwCf/l/adbnWtJk5jb5usVhYvHgxRqORO+64A4Cqqip27NhBTEwMt912G5s2bWLVqlV07dqV8PBwAM6ePcu//vUvIiMjSU9Pr3fOkpISsrKyiI2NJSUl5ZrUJYQQQgghhBC+TGaoCKEws9nMokWLMJvNzJgxgzZt2gBQVFSE2WwmMTGRHj16kJiYiM1m49ixYwCcOXOGRYsWYTQaufvuu+utzF1cXMzHH39Mq1atmD59Ov7+dWu6uN1uHA4HLpcLgKioKFwuF1VVVUDdIsDh4eGyF70QQgghhBBCIA2VZpGamkpaWhoZGRmkpaXx9NNPY7fbr9n1ZsyYwYYNG676+NzcXPr06UNGRgYZGRlMmDCBVatWXdGx3bt31/9CPmvWLEpKSoC6bZSPHj161WPyNQUFBeTn5wN1jYtvvvmG0tJSFi1axLlz5+jfvz9lZWXk5+djs9mIiooCYO/evXzzzTfs27cPqFuot6Kigg8++IDq6mpuvvlmTpw4oZ/75MmTfPzxx7hcLvr3709hYSGHDh0C6hotzz//PDk5dTNm+vTpA0BOTg7r1q2jsrJSf04FwcHBzT0EcRmSkdokH/VJRuqTjNQm+ahPMlKfZNQ4ueWnmbzxxht069YNp9PJr371K7788kvGjRvX3MO6pPj4eDIzMwE4fPgwU6dOJS0tDYPhynty7777rv54yZIlREVF0bVr1yYfa0u0detWiouLASgtLWX58uVkZGRQVlamv+4xe/Zs2rVrx5ilXDCjAAAgAElEQVQxY9ixYwerVq0iLCyM9PR0YmJiKCoq0ptY69at049LTk6mtLRUb955mmIRERF07969wZgSExMZPnw4eXl5OBwOevfuza233nptPoCr4HA4ZLaM4iQjtUk+6pOM1CcZqU3yUZ9kpD7JqHHSUGlmVqsVq9Wqr3uxbds2XnvtNaxWK06nk9/+9rfcfvvtQN1Mk+TkZHbv3s3p06dJT0/nD3/4A1DX5HjyySepqamhR48elJSU8MADDzTYkWXlypX87//+L2+99RZ5eXl8+OGH+l+w586dy+DBgy87ZrPZTGhoqN5MKSws5IUXXqC8vBy73c6vf/1rJk+e3OC41NRUFi5cyL59+8jPz+e5557jtddeY+7cuezatYvq6mrmzp0LwIIFC/SvFyxYwNGjRzGbzRw7doxOnTrx+uuvExQUhNlsZt68eXz//fe0bduWtm3b0rp1a/08LcWFu/JcyLMjjzeDBw/2mleXLl145plnLnm+S53T23EjRoxQZlefi3luTRLqkozUJvmoTzJSn2SkNslHfZKR+iSjxklDpZk88sgjBAQEUFJSwrBhwxg2bBgASUlJ+gKkZ8+eZdKkSQwbNoyIiAjgP7dsVFVVMWrUKKZMmUKXLl14/PHH+fWvf01GRgb79u1j2rRpDa757rvvsmXLFhYtWkRYWBjDhg1j/PjxaJpGYWEh99xzD1999ZXX8R45coSMjAxsNhsnTpzg5ZdfBuo6ln/4wx945ZVXiI+Px2KxMHnyZPr27Ut8fLzXc02ePJmlS5dy77336n9Z37VrV6OfV35+Pp9//jlhYWHcd999LF++nGnTpvHWW28RHh5OTk4O58+fZ9KkSYwdO/bKQlCI2WwG6qbUedYxcTjqdhryrHFiMBiora3VH/v7+2MwGOqtvB0cHIzL5cJms+k//AIDA/XHNlvdjkImkwmDwYDJZGpwvNvtpra2Vt+aOSgoCKfTidvt1ptvfn5+aJqG0WikpqYGqNtSLTAwEE3TGpzzWtRUXV2NwWDwqZp8LSe73a43Xn2lJl/KqbKyEofD4VM1+VpOnox8qSZfy6mmpgaXy+VTNflSThaLBX9/f5+qyddyslgsOBwOn6rJ13I6f/68/l5fqclz/IXrTF4taag0E88tP1arlYcffphFixZxzz33UFZWxrx58yguLsZoNFJRUcHRo0f1WQWe22zCwsKIj4+npKSEG264gYKCAiZMmABAr169GtzCsWDBAtq1a8c//vEP/TfYsWPHmDNnDqWlpZhMJs6ePcuZM2eIjo5uMN4Lb/k5cuQIM2bMoF+/fpjNZo4cOcJjjz2mv9dut1NYWHjJhsrVGDZsmD6Lp3fv3vpaLLm5uTz99NMAREZGMmrUqCa75vV04TdzY1Pq/Pz8Gj3Wc7y39wEEBARc9niA0NDQel+bTHU/KgIDA6/oeG9jupSrrcnf35+AgACfqsnDV2oym816Lb5S04Vaek0ul6vBay29Jm9ack3BwcFer9WSa/K1nPz8/AgJCfF6fEutyddyMhqNPleT53hfqcnzqy/VdOHxLb2m0NDQBt9TLb2mpmikeEhDpZkFBASQkpLCxo0bueeee5g/fz6pqam8+eabaJrG2LFjsVqt9d7vYTQacTqd+teapl3yOn379mXLli388MMPdOnSBYDHHnuMJ554glGjRuFyuejTp0+9a11KfHw87du355tvvuHGG28kKiqKrKysq6j+P4xGY73pZBeP4+K6r2Scwrd5GoNCXZKR2iQf9UlG6pOM1Cb5qE8yUp9k1DjZ5aeZuVwu8vLy9CaH2Wymffv2aJrGli1b9IVKGxMaGkpCQgIrVqwAYP/+/RQUFNR7z6233sr8+fO5//77+f777/VrdejQAYAvvvhCn6J1OaWlpRQVFdGlSxe6du1KYGAgS5cu1V8/cuQIFoul0XOEhITot7kAdO7cmf379+NyubBYLGzcuPGKxnLLLbfozZzKysp6i7AKIYQQQgghhBDXisxQaSaeNVTsdjsJCQn87ne/A2DOnDk8++yzLFiwwOutO5fy0ksvMW/ePP7xj3/QrVs3unXr1mAq0+DBg/nzn//MAw88wBtvvMGTTz7Jgw8+SEREBLfeeiuRkZGXPL9nDRW3243D4WD27NkkJiYCsHDhQl544QXef/99XC4XrVu35rXXXmt0vL/4xS948cUXef/995k7dy6jR49m1apVpKen065dO3r27HlFdf/ud7/jySefJC0tjejoaJKTkxtMIRO+6cfsMCWah2SkNslHfZKR+iQjtUk+6pOM1CcZNU5ze1aDES1aVVUVwcHBaJrG4cOHmTFjBjk5Ofpitr7KbrfjcrkICAjAYrFw11138eSTTzJkyJCffO5P/y/tqo91uoyUlnXFXBOFG41A/yq6tN3v9fnHn/gLAO+99x5nzpzB5XIRHR3N2LFj6dy5MwAHDx5kzZo1VFZW0qFDBzIyMoiKivJ67Y0bN5KXl4fdbicpKYnx48fr9yX6ErPZ3KT3P4qmJxmpTfJRn2SkPslIbZKP+iQj9UlGjfO9v2X9TH377be8/PLL+mrJf/rTn3y+mQJ1t/nMmjULp9OJ1Wpl/PjxTdJMcditTJuZc9XH//vf/6byxCEGDhxIdHQ0x44dIyPjL16fdzpsGE3+dOjQgZtuugmLxcKGDRtYtmwZDz/8MBaLhc8//5zo6GhGjx7N+vXrWbp0KTNnzmxw3QMHDrBp0yZ69uxJVFQUX3/9NREREcpufSyEEEIIIYQQLZU0VHzEhVsv/5y0bt1a332oKVltDkx+DVepvhLl5eUcPHiQXr16MWrUKDRNo3///pd83mPs2LHU1NRQXl7O5s2b9UWG9+3bh9PpZNiwYfTs2ZMffviBvXv3UlZWRqtWrepde8+ePQCkp6cTEhLC3r172b17t082VGT6ofokI7VJPuqTjNQnGalN8lGfZKQ+yahx0lARwoufspr1mTNnAPjhhx944YUX0DSNgQMH6rfvXPz86NGjgbqdjV555RWgbsuwiRMnAnD+/HkAfdtoz6/l5eUNGirl5eUYDAZ9C8fw8HCOHz+O0+lsdDuxlkhWHFefZKQ2yUd9kpH6JCO1ST7qk4zUJxk1TtpNQnhh0K5uaSGnw4bD4QDAZrMxZcoUOnXqxNatW/VdlC5+vrCwEKj7YTV9+nTS0tJwOBxs2LDB6zVk2aM60i1Xn2SkNslHfZKR+iQjtUk+6pOM1CcZNU5mqAjhhdHkz6r3x/3o48bdt0pfLLZz584kJiZSVVXF0aNH9ZkmFz9fVlZGXFwcBoOB+Ph44uPjOXDgAEVFRVRXV+u7L1VWVgLo201HRUXhdrtxOp0YDAYMBgNRUVGcPn2aqqoqQkJCqKysJDw83OdmpwBUV1fLAlmKk4zUJvmoTzJSn2SkNslHfZKR+iSjxklDRdSTmpqKv78/AQEBWK1Wbr75Zp555hn8/Pya/FpPPPEEycnJTJ8+/YqPmTFjBvfee6/Sa4LExMTQpk0bCgsL2bVrF7t370bTNBISEti3b1+D5zt16sThw4fZv38/HTt2pLKykmPHjhESEkJQUBDJycmsW7eOLVu2YLFYOHjwIJ06daJVq1YUFRXxwQcfMGDAAMaNG0efPn04dOgQOTk5REZGUllZya233trcH4kQQgghhBBC+ByZvyMaeOONN8jKymLlypUcPnyYL7/8srmH1KJomsbkyZNp1aoV2dnZ1NTUcOedd9K2bVuvz7dp04agoCBOnDhBdnY227dvp1OnTtx1111omkZYWBiTJ0+mtraWL7/8kpiYGDIyMrxeOzExkeHDh3PkyBFyc3Pp3bu3NFSEEEIIIYQQ4hqQGSrikqxWK1arlfDwcGw2G3/729/Iy8vDZrPRvXt35s+fT0hICE888QT+/v4UFRVx6tQp+vbty0svvYSmaZSWlvL4449z9uxZOnbsCNTtSHTxrJTt27fz/PPP85e//IU//elP9WahXGpWysXPqzR7pU2bNtx3331X/Hz79u158MEHL3m+xMREEhMTGzzfpUsXnnnmmXrPjRgxQonP4FoLDg5u7iGIy5CM1Cb5qE8yUp9kpDbJR32Skfoko8ZJQ0U08MgjjxAQEEBJSYm+HfPbb79NWFgYn3/+OQCvvPIK//jHP/j9738PwPfff8+iRYvQNI0777yTrVu3MnToUJ577jkGDhzIgw8+yIkTJ5gwYUKD7Z2XLVvGBx98wHvvvUfbtm2ve71NzWq14na7sdvtAPj5+aFpGkajkZqaGqBuFktgYCCaplFdXa0fGxwcjMPhwOVy6YvbelbWNhgM1NbW6o/9/f0xGAwNjne5XNhsNlwuF1C3Y5DnsWdhXJPJhMFgwGQyNTje7XZTW1urL34bFBSE0+lUriar1Yqfn59P1eRrORmNRn39Hl+pyZdy8nwP+VJNvpZTVVWV/j3kKzX5Wk6eP/N9qSZfyslutxMREeFTNflaTna7HT8/P5+qyddyqqio0Jd/8JWaPMc3xdow0lARDbzxxht069YNq9XKww8/zKJFi1i/fj0Wi4XVq1cDdd8sPXr00I8ZNWoUAQEBACQlJVFSUsLQoUPJzc3l6aefBupmYQwePLjetTIzMwkICOCDDz4gNDT0OlV4bXk+h8DAwAavefumvfi5xhaQ9baWjbfjL7XmjWdslxvTxVmYTHU/KlSqyWazERAQ4FM1efhKTVVVVXotvlLThXyhJs8W6x6+UNPFWnpNF2cELb8mb1pqTW6322tG0HJr8qWcPE1JX6rpwuN9oSbPRgqe432hpouPb+k1BQQE1Ps55ws1NeUiu9JQEZcUEBBASkoKGzduxO1288wzzzRoiFz4Xg+j0YjT6byia3Tv3p2dO3dy5MgR+vTpox/v6XJC3YwPb670fcI3XZi9UJNkpDbJR32SkfokI7VJPuqTjNQnGTVOFqUVl+RyucjLy6NLly6kpqayaNEifcqUxWLhyJEjlz3HLbfcwpIlSwA4efIk27dvr/d6z549WbBgAX/4wx/YsWMHAJ06dWLfvn0AHD58mAMHDng995W+TwghhBBCCCGEaGoyQ0U04FlDxW63k5CQwO9+9zuCg4N58803mTJlCpqmoWkaDz30EPHx8Y2e66mnnuLxxx9n+fLldOjQgd69ezeY4tWjRw8WLlzIAw88wB//+EdmzZrF7NmzWbduHUlJSSQlJXk995W+T/gmb1MChVokI7VJPuqTjNQnGalN8lGfZKQ+yahxmtuzGowQ10BtbS0mkwmTycTp06eZMmUKixYtIi4urrmHdlmr3h/3o48Zd9+qazAS4Y3VavV6n6ZQh2SkNslHfZKR+iQjtUk+6pOM1CcZNU5mqIhrqqioiLlz5+J2u3E4HDz00EMtopnidFivqjnidNgwmvyvwYgu7dy5c6xYsYLS0lKcTicdOnTg9ttvp1WrVhw8eJA1a9ZQWVlJhw4dyMjIICoqCoCdO3fy1VdfUVNTQ3x8PBMnTtS3RSsuLmbNmjWUlpYSGBjIsGHDGDRoEDU1NSxfvpyjR4/idDqJiYlh3LhxxMTENBiXy+UiOzubffv2oWka/fr1Y/To0Wiadl0/HyGEEEIIIYS4FmQNFXFN9ejRg6ysLJYtW8aqVauYNm1acw/pilTX2K7quOvdTAEwm8243W5SUlLo27cvhYWFLF++HIvFwueff05AQACjR4/m5MmTLF26FKhbz2blypVER0eTkpJCQUGBvoOTxWLh448/pqqqijFjxjB06FC9CbJ161YOHDjAjTfeyMCBAzl27Bhr1qzxOq7c3Fx27txJ7969SUxMZNu2bezevbvJ6vZsyybUJRmpTfJRn2SkPslIbZKP+iQj9UlGjZMZKkK0cB07duSee+7Rv963bx+nT59m3759OJ1Ohg0bRs+ePfnhhx/Yu3cvZWVlemMjNTWV9u3bU1BQQH5+PhMmTCAvLw+73c7EiRPp2LFjva3GPHcIxsbGEhMTw9dff33J+yr37NmDv78/aWlpuFwu9u7dy+7du+nXr9+1+zCEEEIIIYQQ4jqRhooQXgQHXv+ZJlfDddEtRj/88AM1NTUkJiZy/vx5AMLDw+v9Wl5e7vU1l8tFRUUFZ86cASA7O5uzZ88SERHBHXfcQZcuXRg6dCglJSV8+eWXAERERJCWluZ1bOXl5YSGhmIwGDAYDAQFBVFeXt5ktXv2qxfqkozUJvmoTzJSn2SkNslHfZKR+iSjxsmnI4QXRr8Avnr39uYexmUNn7VSf3z27Fn+9a9/ERkZSXp6Ol9//XW9917p+tNOpxOAmJgYbrvtNpYvX05mZiaPPfYY33//PceOHWPQoEG0adOGFStWkJ2dzS9+8YumK+oKGQxyx6LqJCO1ST7qk4zUJxmpTfJRn2SkPsmocfLpNLHs7GzuuOMOMjIySEtLY86cOdft2mvXrmXv3r3X/DoVFRU89thjjB8/ngkTJpCRkcG2bdsue9wTTzzBRx99dNn3ZWZmcvTo0aYY6s/GmTNnWLRoEUajkbvvvpuwsDAiIyMBqKysBOrWWgGIiopq8FplZSUGg4GIiAj9tT59+pCcnEybNm0wm804HA7y8/MBGDx4MP369SMiIoIjR44AdYvQOhwOXC6Xfh2LxaI/X11drS+I2xSkW64+yUhtko/6JCP1SUZqk3zUJxmpTzJqnHw6Tej06dM8++yzLFmyhNjYWNxuNwcOHLhu11+7di3Jycn07t37Rx/rdDoxGo1X9N7XXnuNtm3b8pe//AVN0ygvL6empuZHX/NSlixZQlRUFF27dm2yc/qyiooKPvjgA6qrq0lNTeXEiROcOHGC5ORk1q1bx5YtW7BYLBw8eJBOnTrRqlUr+vTpw44dO1i/fj1xcXEcO3aMXr16YTKZ9Nd27NhBWVkZp06don379phMJr3ZsmHDBm644QbKy8v1HX727t1LVlYWo0ePZsiQIfTp04c1a9aQk5OD0+nE5XLRp0+fJqu7urqasLCwJjufaHqSkdokH/VJRuqTjNQm+ahPMlKfZNQ4aag0obNnz9b7S6emaSQlJQFw/PhxJk+eTG5uboOvPY+nTZvG5s2bqa2t5dVXX+WTTz5hz549BAYG8vbbbxMdHc2hQ4d49tlnqampwWq1Mm3aNO655x42b97M+vXr2bp1K5999hkzZ87kjjvuYMmSJSxevBin00loaCjz588nLi6OzMxMli1bRkhICMXFxbzyyits27aNlStX4nQ6CQgIYP78+SQmJjao89SpUwwcOFDf+SUqKkqfeWCz2fjb3/5GXl4eNpuN7t27M3/+fEJCQuqdY9u2bbz22mtYrVacTie//e1vuf322/niiy/Iz8/nueee47XXXmPu3Lm0bt3aa81QN+vF39+foqIiTp06Rd++fXnppZd+VlvzlpeXU1VVBcC6dev055955hkmT57Ml19+yZdffkn79u3JyMgAoF27dowbN47NmzdTXFxMQkICY8eO9fpa586dGTduHAApKSlYLBYOHTrE/v376dSpE+np6V7Hdcstt3Du3Dl91tSgQYNkQVohhBBCCCGEz9DcV7qwgrgsl8vFQw89xK5duxg4cCD9+/cnIyODqKioyzZURo4cyTvvvENKSgrvvfceCxcu5J///CeJiYnMnz+fiIgIfv/732OxWPD398ff35+qqiqmTp3KggULiI+P54knniA5OZnp06cDsHPnTv7xj3/w5ptv4u/vz6ZNm/j73//OJ598QmZmJn/605/IysqiU6dOAJSVldGqVSugbnvc1157jU8//bRBndu2beORRx6hc+fO9OvXj9TUVAYPHgzA22+/DcCDDz4IwCuvvILJZOL3v/99vfFVVFQQGhqK0Wjk7NmzTJo0ieXLlxMREcGMGTO49957GTFiBMBlay4uLmbRokVomsadd97JvHnzGDp06E/Os6WtofJzYzabpVuuOMlIbZKP+iQj9UlGapN81CcZqU8yapzMUGlCBoOBt99+m4KCAvLy8li7di3vv/8+y5cvv+yxwcHBpKSkANCzZ09iYmL02SE9e/Zk69atANTW1jJ//nwOHTqEpmmcPn2agwcPEh8f3+Cc69ev5+DBg0ydOhWoW5TUs2YGQP/+/fVmCkB+fj7vvPMOFRUVaJpGUVGR17EOHjyYDRs2kJuby65du3j00Ue57777uP/++1m/fj0Wi4XVq1cDdTNWevTo0eAcZWVlzJs3j+LiYoxGIxUVFRw9epS+ffs2eO/lah41ahQBAQEAJCUlUVJS0iQNlZbCszYK1P0+crlc2Gw2fS2TwMBA/bFnH3mTyYTBYMBkMlFdXV3veLfbTW1trb6IbVBQEE6nE7fbjd1uB8DPzw9N0zAajfrtXpqmERgYiKZpDc7pWVvF4XAA4O9ftzORwWCgtrZWf+zv74/BYGhwvLeajEYjVqvVp2rytZz8/PywWq0+VZMv5eR0OjGbzT5Vk6/l5Ha79Z/xvlKTr+Xk5+dHVVWVT9XkSzk5nU79tmNfqcnXcvL8WeRLNflaTp6MfKkmz/FN0SiShso10K1bN7p168avfvUrxo0bx44dO+jdu3e9XVY8f8nw8IQO/wnbw2g06juv/PWvfyU6OpoXX3wRk8nEvffe2+BcHm63m8mTJzN79myvr194G47NZmP27Nl89NFH9OzZk9LSUoYPH37JGkNDQxk5ciQjR44kOTmZv//979x///243W6eeeYZfcbKpcyfP5/U1FTefPNNNE1j7Nixl6zjcjV7milQ/7P6ubj4B4HRaMTPz8/rey/8rC51PNTleyHPYlSBgYFXdLy3MV2Kt7FeSU2apmEymXyqJg9fqcnhcOhj8pWaLtTSa7owH4+WXpM3Lbkmz8+5i7XkmnwtJ7fb7fXa0HJr8qWcHA4HRqPRp2q68HhfqOnCP4t8paaLj2/pNYWGhtb7s8gXamrKGTeyy08TKi0t5dtvv9W/PnXqFGVlZXTo0IEbbrgBu91OcXExACtWrLiqa5jNZmJiYjCZTBQUFLBz5079tdDQ0HqzFVJTU8nKyuLUqVNAXZfes0vLxWw2Gw6Hg9jYWAAWL158yTF4FjmFuv+R+O677+jQoYN+zUWLFumdQIvFou8Cc3Ed7du3R9M0tmzZon8uUNfoubCOxmoWP1+e32NCXZKR2iQf9UlG6pOM1Cb5qE8yUp9k1DiZodKEHA4HCxYs4MSJE/rUp0cffVRfmPapp55i5syZtGrVSr+958d64IEHePzxx/n888/p2rUrAwYM0F+bOHEiTz75JDk5OfqitI8++igPPPAATqcTu91OWloaycnJDc4bGhrKI488wpQpU4iMjNQXKPXm0KFDvPjii/qMm86dO/Pf//3fANx///28+eabTJkyBU3T0DSNhx56qMEtSXPmzOHZZ59lwYIF9OrVi+7du+uv/eIXv+DFF1/k/fffZ+7cuY3WLH6+ZPkn9UlGapN81CcZqU8yUpvkoz7JSH2SUeNkUVohLkEWpVWbLJClPslIbZKP+iQj9UlGapN81CcZqU8yapw0VITwwumwYjQ1vAfwx9i9ezdZWVkNnp89ezaRkZFUVVXx1ltvUVNTw+jRoxkyZAgAJSUlrFy5knPnzhEdHc3EiROJjY1l48aNbNq0qcH5nnnmGa/X37hxI3l5edjtdpKSkhg/frzXe/FbKm/rPwi1SEZqk3zUJxmpTzJSm+SjPslIfZJR4+STEcILhxOMP/G7o3PnzkyePBmo21J72bJlBAYG6h3enJwcfSVq/boOB59++il+fn6MHTuWzZs38+mnn/Lwww+TlJTEDTfcAEB1dTXZ2dnExMR4vfaBAwfYtGkTPXv2JCoqiq+//pqIiAh9K2pf4HQ65Ye74iQjtUk+6pOM1CcZqU3yUZ9kpD7JqHGyKK0QXjTFxK2oqCiSk5NJTk7GZDLhdDrp168fRqOR77//noKCggbbO3///fdUVVVx8803M2DAAPr168f58+cpKiqiTZs2+vk8jZibb77Z67X37NkDQHp6OiNHjiQ8PJzdu3f/5JpUIpPr1CcZqU3yUZ9kpD7JSG2Sj/okI/VJRo2ThooQXvgZtZ90vMthq/f1rl270DSNm266CZvNxsqVKxk5ciQRERH13nf+/HkAwsPD6/1aXl6uv8ftdrNr1y4CAgLo1auX1+uXl5djMBj0rbHDw8OprKz0qS2lPfvUC3VJRmqTfNQnGalPMlKb5KM+yUh9klHjZO6OEF4Y/QL4duGEqz6+32+X64/LysooLCwkISGByMhI1q9fj5+fH/Hx8Rw8eBCou4WnpqamwXm8dYSLioooKyvj5ptvxt/f/6rHKIQQQgghhBDi6klDRYhrbNeuXcB/bs+prKzk7NmzvPnmm/p7tmzZgr+/P9HR0fp7oG5Vbai7fchj586dAPW2j3a73TidTgwGAwaDgaioKE6fPk1VVRUhISFUVlYSHh6O0Wi8hpVeX35+fs09BHEZkpHaJB/1SUbqk4zUJvmoTzJSn2TUOLnlR1xzqampFBQUNMm5cnNzmTRpktfX9u3bx5w5c5rkOk3F6XSye/duIiIiSEhIAOCWW25h6tSpTJ06VW+K9OnTh6SkJBISEggJCWHnzp3k5eXx7bffEhkZSZcuXQCwWCwcPHiQjh070qZNG/06xcXFPP/88+Tk5Ojng7qFb9etW0dlZaX+nK/QtJ92W5a49iQjtUk+6pOM1CcZqU3yUZ9kpD7JqHEyQ0X4jF69evGXv/yluYdRz4EDB6iurmbEiBH6D6N27drRrl07AGy2urVW2rRpo+/gM3XqVFatWkVOTg5t2rRhwoQJGAx1vc/du3fjcrkuuRitR2JiIsOHDycvLw+Hw0Hv3r259dZbr1WZzcKXZtv4KslIbZKP+iQj9UlGapN81CcZqU8yapzmlmV7xTWWmprKwoUL+frrr1m5ciVOp5OAgADmz57OsVwAACAASURBVJ9PYmIiAN27d+fRRx9l7dq1nD9/nueee46tW7eyefNmHA4Hr7/+OvHx8eTm5vL888/To0cP9u/fT1BQEC+++CI33ngjubm5vPTSS2RmZjbJuJtqDRVxbZjNZn0LaqEmyUhtko/6JCP1SUZqk3zUJxmpTzJqnMxQEdfNHXfcwb333gvA1q1beeaZZ/j000/118PDw/niiy/Izs7mwQcf5K9//Stz5szh3Xff5e9//zuvvvoqAIcOHeLpp5/m5ZdfZsmSJTz++ONN1kRpSp71T/z8/NA0DaPRqC88q2kagYGBaJpGdXW1fkxwcDAOhwOXy6VvjexZeNZgMFBbW6s/9vf3x2AwNDje5XJhs9lwuVwABAYG6o89M2JMJhMGgwGTydTgeLfbTW1trb4gblBQEE6nE7fbra/yrUJNNpsNq9XqUzX5Wk52ux2r1epTNflSThaLxedq8rWcLnzOV2rytZzsdjtVVVU+VZMv5WSxWHyuJl/LyfNnkS/V5Gs5eTLypZo8xzdFo0hmqIhrzjND5dSpU7zzzjtUVFSgaRpFRUXs27cPqJuhsm3bNlq1akVJSQkZGRl8++23AGzbto2//e1vfPrpp+Tm5vLHP/6RNWvWAOByuejduzfbt29n//79MkPlZ8RisRAaGtrcwxCNkIzUJvmoTzJSn2SkNslHfZKR+iSjxskMFXFduFwuZs+ezUcffUTPnj0pLS1l+PDh9d4TEBAA/Kd76GEwGPRuoxAegYGBzT0EcRmSkdokH/VJRuqTjNQm+ahPMlKfZNQ42eVHXDcOh4PY2FgAFi9efNXnKSkp0bcOXr58Od26dZOu6c+QrDiuPslIbZKP+iQj9UlGapN81CcZqU8yapw0VMQ153A4CAoK4pFHHmHKlClMmjSJ4ODgqz5ft27d+Oyzzxg/fjz//Oc/efnll5twtKKluPDeSaEmyUhtko/6JCP1SUZqk3zUJxmpTzJqnKyhIq6p06dPk56ezpYtW1rcdDFZQ0VtsuK4+iQjtUk+6pOM1CcZqU3yUZ9kpD7JqHGyhoq4Zj788EMWL17M3LlzW1wzxWm3/qSmiMthw2Dyv/wbBVA3i2nhwoWcO3eOAQMGMGLECDIzMzl58iRWq5WYmBjS09Np164dALW1tWRnZ1NYWIjL5SI2NpaZM2cC8O2337J582bMZjOdO3dm4sSJhIeH43a7WbduHXv27KGmpobIyEhSUlJITk72OqadO3fy1VdfUVNTQ3x8PBMnTvxJM6uEEEIIIYQQvkVu+RHXzN13301OTg7Tpk1r7qH8eIaf1muUZsqPs2nTJiorK/WvrVYrZrOZoUOHMnToUI4fP85nn32mv56VlcXBgwfp168faWlptGrVCoAffviBZcuWERYWxqhRoygqKmLlypUAFBYWsmXLFsLCwhg9ejRms5msrCycTmeD8Zw8eZKVK1cSHR1NSkoKBQUFrF69+hp/Cr5HGlBqk3zUJxmpTzJSm+SjPslIfZJR46ShIoQXsqvQ9VNaWsr27dtJSUnRnwsPD+c3v/kNgwcPJiUlhdjYWM6fP4/dbqe8vJyDBw+SlJTEqFGj6Nu3LxkZGQAUFxcDcNNNNzFw4EBiY2MpKCigurpa3+s+KiqK+Ph4AgIC8Pf397rQ1u7du4G6Lb+HDh1Kx44dyc/Pl98XP5J8XmqTfNQnGalPMlKb5KM+yUh9klHj5JYfIbzwk1bjdeG0W1m2bBkDBgzQb+eBuq2yPc6fP8/Zs2eJjY3Fz8+PM2fOAHWzUV544QU0TWPgwIGMHj1a76CXlJTQrl07zp07p58jPj6eAQMGkJeXx3fffYfJZOKuu+6qd60Lrwl1jR3Pry6Xi4qKClq3bn1tPgwf5HK5mnsIohGSj/okI/VJRmqTfNQnGalPMmqcNFSE8MLgF8DRBXc09zB8XvnQ/+b8+fNMnDiR0tJSoO52n6qqKkJCQrBYLCxevBij0cgdd9Tl4emS2+12pkyZQl5eHlu3biU+Pp6ePXuya9cu/T9//7pbr0wmE+fOnWPv3r3Ex8dz0003sXr1apYuXcpDDz2kv080LfkXDbVJPuqTjNQnGalN8lGfZKQ+yahx0lARzSY1NRV/f3/8/f2x2+3ce++9TJ06lXXr1rFz507mzp3b3EMU11hlZSXV1dUsXLhQf27v3r0YjUZGjBjBBx98QFVVFTNmzKBNmzZA3S07AO3btycxMZGqqiqOHj1KWVkZcXFxzJw5k9LSUgwGA6tXr6akpISoqCh27NiB1Wqld+/eJCYm8v333/Ptt99y5swZ2rVrh9PpRNM0jEYjkZGR+vjCwsKorKzEYDAQERFx/T8kIYQQQgghhJKkoSKa1RtvvEG3bt0oKChg0qRJDB8+nJEjRzJy5MjmHpq4Dnr27Kk3Sk6fPs2mTZu48cYb6d27N4sWLaKsrIwhQ4ZQVlZGWVkZ3bp1IyYmhjZt2nDs2DF27drF7t270TSNTp064XK5WL16NbGxsZw4cYLCwkIGDRqEn5+f3ojZuXMndrudgoICjEYjUVFRVFRU8Prrr5OQkMAvf/lL+vTpw44dO1i/fj1xcXEcO3aMXr16YTLJj8wfQ2b+qE3yUZ9kpD7JSG2Sj/okI/VJRo2TlSKEErp160Z4eDilpaVkZmbyyCOPAHDmzBlmzJjBpEmTuP3223n55Zf1Y5544gk++uijS34t1BcdHU1SUhJJSUl06dIFqJuBEhkZSVlZGQBbt27liy++4IsvvqC6uhpN05g8eTKRkZFkZ2dTU1PDnXfeSZs2bdA0jeLiYlasWMH+/fsZMGCA3pxLTExkyJAhnD9/nuzsbIKCgrjzzju9rlzerl07xo0bx5kzZ9iwYQMJCQmMHTv2un0uQgghhBBCCPXJP7cKJezatYuoqCh69OjB4cOH9efDw8NZuHAhISEh2O127rvvPr766iuGDx/ejKMVTclsNgN1zZV58+ZhMBiorq7mscceA+q2anO5XNhsNlwuF2azmaioKO666y78/Pyw2WwA1NTUYDAYmDVrFtXV1fr5NU3D4XBQW1vLoEGDGDRoEEFBQTidTtxuN2azGaPRyNy5c/X31tTU0KNHDxITEwkMDETTNKqrq/WxBgcH43A4cLlc+n2lnu69wWCgtrZWf+zv76/X5HFxTQCBgYH6Y09NJpMJg8GAyWRqcLzb7aa2tlbfvejCmux2OwB+fn76bUw1NTX653FhTRees6lrMhqNWK1Wn6rJl3KyWq3YbDafqsnXcqqpqdHH7ys1+VpOTqeTqqoqn6rJl3Ky2+2YTCafqsnXcrLb7dhsNp+qyddyqqqq0sfqKzV5jg8LC+On0tyeSoS4zjxrqLjdbkpKSnj99dcZM2YMmZmZbNy4kTfeeIPq6mpeeuklvv32W9xuN2fPnmXmzJncf//9PPHEEyQnJzN9+nSABl//VLIo7bXX9eGlV32s2Wxukh+C4tqRjNQm+ahPMlKfZKQ2yUd9kpH6JKPGyQwV0aw8a6hkZ2fz5JNP0r9//3qv/9///R+VlZV89tlnBAQE8Mc//lH/F2+j0VhvGy/P80IIIYQQQgghxLUma6gIJaSnpzN06FDeeeedes+bzWaio6MJCAigtLSUdevW6a917tyZffv2AXULmubm5l7XMYvmZTDIjy/VSUZqk3zUJxmpTzJSm+SjPslIfZJR4+TTEcqYM2cOmZmZnDlzRn9uxowZfPPNN4wfP5558+YxePBg/bWpU6dy6tQpxo0bx/z58+ndu3dzDFs0E1lxXH2SkdokH/VJRuqTjNQm+ahPMlKfZNQ4WUNFiEuQNVSuvZ+yhorT6cRoNDbhaERTk4zUJvmoTzJSn2SkNslHfZKR+iSjxklDRQgvnHYrRr+A5h5Gi/Pee+9x5swZXC4X0dHRjB07ls6dO1NRUUF2djaFhYUYDAa6devGpEmTKCkq5Mt1G/RZSXFxcdx+++2EhIQAdbdyZWdnc/z4cfz8/OjXrx+jR4/G4XCQlZVFYWEhNpuNG264gTFjxtC1a1ev49q4cSN5eXnY7XaSkpIYP348JpMsIXWtySJmapN81CcZqU8yUpvkoz7JSH2SUePklh8hvKiutTX3EFqkDh06kJaWxvDhwzl16hTLli3D7Xbz73//myNHjjBkyBBGjRpFcHAwAGXnKwkODmbUqFEkJCRw4MAB1q5dC9RtdfjRRx9RWlpKSkoKKSkp+Pn5AbBnzx7y8/OJiYlhxIgRnDp1iuXLl3sd04EDB9i0aRNdu3Zl4MCB7Nmzh82bN1+fD0QIIYQQQgjhs+SfaIUQTWbs2LHU1NRQXl7O5s2b0TSNoqIiTp48ya233sqwYcMwGo1omgZAr1696Nu3r/44Pz+f06dPA5Cfn4/ZbGbChAn06tVLb6YA+r710dHRxMXFYTKZCAwM9DqmPXv2AHULH4eEhLB37152797NiBEjrtnnIIQQQgghhPB90lARwouQIO9/ORfeuR12NJMfVquVV155BYDAwEAmTpzIqVOngLqZIps3b8bf35/U1FQGDhxY737MI0eOAHW7NwH6bUDbtm1j+fLlBAcHM27cOHr27Enfvn05fPgwubm55ObmEhQUREZGhtexlZeXYzAY9NuIwsPDOX78uNwPeh14ZiIJNUk+6pOM1CcZqU3yUZ9kpD7JqHHSUBHCC4PJj5NvP9Xcw2gxYh98HqhbBXz69OmcPXuWtWvXsmHDBhISEoC6Ldd+8YtfsGHDBnJycrjxxhtp3bo1ACUlJWRlZREbG0tKSgoADocDgLCwMFJTU8nOzmbp0qXceOONnDx5ksOHD9OrVy+6devGihUryMrKYtasWfrsF9H8XC6XNK0UJvmoTzJSn2SkNslHfZKR+iSjxskaKs0sOzubO+64g4yMDNLS0pgzZ851u/batWvZu3fvNb9OZmYmN998MxkZGWRkZHDnnXeybdu2Jr/OokWLOHfuXJOfV1w5g8FAfHw8AwcOpH379hQVFREREQFAQkICPXr00Bss5eXlABQXF/Pxxx/TqlUrpk+frm/NFhUVBUBSUhKJiYl07twZh8OB2Wxm//79OJ1Obr75ZpKTk2nXrh0nT56kuroat9uNw+HA5XLp53G5XFRVVQFQWVlJeHi4/MFwHdhsshaRyiQf9UlG6pOM1Cb5qE8yUp9k1DiZodKMTp8+zbPPPsuSJUuIjY3F7XZz4MCB63b9tWvXkpycTO/evX/0sT/2dokhQ4bwxhtvALBp0yb+53/+h+zs7Ca95ocffsiQIUP0WQ/i+jp8+DD79++nY8eOVFZWcuzYMUJCQujWrRshISEcOHCAVq1aceDAAfz9/YmNjeXkyZN8/PHHuN1u+vfvT2FhIX5+fnTv3p3k5GTWrVvH7t270TSNwsJCwsLCaNWqld5s2bJlC6dOneL48eMEBQURHBxMcXExH3zwAQMGDGDcuHH06dOHQ4cOkZOTQ2RkJJWVldx6663N/Gn9PHiaWkJNko/6JCP1SUZqk3zUJxmpTzJqnDRUmtHZs2cxmUxERkYCoGkaSUlJABw/fpzJkyeTm5vb4GvP42nTprF582Zqa2t59dVX+eSTT9izZw+BgYG8/fbbREdHc+jQIZ599llqamqwWq1MmzaNe+65h82bN7N+/Xq2bt3KZ599xsyZM7njjjtYsmQJixcvxul0Ehoayvz584mLiyMzM5Nly5YREhJCcXExr7zyCtu2bWPlypU4nU4CAgKYP38+iYmJl63bbDbrsxYA5syZw9GjR7Hb7XTq1IkXXniBiIgIcnNzee6550hOTua7777j0UcfxWKx8OGHH/L/27vT8KiqBI3j/6pUKgsBkkiEALK2wZAMGlbhGVADyDKGYCM4o+AAoq08giC2bP2MtI02jjb2DKLgoA2KwiiLEIzYQABpQRaDYhpZmk3WhJBAyFrbnQ9MrixJQZAkl/L9femqe+rcOqdeLxdOn3uO2+0GYOLEiXTt2pW3336bnJwcxo4dS0hICH/605/41a9+daMjEz/CwsI4fvw4WVlZBAUF0axZM3r16kVwcDCDBw8mPT2d9PR0GjRowJAhQ6hTpw779+83s0xPTwegfv36tGnThrp16zJo0CDWrFnD6tWradSoEf3798dut9O5c2dOnjzJoUOHOHjwIDExMfTu3bvCx33i4+Pp0aMH27dvx+Px0K5dOw2oiIiIiIjIz2YzyrfLkBrn8/l45pln+Oabb+jSpQvt27cnNTWVqKioqw6o9OzZk7lz53Lvvfcyb9485syZwwcffEB8fDzTpk2jfv36jB8/nsLCQpxOJ06nk6KiIgYPHsysWbNo3bo1kyZNIjExkaFDhwKwY8cO3nnnHd58802cTicbN27k7bffZvHixSxbtow//OEPrFixgmbNmgGQl5dHdHQ0AJs3b+bPf/4zH3/88RX9XLZsGa+88gpNmjShuLiYvLw85s6dS8eOHa84zxtvvIHX6+X5559n69atDB8+nI8++oikpCTgwmMikZGR5oyF4cOH8+WXXwKQnJzMnDlziIuLuyH5aA2Va1e+hkpNcrvdl+z8I9ajjKxN+VifMrI+ZWRtysf6lJH1KSP/NEOlFtntdt566y327dvH9u3bWbt2Le+++y5paWlXrRseHm4u3pmQkECjRo3M2SEJCQls3rwZgNLSUqZNm8bevXux2Wzk5OSwZ88eWrdufcU5MzIy2LNnD4MHDwYubE1bUFBglrdv394cTIEL29rOnTuXc+fOmdvjVubiR362bt3Kc889xxdffEFYWBgrVqwgLS0Nt9tNcXExLVq0MOs1b97cHEwBOHr0KBMmTCA7OxuHw0Fubi6nT58mJibmqr+ZVK/CwkJCQ0Ox2WwUFxebx8PDw801TcoXmi1fJ8Vut1NaWmq+djqd2O32K+r7fD5cLpc55TA0NJSSkhLzOIDD4cBut+NwOK6obxgGpaWl5nbLYWFheL1eDMMwZ8gEBwdjs9kICgqipKQEuDBrrCb7VP46UPpks9kCrk+BlFNJSQkhISEB1adAy6mwsBCHwxFQfQq0nMrKygKuT4GUU1lZmbmWWqD0KdByKisrIyQkJKD6FGg5nTt3jpCQkIDqU3n9unXr8nNpQMUC4uLiiIuL49FHH6V///5s27aNdu3amf+RwYUbwsXK/yOBn/7jKBcUFITX6wVg5syZxMTEMGPGDBwOByNHjrziXOUMw2DQoEE8++yzFZaXbzsLFy6WZ599loULF5KQkEB2djY9evS4pv526dIFj8fD/v37cblcLFq0iMWLFxMdHU1aWtols1wu36brueeeY9KkSfTq1Qufz8edd95ZaX+kZkVERJivL//Dyd/aNxWNeFdU//LP+Xw+QkJCzD/g/dW/vH3AJf9IuZb6NdGncoHSp/K/JEHg9OliN3ufHA7HFX242ftUkZu5T+Hh4RW2/2buU6DlFBwcXGHb4ebtUyDl5HQ6CQoKCqg+XVw/EPrkdDrN9gZKny6vHwh9uritgdKnG0W7/NSi7Oxsdu7cab4/deoUeXl5NG3alAYNGuB2uzly5AgAq1atuq7vOH/+PI0aNcLhcLBv3z527NhhlkVERHD+/HnzfXJyMitWrODUqVPAhUVgs7KyKjyvy+XC4/EQGxsLwEcffXTNbdq7dy9FRUU0bdqUgoICIiIiiIyMxOVysXTp0qv2p2nTpgAsXbr0klWn69Spc0l/JLBpxXHrU0bWpnysTxlZnzKyNuVjfcrI+pSRf5qhUos8Hg+zZs3i+PHj5lSpcePGmQvTTp06lREjRhAdHW0+3lNVTz/9NC+88AJLliyhZcuWdOrUySwbMGAAkydPZvXq1eaitOPGjePpp5/G6/Xidrvp27cviYmJV5w3IiKCsWPH8tBDDxEZGUmfPn38tmPz5s2kpqZiGAaGYfDHP/6R6OhounfvzsqVK+nTpw9RUVF07NiR77//vtLzTJ48mdGjR1O/fn26d+9uLugL8NhjjzFlyhRCQ0O1KK2IiIiIiIhUKy1KK1IJLUp77WpjUdqSkhLCwsJq/Hvl2ikja1M+1qeMrE8ZWZvysT5lZH3KyD/NUBER0zkPfFnoIM9jwwfc6jDoXtdDvSDYWWRnd2kQZT5oFuKjR4QXpx08Brz//vscO3YMt9tN79696datm3nOTZs2sX37dkpLS4mLiyMlJYWQkBA8Hg/p6ens3bsXl8tFgwYNuP/++2nZsmWFbduwYQPbt2/H7XbTtm1bevfuXUO/ilwvu11PlVqZ8rE+ZWR9ysjalI/1KSPrU0b+aUBFpAI+j7tWZl3UtrLDh3Fu2EBy27acOXOGbdu28XW9ODp16sT2Tz7hjjvuIDY2lvXr13NLu7vp378/LpeL0OXL+dWvfsUPP/xwyfl2795NRkbGJfXCw8Pp378/3333HTt37qRVq1a0bt2aNWvWkJaWxtixY69o1w8//MDGjRtJSEggKiqKv/3tb9StW5eePXvW0C8j16N8gTGxJuVjfcrI+pSRtSkf61NG1qeM/NNwk0gFikpKa7sJteK2225j+PDhdO7cmX79+hEWFkZOTo65OHLXrl3p0aMHERERfPfdd8CFFfSHPPwwcXFxV5zPX73ypw1jYmJo1aoVDoejwpW9AbNOv3796NmzJ/Xq1ePbb7+9sZ2XG+7iLe3EepSP9Skj61NG1qZ8rE8ZWZ8y8k/DTSIVqFPJP+wDnf2iJZVOnDhBSUkJ8fHx5vbVhw8fJigoiOLiYnw+H8XFxVdsbX0xf/XuuusuDhw4wNatW9m6dSthYWGkpqZWeJ78/Hzsdru5dXe9evU4duwYXq/X7zZpIiIiIiIi1UUDKiIVsAcHc3rOm7XdjBoX89QzAOTm5rJo0SIiIyPp168fQUFBZGVlsX79etavX4/T6cTlcl11CmCnTp0qrXfs2DH279/PP/3TPxEXF8eqVatYsWIFTzzxBDabrSa6KyIiIiIict00oCIilzh9+jQLFizA4XDw2GOPUbduXQCeeuopsrOzCQkJYdGiRXg8HpxOp99zhYeHV1rv73//O16vl44dO9KsWTMyMzM5dOiQOevF6/Vit9ux2+1ERUWRk5NDUVERderUoaCggLp162p2isX5m70ktU/5WJ8ysj5lZG3Kx/qUkfUpI/+0hkot+vzzzxk4cCCpqan07duXCRMm1Nh3r127ll27dlX798yaNYtXX331kmMLFy5k0qRJwIXFRtPT06u9HXJtzp07x4IFCyguLqZjx44cP36crKwszp8/z/r168nJyWH9+vWcOXOGrl27mvUyMzPN9VKOHz9OZmYmLpfLb72oqCgAvvrqK7Zt28axY8cICwsjPDycI0eO8PLLL7N69WoA7rzzTgBWr17NunXrKCgooF27djX508h1MC56hEysR/lYnzKyPmVkbcrH+pSR9Skj/zRDpZbk5OTw+9//nuXLlxMbG4thGFfskFKd1q5dS2Ji4nX9o/RGrlvxww8/sGHDBvr371+r7ZAL8vPzKSoqAmDdunXm8QkTJrB3716+/vprwsLCuOeee+jcubNZnpaWZr7evXs3u3fvNhearaxe586dyc3NZd++fRw8eJCYmBh69+5d4eM+8fHx9OjRg+3bt+PxeGjXrh0dOnSorp9BbpDS0lIiIiJquxlSCeVjfcrI+pSRtSkf61NG1qeM/LMZGnKqFbt37+bJJ59kzZo1hIWFXVJ27NgxBg0axNatW694X/56yJAhbNq0idLSUl5//XUWL17Md999R2hoKG+99RYxMTHs3buX3//+95SUlFBWVsaQIUMYPnw4mzZtYsKECYSGhhIVFcWIESMYOHAgy5cv56OPPsLr9RIREcG0adNo1aoVy5YtY+XKldSpU4cjR47w2muvsWXLFj777DO8Xi8hISFMmzaN+Pj4K/o5a9YsiouLmThxonls4cKFZGVlMXHiRB588EEKCwtp0qQJnTp14ne/+x0TJkzg0KFDuN1umjVrxiuvvEL9+vXZunUr06dPJzExkd27dzNu3DgKCwt5//33cbvdAEycOPGSmRM/xy95DZWbwfnz583HkcSalJG1KR/rU0bWp4ysTflYnzKyPmXkn2ao1JI77riDdu3ace+999KlSxfat29Pamqq+RiEP2fPnqVDhw5MmDCBefPmMXz4cD744AOmT5/OtGnTWLhwIePHj6dJkybMnz8fp9NJUVERgwcPpnv37nTv3p3k5GQSExMZOnQoADt27ODzzz/nww8/xOl0snHjRqZMmcLixYuBC9vWrlixgmbNmgHQsGFDRo4cCcDmzZt58cUX+fjjj6v0G0RFRTF27Fg2bNjAf//3f5vHp06dSnR0NABvvPEG//M//8Pzzz8PwD/+8Q9eeuklkpKSgAszKh544AFsNhsHDx5k+PDhfPnll1Vqh1zK4/FQWlpqTu8LCwvD6/ViGIY5cBUcHIzNZiMoKIiSkhIAbDYboaGh2Gy2S7ZXCw8Px+Px4PP58Hg8AObaK3a7ndLSUvO10+nEbrdfUd/n8+FyufD5fACEhobicrkoKyvD5XIB4HA4sNvtOByOK+obhnFT9Kn8daD0ye12U1ZWFlB9CqScCgsLA65PgZbTxccCpU+BlpPb7aaoqCig+hRIORUWFgZcnwItp/J7USD1KdByKs8okPpUXv9GDBRpQKWW2O123nrrLfbt28f27dtZu3Yt77777iWPTlQmPDyce++9F4CEhAQaNWpkzg5JSEhg8+bNwIXpWdOmTWPv3r3YbDZycnLYs2cPrVu3vuKcGRkZ7Nmzh8GDBwMXnpUrKCgwy9u3b28OpgBkZWUxd+5czp07h81m4/DhwxW2tbLdWvzt4rJixQrS0tJwu90UFxfTokULs6x58+bmYArA0aNHmTBhAtnZ2TgcDnJzczl9+jQxMTGVnl/8czgcV0zrK9/NJ7SC7aQr+oPo8mP+Hs0KDg6+pvqX4txWNwAAFbhJREFUf65+/fo4HA5CQkKuqU03Q5/KBUqfPB6P2aZA6dPFbvY+hYSEXLFT183ep4rczH265ZZbKtxN7WbuU6DlVK9evUp3vLtZ+xRIOYWFhREUFBRQfbq4fiD0KSwszPzeQOnT5fVv9j7FxMRc8udcIPTpRs640YBKLYuLiyMuLo5HH32U/v37s23bNtq1a3fJ4j/l/w9vuYt3VikfaSsXFBSE1+sFYObMmcTExDBjxgwcDgcjR4684lzlDMNg0KBBPPvssxWW16lTx3ztcrl49tlnWbhwIQkJCWRnZ9OjR48K60VFRXH8+PFLjuXn55szUC63Y8cOFi1axOLFi4mOjiYtLe2SmS+XrzL93HPPMWnSJHr16oXP5+POO++stI8SWLxe71W3bZbapYysTflYnzKyPmVkbcrH+pSR9Skj/7TLTy3Jzs5m586d5vtTp06Rl5dH06ZNadCgAW6329w1ZdWqVdf1HefPn6dRo0Y4HA727dvHjh07zLKIiAjOnz9vvk9OTmbFihWcOnUKuHDhZGVlVXhel8uFx+MhNjYWgI8++qjSNtx9991s2rTJPO/Zs2dJT0/nn//5nytsR0FBAREREURGRuJyuVi6dOlV+9i0aVMAli5dak4zk8Cn5Z+sTxlZm/KxPmVkfcrI2pSP9Skj61NG/mmoqZZ4PB5mzZrF8ePHzefOxo0bR9u2bYEL64iMGDGC6Oho8/Geqnr66ad54YUXWLJkCS1btqRTp05m2YABA5g8eTKrV682F6UdN24cTz/9NF6vF7fbTd++fUlMTLzivBEREYwdO5aHHnqIyMhI+vTpU2kbWrduzZQpUxg9erT5bNzQoUPNhWO7du3Ke++9x4ABA+jcuTMTJ05k5cqV9OnTh6ioKDp27Mj3339f6fknT57M6NGjqV+/Pt27dycyMvK6fiu5+bjd7gqnBYp1KCNrUz7Wp4ysTxlZm/KxPmVkfcrIP+3yI1IJ7fJjbVpx3PqUkbUpH+tTRtanjKxN+VifMrI+ZeSfZqiIVMDndlfr4MLnn3/O3//+d4qKirj99tt55JFHADh9+jQrV67k5MmTREZG0q9fP3MR4a+//pqvv/6awsJC6taty913302XLl38nq+cYRgsWLCAI0eOVFheLufUKdI++6zC77eayhbDEutQRtamfKxPGVmfMrI25WN9ysj6lJF/WkNFpALu/9/6qzolJCRccWzp0qXk5uZy//33Y7fb+eSTTygtLeXMmTN88cUX2Gw27r//frxeL6tXr+bcuXN+z1cuMzOTEydOXLVNyz79tMLvtyJ/O0WJNSgja1M+1qeMrE8ZWZvysT5lZH3KyD8NqIhUwN/WWzdCv379zHVkyp08eZLs7GwSExPp3LkzXbt2paysjN27d5uLQdWrV49WrVoRERFBUFCQueJ2Recrd/78edasWcN9993nt03+vt+Kqjsj+fmUkbUpH+tTRtanjKxN+VifMrI+ZeSfBlREKmCvxqWFDI+3wuNnz54FLgyaXPy/+fn5NGjQgJ49e/Ljjz8ye/ZsTp06RUpKyiXbWVfm888/p1WrVsTHx/v9nL/vt6KSkpLaboJchTKyNuVjfcrI+pSRtSkf61NG1qeM/NMaKiIVsAcHc/rthdVy7pinh17T5y5eL7qoqIht27bRqFEj7rnnHjZu3Eh6ejotW7Y0Bz4qcvDgQfbv38+wYcPMARO3231Ni0tpvWoREREREZHKaYaK1Lhz587Rrl07pk+f/rPOM2zYMNavX3+DWlX7yrd8LigoAC48qgMQFRXF4cOHOX/+PPHx8dxxxx3Ex8fjcrk4evSo33MWFBTg8Xj4y1/+woIFCwA4fPgwy5cvB8Dr9eLxeK76/Vak5zmtTxlZm/KxPmVkfcrI2pSP9Skj61NG/mmGitS4VatWceedd/LZZ5/xwgsv4HQ6a7tJNW7fvn3k5OQAFwYwMjMzad68OQ0bNiQrK4uYmBh27NiB0+mkbdu25OXlAbBr1y4iIiL4/vvvAbjlllv8nq9FixYMHjwYuDDLJT09ndjYWO655x4APvjgA44cOcJvf/tbYmNjK/1+KwoNDa3tJshVKCNrUz7Wp4ysTxlZm/KxPmVkfcrIP81QkRq3dOlSRo8eTZs2bVi3bh0A2dnZjBkzhpSUFFJSUpg7dy4AhYWFTJ06lYceeoiUlBSmT5+O1/vTGiTbtm3j3/7t3+jZsyevv/56rfTnemzevPmSvqelpXH06FF+/etf06BBA/7617/i9XoZPHgwoaGhNG7c2NzdJz09HY/HQ79+/WjUqJHf80VGRtK2bVvatm3L7bffDkBERATNmzevsF2Vfb8VabTc+pSRtSkf61NG1qeMrE35WJ8ysj5l5J/N0EIJUoP27NnD6NGjWbduHWlpaaxcuZJ58+YxbNgw7rnnHkaNGgVAXl4e0dHRTJ06lU6dOjFw4EB8Ph/PP/88d999N0OGDGHYsGHccsstzJw5k6KiInr16sX//u//0qJFixvS1tpeQ0X8u5Z1YKR2KSNrUz7Wp4ysTxlZm/KxPmVkfcrIPz3yIzVqyZIlpKamYrPZuP/++5k+fTrHjx9n586d/OUvfzE/Fx0dDUBGRga7du0yy0pLS2nYsKH5ub59+2K326lbty6tW7fmxx9/vGEDKtWpsLCQ0NBQbDYbxcXF5vHw8HA8Hg8+n89c26T8kSi73U5paan52ul0Yrfbr6jv8/lwuVz4fD7gwjS98tculwsAh8OB3W7H4XBcUd8wDEpLS81FacPCwvB6vRiGgdvtBiA4OBibzUZQUJC58rfNZqvRPrlcLsrKygKqT4GWk9vtpqysLKD6FEg5FRYWBlyfAi2ni48FSp8CLSe3201RUVFA9SmQciosLAy4PgVaTuX3okDqU6DlVJ5RIPWpvP6NGCjSDBWpMS6Xix49euB0OnE4Lozl5efn8/jjjzNnzhy+/fZb83i5u+++m08++YTbbrvtivMNGzaMkSNHct9991X4/ufSDBVr02i59Skja1M+1qeMrE8ZWZvysT5lZH3KyD+toSI1Zt26dbRs2ZIvv/ySjIwMMjIyeO+991i5ciVJSUnMnz/f/Gz5IqzJycm888475ropeXl5V93ZRn4ZwsPDa7sJchXKyNqUj/UpI+tTRtamfKxPGVmfMvJPAypSY5YuXUpKSsolx5KSkvD5fIwZM4bMzEweeOABBgwYwJIlSwCYMmUKdrud1NRUUlJSGDVqFNnZ2bXRfLGY8il9Yl3KyNqUj/UpI+tTRtamfKxPGVmfMvJPj/yIVEKP/FhbSUkJYWFhtd0M8UMZWZvysT5lZH3KyNqUj/UpI+tTRv5pUVqRCvjc7mob+DA8XmyOoGo59y+JRsutTxlZm/KxPmVkfcrI2pSP9Skj61NG/umRH5EKFP3/atDVQYMpIiIiIiIiNz898iMiIiIiIiIiUkWaoSIiIiIiIiIiUkUaUBERERERERERqSINqIiIiIiIiIiIVJEGVEREREREREREqkgDKiIiIiIiIiIiVaQBFRERERERERGRKtKAioiIiIiIiIhIFWlARURERERERESkijSgIiIiIiIiIiJSRRpQERERERERERGpIg2oiFzm0KFDPPzww/Tp04eHH36Yw4cP13aTAlJycjJ9+/YlNTWV1NRUNm3aBMC3337LgAED6NOnDyNHjuTMmTNmneook5+8+uqrJCcn06ZNG/bt22ce93dN1HTZL11lGVV2PYGuqZqUn5/PE088QZ8+fUhJSeGZZ54hLy8PqPkclFHF/GXUpk0bUlJSzOto7969Zr2MjAz69u1L7969GTduHCUlJdVa9ks2evRoBgwYwMCBA3nkkUf44YcfAN2LrKSyjHQvspY333zzkr8v6D5UTQwRucSwYcOMTz/91DAMw/j000+NYcOG1XKLAtN9991n7N2795JjXq/X6NWrl7F9+3bDMAxj9uzZxqRJk6qtTC61fft248SJE1dk4++aqOmyX7rKMqroejIMXVM1LT8/3/j666/N9zNmzDAmT55c4zkoo8pVlpFhGEZcXJxRWFh4RZ3CwkKjW7duxqFDhwzDMIwpU6YYs2bNqrayX7qCggLz9Zo1a4yBAwcahqF7kZVUlpHuRdaRlZVlPP7442Ymug9VHw2oiFwkNzfX6NChg+HxeAzDMAyPx2N06NDBOHPmTC23LPBUdNP97rvvjH/5l38x3585c8a46667qq1MKnZxNv6uiZouk59c64CKrqnatXr1auPf//3fazwHZXTtyjMyjMoHVNLT040nn3zSfL9r1y6jf//+1VYmP1m+fLnx4IMP6l5kYeUZGYbuRVZRVlZmDBkyxDh69KiZie5D1cdR2zNkRKzk5MmTNGzYkKCgIACCgoK49dZbOXnyJNHR0bXcusDz/PPPYxgGHTp04LnnnuPkyZM0btzYLI+Ojsbn83H27NlqKYuMjKyZjt7E/F0ThmHUaJmuQf8uv57q1auna6oW+Xw+Fi1aRHJyco3noIyuzcUZlRs2bBher5cePXowZswYnE7nFb9n48aNOXnyJEC1lAlMnTqVr776CsMwmDdvnu5FFnR5RuV0L6p9//Vf/8WAAQNo2rSpeUz3oeqjNVREpFZ8+OGHrFy5kqVLl2IYBi+99FJtN0nkpqXryXr+8Ic/EB4eztChQ2u7KVKJyzPasGEDy5Yt48MPP+Qf//gHs2fPruUW/nK9/PLLbNiwgfHjx/Of//mftd0cqUBFGeleVPt27txJVlYWjzzySG035RdDAyoiF4mNjSU7Oxuv1wuA1+slJyeH2NjYWm5Z4Cn/TZ1OJ4888giZmZnExsZy4sQJ8zN5eXnY7XYiIyOrpUyuzt81UdNlUrmKrqfy47qmat6rr77KkSNH+POf/4zdbq/xHJTR1V2eEfx0HUVERDB48OBKr6MTJ06Yn62OMvnJwIED2bp1K40aNdK9yKLKM8rPz9e9yAK2b9/OgQMH6NmzJ8nJyZw6dYrHH3+cI0eO6D5UTTSgInKRW265hfj4eFatWgXAqlWriI+P1/TOG6y4uJjz588DYBgG6enpxMfHk5iYSGlpKTt27ABg8eLF9O3bF6BayuTq/F0TNV0mFavseoLquW50Tfk3c+ZMsrKymD17Nk6nE6j5HJSRfxVldO7cOUpLSwHweDx88cUX5nXUvXt3vv/+e3OXl8WLF9OvX79qK/slKyoquuTRp4yMDOrXr697kYVUllFISIjuRRbw5JNP8re//Y2MjAwyMjJo1KgR7777LqNGjdJ9qJrYDMMwarsRIlZy4MABJk2aREFBAfXq1ePVV1+lVatWtd2sgHL06FHGjBmD1+vF5/PRunVrfve733HrrbeSmZnJiy++SFlZGU2aNOG1116jQYMGANVSJj+ZPn06f/3rX8nNzSUqKorIyEg+++wzv9dETZf90lWU0Zw5cyq9nqB6rhtdUxXbv38/DzzwAC1atCA0NBSApk2bMnv27BrPQRlVrLKMRo0axX/8x39gs9nweDwkJSUxZcoU6tSpA8DatWt57bXX8Pl8xMfHM2PGDMLDw6ut7JcqNzeX0aNHU1JSgt1up379+kycOJGEhATdiyyisozq1aune5EFJScnM2fOHOLi4nQfqiYaUBERERERERERqSI98iMiIiIiIiIiUkUaUBERERERERERqSINqIiIiIiIiIiIVJEGVEREREREREREqkgDKiIiIiIiIiIiVaQBFRERERERERGRKtKAioiIiIjUuBMnTpCUlITX663tpoiIiFwXDaiIiIiIWEBycjKbN28233/22Wd06tSJbdu21WKrfjJr1iwSEhJISkqiY8eO/Ou//is7d+687vM1btyYnTt3EhQUdANbKSIiUnM0oCIiIiJiMcuXL+ell15i7ty5dO7cubabY+rXrx87d+5ky5YttG/fnjFjxmAYRm03S0REpFZoQEVERETEQhYvXsyMGTOYN28e7du358cff+Sxxx6jS5cudOnShQkTJlBQUGB+/p133qF79+4kJSXRp08ftmzZAsCkSZN44403zM9t3bqVHj16XLXetQgODubBBx/k9OnT5Ofnk52dzVNPPUXnzp3p3bs3H3/8sfnZXbt28etf/5r27dvTrVs3/vjHPwJw7Ngx2rRpg8fjue7fSkREpDY5arsBIiIiInLBokWL+Oabb1iwYAF33HEHAIZh8Jvf/IZOnTpRWFjImDFjmDVrFlOnTuXgwYN8+OGHLFmyhIYNG3Ls2DF8Pt9Vv+d665VzuVwsW7aM2NhYoqOjefTRR7n99tvZtGkTBw8eZMSIEdx222107dqVl19+mccee4yBAwdSVFTE/v37r/v3ERERsRINqIiIiIhYxFdffUWXLl2Ii4szjzVv3pzmzZsDEB0dzYgRI3jzzTcBCAoKwuVyceDAAaKjo2natOk1fc/11lu9ejUbNmwgODiY22+/nTfffJOTJ0+SmZnJ3LlzCQkJIT4+nsGDB7NixQq6du2Kw+Hgxx9/JC8vj+joaO66664q/ioiIiLWpEd+RERERCxi2rRpHD58mKlTp5prk+Tm5jJ+/Hi6d+9O+/bt+e1vf0t+fj5wYbBlypQpzJo1i27dujF+/Hiys7Ov+j3XW69v377s2LGDLVu28P7775OYmEhOTg7169cnIiLC/Fzjxo3N87388sscPnyYfv36MWjQINavX389P42IiIjlaEBFRERExCIaNGjA/Pnz+eabb5g2bRoAM2fOxGazkZaWRmZmJq+99tolC8GmpKSwaNEi1q9fj81m4/XXXwcgLCyM0tJS83O5ubmXfFdl9arq1ltv5dy5cxQWFprHTp48ScOGDQFo0aIFM2fOZMuWLTzxxBOMHTuW4uLi6/ouERERK9GAioiIiIiFNGzYkPnz57Np0yZeeeUVioqKCA8Pp27dumRnZzNv3jzzswcPHmTLli24XC6cTichISHY7Rf+ehcfH8/GjRs5e/Ysp0+fZsGCBddUr6piY2NJSkpi5syZlJWVsWfPHpYsWcKAAQMAWLFiBXl5edjtdurVqwdw3d8lIiJiJVpDRURERMRiGjduzIIFCxg6dCiJiYns3r2bjh070qxZM1JTU5k/fz5wYXHYP/3pTxw4cIDg4GCSkpJ46aWXAEhNTWXz5s0kJyfTpEkTBg0axHvvvXfVetdj5syZvPjii3Tv3p169eoxZswYunXrBsCmTZuYMWMGpaWlNG7cmDfeeIPQ0NCf9wOJiIhYgM24eM6oiIiIiIiIiIhcleZbioiIiIiIiIhUkR75EREREREARo0axTfffHPF8d/85jc89dRTtdAiERER69IjPyIiIiIiIiIiVaRHfkREREREREREqkgDKiIiIiIiIiIiVaQBFRERERERERGRKtKAioiIiIiIiIhIFWlARURERERERESkiv4PnCh49Lvvh/cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1152x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-NJKAuEMtz98",
        "outputId": "85a0ed3d-25a9-4d43-d4c6-f3627eb78e9b"
      },
      "source": [
        "!pip install geopandas"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: geopandas in /usr/local/lib/python3.7/dist-packages (0.9.0)\n",
            "Requirement already satisfied: pyproj>=2.2.0 in /usr/local/lib/python3.7/dist-packages (from geopandas) (3.1.0)\n",
            "Requirement already satisfied: fiona>=1.8 in /usr/local/lib/python3.7/dist-packages (from geopandas) (1.8.20)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from geopandas) (1.1.5)\n",
            "Requirement already satisfied: shapely>=1.6 in /usr/local/lib/python3.7/dist-packages (from geopandas) (1.7.1)\n",
            "Requirement already satisfied: attrs>=17 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (21.2.0)\n",
            "Requirement already satisfied: six>=1.7 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (1.15.0)\n",
            "Requirement already satisfied: cligj>=0.5 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (0.7.2)\n",
            "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (7.1.2)\n",
            "Requirement already satisfied: click-plugins>=1.0 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (1.1.1)\n",
            "Requirement already satisfied: munch in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (2.5.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (57.2.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (2021.5.30)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->geopandas) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->geopandas) (2.8.1)\n",
            "Requirement already satisfied: numpy>=1.15.4 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->geopandas) (1.19.5)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2Bp3mRziaGhc"
      },
      "source": [
        "import plotly.express as px\n",
        "import geopandas as gpd"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "dxTc1TJWt9s3",
        "outputId": "94e2b2d0-bd61-404f-d650-f5ae5f35a15d"
      },
      "source": [
        "provinsi.head()"
      ],
      "execution_count": 18,
      "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>X</th>\n",
              "      <th>Y</th>\n",
              "      <th>FID</th>\n",
              "      <th>Kode_Provi</th>\n",
              "      <th>Provinsi</th>\n",
              "      <th>Kasus_Posi</th>\n",
              "      <th>Kasus_Semb</th>\n",
              "      <th>Kasus_Meni</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>96.909523</td>\n",
              "      <td>4.225082</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>Aceh</td>\n",
              "      <td>10814</td>\n",
              "      <td>9367</td>\n",
              "      <td>432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>99.057888</td>\n",
              "      <td>2.184779</td>\n",
              "      <td>2</td>\n",
              "      <td>12</td>\n",
              "      <td>Sumatera Utara</td>\n",
              "      <td>29198</td>\n",
              "      <td>25952</td>\n",
              "      <td>965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100.466805</td>\n",
              "      <td>-0.851914</td>\n",
              "      <td>3</td>\n",
              "      <td>13</td>\n",
              "      <td>Sumatera Barat</td>\n",
              "      <td>36268</td>\n",
              "      <td>33058</td>\n",
              "      <td>783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>101.812892</td>\n",
              "      <td>0.510526</td>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>Riau</td>\n",
              "      <td>42698</td>\n",
              "      <td>37374</td>\n",
              "      <td>1050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>103.599320</td>\n",
              "      <td>-1.617750</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>Jambi</td>\n",
              "      <td>7407</td>\n",
              "      <td>5987</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            X         Y  FID  ...  Kasus_Posi Kasus_Semb  Kasus_Meni\n",
              "0   96.909523  4.225082    1  ...       10814       9367         432\n",
              "1   99.057888  2.184779    2  ...       29198      25952         965\n",
              "2  100.466805 -0.851914    3  ...       36268      33058         783\n",
              "3  101.812892  0.510526    4  ...       42698      37374        1050\n",
              "4  103.599320 -1.617750    5  ...        7407       5987         108\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        },
        "id": "GirKI-7ntR2v",
        "outputId": "8572c57c-96da-4d55-b5d5-d891bdd60419"
      },
      "source": [
        "plt.figure(figsize=(26, 9))\n",
        "fig = px.scatter(provinsi, x='X', y='Y', color='Provinsi', size='Kasus_Posi')\n",
        "fig.show()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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        {
          "output_type": "display_data",
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            "text/plain": [
              "<Figure size 1872x648 with 0 Axes>"
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      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "k-yyYT6muDsd",
        "outputId": "1fa11263-ee22-4dc6-bce6-3b261d702e16"
      },
      "source": [
        "vaksin = pd.read_csv('https://raw.githubusercontent.com/mohripan/Machine-Learning/main/Lomba/Dataset/Kabeh/vasin%20dosis%201%20dan%20lengkap.csv')\n",
        "vaksin.head()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DD-MM-YY</th>\n",
              "      <th>minimal 1 dosis</th>\n",
              "      <th>dosis lengkap</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>22-Jan-21</td>\n",
              "      <td>132</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>23-Jan-21</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>24-Jan-21</td>\n",
              "      <td>149.242</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>25-Jan-21</td>\n",
              "      <td>161.959</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>26-Jan-21</td>\n",
              "      <td>245.685</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    DD-MM-YY minimal 1 dosis dosis lengkap\n",
              "0  22-Jan-21             132           NaN\n",
              "1  23-Jan-21             NaN           NaN\n",
              "2  24-Jan-21         149.242           NaN\n",
              "3  25-Jan-21         161.959           NaN\n",
              "4  26-Jan-21         245.685           NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TWoKEHE7xX6J"
      },
      "source": [
        "vaksin['minimal 1 dosis'] = vaksin['minimal 1 dosis'].str.replace('.','')\n",
        "vaksin['tanggal'] = pd.to_datetime(vaksin['DD-MM-YY'])"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jzy9phvdxpUD"
      },
      "source": [
        "vaksin = vaksin.drop('DD-MM-YY', axis=1)\n",
        "vaksin['dosis lengkap'] = vaksin['dosis lengkap'].str.replace('.','')"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LUH6lb7PyIfR",
        "outputId": "83896a74-64ca-4917-885f-15d441708363"
      },
      "source": [
        "vaksin['minimal 1 dosis'] = vaksin['minimal 1 dosis'].astype(float)\n",
        "vaksin['dosis lengkap'] = vaksin['dosis lengkap'].astype(float)\n",
        "vaksin.info()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 209 entries, 0 to 208\n",
            "Data columns (total 3 columns):\n",
            " #   Column           Non-Null Count  Dtype         \n",
            "---  ------           --------------  -----         \n",
            " 0   minimal 1 dosis  165 non-null    float64       \n",
            " 1   dosis lengkap    160 non-null    float64       \n",
            " 2   tanggal          209 non-null    datetime64[ns]\n",
            "dtypes: datetime64[ns](1), float64(2)\n",
            "memory usage: 5.0 KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fo6Yqn2JylOs",
        "outputId": "3b7a82dc-9170-4140-8315-e7e3b5074da0"
      },
      "source": [
        "import math\n",
        "kalkulasi = 0\n",
        "for i in range(len(vaksin)):\n",
        "  if math.isnan(vaksin['minimal 1 dosis'].iloc[i]):\n",
        "    vaksin['minimal 1 dosis'].iloc[i] = kalkulasi\n",
        "  else:\n",
        "    kalkulasi = vaksin['minimal 1 dosis'].iloc[i]"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:670: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n"
          ],
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      "metadata": {
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        "id": "2mW__6gWy13t",
        "outputId": "e311322f-cc1a-4031-eded-9163b75998ce"
      },
      "source": [
        "import math\n",
        "kalkulasi = 0\n",
        "for i in range(len(vaksin)):\n",
        "  if math.isnan(vaksin['dosis lengkap'].iloc[i]):\n",
        "    vaksin['dosis lengkap'].iloc[i] = kalkulasi\n",
        "  else:\n",
        "    kalkulasi = vaksin['dosis lengkap'].iloc[i]"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:670: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "9s4ELoTuPRse",
        "outputId": "4f8cf7fd-3d40-4f23-ec47-c4024f8a39c2"
      },
      "source": [
        "vaksin.head()"
      ],
      "execution_count": 31,
      "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",
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              "\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>minimal 1 dosis</th>\n",
              "      <th>dosis lengkap</th>\n",
              "      <th>tanggal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>132.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2021-01-22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>132.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2021-01-23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>149242.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2021-01-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>161959.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2021-01-25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>245685.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2021-01-26</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   minimal 1 dosis  dosis lengkap    tanggal\n",
              "0            132.0            0.0 2021-01-22\n",
              "1            132.0            0.0 2021-01-23\n",
              "2         149242.0            0.0 2021-01-24\n",
              "3         161959.0            0.0 2021-01-25\n",
              "4         245685.0            0.0 2021-01-26"
            ]
          },
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          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7giG8Xge5Fi8"
      },
      "source": [
        "covid_per_hari['minimal 1 dosis'] = 0\n",
        "value = np.array(vaksin['minimal 1 dosis']).reshape(-1, 1)"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HDqoS-dp3k1w",
        "outputId": "013d8328-d368-4e90-9c7b-19f9a8bcc5ec"
      },
      "source": [
        "for i in range(len(vaksin)-1):\n",
        "  try:\n",
        "    covid_per_hari['minimal 1 dosis'].iloc[i+326] = vaksin['minimal 1 dosis'].iloc[i]\n",
        "  except:\n",
        "    pass"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:670: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rqgWS705QbuL",
        "outputId": "63729231-6729-4c45-cbc4-ec05bec4374d"
      },
      "source": [
        "covid_per_hari['minimal 1 dosis']"
      ],
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0             0.0\n",
              "1             0.0\n",
              "2             0.0\n",
              "3             0.0\n",
              "4             0.0\n",
              "          ...    \n",
              "523    49801823.0\n",
              "524    50497940.0\n",
              "525    51181322.0\n",
              "526    51759158.0\n",
              "527    51759158.0\n",
              "Name: minimal 1 dosis, Length: 528, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "0X-2GWOqTDqV",
        "outputId": "8d1f5337-ba76-429e-aeb9-ee965dea047a"
      },
      "source": [
        "plt.plot(vaksin['dosis lengkap'])"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fde30fe51d0>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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cjtdee+2qvXoior7kHCzDO9uOY+yIIPzH/EksdxuwquCXL1+O5cuX91i+YcOG7seZmZm2S0VEbuWL3LPYsKMAk8eE4OVHp8BTwWmybIGjSESi2p9fhQ07CpCSqMbvFyZB7iETO5LLYMETkShaO4w4XFSNd/+Rj7jhASx3O2DBE9GgKrnYiI93F6HgrBYmswB1kA9efnQKy90OWPBENChMZgE5B8uwYcdJ+PsocM/0UZg2LgyxwwJ4XrudsOCJyO4uaJrx548Oo7KuFeNHDcXSRVPg76MQO5bLY8ETkV3VNXZgxfs/AwBefnQKfpGg5h77IGHBE5FdmMwC9hy4gK1fF0PfaULm725BtJp3XxpMLHgisjmTWcDbnx3DN4fLMXZEIJ7ISGC5i4AFT0Q2U9vQjq17S1Ba3ojzVc14aHYcHpodx6tSRcKCJ6IbJggCvssrx3ufn4TJLCBuWAB+e08i0m+OETuaW2PBE9ENaWo1YN0/8vHzSQ3GxVyaRyYsyEfsWAQWPBHdgMNF1Xjrs+NobTfisbvGYt70UZDxDBmHwYInon4xCwJOnqnH3sMX8e2RckSr/bHqyRSMCB8idjS6BgueiKxm7DLjs1wtTldUQu4hxa9mjMKCuWM4zYCDYsETkVXMZgGvbzqC0xV6PHbXWNyZOgJeSlaII+OfDhH1qanVAA+ZFN8cvoifT2owZ/IQ/CpttNixyAoseCLqlbHLhE+/LsE/vyuFh0wKk1nAlLGh+EUca8NZ8E+KiHrQ1Lch8/8O42xFE2YkRUIikeCCphlLHpiIcyWFYscjK7Hgiegq+/Ir8fZnxyGVSPDfv56GqePCxI5EA8SCJyIAQGOLHn/bWYgfjlUgblgAXnokGSGB3mLHohvAgidyU81tnWht70R5TQsOFdXg+7xymAUB82+PwwOzYiH3kIodkW4QC57IDZjMAk5faMCx4lqcqdDhXGUTGlsM3a8r5DLMSI7CPdNHISLYV8SkZEsseCIXZjYLyN5/Hjt+OIPaxg5IpRIMC/XDpLgQRKv9ofJTYqjKC2OGB/BiJRfEgidyUe16I97Zlo/c45UYFxOEx+4ah8ljQuDjJRc7Gg0SFjyRi6iqa8XBwmqUluvQrjei4JwWnUYTHk8fi3umj+Kc7G6IBU/k5DT1bfjbFwU4WFgNAAgN9IaPpxzTJ0di9rThiB0WIHJCEgsLnsiJfZ9Xjne3n4BUAsy/PQ6zpw1HcICX2LHIQbDgiZyQtqkDH2UX4bu8CowdEYgXFiQhJIDnrNPVWPBETsJsFrDnYBkOFVbjWHEtBEHAQ7Pj8OCsWMhkPGedemLBEzmJ749W4N1/5CN8qA9+eUsM7kodwVvjUZ8s/rWfmZmJtLQ0xMXFoaSkpNd1TCYTVq5ciVmzZuH222/Htm3bbB6UyJ0Zu0zY/NUpjIwcgr8unYnf3J3AcieLLO7Bz5w5E4sWLcKCBQuuu86uXbtw8eJF5OTkQKfTYd68eUhJSUFkZKRNwxK5ujMVOnyaUwyTWbhqeUtbJ2obO/Ds/RMh5T1PyUoW9+CTk5OhVqv7XGf37t24//77IZVKERgYiFmzZuGrr76yWUgid2AymbH2k6MoPKeFrtVw1X8mQcA900dhUmyw2DHJidjkGLxGo0F4eHj3c7Vajerqalt8NJFbEAQBu3+6gPKaFvzhsSlISQy3/CYiCxzqS9aCgoIBvzcvL8+GSVwTx8g6gzlOZrOA3KIW/HSqBQajgOEhCsgNVcjL0wxahoHgtmSZI4yRTQperVajqqoK48ePB9Bzj95aCQkJUCqV/X5fXl4ekpKS+v0+d8Ixss5gjdOBAg0+3n0Kre2daGwxYNq4MIwfPRTTJ0fB30dh959/I7gtWTZYY2QwGPrcMbZJwc+dOxfbtm3D7NmzodPpsHfvXmzevNkWH03kcr4+WIZ3th1HVKgfJsQGI2lMKG6bFMG5YsjmLBb8mjVrkJOTg/r6ejz++ONQqVTIzs7G4sWL8dxzzyExMREZGRnIz8/H7NmzAQDPPvssoqKi7B6eyNlU1bXi3e0nMH50MP7rsanwVDrUUVJyMRa3ruXLl2P58uU9lm/YsKH7sUwmw8qVK22bjMiFdBpN0NS34YOdBVDIpfjPhyaz3MnuuIUR2Vm9rgP/9df9qKpvAwA8OS8Rgf6eIqcid8CCJ7Kj4rIGvL4pDy3tnVjywESEBnpj/KihYsciN8GCJ7oB7XojWtqNaNcbUVHTCn1nFwRcOiRz4kw9DhRoEOjvidW/vYnzstOgY8ETDVCHoQu/ffUb6FoNvb4eNMQTGbeOxEOz4+Dtydvk0eBjwRMN0LdHyqFrNeDRu8YiNNAbUaF+8FZ6QCKRQCoFAv09eeojiYoFTzQAZrOAXblnETtMhV/N4P1OyTGx4IksqG1oxxub83C2QgeZTIJAfy/IPaSorGvDiwuSWO7ksFjwRH2orGvF79/Khclsxp2pI2A2C9A26WEwmjA6SoXUCZwUjBwXC56oD3//ohAmsxlr/+M2RAT7ih2HqF9Y8ES90DZ1oOhcAw4VVePRu8ay3MkpseCJrnHkVA1W//0gzGYBwQFe+OUtMWJHIhoQFjzRFTq7zPhg+6UbWy+YOwZjRwRBKZeJHYtoQFjw5Lba9Ubkl9ahXd8FTX0bjpfUoUbbDF2bCa8+k4qEkZxSgJwbC57cjiAI2P7dGWzZcxqdXWYAgFQCjIkORFiAHPPnjGO5k0tgwZNbEQQBf99ViB0/nMUvEsKQcetIDFV5wddbAV8v+b/uxDNC7JhENsGCJ7chCAI+yi7Cjh/OIj11BBbPS4RUyouUyHWx4MltfHO4HNu/O4M7UqLx5D2JvAKVXJ5U7ABEg6HLZMaWr4sRO0yFp+4dz3Int8CCJ7fw47EK1Da048Hb43hYhtwGD9GQy+oymfFpTjGy9p1DR6cJI8L9MSU+VOxYRIOGBU8u5+SZeqz9JA8tHUYYOk1ISVQjLMgHt02K4KEZcisseHIpjS16vLbpCLyUHpgzPhwTRgdj6rgwsWMRiYIFTy6j8JwW6/95Au36Lqx56iYMD/MXOxKRqFjw5BK+yD2LDTsKEDTEE8sWJbPcicCCJyen7+zCZ3tLsO2bUqQkqvH8Q5PhqeRmTQSw4MmJnSnX4U8fHUJdYwfSkqOw5IGJ8JDxzF+iy1jw5FQ6jSZs/7YU2mY9vj9aAX8fBf70TCoSOTkYUQ8seHIKNQ3t0DZ1YNOXp3HybD1UvkrEDQvAiwuSEODvKXY8IofEgieHt/dQGd7elg+zWYBMKsELC5IwfXKk2LGIHB4Lnhzalz+dx7vbT2Di6GDcM30UQoO8eX9UIitZVfDnz5/HsmXLoNPpoFKpkJmZiejo6KvWefvtt/HJJ58gJCQEADB58mSsWLHC5oHJPTQ061F6sRHrPz+J5PhQ/OGxqZB78AtUov6wquBXrFiBhx9+GBkZGdi5cyf++Mc/4uOPP+6x3rx587B06VKbhyT3snVvMTZ9eRoAEBXqi98vTGK5Ew2AxYLXarUoKirCxo0bAQDp6elYvXo1GhoaEBgYaPeA5B4EQcC5yiaUVTdj81enkZKoxrRxYUiOD4W3p1zseEROyWLBazQahIaGQia7dGd5mUyGkJAQaDSaHgWfnZ2Nffv2ITg4GEuWLMGkSZPsk5pczt5DF/HWZ8cBAMPD/HjBEpEN2Oz/oPnz5+Opp56CXC7H/v378cwzz2D37t0ICAiw+jMKCgoG/PPz8vIG/F534ahjZDIL+Di7GmEBcsyc4I+oYCUKC/JFy+Oo4+RIOEaWOcIYWSx4tVqNmpoamEwmyGQymEwm1NbWQq1WX7VecHBw9+PU1FSo1WqUlpZi6tSpVodJSEiAUqnsR/xLLt0oOanf73MnjjpG5TUtOFhYDV1bJZY/kIRpCWrLb7IjRx0nR8IxsmywxshgMPS5Y2zxm6ugoCDEx8cjKysLAJCVlYX4+Pgeh2dqamq6H586dQqVlZUYMYJ3p6fryzlYhmde+xYfZRchJnwIp/UlsjGrDtG88sorWLZsGd599134+/sjMzMTALB48WI899xzSExMxNq1a1FYWAipVAq5XI7XXnvtqr16ost0LQZUN7Rhw46TGD9qKO6dMQox4UN4Mw4iG7Oq4EeOHIlt27b1WL5hw4bux5dLn6gvZyt0eP7NH2AWAB8vOf7zockYqvISOxaRS+JpCjSoPv/+LJQKDzw5LwHxI4JY7kR2xIKnQVPX2IF9+ZVIvzkGs6YOFzsOkctjwZPdnanQYf32E6hpaIcgCPjlLTFiRyJyCyx4srmzFTp8+fMFdBi6YOg04VhxLfx9FJgYG4wxwwMQGugtdkQit8CCJ5sqLW/Ef6//CWZBgMrXE0qFDFPHheGpe8djiG//r3EgooFjwZPNtHYYsfKDA/DxVuDVZ1IREsA9dSIxseDJZj7bW4Lmtk68+eRNLHciB8CCpwHT1Ldh/4kqmExmmM0CduWew8zkYYiJGCJ2NCICC576SVPfho1ZhWhp70TR+QaYzUL3a8EBXlh4xxgR0xHRlVjwZLWW9k6s/OBnNLYYMDzMH+mpI3DvjFFQ/evLU4lEAqmU0w0QOQoWPPWporYFx4rr0Nreib1HytHQpMeap27CuJggsaMRkQUseLouQRDwxuY8nK1oAgAkjAzCkvsnsNyJnAQLnq6r+GIjzlY04Td3J2D2tGG8dR6Rk+GdjOm6svefh5fSg+VO5KRY8NSrsxU67DtehbTkKJY7kZPiIRrqZjCacOCkBrWN7dj+3RkE+CvxqxmjxY5FRAPEgicAwKHCarz56TG0tHcCACJDfLFycQqCAzhfO5GzYsETtE0dWLvlKEICvPDyo1MwKkoFT4WMt9AjcnIseDd3plyHD74ogLHLjGWLpiA82FfsSERkIyx4N9VpNGHdP/Lx7ZFyKDykePpXE1juRC6GBe+GtE0dePXDwyi+2IgHZsXinumj4OvFM2WIXA0L3s0cPV2Lv2w9inZ9F/7w2BSkJIaLHYmI7IQF7wYOFVZj0zd1+PC773BB04yIYF+sfPImRKv9xY5GRHbEgndBTa0GHCuuRWm5DqfLGlByUYcAXxlGRA7BbZMjkXFrDOQeMrFjEpGdseCdkNksoF1vRJdJgMFogq5Fjy7TpXnZNfVt+PuuArS0G6GQyzAyYggeTx+HCB8dpk1NFjk5EQ0mFryDEgQBGm0bDJ0mnK9qwrHiOuSX1qGl3Qiz2Ywr7rPRw+goFV5ZPB4jI4ZAJrs0G0VeXt4gJSciR8GCd1BHi2vxyoYD3c9VvkpMGB2M4AAvyKQS+Pko4CGTQu4hRYCfEnKPS0XuIZNiTHQgPGScZojI3bHgB5G+swt6gwnApfPQ80vr4O+jwLQENd7dno+mVgNefnQqAKDgrBYyqQQvLEhC+FAfjAgfwrslEVG/sODtqF1vhKa+DQajCfml9fjHt6XoNJquWsdTIcMnq+/E/vwqtOu7YDCaoJTLUFreiOFqf9wyMUKk9ETk7FjwNiQIAs5VNuFQYTUOFFbjXGXTVa+njg9H4qihAACpBGjTd+Gj7CJ8e6QczW2XJvkqKWvEuJggnCnX4WaWOxHdABb8ABm7TDB2mXH6QiMOFVWjua0Tp8saUNfYAYkEGDM8EAvnjkFkqB+8lR5Q+SkxInzIVZ/R0t6Jj3cXYeve4u5lBee0CBziiTZ9F0ZHBQz2r0VELsSqgj9//jyWLVsGnU4HlUqFzMxMREdHX7WOyWTCmjVrkJubC4lEgieffBL333+/PTKLRtdiwM8nq7AvvwoFZ+u7z2TxUsoQ4OeJmPAheOj2OEwZGwaVn9Li5/l5KzAyUoUz5ToE+Cmh8lOi8Fw91EHeAIDYYSp7/jpE5OKsKvgVK1bg4YcfRkZGBnbu3Ik//vGP+Pjjj69aZ9euXbh48SJycnKg0+kwb948pKSkIDIy0i7B7cFgNKGxWQ9tkx4NTXo0/2tu9GnjwlBV34qVHxxEp9GEiGAf3DN9FPx9lAgL8saUsaEDvnBowqihOFOuw7iYIAT4e2LPgTKEBflAIZdhWKifLX89InIzFgteq9WiqKgIGzduBACkp6dj9erVaGhoQGBgYPd6u3fvxv333w+pVIrAwDNWhu0AAAYvSURBVEDMmjULX331FZ544gn7pQdg7DLjVHkH2mWVwL/2qAX8+yRxoXvZvxe0G7rQ0PSvIm/WQ9vUgYZmPVrajb3+jI+yiwAAoYHe+P3CJESr/W02V/qE0cHY/t0ZjIsJQqC/J3blnsOeA2UYOyKw+xx2IqKBsFjwGo0GoaGhkMku7aHKZDKEhIRAo9FcVfAajQbh4f+euEqtVqO6urpfYQoKCvq1PgAUlXfgs1wtkKvt1/skEsDXUwo/Lxn8vGUYE6GAn5cX/Lxl8POSwd9LBi+lFB0GM746qoOu1YT7UnzQoDmDBk2/Y16XWRCQPlWFQA8tZHoJ5k4eAolEgpgwuc0vTuLFTtbhOFnGMbLMEcbIob5kTUhIgFJp+dj1lZKSgNAhBzAmfiwA9LpnfXnR5dc8FTKo/Dwhs/K88jtmXjpDxl53OJpyxQwC06ba5UcgLy8PSUlJ9vlwF8JxsoxjZNlgjZHBYOhzx9hiwavVatTU1MBkMkEmk8FkMqG2thZqtbrHelVVVRg/fjyAnnv09hTkL8ewMPvOjMjb1xGRs7F4kDcoKAjx8fHIysoCAGRlZSE+Pv6qwzMAMHfuXGzbtg1msxkNDQ3Yu3cv5syZY5/URERkkVXf4r3yyivYtGkT5syZg02bNmHlypUAgMWLF+PkyZMAgIyMDERGRmL27Nl44IEH8OyzzyIqKsp+yYmIqE9WHYMfOXIktm3b1mP5hg0buh/LZLLu4iciIvHxPDwiIhfFgiciclEseCIiF+UQ58EL/7rctLOzc8CfYTAYbBXHZXGMrMNxsoxjZNlgjNHlzrzcodeSCNd7ZRC1tLSgpKRE7BhERE4pNjYWfn49565yiII3m81oa2uDXC7nBUVERFYSBAFGoxE+Pj6QSnsecXeIgiciItvjl6xERC6KBU9E5KJY8ERELooFT0TkoljwREQuigVPROSiWPBERC7K6Qv+/PnzePDBBzFnzhw8+OCDuHDhgtiRRJeWloa5c+ciIyMDGRkZyM3NBQAcP34cd999N+bMmYNf//rX0Gr7dx9bZ5aZmYm0tDTExcVdddV0X9uPO25b1xun621TgHttV42NjVi8eDHmzJmDX/7yl/jd736HhoYGAH2Pg2hjJDi5Rx55RNixY4cgCIKwY8cO4ZFHHhE5kfhmzJghFBcXX7XMZDIJs2bNEg4fPiwIgiCsW7dOWLZsmRjxRHH48GGhqqqqx9j0tf2447Z1vXHqbZsSBPfbrhobG4UDBw50P//zn/8svPzyy32Og5hj5NR78FqtFkVFRUhPTwcApKeno6ioqPtvVPq3goICKJVKJCdfusP3/Pnz8dVXX4mcavAkJyf3uI9wX9uPu25bvY1TX9xtu1KpVJg2bVr384kTJ6KqqqrPcRBzjBxiNsmB0mg0CA0NhUwmA3DprlIhISHQaDQ97hnrbl588UUIgoCkpCQ8//zzPW6CHhgYCLPZDJ1OB5VKJWJS8fS1/QiCwG3rGtduU/7+/m69XZnNZmzZsgVpaWl9joOYY+TUe/DUu82bN+OLL77A9u3bIQgCVq1aJXYkcnLcpnpavXo1vL29sXDhQrGjXJdTF7xarUZNTQ1MJhMAwGQyoba2tl//xHRFl39/hUKBhx9+GEePHoVarUZVVVX3Og0NDZBKpS6/l9WXvrYfbltX622burzcHberzMxMlJWV4c0334RUKu1zHMQcI6cu+KCgIMTHxyMrKwsAkJWVhfj4eLf9JzQAtLe3o6WlBcClqUR3796N+Ph4JCQkQK/X48iRIwCATz/9FHPnzhUzquj62n64bf3b9bYpAG65Xa1duxYFBQVYt24dFAoFgL7HQcwxcvrpgs+ePYtly5ahubkZ/v7+yMzMRExMjNixRFNeXo4lS5bAZDLBbDZj5MiRWL58OUJCQnD06FGsWLECBoMBEREReP311zF06FCxIw+KNWvWICcnB/X19QgICIBKpUJ2dnaf2487blu9jdP69euvu00BcKvtqrS0FOnp6YiOjoanpycAIDIyEuvWretzHMQaI6cveCIi6p1TH6IhIqLrY8ETEbkoFjwRkYtiwRMRuSgWPBGRi2LBExG5KBY8EZGLYsETEbmo/w99RAm5/8l52gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DM181J9BSAxv",
        "outputId": "c026763c-a205-4f6c-ffc1-ef0e1ed60f30"
      },
      "source": [
        "covid_per_hari['dosis lengkap'] = 0\n",
        "for i in range(len(vaksin)-1):\n",
        "  try:\n",
        "    covid_per_hari['dosis lengkap'].iloc[i+326] = vaksin['dosis lengkap'].iloc[i]\n",
        "  except:\n",
        "    pass"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:670: SettingWithCopyWarning:\n",
            "\n",
            "\n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TI7yDDyIS2Os",
        "outputId": "8a816c60-ab42-4401-e617-1d506059a17d"
      },
      "source": [
        "covid_per_hari['dosis lengkap']"
      ],
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0             0.0\n",
              "1             0.0\n",
              "2             0.0\n",
              "3             0.0\n",
              "4             0.0\n",
              "          ...    \n",
              "523    23345264.0\n",
              "524    23777323.0\n",
              "525    24481296.0\n",
              "526    25174788.0\n",
              "527    25174788.0\n",
              "Name: dosis lengkap, Length: 528, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 535
        },
        "id": "zQBMKUtYSbAL",
        "outputId": "a5266bbd-f035-4a6f-c149-e56493fcc82c"
      },
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['minimal 1 dosis'],\n",
        "         label='Minimal 1 Dosis')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['dosis lengkap'], label='Dosis Lengkap')\n",
        "plt.xlabel('Tanggal')\n",
        "plt.title('Vaksinasi Per Hari')\n",
        "plt.legend()"
      ],
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fde30fb7410>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_qhoVthpUrVx"
      },
      "source": [
        "minimal_1_dosis = covid_per_hari['minimal 1 dosis'].iloc[-1]\n",
        "dosis_lengkap = covid_per_hari['dosis lengkap'].iloc[-1]"
      ],
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        },
        "id": "ugZ4disYSzBe",
        "outputId": "112e3c07-2196-4140-ad30-33ccff040ce0"
      },
      "source": [
        "fig, ax = plt.subplots(figsize =(16, 9))\n",
        "\n",
        "bar_x = ['Minimal 1 Dosis', 'Dosis Lengkap']\n",
        "bar_y = [minimal_1_dosis, dosis_lengkap]\n",
        "sns.barplot(bar_y, bar_x)\n",
        "\n",
        "for s in ['top', 'bottom', 'left', 'right']:\n",
        "    ax.spines[s].set_visible(False)\n",
        "\n",
        "ax.xaxis.set_ticks_position('none')\n",
        "ax.yaxis.set_ticks_position('none')\n",
        "\n",
        "ax.xaxis.set_tick_params(pad = 5)\n",
        "ax.yaxis.set_tick_params(pad = 10)\n",
        "\n",
        "ax.grid(b = True, color ='grey',\n",
        "        linestyle ='-.', linewidth = 0.5,\n",
        "        alpha = 0.2)\n",
        "\n",
        "for i in ax.patches:\n",
        "    plt.text(i.get_width()+0.2, i.get_y()+0.5,\n",
        "             str(round((i.get_width()), 2)),\n",
        "             fontsize = 10, fontweight ='bold',\n",
        "             color ='grey')\n",
        "    \n",
        "ax.set_title('Minimal 1 dosis vs dosis lengkap',\n",
        "             loc ='left', )"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning:\n",
            "\n",
            "Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.0, 1.0, 'Minimal 1 dosis vs dosis lengkap')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hgRVoR9XXaER",
        "outputId": "359959d4-a958-4c38-b843-543db549b17a"
      },
      "source": [
        "kalkulasi_kasus = 0\n",
        "kasuses = []\n",
        "kalkulasi_sembuh = 0\n",
        "sembuhes = []\n",
        "kalkulasi_meninggal = 0\n",
        "meninggales = []\n",
        "\n",
        "for i in range(len(covid_per_hari)):\n",
        "  kalkulasi_kasus += covid_per_hari['Perkembangan Kasus'].iloc[i]\n",
        "  kasuses.append(kalkulasi_kasus)\n",
        "  kalkulasi_sembuh += covid_per_hari['Sembuh'].iloc[i]\n",
        "  sembuhes.append(kalkulasi_sembuh)\n",
        "  kalkulasi_meninggal += covid_per_hari['Meninggal'].iloc[i]\n",
        "  meninggales.append(kalkulasi_meninggal)\n",
        "\n",
        "covid_per_hari['jumlah total kasus'] = kasuses\n",
        "covid_per_hari['jumlah total sembuh'] = sembuhes\n",
        "covid_per_hari['jumlah total meninggal'] = meninggales\n",
        "print(kasuses)"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[2, 2, 2, 2, 4, 4, 6, 19, 27, 34, 34, 69, 96, 117, 134, 172, 227, 309, 369, 450, 514, 579, 685, 790, 893, 1046, 1155, 1285, 1414, 1528, 1677, 1790, 1986, 2092, 2273, 2491, 2738, 2956, 3293, 3512, 3842, 4241, 4557, 4839, 5136, 5516, 5923, 6248, 6575, 6760, 7135, 7418, 7775, 8211, 8607, 8882, 9096, 9511, 9771, 10118, 10551, 10843, 11192, 11587, 12071, 12438, 12776, 13112, 13645, 14032, 14265, 14749, 15438, 16006, 16496, 17025, 17514, 18010, 18496, 19189, 20162, 20796, 21745, 22271, 22750, 23165, 23851, 24538, 25216, 25773, 26473, 26940, 27549, 28233, 28818, 29521, 30514, 31186, 32033, 33075, 34316, 35295, 36406, 37420, 38277, 39294, 40400, 41431, 42762, 43803, 45029, 45891, 46845, 47896, 49009, 50187, 51427, 52812, 54010, 55092, 56385, 57770, 59394, 60695, 62142, 63749, 64958, 66226, 68079, 70736, 72347, 74018, 75699, 76981, 78572, 80094, 81668, 83130, 84882, 86521, 88214, 89869, 91751, 93657, 95418, 97286, 98778, 100303, 102051, 104432, 106336, 108376, 109936, 111455, 113134, 115056, 116871, 118753, 121226, 123503, 125396, 127083, 128776, 130718, 132816, 135123, 137468, 139549, 141370, 143043, 144945, 147211, 149408, 151498, 153535, 155412, 157859, 160165, 162884, 165887, 169195, 172053, 174796, 177571, 180646, 184268, 187537, 190665, 194109, 196989, 200035, 203342, 207203, 210940, 214746, 218382, 221523, 225030, 228993, 232628, 236519, 240687, 244676, 248852, 252923, 257388, 262022, 266845, 271339, 275213, 278722, 282724, 287008, 291182, 295499, 299506, 303498, 307120, 311176, 315714, 320564, 324658, 328952, 333449, 336716, 340622, 344749, 349160, 353461, 357762, 361867, 365240, 368842, 373109, 377541, 381910, 385980, 389712, 392934, 396454, 400483, 404048, 406945, 410088, 412784, 415402, 418375, 421731, 425796, 429574, 433836, 437716, 440569, 444348, 448118, 452291, 457735, 463007, 467113, 470648, 474455, 478720, 483518, 488310, 493308, 497668, 502110, 506302, 511836, 516753, 522581, 527999, 534266, 538883, 543975, 549508, 557877, 563680, 569707, 575796, 581550, 586842, 592900, 598933, 605243, 611631, 617820, 623309, 629429, 636154, 643508, 650197, 657948, 664930, 671778, 678125, 685639, 692838, 700097, 706837, 713365, 719219, 727122, 735124, 743198, 751270, 758473, 765350, 772103, 779548, 788402, 797723, 808340, 818386, 828026, 836718, 846765, 858043, 869600, 882418, 896642, 907929, 917015, 927380, 939948, 951651, 965283, 977474, 989262, 999256, 1012350, 1024334, 1038029, 1051831, 1066349, 1078350, 1089344, 1099723, 1111707, 1123141, 1134890, 1147044, 1157871, 1166113, 1174813, 1183589, 1192024, 1201893, 1210737, 1217502, 1223964, 1233993, 1243680, 1252719, 1263333, 1271387, 1278687, 1288867, 1298642, 1306175, 1314668, 1322900, 1329108, 1334668, 1341348, 1347060, 1353868, 1361132, 1368103, 1373870, 1379696, 1386590, 1392979, 1398612, 1403756, 1410168, 1414775, 1419489, 1425078, 1430492, 1437317, 1443887, 1450166, 1455822, 1460218, 1465962, 1471259, 1476486, 1482593, 1487575, 1492036, 1496119, 1501127, 1505809, 1511746, 1517888, 1523213, 1527558, 1534289, 1538001, 1542550, 1547410, 1552914, 1558179, 1562902, 1567029, 1571858, 1577560, 1583216, 1589393, 1594756, 1599797, 1604382, 1609334, 1614883, 1620603, 1626846, 1632282, 1636826, 1641228, 1647172, 1651817, 1657058, 1662891, 1668391, 1672903, 1677297, 1682027, 1686396, 1691681, 1697328, 1703655, 1709785, 1713707, 1718598, 1723619, 1728227, 1731675, 1734308, 1736693, 1739773, 1744068, 1748253, 1753124, 1758921, 1764667, 1769963, 1775243, 1781150, 1786210, 1791244, 1797522, 1803384, 1809949, 1816064, 1821726, 1826550, 1831796, 1837149, 1843635, 1850229, 1856061, 1863054, 1869348, 1877073, 1885965, 1894048, 1901513, 1911381, 1919570, 1927731, 1937675, 1950299, 1963289, 1976195, 1989932, 2004468, 2018136, 2033444, 2054018, 2072890, 2093985, 2115327, 2136021, 2156488, 2178295, 2203131, 2228961, 2256874, 2284107, 2313852, 2345041, 2379420, 2417811, 2455935, 2491029, 2527226, 2567653, 2615552, 2670069, 2726826, 2780826, 2832778, 2877499, 2911756, 2950081, 2983853, 3033362, 3082433, 3127849, 3166528, 3194756, 3239959, 3287750, 3331229, 3372397, 3409681, 3440419, 3462823, 3496723, 3532590, 3568354, 3607886, 3639639, 3666054, 3686763, 3718844, 3749469]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fw6TqOGLY_te",
        "outputId": "412c75a1-59a9-4145-d458-02aa2911ba74"
      },
      "source": [
        "covid_per_hari['jumlah total kasus']"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0            2\n",
              "1            2\n",
              "2            2\n",
              "3            2\n",
              "4            4\n",
              "        ...   \n",
              "523    3639639\n",
              "524    3666054\n",
              "525    3686763\n",
              "526    3718844\n",
              "527    3749469\n",
              "Name: jumlah total kasus, Length: 528, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 535
        },
        "id": "XhdYu_J9UHKi",
        "outputId": "ed6c7090-baff-4ae3-fe1d-5850ee6e8674"
      },
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['minimal 1 dosis'],\n",
        "         label='Minimal 1 Dosis', linestyle='dashed')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['dosis lengkap'], label='Dosis Lengkap',linestyle='dashed')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['jumlah total kasus'],\n",
        "         label='Jumlah Total Kasus')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['jumlah total sembuh'], label='Jumlah Total Sembuh')\n",
        "plt.plot(covid_per_hari['tanggal'], covid_per_hari['jumlah total meninggal'],\n",
        "         label='Jumlah Total Meninggal')\n",
        "plt.xlabel('Tanggal')\n",
        "plt.title('Perkembangan')\n",
        "plt.legend()"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fde30136e50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0KHvgwr3WWEe"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}