Collaborative_Filtering.ipynb

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  "metadata": {
    "colab": {
      "name": "Collaborative Filtering.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOklmqtnvez2iirmfZGP2s7",
      "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/ashikshafi08/Learning-Fastai/blob/main/Collaborative_Filtering.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WZ_kIMN9EndD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "16be7ffe-453e-4cbe-9a87-69de670a577d"
      },
      "source": [
        "!pip install fastai -q --upgrade"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[K     |████████████████████████████████| 189 kB 7.6 MB/s \n",
            "\u001b[K     |████████████████████████████████| 56 kB 4.5 MB/s \n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rGowB9OzE2Yv",
        "outputId": "d2a1da03-a105-48ff-8e2c-dfdedf074074"
      },
      "source": [
        "# Importing the needed stuffs \n",
        "import fastai \n",
        "from fastai.collab import * \n",
        "from fastai.tabular.all import * \n",
        "print(fastai.__version__)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.5.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pc0w0WHRFNCa"
      },
      "source": [
        "# Collaborative Filtering Deep Dive \n",
        "\n",
        "A very common problem to solve in deeplearning is when you have a number of users and a number of products, and you want to recommend which products are most likely to be useful for which uses.\n",
        "\n",
        "Also there are many variations of this for example, \n",
        "- Recommending movies (such as Netflix) \n",
        "- Figuring out what to highlight for a user on a home page. \n",
        "- Deciding what stories to show in a social media feed. \n",
        "\n",
        "The above examples can be solved by using a method called collaborative filtering, which works like this: **look at what products the current user has used or liked, find other users that have used or liked the similar products, and then recommend other products that those users have used or liked**. \n",
        "\n",
        "For example, on Netflix you may have watched lots of movies that are science fiction or full of action, and that were made in the 1970s. Netflix may not know these particular properties of the file we watched., but it will be able to see that other people that have watched the same movies that you watched also tended to watch other movies that are science fiction. \n",
        "\n",
        "In a nutshell we dont wanna know anything about the movie, except who like to watch them. And in collaborative filtering we more commonly refer to **items**, rather than *products*. Items could be links that the people click on, diagnoses that are selected for the patients and so forth. \n",
        "\n",
        "The key foundational idea is that of **latent factors** in the collaborative filtering. \n",
        "\n",
        "In the Netflix example, we started with a assumption that you like old, action packed sci-fi movies. But we never actually told Netflix that we like these kind of movies. Still, there must be some underlying concept of sci-fi, action, and movie age, and these concepts must be relevant for at least some people's movie watching decisions."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "XMSAYNWpYcaO",
        "outputId": "27266a0f-1c18-4190-d17e-a6421682b8fb"
      },
      "source": [
        "# Getting the data \n",
        "path = untar_data(URLs.ML_100k)\n",
        "\n",
        "# Looking into the data \n",
        "path.ls()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "        <style>\n",
              "            /* Turns off some styling */\n",
              "            progress {\n",
              "                /* gets rid of default border in Firefox and Opera. */\n",
              "                border: none;\n",
              "                /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
              "                background-size: auto;\n",
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              "      100.15% [4931584/4924029 00:00<00:00]\n",
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            "text/plain": [
              "<IPython.core.display.HTML object>"
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          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(#23) [Path('/root/.fastai/data/ml-100k/u.user'),Path('/root/.fastai/data/ml-100k/u.occupation'),Path('/root/.fastai/data/ml-100k/u.genre'),Path('/root/.fastai/data/ml-100k/README'),Path('/root/.fastai/data/ml-100k/u3.base'),Path('/root/.fastai/data/ml-100k/u4.test'),Path('/root/.fastai/data/ml-100k/u4.base'),Path('/root/.fastai/data/ml-100k/u2.base'),Path('/root/.fastai/data/ml-100k/ub.test'),Path('/root/.fastai/data/ml-100k/u3.test')...]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "LYtiaYbvYqn4",
        "outputId": "52e4f4ef-de61-40f5-cc73-314f29dcb7b9"
      },
      "source": [
        "# Loading in the data \n",
        "ratings = pd.read_csv(path/'u.data' , delimiter='\\t' , header = None , \n",
        "                      names = ['user' , 'movie', 'rating', 'timestamp'])\n",
        "\n",
        "ratings.head()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user</th>\n",
              "      <th>movie</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>196</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>881250949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>186</td>\n",
              "      <td>302</td>\n",
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              "      <td>891717742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>22</td>\n",
              "      <td>377</td>\n",
              "      <td>1</td>\n",
              "      <td>878887116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>244</td>\n",
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              "      <td>2</td>\n",
              "      <td>880606923</td>\n",
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              "      <td>886397596</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   user  movie  rating  timestamp\n",
              "0   196    242       3  881250949\n",
              "1   186    302       3  891717742\n",
              "2    22    377       1  878887116\n",
              "3   244     51       2  880606923\n",
              "4   166    346       1  886397596"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xytpd-vQaYfh"
      },
      "source": [
        "![Screenshot 2021-07-20 at 3.46.18 PM.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JqhXsBb1awdv"
      },
      "source": [
        "For each user, we would like to figure out which of those movies they might be most likely to enjoy. \n",
        "\n",
        "If we knnew for each user to what degree they liked each important category that a movie might fall into, such as genre, age , preferred directors and actors and so forth. \n",
        "\n",
        "We knew the same information about each movie, then a simple way to fill in the above table would be multiplying this information together for each movie and use a combination. \n",
        "\n",
        "For instance, assumig these factors ranging between -1 and +1, with positive numbers indicating stronger matches and negative numbers indicating weaker matches, and the categories can be `[sci-fic , action , old movies]`, then we would represent the movie `The Last Skywalker` as:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3UiyGzRhavW-"
      },
      "source": [
        "last_skywalker = np.array([0.98 , 0.9 , -0.9])"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1VJI_IV2cuZK"
      },
      "source": [
        "Here for instance we are scoring the movie, very sci-fi as 0.98, very action as 0.9 and very not old as -0.9. And we would represent a user who likes modern sci-fi movie as: \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DVyo90RzdKMC"
      },
      "source": [
        "# A random user who likes sci-fi movies \n",
        "user_1 = np.array([0.9 , 0.8 , -0.6])"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "69Om2zMwdSPM",
        "outputId": "6b719f6f-7116-4bd2-f573-384016b33452"
      },
      "source": [
        "# Calculating the match between two \n",
        "(user_1 * last_skywalker).sum()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.1420000000000003"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OaE0CR8Mdj0o"
      },
      "source": [
        "When we multiply two vectors together and add up the results, this is known as **dot product**. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PEXdIYnHdtTC",
        "outputId": "ac363b52-5c39-48dc-e926-67f934ce6f16"
      },
      "source": [
        "# Representing the movie casablanca \n",
        "casablanca = np.array([-0.99 , -0.3 , 0.8])\n",
        "\n",
        "# Finding the combination \n",
        "(user_1 * casablanca).sum()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-1.611"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S8Ve6l3ieCpv"
      },
      "source": [
        "## Learning the Latent Factors \n",
        "\n",
        "There will be a little difference between specifiying the structure of a model, as we did in the previous lecture and the current one. \n",
        "\n",
        "**Step 1 of this approach** \n",
        "- Randomly intialize some parameters. These parameters will be a set of latent factors for each user and movie.\n",
        "- We will have to decide how many to use, but for now we will use just 5 for now. \n",
        "- Nowe each user and movie will have a set of these factors in the below cross tab and we can show these randomly intialized values right next to the users and movies in our cross tab and we can fill in the dot products for each of these combinations in the middle. \n",
        "\n",
        "![Screenshot 2021-07-20 at 4.25.55 PM.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAsEAAAEyCAYAAAAbXw1eAAABSGlDQ1BJQ0MgUHJvZmlsZQAAKJFjYGASSSwoyGFhYGDIzSspCnJ3UoiIjFJgf8rAziDCwM/AxMCbmFxc4BgQ4ANUwgCjUcG3awyMIPqyLsis50llyT7Z572cbd+mlDDtU8JUjwK4UlKLk4H0HyBOTy4oKmFgYEwBspXLSwpA7A4gW6QI6Cggew6InQ5hbwCxkyDsI2A1IUHOQPYNIFsgOSMRaAbjCyBbJwlJPB2JDbUXBHidUvMCFdzDjUzMTT0IuJdkUJJaUQKinfMLKosy0zNKFByBoZSq4JmXrKejYGRgZMjAAApziOrPQeCwZBTbhxDLX8LAYPGNgYF5IkIsaQoDw/Y2BgaJWwgxlXkMDPwtDAzbDhUkFiXCHcD4jaU4zdgIwuaxZ2Bgvfv//2cNBgb2iQwMfyf+//978f//fxcDzb/NwHCgEgCuC2A+OGYuLQAAAFZlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA5KGAAcAAAASAAAARKACAAQAAAABAAACwaADAAQAAAABAAABMgAAAABBU0NJSQAAAFNjcmVlbnNob3TecimpAAAB1mlUWHRYTUw6Y29tLmFkb2JlLnhtcAAAAAAAPHg6eG1wbWV0YSB4bWxuczp4PSJhZG9iZTpuczptZXRhLyIgeDp4bXB0az0iWE1QIENvcmUgNi4wLjAiPgogICA8cmRmOlJERiB4bWxuczpyZGY9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkvMDIvMjItcmRmLXN5bnRheC1ucyMiPgogICAgICA8cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0iIgogICAgICAgICAgICB4bWxuczpleGlmPSJodHRwOi8vbnMuYWRvYmUuY29tL2V4aWYvMS4wLyI+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj4zMDY8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICAgICA8ZXhpZjpQaXhlbFhEaW1lbnNpb24+NzA1PC9leGlmOlBpeGVsWERpbWVuc2lvbj4KICAgICAgICAgPGV4aWY6VXNlckNvbW1lbnQ+U2NyZWVuc2hvdDwvZXhpZjpVc2VyQ29tbWVudD4KICAgICAgPC9yZGY6RGVzY3JpcHRpb24+CiAgIDwvcmRmOlJERj4KPC94OnhtcG1ldGE+CqMTUBUAAEAASURBVHgB7L0HeFxXdib4I6MQCzlngAHMOUpUlthKrXa37W5P2+NxGNuzs2uv51vvzqzDN96d/cbemd5xt+2Zzm5J3cqkSJFizpkgcs45VxVyIRSA/f9bBAlSgSi0pG5Z73VTAKree/fec88995xzz/mP3zwvWJdFAYsCFgUsClgUsChgUcCigEWBLxAF/L9AY7WGalHAooBFAYsCFgUsClgUsChgUcBQwFKCLUawKGBRwKKARQGLAhYFLApYFPjCUcBSgr9wU24N2KKARQGLAhYFLApYFLAoYFHAUoItHrAoYFHAooBFAYsCFgUsClgU+MJRwFKCv3BTbg3YooBFAYsCFgUsClgUsChgUcBSgi0esChgUcCigEUBiwIWBSwKWBT4wlHAUoK/cFNuDdiigEUBiwIWBSwKWBSwKGBRwFKCLR6wKGBRwKKARQGLAhYFLApYFPjCUcBSgr9wU24N2KKARQGLAhYFLApYFLAoYFHAUoItHrAoYFHAooBFAYsCFgUsClgU+MJRwFKCv3BTbg3YooBFAYsCFgUsClgUsChgUcBSgi0esCjwCVFgdnYes545zPHnZ33Nz81jZmoWc/xpXRYFLApYFLAoYFHAosCDKRD44FusOywKWBRYCgXGh6YwMz0L/wA/BAUHLOWRT+YeP1D5nseo042Y5HCE2ALh588PrcuigEUBiwIWBSwKfA4p4MctzI//+bR3MksJ/hwyh9XlXz4KzNMB21Daj7qSPsSmhFMZnvvMOhkY6I/QsECUnG3HM/9qPRLz7PDnZ9ZlUcCigEUBiwIWBT5vFJACHExnki3Y3yjCn2b/LSX406Su9e4vDAVkrYZHByMqIQwpq+IRFBn8mY1d1vL06BTiG1yYCwnA0OQs5v1mP7P2rYYsClgUsChgUcCiwCdFAX/uaeFUgEOC/PFpH2paSvAnNWvWe77YFKAWHB4VjORcO+ZDAzE9/2kf4iwiN73Qc0GBSMiKhp8tCEb9tUKDFxHI+tWigEUBiwIWBT4/FJiHOUv9DPYxSwn+/HCF1dNfZgpIEeWqnZ2dgwlEUHzEEq/5+TmGT0xjntFPwSEh98RAzfM9c7MeTE1N8W2KNQ5GQIA/PLx/xuNBYFAw/wXBJMbNMDFu6c2a3s2z0zMzU2zbH4GBgXz3vbHMan/WM4PJySnYwsKNVT4zM41pts+YC9hCQ01/ljjUe27Te/Uez+wsxx2KoMAg+C8y+0WXKbbr5+9/D108bF/P+PkHIIT0WO7lmZ6Cchj9+Z4gGhELl9qdJW0nJ90keSBCQkPAkzkzR1MaNy/1V3Mlj4Wv19zcLN81xbHPcD5D2LZ3Thfe4/FwbtmOEi0NXdg30cp8xgkOCbVxrgKWfUyod82SfvN+AQjmu3WSYC7xGvlhcnLC8LL4KoRjBLlj0j1h+uP9LJTPLPTWt5/eOZ300nwRr8+TJtOkydSUl77i9RDyVrCZ33lMT03e5tEgM3bfWtUQ5uExfDypQEOOizTU2Be9SHMi3tY6Fo0DyIv6e2ZmxvBaqM3GfvN4dtEzS/1VPCten2M/vLx+l+7ih+nJScxwTsQLWuOSIdNTbq7xWQRwXYjXAtj2si62qbHNsecBAYH30E/zIVli+NqsZ/E0eZ1jlszxZ9vigcD75MKS+yG6S35xHYfawj4gK2amOW6uA/XNjJFtT5EWWt+6/Pz8YQsPN3JpuXSf5YT6ideDg+7ptmSf+EpyVDQW7f395uF2u40s1jwsX77MUyZrLU3ekdGL+78gVyUDRBfJPTMXojufkWyV3AmiTF7OpT1D/D4HrfF75areN8NxT7Mt7zojr2tPEa8bHiX/s0+B/OyObPChExrH9O11HMw1vHjc3r2M88sE8iDylfqmte+eoMwhr/iTP4MpE0ND7p0rH5r3+daAv+Ll81PWAxYFLAp8gALDDjfGxmYQEE7FbJEy94EbF3/AhT85MYbBgT6jAISFR93zqIcK6uiwC8NDQ5icmuF3FCkUMs7BfrY1ymc8RkkMCgjCWN8YYjKjEbDEpDyz+VK5GeztwpjbuxGE3LdReLhJDTkG0dnZicjoGApPN0ZcTrhcLoyNjFGQhRrlebHyunh4H/W7BN/IkBNOxwBGRka4WUwboS9FXEJTG8jE2DD6eroorGcRHuGli54bcvTD5XRg2gNEhIf5LKi9G9A0nAO9GBkdo+fcH2G20DtdnaYSOOJywOl0YpTf+3NDkuI44uzHoMOFifFxbprBkICXouTLpQ1iclzz3WvmdILKgQwPbXjecc9imGNzkS6jo6Oc82luCoGk9TBpNYix0XFMzcxRMaHxQ0XY10vjGB3i+zm2yel5hIeFGsVO75nlxjkx4oTD4eCcDBkFTEqQZ5L9HRxgf11GWQo0BovvSrj4bWJ0BD3dXZilMh8WHnmH1+e4AY8MD5l2xnmP2gugUmKj4jnL7/q62sij06R7IDdIKea+XVIoR4ad5r2jpCV3W9KPCvVt5U4G0bD4mnSREhQYHEpeHzdjdvHzCc6ZPhPNpQj7chmedQ7w3YNmTqe4jm1hUjw4f+QHKaiD/b0YYjtufifjLohfOfr7zGfiERljNvKIr5cxcvl+Z383RselXAXc857JiVHvuLmeR0dGzRjn52Y4T0NwDA5ieHiYSpyUFSrHPvI6B2eUzCGOu5vyIyLabmjuNaC8SqLj9rjHuKbE66E8/naS/4fIa+IHx6CDcsdujFRfFTLxzTDpPjw0AuYrG1mxQL87sq+/38gfihvpg1ybWmdOfjZKY2jeK9+oDPp6yYge4xrq7uokyYO8iu4dUUG60MDWGu/r7UGkPdYooVOUxV4edBlZLwPQawT61roUzXG27eQaGmNonI2ybYHPjezjnuKiLBnmnMvoFF/7zXtM20P8TIp7kOH1wGXNuZv7Un9fDybckwiPZH7Kwrgl+zhGw9eU/ZLr/qTtvGcKbS3NmKAiPCMnEhVh8Xow81rCuZf5zne+0ctSgn2jl3W3RYGPpIDvSrA2gmkUXzyJd9/4CRq7HFi/ebvZAE0jUnYHenDi3dfQPzjOTcFllIDJkW4cfPcQpibGcetmEeYDbUhLTsG4j0rw1PgIGksv49XvfwcXipuwqnAd4mIi7xmfo6cNx1//Lr7341ewdd9+9DWV4vzJ99HVM4ji88fhiUxFfGw0bFTKfLlmJ0dx4fi7OH36LIYGO3H82CmsWrcBkZFexcgzNYGLR9/BK9//B/QOe7BhyzZDF4+eO/IafvLyy4w/ScXqgmyflZJZeloHWmtw4NUf4f1T5xlGUojM1Pg73e9qrsb777yK7sExVF45C+cUPeRzkzj5xg/R2DdKZXgQQbZoJCbE+6wEz8240VxTgp/+5BV6P4Zw6sgRhEQnICMzw3j/PJPDOMn5vnzlOvq7mnHy5HkU5GXg2rlTKCoqgbOvG+cu3MDqwlU0DMKN4nyn40v4ZWywC2ffexPvvPkaRgPiDP0WlOnxERcuvfdTFNW0oLOhArV1dTToYtFefALnLhWjta4cVWWlCIxOQ3JijI+eSW78VLjOH34DL3//7zHsCcHa9Ru5OXs7rY27rb4CVVVVNHw68O5rP4RfWCLy87Ix7ujGD//ur3HifAnyC9cjKT5mCSO995a+9nqcP/IGympa0Vh8Hu2OGSQkpSA6MpweuHm4eppw6v2jqK5uMspvoC0WjtYynD93Fu0dnai5eQFDpFdKQiyV8KXzuvHuuYdw5K1XOH/F6GlvwPmL17nOt5hTFCmcIwPtOH74KNoay3Hx0jW64aKQHOWPE++9hxbS5PKVK5gOiMTKvKx7B7WEv2a4jrrqivHGP30XJy7eQlbBWo7hLv2aq27i1NF30dXnROmFU5gMJU/PjKL86lk0NDbj/bdfRnBsBpKSkhFKY8yni/Kro7EKB7nOXnnlJ9iy73nYo7ynSUY5n3Dg9R99D00tHehqacS14nIUrs5HRekttFMpqq+uxGt67uEnYY+M8DoAltgBvd/Vw/6/9SoOHT6MkIQ8FGSn3nlasq+t5gYOHDxJhX/YGIRBVMDPH3oZjR39THK+gZb2XsSnZbHtsDvPLekXjnt82IETbPsnP/gHhLHt3Nxc3MlV5vfNVcV45+Uf4s2338KOx15ABBF92urLcfiNn2JodMYYP3Hkz4gIGvlLavTuTeNDfbhx5gjefPkHaHH5YW1h/h3DZ252BgNtVXjv4Htoa++mkTKB0Kg4zAx34sSRo2hoaONn4wgOj4c9mnPlk8Gn/WwG108dxk9/+N9R1dSN7bv30Ztt7AueaE6jv7MBp4+fRHsT19alIkTHJiB8fgTf+q9/R5uJjpGRCcQkphqaf1ZKsO8mzl1aW79ZFLAo8HNRQPAvfojPWIkN69dxk7mtEdx+p2d6As7eFgxOh2LtxnVYu2EjYqNt6GkshT1jLXY98hTyUsPQ0liDSR6b0vHi0xXIY6fgqAQ8vf9peipC+fi9L5gaH0JnawMaHQEoyEjhJuSPttoyzNsS8cSzz+HxfZtx49IlDA2P+tSuOjo00InWbid27/817H/x15EcTm+fg55tegd0yUuWtWYbtm5ac2fzlUetsboMPY5xbN60kQL33v4utRPyNASF2bFv/4vISk82StDiZwe629E5OIfHn3sRzzz7JNobKtHb72C3A5C7ZgM27diNnOx0nxVgtSFPa2dTNfK2P41nv/Ib2LUpGz0d7ZiY5NElx+fsakRL3wT2funX8MwLX0PkvBPNLa1o6x3B1kf34/EvPYc5Zy0cYxM8MvZ9/CG2CKzYsAM7Nq36wLjVv0F6/9JzVmPF6vWICmA4Cufj+rUiPLz/y/jqv/htrF+dgcqKSm5o3nnSM0u9FEqRt2kPtm5YSY/fvbwur++K9Tvw5P7nsH3jasTEpSMzO4f0cqHk4hHG2q+nJy9i2XPe206lqnMMX/nGb+JXvv4b6GmuRW/fgOm6lOC6susYnwvGrn37sGb9ZqSnJ2JmYgD+wdHIX7EGWcmxGBsapVJwb78fNHYp9wMddWjpn8ZDnNOnnvsKgif70Oca50kGPWH+QYhKzMZLv/Ev8fyvcB3EhKCjqx/hsWl44dd/Cy989evIS09AIxXF5Vw6sQiKiMNj+5+lsWonD9/LM11NNZiYj+J6fh5PPr4Dt65cxmxQFB578Rt49qWvYeu6AnT39MNjXKW+9sAPEfZ47P7SV5GeEOVdL4ua99AgbO0YRO6KVVhZuAbTY24E0eh66PH9ePTxx7F140rkrN2FBKOM+agK0t0cHBaJzQ89jrWrcj7ANyM8DTn7/hGs2LoL67fuQOGaVfCb86C2vgN7n34W+7/8IoI9DjRTUfT5YtsKnVn/0NNYvzKTXvT71Sw/RMYmYfdTzyMxxqvcz7hH0FJXBY89F1u2bcbGrVuMgebjqE1Xg0OZnJ27Go/s2eKV6YtortCTootnEJyQhe1796Jw/SbEsw/Vt67AE2LHzocfwpoNm5CaGuejAuylEqNJkJi9Gtu2b0FYyL1Gkx894glp+XjmxZfw0EOPweZHx45OJ/hMRFwS1m3ehs3bt3GPi/CZ5D/PA/f28ud5k/WsRQGLAkugAPF86dHVkas/N6iY2Dhk5a9AZ901BEwsxEN6X6PjvKGBLh7RjaKByp+OwfNXrqSVHo3pAQccDKEYGhrG2FSIOV5eJOuW0A8qmjzizMpfCf+JHu/R7D1PzdNr1UxvYDN27t2DG8deNzGNdva3u9WB3q52hjMM81it3xyp3fPoR/wxQe/LKMM6pqm8TQ72AYHhHH8Mj8XDER1ug2tsnOPQuSSP4QJDkbdyFaov2zDFTWWOx/jjowMovn4ZKVkrMOHowCTpo7hZOSt4y5IvxRnGJKcDnokPjfmLiopGsP80j+ga4G+OsR0mti4+ORG9TVUYaCxD4aZdyMsvWJLA1nG3i+OVfj8zPmDmLK4w0YR42GPi0d87YRQiBPvxCNXJ+Y2FPcaOMMLeRTHRcWKO9Jif4jFiL2weeqIZPjI26jYxdF4fy5KHTuU/GmnpaeiosWHkvscUL7pi9SqcvXYafjyiTM5eiWgb0UZGJxEXG4loeySiYhIw1Nr5oQr0fa+7708/+AfZkFuwEqU0uDz3eZg0J4qPVihKdfE1JK3ageS4KAx2t6K0eYQb+kY0tlFB4zGzjql9OyKd57H+EIKpDMbF2ZlESmWL9Bzlsa25qBh2t9ZzDqJRxbYVJpFDhTw8NhOzlRdx6Xw7guml2rc9y2fDR57gUdcAQqMTST87wkNmERVKmtKIUfw1GKsq4yAiKgBt3U3UB4KRV5BnYlTDI/0x1NfOY+M5rFyz4j56Lu1PGXxJGTnwm3QypOCDcZaSP/M0CLo7W+F2DTFko88YV8H0dk9ODGOEYVLphSmEqvrgsw/sARdlbFKaCasJosv/njXKP4JtdqxbnYriq+d5ZB9GL/VqwmIxFpZtu9xjqC66jh0PPW9ikn1Y3qZbCp0IsycgRZ5Ohi3df7kZ3tJNwzbG0YWizlp6fHORRC9/HBXCtpYmxPi7jXEfxlCKpVwyYF2Ux5MzHoa6RCAqOhrZuXlmLHIe3HOxb0np2XBTrgcp1IKD8zBcx8HwCM+oHypLbmB80oM9jz3BtZruveeeF3z8H4GhEcaAHO4oA4bvpZz62Um5HpYWifKblxn7G4mc1RvQRmNoNjIbFUVXTShE3vrtWFWQfceD/PEtLnzLtqjo5q9ei7aqKwhw3ks7rXEZnAM97WiqLsdcWII5eQwJC0NMeBCqy4p4+tCCdVTCV6zIM8rxwps/zZ/3zc6n2ZT1bosCFgVEAUd3C6orSlBTW8sNYt4cK5t4N2qxEhL6Z5KgqPhJEQ60RWHNpm3wc/ejsrIaaat2ITFkGtcvnUEnBbm8PQEUrPeKuwfTWkLJ69m6rT7zh4Sk4oCVVNFQehWT80wY8WN829gYle4B5KzZiYK0WFw4cRglFTUUojaTyPPg1uYxwSPC8uIbKLl1C+OMZVZbilGdYxyYYkQl9aTkmKQ7jkd9W6CL7utvrUabg2oCzxVHGfM2zLCESXo2RC9fLr1TCh9/mDZNy3yH4kI9bD85exUe273FhHtcuXaDCWT+sCek4omvfBPPPP0MMuxBuHTmNAZc9wr5j+rDHI8IGyuLUcJNXR5ljdXDpBQzfupBpv9UlhSLp0mUcqTxKnlNCl9ETBJ2bduK3robuHj+PBh2Tpoz2cU7gI9q9kM/96eHfeE5QzWOW22pPzPcwBWHHMpNKYretyHOl5RHXeqLSa5i36RY+ap86x1eunNO+T+dOpj/cdxKBDJj5VGt4sBvldVj5+6dCKNR0FJbDntSOib5uZv/ZAB4yC++XxwtaasxKgFPxWREdzPnfJ9+BkfEcJ1tRmTAKE6dYhgM4yNFo7jEOLbpZvxmr0kY861tjpYK/5051dxyTkUBJZ9pnSshydHXgRqujcjUFdhAz6XmxDXQjfrym5gPS8a2dSt9a/b23Qs019i1vsz/2AclpHnoic7macv6ggxcOXUERSXlRgEKYBboKGM2FRIwNBeLwpV5DAFZjr9Ma1gyxqtmaJmqfZN0ytjQKeZCaCrDGPPrT0hH52Avprj+1LeejhY09E1j08Y1H6q8L4UY3jWugatV72WSakl3rXMZ3IlZBdi4cS2aKm+ii8WGHn/iKbSUXsL5s+dpAEwhnKcPS7nmaSS11ZWhlGu8pU1ee8mYAPOoaZ2D13qfpPPDa8SRLguxxvxOvCi62GISsXnnLobilKK6tnFZpz2Sm6K5vLJ8sRm7d40roZi8Tn6z2ROxbtMm+I134dLVIpOYFhIZR2/sZoTNOXH67KUlOzfupc/tOb8tmxbGPs0kS5N0x5MRybk59nGMcepDPF0JtqfgN/7l72LPnr3oqyvC+QtXTMLyve/99P5aDmd/er2x3mxR4AtAgcSMfEQmZHBz5LF8IDPQmakrAajEJGUr26hkKDEk0H+WClACoiIcPAqORHxSArpccwjlZr3v2V/D3AzjZhl/NRuRRTxFClyz0S2dgAovkEBUcoR+zjBWdpJxxlOM3fQPCaejNg42xqjqmG6ICTLykORm7sXOp76CDXtGcPPkG7AH01sYtZSNwnsEuGn7Hq+Ao2fKM3mL3s1+JEYEwDnixnq+Z4oeoJmJecQnJvB3bdTcFOeZMU0lhbnzyMlMQjc9GR2dPZgOpledyVJK7vLl0oYjz7Iy4pX9L0NDmfCTIw74BfN4Mjgca/Y+jVW7Hkdd0RlUdLiRREVI4SNRPGpMzSlAbcdNKuBLCwkICgrF6k07jQfcj8rUYHst+rs7eSKQbZJEgkPTeBQ7g0EmZYVFxNJYuMFY8AEqY3a4JjxIjI1FxuoChgts4ZF8H4aZ2JVAj1XgnYyTpY9em6GMDINU4MefVAimlZnNiORhhrVcu1qMX/mf/gPsQYxVZzx0TUMHvfSBGBgcoTdxjAlWPUhJy7mj2Cy9Ze7HVDqmmBBkFGq1y9+DiGs9yLHaY2IQSGPL1V0Pty0VGYw5DvGbpEJOr/yoE3W1vfSSu9DX12eUSF/a1cKIZEzp9Fg9E3Yc8Ax20Bscjkgmp+lUxi8kEvbEFMZ5x9E7H4HUjFSUdHai/NJxJK57Crt3b4erjTGcp65h45qVjGtdCr97eyhlJJpH32POYp4GDCI4JhTD7jnER4XBzQRADw06xUyef/9naHPF40vPbaa3ONCsg2vnDqKm3R9PMVwpMizYKDM+LnFDcxk43jXuNXaEejJJmvrTExvIsKCtj7+AdbsnUHr+IJonk2h8AC0Nt3DkdBG++lu/g5joKPMeanW+kZ13e+ULlR6uOc29MTqUbEsD1uNsRLMzFC999VnY5sfxsx98FwOMCUUwE6Va25C18SEk2Rn37uugb/dygde9DgXx/AzcPGmZD+AA+S+WpzBK3IoIm0I0j+CFlpK5bof518XTnmvXGUOdmbykMSt5Nm/tFqRTJoTYwsXsVHjHjfGj9iXXETBP/qO8S0oiKf35GRE7SBfNRzThNSOimCAXGmsSAZOSE6i/EsHljvq+pG6YmxSCozYl32ZnA4yx5ablLKNnZt6fRl0KomI19kjyegraGqYYH59KBTye8oefZaaicmCQ71owHZbetp7Rupbc1j8p/drPlMgsJBolAGcWrEf+qjVw0hnU2tiAHds2sd1ozPM0MC0tCZ08oaGo+MyuAIJD/NVn1prVkEWBf8YUWFpinJ/JtrbR26asXcxP4yYTzCqrytE76KLA8iCVyu6hV78HW1wmUngE31xxA82tzXDwuLJg3VaEzgzj7IkTaKirpZcoAbv2PoQIZsz7ig4h71rtrcs4c+Ei2traCFFk47FnIG4dfx2uwDRs3bED6zdtQVZODlz9XXjiy9/gxtWOi6dPo7KsAoOTgdj/3JcY10bkhiUoZPLMhIWFM/whgkIvCu7BdlSUFKO5oQ6hsXnYsWM9yi4cQ1nzIArz05jI9DbKykvRM+Ci4uyHTbsZ37d+A1asLEBIwBySC7ZgfSETThY8KkvkLSm9PU0VOHv2LBOxKo13JJSoHD0V51HWNorwACZ3nDmF4ps30d43xDi5xxETOo+rZ07gxvUrqKtvoFK6lbGthUawP6hZeQLlXdW4bfynEMHy6xc4fzVwDM9j296HGZLSi7cOHGNM6iOYHGhBTUUFY70bYE9bz3bymTx5BjeYIFVbU4O1e57hUWXuktq+v28j/R24ev4Miopvwcmj3pCwKMwNd+DyxStGuQ+YdvK0oYGJSfUYm5hj3OA+5NHzf/HcBdOfoXF/PLF/PxNXpJz4oJ1QKZhm3OPZw2+horIMvQ4qgNzpUuOj8Mp3/xFpuat44jCDm+eOIXfnfiYxpZNXIpGRvwqr16xHTgZDUVxTeOixx01inC9NiwZhRBEZYaJUMZPTGhtaGBe9FzkpETjz5g+A+BXIZ9JUxY2rZk5a6cnb89SXkZ0cicb6ZrQ2N6K1pQ0FjGde6SPdddoSGmHHUHs16qp5ktHchPisTYx3zcfpt19B7+gsogNG8PI/vU3Dz25QMIbp7Q4LmMIrP3iV4SfRNJQ6MchThywaX7dPz++f1o/8e4bhJa1VRThz/hyTnuqN4S1Fp/7Su2gcZk7AlJN8fQZlJaXoG5vF01/6EuZHOnHop6/AExSJYSbtDY2MIyae4Ts+GptKdGqlJ//cyWNobG426B52hoT0NVfi9JUK7Ny5BQ2Ubb1EC+nuakeQPQM7GBM62t+C5rZu7Hr0ScQxkW45lwz8wY4GXDjHsTGZc3xiEiGch/GuClwvqUc2Q9DsDE25yBOdThr3gUwO27pxA6qZEHj9KvmgqZVrfBs2rlu9JPmitSBYPa1xwXtNDA/i5ME36c2txuDwOL2+AbDbgJ/88CeUqRvRWV+Ji2dPMymwlaEPDD1Ky6YMB8quUC401PK0h3Jh9yNIjI/12QgYc/ai6PJZXLvBk6e+QfaLEHPTQ7h47BAi01chJy0BV9l2a1M9engy9ShzI/Jz0lFy5SL5vRbtnV3Ml/gKk60TjLK+dPpTZZ+dwqX3D6K45BY6eweMkZ2Zlow3vvt38I+Mx7SzCSeOHkd1eTGGZ0OwdTdl33g33mdSXiVlPZ3x2PXYM8hMiWNoDNEhaCQvZW9Zeh8/eKcfvSLLUfc/+CbrE4sCX2QKcBW11TnR2zuOoAQK7qUqZlQO5BVRjLCM3+AQxkcxHnSEsbPCapT1PEZvlZJo5IkMozKlw0XBVemYXkqV4ulUIK63rBc5ezJ4rLu0+D15SpQZrU1XR7RKmtJGNzdDHNfQKITRapfHQsfggjOLpFd6dtrN2Nwx059gCv1oxr7dj7e6JDag2BmnEj7G4/fZOSaSUOGJjLDxWG7cKKV2ezQ9Z/3cvITVq+8jEBdPoUxlWxnO8jDIERsdFembMsbOGY+kexQuxjTL6FA4SSTjgOFhW0TaUBs6qhUkneDAougJYzQbxz1iYH8UDqD7zVwsQfm/lx5ej5hg5jSnwYzfi2QGOIMg6P0fQQIRJxQrOMb4aGGn2qikRoSHsO1RAyGkBDJB1WmjXThmvvf9H/+XlCKFOAi+SB7SiOhYE+4yRyMjkEbQPE8Xxsa9R7YKdTEwZvRSCyprhtieofRyKbZVpbp9u+R99/DIu59ta04J1UXetZN/nIRki9I7+cpxQZGFRpL3iNlK48Fc5JVZ8uTImDzDNNQ+JMbzQX2R4SOYsxHSUZix0TH0uvnRM81j+QAifQT7z5EXGXLBI3Dhw0bTUzYnXic/yoNo5py0CmW/fMbrZf9HCc82Pj5BLtKaFa+HEu2F3nUZSEyI7enp4zoSXjTh8kj3cFsIwy/6jPIk41FrLTYunmEDDxrpvd/LK6icAp3kCHNYhm44lWBMjxOFgkgsPF8RyowSIINIV61nxacKiUY5CDIwtfYiIqMYP780uXK3BwyBoldPUFyTlCGC3bLbhUzBz6mUxsfHGBQEgw1NWRbCU5ZornuhiEyT10LYbqjPbd5unTSfmhTEnaAlp0nnAPJYLPyppM3rBI7r2o9yRJB4WmfhHJ9ih6dIK60N5WtE0FOqNe6rwaXxCXtZvO7m0b8g0uR1jeC7HA4X5RjRGEhjrUPxlmRMLPnNj0aDYNXM2MkDkaL5MuAAFU4yyneL32ZJhwh6u1V5TcmsgYwBDuZmIbpM8YRAinsk58SfSYEj5BHhwQu/NzqWSijhCH0ydEV67mcat9rmlmL2sPi4WO5xLv4uLHjGuZMftN8EU5aEkyZah07nkPGay4sewdOYMPK/FOBE7mWBAmn/FC9LCf4UiWu9+gtEgeUqwZ8QiTxTsz4rwZ9Q09ZrLApYFLAoYFHAosAnRgEZe5+VEuyrOf+JDdJ6kUUBiwIWBSwKWBSwKGBRwKKARYFfFAUsJfgXRXmrXYsCFgUsClgUsChgUcCigEWBXxgFLCX4F0Z6q2GLAhYFLApYFLAoYFHAooBFgV8UBSwl+DbllZCjIHaPorl/WS4GtRssSSaUfNilBB8F/RvQ9UU3CB7FwyB4wa8svgTcLigo1UUXDuwM3+stTrD4rgf9zgQSYsYaTNMH3brE75XJK5iwUSUDLQMbRbmdSsCY5NgUcG9dFgUsClgUsChgUcCigEWBB1Hg84UTTCXO4Rg0mYSJaZmstx2MEcJGSZGLskcRXobVdVh8QJiXgqBKTEwy1VbuZHdSWZpjFmRPT4/JvpbCFMiqWcpSHu1rZfnIEFO+MTLU1yzYB5F5ed/PEre1vb0LNmaJpibG3/MSKY7KbK5v6yJ8UCozlgMMjJSy+/t7OsGHWCYzFiGs1LNwzTMb1oCQd7mweVUWnJNzrJIThyhmXC/tooLJTPEbly8iLW81VuZnL+2xB9ylzO/+zmbU9c1g1+Y1Plap8Wb7N9ewAk1EIvJycwzO5gOa/OX5mjw5SSQCYb8qIzmWUER3k2GFuciseGaWTxsUA2bMMsvYxuzdSWZQC91AGc/K3F7OJf5S5SRTFIDQFBEErRfqgRApdCmzXNnKE0RoEG5wHOGalDk+RoNDqA2yNxKTU0xW9UIBBl/6MUUcTWUkKxs7NSPbZKKbtUqazJJXnQP9xrAJIM5uRJQdUZFhREkQogSxhLnOldkcR/71tW2DE8z3D7FC08xtZAp7NDPmF10au/rXwwz9mLgEZonbDM1HiKWrDH8hNEQSmcJXeDY1IazU8bERyjInElLSCcgffk/Wv5AplDmujP2U9Cw+QFxVooFMmIxr8gSN3GTJvwg951vmtEGHIK8pe1ug+rEJSZw/ooAQpUAoIMPOAbhpWAu3WvxosrVZ4WxkRIggHoMOEZ9AHvUVpoBU0ztVOU+GO8vHGUxSIaFoBDLQvUgCTpO1Hk7M1CjyuuTNsMtBzFNm0QeriEe0GfeiqVrSr56ZKfN+rRkVEIiOTTCYwKpkpmv6NpKAeFEV42JIl2AuRPGbm58FEMVD/H8HsWJJrXpvkqwWAsw4nQfzpLnGFk3cYiGvsDMG01V0Uba+P/FrwwkfGEUs4onRIfK6MvyFEsLqinExhlY+NG3oKmQMZezP+Xvf7UUjufsWocQIkUS8npyaQUSCQCJKjBn58mG0uvvkg38TCsIo0WdcRCPQGg+l7PKyLOG0SBfn4IBBPfEjAkZ4VAwx0VnJkMgp4+PjBv3mXlo9uL07d3CONaeqqCnnVhCRN2ISkomSwOqL5F3hF09wDcohJGSUCMq9yKgog9f9cbS68/4H/GJoSjnpIPpENPF3hX6ysGSE/ztGuTdKtBkVCxFMYTRlm1AdRrjOtc4W+F/V83y9ZohqMsZ3a81q/jRuoVx4ZRV1IMo2F2WP8IkNMg73EKFHCFFigpjhQrOIiiFG/GKEliV2QutYqD5u6iYsA2UQPuKoh3hhzrzIOEPU4cTrkutCwAglLKfTwdLcRC/xoz4WQfQSOxF5Pqvr84UTTIF49cwR/PXffBuZq7aYspolF0/g9LU6rCrMw8v/7a/xxqETOHfpKstSAnkrCgh9o6pLc5wQg7TEsqUufOdbf4PX33gLx46dwJWbJQYLNGi8FxVN3cjIzSUkP9VoCivBg8hjqopGAp4mzgrfQvgTCQ0KRnmNJRTNhkkvpLysUgw04XrWbLZc6IJzMsDV7Ic2LW02gkbRpM+RaebJlHqfPLOqpmSEI5nXMzmKd94+AI8tBpmJMWbzkFIk5V3vFobjK+8cI8ZlCvEt6wisT4ZnpafSK6fQNDSLdOL8cbUbr628wnPcCCpLi3DyZg1yo/1w9FoVsjMp9DgseVFVTUb9U9EGM2azWbHyDHcp75hZ3pXQUt//x/+OsMQsrMrnBk16aMEL5saMic8aoHBCrQiIX3TXO7UoDGg4PzPGB6GA5MmWgBpjZar6sss4XdKL7RtX8X4BiE+azV4wYPpbNc8XPluoeiNlYJZ9Fq0vH3sHrSNzSE9PIw4r4Z64uU3Ruyw6eeeSHfmUr6XhBN/bCQkNJzF4Tx16DTUtPVi9bqPBkdVd4qshZx/OHXsLFy+cI3ZmD7FEkwi1E4retjq8+cr3ERybgdSUFArveZ9xgidYfKCt7ibefO1VXDl3Fv4s1ysYsgU80BluIp1NlTj0sx+jfzoCBbkZmBoZwJUTB3HgnbdRWl1No5FA53cE7L1j+9i/OO4RAqgXnT/CtXgAWx96isq9t7SqAOJnyPvn3nsD7x18G7UtHSy/moFEltFtI77m6cMHcP7ceZZZ9kPh2hWmWt7HtnXfl+K7aRblqLp+AocOn0Rs+kqkJNoX3SVhPcFS1rfwrb/5fxCVmgc7N+f6W+dx6MDbuHLpGmvdpxGyipBZhCrz6SI/umnANFfdxA/+/tvIWrsT8Szlu7BBau0McUO4RH4+8N4J7Nz3NObcLs7Bj3D82FFcu3gWR947goINOw2GqK/KqKO3nTL0MA6+/Sbq65qQkMnCLYRok+Ejo/rIz/4HTp44ySIsR3H9+g2D3Ro6049Db7yGk6dOwM0SzjnEWFXVPl/gk6TwuKl0XDp5AIc5pxWVtYiITURqKnlXAkbOieYqHHj1x8RvPkkM0VAkJ8RgasyJI2/9E86cPIF6ro+U9HRCCBLSSc/4cKl0cUP5Zbzx2k9x69o1hCekc6O1G4NbMmKgqwnnjx/Ae+8eQHNLJxIzWCWNxQ26m8px6PVXMYwYytk0A2HmQ7NGCZmfnUTpxeM4+OZruHbrFgIjEpCemki4qECzxsdZwOHMe6/h6OGDqKpphj0+iYUcolll8CaOv/sOrly+zsqNYcTHZpESnxr3yhA3lembpw/g6KmrBo85IXaxgkFZy3lpqriM//r//q3BQg5m0ZLmiiuk1asfoJVPzZOu4zSi60ou4Af/43tYt/MJA4NoeJ3fzdO4u3nqXbz79hsorqyGLTqJuNHRKL96Cu+++TNcLy5mMY+7tPKlbe35fcQJPvv+2zhy6F20dfQhMTMPUSzIEMi9R4VXarmeD3M9XzzP8sFsOzaWBRsIHffRtFpqDyS/3Oii7Pynf/j/EBiTgczMTBqO3uc9U+NoqCrBgZ/+E65euQHXpD/S0+Lh6GrEO6/+GBe4xkc8LByRmkx4xKU6qO72bWighzjkp/Hm66+hnPjPcRkFpHs4ZVUw+W0W40MsP3/1HI4eOEB8+jokZRJ3nYVpqm5dwRHJ9ZIKxKXn04kWbYzju2/++N+0xgWhWXL1JN5962coKioxhWiysjL4Hu73dDy4WBXw2Ds/wanjR1HX2ImEZBmbwHs/+y5Onz6JirpmxCSlECs/kVjwnw1O8OfLE0wiS9Ga95/Hqy+/gtX/5x+bMp8jrDYl4HXXqBu//yf/HuEzAzj05psortuCdQkUcIRETM9IJ6h/JKER4/Fnf/WfuQGew3snL+H53/o3WJ0Ri6tHX2NlqE5U3rzKd/lj90MPIYbo1SrlWFFeRuB4f2zdtRN21rh29vWgtLIGURm52MpKTtOssd5YX0Nw6BGsXLuRntlkL94qlZgxgmYXFZXCwVrxOQWrCAKfxY28HG6PHxXPedMvW8AkbpVW0mqKx9q1q6nUJBjFM4BW0bYdu4gRGYTOxkq0DU7C1UvG4ca1siAP4dHxeGjndvQ2V+Pg4eMISVwFvxeeYV3yPGTGJlMAuVBdV4UuFhtIoed2RTqVYl7adMRo+1iZadzRi/NFTaTdOKLiM7CdnlgJgvKKUoYngGPehXhWpxqhh6joZhEtNda9p4UpZV+XhM0Iy3tWtfTSU+ZGMCs8ZSWEoqquHlN+IVi9uhAZVMaLWGQgnM/2OMYIyr+SRQ7yMeMeJnh9CbpZBcozMsj9P85sCt2dHaisrgULmWLDpu1IjbGhubGBgPHDVBCciEvLQwRru/cQCDwxKw/rVuZLF6fgGSegfz2c9gSsWZFFEPQGUxkqMyubHnFftw/v+D7d/7LTNOzaCMY/SY/JLMfEveHONT0xgo76EjjnEvA7/+abuHj4FVSUFiPO/jBa23uJK0lDjB4NPeKbSuBtoq+zBQfePIAXf//PEeXpwOFjF011q0QqZbqmxofRwcpNoTpxITNorgOCbVi/91ls3vcl/Ozv/gI3yhvw5N5oehJ8FNZU9npZGrVnYIQeG2EFG33hzkBUZGANiybseeI5nD56EOcvXceqjCgK7rexcd+X8Y2dWw2vBNII9fVS+dKBjkb0OVTJataLW7voJVKSx+gVOXr4KGLsEZyiOXS1NOL94xfx+//h/4a77RbOXL1OD0sC7KuyFz25lF9p+I260NQ6QL2PmMgyFBfNuQoMdDbXsyTzmKncJ7qER8XjG//6T+lBdrO8bhu+8+3vIo7G7nLGXn75KFxT4fjDP/1zdFecweF3j+K3vvk14tKGGvzaX/39PzPzLCXo8uXLxqi0hc7g63/w79BceoYb1QX07HoM4ekxPhkfM1MT6G8uxo3qAfzmH/4Zumqu0vA7iFVr1iOGMlXGf0RcKl767X+LoMk+/Ke/+Q7SWV0taGoA4yG5+NM//59x6EffQhkVo4zMLJ9PeyRzT526RDr+e/g5K/H2ibP0NNsRa48k/edw/dRBzEfk4Q//5MtoKT6JQ4eO4WvPbEcnT+JCKH8N/98zUUuZa97DhTlPT2MKC7v87oZdaKm4ilcPvIMdG1cbvOMZVuHrbSxCedsU/vX/+peovHwE546/h4TYX8XhQ0fx3K//HlavzDXGvu+cznLXdFB0N1VjZIInh3S+CAd28SVeH+Ce8t7hEyyAEkZnxxxa68px+tTFD6XV4mcf/DsNOipkTZ3DPEFiCB4VMCOszIPE+ybfpxfuxh/seBTl107jKI27LYU53Ks24XfW7kAHy4S/ceIYdm4uNLR6cHt375Aj59KxtxGSshl/9CdfQcONY6TncfzOb/6KwTse5GnpkSOn8Fv/218Dg/UsGHSTeLlRiJ0bNLQSrvH9tLr79gf8Rj6ZnXGjsamT46Vzie9azDpjjh4U3yrDhqd+A9tWp+Pb/+kv0L0mB0mxafja7/4x/MY68F++8xOsK1zBk9rYBzT2wa8bSi+jsrYLv/fHf4Hxtqt448BhfONf/Dq9zeHGAVd64QhahsLw9T/635GREk1n0SyqLh9CQ6cbX/ndP0VuBnGMqZ/4esqlk0VHezlOni/F81/7A67dfrxBB8fGrTuQaA+Eh3pSW9V19E3H43/5P34fp9/6Pq5fOsdiQLkske2PP/53f4krdPgUs4zz5nVrPziwT+mT5ayrT6krS3ttEDfhnLXbkeLPykYt3XCxmo25xHieKbQ0NaKe1V6c41OsNhNmqhSVlFbx2HPh/X7maCQoKMhY9QJG1/EXlyQGuttwi5u6PD5vHruChpoqbsCHqCQ2YKC9At/54c9YWacI77/7Npr6CEA+6MDc5AgunzmOV985hVFXD/7+2/8NnT39PMJiexSAjr5OdDsI2t3TisNvv4PyuhZcPX0Ibx8kI3b3YIBlSL/9LT7T76I38w0cZ81u1xgFFZ/3cOM4fZwVtGobqLSfwj/++DVujiM4dPBdXCmuZCnOXhygoJymoBOovTwLKnBQX3YDt6obeBTkRGsPy0SSOX/47W+jpr6Fo/R6B/rbamkEXKMyTq8XPaYt9ExdLapEd0crzrCyzLmb9XB0Vt8e8y1cO/s+LpU2MpyimZWF5AX3ElRC1NHdjNdefwMXb5Zhmv3u4DsmWBq0+vp5VsE6wvEP4Y0f/yM9EZdRy2pRb73+OhfcIM4ceQfHz13jMRyFQk0rPNyMZD2/8ybp1NCFPno7//a/fBv9/X04ffJ9vM7PnUOD+M5//ku8e/gYjZMSvPzjV9DhpDLBfgRw/I01ZTh5gbXHOearZ3lPbYvxzC/M/i/XT279ASHYsHMfcmQtL7gKbndymt5IR18XMvNX0tsahYysLPIEjwmDIrDjoUdZOndpldo+fMz0HPO4bso/BtlZyYhPZRhJsJ8p3btwf1hMEjbv2ousVJbwvP1hWHQcjzXTTUEBj1+Q8TDo+NTni56BgvWsuradFfDohVx8SQEO4NF3cKAHDbU1GOKRcEZmKkb6mtHeP4bB3jYjPOtoaOk0ZfEGs/g9H/V7ANd7av567Ny1jSVwP1iRasTZzw34JuJW7kZWMsslm/iUWXOiMNDbhYlJGreuQbi4Fn2+OLYYerUfepxV6CifPuDRJJB/4da92LhxvfG26v0yWgPJ2wqTaCy+iMy1e8xxoY/OUL5pDp2tLYhjiVQV5chasQbjg53MO+Ap1+12tIYC6Alsa27AZEAc8jLoIYuLpWxsZanqXswGR/G0yeb13pqnPu4/9DIypMQczfI4vKuFXqecQlOoIolhICEeHpPTOTBHbUjFDGISUoxXXAqzillofI6BPuQVrjFlVfMK8o1hMDn94TkSi3siuWSKBjD0Y4L5HgOUIQhLZlnWBCRn8fRgeoTGPEMjdFHudLNKVlJaGhISE5G9cg2GWVkvlMbHll17aMTHee9b1n95ssdj30yeMNp4ahDMo9+EZIav8fhfl3IhukmXjJXrzZF8WkYmK4YMorW+jI4Tj3F+XLvEan2traST7x1QgQrtl9u2bGABgg+WF3exGl17YxXydjyDlNhI461U6MZH0sqXLpDXU1kJcO++h03oIqfz7iWe5hrP4ZwG0zkSTC+l+DKQxYLCWbe5q62JZdpZOrlgBUMWfTxtobSSYdPT3Ye0DM1pErJXsUxvX7sxnNUJPxZoUGESJ5X0sQkqvGNDLMYydYdWMgqXfXHcoSx//vBT+5ESz1OeO8c83jeq6NE0nR7TE0MmJIoFlMmLDE1gyMbwQBcNvVJEJ6Wb8Azf+zCH/t5ulkBOYThoHNLz18Az3G3WgN6lkuX1ddUIDZzjycgN3KAxP8BCFQ0MJ6QbF63V3OsvXTIOJxVX8eWSwdXb3ojIlBUMk0tmaF8SooM8GKTTTCGrOl3r62pFbuFahvVFI5trYo6yJzA8npULe3Cee3x7lwPZK1axhLovLf98937ulGAJy4jIGLzw3GM48u5hdLM0n6qi6BLj93V3UOBxEQdHoKurF/akbDz7zKP0NrAm4e1Lm8oCje/+7o+U7FV46Veew9OP76A1XIduLsSqWrrnWVc8kjFkM85ubiOMKeJGEcSFG8M4omEKjLLKenpr6A0LZ7waQ3hG3DNGiZ1lHKeN5VhTYsLYN38WpBqhQsgYJW7q+dsexhOP7IG/24nG7mEKiRAkUwAqnmZ+wc3K8UxSSJpqYvReZa/egqf3P4mCNDuamtoNQyu2T5tqBo8JC+mFzuYxmwSrQgUUA6a2A6lo+U+Pop9eVFFKx3+KkVNsXhBLKq5dw81wKgBPPvUoMOFERXUjlQNWCWIsk8fZhd6uDtQ3d+HpZ5/Hiy88j3QJyzs7sMJDWGXGFovHnnqascaZpgqUjZ7XAMb9OTkfo+5pWtVzePzLL+Hppx9BXOA4uvuHUHKrGDv2PYYXXngB+zavUMd4/F6Ducg0fvYinn3uRcwMNMBBATHDMpK5PAJ+Zv9zSIxiucVHn8ITj+9D5KzLeJe1kSqGMZmLr6miBPX1tShr6EUS/77b1wUO+CX6STqGsGKQMcQWmPJ29xQ7Js+M+Y4ezwDGaolGKsEZyopCJszj5xiKwi38uMGo+pc2BHkWpVQuXFIWZSQGLVJSpbTphKGHpw/z9nxsWJl1J4Z44bml/aQxys0gmP9M+NB9D6mS1jQ90YNUgpyMbZqnt1ix07NSkNmvMVcfTh45aAzGhfV/3ys+8k+jVJq2vRW67rmRa66/qwUnT19lyeo4xuGOM17NhQh7InZuWk2P1VmU8kh7gtXkNA++X1SK2H/NXwDHckcQ3XmRHxUC0oVKgfq5cEm2DVHxvn6rFjv37KJC46Pn3bxIG9G0MRbVd+VDcOcz8mChHQmuwe5WtHY6sHLjNobeMIZTcpUbay9zKRSvauKiF2TU3Qc/5Ld5dFHBKi26jlrKU1VjU3Usf80hlUB/Vq7SujUXxzrHTXicR/eXL17Hyh1PICOV8of8L+PePBMYwr4uTRNUTPlgdwtLX1/lkW8NPbnjNKzk8Agw9A/gaaJCqTReGQdTVKz1naGLaYeVBKmUeJ0k9xpp3g778F+OzcNKfMrVuHatDI/QANIc69J4plWZkPwo40/xmH7zDC8jr8/Qg6wqbgOdDTh17H3uK5Tpt/e6pbaudaR3B3Ps9xvZUv476SUuKW9EAmv6KmbZQcfOMONoP5xWS2114T4quqRhCMfgDRFc+Pz2T9GFp469nW2ormnDo488ZBTe+RkaLVz37V10JtGIkjJ2m0vue8HH/Um6Mqb+7pyGcrh3jac4Kpm7t21E1c0LKLl5A6MTWheUhbdptZzY78W9ER8pjlty9a624b1DCvKGtYXoZajNjSuXWVZ5gkYg555rcaCvF32DLvIAnWD0IC8sj8Xv/vjflTOgeFuvky+QMeaqyKZTPF1iH1W+VBhmcLA/Wiqv49KVIsYID1KP4md0aHTx9PHUmYsmJPLj2/rgtzqZDGSuhuin/SmQ60zhi7pEf4/mhH0Trwdyv55jSMycH6tgRtjoDOvCMHk8NIAGLJ1zn9X1uVOCRZhgCtJNex5Hsr8DjbQWxyepdPIK4ISvXrsJDz/yKPZuzMatsioj6EJofUvx+/jLzyQFxdHrEUMvybwYkEqCSirqf/4sMbn34X1ITaMX59HHMOdqw+s/e4cKnhiVIeCccCnoG7buRhI9dNq/xBBV1y/g/fO32Ed6W8TYUjLmA6icJXHiI4yXSd4XbQaRcSnYzPrlire7/9KiUrymSQxRaVv2beFS0L+EjDw6CqrXWBWf095Qg9cPnDBta/iyxu6ngkry1jP2zD8+BysyErjhKJZ5YcwR2LOPHkceGYoORiljP6VU3t2evb2IZEnRGMax8S4cO/iO8dJrA5NCr7EFBoUhLi4aMbF2RDPJSPHC0gC4VswxWSCNCr1zlvTRWFViVc8b7wUXjE4AYuKYxMdA+ghuxPEsPRnNRIbQUH8q8xoz30YvWnJqGhIDRvAWY6nnY/MYWpLEDXSBUr+EP9nxSXqq5I1XHLaULpNAxFKyEuLavIaYNKOyxaPcpPypuARSQiqJSPMtA0nPPZi/Pzh2U5KTnuVeGpL9TIrRaYli0OQJVelcvVfx7EpSkVdax4Mj9MQ315Wy1vsZbNj1uPFuSUny/fImSQiVRce0o2Mj5qhOiSEOJsR5mCQSHpuKdVt3oXBFNq5fvgq/UJZytkUgKzcfWTk5cDvpxTHr6n6u/vjeGCOQ7x9nEohpn/F7ouMI469HWVZXJT6DI2LQ11KD9s4+tDZWw80699seexZ79uzDyjWFUHJYwjKOKiUEJBfGOX9aA5rvSdJW/ejt6TZzr9hcN/smusiLKpkxOT4Cha94orKwgjkAC8mLHz/S+7/155qJYDzkMDfbPgywvQiGDs3S8zpKOeAmLSVXGquKERCVjFUFuUaOTNKYX1m4Hrsp/4Ime9FG5WRpypjWt9fACqZHUslHQzzZkKdRCUkzfqEIC/IzfVGioGuwB7eunEBL/yx2blnLEr4xxgBz9PfefmaESorNeA7vH9n9fxuZTTlllG32IZwyZ4bhRb29/ejv7jblsUMYjDhCw2KMTovIcJYxpvI30NcPB0/n7HHJVETkyZ4wXrQp8oj4f0GZuL+9j/5biUjT6Gqtx+Vz53g8vx6r8jKo8DB8jzHx41xnSnZVmNsw/x5hEtl8UCS975RvDNfIzisgr2dhuLeVpYe9cu6j2/rgN8YjTtmi8s/iKSVDiddGGOY3Sh4cYEiZFN72hkoqIf3cC0p4qkYPNQ3QxbRS6XDfL+VyTJmkO/G6UIWm2RfxtJQ9ndy2Uwm/cPY8QwvXIyc90eStBDAHZjVPiR6HrM3mAABAAElEQVR+4kk0lxfBzfroku9Lvzj73DOiWJpaiXHidedAL2ITU7mOmJBG/vdjefTN+/Zj795HUbhuvSllnMj1LAeSaKV5F62kUC7nUjiGynBrDeskQici8v72dHWZRMcVG3fgsSf2Y92G9UhJSTMJgXLi5K1eh4ef3A+Powm9dOb5NGzTUX/K8DBMsu1+8rIcWIEsC+5Ph8rIkINJr+R17tXJjHlPz8pGbl4aejkXSjxOTMs2nxUwlLCnm/308ehBSm8kTwpHGR7pXeMjmJxjkp0t0CjZ2qdVmlrhpOL1YfE6V4KrtQSzUbnY/9xLWF+QjDIaJVPSkz6j6+c0cT+jXi40Q6EmK8JmC0NQWAxefPFZ/F9/+4/0BnqT0Ww8whDj9XsYe9LZz9jTPB6pV+FKjQtPPf04cuhtXbj0HmMdS0Pi/1VLnLoklVlqZfRSKGM6KTMXWS3tCExIxZrVGRgen2ECEjcwxtBs37sPDU2vIYDH1JlpKeiZsDE5bw1jCUd5dC0vDv0LZCLVxE7hcXZuOI8CegZNIo1qwxsLlZZnXHI60pghnZSVj6QwejyYhRysSHFdXMghtEzFOEFTtKiZsieLUf0OIZKFsTY55mDWXJcV2dXVid6BHNKIFpYSwxhvFpGcgcL8dJxhFnwwPw/iEbO8SLJ4VQu+t70B505ewZ7nfg0D9ALYqYhnp6eA5+MccyaGx5iJHh+OpJoKXLt+E85EoNUxarzhtztJcrE/7JNiiCSshhmKsn3fOnSXOOGS94d9CePCVEJCwDy96Lw3lP/WFK40wfMj/XZ6f0oQv+IR5BC14tqB07hZxMz/EDdgz0SSPYxhHt425B0T8ofxXNJ4kCcxiO3K28DBUTlJwp7dG/Bv/+J7+I9//13G1kV7u/lL+l95glzcdMeZjS0lxEEBEhkYh+NMHli9dR/SsvNRfrYIrQk21NY0IXvTI1SCWSK5u5OCQvXenUQSYF32GG+899KH6ccku2QkcW+7zkTSCE8fD+XCkZYQiUuHXkbUmi+hMDueCjjRWBgfO+kXxQ1liEdrrTy2OomE/E1IYZyXNjStFRvn1qeLjDJKZcgphAYe0fV2tSEuLAsll06h3x3Ck4F0XCpu4VE0j+IHGPvNpJY4hmzEBowxPrwWXOkIoJIcr5ACrVkfLpOkRTkx0D9ARUBoE056WYfQWXYavfOpPDrejt9cu41KKqEGna2IL9zK/IAghlq1ke/8UFlyC6krdy3zmFxGzxi9zR309NHrSmVkxBWL2bEBvHf8Mn77934bo/TKDBERQWFO3V2tbLsAbuYWtDc1YDM37VAZjMsy7PyxbtsunL1eh2oqfe1llxiS8gymh7pwuugadj75IukZiDKe0BQ+9qtMvLPTGHHj1uWTCIvNwVBPFxSpFUOjeLGX+qNJ74ecNVuRwxvmqPA4OiJx9NyP0NKQwTyGGtjT1yIqYAKv/uiHeOKFl2h0MG73bBmeeelrGCdfR/I4N40x/8fO30BWbADKS+ux8cmvIoxy60GXvLhJWavMP93bEcHwrIoKlNy4xdMlJuUl5CLG5oeTr30P2Q99Has3bEJZXQ0CmcTWXHIZa3Z/1SiqTspEw//hLsP/NvK6Lxn7xuDiKcaJt17BZGgmdmzNMCFO4UEpOHfodUYdFPAkbguOXnqNxlYaj6hrEJ+zCTkr1iLk4PtoZSz6UE89wlJymY8iL7pvEy9lzE350Mc1NEEFUAlhLmcU6i+/i6nE7di452lsfIgJbFSIhzvrsGk7Q20CGafc/vY9tEpnAqPvlzcxboDhblJp+qnoJ8eEoKepCkXV3fjGrz6FQ6/8AGHpm5GXnUS6dMMvKhgXr5Qggc4oV08LwuOTl8Xv/nSIrN24EeWVFZgddaCp5CrWP/oNONurcKtoBus3bYaLMtSPe0dV2S1EpzB3Jcn+AVrJUA4O9nUPofJPZbqvg4YLZfQQlU8hTkQFz+GNl1/H13/zmxzrAB0NRJ9pqURo0mrE0xNfW3KFiac2BFF/mfEXckKEcQz5Rnc/5BeuQ/37Z1FZVo7BuutIX7UNwbNjOPX2q1i59wUatGtxgwnyc2Op6GSs/Mr1z4GBC7haUYWgeeopDUUoKHza6Bm+tK2TpbQVG4EDZ9BQXQH/yWEE2vOQyIizt3/4PRTufByZDMG69u4FNKaGs391SC3cTkOYJ330Fk/RyNR6CaF+tzT54kvvPvrezxc6BFlCClRSSipSEmKMtZ7JMICVhYVMRkth5meYibGZoGd4xfodeOrRXSaTPjAkApnpXEz0CC9c8iYLhiQ7K9N8bqNiaI9LMhmZIfRaRNNaWlW4GoLcGnV0ooPesljGLKUmxVKZbUd79wD20mJbnZ+L/LxcKqVMymrvYOIdkRzS0/hOHq1QEKdn55nksznG0m3etgWrVuQjhZmPaZnZjFkOJxROND1dWWhvazTJc0m0CpMoAMzxETf3UCq4+SsUIM9YNlpqaUSJsFHhS8nIQhoTzqLtcVjB75OTEkyCXkR8CrKoxCalEb2hoABRVHq7XVP0Yu/BqtWrubHFkX5pyCEqhGCCspksF0qlcoaWqpuehvwVTKAryMMYx9zO2GaNOSc7h96IPEyNDsBGNILHdm3iuxjbx0B7MWsg6SXrMjcrjR6VMOTSS9fZ3ob4jHxs2bQB+bnZzDSNQS77E862bGGRyOQ9q2k0BHiYcMUEuseefhor6fFYuaoQeWmJ9EwxpCUoCl/5yktIJjycDB95/xLobZZwkDfQToiqMHqGc/PyOa4YxtqlGb7QJnXxZjX+1Td/DYlUgn3cNxZYxOefy0GHYMA2PauVFHo2JNDTL+9vcho9RTSAUqgAJHMe47gxOBh/WrBhNzasW03gmRk01lYhLCbVGDL+jDmMj43HRP84YjKZ0btgRD1gBKEM38lfuYr8Tc+YLQ57HnnMIIr40wiMTc1EZOi8SUicDWICURSPuBjDF0ueVRxzAFFXBKkzQ6NGISiLQyYe0OztrxmH2dZAb4eTvEDeotclhYmmNs6dnfOYzmzqGW5egzQi0/LX4qmnmFlOz1h+QT7GqIwrjuypZ59nkmCkz4qBCS1g7F1jawc9QIRR5JFdVCxjX+3RVPYS6ZkhAgd5LCw8gusrGmk5BSZ22EVkhS56V3LX78I2rmUTKuAzc0kxIBpKTTUS0nJpVNMopRxK4LpUUmk6125nUy1DgCaQTdkhb1QajXH10c8WxcTZtaTRAszU0ii9+C57IsOVGLPlIl3TV+/Aw3u2Gu+/IMCSqegEgKdflFVr6B2T91RGdxhDInq4nueDwrH90S9R5mXT3vTN6NEpWWhkHLIzEmnoDSIhqxBPPPkoE/LomGBseVoWkQ/orQql/Jjh6YS8dXYiOOTkrURcZCAN9GGsl8K2sZA8f1eOLx7bx/0eTg9VDmW5izGgtrhsPPrYPqKNEJ6NvC5nR25BISLYlWGGTeRseAi7t29g4NsUGurriWHFvYY0C+A+kpiYYIz6j2tr8XdSWWcZesZTXobABNErOkLlZ5Iet3xDw0TyfCoTnbNSYpj74ED6ys3Y98hes//kZWeSVgOISc7Dk888TW+hlIPFb3/w7zqCVnhPR68TyUSRoc6H+ORMvoshfomUl9w3Ivh7OHndTiirrPxV5IN0ytTce2iVwFM8XxVwnXo46flvbm7m/BYYOsTQuaITvDDuW0lEqXDPkC9CAw1cmU5Ls1cUUhFjAijHHcKY7Gee/zITsz8YV/ugkUt+CuHD5u/BKJ0yBZsfoQGitUNHUDi9noRWHGWCWidPwIQ0tWPXThO3PMAQmsW0imOoYeQyEBpmpyeoXJfwNCvdtOnHxOEUrq8gxjxn5WTTAdCPLp5IRCXl4AnOrfbHIMKUOaiYu5mY//D+r2BFnu/rTHTRiXJqEtEmGFISk7mWYYN7GboZYU4RU7JzebrAHBPuIeNu7vfrd2P7ts2UvXmIZE7IKEM1Mwt30JG03dtvHxhOsiKIXuf83EyzN4REJ+PJL+1nwmU4lVs/pLJdybIkeyhDPoawausjJi8jJZt6QSANfoZbRafkY++jjyGWSZo6EQ8nYpB0oU/z4omPfHefl8sbx6VYrmAqmdrMZnhUpwEE07Oro5aF+BOFGMhjKvgxHeWbmDJJgNuXjpw1dAlBwQwpS1sSxhtnqZgUxWLyWJ5hBSpYoTYVw0hHEI8JFKup2BZvvKQ8S3peHi3FbapvxqPMnskbbCwc9kHeS3mtFFag+7weLI2JkGSMz1X7StjTPzPt7J9g09RPvU94kUFkDAW3m8/4Po1fCoigTzy8V+NRkp8UGd5kjldn2Hc9r/uktJq+cyCii55T+yamls/IO6x366h9Ycza8DQOQZyx0+YdStSRZ1eXjlCVCCgai2FFW3OMxLZ0n8atI2AZMBKMJg5Q93KQ0zwuYnPGq60jTPVRtNRYODv0uihmlDTnGHSf5kTxzoqT1bt03MeHzTz7qR0iRDRXXsErp5vwp3/0TSpJyznG06h8vNi3tjonjxDHEZRA03cRr338mxjDZYp8cBx8hwSJlHjNkfhDG4/g6ZRZrTGLlrpRz4geJBE/4wnCvD96y/qQsyeDR/kP9pSZPvEF4mW9i4xjaK82TagNPSl+5FPNg/hNDSnOTEfEWhMLx8ImbpJz7OVl89Yl/kdHpfS0ap41EI5TXn0NSn8Hkg/UL7UjXtbJjVkDWmd8RvfrswUeXGKj5ja9f44xowZphr+L5mY9ckWIl3TCsrDhax14ZYJCmbywhqbdZY3Z20slkIiHzbhJVzM28S7HJdkhuigsiJTgOMUPPOWgrNPf8nD9PJuCZKZ3fRGTk2MVr2m+DStp7OQnyRTxmf55aeUxMlDrUetZ8mk5l96lhFXFeJp4QfIzSc/xMoaR68XIGM6vuTi/QfQsyfM+a+Z8ln9TETV0N9LRpy4sjEN0F6+LznqLeFlhVN5xC75RffPuHeKRxfy/3HnX/qB2veuIjXJOhZer42bJvADKNMlHs+bJ6wtyWnyi9sWfd9e+T8Pm/M159wDSUDQQ3bWeFI6hE0+tKe0J+k59UFys/hZPLKaVV+741rbklNkXb7fNgZs9wPt+zSfNjNtrXN95ZV8Ix8x5II/oPu25/uQN32dcosS7Z4nOmlPxumgqPtYl3UC8uDCvbO4DtJLMU0y6r5f21QWITo1NfKvxmv2av2vP1XxrzJJ7pm19Rlop1EjjlmwTDXy9vOuMcpLr2Pt+7rukhfZd7ZGG18mPC7LV7MtsU6Erc9xndY9i1n1v2dtTLy9LRkvn4Jplg9Kh1Bfxm+e2DFBMsPZzwydaHwuyXrTi51KAE7mXeROTfaXC0u//nCnBSx+YdecXkwKKJe3taMLAdBgK85iBzs3uM7moRSxPCf5keudhiE5vWa9vSvAn07T1FosCFgUsClgUsCjwiVFAivpnpQT7buJ8YsO0XmRR4JOngEIz0vPWIP2Tf7X1RosCFgUsClgUsChgUeCfEQXuxgf8MxqUNRSLAhYFLApYFLAoYFHAooBFAYsCH0cBSwn+OOpY31kUsChgUcCigEUBiwIWBSwK/LOkwOcqHEJYexMsDuFWEtntS7BoU8S+cxKaTLiWywvgX3jbp/9TwfpKOFBSnfBVVezCyZK06cQN/ri+K4Ggq5MQM2lpBh1iqUHrCn5Xe0oSVBlcZT9PEWBK0FO+JzP5Rh8lV4yOEZOSY0xlFvKsMIYZGO8mHFg/4ZaiU7JMLXdBnP0iLyUFKWmA/yfc2lIp+8n1WBi8bqIACDPRZgs3CRwLb1cihyrtuAkfE0wQcsHliVqioTChQ4geEsLPl3spMUjA/EwPYbuEm2PyxuLL8KuwPTmPUXZvqVz1Z4LQQfNMMBJutRJHlpPAoYpewi6dJiqJLSLSQK2JP3QpuWNK652luJXsKeB5obsIymmSa0GwfGF8JtgkVizu8VJ+9yZUjo4Q3YIJsKqqJTSIhWQ4U0iG/RondrCSWiKIQCLaKMt/lPi2/ly7YeGap+UljywkruhdwohVYspirhOeqOiivmmMRETz4glz3OZiwokwdJXosyy6cz6VqDLPZCHhcC+8wyRRMTlmZHTUJAgKmSaMCBG6hDIgvGiKE4P3q5g93y8lVVLm8f1KqBTiy+K8H5NAxjGOEj/Uj/MbThoLfk886h4fNfwmvGEltfl63eFjjY18K7oLfnKhfckqL3Yzi2YwIS+SyDMerskJ4sVOUX4qsSoqJob8tjxeN2uc/KTEbVu4l9cX+G1hLBqjZKTaV2W5CcIPTjJpUPwpfvMVkcO8l+tISVjidTZt5IXgKhfaFs2FQCK8aq3nSCI3BHJylWSu+Q4gjYQcocTz5VxKkjL7tnuSYxCuuwoDeROqF943zfYFR+jHZHHxo3DTJ4V9Tj6PYGUxjXuBRxeeWcpPjU1zqvmTvJCsWhi3ZI+KRkzfTqxXEmYoZYwg8Iw8ZKJxINflcnNKTGIck7SFAy34VfH6Yr5dWONCA9IYg1lNcI4JYwbLmfpNBJFwtL4/UOBkCQMXrwtrXHjHzH4kcpNoqIRHrWMl6nv7pWRrJeBFEqFK+MlKzvcmETJhlvuQ0GE+Tif5qK6I7oafKNXCKb8W1tjC/eqfm/PCdEUvL/BvYQZ7Lz+iqIQRNYsJ7dqYP4PrcwWRNkbYrKKb11FWXokr124SP5Sg+mTW/rZ6nC5uwJY1BV7FjlTXojGCjwuAcuDOIjLZ6JwkTbZovKAI6l4JaGVm6lmTlWveoUxyZsff/n0BKULPLV6Yel7CRqDg+tx8x3cpA1SKzAK4vAoQVJYVE24qnFmP7DsB8MtaepBPiDdtuOZ+tqdMSmWKasPUDqnMzVMnTiIjn2UklW3JcQkxQZnsutS2yQal4PC27818HiMO6q2iMpYhtWNqzImz7x+Awz8WGQmE0lLWre4nJVRBRsaEGrvbdyIDUNGSciiOFB1Unlh9M/fwMxXD0GLiU1768XvRxjzHPrU01qG224HU6CBU1rQYAT81zjLKP/oeQrPWIJbYlxrPwjyopc/60hi6h6ZYfnmK4yJP8D/Sy71jXHpvfIZIE88QP7WloQoNddXoZhntaVbKiY2NI43ZESoeKmJQUXwdPTQauoktKTzkYP851LJkdEszS1uPurmx2IijbMNY35hPEGlS9kZZ/KLixkXUtvYRLiyRgu/ecqFuVvBqrSvDGQLaZ7AE6jTnrq2xEhWVVSyx3UIUuzgD2eVrBrUEfnd7EzFprxEesBX9hMCKi483igkHjhkq2jUEyq+pqkBnB4HbyV+q3NhYWUq81zKWJu+lfA8hrBlhrjRpPlzamAe6WA2S76mvqaLSN8Eyp3aDRa13Cb6o9NoF1DWyXywoEUgouTBmKvdRzlRVVrL6WTVCiA+u4g9aw75dxAmmstNBnNyLZ04hJiXHlJ7WdJs1Rrp0tNSjvPgm2kiXQecoxx3OsqYVaGyoQ0drM0qKbyExPYeFY+4q7kvtw7RbGLCNxIC9jrG5EAMtuGB4iB8GOhtJl0rUkC4eotHYY+KNEjI82Iubl8+hqZ1lvHMLTMa2b1SnMkZ51tfZiusXToPw4wbq8g75KOdGiQ3cUlfOtdCIvj4HouPiqBRJKRlF8ZVTqGpoZynWRNIrbKnDvXPf+IgTPZy/0tJStDc3sPhRhDEeF9Bw+jqbDY3rauow6BhhhdB4jPa2sKrlTbS2tWOQmNKxxHQXxJZP/MZxqVhGG2HvykuK0NbaxhK5Eyy0Iqg1KdScde09lAP15ddwq7QSNsJsRoYGoJpYrnXEW+0ddFKRCmclzsg741nqL1MshNLf0cgS82Wkaw2h2qSEq+iMFzN/lMVC2il/KrmeO9uaEcgiMazNjr7WOn5WiXryXJQ9wRihvvK60DUGiA1ccuMKOtraWN2Vc8r1Kpz3hSUrOdDFtq5ePI9JIuEnxESaqqGVpcWkexum5gjXSFhMX1FgtJc7CWlYV1WO6qpKVsJzIoSV2jR/2vdUfKaq9CZaWprJc1WsK9DN2gOUAQGzqCu/jkpWio2MYXGqZfCaDMYJ7rulNy6jqbEenV19RhG2G1lF8hI+rbud+/6tG+jq6IZjeJLOoCBTFKmEFQ672JfBIZYOpyEWKiN1qZN9+75RVz8xxWsMr3e1t5rCPzLYVWBHukgbSyOXlJdTrnYSj3wECaksmNFcgdraWrQ21Zk9e4gVZAWf56tcFwrFICu/FVN+dnC+M7LomFwkIo1ORudG+c1zqCDuvaBVZ0d7cau4BD2d7aipLKdDc4wwcoTLpPX/WUCkLeqej5T+BdwujL38ggKkxUfg8s0KZGUTvzYlnsqbm+VV+1nas4cLjdWuWI9e0EbDLieFaS9hq1hxi95WeZC6SOh+ftbdReZjZSiPV8MzcCnDw8NwscKMGKWzk8Dw9GDKonEMDmCKAtxFAHs929/fDxc9z0ZBJR3kRZigZ66HG2Y3sf/6ueDk4VVlnk56b9Wvnu5eg805zMpfB19/BWW1LcYrG86Flk1QeFMRihikwg7sYt/6KXTNc6bvtNK5IRVw7AEUqEMcl97bRiEhT4GsXfWxt1d9G6QHSbBTgnuZovBux49+9AoXIqtrcSzj3IBVJECVawZYDtZNpXyKVvFgf59pTwUz5PWT9d7R2eEdE/H7RMN+jqOTz7lp1UupN9WICKbfR3xLeRNGSL/unj7jzXCxEMIYaRJN3OI0ezh622rx/e+/jLpmllHm+8fomXAMDpJeXdx0XJyb29BIH8JXmiMJ77HJ2U/l38ikB+XtY/jh+U6cqBxEm8MN1zhh61hCTXT8tC7xjdvVjWOHDxKdlVUA3Q4cPXyYJXm9sGHz3ER6W6txtagaSUlpaC27jPKKauLk9plywQJYv3LqMCrqmpfVxVnOe8ON03j/wFs4d/4SXKzxvvhS/5z9XTjyxis4c/wov3ezP5U4e/ocS2onw91Vx/LCVKZYEMXXa/r/Z+89oONMz/PQB70NBr33XggQ7J27y7aF2qItqivJlpXYTmIl9+ae68Tn5Nz4OOc4dpw4sXVlW5a02qLtjb2CDYVoJED0Xgd9BsAAGAwwqHnebzAEwCWX+CHuWhvPJ3EBzPz/18v7veV5psZQePEUWnvMFMR0OPfB61w3sh5FIJjFhLELJz76GJ5+QZgyduKD9z9WoPMtbT0IIaZmd81NnM8v4vhQvaUxCSZx8fkPUN8xqgTMqoKzqKxpVpc5yWpqfAR3Sm7CK1DwvEnQQa2ECI9N9U0UzCJhbC5FcVGJYl/SWLRIPJggLvOZDz4k7fuHCi9zeQviVxSQJ024dOID9BqnERrgiZPv/IpjPUOGJ2LZpqSRyjkSTdUV1FLPaC5aXrCx36+f+YQsXZdQ39ypLtKOjOSS29XWRvzpcEwPtuIc58XIOBkMuZf2kuDgyoWTKCkgnapQC25gXSzMTaPk0ilcOPMx6gjML5pJRxKBqZdU3B+8/aHCv46LJ6YtJSUhHRjpa8PV8ydw7fI17lnjjlc0/TT1deD0+28qzF83mxGnT19Q9LSSicyhOzfOoLG9T9GsNxaeRumdZgyQ5a23fxihUaSl51mzHpKOeyslec+MD+Hsh+/AOD5HwgsXfPruWxijRc5B9y3smOPDBlz+9H0UXL8BAxn5rOPD6DYMkzQiEHWlV1Fyp/HerNf1t5V4y5c/eQO9pjlir7qjJP8s2rv6775rIkHG5fPn4ekfjgVTDy5cKuYZN4A2EsOERUahqfAMblZU85x48P58N7N7fpmbniTN+HWUVXcjJiYCBafeRktbp9KGOx6Vy0ll0WWUlBSS3rpNXXhaWjoUg5mltx4ffXJKQYw6nl/vT9m76kov4xYJVoKowW+tuISrhRVKBpA83Kj5jSf+d2paprpcd5NddYLnkqGxHKc//ADXeOnf6FwThKIR9usZsmqGRUZz3y7ElSs3uG4EapJr0GJGYf459I8vEus/iPvrG+jpauflUNgSZ5BAhdjFD9/g+PctK6DUa+v+z0BnPSnlz5ANMhI2Yws+PnmJ1PN2TasSghurMT5L1lpi0MfFk/aelragiHiksC8E890y0IDuPtOacVpf4SITzHEtncPZEx+itKSEsLFrtwrpm9GBDlzhHnCd54jgBfuS9Cg1PROJiQlcK/2k0G7dyPayvire56m1ts/7PPDb9JGf0EgK2xn5pvXUlmVmZpJIwBv1t6fRfLsAb9oohFFz8o1XX0VeWiw3njcxOO3CA9WIbQePYdfWTfjJX/0ZF1gkb+NTZFLZgt/7ve9TGymmzhlcPHsKCIjF8b3p+PP//J/x/T/69wjynMOJj0/i+//mx2RceRNDo+T5pokhOmMrXn3pKaXOn+Vib6wswWsfnOUBrYd1KQAvPvc0wsmE8t9/8kuEkZnLTKF5657HsDUtBDUNTZgPyCdH9mFydE1Ri92OZ7fH4PVTxVjkzV0OCx9dALyI6SiavmMvvIQDW7Px6fvv4Xd//K/RUFWJ8ooqdHAz+//+2//ARMctFJbcpiDlAYt1Dv/6xz8m4UaAMonUUJPR0tJIJqYb2Lc9m5q/EV4g3kN3WTBmdTH4zjeeRbD3PH75y1+xX4JgpvB37KmnEK2bx5/95d8ijqQcI2Pj1FyEwJ0HXw+F+T/64z8hC10iPMlcNm7sxk9/fhI//P4raK3mBlLYiL/4yz9F4aUTcAtKYBsXcKdjGGm+FNwNHeQpL8Fju/N4SbGSFe0DFC7ZEByXhle+9U3SNpOO7j5pkqDejf1TGLVo34jvk91nPpLDqGVgCn0kFTHcGkZxyzi2J/pjf3oQ0iKE6U7rXfwzRdz3A9FI9vMG7hGWSZrQ7ZS+htBc14BhCh7eZClypxDAbUWRCJBVgSYzX5om9QiLy8LR2EwKTEO87deoC9h9C3jIh+7ML3nb4/geCSfeyf/sISsa++aGOrhHbkY6BR+F5UotvwgnCzTVC85sAHGYNWsL2KYxHvqT8z7YffQYMmODkF5wGQMjZFckoLw754ah8Rb8E3di09ZdsEToqBF+GxNkNXruW9/BEpmIpmnVuMELi+Mi+pCmrvlacGlr6trwvf/3R4glG6Kn6xzKSD5ymEyD9AdRz4q2z4saqwASCPiQLMKXIPBHn39JmeqHW5Nh3qBZXFRgwZEJ+NYf/BhT/+2P2XcreggxI5qoiZ32CCNF8WHEBXki4cp5GCdnkZtOohjuLR3mTpIoblGkMYK/qTV5+4fiqVe+i/CCcxi652Uxge576kX1qffsMEwFZUposJDCu6ioDIm0BExYtVLYrhQiSoyj3/wR3QxGsUDz7+o0NzOhNLSRWTvoOqVX+58fSQrGRwdx7dxJbH/8OErKm1a/oun3Pmo5ra7heOLIISyNp6Du714nTfAQ0hJj1Cnd1daK9EPfRmpmBtwmcnCR2vagdCEY8KDrhF7NA3FRUBYaDSWLMDZEBYDNJw7b9z1B9qwllF/L51yfUOQs7iS2EWXJdVro4rYeghsVG4JbHBCehKefDcU4qaTDmjfebnFpaOkewx/98BiCvEmdy4tuS1s7dm/NVK2Q9ihsd16A+AuJDQJIHpJBspRtyg3LUJ2BSVod5XKqNVnMRpioaTzw1LNkb0tRl/hR0uUKKZMn3RPkQthWWw4rKcn37NiKMZrHPf2Ccfzlb2GeZ2qovxsq3r+iLilayxZNcO2damw7/rvYnpeF6GB3vH6iArNHdjMrutlwrgsbp1xSOqquqTWZSeIrl9kw/OBHOnx4rlhrkXeft1HL3N1QjqTth5GVuwNu00aU3G7BuJWOiB6kNKbrwfS8GzblbKbgGcM58TaVcwYqGWaQsftxpOWkIzHiXVq6yabJfdaNJBrrT0tobyQLXUgS9h7Yj7msMNz+6zfIXLsfcdEr56sbNcM6uknoqWUXhtowWjnCIug6yUtyZ78Fv/u9fco1ZP3lypO0B3Pu7nz6m7QiLaCpb61SRRbapHmM6/kEcvY9RYt+K88UD6UNFtljpKcBs4ve2LxrH7xlX9S+vWmr7vLTWnp3QwV8GS+Jz1RoXDZ+/9/+GPsyA2hObKemsweXShqQkZGBjJRoNNL0OTJupy4+/I3v43defQGL473oHR5XB6m7lw+pXxdQTQGzvZkmWDLE1bZ0qpurkZTF84ONuFraRBavVLLKheFmQQEscxRRKBiaBnpRWlSMJ1/5EX784/8LEW4jqK6uhpWLfZI0iD/8g3+Fl5/ei15qFhCQgM1Zafjacy8iLztN0ZKOUvssPmO2ORduAN/Bd156Gu10Ifj+v/x97MmOZn1ayazDA5KLwoUHyZ69e/HE3m1IyN6OaH9XXDpzBlZywKSnk3lrpBu1nUOYoa+Tr06PnfsPktEuAy8+exzxUWHKx3DX4efwb/7dH/Lm34a2lma03ilBv8UdaRlZ0C1NoIomObm1TnFC/s6/+H3szUnA5PQcvv3D38PujAg0G0jBSc2tgK77BoTBZuqkKa0THe2tNHu1oaGVpp7aZuXbs0hNsTABbd+9B/GJ6Th66AkkRIZQ1vDAjieewb/4g99DsNcs2rrvPZLXzpxu0zTah61fyL+O4WkKGssCNsdTuOpFIO6iNs5hKVhbm0fzl2zA4tsr5k/xkxPSCy83ao7omyXCL3cUah6j4bNgwqmP38PYvDeZjoKVC8oCNWdtdBUQNqusLPuBprVWMn7+9C0Vd5TPpiW01lXy0mMijXCOcr8RfzXfQGr2I/1x6qO3UFHXSZa/aEUg89n3P+cTNm2OJkFXWXOkwxbB0JduHlPUKNt9s+k3apmgJoN1oy3N3Z1UtW7z9n6hqbGXWpMempUPPP7YBtxopGfpOrTkBh9PCvTsA09vP1o+rHcrHEDmyLScbB7aJfjozb9HYVG5snaM9bfhyvmTKCisRBBN9SK0ak8knBAfT17mxYVodZK9RPz1PMio6O1l9z31oV+ihXRjcqiPkWL6xlVeZg8dVSxfq99d7+9StrBjssvvm+RSYaHg2dnZDR9SCwd4u+IqNcf+iVvIpMe1Tt/0afq2ar98sLUy36hVv5/r0wLdvcQ0LwLjzeuX8dr//9e4VXaTe189jEth3DMCsUhFhd0NjB2lKYmrlw0eVCzIpcPdk76OLssERcxHLjxbduxCR0Mliq5ewh3uXULiE0GWM3+PJdy8fBLvv/EzVPHiZKGPp5aktPu0InhRuPRSY0q/f/60ck+UuS4WhlHOq5b+GaQn0iWOlj4hiREil7a6ClzhBaBncJx05nrZETQmcXOjS527N92M7HNdyAuECtiR/EULlxyNC5+8jZu36nlWxnA/EJP9NLXTvegcmEQqhUM9FUVa0wKVVULwpPPlGmfy8dEp/1yZy0KaYh5sw83iUtKhJ1B9Q1dCKoCEvEJdHMicVk3XgL1PHOPlf62L1sPrIT1FP3Jip3tzfxGyDQ+yLc4xfy7au6+L9WFyuIMWkR7E8oLnx3r60cVp9cX07sMaflmgNnSSSi/xxVVkFTyzXTkO0jYRBHXBkQghCUR9+Q1cv3ieWlcjXL0Decn1R+OtG9xjzqC9e4BzRLuFTfKXOApP+nEL0Yyw5botTivrsDRBYpGSsvMwP2LAlZPv4uP33qEFpFf5Rk+TPn6A7koBybuUtd3hJqWh6VxMohgJVOfZve/NUAM+2NOCvmk/JMVw/6SlWtaZIsLiXtpwpwzeZEHNyUq+99Uv9O+vlCb4QT3h6u6BKNIAB9PvNSQsFEYKESJcyC14nAKmqxfpRjdF8dAj85SnDrExYXAxz3CD96QZXwQOuQS7IyEhDhfzi3Ep34yDTz5JIaAGY3oPcmtvpqmaDvYLrjTJUitKv6Xd27eQylT8acl6RteB0ckZZFFjIEEEkTRhDdDpXlwGPOnk7cdDx48bsMsiD3kKNuKbI4Fqys+Jz4h/svjk+gdHKTpHHwqc+qAIhLA9AaQP7KPwJxd1O1PcIm+IA0rIfPGFb8GXI2g0T8HPW9w95pCRuxWR1OxJsBkVdWrSy6EjjvduvH2KNjEmNgpB9EkL9PFk3enGYB0hXSID2PgvNC6dlLUJKoAtICQcQaSNDQwIpG+gJ4KoFQv096bZyEbfZW4mbIs7fZuzkyN4QDRwc13A0R0JuHbhDPomXBFK+meTZVhdFMRv1Z2HoPrnLjdGMUfFM08ejDo/+lA9+HDx5U31cDZdRsQM+wUk6f+KzgmYrfMI8nNHdowO2xL0iAuh/62cCF9QUuPCfrFOjFG4oHmbmmEbfYK92V4bD6rZBbr50HfVMyIbz+7IVabFdmqsoqPCMTbQyotWAzbtOkwq7eAN1VAOf/mnBBrOQ/kp5jIJGhHWoLaaSppBPdBaX023omHlnxviPo6hMV6Ivv9DjHVVouBGgZqzmnznuGhkHs5RAyauPPOBPJi5DqPYbvFLnWdfeFJAnuwbYb9M8+C08VJm75eBnlZUlZbAIzQbW7JTVf21Nl784FmSKlOCtCQwRwLzJBBP+kP8Rfc/+aI6sFtvX0MJfZNjEhIRR+vT9r2PQeexgLbGBmTmbEEQ16fWJHsGi+G+Y+9zcSuap8ZQXJXkQm9jn4gb1hyFtSmaoX24dpdoHTKRgnZoVo9v8JDYaMCOKpvly1g7/kn7lYDFSs3bLKi5XYIhixeeePoINVfz6DEMIsIrFG30pTUZR9DR2YPwoEzq7bjBaEoy3+wv2NtOdyMKguI6Jj8lWC4+fTOePv4ELn/0c7S3NsGN9fHgwSpavTH6JYsLWE52Og94LWXTdifMc1Q0iBC7SN9jFxfuRVzbEoQlQXiZu44hOHFQuYXNGH0Q4RMN/7B4HHs+BeMjw6i88hEqblWSGj5KE42uzCcvXrKmJ3rVmPr5uVK4ofMT57oER83aJtBeUyEbNX1UK6m86YVnUx21l6SLjknBTvroLhZeQdnNcuzZvZNnDueOhj5XLJ4UrKeohXRxIaMq3fp8fMX9bpLt9kI//c87DSN4+Xs/xFRfHYq4ngPpez/j7YIb584gLP0A0kmDu5HgZblwLbK8Sa4x8QcXoc6dShslfE7YMMyYgMklHX2WO2gi78aQbRgj5qOYWBR/3XKMuMTjxb3bNxCUxx5iv3swdkICiqd4rom7oS8vIhJbI3utMOOJm09deRFcQ9KQkppE4V9YC/ku14ZanctrRMZQSxLtpjuDN8dH6JrIvVTcMOUy4E7q8wkGgAnt+f6jz9FFso/fzSAwJFT9S8rNxGCfQcX2BPEzobPeiLXHnefrHNe0BOXN0fLrRspmsSnKRV80tVEpm/FcYjaMJJUqu3ICDS1dSI4Nx3B/F7q7DLRCvbih8V7po+X+Uv3HM5v/l4uXjX7S7bVV7IdF1HE9m4b70dXRgbycNN7+zajheZZz6BXKGLqVrL6E376SQrDSQFKwVBoFmezcPP1oupSAJm9+7kn/SnGXSEpMIid8BgIY7CNaUYn8FCFVad0ohAo14Er0pQuiYuOREO6L8uYB/Ic/fgUfvPZLDNt0OPJsFn25LIgKDUR6RibiqQnmSckDwr6p64JCEE5TZQ81oeICMWSeprvEJh4R1N5QYG1pbSd/+wDcfYLol+XDTUavfH8jA6jtoWDoQy2Y3NCEStODi8d93lMtAKG49PQSamZ7sJkv27jA22xJYSEm3QOhZ/CEbckdKQkx8CC/fHZODg/LBSI/OAJ2BI3Bg8L/EgbpKxzEQG8RvqUf5Ibqwxu2D/sjKjgRiXEuSKdG0Zubg0TKu9CEo/Pz4/uMFGX9vL0ZtUxtpSd/twfU2Se6aNI25+Xhl59cZeBUBvbuSsbf/K9fIO3gy0oINve52yOCPX1587Mqv2qdByOzKfzJQS4aYamTp4TAPyB5ceePoH/kF5UkInt8mpoD+h1vSfBHSjgDzXhIbWQD0lJHubyFRSdhriwfQ/0GqqDH4KKLpHuOBzqaanjxCMYEtWO6wFDerkPor0jhl0FCkzQzXr14Br5RW+FP7cUcD1NP77Xm5fXUQwROCwPvhsU3nCY6C/0HzaPuMBla4RWegrQdjyOCvvTj9IUXDZ6eWhJLrwQV6RnERqvCYjzqupuVyW495a08Q+1QYATnmviBdsB3YQKTDMSIDgnixtxBwW+eFpd0zNy6zuC7bgYoGeBB857ecwHXzp7GwIQf9uTE0nTHCGPy0osie3nbXSnigb/JfuGF5KRYtDEAazrICz0U6lJTdtOPrx1zXiEIphAgkfm8mlL4nocfteWudNvpHxihAMGLLt2yXOlDb5ccH1jQA77gYUTBy8hAR7EyjJqGMSFILQszaGxqpzYwAu4Lxejt7IDLFIURF39EhwXxUJtkAFEbMnbsQwCDSTc6N0XQH2NMwRj992d8iBYzPgFXHkAjZgtNwjEYbiujEqAIew4fp/adh+m8C/YdeYZmSt7RJigkjs9yD/2sFvsBjV31sf2CNcKYCiuFkOnJcYwYhxDGeIHayltITk1BaHgUYwcmGDsxoszvQWFRSIiJZB1pPh41qL1K9iYNg71cvguD8GLhVtmAtqYWLIx2wDMgCsE6b7TX3UJAfC486Jfr4xcIf38rJmeoGd6fB7FijVNTa+V4zdJyEMRL/b3IBqsaeN9fxWUoKDKefXyT49eJOQYIz3LvjmS7Da0NRF/wRWLuHriFjWDOYoJfZ69aazbLCIwMFpX17UtFytLURtxQXDhfub+H6xn010K3N6IojVmQsi0Wfa01WNTT1W14kJpif7q7hSPANQ53Wu/Q4jCEzm4G0g3O4Phu7k8iOFKxJEgdWpIPA9ECGdRpaGtDFIdtaHgMm2ienxqR2J0xCl7JeOIxL84FxgJYRykQMlgbs6gpu8wgyFHsOniEn09ggRdNrdTJrrzkpKSnoZ9BjTq3JfTU1SEtazOmGU9hHjWrS63r4gwDBuux46kfUAsbpBQAEggssTIWzk/1jxc0UdJoSZ7eVLTxLLxT1MEAuCRaSQ3QhcbDk+XV0Mqat20Ltw5XBhyGgA7vCIhI5hiF8BN+FhDKmIRBeOqjEBcrWvn172z2OroyqCwVfVVtDHJrx0R3LQJjM2jlXqKloxrB8ZlYso5hjnuPlQqwBUpLEnDMsHZ0tzAY1kOPtOQ4Lc1d++wSAxK5xi28yIvgOzzUj9jwIDQyyDOQQa0Z2w9Az9gPm7mPaCE6znV/1e9DbTWYdAuhj3Lc58oCawt7NH+5/SnTo8nqS8qFtwvRvLb0DGPf7m0UpNxh5k19Yt4DW4kOYTb2Ys41gCbiLAS5WnGCh2Y5J7oPzfbJ8TFop/l/54EDHPoFqv4HEJe2CSEBEq0qPOUUQF3m0GFaxLdeegYTvKku+kfgySOPIZgmUl/eUC9fucj8GuDhH4acjEQleIsvXQid76+epkN9cRmStz6Gowd3Yn5yBNeKSrnhNKHHvIRnXvg6MhMj4bE0g09PneZGHI5wvQ8ITICs+DD0jc5hM29Fnkuz6Boap5/UZkwa++hS4c3NI4OmQdE+ZaKkqAgNDY0quj06czc1YsloZWTxWQaOGEwTSij1p+AvWoDFhSUKNQ24XFbL4I4ULE2PIzAmDQkRgWivr6ewnodMCr/DrVU4m38FLb2D1AQnIszfE10DZuzZuQUT9EuT/s3bnEUTVjc3pVikJ1CIoeDKblPR2pW3q5CxbT+2b9mE8sISHP/u95ASHYKJUSOmXXywc/MmDHTUoKKhHbFJ6TzUBpGwaTvC9F4YYuBdQHg83TW4KfwTJBn7UH8P5MRy8wqi6ZAaIgeUjpbqaEWHcKWGy9ufvta8cJQVX8fg6AwOUviICfXBDZrd9VHJiOem0EB/99u3yujyosMOupXMj3Xg2vVSCmomzudGWKnhT0xMxvSwNnSIWR4wJec/xLmrRZiiNloCOiOjY9Fx+zps/gnIzc2hcJKG8IgIRi4PYt+xZ7kxR2O4i4EXFy+ii24xR7/+bSTFRSnrhpa+8qB2zNd9AbdvnMetynps3v8ccrPi0VJZwrWygJ179ilh5dplBnVY3XH8hRcR4DaOD9/9lILjABE1KNB09SJ32x6O14qGcT11EDNfVFQESi+fRll5NcJSduDxA7vQ31iK9pEFWohAn/ZTyGfZxik3HDv+NQprXgy0uYSLDFzsHhzFAfZFRnKCZqFIzLES7Pju679A//Ao3TraVFR6gOcibhTfxp6DjyOAwn7ZtfM0y7dh95GXkM19xkohsLGtC7sfp8ZS76f2q/W09d5npkZ68Mk7b6KmqROm/i4K2d4q7qGurpEBYLGouPwpuukCI9HlHTxEo1LysGXrFlptUhipTYXNghvdUA6pg0rT8cx9e26aqDA//1vUtnZTCzSIAeMYMtOTcfHkCSTSRBsVEY7u2zQHXy8gykkWHj90VAXMSAB0RIgew2PT2LVvP0Jo6dKaRAuoc7Xh7Kcfo6NvEs/QvztM74by/DPwisqCtb8BZz7+CI2tvcg+8BT20gXIRAHiFJ8vK7sN38hMPHv8SWWZ07I3iM+tN7W5fi5UXlw9T9SBHloZXuJlJwxlVy/AxkvXjl27Kbik0MITqayXGVt20iK1wIC29xgod50urGE4/vWvI5xxHpr6nJ0kkIdRYYG4xkCkSgb7ZfBs2pKTimYKmkMLgQpW1GrqwMXzF9BOlKInnv8m/JfGcfUC5z6Dm9vqq+gaOIak9CwK5NrcEtw9qHzi5by26DyKissRl3MYu7Zt4nnUjMqmXhx47DGeScmIpbDn5ToHXVQqUiJ9cPqjkwyY7qWPeDMaeGnJ3rpH5SNnzXqT7OlhEZFovlVAa1Ux3ILT8fzzz2Cqvwl1bX2IpWXHxTaKW0QsOvQ41xyFMQnaqi2+gE9Pn6egTNccBoLHkH1U+l1LEuWGD892U2sFg4ivElMwAUefPAI/12mcO3sRObnZqLl5BadPnEC/yUo3ylfp7hKAhrLr+PSD99HVP4ojL71Kq0O05n1V6ulPpdycuR/nTp3CwLgrXvk2Lcaw4FZxAfQ8+wdbKnD65KdEa+pAwuYDePzgbrqjzKK8tJR/70FmSoLmeWbvH9p3eJk/+fpPUV5Vz8vrKIP7Buj7vAnXTn3IWIYsbN5KN06OeSQF49HxacZJ7aOC0YtoPNcQu+MI3evi4MU5K2MtVlg/KqPEZ/2LTC40iSlL2BdZyKPOW3wpBUrMATGj/AhpUpS/BSpMVAWiJZZoZwc0mfwtZlD5Xp5zmALlM0cny2fKX4nviYZSYL5kNASGTDY+O1yYvbtEk7oC27L8Husk30pZ4u/STh+z//n2ZfzZf/i3CuZFPlf1ov+L1NleJ+bLMGnR7Mi7DtOLfCZaB6mPJClPypcDXLlP8HN5XzSx0h9iUpUnKQ6o9xz5SJvmaeJmrfi8fCsKLDEPEoKN+clzqm1ss2qZ/M185bl766Dqzuf4gHpnpQz7eKi8+J2Y3NzYf5Kvo0+lrxQ8HT9T77Fe0q+qPlJ/Fq7NxMkKPuKk+n+jefLl7uZRomjQpzOMmgP273qTzEnpJzV6nI/KdMu5JAeo/G/hru+pjI19Q1jg9zI3+X/+k/kGDFYPImk/b9L0N1tPkjJl3ig3G77gmI8yGDLfJF/JX56TOtrnmv2du+tqeW045sJ6ynU8o9Yny5eWK7Mt+0zNd5Ync0HKlHLYatUX0vZ5amZVWp5HblzL9h5x5Lq+n+LPq3zR+LjUXcoTPFpps7RfzVv+lOSYl2qNca7KOElfiaVG+kdrcvS5tNUemGTHQZVxkL1J6iHuAapfVDkc3+U1snq/0lquPK/KZv6y/0iyt01+l4ZwvUrZy+2WOWBvp30uq3rxUce6lfe1JMc8su9p9j5U48x9SPKUJHNCWm5vp718+VzaL3V27DHymZakxlO12z5+d8eU+UpZ8r30jaPP5Xtpr9RVusMxRzYyz6Weao3fM6aSv/T56rqsjLucN/fvCy3tlsqLq53MdUlqPDlppWzRUsv3qm+kkep7GQfpCzk7pd3yjggishdon+yqD1m2fUzt1jX5XcZS5rpKqo72eqg1Lu3mZ1KelKjW+AbKdsx1aZpj/NT8Zq5qf2Pe6kyVPUTyV/VY3g9XvSNt15pkvt47flKEyC0y3vb5yLnHjNV64pf2+trHSZ5R7d9Iu9VakfWyeq7b+9c+1zkey3PR3i/Sftnj185HrW12PK/kpHvWkuTt2OPludXrWeqg5qM6b+RM497AjhF4tHCeZV9UYLqjvl9JIdhR+d/mn+Lcb+rnDbu0Gd947knNpqTf5rY563afHuCmuVEh+D65af5o3ragWQjWXIjzBWcPOHvA2QPOHnD2wBfcA1+mEPyV9An+gvv/kWQvt+dgAuG/eDyGPq/r08w9koKdmTh7wNkDzh5w9oCzB5w94OwBZw88tAecQvBDu2iDD1Cl7y5BZvznTM4ecPaAswecPeDsAWcPOHvA2QO/XT3wz04IFl8U8cNyJPE/eZRJ+fkxz0ed76OsozMvZw84e8DZA84ecPaAswecPfDPvQf+WQnBEpwwTRB+gvdKqA0d1KmtJTSZMGA9iiQCsJlwUj5+hAAj/NhyDNOjyNqZh7MHnD3g7AFnDzh7wNkDzh5w9sAj7IF/VkLwLMGib54j81boDuTF+CsImE3bCEfj403N7UN6lZGjQjk870JcW2Lc+gnT1T1J2IxOv/cLZB18kbBlGYT4eFim92Sg4U8ryUDGSUEYTCxNgcFxCtwaOu+36VFaJibNRJUgtqIwWQmM3V1+Dn4nzGlDhAuaFWQQLz9FWOJLWEABVZ8lUoKnL8lMiImtJ0yf1iT4whNmEwy9/SpaOCQiWsEK+RCbWtII8XlNJhOpuMm2RWzd+NR0QunMKfigYSMpi2lUiU1OIxYoqTc5B7UlkiRMmDE8OEgK80lFG+21DLm3SDQTwS3u6uohcPycYs/y4JrLziVBDS+uQ32dGCf9q1AAx8dFc+5rW2cStCrYpIa+PlLWzhD3NwDR8UkktSF+9nJewmg1RYifppY2xMQnk/o8jOQek8T8bIeLTzDCw8PZbu1QXRJ5b+M+NEZ84J6eXiRnblJjymYxMbqSLFbtrS0YM5uJpe0HP2JEhwf6YoTA+2NjZhXxPUVGqIxNmwnbSHg9jQt/mqxNw5xro8xLQP1jk8iKRhxUDyLRqMR9btpC6tTOLrhyPiYmEXpvwsR3TIqMR0fM5Jj4RMIYaUXGIEQaiQH62H+TxF4VoobA4DDExEQru9wSmQDNZMQbJIHAFPFLgyLiSMISynB6G+d6Dz8jgQrnejhhr0KI16ttxIk6wTk1yfEc5Fpy5fgJRJ7Oz050IpH6Js4pwYedthEv2NcPCZzr3ozlWLAR05n9ZegfIPXvDmL2inJDY+lcKIO9XaSuHSX+MZnT/IMJfRhLeM9VZwif6W5rIJ2ui8KPDSUMnIHMiBb2lSep0kO4z4eHBtnHSMN/hRBiamJErXFhoQtgn0dEx6q5LtkIUY9gVY+MjZPq1gVJKYToJKbsBCHCjCOsLz+L554UTKIkzdjUbJOM6fBgH7GhiTNMqLjIqCgEECefEfncP+bYxk4SUBEfnXBqweHRJJrSc/43k558El5kmBOM9JjoCIXWpKHZCn1BMaANDJKggnl5+6q9Sta4ICwJGoGNOOO93R1Y8tQjlORR/oTqmhgdJjEQSS5IWhRILPTIaMK3ca5rTfPEVhaSlW5DLyJjE4nxHnUXMEjmumlogPNqiORIJGgKj0MYCbaETln2w1li/fsFhiMignXSaSfjsRH60mQcJqmWie3kHs01HkjSq9V7tJTVazBwXOYIu5pHHPRZ7qv9HAvuC9zrw2MSoNeR4MqxL6yrA2RMF9UaF2zvRWI16wJC1FyXPlcshMQAN/T2qdymiRceEhah9tIhQxfrMk1G0jDutREIJZ3zl5W+WjjBskHzABnlJtz47QAAQABJREFUgTBKPvvxySnCevCQJCPLmHmCGIukaeSmKSxUwuwmDDVCQCGbrwiMAwP9qL9ViHEvbrA6Fx60UwghQLzrgo2HAgGyLcyP0CECjzZqMhIsmyD+JAuQBexF1qaW2lJcLalDADGB/biBeizD+ohAKgD0RgoMhVfOITyJmJdk8bLx0DRxIxFWOoFBWeSEn+Bzo5wgQpIhG4Ew28lkVWw6hGqZ56Y1TgKDMQJ6C6qNnHHCmjXC9k6Om0lXTIgobi6moV688+t3oY+MV/iNIgg7DvAva/I4y1nbA1pxgkXoEciejoYqXLlwEgZSeG/K3cZ5Zc93kUxPw4Y2XLp8Wc2DmjsVWHL1hNeSBdduFCk4qYaaalJukqWQm/jU0BTxVQk4T2zF9SSzaQAllz9Bey/nZB+Zo3pHEMKDSMDTJQ23VePypXxYOOdmeBiHxSVifLADN69dxPAoN9HmSgxOEYc0MoyHqjYMUZnDg13NyD9zAvlXrxP/9hmuVYEiZK9wXVjNw6irqyeY/wApzytx42YVDh46jAVizVYVXsDps+fIPhWDNOJKOmDj1tNmecZG5rCqwrO4Vd2MCYLVNxNz20MfgYhQklYIHJJal5OoLDiPd995C8HE1oxmG4faa5B/9mOU1nYjI4vC63I/rbdc9RzznuLF42Y+8Ug/ehdpWw6SVCbo7gGJ+Wl8+vYb6CC+JoGUKBz4EchfT1zkRvQZeijE9eACsc8ztu3jwUkSD40CWU9zFYpv3MAIBbKO+kqYF/wQHRHKvheBTKCr5tHJ+fjhr19TdL2Z2Tkou/wx2g1DBMHvRSsJRvQUUAWrWEu/izA2OdqP0598xAvMJPFnqzE4Rqpg0tor4WppAf0dxHCtbSDBQSNKbjcSNzcCU6N9OH/uEvf1GVQU3oAPmTSjKEhpFcjmOOYdtWWkISY+as8Esom7riPph2NMOu8U4UbJLcUwNsNLXyQFfW+S9IySpS//xK9x5vxlbD/4lNprtfS5CAWzUyO4cfEUmlq7MG7qRRUxVEXw8GKfS17CoDbF+X7t1Nu4fKMMkQkZxC13QXnxTQpKfL6yEiDLW3J8tL2+Gv47xcte+dWTJJ8wwDzUhVZiTQeExyA02C5kTJE8ouZWBfrIVFd89SxxZEkfTHKmxspyksMMoPT6OXgExVNQCVP4rRqKVgQvTTXlyL9WTOa4KZQWkF0yLpkCdYiiWpcLRkXBdZ7LvWQQK8fg+AKykiJIVf4aeodGeNEhVKK3HhHhobywaYMpE6i95qpClJZW8CwdRjPZL2fcgxBNUgo5KxdIFDTY0YArZz9BcVULUjNz4EmOgOtn3kffyCT33XYKsEMKO1tYWzUlrvFZMh3eLryKkx+8BV1ECrFxE1bWONdYW/0dtLS0wNBei6oGAwm4QtDZWIVyYqYvkDq9tKQMsYlJFF4DH66gu6dyA11NHMsLGCLZSm9LFQYsrogkBrffMs6zuIQOdLXgxLuvoex2PXkTnsD4QDtKOD6DxnH2DYVR8ioE6ElSIvvhOpMoF2yTRlw4+SEMA8MY6G5Fa0c/5zrJaESzw3JHBrrQ1Nyq2B/LCi/DOLmItIQwVJVXwEgOgrKKSvgGRSI+JuJLwwnWqr5ZZ3d8MY+JdmZosAcFhQVkurJgcs4Le0mYsWAZwoCZ+L+kRN6Rm4g2EmJ09g3DPzQSzxw9jHFjP2qqqghCTcYjAsEHxxCHkJuTjRoH0d52EJS7hgfh9Iwbb/tbkJWZhuuXz3CTDMAAF2NwbCoO7tmCoutXUNkxQfYgF7xE4G1vCstLFFQGyGpVwklrXXSDcWxK4eEKy5ahvQ71LT1ksQvCgYN7QREXt28WwDQL7D30JEK9yORGsPxbdxrhR2H8ib27SC3IQ76yjCxe04hJysS23BQM9HSgiUxCrtzIre567N+1BT1NVSgsuAEXMh/pnn8WySKEaFRQfDGj5MxVUw9wYwAZ2GKjKGRN2ym8He8vUTAwj9oZnbJI0WulwDYsmqyxSbgFxGI7gcYrr32Kpto72JSZLTKMpmQaMKCUzEJ/+Cf/FV62fnzy8Um0d/WS/CJS5SN4jwFhsWRuOkR2LdJ/k+2w8EoZzLNeePmll2AbrMHf//oKcrhewoIDNZUtDy+4kMeemtCmtnaFSarqzzksjJCBkUl4+vlECgdDKMo/D9cwf/gyxrSrtZVkBybERUcpLa7mRrNcGy/FRdeu46kf/kfEBpMEg8QBlZU1yM1MUpoPoTo1kzWrsr4DyaRYF6FYcFZnF10J/J4Nw61+aoqW8Yo1t1pq7IJo0gMHlVxRGqk1WbAsqmCRumkH9mzL5Z5GVkdfH47BUe5XkxjorCNpRh/CKIBrFQSl5LrSfHgGZeHw4ccx1lGGX58rQh7ppwP0OoWZaqXWsLKsmAyFJGZgXYTyVQ6o5//Vn0DvYkPljTOoqW9FEvtFi2AiWqCBllswkvb5a8eew3B7FU6cysfYU8+QMMhO7BObnseLVhrmxg34y7/6G2rpsklx3IPg5G04/uzjuP7xz9DJvX1zHi0CPus/nKV/RfNHVhJkZSSjpJvU3AoTdaXnBcM8IiEN27bvRCDnuk5RylvQ2VSNLtOcAvQX4iEZHi1JtH5j/W2o6xjFM19/BVGkn//FX/85iXEmlAbejdioQlvdXFWMgSkGUpMV1EbtnJdfCPYefgpzU2O4duksOrr6cGT/9nUVrTBYRYPCtTRBzV4xiSq+8+/+C4K9ZlBw+SxJEtpJiBCv8vINiCB5x3Ok1J3CZG8tCTP6kJqwSxHjSB8tjHXSImMgUVIutNo9RBPbRkEvc+dhHN6bi49/9ue0fhiQnJJCYipiBnv6Yf8zXycr3DgaKotxqrAWLx/bzfnvhfS8ndhOgiWhEdcyzxwdJON9m3TT8bteQN4mMqg1FOBU0U1s5++izRec3NkFFyodctFd0qrWs9ViRU1NM1799/8J7lYjiq5cQmv3AEmcaJHQlLjCOVGCYtPIxurNdTW3dt6QJCmFRFGRcaTkHmzHL989TTKibFIIdyMlbz9256ai+3/8J6VFjk8g05zdTLTOGiyRmpiU0yQY+sarL2F2qBY/ffMyzweSHlHbLEoXsQbVlt+gVZtMtdQAz1Hz3EhCpinXQOzbu4d7eQA8qDnXctmTyol8NtxZjZbBOXz3e8fhNmPCm7/4BYzjL9OqolfWxLiMrYhOycGEsVuxYibQ8hBIoqzDz72MhSkj3n79NbR39ODAzs3rbO9v/pi2neQ3L+83ysHGDaGiuBBDVm/kpUejgxPUZrWg7vZNFNf1IIubuQ8neHhUHBJjonD90/fRZKD24eP3UNXSiy15udSAGDkheSMZ7MWt8jLSCQ/hH376D4rS2NtlCh+8/RY6yZBzjTfEesMogqiWv3by12gcIN1kaioSUzLUhqD3FdMpMGMZJdvOWXSNzWNTWiwGSE88z8lQe6sEv3z7PJLS0rn5l1LLUIHbtytw6VYbcjflwJs3rA6Sabz73oeITMtFqI876WlNuHrpPGmbTUhPT8KFj14nw1Armhtr8cmZK0jO2YbWsvOoqicFZmSCYhjaTQaxsCC95gn7Gw2E8+VH1AMMoKRZOItmfrnx37vZu7l7UxORiMWxFrz1i7/DoJWHA4VdMdfKjdpEM61YPCZJ9SkbmbbzeVHRZrp4B1GjqKN1I4w0xq7KNOlonBcpyPvaq/Hm3/9PvPnWm9QSjNBtYwS+etKh0lwbHBEPlxkzL4/TjlfW/5MHQRKpxWNpDhdT/L33N7FqiBbCSCpjuYge2LcTi9SuFF3LR0rWZgrB4VzH2lpsr5xd2zluXSDLox+FvSAyLIXxsjGshF15ZmJkEDVkuUrb9SR57H2Vy4EnTbOpOVsRExm6xqy4/gYvP0mhJzAsGhmZGcrc/hnrDdvssjCFgrPv4R//4ScoKq1S2kkB9xdWv9s3LiF7z1H46fw/02cPr8uCMvX6BwQqk3QQx2+WmhuxPkmykSK4tvgc5oM3ISGehy/ngxyE/r7uaOPlQ9wCzOYpjNBKZg8wfniJjieEeneYGr+IeO7RjJnwJwW3jrTZ45ZpNY5C3CD07F50MzMNdMM7KJb07h6k8p4knX2cEoZCQiOURniGZn2tyVtHyvtNeYgIo1n/Xq0iJ59cNJpv3cDr//DX+PCjj0kjPYV+atS6yZq57wmyfdEFSfZ7rUniRMZocfHnZTKQLgUSKxJKoX90gsoSCqqieRdt7dWiOzh27An7ZZIFyUVpsLMB186fRv/oNNkb09ZVtKwJ5QJBNyqLxUI3kinMLHohJNiPbhbBtGD68ww03c1LXPu8uc6lbSazleMeRXp0f34mdOR0E6GbRDTdEXzv4/53N5MH/CIuTdyWSFkdqWJvQkNDacmdhm2WF0gWKNZQPz8/CmZztJAOIzEtE8K25rJgwdVT7+Dn//hTlN6qUZTNDyjiAR/LZYUuB1RIBXCfkgtdIF0OLKMDqr/lJRHykriPxFD54IAwFUInb3dqaemONEJXhbExUnjTkqs5cY170fVj85at1L768rK6VsySuS4uRpWlBThz4jRSyIgXQNcmFwqkPZ1tiip+fGKCbhykjJbLjKZE2YZWZB99CPdoPd2KhLKbezQt6JJkrbdW3sDwYjjdy3KVq4fM0Z6OFhjJ6Prpm/+AN37+j+jqG+LFQMgz1p9EaWKkYiUkJgU6faA6p4J4WR3jXHe0Q/Y72Tta75TALSRJsdV6enqRrlxHFzW6e7l5k7E2bv2FPoInv1KaYGE7kVvz+KgFPVxAEVEJXNyB0PkHYs/WvUjhramrqRIN5Ofu7jPSfYB+s3Q9MAyTSvjAXlIPZ2H35mxMUIOrEgdjlkJsB7XGsfRD8uFGJ6ZJV56t3r5BpLPchnhqivrryzDKDSJUDg/Sp4ZxMQu1n6RZ8srPkEp0257d2LQpDlsyE+HJOT9A355JCuitTU1Y9PQn640PkhJDEUsT75Ur13DkqedImWrAvFcwdm7fQhMUXSNoLhyiy4Z50g2NFH6D6aPpSV8pL/qCbtqxG7mkTG7NTqFbBRm/fXiQcAOJjIrmzdYukKsKOf/zf0wPzNEsJgfkkk84dm3PoFtArTJj5+UdwdRsMbUsDTBPTcObFgvx3dJ2RvNp0UJTMyAuQC40ZSn2Mq4rRwpP2YI//H8yYaHPcsn5d3DuYgEWKHTr9MK2RmGS74jWVovJzJH3w38yf7o2iZZ7ySeEVNL0FbxTgPbBGQoUQ+hra8Kc/yzXyn4E0mynTSvKBc66C2uVYuPjn8JwqBK174b2JhRVdmHPoSSaifuxGNSGlPQMRIfa3UQeXveNPsExcffFN//l/00/6FkKQU345c9fw+bcLLoreGDESNN1hxk/eiVPrXntpfAAonbPwUwlJmM3ETq4r3IiwDo1ges3KpC59wgpzg2kcV8glbYZL37vD1FVcweNhnHY2Fd6HnD2d9ZfA3WpYTkiDC+K8Md8RGBzFzPpcpoV/1sKwOculOLQs99CYpgrKV6rlLVObnhqnvIQ/YwQ68hggz+lLYlbHsMfZe+hy0AvCs68h4tXrmOppwRWz3C2tYNMkINoaWomnXEuteYa/O85pIIZLwKCYo0TIZVCh7RB+kR80xtLLsK65I2O5iZ0tbfCN5x+2LnpFIwikEzfb2NxMZqqa7A9J0vFC3zeOhcBQ9xOyspuYYECRWAQtX+c69J3Mt6ShPnRkeT5MeMA7hRdgk/cLmxKjVc05BNmI+4UXsSsLg25jG/xXqeLlSNf+enKNoqANbd8yVLKaQ636yrNplC/11fdQmO3FS/+4AlFIf79P/qPKhbA0FKDt99+nReALMbhUCP8eQ2XAu9J0m61xlmwzHk3BsGz0+95auXPQFqOv/W9H6GqsQGN4tPKftL561ceeIS/+dDPOyo+iXNiFsVlpbDt3ILHjj5LxdxN1HCsbUtuvAT6bGCus33c00XjK4KnuGCu7NH0y6dFpvB6IULStmO4t4euKANob2un9cGG+E0HsXtHHnqqC3CW1NG//3vfpd/68r64jrbLfHbjXBfGWJlrvENhgfPdjWtcvpMk1s05mxW3K2uRfegbCKfWWTTIk2MDtDJeRzTrtZXa+i8zrayGL7PUDZYlG8msbQ4Wmir7PWJx9LBwigudK7UI9P0VX5/WqpvoH/dGRnYWDE219KEkj7enC7WsI+ilk/wAb3ZeUcs3HA6MBNyEh4RSgM2FnrcR0VCEBhA9goPpwcAF8duSiSAbl9yYpyzD9DEaxXRYAHx5MMmNUm6yI8PMO4QHlXlSBROIz3B4TBK10zmcCZmIiUtgXu44dOhx1JYV4fzVUmSEyOY4S3NTD/SeSwxu4sTnTT01Mh65eSnIpt+YmB3NNKd5cAFLIIUny1xQk430ukrYHkCY3pP+kdrNFxscBudrj7IHeAhN0F9dAuAsFhs1kiM0V/uhn4E47i7z9JNsRFBMKlJSMrFoHWOAjYGHQi7ihNOem4mV7gLekSn2IMwH7+/3rbGO2kTXeQuaeeHymDHS33wRCTSzD3a3wE0XoXzlZZO2UovgTiFRzHqR9NMcHDOig5rBqb56eAZKoIt2Vwhuh9Rsjqt1OcWLpNE4CD/3YOX3LgE8og0w9dIK0jmErYe/rgJEJmm63U4XgQVqn2d5EbTQR36e61Jbs4kI4+bJICN/dHczCMvogv6eLgZopbK8DngyaMmdF+DtO7epoKwZmqanKRzOUntlnRxnoOAoJuizL/EC0zOhPKi87tu3D/5QAuOmMUqBVgJBRqmVm5ygz6P4xHLMExLi1IE0zT5Z5AXYnQ7iC3S/Ej/ivs5mRGXvRkSQuEKsCI8PLuveb1wRGxuphOmO1jaMddYgiJYGGxUBQ/2kV+edKGf7Lua9SM2RjcITXcb4oXdQCHLy9tDy0EPXiJvIoJVKqyDq4eWj4i+GbzRzDidhtL8f0668yFMuaafwF0YN7cTYIE6++yv4xexCbIgfBR83+HIf7e9qRV8cXdMYyOjpn8L9fP0Hs6MHJFDJIuPH2ArLuMR6TGLUdY5+q1bOdQq683Y3tmkbA7i83THF+RmZtImub66co0YKUwu8JFgU3a4jz/X8lHMkKDwWk8bb9HXuwlyAF8ZmXOnz681ApB6WOwN9WAKyM/w4L3jh5f8kmEwCl2YYJBdM7XdcTDjucL3JxeFhSYQNv8AIbNt9AEu0tlgnRqH3c0UnfYF1box94fkXTRP0YGejWuPzXEsttcUorOrFk889S+FlnlrQPnQ2l+NaaQuOPveCErwlQHVNIN/DKsLvfXUM3HRhoBSD36IYgzNEi05UZB73rBGYDBP0k41DdcVVFJU1YNfjx+DJoNtZBuuKQDZNDTYjIZXAzPu25jXuwqCsqMgQ+tAPQOfhguGWegaIZdAM348FzgWx7LgtSKzNKPec5fU87Q+/kChqcBk0T7ZXa10zUhK1+2HL3iZulmZaTGRvG6MSYYL//Hj+d3V1U7MezjghG/sngNrvLJTdvEmFmQ0h1Epn5dElku4hXc0MiKUfr9bAV+mpcPpQ93cYGWDYhun+engERHIvpytpbzeWaHlMyd6KBV5+zdyH3KjxszHAOoryiY0Cq5w/bvSFF9lHrE9aklyoQ6MSMEJ31YEe+vrP8Uybp+XDzxOGznaeEwGUsXwxSOuiyeaN+Fgq+Ri+Mk4r3On3f4lhaziO7Y2j4E4hWub6Oua7lvo96Fm3P2V60Je/bZ9beDttqK2G0eqBuKggdHOCRzCoQ/xoA2PTkUTfHYlq7Tea2YGL7Nxx5B08jFi9BzrauOnzdjfAw0duG4khXkpgzdmxF17cfMZm5eY0T/MNo2F5AHc01jD4ZBdCdD6cUO0ISclDTLAPWnhLnOLBkJyYBB8KpG7UwE3SxaK6th6TrEefcQxbdx1AYnQYjF0dWOCGPUsfxIAQ+hbaJunP16FME6EMfsil1nhmdAgdvYMY5gYfmZACf27AnfQN8qApUISB6NgYmk5GYXP3xza6ewzTPOzqG4HEuCiMDnSgx2hh9C4d6OnHptWH57dtfL/q9dEeGMdpSrNdW91tdHKuTFHg8vTxVQFa1069D59gBqlx0+jl/FhanFXBkjHcyAPoS97Y0KSEGfiFYuv27Qig2c0yZNEQGGfXqC1NmdBBf3PZIENiM5GRGoe6gjOweEbBfWYYTQ2NMBh6MDQ6Rc3oU0iiuXSc2rL+QSP6evqQt/9JpCRLpLtGwYTrs6+9kYFQNdQ2mqjN1iurRjN909qHZpCRlkBtbw3MCMD27duo7aXAFMx5n5zK9UkT3yKDl1K2YlMGBTJu1jz715+4uXpSAGpoaIFpsB/WWQ/s2LsP5s7baOybUX6CmZs2cV0l009tGEmb9zEoKYqbdwPqGhrUviEaouiY+A1oZJdgoen3TkUZ+7VbIX4ozersGAOISui7l4z6O1WMU2hDb08nQhJysC0vm76hI2igFWnTrscRExHCS7qWBju6xkWZ/Xva2xhbMYTBgVFsf+xJ+vqOUwNVicTMPGRRGZDAPvajq8KSVxB208LV31qHru4e9DGqOzA2Czt3bqVmUFsgrhyoPjz0exqrlZnXOGxGRt4+pMUH4vQH7yE6MRUGBlpWN/YjISmGFw0Kb8HhCA4KQmN1Jd0ixjA0Mottew/QDSxM23iz+fO8MHbUVTE4jUE5E1al7Ajw9UTJhY/gHp6OuZEuXgab6bPahTFajvcxZiNncx5S0zN5xoQrNI/HnnmRwZB+2i4gnJiC8jHJoDTpP0EF8aMZeMfWTJTln1Z+mDvo259MV7s47vUSiC1nkt5tksFRDOoyDdGsP4nsHfuRkZLAPd4xlvf/qbRx7p7KXUan0ynXHbf5SQZhdVGw6+EFLwx5W3LRVXkFPVM+8FkcQ9HVG/AmCoOsiZk5au7EHecC/fC5t4h7wAzPxtCwSM1rXDTOC7NWzuc7ypo0Pu2Onbt3YXKwDaXVHchKDsNHb7wB74BwuiS4KESIMCJ/1N6+jW4iY/RxfUTw3N1KC6gH95eHNH1Nh8izXhTm2lvoxjM4wBgbK/evJ+E6yYtcPS+97OvR3jbU1tcRBcOs+issLJxzsJ77bR+RE3oRn7WdAZTpVDCsL9B4dQXmZiy4Q9/6TqJPLBBRypf7m95nie4PZ7jGstHCoNSO9k7GeBjgQoXDjm1bMNLXTeteKwYY9xGctAVb6BPtCGZbnffn/875RoXgSH83AxuH2Yd92LzvSUTql1B2/RJCEnPVvE5KoaVB50lLmg2Hnz7Oc8Yb7Y2NClVCgmbz9h5inAqFcA1tF4uKt05PuaeByoIRnk+89CTnIS8rHhfefwM+YYl0QdOhgeAEfgnbuNelquBTo6ER585eR3J6iop7EMVlZEQELRKuvDgwWPphk/7zO+Sh39J/m+L/VyQNddXjo0/OIYnO45nxwXjzH/8WW468gqMHd9GY507fNS+7uwT9yKYFGYJaXj19LQV2aIr+UVZCcoiG1pOb0hJvGxwz/u4L6ucJETNGAXiRk1WnIJ8ETUI2ETGziglviaYlXuSUz6RoTMS/SjTBkkRDYKFmYXpuUfmx+RNySW5wos2RfAVyRCBKXKhNEPcMgZ0JYzS/uFTIMwJX5EUfrEAFHUMNl2jIGI0vWuEAf5reOELiBxfMPCao/RJsY0GwsPG2bKLmOYSabD/6tH3Bc+UrMkv+iarJMepuJgTT4BQ8wjhmoqZfRxJzpGh+bNRAifeXaPyD6Dto5fiLr5oIeKLBmuH3Xr46Cl3036PWcJzzijcwBe8lfvCLs0RbqB5E0v44eOrWJ5CKyUwuaIK24uJGvyy9noemGwRK0MXLl3nOKI2MQPZ4+/orSDDxVrQSfUUOa/FnDg4OuutTt47mrnqEGvAxamG4bpSmh1orgfwS86n80/v7c82a4UptqCeDY9xX9adE04u7gMAY6Qjv5TC1rcr8c3+VLU/yGKNWcI6Fi4+1WIEEQ9yFa9WDPmripyzPWaglEmuRuHzMEFJpnFpE2TBlvYogLOtOW7IjwojGRXxCqeqiP5xe+cNaiU6jpybeQl9AgQ9yozATQC2sJwXOWa51sUZ5cFxWQx1pK1sspYQK4/5iJTScm8BScfxEQJQxkCA8x2XGyrbKyeBJDe4Mx8FCtxt3+rP6sa6+mrXf9loqbSph8QT2S+AApf/E79jMPdGHPqeiPZP9UfpX/CYDg+hDS42U1TKuytfpl1F5ll3RtLRd4AAFNWiC81aS7K3Sj7JPu1DjuDA7pdacDImPOgMI47V8s5L9X/rDj+WLuVfThWu5kjK3xEd3YZEQaGyXuBdMcbzlcqDjXJe0SKugrPMloth78XszFTqzFEC9OD+lrxxjs5zlun7I/iJ+oGNc4ws0sfvxTBPBSurjyrk0z/U/Q1/wGVpYJfnStdCddmzpL9GKq88o2IgPunarB90FqWmfotVkipYFPQVtXwYcinvEDCHvRCsowpKsZelUcVcI4R4g559oSt25DmUOyDg5xkJVaJ3/EY2inOPSNjnng+k6OcN2L6oxdFUC+vj4JLWOS1x/vmoNutKqKxB+st9JX9lRU9ZZ4N3HBB1ihtbhIWWp4iJXcoWM8yTXtvhci8bbwrkoGk8917hcKgWtSvZDV677wBDOfZ7xG2o3lXkikwjMnGOPlgB+Cf505VwX6D+ZwxIMKa4LcjmVM0W01YJk5cF1HsRx2KhSTWIXptiHbAjPlEA11wWmTvZV2cumrfzd21/JMBwFzFitCorTse5lrgkknz8F4HB/D+79Wq4/dwdh3b98pYRgC81lZ0+eQHldFwVQBmzQjPTiSy8gdTmaXU0YTmjpTDnA1N8y2rKbr/5M/WX/j+MdWQiS5G/5p+4G8js/U7/zN3tW9ufkD8fQ2L+3Rw47ynS8Z//Onq/kv/K3XXslf8s/R7l8gn8vP7eqDHn3br1W/b72XXnKmf5JeoBjthEhWOqq5oTMA/7umAfqs+W/5fc147z8t8xBSfLOvG1BsxCsXmZeMvfVbGZ2K3NMzWA+Yp+PjnrJO5+pj8pI+38c+TjelDIcaaUe9jo5Pr/7U/qAf6x+5+536/xFBITlTFa1e22e9n6XDO17gvyt/lrV9+oDDf9ZT7vt5cqes9wnj6C9jio6ype8H9TPq9u5+nnpB0eVHPlp+anylT5cLlvedZR17++r6yfPOP7WUt7Ks/Z57ChL8rqb5Hep06o+XvM9H3SUf/cdjb/Yy5Uy+CK1L/Yi5Q/pipW6rK6fzE97V62aB+oN7f8Rn1iVWJaU5yhHfbbcbvl9pS72/rr7mbynHtb6n5V+l7xXl80/aeGyr2NHrnLZlLrJP8fzju828vPevNa0mxk6/l5p98pYr/5Me9ncV5VN3/6moy2Odqlyl/t99Xfqe1ljv6FGS/JxlKXasVwWO3VlHFeVL7V01Ek9I4OzwbQ6H84oyW5NP6vvV9VD/lafLZcn9RXtr06EYCp0nELwqoEQn0SJLhWweOkoubGIZmwjN+RV2T7yX2dFVczkQe2VTABn0t4DC3Ssl5vr6sWhPZcv8Q2eZ4ZWM2+01NhGMIBqlebyy6jFhoXgL6NyzjKcPeDsAWcPOHvA2QPr7AG5A4grxJchBH+lAuPE8VpH9biYhn6bU32vhTKQCzKjGdxBc58zae8BEYCVaZS3xK9CEmHdQnPrwsJXakl9FbrWWUdnDzh7wNkDzh5w9sAX0gPOE/sL6NZbXROMenQlygP9976A/P85ZGmH1mGUqMOM9xVotF1zrT2I4ivQNGcVnT3g7AFnDzh7wNkD/8f1gFMI/gKGdJYBO4K7+RVRYn4BPfDbm+U8XWokUEFg9e51VRG/OQnScGcwjvim2T1Z7PiaKoaJn2mFhlpPT0i5yi+XFZII29X1svtLOXwD+R0tDBKcJv5m8p3dn+w3szZI+TJj7Xmt9d+xl6++tUfpskypq3wu/l7iuyXvbTQpv0e2RWjFP5tW/OocWMSCP6nKVn1lJ9T47Hvr+UTydvTr2nykTsqfT7WRebEsNR9UO/meTIblz9ZT0v2ekTZI+Sv5rn3KMSaOdsu3K2PB4u/Oz7Xvrecve7tl/CQu77P40mu+ZzmS5DNJMtar66Q+1PCfu3Nd8pI2qD61Z2BvH8eE80EC49Rcl37iP3nP8fzqdzQULR1o70Mp+551Jt8trvLBXd1Gx3wQuLNV1dVUtDx8vzFdycQ+H+z1cqwn+Wx5nJbHYeV5Db9J22Su85X7jZ9aT9I38v3yvLK3WcZ89dzXUObyo2vHVMZ77f4mj63MaymLuxvrKmMu6UHrQ325jv845vL92m1/nX2zaj1LXe7OdfbFRoPDVuftmLf3Vle1W+b1qjXoKP83bbdjzkqZ98/LMbe493JeS9CqlG2fBPb1sXoN3Fv3z/v788pWbVbrTM4ux3yQ9c368PO78/83WWifV7n7fPeVgki7T/1/Kz+qILWyuEPkxjEC2ekOsaExEq2q+H+rhbmhHO730jwqbxaj3zSB4LBQ5bO98hTdGQhFd/aTE/AKiSRltg8jxxm7ynoMdjej+BYxcYnOEER62Qcli1kicN3hSUaodUN1cOEL/NM4UT9sRAARAXwFCYHYrYxMFxxLM79f4qahgO6FZYrvmEmJKiD4bu6MnibiiDaINHsrBBZQ8pohDq5sevdC4kiUuEQazxB9woORvUtEF5Do7VGiG0wz6lrgeORCsZEk6BRWoqNMEBHAi9BwdgF/JSfBLJXobqEo9mQ5LBwm4nGPEfNboo8F0cCbSAWahSJ10M0TFWNYlS3MSF6CALG88U4TCcDM70YJFSRoLIKjKUKZRKkLuoKJ+J8im0i080b2ajkkBHFg1GgkdayM91o2MoWiQCQBiRT3JjKAowyhc7YQXWGG9XHnmG8EK1j6XBAvxmT8GLHvTWQR11WCiaw3C+HJzIKFzgh9cUETdB1hiZskmoGIRcJ65qjTymg9/Ddp1zSRHkaJyiEoCALiL9jujiRzTRBDBDHA1U3gJznfGK0vbTaxr2S8pT7C7LWRJBdgK1mpBPJLoC1XX2jnhSqb82qcc1tQgnxIziDzyjFHR1hnb85Ru0ChvXQ7M9wk561FsbGt6b+783FE7XeCiuBChAaZ/2b2h6CIbHyukZyDqBMjxOEWtACZt7KWVq+ZeaIjWQX3mv0iqChsNJEKLFxrw0R1IFoAUQrcBaFBe7M5z2fU/mUiDKLgFqt5e0+8xAxJpQS5Q/rdk2XJGMn8kzUuiCUOYhGtxQtltfADmImkI/NNxk/afbcd0u8ytzm2EoMiWOiClGIiqoPEHXHRs6+Il6u1YD4v60jylrnOw0Ch/qwec5lXgoU8xroJMoUSOCkQ2wQ7nEgeaj9aJRxrqYLkPcU9bJRrVpBYhJHNrvRZaYnMLUGJEcQSKV+weqXPpa8sHPt5opjIWGxEEBZcdUG/mSLqgwvhzmSNO+abIJVMEida8JkXeWbJvJL5NsUxH+EcESQi2RdkrxXZyY8oKV80RJpTCNYyu9b5rFMIXmdHfc5jIgRbCRkjeIv9gxRIuDGIoDg5NcNNcgzG0TEeDoS2oRAhNKHDQ2TbM5p4cPNw5QVEwObHJu0BlPK9CE8U80g40EnAcG9C1IWS7W9CYUJKniKAzZGW95N3PkAM6XEDiSE6wQ20l/jN/d1tKKpoREJKCqLCgh5Ya61CsAhDCyyzsigfNwuvopEYpvDwQ1SE4KDyABYhcHQQ1y+cwp2qEnQPmqEnHvTSnAUXz3yCxroatHcNKR/5QAKRT2nCCSYyIOGLTP1duPDhr5BfUq8wUQMIW+RIgk/dVluBT956DcY5P6QmxsA6Pozy6xeQf+kSKspuIiFjM3x9SS18z8HmyOOBP9l2wSYuvPAxPvjoJLYdOEYSBIemjcI/D+Y24rp++Ku/Q49pWpHOuM6a8fd//ReoqqyCobsb7iTqiCONsWODfWBZ93wh8EQddaXIv3AWRdevkjp9FLrgSMIR2g+jscEu4nl+TOamStwquozy6mZEJ2Ui0M8DnXzvJ//9v2LJNwRJycnawezZ7knOq+qSK3jtZ39HLNLdZL0MWLkz8fv+7nbSxr6LE2fzsevgMV7WRP63kTSiGb/66V+hdWAKmenE2NwAVNkA8yi9cRGXLlwkm2UDiTBi1JwSOD4lCA5340b+JZQWFrJfxhERG0vcz1pcvXgR165dIsaujaQDqYRvkrFaOVTv6eLP/ClzWdjRLp36AAU3rrBv6zjXfUjeEavymZ+ZRFdrA05+8C5p4pvQ3GUknbc/yR5MOEWM0eo7t1HNcQgOJ3Yw4ZMcF5bPFPSAD2yEZRroasHpd3+BWy1DSEsjFjIvAJJEYDH2NKHw0nnk519EW5cB8SnZKuBaKLTLrnyC1954B1uInaojO6fWsuWQ7+tsxaVP3sK5K0XYtf+wGlN79y0piLLGypv49c/+BnNenFdJiVicm0FLdQXe+8VPiIvvQprtLF56pLbaklw62muKcfH8eZQUXCXD5JzCX1bQm8xK9klDWz1O/vrnaOy3Ij01ibThA9yTLqKgoAhVZRWEIo9RcKECraUlSRu6OaYn3n8d9dyrauvbERXD+SZQoMtzZ4EMZs3VRVwLP8WMexDJoUJIJnUDl8+dRiXHfGLWHfExUWsuS+upgwh5hpY7KMg/h6v5l9HZ2a1w1wO4fzou+gLV1tN4G3//v/4CEwueiiq8s/Ymrl3Ox7WrFzHv4oVIYoHLXNeWOKYUBOtvFeGtn/0EboExiIuLWxk/zgcjKcRLr5zEO2+/R0zeI0S7clPMfZWF5/GrX75GPPDDZISVC6q2kuVp2dPvcH85f+48GqoqSL7E8fPzUzCEjtyMfV049e7PcfF6KbbvOYjWiku4fr2AZDjFKC+6in6LO/eYJCUIO9552E8RvhfI+njz6lnurWd4ZhETfHpezWeBFhTM6GHW7cT776DuDhko2wdIoEHc7aU5YoW/gXKeJzXVDfAhxGxkZCQxqr8cnOANLKuHdYXze2cPPJoeEIrFKW7IH330MfKv5OPihQs4efosSsiwc/rkpyipqISJwnB7QxUu51/FVT5z5dp11JABzTTQjVNnLqJvyEi8xgFC651CL0lUhvp6MTA0TIF6DIU87PPz83GGeVaTHchCzdgMtc9yWxUu9Qvnz+F6QTGq65uVZsDBf/5oWrecC7UN4QnZOPL0s4gmJXd5ZfWK9psHhSuxFjO37MGBffth7CQdeE8vDA2lmEQQjh5/EbqlEdzhhiJaFGXK0lA5EcKHDJ1i+1L4qdM225q3RQsnGjhfMhmOmsljL6Y71jc+fQuePP4cXCb7KazwciFla05LSvswaRXNpGhi7K4JjmwEU9s0LExdswpnVLl/8GCbsi5ix4EjeIpMVhkJG2FzImcN21lw6Swi0vbghVe+Ad+FUR64dUobJOUHhMXh69/6AV7+9g+Ql5uNsPAoCj/uCq+2rLSCOJ++ZHWaZt0ctdX2c54HxegksY7JAGgjnihlsFVpEaPD/SROoaaGLHGqa/m9mYQ8zXduQkfc81FSGc9RG7yR1HanECaLC1745qvITQnFlctXlbZI8pohPnTF1TMY4gF48NizeOyJ/RQUvUhkEoS9h49jz7bNaLtTTAzzGc1zbZ7CznBnNeraR3DsuW9hc0Ysbly6gAkrSTnYASKkNlSWIzhtB1769ncw2VlCcpAatNSUw+bN8fjm9xDiPoa6mjpq5pcZP7V0APeSQc51DxIomIn1LEREq5M7qem38sLx5LGjGGooRnsvsbuJnztA9sSyW02cNFb2+YLSpK5+b12/iwVjsJeWExlTzvV7lqrLEq0SZuJuLxKblxd/Na/4mWjLQFIYweXe6FwTJsrL584hbftRvPDyS2RI7ERze89KtaktHeae6E0hbJSU6DKv+trrUH6nFUe+/m3s256Km0WcMySe0pqmLRyvqnLo4nbgxW9+F67jHWgjEZSNePr2tKT6pbbqDoJCQ2idkD1mCf6h8Tj01NewNTNBXXjFGqc1iUtD1c18QBeLF77xHSQEg0JesVr7kpdoaeUCcLuinJd4b9ioMaWBHr6BkTj45LMkpkpBa22lsgJpLVuelzEdMzNPMhEKDq5o4FcnC9e2eYpWwHETrYfiigBeEqkNtZBJk58JQ9/afWH125//e09zFeqbDTj+0qs4sCsblygMj47Zx09ZoahY6mioQN8gLTLUBguYVcaOI3j5u7+DJ5/5GoJ9XHlZiaUArk08FPSuUUMDCkvrsPOJ53Fg7w7cunEZI5MzalznZqa4fxRhnmPy/De/A8+pdlSU3CRBSQUM42549uVXkRTOM5DWWiutjPd02ec3+jf4Vlsrf4OCnK86e0BrD4hv2CwXbFt7B0kM9EiLi0A1b6qu+miEeS2isZ7sPtQSX7l0DhNzXti1ezfc58w4c+YS3H306CXlcFtbG7o6SL/bM0zWMV/F2GSkmW+ovxMXrhQgOCIOomEsI3+7aI4lLc7bcLu8lEx+RmptDpI18IsJbxSB0t1Lh7SsbDIyRZA0gQDtq8gXXCgA+wWEIjQ0iCZN+o96+/OwInECNbhiJhciAx0JYsZ5URBYPq2bhjvfT9+6h3zxW2ji/mwbPXXB2Lp7H1KoAXYk/6AwRPCWLtqtJVeSOfhrJYtYzoltT8nZQba7bYrkZpWRkg9Q+CeZws4nnkJyQgw1cjSZUSMiLgl+1OSIiVWQQ8S0vN6DQsEr0vVC3rHyUOrqGUJWTjpS0rNIXZpKdrYuNsl+OItrRnBomNLQ9hsMpC/PJWalK7VG5bC4hiA+Ili50jh8Bx19s66fvHAEhsdhz2OHEBbkv8Ykr96nyThr+37SpueSlMI+JvNz0+hprqZgNo7Nm7LY9zS18lRdT9tFIyYmViHzmSEBR0tDHUKj45CSlo7srdshWm+5+Emy8fva2jpSN0fxWQuZ3QTtZJGUqkmK5GCeApKnf5B2rT/zljEb6GpCcHw2ouOSEZ9ELZONbhkWuUyITyAhESmYCFC+N92O9L5upFfuJKvdABKzchGbkIrUtBQKLmaa7bULRe7eOuTsPMBLTaYyyasGL/9HtJKhMclkqktGCMfdx9dfaYHNpgHU1bcgZfMuhFJj5fAvXf3uun7nOs4h09+mnGzFMnrvO54+Adh35BkydNFFS7SOnOsilO8+9LRiBhVSpY0laiQ5pkMjwoKYiZSMTYph1dBruJudh28AcnftV+xdDqFHlACupBb34QUoJCwE5uE+ClETd99Z7y/TJFkRK1taTg5iOH6JvLROkPhH3ItEGBPXg8bKQtI3hyElPlr1r6tYB0gdLiQVNiol/ANIJML+0JrE9aajrZPsh0lc4xmkI97KC02rIoeQvMQFo6fpFowzPkhgvwsrnBtdcGITktR+M8dLkjc1khsoWlXV0y8Qe488TXZH7hXiYrI6cb4lZORhB9nzAqjtVVpxfhZFNtA9+/cjWC/kPBsteQm9pKn2oZUsLTMdm7buxOxoP9187OMnF4qBzgbcqutFcloG/LjHyPrTBQQr0i2aIGCc9cdu0tPf70xY3Yx7fxe3G3Ed9A1PQ1xyGmLjE+HvQmvjhJ3oR3x+ZznmQlQjZEN6HanDDTyfSWkdlbqZ+0wyklKSsTQ9hkm64Wi+ad9boXX+7RSC19lRzsf+6XrAgwdYUmoyD88YHsb+SM/K5E01koKICzWDNOf1GJG7YzsP9jSk0mXBRv+med9QpET60+RbjyqaXqPSchEW4EOTlAsPdjIJ8ZlRajcqK0pgGKJ/En3CHJpQMcVP8HAOprCSRqrSjIy0DTIHra/PRFDp62hCR9cA9u7Zww3QDhgvm4BsGm2kmr19u5w+ZGT38SPf/KY9mDZU4sNf/wIV1GCKALxWiFxfuRIQIX5w3H/XpmXpyp3+l8rfeNUDwsJk6GhARWkh+ofIWsfDRg407Yn+YPT5lH9rkwh39qAJT7q6rPikMYjCW4/nqbmNCNaj9uYVvPXmu7Bx3B4m/Et+YlavoJnvxrUrpFvvp2uMG6gUZP72w08OfnnOkcQ1wNRdiz6LF2Jojh0fNuDc+RvYeWC/OrTEX120uNoTBXz6+on7gWPMHKXay5d+Eb9XR7/QR9fUh9t3mhAlJnp3zglegkRT9L/Ze+/guq8rz/OLnHPOGSBAgDlnUhIl2bLacmi37O52u93jru111UztVM3OTk1tTe0f+8/Mdu9sJ3e3223LtqwcKYkUSTHnDBAgcs4557Cf83t8JCVTIkCAstSNK4EAHt773XvPvffcE77nHHfw0GeNwZTIiuvn9BGKYnHZLay+VOLi+UZXL2BBVklqFkul7TUTHAx/brCj0YEuSufibblyEwsVlnKUz6tXr4LPZm86NHeP+rN6v/s3EyDNAu+PW9YueC8EQ29PsNGOFWxOgaHRys1doZsfvaKf/M+/VElVIzjOCUf5c8M+fKjmZ3vtYZQPw9I7875nLzujc6853w3+01hdLo+4IhVkxKr84lFNegYgiMY7Y7cqjg9jlTQpzs7ZJ7Hz7vW2wClnr5vlzSErO4Of7TWDaS2mWVn2OdbbeKWtue13p0Lb7Xm76HIXk27dZ61YpawYH/3L//d/68033lX/IFX2HmIYMxgTLI7BDaOwapiGvbX1cyBqDaU6faVecQlJ8mScE+zraaztPS11ukzJ4UtXriOc+rLmQMMWRAR7N0oVuFaDPjjzprqlMx6bN3uoB/jc+8CN1iN0Gg8yRdAwuiN9Hbp87pSuXS9mrHZXPITXAWIZnQ2qZ+t4b3OvufFV2493G2fC9ij7ZHHNztSsE2vgxV73ZN4A/WDTKI7M3aBgHwE1yVq1TtHAsEzxNdihGQDGhoD/NdQqc+0ORYWCI17g3rO5GU/044wbjtto4OPt4eB87W/+KAa5q7aqu/Qj/exv/0oXrpU6d+4keO0AIHWmDHijiMBhoPvD3CkPRzk3p324Ty9/apkCnwMF7N6yA2Ks0PXd3SngfcpAJiREquJmmUDFOhhev4hYRVDycsPmjXqJMtsjMz76Ou4Zd0CNafxBlAe14Lh9uPWDfbDORYRjeXMxLG/KyYaiobf2d2BJrld1VQ0WlY9DBdwjWNx3C56YoWb7RV0rrlD22r1KT4xxmLSV1DRGYqVz82FK+as26O0X/4mxVCn36Sf17R/8ByzWY+Cv3tWQRzS4td+Oup7X2ByLokvwNEZlAVtWotfDN8ixhjlRuzBIY5L290mElrS8NYpNzlZMwJTOnDqvNIREw0outNnzTKix705kPkKYBVMYAwwF4+zuk3fdfp8HFoY8LjOsBMAkil95myAnArXgYrZHPq3ZnvHF8pCQnCo80lgaKR3qSdnkwTH5YvkwjG5YVAwlVSnZy1gsCMkCdU4cOqiVW/crFmtYV10bVvlIlZ7/SDfLqhXc76OCdVsUSZnjhTZnvkZPZ178y7wnEcIt8Cw8IsK5tB3a2N953yRQAgsgaceCU9/XhhKCsNbeq9jYGC6qT1iZPjEYCyyKjAU24heqUOYYjiJoZZn7KdXe19aowLBY9pGrrLyVkLZy8KnZBUoKo0z0UDdWxF7NeOZqz5PPakVeto6//5ZuVtQqPnIVfX/8gv9E1x/71Uq9WwnV9tI6Lt3VTtDfCAJ1KDATKwFupXxz1uzQj3LWYowa1cv//NcouqmaHWhRO7j8yaIMJxjT0ysUa+pvey0+1tn9fnH2mgn6tt9cX5NYyG2/O2WTx/sQfo6pvKZP3/72t+TnBXZ7gKBQhIZLZ2rVhkX6xrUrWPYe/xi28n5d3e81Zz3dY7D+OXcjBCWZAGzldJ1xOTvCxmZCHNyOsfILr7rGawFWC22mbHhOjwJ1IL4Cq5zBLcIjEgmG7cW7RgpPBDXX2KwP6w6rYFSS9v/Bj7QH2lRcOqrLtcNYCT89FuLTxuSPwWKOfd0J/GwqLUY9QNeCM3KBCHD2GMcg8IuIqHBVllyRYVS7J4PU1rlb0QnZQGZStQpPxd//7T9q+Dl4tFMe/dN6+uTrdmF4ibAOLKDDQIkIIsaaHRadiAJp5bF9HGEwAK9GxaWTKgcK5xU6otrG7cpPj6bvbyo/Nx0M/EnVt3SidLvKWn+yl8/8HTreWVNnvRHKCTy0EuFh8DYTdp19yEPurLMjn7MOtuLGl/nP9sHCmif700ddBJP29eP9aavHgxjuCLQj8LcpcNpwOHUAeWlvrAHu1qayW5VKiF6nxio8q6092vPNZxfcq43RhPiwiGh1X6l1gqc9ofUAcLeIYD/n9wA/H8VnrNSf/of/EyVoVAdff0HjPlHw0AmVNNZh+c93FHDCw2/fJwud+8Io5X6313+juX9Z/r40FFgOjFs8HV3ZIUbBTQ6pEgtpfkGBwgJ91NDUrtUbNwKgInIfQ1zBykKlxISrqqoCvGyDRqc8tfPxfcpKBlhPxH9Hexsu3Fjt2bmNg+Wj5poa+YbHqrCoyHG7NDQ0qQMmPevlp4yUBIJzapW7frMyEaw7W5tUW1dPsN20/HAbFq4qxIX96YVaFhwYZwLOSI/eeekF+UWkknkiwLFWBAf4wiB+Ja+gSI12VquqtkWj/V2qY6wZ+WsU7jtDoEeT+mDsDe0D2rh9t6IeIjDOLoTetibdJACtrLpRaekZsEcyaBAI1I9gHewzQ/BanUqLL6l/wlOJCfFgvm7q5q1qMHRDKse1Hp+3UQUEUPjD4BbUsD52EhhXdasEJlyu2MQ0hROYZhbesoY+5WQkqa6iVOUE5nUPzwAJiVIAgknJjVKEoU7VlN9USPJKbVpX6CgLD2KXFnEcFh7lcncjRE0Nd+pWNZfzcA+BWNVaCw2H6q7qZsOAEuNjuCz7dfz4OT319W8pKhyYCgJwNpZKc63OjrYrJmON1qwuXLhAxIU41N+L4gMdb1wmWMcC0wLYzq1674OPVFiYr67mRlVi/S+rrFF8cppi4hKVvaJAmZmZXCjgt2dCtHvXFuAzwQ8M0jIhKwjhMzI6lss31Ck3X1Za7lzQJZcvKW31LsX6gQU+f0FxuCO9gQaVVjXJa2aYs9aslWs2q63ysrr7RtTRWKsmggjXbtmtuCiC+RZgKTKLmB+BfNfOn3bOZX3lLQUmrAT3mag3f/0C65+qoZ4OtTS3se4lah/10+7H9hAdLoTPEnnPofRgGVyxYTcQGfCKC+jb9qW5vzub61WKwFXX2qvU1DTwH4M6feA3mgtLV3/jdR0/cUUpWQT9YW33gB+k5q5UXj4Qgvg4dba1aO8z31ZsdPhvu7cftPHZ66211eyz6w4eNxFlLAJX8In3XlPPGPhL+FdNWbHKii9oTEHAcCIcnGo9e/xWyUX1j3sBl4pRRESkYxl+0F6/OxzeSd8D7TVqaCP7A3usuW3AMQ7UXz6kOhS5CMrS9qIM3Sy5rObuEYLDUjQDFrq+poHsJR0qLb2pVdseUxY0t4j9hTSzBPZ3NaM01kqTA8DXarRu606NdNbo9MVybcarYmcqPT1Nvh4TuNFzVZgdg2J91slO0VJLLIZHsHbs2Op44uY/b0Zp8uP0sEpv1ROsNQqM7rKKdjwp/9FmXSmuUlrOSiAihZznFfKa6FFwXI4KV+aoBKG4f2BErXWV6rX4gy1bHb60kHmbNjHGvVVTWgzvvKgpn3BFhIdypkb0+kuvasXKAhTvLlWzvjehb3RiOlC9YDwRxLdUlKmk+JoiE9IVFhoCJOVu1pr5jYFKuvDJSp47M+ep8utXFZa+XplxYG0/+kDBCSu0cvVqZecVYOjx5lyP6YlnnnXgR1dPHdZ0UKI2bdrgwEPm19/dd5mxwQwMJeeP4wHg2Sg2k77x2roxX++/+M/yDIqSF0HdteytjqYa1bWPavcT+5WUEIMCet4R3iuAY6ez1Y0AAEAASURBVMXnblIRaxGAYceqxi30rN8d0fx+WhaC50enBb1rWQheELnu+2aXEDyOO8dXsbjLkhJcmNn4xEQsv3FYBkJwUycjHEVjMUpRakqi4nlf4arVyk1PdRi2WfRi4xKUnZ2lRDIumOUqOCwCrFIKlo0ooBNgALlY0jOziYTNcSJoY8G7JicnEQwVp8yMdOf76jVrlcV7E+KiPxMWsVAh2JilBUlZxL03bqNpLJwW9JOQmIJ7bkJRcfFY5sIJ8mt2sHW5a7YqLwdBxWNWDVyqY9MeWrVxm1ISE+SFkLHQFGnmkmypr1JrzzBzi3Xc9IZNtkIvoWClg31mVV9dpXEFokD4kiIuVLEIBFMEvLR39igWrX7n9i0IcS4X930X8lNfnAMjWqWWtk6emeiUyE5E4LOLzh/LWEJsuMq5DHCgY70MdVybScnJaiW4qZssIJFJ2dq2dSuYZEsh9uDr0YQwc0fbl7k/4xOTNTmMIjUyqbx1O1SQl4VxGax1WIwi8QqwMPIOjVF+DkIR1jLbS8GhYU4mDj+smgmpmeAr4x4ohP729F2BLxVlZQqMiAOUYXi8CEdAtfziaQgbLWRw6OwZYB8kOXRJy8lHMIokIA9hHDxdaFSC0lMRSuYRrW+0MWHE5mz7PygsCguZJ8php2LSC7V92wb5eMzIwztAMfFJDi52CivhAFkECsCL59p+85pRW1OjJue8tXrLHq3gNR+eNw+y35m+jcEXRTIyxE9dXeDzsfZt27bZwQUabjSBtZ2ZxBqHkmpW6937n1ICey00nDPHDuwCupSzdjdKAjhGrMYLbTOGq66uUM/IDFknwpmvr8M7bB7hCByzo1hGec1wyRMECBoePiUlGcuWCaSBeI5ClI1AbDjt+ey3j40Pxae+skQ9BErFc1YNApKMEG48zjwQkVjnb5GJhFQdwL3ICIAnKiE2WpUop1NeQY6yM4tQYZ8xF/WDd/vd3s3tnpSSqmEUx5FJ+MWmHUoD3jGNhTsIy6hhr5vrqjWAkhsJ/taDvqPY//2dzezBfqUVrFdRQR6ZCsxdffe58/nJeHcYngXPKTL1YFUv2vI4PDeF8SOh4qbPys52zlMwylxQcCjxGcko2rGaGR8EC94qb9znO/Y9odioSEfRnU+f7vfYGkVEx8trdhwL9KDSVm7Wpg2rQUmMyxtYVSxny+4Aqz5r1vC45HQyEsTJA+9aG5jpWTxhG7btJjNFIvt/4RZ44+u3iq/LMyDSMRD4gPGORZEZBeuaitDfT/CrBTlHo+AaVCEOnj81ghBcU42HMgHr8IzjwTHet9BsJAaZi8JY09bcrMCoNO3Zs40zD6fhDEZhbIjlLgyBl/kjYEeAgc9Gsbc7ZQi4XdaKQsXHRi1oj92hOfzFh1icOBTFAbI5eQdFa9vOXYqOCCYWY1wxCYnyx+taU1mpCXjJlr2PsxeTUdKjFOo3p86uHiXhCdqwfrVCiTX5vFKkeeD+MJ1puS0hBf72SBML6KHvbk1wNJklfPS/mUcZ5tLytJpL6cvS2utGsAAAtUhEiDLA6efU7G6ankBQud6uzJ0pXOAP4S7+nMa63M0yBZYpsEyBZQosU+CzKGCOHssRHBti8REL1L4+68H3+dvC/Bv3ecDyS/96KODChoFE+gLoRV8m4de9A3xwoY4AOp1Do56b/fyOllkKvMHRzgDb8AR35mGKw6PlG+4pL39fpsAyBZYpsEyBZQosMQVcMUBL/ND7Pu7zu6nv2/3yi18kCljE+QgBCw8XEbv0M/GnatMnI6qXvpele2I7wTVN5b1KRgi1YJbPq3nirrMo6IaybiJ7IxUYPAV28PPqfbmfZQosU2CZAssUWKbA0lHA4Czes5bZwmJNHq1FZ1kIXrp1+1I/yay/Zn21NEaGVftdN8MwhoOHNbzWl6Vl5HuD1yTvoqWkAdP1eTVLo2QptbY/lwrGENwrFXiAeC23ZQosU2CZAssUWKbAl44CTizDnGW+efRo3WUh+Eu3PR79gJcSDuHk9SQNGKkLnWAad6Sn9WH5Ki2till77xd04RwEwPZflhYZT/CI3wT5Jk2hIDvjpCuXq83PclVaAIRVV7O5uwO15hPcNJ/5G60CI6zksQvOYn046bVQaHwsFzB/mbH+Ccpx5yxdaMDFfMZh/VveR6suZxq85cR18j7yuylZNs67eVGXUMNnvubBsFRj/Og0Jxcn+4t8ak4lLOvb9dpnpxVzfXph/1oxDqOtq6oec8QU72PR9AzGlEpW3Alks33wKJprbV39mEJkngFLvzd1W6G1nKSWcu9RNFP4bK/bHG3Ott9t71lZWtsGrpyoCyuzPN9xWt9Gd9tbzr6Gvrb3LZ+vrYV73rb2j6aRVpDiD9asf3cv1r+z320twDRaoRHHw8b4nPy/SzAYZ56caaO7nWXjtfdWGruz153XgUphWLA0kUuzB13nbQbaW9Coh4drn9ta2Ll35ohy7vA82//k+jVetzR9u3iZnXMXH3Xl8zUa04FjEDBM6QT3i+1DYwfWr6Xps+DQxW4Fo7vtbSve40pRyNxv5+1281br13KP801enAmj+1LsQVtjSyFpX06ucSZj+8zOge0Db+Y3BS+yvWb0seaDIcm5gxYxcZvPBCnz7tAc/uLDnGy/2Tlz5ZtmjvRndLcxGaHt9YVmFXEG/Tn+sywEf47E/vJ0ZYKUa7R2cO3QW7v3Z/fvzh/4++233zno7s9McyDGqNQ1NDFLcm4suyYY8G67tLva2xVCdoYgkms/TASu0/cX7B+btwkfkyQN7+7uchKFW4WcAKK+p6wKF0U4jEFZyq5AMlxYFPhSNDe93c+yy2eUtFA95AeNiSZCG5oPkR92eISocCKiQ4k6tqpM7kvb/bnFfTfBm2T3zHt0zDJ7+Lgq25F9YIQywxMISnZpWaU6y9axVAqAjdkuhzFLg0XmCFJsOkzY5mlV+GbJszswMETaK/JPhoY62SaWWgEYpRLdIFXZxkhcbGthc4wkLdIc6zBAmV4rZ2Jpriz6fyH5deezHnbhDFP+dGiY8qz0ExgU7PQ9THWuQfJNU2vQiYIPJ/p/qedt+8zOdzf5hOfox7IpWNXDWQQA2/+WuD+QyH/bbw+V3/ezCACdx4zuVLazrCpBVPiyVFNWEMD2+hilV20P2Lx9F12E4LcHYutsgk4fOZdNIIokU43F8NheNNrbXgggH3mwvzd5mXudM+Dl5++k+/NDIF2MUGR9W45jK24y6+XvlLe2Ij/d3T139r9lMzHeOk0qxMGhUap0BZJhJJTXAhZ57k3gnWKOww4/iSPq38oED5IDd2hoxBFEI6PI6kGlR1sfq1ZmlZJjbP87ELfFKGMuj+UQBV2sGIYvaTCDyFxjvw/St/Gc4GCyTZDFo6ujHf6LMmLnkfWPpvy5ZfewIhIP3W6veTfP9iMLQyB7fY6MIr09PZqE8VgauyCyLsywFj3d3ZpEWA1mXxrdF5xG8j6DtP02ZHQny0QiWZLsPI9z/kYJJCftBRXofNlrVFyDFjZvyzccHRsPH6TCKILrQzVHiZpQG0WGrKy1D7zNaBxGasee7k5ytU9TxCmYcxaGYCzo3uEIwl4oHZb1w4pyLGavP9SYF/ChZSF4AcT6t/JW0+6nudysbK9ZMabY5CjyTqooY7yW4scsLD6m2fO6CbQm4DhpkNA6PchNOW6WIS5nqx9/6cQRXe2QfvSHzzk5F42Bjo0N6pd//zda85Xf187NaxT8iKxUv4s1GydHZMX183rxjQ9gVuPkX82lHOZWDdZd08XSWi7oAcoCB2v1zqf157+//5EMcWigVycPvaVDl5v047/4U412N+mdtw+ob3RSwREJ+oPvfJv8vpnO+i7VAKwAwCRpfl746d+pvq1XoRHRKti4U+mBQzp25qq6evrYV3OKzVmn//ij7y6pEDzLRdRQVawXfv0GBTHIjcolkF24Xt989kkdf+clVVJVcJKLeN3mnfr6159x8rQu4ir8LZK1N97SG28dVHNHL+ntRhWWlKvn9m9XA6mxzlwu5bx4a8fT39DerVRqIu/wkjUThkjH9O6rv1JL75hTPTA0Jll/9AfP6v1XX9QNciBPe/gqZ+V6/fF3v0GeYIonLEYI+MTAB/u6de7EYX1w/JKjeKzd/ph2blqtweZbevHNg84FmZC+Qk999avaWJj9iU8v5lcueNLYnfnooI6fvqCRKS77xCz96R99S5U3LugohQ4Gx0nUH5emH3z/e5QkjsFKtnQrboKuCSTVt4pZ9wOKSMnXD/7oeXKbUiKaYjOnjxzQ6auVevb5HygzfFavvvq6yqoaFEZKrGe+8bw25Kc7xWgelgIm6Lc11+vVX78gj9gCfetrT6ivqVS/efWAU9DGqrzlU8zlqd2bdeitV9XaOySfwAg99uTT2rdjk5N+6mH7dkrvNtXro8OHVEJO7//jv/wXp6jJwfc/UGVDB/PyVM663dpWlKbii6f1wZHT8kT4377/63ps+/pF7X/r2/bcwXdfU23XlL763Lepbuenl3/xM1U0tGH2DCSP/FY9taNIL/zzP6l7YFgj8GBviir92b//31VIJcAHFZj5LLqYx6e3o1F/91d/pYQ1T+qre9dTSKdEL75ygLRf0pptj2vXxkLyTpfppbcPO3dlYtZKPc3+X5ef8VmPntffulobdODtt1Qz4K//+p/+XB4Uvyi+fE4fHjmhwl2/pyc2ZenQO6/reimpLTFA9TH/r3//x3p659qHFoJN0bXy6v/vf/9LzRD8HUFqvV1PPqUVUR762S9eVkdvPzm1i/TVZ55RNpUG/5FqcN0k8Q+LitMmSn8/u2cTFuGlO3vzItQC3rQsBC+AWJ/1Vitd2z00pZb+cXWS99XyOd5oGiLFh69So/wXxXQ+q99H8be+7jZdvXxFMdlrlJMYSgnLK5r2DtKawnRdPHdOPSQTj4CZ55NfMCkuQiVXLquuqUX+obHKsZy8kd569+AJp/a4P8xvimprk5OelK7tVzMJ0G+WVSoYK5nl/pzAncI9/q+q2QXZjXWocNNurUyL1LGTZ0nQ36c/ePb3tXXfsK5dOKVbDT3au4W8lY+gWRGMDi7IizcqsBB4OhXHGupqNapQfe8PH6fy3IsURKijYECywoMWXunt04Y8h/IzMtDj5JhduX6r1lH4ITktXaH+XspbtZn8kOX68MOj2rVz24Lr0n9an+7XPakCmLFinX7871OZe7UOHzuv/MJCJ9fxtHegvvP9H6rm6gnVtdQ7OZcjqAi4SHOYu2vne1JmkX7w79KxlrTowFtvKGsT5a+nh9TU1qcdT35NXt2VunLhgvKzMxYlBHysU+cXrO8Ig81tHcol3/HMSC8lliux0FDhjOIEq7fvUYiGdfzMBdXu3aO8ZKsuiLlmidogRVzKblVpBXs91X9YF26Wkg81Qt7D/Vq3/QmtSA7WkRPnVV7bvKRCsPGMyfEhlZZVKTpthZ4uTNPLL75KueX1FFgpl39Uqp7eVoSQ+LLKKDYThRcqBIvhUjUTxrqbqvTh4eNqJWd2SMKU82g7+43wuOvFVs7cy7GcmVIUhOL5+OM5FL+4pg7eP7cibVFDsbK/7yEMtXX3KyYSCAIGi9yizfpxQhaVwCp18KPzWkl5+YnBDtV3jOo7f/y8rnx0SGU3S7RuzSrFhht06iEahB/ljJ89eUI3KW09OWcV5yz9LvnOhydUsHqd5vrq1EqVv65oD+6FNq3d8xUlePKZ69e0piBnUft/EiPM8UPvqrSiTp4hCY4iMoTl82Zli/Z/4zn1N5Tr5rVL2kL5+T/58x+rv7tV169eVut4kHLY+wYXeOjGRAcodHPmo8Nq7xtSNMr2IEUvSqlWmly0VetT/XXscqVq4yM1A//fvOcpZcX66sMTF1Xd0LpoIdgqWt4qua5S9rNHSIpD95qbl3Ty5BkqG05pCg+jF/mNn/nm89qys4282KU6crlemwqzHKv8w87bBP+B3g5NeofqiX27lJ6ZRWGnIJVdOS42vr61Z5eKb5Tqys1Kxa2JxevrQY7lXVq5Ik8paWkY0764ArDRZBE74mFJ+q/zcybHtQ1M6PWLHarrGlM1jOedq51q6LYyhV+uNsphKyu+gVWrz3EtVpXfUgXVqxoqbnCZXoWxz3DAKjnYLVSRqtCBD44g+IxT9eia3jv4Efl9u3XhwmV1QI9op7SrHQIP9bY36vSp0xqkqps/lcmGwY7+a2zmLlqDxfExqnr54hL05feUZBLTh5MMH0tRa0cPF9ZaJcdFLvn07RLu6WrX9WtXlZaZ6bj+DA9nmTY8ZyfU2NiiYQc20OtY75dyAGYJNiv3HLCD1oYaXUE5quUSDMAlFozbcGSoXxFpRdpQlIMgtsAKcw8YqLmjAwNJSM9+62xpohBEgdauKlAULtCvPvt1paKsOQUvcE87bvkl5suBQF5CrLTr5JDmghO0Y9Mqp8CFD/nCOxCMe4Fj9FOe2UojL3nz8lVyYhyFTcpVVdek+LQM3MEBQC981Qckoa2zG5fpEJb4QQe/t5T9+4IHDaASXD/VxTq7KT7C+g8MT3IJ7tXeHRsd3KCff6DiKT29lM2Wz4EUBfpR7npQTS3twDKG1N414GDgDQLQRPU5e83Om7nFl7KZe9ebAgibtu9QSryruIB5xIb7OnX50hXKUeMWv11YIzI+TU8+sU8+c9wFXgFUAgtatOLvC00L121WQXYqVjbDuVIIBZd0NHRubaxXUt5arVqZy54MdgoUtHDu+4HlDPT3a9RqjT9sg/AGOcgtXK11q/LhL67bzcM3gKqVgVSFu6EmvCFxCQkaNsgCwU1ZmRkUWMlwICJWFn0xzRNhPyUrnypkaxyvBhN3znUQJvgO3PVdwHJsrw+NTkGLaM2iKA0So/HEY7uciqHumJSHGcMEFv72ZqpcdowpIznOwd0b3GMIiFlKaroy0jMQqNgDeCC27MIivHW9A33yDwim4MfCy07fHaPBE2fU0lSresoa52QhWN7+Y1BIlDZs2qSoUFcBGaOPlV63EsWVGDq27XkMpSOYc/jwop7t635gNhZbUXqzWJev3oCn9Dhwj8i4JCWnpFNBMkSNTa0Iy71WP1l1FKa5cuUqRoBuxv7FloAenjJ3V2j5Jyhgrjaz+JoFeAqX7zggKKsAlRkbsDgM0u+AuoYxNMiCBdXYdws2skvEmN8sVc26uOxCI8B3UV60obpKHf24nMAlWQhCd0cz7qcJLltPykNSdjQ3644VvLOtQRPkz92waaO2btukSDBF7sP8O5jmI+vSAjBCQiOoSIar+Ow5hcenay3uT8MKV5ff0PBsoDKzMmHiSysI2oQMi1YOo2rqmVBGaiIARYJluP+TEYziIwMoG1vm7M9HwZiM1U0CnbGqc5kZ6U5luUNHzzjW/u72BtU2tlOGdzXlr/2Aziz9ys/OgoMeQgG7XqG8FblOpSlfLufoiBCqb11Xc8+4Vq3doIgQ/0ey7waoynX16jWl5RUpEkEnLildednp6mqsxlroLvyytBeCPc05k51dYBRDFREWpJ7ONk1SaWzj2kIN91CGGCuUq9el7ZuuFUJFt3VrV2usp1V1rK9Zo1z7P0zjA506c+6CYlNzVJSbam9fumbCjz+QIkqZ+8yNYRGudrDPXlQ8K1iZr2BfLuzSSkrH3o1pWLrOXQJ4VEKa1q9a6eCQGY5jlay6eUUN/XOKQxnz4OyNYQU2TLYfSmhUdAz4YKm2odmBjixmPKbcrV27ln0WeMe66cQBDHTpUnG1U347hlLj0QmpeB8SgW2UOcLa4veBBzjnCJ5fqGTKi9tBspM8Be6+t39AYZFU/6LaV0tLq3NvmPxjtLF/rO/FykO+fn5au2kbsRRRjoHBIHhB4XEI5Llqb6hVGwqPqx/uMGIwrt24SeWyCGWmgFteDMH5rFlDSzAOxaRkwcN8gCGNO9mUDCd7F/MK/phKeYYDHult0zmMQSnZ+axB8kP3bsaFKUpZnz15XL7QPgZ+ZtbZMTysxmtyszMdXLS7A7sDmhrq8ErPaMOaAgwgi/P2Ga54csbDEfSz0lPUQknp4+dvgMm2eVu0CY31tWC9cfLUx4MRz6Iq3hBW+A+PX3CCwd1j+yJ+X4ZDLNGqmPAbFgDuLy9CXcAiptgQq1KClYZg/Cgu/CUa9n0fYwfa/hslmGmcr0kgC95w7zSsC89/O1iN9dXUX7+i8qoa7VmTIf/gMBWtWku5RAKwUKtCvMcBz/vhgrFoXIcDckYIm0FDhA0iDBLdiivJfXjuO4gv8YvGoPooO/rrX/5CyYW7tGXTWkfwM436VkkxdeHXKx5aPYo2gRWkuqZOTU1N6gG7NoS7+gSYyY1r8rVi1TpKTSfp7V//jNKxEYvCJN5/7AgmfsFaWbRKSVyQHbUlOnCuEWsQZWOrKpwyz9lpSff/6BK8Oo2rtBOBc1jBWCbCsYABwSFA6dLJgzp6pUFPgGMrXJG++Jv4vmOdU1dbC1awPj29L9fBAE9xjqISU/XEU2ka76jS8ZttTgne+378IV+0QMSxoT41tPXrG09slP9kr1refVctjMM/Ila7H89zXUaHj2GZDnMsUw/Z1f0/xhz9w6O067H98pvq07ELNymFHKie9ia98It/UfbG/dpMudoQFJ8lb0hUfggFG7bsQgjw0W9+/jMszlhgvca0ZsNWRQC5euUXP0UgjVzywDiHRzoW2NtCHpOzSPkb165hFR9Ta90A/HNcx44cltfQCtW0DWtVQZZyUmN1vAqc9szORZHD+r+TaeG2dDc1Oa6OhiqNeocrIZJALAKhRuG5SZl52rQ7Q+ePvKthrxAnOHMxnVu/c/Rvze4Ja4ZVnZj10cZNWxU+2aKffXBD61JX8pdpdXR0ch568BgELFogs3m7sgm5e+Y7r0Ui7D8FHKT+1nXc8lWOtX0IpbS9b1TZa5IV4r94g0ML914ZHtGxmTr1Y+zxbp9ShN9qJ+iuqxNPCOW1zbluwXddrfX65S9fUMHWr2jjukL6f3gojmV+6IeXl9V1YJRqQeEYV9/QpE5fLNb+nRtv7wM3PaTxEcpOYxUPjs9UbChGuMUaHBB0Q8H3btgYp/S4UMfC3zI4qpC0EDWwtj090RrGwxUNVtifYMHVa9Y63pFKSiFfqhmQ3fR219/epvz0xWrLQvASrocFka1LC9X5agKfWPGdeSYUflGX/tMnblbM+Lgo3bp6RlPtEeq02usxnmqrq9LBwx8pBi08GME3IjlLKwqLdPF6mW6V3VQ91o6Y5DRtzI6G0QY46ZIsHZZF5poymp6zUg1NXTr24UHdDPZCKMKCDqO+zU8/fUBfsr+MgH0+A/6uoWNI4wIW0lynlQSpPL4pFxz0uFauhj6LYIqfRQ6LWH7yq7+nTbg9LZjh9UOXtH7tKvlO9+vSmRM6S/LxGb8Y8NyZWKUenjHfbwx2GXl7zena+ZM6g0XALoTtex7HY+BB9oAhIojDnIji+312KV6zVGSdHV2KiY8nQ4G/E7Xd19WsQ0fPaswzSMcPv6+a6hw99fRXlBhtEctL0evtZ+CuHDSoAxbY2OhQR9gkKZ7qCJy6Dl5ReFBW7XjSZT1bwm7NEhYYGq2VOcm6fPYUFCcjAXjYjMQYnbx8UOUNli0DL1XBRmXGAwnxXlrnn9n3TPE4fKZEvvC/5Px1SokJ1qkjH2B5xwpKkFpbQ7XWbNqh/TvWLeHMeRSXc19bvU5dLEEoww2cXqT8jCTVFZ/WmVMXoL63/OJyVJiVgnv4EV11bCKDhHii8AcAx3n82e9oM5H79RXFugImv2jzZqWCi7548R29DZzMxrxtz1dRQBd/9kwY9SHmwnfOlf5umj3W0dGt+MQkhE2ez9hmUAwrblzSeSyS5hHavq9oaeIAeLalXrSsN3aOEtNyFXytXOdPnWA8I1qxIl9ZBavU39uFBfMQVeTntGLdvkXCAu5uH1dgtq9zf5i3q7GyWKfPXnQCb7OJP0iMDFYHkD0LiIuLi16Ss55ZsFbfjUohI8aIzh59V1NhOVq7YYMGGgP19uEzain3UlzGagRPX3DL7xOMOCaPa2fVXFcBPGi39m5edXcCC/jJjEdhsWn6/ve/j1FqUFVlxbpQ0a3VBdkYmnw0xN8tJZ1lXjIebLCN4ZEJpafnOHLIArq671sNbjM5OqBjB086GYW8/MO09/F9Sg0a05VfvaH3PqhXUGic9u/Nl+dMt86fPKKziLyeZC3ZTmCcLzxqKVntfQe5iBc9cIs6BrlFPGP5o/dQwFwEx2714hqY064VYECpf/1laLYNrFBGP8LTyDA4KvCLxQD+g4E9zBJ97hccqZzMZNWCO+zqHiCwLUYZaQRWkZKorake4bZF3gEhysiwQCg0wGuVyi3IVzQ4MdOgO4Y9uKhT0SJ7VVldi0stUtPDPYrLKlAqeMZPYpaMwUaAbfLDovxlaQYj6QUTZZjcMiy+bdDJlCBvX38lpGaqID1O589fUCrKQAKM+ZNzXop5GibYySOJNXoYK/C1sgatMSHYc0atBPLUtwwpLZuAhYRoJ5XVUjIn69tchC2Ndaqpb1FQZILywAKGk7anFHrMEKCWn58nv4dN1fMAAlnfTShq3QQDrszLQtHwdiySF68gJBkj5oIIxWpZuGqVwoHiLGlj7g21VViCCQhbv14BYMGnidzu7mrDVV/J+UFQzTeMZiCC6NLyBHODd3e0qb6uTqMz3srIzFBifKxMAaisrtGsZ7CycZkaLneplXLLkDCMJbq4pERTcwEqKFghP/ZadcUttYNBNqudN4Jacnq2VoJfXdo2p76eTtXVVpIFYFbZubl4IKKwhA2oAZdtW8+kMnPyUDxI14VQuJR73T0Pg6LcLLmhWW88IMzdUoUZL+3tBB7S0KrkrDxFg9fsaG5QdX2zQmIT4aMZCiVN2WJT5VmmnoaqMg1M+yk3JxO6W1BelfqmfNn/wK2YswXltREoWlnXrtjEDKWnJMCzQxYtFM4BPWprblQVGRk2bdmK8DOhXvheFd5B+YUqLy+XOVJGfrBXtwiWnMZDVAg8LgyMsu8SBGaapbWxvU+pGTnAm/zU2VqHZ7JBAQRnZ2emKioiTP1446qau5Wekel4htxr9rDfDc5mOXEtR3ANyu20XzRu/wQUXBSNmzfVT/qZ/IKV8iMlZHUF9yQwQTPyGP9PzczVCu7Ph23GW5085EAdOlqbVNc+rM2b1uDt8obGfaqqrFBgTJqywCpPjvZz7usVHJ2k7NT4h+3yzudcaRCHgfLd4kwNKQWapyTGOljzuqpy1qFbiZzv1MR47pk5Zw/WN3cqIj7FWYsweJ7x3oU0e38AhjQrmGU85FG2BQnBc2wCS3tlQSgeiwBaP8oJfRGe3TfiihQOBze0wLX/nQ3/XiHY3Hom0E2RYsUSrDtrjgXDDrS59J08t+wBS/tkm9WYg1Nl7vZ7bLtPYpVzJWa3vyOYcTHY+3mwE1hnydNNg7eE7mbN+hideK8Pr1veQX/yXH5ZmsFGeggKHBoedjBbpgjZf4absoNswo9TIARs9aMqXOBDUJon/Rn4btaEUvKnesMozSHhrCm/O6ntsCItjC3NfxUsct4uC7N6ufNC3ykowNw/ttbzf+wD32kXhe1Fs3wavW3OFsQ5Sbo+d7O9ZvRYrADift7d75Y71VW0wQdMuHuOztlgTEYLW/+FXgZ3n/+An1hvp1ACb/Oy/cXkLZjG1p/OHaude0wPeNKC/2z8wRL0cyk4Z56dhgJwew9Y7+79D92XujlKH3R38pdiDbM1d14zngTf8WUtllrw/9gcjO7sd2vm8XKfKeOThqW0/WZn3c6EnT9nHywRHYxn23MNmmBpvwxydmf/s9dcqfB4zc6A8QF4g52LpdkH1rfReMaxhNszrW+7G5gldLdzboUc+N1ex9Rmho2lSs/nzJt+XHvLCqS49rr97rqXXKk7WQL6NP67dB4Qo7sVxzAvp+vucq2DzdG5426vi8MD3WNkPexOW3SzZ0NPZ29jBb5LY9fesnk6fNAmzm60O3spmnuv2TmzPeR+rkH/7DWHr97uy/2arYVTMOghBmDz+kIKwZOk/ZjE0uWDJumJpWOJTtNDkGj5I0tOAQ6XWYIHSHj+uy6bbBeJF+50S8gdAsD+y7LPOkgd1NzRAhaQCOiluWkWvMxRASgOBGY8MmFrwSNa/sAyBR5MAbtkrS3v2wfTavkdyxT4104BtxAcHY3HFOXpUbYFqSZ9pLxo/M3LCluZo+khUmE4Ot+jHN7ysz9PCpjF1rJBuC+kz7Pve/vyCSXPYv+Yukn9lPWf/+OdIIx73/NF+9loduT6aR29eZagyOlHYGmc34zXhWYr2jcUbKjbJjW/zy2/a5kCv0sKmIfELr5HfeH9Lue43PcyBZYpMD8KGN49KipK27Zte+Q8YUFCsC8YzeD0aMVkNZH2qhb801034/ymtvyuLzIFnBhODDIum8zvcKQ+ieqqiSWoLMGBFlj5xy96M9r1kEh9R/4GPb5qO+nPlhhzOk8C+Hmay3FZBJ4nuZbf9gWhwMGDB5WSkqKV4EaX2zIFlinwb5sCBu0qLi7+XIiwICHYO4Sky8HeJPy/II3VIy25sFCfy0iXO/m3Q4GZWgVHbacM5brbWOMvvlXTLMHT4N8CCYKIwZIdRDL7z6sZ7s5wYlbm2rCgS+VSduELDVOIiA/e1jBthnOzvJXI2U7eaMP4ffFX5/4rMWvWR8NGG1aP9bOYBw/wbhDw/h9Y6Kv2TEeBg0YGVv2cm/Vt3dsK2Xo9qmZ9uPfEp+09ww2zSRkM9Aa3aHh18zwBJnTwrBZQGk9WD4NALbdlCixT4N82BQya+Wm8ZKkpsyAh2GGq0+PymOnjwgD3CBj9Qc3SstyOzaBKlIHUjSm7mvHFcYzJZuezgFGLF7C/2ev2Gfij8/rtty/om/FX69vuNzL3fPxeo0PL4ASu32m3s8k4PNo+Z/juh8HR27ipXuiAROwZlhji3vvU7gBqCThBAmDaSXJul4frNeQKgglcr937mflO2ubiHrvRzU1ju6Cs3wn6degJPZwsSbxur9nn7HX32sy3v097n83D4pCcsdCXreu99797P/C2O33a+Gy97TVL5+hFgI2mrboVA+RFxDCqjQ2xnjNklQhzsgsYjSbGyWM8NqZpS4+EgraUwQ+fNr+let2ESguuGCHdjgWN2dy9CFyxpPpBVFebIQJ5gOpbw+QateTr0eT1HaAC0wQJ0m1TGYPwDwymEps/NBhRS3OLkkiJM01S84kpKMYDnff4eVEulqAMDsEkBVz6h6d4zxw5O73Jrerl5NL9tDmNjfSro6tPHhQg6O/qUlZOulrbOtmzEJ9o8AQini3/pZOHko1mUBoTZixQyKrkBSHQBN6TqH2S9RqmwtLoxCyldV25Wy163aqMkVqElG3kNWW+lmElOibGee74yJBDAyt6EBMRrP6hMdLvBRI04ecEBQ309ZKnOpTgtwnGNUP2h0jnvFsuzWECFIep5mQCmNHXAjX8iTgOprKWn6Y0SvS+d0SU/EkHyMM0SqlXvyj6hf5zrM1k34B8Lfc1TGSO9ZgZt+qPBBmyr2fAfc/YWrBm5iHztECgezc6/c1SQGCKSnEelDL1oYjFFLTxIFDLi3yiFqw1w7rZFjeOMUf/0+Tk9mCtfUJJscb8PnkJTI4xZvKD+hJ17wetvFhT48kzHJ4BiqMEUKLdP9ACTV2nfxrmOjw8Q3Cpj/P+Oc7PCDnMp9kHnjA4P173J7f5J/nNHId3iGqPxkWCwvycfmyUMzDNcfIaThAFHxZJYSBjrPY6zx3sHqNsur/TzyzjGaNq3BTFgqwZD/ImY4TvBBXEJuYUSAQ7IrDa2lo15eFHCrEER4lzAsecT8z/H5u/5Yce59K0hP5Wjc0Ccu9tY1RIHCF93QTnzAp5WNaZcV4bYw0njQHS7LzY6yaEf2IZ733UfX+eJCuJVUKbgK5xZOBwr5v7jPexRy1A0Zc8uXYmAmD0AwN9FNKYgAqcY16PIJvBQoLGnD4ti8/wmLPe3j5+CiSIOCzk44HENgYLcO6i4lcogcY+0Mboce/ngvhc6Cc+d9+J3n7Rztng4CC8ixR40M3Hxh8W4gTD3fs540v2HqO7VdGMoA876/aae9OFU1wjAJ7nPc8L1xRzG//Q8Ch8DJqSecTmZRUo3fvYArNGnUpu1o+rkp4VjBjGUzfOWBylnoEav42No/Ibfbt28r2j//SfjZ/Y3AagfSBnOZS7x92MNiPW9xDB0RDHimYYP5+bneK1Iar1TTi80Sr5BZJebiHN2cfcF+MIGRZQHh4R6czbfd7tLIwZv4S+FghpFTJtT49SqXMc3mW1C6zZmhnW1tKYumk233FMjo86RVesAIzlmnc3VwaJESr29UNX6IlQYRU8w1gb42227j4YiKyqockbX6Tm9d9o8x3QRE+PRiquKTy6HCFlmI9Bzc9oJtx0D5JIm6+h8dvCFheIMRkTGO0OaQNa3MOj7F51Yu145BB7t5170XYm/H7Bzdaau490HjyC/kwQu/eMmZDWO+QaF+n0EAaYCZ+hHDj1z2HYpFi0zyxkgxij594kOTdz5jnG/02otedYs/lyf6u9XwgirvkaHeDdzmf6rJoqv5sisNBUnsbHbexkL6F2OP3eM3ajBfewOliDQdbA+qCaKkID84fGRnsTho0GNh7+f+hmNHCvaS/P5U5w5m/ras32Qz/zJIuUyLVN2irmSofwM+c1o4FDMy6qqZlUjczlyzc9lctiRCWXT+v9D48pKXulQgMJ/GLBOlsbdOD1l1XVPaW8zJSHjkR1jW7x/5a2ViuEQ74iyarksfif0Sy90QBp6C6fPUmp6cOkTjuvhuZ2p8SwZcWYGhvSy7/4J/3q5dd1ubRGq4vy9dK//ESvv32AnKOXdPbsWTV0DpOWJlYN5Mh899gVbdq0XidONuuXxzp0qqRf16qGNIDQERNOPk3o3N0zpl8eatLBSz0aYP1jI/wo4oEQ9Cnj7G2v1ZHDJ6hwJ73/9nsqWJWt9976QK1d3bp+5pQSC6m+xgE1IXhmBibf36nXX/613nr3AzV1DjqlUyMpWOB+fi8J5l/6+U/0/oVKKhkVknPSR+2NNfrp3/+NSltGlBEXotd+/XMdvVipNevXKIDD095Qrp//7Ge6VNuvNelB+oefvqnkzHRF8dxxBI8DL/1cw8Hxai2/oiOnLqto9TpyksqpHPfmS7/Sq2++o6NHPtTR46eg8TnKCjcrNT1Dfq2Vanj7mAJJn+SHgDqNgtFxmMIGFF/wCqKoN5W3av7+NwonDZGXny86Wa+6P3hHQ73gVr0RKj46qKbX3tVgTZP8k1PxkHGhOIzNrOQIp6TOmupuVy8V5GZmEGzDA9Xx2q803DWugPg4hFD2fcllNX9w2gkyHjj/kRpff0+D5XUKSElGEOayuEeYs4u3q65PH/6yTNN4GaLj/NnvRIJPI7ByuN/+hxJ5M4+I6ACUJqLyeX2gY1jlJX3ypZCEH8rQGIfy/Ht1una8mUqPg/Khcl5kNMK2rT9n106//TwJozr9eqWqKoaUlBPBOrlurdG+Md04VE1Z4D5lr4qiH/qHwYwOUqXwfItmOLf+KFZDXcM6yeeLz7ap4kq7Ss61qatjREmhPWp564hCcnM46J6qvXVFB45fU1FBnuP6jIuLVVpamg1k3s0pTNPdoZuXyIFd1kkaqhSyFdw9eyYENtfd0ttvvqJ33z+qDnKeW8qsiktH9OuXXtOx4yd0+vQpHSL/eWRChtKSEz92VzxoICaU9ZIG78P33tKhy3XavXk194Zrx8+wBwaopPfGq7/W2wcOqbmzT7GsfQhZg86dOKiXXnlDpy9cgf/6KSvLXf7YfVo+u+dBKgG+/quf6oVX39XFC+d19UYJihYpsVJi734QhjzFBdPZ2qi/++u/Yg8mKZRKem/8+qf61WvvUdrePneToipJyky+53N3n3Dfn2ZI/XfuxFG99vKrOn7ytJp7R0n7lu4opq65o4Qj+LSSKvHDg+/onQ8+VOcoaQtJEfnWyy/ohRdf0cVLlx0e5hNNaq34SM7U/CQjU3bLyL37Cmt3+MgxNSNcxHP+wqlS5ygRzHlkeEBXzh7Rb155lYptNyioEuoIqgde+iljOaKTp07q+DH2y9VSbdm2k/tw/hkzTNCcnBgjD/QN/e0//osCIhKUmZpwh04TCOi3ONcvUCjp5OlLmqWqYSyFe0YGunXgjZf15jvvk1auW0nJSSgOxG4sQMgwXvjOG2+ylz5QWTWlsdOynFR77kwNlrauquyqXnn1VfL5H1NLG/n9MzN0/fgbeumNAzp24qROnTxJ3vSTyi5cz7hM8boz9Af8YGs6o672Zr326m90vWFQWyjA5G5TVOcrv3BY/9df/gT+cEkX+OodmdWKvByUj26dOfKOattHnfSNVk/hQc08my0YJRITE50cyA96/2L+fls8Wcwj7v9ZE3g6O6XfnBcaB+wVQWsSxecHO+SUjjSBsapWKu5GIEJwHOFS+OoGKQGh96Xj0vlG6TuP81rh/Z//Wa/28ryDF6QjpdKzT0tPwHPdwqjxetIJ6lS1qLfNF0pceBiCYpf05lmphs/+8OvSqriPWzA/qz/7m2XJqWfMl1qZiwmkCBlf3Sqtvn0+MErpdIlUzd8yUNavM+/H2EMUtVEjwnEUfLuV789Agzz6XkhrbZNePyOVM4cfPietITWgCcLWTOA/fh36I/her4O+idL3tkklt6QrjDUlCq0wRKKYFJcqH3jw/nSee79/MMrqVo30Ls/OjZbqUHB2raFoSLbr3RgP9P4VBBR+jWZ81bz/G6uZP+OgoJIaWqQ47sBnNyKo2/hhOGZN++iDt3Xs5BmEkyhHw7WnTVBG8sbl87pYUqX84EyUDCS1L0vjYm5vqteRD48rd+1mfeNbdnHOaAihuPL6ORSTSW1emU71pY3q6hvUqr1foRqhj+O92LzrSe3ZutaZaQBlcoe76lVSWqHHnnraqUpnVtYiirRsLQjXxOikjl/q0CsDU9qSFahb5d2KTAzX/i3+OniuQ8fQDL+7J87kkfs2b0+sS1gsfBG6AoICFYRlwR/LcwBfI/YdYcPNw8eGBxGMj6p9IljPf++7KrlyUQc+OKYf/+h7nD2XcGWC/1B/H9WM2nWzvkNrMqbVXF+JAod1Y3DYsa5MYMHtb++lImGV9qzP5jmXyb1LmW7/IYRJs45TgGSCw0UzGMigWXe46Mc5YENsMEtTZC0gOEJPf/33tWF7l0rOH1HVcLie2L1BSeRnDkPTbH3xsKL3fVPBCA3jLfVqeull9d2sVi8J/6Mf26fwghRN9lDq2BgZzYTaGS64qcBxdR06qSnPSKU+/7zGa2+q8ZX3lf2Db8iHqmgzZvVCiRmvrVDLOwfUX94gz9ALitq9T1EbNqn18Dn1Yh2KKkxV6wfHFfnYVzRGTtv+WpSAP/2BBhHmOk5ckhfW7eBEDuftNoUVuJccz3MoV7U3OpSXH4rQQco9rL1NJZ0I6j5czP0ULQjBuo1yUdWlC0caKR4yqbqyHq3cmaz0RD9lb0pSPly/s7ZPl442KzM3FIut6+z4sMfMWNDbjAdiBIiNxwS5YEcUmu8qLNLXNqSGGtYBT017+4RSkj013Dmka0fqVFFKhbriPmWsjlfhphjt+EYePBEr7fikSs+2ahZrYzC5a0OvXVFvaZ1iNhdSTGGdrlxBwbnV6JRad891Id+tQuJH77+hw6evacWOr2F9u8sHHEvs2KDefO0NhSUX6Htb9+j8sYP6kPfuWrNBf5a7zvEgjCGg/Orltx2l7F5jyYPGYQLRUF+HTnx0RNdY57mQZMfq7f7cEHvz2HtvaswvTd/93mMquXpBr75+QH/07CYdPFWq/fu/Jh88XkcPv6fMoiKtIt7Gz31RuR/yKd8tP7N5XjbueUY71+bg3QiSWVXvbSaEd5Gt5jevvO6cMUsVOMlZsfRim/Y9o+2rs53PRUTCrBfYYhLT9dzzWXhIxvSLf/4n1WzZjEXWqtRZWrRZPAPNeuutdxWSnK0f/vBp9mqQM7dRLC7ZVHZ77pnHZCw+MiZh3nO2IVoqroCQKD37ne9qcrBLVy6d1wkqp6V+bTd7F5gNyngXQv+bFAn6zvPf1XBHrYovnlMYFc++8o0/1G54xyRGlcryUu7jFsfz6OZh8yHBFJbQjsZKvXvouHrIlmW8597WisJ17sJ1bdjzrNIjffSrF19XGF6b2ZEuVWOU+7M//5FOvf+6Lly+6lihI8ihPt/miUdu/c7HtHH7JDztmN6BD33/W08r3i8cBkXqUfL5v/nGu8rbsEt794bp+tnj+uDkZe3fsE856/ey9vDW7jYUoEMYGDwWIADDa+GDA+Rdfv/Au6qoa1VMNkLGPc0s4JYWMDptpf7kW0/hkcFLCZ8zj+HB13+JsntR+772PFZoY9CLEDLu6XOpfoQdPppmfBVep5AYhL08hEQEnp8cRSjjdSODCVx5CEep6Qh/CHEHirFmYqlMRUDczR2P0cOxzj7M6MwDm5uJdZFnGLkdursfRP/nEdIoea+iNJelGS+iZoBwblqBAFvisto+wMjtftqd72a0sWxecQiZFK3S4RtYWhHs7m1mqY1B4EyJQCBF4OvtRxBECN6yQcpk3v/wIYI0wvFChWBTMjYy9gHo5xYC3P0azOFxhEpr7EeV8HxkI52EBpsQQJMZC5UVhVd00XtzgPme5blbee7aOOm9s1IF89zOOrvlLBtjGucnnjWqRGC2Whhbi1CERqQy1gEjpgORcYRghmSHb86LZPAk+28xEzsLY1axhpoKCjI0U0M+mvXlNf7yxWlzuJ+GdR2L7cCIufddF7O53xLSspUUFaiGhnrKTuZrsr9Bp2/1oy13UF7SRzv2Pq7rV65p/YpUXEnhXFJY/aJjHEFyGgFxEItle3u7Y22KTfBRRVmZRucCsYAluSyQECEsxAcaB8jXw1/RQZ76yQftuo4W2t0zpV2rg0mo7qcVLEANFY16eV7N9ct4ahDyzE9Gs3yniWk5VF0KVQ6Vn6Ji0eS2b1UolQQLiwpxw0WpDStCOBZ5BwrBZ8w9WFNbp+z8/cqiGMdIVwsW3VsaHp/hfbfz47JOZqVbv26Fzp25oMDJLAod1Gnd6kLdsvPO34PAU2dh0bp59ZJyoki8jvU6PTNLfWxs+7thSd3N/Tsv8zcc7Pf8zcsgJHHxuJr91F4ZpjavSKwvKUoID9BUaz3uem+lZMazL4FBUHBgYipYkZvXK3rzNvlRXGFuzuAVd/ty+rTnEww8XN2osN2FCmZPBmBlbz//EgIyVZpuXlZvRYcyfvA99Z4/o7nASEXvSuJ9RVh/gV3EhCk0rUo9J49pqjlGHlEZCqGMbkfpZfmlZig4K11elB5uPHxVEz0UpLlHCB7BCtuNJSVvW5KqzzVrFFhCMBbm8dFp1WHxX7U3RVVXuiiVPYal0VNlCJ4RaREKTfZSZl44FacCFBLlh6A+SYW3QfbnNApnCK5LD7XcaKO64Yw2PJ4GfMVDzVV9is6kuhyWpSaqX+auCEUJmFF3K0Vz0JizE7xVW9qr2EjGXtevprYpLMPRSilK5PLzVQgQCh9zPdDayjsp1uGNsheL29xPkXgrGj+8odCsZAUlhWvrxtV67+JFDaMEPUzzDwzR3qeexbDirdJRFwb6znPYGBNjA2rFY1KwPR1rawbW+Tx9cAsFa2MBClEk/VJWu+ScojMKKSSReEepu/OMT/nBcf9SlOPs6ZNY+6K1fXMwvA9mfg8nMqGjCe9Oxp69Ss9K08QAVvGDpzQyuUWzCI9jWA288TL4MYcIrPLus/QpXX7sZdv7BnMYAmrRR4GjcNzeAYbru93MBd3aXK+zJ44rb/0ueU4OOG5/53MI0GN8rr9/wPmc/wJLCnt5+yuXwiQd7S0UaWhkXyUoEqiD922zotGmlmISHUBvwmbGeU+lktjfsewLg3kNo5j04FWO4bL097Mc5vMXiiwPb1ZegXo621SJ5QSvv3JZNzckYJY9O9DXBq4uXFkZ6ZqODUa+aMfQ0q31eesVBd1a6yuAd3Vqx+49CMHwJjfRHvB9CgtwCzQ9ePCEtu7aBz99jc9+/Obp7QLiQwW/nOxsp8RwWvR7am5qlMfEAOdwpbIzsjRUVKBrDX0OrGAhQnBMQpqiuTuHsKx210YIW4FzD7iGzSyAfvhj/RoDVjUyhtLBeQsHnhMJ/7biPX09Haq4fEI5a7YoGqvXfMluytRgf48+PHxUkQi5qxHG25Ah7m22r0y5GgWiY2sbAqTL8vz6c8F/9ff/BBjfCHAIU3u+eM0tmyz5yOy+6BjA8oiQFYngx11O5TEuS7tH6M1wIZx/LDwu6AL0UgKWWbzJykaAsnM530X65OCtrwy8O/CVj2s71jGHphJBq5WvEwjeJ8pcwioeEy5IrNZ3+cgnH/uZv7vnY32aoWqG+SXzPHczITmDDYxcoA/pNycdQdD6Q/g0WILBGQwGMsDXg5o9H6+e2hAcMBqigbvojJftt5r1GwZNDb6NMUlUU5UXP9ejldY2SB9dQymo4nljt4X/33rC/F8Azuk8JzkaJYM1R94AH+WQ3HkIMqBSGOuxG/QL3fNSWG/oZfAMg0y0oBTgMVMwgrHT2ABevgHate9JZaUlOS4zszKY9eX8uQvyDY1xqpGZhdHwYV+oLBIcgM62FjU1NX3sqxvM1OjQgMMAkxFyrl4r1abtO7Vj0zoHn+sF8/aawjLKPA1XZYnJ7cvh1PC5mooSBzph8ImyimryEvc6Vf3Cgilf6iKacyGYq9wfF3hybKBDTwyUuM68VNM0rLq2MUp6TmocjKfRsxNs5ifH2YMF2i8gWEVYqOJQNHbt2Or8vmnTJkeY2LV7L5ZnV7J269aieYfBtQSzGf2xHAejmc2yLoYHvPeeMJxaTuE6Nnytrl29rIGZYGWkxHPWXaM3fGFcUrpm+5t18twlSnNnU90u1lGiHHuyneF77x1+dn3Smfydf+x5pnRYyi0XDb1x3/MzzHoaa4hXWJy8+Jtheb3AriGVYFkawZpBARfDyvEk57mf6IvT42Bax1pbNNLQqGHcP9MoOqY/BOcWKG73ZvoDMkGlozkw0FMId6bIeWGp8/QLVDhlVv18x9VxplQxe3eBJw6XL4dlorVBQ1U14JK5RO0z5ipzN8bc2zKovgEUCuAOYSGeamkaRZCf0hhaZd8IkJdEcJ0Bc+pqGkLp4lwhjE7AHMY59HOMxxdrlCeBCj5YgFore6geOAZekIPGuMPRylesiXZgWGa5bawZVmiEv0L46qzu1QhMe5R+ujvHFJUSqrjUEBSLHi5bsN9ozxb/MIzAM8l+8iNw2gQST/o0nHXDzW6FJoQAjcFdzT72T0qFEfVpAguAFRVJpvrUSA9CPdCWh2lePCME5m2wm99q7AFfvyD+5ge9qGrJerV2dDPuUabNGPl3EuvZhRvV2rlzB1XG7kJ3futZn3jBeE4lJaHP32zCrR0EJASsK5jPbhi5xS5Y82MvxyCENFSVqrGxEYG4FaVlnP0WoVwY3c2rF3XuPHs8lepqXHj3brVPdPdbvxrmPgxldKirEUv0Yb1/5KRa4AXuNjUxqkvnzqh52NOBPBlmuRvPxjhSoymxAx0NfO5DfXD0FEoCF8kCmvElXy7vYfjwxQsXgfOHY1m0Ig2uhxhP6YCnTE+NIqAPqK76lt58822ghhNYqyM1RaXQE8c+0quvvkEZeejFmZtvs76NrtNj/boKpGJ0zva9ax/bM8xSHEI1Us+pQVXU1Dh07+GyHOPSNBytZbSqq6pQ14SP1hXlclbnLwKNUO303Knjmg0AIsQlOoLpFBJDAABAAElEQVT3yzxTg4bnu90iouLBzo+qtq5G1fTf3QuvRzAcgUcEItxYie0wBMRZrPgT5qZdQHPKc4MiN0GzrK5La1cXAWPkAnU3MgPl5eejuJbr7BlgKkM+SqYyqPE/7POOIHutqh1evgXYnovHuT/6Wd8niNsovnBC5XiIorAYjnB/DQ+hyPTjFWKtrXl6+eA1DFEA3qOLGADefOuASqubCIL1BqIV6xhzlrpS5meNeSF/Q/R4dM22F/zfYcpGK+ee47vxCOdv/NyO1fR0OfCDlS4h2N5jCuVvXUALGKYJpO697WYsds6w2MuL7/BqymtKKxAIj1+RLiCoP5Hr6tcOsvszC+jSYQA2V+NDZ5kPyqmSEfhs3madtYA5w8NiZBLeStW2SgWMYe8qxsD7kck1xudNMXhQGxvHklzN81AqVmZjRY50jd353O3x3+bDDs1NaC6vR8jmb3tWYIXnjTam7HQuS34+gVAaCS22ptoVv4jmLBrri9xjtKALZyGdn/nFxmHY8KRYlBzoUsekt2QiKPNaA8p7PcagP97mUoyIGXE+7MkhCsPN5gdh7PEOg22qUWv/OMFi/ljECICaaVffIBYwtB/n8rWP/o6bJ9av9OxcRY9hYb19OxiDjkGgm5vGzT5nOVE9UXqmCfgKhS5kXoFJGxbKk8pPZpV16HfPPMy6uXnXTj2xY71DiwCE3N/UlCDggAN1Dtc9b+bDFgAygsXPBLTYmAAVxYborfPderNpUJ0940pNg65U2crIyVUsbkq3EuEEjLBRLYjIhEjbL65dg7LyCW3erKUsJc3m4+W4aA2mYEqJaboOXtgOniNy8C5zZ4bFak1Bqs4VN2rbnnUK9+27IwR74GoPDg3XupVpevtMpX7w/a3qqLdLZti54MzSYwGTtg/sywKbzJI079AWxjKHhc4TmIeNj4gdBeauUhRg/Y4TZ9T69luK3ImAn5PEYAlY4/k2R/s+i0DvyRqE79uvHpSwlrfeds6XB0K/J7TyT8bybGvNeMI37OAyPKWeqyVACro01rlVyU/ukF8cZWvXrQNuUKWwzAQsgT4KX7NGY+1H1IKgMAuWag7LojdKhFm3reogE1ZbPQEvCJp9rWi/DLuulJLj0T4aaqaAEeRtrx1wAtT6KKdqgWsF21NVdrGZCx98JAJs3pYkrVpD0BZ7rHB3mkKKO1V8vUtFW+IUhpBqZ8sC7PqaB/FQTSuic1Q+ZP+ZAKjfDk7Lb5TLvncCYc1fXZ3TwHD4fXBK0akRWrV+SiUXKQ99skH9PXFatTlOoQjDPVi7WnjvxvUEBwXZVUM4DXvVwwuLvtES+vvjJoe4jqLAG5as2d4w65QP1vinntirE+eu6PWKYk2ODCo4dT171ZvgqSEs2lc1F56uFWlxpDWcB/O9PUJ7thPghcJ6+iSu8e4ujD7julnVqK1rEK64xAyutHPf43rtnQ914O0qvDhDmiVoY7y3Ra0DwOWe/IqG2+uAcpxTTfMurc1NxOPD4s6j+dmzn/g97aIccXdLuQ58eEpXb6UoKyWOPcO+QcgyAaWzuVYfUT67vKpJgx4XlZaawue+rt3+Qepq5nOHTut6QqrzuXl067zFOfNsy9ScIn3jm2H65c9+qrpOBCSCSC2o2fiOKcXpKzboMXiV9/So/ub/+R9qwBW6YccT8DCslSM9+vk//oR7rFmRBAX6zhMT7FgcUa6iErP1e889B+2P6WpplYpyU5w7x4MgoOikTG0pytCJI4cchWeKgKO820qSlbMu5/LNKdqoRPCQC7FCz1CyeIKLvJny8z0tVWrr7NXN4hLt2LZZwSaIY4mNQ6FZW9iqkyeP6hper6aeEaXjfUPdYk0sANpFGzpekABuhJ+m/x5KU1+7cgnP0gptJkbDrP8uXgjPnRxRWXk19N2vcO9pnTpxRFdulCknKUpT7PtqICAR6UUYn2KAoLi4+nzW3JR4E+InRvuIrzisZoKwp72CVNvSpdVAwIyneCAEJ+as0Y//YhWhw6N66403dObMOa1flSc/U4i/wO2RCcF2v8SinJfhfs9H6JnF0iiUFm9uTIIqHaZrxo6fH0MALuQrxYVjtTvEXBy3eb8jMJulYSGNs+8cCBN87S62Z42aFZqvcO6+OPgugeaOtTKa7xYY5rzP3s973Z8x4sx3+WzcFoz36mkgD9yfW3KYDzTA+6NBvjACwATA/G6WsrAA/+2bLsvnvgIwuglYg7uw7CIEJiGQP6iZpXtDnivwDGim05y5Mn4Tfk3owSPiNNvrt2rBDCPofnsnAjNCOEYMRWGlxTvLpQ0teJ5lrbA5LKYRI6VQvuo6oTH9diP0A21EGEBg56uhiX5Yy+e2uhSB//4G8+ZOb2Gsr5xjfPvACjOW+50Zy31rQqQxLb+gcK1ckQ1D6CCojgwRU0TdwpzcQtxi5rA0n7VMCWCZ338HWvTfsXSYJXLN9v3atz4LBggtEFADYVadZCGYwKJgmSIs48UMGn0gTHKSBbGyvyYYWzOrVygQiYQENow1+gjgMjf3o+1bN93sErJMEGaRul6JhWrOSzmpBOwlB+gvEHiGRyb19ql2RcUhPM+O6PC7b6mJiFArxWnNrLUbdn9Fv0cGBwte+6w2CUTDsk2YcBsdFQUGsZ15xBOMOYx8SSQ87s5xBCgvhE27nM1Ca1ka1m7Zp/jcITwTkRiFr9w+Z67TFhgUAkToaXnF5BGwE6fepkpHYPLlebPTAwhfrDeu5DEsFJ0IFoFs8kmEB7sg7fKd4jEmYNmXu9Gtq/GaB++fw5XsbHhoa1ZaE3ynob0PAtpwXa0CE+OYE4yfyF4fLppprHxj3VjdC0MUmJVOQF0W1TN7CG67gGtyCmuYv2aJwJ6F5t4I2J4Id1HbtmJVDmT/e6r15FklgEn2Cgt0LM+WgcJR2BhPYGau0v4kmUwSg+o/e5S9jHUY95kFAY2AXfImuLEPy703Lv/B7lEEZD8NELzQUs33hn6FRPoBgxiRB+6UKbJHdHZOKD3ZX4VbkxhHH/OaUtnlLlzYZJ1AUfHDgh/G2k+NdLNvoBn70AT36YkZNcGw/cLJOMIemUIIDwnzUm1ZrwKHeQ7bwyzUvd1EvQdiUW4ZVTiKaFJBNDhLItZx6dQAn+jOwBsAhKn4BHCloiQUv0B7vMOY5hDOjKtaKjpbL8O1msJoFr6HafYMt9JlwpmdF7u0rYS5YcdDqW66cuNOZeSvAx/dquMH31IY1jKzoLU33tKRY2e15/f/FyLZEc7de2QeAzGc/EbOSOHmx1jzCV3G+nXwSr02r4bxo6SNYz238tXJOav0w3+XAeyiD+jECVW0A0XobdMskILwmFglwvAqb91QU3unirLi6Hl+V7Inz46MBWKCRTjIK524jqsEwbkErSEyYQSy/77y3B/osa+AgWUf/eaf/qcyN+3BA5mExwmFlc8FeqXhpeVzC7RIGh55nAtjzgROsrhYcO0Q59EyEHhMEyTLPolmbpX1ZD9hrX1xifujbNu9FAm0yw+Bd3LcXymx4Q7PWQjfNl44SFVTf85VeGQEyn2EirFkGw8c5yI3uERIWKS+9q3vOdlh6ghgOw/OPxMF1XCrxRdPAVOK0oZV+QuCn9iWCItL0bf/6IcOrlqTw/off/XXxG1sAOLo7wRve3gzz+Awbdv7lArXbyPWqV2/eOFlZRDcPdgGRISYj3EU8M7uTpQwMiXca8Wdx54b7O3SkUMH1adwfecb+10BfZxRwyWbZ2J2vJ+g5UHtxtKcnozgO9Sid4sbWP/NasMaf50A66e+80OCzzlvC9jrgSHh2vvMt7XlcQQH9vrB999VVT/KdFaS068ZPAwW4k9QcUIIJZXJvJOEB6R5xAwWfMSUXDubvM++KLJ8m9/PY9Kfw1vmd+IeYiAmuK7NJwjtjPQWgqFd+hb4BkRIb14nYCyb4LEW3LvdCItVWEKxCq7htSzc6G9cQDDqBTpQAaQBoWhv7sIG0IWweeiqdJNnBrJueIEFfFIf0O+PvgZGdi3W50rwsdV24ROclYklpV06WuzC6E5dQjjcgqUWnsQdPq9md2pxOV/NEvE+4JJw96dhbUUofI3Xn16JgItAeIi5kZkIdym/83WWMZXRt10wO1bNDw9stCUYnc3EZc9mrm0EYsFzqqHlJGM3PO0gtG2B1o/xTKM/8FARiK0aXt9ViOW7iODB8zyAz+O51VoE93nGZHwqPVDotR/avmn9sKYGbdmZhYW3BgwygvGTrKM33985C30ZY1qqoxfpGHQnnkunmcMtxrKffRLMutzbYhNTlF9gigsY2YQ8sLW4UYnYL0YrHg+IUybQAkv/88VoZuGK1I/+t/8ME7BVuttMwPSYnQSv16RGXN+P7d+nm9evoi2jGBCg0lhTqqSsAoxj47p+7ZpKK+o06vuhMr/zDIzTZZm98zQEjfjoUNa9A4vyhJOpwQy11wDYtrSReg2hpp/L+KntCcqN9VUTLvV3zvVqFCtcRHSQtheQEgqm9b/+p//qCEN3nguHtL5852EtqCm5qGsc4g1btmjdpq366Ytv68XmYi7Fca3d9jhW5Cm99covFZG7SdnxIY6AbW6xsOg4xSYg+IEVG8CK4I8VzpQE69OPSzMwzHCWkTBUAs14zZ9URAFAGHasy9WxQ+/g6iUtGjhk7xgESDA+ky1ejtXrFz/9ieOeD4tM0PZd21EqSU92ey5mnfNAGPeJTdJ0+0VHoJud8FDf8SNqv1KlibYmsjyEKHQTxU6SEhS7bY2aXnxBfkAWLChu1itWkSvTNQO2s/P4OY0iuMwQ/JX03Lf5HGnkCMDpq+lU2vPfVjdR8f11bQjRPVhKAhS+cRNWUCAr0NYsJ17g9ZzDx7/jLQ3qOHpa4+A0TWFMfG43AXAzKr3wkc7UjOuJ/DXyiwzSaqy5cbF8jovk5MtlXGxc/vhudn0rVxGhKEMIM6VnW9RQ3queklH19k1imZ0kkMhPmesS1HKzXRVkfDDX6MQIlro1cQ4Ep+V6Mxlq5pReANa7eVQbniRiPxVhHQ7TA27q5NEO9SLg5O3KUP5atGhutvbydpWWD6m0f1idLaSiA7vtC5YsJieafeyr0T7c7yMeeqwgjEBK17m0PMxjjbWag/n5kV7JwczW3AK+mcgqt93Zfgv5YWyoT+cRLo8RANQ+5qtDWF72blvnBC+dLW7RD//kWwjxl3Xu0v/P3nsHx3ml650PAAIgciQyiEgiMIA5SqRI5TDSzNXM3JnxHV+X12WX16H8x9a6av9ybdXWbpW31ltrX7vunagZaZQTRSXmnCMIAkTOOedIYH/vaTYIUhLZzZHGM2UcCUSju7/vnO896T1veJ4y3LcDCoxIJfkY1JmAaRceEZK+WuuJywrxc/GzA5Z5YIKB6JpDMTBvVVRUlBvHVVdP6mbTsLbt3KbQ6V6998FBDCTDHI4S9FffJ5FpKTBZR38NusIbjG/gH6fC9OyqPLwybAw+lgFi7j9+/0MN3OYOxNgGRiRpz6pc9Xc26LW3v9RP/+avlYoiYvBrxsbn2sfhbIyx++En+zU8GwxEH9eBrLJu9Qofa+VrHDrGh3oc6kovED+BhBH13I5WIRbo4a4mHThzXoXbntKKki06f+NNvfPG7wl5C1Rk1mpyYYL12QdvEsvKATlwTu0TEXo+LxULvI+bLNWbkeCz918XiHzMf+AWyTl4+uW/Zt4MI88PlV+yVesKs3Tq8OdY1zvxEI5o7ZZdWs64GCNW+HJFs7Y9+bKDW/T9oT3fNA+ZwX6FIVOz5tgBK4J1aYq+PcaaFLZ8kzYVZ6ji2kVdvFbuYMGKtu5h31qlbpSQs+98rL//+wZ1tLfriRdexSDHpuxHuXH2oC6hZMQuS9Zbr/9Okaxxz+7Zquqy66rvndVPv/+ESvJS9MX+jzkEhRA7PKDdL/5ES+am8AQ0KD5njVaQCLzQOOBL9QanaNCSBkdniUXRKNmRM4EuxvzKmaNqHg3XRhS6ShBuLtb1Ov2mn1Csx598HkvduA598aGultdqIrifg/8SvfLSc4Sd+qeI+9LOR/1OACfpe3fpB9xpqLJKnft+pazCjzQ3zqL1EJxg1jwHOYYhwinBoJiIQyibsMcIY2f/nhGUYOYAhxOsRp4YWct/smvYK8A4RTmIeECjvuYjs/gyP0UIEh3OCY7r7eBjlmc8zw6WbAQF0SzOtu5YzLKFGBiEmYUt0E/uPZKl58Mqvqaae94yC6xZX836aRY50x8srtm8gHgNyZrFQMB3LBzATmHmebO5P//enXZafKzXondPBQ/4wyzrFk9sMsMgJ/KZ3DOaZ80MeUC98oGnXpOxKdDEujv5mAXR6jQLub/13t8kG0mEFDqoNnttVmqTocnerOGm2Jp8zSpv/WIyMGu5/W19ZfIwuVlm6dTMTnXNvqro3Y/z5QBiG8GFRMghWDgMTsfuaS4/W+DN3WV4uf5O7vvb/8f8bdPonYtfYNlM1itbnn4gWYa5uc0td2D/5yQ/LVeic9VxkubZEnGXG9ZnMK74mzeuuTi/kAisCyQU1VRVKA5rRG5m6nxTm6tLgcM5rlXbn8IKVaDq2kHV9Uw5C0wY8ZrZWPySSN4KCwkAm3SKg+WQS1xakY4lhcEZusQk+YiF5/j49f+mkbAsPf/MHhffXldTjXLfrmXAFmWhSIYFTOg//t9/pxf++ucksCSpqa5K8cuLlRIf6RZRByPVRYINCV0FWUlqBTkiBldKRvIdlwgTpLmpUa1kzW4Fkqe/txvonAa1gH8YSmxlfl4O2KzxTgG+WVFFyL8l4THfwmNUTBJfIlmfnU016gGaJj+HZCwG2TTJgI2//HtF7XpZsfkkFLKRD5SWqev4CWcRTli/BviwCBRfLM6NDRpr78FazIEhdzluyCTdJiFq8EYF7kksornZWsp7ZtUdw4I8DuZg3IZ1munt4DvXNVhRo6X5JUravs7d08b9BNbykbZ+JawvdhbQaSxEgzduotsSCpIPZFtinPp621AY3lFk8V5ts4zboDCSYiIYIx6FsquuzyE3hAO9llUMxJRNXqwtfYRDdILckETiY/PNbuJQJ5SLspuVhxUY6XQCbWTjIJxFNSWDDO7oYA0QUjFIXHEiccVtVf3KWJXIRs8mhRI8hSW6mrCJmbkA6klwll8z6U2ykLUQvxRGstNwx7CDQksuStFKoNMiCYUY6R5VLzHMWStwddsJj7EyQwxl+3tvaTaB2OnH12l4ckjvv/FbpW9+SRUXj2rb5o3atWuXX4PRcEsrb6IEtHIg4SCdmJqptUX5xKt2E/s+qG1b1qmvvVkVlbX0YbRykeWyhHi3mVdVVSuUvIK85b4nxH1t49gHO9paVUd92zeuZiwSrtU3oZzcHJILx4nhv0LdUVqRl+fwgO2g2tbcpNr6et3mIJuXR7Jsaoo7xNvY9aVMkIjZ09msm0AdBQQuVWFRoYtpnsNCefHqLW3YvIGQlAjPOslGfKv0kqKTs9n/wkkKa71zXZgKiwu0DIvqwqS6h9VvCWLt7czZmjqOuEuUk8OhKT2Zg1W/amsblJJTSBJcGN7NTowhVZoMILHZQq7YaC2h7RawUNMo7znIw66z5Clfn3saK3RXe4uLtzU9IjtnBaGHyRgRbuvylet4YbNdwmNNOWFIhF9kZOcoJWkZsgh3Mcw3atpUVLCSEAzf47+/Kg82N1AoLly6rOQM1h+ey+pbEpep5SRBtTc1gHzVrKT0DJkV2PIjpti/DDKutqlNselZWpmVQV/QBh/729pQf/OybhE3aHqLwaKFsi9sXFtMwmybekkK3bSuUH2sLRaP3IeCk5kF5F9mpkcJrqrF85fu8iv8qfMrz856XF/H/dE51nNwa+YQ2z8ZQlIplnZCg66VleMRuE0i6EqlpSxDBwhW2eVzwAMSAsgKZEl6Wzaud4fOBz26kWWcP39eGzduJJTKTwXwK41+8Bv+KcEVt9T+8WvKLDqmgIlGFjZG4WJZlMC3LIG5JXEo9VvVO/esokkemvujZu233LhvuJ1XCU7CmvsikDQRZi14QDGA/6HBXlWUVxLSgYLPuhobn6KSdWtJZMNdj9Jgrn0LUTDrocVEe8MJvLiQdvtxMDFLL5/XtYZB/ezHr3DCNtxXNC2usQQli7XjlysWXzqFy8HA4S15y/u+51M//0Xpn8MqYHF9a3Y+q5LVhS6xylzRFoZhyRgAFqm3pVJvfnFFr/7gRaUlxTm3mMX92oHFdSv3MVeZIWiYpdYOT/bBXcIDyzo2N/cs8cickCgmF3OrWViFvWfyMbf6DBZur2vVkrDMNeqBTbJYPOTAc1s4zSwuyeFr59R5pUmpLz6jSILUb2Nh6jx0QPHbHtNSEgHtnlbMfW8hDuautzAKe98smi5WmM8D79TPN933TBENxPVrDzJNFvfgzQqFZhaABJLs7mffM2xd+7Frrczfj2sC6Wero6WuQvs+PaznOTykQQBh8daGP3ynWU4msy4MBVkRW+4txsJm4TCW8DOKQl5TPaqsgjjFgQxhZYYd1GRsdXivM/m6wnt2vb0///zcy66xiu2e3ph7G+9WvxULhai+2K4kkhwSwR02h4wxyPG/u8babGQj441Vav74mNJ/9EMFJ0SR5HkFy2GFfvaznwBj9rbWcmjZvn27u6ev/7ixY31vVgiKJT/Z2LH22XyxBC6LxfSOl2DrL75nIRQmJx7MKRR27R9TPK5ezxi1segS7xifAcT3TxGmYBYwm7feg7rVb+PY1c+4snHqXzH5Y9HHCHB3rNN/PJNBodlzzt8TWVhd9j2r32RmxoO71/lbNzog4QcmcxOhrU02r0wGdm8LjbI1xoWp8B3rC0vqsnHgvY63XN/4E5PrlY+tjdZ+k7HNcW9/u2fk+ewZXZ/TuCVY17yfe/rcMya9/eC9p/+/kfOduHb37Iwxe25bcz1jgbAoPFuOOMJNAE9om/WNoe9Ym7xzzNe6DQ3EydiER3EJitzLzUW3PnrWHQsFsnXQJQYz5mxNdusi7bB6/7hiIUyePrW4eiN8oiHz49oOKXMcmF2/ULe1zWD5DLnHmm1tCmF9NJE8qPzZKsF9YNt1H96PWb1PwZNnWdkw3y2WRQl8yxKYW7pCA31rSCVIVdT3XnAK0Ldcxbd+O5vs7186gGITpJ0khISZ6+ghxa6xOMZxFDDbTGzRtFAAv5RT7jEyNICVuEqJ2StVtHw5qCMJKL8eBeshTXj0j6l3lpCNGwBDZ2Fdi8U1eH8xS/1gT5t6sBRkAhEWxmb5Z1FM7riwB6+XaUliiiKy0p0VdayxEatuKjG7Dz7A+PoMc8RLT4IlGohVOsRcWn6UPuIG27oHVFy4wikYflw6/9XbuF0GBqYd69tSiz/6jspt4s8HgCEz67Ix2X2dPjfLGB+tr8MWHa6onDQOY5Oqw6K0JHIZZAMpOnL4sCPKKCws/I5auXjbRQksSuAvRQJ/tkpw1xFYjV7/lRLWRChosgwlGB/3YlmUwLcsgYCIHFy0cZpZkqzk//lf3Buv+i3X9W3dzhTaz6/DRFRFULaduC2+x9fiOdh7vv2QE/LX3TIGnNEZLBEtJNw8U/K4/tHjrwBlQ3D1YlmUwKIEFiWwKIFFCfyFSeBPqQT7sVODKACDU2xcngK73yG4swWxelxQf2HyXWzun7sEgloUt/EVDSf84C9CATZxmmtrfXqB8mMzIIvI+87jmBZ2oWXntvd3QUwxppS4ZcR8hy/8ePH1ogQWJbAogUUJLEpgUQJfIwG/lOCgUGIJQ7u5TR0BPUAgEJWzWBYl8K1LgMztoMBm8FI9APKWRW6xVBYDFkqGvaELGCSMvWdWV4PLcbFX33pD/LvhUiByDIUjITLWZYrb1R7oHms7bGhkEn9dmeb5pomvDCS+zWhT7dnGAUq2OEJ7XoO0eVCxeCuz/NrvJcSlBfFjxYVakEATALatISxYnJ63WLvstG0wUsHEaFnGs8WzWd1jZHiarMNpr8UW+hW3Z+EZgLl7+stzOIgAccHix+7ehwxz4qDtO/aMYdRjbZsmfGCcrFZD1AgFwsmSdfyJm3PxocSkedtvjElLkd/dej0ysbg1w3g1yDljlLO2OSxMqJcN0slCUjzJOv6b5c0jYLIdpf/s3vcibJBQRl9P8oyGEx1B4pI9t0FLGXsYl7oSRga6tcFipH0qXGhxqHYPiyG3sJpw7h30NYF3ExyUJulzi8s2Smxj+TLoKIvjtpAcQ+l41GLPPU5mrMVbhi2Af7JxaDGc1j5Xh40rntvCZUYtm/hOMUgx6y9/2mDjdQJ5WhykFbtHuGWy34m3tvds/bDvWFz5EmJTI/h8DhgzG/9GWGCA/sbM6CEVsCv8KxZramPZZBiF3BcWi191Y534UcPdDuP5LB7f2mRj3WLVQwmd8icxbeH97fU4c9ziMh2uN2vjwuLicpE9g93Fg1qoio2VUWDUrO6l9FPonXjdhdf58tqezeLwx3gOW9sW5iqYbjBBf1vMsltLLKGZtc3qnmS8G763zfGlzPH52GVfKl3wHZOhGQCWGOILc9g7W2wuWx0GHeZdQ70488akZ3WbvPxB4/BUS2w1/WzPNYXnzUg7bJ4uJIFw673NZ2TiCnPQ1lF7xskHXLfgsR760ivDoBD2BvYMW7et2NozPgpOuMUEM9G8xCJEBd8Zn6azEdvPXmDJeha3629xsqVP7f4RzBlv8bbJS2lv7xsqj6FKzAF5Y+uCxQPb/La++nMqfraGVRLMN18T4mxRN+xch4jA5DOGNG9h3XCoAGDUMzlBUSBkztjayCNQx6ADBHDoAoZk4C+LG2u8wyI2xAHbBwz9AWhNNkMbKKAlcH9DKbC5YMWgvUh4ZWDzOd9hrmoZbSWnyOdi97X79XBvyyOxNdieyRjkrDAvHSmEMcLZ54bgYMgJzClHomG5KcbsZt+3+v0prEOOdtjQIUDqATfV86x2D2uX1QEMrKvX0CEMdg4dxMkfYAUWYFPcbHr88cXaMsyaDJmVQ/VYGArJuuFQLGw80CzB3Ojaav1lyBwmf9e+MATksAXBFYRmsKGqHPafBuhXQ2XEDvnLU6BNriYDtxFGOSiDV68lKxdq4T+zyWWbhKEZXLt2HWiMZD25Y/09ArZFy9ARGmtvqaKhAzSDdUqHlrbixlXY/NrAno1W8apVyiWT+EEKkWEo3w82bwkoY2TjXzp7goy7HG1cUwBj3J3BSL19wKpVAZ7e0gnOLLiam7ZsBs7sNpnXjbp+s4Z5EKgVBWvJpocKF6QE3wq9SrLc6eOHwT4edpu7Jd+s3/aElqfEsSHdUbhgsyq7flUNze3EqyaqqKiIrOUENdVX6yaUthOgLqSkZmnDhtWMTd+VQTtMNNZV6lZVg2OISidzvIiY2oQYb7wyCjpsR3VVN1XT2M7hIFQl69crEQi00f52XQOhYRhsy9yVWPTzyOQnIc2vglwnUTJbG2p0oawWFrLHlUGGtLdMArNWX1cN0181G1SY8sD8yyeruuZWma6CNmHKr5W84g1aXZBDn/u2ENjhp7u9STdvVoHIMAzTW6JWr1uvVKitvRu0bV5jI8SOM28aGlvBM03Q9sd2KCwQRAnij+sbmpQAO9/KrBRvc/34bYq/jZ0WXbpaqiQIA7aUFM5fb4eblvpa3aB903xv2fI8FeRmgKTB95GTFVNmQwjrWbd5JzBOd2U2f5NveDHSB3vkhUvgjY+DRRsMHFycjNUwmWf3FKPJrWFM1AEjOKFoWIE287kmBomjr4ROtwv8ZSCetmzlGpjAFijP31DlPW/bHB8C2q4CdIDuiRC99NTO+UOXOxSAMHL5EvBtXb2KS8pQcVGBQ0moqrjhEARmwPDOyl5BUmAhe4YncfOeCh7wh1O+ibUuu3RWAzCnbQKVJM4W9zvFlERrW+XNUui519C3YF8Dz9gLGsuFS6Xg48+qcFWJcrIyQU/wL2bdNpYxFK5m5tvlyja99Oxe9h7PPDOZ2Fi/xfpSU9/MRsq6nV2gIggtejpbVQaCwDDJlJYIvGXzOkVHRT5wffM+z8LfUzx3A9i3t+patG4r84wN2xJHbWeZAHax7MoVtcLENQMiQT7zbEVejkIZ610d7appaAW1pEjZacD9+VEsgbWvu11XLl9Hv5gAWSRe60rWQLyVNN/+Gda2G5cv6CZYpJEoAEauU7J+A8g5syoFvWIE5XhpdILWrVujtORl89f52gwjzOjp6tDF8+eUUbxdRRDueMesHTbLr5xWjeHLcsg1fObcwrVKDJmENKNMQ8jcDpjRyH0HFPFRfirB3v3s+vVruh2epKd3bphv9jTr3g2o7puMy5liaE5R5KZs3rJNHY3lrPWdoPlEq2hVsbKXg1hxR3Gfv8F/xxdB/4Hic/0zQ2hTx9G4rvh0iSm6NY3SawfAwkU5fCz/7mV2OL1JWPG/f0u6XOUhkiBfQl18/3/9AyxuFWDNdsELno1id2fvvnv1g1919Ej7T0HAcBpKYO4NTjaWMuYic8QALf5hn/TJRXBy+dl3jvvzeQ1t+eVh6WwlbW2TNrOGG7IPl/hUmB/gckq/OwguL/cERhNGJxT/O2sxazzMNtIvDoBXfBVFFJQeWElVX897X0qfXkb5ZQ9Mi/Nf6YeXQCe4/hdfwOKTC0kJ9/Ea/cxA0twqvYUu9MUlqZ0uzM+QyHHUG8elg7QJ3VIFqXcVZ58e+Gu+xNoHEYN0knv/f5+zmS/XPeQfrFs6Sht+g5yP0b9gvSuetbedfn77GBjKfNbEoQjUKhaKPI1F7HV0pL/+ze9UWVMHrmejSiub2CTj9fbb74FTWgkdaqOaAI1cW7yCk/3Ds06/ptnf2ltm0bPs3cTERKeQ20Zw4eQBvfPRF9ADh2n31rUL6rKs+yn1syG9/fqvdfZGgzKWA2HEgvVf/us/gPsZrYbqMt2CVq8ERjFTcn21itpiaGxYFSAg/Po3r4EzvExFK3LnleBZIMGOf/GxDh6/6EgCzp08rOkIhD7aof2woPWDnWuA/ifOXVN6di6oDgxWXwobo6BKfe3Xv1IXmHhxnC5NQU8BRshonc0aYqgY7TXX9Q+vfwAWbhAwW1WqahvWquwE/eLvfwn5xQSpBmBLHjionLWbUGA91lJfqh8DKePM0cPqoO5hIOguX7uhWBS7rBRP+83iWXOrVL997U2FRsaBH3sZRqcJsKfDdPijt1UNW83sOAxrpTcBxl+O4p7gS7Xz3zELs23yhnRw4PQ1NsgSt9F5v9DRWKn33t+nLqgex/o7dPx8qUpWrdC1C6d1+Ox1ZWSkOut9fHKag60yKEBfio25iqtndbOuDbSQIZWiFPXPRbFBZsx7EaY45V8/fVDvfnZUM5AchGOlScvOhgSkW5+8/64OnbrklOAVy5N9qfKe71j9Y8MDOn7gE33A/UOikzh0rZz/zvgoFLenj6selrlpMGYPHT0FTnSq4sEPbm7vdigCvRBZ1NbWKSmbTTLVx/FGDR11N/XZgcOamAvB6AC2NdTUaZDJGC2sp8zqzMFPVY+1ZYI5cfLwl2BAFylwDEXiCgxyWM7LL51UwyCHPiDworzsQ/Ot/+YXdoidBKv6xuXTevO9fWDeT+q5XeBBm7mVMoUyVld2Tr997wsoc0NVAZ5rN9jJeWA9/93f/RIynCASRzt07PhpFW/aDumEWUV923FMIZlivamHBe8Xv/q1OkcDUbAL71GChwiROvL5Pr397vugk6xVTvoyN+4+efd13TTmwfEe9qRa5mcWeOMLLFTf/MjznxhJTmtDtd56621YV6u057FtDtrSvmDKfxtMlr97+xONTaEsc1CxtWYDTHqfffQB+Pwtjujh0Oefaln+Wle3r2PdlG9T/ruAvXv/nT/o4vVbyuHQmJbIWnNHdsODfTr4+eeaRvluKL+m8tpmrSgs1uxwB7jFb4BHXwVdt+GLs0H7UWaxaNZUlOr8tVsYquZ0nLE0GxqjwpX5GPI8/TbB+D5y8IBuNPZ4DmIoo0lAtPW01unSjWqgL+d07DAbNUyGBfm589f50gx77sG+Hp068pneh5Y4KnM1TH9J80rwDHI/8P7vVNtJkiqwYub9iyfxd6y9UgdOoOxA0BKO5T00PFKZwFf643GxuifBZb546qDeZj/rn16qPdtK5pttUIVdBtU2MOI8PC0cPCtrapVEv7z5h/cUBmtWLYeiG9UcWjA8hC5AoJm/yYIXtqa0trYqLS3NoUks+Ohbf+mnJdj3+m0/ZJ6oqc8dSjiF3Hst+7Sz0j7Oofwfb/NYIvFQqZbrNqIr/HyHR4E0DGF/CpCNuoSCBSa8/sPPpVMXUMpQbJOZ45n8BGJt/peveiyzlY3S338Oox0K4KV66Rna8fwmrLiMZ7PS+rYceVpn1s/DZxlnzKt/vwdlGuPfu9Rdkum5jxl18rKl/yWLttG+t/lu+rP8oPj/ux9CKFEjvYlynINiCI+BXwVKeA0iX8aVwwo22XuLYQj/FiX7iV3S/4RSCnSsw0FekQ/r3DqUYBT2T89AILKGwwCy8XEN9t7+nt/Wp1CKa5J3YQt21vaFX8AbImA0tbbQo4R/eJ6DwHbIHW7R17TtX/2AQwr3YJ6CP+kp00zstVuxDuXnaxCK0V+//Tm4sU0anw3V3uefUMxcv17/+LT6vv+Cc898hT54YQP+RK89m+OYTh/ar1r6prCwQFP3KTS2UQyCZfrOH2AUWrNNo5BimKLSBvNJcHKRfviDV6GdZYP/8hin634VZyU6S6ovjzA5MYK18waKWIX27NqhgYUxwrZxj2K5qm3Xmh1P6+W9m1SZl6CPLl/TbCrMaEsi9cJzLygtbEq//N17HGrGfKnynu8EwYa0Ys16vfD043dc00AoeRUDXJRGcJK3bre+/+wO9TTd0mt/+FAdOwvUNxWil3fvVTb0zhMD7XgNCBvA7eZriYyJ0ws/+hu3CLeDDXwU5cLctd4yM4WVtqVJ0Vkb9E/+9mfqpu4PvzgOAH2ZKpv79W/+t3+rRPi8Pwds/jyWsp1s2r6uAaaUdLbW6/AXn2t50SYU+yNO6ffWbb+ryy4rOjVfzz3/rCKDpvSf/q//A5r1Id1GKU1GWX/2ueecW3kp7mlzzftazM24jr5cvQVaZXBYL52gLbhdbBy6QtvGsUh+evC09n7vh7BnGRZ1lBLwDEwFYJ1ZvRrcT4OR879YHYZOcuyzD6DljceqmO5wvBfeKZwDhzFOPY4rvL+rmWd+FwtZMMrLeuDbSlxowuF972guNNZZthZe68vrqJgEbXz8Ca3Nz3SHOtv875ZAPfHKT50bvhtL9RRkEbahp+ev0d+u2oTjYkxVF2P1LhBvI+a2nLcg373D17/yhL3cuAgxRl231oFnequNTWBBsYNo6dVr2rDrRb20e73KLhzTF8fPqqMwDuKAWO3e+7TCA8a0771374z1SBbnBTd4wEvD6u1oqebQcVq7dz+mtjEsKveV0LBIZeM5y6ssnx+L3VhCqyHN+af/7l8rKXRcb7zxNsaEOq0ryLrv6m/+08Z6MxB+J0+cYW1+HMPFsXkF1K6yMWEW0+ikHD3z9C6MWAH6u//8X/HCDKt/fE6bd+7RltW5mh1q47kxHNjG4WMxD9dwH0QhH34CZjp0zyG9910ZoJj4JP3jf/GvIAua4HAYr/OltYxtwhLwEqxZV6JBlOBHKWbVXbVhh6NcHqdvZ4baCSixWXPvzAlhvS0sWa3nn97qUUaxuN7Gm1e8biseWA6Cg610sz3zvdc9rE3jsDaePXVc1R1gpm8oduEtX7kGpXtFcYl2cyiJx5Nl4Qe3BqvxQqTpsSf2auXyFE+Y231hM1+5z8I3bM/AgnXm8Gcc9G67w9bYffuZyXbzzr3aSF9O0s733xvSkphADTZXKm31Tv3g1WfU31yh/Z8dUB008kbqEehPGxa251t+7Zup4REqtTAEDuWOnYz9+yv9bcqWrdHNbShiV7AG13sUOdt12julI9dgjEMx7Lt3XXloS8zlbtdkoVyCx688fsOyKAxM88WULLgI1NtP2EMG1tNoj/XV2NTMGnm2mlABtDA/9l9HElFLu1dno8TGYOXkB6xwwXjqhjrzAFBtFM0wrKW0BdpyR+JhRjYLRTCl0QgrvOET84314YUp0uQsOspik+l84bVZoKu6sbC3S4ewFl9t4D0OChko2xHIwdpFyJLH6u3rjj9fwb0vTNE36+7uVR5l+/45bnuTGeUsXMMIMowPAa+JGmjfGH30GQr5ZdrnPTAZ7mJ0QgYK/OMKQS1uaGhUwZqNys3LdVTPV8+d0dGTlwi5GXMxR/c8+71N+5P+NQFPe3XZBZ3DpbAOi1g4DDEWC2pxol7FpKejFVrlj2A8y4HNCPpQ+5wTRGdnFwQG0OaiCEVHRRMeEqQBaIK91z30QdjgjTzgIAxkG7dsggwDvFiLE8Nq5B0aQUFYzLEGD/b3qLOr223+A319isVdmwZN7ofvvKt9n3ypiDQDoqdD/SlMfDvl37h0Rr///evaf+A4IQZ3n9tO+D29PWxURsgQ7uhdAwl9CQhLUCFkDce++BTL2BkNBSUoF4ugzxYi2mi02haD23DrKtz1H2oiMAqyEAbcnWL0vNjTsVr2qq0DFrS+ARcbOUa/LMFV2tLagjy6kNc4ZBV98/LyXv+g3wNY9M+ePqPR0FTHyjSLVXgMl6nFnHpLGJvjKNbqNogVemCSM/zYwdEJF7vb21qtP7z+ut75YD8Uut1+JYSah8DiSgdRML/49BOdr+oDyL5gPkZzFuvCBJjUjTBVXT19WH/43W/0BzwpFfWE3IRGKD8/j5AQFqRHKMbaaB6Hm20TKinOdSQvFn87Rgygt1i/WBxsc9V1vfHm2wpNyFYO7jkL97BY/v6ORlW39Ch/1Xro7L+qzHnv83W/g1BMJgjzOPTZx/o98jNr25Cd/OdLgItPbsfjsH/fR+ocD1MxLscI+sLcyBbLWF5Vr7xckr4h6fG1mDu+vuKyDp++DjFAHoreEvpzEsxvT+yx3cfiR/v6IbmN9zC3RRODfRtouGAY8tKjbsPs9YlOnLqo2ThIDdgwFsbsP7AdzPFmaDjfe+9jFW/Ywp4Riudn1BNXvuBCI9/JyslXCtTCnkMoVlni4KbnAh2kYSQEHkZrPjDQ7/NYt3Wou6XOzdGguAxlwFhp3h0b64aba8XqSocwI2CkRfuYh6eOHVFS/jotS0yCMCdBZ2FzO3jwiJqHAlWAJdPiWn0qKN+jeBzefftthbBuZjOGTDkz5XrhYdkOkKFYz84f+1z7vzyuhDT2C0K6wglfKFiZ54gzfKrvvi8ZLrnFPU/iPXn3jddU3j6l3Jys+QOGfd32LCPSuMnh6PXXf68vjp5VNwddu25iuEvvvP5bVXTOcFi897r7qrrvT1Zu7nnm+CE8GsOEvawBnpLDAPuFYSN713VQxN1Yr7h2QW+98br2fX6QsLQx2hSs4V7Idz5+X2+9855KqxrvmZ/3VfaVP+0AXcN+drasRWtX235GfDP7ie1nXlx2W4NM7hZn3FBTrsFJoEJ3bmeehaofb0dPT7eGcFmbt3R4ZMz3/ewrrfn23/Bx9D1axcwFF4tLfpMCzDy4oGAIUG6u9CPWvNusWV+clyzEZBuW058yjmZ47wSW0SHm1ffWLrjwIS9NETLiAeY2gxOrLr+ZO2wqdy80Xa+7j3CMJpR0LKD2nY38zsB63INivO84iime0MJlWCV9lJAdZmGpdfHLdsCxgxJrlUeRpkKThcXK9w8RFtEsvbQHhTHKE0fcjwJoyt8TWKFTH2EvMqXefr7uYGWW8SHqJTcJWDsOFyj5eNpVxLO1dJHiiAL6yg6up80mlz+mMA9QWlDGUfTvOyi625oMTOk1BruyHulnL1Inr6F8F+uxklDG3z/K9bxv4Rk2qW0DHerr0gVioHomQvXU3sfgpY/WY8QzVhHnZ3U29153sY/2+s+hzLKx1lURn9nXqyMHvlRTSwsu6KWcgJ9RcW6aUwiM5OIWrEKTgX3qqrumtvZ+R529ZYUpbR5FwBYWX0Mg5p+bwd7e3KQOlKyxcyfV01yj6aWJKic2NjuDmEDuuSQ0Utu2rtfhU5f1Xie0zLgrl6C8TZJgMzIVoMexIgw2lauRUJO+gWEsh1w3X8EDXlgHoGDvevIFzWGdHMTlfwjXX3bBKq3Jsdg1BhnFKfT2Xbspvy3WzpSpvrFZlWzYpOCJPlUNdqud4P0EI4qwiexjsQ04OSNX23fsxFVaoabOPhj2PIp8IG3LXVmkmKtlWCreRTGEzGJmqQrW4w4OGtaJA5+6daONuLa47BLfnvlOu2bGh+nnVtgSp/R5Z7VTps9duKKCAgvTYbGjZBdt0I3az3Tky08dO2MzZBZGRVq0doOSMg0PeFpffrZfcSkZSoTVLMqoHH0s1q+Rscs4+GzT7TOndKO8SquIF1QoN2BRnJqeIMY8To8/8RSb2JyunT+js8RnrYDu1sDrvbHDPlY3/7VZ3H23yis48Pfq4BdfEG8Jsst4kDqf3q2cO2Eo1seWoJSUmavHdj6mg0fOQOuN0guDnx0WrhNLuDQxGw8RSrQffW2NiCasYu8zLxL7yTpQW8rh7XMl/OOfOHp1byNNNgnIdDO03ieA+azA2rEsNgKPyLiaiINrGQnWj17eOB8u5L3uQb8tCbOtqcHFYJ89dQxc8z7m3JCu49HZBnOjJ9nL0mE965jJwIopL6OQqEyAl7xl4wb1t9UREtKujt4hRS6N4zpfNpw5wig6qa9fU9fPq7e1VmNzYTp/JVcrCYGxsD8rFo9vVvFgFJM71dMez0bo/uYf+8/Ghz9lnLna3tWjybZuNVbMYWDhQM9a8pNXGUtsACYbyzlYEp2szSvy1Ndcra62RtZD5vjQhFat36z0CJH7MKDWrgGlYgkKJbnNlzKH5b6OMRYG/nXNtT4MBCOagqp56/pCnhUCCncTG29YRFdv4GAwBZNfM/vuKJbRRA6L0LPz2aMWU4TDIuO1dedujR34XE1Y8VYXUzfj20rw0gitxzqeVUzS5ViP9nOoX7ZsmRLji7BEx0OlvVvjX3Jda5uKi1fOX/fA9lj3EIpRAfFO14iFgjSqh2cKHrqgXVvWKAHGUetPIwNau2W3cmcwnPR1wFR4TqGx6dq4PE3Pv/AyiZsTqq64CgnPQaX/kx87BfWB9d750Paz+upqz35GqEcLYQqThB/VEOe7Oi+DNd8jdQs3m5oY1sVz55WZv0UrOSBMQ9JzruwtfcaBz/bxCSxwljDs977mS0Mf8Tu+zLhHvLVH+TSLHwcGl/SEQUi2HeB5cxtgBAfvDblYRlE+r9TiLsRy+sQKaV02741gwWxBUW3zTwm2gxggFmpBsbRkMOYYCSf0EwOJAxmnQOpGYb1Zz+coiCXLPX2YiNIbG+Ox1IZdZkFFOVvBe74WU6RjUf4aUSqXU58lemHIc379foxBRg/MfqwPT/A+e3I2oRnWpi7q+fAkskIJzMdi7qvSvbBdFvdrhhf7MXlb4p3RQFMlyojHIr4izXOwICRHncghjD549yjWWMYwRE+eddAzlhfe2q/X7gBC3UbhbElulqhnfW/JjpYoZ6EYZm3/BIsvuoEykc8AbTYLeBZKuR06gs9gted6K+a2nBgf0FHiV2u7p3BlbXDuy8nJUDbRbpcANM2pPDkt28WcLkQB8Nzhv8+/S8h6XrPpMUVhSbVN/jYKSP9stGvjODGElsEeEZukZ59/iYTGCZRQTsrDV5WTm8fhC0tlU7dLOunHhTGGEKOxYvi8aLBIF67dyOKX7DLiqwLH1TodpyRcD1O0ZZKBEYlFqnj9NiwjiapraoHmFfrfsOUa6u3U+BwUp8XFCs1dpvJf/V6NfL5xdf6dzeUh8qSf4UFT8doSvjiHBSBel08ec3FiY5x+5m7jFsS9ksAJs5kDwhBu9BGs1LfZ+CcGOjU8G6YsZLAsIo8kOZJeahtJ5klCXQh+SMWejy0m1yxiZvHJY/Otb6hXTVObdq2HRheFx9AiUtKz9eMf/VAV1fVYfJepmfg5o17O2LBCiYRFDLAYLVnSoOT8HN+e+U7LliLLJ3Bv9w0McoAfQgmtVjYuULPgWPZ+AAp4PJPtqaefVWV1DbGSJLhwUIknGzY9KUGpGTNI7rZqr5PkxKl42jJlfSwWA26IHIHBYVClZmkcN/OnlxqwRG7XGJPPQm9C2JwjiRNMgpY7Ct26MzlBNweRPZ8ZcoMhRphVyax5phD7Ot6Cw6K05fG9Sl/J4sYm293ViRKfxqGacWxtwlJrm6PN5RBIQ1bjJr5w6jQej05X3zBkKhdxT+995SeMURZFP0uIS7ZZxbi6rWTWk4vXPsFChucDq6w9U6TR5ZKoEILXITs3Rw03o6CSblVfToK6Gip09Ow1bdn1NMnTYSigvi+ANodzi9brxYhk53avqihzcf8pUF5PMtZvzzBmcU3Hsqn04/kYHkrGQj3Koh+soY4mTQXHaHlOLgfMBLU2vUnuTJuySSCBLNKHEkCs/kq99BKIKsQ0t0QGYJUch6Z8mQsFGgFxwzL3DR3E+tT1K/Iw9AqXnc9z9qCQzgWPs2dMKyo1xq+xHo379Omnn8ayN0xCaQ95Gg1amZfJUAfVhoOsIZQ01twiHIJwhZWFWsFh5+KV/6Ra5mPX8DTGrjwVZsSTLHlTZcyTVSTMRVvmug8lJDJGL778V4Ta4VFqqycR8waJVhkKxNozMjLlrOnmXbA+T0pbrhVFvWrpOE+uwYhyUmMZE4xxxruTCwcSOyD4WgzNxM2V2wEqKF6l5uqraiepdBzZBt6e8Ix1rOxZeSuUhtVtbmZUZ44cUz+yNkv53G3W5lWrue6Kurq72SOZ4748tg1Lxs2up15QH4mvQwN9ujLer2CbZ3gZJ7CGG3tgOHHwabmFjjVxsC9OPYzvTg4rSwrTSbBOYz0g/yF0WqXvn3HP4etz2362auMORaTks5+xoePN6J6OcLkUtrYZ2kQw88G8HHXlV1WPTvNj1tT4+FhyTUL1/VdeUX0zBoKuKFXXd5ArFXvHM+FrC77b7/k+AvxtBxsi6yubDOENKKJDKEeNWB5j0czeQNHZtpr+53NzXPWwfnby4gUUtYo6lCjeN+uoCfPZnf5VbGPa4mpPolie4feZKyS5bUMJo47/cz9Jd3/jqfdGM5boHKyPnEgtNOJiOb+5tqOXHxSzwmSPhdjX2llztL1A+v1F7s9ad7NB2lIoMU/12lXph1toC7/rx6RXeXaMXHa4EwdoXUVGP+U5TWmH2l3LUIj9KXjL1c7zdXN9KzIeQqkl+V51tOOV7SjXMSSi8XzB1NfBGH6CZ34dWQShdLIuOFljGHHhEX7sA19polncDa2nshV5T3jaZMmiAxxkvmjB6r8exfs46hFK78okZMNnFv9sschHSjmk8N4ISjuGXrcoW8Z5B8HSpdWtuBknsC506wJoAv/in/2tU5quEctmG+uTL/0QuRkU1lea9N/ljVDckHlFKfyscYrBKIkaNYNLlE4Gc2XpBZIKwrWquEBbdzzuTh8D7TVq6BpWfkGRVqQEafjTf1B1Y71aQA0YEUqSc2f6+HCcArPzC92PxRhHzPRq6WgCyW2JGuhs1qlLlXr+ub0u/jgEBSaZjNEzJ9v1o3/+E001Xwe54LSulFUoKWBQw8TyxMaSde2jFC1WcIxDyeefn1FG9nISUbpIUpuh7hjnqi9r63ExioXFq3X8g5MqTwllbNQoPDmXDOtl5OmQUAI1+0rcIe1Y1fIS4/2y2lgm/KFDh5VTWKThjho1YqnaunoXFj8OUofPqGTzZpQd4mDZjLIyU3APntHydXtcv4z0dig1k+z188ec1X5LyUofn9rztSjiEDduYQCjjJm7FHBh7gAAQABJREFU9CgLTz6WkCW4uS6cvqLE3HWEZkSg5pIow4n72oWTSsotUWzEEl27eFZjYgOLDVY5SUO71zzp3Lm+NsASYs4c+kwhSZkKnRvX2bNXlZ67g7E1rSsXryooIl7FZJumRt7W8bOlyk4M1PWKBhU99j23qfWz2A5y4AoDOaOfTTaB0AhfrWWW8FLMoavYLIxTo6Bf1MK6t9zJuezSaU2FpyuZ+V56o0yJGdlM8Fa19I+qmBCBaQ6EpedPsA4RdpOeggLI5PeztNSXqbyuVxmZaaq5etEd/qIIqWgGaaS8rktP71qvzz75VMmZWegbIClUN2rz955ibl3SkTOlWrP1MaUnRBC2MOAUqPshzr6pOcGEK2XkFrgfUwqicaW1TtSQqJSilpobJOtOKCcnU4UFK/UmLvG85CAOdTVKzCokcS9RvftO4gmqV9TciHpI5NyBwuCxHn9TjQveZ44nk8xmP1ZuRmCBq+rHxQ7ixkCXDh2/rCee3K0IQqmGBgc0iPt5EpQaOxxYxn56XLBOnjmnvLhpEvWmVZKzfMHNH/zSDkcWX7qVH8zaLpTl4PkyFZAFfXtsgFj6SqXmrVJMbLyOnbikxNhwxQQMYzkM5ZCTqNuj53X1Wikx8QXMzy6tLMA6y6HLp+KssLF6bPce9/UWwmsGBodUCOJGIPPs5ImzSs3KVWJ4gA4y59aXFKns6hX1T9wmMT7MJSr2EgI1NMTaxlgfJJEnHiuqr8aTaRLDruJB6Z0L1/KEpSTeVip/y1MouxPOmxGStBJP7ixoQOWKTEpX4HCbutFrIpYGqvTcMQ0GRCgzPhTFvVJFO3NRYH18bluBOUSv27TVPfdANwmw3Q0KQs7ReIuqy2+oc3hWex5fo8MkGybnFej2SI/KUTgfW5eOt8NkEErIU6RuXCABNjXTWWN9kjlfCuUAmVe4hh/+4FnHCT+q6LGQyjhVlV5U79RSt58FTI/i+Tyo1dtfUXpqstuPAwgzm5kNBJwgDiv0DaWtXA+SRxRKsK+7iq+tfPTvBf0His+X+4kOYZBh1ShAFnOaE49lklNuZiLJUChlGfw2F74pQhgL9NQGFM9UXiObtn5axPjYtZYY2wyUUV/Hij0I11uiq7nTh8a4HsV0Wz7KN8oWfaYslNtA1utYXq/LRuk0zzPXGGRaD8ok0Ht6EcUxl/bZGPW1q8zDgp6hNBS4KZTB9VZvHhMA6zDrmzj4ulO+tQPdzsXlWuyweTwNws2sqGY9tbyMaK7xp5gS3DHEs6UT9oCMQXxyimQaSq7JeU0OYxcFOJp7P42cs2iLeW/Mcm1hHHYgxTDkrNDmVnnUwiNgXaPPUcSLWFdZd7Biomgja7y7wuBAzJIn7plDuHNhLkdvyEdpt26wU/HLyD6bNissT+PRzyokIkmmNBnskf1s2rhOaSmpzlq5Dsvwlu07VcQCbDFgvlqvrKrvoixEhzD8SFfo2FHi8MJjEoB2S1Mn8XR9Y1hy0lKIx6OzkLeFA4wwAJdn5yiVzPbU+AjdBK4rgAzip559hmz5RL+sVN5ns/6YJgZrCXBYlgk9TeD1rdo2FeGGGyVz/CwbYdvAhJ58/ntak8+mimUhGey+GqxaHWRa7n7qWW1YtZIsYtrpU7HwlQANdLeqHBe5be5P4oZbsyILxbCX+P8epS7PUXrmckUumVVtTa2CoM196cXnUEqzHMxRR0s9B+derSPJ4jGyKCNYJHztV4eKMdzHJnQNdIppbdy2S1uIyQ6cm0IJq1D68izG+JyuEEteWt2M63CXdm7ZwDhdwmGrWodPntNSYtD37NmDvAy+yHwpj1CYVANssCsLCvAAzakOV2J4QjqhHWEOPqkUqukUNrAXn93jXJkTo/24OsuwkrRp/c4ntY2YP4Oz8/W5GUEkAI5zj5uE3HQpo2CdnidsKJLs3tqaGs0u4VCGopObk61OXNNt4DgWY9nZuWmtZkYI2Tl+mrUSLE82t8CwGCiul/msBN+Vjg3kORf3tywl3SGKNNdVoXZyiAP+bho3aen162rtHdPje57V5nUgNOA3qMbav+OJJ7GG24HHf3kHYAFsa2nQ9RvlzJckrKPPg+oRrwG8Gk24vIqL8jWFZb7q1i2Url6t2rxbT2xbp2msIl29/WonDrwWxb2xtUPp6ZnsTWjsj1As5p94ExWvzGX8t6i9d9ShvaQxroNRDiqrahSfkUef7wUFhPAbkkPqawmZGp3SNpPHagub8d0Cv7CJM1j4ZpegmJHwGEAcoVGZr1iZr9vI/OzpE+odAUmCMTYbHEWCMdbnnGyskRUYTka19fEntB4ZhVocm98FayeHviFcvGuAvpqZBAKwvpEY3Czl5eU7j0MDY6AHN+Bz33tFa4pWAmWZpKGeVgd5uXLDTu3dsREPGVBij7DxmJt+Esru9Kwc9vFAlRMuEBUPyyhGg+62Rgd5OLc0Qbv2PAkUYbIGOxt14PhZ9jxio4mnjYhLUqoZGHytm++Z1fVWOag9tU1auW67du/YShjLEmAuq9izzNgQpxHCrAwWs6N/Uk8995LWFKIIkINxC2XVritcv1O7tm8hLjvcjzl+t3Ms3MTGW1xKFjCIkepsa3Z9XMAaPsm4vgkEXQd9u2E7a+jm1S4npa6mShWED0Yn5+ml55/iQBLj4vHv3tXHV8xxw2FfSmjHCuAzO1mv+9Cz0lKS3NgzpKanntjhwpFMrgZ9ePboYVXh3SxYt1lP7UJeYLI+TM34U6JDBBCfZ3ulb2WiGX/2/06swS99+r5ZBi3hy9zzNs5sT7H44IUJZ+bCt89sn7U4Uqz6zq1vUrIQA/uxz/0ppthZnabYmmU4lB97SlM+LTnL2oW3wt3XexjDc+ausXoshM8pwH7Wa3XY85hSaYdbb732t93Kns0UXSumNLu4Wa6xmFgrLpTjzjN73vHtXzxa7r52f5OVHS5MBiZva4e3H+wzW+usXgubsH6wNltb7Brbg/x85HsaaPeyg4+FQPDS1W9ytB/WKjY9z+fWN1aR1WfjwRmRTCnmIjsUWPsmonEtp/5HzQTG0G9cPF+IaeWhbNh6h64/mfTzt/kOXvSTBGNu2MLCwnmyDBO+EV/M0CGGGzlmcT64thbGYc5yQplgYFhShcWPmjvVSAQsgz4MUPMwr0LtZ5vNMmv3miPcwGRkG9YISUMxWD8smWUcF53NgwjCI0LvTAyXwMdJxsIaLGzCYuj8UQatTnPNTzARXPwcLnjD+jUIndtUFoQFzTZcc5WPM+ksVtTqD6FPra1jAMpbm5ZifYgw674fiqi59g3I3g4dATxzGCcuI20wRWmQmED721zeY7grTN4RtM3i02xcTmI1t4QNi9G173njeP0UOV83xWDWWZmsbssetzERCGJGCCf8MdA2jEDA6omEWMEMItZm21jMjRxOjFgYySS+WmKtfTYPLEHIkp5mmNSWVBkF9moAfeHIKLCgGRmEuXOHcWGbfC2RLoKxZTjVwyjsRjZhcZRm9bFx6k+fz8tovj4SdBizho4QACyTwUfNUI89o5GRRPKMRkZi49GSNsNICLA57bMyMl8h64obx7j13VgKds9tccUmYxuDMWBEG2apZ6xDwnLn+Sz+fZwDooUIWLG5ZolrNh78LiZ/+thCCwwr1wgL7DkdiQPPPmrzgc/MeuwIaHhWcyM7ghT6xsh+jMDD333O206bN1ZfEJudjTcb69b/nK6pw5M0bN+1sWXhEOatsKQquyYcbGoj8Hg0y5zhnM9w8Bkl5yQSi6gRhhDWAzSZWfXdMyIXJiNzjbWEtc31F+PAkU3YczMG/Rnr3me233avGfovgL4LQc42f42u3tYyG1cTjIElWNgsIdUO8hauMUgMsRFsmKxM7kYa4eth0+a1Wx+ZZzZuDNc7HNkFEHI0wXs2x22sW7tc+IONdZJxQpCFwWHaumTXOZmzNvgTirHwuU3mhgFt1kM31pHxDEpGNLGe48ByeupmXEHmYXPZtYe6p9h4jVDFxoYdOH197oV1u/2M5CaToYVX2Rynw13sOdkdbi2JZg54iThsTR7Ey2JjLZQxbvKycJWHFZtP58+f18aNG906/bDv/zGff6dK8B/TsMVr/8eWwHiURwmeXYIZmQn0l1C+Vgn+S2j4YhsXJbAogUUJLEpgUQJ/JhL4UyrBD1fJ/0yEstiMRQksSmBRAosSWJTAogQWJbAogUUJfFsSWFSCvy1JLt5nUQKLEliUwKIEFiWwKIFFCSxK4C9GAotK8F9MVy02dFECixJYlMCiBBYlsCiBRQksSuDbkgBpUt9tsWQ0w4u1JCxDC/AWS6KyhC7Qclwh/8YRa0BGInJ3XKKXJaiRG+NJIPNe6ONvI68BVYsEEE9y3f2IHJa8ZflW4MQ7uuFB2mGJdDTLJSgAL+nQEnyI4Z5vkSWjAUfqEt0sz4gE7/m22/Na8t2IJaRxRQz3t2e1dhqcmKVnmHwMJ/hREiQsIc/uZc9r9/Xew+q13A9DyrDQWkuAg6KeQHqg6KjX+sXe85Ooaf6Z73/h6jPZI0tLevs6YAHrd+BxCdxH/pY0Z39bf9CWGNAzvGggFlQ/MtSlhpYOklj4Ag8QTLD/ivw8jYBP2Qur1/QcQPjLkmFFSiA4/zsfzvc/7kP/Hh0iA72rV7NAo6zMzfrK9y2RrLO1ib64Da50LM8fAsxUvXveJSTxJCxLUnrysvn+/MoNvuENS5ay5In6mkotjU2CfCGBrNy7ST/DwLZ1w47WB36mQbplZYHYAIyLjRuDVqurrlR4XIq7LsIP0gZvcyZI0Ojt7VXnwJhWFeSRFMMgo9jzWoJKY2ODS+AJDQemLSXF4eUa6H43fTpFhmQkNJxZwJ1Ykot3LHvv/bDfhknb0ljnoNASktNgi7q78NhnkySidcPYFxy9jAxtIJKAEjNw/46uPpe8F5e4jDYl3yOvh9Xp/XzGkm/6ex3V9fJMECEMquVOsSS0TmhrO7sZD4zb+IQUpQDLEhRA4h7wbq2dncyBYGVnZznoJl8j4e2ZBnqBo+vsISlmUkvDI5UBXnAU2Kv3J7gZlWxrays4xbBW5eTC1NgNlijEKiwg4VApZy3Pdqgl/iZK2XgbGegForGXhCHuA2SZtxjFbx9Yua1tPB8LThzzNWlZIvN8Th1tLeBID8MuyjhISma8+Q7J572/jakxEqHqyYCPSc6CmCDWg7zCaj7HGlJbW+MSoqxuG0zGkpebnQl1NIk9JK3V11bfd533zr79HhsZUncPWMATs26sexOOLPFvkoTQhoYGkqImHRNkEmM9lnonSChq7+wggXKM+RflmMxsj/K1z13LkLn1fUNtFYtmBCRCyfOEH3PAl3W0t6kdZsQZW1iRRRA40tFsbMEBM2rr9kDChTD3k5B7WrJB8vhYuHd9fR1Yt70umdeuysjOZ6wbzrElLZNAxvO1tLaDkjKiYJIwU9MyFBE8BylQJzB8QBlRrO0xzIE05lpMFBuiH8Vka2NniA03ISUTIozw+cRKS2CzMdfc2ky/jwELF6+0dEiKwPKtb2giQXOS9+KUnpGOzuEP+syMI0VpAWfaEh3DImOVAhRYAljQ3jXKECt6gaNrgwDF9rnk9HQti48DHGJCHR1tjnwoAhzzVJ45lqRNv/ob+Zhsh2D4a2lpAh0im7qjkPndfc/Wn07GVQ/raEBgiHJWrlQYyXqTrMeGUz3F+pLh0IYezf45v58FsJ/l3d3PboNQ0t/X49AvLOHPEg/jgMRLS04CvaKJPvckhCckLAMZKdklKPvR3d/pV79TiDTGqcPdPXoVvGCUsIKUu89iSlhLi/SHM1JDBxTGyCgFmC76UCduQJnMvO7iPZsbpjD6U0zBBSJUn57jKpQqoyU2xdBbSBAV7Jo6U8kgBUbMYMVOXvcQdtyol4A6BLqJ9gB35hAcvBc+4Lcp+wYPdrKMtnO9QZax1gmYRFeYG2pqlw5fA8O30TJ1URBpU18vdMbUfZV6SS5l40U5vDumH1Dj3Y9IihVERTrIveN5HoN98yr9pnjf4rNTFWB1NrDwUCckXMAxQQ9NO6/zHgg6SiP/zODpvJP57t19f8Wa7A4ehvX8KX0O6pFA+7qnmMILPKTePUF9wKeF055G5GI02VVttBtdyaijAyFMGAt/EgUR6k34xq+C93i9tBTsz3atBtLnHBSSJ06d1s3ySqdwFBWudIrWH9P+exr6CH8shEgLsUxoNsDayuuOoraZ8bB9fdE9d7Vs/SGU+eMH9mn/0UtalrYczOQJfbLvcxbwNl29ck3dMCwVgYNpWcc+L5h0hGWMN9dW6M3f/0ZNo7CiASNnFJZW5ozW8+p5ff7lIYgD2oCuuqqIZWC7Ag81C+ZpU02FjFq3ZTwcxd2uo1P8KKZodbTWQ138no5crtYT2yHvuKMEGypFa22ZPoLZq66+SZW3KjU8HQB0YZQ+/+RjyA7K1QSofumNWzDNFXMwNEXO1yf3ZKt3t7do/wdv6XxZnQqKVjlQd2/zTS7V5de177231TmXAK4r0D63yUQ+cRh85CrVAg9X1dCmxPTlQCoyQP0ot8kANyD742D2vr3vMNB+qwCGZxLcKUM97Trw5Re6wDOakl4KY8/KglzHIHb0wBcqralDcelWWnaO4sj09vWpDTLJQOpPnrmsWg4vpcyTWeCaMlGw55ngnMKEYoTi8N7bb+h8aY02kHndUn1NJ89egX2xQmVlNx2UWzLEKv5k7HsOFiNgsp7T62+9r+ngWMf+5n3uqclRXT17Queu3FRTbbUuIWc73IXMjuutt95UPWPwxvVSyBvClYli4hdrHM9liCt1zLPf//bXGgxOAYow1aMEsx7NMZ5PnziqispqlNF6VQJTdbGsVquB9AoFvq72Fte99hsNw5iYv/wObKG34T78NtST5vpKvfvue7pS18dYXz+vjNlYq6+4wvpl86xF5beqNAdbYyYbXQXz78jJUxzw2zgETGkVdLRGbuFrn5tSO8Vcam+u13t/eE03W4a1cuWKeSXYECBqwBk/f/GKmpqaVH3rps5dusKiu1Tl5w7q1PUaDk7dKO99ikpIVRpQYT4XZGrz5+CJcw6FwQ5VEYnAvoH5aagDpqj1Q+H95cGjqq6pUdmN6+oZm3PU0JcuXXB90UhfXIHRsqZjzK1vMWYx8rVw/z5IKoxE6cCxs0oHbjCZueo9uE2AP1194yJwaMi3qQUkJGDU0lNVBxHN/gPHVM/cM2i+yDiMJxy6vNc9rHo7UDVU39ShI6fU2tKsM+cuKCw2kTGbOr9GDfZ16RxryfFzV9XaWA/vQQu40MCzAQv37rsfqLWjQ1cuX/VAuYGp6hcsIGN9eGhQN6+c1dvMm9nYHOUAfelVgm0etkEPfuTIYfCwOaRw6MwAez4EiMibVy/o4IGDGhIHLmjD7z8cP/TZkbntZ3VVpXrz7ffUMDCrHRuK5y+bmUDmV47rv735KQe8IQ7kXSDVBILPHKx3oLmub2p1MJAtMKPmFQC7+RA4wD8lRJqf6tb8Mz/0Bf3FKVjaj7JzEqUoPRcM2JK7l5lSiJzUjgK3ZSX4wShvHJbE/qCjfP+F1ShpvLbP/+Ue/07IAwPSe4dQplHyloALvIJ7G1uZtzQ08jnt6kMRX41ekoLCW5ANji11GVnGO0elVWAUG7SZr8UMlVdQ3g+hXD9P2y9Tdyv3+zdPetpup8KWbuqgLRU81y8OS/+c5wLb3GHojvLMrx3hWV9A6V9wWPClfoxLjoSihvuv4HkyvMo7fWAK8q8+B3N5G+3olz44jtHgGb6PfLZtQeHm84953hUZ9AF7PobZRy526GFt0nsnIR/hgLM6T8pLuvd2hml87CKHgcv0SSoHASznB1CY8/M5r9D/vz4o/duXYN1DTgbZlJJdqL/92wwoSut0HjrYkLQ1CpoaAuNyWGs37VAcSuPvPjii559/TlFYOR4FZuneFv7xf5lVzGBpWuoq9OWRs1j5Ax0c0sI724I1igXp4snDqu0EPoxFxqwLSyNT9NIPfoTyEqBLpw7rHNivo5MvArdnFouFd/jm19OcJLug1fwM7ngjxPCwI90ZzLTN8DxPnT4PU1SBXti7RZePfKTjJy+g9AFVNj3orgvFmmiwWQaF43sxyxQbYA+UnWfOajooAmi0fjZFBuKdYjibZ48dUmjKaj29Y7Xa68v1/qcHVJIdrQvlrXrxey8C5h+mj976rWpaehxucbCPJ1GDDhrB8n7q6CGN3TYKVfBRzT2yoJhiUl7Kgar8lrYXPeUgxcJxn6zZ8rg2PBaq3vYGHT560uHtroLq2ddi1ieru/zKOTXCQmcsgTN24ltQ+trr1TEwo91PPsOhc6n+23/+L2rr3AVxwxVVdIzrJz9+hQPsUpiW/GPwMii6pMx8/WB5IdbYHt04e1Blt2q0cx1WIHkOMA6qCEKQw5/tx9MGlBWsVwZbtCxzpX6Uvw7PSqfOHdznFPQ1+RkcWrAM+FCc1Q+ZNqBMnrxQ5vp/AnijhSUQSMBCGApXrg/SFEQiv/rtHxxG9O2YaXVNRurf/PyvdfPcIZVxGFu/fr3C7j85L7zZfa+nsEC1sPF/8ulhB1k1yRyah1Q0pRLLwlMvfB/PF2NjsF9XTx3QzYEI1rlZGY7xPnddONBXC667r46v/ZMxbTI1PNrjkDTMBELFgYeBwT7/dbOanTp6RMtW7tKejfm6fv64Dn15UGtZFD/4+DOtf+I5lRStxFgSrgXb0/z1D3phY2uwvxuq6i/BdgbykPVk2mFPeq4yiMDidVuUX1SCh3BG1SiAR680gEMfzr43reINu7V3MxTiwFkZhJhfhbXK5JyaXaRXf/Qi0H/BHiiwO/PUVHnDkX3xB6+yidI/kIf88qOzemH3Zj37IvS9tH0EtshP3vqNolYU4u31jFFf2uAOXGPDHKqOgyc+wIGJAz9zfF7qyH8IT8y+fZ9p5a6XkHWm88YYvffRgwe14rFXIQdJUPnl01A9X9LaFct9guxybWM8pSzP01/9OBPj2Jw++cMv1dTYpGmwxr3ey3bW/MqGLj314g+Ukxiq//z//L+qqEjX7Ei35mKz9bc/e0kn9r+hm6zrRqm+FOu8r2XSKKMrSnXsJDTjQPm5sW7eDVdYe+nX41C/j0Uu1zPPbIAaPBo21qWaHGJNKL2qqromReVsWjhEfarau5+11t/SgQfsZzYfYlNy9L2XX1Z8XByGx1l11FxVU/+c/tnPn9dgR70OHT6hzv7nMWyGsL/7uKH51MpH/xJ2uO+mMF7AwoQl7GnpyVUoo19Tk4mA+QPenMdqCqyfswA/hcK2uRhK4ywsnA0ox/Szt6t9aS3eB/1gr/Q4ihXema+U3BzpJ7shjfAefmmIKeEF6VgvUQRnGJebUQrDfdsH3P1N2TyH4rt3K0o9z7ueOswi6m07nmbt3ig9Vsi9aZftj6xTemyDtAel2d4zEVnoiL8lNU36a57HaJcXFvZlR0ndz413FEhPcAjJ45lrulB2eWaryzxlQBa6Z+WtP6oYpCveD/3bV/iNHO834JmSjBFGN3tpC8q6jYnuPpRz5LwqS9q5BozhQRRprKZWbHMPCQ13rmFzXw/OLNXTAHEnpefob37+c4gOSlAOwUCNS8SVz6SyQfdnUMwl1Qs72/ufHNaTz70IW1e2s/IsbNrY8IBuXT2j8o5pvfzsLqzmMVgkgvAQRBPaEQWL2CndrGnSus1bFQPpwf2yXHive1/POQDzE0dhTitBsSvOcTi9C79j7RufvK1oFqp43PXFWNF7u9oco8+JY8eUt36XNhRxncUo+VFMAR4DKN4suksTlmvvzo308b19YiyA/X39SgRcPTY+Qctw4QbehuY2KFqJS6dgOLukRk6LM2FJANwvY4O1WeFLwUqCknP8i480EpoB4cRqXKQsLPeVaFwlL776j/S9p3Yo3AY+xTB7k5OTZUrqieNHmRBxWpufed+VD/5zcpyN+dI5rIED+uEPXvQAwt83HmMSmajjfTp14pSam5oVkZyDJ2QKK2Ez4P09evM3v9Bb732kDiaFYSr7WgxLOSklTbOTQ7py4ayuwqC221nfPQuYw+MdGdRH776jxMLt2rQeAH3cTTbeUiC2SITJxjCZDc/VaH79wWY2KtYOCGA+Pnhe3/v+97XcXJ33drlnDsfH8+itHLA+U3RaHnTByBu3rZGnxMbEafny5WyauJvNbeprQeFpYWM+e/6qNqFQruUkH7LANWy3cVjVhgcLpqmN+3NQND+1dxcMoq06d/G6tu59AaKYDL9DqWzDH+7v0Mcf71fe6o3asq74zh539+FN2RsCs3fZnbGeyuI41temqpvXUQzGdf74Af32N7+Bxe8yh7XZew6LDxbBnPq623Xks48VnlmirRDCRIN3e09h7BletGFwGynPZeZVccl65WSmcECf0q3rl3Xm7Dl1GzXrfeP0nvt8wx8W2tNcV8l8OeHIbWZRjAPuzPUAxmMU5EDJhLzEgklrh9howg+COMibwh2OAjc7MahKqFl3QGluZBm+FfB4OXCdPrRfNf3B2rZ1s1P0Fl5rYSB2oKtq7VbVhUN67Te/1vEzF1zYRCvzKi8TIpdUWAwJk+rEY7TwgL7wPl/32g5zMYzViJBZHf3yEzUOzKkQ6/vSBWvUMOu6o0hnvMctS4W4JYYQKAtP6NdySD1iY2KVk53rwjUMs93nwlivu3VNl/EebXviaeVnJN1rzWXtnYGx73JZtVph0nvr96/pnQ8/IxwFoiYo3V/98U8xOmDZe4Ri4Wt9XS3sZ4e0++nntGpFzlf2M7utGSE6mmph7juJd6ddtwOWKCYJRWqoRWeZay3thEol5WB9j2SNuTtPHqFJ3+olqGHfXWGNdexnti4F3GsccKQVhEcprQNXPZbAGb5jzGHQfzsXul1jMaV4XhyJAhTZPhczYlgYoMXzft38tvUevYKOuHtLew1jqG6ipG1BKSU00w/Fgzai4FnbYeBk4/bEwnIInm+7tcOMBPAT6HgFCjrjMS3WUz9GQ51GgS5ZgQX0rvf0buMe8sopsRw4Fj6PXWJKsMU5my7j5inPbIq9EZiw9ujgRU/88laUz5AFsnhIdd/4MXuoi7F24Qxf01+E9qq0VdpUiBeAA4IRdpgCX4Ml+8sLyI62daEALzBo0IHMISweja2dSssr1jKslRbaEkTMWTmbydlrdfr+919RHAvp1/X1Nzb2O/zA4v3OHflS7QS8Xzp3Graqco0tiVdVYwebf5JzgXW3NWnf54cJQ8jBknRalRVVuCXTYWjLUxgdGcgJaQmL7ghA4+MGcs7fPj0fm3Pp5Qu6WtWi3Okl6m2qUPdsu9auzMZdiRWdm4TACpaflcz3Tmmqv0V9LTWArBMac+m8eocnlTMVpJ6mcvWoSyWFObAJwi70Nf15vwgtvKP6xiXdaOhR1ky1Gm+NEM7SCEVvnTasKXDhGKFYOks2btKnJ7/UcOstDbKZ9w0A9o9ynJaZTaz4bdWWX3PzaRr3iln1fHKPc8Lq62zR0fM3BJutzkMZWtPSp/i0UuVkPOXGvz2CxWuah8EA273y9L4XTPxxCLGVU7iAeqBXzUr1fTIOUPeFS8T0LI3R4UOHcZc2qay8yrn3E2MjnahMKUpOS1XP4KRKr1zGeheiUcgrpqZuKyktR9tK8nXl9BEsqteJH412Lt77ZfxNf5uyZyEnRj4SDflEK/OlGEu2WXRtE+uoua7z5Q1aHxKtHkJVmuCyv1p2S09sXqUp4gWrb91CsQjSP3plrc9WYGvLGLHlx77cD+X7bZ05cYywiiolTi8lRKnPMbfZd0y+jsiBjS+cOMoBWKUGcNeNE4ds75vyFILsbQma8tnzwGJKGMvpY0dgJR3BWzKt1moY6qLntKk4i1hJNto7Y9bqHxnqw4p2XTFZa5ULffUHrx9VXdcE102phTZPshZvLs52IUHe66zt31Qs3v762eOqJu4toOw6SkKr2ttHCLNrVFGux5IeGRWjYlyNp7Cw99Vl4RmqQhmbwILbjxxitGHLNoXOjenK+SNYGFdoU1HmnVjmb6r1zvuM9caaWzpdSrhP4VI8jA1q6L+tLJSrzNTtLqzNvmnPPYV1uqHisrqmIvUkMZyJkUu0onidIoY4jMKg9s577Xr2hRfZ83Db+VpYiwqghA8Mb3dy/d0v/0E//+f/WsV5GZAdsflRrG4bd80NdTpy4rKee/YVR9Rh7w/0devU4UNau2MvB9Xo+VCCh1ZvFmj68cujp5WxYq0uE2pVRQiR4i9zkElXBHN6lvVvHGKIuYAQlWzaqQC8huVYTydnkQXzzEiDglBMgrG+zeCxYNv2q9gB0WJeQ5eyDzHnRoh5tvUi7I4pODOnUMHXq7R/3wdKgh72akWTVm9JVxBreJiN9Tvz1FhCp22D9qWY4gAT4Jf792soIAYyliHVV9YqZChGm7EeRUOIYSQWE4QrTOD4Ks4vJkwiXrew/r7/2XH9zSt7Pc/Nsz9KsfyOc0cPwO47qsscsmsJnRpSDAbKdhdOZqFTQcHQMqcu1/aNEBXNTenj99/Xmo3btLOEfSeDA+70sKoJDYnDY2VelzlTwHzYUx6lvf5e4xmx/l7l4/cZ7+457VnNrmF9af3OWHSvk1B6f7YbJYfD6PuniYtt9sTJWnzwBIuSeTLRA+YntY/VMtA8Cqy3TrsO7427nymM9rkVa499x/6x180oaZebpH+CJfPrLMj21W8qpnBDHw9FpCcu1p4xkLbbLLMkMVNCzchxhn1yijG7Z4VH0e5H8T5fivLHd/4pymEM7fO3eBdt7/PYM1lctFle7VnNS2eKJWsSLnfqoNfP1Uqv7uY7ppRfJx4Xy/t6FFI7uPwxxcn2jnztPtbf6DEuWbAd+fYhgyHaQyicltDQHVnQVO/k+RkDhA462mg7pCwsve2NGkI5KiJ5K5iHncEtdAMF7uj5Cq1av4WTZTSJRtzMfrydu/AGf+LXxsqTmVekdUFxuDkJhrDFB/Yma5opipqDzQxlYCNW3tEp3HlD3c4SNU1Mqbn7ZoNCtGPXXmetO3LiKgrG84pEObMN5KGF76Rnr9B6ZDzH7MPQ7g6DZli0exvDUjAL1o69z5FQUuYOF8GckhIJ4C7EFTKKJcPE2HPnOpdL9NBKPV8wxrvYZWnagqXR4hX7u+lQFufbDAJP3cYmFaK12/ZwCo0nHrJdc1iDI2K6NTnQrvqeKb303F7Fhc5p/4dv6VpFA+FDscSP+bBM8dyR0XHavAl3C/LrGfEwC04z+MxlP0UimFusv2YjsPizaRaItJwCPYlV+PDhY7pZ16aNq3J9fHLWLRK7Vq9Zqx6SvAI4/Vqfz7AhW5e5sAhk09FUI+wyegJK44igGb32q1+ota9AASFhTqlYV1Kgye563WjvInGNceJjMWuWyTs8Zpkee2KPlpWe09HSMu3ZugqPU5BLRosi/nHblo1O2exjI1/Cj103PjpI7Hi5rlc26qVXvk8ccSzjhcXKxxIMz3xe0ToFxPYplAQ/U8LN8myKrY1nGxMWKjLHQErJJvyGJKXXf/UaMe+dSmGiTwxyAOJzD1PgnEtU8q1qBItCkVuwRgERHXdCT1C2edvGr/WphQgEWyw6v9tbGok3r9TjL/+UebWUsLEShcR0edpIJ7nrfKvYfSuI51yWkavNJciRGPv+Hg5VjDPbS+xANzNjh80Ibd3zgoKjrhBm16sYXJRRA9OOmjkyJlGrVmGRZ0S0VpWRFNmj9SvTfWwBycBYMrdsWOuUj1Ymq2Plc3JGUcQiZ0nCNvYshvTYsdNas+1p4tPjsFoGaOuup1yi7mBXgz7e9wX5Ia1+KcFzyL1k8w4VrZsi92BUPY2VqrQDPtTEwYQJWL+YTEzm585f0MqtT2rzmhXOSj89NQ5VdZNuto/rn76yybEj0kwfCzIlWXjj5m20fwlK/LBjJrOER/vP5jCDyY3BmIRklZSUYHwb5NDVg7W6zx3CHZMgSXOTzBcL+bJ+97XYGmbjakl4rPY++zzz/B3izBu0hXCI4AD6nnkTi+XzuRde0qUrbKr0QTwxxwkkiM0Mzrg8DbOYj8AaGcD6sNQsfb4Ua2NAkIpKNnOAhmkQpdSUcetfPqBNM4RCsLYy14wJsqh4NZbiBIXdHtQn11pcKBCz4JFLkNvPCrUOBdztZ9QTgBzcQYd6bcLN0b7k3DX6YSp06HMT+uLjD1RRdk2pIYN49ZK1c/cuDXQ06MCho2poe0yJ0ZnuMPLIjfoWL/SxFx6tRjwT6ka5wdDjlNBOXofRcdcaCT9I9ihBRqcLbb34qvJ4j3XDJa2lsA7XdxNXms9Y4hrX3z42w+JzTbnEqIU7gN8oBFC0q5R6d21gntj7tMnQEfqwPI4neNpyq0Uyj+UKXPowW/pVTHHjIE9AOtZNpNrQ6Wn7WD+KNQrfGj67fosEsBqUvu0eCy1zAZe39FkZccTbbOH2yMkbX+RrA+w+A+gb9rx9yHiM9ndhXe3j78xElG2EV4sCOj7A+8hiVRRx16wXHFRdMp5Zr82KzfL1RxXbA2AiFaGc7sBhbepH6Z1AxlW0K5227MUCbjIfQzsLoh12IDQFzZIfbyGnlXnEaMfc24xBss7DI+LIKI91Cs0w7q5T565peHQGFIMKdeFWffnlV5wlzJ9F7d5avr2/bHEtIca0aD1CxpUROEdCxUiolifHY61s1vgcp2YW6edfesUppUOdDeodnXWJLRO9baodnCI+N0KDA4MKAg3DWUJ9nQAsUEUlG5VfvJZ43AldCptSxWi8snE/jxGjWNeEhZA4RKNvzc4vVAwhESePtGjztm24VXMVAde3UfBeDJ1U5USSsjNT7yy2D5ePKQaZ+SSpZBWQDQ0CRE25KjvHtaYgW9Njg4zJUTbvVDajcKVm5lF3rK5fvcpBZjOxsCiN40PMWyhfieM0a00QJ0efxySLsGWJv/JXP3RKUNPNCzp0oVwbSjjdTY+pkszRdFzuZjUZgTJ2xCxyA/28HnZZ45aMF8NmZYcAQ1jI8NlF65FLdGKq9uIqNHrgqeFeXb1ZpTXFBUTkTquBWLzw+DR3GBgmXnGQ+4eGc0RhIzNEkASyxJsa69STs0y9uKej4nJ83yCp3pTIBqwzAcR/4xNVN1n7Nl/MNdzU2EC4URiu2AL9KDnbNfbKqXCNX6hQEcmS9eWX9dnxKypauwG3dIj6qT+eWEKjMfalhIHisXXXk9pgFgvk3ENSQETaCiXiDmonjv92SKyiQgNI+GsnTjRac5MDzmqbFUeGPO7yk5WlHIhbVFNfz2Eg0j+UACwkm3bs0jo24tHhQUXc7lNvdIlL0BroBe0Da0pxYT7NGsFrVK4leF3+f/beO7zu7LzvfEn0TvTeSRBsYAHLsJNTNRqNNLJK5LGzjpVmx45jZ73Z7D/7eL2bJ0/W3jiJbTkby7Esaazpo9Fw2DvYC9hJkARIECAAohONqCT28z0XP+ICBIl7OTOSsg+PxLkXv/s7/Zz3vOct33fBnHzQCkJt5dpNtgzmoRcm8cBIh3XOIl9qUsBrPQw78jmYQeTPXeyc704dO2RdM2ud01Efjh5d9+5bKuYPkVFRbp+lpbfBEJ60Fes2WGFRpoXuP4dPTKvNChuC9o5aSRIS0UCJF+smr6jU0nMK3Vq/ejLaDl+7a/NLULOzh65er7M5c2ej3RvFOarW6ntm4I8z14UI7u8VskCDxSalsM8HsIyGUQNhIJh0/z4oJ81Nzt46BAnlfTlA4Zg2gMlNe8Ndi0vJsNG+Fvv4o59adFqBFWQmWx82wBFow/pY/1evVFnxohWWl4aGSdKjQBPMdRTICl/9+jed0KMJB1sxpUsWl1kYCC81SOFl4iWTpxjMjG7dbrG4mb3WA4ORW5Bmyb25dgWpf/j9NLtVX8c8FKItCLx+Ob7erqu13pGZmKiFWgfaogjomfw/6psaLTQ2FU1lDKYfyS7cb1PddbsSl2Ylc4qts+GBHb12w+puF9vVmmqLiS/GRGeStOex4wDxR3iw8aVXEaIICeaOhQ50WEjRYocm1AyqTk8/aC8wvrnpiQ6BIzF6pjXi4JSelsmFhNDWvb2YGnVZf0yP3QUZIBGa89Bp9rH1+n6IiIq1RSvWWeliJLicZ7L1vYbWKD+D8wwziX40WonAOrWzj/tDoqHf8m/BPpgLr5a0bPF7+VtCgVAk8AEJc6Zp0+f58xfGBOs2Tnh0++tPYQwbYHQYjL/eh5R1OUxuLXPK/IsR+hA1OKyCvQpjuAE1JgIS+/4Ws7/4GWrzhWavLw6OAdbgyOHub7fBeMFEV8GE6nK6LBWJ6zVMHWDCqi6Z/fgwiBQwj3+/HQnu18xKkTyjBbbnqU8S3WCTINVeWAXzu9Xsr2j7knlmaBaxU8Rh7iY2sjCaOGQbF2Z7eydmIvFmvwLje+4qqBG09909PIMWvfkyKAKFwdVec8PsR3vNGmEuP9yNSUIY4wgj2ghjW5Jn9utreE75Izx/Yy1mFwUwp7Ttx7QDvttWLjIrz2FOAqcHUzZQEl/8BOxPmT/Bvn1w0CcBLgmnn/R7yXrak89vrIswJj0kC7MVVuA25uIYYwQylP3GCz57YrXLS8kZBbYiMRT1ko9YPxidiSpxDUwwEygpDpI02Z2xxH4pkm7k4RyS+qdBT0QC1MXmF72/ev643eyNsy+/sgm4IvqjW3R/PM5Q2GXiINLRVGM//MlWRzDCcXjZ/MpXLS0hCmIdaO+QlmAL6P6hYp4Fs5EUJuiimTjx1OCQc8gKigustf6avfvuz6yN22Fx2QpbgypehFH1hKO2c/n6EywSKXHANZNXUnD9swdhrPEEB7GmMhrqLuExfdk2fvl1S8cbUyrUdgzpixYssV954wXLwIt4UdZp2/b+j6EVHKpZRfatpZhQBOE0I9V6TGisWwPxCQnOOSMG+8MBmFIdyF/59ncsPzXWPv3gLas4VcUhXuuY81c3lNuBHT+zmibg2ZAmzV+62lYFox6mxhDNL/9sNNxggy0lJQU72yguHh22d9snVrTmq7ZozmJLunTD3v6b73GmhWPeU2YLsMfOjJ1h77z7vv3HysMwisn2G7/5NUsGHSLQJMnjZezLj5y7jtMb8E9IGX/tN7/KYXUfc4E9FpYym72Vg/MS7SMlYJ+ZDLMQjrrrUuUJq2fT1sIs798dZSn5C+wP/umvWmwoBC2AJIl3hP4hvbfhmW4dR4qQwYBXHtljPXHzbUVJih3euxX61wDDPmIF81ZZ+bIloPLAKM6swEHwv0C0Yu3VN75Bv1GTBZxmOMmXttlMbuCJicn2IBYGnn1248pF23MKZhDGsLu9yTpBJ9iwfh3IM74xkFkO2Zz0dhb58BBjj3BAB1i31Nph7DP9s/vYis6aRd8TnSnJ9ZuX7OTVDnvhlRctYvCOff97f2t9zNHi1RvtS5tXWxLOSqsXZNq2D9+ygfszHUP43CJgBAOVDNLKUNqqf0qyU6Vq9moofW20Dz78xP7Z7/xTiw8ZBg3jkpWv2cy44nwHAepjPR7c8bFVNbTDHD2wpWtfsiXziwLstV7DIRCnz5OHdtvJ89cY+DCQVGZbGYz9QEcdjn97bfGm1y2s7YpV1wL9eKXazp447Jz3/uXv/Svrg+5gDm0vvrAcehgMGoaviVpv0dh3K7k9Dt2M42I7Mthj2z/9xBas2gwKzxzMfErt/bf+u3M2LoOB24j/yFBhjP31D9+zw9t7LCN/tn37za8hNWaxBJjU72sXTtjP9pwgxyh7NdV+9fkFFoo69ei+7RZVtBYhW5FVHt1rn+4+amGYJf3Kr/0GkJ651h4TZkeP/MD+7E/Pc1mNtzd//TUEP1qBgSacDRGIKN0fiudMgcFkzcrB88Lp4/A6M+xffPfr9tJLm+zDn+2wvfQxMTXbvvvP33QX449A8zhz+QYS9Ks2A4n2d772MvCQvnGcrgWSOntnitZ6IrQjkTNYl7brjEdNV7RtWL3Iai4cs58epH/sxbS8ufbG1zZj3hluh45U2t/81Z/bKGtlQflam18EOkUQ4z5d+z7r7zNQiUG9AkwD9YgU/xhR3/cDyqCSZZPq2XhKuCAzAzFLSuwBhwes7/pN/0SEpLJXozROnGtBM2eSqDrBhDgpChRTOIMC0Zq4797vkkCqDZzRrl6vXYFoXyn5kYRAxjmbqd+sG9dX9UfSbm011c+FyPVLv+uW5D3T316eYE0xpJFQuWo/tBliynf6rr5BM9x32SxTvRtj0VqnOeKB2qp31Ge9/1mSyvLGQG1x80fZ+tQaULtUh95R+zQoqlLvqn3i8xwDz/OBuJesI/NP7EFoorv9qu1iLmVQ79SNFCAJmEpQvjAYr1+0sX0ntn6KeV5aWmpxYK66BEHoxK4XPzRsa2dhD9gGViMOA+7QZdBJwlhsxyA9ElVfFAdZe3sbqB4DaEXikNLAiMLIaZyCTT7Egg7s4cJAzohy0tnmti4HFyS4G+EsS60oxyjV4anBNa692HoKUzIexxYxS0EnFoOQIFraqS8zzeFU9tAnST7pItKoRhaG74IgBzUdiP19fdYBXq5s7OQ0F49Tj7PdDbpy1g8e5L0YncfAFMmDvBETgySwktUXwSt1IXHW2omhPRpjHXBtbTAGEGpdSOSx/3SEGi9tJB5efaEQnk76FB6LKhwGTPBNHayTEXCCU8AjVt/1fi+35c673RabkMThFEc7A8dHFglXucJlHoTYxOF8k8j6wkLS9WlGaISlogr31pA887W+kpB8321tdHaqokOSTIfhiJoDpFOgkuAJU8Nab21tgy+KcAfsXcb5QVgMMJeRSMsYX9qHstr1O4Z+z4Ai9SGVb8NRMoILYSIXl6inXOs+R7V2uw/zrvoG+nuZ4wHWegaQTV1cDkbAno7HFAJi75f88zkMXR1CwSbGvxe84bvc/LMzUmE0O/F3APeb/oSgBWoALzckIso5oUbBfItO9TNfnYzHCMzErLH1FvhFd2ID77F27mF/F8t+kdapEdOKDBxuZvBd2qSIGKTxSB1Vr8yx7vX1WAvQaDORRGnvu/0XBFMi8yLNWzt0TXQ7iQufGFFh83aDARwZB9YzEmI5gw3zgtaVzGJysnPcXOgsUJ/Dn2as/boueLpu4IYisa+Owqnlzp1WbK3juM+AbIPNdjvrb5jxTUQQoAupmLNOaKvoUDQX9CTmJ1BpqKoVPRVNE33uH0TS6WhUDGfaqIObmxkZj6YpAtrZ5fCAY7kYaS+rDrfH0TpI0xPNpUUCh0iZ6jxFGkEiLShGi4jD9yncmbwM4IGfmZHCPhtymOO9OB/FQtu0pyS9bWltRfjUz1mJIzn1p3IWybY56MQYyp5f9aWjOenCvlvnWbzQDVhvzWDPi/cSky60JtF1aVu0VkIwnUrmthaNdmS6ta5z9Pjx406iHjN26Qm6rQFm+EKZ4ADb8Oy1ZyPwyAj0+zHBYlb+R0hTMsE0XEylGBU5ZUh9J65dRMBTC+k37y6qZ3pf/3QDl+Tjs/RedmwaP5WrOmSfK9tYfVcdSs45yX0b/49/Pq+d478G9s3VR3/Vb33XPxFhmsJhDKXkuyQxHkH03teFR3m854HVNvEtr2++vuvShb2qDmONL981DkruYkUbNMaC0dLv3mXLvfBU/wGGDkbeV5/GWf1mDqifP1zd6qPmwTe2vnfURvXbMQ1B1us/dqrXXWjG5ltFqVwvaWz0vt7TWMieXn9760QMsK9dXo7AP/3Xt1tDmmP6rvL1NyMxYW7FUMlOXW3xjdfTrXaVLyaFhru2++pjrXPQP2ktT873tP3WmGocNacaUzeaY2vdrauxOfHKd+0be097/HNZ6+o7UyVYQzffGhP+aT35l6+2ap60F/33X+Cz7KNpvnUkQZVvvXjryvWRerXHVL9LtE1z4eaIB5+VrqlMlUUPVZqmnT75ECq8te/gHflBJg+egET99sbEu/SrrECTmzfZBrOn3f5lbCnQt8bG1rpbC7TNzSu/+1a01id0gfp98+1rc6D1+r+nNvivdTfuvKD2KE3uo/aYxkbvaaA8+uCtRZcpiP9486w15r/ffXUDV8cFXwIE1aPk7XGtQ415IPX+PJngp7gKuH49+8+zEXg2AgGOgEcM9Lo/M+JlF1HwJwx6Z6r3vPeD+RRD5yXV4bXF/7v3u/+nfz7/58F8Vx06+JT8+6e/PVWuvnvJ/33v2dN+ev308nvt0N9i+sdHxXtD2gSfenn8ydN+U7+9GnQg+JXDISCntIlJ8zI+NxN/C+yvKceO8Z9qHfmPzePGIrBaH33Lvz7ZiHtJ7fOvd/w50mfBvXzGpPLlbOQl//qetJYn5/PyB/upvnm9EJPjn6ZaV6pXY/95pMnj+lDCRx1TJdfWR9bgVG8+/tlUZUxux+RxcKVNGpvH1zD9L5Mvi+N7jrz03X/Pe6X5r0/vWTCfbt5Y1xO6obn0W+uq49F6WJ/s8bDPOO5q6+Q1O7muyX/rshP6WW0d/QbJf54n1yWb38lJ9X8ee3xyuZ/X396+/bzKe1bOsxF4NgLPRuDZCDwbgWcj8GwEno3AsxH4pR+BZ0zwL/0UPWvg/6gj4NRWUl25f8H3Qvm+6PRF1/GkHnxRdfvG+0k1S0WneZk4uoHkm5jj0b+8MvT5+ORbE4/87tr0pHyP5Jj04DHlTnprqj+f3N6pcjz6bLoyAhubR8v9XJ5MMbb+7Zmu7U9qg6+cJ73hW29PfuPpfvX68KTcU/UtkHxPKlO/PW0ZXr6p2jVdnd7vXhne31N9unem+OGz1DtFcY959PR78TEFPnz8uH49fIEvX1QfAyl3qnemeubf3l/k989HH/OL7MGzuv9/PwIDwIz0OzifmSYjeQUAkEpIUF7y5o+IjsH5yWdrJIcI2ROFA+sixAh/W7if20Bx4Mp5QY5KI/L6I8mLXF75cgbx11LKXqobyBo5pkXIzV1WbthudeNMIJgZ4bAmAlk1tWLTFf3Y/8h2S/A0M0HPUNn+TiAKH9wHqPwgdUQAlybHBtmUqW5Fg5JjjxxmJqgYH1vToz/ILnKQuRBagRzPJqrNcCTq7rZ7YBkKUSEeqBSvbQOAWstZSU6BaA+DSr46+3EU6QW3cqbzIo/Bwc1/DXjv3MWBRxGs5Ewkr3ytm26A72WzKu9zrTM5dQScmHM5R/UAuSYnMyUFS4imfv9gH/2s5XuM+wheuW494JEqB7Eh1mwPzkbDwE3JaTIYBzEdMHI866H9ckTyrTXGHNXr5B5o3hUuWX2Xk6AwfbtYa9pHLh+ONP7j5evJE/6rulnrPTgoCYNVOK4acyGCeGmIfdqH06Pm20tR7NlYnEe1H7TeenDakUo5Tg42T5FGcPiSA05oZAx1R7CWPfkOWMiM9z2QZIQZHclaVx33mCvfPPj2J7pqxj0BB6roCfvz8U3x9mk3zlKDmGKE4pQV6yIF+ufReuvGEXEAD/Fw9rIiuEWMeV7LWeoeDkwK7a3IjUElN+6DdheHIzkbah1Hy/nLj7iofDlyib6EQQNi42KY81DmaxDnqbF8zIH2uX++adsBzXLzyZiOsNijcTiUo+P4mHslMPbsf4VtloMti826cBoT3aH5LsUDo6W1/mher4yJn6JPCpWtPsnmOALEBNEP/70qmirYsrs4mrp5Ya1Fg8Sgta7xGsIzT3i6cTitBVqvfyu03+Rg2A26jeiqnO7Gk88huA9IMkUBFAxkJLTfOSWyFgTPGBWjsylwx1evbO3xXqCVFGwiBNMtIZKEQbP9ptxBNGovDuOT4BubWEcDBJM2RLCeoZFRoNkmrhOv/Cd9atwH5YhI/SHgsEezhyZHFNWYiK73Q0uigQkV7ZPzv8uHI7LwhkVX/WnDk+r8ef0W8kekgCsbAYOr8wDRDiLHqysAAEAASURBVCqnz8Iil+coqDh2uc6InsUewFSK6LYsWF92bQTWpZ0GJky4+jKXwUHbLtwyI+CTVfNPcCpZwL8EkwTBJSiyi9QLEgyDzj/q9c40nGftOu1S+YJJIwiZtdE+PROebgfPFORJ7Zx8iDy2HWP9bQTu7NJt+g5tBTLwYVKYZGD77PxN6m2ibLWHX3HetXM8u84zoE5dO4N1xtfZov5eo/3hIBsREfVhX1m7EFpfuOJ2PnFOdvaQCgxypZ58jMWQ2kp/A+7rw15N/KK65HR/toZxpD/CLRYSBQ6sLsF3WBV1Co9Z83u9mTrJQ5Rc15Za9YFnUcxXVEIxMdBfhJiBr7h/p33yyVY7deai3QNrLxeP7348nC+eOWYf/nSLZRQvcniJ9/q6reriGXvvvfctOZ+wuUAR+RPHia39/P8agFGXo4A8rkf62u1P/uRP7ezFy3bx0iW7cbPO8sHljQUYWQeOiIowaavOn7Z33vsYSLB8S8NjV8xY9aUztmvfHqBliOB2byZBLAqmtGF9Ug90CHQAFv3uj//GLhKetLggh0AEYWNZRoH6OWXbt22ziiPH7MLlKnA0i7BXYx/cuW3HK3Zbxfl6m1OUxwE1NnlPqmzSb6MEBmlrbiSS2M/sp+ChPle+yKEd6DV38BMcZOuWn9mOXbutCmzPEKIvZaQlg2laZ6ePHbRPdh+zRUuXWri72Ewq/Al/3gMRovLoftsOTFPF4aPWBcxMckqaQwvwZRu1diLU7d/5ie3af8QB+T+YGQVzEmqXgSfbsWOfHTlyhMAt/ZYIcsKsuMBgwlzZD4aBAdtu//1Hb9v16mo7f+6cDQJNl08YYV3GlAb67tqp44eAsPrYzl24RPtmWiZBSoTffKHymH26a5edOX/VcoqKLBEP90D3oxy/blw+Y9u27rSDFYftyvVaAteluOhnD51lYES0Hs6fPgI83BXmGyxiAifcun7Rdu741HbtIdRpfaPFzEql31wAPCLtWv74/wjyrL25zt5/+z2Hg3v63BULi47DU11hXX096LvbSijtj+zA4eN27txZO8Darmvpsblzia4FjNv1S2fthz/+e+sdjbbS4tzHV/aYX4ZAJbjTUGd/99d/CSxkvBVmp0NHITwujdr5YwdYE7vcfqq5ddvyCout/vJx+3T7boIaVNoZsKp37d5r8al50BbCeAcw8I4pIEztpz/9qe3fX0E5Zzk3hq2ogL2qywdliGlpv3PLPvzwIzt46LBdAqs6FAKdlZXqkAqabtfapx9/YBUXm2xN+YKgGNE+MHmrqyrtnfd/hhf9MbBagUPkkh0rwPqxfrewlw/u2Wrb9hy0M2cvWCKYsUKPuHX9LOG5le+4DQDpNzHfWPYnfIwM99uJQwdt26c77OSp03aZSGBFhQXQChAoHEeGoxhM160b160CiL4T1Z0EninGY2vAPn73LSC8ttnVa9fcHglNzLPs1FkBM6Oia5dOH7Zt23bb4cNHCLjTYrGJrHX2i+f8JszoE4d2Mb97CKl90u7PRAABw9tYc94+5hzRXNzgwIyMSbBUF64+gAn3xgOmRUzdpcqj9v0fvAX+d6YVsGa8pL186dxJIvF9YGc5r9pZE6nJMDAgNNy4VmXvvfOOJeXOZX8HecmmgqbaKtuxdYftO1BhFy5esZmxwF8m+C7xql9jXnXhpH366Vbbf+gI4de7wUbPp+4B31zs22WNvaEuZLm/Xa/X9sd96lLRf6/bdm77qe3YuQ8aBSY52ONZWRluzDV6IwRBaQMD/+///id2mHDct+7cdZd5IRLu3PqR7dhNvgvk4zKWlTme73F16hxtaGigjizoc/Bn0OPKneq5jzpP9ctnfCYBWBMMjSLBXYDxOXHJhwksyDQvyUG8rtHsB2D1vn+ciGowaYS6thaCOtTBEO05zb/r3tuBfYqxrqVM4ebepP7dQPodvwE27ZgQQr9XUG5FFYwaTONPeK8BRlTQfwcv++p97wBtJ8iGB+0WSM0qF9QbV9/3PgEbmD77JzGIV2t9TLaixr1/Cmab9zmvHAN84rzZO8foe69/rsC+g1hin1SY/c1W8DFBThH0m5dYS1YFU/rj3WYf028FxZCk6iLP6mE+9/LsPcZeMG5+2bzsQX0qJDTRf20r/RNT/u5B6mEuvKQxaIcRboTxhvexH/O7ogPqGWHFrbrON29N/K2kzac48MfPXrakjGxLjgux3bv2WCeh9y5UHmdDEp62sRG4mmEgrsDEJELN9u07wDytI/wuzzyRnK+4n+N/kUQg2WtiIS8hRPCmTZt9GKXcAMfJLRKD7jbbtWO7nbt203q4ufkYxHb7ZMs2mxEN4DoR5YSpGOwmlWStC1D6fbt3wtg0AY7e4yRR4wPATIdE2FwCJGxYt8Z6G67a8Qs3nVSq6uwR2wFD1NgKtJpw9IJNbISujnaYreN2iYgxjYQJlPe/l3SIXT93ws7VtNkSwsZmJEU4pnWAzabwrp/u2APIO3lYxMGvRzCOORhWrltvzy2bB2N4nj3OYvMS66mhttoOVxLGGZzpsrn5dv7MKbtDeOuouCRbvnq1LV+ywBqIoHbdP5+X/0mflN3FRhycEWvrN2ywzc8/T6Cf3IcHs7J23Kmzk5WXrWD+Ulu+tNQq9myz5tZWDq5K237gtBWULLTnVpQDpcYtMMikSHzzlyy1VUSFixzy7RmhEnhJe0mR4T766GeETG5xe0bS04rd2204NNnWrVtrMQ+6bPuew0iaIBJBpRlEjVto69ZThhEynChhgrnzUmhEDMEpNtqLL75gmzeutwykA570WlH0DnFhaWxuBVYKQhxkGkGq2Q5zv+PTLaybFtZ6n5OsTigGKLCy5ats9cpldrvqNPutwRIyi+35F2jPpk22atkC0J2GJQwOKqkPKZn5tnrtGsLHpjOfuwnCNPRQFS0YwvMn2EvdM2zlqtWWGPnAre8B4MzaWhrt2OEKu15PUA9gpYJNna13bPsn2y1jziL6tRSc6FOOGfXKkdSz+vIFO46EZTX7IScp1A4eOWnVNdddvqySMvItdnT0yk2kEkGmaIJWLFu1igiNS60G7PO6ls6HGhAV9QAadPrIAdtXcYz+cdC4h/Qb7VhkfJpt2LjRjf+cbAUoGaeKvhef/N8wtHxLV660leVLbLC9lvmspe6x9cYFvPtum+3cc8RKly63pfML7CJY2NW3Gt38hCbmsEdWWvSMXtt//JwPMeHJ1fn9Ksl2nzURIe/YybMOdqwL2uqf2hprYbzP2OyFK23tc0vt1IFdVgOT001gnr27tlvFsdMuYpyLcOqfMYDv0lIVlc631atXWXL4gB06egoN6ThjI5jHfTt2WiSM+XMrl1hLzRk7Bnb4PbQwRw8g2KC/LUTTCrZuzWVH4w3yX7ElnEkFmXG2l3OrhWhYQr5R6u/ttsqKPXb3gejfOutprrEDh45bc321VZysciHC8wmWsI+LfmuXokQGT90DGKKneiXIbR94HTr3FCEtEhzyV1YQDIN/Jy4yWJyr6r6YRoI22S6YQQROTgo1g8u7LoxvrCFwxjyit8UTMKMg8Dr1JnvAzt3gjJ9l9s21Zuvm+CTLkvh66XKtGQIYm5/LE56LCdsHA0wAJVtdCvwe7ToLg6w43IEm9UmMPwGKLDqMvJP4B4QDtmKh2QsE41hOPTeRlIohRUhmX3vObDP9FeOPgCToJGa9tIDIcNQLfKEbW68QmoRpAOGJGQeRGr0rIY8CZLy4hCh3GbSFvkoa/FkTmibbjZJgCf38ympwcSOZc5hir2i0N7Z5qdmXlxPJLs6IYoaUP425Zky+spJ1kEhUuWxwJ2O8luDhiyrrxVdfs5de3Gxl80tEXWF4hyCsnQ7PVVI2jf0DwnS2tXP7nJXyMH69V8rP/9OH9hCGyk1Slkw6lZuX6wI/eARfn7EQq29+85uWSqxsSZ9ExJpuXrab7YMEyJBqNQq84Wj6JiigQNMoAVo67OzJQ1zuOHyXlKLuD3OS5/ESkC4vWmrr1q61JUvKLC8zxanKAA61spUA+m8sh3kLIlrbWMFitAYH+gDHP2C3mvtg9BaBCSx4rHGoJDHB16ouW/68ZYQbXU1UtQXWdaeGCFvDVlK+0V7atBrNjSfFG29xIN+iMaEoX7Ha1jy3yhaXLbQU1DmK/vYwQXQc7WXsU5GKFeZlI62IsxhUwktWPGeL5s1Gip/g1IzC3ww2KWRwNOs1JTXV8pCsK0ytPxbqHSKohcWn2ioYohUr11nEcIc1NTbZucvXLSE9mzmnLagqlUdwSoEmmREUzVtiS8oWgFOb4togfFJ/3Y4QEmYvXG5vvPYiWi42JivqPpK5a0QXK5k33+Fxrlq5yq4RZEJq00DTDNZMalaBbdq4FglPmlOBpoAF6i9NjcYspLhkHgEyltlsmMV798NtbkmJ05Zs5cKXjiZHGNpaccEdjuCzdrTATB6y/rAUaOkcd+mYeMjPsCWr1tmaNautbNECyyTE+gBmGykZObZo8RKeLbRIgh1kzSX6Ww6R3AI8EYV7G8mFa+Om9Ta7uACVfCzznsJ6Hy9A5kjauxGYiKRn5lpGeiphgsMdhvWR/bvs3ox4orzNpk6FvtUeCXTUuVCBVdvUPQQTv9nWrllrSUQdqq659bCAURiXJi4WMelFtnHtalvL5aiHsbpM8Io7PcNcRpRvnSVGh1gNWqpgUghSwKXLlxOpbT40GGxczBHi3X7xOoC5TVikbXz5NVuzYrHfWhBiAypxsHxT2SP5SORTiDTnaUoCaYNMduYTPnjxwlK0R4lu7yagdvfWutT+fWDodgyF0+cVtnrVc5YaHwYT3MS6HnJq+uycHDcXnllKIPXqHZm43bl9E0nrbismWmACe1Wz7b9m78AE358RYYuXlNvK1essZ1YI0fVaLQoNy2tvfIPgVcloWXQSB5+yC+fZsqWLLS87jTGMccFZPNMlad8UlbOm6a4tIGzyGhj9ZfPy7XLVNbDPQ23zy68SGrsw+ErJMYx2srke2pWcx3mxzJYvXmSxM3rsdnOnM0lRoTK7qyE4yuIVa7nwraGfGdZws8pucekKT85/mC/Guq1BFyZJxH5J0viO/ZwbJIawAalkfgpMDfRY5o6hMH39PFf3EZQZkTStHnq7NIvoL6LLJF0KtUbOXOE751AZjFIwScIPcNEtG+Zb+zKLTy7k1g1j66VXV5kdgvn+jz814r8TxSwVcwDevQETKgFQLxLp2+3BSYLF5IJRb8sKiIJGXyYvc5kFiEncgcT5neNmG5fAJCZwSaBemS+oXmlV0nR2BZmg3S7kNFFPH0nSgOtikRLLHPjxFn1IYLccQSJ+3WxVGWMV8mibHylsmgeKEtfG2M2hPYqglwTzDU8EmLYvo8ZEh+Nd6t52jvDR5T6GV8/AL7ctMNCv8iwt3ve+Du64hAwrWzif6IJ37Oip87Zi/WbUS0n2FQjKcrhtHTqwnC5q3OaXv8ztuxym7wtb1tOMwPjPYiLDHvTbT374A/sP/+FP7K2PdnIx8jvoEDspalV6RjrqHp99mKTHd+pqrUVq64sX7ZOP37O//pu/s4ZW7EwDZYqQAJ04tM+OYgu0CmnACNLcHtlpYarhHVFqpVOHcaHo62q3S7fu2tJ5he4g1wGVnIhdqCYlyKRD4jqS5P3Eq88rRN1OqEbZbcveU7aqSrLjE9h6FLaXgtMJQ9UFeigXYh+4ezz2hf6MYzBN0MVCanyFC76GFPjegwibV5Q9XgTrKT0zx4pSZtp//6/fs+99/21LzMizrBQ2Iu26ePKgvfWTD4n3Fgv9YDMHlYA/Yi221F60//Jnf2b/7j/8R0Ko1zmbSa8Y2YbO5ECSes+tbewUW9taTGFPq5DanT590r7/X//c9hw+4wJ9ePkC+ZQKvqWOKIBvv2PnanvY85i3PIRpY76xHRR4vmwzZVOv3T4DApuSGIm5zgW7UXvTampqrA87xxFdWgKpVKUw5rJpHuhptR8RBfBCTbvl5hZMydgMcQE6vG+HJRWUEUI9xg7t3mK94WlWlMntF3OSflRJff6XlunawMV3z9aP7Vb7gJWXlRAgA7to7ILlEzDeftYEYzPK2uxsb7FbnaO2eG4eFy0uhvSzt/eubd1z1DZv3gAjTjuCSOr7A0wDdn7yoW3dVcHFZ74LO+4xJhFRMbZw+Wrrqjtr3//L/2T7T16FOVpkV47ttMraPivKz7KwGdjOj+0RD7t6+iawr2BMpC2RXWY4l+1w9tI92aOPZZZdfT/jEI7NbAi0Jo59fV9ScwK3SEgvu8yIcPJxMPnnm75u35xLGHEVjc4P/vaHFhKXa/GYYXjmLypDlwRFFovnMuaNhw73cC7F0jb9GXvk3/8/f+EYovv+qstpGuDb4yFWL5OOt9+32x0PuFihLaNspfvQv3sDvaYAMSE8i4TGaoz6Ga/1G9Zb5cHt9pf/5c/t8JmbtmLZItoZ+FnRRWCZg/v2WkRaseVzSElCeg9bw35F9xpLsxDC9BGh8sKVS3bzZjWaHsKEsy5DYd4Tk7kEse40H0+TRLM7MTn44J237QBhaBfMmcM8wliRpJUY4LAdfiAaCI1B8CE7c9Hamdheys8gHjOnp0laS7Kl1gVf4ewVuU525F3yoRg7lwadvfI9LvEySwnl/I+2IdrT3NKGDTQBRcgXRT6ZzCjfxIvq07Tq88vzdLMRYP1almh+dL74ErXpbNVzhHb2ASp8MYHnbmEqUO+zaZWkEjpmJ3lWyPmFkCy4ROGqTxJRJZ29jL+TfooySlJ8vg6pY77Zy0uxRW6hbpj1f/Qq0knWyCXaMcB7yTCjfpd6X2HT/Ff9cv3TlymSfAPmFSCdng8TDsPX2AnDDvOHqZidRBr7JSSiabwTbNL+dzTgMfV6bfJ+1rsILgy+x4q5AFy5ir0yzGoQtOjxTWTsPGk0XyEyjInf29Aia27jGXzHHC5IYsw5G43gZXaPs1kXEtkR+ZI8bO9DNI/avsMnLWvOEltXvtDha4pxdPaOfp0SHqeeiVD+QhPG3dGJGfav/+3/bn/0f/yRvfHKOmu6dgbzk66HN2df+3wSY6+1MgAghAGhJdfbN7/xbXvzm1+zlIgRq7l9Z1K+J/QOYhiJujBk5J4d2LPDjpy6wIFxwa7dqPdJQcey6kCsr71uWz75xNa++g3LS08cc7LwtekJNTz2J+FBhhAtLDZ02E4ePWg791ZYa0Otnb5wHfU4G4+kuZEziZN8QUDlOKRfFKpZoPZPWseugCf9h77LpvrMsf1og9psxer1lirj/rH0AEaoob7Wmu8n27/5N/+z/drXX7abVefZf42OIS9f/yX7V7/32xY+0oHWqsbLFtgnB8+KdS/ZH/9f/97+7f/6hzY3PcyuVGPm4sfUiVnBGBT65JOMy0FHTnNxSen2la9/x978zpv2xstrCGNcb50KCR5kykai+s9/53ds07Ic27Z7PyYw44ezitLYu70xtj/kqPX6t37dooZ7sdPda1frmi2eKFhhEExvTQbShBms95jELPvdP/zfbMPSPLtw9jTtZ1P7Ja03hfStvNZia5YvRBOX4Oxju1pqbSu26TW1Ddi4XrS27iD6zXxHxcTbvbsttmfXDjtzqdpuYht9u5nIfyI+Y2mEA/p61QXbh+3uy1/7FuYYsQ6ruU/Sq/MnLC5/iRUjLYkI1hmDUQrDnv3rb/6mvfmN17gAHrRaLqyeM2wfKuLjB/ZY6bqv2u/+3r+ypbPTCE2927qGQyz0fo8d3L/XjpyotBbU65dq6p0/gdfm6T7F6DhnK9aSbMJlDhCqy/RYRjF3ooW+ACXsC9Y+3JFjYJRPa/A+jKwu1wpz7uWbrl7vd5nflBGi+Pd///ctpLsGf5R2HKJ8e9x7x7fe+MsrHBOsV772Hfvj//Pf2R/8y9+2JOuw89gk3sOcLdhUuGCV/Yvf/W0ryY60fUdOPxw70ZAw2gYX4IoUA6cAFWISd+7ab1/5B79pv0++0pwEfBL2oxn1BTYJpH4xgGHQt8YblzFZ22qNLQgQuEDe9dvj2bMX2aa1q7A5P2u79x/Gp2nEOWLqYv9w/wVS2WPeSc0ptu/+1u/YN1Gv78SnwjPH0FVUUnZFr9P/dKGSj4porfCJP0vdWkty3PbG0Y0p0sYILvNjpMTHeGOHLxMsjfXQyDB8V5hzkr0P7dczmcXpd0XKU3t/WZKfbPDzbZIYyPw0mLtGs9kIVe4jIYyC8ZkJbWxo9TlNLZwDwwuz2gDjyT420U2F3DtTBbMKEzo/x2cmEUzL2OcWz+XoHMxtLf/kLIa2xmawz2QDnEobTtWgkl8PwwnT2wtDVkN7VmRgUpCHRBjm/NIt6s6cKDmdrg0iupJCc/Fzds2ybe7ooQwyNvNd0l7WJSoUmL8ss8PVPtvnEPr833abYT7k2q13gk1yfOuCicVEx9UpkxP2p2NAUxh7MZmY4VgnElhM5uwejWqjbdjmWxH9Vn+dzXQ0NX+GtZlAfkmcL97ENIM6m7jMJLIG8FezW7QxBxOUDsYHvxx7bqHPbEQMege/V3ApWMazONrmaYvEIHW137YtW3agOsTLP6LRTvPeJuzJEuT0BuPkhUvWptJGl8RLgRgklfA2aLDj+Vnf18EzzI1C0hC1SbfmUVSwIgR3CTMZijoxkmf4xbuwpoMQq17nvT5qqYQ77cfpYYSNMAyTpMMtDGlNwNNCnVJJFcwtc9KicxXbrKov0eYUZKER6SVkb7dzQmusq7Gd27dbRMZcW8JtSI4IcuRx3uTc1IXScI9/Q8MK4RsYmdDY55Ustl/F3nIY6dbtm1e5XFU4NfUwTmud2NOJQZA68jTMaNOdVOyH2YDhcZh+RLjQv/LYl0SwG+l1bIQvrGmgfVc42NqrZ3AwO2prX3jZMlPjnZd4KNK2ltZOvLjDuGArlCtzw9pJTMuw0Kpb1tTabg23wzAbIrS0mAlo1z3mK5gkz+hRLWYOoHCkPlEwJFq/QkboGOhxzn/Jqek2UHUFO3YuJAmh1j0os4wMVI11DkFgeCQHz/cRmBvWhghZgElz13Kn0eQJL6SBGGzPJQWUbXhb2wDrkNCxIHTIgUxoBPJcl53g8KxoTBnybO2GSGtDGlBz6aSFY54iKVKgaQTi0se4dxKiOCo8hEM3zAb7YQQxqeiAGM4Mx4uccR3Akev4wb2WkI9JAk6QCi+7+Utfs3J50iJN/fG9H1vy7AWWkoD6KNDEIbvu+Vcxd+ijTz12ePv71hG/CEerBOeFrz2VkZZiN6svwzDss+z5y60kP4N9NezmuJl52IODyIav/6bz8A9G+yH7/UH2k5h2rRcxoEPslxEIuELayjSmDzt/2cCGJoBSA6OZSlsGTlXZ7MWrbQEqfTlLVZ44Ygcut9oC7McDn/MZLix7NISypvaW9WK/14NtYXpuqltvLW2dlszlT4gv/Y2tVn+nmYvVLdZllOXnZlvzzRqXLy2i32kccmDOA91jmppB9vJd5k3aHRfwA0FFPxcuOSsP9t4HoQNTLiQZQpDQGAwOzHDMmkIbu4AmMN/aIzIDERMeDJ0eYl+2NDVy+YhytESmU81a62gFmpvvsna5kCH1DkMI0NTWZsNd8onos8zcWTildrgxDkVFnIHpzpljN2CV/W5L06y7KJxNX37967aGPtlQL6ZMDbZg4SKLJix7R2sz51MsApxwKy7lWQK0rbPZGm7VWiZmMKO0T8gQQlDpRmIvRJEwmVMEMfAtd5oQVMFMot2LhKGQxkN2/ZLSDrIPE0BkSIgMQdrfbrfDR3D+ayBUNaZt9FES6172/UCUUIFAYmFtBOr8KsY/JT3Deo6eBPGoxbqbm5n/EbRI8dZNXQqHPBPzl2Qk/3WSfqeHwn/cxWEx1XJysmz/hbMu392WZuvqJV+wzojTzMtn/Tmw0+0pahENL5uLU9ZhnwmAztEXl3FEcLb89JTZepi+V1b5TA5qYTgP1WIrW+Tjwa7CrD6/xCwDhjXY5Ootxs71KM5ix2CwYMReg+EVE/5D/v7dN7CHnQ1zXIfJA7R+CKZrPoxgDfXXd3D4wcjKprUYhg2aHnhiL0EDbNcZXxk4zNpZyi3iUvrOBex+6fu1W2N10BbVgX25HYOpw7QLGy8YYxjH9WU+6WzgFfvyHrtKvVwkZIedT9u76N8N9uo314HOcZ2LRT3S1gGcBGFAkxjbo5d4H2a5rdsMUzkngQ6GGE3VPjQu9uWVPqe/VuoLjcXUgjm9XWu2/47Zb2zwMefwwfYqc+AJXuDLrJ62/fr8iRcPMY063BIzci0SoqHY9K3Ah4iR0qUjISnFSkrnufjpCABciiMu+tx5C2CSgaX5rB3yFRn0f6Vm7W6rBwHhIPHlE6wZYpldugTbtEi7deG0NfZFYbe6xEIGu6wCT2URxgvnzzhGJX9OmSXtO2n79u2zob5Oi0gusOKcNBijsQ5O1xoGIiExyf1z3uk3s3G6S0AaEW13W+ps+75z9qvf+rKdOLwfCXOb5YUnIrU9ZAnYBZWXlVojaAHnrtZZT9sQTlznLAGbR9nWBpKk8opB5a5/6F5tJpsuA6Y+CVvXzqYaO3UBh7TnVuPAtcJOvP2JHdjb5Rjv+eUrMSEKsRt4Nl++dsM5WRxiXF595QVLjAsczkeH8F4cJ/tHI+zm9Ss4TDVaRl6JlaNy2LF1m63dvNmycvJtZsUp27pzp90HpSJiVpplJUTY3p3bWHxAZ3W1YkYRaatgSoJJuvhcxGO8qrYVBiAU1JVB+8rmPOhdrx08uM9yyjZie11kqbFVVrFvD8glIRafN9cxJaN9xbbjwBG7f/cO0vkGW/PK1znQkBoHmIRUcOH4AWvoHkY9j/0eTM/yta9xmXxgx48ctNBZubZpzWIc46rs7KVrMMb37NTJE5YQtxmi1W5XrlyxluYm67sfay+tXwmDEjgTLGaw9uIJO4D3cyI32JvYpZYuXeuQJy7C4PVG5dva5fOtB8bw6q12e+GbrznJmJhlQTglpbCRh+5xMcq2uJRkkDyCYIJZ60kpqe7fPaSudZQRFZvJpTPCbt+4Yqeqmu07bzxve7dvsdbu+xbZeMtO9HZYam6RLZtfbHUwhjE5890lUAghwSSNeWfTTft4z0lUv+Fc1ludk1oWTn9tN87alVtdVobNrJik7ceO2v3OWuuGyC9atdZy8I6PhvjNeDBkrTDiaW0zHCKHLsyBpmRs2lcsLnaOjbMi0aZEJ6Iez8MethnkhAP2xq+8bsWoyy+h5tuxY6e149g0d/mLmMlk2miXUCN2WEI4F7fYZJcv0HpFeIe5zO7bvQv0H+3xQRsI5ZKdnYpJTJudOHbK5iMhLsqIt7OncUjDTlQCmkMnz9n68jl2lItQWzcMIKggfagD5xemI4EPfOwVbv34wd0giYSzbLo43+/Zqs1rWPf3bN/O7Va0qNyKsSucl5dou3fvsRGkXGHxGVZamGvDC0rtyME9lsoc9QJVVI5TXzh0NdBRj4iKNv1LSUFSxb7Oys6GocPuH7Ovw4f3WUR2mS0tzQGppNYuVd1w5jeLVj+PDS+CjZ5OxuawdSMZPnPymEWjAl+yABv2IOb8xvkjaKrvIuAZpY7btnjpRvxM0DhxptTfnWFvvLrOVq9YZJfOnLZqLhxtncP2+kvzUD6N2PmzZ6ymvsXuoaU7exnHuaULMYGUxHz6JE1BegE22FGHreLgAWDQ8MeZvRBT0zjOM3xPeiM4O+bYchwlf7L1sO3tq8f5vQ9N3EbLR+KXtu8YNPAANKDdkosXYH4W77QY09f883kjBIS0Pwq4qiAg0nRmc9mwkhzU7pwnZTA9ywqRECItXFCAxBAGMAY6Dy2EKPI7v0mSKFqEv4rNQYKIyVzAC/RhH1jRXFCsrMgniV6zyKwgFcaPZ+W0YRb1zs1DOg3jXZgF4w2jXpiM+QMMdy5M6wLasYL35GQWzC1NF0p4ADBRYWRhcJfPwR6Z7+mo/BfRX/wxLI8+5aVTB21bR70yuShkfFbxXdLhYv4lM2bj5gAPe/XEL4Tqtnz68xzM7OJ8bIsTYWqpdyHfNb5cOJ3pw8oSpN3Uh8+VQQtde8qpeyVtncVcBLEfp2yPBEgyq1vI+EKPXb9yYcjhyVBb+WylJZVfxvim8ykHPSXoiq2gHdnMgZ7RHRuJKLaB+FeAesq0hQsW2RIgs5YswZFlwTwkHNygWWBxCUnALM1jTrF7I6PyCbOyhGdJiLmFAflZ+6T2BZo8iLRUHGSiQRuICAU7FvVGCYR503q8wzEWv4c0IDw6wdndimG5Wc9tPTcPm61ZJklhXm4OfaLvSM7SCkqQeq+D2OA0FNRiHG+xGNOklHSggBhwGLVeiHBhfjaSE9YZ0mhJeXXZiIZx1c1+AGPxnuGZlpORCiOd7KCuxmGXxssN6BtMijAxC/KQcGKYP4rna0p6pqVl5lheVjoM8LDlzi61Teueg3GM4LJQZ8OjYdjtChYnzAoLsSvmM9CDQgek1IDCqZUq2Nmm0a/cjGSkQfdggHNwvMzBGanYOpHIJ2YXMi/rXFtScWLrxF4yOjnbNmzYaMXYa8qWNNDkJP7YwQ3CIKgPL375q1bCwStpvzB4E1IzkEoiGaH+cORPYTAfr732Kvs02dK4KOTDRNzt6rHlG16wstJii2PTaj0HlHgxnrlS3aNh0Va+5nlbvWw+628mF6B+bIGBgoLAdQIP18fcJo3ZaqZnZlsEjPId7PaSMgvs+U0bMUFLc2MXUL28JFVrVDwEdAQpM9615Ws220psLWOQ0IkxjUZ6JqmkTBKiMJlYtmC2s0ke75vvm9TrmcAhpYqAPmUSDmlKRpa7tEkSPYJ9ZEFulg2iUYmGyDjMa6qLTUiG3oNQwXqct6DMspAcB8OAqnl6XxBbUREzkKzhWFdUai+/sAlJdgx7qAdNA/b+rOP8ojmWgcRdktKSRctY6yvRBgqX19dJaYtmMR+5wE15zwLpvi4Q2QWzndlTWEyird+4gbMkHYkj2iXmPC8/19LYa8VFRTDoHVa0oNxWl5c5h7Bc8s2EaQyHRm1QPpi0gNc6jZyJFiUWh91+JL2hsYn26le+6vaYnPEkoBC9iY0KRbtyG/Mo2gnTH4Z9dHFBniVy+PSDVR2ClufV17/KuYUzYRBMsDQtScnJOP/eZQ8l2XP4iCwpLXLaw27Ur4JEzMxMd2fAIFBpiRn5IJ+sc32cXbrAYsNA7hnF5GzZKluPz4ToS7Bz79uY2N4iIc3NzeUSFAGEWB+OzunQ+GiHldsJ5z9/2XO2YdVSm4XtofZCM6g3qZm5rMUoS0tLd3vf3456unmPZt0aF6fBkRmUvcY2oj6OQap9j/UnR8SCvCwg0Qotin0vCLPVm6AlXOZHdTFG2zWTS35GaiJ0PRValBSwxkdrNCwiGsjMQoRSvZbNWt+8fi08TbTrV1h0vPNtScW5N4O93odZzKp1G2DygQSNi/PlQ7uYM3se9HYN+bARnmax/zwh0mZwAMK+BZgGEO/V/DGive8HmMFnAiDbafXZnSl89yr0znW1QM/0jmgD+8gxoNOM02Pb4MqjwIf1jhEcPedcdlJEhHUP6xTjxdnp3lcDpI5/mrpVvtru+jLWH/XR1Tv2qTYpaSx45Or0nulvPffGRe8Fkry2jxXtYy7HGuHV4caEwtw86CG/u3r5rvqCrfNx7VI9ao+qV5neOKou9U2/60e3FsYKcW2b9Kw/7iXryPwTux8CV60sLiNfKNDbQN6zCUSM91SF3lM3f56ps7PTqahKS9n83ABl0iAHAKmjperUQSO1uRahr80KNIA0hgY7e1reEeMu5w4RAUbJl08L9KmSEAB85Xj1ySZLttM+hlG2Wr6C1T5dLCTF9iDNnGnJ2POnqd7ZHVJ/KIemZwfrxoJ61A490zyFjtk3SrXn85KXihR7SzmQ8RlocvWNlatuqQxdAsT8qD71R+XJTEH2bfpd/danJHt6xh9jc6Xngdas9zTW2FkiGdWYymbTOenxh9ql+X1oi0k9ap/GRTaMVD4254Q9oD1uLoKr3M2z5lp7wuuzWuWbf7UH+1BnH+mzR9ZcS5XNAeDrN+96bVa+wJOvf1ozXt2+MVXdI67fmnMNitqiPmu8JyafvaA3HxN/C+wv1a15pfOufM2nxj2M+oZZV/rOK+43jY+YD82BmwfG5mmS6vTWsdu/rDO3x7UGoD5aa+qT1rXU/m7MqUufXpIGQVCOamewSX1S2apLY+4YWdqk4BTeOD9c69Tpuxj6TBAm5gtyravfjPXDtUXbVbdohzNv4Lv67vqtA1HzzTqXqYLQMtw6VZvHxuvR9fD4kXDzrDHTetMYQxvVLyWtQe2xcTo2wlPf2Lgx9+aLT7cGqD8Y+uIqefif8TWrOtUn2cZran10QG3x7TFHc2izb61oxcl+l/nSXnhY3vRfNJeqxztTvDWjdaBxl9mcR8c0Ttp3esf3DAEBY6+x9uh6MOPu9q//ueStddaa5lfrfwb2yJoDtechHaNbD88z3nm4Tqfprkw9hGNdXl6OUAPJ4BeYgt95QTZGi2J8y5NZ+2FSGW6P+D176jN/rAxXHpVMqFdVj1XsPifRvUfa6deeQL+qXNbGI8m/3sltEsM9RZZHynjSgynbPtZX5VMdjySeTW7LI+88xQP1daozxWuDG4tJ7dEzb4wmV+l77jtMHv1tUkF6gQxTPJ2c9Qv/W0RBTNzkpAhp/iki4tHZ9zEjn8fW1AHgXw7e2WNtkt00FtX+TRn7LqZxqudTvDrNIx0C7vDhPRE//6RDenJSvVM8nvzaY/929U0x5sogxt9LOnycLaP3QJ+09ZFn/r9P+32MEZnUT3foaIOOJXcITHpHDEIo73yWvk9ZLnX6j7PW3oTlMNam8Mnt8Rob0KeYjhDW1cT5VdYJ64h96a2FR4sVU/Doenj0vcc/0ThPmD/65K05+Q18EUl1+q8rr46Je05r7/H1a+z8lodXRECfGk/Z1k5ItMnb43o+1VoX0/ZIvgmFTPMHdWi+Js+ZxwR6uV2/x7edexyClHLCPHkvB/jp5tldMB9dL2ICvaS2PLImNV+PoQ9evsA/J67ZUBmGjyV9nzw2j9sjXp5APt0lfoq96tv7vhIc4ztpQfmehbMOA6nlMe8wdlOdSxPnUvthfBy8kqbK5/32y/D5aIt/GVr1rA3PRuDZCDwbgWcj8GwEno3AsxF4NgLPRuALHIFnTPAXOLjPin42As9G4NkIPBuBZyPwbASejcCzEfjlHIFx/cEX1D5ZwDjDKz6QqD+SMF3xJanE/X7V86ne93vliV8fV66Xya9a75GzGfP++Mx1T+qPV64+XdvGfn/YTu+FJ+TzXpnq07+cqdru/e7/m/dsKhOVqeoI9Fkg5eodry0P31cFU/RftmbeO1KH6Z+S7J6c7ZOzRxr/2/3IO09v7+VK+Bz+I3tJbLP82uxfqNd+Xx98/fL17cn5/Mt43HeVKdssDajUn96Yee8/ru7p8nn5n/Tp6tWEaZ4eNw9qH//8x8abZ+1NzfDj1edPqt33m6/vqn5i3339nmo9+daSr9k++93pa5n4xuPG1P8t7x0989rmPdOn90yfwaRAyhh/x00LdfnsOEWg1W8vSXUbTPXj5T6+/Xpnqjnxnqlu13dUucH1XPveZxNJCYGtdVeHb761Px+XzxuP6T69/uu9iWuWOijfPzCAb35lPzmRXk3MN12NE3/3xtBnlzn+m2sXNODh1GovjP2s37ykNgVbv+xMXfkU4t8nr0x9+o+LN8a+teZbb2qBaLTyB5O8cvU5Zd1aa/zT7xpo17+xOjwao/p8eYOr22un14ZHy9A6H6vbV8nDc2hyHuUNJnn59enVO7kMtxbUdwr23vGNuW8+fE3SmPjWYMD1U6Y3pl65k+v2yvLG2HtP9T/pHPTy/aI+v3AmuBtsWoVHlgGqHNRlAqm51/rEadpBdClIgzBrcfJ3dqr4CrkIbwR6cdHXgh0clUvgI1eGECoUjW4yAo6g/hQ5B0dNvKhlVO/D2u0HrgxHdSCMsKcKUk6uPqntPYPYgVFm/BRoP/hKOSxhtUvFK/R3N5BpSrLXE44wzsRBJZUpjHnhLHtt90yU5JcAfKV18rtsgjTGIPq4eoUbrEYAtjBlW4NqxNjLasvdHupkHBQ1TvV5UGh6Bbt5PKV98GxCCNFu9TCORaGFXKGIe77EZsYYv+rcSTt15pKNzIxy8eoXzCmEsIxa3Y2rdubsJVu+6VXLJPJVffUVO3Gy0u6CFbdo+UpbQphlwSX9IpKI0QAewxfPHLUHkWku3KWiJXlJYZ4V8nXXjq3g1N6z0sXLrHxpGV7rcS7fhcojNiMmk9Cki1i74/m8/E/6VKSeWzev2e49h2yEqGCbX3qZ4DDZoK2M2yZ2d7ZY5anjQGbdsJTMfODInsejn0hMtddsz17li7DnX/4SIc2zXJSjJ9X38Dc2wAiYr0crDthFcPkehEbb0lUrrXzhPIcI4L0nIqkwm2cqz9jMuAxbt2KBc964drnSjh6vtK7++3h3L7EN68odlNDjiK1X3sRPCC6OSWeO7rcbLX22ftMLlqGQlWOpmbCn2z7dAk72kDskUrLyiKy30oY6au34yQvWh+f1MrV5cZnDLvbyTf85aq136oAkO2zX65qtkPave26Zw8T0Zu/B/SG7cvGsHQVvcxAEidUbX7TSoizC2d5x+WrqW60QKD3lSwapw8s3Xd1yQKuvuUK5p+xOexfYv/m2+YXnLR0i5jkNKVx1XfVF23/4lPUQD76UelauKLMzFVvtys07ICj4nDgBNLZf/5/+EcEsCLgSQAM01h1A0e3euQtc1i5Lzy+21atXWkF25sP2C1f2GhHxDh05RSj6BzZ3yUrgvebZKPBsb73zPmFmfc5yOYUl9tJLLxFh9CEBmK7rDpP4yqXzVkG/QiLi7JXXvkzkzRS8/sePts62Bjt65Khdr22ynEKhOKzHHn7Yrl4+R5tOWygA9q98mXzgFwcbSlcNFPTT2cqTdqt7pv3a1156yFAKCeY067Dy8g3oHg5hHDIxoNd8+VfetNzUOLvX3c4ePGm3+8LI96Jbj9N22O8FMUMa/yN7P7X2kVhbR2jolFkcICTh0p4+fohgHGccZrn2XCg4toUF+dZ555a168AgKepc8bwye/3Vl9056B5O8x+Fdz976gQRDonKyHwWzFsMBB9hhGNj3dnuyw52bnODVTIuV281Wfbsxfal9cupcMBqrl0miE+lDVq8ffsffA3sfiCzpqnT+1nBcG5ePW9Hj50B937A8kCXWQ/igGAcfUIPwsYD4XX84D6rIgCJgVO9DOiuZYvmA3k6ateZ8xOVlQTEigRj+hWbmyP4yQAWutcAPuXw11pfY1v3H7WlhD9fBtSZlwZB9Tl0YK8dP3/VBZMQfu4mMMuzkqOt8th+u1LTYnlzSoHIXAGOeYrfeHklPP6z5XaNHTt2wm7ebrFZIH+8/PIrBANS2GmfPb7owOGdH9lZIo8NMS9CEFm0YoPlxg7ZwSMnrKWzB+fEcEvKKrSvvLIZ1BYYsgCSzuBeIovuYY/famh2Id6fY63NLcx7uMe9YrTOqi9VWuWVW7ao/DkrLch84jno5ftFfn5hEGkSQhGxz7aeMNt51uxCLYwYjFFBio8pErN4u9Hs4+NmB84TWIE9mQZEVij59p02+95WGDOgtRTRLNjU1ExYXuo9UmW294pZIdBnQAOySXwl6fetR8w+5J3ZBfwWRcCIarNPacth8pyvBXIs28csBsoIM/cA0ZsdBCf4e9tgrllfc9Inthw4WGtoMvt3b4HZC43O42w+dI52XqXOGvCTqR+0EZtLe4NJl2n7FvIeoa9nboy3XYwwyDx24CQ4vRfNdl/AU5NnmaAQbT0KVvBlcIqpW/jBCpohm/YgL6cTmknMB9e/v9sHRjJtqrrjg6TzwiCzR626zuy9/bSF/q4vgaDAEH980OxnjBt72yjC8pnzGVHF1hfzvPV0dti7730Mkz8IHMtdcJBv2uKyhVYH5umOrVuIylVrcxevsqjRPtu5Y4fVNlIIMDLHT1+wMiDVYsEd/XlJhD2ItJQUiBvc/aGdH9s7H2yxqKRMm1c6h8vAOLHtggE+uucTq2oastl5mWBqnrKhkBjgulLt8A5fvpiUHCudO3tCvgkD/pg/muqqbQeMnhFyOi50wE5euAkOay4HxRgzCLh95eG9VnHyohXMLrb6qkrrDWVj3msjytwumzGLfCH9Ll8OEEDJXr7H1Oc9lvxhZLDPTlWeBy4o1WYM9diBQyds2YoVLnSp5kFEcoSwpp9+9B6YxUcsAtisxXMLiPrVZD/68XvMe5Klc5AfP3zQ0oWZPAZ159XxxE+YguHhIbt28Yxtof93uoaAwFpEGdEPs925XWs7du5xeKJ5MGpZwFilAEFXW30NuKdkC7/fbZcJ4ZgMI5kh3MQA0wgXD7X58Llqmz+v2M4cr7D4tDxLSyUC2xgRab9D3TvAMWaek2NnwLhVWklxHvjCJ+3YpZs2b24RAP4VTFuBpaYkPcw3XRPEDDXeuk4wklEHw1cPs9t0L5RDCjg23cYZc+2dH/7t31kMeNCzImfaVSJdhczKBLs6wqJjE2wWwTTCWZ/nIIRr169DKDEO4/Wk+hXRsQsm/lpdK2sswy6fPeku3PNLS1wwBOUVPNqNq5ftfmS8pcSE28FDRyw+GRit0CH78NN9tmLlCssCHi0TyLYs4K2CCZutvu7es99igGcKHWqz05cbYfSAHASqyt2wOcAr2E8XbtwBuD/Trl84ZQ9is2yo/ZZVVBwhHzB2A61WWdVEvlwYufG18qR+u98Y937G9Xzlcduy44C1Ilh5HmbQY6rcWudyERYZA7ZsMuu+z6qra2zZ6o0WOdpvFyqPEdjlAKHmZ9oLa8uhveP0IZC6B4DEu3D6qP2M6GXd96OgMSW0n8NsLA3hYS/YuKTkFAsnWlRtfSMBNWaDV50CLFsy+N2xwBLeBlc7Eli7soCFPvch2lWXOGwIipHIOhFmcDEwkMmU51A3OPz7YfB3QZ+vETFpbskcS0pK5pIxi/VxwnbBPKblz2Z/JVlBUYFFIZ0JtOdCGrh57YoNzoy2hKgQq4ah7g9LJHTyOMybgsJcunDZkrNzrb/ttl27eduygA7rvn3FPt62H3qcbgU52Q7CTuMVzLgrOMzdtjucNdvAPj5v+cUl8BA53pCD7X7XTh4/Zm0EIFi6sNQHhYb0r/bqOas4fcMWzithzg7bSEgc8Grsz6k86R+WNvFLe/Mtq2vuBk8+zm4TBbShJwQhRSahiMPdi0KPOMyZ0zMj1opnz7FsYPeysoGn7KizU0SwyuKCWgh0XnpGpuUAURloUByt435CQZ+vqrWs3GwwuKu4ODc7wY4cer1lK1z6JujQ1i3ab82WV1RimcmxTzwHJ/Zw/C+hYDQ0NDi64O/oOf7G5/dt/Lr8+ZXpSpLE7wqMUDVSwReXw5fA3bwFo7apFAaROdPAcVGxtYt8oYsreLepECYQGjRAXkU2c5LKp2gXAUwMfHbH9P7Zu7ShGSYvDUnr2E4Dss5JgcW0SmrLpdm2HAHXt8BszUICXvD9EEzaV/g+hdPzlC1CoIlUAmksZUkK3UEd/gl66SSkWw77nup3MaSby82W0te620S449JARM/AE2VCE2wb48p5Zl8da/tBxvKrjGsE4yvGX7jLQKPadvq1uxIMZd7dBUP8j78E39MN8w+TvJjLbEkyl5CxMQq8EeNvalx3wFwnw1CvzfeN6eHrYBRTP1110n/1G3haFrhvDkYZL6BrbTHrYhnvpXPxURvolkuSqBaB76goYz1E4Phw53EiEd2zC+fOEJlvkGhEA0Cw+FRzmXkFVjB/qcWHDNhf/OADoigNStD8C0lSN2XkFhK9KtZBNGn+/ZOY4LPnr1vZq/8QjOQMG+ppRTJ10davWkKAB/KlxEyZz7+Mx31vqK2xOwQH+PYbmy1h9K79t799227WNdlcosaJMRA+8cXL1ywpe7ZtWLvW0kP6bP+5c9afNMNaex/Yt8gXP9ppf/X9n3BwNhFliwUTQJKyNRQsyhe+9BrzDf5sA5LRk/+vm6eHDDjvzCDSV15Bkc0ieowiQImJG4ZBaO7st/krCpGaxCJNOGd9qGX0W6BpUMFUGm/aoaOnbXbJXLvV3OMghfzzSxqnqGxZuflWwGITZm4EEvIVaze78LHNt6qsa+9Ba26HcLEnAk0DhEWsI7y1LmSbNi6zodZbBOCpt3lsvOgxqWQL0qO+0SiwMjdYRnyYnT35p1aPJOBG/R00AeRbv8T6m29a9c16K51d+DDfdG3Q5SIP8PrU7H4ChDTZAAxerwiwX3ow1E8Up24CcZRYpIE12t1GuNoRK0L7MIeDrKuz1c4e3o0kugytkCSzfpmf8FXrPDEdTcKXM5wksY+ALHXNd6Cvoy5aprIKT3URUQyLIbhtTbes8vxlH1wUBHD4wUzLLywEx5gocoCI+0twn1Dtw59uXLlgw6FxtnHdegsfaLb/9N/eBRP1OcfoieDcH+qzE2iR5q580daUl1ocIbHPn79ozaONdj88weFEh95rsv/81x8QiOc58G5THpb9pC8yB9Chf+3KORiCVithnq80cZj4UZwwDqLCkgWWUzTimOUKgrOk5C+yxOgZdv3KWau61WFzZhfZtVaIYJCpn2h1d25XE2zpmi0pW2D1vUArSu03ljQvOQXFlp6d56Imntj3qaUTOKYMxiyXEOl6t6n2ql2rriWgx0IX9c7LO91nCJjOy9esJwJZj4s0eBymzwdZ5ssp2LfbhBY+X9tu5SuXW252Nnix8S5gRMXhExaVmgfjmI9mKtJCmSNt8UDXm5AGSstWWAES4ZbGehjSJgfLNT7u4DcTNn4j2i9h90Y96LUzRN9SBMzKfXssMn02dRdwOU0hImXYdF2d8LvgLe+yTw7s3ukCcMRGXHP99n9JUlNJ/RNSsmz2nDlE9kuA92m3I4xz0aLltnEzAoHRLquqq4XHWe4i6/nnf9L3pIwieym9iHEkGptCu4M7rAiRXpIQQtBicWhCZs8pcUGKdPmobroAzQ233IJCKwIHfBbA/QpdHGjSWoqZlW6vvvYVmHZ4ovv3bCcSNEmbIxX0hYK0F0RD9kE70wrnW8tAtYPqU94nnYOBtuGLfE+8yReSYOQNqbzNySVAQ76Zzt97MHloOh2ZkGoevGaLZS7gaVgsMMA840yyLy3zBdPwJLfBNlDlzqPOTMrSJUnqf/+EoMCWFRFCWYIxNiD7yeo583LTYQRp52LajIYQ8Hf/XE/+rk1MvAP7UrlPoj257ZLIXqsjhDJ0as1snzRcYyBhUxbtbaC+8gWBSb41tgOUJzMTmXXUd8Po0nYF3FhC3275tV0a8IUwwLnQdiINm4RiIjqil4QVd6YXkbT9NnPjR0Of3Fm/XznrfOYN0P8WyrjRRj9KGUfakc14gNFNqEdfBkwNXXASBfRwUmcec/46WDm0uNbQweWHPnnvC6Q7Hmnoyy+9SJSZBOvo6LACVEmS8qx9/su2qnwxAVd8qlQB9q/bsAnpVzbRr+5w85/N2P78pMB+Q+K+hjO4i8pXWzE39egpiK0YxhBuZfdRkWPhxRjMJOwqwQ5mhmHKsYYbfkbgZggTKic0M9GQiGUJMHoqkohMR7h6AI5308B/JJnrYQHFxici5U1wATp6ME9oaLoDyH/EhHwK9Tk2fRNqmfIPNoEOyOREggiw8Yb7uzkMsjHxGZ8HSV1CCd9avnIV9WY6aaGeRcWnWmluvJ04VGFnzyE1jM2wQlQWGpeAEou6iwAYW7d8arNy5xEAIdmVrUPBv/2C9AkNeWBHD+yxnbt3Ww2XgxlXKKiYAABAAElEQVQzQx0zHIPpzBAhf2dgxpGRyuINIkkqNwTjmUrAk7iYOBcqtY9bYb826lhqb2u1SEKbJienWhxBPOKjZhC9rcX6YcpTCDAQR7jXLEKs9hJWVcEVAk2CQIqfBWMzcBdV7B672NBPCPK59JMN5xI2n+GxBLBJJlT2Lmcy1DkS7aRIkVHRhGCNsO72ZlSYtQRPWI9JVYQ72AKpX3s0ikAICnIxkxttDyE3s7JyJkixxQwK6/Nu0w3bsnWrxWeXENghg73PATqsKH87be+BQ1bf1IrdYSC1eu+MEpa408K57acROS4jIxvcY8L3EnpbyXe5uufMP+IIGJI8a5blIQFsb28jdPUd1MWEjWYu0pEi24NBF8TBK3m6T6nEm7gwKUR3SelcSydK0AOeDWKL57MzhrFjXgTJpeAIvZ3NXKx6beXKZdbbVG3b9x630nlzOQNnuXwDyifCHEhCMtfcUGuffLLdcuYuRiWO6QzP3IXSy8+eEkSZ5nIUE4TK81WYVi207Iw0nkXyL9SuX6y0xMxCW1BS4IQlXtbpPmdyiY2Pi7EuhBI7Pv3YIlMK0N5EI2QSOwT95oCqq7nOeHajHdlvP3nrx7YNiXdz021U8l1WfeW8ffzBu/b2u+/b7WaFMedACzAJDmwWjN1AV7PtR2t1B43H/OJc2j9OJ8KAjUsikltV5RHbW3ESCehseIAQq7p6zdrrr9n2rZ/YO5jhXLpe+9BOPZDqB5EYnTl51Oq6Z9hz5YssAgZQGNTCZfaS9gPXEau+cNq2b99ulRevOiGAaL0CuAyjDlWAjiGEN32yCwwiaQ3HY3ISSlktHT2Wn58PDBxMxFjSmaK9XHv1gu3auQNt6DnrwS5xJtCIA0hyD3EJ2HegwuqbFXU18DEXI+v2GGtc2kwFh8lGqqwLq2/GfSZBFbu2WTdRAOdhAiHmeBgBhzQRTzoHvbb/Ij+/MEmwtjOmZzaLOZLEX4MlkjzCD26r8x80C3bqqtnpa/yGBFR7iDXkDu2x/fTUYyM6eAypZyjSTUWM82xkVaDWjaeFUFvcHqRu5s0RA0mqh+AjuOwHnNRenTmSHE9mgFWITDBOXodBLPGFNNb6h+65OjinTdLbf/4NmP8AJMEKM6ywx1K/KfrdEJ2Q1lP1qu06PycztLduE+ek02zzKph0LgcvFZv9xYe+Noh8kDXoJJrNZds+PcFc8119J2iUu3RoPMToSlKt7aat6jG83tirQs4he2kF40PbqhmD/5uy/vUbmEQkqU0c3tz8B3qbbC8qt7bBSPv2N17nwkSM9Pg4a6qOGZMg8CYLZ6inw04dOWCnr7far/3am0QniptyLlTvLzolp+dgF7bU/uYH37PtqD86OzptNpKCYCIIPa4PcsYRAyDmUgRMc6tnXtJvvvNWvzMvMJqSbEk6NEpITuXDNcyXz/eilzWgT0lDpDLbvnO/bfjSG6jWFcL68VnVnsG+Lux0iTiG6URIb4udrrthDS3dRBeKncBQPbYU1PJ3sUE8fOykhV+sRsPRyb4ItY7BCJvzv/yWzxeBzMnpWfatN79LtME4O3Fwm23dth0px68SSZGocqgbt+yosNnlG7m8pz22qql+kMbCDZUGlP+HsB6lRtQ/L7l3NK56h6SD24HfMzdjj8g3FnTgKcY9PjmTi+Dz2IDttBOYA80lRGWku4DJMWUY7dSIvYh9YitSulOET25qbrPZ3MDvEwL2StVVC89caMvm5gY23l6n+NT8jQwDbn9gh/WFpdpm7B1lWuGftI+zi+ZxoR21Dz7eYTfqSm3Vonz7x//kt5EAR9iubR/bz+60WcY//ceYxaHCCjAp0ISSG3atdf5063ssv28OfH+4dc34ugAVWuu028unQ8nLN7HlYwVN+hhGcnKJsMDXrl+3mhusNyIt9kH8dh5Zay+vXeps2X1ZNPZDdmT/fguLw7wpP90q93xoV8fy9ZGvf3jUdh9ZZy+uLnuo2p5U3cQ/tb/Q9pw4fdYuXr+FyVgLQYWIwoVNdOF3v00Y3/HXB/qZ25MHbSi+yEXPi4L5FbPeS1j3g5U19vq3n4MRjx/PEOA3MfhZ+SW2+fkH9u477yHA6IPxTBpb96PW3d1l+XOXEdVsCdHpeuy//uc/59yBaYqIt5dfeZEoskm266Mf2e6KSvvW65sm2O0H0oSk9DzbuOl5wvFW2LkrNW6/KjiNl3QeLFyxjovBfbtcW23NRbkIje7bqy+/YblpMVaFWcaHH221ZWVzLYaDO5A578YM4tTxE3bhZotdO3/MmZcMhOy3hYsWso9gNEhhaMJWrSM89Qr8Hu7eth+9/ZZ961fftOKSEvu7t96zUwe2WE97uxWUrYYHGW+v1+7pPqVxqsau+UpbiP3L75RDW8f3inCEy9e9bIvwnWnF7nvXzq02EJJgq2fn2K988zuYivWjfTpgf/eTj+wP/tmvcyEKTOvha5PW8QgXi8NW23LPXiJKYKSf2rjtToMdOHzM7g6GWGUFGqku/vWM2JJFpZauUMC/xOkLY4J16KHRtTokgR0wbUTVRP3EIuFMkORXNJ595Big5bPNfnLQ7MQNQgoj0RTzKdLm/vEf74AIdByJPmpoiexIg9l3n/eF6JUDmphD+CeOIV/9jn5SvjsnYNhlftFDO2tbyJM69jzQSsfaqzLd+cWn+iE7WM9EQjuNkOJWfwsJLmNzaw4OeEhjz15EAo4JQRqSaX9m/XFVRyPRlYQ9m/4QhttC4TK5GBp+AoapDlIJxhsGmyiSgHZTX6PZ24cJTYykeWkO/WIeXlhntmktJiu056PjSIphOp9iT3ITNZtfQH00dpD6LlIf5kCWGcZ4MpYyeeEMcPbgMleDx/KNj8ZL3xkTScPVp0Ty7GTeNAdKOqzudbXaB++8ZfUdIzZv4SIcvm5g41mGdIWKyaukw2sQ27zd237G4Y6N8KKlHBLVLoRpGEyUZ6Pne/sX91+1U7djLXyFEV2y7lX7w9wFhLbtspM4VIUk5yA1Hr9dP11LZyCloc8wX12EuDTMIaQxi0YS5zMFGOISiHSKegY5IO+xKZqbm3HYSSDk5Sh22d0u3yjmEESbdfnGhnn65tA/EcoaVMSHjp+xsnUv2ZqlJVxqQ50URJIuEepxCaWvSNmytTTUWq9FEwq20NJjZ9vt+mq7Wl2LRiEViXgAZAoGKLNwrv3eH/whayrEmmou2Kkr9TjNrMIJCidFbp0KEBIZE4+qcDaXrygb6Vtm7QfPES6ZkKbWZZ98usMWrNrkNAyS8gSToqJjkLyFWFf3XcfYtiJtjI4pdE4rss2cARM4a1aSjdxuRnvTg612KHbuw0iFU7DLbCRfl5POtHJAxsTMcTbUgdavdSXpZygS14zsLFtUNse2nGxwJgeShMsJs7fzjjXeHURKm4FKNBkGfNAuXcX+t6zYbladZ9677IWXXncMcDD0VpcnOSKdqNhjV1vu25de3mQ53LLFfPrWOpcB3tG/8GhCqJaWWMruvdbe0Wah0YtsLn9HESde9pMnL992IY4D7bcIQBIOhK2YE3QTwndosN0e4GQXgfTTSd2QvIUT7jUarlCmMveQvrW04FTEPKTF92OGNYLJVJ+F97c7DUwEEtJA13o4hG3Z+lcsfe4KmEocHi/g8IgTRPmCYhhxhcoechd4xLBWV3XGbkK/Nq1caMlIKJdvxJF33ip+GrKL5yrtRHWbLZtf5NZPQH2HwZP5zO//60xoSajVXjhmF5D+r1y2kH0PzUSFKRMfncF3WYe7D5+z57/1Xaf1Uf/EeO/e9qnlLnyOULvZ0P1Ae+1r3X3aPYwqPBwa5kxZ4kOtuaPL5gymU7/PLEMq97r2+845Kwrb3SikhqHYRguFQpqX+IQEJ6SoQxJ23++iOF3/dSZorYdj8pCVm2PFhVl28XaT23NyDFP5ovfSwCQRQrm4dDZ+Ikc52wldLu979l0s0tRZaAUeDF2DMgSeEtJy7Btv/iN7oafPQu732w9+9BNbsnSxpeD9LYc9zYVoT1Z+gTOJsPtplrNjtzO9LEUr+Afk74b5uQQjOhKXOWa3Hnj9ck47efQQTH2b/cM3v4kDqaTvCJ5Ya7pghzPnadh8hyIRS4yLsKZrF/DL6rKwmHwrSse8Dg1g5Gi3XXwfm2Q/6fV0LdBeHiTUdeUxBExVDbbx+eetmDDv7jzDB4MJtbScIvsnv/W7aLXwP+hotO0HTmACtcISUMMHQ0+ma8sX8XsAp8vTVStpX1kJjlqHYEb5jr24LZ8HYwOD8/cwZKtgyOQkJrtY3ESdQ1QRjCc0yTlV3eX8vt0KQwVDWpweRBtgrGrqzN45iEp+NnXc4SCHucJHxz5CyvhbX6cuVO/VPL9Dm67Vw0zCGG+grWJQZ7CW/z/23ju46jPd83wEKCIhCeWIhAgim2BMNmAw2DiHdufpeKd77qQ7tbu1f+xO3dmt2t2auzVVM/fOjR2n293ONgaTc04SICRASEISyjlHBNrP9z06cBAYzsFud99avYU46ffm9LzP+zzf77VWszeXm+HD4XfQPJb2WQ5hsnutQfi/Rv0iqNv7CLkvLTH7+jqPgHcGga+KtLPjiUN+p4iz9imPaYI/yxFrvDH3GfgewXVdLqYn5QicCC1Xyfe1pQjYZWbHaOtNi8h/P88iYDMHrJwyZdGegAJozlohbTV/HkIwgugo5c0j667BLZOO6enIWjyt+q+hj08U8BnNbj19uZbP5SWUpcHsLcrVTNsW0eZyortYaTYVgb2Cvhig7NerMevIMEumLAqafG2N9dbUickAgtL1kmJrxL5iZu5sp2mJRHBLxEtWC2w/tjYN2DxqAZSWpBHBbur0WfC2e9L6qv+XAHDj+jVrpMJ9fVVWWoa2YuoUq7icby03I2z2zGy72d3K1Wy7dbbWWK+F24ali93GWFpyDTMSNJk3q9AyXbeZ2A0GczryZ2yonulZ2NtewBv/+DGbdLvVbkfEWQYOdy31N+w41y6bNq6yWdOz7ERhCdqkGBAsiixn5nqblxpsnYcO2nEE8olDzdjPJGBPnuJ306m/ehG23nnnA668p1vKYK+VXL3snFIGO+utkgk9Yx7Xt1FhVlx8levROhs3OBHHlSrs1xDMepqt4FKhZcZHWEPHgK1ISUBgZ/HwJ7AQT4yKsbnzFzBuMPsJ6uXgNOAcQG72ttne/SdswZOLGWgdeIdfxcY8xa5fKrAJE2NsIg5a2z76xOqHcFbhOr2cNu9MYAOVd6yfIWxiNKgEcXby/BlLnnjTCkpqbNmmFUy6bjt55LjF5zxh8ek5Nj7vqp2CDlTP3AIZIzMjzbqbqi2feIksFgVltbbq+TUm0wx/gzb/c0f22EBojAUP93NlW2RTc5YhjN1Ec5Vv48JjbQYTfCKC72nscRPDhuw6C1QO7SGb2fP5F3Diy2JNSQx4wxJSQHVxPp7y52z56tXWUH3DhtEKx2OKU3UlzwbCUy19cohdvHDRImLjbbiv2Zp7hmw+5ioNN4osr7AOm9F4K0SbFxWXBSIHC0oAYVruXLty45CdOnvWbrVctyiu9+PRbFaBHHO5vNk2PbMc7/0c50AVQT/ns/DlLn/ZpoSn4TF/1k6fwyG1qdSi8ZiXM6K/Qex7CSkZFpuYypzFN6G7za42D6NVjbaGiitW2YR9+9w5NpHq5FG2THwVpk1JRWkQck+8HgSbkvbxlhg3CWFUm6EfgbEei/lHFCYwGuvBvfXWeKsNxc1k68HsYt+RPFu7/mkLx8u8uvwqh+ssFBVcUaPtkcDew43ZRRxlvvaD1y0WJYG/64qnZMNcrbeDMnLGQjHfMUxwmnqG8WGIJe96kAlKLH3GfNBR5trJj7mROBtu8eFcyU9KttzpM62FG54CNOjhQx1WUtVi8zZuAA3I/7GuA+XRfbssFMeT26CLXMbGcNri9fg59NixY6csJWs6h+hxduBEPuYCaXYdpIK+4RBnIz60aIEdO3TI+udNsxslV23m/PkW6m+bU/lQDnHZ06Z77IARKBIYw0lJSTaeNSP/5GkLSZxuGXETQPy4aBPw6h/uajSski0pMR4zq24E0k5ra6lDydZlzy6bjXliAAIG+ZdePGFHzlyyGbPnYPtfy8G+Bwe/RPaZMmvgFm3dqnl2/MAei0hI5YDfZmXks3xJujVWXbYLHMKisIcsKbgIQgrmIdI6+Rl0c9BUecU+3LbfFq9YZR0t9VY27palpGZYU0WhtQyG4ww8zWbMmoNMwi1AQyR22DcwT8LkiUNZ2dWr9+yDudNzAtrP/CzmYz+GGPSHCTINYM+3124iBCHMxrCfLMhhX2XG6TWCcT+b3wvKnQxsr64EqSHZAzHWhBC5diFCHf0kbWKgQdrHVXOJRe0kTKOZt2jSWjrDc2XfyudblO8pBLRxaMn6ESZXsz+WVCOkIchtpiwzEVAxN/U7sBZxusJEgfzk7CdBtZW0ZFq4iPqisHCmDvG0x/gF2O4y/gXDhoLClsznmSxPm/iToTS2vlpblT0OgVLmEc8ivM/iMFGJ8B2JYKlD/jTa+SZxUIxwRYHQz+/SODNHsAfDZhvBc2IAdfUtowRh71yWOcST9NvNIrTS5PUCMoAE/Zu0w0x+U+jgPWantnYmfUt5h2KpC781ITRP5tlnpnlstdWeusqPmpxsL7/ymrO10w4tbZc2SuWbgt3vCy/Go12JsCBOoBs2bcEpkQbVj5zIJ3NC590fJUhjca3ogvVPiEEowJGv6Cpal3S3cPXQN7oGv4UWpJBFKQRhfuOmTTYdw3lpzIRuMBA8GTPFLhzYitF2ZHmuqP2sjCCyntmwgU3+nLXSFpue22gZeIT3cUKXvfBtDJPmLFqGuUAwmqgCi0iezhX2XOYIGmoGzBEcy1rYHJ57/llLJ14gQYeVOGwzO/EOL77cY2WchhcHY48J2kQXmukhNEgSnAouXgCaSiezdisqq7aX1i2xFzavt4IrV+1yW5DNW/EMtuWZzn7O3/ylZQ7VYCLEJCTjrIT2h+sHQZN1dHQ4J5JItH022GHnzlRZcESsPb0aWKlJIU4THo6m9CrOiSHY6GTNWhSQECwt17yFS0CIOWEXz1+y7CdW2pzp2OzhhCa76siBm9gqp9rK5cs4eJy3io5g2/zii+4QF7p4KXPzJIJioeUsWm2zp2W6g52/9dZzEoiuM1baGVzJ0xfaqlVLufEZbz04L40fF2kR0Qn22ktb7CJ2kZe5fp+xcLk9+cRMJwSHTM6w3Hk4xPkgC/ibt7RBoqiVeVIVZgG1leOdkLdq1UpMBLpQbmCTLU9+nBEKLl10N0ZPb37B5s7ItmH6vqcdTWhNhcWmz7LFi3FqDQ9MMEjJmmErl/XZKewfx2Mb/NILG7FPnmS1Fej20dgNc9JfsnqDDZ/Ns8LCq5YyY5GtXDjTQimXzOBOAfMVHB5hL27Z4ODs/K23TCvuUBJzUEtOTbf5syAiZ7xL49aNs4aDRQOVYWhCtK3E4SMGE5zR8VLSMmx+Pw5ijFuvmYw/ZfClopVp1YzbsRaFYHML4VJjXTafQ9g597C5rV37tE1kw5XGV/Ovu73VchetxI8kNqD55S1XEGWVL0ZRYYHdpn1XP/uSZSXHOjtdjXU5RaZn5doza7qsoPCylU8It82vvMpBPI2yrAVaLc8uFhZZ1oIV9tTs7IAOfCrDJAT3IiD3ejB1mDb/KXtq4Sz2OYQv1rZYrnzHoW0fh/PWOQ4fMhFZ9fQSy05LstQNz9utoyeY40VoTHNsHX4JQm7xc1kd0TJDPzyB3Ym/uRzoU3FCExKQ5tnQJDSyCNwRaL7zz+c5/4hNL71u2RnAhHU02mXa6+a4ENv44hs2i005xJ9rX2+j83oLZ5lY5lFNZTkOpjUWHptkyfGrULL0sLbKLY49DzjIoquFKJXG2cIVG2wpDkGtNTetpKzASq61W2xcpr20ahV+C2jF/Q06afFvMggnteTdBKJIVHSsrV4f5/LuxhaSOz4OeGzshNv8ljsTO/l4hB8UI6P3wZyp3JBJgPG34f0t52M+F8QiJnnDv9BfhZr1/0BF+zP/nh97aqwFHrMF+qI2WmvKX4E1i5T8pzJbHlGXtrY2552bm5vrHIGEEzyEUKsZpqv4cE5n2iC5J2VDQliT5hShXU50wRiqSxOkay15NXsQL0bi4VgTKMybtIPSmtxmcdLVqNKWOUQ/5g/hgo3Thjh4012ljUc7Jbgc5TE63mjThYc2ARV115V9/W4T1rPa2IVXiSpfn6i6zCHGISD1umc8QkEwG0cYzXGL9hvkehRkAU7ATjB4aIaf/+MQ13QyTZJtoNbbPjZH1VGONXJq6usboF3CaHdOf7T5QH8f5h+chgk6fKm/VKZAgjThuobvJ69QBKsJCEQ6FCg/IWJIQJLpx02e0bgIxxZczkT3xOM71TvQ/ta4EUSfTE4myCGK8aR01Z5q91Bp2zS2qCdiKzc49DnlUdlUbfWLF280oDqTpuosUwNvmICWVONZGiTVW/URlJqQXDQew9W3agviDnIQFFqHyhc8Mga96fj7qjro5uWWS1v250GujeWwJKc0LR+aC0NIvWobwcZp3HnjqUxyKPJbE3tfwQTNN+TSD2fM6GpcbSw7aN2uyclRc/D+uXRvvPuS9fMLwQIOY1fmTA0QBjW2wzR26X8dtsfhJKs5R5Xd/BSSg3xzQtXe0pI8RlCeGscaOxFuPWF90Wfyk+lPMGYHwjAeHJmH4SNrmMak+kqoBloXPOUKrAxujeR6nlHrxpnmtZQH/fSxG8f0r1vrGG9yzJL5l9f+Vn2jw4n6Jow+eezAPOsjP60ngglTe+hqVXNIa+gAdVSfaPzJVlltJdMktY3yfZyx5tYo1+YekU1phZOW2kP7hdpYba71R+NPZkEqj2cd8Ix/OS7rRiCQA5fiqz17Wde94qLqHcL6KTxqGpM6yuGYhZYwTBncWqp1lO/u2wdHxsLD2l5tdZobs8WLF7u99GHPftHfxoTgL9qCY/H/IC3wz10IjgLuRAuGd9HQoqM/3898cEKL9zdvQz4onve3QF7vyUsRVR5evAug93f95P1O773f+36n7/0NvuVXnHvSUTvwne8z+t37jDdvvnDP+Zvnfc+N1NWbjjdd5ePNe3S+3meUlu9v96X9kC/upu0ROvSoJ13V0RPRm4+3zt5n9L1zZAxMJvAkeicfz0dv2qPz8n7WU+6ZUe3kiR3Y/0rzvnR9kvDNR+PPV8D3xFVZRo0Tn/iPfOutAw/6XW8l+oB4j8zrcx7w1l/5e9+rUt6x7i3X6OjeZz/v99HPP+jz6DT02aXnrd9IObxxRz/v/T6QV28ainOn7N78qLX6kwZWE7tw5xl9e/fLx57jd9IgPW/a3u/0We/1p/fe31UQ7zN67/u9PgcavGl581N83/fez3r1Puv7nd4HElwaqpc30qh+9dTnbptTmDvt+4XzJ19f9BJPXm50u9J4PnsLdre+3vbw5q/Po5+9G+vuu69SCH7MS/C7hR17N9YCYy3w4BZ40IS/ZwFgQfAVCLypPCie97dAXu/JSxF9FkXPR7dT3ZfkffHue+LhX/hT/s975ovmfadkD6nrg/J+0Hd30grgzYPSGV2n0Z+V/IPiBZCte/Tz0vVN575nRrWT77P+vver7CP5jB5xnrj+5vQ5zz2gDqPrOfqzS+kB8T4nh0d+7Zu+73tFHP3ZN7GH/eb73MPej07jzufPqd+d3x+W6CN+e2Aa9+XnFYbvTeyBce995JGfHpSG73d67/vZm+CDvvP+Fuirb1qf996bpu/v3u8CfXVp3NfGo1P5A7U5+T5or2J0jy6A++xbX733/fzACH/ELz366z9iAcayHmuBsRYYa4GxFhhrgbEWGGuBsRYYa4GvugXGNMFfdYuP5RdwC8jGysuG5JxRZN965zuc5bAB0ylV9qiySePmxtl0uhNowLl9ORFkRzWE3ZtstYSpOQGbKV8cSxVStlwCW3flxYZOdlbeE7OLL4M76hJM/QILMGURVzaPsg0LxkbznrxJzNl50VaykxRpgacN5Xzx8Hj+lkPXX6qfHHRks+etlze+7Ehd29BvsiGlibANhTBA/cdDel52qx47R28s/19Vd2kpPDbB92orXNnIhx+dTaRv2R4Wz7/cR+pNu3rHqm88N275TXWUDazy1neCLNI4UJA9srOH5jd/g8a+xpuDoaM/NWZ866U6e/PmB1c2Z6PK9xqD6ne1tbdM/uar5zztiR2gxpJsJPlTWr7B2S1SR/W5+ts7HmXD+LB4vmk86L1sQYe8a4EbMx7b+tHPKn+NeYwyscfkutwnnkxQnD3yY9rHetr2FuN9GOegB6NbaFx7rpM13uUPALbySHuoP0KFNfmYQXNJaWgej7bxvTPW6Q+tkfzzrDuKw/yYMLLuPFbW1MGzht1y4823z+9Z/0Zs7L1QbIqj9hDChsoTULiTp+YLrmAab6PSUdqyReZnFzQPZAMsW3CVy0NmIrKie8eoP+VQ2t5+8xDvsPeMGjfuGcak8vGuYbQ6c0xzdGRdcHMksMr7ziE3Zhlro7Wzsk3WXFbbqN4qo55R3orvCFxYX0bHe2TdSU+U1dovvOmOtmv27XNP23jwlx8V75F5/4EfCHR3Dbg4ck7xDsbRY07f018uaDK4Pz7RVyMboee7UWPMrzIoDeWttdibrm9E5e0tm9YklcNbTj3v4vlG8OO9S/MhZVd+KpfCnT1ipBz6jrfOkeLOb/rSj+BbFz2udlYdvMHbFvrsrZv2A5XH+93ovvH8Evj/Kotvn6rvfMviW1Z9rz99pz8FvdxTFr7oAXu1Faah20J8AFdVXuxdHe0OckbOCAlJHna1frzRWyCdwGnYEoBnmfiFnF1ccR7vPyojx6z62jpwSMG0BDlgMjSdk/Fq9gYJLfIobqhvwJN32NVrMuxRclZRuInDUFOz8EtDQGhI9Ebz61Vp93Z3Wl19o0OCSE5JAR4HJyyfgaXytYJJ2wpGrrBzU5ITEJbHAZ/UafWKR1unEC9yVDy/CsBDohjtpI9aOvssGyxSbbbeICep1pZG+q/LgkFiSARmKCJ0vNVW3wBDt5cx4NnQUzOyAIMPC3iz0gbQAQ5t383beEMnMA7uChj6zZWtDUzZ4EgwlSOcg5jKdjceXtiMM9943rI/6lUboChtaxtbLZl6RUXe9cLWJtENHnAz/Tp0O8iSUlLx6A8FNqnZGhqbXL2VfjyEHnGMBTmu+RNU7n6wX5WGnLDCIyKBL0plLN09VGlMtLc0MT86YMQLpn5xMPuJrWwAqLqGkXEaYan0eaCOMx462WbGa7uFM5bi8SKP9AHx1+Qe6O+1Rsa6WLLiEpMtFuxCUWu3009NwAS6eEBOReJkFUgYBF6nhXHcDjj8OJx+UtKg6AUlwXesq30G8KDvBp0kNGoy6DKwGY7E6+jshlwxzNLSUnHY8zjVBZK/ntVcklNsNziP2SCA+B4+XFrk39fbZe3kFRpB+wAVpDYTg2A7rIITQiZadlY67RF40JhqbYKmOigEJrXJzKO7QrjqrXWkCzSIoDCxjcnBlrKwTtaATc1xxBISodGNDgCezaeIOlT1aJ1pghgDqD85Fyoo3yEcwwRT2QlKhmizE5NT3FxmuSf/bmsDvzYphXWBxd53f3AJPOS/29S3F1z1+oZmx9AYCYtaUlKix9lR8fi9n/lXeaPKoVRo7IkxLSoGmEggF9Xv7Z3CGY6wmKi7c/MhWd75SW2tud3YAPQZ4zgSFAQ31n3gxnS46qF8jU1NOMcNW1Iq9QaXeBiEGs3zZkgTosCpjgeOL2Kkve5k8Ig3g1DLNzU1gwTRx7oZDuY3YxbHOK8QrrxbGmqtrbPHOaZpzY2FiTIydBzzrI05jhM28VI01hUvgIaXAN3V3gLUWRv9GeYgEKPvaT+NNfq8vpZ8BmxSbJzFwzAndrtO4jUB/yT0lnig/cT4+qcU7u5Mf4BSMWasut5s3wU8UePMvvXU3UwkmLEH2vuHgfMCkhSYOVsLrFk0+9UnR8G9Jd7UTMg0FoEdK4CAAALOkdAxmn14BBg0IMOWko6wgn1DE3i1u84C08U+8+frzU6eg6jhCps3szQOZI8fPwfsEGXRpPUnqD5C59p6DAKKWsqcDkbvYg/zmeLj7GiXr5tty2MR4NlXn4YumfX+IJ8v13lyEFTb88CKbZztT453n2E9sP3nwd9Vving8a4GRoa05ZmstoAx0w7y10v6TwHftpq2LqSuBy4jCFPHp58AUo7vHuewcbcUpIXwKWKU9+jTaiDP5s4wW0efpkSPPIVAq345yHiAdMemZXv65gCfoZnXemWD7ATf38hvQMoJLaCvp9F+9+tfWWkljTQhzFKnzrK3tqyybZ9stWvXbzjQ9LlLnwZia5Ed2fOZHT2VZ7d4bvrClfb1F55hwgW20PnW53HfizCivaHO3v7NewiYkU7oic+aaT/+3rcYh55FX0QV54/uskMF1GEYylYLs+deeMWWLZjuPHwvwfL0u493W9qcVfYffvBaQEVpa6yBgetTcJjbAEfvs4Tsxfbic+uhBZ98pyOKL56y7XsOIgjCVgeBwEvf+jPLjB5nJw7usktVbRZKvMScJfbipvWWDpRSIGGY+t8ouwI16Xt2oy/S/vP/9m8RBie4JAS03wZ97t///G2pPKWrtZx5K+zNDQvttz//e+u+HWppEDpIg7L62TgPtFMAmUvYa22otv/xi3+0lltR9qMf/Rj8WxafkdDb1WGX8k7btq1bLWft1+2V9U9yOJFXteJV2a9+/g/WbpPthz/8wT3xvPEf9qpNsqOt2bZ9+Hs7cKHS/v2/+df2xGwm1kjobW+yTz/60IoA646OQPMfPcW+98ZmO3Vot312KM/mzJ7h1pt5S9faUsgEBFzhT5AwUnjuqJ04XwoyQR/EG122ZMMrtmnlgpGNVkJoj219723rvBWM0NRokXGp9s1vf8tqi47ZXoC9pUXsB+h72sLV9vrm1bS7f8gY6usW2u3v/u7vLSwmwTrAQl20bK0bb2EjEFD90M1eOHPE3t91zJKAcOoZCrNXXn7JkqLM/ukf/8nFa+eQu2TlesbbOgsNADqqrrLYdu4+BCERBx8wxVPmLrdXn19vKYJnGgnNtRV2cO8euwAz0Os//Hc2f2oyUE9Xbcfuw9bLQam5vtoWPP2ybVrzJMQ9kd5ofr2q/iVFefbuB1utH1a2/+t//jHrLgvvSNCYEEbs3k/ftSMXyu3ZV75hG5+abfnH9tj+swUIBqLRzoSGNs1CiXc3pjeFz3+V8N1cV2F/9zd/bRNS5tn3vvU1i0i8W++utiY7B7nC7t17bekr/9I2LpsFTHa97d0GY10dwjeCWWTKVHvxhedtWkbS52f0gF+0NjfWVdlH7/0Okqsu+7//4/9kqWFgbxLcb9Ul9tGn+60fjfNAF4fd1Bn20++8ai3VpXbwwCHLL6mz//0v/xNEEyAl+LTXA7K65yuhfJw6tAuc40YIuCD7AZb06S2v2Rpg7xwaC5tID/CMJ44ddkx8EnpbEbhjpy627z+3yHbDEFl0o9W2vPaWLZs39Z60H/VBGMsl4A5/tucEh7wwK4ekYwNr9rNPr2CusnEROtvAad65HVKJKpsECcxgSLS99fpLdqu7wd7+/fsWDa16I7TFz738pq1etug+ZsWHleHGtYu2+9BZ6wdNpaO1xaY/9Yy9CA62V7kibe+BrW/b5QaIQjgQTQRpZs7ilRZ5s459sYB4N4nXajOXbbQX1i8Dbs2/vVH92QNp1T/9/d/Y4IRIDpR9EBPNtX/xzdfBovbsZ4McMsuv5ts/vL0NXORY2n68rd3wnD0xLcH+6W//xoZColhf+ixt2jz7ztdfuxPvYfX9qn7zc5kNvDgSaESichrMWPZ5i2Gw+gYOwHYcwRNZ1GEE7+H9Dm5oshFWKxEmX0J4PXEJQZW/H6/xXxhVHhz47QDC5bUahFCEMjFfGel6A2uHXSpB8C1D8GMcSCPaiBCGwspWzoJ6mGeB+gtoQZIADEmWlXaZbVkGHTRC5mcXzX66biQdVjfB0jy7BDxi8v7oFMLe0wZBAlTKlJcxbe+cpoSBrII8LuSpvcRrIe2XnzLbeZx2q4C0IgchnoN5L0LwOxwqXnqGdmmmjAicczMQNnn+RQRu5oZ9fAJ8X9aDsADr7G1P76uY+o5CSNJL+71K/22nXChZ7PXFnmqpX46SXyfrxbc3ejS+wB7aFsrRRlz2ZnuHNqRoLsgPtrcHAoyIGHvuxadsoL3Oth/Ot/JZKXajoQMcREgFbjYD3H7UVi2eCQZpMIQIK224s8auVNW4KyBv2b7KV11VTYxJtDe+8U0G1xBC10k7W1ztNBcSghWEdzx94SrLACP6dl+7ffzJNrtaWmELZ6ZbyaVzkC6UwKoU4zQ5gZa9Bra8Uhb6l19506JgjHv3431WDk2tVwgWuP9FyDQi4rNt8/qVdvXMfjvF4aE9ZYJdr223l199A4zpNvvdR8SbMysgIVibfu2NMjt3Lt8mp021CjYDaYa8QZtYUf5pC5481TavW2od9RW28+Bxew6g997+mzbtiaW2buUStEphFgvep+CH/A3SrnUhaB7cf8jCotAqMvZ11e4btN+2oxnrZdHW1Z7g2CSYdyK87ideBILcECcxL1yab9yHvVcdpZErOHPMboKLHDJOV773LnoN1WXWBKj982CHJkUF2c//6dfW1L4C7S1A9vEZ4Dk/h4Ym1KLB/PVuqg/L0/ubBNisWQsteepcND5N0OQetlpp83UydwHTEsbbui2vcu0eZpXXCmz/oWPQUreB4VloU3IX2OzsNHCkq2x3Xqnd2siE9DMMouGtKSuywYh0++YrW6y86BS4z1ehTV1maXEegbKztQGM1GJ7Cqa0pbPS7OPf/caKICrpS4BJMDLTXn/1eSsrOG5XSoutZflTlioAdT9DTGKGPf/K6067eL3ghJ3isCxtuG/A+AHNIwyIjI9BcHK1rsQS78XXv2ZDQMaV5B+2YwD6L4dxzX8hGFMAhI6Ka4XgPheCS51q1V0MOJ+xrrkg2uIzhw9YTfstS0Qw7+Wg0cs6thdGremLl4MNnoEmNtaCAxaAB6wVGt8duw5aUlqm9XC9rvHsG7SVtKJp70cQvMlY1AGxDrrSCyUN9s0f/pmF3+q07Tv22KXi6wEJwaqXBOD8MyctfDIabDBo1RbeoCv36Pg0e+UN+gVNcWNNuX10qNDBAopeu41Dmm4GfNEGvHEf9SpToTlLVtmMJ9B6NtZxuDpu9RASeTETtPaKPvyFl1+jvsNWU3HVTqDhmgEu9RDzvJ2bmEEEc5leBRrEdJc5bbZ9nbkqFsZ9295Fm8+N0t3lzerKi62qsdteev0tS54UbL/5xc9M5Ee3uhosesoC+/qWpy3/8DYrLyuzBfNmg1Ee7ncx4tNyWJvTYWhstxJYyK5yg3PTCTeeJNQGfcCYTZk+15YD2B8Dc6j2kP7uSfZySo67Pb12/igkXtwc+PTXowowBKxnPYfGhr5w+85bL0KGcd32Hz5LPZ+xnOQYp83vgTUy79Qp9rTVyDS5kHbsYnycQp2QY40DE+27r71k7bWlduhYPiRoz8BgF+3iPSrvr+J3/3eYxygNih5bsQDmtmRtRvcmwM2Q5ZVBGjHTwzg2BSVVHoLjmVKzeXwH3bVN5Ra4kM8SHn3G2b0JPeATGn/oQBGAUWBx03zPINUaVY2wdYW/J7JJ16dc2m9ZS2Qq6OIEkqeY3/JHyi4GtRzqXFBCvUlE6eigKKrjWIRusuC6GQERLWwy9c7mWW6IoIEknucw/YBa3f+V6sJtl+VXkgZ5Tkuh7VI9LHA9I/uAnglifWrsRNAkD9VNGqZZ1D2GdpK5qdr3ywgSgvOue/p0ZqaHha6kij4YSRxlD/ShlDXes1dgpsXVK+QdfM7gr5Y+yZ3uIctQFC1okbFJtuWFF2Bby6CsQRYTl+iumPW+ub7O6jhVNyN89A4G2bI162Cvg4mqvReg7ni3yH5JVQuoebQJhMMglpmeZPXVFQikdTCZzbewEQFYiU3gilDXgVnpaVwTRqD5DEUACnaand0HYDdb4tFKaeMSpqbP3vqIsgxz9dTktOFTs7MtZ+o0BLKb1tyijYJAQlrUGjl1RMO6pGvMmTlT0FbX2/WyChtGiz41i3g5xAuSycRIvEfkqp8l9HW21Nu+HZ/Z7fA4t7F6KGSx9R0RyGS/WHWj0pKn5MDalonWIMkGYYrrgupVdmTNXOddKynlUNTrruvuu1r+vHJQr242h4O7t7PohiJceK5aRSnqOwZE9bpk+RpoeqEXdbaZXPNhtnFw9zaY/MJtOqxesl28iSDlG+/zsvV+3wdtd0HeKbtQ2WkL5s5yc1y2g76bTRMA96GRMZaRnoG5QqZFjEf45upSk3IQxsNrxcVcLbe5zdt7xelN/2GvssWMT0yxiVx7VkHPWNbUb7nTsmg/JvtIkGZ9StZUWJwSHf7xuPFhTkusa+rKYhjOqmAdq6+3tIxMisPi5GeQpq2JK1AxpyVj3pGZlg6D1gDCBkQVI2l0trVCEd1nmZnZlp6RbakIx2K8qqupuRsvHWEKtrsOcb0HECbBQjc5Jsppoy+XVdn8BfPvM2OJQihavXqVJWrxHQmTYhNgE0y1REwwNCcmQVgTiO29xnFbY7Xt3rUbJsCpHBRZyJmrA8xVr3AnvO/iC6fsdGG5PTFvFqYKIc4so76yxCqauxy9+OFDh2A9K+VQhi2nrzTlLeiDXhFC25ob0Oh+DBskzIawhknQFxatt80VLSwy2pavWW8zp6ah6feMhT7wdYWLHAmEYzS3DWHBQVYLdatvvAdleec72kosd6eOHLTariDHPCmKdmEyyxZVwSkBYG+Mhz2vvbnW8jhwz8xFU0sZ0nPm2JpVKzADYvN7jCD736SUdEhxbsFEetlaBsZDA55E/UfGLIcJ4Q8nYQ6XEB/L7UAd7G1JNm9Gljv4PLthvWPne4ysnb17DNf8CRzSSq4UWFXbEIRgGcyzu6n1cush4ogwsHAnYfYQw41PHaYnzTCAJrPBpzE/MjMyOBx1QeyE0BBAiIlPxrQizBqqyq0Ytr05s2diBiJpwhPUBrJtb2dsXLtWYs2Qh8gWenK8xxSlvuq6XatudfGCJej4GdyNQ72HnEMMrZo3k8I4CLVgojgyZp1pH6YaU6ZOt9T0Ke4mpq2pxqpv3HCkHkkj8SJDb2P+RDzG0Z9KuLtKfsklksZFQnAKgmhMBBNjVPoofawLQU2/iyFU5gockq2FccHhwjHKSSN7S9qcANsrkvzQyDvaY98BqnbXAWjfGfJA2BQ9rw7PKGKw30NDhID23kGzn+0xa0Bg9Nq2jir6Az+y9lm7t+xoP1V2FG53yq4xJ+33sQK01FcRQhFavYx07NN2+LLZ8mlmHJD8D9SHdc+G6EXmhmNui59EPuyrKo+C5sgyDhWfHkHTTt4SlqXlZn22Q2iF8yo8jHGj+8dFDvA/1nHrJl/1n4Rb0U5z+HYHESXViSCOSaKdo/7vHzL75QE+0ybqF8yV7AQC9IY5noOCntdiGhoW6Vi/yosL7VJZg63f8IxlIdgtyM22ntZGJnqf27SHGXDh2HnFQnebnZlqVRUlaMEDER6V45cVaE01KFrgehbAQWwFe7ohCvDZ5DzCHbacaIou5UMjGgfrU2aCnT5ywJr6gqy+qgLBtBmq42prwMbEV5v6qFI6BzPyElC6FkVdN2oh8wYJqw4wnk1JAl8E7TbEaaoHQUVFlHAooUm22Q4E3hvxEa+6jiu/ct6KG/usD2rVGyyAHdj+lnEIGBzRUsmmr4/rNOeQgwbTObbQVrKLzkJIC0affz7vrP3s5//DqprFPuXZWB+RNYMIzVB9lR3Lu4ypwXirqKyyZsw8ikvK74w/paFNNBwTlYnYnjrHGOI1192wE1ApTyJeeWW1J17pvfEelX8Xm/15tJ067NaibevCtroMOmhpt72hH+2XBoaA5d3Y5gQ6wCITF59o6QnRVoIw+ttf/9LyubYf4Jo+kCAhR7aQzdjlyvnmFn+jDxDj2J6l8S68XApz2gLLhOUrDhu9MOyxSwrzoTCuxBYZtq0Rgcmf/GWKIXIGjRflJ1pg2RrqGtwbbqL9k0be43TnIaYQaUxPTz8aasWTQsATb8Annjf+w16Vl8au+rqzB9IOhG8syu+JIqFoIgxZvuQI2heklZQwnl9cY6tXPmWxAZhOKW5R3nGrRMPb3tJgtdj/tzfV2Y1aDqAjG4eY2Q4cPGwhCKOVFRXcdDVZ6dUrdqO61o3JBJjeYiJDbP9nH9ml0lrXRvcU/PM+MGYrSq5iUlDLuh9kZRVV7iBSfqPGzV9vtOCQUIgsJsLIFub6RGMvjuv42NAhO7B/LxrSk1Ze1cC6xPTxRnrEq55r5kaj8HqdsyevqqzA5rPViktvuGt6b3QpAm6xATYjGPX24Qjq9qMgC1N5sJF9HGIWb9oanzJrambzGNIaLy2L1lufIPvYVmjiz1+rtakzZltyHJpHbkHENvf4ToieTIYG+6y6qo6D7nh3i+PbdgnJMMGNg9r5KLcLx9C6wlw4wFgfQPMsLbaCyGKGGSODHBwCCRrrg9xcNDW1QHoDEQnXvFpHvEHzL5WDZhi3UMWwjv7mF7+AxrrarfW6sZGPSV8/ZD3M19FrgzeNB71KEdOHwO5xHvU4keq9CIi8+5Icigcw09A6oP7RfL7NntOFTbhn3nsEdJGoiGTEbfoPyuyP8N3dFvyKM9ciNJ7RoxskbbzSRtJ+0FnyHcKkNLj6g+zGUPp9KYG1A5sYjxAqM409mExIU3myFO3lXLO/eB0ThfVk1W529gaC4t11/JH5ayEXm2Knyk4++tMh4E7Z+V1KB5lK/ORZTBiOm11v9AixDfVm9UzkDAT30bbLD82YNLVfaYGRACphcoAySwCVAKPPInLae9VTtx+vw9a6GNI/TC/w07Lnl1OeJ9AkIwxXIpyqzF8kqE+ZfziI0Ke8cvPo2oCiuKA2Ur6yh/7piwgLtHE9grHmRE0t6xgCfHrU3cMBNSCdITt94FM7cbEMm8G1tnDWVDeBJyWk2bpnn7NVT85BoImy2/0t9v6771hxdYflzsq1Zq7g2rv6qBON8EcIWpxCMON47Rvftc3PPGXVl/OsFp5oXb97gpx1eu3CiX12GHuhVSuXWQ7Ce1rWDJuaGosGtpmrTK7te6DE5IQQyMlZ7FRqawm6ugKWIClNszdICJMGQVeYEsx1RTsBp4XIEScuefC7eMTXYkZSfgUtrLqKnJOT4ewg5fTXTx07WAi9ZgnSTophSlorCcSO3lWak4kx9o3v/cj+zb/9t/bdb71liRParbhSG4j/G8VEtHkL5s1hg2x1DpJt7e2OQlZDwNvqD6pIJFqr+XNnI0C14GTVipOTf/F80wrmsDY9Jwft+U2rrq6h37rYALqdHZ73uXC00MwM2lwIJmKcgkkMp8lla5+1f/cXf2E/+clPbFlukpVXVFu3JnSAITV7lr359bfshQ2LbO/+w45BzpuEhILBvk7b+dHvbTAszp7fuNZCmayHDx6yFes2249/+lP75uubbM/2rVDtivHMvzB+fDACZoS7YladBhBINVbFWOcNolPVeJNmXD2hw1YI4y0qKgJzHw86ipjtNDXCRgQFb1x/XmMTUuy5V96wH/+Ll+0iV/TV9U2PjKb2qLtRah+8+57NwEZybk4ah0E2Gz+DrsbjUrIsNyvZOe42c/sip6mO7t47QrCckHJno5megN0087mF+SxHMjlFpkzJtXXrN9pzGzfYvKwEK6mocTc+fmaPoy3aTa7NOhDAW1rbMfdo5+DVxeh6WAiyzKm59oMf/0uLHB509tBRXJnHsyh71+iHxfb+FhYZazOnZbF59VttHeYnaFTkADf6ABMJVfeml17D9vxVu3h8v7UjtKmPv4yQlbvQvvGtr9vieel24PgZBG5JwneDGM7OnTgEVflMmz9nhjvs3/318d9JsxqblGU//Ff/mlvuNLtees26fOZqSnauvfDiy5bIRt6Fh3Z0dAQHyzhoij1rnnKWEmAcioYQH2dhf0uUmJplL7/5NfvGa+vs+JEjHufwkci6SVvz/Nfsp3/+5/aj73/Hls9MtHMXCx1LaGJaNuYpX7Ovs/kePXzE+Q34m6fMrTTHxYqoNVtrt5zgIhDmvcK0lAth2EC72wieEXvfeOa96NQVT2uDi0dcxXMblL8F+AM/x4X0Hygw2KV1rUHQq0HoakU4q2Rt0jZwrASNJwLfvEyPPevwdI8zGfKMJbBOHjyL8MTVeiFC0lx+48bG741YtWGNtXrylIB1mzxb0z32picwt5D96X9A2NVkvFqBiQBlnJGI/XAlgiOtUUe8BgTHzMloJ9CY+htwvLWFU9GuniMe2s1LpDc7B812NfUhn8XUtQYBHJkCL26PcCizBJzz7bOT2PAuhpsbAdBfgUPlkqAj049pCNeXy7AB5js5u3ED5uyOL6huKQjCtL00rTpUhJKnNO67yhE4EUhrKdMwKyDKoC88Ljls21zaeu8ZzDSyEbip5+xc+p2y5TebLaIs3Hja6au0C8/eZi7IbrmO33bS588upz4++5AWsvrqK3YA4/BujJj37fjUzqI1e+Ol59A4XrRKOisIFIOV6zZYGggR0eFBduLAZ3aGDXfavKWc/qO+tMVP7e1vGOKKuKa+0kqa+y0jMdrKytDsBYVYOAOqGoexfgtH6xRmJQWnbM/JYlv3zHq0BwgQnATnLllpMxcsRYLtt62coGoHo9x1pxde6NFlYINNTbPgc0V29vwFix1uwiEy1BISYrkmq7fLJdW2aEGupSXEWGlVqV0uTbf8s+fwGJ5js1OC7czpcy5e9K1G6xsOd97jj87T84Qgj9JzZttL6dPQRA5YZUmRVTDBFjIR+tobuarvxpwlzqbPnGWfnM6zqylh1lZTauMj8e4e7sQuuZz84qy3jav59kFLZEI4kwV/CsBpMC45w1557WtOCKssOm37z1yxJQvncUDqtDN4h2ZNm4YTyUSH0NDBdUnnhBYEVUxnsOd85fWReIWncFi6ZksWzTdZr/g7Hydx5bj+2edZ6KEB7my2K1zNL5iba8GYBhRdLLGoxCyLT8203gtHLL/gomXFBrEmhhrDAO3gJRu8HWyTI8ejNW+wWVnL0Vb5v/hIuLyIbWQIQkfQzW4rKLgMAkMmyvGb2OIW2rjQCPp7kr37P35ufWHJtjR3GuYevdZ5G60OdSwsuoxAjMlMTbVDCvFFVnhU04seOiVjim0/ewy781lWVIh9ME6e0Vx3lxVdsFvh8RaB0BSHBu5c3hmLDpqKr0ab5S6aZVOSQu3I9lNo33OtgHIOBoU504ZH5en7eykarxa8oybHRtlVTvMT0PJLs11XXWlV+A0sWjgXWY26cg3V3tGB1laaycnWWF5g+w6dsLjpi2x2VhJCQadbK4QQ4U+QlnX6nEWWMW2u04ieO3nUes5Vsl9lWlvDDQS+W1zJp9jTG593tro9rfW2bedui86cZ/NmxdnuY2/b1eJrFhM8YOUswmtWJ/qvHUUoyUCYfS11CmOddRab/uMl7TaXfu3nIHemqNTmchgMY4PpwgZWCBiD1LsbQXX8RAQVNoL5ixfa1QunLWxSIuWZ6k+V3TMSeuIQxDY/n+o06e2NVVZYVm9PsqYMM8+KuIGLTsqwATa+tgHWd8wBbly7ZEEoBOTwqENAB/bZQoERykJUKMgwtLkUKP6EfgTI/NMnLDaVPDoarLS00hJSnmC96eMmphCTB67rk+MwVam0k5du2JY3VmPnPZG5gPCGRlYoQ+3uwNCJ4N7rhFOvrcDT2AAAQABJREFUIPeo/AdA+CgvuWYdOJcmRgfblWsVFjVlIRrPfiu+dNkmRGMShKnPBMbGrDmzrbz4og2FJ9r0GTOsteo2TtD5VjY3zc5cKLDQhFnccEY8Kst7fi86d9wGJky0iJBxdgkTk8jYyYzZYeyLS9x4mzc7y04fP26xyWmMg0bW9wbLXrnarp4/xdrAPORcKl+QKJzmRGvubwiGHjklc6q17/6IuVpuLTeuWlPPOEthD6mtKLZ+9okoBJEsTOvyz56wzKh+K6msZZxk29Tp02370a2sDRXMuSvW0jfeUhNVbhaeP5GASPSHC7qBPXgRIRTBJwyB7Og1s80zPVpLUFlsA0JP13GzI2hl5/D9EgQnbiSt8xROc3wndIhVs/zfiLw10VX/kQI+scG019PxVQhnCIp9CNjSNs8lH6k6uImyAf5kFsFNkp2v0LUsDmNPm81EQJQpgb9BVO2rlpDfabMTCKL4O9iKGcRGAJUQiuKDq14EQOqlY/f3NlM/8sBB1yISzNZRz0j/1t97isR6aC+upm1p52PkO3cO5g+0W1mp5+ARg2nCK5TrNAcAhSfR/OYk0sYIqMcuIYgS/9ubOJRMdMXyPPSY/2Nmhkc6Tn/06VHyWzIPwXcKbdruEcBBZLJnFyAkX0BbjPD/9fUe04nGBmChKPNTrMU6GHiDFqcQbGvXbnjWXSfpFC5IrWhsrZ7FTvg66BDBExGqpk21KBwM1qzfbOlTSqyHSk2dNsMtMv4urt48v5RXtJ03B3ssH8/sU5yYh4OCbd3m520ygsFlrpwru8LsyblZVlVVZW2YdBw9uBfNWJhlz5hrL2/Z6OFKZ2Ckp2NfORCBQKSR439IRZu8cmm9HTu6n8lz2xauXGPTMtFYddTZ+YuXbf4Tc9Cqr7GOPXtt+6fbHAzbqy8stTjG8Hjsj44f8cRb8vRa4iX5nbHrL+qhusgUpBd735yp2c70oAWnq0uXim35WmwUn1huM9g4j+zdY8ERkbbp+WdZ2DkglBba2dPtzmZx/spnnX13sK40/ArCiw7BEYQJTeiTDVp6F1BcUZhU9WBikWcxspulKY+DxnAN+JKgpnN2CG/QN1/cQDwWAUIvgkt6Rg/C2CS/BWDFU976s2E0JuShek+OIU2uhIsu5FnmoljLRXhYkHvDzuA8d40+XcxpNQm7xcvnr9kpzDgEDTcxZaYtmjOdA5PPRFAGjwjy3j566izmFwMWEh5lmzYvZy6Ns5KrRRYcm2mpMSHYz6OttC7bgy1rFNBSTzy12tbgwX30dL7t2nHNaWe3bKEvcM7zUyZxV8ypOQh2mUW2c+tWuxk0wVaupT0Z6yU4CXWGDdjKJ3Kww15hW7fvs09qii1mymxbghAWg13WnLTLtsPFG2+r1q+x6ImBLYK3bvZYHgc3aWAlEG7ctMVdfddcv2wXixrsCcZ6B/U9eOSY9eA3cOrQTq7jJ1p4W6Pneri+1Roqr2E/G2svvfQS5mL+jXd35cvGL20vEpizh86ecttBT9V3NFphSYvFY/OvvBRCxg25+RwFZFY8tvCb1iy0i+eOuRvQ7EVr7AkcSfw3EWBdpI/0p5CILXZ6b7hDwhnsbbP8/Is2DRvc4YEuO7RvF055aOUKjtlRNN3PLp9jFZcv2EmgiiTcPLNhI2YxbI4BBB0A9IdBMutFv02bloNNdaQNYdtfcOG8zV0RbyEIhmdPnOE2rgtztWB7/oXnLIpNsrzwJM5RJ93Y3Lb1Y7S537asFOaNNDp+BD0mW9OTefncdAw4h8R1T3KNy4Gv4HwejlkrEM6iOXCX2ZQ5S9mHU8gLfGDWo5baMg4i+5zG/Ozxg0B4xdiTc3LI2t+8x3GTXG+HzhaiRMPBMiTBnmEch7DGll4ptNCMYEuIjbDK0ivMqQJuAifiIPeG5WSlWMKkMLt6rcI+ev8DRIIwe36hbNcDW9dv9nfZ8bzT+E/0o7ALsU0bNznYu4KrKITax9nc2VOso4n1JT+P/RItNF7XK0DNqC08ypq3H411H/FCbdOGtcTzXwBXXnEZ7CkLprJm78Zgbbw9uf5ZS6auxWU3rLw9xFYtW2BL1myw0ne32qefbrfQmETbsHYVMJux+GcV2KHdOz3xUFgpnkw7/lRCEGpqlg4/Qz/SZNn/gWfZz/yKwK2fc8aSEKg6yzwgmv1R1+Q6CEjI5JDqcF25IcWxw5OsvpMwqtspaVj93gdHSsXc4EqPjZB8FdTf48mfccuGTN68VxfIdEBlk4Om/DHcrQY/cHPBpux5ziXg538cNlmMPWWXRlN2usrTCd/UVZpxIP5c5hxOTZCOusURgoO3nipXoIHbBqfplW2zFBnSLmH24/KR/KTDiMw01AfAkro/acvxRcJwns88L/vdLyOoLPL1EVav6qQ+1DhQG6h/ZfKnvpH5S0ykR+jlRhT7KE8/eUWevqiN1pLyn5k4k9x1itccQLZmoSzAwpr12N6xIYwIiTrtSysmkwPZffm7uH0Z9VYawgoV5/nMGdO5/p1g1WjW5OgTFT0Zm/NExmGoNdVhozUuzDnBdYOfWA/uogsIzsKmzZqSybygFWi0RuzpZCubAWRYIEE2v93YpFZXV7PgojXCESOKTtZ1bVVNM5tWtslhrRWc0vrGZgvHOz2TzVlX1t1oxBRvCA274mlzCwSh4U45Gfi9Pd1cTbfgaJdh3dghdTPQo2LBeWZyNeGE1Qi+azAmAsK0jeSKogEHqya1x/hQS01Ls1jgqh5XY9BDfrqmlIlEGHZK18urwSpNRjs2DlzcGmvCOF0rXyw3C6kIERM1UAmunCwckZNiXH/dqY+/b0hUUEqyzxQG6wQ2yBZsu0MnxQNJFOGuzp2ZCP2aPiULwSDEfVdbV8+cvW0pHHziYinzyJj2J1sPhmcruNCkwcSLiUuwtJQkHM2GsFVtsCBMFhLQql+7do01z2MnLwEoLgHnIa5rmxrrgTbstnBsVzNod+EEB7JJyd5cGMTVdY0WwVhKot4R9GdjbZXDpxUmsBBJGrCPl8NjMo6BOiBgkINQ0Uy8BlA54tDIgyEawOasthGudVNTAzBYXRYKRrHDq2Ucd+Ds2Iwn8LScLBNUWC15yBFJNuipaLWktZR5Qp82AUIwZilTMlUutDOBBsZ6B9rFlo4ey56SjpBW50zpotHUad4p6HaoFUelYcZ2Ig5j3XjT12FHPMg1XCK3WAmTY936HGjWer4TRBBBhUViazt++KZdr6yzKThsBSEY1tXWkC+bEiEeDWEch8I+8q6qbwZfHeFMeLUIp4+z72hzGwQCqryqFmevdOrY667nw6PjgMAaRtNbjxDc424XMtLS2WdCHBxdPfbb/YNsjGw+06fPYI2ZyDz3rwS6Hexg3dR8GaLtZE+fzO1REGO98gY20sz3WDaWtqZ6Gw7lvbMBnsByiu06fgplldXOPECHFzmTphLXXydUpSHNujCWe/q5qaI91W/jmeNyDp0wcTLjN8zdNmhdnTQ53lJxRJV52k3ayTtHdBhPwjYyUpqzAEJXR5s1NIC9zLVuJHtKRlqKu8mR70gPtr7ZOAMLoUYYylBysP4k4fsUx17QTrx6zOr6XbzMtFT2TA+Jhr/Zy/a/E2z1mtp6G89cScKJKoYDnuAFb2LEGoOGS2tdA+OtpaPLJoMFngBeuLT/nUBfVdNfE1y85DuQbg/LW/vo6dOnbfHixR6l0MMe/oK//UGF4C9YtrHo/z9uAQnBrSl/ZbcnYDfzeEv0V956XiE4NzcXe0cZp4yFsRYYa4GxFhhrgbEWGGuBQFrgqxSCvYq3QMo39uxYC4y1wFgLjLXAWAuMtcBYC4y1wFgL/LNugTEh+J91940VfqwFxlpgrAXGWmCsBcZaYKwFxlrgcVpgTAh+nFYbizPWAmMtMNYCYy0w1gJjLTDWAmMt8M+6BQJzQX6MqspjVw5h8r57kMOznMnAdcdhAcc5RHI9J0cqBw+KrTxwegGhNHiL6NLFWQBAAecUN9oZEft6h6mofOU0pyCnLjmqqQxyWpPznn/m+i66c7RxaVAn+TaJjc3X3l+OOK5c/K620G9Asbp88ZNx36m+geSpnNW+KrfSEPSgg3YalYicz/C9cuVSviqLt6z6rPqObiNPrQL7X/0t5zdXFvUpf75toHLqT8/J90dtr/JrDPDVnXb3zbUXKAkBc8uRIkIQSCNOQ8KgFQVmGDjB8oQX7m4fGKdDJK7nwnFICAT43zfPL/JevqZyFurEEUY4uEEMQjEIReKV6e0WYfTKqaQTxxHRXQpRQQ4U43nf3tnlslc6wvQNxXlMXPX+OivdBKtVWJSuzchR4PSiIZ7g42HqcGN5ToxqE4DQCmWwiiO+HzD2HmHouXhRxAsNzDkNZxlnG82Ak2Oi/qKg7gwF//WuA4raB2IDgbYzyaJGPOhVabVbP30oKuHJOFs4QgvXGv7/J8/tLhz8hLagthNUlDcoX42bHuhFxzH5J+LBrXYX+YH6Qk5mofRFuL73ieeN/6hXT7+CwYAToByVfCG31L494D5rjA4Pi9kqgvzDHG2zsJrFDCiHNY2TkMfAy9V46YcOWv2uOaF54m1zEZnIiUyg/SKW0XgQgYTA9zVWhOMsrM/IqEnOQdJfp1LlqfHWxZgVHrUQMoQDLUKA0UH4yL3dPIdDUyjIBsFMfjFNCQt6/EPijU7nvs8qA+NGznBhEZPcmPUd68pDY0qY4cpH2KVykMMhxsXrJF7oA+Ldl889X3hokzXHtQYFsTaFUOdJjGXfttM8E0mK6GzF1BbKM5G0j9pBpAGOXUzfKd496T/8g+841lwNj4iALCj8HoQJ4fcKZ1wU4CqTSEPU78GslVp75LwcRj8Eij7jLZmc1AZw+NNYjwVdxeug7P1dBApCcFC7q821wqtMaoshNgihW0QyBv2GQSQFjSGt85q/t0hDZCta3+SI7G0/YdiKWlhQcHSxe0btIyg2jVeNB1FMh4JMozlC0wQUtL5o3nSzfrl5RNreoN8E49YDBJzw1kXMo7mgfW6QedKNs/Btxr/mnuZJIFmLaroX506NN2H3aq6q7zxz3DMeBf+munlopFl/cYqNYu/QOq++cJi/kVHMP0iUJOD4E2gz9eU9+xljKRIn1vvLT/uCCHKTPhdxRihOqsJe196uMajvIidNYu4z/+6P7E9pvvRnxv8lwe9Uh8C1ajuMO2q+31EYq1YNDiwoLTZCJX8nroQfIUGU1nsEIiEXMG7wLoRIog5mGrKjzQKGDlMawsUtqyUrBC0hNXgFXWUuwbMJfNw6HNGFcKO9DudHg7HUrhOngXxxTHc4wf52lCabBOsb1KWikfwRBOUY7LuPSuhsAS7sOu0hBk+VCehGK62hjVooqresfo5Nb0MqjQryraJOt0hT6BBeeUflUn1hRbUO+kBtrMOGygIkqVVS1k7aSk7RivNFxqXyYp67vhMmtBAg5AArFBAF1ge80OkX+lZtL5QdwaHquxLaQLjOQuZQm90OA1sW57jbw8F2/ugee+f9D6EfLbboxDRLwrtaOLSXz5+yjz7aaolT5zmWsJLCc/bBO+/YfsDTg6PiLQU8QjHUfFXBbbQMarFu9Xe1wNjzS9uxaze4u0V4KkcB+Qd96ciAGuzvsSt5x+yXv3wbVqlDVk6DxBCvvfy8/fU//tqOHDlihw4esGMnT9n46DSoQRP8FghbG6ps56cf2wcffmrHjp+CwjgWD+p4h0jhbQst4lXXr9mOj96zwUlTaNNIG+hps7PH9tmvf/s72KTyobuMh+Blsv+bpBsAPfa3//Wv7KOtOxwj1clTpy06fRbpTxoRwlmeaSMhB+zcvs1ugCM8e1qmK5Y2KIH/H9z9qb23L89WPrkgYGFQaahuB7e/ZzuPnLOc6cLjZBB6cgCNoMEO79lqv3vvIztzrsCiQFKIgbThRvEF+8WvfmP7Dhyy2qZuh9Kg7wMJynsABI6ic0fsv//6fZuaMx2KVjl2esIgVKnHDu6xt3//nh2hXzrB2szMSKItSu39379tn+7cA/Z1J/TCoHk4Ycob079XHSCK8k/ZL3/xcwtPnmkpcXfbfKC/2/Z88q599PE2O3ISKDUWiimgf5QXnbF3f/++7dq91wqvVVgijFPCUvZ3gxT0VCMMYr/++S9s55794JVXOsQNeb/7rp0e4aDHju752N7deRxq1UybcLvXPv3gN/bh1p12pbQcGu9EIOPw1veN6EfV5bneVF9jv/jv/6/V3Iy2bGh0hXDhCbct78hu++D9j2z3gcNWAYLF9Okz3QHZlR20lp//7X+x2qEY4NESnVDkR5asZbfdfHnvt7+xbdt32Mkz+dYF1vOMnCmu7dw6yngQbvSV86ftg08+sIPHzllQdJJlQwt68vAOe+edD+w48HS3giOh34U2Gm2Bv+tvZ3uTHdj1qb377sd2+PAx6749wVJBWfGinKgOJRdO2n/9b39tB44ct+PHj1kpm0zGlCybMNRLmU7aR/vOWVZWFtBqgY1zpe2Eya42O3d0r/3D73fY0sUL3OFNvynowNcKZfHxwwftxJVG4DKnodwCt5p8333nbdu975g1s0lng4YjJj/fg4MnhQf/P8jBoeDsYfv97z6wvfv22/WaJnCqoUQGisibRltLo/3sr//Ktu056FjbCq+UWnxaDlS+IA2BFXz60C57f+tnlpg1y+JBkghovKlP2eSuF+XZ3/zjrywsJtmmZqTcKaxY8i4XnLVf/epXduDwUTDaw0GfSYREahBWxjx7+73fO3zqCEiFpqQnB0RSUnO9iP3tPdv22U6oqItsErjo8aB9CFpP/XGzu9X+8e/+2s3Dw4cPuz0k72qNTU+Ltv27P7P32A/Onr8EgksS6xKHFmnp/AhCYupsqbPf/pL9DKxr7We3QyMtZ8rd/UzJqAy3EJbPQwD17id7TNjp0eN67f/8T38JLJ7G4HErKi6x7JkLbBJwVA9rdx3aa2pq3JgWYdMfMvjXCo9RAtrDOGzau7vBCi4xA9vb/vLFuwlRR0ca8Q/bIVJAKPr3b5qtm4GwjAD83z42mz8dSuXJHva4JAS0QAKsgvbeXrP9V8zeeg1mtFkeaDZvGvSD/XIfQiFC2b/5GhjF4OYCOWvb8sympELYgQAstjgHG+bnqsRBy66Vmv3qFKQZU8zKETBnzjT72hJPrhKQCyjPb48ifCJ0/s0P0XrSRrt4HpnYkunnHRfNvvE05bk7p7xFfujrOfB+62hrDuX233ea/T/fJz0JtZQdIiY7fo58j8FIl2P2L58FKgeZ4Dh1PVlNO1PWONpB8GqgR30hKViwaxcKzT65AjlIutlW6rZhGX+0v4L69oNDtC35TEb4/eCM2ffXIBTT9l2MBzgl7ATxvrmc/orWQgrMVhe4jKcLYVKbbkNdzbZ7/3GbnR5nxw/ssv2HAQ8HE1iwTz1sCoeOnLShsFhbnB1l2z/+1HJhLpOmw1cT7QryFfwnwPTl6zfbZiB6CgA5P7p/ry1dstDiAKp1k18aUBbCr333exZ8u8+279jlsGK/Cejzv06e4RaUGsDFTxw/bTHRYNYGIBhMCAm3uYtW2MLl66zx+iXbe+K4ZaSnItxk3al5S10FbFlv25XyOstY8RqHjdt25cIZxkWxvfLWv7DhjmrbiVAWFTnJnpzHZPQrMKBJpxeIsSWrnrGnVyx2AkE8cDnSPilooRzs7bDf//pndhHKxFWbM+6k3NvRYiehG71QWgecT5DTyt750Z83SptJcHz/Drt47YYNBU+6h7HtNhvUtcuX7ERRo33vRz+x2pJ8O3f6DFrgfjuzd6ctfeYFS5sUDFYxJCZH8+3P3mKyBBAGoMCuvHbR9h2/6DTR0r74hjqway+XN9kzW163hKjx9ttf/dZyZ6bYtYtn7eakTPuzF1613R+/YxeuTLdYtOBRAeCISugoY2Pef/CI0/qIrtkLK6gyiMgkk81n9tK1kBcUILQdt+m588ELjrcXYZIa7O3kUHbU9hw+bVO+tpn+4jTqZwhB67zmuVc4TITZgc8+gTL2hOVOz3HYz94kRHN78cR+O3up1Fp7gx1cVPu1a3aja6J97/s/sMKzh+wYTFaZmZlgqvqftzbohppK+/Ddd6wFqtEYtJK6ffENUQnp9uKbEEl0t9uurR/YmcIKe3rRNOtsqkao+L21wiw5Ga2eGBYDCmjj5j/1tK14JtxulBXbZ3t32KoVyywFHNQJLDoSuOrLC+3D3SfsmU2bLAOIvolozzrqr9uuA+dt3abnLHioy/bt2Wa5c+ZYVgICjVd78YiCCLs1O/cJm7lotXXUXbeDpwqsaEq2JS7OvRNTGtfxoZPsW9/8rsOpnchcjoBIpOjkXvvlu59ZVPYip1W8EyGAN/3dHXZZ6wVMnl1Os8oG4g3MQ8Glbf/w93b8QolNWfiMm/dtEAgdOJZvWfPX2GYo4j9+5zdWmDvPlkCm4y9mrjSZMfFp9ua3v2P9Hc12/uxJO3L2kmW+sIb9y7PGSEveDU39c69/26amxDvhXNjyOvRcOnuUdfaSw9HtFzweZQ1k09P60lB51bbvPerIV6T48A0iSsk7d9FmL9/A3hpjb//2Q8g7gE6DFOW97Ydt86tvMPejAmbpUx4hsFKu3fyCPQ2G/PWCk7Zn/xGbkvKag57T8SkYQpKvf+eHnv0QTfi1glN2pT3K8o/vs96gOPvmd75r/a03OLR9ikLmh+4Wyrfsn/deLTQeQXTZuk22if2sMI8237vbntJ+BtmCV5gVNfPV/OOsf+ed0lPMkLfYn3tvhdh3vvtdlFLxaKDDLH7ynxZOsGfUfF7tv+D3GpNL5vM3VVcB9yamPT0cTeDLqxA2EcV1RS6tMVj+qDJhbEuC0SwBgc2DNX5v5Ed8ElbuwnkeYVLrGpr5e4Iw7DcuRPvJc8pX8+BIPuVB+J2eSr4IxcIzDkDuAIPS7BgC4Lw5kGSQ92zSOXmV9MnZTTPqm0x93lxJechT2mrYWa0UYXnuNLPlsxFE9bn+nqL69WExbfzsIurMIQJlE+xqnjwVWeYeHLYdPTK8AA6jWaYRBxCcFyEUZ9POmdQ3PJiHKeMXCRJyD9MGK54wALI9FMiXKtBEjyRaXYuGnDw20PbPLKacLZSXH5+ivSSMZ8WjFab86hMX6IBQQOxffPEFy0ia7KhkNZHUYRPCohwer7TMusIW7mY3knzW9Nm2cMECRwzRzqb4x6BN1tVoRNRkmzkdjFKE83auO1LQfE1E7e3V9YjGOG1KDsxD4WB5VlvQhDCwPcHSZKMSSUZyAvWF4Qo1qs3MTvFbM6d2E4ak0ro9CC4w+IzJaIgms3j5htikTHv5tTds5pQEz/xAeBV+bVDIRMvKyrZZs+fAdtYF9myjG7++cR/1XlfTbTBUias+CHB2mRV4F0rPYh3NYv19e4LNTyPVXRn3dNiZk9B53gyxNcsWoiEZNWkflSm/i42q8NxR5lC/LYUpbBJXMRK6veE2J9E2sC7DYxItC23rjBmzLAitWH1TBxq0UKuqrHbXjcEw2ySCHxpIGGTTLysutIOwG65b//QI2cXdvJWW2NUkHDTSzre5qg2nn8QM2AF4eE7ODDSzmVBnp9APsJohzPkbpH0pu3rBTuRdtWmzF1gi7GkSgO9WHSIRhKbc2XNZCxAy0bbKTGk8/6WkS/Mbbh1t9FdHn03LzuA3fvQzaKxHT06yObNmWmY62M5opm47YfLuYtILTqlY8S6Wt9v6p5c7E5EBbkJqquth+EqzNHCDc2fMsFv9HeD9dvuZsx4Di5YbhXNnz1ps1gKbNy3D3ZbcrbeeGWc5M2Y78pIksLrDtGBQtMa6G8Q7Z/E5C6H5hpRGm9W9ERX5c4No0UPDJ3GImUoXdnPl22KJaVPAfdYh1xOtn1uB/FMn7Nb4EJjGih1DnEyFGmtu2DAkP5mZWQ4XPDZsCLKmZneN/bkZjvohfCI3S1OncoDuZ46Cjws+c7IoO32Cm1eYH9TX17kxJhMUmfnMenKdfet1HXTAzw2gzt6kddgrvHjOisoa7Zm1Kxyjq/riTmDdlonVllffsrUrl/A1mx35dCO0SmmRxjhPB1d4KsqMa2XVmIWMEg7uJHT/G1EDZ2RPB9t/Am3eCAHKbTT4aFS9jU4UpxVlDWoGG7eVTVbmaMIRLuTm7QwscvPmz4OdNYJ9w6fM92d13zc61NTcuG479p20FWvWcsOkw9q9abSh/e65OcwhcIZl5+RaYlSQ1ddU2dWiQrvFHLxx7bJduQKJDHtCoHvT5MR0bkpiwBVv5baqzaZmZ7kbDVdQ2lz1TExOtTRwgENhGy3mKnz1quU2OQ6sYPaShsYWbuGGLRbK7eAAzK3Eyur2sxlZrg/bMH0SS6SwwL37mcZ6dflVO3Gh3NatE0tfpGtfjUEJx8IpFkun1tYQ1h2K+ycT/mBCsCqpdp6Z5rn69xmj3j6DpclsVjoCWIiWKo/WshTtpEwkPj1h9uFJtKato4fZo9sOEyHLSUbbGMFC/4AagsluyTEICwi6LiB0FdWgDa5Ce3nMo8FsQBiTnaq/QYfKOoTYHLS4ooSWuQO3RcZ8cEFrbDLyG/MeUGmPgI2pkDsAsAc7so428mwNZA8YKZxMNxzRCBI3B16LJV1vtbXZsa9aPM84xRLlQSFmxXUw5HHgeP8wGvNC8kWIl2AeSND6KYG1kXrWU3eZODSTDjIbgPCe9u+mPsw7Fxr4XeYOyLOAtiMU8C1syI7m+nI5ByD6fkGOx1zDRWAQjWMDycyeimYMAgHsWgQYfmscbFvLV9t0KAVlc6QwxBUVFn+QI0SB0UtluXobQkPsKwS5B7+C/6S1leYtLCTILpw9bde5hkxP4brTZ+KL/U42cX1Qf548fZY6RUJcEOmxLeTU3QXNcDl840ueWgblbPg9i/yjqiC7K111lV4usMKrFZhCpLHweEeEJ7Zs1WJiY9HekacrF3SomD70MWjLK64Dil6HpqPHkX88Kr+7v2tgj4OJCVra6uu2Z9dOe++j7QDm6zAyMrhcn04AbD3ZJsk2kyi6zq5EiDt8voK4sdDc9psWVR0eZCfrV0CIb2ussV2HTkOGkEn333TaWNnIefc6CWyTANPvgOq1pLzcCQ9tkCwMMkDnzJ5uNaVFtnvnTsyGJkApHuVXtt6HujGzOIIZTnxqBhopzCKwzZWNseyevUEHt0wWnoK807aLa8XIRK6moVUegj0oAjs92RfGovXvR3Dp97veHq3b7h2f2cTJkFRw0JLdcUtTIyZP2P+OZO5sCDGxkBBeW1Nr4Qk5lsaGGoH9sQ5LeQiSbQMhFo+9noREf4OEQW2oOkSIoKC+tQ+t5lzG291EGm6U2L7DJyBrSLZhhJNuCAf6MUiNQmBuqK2wmroarj6rMQ0b8L/eKiDj5vRhTEhYdBInT+TmccBaEUZ7scn0le1kKytyGJHT9IyLgSY5wV3jV1HWBBZqTzzRKctW28+aj4zjcMwuSq9csqKr5ZaSnIE/xt16D2CWU1sHIcZgH38wmmGq8umO/dbQ1OqYL52fAPakYu9qh2Dgzhzxowiy35Z9cS1sd2fzC9HoJ0AK41kLvdHdWggN6fnTJ+yTD96z0wWlEEjddoQS6VzRP67deWtdhR05U2hxSWhQGGP9CMUdMCT1+wizmmvxbLTOrl9twr+widj43+qz8vIySFwgVWhtd1TOgWjg5eMh+96bva0cYvKgdo+wGG0qPiGEW7gEzHFKi87bju1bbdfew4z5Gvts1z5uFKc6v4uurm7YOluc/4i/Xd4LJfUxzDvGR07GRHO8DWKbrHTE4OYN3RzEb2PvH+nm80TH6NbR3mrNELo0YRs7wNp24cxh2B3zkXP6vNH8elV/B90esPNnzlhVcz/mHdCk3x1uvJfNbTAstAMc6MtsfPw0W5g7xZIzZ1hYELddxw7boRMFNm1mrrOJ9ytTHnL7GbbF4VwVXzx3xsqqmiBw4sDpk3dbY61t/fQzC+dAHARZkPwPutn8HWlHbCQa+zO29eOPbfehU47Q54+xL39efe/dGT/vqcf8nvXRCaE+64JbZCQ4aWPS984OlVcNRO2TupZPREh9bRVMbnz/2+OBC8FK07seeBc1pe20vuQjuUnP6Dc3AfhNjngoz2zLU6ytCKV7EBBlEhFQIDEJzlKEKG3WAVcnb74ShL1CuX6XueBz5NeMAC7q6B7KMEJcFVC20uzeQKjdk4eGm/QkEKu+7laQNpSN7Z3JQr7IC05DvXguGlm0sNC920W0tGLyCzTI5OXIRbN95zEBaSG20lb/+vSxyuJ1fPNq5vVK0VwHUCRYizw24/lX0A57FQMMkt6uVqh+L7HBJ0MJnWvX0Sh19bOQy+kIg2PVS6fREE6Y42Cs6UTo6cApKgjhWY4amsBfddAElw3k+JBIe+nNb9qqxTMRho9zwJGTyC2nfZH2WvVOmTrHvv3tb9vE4Q7Lv3iV32VXNWD5Jw7bRK795szIZrEJrA5Kezya5tUbt9irW9bbJTbfak4gKpdsrZTv/WGcTZuz0JbOn2b7PvvUtrFhdGHWIAfDQHIfpt23vPoN+8lPfmqbN6612qtnrQiD9QEGgKuzBv6ooO/7cAwLxkb02NFDtgfbzQaE6LMFHoazUY8/+CPtrWvQQQTIvFOHbe+hY9Bql9nRE+eck4bYBYPQxGRhI7xwWoJt/8SzIHcjjIUhsOVdvGabXn7Tnt/0jAX1Nto5ru0DmQ4D5Cuh7EL+Gft02w7H3nYmr8A62CBVP2nc2hHS2waC7SU08GtXPGmNZRetvg2BjRrJoU79c5M6jOcA4y+DlibQMNej/Zy2r1w8YwcPHWKTarS8M6fdzYjq7fKnDDpYXL142qrbbtqap1ejDcNRiO+jEzPttTffsrlZk+zE2fPu8PjgRn7Qtx4nx7bmOju4b4+l5y6yBXNmOHMAb711La+N+dL5s7YDO80mtLClFTU2dcEKSwrpZ3P8yE6ev+LYESfKgcOvQKsh2A7cGmdNjJWj0MKeKSi2kkvnuP1o4uDNWKduCrrCrobC+Tg0vgtXPWMpMeFQhQdbYxXjg3jnLl1z8aph2gqkz9V2dJat2fiCbVq/0oovnEAR0sv652lz5a/5vHjFRtvy/BZbgd1sZeEF62DMidlyWHOdZ+R0FEyfe7Vq/lRf64sWvyeWrbW33niFNiixEvr9zhyn/slTZmD281P7wfe+g7Y70c6dOWUNj6NlGVWgfg5Z46BXP4uWe9uO3WjVa+zI6Yvupk59rjKMDlqHJydl2FOL51kt9vcffPKpXbvRZJNiYtBI3yu8j47r+9lbv/j0GfbG1960lGhjnSh2tw+e8eY5UL70te/Zn/3oR7Z+1WJrqLhixRW1CKCDHAiO2P5DR2DVq7aT0IwPaCPyM9zkUKP5VHatiDm+nXEGPfalQmdO4x3rOpwEBY2ss/SRDj/uDABT4Io1G+3ll1+1Z59eipKg0po4OAQStEZM5BbrZebqaq5xjx8/gRPzyPqisahA2zfWXLfS8npbvvwpbiYmWBUmWtEp0+z1N15HKM6ws8ePOHr1+3vJk8R9/5Omxtu44ImYTn3dVi+ZTTsesxbvfsY4FrmFwvXii7Zz114OOtftwvnzUMhH2fd+/Of24x/90BbOybZLpw+hLMMB2e/M7yvNl/4F4tEfMFBR9Y0qrDprvKGgc1pHmUJMQmOp7zRn9Ccfpgw0pbLVTUBTKGrhW4GNE1cZpXUn35G0scE3FFtcJ7Bu8ZS3TK4zyBfbcbwoEcDJVw58vSPCrL+tI0FTtsuXq8ymoURqRJCGCdSCEOga0I7id2QcHj31Hcmf+YJDhFl2pnE1iE1xM1pbyhdoYM23T7CvTc4yewEzBMa9tXWSF3WfTL2QvV19VVea1oJo+3iEThRBFsl3cqTDhPBzhKPPL41kMw6ntn6xJy434FZczB9CfTp7WS1tgH8amj0Eff5iaN92hO16tPtJ/N6K0E9RnRPiKoTxmYlm//FD2o6yJ7sys8n1tNn2rR9ZGBre8RA0hqBNCNM1jK9gyHvR8UaheT13fC9OTlGcSNO55hUiQiAi3OfXNZBfZJ8p56x+nI9i0YrGqxNohB6uC/qx/xg3ThseXyEYBHNFnpKahE3cBGzrhCYB5XFDuR06V2rPv7EUrTmDKcAg7+lBTiJRXJGmZyQjgOShZetBuEELx6LpNLA6kY0K8UnptvGF123lum6ruJJnnxy56mg/Rz320I8aX9IQibZaB7oEBC1t9AM6LSGwBKOlGe2QIQ/v2U+utez5K+w2jkTXiy/Zzz4+bKufnOvs3R6aofdHTpxpU2fZX/wv/6tbSyqLTtv+M1ds4/pVjDG0gHiPSvOWlJZpr3/ze3io97IgH7RLNb3Qfwbbyfomew6a0czYNKuvq7WzZRVurtzfSt4M732Nz5hu3/nBFNengzhFNv+Xv7XVK5ZYDBTR8ogfF4zWrrrcBm8HUQYcWiIy7cCenYwRNhd2yUYmz036XtTHk/hdzkJ+BTQNoWimfvzn/95t0E04qW3/+H2bsnI96+sExlsvyvlx3D4NWwEb0M4T1zCDeZnD1VS36HY5ZISJUCjHQe09Ge1aizso+ZU3D0kQ7IC295P33rGgpDm2cfliS2RhkVAgjbaExOzZi+2nM+YjjKKprbpif//hUXvyySU4DubY9//sX9E+XXZwx0fWOBjpHH38y5sZhGCx5bVv2EZs7XqwOT687XfWHL0AR6VkdzMkJAxR8tZWFHOwOm7ZC5bbhpWLUYIE2UtvfMs287soZQ99+jtrj13ouVb3c7lw17wI130cPiK50kxIiHWCYTfaUKEDCNVEtz2JCfE4Q3f+f+y9d5Cd13nm+TQ6onPOOQCNQOScCIAkmElJFCWNbHlWHtleeafG3qna2pr/pqZqa7dmZtfeGXvssSVLJCVRYk4gcm5koBu5G+icc855f++5uEgCiXsh0fas+qAat/ve+30nfCe85z3P+zxs0sPcM7XTn4SkZI2cqSF4GwaByUF1cQy3FviNP0wo1pbmubYxnp6OPDcddQDvm52qDIHNM+xxCMwoySlhOBhCVYh0eX1fK6cDTLq/QbJ5N3PBcv0gZxHzyTgbuya1/Zefate2tThfAt1m1uIhft3LjJcS2dwNGIIr1m5WB7CBN3/0d1q2MNuxNvhaJOtX/X29nPhFIwuchCOJmAuOIq3eNscE4Qm1nzjaOIZTlamRTt2sqFZYTLL+/H/7d24dbKm6qr2HjmmNwZZoOB8fuWKBkL3++/8KwxaDb3xI//H/+X+1es0qB2lzY5xNdlR0nDvp7WJc5Saz0eoZ1hMLEzQdMqsmWBPCw2GkYGwbFMlfKMoQz9fYTWLj45WZkawDpVfcmDLvsjEiGcOIyZOfOlGiiZAYLV9c6AzymqpaxXHknp1PcGB8mD4//jcYwRhEPiZrc9tI2noWixR4osFuJmHAuGc9S8ku1B//6Z+5dWewo16/+Oiglm/YQMB9OCeiGcSWhKmnJVWXg2+473g2Sr62vI8FfcyvmQ3ylSQzRDkR1M8OSidvcdzP3z8+SpDaQk9A1LaVLJAM3H84hLHUS1DaKY+hZhjiS3ukv/0E4wgj7Vsb7x7t+1pQZOL1yyPSuQY8jBhUgRi0RRihH2Ao/q/fxmta5YFalLdRrv18/ozHg3qwVPpv1RhufPdbYHRZv31OBrl8jrK+SR3/Gs8qcS16fQ0GH0bxz69I39sGXADj8EPK0EN9/36f9Mo6DGTeO1/v8Rq/wPWL0nzO0vNF2nX/SYLuamGY4L51dbQxefXxWkc//+Zm6Sz12l0G+wV2iM2Br2+RvkbeH9L2NA1YPnC5OXdZHDw39u1/s6Xo5y6FpVCnTTzzEukq3uGUJGn7AnaHPP9DrZRlFc8Bg/0Xe/FOs8bv2oCRjjFuwYEEseIt5D3awLDBlsxYjE3J0+99+xtElfLQOE5esmwleDAD42PEp2Roxco1eLRYYDj2e/7Fl3Tp0mUNTM3DmFtD1LN/XkxPrr/5/9McB9XeukhQ6BlwUwQBAZbOW7IGfFiIrp7ep6aRKPCw2Tp3ZK/qujCQOOIaAQv77EsrnBF45vgxLVy/w0Wae7G0/pSqjt34ZweOawYDabC3UxkLN6gAgH0LHpH39pzXD37wewRItHJU+KkuVdSpqu8tzYx/QysLEnTxxFFdBRc0wiK7Y9erGBTsTHxM5i0YH+7SWz96G1z6FN6ZKZgncrUoJ1ldDeW6eLVaG3c8o3SCz955+y1dLL2sgPAmFoYwvfbsVibxEJx7IRjp0Z7jRBaLeXac5FMCh8jiZ3LVNvdEs0ja70aTZ5CTN954X0+99Aob1SAd2P256ts7NQKecNeLryqXaP32hbmU+6+d52SSSPvtO593m2WfsuZLRg1mRo9BdibY+bq82SEO9nbo0N7PlbXqGeUsWEHQ22795O//xuUzMj9VSziajA+aIqhqr1orzrFoDhAcm60oo3HxMZmRG4HH3haWcdrO8jbqqVkWqv179yooNlPbVubqnfc+0kx4kj6FEaQkPlFLVqxVz63TqoUNwyizhjie3fHSd6iD73kbvKL26mkdPntVefnD+gmBYOnZ+dq2dYtunduvoYgibd+4DIdGpAyTOknZrHwO2tTXrvfffo8TkiHNzo/Vrmc2KdIFJ/hacaje2NjYfedh5EcBr5nghCiQE6GKKxa01awf/P6L+uSD93SruR/Y1gCBO6d4Dsu0Y/Na+kgUDoIZ19+mmSvMcPN1WTamg876G3rjg0MYr7bWDSuxcIXykmLUeOOUrtX1a8Om9Vq3ZYd+/LP39KO6UucVXE2w7JInVmrR+Qv68Fc/wxCaVgjsKQvw/vjjEe1gQ/Xehx9rgl5qEKaYlCKCybPV216nN365jyCob6m16or2HTkjM0oNHrN+58vA4oJ048IxfbD7AIxCQwRJheprr7ysAj/GeRCTdzgeHBurM6M8T9rd+kx3ay1MFae0dMtzwCBjtO/TD3Ti9AV1j80jEC9S335lh8pKjuo8gT+DnPxkrdiq/PQEIG2+jnHWCIy3Pe//TC0Dk0COhjD+grTr5deZvwb1zi/fV9HKDVqUH6+f/fhNTRHcOQgUITFroZYUZgIDsTHC3EB5rQ9GAKvwZ341iNt8Hrb1N4XieOE+RnM2QTmO7PlI87PXagX55KTF6eO339AJ5vuxqHQtWIwxwbxY+ssP9Jd/UQ3+vlNrt7+gjAcw3I/q9ZdL9uhMeaMz+PvBOm988hXmiRCdLTmsmu4A/cG3nydo75Y6RwO1Zus64J7B3DIAD/ST+uzwaf1VBfMtc8KCVevB7Mb43NdtPavDqfArFur5OKD6Wc+yl65RKgbStbP71TA0X9u3GmwPA98Zfp4+YVCh3tYK/cObnymUdhoYGGAtWqUsAkB9P+l6VKv85p9DlWil9jGNYdFV/wesrR89+gLuasfxbRhmnBA5LyPMO87oMZiBQQXCMcGBPbKbpk9hFJnTy7zDrXgUgS4xsDxeQnvPn2ReX/OEWr5gupUYY13BPG8Y3vEEZA3xOT+WrxljBG9ifGAQc515RDlFd7henjc7Kd9ytla04L+WHvKh3kYNZsYht1cPxqd5W7EJnId4hO9ZWxAT5RqG0wEMPjxolNNwyg/AN7+8AOTLKRhHn5SVe9i1OCUIrMG4p+7GfmP17ebHPMM4CFw7Gy7Y2sdozAzfz9ztoBo+VvehZWLD6IIbW2kDfnV5Wb1Zn1wbJFBnY5Doo77mnoY1C/wk79E+RtPG19x7Fhw+HfeMetL+k2aC4uC6HHLckrM8TMd5exvmYLtvi8APi4DblIqb99XwgMYPGYUxcD837UOL/Ft90/HjYjwWFRa4tiyvqAD31q/oBGiR2GkkJ8arsbocJowwpaUkEFAzqPIKjvzBoWTnFSo9JRlsZbCulV3w0PfEwXlqndHP1E/wVzPHbQ3N7Qoi2nMRhlYcHW50qFdXKhq0Yf0qHBl9unHtGrSABh0Jhr1lmcPBttTXqAHPSlomkzmBTlEYU756qGwqmSHQq662huPGZjqUBfvlEvCVpoGuFjVz38zcAsXOD9Q5GBi6bJACn0jOyNW65cWMAToDRkEfXtErlZRzzYqHeJR8a4y+Tk9+aZk5igiehg7tqgqLFzEOA3XzxnV3lJeTl89GLQGPdZAGerpgd6nSAAFpGTn5ykxP4xTFfy+8rbLTYEBPEyG+sLgYqMUsx6c3FZ1ehAEeoq6Odo4qa3CKg3Unn6y0JIcfbjYcNsEuCXiqi3KzOR3xYrV9q6/3WyMDYLprqhSZUqAUIn9vcTQzD4YAC0I6fuwYMCiCUph8jTM2A2M1EgO8obGBek8qlbzziaI1TmpfKdKmCRZqbajWmUsVGKTGZT2PQLlEaMiK1NNcCVtLEpHo6c6jb97TsYEuXYUjMYc6RjjM/EWNB+Atzs93WHLDxz5OsqClxuoKjYcmEUQbq/6udtXiXdmweonOcWzfDfZ7HkaM8QMnpGZpMZ7wCMprxn+TXUc5c/Gu2cLtS3J80ATEVVaBbyV4NJQTqlzaLisjjaPuKub5CZ5vjjuVq6muAmPfxqlYinKhpUsiIKKlsZ4j4zpNAsvIpR/mMtb8oUgzr2BrM/fgWH+WoNoFCxaytuF5mRzWeZ7FSqAXM/TD2qpKNlZDnJQlE6ibx1wfqk6Oy69U1Lh5MjouSUuXLlGKnwaZayM2vWPDgzoNJnnt6hWaIiq7tq4Bmj2oAVncrl4uVTMnLNPw4sbjsFi/arFaamthYmpSJHR4RtEXDzfngydDX9b+dnrWytxWW1/v4IpZUPplZ6YzzmZUBv1XYnomWNlY6n1TTa3dzH/RzMe5SklOZj1gQSQN9nSooamFsUZgMke0/hjCnrKxUrEJOn+hTEmMGTutq664ruC4LNf3ho2Zgbl/CFx/DkGZGcz7TAqcBNUx1toUDm62iCPgBGIy/DEGOwmArKuvZd4c5JQ5RQuKCpyh21hfx+n6jFavWKRuNkdtA9MEx6URd+OZvwZYD1qaG1Xb1KpwPNWFBYVKJMbGV37oGeA6IzzncuaSLnDc1pfyCCy2ubOpphynU6jyOGmIwplhydaWm7VNlDEJ2ytM5TduqKOr33MdmNM0GAIe1eYGrzh79qxWr17tOJU97f7V/P/VGcFfTXnn7vo70gLGEew1gj1bmH/+FfcawcUYP4ZZNozqJDvBIDyEhvmzZO/ZbmUex6UBmP1mxJuoQzALtJHGO28qE4AFt5mYw+NsSswYtePBScOjgTGyKHCbdAyWYETr5skwrl4LnDKMmyWDKdh3jIzeKKacdw2j9HHyN4yjEbbbcwtx3twAh3u0jaJ5Lc3AsiM8K4/tMs0wsfy8eRlu2Y5tDVJxH+zFldS3/6z+Lj9ra25sR+NBPAPMbMoy5Y4P7f5eA9/azI457RqLQP9N+KU99yI/nqfVyepju34TcHDtS/4GTXJtTP3d8+I9ezZ2XG7t87j1tvs7dgZrZ+7tPf62slgAmPcI1kEkqKcxQRibh5Un6DHqbf11mmc9bh6A28mep2EjjZLK6h3Ijzd636BChpm1DY+1jaOR43MbH74a3t587n31tKGNLU9edoTrBBHofwYduIuFN6YMz3i0Mtx3nUEYaDN/krWd5WOBh8FsWO16G+M0p3svEOiF688YRDaebZxbFg5OYV4ZWsFOEfwxhqx8Vm571mYszGMTa/3V8rJ6W18P4Z6Wj40DJ8LC357+yNxAX7PvWPKWyT57nGT1cPlRd+sL1vdsk2XjysaTmwcoiG2OTJTG8rZx7zZij7HBtzJ650hrO/POenhyDX9LG/NMrS62SbE+aZ/b8763fe0zo4S0vnKvqIp/9bf5gvn1dt82hhYmW898wrOxetrcf3cetTnZBJIQJ3LzDv3UHpAfyZ659Tebsz31tjXFhCyYTxjANtca5M2CVb3l8t7e+qSjDrTnQLv7O79Y3t57mICTm0spvq0x3vXMO35tjJuQiXVA6wfe9cCuc9h3H+o9ZwR7n9zc6+9sC/yPbgTbcdtcmmuBuRaYa4G5FphrgbkW8K8F/jGNYHOMzKW5FphrgbkWmGuBuRaYa4G5FphrgbkW+J1qgTkj+Hfqcc9Vdq4F5lpgrgXmWmCuBeZaYK4F5lrAWsADVJxri7kW+GfcAhYMYfypsw5XRmSuw8KBxQNjZbiwAECf4UT6GtbLcEuGbzSCfIc79A929VtvBcPtGXbMyhROIM69yfB6YwTzmViCUSi5QAWwV/beJDhDw1Uazutx8amGnXMUWQSfeTCD9+95Datlx06GpQuHXicYzKK9N2aiAbSrtaGvGK5762W/G1bQMMfj3DuCyGB7Fg8mw9FZPS0vk7c2qJjDp4J5s/bwATp23y0tTyu/8dLaPa3tvLhb7xe95RohQtOxOZCv8Ul7k0Wf27VerKH3fV9eHf6SvjoOzYkFntl9vTg57/XWl8fBBbo+Sp/14oQNt2rYyi+6znv9o14NE+jhGg51WMk72D/DKdIXR6m31c9o6YyqydNHPP3NMHsW7X7nmkdl9sDnxgYyZjhJxunDGCYMrzoKLtlRRNHXbGxYe5h8rRN4oTz+qNXdm72N/TGUqQKhojNM6K+1O+1ifd3wyMakAXqWvCccXtbwqVZvwzI/znThKBHB/Br+NQLxEW9yuF3aZJRgXeMLtja3/mhlc7hWcPGG17X8jd7Kn7w9bcdY5R6GyTQhhQexnp7vQNlGmxvuOBQGB8PHG47Te50JtDwOn7qNXcPcThIFbnkbs4YX9+2tvwUderDHzCX0dau3sWpY/7dx/0XXea9/2Ku1qeVtY9zw7dZvPAGZ3tbzcG2bYAwfu+TFKM9jPpzk+ds9bN2w522xGw+W+2H5et7zxHAYp7mNX0se6jueKdhXb7IxaH1tknnd1iUPfvY2Xpv5JZi57XH6mmtzd18PBt3u7Ykt8ebseTUstmGP3Zpj9SMy3Z6FB8PsGeMPm4/vv8vD/7q7ns2ynllk/93k+rubY0bcWu0RbQqEKtHmF/DarGfW//0JhLx796/ut8B/T/L59lNEc/ceI5S/1KdLmPMcN68pYZoKqIXgWICmLW60iYYZvyaTa5LDKHY6wQp469GAJwveM5YFxrd/bAnkQT93jAPdFNd4jqx/2uD3JmMjMM7gfvKAP5uo0bt/23uOw5prGCP3Xee9/oterb5WF2NdsN/vDTS2v731tTysXlYm5iPXBoO8x5hhQPpfX+YT117WZmD9XX29BoTZiQhXuboag4Th1e0ZuDbn+0isszB42DnuaaIvquKXvm9zi9XH2t2YNrB/PPUhP0uMS9e2xg5h9e3jO8ZmcacN+NvKZ89rJqxAhgvGHFJTVblOnT6j6uY2WNKiNTvaqxMlJ3UVdoMKonBvVtWjQJYGYXydzpw+TfR9I3zCMTAb2MLGzf6Rki0sFvyQmGga6QSfMelaZO7pkydU3z2mwuy0OyWZZqIc7EeB6PgRopqvI/85BTUf9BkoKp09WaILF8sQQOl0Cngx4Iu9z/PODR7xixkFo7BqnD1xSLVdE6jGGRXR3T2vSVl2tDVDGH9Sly6XKzI1E9afKTXX3dKR4yWquFWFuEQEi0S4xzh/RH73fUxHGCaa+Na1UpVcqtRCorMfNG7MYOqGK/R0yXENzcKWATG4RSA31t6C0u8GbBl5XOOPfAD9iIm+FiL7UyfP0DduaIT+F4tG+l3OXcRXvOU6c546VrMQQydGu5sxagwDt66e18XrVUpNy/CZKcDqbs+6t7td5+zZEaXezYRmCnzWD7zPbgqu6Hr4Ao8fP0GfrXUS1THQwQz0dencqRJd5LqegTGnmnfvdfe17Zf8YbytrY11OnTwoELi0lEDpL4abqYAAEAASURBVP/bhEKyzUEr3JAlNm5u3NR0QAg0jjEaG0KM5sI5nTl7ERYBos7jExwjie+GgadAtjja8zx69CjsJ0jbmkb87WSLo20uumHsOHHyvJPxDoORY2Ro0InInDlXqpaOHjhvY5wR6W/AkAUhDcETfPzA53ANhzmmg3vpxkzIpLmxlr4OdRnPNgHJ11kkmq+UXiAC/YLqGlsUm4iksjPC/ZwvqNsgbACmAngJGeHiguw7mwjr4z3tTfTHUyotuwIV3Ci0n6j0QaPXDxvJdYQzzl24CEPSmAq4znL2dQ424ZNbNy7rFAIgN8orkGYOc9RfdyP+KRfqmuVXzuvUmQswxSBRnZAIj+wkCndXmE+5rgKRCZglTGHz7nXep/bFr9bXO9obdaakRGVXrjHXTyPFHY9BejvojzaZpq/fREmvpOSUquuYj8OjUU8Lgx2lWWeYDy9ducHaM8N1cWzWPNd9cY53P7FnbXOUjfHL5N3DQhMDy8J82tRt3ux5dLdp37791K9CFeU3XD27RwLUVXdVFy5ddWvG9evXdbOmQYULFjlmIe8YvZvTQ35jEW9GWcrEcCqrq2FeuaUB6pCensqa6uk304zBtpZGHTtylHxvaWrefMYh8zpt1sdacKbkBOwQaY6lw99+3o8gzXkYE85fLIXdApaJuAT45UPd3GWldeOMflFbc5O+fpr5rUFpuXmaHunXjasXVUJfaUEQxthb7Hn7uzZ61rMenWGuqu1EYj0n/W4j0e42/zYwv509f0Y3btVTzwSFz5tijmduK70EK0iLguBJToAR5FF1t3W0ubmZtk1nk2YcW19d+sqMYNrE0XS9e8TDyXu2goeEIywHAQlnhGEI7T0tvX1COnYFztozUisGWTqOvn/YD6/sJakKqrSsFDh3726ufWoJOMh18Yb0l+9jhEEXlsOP0Z1ZsnJdvyX94ij5Y8vfaJEWZ1FGyvnpOZTPeO+940xGXFOQePc6u/bLkt2XPqATZdJf7WaHCP1XcerdK9jA6Qz1fIN89lzk/tQphdip+kbpv++VjlDfml7qm+x/fQfYNFhb/oh2gzFGKYw5r+2HE0D7S5BHPsXrNfKlP+XESwdo74+55shVjHAMV5Ovtmt8nYTv1uzub7axgYVFf0P9D1OfWx0oorEWmmSzJagq9eYhOIvPk+9lysTrsmyec62HL/o47dNOG6JqqtDoAo1EPu1oz37yox+rvKpOTfV1aoVwOi9pvlORq6urU03lTdW1D2hRQbo+++QTXcOwMUWqmw3dWrZkId7Mu6wDnlJ8df/fawSbd2VibFjH9n2ij/Ye0cD0fD25ftmdzIf6u3Rsz/s6WlqHiAhcj2fPaUws4NHztB9uz/nQzVy/fFHldd1av3Ylz8Z3g9AmwzEECK6cP66fvvVzjYYkalFRPrR8dz3RbfU3nYxldTdiEUykSVCJDbVV6YP3P0KKNFRTg5Tv9EWlQaOVYRrYfiQzxq5fOqtfvv+JyqratWvbBgyM0Dt3sPIZldeeT97TYYyigMgUSPPzdOXkfr3183fhdO3Wlq3bkPk2loQ7lz3yF6MmOnfyOHR81B/DshTO6MjUfOWmMelYIt/q8sv66c/eVQQ0P70ojV2tbFR2QRGiFsHwh1/Xm7RXbVu/Fi1dDmUhA8nHZNRwxw/s0Z4T59kExSKvehju1hzkslPY6Hkq0d/ZpHfeeU9N7AIDcSiYhOni4gLUAY9o/6lSjN9olRw9rNi0PGWkmgCC75V3RnhHC0p47+noidNKW7hG2clmYNgOlPZGiOWXP/nvamWjOTrYqbLSMqWgKNZ4tUT7TjEYA2dVh5JX5/h8Lchj4blnw/SoJjADeGyoX3s/fU+7D55k7kvW6icW3LnMWCLq2Zy89ZOf6HBplTasWwXXd7Aqr5zRm+/sQWgiCVpAFmj64pIli51RcufiR/xifWmYvnT66F699YtfKTipUAvzMqE/Y6K7nZoqL+uDjz9TBzRSMfT11Jw8DbajaHUV4xGJ25tlJ1XdPaMF+dDD3aZ58l775a94HaEhu3DykN77ZJ9qUAR6dts6Nv4eg8gUxqqul6q0qpXmHdfl0lKEoCK0JD9Vhz75lUpQRAyeD5c1IgtFC5HzpbP7+sT72HCdOn5cw7NBGu5shnu3HGoyxiqbSUvmnb548rDe+/igM3oqGI/tI4HMNcHI7iJdOxuMKE8TamsVSskuUDp91tc0PTGsj9/9pc6X12LYhrpNV96SFYwXD/+r5d2Fgt1PGMvDeKQmhjp0qqwabvQ87aV/lmEgRUWG6MD+gypcugqaNLidfezrJohx6ewJNffh2aTPXbsExd78JC3ISeUeHg+7ba6akQY3Ss0peHHramrUMwENX3I4Ti/zBM9gjLep7Hq1nty+3XHf+jTPwKNacaVUv/r0kAoL853Rn8DmKTn5Lv3acH+n9n72sS7VtSsyZFKHkQk2+st5U0P66Fc/18/f/1wr1m91gjL+jG97NnVIy1+9WeccLdXXLqqqY1zFOBhMstySnXLdunRS7+8+SLvzrDl5TM8vgK/7gA4eL+V0K0R1t66oqn1cC9l0mYiKr8nabBLHybEDn+qjPYfVCy3ajg3L71w+bbzZzTX6+7//B40FhTOOIticxCp0ekgHj5xWGCct1WyKLl6r0npENELxfn1Zm/9jGsF3XUN3qvPb+YVTHpViYLVzu++/wANi8v2rw9LmQo6q8bya0+uVJxFH2IRx1IkxfBK+Xoyl3bwuXSGtwfg9dAHjjnv86Xb/ymRezs5hjzE5RjnMu+gSr8YH/DZGLlzSKmJt/PQYsr/1iEfsgJeY9aKBAv/XjzHOMnw3gO3e9BG8TORlLUo+5vm+N9m8aOtCfq6E3aZPMPjieY85SBvXSOvI77+R74VqjEDK5etkaHmY+AbjXaHcz7iPvUc19hmbbK3G9tq2XvqMeh/DAF9G2+69Lv3Zq5RzABER2ryqGKMdo988s4+b4O92z2/hYml7PpuJIxjD5LOQ/Kw+iPjoh694PNM3K9l4sBlBvl2lDdJrO6U8Ng7/x6+kFTme9rdyQK6jtRueRHErSFV4PnqpXEr2Qv3L7y9QLcpie/bs1YKNLyoUyd0JBv6GJ59SVuSUfoQiR2ffy4plYvZ3snnc+nuvc0YoO7GS/R+rZXS+ihcWMTHc37Dd7S26er0WVbg/0Yr8JB3b/a6q4Xedv2OT/uh//hP3HEoOfKZjLB6j4xwd+rFDMfL2qvJLOnK+VjsxQLtDwr1F87wyCM6cPKmx4Hh97akn8SZgfEOWXdF0GY9SuJ7c+bRS509gLH7oeJfvv/jL/7IFsOrGeZVdq9GmLVu17+QVj4fm9mU2mU5NjOjAJ+9rKiQOY2mhE2yxj7MXLtea1a0YDeyWHiNFop71DNLHdsxtsstHj59yC96dW5H3EKpNAfMT9eyzz2mkA7ndc9dQ2kK1a6ZTH3x6RGvWrFGdTR5+JjPqW+HCXL/9Rb24ZYXiAobVCBfpwGL4W2M87d+KdO88DP7Xnn4a4ZQg/cV//L/U0NCgJiQS7brnNy9T9MwQG+MWLS0uunPdo4pii98QwhO7P9mtmdB4NoRMJvckeybjcESXtwzpz//tDzQfMY8TeE3Lrt5U/40LCDq8ojVLChB/uK43dl/QqzuZkB6A7txzu/t+tb4+xObjEAbwxPwMeHA7Mbzv7+tG2ZSQmqEdO3eo4eMj7gRshPLcxFu/aCNSss9uUu210zpZdkvtXQOKzPB90zWGl6vswmmVVg9ox5Y1mrnPa+SRlD64d5+Tjd2wbiUeuHClJiCoEreczc8TbFRHVJUVqQ8vdqCqOOoha7+vhl/0hx3LT+ny2aO61TSolatW6lrj0H1fDgYSs3jtk1qwmnUBTvD9iKZcx4PY15akkssN2vn8syrIgV+V061gPwxgyyQuMU2vfuf3HXyoqeqGDrKRMRlmb5ocH1YtnrfsZVv0ndeeUkN5rj4+zonTE4v19X/xPTdGGqqu6dCpq4yRu9d5r//CV75rntZ2uGi3PPWS1iP6E9DfqvLqFkQikhWCt9cMGPM2x2cv1QvPbFUIi/9f/ue/UH1tnZr7PdetKc7UbG+TymtaODVIdNd9YZ73fGBwoY1Pv6w1jPEulKhOHz98X70N+hCXlK7nXnyFZXhWVWy0+vuHtJkFcFlBmoOlmEf1xKF9ispivLHof5kxdk/W7tcAIEPR8ekYzzsQY2IDAyQghFMNb+pqrnOn2q+99m0VZ8Xrb/7z/6nW9g5lpy1inG3HQ1qJB9af1d17Z9ZHBJfSC5dxugiPeuS0ygfts9vPjucyPTmCB/ywildsRoSn0J0smjjQezgzilfu0HbGxxCbv7/8yUdoB2yCK5gF15fEvceB9Jw8+Imah0K1aNFCDXq9bLevH+ZU8/zxQ4orWK2diOPYaWgMXP0mrvGv/vgHQOyGcVAE63xFG1f40d98Kd9v+J37Z6vf8Gb3Xm6QhFoMyhwMIBOj4ORNEzw0kyPmI3dMzumTbH3gtAQNcYzEdI+x1I5Rx8kRspIYZ6333tW33zlx0hqM7bj5nvt5x7jNEeYl7sFANQEN+8H+QBwARwj9OARDcqCfsmCsZdE//BCycfAGU7jbUCTkI3nMDzxnc8gYJKKqCQW3KgzwbMNmURbqmJ9GWeKQbKYt4HS/a7T7Vl3Ip/Hksu7hUHxovqkJbDook8EtgAi5euKkEIqODjYChEg4vxyMxMcsH/o1g5E08uwWZFIf2iKRjU4vf6Ms6pK1gTlarG1KyqUdK/Gek7dBVjIwwBNogxh7BpTNnpUdbxnZ+ar16xQwNYzAwRj9hYow0c1DFaqF45LpiHStW1GsJMjY41HouYqX49CxM8BDhsEfmq76Aw/ioSX/7b5pXtiKS6d0sbJLyxcVYMAGcFSEKhxuee+C4+Q96XMtLY1M0n2cmowyMQ0xNgLd5DXLcWIPnSE9pxDVOb7o67yJwVN+tVSHjl+AMB+xCXZfJhFsGDVPS8D3iARmI56SOoyyA3t362dv/kTHzl1WaDSywQmhKGx9wJHffsUgjZrJAuVrMsxaU/U1fX7wrFI5kohGsWiKxWpk1LCYDHySCZwc3/ex6gcDnYBIAOU13LJhBGMTU53MrD9eyHvLZpjWMPB2TciifvzRx5oMilGWDXJvwhhLTElXQvCg3v3Vezp0+JiiWDDnjfXpXbzWuYtWIFKBAhRtZbg/f3rOOF5/wz/GMgkYVi8RadOhQUReDAN0O/VwHBpE+aKQ2Z3PsWAku9ZujsVHwGTdvS7OGepj91znvf6hrwymSVTb9uB9mkYNrggvqAcegIQubWt1MCN4hD45gbpWOEZELIuTiRR0dHXw04M3LxKJ2RjKkOAUtqZsovIxjQz26ur5E6rCk/rEwmwnz2x9bdRwZreTGcGRGHrZGHwhzjNt83+QMx462Az2M+kO0/dHhkeAjNmE4GPCw1x65oSu3GzSutVLxSihngjoMLG6etM2UwhaVDc2q5ITAGujn731Bl7JCge1M0yjOSBvVtWpsGiBk1j2MWd39Ftz/bwOn7mh/MI85l74lplIh+nrjv+aGxlXqxlthokfQUCgn6P7xQvZbDTVqR3p3zMnj9EP39Yv332fDdSgwyv7mn8g0APD+d+6dEYf4uWOTc5UahxHi7eT4bLN1urralM33gmTDR9EsWsM75RdV1F2Wh9/8jmbE8Qe8MT6mqxdDVI0zYRkqoymumay8D3dPbfxv9bfZtTd1aXwqBj33MORbw6ZN60OjgKn8LzfuQ5PYTf9z7CqvibzsofjZexrq9XuTz9RY1+AFnIsb33Mm4z72LDO82YmdO1auaKSc1WQnXobvxuilvoqNXSPavO6FeDHPXzV3mu//JX1iPzHB1p5br/U2+99qFuIQtw7XAaYy02AKpq6h0dEI1I0380lNu7Ts7I5jTNMuK+T+f2lCQ1lbhru1ZF9n+vEpXqtWrb0DoxlFpGhieF+19evlZ3Vpx+9r5//7OeciNexXM6yDnfhLOtFtW2IfjCEOis86vff/gv/MujNzcundP5mh5YtysdZeHs9o69717NhxFsqa2rVCFRl757d+ukbb+n0xausZ0F4fWd0aM8niKpUaNnylThBWeT/GSWbN76SZIaOqa8l4om0jdIEfXQe791rk5j3FBiejt1Atnetx2CO4NWOyX9ZiwGFwcq87ncyLC5wUBrfDKn7LzfjfIb3bC62ZwGUiEHIdyhbL4bg+ZsYsovJl/f96auWD3OLM+rv2Rjeydw8waxFwlmkXoy8AIzdYb5vXmo7ufOWxwYUb/mVzGljxuXD+pZV396vbBLa5dKz69kcYOC/sBRv8FmeEWuObUz8qesXFQ47hoWWtqcs1haWr9X53voAk0O9SWom3+/nAke57snbnpk5kOzH+ohdYwNsEmNwAFBzcla+lmMYHDhzSQPP7lTgaBceM5SnkKJNjInUZMiMNmzepOtXy/F+B6oSGb3HDer6ovr5+r7hfWurqtTY2MBE/ZFaUZQyDOathqf0BLKaduwZk5CKtOx6fXz0kOqvnlFTQ6PS8lBN44GNM+lU3biortEg7XxmI+PH92NSViCUiRpd3t3IW3a31NA5knWF4ztTxLL+4IJTkGRcsHStdqxfoqabZTp05Lg2r2SBRo5029at6gc/dw51ux6gGPlZvtngFvjUDc64gwWwg3o5jGp9g46fu6KXnt5MH/eQ2NdWV+EdGdfn9RUaZHEemq7X0zu3qhC5USdg8Rt0RhOBSMkq0LYnJ3XybJkaOwfcAmjPzhmDwAJGAmL03KZ1unnxmJpQaosPD1BdXQMqX+Pq52h5giPmvYdOASHJcYqGvjx372LgdsNccCe4zCbC28m84NaS9pnNF/YszGCwb7j3eHVY3Nv9nz99SPi7OJKvAH84AozlRtkoi1y/2sEebl231Kk2uptYOSxP9+MpgwUW2XzjKY+nTG6HygWuTD7kbrLJho2sRQXus75WoE0NihmcVisnDPlptz26ZGpBnmZ0WhCr1TsUJcOlazfp3Fvv6O1fdLp+E5HgHwwDeULVVFWzmWvg+LtRPcj2BsaNqoYjtzSkQVGCwjtGwCHr0KpNG7V8YRYSz2fdCUFRThobazCMlVdUPxCs7766AgOFRcPHZJj7lgbgWe3tOrx/j5OEbUfy+iJH7JtXLXJH83Yre76DQHMunDqhedFpWlWco97KcyioZWv7jh0KnR12stqXbtZrx+oFjBEWAx+StaEFV+UuWKptTLqnwd63965Qdrpn0zovOFRLn3hCFR9+qrfefFNjwK9Gg8GCYjzbdXkLl2rrxDQQPdTtevGKp/m+2bW+bk/R28fN4Hb93zoNyV6sr1sZvd+x351ABa+uE/JiBq15a29fZp/4lOyeUfSVLdu26yR408r6FgeH4453rjeITgNKgI19M3rqWZPtZlEiDfZ16vK1m0rlFCCP+dDK7nPiu6lATr73vT8Aux6sI/t368z5SOWgBhpjBgPJOw/YOPb+sxq6DTobIpsD7f3HSVbvMGJd1m/Zxhx+iFiOq5wuZ3tuxTOxmIaZeWGcnG4FVhmjW6UndeTERW3Z9KTOnrugX/68yokkTcz+euDol5XHZJNrOcFoamrQ55920ec7cWyhvFn/NFLdWc6zbcF4Yxh8a7ds11IwrzfYGJ87c5aTPcYVxvtayjAzfRQc/BW86JsVj8fucdvhy8r6OJ9hqnw1ydYxw/I297AbHbKFnUFrhhqTrgWImbGDjaSb1XxOKXLwvsaxIZ3PM/0uG1rzAh8oY0eV5n/5zOlkm0sLzDKHhBlnbFqcsUsfVCBlsMC4AcrTiqeSTbQbPuV1GIrk+1rhww3KR5XEFpRR8jMoiP1Y3rYbH+V3e+UkzhnYeXhm//oA2N0ltAM3bccoTKRczivMd/y1AQyLa/W1yd5+zOPLyYiba6y+Te3STw+yEDwhFdLOZnDuxBhexXeqGzGGL+Otx2H2wAnHo6r7a5/bhiKCCjUBcUglDwsQNM8zcCH1U0bzkFuQ3tUqPOH5nA7Q/vF4i80QRwlSYXxn6Pb3bGqyBWSgq0m/eHu3cgryNTPSe8db0tlSr2FczEuy0l3bTjDpNTY00ceI/J4YUEJyluJcYNDjTTi/Vjk/3ggKmQ/ua5tiM4sJRBl3gQQ9isNTHe4ChIx5ICwiSovW7OD4OhGv9YiCNanI5FTnvbhy8YQOnS0HlvAUntgk58322XvARLl4+VpFcGQ3hkfuVtmsGiZilZkSR5+EjYH3QsDORJusNB6ajIxMhYx1av+5Bif1OR0YoYVo3YfkJ+p6zRuqxzhfvbTAp2nbPF9peYv0ysvRzuPb0Vyvlt4xMKaZzks2bvrZAUHauON5FYGLNSynYfpGI7IdLtqYPSyK2KLsnZIe8sreBdOX5jflJAvAiopNVF5Bniorq1RV36QnMe7NGx0YgDeqvU1BUUlasnSRkqLm6VPwbT0TQfraa68zXxDwg2F+saJZyxbnu3FoC7QvPSiEid482AMYoKOUoQfvW3hELvNcgCuTSVNHI1k6Vd+G4T8gQtaQOp9RXFy82kKa8RJinHPkaF678MgkxqjNDL4kotxDw/X8K68R7Dqm3s5WnTpxDHlqAgvx1xnTB52QCPpIQkynPZ5WFqyePsZI/EIF48UbJJJ+AC9hH88jAi91IIu9L3W20hmmdeP2Xcou7mLiGeckrVfxWXnI2AY4D7/V2xZ+Uyg0NgEzHid4TvNgcUhls/Ltb34DOW0W1rpQnkM4R8xMgL4m+vG6LTuVtaCLQMwhXTk9ooGobCWgV2/e4GnyCwYHGYvXO5p6ZWRkaKY/QyUcSQ/giW1GOvj4hRvavOMp5opwNu2+G0Q2hguXrtHXozMYU6O6Bd5xhKCOTI7dLEBodsajyjUB3uz4ob1qGA7Wls1LkTaO0SRjz04skpJTFDmPAEqw5wNsBo1BwtdkLCo2RmJMPpej78vXKlXf0o6RncXJDwwceEZyixbrX3wnnDHQqN72BrWMRLi4APO82qnLwuJhXbpeqcbWDq1ZnOtr1u4UA54H+vEgeeHNxXsUtyCWPoN6HKdvxsARS7+ubRvAAz0IVI1TkhkgMQTmBanavTc6Go38L9ctjmWT72tftw28nWqMaH5kDCcL2WpvydDVmnpNb0O2mfnDvMB2P4O5nDx+TAWL1zvZdgvEMsO8BpjYkCK0Y2mx54TN51ozjKhhfHKalkdb8GiQuoAPVRPFP8wYC2NuMahEeCS4aL7pxnNsEOvaqNJt80c+HrU3+r/1TeoxixHk6zizYtrpVGBQqFLS0rVy5SK99dk1DXPyYd5lC3wNYg6KJsgxjsC3DAz80c5UXbzQq5zCLYrneTc0NbMJaAOaNwjayfdYmaCQMC1fu1Ux6QvYd447GfKOqShk5SM86xkbK2N+iEOKORwjPYvA065a2qalgbYZVRD487TMLOUX5KiisoQg/QlsQ4wFfyrvx3Py96u+9z4/72yezZULwAEfBP+KETyNQcSpkUYx+N7cjxG2DkOIzednZ8DnruE4HKcBfViVdRjOGETNrRhH5PkS9/A3MZ+wSwGOgTE2hJHXkEoHpgxvH5f+998HdpEinb7K5xjbF5ulf7Od54HheL1Jys2lLLzvryFqTh6DWly8xRE3hnUM5a/kZz7v/aQUzPFqqbwBAxTDjyBqjp6pPx62SK77iHLVJPM+RvPTGP00nV/JIAfl1LOZ1xu13DeB10vck3Z4ZQMBgm+zmSAv1kJnEAfTHufLqTMZXaymzgU8G67xYw14aPmY37WZ52XY465s2pdnvZ17Aw/TXsr3w2d4j9dSns13X/WcEGRS36gK8MMnpMxQJjnWQDaxrv3Nq2fHfNmJoTp/8rjmseBu2fGs4thFNpshwXFTcjwNGcBmAqqcgMlhlZ2/pHlE/D/93NdcVK6/z/GhFfPzzTCO65JSUpW/kAunRokE71QVOz0LWqm4dJrgo3A9saRQM+MDGDARmmir03hAhDYwMXdWX9LfvfWRXn7tNXCC00QaNyktw3TZjWWAij4qccycW7jQ/UxgjIWNtStoOMHpvPe01unomXK9/NJTzjt6vKxMJ+MjXXCUBdXkxc3o4sUrOnH2vJLmYRSxITR2BR9ydaUyueGUzDz3gwWimoorOlnepvzsNA11NYJ3b9HilWu1ZAWDnzTSy+4MjFSr0hUPDMEi6dvwrBk8pLa2TpGLgIKws/L1GfZ1d2rf3r3KKlqogZZK1TZ3aOOSzRqFAWHP3uNauXa1OyZtqiBSunSJxltuEEAyT0WFRVq/NN+VqbosWH2TISpk04Ud53OKiIoFAhQB+8FhpUVP6wQMFzu/tgYv7ZBKgF0kFa1WQnqupk5f1tFjx5SfME+9s5HKzEhTL976syVHlBoxSbkqtOubm3wP0KJPBIVF4P3Z7MraXn9LHY1VGKWLiBGYgXXihAIxqpeCUcqInuXZXlDkLNHiDZ3a9fXnNDxvsc5fIChzoE0teEVzF9oRse/LQjjGSDFBHMVLMeAImKqsvKkw8L8JUWHgZY9pPDwLSFCeZscH8djWAXsYUENjIwY4kJBgsIZ4MSOCp1Xf2qflBEck3sZP+9TwGNgLlyzjh3keA36qs0pdMcUszvRpGGWuVnfqpee3aXFemq6UXWAxZlNYehYs8BoM4PM6ebFCC+iLthlvbmnhWWRghLMr9yGZzHhG3gL3Y8Z/eEiA6ocrlZ+ZqkYC8WrbRmB8yNHN8wcJWr5FOZ7SNJ6g1vZZJecUa6p7D4wc5xVL8FR1y6C+9bUsDPZAH3L2fKW1vkZHSs6pEHxme2UZp6YTWpMQo4GeNk4xzurpZ59S4DTwDIJiYsHCnTpWrW2v/J6mh7r07vFDKuK61lsX1Tc2rVS85r4mm4Ki45Mc1PACUJSwafpPRZP+4OkUjRNMe+JchbIWraSNF+rghd06eWqeojn2nIpMUy5wmMSIM7LrgieLdeFWs/7wuRTH7OBr/kYfuefDd5SQW6SJ/jaVXr6p/LXP8giGdfRoibIKF2sxC2tHQ4WugNH+/jPZio+OcAbw9PiQ9u8/ouLNLygvi4XHz2TsLjeunFN5/QCBeEk6ffaK8lbvUADtfL7kuEJSirFjUgmIm9XBw4c1uCCRNXBKW+PjmA5H1Fhfq36Mk4b6enDpsQS/JvoFjbhw+DP1zEawroXo0qmTSsxYxMYtgADqUrUN4PHetkoFaVE6DfNHT1uqbly8rIXLnsbjbqdN89gczKi8/JY27vyOYwTxtfrmLMljkNkP+CLiD/Bsds0qMzlWN4HjdIyFwRSRrKWLFujdPZ8qJmCrLl69pbDoVHXevKiDjQMq5nNjPJqNiCUI+S5jjq9l+Cq/F/jvST5n4AdFmg0WNkUqxOBifRPOIHZfeP54zxgDOPl0x+Zs0LUqD6OR75i31AyxYTyDSRjIW2jzDL7H6bZfyeB0g2PgetMx8DDuDBaYxA8EAhgilCkDQwvbKZqyGC7VvKO24CUwFyzFWIz1wxlxp2CsAeb97cTYXogBmEc+xGQpnfzZlCnzdp3NW5zC3y+upTwY49mUKRlvqbXV06t4j8/YZPqVgJMKphYtzOXe1MsChA2Ty9yvRP42+INtMuxEyGATzJUOmgI8S4sLaWeMNdYsn42dLyqcrZ0p1DOd/CJYS7Ys4/7UL4a/7bQtlTLZdwpzMNTpF6E8V8OFGwOI8wpTxudWe565wgs0FvUsDz+K6NoFWr5ihdauWwfgP9/tYiPBLxYUFoIjjnEYN+N8Tc/O1fKVK/neBi1ekOsm10dRsXxRXR7n/XvZIYziyiX6hWGTI6y8PGxjrhiaDFJqSgLe+gGdOH6aYKlEdzRahLE4NTqo9u5+6I361NragseuXykZOYrmwflkBN9TcE7IwOTiFYpOcsEn0+Aja4CJFBN0lZKewclLKHQ61YpMzyeAZYeKCgoYMymwcBC8MzoDFGMXOM8Cvxapu9mbpj08sHiAbHIcGexRB9x5yemZzqC375lnxnhGI+OSGQdJsAWcVVVjJ8fm4XglB3m+RXhr8DL4Yvzb/ewfk3R5ebn6wF+t4whuJRg284hWVNYog/6RnZXFUWGCqjGSxqEv2rZ9h4rzsuiHnkFnUJZZvC2ZfC/Sj+jpADYfcVACRcybhj6pXovwnKxbCWbPsOvAYiISMpQBU0Qyk0xfeyvtO6tdL7yofAyD1BQMgQCoq6BsWrL+Sa1dvhhscrjfz9va1Gi5jAvVjm0To0LVhMEZEBKpvJwM5eTmqBvYwCDsGWu37tAKNhnpeGhCZifB17cpOX+Jntm+ifkiwh1V2/18T0wmdLghJqMkjOB0GEXaoCWbDIrGyIpVL9RYp6BCi+BoyLzyCUmpzDlBOn/6FHPmtDZt20EA7yJgbPRz3zO9800LCjNMblRSBotzjIbwSLd1D2sh/Tc1I9vR/9mpRlrRE9RxM+wcIxgkI9DadasVA7i9qw86pgzw0kzGj5GMl3UeAaiLi3LVbzjcwQklJiXAmoE3lDbpJQK4pbXVeQaLlyxXQW463tkW5gKcQE8/p2XMV6EsdL6PccP2D+n69RsanRdBP94JJIDFi/5/q6pRBUUFDiZzpayUk7lhnAe7YGcogjYyFGN8GBjaDY3Ni2LesetoH9hsfEuEKrP5SIIRIYD86zlmXPPkM1plCwlMDK2tbYpPzXLUVsksPJ207fi8cL3w4guM8TSlp6VBTzcEZVuH1nGCYH3QmDx8rbcHZsEYu3VTXQMTWrpmkzaveQJIYYCqGOPReMYTwDg31tYos3gVlHU5bv4yKJQ9l96pMK1eCfNLrNFO+tfT7OvmiW6qq1ZNXYuKV2/W5g2rFUWkf2tjPZtNPLDMnym0zUhnm5rBeT+56wUtKcpzgannoOhTcITDVEfGxCsdBhifT/h4OAEYR62M37rGViXnLdFzQI7sFKGzg9Ml7J0FhbnMWzmagf6vpaNbhcvXa8fmtQrhlPEyDo+2vnGt3/qU1i0vBssNZtrP+rv+wRi3dS6C8htFWldrI304kHwzlJaVq4jAcdVy8pCzaLl2bNukJAJ9OglgrK6tV0JGoXY985RjG3pUvf8x2SGATdlS6WMaa+T8/D/gTvyRjxd4jroNlsAJGwsal9nCjMFm7W+QCIMPmCFkxq99ZoakMSvYMb4d2/trEFrB7B5mCAN5cgnPPw+c25Ov5WWGqH1ueFw7dbRjfMbInYC0x8nTWtHuawF9dqpl9bWNvTFhWDmsfi5fJj1Ltr6acW8YZYMDTHGNYYMtb3/7ptXFC4Owaw0jDE6ehczzY7zIDmd7u77WruZ1t+dgRinxS5729xTtN/qfOcJBT6w+dl9rX2t3HD4yjLbDZNvv1JWiuuSFctjzMEPd+sVY9DPqSftP8FjGcT3YPms8knkb7TobJJbMW+wdzAafmLbMuI8/3ix3o9/Cf7245C0oqLi4mJ02uxpLlGeYRdCOCKOhRDE+U4H7M3J5o47qJqDEosiNq9aOwCc5Su3q6cOeoBIkI2OPIthqPh3D30nb2mMUfPHsPE8QzQz59RO9mIBnwo4uLYhoGNzRPLzoFslrR/fmaRkkoGuGjmQBLPMJMPGXT9IVnPLbca0d8xofrXmlrQ0sQGS+PXzSDEd4Fkw2wYOPxuizI2qDBEzxvA1Dl0CEsR1t+joeLCDMAu8GCbLifI6NWIQLSrJn0Mvxfzh/hzDoxjhWNEaIQHCTZpSZiIm3D40TxWzjwj6zI09/khlhI0ALzOiZz642kqAhw63aojEveL6LlDa4xjABYBZ8Fh0bRx7BMNZM0EcICuO68EiCjcCm+nNEfG8ZrQzW7gEY8oYlt7xsMrJjUvusv3/AzQVhlM36oxkHBoWwQLwgmBUsQM+opnxt83vztnY2jLflZ/RLw0BD5gENsr5u+HAbH9ar5wFRcNy0TJB9vDfDkZSJFjx2X+OeZpxYX6eDOY+qNyAznkXY+pnBJSxYLwgPrvV1C/axY3UnVkFlrUyx7NYfFLS5r35f9Af1NhEQgx/FEmBoFF0zeN4M82rHxwMY24aXt3axzXE8QZMWzGjBaoactSDJKNv0fNH9H/K+Ha2P0tcMymLUV572C3WboF4CamOoi80v1h/H2Gga/MmCxey9B69zAYK+HrfcLouNZxOkGGX8GgQgkuA/23CbUItBXeazyIzQ5hbwayJH0bSLGdo2v7kycZ1njHhwsg+p4kPfMqyvjXFv24WxYbbATpvP+gn4Mq7iMBZ0G8ezgTaGEWChn5nxbOUzz7gJudzlDn9oNg990+5hcI9B5g4nAkS9TWTFxCiMk936uuVnfd0CPS0IMdrmbtp9CryuBc0Z5MpgFfY8oii3YYd9TcawYPWe4HkG048swNXsCmvjCRwOcQQaOv55oFUW+GYQLfvOFDEDNi4nmWfdnIigi3e+8zXvO9+jDTzrGX2KNc7G+CybohDGVSBBX0PkbeMslOdi/SqQtunv73fjzNYyE6oxTudHJVtHz8KJvHr1alfmR33/N/n8KzeCf5PCzV37u9sCJpThNYJZPf6HaIiHGsH/Q5R8rpBzLTDXAnMtMNcCcy3wz6MF/jGNYPYRc2muBeZaYK4F5lpgrgXmWmCuBeZaYK4FfrdaYM4I/t163nO1nWuBuRaYa4G5FphrgbkWmGuBuRagBeaM4LluMNcCcy0w1wJzLTDXAnMtMNcCcy3wO9cC/kV+PEbzWPzSOIFqFpiFouKdZHE/FpzVTyCZ/W6xMoaXNpYGqPVckJr9bcFifmDH3f0tBsECxYxlwgKzLCDPgtC8yTiI7XMLxLLAMGPlsTysrBbEh0ot2vb+52v1MA5ku4fla8FvFuTlTRYUZkFsFvhnwbhWP4u9sfIOEr9CfJL7+95rvNc+6tXuC14egLqnrl4UrbW7tbO1BTSurj0tQO1OWfnMghCJy3DsHI/K51GfWxtaIJ4FA1pA4n1Bd5QFzLwLhqTKMB542seCcIhpEoJw7hpruweTRXt3dHQgeQs/ZHoyOuV1am7rcoEGIXCgLl68gMA7eFr7iPYmQjk1u8jxJz4qCvXBfH4bf1sAhanGVcFTO0hnC4bCKjU9XRlQZ3gDjix4op+I8WqI/h2vZmKK0pAdnU/dvdeFESRl3KYWYet9nr6Uz/h3G+rr1Nk75ILaQqC4yc7OVYpRhtxOI8MDRMU3q72zz1HNFSGmAWcb9H1IoqLiRGQVrBwwDMSj/+5rgBidyoQ46mtr1UnAnwU8xSdBjZSVRn/3PFRrmxkjX4eVort3AL7kaMfEYIwEnQhttLS2a4yoyrj4ZMdoYEFV3jbzlv2LXo2ftRv+waaWDseQkJiSRvulE2zJoLidLGCmi+808J1gAlmyc3IUT0CJ6akbHV17ZxeUY9HKsvf94ay9ff8pApYGejvh3+5Ufn6eYy+5m/cQbA1N6qR9jT83JTMH1pRYgmoGIKJHOZCo2sioeKikYNCAqsvX4BULuurrbucerQTmQtdFv8nNz3csHBbkZsnU/Hq72+AKbaVtEBRJTSWSHTYSIvXrG+oRChomADNOuXl5zJfQ0vk56Vog53B/j+qQig6HRzU/O91bbQ0P9sHhXY9IDoFrVhYYLKxfpMOW0d8FM0Nnr8Ii4bKmrxt1mj993e5neVtQXFXFDUWm5DpmCgs49CYTq2hCXbKPhSU6Nl75ebnQUE67qPrGpjaeRYgKFhTByBHhguq8133Zq+VpQhwm1tFLsGEAwWlJqenKyYDr+3bbWZvbWKyG9WOUQJ/I2ARlZFJHow0ijaK81gpjxOBEALzURX7X2yZxE6Coq6xAjCqMvn6XecXuP4Z8eie82I309RD40/Pzcx2dl80NQxaRTjJFzfikFC2k/v6uOxbk1tvdoZqWHj3B/GvqcZZsjE/Qp2/c9Mx/gQSmBREsZ3K7fV3takdG2IJPoxOS6ScZLlDN72dOgFx7K2Opp19p2QXQoN0N9rL8TTrdpOknYKZISkzArphWbWU57BxjLsja1sVgAseWL1/OGmWsHK7oX/qfBZH2ofpYB9PBCAtuTEISfTYdyrK7jCI2/3V3dTp+9XEEiZKSYYVhvQpFftbkxWsZB+M876zcXKWlJPrthbS6GXNQHfNnHKw+KVCtWbCvJQsaNAGX9s5u1sVZxcBWU8AcNDpoDCgwkwyMMN9GqrDQGDkskO0e4+RLa373w5GhfsZSi6Zg1jEmFG9yQkQEB1YhEmWqiVExiUpNhgJuZkQ3axpdYKiVPYiA49TMXMdW9FgB194Mf4uvDzE3fnt3N+Ouq1c6chkjF6qwr6+4e2/mQTU0SG+dxQDDWDLatOfWYKhhCO0rQ363T1CLSJv4MdENfxJBorp0i58mD1PCc9CRpbPOWV+h76vsGtLF9Rh91B77Qt/aivHIIDDZ36OlSAhjwP3hNsp8dx59ZPZm/BHYriOX4Adupz5QnW2FEi6T+1vi+UOgDT/xDWSi+ZzAcD1LfePI1wK4f3UYarNsaNIWQ1dGe/iTCA7VLepTUkEbUu486urYNriJGZfwqOtMFWXAFtj6BO2ahpBFv3SONqpp81DDvbSB58DnFOexk+UFsYA+v4AACPfPpz4bF3po2+ymZhzfqKMslHMeeW1eAa0Lz535wan1vXVIUKFxTd795XCKNTevaM/BEmUv3wLFSpwunzmqYxDdzwbOR30pV3nQ0Bgd0bmSw6j4XNGr3/9zLcYCDzTL/x85GSvDMMpEh/YfRLwjDEnRXiXmLNT3f/91JlwPQbrV6WbZKZVcaYAqDiMG2b6tzzyvJ7Lm68D+Axhi8Ob29KjgifX69qvPwjTiu77OUE+b9n36gbomw2Q0RUZnExWbdNcIZvFsrLymT/cdUQBCCwM9vdr12veUDk/t0UOHNICIwzCTfXT2Yn3jleccv7EvTWgUZZPQLx07uF993GOaSOoBRAN++MM/VjIcumbUGaF9S/VVvffhXoxQRA2IEi9csUEvbFmqvZ98qBZU20JZNAeGp/QHf/RH0JnFMm59m6xNMeni6eOqakEyGKq5qZAovfTat7QkN8UV3ybqDih93n/3PU0FhbM49GnBys3auWUd/Klt+vjjz1k0gyH1Z2GDkB7GPr+SGT2DbNYO79sNR2qV/pcf/sn9RvBIvyPw72G3N0FfnY3N0r98/Tndgnv00KlLSBnHIObRree+8W1o0ord4uxLAWxxaai6rpILFdBmjTl6ufW7vq4daxfDQx3ijJIxZJ33f/qhmnowfuBwDsbYfvXr31BPTakOnyx1DAMjPK9NT7+iLSie+U6ZZXMbQhiwBVyHM/Td3ce0autz9xnBk+RtBmpda7ebCM14iU7J04u7tunTD95VYHg0hvKQVmzYoWd3bHZjxJd6u+/Ql8dgC6gpL9ObP31Di5/+nr4GCb3HCKZHwoZgc8UpFgSLlje2khdf/56Sw8Z0cN9etQ4gHzs2qMrmzXp+50YM1LsGzZeWgTYfH+nTIe4xSZ8xRghFJOlP/+QPcfYEOaeK0dU1MG8dKrnimDpsk7N08y7Kt9oxFTTVVuidDz7TeFQucrSFTHr+zL6MNTZcRrn4q5//REGpS/Xd179+h37QDOT2plp98OFHmgy0vt6vdTtehpYzAlXNK+phQ2AGmxlHSblLHB2hP0awsRD0QDn22ccf6Gxlj/7Dv/vzu0YwFuZwD9LC772P7H0khlqcQnjG2dlZKOeVqL6NTTZ5tw+M60/+9IfKTglhnvaj7tStr7dHh/d+out1nfrm9/4Yuke8VsaxSrI5ph4KxAOff6bgrFV69bntioKT2ozg+rY+HGCMUxhROlDHLCyGxtCM4C992J4PrZ83ITV/6Og5t752IvZhIjWbVi+7U/5RjMRTRw/oUlUbFICBiHLN6vVvfxNJ61Ad2fOZqlEVjJ4fDed9pDOCfcj27leot/Wza6Wn9MHHu7Xx1R9o14ald4xgk06+dOqoartG6JsI4KDg9p0//KECe6t1tOQiDqgJ124bnnlN29Ysdobw3Zt/+W+26TOGizr689vM3bH5q+4zgk2cpPLSSX1w6AJOhWgYIUa0bPUmLcuN1CXo2YzdaYQ5z9Qs1z37HbdR/f+9EUybQVMifXxCOlUNF27u/UYw/VCdnRiGGI87MJQyE3kIGFGtvIdTQAX0yoMYyMY0tS3/yx/QfZ+Sb2m59AGG9Nc3Yexi1O65Ir2+HmPPjGk+v1HDLpQVbkWex+NrZhL9Gw16vnuZMvGd7270zwhmo69zlzCCqesuDNkrvL6D0fdvn/GUjrVeZ69iqNZJ36QszsPNR0aPdpbr9lLOxTPSWurqrxHchLH/UQliHy0IgSyHdzf6rhFsdHENXQiXMMcexjh9+xiCIV+X9p+irann+gVwCTPvOzODv32aDTxV+rX/YRzSodO0LwbwTvLbzzMYoU7fpb6WcHpoP88CMS4FYiy/cVD6s5fYELDZOEB5DtEGoh8sy6APuCs8/w33d0OXck71KKjEFY7g1WIw4sGJT8vRhvUb8KCmKQyKnIMHd6vkTKnzqBmNjO32/0kSi1lYVIJeef07LMaBunjykI6XVeDpnsTA83BiGq9sPgZuDkb9zGi/3nn3fVVW1Wjtkif18uvfxUserJPU50zZBb303FPwaNNIvszUVNiosOz+qzc/hQgEnj2oaubz402zGEGnT51RcEyGXnl+h64e/1QnSs4ibbxBu17+ujNWmxAT+ODELcefaiIfviWjmgrVUy+9hjeMDXB7s370dz9WN7tL89SEsEiNoyhz6sgBDOyVemr9IrXV39R7n+3RCibL0qpOvfjKS8qKn68PWNirmrqUEhflsxFsXoYVG3doLVQ8vW0NOnT4KGpZLXeMYPNAV2KMtY9F6N/88HtqvnlBx9BJv4pYQPvV45qOzkZOeaXzHPlLlWWLxMhgry6dOabGbmjeoMAyuqh7UyBG/64XX3Ge0L62ev2Xn36k7s4VulXdoJzFa/TspuU6+OFbqq5r0mL4bc1D5UsKgIIqDQGGb+Yt1chAjy6f3KcrN25p0/IiRwU1izHWh2LY8Ys1+td/9qeaN97nNipnylB1Or5by3d9ywlKNFVcYKN5TKsX5/lsBFu9zQNffe2CTmCEGw2f8WLfm4wHeufzrzjqtilEA95548cKg6e1tea6uqei9a9f/5ZunDusa1fLtG7tKjjkIRn3MU3xTOsqr6P8d0wRLBZGzzRtR24kV7bhXup0Squ2v6BVi3J09uCHOnG6VFlB7cjXz9PLr7yiwMEG/fjdE3oCQ9RnI5jBGITQzfNsWELY2FajCPSrj/axmcUTDwG6bfiMvjE1f5G+m/sEhyxDOnLogK5eua6Xn1yhjqZqHT7GAoeH1KgK/U1GCdff26Hdn3zmOMiH2YAZ3Zs3zaKMdP3qVXWPzdcf/eD3VFt6lPXpkrJeel6vfuN1d1IyjFjNex98wolEtnMQea991KvzRrLJP3fyhIZnQpw6m6k13k14qKGGm8FBYYp+G5YVsckKdhSBG7Y/o/VmEOEF/5u//L/hRIefOSnujhF59x4P/80cDBNstE8d2qP2nmHn4R3j6PXeqd7mv8baSrjBq5URWYAjaEahnOpse+Zld+o2OtyvC2yWLzVNOJET3/ceAUrPK9brKflwiAfpZ3/7l06Vcs2KpZp/29li46wBGdotO57R4twk/fi//oXq6uvU2zymMtS7/sXvfxuVVJQRoS7zcTq/0xB2elh++byOnSpzIkImU+ylDrUvBXDytmzjTq3G8dLVUs8G8x3VNnVoSUaavvZNnjmnk5dL9uhc6WX40/N8N4IZ47bpaaq+rr1Hz7sjZaMXvDcNM+9cKrukjIVrtGvjYp06+Jlu3arQUzv+J303s4jN6Iwqr53TgSOnlYYKqr90n/fm9dv+3dk+v+2b2v2sY0Edp9d3IppQ7PH2PZiPfYexwSKN4YeBamI98PhrF4bcigKPiARCOH4lG4sNOBw4DdQGDLynuFcHf3c+MM9wyuryhFfb7do7ulCZa8dTugwDLMjznj8ZG5zhfKW0fa20ZhHGaDYe4VpgAYxOG6A421TZIiEP72AQpq6Gw4CBjAGI8f3yKo9giD95er+bkYnBv5k620bigWSQhKfWSHkpHqES+5v5UiVVlCUH7zMGs/HDG2zB98nggUxu/8l8plLqvAujl42mFibzLDB8vdOjPQfoA7WItlnH5120eT/GsKn7ncUj/Rxtb+W4N9ngKT11BEW1UPTtuaEtuhxpm7xs+ZUyffDBe9rDwJpgIly0cpN2Pb2DY2wq+U+YjB/U1OxSEyLxTB5V6Y1qrdu8FRGWu6TwwUhRxsODO4OC0769n2kyJEYb8ChEosCVm5kK3yjymxxV2N/+KEl5q21HraVnSzBuT+ONgKvT+wHtZwZaH97IOAQLUiH0X1hUiLe6g04fAoRkPpPVRX1+qAQVsvXILbNb9DHZxGaS0SkYzS11FTp8YK+yl65F8CaSo1bPVGP8zn0cQ8QnJymW47qkxCSUrTAYg2OVGj6psydPcWTYrsnwZC3ITr7j5fClCMZDmQxRfU9LNV74PZoOi9Nyk2W8nWaAPEzgzQhDocfaN4PFPyRwloWsRpcwGrsbrutv/vqv9N7He/CUPTBheG/yBa/jeJ7PnzmpG62TznvuRB8eGFAmKWpiBXUVl/TRZ59rzeZteJ3x0KMgdAnFuEtXK9U5iHcKZSETCfE1WX8z6IeR5J8pOarzVd3Oux1qGDOSeYjMcOB4gfzxzCHPnZuZAjSiAW7VEbcgJ/IcsnMKELXgqNOOtXxM5h1qQaHus6Nl+trXX1EWEIfbDrk7d7B+bJsw24z1t9aqbXy+8vI4pu3v4ig7F07bOGVlZmKI0TdMz97nxIlGTblOn7uMCtZzWpqfgVfvnnbDWzuJ0W1wvEiMjoSEeBUvKFRbazOKhPVAMIDi4PHPzilikhp0vLa+Zm0GbggwpzRUmG4xXk6dOaflG7YiwgSv9u3nbvy9sfFJCpoe1oljB9SIeMLOzSs12N3CvPUZQg/rtXLJAsfP7Wu+nu/Nsnlq0b6P31dcwVqEKgrYNLOI3pNmMJiMnzia4/i0xHjX3uNAXwZ5bz59wHiazagJjErV6hWcGLAW+5bwvOPtPHJgP86iaD23cwtebuOV/vUbjLIpvHCmRCfPnNcw+Djj3k7i+H6gq0n7d3+gyMxFynEnPb9+7ReVZYxN9PF9H6lpPEbr1qxCGIoF7IFkvMsbd76gl3dtVRxiEpZMTnk+Sp6R1Huwu1VVtU3a/uRWyu6bF9jdA7hdXFyCE7mIYp6cmYXfmra8F1YQEZeimDCcWrs/182KSo2HJOAACFNzHVLd9Pc3/va/6G//jg0+G12DwfmcmLery0t16WYzBvbTykeBa94DJ2QmW5+RlYkgDnLgx4+5Tf1qNn5paRlKZq2JxPi2DWJ8XLzjTvY1b9todmPcv//JIZRYn3MCJN4+7r1HWHiUiorydfH4AV1mHusZnlHR0mVA0ULpa1FuXa+jzuHpi9hwp3Ky6VkPvNf/U75ihn11yTZHUYxNZ2A9YMzaXAVMUgUYhygf6hhe0h0YgqsxkFD503U8qcFmMGG8+ZPMowsUx2F6LV/D9pphzKbJkxhvKzDKqzHIDPrQwSnWH+zC63wazy+GaUqUB1tr3zcssa/PCq5qDeLVxe5xWGDLm3nIiWAEk6dJKnfgIR3FEJ4YQEoY43DbUozzdtTTMNjnj/I+eWLLOYPF92nBk5/hjx/mOGLsgM8EhgEE4VIj7UuekzhqTNq5gr+r+enCEH15B9AEjGjms8dOhrMepR1Q4r3bBtzbYa+pUBbPu7QBGe1TGPz0PNYEcL0Yythfm5cA0eCzIfqJOTSs3Db7wXQVAABAAElEQVT42pqv68x1FJAKcpHlhGyc44VxJtScgsV4UiFpD55hd3lWLTu2KJvdwBALzL2T0mNX5je6EI8o3rlgcImRyOlGM1G2g6MapdyRHJHZgmE/ZhyEsmuPS0hVF7iUtg6wdcV5zitSW35Njezctu7YzvjxT7wgnGOOJcvXAEkAZtJeqzd/0aJvYKAsKch0tTLsmE3A5kEMYnEwEv1pvJbTuM6DAZWHQ+KeAk6wtbFFg0uKPdLUPraHM4TB/0ZERGEApDjp4oHRCTcBz2OlNUN12arV+rxkr3rrrmgA47tnYBTvPsTytENgqC3OqLnRmUbAz0xPmyfYt8xd3uZxYhGMS0xlvI2DGRxQbjodmxSIEZiWnqWhEx/rrZ/9nHHYqbq2IeVGxgNlQnZ25UZORQJ19fIVfcbRxB/93ktgR31L/e2NOo9M6URAGJsa1MGaG5F0vY5CXaZTdbK7mOFk8t4RkOynpKRzXE2fGF0iw7SnZWZouLNebZ0Q3XM85DFEfc2duvEcQ4HQRAN9SYjqA2qGRHVuKp4IFPfAH8ckZCotalofffyhU09r5VQliiPNlSuXqOTQXiAZ8TyLTuZJA7X4nkbAAR/du5sTg2HgBftUcatSiWNBamjfwDG3ZwNlz8UGtMnOmrTtyrWM1bQEXa2Zch5COxYNpd/Z1DNhk7Wvifnh5JHDutXQw6YF/GvdTY3HTOPxzXaqYda/wyISkYxO17kTB9VYUYaHrE7TgakcDU8pHMlME1cImUXG1cqH8W91p7Q+JTd+uD4SY9oM+S7U0ey0JzhinjOEvWM8BGGDaOBIoR2jKBXWa6LliqqQiZ4+fVI9KIu1dI3qUkWdlhSi3vewgIgHS8P4rb9VrnPX65Q9Eqyb3fSbIbyUqIVlpW11cTXmPLD6BLAI2xh3Cpa8N2kLlUE5TOL49BUte/J5h0t/MIsv+tvmZZPmvlRRQ9t2qq+1kjm6QacvXkOJj3YAlmD1Do2I08YNG4AeTKiV7//d1Sr9mz/9PpL3oRjhEcx5aWoqR0YYz3kC846dEj0ysZkbB9964OgpJWYuUAnyxY2GT40+q6XIwEbSj+wuNs6CMbhDrO9PWa/yJHt/cnRAly9fU3BCrhblZ7q51vv5o19tXrd1epzTvcMaj8jUksXF921izGMaQV9A41MNwC9sA2YQhiGgMEmZhXpqwxOcmpzXqdPnlJySqnSTdH1UcovhqPZ+9pm6J+eDw25Xa12NggdOa+1icsIg96JJTEzKjP1Y8Oe9OBNaO/oUiwfMBDOaUQK93jKuV769Gk82lrqPaQys7xkgHg1g948fPggmukbDnNVW1LaoMNtj0JpzIwBxkrzCAg131Ll5N50Nsq39ITyXhuobboO/FS9hGH3cpoR/LuluD/kKSmQVdZ2Se9vkYs+StnLBUWao4nzQq+vwvuIVnMYIPF/nCRwrxWA7ye+bMdhMUtif5PIkHyApLlDMBZxhkNoYG8X4szIsyMfgXuGRa+7CGL3WhHHW6IFinL+FgdiJwVjvud7XvM1YNhngbow+g0aYMcvJMDgL8uVvXlzQV3G2x+CbweFRVoUxjFHc3iVdqBYGA95ijEIroz+Jse3a2a7zXmqBcvZjm01sGq1bRJ0x/q9Tvx7KY06iZQVgcGmLEL5XQxnsu79JYlONRC33p26Wt2sD2p4TUheYh2iQnt+It5znvZD12bzhiMkg5+jBNF/lGVTS7m1sEqwephTX0dbKjnsWw+QyXvN+vJSlqsWCD8HzERsb65SRJmnwSSZ4W2xs4vunHmB2XGjBP+j6aDnenlXLF6itpoJ24ZgcC98mDDs+tF15dGKatmzdgtx1EMdHt1wAjR3v7kXjfuHy1VpalOuHl8bz9MIiWYCQoX1q53Zt3bhWY91NLjjGAqgmMHZNYtqCKaY4EpikLKaAFIIhbBOpLZoLFi/Xtq1r1YH3og05Wd+TBcZNsfgCb8or0gY8ybODbWrqGnD5Wp0DMRqeWLddL+BBMmngBDy3EdGxGu9vUysL+fI167Rtx3Ylho7rakWtX0aR1c8gCMkZudq0GflfNtE3apoZT4afnES5KlDZBcX69jdeUgxekSi8dHHg18xLYsGDhQsXs6gtdkEb9dW1PL+74+lRbRDM0fgyAO25BPpE0DfNK2OqhdYXvM/awSMIOMwrfkJPsmnrwYPa3t0FzKcD/Nx6bX5yu9YuzdF1vNLDFkHqY3LH/hwBz2fzs3rdeq1Zka9r18oxeCY9eTOuLVjttddfx7OfhFJXNME8oc77uvnpFx2mcT4em3S8S6lAi4Iou6/J1AaLlqzQ8qWLUKdiw0KdbXNHV3LYTOvrXshEK6cDtd1TWsZGz4IRw1m8zbNnz82UAqd5TvcGtD2yDAz0vIVPEJS10AWPmjKY5W2BaZavGXyBYN53PPeqNqx8gkAolNXwbJjxYXLrMxhVhpM0vLSpeJlBbOX2JVmd3BjHkC5avExr1yzXQHM1cxnKXPQ1M0BNNtzGmI3HdcC2CnOSgHxcU2x6ntZz6pNMwJYpl7m+YguIzymAk5R0rV29UhmpiXjYGbsYuq6/2RinTqbSZga1U3HDaDbIRYBteJkjDb5y+VyJxiLSVZCbzdG6LVS+JwtiXL1yBU6NtNt5e/KyID3X120zTZ13PrXTzUEbN20E+nLDBWaZalliarY2bt6iqHnDqgUf7LtH1CAo87WKOTUrA4/rbXlvjzqoZ4zbc//iNKuW+kpkpMe0atVKxoB/UvQ2lofBtVaBPz93rVYvvvgcmw7ko1nd7TnbfN7T3qSOvlGtYwOw/ZldyogYBbrXrgDGSUZWnp4Ar7iY4+4xMNr9hoX0NTF3FS9fy0m5J9jWNo5OPZUO6/q6zW+UzxQ4U7LytX7DWqVGTBOU1gDevl91YKSPnynTpu1PqSAziXXSVmrfkuWTmV+stYwhUxu1QGnrb3YCZXEQlr8FgJaVXdGiVRu0Ydt2rShMUfn1ay5Qd5xYiDMnTio+PVd5nHJ6DXbfcv/qv+V7SzxGWcwr24O3D0ePM4i6+T0E6+Z0JYYoxmAAxpG5WsxYMg9iEScXjRiCPz+BYbwKrCheXPMKGhzS18Qc+P+x9x7AdV5XnucBQASCRM4gcibBHMAcJUoiFZ3kdttut93b7u7dCbWzU1tTu1u1U1NTu1MzPT2zu9M9O9O2O9iyLSuRIsWcwAzmDAJEIAiAyDkHEvv738cHgjQlvidLbk8tbokC8N73fffe89177v+ee87/WGoM1uVyrJwASgFN1iWCH8w+OceRO6BbLgis+Q6YTfBsTrTs7Y0eizGEAyzOgG8+8wJKX+qWHilOBzxXmM3hmVWA6/m5WDZlha3DDxbQl067mgF9g/zspl+LaVc69fTStnL+ZhxbnOf0xpcqJ69RQB6nmibXEQXfYdQixzj95PNlgNxb9WaZSZosHvArpJoTi2UawB6L/OWXLVn7ugBMVvzUL3KrKKZPl5BBDP2524UlvxBLNLIo5/eSbOqgkmjASVUNIBxQnp9F21IZJ7TlAuB3kGcoQE9FO/fUrCLbNjPeugjCuEAaxeDEXEvAZ/AGf9+8We4W3fSC+fgR4j7Aw2dgCVQqTQVT/UOBYfnrtTfWWkPPOP5uUdZNgFsgVjotcwpkGcKPTj6y99jNz45LstCJQaKW+y1yTjq+m3X2/gc7LRM3glQsaUEBKDYmgT/pg0cI9LmHL1g8gEcR3EYQ2GxcMfqx2lXfa8bfNBswFE9QZL01NDfbjYpKS56Ta2NYWW5V9mAFjiWAAUsVx7lK5exr0aZlEP/t8rpWFvhoApZ6HNPKTI5F+jgK7OWoO2lOmrMEzcnKN6W0PVd21uYtXmYRRKaOc303FpNYoswlq0CBSBZ1X4sCpG7frrB4gNwwFp9enpWaTRpTXAFuYblSRHY4z04mmjyaHfjZ0gOWRjvys+bYfd5TJYMyMj/ZpVhOSkt1VmBf54SOnTe9mAjoGLVR5Hjh2m3n1xsa+MBq7ty2iIQ0mzHSY81dSiM92zFIjDHjggBiOrpuJCBuYWE6i8qIBXOsozHka5GMqsuvW3Ak0di4ljQ3tVrozFhSp4/D1FFjgVjX0wG4iRyLRsbG281LZdbSGmnzCrLZBJBWFgAfHV1rZwlaWrxkDeDJd4U7C+C9Yu1mWyTlhbWptaXZZqXBKsIR3P171TaOm8uc5DiYI7oICjxh+Tw/hiPsWSwEKelZdohNbVNrC7KvsgACGaPkE+drwcK9bPU66h53C/3M0TbriFyAe0m0Y8towiJRXJTHRjnCCosXWFRDjR29d9dKAI8BrTOIHbkHQGmwh+13bMbsBEAVx4A+FgVJ9eKSUMWOPQX3H0X+P0T3CHj2dLagj8ctnvHdXH/XAsOjObEaZ1x144IEE8OC5ZY/dxELDqlhT5Vaz5VGy89M8d3tCb2Ynltob6VlAXxwJzsXaoF3uq0wL8tZOivu3ONoOsuB7CtsqGs5caipvI2FMh7DQziWyR4Cpc7b+jf/0G0e/AElsvLGz8m2FxPTnJ9od2uDlQEIF83Lw+o6xFivs5jkNAvA77ypg7HOYio/9TBOZwIZm7dutzDWotBLWEexAkeEk8rZ14UWYK/N3Otvfd0ZRpqqb2BwGrUFC+db8MSYVVXUWjQuXmLBEVvIIAuh0hdrAzBKkPAMtrVnSo9aIgG/YqXwlX3FOySUfrv61mX75MhZXFnWcMrN4sn8VdrilsY6mxGR6DbtCkLsZDFOJbZBfrvJuAOERwXbBdyuuroXOMNOCKeDM2U18qVoIUMXb3jhZfQDLkOwvAQMtlpQziI282HWcr8eDDFh+RkJWLlvMc9TXP+7OUmLA5jcr7lB8OtlSwXI5mToOxiLGEOBPur2UN7dAvpbsJA5zpgNQtaVXUGWmRyL+1SD9Y9jcRcIx9rVDvNNUG6i21y6TRgyq8fNrLLjob21MYeNB4v/71jxfYXzs+Ea2PL3/9v9ZtcbAGC8xx+Xmn2LuX8PSytjgMWCo/ELgD+e/eIKLLPpXHvT4zaw9wzg8QZW02VmX1vie+UyYiwFeHUDqP5qJ+4NiWbfyaMt/H0HYLiJteVSJYALEBYA2Nq6DjCaBjhHEqS5tnrcE9oBkQWARn/At3T35pX0jf7+eC8AuMBs+3zqpY/VrfgIZxL0Buh75xDtKocZYq2H+UJBaQL6Caw7Waz3+NL7vVNibtm7J5AbQPjjox73kwfIGKOLsa4SaEPgHN8TlErgDwA4jvewweyD0wBg6ty0FLDMdb4eO3/a22Dtsa2rzX60x+w/I+P1vDcxPfTSfzFm5AL+CR61G2xOcpHHd2lDPHITOwTz0mbRliGuSYryyECANlGL95xMt9NMhoJoPDTaRRm/+dbXnOW0f2yGzV+4EFA5yx1txSXNsS0vvmwpsZ6/P62tX+bnLnK6td5+/stPCHwc4dgwxtbjs5gAuj975qzdG4yy5Zjhyy+fsdPX7jhXgPT8Rey0i6y7ocouXivHIt5oJw6GAGRT7Rvf+T7vEd9ZH61FvSzC8pu708huD0vVhm1fsdz0JGvFV+xDIlWz/scf2pKSFda482P7iz//D0Rwz7If/tk3bLSlyvbtPwhQ63OnAi+/8XuWw32+Flkihvq77PAeWAigOgsk6CeveBUR6dHWWInf5MVKW/fSdnx/h+3v//qvOTUZtLwFS+z17S9YSmSILcy8Zgc+/Bn6IIijwxxbszgfS1Oor9U7IHT22D67wwZgCIvI/MWrbWVxjqMI2rVzl71KcEhKdIjt/MXPrLKxzeKh0fvqFqy3gLSZr2y1v/nFTju2a9CyihYTUb7GZ1cINVBjVf903DMaMAY1EhZuLMIDgP/jB/da1qrXLDmo0/buO2h191tZ00JtxcZXLCsrFyt4Jz7CBLOd2c8JR4z9/reLASsoBh/LOGC38voFO3O1EvA1bNG4lXzz21/hWHwc4HmMo99sgEGUlR3dYycu3rYQwPKWl1+xAqKRGyou2c/f380pxQhWnBLbhhIL047exyKLUCgBUHLrMeZiPFb1UMCkAPil04dtILLYXt6wlE0sFG49Zn/4eyssAiqyGYETlkQwX2roSfur//gXTjlte+0ti49iN+5zIQCVzaVRdSDKOxaADzcTeuCh1dxi4b9wzwo49rt355p9tOuI9UENt7BkHTEbGTaWHg7lYpv96P/5j5xOzLCtX/sDR+nka9U68RjoabWP3//QOvFxD4aCbEnJJsvEH6783Gm7XE0U/KrlVof/9+EzV12wYGJarr3x5ivO8orDAIsiPsP4Z8bHDWJd0wkWi6RPRVbrEPdPl0dyIhYfh+sHCrxX/sYf7bY//rM/AmjPs+qK2/Z///mfM0CD7ZvfAfQi3+aqqzYWkYEPdaoDoT5VOeUiufTonz1kszYcZQkJCW7MCBAfO3wMF4vXiG8maI9AwYbmdo7nI5n3r/KaRu3g8QNsumuxSs8gmHOBFaQy9wge9rVovM3S0SZlAN/+eOqWf+44G/8De/favJKNFrG0wI5+8r7tUawIwKO3q92+951vWeQEdHWdE/ba+gKLVzCQn0UsJ/eqK+3qtWvQhOHXDJDMW6A5s9oulu63mTnrbAUBrQWZ9fbxT/9f+4TNpNw2Fi1eYqEc/d6+8Y79xb/7N25T+pVvfNNS4ljofC4B+NV7AOQD/NwVSxDIZjKQAMjrl89bZQsugt960c6g/2o5yh5/iHtM1lyMiUVWtusnVsUm6EZ5hZ08sh9mliz7sx98GyML88WHopOKEI655coG5Q70lXEGhHDrbeW1Mqvtn20bVi+xjZs22Y/e+dAuH9thEfGp9vK21y0cXHXs/HlbRaBgDtSP/my4fGjaF3IJrlA+78PwY6gHUf0rs4Yf+VQ5a6KztuLe56yqivVQMJhcIVSciwKAc4Lf0QEOhMl63D/iAUGMdwdOxaTgTxGodP61PEtC1zqqXupzucLoFIINlatXwE++v179o2tkSRXjij8vTM+X0Uo8wc4HlueG0lc9Y5hnCmRLHnq2+itZqM/ywdW9ai94Bf8tz2f+9Ne5PnC/eILZLOOMTv/4W79rs6f+clLDB552iDZVhhv5PatuXSMZ+dPfZ7VPz5JcJQP1UX2WfKnWIwN+1/dqJ/qDxUATyfO9ZCcZyASoe0ajtlpnyr/DugIq5gmyjD1gcDxESNphyodUR2+qxyllZ/nlGPTR5wIZLkJblf+WSldXF5aJETg3C9wxZzs8wIpWDw0jGjgK6xeDr6ezzR4QgKbjZ1kWOrjmAX2KxCVAfloPsaaI11OKR8e6UjyxWC3FdevrIqnjzv6+Xo4f4QnGghDLEdZMjl1FIdba0QNvZbJzW+iHJqgHC3QwQCI+DrXGTl739fUNECMXypFxLIoXC4qP4FuD6QHUR91YvHp5BpVjXYvCujfbceEOoQhm4is8Eyf5+/eb4REOpN/IBR/BYJSBaIt6+DeGRTkCMBONzOTP6J2bz3uNokbq57hSgXdyfYjE/0aAK5DjyqbmNgAHVE1MuC4s84O0JQrwoGARBR4qoryzo9P5is6KiKRdBHNogvpdFBk/bvdb2rCyxgBEJ6wXWqAZ4VGGO7hrXx+ciIF6L8g3nPc6Cr1YD9yfcoEIx184hnYrqM1XS5XnmLbP9XuUCSYZi25NuqWDiFwxhcjtQ7zUfUzOMKzhkQpWoQ5RKbVzzQTjTWNUgT4ad59r2mAVEweyfJCjORbqxt/bQghGAqToRKIHlpBErBLedyqKr3763c04DWaBd/XTts9Tt6On64abmkASBeOMQNkkSrJUxvogVtpuHZFpPCJbbU5kyR3AV7OLscLLsDjA+0xcBXwd65K56hSNYT87eDGTaKxHYg3pY1Oj002dSAmkdHCN3sss+Q4zrjT3XeEZfcy/Xt7JHAX9fs6io2j5nuq9iv+4uaXDyVnTdhBLqEC69GFsbCzrTpCjlOsdxG0oPhYgjZL+vIX5rnd4n7mVzHsVI0Q/YzuEIKmZEP53aUzjAjaDIGDNBcU29NMezfGHzErpPLk0yIXm85RhWXtl1ZyJpTUk0FoJfglT8BvjTXzxXVjCtBaHM6bV9xlYMDseBYJqDPhbxC4jajYxWnjGcIDj5I7ArWsEXuTAsAinpzWfZfUfY9GNgpda3we4d41+YxzKsirdJjcWX3X61LZKV+nkwUJmU18wMu1Dbz1gExdnPd1d6Js+p1ulQ3Xq0o3feQ8Gh3GEoWA6cTYnA4DlGuN3oR/Sr8Ms4kmMnx42GOO4/YXLBYz536k1j8Efjg7SWJfbXTunQ+HEKigw1tf5pXW0jJPfZcuWufXB73b6ccOXCoL9aMf0pdMSeEICQxFPguAnvvwd/cMLgouKivDDnv0IuKPuAXLiKxaYkx+hQL1cPQKA8B4gryA5ruEC+dWNaSf2qOi6GSzeXgJ+7+ef/VO+uVMDYzyuISLGl6+iFh0pX8/GggA56lAwoad98mf2BtToM/8hife56qf89fQIfaYNi56nfwKsqtcL9tUfByy4jma6+3wFgVNloWdIfgpakuVcfmva50vOkrGKfFAlC7XtsVwB8AAV1a17fLW6T6178nfVRz/0HElP9fGHA7WeutkFAgK8slH7vMGKrk203V+x6xkaW/ygKvnGgoAetUMP0/vVO5B/vad/j2Xh3reucRsO/9/3ZL/5Rc9SUR2qj5fMfzxT7UMOTwMeuXKM8W48c+TzjTfV55Wh6tO4mXzHgDzXb+rRuJN8vcX7LuQP7AU13u98/en8ghk07tnMU6qYlIHGoP72btb1Drxj0Pt8TxtIIjClXd7vfP2psTPBRtrNLekU5O71jdbzZRiQP7A3YFgyl03EM+d/s/ftmVsPaH+Qeweaf3oHerbqlZ+32uV972qrfGelC7x6yNd+Pn2d68ej56sO7zj2jj2NN7Xv8Xhnnj2a359Ht/AwV4fk6y0atwqCdhYujb0pY12y1+mQR8dojj/WQ2qT2vx5imesS84K1POMdX2mMeTe96P2eceAew+PZKH6XEDnE7rPv1ZIzlTn3vmT65l0nef9uvUM2XjGh0f3qs++lt8mCH6sEXxt3fR10xKYlsBzJSAFp4ACD9R4fLkU0+PiOdZ8/DfgAQtmqCIsf6OCckQBhfBvapEyDpmiiJwCf+oar/Kaep+/vz/rufpsahELxdPFo5x9V5RP36+/9YyQp57tFuEpfq7PVsbPfl/PquO5n/Hup4IaL/jQfc+SrxsrjIunRPTcaqZeoGc4d4wnP3yyHc8Yj5LFs+Ux9UG+/z4V5Gn8Txba96x6tBF6+n1N3uPHL14Zem/xyNnz17Nkrm++iL5rPj/93qbKQPUo4O7TyhfRBm16Hhd0ytQ5rvf79Hygwb/ZLJtSG+/Va03WO0Cqk18+S/95Nr1T2zt5ud+/uM37lLuemHPPGOu69HHrptzo66/0z/Vp6rievHfKk7nOSwk5+TUbLad/n3oXj7/3/TfPWH8sw6nj7Vnj6Vnvwffafv3KqfU9uZ5Jvz05H9TWzxr/v/703/4nU97cb7/y6RqnJTAtgWkJTEtgWgLTEpiWwLQEpiXwDyGBaRD8DyH16TqnJTAtgWkJTEtgWgLTEpiWwLQE/kElMOW86h+0HdOVT0vgMyUwBvWUgjDwtITua6YLShmCG04pMRUMERQAVQ1E0KMuuo5HcSyuIBjRPblTus98+hf9pfxLCdKCf3eY9ihoJpwALAWneYv82UYJcBBHr4IWwwngCleEPT51uk98j8EExYnSS5Hj/hTVLdkoKEW+gMrY80SgFXX0Epwiblb5dqmojTMVMcl3CjYJILgpguAmJTHwy3NN7Sf4ZUik3LwDZacSw4PXB8/5s+G7qiA4BQsFE7CjLE7BtFPBTKpb8lAEuAK3PEesnjY+7//yR1NQoAL7XN3ITgEwk8+gs0Pw0qrv8g1UcelcCdhQAJ2KiO3xHnWy94ceTveOMz71/EGonxTgpgAo+UpOLeLF9fRxwgXu6ShZAZJP3Ie85KPqT1FWODfeCPhToKiCzLwy13Mk9wcE9rigmQmYBOjzLAKIRPHURyCNxtuz7nt+GwiO4l4F52juKchSY3ZqUKHeywiplAf6B4han3Dpjb2BoV1kfpSfsoqSfcxmrCqLl69FMlcK1yGif8Vx7ZnzHp/3J55BHSMKKGJsRkZF47MaAI0ec4R7dV8kQW16F/6MdQXXOZkT0Ci2AyWBmKUI40dF/rHyfdccV5CUmCxmoQfkHqOxPkAQmQLEwmFnmaVoZj+KfDElUwXWqf2aLwpinfrOFUDllY1kq7oVhzBMnxXMp6Lxr/elAFGfi9MRyJxn6H3OZKwrGHHSj/7RWOt5NK70XLVRwXHiLZZuUmIezRFxFE/e50MDnA+59CbvUc8QK8lsnqP3ObVovI8i4wl4ueUOEEyUqO5VAKreRSi6VXEbU+U19f5n/q5nUrfG8QjvVQF3krnX31n3eHXYsKLVHxUlx1HGxADmmnQPSxbvAn0v3eS9yIef7n0yZsRtrfemse4NMp16u4JQJZsArpEOc0GgAwNufRRHvAI4ZyCPSb049eZn/i7d4RnrI6ob/RLOmuvWi2dcP4KOG0XGQawhYTAAjJDhVeMtINAz1vxh/HnG47/wj75UEMyYMfIbwEfKZEPfLs183H7mkcHmY9dqPTzCBBq61L6i3rtx18MbC5+65ab4z53LOLF6ApPr4OiVCw7886TSpQ2PRpxS299tMRODlHDJojwtflzPZ70wKYjqS5y/jjbtcZM/8zf1VeP+Jm1XwgzWIMtLfbLtugZcYqdvwGWcZp40x8gBrnyrI9hzWS78up61+DPrevrLbgKfa5rgoOUneMIWZcP2AG6SmV+6TglAhvHlZ41C4Xo4mlu4vlN6EJnEQ8CwmHt+42MByYA6IDewGmRfnGWWPIUFRv7699uhS7uPAz1VQ89qSbSXYFuXJEThBguQQcJT7DVaTO6TdejQoWOWNLeE3OQLSVV6yU6ePmfdA2NWtGCZLZuXagcPHqFu2BaYgGOBYfb9H/yRZZGZ6ukUj1TzpRa3OHa12Icf7IL3lqhcPIPnQT+1dcNqFKYn8l6Z70Qvc4SsTSMorXjokzasI2NZ+IR99OEueINR4ETxrli91tYuX/xrSv6zOtADj2Tp0WPwg7a5jUPR8nW2ZsUiUox6eFAnYHA4f+ooiVPuEkSjhZrFlHH/4paNpByusdr6Nsd3uXLTS7ZkfqFFE93sS3FBEKRmPUIGsdp7TW6xiZ6TZV9/89XJrEailmq5V2F7D5Mtq6vHwsiot3LtBubgHCsjdfDlGxWwQwRbel6+bdv6gktu4OtCJZ7gC2eO2bVbd2FBGLCcufNJjboR3lgmI0XjqLG2wvYfPo6SJkgFft4BqFuWbiDF6obFUKx12ZG9O62m86H93jffJu215z6f+g6zRh2Z7g4ePAy7DYAnMsFee9VDpu9doEUaX3b6hJWRXUuAM2fectu0epG13a9lbB+BSeehzYxKdPelJUOJ99TC/mntUOBXK9R6h44et3ooqSKiEmzjiy9bYVaKY1LRfdocXDl3zM6SiUgsHTkkmdi8ab2NdtXb4aMn0EEdFhGdCNfxy1A8JU/e92l1ej/X++yC2/qjHftg3Bi18YBgW7lug61evsgxfri6WQSvnTtlZ6hbG7TZyZn24qa1UCL22n/8qx+T+IGsUwCVFPibX33lFb9AcCfpXI/S/oZmz7xftP4FW7mQxB1P8JFOON7r65fK7ONDp+xP/9E/s7CHPXax7JTdqGpgToZAV7fVFhWRflgbAx+KxtLIQJft2fmxNZFJawxKqvSCYntz24uOqkwbbwH0e5XQ/pWed6AtMiHF1m/YwLoQY4f37yWRQaOjskrLLLDtr71kEUT6+/rOxQhx+thhK69tduwiWcVLbP3aVWQgY/FyZYJUvZV25NgJWGIAq2j3ba+/CWdtsB34+D273TTgZCQmkZINL9kKKWsfywP0xflTpaTHZa6iP4LJhvf2V9+0BLIfqf2STT+pkf/6b9+1IaigothMh8CO8tWvvGnlF5H5zTsOJIUy3t7+2pusP5E+91uJSG7wjDLGUh+ZzCKh4trwwotWyJj1+t4LLLY3N7r32xuSatu2rIGXOgDavEtWeoY1g0U+KS3D1m3cQvphqMam+FB/lgiUdl1puvcfOA4nP5vGWZH20ksvkUY4CzDtuXOwu81DM0mmSod/2luscPkW27JqkTVWXbPztyqYi2brXnzFlhXn+wWCNcePHDtNcq1uNl2M2U1bSZmdM5n9Tfq3p6MVKrYrdrOq0V568+uWnhAJh3EtaZRPWg20kMqkt3DZWlu1bJ6jlvus/nq/0+ZhoLvZPvpgN+sSG1nWs7lLltvWjWuZq571TNfqOqVRP3/ykJ0C2L20/XXLS4mwPbs+tgYy1z14GGiF85bYCy8w96HO8h2Ee1vy5fwM+pcUnx89DtluVylI8dLzbwEQoQNs70mznRfgsCXgfX3+49tE23XzttmuawA/9M5xgKESV4wBiD64CIjks/PlKBJAqjh7fS7Uy9puPz3mAYRwR9sIz02P81CWKSxV3++hC9r8yuZAOnPbdwL2N+oOAwke4LvCHGjS2NR7gTOXfWZhg2RV1Wa/Ou9J1SwuYrKHWtGUtqvP5Xz+l7tZlAC7hXzHmHUcv/vhR15ZQFueAoCfWSlfaqKdob2lPFfA9wiyQ9eS/hXrHn0RKCV3gaPQaWwxO4lM8zK57hQ3I2PRkckIkcom5NE8fl6Vn/o9m09SOtKfY7zXKyTKyCJzGADbWzAM2A7Gg5J4iLf5aIUnc9zNGs/m4zIyqGEDUUD7Q2bn2lDES1A3zYR7tsdKD+2zizfuWFhMiuUlzwZgfmQ9o4GWkRxjVfcabd7cuc6ypl3mIFyZ/QERtnbFYmc19hVEedv5eX8Os7tS5GwcdDxSmEOk7MzMTHcpSi9cvW0r16yGItDDEiEA1gM1VATpfdMhHb9+5ZINBcwim0+8DXJfbm629bDAXy6/aytXlvCePJHmvrRNNGdSVMlkdAqBoP7CjSrLys2fBIOaA8FkXkpITHIUUgGj3SR3GbQCshHFxMXbnDlpFjTSYWU362hHvh+cmrIYjAD8R8lXn+zooo4fPWrFy1dbDKBE70GATVmXguBOFtAb6CIJSkUzczzYfrHzKBuaJZYJN/Tp0iOWUrDI4qBQ8pVWR0Cvl11mCgtcLIv97Zu3LDwp25G6O7kxWUQXJqq09IwMAE8IyXmaLT2ngMUiwq6UnbTzZNnph2+qcB7ZkaJ835GODfXbsUMHrWkk1NatXGJ3b56z0ZAYy0hLnQR1bQ13bN+RMssoLHbE9ocPHbU8eGwvnT1lbePhtrZkidXcOGvjYQkk+AGI+mgRVbaq04dYaAZDyJ5WYDOGW0gS1OkSGLhTBEDJIAD/nb9/x4qWrbY59LXy2iWbET3Hai8fs+axcHdf0FCzXa3ptsUkPlDmRV+KAzxYgR9Auq6x3nW/2mpJCbx06WLajwKijJFEQ9Rs0fFkpIuLsAvnyywcABQV8sB2HTxrr2x72fLzci0nJ9tjyfWx33p2L7RoAdCiJSahTAda7eLtRisqKrQYxo23aHN056aSHJSRTroOkL7Jqi8etRu17bZsObzFQcNWevq65RfksRZ4Noreez/1JzJ1c3jwgaWlz4EkatyOnzxrK9asdwu8xroAv6zAYSSpSE9NtPtkYKxqHbGChED76QdHbPGy5ZYYM9susCFNLy5hrM/0GQwOsbEYHHlgKXPmkLRhBlkGb1sMmei8qarVbtF0ia4sMzPTWmuvW/PgDJJAhdmNS2csKCHfSpbC01tQYClQa0X4YQkWVZjo5+LiEywxMZ5sYIctDW7tFKwpDgQLNAGC95ZeIJvgIlu2eL5lZWWR5CgCwxdJROD2TaTO06WHLHPeUsaExzL/qbKe8oU4sXvpV2xSClzaEdZWX2k9AVE2L2fOYxAMvdbFU4fto517LCQ2w+YyxwIfjtj77/ytxeYsIWNsOsmMqq2+Z8IWFGZN3jelmmf++pCNrizQwTMjLTcnw25fIOteYATPz5t8b8oSGAWPblJyClSUSaS3JkNgcqbNGO+3Tw6SLGb+QsvLzrW0lCT042y/1tzujjbo1cTLHGdjXQ12q7HX5pMMZjIFMvqtoeqmvfvue9Y2MG7zFi5Fd8+yy6Uf2522UStmjYzFyHLi3A1btGCeRfpq3OB9Kqvi4FiAm+OjA6wNl27ZKq1nAAiGutv4jDjDzgU7cOystWPESZmTYWEjTfbhoYu2lmtnBT+0SxfKLH9RCUk+Hp8OPkvYWkcbGxtZn9CfX0Aw4bPq8H4GTPtyCussCx6AC8teA4CnHevr1CJ6xiMApfmLzTYBOFm3be85rgeYFRaZbczDMom58PBVUu0u8IDVqfd/2u+8L7sCqAqPN3u9xKwMkHeunuxkWYBiQK1A457TWCELSeQw91F2MgD6mSqu34L1ErpGgfMrDQBJQDIbJ58KBj8rpT/5PHcDYHYm+l9g+rWFnrar3pZ2wCEbggIsoOJ1lGVW/NPr55PAY7+HP9enyrwX8cwHgO+9l8nGtoznILPhTvoCGM8G9IexDnDqYluWet7Fh0foE58nApBV/wKuz0VO4ir/TQGwmsS64B60mv6U3fUAcH3uLfd4D720+RVkkoJs/8VPGBecXG9a7rFYx3H/+zUobz6jia5od1uHNaWxtcvxeMrK2t3aSEKHfpuTPceSUfB5SxIsJXUOijYTS3oImYNu2zbI2cVV6qtlxdvGL+Knjv6i4lJt/foEa7h3l5SVwZ6FcsqOKnTmbDJHLbW5aJAhSPevXr0OVdQDMkql2ubNDBD4RXtb71kDljrxO/pTlDAkkpTA7c0N1ttcxakDWdp0rPGo6Og2PSvH0jNlIeu0m2VHnOVw/oK5DvhpkYsJ7LPy1kpONxhgPhYxMwTDlbly5Qprh5vy5vVrFpcQj4Xrcd06xktKz+O9BZLdCvA01G3l5+vIrFVrIVFk0ypeaAkzyYB29aTdwVKWiyVf3Ka+lHB4WBctWeEWtda62VZX1+hcPrz36r3EkrErNiHRWS2O7y4HABdZXnq83b56xk6SK30pWW5uN3S77733+fJzqB8u2v5hK5y70kqwgvbUXec0qt36cI2YjYVPpeluNYAoEe7LFZx2zLCDu3czPhqsHcuUTjNKli+wrtorjmNY94kD1JeiBUOZ8uZtfttWLi6yjrooO/q3nwA+X+b2cPrygIQhXVbfNWp/uGC+zQ4aI5X2ffRctfWwUVj1xvdtxYJ8gFKElf50P3rpJe5DEftQtKlITM2EyzrZ7tXVAEhDLCWZVLJTFEoYyRLmki5WGQurKm9icY53IDUQBS+WEHFFpzJ/lWFNx6f+lCSSqsSw679/r9ba6khNy6ZDG0ZvUd/vVl5hI1hjxYsXs/lupW3jGCzuWSRJRJYtX24BA+lWeu4vyXbVQea2VO+tn/lTY0npkNeuW0XGrgbrJHtc6pzUJxI/BMOPm5k3z7ILcPXBatzcUGfVZE1U0XF0KAA1EWtiZDT81RxbM+ndd778LzImwZYsj3a84zd675NUJ2lynHnuB7Bk51tGdh6Z3casreqitWKuHIXfVacQ4iyOIblIRnqaf64QPDwoJNwWIsteLB6VleW4t/AsQI2n/d4Xr0Qm4c5lQBuURKz9YVj/FrM5Erds5e1ym82x/K/f99m9D8F9qnDhMgwj3VZ5c8BCsWTHouenFvVv6ZotjLcuu28hrl0jo/3ok2Z78VuLLJ2FPSxg1D7E8vbg9U1sYHwrgVhfM7Rhzi6wAIwc104fcgurXA+8K2hENBsK/j3AyNHGiddQYBT6JcFa7mKNAzzPluWUyeE4enWf14TsQxPm5MzFwDVgdTWVZIELtaSYxCfdOXhuSnaRvfXGNiu9gLXrUdEpBblpSKKTSMY9dDTZBf0Za2L2iYzVKUa8Nd67S/2c1GWw8ZNh5lEdOvVovMsJ36HTXLfOTpRdAf8BMmA7En3fLDL9hQeOurHuq+Xd2/4v++djbfEF1yQliLHJ5qdjmYz89aN2JVRoBzjK6qcNiSy/uOtYPdbC/GQAK+AtEoBIdkXjlNBn9cDmGwscIAuwJ8uofuIa5FITu4fw3e0ms4MA4f/lR2b/54e4BbDOsyZZZYPHjaIHa2RjFyAVEO9rUeKJZtqq/sgIQVpy1/bhR23HDctu1dGeTGSC0UK6HixCyk3PPVrnvQPK1zo19dj02gg3sslGCZIimufBV+8SYeg5eqbWBFyR7E47m4F8ruU6sXD9+3fM/tlPSCd9DQDuh4z13GcV9ScOeS/gncu99On+tPB+dUqZGM336MwI2jDORXJJQTdY5X2sx9mesaDny5dQAPHwsTJLzcjGYhrnNjHaccrP6PL5U7br41323vu4D5Dxapj0fFWVFTYSmsIxUZbfC+qz+vR5PpOSU98fDPdgffg7O3e1GqtADslTHr9kXeMAOjuHmgrSf2IFXogVT0BSn/d1tuKW0GIFgCNZejSffC1SMsMDfXZkz07bsf+MJQOsox/5vE59htwg2hur7Fr9sC0vzvIAE+qRRfX02fMOuKQkTDHlT735U35X+ydYIM4dP2Qf7thjUfHZWMaU+MFzg+s3SlWKRymkb1dU2+rVJYCoJOtsqrXy8ptW31BvLRwx9+N7J65PX4tHpqp/3MqvX7YhgNxc+dw8VWSN7u9osIMnr1lWVpY96Guz9/ccx7JR4nzs5N8qC55b256699P+HMFSMgrYkI+gXpb87uR7Kf89b+ntYwIAnkJYpEUVFcGpRRdppuU/OBPfRrU/Gj+/YVw5hnmWb2WCOTHOEe+g800M5dlK0jCK9XOMsSUdoXk0jKX6Ia4KGluhkORH4g/ZTd3dJLCQT6Pa5L1vnI2n7vOlqM3OzxQZ/uwnP7YK/LqSSSEdMgWIispK/si3L52yn/zduwCXZEtEUWicTrBr/5u//q/2r//1/8FYPYUbju/vW+3TM/q62mz3h7+yfcevW3Z6JusJ74Di3JLa6u2nv/qEVL5zsIKGu8xtXd1K5xtujfU1VlF1ByB3B1kMuvTkvvZbz1ffH44NsZnZYQePlllySq4Dwd6TJzceGeuSTxMppJvae20dWeQiEzKtGCvF4Z2/tB/9/a8sJnuBpXEE6D3O17OfV1SH/I3Ple6zdz86iDElBncnFtopxYEN5s9Qb7td5FSnMJc5jqVbb6zs6Cf2f/2HP7e//Mkv7V4zC4YfRf1SYp2Ka+fsZz/9JSmnZY3GH9k7yXmWfE8nRntt74537c///N/bj37xCRvSUZdJ8PaVMnvnnXfJXJiOFROf4Cn3Pa8Zqlt+sA13rqL3d1pT10PLwuLquHof3SzXmtkuEQduGG5zIV1L0qHIIDt74ZzV1NZYdXUtJ1KDLpmGr+9cdaseZUNsqr1l1e3jbDSyWct/HUYNMIf379llBUs3kgVxtrU31VtNTRV119qOd//OPtx9EFe+pyyDz+m8xkdnS73teO89O3Otng1b1hNxJmqfNjdK9DPVXzcfa/vEULv93X/5K/vrn+3G/YzTCj8s/1rJ9cofDPfahz//qZVdvsNpYa5LfsJXrjTVVdmvfvWBZS0sAVvI7xy/aSXNiM+yjJgA2/Hzn9jPPiBNfdESNw+9c+Q5Xf6tfA1s+fKKBKd1f4o+fLIy9J3Al4ospbxjt2PhlMfzGf9nrZhcQD2fPv//epbcAFS/rJN6xmQb+I64ENtUgu8sm350lx2tIo3wViy1WKfrAIpk13RuCZP3PL9KzxXUJQuriiaWq/fRILkHwDuNhZm5id8ewBug3JANIOTn5wHArpJH/2ONwzfL84cwAzrA9X3qNdcqsQpHAVDT2BwAQP/gdQAo11bUYBk/B/jMAIwDYB+dYE691a/fpc+kd35dLWgq0U7k48AFF0hGqk8+3LiJWT3v7I/me0CwvtNx4p0b1+w+aXz7R1moOjpsonPEiuesIclTqC1fs9LmZ8fbr97bY204Rj8M6LX6plbLK1pGBiESIWgA/AMVJQgImRVrf/in/4Tj7uMo3xNWsmYZaXsVGONp1yjuE3exch8mr/vKdaSVTCPrEgq2v6vV9u7+2CJYVNevXOT3+FeXw8kW9Oo3vgOQvWq7D5+1DMBgghzjJ8uES2VberjUSjZttShAkQzVymh3+ugBG5mdYVuxKkb56CM5+Vh+CeLdbHjpTaysc+2D9963quYttoBFctKiywSVn9qx0lMWm7XQVi2eZ5zS2te391p5dY3VVxPA5I5N4xjLTF5fC89VVrzr50/YtboeW7VuE0ewT1qJ9KgRMjrJnzJx7irL51hzYqDdYthByke0m0WmFcvs+cs32JTkGcntvHr+M1sRhJVI/JnyR9fAHgX8zuCYfipfaAiWQaALuk7AVbpijI0a1zBhvQkERgDEM0KU7e1ZM+hZTVADxS0N6OChSrai5AyBPFPwSyNNG5MZvJPAAE/bRKivILHQ0Ej+BbvANO99Xk5R3edrCaD+Wbgp/ek//Z/szNF9duPaRSx+CyxeR2+PiqyiC1a/aP+cI7hf/fxX+KOn25a1i+1f/K//O+A7BJeAw1bDUW5H70pcs1CKfpQo0kR/6/s/tKXXz9k+3mtWRtIT7hDJyUlWdeua3RoZtDas85cvX2VebbGI6go7d+I4cRJsDrAwKqOVP/3WyAgOnWVvvP1dy2fTtWfvEavbst5ykiInrdHSYbKQ7T98wnLnl1g+pw73q69bXVegffN7f4xPdpMdOnbMLlcsspJ5GbQD64iPJYTNzLqX3rLM/Hk8/wz+zTmWKgvDo6KAS1moP9m5w4pWvWQF2eluQ/36N79vLzM6+jtxWcC/9cqtanxjORL0oygr4PwVG+wfJWXZ+z//e7vd2G7RBNNI72rTMzs+zf7kv/8nbMDGrbWpzt55l9Tc2zfjihNJ6upNFpucbe9xX0VjB1nVotx9flSPS9Fy+5M/TbKyMyfsOFbHnPStjwPs0PsePmLNDT0VcEgQ29vf/p6du3LLTp1udEGRMbhlyPjizzuXfmlvums79hyxTS+/gT9wxq/pZ/nFdrXds4qWMfujN+farIABCyGr3eaXVtr29Yvsbm6ynbnRZG1sQGMjfDtx8comLiXLvvfDP7Wbl0/bkSNHLTfj7clNn+spstfm5/Ha99CunjthcRnz7B9ve4vTnnL7ZO/HNi/7j8nkOcvnvgtgK6X7d//kH9ll3MZOnSvFvW+5pcZ41jNxlMs9ppY04XexXN6/f9+uXDpvMdZug6Gp9od//HtsHMpx3TxhlbhlLMghDsBvgOWVwhf780sFwQJn3VhV2Xi79Mmd/C612IRV0llrma/XqjHTc10DllfWI4tHT3NyZYmsAQ0d+JQCVPFp9/llyRoZzbi60ASgbcMHtx7Lp/QCBpmbd6ljDv7BgEEBMYFtpbdk7cKCY5bFQqxT43H00FwsulNOcZ8rdaV2Rr/ZddqexPPQCYZLprMG19BfYeMleVhksdx2AogJFMXKhRz4uw3wrXTK3YDBQX6G8yxfizIfxtJufN6tHoxznf5yWmO4ytkYz8Pv38gWacew9i5dTtswFpDJ1fVf6yxNcMDU1/o+6zot7DJ84QOPvxp9pX6d/j3ks2Z+l7sdJ3dWw79o6h7iXzD3XK4wew8gvmUF8ucztY//3OIdxVHnOvyJegGGlQRCBADu4pNT2f0nWsf9eisf6iQIKdoisf50N95BnhOA5GTGiz+q7bN65f93zhews93ayf+to/Ag0KWAl4LQXCrZoFA2CgHW0XTXPkaZ5i1ZzeIVwxHbOEeFvbZv105rHZtlm8hDHw5IkZ+ZwKCvPVJ63F4sEbL4qR6xasitYRD5tROpmoI/Gud1HGthmeiesB+ULGb8hwKAW+zi2RN2s7HfNm/a6CzXsqYxQ3wSggIjRrDGtzLplYo4mMmkFKLjPKO/r8f6+D6E46FxQOdegiUmotJtcQEWeywpIVgvs/IA3RzZ3W9ssGZ8dfMzkwDOvquoIaJbq27ik3b8oq3csAVrYxTgcgyL2UOXSjYaRTATsNjHWDp9udLe+oM/ITU0ygGr4Nfe/paLqL5fedmOXqqy5Yvm+bVAiqFE76qRMdnemWh1jU0WmbrUgpjo7a3NNmNmlLN2j9y+ZQ33G+1hVAC6IJBj4kSC2uo893XEu/uiMjOesPA8T/iyTqXhg93U2sJzInleLS4fKWxEH1pbG4qBEqYI/kAsWJ2dBi8IgWSdliZ596SQUrrZGuNnWYvuS0xxYP55dXq/17FvH0d43Sh0uW8Ecu46yvHUGACsoxV/XdImSwYDWIYUrR7GNdroDbv5ILAO+ISdQKckE1jo/S0dyHaYnbWzcLNj0SZiVG0iVXUPfomJsQn2la981bFHtDXfx3Wh0RYtWmhJSTGc2IWjSzhxqbxqiWl5Fq+IaB+LThOGB3rQ3UOcegW5+ak5rpML+SnLDBAMoB1A2e/evddisfbmZiBb3onk1Y/CFwNLJOMvLBDWAKySyijma5Hfv1I2i2FhBvrFyZSNjRgRmpF7In6jnW2NdmT/HhsOjbdV8/NoI6wUXCOdL3aCBwOcSKC0tXnyp4xyqtCOnpKlJZQjPwFDZf1TiubB8RGXxtg4ZZoBM08Q7jLh6OZxfP9GuK+paciB1RDdx4me7vOneumyZvRDKKBWNg7hqEHFYlBvc3v7o5TgsxxLgxhDBhl3Q7yXidlRloZ7SAAuCe1EhV+/dsXmzytygNHXvus0o4nTg507dtns1HzLy0h0es4x8XDKExQa4YLN5O5x+ugR/J2XEfTH+3ngYca4gzuQNoxiOnKJPtQBP0orbjcKcJS85G8/RL8lD6WBH0HHJSXhK8zcG4aZR8w/Q/R9dCyKTUizBc1JcswtCUkJNtx/jusBBT4WrWeD9K+D6Olw5q/Gmww4bj3DaEI2FgvDx/+1N79C4P8o/uCN1ruH+I6iIhvDT1+fBbLJlP6dwSlhP+3zd8z52NTPdZnvK4y/j+dFKQpyz1kPMOtG5vsBYpuzOX4H8JQUm70E6PnpKcBbNUA1lr+LAHQM6p+dNPvFPdYmwOoLi55tVfy05gjQzqeOWkDwL44AuoawMG0GhALCPsTq+0/fNtu0BL9ZgNftWg8wW5WFRRQXmgruAUPhFwhY5hRYvrK+FrEubF5q9o7aDhBV21+cB+BtMfuIfv/+BrOXscKKHYKuWgPgNZ066hv4HnkoaG7/BY8rRXGqb7VqDhHYbFup98RNs1/yLPX/zVyC9G7BgEGff28TMmAz0Ut9uWCfWQB8vRf5L98HrPZwIgNxgNsY+HEq9cwGyurezpx4j3eqTc4J+h0Zjizo8xFk++ZCXF34fkep53MC420W7d19lXZwTVUd8qJNb6ziHmqQ/2gaPpuJ6fnWiyBjoTaaiAQAZ2TaSy9vtStXruEGMWqvvPoqRyyzYJ4QkMpzEdJ+6pdn9ufzfqgFqfXuTdt5/JoLvmpBCeUQvR0dHmxVly5bff9M2CzS7eTRgxwfNxEEeIuNUR2BbGmWEfXQDh4/bwXF863s7GmrYGKs2/iCCyjSbtyX0lJfRXDCGRajmYy/BksrWGxz4qOss/kuVuEr9gff/ToDrteqa+9Z8dISgsKiWAwC8FursGMnztnDsGi7cuGMlUPdtGL1eivC99qX4oKkOptt1+7D7nIB4rDELMuk7t62Wrt4tcqWrVlrLbfO24Vbd/HfHLey4T67BkPE9u0vWi3Wuur7LdYN7dOCletcZLOvwWGqcBCgffTQIYBJoN24ctEa7lZZSk6xrZmbRITybtv0ynYChyJdkFRYcr6lsfEIx0IdEBBmrIfdmgAAQABJREFU2RwjqgQPd1h6y6DF4zzvz3wIw7czLzfLPt5/3D7q5ujzXrd9fV26UzzHjhywjCVbLBMrTsLs23YQN5XYiBCLSCtgk59i433ZtufwSdvRVUcEd5+9vTkdqi0mto9FFuhFy0oI7r1gH1XdsHEsnstXYhkDkJ4uPWbBMRkwjBTiIpQJK8E+NsViHpmNXHJsOHLQDp2+YvV3rnHfkLvPnwxPWiDv8j4PXqjm1CAEv+B6W7x6s4Uxr6+ePml9YVm2ICuSdhy1TilXfDOHgmMtl5OJzvsVtuOTMosmeOde3T1bULIBdynf+y3xqN2nYAoIYrOkI+d5SzYg23CrQwGW3Wqx737rdfzxM5wkZyPT5KREAsESOCYft8vXr1hdc6t1QNP26vavsSGS1vGtaHPYhfvOh/tOY80PYvPaacn5CywFep+26ksYQ7ps+bKF+NuftKuVHF1PhACImzmhibY10BFFPjxnhwn25QzARmcmwcjh3+ajp73Zdu/aYzPYfPW234ehgdiItAQ2eHy++4h9/e23rJzgx/McASZn5ttJ5B+JxXweLCznjpfayIxwG+5pIzgy2YpyfFxwJBoQ2MhArx09uA8WpCELJChlMCgaFoA4VAqbS4ID563eYuGjTWxGL7lAYQU25+HHGzYxyPw86dwAAh4A1oLj8PmPBUiy6PtY5AJy+uh+6x7D5YvnilFlzQvrMLQwjvftsbxFq2xJcY7dwuXiwvVKNt7hsAiF22tbN1l3c71dIvq6rbnJIpIybOWSecwR3+t+yObq9pXzdv1OnRUDeI8dPYx7Y54tX1hkF48ftrC0xbaKd9tUTxxIx7i9tW2Vc3MiYbVl58+10+9+aB991Ef8Q40tWf+yG6c+dttdVnXtjF2pbuX3B2wwW2zR8q1u433r6gXYpThZeOsFawFMnTx7wVpa2u34kYOwRb1pcxcvt+PnrtkuTgUCRwcsk8DcKD/cIbSeNeP+sQPQEMn8bGlusez5S/DnDraay2esrjfENq0vIfYk07WzN1IxMGkEqyZbbkwy+uWXtm/fXhtl0xgSn2HpibHoXN/WMn/k83mvDfqXFJ9v9ocdgoeqnwSM2tJ8AOICs6xEwC5rjUBqEpvuJCynC9BPxfwtZgSBtFiuL370WQmfZXOPX1Zz6pTFcX4OQDaFYDGAVxb1iCVpWR7fzcI6yjMLqWMB9a4oxGKL7oPdxVmJFwEgV9Be9LlfiyCnj/jzmYFtjDloK2h7Hv0hZoBFgOdTr1gYwkOxbifjikH9Yp8Ap8BwQLDYMmjKqFuWWj/WP4QMDRluDHMZf8XUs6bYQ0uGIcDJUfXhbsiCh3Wd9nljjHRqJt1XQv9Fj6aTy990XLLEsRh5/Jy3LjFbjhxTqSeV/hWCo8AcROrjl0x9ktEqZCQfYVhebCXtmMsmoYB/nLBY4KxcG4YdIoDFOhh/RVH5ZGTnWmZaCotOKBHGyVZQxLHKggWWn5vpotkjYuItN5sIc455nD8c7fltFi87RALHbFEECoXOgIaLoITipStt/eoVjL0wG8JXd1ZkjAtGCSMqMpLdkoDYDAKEtFNOJogkNHw2PpuzWKiDXfCIwLF85x4fcX12r4IJSImOno0VZBjapkW2Zf1KSyICW8fkw6MPifBNYyHrs9DZ0VY8jyhh2sUwctbiEAZLJFytAkJhBO6oPT6DAx4SQsBfJEd8sl7Hz8myV6C8SgYEj2GNCQqZSX9j8AHHOoQFS9ykqkf8qjm8twGsdw8DQ5HXCicvca762mdJRCwJ8D84v1rx0IZIDmKCSI7H+jBG8CRsGVjGh3DgX7hslbMUP30kJytLFAFD8RztzcSy62vR8bACjcRsMUBd67ZuB1xk4E6BXy4PjcYymwQAm5OaarOxEM7EcrL91W3owHjH0pFBcIAi59cT0FnIsfUsOdX7WDTW4/F5TRDVFLviwiUltmHlYk6yZC0acxy4Att5+YUWxGlDdMIcW7thIxRqcyyJsSVfUrlLFGmcruBUAB9uXxcpXRdG0EsQwWbjQLqS9ZttOWwAokAaxjIfiWU/Pi7Wkjh9EEfyTBbF7bBB5BBYE4ZVLngGdIb4n5Ws22IrsD5Ez0Yh+lG0+QhHYY6MT1jughX2wtrlzhViFOvwBFa3TOqZBDq8W3Fmp2NpD9TpBD7nEzNm2cYtWznW1sbDMw98qV66MhTr4iz89ccIXM3Mn28vbN6ALGc7f/wQzWEC/sSXPJtFQHzV0mPRMAfMLV5shXmZjO2HFpuSZlteeMFyGTf+gMEg5k0Cc1q8s4mZRYCQNaYxpNOYfiwQ6SwyMxiTYVjZxfwgDuRINtTJsCrkZqc6ZpqEOXm2eeNadOpjerHn9p2OyzgRgY7VBkgsH9tee4M1LZ5YXg9fckwcgXAExMpXVvovk83B9pc2QT0ajXFotrtvFkFd219/09KwXvpz2qMjQgXbiuM5PDbJVq3daIvm5nrc6ph3cejeCPSZgvYMd58EjT02PWKkCAl8yClNH9SJC23tqhJXtz/rhMCgjPXSzxorkmlsXILTN7LwRxHXEI3uE+d2UnquLSzMckf+8o+OwIBTwDrV39tnC1dvtGULi8Ec/rFDhEfG8jz2IbheFS9faxtXLaEd8PDi+6kTtjR8o+XONgIVmdqlk40UgGlOdo7NAWzJSJGSW2SvvrQZPCRu5cDnvm5d4OZ4BEGrqMPxBwFsNFfYhjUlbq5qPQtnPYvRicakK484oKM4CU/FsDPHueGMYrFOo+5NG9c7NqTn1f3bZIcIQEHzWn0sw/XwiP0rzJg/8ukGPZm10A0c3SDFoU2fKtSiq7/1va7T+5AVU18+8Rmf6zp/ip6HLnA+r+65PEPP1QB+og4+lrVHA8u1k3tUl67xxwrkbZvq1Yme6pmsly8V3K/neZ+ptkkA/OeuVd2u8IHk4xfo50ZXL8/Uc71ydHXwnerU9/zn+ub92/X3Ubs+b39dm5/6n+r1+ierg5ycuDY42dM3/ZQbiIrkrobpb32u4sYIn49EbrXOlH9nD2eAnHmQd5jqMi8w0mf6p6Mlqpm8Rtf7O2a4/TcuXV1dKCQi/QsL3XGjXBDkf6noWoE9TXxF0dJgV5esSVqsPUWLC8eqXKtneIvuVUT002DN+/2zfuqoVsfRAqKSjYKeREivz3UMJvCtupWkQFHu3mfLyiIeTm8wmvdeKXtfixSt/GGlxHhT7khYfXoAAPfUp0Hg6bf3ncp/LwzwLX5P1e36TJunBtr4Ur/6JzJ7HdOpuCBDZBqK7PUu5Lem+eHaBkBSv58Ge952qk3+kPirvqly11GwAs7URyU2EIuC6tPzPUfAE8jG814FXLzvy3ufP4uz6vbInXeHDPTe5AqjgKyxR+NL48+5qyAHmoQsSCCgRWvyfSF3+hzighg1m3ws6p/epxvrE4xhJSbwyNlz7CsfUVqid8PY0twUI4Rk4R0rcgPw3uevzCVb9dHTb941z9a40eca/0qK4NUFChDU+BYYVd3j3DeO7NVelyjDe6GvXedejSvVLdl53h3H3ZrjTiMhR1xBHCCX0ClBAKJQNmhibNA40HUzmF/a8PpT1Be1X/3RHNb7lcuU9x2LVsrNB9ryqGonY50aBOid6z7mgPe+p+fBZ7VFslO9kq96JXnK/Un1af6qPbxexoRnPLpxpfeCOLzjfOp9/tUtGsYxj0ypW+PYIzslshjjPRBYTB+lZ8W2o/nnHVs4jTiAqvmhd+5XvAF1ecYMbh3U4y3SKapPwbhi3ZGO98pBc9BbtA542j3G9Z7xpvv8KU53IHevjnSJjJCp3oOeLx9x12/Ghf52+hsdozVYBhDRy/EhcwTjAi/Dd7kTa4BOdXqd53rXM8UtuLHOM/WZF9hqbXE6mPkk3e95F8iH67z67Xn91hpYVlYGk84yt5Y+7/rf5PsvFQT/Jg2bvvf/3xIYingSBP+3II1JEFxU5CxO/y20ebqN0xKYlsC0BKYlMC2B3yUJ/DZBsMck9bvU++m2TEtgWgLTEpiWwLQEpiUwLYFpCUxL4EuWwDQI/pIFPP34aQlMS2BaAtMSmJbAtASmJTAtgd89CUyD4N+9dzLdomkJTEtgWgLTEpiWwLQEpiUwLYEvWQK+R7x8zob0wRNLMi8XJ6CsZqId88Yf4L8NHRJBUMTQKMmPAoMJKHXcuSTwcdeJUYGAS7+LfNfFUyvqMgKVnaO+9yHQ1DnqNAVjiSlEzAjiC4ZW0v0k8FPUoc6R33uPLz/xGSenOu2nbmVBE/PBVJo1cQLDj+36KwYLsQHhQ+64dJVxjmBRxx7hB2OMa5biK0QFJ65h1SsGjCeeQT/F10y8AkFRHhlDp+n4mxW/oXwIynD3RRTJFN9960PGendTmS68clc7NQaII3BJSSSDPtqvxCnxsGM8HZR/+cReO3v1jg0TAR5NtqVvfGObddy7Y6eg4+mHemjD5hdhuoiz2oqbdu7CZYOh0havWGsL8sldLoH8tot4UTub7Ec/+VsbgI1BAQExRMm//tVvWgo0IZ6AL5gjEFQ/WbsOHDxmy9dtgvA9hfFAfvrOFis9WQplXItlFCyzN7dv8Dm1p7erCuJQNP7h3e/bWEy+bVm9lPHlmUgPx4btIITp18prCAxScCHBQeHR9sabb1lBVorL9nNw13v2MH6ubV69BDod/weHeCXLr563suou+/4334QqyBMkoroewul58tghu3StwqIT023zC1uIbI93AY8D3Hfryjm7UNvLfa87JhBvn573U2wEt69fsNNnL1v/WIAtX73aVi5VBLVnDCh4pfLGJftk/xHHJqCIoUAYK3IKF9hISwXc3soSp0CvCYtPzbY/+M63jOD/SX31vPr1/Sg0Y/drym3XsYv22muvkcEMiprJMmE9HW129fI5MnhVWlzaXHv9hVV2v/aOnTh+GprAUcssgs1jw0qYHqJ9rleBOPU1N+3kibP0oZco7Hx75SUSoPDevMEq3iaMkmmx7FSpVdzvsW++/XUYagiYY7zW3bllh48es5KtX4NpBk5RAp38KXqvHVBQ7T901JLzFtsLqxdP3i5+2MobV6z0RJkNoKtWbthkS+YXMUvH7eKZYyQwqIAlIcc2b1pvWWlJLqRs8ubn/NLRfM/OnDpjt+7chcw/yrYi8xw4Uacye7Q311lpaandYT4lk+lq+ytbYZCAV7yjxc6eOWG3q+vg6t7MHFmE3vdxrNPfB8P99jd/82NrJc+7gsFmQle2/WvfteyUKJcsYxxKLVFWHTxcas0dvZY7b6FtXLfGsXj0d7fbuXOn7frtGotMKrBvf3M7fPj+sZsr6Etj+vShXXZ/OBx2ivUWp3SlU4rTJ90d9t6v3rVFa1+24vx06yaRw86d+wwac1u/5UVbQKZKf9hIvI/XfLtbcdX2lVXa937va/Dxo7wpCs7r62qxo/T7Tk2dYw9Zs+UFmw8DxwOozKrJkFl6psxGIML8zne/gc6PIITWt6Lg2RoSMhw/cd46WTSyi+bbJsZNPBSZ3oBpZROtLr9kh6F7nJgxG4rJjTYvPxtKuFbbt38vyar6rGjhYlu/djVzhAQpXkDiWxNcgFtrQ7Xt3HfMVqx7wZbNz5+8cwQasFKo704zpkMJPA0iScyLr7zhGCyUSbO1/o7t2FdqqzdutSUk4/GntDRU2YnS01ZTDwd5XIpt3b4NujFvym09iUBY9M8tErecPX8RmtJQ+/p3v2v15/db2fVqcBXsOazPD6Bs++a3v2e56UlP4CJf2tLT2WrHS4/ZcFiKfWPb+slbxqBlrK++bQdICtMN4FuwfKWtWrEUXDHDrl88BW3bFVLGJ7FWb4I1J92vOT5ZyZf0Cyr+yykOEPaY7TpH8gSAriIUMzPNti30ACOCau1eA9y9lwG/BMY+4N8GvsuFUmvnKXMTlCRWpHOFXstPEAwLCTyknrphn7HNjDVRnnnLjdsk6bjvaRcsUfaDTWYXb5Cko1HDCDBGW7+9BVozQKza7UsR8GttM3u/zMN0QOAtfJBQkGV57gaP2MUK+InvwpHLd8P0adt8uE274QembvFqQldq25dDrZboucfX/5dXw8lLn5ReWmD67Rfg/aVfAuBqV209Mj0N+I03+w7jVty8u5BxF8BTG5QE6vvqKgA4o8FPffBEE/XOu3nnB87DQ1xl9qevQwWX/vgS1gQ7fhUuYW18eP8VsNj8EDmT5M3u8E8Jrci4ai/yzmE+ovA2yPRx8/p16+wZtwTofaJQ8qP9XXZg3wGeA3k3O5zdnxy073xlM4rxlA0BilNI07h370HLTvs20eHQPT1uwm/nNzSNlFFF1T0WmS2kaI0kUA4qNHHMPGqMFooe+D3f+8Uv7FJNu+XMX0Z7k6BQ67WPP/rQBsOirHBuscVBc+N3+6lfdGMXzhyzk2fOW/KiKDZI4457WQLQgp0BcXzQzGgX8dsFSLhc3YaSHIXCp5vsXcfs1NnzlroU7k8Up78geERg9MZl23v0jDUPhbjIZLY2TvaKFL53+6IdPXvd8gtySYvdbrv3HbX/7rtfZbAO2W2yje07dsbaRjw0a49u8+m9KSK6i13onNxCG+pqov+nLY4BtSg/7dH9pDOOTbTFS5Y6WisBkVuVNWxKA6xw3gJL6od8HuL/O5W37X5rl2cu+CH8MdJNt92vs30AwWsVjbZh46Yn2i1+1TMnjtit+k7e7XwotDzAf3BwyBLSsy2NdKOnTh2ylDmkuV4S6Qjxn3jAp/whndVPooLZpMfOg46rqvyiHYtMtlfWL2bMeTcfRHiz+RCn6JHSEzYcFEmEPfRtIQ/gLa0FsBy0SsBgzgpSVafDXPEpdT3rY0W9D/AeS48csnOXbtpy0uhOLWIy6CUNdUpOPgqq2w7s+YS+zbCUWeN28MRlW7xssTXWwFF9PNC+/tXXWTh9r12bjgnI+ucVz7NmNh8fk472O2y60pPExo5kAB5H9+6ypsFgm1uQT0ar63bgJNzbpM68euG03esdt/kLFpPuHXo5ot19LwBQ5FlVVWvZcIBnpqU6JoqoWY9p/bQxUGKMmbEpVoySvX0bLuag2faNF5fasQOfWD1158LZGjErGhDox0BTI5njIyTGuHGpzA4BjGamziNBAhRhHhzquiEArMQNB/bugaP7hqXNW0WiiBl2cOcOexgxxzITHrL5KrUw6CcXF2b63nWuVFKOe4CePYdIrlPfjZ5AuT8qSMa1DaJy5tU862lpdCnUs//s21Z9/bydPH8D6kYYdMioGAx7gD89F4jrY4FPysix+KFeDB9X7Aw0bdvXLSbxioelobOtyT76+JDlzV9kIwDfE8eOOlaCG6UfW3dAtOVkpVnNrSsskBG2bcMyx2Dgbfvzfkp/9bST5e/QYbty/bZlzYWkf0p5MDpkra2tFhSRYEvhAQ2EslAJM5RUprdD9x2xazcqLB86P3+LwH0I1GNz50ZaQzWZ38j29/tfecniZVGjaDN869IZO3H5tsWnwBsNgAqFEjJhTrYtZr4Po58GxKV+8oJjNfFH8GJ8GMJAcQY+5JNlVy0u58l+S/d2k6QpJjXTUtjeXDp7CvAUaiX5sbYL0F+0aLH1KXshiWMSf/A9OIbFFuLPm/dXWr5f78+s9/2pXMn7sNsAoTqA1ipATQlAVMkgBNKktAXOyGBoA7RgAfNvFGB0FbB2h3suA1CLcz0ctsqG5m8hmYl18k+gqxPwOUpbphYoQG09AHQhAO3oRSMTitkHgESBwVWFpE+mHdeaAGrjU+/67N9l5YQb3MYAt3p2bAhJIXi2+qoiHXGFvsETbUuyYJrj94p71M9czKAdSgrSzKbgSt3je9yNz/kfhgDbdQaIwTzYgJyD1Q6ercxzKg9pAIYKi6JdZB92m4t+fh4CeC9mTVqC7K9cZ0MCeBWV229SpKBISsZiALDtABAj+6klmM/F27xpARsilLXSU7e0eDYfiwpofxFtZ4w0dnnucvRS7DDvNbWxow5xaRnz4F4d7Gi2ey1d8D0ustXLF7PrvwpIHiArFeTtUNZEgua7u3uhaXnqxU9tzJf6uyw0ZJRi4KWz85tXXGxFc2GMwCI5deKLN3fuvLkIggxbTIiH8Gy23rvNZqkR3tI8lxQkQ5YxvUQ/yiDcjbV3rttVdhaF+Zmsl6LpYofxqIiuK7dgrq1es8ZWLGcRmBi17LnL2SgGWE3FNbI4tjseU1FXeenSvPd+1k/VI+tXY125XSbtY/G8Qqf89bm3KKPRbZIURKYW2ooVK23h/GK7g/VW768eEHPl1l2bV1TgnjP1Pu/9n/VzBlaXRctX26YN623pksWc8ExYU1v35C2yyMcnzbFVq9fY2rXwqkLKHQFAWVycZwuWLLc1azk9mFfASUQI2RWXGTkQfF4nBAQ7WhsAePvJPpZDljQPbddk5fzS2VJn1yobLTsv37IzMixDXK6AwUIW61Uly+DxzWMjKgooOG6n3vic32XJSsueaxvp9/JlS60oPdZlnhN1kivIXxY0zZNDJ69ZKpzBGp+i9uoCMBzef4BdeLSz2ozCb+iP3AW0BlEoJ48esv6ASMcdqrE8tSiN9oLla2zj+nW2ZuVyMmgNW0NDg1vIg6JS+Ww1VrF862yqs04daflRIuNS4YpdY8VzCy0V8nlRAD4x71GQdffuWzQnMdk5OfCUR8OR20cyoUtWSUrRwrwC5lmWpZOBErzge3EvaAJgoc15KvN7HmB6AfyrYZNzPJB5lpZXbFtf2GwlvN80CN0rq6pJzV1nx8puWkZmNnVnWDZ8zdA0+V43Vw4rM1x9pZ2+UG4Ligs8NFhT9J0D4L1ddunUUeubmGVzOIHSZqS1qdEq6jts9bpNtnrVKpfA4kZFrV91K3NaS2ONnTx1zvIKC2GBExXkY12r8TgbYLpu/WraVojxK9WdSg2RtenEqfM2OzHN8tCLOY5HW/SXvlcvWrG8eYutBL2fn5/DBp2slLKoPZoxD8kQ2Xq/2loHg2wN/Vu1ssTCA4bsanmFXdQGbdVaK1m5Eot4ppWdv/yEXnxeKzTWe7vaSMqx14KjUpx+EPXY1OKZV3AGM94KAPqLFi60OKzUfd3ct3evhcakOu5wzXF/S0xSlq1atRIKznxLjp3tqNpEXeYKQnyAEeHIwUMWm4R8s7MsOzcHfRJEwqlCK0EWyzkViwcHxHIaonTNoqzzpbi1DCve5XMnrb4nwFLgHPbI/PHd4ifPX1hiL27ZZCsZ6zGzQ6ym9i5JNm5bX0AUdS+3pQvn2TBJk+639TJe/Hjpj6v5Un770kCw9O9twKSMMEWZWCaTPVbPAT5X95knLk0yyVvsZi1H9QCkFAAvVnsI9wHDjaTXBSA9Xrp9738sQHM1gCoby6c3OcTUu5UAS4ki5DagjGZe14EJ2hQ3m88BsDVtKBo/xqkywVXeJzEIYK4oiwQRcaRDbgb80lnXXySdDvi+WAnorDHLSgcwA1hljV3IBqEomyQX1E1WW5/BqJQHmzusHI8SgNAvJeG4R70kUnNF9JMLC3kPyF9AWI3R+BPAh1/bWbtn0m+MUwAezz2f9/8ypKRQzxaAbiTPfnpwyc0kmXdDUiW7DeDftpK1F1lLdyvDnmTG+uTcQ1wb6KCO3PpB9M2NjXbp/Fnbtf+otbXT2KAwl5EmJTmRyT9o45jekxJi7N6dG3aGPMwp6el+7fA/b5+ffR8CFXwaG7D9n+y23Xv2WXl1gxsHGgsqssZGxcTbSpRaDNZtpX2V9biprspaSIN5YO9u+/k7P7XdB1jE6L/PwATrU3X5ZTuOpXX+kmWWyBEljKwO8HhqVuXkgYc/VS4K4+R5v8zL2LR6IRm8quzU+VsAwqXPvm/yAc/+Rcqy/X6NffTJccvKL7QMZUmhPY7H8tFKp0WjhTS98Vj1RegeRUKBgPEBqyXD1/u7Si2noMjSSawgLtOp9z27xic/FTdqbGycSw4wPtgDqXy4JSdEP76IfounciYpmoNJ7nCaRTwHQJqFFS+Mz8JJzlF76zJHVTG2iKNKXxcJVTDM6UQpFtbg+CxbsXgelk64kRnYUzcRTXdrrANr0LnTx+3nP/t7e++jT6yHdxuOT9ZYf6t99Kufk+I2ySX3mOFH5eJGjYqOIUnMbN71uDW09lt2ZrrjL1XbBFB6Wuttx+4DtnrzZsBiAjpvwoHXw/s+tqC4LCvMzXZJU8Tt6/NY49myCF6/eBJrYJ+tJ0FHJEkUVN9UIKqxpsQR0YzzIY6LA2fGAhZnke61m/TOySQUimTuxjtd3dP/1M5ZHfiMMktpgwMe2JnSg3bg1DUAtUj8UTCuMAexRi3XRvn6Rdt/oNQqmwZsGUk5muvvWv29ajuNZf5v/+Yn9snBUlzz/KhbU5wCUyrWsSP2MRkJL92sou+ez/V/JZWYHRHFSRDJZ8gFL0ttAYtPa0MNp1h9dpyMkb/6xTv2/o7dDvz7DAyYS020fRcp1/MX4TpDlqZgiHk1X7z6RRvqi2dOWPn9QUBfCS5Boc5NQRuAMS5KS04miUSK0wGy4Hnve9z6T/mNuuWutR8LcCyppufmZnG4zuaXumUNVNFmU8mNlA794umj9glZ4kpWlNhIX5d1YBm/dumcffT+u/b3P3vH7jZ1PjFWPqXWyY/F+RtNUprBrkbbh25tHpiB21sWc9Wz2mjsKvHLOP0f5/eZnCrIyt6mhZV29mMoCZuphTCAxBIdrLU+95yU8L127sxJ6xyf5ca6Tlk01qcaGFDsbArG7FrZCfuQE72zl2+Q3rrDyriv2yIf3Rfi0Q1+LrgRkSyS44N2/NBeO3Wj3lavWOJ0loSjTY8yst1hw3cFsLrro/ft7376Dhu9+7hBSueRxGOozy5cvW0bcE2JjPQ9UYc20EpHX3qp2tasWIhlO8ptoj08zKodDIXhQO2L5dQTnxfGWAh6PN46SGWtDUEk38UDzCJmh5GhkaRIv0MgeIanC1/8/zW0BCKjqEHuZdIZ/HAATN+xoXMgbBgr5R2A8ENAcBHAsANLYhA6TBnGLt4yO9dg9r+97rmf23wqqo+kVJ9ZWgC5lyrMNq0A+GJF/eYqLLdYIfeeRLGjCzcVc7vv88P1SxZnneRp/XJuFOgEZ13lb4FR5RzoYC5epo/xbA7SAb3cQmYnKQ4PGNecnKJHP7MPap8ApPde1St/Wvlae+eXPvO2SQ+Tm8ZsgP92gPF/3UlfMdqwwXXP+OzKnv+t2qH36vy+P+VydIa1Y5yr5b1/P4s+U39Pr9l/epf3wPzpeGodCpwx0za88LIlppLlrLfF3vn5DmstTkdxKumAFJCnon4y5dQ0tNmiNS/aIszMf/k371lb9xYWXhZJCeG3WRDETLL7/OCP/wcUdoRdQinteO9drML/s6WxyxLgfVYRQOzDiT6PnPO//8YW62+v4/jsGBvDFZymZPnmp4nl605FpV1gw3D1+jXrw+/RwuMBg3E259VNT7j3DGApunq61OILSiw5eqYdOVVlF86RmvPqVbfQBXBfamKcpW7b8MR9z2q7PlPGtjr8smuqq6z8djnjatQaWzpt58Ez9tXtG51Pso5KtVhqrHh88aCwp981HFNX11RZdXWFI1dvYpB8fPisfeWVDQ6cfVqdT3+uRamrudY+OXwGP8/1lpee+PQlzipacem0dcxItpewJoUzAQXgB7qa7OSlSltMStPU+Cng+dee8OsfdOEPW37zJunaO+3MsU/sDj5Iu/YeIWNTmqWRMU+ljzSvKZlYbDeus4iQCfu7//yfrLx2FWO00OJSsu3VN75qH7z7S1Int1oawHwmGyV/ygD+5RfOnbfBWdm2kbz0Xn/4B+y2W+9hCbtWjp95I0f0XU4v7di9x6o5Th9+eMnJfHCQ4/XWDzjG/efu3k8Zpk80SXVevnCBFMR1Vlt51e6ThjjxXgfWoOW2QCk7HxVnRQM8ffjRXlu1+S3LTY2wa/UcQT2qRCBGY0JuQv6WmbOinI4IRfGfOnkKK2MqG0uUHGNNgKTubh3Hz0stOyHSDu7fbTdu3uZd91l2wUL8trdZ4FC7/af/8o4VFuZZIu/96c37s9sTgD/5LPvGt35gswD+NVU37eN3f2ZpWbmWn4qf5iPLigMngI+De3bbxMxk0uoWWmv5SUvOKLBvvPGyhTzos707P7QzxDy8uHKub765zPGmelyYLl2ymxU11o//7QMy31nwLPuz73/DQujAKCnLq+5U2pnzN3EnUwrxGqtoG8eKmOcAiDSQm38OBPq+0Gn+tt6rssqKcjtVdsH2MESrGOu/3HnYvv+dr7J5ZlF7VIKxsqzC9zWczJOHT5+2/LgVFjIr1ra9vMUK02Ls6K5fcDR/yRJiN1tSzOP7vPd/1s945svL27bjn1rqNh+5pIxWohWdOsSnklk0cq/9xb/9NxhIsAbxnko2zbe5W9bYzp//2D5kcdQaGZqY6+O79rSkt73Zrl+9YlermuzmlVNWy1waDjpq8znNyiH9s0pw2Cxbs+kVW7Cak8DeJnvnvQ9soH2l3a28brdqmu3mpRNWw31joUedC092cozn4T7+f3ZUvG15abuFHTtAOugyy89IYj0n+ZFAMEaUAFw8Xnn1q6Roj7Zb547ax3uPWeYffs1lp62rrrSBsFRbUZQx6SblS7XDnCzevHLJym/dsHs1t62TNONBYRF29hqWdix43vgBZzEe6AaA77DU3BJbVJRrdy/XTep5nYJquns2S76POV/a+Jtc8xyo+Pkfrc7GMy/vtXMsjnUPVxl7gNUvGB3HZsw6MObtO2u2dQPWUwxGuIY5v9a5ANJhALHWoET+VQsg0wz/lgMPfpWYvRuOYdwRBPgUCNdK3TvKwAYJuCHMpU08HHcx+8eZuCTw3U/383eSB1D6KgEBXHCEs17nAuZ6AHPEaVggkw3XL7vfyLF/A8Bvm1kW3//4E479qRc3QGukzkTubwMY5qYBDKWhfClcFwLoDQQIkg3SBobN7rbwrDgPsCW1OzthvudZ0nXef7pnA6CfTL52u9YD/tOZi8ry80UUp1dVJ/8ExsE4LliQTSBpPnF7wRq+oIhgPMYDGSBt7TLSXPMeOlqRAW3m9MgV7epHmFTl5bfw0Wy3iZF+CwidbalzSLkacMb59DVHKQUtvsIcv+CkZ71YGjCyUC8T7gvqj6c1vv9f/Q9iASjgWD+E3Vh/exbAtJb3Q6Yj3AGUqUgZdp5unrIPxcbF2UhVi8nCFTiitKukn2XgSpY+FYBTyYYXLaNwkbM2SBHWjsQQGJLlgu6UKcpl0WL71VBXa2dvNdhb3/2hq2/1ppcte95Sd9+Ns4etbizB5nJs6OtwlOUrd+FK+2FinvOtbWmotXcPlNnqZXPdaYuO0JTWOJ5UwfVYu4ewIg7j7kJUni1eSfDKwhXOz/I+Vq4Pj1y01UuKCC5hYvhYZLGQy8GOj/fbfJ63ZME8AjMfZ0qT64EWykF8c/cdOW0bXiZQkc2BlPMo/tBlWPQi0oqsKD/7/2PvPYPkTs4zzwdt0GjvvUV3w3s/MAM3GO8dhzMiKZIStRK52o29u/1wF9qLvf1yF7EbcXG3WgUlciWRHLrhGIyBH3jvfTeANmjvvXfovt+b1QUUemCqMEZ7UieJqeqqyn/6zDdf8zxOk+tnse5ncWm5+vZ3vq/u3j6NDnTpb3/xO61etUQxCNjGYmcuKNFQRo9VN0GRPQ2q1TD89YKdn56Nbxi+QlmYxjOSo/Gr7+KQHlX4vcxY96iUC0TqaNLnu3apd0q0Xn9xNZYY8031sGiNshayZi3T//TvUhASgnX9wgmdvFqptWvWaP3y+W5MOpprdQC/4NxVaxzlsQmk/qRIDuXnXntHKzZ1s5cNEXD1sWJz5mPViaJPB1y7x1iXzfXV2r5tpwpXbtLSOfms3yFopuN06SYCOTfZDi5kZj20Az2QNEgZNqdioQSei1vLiaJjjEGvu5A5NrXhLpVWNWEZXKN8Dv8tA43acalcmVgNhtkgpoVHEsA8yp5r2kw2qgDSGJG9M2ZDRY3GY8qtXp2eegSrzaBnvMds3rJ/IYzu3vaJhqKztAmq3mSEvcH4RI0MVcMcB6Uxm0AkWgrzqR3zHlYPqwNrfOaCZfrxX6ayj4So4spJXaju1aplCxREkGMfAZbB+OM+iTC0aPVmt/Fvf/+Xylu6ThlopWrLStTe0wtzX5+j3I1BYPJzuPndFKXmzdH3fpCofqiL+zDz/+2vt2rz2qXM1yBnJjdN8CgXYqOtNgtF/pyZ+nTPafzPIzhjOPTsc2iEowlK62RPMMZBf5MJUBbwO5VxS8XsmJeTpuL6BveMUSLsnVWE/n37+z+CIrkTt42bulxUppmFeZqTsUC5c1dggWjRjeLL6gnP4/f+tpzzKilDr3zru9rQ1aOQ0QH9/S/e1eLFi5WAH7jt61PY063NaVghE2wyjyQoOWInd5MEvUy+J+hzy/fzf/illuCulRhgNLpRRRsrXTxnxJy5Bbq067rbP2yemzvWVATwaWigQmCEM3rwBDS2/VUE+9JntRVlOn+xWGvXPYNMAINoAO02n/F1T76kgiUbmF/DOnr4oGr6p2lWbporl4nrhPDerjZ99tFHis5f4jTGcbgldlHX7qtVrK0h1iVWXUzUcVhGbI78j5L8P2ECrDF7LWYKXB1OSvs4wZFftAJB5xZCzm+PI/RMxwcXgdc0sjXUohMhtSADP1UUN1dOePxnq9rxIZ3rEeICKd40i5dKMfGjceypRJDmkhaFMLb1NIFYL+EPewxhtRVBl/32Gt+b9rTkJr9FSMbVVJm50lwTgmmDv8kQFtbNkz4rRoilrVWNuAXMR6irJfjvKu0o8ASecQYiEaKt5dmF2bwiEB/lAtCAEDpMPebymb/L0g4qLr7aMFsqov5BCMEl1P+Vlfhil/Fc/n4ZYbeuju+5TJjf7xV+F1XI3+WMBfmLqd/KxZjHYsnvb8H36RRT4nRQ/olrHrSHokrcHxjjW3x2lHZ/ezXt5FJUSt8/v8mjrTeXkGsVCMeMf3kNlxLqzp7sktE+RnDIzmSxXa+oJwAmTJueflq5ObnasGa502w1dYZr8+bNSkvP0solC1yU+IXiTq1au17JPhHD96ny1/Kx3crb8X36/NBVZWamqKTouiJTcog8DyUw57xaBvFdnc/hiWnr4tlz6uzo0I0bJc53zHwIQ/Zf1GlQLgY7ajQUHKscfAl9fYkfWGk2F+uLpJQ0TNUEQtRdQ+hLcAGF7Y1VOnLmhp55epPGhnrwSy9R6oxFmok2YSoCVxra9qTUNFxs+tVdU4TfYbIL6vN3Xhg9anxSuqLjkp1/s91L4hPKlJoYp67mal0vr1Ph7LmaPX+xzu84TmQ+AVOY6TPRyJlvZIiZT9gsI4JH0aBXcpkzjZr/i9A029swQdZ2Byulp0MlaMLaO9OVlxql3Zhkl6x6DI1TpGpKr6gnOE5zp2c4ocv5tXa36jS+WBtfehvNlP/IDN6xiIjmsJ9BAAyH0RDPSmTzT0XANgSBY/hBJs9YqmTMx9MulYHicFzTU8MQWCOVDgzNycP7NYrZPgxck8qGLs1en+jpC+/DH/JqFMFnD+/RefyNzV+w8maZ2olQnT09XefOnlVwVAouGrO1cKFnYQ221WJ961FWJgF4ETnu6c010/DVPoe/cKbrc3+3AhNGsvLylZbFoY9b0smTJzA8JCmC+XSFqPD+sAzlp2Jl2PkZvv7DSsZvsejqFdymUpSaO1Pdxz7TUQIYS7BaRCYXOteghzT3rq/LL5/StdoO5inaWFxZkrKyne+9BW1dJeB0y4bFWDPiVXTlIgoY5nxJNZfo2VqQVaBz5y9S9klF3GpTGBfp1KREv/deu6D3djZoD5e85LRktSBsBcWkKw3hvxlf3aqmPuezWnLuAPv7DS1HM34TC0kHfl/ZmYVKDD2ms2jQY6eOqG0wTKtxk/Cbxpc1bmgzUXapGmPf7qlT/VA75uY4NNyN7DtntHHzemXm5IGG4aESP5+SrHSExvz0GM1gD9q/d7cyonGTuRWiZQWeOXBXx97vDw6dKNy4ZjDfzeWiEz/4eFyQ0tC8DHS1sIaKlDtniYZbK3S9ppULRqhq0B4mZeUqDReoPA6Ei2dOKGSgRaU17VrydCGXLjYKP5NddA/jDhAUzUWit03FpbXKX7IRC3yvjoCwklk4VwXsZ2aGb2dfLSsrV0oeft+Y5vt7mhGMO5wrTMdgkNY/vsAjlPtZtgmDufmFymKNE52tZFx4kvgHUTZuH4c1NWWmclNCdfbUebRP0RrrbVVfUKRy8/B/LijAKsElC0EomfVh/yJxpwgkmUKjFtkiIixINy5fVmbeDGdxKL50Xg3dY9qwer6WzMnThXPn1d2SrBL8TBfMf5z6jWClKtJoVJrmzcz3f56NVy4Ud6a0rDwlplF/gkEry0twRwlWHH7FN0HhaOzDHxhEmdMHPtVFtJark7NQ+lyjjYkg4MxQSD8oQWdA86hFKCMGIAMXtUAuH4H00aP8Nvg/kvzOOIJ02X4QieXcQ7OYgIbAr/gI+o39MRXhdt1cBDAEvUg0fabtm5PLd8wn0xaCZqVl+fiFJvE9QrG5EczOw8eVfwZhFkjiwqU2Jou50KRgZTG3QBN02Z+UmUz1+zxQXKaZtDMWV1I7e0VwuMuDVUrsFU5D7G+59hz2IIXzanWfMx1BP4sJS7nme2vWklz6wALo7MKPtVLz+N7ai0sbqkP6Z4E0nd+Y+4K/yS5UFhxKPIaGeC7KEC3IpD30qVlhcb1jM+A7HphOO80P2qDqsHyqj74nJkNL6fdkPvdX+3O/upkQbC595l8M0pZzbzCrpLmbEMCtVPqHuBshFzph3y4ZKAIcPFonFwNzIV07y+MzPDqtQAPRT5MvzqFCZGfnaMas2Zo/dzZ+h1FsPqkEXExXIcEH7jP8ClNS8KfE/JyZnaelSxc530DT/H1TaQCh07RaiQhvQWgEKtgsym9W4mKaqTWrH1NuRrIaMCV2D4WwgSbg3tWpQ0eOcZGJcPliECDzcnMIUJqiasyXg/i0PrZmDf6aucxFoqj9kkzQgPNbL6e9+WxOI0glKxUNM1AkRTeqiS6egX9em1o6B9CeLWA8EtymdDsfl49hIpHD4+jPjLvhph7Ul2ZeNU2MaVzNRGZ90YN2ZvG8OQ4yqb6Jgzo9E1N/loJGhxDWbiosPtUFqWURbDEVnyHLZ64u/UzmRfNm40bEZuBn6u3uwvRdDswhUfldHfjidWAmjuDgjdVFIGHSMrOAJQyi3AoE7yUclunO7D+KebmNCPb2kWlaRvCG+XD619d3KmYXtmC0NKG03bQsrQT6zWJuTsVMU3mzHCErQ1npKfjERSAwlaupawB4pY3EJiS5IECzdjRhzpmzZLUWEyQWi4nd4y5yp4z7vTMhuLL0mnr6B7GCdNPuNnUO3FIhWjJzBbgVNE3TiYh3/UsfG6qAQTfNht7b/BpD+cygtsyvMy13hlLYIPxdN1ZHC1ayZ5hfahd+tUn4mmbh/F9VWswcJvgwbIpaWprR9vbiE9wNik4LMkICgWF5igoexg3mJpfEXBdQk8088PvCR4f0sNk31lcRcFapoIhEPbVlk9KSYtSOWamyvkPzMDElxBEw19uusqpaotfztGn9WsYi3fkol9LvPSNB2vTUU6Cz2Hzwc/M17RcbXn1tpUoQtG6FRBOgtw74pyzZZbO5YwAtaIx6gJRq5cDpRwvWhvmzGx/BuaBRWABda0ON2vpvaelja7SUMQ/j4uDvmHvWGX1Ovw/jUxg0LUaZbKBBIwSBXSl1QZa2T9r3Nj7mApORW8Aem4ownM58uaFmXEKWr6HOhdOZB/4LonfWuK3NMQKu+wlwnaMR3D6qq2sVlZjGuTdGHEc1EGkVColO0caNGxD+M1wMwK3+dpVX1SsbOMDVS+e7C7q/Y24+6x3tTbh6lBB83a2Z85ei/JjvoDiLTNkQh+CFcFFadMn5w2YVzNPyJYu4iMcisNfp9PnLWKSjCVRcqTmF+ayJEL/Xumkv3VzH4hWKu0t7Z7dyuAAmEABjrgYKT0LREeL83i9xGegED3Dtxi1u/47BTz10PF8bpvG8/AKlm8k2gGQIKzVVN3GnqANWL1dPAA1n86i+tobg/mEuwAWKB1pxgL39ZnUD1sAFKItWgjyF1a+pwykgZnDg+9vX3qq5fd27xtmf+xBipuGCNAuoszqgSru4UEQDx9je0sRcwLqHJaalBX9rlFaFxHjEcp5VsMYVEU8w9mqg2dIf6qJoZ0ctcUAZGRlYU/2fm946B/JKUKrdJf1MA9WoVf8Tqtuf+5lh8meTPfBoPdAf/aTa0v+zRkOQ3P3WzzxaWV9Vrvb2dsyLg064iGLTMxPZINBkoZjkw8LCXCvMRGzmQNtMzYzUy4ZhC9CEqKmYscxUZearfnyGzLxmn4U8oiBvS9s0J1ZeEM+wQ9vMrhEREc5caZcxc2GY+HzffFZPfwWiu/vREywziJuBBWWYf7Dh71p5TtDFV28QNwBr97RpdyLq7VA1Yczli7AIZr8kf1e0RVwPoMU2X3FLdmi5QDj61DZu20zteea7bNBFJrTZBm/9Yp/ZxdEExUdrryvS/ccsAX0IpIYTytNB/hhhCEJ5djBje4sxIXCEm7+NgwkUTntMP3k/C6HPA2g22kACSLm0DHPDNJxjy2xa+Qh8oaxsm3jWx96etPJtjoUyJ739a4L0Les38tn4+CuM3Wk176wetMPy2uXFuUNwMbDPbWzMFceTprj1YPCF5kdoEHFmwrXxCcRMa8/y+EIOOTN8MC4l5gdtfWcm4iHaHskcsmRuE8PUIZTfuHHhRzbm1hcjuItE4IYRGESae6xro61xu0BaH1v9rd3mouEqQr8OUIYNiyW7nFogpK19uzTb78w9aeIa9Pzav//aGrfn2JjbfOvjueHUxS6jltz8YF3YWghhHhou9CCmdZwHCJCdijbR/4vmxBoZLFcfvoYWZGtjaQGRFohlc8gsSsPu7xCEbMPjHR8v+mPIXIAsQHV8DU587oP+trnb14emi/UdSkCWjaet4X7abRdR06jb3jvCGgsbv+TZANxiTvTxuScPewFj9ciJ5/XTbtsfbeycy9N4u22uDzImo0TaR7LG79pPfPJNpd6BJJvrNmdsf7RANI/Pv8flyYLzwm2u83yb6/a3/cb6xvYX6wsLxjah/8ul8fLYy618z3mGoonBNU23rX9PYg+g7HDGnS9wncE1ir6yc9CfdWbn6MmTJ7Vs2TKUpmjovsY0KQR/jZ07+ehH74H/vwvB5pNlmxZ7ktsgvMKGfcYHtzvGNnSX2ETcjdtOCg4yb/SsCYl3fn07m99v7AD0Tfa3CV53PrdyfX/heX/7e6vXF7/26xN7xhfLs+5gwxz/zh5k9fFN3u8mfu77m3u99+azV0/ytM2eY/18R7Cz7z2BWN7nuLz8Yb951PZ6n2WvXyzP6sKTx9vtajDe7tv1Jp/Nkzv19H3ig9+7eWTPHv+Za4f18/jf3vlnf3r7x7cc72f2ve/n9ncgyfsce4YJJjzMZfe20fssm9euTtTZBHdvfb3fB/J6+9mU5W2n9zPvHPKuRd9yvL+xsh51nfk+405Z3l63J99Zy64cq+P4uHvXvl3WxrvJfhJwsjr4Jvvbt532nXcs7HNLd8p+tPnmHjL+H89ctzV8px5WjpXp/cTbZsvi7bOJdRx/nF8v96q/px6e9njL9i3DW651tnee+FXYfX5ke7R1p/1z/ty8ce2m/71jcq+xvZPPMxb3efw9P/a227cN3nZ5+3jiXPfWxR5o9fuyyZXHQ6wP7zrPaLe7hI8XYGW5Ovl87u86+yaF4C97Lfiy/TmZf7IH/tn2wL02QPvMNzmNsO8H7r1tHl9+s7JHTdz0vH97X79Q9PgHD/v+fvl8P7dneJ/jffV+7/ud9zPv64O+8/7mXq8Pyuc9IDz5vti3Lu+9HvqIn923vPE+8a3Bg+rtb/F3l3cnl2853k+tvInpXp9N/I0/f/s+xw48b/L93PuZe7WD8h71ues3D/nDnj3x+RM/u/da/GK+hxT1ha8nlmM/uLsu5i7yhWzug/uN2b1/ff9P7y5vYvmefL5jYZ98VWXf/ay759X9BJ579Zmnlv7/91719/3sXmV/FeX61tB3j57is18/rBzffL7P8+e9bxu9v59Y3sS5bt9/lcmVN/7Au84zyrnnVOfzL7vGv8r6T3zWnV1q4jeTf0/2wGQPTPbAZA9M9sBkD0z2wGQPTPbAP9MemNQE/zMd2H9OzTJ/RTMhYVXBbAnhAT5sdrc1U4z7nPcOesdMj/igmUnGNKz30gZ8c/1iZtBRj58l2l+rz0QNgJmVvG0zn0LzlbJLu7EAWWAADbhnvoe1wUyBBjvkBXG3frD+8fVNs7K9QO/2vfmh+n5mZbh84/V6WJm+37s20YYx0wzcI79rN35zHjM4dcOHz6MpsP6wMTXQf3zKbJytQ/xM9lxru5eowfUp5X/hCa7tHlO9rxbFO5/ss3tpXPysxngdRl1/T3yOp4894+sZF3CSbbxotzd55sIX54v3+3u/3iEscOM5vkZ8f2vtM39CS+Y/6pkPD8/n+4x7vbf6m38t3eqSe/btMb2Tw40789qtTfrY0xeeeWoaJavPxP66k/vB79yzmVPmd2hzyXfeWLs988r8Ij1z3aaVfWbrzH7r9hT7MMDkXUOWzbPGJ+iV6BQrw0hTrG3etj8030Pq4TuPbNO41zqzR3j63LN/uvr5rAfHWkZe65NANXXWJrdOGXMjsPhin3vabXPD+td8dRlxtzbtM2/y1imQ8j3rBVZFyra59kVUDdvbbF6bPzxlW/v455mjnnPEyrd2W7AaP/E7ecr2EIM8qO7W77YXUQ0Xj2FF2Nlkvrm233n2+gAKJr9nHlvZ5oZhAchf9N13v2GN21L0zjdyunPI5uCjznVrj/nZ26sl9+zxcXcfUIbVy+aUp2zv/mLrzDP/rL/tHJp4Dnry/9P9d1II/qfr+8mS/eyB9qZ6Iuc72UDGCKaIVj6QPqEsKAsIaWkyoPgIYJCSWICDampshJSgXymgEMTFGjHFhEPJzzK/7M9sszSKzSqidEPDoxwigkXQ+iZHJlFV6ZAEkoEPSoPJCzlAnZavpoG2RikTJIWJ+Xyfca/3hghRDZi+URFbCgUJIDs3D6YfIE/Gk6MXbahXA6DZUbGJwM5laBS8umrq004UvyWDxsnOmU4+4D38TIYy0NxQp+bmNo0GhSoL5rJ4CEu8h5zbTKlfVWWVuqBZjIiK4Tc5HpIA+qy9pVH1jU0EREZoDtHOUzm0/U12yHS2t0DJWw8o0BSHKpIBFNfEYCsbm87WRg0AX5QEuL8F8diJegsw81owEhOBLwoUr9ZbRzv4BsAhLmf8ckA0MTQI32RwbK200UglwqISgb9LAN2gVi3tIO+Mp8iYeMYjhzr4D4tjCBcWjd/Kc8Kj4pQ/3SDn7sx9OxwHQRG4WV6pYQLBUtIyHMOijVd9TZUsYt1g3qZDZembz1un+77Sb0bMUHyjxGEb2+8Mumt63nSFh/keLxySRlxRWcucBueboBo7HFsa61QLbqIRXmQSCR7rSC7uW9p9v7DgnxqwUENiUh0SgBvT8V8blbfRNLd39FC3BOD4smgjqDnMgdq6BpAyItlT8kAYsKC6AAQT2t7X3cEar9PolBBQaXK+APFmgmJDHWgRsCTFgFyQRdsNWaAX9rTq6nryhZLP1khgwT/WXkPAqK1ttIWqrOwsUDBib68zb0cNDw2AUV/N/OqGRTMPGLiE25H5rY016rsVqjQQIwyP3N9kc6mDshsamjXInpxB/ZPBpDWh0CX6xdGnV1ufd4F+E67svDxNAymloqCiXfkAAEAASURBVKJCXQYhNJ5i4pNZJ5l+o1PY2rW+q6mCqGJkTAkpIN8A/ea7xr2/Ka+ApZNxSWOuJ4AYUVV+Qx2A6ZuwxkATNBfp6OyN2MSvUafd/T1dqqmuZe/qU1xSKugFqfeEOrNx72hugPzplrJA7QgNGlVTQ63qQWkw+EpPnwcWGDfE+q2rqXPMhuEwEU7Py/GgW3g7E/FzGNz1SvbWPlB5koG7TOdMsYDFRspuZE+2sci3tRnuCRK+nfWBbzx74/XiawR5eoRcC2rML5ypKKCsbM24PgeRp6qyRgME6CbQxnSgAw2era6afYm1FwFcl83/KCMv+B8o+T/zA6w064Cbl6Dak/ZeAT2Es+DFdUB4AZ3lXW8GFwbTpQ7zPRwIeulxsHtBDblWDrbuaYg0VgOZVRhgwfycdafjPHcvmL3G4vfOJuDJgCIbJ/ERZ6Q+OQkuLZi183n+m2slZCft4LNK4MQWzpZeW0GdQebwa3FQJvs5lKjS7w97cHBXLAALdwlwX+F36s8acnX7v9+nH5ZKT1MOa0q/OUD5vD62WNo0F2gz+iKQZOQjF69Lu2nzm896+tDbVttvfrUN/GBgy7iECf4BvbhI+ptPPOQcAwRzGovkO8/QbsbGmy+Q8r2/Za05YpR3P4e0g75YPEd6ijaljcte1v7mdunQefqZQPGfbKE8Ml8pY7xPeCDeQHTR+gLmg1fuItPhnR/pVHGVxmCPS8mcoR/96NvuNl1+7aI++niHUuc8pm89s1anD+/WgaNnIeYYU3zadP3oh28rEZgif8fQ244v+2qbTi/kBX/73/5awbHJ6u/qVGL2HP3gj96AHdCj7bUNrRwQ7Z+9t1s5YMa1dw2BgfyCFucn6Kf/7b9qalyaetlUUnPn63tvv+ooSP1tRwfYu9s+fE8dY9HglsbIhKpIsHvvCMFjunb+mD7ZdUBhfNfIIfnsWz9STviAtm39UF2KRpAgH0JRNPBq/grBdjgOAcP20ft/0MAY0E1AJnUrUv/uX/8ZcHUgIdAAY3CqvHZOHwGeH8EG2gGcV/LsFfqTN55U6cXj+mzvEQXHJAI1lKg8BBMHDefngPTByLZvx8eq6UQTAvxc72ioXnjzbS0uzLz9BBNaLsCKt+2zzzRz8zt6aeNSIOmC1FBZou2fbVdVT4jeeefbmmu86gEma78J4R//4V0duVqvv/zJn7OXMJnHk6OyPfy5dh4+BUMcmMzgaSZGLXRweDcqap3mqKOlXv2hCfr2t9/WrJxkb9YHvpr2pfTySb2/fT8C3VQonHu0asvr2rgSshCETUsDYCJ+9t4/qripH7xc0ASA9Hr7j76jvtor+nDXIYcUMQDc2OqnXteG5XMRUv08oCHCaK2v1N/+9Geav3gRMF+hSs3KA4s357YQbFHjRoCyZ8cOnavo1P/yb/8cyL541ZYX6e/+4few6mUzB+uUDcHLW2++zNgHBolk1OolV07rb37637XshT/Ra1tWAR01fvkgMv3wjg90HMD+aAhoGmEteuzpN5UfN6x9n+9zMIRG+JA+Z7VeeWYDwpx343lglzut3MhAt979+5+qHYB3MD4gg0jUj//8h7BzmWbUYDcHVF9+RX/zyw+UDE5vb9+AFq9+Uk+tnKFf/fyn6hxF6OYSMiU8RT/5Vz8Avs+02A8u1/ttJ+x7n374vrpugTfdWquItBl6/bWXlQMmsjd1A892fN92HbpepwzIROZPmQaBAjiVXBabgen767/+a0XnLtN3v/0a0KGx3mwPfR0Z7NW+3TsgZupSMHOpvnNI//Yvf+zYJa3+JhA1V5fo00/3ge0erP4OiI6SCvT9l9fDrHeDiybwWQjxrQ1VuhXL5++8wWXQvzE3NIITB3bpShXwh+w1vUApvvDmH2kxGKtey4YJ6O/+/c80OBUsY/YBMCL1/MsvqhE2yqomlCmsl47OTmDDuvRX/+F/B8LTgyjysIZbnUuKzmnn/jMOXq+k/KY2PPOKntm0FpnmzsCZcqMF+Luf//SvIeTI1Q/ffkW9jWV6byvYzJlZqqyp1lMvss7Aup/qc1F9WPmVMDLuQqAyC1pTfY2WscafXL14XEniuXhse++X4GZ3uee2owx654d/obG269qx56imTA3nLGpXXPY8vf3a0+5sfFiZ7nvGs4/z7Oc/+zvlzZitKNAaYuISlJqZD8azR5M+1N+jC5y/RyEkiAbHuL6tS6s3P6MVMIf99ncf8Ps4NSBkGTSl9Ydhwt/pMb9q8bX9yGSQryWxznS9VDpSIW1cBmRNj/TeEel/fcUjBIOSgrYLgYjfmHCcgOBnhBNAfeoCQnBZA0JUd+BVM0Hr0g2Eb57xxnreF0kHrkEgsRy8Wp5vgtpHh8DPTaHcPIgzELZPpCKMI4Tlc169juD2yVEE8elg2fIbozT2J5kJAEIwLSL/XBRpBynTsHLX8RxvMgXbvlNyDHExCKUNCIqnLyIoU/76BQiCx3hPPzyBIBzIBDHh+zyCpD2vA4HYLrrexMVNdZT18gbaz7lgz0fBp9c3InRS3+sV0p7LaG/47MumbsZ4H/14C6XGt2jDnnNccCjzDfre2uPmRIWHqKSMvjALMOQ/OlYMtjH9loPi671TUGYn8d6d/5iU0E7eRGMSm5KhObPnKG96gcLQ7naxwZ+HCKAFHvJwJP0uDoWLV24A1J+tDQsKYP4DegyIGmebCaQzv2wnkH+EOrdUFqtlKFLvbNysDmh8Dx87p5rmp5TPjSAYU1ZvZ5vOnDytGQtXa8PSGVDt7tb5UycUdytXrcPR+u6mzWqtK4Wa9LLqWp6A8AFNi58npGnIzexWMH+hls3OdZzusXYbHE9jaMzPX7gMOUGetqxfqRtnDur0ybMKm5/OGI2qcMEiLZmFFpObe5xPPm/++73atmZatadeet0ttFY0Ib9897cI+P3gVXvgzgymJzl7pt54IwutCiQhUHGeR1PQ29WsHQjlKQXzNRdA9+ioWDRHdzSZ9yvT93OjaV214SktBhrLMFhPnrL5wYaiO0KwzcRBhJNhxsjgfEbMtMj/TEM7isDUB46rQbcFmkzD3QGt6umjB6HHTWRyVzjzoe9z2rmcnLlSQv+uAE82W3EwW4VHRmnB0pVQ+BrE2aB2b/2tkrLzYUD0XwtsGtXz0GRnzVysRYxbR8117T9xUmsWFXqEYDa9AXByT8OU8+o731XYaJ9OHTms8zBpdRUfg9xgmRbOyFJb9TUdOnFKqxdC6uG3EGxm52H1g7W7AjKSRLSR0Wip7tIC2zK0jZkDv4sN3syqJig0VbNpRSbr8cfXq7b0EsRFDeBDjwQkBA+h+Sq/cVW7D10AhzbVwaLdcS1hI7w1pAvQRWcVLtX8mXkqP38YzW2VmsDSBZwYAWadhtqq9d7242pYOs9vIdgY0VpqoPluHNILL21R2FifdnwKDXVti+ayeRnmrwnnF8+eUnLeQj2xZoEj8zhxaL9mJ4+pHArjl15+SqEjPdqxbYdKa1vJl4gwFew7Ze773nBaNz//qtvjjJxjH1qfWuhObwvB9HfZ9asI/zVav2kTxFQwbWZzINEfbW0N2rH7ENahXHXBlOeFFLxvYRO+CILmc9WGJ7UUGKsBLvP//ac/xVLX5bTMQSbcoBmMTkzXi6+8jKa8S811N/XJkWtgvkdoxep1mo/WppcL69bf/UKFc+Zx7vsnAFs1zPViztI1mrl4CtacetbbId0or9VCqFadEEy7+7paEXZ79eY7L2u0v00Xzl4Aq3lQi1as1SzmVw/MZhdOH9PItFQuHv4LY2bOzy6Yq1fB/Darxq2eRjCLsXiZxo89xJLtIw01ldBkb3eXuws1g1z0m1RWXAzj2lptWjlfl47tgjilTEsWzgfLnwPSz5SQns+cyVYfmrPrZw5gfSnV2iVznBDsoAY7GnTqcoWeeP5lpcVPcwQ6J89dUVzXJUUkZmgpGOjqb9Yn+684eDc/i+VnZsUB8x1M64VLlyknIx3YsigUG8B+jp+twUBOzqB9KbOABQWneO++A+CBtypi2Qy98ua3YMcM0rkTh3T6erH6hl50TJrjXeZ/Nb6mXwZ2ygRQCXM9M1YytN+CrRL2IkgUqqH2RSizKQNMIewyHo2fKStQYHB7AU8ZAQoiF8fWxlnmV7I5aOUNcnbZ+VXSAElGGprNPA8hRW0TWlqELfsd0IW6WIvAi6JnJnUzzfPFCpjT6hAEmY8mJEYysEX8Pehn+VZJO6+xvGr5DNqMEAdmNkQB9o0nmVa8plE6S90WZXv6wNjTypqpYz5CIP9SEEQr+A3HRUAJi7KWFaLRpUwsEa6dvg8wodjIaYDCxHyC9YzfGTtfAX2EvKQMxieDZ/gpY/k+2pVlgrb9a+lAGL/p0a4bEUpGNGPBmFOl28nmwQLab5cgGw8umSww+oa8prVGpXKbNtppFtlku/rsZl3nmKaKAMU3DMjrl0+rtWcEIhQGjAcZW1h7VzcbTrMuXL4KILrh63r6+Xbh39CbERrXjPkpPAFzWWa2cs0EFMbt3cgbxm8ovd1QerJJ5BXMUi6CfTo84e1NtVAZVykiAVOS5cvMVORUzGgcMKZd8TeZoGljaWbu8psVzCePT54nv5m2BtDId2HOS1MBbEZzZuQBbt4IpSXYxOSrYxO/CcnCGMK60bL6ncgcHGrEDLnOxBmPNm4qB1+Yj1ncDrGYhGQOzFg11VVCaVuvhXMK1IVptqy5WzdvXIHN6nMuNEVs1B48W3/LDwOTMh1NS+jYoG5cvQBIfxIaMOaHT5rKb+YtXgFzUu5tX0LzI03OnK61q5aC68kieYRkLhDnTx3TtcZhLZgHyQfz2A6OOwIZdO1oQ1ugXC0vuqB9e/bo0tVrjA3sXwnUk4MlhjnS0DGspQtmQYDDRuhnsrlRWVWN2RV2NuZS3vRCxh63BwQ1Sybc9zPf2vvHlG2sYQg/2WnxqqisZn5UITxmki9feXkFLl9g9MEW+c08gU61vLTEafnMF9zXpcL8FxNTM7Vu7WpMxx5yAhOUYlOy1Yk2sLyqwRFJxKUxdn4Kga5hCDz1kM8cOnJas+bNR7ucMN7nPjsOdNUF+TmOHKKB+dXeM6Sc/FyEMChswVFNgO3MyFvMgtHJ/sGW5FdymkwIVoJtjmVkY83JVFIMlMRoIrw+6UbvW1dXr6x8mMQg9klHG9wBc2JVRQX5Et3ekJOZgSYy2PWb11/bnwpEwF5mBEJ5uBvFQNs7DQrmaVBle5MJaTfLy9UODnnR+ZPatx+2MVxwGutqtGPrB5oSDeVwurlfefCS/W23Pd8wtq3PcnBjMiuRCcURPmWbsBgZk+BY5LraPAQVs+fMdnVMTk5xbIGRIbBFjkZp1UIuvBPcxLxtuNerjVk6VoacnGzKjrWdDYEsHBmUjWs8BWNGjAga5PIDgYxRmEIkYgQwSbicOVcc3DKa2/u0DrNjGAvVJ6v3Efd8NepzW6vpKXFcMK5gNUZhgNuR77lprmxHDx2APS5fcwryOIBwjwLD23DDjXEuMRENqlkFuBx0YRkIJCWwX2fjemIuDia6R2HZ8PrXOjcz3Ll6IcmJjIpSYgJkNBkpqmBfiEQA7mKdlVTUqw2imgQOfIu3CCTZeg0JGoP0olxVtQ248Zg/tfWdp9+NCt7YRhNgOistKdZQSJTmFubg7hanmTMKlcG+Mw0hLyoSJVCAyo1A6vkov2Wr/nqSnfUo4xxLm112zAUC4hINmdBDkeYKUYXmEjlAe9EY/v1ONII3ma+cQdkIkZEIxXem9YPraAIm+6i4BKkcgXeQAqxMO3sTEMTsLICy2iOw8SoEQVuz7B1sXAhffLYkFw30NWnnWQSyNjTS1M/A8/1NNq5YAhVKpW8i+AWzLgtohzdB9qKzpVwGKCeF840LuGOuw3IvlHweIZX87F13aXK9+R/0aq6eWK+51X7xV3amGEX1aVwlfrlL+t1R+oIybO5iEVI1irIVhVwAKNt3MX/xSV/8xIRYlDq6VoVLQyVjQL/ZJScjnv5lHI0tz9qD65ZLxCC4eiZTV+/GA5a4Y9Lbd5w5cIC65sMQSN9ZsoVtWqZUFu2ChdCfMliHMMNdu3FNh8+VwgCWia9XlPuNaZdMA9rDpm+myaN796kORiHPLd3zvG/qv6aZG2CCGyi7CQCOTYtNp5+N0NpkyQQUA4wPdX6IgNYzeUw71o2vmX1mPrQGpm6blYHAj3ehX02YyoGYmZ2n0FsDaAiP6Oe/eE8V9Sw0SzzIGNlu4cvnDUaKwFfJSAOmwMFt+UJGBnTu1GH9jHxVZl4IILlNkY2/07SiJ05o1tK1UPPeTYJgQRXmt9yJaWSUW1s37GkdbS3OTJmSkavc7AydPrhDRy+UOB80f4v3lG0uRp1oG0zbzuUBn0DfZIdoJIdHFIQFXkHNgmtMOI7HdcbG4VFSV1MVNN7X0G63q/RasTqgbL1aXAILJQtgPLW0NnOBG4ZmuMD5YO/9bKuuVTQ4kowBmNROHNyvpJnLlALd6DQ0if4lC/RByKUca7+RVFiwzy3Wwi3mms0b81MeRvs/BmmKdz4aMUUvJky7aNhc88zR8Xzk8nu+2Txlvs2bPUNtsMLt/PRD/eGT3fS/jyDKGphG/ybExzttHVsPQUnGrBekJJi8Wqqu68qNGvs0IPOwbS779+zGUtLmLnylFbW4WBSrsbXjdv1Nzx/O/DZBq+TKWV2vakZBgTZx3ly1YWnZvmO7du45AHti/+216U+/28XDCG0sOMkCGe01jIu3kbI4n1MeYsFjRqhgfRtEe51rD591YjKzQDFPUFcIe3+Ye5Y3nz/l21hPYZ31drZo/4GjysVMne3jCmGuN1093cyBYCycM7hg3dLWrZ9oz979Ol+C6w2m2SvMz0YuS9dKKgI6c7xrvA+N6qkjB5U6czmCvK0nG1lPsjU+PAj9OgxiY/igD2FhMU2RzazujlYdQSifjhUsFg21v9pve7KVYIL7IBeMC+fOqTckQYtm5/sIVhZQG6QUKGpv9Xfq6LHTaDCHmQOey+0IdTqFBS44Nl3zZ1k+f9eZnVlWOmcSa8tiHsJpTwdseb6CSumFYyoqq1Yb7HRFxTfU1drA/IQqGQ3Z2aN7tWv3bu07fBKWVMg0AlBsWNtN4DV3srqqctxBurQedwovGYyt64joZObANB09vF+79nyuExdL3ByM4pCNALe+FReV46cuK459zohT/E+m3AjTPC4yA8ypw/t362f/+Dt1oJzynq+eOUF8AEqrto5e2FD7nObYlYGWq4myK6CEX7lmjWPtdF3pfwW+1l9+bUKwTRfThph53oRJd/ZzHk3lM/vOOsGEtoWz8EfdjGYWjewphFCfrdPvhpv2tw6NanEl2i8EOxPMuOi5ZN9x7jnNshXMfmUWIac1NkGdccT0ig8wdfj+E9AZz4RamL+NYtjvc2i8pliSdfkGLgGlPGcuwh3P8CbWhXPzuFrucT84U4QW2LS+7A1WB+sf2ydsblr/fFWJvUmvbZJ+9Kz0zAL6iXrgTuU0sKeuUB57w4KsRy/N+rqU8+t6rYeqOph2YHlyzzdNOmctd/X7p6YW8tIP//p16d/z7+R5tOGMpUs8awQhKQWtg2kSLGhnjNtu6fUiTHpspIcO4QtdruJzRzAv9nMYR0ENOV8boEWd0tvpAjDMLeCbTna4RXEbNyHXc0OHDQyzhjF4eTZS+h1tyjSYzIZtgrKxmqBrgWjmfmD5bHMZQjB1+bgZBjIn4lOz9RK+sD/60+/rB999S2PdDS4gydsPIRzAxhxkvqR28PbCvjSVMlKy8vUy+f70Tyzft3SroxYNY503m9+vPWhD9qHN7QqO16vPPeHYpCbWPy4pQ8+8+JI2blihc8cPqZ+DMh7N4GNr1mvThvW4ceSoBo2DCWmBJNvcZy9apTfefEUZiWE6foGF9g2kkPAYzUOwMstEDz65Qxy2TF8sU3fqb4JPZm6h1m/coiee2KLchKnQnXaxF2Hp4NJw7FKFntq4BmGRW6LfiZ5FuDUNtkV/m+A1iKuHMbAFm6DEc+yADMMfcArCsrtYcgkyYS0yAo0Z+UxzeScfrGeWx9/ymeuJzJs/+4sf6wc/+IGe27RS/S01CJVoQB6QBlifJVfOI0Ct0KtvvqU3X9zEIX1DlfiL+p1o38y5i1Ro+8LoMKb5IaxJxpZlri22p7KGetp07GyxFixfq+989229vHEBWtHD+CYu1osvvIBAjEYNoSAGISGSi5G/7TYhz5isRljX1u+mxTU2L3uGNwjUAsWsf4dwuxlFYB1kswziMIrHZcS07SYE2esAApE9yxdr9mF9YFayHlyqtr73a4Wmz9byxfMVb5v97TRF0xjfnML5UElv0QvPPMHlFvcfAk6XLV6oKRyCNu526TZTus3VQFI/wWmnjh3StaZBvfPmS8TeQDU+4QFRsUnasOVpvf7miyriUt3Zx8WMMqsIYLxa26NnNq/B+jqu8ZiQ975/MqYm4J8+tFM3Wwa0actm58/s1YiaBry1oVq1vaG4XL2qH3z/O0qcOqBj54vdI+srr6muCyp3zPpxaNoCFcaMDS8uJUtvf++HWrkwk7aUI9DaHu5J8Wm5CIuziCcKQiHT5xhBI6LjtHjVRr1Ee4eYJ6kEjNmFMHJcMPfmfdirjVNp0Tnt3n9Uq554VjOzkynHI8ya9S8sMl7vfPcHmluQh7aeekKpnJ6eqlNHDytnBn7A3/2evv/dN3Tu8F7cxNr9H3PmegQ+mz/4sz/XD374A7309EY0aNWqxr/aa9m0ujst/fQ5euc77ygvJUKXzp9nzo84Afg3f/hU+XMXaiX+osjy/0Olu9UkX2HVTNg0E//vL6L9430fVgmsERpCSH3vrIQLmublSZ8yN2dGo8FFGELTLxQWcL7jvtCD+ZDfNqOpNM3hg5KZ+i3gay5z0TTOVtYnaD5P8byjCFU5BWgo+ezvThE4tlGaHocLRKnnd0fLpFdfoCz2XtOamka5m2csyUA7G0DvIK+orIIy9gqfOgR8nkVAsMZoxy7KWkkdfvgMAiKXgjPnEEYRPhfz2bVb+CXTHx1p9AHC6avLEBoDnCTmi4s7mPDzVy0CZHeyp311lMWe74TUcPaaizcRThFK4ygbxZMO0vdYKJWIZvpRkm0gKHj0xFKey3vOc/Uyjnvo51uM/fUm2jgfzXgJbaZezy9G0OdygjJGKAhUxW9HqAdngLu4jNLf7O3uALP6mMBoUaid9RW6dJGJhI53zop1euyxNVqESbuL6G7zCeuLyNTCebM0BR+tY6i8P64tVULeTGUnx93W9tnzvqk0FWE2LSdf7bs+xCpQqaayYrUOEKWMur62/Jr6xsIVS7sKcjJ19sxx5cTi3sGkT8zIU/6MAn16+GNV4MpQh/9Ux1CI0pPj0QIE+V391qYatDs1RIMTcEQwyODYVPw0w0FeqNdVNG7LiFi0wKRrVTd07Waezpw+i4lxgUb6W3XqVI3SsjLVUEI+TVNsLIvTz+SQEbpb9Nt3f4XTfborZ3jAtI0h6uvEFNvcqZSMLKf56w+OVlw4vpGlJcStJCsLFIrgvoMqKipWUF6SSuiPhXOedMK6n8Wrq6NN589dUMb06equL3Wm6cLcpRrs69I5hOH8mTOd5cBMkd343nSGtjuBNZqFPjrcB7JCJ3OYf5htek1IDOCQisH1Zd2Gzc5VZ6inVeev3tBsfJtD0MZfPneN7sgnqDNPPZcO6eyFK5qTFana1n49zg28Hx/GS7hSZMxeii9fdECaMesb06jOKMzX1aKriqFPK6+cVEZeoRN6r16+pCCijtMS4pU0bVgXbpQqfkqPitFAz398hXpGCnXl6hXcdYjcv3xKmXkFzu/S3z4360VjbRnzqBNhNA1TaLlGg6ehABlTydXzGglLwh0oRVOwLrQQvGAavHY09FFhaKPYcG9cLlLDsllceGqcK1cYWlq/E9rVhcse06wFg+xnnTo03KrWmPnOr7expoK9vIPg3CwEvkGVlJUpnaCImrpGYiKSUDag/cePbBZjdOzAHhUsWAlaRqLfRRv9dyq+2yPtB1VaVqKI0S4sYcPaQpBrW2OVbmISS2AsC/Ona/+Fk5qZForvarniMgpUyDwc+fykSstLNXWoTdUdI3qKPgrEFcQEve0ff6jWsVitn1MIM+0wc7lbIbilnL9covkLZtOeBJ05cB4t+xJ1VhQRuBepxUuWaRbCkwkv105x4Snv0QyEpkDOnKHeDm3/ZCsBqKNas2qFbg324F8fioa3U7VEnds+NtBaxZ6He2F0mMquXtIoc3AqhXQ2oyG9UqS5y9YoNc60x8F+97n90FxMju7+SKc5LFetWKZwTK+dmDSj8QW8fLlY8UkpTjPfWntTNwyZp68BN7k+zcD0a+g3Bz7/nHFbqMLcDHe+BFK4BX+VFl9V95QIpcVOxdJTpoTClSjV+lV88YpC4zKJd5ihJwkYs3o2lZ5TaddUZ9kyH/nktEwERWn7uZN67KnH8PvnIA4gXT9/VLsPn8eHf7GyEIrMfceCeepZOx2cp4vmz3C31+kFzMuiS7ra2K83XlioombqUVqKC0u6+kwLhvtKCEKzv8n8nNtx4zl7pVaF+F5XVlSo/9ZUxaDFtPOsl+DMREzv5SXXFJUC8gtrobq+WbHZKWqtuaFfvPu+Zi9dpay0RIdQM0BfhKGE8SqE/K3H1/W74P9I8vvhI0g5LHp1IcU9JJmAZG5toVwxS2v5MYLq5kW4H0R4tLW4I2k6gl8nwmclwlBhLugIjGEw2sPdFxCGGCMUF5rGGZz3kL3J5AMTfs3FwS5GXL5FMbqBEgt3IG1GEAujPuyJRH173A/aEIqr+XvxbI+A2oLAdpX5McTv1lPPwhTy8Cz+9CtxwZUpzW4ijDJngGIhL/VJQuisZq7OzSE8h3aYi6JpyJNTuQRkelw/Kumferp2DeWaVjY6sLWhJupO3IHNbSdQEgisKQiW/N+5llwu97TN6rNlCRpq6mHCaDMCJ4HKSqGP/W3nxM6wWx0KTYekYb7dKTy7vp420w+m5V+cjehK3zRTmXzG3JAgWEvO75duUkG6Z04U1Xg0yciyzmc6LKZA/TFPoTmJUQIbWzzRpbkFs7Vy+RJlcruN5yZtwV4JSZiA8vKVh+CWSKdm8F0S/oerV69WZlqScyl41LZNbOvD/jZNkGk6LBI8IiZOg0TUFl0t4jI3oCWr12nejDwXAFTZPIBPW6Yz2ZVyQFy/UaKwhHStX7cGv84sDXQ0unzNqNQt3/yZ07FK+O+71tfdqqsXz+nMeYJlgPxa8th6ys4mOLVVR08Vaf5CgikQvjrxabyAENLLzejpp7coGv/j61cuIqSRjxvosrUbNJ86+w0Xxg2mv6tFh44TkIZpvIGJUIowHRSdqtDhDhWhtU/OyKR9BHCcOaPLV4tBkZimDRseZ3Ml0njqmMrYSEvwU03OmaWNa1cqJircx9T54BGwg6f48lmdO3dRN/BJysyfo1WLQUhgU9m3/4jSsnOdi86RfTt1pbQa0x7R5cNBys9JV1PFVW3fd4xNelCt+G5ncIlJBFbJ32S+zmFo0yPQbBncVDmbwcJFi51b19lTJxQSm8EhgA8m/srF9PFNvs+ZvUgrF8+jP5pBxKnT8jWPKxOTdqCCgS1e00A2cuG6jIAxAArA4xs3KINo44vnzqp7JFT5eVn0A4IPl4yyCi5IhfO0evli/DaBaCPfFebpUFAEWuoNymIRm4DqTzLtVE9nsw4fOor5F3cQ5tJj6x5XTjoXGfz2G/uAyePwawGN4LOdexx8YWtrmxLTshwMXGNlqW6U3FBL96AWr1itWQhkfsN1cchMxZUgAnOvubH00o/TkvJUkJWslroKrEQETC2Yy34aCnwaFqOSEk8bN21SCkLMJYIJLyDIRIHS8cwWkCES4vwWRM3vNRQ3EFTNuk7QU01jm2YtWeU0XR31Zbpe3qDMnBy0fqkgRJSoGBeZkdBobdq4XuaHT/SQJ19TuxMQVrImLZjOX8GgvblBZ7nwNaC9MYi9mzcr0fIC+cf5sv/wGc2cPRuzd6zG+tt08fIV1bcSrc8lbU5hHv6iaCHpsxEuh4NB4ZpZWKDoCA4HvxLadVBfTnFxrgFpo5nDpwT3tP7gWMWGDuvyxUuKpj+Dhrl4Erh88dIV/OCHtIq5PYtg0GaCIWs7BrV8xXKlJIDcY4JCAMniQS6ePkp/t3DO1KkKSMeGrmGUaom4ARzV1Jgk5xt/C7ek6+w9FQRVZxLMtozI6xDqdOJyhVatNoHsi9CJD6uGXfhqq8t19PhJFV8vAdUjUY+vW4vLZbiuItj2BsfgG57q9tZwNHNBXL4aukdRBM3W2ECXQyOpYbwLsVStXILm3rTnATS/HASUIvatOvbVuppqVQCPN51zpKrshsobejR3Vp5qSq9Qv7Nq6xvRysc3aMmcGWjpY9XOXm9rvBm3nyWr1uKvm+csdA9rs31vVocBfOZPHDnGnn0Vv/pbWr5uPXMpV3WUd5MgxFQUTo34559Cw3ftepliUy3GYomCBlp16OQFdXV2qLqyUlXVNQ49xgKlHzT2do7W1tbib5/BGY5g8TWmKZiMEFP9TANIiWX/CafZn/uZAXkZLaWZ++3i4WJUELzMTO4EVz6z7/HldoKr+ceb4GvaX7NiWx5bm4YcEUjC4oD2CQEbQc+UOeZjiuWJqG8uTpxrXJqdRtaCyExgjuF7bz2xWBJo4HGfCGSCmhBsGk27kVlZdsE14RCLhPooz95zAXLfcc7yAzOJ8zd9YagRwPo5Nwxrb6DmApRa+B6yH/Msq3McQi1nE8KDp4xunm+uFiakIlM4DTeWOec7bXUIROP9sHHA+uFg0sz32/rdAn+tP6wPIkPRFNN2c6Oygxu5QfGcI9Z3piE3EyYuvi7PcOyTakv/z+DFAnPDZBjGbGj+fbYgvP3jBZy3fGbet2Q+xLfwv5lKY+2gCmCPcfm/zH/aMTEZ5/lsDqAIVO+d+Lka5m3wtEglJye7YCeDzjEM3OjoaC4Cow6yqYMBjEPQTyZowqJoLV9dY7NCLF9KCsIYAxpAsqj0Np7RAB7d1LBINpI05xPZj9tDTV0LPoK5msIEaWtpwSe/DTi6WBcwNQUtUjvausaWdg74SHBb03EVivRbm+58T9H8llVUO1OgVdlMwuloeYNG+p32aVpEDK5JtsHVgWU5rCguC+lpaazDMPVgYrVDtRf/1gQuNA7TNABNkcEnmW9xPX1n/s3W50kINqiAEDrr+TsJQSMIbNoGgg07nbk8ISmVYJV4Fg8YugimZiIOJ4AlOcXK5/NA07i5tgKNWFJSEsscTFU01KGRiRx64Q72zi4IvSz4jCwQItAU9HBA9OJfmoipzHyBH3Q43Ls6BDuyoE0o6GAjC4uIwqoGFi4YnQ0WfcumZpidgzb+NTXEZeB6kpikNDSfBl/WUGfYo+SzYCsuk2EIwP7WwfyR+/DDr+O53Zi7YwkcSsanOZwo52ZgnILC47jIRHCIdjn8UnONM+HRxjwO831rE2PR2q5wTMY2PvExJhjdu5UP+nQElxKDxhqbilsDm05/b4/DJi0gCG4Qs1cT86qTdWaX06z0dKZEP36dzXw2wKU5FQE4/vYe8qByfL+zo7PL1llTMz2NfzOBQSkEa7WBaz40irsE6yoiLNit8bZOcJgp23xVozgMOnHnaqROt/BZT2KumQAeSLO7O9tVX1fj6m91ssCkBPaPFFxpbK5nIxxNY0/s4ncWnBccDjpEGsGXzDevu0Yn/TWEtskQSqJ8Att823iv98NoRKtq6vD97Lz9dVpWrsLQ/ts4TI2M40whoLepkXO13zMfufxGMC5tzY1O4x9PgJz/fu+3i8HSMqDaqpvOF9fWqpn9I0CSyUfrWIf2MYK2mDtRL2uqhnaP4XaWhKLEUEtMY92EEGjuKDEmCASYTCNqwlx9QwN71BB7RDo+7fi5s8bbuJQERyTgghDFORviXEwMP7uJeAdzcRtFW1xbU6tbaKoMD9v21UA0/1bVhpoKtXBB72ffdL79jGkulge7uPexZ+Yy5haQbVjhoeGRBOCluLU3BBpAc3OT2to7QOgAszkry1m5PJByD+8EF6Bu/Y7g3cXhHcG8NkVPLMKElWeWn3AUAKZpr2UvGRkLcvtnAkL+CH1eikLCXIYs2fikM1fiyOt1YblXDewcPXnypJYtW+Zche71m6/qs69dCP6qKjr5nH9ZPdAffUcIfnQ99TfbZ75CsAm5k2myByZ7YLIHJntgsgcmeyCwHvgmhWB0hZNpsgcme2CyByZ7YLIHJntgsgcme2CyB/5l9cCkEPwva7wnWzvZA5M9MNkDkz0w2QOTPTDZA5M9QA9MCsGT02CyByZ7YLIHJntgsgcme2CyByZ74F9cD3iiib7GZlvYnQW5WfQdMR/3TBZMZVEBFshlP7QAL/u9/e39d8+M9/nQW6YFyFkAngU6e4OpLAsxVq5O5qptnxuihEFzefGMvXkCCVTwVsWCtFxQn7c93i/GX61u1j6L9zFYGvvbyjW/cauntfdRAkOsTG9Anm9b7fn2uZVhz/X2p31mgYGWrC7EY30lybWH51p9vM/1bY+3PnA1uMBA62MLjHN9z3tD+fCtv1XKglyMytb61qLwLahghEAg8xsyh3uDJJtGIJyRZQw6TE6C/QhMM7IJbxCIPecbTTTU6tYPNWIIdbY6TmyXpz5jBA31ufYbxq21w5IFmBitL9F9jtjB89vA/uuoLg02aWoYfRF2V4DbMM+3gIohFp/hk0ZA1WiBGhbcZsGFNjcMxzhQpAILougDH3OI8bHgqlDKtaAJbxCEYaMahq61zTCKLbjIMUxBYGG4tkYdbJ+HU59799f9+8DwYS0IxAJHLBles5XvywLnfsM8MeIS+34adQujz10ENGNl9TYsUEN6MBgff5Plt/40hBDDeA4OhUWLZxh5hTc5CDnqZ3PUWNWMQMICOo2o5EH5vPnv92p96Gm34bDCQUe7gplLBqQ/kZ3JgkmN5MGINGzMB2GzMixqL+g9S0wxRJMbOoStzUCSrb9+2mZ4yF4Qf8tvfWNt7KN/bWxDAd4PIxDSE8wKbS/fWT7DrzZ0jUCStWeQPndrhYwR4O06cgqfTcfmlI2N0QMbA6LD5CWYyZAGPPmY/y4fBBY++R5cD+Yuc7mXoEB7rs1hW2NGyuDtN89agrTCIpNJDlHCArloowUTGmnNlCk2R5krfObN9+By7/7Wxr6XNW7kI4aUMTHYyr63Od9N4KORhlgwlHeftEBjN8/J5yWOufvpD/7L9pchxtwCXD2BXt65Tpkcsrb32dwyRsZplD0VAWCYPvfs28wD2m17gwXPBpqsXYYGYzjwRnRjc+l2//Gd7TODrLUprGXbV4Ngp/LuDTYHg+gHIzOyeepvEKgd1tZea5dBzBku7jQ3jxEgxpMFz/UTlW8kKbbnWQBbOGXYOrT62H57r3ze/A99tTrY2UAdLMDUUFGMPMSbbM7ZvHZ7EPPRiEgsmND2HDf/qUc4yCC2L/k/171Pv3Mu2dyxMfcmN884N3rZ++3cszZa3azfLejXvrf+s7kwFXr7CM4Wv/vdW8jX9OqdtV/T4z34rzcbaD9n+2wg0b6Q6JsblQhCzKNCvh8C6eBkmUeIItDSsZ0Zrm0gyYQqI8+4Xs+GTnzSnGwPSoP3GTXUpxRYsWEENYNxWzmbwQW14Ho1MF2Un0U9DCLNBMZAko0z8oyu10GhnAwkGoHpExNnrCDCUgLPzwXKDNQVFVd52PXys8A0BmLsfpeFic/y/RuIU1XSJlgcHQ6wd10wH4n2B4+YOhHw76iiE0Bk6Oj2kIvcYv8pyLx3XX2f7+97a5+RljTx/Gz6MR8oOKPD9ia7gNRTn1bavZBxsS5ubPX0GeHsgkVT8RPOwWM73tOeE5cd619K1iz9m3/zfdUWn9fuPfvBR+7VYxuf0VMblusGOIq79h5UG2xhT774utYumg1snkeo9Jb/Tb0aOL6xBu3f9ammpc3V009sQKi6s1l562EHySnY0Q5erNCz1Hn5vOnuq2awV3//wScKS5+vv3jnee/P/X61zbAbyKh//Nv/V2HT1+iN5zbBU88EcAl6XkDjt23fpevgxYaFx+r1t95xMGq97Q0qugAUT3Ow3np5ixIMasTP5ISdgW599NtfgU1aqdGgUC1as16vPr3ZbXr2GDuITh3Ypp2HzzoqUTssTRj47k/+CobFIKCGTukSLDI//NM/BdrKUAr8LJyf9Xd3aNfW32j3yetOgI0kGn/Zhuf1xpMrbz+kFwSKw3u36/Mj5zU1PFpPv/Cq1q1YCEZyp3Zt/0Tni64DDJ+j1779lmamsxj9TKMcAKeP7GVOHgb5YVCJubP0rTdeUUF2OgeB5yEjIFDs3/WxjpwAP3csTOufeUGPL5urCycOweR1FBSdQSXlztZb5MtnE/K37SbkFJ/er19t3QM4/agTdrLAHP7hWy+wv7HYfdIgEetb3/uNbjT068d//mc68skvdIYFaxcHznUZ7v//9h/+D+VAYxnI/mfzrabsin79/measWyj3npuw+1SjdzgOhjEf9i6AyScASANF+j5F57RbLjbTVipLrmkdz/YBgb4E3rz2cdv5/PnzWBfp/bt3q59AMJPCQ7TS996R8uhnY4wfMvx1ARW6YdbtwMp1QJEX76+98fvKCZ0BLa57Tpw7AJIItP0yrf+SEvBWfXN581/r1drbz9QhO/+wz+qvLpRIRBTPLZxC2Qha1EoeAb8FtHylZeO6f/829874dguwpnTZ+l733pR7/3yH1VZ10S0foTmr3pc33pxiwcG8V6F3eczEyyGB3v1wa9+qvaQdL31+stgIYMJ6pNsXtZXlei//s3f6anXvsd5mqKDuz/TadjERsemaPGajXqW9Zl8e2/wyfyQt31ADJ48uFsfHy/RX/3PP3FMh5bFxrStoULv/WGrQ6oIhSr3uVff1Ip5+bpymrm+76BaIayYsXip3njpORmKgL9z3VslI8U4sX+7Dp8t0it/9CPNA2/Ve+Gz8g0pxNZja3C6ntq4GkbUUR3b/YE++PyME04jqNPs5Rv03Zc3OSWF97kPerUyS66c0QcfboPkpk9p0JO//NJL0CPn3hbAB8FQ3vq7d7XvzDXWXjgKiAi9AgFRbtI0cJ3fV9FNUGPAin711ZfZb+/ke1C5vt/Zpa+qtEi//tUvtfiZP9YTK+fcQfZgPvSzvovZvy8hzGx6/lXlpcWptuyytn6yx8HKTY2IdWtkyew8FC531ohvGQ9631J3U3/48BONJc7Uv/ney7d/an1TV1GsX/76D2oDlzk5vUCbgFuMuVWvv39/J4qVW8yLW1x4QrXxxXf0zLpFoGgEXv7tAr/CN1+bEGwCIQof/XK7dLQScgwEzb+acJY7gQhB9b98AEMbwtsPNwHl1QjjWrG0aa6H+tiphANssLG2vXtY2rhEOsZr1QLp6YUIwsCPWb2OnqNunA0zEf4MHm0KQvNvdiAU89kMhNeffiz95bcQ4mIRSP0UhFl3Mpryv9kqXWqS3npKen3Z3RVHYQFVpfR/fSit28j388Hv5e/zCIWLEBj/n49gz3sSvGQEwUDSzQrp5ztBrgNa7i/elpZm3BE8TSm2j/YCn6udR8CQjJf+1RPSX1OHpZQPnKJ28P2/fxPhmf7xHtiBlO/9rV0Azl0CDLwMEg7a8Itd0ubHpCfneH7Bfqxd1OFTfgOspP4zdR1DKD5znTGg7GuXeV8j/fE6LicxlofBGgXo/maNcmcu1JLFC8G+jIOApEU7dn6ukJhU5skcXQSUf/m8XJ29yMaTkqe8kH59/vlBLWGT+acSgu02vvPDX2vn0Yva/AKQTDbxbm+Vnv4w4oDiM4d0kA2ze4gbMxoE0yR0NlXr9+9tBde6G1pvjxbJk8O//5ow2t7aiLDzO0hnhhWH1nPYq/a3R8AWdejAIY1GpOtP/uQ53bxwVHsOHAb8fJNKTu7Qp/sgTVi4wWkO/CvR+ysOfzQfC1Y/oWWPT+EgatBvf79Vq1esVE4a+LdMLtPMLl69WXnzVjmNc9XNG/pk217g4aJ04fAH2rr7mMKTc29T/nrECe/zH/xq7FtDaEjmLN+oTavmAVcU4yiSb+cCzquy9IaOnC3Td//0z9VVUwyr0VlHatBcdFTlncF67c3vAHuUiDaUzSDAlF04V29nQjbBnvHRb/5B10srgJ5LBQrKs4mUXjqtkpoePfvq24oKHtBvfv8J+OjpygKz9x1A9m3tffjrvwdjthKMa4OQ8uR7WDWcQAYMWFL2HG14/DHoxePQjkXetipYfpsTIwhMez7+A6QNNeoH8N9Yph5/5jWt2GRWgX5IL8r13o7Tjk4+EKFkBE1rW125PoIuua2jy2mafevc0VSj0yfPav5jT2ohmo49W/8AeckF4J0S1d1Qpo8++1ztlo+xCzTduHQKJUqLXuMSN6W7Wtu27QR/Nk6zTaPg9o8h7fz4U0D8C/XOhid04cgefX74nLLD2lRW3a7Xv/2OxjqrtGPbDjDO4zQzj83Tz2RaxpWbn9dGbvmVEOLs2Lldj4F/mxgFWx+DaRjKhi0bmZynd1571kH+mQY8HOFj3ZYX9CT4xVXl1/XZ7s9hTlyn9FjTGPo54xnPPjTAuz95X7Vt/eynHquOb9Wt7CZINX73/jbG37S2WGcQ+BeuAD927ZPqbKjQ3mMXVVw+S8lLZvpmfej7/p5OXTl7XGcB4zdNtGl87yRodoFm3Pz8K9AzD4BDfUMfbd2mzIinwIy9rFkrt2gGY//x73+lSzD+rZpf4Pflw8bU+vXKqYMI8sX07zBaV2PmvFP6ANaNY/u264NPd2vextfYx0a5kGMBgSQna/YKPbluqZKAsnPWJtaAv8mKiE/L1svf/g6X+mB9+ttf6DzENwW52Q7a0p5jl46xKaFauv5pPQvwv62xaEglDNu4eSxBP/7xqxCYfKazZ88rOzNdsUab62eydleXFemjDz/WAP3dB0zbLTOpjic7Y24WnddvfveegmIytJrf2LdhUQl6/tU3sAD0Q4hzQp8fPMolO5n94R5aOu/DJrw6eLiWWr3/wceqA3M6etrd55KxhB7Z97mSZ67SK4vyde7ofh09cVzf/86b+slPIHOhbvWV13WQcybe4AAD2WAm1OWr/tO/XfYRS7X5tWYphAkIuCgA7ko2aYGV1PYz0jLWHyyDaDHQjLKWBhEouUQ53FxfLeJdD7jPH4a7ex1BKpG9bHE+Wt5CqaTOo+H1Zullr8UK5fB0DbsYmUAXqhEUkzyEFsZwd6nWg63rzfOwV9u6DNP5ubUeTSzz865k7W1olbZdRODNpZ0I3gbheYlyVyAkLqYPUslfyqWA5geUgN7TZgT+GC5WhsFsZXmTWWOfWAExB2VCxOW0rhA2qaoTrTN/F9JPU5jP5dTNXBi+TOIc06EihOu5lDcdjXo0Qn8Fzx1/qM17yI307GLmA2Ng9bTL4GPzPQQeyfyeS6SGxjPYwjGWnoaWNt0su6bjJ06idalXOzicjeC8GruXLcg5ixc7muINmzZrdl666sHHTQYb8p9yoYVg9tzy8ttax4ZgQpHPkLjeGKRdlaWXdaqoFprgxxwhhZkpO9uaOEz3ai40r9npKc7kGtiYjMEMBxnFsUMKS8rXgkLwYjFBec3d7lnmYoGJzvBM6xo70QIOKhUcz0jMW8vZvF/YtNz9/q48flTCxjckNFyF03OVlZnh8DhHnan4TuYg6hIJJmya4cQiaPa0tyhn7nKlxYVryfrn9OwT69zF03cO38n9kHdkMleOdphvDBt1BNWmmae9yQ6odvBZx8LjIcjIgrAkl0tYv64D7n7q/GUFjQ7o9KlTunajzLnfePP582pm9lQwYGMiQhGIYFGCNCIVocpXm9pYX6lQNIYp4MmmZ01X+JQ+tcCqk8hcjXb5itWPhtiEOL+FofHKmUWht6tDdQDMd7G4ogwP1vy6SCYAD4ARfHDPTljy0jRnVgFaR4+pNg5c31TwYyMBCy8rugK962p3cfT3jDJByywe23cfhtjlcYSLmC/M2SCwWsN5fjlkFT3gxg7cAkMX7OC2plptQ3O+jHyGhW31DDTVVFQ4gSsHYooZM2bBXdGEQM3mRnKaUgSiSjZeI9zJycrUDJjCKiFYMIKLELBUc7I9+Qa6G9UB85jfiTUUBk7rjPw85jrCDJCIowhbzsRshwHJ5rBpv3oYF8Nn7sFEHg6GczhzII/LT193m2PKMxztGGce9uTz57/dUCafPbpXHWNx7LfTsXyEUtadXcYEprqqcu3dw16ybLWSAW03+drKz6C+Y5B8lJeXKjohEWxhNt4A0tBAry6dPYHltFPrVi2FmdDG7U7Ztu9GxSTAFJgJHnQK52wU5x0UzZCqDI4GKwkM8DRIRLJSYmDNq3EYt/4Wb8qFq+eO6jiMS/PnzXMkHxP3Kbtor9rwtJ57Yo0jXrF5YP+cW0h7q8Oy7edCEIGVxN95bvULwuUkMSlN03NzwFxO5ezicLVB9k30he3jzQ31lFOPph/8XFsjLS0w5mYpMxOSGJg8DefZKL79TwiREI0cP3VRBfOX0Xfxrk207PYjrN+zZyzQa2jXEyEo8M6HhOR09lr2++Z6lUMpayyG5qrgb7qFlrcLq+LOXZ+rcOFKTcdKZRdv32T7Xyym+6qyEnDRe50cYrjnUVHMt4wMh7lu2NjBCXmamYvW/hFcYHzL+yrfe3bJr/KJ48+yyYUcoJkIWUmsMfN/9U3sByq/idsCr/kJ40QS/AD3Hm5sCIsnod9FM2j0yYEkc4WAoAbzjpQR72FMM400pF23E4oSGKXQuhyRDqOF7CdPKnVsQCtqbgKmkKhnP/RVnt3OfL83tA9XG4/rBW2YuLh6EDSNqpn5qPxEz/ctlAG7ppDb0N4gPJMPlxoEkPsVcu/PwXlXFvlhLvxCsnVqwr1dOLvpg+mZvKecCEa+gbYiSyIE0c/UL9Bybf2ZMA8Jjuu7ujaphfoXUoaVaUQYKAnQ6nmqZWdyTirfUV+vcGBCMC5LzoXiSp3HHSLEO1fYYIYZvJCwaLdxThnp04G9+5yQa75VjQ11qoHt6tzZC+q7NUWpmdmOMS4eE353RwvjhwYgwL78Qgc+4gfmh2ag4AlxkEPYIExIbY01+uSznQqJikPZjU8jQooBjx/eu0NlzX0wjeEfy+e9PV3MyT4nlE54xL3/ZHO6fOaYLpY1AdIeRd8OOjph8wm8s18HOXrcaWO9Onl4H1S69Zj0sp0ZPQ66wayMVMbnUbaGKc7n0vwbx7hZ1qHlyp61SPGRsCeNLwjbqM2vO5SBb0UoLINDe9WKpZArhCIcAj5vRAtoyB4lGZVtdGyCBjobdPzIIX386Q7VNHXcfpQJJAP0aRCCejR1jIvF9xXJoB7SggYA8Ec4GIMhMDl+5KCO47MUyNQxjU8YvpVjw91uPo5BC20EIKz02+XHJ6Spu7UeFqtqmK4q1A6o/SCCk/lGjg4aw9YFjcGQGBGgC4/5HRqAfehYv87DgvbxRx/oJOZur3bOtDhN0ObuQwuXkRLn/M37Mdu0QJtph1cIm3NddYVuto/B8rTM+UjfqfXt6t/zzQDz89CebWrpH4MMx+bsIP6nXU4Q92YIRgjOnV6gNsZ7/+6d6g5KYG8I1uHPt6l9gLoz183XsrsLOuuJ2hLvQ+75OgZ1bK9rQxx+zPHxiY4qepAxdmPHhB9B+zWAlSUMP0QjSEiGIKSHy3MzhDBmmjU2rbg4NmTmhvmq+jvmNo/NdzwKbc0Ie5QxeM1duhIiDHwtx8fc+QmHRdAvY7pw7rQ+3vqJTl+tQAGD7zOIdCI+AABAAElEQVTEETdvGHsfNMP4xuG66X9Cq1tZUqQD50ogJUhi7xhwCoEOhH/vfmftPnH0sDpHI7iYhbm2tTHeAwSk2MWwEeazy8Xl1ANiCwvE8DOZMNlWX6HDZ4oUY4x0CEjmV24EDQOsH0vWN7fjNPju4oXLWrJ0KRezBObooMrKoDSvrYGZsdP5kJqA7FdCwBzAdLkdK2BaZqazmpl/e0szZCXse96xMyE4HhKcFMhuvDEWdvmOYm+YMtiu0yeO6JOPP4Hqu87/fdXaxZ5o8QPhXFiaoGVu6gtRPgKl74XV5kS0XfD4/uCBvfodlrCaugbn+hUJTXc4Ak6C67cR3KYmaMru2wm0DEF6z6fvc7kOcRYiuwy0Njc5n3Zvu63fY1gDNseNoMabzB97CoRBRZcuqrEDlyusqb519v7ufq/D0MuexbWkpL4XunPzKedcYo23s/a8grbtI7kz5mm4u0lH9u9STfsIrpkZTti1fbEXJtGKunYtXbHCud4EUv796vVVfe7/7H+EEu0cNYHfbqDeZAex/WM9avtpGMySPdrPph58WlulDYWY5l9FGOXs2nsB0zl5f7zBm/vhr/ZsO76Ngc3eW+KMcBdV03RaXdavlJYgeGFl1+8OIBhmo8F9DMEYLezpMgRCvpvN+RWIGMD8c+WYBdPee5PVwTammlq0zRX4AiMccu4LC5aSqI+tf7tU2W/st/fSGnqfdb9X20C9QqX3N7cvatTFtOtcIDVEm56Y59Gwv7UG8j98o82XGIs5HOzk9Km39zkPeqW6OOhL0NOLLvMwz1lb+Gdtce2hbta2EWsbz7d6+tbVfmPjYyx9uCHqzBVpOePB2/FNbSo0j6uUjoA72NmoX/16K9SsHi3W3EXL8HFL0rvvfqRKOni4q12xiclasXKFjv3st2jZ+pSI2csrgD2oLd/Ud3aIWHKBWUyUypKrunmlS+WVDVwWgjQXdX0fGpO9cNxXVFZoSkSSu70vnAEVqS2mhyUOyGEuBD2tdTpzsk1NaA96guNVumCOCjH1BlH+GA7w165eUXLBIi2fW6DTh3bq872HcJl5XZExX3JL4PmDbJoXT0OxWdWuJ596zgmDGIfvrEfaPYw26fSp84pIzdM8aKEfTei+uzOmotlbsf4ZLXw8RB0t1Tpy5Kj2Hr+oWblPMSc9k9KCr0xLZqNg2gzz3bagoGD41Z985kWlYFUxs97xoyf07KZl5qbu17LwjOsUJeAL9+a339an7/8Wf+ta5eVlI2h7+jR39iLNgw7z5P7daCEj1IXJK4IDwjS2SRmFLt8nf/iNrlfWoSnMRlvr31hYkE/2zMX645wFXDrbdP3qGed3af7l5nd3i0Aau1BZMOThg/vUymWrpXtI56+WKD8zCe1pKzSw5Zq1eCXxAYmMhf8bgY21zVtjQty1u043yqDGHp6qupaNzlfRDuY+fLWvXSvR+qdfUFbkmPbt3aUz5y4qkct4U32Vdu2qVknZTXUjsNW3bXTshneP7P3/CjV2LoRcG0ejWrVxDuZCYuNhmmW7nASz8dj3pjEcIgjPUVwjzNhv7TemIfTkC2THt/2N4CzcUI4d3KPWwVDov1ePm8U9c90EouTp8/STH0/H5c6E0kPaue0zrV0+F9bEqXp8y7MwI57Tth37Vf/Mk/iNRrHG/eh76m0m/mEEwvOnjqidy0Url4lL02do3uzpCqFeJphb26swn7fiqnKtrErdoec0CzbLeLQUC1euR4hN1J6DuOhUzVBeBgexn6mvm2Bb2CXPnTnFATbAGNbq5PkipaPxu33hpw7mM3zsyGENRmbrBfxyExjvVcub0Gae08cll9VS36rFS7iI+rOvWd145i0uS/2YWS9y0e/Hv78Oc+pI9Fk9vmoR64WAN7rP5tzEFEIw5txl6zV9ySZY/hqoO24Bh05p0czsAPYeY8QbxoJRre07dmvNlueUzzq1i7THimFuIBFas/k5LXgM9xQoq//xH97VNbQ+QRzSbr6x8xj7qQnUfoee2maFiXuQwKpa/IFvXh9RHWfD1I5wPbF2qZKxvliT73fOWblRcSl6/pXXdeXcMR0/dkILZuXcJShP7C/fvy1wdQiN4AD7xN69e1VdXQVFN1p8fOH/P/beMzrv5ErvfJABEhlEzpkBzDmzc5K6W9IozXhmvGN7d73B3j0+3v3q4w97dnd81h6PPZqRNKPQUqszm91kM+cEZgIgCCLnnHMksb9bL18SbHWTLyippfFB9UEDfN9//avqVrp1697nMfkFwXpoB6Eb0MOvZf1dGh/C3nNBl67c0HpcGMM4BF45c1yL4pK1PP/RQ8Pccn5ff/u2yj5t7eg8p+Txmy3IXbdzIykOBAwEaXkOlkOUqHash90ovRi8nLKUjGU4AqWMA5ejOp5P8TafzOrJLbNgLGRDwSIZjVWaCtS0oPBimbZnoLqGx54yKMeu37HQE8SCgopiWNWMRTLN8918ymaOOsuoKX32Y203JbENNwFugbSUd/ZaW7GOclBSUIKHStiU7yUM4gbksjmXuv76HH5sNaxcU/BdmZ69npO5x8INPbuul2NZx+L93d1Y5hNxQaDXl+fTRuqEjuBcI9Al512uTTxAGPTsetYn/u7t4WBRiwtEE5Zt5IoOpGjkSqyUepFDOmX4Uz+rq7fOdiNgOsKGQlxRsMb/358xJpAX2dxD05PDWLcu4Xtl19VcYS1JUW5OjtKxaNXfuaWRznD54f+4CCrek5fPqx33iNioED6LcvSpqMuPld1X+aVtmuNsmkYrmZSRp7/47/8nt7gMdTXq7X3HtW7bM9qxbqleYdGxSM39n+xV+3QULh4Pgz6eWF+C0bbueVGrN+101rXrJ7F4jMVqeUEOytAkVuVRfD7vqRsrTGR4BkFKmZodWq6yg7eIYh9RMsFkT51on5Vx5cwR3Woc0DPPvwRHPZsMSto0E8EQAMwPzyKWLRiqfXRWOzatgl7bIoWfutQHGe2QEIRyGRUZo2gMIaVE/I+xeVjQhvmcLoYadjEoFBMDpdwMTWENbEOBC1Q6bgxdWMuGsKhlxse4uhiyyHySuVoMjYwogOtPu+oNxgfRXDMsSnyGqy2joQ6Pideu517Whi3b1Vx/R12dffh8B4MUMOIsZw/z4dvMJHloy3l8TWzT98eaHI31J4aGD3XWaeZ2g7OUmcvQLL5f6cs36t/+m2XuRTcvHNfxK5Xatr7IHQCuXjorDER6dS3/nocCbC+LjEvSq9/6E+3Bn90P15Kf//znCk9fqQzm5xhW4nv+wbigdDvK1uzoJcSGpBB4eUG9tO65N76ul9kZLN9PfvJTxeasdvke39q53/opAWrs5to+9aOYBY9AS4uvs1k6zd/efCajGQMx4aGO7naEz5qaW7lVSmF9mVUX1279jPmAoTbN+ls+LGZzX/+Yv03pMQvZqcOfqGUkEAV4B76hiYwdP6cQTBCgaFZDVHJHlRxGYFbVLajS1efQbkZZrA2FI5rTvx/jc5wN0dZvnxIL5tLVG/Wvcpe7w1z1Nfwvqwe0cf1K9y6jaI7gGvolAm13Ps/44/Dz7t+PKHvTdqXge2/uItFsiglcqbNrEMzNpuRjsval5q/Sn6cVOIvgUHcrPsk/1zPb1rrbK6MVDga14N7UsA58/KHGg+L06su7Cdgj+I3arqUOy1atg6q7Rb/8+c9QojLcOu1T8SiOEaz///O//jdu/2ivv61Dx05p3c4dCkMBHiIox5Ai5iKTeN9rB8UAAhOXcPMWHR6IK1okrmAoI77KnBfNsqG3NdZo//7PlLh0qzauLoTmO8Idoswv2m6YApFPCFfCEWbtmsL1hUONQzzxj8TIZrTsM7jGNDHfodRmnPqUeCcLm77zT/4ZB9lp5zJ37JN3FZC7Ez0mHB/8EXdrHY1L0ReNX6P29uMmJJor4yWxERoagrqa9/iaFuG+tuulb2j9LhSqu5MEEO9XzWAw+luKW9e5W9Mgsu/s7FTu8hhlL8shGLNKnTU9uACBlNHdonNlzXrx9c1KNIXkDyz9zpRgU3Jwe9TfHyI4rYZrfhTCH2Bl+WYR1l0swNvXoDxt8LgcNDSwmKI4rUQJreDZI6UoqCzKORnSczw/n+RVqAyB4P962+OS8d1nKIfr/ncvSf/qWwSKUT59gkURRXAl5aIYnue7q/UMdPa+PVtQltEF5uOPzGFL0KLrBwc9SAxdrCu2n2yNk94vQwHdLr28GTkwji6hpLdgld2MImqBeO+fk05jhCjk3xuyfbM8zZVJVbX0D8dR+FHgOyl/9kV+ulCqqcMr66T3TlA35P8z+gIXUf3RDqzslFmD5R3adX1zF1ZYdlyz3M83WR5vYHFogvS1bQRDnkLxvs6hIkPamYcyjFxPUrd/spV2IvuD9G8TZf/nz6TvIGvi2XS1juUYeZlPdToys2SWjPC4NH3jjdexVFVrJmCRXlm2HN/LFL3xrW+r4vZtDYxOuZN3dmaWwl59VbfLy7kyCtAzr6x0C8TTtMlT+m/2fws0OvTRLwh6q8DXp1WD+EJ+/1tfV8Wlk2oYQQHYvYWoaFwh2EwDpgYVxdV8BNGARrdsJ3dTgu2z4QkCnFBwvsi68YU1ZMG0zTyEBX+Kayt7R2RgBIqnv0OEeP+zy/rnf/EdrcUyfPjkGf1/1Tc5pAxqw57XcVsI1MUTB3Tw5EW1DU7r7cBZfe+P3lCq2yy/sLRHPjR3g2EssJ8cOqmRKdACmhucn9iW595QQgA+jGW12vHCK0oHnsSstHkEqeRmJDul015UfPQjfXr4tFq7B/W3f/dD/dM/+1MWzXCfLZMWrHN8//uq7SRQB8tEKCewl3cWYlnv0i9+9oGe//rXlYIfcGbUGf3Vf/hLZ0myIL7VKwo4hPbqwHs/03GucgK5In7xpVd9tgJb3acmRnTis70qq2l1LhUDw/e0DSvw1HCPDh86oMwNL2k1fl8nDh5Q6Z1azTC2X3z9TQJMAnX8wEe6Xdfm8g2O+GlXVhoH+UB7rU/JLKAV108T8FfjoNbMarPnuddRv2Z05LNDCorN1tde2Ia7gEex94y1cDbhEE1wTXm1vF65a3coyfzE5pnMBWXRYg8ElqbH3HgLNUQKDh8Xjn2ioUV5xHwkq5BAtU9+9Q86h5I+gHXiNaLy47iWddCMoGZERRHESL75+CpaVfOK1qmmab/+9q//Sv5YJQs37cH/MAo0iqs6V9quf/FPv4mCul1HTp7Hl/SixjlgfvtPX1O0cnX25DH94K//k/MFX7r5GSUl3l94fJCBuZj0gzrxyeEz3CIsVjOuPzHRMUTkf0tBA9UqbRjU9u2b1H77og5fquAGBneLGX9t371LI+2Veuujo5QCwgTX+SnL14MKBESgrwcQU7RQ9gziy3Q468+oSFBBOLgNcKD+6a8O6U/+/Pv4luMOwFpg1u9IgkQN0mqQg9+BT/e7vc/QVBKzVqmIg+p8UhBrS4SVfRc/YzZWW7cMDrC/s0nHT5zRyu0vKaC3UhevlukuFu+Gmju460Tr+3/8PdXhz1t8vUwjHIhzN+zBFTDWHYp9Kx9LK+MtOsb8Ydm/+63dkQ5CcmZiUB+8874K1+/QxpW5IEcc1P6j59kL7Cq+X9/42ksqO3tAJXXdzNUx+QURuPfK61jefd/0pifHdJsxVHzjlhI7+lRx7ayycPfas3Wdrp3+TKEZG0E3imCOHyS2B1cjXML8l+SqAOv7vdE+Ff/yXf3l/1utnt4+vfat76OMowT4mrgujUDhNvcDv3tTrs8DkLs/ETdXzp9RXZ+//vy7r3CreEXv792vRqzs7f1j+qPv/Zl6yo/rChBUNg7swLPt2W88Am/2pCqYq4MzXpiv6v19KRy/fttTbhSfJqA4RJtW52vTxvX6cN8vVHomArfOSW3Z/YI7nJw7f1YFG3bhP5/hDCJPKu+r/t4P65TNI9/SBJpj7b9Hg/vxE5+3t7JOqBVlpw9l2BQc879fghzt+t38si0QypIFVPGos9BaFBWxOs5aaPBlrA0uWtk96OP/RlD++ofxAx6nHPaSpFjeTwH2edISFEIslKaMmvVyEYexVL7v6kPx5nlGFRYyjx+zW6B9LBNdxlmtzdXBLNBmSLKguzje38177W9DojAfWg7iPOBxQeB2hytAWw55hkOSPWeW7Pkkc2nglpVTl0fpT0WxBoaS6yFP+xraeBt/m0IYwf5kZfQPYKFFJqxlLgARA8FvnEx3s4C3FmRAM4VLKgEfKLOMBbP421WzybiL+loAn6FvGVybuZLhS+8WdNy4nBXvXswL6kv+S90LjHH+Rw5rkEaEs+gZxqApmaM4Wk+hAJivVTgdadafUXxrzZc7MgpfN6KwfxvX7L4Kpr+/3/neLWXRMyuQQY01c103y3XREhT3NauK1NFwR2NYwTLS03ABQTi0eoJrverGdlw5CN5JpvMsoUTU1NSCGoHrThFm8qdIBj/W3ljlrplTGPgGA1Z6p0mbN63V6ECf82Ns48pgEfIrLChkngWqA1/Byrpm5DpLnVO1Ylkhysr9ifqEOpibwcRQr87j5jCKo3kwynsAVt+cpasUem8E//NRJadnKxZl+8qVa8BF5aF4JDBOPRtR7e2bqmkEuYDBsYjAmk24tZiMvuya7/PVMb9qu16vxg3BXEIys7JdYE5YIBvFtXLlFhQwt0O4um9TNQgMs/iqFhQSGY8yNjU2pMrqaufnlpxOsBNXu7622+phwULmV1yNO4CNv4TkdHziUlGwJtVYV6vwpFx84UNVW1WFT3uf4pOSlU4wl1mwuvHtq8EdYJp5kphEvsxUF2hlBiBfkgXFdYMCUNfYrEEmmI21LCz8EfjvVXFC9senfvnS3AdWorbmeuowoGUripiIQ7pV3aTk5FSlEYjpa5lfWC8smrduV6AURrjDTV1lme6FJSiZAI1JbkAqabtZPBNSuIFITsIq5bG6c32gsvLbBA1y65GX9YWv/rIPzR2hgyCkqpo6F4RUuGyFYlnkDB2lsW0Af/PVWM661drczOGqT9EEyC2nzwO4zu/p6lRVdR31DVMhh2tTyg25wZdktwuj/V06DdyduVkYNnFIcIjyV6wBvaaTm4ZZ+jJJgXfHVF5ZoxE2nPikNAKq4rFOBzHWatRFfUKA6kpPS1NWBu5OKME+dvkjVexuqVMPViYrL2h2QldvVmrNutVYmT2WQVsHykuuKiY5i7UzSN1t+KTjpzqLgpqXm6+khASsp/NQyLyls+nZzVbx9VvaQHl242GWdivHf7xbt6sbnQ+yHWz8AkO0Ed//vvYWNbW0aVE0sQdp6YonCPRpobKG6OPW9g5FJWaCyBGgktLbimPNSk2Kww3kjmrqmx3+emxCsgry8/BX7WZ9aeV25q5S0hiD6ansQRYc55vUZ5jjdTWVKqtsQCm0QEM/V15GWrJ66IOgmDTFc7PTBzxbNWtoAPLNzGGNS4glVmBSzQ21au3qxbCThGtaBog4sc5Q5hWnr79tzDfX18gPBIhkXGjaW5rVT/+vW71MXS31qqiqcb71FgRpLoOz4/1qb2sFumwUn2FuY/LyGBvhv4Yp7VP57Et1dfXqH7urtSvynbvNyL0wXOlQrEACuXMHpCNu1GKJ70hnDY3FUl1Rcl2xoN8s4fBi48+XZP75ly5d0vr16x2uty95nvaZ35kS/LQVWsi3IAGTwHjEQyV4/rbx348M5yrB4VzDWoCOAYfbgdDjhxji/DMxcWOBwFfxvpnalEcDfbfPH4Ld4zuGwmB553s17229nW8NQmjWyuMHJ1gQWKY5HHiIO6b5zsow64ojdeD7Gf5thBGWvJ/77LOHQj9LOyY42RlpgyXbYCxQxcq25IgcuCI08hPzzzVSBm8yUHcDdLd6W7BXKNeFXhl5n3n8bw9I/gQuCHaLEEQAnr3ffH8nsIJ4/h2INQWrHM/4u+8DXRlWpl0bG6KE1WsuycXjy3z4rfmWmjytz80Sb3W3suxzIzMwS9807XZ+yJw+vX39a/k4FPi2LT8s267np7CumUJm/WaR6+4z6mPvsgOJN5mbxiztNEKNWepmgavml+x7P3vf9Pnf5nNLeRRocjdfQtduxrod9syfchqF3ZRFOxw9bOPDfKZMzjeZ/OzdYDPwbo9rjSl+VlYoPtdWH5O7BWC5MW1l86F7hucYbe7Q6uthy9UPOXsCLT3kLvaZC4SjbbMoCvyD/g5whgfb0M3VwZHm3G+f+Wd7yQusb+ZV9ucE5PoTi471obkc2Fg3OXgj8G1sG2KBtd2esZsDW5s8ssBQMA9r6OeKRgasKffLs3lmY9/kYPPd5oK71XLC4YYKa7HJ3J4x6+LTKr/eOli/O8so5RnRjiO6sb8ZbzaXvWuJkbdYIK7NP1sb6ByC9vmM+T+fZO0zWdva5U2GAmTl2Rru8T83319bB5hjlGPjz2RufWCH1QnGgq2HNj+ets9NptZ2g7iyNll/etacEE+778vdOx7dukN97DnP2sCh5OHk8zbFx9+2L+F7T/8aIomNYxvrtp9RFc8cZw23wPAgZGPmPVtrLfjXnvG12AUl2MfuWHjsv10J/GNXgs2tYSEtSGBBAgsSWJDAggQWJDA/CXyVSrDnHnJ+9Vt4ekECCxJYkMCCBBYksCCBBQksSGBBAv+oJbCgBP+j7r6Fyi9IYEECCxJYkMCCBBYksCCBBQk8jQTm5xTzNCUs5FmQwG8oAY+vqAdCyHxKQ4j4M/+vh36n5j8KQQO+WObTivsd0dPm94qPnK9OSL9hHb8su/mKGbGH+QSGhX5B8Am+YhP4cpqPmPkMenxTJ/HZm3Z+c+YvaN89TbJ3WQChgfPbu+f61xrY+hT+XF4ZOj81fAPN782iiM2ZMRQZmn/svGRoZfJu5xNHxmD838w/9YuCT8w/0Pw0nU8mPntWJ1/yfZkszAfW+t/KtzFgfmhf6m9JPY2m1+sXbBBn1g/mL2j+gx7f0vkPHuf7R5/bu+wdJndvMr9Mo66dSw5g49Z850zGzmfwvn/l3Hze/F/+23y/rd30J/1nPpDmT/2IzyHtvWv1ArLIxqI3kMvK9fqk88hT+59b3cxH1lHzMu8sMNSb5vaLeYabT7r5ZHrr53y0kYvN17n5vPkf99tQGqxMGzc2ZsOQp/lozu05k6uRcZjfvflEegkUzJ/RjXXKNX9Vrw/t48qb+521y/wdHe4r7wjG/9OxiM15yJ4xmc/gJ2n9Ys8YLrUlm2vml2/1WmRYk/NI5hdqftDmY2r+88HI2wWgzZms7v33nzEfXI9/qvlteuYIC4yTt42FufJ6cjXw4WasmcxdUKCb4+Zv/PAt1i/j99ttc8qP7xYDj2j0zeYrbkRGQWD3ml/w3HxPKtvml2esm581/vvU3cgYvGPJ8jufZ9Y9k6s9P9cn2PrrwfhnPX5Y4yeVPPf7+/69jDtbH78oZsPrPwycs/M9tjlm8rD6WHLrIvU2f11fk7XbxquNJT/GuEEBevzAvW+Y2y8WJM9Yp41ujtBftu44pIfPrw3e7D78frifwcbJnPmi5I2tsLrZWDeZu/HPWmjj9DePPfiiUp/+s4cr9NO/40tzWn+DDCViJdwibzqABQd6+50xCpajBzEBeTGJGTD8NmYz5jgbCMoMaykoQvNKzHGH1GDoBzbEjIKZwHdXB3sRkJYOncAmA2MJnFIPqoHV05L3s/nGC1idgaaE19tTb4iyHiTmgMb4bhS/fHuvycIg2Oxz+8zqYkgVFpw8H1QKK4Dx7cq0qHSTLWy0rg3WdquTMcJZ2/jTydjqZc9ZvnF+DBHDcFV/02T9zfx0CBBuoUHmhvVssvcmb12t79kHgfXxtNfqNwCKiKErfT6AtKYEjnpQDe6Brxsek6St63J14eIVcJ7HPItK0CK9/PJLGu9p0Y2SW2Ayh2r9lm0gLcS5Bchb9lf+G4EYTuvFc2d0NyJdr+5e/7AKfGdBFiODvTp9+gIYwbuVBoyJKfzlN4t1vQxK05hEbdm2xdEnz13kH77ky/9yigVKXvHpwxpblKE9gMkvNmHfTy1VN3Xs/DUwiwmoYeNMyCjQ1rVLAWIvJ7q4HgihUG3auQfs7CRHo+vN9/jftkFNqPT6ZVWAdQgtgQrBBN1E1LJng36Y2+o3AL3zxYsXlJC3VmsLUgHAh7IYCmN42yBu2KCNq5aSDwX6YbbH/mVKZi3Y0ddulEPJPq38lWu1fvUKECYeVTCs7HEwbI8d/ESx2au1jihnIy25Tr5RBuLSVetdpLWxys0veQKQOhqrdeziTb300itEqhM1fT8NdrXo6KlzDi7Po0BNaO3ur2lzUQ4QWiB5NFTpeHGpXn7lFZjd5gHXxWTrbmtUcfE12BsHFZeUoW07tykBeBZv0NMMG2hLQyVQkNdYb+6pEGin9etWMNcgVmGMlkOekpBdpPz0++gk3kr7+Ns2x4GeTp08dVpJeWu0fd2yBzltU2yoKtelqyUaY56vWr9JK6BuNvlaX/R3d+gE+VIL1mkbY3A+aXQI6L3LV0EEaVbwokgwsp+BlTKOdceCciyBHwuKw6Xi82pqH1BW/lJt3byBhWoKxrZSkA3KofGO065n90AfHO3Gm8v2pP/Z/AUy68qF81D/NskveJFWbtysNaBweFEeTPmeHB/SeeZ/HQD0MfHp2rZlM6yW9C35jQ3yJqQNbROL9O1Xdj3Yn55UtH1vaCQVZTdVUlapKaCXVm3aqiJkGg7snScZWQX9CipEyZ0GZBOlXTt3ActoTHW3QFKo0pRfsLbs2OaQCsJso/UxGTJGTUWpbgAVNsqmk1lYpB0b1zjcW3eoQvEfh/Dno08Pgfw06pTEIPrm9dff0NRgG3P+knoGx8AoX6ad24n+Z+PzdX0zha4FjO3Ll2+CKDSu1JxC0G7WQxMM3vL9A8AEuLmH938EOxobPZ8tjogBmu5ZBYy1Q9BTArIB8GzLl2vjurXs/RY46esKYwLyKOHdoNAchmBo/bZnVVSQ+YjkPHN7HEi+C7rTNa2Xn9muYaDrDhw5STCqp38yC1bpmR2bwBWfszk+8pZf/8dwf6cuse81tnUqHJbBbbt2wTQbBVSZ5x2meBvCzs3SCiAq6ZeC5dq+ZSO46O26yhxpbOtWTFKKdpMvFnnNWxllzNpacfH8WU0tToUAhXk0N/G9zed2sJQv3KjQhq07lBIVpPNnzkBM1gnGM3v31i3sy4anPTfj7/fvgH9H8rkKM+Bw9Z8GAwwQ2Cck5AEGIpixRyBquCpduM3EZV1ypAyeYGEHWfbOMXB7b0jlLSiBQGiBpKT/ekC6yPPXGoHzYr1InmeMUUen9Kvj0v5r4NKW8Q5gtxxVL4JnfoLdKu0tls7cAi+4XVqTA+vZGenHJ2CMqwHntxXs4Nz7ivMT2un92trLQU9HLlD/gyibtKUwyfstsuAw8PFJ6Uf8wHapAZRPqNNVdkf6BSI19rx+FMjsRA902sOcT/4LlB/9gvcevSmd532FWSjCzDVTdE3hP3gWbGZkfAZZ1AGNtjLTc9iwfP/xY7CZ6dYdeU8u50lPmMLNXqT/sh86asoqpU9BBFI8srBkMmLt1du01/q3g77OTPAcckCs0v/xIxRzns0lT8DiXBAiXgTZIFifvvcLVdS1OtgugxtLTYhQJbjBbcC+NNRUqRG6weW5ydCS7lNVQwuMPi263dCtlSuWOusrYvhKkll8zAqxZMkSZwWcmR7Xwb3vgLt7QYN3Q5wi6q2IKQ09rXX64d/8tY5frtDyopVKiY9Uc9UN/d1PP4RwIQWlpVpXS2u0dgNUti6i3Zv7yb8NLuwapAhvvf2eJoPjtRSmHg8kmyfv9fPHdOH6baWmZzmaz6SUNM2M9auyohJYulANtNbqAjzfWbl5QIj5NgHNyjE1NqhTYLLOcLK6OzkKG9ZhlINtwOV5IIW8NZ+ATerjD9/R+StQBYdRv/Rodxi4S8TzNADjnx06CuHH1nlBpA0PDcBadFHDYFjeBfLs5s0ShSZkKtuUjgcJyzub5KnDn2rfwaMKigCWLiUBJqVLGgFf+h75bpAvLCELDNO5+R684Ev/sE2oG7rUd999R2fAh165ahVK8EOlcghYuhHDEMRyZxag0qvnFZdZ5GDxBrsayPce+W5rzZrVSoYO19dkCCAVJZfV0jsMG+C0asEKbR0PcVTYzjJJvxht6Y//5m9YZIFrQoEquVasoLgMhWtYv/jp3+sUlMrxaXnKN17zeSa36SO3j9/7pY6eu6KgyARtWFnw4C1jwOaV3riuduOzB67p1NlixSVncriLAzptUHvJd4x8huu8rij/QT5f/mipq1D5HRZt2Nk6asp1tbLNwWEZ9JUpLLMou+/+5G8gQBpwZCnF0IT7R2VoqLkEJea8U5y7myp1/U6HcvOyGae+WQPMojmGTI+DqR2ERWwARf7oyXPatH0nB3tP5P8kkGHXYGP8hI3GKHybayt1ubxJW7esh9Ri0tFGf3L4FEypk3plz6Z5KWN9lHf10mVN+odoerBHV1BIY9OylWYsUJbo86tQ3X508IyWAJ3WWV+hW/XdYPqGwRZZpml/CES66nXjdoPScvIdpron45P/Pz05wqHisvpHgEH0n9VnsOBlr1gHLnGUG9e2tg131utXew8rGHzgFGAQjaTG1rcP3nmXcToCHGi4Th/9TGHJBazn0Cn7aPmxm61S2Ch7xrDywopXUXpNY8GxKsiEotcsaaTerg59+PZbCo3PUAz403Gsx+FgJDfcuQlZla1R/RzUryl0SaYygFOblyWaOW7K6Afv/EInL95Qcmaelhog/px0F6iw6rIr+sXbv1Rt16RWcTDqAqpy76FzrPPLnNU/KTlFS+LYJwzH1MdUd+eGg9I0DbKZtlRAY7yMMWskQDbW73I4OX/8iMYhAJpi7J0/dUwxWSs12lmtOnBL7zFmK1HM2yfDOPik+QwH6KrHeLL97PC+9/TZifPqhxXymS1rHqm5M2zApvcPf/9jlVS3KDktU9HBUzqBsSUcvNvailu6UdmiLRxajKr9cfuy7aOtra1KAWZtLrLNIwX+lv4R+Ft6z6+9xqyx11CEhumfP36edR/r6H9FMd3FGmeWPlPOgIZUB4rfn76MJRJMYNYrFaMMAi2p1zEIXKvkp15al/Jrr//SD0zJvYwi2MvY+t++AVUxdShmjTTl0pRpKNX1CcrxN55BCQ2FNvkYZA0owv18vnmV9CL9yhqmcOr4uE76fAWsXFP6F7MG0b9Yoh59gnUBhQzCjB3Snlz2IoxMrB9aTTuBDFRDA/WivRtRRo1e0tdkaDwfnJNy2HO+yXuOo4SfQNH85mpkynvMynwEGfzr74DV28UBAJn3jIKDTBv3XmTqsG7MgzDosdUyKuwDlG/wo9upy6fU62Q5THnI3mTJIVIXqNt65LwxEwswdTB4ys4ez6HF8JytvmbRDraSEOo9FKmO/hGYqZYoL79Qq1evQWlZou+k5sAYV+pRsna9ruB74+QL1HpOn+kRd/WT947CQvh1h4c4XxasxzbShy9NGZyArOHskY814LdESwtyNfp5lwYW7PCYBL3+xptqe+sDW9dQzsBSLStV6vLNev6lPRpoq9GRY8fV0NKjopxE5OVZ5J9UhUmUyOrya7pQ2qZnd25SN2xDv56g+I1P0uZt26HdjABwntMH8s5kQxwbGVFNaZhO3e6e1xwwi0rwohh94zvfZkyNqrUFzN66BnCAH84kU5hmpsZ08KN3FRiRqDXL/SCO4Dp3cYy++d3vModG1QK7Sk1j87zZy8IhH3nmlTfc9XMnuJ1nzl92B8G5bR8Fk/nGuWMAvAdqbSFKIBtIRFSMnn3V8k2Ck1yrMxeuuDk8N9+T/rZ2tTfV6NO9+1S4dptq2g45hWBuviXJGdoOdegUm3dPW52ugK+6Jj/ZKSOHP/1My9aRr/3X8819xxf9bVf8RRt3KW/VBAfAdl33G9GQEzkLjEtskFjJe1BCn9+0WeEBMyq5eNphOS+KTNKLL78ivxOn2Ubnn2ysj3D4OMrm6B+Xq4zUgQe4z963hYXHQJLymjZyfTwz0qP/+sOfqK+vT8OD/Try8XsKWpIPpmjfr+Xz5n/c79ScFfp6SjbvGlBFxD1dannYCjuUjA51qKIB9sKvfUNrCtOUnxiq8yhOgV21WpJF3tde0Oxwp/7zj3+pzq5upxQ9rrwH33FYWxSVqO/9yR+7MVt5uwTmtEuPjDezgPf29Cglq1A7mIeNlSU6V9Lg3AhKio+qqW9Ga6GVvdXK5jPPFLMkWa9+44/cWG+pu62Tl8rtQu9hQuEZHBpRWHQiZCHPqLcuRsWVPexPCRANfReL3aw6YFz75Pgl9cIeqUwWaR9TYMhiPffyq2DRj8IG2KPKO+WOOMEUsbm7ZhjsbMu5jdmyusAR+Giiz2HTFxSt1UboYkdRwu8yfu7ataGPKQTms817XtFqbsx62ptVfA6+Mls8545e/h0ABvjy1eu0LMswt8OdIpWR/ApnAz8IRVqhuj6m1o5u/o1C8qjkvrQmNsf7utt14KP3lZC7VgmNXdxcP1zbLONdlJiq8pv6+OB5Pffcczp0vc29z9wQImKxhG7bxsE+3GHfhviISe2tUPayDUqGhnsAmZeFTKp6IpCvvLKjzRwEn3/jO4yJcbVije2DytwU/JzlG1RQtIlDW78qlgTpLHTH5jrlSAO8L3/cb9vPIBg5f3Sf+u7FaNnSfA0y/ucms9APcuPy9i/e05ptezTDrZrBI8YmZ+vP/vzP6aNZXT59RCeuVnFbDkwihx7XbXNf8nv6+5F589usg11313d6qHITUW6wvnNFgpKDgsNXzjJ6sxZllc/2oTgdK8U6igIEu6vaGvjsPKQKrA2r5qEAW/3pC/Wh5BnJFQdPZwEextJpSq4ljDBO2e4Zpg6mcPFj7GU2lG5Tn73U5RK/jUqZvvc52XvhcdBqlD+7/v/8vLYOx50HxUT6COWzCtkYPicHHnFo0kUU9+w0xiWKsq/J6sda4Mg44igbTHqYhwQgN4othw5LpnutSkXZPy0dugmdcTLKOJ+d4e90ZJ3J8w/mkcvx9P+DC0GtAyjklBGP/E0JZ69zVNj2VlOSO/i+BEX8IxTkaw30Of1QVo/s6OcCjF+2pnjF7lEmR5yLySTMSo0wD32K9W5sBlxPTtBdnR0KicvWhlWFWgIg+pLoEJVdKdaJs5chDRjhoOXxG3v6Fj1dTlNCy6+eVQmsUcbRbgvlDJ1vnPfWJkumMBrrUxKkAeYXZ+PDfPsWcTXYjSVjjIVsDFD0CfIMQe/qzffEGnHaul1yRaeKy7Rq9QqnWBgmqPmSeeVq77DTtW0GH3/4vt559wM1dMBwxMZhlN3GAnToVDFEGStgA5zHgERlNqxMa0NN+Q0dgF40KXMZJDEPfQ4nOCmehmq2A0rRjNQkcnj8lu+yORmNaFXZNSxLh1EcHs33xHbzgCmDxpbX0VChT2HFuhccoxRoQr1phhOwAbdfru7B3WG5O1RMohwanqgxa7XVlbt8Co1T8px83vyP+z3U26EzZ88rIm0p1/EMfk6nttGYP7g3BYINvAj8aMyTzvVjOSxKRqZw/nyxItMLlQbV8Bfl8+b/st82lhaxsU4OdevYoYMqR6lakZ+DEu7dqNggQ8K5tk3TIeRy8OARdU4tVn5mskLCoBXGDSDcRwvo5+swjkX/OjcOzVAHr8hNZfyYS8gUvqr3FyAyWL8swh80Al+n3s5W+YctgbAnxN1UtI2jrORixWPc2Ridm+/zZX3Rv833Hw1f508ewZWkXOuwvofPcfsJhLAgAAtMT0+3UxjtoDPYP4S/pB+/eyEVGHUHtuGhMeYnPptfVMgXfGYyN8VmMWP7evEZnTxTrMLlayCcMQxiT4ZArr6XrVqrvoZSKNA/wS2hSatQepvKL+nMtTpIC7Jx9fN3a8MYm5Eppr4mry+sWf0/3X9IsQkQT3ipO+0lrCUZ2TkKmejQxx/t06kL15W7dCnrMsx8UCobe1xXW5PCo+Nh2GPczSNZXEYYh8dubov2fvCBgqLTFRse6tY072tsHTA67HPHD+m99z/QxRtscLitLctL1Y2zx3Xw0GF10vcFMFX5agW2dxvW7CKsyiMwUx46cIDbxEDlprGOeIVuz1B2MH6VFyj7nXfe0dni624/N1Ila/fYcB+uEpMw0qa4Nddb5yf9Hh3oRek+rcmwJCzPlIlSbBjJc3GDm6vLdIHbrdUQ/UTBejVta6/5q1O/iYE2ffjee3r3g49V29Tu81jz1svWqJmJYSzoh1Rc3qrVy5exD2Ktu59s/4jAwt5KHQ5xk2Y3HpkoX4tZG6zdfszNqvo2jDIFD/zivXkf93sSg85t2PFuQE9exH4WzH5m/vRz97O+LpgIP/5Qi1NyIUELZRmbdvMZLmlFR0exB86qF1etdNxXwlCQ7k+RxxX7lX2H6va7SbbXm7+pubyYu5H52Zrl0zvPMQpoYAyLJAryujypuZlr+zKUUlsH+JnhpxsF2ZjF5pM4/Dsl25Q/x5iGpdHqYr6qJnj2eX1jM24B9bhLXEU5Rom0W5RVy7GebkOBoz7cWqiim7qYtu5jsjlo4xGWVwbmr2cyZjazNL+xHkUU5fCnh1C+UQoZl85v2nzlurGImlzmk6y9vMLJ1yzY5u9r+64dQuwLa7PJ3uRojHLcmDpl9CiyTqGuzoeXfhjgkODtm/mUP/dZ3A7dYsPNN4uQx9fX6uAVo1nKTabZGdCdJiB/5AyTrkro+yR0FVsrjOnPrOjWZ1xm8l+Aitas1Y4dO1W0LJcrrXIsWmOOP70RP6P03AIOPCxu0XFat2GjCnOzlJPN5sJEMzKCx1+6zK39b+/vGRSrFgZ0S3Ojjh4+qLKKajVVwobW0oWMrbcseShAw9mQzDfL+ikomGuqVZsV7TekfR99oM+OndHQ+DSy/IIB5d7xBf9jYe5sa4chq0GXi8/pHD5wTVyjlePn+6BosqXmLteb3/y2dm3brOmhNh3jWncIViuPBWWDNqwpUnnpTQ0ateI8klMOmAxZecu59tqIy0etuuFA97bbfFOb6uvU1lyjY0eP6mZ5jW5cPKe2PhR9yskuWAHL1wZ18f3cfL5UwWRoATjxKVnaif/j1BCMUnbavZ9sYe7pbFN9bZXOnz6uS7fqODDcUBWWdgvKSuQ62fJNDHQ8ks+b/3G/J7Ewt7e36yZuBocPH3VWxfP46A5bgMCcZJaizrZmlTcNajc+gYEwynXCNHfz6iUdPnJMnZ1dOnvxKnP10XxzXvGFf5rcQ8NjtZV5khoToDtVdShVnplnFqx70J32sOBu37ldOekpGultUQfUmd5AmaclLpjGtaIRq30dbklHDh1SbWOrKm/d4LCLr9P9ZHWbwdrQC6vd2QtXtWXXHiXFLFIT+WqrK3Xk8CHVN7XpTtkN2CRZJOaR7N2BzJv1W3Zw7Zytm7hdjN6XnQsY42biGbPCcn38Du4mxfhj2fOrNu1QRMC4PsR15dPDp/AFJ1ALZX0+yY11FOFl+L0bDXntnTKYu+yg63mLyb+1sR62rEKtX7lcoX5TKiu7rcaGRvq5Q6dOHFXx1ZvqqMNHt7LBBS76Wr6VbT8Zecu0HetiJ0yP3Ua7eT+ZFbyfq7/Z8BRtXr/aHUTN1Wmcw4kdyBurUNawQq1avQpqcqwn80pWtj/Mf1mUvV13R7rUzgbiVeLtu9DIJXrt62/q66++6NzXTGHt7htQcxu3Wus3qzCDG5GRPtW19jkXsvkUb5bfxVi4tzFXw+nDumbY77zLKi+yg+YLX/uWXnnxeeWkxuD6c0mN0BzbgbuHQ9jla6VKzF2F22DKvFwhjFWypaVVFeW40hw+rI6eft28ft35GHvr34v1tZVnis+f09HTxY5KurSqUfGp2frjP/4T5LUZj6Am/ONvsM+xYc4jWX8Hh0Vo07ad+O7H6datcheUOfcVJvvEzHznez410IIvLmOAsWC3LhWl1zURmkxMjbkJopD4mGzuGuNiS0sz+9khjFiVspiSaizK3j4fhYK7qbVDVezPBw8dcWykV2B8G0EJnMIoVEGcy8B0qHZu3YCR0MaPj4V/BY8F/q7KsEZGoQy1oegRv+Qsv7ghKZjBasFjpuSar+gUh9D8VJTSRnxlUYYCsBTiEqcNWAbNf/TgTfxV81FUfayoKbSmDDZQrilTvViBMXaIg7/7twWkbSjC7zQbJbRD+hBFOyuOzZcfDvHQifI8e0cz+c0yae/yNZkSaePaFEv7MWXU6j3J33aTnYriZxZqxqP2XhW+UVhi86hPIb9Rvn94TKrppFye8zWZT3wwbfMqj1CWQ0+I4kmZZukeRge4STv/x9f4m7aaBfhWC99Tn+vItxKZD1Jvs4Yvx4L7wHjkawXmPGfKP4ygcJZLafS1WeTR8czwBYc7CgrzDhZFZSXxg+XarNN17XzPdzWtHn/iGfJ0cSChO0icOLGIDgwNY0SI0DTX9EHBoSiFWIEbGgg0nFURG7qzImF5a2bx8bOrf6hgY+JToek21i6E8xWnQOq4auMORaXko3xMsSCeUZ9frLOqThPNfY/N1jjr/VicLFLbfKlc5C6WoyUpmfrWN3CR6OpRK4FMlY19SoiLZrG2keRDYuItW71Bi7l2t5N6VdCk6sfxy8NX0Mow/1GLwE9moUxMN1anSY13Vqm4uVf9g0OKTIpRUmqGNuCcf7XsgDqhdl2axcDwJbETWVssyDEuMVmFXMucw0etC3N/ip0O6Te7Ituy5yXlsWGPsXCWXrsMzW2WwhnEUywK8VD+FnAaOn/yGJv6iNKptx1mfUnmR2bMYDHxlM2Ju76+zgVM7eaUbWgbxpO+dM1mBUNvammmt4FFKE3RofghU2ZMQoqWIua6ujpH37x7HQuPjymETf/Z51/C2jGAb/WgSsrvKB8/bPPRnZ6iAUwsc2cZQ1kuKylRQs5y56uMYUfPvvAiB9NBTY8OkK9ShVgI/R4cHZ9cAbslsIDKxZExysrJ0eRwO65OBCZObXFWNgtkGh7oYr2Z0HdzshXEBPS7O6zS29UE5WU7JcSit01+hhbiIs59nDZBoeEotc8rrYCFE0W7u7NdcamZzlfU0D4sit0meA/Kwf5PDigEH1CzGIdzSLV86QU9Ll8n/v2JaViZoJGeTzKrs803o8Hdsmmlrr91ElkOKJVrMWuTWYrXb9ujuJQctXPYqL19XUEZWSpcsVI5UEvXNzYRnArFcs+UIrk297HZKF2GEEC0PutsCr6PE/g2X7pwCfr6cW7AsERyALeg2KqqKmWvf1NLl6exTk3pnY+OKO6lf6avL0nHgA3N7K0SvLKHlcSiPVeRe5IM7DBpCoi52BT53cUvulaNre1avyzdWSaNFrq1nQCqJSlat36Nliya0XuHLhGg16LAUT/t/eSQVm97Rtmsn75S2XrrZO2eBvbADA/LVq5U8alD6kTBHZuAdts2TNaqoEXRUN6uoY4z6myP46BzVh0c/gan/HHtytey9BhufG+7QNjVy7K02EelzA4WNtYjY+Jxj2N/xwe1pBa3il2Uxfi16/8wLJ8r126QIXEsiQyESv2U2qErzkLX+ISbr0WMQbsJisJi5GtAnrU9CF/Hnc+8oHzWRE2P6U7FbaVnZjKXbI6z2bK2JRFc+jI3SUPcRPa3VKmyswY68niCVaFUTkrlBi5QQ62VqmVtG2N9tlsyX5PNp9CwcKVlZunuRLd++kmJRkZGXbyFjQV7t910mJtbHrcj9Yz1+mYsv2mRusFtTXXHmLbt2EEQ4SJnIPK13ACCpFdu2K6I5DzdwwJ8GaNF590o9vIw1phJAAyCcO1L1Cuvfg09ZExjA93q5gCQm5fD85Mc/C7o2OVq7dmzR1lpKW7umEL/h5J+Z0qwbVzrUO5+fBplB6WIUHECNVBE+futo9KWIpTdpdLfnESJQ/GpQwlbnYW/MH9XtaEssRaaAp2GQjgfcQUwpnITcWk4K71/DktjJZvMDiydrNH/7lPp3/4x1/C38E+lPs18loACvhxll7gQDTGOOymTIa4VKGrzUYBNkcOl0wWfNbGuhzRg4UR3iKGcn6F4fgfrM/MQx3zKRSmF4lwRSH//BQ4F5CVmhiAd9mR+fE02jlj/tTELRfe2p42l9dJ/9y3KpsxmZPnSOrfH6FYj85Z/30M+uElpawGKOQXtP487BnWyYDRf9awvq19MlLQbBXbfKamRtrdS3q48rOql0uEW6dvUJQIlYy9jwizui+MYB6uwApPP3CKO055h+iKFxcpUPpsoi1loYxf56RrR3RZtuPXZF5QYxbUqZuVwfDntes8GiF09Lgq8R8RyifxDIvUyEzKKK6Dfgw7srpjj4hO5+kHIoCWYn2bNYBA871GqvHlRnRNYrtYsV9C9CZXdKtPAwKBqa6pZLBOVFBem3t5+gspG1MJgzF+5ng093C3uXyb3Rz5nIU7PzmOhRBliswgc5WAwGkcQRox68UM9SUTiG288qytnThKoNM2BKRxrcalyt71JYFEZ86Zbqbgp1N+6rODoJYoz+fqYTAHuba7WgXMliueKdQS0ju4JfyVx8ultq1VVbSuL6RYtLVrnFsKxgU7NjPar9V6C7vY16f2Dt5WI0jvIxtY7GaBE8gXM8Sd+UjUGert18LMDIF1ka6i9VvVtvdq6PF7jw73a/9lJbdi2Q5nZ+ciGhYjUU3NVM3EEiATc0wfvvq1E8g2212A16teO1Sw880iRRGsXIS+D6ZvCLcHcSdJTEhVwd1QnDx9TUuEmLSUwoRJ/1Pq2Ab30rVe4OQKiKi5RK9nQLd8EiurBU5eUhvyj5+GeYArRif0fajosRv6cIkuvXVPm0l1QIuMmwGYUsBi/9ExOxqPdBK4VKzZoSpV1HconsMUCaKoqq9SGwjQSyI0FAabpbNq+Ro6HhUcpb2kRMQksYlMjunP7tsISE931+I2LJzQemsZ6HOqi9etY455ZGo4ltF7JKWnKAVUgt5CFnnzlBGtFJibN2yp569IpApn73XirvH5O0Rwiw1Es6ipvqbS2W2+89iw+7ihoY2MouxwsB2b0p98BySDUD6VxAKWfTbr0FpH2rxO8xqLkY7qLMtBRW6bDV1FyODg211QQgBoJIgfuOPja1hP1m81Cm0CA4wVcNQLHV+ETXKE4fNDyC5dx6CN4jluAgFmssuONykyJZ6zbqudbam+q1bFTF5SZm6PO2lJcCe9pA3NnqIdr6WPFeuH5XS7g9RxBqifTYtVTfU1B+OhO9rXpZ58c170YEElwV2huanD00pkEh/qU0NRHcP05ivtHANfzgVNDqm4f0nOxkRrubWcfvaWsoo0KGG3W1dut+OOGqZs1ITg2jVvfaAVMDhIAe1JjRbm4HzZr09efdwcGn8rmoQkizA98+CuFJ2WANNGpsvIq5W18kWV2RCeOn1ZG4QqlJy7iJu0QqBUFaii/qv5JP9CPArTv7b8nMJxDUYY/ynObs6IuI6jNVwNDeFQsa1e0ClC2OWnq9NnzuBcmOcPPxZMEASYt08qCDCWlZ+EGMaaOO8G60jwDEsMiDl+XVY47QTaW6dMXS1S04+V5Hz4uH8eNDD/giLBAlXPjlJSxEgMBAbag8bQN3NPzW5fpnff3oluka5R+Lm/s1mu7UlR2/jOdu9Go/OUrnPW9ompGy/JznfuZL3IPoZ8zcpcqLduznw30dupujx+GFfazkmJ1jIZo3doirVq3ya3rg6y91U1dzMk4DTaV6Udvfaxdz78AIs+gamoqlc3tbRTuM/M5gPhSz6d9JuB3hQ5hCho6iFhTufrCupmJOwAyNFc7MyyZ+1syCk8uc898hs0auiqD5/hJ5juzGHJA1Dp+IjHu+ZqsXAIRVUR59g58bjun3gAAOxZJREFU8rEWooxS7lLebe56ZrG0PSYXg9AWyo3leTuIWpAl6792oaCbb60pwfY+nxJruVmCzZ1jRTaKNWWaj24i77H2xlE+iEXONQRXPO1egbJHu1P5Hvc4FlJpD+Waj+4XuVN8WR2sfvG8J5f86B3ajBKazyGAoFhnYbfPimi3yd3qsoGDRzZtNJlaew2JaQVySOS5eazBX1gds0rH8b4s+tX6dMsy6kVdYpG5HWYMocOswOmm6PK5yZn1mU3LUxdbh01uccjJf1GuJkCH8ONkYFGmK7A4rF27VssJMgvH59SsXrl5uYrF38gi4M0PLD45VUUrV2ntuvW4RWTir2c4ir524Bc2aV4fetEh4uPjHcauLa420SewTkYCc5KLD1ovfriTs6EsEDGaAT7p8tXrWkQEtdU/ImYJNwURulNaot7RGa3bvE0bnMXC/Ll8r4odHrzWPAvOWcwpPZXOv4f1orm9DwtlrrsO62cxa0fRLli9RTs2rUbhjcY6PYF1rFmhbFovPLvbwbPN56o8AL+fe2yuLc0tukvfPfcCVl/aPYmVc2B4nEj1FOIDQIpANn5sqOYXH44SmJOZitI2wZVbi+6FePLlcmVqPm++tt2u/W3ONtTXa0wh2rJ9t1bkmQ/brOoaWrDYpSsmOpJxTr/wY0F4cYnpSk6kv7gqqiffuEJxKdil5XmZbFJMEB+TV+auXeQxd4aCAnzvuPoz3/XwuBTWoBCnbCYRKLWiEH9NJszn841isS4kXxS+fb4nw0sNxOLWys3XhJau3aqdm9cClRiMi0aHArDWZhF9m5OZ4SLbR6dZV7fu1NrlBfLnZFx2+w7rFu45+GYtRpFPZkHxFTPX6v+gDfw9NjmlBOahQbx1YflTSDTrcLCzWNn8MJn3EhwQujhSqSgQ5rJkU3QceSWlpLqDg+/tNuNbkMaxwja2tCsmNV8vPbuLdS4Kg8QgMFwTKsjL0nBft6qq6+UPFNpzzz6HO4hZwoFtq61VW88IluJd2sg8iyZwxYsw4EsdAsE7nsTq39LSBuhGsp5/7lmU2QSNECA0Mj7r2pOVk4eSNOvcXJKy8vX8np1Ovob9bbdUM0QBB3NVuYxbA5Oj7wk8a/8Z1dbW6S6H/l279jDPkplTWAC54szBCpdCP6QRnNHc0qgwxt+zu3diGQ3TGIqkwTOOjQxzyzaiUNaftEQWZV+S1ZGfWa73WpubNDzlp93Pv4yBi02Ged/b26doblTMODGKu0NzayfGjnS98tKzykijPqmpjLkRdRGMt3LTLm3GGGCIHL7K/Z7NcSZ5S1OjBicxpOHWsgEoxUUh/mpsQumOjUfZxqrOuK5nzodEJRMYuIv2xTH2e53CPzY6QtDgMHa5IOWx7tic9SV5xrpn7bAso1z1Z2bnOLixLuZecEQ8+2kUe7ytWcwL6no3cJHycjKcP3xXR6vaOvu0avMebVq7EuSKiHkpggavNsBYbuvqU2r+Kj23c6tiOXRZcOLYtJ9y2fMCWevMbWFiNhhYuBe0GsvjOIc/g4y0g+DQ4CAQptPKTOfw7+P65mm3Z0+x/cx8oCOiY53s+nAvm5gNUSKHPVsvnSxp9wwmtmQOtYu5+u/C6n2XG5tBglfHwMRNTEknJu/xVvivEh2CfWgelzATLGq1/557/B/7MmbcM4YCYS4CuKoI5Z+rMRRFDlL2b3zXmZD8+x4KJ0qow4fle/NdNZ9W1nWHp2vPzSdxYyK7/TR3APZQh0VrrTT3BOt3q5Nd2dpNnSE2uHrcr6eVY88YNrHNd1+Tvd8OiNyGcQXkaZ/5Qy+ifK87hH3P+HOLvsUbmdJpdbJ6sgc5pATLM1+9zb0Xi7NDVbjfXq9vscmQm14PHjBlhJiyz4+3afacKSJzYkl8bfIXPmd1MTdSbsuckm1KiR0O7NrQ+hejFZOIMsmNLuRkb3I2mZksbFywP2gy8gX1Jf8lrgMsaLzAQzCA/59THEzWkGLwXlMevYquWSLtWsg+D7KGf8Wpv78f6+uklhKAEhHBqcMSC8IwV1YG3B4VSUAHvjCzBOsYwLu4RuvqMj9h28yDgZEJdwpiD59xsUcASLiD9gmygfoUyXzBxsAitfKCkJtdY/YPDis+Pg5LxTiuMsP0BUFhBC1Fc2qya/NRNkaD8QoEAD86KtotlF75PrEKCN7KGGCxG2WS+WOVjoiM4tAShqIy7GQQFLIICwQDkGSuIkYqMcFgieRgM8gCPWb58LP05vO5bN5n5AEWTGhR8UYQYv7WBo3kR6R8DxG4BtOzeBGn3/tpoL/P3SAYWcDEOIgKbIx+XCWF03cWSOLrxux9n+e3yQCLOO4NVjb0I7iCjck/eDHzO9BF1Nv4jIqK+tz64s034Or9ZUD0j5Z1v0TGmG3sVv8ZJrNZbmLtQMMoGhocsUnixt4kCujA0JCb7xaoFsl4tCv5Pm4i7BrVBbARdBSNAu6rJfiR+lAPUy7ML3ExfT482Ofaba4dU0SXD5lfnCW+j6T90fw4dyXyDTAuzUUo0jtvPE8+8f8WaGnj2IJgTUmIRQEKJtjMiFBGWYji2ZxHcUsYRQGY9Qug3Gg2a0/A0pDlY6Pw9vd82uzcIVAk+5jzRlhhZUdGRGL4CXNzHGoMBTHHg7HUDfDMOOM8GGSDCGT+4HBl/cYGOEbdl8RhDZhHsut3m6s21gOYq5FEZduh39ydelAwrf9tfxnFhcyu5k1hj+IZBqdGOCDYVbwliwGwdceMCb4mm+NDjKMRggrvMcoiQWWxdtuaMoU8/fG5tv1zELmbS5bd0kVTnxDWZEPNGaE+Eyz2ixZHOOSG+azVNrc8c3yYslkj8f+1ddWff/UR8GgBvxa0Z4glw/S/rWMRjOkQc0PoRxnksGWEMrbGWGCyWf99VYIfkQ9riiuPDdXaZX3hD1a0KZZ2sLO1d2Z6gsPQDAaRYA74oCewvk2ieISzJtr6Mh/jgpU9bnPc1mxkF0x/xsbE3O/jUWKJ7jL2o5jvrL0WSM1Yt2BZU7QtANQ+m8I9yBTaAK6P45knRqQx78SYNReMafohmvFkvsZuP8PtyIvNbWuKHeZN1zOPgK6eXrcvW1lW72gMQuaCY3X5smT76CV8itevB0eaPv5dpt+5Evy7rPzCu//blcB4xEMl+KHK/ofd3i9Ugv+wq7xQuwUJLEhgQQILEliQwB+UBL5KJXieNtY/KDktVGZBAgsSWJDAggQWJLAggQUJLEhgQQJPJYEFJfipxLaQaUECCxJYkMCCBBYksCCBBQksSOAfswQWlOB/zL23UPcFCSxIYEECCxJYkMCCBBYksCCBp5LA7zx6yALcLAjNgkGMItebLIDKBa95/PNdQJShIljMjAWKWZCUxTYZasPToBbgA+7wiB1pA87Zc4PNrGwj8rDgLSvD6mWBWRYrYMFlFphln83N4633435bG63u1l7ikFxbvHW376xNVi5FgYtI2RxBTD7ERbjgQGuryWC+5bp3WN3vlzu37lauBb9ZuRZfZe+39nmDA/naEVtYfb7cTf1xrZ7zHS8zuRv1sbXR+pJYoEcCgKwuxCY4eRM742DaHowDKuDyUMe5aZCI2AbwPCeB3jCMRGM46gd2rJGo7Km7fkrNyHTR6CMEPjQ0NWn8rj9kDXmgc0Q8XYDP3MKf8m+Lvm5vqVcjeHiGpZqVnU0QRswDGRuSgQWJVN25A2rCKBiSGcoAszOUQdHe0kDbLF8EuK/kAyd4Pn1j+Ls1VZUuKteCu4JDFykXyukkgwq5n7wBJu1EeIcnZSse3nLDsbWAHwu6qa4ok194gsMRDbNB41MiuIt21xN139EJVz3BGQmpoBJkpLhgEfcK3m/YofW11SBT9IASEKWc3BzFgNlZcvO6+oZGXWCVoRPkwcCVAISbr3TRVu+u9hZkzrgAczgpNV2ZGakEaDIQ7ycDdW+sh1gAAPFgAkdyc3MVQyCYMZ9VVlUROHOPMZapNKgV5xe44qEPdu+G5juWCPncrHTHnuftu1mCkjqJEG+ob3LR01lABRmSwQQoIY319eohXxzYiTlZaQ6+yJvPW/cv+21BOAZb1NDQpCHA0SNj41SYn0+AL3jU94NPPIFcU5ASNYBQ0aXA0EgtW7EMOLceR3YxTL6ouCUqyM9zAS7efF9W5uc/t/cbLWsVmK0RceCUEnXvTRawagE0VVXVBApNEqyWrgyQDCxotqm+Bmz2fkcCkJ2VpQTQDOZTtgH5d3a0ge3cBJJMKHi8oDwQADl3zIwBzWSIId19Q4oGkq4QWtIAgga7yFdb30xQmydf1Ofyeev/pN/GqNXCPOqf8IMUo/CRgB9ru1u/WJfGJmeVmgW1NBBFHW5taGcxDlUG7U4hgO9xgUKfr8Pk2AgEJZWwgw64gEILOErLylMWUGveZOU2NTbAyjrqEGgK8nPZdwgaG+zV7coa9jrqk57NWE8koOvhHPHm/9LfzN+qOxVqYRz5GUwCKbNgJdBkHvY3GwuT4IUackUv+MGBBMNm5OSCzBSu9lYjk2B+Eg1s2Ll5jHXDLfd1rHvrZGO+qx0CB6iPMyEMMexbJz/WVQvILAWqbZo1wPY3wyaPBjs8PnRGNazHhoVt7I2xSemwFab7HBhn83eAPaa2uhaEhSnmeKKyQFwxKE5vsmf6kXsNz4wT8Z8BJGNyQiwx0ONqqIM4iDFoNOJ5rOsxIAHNZ6xbGbZvjBBwWA3cXkxaAahLMQ/X1vuVsOBIQ4qph0zKkJIMsrGypg6+Bgt+JWAuMlZFS/N9hkjzts1+W4BzAxCH04ERWlWY/eArIwEyiEpDYbHAvVjw3jMz0pENm7zLNwT6ToNDDFo5J9+DF/we/wj4dySfy58ZgpXhNBAI133KYoolQdIOC7eewGAjY/AmEDN0pFj69CoYvXeksxVEk/J8Dvs0mN46wOftwx4YNYMQm08yRau7F3ziYyiZjE9jIyNg+EHq5Lv9lH30JmVSj0ygueAJ0OHL0mfXyDsqB+VlyqKvCqm1FQQgHeEd+69IrbTbIOC8dSc4VLUN0q/OSBdqgDUDSmwRCiJBtnqfz07fAimDGiYSpOtQMh7U9sl/gA2vw5R5gLp38L7sJE9UptXd0BhKkO0HF8BHbgaujPdHofAePIvseR6YS3XS3hUZtPXJRT32CVPGmQd6l/acoD0BjH/DPTbEC0uGUlHd6Pneyg2gHlH07Un6+l3qV1JLP1DfnEQeDsvVWPgLKEx+OgYG6knwTStZWHqG70L3Gq+D+z7WheLLgK1XOVxXgxi6dPqojp86wwJf6Takwuz0+bGtuVo+/f+8EGlxRN4azu/bb/1MTQCrV8Oi09wNle2yAsahQUrRL0TQNt65ol9+dJBo6QHdLCnTYmCWYsJm9cu3fsrzA04RbeuddFztgUSZk82n1NfeoE8//kh3wGocJRLcFBwjoVgyB/N3dKgP/NJjOnTkKJS9y5UMhp+VYYpkc225/uHHP1K/opWPDH0FsncK9MSQ9r73vhphnWllsSyGQ34ljH/eaOC7bKADHfX66c/fVjtRwzVVtzU0HaLC9Fj9/B9+DDlIu4PR6mdQx6ehoEaAReo9ST6h9RMs0GeOHdStmmZ1NNapFKa+pOzCOXSysygfdfrkwGEwu/t088oFjfstAps5UueOfqJzV8tlkD+3qupQVvIc9NETinzwtSFrlF29oA8/PQQCQ7+uXbsBGUkOMrcofU/PjUOUcWDfXl0B27QTJr3Kxl6g/NJVVXpFew8cASHB8t2EyCQXuMMoNmffetwUrTvgT5+5XMYBqlHXrl5ReEK2w6X2Ys/axthUWaJ3P/pU7SBljIPUkJqTo8byyzp35RYMT5bvqiISs5EHqA0+ytwEYArJNOO59Mpp/WrvZ5oNjYEuPPuBbEwhugShwtHzMBCiIFy6fFWLo+IVfLdfb739gYPpunUDtjiA2gsL8uaFGzvQ08pY/5Cx3g42cKna2USyUcAfHHxQyCqun9InR04B39Xr2hifUSj/yT4d+PRjVQInVks+t25yWHuQ70HtH/+HQRA219zSr977ULdbh7Ub7GWvYmMK0eTokA7te1+X79QzF0fkz6EvYdFd/eqtt9TQyuG+tkYV9e1aWVSEMgNs4GMi5ufWxGi6D/PeKxXNTjEZBtElMiYBZTr2/mPAAt6+AevkWSije3T10gVwv4EnDJnVEfJdu4NyDFZuCUD6S4CgTATn1+cEKcpn+z7QWfDFjWynp7tb0YkZDhbN2mCKWm97A9jcxyGp6FJteamq2GRWQI995uhhldc0qqu1WecuXVPhyjWORMgrM5/qQJ8Og/7w2cfvgnF+E/bLIndYtvkyC2rDYG+XiouLOWTDZEc5lSjsbTBC+fdXs+8ZwQT0JPSFH1CM2elJvivBbOLV5dfBSL6sHowwxaAXREBKlA6+u7f+k6DMnD/BWL94g7WkGUbMOmVmpquz8Y7e33fQIZlcJ9800GkGWejr2uaRy6wmQDkpuXxa774PXXV8njJRMgydwpucok77937wKx07f11btu1SX2OZPj5wFFg6EDNQOCZm/OYFkWbvtrXdsLHrbrNnvbdP7SP+2rp2mbdYh4tccu6Yzly9rYGeDl27flOBUUngIse7fLXl5Ht/n7rGIckxgognpK8SIu2h9J5Qqfl+jcywcEgfoxAVo9zEomT90do5b2F937gCzFgMBqDZ6IOLKJ/9KMMoc8Wt0nMFMMaR720Up//9+Tn5fPiTOakPUPJOlWFxzfQQX5hF0hJzRG8dACcXRdFwiY+dB5eWdYP9kE6T1ueiHBejnKGk7skjv49GMBA9dAGl8lyT9Cx1v9NIObTp377kKdcsr/20sygHRbAKkpBD0l/soI3lEEUgi82Uu++cnVql11Z58vj0f+T8/lFIJqjnxnyUcNoRSd2fpw6Lgz3WdlvgdyDrE9Tv749I/+c3KLeOtm7wEFMYmRfF/sbJDjbA0CozjTp0QYpBH6DDaEO659UgUmkf/WsYwQkovz87LP0Pz5GHfgf+V6s5JBmWMeJwJ3gjEBjobtRpmExWbNiq3NQlamztYvFuR8m9q7Wbdyo2ZFo//eCQWnduUt/INAD8qxU23aOzN2/pa3u2OHiu37hh83zBXTaG9oYy1XTf07/856+qp7lSR49fUEvPMyj44NSy0RmW6MVzF5S6dJNeo3NOfvapzp86ocUMhNoe6X/5F6+qE0alEyy4bb27lZVg+LYmmScnU0gMImz9lucgpYFC2uBr+JmbhoDNaW5pwnLe6DAkDVrOlKm2xmrt+/SYYpgUBjs1baZ9nxNYkoEheuWb30eJ8mOjaNMPf/BDrLtYRgHNDwYzd5qTYtmV85qNztaLz2/WUGeTPjxwSM9tKsRKOK3lW3bqxT1baSvwR4vCnWLga/EGU7Vx1wvaDvTRIO89cuykqrH0Lc+If/CKqCWp+ua3v+sg7K6c+FjlDXWqiA7VeRTIb/3z/1UxAZM6C5j/kbPXlPf9lx/ke9IfUyh6tyqq6M+NevO5zdr/qx+7f2exwEXbRCR1NFRAUHJPz4Crmh4brL/6T3+ruvXLYImDKIV8rz+7UZ/88keOZjszLVlR4Pz6kkxxSs5Zoe/lr9MYmKDXTh3QRahhV+bBUOU2SNs8h1EWP9HSrS+rCAzkJeAlhxpQeO5KfW/pBo3CJnT15AEVXy+bk8+X0jncMt6qUMLPXq91UFDjttjNSYPdraqGGGHV5t3atipLH/z077AklrLwgbMbmqA333xDtaUXdB1FsXcY5rt5WAEqrl0ELzYItqqXFDzWqn9475TWFhUqdjkLCqvILNi1hw6dVGbRdrCAC3X9JIed4utK9WvX8EyIXn31BQWOtOgnH56B+riQW4HsOTV//J+m7PW0VOvY6SsYdMFrBcIKbeFBpumpcVWVXNT1pjF951uvgQUPeQr4unWlF9U0GqrvQZgyO9KtD1Foqlrol6x4FJqAB/kf94cp33excCxdt0cvbF7mgdwy2MU5KSGzUN/7fqa70Tj+8VvcdNQpGOW/rLpZb/75v2QNntS+ffsZp9An57Fo+5po9zi4p8lZS/Xd73/d3eYZHJcxeVqy4/qiqCX69ve/j/wnGfdV+sF7JzTx2k5tf/5Vp1AZJOFf/4f/B8tov1K4ofJ1bXPK2NSYjn36Iev9FPCHkMxg9fJK3Y/bp5jENH3zO99zXWFEHUdOXgCbNk7jkPAkZC3Xa89vYZ+BiRJr8HxgEK2MtLwifSc53xFWvP3Dv8IqXAPmb5HCgOq01AchUXVjp3Y886LWwED1g7/6L7pdfkt3YXGMTF2q7735nK6e+kQNrL0DXJkmAavmazJoutIr53T2UrmDmRzDGm1wb95kshkf6dfB/fvVOwILKQaNGdb1CaARjWZ69wsvsIdChAMs3iLDhp1HsrKbq0t08PRNBy83yjvnJpN7wfodsCMCfTY1rHff/UDVyMZYN5uhWLZ8dmswCqzeH1r6beg+X9gm265tTn5zt7QJZdKu/ucmu6Hk5kvLUEQDUHSXLOFvlKMbKGe713vY5gpRkLnhE+y4Dwb53Hd82d9xKFJf24aSl+mxiHqfY+5iZYKiF8vp8iyUM5TGLax5Vysptw0yDf42Jdhomiso1671fU2wBYo9QDvX8Y6lvIs1xaigvXU3qDsou7WJdxt5B7j0gnpbLSiAezgc2IHAaB3NSu2r2mHrLdCMqkJpKqQ963IgoCj01H34ft2BX9WzKLtr6IMMZGxTlXnh5GnTx3CUzRXic93ja7Mfec76G/x97aItRlYCRr7DiPY+VNfCZxgcthd52ov+KvDsHUay1cXY/syVwyzwluzKvr+7k2ulGd26flnHzpzn6j4VqtBMfe9739emNcsggMACwml8CQQVL7/2mnKSFrtFflXRCocp7HnTV/t/s6b2dLQrNjld0YCKpwAaHhMRDF4iTHD3Fy2zRtgGkJ2bp7glSUqC7WkExrBm3D7ivPmSkrCSBJFvEAXVJOR7smury+dO6fjJ0+oZGP61+ROflg3N7wsoROn3rU+z0JhW6dSpsypCWVmRA5j6HDcCX0o2ZSwQjNAEmPHMmnzk4H6Uj02QpNj1tK0IdhswzdVxs1JhtEuAWjmWq3u/GfAvmWxTDObSa8U6euw4c4MTE1l8tYzZu0O4Ejaikh42voMHPtW9sFitNEacB8nPYYamJKNggkdrylsU+Mj+AMybq43h1iYkJoCtGSmj8Z2PxMdHhngHrhRpGfR5tLIy0sAFHXZ4yd7iuxgTYRFRjsQgOjZRMex/9tkoCkVaGkQeYNia0mwMgqOAyvuaDOc0PiHJYc0aBvP4xAx/I9f7V9VmHZoY6tUtXAZusgH/7X/5a72HxXZ4bIp5kwi5QKyz9nvzea1avpRv2LDN9RU6crFCb77xqlKT4n/t9iyMU3kGm++pwwdgdLylvqlQ5RUuhVkrRwP1pTqJ5aOmoV3xGfkQa7AY+Zyw7GPtC+GwlJacgotFHiQYY2y0KKMkwxefQtkaGIMSG1ePJFwO8nOzIC9pc3TJoeDUplo+YxCcgcb7fj5fir+L5X+gu1kf7j2oles3QkqQ/2uKnJFRlN68wXv79NMf/a3+7kc/gTWsEdxwCCqocwS4wobZnQg7kLkWGM3zfJKtM6UcKG2+mFvArE2YB8mP6/ZYJcHeZ5i0Rie+BHes+KRkFaRF6eMP96qiokb+uDwty2exnmcyjO96bhYOfnYQdjBcDFifvHPVxl04ZEaLQ/zd7ci+Q8e057lnwXuNYKxFaaCrUQf2vqcIbqAyWCuM9czXZK4nJw/u1UBQijasXe1hDJ2b2dYgCFTCwQY2rOrKWyXcTEQ70gh7rAWr/bGjR1VeWcv89r1cy+vPBuVZz+PBReYAx/5l+Mz+Zrm6n/p6cAPD/SI9NU2xuAUlxYahpM/ghpOkWhgNT2OdrW3ogNUzB5IoNkhfE5t9ZeklDu29kGDsVvbnGAbtQDY9Mcqtw0eKSCvUlo1rMQA9dDMxq/SpY0d14fJ1LMGMs3k03VyOuri5+vjgOb3wErTR3A6aIWduCrqP/3t3uEv793+siYBwbVyZr27Ld+g8DK4vKR/3sM/nm/uO39ffD3vvt10DZGSHIwxATrF5VGS2uXkU1BCeOX8bg0SK5+p8GGuisasZo5vRanPg9Vkp9DbBiDeMiMHyzzWeofu5K3lcRtngqRvrbTTlgLENi5fnM3NhYc/GKuXxb/W+80m/zZcYI4aWzK07iihuSS7ZfmRGGVN+L1ZjqUXxNSsze69jc3OsaXxvfr2mpD4u4ULKdRaWbowpMINqnN3alEdX93APWYXVx5KVa7IYpo1NKP+bUVAjafduyg+kLAxg+tkJKGRp75PK9bzxy//vbWMwZd6skrLRPzI46HiTHRTMRxtiJo+yyxd+tHlVHrKnDTfLpZ+c5CBAXS2ZGGxy32MBSEjPVB5XV1fOnMWiDti53z1V3y7VzZoevf76a7QdkHJO9mk5hXpm52ZY1664k/bd37RRribz+59ZVCcBxw/khGHkHuZbagDqxrTjtRSZFWeaTjLFzfzTDDDe/GnH8Jm0fwe4fHzOtfQkJvYnDIlHKrgoIkar123R6hUFsHt2cVW7V3UtXY88Y7IKDQPU3qvoYnUvuXpZpWwOly+c5oq8VHdKrqiiumFe48KIEoJobwzMTampWRpA4RjCwuvtButPcxsx2QRhuTUSD6DlBcS+NmzeoXWrV8H2NK53f/kLqGf7UQx8V0Vt8zXZRUCnnY5iM4NS0zPwqOXBH19jI7Boriph7PRr2bLlWOhSlJcWow/f+YV+9c673Ojc4gmuph+R2OP/MYNSYNZ0b5+bXM16MlexmYLG2uRjgP62UVvfjqNEmo+i9YeNFfPNvMfY8JDDPL7Mh996Nv4ZLI/Vd7A2z0Rr2/oVD65JzV1hHB/SaZidNmx7Rq++9IzuDbbo1KUStxBbvqqK2+q6F6ut65ZRPyapj2kMt5ozx46gVDboABaoO7gsVXL93QQToTeZHO7Ry/kF+Rrva3fkEGO4Y5gSZ4exJdCid3X1Oh/5+d08sG6jYNAI5liI57aD8WUy98wXIyCZdrEfRqpj8zCMMT9FuePMM8sXysk9BBILOo9+8Obz1vzLf09z9XeL60Nzpzh78rjOXuTGpq5C17j+nrJFnDTNvO3nQJNdsEpvvPlN5SRHYaU7rPCUPM0ONOrjj97Xex/uU10rVow5itSXl/rwm9BFEVq2erO2rl+lEP8pffrpAZXhBjQ3mV/9LO2vv31NTYOBKirIZk/0113/UHzGs9WNX7L5l47iLjWvhCyXFq3R9i2b2FsCte+9X6q8vgODx0Ml3sgogumTeOZWJgphM37wRspk8yMS+uG0jFxN47s7wEHM1nefkq0dHOaOnTqvFqiij504jQ96g86dPY+h5GHfmTJuimlfe4MqcVFZXrSKOBLWBNwmdm7dyC1ImC6dO67j0Bd7jRK+lG/vdZZj1spr50/pXnQOrmoFjyjxNqappmu7WVyDWfctPsTmcyp09ov9xtXRjcyxiNp48ymZfLjROHLwIL7Gd3Ty+DGVcmtyvfgct+eQhvC1kXH0tVbr5CX2RMblydNn3QH7zIXLCoEpccvmLcpKS4S6+7re2XtYg6ZE+JjM//zy2ZOqaWqlDgd07WaZGqvKdLuu1a1d9hpb12zPWszBLo3DrT9rSk0N7nBnTqi2qUWHoLO/XnJLDeQz9x9b8/5QEirI7y6ZomtKqG0mNsytL+3HFDTv5xhcVDmIBRUrsFlGODxyzYEFNdYTQIWO4KyX86mlvdsOl94yLa+tS+aT6tYa/rYgOGOyG0QxIy5GgTxsa4GtqfbZYurCHuVzsjIt0KPX6m7vpixbW82chGHG+SQP8t2JK9SL8jZmmBXI8z1sspqiPAwWikOBN3k9LplR0OpqzGw2ltAHndXa2kgMhKu7zS/Tuay9kDjpwEVcT9KxFmd6fI5XF3jaeofv917gqpZnolGkrR1Pm6xvzYB1EeW8mvd9dwPtQeG1tdH63A4B9r3J3g4/dgAwS3UefZ9Mf8P+qB+coC4rORhQV7NwGT1jKAuJWckiwgM02FPufLpqKop1GZ+OvGWrCOqK0MTooE5i9QyFIjiagowlZ4JOoIivPNmGa2xhkwQ8mQV3goXRFGCzrNrCdxchGzuXKTxGZWnsd3aF7FidCOab5ERiivQESpMFGRgL0Xy6JRQleMPW7YxvWJTaa1T94f/f3pk/Z3ldd/xoQ7tkrUgISUhCCwjJCBnEZiAGG4yNx02d6Ux+SWc60x/6Z/THNk3TJmnaSeq0cZzUcbBjO7UdvAC2weybQAixaEMLQkhC+65+vveVsCd2h+fFlWdM750xll49z3vv/d5z7z33nO85911r7+yxCu7vVv2hW/e++I3LCkutdgKBAPfm4W4bQ2lSUFxwDKV0oEwgjzlYRKv5oeH8Wegcgy7wLoJxlLVKNwAN0W9tDlP8J8vJEoJnNm//FpODm5hud9vFU59aO0pwgQv8CDYRhbUOF+kEl62t4YamwY+tsaUDL8sKpxiJ5yoX4a2OZmgmn1rdE08TmJPPTZZRtvf5F7g+uInbKkedtSp1+bKwMNfNW9HwIaXgS+mUu3BJbJazDmp8NRHjuaVtlriKSU72s0yAMRabJFE+cCNrrHUlrG52io1LxXLOBAlY5AYVF/GyDi0tPfYE112vyM1w1ncphPKo6EbCWFz2K1eWWVIMN5XBpW1gUxNnvLnxvDW237GdO3dYYY7eC4a3mqcb9soqaywylSDHaA6mTSib3Fin1XeasdDmONjX42hMq+t2WXFWgg0N3OK5Rpu+HWUZeSVWWV3NjYGRdoyTswIjM2SdCFh0U1nv4AyYTuGGHQVDrhPWgZL5o8OExiUWxS8kawToceNWXDy3jEUnOVw0L+cY89B7uHID1iuFKCO30DZvhIfK+LZx5XfUwJQLRlS/5d7XehirG8yylllZebnFzqBMnLhocZkF9swze+1mBwdE8O9ov4kniNu/wsB9SXwSVwZvZg2NxLLaZt3vvGdXUUo2VBbNy3qUu6WvvfkKFMN62woFJ4+rkTuvXbCOvgl7YW+dRY4U2YcfHCSu4pptXgdPOmDfdRvZmprHrARZnwC7K2eOoejcsrJCrsHGq8ICwhzgdjJkY8XKcta1GPv3X7xBMNmEiw14JCuHQ/o65PWUtfb0oyRnuwNhkOp129na2jqMJ7E2eKeLmyD7WE8IipuXN3kxpKjqUHr6+BH2kVJzAarQwQrK11huaSSBgb22ZI5DTMNVe2b7Ojb6YHPN0Q3wsIkXfBpX8dN7nnWeD9U9o02OejXHIrB0TbDOKABYB4xE/t9FkNqK0tX0u8JiIiasnkPjIHikEhAcqDCPKqrXWxYbvLt9kTGX9VVXnWtNl6zHJqTapi1bkLs5u3OrA090u7sVTle21+UUuoNwZ3qM/fbABdaZbZYBJSpIiWA/yy+usI2G1T6SPaX3FoH8itWQgs/aJg2NYdf6q2vXa9bVYDnuIBi11XZsXGUbIwne4707t7pY6+PdWAffU4K08Ks9s6hKsE5EUvyGUdikoMkoE8VnBy+ijK1CQWKtO4IxonoNShAWw0RWoDXLoSdchnuDMni1i99LUJ74POjiJDik7MrqiAHKWXShzsCVM/sAq+dzm+CspqJ430Rp5e8XOs2e3IlCiALW1AZflTadbUUpfyK8ADX0GUdzOE3b85HrKyj3lcW04zYW2+tmOypRDs8R/NVjtrs21B90NyuAAnGqiT7mmbUOQlvIAqP7dFZZFWrKQsqlFO+KbLCi7UV835kWs007sKbqcEE/6soJ1PvYrIs5uoPnkmmb9mRiY1AqsYKjrEaxZ4VBwxPEX1o0H4hFsjfOmO3bwniCCYYI4/p4q8e7nU9fJ1rAgP8ymAWT/D0JoxNeY07MIfnASGEYF1yRMplGwEVtZYldJoCqHcUxl9N09BjWJwjYAwjWJOaF9vY2e/bpXTaF0nnyzFkWxXhbtqLMuVbDce2Gav3q/8oauZSo6+EP/gC9pRduL5G5s7jqCTjqu3XTRmZw16H0lRTkoQw0wE1PsGaU1Cw21aKVK+3tY+8QxNBnHc03bHQu3r0XztWeE+NE8LIp5eGSj5CFkghF8SxHsKJcbe2xNZVEsDM5dSvPOCc2Xcc5gcuionodGRmq2NjG7GTksF0Zz3aR40EPRlp8xS29hCKWj7tumiA5UVmk/A8P3LE2XC4ZXFNaVFxi714gWKU7z3ra4CmmEJ0eNYlVpwML7nJ4kyjGFs01tAh6GEXct0sNl6FarEDGuSIYa0c+wQDTE3yO67egiDHpvWmv//4Plla4Gs9ClmubrutNTc+22g2PWEvDKeu5nWo1q5m8YZR4lFllmWjEorp+VQ7zoNlWrF/F9kAwDZ+lIMdp2Xk2U99mTS2tNpUK330yBmpEtvUjE3qvtizbLmM9KdlU5Q4+QauXwtd0/pi9f6zRamprGbNsxharM8p1a3MzAUCJtC3d0rG4Xm+/baU5sQQs9RMdn+e4vIfPtVrt+lpblpMJJYXDGHxBKa9BSiJWvdpN261KLjuU0O7OTkvEupuVmgC//JpNEmgxg1dkCmWpb3icmIilKH4jFoUbeY4NvLuHBZK5MM27kViSRJcJXkKZYZpOXLKWrk6L6G2yiIRMjBqJ1oeFoQuLRGVZvhVxIOjoIFiyN8sFPeYX1FleVCKWrE5rg44yc+sytIAs6AksiAGLrkBeWbnO8kurHO/1FFa53tkWW1mQa+NDvdYOzysV+S0pLrJjN67aSGWh9aGwJWVkQ8FJtri8AluWl2vHPj5kmchiyfJMDlEs5gHLNFzb61hX84qKbQkKxsRMBFkx4jAGDCJ7rVaOhVKBkG+/f9QKKh610gIUTb5fVurh/ttYYCesCNqPrnxO5PAWThEVpAMlJymN4EaU3nGsGllQOsbJwtHVctsylxXYRH+3DUxEcD1vAkp6J7OAi41Zly5cbIe6kwVmo84amYwHj2UjWEEmEwnW2ff8n3NombOu6xfdtdOVZDmJZs240nDdZSVQ9qAhDnmfnL5if/bdTbY0CwsLK0o3GRPi0vMc73pgYBDDSmGweuefklehqf6kHfjkvK2t20zgbAKGrwj6P2adbc0WnZxtiWCiPa3h2g1LjRyw9v5xK0ZJHx7pdWt8ZDzZGlBGojgcTctKFaTImhgVi07ypFO2BwiKnIVjHFVchVc1jr2+zdEKFWT73L4slNE5FPWz8I5vWdXqcvbFDusfjiODRhwHgLscUpPQ1++jZHyuXaINVeJZXLmG9iJ3ETMT1tQfbQU56dAVO2xwgixABBZdb2qy9GX5Fh8xbXcGBiwtrxKq0CZbXR16bxbrcMtIrBUwH4NywD/XjEX7cdGUYAk2e5K9ctjsIgrnFJj/+ihK6KqQUiyLaQpKUB/K2VMoiFkocGrMtg0obAfNXv4QfmmJ2ROrw1OAhVQ3iuYbR+DcUkc3SnYKX1zM92NkQCEwe35riErwZjvBWNUoiivM8hDcQyipr/BeWRncXZTxhcwO+s77Fbn4t62nvkNkpaD9eJ5sO31lT7EBLL0EAps8hFC/7K1PsHqjEO59jGc4iL76sdmvbqAco6BXU+/9xFMWVfYLd/rS/Ni7EQszbf/NR/STvVttv3AJBZx9SYeQRvo5wnOvo4hyWLe9tPNYA9xo2oJRxL69zWwFB4MwDBFfCsco/cTT4azR73xKH/nOTYzfcrCVpVkc7c2lBCOe4dCMMv6XT4ExMnCcg4MOHsQz2V/vRlnOCH29TqBLON0+/fx3rPTadRuFYF1UUmIJnKS3f2unDeJS1TOyDsj9vouTeWl5M9kGOBisXsNJVylovrSpi/qhLLrpuDxritLt1y/+m83GJNqGrTsslwCsU6TC6BhPxS1XY9WbdtipF1+yf6o/YpkEmezZstFyctJsbeFR+9XPfoq1MNHqOI0tzwxv0RrCCn7myAH7zSuc7LAUbdkFVxqFr6cTLt7bR1FCC20EXt5rv3uVAE7S2nS/iPLzXduzda3jzC7BZZkGVzdnKt1ZsoJCKAvoJAeREx8dsFdJgxRJ6qmSmsddUF/39XN2gvQfdTvgIW/YbucaX7KXf/6vloDy+fjOnc6le/HkIXt9f5dLdVVUtdXK8vAC6JQXsIzAy60/+bHtf+130AwmrRJ38WOri9ic++yP775ne/Y9Y5P9HVi+Gi26vcvOHzvsrHk7d0IP6Llqbx46TsaSJNv+xC7WnoKAtYYei0t+xCpWrbKrb75l//gPFywOnvpTfMfs2ACu14NW8NgeW4sSXlpwww6+9rIdwlVc/fhOy0UZipwiUwhUgh/84IIlZOa6jBHJAYPiVLus34315+wmlpfW5mv2Hpb2dNIn/dV3nrSTxz+16DQsjwTrPbt7u71/8C17D65XSUWV7d7wqJ18+5cctm5aWwsBRAQ3ZeSX29987wU4jwmB+h+F2zuKU2usAi+nouFU51gs824OC/+FEx/ZaMoqq6sqtPWPrbPX3/mtHT8Q6TIJ7N68xbISo6zh8sv24x9+H1mJh+u406XZClTx/ENF5VV4OW7ZL3/6Y2IKom3Hvr8gpWCyc7sePtPOWl5sm7bvsD8e+ND++UcniB9Yat/7drUlzo3gfTlov/jJj7Coxbj3crLnF54ADRD1RmnJYhhHm1ni5svSrCFHubgGH/5Cy6Bt2fa4rd2y0+r/8yX72U9+SPaXHNuxZ7elxUXYf5HxppF0XZnLix1fMh2LQTgHdqX6u3LuE+gUrzL+s7aOtaSqrACrezeczANwvdOtlYAaWdxbsTgfP3zAsrCKbttYi3Wuxvb/x7+wNsxZMYr8ptoqVNSgRVkCoN1cOm3HzzZwkImxzPxHie1ZaqPMreNHjhB8+ZTFEmz4/qGjpL+7Y3FJqfYUlu+YuUm7ePqI1TdeZ92OtqVl660EF2A4c1w0i8Sk0GFlOCWV9TLHkpHV6YkhO3zwoFXUbsH4UQYX+JwVVW+F870UA0+UjQ6PkMXjgn1y9jUU0glStpXbHoKpRRkJWqbxtnS2tVh9/Xnr7LxpB9gwS9ast11b19u5o4csvmgjdMN8q+AA8sZ/77cTByIsv3qjrSLzx1hvhjX+7nX7/t+dR04TiF95DsUxJWjVKAUEGyYkuAPDLAdGxQBEwq+OJDCwgbl/vRcjBhlZEhOlGBDYj+d0WW4O8zjeuto67b2DZMvoHYSu8Ig9s+8FFwsRtHJHJWJzlrxL1jMysyybw48yHV27eIogT7wSeCBu3rhkr+zf7w6yy6GebNm4jgA8NnWtDdNLXNzOCB6wULBu0NoX/7kIrDeoqwHLONrU9b+FXf7zQC+wJ5K3EossypgqEQ9XacEm+Zw1xOWQde57cJIlUJutvAr6jMOM44/qnYXMDoEq5SEdsEQVUL1SEsWVVcFr4LIVsD86l7z4ugpolQKL98Llr5XbXgdyfRbOAVko6vvVdoyTzvUv67BEcoT26LtkKR2hbtUpJTaev2MMwU2kc2oIH32mv4dTlGdYfVXbNacxwrh8xfoO9BlSEPED9QsLYYl3ndMrz1Op+4w6FY8SVNn539qm/olqd5f+LPRR9eGNtFH+JsuwxgYamKtXVAhZvUVBEUVCDVA72JNsMvVJ68v9e5uNTrNprEPObQnIMZygxenU7wucKlmtElgI5ZaUJUn4i2sry4fcll9X6e/vd9bViopyN/kHSIcxTOoiZWpIIhArFUvTIHkm5zjVK1sD7Dy703uH/k/PB8pgIWIi3MUKPAxdIEIBHnCs0rCahdONCaI/hyCB65CgTSOVQC1FA4sK0Nt313LZGKY5nQ0M9JtSK2lDz8gMBdAowlvu8yEst7PkMBWHMi4gR1RLifJF9hHwN0LKF0UMJxKgkobbTYFjk2zWylmciFD00u9RLChRWM2T2cySEfw++u0Cwtx7WFZ5LxxagPh4g6ROGsINNAdgqjsF3KNZsLvhnKamJNO3Kfinym8a7WRDrnst1NFwiu6Qz1EuRr0jykZ41gry5GJRHyTX4igTMhbqQxppziKw0urzyLhkZDsa+sEQltBht74lMS4pbgMfp913eW/y3nvxyEdQydV43e6G2sD7kn1t7NEcDLPZJIfY/BFAAhBTGYMh0rANuojxeDbUFGTrbm83VKoQZzv0Xjx5TTMdpSDseUNfFeypTTMVq/hd8iVGxiYxF2NshrHpxzo0BUVGmQSSUWS0JvYz5jqwRDOvFSgm7MPBXUE7Q/C97oKrqDYKgEugvnHoRZJ/ybqCqQZ5Zgx8ovFKZGUQvMfcGyZAbVDvsX6kpWdCI2PNCEMpuocPXhWl3BqEyrKMDBCDzJ0ZDp+S9VgyovSRmm0Mi6vGJJn+JaOY9HTDoWXBjkW5SEYuE8OM1pfFfpg5PkDmFRkCNIek8ERAJ+ru6bMsOLBj8E77WJP0d62DCsZLYEONZJz6sQiK957g5khSmJ4HvBikMFSfRSOJZ65I1qfht8uyHMXhPQZroDB3v0NJSUEpS0ABEt7DjAtiynvJpOxMYU0PTkO5hzk/KPh3HNmJJMOCgvB67wy4w5hwGIVmMmkxYJ3oKCqiJIn6I7wUJxIvSgxtjkPugq6tyvozgAwrwDmGjVXviQOruTo1Pky/k6F7LHF0hQHwFb89ifiEFAKcZvGU6N0xPG/yIqSypifRtnAssgt9n9LYs54axpUE1tJRxlnBdzk52ffWjBHmuoKv0wi6nhxTSjjkn3muOIw0AmFFxQsnM8ZC3aKr9aNQiKaXnZnhUh5qPxPFbo61X3NcAYea41pfJG+uzL83icwvZX25X5GX8jip5Gpra91afL/nv8rfF1UJ/ioN8+/+/0ZgLPkzJfirq+dfD5ZSgrWxlpSUwAlOctzQKRTcUNAAGxHNcPxQNh/RG7SISoGZRjFQEnMpIXrG5V393HvhWIhcT6WMcgJ1nEw2QCmSsoiLszVFfVrAVYfjkumkSlGglmgBqkvKrNqlBkpBDrd+9TEU+EDAFtY5va/P+Fr3fVp8Q/2GN8jfFCyzgM2fvucaF/gfpXkjyI6DkNotPFWXi5xm8Q1xLuGqsoBrE1bROLix4Gdho8Vc7zzI4cnhhoIhHq7DE9AXPpMiGuKJznP4AEPjcA/vP3kvnPpDhw8Of4ylMFZR/xV0qDFXUb9UpkRbAG0pqtqAxZXVM59/T56AcOp3X+z+EQ8YueH7hbUs1FQSwpcKJG9q44KsqdIFWVfAosYrXFlTtaKD6LulBDu+u/tM8q2AQ/Ul1C7109UzP76SwRneXXjvQepW/TLxqC7JnvjI6reGISRbEcg6c5G69Lss5+KQSkZVr+ZcOAc9V52rEllH+Q7J+vwcZzyd/FP/wtiHOJuhtzTmIYxlkAnV7yz5tCHcsjB/JTdOidW6QR9FU9B6J9ly6wCY63fJlIqTATdWvDcvZ5r7D1I07pJ9hN3JTWi9C9U9ixxK+Vc7FmRZzwovJ/8PgLvWEbU/JOOhFrtAW8YV4J2sO8WSeiRX9+RPf+cztXeKtUfr3YOuMarVBYsjU+o3sPO9mr+h9STUqtCc0OcaXxXJ5AzPSAYkb3rvwcq8rKs+vmeadZ2OO9nWPFiQK9UhWfushN5TOxfWos/+9sWfJjksnDlzxurq6txe+sUn/u8+CSEU9Pvkw44rwEyKH98Xj8AiIhCZUIpVDusup8xvSpG7qhNO5MWLBL/IBeSLR8Aj4BHwCHgEPAJhIaDDhoKMdXBc7BKeJXgWX/c0EVWKIvPFI7CICMxG4bqOIoACC9o3pWjiKtuDrA1fx+T9puDi2+kR8Ah4BDwCHoFwEJAlWfQheQwWs4SnBC9mS/x3ewQ8Ah4Bj4BHwCPgEfAIeAS+JgQW39b8NXXEV+MR8Ah4BDwCHgGPgEfAI+ARCIqAV4KDIuWf8wh4BDwCHgGPgEfAI+AReGgQ8ErwQzOUviMeAY+AR8Aj4BHwCHgEPAJBEfBKcFCk/HMeAY+AR8Aj4BHwCHgEPAIPDQJeCX5ohtJ3xCPgEfAIeAQ8Ah4Bj4BHICgCXgkOipR/ziPgEfAIeAQ8Ah4Bj4BH4KFBwCvBD81Q+o54BDwCHgGPgEfAI+AR8AgERcArwUGR8s95BDwCHgGPgEfAI+AR8Ag8NAh4JfihGUrfEY+AR8Aj4BHwCHgEPAIegaAI/A8zdXZBLFV2ZgAAAABJRU5ErkJggg==)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lIUfhwIQjytU"
      },
      "source": [
        "**Step 2 of this approach** \n",
        "- That is to calculate the predictions. And we can do this by simply taking the dot products of each movie with each user. \n",
        "- For instane, the first latent user factor represents how much the user likes action movies and the first latent movie factor represents if the movie has a lot of action or not. The **product of those will be particularly high** if either the user likes action movies and the movie doesnt have any action in it. \n",
        "- On the other hand if we hav mismatch (a user loves action movies but the movie isnt an action film, or the user doesnt like action movies and it is one), the product will be very low. \n",
        "\n",
        "**Step 3 of the is approach** \n",
        "- Calculate our loss, we can use any loss function. \n",
        "- For this we will be using MSE (mean squared error). \n",
        "\n",
        "Thats all we need: \n",
        "- Randomly initialized parameters (latent features) \n",
        "- Calculate the predictions (the results of the dot product). \n",
        "- Calculate the loss between the predictions and the actual rating. \n",
        "\n",
        "Now our goal is to optimize the parameters (latent factors) using SGD, such as to minimize the loss. At each step, the **SGD optimizer will calculate the match between each moovie and each user using the dot product**.\n",
        "\n",
        "It will then calculate the derivative of this value and will step the weights by multiplying this by the learning rate. After doing this lots of times, the loss will get better and better and the recommendations will also get better and better. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "09We0faljxd7"
      },
      "source": [
        "### Creating the DataLoaders\n",
        "\n",
        "Lets get the movie title's than their ID's for a better visualization. The table `u.item` contains the correspondance of ID's to titles"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "r84OHc4-r4l2",
        "outputId": "b516340d-383c-4e6e-ee9c-de274dd959c6"
      },
      "source": [
        "# Loading in the movie titles \n",
        "movies = pd.read_csv(path/'u.item', delimiter = '|' , encoding= 'latin-1', \n",
        "                     usecols = (0,1), names = ('movie', 'title'), header = None)\n",
        "movies.head()"
      ],
      "execution_count": 9,
      "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>movie</th>\n",
              "      <th>title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   movie              title\n",
              "0      1   Toy Story (1995)\n",
              "1      2   GoldenEye (1995)\n",
              "2      3  Four Rooms (1995)\n",
              "3      4  Get Shorty (1995)\n",
              "4      5     Copycat (1995)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "0ImUvdOksPyt",
        "outputId": "12062186-0ccf-46b7-bdbc-1ed1234bb466"
      },
      "source": [
        "# Mergiing the rating df with the movies one \n",
        "ratings = ratings.merge(movies)\n",
        "ratings.head()"
      ],
      "execution_count": 10,
      "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>user</th>\n",
              "      <th>movie</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>196</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>881250949</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>63</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>875747190</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>226</td>\n",
              "      <td>242</td>\n",
              "      <td>5</td>\n",
              "      <td>883888671</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>154</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>879138235</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>306</td>\n",
              "      <td>242</td>\n",
              "      <td>5</td>\n",
              "      <td>876503793</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   user  movie  rating  timestamp         title\n",
              "0   196    242       3  881250949  Kolya (1996)\n",
              "1    63    242       3  875747190  Kolya (1996)\n",
              "2   226    242       5  883888671  Kolya (1996)\n",
              "3   154    242       3  879138235  Kolya (1996)\n",
              "4   306    242       5  876503793  Kolya (1996)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XTlr6_yusZ1J"
      },
      "source": [
        "Using the `CollabDataLoaders` to build our DataLoaders. By default, it takes the first columns for the user, and the second column for the item (here our movies) and the third column for the ratings. \n",
        "\n",
        "We need to change the value of `item_name` in our case to use the title instead of the ID's "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "GlmJ-04rs3jf",
        "outputId": "4f0ecba2-0a28-459d-fc73-40894b3132b2"
      },
      "source": [
        "dls = CollabDataLoaders.from_df(ratings , item_name = 'title' , bs = 64)\n",
        "dls.show_batch()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user</th>\n",
              "      <th>title</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>892</td>\n",
              "      <td>Braveheart (1995)</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>94</td>\n",
              "      <td>Immortal Beloved (1994)</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>311</td>\n",
              "      <td>Just Cause (1995)</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>880</td>\n",
              "      <td>Shining, The (1980)</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>328</td>\n",
              "      <td>Star Trek III: The Search for Spock (1984)</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>766</td>\n",
              "      <td>True Lies (1994)</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>500</td>\n",
              "      <td>City of Lost Children, The (1995)</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>868</td>\n",
              "      <td>Bad Taste (1987)</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>828</td>\n",
              "      <td>Three Colors: Red (1994)</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>592</td>\n",
              "      <td>Paradise Lost: The Child Murders at Robin Hood Hills (1996)</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SUzqRX5btDtv"
      },
      "source": [
        "We cant represent collaborative filtering in Pytorch with the cross tab representation directory, but instead we can **represent the movie and latent factor tables are simple matrices**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TTtIjbWbtrEN",
        "outputId": "daf16086-6c65-4873-a81c-c7a105a7816d"
      },
      "source": [
        "# Should return 3 elements (id , title, rating)\n",
        "dls.classes"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'title': ['#na#', \"'Til There Was You (1997)\", '1-900 (1994)', '101 Dalmatians (1996)', '12 Angry Men (1957)', '187 (1997)', '2 Days in the Valley (1996)', '20,000 Leagues Under the Sea (1954)', '2001: A Space Odyssey (1968)', '3 Ninjas: High Noon At Mega Mountain (1998)', '39 Steps, The (1935)', '8 1/2 (1963)', '8 Heads in a Duffel Bag (1997)', '8 Seconds (1994)', 'A Chef in Love (1996)', 'Above the Rim (1994)', 'Absolute Power (1997)', 'Abyss, The (1989)', 'Ace Ventura: Pet Detective (1994)', 'Ace Ventura: When Nature Calls (1995)', 'Across the Sea of Time (1995)', 'Addams Family Values (1993)', 'Addicted to Love (1997)', 'Addiction, The (1995)', 'Adventures of Pinocchio, The (1996)', 'Adventures of Priscilla, Queen of the Desert, The (1994)', 'Adventures of Robin Hood, The (1938)', 'Affair to Remember, An (1957)', 'African Queen, The (1951)', 'Afterglow (1997)', 'Age of Innocence, The (1993)', 'Aiqing wansui (1994)', 'Air Bud (1997)', 'Air Force One (1997)', 'Air Up There, The (1994)', 'Airheads (1994)', 'Akira (1988)', 'Aladdin (1992)', 'Aladdin and the King of Thieves (1996)', 'Alaska (1996)', 'Albino Alligator (1996)', 'Alice in Wonderland (1951)', 'Alien (1979)', 'Alien 3 (1992)', 'Alien: Resurrection (1997)', 'Aliens (1986)', 'All About Eve (1950)', 'All Dogs Go to Heaven 2 (1996)', 'All Over Me (1997)', 'All Things Fair (1996)', 'Alphaville (1965)', 'Amadeus (1984)', 'Amateur (1994)', 'Amazing Panda Adventure, The (1995)', 'American Buffalo (1996)', 'American Dream (1990)', 'American President, The (1995)', 'American Strays (1996)', 'American Werewolf in London, An (1981)', 'American in Paris, An (1951)', 'Amistad (1997)', \"Amityville 1992: It's About Time (1992)\", 'Amityville 3-D (1983)', 'Amityville Curse, The (1990)', 'Amityville Horror, The (1979)', 'Amityville II: The Possession (1982)', 'Amityville: A New Generation (1993)', 'Amityville: Dollhouse (1996)', 'Amos & Andrew (1993)', 'An Unforgettable Summer (1994)', 'Anaconda (1997)', 'Anastasia (1997)', 'Andre (1994)', 'Angel Baby (1995)', 'Angel and the Badman (1947)', 'Angel on My Shoulder (1946)', 'Angela (1995)', 'Angels and Insects (1995)', 'Angels in the Outfield (1994)', 'Angus (1995)', 'Anna (1996)', 'Anna Karenina (1997)', 'Anne Frank Remembered (1995)', 'Annie Hall (1977)', 'Another Stakeout (1993)', \"Antonia's Line (1995)\", 'Aparajito (1956)', 'Apartment, The (1960)', 'Apocalypse Now (1979)', 'Apollo 13 (1995)', 'Apostle, The (1997)', 'Apple Dumpling Gang, The (1975)', \"April Fool's Day (1986)\", 'Apt Pupil (1998)', 'Aristocats, The (1970)', 'Army of Darkness (1993)', 'Around the World in 80 Days (1956)', 'Arrival, The (1996)', 'Arsenic and Old Lace (1944)', 'As Good As It Gets (1997)', 'Assassins (1995)', 'Assignment, The (1997)', 'Associate, The (1996)', 'Audrey Rose (1977)', 'August (1996)', 'Austin Powers: International Man of Mystery (1997)', 'Awfully Big Adventure, An (1995)', 'Ayn Rand: A Sense of Life (1997)', 'B*A*P*S (1997)', 'B. Monkey (1998)', 'Babe (1995)', 'Baby-Sitters Club, The (1995)', 'Babyfever (1994)', 'Babysitter, The (1995)', 'Back to the Future (1985)', 'Backbeat (1993)', 'Bad Boys (1995)', 'Bad Company (1995)', 'Bad Girls (1994)', 'Bad Moon (1996)', 'Bad Taste (1987)', 'Ballad of Narayama, The (Narayama Bushiko) (1958)', 'Balto (1995)', 'Bananas (1971)', 'Band Wagon, The (1953)', 'Barb Wire (1996)', 'Barbarella (1968)', 'Barcelona (1994)', 'Basic Instinct (1992)', 'Basketball Diaries, The (1995)', 'Basquiat (1996)', 'Bastard Out of Carolina (1996)', 'Batman & Robin (1997)', 'Batman (1989)', 'Batman Forever (1995)', 'Batman Returns (1992)', 'Baton Rouge (1988)', 'Bean (1997)', 'Beans of Egypt, Maine, The (1994)', 'Beat the Devil (1954)', 'Beautician and the Beast, The (1997)', 'Beautiful Girls (1996)', 'Beautiful Thing (1996)', 'Beauty and the Beast (1991)', 'Beavis and Butt-head Do America (1996)', 'Bed of Roses (1996)', 'Bedknobs and Broomsticks (1971)', 'Before Sunrise (1995)', 'Before and After (1996)', 'Before the Rain (Pred dozhdot) (1994)', 'Being Human (1993)', 'Being There (1979)', 'Believers, The (1987)', 'Belle de jour (1967)', 'Ben-Hur (1959)', 'Benny & Joon (1993)', 'Bent (1997)', 'Best Men (1997)', 'Best of the Best 3: No Turning Back (1995)', 'Better Off Dead... (1985)', 'Beverly Hillbillies, The (1993)', 'Beverly Hills Cop III (1994)', 'Beverly Hills Ninja (1997)', 'Bewegte Mann, Der (1994)', 'Beyond Bedlam (1993)', 'Beyond Rangoon (1995)', 'Bhaji on the Beach (1993)', 'Big Bang Theory, The (1994)', 'Big Blue, The (Grand bleu, Le) (1988)', 'Big Bully (1996)', 'Big Green, The (1995)', 'Big Lebowski, The (1998)', 'Big Night (1996)', 'Big One, The (1997)', 'Big Sleep, The (1946)', 'Big Squeeze, The (1996)', 'Billy Madison (1995)', 'Bio-Dome (1996)', 'Bird of Prey (1996)', 'Birdcage, The (1996)', 'Birds, The (1963)', 'Bitter Moon (1992)', 'Bitter Sugar (Azucar Amargo) (1996)', 'Black Beauty (1994)', 'Black Sheep (1996)', 'Blade Runner (1982)', 'Blink (1994)', 'Bliss (1997)', 'Blob, The (1958)', 'Blood & Wine (1997)', 'Blood Beach (1981)', \"Blood For Dracula (Andy Warhol's Dracula) (1974)\", 'Bloodsport 2 (1995)', 'Bloody Child, The (1996)', 'Blown Away (1994)', 'Blue Angel, The (Blaue Engel, Der) (1930)', 'Blue Chips (1994)', 'Blue Sky (1994)', 'Blue in the Face (1995)', 'Blues Brothers 2000 (1998)', 'Blues Brothers, The (1980)', 'Bob Roberts (1992)', 'Body Parts (1991)', 'Body Snatcher, The (1945)', 'Body Snatchers (1993)', 'Bogus (1996)', 'Bonheur, Le (1965)', 'Bonnie and Clyde (1967)', 'Boogie Nights (1997)', 'Boomerang (1992)', 'Boot, Das (1981)', 'Booty Call (1997)', 'Bottle Rocket (1996)', 'Bound (1996)', 'Boxing Helena (1993)', \"Boy's Life 2 (1997)\", 'Boys (1996)', 'Boys Life (1995)', 'Boys in Venice (1996)', 'Boys of St. Vincent, The (1993)', 'Boys on the Side (1995)', 'Boys, Les (1997)', 'Brady Bunch Movie, The (1995)', 'Braindead (1992)', \"Bram Stoker's Dracula (1992)\", 'Brassed Off (1996)', 'Braveheart (1995)', 'Brazil (1985)', 'Bread and Chocolate (Pane e cioccolata) (1973)', 'Breakdown (1997)', \"Breakfast at Tiffany's (1961)\", 'Breaking the Waves (1996)', 'Bride of Frankenstein (1935)', 'Bridge on the River Kwai, The (1957)', 'Bridges of Madison County, The (1995)', 'Bringing Up Baby (1938)', 'Broken Arrow (1996)', 'Broken English (1996)', 'Bronx Tale, A (1993)', 'Brother Minister: The Assassination of Malcolm X (1994)', \"Brother's Kiss, A (1997)\", 'Brothers McMullen, The (1995)', 'Brothers in Trouble (1995)', 'Browning Version, The (1994)', 'Buddy (1997)', 'Bulletproof (1996)', 'Bullets Over Broadway (1994)', 'Burnt By the Sun (1994)', 'Burnt Offerings (1976)', 'Bushwhacked (1995)', 'Butch Cassidy and the Sundance Kid (1969)', 'Butcher Boy, The (1998)', 'Butterfly Kiss (1995)', 'Bye Bye, Love (1995)', \"C'est arrivé près de chez vous (1992)\", 'Cabin Boy (1994)', 'Cable Guy, The (1996)', 'Calendar Girl (1993)', 'Canadian Bacon (1994)', 'Candidate, The (1972)', 'Candyman (1992)', 'Candyman: Farewell to the Flesh (1995)', 'Cape Fear (1962)', 'Cape Fear (1991)', 'Captives (1994)', 'Career Girls (1997)', 'Careful (1992)', \"Carlito's Way (1993)\", 'Carmen Miranda: Bananas Is My Business (1994)', 'Caro Diario (Dear Diary) (1994)', 'Carpool (1996)', 'Carrie (1976)', 'Carried Away (1996)', 'Carrington (1995)', 'Casablanca (1942)', 'Casino (1995)', 'Casper (1995)', 'Castle Freak (1995)', 'Cat People (1982)', 'Cat on a Hot Tin Roof (1958)', \"Cats Don't Dance (1997)\", 'Catwalk (1995)', 'Caught (1996)', 'Celestial Clockwork (1994)', 'Celluloid Closet, The (1995)', 'Celtic Pride (1996)', 'Cement Garden, The (1993)', 'Cemetery Man (Dellamorte Dellamore) (1994)', 'Century (1993)', 'Chain Reaction (1996)', 'Chairman of the Board (1998)', 'Chamber, The (1996)', 'Charade (1963)', 'Chasers (1994)', 'Chasing Amy (1997)', 'Children of the Corn: The Gathering (1996)', 'Children of the Revolution (1996)', 'Chinatown (1974)', 'Christmas Carol, A (1938)', 'Chungking Express (1994)', 'Ciao, Professore! (1993)', 'Cinderella (1950)', 'Cinema Paradiso (1988)', 'Circle of Friends (1995)', 'Citizen Kane (1941)', 'Citizen Ruth (1996)', 'City Hall (1996)', \"City Slickers II: The Legend of Curly's Gold (1994)\", 'City of Angels (1998)', 'City of Industry (1997)', 'City of Lost Children, The (1995)', 'Clean Slate (1994)', 'Clean Slate (Coup de Torchon) (1981)', 'Clear and Present Danger (1994)', 'Clerks (1994)', 'Client, The (1994)', 'Cliffhanger (1993)', 'Clockers (1995)', 'Clockwork Orange, A (1971)', 'Close Shave, A (1995)', 'Clueless (1995)', 'Cobb (1994)', 'Cold Comfort Farm (1995)', 'Coldblooded (1995)', 'Collectionneuse, La (1967)', 'Colonel Chabert, Le (1994)', 'Color of Night (1994)', 'Commandments (1997)', 'Con Air (1997)', 'Conan the Barbarian (1981)', 'Condition Red (1995)', 'Coneheads (1993)', 'Congo (1995)', 'Conspiracy Theory (1997)', 'Contact (1997)', 'Contempt (Mépris, Le) (1963)', 'Convent, The (Convento, O) (1995)', 'Cook the Thief His Wife & Her Lover, The (1989)', 'Cool Hand Luke (1967)', 'Cool Runnings (1993)', 'Cop Land (1997)', 'Cops and Robbersons (1994)', 'Copycat (1995)', 'Corrina, Corrina (1994)', 'Cosi (1996)', 'Country Life (1994)', 'Courage Under Fire (1996)', 'Cowboy Way, The (1994)', 'Craft, The (1996)', 'Crash (1996)', 'Crimson Tide (1995)', 'Critical Care (1997)', 'Cronos (1992)', 'Crooklyn (1994)', 'Crossfire (1947)', 'Crossing Guard, The (1995)', 'Crow, The (1994)', 'Crow: City of Angels, The (1996)', 'Crows and Sparrows (1949)', 'Crucible, The (1996)', 'Crude Oasis, The (1995)', 'Crumb (1994)', 'Cry, the Beloved Country (1995)', 'Crying Game, The (1992)', 'Curdled (1996)', 'Cure, The (1995)', 'Cutthroat Island (1995)', 'Cyclo (1995)', 'Cyrano de Bergerac (1990)', 'Cérémonie, La (1995)', 'D3: The Mighty Ducks (1996)', 'Dadetown (1995)', 'Daens (1992)', 'Damsel in Distress, A (1937)', 'Dances with Wolves (1990)', 'Dangerous Beauty (1998)', 'Dangerous Ground (1997)', 'Dangerous Minds (1995)', \"Daniel Defoe's Robinson Crusoe (1996)\", \"Dante's Peak (1997)\", 'Dark City (1998)', 'Dave (1993)', 'Davy Crockett, King of the Wild Frontier (1955)', 'Day the Earth Stood Still, The (1951)', 'Day the Sun Turned Cold, The (Tianguo niezi) (1994)', 'Daylight (1996)', 'Days of Thunder (1990)', 'Daytrippers, The (1996)', 'Dazed and Confused (1993)', 'Dead Man (1995)', 'Dead Man Walking (1995)', 'Dead Poets Society (1989)', 'Dead Presidents (1995)', 'Dear God (1996)', 'Death and the Maiden (1994)', 'Death in Brunswick (1991)', 'Death in the Garden (Mort en ce jardin, La) (1956)', 'Deceiver (1997)', 'Deconstructing Harry (1997)', 'Deep Rising (1998)', 'Deer Hunter, The (1978)', 'Delicatessen (1991)', 'Delta of Venus (1994)', 'Demolition Man (1993)', 'Denise Calls Up (1995)', 'Desert Winds (1995)', 'Designated Mourner, The (1997)', 'Desperado (1995)', 'Desperate Measures (1998)', 'Destiny Turns on the Radio (1995)', 'Devil in a Blue Dress (1995)', \"Devil's Advocate, The (1997)\", \"Devil's Own, The (1997)\", 'Diabolique (1996)', 'Dial M for Murder (1954)', 'Die Hard (1988)', 'Die Hard 2 (1990)', 'Die Hard: With a Vengeance (1995)', 'Die xue shuang xiong (Killer, The) (1989)', 'Dingo (1992)', 'Dirty Dancing (1987)', 'Disclosure (1994)', 'Diva (1981)', 'Dolores Claiborne (1994)', 'Don Juan DeMarco (1995)', \"Don't Be a Menace to South Central While Drinking Your Juice in the Hood (1996)\", 'Donnie Brasco (1997)', 'Doom Generation, The (1995)', 'Doors, The (1991)', 'Double Happiness (1994)', 'Double Team (1997)', 'Double vie de Véronique, La (Double Life of Veronique, The) (1991)', 'Down Periscope (1996)', 'Down by Law (1986)', 'Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1963)', 'Dracula: Dead and Loving It (1995)', 'Dragonheart (1996)', 'Dream Man (1995)', 'Dream With the Fishes (1997)', 'Drop Dead Fred (1991)', 'Drop Zone (1994)', 'Drunks (1995)', 'Duck Soup (1933)', 'Dumb & Dumber (1994)', 'Dumbo (1941)', 'Dunston Checks In (1996)', 'Duoluo tianshi (1995)', 'E.T. the Extra-Terrestrial (1982)', 'East of Eden (1955)', 'Eat Drink Man Woman (1994)', 'Ed (1996)', 'Ed Wood (1994)', \"Ed's Next Move (1996)\", 'Eddie (1996)', 'Edge, The (1997)', 'Eighth Day, The (1996)', 'Emma (1996)', 'Empire Strikes Back, The (1980)', 'Enchanted April (1991)', 'Endless Summer 2, The (1994)', \"Enfer, L' (1994)\", 'English Patient, The (1996)', 'Englishman Who Went Up a Hill, But Came Down a Mountain, The (1995)', 'Entertaining Angels: The Dorothy Day Story (1996)', 'Eraser (1996)', 'Escape from L.A. (1996)', 'Escape from New York (1981)', 'Escape to Witch Mountain (1975)', 'Etz Hadomim Tafus (Under the Domin Tree) (1994)', \"Eve's Bayou (1997)\", 'Even Cowgirls Get the Blues (1993)', 'Evening Star, The (1996)', 'Event Horizon (1997)', 'Everest (1998)', 'Every Other Weekend (1990)', 'Everyone Says I Love You (1996)', 'Evil Dead II (1987)', 'Evita (1996)', 'Excess Baggage (1997)', 'Executive Decision (1996)', 'Exit to Eden (1994)', 'Exotica (1994)', 'Extreme Measures (1996)', 'Eye for an Eye (1996)', \"Eye of Vichy, The (Oeil de Vichy, L') (1993)\", 'Face/Off (1997)', 'Faces (1968)', 'Fair Game (1995)', 'FairyTale: A True Story (1997)', 'Faithful (1996)', 'Fall (1997)', 'Fallen (1998)', 'Falling in Love Again (1980)', 'Family Thing, A (1996)', 'Fan, The (1996)', 'Fantasia (1940)', 'Far From Home: The Adventures of Yellow Dog (1995)', 'Farewell My Concubine (1993)', 'Farewell to Arms, A (1932)', 'Fargo (1996)', 'Farinelli: il castrato (1994)', 'Farmer & Chase (1995)', 'Fast, Cheap & Out of Control (1997)', 'Faster Pussycat! Kill! Kill! (1965)', 'Fatal Instinct (1993)', 'Father of the Bride (1950)', 'Father of the Bride Part II (1995)', \"Fathers' Day (1997)\", 'Faust (1994)', 'Fausto (1993)', 'Favor, The (1994)', 'Fear (1996)', 'Fear of a Black Hat (1993)', 'Fear, The (1995)', 'Fearless (1993)', 'Feast of July (1995)', 'Feeling Minnesota (1996)', 'Female Perversions (1996)', 'Field of Dreams (1989)', 'Fierce Creatures (1997)', 'Fifth Element, The (1997)', 'Fille seule, La (A Single Girl) (1995)', 'Fire Down Below (1997)', 'Fire on the Mountain (1996)', 'Firestorm (1998)', 'Firm, The (1993)', 'First Kid (1996)', 'First Knight (1995)', 'First Wives Club, The (1996)', 'Fish Called Wanda, A (1988)', 'Fled (1996)', 'Flesh and Bone (1993)', 'Flintstones, The (1994)', 'Flipper (1996)', 'Flirt (1995)', 'Flirting With Disaster (1996)', 'Flower of My Secret, The (Flor de mi secreto, La) (1995)', 'Flubber (1997)', 'Fluke (1995)', 'Fly Away Home (1996)', 'Fog, The (1980)', 'Fools Rush In (1997)', 'For Ever Mozart (1996)', 'For Love or Money (1993)', 'For Richer or Poorer (1997)', 'For Whom the Bell Tolls (1943)', 'For the Moment (1994)', 'Forbidden Christ, The (Cristo proibito, Il) (1950)', 'Forbidden Planet (1956)', 'Foreign Correspondent (1940)', 'Foreign Student (1994)', 'Forget Paris (1995)', 'Forrest Gump (1994)', 'Four Days in September (1997)', 'Four Rooms (1995)', 'Four Weddings and a Funeral (1994)', 'Fox and the Hound, The (1981)', 'Foxfire (1996)', 'Frankie Starlight (1995)', 'Free Willy (1993)', 'Free Willy 2: The Adventure Home (1995)', 'Free Willy 3: The Rescue (1997)', 'Freeway (1996)', 'French Kiss (1995)', 'French Twist (Gazon maudit) (1995)', 'Fresh (1994)', 'Friday (1995)', 'Fried Green Tomatoes (1991)', 'Frighteners, The (1996)', 'Frisk (1995)', 'From Dusk Till Dawn (1996)', 'Fugitive, The (1993)', 'Full Metal Jacket (1987)', 'Full Monty, The (1997)', 'Full Speed (1996)', 'Funeral, The (1996)', 'Funny Face (1957)', 'Further Gesture, A (1996)', 'G.I. Jane (1997)', 'Gabbeh (1996)', 'Game, The (1997)', 'Gandhi (1982)', 'Gang Related (1997)', 'Garden of Finzi-Contini, The (Giardino dei Finzi-Contini, Il) (1970)', 'Gaslight (1944)', 'Gate of Heavenly Peace, The (1995)', 'Gattaca (1997)', 'Gay Divorcee, The (1934)', 'George of the Jungle (1997)', 'Georgia (1995)', 'Germinal (1993)', 'Geronimo: An American Legend (1993)', 'Get Shorty (1995)', 'Get on the Bus (1996)', 'Getaway, The (1994)', 'Getting Away With Murder (1996)', 'Getting Even with Dad (1994)', 'Ghost (1990)', 'Ghost and Mrs. Muir, The (1947)', 'Ghost and the Darkness, The (1996)', 'Ghost in the Shell (Kokaku kidotai) (1995)', 'Ghosts of Mississippi (1996)', 'Giant (1956)', 'Gigi (1958)', \"Gilligan's Island: The Movie (1998)\", 'Girl 6 (1996)', 'Girl in the Cadillac (1995)', 'Girls Town (1996)', 'Glass Shield, The (1994)', 'Glengarry Glen Ross (1992)', 'Glimmer Man, The (1996)', 'Glory (1989)', 'Go Fish (1994)', 'Godfather, The (1972)', 'Godfather: Part II, The (1974)', 'Gold Diggers: The Secret of Bear Mountain (1995)', 'Golden Earrings (1947)', 'GoldenEye (1995)', \"Gone Fishin' (1997)\", 'Gone with the Wind (1939)', 'Good Man in Africa, A (1994)', 'Good Morning (1971)', 'Good Will Hunting (1997)', 'Good, The Bad and The Ugly, The (1966)', 'GoodFellas (1990)', 'Goofy Movie, A (1995)', 'Gordy (1995)', 'Grace of My Heart (1996)', 'Graduate, The (1967)', 'Grand Day Out, A (1992)', 'Grass Harp, The (1995)', 'Grateful Dead (1995)', 'Grease (1978)', 'Grease 2 (1982)', 'Great Day in Harlem, A (1994)', 'Great Dictator, The (1940)', 'Great Escape, The (1963)', 'Great Expectations (1998)', 'Great Race, The (1965)', 'Great White Hype, The (1996)', \"Gridlock'd (1997)\", 'Grifters, The (1990)', 'Grosse Fatigue (1994)', 'Grosse Pointe Blank (1997)', 'Groundhog Day (1993)', 'Grumpier Old Men (1995)', 'Guantanamera (1994)', 'Guilty as Sin (1993)', 'Gumby: The Movie (1995)', 'Hackers (1995)', 'Half Baked (1998)', 'Halloween: The Curse of Michael Myers (1995)', 'Hamlet (1996)', 'Hana-bi (1997)', 'Happy Gilmore (1996)', 'Hard Eight (1996)', 'Hard Rain (1998)', 'Hard Target (1993)', 'Harlem (1993)', 'Harold and Maude (1971)', 'Harriet the Spy (1996)', 'Hate (Haine, La) (1995)', 'Haunted World of Edward D. Wood Jr., The (1995)', 'He Walked by Night (1948)', 'Head Above Water (1996)', 'Hear My Song (1991)', 'Hearts and Minds (1996)', 'Heat (1995)', 'Heathers (1989)', 'Heaven & Earth (1993)', \"Heaven's Prisoners (1996)\", 'Heavenly Creatures (1994)', 'Heavy (1995)', 'Heavy Metal (1981)', 'Heavyweights (1994)', 'Hedd Wyn (1992)', 'Heidi Fleiss: Hollywood Madam (1995) ', 'Hellraiser: Bloodline (1996)', 'Henry V (1989)', 'Herbie Rides Again (1974)', 'Hercules (1997)', 'Here Comes Cookie (1935)', 'Hideaway (1995)', 'High Noon (1952)', 'High School High (1996)', 'Higher Learning (1995)', 'Highlander (1986)', 'Highlander III: The Sorcerer (1994)', 'His Girl Friday (1940)', 'Hollow Reed (1996)', 'Homage (1995)', 'Home Alone (1990)', 'Home Alone 3 (1997)', 'Home for the Holidays (1995)', 'Homeward Bound II: Lost in San Francisco (1996)', 'Homeward Bound: The Incredible Journey (1993)', 'Hoodlum (1997)', 'Hoop Dreams (1994)', 'Horse Whisperer, The (1998)', 'Horseman on the Roof, The (Hussard sur le toit, Le) (1995)', 'Hostile Intentions (1994)', 'Hot Shots! Part Deux (1993)', 'Hotel de Love (1996)', 'Hour of the Pig, The (1993)', 'House Arrest (1996)', 'House Party 3 (1994)', 'House of Yes, The (1997)', 'House of the Spirits, The (1993)', 'Houseguest (1994)', 'How to Be a Player (1997)', 'How to Make an American Quilt (1995)', 'Howling, The (1981)', 'Hudsucker Proxy, The (1994)', 'Hugo Pool (1997)', 'Hunchback of Notre Dame, The (1996)', 'Hungarian Fairy Tale, A (1987)', 'Hunt for Red October, The (1990)', 'Hunted, The (1995)', 'Hurricane Streets (1998)', 'Hush (1998)', \"I Can't Sleep (J'ai pas sommeil) (1994)\", \"I Don't Want to Talk About It (De eso no se habla) (1993)\", 'I Know What You Did Last Summer (1997)', 'I Like It Like That (1994)', 'I Love Trouble (1994)', 'I Shot Andy Warhol (1996)', \"I'll Do Anything (1994)\", \"I'm Not Rappaport (1996)\", 'I, Worst of All (Yo, la peor de todas) (1990)', 'I.Q. (1994)', 'Ice Storm, The (1997)', 'If Lucy Fell (1996)', 'Ill Gotten Gains (1997)', 'Immortal Beloved (1994)', 'In & Out (1997)', 'In Love and War (1996)', 'In the Army Now (1994)', 'In the Bleak Midwinter (1995)', 'In the Company of Men (1997)', 'In the Line of Duty 2 (1987)', 'In the Line of Fire (1993)', 'In the Mouth of Madness (1995)', 'In the Name of the Father (1993)', 'In the Realm of the Senses (Ai no corrida) (1976)', 'Incognito (1997)', 'Independence Day (ID4) (1996)', 'Indian Summer (1996)', 'Indian in the Cupboard, The (1995)', 'Indiana Jones and the Last Crusade (1989)', 'Infinity (1996)', 'Inkwell, The (1994)', 'Innocent Sleep, The (1995)', 'Innocents, The (1961)', 'Inspector General, The (1949)', 'Interview with the Vampire (1994)', 'Intimate Relations (1996)', 'Inventing the Abbotts (1997)', 'Invitation, The (Zaproszenie) (1986)', 'Island of Dr. Moreau, The (1996)', 'It Could Happen to You (1994)', 'It Happened One Night (1934)', 'It Takes Two (1995)', \"It's My Party (1995)\", \"It's a Wonderful Life (1946)\", 'JLG/JLG - autoportrait de décembre (1994)', 'Jack (1996)', 'Jack and Sarah (1995)', 'Jackal, The (1997)', 'Jackie Brown (1997)', \"Jackie Chan's First Strike (1996)\", 'Jade (1995)', 'James and the Giant Peach (1996)', 'Jane Eyre (1996)', \"Jason's Lyric (1994)\", 'Jaws (1975)', 'Jaws 2 (1978)', 'Jaws 3-D (1983)', 'Jean de Florette (1986)', 'Jefferson in Paris (1995)', 'Jeffrey (1995)', 'Jerky Boys, The (1994)', 'Jerry Maguire (1996)', 'Jimmy Hollywood (1994)', 'Jingle All the Way (1996)', \"Joe's Apartment (1996)\", 'Johnny 100 Pesos (1993)', 'Johnny Mnemonic (1995)', 'Johns (1996)', 'Journey of August King, The (1995)', 'Joy Luck Club, The (1993)', 'Jude (1996)', 'Judge Dredd (1995)', 'Judgment Night (1993)', 'Jumanji (1995)', 'Jungle Book, The (1994)', 'Jungle2Jungle (1997)', 'Junior (1994)', \"Jupiter's Wife (1994)\", 'Jurassic Park (1993)', 'Juror, The (1996)', 'Jury Duty (1995)', 'Just Cause (1995)', 'Kalifornia (1993)', 'Kama Sutra: A Tale of Love (1996)', 'Kansas City (1996)', 'Kaspar Hauser (1993)', 'Kazaam (1996)', 'Keys to Tulsa (1997)', 'Kicked in the Head (1997)', 'Kicking and Screaming (1995)', \"Kid in King Arthur's Court, A (1995)\", 'Kids (1995)', 'Kids in the Hall: Brain Candy (1996)', 'Kika (1993)', 'Killer (Bulletproof Heart) (1994)', 'Killer: A Journal of Murder (1995)', 'Killing Fields, The (1984)', 'Killing Zoe (1994)', 'Kim (1950)', 'King of New York (1990)', 'King of the Hill (1993)', 'Kingpin (1996)', 'Kiss Me, Guido (1997)', 'Kiss of Death (1995)', 'Kiss the Girls (1997)', 'Kissed (1996)', 'Kolya (1996)', 'Koyaanisqatsi (1983)', 'Kull the Conqueror (1997)', 'Kundun (1997)', 'L.A. Confidential (1997)', 'Lady of Burlesque (1943)', 'Ladybird Ladybird (1994)', 'Lamerica (1994)', 'Land Before Time III: The Time of the Great Giving (1995) (V)', 'Land and Freedom (Tierra y libertad) (1995)', 'Larger Than Life (1996)', 'Lashou shentan (1992)', 'Lassie (1994)', 'Last Action Hero (1993)', 'Last Dance (1996)', 'Last Klezmer: Leopold Kozlowski, His Life and Music, The (1995)', 'Last Man Standing (1996)', 'Last Summer in the Hamptons (1995)', 'Last Supper, The (1995)', 'Last Time I Committed Suicide, The (1997)', 'Last Time I Saw Paris, The (1954)', 'Last of the Mohicans, The (1992)', 'Late Bloomers (1996)', 'Laura (1944)', 'Lawnmower Man 2: Beyond Cyberspace (1996)', 'Lawnmower Man, The (1992)', 'Lawrence of Arabia (1962)', 'Lay of the Land, The (1997)', 'Leading Man, The (1996)', 'Leave It to Beaver (1997)', 'Leaving Las Vegas (1995)', 'Legal Deceit (1997)', 'Legends of the Fall (1994)', 'Leopard Son, The (1996)', 'Letter From Death Row, A (1998)', 'Liar Liar (1997)', 'Liebelei (1933)', 'Life Less Ordinary, A (1997)', 'Life with Mikey (1993)', 'Lightning Jack (1994)', 'Like Water For Chocolate (Como agua para chocolate) (1992)', 'Line King: Al Hirschfeld, The (1996)', 'Lion King, The (1994)', 'Little Big League (1994)', 'Little Buddha (1993)', 'Little City (1998)', 'Little Lord Fauntleroy (1936)', 'Little Odessa (1994)', 'Little Princess, A (1995)', 'Little Princess, The (1939)', 'Little Rascals, The (1994)', 'Little Women (1994)', 'Live Nude Girls (1995)', 'Living in Oblivion (1995)', 'Loaded (1994)', 'Local Hero (1983)', 'Loch Ness (1995)', 'Locusts, The (1997)', 'Lone Star (1996)', 'Long Kiss Goodnight, The (1996)', 'Looking for Richard (1996)', 'Lord of Illusions (1995)', 'Losing Chase (1996)', 'Losing Isaiah (1995)', 'Lost Highway (1997)', 'Lost Horizon (1937)', 'Lost World: Jurassic Park, The (1997)', 'Lost in Space (1998)', 'Lotto Land (1995)', 'Love & Human Remains (1993)', 'Love Affair (1994)', 'Love Bug, The (1969)', 'Love Is All There Is (1996)', 'Love Jones (1997)', 'Love Serenade (1996)', 'Love and Death on Long Island (1997)', 'Love and Other Catastrophes (1996)', 'Love and a .45 (1994)', 'Love in the Afternoon (1957)', 'Love! Valour! Compassion! (1997)', \"Lover's Knot (1996)\", 'Low Down Dirty Shame, A (1994)', 'Low Life, The (1994)', 'M (1931)', 'M*A*S*H (1970)', 'M. Butterfly (1993)', 'MURDER and murder (1996)', 'Ma vie en rose (My Life in Pink) (1997)', 'Machine, The (1994)', 'Mad City (1997)', 'Mad Dog Time (1996)', 'Mad Love (1995)', 'Madame Butterfly (1995)', 'Made in America (1993)', 'Madness of King George, The (1994)', 'Madonna: Truth or Dare (1991)', 'Magic Hour, The (1998)', 'Magnificent Seven, The (1954)', 'Major Payne (1994)', 'Malice (1993)', 'Mallrats (1995)', 'Maltese Falcon, The (1941)', 'Mamma Roma (1962)', 'Man Who Knew Too Little, The (1997)', 'Man Who Would Be King, The (1975)', 'Man Without a Face, The (1993)', 'Man from Down Under, The (1943)', 'Man in the Iron Mask, The (1998)', 'Man of No Importance, A (1994)', 'Man of the House (1995)', 'Man of the Year (1995)', 'Manchurian Candidate, The (1962)', 'Manhattan (1979)', 'Manhattan Murder Mystery (1993)', 'Manny & Lo (1996)', 'Manon of the Spring (Manon des sources) (1986)', \"Margaret's Museum (1995)\", 'Mark of Zorro, The (1940)', 'Marked for Death (1990)', 'Marlene Dietrich: Shadow and Light (1996) ', 'Mars Attacks! (1996)', \"Marvin's Room (1996)\", 'Mary Poppins (1964)', 'Mary Reilly (1996)', \"Mary Shelley's Frankenstein (1994)\", 'Mask, The (1994)', \"Mat' i syn (1997)\", 'MatchMaker, The (1997)', 'Matilda (1996)', 'Maverick (1994)', 'Maximum Risk (1996)', 'Maya Lin: A Strong Clear Vision (1994)', 'Maybe, Maybe Not (Bewegte Mann, Der) (1994)', \"McHale's Navy (1997)\", 'Mediterraneo (1991)', 'Meet John Doe (1941)', 'Meet Me in St. Louis (1944)', 'Meet Wally Sparks (1997)', 'Men With Guns (1997)', 'Men in Black (1997)', 'Men of Means (1998)', 'Menace II Society (1993)', 'Mercury Rising (1998)', 'Metisse (Café au Lait) (1993)', 'Metro (1997)', 'Miami Rhapsody (1995)', 'Michael (1996)', 'Michael Collins (1996)', \"Microcosmos: Le peuple de l'herbe (1996)\", 'Midnight Dancers (Sibak) (1994)', 'Midnight in the Garden of Good and Evil (1997)', 'Mighty Aphrodite (1995)', 'Mighty Morphin Power Rangers: The Movie (1995)', 'Mighty, The (1998)', 'Milk Money (1994)', 'Mille bolle blu (1993)', \"Miller's Crossing (1990)\", 'Mimic (1997)', 'Mina Tannenbaum (1994)', 'Miracle on 34th Street (1994)', 'Mirage (1995)', 'Mirror Has Two Faces, The (1996)', 'Mission: Impossible (1996)', 'Misérables, Les (1995)', 'Mixed Nuts (1994)', 'Modern Affair, A (1995)', 'Moll Flanders (1996)', 'Mondo (1996)', 'Money Talks (1997)', 'Money Train (1995)', 'Month by the Lake, A (1995)', 'Monty Python and the Holy Grail (1974)', \"Monty Python's Life of Brian (1979)\", 'Moonlight and Valentino (1995)', 'Mortal Kombat (1995)', 'Mortal Kombat: Annihilation (1997)', 'Mostro, Il (1994)', 'Mother (1996)', 'Mother Night (1996)', 'Mouse Hunt (1997)', \"Mr. Holland's Opus (1995)\", 'Mr. Jones (1993)', 'Mr. Magoo (1997)', 'Mr. Smith Goes to Washington (1939)', 'Mr. Wonderful (1993)', 'Mr. Wrong (1996)', 'Mrs. Brown (Her Majesty, Mrs. Brown) (1997)', 'Mrs. Dalloway (1997)', 'Mrs. Doubtfire (1993)', 'Mrs. Parker and the Vicious Circle (1994)', 'Mrs. Winterbourne (1996)', 'Much Ado About Nothing (1993)', 'Mulholland Falls (1996)', 'Multiplicity (1996)', 'Muppet Treasure Island (1996)', 'Murder at 1600 (1997)', 'Murder in the First (1995)', 'Murder, My Sweet (1944)', \"Muriel's Wedding (1994)\", 'Mute Witness (1994)', \"My Best Friend's Wedding (1997)\", 'My Crazy Life (Mi vida loca) (1993)', 'My Fair Lady (1964)', 'My Family (1995)', 'My Favorite Season (1993)', 'My Favorite Year (1982)', 'My Fellow Americans (1996)', 'My Left Foot (1989)', \"My Life and Times With Antonin Artaud (En compagnie d'Antonin Artaud) (1993)\", 'My Life as a Dog (Mitt liv som hund) (1985)', 'My Man Godfrey (1936)', 'My Own Private Idaho (1991)', 'Mystery Science Theater 3000: The Movie (1996)', 'Nadja (1994)', 'Naked (1993)', 'Naked Gun 33 1/3: The Final Insult (1994)', 'Naked in New York (1994)', \"National Lampoon's Senior Trip (1995)\", 'Natural Born Killers (1994)', 'Nell (1994)', 'Nelly & Monsieur Arnaud (1995)', 'Nemesis 2: Nebula (1995)', 'Neon Bible, The (1995)', 'Net, The (1995)', 'NeverEnding Story III, The (1994)', 'New Age, The (1994)', 'New Jersey Drive (1995)', 'New York Cop (1996)', 'Newton Boys, The (1998)', 'Next Karate Kid, The (1994)', 'Next Step, The (1995)', 'Niagara, Niagara (1997)', 'Nick of Time (1995)', 'Nico Icon (1995)', 'Night Falls on Manhattan (1997)', 'Night Flier (1997)', 'Night of the Living Dead (1968)', 'Night on Earth (1991)', 'Nightmare Before Christmas, The (1993)', 'Nightmare on Elm Street, A (1984)', 'Nightwatch (1997)', 'Nikita (La Femme Nikita) (1990)', 'Nil By Mouth (1997)', 'Nina Takes a Lover (1994)', 'Nine Months (1995)', 'Ninotchka (1939)', 'Nixon (1995)', 'No Escape (1994)', 'Nobody Loves Me (Keiner liebt mich) (1994)', \"Nobody's Fool (1994)\", 'Normal Life (1996)', 'North (1994)', 'North by Northwest (1959)', 'Nosferatu (Nosferatu, eine Symphonie des Grauens) (1922)', 'Nosferatu a Venezia (1986)', 'Nothing Personal (1995)', 'Nothing to Lose (1994)', 'Notorious (1946)', 'Now and Then (1995)', 'Nowhere (1997)', 'Nutty Professor, The (1996)', 'Nénette et Boni (1996)', 'Object of My Affection, The (1998)', 'Of Human Bondage (1934)', 'Of Love and Shadows (1994)', 'Office Killer (1997)', 'Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)', 'Old Man and the Sea, The (1958)', 'Old Yeller (1957)', 'Oliver & Company (1988)', 'Omen, The (1976)', 'On Golden Pond (1981)', 'Once Upon a Time in America (1984)', 'Once Upon a Time in the West (1969)', 'Once Upon a Time... When We Were Colored (1995)', 'Once Were Warriors (1994)', 'One Fine Day (1996)', \"One Flew Over the Cuckoo's Nest (1975)\", 'One Night Stand (1997)', 'Only You (1994)', 'Open Season (1996)', 'Operation Dumbo Drop (1995)', 'Original Gangstas (1996)', 'Orlando (1993)', 'Oscar & Lucinda (1997)', 'Othello (1995)', 'Other Voices, Other Rooms (1997)', 'Out to Sea (1997)', 'Outbreak (1995)', 'Outlaw, The (1943)', 'Pagemaster, The (1994)', 'Pallbearer, The (1996)', 'Palmetto (1998)', 'Palookaville (1996)', 'Panther (1995)', 'Paper, The (1994)', 'Paradise Lost: The Child Murders at Robin Hood Hills (1996)', 'Paradise Road (1997)', 'Parent Trap, The (1961)', 'Paris Is Burning (1990)', 'Paris Was a Woman (1995)', 'Paris, France (1993)', 'Paris, Texas (1984)', 'Party Girl (1995)', 'Passion Fish (1992)', 'Pather Panchali (1955)', 'Paths of Glory (1957)', 'Patton (1970)', 'Peacemaker, The (1997)', 'Penny Serenade (1941)', 'People vs. Larry Flynt, The (1996)', 'Perez Family, The (1995)', 'Perfect Candidate, A (1996)', 'Perfect World, A (1993)', 'Persuasion (1995)', 'Pest, The (1997)', \"Pete's Dragon (1977)\", 'Phantom, The (1996)', 'Phantoms (1998)', \"Pharaoh's Army (1995)\", 'Phat Beach (1996)', 'Phenomenon (1996)', 'Philadelphia (1993)', 'Philadelphia Story, The (1940)', 'Piano, The (1993)', 'Picnic (1955)', 'Picture Bride (1995)', 'Picture Perfect (1997)', 'Pie in the Sky (1995)', 'Pillow Book, The (1995)', 'Pink Floyd - The Wall (1982)', 'Pinocchio (1940)', 'Platoon (1986)', 'Playing God (1997)', 'Pocahontas (1995)', 'Poetic Justice (1993)', 'Poison Ivy II (1995)', 'Police Story 4: Project S (Chao ji ji hua) (1993)', 'Pollyanna (1960)', 'Pompatus of Love, The (1996)', 'Ponette (1996)', 'Portrait of a Lady, The (1996)', 'Postino, Il (1994)', 'Postman, The (1997)', 'Powder (1995)', 'Power 98 (1995)', \"Preacher's Wife, The (1996)\", 'Prefontaine (1997)', 'Pretty Woman (1990)', 'Price Above Rubies, A (1998)', 'Priest (1994)', 'Primal Fear (1996)', 'Primary Colors (1998)', 'Princess Bride, The (1987)', 'Princess Caraboo (1994)', 'Prisoner of the Mountains (Kavkazsky Plennik) (1996)', 'Private Benjamin (1980)', 'Private Parts (1997)', 'Professional, The (1994)', 'Program, The (1993)', 'Promesse, La (1996)', 'Promise, The (Versprechen, Das) (1994)', 'Prophecy II, The (1998)', 'Prophecy, The (1995)', 'Psycho (1960)', 'Pulp Fiction (1994)', 'Pump Up the Volume (1990)', 'Purple Noon (1960)', 'Pushing Hands (1992)', \"Pyromaniac's Love Story, A (1995)\", 'Quartier Mozart (1992)', 'Queen Margot (Reine Margot, La) (1994)', 'Quest, The (1996)', 'Quick and the Dead, The (1995)', 'Quiet Man, The (1952)', 'Quiet Room, The (1996)', 'Quiz Show (1994)', 'Race the Sun (1996)', 'Radioland Murders (1994)', 'Raging Bull (1980)', 'Raiders of the Lost Ark (1981)', 'Rainmaker, The (1997)', 'Raise the Red Lantern (1991)', 'Raising Arizona (1987)', 'Ran (1985)', 'Ransom (1996)', 'Raw Deal (1948)', 'Ready to Wear (Pret-A-Porter) (1994)', 'Real Genius (1985)', 'Reality Bites (1994)', 'Rear Window (1954)', 'Rebecca (1940)', 'Rebel Without a Cause (1955)', 'Reckless (1995)', 'Red Corner (1997)', 'Red Firecracker, Green Firecracker (1994)', 'Red Rock West (1992)', 'Ref, The (1994)', 'Relative Fear (1994)', 'Relic, The (1997)', 'Reluctant Debutante, The (1958)', 'Remains of the Day, The (1993)', 'Renaissance Man (1994)', 'Rendezvous in Paris (Rendez-vous de Paris, Les) (1995)', 'Rent-a-Kid (1995)', 'Replacement Killers, The (1998)', 'Reservoir Dogs (1992)', 'Restoration (1995)', 'Return of Martin Guerre, The (Retour de Martin Guerre, Le) (1982)', 'Return of the Jedi (1983)', 'Return of the Pink Panther, The (1974)', 'Rhyme & Reason (1997)', \"Rich Man's Wife, The (1996)\", 'Richard III (1995)', 'Richie Rich (1994)', 'Ridicule (1996)', 'Right Stuff, The (1983)', 'Ripe (1996)', 'Rising Sun (1993)', 'River Wild, The (1994)', 'Road to Wellville, The (1994)', 'Rob Roy (1995)', \"Robert A. Heinlein's The Puppet Masters (1994)\", 'Robin Hood: Men in Tights (1993)', 'Robin Hood: Prince of Thieves (1991)', 'Robocop 3 (1993)', 'Rock, The (1996)', 'Rocket Man (1997)', 'Roman Holiday (1953)', 'Romeo Is Bleeding (1993)', 'Romper Stomper (1992)', \"Romy and Michele's High School Reunion (1997)\", 'Room with a View, A (1986)', 'Roommates (1995)', \"Roseanna's Grave (For Roseanna) (1997)\", 'Rosencrantz and Guildenstern Are Dead (1990)', 'Rosewood (1997)', 'Rough Magic (1995)', 'Ruby in Paradise (1993)', 'Rudy (1993)', 'Ruling Class, The (1972)', 'Rumble in the Bronx (1995)', 'Run of the Country, The (1995)', 'S.F.W. (1994)', 'Sabrina (1954)', 'Sabrina (1995)', 'Safe (1995)', 'Safe Passage (1994)', 'Saint of Fort Washington, The (1993)', 'Saint, The (1997)', 'Salut cousin! (1996)', 'Santa Clause, The (1994)', 'Santa with Muscles (1996)', 'Savage Nights (Nuits fauves, Les) (1992)', 'Scarlet Letter, The (1926)', 'Scarlet Letter, The (1995)', \"Schindler's List (1993)\", 'Schizopolis (1996)', 'Scout, The (1994)', 'Scream (1996)', 'Scream 2 (1997)', 'Scream of Stone (Schrei aus Stein) (1991)', 'Screamers (1995)', 'Search for One-eye Jimmy, The (1996)', 'Searching for Bobby Fischer (1993)', 'Second Jungle Book: Mowgli & Baloo, The (1997)', 'Secret Adventures of Tom Thumb, The (1993)', 'Secret Agent, The (1996)', 'Secret Garden, The (1993)', 'Secret of Roan Inish, The (1994)', 'Secrets & Lies (1996)', 'Selena (1997)', 'Sense and Sensibility (1995)', 'Senseless (1998)', 'Serial Mom (1994)', 'Set It Off (1996)', 'Seven (Se7en) (1995)', 'Seven Years in Tibet (1997)', 'Seventh Seal, The (Sjunde inseglet, Det) (1957)', 'Sex, Lies, and Videotape (1989)', 'Sexual Life of the Belgians, The (1994)', 'Sgt. Bilko (1996)', 'Shadow Conspiracy (1997)', 'Shadow of Angels (Schatten der Engel) (1976)', 'Shadow, The (1994)', 'Shadowlands (1993)', 'Shadows (Cienie) (1988)', 'Shaggy Dog, The (1959)', 'Shall We Dance? (1937)', 'Shall We Dance? (1996)', 'Shallow Grave (1994)', 'Shanghai Triad (Yao a yao yao dao waipo qiao) (1995)', 'Shawshank Redemption, The (1994)', \"She's So Lovely (1997)\", \"She's the One (1996)\", 'Shiloh (1997)', 'Shine (1996)', 'Shining, The (1980)', 'Shooter, The (1995)', 'Shooting Fish (1997)', 'Shopping (1994)', 'Short Cuts (1993)', 'Show, The (1995)', 'Showgirls (1995)', 'Silence of the Lambs, The (1991)', 'Silence of the Palace, The (Saimt el Qusur) (1994)', 'Simple Twist of Fate, A (1994)', 'Simple Wish, A (1997)', \"Singin' in the Rain (1952)\", 'Sirens (1994)', 'Six Degrees of Separation (1993)', 'Sixth Man, The (1997)', 'Sleeper (1973)', 'Sleepers (1996)', 'Sleepless in Seattle (1993)', 'Sleepover (1995)', 'Sliding Doors (1998)', 'Sling Blade (1996)', 'Slingshot, The (1993)', 'Sliver (1993)', 'Small Faces (1995)', 'Smile Like Yours, A (1997)', \"Smilla's Sense of Snow (1997)\", 'Smoke (1995)', 'Sneakers (1992)', 'Snow White and the Seven Dwarfs (1937)', 'So Dear to My Heart (1949)', 'So I Married an Axe Murderer (1993)', 'Solo (1996)', 'Some Folks Call It a Sling Blade (1993)', 'Some Kind of Wonderful (1987)', 'Some Like It Hot (1959)', \"Some Mother's Son (1996)\", 'Somebody to Love (1994)', \"Someone Else's America (1995)\", 'Something to Talk About (1995)', 'Somewhere in Time (1980)', 'Son in Law (1993)', \"Sophie's Choice (1982)\", 'Soul Food (1997)', 'Sound of Music, The (1965)', 'Space Jam (1996)', 'Spanish Prisoner, The (1997)', 'Spanking the Monkey (1994)', 'Spawn (1997)', 'Specialist, The (1994)', 'Species (1995)', 'Speechless (1994)', 'Speed (1994)', 'Speed 2: Cruise Control (1997)', 'Spellbound (1945)', 'Sphere (1998)', 'Spice World (1997)', 'Spirits of the Dead (Tre passi nel delirio) (1968)', 'Spitfire Grill, The (1996)', 'Sprung (1997)', 'Spy Hard (1996)', 'Squeeze (1996)', 'Stag (1997)', 'Stalingrad (1993)', 'Stalker (1979)', 'Stand by Me (1986)', 'Star Kid (1997)', \"Star Maker, The (Uomo delle stelle, L') (1995)\", 'Star Maps (1997)', 'Star Trek III: The Search for Spock (1984)', 'Star Trek IV: The Voyage Home (1986)', 'Star Trek V: The Final Frontier (1989)', 'Star Trek VI: The Undiscovered Country (1991)', 'Star Trek: First Contact (1996)', 'Star Trek: Generations (1994)', 'Star Trek: The Motion Picture (1979)', 'Star Trek: The Wrath of Khan (1982)', 'Star Wars (1977)', 'Stargate (1994)', 'Stars Fell on Henrietta, The (1995)', 'Starship Troopers (1997)', 'Steal Big, Steal Little (1995)', 'Stealing Beauty (1996)', 'Steel (1997)', 'Stefano Quantestorie (1993)', \"Stephen King's The Langoliers (1995)\", 'Sting, The (1973)', 'Stonewall (1995)', 'Story of Xinghua, The (1993)', 'Strange Days (1995)', 'Stranger in the House (1997)', 'Stranger, The (1994)', 'Strawberry and Chocolate (Fresa y chocolate) (1993)', 'Street Fighter (1994)', 'Streetcar Named Desire, A (1951)', 'Strictly Ballroom (1992)', 'Striking Distance (1993)', 'Stripes (1981)', 'Striptease (1996)', 'Stuart Saves His Family (1995)', 'Stupids, The (1996)', 'SubUrbia (1997)', 'Substance of Fire, The (1996)', 'Substitute, The (1996)', 'Sudden Death (1995)', 'Sudden Manhattan (1996)', 'Sum of Us, The (1994)', 'Sunchaser, The (1996)', 'Sunset Blvd. (1950)', 'Sunset Park (1996)', 'Super Mario Bros. (1993)', 'Supercop (1992)', 'Surviving Picasso (1996)', 'Surviving the Game (1994)', 'Suture (1993)', 'Swan Princess, The (1994)', 'Sweet Hereafter, The (1997)', 'Sweet Nothing (1995)', 'Swept from the Sea (1997)', 'Swimming with Sharks (1995)', 'Swingers (1996)', 'Swiss Family Robinson (1960)', 'Switchback (1997)', 'Switchblade Sisters (1975)', 'Sword in the Stone, The (1963)', 'Symphonie pastorale, La (1946)', 'T-Men (1947)', 'Tainted (1998)', 'Tales From the Crypt Presents: Demon Knight (1995)', 'Tales from the Crypt Presents: Bordello of Blood (1996)', 'Tales from the Hood (1995)', 'Talking About Sex (1994)', 'Tango Lesson, The (1997)', 'Tank Girl (1995)', 'Target (1995)', 'Taxi Driver (1976)', 'Telling Lies in America (1997)', 'Temptress Moon (Feng Yue) (1996)', 'Terminal Velocity (1994)', 'Terminator 2: Judgment Day (1991)', 'Terminator, The (1984)', 'Terror in a Texas Town (1958)', 'Tetsuo II: Body Hammer (1992)', 'That Darn Cat! (1965)', 'That Darn Cat! (1997)', 'That Old Feeling (1997)', 'That Thing You Do! (1996)', 'The Courtyard (1995)', 'The Deadly Cure (1996)', 'The Innocent (1994)', 'Theodore Rex (1995)', 'They Made Me a Criminal (1939)', 'Thieves (Voleurs, Les) (1996)', 'Thin Blue Line, The (1988)', 'Thin Line Between Love and Hate, A (1996)', 'Thin Man, The (1934)', \"Things to Do in Denver when You're Dead (1995)\", 'Thinner (1996)', 'Third Man, The (1949)', 'Thirty-Two Short Films About Glenn Gould (1993)', 'This Is Spinal Tap (1984)', 'Thousand Acres, A (1997)', 'Three Caballeros, The (1945)', 'Three Colors: Blue (1993)', 'Three Colors: Red (1994)', 'Three Colors: White (1994)', 'Three Lives and Only One Death (1996)', 'Three Musketeers, The (1993)', 'Three Wishes (1995)', 'Threesome (1994)', 'Tie Me Up! Tie Me Down! (1990)', 'Tie That Binds, The (1995)', 'Tigrero: A Film That Was Never Made (1994)', 'Time Tracers (1995)', 'Time to Kill, A (1996)', 'Timecop (1994)', 'Tin Cup (1996)', 'Tin Drum, The (Blechtrommel, Die) (1979)', 'Tin Men (1987)', 'Titanic (1997)', 'To Be or Not to Be (1942)', 'To Catch a Thief (1955)', 'To Cross the Rubicon (1991)', 'To Die For (1995)', 'To Gillian on Her 37th Birthday (1996)', 'To Have, or Not (1995)', 'To Kill a Mockingbird (1962)', 'To Live (Huozhe) (1994)', 'To Wong Foo, Thanks for Everything! Julie Newmar (1995)', 'Tokyo Fist (1995)', 'Tom & Viv (1994)', 'Tom and Huck (1995)', 'Tombstone (1993)', 'Tommy Boy (1995)', 'Tomorrow Never Dies (1997)', 'Top Gun (1986)', 'Top Hat (1935)', 'Total Eclipse (1995)', 'Touch (1997)', 'Touch of Evil (1958)', 'Tough and Deadly (1995)', 'Touki Bouki (Journey of the Hyena) (1973)', 'Toy Story (1995)', 'Trainspotting (1996)', 'Transformers: The Movie, The (1986)', 'Traveller (1997)', 'Treasure of the Sierra Madre, The (1948)', 'Trees Lounge (1996)', 'Trial and Error (1997)', 'Trial by Jury (1994)', 'Trigger Effect, The (1996)', 'True Crime (1995)', 'True Lies (1994)', 'True Romance (1993)', 'Truman Show, The (1998)', 'Trust (1990)', 'Truth About Cats & Dogs, The (1996)', 'Truth or Consequences, N.M. (1997)', 'Turbo: A Power Rangers Movie (1997)', 'Turbulence (1997)', 'Turning, The (1992)', 'Twelfth Night (1996)', 'Twelve Monkeys (1995)', 'Twilight (1998)', 'Twin Town (1997)', 'Twisted (1996)', 'Twister (1996)', 'Two Bits (1995)', 'Two Deaths (1995)', 'Two Friends (1986) ', 'Two Much (1996)', 'Two if by Sea (1996)', 'Two or Three Things I Know About Her (1966)', 'U Turn (1997)', 'U.S. Marshalls (1998)', \"Ulee's Gold (1997)\", 'Umbrellas of Cherbourg, The (Parapluies de Cherbourg, Les) (1964)', 'Unbearable Lightness of Being, The (1988)', 'Under Siege (1992)', 'Under Siege 2: Dark Territory (1995)', 'Underground (1995)', 'Underneath, The (1995)', 'Underworld (1997)', 'Unforgettable (1996)', 'Unforgiven (1992)', 'Unhook the Stars (1996)', 'Unstrung Heroes (1995)', 'Until the End of the World (Bis ans Ende der Welt) (1991)', 'Unzipped (1995)', 'Up Close and Personal (1996)', 'Up in Smoke (1978)', 'Usual Suspects, The (1995)', 'Vampire in Brooklyn (1995)', 'Van, The (1996)', 'Vanya on 42nd Street (1994)', 'Vegas Vacation (1997)', 'Venice/Venice (1992)', 'Vermin (1998)', 'Vermont Is For Lovers (1992)', 'Vertigo (1958)', 'Very Brady Sequel, A (1996)', 'Very Natural Thing, A (1974)', 'Victor/Victoria (1982)', 'Vie est belle, La (Life is Rosey) (1987)', 'Village of the Damned (1995)', 'Virtuosity (1995)', 'Visitors, The (Visiteurs, Les) (1993)', 'Volcano (1997)', 'Wag the Dog (1997)', 'Waiting for Guffman (1996)', 'Waiting to Exhale (1995)', 'Walk in the Clouds, A (1995)', 'Walk in the Sun, A (1945)', 'Walkabout (1971)', 'Walking Dead, The (1995)', 'Walking and Talking (1996)', 'Wallace & Gromit: The Best of Aardman Animation (1996)', 'War Room, The (1993)', 'War at Home, The (1996)', 'War, The (1994)', 'Warriors of Virtue (1997)', 'Washington Square (1997)', 'Waterworld (1995)', 'Wedding Bell Blues (1996)', 'Wedding Gift, The (1994)', 'Wedding Singer, The (1998)', \"Weekend at Bernie's (1989)\", 'Welcome To Sarajevo (1997)', 'Welcome to the Dollhouse (1995)', \"Wend Kuuni (God's Gift) (1982)\", \"Wes Craven's New Nightmare (1994)\", 'What Happened Was... (1994)', \"What's Eating Gilbert Grape (1993)\", \"What's Love Got to Do with It (1993)\", 'When Harry Met Sally... (1989)', 'When Night Is Falling (1995)', 'When We Were Kings (1996)', 'When a Man Loves a Woman (1994)', 'When the Cats Away (Chacun cherche son chat) (1996)', 'While You Were Sleeping (1995)', 'White Balloon, The (1995)', \"White Man's Burden (1995)\", 'White Squall (1996)', 'Whole Wide World, The (1996)', \"Widows' Peak (1994)\", 'Wife, The (1995)', 'Wild America (1997)', 'Wild Bill (1995)', 'Wild Bunch, The (1969)', 'Wild Reeds (1994)', 'Wild Things (1998)', \"William Shakespeare's Romeo and Juliet (1996)\", 'Willy Wonka and the Chocolate Factory (1971)', 'Window to Paris (1994)', 'Wings of Courage (1995)', 'Wings of Desire (1987)', 'Wings of the Dove, The (1997)', 'Winnie the Pooh and the Blustery Day (1968)', 'Winter Guest, The (1997)', 'Wishmaster (1997)', 'With Honors (1994)', 'Withnail and I (1987)', 'Witness (1985)', 'Wizard of Oz, The (1939)', 'Wolf (1994)', 'Woman in Question, The (1950)', 'Women, The (1939)', 'Wonderful, Horrible Life of Leni Riefenstahl, The (1993)', 'Wonderland (1997)', \"Wooden Man's Bride, The (Wu Kui) (1994)\", 'World of Apu, The (Apur Sansar) (1959)', 'Wrong Trousers, The (1993)', 'Wyatt Earp (1994)', 'Yankee Zulu (1994)', 'Year of the Horse (1997)', 'You So Crazy (1994)', 'Young Frankenstein (1974)', 'Young Guns (1988)', 'Young Guns II (1990)', \"Young Poisoner's Handbook, The (1995)\", 'Zeus and Roxanne (1997)', 'unknown', 'Á köldum klaka (Cold Fever) (1994)'],\n",
              " 'user': ['#na#', 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943]}"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BoOfG0eItvkx",
        "outputId": "c778c743-aded-401e-8529-eb0db537b3ec"
      },
      "source": [
        "# Initializing the parameters for our user and movie matrices \n",
        "n_users = len(dls.classes['user'])\n",
        "n_movies = len(dls.classes['title'])\n",
        "\n",
        "# The latent factors is 5 for now \n",
        "n_factors = 5\n",
        "\n",
        "# Creating the weight matrices by randomly initializing the parameters \n",
        "user_factors = torch.randn(n_users , n_factors)\n",
        "movie_factors = torch.randn(n_movies , n_factors)\n",
        "\n",
        "print(n_users , n_movies)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "944 1665\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xCJcXIWeubvk",
        "outputId": "1acc2a51-3c6d-4f71-d5cf-bba867b4ea2f"
      },
      "source": [
        "# How does the user_factors look like? \n",
        "user_factors[:5] # intializing random parameters for the 5 latent factors "
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[ 0.5298,  0.9391, -1.2739, -1.6505,  0.5364],\n",
              "        [ 0.1157, -0.9186, -0.1454, -1.2527,  1.2772],\n",
              "        [-1.2634, -1.6158,  0.0313,  0.2093,  1.4688],\n",
              "        [ 0.8656,  1.6587, -0.4650,  1.1380,  0.2891],\n",
              "        [ 0.2178,  2.0728, -0.1768,  1.7642, -0.2719]])"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A1bTHbhVuism",
        "outputId": "bd73593c-e1e4-463d-c6c4-69a8fe6d0e94"
      },
      "source": [
        "one_hot(3 , 944).float()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
              "        0., 0., 0., 0., 0., 0., 0., 0.])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8zlIq1pkyoBK"
      },
      "source": [
        "We got the matrix, but how do we optimize the latent factors for each movie and user? We have to locate each latent factors of the at particular movie and user in order to optimize it. But *look up in an index* is not an operation our deeplearning model knows how to do. \n",
        "\n",
        "For this reason we use **one-hot encoding** so that we can represent *look up in an index* as a matrix product. The trick is to replace our indices with one-hot encoded vectors . "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k5hr9hcfzO7T"
      },
      "source": [
        "# Trying to locate the index 3 \n",
        "one_hot_3 = one_hot(3 , n_users).float()"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NIW3BCFR4hDu",
        "outputId": "116f063b-0ad9-43fe-8997-faac80759c94"
      },
      "source": [
        "# Performing loo up an index \n",
        "print(f'Locating by using the one hot encoding: {user_factors.t() @ one_hot_3}\\n') \n",
        "print(user_factors[3])"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Locating by using the one hot encoding: tensor([ 0.8656,  1.6587, -0.4650,  1.1380,  0.2891])\n",
            "\n",
            "tensor([ 0.8656,  1.6587, -0.4650,  1.1380,  0.2891])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "InkQH2m-4qQe"
      },
      "source": [
        "But we cant do this manually for every indices and the latent feture, because it would use a lot more memory and time. \n",
        "\n",
        "Also we know there is no underlying reason to store the one-hot encoded vector and search using it. What if we can do the *look up* into a array directly with an integer itself `user_factor[3]`?\n",
        "\n",
        "Therefore most deeplearning libraries including Pytorch, include a special layer that does just this: \n",
        "- **it indexes into a vector using an integer, but has its derivative calculated in such a way that it is identical to what it owuld have been if it had done a matrix multiplication with a one-hot encoded vector.**\n",
        "\n",
        "This is called Embedding. \n",
        "\n",
        "> **Embedding**: Multiplying by a one-hot encoded matrix, using the computational shortcut that it can implemented by simpply indexing directly. This is quite a fancy word for a very simple concept. The thing that you multiply the one-hot encoded matriix by (or , using the computational shortcut, index into directly) is called the embedding matrix. \n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zMq25ZIK59_g"
      },
      "source": [
        "In a computer vision we had the RGB values which is enough to get our model to work afterward. \n",
        "\n",
        "But for this collaborative filtering, we dont have the same easy way to characterize a user or a movie. There are probably relations with genres. \n",
        "- **If a given user likes romance, they are likely to give higher scores to romance movies**\n",
        "\n",
        "Other factors might be whether the movie is more action oriented versus heavy on dialogue, or the presence of specific actor that a user might like. \n",
        "\n",
        "How do we determine numbers to characterize those? The answer is, we don't rather we will let our model learn them. By analyzing the existing relations bwteen users and movies, our model can figure out itself the features that seem important or not. \n",
        "\n",
        "This is what embeddings are,\n",
        "- we will attribute to each of our users each of our movies a random vector of a certain length (here,  n_factors = 5)\n",
        "- we will make those learnable parameters (those vector will be learning patterns). \n",
        "- so that means at each step, when we compute the loss by comparing our predictions to our targets, we will compute the gradients of the loss w.r.t those embedding vectors and update them with the rule oof SGD (or another optimizer). \n",
        "\n",
        "At the beginning, those numbers don't mean anything but by the end of training, they will. \n",
        "\n",
        "By learning on existing data about the relations between users and movies, without having any other information we will see that they still get some important features, and can later isolate blockbusters from other movies..."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UywA0c0CCZEM"
      },
      "source": [
        "**Important tidbits** \n",
        "- We use `nn.Embedding` to represent our matrix, but we can use it as an lookup-index and also these embeddings are trainable. This means as the epochs goes, the embeddings will learn patterns around the data for better representation. \n",
        "- For the Colab Filtering, every element has a certain latent features that defines the attributes of the features. \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bR2O4G2CmsOD"
      },
      "source": [
        "# Building the DotProduct from scratch \n",
        "class DotProduct(nn.Module):\n",
        "\n",
        "  def __init__(self , n_users,  n_movies , n_factors):\n",
        "    super(DotProduct , self).__init__()\n",
        "\n",
        "    self.user_factors = nn.Embedding(n_users, n_factors)\n",
        "    self.movie_factors = nn.Embedding(n_movies , n_factors)\n",
        "\n",
        "  # The forward method (which defines the model)\n",
        "  def forward(self , x):\n",
        "    users = self.user_factors(x[: , 0]) # indexing the user ids \n",
        "    movies = self.movie_factors(x[: , 1]) # indexing the movie ids \n",
        "    return (users*movies).sum(dim = 1)"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZlCsknUpn4J7"
      },
      "source": [
        "model = DotProduct(n_users , n_movies , n_factors= 50)\n",
        "\n",
        "\n",
        "# Taking a batch of the dataloaders \n",
        "x , y = dls.one_batch()"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9SwfQ_V_oFFY"
      },
      "source": [
        "# Creating a learner out of the model we've created \n",
        "learn = Learner(dls , model , loss_func = MSELossFlat())"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jufBm5pDoXFx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "eb14637f-b511-4cfa-aa58-cd839ab71a3f"
      },
      "source": [
        "# Training for 5 epochs \n",
        "learn.fit_one_cycle(5 , 5e-3)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <td>1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>7.617049</td>\n",
              "      <td>11.998022</td>\n",
              "      <td>00:09</td>\n",
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              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>3.611437</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>2.728474</td>\n",
              "      <td>7.993670</td>\n",
              "      <td>00:08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
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          },
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "urE2GDpLobfd"
      },
      "source": [
        "The models performance isn't any good, lets force those predictions to be between 0 and 5 by using a `sigmoid_range`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HYIYBYiJokt4"
      },
      "source": [
        "class DotProduct(nn.Module):\n",
        "\n",
        "  def __init__(self , n_users, n_movies, n_factors , y_range = (0, 5.5)):\n",
        "    super(DotProduct , self).__init__()\n",
        "\n",
        "    self.user_factors = Embedding(n_users, n_factors)\n",
        "    self.movie_factors = Embedding(n_movies, n_factors)\n",
        "    self.y_range = y_range \n",
        "\n",
        "  def forward(self , x):\n",
        "    users = self.user_factors(x[: ,0])\n",
        "    movies = self.movie_factors(x[: ,1])\n",
        "    return sigmoid_range((users*movies).sum(dim = 1) , *self.y_range)\n"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "47gpfVkBq0xQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "ecf29ef7-8245-4c29-8a3c-0252b82b7251"
      },
      "source": [
        "# Training the model again with a sigmoid range\n",
        "model = DotProduct(n_users, n_movies, n_factors= 50)\n",
        "learn = Learner(dls, model, loss_func=MSELossFlat())\n",
        "learn.fit_one_cycle(5, 5e-3)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.990447</td>\n",
              "      <td>0.979351</td>\n",
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              "    <tr>\n",
              "      <td>1</td>\n",
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              "      <td>0.894500</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.682093</td>\n",
              "      <td>0.864289</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.483649</td>\n",
              "      <td>0.872441</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.363440</td>\n",
              "      <td>0.876046</td>\n",
              "      <td>00:08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u3G-iJ6mseci"
      },
      "source": [
        "We can do still better, there is one missing piece. There are instances, where a user might like the movie but yet they provide low ratings (or) the user might not like the movie yet they provided good ratings. \n",
        "\n",
        "How to balance this bias in our above model? Well we add something to our weights called a **bias**. This bias will handle this missing piece very nicely. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FzcC5Rx8x7CT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8086b3c2-27c0-4719-ffa9-460bba5ee4aa"
      },
      "source": [
        "Embedding , nn.Embedding"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(fastai.layers.Embedding, torch.nn.modules.sparse.Embedding)"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l_rDDkcEtoS-"
      },
      "source": [
        "# Using the Fastai embedding layers \n",
        "class DotProductBias(Module):\n",
        "\n",
        "  def __init__(self, n_users , n_movies , n_factors , y_range = (0 , 5.5)):\n",
        "    super(DotProductBias , self).__init__()\n",
        "\n",
        "    self.user_factors = Embedding(n_users , n_factors)\n",
        "    self.user_bias = Embedding(n_users , 1) # just a number \n",
        "\n",
        "    self.movie_factors = Embedding(n_movies , n_factors)\n",
        "    self.movie_bias = Embedding(n_movies , 1)\n",
        "\n",
        "    self.y_range = y_range\n",
        "\n",
        "  def forward(self,  x):\n",
        "    users = self.user_factors(x[:,0])\n",
        "    movies = self.movie_factors(x[:,1])\n",
        "    res = (users * movies).sum(dim=1, keepdim=True)\n",
        "    res += self.user_bias(x[:,0]) + self.movie_bias(x[:,1])\n",
        "    return sigmoid_range(res, *self.y_range)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1ig5fKPstrQw",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "613bf29c-6c40-4776-ea57-6eff20faa054"
      },
      "source": [
        "# Training the model again \n",
        "model = DotProductBias(n_users, n_movies, 50)\n",
        "learn = Learner(dls, model, loss_func=MSELossFlat())\n",
        "learn.fit_one_cycle(5, 5e-3)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.933707</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
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              "      <td>0.872352</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.619833</td>\n",
              "      <td>0.874323</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.391215</td>\n",
              "      <td>0.903236</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.276439</td>\n",
              "      <td>0.909220</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-e-7kGgku6qe"
      },
      "source": [
        "We can observe that our validation loss has stopped improving after a certain epoch this clearly shows our model is overfitting. To prevent this we use a regularizaion technique called **weight decay**.\n",
        "\n",
        "Regularization is a set of techniques that will help us to use a model with lots of parameters, train them for a long period of time but penalize them effectively preventing them from overfitting. \n",
        "\n",
        "## Weight Decay \n",
        "- Weight decay or L2 regularization is adding sum of all weights squared to our loss function \n",
        "- By doing this, when we compute the gradients it will add a contribution to them that will encourage the weights to be as small as possible. \n",
        "\n",
        "We can reduce the latent features in order to avoid overfitting, but instead we can try and force the  parameters to be smaller unless they required to be big. \n",
        "\n",
        "`loss_func + sqrt(weights) * some_factor`\n",
        "\n",
        "**But how this will work?**\n",
        "So now if we want to reduce the loss, we can just decrease the weights. Also by using a weight decay we are not letting our model to learn high parameters and fit it into all the data points. \n",
        "\n",
        "Weight decay limit our weights from growing too much also it will yield a state where it generalizes better.  "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "CxeUzs2Y1c60",
        "outputId": "897088c5-7732-4600-e222-ab6627429a6c"
      },
      "source": [
        "# Adding weight decay to our model \n",
        "model = DotProductBias(n_users , n_movies , 50)\n",
        "learn = Learner(dls , model , loss_func = MSELossFlat())\n",
        "learn.fit_one_cycle(5 , 5e-3 , wd = 0.1)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.742479</td>\n",
              "      <td>0.835276</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.590814</td>\n",
              "      <td>0.822301</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.495636</td>\n",
              "      <td>0.823303</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FHi1qAkV1rph"
      },
      "source": [
        "Awesome now our val_loss is decreasing and as we train our model it will further decrease. \n",
        "\n",
        "Lets see how to build our own Embedding Module \n",
        "\n",
        "## Creating our own Embedding Module \n",
        "While building our `DotProductBias` we've been using the nn.Embedding and Fastai's Embedding module to create our embedding vectors. But what if we create our embedding module instead? \n",
        "\n",
        "Well that would be cool, also we get to learn whats the underlying working principle behind it. \n",
        "\n",
        "Lets create a simple class "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c4PoA6SVIsWa",
        "outputId": "c576adc0-f051-4377-e2b4-2ba5e2503ed6"
      },
      "source": [
        "# Using the Fastai Module instead of the Pytorch's Moodule \n",
        "class T(Module):\n",
        "  def __init__(self):\n",
        "    self.a = torch.ones(3)\n",
        "\n",
        "\n",
        "# Instantiating the class \n",
        "l = T()\n",
        "\n",
        "# Accessing the parameters of the class we've just created \n",
        "l.parameters()\n"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<generator object Module.parameters at 0x7eff578006d0>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gJzjdlcMJct5"
      },
      "source": [
        "To treat a tensor as a parameters of the model we have to wrap them inside a `nn.Parameter` class. \n",
        "\n",
        "So now this class gives us an functionality of the `requires_grad_()` functionality to derive the gradients for our tensors. \n",
        "\n",
        "Looking at the example below we can infer that how the `nn.Parameter` is used and also adds the functionality of the gradients. \n",
        "\n",
        "\n",
        "https://stackoverflow.com/questions/50935345/understanding-torch-nn-parameter\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sFheOq7aMyCX",
        "outputId": "5fb4bd38-d531-43af-aac9-e52a1a543119"
      },
      "source": [
        "wit = torch.ones(3)\n",
        "wit_nn = torch.nn.Parameter(torch.ones(3))\n",
        "\n",
        "wit , wit_nn"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(tensor([1., 1., 1.]), Parameter containing:\n",
              " tensor([1., 1., 1.], requires_grad=True))"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zz9mj_rdM5wi",
        "outputId": "405474df-1dc9-4685-eb87-63a9e38b7e58"
      },
      "source": [
        "# Wrapping the tensor inside the the nn.Parameter \n",
        "class T(Module):\n",
        "  def __init__(self):\n",
        "    self.a = nn.Parameter(torch.ones(3))\n",
        "\n",
        "print(L(T().parameters()))"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[Parameter containing:\n",
            "tensor([1., 1., 1.], requires_grad=True)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xvn84ye6N_TA"
      },
      "source": [
        "Likewise we do in the TensorFlow using the `trainable = True` parameter, instead here using the `nn.Parameter` means our parameters our traianble. \n",
        "\n",
        "\n",
        "Instead of the parameter lets add a linear layer and see how it goes. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s8wOmOrnOiOQ",
        "outputId": "4ea34540-cb61-46bf-8f7a-7bf5d0bf451e"
      },
      "source": [
        "class TLinear(Module):\n",
        "  def __init__(self):\n",
        "    self.a = nn.Linear(1 , 3 , bias = True)\n",
        "\n",
        "t = TLinear()\n",
        "\n",
        "# Looking inside whats the parameters are \n",
        "print(t.parameters())"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<generator object Module.parameters at 0x7eff57c21f50>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6fumUNbAO3iA",
        "outputId": "72d34871-ddcf-4a44-d3e1-8d333b93a2b8"
      },
      "source": [
        "# Checking the weight of the tensor \n",
        "t.a.weight "
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Parameter containing:\n",
              "tensor([[-0.4808],\n",
              "        [-0.4352],\n",
              "        [ 0.7877]], requires_grad=True)"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g7TI7lBIQXLZ",
        "outputId": "eddbda62-8c85-49b6-c7cc-f8b2330f77aa"
      },
      "source": [
        "# Checking the type of weight generaated inside our class\n",
        "type(t.a.bias) , type(t.a.weight)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(torch.nn.parameter.Parameter, torch.nn.parameter.Parameter)"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5tHh_aLLQa4Y"
      },
      "source": [
        "Likewise we can create a tensoor without random initialization. \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dyI3vYkiSa8G"
      },
      "source": [
        "def create_params(size):\n",
        "  return nn.Parameter(torch.zeros(*size).normal_(0 , 0.01))"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1coxAHnJShdG"
      },
      "source": [
        "Building the `DotProductBias` without an Embedding Layer!! "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fiqy0oZ_SsV4"
      },
      "source": [
        "class DotProductBias(Module):\n",
        "\n",
        "  def __init__(self , n_users , n_movies , n_factors , y_range = (0 , 5.5)):\n",
        "\n",
        "    # User factor embedding layer\n",
        "    self.user_factors = create_params([n_users , n_factors])\n",
        "    self.user_bias = create_params([n_users])\n",
        "\n",
        "    # Movie factor embedding layer\n",
        "    self.movie_factors = create_params([n_movies , n_factors])\n",
        "    self.movie_bias = create_params([n_movies])\n",
        "\n",
        "    self.y_range = y_range\n",
        "\n",
        "  def forward(self , x):\n",
        "    users = self.user_factors[x[: , 0]]\n",
        "    movies = self.movie_factors[x[: , 1]]\n",
        "\n",
        "    res = (users * movies).sum(dim = 1)\n",
        "    res += self.user_bias[x[: , 0]] + self.movie_bias[x[: , 1]]\n",
        "    return sigmoid_range(res , *self.y_range)"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "j_hE3KpsUbaQ",
        "outputId": "f3325584-1035-40f4-c1d1-b1264454f696"
      },
      "source": [
        "# Training the model again with our newl created Embedding layer \n",
        "model = DotProductBias(n_users , n_movies , 50)\n",
        "\n",
        "# Creating a learner \n",
        "learn = Learner(dls , model , loss_func = MSELossFlat())\n",
        "learn.fit_one_cycle(5 , 5e-3 , wd = 0.1)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: left;\">\n",
              "      <th>epoch</th>\n",
              "      <th>train_loss</th>\n",
              "      <th>valid_loss</th>\n",
              "      <th>time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>0.934034</td>\n",
              "      <td>0.938299</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>0.838885</td>\n",
              "      <td>0.867944</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>0.739571</td>\n",
              "      <td>0.831791</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>0.582375</td>\n",
              "      <td>0.822119</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>0.485546</td>\n",
              "      <td>0.823033</td>\n",
              "      <td>00:09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F3kkjBVqUvlO"
      },
      "source": [
        "### Interpreting Embedding and Biases \n",
        "\n",
        "We know that we assigned some parameters for the model, but what are those parameters exactly? Further we can interpret some of the parameters in our model, lets see how to do them. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iZdCPgFt3Etk",
        "outputId": "05a26096-a837-4258-d320-2f5ad246e192",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# To access the parameters we can use the learn.model method following by the parameter name \n",
        "print(f' Looking into the user bias learned embedding: {learn.model.user_bias}')"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Looking into the user bias learned embedding: Parameter containing:\n",
            "tensor([-3.2766e-03,  7.4514e-02,  7.5592e-02, -3.7159e-02,  3.4565e-01,\n",
            "        -9.7664e-02, -2.7211e-02,  4.1872e-01,  1.1771e-01,  2.4231e-01,\n",
            "         4.3828e-01,  1.9214e-01,  2.7286e-01,  1.0960e-02,  2.1359e-01,\n",
            "        -1.1632e-01,  2.7781e-01, -8.4118e-02,  1.9686e-01,  1.1759e-01,\n",
            "         4.3407e-02, -5.2426e-02,  1.0130e-02,  1.1071e-01,  3.5037e-01,\n",
            "         2.7134e-01, -6.1384e-02,  7.0503e-02,  1.4768e-01,  1.8686e-01,\n",
            "         3.3464e-01,  1.8636e-01,  3.1262e-02,  2.5158e-01,  3.2723e-01,\n",
            "        -2.0464e-03,  2.4578e-01,  2.0266e-01,  2.1613e-01,  2.5712e-01,\n",
            "        -1.5468e-02,  1.0173e-01,  1.0519e-01,  1.4018e-01,  1.9399e-01,\n",
            "         3.0773e-01,  2.2839e-01,  2.2644e-01,  1.3088e-01, -1.2935e-01,\n",
            "         7.2053e-02,  4.1562e-02,  3.2748e-01,  1.8165e-01,  2.8649e-01,\n",
            "         2.5033e-03,  2.4982e-01,  1.5268e-01,  7.2270e-02,  2.9123e-01,\n",
            "         4.3412e-01, -6.4822e-02, -3.7550e-03,  1.8683e-02,  1.0779e-01,\n",
            "         1.4510e-01,  3.1113e-02,  2.9107e-01, -4.6850e-03,  1.4561e-01,\n",
            "         1.0977e-01,  1.0705e-01,  1.9816e-01, -3.2744e-03,  1.0621e-01,\n",
            "         1.7231e-01,  1.3480e-02,  2.7970e-02,  1.3437e-01,  1.7359e-01,\n",
            "         2.4898e-02, -2.7599e-02, -2.0641e-01,  5.6094e-02,  2.4798e-01,\n",
            "         5.9837e-02,  2.2412e-01,  3.0230e-01,  2.5623e-01,  1.7892e-01,\n",
            "         3.0183e-01,  1.3197e-01,  1.1300e-01,  1.0544e-01,  2.1665e-01,\n",
            "         4.2433e-02,  1.7351e-01,  2.4751e-01,  5.9521e-02,  1.3807e-01,\n",
            "        -3.4973e-02, -9.2475e-02, -2.1837e-01,  1.0744e-01, -2.4832e-01,\n",
            "         5.4361e-02,  1.6174e-01, -3.7117e-02,  2.1044e-01,  6.4248e-02,\n",
            "        -2.8390e-02,  1.0302e-01,  1.7823e-01,  2.8433e-01,  1.0085e-01,\n",
            "         1.7116e-01, -4.3348e-02,  2.2372e-01,  6.0705e-01,  3.9962e-01,\n",
            "         1.1991e-01,  1.6711e-02,  2.5359e-01,  5.3466e-02,  1.2898e-01,\n",
            "         7.8451e-02,  2.1203e-01,  2.6700e-01,  1.5067e-01, -1.8753e-01,\n",
            "         4.7397e-01,  2.4054e-01,  8.3075e-02, -5.6126e-02,  1.0734e-01,\n",
            "         1.0842e-01,  2.4115e-01,  3.6489e-01,  1.9780e-01,  2.4586e-01,\n",
            "         1.8153e-01,  4.4073e-02,  9.4459e-02,  1.9338e-01,  9.0286e-02,\n",
            "         6.1717e-02,  4.9786e-02,  2.9221e-01,  1.7015e-01, -8.1906e-02,\n",
            "         1.7654e-01,  1.3920e-01,  3.6759e-01, -5.8366e-02,  9.7556e-02,\n",
            "        -5.8690e-02,  5.0480e-02,  2.7686e-01,  2.8751e-01,  1.1451e-01,\n",
            "         2.2922e-01, -1.5900e-01,  1.8968e-01,  2.3316e-02,  3.2448e-01,\n",
            "         2.1172e-01,  1.1869e-01, -1.0455e-01,  1.6917e-02,  2.6372e-01,\n",
            "         2.2724e-01,  9.0241e-02,  1.0233e-01,  4.5672e-01,  6.1708e-02,\n",
            "        -2.6935e-02,  2.3858e-01,  7.0194e-02,  1.3896e-01, -3.7496e-02,\n",
            "         2.1849e-01, -7.5724e-01,  1.4705e-01,  8.0825e-02,  1.8792e-01,\n",
            "         2.3955e-01,  1.3256e-01,  1.9125e-01,  1.4078e-01,  2.5980e-01,\n",
            "         3.1648e-02,  1.1753e-01,  1.4020e-01,  3.6868e-02, -1.6917e-01,\n",
            "         4.9504e-02,  1.3888e-01, -1.6726e-03, -8.9357e-02, -1.1656e-01,\n",
            "         4.8806e-01, -4.4162e-02, -3.0205e-02,  1.4692e-01,  2.5651e-02,\n",
            "        -4.2551e-02, -2.6720e-01,  3.5383e-02,  1.7082e-01, -5.3877e-02,\n",
            "         2.8545e-01,  9.0246e-02,  1.2610e-01,  3.6376e-01,  1.9691e-01,\n",
            "         1.2299e-01,  1.0248e-01, -3.9321e-02,  7.6881e-02,  9.7327e-02,\n",
            "         2.4546e-01,  2.5401e-01, -1.8177e-01, -8.2099e-02, -7.8631e-02,\n",
            "         1.8127e-01,  1.7948e-01,  1.2668e-01,  6.7139e-02, -1.0093e-01,\n",
            "         1.6013e-01,  1.3527e-01,  1.7434e-01,  3.9894e-01, -7.9747e-02,\n",
            "         1.7290e-01,  1.1227e-01,  1.5654e-01,  5.0058e-02,  2.1771e-01,\n",
            "         1.2688e-01,  2.2656e-02,  3.3619e-01,  1.2450e-01,  3.1985e-01,\n",
            "         5.8234e-02, -9.7560e-02,  1.6408e-01,  5.0190e-02,  2.9930e-01,\n",
            "         3.0947e-01,  1.2616e-01,  2.6146e-01,  1.5286e-01, -1.4621e-01,\n",
            "        -1.3506e-01,  4.0468e-01,  2.0991e-01,  1.4919e-01,  2.3749e-01,\n",
            "         3.7210e-01,  3.1873e-01,  4.6226e-02,  1.4988e-01,  3.0795e-01,\n",
            "         1.0781e-01, -2.3277e-02,  4.2549e-01, -1.5661e-01, -2.0332e-01,\n",
            "         5.0518e-01, -1.4081e-02,  1.5272e-01,  2.1299e-01,  2.5453e-01,\n",
            "        -2.9995e-02,  1.5343e-01,  1.6670e-01,  1.9770e-01,  1.7794e-01,\n",
            "         3.4917e-01,  1.1190e-01,  1.9158e-01,  2.8793e-01,  2.1730e-01,\n",
            "         1.6171e-01,  3.6430e-01,  2.9251e-01,  1.4465e-01, -8.8032e-02,\n",
            "         6.5531e-02,  3.1112e-01,  2.5769e-01, -2.0001e-01,  1.7923e-01,\n",
            "         6.3018e-01,  1.5376e-01,  1.3441e-02,  2.3258e-01,  5.2260e-02,\n",
            "         2.3148e-01,  2.1690e-01, -4.8337e-02,  8.2554e-02,  6.4807e-02,\n",
            "         7.4574e-03,  1.9942e-01,  2.3385e-01,  3.7296e-01,  2.8195e-02,\n",
            "         1.9662e-01,  2.6358e-01,  2.3738e-01,  9.6356e-02,  2.7799e-01,\n",
            "         1.9634e-01, -5.5804e-02,  2.1596e-01,  1.2116e-01,  6.2908e-02,\n",
            "         3.1999e-01,  6.1460e-02,  1.1203e-01,  1.0808e-01,  5.2864e-01,\n",
            "        -1.2880e-02,  4.0493e-03,  4.7657e-02,  5.8546e-02,  4.2663e-02,\n",
            "         5.5746e-01,  1.1917e-01,  4.6579e-01,  1.0041e-01,  7.2713e-02,\n",
            "         1.6890e-01, -2.6917e-02,  2.1186e-01,  1.4895e-01,  3.3040e-01,\n",
            "         2.5056e-01,  3.2765e-01,  1.8359e-02,  2.6441e-01,  5.6512e-02,\n",
            "         1.2674e-01, -2.9668e-02,  4.4880e-02,  4.2050e-01,  1.7150e-01,\n",
            "         1.7472e-01,  2.6594e-01,  6.1141e-02, -1.1533e-02,  1.8100e-01,\n",
            "         4.5098e-01,  6.6000e-02,  4.5356e-01,  1.9186e-01,  1.6283e-01,\n",
            "         1.1570e-01,  5.7406e-02,  1.2332e-01, -1.1348e-01,  2.0968e-01,\n",
            "         7.0544e-02,  3.9530e-01,  4.8582e-01,  7.0842e-02,  3.2740e-01,\n",
            "         1.2663e-01,  1.3723e-01,  5.8294e-01,  1.7374e-01,  1.8668e-02,\n",
            "         1.4491e-01,  1.1882e-01,  1.6369e-01,  1.5973e-01,  2.8431e-01,\n",
            "        -8.3836e-02,  2.1967e-01,  2.0139e-01,  1.8829e-01,  3.2524e-01,\n",
            "         2.6231e-02,  1.8536e-01,  5.2496e-03,  4.1300e-01,  1.1674e-01,\n",
            "         1.3578e-01,  8.7447e-02,  1.7807e-01,  2.1504e-01,  3.7736e-01,\n",
            "         1.6253e-01,  9.4191e-02, -3.5325e-03,  8.1472e-03,  3.8172e-03,\n",
            "         1.6877e-01, -4.6151e-02,  1.2220e-01,  1.4180e-01,  9.1330e-02,\n",
            "        -6.3189e-01,  1.0442e-01,  2.3851e-02,  2.0840e-01,  1.8067e-03,\n",
            "         7.6470e-03,  1.9075e-01,  1.8100e-01,  1.0606e-01,  2.5756e-01,\n",
            "         2.9238e-01,  2.7017e-01,  1.1527e-01, -2.7181e-02,  1.8085e-01,\n",
            "         1.7840e-01,  1.2012e-01,  2.0073e-01,  1.7958e-01,  1.1209e-01,\n",
            "        -4.6373e-02,  1.1744e-01,  5.2457e-01,  3.8921e-01,  7.4785e-02,\n",
            "         7.0593e-02,  6.9132e-02,  1.8706e-01,  2.1191e-02,  2.1993e-01,\n",
            "         8.4808e-02,  2.8376e-01,  1.5420e-01,  2.3702e-01,  1.9206e-01,\n",
            "         3.4472e-01,  1.6181e-01,  5.0742e-02,  1.0600e-01,  1.6132e-01,\n",
            "        -4.2595e-01, -9.3685e-02,  1.0861e-01,  8.8984e-02,  1.2544e-01,\n",
            "         3.8856e-01, -1.8648e-02, -2.9665e-02, -1.4684e-02, -1.1931e-01,\n",
            "         1.2936e-01,  1.9459e-01,  3.7657e-01,  1.3635e-01,  1.4122e-01,\n",
            "         8.9043e-02, -3.4941e-02,  2.5133e-01, -1.6185e-01,  3.0595e-01,\n",
            "        -2.5561e-02,  3.6304e-02,  1.1708e-01,  2.4813e-01,  2.3693e-01,\n",
            "         2.1411e-01,  2.1017e-01,  6.7646e-01,  9.3949e-02,  3.2102e-01,\n",
            "         1.6955e-01,  1.0964e-01,  5.3245e-01,  7.8876e-02, -7.5158e-02,\n",
            "         8.1066e-02,  2.6328e-01,  1.6367e-01,  7.1002e-03,  2.0563e-01,\n",
            "         2.3647e-02,  6.2478e-02,  8.6711e-02,  1.2979e-02,  3.4153e-01,\n",
            "        -7.2215e-02, -8.6810e-03,  5.5512e-02,  1.3940e-01,  7.6151e-02,\n",
            "         4.0530e-01, -9.2449e-02,  1.9063e-02,  3.2833e-02,  1.0199e-01,\n",
            "         1.1351e-01,  3.5276e-01, -1.3392e-02,  1.2452e-01,  3.3559e-01,\n",
            "         1.9861e-02,  6.5368e-02,  6.5286e-01,  8.6094e-02, -1.7579e-01,\n",
            "        -9.6813e-02,  2.5729e-01,  1.7308e-01,  2.3980e-01,  2.1977e-01,\n",
            "        -5.5169e-03,  1.6004e-01,  1.5747e-01,  1.5854e-01,  4.5376e-01,\n",
            "         4.2456e-02, -7.5547e-02,  1.8888e-01,  5.2658e-01,  1.9136e-01,\n",
            "         6.3652e-02, -2.4397e-02,  5.7880e-02,  7.4030e-02,  2.5573e-01,\n",
            "         1.7348e-01,  4.7593e-02,  5.0928e-01,  2.6949e-03,  4.8347e-01,\n",
            "         3.0030e-01,  2.1548e-01, -2.6471e-01,  3.3677e-02,  1.8045e-01,\n",
            "         2.9981e-01,  1.4880e-01,  1.5304e-01,  1.6258e-01, -6.9983e-02,\n",
            "         1.1815e-01,  4.5108e-01,  1.5252e-01,  1.2061e-01,  1.6561e-01,\n",
            "         1.8709e-01,  1.4612e-01,  6.8292e-02,  1.8517e-01,  1.0682e-01,\n",
            "         3.9347e-01,  1.2176e-01,  2.3983e-01,  2.0436e-01,  1.2703e-01,\n",
            "         9.4169e-02, -1.3833e-01,  5.7270e-02,  1.7046e-01,  1.8785e-01,\n",
            "         3.7166e-01,  3.1761e-02,  2.1917e-01, -2.8161e-02,  1.1873e-01,\n",
            "        -1.8821e-01,  2.8177e-02,  8.1410e-02,  1.2238e-01,  9.5314e-02,\n",
            "         3.7075e-02,  6.4075e-02,  2.9633e-01, -1.0703e-01, -7.7883e-03,\n",
            "         1.6365e-01,  1.0749e-01,  1.6584e-01,  2.3952e-01,  8.0638e-02,\n",
            "         1.5493e-01,  1.3696e-01,  1.0209e-01,  2.7495e-01,  2.1405e-01,\n",
            "         2.7442e-02,  1.0676e-01,  1.5125e-01,  1.1694e-01,  3.4199e-02,\n",
            "         1.3203e-01,  1.1633e-01,  1.9047e-01,  1.8326e-01,  3.4245e-01,\n",
            "         2.2372e-01, -5.9006e-02,  3.4305e-01,  1.6596e-01,  9.3614e-02,\n",
            "         1.5348e-01,  3.5487e-01,  9.9879e-02,  2.0278e-01, -2.1167e-01,\n",
            "        -1.3583e-03,  1.8352e-01,  8.4214e-02,  2.1206e-01,  6.3896e-03,\n",
            "        -1.5523e-02,  1.7141e-01, -1.5405e-01, -6.4401e-02,  4.9217e-02,\n",
            "         3.5868e-01,  2.4041e-01,  2.3959e-02,  5.5491e-02,  2.3591e-01,\n",
            "         9.4328e-02, -1.8388e-01,  8.5088e-02,  5.7244e-01,  2.3690e-01,\n",
            "         6.2071e-02,  1.8201e-02,  3.1390e-02,  6.7782e-02,  9.8230e-02,\n",
            "         7.3764e-02,  3.9588e-01, -2.0746e-01,  3.4416e-02, -2.2735e-01,\n",
            "         3.9915e-01,  2.1895e-01,  3.7488e-01,  2.7243e-01,  4.3221e-01,\n",
            "         9.7198e-02,  1.3453e-02,  2.1457e-01,  1.5152e-02,  1.6820e-01,\n",
            "        -2.8166e-02, -7.6879e-03, -5.5127e-02, -3.0377e-01,  1.1113e-01,\n",
            "        -2.2113e-02, -9.7750e-02,  5.2018e-02,  5.4589e-02,  2.6448e-01,\n",
            "        -2.7496e-01,  1.3209e-01,  2.1192e-01,  1.5411e-01,  1.3670e-01,\n",
            "         2.2228e-01,  2.2321e-01,  7.9168e-02,  1.6688e-01, -3.0685e-02,\n",
            "         1.4082e-01,  2.1108e-01,  4.4731e-02,  1.9468e-01,  1.3376e-01,\n",
            "         2.4560e-02,  1.3419e-02,  1.5953e-01,  7.3789e-02,  8.3641e-02,\n",
            "         1.8962e-01,  1.9560e-01,  1.1364e-02,  2.9472e-02,  1.5718e-01,\n",
            "        -2.1528e-01,  1.9946e-01,  1.8971e-01,  6.0914e-01,  1.8444e-01,\n",
            "        -2.3773e-02,  1.7570e-01,  1.0353e-01,  3.0774e-02,  3.2212e-01,\n",
            "         1.5627e-01,  4.6776e-02,  2.4723e-01, -7.0010e-02,  1.5328e-01,\n",
            "         5.2745e-02,  2.3979e-01, -1.4673e-01,  8.6090e-02,  9.7345e-02,\n",
            "         2.0067e-01, -3.4713e-02,  1.5081e-01,  3.1134e-02,  1.9682e-01,\n",
            "         7.2966e-02,  1.9333e-01,  4.1033e-01,  3.9882e-02,  8.3212e-02,\n",
            "        -1.1321e-02,  7.1226e-02,  2.4922e-01,  1.5734e-01, -1.3511e-01,\n",
            "         1.8617e-01,  2.1425e-01,  2.3516e-01, -5.4025e-02, -3.4000e-01,\n",
            "         1.8750e-01,  7.4833e-02, -4.3616e-02,  1.5737e-01, -1.4031e-01,\n",
            "         5.2466e-02, -6.3665e-02,  1.1312e-01, -6.3437e-02,  1.0839e-01,\n",
            "         5.5369e-03, -2.5805e-02,  1.0791e-01,  1.0913e-01,  8.2159e-02,\n",
            "         1.3548e-01,  2.6092e-02,  1.2347e-01,  1.0595e-01,  1.0608e-01,\n",
            "        -8.8980e-03,  4.2244e-02,  1.3462e-01,  1.3571e-01,  2.1470e-01,\n",
            "         6.0012e-04,  1.3534e-01,  6.2646e-02,  7.0144e-02,  7.3082e-02,\n",
            "         1.0685e-01,  4.6991e-02,  1.0329e-01,  4.3371e-01,  1.6021e-01,\n",
            "         1.5320e-01, -1.1497e-01, -4.9954e-02,  1.9906e-01,  1.1354e-01,\n",
            "         1.9930e-01,  7.1917e-02,  2.7937e-01, -2.9545e-02, -3.6872e-03,\n",
            "         4.9575e-01,  1.6296e-01,  3.0610e-01, -4.5693e-02, -4.7912e-01,\n",
            "         1.9323e-01,  8.8345e-02,  2.7971e-01, -1.2962e-01,  3.0209e-01,\n",
            "         4.7828e-02,  5.2972e-02, -6.4170e-02,  3.2678e-01,  2.2734e-01,\n",
            "         6.8335e-02,  9.3346e-02,  4.3045e-02,  5.8967e-02,  7.1769e-02,\n",
            "         1.4399e-03,  1.2883e-01,  9.1134e-02,  2.1415e-01,  2.8841e-01,\n",
            "         1.1908e-01,  1.2307e-01, -1.7269e-01,  1.4873e-01,  1.5558e-01,\n",
            "         1.8992e-01,  2.4415e-01,  2.8179e-01,  8.3133e-02,  2.5473e-01,\n",
            "         2.0378e-01,  1.2431e-01,  3.7390e-01,  2.2902e-01,  6.9561e-02,\n",
            "         4.9318e-01,  3.8505e-01,  1.4479e-01, -3.3558e-02,  5.6941e-03,\n",
            "         2.4611e-02,  3.0689e-01,  8.1444e-02,  1.0178e-01,  3.1818e-01,\n",
            "         6.9057e-03,  2.6520e-01, -7.0713e-02,  2.4800e-01, -1.7704e-01,\n",
            "         2.9847e-01,  3.9140e-01,  7.2908e-02, -6.9806e-02,  5.0482e-02,\n",
            "         3.3636e-03, -1.8070e-02, -8.9456e-02, -7.9825e-02,  1.8741e-01,\n",
            "         3.2547e-01,  3.6099e-02, -2.8191e-02,  3.0780e-01,  2.6144e-02,\n",
            "         2.9080e-01,  1.5770e-01,  1.3525e-01, -2.1559e-02,  5.4397e-02,\n",
            "         3.9025e-02,  2.7929e-01, -1.5092e-01,  2.7144e-01,  4.5836e-01,\n",
            "         2.6159e-01,  1.3909e-01,  2.3243e-01,  1.4709e-02, -4.7089e-02,\n",
            "         7.9132e-02,  8.3087e-02,  9.1926e-02,  1.6716e-02,  2.6569e-01,\n",
            "         3.3937e-02,  2.1953e-01,  5.1223e-01, -3.3797e-02,  2.4298e-01,\n",
            "        -2.0525e-01, -8.8168e-02,  2.3073e-01, -1.0752e-01, -4.7247e-02,\n",
            "         1.4600e-02,  2.0768e-01,  5.9972e-02, -5.1372e-02,  1.2127e-01,\n",
            "         2.7711e-01,  1.8082e-01,  2.2247e-01, -9.5450e-02,  1.2555e-01,\n",
            "         2.5622e-01, -2.8870e-03,  2.3450e-01,  3.9994e-01,  6.7282e-02,\n",
            "        -4.9993e-02, -1.0857e-01,  4.2293e-01,  3.0938e-01,  1.0059e-01,\n",
            "         8.5798e-02,  3.5610e-01,  2.0958e-01,  2.0051e-01,  3.1775e-01,\n",
            "         1.7448e-01, -1.6353e-01,  3.5909e-01,  2.2659e-01, -4.0087e-02,\n",
            "        -2.4107e-01,  2.6087e-01, -6.9922e-02,  1.9753e-01,  2.1198e-01,\n",
            "         5.8742e-03,  2.7206e-01,  7.7434e-01,  5.2644e-02,  2.4709e-01,\n",
            "        -5.6204e-02,  1.8214e-01,  1.3064e-01, -4.0022e-02,  1.8197e-02,\n",
            "        -6.1531e-02,  3.6389e-02,  8.0537e-02,  5.2951e-02,  1.2656e-01,\n",
            "         2.7189e-02, -7.4149e-02,  1.1868e-01,  5.9015e-01,  1.1481e-01,\n",
            "         7.0186e-02, -2.9664e-02,  2.5050e-01,  3.6954e-01,  3.5314e-02,\n",
            "        -3.6713e-02,  1.4058e-01,  1.5066e-01, -4.3259e-01,  2.7137e-01,\n",
            "         2.9362e-01,  3.6799e-01,  1.4843e-03,  7.7949e-02,  3.9921e-01,\n",
            "         6.2638e-02,  1.9880e-01,  3.3218e-01,  5.4590e-02],\n",
            "       requires_grad=True)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ekkwzvdZ3ILS",
        "outputId": "6b93eba3-3537-4938-cd03-94ce7c8d555b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Shape of the learned embedded \n",
        "# We can also access the shape of those embeddings \n",
        "\n",
        "learn.model.user_bias.shape , learn.model.movie_bias.shape , learn.model.movie_factors.shape"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(torch.Size([944]), torch.Size([1665]), torch.Size([1665, 50]))"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1BwsuiEr3mbY"
      },
      "source": [
        "# Getting the indexes \n",
        "movie_bias = learn.model.movie_bias.squeeze()\n",
        "\n",
        "# Taking the first 5 indices also its sorted in ascendng order \n",
        "idxs = movie_bias.argsort(descending= False)[:5] "
      ],
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0_1csrtL4JBq",
        "outputId": "e0dd0d28-929b-4e9a-fc15-263f1dca7c9d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Whats inside the dataloaders class? \n",
        "dls.classes"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'title': ['#na#', \"'Til There Was You (1997)\", '1-900 (1994)', '101 Dalmatians (1996)', '12 Angry Men (1957)', '187 (1997)', '2 Days in the Valley (1996)', '20,000 Leagues Under the Sea (1954)', '2001: A Space Odyssey (1968)', '3 Ninjas: High Noon At Mega Mountain (1998)', '39 Steps, The (1935)', '8 1/2 (1963)', '8 Heads in a Duffel Bag (1997)', '8 Seconds (1994)', 'A Chef in Love (1996)', 'Above the Rim (1994)', 'Absolute Power (1997)', 'Abyss, The (1989)', 'Ace Ventura: Pet Detective (1994)', 'Ace Ventura: When Nature Calls (1995)', 'Across the Sea of Time (1995)', 'Addams Family Values (1993)', 'Addicted to Love (1997)', 'Addiction, The (1995)', 'Adventures of Pinocchio, The (1996)', 'Adventures of Priscilla, Queen of the Desert, The (1994)', 'Adventures of Robin Hood, The (1938)', 'Affair to Remember, An (1957)', 'African Queen, The (1951)', 'Afterglow (1997)', 'Age of Innocence, The (1993)', 'Aiqing wansui (1994)', 'Air Bud (1997)', 'Air Force One (1997)', 'Air Up There, The (1994)', 'Airheads (1994)', 'Akira (1988)', 'Aladdin (1992)', 'Aladdin and the King of Thieves (1996)', 'Alaska (1996)', 'Albino Alligator (1996)', 'Alice in Wonderland (1951)', 'Alien (1979)', 'Alien 3 (1992)', 'Alien: Resurrection (1997)', 'Aliens (1986)', 'All About Eve (1950)', 'All Dogs Go to Heaven 2 (1996)', 'All Over Me (1997)', 'All Things Fair (1996)', 'Alphaville (1965)', 'Amadeus (1984)', 'Amateur (1994)', 'Amazing Panda Adventure, The (1995)', 'American Buffalo (1996)', 'American Dream (1990)', 'American President, The (1995)', 'American Strays (1996)', 'American Werewolf in London, An (1981)', 'American in Paris, An (1951)', 'Amistad (1997)', \"Amityville 1992: It's About Time (1992)\", 'Amityville 3-D (1983)', 'Amityville Curse, The (1990)', 'Amityville Horror, The (1979)', 'Amityville II: The Possession (1982)', 'Amityville: A New Generation (1993)', 'Amityville: Dollhouse (1996)', 'Amos & Andrew (1993)', 'An Unforgettable Summer (1994)', 'Anaconda (1997)', 'Anastasia (1997)', 'Andre (1994)', 'Angel Baby (1995)', 'Angel and the Badman (1947)', 'Angel on My Shoulder (1946)', 'Angela (1995)', 'Angels and Insects (1995)', 'Angels in the Outfield (1994)', 'Angus (1995)', 'Anna (1996)', 'Anna Karenina (1997)', 'Anne Frank Remembered (1995)', 'Annie Hall (1977)', 'Another Stakeout (1993)', \"Antonia's Line (1995)\", 'Aparajito (1956)', 'Apartment, The (1960)', 'Apocalypse Now (1979)', 'Apollo 13 (1995)', 'Apostle, The (1997)', 'Apple Dumpling Gang, The (1975)', \"April Fool's Day (1986)\", 'Apt Pupil (1998)', 'Aristocats, The (1970)', 'Army of Darkness (1993)', 'Around the World in 80 Days (1956)', 'Arrival, The (1996)', 'Arsenic and Old Lace (1944)', 'As Good As It Gets (1997)', 'Assassins (1995)', 'Assignment, The (1997)', 'Associate, The (1996)', 'Audrey Rose (1977)', 'August (1996)', 'Austin Powers: International Man of Mystery (1997)', 'Awfully Big Adventure, An (1995)', 'Ayn Rand: A Sense of Life (1997)', 'B*A*P*S (1997)', 'B. Monkey (1998)', 'Babe (1995)', 'Baby-Sitters Club, The (1995)', 'Babyfever (1994)', 'Babysitter, The (1995)', 'Back to the Future (1985)', 'Backbeat (1993)', 'Bad Boys (1995)', 'Bad Company (1995)', 'Bad Girls (1994)', 'Bad Moon (1996)', 'Bad Taste (1987)', 'Ballad of Narayama, The (Narayama Bushiko) (1958)', 'Balto (1995)', 'Bananas (1971)', 'Band Wagon, The (1953)', 'Barb Wire (1996)', 'Barbarella (1968)', 'Barcelona (1994)', 'Basic Instinct (1992)', 'Basketball Diaries, The (1995)', 'Basquiat (1996)', 'Bastard Out of Carolina (1996)', 'Batman & Robin (1997)', 'Batman (1989)', 'Batman Forever (1995)', 'Batman Returns (1992)', 'Baton Rouge (1988)', 'Bean (1997)', 'Beans of Egypt, Maine, The (1994)', 'Beat the Devil (1954)', 'Beautician and the Beast, The (1997)', 'Beautiful Girls (1996)', 'Beautiful Thing (1996)', 'Beauty and the Beast (1991)', 'Beavis and Butt-head Do America (1996)', 'Bed of Roses (1996)', 'Bedknobs and Broomsticks (1971)', 'Before Sunrise (1995)', 'Before and After (1996)', 'Before the Rain (Pred dozhdot) (1994)', 'Being Human (1993)', 'Being There (1979)', 'Believers, The (1987)', 'Belle de jour (1967)', 'Ben-Hur (1959)', 'Benny & Joon (1993)', 'Bent (1997)', 'Best Men (1997)', 'Best of the Best 3: No Turning Back (1995)', 'Better Off Dead... 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(1993)', 'Cinderella (1950)', 'Cinema Paradiso (1988)', 'Circle of Friends (1995)', 'Citizen Kane (1941)', 'Citizen Ruth (1996)', 'City Hall (1996)', \"City Slickers II: The Legend of Curly's Gold (1994)\", 'City of Angels (1998)', 'City of Industry (1997)', 'City of Lost Children, The (1995)', 'Clean Slate (1994)', 'Clean Slate (Coup de Torchon) (1981)', 'Clear and Present Danger (1994)', 'Clerks (1994)', 'Client, The (1994)', 'Cliffhanger (1993)', 'Clockers (1995)', 'Clockwork Orange, A (1971)', 'Close Shave, A (1995)', 'Clueless (1995)', 'Cobb (1994)', 'Cold Comfort Farm (1995)', 'Coldblooded (1995)', 'Collectionneuse, La (1967)', 'Colonel Chabert, Le (1994)', 'Color of Night (1994)', 'Commandments (1997)', 'Con Air (1997)', 'Conan the Barbarian (1981)', 'Condition Red (1995)', 'Coneheads (1993)', 'Congo (1995)', 'Conspiracy Theory (1997)', 'Contact (1997)', 'Contempt (Mépris, Le) (1963)', 'Convent, The (Convento, O) (1995)', 'Cook the Thief His Wife & Her Lover, The (1989)', 'Cool Hand Luke (1967)', 'Cool Runnings (1993)', 'Cop Land (1997)', 'Cops and Robbersons (1994)', 'Copycat (1995)', 'Corrina, Corrina (1994)', 'Cosi (1996)', 'Country Life (1994)', 'Courage Under Fire (1996)', 'Cowboy Way, The (1994)', 'Craft, The (1996)', 'Crash (1996)', 'Crimson Tide (1995)', 'Critical Care (1997)', 'Cronos (1992)', 'Crooklyn (1994)', 'Crossfire (1947)', 'Crossing Guard, The (1995)', 'Crow, The (1994)', 'Crow: City of Angels, The (1996)', 'Crows and Sparrows (1949)', 'Crucible, The (1996)', 'Crude Oasis, The (1995)', 'Crumb (1994)', 'Cry, the Beloved Country (1995)', 'Crying Game, The (1992)', 'Curdled (1996)', 'Cure, The (1995)', 'Cutthroat Island (1995)', 'Cyclo (1995)', 'Cyrano de Bergerac (1990)', 'Cérémonie, La (1995)', 'D3: The Mighty Ducks (1996)', 'Dadetown (1995)', 'Daens (1992)', 'Damsel in Distress, A (1937)', 'Dances with Wolves (1990)', 'Dangerous Beauty (1998)', 'Dangerous Ground (1997)', 'Dangerous Minds (1995)', \"Daniel Defoe's Robinson Crusoe (1996)\", \"Dante's Peak (1997)\", 'Dark City (1998)', 'Dave (1993)', 'Davy Crockett, King of the Wild Frontier (1955)', 'Day the Earth Stood Still, The (1951)', 'Day the Sun Turned Cold, The (Tianguo niezi) (1994)', 'Daylight (1996)', 'Days of Thunder (1990)', 'Daytrippers, The (1996)', 'Dazed and Confused (1993)', 'Dead Man (1995)', 'Dead Man Walking (1995)', 'Dead Poets Society (1989)', 'Dead Presidents (1995)', 'Dear God (1996)', 'Death and the Maiden (1994)', 'Death in Brunswick (1991)', 'Death in the Garden (Mort en ce jardin, La) (1956)', 'Deceiver (1997)', 'Deconstructing Harry (1997)', 'Deep Rising (1998)', 'Deer Hunter, The (1978)', 'Delicatessen (1991)', 'Delta of Venus (1994)', 'Demolition Man (1993)', 'Denise Calls Up (1995)', 'Desert Winds (1995)', 'Designated Mourner, The (1997)', 'Desperado (1995)', 'Desperate Measures (1998)', 'Destiny Turns on the Radio (1995)', 'Devil in a Blue Dress (1995)', \"Devil's Advocate, The (1997)\", \"Devil's Own, The (1997)\", 'Diabolique (1996)', 'Dial M for Murder (1954)', 'Die Hard (1988)', 'Die Hard 2 (1990)', 'Die Hard: With a Vengeance (1995)', 'Die xue shuang xiong (Killer, The) (1989)', 'Dingo (1992)', 'Dirty Dancing (1987)', 'Disclosure (1994)', 'Diva (1981)', 'Dolores Claiborne (1994)', 'Don Juan DeMarco (1995)', \"Don't Be a Menace to South Central While Drinking Your Juice in the Hood (1996)\", 'Donnie Brasco (1997)', 'Doom Generation, The (1995)', 'Doors, The (1991)', 'Double Happiness (1994)', 'Double Team (1997)', 'Double vie de Véronique, La (Double Life of Veronique, The) (1991)', 'Down Periscope (1996)', 'Down by Law (1986)', 'Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1963)', 'Dracula: Dead and Loving It (1995)', 'Dragonheart (1996)', 'Dream Man (1995)', 'Dream With the Fishes (1997)', 'Drop Dead Fred (1991)', 'Drop Zone (1994)', 'Drunks (1995)', 'Duck Soup (1933)', 'Dumb & Dumber (1994)', 'Dumbo (1941)', 'Dunston Checks In (1996)', 'Duoluo tianshi (1995)', 'E.T. the Extra-Terrestrial (1982)', 'East of Eden (1955)', 'Eat Drink Man Woman (1994)', 'Ed (1996)', 'Ed Wood (1994)', \"Ed's Next Move (1996)\", 'Eddie (1996)', 'Edge, The (1997)', 'Eighth Day, The (1996)', 'Emma (1996)', 'Empire Strikes Back, The (1980)', 'Enchanted April (1991)', 'Endless Summer 2, The (1994)', \"Enfer, L' (1994)\", 'English Patient, The (1996)', 'Englishman Who Went Up a Hill, But Came Down a Mountain, The (1995)', 'Entertaining Angels: The Dorothy Day Story (1996)', 'Eraser (1996)', 'Escape from L.A. (1996)', 'Escape from New York (1981)', 'Escape to Witch Mountain (1975)', 'Etz Hadomim Tafus (Under the Domin Tree) (1994)', \"Eve's Bayou (1997)\", 'Even Cowgirls Get the Blues (1993)', 'Evening Star, The (1996)', 'Event Horizon (1997)', 'Everest (1998)', 'Every Other Weekend (1990)', 'Everyone Says I Love You (1996)', 'Evil Dead II (1987)', 'Evita (1996)', 'Excess Baggage (1997)', 'Executive Decision (1996)', 'Exit to Eden (1994)', 'Exotica (1994)', 'Extreme Measures (1996)', 'Eye for an Eye (1996)', \"Eye of Vichy, The (Oeil de Vichy, L') (1993)\", 'Face/Off (1997)', 'Faces (1968)', 'Fair Game (1995)', 'FairyTale: A True Story (1997)', 'Faithful (1996)', 'Fall (1997)', 'Fallen (1998)', 'Falling in Love Again (1980)', 'Family Thing, A (1996)', 'Fan, The (1996)', 'Fantasia (1940)', 'Far From Home: The Adventures of Yellow Dog (1995)', 'Farewell My Concubine (1993)', 'Farewell to Arms, A (1932)', 'Fargo (1996)', 'Farinelli: il castrato (1994)', 'Farmer & Chase (1995)', 'Fast, Cheap & Out of Control (1997)', 'Faster Pussycat! Kill! Kill! (1965)', 'Fatal Instinct (1993)', 'Father of the Bride (1950)', 'Father of the Bride Part II (1995)', \"Fathers' Day (1997)\", 'Faust (1994)', 'Fausto (1993)', 'Favor, The (1994)', 'Fear (1996)', 'Fear of a Black Hat (1993)', 'Fear, The (1995)', 'Fearless (1993)', 'Feast of July (1995)', 'Feeling Minnesota (1996)', 'Female Perversions (1996)', 'Field of Dreams (1989)', 'Fierce Creatures (1997)', 'Fifth Element, The (1997)', 'Fille seule, La (A Single Girl) (1995)', 'Fire Down Below (1997)', 'Fire on the Mountain (1996)', 'Firestorm (1998)', 'Firm, The (1993)', 'First Kid (1996)', 'First Knight (1995)', 'First Wives Club, The (1996)', 'Fish Called Wanda, A (1988)', 'Fled (1996)', 'Flesh and Bone (1993)', 'Flintstones, The (1994)', 'Flipper (1996)', 'Flirt (1995)', 'Flirting With Disaster (1996)', 'Flower of My Secret, The (Flor de mi secreto, La) (1995)', 'Flubber (1997)', 'Fluke (1995)', 'Fly Away Home (1996)', 'Fog, The (1980)', 'Fools Rush In (1997)', 'For Ever Mozart (1996)', 'For Love or Money (1993)', 'For Richer or Poorer (1997)', 'For Whom the Bell Tolls (1943)', 'For the Moment (1994)', 'Forbidden Christ, The (Cristo proibito, Il) (1950)', 'Forbidden Planet (1956)', 'Foreign Correspondent (1940)', 'Foreign Student (1994)', 'Forget Paris (1995)', 'Forrest Gump (1994)', 'Four Days in September (1997)', 'Four Rooms (1995)', 'Four Weddings and a Funeral (1994)', 'Fox and the Hound, The (1981)', 'Foxfire (1996)', 'Frankie Starlight (1995)', 'Free Willy (1993)', 'Free Willy 2: The Adventure Home (1995)', 'Free Willy 3: The Rescue (1997)', 'Freeway (1996)', 'French Kiss (1995)', 'French Twist (Gazon maudit) (1995)', 'Fresh (1994)', 'Friday (1995)', 'Fried Green Tomatoes (1991)', 'Frighteners, The (1996)', 'Frisk (1995)', 'From Dusk Till Dawn (1996)', 'Fugitive, The (1993)', 'Full Metal Jacket (1987)', 'Full Monty, The (1997)', 'Full Speed (1996)', 'Funeral, The (1996)', 'Funny Face (1957)', 'Further Gesture, A (1996)', 'G.I. Jane (1997)', 'Gabbeh (1996)', 'Game, The (1997)', 'Gandhi (1982)', 'Gang Related (1997)', 'Garden of Finzi-Contini, The (Giardino dei Finzi-Contini, Il) (1970)', 'Gaslight (1944)', 'Gate of Heavenly Peace, The (1995)', 'Gattaca (1997)', 'Gay Divorcee, The (1934)', 'George of the Jungle (1997)', 'Georgia (1995)', 'Germinal (1993)', 'Geronimo: An American Legend (1993)', 'Get Shorty (1995)', 'Get on the Bus (1996)', 'Getaway, The (1994)', 'Getting Away With Murder (1996)', 'Getting Even with Dad (1994)', 'Ghost (1990)', 'Ghost and Mrs. Muir, The (1947)', 'Ghost and the Darkness, The (1996)', 'Ghost in the Shell (Kokaku kidotai) (1995)', 'Ghosts of Mississippi (1996)', 'Giant (1956)', 'Gigi (1958)', \"Gilligan's Island: The Movie (1998)\", 'Girl 6 (1996)', 'Girl in the Cadillac (1995)', 'Girls Town (1996)', 'Glass Shield, The (1994)', 'Glengarry Glen Ross (1992)', 'Glimmer Man, The (1996)', 'Glory (1989)', 'Go Fish (1994)', 'Godfather, The (1972)', 'Godfather: Part II, The (1974)', 'Gold Diggers: The Secret of Bear Mountain (1995)', 'Golden Earrings (1947)', 'GoldenEye (1995)', \"Gone Fishin' (1997)\", 'Gone with the Wind (1939)', 'Good Man in Africa, A (1994)', 'Good Morning (1971)', 'Good Will Hunting (1997)', 'Good, The Bad and The Ugly, The (1966)', 'GoodFellas (1990)', 'Goofy Movie, A (1995)', 'Gordy (1995)', 'Grace of My Heart (1996)', 'Graduate, The (1967)', 'Grand Day Out, A (1992)', 'Grass Harp, The (1995)', 'Grateful Dead (1995)', 'Grease (1978)', 'Grease 2 (1982)', 'Great Day in Harlem, A (1994)', 'Great Dictator, The (1940)', 'Great Escape, The (1963)', 'Great Expectations (1998)', 'Great Race, The (1965)', 'Great White Hype, The (1996)', \"Gridlock'd (1997)\", 'Grifters, The (1990)', 'Grosse Fatigue (1994)', 'Grosse Pointe Blank (1997)', 'Groundhog Day (1993)', 'Grumpier Old Men (1995)', 'Guantanamera (1994)', 'Guilty as Sin (1993)', 'Gumby: The Movie (1995)', 'Hackers (1995)', 'Half Baked (1998)', 'Halloween: The Curse of Michael Myers (1995)', 'Hamlet (1996)', 'Hana-bi (1997)', 'Happy Gilmore (1996)', 'Hard Eight (1996)', 'Hard Rain (1998)', 'Hard Target (1993)', 'Harlem (1993)', 'Harold and Maude (1971)', 'Harriet the Spy (1996)', 'Hate (Haine, La) (1995)', 'Haunted World of Edward D. Wood Jr., The (1995)', 'He Walked by Night (1948)', 'Head Above Water (1996)', 'Hear My Song (1991)', 'Hearts and Minds (1996)', 'Heat (1995)', 'Heathers (1989)', 'Heaven & Earth (1993)', \"Heaven's Prisoners (1996)\", 'Heavenly Creatures (1994)', 'Heavy (1995)', 'Heavy Metal (1981)', 'Heavyweights (1994)', 'Hedd Wyn (1992)', 'Heidi Fleiss: Hollywood Madam (1995) ', 'Hellraiser: Bloodline (1996)', 'Henry V (1989)', 'Herbie Rides Again (1974)', 'Hercules (1997)', 'Here Comes Cookie (1935)', 'Hideaway (1995)', 'High Noon (1952)', 'High School High (1996)', 'Higher Learning (1995)', 'Highlander (1986)', 'Highlander III: The Sorcerer (1994)', 'His Girl Friday (1940)', 'Hollow Reed (1996)', 'Homage (1995)', 'Home Alone (1990)', 'Home Alone 3 (1997)', 'Home for the Holidays (1995)', 'Homeward Bound II: Lost in San Francisco (1996)', 'Homeward Bound: The Incredible Journey (1993)', 'Hoodlum (1997)', 'Hoop Dreams (1994)', 'Horse Whisperer, The (1998)', 'Horseman on the Roof, The (Hussard sur le toit, Le) (1995)', 'Hostile Intentions (1994)', 'Hot Shots! 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(1994)', 'Ice Storm, The (1997)', 'If Lucy Fell (1996)', 'Ill Gotten Gains (1997)', 'Immortal Beloved (1994)', 'In & Out (1997)', 'In Love and War (1996)', 'In the Army Now (1994)', 'In the Bleak Midwinter (1995)', 'In the Company of Men (1997)', 'In the Line of Duty 2 (1987)', 'In the Line of Fire (1993)', 'In the Mouth of Madness (1995)', 'In the Name of the Father (1993)', 'In the Realm of the Senses (Ai no corrida) (1976)', 'Incognito (1997)', 'Independence Day (ID4) (1996)', 'Indian Summer (1996)', 'Indian in the Cupboard, The (1995)', 'Indiana Jones and the Last Crusade (1989)', 'Infinity (1996)', 'Inkwell, The (1994)', 'Innocent Sleep, The (1995)', 'Innocents, The (1961)', 'Inspector General, The (1949)', 'Interview with the Vampire (1994)', 'Intimate Relations (1996)', 'Inventing the Abbotts (1997)', 'Invitation, The (Zaproszenie) (1986)', 'Island of Dr. Moreau, The (1996)', 'It Could Happen to You (1994)', 'It Happened One Night (1934)', 'It Takes Two (1995)', \"It's My Party (1995)\", \"It's a Wonderful Life (1946)\", 'JLG/JLG - autoportrait de décembre (1994)', 'Jack (1996)', 'Jack and Sarah (1995)', 'Jackal, The (1997)', 'Jackie Brown (1997)', \"Jackie Chan's First Strike (1996)\", 'Jade (1995)', 'James and the Giant Peach (1996)', 'Jane Eyre (1996)', \"Jason's Lyric (1994)\", 'Jaws (1975)', 'Jaws 2 (1978)', 'Jaws 3-D (1983)', 'Jean de Florette (1986)', 'Jefferson in Paris (1995)', 'Jeffrey (1995)', 'Jerky Boys, The (1994)', 'Jerry Maguire (1996)', 'Jimmy Hollywood (1994)', 'Jingle All the Way (1996)', \"Joe's Apartment (1996)\", 'Johnny 100 Pesos (1993)', 'Johnny Mnemonic (1995)', 'Johns (1996)', 'Journey of August King, The (1995)', 'Joy Luck Club, The (1993)', 'Jude (1996)', 'Judge Dredd (1995)', 'Judgment Night (1993)', 'Jumanji (1995)', 'Jungle Book, The (1994)', 'Jungle2Jungle (1997)', 'Junior (1994)', \"Jupiter's Wife (1994)\", 'Jurassic Park (1993)', 'Juror, The (1996)', 'Jury Duty (1995)', 'Just Cause (1995)', 'Kalifornia (1993)', 'Kama Sutra: A Tale of Love (1996)', 'Kansas City (1996)', 'Kaspar Hauser (1993)', 'Kazaam (1996)', 'Keys to Tulsa (1997)', 'Kicked in the Head (1997)', 'Kicking and Screaming (1995)', \"Kid in King Arthur's Court, A (1995)\", 'Kids (1995)', 'Kids in the Hall: Brain Candy (1996)', 'Kika (1993)', 'Killer (Bulletproof Heart) (1994)', 'Killer: A Journal of Murder (1995)', 'Killing Fields, The (1984)', 'Killing Zoe (1994)', 'Kim (1950)', 'King of New York (1990)', 'King of the Hill (1993)', 'Kingpin (1996)', 'Kiss Me, Guido (1997)', 'Kiss of Death (1995)', 'Kiss the Girls (1997)', 'Kissed (1996)', 'Kolya (1996)', 'Koyaanisqatsi (1983)', 'Kull the Conqueror (1997)', 'Kundun (1997)', 'L.A. Confidential (1997)', 'Lady of Burlesque (1943)', 'Ladybird Ladybird (1994)', 'Lamerica (1994)', 'Land Before Time III: The Time of the Great Giving (1995) (V)', 'Land and Freedom (Tierra y libertad) (1995)', 'Larger Than Life (1996)', 'Lashou shentan (1992)', 'Lassie (1994)', 'Last Action Hero (1993)', 'Last Dance (1996)', 'Last Klezmer: Leopold Kozlowski, His Life and Music, The (1995)', 'Last Man Standing (1996)', 'Last Summer in the Hamptons (1995)', 'Last Supper, The (1995)', 'Last Time I Committed Suicide, The (1997)', 'Last Time I Saw Paris, The (1954)', 'Last of the Mohicans, The (1992)', 'Late Bloomers (1996)', 'Laura (1944)', 'Lawnmower Man 2: Beyond Cyberspace (1996)', 'Lawnmower Man, The (1992)', 'Lawrence of Arabia (1962)', 'Lay of the Land, The (1997)', 'Leading Man, The (1996)', 'Leave It to Beaver (1997)', 'Leaving Las Vegas (1995)', 'Legal Deceit (1997)', 'Legends of the Fall (1994)', 'Leopard Son, The (1996)', 'Letter From Death Row, A (1998)', 'Liar Liar (1997)', 'Liebelei (1933)', 'Life Less Ordinary, A (1997)', 'Life with Mikey (1993)', 'Lightning Jack (1994)', 'Like Water For Chocolate (Como agua para chocolate) (1992)', 'Line King: Al Hirschfeld, The (1996)', 'Lion King, The (1994)', 'Little Big League (1994)', 'Little Buddha (1993)', 'Little City (1998)', 'Little Lord Fauntleroy (1936)', 'Little Odessa (1994)', 'Little Princess, A (1995)', 'Little Princess, The (1939)', 'Little Rascals, The (1994)', 'Little Women (1994)', 'Live Nude Girls (1995)', 'Living in Oblivion (1995)', 'Loaded (1994)', 'Local Hero (1983)', 'Loch Ness (1995)', 'Locusts, The (1997)', 'Lone Star (1996)', 'Long Kiss Goodnight, The (1996)', 'Looking for Richard (1996)', 'Lord of Illusions (1995)', 'Losing Chase (1996)', 'Losing Isaiah (1995)', 'Lost Highway (1997)', 'Lost Horizon (1937)', 'Lost World: Jurassic Park, The (1997)', 'Lost in Space (1998)', 'Lotto Land (1995)', 'Love & Human Remains (1993)', 'Love Affair (1994)', 'Love Bug, The (1969)', 'Love Is All There Is (1996)', 'Love Jones (1997)', 'Love Serenade (1996)', 'Love and Death on Long Island (1997)', 'Love and Other Catastrophes (1996)', 'Love and a .45 (1994)', 'Love in the Afternoon (1957)', 'Love! Valour! Compassion! (1997)', \"Lover's Knot (1996)\", 'Low Down Dirty Shame, A (1994)', 'Low Life, The (1994)', 'M (1931)', 'M*A*S*H (1970)', 'M. Butterfly (1993)', 'MURDER and murder (1996)', 'Ma vie en rose (My Life in Pink) (1997)', 'Machine, The (1994)', 'Mad City (1997)', 'Mad Dog Time (1996)', 'Mad Love (1995)', 'Madame Butterfly (1995)', 'Made in America (1993)', 'Madness of King George, The (1994)', 'Madonna: Truth or Dare (1991)', 'Magic Hour, The (1998)', 'Magnificent Seven, The (1954)', 'Major Payne (1994)', 'Malice (1993)', 'Mallrats (1995)', 'Maltese Falcon, The (1941)', 'Mamma Roma (1962)', 'Man Who Knew Too Little, The (1997)', 'Man Who Would Be King, The (1975)', 'Man Without a Face, The (1993)', 'Man from Down Under, The (1943)', 'Man in the Iron Mask, The (1998)', 'Man of No Importance, A (1994)', 'Man of the House (1995)', 'Man of the Year (1995)', 'Manchurian Candidate, The (1962)', 'Manhattan (1979)', 'Manhattan Murder Mystery (1993)', 'Manny & Lo (1996)', 'Manon of the Spring (Manon des sources) (1986)', \"Margaret's Museum (1995)\", 'Mark of Zorro, The (1940)', 'Marked for Death (1990)', 'Marlene Dietrich: Shadow and Light (1996) ', 'Mars Attacks! (1996)', \"Marvin's Room (1996)\", 'Mary Poppins (1964)', 'Mary Reilly (1996)', \"Mary Shelley's Frankenstein (1994)\", 'Mask, The (1994)', \"Mat' i syn (1997)\", 'MatchMaker, The (1997)', 'Matilda (1996)', 'Maverick (1994)', 'Maximum Risk (1996)', 'Maya Lin: A Strong Clear Vision (1994)', 'Maybe, Maybe Not (Bewegte Mann, Der) (1994)', \"McHale's Navy (1997)\", 'Mediterraneo (1991)', 'Meet John Doe (1941)', 'Meet Me in St. Louis (1944)', 'Meet Wally Sparks (1997)', 'Men With Guns (1997)', 'Men in Black (1997)', 'Men of Means (1998)', 'Menace II Society (1993)', 'Mercury Rising (1998)', 'Metisse (Café au Lait) (1993)', 'Metro (1997)', 'Miami Rhapsody (1995)', 'Michael (1996)', 'Michael Collins (1996)', \"Microcosmos: Le peuple de l'herbe (1996)\", 'Midnight Dancers (Sibak) (1994)', 'Midnight in the Garden of Good and Evil (1997)', 'Mighty Aphrodite (1995)', 'Mighty Morphin Power Rangers: The Movie (1995)', 'Mighty, The (1998)', 'Milk Money (1994)', 'Mille bolle blu (1993)', \"Miller's Crossing (1990)\", 'Mimic (1997)', 'Mina Tannenbaum (1994)', 'Miracle on 34th Street (1994)', 'Mirage (1995)', 'Mirror Has Two Faces, The (1996)', 'Mission: Impossible (1996)', 'Misérables, Les (1995)', 'Mixed Nuts (1994)', 'Modern Affair, A (1995)', 'Moll Flanders (1996)', 'Mondo (1996)', 'Money Talks (1997)', 'Money Train (1995)', 'Month by the Lake, A (1995)', 'Monty Python and the Holy Grail (1974)', \"Monty Python's Life of Brian (1979)\", 'Moonlight and Valentino (1995)', 'Mortal Kombat (1995)', 'Mortal Kombat: Annihilation (1997)', 'Mostro, Il (1994)', 'Mother (1996)', 'Mother Night (1996)', 'Mouse Hunt (1997)', \"Mr. Holland's Opus (1995)\", 'Mr. Jones (1993)', 'Mr. Magoo (1997)', 'Mr. Smith Goes to Washington (1939)', 'Mr. Wonderful (1993)', 'Mr. Wrong (1996)', 'Mrs. Brown (Her Majesty, Mrs. Brown) (1997)', 'Mrs. Dalloway (1997)', 'Mrs. Doubtfire (1993)', 'Mrs. Parker and the Vicious Circle (1994)', 'Mrs. Winterbourne (1996)', 'Much Ado About Nothing (1993)', 'Mulholland Falls (1996)', 'Multiplicity (1996)', 'Muppet Treasure Island (1996)', 'Murder at 1600 (1997)', 'Murder in the First (1995)', 'Murder, My Sweet (1944)', \"Muriel's Wedding (1994)\", 'Mute Witness (1994)', \"My Best Friend's Wedding (1997)\", 'My Crazy Life (Mi vida loca) (1993)', 'My Fair Lady (1964)', 'My Family (1995)', 'My Favorite Season (1993)', 'My Favorite Year (1982)', 'My Fellow Americans (1996)', 'My Left Foot (1989)', \"My Life and Times With Antonin Artaud (En compagnie d'Antonin Artaud) (1993)\", 'My Life as a Dog (Mitt liv som hund) (1985)', 'My Man Godfrey (1936)', 'My Own Private Idaho (1991)', 'Mystery Science Theater 3000: The Movie (1996)', 'Nadja (1994)', 'Naked (1993)', 'Naked Gun 33 1/3: The Final Insult (1994)', 'Naked in New York (1994)', \"National Lampoon's Senior Trip (1995)\", 'Natural Born Killers (1994)', 'Nell (1994)', 'Nelly & Monsieur Arnaud (1995)', 'Nemesis 2: Nebula (1995)', 'Neon Bible, The (1995)', 'Net, The (1995)', 'NeverEnding Story III, The (1994)', 'New Age, The (1994)', 'New Jersey Drive (1995)', 'New York Cop (1996)', 'Newton Boys, The (1998)', 'Next Karate Kid, The (1994)', 'Next Step, The (1995)', 'Niagara, Niagara (1997)', 'Nick of Time (1995)', 'Nico Icon (1995)', 'Night Falls on Manhattan (1997)', 'Night Flier (1997)', 'Night of the Living Dead (1968)', 'Night on Earth (1991)', 'Nightmare Before Christmas, The (1993)', 'Nightmare on Elm Street, A (1984)', 'Nightwatch (1997)', 'Nikita (La Femme Nikita) (1990)', 'Nil By Mouth (1997)', 'Nina Takes a Lover (1994)', 'Nine Months (1995)', 'Ninotchka (1939)', 'Nixon (1995)', 'No Escape (1994)', 'Nobody Loves Me (Keiner liebt mich) (1994)', \"Nobody's Fool (1994)\", 'Normal Life (1996)', 'North (1994)', 'North by Northwest (1959)', 'Nosferatu (Nosferatu, eine Symphonie des Grauens) (1922)', 'Nosferatu a Venezia (1986)', 'Nothing Personal (1995)', 'Nothing to Lose (1994)', 'Notorious (1946)', 'Now and Then (1995)', 'Nowhere (1997)', 'Nutty Professor, The (1996)', 'Nénette et Boni (1996)', 'Object of My Affection, The (1998)', 'Of Human Bondage (1934)', 'Of Love and Shadows (1994)', 'Office Killer (1997)', 'Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)', 'Old Man and the Sea, The (1958)', 'Old Yeller (1957)', 'Oliver & Company (1988)', 'Omen, The (1976)', 'On Golden Pond (1981)', 'Once Upon a Time in America (1984)', 'Once Upon a Time in the West (1969)', 'Once Upon a Time... When We Were Colored (1995)', 'Once Were Warriors (1994)', 'One Fine Day (1996)', \"One Flew Over the Cuckoo's Nest (1975)\", 'One Night Stand (1997)', 'Only You (1994)', 'Open Season (1996)', 'Operation Dumbo Drop (1995)', 'Original Gangstas (1996)', 'Orlando (1993)', 'Oscar & Lucinda (1997)', 'Othello (1995)', 'Other Voices, Other Rooms (1997)', 'Out to Sea (1997)', 'Outbreak (1995)', 'Outlaw, The (1943)', 'Pagemaster, The (1994)', 'Pallbearer, The (1996)', 'Palmetto (1998)', 'Palookaville (1996)', 'Panther (1995)', 'Paper, The (1994)', 'Paradise Lost: The Child Murders at Robin Hood Hills (1996)', 'Paradise Road (1997)', 'Parent Trap, The (1961)', 'Paris Is Burning (1990)', 'Paris Was a Woman (1995)', 'Paris, France (1993)', 'Paris, Texas (1984)', 'Party Girl (1995)', 'Passion Fish (1992)', 'Pather Panchali (1955)', 'Paths of Glory (1957)', 'Patton (1970)', 'Peacemaker, The (1997)', 'Penny Serenade (1941)', 'People vs. Larry Flynt, The (1996)', 'Perez Family, The (1995)', 'Perfect Candidate, A (1996)', 'Perfect World, A (1993)', 'Persuasion (1995)', 'Pest, The (1997)', \"Pete's Dragon (1977)\", 'Phantom, The (1996)', 'Phantoms (1998)', \"Pharaoh's Army (1995)\", 'Phat Beach (1996)', 'Phenomenon (1996)', 'Philadelphia (1993)', 'Philadelphia Story, The (1940)', 'Piano, The (1993)', 'Picnic (1955)', 'Picture Bride (1995)', 'Picture Perfect (1997)', 'Pie in the Sky (1995)', 'Pillow Book, The (1995)', 'Pink Floyd - The Wall (1982)', 'Pinocchio (1940)', 'Platoon (1986)', 'Playing God (1997)', 'Pocahontas (1995)', 'Poetic Justice (1993)', 'Poison Ivy II (1995)', 'Police Story 4: Project S (Chao ji ji hua) (1993)', 'Pollyanna (1960)', 'Pompatus of Love, The (1996)', 'Ponette (1996)', 'Portrait of a Lady, The (1996)', 'Postino, Il (1994)', 'Postman, The (1997)', 'Powder (1995)', 'Power 98 (1995)', \"Preacher's Wife, The (1996)\", 'Prefontaine (1997)', 'Pretty Woman (1990)', 'Price Above Rubies, A (1998)', 'Priest (1994)', 'Primal Fear (1996)', 'Primary Colors (1998)', 'Princess Bride, The (1987)', 'Princess Caraboo (1994)', 'Prisoner of the Mountains (Kavkazsky Plennik) (1996)', 'Private Benjamin (1980)', 'Private Parts (1997)', 'Professional, The (1994)', 'Program, The (1993)', 'Promesse, La (1996)', 'Promise, The (Versprechen, Das) (1994)', 'Prophecy II, The (1998)', 'Prophecy, The (1995)', 'Psycho (1960)', 'Pulp Fiction (1994)', 'Pump Up the Volume (1990)', 'Purple Noon (1960)', 'Pushing Hands (1992)', \"Pyromaniac's Love Story, A (1995)\", 'Quartier Mozart (1992)', 'Queen Margot (Reine Margot, La) (1994)', 'Quest, The (1996)', 'Quick and the Dead, The (1995)', 'Quiet Man, The (1952)', 'Quiet Room, The (1996)', 'Quiz Show (1994)', 'Race the Sun (1996)', 'Radioland Murders (1994)', 'Raging Bull (1980)', 'Raiders of the Lost Ark (1981)', 'Rainmaker, The (1997)', 'Raise the Red Lantern (1991)', 'Raising Arizona (1987)', 'Ran (1985)', 'Ransom (1996)', 'Raw Deal (1948)', 'Ready to Wear (Pret-A-Porter) (1994)', 'Real Genius (1985)', 'Reality Bites (1994)', 'Rear Window (1954)', 'Rebecca (1940)', 'Rebel Without a Cause (1955)', 'Reckless (1995)', 'Red Corner (1997)', 'Red Firecracker, Green Firecracker (1994)', 'Red Rock West (1992)', 'Ref, The (1994)', 'Relative Fear (1994)', 'Relic, The (1997)', 'Reluctant Debutante, The (1958)', 'Remains of the Day, The (1993)', 'Renaissance Man (1994)', 'Rendezvous in Paris (Rendez-vous de Paris, Les) (1995)', 'Rent-a-Kid (1995)', 'Replacement Killers, The (1998)', 'Reservoir Dogs (1992)', 'Restoration (1995)', 'Return of Martin Guerre, The (Retour de Martin Guerre, Le) (1982)', 'Return of the Jedi (1983)', 'Return of the Pink Panther, The (1974)', 'Rhyme & Reason (1997)', \"Rich Man's Wife, The (1996)\", 'Richard III (1995)', 'Richie Rich (1994)', 'Ridicule (1996)', 'Right Stuff, The (1983)', 'Ripe (1996)', 'Rising Sun (1993)', 'River Wild, The (1994)', 'Road to Wellville, The (1994)', 'Rob Roy (1995)', \"Robert A. Heinlein's The Puppet Masters (1994)\", 'Robin Hood: Men in Tights (1993)', 'Robin Hood: Prince of Thieves (1991)', 'Robocop 3 (1993)', 'Rock, The (1996)', 'Rocket Man (1997)', 'Roman Holiday (1953)', 'Romeo Is Bleeding (1993)', 'Romper Stomper (1992)', \"Romy and Michele's High School Reunion (1997)\", 'Room with a View, A (1986)', 'Roommates (1995)', \"Roseanna's Grave (For Roseanna) (1997)\", 'Rosencrantz and Guildenstern Are Dead (1990)', 'Rosewood (1997)', 'Rough Magic (1995)', 'Ruby in Paradise (1993)', 'Rudy (1993)', 'Ruling Class, The (1972)', 'Rumble in the Bronx (1995)', 'Run of the Country, The (1995)', 'S.F.W. (1994)', 'Sabrina (1954)', 'Sabrina (1995)', 'Safe (1995)', 'Safe Passage (1994)', 'Saint of Fort Washington, The (1993)', 'Saint, The (1997)', 'Salut cousin! (1996)', 'Santa Clause, The (1994)', 'Santa with Muscles (1996)', 'Savage Nights (Nuits fauves, Les) (1992)', 'Scarlet Letter, The (1926)', 'Scarlet Letter, The (1995)', \"Schindler's List (1993)\", 'Schizopolis (1996)', 'Scout, The (1994)', 'Scream (1996)', 'Scream 2 (1997)', 'Scream of Stone (Schrei aus Stein) (1991)', 'Screamers (1995)', 'Search for One-eye Jimmy, The (1996)', 'Searching for Bobby Fischer (1993)', 'Second Jungle Book: Mowgli & Baloo, The (1997)', 'Secret Adventures of Tom Thumb, The (1993)', 'Secret Agent, The (1996)', 'Secret Garden, The (1993)', 'Secret of Roan Inish, The (1994)', 'Secrets & Lies (1996)', 'Selena (1997)', 'Sense and Sensibility (1995)', 'Senseless (1998)', 'Serial Mom (1994)', 'Set It Off (1996)', 'Seven (Se7en) (1995)', 'Seven Years in Tibet (1997)', 'Seventh Seal, The (Sjunde inseglet, Det) (1957)', 'Sex, Lies, and Videotape (1989)', 'Sexual Life of the Belgians, The (1994)', 'Sgt. Bilko (1996)', 'Shadow Conspiracy (1997)', 'Shadow of Angels (Schatten der Engel) (1976)', 'Shadow, The (1994)', 'Shadowlands (1993)', 'Shadows (Cienie) (1988)', 'Shaggy Dog, The (1959)', 'Shall We Dance? (1937)', 'Shall We Dance? (1996)', 'Shallow Grave (1994)', 'Shanghai Triad (Yao a yao yao dao waipo qiao) (1995)', 'Shawshank Redemption, The (1994)', \"She's So Lovely (1997)\", \"She's the One (1996)\", 'Shiloh (1997)', 'Shine (1996)', 'Shining, The (1980)', 'Shooter, The (1995)', 'Shooting Fish (1997)', 'Shopping (1994)', 'Short Cuts (1993)', 'Show, The (1995)', 'Showgirls (1995)', 'Silence of the Lambs, The (1991)', 'Silence of the Palace, The (Saimt el Qusur) (1994)', 'Simple Twist of Fate, A (1994)', 'Simple Wish, A (1997)', \"Singin' in the Rain (1952)\", 'Sirens (1994)', 'Six Degrees of Separation (1993)', 'Sixth Man, The (1997)', 'Sleeper (1973)', 'Sleepers (1996)', 'Sleepless in Seattle (1993)', 'Sleepover (1995)', 'Sliding Doors (1998)', 'Sling Blade (1996)', 'Slingshot, The (1993)', 'Sliver (1993)', 'Small Faces (1995)', 'Smile Like Yours, A (1997)', \"Smilla's Sense of Snow (1997)\", 'Smoke (1995)', 'Sneakers (1992)', 'Snow White and the Seven Dwarfs (1937)', 'So Dear to My Heart (1949)', 'So I Married an Axe Murderer (1993)', 'Solo (1996)', 'Some Folks Call It a Sling Blade (1993)', 'Some Kind of Wonderful (1987)', 'Some Like It Hot (1959)', \"Some Mother's Son (1996)\", 'Somebody to Love (1994)', \"Someone Else's America (1995)\", 'Something to Talk About (1995)', 'Somewhere in Time (1980)', 'Son in Law (1993)', \"Sophie's Choice (1982)\", 'Soul Food (1997)', 'Sound of Music, The (1965)', 'Space Jam (1996)', 'Spanish Prisoner, The (1997)', 'Spanking the Monkey (1994)', 'Spawn (1997)', 'Specialist, The (1994)', 'Species (1995)', 'Speechless (1994)', 'Speed (1994)', 'Speed 2: Cruise Control (1997)', 'Spellbound (1945)', 'Sphere (1998)', 'Spice World (1997)', 'Spirits of the Dead (Tre passi nel delirio) (1968)', 'Spitfire Grill, The (1996)', 'Sprung (1997)', 'Spy Hard (1996)', 'Squeeze (1996)', 'Stag (1997)', 'Stalingrad (1993)', 'Stalker (1979)', 'Stand by Me (1986)', 'Star Kid (1997)', \"Star Maker, The (Uomo delle stelle, L') (1995)\", 'Star Maps (1997)', 'Star Trek III: The Search for Spock (1984)', 'Star Trek IV: The Voyage Home (1986)', 'Star Trek V: The Final Frontier (1989)', 'Star Trek VI: The Undiscovered Country (1991)', 'Star Trek: First Contact (1996)', 'Star Trek: Generations (1994)', 'Star Trek: The Motion Picture (1979)', 'Star Trek: The Wrath of Khan (1982)', 'Star Wars (1977)', 'Stargate (1994)', 'Stars Fell on Henrietta, The (1995)', 'Starship Troopers (1997)', 'Steal Big, Steal Little (1995)', 'Stealing Beauty (1996)', 'Steel (1997)', 'Stefano Quantestorie (1993)', \"Stephen King's The Langoliers (1995)\", 'Sting, The (1973)', 'Stonewall (1995)', 'Story of Xinghua, The (1993)', 'Strange Days (1995)', 'Stranger in the House (1997)', 'Stranger, The (1994)', 'Strawberry and Chocolate (Fresa y chocolate) (1993)', 'Street Fighter (1994)', 'Streetcar Named Desire, A (1951)', 'Strictly Ballroom (1992)', 'Striking Distance (1993)', 'Stripes (1981)', 'Striptease (1996)', 'Stuart Saves His Family (1995)', 'Stupids, The (1996)', 'SubUrbia (1997)', 'Substance of Fire, The (1996)', 'Substitute, The (1996)', 'Sudden Death (1995)', 'Sudden Manhattan (1996)', 'Sum of Us, The (1994)', 'Sunchaser, The (1996)', 'Sunset Blvd. (1950)', 'Sunset Park (1996)', 'Super Mario Bros. (1993)', 'Supercop (1992)', 'Surviving Picasso (1996)', 'Surviving the Game (1994)', 'Suture (1993)', 'Swan Princess, The (1994)', 'Sweet Hereafter, The (1997)', 'Sweet Nothing (1995)', 'Swept from the Sea (1997)', 'Swimming with Sharks (1995)', 'Swingers (1996)', 'Swiss Family Robinson (1960)', 'Switchback (1997)', 'Switchblade Sisters (1975)', 'Sword in the Stone, The (1963)', 'Symphonie pastorale, La (1946)', 'T-Men (1947)', 'Tainted (1998)', 'Tales From the Crypt Presents: Demon Knight (1995)', 'Tales from the Crypt Presents: Bordello of Blood (1996)', 'Tales from the Hood (1995)', 'Talking About Sex (1994)', 'Tango Lesson, The (1997)', 'Tank Girl (1995)', 'Target (1995)', 'Taxi Driver (1976)', 'Telling Lies in America (1997)', 'Temptress Moon (Feng Yue) (1996)', 'Terminal Velocity (1994)', 'Terminator 2: Judgment Day (1991)', 'Terminator, The (1984)', 'Terror in a Texas Town (1958)', 'Tetsuo II: Body Hammer (1992)', 'That Darn Cat! (1965)', 'That Darn Cat! (1997)', 'That Old Feeling (1997)', 'That Thing You Do! (1996)', 'The Courtyard (1995)', 'The Deadly Cure (1996)', 'The Innocent (1994)', 'Theodore Rex (1995)', 'They Made Me a Criminal (1939)', 'Thieves (Voleurs, Les) (1996)', 'Thin Blue Line, The (1988)', 'Thin Line Between Love and Hate, A (1996)', 'Thin Man, The (1934)', \"Things to Do in Denver when You're Dead (1995)\", 'Thinner (1996)', 'Third Man, The (1949)', 'Thirty-Two Short Films About Glenn Gould (1993)', 'This Is Spinal Tap (1984)', 'Thousand Acres, A (1997)', 'Three Caballeros, The (1945)', 'Three Colors: Blue (1993)', 'Three Colors: Red (1994)', 'Three Colors: White (1994)', 'Three Lives and Only One Death (1996)', 'Three Musketeers, The (1993)', 'Three Wishes (1995)', 'Threesome (1994)', 'Tie Me Up! Tie Me Down! (1990)', 'Tie That Binds, The (1995)', 'Tigrero: A Film That Was Never Made (1994)', 'Time Tracers (1995)', 'Time to Kill, A (1996)', 'Timecop (1994)', 'Tin Cup (1996)', 'Tin Drum, The (Blechtrommel, Die) (1979)', 'Tin Men (1987)', 'Titanic (1997)', 'To Be or Not to Be (1942)', 'To Catch a Thief (1955)', 'To Cross the Rubicon (1991)', 'To Die For (1995)', 'To Gillian on Her 37th Birthday (1996)', 'To Have, or Not (1995)', 'To Kill a Mockingbird (1962)', 'To Live (Huozhe) (1994)', 'To Wong Foo, Thanks for Everything! Julie Newmar (1995)', 'Tokyo Fist (1995)', 'Tom & Viv (1994)', 'Tom and Huck (1995)', 'Tombstone (1993)', 'Tommy Boy (1995)', 'Tomorrow Never Dies (1997)', 'Top Gun (1986)', 'Top Hat (1935)', 'Total Eclipse (1995)', 'Touch (1997)', 'Touch of Evil (1958)', 'Tough and Deadly (1995)', 'Touki Bouki (Journey of the Hyena) (1973)', 'Toy Story (1995)', 'Trainspotting (1996)', 'Transformers: The Movie, The (1986)', 'Traveller (1997)', 'Treasure of the Sierra Madre, The (1948)', 'Trees Lounge (1996)', 'Trial and Error (1997)', 'Trial by Jury (1994)', 'Trigger Effect, The (1996)', 'True Crime (1995)', 'True Lies (1994)', 'True Romance (1993)', 'Truman Show, The (1998)', 'Trust (1990)', 'Truth About Cats & Dogs, The (1996)', 'Truth or Consequences, N.M. (1997)', 'Turbo: A Power Rangers Movie (1997)', 'Turbulence (1997)', 'Turning, The (1992)', 'Twelfth Night (1996)', 'Twelve Monkeys (1995)', 'Twilight (1998)', 'Twin Town (1997)', 'Twisted (1996)', 'Twister (1996)', 'Two Bits (1995)', 'Two Deaths (1995)', 'Two Friends (1986) ', 'Two Much (1996)', 'Two if by Sea (1996)', 'Two or Three Things I Know About Her (1966)', 'U Turn (1997)', 'U.S. Marshalls (1998)', \"Ulee's Gold (1997)\", 'Umbrellas of Cherbourg, The (Parapluies de Cherbourg, Les) (1964)', 'Unbearable Lightness of Being, The (1988)', 'Under Siege (1992)', 'Under Siege 2: Dark Territory (1995)', 'Underground (1995)', 'Underneath, The (1995)', 'Underworld (1997)', 'Unforgettable (1996)', 'Unforgiven (1992)', 'Unhook the Stars (1996)', 'Unstrung Heroes (1995)', 'Until the End of the World (Bis ans Ende der Welt) (1991)', 'Unzipped (1995)', 'Up Close and Personal (1996)', 'Up in Smoke (1978)', 'Usual Suspects, The (1995)', 'Vampire in Brooklyn (1995)', 'Van, The (1996)', 'Vanya on 42nd Street (1994)', 'Vegas Vacation (1997)', 'Venice/Venice (1992)', 'Vermin (1998)', 'Vermont Is For Lovers (1992)', 'Vertigo (1958)', 'Very Brady Sequel, A (1996)', 'Very Natural Thing, A (1974)', 'Victor/Victoria (1982)', 'Vie est belle, La (Life is Rosey) (1987)', 'Village of the Damned (1995)', 'Virtuosity (1995)', 'Visitors, The (Visiteurs, Les) (1993)', 'Volcano (1997)', 'Wag the Dog (1997)', 'Waiting for Guffman (1996)', 'Waiting to Exhale (1995)', 'Walk in the Clouds, A (1995)', 'Walk in the Sun, A (1945)', 'Walkabout (1971)', 'Walking Dead, The (1995)', 'Walking and Talking (1996)', 'Wallace & Gromit: The Best of Aardman Animation (1996)', 'War Room, The (1993)', 'War at Home, The (1996)', 'War, The (1994)', 'Warriors of Virtue (1997)', 'Washington Square (1997)', 'Waterworld (1995)', 'Wedding Bell Blues (1996)', 'Wedding Gift, The (1994)', 'Wedding Singer, The (1998)', \"Weekend at Bernie's (1989)\", 'Welcome To Sarajevo (1997)', 'Welcome to the Dollhouse (1995)', \"Wend Kuuni (God's Gift) (1982)\", \"Wes Craven's New Nightmare (1994)\", 'What Happened Was... (1994)', \"What's Eating Gilbert Grape (1993)\", \"What's Love Got to Do with It (1993)\", 'When Harry Met Sally... (1989)', 'When Night Is Falling (1995)', 'When We Were Kings (1996)', 'When a Man Loves a Woman (1994)', 'When the Cats Away (Chacun cherche son chat) (1996)', 'While You Were Sleeping (1995)', 'White Balloon, The (1995)', \"White Man's Burden (1995)\", 'White Squall (1996)', 'Whole Wide World, The (1996)', \"Widows' Peak (1994)\", 'Wife, The (1995)', 'Wild America (1997)', 'Wild Bill (1995)', 'Wild Bunch, The (1969)', 'Wild Reeds (1994)', 'Wild Things (1998)', \"William Shakespeare's Romeo and Juliet (1996)\", 'Willy Wonka and the Chocolate Factory (1971)', 'Window to Paris (1994)', 'Wings of Courage (1995)', 'Wings of Desire (1987)', 'Wings of the Dove, The (1997)', 'Winnie the Pooh and the Blustery Day (1968)', 'Winter Guest, The (1997)', 'Wishmaster (1997)', 'With Honors (1994)', 'Withnail and I (1987)', 'Witness (1985)', 'Wizard of Oz, The (1939)', 'Wolf (1994)', 'Woman in Question, The (1950)', 'Women, The (1939)', 'Wonderful, Horrible Life of Leni Riefenstahl, The (1993)', 'Wonderland (1997)', \"Wooden Man's Bride, The (Wu Kui) (1994)\", 'World of Apu, The (Apur Sansar) (1959)', 'Wrong Trousers, The (1993)', 'Wyatt Earp (1994)', 'Yankee Zulu (1994)', 'Year of the Horse (1997)', 'You So Crazy (1994)', 'Young Frankenstein (1974)', 'Young Guns (1988)', 'Young Guns II (1990)', \"Young Poisoner's Handbook, The (1995)\", 'Zeus and Roxanne (1997)', 'unknown', 'Á köldum klaka (Cold Fever) (1994)'],\n",
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            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "07EzaQF55jN2",
        "outputId": "be32471d-6b2b-4c10-c062-1efab3b29039",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Looking into 5 samples of the title class \n",
        "# Also sorting them with the indices \n",
        "\n",
        "[dls.classes['title'][i] for i in idxs]"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Children of the Corn: The Gathering (1996)',\n",
              " 'Lawnmower Man 2: Beyond Cyberspace (1996)',\n",
              " 'Cable Guy, The (1996)',\n",
              " 'Big Bully (1996)',\n",
              " 'Crow: City of Angels, The (1996)']"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8B7IMRjA8iWR"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}