Notebooks/Explainable AI/Encoder_Physionet_Challenge_explain.ipynb

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  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "Encoder_Physionet_Challenge_explain.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "machine_shape": "hm"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NHpUgjVmZhme",
        "outputId": "bf93353d-7545-4430-e881-9f96d46475de"
      },
      "source": [
        "!pip install wfdb wget"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting wfdb\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/b1/a0/922d06ec737e219a9f45545432842e68a84e8b52f292704056eea1d35e41/wfdb-3.1.1.tar.gz (113kB)\n",
            "\u001b[K     |████████████████████████████████| 122kB 5.8MB/s \n",
            "\u001b[?25hCollecting wget\n",
            "  Downloading https://files.pythonhosted.org/packages/47/6a/62e288da7bcda82b935ff0c6cfe542970f04e29c756b0e147251b2fb251f/wget-3.2.zip\n",
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            "Collecting mne>=0.18.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/4d/0e/6448521738d3357c205795fd5846d023bd7935bb83ba93a1ba0f7124205e/mne-0.21.2-py3-none-any.whl (6.8MB)\n",
            "\u001b[K     |████████████████████████████████| 6.8MB 13.0MB/s \n",
            "\u001b[?25hCollecting nose>=1.3.7\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/15/d8/dd071918c040f50fa1cf80da16423af51ff8ce4a0f2399b7bf8de45ac3d9/nose-1.3.7-py3-none-any.whl (154kB)\n",
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            "\u001b[?25hRequirement already satisfied: numpy>=1.10.1 in /usr/local/lib/python3.6/dist-packages (from wfdb) (1.18.5)\n",
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            "Requirement already satisfied: sklearn>=0.0 in /usr/local/lib/python3.6/dist-packages (from wfdb) (0.0)\n",
            "Collecting threadpoolctl>=1.0.0\n",
            "  Downloading https://files.pythonhosted.org/packages/f7/12/ec3f2e203afa394a149911729357aa48affc59c20e2c1c8297a60f33f133/threadpoolctl-2.1.0-py3-none-any.whl\n",
            "Requirement already satisfied: urllib3>=1.22 in /usr/local/lib/python3.6/dist-packages (from wfdb) (1.24.3)\n",
            "Building wheels for collected packages: wfdb, wget\n",
            "  Building wheel for wfdb (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wfdb: filename=wfdb-3.1.1-cp36-none-any.whl size=117829 sha256=e95c3e77e8640f0b20791a8c81c58bee38399a2de9d5ba02f640c6da760bc1c4\n",
            "  Stored in directory: /root/.cache/pip/wheels/bc/d0/c1/90538d266ccba2d1076fbc9970192c7ea1a09c99df3e65c69b\n",
            "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wget: filename=wget-3.2-cp36-none-any.whl size=9681 sha256=2462ca2ed84eaddf9f1f12f9b18ff4fc71e237e68aabfa91bccf5c9dc4778c82\n",
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            "Successfully built wfdb wget\n",
            "Installing collected packages: mne, nose, threadpoolctl, wfdb, wget\n",
            "Successfully installed mne-0.21.2 nose-1.3.7 threadpoolctl-2.1.0 wfdb-3.1.1 wget-3.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "02UxjZbnFRwC"
      },
      "source": [
        "!pip install -q kaggle"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hFosbpXkOi6p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b5c727ae-6d73-4d8e-bf6f-2728daf7c966"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "L65YY9QqQZtf",
        "outputId": "f25ea065-985d-4403-e608-b0e195fc9111"
      },
      "source": [
        "import os\n",
        "import shutil\n",
        "\n",
        "shutil.copy(\"/content/drive/My Drive/kaggle.json\",\"./kaggle.json\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'./kaggle.json'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ls2UQcuoFUoz",
        "outputId": "7e93ebff-cdf4-4a77-c369-f7c83f83c7e9"
      },
      "source": [
        "!mkdir -p ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/\n",
        "!ls ~/.kaggle\n",
        "!chmod 600 /root/.kaggle/kaggle.json"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "kaggle.json\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZYvFpr3_Fbxy",
        "outputId": "2075727f-075e-4d07-fb09-b58034d38455"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/georgia-12lead-ecg-challenge-database"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading georgia-12lead-ecg-challenge-database.zip to /content\n",
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            "100% 483M/483M [00:29<00:00, 17.1MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i6z9N1N-Fejq",
        "outputId": "ac0d8762-b053-4161-dfa1-b721761763e7"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/st-petersburg-incart-12lead-arrhythmia-database"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading st-petersburg-incart-12lead-arrhythmia-database.zip to /content\n",
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            "100% 564M/564M [00:32<00:00, 18.2MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eh6rvtI3FhtZ",
        "outputId": "b24cf073-6e3c-45ae-9cc9-63473efa2b1a"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/ptbxl-electrocardiography-database"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading ptbxl-electrocardiography-database.zip to /content\n",
            " 99% 1.34G/1.35G [01:16<00:00, 27.0MB/s]\n",
            "100% 1.35G/1.35G [01:17<00:00, 18.9MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nQ10o4CbFl5P",
        "outputId": "362aa3da-9220-4484-c85f-71bd35cc73eb"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/ptb-diagnostic-ecg-database"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading ptb-diagnostic-ecg-database.zip to /content\n",
            " 99% 881M/890M [00:27<00:00, 24.9MB/s]\n",
            "100% 890M/890M [00:27<00:00, 34.3MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ubNpillvF-7I",
        "outputId": "e7cc97b6-699f-4ccf-8835-006ee074dca2"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/china-12lead-ecg-challenge-database"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading china-12lead-ecg-challenge-database.zip to /content\n",
            " 98% 399M/406M [00:24<00:00, 21.6MB/s]\n",
            "100% 406M/406M [00:26<00:00, 16.0MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fah_ygLLF9si",
        "outputId": "169df286-915f-4bd5-8777-d56450438b46"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/china-physiological-signal-challenge-in-2018"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading china-physiological-signal-challenge-in-2018.zip to /content\n",
            " 99% 817M/824M [00:46<00:00, 21.4MB/s]\n",
            "100% 824M/824M [00:46<00:00, 18.4MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "62Bmmz9w0_qt",
        "outputId": "20210846-7457-4d03-83c8-1deb2368617b"
      },
      "source": [
        "!kaggle datasets download -d bjoernjostein/physionet-snomed-mappings"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading physionet-snomed-mappings.zip to /content\n",
            "\r  0% 0.00/3.37k [00:00<?, ?B/s]\n",
            "\r100% 3.37k/3.37k [00:00<00:00, 3.16MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V-bIBSr6GMjJ"
      },
      "source": [
        "import os, zipfile\n",
        "\n",
        "dir_name = \"./\"\n",
        "extension = \".zip\"\n",
        "\n",
        "os.chdir(dir_name) # change directory from working dir to dir with files\n",
        "\n",
        "for item in os.listdir(dir_name): # loop through items in dir\n",
        "    if item.endswith(extension): # check for \".zip\" extension\n",
        "        file_name = os.path.abspath(item) # get full path of files\n",
        "        zip_ref = zipfile.ZipFile(file_name) # create zipfile object\n",
        "        zip_ref.extractall(dir_name) # extract file to dir\n",
        "        zip_ref.close() # close file\n",
        "        os.remove(file_name) # delete zipped file"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L7Znt-5GdNGs"
      },
      "source": [
        "import shutil\n",
        "import os\n",
        "\n",
        "source = 'Training_2/'\n",
        "dest1 = 'WFDB/'\n",
        "\n",
        "files = os.listdir(source)\n",
        "\n",
        "for f in files:\n",
        "    shutil.move(source+f, dest1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZduM0OfxdzQV"
      },
      "source": [
        "source = 'Training_PTB/'\n",
        "dest1 = 'WFDB/'\n",
        "\n",
        "files = os.listdir(source)\n",
        "\n",
        "for f in files:\n",
        "    shutil.move(source+f, dest1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L3UgDi5veB_X"
      },
      "source": [
        "source = 'Training_StPetersburg/'\n",
        "dest1 = 'WFDB/'\n",
        "\n",
        "files = os.listdir(source)\n",
        "\n",
        "for f in files:\n",
        "    shutil.move(source+f, dest1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wf1k84aJeKl0"
      },
      "source": [
        "source = 'Training_WFDB/'\n",
        "dest1 = 'WFDB/'\n",
        "\n",
        "files = os.listdir(source)\n",
        "\n",
        "for f in files:\n",
        "    shutil.move(source+f, dest1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ql5qFTU8cnVG"
      },
      "source": [
        "#@title Loading some packages and defining a function to load data\n",
        "import os\n",
        "import numpy as np, sys,os\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from scipy.io import loadmat\n",
        "import wfdb\n",
        "import tarfile\n",
        "import wget\n",
        "from sklearn.preprocessing import MultiLabelBinarizer\n",
        "from sklearn.model_selection import StratifiedKFold\n",
        "from keras.preprocessing.sequence import pad_sequences\n",
        "import math\n",
        "import warnings\n",
        "\n",
        "\n",
        "\n",
        "def load_challenge_data(filename):\n",
        "    x = loadmat(filename)\n",
        "    data = np.asarray(x['val'], dtype=np.float64)\n",
        "    new_file = filename.replace('.mat','.hea')\n",
        "    input_header_file = os.path.join(new_file)\n",
        "    with open(input_header_file,'r') as f:\n",
        "        header_data=f.readlines()\n",
        "    return data, header_data\n",
        "\n",
        "\n",
        "def fxn():\n",
        "    warnings.warn(\"deprecated\", DeprecationWarning)\n",
        "\n",
        "with warnings.catch_warnings():\n",
        "    warnings.simplefilter(\"ignore\")\n",
        "    fxn()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NqWJ0YPwO048"
      },
      "source": [
        "SNOMED_scored=pd.read_csv(\"SNOMED_mappings_scored.csv\", sep=\";\")\n",
        "SNOMED_unscored=pd.read_csv(\"SNOMED_mappings_unscored.csv\", sep=\";\")\n",
        "def move_unscored_ecgs():\n",
        "  os.mkdir(\"./unusedECG\")\n",
        "  eval_array = np.asarray(SNOMED_scored.iloc[0:,1])\n",
        "  for i in sorted(os.listdir(\"./WFDB/\")):\n",
        "    if i.endswith(\".mat\"):\n",
        "        data, header_data = load_challenge_data(\"./WFDB/\"+i)\n",
        "        diagnose = header_data[15][5:-1]\n",
        "        diagnose = diagnose.split(\",\")\n",
        "        diagnose = np.asarray(diagnose)\n",
        "        if pd.Series(eval_array).isin(diagnose).any():\n",
        "          pass\n",
        "        else:\n",
        "          shutil.move(\"./WFDB/\"+i,\"./unusedECG\") \n",
        "#move_unscored_ecgs()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oC5Oc1l5ns55",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7273aa80-f041-43f5-a288-1a57f527c4fc"
      },
      "source": [
        "#@title Import all diagnosis to Notebook\n",
        "def import_key_data():\n",
        "  gender=[]\n",
        "  age=[]\n",
        "  labels=[]\n",
        "  ecg_filenames=[]\n",
        "  for ecgfilename in sorted(os.listdir(\"./WFDB/\")):\n",
        "      if ecgfilename.endswith(\".mat\"):\n",
        "          print(ecgfilename)\n",
        "          data, header_data = load_challenge_data(\"./WFDB/\"+ecgfilename)\n",
        "          labels.append(header_data[15][5:-1])\n",
        "          ecg_filenames.append(\"./WFDB/\"+ecgfilename)\n",
        "          gender.append(header_data[14][6:-1])\n",
        "          age.append(header_data[13][6:-1])\n",
        "  return gender, age, labels, ecg_filenames\n",
        "\n",
        "gender_temp, age_temp, labels_temp, ecg_filenames_temp = import_key_data()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            "HR20881.mat\n",
            "HR20882.mat\n",
            "HR20883.mat\n",
            "HR20884.mat\n",
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            "HR20888.mat\n",
            "HR20889.mat\n",
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            "HR20891.mat\n",
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            "HR20893.mat\n",
            "HR20894.mat\n",
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            "HR20896.mat\n",
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            "HR20899.mat\n",
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            "HR20904.mat\n",
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            "HR20906.mat\n",
            "HR20907.mat\n",
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            "HR20912.mat\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kFzKhSEbuh3-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 893
        },
        "outputId": "3492043a-ceab-4a41-9c62-d3faf232a39f"
      },
      "source": [
        "def get_signal_length():\n",
        "  signal_lenght=[]\n",
        "  for ecgfilename in sorted(os.listdir(\"./WFDB/\")):\n",
        "      if ecgfilename.endswith(\".mat\"):\n",
        "          data, header_data = load_challenge_data(\"./WFDB/\"+ecgfilename)\n",
        "          splitted = header_data[0].split()\n",
        "          signal_lenght.append(int(splitted[3]))\n",
        "  signal_lenght_df = pd.DataFrame(signal_lenght)\n",
        "  signal_count=signal_lenght_df[0].value_counts()\n",
        "  plt.figure(figsize=(20,20))\n",
        "  sns.barplot(signal_count[:10,].index, signal_count[:10,].values)\n",
        "  #sns.distplot(signal_lenght_df[0])\n",
        "  #sns.barplot(signal_lenght_df[0])\n",
        "  #sns.barplot(signal_count[:12,].index, signal_count[:12,].values)\n",
        "  plt.ylabel(\"ECG recordings\", fontsize=18)\n",
        "  plt.xlabel(\"Signal length (samples)\", fontsize=18)\n",
        "  #plt.savefig(\"signallengde.png\",dpi = 500)\n",
        "  return signal_lenght_df\n",
        "  \n",
        "signal_lenght = get_signal_length()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1440x1440 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B2-Mhmj1pAzS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9cedfb6a-ba5f-4345-fff7-9462cc54dc29"
      },
      "source": [
        "def clean_gender_data(gender):\n",
        "  gender = np.asarray(gender)\n",
        "  gender[np.where(gender == \"Male\")] = 0\n",
        "  gender[np.where(gender == \"male\")] = 0\n",
        "  gender[np.where(gender == \"M\")] = 0\n",
        "  gender[np.where(gender == \"Female\")] = 1\n",
        "  gender[np.where(gender == \"female\")] = 1\n",
        "  gender[np.where(gender == \"F\")] = 1\n",
        "  gender[np.where(gender == \"NaN\")] = 2\n",
        "  np.unique(gender)\n",
        "  gender = gender.astype(np.int)\n",
        "  return gender\n",
        "gender_temp_binary = clean_gender_data(gender_temp)\n",
        "gender_temp_binary.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(43101,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2JCBPzaRU6Za",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "829bad5a-0784-4dee-eca5-d24abca02c60"
      },
      "source": [
        "def clean_age_data(age):\n",
        "  age = np.asarray(age)\n",
        "  age[np.where(age == \"NaN\")] = -1\n",
        "  np.unique(age)\n",
        "  age = age.astype(np.int)\n",
        "  return age\n",
        "age_temp_clean = clean_age_data(age_temp)\n",
        "age_temp_clean.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(43101,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LMdxGUdEKHlY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ed56c336-2313-4748-aad2-2a611d22578c"
      },
      "source": [
        "SNOMED_scored.iloc[21,1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "426783006"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "__MzvKNaKbDt"
      },
      "source": [
        "test_labels = pd.DataFrame(labels_temp)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3mUvvJVtKjfQ"
      },
      "source": [
        "test_labels.replace(to_replace=str(SNOMED_scored.iloc[21,1]), inplace=True ,value=\"Normal\", regex=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LmkKqpL-LynN"
      },
      "source": [
        "test_labels[test_labels != \"Normal\"] = \"Unormal\"        "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3uqbfLWjL-hu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "outputId": "a9dbba57-847f-4c7a-a048-a4c305cfeb16"
      },
      "source": [
        "test_labels"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Normal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43096</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43097</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43098</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43099</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43100</th>\n",
              "      <td>Unormal</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>43101 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             0\n",
              "0      Unormal\n",
              "1       Normal\n",
              "2      Unormal\n",
              "3      Unormal\n",
              "4      Unormal\n",
              "...        ...\n",
              "43096  Unormal\n",
              "43097  Unormal\n",
              "43098  Unormal\n",
              "43099  Unormal\n",
              "43100  Unormal\n",
              "\n",
              "[43101 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NGwJfQ2JpsAD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b062776a-b7af-4b1e-c1be-4ae20d807b31"
      },
      "source": [
        "one_hot = MultiLabelBinarizer()\n",
        "y_ohe=one_hot.fit_transform(test_labels[0].str.split(pat=','))\n",
        "print(one_hot.classes_)\n",
        "print(\"classes: {}\".format(y_ohe.shape[1]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Normal' 'Unormal']\n",
            "classes: 2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3MHJkXcBk1gX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5ab5bbbc-0475-4662-b567-9c644b4458c7"
      },
      "source": [
        "y_ohe.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(43101, 2)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N8XgKzMNdDNI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        },
        "outputId": "2997e7bf-ce1d-400c-967e-aa1f9824a290"
      },
      "source": [
        "def plot_classes(classes):\n",
        "  for j in range(len(classes)):\n",
        "    for i in range(len(SNOMED_scored.iloc[:,1])):\n",
        "      if (str(SNOMED_scored.iloc[:,1][i]) == classes[j]):\n",
        "        classes[j] = SNOMED_scored.iloc[:,0][i]\n",
        "  plt.figure(figsize=(10,10))\n",
        "  plt.bar(x=classes,height=y_ohe.sum(axis=0))\n",
        "  plt.title(\"Distribution of Diagnosis\", color = \"black\")\n",
        "  plt.tick_params(axis=\"both\", colors = \"black\")\n",
        "  plt.xlabel(\"Diagnosis\", color = \"black\")\n",
        "  plt.ylabel(\"Count\", color = \"black\")\n",
        "  plt.xticks(rotation=90, fontsize=20)\n",
        "  plt.yticks(fontsize = 20)\n",
        "  plt.savefig(\"fordeling.png\")\n",
        "  plt.show()\n",
        "\n",
        "plot_classes(one_hot.classes_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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gVOB9wJ7AKUlOmKHmBOAU4IGt/6nAY4D17XiT/dPGP7HN56Q2v/2Bc9u8JUmS7hZSVXM7QLJTVd00ZfvbgNcD76mq32nb7gt8FVgJPLGqNo6OAZwNPAF4QVWtGzvOauDLwPXAz1fVprZ9d+BzwN7A2qr6zFjNWuBfgcuA/arq+2PHuoAh9P706Fht3wuAvwU2AE8ffack+wGfBrYAe1fVD7b2e6xZs6Y2bty49R9NkpaA1a/76EJPQbpb2/T2A+d8jCQXVNWaafvm/EzktADZnN7afca2HQysAtaNAuTYMY5tH18+cZyXADsCJ42HvhYM/7B9fNlEzejz20YBstVsAt7djvfiiZrRuMeOf6eq+hxwWpv3wVO+pyRJ0rKzkA/WPKu1F41tO6C1H5/S/1zgBmBtkh1nWfOxiT7bVdPOhK5t45/XMY4kSdKytMN8DZTkNcCuDJeq1wBPYgiQbx/r9ojWXjpZX1W3JLkC+BlgL+DfZ1Hz7STXAw9OsnNV3ZBkF+BBwHVV9e0pU/1Ka/cd27Y3sAK4vKpumWWNJEnSsjVvIRJ4DfCTY58/DvxmVW0e27aytVtmOMZo+26dNbu0fjfM4RiTNZIkScvWvF3OrqoHVFWABwDPZTib+Pkkj5uvOSyUJEck2Zhk4+bNm7ddIEmStMjN+z2RVfXdqvow8EvAHsBfj+0endFbeYfC/7z9mu2o2TLRzsUY10zbWVXvrao1VbVm1apVMxxCkiRp6ViwB2uq6mvAxcDPJLl/23xJa+9wb2GSHYCHMawxefnYrq3VPJDhUvY3quqGNu71wDeBXdv+SaOnxcfvsbwMuBXYq81jNjWSJEnL1kK/9nDP1t7a2rNb+4wpffcHdgY2VNXNY9u3VvPMiT7bVdOW9NnQxn9yxziSJEnL0pyGyCT7JrnDJeAk92iLjf8EQygcrdV4BnAVcGiSNWP9dwKOax/fM3G4DwA3A69si4WPanZnWMwc4OSJmtHnY1q/Uc1q4BXteB+YqBmNe1ybz6hmP+AQYDPwocnvKkmStBzN9dPZvwz8UZJPA1cA32N4QvspDA/WfAc4fNS5qq5NcjhDmDwnyTrgauDZDEv5nMGwsDdjNVckeS3wTmBjktOAHzIs/P1g4E/H31bTajYkORF4NcOrF89geJXhIcD9gCPHFy5v1jE8EHQwwwNB6xnu6TyEYfmfw6vq2u39oSRJkpaSuQ6R/wI8nGFNyP/CsATO9Qz3Dn4QeGdVXT1eUFUfSfIU4BjgecBODK9CfHXrf4f3NFbVu5JsYlhG6EUMZ1gvZni7zF9Nm1hVHZ3kiwxnHo8AbgMuBI6vqjOn9K/26sMNDG/JORK4iWER9OOqakPH7yJJkrSkzWmIrKovAa/cjrp/ZTiL2VOzHljfWXMKcEpH/1uAd7Q/SZKku62FfrBGkiRJS5AhUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUbU5DZJI9krw0yYeTfDXJjUm2JPl0kt9Kco+J/quT1Fb+1m1lrMOSfDbJdW2Mc5IctJX+K5IcleSiNq+rk5yVZO1Wau6d5C1JLklyU5Irk5ye5JHb9wtJkiQtTTvM8fGfD7wH+DbwSeDrwE8CzwXeDzwzyfOrqibqvgB8ZMrxvjRtkCQnAEcD3wDeB9wLOBRYn+TIqjppon+AdcDBwCXAScD9gEOAc5M8r6r+YaJmR+CfgScCG4E/Bx7SvuOBSQ6oqvO3+YtIkiQtA3MdIi8Fng18tKpuG21M8nrgs8DzGALlhybq/q2q3jybAdqZw6OBy4D9qur7bfvxwAXACUnOrKpNY2WHMgTIDcDTq+qmVnMy8GngfUnOrqofjNW8miFAngEcMvo+SU5jCLx/meQx499TkiRpuZrTy9lVdXZVrZ8MVlX1HeDk9vGpd3KYl7X2baMA2cbYBLwb2BF48UTNy1t77ChAtprPAacBqxhCJnD7mcvROL83/n3aGcvzgEcBT7mT30WSJGlJWMgHa37U2lum7NszyW8neX1rH7uV4xzQ2o9P2fexiT4k2QlYC9zAEP62WQPsDTwUuLSqrphljSRJ0rI115ezp0qyA/Ci9nFa+PvF9jdecw5wWFV9fWzbLsCDgOuq6ttTjvOV1u47tm1vYAVweVVNC7DTah7R2kun9J+pRpIkadlaqDORbwceDZxVVf84tv0G4A+Anwd2b39PYXgo56nAJ1pwHFnZ2i0zjDPavtsC1NwuyRFJNibZuHnz5hkOIUmStHTMe4hM8rsMD8J8GXjh+L6qurKq3lhVF1bVNe3vXOCXgPOBhwMvne8531lV9d6qWlNVa1atWrXQ05EkSbrT5jVEJnklw9I4FwNPq6qrZ1PXLju/v33cf2zX6AzgSqYbbb9mAWokSZKWrXkLkUleBbyLYa3Hp7UntHuMrgPffjm7qq4HvgnsmuSBU2r2ae34vYyXAbcCe7V7M2dTc0lrZ7rncVqNJEnSsjUvITLJ7wPvAP6NIUBeuR2HeXxrL5/YfnZrnzGl5pkTfWhL+mwAdgaePJsahuD5dWDfJA+bZY0kSdKyNechMskbGB6kuYBhYe+rttL3cZOvQmzbnw4c1T6eOrF7tN7kMUl2H6tZDbwCuBn4wETNe1p7XFvyZ1SzH8NbazYztgB6e6POaJw/GZ9jkucwhNGLgU/N9N0kSZKWkzld4ifJYcBbGS4fnwf87rBu93+yqapOaf8+EdgnyQaGVxgCPJYfr7/4hqraMF5cVRuSnMjwRpmLkpzB8NrDQxheZXjkxNtqYHjl4XMZFhT/fJL1wB6tZgVweFVdO1FzInBQqzk/yScY1o58PsNT5S/xbTWSJOnuYq7XiRxd+l0BvGqGPp8CTmn//iDwq8B+DJeI7wl8FzgdOKmqpi0OTlUdneSLDGcejwBuAy4Ejq+qM6f0ryQvYLis/RLgSOAm4FzguMmg2mpuTvKLwOuAFzCcGb2W4ZWHb6qqi2f+GSRJkpaXDFdqNV/WrFlTGzduXOhpSNKdtvp1H13oKUh3a5vefuCcj5HkgqpaM23fQr72UJIkSUuUIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSuhkiJUmS1M0QKUmSpG6GSEmSJHUzREqSJKmbIVKSJEndDJGSJEnqZoiUJElSN0OkJEmSus1piEyyR5KXJvlwkq8muTHJliSfTvJbSaaOn2RtkrOSXN1qLkryqiQrtjLWQUnOace/Lsn5SQ7bxvwOS/LZ1n9Lqz9oK/1XJDmqzefGNr+zkqyd/a8iSZK09M31mcjnA+8DfgE4H/gz4EPAo4H3A6cnyXhBkucA5wL7Ax8GTgLuBbwDWDdtkCSvBNa3457axtwTOCXJCTPUnACcAjyw9T8VeAywvh1vsn/a+Ce2+ZzU5rc/cG6btyRJ0t1CqmruDp4cAOwCfLSqbhvb/gDgs8BDgIOr6kNt+32BrwIrgSdW1ca2fSfgbOAJwAuqat3YsVYDXwauB36+qja17bsDnwP2BtZW1WfGatYC/wpcBuxXVd8fO9YFbc4/PTpW2/cC4G+BDcDTq+qmtn0/4NPAFmDvqvrB1n6TNWvW1MaNG2fx60nS4rb6dR9d6ClId2ub3n7gnI+R5IKqWjNt35yeiayqs6tq/XiAbNu/A5zcPj51bNfBwCpg3ShAtv43Ace2jy+fGOYlwI7ASeOhrwXDP2wfXzZRM/r8tlGAbDWbgHe34714omY07rGjANlqPgec1uZ9MJIkSXcDC/lgzY9ae8vYtgNa+/Ep/c8FbgDWJtlxljUfm+izXTXtTOjaNv55HeNIkiQtSwsSIpPsALyofRwPco9o7aWTNVV1C3AFsAOw1yxrvs1wmfvBSXZuY+8CPAi4ru2f9JXW7ju2bW9gBXB5m8dsaiRJkpathToT+XaGh2DOqqp/HNu+srVbZqgbbd9tO2pWTrRzMcZu03YmOSLJxiQbN2/ePMMhJEmSlo55D5FJfhc4muFhmBfO9/gLoareW1VrqmrNqlWrFno6kiRJd9q8hsi2dM6fAxcDT6uqqye6TJ41nDTafs121GyZaOdijGtm2C9JkrSszFuITPIq4F3AlxgC5HemdLuktXe4t7DdR/kwhgdxLp9lzQMZluv5RlXdAFBV1wPfBHZt+yft09rxeywvA24F9mrzmE2NJEnSsjUvITLJ7zMsFv5vDAHyyhm6nt3aZ0zZtz+wM7Chqm6eZc0zJ/psV01b0mdDG//JHeNIkiQtS3MeIpO8geFBmgsYFum+aivdzwCuAg5NcvvClm2JnePax/dM1HwAuBl4ZVssfFSzO/D69vHkiZrR52Nav1HNauAV7XgfmKgZjXtcm8+oZj/gEGAzw9t4JEmSlr1pl2bvMu3d1W9luBR8HvC7E285BNhUVacAVNW1SQ5nCJPnJFkHXA08m2EpnzMYFva+XVVdkeS1wDuBjUlOA37IsPD3g4E/HX9bTavZkORE4NXARUnOYHiV4SHA/YAjxxcub9YBz23H/XyS9cAerWYFcHhVXdv9I0mSJC1BcxoiGe5hhCFkvWqGPp9ieIc1AFX1kSRPAY4BngfsxPAqxFcD76wp72msqncl2QS8hmH9yXswPLxzbFX91bRBq+roJF9kOPN4BHAbcCFwfFWdOaV/tVcfbmB4S86RwE0Mi6AfV1UbZv4ZJEmSlpc5fXe27sh3Z0taLnx3trSwlvW7syVJkrQ8GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdZtViEzyxNlskyRJ0t3DbM9EvmuW2yRJknQ3sMPWdiZ5ArAWWJXk1WO77gusmMuJSZIkafHaaogE7gXs2vrdZ2z7tcDBczUpSZIkLW5bDZFV9SngU0lOqaqvzdOcJEmStMht60zkyI5J3gusHq+pqgPmYlKSJEla3GYbIv83cDLwfuDWuZuOJEmSloLZhshbquo9czoTSZIkLRmzXeJnfZLfSfLAJPcb/c3pzCRJkrRozfZM5GGtfe3YtgL2umunI0mSpKVgViGyqh421xORJEnS0jGrEJnkRdO2V9Vf37XTkSRJ0lIw28vZ+439eyfg6cCFgCFSkiTpbmi2l7OPHP+cZDdg3ZzMSJIkSYvebJ/OnnQ94H2SkiRJd1OzvSdyPcPT2AArgEcCp8/VpCRJkrS4zfaeyBPG/n0L8LWq+sYczEeSJElLwKwuZ1pXu9UAACAASURBVFfVp4AvA/cBdgd+OJeTkiRJ0uI2qxCZ5NeAzwLPB34NOD/JwXM5MUmSJC1es72cfQywX1VdCZBkFfAvwBlzNTFJkiQtXrN9OvseowDZfK+jVpIkScvMbM9EfjzJPwJ/1z4fApw1N1OSJEnSYrfVEJnk4cBPVtVrkzwXeFLb9Rngb+Z6cpIkSVqctnUm8s+A/wlQVX8P/D1Akse0fc+a09lJkiRpUdrWfY0/WVVfnNzYtq2ekxlJkiRp0dtWiNxtK/vufVdORJIkSUvHtkLkxiSHT25M8lLggrmZkiRJkha7bd0T+Srgw0l+nR+HxjXAvYBfncuJSZIkafHaaoisqu8Ca5M8DXh02/zRqjp7zmcmSZKkRWtW60RW1SeBT87xXCRJkrRE+NYZSZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd3mPEQmOTjJu5Kcl+TaJJXk1Bn6rm77Z/pbt5VxDkvy2STXJdmS5JwkB22l/4okRyW5KMmNSa5OclaStVupuXeStyS5JMlNSa5McnqSR/b9KpIkSUvbDvMwxrHAzwLXAd8AfnoWNV8APjJl+5emdU5yAnB0O/77gHsBhwLrkxxZVSdN9A+wDjgYuAQ4CbgfcAhwbpLnVdU/TNTsCPwz8ERgI/DnwEOA5wMHJjmgqs6fxXeTJEla8uYjRB7FEO6+CjwF+OQsav6tqt48m4O3M4dHA5cB+1XV99v244ELgBOSnFlVm8bKDmUIkBuAp1fVTa3mZODTwPuSnF1VPxireTVDgDwDOKSqbms1pzEE3r9M8pjRdkmSpOVszi9nV9Unq+orVVVzNMTLWvu2UYBs424C3g3sCLx4oublrT12FCBbzeeA04BVDCETuP3M5Wic3xsPiu2M5XnAoxhCsiRJ0rK3WB+s2TPJbyd5fWsfu5W+B7T241P2fWyiD0l2AtYCNzCEv23WAHsDDwUuraorZlkjSZK0bM3H5ezt8Yvt73ZJzgEOq6qvj23bBXgQcF1VfXvKcb7S2n3Htu0NrAAur6pbZlnziNZeOsN8p9VIkiQtW4vtTOQNwB8APw/s3v5G91E+FfhEC44jK1u7ZYbjjbbvtgA1kiRJy9aiCpFVdWVVvbGqLqyqa9rfucAvAecDDwdeurCz7JfkiCQbk2zcvHnzQk9HkiTpTltUIXIm7bLz+9vH/cd2jc4ArmS60fZrFqDmdlX13qpaU1VrVq1aNcMhJEmSlo4lESKb0Sm82y9nV9X1wDeBXZM8cErNPq0dv5fxMuBWYK8k0+4JnVZzSWtnuudxWo0kSdKytZRC5ONbe/nE9rNb+4wpNc+c6ENb0mcDsDPw5NnUMATPrwP7JnnYLGskSZKWrUUVIpM8Lskd5pTk6QyLlgNMvjLx5NYek2T3sZrVwCuAm4EPTNS8p7XHtSV/RjX7Mby1ZjPwodH2tsblaJw/GZ9jkucwhNGLgU9t80tKkiQtA3O+xE+SXwF+pX18QGufkOSU9u+rquo17d8nAvsk2cDwlhuAx/Lj9RffUFUbxo9fVRuSnMjwRpmLkpzB8NrDQxheZXjkxNtqYHjl4XMZFhT/fJL1wB6tZgVweFVdO1FzInBQqzk/yScY1o58PsNT5S/xbTWSJOnuYj7Wifw54LCJbXu1P4CvAaMQ+UHgV4H9GC4R3xP4LnA6cFJVTVscnKo6OskXGc48HgHcBlwIHF9VZ07pX0lewHBZ+yXAkcBNwLnAcZNBtdXcnOQXgdcBL2A4M3otwysP31RVF2/7p5AkSVoeMndvI9Q0a9asqY0bNy70NCTpTlv9uo8u9BSku7VNbz9wzsdIckFVrZm2b1HdEylJkqSlwRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSeo2pyEyycFJ3pXkvCTXJqkkp26jZm2Ss5JcneTGJBcleVWSFVupOSjJOUm2JLkuyflJDtvGOIcl+Wzrv6XVH7SV/iuSHNXmc2Ob31lJ1m77l5AkSVpe5vpM5LHAK4GfA765rc5JngOcC+wPfBg4CbgX8A5g3Qw1rwTWA48GTgXeB+wJnJLkhBlqTgBOAR7Y+p8KPAZY34432T9t/BPbfE5q89sfOLfNW5Ik6W5jrkPkUcC+wH2Bl2+tY5L7MgS6W4GnVtVvVdVrGQLoZ4CDkxw6UbMaOAG4GlhTVa+oqqOAxwKXAUcnecJEzVrg6Lb/sVV1VFW9Avj5dpwT2nHHHQocDGwAfq6qXltVvwU8rc33fUnuM9sfRZIkaamb0xBZVZ+sqq9UVc2i+8HAKmBdVW0cO8ZNDGc04Y5B9CXAjsBJVbVprOb7wB+2jy+bqBl9flvrN6rZBLy7He/FEzWjcY9t8xnVfA44rc374G1+Q0mSpGViMT1Yc0BrPz5l37nADcDaJDvOsuZjE322qybJTsDaNv55HeNIkiQtW4spRD6itZdO7qiqW4ArgB2AvWZZ823geuDBSXYGSLIL8CDgurZ/0ldau+/Ytr2BFcDlbR6zqZEkSVrWFlOIXNnaLTPsH23fbTtqVk60czHGbjPsJ8kRSTYm2bh58+aZukmSJC0ZiylELltV9d6qWlNVa1atWrXQ05EkSbrTFlOInDxrOGm0/ZrtqNky0c7FGNfMsF+SJGnZWUwh8pLW3uHewiQ7AA8DbgEun2XNA4FdgG9U1Q0AVXU9w3qVu7b9k/Zp7fg9lpcxLOOzV5vHbGokSZKWtcUUIs9u7TOm7Nsf2BnYUFU3z7LmmRN9tqumLemzoY3/5I5xJEmSlq3FFCLPAK4CDk2yZrSxLbFzXPv4nomaDwA3A68cXyA8ye7A69vHkydqRp+Paf1GNauBV7TjfWCiZjTucW0+o5r9gEOAzcCHtvH9JEmSlo1pl2fvMkl+BfiV9vEBrX1CklPav6+qqtcAVNW1SQ5nCJPnJFnH8AaZZzMs5XMGw8Let6uqK5K8FngnsDHJacAPGRb+fjDwp1X1mYmaDUlOBF4NXJTkDIZXGR4C3A84cnzh8mYd8Nx23M8nWQ/s0WpWAIdX1bXb8RNJkiQtSXMaIhleWXjYxLa9+PFaj18DXjPaUVUfSfIU4BjgecBOwFcZAt87p735pqrelWRTO86LGM6uXszwdpm/mjapqjo6yRcZzjweAdwGXAgcX1VnTulfSV7AcFn7JcCRwE0Mi6AfV1Ubtv1TSJIkLR+Z3RsJdVdZs2ZNbdy4cdsdJWmRW/26jy70FKS7tU1vP3DOx0hyQVWtmbZvMd0TKUmSpCXCEClJkqRuhkhJkiR1M0RKkiSp21w/na0F4g3v0sKajxveJWkheSZSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSpmyFSkiRJ3QyRkiRJ6maIlCRJUjdDpCRJkroZIiVJktTNEClJkqRuhkhJkiR1M0RKkiSp26IMkUk2JakZ/r4zQ83aJGcluTrJjUkuSvKqJCu2Ms5BSc5JsiXJdUnOT3LYNuZ2WJLPtv5bWv1Bd/Y7S5IkLSU7LPQEtmIL8GdTtl83uSHJc4APATcBpwFXA88C3gE8EXj+lJpXAu8CvgecCvwQOBg4Jcljquo1U2pOAI4GvgG8D7gXcCiwPsmRVXVS/9eUJElaehZziLymqt68rU5J7ssQ6G4FnlpVG9v2NwBnAwcnObSq1o3VrAZOYAiba6pqU9v+VuBzwNFJPlRVnxmrWcsQIC8D9quq77ftxwMXACckOXN0LEmSpOVsUV7O7nQwsApYNwqQAFV1E3Bs+/jyiZqXADsCJ42HvhYM/7B9fNlEzejz20YBstVsAt7djvfiO/NFJEmSlorFHCJ3TPIbSV6f5H8kedoM9zce0NqPT9l3LnADsDbJjrOs+dhEnztTI0mStCwt5svZDwA+OLHtiiQvrqpPjW17RGsvnTxAVd2S5ArgZ4C9gH+fRc23k1wPPDjJzlV1Q5JdgAcB11XVt6fM9Sut3Xc2X0ySJGmpW6xnIj8APJ0hSO4CPAb4f4HVwMeS/OxY35Wt3TLDsUbbd9uOmpUTbc8Yt0tyRJKNSTZu3rx5hkNIkiQtHYsyRFbVW6rq7Kr6blXdUFVfqqqXAScC9wbevLAz7FNV762qNVW1ZtWqVQs9HUmSpDttUYbIrTi5tfuPbZs8azhptP2a7ajZMtH2jCFJkrRsLbUQOboWvMvYtktae4f7EZPsADwMuAW4fJY1D2zH/0ZV3QBQVdcD3wR2bfsn7dPaO9xjKUmStBwttRD5+NaOB8KzW/uMKf33B3YGNlTVzbOseeZEnztTI0mStCwtuhCZ5JHtaejJ7auB0RthTh3bdQZwFXBokjVj/XcCjmsf3zNxuA8ANwOvbMcd1ewOvL59PHmiZvT5mNZvfF6vaMf7wFa+miRJ0rKxGJf4OYThjTHnAl8DfgDsDRwI7AScxfC2GQCq6tokhzOEyXOSrGN4E82zGZbyOYPhVYiM1VyR5LXAO4GNSU7jx689fDDwp+Nvq2k1G5KcCLwauCjJGQyvPTwEuB9wpG+rkSRJdxeLMUR+kiH8/ReG917vwvDAyqcZ1o38YFXVeEFVfSTJU4BjgOcxhM2vMgS+d072bzXvSrIJeA3wIoazshcDx1bVX02bWFUdneSLDGcejwBuAy4Ejq+qM+/k95YkSVoyFl2IbAuJf2qbHe9Y96/AL3fWrAfWd9acApzSUyNJkrTcLLp7IiVJkrT4GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshUpIkSd0MkZIkSepmiJQkSVI3Q6QkSZK6GSIlSZLUzRApSZKkboZISZIkdTNESpIkqZshslOSByf5yyTfSnJzkk1J/izJ7gs9N0mSpPmyw0JPYClJsjewAfgJ4B+ALwP/FfgfwDOSPLGqvreAU5QkSZoXnons8xcMAfJ3q+pXqup1VXUA8A7gEcDbFnR2kiRJ88QQOUvtLOQvAZuAd0/sfhNwPfDCJLvM89QkSZLmnSFy9p7W2n+qqtvGd1TVD4B/BXYGHj/fE5MkSZpvhsjZe0RrL51h/1dau+88zEWSJGlBGSJnb2Vrt8ywf7R9t3mYiyRJ0oLy6ex5kOQI4Ij28boklyzkfLRk3B+4aqEnoe2TP17oGUjb5H9jlrh5+u/MT820wxA5e6MzjStn2D/afs3kjqp6L/DeuZiUlq8kG6tqzULPQ9Ly5H9jdGd5OXv2RmcPZ7rncZ/WznTPpCRJ0rJhiJy9T7b2l5L8p98tyX2AJwI3AP/ffE9MkiRpvhkiZ6mqLgP+CVgNvGJi91uAXYAPVtX18zw1LV/eAiFpLvnfGN0pqaqFnsOSMeW1h/8O/ALDGpKXAmt97aEkSbo7MER2SvIQ4K3AM4A9gG8DHwbeUlXfX8i5SZIkzRdDpCRJkrp5T6QkSZK6GSIlSZLUzRApSZKkbr6xRpKkZSjJ/ttbW1Xn3pVz0fLkgzXSAkhy+XaWVlXtfZdORtKylOQ2YLv+T76qVtzF09Ey5JlIaWHcg+37j3vu6olIWrbeynaGSGk2PBMpSZKkbj5YI0mSpG6GSEmSJHXznkhpEUmy4//f3p0HWVaWdxz//gZmZN8xCoQQh3J0AigqawGyaMSIQiVATFJEo5LFLSQQQxUIBogS0IjEpEJJUgpJJCBFLFCiEEgBM0DYh0VIlEUYoRAHCZbBYXnyxzktPU3PdN9mps+5d76ff7h97ntnfkNVv/30e877vMBuwLbAKyYbU1XnzWooSSMjSYDDgXew8nmmquqgWQ2moeQzkVJPJPkAcAaw+cqG0Ezu7pqUNLD2l9RvAvvTziesuFlv7GvnGU2Lt7OlHkhyMHAu8ChwHM1E/nXgBOCK9uuLgA90lVHS0Ptz4ADgNGArmnnlU8A2wG8DDwMXAPM6yqchYxEp9cOxwI+Avavq8+2126vq9Ko6GDga+HXge10FlDT0jgBuraqTq2rZ2MWqeqyqLgAOBA4BjukqoIaLRaTUD28CLq2qp8dd+/n3Z1X9A7CIZmVSkmZiPs08MqaAuT//oup+4BvA+2c3loaVRaTUDxvS3Moe8wywyYQxNwN7zFoiSaPmWZq5ZczTwNYTxjwEvGbWEmmoWURK/fAYK07mjwILJozZFPBhd0kz9QjNjuwx/w3sNWHMrsAypGmwiJT64W5WLBqvBQ5Ksi9Akp2AI9txkjQTi4C9x339b8DOSc5N8q4kZwJvA/6zi3AaPrb4kXogyUeBs4Dtq+oHSRYCNwHr0awKbEGzk/KQqvpmd0klDask+9Ps0P6jqnowyQbA1TS9acfa+3wXOKCqlnYWVEPDIlLqgSRzaQrFJ6tqeXttT+BEmofhHwTOqqpvdRZS0shJsi5wKLAjzTxzaVX9tNNQGhoWkZIkSRqYz0RKkiRpYJ6dLfVMe7btqxjXv228qvr+7CaSNEqS7AK8AdiOyeeZqqpTZzeVhpG3s6WeSHIEcDywEyv/Ba+qyl/+JA0syRbA+cDBY5dWMtSzszUt/jCSeiDJR4Czgedo2nAsbV9L0upyFvBO4Ergn3Ce0cvkSqTUA0m+S3Nqzd5V9UDXeSSNniTLgHuqap+us2g0uLFG6odtgYssICWtQesAi7sOodFhESn1w8PAK7oOIWmk3YrnYms1soiU+uErwDuTbNx1EEkj61TgkCTeztZq4TORUg8kWQe4kKblxieAW6vq6W5TSRo1SQ4DvgRcRrMy+dRk46rqvNnMpeFkESn1RJIDgYuAzVYxzBY/kmYkyTzgHOAoXrwTObEICLb40TT5w0jqgSSHAl+jefD9AeAH2HpD0ur1GeB9wD3Av+I8o5fJlUipB5LcRvPA+7uq6rqu80gaPUmWAk8Au1XV8q7zaPi5sUbqhwXAVy0gJa1BmwHftoDU6mIRKfXDE4ATu6Q16TvAq7sOodFhESn1w8XA25PM7TqIpJH1OeCwJK/tOohGg89ESj2QZEPgCuBx4JiqerDbRJJGTZL9gI8DBwFfAG5h5S1+rpnFaBpSFpFSDyS5H5gLbNNe+jGTT+5VVfNnLZikkZHkBZqWPmkvrbQAsMWPpsMWP1I/zKFptfH9cdcyybjJrknSdJzCKgpHaVCuREqSJGlgbqyReiDJSUmO6jqHpNGV5P4kX+w6h0aHRaTUDycCO3cdQtJI2xr4365DaHRYREr9sBTYpOsQkkba3YAb87TaWERK/XAJ8LYk63cdRNLIOht4d5Jdug6i0eDGGqkHkmwMXAUsA46tqrs6jiRpxLR9Io8DDgDOAW4CHmOSHdv2idR0WERKPdD2iZzHi0eSPUPTeHziN6h9IiXNiH0itbrZJ1LqhznAs6zYJxJe2hfSPpGSZso+kVqtXImUJEnSwNxYI0mSpIF5O1vqoXajzWbAU1VlXzdJq1WSfYBdaecZ4Naquq7bVBo23s6WeiLJujQ7Jz8E/PK4tx4AzgU+W1XPdZFN0mhI8mbgfGDB2CVefE7yPuB3q+rmLrJp+FhESj2QZB7w78BbaSb0R4BHaXZrb0cz0V8L/GpVLe8qp6ThlWRH4Gaagw2uo2krNjbPHAjsQ7MquXtV/U9XOTU8fCZS6oc/BfYHvgG8vqp2qKq9qmoHmhWDS4F923GSNBOfBDYGfrOq9quqT1XVOe1/9wOObN8/sdOUGhquREo9kGRJ+/KNVfXCJO/PAW6n+Z71jG1JA0uyFLi+qg5fxZiLgT2ratvZS6Zh5Uqk1A87ApdPVkACtNcvx3NvJc3cVsC9U4y5tx0nTckiUuqH5cBGU4zZkKYhuSTNxA+BhVOMeR3wxCxk0QiwiJT6YQlweJKtJ3szyVbA4cAds5pK0ii5CnhPkvdO9maS3wAOBa6c1VQaWj4TKfVAkiOBC4CHgNOAq2l2Tb6KZsPNicAOwG9V1YXdpJQ0zNrd2bfQ3PVYzEvnmX2Ap4Hd3J2t6bCIlHoiyaeB45n8bNsAZ1TV8bObStIoSbIbcB4v9oksmvkFmj6R76uq/+oim4aPRaTUI0n2BD5Ic5LEpjQ9224D/rGqru8ym6TRkWRv4E2Mm2eqalG3qTRsLCIlSZI0MDfWSJIkaWDrdh1AWlu1DcQHtrJekpI0lSRzaXZg7w5sDqwzybCqqg/OajANJW9nSx1J8vwMPlZV5S9/kgaWZBvgCppekFnF0KqqyYpLaQX+MJK68zCT78SezEbAlmswi6TR9zng9cBXgS/RzEHPdZpIQ82VSKnH2ltPHwNOoLn19EBVefShpIEl+RFwZ1Xt33UWjQY31kg9leQI4DvAmTS3nj5Bs4ogSTOxHnBj1yE0OrydLfVM27/ts8AeNLeazgZOqaonOw0madjdBfxS1yE0OlyJlHoiyfwkXwOuBfYELgYWVtWfWEBKWg3OpDk7e2HXQTQaXImUOpZkC+Bk4A+AecD1wLFVdUOnwSSNmseBS4HFSb5Ac472jycbWFXXzGYwDSc31kgdSTIPOIbmvOzNgO8Bx1fVxZ0GkzSSkrzAimdlr7QAsMWPpsOVSKk79wHbA8toism/raqZ9I6UpOk4hem3FZOm5Eqk1JFxqwJPAj+d5seqqnwwXpLUOYtIqSNtETmwqnJDnCSpcxaRkiSNqCT3TzHkBZrNNXcAX66qa9d8Ko0Ki0hJkkbUgHc8Cji9qk5YU3k0WiwiJUkaUUmmeoZ6DrAVsDfwZ8CrgV+rqm+t6WwafhaRkiSJJNsBdwNXV9VhXedR//mAviRJoqoeAb4O7N51Fg0Hi0hJkjTmIWDLrkNoOFhESpKkMZsA/9d1CA0Hi0hJkjTm7TSnaUlTsoiUJGktl2TzJOcCC4BLus6j4eDubEmSRlSSq6YYMofmGcjXAnNpdmfvUVXTPYpVazGLSEmSRtQAzcZ/BlwAHFtVy9ZgJI2QdbsOIEmS1pgDpnj/BeAp4L6q+tks5NEIcSVSkiRJA3NjjSRJkgZmESlJkqSBWURK0ixJ8nyS25PcneSOJMcmmdO+95YkZ3ecr/MMkoaHz0RK0ixJ8pOq2qh9/UrgX4BFVXVyt8kkaXCuREpSB6rqceD3gY+msX+SywCS7J7k+iS3JVmcZEF7fYMkFya5J8klSW5M8pb2vZ8k+ct2hfOGJL/QXt8hyVVJliT5jyTbt9ePSHJXO/6a9tr4DG9tV01vb3NsPPv/lyT1mUWkJHWkqu4H1gFeOeGte4F9q2pX4CTg0+31DwNPVtVC4JPAm8d9ZkPghqp6A3ANcHR7/W+Ar1TVLsA/A2O3q08C3tGOf88k8Y4DPlJVbwT2xfOUJU1gESlJ/bMpcFGSu4DPA7/SXt+HpiE0VXUXsGTcZ5YDl7WvbwF2aF/vRXPbHOD89s8AWAR8OcnRNIXsRIuAv07ycWCzqnruZf6bJI0Yi0hJ6kiS1wDPA49PeOtU4Oqq2gl4N7DeNP64Z+vFh9yfZ4rDJKrqD4ETgV8Ebkmy5YT3Twc+BKwPLEryumlkkLQWsYiUpA4k2Rr4e+CL9dIdjpsCS9vX7x93fRFwZPv5hcDO0/irFgPvbV//DnBt+/n5VXVjVZ0E/JCmmByfb35V3VlVfwXcBFhESlqBRaQkzZ71x1r8AFcC3wb+YpJxZwCfSXIbK64o/h2wdZJ7bzFKpwAAAJVJREFUgNOAu2mOrFuVjwG/l2QJcBTwx+31M5Pc2d4yXwzcMeFzx7Qbb5YAzwKXT/tfKWmtYIsfSRoSSdYB5lbVM0nm0xSiC6pqecfRJK2FVvnMjCSpVzYArk4yFwjwYQtISV1xJVKSJEkD85lISZIkDcwiUpIkSQOziJQkSdLALCIlSZI0MItISZIkDcwiUpIkSQP7f4SsfB5+uWbHAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2osv0gNySxCD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ea2ff0d2-1809-44d0-9cb4-5ac2977cc9ff"
      },
      "source": [
        "#@title Transform our One Hot encoded multilabel output to a new type of label where all can be represented by a number:\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "def get_new_labels(y):\n",
        "    y_new = LabelEncoder().fit_transform([''.join(str(l)) for l in y])\n",
        "    return y_new\n",
        "\n",
        "y_ohe_new = get_new_labels(y_ohe)\n",
        "print(\"Total number of unique combinations of diagnosis: {}\".format(len(np.unique(y_ohe_new))))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total number of unique combinations of diagnosis: 2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PZS0jJN_R2S5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dbfe9bce-45db-4161-be60-2ed630a69337"
      },
      "source": [
        "#@title K-fold, 10 splits, Shuffle=True and random_state = 42. The distribution of Training and Val data in each fold is now:\n",
        "from sklearn.model_selection import StratifiedKFold\n",
        "folds = list(StratifiedKFold(n_splits=10, shuffle=True, random_state=42).split(test_labels,y_ohe_new))\n",
        "print(\"Training split: {}\".format(len(folds[0][0])))\n",
        "print(\"Validation split: {}\".format(len(folds[0][1])))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Training split: 38790\n",
            "Validation split: 4311\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TsFUOWLgT070",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "cd28a4fc-f1c2-449f-e31c-c134c19fa9cc"
      },
      "source": [
        "#@title The distribution of diagnosis in each Fold:\n",
        "X_axis_labels=one_hot.classes_\n",
        "plt.figure(figsize=(20,100))\n",
        "h=1\n",
        "for i in range(len(folds)):\n",
        "  plt.subplot(10,2,h)\n",
        "  plt.subplots_adjust(hspace=1.0)\n",
        "  plt.bar(x= X_axis_labels, height=y_ohe[folds[i][0]].sum(axis=0))\n",
        "  plt.title(\"Distribution of Diagnosis - Training set - Fold {}\".format(i+1) ,fontsize=\"20\", color = \"white\")\n",
        "  plt.tick_params(axis=\"both\", colors = \"white\")\n",
        "  plt.xticks(rotation=90, fontsize=10)\n",
        "  plt.yticks(fontsize = 10)\n",
        "  #plt.xlabel(\"Diagnosis\", color = \"white\")\n",
        "  plt.ylabel(\"Count\", color = \"white\")\n",
        "  h=h+1\n",
        "  plt.subplot(10,2,h)\n",
        "  plt.subplots_adjust(hspace=1.0)\n",
        "  plt.bar(x= X_axis_labels, height=y_ohe[folds[i][1]].sum(axis=0))\n",
        "  plt.title(\"Distribution of Diagnosis - Validation set - Fold {}\".format(i+1) ,fontsize=\"20\", color = \"white\")\n",
        "  plt.tick_params(axis=\"both\", colors = \"white\")\n",
        "  #plt.xlabel(\"Diagnosis\", color = \"white\")\n",
        "  plt.ylabel(\"Count\", color = \"white\")\n",
        "  plt.xticks(rotation=90, fontsize=10)\n",
        "  plt.yticks(fontsize = 10)\n",
        "  h=h+1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x7200 with 20 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "dark"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zSI_XLBQOWmB"
      },
      "source": [
        "import tensorflow as tf\r\n",
        "import tensorflow_addons as tfa"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rpom3rDRONqZ"
      },
      "source": [
        "reduce_lr = tf.keras.callbacks.ReduceLROnPlateau(\r\n",
        "    monitor='val_AUC', factor=0.1, patience=1, verbose=1, mode='max',\r\n",
        "    min_delta=0.0001, cooldown=0, min_lr=0\r\n",
        ")\r\n",
        "\r\n",
        "early_stop = tf.keras.callbacks.EarlyStopping(monitor='val_AUC', mode='max', verbose=1, patience=2)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W8GzafDIOVI3"
      },
      "source": [
        "def encoder_model():\r\n",
        "    input_layer = tf.keras.layers.Input(shape=(5000, 12))\r\n",
        "\r\n",
        "\r\n",
        "     # conv block -1\r\n",
        "    conv1 = tf.keras.layers.Conv1D(filters=128,kernel_size=5,strides=1,padding='same')(input_layer)\r\n",
        "    conv1 = tfa.layers.InstanceNormalization()(conv1)\r\n",
        "    conv1 = tf.keras.layers.PReLU(shared_axes=[1])(conv1)\r\n",
        "    conv1 = tf.keras.layers.Dropout(rate=0.2)(conv1)\r\n",
        "    conv1 = tf.keras.layers.MaxPooling1D(pool_size=2)(conv1)\r\n",
        "    # conv block -2\r\n",
        "    conv2 = tf.keras.layers.Conv1D(filters=256,kernel_size=11,strides=1,padding='same')(conv1)\r\n",
        "    conv2 = tfa.layers.InstanceNormalization()(conv2)\r\n",
        "    conv2 = tf.keras.layers.PReLU(shared_axes=[1])(conv2)\r\n",
        "    conv2 = tf.keras.layers.Dropout(rate=0.2)(conv2)\r\n",
        "    conv2 = tf.keras.layers.MaxPooling1D(pool_size=2)(conv2)\r\n",
        "    # conv block -3\r\n",
        "    conv3 = tf.keras.layers.Conv1D(filters=512,kernel_size=21,strides=1,padding='same')(conv2)\r\n",
        "    conv3 = tfa.layers.InstanceNormalization()(conv3)\r\n",
        "    conv3 = tf.keras.layers.PReLU(shared_axes=[1])(conv3)\r\n",
        "    conv3 = tf.keras.layers.Dropout(rate=0.2)(conv3)\r\n",
        "    # split for attention\r\n",
        "    attention_data = tf.keras.layers.Lambda(lambda x: x[:,:,:256])(conv3)\r\n",
        "    attention_softmax = tf.keras.layers.Lambda(lambda x: x[:,:,256:])(conv3)\r\n",
        "    # attention mechanism\r\n",
        "    attention_softmax = tf.keras.layers.Softmax()(attention_softmax)\r\n",
        "    multiply_layer = tf.keras.layers.Multiply()([attention_softmax,attention_data])\r\n",
        "    # last layer\r\n",
        "    dense_layer = tf.keras.layers.Dense(units=256,activation='sigmoid')(multiply_layer)\r\n",
        "    dense_layer = tfa.layers.InstanceNormalization()(dense_layer)\r\n",
        "    # output layer\r\n",
        "    flatten_layer = tf.keras.layers.Flatten()(dense_layer)\r\n",
        "    output_layer = tf.keras.layers.Dense(units=2,activation='softmax')(flatten_layer)\r\n",
        "\r\n",
        "    model = tf.keras.models.Model(inputs=input_layer, outputs=output_layer)\r\n",
        "\r\n",
        "    model.compile(loss=tf.keras.losses.CategoricalCrossentropy(), optimizer=tf.keras.optimizers.Adam(learning_rate=0.001), metrics=[tf.keras.metrics.BinaryAccuracy(\r\n",
        "        name='accuracy', dtype=None, threshold=0.5),tf.keras.metrics.Recall(name='Recall'),tf.keras.metrics.Precision(name='Precision'), \r\n",
        "                        tf.keras.metrics.AUC(\r\n",
        "            num_thresholds=200,\r\n",
        "            curve=\"ROC\",\r\n",
        "            summation_method=\"interpolation\",\r\n",
        "            name=\"AUC\",\r\n",
        "            dtype=None,\r\n",
        "            thresholds=None,\r\n",
        "            multi_label=True,\r\n",
        "            label_weights=None,\r\n",
        "        )])\r\n",
        "\r\n",
        "    return model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HKrer0d3PxcP"
      },
      "source": [
        "ecg_filenames = np.asarray(ecg_filenames_temp)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zCNzDoQEPb8V"
      },
      "source": [
        "ecg_train_files = ecg_filenames[folds[0][0]]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e5-cWcmlQAoK"
      },
      "source": [
        "ecg_val_files = ecg_filenames[folds[0][1]]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TdHN5wlgRIOi"
      },
      "source": [
        "y_train = y_ohe[folds[0][0]]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IMJbwTVTREoy"
      },
      "source": [
        "y_val = y_ohe[folds[0][1]]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nGqBBQs5QiCe"
      },
      "source": [
        "def batch_generator(batch_size,train_index,y_, gen_x,gen_y): \r\n",
        "    np.random.shuffle(train_index)\r\n",
        "    batch_features = np.zeros((batch_size,5000, 12))\r\n",
        "    batch_labels = np.zeros((batch_size,y_.shape[1])) #drop undef class\r\n",
        "    while True:\r\n",
        "        for i in range(batch_size):\r\n",
        "\r\n",
        "            batch_features[i] = next(gen_x)\r\n",
        "            batch_labels[i] = next(gen_y)\r\n",
        "\r\n",
        "        yield batch_features, batch_labels\r\n",
        "\r\n",
        "def generate_y(y):\r\n",
        "    while True:\r\n",
        "        for i in train_index:\r\n",
        "            y_batch = y[i] # y_train_ohe\r\n",
        "            yield y_batch\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "def generate_X(X_name):\r\n",
        "    while True:\r\n",
        "        for i in train_index:\r\n",
        "                    data, header_data = load_challenge_data(X_name[i])\r\n",
        "                    X_batch = pad_sequences(data, maxlen=5000, truncating='post',padding=\"post\")\r\n",
        "                    X_batch = X_batch.reshape(5000,12)\r\n",
        "                    yield X_batch"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k6bJvRcBRlj3"
      },
      "source": [
        "X_val = []\r\n",
        "for j in ecg_val_files:\r\n",
        "  data = load_challenge_data(j)[0]\r\n",
        "  ecg = pad_sequences(data, maxlen=5000, truncating='post',padding=\"post\")\r\n",
        "  ecg_shaped = ecg.reshape(5000,12)\r\n",
        "  X_val.append(ecg_shaped)\r\n",
        "X_val = np.asarray(X_val)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g_dQ1FlHxMdh"
      },
      "source": [
        "from sklearn.utils.class_weight import compute_class_weight\r\n",
        "\r\n",
        "def calculating_class_weights(y_true):\r\n",
        "    number_dim = np.shape(y_true)[1]\r\n",
        "    weights = np.empty([number_dim, 2])\r\n",
        "    for i in range(number_dim):\r\n",
        "        weights[i] = compute_class_weight('balanced', [0.,1.], y_true[:, i])\r\n",
        "    return weights"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yitq_4UcxQYC"
      },
      "source": [
        "new_weights=calculating_class_weights(y_train)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wlkc3w4OxhaF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1a4f9df6-d37b-4e4c-acbe-65d1a45a0c97"
      },
      "source": [
        "keys = np.arange(0,2,1)\r\n",
        "weight_dictionary = dict(zip(keys, new_weights.T[1]))\r\n",
        "weight_dictionary"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{0: 2.3472104562507563, 1: 0.6353392079143053}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nbf8YqArUHDW"
      },
      "source": [
        "train_index = np.arange(ecg_train_files.shape[0])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pTmA0759Azm1"
      },
      "source": [
        "model = encoder_model()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kA0PWIXpQmkx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1247251c-5187-4bf2-c1f0-fc38b66d5adb"
      },
      "source": [
        "batchsize = 30\r\n",
        "\r\n",
        "model.fit(x=batch_generator(batch_size=batchsize,train_index=np.arange(ecg_train_files.shape[0]),y_=y_train, gen_x=generate_X(ecg_train_files), gen_y=generate_y(y_train)), epochs=2,verbose =1, steps_per_epoch=(len(np.arange(ecg_train_files.shape[0]))/batchsize), validation_freq=1,validation_data=(X_val,y_val),class_weight=weight_dictionary, callbacks=[reduce_lr,early_stop])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/2\n",
            "1293/1293 [==============================] - 98s 76ms/step - loss: 0.4240 - accuracy: 0.8059 - Recall: 0.8059 - Precision: 0.8059 - AUC: 0.8934 - val_loss: 1.2965 - val_accuracy: 0.3616 - val_Recall: 0.3616 - val_Precision: 0.3616 - val_AUC: 0.7266\n",
            "Epoch 2/2\n",
            "1293/1293 [==============================] - 97s 75ms/step - loss: 0.3878 - accuracy: 0.8219 - Recall: 0.8219 - Precision: 0.8219 - AUC: 0.9084 - val_loss: 0.9294 - val_accuracy: 0.5340 - val_Recall: 0.5340 - val_Precision: 0.5340 - val_AUC: 0.8090\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7fea506445c0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J3LZkaMiT5hB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "680e140a-cbd7-4ad1-f9cc-1d7d6d011a5e"
      },
      "source": [
        "!pip install lime"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: lime in /usr/local/lib/python3.6/dist-packages (0.2.0.1)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from lime) (4.41.1)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.6/dist-packages (from lime) (3.2.2)\n",
            "Requirement already satisfied: scikit-learn>=0.18 in /usr/local/lib/python3.6/dist-packages (from lime) (0.22.2.post1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from lime) (1.18.5)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from lime) (1.4.1)\n",
            "Requirement already satisfied: scikit-image>=0.12 in /usr/local/lib/python3.6/dist-packages (from lime) (0.16.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib->lime) (0.10.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->lime) (1.3.1)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->lime) (2.4.7)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->lime) (2.8.1)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn>=0.18->lime) (0.17.0)\n",
            "Requirement already satisfied: pillow>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image>=0.12->lime) (7.0.0)\n",
            "Requirement already satisfied: PyWavelets>=0.4.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image>=0.12->lime) (1.1.1)\n",
            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image>=0.12->lime) (2.5)\n",
            "Requirement already satisfied: imageio>=2.3.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image>=0.12->lime) (2.4.1)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from cycler>=0.10->matplotlib->lime) (1.15.0)\n",
            "Requirement already satisfied: decorator>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from networkx>=2.0->scikit-image>=0.12->lime) (4.4.2)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2Wz7lPwCUlMR"
      },
      "source": [
        "class model_wrapper:\r\n",
        "    # drf is the h2o distributed random forest object, the column_names is the\r\n",
        "    # labels of the X values\r\n",
        "    def __init__(self,model):\r\n",
        "            \r\n",
        "            self.model = model\r\n",
        " \r\n",
        "    def predict_proba(self,input_data):        \r\n",
        "        # If we have just 1 row of data we need to reshape it\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "        # Predict with the h2o drf\r\n",
        "        self.pred_positive = self.model.predict(input_data)\r\n",
        "        self.pred_negative = 1 - self.pred_positive\r\n",
        "        #output = [self.pred_negative,self.pred_positive]\r\n",
        "        \r\n",
        "\r\n",
        "        return np.hstack([self.pred_positive,self.pred_negative])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FHEtPd6WAwyb"
      },
      "source": [
        "class model_wrapper_2:\r\n",
        "    # drf is the h2o distributed random forest object, the column_names is the\r\n",
        "    # labels of the X values\r\n",
        "    def __init__(self,model):\r\n",
        "            \r\n",
        "            self.model = model\r\n",
        " \r\n",
        "    def predict_proba(self,input_data):        \r\n",
        "        # If we have just 1 row of data we need to reshape it\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "        # Predict with the h2o drf\r\n",
        "        self.prediction = self.model.predict(input_data)\r\n",
        "        \r\n",
        "\r\n",
        "        return self.prediction"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3BGoIE0jUovi"
      },
      "source": [
        "classifier_wrapped_ =  model_wrapper_2(model) "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WiyprFfSU5C9"
      },
      "source": [
        "X_exp_train = []\r\n",
        "for j in ecg_train_files[0:5000]:\r\n",
        "  data = load_challenge_data(j)[0]\r\n",
        "  ecg = pad_sequences(data, maxlen=5000, truncating='post',padding=\"post\")\r\n",
        "  ecg = ecg.reshape(5000,12)\r\n",
        "  X_exp_train.append(ecg)\r\n",
        "X_exp_train = np.asarray(X_exp_train)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Ph8Udn9V7WP"
      },
      "source": [
        "import lime\r\n",
        "from lime import lime_tabular\r\n",
        "explainer = lime_tabular.RecurrentTabularExplainer(X_exp_train, training_labels=y_train[0:5000], feature_names=[\"Lead-I\",\"Lead-II\", \"Lead-III\",\"aVR\",\"aVL\",\"aVF\",\"V1\",\"V2\",\"V3\",\"V4\",\"V5\",\"V6\"],\r\n",
        "                                                    class_names=[one_hot.classes_[0],one_hot.classes_[1]], discretize_continuous=False, feature_selection='auto')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_oamTdWyKq2S",
        "outputId": "59881fa1-1c57-48b4-9142-4df0ada1cc54"
      },
      "source": [
        "one_hot.classes_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Normal', 'Unormal'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MtcL47UBKU2b",
        "outputId": "ad9657dd-ce34-4a54-ac8f-a13e83228200"
      },
      "source": [
        "one_hot.classes_[np.argmax(y_val[6])]\r\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'Unormal'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZtDD-1Z_1Ayy",
        "outputId": "f99fef69-6dfe-40e2-e957-7e0cfe1f534b"
      },
      "source": [
        "np.where(y_val[:,0] == 1)[0][3]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "32"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 195
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IuR3ULzb6WAt"
      },
      "source": [
        "exp = explainer.explain_instance(X_val[32].reshape(1,5000,12), classifier_wrapped_.predict_proba, num_features=20, labels=(1,), num_samples = 5000)\r\n",
        "#exp.show_in_notebook()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XA75Sepfob3p"
      },
      "source": [
        "exp.predict_proba"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TAHPR0p5Xlpp",
        "outputId": "98f6303f-507f-483f-8d59-3abc0f991aef"
      },
      "source": [
        "exp.score"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.25952017542877404"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 213
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IxzGnW9x3xFn"
      },
      "source": [
        "exp.save_to_file(\"explain.html\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rtcXcX1mQ84d",
        "outputId": "0f7f8d9e-0a04-4aaf-8b95-f7690e9497ef"
      },
      "source": [
        "exp.as_list()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('V5_t-4303', -0.002617452848208946),\n",
              " ('Lead-I_t-4268', -0.002577436482503855),\n",
              " ('aVL_t-4231', -0.0025688325946731645),\n",
              " ('V1_t-4409', -0.0025126953693953543),\n",
              " ('V2_t-4575', -0.0024550283175868155),\n",
              " ('Lead-I_t-4302', -0.0024446936793997742),\n",
              " ('aVF_t-4231', -0.002405920079115819),\n",
              " ('V3_t-4575', -0.0023542615757169805),\n",
              " ('V1_t-4231', -0.002339355776793143),\n",
              " ('V6_t-4303', -0.0023190746931739726),\n",
              " ('V2_t-2636', -0.002308763425622518),\n",
              " ('aVR_t-2742', -0.0022870303127295807),\n",
              " ('V2_t-4409', -0.00228266239927486),\n",
              " ('aVF_t-4409', -0.0022822230895974812),\n",
              " ('V1_t-2636', -0.0022615506584295697),\n",
              " ('V6_t-3742', 0.0022387922539441525),\n",
              " ('aVR_t-4231', -0.002172155735131314),\n",
              " ('V1_t-4338', -0.002163471609797179),\n",
              " ('aVF_t-4338', -0.0021028080637131063),\n",
              " ('V4_t-4195', -0.0020131686650628443)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 199
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HkAjrYKSNrVv"
      },
      "source": [
        "lead_arr = np.array([\"Lead-I\",\"Lead-II\", \"Lead-III\",\"aVR\",\"aVL\",\"aVF\",\"V1\",\"V2\",\"V3\",\"V4\",\"V5\",\"V6\"])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wdH0NvSEkzIG"
      },
      "source": [
        "!pip install git+https://github.com/Bsingstad/ecg_plot.git"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6FCVLcrma7PG"
      },
      "source": [
        "import ecg_plot"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_GPCw9q-a5d5"
      },
      "source": [
        "ecg_plot.plot_1(X_val[13].reshape(12,5000)[3] *(2/1000), sample_rate=500, fig_width=15, fig_height=4,title=\"\")\r\n",
        "plt.axvline(x=3721/500,color = \"r\", linewidth = 15, alpha =0.5, label=\"Unormal\")\r\n",
        "plt.axvline(x=4255/500,color = \"g\", linewidth = 15, alpha =0.5, label=\"Normal\")\r\n",
        "plt.axvline(x=3507/500,color = \"r\", linewidth = 15, alpha =0.5)\r\n",
        "plt.axvline(x=3565/500,color = \"r\", linewidth = 15, alpha =0.5)\r\n",
        "#plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "plt.legend(loc=\"upper left\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Abnormal-aVR\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MlHNkNooO4WV"
      },
      "source": [
        "ecg_plot.plot_1(X_val[32].reshape(12,5000)[11] *(1/1000), sample_rate=500, title = '', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=4303/500,color = \"g\", linewidth = 15, alpha =0.5, label=\"Normal\")\r\n",
        "plt.axvline(x=3742/500,color = \"r\", linewidth = 15, alpha =0.5, label=\"Unormal\")\r\n",
        "#plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "plt.legend(loc=\"lower left\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal-V6\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AsDpbuBwYvDt"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[2] *(10/1000), sample_rate=500, title = 'Normal - III', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=2053/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV/10\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - III\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pFN6oYwnbjZ4"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[3] *(2/1000), sample_rate=500, title = 'Normal - aVR', fig_width=15, fig_height=4)\r\n",
        "plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - aVR\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ElZi6DzS8q3"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[4] *(8/1000), sample_rate=500, title = 'Normal - aVL', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=4421/500,color = \"g\", linewidth = 15, alpha =0.6)\r\n",
        "plt.axvline(x=3424/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV/8\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - aVL\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bHHRRTlIb1aG"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[5] *(5/1000), sample_rate=500, title = 'Normal - aVF', fig_width=15, fig_height=4)\r\n",
        "plt.ylabel(\"mV/5\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - aVF\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ySwbAyAtXzG7"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[6] *(2/1000), sample_rate=500, title = 'Normal - V1', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=3424/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V1\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2AfuCjlocIcR"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[7] *(1/1000), sample_rate=500, title = 'Normal - V2', fig_width=15, fig_height=4)\r\n",
        "plt.ylabel(\"mV\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V2\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gwvbz0yGTo9G"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[8] *(5/1000), sample_rate=500, title = 'Normal - V3', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=3588/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV/5\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V3\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XbvBVDJsOZ0O"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[9] *(1/1000), sample_rate=500, title = 'Normal - V4', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=3458/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V4\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VJJW683PfzTa"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[10] *(2/1000), sample_rate=500, title = 'Normal - V5', fig_width=15, fig_height=4)\r\n",
        "plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V5\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "27i5nPI0W2ap"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[11] *(2/1000), sample_rate=500, title = 'Normal - V6', fig_width=15, fig_height=4)\r\n",
        "plt.axvline(x=3588/500,color = \"r\", linewidth = 15, alpha =0.6)\r\n",
        "plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "ecg_plot.save_as_png(\"Normal - V6\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j4Y90CRzP1tD",
        "outputId": "9c7e4ba1-ae82-47f1-9651-0bae96e15a2c"
      },
      "source": [
        "exp.as_list()[0][1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.003104542909134603"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AR9BRVBQlpxi"
      },
      "source": [
        "import ecg_plot"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 273
        },
        "id": "8SJKjdcRi2Bc",
        "outputId": "ea93257e-f998-4fb1-ae53-6e26106abfa1"
      },
      "source": [
        "ecg_plot.plot_1(X_val[7].reshape(12,5000)[10] *(2/1000), sample_rate=500, title = 'Normal - V5', fig_width=15, fig_height=4)\r\n",
        "plt.ylabel(\"mV/2\", fontsize=14)\r\n",
        "\r\n",
        "#ecg_plot.save_as_png(\"Normal - V5\")\r\n",
        "ecg_plot.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dctnkdTWPf2R"
      },
      "source": [
        "\r\n",
        "values_per_slice_ecg = math.ceil(len(series_ecg) / num_slices_ecg)\r\n",
        "plt.plot(series_ecg, 'b', label='Explained instance (class 4)')\r\n",
        "plt.plot(ecg_test_x.iloc[ecg_test_y[ecg_test_y == 1].index, :].mean(), color='green',\r\n",
        "        label='Mean of class 1')\r\n",
        "plt.plot(ecg_test_x.iloc[ecg_test_y[ecg_test_y == 2].index, :].mean(), color='red',\r\n",
        "        label='Mean of class 2')\r\n",
        "plt.plot(ecg_test_x.iloc[ecg_test_y[ecg_test_y == 3].index, :].mean(), color='black',\r\n",
        "        label='Mean of class 3')\r\n",
        "for i in range(num_features_ecg):\r\n",
        "    feature, weight = exp2.as_list()[i]\r\n",
        "    start = feature * values_per_slice_ecg\r\n",
        "    end = start + values_per_slice_ecg\r\n",
        "    color = 'red' if weight < 0 else 'green' \r\n",
        "    plt.axvspan(start , end, color=color, alpha=abs(weight*10))\r\n",
        "plt.legend(loc='lower left')\r\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UyztG1JlOPO1"
      },
      "source": [
        "plt.axvline(x=1585/500,color = \"g\")\r\n",
        "plt.axvline(x=4588/500,color = \"g\")\r\n",
        "plt.axvline(x=1583/500,color = \"g\")\r\n",
        "plt.axvline(x=3635/500,color = \"g\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JCwsZuQZg78w",
        "outputId": "ecf2da04-d52d-4ff7-b892-a53e9038bbe8"
      },
      "source": [
        "load_challenge_data(ecg_val_files[5])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([[ 140.,  167.,  192., ...,   -8.,  -10.,   -9.],\n",
              "        [-306., -249., -199., ..., -170., -174., -178.],\n",
              "        [-446., -416., -391., ..., -162., -164., -169.],\n",
              "        ...,\n",
              "        [ 693.,  845.,  998., ...,  -61.,  -58.,  -56.],\n",
              "        [ 695.,  880., 1069., ..., -107., -104., -103.],\n",
              "        [ 526.,  705.,  893., ..., -111., -109., -107.]]),\n",
              " ['A0040 12 500 15500 12-May-2020 12:33:59\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 140 -1864 0 I\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 -306 -1246 0 II\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 -446 618 0 III\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 82 -6024 0 aVR\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 293 -956 0 aVL\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 -375 7158 0 aVF\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 330 -536 0 V1\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 711 -2234 0 V2\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 637 -1578 0 V3\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 693 -5589 0 V4\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 695 -4776 0 V5\\n',\n",
              "  'A0040.mat 16+24 1000/mV 16 0 526 122 0 V6\\n',\n",
              "  '#Age: 28\\n',\n",
              "  '#Sex: Female\\n',\n",
              "  '#Dx: 429622005\\n',\n",
              "  '#Rx: Unknown\\n',\n",
              "  '#Hx: Unknown\\n',\n",
              "  '#Sx: Unknown\\n'])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 160
        },
        "id": "c5ZnUQkQf5rM",
        "outputId": "c1644d54-c03e-4819-c9dd-831cd0f68f7e"
      },
      "source": [
        "ecg_plot.plot_1(X_val[5].T[1] *(1/1000), sample_rate=500, title = 'MI')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TGXZ175Nhb4O"
      },
      "source": [
        "data = load_challenge_data(ecg_val_files[5])[0]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6lriuAmziEL3",
        "outputId": "26891b0d-6d24-49d7-c48d-e0f7027f7855"
      },
      "source": [
        "data[1]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-306., -249., -199., ..., -170., -174., -178.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 160
        },
        "id": "bkFRvEJQh2wd",
        "outputId": "d9cc99e2-dcce-4d6e-85b5-229526b7c101"
      },
      "source": [
        "ecg_plot.plot_1(data[1]*(1/1000), sample_rate=500, title = 'MI')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Zi6nCGUHbFbXUNO1O4E6AC6NRuOuu8oneXhgZKf9/587y/yuPTfXZvPn0sdlj+vpm9vczprcXLX8p7N4Go4cbHsPIyLy832a9nENTujY4Zl7eMuwzm4MMXX3aZwZvGfZp0hfcnS8QlGmfxM1l35alKy+XNlfcoxPE3CVYO35HBK8pXZ8a83g3QZ7b3wnbf3Fe+sIZmysLoatM+1Tj5bd9BmV8fGIJf2/ulCbT6llJpLgS566fEUJUlbG7ZyWXjR6tKaOybaET7rqUQsGC3+xrSdepdiz6Kgpf+srpZ5YPGTJ4nDGZC8wrGOzBNS6tPad98AroFyG0GPQ9JEU3e9RFD6+Fu34qxV4i1YtRWIf1/UfBm5Bic7vrSvRCCZ7c25Kule2/TdzMHblftCRjTnvqeS1J5tB8z/8m/cnuWY1eXFS+z7J0bdav57lvgfgbce76IqHelBSZYmRk/vcnH34eHu/FFCY8fFDKXBlLLeaDhdX8e/HJlnhNtfdqCRb1xOlMn2qJF729/DRjsD8Q56+tvS3z+mL0ev7rY4/QO3qoZV4/K17NJ579MUmclnlNEOJNyRt5fOLRlnmp519rMk+kcywWpdM/4ff2Ugtn6oPEcWBlRXvF5LE5EEJ8FfgqwLXLlgk++tHyicrQj7vvhjvuqB4e0tdXPjdrzMPfu5/X9f1l9fCRGmO4++7yudlhi//rYezoNfCuNzc8hoGB+Xl//OdM69romPl4+xlTj7cMXf3ap5J3A2Oe1Ht5wVnMH7/n9xrjXcc+N3xzF0/2vVWefb65r3y/Jeg65T/iIx9B07SWfcH53v3ELrsM68qriRjBqhyGCg6Lrr5ijq6/++EW/uKqHrbtGIV3vKotfKFpv/czZiHmykLoKtM+7RoOWGfMDz/+cz774ZsIzJ4rPmXascUkfvwM1uv/nJA+d/eBTz4xzK9HHO57+23E9UBdmVbBwbCScPAYXH2zFHuFf34M861vBGvYtwwZPM6YzAXmpZ0swrNp+Mv3SOMV2J3By9jw/ldL0c15dBv69jG4ucZzpkmZzppLif3vR7GufwdcEJFic/eIRiA9Ale/sSVdZ7Snnq2tyFhomd/cV35er1/fsk86gRSh+3fAG6u8K/vU1fvkpwjs3dMSr6lj4e/ux/rTPye04TIp88/d3U/wO/trvz/58HP9+7/F1gPwkjfLeSYsu4ij/7QZPtTgPanT5x8eOsF/uGk9bwhlW+LFunWU7n2K4WETXv3GlnmFfnEc5803g5v2LWOqHd/0Swrv+DDJWKhlXk7JZfyeY/D+Kn9TNcmLgQEeOJxjtORyx23XvSief786nOPil65jzdisP9N9yLxt0y/52a0rWRIPne6zaRPVcKY+SNwLfETTtB8C1wPZWvUjoFzUErh1TW9vuSAGlJWc+v+yZeX/Vx6b6jN1btaYP7bXcmh2/zpjWLas6jUM18HumYdbNV7pdE3eor+//J8mxtTl7WdMPd4SdPU1ZjbvBsacyk6wLdzEPapjn5MYcu0D0nRlYIAgAmckXQ5/bdEX7J4UiVIec7gAkcAcDv/+3CD3Ddp8PRaacZ1T216glCtgZCCTKZDbuZvE+NhZ94Wm/d7PmIWYKwuhq0z71PJrP+0afZ7ac5LrUnpLMma3Y0EoDqWJhzQpMu1TRRLCxRxJEzMCM857QjCULfCJl/Sy5/AwV3eHqsp4yz89xE9fGQPAzLsYZgEKxer3pAldp9oRz8E8eBgiRd8yZPA4YzIrjv3Z1hz/eHWcBMjjlbURtiNVNy1fwiu60uxjZcfRXbv2nG/Wz22POA72WBYCeTn3LY1UPz8tdwH8SaLMoFau1aRL4GUX84Qcu7YNm2wbAbB29xPJjrXEa+qYoVFeGyXNaWckTUijMb9u0J8CpRKeDaSFnLmSs9HxGr8ndfrojoV77DgkzZZ4MTAA+TzCdKSsC7prYx0+AtFSy7yimqAwPAqJYMu87JJHSHgt38ep9rFTJY4VPWnPKmt4hD95Ksc3X5GUJvPdPzvE916VbEnGVPtXe/NcZ+5mTcpumZeOhzM6CqXg6T41IOWDhKZpdwM3Ab2aph0DPgXoAEKIrwD3A7cA+4AC8IH55C1IUctqhXrqjalRiE5/cBD71GjtIoK1vhrV4G1fcikh9s5fRLAZXSvGbNm8jVctjfnWdQYHCbqeqeJ+4Y4OrF/3N36P6thHYxT30rUEqfKrgR/7ME+hJx+FDA0GsLp60Gf/QuunqOXoVmJrrsXq9CChzzgvjg+yPXw5Vy+PcPSCldNhT7njJ/n+qhDvf9lSiIdwwy6PeV28KRU4677QtN/7GbMQc2UhdD3Hilq+/Zv7OPSBNS3JmN2OGQfJJ7uIS/glBsAO9ZLoz2J2dEN8pszjEzavvdhgw3WX89DmHVyd6pwjI2u6DNslRmKd9EZDWEGLcCQFOXnF/sJRE3PJMghmfMuQwaNe++iEzcpqBRNb4PVMZpxcoouERJmeWSBouFLtJYYyaLYlzeb2kTx6xJNW1NK+8GJi0VNYiSSkYnJ8Ia8BI3KLWk49W1uRscAyI8EMZlcPugSftJ1OjEhWWlHLcDCLefEaIkcOtMRr6pgRGsfq7JY2py3LRQ9m/RXKrNEn8GwaL6BBqkfKXHF66xQ6blJmMGJjL14C0VxLvFi3jsCecUShKGVdCBgm7rLlEMj4ljHVNowjWB2d0B1umZeds9ENs/rfVE3yYmAAfSiD49rSnn+W7fHUaA0f9inzN9/cN7++TbSDERexZDF0zPoBw4dMI3QYq6MLOo3TfWpASikcIcQdQoilQghdCLFCCPF1IcRXJj9GIMr4CyHEJUKIK4UQT8u47tmCHtCwJO787Hge+gLtxv3OXw4uiNx2RygQwJV4jwwEltO+RXLCCExJxcZsNOLhYFV5+0WEDakwf3BhnC8+Us5v/8FAlg3mNXxp836WToZl/emV3eQtVUTvxQLXE76KoJ4NhAMaluTiWQk9UHW+7B41Wd9tsLgjTP+YOV20y3E9TLdcXOwfn03z3ldexJYT5Ye/uQBFLcNBDbON168p3Phvh+t3ahKRkEZJcoEzyxMYQbnFGG1PbhFKx5NbMNJxPeJ6QGpRS0DiU3phILPQ3hTCQY2SpPnoeIKQxPusB+QWBAxLLoTqeEjVF8o+KPPxZbtyCx0HNaQ9X2Vazghq0nzFCMjzE8cDPSjvGRrUNByp7wwCXfLzQyY0Td58aKYQctsVtYSFSdmo2q43pkaYte5Y2N2ppsaQTtfkbZtueYFtYkxd3lNjYGYfSWHoOzMOGySmbDyz9xQrFq1gcSO6NnCdQCGPF440rmsd+xgBsPoHiOYyM/vXsE9dm07dFwm6MjBQfuiPjEI0UNsXGvQft6ubWHYMy7PBCc44/1hyJbfHTXo9m7Ehi28/7fG1/SbfWTLCDW+4flpGpORRGs/DIlelbLSTrjLtU3Hse7ueIpPJ8Z/WRaueb3gtnt0Hml/P61w3jIeVHgOz9dBQALuQJ+GamOkxsGfKfP5Ykdeti6Dt2cPbLhD8ePsJThY9Bh49Sa9m85YVBinP5j0pi74XxnhTh0lh1CVWcmuGsntCkHcgWWmbOjzDjo159Bh0tx6C6cfmTbVr+ahPXhE8zHRGqkw7a6E7tlR72RMldKtKWLBPm1vZCUK21Zg9G5Bp5x1iroWVHYdYSY4vpFmQlA1vZKRcI8avjIq27QqMAFL9PqwJSiOjUnzSrrzPLfICMDSBNbAXzPGWeE0dM/DKa6Ok+WenR8s/4PlZJ2r00YrF8k+CklI2rFETXchL2dBMCzF4Yub67Xeu5HOIkpyUDcOxsI4eh06rZV5h4WCOZkGrkg7WpEx7wiXk2i3fx6l2sGDilaqk6DUho7Jtp0fLBbCr3QOfMgFpz2HNLOGdPAnOrB8Vfcg0hIs1lgFRka5aA235QaLdUzaMx09hH8nIS9lYvgrd27MgKRuwbyZPCWHo7u5+br13Pwcj8lI2vvHoSd5wosBtr5OTxuB1daGZu6WlbIS9IazVl8Dgobr2acimklM2wt5OzI4u6NBr+0KD/uOMPUv8VUsw3SykIjPOZzIv0LvsAgC+8qdr2fnEDn71UoPoj34Hl71vWoZhulh6BFK2StloJ10XKGXDdnXG50sx8BuCOXv98iNj9vptHMFMdkJP66GhAHZHB4m0iZmMlefL5HkhBG5klGBveZ6/FNiyY4yc7nJw3ON3GYdHhl3uu20lsQ2X8frBAs+5QbIRj0VrV8NQsaru9x+c4Lv9Wb7/0UtnPsDn4RmOuZgXLIbO1kMw/di88fY866JPXmGjQCnRIVWmPZEjFJ6Qai/n2Ci6LqTZ3Nk3jhENyEvZuGAl8V0ZrFgYUkk5vrAAKRtGKIvV1UOkMsqohXvv2B6h0ITUlI2wniuHMUvwSSccRz9WkJKy4QlBRM9hXbQa0sda4jV1zNDz5fVW0vyzczZ6KC83ZeO50XIkjKy5EluMrg9Je3ZpEQexZCkk8r5lTLf3jiNyclI2wlEHa9ESKbyM8PHa6WBNyrQ1Ez0ipKVsaOlxvEJR2vPPztnowRo+7FPmjHclvzKm2mEXsXgxdFXUBvEp0zCOYSU6IBWt4FodbflBQjZkhxKHAmALeeE2tuuVv5YtEIQQ5d0XJMH25IcbhQJITbGQbVMdgSUpNG0h9qc2EJiS+NloxI0QVn5+noGAxlW9karnymGa7Rsi/oOBLItjIV53tomcJwhoGrIjm70FCJWGyfQFiSHElitIGHNTNo7mHFYl9RnH/vyq7vJ6vH49zu5+spZHZ7gchfTalXE+u3WErOnxiVdGq17r6ITNI0cLvO+yLp45PMb1DXIMBzVKttu0bucDyikbcn1pIUJubU8gMcoY2xPIzPxxPEFMD0hNd1oIhINljtWfTM1DdkoElH1S1hrkeJ60+2x7ENPlheGD/PXWduWmIoHcdA2YTMOWyDEUKMuUASFAFjUjqElLZTaCGqaktcX2BCGJ67NASE11Kf8NJVGgZKiUjQrITtmwXVEO8Zrdf54x09epcg3dMrG6upsaQzpdk7czYaOHAk2Nqct7ckxIA3skjTG1+4KEMHRrZBRDE1J32QjZFs6UTevp2sB17OwEejTcuK51bGqEAlh79oEzUdc+9WzqpdOEELgjIwShZV1Ffz9hPYg1mgEv1NJcAXA6u4iPnMIq5SBUmD6fPTFMsjPekK6GEFgnA2CItkzZGDgxjhUPqJQNP7rO7gNow0FEsVRdRiPtKsdsdwB9qpq6TxnV2mFvMoQwoEuRaY+NkzALmGOl8nyZPP/EYZNX9oYgPTO0X5uUERobJQWQL7f1sVH++yUaj5zySB0/VDWU/b69Jf78Qp1l0RLfeHoP168QNXlVtsNWCfPEKdBmvTw2e5982rypdi0f9ckr7DqYY1mpMu1xE0PyLhsUitO+IcPm9ngOw/bK6QvQskwnYxEzi9ieNsenG5axu5+Tx4dZEZt8G08jPWXD0EQ5fTEc8C2jsm2XvNMpAi3wmjEfhYs5KieNyB4OEbJM/2tvpa6OII6Huf8gkPMlY/ax6fVW0vxzxjKEhOtvnajRRxQK5bnXiMwGrmNZBXTPkfbsMiwT6/hJsB3fMqba1ngOw5KUsmGZWIMnwHV9y5hqG66NlRkv79jRIi97zEGvTGNqgdfUeh+y5KVsOKOZ0yk9sp6pzEpVa2G+aaUS4tQp8CSkbLg2ZmYcwsUZXKuhLT9IyE7ZcGyPEOnaoTHNpmw8OYx9fFxeykbPcgx3YEFSNsLB/VhdPRhTuy9ICEO3Sy5GcFzqLhvB35zCPZGRlsZgh+PoxV3SUjYMdxD7olWQGZzZv4p96tnUdjyijGB39RCUoKu75lJi9nOYU2FRLcwVACe7ndjqCzGPHIVUfPr8vbuz3Jw7BKlr6uoaAERBg5Roy5QN8cQwWlyHfSplo2ldZ/cBAoTxsnJTNpxVlxAKHpCfshE5jhnvkBIaCmCFonSHAlhBrTxfJs8/1z/E21deUP65oUF7BIHf7y23xbY0E8luTuRt1q5bx+j2XfzD7oP82SuWA1AsCkhpdWUChBNgdqUgNeuDRCthnbJkzGjLT9kwIiZWPClVpj2SxYiZcu0VS7cuo6Jtv8h+E3EAACAASURBVJAhLpxy+oIEmXZyKbGTRSwhIDU33WCs5DLUuYx188h8yO7g688f50e3rABALETKRrhYTodI6L5lVLbtnI0RNhE9PTMjTVuQGQ4Xy89rCT7pCAN9zJKSsmGXXOJRC2vFSigOtcTr9PwrlUO2Jc0/e9RE10tSUzbYNjn3ZKVsaD0Y4TFpz65w3MNM9ZZTYFvgNbUu6I4tRVcjLrBSvZByfMuYaocfPYkVi1dPB2tSpmMXMeLF8q4pLfJiYADn1KTNJD3/rPl82KfMqb/1plPVWphveszD6b0AUhW1QXzKNB46gRVPQCpxuk8NSAn00jTtjZqmDWiatk/TtI9XOf9+TdOGNU17bvLfh2Rct1E4npAavm8ENWyp6QVy+VXCkBwuBwsTrqqhSbWA43nos38NbAE6nrTQNFdAFE9a6KvtChKaKy3czZncZaMyzMrzBEcmbFYGrHlGnjsQlP9OVJADTQNP8homu1L5FOSHEHtzUjZytkcqEmwpVW7c9Ljy+wf4zNY0n7pnJ2+//xi/uH3l9PmoHqRgN7YmaRKrtE9B9nNlCrJT2oyg3F1VYDLkdgF8UybsyRSLBl2kvrzJ3WRqhd/+cM84n39wgMPjdtXzAE8eGOX6xdXTkWTBCMlNK3FEea7JsiPIXYMciak+tieI6wFsiTvynAspG7Jhu57UNB9D4i5JMlOQZKdsSHsnlpyyIdvnZO+ABHL/1pO5K1czu+y0HCGhaVoQ+BLw+8AxYKumafcKIXbN6vp/hRAfaVDmrchM2TAnX2xn959nzPR1qlxDN0vYyY6mxpBO104vSJvoerCpMXV5T46ZDl+c2n1BRsrGVJVjiSkbAauE19XVmK4NXMcaDhGKxRrXtY5NDUPHOnAIgvmZ/avYp55NnZE0sVAAu1aV7WZ1NV0SUQNzbByMYktzBaCU7KTj5HGOZScgbQKwZfA5rovbzemaBuLzcDiLaQxOsUjQsFXKhh9dZ/cBtKEQnuyUjaIzM1Tah4xqbcOxMbPjkG49NBTAOhkkGTZJ573yfBkY4Km9Q7w6gX97DAyw61SeNy3T+S/rQjw4keP6Lo3LRA7S5VDqa4Mxnt6X5TWL9LoytUIRGCnPxybtVa3teIIbH8zy1Bu6fMuo1p5OMWxVZsUxw5ncGUKiTKvRHTGa8adCsXUZFW0nlyce1LBG3Krnf7nzBGlT8K5V4YZkOqeKRIs5rJwH6bm6T4wX+R8vW8Ivdp3ifasjc2TsyDhcHYqxv1SRopGe9M1a86RBXSvbhutgpTPlHW98yqhs2zmXmHCwRtIYITk7d4RdBzMjJ43IPhnAMFtYeyt1LXjlnVQOHYFI0ZeM2ccMx5Y6/5xMFsNzGktFatSfpuZeredjkz5p53KEHLvxe1Knj2GWsE8NQ3ieFL1GrjMwgJ3LY7hydA2VithDw8wo2OL3uWybWOMuVdPBmpRpZ2xCpcl1qkVepNPY+SIhe560/yb92h7LEvJqpM34lBlm8m+9SMC3jGl/s0pYJ4dAn/UhwYdMw7Gwxj1IW6f71ICMlI3rgH1CiAMAmqb9ELgdmP1BomFIT9nIO4S84dqhMU2GZge3pbEP5OSlbEQXodu7FyRlwwgdKocvTu2+ICEM3cpYGHpRasqG/sQw1lQaTD1dG7iOIwyMwk55KRvWEezlK8AeqWufeja1iw4xdxCrs1uKrvbyVSRKv8OKX1wOi/IxV0oXr5l+pnjjO4lcegnmcAlSHYyVXLaMB/jP66Pwr5sb1lXk2zdlQ9syhIiHYY+clA2xdi3anj0v2pQNjzCBjCk1ZcNefCF66Kj0lI3wY/JCQwFsK0QiVsD0yvOFdet4/Mlh/u663tPVw3yEOn7+dTa9kSCRUIAPV+F19SVr+PK/PcVrpsJS55MZS0Oqtzwfm7RXtbbjeGScrJz0ispQ0WCmnGLYqsyKY0bUwYpGW+dZccw+PoauuVL8fLotOWXD2pamOxbC7oxXPb/96RFS0RBHjTgrk3pdmbbeS8wVWHapHApdcX6o4HBBT5BFV1/B8O5s1Tn762OjvP/2l3Ls3q0UO7uIhgJoklM2hBDoURcr2XF6h6gmZcxu25pJrCOP3dkJkaAvGbPb4aiNGat+X5r1J7sYQLc9KSkbjm4TT4C1dBkEMr5kVB4T/f2Eo3Z5vZU0/6wTBWLRBlORGvUn2Skb8SRGrb8RfMjUYmlEKjVz/W5hXQjJ0rXac8UnL+OJYayIXjUdrFmZdi6H0eGVn8ct8mJgAOfoKLpRZQekJmRUtu2TRXSjRtqMT5mGfgirsyJVrYX5FoilcXtSUt4XjN8MYUXDkOo83acGZHyQWA4crWgfg6rFv/9I07TXAHuAvxRCHK3SB03T7gTuBLgwGoW77iqf6O2Fkck/BnfuLP+/8thUn82bTx+bPG9rUfTQ1Xif6iOQrug/z5jp6/T1zbmGNt4FQ0Nw146GxzAyUpO307MKPZs8rWsDY+rynhxjFC7D/s4jIPK+dJ3BYfKYPWpihK+CrZub1rXWdcLjKawTR8o2qKdrA9exuzagHz0Jdz3bmK51bKq7l2N989swdqCuferZ1E1PEHPXluXdG2td19RS4kdtzPsHwTnR9FwpEOTVideyObeZDhzIdBD+wucxswbil0f4bPhKrHAUY/yp5nTtvAqyO5r2hVq6Phy8gIHkYv78N83Zp9p9NcYvwBRF2La5aV+oxvvm5EZ+OfFY077QFG+fuvpdN2vynt0HsLuuwCi48HR/1fN129Vk9iwnVFpT/RnQoIxq7fDEEsxdGXCOSZFpd11JMrsHM7gYHjjCo92XcOVEkeDWwYZlVGuvqMMr3NtLcTyF95uB8i+F88k01iCisfJ8bNJe1do2IYz4a2uv1z7bRvx12F/5KvR2tiaz4pgRvgJz5wQ883NpMm39EgwtAPsebNnPp9vGmnK7/1dS/JzxLgyviOWOwr3xGeeP9ixjxXiQje4wvwwt4UP2oboyne6LMbJjeKEU/GbfjPO/DS3jRjcL239BcLyL0pYDRPCm+3jAuLGO+K4HWDUW4vCvc6z3cuVnRLFQlteKrpNtF41Y8gbM//sAeBlfMma3nUAH8cQVWDufBWFKkRkOX4XZPwJP3teyTzqdVxEoFmBLDRs20ba1ODF9Oda+Z2Bsb0u86O3FHUkTDV+OuSsLT7WuK729OGOCuH4h1pfvJdLbJWf+jXeV/z/Lr5uSUflM6F6HXgjDzh+1xqti/Wb2+t3CuqDJ0lUir/B4L5YowcOHWublBJcQil8EW3/XMi9GRvCMNeVn7MCvfMuobNtjAl2/GO7695bXPACR6sUoXo79rYdBFHzzmve++pRpjC/CEjn41ZHTfWrgTBW1/BlwtxDC1DTtT4BvA79XraMQ4qvAVwGuXbZM8NGPlk9Ufnm5+264447qX2f6+srnKsY4WYv4v/dj/fe/I3Jg38wL1hgzfZ2+vrnX+OEWeH4nvLfKL4q1xgwM1ORtB1OEvvEgvO+jDY+py3tyjP4PD2Le+C5Ihf3pWslh8pj92+3oW4bhppua1rXWdYwfbMHaZcB7bqqvayM2HQyiP7QZ3tugrnVsanz7aex3/RFoVX41mGWfeja1n9lJ9Mc7sG9/D1x/Zcu6OhesJP5P38N85dVwacccDvtu/iOOdi7mtdpY1es8fijHnZEunrYv5PdWxtG++xjhv/kA1i+fZdeSKM9sPsnDf/v7sOf65nQ9osGFG5v2hVq6Du/JctiMQOhkU/apdl/D3/stVjgInbmmfaEa7/5v7oOPfrRpX6jFe2pryGZ9odF1oakxtexTOd9OhNCPnYSX/37V835+8bC7lxP++ha8D36kXDlawi9XrFtH+Fu/wezU4fLWf4kBcI5oRJe8BnNPlvG1HXzn6Rxfe0XHzL3VWv11sAavjY9u42N7ruKfNy4msH597THbJn/JunDjHBl+eNgll9BPDsMHPypVN+OHB7He8SG4+gop9mFgAOPJYaykDn94vTSZ7rZ0+aX+Ha9q2c+n2qJRmQ1yFz/cgtFpYPWE5zxn7h0MckePRU8kSOaZNFxz6xwZYu1aHntkGxuXx9A0DZtu4sMn4Fgerr55Rv/+rSO85doUrF/PLU/u4N6RG3j7pR383OzgwSf3MJCx6Lv+Atj4Ui5+YgcDGYv1FyfLz4j0SFleC7pOtR3HI/a7CayL18HSmC8Zs9v2cInYYRdr3UsgKadQpvHbIczeMNx2Xes+eUQjNJrGueqN5doAreg6ahI/msdaeyFEc63xWrcO+4XdJJ4dxUqG4C1y5p/90LPEDuawr3slvORyOfPvh1vK/5/l103JqHx2jUfRdxyCV1f5G8GPzGrrt9+5IlFXTSIv4wdbMEMavGTuWtSsTPvABHomCC+7rmVe867NTciobNsPPYu+Owt/8IqW1zwA+5JLiX3+YazXvBu6w755Vfqb1tsLK1t/XzC++xusWAg2dJ/us2kT1SCjFM5xYGVFe8XksWkIIdJCTH9a/hpwjYTrNgxnsoigzL2VZcL2BAYCdwH29w4vREEvV2BILmoZDIAtZBah8dCRWdRSyCtq6UEMT1oBGsv1SGpuzcIxP9o7zo+fPUbWdKue35E2+cANq3hupFSWJzTCeoDnR0q87f5j/PDm5b6K88kuO+V6EJBYjEmW/T0hpBfIvOnHR+QKXGDYrid9TahXRM8vZBTP+m9bhnAmZWicLtz2/f5xPn37BoJnqOjaq5bFuGl5jCdPFOv2lclIZmG0ShiBxgtgNYpmimo1g/Yuq1fmZwSq+3rJdumZTD8IBqj67tF37wv8ZP8EP9lf3uratD2MgDZHb0+U3wemnhHrusM8farIhx4a5FA6z+duXMz9t63k+iXlYpbruw2ePFHk6y9kkA3LEyTCQblFLT1BzJAnUwghtdCjxuSaJkGe5ZaLWsp617FcQcKQu4ZPFd5ciDktCwtReFOWtu1qtVCgfG9lQLb9Za/1tid3YwDH84iF5M0JDQ1ZtaWbeabLiJDYClyqadpqyh8i3gG8s7KDpmlLhRAnJpu3AbvnEyi9qGXWIR4OYQ3shfysh2CNMdPXqXaNQhGSyebGpNM1eTuFPPGogT2SJjjlpHXG1OU9OcbwXOyxDAR0f7pWcpg8Zmay6K4jtailVmnTero2cB0xAloz96iOTfVoGOvocei0ZvavYp96NrVHx4jHwrX35m5SV3vUJN6VpDiRg/TMvZLF0mUYVom/uaqT+3aemlnAbNkyRgaHSdoW4f37MEpFVn1zH/+lO054/15+djDHC7d0ESlm/emaRmpRSzdXImibUgo9asVi+cEsoahl0RFEg5ovX6jF+/CE7csXGl0XmhpTyz4Vx9xhCBTnKU5Xr13lmDNSIo6LOZwmYgR8yajWDlslTBeqFeZrROaRp3cyOl7kyT2nePUFOmIE9JjgyaM5ru0JsXL4qJQiVY3yur1L8LbfpHlT+knuXFajiJfkopZ2wau9j7rPthACAw9rdEyqfQyrhGX751VNZsMFKJvx0XlkipER3vlEjv+w0uAPV4Ybu26hiBG2sZyZBb2FEGhpDRLlrhdpJkeODvPz58coTRT4T+si6AGNjgJs2qDzud3j0G2THxsnYZQQBWvGfd+VcbhMn+kLn14b5NkxwauWuZAencFLGx3lM+sC/K/+HAHLRSsUESMj5Q8aPuf0VNsxPWJFDyvjQaTkS8bstj1mEy8EsdIeOCFfMirbjidIOCbmuCXHJ9Og2yXsEQeqrJPP/3Y7V2pVinFXaVtjDgnTxTx+Ai5wGhpTk9fAAHZ6lLhlYRarFAT0KzM7QcxxsNM1ioL7mX+yi1qeCmJYZm2/blZmtfXb71yRqKsoFNEk8dIk8nImTEKFIKQLLfOad21uRkZF285OoNtWdV19yHSscuFdcywLU3O9lflWLEJaSHlf0M0SlklZ3lSfGmj5g4QQwtE07SPAA0AQ+IYQ4gVN0z4NPC2EuBf4mKZptwEOMAq8v45MqUUtXVEiZh3BWrUaTs765bHGmOnrVLvGtjRMTMgratnRQbT4PHZXT/nFu4ExdXlPFbUMHy/vAZ2K+dO1ksPkMft4Hj3sSi1qKSptWk/XRq6T18ppNZKKWoaLe7EXLYFEfmb/KvapZ1N3zCRa3IeVuFSKrlZ8Mcnso2RXrYHUzEKZxwdHWHrNS1l57QZO7Nky0x53380jy67mjZd1wrp1vKvk8rWDh3l1/jja+ncS0w8SWdTrX1fJRS3dUxmCgThsG2y90ONUEav+1ota5gsOsUihbFtpRS3H/Pl9g+tCU2MaCSmsV5zORwimFVlEPDaG2dkNsZCUUFrWTRYlBt9FvX5+IsT/c9MKvrErw/pYJ15PCK0Xfj2c4Ru3XCQlBLMZXjrw07ek+Ek+wc5Smg29Ee4/lOOWV1WMkV3UUrcJhfJSi1rariAWLmInO6XaJxBLl2PlJMpsuABlE76gzSOzf9TkHVeEeX7E5K09PWjV+jyxg89vG+Urv7eEwOQap3dGsUMzw/i/vnOMq16yGoLlH2cuFSU+tmWYSy9MEhA2fXvL0U4br18LjBGIp3G7e8gRIREvQDozfd93PbGDv983wpdfu7T8x/DkdSLAqxbV1jUILO7NstOOsDKhYXd3lyOsWpw7dsEhsQgso3R633s/96lSZilPLBzDTppSCmXatkesI4PpVe9z4Knn+dSTw/zFS3p4RSP+lNcwChnMzvicdTJdcvmbzWluW67zp1d2V5dR0bbMAomwRy7eAymrap+G2pPH7LxDfCLPRMGRNv+c/RPEPRurIyFv/skuaumEiBQcnJ5U+Zf6FmWKWBpNUvFITaauEotayrwH9nAWPRKFlNE6r/nW+2ZkVLSd/RPo0RrPTx8ynRWriceGyrs/pqK+eU23o6NovXKKWs7wt6k+NSBl92IhxP1CiLVCiEuEEP9z8tgnJz9GIIT4WyHEFUKIlwghXiuE6Jdx3UZhT4bI2057BivZriCuudLClSqhL0AIrO0iPTy73cNfdU1gSUr5mfZHSffbcjwSuFVDQH/nJadDZQOB8guK5Qq+9usD3GGtY+upIqs7y4t2dyTIc++8mJcEyh9dnn7H6pZ4yfZm0xWE9WD9jlVQEAG8yRg0IQT2LFt5FfFppwoOXhP3puB4xIwzVY7HP+5zu9k2XKrfsU1gux5JPSB1D3uYf60ZnjD5wIOD7MtYVc8XHY/BTJHuSJD+MYu/+e0QH3x1eZ5clNSlh+k2Ck3TuO2ly7jvUI5twyU+u3WEPacmFux6skNOp2TGdfkphucS5iZElPHr4wU2Lo9xRSrM/qxdtc/9h3LcvCrB1lOn5/jsUH4hBCcLLq+/fPH0sQ2pMP/w6kXccuVSPnfjYj50RRfvXt/JTesWAXBlKsKzwyVGciY94cA0w5Lt8uCRPP/f65aSNJp/lXzV0iglx62ZVuIHliuIS07ZsF3KEbaS1iHbE0SCAdwaMdH/unecT7y8l6dO1k/DmkK4hg0PZC0+fvN6xi0P0UAMtuUKknpg3nednN34e5DtyU/vtT1BbAGeCzJhu4JEm3OUgXZ9b7ddgR4MNOTzZwOW5JRHx/WISkzZEAhpKRvNoC3fomWnbDgZm3g8grVvP7izXtJqjJm+TrVrSE7ZsMfGiSVi5RC02XvItpqy4dpYmXGIlfzpWslh8pidHcdwbKkpGxSKp1Ms6unayHXSNHeP6tjUiEexB0+A487sX8U+9WzqjGWIJWPl+yJBV8ssEOntwcsXymFRFecPxnv5Q7t8nXdc4PFXDx9lqCS4JBXlM8uKrF4fnCtzknc4M1qbQyO6ppGaslGaKBKxvYbt85thm28fNDn1s6OY3lW865lB1iSDHBrIck3UZkfG5dSiFdz8qV8wanr8wRId0xMUHbj1SJ73NKhrPusQx/HlC9V4Tz9E/fj9PD7828hSrjgyytXNriW15srse12QnLJhFoi7FmZ6DKygLxmz2+7ufgLFIp6gqv1+sTvDX18S5Ff9w6y5NDJHxmMnLN66qBvS4/zzBp1oSINjByGd5uGNcWkhmH501YFXxB2Onhjjnhvi3P3YTtaumPSlQhEhM2Uj66B7bm0f9NF2LI+YcLDHsnLt4ze9ogWZPzhk8nuLdZZA475QmEwjq3I+k83TlfO4IeLx873jrOma2Wf8+V0UcwVuXSn4wp4s1y8pP1OjeYehkofo78dLp/mTrXlev1ifcQ0NuBy4PBiGdJrVs3j9Xkzw8gey3L6mAy0RwMwV6D/o8v8+OMgFAYdoVszg2qhNLwG+cHWKb20dq5lu0KxMJ+cSGw9hOSWm971vUsbstpW1SARtrEAJQnNDwIUQjYXlT80d08MoWmDOTWM4vHUnyzBZLzTuyxWrythzcIguQ2PR1LtiGoyAiZUugTlznew/WuJ18RBjIYuBQ8Os75i7jp549gWWFDNomoaZteiJBLDyJQjNva+f7y+yK+tylwbR7Nic8zMwMICVHkMvuFBwq+py/Ogwn9iR54vXJsoZRA3MP2s8R1wDe8ysaePnMw5XdoUa9qdy6gE11zMxuVNMcKpYVJ17bZ/S6HSKWMMuhFtPN9TaNGWjXVNJnFyJSNDBHeH0H/6trC2SUzac8RyG7eCNjJSjAlqUaedsYq6FlclCRMLzTmKK54y5NdWnBtryg4TslA3HLBAt7MNaeRFMnJh5sRpjpq9TK7RIYsqGo8eI5bdhdXSdruJcZ0xd3hs3Itauxdh8Eiseh1TSn66VHCaPWQcmCEXyiOODVUNH5+U9j02F5JQNITFlQ8/vxkpdACl7Zv8q9qlnU/dUkVhuF1ZsrRRdLbrpePQhWLx2hv0mLA93Yle5Wu66dSwDPtPZheMJVl93JfQ9Cr03NMy7WV01ySkbIjoZtjgwM2WjdPEa7t0zzsDhIH97Yw/uJWv47JPD7M24bDlp8+nbr+CWX36PT03cyNcPmaxcHOF7Ny5lx7Y0X9uv8ZdvvowNbpYDWYs3XJQgoQf46qkQX9oq+LPX9KABpdVriNbgnbeLxJLyUjYsV6AHMv78fh4fdgp7MJI1wlzbMGXDFt3EBwtYHUnoCcsJpb14DfrODKbrVV1rhibgilXwvRNDiJ6e8h8a69bh7u7nZwdzPJq2+dxbroR9e0/7w6SMUI1r+rKHT11vqjht2sDk7ZCesiFKhHRLasqGVXSIx1zMRFKqfURsskK6TJvH0mhouJeuJcieGefHn99FvzXKoRMa/+11tWU4nmAw73DhrLBgsXYt2p7TMvOrLiG+fRRSPSwCTp0YQaxdi7V7gLGSy8Fxi5/02/zly5YQSugcfOEk3xkNsz0f4LbebvIjJs9GF/GpLce4cVmc26/qacpHg8Ajb+tmePFKyAzyVLbIb8dMPvj69bw1lm9IxnxtvT+LVSXdwI9MO2CSSHRgDQ2d3vfeJ69pmZkJ4ouXYGWGIBWf0+d/PjWCHhB85JpLZr6/15Bp5x30XB7yc9MYHho2eMuGJRAJ0tE5xsjyVfTOkvk/fzXI0ZzN/betJBIKIPIahjdR3klm1jp57MAIy67ZwCsCL/DjfROsXz0zpXP3qMl/uOcY3/v9Jby0N4KVnSDeE8Y2wnPC8EV/P25klD+/NM6v6eYPUoEZ56vdt9JIiYjmIFyzqj1+sXOM5d0xnraj3NTg/Cu9kGFJLIQVDVaV+cdfepTtIyZPvH0VeqP+VCdd4L0PHOeynjD/7eWNPd+8vEakOJlGE5eQbigxNWJ6xwgJqREyU0mkpmwcGyWe6sXqcgjpAV8yZrQlp2zYuzIkXAerq4eIBJlO7wriu7NY8cjpVLVWnncS3xeaSdloyw8S8ota2sSTMawDByEw6wFaY8z0dapdY54ICbF0GV//ye/40JJ5fkmfJdMazhLrSGCPTv4S2MCYurzTadz+AaKOhZX1yr8W+NG1ksPkMSs7Qdx1sJctw6g3Zvb5RmxaT9dGrpNGWoSEEAI9Ecc6OQTBKkXjmi1qmckS60xijU9I0dXK5TAu6D39C/Xk+ccHLW5dEphxbGWt6/j0hXnHpJEaIaEVi4j0yAwOJ4seH7r3KF2ay23dYW75yUE6osd5z4ogf3WRgXWlwQU9JixfxBcuD3GsEGD5yk5Ip9EKRaLJGO/pMSGd5+puYLz8q8+di1P8j3gXr//RQTZ0BXlk6AAXRgP85MYk5uLlJPv7CYyWI0jyozYJx/PlC9V0LVpeuUimH7+f577a0Th6Idf8WlJrrsy+15IjJKxcjqRdwhx1QVT5tasRXrPatuVhlAqYtphjP8cTOCNAUmNDxOHnz5/kzcsNHn34Wb78zDBdhsbtKwz0fXtb1q3ldiN90kCiHKZPoTS3+FgLPOwxh5Dn1PZBPzKLHnHPwq4VOebTPto80QzjJ0cYKnmsSTYXgSMKRaJBDWt3/5xfin/5wineuzTEtjGbXU/s4HKRqyrj6/tKbE07fC2pT8sMB8DePYBREZ32k91Zro/a01xuTDj84ecfZnVYMG4Lru0J8daLullm5sGEN/QI/v7hAR7ZmCCby3Js2OR/f/9pdOHyny6MEslWKRpax6ZdQFe4HE03WrD4xcYOorG8FD83inmsERPiVe5BkzLNjENSmIxOFXj2ycve3Y8+Vr4H5rhJR0jDmpiA6NxCmRGrRM4RbH50O2/qMOtew8676AUHrTC3qG72KKQuAvJwW7fHvb96jg9WvEuOP7+L6zsE715usOfwMFd1hSANumFhu4EZ6+RQyWMx5fe+xcUsR0fyjA469ACk07hC8F8fn+CeNy3nwd3DvDQQwcqaGKEipINzfvU+cGSY1QGHlwQEX9iR5w8uqn6PvnGgxPtWhwkCpdEsEVdAwZmjq7O7n6HRHJ9cH+X/7BvjpgbnnzmRJxkIYptz++R27uaahODtSyLc//xJbg9ojfnTPL/OP/bIs7yxV+NYodTw801LQ1gzsdImIwe8MQAAIABJREFUlOb69Z/8y2Zu6hbccVF4fl5T7XkiEYQQ/N3zRT5zVawxP5ccITEn8s7nHBaFYnmnbAm8rFyRZGgUO2iXI69a4EU6Lb+oZS5P3BGYI2kiEmTaGYuYXcLKWpA2ffOaak+/a8t4X6j0t6ljNdCWHySkR0gU8kRzWewVK8EcnnmxGmOmr1PjS56Wqx4hsf14ll3dYR4ueLxuZXzm+VoREsIgtnUrdseGuXvIthAh4Vy8hvhTI1gxo/xrgR9dKzlMHrMHsiRsG2vfSYx6Y2afn8+mEiMkhMSilo4niOVfwO5OQcqb2b+KferZ1B0sEB0fxYpWj5DI/uBf2aSt5/OvWdyQrlYiSfg3D8IF62bY77n9I9w8cgRSNzTvPw36wrxjJEdIEB1FpFLQP4j3mtfw2LECH3v8FH/1hvW8vbNE/N+e4OY/uobEhvUzfmGc0jW0cSOrKq4hYulypFMNX/g7824+cOvbSEWCFFddwlO/fZ5bfzvK/sxSPp2J8u5J38plJ0ikAuVfzyRESORzNnE978vv57uvdmE/oY5k674wuw/l+abJjpBIJEnkHcxEuFyoafavUJeuJVD563QD17GWr0LfNw6mO2etefRInldfdyF4ad7ZI7j9vmM8kglw7VW9fOrVIa5IhRu6hqxfUVqVuTaeZNvEMFf0hNETY5Prl6QICbu8g4PUopbjNrE4WPGYXPvE0uVUiCpjHto3zq8Hi9y5IcFlTcjUYmnC4SClVZcQPXZwxvnDz6R5+6oUS5Z7fGsoxOXLw3NkiP5+sqFRLl8yk6ehB7AuWYNxaP909ycP5rnjZYtgMvT4hhTccHttrrem4JY/Wktw7x6Sjsc//uoAT33idSwaPNyYveq0H35bT3lbW0l+buyfwOoMQ6fRssySUyTZu5SThYPlAs+z+uRsj70Zi6vryHzLA0N8d2OKnkgQezhLYvVFZPcfrlooU4ul+eTVPfyvIxpvaqCQphW00B0ThDWjz8GsxX3H0/zVy5YCsAQ4ZXp8Zv8oa7sNHjySZ+lyjzs3LKLkCF4YNbkqlYQcGKE8VigwY518aCDLa9eeLhD7p9d28H8GsiS8AD98YoL/eGkH770yxSXXXck9+8sFr0vDWSK9cUCf86v35hcy3LK2h2A8hD0hED2c3g68Qo/vbT7MKy7p5fJ16ygNFogENLRSYY49dsUXc81FecKLEhSOjMx7X4/lbFYkdFi3DnNbmkQqXt7GfNaYraKb61abXLMowue3jTbsT/MVenz6MPzVy2J8Z3eWE5EESxuJeMhrGO44ZtIov9NXnE+XXK7ZEKb/4Am8nh4CVWw4uy3miZB4YaTE9okiA4EE6xqZK3UiET73gy287dIkqzqMury0WBoxT4TEt3ZlODRu0/eq+XmJtWvRtk2u05KKbYaXLcEM58qRV35kVLYlR0hYO8ZIBMDqrPI+BgwuvpBtB3O8aXVj0Q5O51Lix/JY4SCkOnzzqnzXJiXpfeFMF7Vsd9ieII7ne29l0xXT+3QLIeYt1rfFS7Lptit4ronicbYriGnenEJ7rcJ2PWILsF+z7QqSRgBTsvvIZKkBQa36/urNwvHK29HVKkLVLGxPEMOrWoRKCMEN5kvqFrz861+f4uhEOX3EcjyMWdbbcqJATNc4SzX2FgRTM88RcNX3D/DFHWP82y3L+cANq4lPhuUljcDpl6T6AutiRUInGgrQEzd440UJHnzrhWwPP8u92wcpTBb3ytkeybC8b7t52yNpBJoqrNkIdAQLWddXtmjL8UgYgXJ6RRV87lcDfPKJ4RkFSeuh5JSLP1XDrlGT61b3AOUX7S/dtITPv2Yx77z+wtMfI84h/MEVi3ngcI7iPDr7he0JQo3OsyZkxvXAghR3roX9WZt/uGERP943fwHQp08V+YenR2YciwQ1zCrvFFNrbkIPkDPdqoXVfj1Y5MpUmI5wkL0VxUfDQQ3TLv8iLoRgz5jJS1Z2Nl0ALTjZPxoKsOe9l7AoGakzonnZsjC78GYlvr0rw4+ePtqwLNMVJCOhmj70nd1Zfrp/gi37R6qeBxgrucSNEHsmC9taXu1CmQNjJotjIQKahuuJhoro2Z7AqGLDew7k+PYHr5tx7IrlnSyLh/inZ9NcvyTKS1d2sSKhsyIR4ulTpfI1ASOgYVbwy5guh8ft6YLVABd16Px4/wR7h3J84uW9HJmwuWlFbJqT4wmylkuHEai6lg8VnPIf48DaxYlp+1Til4dzvHN9J1sGy7U2So4gEqruL1sPjXHt4nLiW1IPULTcqv3u2T/BzT89OqNAZDhYvYjn9mMZruqN1H0HeMt9R/nazrF5+1RC0zTecFGCXx3OVT3/7JEx0qWZ/MPB6kUtHzic4/cvX8IbLorz0JH8nPNVrz/PuX8/MMG/3rKcj24+1ZD/Tcmq1nckZzKYd/jZgep6NoMv7RjlQNYu11mqA8v15i1+WrJddow0V5DbCGo114GhgjP9/twoahUchuq2nA9ThVlr/c337ScOsb0JfR1XzFvUcvOxPO//5lNS/h4C+NHecbaearzobqOQ8hatadobgS9Q3vbza0KIv591Pgx8B7iGciDpfxRCHJpH3q3ILGqZtYh1d2AdOlIu7liJgQG+/P+zd97hcRXX3//c7b2rV8uyJDe5F9wB0zEtMTUQQgK/kEAIqYQkxEASkkBIIUBCEpJAgk0gBUwvrrjbuFuSLctWb7vS7mrr3XLfP3atupIlWUmcvD7Po+fR3JnzvWfOPXdm7uw5Z3QllFe2sDBNOfA+VVX8fGsjAN+cpCVSUYU6FCQySDiAV2/BWFtD1J/ibO3Bklq2ytDZzIipzpDNzibY6qSiLcRMeb+zpE8TshENxdCJQSJRAVyx0/Ok0mdvuZPXIj4/eiCckXV6nv71/8aQDZXJgNjuSgyIp+vrEDqNRiQUJhP0d2FK1ktZ2cTanYlF4zB0GnZ7MdottHkHus9Xbj/ID9I9RMxGKk+09U1ClZStdtchZGKYbdXt5OWr8bd50GeldbvM/3zNNrbWe1mzwADeUYb8DNMWhuRxMaYhG6fOvP6TYQKX6pT8eLoGedx3elsYpK++rgBZZsOIbAHAmJPJ98v1PLC+nkAUtArItenB5RuTkA1fRxSrPI5YUYlmDEM2lLpEjPAZ20L/NiRcVKUhQjb+9uYu5qhC5OvlKetTXYu4vFhFf+IMa02oT31cklB0CiwyRtl/vI0ZVkVq3KoqmhvaydImPshDHhF10J9IstZPfxFfENXxnnCMPEjY8GDPbbjl0fCMAaYa0IkhNla1YYxJeF2xMUxqGUERiwxug6PCjKKLRBA94UHbeCMSJuUwEggmr0XbnciDocRGXAoeIRhE5e7AEQ/jOXAEs8+dEvP9o4HEjtupa4EgakFG+Gg1RLzdLK17D5Me73HtLpep+fFHndT54yhlArs7ovxwsZ+ndrfxwnwjYbXEL9/dz3fHCwiBECpJhni0GkIe7tzhIxST+N1l+eDq9/E0Ah2rhtN+hJhjiaH0dw0INwBoCMSQBSLUHauHQcIDJEni79VeLjWK6BUC4U4Rk6oBKZBM8NyPx+cNsqpMw5M7j7JgEMyXjgV5eFoaO2uczFdqiHSFMDQ3EPF20T9R5o+3tfCT6TpwuSiMKqk4EcShlhGMSWgDUdKDngH3iLijKEPx7kSP4TYnf60T8fhj5LXX99HPVXYgM8YdmSYgBvpEmIwGmKGNcOubtVxbZkMlBumKSqAK8pfXdlLT6uW+Uu2A9/PNxQYychLyXj5JAYFEAtkp6ggfHG4h3BVD45F65u4kVe84SKFc7MZZqI2y6PV6PlWoptggZ6ozRH60i8+v83BihYWfVibG65DbiyYmh4A44Nl31IG9EPDDRGWEih2HmISP1lCcgmT4TqTdyasVPp6ZpWNPdSsL5AJSIIiqK4boHZgoM9oGqsQeC5lSmC3r97JQ3ffDKXykkiVWgRaXD8kZS3xmJt3KJaezTwK+na4IxQo9uEQygZ31Pm5Lj/ZN0gc8t7+Zd2r9VF9pSawDXaDSRBDDQmJN30vOmpYAN7sayFME+GVNiIsN4QE2uK41grop0CP7ICEbktOJRgyj9XTy6XwFLXuPkBXqa3MbKlp4o1HkiRn6BE8giFoOYrsLtdBXf+uOerm3QOCPJ/y0N8ZI0/RNyOkW45gkqTtcVRoilCToDfLIRC1PVqZOzhpodaJLblaExRjqUBAxRSglwJojbo62eLFO0JCnG2QN0bscCKJqb0NUBBOJXnvVNwfjPHssRESS+IFB0d2XITEHSzgMxCsreWxzA+UWBStyVMMa8+L+ABpkiZCefvWNgTg5YSW+WLhHR6fBjLaH0IX8dEYkukPVerXZfiLAvaUOfrq1kW9M1J5Wf4nnKqVcL3hbnNS2hjjRCnMyhpZLqqwcUVLLM/7ZRBAEOfA0cBmJZM03CYIwqV+zzwKdkiQVAz8DfjwUpiRJayVJususVCbdRpIuPKf+b2oaeO1U+VRdr/qo3oDO7ULMyu7bPtnG7Qlw374gbVrzgPt05I6jIabAp1CD3U6wcDwak6EnqWWv+zRrzGT7E25ipdlmjitMfeVMylbnyGN3VNfNH7Ha0XU4k2fI9sXsbGzlxp1BHjngI2q1nbavve8jjivCYDYgarSD8mwTtT08qfTZW9/Ja6JGh9FiJNzSdnqe/vWD3Uen7RuyMdRzHc597A7UXg+ixZpaPwPaD65T0WJF5XUnk/cMlGFTg49LN/uJWG2nv09pKSGdAVNHGxGtbkD9TsnEAk8tV07N5G23PGVf3w5o+faiHGrjCZt0GSyYWxoJqjQ8cRJEi5W/XlWIzOEY8bsyUlsYWqeO0dlCCp42rRm1UQd2Bx63nyeW5yN3OIZnC4P01StTYfZ2jMgWTt2nZH45RwMCdpMWSaVGlZ42cv0MIrdfZ8RmUBMuKh653Q8htyroR9Tpz9wWUtxXsjtAp01Z36Ixc0xm5MUW2aD8qa6JjjQMNjNhnWFA/QHJQMnkQpaUZbDJN8g8kSx/9ZDIR+GEbKHcfDQWY4+syfZ74/rEGD8MuUZcHguMUWJeOTmdPzfEKMyyIjgcSDbbmMgR1RtRqlVj2jfRaMZoNiDqDCnbfL0iyq27gsT6j7ND6CditaE06BPPu1+blswCMhxGsNtZVuLgXdGYEvOApKc400xOmpHmzPxEnU6LxmIilFfQ8w7YbHwgGphT1DNPXH7JLMrzrNw5K4P752fy+JJMflYR5BcX5qLLcGDNSqM6ouS5ZjkOuxGVyYA/N59rtgXIten4+fJcNJMnnjX29K/AUFnMiAbTgPqX2uRcNTUTeZpj4Non+f8/PWr2RjS870vMhWG9EfX4IiStdsB93AYLFrMeweEgZrX1fRdKS/EYLJxUGgkotUw8rxynTAN2OyG1FkNZMWGtfgDmlEwDjuzE2H/hsnJu2Opn7nsePrUjwC9OxlkX0HBI0nP11gDvxywJOzeYUFrMoNMSHl/Mez41PzgS5FuLckekv2unZfH0RXl84vLZmNKs1Ata/tap5DdVfsxmPaZMxwCejJy0lJhzxqfxx4Y4z1aHwG7vs9aJ22y85dNwTXlm97X0GZPZen0hzTEFNTEVb3WpuXZrgF8ty0BwONCadPgKx+NR6TBn2Aa8f3GbDZmjR4bZxWm81AIPVES5bGMXb3hVVJmz2RjUcueMdOaVZLA9oOxeK6ps1gFz2a6oDkNORnf5+hlZvNEp57tH47zQJu++/rcuHReXpTEpx8wJpakH06BLhLX1wnyrQ86lF83oLi8tsnJSaaIhPQ/RkrCff7hVXDhnPM8vz2K/dMpGHKitZsJ6Y59n4DNZcdgS45sizUGzpOzGOdXGqTOzL6xkS3LOilltCLrE2qf/c9svGZicm7Cr6YV2dsutfdrEJ5TwlkvAZtb13EOnRW00ELZYB9jCSaWRcQXprJyazu5I3zkSu517D4h8kLTjU+NgKrkkmw0hOceqjToC48b3adOUkc+kt9z84LiUeCfGjUdtNAyYl0/9ufQWvrc0j5daB19DNGXk95FLmZtNxGQe0P7jiJabpqWzaJyNI8asQd8vydZrntFpU84h2O1swMqfTopUREYwH+q0qMxGRJN5QP2OsJoFCyYzJc/KoVP2dBrMaG5e4kd3jW5Am5DZis6oZ9bi6Qja1Gu0XzUIPXPbYM81ybPWrWRleQYag46ugqIB9V6jhSpZYs0WnVCCUq8buDYchMbCj3MuUC1JUo0kSSKwBri6X5urgT8l/38VuFAYtl/1mZMYkzAQSxmyERCjGIQYv1yawVc2tw6oP9Dg5raJZorNStqDUYKRWEoXJHc4xju1Pi6UJ35hWZKj48+VngHtAF79uIF3av2JGDgSv/ZphHhK96JNcTOPLUzn5rn5HOkIj6zf0WTIxiBuOkExxhfXt9DgG5nrUvd58YOYz+s1XXgk+YgwYexdvlXEU7rM+SUZC3+0jqf3d6TgGkihaBwNg4f77IgbefS8NDY3BlLWd4RifNwWIpS0v1BUwkQ0pXuV0xcmTYiiUciIxAe6gjX4InT6RcxqOVWdYTY3BgiIMZSCxLbmIDVekRvm5A3A/U/RWJwDHYzGeXBrO58qNZ++8QjIK8YxCqndRIdDv1qWyQ8XpPGrZZkIQuI9bpWUPL7HxXu1Pm7+7Xa+s62NL6xv5q1YTzxzsz9Kgy9CmzdErTfC+zELTx/osUWvGMeulaccrzr8Iv4RnAPfm5RIYx6+dYqGGsz/cMTNnYvHYdPI8Q7ilpuKxJiUDNkYKPNzhzpZON6BRiEjOoQbYkNngCvHGdjenPilKRSJD3AhliSJPxxxc/8M27Bl+2+hIrOKv16ey9xMLSpFal0CVLvFEYW+ROMSyjF23ReTIRupbDQWl8jSK/j2HAcf1g/t5lzrjXS7pooxaVBX4H31nUx3qAEos6k54fQjSRJxSSIUjROOxmgNRPmgzs+KcQYuKTDw7qGWbn61XCDc6xjov1R5Odjgocym7nOfywsNzEjTUGhSsSBbxz+/uJAcg7K7/g+3z0GS4NrxRvRKGZ9+fhfzM7XcNcWCQ3tWpvkaU1LKoMEX7Z4fT5FCALNaTlGageoU4QEA9V0RHrpyMpWdibVRMBpHnSI8SZIkNjYGWJid+Pl8So6Zg64wrYEoX/+olX/sbeCSf9axtsbH3eWJsVqnkFHRESYqSeiUigF2GY7G+rwDdoOag58q4uXLcnjz6jyyLVpeqvLy5kkfWXoFFc0JTxpfJI5eKdAlxlnx1EesOeql4taiIV3WU5EgCFg1cmQyAZtGzk/2uFAIAuu/tox7pllPD9CL0nUK1lyWw76biwDYU9vJhgY/l79Wx7yXT7K/3j0g7MuhVfDsBVl8Z66Db15axjtX53PlOCMAS7J13PGHXbQHY9g1A9eCq6u8nF+W3l02qeQ8sXIaP1yQzofXFbCuPsAlP9/EC5Ue5mVqUckFVDKBFk8IgYTN9F4vS5LEL/d18NlF3YfWopQJfHbROKbY1bx10s/Va+t59kAnYjTGFLuaaWkaDjjD3aGRqn5hIPVdETJ0CtSKHvnnpGt4ZKeTS3++mS+sb+HJj13sag2ycnYe8zK1bG9JelqQHB/6zU2bGgPMyegJn7q0wMBbJ308sqOdTn/Cxn+4y8Wdk60YNAq6xDihmIRWkTpgYEtTgKU5CZueZFNxuMnLjpZg97rr47pOlufpMatlfdYNarkwYC4IROJolYm+llpVA8LO2wJRlubq2XUysVYRY4nQo1RynfBGKDQlxrgyq5r3Dvf9tnptXxMA0aScYjSOehD7P9UXtVxALggp56m6rgjf/NuBPtdU8tRzyVF3mAkWFYuytXxUnTp0KxSNc80bDX2uyQQhZRjt/noPB28pQq9IvNPDJZUsdajaIVeY8Wl6pjnU3L2+JeX6xheO8scjPd58kVgy3DEF3t72EDPSEjZn1chxBqN96mNxiX3tYX78duVpZfaFo9R2RSgwKZmbqWVvnbtPfTwucfXaBn5z0J2Ua+hQnP40FrNdDtA7yK8BmDdYG0mSooIgeAA7MMAaBEG4C7gLIF+rhaeeSlQ4HOBMNj90KPF/72un2mzY0HMtWR9W5GOo3ocLJXT2dRd5zVLGJXvWU+I+yDbVBFi1qZs/eugwa8VxPOr9GJ1Mx5aNRspNAjqvBO0+eOpA930+5x+PDwWf2fUerBKxOZ3kKwt4ep+ccYZ3WNx5ArGyiuYOkYBxPHd7DvPnj3P5YqQGyVyOct9ufB4/xNr7yH7MbeGqvzyH2Z7NZo+M8mjDkH3trZ+wLRe1NwYyPXxUPYDnJctkfu1t4oM/m7h97wZYtWqgPp3OHn0nr8W9FjQxL+HqwwN4IvY0Nviy2OUSePSppwY+o0OHUt/Ha4G29sTz7sfznrUYw/4aFjifGlS2NZYyrnBXYyT5spnLUR89Qvj5kyAF+2Aeqe3kh9MN7Nwuh03HTm8/gg51UxdIKvAc6NO+y+lG5jYw79X9/ERVwgUfvd73OaxaxftuDe8qMrgk2soNlpcJeXQYD25G9GnhyLvd7UPIiJmnwpaEDFPkmWzdEcFgNlDY0cj+eje3hWr5tbIa3jrGT1DyQnUBtxoDsGkD1fNm8NfaD9G2bBj1uzLkM0phC0PxqCxTEd2HUR86kFqG09znn24VNXoH9oCbb0Y7MFf4wFwOtbU940Iq2YbZV69mLqajewbKMEz9FPfiUVqmstbn5D7NdGbtraEt7udqbYQr3ccQgB/40/F851c8H3ZgJEpOPMjHyqM4JQW3N3fi8G3h4MHNhNxdPKGZyqcidYgnNvPOgUZe9W0hjoBZiiCotxMSI4xvifDVVO/XEHKrvXbEgBsOvH1mttC/DYC5HCEYSIwz/e+rmoC9+n1WuHys2ZrFXZETA/mBDnsmv+yy8j2xAgGIWKZg9NQgym3wdkM3jwSMV03A+nhCZkE1geat9WRJoQG471omc5Gnhp+pJuDfepiQNR+Nxw0Ke/eY+JTHzPVxN+YDrpRypdTxSMpjgTEGmGrLZMLuKjRE+7T5q1vDPrmZayJNzLXJh4UpKrJQy9OJHvkbCod9TPomyu0YkOOVaWHvW33aVNvymOCNMCfawk9UJVy8dW1KjA6UfEk7m2+IR1loFQi5ulDL00Gmhsr3+vAcMZdzUa/xPGCeydJ1RhTEaRK0lMoOII9GOC/mQrPlGBqgxjyTkmgal0VbmBttILTJCB0nCSHjmKqUH5naYf3InpvC4eBupxM2QoHMwGJjGQ9s2w3bho9xVtjoKDFyXX4e1szky3IT/1C9wYyOWtoENQZFNmw5wXx7Jm941ZRFavtgtApqfq47ny9VPILRY2LLTg+tMjP2nW9Dl6lnLAK2WsdxX6SMGt/bACyzp3NTYDwtgoaviUfJqd3Jjzw+mrdpMGxOjDV3OZ18WjMHA1GUFR8geg2wrqYb82lzOfN9DbC5o49cpxa/X3Q4ONAh8kdlAb8OH+TJhnLwHKBLkUlOzMdWzTSe1NYzpaMOTi1DRqlzq9PJfcpCrn7rJOx8Y9TP8ZSH9lbDpew/FuWNwFZypCAKyQ67h8ZQ9SpPBa62TGTrMTWKj/aBqhgq3yPs7OAxVSleQcEt/d5xHA50Tic64EngSYcDqpyQXLJ/QtBw094mLg83oP6olrAyE/YkMH6gKmOWFEX56KY+mMUOB8VOJ9cDnSjZVm/nUksUXE7GAa+pJrB920YsvjgyJMT1zeAwg9PJX1Ql3CdWw+F3ujELgR8JatJtRsIVHfxDkc2KmBtqP0TvdNKonkzLpmowlaLqOkFY0EGstVtfB1UlXC4ehQ8T5dko+LZ6MhVyE4cq/o4pEmBhzIVxfy3zbQXs9AQoifuwyu0E9LY+60+fPR1/lwX9pkRiZwEYbynl85FcrJLIrJgbjUbJ9zx7SZOZ2PKRmoutcQSvBXU8SDjmAruhu28Pqsv5nN4NHXUogYiqjK/uVfI1w6tIHZ38UVnA3WINayyl+N6uIIIMvTIbt87cR6643cEF4Tls8m8AKcgSBB4xz2Ce9wi/UxbyRfE4DeZyjvk+5pf7imHnMcK2HFReCWS6nm+VpFwNgpYccwG4K5kiz+DA9hDT456eeQOBJYZLuUHeTnjvx6iJI6mKUR7egehxQdzdbV9xp5OQqhTFR1WYgS7zNIKeg2hP/eCYxJyvv5AJcR/S91YhuJxIqmJUUhzxyHtoXD0HI0hAxDwNtWc/58uMrN9q4CpLZIBdt7m6AEiXwuBwIHktKGNuRCkK7/+ju30QGRblOISaDzA7nXxDkcvRZzcyyabug7nROoFjARUfbGhneayNoHU8No+TmDwNNvddg+1QFnN3pAY2vcYKVxevb87ksmgr6TYDcpeTL6unsTLaTKUxE/Gjg4l8dKpiZDodMfcBem8nvmst5Xp3A2z3Mx0ZD5tnMN57mBwpRBSBw7Z8vuEJcdhpgv3HCNszUHk1+AVl37XhIHTWbb9LkvQc8BzA7OxsiXvvTVSUlvbEnqxeDTfd1PfaqTarViXqevGED7sxmCTEK68Gc994sqZauEnhhJtuQrmvgz3zS3lw9R6KzEryzdNZ+dkr0UXmMxn4YF8HmwQtVzvinFy3G25NZKWPTyhhyotbuKrICPplCRmqqrgqGOW3h9ysDit4KW0qTcYOcrJs/P4Ly1AdP4Z/jwtmXYFQJ6CUdyIuWg4Fhr79fWETwm23kl1SwpbnNrFySUZPhusUfV1b08Us+3tk3/wJRGMW6oPHEDpFmHHZAB7nCYm54wQ27HGB2d8tdx99VlX16PvUtTVbUadrCW/Qwaqv9eHZLrPxycYGtr+/i40XXs7SC2b2xVy9GlatInCoAl3v84HXbEU4eAhuG3hywOaKCFLczNrxxTy2MD2lbDv2BXm9ZRIvXZqTsKM6AZUsRPjK88HSN3tApupdAAAgAElEQVT3wRfXcfU37+DE+/toK1xOeu8svEn9rG/wM2nOJDKaawl1hNG8tR6WLIP8vicebHh7NxdtW4/sllvR7+ug6+rZGGtruvva9cC3OfrKDn4/x8HP9nbATQsIvrodnSkEE+fCjQu65Xr+QCc3Ly8HZSPcdBPLYxLTX6qhJMNMYW6UeZaDzLJpmP/5u6H+BDbgy91yi2y+phittuyM3pXez2hYtjAEj6pViWhdgvpvL6eWYYj7bP7zm2wtnM2ECbk01TUzYY6j+7myYUPCTgaTbZh9dWxowaSbAqu+MTCubYT6UbcpaWhuZdfhD0m7eeUAni+/9Aq7PvkJfhN0YlDKSNcpiBRPoPNABemvfUz0hit5qkGGwdvBuskW/llTROPEIt7/7Vq+e+0sXqz08I1ZdlSTyqCqih+8ILD94lkcFEw0nmjCGYpxc6mJvPJSHJKM3UtX8GG9nwduPg9NTWIiUL6wCbF8Ctxw3pnZQv82AHUCuJyJcaZXvVeMoan0wsr55FZV4dnjIjLjCpQTywZgvtqqQFXXQkPZUvKMSsQGGQb7YsInfDDJ0o1Z1RGmsCMMV8yBqipMhzq5obKMfKOSycVZLNaGOOwKM8mmJqYwkZ8R5ebWIL9rnsqbTSLPXGmDE12I5ZdyUJ+Bdd8xFpWZU/cr1bWRlscCYwwwNW4NYdWSnqzjyTa1L23lO+VWfnfYzdxUtpGiHK32om8NEZm3CMXkiQPaxCsricQTv2oNV06x3o9BLiTiaj85v0+b/V065kkeBJOSwPZ2Gq+eRU5r3QCMvx9282yBnucOFbDgtoV07TyEqSNMm0fsM9bG4hKxOpAX9owjs0JGFrW1UGhSkmdQoCgrJVRRhUEpAy4F4GsFRazYeZg5GSXsbg3yN6eMF9s7CUTjfHWmHc4rP6PnVgb8qLQUqs4bNcaoyv9BjLyqKt4hkXhtu7yMaZkR3qn0cHGODkwq0ktLaX5xC9HZK5ALcNyWi67+JHevb+GNhelw3pXcdrCCWWtOYFPL+MJDl8Kard1jUSga542qKOtzQWZOrCd1paW8cOAIJ7wRpqdNSSmXvKqKP8YlDrvCaBfeQejlbTDjCgA+agogjxlYkJfi1K1e5fKqKp4EYBnhmjih/MXUHXFz4UQLmncbKf3yDVB9bEiM4ehcVlXF587gGfTHvGZ/kCfKNciEiaPGuKF4Ap+orALFYoK7nNyNhqDdy3XFRorMKlhwmnelXzkLWH9qrIhJNH7sYseCMp58fR8TrWrummWHKQPHIqqqEAAbcEWvazLAeKiTv4RUPDJFw/t1PsI5epqKinjmn7uZna5FO/6SPnIIQEYSQ1NVxU397nOHW+SRvROZVJKDWn8eYkcYiox48opY/dYeMuUCTOrBNAO/IpFI1Z9fSLT6eMIrSimjvHgCj6/ehtuqYrpdTWOXBilvSXfCzof2B7nUEoOCS7q7u7K0lBk7DhKKScgEsE8uQdG8kKlxie9ua2fydbOxbziAWi0nbFfD3KlQVUUoGqfgYCdTeo2Rt3dF+PR7TdxjncrcEomL8vRYMy6mXG7nYEM9uQYl+pYgbrW5z7p4m9zO7VsqyZ+fsEglsFyw8diG8VxeaOD/Dk/k/hXTUMYWkF7poSVvOW5HNuZjJ6A91POtkpTj/cNuliyaDJ2NLIvGeeZgJ9Nn2HmsJs61lgiuUIw/xCWE3Dnsa5nOvEwtwl4X6tklRBobIFPb/Yy2r9/LeXEJci8GQF4ncO3Hhfz5kmxUcgFvbiGeimrubw2iVgg0LPwEee31CHtdqFRywpfNRFPXsyl5yBliqikdVEuYKEms3ePiqlsWDrDBV1/ZzpsnfLy2IhfFxLLEN1SGFlEmwNLp3e33NgeYEQcumAFVVSwPxXj2QCfmFTP5/et7uH6CiTKbmr3HYjxaLOPxPS6Wz3bgDxnJC7nghK/PGixSUUlwjwv1nIROM6qqaNzZzmebgwgaDbOLBDTROEvnL0KSLFR65jHJpkZ+oBNVZjph++Ke7zTgxEm4rkACQUAD/PPPJ0hbUEpMgoqOMHG9nqfnGKmv9OApuQhfbiGGrYfp9EX6rg0ffphUNBYbEo0k838lKTd5LVWbBkEQFICZRNqcfwuJMQmDEEPsl6094QrU406yPF/PPa8e4KpCA+PNSnKaO5lZZE/s0gL3TbfxbLOCcmuYjyX4zcFOFDKBQ/v2c2uRkZnpfTNZO7QKvjXH0f1y1f5lB5F5V6JKur7lGxVsbwkSjWtQpXCn3tseIltIuHEJgsDyPD0VHWGmOFJnzO4S4/xot4u7Y2Y+xdCZaxt8EbItRiCUyAYuyTAMor/jcQ1/2tbOw/Md3dpSywVEaSD2oUYvn7JrmKdo4hetIZYOaJGgL29q5YI8HTeWJD4EhnIWtuiUfFVZy9PGMvyRePeJCqfIGYySbdEwDm2fjPLqQU6y2BQ3cYdBzaJsHa9Wd/GF8r7ujXvagvyl0kN+oIaHSuSEY1Ji1zWFbFWdIlckE5FeVmjgj1tO8vnshDtzq6TkJ68f4VhrCEFIuMhJkkSgXwjI/vYQL1V5sWvl5Fp13ddVcoG9NxehTn6Esno9N12RCzrVADmAs869Vz1EuNBQFI5JvBG38ZUZdjJnFkHVyEKKhku/WJKB/OXUYTYjJZVCRn0whpVoyvo0IcrlU7OgqicBnlIu694MU8gE7r+opHtiUskEjrV1cbXcRYFJyXfm9t1VvkPRwpPVXnIL9Hxlpo3jnggbGwJsDNYii2YzWYwhAT97/ygPFAlEJZAhjdlJMf2p70jaQ3taQ8zt5aJaZlXxzkkfaWoXBmeoeyxrDUQ56RL5zAQTH9QnXORjcSW6fmEGkiTx8jEvD87p0cfnplhZlqsnQ6dgvyYNz/Fafn2wE4tazjvfKIfj1cxO1/C7Q25euGM+6c0niUvw3W3tyKwi359o+pfo5GwjlVzGwzucPH1+Zvc1byiCRi6gU8oIjuAUqmgcdMqEy6k2Rf3aEz62NgX58aL0FLU95AxGOfUkwzEpccxiijGjoSPAyvzEu3LfdBt/P9jM59LBK8bQK2Qca/ESc4Vp9EXINigpd6jZU9tJgyuMLYXL+Nc/auPi8yYAPe/jVdOyoaqrp5FcltyM6CGTRsmc5MkAGrnA3jo3T51no8CoHLHL/TnqS8ty9fxzr5eHTvrI1it7jh0Eris2csu7jWTpFEyZqELu9PPoeWlMtCbaGFUy/nhRFjPTBq6NVh/18tlFkxnX2XdZalbLmZ42dGipQiYwLU0DyY/AaFzivTo/H9T5+fZNk6Dx5LD7d8vcAl5Yf4BwNJFh/59X5oH87Dzo7snrpw/c+BghKeQyFMm12HGPyLdWlpPR2oBRdeZ9VskFnjvkxp7n5g/Ls9EohJ7jM0dAd06xdq/PVTKBz33QTEzl4sFyI0tydKcH6EfFFhXfmu2AohyoqSEUlfCEY9z2/A5WZCu5aZCwU6tGjtWa2IA7RQq5jFyjkqf2dbLhkwW8H5QRiccJRGM8c6CTnHQHFxcMxCq29FofmjTQnLDjO6dY+Owfd/HEXAsNvgih5JFb4ZjET/a4+MwkSx+cfKOSu8utXHPprESy5ySV55r55bYqzs/TkaNX0BhNzMtCMpzilt/t4N1r+oYNLy1JY6mUmHfOy9RiLLLDMRfzM7V8WO8nXSOSoZEPOMkiHJNwhmIUpxugEzQKGbkGJXd+2ExObhq/OeRGJRP44YI0xHF2frfvOPOSGxBKhYxQv2+qzU0BvjbT3l2+f/kEqo41ccs7TYy3KKnwtTHFKPD989JoDUT5uK6TvOQEp5IJRPp9Q25oCPDZa9PghBdBEOiKxHltXyMXKuJ95g5fJM6Xpls57AozLXlNJRcI9Dv27I0TPh7qtdaza+TkGhQ88W4VNxYY+FOFhwydghmTCpEJXlRygVA0TodfxKyV0f8MyFeOeVkxru+X3QOzHYRjEi3pedia67rnxyXj0vjJ6uMUzFCiUwgokmsvXTK6sMkXIRSRkUgbmaDtD17IY6u3Y1DK0CtlPPWZuVBVxVSHmsOuMBZHFKNy+O/7WHzB7AImCIIwjsTGw43Azf3avA58moQT4ieBddIQweWnTtkocqQNnvl9BBnmRV8QQ2YaYnMrSD0xn5/a2sXlE6zdPJOAdVdmJflFyDUPuMfdWXZwuZGbjKw95ub8DCW3TtAkTsBw+YfMpl+Qa4dYV3f5EmOcGW+3Y1TKuCUrDb+7qyeLc1UVT+9u5YfZ6u6+TlcGWbq2lUemarmttx6S7V/e18zTM7W8f9Ce6HdLEJW/CykQTWSc7qWfd4+HWDFFAJeHOZoou60FLEsht+R08qEhnzyZSH19O/mCkMgw7oviszsG9PXosShGlQJysokGgoQOV6Dx9MoQnp2Nc99h5pvi1LV1IVojqAAhEERKccpGV0RC75VDdjbLDBG+u6GBb0/W0toRprLOxdKMXJ7f08IdszJpiEbYVNnKJVkqcIHabiXc4e6Tvfu4L8bltoQuxke9bDjp45a0KCZlcijMzmb9URe/nqbhF/Vu4k6JUEcUtcNK/1M2pMpK4sEgspyETouBUGsX363yE5Hgb+Hp8HEDJ1ZYwOViuTnGNT/9kM5AhK/kZCMFgngOHOGbm5q5t0TDOL00wIbVvW1/FCcrjJpnEBseCY/KpSCsE0d8ysaD6+v5XGaczJBnYL2LntNYBpNtmH2VDybDKPSjcikI+oMocs78lA0ApV+kpTPMtHRrSp6snDQen6gAexxcbmbIYEY+YJdBfRxMIleaZDzX5OHz73ip8Mb4WYaKjYEgHfuP8P3NjfxfsQarSiAdiGdlIxuu3ECkohJlZ68cLC4QgkHiTmdiYZjk2VcX5AsTNN3lYqKs3NLFhfV+2r0hVuapmGVTsLk9yhdK08gOebhoh5ug14+k0qDWSoi+ELjiUFXFu4dauNAsJO7dS65igC5YpJKBKcy+XCUPTtIiHK8GlwsB+M10FbTUQkcHVa0+rs5VccVk9dAZsVNdG2l5LDDGALO5voNNDT72HGtlhlXOsa44T37YzNfHy8Hlwh4P4z14BFNX6pMmepcjXWH0kThhZ0fKNhWNbtIEIWEPkBKjMRDnnj0+/qFVgMtF2COiR47o65uRPy5JhNpAMCQWqzZgx0GR/TGR6q44hXoZbzcfRyuHD843g8vFxUaJGc9tIxKHTRea2N0ry//3DwUo1ci4VOk9I52bAjHUUZEJsS5wjw5jVOWxwDhL5bq3yIjFL2BXx/uMoxMlHz+dokKSIC89AvIY4IeOnhMMFqgATyKjvxQI8tr+ZjyROC3BOMWdjWesr/1NXXymsYvN7VE2XGDC3nhyRBj5gCUapN0Xo/vnuLNA5/8OW/j9DDV0NkFX5/AxToP5xHQdn8yM0ucEmjPom+ALk66I8YfLMhL1ruCIMSD562x7PW1eN9/b7uEbW+DWMjOfy4yBu2NEmLemRbn1fAO4XKg6ZBz0i/ysMsjXJ2qZnCeBq+O0GKfKRcCNBWomSV20+6M4A/Doix/xYoWHH5TryBO9A/ivtwG9Tp4CMAJTNRGe39vOD6fp2NsZop4of60T2eGK8vzyLErjPnD5UsphBjh2FFwuJgDP1Pt5c8dudl1ihmCY7m8Vl4u36sNcbJb34b/eBst0CtJzFPzSFWFlvhp5ZwfaE9WsrXYT9gWIA6qGero8XtAkcmq8X+vDEAkh77VuEY4e5TO5AhPNWsIxWOtWEvf5MfvcGCWJvx3q4qpxIJ06AanqGIQTm9iSJBH0hdCdON4t2335AnPW7ANgslnORZlK9Ic6KRDCzFfH+f3RMFMdlQiBICpfFHco3t23x44EmKqXJ76XevX39gzAnjgxZ8I4AYUsjkmdmLsW66N8VNVKW0hFeiHdJ+1B4vvkeIuXmx06cPWMk0oSXivFShn43ZBMyaQDrrDFufa1Wn48XU+1q51QSAStDLcY56eHg9w7NxNcPesDM/CjMnlyQ6rnlMrJgsTjlUHyXGEW6EWOBCI983nl4LkqznhDIpkT4h7gXRLHfj4vSdJhQRAeAXZLkvQ68HvgRUEQqoEOEpsWQ2GuBdZOzs69E3tyN6u3+1ZTEywd6NpPaSmsXk108RJue6+Jb1yXwXRA0rpQn2xCnHg+2BMbEu3BKDNz4Jar58KqtxJ4qe4ziBvZHYEP+L8brh/okjoET3+5rcDGT1jImjGJyKPfx5M+mRqFnnSdgmpdBksK3aTvawD7YigtpQDYcYON9Q1+7tnjR3FSw/wsBRfk6jEVFfPGG/V8dk46H2ytQrLZCMns6AQgGOjJbrp6NSxdSluNk/QZk6GqimkWiYe212DVZbDjYCd3TbXii8QxlJby+0Od/KLDwGtL0/jYFSa/tBT2ulDZDIRd7j599YRjlJWowR6FpiaKZs+g7MUa3liRS5VbRC4IXNPUxIcRI0smxDnpjXAYOTOSmH1O2UhibjnpY97cInj+HSYvXcoDmVHu2djKomk6XGEvX6nN4ttz9DimT8amqeS6NxuYU5yOYFegOrwNcca0xMucxHynoYNbu05A6acQgDuna5n2TjPXjjcyc6qGWF2U/PkmFGkmxusNHBc76FSLFLlaYdICsPfso+1Wp1Ge64dtTd328/UFpbzyxi6uHW/ku2tewfDQtxGSLplz7PDz83LJba+Hl3ew0VBEzaEQL1+Zj1kt72PD3fY4hP30t/tBbXg0PKez4WHwqDR6xFjn4DKk4GnMyGdylpuJB+rAvnBAfdgdx+w7QPe4MBb6Gcz1eAQ8Ko0esTk4Iv0MJbcq6KelQ47D2QT2BaPu6/XTx7FofyUTrSqENTvYlF7C8y1yDAYtPzke4ZhbZEqhFlOdipAQ4fHFGSiHoZ/bNnYy1wT3z0g8B8EvoHJ3IFrMaBQyKC3ltbd3Ux+Lok7v8RIrtUmsy0xkad+5cR+1XREerOhCI5dxy6wpUFXF+utMXPpaPVNyNXxlpoNog4uo1cY39gVxtUn86eKsgfrtp59vL0kxb/QqewkxbZxj8GeSAnPU5bHAGAPMu+YUc9eUo3z9ozaeb4jSFoxy58WTKVYkki8X+v2ctGZTrpKfFjPS6kankhDNhgFtvAVFGA90MNGqZo0rys0LU2O81dzJlAwDf/Pp+YQdwh1e1HYtdHr7YL51oovz5uQDPR8el8zTswA3ClnirPlnZk7m0NYD5CQ9bgzA858p4ddvHSQnNw1cHRwyZLLpQCeTcsxcV2w6Y53n2+HVCyaMzOV+OG3+S+zpX4ExfgjMXPvwMCgt5Y2/11IeVZClV/P1hfYx0VfxTidfm2lDLRcSbvOjwLiefnQW6PxstYXTYX7SPrZyTZBC3GyLjVnfrHGJT06AW0pNlJ1hKBdAOCTj9g3VbF1ZmPAyGQXG7QsSZXUkwC/2dfDdldO5qaSO8WZlwgtomJgXR+MENT7Sc0yoFUquW3eU60tMfGGmhvOXzxyRXE8ut/GTCSUoq48hNbvAbsedN47n97qwqnVML7YM4E9PYnyp3z1eWRHjpSovi7O1GEqLqfYcoUGt5ce7XRwL+nlmQTqYVX145veC+MyyEoSjVSAIyAClD27a1cjnJlvpisQRC8aBq4FYXOKx3S4uKu47tqQBWx+YRe2+SpQygddqfMgsdu7MTXhWlIt+Hq6KkmvWo7bpCLlFguOKeeijVqY6jNxYZk79HJJlW7/yTJvEtL+cYF6xAexG0CX094/jXXzcFmXpOBvY9cOyDUpLmQOsK0kUGwJ6frn3BJ1hkdZAlD9clIOlfFJKDKFf2QR8wRhlU8zIJGOAdd5Odke1mNVyPv9mT2Lo/iSMRRb8saZTHhL5aRl31v7z74mLdnvPLt2hQzBlSt9rp9ps3Mj7jhKqvDH0ZgOfyYjxZGWQ+yLH+ZVlKvflSWxzRnj2WIiHp+oYV5AOGzcm8FLdZ+nSgfdwuXpkGA1PCrmlDRtZ1JJHYzDObYVqtAYtX84HbeXhlDxBs5XPv3oEucnIutYIN5WYuNASY3mmir9sreGCGYWs96u4QC+ypi7Ml0u13fo5mj+RA+4on5zR82tu5ceV/FE3gf0tfnJ0Mj5oifDLpRlsP9nJbbF6SmaU8v3DQR5amseTWxq4JlfFgYMnuebKueByEZckfns8zOWT0hM7rYcOESibzI9qJF6o9PCHeQZerguzry1EeY6J56arcIXj/KNB5PbZ2TyzvZFYaxtfXpyP4HCAy0UgKvHDI0EeWZaLbNOmbn1vd0aYX5oJLhcvbDnBbQvHdevnvWaR39WEMevV/F/0JIH8cSxJTxwLuLmihS/s9nMwv6H7GQWiEns6omxoizA9z4K68ggXzysGwGOwcO/79YRi8IKplmctU7g/P7EzGpXgsRqJ74wXkB0+PCpbmFSbw8FPje+zY3vqGXXjDdN+hrTh0fCMgd2/6VVTTIDSuorUMqTgebZRxk1pUSxHj6Tk+dEJCWNDLV9cXDh2+unf11HwvOFV8VZVB89oT47JuLDVGeHZkzF+p65GPXXsbOFnivHENFq+lC+hFCAOxKx2VB9torpgIq/UhfnWkryh+9oosieooEQZYY5NQbFRzpN1YIqEWJmvwqyUcRgDv9nTwrcn68jQyFLLmUrnyWt/ORlm+cR0MoIe7tntoyEY54llOQRcnZRbFMPCGKockyTkgjBiuUZVHguMMcas9ccwKATs2T1eiMd9MQ5EtVxrEU+L8bvjIdQyWJSmTMyhvdrsienocnlYlq7k8YogX1+UmxLj8YogXy3T8PM6ga8UwAP7/Hxvio5nq0N8ZWEuLQ3tbGqPcMQTY9WyvDPSz5OVQY6G5dySJbA4Xfkf0flZhfE/LtfaA82syFGdEcZ/hb7+l/t2tsr1H+qbx2BB5e7sOeXvDORyheO83xLhxpnZZyzXWo+Kk60e7i3RnrFc3z8UoC0cJ82i49YMiUKDfNSYIbOVO96uo1OUuDhTyf0Lc0clV9WJNkpNcta1RjgeV9Pq8vFGk8i9JVpuKVQPieER40g2Gxafe0B9eyjONZu7yDKqmGOCb07SpsQ4XdkXlTBkJL6ZflIRZF9nlEkmOZdNdDBLHhgVJiTW769Vuvj2ZC35OlliE3aUdv700SCPV4ZY4FDw+Pk55M6eukeSpNn0o7Mr6DxJpzwkJo3SQ+KwaSr3zLPywKEwQbMKQQfyyiZiRct4tcPDT/d18djCNMbl6kf8S+iAXyhHw5OiXli9mi/NmoGExOx0LcXzpibarEvNoy0t5U+vvAyX34QrFOOgxsHCeAfIBEq8W9keLqNVayI9Jw7tnWBPnKnb+tKrvKCayIOzM/tgljnr+NGqOxCPVOIVY5zwRnj0gI+HytMoW7cFHAvJdrjZrnSAzoXabkLs3N+N8cpRL+0C5M2e0t1X3dKlPLKklIcrKxEEgVnFMTpeeY38zz8Ax45iBwJtHXzpYz9LHSacx6sJW2xoSkvpOljBDW83cKRD5PtlZbBmTbe+59t7dHqb/z2wz+4uX2yH3OwwpfOmcnjVTpylUwlb9MTHFfPcu43subkI/rqzu70OWJwBiycmMXe8AfZEnmxzaSnF+zqYm6lFs3Ub8aKlHCbMlze3cswt8vzts5EJ7lHbwqaVC5H3T+7X3x6HaT9no4eE2mIh3NkyIg+JgA8sWcCG1DwL02yoqraBfdbY6WewXwVGwKO3W+k66h2zcUEdDeJT+FE3N8GysbMFqWwKcrsDVVpiI1oOyEtL4a9rKF66lPoTzTzTLOcLWfZB5T5y0sX3bluA9+ARvrq5jfummYhY1KhDXrx6HdWBKK+0w8RMExk51oFypCr3u3ZLr3f8g1Y3Gz9ZQEbSo2u4GEOV5cNtPwLMfynGGGMW2AdeK7RKvNYgo7cX2GAYkcZOrDo5okk9oE1dQM80tRzMKrTGDgLjxqMjcfyxLxInvaiYj5sC5KYpkDnMHKnu4g0vaA1xtBkOaHIhlZSwrsrDg/s8VN5adMb6yU7zsLR8ArNCbf8xnZ9VGP/jcq2gH50lcp2VGOfk+q/om3kM5bIDN2aPjVxXnpfMfXUqh8cZyHXXHDM6pQzDIMlJR4KpKS3lTzKh52jeUcpVmvw3UwjznQ3tmGQSFxYYuXFGGsiG9pQyD3EPW1yiyCrym88vSYR9jEJfkPAGPFVe56zjwTnpzM3QoEmRbHok5aBaT1ZrkIL8tFFjnCp/bq7E/KIQk+3qhFyD0Fm5IXGKpCFPt09Nh+I6TnhFFDKBqpYu1iiU3UnRfKEou9tDPDDHzrJc/WmQ/v10Q8nokqvZNXKWlaZDVcKldaIQ4MEDnXjjbu7Pz+tOdOL0hXkmmsWDsx19Mqf2JpVcwKFV4NAqeP2evomNPlVq4qcVrUwwJBJ4hRHo8Is8vbOd4+4If7goKyXmqazAJpUckyyceImTdO80K8esOZS4m3h+R5xgVKKp3ccFf6nh3mlWVidPzRgJTbKpQSagRuK5Q26+vqWN5ZNDfHO2Y8SJxx6al3wZt0JVSxdPHWnlW7PtXJinp6gkHY65hwYYgs62JJRjTVqVvDtx0nApkZhqcJ7FE9JA5hu0/j9FORYtTf7UCS1HQ1qljKAYO33DkdJpHsej56XzVG2YrZLIJLsaV1yD1NZFZ2uQEouKl6q86BU97/Mnio3c+WELv/3sfI7v9/H7w27+WOHhwKqLMdXWDH2zYdK1441k6P6335WzgeQyAY1SxiGnn1yjEot68IR/4ZiEUZn6nPeGjiBXZCW8EC4tMPCJZ7dR3eql2KLCpJIhfNxFrizCE4szAPjtbbNYs3YX35yV2CURYxK3Pb8TSzTEgixtIgToDOnGEjMUWKGq7fSNz9E5Okfn6BwNiwRB6NmMOENKH+N5XikbG7kAJlpVvPx/55HXXj8meHKZwIuX5IBq7Pp87zQbi7O13d9cZ0JXTcvmSk3XGEiVOARhVkaq9AuMDE0AACAASURBVNd9Sb5q1aoxueFYkiAIKx5++OGvqbW6WV+5egUEgxAIJFxBgkEIBonqDTS2eTH73N3XfB4fv6oW+eY0M/pIiJunOrjxrQYeKFGSRZi3gnq+Ok5gliHezUMgAB0diUR5Ke6DwdC33Lt+tDz92/eXYTQ8vepVoQC3zcllRZkDQ1cnmxqD/PpAB999p5pHswPk2vWjklsRDrEkV89kfMQCIT5sjfDaUTf1nUEW22XM1kZOL3e/+wjBIHZZDFwu6l1+Xm6ReHFXI52hGF8er2C8IjJq/YTbnbwd0rPhAhOXFplJD3oG7+swbOGy8yZwe2acxVawSSJCMHjW28KoecbA7ts9QQKdHgpl4rBsgWCQ7S0BzlONQO6x0M8obKE/jy4eIdTlZ64uOia2IIRDPFPp4/M50pj29T3RgEMRTyThTcGjiyTe8ZVv1iMEgxwVlfy50sOv9newttqLTRbj5mwZ5mgIXC6KVTFuL1SRqYzjbOvk9doA/1xswhYXB+9rqvIQbZY7ZGeMMery2YLxb5JrVpqaL37QwEM7O1hsiJAtJZ5zyBdgR72XfCEMLhfbmoPkKaLIxXB3m1MY6+r9LNOGIBjEJol8YpKdG9LifLpAxRUZclZOtHOZIZQYP4OJOWCq4EcRTvA8frCLr06z8JmMGCtzlf/zOj/Xt3Nynevbf5Fc/8t9OyfXoGUhGMQsRc7qvpWoY93z6pnKIQ8FUXR2/Et0/vCvftW8atWq5/p/+5+VPzudCtkozc4bNGTjwvZCRFmIbdflAhCIxPkwamJNl54f5aR18+y/JZ74hWXXOn686q7ULjtnQcjGv8JNPzN5ba+vkYhMwe7vLMP+xGN0J8k7g76qYxJ/8HTw7DVlnC909hy5dDq5h7hPnnsLe+zjeP3uRUjJMI8z0U/O6tW8csNChP5uVaN001dMLMMm+++0hRHzjIHda4yZOA9Vj8wW/ELCZfzfqZ9R2EJ/Hm1pKV9UyGD15jGxBZskYTZE+up7DPrqySljUn42GAOD8shKS9lyQ+KoMFZvJnD/SkIVR4lJEmmnvHp64SqS5bJglOvlAdJzzjxh4KjKY4Hx/7lcstJS/gq8VuPj0Qo3/7iihLZ9R1hz1Mthl8SCq0oQjh4FnQuVRYvYD6PGIzK+1AKmHvvSlpaSoxi+XE1hL7MWlaMYSbLI/2Kdn+vbObnO9e2/SK7/5b6dk+tc3/4dcg1CZ7QhIQiCDXgZKAROAtdLktSZol0MOJgs1kmSdNVw8AcL2QhLAtcVG4nb7MTicQQBfrDLyQfNjRxT7yZ5CBzAmLh7/rdTuUPN/TNsaA3qMcNUyeBx5QkunLgCqkYfttCbZsj8zJif2EwaC5cjSLhFnaP/DGmUIwvZiMUlZIKM08YV/H9AMkFg3VeXwSMbxxTXI8aw6FRAYMh2il7vjU6lQKcZ3H3/FDm0Cq6fMLqws3N09pBMEJJhMnLueWkvXpebe6bZKDAqOdrq646pVckEfNG+57Lvag2xYKEd2oe2r6Fo8ycLUMjPzdvn6Bydo3N0js7R/y90RiEbDz/88MPAEUmSbnj44YdzgItWrVr1QYp235AkKX/VqlW/XrVq1erT4faEbOhnfTVFyMYzzQouLTAQiMR4dGsLHe4AWinG40uz0Xs7/6Wu2X3q/0vc9BdbBZTh0Jj2VQgGKQt3jLyvZ4t+/j+1hX9nX0P+IDVNnUxRR4ZlC76uAMc6Q8yUB87ZQjCILBgc877+v/bOPEzOqsr/n9Pd2RMCSSchC2GHgGEPiAgBBJSgAXEDFBBFGLeIOjwzLqNT7W9wHEcFDeqIa5ABBIYlqGBAIEEgQIAATUIWyL7veye9nN8f57z0m6Y6lVS6qt9uzud56umqe99z3++573kruee999aEjb05rz8M3b5x7/snI9MUQ1dp2jigsoETB/diyrwNfHG4MLSygT++vIL3dN3Ks8vrOLxrAxs213Foxfa3bB5esIXz+yuydm3RuqqSf6vau3+yGgud2bfQFb5lXVdn9i10hW9l0FWqJRsXAWf5+wnAE8C/7mWbby3ZOHTw8LxLNuo3vsaRBw9kvyEH0qWiloWb6rnuePsVCe67q6RTs9/6HNP0i/M1K/0TsVD6JRvDDmbbwi0wa/diYfu2Brp17QX9tkcslMjX3v0Pp/row2HN4r3vn6xOBwxdbdbG4COP5De97L8JfYB5CzfzZJ1AT6Frv97sWF+/s02PNciIPL8clEHfOqyuzuxb6Arfsq6rM/sWusK3cuhqhb1NSAxS1WX+fjkwqJXjuovINKAB+IGq3t9agyJyLXAtQHXfahg/3iqqq2H1anYgVK3rDeNfZmB1NRevXm31T/oxTzwBSZnbAFBbC7lc8+eEPbVJ6mtri7dJH59PQzE2LTUUY1MOX7PSPxELJfe1R/+B1G3sBS89sVux0CDd6dL3IFj/esRCiXz9w8jVVNw8uW36J5+uYj9npY3QtcvPP+k/kEtfOZQTG9fT9akF1FfuC1MfhNWrubNqGN2kG8ye1CF96zC6OrNvoSt8y7quzuxb6ArfyqGrFQomJETkUWD/PFXfTn9QVRWR1hZ/H6iqS0TkEOAxEXlVVd/Id6Cq3gLcAnDQ4AOVceOswjMtM1fVcdTfHofLr8qfjcnl4LLLdrIB7AlgLpc/W7MnNkn9HXcUb1NIdzE2LTUUY1MOX7PSPxELJfe12+FHUHfXVJ7qDe+9/EMFY6F+Uz1Vsi/03hKxUCJfK9qyf7KafQ9dJWuj55FHMubuqayta6TL0WeyY+k2GHsyzJrFspfW8JXj+sFRMUMi822ErvZvMytthK7wLXSFb+XUVVNDPgomJFT13NbqRGSFiAxW1WUiMhjI+yPfqrrE/74pIk8AJwB5ExJpmvKUTV9Vx5iKzYVMgyBoZyoqBEX5VP0I5u/G8fVNSpeusQlpEGSZLxy7HwCrtjVw15yNnLWxjvtfXcfdczbxtRP6t7O6IAiCIAg6Gnu7qeWBwBG5XO4fNTU1XwYW5nK5R9LHiMh+NTU1msvlGkWkGqgBxudyuVWttfvWppY9+5x00PHn8vzijRzfzX7X/u+Lt3Je7x2davO6t2koxqZlfTttZFhQd1b6J2KhLL5OfXMtz65p4KvDtWAsrFy/jY1btnN446aIhSzHQr5jMrRhUugqTxvdttfxjZc2s23VGobLDr50WDf6NWZkQ8pO2ued3rfQFb5lXVdn9i10hW9l0FWqTS1/ANwlIlcDC4BPeEJhFPB5Vf0ccBTwKxFpAiqwPSRm7KrRZFPLAwYfeM2LW6sY2b8bV/xjPVcO785qGmPzut3RHZtaRiwkGtozFl5aA9RB//4FY6FB66jadxBUbYhYKJWvbdk/WZ0OGLrK0kYV8OFDGviPq87odL5lWldn9i10hW9Z19WZfQtd4Vs5dLXCXiUkVHUNcE6e8mnA5/z908AxxZ5jYM9KPjWiL5ccdjgfvfEx/nDeEFhYtOQgCMpIQxNU0trWMjtTr9ClqqLEioIgaCtuOjPf9lJBEARBEAS7z14t2SgVyZKNLj37nHT+OWMZ1aOeirptXFbdQI/6Opv2EVOzMztNf5e6s9I/EQtl8fWxOWt4fX09XzqAgrGwaO1W2L6D4Ts2RixkORbyHZOh6YChq4O1EbrCt9AVvnUUXZ3Zt9AVvpVBV6mWbJSEZMnGoMEHX9OvXx/ov8/OUz9ianZh3bFkI2Ih0dCOsVD39Eq66+bdW7KxfStdDhwO9asjFkrlayzZCF1ZayN0hW+hK3zrKLo6s2+hK3wrh65WyPT86EaE6u6V7S0jCIIiqWtUuuf9vZy3s6NJqarM9FdSEARBEARBEARtSKaXbFT22u+kL3/oAgbp9rdP/Yip2Zmdpr9L3Vnpn4iFsvg68fU1rK9r4NNDKwrGwtw1W9mnaQeDtm2IWMhyLOQ7JkPTAUNXB2sjdIVvoSt86yi6OrNvoSt8K4OuDrlko9fgw64ZsH9/6FW189SPmJpdWHcs2YhYSDS055KNR5fSo2HH7i3Z2LSZLoccDBuXRSyUytdYshG6stZG6ArfQlf41lF0dWbfQlf4Vg5drSCqu7cDfl5jkY8DOeynPU/xX9fId9z5wE+BSuA3qvqDAu2OBcYOGTD4mkX33U2FiA1o1qyxA2prYeTIncvAPk+ebHXJ57TNmWfufHwxNkl9oqEYm0K6i7EpRf+Uwtes9E/EQll8/dSD89m+aQv3fGD/grEwcckOjh7en8MaN0UslMrXtuyffL4U+zkrbYSu8C3rujqzb6ErfMu6rs7sW+gK38qgS0aMeEFVR9GCvZ0hUQt8BPhVaweISCXwc+A8YDHwvIhMVNUZrdkkMyRGDRlyTUV1tRWmMy3xJLSw7pghEbGQaGjHWNj258X0qq+zL6YCsdCwbiNdDjsEVi+OWCiVrzFDInRlrY3QFb6FrvCto+jqzL6FrvCtHLpaYa92kFPVmao6q8BhpwBzVfVNVd0B3AlctDfnDYKgY7BhRyP70Lhbx9Y3EZtaBkEQBEEQBME7iHLsITEUWJT6vBh4d2sHi8i1wLUAw3v0gPHjraK6Glavtve1tfY+XZYc88QTzWUtbXK5nY8vxiapTzQUY1NIdzE2peifUvialf6JWCiLr+du7M/2Netg/LMFY6Gh6gCqpk2CNcsiFkrla1v2Tz5dxX7OShuhK3zLuq7O7FvoCt+yrqsz+xa6wrdy6GqFggkJEXkU2D9P1bdV9YFC9nuKqt4C3AIwasgQZdw4q0hP/bjjDrjssvzTQ3I5q8tnk8vlnz6yJzZJfaKhGJtCuouxKUX/lMLXrPRPxEJZfP3mrFnceOtkuPKSgrHQ9PoGKt53HCydH7FQKl/bsn+yOh0wdHWsNkJX+Ba6wreOoqsz+xa6wrdy6KqpIR8FExKqem6hYwqwBDgg9XmYlwVBELyFqiLS3iqCIAiCIAiCICgXlblcbq8bqampuQqYlMvlluapWw7kampqJtbU1GwFfgZ8P5fLrWqtPREZW1NTc32v7t1P+spFF+X/PdM+ffL/5unatVaXz6Z3750/F2OTri/WppDuYmxK0T+l8DUr/ROxUDZfpy7fxnsGdi0YC9NXbmNEl3p6bFgXsZDlWMh3TIZ+4zp0dbA2Qlf4FrrCt46iqzP7FrrCtzLoqrn55mW5XO6WlmP/vdpDQkQuBsYDA4C/iMh0Vf2AiAzBft7zAlVtEJEvA3/Dfvbzd6r62q7aTf/KBv37W2F66kfspl9Yd/zKRsRCoqG9Y2FTLdqvH1IgFppWrKfi8MNg0byIhVL5Gr+yEbqy1kboCt9CV/jWUXR1Zt9CV/hWDl2tIKraamV7ISJjgbGHVVdfM+cB36Yi/XumtbUwcmT+3zydPNnq8tmceebOxxdjk9QnGoqxKaS7GJtS9E8pfM1K/0QslM3Xnz25gC+dPpzK6updxsJv36jjY8ftT9/N6yMWSuVrW/ZPPl+K/ZyVNkJX+JZ1XZ3Zt9AVvmVdV2f2LXSFb2XQJSNGvKCqo2hBOX5lY4+JGRJF2JSif0rha1b6J2KhbL5WbnqV+n37UVkgFnTZOiqOOBwWvBmxUCpfY4ZE6MpaG6ErfAtd4VtH0dWZfQtd4Vs5dLVCRas1QRAEbUAXlMbdmIjVpCCxq2UQBEEQBEEQvGNok00t25rY1LIIm1L0Tyl8zUr/RCyUzdfpK7cyYr+udN++bZexMG3FNo7vtoMu69dGLGQ5FvIdk6ENk0JXB2sjdIVvoSt86yi6OrNvoSt8K4OukmxqWSpiyUYRNqXon1L4mpX+iVgom69dNkynft/9CsZC05J1VBx5BLw5N2KhVL7Gko3QlbU2Qlf4FrrCt46iqzP7FrrCt3LoaoW9WrIhIh8XkddEpElE3rZBReq4+SLyqohMF5Fpe3POIAg6FlW7u2QDJVZsBEEQBEEQBME7h71aslFTU6PAncCxwKRcLre0leO+CrxXVX+Sb5pGS2LJRhE2peifUvialf6JWCibrzNXbWNo327sU1+3y1h4bvk2Tu5RT+XaWLKR6VjId0yGpgOGrg7WRugK30JX+NZRdHVm30JX+FYGXSVZsqGqMz2BsDfN5Gs3lmzsqU0p+qcUvmalfyIWyuZr1YYXaOx7fMFYaOqxFjniCJg7J2KhVL7Gko3QlbU2Qlf4FrrCt46iqzP7FrrCt3LoaoVy/cqGApNE5AURubZM5wyCIANUotQ3FV6zoUBFrNkIgiAIgiAIgncMBWdIiMijwP55qr6tqg/s5nlOV9UlIjIQeEREXlfVKa2c71rgWoDhPXrA+PFWUV0Nq1fb+9pae58uS4554onmspY2udzOxxdjk9QnGoqxKaS7GJtS9E8pfM1K/0QslM3XLkt30LhhKTzUfZex0NT1MGTG32BNxELJfG3L/smnq9jPWWkjdIVvWdfVmX0LXeFb1nV1Zt9CV/hWDl2tUDAhoarnFjpmN9pY4n9Xish9wClA3oSEqt4C3AIwasgQZdw4q0hP/bjjDrjssvzTQ3I5q8tnk8vlnz6yJzZJfaKhGJtCuouxKUX/lMLXrPRPxELZfK287SHqx7wPTjt217Hw0hrk0tMiFkrpa1v2T1anA4aujtVG6ArfQlf41lF0dWbfQlf4Vg5dNTXkY682tUyoqam5ilY2tRSRXjU1Nd1zudwOEekF1AB353K5ua21F5taFmFTiv4pha9Z6Z+IhbL5unDdVrr17MH+uutNLacu28Z7etZHLGQ9FvIdk6ENk0JXB2sjdIVvoSt86yi6OrNvoSt8K4OukmxqKSIXA+OBAcBfRGS6qn5ARIYAv1HVC4BBwH2+8WUVcLuqPryrdmNTyyJsStE/pfA1K/0TsVC+TS3XTKXxxOMKx0LPNRELHSEWWh7TFp+z0kboCt+yrqsz+xa6wres6+rMvoWu8K0culphb39l4z7gvjzlS4EL/P2bwHF7c54gCDouVSj1hfe0DIIgCIIgCILgHUabLNloa2LJRhE2peifUvialf6JWCibr8vWb6Ohew+Gy/ZdxkIs2eggsZDvmAxNBwxdHayN0BW+ha7wraPo6sy+ha7wrQy6SrJko1TEko0ibErRP6XwNSv9E7FQNl8r16xi68hjC8dCLNnoGLHQ8pi2+JyVNkJX+JZ1XZ3Zt9AVvmVdV2f2LXSFb+XQ1QoVrdYEQRC0AV1QGpraW0UQBEEQBEEQBFlDVLO3uFtExgJjgSuAxV68Aejr77sA9S3KkmOqvS6fzeoWxxdjk9R32QubQrqLsSlF/5TC16z0T8RC+/ualf6JWCiuf/L5UuznrLQRusK3rOtqizZCV/u3mZU2Qlf4Frrar413oq4DVXVAi/JsJiQSRGQa8CKAql4rIsmakxOBF1uUJce0aqOqo9LHF2OTqj+xWJtCuouxKUX/lMLXrPRPxEL7+5qV/olYKLp/8vlS1OestBG6wres6+rMvoWu8C3rujqzb6ErfCuHLlohk3tItODBPO9PTL1/kLfTmk1rx++pzYMtNBRjU0h3MTal6J+29jUr/dPa8XtqE7GwZzYRC7u26Six0JquvfmclTZCV/nbCF3lbyN0tX+bWWkjdJW/jdDV/m1mpY13mq78qGpmX8C0PSnvqDZZ0JBlmyxoCF+zYZMFDeFrvOIVr3jFK17xile84tU2r6xvannLHpZ3VJssaMiyTRY0hK/ZsMmChvA1CIIgCIIgCNqATO8hEQRBEARBEARBEARB5yTrMySCIAiCIAiCIAiCIOiEREIiCIIgCIIgCIIgCIKy0+4JCRE5X0RmichcEflGnrrZIrJJRFaLyLMiclDKZrWIrBCRV0Tk7yJyYIv2bhMRFZFRLc613O1eE5HbReR3IrLS6x4XkZe8zUleXisiP/M2XxGRE91mg4jUicirIvK0iByXaqvWz3myiDSIyMdSdfNEZLqff7KIHODnfd19XeJ1/+zlM1LHJhrGeN1i17DUNby/hc11KQ3/lKqb57ZJu91F5Dn3ZZP30Wsico2Xv+x2ta7hWRE50uuWuIYVfh2OSNm8JiI1IvJRvxanpeoWiciq5Dp4f1X6OVanrsMFXtdDRNaJyBY//0Epm8Wu+61YSNW9JCLTZOdYSMpfSPXV7SIyP3UdtrY4/3zvn1XubxILSfkCt0nHQ1I33c+TxEK6fJbsHA/7isj9rqFORN4Ukc94+T2ub637nGjY1/ukLqXtuBY2M0XksykNSd3C1Hkm+3Wd7m1sEJFGEVkmIt/08uS13fviFRG52MsWiMg2t5knIhe2sNkoIj92DV9Jlc9NnWeyiHzN+2OGWHy94p8/43UzXNsmsXg6KGWzzOtelebvhaSuVkSelJ1jIalb6HYzxGLhOj9+tojMkeZ4/B8vf01EpsjO3wvXicV1+p48zs9zXcou6YOPtSifISL1bj/Z7Q70fm4UkSYRWZr6juzn/dPgNm+41i+KyCPuT71YXL7mOj+bstksIsPFYunXbjPH/x4j9h0403Ul99sPva2ZYt+LUpp/HYIgCIIgCIJOT3vuqAlUAm8AhwBdgZeBo1vUfQfbWO1l4J+Bu1I25wGvAEcDX2hR1w/Y7HajUu29D5gO1LrdQGA09vN2a4Ev+PmPBpZ5+XzgIUCAU4Fn3eYqYIYfPyZVfqK3Xwk8BvwV+JjXjQbqgOFuNxAY7DbfAm4EZgPvBdYBp/hxHwW2uK5TgRfd5jTgALf5p6Tcbfp4+VTX8Dm32Rd4HXgz1QcC9HYN/+2+nO99sp+392VghZ//UuBPbnM2sI/b/DApd5suwPPAS65jlNsc7mXTvL2BfvzXgbnAq6nrMN/f3wPMAf6cnD9l8yjwV//8hRZ1dwFrkvOnyh8ENqT8G+jXegI7x0Fy/vl+3paxMB+o9muxX4t4SOpaxkJSvi8wg53jYQJwL/Bf2H1xqF+HP/o1vAB42G0TDROA/wT2c5uPpco/5213B6akNEwAxvn5D/X2Bqbuz2/59VwOnOAaunrdh4DtwIGJBi8/DejvNp9OylP39HLgqUSDlyd9sNLbOxaYB/RwDa9j99oA7J6YB1wH/I9f218CE1M2ZwP/5zZfaFHXB1iFfReMAoZ63UgsHu9zu9HYPdwT+DUwEzgMuBDY4eUfAlZ7+anYd1Gtn78ai8nP+nUYmWqvq/flE8DXUuX9ga3A1V6W3BNT/NjRrqUpdR1+6P1wFtAA/BSLgfVAjdvcCqz144dg34u/x74LlmP34O3Yd8c3/LhvAAuB8/xzb9d4ml+/Sn89A5zV3rszxyte8YpXvOIVr3jFq2O+2nuGxCnAXFV9U1V3AHcCF6XrgNOx/zzfiQ2o3p+yeQS4w22mAiOSOuC72AC2T4v2zgduBv4XuEhVV6rqFGyAADawBuiLDVTWetmtakzFBlBzsEFCkx8/FRjWoq1x2MBoJYDXjQY2qupCL1upqstU9UVAgW7Y4OcQbBA9zdt6v5cPdQ29gGWq+rSqLvK6lcAgbwtV3YQNGp/3uvVe90nvm1e9vZXu22bX0BdLJHR3Xza4houwgY66/TnAFlV9HBsMdfE2h3lbeNmB2KCoznVtBq7BBlcVVqQrRWQY8EH3pSp1HZZ63dnYgIvk/Cmb77e8Fqm6CmwAWgeQKt+CJRvWJdeCZtJxsDRVPoa3x0Kl2z+dtJVoSNntFAspPgncm8QDdr1GY9esD1Dvfq3H7oXfYtdhgqqudw39vG++parr/F76O5aoGu02AJ/HkkUrscHlaKDRz/+Gt5fWp9g99Yaffy12ncEG+vNVdUHSDyIyWFWfBk5ym4kt+uAcbMB9e4t++CSWDJijqguwuK/CEgiCxeFSbFC83usuBG5zPx7wvklsnsTuo6V+HQan6v4Du6+T+MTrrsUSG13cbhCWTNnq/b8Q+AhwDLDOy8diSaaPeB/0B15R1cdVdTUw2a/BMOCoVHtfxAb1vb0uKb8EeA5LcKTj8SgsgfUklowjdR0uwhIPx7hP56dicLl/54zHvi9Q1aXu76+x61kHHAFMAg7GklQATwPV/h2Lqm52jerXo6v3cRcsSRkEQRAEQRAEe0xV4UNKylBgUerzYuDdLepO9b9JXR07D2aS8quB14AtInIiNhC4H5tFkW7vCP/8YWAfEXlJVR/2spXA5SIyDvsP/LleXpVH51Ds6WjC1diTc1I2F2MDxZNT5YcAlSLyBDbg/Kmq3up1N2MDg1OwwdslqpoMsg9zn55toWGZT6U+ARvMvKVBRN6NzUQ4neaBPN4H/YAPAMNF5EZVvVVEKoHLsFkBddiA7xJrSqZjg55fqeqz3v4GYICITHJ9P8euxUPe1gt+rkWqeqOIXOR2ldhsjh7e5z8VkRz29P9fsATGH0RkMc3X4Sbs6fgKAFVt8PP/wm2SxFP6WtwE/A4bbK7EBoB4+b94n/QSkeSJbw4bcJ0AfEKalxAlcaBY3LxbRPqo6i1+HUYAk0REvX9uSWk4B3gcOAi4PqVRsWs9FJiRiof7sCf478IGm1dhA+JvAFdiybmLgSEiMlFVt2ADy17A7315wAvY7JckKfJ7X57QH4uHk7GZGKuwWS8DRORq7Gn5jS3i8SvYoP9Vdo7HY7CkUMJb8YjNIrmDt98Tn8USIL9k53viCOxpfZWIvODX5UdYEqAOG3xP8P65BIu1n2CJiIdV9WERWYclXhYC24BJqjpJRG724za5xkrXPRRAVZeIyI+AH2MzH7YA3/O2zhCR/thMlVexWUuNwHovPwAYTvOAfCHwXq/bhs1kafQ+qAVuEJF3YbOdqvyaLQTGus3RWCwdiSV4rvRrkST1lmKJMk1dh0GqukxE9seSWYO8vJu3D3adqwBE5BRvb6q3OYDm5EZPVV3m7/sBXUTkXixR8Sg2e+IZEXkcu84C3KyqMwmCIAiCIAiCImjvhERbcQT2H/WbsMHjT7CB3Bl5jq3CBmXfx5IFvxaRY7yuL/AjnggXSAAACjtJREFUVf2xiLwHmyL/wUInF5GzscHX6aniwcBVqtrUYol1JTYQ/6D/fUZEpqrqbGwAegjwcWz69yMi8iQ2ID0J+KGqbmxx7t7Yk/ffAJcnGrz8YSCnqhtaaOiBPe39DPBIWoOIfA9b1nIUNh38F8Bxqnq8iMwAjheRkapa6201ed2+2FPVemyZSaMnhqZgCZiRycm97kn/2BtbanAb8ICqviAinwUWq+rRfh3uw54M17Xo+p7Aarc5y/2+HJuK/wNsevo12AD4crc5HVjpNpXYoO0sbOA+BZuJMgYb/H4Emw7/R9d/OvArL7tBRF73Nj+nqg+JyEC/Zj1ojofuNCdAfkDzbIvTfTD8W2wAfzE2Zf5F130vNpCswGLmm9hgcxy2HKAOS1J8BxsYjgCuVtVnReT/sKUAlwJ/c5vrsTj6Vz9/BZYEuA8bWL+ADaK/k4rHD2IzQA7y/kjisQ7YH0u07ISIdMVmL/wZuIHmeOzqPn44zz3RFUsyHIElDp7FEkgHY7F4A5YsmorN/JiPLUUaA9zk17zCPx+MzaK4W0R+4T5ehCVIXsKWkfzI+xIR2c/rH8Nmbwg28+m7WCJikvfBy1jC70/Y/TbJ+2UKlnTA7Sd43Rb34QxsJtYaEfkv4B+ufypwJrAkdZ79/fx/w5KS3xGRqVgCYbr3xWjgCRHZp+V3gdPq7ziLyGDsO22rX4MrvL+75Tm8yl/XY0mTPwFX+b4WR9E88+URETlDVZ/M00YQBEEQBEEQ7JL2TkgswQZDCcO8LF2X/B2GPZXrjj3dTTgTOB5bo30oNiAZiQ0q+mID3onAt72dediAZzC2Nn0YlqBYha29vgvAnwR2x54UNrSis5u/fgOMUdU1qWN6AHf6wKsauEBEGrCn0Jv9yfYWEZkCHCci87D9I+5U1XsBvOxd2GBshmtPa1iBDY4ewwZaY3zg08XLm4DPi8jnUxoUS8Q8pap3+HmmAMdhg7zPYAPns/3c87DB7nPYLJEFwPk+GO+LTa8HSwIMAH6uqtu9rI/bVmIDt57ARBG5EHta/az36zHYAG6siMzHnl43iMhtqnq5iPTBZibshyUDeojI//r53+823bGB4xl+Pb+GDTT39zLBBmsnAVvFNqoc6Np+7+eZjcXL1djSHsESFt2x6etLRGQJzTMZTvHrMB1sir2IPI0lCU5L4sFnJ5zs+ka4hmuxGJqDLc841p/o/wNLqp3h1wEs8TAPEE84LMHuhWSWQT9s+c6zInIsNqvoNX8t9vJR7sdYj4s6bGbFC1hsPernScfC9dheHiuAFR6PI7B7ZwXNM06g+Z4Y47b/zc73xBh8dkSee6IXsFBV53l/zff+XCUiV2LLtU5T1dtEZCOWcKhzHfdiMxf6A4+p6ipvY5b38ZHYd8RibMbCo36+/bDvhZ9639Zj8djo/TcbW0pxs4i85v00278X6tyf/4clNman+uCXqvpdvw6TsRlQa9yf34rIv/m5L/Pr8QvgWlU9yWfkfNBj4iQswXccFreTVVVFJFk2kdyTKzzRsBz7Lkpma2zH7ilongXxF+x78Aa3OdH7DSxJUyUi41V1HJac2qa2/A0Rud/7pR8wNVmSJSIPAe/BlpMEQRAEQRAEwR7R3ntIPA8cLiIH+xPUS7FBwlt12Frrz3jdduyJfmJzMnAF8Glfb/08lpA4GXvauhB7Knoh9mTwcGwTtvd5e1P8uDf9nPXYFHtE5ChswLAG2AhcKcapwAaf2jwEm7J9hT9RTjNbVQ9S1YOwKeJfVNX7sSehPUWkSkR6YkscZmJTxJf5+RCRQdhg6qtef0NLDV62GHvyfIXPcBBva6aq9m+pARukP4MNPtIalvssh4XYUo7zsEHOUTQvTXkIG9C+jm2K+BTQV0ROwDYenQ9ME5EBIrKvqm7AEg612HKDqf53Lrac5hw/z1IsMXC0a30RmOVJgqOwwdFQbID8FJaAeRD4s6oOc5t/wwaTo9T2xPimqg5V1Uo/z1+xQdPZqjrIbXLYbInLRaTa+3ul98EYbLbEBo+DLZ4YmYjF4/uxQd4mfD8CETkSm5lzg1+LXmJLOw7GkjszsJj7GvakH4+H47FlGz2xDR0X+XnP8dd8LK4X+DkmAp9ym1OxxMJ8nyVyLzYz5nlVXQ4sEpEjXcOvsGU192D7SczCnvyf7tdhNs3xCKn9M1Lx+CY2mL6H/PfE1VhisOU9cRnwpVbuiQHA9lQ8HgQc6O8XYptHznQNiY6HsCTcOX59ngNOFZGeHo9fBMb798JCbIA/3Pvxr1gS4kIscXmqt3eWt7cQ+15IZiCsxOL9do/HnlgC8xkseXR76p5sFJHhfo02YrNj8D4c6NdhNHZv3es6n/ZDnsOSBH/GkmHJtZiLLa0Bu3+U5u+sid4PU7AE0cM+6wMsGQfwCW/vVlW9J2XzVez75kbs3nqZ5oTwscBmERngn9+Hxe9C4Ey/Vl2wZE8s2QiCIAiCIAiKQlRbneFbHgH2pPombED6O1W9QWzZwDSad40fjCUj3sAGteuwAc4w7GnvXOw/3wuwDd7eag8baM3BBrANXjcQWy++AhuEDcCSFdXeXrJHxVZsKUi1n38rlrSYgA1sLsJmQtRjAwx122FuswL4d2xvhFe8rbP8/Ml5nnLd12P/sR9G80ZxtdgT01f9+KHuQxM2oL3C+2If17AUe/o7KGUD9ksF3/HzXeh1/Wn+NYTnsMHph7CnrAe4r6tcx0HY09ZKmje164FtjHcRNt2+R+r4fbHkwBYs6XWXqn7Pn3zfjQ3iKrGETlPqOkxQ1Yki8mlskLTIffmF23fHBtsnY0//pwKPus0L2MyYmXgsqOq7AXygfj02YJsDPOg2Z2ExUud98QA2COyGDV43uLbJ7tvHvT8P8H5YiiU5LsQGdsO9b2Z5exU0J3OqsM0cD8eWKIymefPGhdh6/r5YPHwfi7FDvH+WuK9LsZkbXd0X8fcTsJk9j2BP37d4m/tgibjE5k0smfJXLB5/ic3uGYrFzWIs5h5zu0XY7I8Bfq7n/PO/u7bve9vdXcMN7tM2LKZxPT9ObDxJhYg84xq+7lpvwu7pJmzg2xPf3NH9WIvdN3/EEkCX0rzEYRaWHBiA7f8xDIuv2Vj8LMDi5hLs/nnJr9Vs7HvhJK+r9uux2Nsc4e1XuF0jNkOgAouNeixZNDLVB2f45z5et9n74D+xJFJ/t/s6dv9uxwb79f7qhcVClffjOOzaT8Huq2SmzzIsdg/GvuOSX3Jp9Gswwc+3j2ur8vbXYrHQ5O1VeFsPu2+nYPf+Amz2Rs6vRZP71ejlo13Hw6r6dYIgCIIgCIKgCNo9IREEQRAEQRAEQRAEwTuP9l6yEQRBEARBEARBEATBO5BISARBEARBEARBEARBUHYiIREEQRAEQRAEQRAEQdmJhEQQBEEQBEEQBEEQBGUnEhJBEARBEARBEARBEJSdSEgEQRAEQRAEQRAEQVB2IiERBEEQBEEQBEEQBEHZ+f/I7HTrDqWcJwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1080x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "scNzRe5Th3zg"
      },
      "source": [
        "data_pad = pad_sequences(data, maxlen=5000, truncating='post',padding=\"post\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 160
        },
        "id": "87tbADtwij0Y",
        "outputId": "d4a84776-a36d-4716-8313-a9fad7b581a0"
      },
      "source": [
        "ecg_plot.plot_1(data_pad[1]*(1/1000), sample_rate=500, title = 'MI')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 160
        },
        "id": "lE1fCNsKishy",
        "outputId": "ac1bdd58-5871-4106-920b-e2b9716ffebf"
      },
      "source": [
        "\r\n",
        "ecg_plot.plot_1(X_val[5].T[1]*(1/1000), sample_rate=500, title = 'MI')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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0lg46RaysMc3rWprvMueST3KLMMgyBg6fxOv9VnwUMSgAG4tuLRVFCCMjACISEqbIULp7MrqFhManAYcIWIXI81EvmJ4UANDO83OsQxofV288Ca+5Uc/14mLCH988goFF5enXoV47xLZzFiQkAkISkEwkJF3dgCk1CQmZzeptGunUQSyfzQbMyL/myCcPeyCUlSVN/+qQFQIY3i5bk9epno1WK8hshmyxAubUbJx0BeLXUpcbNA8Sku/sGMYnxny4vLkiaR3GlpdJItDXBySTrcXWmd7zbCAbxzhCX9xaAJxK8Oy3AD4dFTYDWJKMk0tIisDGPB57vernu6l7wqV5/tdXBungbb8Ih31BiYKnO3Jr43zz5dnGt/9kJw0dPpk1vrTCueDkEpKir8PoOElW6P+2dxF1cglJpnfNB9o7aPUtL2TPRr6WJuTL2RH2XHAWAd+Q1UOX37WTDvRM0bUbd1Acsmzjb/5+MKt8s9mnd3x77Ogc5Z1p2PiZ/9tJ+7omNc/ffPuLZHH50+KbCf/pQD/d9qxWQrKva5I+oyMFyFRC8uihAbr5qRNxz1Mdf9m+nSJXEpK13w1JQNJcS8+9bQu5/KJ+mhjOlps2aeURGY5n98nTdM6tW9Lie/HUGH3plkeSpr97m5nu2R6/55oZW6m0syQr9L8vnI7j8ItS8nYK8f3Hw0do84ncS0i+cO8u2tkxnvD5bG3yzp/uogGLW7eeolFUEpIUsBTAcFT4TCiOgyN96Bz/U4g08oYdHRN4bdI/fzad5VAUglFgkPktJFkF8frMOoKSglKTusTx2s0M9oCMxsqSfJtx1uN3+3rzbcJZB1khGAQGu0dEY5kh5++764g15++YDZc+MTAv72Fg6Ld4wmtXplKFGcQuhdmQkGRybH6+8cDunjnn2d05mfhhhpXHkPr+hLH4tA/t74cnkP7tGunKfJQs/MBNtdwKEWQdacWvds9tPp+vXsrS7BQCAwpIQQKWrY0zY6wFwCYiOl/n2SYAPyGi/aHwTgA3EdERnbTXA7geAFaUl28YvPHGyEOLBWhqSj+8Zw9w5ZXFw1cMNuaabxaOdwfOx+9MPVhjOxN+/oi0AMtPHsaVF7UAAB6UFqHVNYGr6pPzFUyZk4XzaKOdDPj34Dr8wn0MrY3lifPn2r55LPN88CkE3Ouswzdrp3GP2IxvmUazOlYKscw54YuKmyYDnpab8O/T7dhYeyG+bRotDBuLZH5oqfogBsoOAwDabQH8v8q3YGtpe2GW+SxYSyWLFZdUvQd2mNR6n8e1NF9lng++3oZl+Iq4Bl80TKDTJ+B/qyegQZZtbPFfEh436fCdtAWxtXoVbjCNJLWvxX8JBtxbZn9/DtbSz7hX4avlVnxLXIXnSk9jiXUMF1ddjS2lp7CASWnX4Z+lheihMtzpOBZ+vk+uwe+mSvHo4ilN+uj5KRn/1d5z8Vy5GRVMCZf30Xdci3aqwF2mwXB6ImBV4JK48acQIFiz2856/aan9DDWzLx/zx60XHpDSmWc6Qd6ddLm34Djpa+hfO+utNbSC6reiwOlJ1DD5KRjpdW3AZ1lx2BiFM7/tqr34NnS01jCxDmPZ7fFjrdVvQftZcfmXKeb5Xo8Py7juiUK7GTCBwx2HLNJ6K1ZhGuN1nD6jbUXQmDAN42jcf2gz70FrVUfQH/ZkYQ2wmJBoHEB7pKW44emIY0NPxGX4WbH8VnX1hm+/wq24hqDDR+yd89pbZ55Hu6PUfZJBBhj+u117pX4Qvk0rjI4UqvTKL6rAhfgQVM3WqN+c6UzB7Hbbz9KRBcjU2TjGAdxCUlu+IrBxlzzzcJx1S/iJSR/OtBPO27dGA7/aFM7bdpyRDd/1mycb7482tg94aTrHz5MXYdOZIUv7XAuOPPIJ8kK/fLxl4mIS0gy4ouKm3D46NFDA0SdXEKSqYRk946j9LkHD2XPRr6WxvG9vv84/X5fL33ol/vo9ufa53UtTZuzCPi6xp30nrv30C93dNHP/nIg/EhRlIxt3NY+Hvc8U2nBru1H6QsPvZI4fRIJycqbNkXKlsL70rHxU/fspP3dU/SxB/bT4X4rUWcnbbhzO004fGnxzYT1JCR7zZP02RQlJMcGbXT/ru44/nO+9wK5Z2QQIfseOThAtzytlZDIskItN8dLSO7d0ZX1dtbjs7j8tP72F8N8qUpIdOUOoedtt24mT0BMap/75Gkan2m/qDSa22WSjJU1t2yigBh1W1VnZ+Tmiqj8056gKjVJwuc40U5v+v7WhDbPFn7u+Ah99ZaH6e5tZro7tP7/7smDdMfz7Zr0ehISKdQPxNMdtOrm+Hb2BiQNhy8oqf02xoY7n9efxxNJSF7IsoRkRkIbjX+7dxft6tDeIDTr+6L49H5z5VNCki0nnsnwHICvM8Yeh+q800FECV22cieeSD1Pvm3MNd9sHMEg0N8PyBEnnsrENMSGRvzh6VfQUmPC9Lgbnkq5uMqconOlfNi4r30aF5UTZLsvv3U4j2WeDz5FITCfFxHnYdyJZ1p8UXEBl4jSKR8gi+BOPNPgBMJxk1MOLCRDJE2hlfksWEtf7bPiXy40oa8aONQxgqGyMqyYi/18ftA8JyJIFiu8U34YgkFIU1Mw+NV167UpPx5qn8Z9Vy7OyMavPNyDgY/Ux9dzBmUmlwvMM4vjwhTaeU6OFNOwEZIIDA+jTgnC0TMAVPjBZAnU2wtUGNN34jkR78STRjxgpaWzzk8z+ccG3DjZ5wJinH4SEVh3yBFlqLw0MRHnxFNWQrKDqDgA8IxbgHKW1XbWawd3RzeqBVLjs+TEM+yEM4l9A8NTGBzx4kMtVZo0TFFAPd1AqSFpX2QAFLMZMAqR/LIEpacXqI44Jn6xy4lLl5RjRawzyBg+stnA0nTiqYy6IJSXwWCzQpQJMBPI4wXzylo+a8jyqDanUD8gqzXSH6JsfPPtL8L8b61hDpIUyDZ7XL8RrTagQZi9nWbK7HYBo9l14umbsAAVMf1WDAIjZwBmj8+vF47iE4JBUMxvLt08sXWm9zwLyMoHDMbYYwCuBNDEGDsD4AcATABARL8BsBnAhwD0APAC+OJsfET0PIDnL25u/gra2iIPzGZkFH7ssczyzzdfEdg4fOQUlufSvlk4WMkYsKoFsI+GnytT/ZCPHYLtvFq4YUBZYwl85CnoOpxz/jzaONp9Ghe3NEB2Tua3DuexzPPBR5IC4aRdDQ91AW3rsjpWCrHMOeGLigtMulBicgFlLsDD1DotBBuLZX6A2h/dAQm9hy1oXtEUSVNoZT4L1tLpo1Y0rD8Pvs7j+OCGxTjgsWPFPK2l+SpzLvne+dNd+M4FNfhDr/pDhhoawWAF2trgESywdvjUtBnZ2AM0NsbUc08c3wFDI96+pimlMilDHrAqORI3q33x7xdYD2hdmypYT6UO51xmQNg6Alq2HLWTDNP1TUCVB8zoBa1uBWrLUuIbWbQCJgPDwuqyyHNLP5jgARpNkfRsCgh0JpyfNPzBMbCpUaCxSpOesV5g3VqgxBgp74XvB1Ocmj6gSDIMQn9cv5C6ZaDRkLSd59qXfzdhxJffsRpBWQHQA1fzclRVh8r12GMAlibuB3r9UKdOmNAPWrsWePJvs9ojW/yg6oVA2xJNGmZwg1rXAJUlyccK6wXWrQNMhnB+Q0kAcssqoKkyUs+OIcgtjYD1zKx8FJDV/pBSHWjDivcMBN9pKA2N6keItnWgk3aw8hotn4epX16i9lyKpEAQ+tS8gjPOxoCsbRda1QrFLMb1G/F0EGgsmb3vhsrMDrvVjwUlzuRl1Ov7M/0xqg71+i1tGwWWLQPaFqZWp1F8hrIJSCtW4sbNx3HXF9fBIDCkNAfqzTlZQFaceBLRp4loCRGZiGgZEf2BiH4T+niB0KmRrxFRKxFdQDq+LziKE+98cjDfJmhARJDAYBQE2DwBHOqzQiwgpzPFjN4pN5bWl0PQcdTEkRkUoshfzDiyAr+ooNSYlSXuDQsiwvk/eBENZQYIvH/mFDO/Nz0BCWsXVWProAe3PH0iv0YVKRSFMO7w4/iUH1Z3AC6/iKrSyN/rFKJ57c+fffCVOaXPxDKG3DutZEx9R225CQ6fGI6jObgh/OP+fvzjtdGk6bKx11DrJHk6RdF3GinKSsY26OHXe3phcQew4c7tMDDA6RPRVFWCgCRn7R2pOuEUFdLtN2q7zuVd2jiDjtN3hQBZSV6nRJjTvigoEx7a36++QwEMMZYTUuOb2Y9Rih5kFQIkOb6WpDn2m2wPWylBp093fjEZGURZwdZBD5yhcZ9PzJeEZE7gEhKknidDG3+0dxi3zuV9ejbmsg5n4wgGgf4BzXEmecIOqa4esFpwdNiLOy5pxIkhe2G3c76OiM/Rxt3t0/jQykp0jNkhB9z5rcN5KvN88ZGkgHm5hCRjvqi4P700gatXVAJVAXAJSXoSEuvrp/Gx1mq8v0bEM1ZL8dZhgdtIRGA+Vd7gnXaiYnIMTYIEk9OJ4OlOlBhYbtfSeSjz3hEPWN0qvGse+o0rIOOc+hKUin488M4F+MqOMbyv3ItnvT4onZ1QRrxgXk/UfJvl8RfLNwcpALmcgIcSp09iHwNA5i7AEJGQ3PLQS/j2WxqwoNyYlbWUiSLozDCq3H64fE5AIAiSDOrpBapMYb6nepx4R3MFFvkc8Xx2AgIGwCyG+WlyGnDGSEjOpC4hoRE34HIB1oDW3hkZRUlEQoLxeAmJIirqj96YfiHa7IDVkLydU6zDgEwonbZhUSnDM9uOY02NESctMqa6BrDKIMLdbkZp1iQkCqhbKyF5vMuBf64TURZVFHnaAcUtqScWozgFWQb19ABlqUhICNTVFZHqWK0QxCCUvn7AVhKp53EHZJoGFPesfGSzQVDklOvANWHBfXtc+LfGAFxDDrCKcsBqCdWLKiGBPwUJiaSofcZqg0CkeYe8pBmsX1vPSlCGPO2I6zeS3QFYPbO3U6jMbEZCUqPtu0NDk/FSwuj80XVgNmvqULTa4vttMAicOQMgNQkJLWkGC4VLgkEE+wZQZwQcp82orynR54i2L9HzLKAgP2DMt4TktSE7LlpRnzW+rNmXwzLP4ME/9uDW6zOxMclRoUzrcDaOkjFQSwswHSUhGeuFfPwIcGETHv1ICypKjDj29CtFc+w1pfA82xiQZJQCsDkJzRvOgdk8CXlyLL91mOMyzzcfBSUIHQ41zCUk6fNFxT35xx5ccN4KoDHAJSRpSkgmFi7D+y9rRIvJof4prljrsMBtdPlFVLdPA21tcGybQs3aVbh7aQX2oB6/Gp7GN6/WmQ+KbH44MmiG0RLAu+ah3/gcfrz9TQwfrRdx3mUXwrBvCtXnrUP1sAeula0g2CEMSmrejMqcmoQEWApat07962+SMtGgG6yKInGz2hf/fsZ6QOvWAsbIMf79lhH81/JVQGNF2mvpxiGGNy+vxbvPWQS8OAJpyVKYFKf6V/tGAjP5oKxeDdRXhPke3XkALeevwSK/MZ7fJgM1ZUDb6sj7LP1gBi/QGJ1+EizQoTs/xdVRYAzMGi8hEYQ+0No1QJkpXF664H1gcGn6gOwXIRiG4vqFeMIPNJYlb+cU+81bvr8V7Z9dhUULjNg8IeKb11yIGx4/hvHKerSuM8C9bAEan3kC2ZGQDIDWrAWeeiL8bOpMN6R6ScMnjXlBtQuBtqWadzCjB8rqVqC6NOlYEVivKleZOe1kNsNULkFasRJYUhPOT7YBSCvqAdd4OL+sEBx//TsaovgUnwRm9KVYB4DXJaKiPIinPZW449VefELwAo0h6VbbOuCEHayyVsunIyGhoARBGITS0ADB4NK8w//Xv6G8ZIWGg1ashtIeiOs3waMeoLFy9r47U4dH3KDmJUCp9n1/O2rFDe9Noe/rSUhOBoDGUu37dSQkTzgr0FBZgqvPWxRXp997+GVcY2zCphOjmBAZgs3LUFtuwfTi5cDyOhS9hKTY8bFfvRwX943HX8uDJRxzgd5RMIUIYuiAVF1FCYwCg5ib039vGGy4cwckhWAyqNOFgbGiule9GKBk4a57Di0+d+kKfPTNzXl7/+/2ze0O+Gzjb4eHcGTAlhHHhNOPxbVlyRNyZAS7J4i6UvUH56na1AMAACAASURBVEUr6tDSWAEAeNfaBRib9ufTtKyBCBDmIDHIBN6ghHOX1OC8hlIAAAODySCgvswAqzsAAoUlO/OFVJdM9Zh7+u/RO8avHsVPnxMAvAEJPZNuPHFkGKICTDgDWFBdGnkvY3HvVbLw3qx0GQZQCvtAUqDbLxIdxU8XnqAqEVlWXw5/UMZVbQvx6XU16Jl0Y3FtGdwBKWvvYgxxdSjpyEVkRV8CNBdpkJ58ySCwOHmFQqrEIxqTLj82y/WaOIJ+eySCV1JQUWJA17gLNeUm1RGnnpFJoJD6Xr19WTA0l2jsJIKOgkRXVjJXiBn0PT3pk56cqHPchQGrR5dDBkPHmBMj0z6MTPsQkBTUlQph6VgizvlAQZ7AyIuExGzWhP9xfBS/XKH1Lr3t1Bha7AGsqy9NzpcN+3Jd5hlkamOu7UvAwWY84kYdQ1MmbZBr69RjY+aQJ+GZo/m5srFYj4inaKM7IKF7YBJrmfrXG8OoF7Lbmd86zHGZ55uvz+KH26keNWRWG5TOTgg2W9bGSiGWOSd8UXGNfhfqhvsjx0TnWf7w4809uH6RlLf54fBpCWxxOS4OTM2ZU7Gox24nugZx7rJKwO/ISx1mja/AbbRO+tEoquvUHeeYgFC/FdCFRZIb/vYOlDmSSCGT2HfT/kn89FxD3sqsWK0Qqqvnpd94rQGUu0VVPmY2Q5AllPT14PKyAF7c345lVSYI8yghEfrVm0EgJJcCkcsFuKM45mgfA4CuLs1NECSKQF8fMGXStzeFMpc5Ab+HYZvFj0PjPlQc7sUdly3A361OoBLqzSQz7wjxkc8HYWgIEOKP0ZNdAQJGaCQkE9OAS09CUhZvX3Q9z+QfdQEuN2IlJAJR5CaNmfJOTADTQU0fkP0yhJlbL6LqIGh3AFZv0naea79pCgCbPrAQMJvRMe7GFauNqJocg9vC0r6FhDo71T/uzeyTFQVKjIREmrKCTIomv+RwQvFJQIVHyynLQE/odpkkfZGBVLlKiSGc3xgMQOwfADxl4fzKxDQkxaHpF5JLBNXVaceCza6+P8U68Fim4XL7sFJ249fvWoBtL9shWK1QELqFxOsFAsklJEpQVqU3Nh0JyeIlMIxrORS/DMXhjOs3otMZ1xfj+u5MHbpcwCgBNUFN+qBH58a/6PzRdWA2ayUk0zr9VhTBRmIkJHYFEE2asTiDhdWleOJAD/738gXYYwamegaxwiRjuncQIJv6ocdqhWG2sWG14tDe41hQbkBrbQmyhYL8gDH/t5D06BwljD8Ws3nvOK5Y3YB1bcuS8KUe/puzHP96yQp9vpyWeQbxR33GF6+M/NUtGd8cJCTX3Lcfz79vQdaOvbLScSgtLYBjLPxcGe6GePI48OYmhI87v2bNbR3ON9+829iDfZ4SfOpD64EKEwSjFfLwUH7rMOdlnl++H+89CMUDoK0NhjPdkNe2QujpztpYKcQy54QvOi5aipMXCYneupKDMpvNeMXUhHMW16C2whRJU+sHFjUAbcvnzCkrBIPgwGRFPRasbwV6uotbhlPgNtrkCSwUoJueBs246PF+dHxuVUb2/e2PPfjpO9Zkvcx7WQOuWLcgKR/1dwKnT85Lv/H221AhyYBiU/cKphGYzmnDEmM3pgYIzc11YKOK/vhMwOkOSKoj0CT7RD1pAWPLoKxbB4NBSF6mATcEbyYSkl4oa6Nu3DCbAaMfWL0aaEhfQiJ4GEQirKslMDaOEdGAZRvOh3+iA2I9g1DiB61arcpUQnzKtkkILSsBz0Q8v00Gq42RkEz1A8YYCQlNIHUJySiYdTzu2D4T+qDM3KQRKi+d/z4wuDV9QHEHYDCOxPUL6VUX0FidtJ1T77tqu5GHwXSuOqdaNw3jvDevQXWZCebxkD+ENCQktK4NTIhIlZhxELRmDfBMREIi9XZAqScNnzzkgVK/QF0vot7BjF5Qa6sq95mpJ4Vww5MncPfoaEzf61PlKuWRdchUCUjLlgOrGiL5p/ohL6sFAlMRmywe0PQ+DR95JQhGf4p1APhGvairAdZvWIcLl9Xhq1sH8Y/3rsdzr48g2NoKOmEDq6rX8ulJSHwimGEYVF8PZnBr3qH89UkIphYNBy1tgXwi/lYj8YADaKyNt1nvFpIjHqB5cZyEJHBA58a/FCUk4qvuODkVXhwBW7YciJqzySoBdeXasRiCwb0XNctacNHb1+OF1lX404EBXLKsDo66JqCtBQLrhdLQCMNsY8Nshj1Yg/K68pDsJDvIioSEMfYBxpiZMdbDGLtZ5/l1jLEpxtjx0H9fzsZ7AcAvZs9bbzKkekhm2ObFHvNkSmlveupk+gblCI8cGoiLOzqY2VFkADg54kg774DFE3dMSWAs7hiaErqFhCO78EhK+MeRegtJng06yxB91FYQGOQsH1nlOLvxsxfN6Jp0JU2nKKTbt/7Rq80rKwQDU73HGw1z2yZY3AHY/PO3Lp8NsHoCaCgz6D5b3lAB3zzuc+aKLzz0akrpFKJ5k5B4ghIqo24dMQgsdOWfunZN+8Q5S0jW374tbXvmsmYSVMlLLP5xfCSl/EznXUSUuZQDQPeEG+c11+C/19dDCE0Ll7Y24sluJxhUaekPn2uPei9mve0lzs4U0qSDRDdxxJqmKPq3gWVDChALhUjTypICGAUBKxoqcLDPmhan3o0hemUXZUKsuEAifaGIXt+VFNLvjzpyFaOBxd3GQRS/DsmKEmfTXCVIHlHBL65djwuXqT+S7TBhRWMFaitKMOH0AynyUeiWIkXnFhQZQOySqBDibloBAFHK/BaSTCQkUgo3vSQDEbDxX9dDEBjqKkowaPXimtVVcHhVCclMPcXni+lzCW65yQQZn8BgjBkAPADgvQDOADjMGHuOiE7HJP0bEX09Rc5roCMhIYtFO61brVj/cC/M/9YaDsNsxrO9LogK4doGUZN/LhKSuOcAKBAAGxuPHLFKwHei340XBly48sKSWfkSHiWKKWNSjtnCaUhIApPxHrB3HrVig78xbxKSp45Z8a2LGjRH44RgAMrAAICIhIQsVoxX1GO1dzrC49U5gqUTPm0LqJrZQjsWP8sx+fmwUWCAyxk5hmaY8CHg4BKSbPKR1wujLAFmMwxWu3qnuNM+N74iK3NO+KLiyGpF+DYXK5AX+UPMuqIQgVmtcetYpnXIfD5gaEj9i9ZMGocEjAcBszfMeWzCB69EeFeZdk78xr4JfLQ1ElasNvXH5szNI6E6pE5FnYNnsfEPRyyoEv34WvQP8nz3m1xwZpHPOmBH4yJZN/3lTMyOfVClQdF7b/vYFOqir3BOp8xA3H5BLz1ZbWA1NfMy9rz9bjTXmcLy0hJZBOvqAqxWXFlegWdPTkGYuY0gRU5Zib+dQtem6PoI8bEBgmI2q7KOZPvMBBKSbzzeg4+Wu5NLSCh0jN8ULSGRwPr61BtC0lxLmRU40ufEbeeVwuZwgHzqUfcrifDWoxZUlBhBfX3488tDuHVVM4xmM2SfH2xwENF7tDC/joQEk9Ngbh0JSVmKEpIRF+DyAFa/Jr0qIekByo2R8k5MAA5R06ayR4JBkTRxChFElxuwiknb+bt/fAk/vnxhwjqMDvsnrSh3RCRdoijBODyEMm8pmkU3zE0r1F9UKYytmbCAeKkSm7lFJFpCYrVBqdTaLztdoICirhfR7S5JUHp6NH1HkRT1A2CshCRWqmO1QvD5oQwPA7I1kn/CDllyAKWRdUi0BaDU1mrHgt0OQUpdQuKbdqF8ZAhwR8kUzGa82yTi2Z2jIK8XTIr5fWMF4iQkfhlMkeNvQQEgL1wMg01rE3klyE5X3PwgeTyAVYm3GVF1r5GQKEBtjITE5589f+x+I7qdnW4olqD2pIIoqreQkC2S364Aoht6EhJUV2PZ5DAwCSwF8MRVDYDVCnEKgFlRZUM6cwqZzZp1RbI7oThNgC+1P+6ngmxISN4KoIeI+gCAMfY4gI8CiP2AkTISSUje/8wQtt2sPZYSkOOP0gwOd6tfnhqR4hGv1CQktGccrHkJwl56E/BRYFQdFLFHdzT8obCeN9po6OXJ5hFQnaM+gUkxrk4D3afjjiclyp/0mFsS+6Q1a7V/9TObEXQokNeugxB1BFMonwStWAl4Ip6MlQEzBk/2413ntCDsZTdFCcmHbn4BAz/5J81zIgIrtOPSueBMwCcrhItX2lBVHTluKJTbIYv981tmvTootHbJgE/ZZQULqkclDRN9UNauAAZ65ziWi6vMOeGLjouSkFCBSEh2np7AMiGIc7Ndh+VW0PIV6jHdUByr9YMW1wNtK8KcotGKYEACDNOzzuNyUAETXJDrG8JlMPgEKOvWqH/JnsVGpU8BczsKq9/kgjOLfN4BM8oXQTf9MgDfsJUAjZQy38ZtZnymqRaG5pawo0Wj0Au5oRFCVJ53/7UPO298KxpmjtanU2ad48w3Pvk6fvaJ9dq1tEeG0Dk/EhKPcxiVaxqByWGgrQ2llZPhftyyZCUGuo6jrqYibnzOXubU9om6EhJhObBuHWAyJC0T9bshBBBXp3pHxBNJSGhN1I0bZjPI6ANrbVWPiae7lnoYbv7wCjS/ZSnsL58AlTqBtjYwANedb8ejPV7QqlVorBqHbXQSC9vaQCUTEFa1AM6xeL5EEhKTVkJC8gSYP0UJiX8UsOtJSPqhtLYC1WWR8p7/PkCIkZBM+yCYxjVxsqyADjiAxrqk7fxX/1L8+IvvTFyHUe3mralDhakSaGsBAEhsEKbWVcCianxhpYgf39mJEoMAtLWFb4KbjQ+NjWBsGsradeqHstBzZhwCta4Bnv17OL10OgiqFzR8Up8LSuNCdb2Iegcz+VQJSVTfkQMSDMKgKnOJ4hBipTpmMwxV05CXLlMlCzP1PN4LubkmLPECAHnEAcVxQMOnuEUwU0BnLOjVAeAxO1DZthYISeCvEo4AbW1YCsA2dhpVMoHNrGkz+fUkJO4ABOMIlPp6CNG3oABQ/vI0hMpVGg5ashLya564+UHcYYmfH2L77szYO+oBNS9Wr7GNSi/u0hk7KUpIlAMOyA01mjmfXhxRbyGJlv1ZJbD6CqBtVXwdu/bqrqUBhyrBE4T+yD4hBIH1gNa1RTywms2QSipATZVASwOyBZap91DG2CcAfICIvhwKfx7A26JPWzDGrgNwF4ApAF0AvkVEwwn4rgdwPQCsKC/fMHjjjeFnLf5LMFB2OJLYYkFL1QfRX3pYPRZksQBNTfil1AyJGP6f43WgqSmSfs8e4MorNfnR1BThDYXD73Jv0eT/b9dSXF3hw0cNtjDf2BXvhQyGZSwYzr9JrscWuQEPOF/Rvj+KP9r+cJli7UuQZ07hBGWerU5vqr0YPzUNaNLfKq7Ej0yDcXx6+RPZo1eneva9pepqHCs7rom7s/Yi3Gg8g1JGYc6PBM7DnaZBrLcNAk1NGCMTHpQWY6u3HH+pHkSLEAAA3OOsw7dqppPaqNcP3h94E148+MCsdZgs/BtHNT5cE1D7SIIyz6lN9eJm4XSQASemJbyzniXOn4DvUv96fNIwhX93dKCuqRYA8LpSCYvDi/fU05z5kqV3kYBqpqRWB5nWY5o25oLvXwLnolL045GqfjwoLcK1BgtqrRNz4yvAMp+2BfBU9RrcZhqeH/ui4u4Rm/Et0yhgseCe2gvVf89DmWebT16Q69HsmMRFDabsldliwbXV78ANpjN4q+AOx91YezE2MDf+1WgJcx6Qq+GCER+wd4c5iIBVAe08/jNnA35V0oq7TX34uMEKWCy4v+4C/IdhHCZGs9r4Y3EZGrwO/GetS/d5tso8J75ccGaR725xafx+JSr9PWIzvuU4kTLf+wJvwn2eo/jnistxuPQ4qpiCdf4NOOHejt6GpTiP+cAYsN63HnvLTqGOyWmXWbOHmaXv3ykux+K+DnylrSqc/YQtiM6aZnzSaMm4DqOf/1FaiI8ZrKgLzaEfC5yLZ0o7AIsFSmMT3hc8H23Mh88aJlHusGnHYxr7RKWxKbxXj9sT7dmDcy79No6VHkdFCmvbpmkjtlSsxAMlvfrvj7KvxX8J+t1bgMam8NH4830X4eWyE6iJatPLqt6Dp0o70By1T9UghXaOnkPbbQF8p/It2FLaHrb562UXYWfJSXxZXIsHX3sUrZeuV/uhqQ9ttuEw3yPSArS6JrCjaiWaWRBfNk6E3/egtAgjVIIfOF4Lp98u1+HxSYY/LLFr7NHrd8/LDdgq18ftvS/2XojN5R1YOHOaac8e/Okdn0QfleEO01A4/6BSis+J6/BS6clwnJ8YviyuxaPOl2ffO+/Zg5ZLb4izSa9OW/yXYK9nLw7XLccnDOpf1K/ynocHy/rQKqi3Dv2wX8BTS9bjldLXcVXgArzi3gk0NWG7XIf3GqZ1++HaqvfjVOkxTJIJy22jQFMTLva/GZtLT2Hh3h3hNr5RbMG3nSexuLE6bN5T0yUIVNXiM8Ypjc2XV70bT5R2an7jOMmAywPrcerQRk2/uci3HjvK2tHIpHD+L9RchusMk7jK4Ajn/5W0GOcyH66y94bL8JpSiSPdE5r5YdjqwacqL8OBshNJ6xQAHnRU4doaH2pn+n5Uv94t1+IhXwPWlwbxHdNIOP/G2gshMOCbxtEw3xQZ8cHA+djs2YcPVb4LR6J+j/QfOo7rLvo89paeDHOMNS7BjeIqPFLSpbHpw4HzsMm1L6XffV8LtuL9Bjs+Yu/SrM1f9qzEH6oGE+efZX74fHAdfu88hLKmyEeDz7lX4T/KrXinwRnOf3vtRVgaMxZnsLFHxLfXRM2PoTyP152DiwU3PhY8F/vdu1HbFPFt0erbgM6yY+peIZT+r3XnYo3gw1sFN9jttx8loouRKYgoo/8AfALAg1HhzwO4PyZNI4DS0L//A8CuVLg3LFlC0Vh50yZNmDo7qeXmTSTJSjhMRHTPdjP94sXOcDiMH/wgLr+GNyr9yps2kdzRoUn+td/soWdfO6Phu3dHF/18a6cm//Ovj9BXHz0a/36dsKZMsfYlyDOncIIyExEpiqJbp9947Fhc+hv+flyXTy9/ovDKmzbFPX/we7+KS6/HeduzJ8kXlDScH7l/Px0btJF0Wm2n7z97ks69bQutvGkTKYoSzn73YwdSsjFRP5itDlMJf/QX2+nIgC0SkSGfbtwsnMcGbfSRn2+f2ztCfCtv2kQ/3dKheX7yzDS9+OKRpHx2T4Du2tyR1L7o8OpbXkjNvjlwphzOI99H799Pn793FxERPbS/j2zuwNz5cmxjOnwv7TpGn3vw0PzZFxW3cZs5HA7/Ox3ONG0Mz0NR6f9xfIRe2fNaWnyzhT/x6wN0qNeiibvh78fp8VcHNZx7zZP0j+MjGg5Rkmn1zZE51xeU6B13bqUv/ekw9U+5w3z37+qOzMGz2HjH8+30uycPzq0MMXyjR0+RedypSe8LSjRk9aTFl1KemPC3f793ds4s9RtZVtT+OUv6W585SUf2pt5v3v2L3dR16AS9d+Me6hhzEBHRubdtIffJ07T2e5tp2hskIqLzb9tM056ghrN9xEHPvz4Sx5moTJr1OvR8Zl+2c/tRkkP7s9ufa6ffx6z3T216lb75+Gtx+VMOJ7Dvvp1dFBDlcPiTv3lZ8/zKn++mr/3lKP1uby/98M8vpcQ5U85Hn30l/GjlTZvIcaKd3n/PXk1cLN85t24ht1+MK8MjBwfiyvTc5sPq/jHB+6Ptm9mnXvWL3eG482+LtO9M/st+vIOGbQnGzixljg5Hz6HtL7+uKfPJ/cdp5U2bqHvCRdfc9xIdv+1nRET0nrv3qOM4iu+Gvx+nx597Ve0P+3qJiEgJ7bV/v6+Xbn+uXZN+W/s4femWR+Ls0et3/zg+Ql/9S/ze+5IfbqFxh09T3of299H3nz2pyd894aKrfr6bzti9dMODavlcfpE+8/uDcZx67axnk1545U2b6OT+47T11Fg47h13bqUBizscvvm7D9GGO7dT55iTrr57T/J9amcnrf3uZvIFJc1ee8Od22nC4dO08bcef41GjpzUmPe3515V+2OMzZfftTNu3rV7AnTBD7bG9ZuLvr+Zplx+Tf4v/vFV2t4+rsl//65u2nF6XFOGw/1W+u33fq3hGzx8kt7+k50avlj7onHv4y9TUJIjEVH2jdi9dNkdW+kXL3aSKMnqvNTZSXdvM9M9280avgmHT623Y6fo4h9p9849t91FV/18t8aGM3Yvffp3B+Nset/GveG+HZ1e73ffV/9ylJ6LWZuDkkzX3bdr9vyzzA+f/f0hcp88rcn+mf/bSfu6JjX5f/jcqfBYnOHb1TFB094g3f3d31IcQuvxXZs76M23v0iW4+2ax603b1Ln36j0f365n17uUfcoAI5Qht8eiCgrTjxHAES5rcWyUFz0RxIrEQVCwQcBbMjCewFAdTSm40EkU39FRoHF3etLOg5d9JzMFIuDw5m7jmMR0HE8E5yjM5pUcae0InkiqE6HYtt55p7m67aPonPcibISQ/je4+h2yrdLz7y/P03vXZKs4F8vXo63rW7UxCdy2hMLp0/CphOjc3qnrIQ/er6hED0ZGwSm6xCqGCGTvlO0NwJYaH6KhqLQnJxyTTj9qb0LLCX3iDJRnGMxSaGwg0MAGHP4MeyWcM36JWhpqgzHGwSW0tqmZNjmRIStg248emhQE7evawrffSYzp9cBKXVnmE/1JHeKmg1M+0TUVZhmTTNg9eC7L0/NmiYaFFrbm6pKYXWrJ/8MAoOkEJbWlWPKlbhfnR5zYldHYp3y1lNjuvX4yx3d4X+bDAJEWcEN+ydhcatbvxmnhb/f14feKfWkkDxHJ32pIigTSoyR7W30v2dsEWac1M7BACLC9w5Ohf8NAI6AAqdPjEv3T/e+FA4LOs4VAeDWZ0/FvwNIedMw47Czbyri5HzGaePhAVtUuvixS0Th/VIqiM6uviMSXh26GlFSFNSWm+AiQzhdMmzc3oVN/W5N3K9P2NE+6gjbCQAv91rQOe7UxAHxY1rvnepcrOfEU5taUhSYDAKmvUGcsKj9VpYpzll8pmAMcIqKeqtN+N3QSKf9JKDMJMDpF1FbPvv8EM07g5ny6jn2FJUETjxTcHQKzNxSFf9Ar5/NjLNhmze89ikKQYpZByUdmyjB/DBk9cbFffI3ByERwZTA6fTC6lJMeFUX/3dt6cRTx87opgPU+pr5fRFbTAV6v/n0nWMrRHF7gOg6jnNuGpNfVuLzzwUKxdczoO8kOHYsnJn2wR2QEnKXmQwoNxlAQNw71Pkupn3l7O/ts+ED4zCAtYyxVVA/XHwKwGeiEzDGlhDRWCj4EQAdsxEmcuIJQBu2WtVOZjZrnSNZbGrPr9Km/zy7AI/E5A8/N5s1YYEBssUKU3T6YABsdFTVKAGqsxSrBSzWudNovCMhUSH8+cgoNNevJHLmEpsmkc2phGdxzqQooR9NUc/JYkFgOsqJTCh9wO5Q47LtxFMvv06cZJegdHUDJZF2Fvx+0OAgyhUJfa93o9QRwH+8qQ47Oye0+XWceD6/5QiuWV0db1NMP0hWhymFJQkYHAT8k9nh04ubjXPKr9oQ9Tw4ZcE/up24dm1NQr7ew6dweWUQV5BNOzZsASguV1KbFWcQgiTq95sEZaw0MrhOdaDGNZ28DvLtMDKLfIrPD8GoOnsSJh1Quj2AzzE3vlneMegUsbTKCKPdNq9lVhwuCJ4oJ1a5bpPoOKsVMw4oyQrMtxNPIwPkTjMM05E6l0acECVvynxv+2MPBj5Sn9wenw8YHgZESyQu7MTTF+ZUhj0QfRLQGJkPZFGBERHHZqOjXnx5dSnW+qyA2R3mE6YEKF1B1TngLHVINjsEQzDtOnyq24l7jlnxibURp3mHuibwYO8I6ksN+nN0sjaBura9/bF+7L92JcqSOFMMb7TmYaxY7AE0OYMAS1xnPocbjUYFckdn5IfDLGVWAkEI09NoVBRYugYA2QoDKVBsNjQKMmwdvYC9HAYiKN3dQFnE6R7ZnIDTB6mjE97FS1ETY9PP9gyi1bMEa+tKwut14HQnfrmzF9+4Ru2rJhDEzi40lwIjJ8xYuKAMsNsh1NbgSPsQmr12tK6qArndMHgijgyjHScqBPzXi0P4lUJ4ZdyHdzRXpD4/RI19mM0o9Xs1/UYOBCG4nPCO+VAu+lNuZ/epTlQZodqoqB9knFM21AhaR32+9k70TrjCax8bVqB0dQElBt1+8dQLh/HxNepaTC43mIvpz5kxa6kAgKxWVJcIcJ7sQG2pIeTEswfXPtaPvutaIdhsYJII6usDpiKOGHcOebB5wI2N71qUWt+OmkOZwwEEAuE0FU477r9yEaZO92K1UYS7Qd27s2AQSl8/QFFOPB0OoEIGxAAQNGLQGsCq2lD9TdrBvBK6HT40HO3Cm1w1wIgbKCvD9gOdWFppxDnn10MJ7f09pzpw5VODOPzekHNYnb03AAiKAurpVR1RzrTx5CTg1DrxFC1+GMUg7OY+NBpUmyS/DPJ6450xzrRHdL/pg367xYQFAC6rA4uNgurcEoAkyzD19wEV6s8yqbwCRkmCu2cAVVIg+T7VagUjgmLuQpWJwTVhQS0zQ5AlUE8vNpa14dszc77DAbIZNPlllxuKTNi6zYpz60uxskbtK0wUofRq+47slWBQFKC5GZ5THagMOYxligLq6cFPTk/j5oubAKsVBk8QdGYEz53uxzV1ElYIDIrFBllyAtWRPiSNeqHEOPklux2CKMXV6bv+2IOBL67R1MGrAzZctq4svk1CYSNCH0xtVrg8EmRyA0EJuk48PRIEWYJit4NJEsaOteO+12348eULIS9cCINb1NhELhGK1xvXLkogAMlihSG6ni1q3w2e7sQVTw7iYMhGpuPEUwwqUII660J035tlflA8Xig27d5fdeI5DCjWSP6wE89gmI/GpyEZXEB1dcI91gKvzP0IrwAAIABJREFUAy6fCNFqi0tD5i71d3kovTQuQBGnw/09G8j4AwYRSYyxrwN4EYABwENE1M4YuwPqMZHnAPwPY+wjACQANgDXJeHUdeKp5zBSEByRO6/NZtUBy1CX+gEjxonnS75EDifjnTMZDapjksGmZVjZGPor1O5xsKXNQFuzGn7sMdDqK9XPZtEOYHQcCdmdfvz2iQF8+fMpOHOJRpRNaYVnc7YmyRCY1lGgpBCkCmecg5jAQaeOAykgVSee6oYwBYdXsXUSihMrvVDWrFHvlw5xCrutUJavQEOPC9N1CwDBj++8dx2+88MfAm0fC2cnHSee//1cD6754MUxNidw0hXjqGiubcCMZ0ArVkSc1zz2GLrrmvHwwUHc+c/nz71N9eJC7TJg8WDU4cPlUX2fVUyDDk1p0vsCMu7YPoxrP3xJQr6951Ti2nedozpkinpumHBBng4mtVmqXwpjqVW/3yQoY1PtKB6eMuHrS3UcH6XjeCxLYyXXfErpJASDBLS1weAYgrJ6ITA+ODe+mDi/KKMMQG/DUvzX5qP4yccvxFsElrMy+4Iyyv76GFi0w6thDwzVMp5wVcAbkHBdU5J2zbRNouOinHjCjcTzbI7aWRD6IK9ZC/RH5jjFOQxxemoOfDpzpp49FTbQsuVAa2MkrtYPxDjxlKVxiK4AUO8Pc0heEQbDAEYWrcANf38dF7c04L8vLUXthedp3iHIJshrlqvOAWdbVzpFGBRPWnU45QrgO3/cAQA46RXwh6kSnB51Yl+HD36F4erzGnXm6BTaBMAHnx2CLSDjePlCNFWVYA2QkCMgyig19MVxOpavDl8nna1+Y+mxoGkBAyRLwvSerZO4aEEZBpuWYfWCqqRllk0jEOrr0ehnsNSoztmMpiFIdfWobfDCsWAJ0LYITOiD0tqKLz15Ar/5/AaYAFBJBZjXhpdYA/40VIE/z3AqBAO6sHSRAWfqFmFt28Lweu1Y3oKGyuFwXzWVDEJa3Yq6yjFML1gCtC2E0ilC6D6BmlUXwNlQB7StgGx2QDCWafYbXXXNuGtzB3768Qtx3DGA8UUrcMOzB3HwlotSHnsseuy3taH0iNbB3q+vW4wdHROhTJaUOIEe2JtXor5sCGhrgyIrMAh9cJRXo7bOpBmzrhWrUFs5El77mGElaM1aPHx8BJ+pb4AxZnz/v+d68PF/Cq3FvS4w2YBH7GWoLTfhI+G1PN5JH2O9EOsbsKBWhL15JWqbKsGEPtCaNagqHYZrZStqGQMr8YNWrVL3pKHyONxnQDYh9fU5yhGyYguAlZGm3VhVDYZ9Itad0wDn88fVdiidALW0aJx40gk/UBYEUAnUlaHa4IELXvX5ZB/g8KNcsiLQtABoawFJ44C/A0JDA5SaUqCtNXTdqQPO5S2AcSQyR4b23nJ9BQKrWlFRov7EYYYBKKtX48FT4/jyO1ere/fz3gsYvHhJaIDi9+CKtjaI5XYYK92w1i9EfbW655WdfiiHHPDX1uGLe+147PpLI20X22+wVFMnieqUsV44Syuxpq0VCI3nEtMAjOvWhh1gvj+4FRNLl8G1YDGqJhH1eyKxM1kmOCGvWYOailG4qupQ29YGZjwDZfVq3Ds9gG+H0ouvuKDUleGabVN4/r/fAQCQTk+DLVyITYN2BBbWY2XbUrVdSwKgVavwk8PDuGlVA1hbGxSHH4JpDOLIGN76xCDa7/hAqJ77gdZW/OZvO3Hjpy+HgC4Yat2QlzTDLtphKROxoq0NylAX5IVVGBZtaGhpRWWpERImQc5XNXWmOIJgJZJOnSaog4ryJOtAD9DYBENJAPLCGqDOr+vEU5n2gZnGQXV1EEwBWBctw2tO1eGo/JdnITSs0dikNC2D9KojziYyjUFpaMAz3kp87KJlaplkgkFwwLF8FQJsOPL74qgHtGQRUO6OzOPeIMg0Ft+PUnXiuccGqa5Gk5+2jgDLlgNrmyL5rRIQ48STrAPwLW+AyX0gpg4j76wPjkF+eQpSbR12yHW4+rxF4f5Na9epH2xD6cWAAcrS2ojz0CwgGxISENFmIlpHRK1E9L+huO+HPl6AiG4hojcR0XoiuoqIOrPxXiCxhETv3JEA0r2POBGvpBDed88+OELHA/VuSVYotWNykkIwpXjx+Efu359SukyhJ4mREhzhn4uEJCgp8Aa1R48SyVVShagQlJh2Zky9d7y2REDvlBuTKR631kN0H5ryJT42lQ70jvA5fGL4iGQ2cXTQjiePaI/G6R3BowTxM3hBrsfhATvqZ7xJR0EQUpOQBCUl7uhuMrQ0VmLzyXFMB1I/6p0MkqwUvCxFiTo3LDD9O8XnAodPxBU/340zbhG3PH0SD3zmLeiZdCfPmAEePzyECWiPus7coz5k9WIsg/GZKUpNhrg5KdfQkwLJNDcJSapg0F+fYruRoishUWBkQN+UG5JCkBUFtaUGxEJgDBSzDPhFGcM27XHemeP5qcITkPCs3ABPQMIjhwax+X/eif95cz1eH3Zg0uVHdZkRhz7ZgvefvxhBScHLPZaUuaNh88tQCHhofz9ebJ+YNa03KKPMEF+G9XdsS+vds2HKHcCC6vh5NhqegIQLmkrRO+VJiZMI8EgKmuvKwvIGgTEEZUJdRUl4T6P2G+DUqCMs9UBorWYMkKN2N5/87UEMu0QsqCrFlCuged+0V8Ti2jL4Qn3LKKgSkrpSAxxeMWwTA1BXacJ0KE4hQBCAB3b3YPPJMQDqh1CrJwhXQEKVScCYw4/muvK49X/W8seEY9ehdYurUGIUUpJd/fJ4RIph8wbREDqtIitqP3cGFVSXmTRrjNMnorosMhfOyDru2d4FR3D2vRSF0jt9IjrHnLOmZUzt16ubqmD1BDXvqi03ado+di7wiTLKS+LHeSyCkgKvqGj2uYrO3lFgwDOvncEV6xbABUPYPr2lLDpnXXkJHAG1TmbS1pYawn1kpt+UmQT4xUg6gaky1booecVMGzzR7cRPt0R+ZsxIXn6xzQxPzLH4Az1WnArJRSRZ3afbPUE0htpZUgggYDqgoGcqO2soY4BbVFAdJSHZ+bEVkduAAHzYYMdlrY2Y9gaTSsyieV1+Cc115XAFlXAcATBCCcttpP/P3HuHR3bV9/+ve+90jTSapi6t+uyu19517zZumG5jCAGCSSihJNQACSXfEKoJhDRCJzGY4kIH4wau67L27trerll1rbqm95lbzu+PO5rRSKP12pjfk/M8eh7dO/d+zrmf0895v99HNzCE4NBcsjL2XaUrOK0K+ZJeY1MAtz41Q7ycT7owKSRxlJoyJGGWDbfdQqbc365SSGLZEpHy2HqVcvGZJyPsHo2U01SHQlJ+/1TDc9Xnq7tdALjtCpnC5uMBUe7DVst5Mq9WypmBhCJLqLrBQ+Hl8vNU2qeMWv0Kk8IBH779QOWeXradzNenBn16zwr7p802R9VPTiH561v2nfR7RR0KSz1v1qujhhDEsyqNbD4W7wuam/uaAe9ck5Z6FBKzfP3fo5C86OFkFBIxMlJztqyMMKkF9jXQvFWIzbpzjh2SoHAsjHvN+djGSNjM0HXQH1kY6NEYO/02juw5zEUdLiiWzNUy+xoKSSSCLNfCj5hPQ6oWxqalVRRxaucBH5xdAx2PRjn82AEemc/zN2d4X1wKiWogr4EOA6iRGEamWBM/4TDFdMb0/Rp7dWG20Sj/eyhOvKDziXMDVUjWKl3lhVJIEiXzLGpHNZ/lfB5jZgZ7qcCDh+e49eXmivGGs6nrUEhq4ohGueC2ewF4yRfuI1XUeNq5pmr8sdBhVYWZGSiuVO3NzMDq+c4vIoVEWkxhJHMQXQNTj9ShkERi2NbmfdneUk6j1WXhKWcbH99q3/A7gJIqoZ8ChaS4UsCulermyWbfuMulMdzhYnE+isdWW9c3+OAUbd45nqbJJnOlqxZW+ujIIpe8AHsAD81mCc8lePfa9/8I+oNcLCKMMoVkKYUhpaCUen721tyTSjrZfIndx1d4ajJHX2yOu8bj0C2IHzjKRKrE2S3OFxUWn5mNoba01fyuJVMsr2hMzMV43WAj+SUD58l89ieikJwpOXly90Gu6Gr4/41CoiDQw8chU6VD6QtJ1OKpU0hOOT2rFBKtCguVkjosFVlLIdFnM6gZFdZA3vWchgXB7LFJbuhQsGlpiKob4pBXFPTRvNkGl+3tm8/xzYNxfnxuFbqrxxIk5BKFI8dMqsZzfMNissSH1AHecusT+BwK29OC4S7B1541uLqhyO9nsihxic9v97LrJ5N0iTwX9Uun7EPVEHx5X5Q+l8RyHoJ6nsJiiV+tFLkeNtgoaAYfvH+BrGrwZ/9+Pz99hblz9oS3Fxao2ya+oOtVCslEgqDcWFNO1j//qV1NnGvN89Ojk+YRuM/xzZKqElmKE7AWSSVVfvzrBBZDJ74cY4uwkpgugDtrjp9Gx/DIguTRUdpFBiOaREoVSE6UB9iVcpIjuqQRUBUikwVozFX60sTIOP12g9hClE5LGKuho46O4REqyalZcGVMOHazB0cyTiEJhDWMTBapVCRbyDC+LEG3wFgpIBUKZI+P45YMFo5N0C6rXPz5+3ji6sZTqyvrKSTZdE1fK+mC7II5SbAWquODgmbgWGfz35+J8bdnjCBLEA9P4JN1jJERhC6QEaRiKdqFldyRkQqUPhUep0lolb5PmjUQo2N4LRBfjOJ3VO3rkYi5aF2mB4l0Gjkto8kFFENA05oyFw5zndjJr1fzWQhiSzEGLQqx45NQWEYWAjE2RpOskzw2SreURSqpGBMT/OixPK9uLuEB8nNxnLlqGjcre7ePJHnmRJLhtqrvjUQCZS20PRpFSmdoNkq0L86QaWwu90NFjKkpYA2FJJUEXYdSEVQrSklHWx2jrcSRcjoWtYC2sgJhA+YySA4HlnjMnEqFDYxoFAlIhsdpQqumdyGNlM6SN3QkvZo+SRgwMYHPJpM4PEJDRwdieRnSKlgkhFpAjIyQnc1hLRZInFikSTfHwXqZHhBfUvEqtePl1fbCYZGfF4VEEoJ0IoN7ZtKk5AGOZHxj2Y5GiMckvIYoU3iq5aAuhcQwSB4bpUtRSUdMe5KmIcbH8ciC1OERgk4LWjqDkSjitcvEDx4l4LSgZXJYpGWcWZXiXMHsN6JRpJJJP/JaIL4UxRcOY6RVZF0jHuzAl6HGz2J8nCYLpI+EaSqmUDIqxpyBNZMnapjlzYhE0dUUslpCzM2BNYk2m0E0rqeQJEDdSGnf1Afrx/rryvX3zrTz7zMRnALyaQmsoi6FRKRVk3YVjyNpKsnxaTy6OX7UA0GUUpGVZ4/y93fO8tQ1TRjJEnq+gHZshK88NsdnynkqSipGNIqlTBmxKRKllSg2udxGoFXSKGdMCslUNEtqdAoKK2hZDaOkUjo6wp7FPJd1uiptrnZshN8fXYLBUo1Pvuca4p3la5HLo8dq552SqmKcqEMh0WopJMZSgngmRqN3cwrJcHkOqMbiSFTbMEmU5+Vr5traMgiRBuK8WOH/5ALGZhQSWRpDHxquCt2EwyiWTPXc4XDYhK2dOG4uxa07N90ujlHs7cfttlfe1weGUOSJDdCfVbjljkGJQ7Kdi0IDiAcWkDo6IdRuvn/rrYiLLkdSZAgNVd8vzCOto5BoKxksljpUhLoUEhMKVFB1vvVMDHdnIxNwatDZdde5n9zON6bgo9duhLUZRQ1Zmqx5Xi3o6M7kBniS+ocIYjiEdNttVXiUIZAY3xB/JKbT0mJC/Vbf11UdWZ584RQSVwqjfwAa7RWb8iNxjM5uWMxzy3vPwu9Zc8b32vfrUEhW43govMxH7pskWjBXGa/a2YUjlUAMD5cnz388hUS2zSK6e6CvSiGRru1BHN54bvQp2a93r/zNcm4OkV4Gv6uaz64EWGph61pGxWIrbsjn8z/+O4599mW05h5k4LzT68anxHLoS4XnTHPJGmA0tcDNERtXzUbpOZVvnDlO61CAHzxwBHtJ559fc9rmPjgF2GtxYJDZuQlm43mu7K4te2+5eYyxVw1V25NN7P3qmTmCjXYuXkPLMcQSN/1+gTe/ob+607ZJnjznNwOKawUDFUIhlOwseo8XorPPz96aeyKnIikncHoagRyWbVvRZ4+DX/AsXm7eP8Utl+56UekUmfFjFI+sEOnsJVBuY5eOJjgYibD3U1fz6NgKi2qcvudj/0WikFw4PMwbv7OHl1x5JtKfgEKiDw1XtQnKvyuWafSBQZittrFGbAo1upFCkt7Sj9tuMduccvo2pd3VS48zBt3dMLAGFuopQqsJ1a9QSArzaLEc+PVq35TIY1FmWXI18/4rh8zvqBOHLNkxBtrBba/YM6QVpPES+JshFOKWJ6Y4mIFb5wt8dWSCO99/CTs6PXXtqYNDpsCkTwNm6B3oZCpqtokWQJDg3Mt2cW75ecvgECVjAkdrENVrYN3EJ0VNZ/nHP4dgN7ftnaGtycF1V+7gk+kFbok5mI7miOs6Xz2c5vo3bLRxdCZOOD2HJmBrXyuPW/z8bN8sS0vm7ui4r5OBoLvy/HKqQEuT4wWVG0IhUjPHaTp9CI4f3/T5a0Pm9d6ZFNe3b6G1XnxryrVsn2cKB1u3D/DNXx5idDmO12VlXLg47YxuDs0lITSMJE8iBgZobk6RbO0ENYKwOJFLCeJNjfgLB6s2749gNLlx2JwUoAq5Jk4i0EZfyUXcmaczFMLqmCfR3k2HP0OyyQehIcTREtL4QdhZLqOhYcSxBEpDA4rLii5L4BcYjhakAxkyrZ00N0SZsnno6G7gzsmJjXVhs7q8jkJiG1Fr+lpZN/jGLXfzhdfuYHnSpHosJgu88TtP8FC22t/rhkBijHhXH17XCeK+Fnr8OdI9AyiKhKxMk7Q66e9uJdbRSoPPBYyRaunA61dRB4ew3norsqUXMTiIpzlOwtmwJs1jJN1eenwlUj39eBtsiLEUElYMn8vcXKuMY8dIb+knXFyT7/IEUbubwa0txAwDQj1I8iTGwACe1TzVo8j2EqKvjx89/jRnnW9SC4pzo9gbyu3AydrE+DSZuRwNXe0Q2mL6ZaWA4kzXjB9yjgZccRll21aMHz1i+tmxDFu2MDk3U233VykkDSaFhIKGWKXxLE1AqmAu5vkDEBrGKC0gF46CP2Du6YaGEZqBLKdIBdtp8pbA7zHfz89BYpmStYjVWYXOS/IURl8fTY0xku09dM7/DLZfA5YcNoeFUizK084W3vaHJ7h0KIDwe01Z5FAILZJF7E0Rdzpp9tZShQiFOPfT93LoM9c+PwqJPEHW6sB52tYqFLZefe57CQXdwKbICJ8Bw8OcjEIiK2kSLZ10brGRVnLoQ8NI1jmM3n48YoRU5xaCQTfaw3GEpwGPWyPZuYVA0I1+IIYlGMTtKpG2KazOaVbLjtebIuEwy64eyaLYVogvx/F2blvzXZOI/n4a3VFSHT10phaQPXn01gA+OUM0ZY67jckRdH8DrrkcuUArhLrQiwsY6f3cWWzEpsi89LQ2RKKEbDfq+LS+D6TnopCEw5CVKsgz/KI+hSSaRbItI5q9yDaNRHMQT9DMe/3Hv0FuHSbS2kWLLw5+P4a3E/2JBLHOXlbEYrW/t86heX143QUSXb20NDko5jTstjzJlnY8viJieh4pFEJ+JofeFsQ/lyPqbYFQF1osh2FZJNbZy+7JCS5b/WbiJLv7aHbNrGkTTZ98PjbGO1fjvz+C7vHw3SUrf31Zv5lH984hurqqVI5wGCIa+NZRSJYniFkVgol186c1+SADV25Nk2uwEmgskd7ST7PLZlJIBgdNumn5eTUlMDq9EGrlxQr/JxcwNkNgWCTQRsJY1uzqyLqOPjoKTkt19SyyCQJDkSiER6tCPtEohmYgS5A+dIy/u/8E3y0/qxg6kcUo3Zqd+EICwhqUSkgL82Avw/o6OhCRKJIiQdioxl9HSEhPlLAIneLREQ5HCpzd6kREylDY1TSuXS0Mh1lMlchnsvz04VEuanfWrBCWdBOK3JBat2q7bkUy09rB7Xsm+Wjvxt+Nkr4BgaFFYxjZImJkhHjRwJc1d4XUbB49HEZeKxBjCJMWsi7+7LJOg243fbbqE62M9niBCAw1VTARGK5qPsv5HJnJaRpKBdoWp2GRjX6EuiKeYKJ53vfjCW7otPG+87t530OLXOYqsJQp0veJuzj+1oH69p7nTpuiaWhT01Bag8CYnjF3Tdfk6Snbr3dvFYGxkMZIZiFa/WZ9OY+s1yIwtFgci7FRHAngjt/t48o226ZpkDMqRjpz0jTOz65w+8QSuZLO8fAse61D+L6/m89dEDQnaZt9YzRKq7fE47MZ3u618eTDz/LVp6O8t9fCFawL6/KluBxh90yWq3tMWNvB8SUOHEvyr3tWeMNQIyKiVOBzD89lCTXKHH7iELuCjrr2VtOUP5Hkq6NpLrjAgYJJMXr7bVO8e9DO+L6j1ff/iJ10qVBAl3QIh1EW0+haHLT087O35p5e0FGEgSNXhryGw6jLEYoO0ApZrPms+e5z2Hw8vMhF6+xHnj3C3VNZbtzmqXk+vRRBDbbwsq8+yF2v6abFZWFq2USrBeenaEvmWEil6Cu3XzblJOVgNX5vLxe90LqxZhdWOn6cN3ZbGdlziG1/AgTGhZ+7l6fe2Ffzu2IYZt+UqyLq9MUEamEjAuO6X0zzvavaTTX/VcHNskjgqaRHyhdgphaBQVKHpfJO2qrNuTSlVAnsVNOUVlEwMCIRlFGxaRzyisUUl3VZKvbEXBYpl4WozsHHDvDU4QRH5jO0OyR2/3k/n/39IX4mwT8PyRvsHVzK8/m9Eb5yiTmguUBOI/Q1bSLVNBKNmoKTAnZJGS66bZGbry2xw29n/1Kesy1Vn+6Zy/KXpZ3IX3mQj5/t556RHDf6OiEWwxWz4s6qvLa/EV/Mwvz+w3SsGQ8QDvPIMzEeuK6T6381xbUelQ/9aB9/d5aPr8sNYMCN33qMn7+yi/n5KHc9tcL/HEluEJQ71XJDOIyIRpGO1+kb61xvtcJP73mG9+301bWXPnSMRpuMVFI5OJfiz4aWuOflrTwy38jbfr/AU9NxPtbl4kAkAWGBLAyMsXGa9CLJsSlwFzFWLEjJIgk1i6fRWW33CwVEUodMmcayinAAYhMz9FtkDkynaXYcxqKrHN5/nJBS4ItPTbIwvUi8qCM3exDRSBn1KtAzWWRdRSrIJnzcBWh55EKBzMQ0fTaD2ekF2hssJ/XhBp+tQ2DYUsmavlYun4jyF80F/r08PiilVfRiiXhrF9n9h+lyW8uUAogdCeOzQmxqjl6lxNLBY9x6PIUsDNLJLLs8cWYPJuhqM/FlqYkZuqQiqcMj+Ds6kOZ0jNFRfKJEPFKLbkosRelzmnF4PTZEJgMpBUTO9NOacWzicBjfGhSAJASxSJJBu8ITC3loyoMwyI+M0UaJ1Pi0KZSolhATkwRljeWlONvDYfSVmInwWNMPaIZgJa/TXliDAl5KkssVccdWIGzSAI1EErlYuzOuRVNYM6YvRVn4TyqaCIxX3jXLEw7FpKatQ2BQ0itjNLEch7wOagGIQFhQOpHG7nIgoqvjZYERjSEJQWpyBq9WQI+oJmmljH7OWTWcWnXnWTIMxMQETUIlNTpRFfFMq2CXIZfnpp8/Q6tLwZrPIaLVNOmJEkYuRyJSwqtTk3eFI8coqGtQLM8DgSHyeaTjxzev7x0dPHRghr/c5mE5o1Ow69hEfcR45X1hkBybol8zCC+m+chn7qHBKpMcGaXbIZEKj0PMgZbNYsRVPJJeuadmc1iXlrFoBipQmdOUy47XqJZdPVlC0VTizUG8RrHGz/rYOE2opI9P8FQqycqSjt6gYsuolMo+NaJR9FKKRkMlPTMH7izabBrD3chMeIZEUeelliRGPIG0Dumzdo70fBEYRMuC3qunmzRQH4GRKiGrZRFPVSU5M09z0RyfGYEgSrHA8rEJWqTyHCdRwsgXWD58nEi66g+jpKJFY/gtgtiR47T47JSiMWzCIDU+QwdFllu7aA2HsWbTqHOa2UZMzZo+SZYQqkb86HGi84mavjFx9DgdDonsUoTVs8KMEZM2tcpUMPImAuMLD0zz9mDJREesIjBErOrTuIG0DoEhluMkdEF/oPmk848buxUWlxMMNsjED4dp9tiQEYjR0aoGRjSKtiIwlBzICV6s8H9yAWMtAuPuUhMvP70dAEUerwp2gtkRWXPmzvzaHYmZcqOwHoFhHKbY01sRzSEcxugbQJanWGnrZjR7ovK8yzXPOC5aBzuJL6bNVd8HFswKsQaBYVxwGdKa1crVVWApUbsLrs6nUCyLzLd088HfPsmj/3Bl+fi6JGJ4mK89MMYHKjv95kpaZi7JOQmVj7/jTPo+cRcJq4t/2t5EdyjELbsnmEvk+fTwyXfntJ/8HIujr+6qsMipSHKtUKCaUTEcKRLd/Vz11Yd45s+3mKvQ1iXT97dXERjm4s9GBIbwFJHayjt/5fiMooasTL9wBIYjhtHfDx5nxab8WJJIUwBv0eCkq66bIDB+mXPzv2+/gLMLyyjbtpLdHcMfGuCS9gWCZ/r456NlnvQfgcDYMxGlIJ9A61yz4nnrrXBtD/wJEBhSYR4jUYv+MewxLNZaH6jJElaHXlMucn0DwBiffjLClGMGQm+vG5+czGPM5U6axv94dIlfjJuT15vefimFT3+GrSNOztnZz/Vndm4sp8dGTGGzmeO07Bpg7ufTvOqaXbzxO3sYXS4w4GniivU+WJfPx1YK/O9UnuGzttLcYOU7Dy1yIJlBkSX6BjqZteextm3h24+Mc8feZV7a3cBeo5Fdof6KvSONbXT7XDQ5TOi0GB7mnsf2csnpXYwpRX4zJaDM7x1o9TDVEEB3ONnV7eVY5CC/HTf4xCu21U3fyfL1/HGDG1vM/JAL84j2RojPn7xcn6TosZD6AAAgAElEQVRc6OkismUOuamR779tO4RaeJ23g/95+Ah9W9uxLBrPvfMGvPnmMaZeU/v7oruNWx8+yI3X15bd7DM5SpNR+ju38aDWyI9/P8N1HY281GnuzncEsuzfcxRCIc7+53s59M/XPmdZf/PNY0y90Lqxbhf26i0q//Dzg3xtbh7lBdbnute33kpC6ybfN2jygcu/K9YTGP0DPLj3KC8pI7r05Ym6CAxVKaAM9Jv1tiK4aYoEngoCQ3LFEd3dMPgcCIzMLKqcAX9VzFVdyWBR5is7npvFIStOU1zW46giMFhGntJYdjbwwzGNL7/tYj6ZU3ntfz2MZdtWPthd5MKbHuAtW7sYXGdPswawHM2ZIn/MsOPinexY+43rhMpMcdhxLrhsJ1+R4OZZQWQkycPHV8wFhFCIpyZj/GQuzeVygoeNZt7ymnPwHVqEUBeEw1idbhrTRfrO6+eK0gFGGoJ0rO4Ileu7OhXGvWMryp2zDJ+9jXdZPLzx0n6u3vd5/tx7CX9x/hbe/fgc53sUfjlV1v8ot+MjnnbuOrjA3730FNr11TZ7XTk9WT5/9KIQX7p7xEQIrkNs3PLD+/nM1CQjn3sZsn2BvCLhPM1siy4PCRoeXiYuWWk+YzvR8UPEu/qQZVPc0DOmkfT5oDGHkB1IRgrDbUc6dKja7j8Yo9DgwOZyky5oFPoHMZdu48zbPbzt4j4++v3H+O4DK6zkDR5JKfzrrlbiR2ZRfM3cs2eGXZYM7vNayRZ1CA1jHEkgW93VnTq/wLAHkY7kyAZb6c1oPJKUaPd5zPLwQhEYk6Kmr5WEQKyiR8vjA3Ulg9URYd98hh8eyHHL289DK2oo8gTRYAc+b5ZUo5ezPFY+sCeBx2lFVhRwOgmds41Xf+1RurzmAsZKo48Br0yqM4h//g5kax9iYJDm4xpx21oB7DHizkb6ttiIt7RBrw8xaiIw8LkqPhHlnfdkezdNxjEIhfj0rw8jyzITup1rzz2Nj379MQhakGSZeFsXPb1Wks1O8OSR7Sqit5fgtM6KxUSj6NNhFFki09uP/Se3YQ2FmFxK894fP80fXtlWTWNsisxYioYtXRBqA8BYyqO4cjX1U7c4UYoJCIWYTz9BoX8QybGC6NlCT9MyJ/ydeDo9FRFPw+VC8rkgrwIRvrGgsGJvxOKUIJ1AKrdHucQMzvxhs30CCA2jFXUslgwJT4Aum0rKreFdHXsnl0HK17RnsjJNsbuXYItKMtAGD84jtl2NZM2Dw8p8ZpHXXdLLxErG1HfxuZCIYgwNoy2nEftSxK1WvK2OmrxL9fThcc1W+9JTRmBMIhzOk9f3W29lztLPJZedzr2HF8k6syhDwxXEeGXMVE6LKeKZJuENsqPTw2e//TjJkkFJSMSCHWwp7SfV0gHDQdQ/RFCbGmn2FcqCvi3oT0cxgkFzQansZ8JhJFsJ0dtL87RO3GaWHWMpjWyPEoul8Z5VrZOSMkWms4f2NpWwrZnvHlwiXoJXX9gK9vKiVCiEGDfQfC4aMxrpMkJLy8wi0s9gbW1BTebN52JFZLuo49MXKOIZDvNfvxnjs9edZqL/NkNgrGSQ7VEKjR4cLkG+2YcdiHX18oulx5G7nax4AgTbLOC3YzR3YNhiRPxt2O1VUWChzBJ3NtHb4STW0gEDAUrJEnanTtzj56JOO2++bYm/TjpZEHZKgSCurEqmyQehYfTlNIZlmXhLB1HFRD1nDh8D4iRaOwlt0Vl2KGV00xiZ3gHaOEamd8DU5fn9CprHg7+hQLTTRIBI981DZxeEWqo+jWiI9QiMpXHiqSJN0eWTzj+scoSFxBgDvQ3E27ro6/GCPIEYGII1gtdaVMPo8FfakBcjvCginn/K8N4fP10R3lSkjefNKjJ1RU7q6b5YMM/E/cCtz1BQzUqqGwJFkohmS/id5sTk4GwCWZK4bybL+auwf6piQmuDKYZYX2TmSLTIY2XBMd0QWGSJpVSB9jLVoaQL7BaZeE7lu49MlOOofky6oOG2ShX7X3jtDr59OM7huSRLqYIJI10Tvv7gGI/N1wqqaULCUkeMDEyRlvU/maIxgmi2RLOrKiikGkZdQbjNBGHWu2RVuOaFBq0sZvOJXxxECMFKuojTKnMilquIaj3fcPveE5zX56tAv2PZEt4GG4oscUWopUYc6oWGr9wbZjReQjMMDs4mmI3niAoLT03GscovfvWTK9i4atB0s+zV3DM23vvcnUcBeM/lAyeNQ5Ek9Dp1bvVM+cfHI/Q22Tj8mWsrvzkkwcQXX1FzNv3acMHtU5X/7RYFTYDfbcfrsiFL4HUoNXXjV8/Mca/eXLkuaQbX3znLK89o5+mZON97ZILPXBDkRCyPy6rQF2jgcLTIa/77UVbSxapQWkGt2BACfvLkDF9/YKxybzae5+HjK+zsbmbvUoH903Fu33sCX4ONniYrk5EsNz82xRd+d4xX/XaWZ08kGH8BQl8Oq0J3o1neZEliVWv4VMRHHx+LsHt0pebeqpBiyRC0e8xB9WBLI1nVoKQbG85Kj2VLfOSOA5xKMIRAluHAiQT3n6iKCmYKGtPCzjXbWllIFjijy8MFbU6+81bztJ92j5OxpOnv9EkEtP5UodFhZXw5ywNG83M/XCc8NVm/7ALYFBnVqIp3/ebAPFZFpqQZ3BpOsVIWSNQNwRqNr0owjI1iZaafT63NVOSNYtb1mltdiEo9BbPe3HT3CPM5jZ/tO/EccbBBhMsUOzN1Al5+ehsumwWLUm0f/G47v3n/xXz3cIIf7pmuTYshymJoz0/Yy2lTeElXA9dsb6mpa0II7juyyNfedBY/sI0C4LJZeP3ZXZVnLIqE22FugPjsCvGsWmN7JparnDqmyKb46zsvNRc4A5KGzaJwbq+P+USeT50X4K8u6gVMAdSDkQLv/ME+np5JkC7U2n0xw2kdTdx3dKMI6a16EN0QXP7lB5mI1Ip9yrLEV/5sZ6Vdec/lA7ziv3ZjYIpjN7usVbHyOv16QdVBgmPxEgNBNwdmE3zr4XEmk6ZwpAC8DTa+dnkbrU0OsiWdoqbjtMg8+cmr+Pz1Jh3xEcPD1dtaK12UWDMukCr3zH4sU9Doa7Kyki5SLMPoX2h47ZmdNddrx2xSOWZNN8tjAbkirrjad8ayJVNgUQgubHfxnRvP4a8u6qUv0IBFluhsdvL7D1/GQNCN36GQyqt0eZ0Vn4JEUdMJNtpJFGpF8ZJFg4GWBvZMRPne7gl+M5nBsU5cUy+jXZN5lYCkMrqU5lfPzpNXdRIlnQa7hR++4zx+8tQ0miGIpIv0B901Yq2GgGCjnZV8eewrzLHvp355iLsML7C52HpWFTSsEZw0n9u8vXqlHOfgbLIs5gcBp0KsLDK6mqDVciaEYCRW4sv3hLnn8GJFcLWoGXzhd0fZNx3DQVVEVDcEy3kdt91CMq/S63c9p+i3JEE0W2SL31URNjWTYVodTZQYanHzqVduJ5Ip0RdsoM1l4fuPT/HUZAwhBImiXjMmBlNEtMnx/MeJsgTGKUjIquVy32C3kFGNGh+vHTNVv7M8l3HbOPAX/dzy9vPIlXTi2RI9UrFSHjTDIFHU6fG5SJX7YlPAf2MaJEkir+q0NTkqfq6KeFoINtorIv+SZAr6dnqdfHf3JO/b6SNd1MgWdezWav01hNnuWOTqnE4zDAxMCqDdYpZ/g4392IshyP6Gc7o33PvB41P8eCRZTl95fFgyKkKblw4F+Nf7wuw1GpEliUi6iN9tq3yPJEEkUxV/XfXdSl5nsMVNPKtS0gzumc5iU8x536tOb+fb1jFu3XuCJyejFLVasdzV+Vgip+Kwymi6wTm3TgIQz6oMtbor9RkgmVPplQuVfs0QZtp8DTZiObP+1RPYrBcMAfFs6aQingCnd3p4aC7HJYOBimCzOQ2pjUPTNx7E8MeGFwWBIUnSy4D/xNya/J4Q4kvrfrcDtwBnYwJ2/lwIMXUSe68GXj0QCNDmUlh69iidbisyYBwf5UBKZWfQYcJaNR19bIyfLeR5vc+EN4loFAmJW5byhBbznF+G9VmsFtTxScLTEcb3HuE0MhhFk0YRCU/il02I0PceXmQqmqVBVfDPTUEkihgxoFQW8bStoZBEo2CTIaxXYTVlGNujYzor42ku1qNoKwUUXWNxZJJ22UxncSWKXRKsHBqh1SGBvwNjJFyhZeROZAkUq1D9lvlprvIYPLM3zHf3rPDFi4JgrdIAwqOLdDbXCraUWlqxpetTBfS8hixMCOHqhGd6PoaeU4mPjOGTq9+kFYoY4eM1kCyxWtnWQ7SSGtJSVQSIcBhR1JGFsRHyVef9evfUbA5jbJy7D8zxEW8jP3o2xspyniPTUf7ywoaTw8bqUEgUCc5pFDWwsVimiG9uCspiSi35ZF17IhKpHeCt+aZvHIzztla9IlTYpajs1wTF6VmeSKvECjoXeLt5/OA0VsHmUMB117f/di9/Pty0+TOrFJL5DEYqXUtfms9h0aqw1XTJ4POPLWDRq7BuPRLh4SMZ3r2jmQ/1CDixOcxezmsYmY0UknN/MsH+N/Zx95MRPjskIU2Nc/d13eZzHR3Io8eJLEQZf+oQA2voEUIIIgV9jS8EP7nQ5JjfcYWP3ptjBI0CY08d5h8eXea9Z3i5ezTFQEMbFx06xrW/muGcVnMxrzcX4+mpApIQ+N3w3ava+dijS3Qll/jldJwvne/D61C486BOMlOgKxpl3yPP8tPRNH7nVn667wRvCZlCUn84ssD3Z+cA6Ews8duZJG8a9NIWCvK5pyLYMykWFlNc0uLgycUIDQq8pk1h96NHGNjejNHegRwO8+CJLFd0N5wcUhqNVqDCykIGPWtlOZ/ib343y89e2VXJ48WnjxAt6Jzmt1fenwonORgpcqkRq1JIMiqKoaEm09hmpiBpdrTtFPngbc/y7h3NlXwhHCaTVnnq+CJ0bRRsEiMj/HAkyVu3NZt1cTmPUixyYH+YYwspruo2n88n0/xI6eIbTXkCTgtgq/lGG1DI5GpgjkSjlbq0nNPMOlenfRBCVKhH7/3mQ3zzyvb69WDNPbEORg5w98tb+MTPOxjee9g8576ejU2u31Dn7PnVfFFmDfTwaEVk+J/uncAQUBwdJ50rMrrvGEmXhchMCv8ayO2qfUlTYWICVqxVwU3VQKlHu6tH78gX0dfDQpM6wrqOQrKQRI2V+GGihHcyzRkBB0dnopR0wdcu9tftJyppjFkx5JRJwVy1dyKLkckSbDC4UkpAOIFS0NH1aj/UrwtuH03R27RgHt9atqcVclgKedSJyUo+r43vvFZH/fSU24mX+eGXjTKzcbj96Xk653Nc6BDYxkc3wrnLNiyZDG5dQDhPcy5BPJoFd7by+9x8jm4JCOdQdB3n5DiVVf6ODvIreRrmZ9jzum6IRnlLoJn7A3Zu+uk+Cvkit1zRwaFokSceOchL3RvzuW4/VaecnqwcvsouuGlflB6/ThnrxS/H0wy4oLnRyTmtDr52oGBC9Ne8ryxkMMpw7G6gUCiRKBpEjo7SrRZIzCVBEYhlBSlZgoICjY3sf+RZfjGe5thcBntG5pvDTbz8ch+fe2qZD+3L1KTNlYpz+0v8/JtHcDiSgahaOZfo/ht6ePtvJuiPzTExschd96YxsjnknG4KKZYh3YaaR8rnycwu0uNRiSSy5JcknMpJfLjGR/qxEeRovKZvHQJI1Hk/HEYp5FCPjaDFS1i0EgmPH08pWx736FgRxCZO4FNLSLEidjf0KBI9NvhOscBFLpNu6Qfe2AaTU6CuRPA48jw0n2dXRwfygkby2BjthTwLiUyNGH08muTsBguffGaFgm6wnFU53Z9GFNPmRMAl0HVzsyk5Pk2vW+Hvf/Qknzrby38+E6OpLFbZDnxyp4f3PrjI4ug0O/x2JhayYAWpVEJMTuJIZiiuUiMiUWSbjJxWUZt9Zn2OFZGKpVo/LSXJFTUaFudAN8dnejKJVKgdVxrLFpSUWeZ2dTTylp8+jUUGY2oav6QTHZs226ekSSGxqSVOJBMMemy8OWThv18ywPAt4xiRKF6jiL2Y4v/tWcFrl3ljowsRiXAsXmLX7nE03aDDbUVEI3hlB7+ajvNhzxr6tkVjlYJS0AwkQyc2OkWvKkjOJKsUkqwGNpnJZIn+5CKEV3hsLMLNF3sQPpVX7B7FqkhYZYliRsIpTJj+6uJNKjxOs6Sb4oXPi0JiIPKF52wf1BkN68Q4rckCS5kUwfBxUxz62Eh1zLTmfdnQmZ1coK1dg1iMnW6dGwYaWZk4QSjgYs+RKVbGT6DlCsQiOltkB1MjaX41N8/IUoZzbMtUVp/DwhzrlkpEwxN0lzQWkma90KNF5FKJkruJQDZO+sgITy7mQTeIjk6yTcD3U3ne4LNzeKuHqbE5zmtzsDuW5Z779hNbyNJWtJtj83I+afNJjMZG1OUVbOW6KRIJKBZry9maOdJ6nzWUCs/ZPmxptOKYGDPfXUMhOaEaBEU5rkQJSS2RiiZo0k0/nNsjOHe7jdc9K1NIZ9FWBHZJQlsxWJrLIpdKRCZnaZc1SkdHWMppyJrKykqCoSadv/3JGP95eStf3h/ldL8dfSWCPCoY7PLxy8v89H8/QWlxudYnkQKGqhGfOIFXLfK1n+7hXJ/C7hWN+eNTnNZkZSGS4r779gOQODZKX4NC9NgoPUEHRr6AFjfwShrxkXFIusoUkjkmU8v0NlmRYrFNKSSx5TyN7cFNx1gAHuBH5ziYykd4erkAUtwUEh4tH7pQfl6L6RiOIndM156S+MeEP3oLWJIkBfg68HJgO/AmSZK2r3vsHUBcCDEI/DvwLyezKYT4rRDiXS6rjTP7gywGTFiWIkto/QO89nezFPoHTdEamxWjr5+PP75Crslrwlr8AQj4OVSwMOXymfdCIWxqCa27h9YWDyv+NlN8ZWAQWVGIeAIMtri5acKgv7+dL91wBud3NUIoRNdQN9OBbmS7DaO9gy+M6Sy2bYH5eYTPhxQMcrSxnbynHH9HOzQ1UbQ7sQVNeJXW1Y3VZmXB5aWtqwVCIYoeL3a7jWV/Oy2BJpifr4rBhUJo7R0o3uYqfCcU4ortbdx4/Xl858az+eTjK/z9MY3ldpPmYbgbkRobK99LKERhOYJ9FVYVClUhmKEQxsAAkiIz29LNDfdHiXf18Vd7MgiHg6ivDa/fA34/h91tqLIFfXCQu07kK++LoSFzNTgUYr+jpWJfNHmQ2tpq4jMGBpEtSk38a7+rJn2AGB7mjrSrck+12jH6+mhtbmDZ0cSyrZH5IuSFTEdXsNbGKuVj9W/t95ftKbIMfl9NGr/8ZztNyG35+lXX7MJukTfY+6unS5wIdtf16Y/GssQaPOhDw5wIdhPoMGkj8w0+RnQHXYNdvG0xwLJuwdrk3vD+ZteHdMfJnymnUe7sQLgbK79P+rv48ZyBbLeZ+TA0zDP2ALtXNCxOJ2PeTvbZgxzDjdNl553XnYPjtG0bfbgmPmVoCN3VsOH3RNHgG/MKV18UQgoEIBRi24Vn1KTvP955KXelHSTdzXzg6Rza4BCxrj7zyMJQCOE337toa1tNGelubeautIPLdnbz6X1x7p3J4sgkGW9u5w0X9rFgmMNkW98Wis0+lGAQ/H6uueYsZIuFzl3bOJyTCGzt57QLTufz1++gpFggEOCxUgPves2Z/DjhpKQLOvs7WWjrYV/eytMRc+fNPjTATEmmY1s/51++C8nhQPZ4WJIctAxt4S+u2cFpAQf+gW5ibi+fH9W5fqqZ25JO3vaHhefOZ3+gci13dWL0bEHzNDNboCaPHxUe/mfWqHnf0dVBweXmSWuAfzyuM+Hr5J58A0s5nRM4sA0PVmzccEYbj3/8Sr59OMH79mc5OGtCfgvdW7C7HHXr56S/i2+PZCtx5tu6cDW5ibiaKVrs3ByxcVepidmihFEsEdh12qbldLi9ic+ENewWmbtVD1+cqH7febdP1Y1fDA9z9e8WK/buns5uXg/W3iuXpbXPyFu38pnSMX4Wt560vtW9LqelXt2z2iyo/f189GCBgsdLa3MDWU2Q6+xmIODiuK2Z+wsuDmRlVMfG9shit6H19tXUFX1wEEWp02bWuVbcDRgdnbXPeDzQ1oYYHkbMzZPs6Sfq9qE2eZgVdiatHmab25jLaCgSnH7RGSeNQ25vx+jtr0mj6Ozk4bkclwxUn9f7+832tXxt276V3a/fgr+v06RoDA6B34/W0YGl0Y3a1V23H7jjw1dtSM/uv7+i5vptLzuds3qaOViw8P/2J7nwsjXtTR2b1u4u3P09EArR1Bog3eit+X2mwU/XGeV0261Yt9Xmcw4ZV2gIy7at4Pfj27md1pZmXndZCGG1suWcHbzsmjP54oEUpWbfhvjrtdn1yunJrqWtW3G0Bnn5w+nKb8dlN/+tH2H7YBvujlauPa0Vw2qreV/p6kK3VMv9/77jAgQw5vDRd1o/wu83x0TBFmSvF/x+kuk8H3wihqvFT7pkUJAtuHeYon3nnjlIV7O5VN850FWTxl27BjAaGmr7jf5+7LpJn/inN5/P3zy4yEjRguz3mc+V20DR1Y3kclFo9tHbHeQXH7gcyduMkOXNfbjGR5P+Ltydrc/t03L56GvzcKyxDa27B6vLSTKRwdNujim0vn4URSbu9tHcEUT4/DU28ooNZ1nAllCI8y/fRVezk6FtW2g9fZhvHUlwaDaBZLUw39xK+/AWvjVW5CHJx9fnzcH9suyk5+zt/OIjV/GmS4f40FkBjhQtDGzdgiUY5KZJMAaHkGWZRHOQvlyMM4c7eMOrzuWanV0EvO5K/KedYy5pHdYcDJ17GgdyFnSvD9lhx9jSa/bL5fGQ4fWhtLTQEPSSjafM+rylF8lhr/VTawsZHdzD/ZV7Qz0B3vOy02v8qgWDKF6zPnmXZjl/WwcFxYbo6cHvcRJtLNcHjwfcbmwtfg5kJLbuGqStK4ht+1Y+dm2I384WuWZrCzdefx6TN72CrA7RdIGWvk6+eOOFvP/qYQab7bjcLvD5ad02yDfGCux3BHkwpSA1NYHTWalXH3o6hybJLDb46D99gDsXNO6YKbEno4DXh+QP8OGzzLpMKIQArNu2YgsG+MWHr2DrliCy0wlOJw0drWR6ByrlJ9XSTleHj/SW/o1tzknKniQrCMdzj+lUAdatIULnbuf3CUulT4h399Fsr7axAPj9lIREyd2EtNVsnzxnbOfSc/p5tmDjovgktpYAn3sqwmJRELU46dnay92LGl8+kGR/wkD3BZD8AR6MGPzHCYn/N2qwkDdYcAdoD/WStzqIdPbywT1xZIcD0ml2nRPiXY8n+NDuZRYLBiuNfnp2DLL741eB38+H/uw87prNc9GlZ3Bxn5f3PLDIY8sq+mpZLOeT3tKCSGfK7YB5TzR5kB0OtMGhypzPGB42F5Dq1OemNXVhs/bhoU9eY9percvl+aKrNUDOZuaJ0duLbLeTtDUgGtw42loqNr7JUc4KtaN7/XQMdPH2Z0r85X0LSA4HuSYv3S2N/CrbwHsej1OQFE7gYNtZIX72ngv5jyMZXr6lgWZfI3LAX0mjvHUrAAWPF8nlImJvJLWlnztTNrBYSDT5MJqaaOxs45MXmZs3E7Kbiy/fxb6chW+MFrApMkveNvryMeKB8vjZYUdt9OAPNhP3m/dkmxXR2clbHlhhOtBt+sDrhZaWGp8agQBxyYp7ca7Wh5uUbe9pW4l7AuXyLWEMDHDjo4nKmElrbMJob2fW7jnZ9P95hRcDw34eMCaEmBBClIDbgOvWPXMd8IPy/z8DrpI2412sCQvCznW7OllKmbs2iixR0gwGW9ymWnn5niEE7c0OlnJVWLKEhM+uEMlUYWsWTPjs2nPMi5qBzSITSRf5wE4v77tikA9eNcQbzu3mH88zOXcX9vt5MLyMwITjjC5nODxX3p0vQ+luuvuYKaK0JmiGqJxwEMuWUGTz7G2H1ey4ZjMqdqvMcqpIa5PDPEt4DaRSNwSWspf6Aw01ts/e4sXrsvKhXT4++rOD/Ms9I4wuZZCBO/aeqEC6ikjYLDLfenickcXaM8WFMAtALGtSHBbLfhbCPJu+zWOnoBm86muPVs4j/ht1sGLbENUC9LpvPl61W/b/8aV05Uzk56KQ/OOvDlX+lyXz23/9rLn7fWClgGYYqLqg1eNgOafhdVlZTBV44KMv2dTmyYIiS/ga7DX3rttVCzMNuO285/IBHtab+PufHSBT1PjqfWFm0ipFrf5Z7k1OK6mSwW8OzHHplx/kwn4/TovEj/ZMs7PLw5vO7eYh20HsVhlLmUJyIm3Crh45vsJCMl/Xbjx3apBkQS10a/90nIePryADj45G6P/kXdy+7wRnBu2Mr2S4+t8e5r8eGOOXE2l+875LCDbaN7W9GmR5I4VkFVqu6gaXr2p91AlOm8KTkzF2/mQSt8PC4Kfu5uzP/wGnRWK5XP7qhe5GC7tHV3jrhb3MJ83ntkhFnhiPctXWVl5/dhdDzSbdZDFVoLWp+h2yJNHssjKdUgm47dgsMr3+BnQBVlmioOkMBN0VJEBfwMV8ooBNkfjdBy6lwa6YdnMabWXa1ir9ailVoKXRwTm9PppsilnGhcDtsPBSJc7Hf2GW6/Vnz68Pa91ptcgUNaMufFKRqaEK5Es6o8sZji6k+Jd7Rjjd7+Czdx7lliem2NXdzH8+G8NlrUIaXVaZjvKkY1t7E48bJqonU9RosFt4cDZLtEx30HQTYfX0TIKztngr3/DUZJR4rsRKpsTHzvZzzhYfv3h6jtvedQHfK0P3Nws7fHZ+8MQ0NovMV+8LownB2HKVBrCQ1TZQWWbjebJF/XlDRzdrbRySwG23cNtTM5vaFOV0LSYLlHRRaTuv//pjfPiRjfB9iyyjG4KpSJYnl/IEGm3ohmA+kWfIY+PgbJKbH5tkKppFFSJxNh8AACAASURBVILb985wxxrKhkkBqW1TKiLJ68LfPri4gS5Sj0KyGm66e4R7jWZ+d3CBr9wbRgB2RaKkGxyaS/LF157O8bcOVKDbm4V6FJLV63Nbq3TGJoeVz15Y2wbYFYnpaJYr/vUhrvjXh3jlr0/wn38wy0ppk7a0Xuhe1QUohwv6/SiyxGv6G/n89Ttw2U4OKm1tctBd1imoNwSZT+Qrcbgs0oZn8iXd1DlZEwqagd2q8KNrO1FkCbtF4Y3n9Wygu24WXgioti9Q9cNyqkCwfOrPKmT/ul2dG+wqSm27vau7GZsi8fh4lPN6fRQ0HdUwe49S+Zv+0XKCr7x+Jw12Cz99z4U1dN2X7WjjU+f66fW7aPXU0llNGpzYcM9WTlVLo4PfvO9i9izmKZbjqvpDVNo9pUzPcNkt5EpmGzATraXJrg9X/9vDNDpOHVz80h43vzu0UKFVloRUodhphsBarpujSxnzKNE1oaDqOC21ZWQ+o9Hjc9HldXHn+y/ltaVtLKWKHF9KM9Di5uBf9PHAsWW+//gUADnNqJTbGy/s5c2hJh4Kr/CanR28/6ohZAm+cNdRFFkili2yVcpx9haT8pEuaLht1Xrb43fx/p1eSrpBg93CGV0eBn4wjqobxHOlChweqvRpt91KuqzrZGwyTsuqRg2FJOi0cMXWlppndKOW8nZBv4+JSAZDCBptcoU2uNqEKLLM0zMJzuiqUvrecUkfy6liBR0nSRJ7P3k1j+lNXDIYINho512XDfC3O734GmzIssT2jibuv2ELH7njAE+MlxF9EnQ1O/nULw+RLqrMZTSOLqTY1t7EJ1+xjX/TOvnDsWUAGuwKb9ten1bY5LByXp8PqyIhMCk4D4dXWE4VKpSeHp9rw/jsn359uK69SpCoS9dYH1RdYFUkAm47bqtMKq8iS+aY3b+OOl3UBdmSzo7Oppr7kXQJSTIPQXj/lUN8/23nksipHI0VOb3Lw90fvJTfvP8SUiXzCM8ur7NCPUmVDPKqzlQ0S4/PxdmtDt7x/b0kcqo590LijK5m/vvNZ/KlG05HF3B0PsVwq7tyEpkiSRQ1A1+Djdf0N3L4M9eymCqQLmg419DCVH0jscGk6Jvj2Hf/0EQZ1Cujq/14k+256eSrbfqOTg+PL+SqGbHGpknZkkiVDO4fWa6hIbZIGofnknR5nbz+7C4+fKaPiwb85EsamiF4Za+psXj5cJCVdJHjZdrdOb0+7v7gpXzzynayRY1zeqvyBAAPf+wlPHMiQZ/HyvuvHOK6/36MWx6fxiKb/nNaTfriVq+Niwb8FDUdiyLzuQuDvPm8Hkq6QXgpzelSlrsOLfLI8RWzzSjo9AUaiOdW58LmnLnN4yBSHuttFnIlHZt0aj1Uk9PCfCJfjsHMu0NzyQp1TDPEhvHDHxukP5ZPJEnS64GXCSHeWb6+EThfCPG+Nc8cLj8zW74eLz8TqWPvXcC7AIJN/rOPf+iDfFbtwStp/Er18h/2Ke43mjlPTvPy+CgvabyC71pH+SdtCx/KHOMCn8y/qR0oknluueR08WGruTL6huU2PuzP8pDhwSNpvCdxmI82ncsh0cC1cpyPJg9AIFBNTCQCgQBCwN+pfdyle/mybYqnjEZCUp63PnoHX7j4RgKSyrhwcFZ2kTc2F/iV7uMBvZneQpwVZxM3KFHeUxpkq5Zkl72EVzIb8q+pbbTKGq9WYlgRvOmJX2K55GLOLe7iqONpfqv72JqYZ8jvqOpKlNOUFjIXFHdxJHMfSX8rVgRnF3fRbuQ501Jgm5xjXtiYWUnzB98Q/2SZoU0q8Yr4aOUbF4SVG/IhvmSf4Xt6G29XlnhvaYBtcp7z5DQ75Bx9yUVe57oQK4L77Ye4IdXHL5omaZVUUkLh4sLp7HUc4IziWRx37IdIhI95zuEcKUMKhZ2pec7zKSwLC68o7uD/Y++9w+Oorsb/z8xsU+/FklUta+VecMfGYJqBxJCEGiCEFAIhFDshcRIIJnmTkEAgIR2SENJMCITQTQm928a4e2X1akm7Wml7m5nfH7Na7eyuim1R3vf7O8/jx7pz7z333HPuPXd27ik7PC/Exn9MzueG8AzaLNupDiylzbId7HbqM89kr/k9lgcX8q75fRoCJ1AmhrjH2MzjcgHvhcwMGyzcaOjhU5IjxpMYvPwynHxyrHi3K5eN2aORb7c5JW5Jm8vNxk7OlQaT+8eVvxSqI/dIF0wr5bCSxm41E5MqUyaGsaCwzbxf1/7CoJWNvoO8lTmdNZKLRYIH2THIu3nVrBDdGAUVXn6Z4bWncleknCIhzJ2R6ewxv8fmcDXrJScbnI1J9FyavYq/mxpT0jgy58DaU3hELuQNJZs7XTv4Rc48coQITUoaB8ImGoxhzpCcZCKTNeygL6cYu2pglugjNOxmZZ6owxfPw/jxPKrIP1wZXJXjjlUH7IM0ZJ7JNwxdfM3QO65MNoerucp1gNqCdMKqwJmhObSoaSwQPKwWXdxk7Nb1rw4sZY/neVZmrmO/5T3+Ginilkg1T+15gB8u/BT3GJspFCKc653JrWk93BmZzjVSL2ucLVBYyImB+bxh2UOd/wT2W97DLKi8KWdxj7+IT1jc7FMzuN3YRvCV17Au38SjpgPsUjLJ8Tj5TG6I1cH5bDUe4sv+Gh5Pb8QkqJwVnMOd3ve4MH0lr5n3kC9E+KKnikvShnhVyaFGCJB7aB8b685hjTjMJdKAbu8l8vSucBmbhvdAYSEdipnXlWxWDrfz+czlvGLeG+PhY2s+zQtyLr80tYDdzjv51VwUmsU75vd5X8ngTGcTFBZyW7iC6UKI84ds5BTmJo25V0lnnujji715fKfEz2E1jYflAjKDPlamhbjIYOeIamRFcCHzBC+bDZ3cJ5cihkJMM4NXlfiOsZNiR++4ey9xHSh2O4MFpRQQQQZ2OWXuzpzN/cZGrMEl/Mm/g/szZvJXUyOqCjXBpfzO2ESzamG3ksEifz93mOs5ZN5Jt2qiZrBbP37cmHeHyzTdP8Za/FukiGeVPP7gehtz4ejLhMfu5Lc5cxnEwIBqJCvow2nO4LCSxrWGXvp8YZ0+4eWXOXHF9TxoOsQv5TKejuTxR/NhLgrN4lzRwdWeg3hyC3hOzuM+uZQbQodR07QfoJuMPbzlVPhu+nx+Y2xmUDUw583nyFmzEodq4LTgXHbF6UyAOf5FvGPZTaag/fBX7Xauzl7BeZKDVtXMEtHDdrfII5ZKviT10apaMHa0IVZWcq9cygrRjTkUYJoZMpH5ZsJ+SyU37HYey6tnnuClVgzGeLhNzuPqcB1tnmfG7e+0D7Mo8zReMO0lgkDLcJgfps2mGzPzBC822Uxj+q5xxx+r/MngbP7Hu5sF+XG+6C+/TM2Kb9Bq2TEujrty5rPR0EMIgYFBNw9l17Mp+r5wjaeC32Z26nBWr7iJFvN27cNSFN+FQSsbDT2sdLbG8P8xUsK/grn8J70Ry8gL4Bjr8K5wmTbmUcxZUWG9r4HnMg7xlJxHrRBg1qvPcPuJl5ElyFQLAZ7yZ/CbzFFz3VflbO71F/C3zNbYs8eGjDyXXsmvTc18KjiL+UE7obR0WhQLnzP0c85rj8b2804lkx/6S/l3RpOOpi9lr+ALUh+rJHeMxtfkbH4nl/J315sxmjsVE9c7ini0SLuYUFVY5Z/LAoOf8yQHB5R0Ng3v4c28Gn4pl7FMcLMxqhP/K+fwo0gFf/W8zYaM1eywvK/jYTw91Zln8WtjE+dIznF5GP/OcWX2SlaKbl6Qc1nRuReqqjhbcvKTyHSaIiY+ZXTyrJLH3cYWZg92xnAsDyzgP943mFaQGRtirW82D1iaqRa1Hwe2d/Zx5oIr+bRo52fGVgSHnX/mNhBA5JeRMi4KtXNTtjPWX7Xbqck8S6MN2D0Y5u7M2bypZHOVdISvv/F3WHsyggAbQzWs9nXzmdzRi7oHhyzsyCjlTmMbigo/dhdwn6mWHxnaKBZC3Bso5CSzjz1KBstENy5VgvZ2NtUZ2auk8+1wNU+6X43NceS83WN+j2xBHnNt3pc7hz7VxM3GTnj5ZVpPOpNTQvO513iYbk+Y/elFfM/QyW3hSpb7eujOKOAXcnlMBhQWElAF5gYX0+R5Voe/OrCUVvP20d+Ydjvrs9Zyh7GVeaIP7HYeym3gH3IR9aKfGt8g1+S4eF7OxYfIv/w5GE0G7o9+YI+8/Ar3r76Q+yMl/Mt8iHJHT8p1QWEhLlXip5HpFPuGuCjbxxWherpVLR7KJmMPOYJMjRBg0atPUb3iptH32XF04oLAIj4V6mJL9kDK+pG1PYIPoNfh4efZc3lezuU3pmZ+7Svkvow2LIJKdWApO7z/ZUnGqfzJ2Mg6aTiG745wORZB4brXt8LJJxNWBe6JlLEjaGZrZktsuBaHj7MzVvOWeTd5gkyvasTh9GLLmca/5QL+YmxEcth5I68GB0a2ykWsb36XK2aN3qg/MJzOm2ll/N7UFJuTu6CYlcGF7LO8F6PpC6GZSKhc5G2hMauYN5RsZgt+6OwkvaIMFe1s3DMY4rsZC7nR0M3f5GLud71FoKCIBcHF2KK/NygsJKJCXXApf/O/y+o8QcfDsd5HZBUu9s1gvilEliBrH2f9PjZlD7FTyeAH4UpOCfRyt3lmTAYjOGes+AbNI2eL3c5QQQk3hmtZLzq5eOgQFBaiqPDDSAVNQYkHMtt0NNRmrsdm3hn7PTBCY3VgKc2eZ5AKCzmopHFbpJJAWOEkkzd2LmG305FfTo4QIUeQwW5nuKCEq8N1FBDmZ289wI9WXcpWuYg0FL4bOIiUlcFfIsXkCRHsYYGvWfp5UC7iCqmfU5zNbMlZTKUQ5AuGvhiPfhmZxqNyAS++9Ss9D1Ot1Wj5D5ESpgkhbg1W8EzaAT4XsnKHsZW5gx1cn72MddIQLYqFr//oKztVVV3CccLHLguJqqr3AvcCNJRVqLm33cK1Ax52tA1S/JKNp+tO5/wTynngzXa2h0+g/cAwbRd9nhO6huiTZ7J/4Uy23r+dz62oQu4f0Mwiz7ByoMdF8JfP0P+ZT1LmC/OPdzoQFizk3zsdLKrMRaibB1UnjZpjASORVgXgLlVl9+3Po6z/NAUDXuyCAIZ+gouWYyrMoMgTpH/ICRetRN7ZhdRkB8XHZWvn8Nj7PeQc6KMtkMa6k+v54uoantnby9wXD+JQDfgb5nHKvGlcJeew+Yvrkf74LmzZgvJ+N2JoEJbNG71NjNJkDMuEtzwH111HTpTm1zxBTr/jRTZt3MCXH9jB0zesgS1bqA7AaRuv4N22Qc3fN9peGfIj/vJVhj55EdkH+ngzZyFLm48woORinrOIpcsqufy3r7EoP5O3WwZxXnMdtfc8if0rX6OkLIcDLQ7487sM3HATRfe+DZu3aD6l+4LI03NxDPpoibhY9sllqK4A4i9fx3HJV7lxh5u/fnE5N2x+CgGV8C3fw3zrswRvvoXQwUakh9rx3LSZonvfpvtz3yD/16/hUo20bbiE5UaJt5/ex0PXrBkNYqqLRAxs2aL9G4EH34SLR5NBPvjLl1hekEP+0tUwsyi5f1x58DdvcLXhCIXXX4CsqkRklfue3EUvJhZX5sEZF+jap9//Lv4KK4qcwdIztWcGm401CfTlbLkF/8O7uXNHF1vXl3Hujgwq89N52ihRUnkSS9cs4OARF3PKcvjir1/CGTHADZ9NSeMIzrcuvob/vNxEaU4a/7LU0zgkIIkif7hiCf98Yjs5NdNZP3da6v4T8TCuXgxFUB7fAeeviFUH9xyAf7Ryzo2XQWHGuPhuj8NnBF4Eqjc/xT+/fz6+kAwZJn3/zU+R9bWryX+8B765hcuBWzY/ReXSuexW8yjY8l0QBNQ7X0C86By6H9zFtCs+EcviYf7Zy/D1Lay450XM19+qzaHFgfLY+xSePhvHe93wuc9j3rIFApB/w1d5/pG93L4oE5bORb39RYSv3MgzfR0IDZcAoP78VcTll/DkzBnkF24AQPnVS4inzcaxs5ulc0s569/9NK6cQSiiYDMbOLtyfWxO/a4Axb3tsbLwfCNUrgWrlUrgwH/24op4MXUEYdOWGA/FT52Psu8IXPo51EOHeLtLghcaMX7zJs6M45v45AGUbAs5JetSynletPi7W2/j2hnnkJdu4q09PZRmiVBTxMF0E7Yjbmhx8Mdvb6A428KJwP4390B1FXPKco563QCINhuF0bIBWGqz8TWpgE89NR16Xby06FTqC/O5OTKP6Xnp8MwhHpl5Ir/+7GL63QFW/+QlANw3bWbdD1+g6dpPIc1qQAcjYz7fCKenyO4QpfESRaXlqYNY38jhltNmc868aXQ5ffzuqT280Oml9cdn8/juHj5hdiPNauCKP73LtFWr6Xu/SadP2LIFY0Yerkuvpco2wO9ws/yUc/lX2yDf/vdeGj63DKGhgaXA4fvfhbQ8yC/QbpvOsHLj97fhUwQiX76a3247xOcROXXLRg4cHkD65/tw5XU6+g3fe4bItzZDNKDcn/79Dr09YYInnsJQr4ud6SYG2ntpOThMYP3ZpPlC/PbFYr579lyUpw5qH9jyC7n5KydSkZeuXdtPpA9sNoRAFsq0LCjOivFweHsHPLIXrrtu3P6mfQdJ+2c7dd/fDECDzcb6mfXUfudpnvjxhROum/HKwbtfwbziIlg5XycTNSBMiPOFbf28apiDOxBmED/nL6uCczQP2PQ/vApf+qJ+3QRAvG2LDl/gV69j2bAe/KPR2iOvNBN+s5n9n70+dls+5l4Za52OUxaBVQ+8zgX+Sk6oymftujoQ/UgrV6MYJNSiDIQ3D8PVX4p1l5rsyE/ugRuviD0TntmB4BThs5fzKPDNP77Ks10BghGZRV8/DyRnjIdChxP1Xzvh65fpaBLecWM66Wyozo/RKDXZkV88DGtPGNVxTh/Gnz42ig/427t7OX9bL/d851J2PWfj+/bZrFoyE/HNVtSq/JhOPBXY83wjXaY6qg744Joteh7G8+j+JjIv/6yW9Ws8nm5+Sutrs3FrwXR+8d/DmNxBEF1YTl/Hp19sQpW0bWZeu4jgjk4snz8LBrtjOPxbnsVyyRdgwajXtP+2baRv3KhlxgPqb93C6TNKwFyOcNEVYLNxUbT/i396l4UVlXD64lGZROcwMq8FNhs3pBWz6/7tpK89BcHYHatTHtyFlD0Hzh79LeB46C0Ks/LgrM8jAl/bc4D7/tFKx4mncsKicm5taeXq1+0M+cIsXbcKAmF45RXYchVq1xDCo/vgjNH9rL7VBo/tJ+PWm0cjfKbgq3zEgOgNwdmzYMsWKm75Fnz3GY6cfR4lLgd/2DXMTeVz8YcVhOLZqOYc+O/hmAywWhEiMsKtzybrk81PIYzsu+h4Xf9oo3LzRkjTMoZdaLVygaoyf8tzPHPZEjhhLqePtH96B88NifDZSwEwbNnC5d+9ijtue47y274z5rrAaiUbeOtnL3PrqTmUrFvEfYM+frLtEO8e7mf4xNOYP7OQIX8ERC8EIHLL9xBufmZcnSh8/zmUhgXw+dWp1ybE9M2IrKfZbIj7Q4gH+hg897PU7Gxm+NMXYcm2wOanGL78Si7rgaXrz9Cy+ozopycPkJttAUOvdlYBc/cfYc+LB+G6z8WGqzl0iMCfm8m77RZtvOiYTb5Mcg/0IV36WbDZODFK4y23PcfdDYWw5bsxHJ6H3qI6MxfOviw2J9OMOrbs7oUTNsRo+oOi0nDLNn5wxSJOWzyHnHfaufNZGxdVqHDySciKQsvi6QQONCHs9eBcuYrcJjssXKJljvzBCzoZyREZbt5G+vmfhjUL9Dwc4wyQgKuef48f73GxYUEZqBDuH2DfyXN5elc36b0ulKwKeN+px7FlC7s2nwmWT8Rw5lqtZPz9PU4/dw50t2nvYEDN2+1UH+mD8z6vo6FhWz/GG25NonG3P4zUobn8zgK+dKCPv/z3AMG6UjhrVqx/ZcK6yrFauWxPLy8c7MNsWsOWW6/ksn4Pp9/9Ku3LTmLdiQ3cnW7igt+9xZAagotOIWvvEVyzToY0D9giWtaj1XFZSP57GHVXt/bxIn7+qdZqtLze6WPzI3tRu5yom75B2b/30rN0DV77EY4c8iMvqUAY9MGPmBKYCheSbiA+pOv06LOUbQRBMKDF/XBMhNgYNSiaUZTJRUsr+fGqYrqcPhZX5jGvPIcuT4TPr6rm4Z1dXLy0kv+0uPn9Ky0MuINIkoAkChRlW3hu/xH+/GYrbaqFfd3DzCzOZNuNa8gwCvzjS8s1RZ5gzpMIgiDw85NKOHTETXaakSFfiDfkrFgkdYMoElFV9vcM8/tXm8lL14wl55Tl8J2zZ/H4davp9kS4dHklAGfNm8bv1k0j3SRRW5TJ3PIc/sfYzt7u4ZgZnmbil5oekyQSkvWmtwUZJsKKSnluGk9ct1pXl2aS8If0ZuxKNNSu0xvipJmFLK7M41snFMRMzEtzLDz6ielcvqIaAIcnRJ3gx+EJISsqF9/7NiLEMqtEZIWmoRD97iCyqpm+9Xoj9LsD/PH1VkRBoMcTxu4J4Q/JiAJIqDg8IaylWQx6Q5ywtQVJFDjiCrByRgFN/R5yTSKuQISDvS5ml2Wz7bzKpAwsk4VAWGZRsYXltQUUJLiQpIKQrGBCobowgxlFmVhLszi7OhODKKY0tcwwGej3az7+E8FtG+byxuZ1rJyWzrM3nsTN58xie9sg3Z4wuzqdMVP6/3b6GPaHJ4zg2zzgoXnAi0EUcARkLl1exdfW1QFwUX326MeL4wRREJATLLdCUdrKc9NSdZkUWIySFuk9BQiCwKs3naJ7lomCNyTHTAJHotf/6+qV1BSO3oiNRK//25mjLkKa65m2PzcsKNPhzU03caDXRXmm9n13xGRRSDIxhJo41y5FjUad9mjRqQ2CtidVVTOnO+KNxLKeLPvRf8flxZlzSnn4sCspW4gh6irQ4fDxued6qC5MJ9NswJigKEZc6yYCo6CyrCafcxeVsWXDHJ7aUEFJtoUbTp3J0pp8Xju/iuK4vTanwDz68WKKYHFVHnXFmrzOqcnk62fU892zZ7Ojzcl3DJ388pJFmAwi0/PSeeOCKn5x8UJW3v4iJ80sosd77NlMJFHglk/M4tDltSiKyo+ePsgrjQP86uQSvn1WA4IgcO7C8liWop+eP5+VMwrGxNXu8FGZn87qMs26Yml1Ps9vPEm3bv585TLaXGFkVSXLYuDNJjul6QbcgQiyolKWk0avaiIUUbj8j+/GdIwzaoYpR03a43V/01CIdoePQNQ9ccgfIjMa8X0k6vwPDO1ctLSS5zet5c4LFvDipyupKsiYdJYT0EyBE1VQlzO1y1simCQh6bw6mrHHg0BYwWJIxrWsZvwzHeD+K5eyu2uIFruX768oonlgNHtHpjFZh49kHYkHf2jULXQEfCGZVdPSeb9z4pz3x8qFHm+Es+ZO4187OsmMmvdLUd2cMjNbChxigin7T1eX0FCaRSCsxN4DRtsmy38Eb6L7kSgmtxUEIckcOceknaMmg8hNZ1rpcIf5545OLTtECv01GJTJi8sEERlDxaUZJzYlj4ey3DQO9rpirienzyph+3dP4zvnzMIRkFlekx91MdHP86qTapNcSCLRd8LRecMZs0tSCsAflsk0TrwCFlXmUVOYocuKB5o+SM74hu48yDFL3HnBAvZ0DVFVkM6cAjP/vuZE3IEILXavzi1r5AxNBdIE+3XE7H4EDJLIHz63hO1tTuYWmPnbl5ZTX5LFq40DhKN6LBEEhEm5VoD2bpb4niUIAu5ghOmZ+swgnrCSlC1EGLFznwR0D/lZUqydgxX56ZTnpTEU1G7tizItXPnn7bytaO5Fw37NVTUY9dd6dFdXLDvD6DyPzXVsRlEGkggOb4iaHCN3PmvjQI/m3jgcVDi1oYSshHlq54KeT8O+MMXp+j0yllf/oDeU0rXYHQhTgP789Uf02WpAyyoX74IBmn4IyQqlGVrbS5dX4fSFMUQdoPtcQdb97BXu3jWIIAgMxbk/KSPW6HEw4n1pHusH0xiwbno6LXE6v3EoxA+fOsi2fUdIj7qjvHfL6Un9UmWe+fWliynI1PPpshVVXD4r+X3p6RvWpKQnJyHz4WmzS9hrD3DugvKU7ePh1FnF/PjT2tWUIAjUFWdyzvxp7HMEaSjNprYokx03n0Z1thFFhUyzIZaBJhUoqnrUenR6XjqfXDANR0DGHYxQV5LJpod2c8dOB++2DkZdlY8ta2QqmAoLjO3ATEEQatA+VFwMfDahzePAFcBbwPnAi+o4visjWUhqCvXRTxeKXv66ugAaG/lCkcqlc400ihEaBZWKgU7uX2xGyU/jxhmVfPLxRv6yIpMT8gI8dLifDF+QYQzsONTDDVUCQqODzxXLIDtotXtZozhgcHDcqMB5Phf3vuJi/2W1pBUZuGFPJS/v6mLmonzUgEzLgIcHntmNGArxxHsd/GFJeqx/JrDRatGi30Yhy+1kd+cQD56sRX8vLyugq7kbSdGiC8s9LiRz6kjFIvDceRX6yMbAjjNyNCuIkfbRyMjp7S34uodBHY0Or7rDiIpCf3svX18UTScqeNneMsxPF2q0Z7qcrMpQWVmaRsv+FlYWGmnZ30Ktuw+TJCCi0m9rZVaawuCeg9z1di87HTJrcxSEoIzq89P1vo1/b+/FLAoM9A9RIio89NQOpmcaOOIJM7DPhjVNoeN9jS5RVeg70Mwqi8qX/7KDS6pMuMMSh5qPUDFDnFBO42Uh6RwKUSMGmR4eYrrDC25p3GjREV8AQ1Ghrl5xuZB8KqojQnz0+KfbPPQeGWLz3gB/ONUwdjTqKH1pQHm03gTMRDuYNr3WD6/1c9XcXO7a+ialFoEBlx//gUNkRA+ipEwoZWU4OnopNILPMcTb3iCbFg+BD7D1TTrC/Zg8jKuXkFM4dgAAIABJREFUFBXF69PVB+1a9gNT8+GjxheDCegTGht1zYXyMl5eVBlrJ4cjiO3tFBdadDjMkVBSxGqxz48cDlMx0EmFJTp2dK9ktzczzSJgcGrrTAmHEVtaIDCaIUMJBpGG9RkzlFAIsbuLUwsESh29WnYK+wCKKwxmkbsOe3nv2W7OjvpIxtOjxmUhAVgDTDOpvNbrwr//IO8c8bOktJzuwx20dLv457Pv8/N5JgrSPNwUkTE2N4FBjOEUBgeRvRIYlQnl/KXiMEQckAU4nHx7RgF0tbKpEnC4pmzdjFW2APcsTufOBTMwDQ1CazMAv1+WiRQUIU5nlgdd5GVLvHthFU1DIRo77FRk2dj0ah8/WlWEJY4HY2Z3iKNRACzDTr5cUgAl0Rd5h5OvlCZn5CgZ6Z+Q1aizqAKDO0zrwTZOLEsHr1eHP3H8x1o8fN4s8aWF+dzx2kHSVM0s29/SRknER39mPo49BwGQZJmB7gHWb21l5yU1rPpnKwYUIo1NkGkkEFEgGGDYH8bf3QtBmX19AU7O07I+nPHoYe47dRrrKk3Q2kQNUJMJOCbQoakynbg9KF4jDJm1jBz7DxLsH5xUf8OgA4tIap04sveOkp6RcsAfxOwaTpLxQ2vzJ8RRApxZmcH2vgArzAGqZo5m4UkPB5NwbrEm6/XzKkxkdHdAaHSvyAMOigky1NkLtlDq8Y8xC8kIOD1B5sjD3Dg/J8ZDcXAQRVVRwy6EhCwk9PggLhsVgOjxoLjQzekPq/JY0elMkosYjYiftC68IUydHeAdPWfEI35Unw8c6mh/bwSj2azrLzidKBENpwG4b6GJc95wYhQFMnJVcCg62gaVIPkRKfZsWXgx7yXyCDB0dUJoYGKeRvlvAvqdXhZkCZCVxcyhHhiCy/Pgd2kixfYeIsEQhrYWCI7K+WvlwEjGkyhEFBVDSzOMvKiXlRHo7iXNG0w6hyIeH0Z3OJnGEdriaA55fZi7OnUyUVwuJCO6/rLXh6Cquv75Pi+mgD+WfaEIuHJ2Dve/28HGGpG/Z2nrXhkIIAQD+vfKvmE9Pan46HCg9AsYZFW3btL7fbR2OaisSgdHF1+vgl8C+7uHWVMr6WSAzYagqFo8g0m8H0RkBUPTYe2LywRylj0eDOHQ6LOyMoTGw1rcoQSZJNIEEI4o2tkULW+shGCVmXD/AJV2lTcvqGLjE0EAhg40Upkm4O6zY5Zs3PFkG0uVIXLi1k0kLGNIzJiRQj98NTNPJ8eFajqSLONs7+Gs3Agv2rxc9FvNtWCg30m5CNicOnx+uxOLMaBbN64OZyx7jW78FHz29QhkRNQknigqGMun6d8DvT6ynA6wKannNE757OoMhgazqfM42TQ/l/OLy/nV9j4EWcHT3Ue2qoIDlFA0o2EcPUo01p7ZnXwOjDe+5BzUPuLa7aDC12slZtfm8f13ItgDPhQ5Qn7XqMvdZHBO5bs2gDOoMNvdC7becfHFrplGMhIC5xfDj1sDZLRp71QCcNtsM+0tnUyXZdydXu3rj1OBxCwkdgeZSiiZvgnmVOfXLjUGDzYxIxKmwCRwbY2Be8U09h7o4JyaTKYKjvsDhqqqEUEQvgY8i2aV8ydVVfcLgvB9YIeqqo8DfwT+KghCEzCI9pFjPJxPAE8sKSv78lgmWBKQLtpYaLWyMK5etFqpBR6aXskctxa5/sIoilNuuYtvhxdqUbTj8F1zsqpF7Y3DnzgeAO4wlyzPJT3a/x75Qa6sORt3dh5peSL3LMqPRZN98VAfC4QhXf8bIAn/hoXpmGZrfdK3bsU9fwWiUcv0obg6EEXXmDTVp6DRkjjG1q1AOZbZDQSONEGBEqvfu6cXi6kXQ1Eh0qz6GP7ttywfvVGy2cizWtkQzMR2xM2nh9q4XVhMFrmU59lxeQL0Z+Yza5bEW4JEeoaDsMOHXFQMvhDBiJ2mtHyyM5yEZAW7IZ3Fs3O59flG1s8ppXt/L83phSxbkM9FD+9hTVkab/cF6MksYFFlLs8vrGe6vYsFXi1PujgZOW3dqi/vcsTKHQf7qJqmsGD1grH7x5Vl4xEMA/26eqXdg5ilIhRko8yciUgjWK08/u5OOvwqGQaB0+JMQiekL65+75Za/vLEDq769HKUaCDBUyvaOPfJLrxVNWRkWVBVld/vdbKqqoQ5ZTlIooD6j60YTlzL4xfWcfszh7iuIDJpc+SjpVFSVOTdTl19R6+PdQ2W0WdHgQ/gnOoj49Q36TJBxJ719FB91bzYE0XqQKiphgT3BvPLg1rfOJximhPlXXvKvSI0NLAtbp0pUidi3QyIc/lQjb0I8RmCAPXZbsSKCr6yLhrA8OlHkOadgSx4IMNEKfD5xeXc/B8twFd/Wg7FI/07GqFA1eELP9PNt8+qY8OzXcwuy+ZPHRm82mZnyydnk242UJDlA6uViNKEcVaDzhVAalVRzQYokI9ZzsdUPg58poSyBPDPB5Pap1utpAOLFJVb//I6S6tq2es+QltBOQ2l2aM4OhrBmsI0/3jnHKdPAM6+/xCZOSJ3vDfIZ885Abpax+1v+5yKOarzfzBPpX3HPtb9u4NdahaLFpbx5t6D/LZTpbYwg2BEYZ+SzilzsmgvnM5QqIUso0ikuhYK0nlxby+nz/TzSHcfveZs8vJM/P3iGbExv+FLZ9WJ1fD648ctZyE7Bzk/TdtfW7fyF7uJy89exL37Xkrenwn9BWDnrSsg7lzR6pu0/49HJoZODAV548t4HBw/qahl9U9fpKi8iKK4+q+GlEmtm2ut+jJAuOUg6R4RcuLoGmsdjrVOJyi71Q6y62u5fFp2DJ804xTCERlKshA6vPr+kh0S9LbY5kHxqzoaxeoZKEJ7klzEzGHUNweSaBKzPZjqaqEoc5RG0yAc9OnWhTAcwBjcpR8/IKNKvtE2QEHBEK8dtnP7pcvA1RurC7Ycotlup6SiKPZsUGlK5hFODDVVMD13Ah426c6FC1eoNA94WOLRnwuK0IZUN4OIeARDfR30tI8rl4jajMFaDyM30Vu34q5fR6YpnHQOyS/YEXMzU84hcd0EpV7MdbXw/KOj/d91I2UL+nPoPQdSYRFYZ8b6C/l5qB0R3fibZ9Tx91ufo3jRHNSH39DOOosTYY9Hn3lpsA1IlntiOeIVNJNua31s3YhGB+mHAqMZ34DXv1XBub94le99eSHnOHbraBJkBZXm1Od9wniK6kRqsGrX8RO8L0T2DyFlxfF561YEaz0ILUkySVwXALLahFQ4itMCHHq+l6vW1oG1hDLgs/95kXeYgbO4nKpyGVeGRKHVSkTsxFBXB0dG141PbiYjM33Cs/SbW67S1S+aWc/ZroNETBIzq+BPp83kid09bHpoNz1iGovmWyFL71q91p9JfUkW7Hgqhr9eGKCus3P8dRd95nVpQa+x1ulovGhJEPZt17UPvjWApawUrNVjrpOR8hNfKwXv6Hvfb6xWTtj8H/66fBaUZbPCCre98zzFhdkoBbnaZUCBilpZiyB16mQkB8JAC+aJzoEU9Lxy00L+tbMLgygwe7qm879aXs3dzzdiDnuSz5EP+Z3phoWOY8a3uCLMXwvMuvqSoRCXPdrBC5vW8sTuHu290x51IbHGuZC020j3D0N7z6TPUoCFM1UuaXLTk11E2TQzr3xyKdhsWE+p5LS7XuF/rjiRqYIpiYGhqurTwNMJz74X93cAuGCy+EYsMOoK9TffR/Nla06K+rppOXy7Nnv0WbT+WzVRBTgB/oqQix/NjruZKyvjF0syWftwEw+eVY446InVrRMmR+/dC/X4FOcQkqLdSMi9w0gZKb6SHk05eqssNtpQ7IOQDthseMIK9zzdRToygkPLOTzSX+ecEcUX6RnmQKubjPJSrpimculT+1hUZGGHS2Gwo5fzZmRx+j87WFtsxBeSUfr6IKQQ8vn55sN7WFxkISKpDDhcXFGVQf26UgDePKjSfKidGxbmE1lVhOzx8lqPStvhLj6Z7iXHLMGwk54OJ7MM4qTkNJ4FRrdtiPnZKW48xijLgSBScbGuXnG5Eb1gGAwj2xTE6E39dAK8Egjxx6UZR0dfXH0WcG25Ck2aJcMcANHLj1cVseyH/+XUinQKLBIRf5C3H93FHWuKKUoz0FpUSXXYhaWlSbsldAwf/7oZo14E7XYtrn5X+yC/WhLX5yi/Mv96vvHo6EuBU41EkNrbwW3W9bGM3HTEz2EgxW3iGHnc1XAEoaUZfPEWGCHEoSH9ugiFEbq6QBmM4ZP6+4kMBiEggc/PrJB2OzK/0MzLtn4uTNdUsJBggQFwZYXIvEw/Z59UQEWWEXXYwyn2QtYYPczIMsXoK003IB1u1NEsDg4iSwKY1WOW8zGVP0R8EnB9pcDtW98mQw3jPdwCw2lHZYFxTDQlWGCUm1Ra3AHWlKWR19U6YX9z3E2eBFSFNRPgn2w7xJ5La1hVKfOSJQiFBv7T4mZ7u5ObFpey4devYRRUPCGFUFMzn3mgn4Y8E9+vF3n/4moWbm3lkbPLdWv9mmloFixTIBfJ60UdlsBtgbIyvL19VJRGuGdtyaT6pzpXDAJau+Og74UNZWS5nOPLeBwcFlklEIok1We5J8A53rlhH8SoBlFVlf5d+ylON6Rch+qhQ2jWMEdvgREMRbB0toPLFMN3erqfiKLS1OOZlAWG4HGjuNHpPDGioI7cTMdbKzmCKS0wBHcYU0cbDBpHdeYRP/j9+pt8XwRjmlk/vnMQJSLrxv/zqnxmHLbTMNyjs7Z8dW8nZSaVucZBlEOHRt0VEnkEiB16i5AxeRq3VzbXCjS83s/PKiy6NrIsY2htIRIOY2hpAe/QuDgjioqhuYmY/29ZGZG+AYxy8i227PNjcMsp55B4DgX9QU3ecTKRXR7EdD0PZJ8fo8NO/C14xOvF6PfqxhcVFWVEzlELDPr8iAG9BQZ9Q6n5nFA2OgVNJnHrRu31gV9viZMWkFEUBXNzE78+IUNHk2aBkQL/GHKOWWXGtf/HmWXJMvF4MQhxa7esDKGxUbP2SJDJqRXpSc8AhATL387hIHWeAbBp/Fk6LQM6oOtACzPEMO4Bba+JcgSlqUlnuSMrKmkh//g8TaFvJBqRhpzIogCZYAROEiMsK7HQNeCmuKc9Cd+5aYDLo8N3kiaIJPzXL8xLelbslygVDEk8+ck8MwzqaQz4/Jgd/WALpp5TXHleinoHRp21wR3zzDztjIDDrrncZIAalBETLGeUoGbFaHYNTcjDxHIF0NJyhNMqMsCh/d4qBP7+TgdvnZ6TvA4/5HemjZUcM74cIMev/y0QGtTeQeuc3aOWv6ksMBwOMoLho7bAkIAFaRF272nl6nl5YHOAw4HsDlNqEXVeCMcLH7sgnjA5C4xjKZdt3UrZV794zP2Tylu3ItXX45Pbsa6YPyX45DnLkfq1XOmysx3R7Dn+r3vRW2U6R29523uGafe2EQgrnJg7+nV8LHxz05zk1vjh0deou2oeby+by9V/20l+ehgKCqhdZmXHHCt3PPQO9IXx5hRglgQ2LZa5/tIavvnIHvwhmaBZJmf+bNZH4601vbqD4ewZGGY1cMksGN5zgJ58kZdtA9w8f3aMhmuX1Wn+p5MJODeOBUaovwVzbmDSPAwbujH09+lvZNo8SAEQi3OQ62owtmhf7DM6BMTDblY1lB7XF9dU5bMW1mBd6GXYF2bIH+LP/z1Elz/CYGklRaVZvP+351h00SztFmySOI+HRjWOp4GwTN9bAzHLpKma83g3KiMWGDq5SB2ItTVQkqXDYX7HnXSjImUOoyTeJkb3SuJeUKQOxLq6WHAmANnYjZiX8LV/WzdCRQXUFcbwCQvWgzxEVmEmvW091C+bw4mNAXLTTXQxug7VFBYYZ4KuLGzdipxeh1RbqwuU+vp365OCq4kdjSgCSTinVi4fPb5i4B/PaQeiv3Q6zCwcbfMhWWCURHZwSMllXn1Zitu8ifFJwG8ureV7j+0je95seOQh1n/lKlYHI9gf3s2ugWG+uWgO2+pn8sSeHr732H4iVVWE3h3m8TYvP1xVTbrVyt+/XMLcqrwUN5JTMGebDTEvFyXLrN1sb90K1VqAxQ3WY8OH1cruLTO0m+rjoC87Vf1RWGCYVJWwkuLW9zh4GLFFECMequoquPi5Ri3ddwp8obqZmHpbSbzdnAwPgrRhrq+DkVgVW7fScJV2sB7e1YXQNbEFBu0e8OotMITaOhShTXsWb4HR60J5rS+JJiHbi6m+Trv5HaHR6Ei2wHAHMPl36HVaUEYVvLrxJasVaE6yinXKXdy3poRt/gzcldPJSTeS6mYenBhqqyHeGislD5Nv2gNyE1m93bo+stCKWFeHTBcG60xobxlXLhG1CUODdVQnb91KpHotBlFI0keyqR8xNyflHBLPoQCdmryffHj03HjLhZQt6endYUcsLtLWVLR/JCsbY5+qm6+oqMg0g9VKmed5WvLLUcwhxAN6uTHYBtjHnTM2G1cvn6nFURCF2LpRJDtSYxDibsYzwjLeh9pS4hMUddIWGKl4BLAqhT6K7HEiZcbxeetWBKtVGythDfwxBc6UVh1CK8aZMyBH239lW7dy8zmncNAd5MQFhQx3dWl8Nnah1NZCf6cOnyEz45j0zUtPH+FHn5oHQe39pRCY3yVgcQ0dE7748qZVyTrzylWTx2l+a4Ds6gqwThtzjHHLCXKeC2x+rp+l1flabI8CFWV6DaKhSyc32RMEWrEU5R/1nLFaefL+Jm797AroadPJaNr0ogT6Jo9z0uUPGZ/BGeT6U0vBWo/v8AHCeSLkyQgFegsMpe0QGcYg7Ds6CwyApcMhBtwWiheNWoFNr6/n8XkNo5ZpUwBTEcTz/2mwGCUe+srKKcOnxOXSVhKCQR0rbDytPulZh8NHIOo3dv2pMyfEsagyj0/GBTsUBIHlNQXMKzTHnuVlmPjRqmI+taicg72uWEDHvAwTv710MfOn5+AO6wO5vSTn4A3JsXKOWaKmMCMpAJvZIE0JL2RFxTBGsKKU7WUVKSHwWKFFwlqalTJQ4s4UAX+mAnLTtawnpzQU86lF03n4nOk4vCEc0TzOPapJy9rwEcCbzXY21E6dX9uxghZsM/l5YoA50H7jJQYiHQsSg5OB5jZ4NMtRRQu2lmUxcvmKKsIRZeJOKeCSZZVJAQNTBUMUBSYM+vp/BWz/s571c0rxhiK82ZyUmfsDhxIhzIKKXL65vmHixmNAQ2kWv7vsBN2zTLMBi1HixydqLkl5GSbOXVCOQYDeoQAbFpTx6LWj2VCWVuePGYhtKkAUtACyUwmJAd8+CvggePbVk2fwmbosPjG/jLPnTSMip97vgZCStJ8nC0FZHTNYtKomx4xMJTlZ1QIDx4MoCCl1h5A6riaiIGCWkucgJFAgIGhpAxNxppxBMvjDMmkGkdw0I0P+0LhtpeOQaXJQTBWDKBBWlCRepQJFTQ54qQUATe4rKwop4s+mhIiiJOGVU5x5WiDO5PETz4n4AK4nS8O82exAUdQkuU0WDJKYRJ+iJr/Dmg0iITm11D8o9SWn4H9iANujhYhCUlDXsKzS5fRTmmPBFX2vFYTUgUmP9XXWG5STgth3Of3MyjeP0ePDgy3LCzlrbumU4tzX7eK6dTMxG0QCESUWVD0eRt7lzNKx/aT91vqGlIFK/y+CNc/MptO134Qn1Rexsz+Qsp2qHvv5PCPHxHUJvysFQYgFm54q+OjfHlLAVLiQpCx/AKY/0uFGFgDHFCgxFX0uF2pYMz2LHBlCyp+8u8NYOG+oiDO3ipqpt9uc/OWMMhrw6k16joKHXyiCnx8OUxhvouRwcPu8fKx/aeYXJ2QwEizOADi6B1ibozeXLE2X+FqloOv/mXyVDXWS7tlxyTnO5DvSP4gkThDYMK78rQU5FHTog8kuM/pYVprGffsGkG0hcDvx7jtIZMCJpWUSpsDHuw4Bo3OQ2hwjjsNtIDsIZ2aPBtA8FpxHSaMQx9PD+5xcWpzCDPaD3HspcKoRGaGtDZwmXR+z1zO6/qPtpcEgamRyLiSKLCM2N4Fn1DxRDYeTXEgIh6GzE2THKL6+IzAUZFGhArnaujMd8RIadkPG6DpM5UKSiodfnSZrvrRHxuBJ9Flt2K1FQXdMoD/+F7uQjJTNwPdmm/nGCwfYYw/w4inZFMfafrAuJEFZpSrbxI/XJQf9PBr8tUAtgG1AR99dC9J07XOA+5Zl8ttn9vKrk0spdvaMuw6mbM4OB2LAi2IUwd+POq0MBh3HNecPdd1M0OfNC6qmlMZiiOmLRZKX3W/s4QSDLwlfwNZI2qCXeNPdyc4xGJExt7XASIaBOPrUXhdiKMH9tMeHkOBCEh52I3n156+oqNqHeZtNH8TTGUSRx3AhadUHEdZcSBKCeAZkjOlpuv6i04kq611IYn8n6Gw5IiM5B8mNBBjyO6gqivP1j+cRILW3wZBpXB7efmJR0hiJfASQZQWxuQlZVjA0NcHQBAFwE2kqK0O2O5DMEtgU/ZwCQaTEALTROSTy5Hsn5JHR3qJ3IXF7ED2Srr/i9yPaB8AWifWXh9wYPHoXkthPQJuNkrIi+lu7qQumIwT0cqNvaNTVa6w5j8FDucuL4POCY1TG8eMm9heAL87JmZinY/BoLHoiXh+G+MCmUReSGI7J6NCEclhWMLXqg7X6evuwGgRyejoYHnSDzYYYCaM0t0BYHxBbSHDDnay+8fuDpHe26VyZvM5hMrOkY8I3ZnkybRJwSs5BiA+2fpQ67ca8FEHDgfyuVrJdw7jUEIQUhGiig9g7WjQbmcl5bHO+Zhqp18Ek3js/9mffOO3nB2Ue7hgExQSy3oXEMDRImVE86rN0UuUpgo/lB4wPyoXkf4PpT96S1RSFnLQWTOcH7zZxwaU1U0djRyNKvsLGXT6q8vM4aZ31uOd8vaoiWK2jn85tNqS6mQhCsxaoLq7/T6zJ4/1a3gonxIVHsWmBWHXfQo9XLnEm33LXYQyFEwQ2jCufawW2PJmyXhxoRZkxHTpbeGI4jQ3rpkNp1ge/bqLPHr5+Cb95qYnr7m+iQTCw8cNc23E89XY0klnyQboqTNKFRGxHHHGviMNh3h9KMhMVjrhRpb5kGlO4kCC0IdTrTYdlqRMxP9mFhAQXEhash8gQS08adTEziXZCrU0I6Qr39hk4bVYJxmJRF2D3mHgY92yDdYw2/wt14mTalwGbCgZpsXuxuexacNQPwYXkkXc6WOTpRZrVMPn+xzlnU4+P2TNMFC+ak7r/MeCcTFkU81GNElTnE/zHg5jr1xFvpv6xXjcT9Cn7AGlcWRPha//YxR9W5CMm4PNXVJOGE6zTj3qOQaUJ8ywrjNw6xtGnerqgx6/vL9lhj96FJHjYhUUw6XSeOLN+1LQ+3oWk343yUnKwZTHHjykhiDBGBxzy64I3Ct4QRt/buv5CWEER3Mk6N4V7h0IrYkEBudklDAdlqC9iTBeSGTOgIH1cHl6cUkcmnysyWlDOsNKquYYcbpxADzclrZvIktUYcyxgrdW1v+mTOZSqyYETU7lHfHqkyb/+OcqT15xI2WY9ve8MIJUUa2NF+0fMGUgjwUkT52u1ImzdCjVrUaYXINoCOpcPBtswSY7x5zzGXlHVfqSOCBTo3WR+udY9Zv9bkmhMwdMxeDQWPfJOB+aiuMCmUfq+slZJwZNkHOct9GnrKa5NqmCtoeVrSEszkjevlvb9mkuHaO5BqakBR5eO79IxupB45RbSZ1mhdZQn4VcGo+trCvXXZNpMsd6+0b8VrJfo6m86sxisdZyY72HbG/s5c8kMREOvTm7ykB9oQygsnEL6Ur13Tv2cP0p8ucDh7Q6U7CwozibehUToaOTLp9fDlm1Hvy4ms7amAI7LhUQQhHxBEJ4XBOFw9P+8MdrJgiC8H/33+PGM+X8dbj5nFifVF9EzpKWiOR5TyFRg98u8dKifpgHPlOATBSHJBFcSBZ6+PnWe448aNHeAqcElxbkhvNZkp77kw3WjyM8woahw7Skz+JTk+FDH/jiCQmrZjmlmPVm8KUwWFXVyJqBaVnN9Q5NBJBRRSDOINPV7+OFTB8nPME+Smv8fxoIl1fmcXF9EmzvMOFm6pxSODPtZJbk/lLFG4MSydLZsmPOhjgl6F5Ig4lHniP9/FdJNBmaWZNLnk5Pq/GH5mPm4ojRtTJcGVVWTzPFLss2sKE3TPUvlhjKWqwikNoU3SkKSm8BYJvNmlKRn6iQ1saJqZ25VQQaNfePvOXEKnaMjcS4hqdz1JoVDTnb/AFg/t5Qs07ETKytqLFboCCgpXEjkSbi/iKKAyx9OWjeqCubEQY6CvkRaAD5Zm3VUeH5nPL7Af2FFRUoxh2+fNStF62T4+cWLUuI0JOA0GySyLUZMBpHiNIk+V0BzyUqxIY6RpSyrycdiTHZdMR4rwo85XHuK9pG8tiiTbk9Ec4dKcumd+vP+P9dOXbaMjzOcOyOT3V1DHzUZxwTHa4GxGfivqqq3C4KwOVr+Vop2flVVF6Z4nhL+N7mQTDU+obERweGgJ6jl3pacE5grHg2NDgcDkQiuQIQNRWjPP4A5C42NzAItBdrx4jveOYM+a4DDgTCRqf4kaZTsw0QafYS9Q+CKpIyIfUxzPgrTvu/VR19+28UPd23H8XSy7g9TSl8KnIqsILa2gt2o6xOLTB2HQ3AGIdEceiwXEkVBPHwY4jMdRCLgTMhSEA6jJrqQHOmDoaBufNNAgJDXR36eRLM3xMkFFuZFnODwfvR75WOoE4+mfZGq8k77EBcdtGEYdKbWcVPkQrLp1T7eHwiw6ePGww8Cp8OBGPJpPz/Ddvwl00gbHABb6OMx54nwfcQ0LhR9DPV5mZaA78cP7+QLs3PA6Dpqev66xKI31453ITniQggGde3rgOsr9FmJgi4PZjXO1SR6fgPas/g5D4VASXYVtHgUXX9sWvZK1+EJAAAgAElEQVQJIcGFRAjKGLP0GbqEwUHtx0dC/9j4cWVZ0TJ+FRpFHB12sIVH28XzCDC0tkJ/iswvx7BXZEVFajqMSZpctrokmsrKiAw6MeBj0q5C8TjGoU/x+hDdelchxR9AHOjX7c3wgAGDO5ia/qicV5t8PLtrAMkfBEecTPuGMAkTZLMag0a5y4Po9TKhK+ME5fUVaUn1fzh12tg8SihfOU3FkBu3H6bgLA0rYGw6PGp9XFbGDdMVREE7H9ZkhHn7jX2I4RBKSyvIbv3a9x6bC8lfV+dq+z6ufdjrw+ROdu86Lv01mTYf8tl3eo7Mv7a9jzjy7hatl10hMo3C1OrssXjycTvvjxPftJCHPqcP+vv1+snhAJv6f9qF5Fzg5OjfDwAvk/oDxlHB/8suJFit0NHIEVEA+nW5p4+bxo5Ghg1eFldKVM6dCWUTRen+EOc8Vv1U4IzPGpAi28Ox0igNdaDUFtN+6DBnrMgHa/nUzHmi8geB8yjxqUfL0w/BhUQV2hBm1MJIMNMojqJ+I4mmu/S5UcUjyTSmykJCC6K1XktHGa0TDJ2ouXoXEmFbN0yv0DJhRPH5Gk4jTQzozB0NmcPI77nIK8hgMCBz+XlLJ8eTD2OvfFx14iTbC8BKm4s/9huRSqKR+KeaxujaL2uDn32pHm677ePFww8Cp82GaCwkoqhQV4j/7//GsrIMrNM/HnOeCN9HTGOe0cGtj73Pb9ZUU5hpjuF7NVDOVevn6bPnTAV9rk6EPv+EPAjuHsSSHafHYvVRXRfvltLnRpB6k2iwFCvJ/Q12hMaA3oUkEMb40Ov6/SqrgGvs8ePoVdRmxOg5kNUr4a+pYSzXAmlmHWSZj2GvpHAhUZuQrFZ23zoTTNKEON+4IJwkF3neCgzTcsFaOSm5nlBFCp6M4hsp/2paFbldbbp65a1+pNISsFbH+suYkVRPEk/j5Vx2oZW2tv0Ys01QkD3axtGGyTBBhosxaFTDvUh93VCQNeV777TxsmMklEthQnxHrS9oQmyIcx3culXnSjhTVdny6hCi2YxSVQ3DPTq+i8foQpKqHHqmD2N+7tTqr8m0+ZDP+yXA39/3Ixj9urUsD3jISOtLfk+cavo+gjl/0PhKIwrDIRcUFxPvQhJzwf0gztIpAuF4TG0FQRhSVTU3+rcAOEfKCe0iwPtABLhdVdX/jIPzKuAqgMq0tBPav/nN0Uq7HQoLj7388stw8skfe3z3RKbRrKTxmFJAi+cZxCmi8e5wGQ2ePqpzTMwS/R+rOY9ZPwU473Llsil7KMaDjcN7poTGf0YKWS252DcUoTzHwlzRNzVznqj8QeA8SnxHzdPjoK86sJQ2zzO6+urAUtrevkOHc6VvLo+kNVImhCbEeVixcE2ghhfSD+porF5xE22W7br29YET2Gt+D7NjINZ/eWABj3lfp7QgK9b9Uk8N16Q5WC25YvgeWH0hOUKE86TBGL6DShobw7X80Lubn2TM5SHzocnx5EPYKx9XnTjp9tFnP8hZRIkQ5irDkSmn8W5XLhuzh7grXMYmY89HP+cPST9sz68moIqskVwcfmcvtiUn8QnJ+fGY80T4PmIaA6pAQ3AJb5h3Uz6in6L65k/GRtZJw1NK34ORQt7zG/hp1pFxefDvIRNCVtaoC2K0vl81UCxEdDgbFQtfTdSZdju/z53LVwxHdP0DqoAdI9MdPbHx3KrIXw97+Gr9aLaskN3B7MwzaLLs1PWvDizV9HAcvTWBJTR5tiEVFtKkWHhSyefnkfJRfQ2odjs1mWfxnnkX+ULkqPdKqnMlRstk5ZBCLtvWnEeFEGSO6P/A1+F33CXMTlO4zDAQq/9j7hw6VTNbjB269osCC9lleR9efpnI2pM5KzSXesHPr13vxNo8ECnmL6EC/psg98nQ+JScx5NyPr+Nw/dBzPmjeO9MWhcpcP41dxZ3R8r5u8nGrMFO3Tq7PbCXi3MDuvbHOud1wbnc69lOXUHa2O2P8Sz9WMnFbufG7GXsVDN4zbw3Vn9YsXBXpDx5nU01fR/RnD9ofNWZZ3GroZ0rDf2x+rvDZWxM9X4zBTQKt922U1XVJRwvqKr6/7V35uFRXFfaf482EALEIoIBs3iN7eDgBS+Jk2DHTuJkJnb2bbJ8SRw/cZbJkMU48RDjfPky3kkmuwfH28QLSezYxmDA2GLHNphNIAkQyFgSAqm1772c74+qhlaru+ve7qruutJ5n6cfdXXd/vW5dfreU1U653bKB4CXAVQkeNwIoC2ubWsSxgz775kAagGc5fS5zIxLp03jQaqqymz7jjuM4j23q95V5gNrqvnJ51/j+tYe12z0/Bi6wHzgyc2nnq+pds3G5W8c5aOBbv7D8q3c3R/MmKe87QVTk6d9TDOwb/aiFUP2z160Ygjz8jtX8bG2XiXmgcYO/uCvVg+xcfaiFUPan/XTF3kgFB70/iv+38vcsKNi0Nu/9Ot1vPFA0yBeos8/0NjBH7zvVQ7ur+Smzj4le1PxUr7mt/HsNc9+7Y7nKnjZxsOe2Bj97t+/ptoVninzw/baFi6vPsHMzNWL/4tf2F2fEc9t+1LyfGDjxT9fyUcD3YN4596+kncdbXXdvidfe4tvXbaBhygDZtWxDr7uv9YMaR+JRJR4wVCY9y++a9Du4P5KPvOnLw5pf3IejosDkcrKk9v3r6kePF8zc2h/Jc9etILbegbU+pfgM+L9HP8Zvvtux+1f9NAG/uu2twbtf3jTYb57VeWQ9gOh8CDmgnte4R8t3zWozSObj/D1dw/1u4qNz+2q5+/8dUfOx54XsfQDvxx6/hDfvrz6BM9etIIr6tuGfM+efuH1zGyM2f7ysm1cv32vazzlNjmIff/+5Jv8vrvXcSQS4Z6K/czMXHmsnV/c0+C9fV4wfcCbvWgF/2XT4POlB5Kd37hgI4DtrHAPwOnhuHoQM1/HzHMTPJ4DcJyIpgGA/fdEEka9/fcwrDKToSviiIbohnnTXWe290dQWlzoOtfP8mo5v/w8a1G73nAEY4p8+YM+WVF2lkt0lk4ymc7auIkW8VxywwWYOCq9xdcK8vMQsn+X/mQ6uchVBcMRzxY1Y7i7GLApyqNTi6UxCIQRdgAy1OIrppxcBDWqby84C/NmDklazVgMvTlOVYmQ8Yt4J1NBft6pzM8YXqIFDi+bk3A9+MGfFfO+rTVWBknYfslpwcrhrGtnlmDezNJBr33lPXOw8EPnDmlbmD84hs2aXIIxRUMXlS1K83gys+sL0ftF5Z+e5dhm9iQr24gZ+OqahkH7XFxnFo9943JMHzsyzutPGz8aJzr6cbi5G19YVQ8g+WKxIjV9fN50I49fplddzwP4GoC77L/PxTewf5mkh5n7iagMwFUA7kkFHcmLeA7adpm5fGstPjI1H2OOHDp1duO3PqezkJATM24RT8cFJxVtzG/sRKC7eTDfjT7naJE+LZ4PF/EkjgA1NUBJgTOjbQAcDg+1MdEingzkHagGWk4tqHt9IYBAkkU8I4GUfS7oDCLcr7iYW7bHit/nRMWx0dMcQklRH1Dd77qNke5eVG3bi0ld9hjIdZ+zND+U5PWjoS0IUCvwjimgYw3AqA5/9DnLsTSd9xd0dyFUcxgIFJ3iBZqBanbdvsixdlB/n6vzA7f0D134OMNjmNcSsO5DxM25f7tmsvVaCt6UHmuh83BlFb74aA1qv342IgFr7s0/dBAoyHNnrACu9tnr7+GHSvqAzkaguvHk/nwcQH6S9rHMswoGUNQZBAJ0qs3xNozioYu3qtg4s7MPlxUHcz72vIil1NLiyJxh37CM1NZiY30PgpVVKIz+ok13l2t9Jjf6nM75RA5i38LZE9HfNA6B/YdQGLHmo0hzH/J7wkBJn7f25ajPXvPuOL8Uq2pPoLuiF2PaW2K+T/5exDOj9A0AkwGsA3AQVqnJJPv1+QCW2c/fC2AvgN3232+q8kd6CYnbzNmLVvCVd77kro0+SOVzYnpVQrK3ro3P+umL/KvHN7nCU972gqnJM72E5ODxTr5GsYQkUTpzou1/+8063nDgxCBeovb1rT185a9e9uVY8f2cqDg2bnr0DV6195gnNi58cD3PXrSC1+5rdIVnyvxwoqOPH9tay8zMlYvvslJ2M+C5bV9Kng9sXPnS9lPfGZt3Mk3XZfse31rLtz3kbgnJ/oZ2/nCCEpJ0edH9iebcRNvxceD1IwG+dNGz3Njey/N/uZaZmXsq9ivzkn5GnI0f8qDPvuLFMNt7B6zSuJg2D286zF/+zbrc2mjgeWd0/6q9x3jn0Va+5I5VfLzdOj+ZvWgF//PFNzKzMUux1I82PrCmmlfuaeBv/f5VZmbeebSV11U2ZnWsuMb0Aa+5s48f2XyEP/vHLbxz4y5mHiYlJA43PwLMfC0zn8NWqUmL/fp2Zr7Jfr6FmS9k5nn234cy+UxRZpo5buSWOrituTNK8fdb3otpJSPvmPqlbCRWOiUkeZR+WmymKsgj69ccRJ6pLxjGqAI3k3RPKcSMj8+bjvOmjfOE71dNGFOItm5rAUpG4nICUXIV5BFuemz7kDISL1QyKh8T0ixxS6aysaPw2XP8852/ZNZEfCq/GY3tfTht/GgAp0pI3NTqT8x0H+pTjR9dCALw1IF2PPn60ZOvF3lUjjcSNLowD+FIBKVFeejoC5183cCMfV8p0D2AyaOtvCIpIclMRQV5GAhFML64ACd6Qs5v8Il8eeUlJSRQf48mc/kVQ39P21d9TieNzYHJMeUOHAi4VkICWL8VfdHU9NIr0+6fF0xdnm5ZTgb2bf3cHLVUvkgEdLgGGONcQnIGM/753jFDbPxh6aTB/aquxtMfnWG95mTzQBB4uw6ItKTsc35fGKGBNNJqpYREeWzcfEYxTms/DlS3um5juK8fH50Vxukn3rZWfcp1n7M0PxQCCDUFgOoIMGUKqKEBKJISEtXtgq5OTCnOx/6te3Bh2WhPS0g+UczgOXB1fpgC4KZpEfePIWLs1ODlAygeV4KG/TWYlh8CV1UhEmhBAWnwFGwcUirgt+92prx4ZiCAhp5eoDsElPaCTrShKBQcXn3OYizNr+9BUzCCWaMZXQdqgNbRmF5SgLPR468+p3MMcmRjqCmAQAthEg8A1dWIHO9FfoiB0b3e2pfDPnvJG8uMzoYWjBsIoaPFvp4JBDCsS0i8fkgJibvMRKn4vuuzB6l893tUQuKWfWmlseXYxmyWkCTaTpTqu+CXq7mxXa2ExAsbVUtI2roHeO4dL/lyrOT8u21A2mvn3v0cjK7e7wLPpPkhmla6b/FdvGqvlJDobG9Y9yb/7Jk9/D8bak7yvCohSbjfC6YLvHRLSJiZ7/jZQ/zVh17j371ykDt6B7ht9z5+KPrrQyr2JPoMv41nr3lxzAfWVPN9T2zmpWut7+bDmw7zv/+5PLc2GnjeGd2/8UATf+5PW/iBJzfzpoPWr5Tl4pzJj7E0Xd4Fi1fx7EUrTp6Hbq1p5s0Hm7I+Vlxh+oT3yxX7+GfP7OGH/rGNmUdACYlIZIIksWz46QPnThny2kufmImpdipxLvSeacVKn1+QT1lJIxd5o7GFeSjIH9mh0/r2ysyqo4I8YM7kEnT0BnNtiq/0yYtnpP3eRi7E5y+bibKxRWjvDSLMGHG/DuS2yqtPYCDMiIaoUIQxxqNyvJGgYCSC14604NqZJejqNyc938/60hWzsP4nV58sZY5EGHky8DPSDfNmoGzsKHQGIwD8WSYeLykh8TPPBBtNSOXr6QVXVVk/wRYIuFpC4kmfXUh79dzGLJaQJNp+7KpSIDSYObq9Nad++e4MBtoagLbUvPxQBKFwxJ9jJdff7WGc9po1npc2RtNKp7wD1FAPFLb7o88GxNKCzk6UUgidnXY6voclJAn356DPKrylF00eHEs0eN2jxqCk6Rjygoz2yjYU9nWgsLMIqB5Q4+Woz77ixTF317VjfH8BLi4goJoROt6K8eH+4dXnLI6V4FtduG5mCcZ3d+BQ2wBQ0J6Tc6bhFEtvPzsfaK4D9fQiUlWFcEMvCgsIKOjx1r4c9tlr3oUALpwFPPC2dQwpGuulhERKSNLiucwcqSUkv316C/cHrZRvKSFxx8Zcl5B4wswSbyAU5qvuWufLsWLKMUy6bYKNBs8P0bTSvYvv5pcqjmXMc9u+pDwf2Lh70y5eu6+R719TzeFwREpINN+f6Pzlk7c9xdtrA7z5UBNvOdTMR9/Yy8vfOKrOT/QZPupzVnhxzOhxjn43//vlA9xbsT+3Nhp43hnd/8Luer7lf7fziZ0V/NiWI8wsJSRu8f70t63c1RfkVyqP85tvtch5pwu8aMm9CSUkGWVgENFnASwBcD6Ay5l5e5J21wP4Dax1l5Yx810O3I9DMjBcZ67/9Gz/99mDO+GFfb0IVVWjqDBP7c53rvtswH+NOMcZGLnos1u8QgAbbpzuy7FiyjFMum2CjSbPD9H/ykyZAqqvt/6b6Ic+ZzmWpvP+C9EFzmtFc18HVq99Ex+VDIyMed0Fo1DSUIdRDNR1BTEVPSgK9QHVPWo8A/uctVgaAFDNCDYFMGo0D68+ZzMDo64TRd3dGNvRh67jnUB1f27OmYZhLB3T34vu/dUYaOpD0dhCAF25GSsmfbedtqPn9tFYP1wzMGDduHgngHIA85O0yQdQA+BMAEUAdgO4QIUvGRgG2GjAnfBl/9jGbd0DzCwZGG7ZqL0wqtwJN2KsGNdnA/9rZPL8EP2vzJ7Fd/OafY0Z89y2LynPRzZuOHCCZy9awQM/XyIZGBrvf3TLkSH7r7ntb3zoRCe/3dLNT7z2Fldu2c0v7tFYXDbuNcnAGJqBcf9wOGfK4Vh5+vWj/OPluzhSWcn3r6nmSCSidkxzfQy9YLrMe+bFN/hwUxc/v6ueDzR2ZH2suML0Gc+kDIyMVuZh5kpmdrqtcjmAQ8x8mJkHADwF4MZMPlck0lFhnrWQksg9yXJJItHIlswB6en950zBo9+4HNsjY3NtilH66nvmDHktBEJBHmHGhGIcbelBMMIoGuEL7LopZpZxnqEizBhTlA8iAjMjHGEUyIKTrmhCUR5auvsRDEdQKON+xImsmyEZQojKAfyYE5SQENFnAFzPzDfZ218BcAUzfy8J62YANwPArOLiS9+69dZTO5ubgbKy9LfLy4GrrzaHZ4KNXvNcYD7RVowPloZwGgWxNDgdC9v3+LvPTts+sHFpxwQsHG+tVql0TN22Lwd99j3PBBu95plgo8Hzw9LgdCwsbMCeNypx4pIrcV1+uz/6bFgs7WPCef3z8YP8eiwsbMiOfTnusxe8q9rPxVPjajEzbwAPBKdjQedRdJVOwoL8DjVe3Gtz+i5D7bZ7fd1nr2PpnL7LUNu1CssmvAufz2/CstBp5p8z5XCshNm60TYq0IT7SufhewUN+Et4Kr7TVuGvPhsYSzub2/D4hPMwGSG8P78D0wMNct6ZIe/+jon40fjWk7Hei1hKd965g5nnI1M5pWgAeBlARYLHjTFtypG8hOQzsNa9iG5/BcDvVNJDpITEABsNSOVb/sLrfDTQzcxSQuKWjbKIpw95Jtgoaa9Gzw/RtNJdi+/hl/dLCUkm21/66V/5Z8/syZ59XjBzzLty0TNc39rDzMx/Xn+IV6/ezpsPNanz4l674bcbfd/nbJWQ/H3721zb3DU8zpl8MlYe31rLB4938IPra/zXZ0Nj6f2rq/ixLUf4REdf1seKK0yf8R76xzZu7uwbHiUkzHwdM89N8HhO8R5JPYCZMdun26+JRFlRYR4hGJYSEi/ELmRwiUQi80SSBZ2Rvp3fiCPN3bk2w2iFgJPp+OdPG483m/oyKiF57nvvc8ky8zWppAgt3QO5NmNY6cIZpdh5tA0F+TJ5uqmBMKOoQEpI3NC7Jo/C/mMduTZDSRn9Comi3gBwDhGdAevGxRcAfCnVG+RXSKD+nlzbaMBq0AXdXQjVHAZaRqmt/pzrPhuwcvrJXyFhBgVagRKHVcplNWgjxopxfTZw5XSj5wd7ZXIuKwPq6gFq80efDYylc6ePxy1njTr1mswP2tuRvHzkHa4BigtwZYRxe00HPn12PdDfpMYzsM/ZiqVnFwWx+WAP0B0y/5zJJ2PlnaEIvvJ8LX5y6WSAQv7qs6GxtLCVUN8YRtHEPqC9NSdjxajvtsP2BejGE7trwKEIhvuvkHwSQB2AfgDHAay2X58OYGVMu48BOADr10huV+VLCYkBNhqQyrdq9XauqG9jZikhccvG6ErF4XCEl66VEhJf8EywUdJejZ4fommlby6+h1+pPJ4xz237kvJMsFHmB+3teYv+yS1d/Se33714JTd19qnzsmCj73lxzGgJCTPz/aurhsc5k4/GypLnK6SExEXetppmnr1oBYfDkayPFVeYPuR9/s9b+Fcr9yfmuWAjXCohySgDg5mfBfBsgtcb7JsW0e2VAFaqciUDA+rvybWNBtwJL+ruQuhwLdA52mpr+n8TfGAj2RkYHLEzMMZIBkbOeSbYKP81Mnt+CASs/8qUlQH1dQC1+qPPEktH5PwQpjzkHz4EFOUDAH4xtxgT3z4CRH/lwYBYmnNeCiYHAlapmOnnTD4aK2eEu1BV0wIU5Purz4bG0ismA1eeVoy8gwdyOlay2WeveQsm5mHH4UagOm/4ZmB4/ZAMDANsNOBO+Pp1b/IbRwLMLBkYbtkYXcQzGArzb14+kPP/GrnCNJ1ngo3yXyOj54doBsaOxffwK1WSgWEUzwQbNbfPX/Qcd/UF0+dlwUbf8+KYsRkYj2w+wguf2pl7G4fRWKlr7eENB074r88Gx9JVe49lxz4vmD7kHTzeyQvueSUxzwUbka1FPEUi05VHgCw16Z1kOSqRaGSJIeNelHuFQMjPk2+im/r8/FNr7n/4XVOx6VBzDq0ZfpoxoRjvP2dKrs0YVrp+7mm5NmFYadakMfj6VWfk2gxHEfvwVwRiSki+dXDTplM7AgFg8uT0t9evBxYsMIdngo1e81xgbqlqRP6EUlxxWjGW7gxg4Sz4u89O2z6wcenmOiy86nQEI4w/7WnF92dydo9hDvrse54JNnrNM8FGg+eHpTsDWHjxZOxYvRVdc9+NBTNK/NFniaUjcn44++GDqPza2SiMLRnxyVgxhpeCycw445Ea1N4wcXj1eQSOFYmlLvBMsNGAWErnnbeDmecjU7mRxuHVQ0pIDLDRgFS+La++yVsONTOzlJC4ZWN0Ec/+YJh/u05KSHzBM8FGSXs1en6IlpBsX3wvl1efyJjntn1JeSbYKPOD9vacRS9Yi/ely8uCjb7nOTAb23tzb6OMFYmlfuCZYKMBsRR+KCEhos8S0T4iihBR0rspRFRLRHuJaBcRbc/kM0UiXeURgX2YaTQcxGAQSQqvSDSSJCUkIj+IQciTEhJPNXX86FybIBKJREOU0a+QAKgA8CkAf1Zoew0zKxXTya+QQP09ubbRa54LTOpoRyTCQDhgtTV9RW0f2Bj9FRKEGWhuBUbJr5DknGeCjV7zTLDR5PkhEACqGVxWBqqrA7jFH32WWDoy5wfAv2PFFJ4JNspYkVjqB54JNpoQS92SG2kcAMoBzE+xvxZAmS5XSkgMsNGAVL431u+0Vn1mKSFxy8bor5D0DoT4d68clFQ+P/BMsFHSXo2eH6IlJK8vvpc3HmjKmOe2fUl5Jtgo84P29uxFKzLjZcFG3/NMsFHGisRSP/BMsNGAWAo/lJDo3CcBsIaIdhDRzVn6TJEIAEAERKSCxDNJBYlINLIk06nID3q6qDLXJohEIpEoB3L8FRIiehlAot+ouZ2Zn7PblAP4MTMnXN+CiGYwcz0RvQPAWgDfZ+YNSdreDOBmAJhVXHzpW7feempnczNQVpb+dnk5cPXV5vBMsNFrngvMnS1BtJWW4Zr8diwNTsfC9j3+7rPTtg9sXNoxAQvHt6GPCQ+Hp+KWtorsHsMc9Nn3PBNs9Jpngo0Gzw9Lg9OxsLABr+04hNBFF+Oq/E5/9FliqcwP6bzfBBsllspYyQXPBBtlrBgZS+nOO/3zKyRwKCGJa7sE1s0OKSGRtNespPLt2riL11U2MrOUkLhlY/RXSHr6Q/yHVw9JKp8feCbYKGmvRs8P0RKSbYvv5c0HpYTEKJ4JNg6jsWIMzwQbZaxILPUDzwQbDYilcKmEJNNFPB1FRCUA8pi5037+YQC/cHjPxyGLeJphowGLKVFHOyK9YYDarLayiGfmNtqLeHIwAmpuB4oisphSrnkm2CgLj5k9PwQCQDWDJ5cBb79tLYzshz5LLJX5IZ33m2CjxFIZK7ngmWCjjBUzY6lbyuTuB4BPAqgD0A/gOIDV9uvTAay0n58JYLf92Aer9EQW8VThmWCjAXfC927axWv2SQaGmzZGF/Hs6gvyn8olA8MXPBNslP8aGT0/RDMwtvznfbz5kGRgGMUzwcZhNFaM4Zlgo4wViaV+4JlgowGxFH7IwGDmZwE8m+D1BgAfs58fBjAvk88RiTIRESHisNaLKH3JIp4i0cgTQQa+SCQSiUSi7MtxEc9cKKaE5FsHN206tSMQACZPTn97/XpgwQJzeCbY6DXPBWbl4eN4K68E188Zi6U7A1g4C/7us9O2D2xcurkOC686HV3BCJ6oasfN0yPZPYY56LPveSbY6DXPBBsNnh+W7gxg4cWTseWlraB58/CeaWP80WeJpTI/pPN+E2yUWCpjJRc8E2yUsWJkLKXzzvPPIp5ePaSExAAbDUjlq9q6m1/c08DMUkLilo3REpKO3gF+cH2NpPL5gWeCjZL2avT8EC0h2fyf9/HWmuaMeW7bl5Rngo0yPwyrsWIMzwQbZaxILPUDzwQbDYilcKmEJC/jOyAikc+VJyUknkpKSESikScZ9iKRSCQSiXIhX5eQAPgKrIU/oyoF0J7BdhmAZoN4JtjoNc8EG7PNM4sKYZ0AAA9BSURBVMFGr3km2ChjJfs8E2yU+UFiaS54JtgoY0ViqR94JtgosVTGSi54bjDfyczjkKncSOPw6oG4NBMAD2a4bRTPBBu95plgY7Z5JtjoNc8EG2WsZJ9ngo1e80ywMds8E2z0mmeCjTJWJJb6gWeCjV7zTLBRxsrwiKXpPkwrIXkhw23TeF4wTeN5wTSd5wXTdJ4XTNN4XjBN43nBNI3nBdN0nhdM03heME3necE0necF0zSeF0zTeF4whxvPC6bfeV4xteXLEpKoiGg7u7FS6QjlecH0O88Lpt95XjD9zvOCOdJ4XjD9zvOC6XeeF8yRxvOC6XeeF0y/87xg+p3nBXOk8bxg+p3nBdPvPC+YI43nJtPvGRgPCs93TL/zvGD6necF0+88L5gjjecF0+88L5h+53nBHGk8L5h+53nB9DvPC6bfeV4wRxrPC6bfeV4w/c7zgjnSeK4xfZ2BIRKJRCKRSCQSiUQikUgE+D8DQyQSiUQikUgkEolEIpFIbmCIRCKRSCQSiUQikUgk8r9yfgODiK4nomoiOkREtyXYP4qInrb3v0ZEc1xg/pCI9hPRHiJaR0SzM+HFtPs0ETERpVycRIVHRJ+zbdxHRE+k4qkwiWgWEb1KRDvtfn8sBesvRHSCiCqS7Cci+m/7s/YQ0SUK9jkx/81m7SWiLUQ0LxNeTLvLiChERJ/JlEdEVxPRLtsn6zPhEVEpEb1ARLtt3tcdeDNt/0W/Ez9I0EbLL4pMZb+o8GLaOvpFlafpF5U+K/uGiEYT0esxbe9M0EZ5DlPk6c5fjsyYto5zmCqPFOcwxT4rz18x78m3269IsC+duJKKp+UTFWZMG6W4osJT9YkKL02f1NpzyS4i2p5gP5HeHObE04orKsyYdqqxxZFHenOYU5+1Yov9nglE9HciqiKiSiJ6T9x+Xb848XTjfUpeTDtVnzjydHyi2GeduPJO+7Ojjw4i+o+4Nso+UeTp+sSRGdNWJd4r8VT9othn3fOwhXa7CiJ6kohGx+1PJ644MXXjfUpeTDvV6xVHHunHFac+a8UWIvqBzdqX5DujPFYUeenElZTMmHaqc5gjT3WsqPBUxgoluO4hoklEtJaIDtp/Jyb5/K/ZbQ4S0ddS2XpSbvwWa7oPAPkAagCcCaAIwG4AF8S1+Q6AP9nPvwDgaReY1wAYYz+/JRVThWe3GwdgA4BtAOZnaN85AHYCmGhvv8OFPj8I4Bb7+QUAalPwPgDgEgAVSfZ/DMAqAATgSgCvKfjaifnemP5+1InpxIs5Lq8AWAngMxnaNwHAfgCzFH3ixPsZgLvt51MAtAAoSsGbBuCSmO/agQQ+1vKLIlPZLyo8Hb8o2qfrFxWmsm/sYz3Wfl4I4DUAV8a1UZ7DFHnK85cqM+Z4qMxhKjYqz2GKPOX5K+Y9PwTwBIAVCfZpxRUFnpZPVJg6PlG0USuuKPDS8UktgLIU+3XnMCeeVlxRYdptdGKLk426c5gTTyu22O0eBXCT/bwIwIQM/eLE0433KXlp+MTJPi2fKDK1/RLTr0YAszPxiQJPe6w4MXX9omCjtl8ceDqxfgaAIwCK7e3lAP5PXBvd6xUVps71iiPPfl011qvYp3u9osLUuV6ZC6ACwBgABQBeBnB2umNFkac7fzkydcaKoo3KY0WR5zhWkOC6B8A9AG6zn98WZcS9bxKAw/bfifbziamOKTPnPAPjcgCHmPkwMw8AeArAjXFtboQVGADg7wCuJSLKhMnMrzJzj725DcDpGdoIAP8XwN0A+lKwVHnfAvB7Zm617T3hApMBjLeflwJoSAZj5g2wvpzJdCOAx9jSNgATiGhaKgOdmMy8JdpfOPtExUYA+D6AfwBwOn4qvC8BeIaZj9rtUzIVeAxgnP1dHmu3DaXgHWPmN+3nnQAqYQWCWGn5RYWp4xdFGwFFvyjydP2iwlT2jX2su+zNQvvBcc2U5zAVnub8pWojoDiHKfKU5zBFnvL8BQBEdDqAfwGwLEkTrbjixNP1iaKNgHpcUeFpxRUFnpZPFKUdW1JJN65oSDm2KEhrDlOQVmwholJYJ54P2Z8/wMxtcc2U/aLC0/GLon2Aok8UeVo+UWRq+SVG1wKoYea34l5Pd6wk5GU4VpLZCKQ3VpLx0h0ryXi6PikAUExEBbAu9uLnPN3rFUdmGrHFyUZAI64o8HSvV1SYOrHlfFg3EHqYOQRgPYBPxbXRGSuOvDTGioqNgPpYUeHpjBUVnuNYSXLdEzsmHgXwiQSf/xEAa5m5xT6uawFcn8JeALkvIZkB4O2Y7ToMvZg42cY+sO0AJmfIjNU3Yd2ZS5tnpyPNZOYXU3B07DsXwLlEtJmIthGRkyNVmEsAfJmI6mDd3fu+gq2ZfF4mcvKJo4hoBoBPAvijKxZZPplIROVEtIOIvpoh73ewJo0GAHsB/ICZIypvJCst8WJY/6mOVdp+ScGMlbJfkvHS9UsK+9L2Swqmlm/ISrPfBSvorGXmpH5RmcMUeLFS8okTU3MOU7FRaw5T4C2B3vz1awC3AkjmN9244sSLleo4ScnU9YmCjbpxxYm3BPoxhQGsscfqzQn2685hTrxYqfolJTONOczJRt05zImnG1vOANAE4GGyUraXEVFJXBsdv6jwYuXkF0eepk9U7NP1iQoz3Zj/BQBPJng93XifjBcr3XOwhMwMzsOS2ZhuvE/GU/YJM9cDuA/AUQDHALQz85q4ZlpxRZEZq5R+UeHpxBVF+7TiiiJzCdRjSwWA9xPRZCIaAyvbYmZcG52xosKLlcpYcWRqjhUVG3XGigov3flrKjMfs583ApiaoE1ac1mub2DkVET0ZQDzAdybASMPwAMAfuSWXbDuTp4D4GoAXwTwP0Q0IUPmFwE8wsynw/pyPm7b7isR0TWwJoRFGaJ+DWCR6k0BBRUAuBTWfyQ/AmAxEZ2bAe8jAHYBmA7gIgC/I6Lxqd8CENFYWHdo/4OZOzL4fC2mjl8ceNp+ceCl5RcHppZvmDnMzBfBugt/ORHNVetZZjyd+SsVM505TMFGrTlMgac8fxHRvwI4wcw7VPuTSjo8VZ84MXV9omijsk8UeenElPcx8yWw0m6/S0QfcGjvJCWeZlxxYurOYU483TnMiacbWwpgpf3+kZkvBtANK9U3XSnzFP2iwtPxiQpP1ycqTO2YT0RFAG4A8DeFfjlKhad7DubATCfep+Jpx3sHnrJPyKrdvxHWzarpAErs+T5t6TBVYosTL424omKfVqxXZCrHFmauhJVNsgbAS7D8GVbpX6Y81bGiyFQeK4o85bGiyEvrmiXucxiJs3/TUq4vYOsx+C7P6fZrCduQlW5UCiCQIRNEdB2A2wHcwMz9GfDGwaofKieiWlj1Vc9T8oVxVOyrA/A8MweZ+QisOv1zMrARsAbZcgBg5q0ARgMoS8FMJaVjrCsiejesdOUbmTmVj1U0H8BTtk8+A+APRJQodUlVdQBWM3M3MzfDqh90XLgnhb4OK72LmfkQrJrA81K9gYgKYV10/5WZn0nQRNsvCkwtvyjwtPyiwNP2iwJT2zcAwFbK8KsYmvqmO4c58XTmLxWm7hymYqPuHObE05m/rgJwg92XpwB8kIj+N66Njk9UeLo+cWLq+kTFRh2fqPC0Y4r937doOuuzsMofY6U1hynwtOOKAlNrDlPgac1hCjzd+asOQF1M1tPfYV2Mx0rHLyo8Hb+o8HR8osLTjSsqzHTiykcBvMnMxxPsS+c8LBUv3XOwVMx0zsNS8dI5D0vF0/HJdQCOMHMTMwcBPANrLYRY6cZ6FaZObHHi6cYVFft0Y70KUyu2MPNDzHwpM38AQKttQ6x044oTL5244sTUjStOPN244sRL67wYwHGyy3Xsv4lKWdK7pmSHRTK8fMC6Q3QY1p246OKT74pr810MXhRnuQvMi2EtenmOGzbGtS9H6kVxVOy7HsCj9vMyWKk1kzNkroK9UA5OpQFRCuYcJF+A8l8weEGc1xX9nYo5C8AhAO/V+P4k5cW1ewQKi0c52Hc+gHX2sR4DK+Vqbga8PwJYYj+fCmuwplqYjQA8BuDXKdpo+UWRqewXFZ6OXxTt0/KLIlPZN7AWM5pgPy8GsBHAv8a1UZ7DFHnK85cqM659OVLPYSo2Ks9hijyt+SvmfVcj8QKUWnFFgaflExWmjk8UbdSKKwo83ZhSAmBczPMtAK6Pa6M8hynytOKKCjOu/SNIPYep2Kg8hynytGKL3W4jgHfaz5cAuDddvyjydP2SkqfjE0X70on3Tsx0/PIUgK8n2ad9HubA0z4Hc2Lq+kXBxnT8koqnE+uvALDP/lyCVc///bg2utcrKkyd6xVHXlz7cqSO9Sr26V6vqDB1Y8s7Yr7DVRi6gK7u/OXES+d6JSVTd6wo2Kh7buzEUxoriLvugZUxFLuI5z0J3jMJ1g2RifbjCIBJjsdU9eB79YCVHnTAHqC326/9AtadRsC68/Y3+8vyOoAzXWC+DOA4rHSYXbDuHqbNi2tbDocTTQX7CFaa135YtUZfcKHPFwDYDOvmxi4AH07BehJWbVoQ1l28bwL4NoBvx9j3e/uz9jr1V5G5DNZdv6hPtmfCi2v7CJwnA0cegJ/YPqmAVXqQSX+nw0rX2mvzvuzAex+s1Ks9McfoY5n4RZGp7BcVno5fVHmaflHps7JvALwb1grce+y2P08w9pTnMEWe7vzlyIxrX57qu6Noo/IcpshTnr/i2FfDvvhO1yeKPC2fqDB1fKJoo3ZcceBp+QTWr2Ttth/7cCpOpTWHKfJ044ojM679I0g9hynxoDiHKfZZK7bY77kIwHZYY/CfsE4iM4ktTjxdv6Tk6fhElafqE40+68b8Elj/vS+NeS0TnzjxtHyiwkzDL448Hb8o9FnXJ3fCurirAPA4gFHI/HrFiakb71Py4tqWK3xvnOxL53rFiakbWzban78bwLUujBUnXjpjJSUzjbHiyIPeWHHqs+NYQeLrnsmwbqQctL/Lk+y28wEsi3nvN2CNm0NQuCHKzNYdLZFIJBKJRCKRSCQSiUQiPyvXa2CIRCKRSCQSiUQikUgkEjlKbmCIRCKRSCQSiUQikUgk8r3kBoZIJBKJRCKRSCQSiUQi30tuYIhEIpFIJBKJRCKRSCTyveQGhkgkEolEIpFIJBKJRCLfS25giEQikUgkEolEIpFIJPK95AaGSCQSiUQikUgkEolEIt/r/wP4A+2mDe+EtQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1080x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 160
        },
        "id": "NsplimcqlbZa",
        "outputId": "5c0c0bbe-87cc-42ed-f0b5-c1c3b21a611c"
      },
      "source": [
        "ecg_plot.plot_1(X_val[5].T[1]*(1/1000), sample_rate=500, title = 'MI')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x144 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "jZ9NDc7jl2vm",
        "outputId": "8208e890-a8be-4e8b-c14f-aac442bed3c8"
      },
      "source": [
        "plt.plot(X_val[100][1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ff2fa3b60b8>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 212
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "ywstC8Y7mCbr",
        "outputId": "f3509ebc-b61c-4d38-f139-293cffd69710"
      },
      "source": [
        "plt.plot(data_pad[1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ff4db926940>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 193
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "WsStZHivkTIm",
        "outputId": "8f9a6dc7-a28b-4e70-aadd-97a9aeaf23aa"
      },
      "source": [
        "plt.plot(X_val[5][1][:])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ff2fa3fb208>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 264
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nid69FGpk9e4"
      },
      "source": [
        "X_val = []\r\n",
        "for j in ecg_val_files:\r\n",
        "  data = load_challenge_data(j)[0]\r\n",
        "  ecg = pad_sequences(data, maxlen=5000, truncating='post',padding=\"post\")\r\n",
        "  ecg_shaped = ecg.reshape(5000,12)\r\n",
        "  X_val.append(ecg)\r\n",
        "X_val = np.asarray(X_val)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i1TIuQqAlYcv",
        "outputId": "780dd186-421d-4fa7-aee6-d020521cbaa8"
      },
      "source": [
        "X_val.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4311, 12, 5000)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 257
        }
      ]
    }
  ]
}