UnDIP.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "296078f2e9cf43d38785fa2fe286a8f7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_2638a1da24ba42e4b3ec12828299d275",
              "IPY_MODEL_c800cacd03dc420b9caa5bf18160d5ad",
              "IPY_MODEL_092930e5d1e045f1b06e5834fe1cf1be"
            ],
            "layout": "IPY_MODEL_8ba585478e4841269b2aa4b18e5eb740"
          }
        },
        "2638a1da24ba42e4b3ec12828299d275": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_6aeee3ec640c485ebdf07496097bf6b3",
            "placeholder": "​",
            "style": "IPY_MODEL_9cac5631ca2c4526a165d5c63d5349ff",
            "value": "100%"
          }
        },
        "c800cacd03dc420b9caa5bf18160d5ad": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_b8ae24ab7ec1435f9cf057859efc3ae3",
            "max": 1,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_6a0568f98ca7407994983fc14aed5c4a",
            "value": 1
          }
        },
        "092930e5d1e045f1b06e5834fe1cf1be": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_0687501c6f0f4074b6cc1f4ec1fac4b9",
            "placeholder": "​",
            "style": "IPY_MODEL_0640b14bc362480883e1b20b1a47ac2b",
            "value": " 1/1 [01:09&lt;00:00, 69.56s/it]"
          }
        },
        "8ba585478e4841269b2aa4b18e5eb740": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "6aeee3ec640c485ebdf07496097bf6b3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9cac5631ca2c4526a165d5c63d5349ff": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "b8ae24ab7ec1435f9cf057859efc3ae3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "6a0568f98ca7407994983fc14aed5c4a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "0687501c6f0f4074b6cc1f4ec1fac4b9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0640b14bc362480883e1b20b1a47ac2b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d1dab3f91fef4e728f6bc501b3f06120": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_78d060d63b82457dbc706ebb0ce3143f",
              "IPY_MODEL_4ffadcb8802e4cbfbebf8980235faf45",
              "IPY_MODEL_69eec63eeb2b4d32998e5d11c5a77078"
            ],
            "layout": "IPY_MODEL_15f888431f374e0abb1463c22aa9b408"
          }
        },
        "78d060d63b82457dbc706ebb0ce3143f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c805cedd95ca48d49dbd92f29e7b871e",
            "placeholder": "​",
            "style": "IPY_MODEL_3efe02b5fc97450e8bd0ce3ce0e19e8c",
            "value": "100%"
          }
        },
        "4ffadcb8802e4cbfbebf8980235faf45": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ffbed2893df34ec9a3707449b165bf35",
            "max": 1,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_caa9c79064804058a64c48dc2154e26c",
            "value": 1
          }
        },
        "69eec63eeb2b4d32998e5d11c5a77078": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4b35eacde4204ee6a1e435beb08ef773",
            "placeholder": "​",
            "style": "IPY_MODEL_ce714fd2aa8d4c3a8039ecb74bbed7cf",
            "value": " 1/1 [01:09&lt;00:00, 69.54s/it]"
          }
        },
        "15f888431f374e0abb1463c22aa9b408": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c805cedd95ca48d49dbd92f29e7b871e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3efe02b5fc97450e8bd0ce3ce0e19e8c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "ffbed2893df34ec9a3707449b165bf35": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "caa9c79064804058a64c48dc2154e26c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4b35eacde4204ee6a1e435beb08ef773": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ce714fd2aa8d4c3a8039ecb74bbed7cf": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/BehnoodRasti/Unmixing_Tutorial_IEEE_IADF/blob/main/UnDIP.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Supervised Unmixing\n",
        "\n",
        "Supervised unmixing using the UnDIP architecture for both abundances estimation.\n",
        "\n",
        "---\n",
        "\n",
        "## Imports"
      ],
      "metadata": {
        "id": "lpc_zzJUQzHv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/BehnoodRasti/Unmixing_Tutorial_IEEE_IADF.git\n",
        "!git clone https://github.com/BehnoodRasti/UnDIP"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3DX-laLkPbxL",
        "outputId": "cda917d2-efd5-4e29-d990-cf31499b9fba"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Unmixing_Tutorial_IEEE_IADF'...\n",
            "remote: Enumerating objects: 254, done.\u001b[K\n",
            "remote: Counting objects: 100% (12/12), done.\u001b[K\n",
            "remote: Compressing objects: 100% (9/9), done.\u001b[K\n",
            "remote: Total 254 (delta 4), reused 3 (delta 3), pack-reused 242\u001b[K\n",
            "Receiving objects: 100% (254/254), 58.99 MiB | 31.69 MiB/s, done.\n",
            "Resolving deltas: 100% (126/126), done.\n",
            "Cloning into 'UnDIP'...\n",
            "remote: Enumerating objects: 179, done.\u001b[K\n",
            "remote: Counting objects: 100% (179/179), done.\u001b[K\n",
            "remote: Compressing objects: 100% (113/113), done.\u001b[K\n",
            "remote: Total 179 (delta 74), reused 163 (delta 64), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (179/179), 21.72 MiB | 30.43 MiB/s, done.\n",
            "Resolving deltas: 100% (74/74), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install munkres"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZhXa-_L1RVmB",
        "outputId": "5d28d98d-476d-4acb-9d3e-b6b719315c38"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting munkres\n",
            "  Downloading munkres-1.1.4-py2.py3-none-any.whl (7.0 kB)\n",
            "Installing collected packages: munkres\n",
            "Successfully installed munkres-1.1.4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"\n",
        "Created on Thu Apr  1 09:23:20 2021\n",
        "@author: behnood\n",
        "\"\"\"\n",
        "from __future__ import print_function\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import os\n",
        "\n",
        "import numpy as np\n",
        "from UnDIP.models import *\n",
        "\n",
        "import torch\n",
        "import torch.optim\n",
        "\n",
        "from skimage.metrics  import peak_signal_noise_ratio as compare_psnr\n",
        "from skimage.metrics  import mean_squared_error as compare_mse\n",
        "from UnDIP.utils.denoising_utils import *\n",
        "\n",
        "from skimage._shared import *\n",
        "from skimage.util import *\n",
        "from skimage.metrics.simple_metrics import _as_floats\n",
        "from skimage.metrics.simple_metrics import mean_squared_error\n",
        "\n",
        "import time\n",
        "from tqdm.notebook import tqdm\n",
        "import scipy.io as sio\n",
        "import scipy\n",
        "\n",
        "from UnDIP.UtilityMine import *"
      ],
      "metadata": {
        "id": "7V_OZm0_Ra2D"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from Unmixing_Tutorial_IEEE_IADF.utils.data import HSI\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.metrics import MeanSquareError as MSE\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.metrics import aRMSE as RMSE\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.metrics import SADDegrees as SAD\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.metrics import SRE\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.aligners import MunkresAbundancesAligner as Aligner\n",
        "from Unmixing_Tutorial_IEEE_IADF.utils.noises import AdditiveWhiteGaussianNoise as AWGN"
      ],
      "metadata": {
        "id": "M9MQc-WGRz2L"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## GPU parameters\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "ZML7VOm6R5DO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "torch.backends.cudnn.enabled = True\n",
        "torch.backends.cudnn.benchmark =True\n",
        "dtype = torch.cuda.FloatTensor"
      ],
      "metadata": {
        "id": "ZCijqH1jR2Jl"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## HSI Data\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "M-YzCpu3R7aw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "hsi = HSI(\"Sim1.mat\")\n",
        "print(hsi)\n",
        "\n",
        "noise = AWGN()\n",
        "\n",
        "SNR = 40\n",
        "\n",
        "hsi.Y = noise.fit_transform(hsi.Y, SNR=SNR, seed=0)\n",
        "\n",
        "Y, _, _ = hsi()\n",
        "p1, nr1, nc1 = hsi.L, hsi.H, hsi.W\n",
        "rmax = hsi.p\n",
        "assert Y.shape == (p1, nr1 * nc1)\n",
        "img_np_gt = Y.reshape(p1, nr1, nc1)\n",
        "print(img_np_gt.shape)\n",
        "\n",
        "hsi.plot_endmembers()\n",
        "hsi.plot_abundances()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 874
        },
        "id": "IxfulLI2R_4h",
        "outputId": "3d75d159-c042-4b8e-e0da-41db8eca42b3"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Matlab data keys: dict_keys(['__header__', '__version__', '__globals__', 'Y', 'E', 'A', 'p', 'H', 'W', 'L', 'labels'])\n",
            "HSI => Sim1\n",
            "---------------------\n",
            "224 bands,\n",
            "105 lines, 105 samples, (11025 pixels),\n",
            "6 endmembers (['#0', '#1', '#2', '#3', '#4', '#5'])\n",
            "GlobalMinValue: 0.0, GlobalMaxValue: 1.0\n",
            "\n",
            "Y shape: (224, 11025)\n",
            "Desired SNR: 40\n",
            "Sigmas after normalization: 0.0668153104781061\n",
            "Sigma mean based on SNR: 0.09648830104929844\n",
            "Final sigmas value: 0.006446895792113846\n",
            "(224, 105, 105)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 12 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PLOT = False\n",
        "save_result=False\n",
        "\n",
        "tol1=1\n",
        "tol2=1\n",
        "\n",
        "for fi in tqdm(range(tol1)):\n",
        "    for fj in tqdm(range(tol2)):\n",
        "            #%%\n",
        "        #img_noisy_np = get_noisy_image(img_np_gt, 1/10)\n",
        "        img_noisy_np = img_np_gt # add_noise(img_np_gt, 1/npar[0,fi])#11.55 20 dB, 36.7 30 dB, 116.5 40 dB\n",
        "        #print(compare_snr(img_np_gt, img_noisy_np))\n",
        "        img_resh=np.reshape(img_noisy_np,(p1,nr1*nc1))\n",
        "        V, SS, U = scipy.linalg.svd(img_resh, full_matrices=False)\n",
        "        PC=np.diag(SS)@U\n",
        "        img_resh_DN=V[:,:rmax]@PC[:rmax,:]\n",
        "        img_resh_np_clip=np.clip(img_resh_DN, 0, 1)\n",
        "        II,III = Endmember_extract(img_resh_np_clip,rmax)\n",
        "        E_np1=img_resh_np_clip[:,II]\n",
        "        #asq=Endmember_reorder2(E_np,E_np1)\n",
        "        #asq1=rmax-1-asq\n",
        "        #E_np1=E_np1[:,asq]  \n",
        "        #%% Set up Simulated \n",
        "        INPUT = 'noise' # 'meshgrid'\n",
        "        pad = 'reflection'\n",
        "        need_bias=True\n",
        "        OPT_OVER = 'net' # 'net,input'\n",
        "        \n",
        "        # \n",
        "        reg_noise_std = 0.0# 1/100# 1./30. # set to 1./20. for sigma=50\n",
        "        LR1 = 0.001\n",
        "        \n",
        "        OPTIMIZER1='adam' # 'RMSprop'#'adam' # 'LBFGS'\n",
        "        show_every = 100\n",
        "        exp_weight=0.99\n",
        "        \n",
        "        num_iter1 = 3000\n",
        "        #num_iter1 = 500\n",
        "        nf=256\n",
        "        input_depth = rmax#img_noisy_np.shape[0]\n",
        "        class CAE_AbEst(nn.Module):\n",
        "            def __init__(self):\n",
        "                super(CAE_AbEst, self).__init__()\n",
        "                # encoding layers\n",
        "                self.conv1 = nn.Sequential(\n",
        "                     UnmixArch(\n",
        "                            input_depth, rmax,\n",
        "                            # num_channels_down = [8, 16, 32, 64, 128], \n",
        "                            # num_channels_up   = [8, 16, 32, 64, 128],\n",
        "                            # num_channels_skip = [4, 4, 4, 4, 4], \n",
        "                            num_channels_down = [ nf],\n",
        "                            num_channels_up =   [ nf],\n",
        "                            num_channels_skip =    [ 4],  \n",
        "                            filter_size_up = 3,filter_size_down = 3,  filter_skip_size=1,\n",
        "                            upsample_mode='bilinear', # downsample_mode='avg',\n",
        "                            need1x1_up=True,\n",
        "                            need_sigmoid=True, need_bias=True, pad=pad, act_fun='LeakyReLU').type(dtype)\n",
        "                )\n",
        "\n",
        "            def forward(self, x):\n",
        "                x = self.conv1(x)\n",
        "\n",
        "                return x\n",
        "\n",
        "        net1 = CAE_AbEst()\n",
        "        net1.cuda()\n",
        "        print(net1)\n",
        "\n",
        "        # Compute number of parameters\n",
        "        s  = sum([np.prod(list(p11.size())) for p11 in net1.parameters()]); \n",
        "        print ('Number of params: %d' % s)\n",
        "        \n",
        "        # Loss\n",
        "        mse = torch.nn.MSELoss().type(dtype)\n",
        "        img_noisy_torch = np_to_torch(img_noisy_np).type(dtype)\n",
        "        # if fk==0:\n",
        "        net_input1 = get_noise(input_depth, INPUT,\n",
        "          (img_noisy_np.shape[1], img_noisy_np.shape[2])).type(dtype).detach()\n",
        "        E_torch = np_to_torch(E_np1).type(dtype)\n",
        "        #\n",
        "        #A_true_np_resh=A_true_np.reshape(A_true_np.shape[0],A_true_np.shape[1]*A_true_np.shape[2])\n",
        "        #%%\n",
        "        net_input_saved = net_input1.detach().clone()\n",
        "        noise = net_input1.detach().clone()\n",
        "        out_avg = None\n",
        "        out_HR_avg= None\n",
        "        last_net = None\n",
        "        RMSE_LR_last = 0\n",
        "        \n",
        "        i = 0\n",
        "        def closure1():\n",
        "            \n",
        "            global i, RMSE_LR, RMSE_LR_ave, RMSE_HR, out_LR_np, out_avg_np, out_LR\\\n",
        "                , out_avg,out_HR_np, out_HR_avg, out_HR_avg_np, RMSE_LR_last, last_net\\\n",
        "                    , net_input,RMSE_LR_avg,RMSE_HR_avg,RE_HR_avg, RE_HR, Eest\\\n",
        "                        , MAE_LR,MAE_LR_avg,MAE_HR,MAE_HR_avg\n",
        "            \n",
        "            if reg_noise_std > 0:\n",
        "                net_input = net_input_saved + (noise.normal_() * reg_noise_std)\n",
        "            \n",
        "            out_LR = net1(net_input1)\n",
        "            out_HR=torch.mm(E_torch.view(p1,rmax),out_LR.view(rmax,nr1*nc1))\n",
        "            # Smoothing\n",
        "            if out_avg is None:\n",
        "                out_avg = out_LR.detach()\n",
        "                out_HR_avg = out_HR.detach()\n",
        "            else:\n",
        "                out_avg = out_avg * exp_weight + out_LR.detach() * (1 - exp_weight)\n",
        "                out_HR_avg = out_HR_avg * exp_weight + out_HR.detach() * (1 - exp_weight)\n",
        "              \n",
        "        #%%\n",
        "            out_HR=out_HR.view((1,p1,nr1,nc1))\n",
        "            total_loss = mse(img_noisy_torch, out_HR)\n",
        "            total_loss.backward()\n",
        "        \n",
        "         \n",
        "        \n",
        "            out_LR_np = out_LR.detach().cpu().squeeze().numpy()\n",
        "            out_avg_np = out_avg.detach().cpu().squeeze().numpy()\n",
        "            out_HR_np = out_HR.detach().cpu().squeeze().numpy()\n",
        "           # out_HR_avg=out_HR_avg.view((1,p1,nr1,nc1))\n",
        "            out_HR_avg_np = out_HR_avg.detach().cpu().squeeze().numpy()\n",
        "            #RMSE_LR = 100*np.sqrt(compare_mse(A_true_np.astype(np.float32), np.clip(out_LR_np, 0, 1)))\n",
        "            #RMSE_LR_avg   = 100*np.sqrt(compare_mse(A_true_np.astype(np.float32), np.clip(out_avg_np, 0, 1)))\n",
        "            #RMSE_HR= 100*np.sqrt(compare_mse(img_np_gt.astype(np.float32), np.clip(out_HR_np, 0, 1)))\n",
        "            #RMSE_HR_avg= 100*np.sqrt(compare_mse(img_np_gt.astype(np.float32).reshape((p1,nr1*nc1)), np.clip(out_HR_avg_np, 0, 1)))\n",
        "            #MAE_LR= 100*np.mean(abs(A_true_np.astype(np.float32)- np.clip(out_LR_np, 0, 1)))\n",
        "            #MAE_HR= 100*np.mean(abs(img_np_gt.astype(np.float32)- np.clip(out_HR_np, 0, 1)))\n",
        "            #MAE_LR_avg= 100*np.mean(abs(A_true_np.astype(np.float32)- np.clip(out_avg_np, 0, 1)))\n",
        "            #MAE_HR_avg= 100*np.mean(abs(img_np_gt.astype(np.float32).reshape((p1,nr1*nc1))- np.clip(out_HR_avg_np, 0, 1)))\n",
        "            \n",
        "            \n",
        "            #RE_HR= 100*np.sqrt(compare_mse(img_noisy_np.astype(np.float32), np.clip(out_HR_np, 0, 1)))\n",
        "            #RE_HR_avg= 100*np.sqrt(compare_mse(img_noisy_np.astype(np.float32).reshape((p1,nr1*nc1)), np.clip(out_HR_avg_np, 0, 1)))\n",
        "\n",
        "            # Note that we do not have GT for the \"snail\" example\n",
        "            # So 'PSRN_gt', 'PSNR_gt_sm' make no sense\n",
        "            # print ('Iteration %05d    Loss %f   RMSE_LR: %f   RMSE_LR_avg: %f RMSE_HR: %f  RMSE_HR_avg: %f' % (i, total_loss.item(), RMSE_LR, RMSE_LR_avg, RMSE_HR, RMSE_HR_avg), '\\r', end='')\n",
        "            if  PLOT and i % show_every == 0:\n",
        "                out_LR_np = torch_to_np(out_LR)\n",
        "                out_avg_np = torch_to_np(out_avg)\n",
        "\n",
        "                out_LR_np = np.clip(out_LR_np, 0, 1)\n",
        "                out_avg_np = np.clip(out_avg_np, 0, 1)\n",
        "                \n",
        "                f, (ax1, ax2, ax3) = plt.subplots(1, 3, sharey=True, figsize=(10,10))\n",
        "                ax1.imshow(np.stack((out_LR_np[2,:,:],out_LR_np[1,:,:],out_LR_np[0,:,:]),2))\n",
        "                ax2.imshow(np.stack((out_avg_np[2,:,:],out_avg_np[1,:,:],out_avg_np[0,:,:]),2))\n",
        "                ax3.imshow(np.stack((A_true_np[2,:,:],A_true_np[1,:,:],A_true_np[0,:,:]),2))\n",
        "                plt.show()\n",
        "    \n",
        "            i += 1\n",
        "        \n",
        "            return total_loss\n",
        "        \n",
        "        p11 = get_params(OPT_OVER, net1, net_input1)\n",
        "        optimize(OPTIMIZER1, p11, closure1, LR1, num_iter1)"
      ],
      "metadata": {
        "id": "EehS5ybIPakU",
        "outputId": "fc537107-a98d-4bff-98f8-a1e1fbbf5c54",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "296078f2e9cf43d38785fa2fe286a8f7",
            "2638a1da24ba42e4b3ec12828299d275",
            "c800cacd03dc420b9caa5bf18160d5ad",
            "092930e5d1e045f1b06e5834fe1cf1be",
            "8ba585478e4841269b2aa4b18e5eb740",
            "6aeee3ec640c485ebdf07496097bf6b3",
            "9cac5631ca2c4526a165d5c63d5349ff",
            "b8ae24ab7ec1435f9cf057859efc3ae3",
            "6a0568f98ca7407994983fc14aed5c4a",
            "0687501c6f0f4074b6cc1f4ec1fac4b9",
            "0640b14bc362480883e1b20b1a47ac2b",
            "d1dab3f91fef4e728f6bc501b3f06120",
            "78d060d63b82457dbc706ebb0ce3143f",
            "4ffadcb8802e4cbfbebf8980235faf45",
            "69eec63eeb2b4d32998e5d11c5a77078",
            "15f888431f374e0abb1463c22aa9b408",
            "c805cedd95ca48d49dbd92f29e7b871e",
            "3efe02b5fc97450e8bd0ce3ce0e19e8c",
            "ffbed2893df34ec9a3707449b165bf35",
            "caa9c79064804058a64c48dc2154e26c",
            "4b35eacde4204ee6a1e435beb08ef773",
            "ce714fd2aa8d4c3a8039ecb74bbed7cf"
          ]
        }
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "296078f2e9cf43d38785fa2fe286a8f7"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d1dab3f91fef4e728f6bc501b3f06120"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CAE_AbEst(\n",
            "  (conv1): Sequential(\n",
            "    (0): Sequential(\n",
            "      (1): Concat(\n",
            "        (0): Sequential(\n",
            "          (1): Sequential(\n",
            "            (0): ReflectionPad2d((0, 0, 0, 0))\n",
            "            (1): Conv2d(6, 4, kernel_size=(1, 1), stride=(1, 1))\n",
            "          )\n",
            "          (2): BatchNorm2d(4, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "          (3): LeakyReLU(negative_slope=0.1, inplace=True)\n",
            "        )\n",
            "        (1): Sequential(\n",
            "          (1): Sequential(\n",
            "            (0): ReflectionPad2d((1, 1, 1, 1))\n",
            "            (1): Conv2d(6, 256, kernel_size=(3, 3), stride=(2, 2))\n",
            "          )\n",
            "          (2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "          (3): LeakyReLU(negative_slope=0.1, inplace=True)\n",
            "          (4): Sequential(\n",
            "            (0): ReflectionPad2d((1, 1, 1, 1))\n",
            "            (1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1))\n",
            "          )\n",
            "          (5): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "          (6): LeakyReLU(negative_slope=0.1, inplace=True)\n",
            "          (7): Upsample(scale_factor=2.0, mode=bilinear)\n",
            "        )\n",
            "      )\n",
            "      (2): BatchNorm2d(260, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "      (3): Sequential(\n",
            "        (0): ReflectionPad2d((1, 1, 1, 1))\n",
            "        (1): Conv2d(260, 256, kernel_size=(3, 3), stride=(1, 1))\n",
            "      )\n",
            "      (4): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "      (5): LeakyReLU(negative_slope=0.1, inplace=True)\n",
            "      (6): Sequential(\n",
            "        (0): ReflectionPad2d((0, 0, 0, 0))\n",
            "        (1): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
            "      )\n",
            "      (7): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "      (8): LeakyReLU(negative_slope=0.1, inplace=True)\n",
            "      (9): Sequential(\n",
            "        (0): ReflectionPad2d((0, 0, 0, 0))\n",
            "        (1): Conv2d(256, 6, kernel_size=(1, 1), stride=(1, 1))\n",
            "      )\n",
            "      (10): Softmax(dim=None)\n",
            "    )\n",
            "  )\n",
            ")\n",
            "Number of params: 1273394\n",
            "Starting optimization with ADAM\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/container.py:204: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
            "  input = module(input)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Qualitative results\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "1gVDtdfBcqjS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "E0 = E_np1\n",
        "A0 = out_avg_np.reshape(hsi.p, hsi.N)\n",
        "\n",
        "# Plot results\n",
        "hsi.plot_endmembers(E0=E0)\n",
        "hsi.plot_abundances(A0=A0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 631
        },
        "id": "SxRy0hH0YKzX",
        "outputId": "838d10ab-0283-43fa-eda8-967053c6b17c"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 12 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAArkAAADUCAYAAACYqzsZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOy9ebhlSVUn+luxz3THHGqSqsqaqKyiBgqwsPXZ2oqiIt0tft0+BUSkfY40+PQ5tAPdjeL0eO2nLeKATy0R0AY/9UOaFhqfgmirzArFXFBzQVVlVU43773n7Fjvj4gVsWLvfc69mWTmPXVYv++7meecHTv22nvtiPjFihVrETPDYDAYDAaDwWBYJLi9FsBgMBgMBoPBYDjbMJJrMBgMBoPBYFg4GMk1GAwGg8FgMCwcjOQaDAaDwWAwGBYORnINBoPBYDAYDAsHI7kGg8FgMBgMhoWDkVyD4fMMRPStRPTWvZbjdEBEVxDRCSKq9lqWJojoKiJiIuqd4fm3EdHPnG25plzrpUT0mvNxLYPBYNhrGMk1GBYQRPRlRPS3RHSUiI4Q0d8Q0RcBADO/lpm/9gzrHRDRHxHRpyOx+8odyv8VEW1Ggip/f7aL63yaiJ4u35n5LmZeZeb6TOTe4VrnhfjFZ/EIEQ3P9bUMBoPBYCTXYFg4ENE6gDcBeAWAgwAuA/BTALbO0iXeCeB5AB7YZfkXRYIqf//6LMnxmAERXQXgywEwgG/YU2EMBoPh8wRGcg2GxcN1AMDMf8DMNTOfYua3MvM/AgARvYCI3imFo0X2hUT0cSI6TkQvI6LHR0vwMSJ6PRENYp3bzPzLzPxOAJ+TVZWILiSiNxHRo9Ha/NdE5Ijo9wFcAeDPouX3R5suAdEq+jNRxhNE9GdEdAERvTbK/K5ILOVa/5WI7o7H3kNEXx5/fwaAnwDwLbGeD8Tf9xHRbxPR/UR0b7xWFY9VRPRfiOghIroDwL/cxe0+H8DfAbgNwLd3HL+QiP5nfP5vJ6Ir47VarhDx3r8zfn4BEb0zyvMIEX2KiL5elb061neciP4ngAsbOngDET0QLf7vIKKb1LHbiOiVRPTf4/l/T0SPV8dvijIfIaLPENFPxN8dEf0YEX2SiB6O78/BeGxERK+Jvz8a9XTJLp6fwWAwnDaM5BoMi4ePAaiJ6PeI6OuJ6MAuzvk6ALcC+BIAPwrgVQjW2kMAbgbwnHMg5w8BuAfARQAuQSCbzMzfBuAuAP86Wn5fPuX8ZwP4NgRL9eMB/C8Av4tgvf4wgP+syr4LwJPjsdcBeAMRjZj5zwH8HID/Fq/1pFj+NgATANcCeAqArwXwnfHYdwH4V/H3pwL4pl3c6/MBvDb+fV0HsftWAC9DIKHvj+V2iy8G8NF47ssB/DYRUTz2OgDvicdehjbB/h8ADgO4GMB7O677bIRVgAMAPgHgZwGAiNYAvA3AnwO4FOE5/UU858UAvhHAV8RjjwB4ZTz27QD2IbxXFwD4XgCnTuNeDQaDYdcwkmswLBiY+RiAL0NYGv8tAA8S0Rt3sJi9nJmPMfOHAHwQwFuZ+Q5mPopAhJ7yOYj0K9FqJ38vi7+PATwOwJXMPGbmv2ZmPo16f5eZP6lk/CQzv42ZJwDeoGVm5tcw88PMPGHmXwQwBHB9V6XxOT0TwA8w80lm/iyAX0IgfADwzQB+mZnvZuYjAH5+lpBE9GUArgTwemZ+D4BPAnhuo9h/Z+Z3MPMWgJ8E8L8R0aFdPoc7mfm3or/y7yE800uI6AoAXwTgPzLzFjO/A0DhD83Mv8PMx+N1XwrgSUS0TxX5E2b+h/hMX4swUQACyX+AmX+RmTdjHX8fj30vgJ9k5ntUvd8UrdFjBHJ7bVxleE98Xw0Gg+Gsw0iuwbCAYOYPM/MLmPlyBEvspQB+ecYpn1GfT3V8X/0cxPl+Zt6v/v5j/P3/QbAOvpWI7iCiHzvNenctMxH9MBF9OC7LP4pgTSyW7hWuBNAHcL8QcwC/iWDtBMKzvFuVv3MHOb8dYdLwUPz+OrQtqqk+Zj4B4Ei8zm6QfKOZeSN+XI3nP8LMJ7tkjW4XvxDdCo4B+HQ8pJ+L9rveQH6mhxDIeheuBPAn6tl9GMG15RIAvw/gLQD+kIjuI6KXE1F/l/dpMBgMpwUjuQbDgoOZP4Kw/H7zHotSIFr/foiZr0HYjPV/EdFXy+GzdZ3of/ujCBbYA8y8H8BRALKk37zW3Qib9C5UxHydmcVf9X4Ekie4Ysa1l+J1vyL6vj4A4AcRLKZPUkUPqXNWEdwq7gMgBHVZlf2Cne5ZyXmAiFamyPpcAM8C8HQE0n+ViLCLuu8GcM2MY1/fmNiMmPneaLH/KWa+EcCXIliEn7/L+zEYDIbTgpFcg2HBQERPIKIfIqLL4/dDCD61f3eW6h8S0Sh+HcTNRLshRs16/hURXRvPPYpg7fPx8GcwnUSdLtYQ/GsfBNAjov8EYF0d/wyAq4jIAQAz3w/grQB+kYjW40aqxxPRV8Tyrwfw/UR0efR3nmWB/sZ4XzciLPU/GcANAP4aJbl7JoWwbwME39m/i+4QDwK4F8DzouX1OxD8j3cEM98J4N0AfopC6LcvA6AjW6whkPmHEUj0z+2m3og3AXgcEf1AfB/WiOiL47HfAPCzavPcRUT0rPj5aUT0RAqb+I4huC/4rgsYDAbD5wojuQbD4uE4wmakvyeikwjk9oMIG73OBj6K4A5wGcLS8ymEJepp+FUq4+S+J/5+GGHz0gmETWO/xsx/GY/9PICXxCXvH/4c5X0LwgapjyEs12+idDd4Q/z/YSJ6b/z8fAADALcjbJz6IwRfVyD4Ob8FwAcQNmv98YxrfzuC7/BdzPyA/AH4VQDfSjlqwusQNsodQdgA+DxVx3cB+BEEMnoTgL/d/a3juQjvwpFY/6vVsVcjPI97433uehLEzMcBfA0CaX4AwMcBPC0e/q8A3ojghnI81isE+AsQnuUxBDeGtyO4MBgMBsNZB53ePg+DwWAwGAwGg2H+YZZcg8FgMBgMBsPCwUiuwWAwGAwGg2HhYCTXYDAYDAaDwbBwMJJrMBgMBoPBYFg4GMk1GAwGg8FgMCwcjOQaDAaDwWAwGBYORnINBoPBYDAYDAsHI7kGg8FgMBgMhoWDkVyDwWAwGAwGw8LBSK7BYDAYDAaDYeFgJNdgMBgMBoPBsHAwkmswGAwGg8FgWDgYyTUYDAaDwWAwLByM5BoMBoPBYDAYFg5Gcg0Gg8FgMBgMCwcjuQaDwWAwGAyGhYORXIPBYDAYDAbDwsFIrsFgMBgMBoNh4WAk12AwGAwGg8GwcDCSazAYDAaDwWBYOBjJNRgMBoPBYDAsHIzkGgwGg8FgMBgWDkZyDQaDwWAwGAwLByO5BoPBYDAYDIaFg5Fcg8FgMBgMBsPCwUiuwWAwGAwGg2HhYCTXYDAYDAaDwbBwMJJrMBgMBoPBYFg4GMk1GAwGg8FgMCwcjOQaDAaDwWAwGBYORnINBoPBYDAYDAsHI7kGg8FgMBgMhoWDkVyDwWAwGAwGw8LBSK7BYDAYDAaDYeFgJNdgMBgMBoPBsHAwkmswGAwGg8FgWDgYyTUYDAaDwWAwLByM5BoMBoPBYDAYFg5Gcg0Gg8FgMBgMCwcjuQaDwWAwGAyGhYORXIPBYDAYDAbDwsFIrsFgMBgMBoNh4WAk12AwGAwGg8GwcDCSazAYDAaDwWBYOBjJNRgMBoPBYDAsHIzkGgwGg8FgMBgWDkZyDQaDwWAwGAwLByO5BoPBYDAYDIaFg5Fcg8FgMBgMBsPCwUiuwWAwGAwGg2HhYCTXYDAYDAaDwbBwMJJrMBgMBoPBYFg4GMk1GAwGg8FgMCwcjOQaDAaDwWAwGBYORnINBoPBYDAYDAsHI7kGg8FgMBgMhoWDkVyDwWAwGAwGw8LBSK7BYDAYDAaDYeFgJNdgMBgMBoPBsHAwkmswGAwGg8FgWDgYyTUYDAaDwWAwLByM5BoMBoPBYDAYFg5Gcg0Gg8FgMBgMCwcjuQaDwWAwGAyGhYORXIPBYDAYDAbDwsFIrsFgMBgMBoNh4WAk12AwGAwGg8GwcDCSazAYDAaDwWBYOBjJnVMQ0e8Q0WeJ6INTjhMR/QoRfYKI/pGIvvB8y2jYHUyXiwPT5WLA9Lg4MF0uDs6FLo3kzi9uA/CMGce/HsDh+PfdAH79PMhkODPcBtPlouA2mC4XAbfB9LgouA2my0XBbTjLujSSO6dg5ncAODKjyLMAvJoD/g7AfiJ63PmRznA6MF0uDkyXiwHT4+LAdLk4OBe6NJL72MVlAO5W3++JvxkeezBdLg5Ml4sB0+PiwHS5ODhtXfbOqTgGAMDXPW2FHz5SF7+95x+3PgRgU/30KmZ+1XkVzHBa6NIjYLp8LMJ0uTiw/nVxYLpcDMxT//qYIblE9A8AngdgAuCPmPkL4+8HAfw2gK8F8BCAH2fm1+2ZoB146MgEf/vn5WRjdOmnNpn5qZ9DtfcCOKS+Xx5/m2vM0OOLALwAwBMB/AEzv2CvZJyGLj0CpksoXRLREMCvAXg6gIMAPonQJv/H3knahumyxIx2+RoAXw1gBcADAF7OzP/vngnaAetfS0zTpTp+GMA/xWPP2wMRp8J0WWJGu/wrAF8SfweAe5n5+j0RsgPz1L8+JtwViKgP4EoAHwdwK4D3qsOvBLAN4BIA3wrg14nopvMu5AwwgAnq4u8s4I0Anh93G34JgKPMfP/ZqPhcYQc93gfgZwD8zh6Itit06dF02dJlD2E56SsA7APwEgCvJ6Krzr+U02G6zNihXf48gKuYeR3ANwD4GSK69fxLOR3Wv2bsoEvBKwG863zKtVuYLjN2ocsXMfNq/JsbggvMV//6WLHk3gzgdmZmInoqorKJaAXAvwVwMzOfAPBOInojgG8D8GN7Jm0DDMaY/WmdQ0R/AOArAVxIRPcA+M8A+gDAzL8B4M0AngngEwA2APy7syjyuUKnHgGAmf8YAOLvl++RfDNxJnoEPr90ycwnAbxUlXsTEX0KoZP+9PkWchpMlwVmtcsPqXIc/x4P4D3nV8TpsP61wFRdAgARPRvAowD+FsC1eyDfTJguC8zU5TxjnvrXuSa5RPTvAPwSgAEAR0SPAlgFcIqIfg7A0wBMmPlj6rQPIFiR5gYewCaf3iyGmZ+zw3EG8O8/B7HOG3ahx6cw86f2Usbd4Ez0CHx+65KILgFwHYAPddW3VzBd7l6XRPRrCK5ESwDehzDQzA0+3/tXYHe6BPAwgJ8G8FUAvnOvZJ0F0+WudQkAP09EvwDgowB+kpn/ai/k7cI89a9z7a7AzL/LzPsRrAZfAuAWAB8EsB5/XwVwrHHaUQBr51XQHcBgjBt/n0/YSY+PBYILdOvRdDldl3G57bUAfo+ZP7InAk+B6XL3umTmFyL0qV8O4I8BbO2RyJ34fO9fgV3r8mUAfpuZ79lDUWfCdLlrXf4HANcgRBZ4FYA/I6LH75XMTcxT/zq3JJeIDhLRo0R0FMCXAvgrhBnL9QAeIaIfAHACwHrj1HUAx8+nrDuBGRg3/j5fsEs9PibQpUfTZbcuicgB+H0Ef/kX7YG4M2G6PL12ycw1M78TwZXo+863vLPw+dy/ArvTJRE9GWEz6C/tnaQ7w3S5u3bJzH/PzMeZeYuZfw/A3yAs488F5ql/nVt3BWY+ghDo99kAnsbM30NEfwLglcz8NiD55PaI6DAzfzye+iTM2dIog7DJczufOKfYjR4fK/h81iOwe10SESFEPLkEwDOZebw3Ek+H6fKM22UPwSd3bmC63NVY+QMArgJwV2ieWAVQEdGNzegLewnT5Rm3SwZA50XIXWCe9Di3JFdB7yp8CtSGB2Y+SUR/DOCnieg7ATwZISPGl553KWeAAYznROF7iKl6BAAi6iG8jxVC5ztC8LeeYE5gekyYqUuEVIs3AHg6M586n4LtFqbLhKm6JKKLEfw33wTgFIIl8Dnxb25gukyY1S5fBeAP1fcfRiC982WVh+kyYla73A/giwG8HSGE2LcA+BcA/s/zLONUzJMeHysk9/VEdAGAmpkfaRx/IULYqc8iONZ/X2NH8J7Dg7DJj4VHfU6xkx5fgrCTUvA8AD+Fcqf+nsL0mDBVl0R0JYDvQfDbfCBajQDge5j5tedd0ikwXSbMapeMQIJ+A8G17U4AP8DMbzz/Yk6H6TJhqi6ZeQNhNzoAgIhOANhk5gfPv5jTYbpMmNUu+wjhNp8AoAbwEQDf2NiAv6eYJz3OhxQzwMxfpb62lsmief8bz59Epw8GYZurvRZjT7ELPb4Uc0Rou2B6DJilS2a+E3O0bDYNpsuAHXT5IOYsUk0XTJcBO/WxjbIvPbfSnBlMlwG7aJdfdH4lOj3Mkx7nnuQuAhjAGPOhcMOZw/S4ODBdLg5Ml4sD0+ViYJ70aCT3PMAzYZP7ey2G4XOE6XFxYLpcHJguFwemy8XAPOnRSO55AIMwnhP/FMOZw/S4ODBdLg5Ml4sD0+ViYJ70OB9SLDjmyT/FcOYwPS4OTJeLA9Pl4sB0uRiYJz0ayT0P8CBs+vkw3RvOHKbHxYHpcnFgulwcmC4XA/Okx5kk9xlPfAmDGSACE4G8BwCwcyDmkNaCGfDxfwCoXCjvHKhWuYs9h2NSzsUYarHOdJwIXBFoaxLK9iqg9qFcryrrIQr/1z58dgQ4F2SN1+aqSnJjUodza5+uleqQ+2zKXftwzLlQv4REkvuI14ADaOLx5x/82dbO8pD9Y2/nE//iX748CCzSxdDR5AF28XsDFH/j5h3pOhrlmeLx081ucibn7LJe8vke0j258vfm9YmBt7/5R4s7nwc9AsDX3vpShgPgAWIGU0cwAx2i0KvvsSm0znMA1e3finM1fHl86rlalqYcXfegz+tCPJ/qoKzmeVIXMYN7DqgZcMBb3/XSudTl13zpyzjJSxTfVwY7yv9PPLiKN+6kv0L+DuT+SELCE4FqH+p0FPpNINUPz7lOUucxQv8by8v/7Chdk7h89sV3uVazPTdlUuCK0jEtR6rLEWhcAy6MQ2/7m5fMnS6/9taXprvV73Pr3XYu90W1j//Hd1WeY+VAYw9UsY5JfGaVum3m8L7XNXjQC+/J2AM9F/Q3rsOY5VVjIgL3XGg73uf2oq/Tc4AHuO+CfC7KVcu4jTRmUp3PFbkR31c9PkLpm8ZxXHYOb31P2SbltvZal1/9tJ/jaX1Vq39iDuOetEtS/8fjqCg8P6J8frOM8J6ay3qA0DZiXwBkGchzHG+p1b8XffOES/nkeJ3rb95XavdSv7rfBKX7v/jLn5i7NimYLcUkdiyR1HIkpqRv1DnAR1JIsVOSm48dFIgAacR1IKtMBBpPQv1VBXJCmD1IegHvAeoFQirXIgYmNXgQZgnkPdDvlQ9fIZFx5wJJJsoEW44BicxSv5dll3vqVZnM99S58V7Ie/CMDMnBP2WPTfcycLAio+ggsMjHNTEsyk0ho6nMbslqR3m5VpNgh45Eya8/TwlY1byPQk59XgfB7qpzLvQoiB2SdIxClIBINrrIqeqkOXZsiZx2EUvf8Vl3ho360oDuVFkgtCHpUBtyUbPddnTS8jsxg32ov7hOU1Z5BvX0F3GudElBniLwGlFuo5VLJLETzHHAa5DHSJrDQMyJqLL0yVJnQwdUc5sMK4IrBFy330Rw5VqKsKcyTl07EnWKZK2z0+B4DR9J4LRi86DLShE/1RYLeIROiSj0b/KOKjID5kBW5fskfo7jZyK8DqEduCoSpEiMJx6EQFSDYciBtkM+HXYObjIJxNSrthffG3YuyuaB2of3oK5Lkh7LBzJcR8NQeB/Ia4OTC7Iwg6tI3OtAomnS1dkEzIUudf+miaE+psCkyjmEyLVA7MOo3Y8mQ5/8FicZ8V0gBhgl0U0kVU8qXEMup+RQ98Ak16Kiz07vm+fQ/6j3IZFbZQCUY4lczzBGzIUeI3aVkoJ8sKTSeBKI6aQOf/IAqkggKwdULpHhRCq1xRWIDahOllkaT0KD1I2uVwFVla8RCbBcl+o6NFLdSXOjw/AyY+Vcv/4T2aR8lJurKt9PTymqV4XrjyfhRRj0M/HX1t8GQoq7fvG3q+dO9Awi+igRfYKIfqzj+BVE9JdE9D4i+kci2jF3dUEKufG/fCUUA+40Etmst/k/cVdBfaHy8yzyLcRUf27WHwaOBkFulNMEeqa8U0huU4+70eW50COA1HrFmsJxxaWY1ftG+S4iJJ+rPHjKXyYh7esW310k3M3yulOHGliFHFdUWqlcPta8hySrPqb/d2gRvWmW4bnTpZqEcpc1lIG8ahaeo5v4PBmXOmRw0r/HOtlRsRpFcj6jTcrknF6pbI59ZnrOclqSuTzGkQTFhxN/D9cExfrifRfvphBkVvc0bXI9L/2ran/cc+B+Be5X4d2WtiUkNlo70yqjkF0hIVUkGlW0vooFVOoTHdYMTDzcuC7bpQO4H6y63K+yoUrambQ7PRbG/oF7eUVVW2oLS1+cQNLEh/vR1l4g3F+8NjzgtiaJ3HLPTWUec6FLIYvhxHxvmjvkirM+XG4f6Oo3gZJ31AyaNOqsFMF0jfOAIMes1bUmH9LHmuRdqhYVq/eqaUlOMjqAe5QmddNwpv1ruNzZbZezLblq1r19yRoeumWUCNAFt29jdM+xeEdcWG15qY+tg8NEWoZHtuCOnQL3e6FRy8PxHluX78NDtwxDh1gBF71vC8P7Y73aLaHfw+Zla3jwSYPYOQIXv68hQ1xaIWZsXr6Oz9w6SLdy8fvGWLrrqH5SWY7xBLS5nWTCyhJ40M8dv5BzCmSZNrfDsoxn8Npyrq/ueqvPbFZDRBWAVwL4GgD3AHgXEb2RmW9XxV4C4PXM/OtEdCOANyOkauwSIvwXSZ7bjktlzKiHVeFmQJzHk2rLo390M1Uz3jdCPSxbmOi5KOuB8YFYlpBdA6Qtb3v0jm+nOiarg1a9gqJeIozXh6iHriUzAGztq3DiULb6rN3tMThaTkCkUW9c3MMjN+bfD34IWHpwUjyv8hHOgR41PEDjGm5jMy9vLw3hB7FZN8gu1TXcic303vPyKJcVebUlKv4REJZZK2UJ0NbYiQdtbIUvzMDKKE90myTTe7gTW8nC55dH4GEVOnxmoM6kvZCXKJftsDAXz6H28CtLoewUzIsuOVlGCG57Andc3e/aKJAEqMETkZSOa7gTW3CRXPq1EXjYg3YdE7cDtz2BO3YqTdj9yhC+X2ULsSLS1akxaGucLHJ+NbxP2hIs9btTE7iTuW/wa+p9YmTXirhqVz2yUZTlnisnJVLv2Ad51XPw/SrL0HyG86BLRVJo4uGOnUyuArw8gl/qh3e1IqTwoTVjfGAJxw8Ng0zMWL1nG72T40BqNfGsCLQ9gTt+KlptJ/D7VsL7IRbhKipz4kHjGtXGydSGeWUp6MZnGeWdCu/SySCrI2A4CGXFm0Wt0FDNwNY43Wuw7Pnc3tV7StuTov3ysA92cUzudff1c6FLIYsI5Lw6sZW+T9ZHmaQLqa9DebdVozqWx6l6bQgfJwxI1nOAESao1fGt8I44h3plAD/sNYhqfL4Tj97RU2W9sV9ouiC4rTrUG1GU7Xp20p7jBCi5s0DJ4QB3qp7+HKYYEc7Eknsu+tgdSG72b33wSSN8//f+cTr0il//N7j0bvWAq/zSbu8b4KFbBskadvF7GMNjp4K1U4hg5QDPeOiJQ/zf//63AQA1CD/xiu/AZQ8oAupyvQ8+eYDXv/C/hNOJ8W9f8SM4dI+SdxLJjCN85tYB3v+iV6RDT/mVF+OKOwMZZ3FJiA2UNrcxuTtX1Lv8MqDfCw3XAcSu6KyLsldfCR4NYofUbfJk4EwU/s8AfIKZ7wii0h8CeBYArWwGsB4/7wNw38wapS00iCtH4krJYpZP6R/bAr8nZ0nu33oT6ouXi2qFOPePbnaX7SCMvePbqD5yZ/hSVcDhy1EPR616gen1ChnXFuDjVzg8+Vm3w5GHZ4cP/MmNuPDRutMa/ciNwMe/7dfT9+te/X1Yenu7XJIHc6JHIA04bmMTkzs+nX7uXXMVoAYo3QG546cw+dSdRVnqV9laI24MQJzMxcGMCDzqA6CyXvEN29iCv+ve8Htdw11zJXil1GWS4URb3rq/EiwEXllqHeCOdpQdrmSLVJp7Mmhzq7ve+KyamBddUnKDIrjjm6g/9sl0rLru8ZhcsBpXrKAsK2iXveFwGCTjcXC0hBLBbWyj/vgduez118IfXMnSIuudNrZaMvgLV0uLbTzRNctefy38wV4mzmKxZe6Ud7J/OVlsk0XXEdyjJ0t5bzgMv385l2lgHnQpS83cr+COnizb2VVXAMuDUJ22fjng+BVDPPLMk6kD4zcv48CHt+OqSpjIkw8GHNrYaLXf+sBKIiJCuogZ7mSjrV99JTBYzTcm1lpmVEfKeqvHXwWMeokAA6JSClbjDT2xWQrl5P7hEol3R09icufdWYYrDwErw2iNnGYQ2ntdikWWJh7VyW3Ut+dsub2brsf4oBr/lJWzOrZZlK1uvA5eyqY9BPFYs+xN1+f2KxBPla6yB5ezO0Qyxk2p9+Aymq4O8HECvDVRP1WKdyET7ppbz6G6+QmY7B8lV4smzlCPwDnoY2eTXO+BftV5I+SR/W/FwV0R0uBLBcABvu+Ub27cSKZ8eWsQKoj1IZ6v62ouEQComcI1tsfAoB/8esmnuokBD48eKnhwInhwsqQa3yDfrjv5qsiSw6QujzWfEZA3x3U9RiZsnf5Ow8sA3K2+3wPgixtlXgrgrUT0YgArAJ4+s0YZIzuWGVq+rWksm74kUVTd/a7Pvo4scbKP70eWUcp2V0LJmp98axsWXc8Ojrr1caaYGz3GjQydG86SsCgsMeFDWV6sYq1NYwK92tH8Hdy9HCcuRlNm+E0ky5z43GqLUaswZyKu6uaKZucR7pBjbnRZbABr3EWlrOfRsJP+76gHAIqNX81jAs5kCEDpJ9uUIRLLvPGMlbWugdhnJv9ijjqNbmwtpPabDQQkG327yoo8rVvfe11yRWHpWfvYCtSqRtpkpt9vJpAL/uZOn+89yMWyFbJ/s0BtHgvVUCRo3VZSP+rBbU5A44iod44AACAASURBVDqRXNRRP5R9bIvrRCuythYmsaOlPllxNTEH2u9dcmN0pRuElnEOdAmPsEdoWv/HHDiR3lAGdLcdKa/b16wxVfWbyfe1A8mPVvsAzxoPlCGjuI/m5y6XBu2ClK7vy/MaOEM9Auegj93RJzcNNo2S7JA7LrnR6Kub/LhiJ+bG5SjDslFMiA0C0QWU+VzKSl2TOhGgSrMfcZYXN4goExPg4ALBTTcTZ8u6k+5VbUVNYmQHbXUW39xJw/dWl+l3zxkYhLGvij8AFxLRu9Xfd3eePBvPAXAbM18O4JkAfp9oSg+3A1qNidFpNTlTzCTBcYNL1zmd5yWfo/AfRVmL1yJacjGtjq4xeoaI4Xhbj2dJl6enxxgxYCZc/j/5vTaQd9BK25tCaKVzlmYsrgUaTR02fYEbLg5NGZrRHrhrMFDHiZUMvk0AimXtTkvufOiS4zI8Gv1euC/OG3qC0FMnLEWUhVkEVyDFZ/i6FmWlDEci2lVv5RJhLTemdZTVkRSU7OwoTJSaZfW1G5iL/pUok73m/YqRJvqgAwiko+dyG2QAxPA9KtqaWFKnQvnjU12Ha/RcnjhpEWuf/IUBBBLNHCcWvnyn5DFr31JN6JAtzMH3NpJm7/PGucZ4mGTyHrTVfV9zoUu5Z4esU4202tU4p6seKd81gdRFm/1dpXzZZ5FisbZOqztZeTsMGbraptuQyCsGv6YBT46JK0bzsueufwVOs4/dOcaDD9bRi997Cq/4tX8Diu/mhR/OvjZNx/XBo1u46P05bEX/SPZTSQ8hOsJf+IEt/MQrviMNRBd+YEu9RB607RORvegD2/jmV/5w8u+86P1bqWEln+Aoy8XvG+Mpr3hxuBYBl7x3u5RB/ISIQIM+epddGp9IlTtZtWGCnQu+R8M+eocuz8+n38sz1CYBlnvt9k95iJmfOuPJ3wvgkPp+efxN4/8A8IxwO/y/iGgE4EIAn51RL+qBA9aH6aX3/emNb7xvhP5Tb06NZbyvexk6lb31puJ7E0I4J6sD4AlXpt8nK/2pg+1kfYjerTeld22yPsw+vmoAZgLW7vL4wJ/emH5bu9u3LMShMHDgduDwq78vjcUHPowcuaEDM/yMZuny7OtRyeeXR6iuvToMVNFvdVq4G788Qu+aq5L/rl8d5Y1qYiGVutkFH0+gnMlri2uUhZcGcFflNsHDQUGCJSKClkHeJ78a3pEiOoPIu7IUllnlPV3O75OWmzjcS++aq6LoBB4Ns+WsY0YzN7qUpXoC/PoSquuvTf2OXx2htKJmUspLA1TXPT78SAS/MkRyD1Dve3g2Q1Q3HE6rVn4tP/NUNpJSvzYK9UZ3Mr82ypb72P4YQVed8hJag7K8a9UNh8MPtYdfX1JyqugQLvjgVtdfG8q6cG8tK6bCXPSvshxMBH9gDT26IrnF+aW8N0R8LDk+07VPbwJvWkqhHFfu3y6fH8e3d8Lwa0vhHY+Ew68vF6G92FUxIgKDR0P0rroCLH7Yy8Mc0UHGTIR3gJeGqB5/Vdzox6lNFmGv6kB0eNAL1+V4nUiY0+RD+gdGljfCry5leadYcudCl9IH1Qy/3Ed10/XheUV/2ALJQkqY7Buhd9P1qS+r14YleZT+uCLU66NQL4IO/OqgPcmIVtp6dQh38xMS0azXhjmig5bZoahXyiZXS+WKEPYCUPDXJXXPU8h4vTrM9TKjXlHv9On55J533jOb5Kqb7d9/DJc+cDx1aCxEMFkyKf1WHT0VHLA1Aa1c+kxqh+/w/mPBB7f2mVQKYdWzqF6F0T3HcOhuzvWJ+4P3KaqDRIJYuusorrgz+EgVsecQTe3qs19ZAi2FlzfVAWQn7Emdh8lBP4Qv61p6mOaTy8CWP+2Yce8CcJiIrkZQ8rMBPLdR5i4AXw3gNiK6AcAIwIM7VcyOMBlVrTBdAFqEsB461BctFed3hveiWFb563a5G0hZP3DYGg7bBTowGVWYjJZL2eSzkNL4+/DRurXRrOs+iYHlz06w3GgW3Lj/4tic6THsoK7A/eX0vbWLVpcdVsn/ddoKjQ5N1rKoRSTSGq8VZFhK5zfjqKZ6427ret9Ki9DCIZNRsaIMK9TD1XYn2rjPsJwa6m2WYfEXbN7DnOgyPSsQ/KCCv2ClDMkkA1Dyyw2Eol7qA0v9tBkrhfUKlcXK4zPtV8H/Nf5WlInWYSHSvl/BX7CayxY65EJvflDBX7iaY99SaVGX+L7EDN9z4H1LeTKj+0oh8kAgWf0q+AzL/RaTqo4Jyzzo0gOIS9zcr1BftC8RSRKyWCEbVqLeq80J9t9+PPuZa7cAbR12AMgFH1wd/5YoDEGq3WHigwwXrEFcEgBkNwXvQ6SD6IrgRz1g1Ct+k3sqJrMIUR6CCw2BiNP4l87tV2A1ftb7VvJOfCXLNMyFLpVxwA8q+OFySf70mC99YXw+4+QrG8tpi2g6J7azg416ka+b+uWK4Ie9tr+uyKENEx7wPZf9dYHS+q7GBXKco63I9fSY0HBXSDJ0rSR1WJrPUI/AOehjdya5k7pc0tfma5nhx9+prpPVdepSI/s84EnihUhWU+OXJRXlSC+EOfne6pcjNvokk7gaOMqBr3UCCI7LLDEOcAr/JUkuJEi3yC1RHqQOCZAtv03ifXf5nWHmrGYqmHlCRC8C8BaE7vF3mPlDRPTTAN7NzG8E8EMAfouIfjAq4gXMs9Y2RBdQlqGWsDPPmRWXtukX2xlrlrqP6XqnnV9sjNNyasOHQ+semuR2qhvEDIIbLjMnelTW1CI2bXNFSZMDsQyocq1jQB6Imu4GQKv+dKxhNS7k0edqSwKoPK9Zd7Oz19eaJpf+ruructWYF10W1tQIiVObXQkywQXFyXe0fGZXE7Ri5TbL6KQQZUzlbOnpsqhT7aPfrliA9CCfLbDgbJUGpP/Mk5fOe1UEO8nIyrdXnxeU0H6Gc6LLZNRptKuU6EHFmU/xYmNUBI479FP7c4H4E1GIlhCJq8SuzTeixsJC14i+9si+o0C+nox1jdXV0EeIvPFdEYttpSaiEL2HskWSCSBMbny0Qqjnw31KFuNOvcyDLqU/0TxGP0P9u+6ThCj6xnnS94mOp/RjLbcx3X9q4ik6EznUSlnnfQAt/pZkSdxKjcHKigxSiSgc8rV2mqycYXSFc9EuZ5Nc5pIYCkg1Ep1NxzNQT1Rmsty5hs7RZ9/W2mdlymxQK0L8/rQrApB9b5uzKmlQ2k/YVflY8bvMjinfS63i/gKhIxFyK+dI41ez6Ey0aWYIse0zmNUw85sRwmPo3/6T+nw7gH++6wplgGmS1R3IXbhY/E/zhXheZ0xbdbwZp7YlVoPgTpOriwQXhFgRganW2A4SnA9O+T0dnhM9OqRIBK2kCPoaHeSuSUSLZBAOZTt37fO6ftdJGoBYp7b26jp0GZFPDSDNyAnpNyp/0zIVx536bcZ2tLnRJbL1Uw9y4hKgf88nxFiaOvtZgyxK4P1QQexba4ZsdCtcIGI5uU7x3HS9+ufY7zevkwsEoqOtv/K/jpvLU9psaeVX48+UCcue61IP/BXUuAQQi2tA2cH4QRX8V8VYFMcaCclFepVUyGRr+Vu9Jz01VuvJbzM7IBHQI/Akj2M0rgvS2rK8KottCh0lFv1+Bbc9ye+vjp4wpW9Cl68r5kSXQKfRoLCyNzbjp41guqy+Ra2LGoWbQyoSYwsX/tBCRjXxbsrHMvvl8rpNK7HU3bwP1ecXRDeWYVbXE1K9A85Uj0Hss6vL2VJIIxPSKqRQW201sdNpeyt1TCIa6FS+zID4CovFWIiouAdoyyiRckfgPCDH+J0FYY6W4RTxobm5bDxpy6tnNeDga6s3lUWLdiLEQqod5fuYRjYY4nS9t5Bb5UwQZ7kqtKCOF2kG5bDvJqjNBAwtsYSgRhmTXB2DX1NmSc/buv6U+2yWOR3MjR6RrUHTgoN3WuW6LJ7N767jOFQ53yjbJLH6+proyv9CpEifkxXMjU68IMNdVl9F+LUMBSnuaJdzo0sKsoYBLhOZljtHIkJQBKrMLiZlSGUpS8SyKIOybSViFH/T7aNBbgEkC7MYOUJf0C5XlAfaMW6TNYzS9yLtLzXKxXtu1T8PuoxWSrddI0c34LKdCqmX1dCUBdCHiAMk/arLk8e0SSxehoMLXsqEVlG4nnyPk5nC/cEpwu09WNqFuBHEslRzJr5AOK/n4Alo+UQrw5fbnkQjULgX7ldhwxyryAsSw97H/mqKuuZCl0IuKwr/a2Inn1kyk6l3W5Ff8lwaqzXB1H2irltP1LXVuAu6D5TJSHNlrklma85jYddksau9SfzlaVbhZnlVZM/1GDGb5EqGL4VEcIG8NCOds5DQZPkkZeVtjJjNyAzaYqwtqCIHohVXk2HfsPp4zm4PEpNXXAy0q0Fj8CgsyNIhVxUIkrYwWq3HE1Cvyg16UmfCvcPGiMm03UznC4pETnNRaBFAUr81LS3NAYsa/LjxOGal3u0o3pYtyt0i0YX1J5ZT5YOsudw0K/FMN4wkyhzoEchL8HrJqNG8ErFoWn7QLpeIpLbsTlv+ahJdfQ1p0h2kM6EjMoQmdE2rcKcrxjQLs5w/JUuTxrzoMrkURKtn+DEOnjrfvPZ1jdZVUkQHQCobJn7ZApuer1QhZAqR+Cbf3y4BocgvFcS66AP0ap8YlqQ7ZbRcJcJ750trr6MsE5f1pvvpkHEudFkzSCYTYpHV76LYc2LkgcIi6gEQZ0OAREzQE5r4OzMgURFCO+NAGOX2FcHNLgMAnANNJsUYV5Bh5+ArJJ2EFL2hrRYRj9S5AIBetAL3kIk5fMx05vMkVqJGMJeZtRqYC13KEr22enYgvf8dk+/WWNJlDGiSXqBNerUFVX6TZ6jr1G4RQAorltymtXGhafTQZLVZL1BuQGxYfme5ney5HiN2tic7Sr6rYdMY5yWNOHvNOZfVDQs5ZrE0xRdbyCaQGlzKpd10A9DmdrWBjasYdoeib3AisOF6BCQym4i3DBSUibBkfklkfVKXnXXtgX4PKWC7CoFSLOtIDzPNJ5cJ2/WZme7PFjSB7SR0TZIKdBJibR0F9Oxv1sXz8TyTLM/RJLaZdrfTh1YN2PrSnT6/HbI1Cf1O/sDAfOgRwPQlwK4lfikvnXDHMlwRYaErnqK+ru/4rNGwHHWeoy3PkbBLG9XXz2QouyPkwR3Z6qyX1sTXt+u4vuc50WVrI5aeuCViy6m9ZMst5ZBMzVBDjExqdRxe5OoAISSl1Vj79SYyLRa5hluFkFnxvUzxdiNxpprL9zAOsByXVkUuUnKncSbKxtoiNe0ZzoEuw3vpy01WCM+AK4R3N5JMrggMl9uBkFqn/FU9cl3y3tdIe1hSml4qozUASKSVPOdUuohZyXoupdwFoFY8PFwdLbpCihwHf2DmNOYl15ahy5MsEkItK7d6RZeyu0RFIFn/npYMYg50CSBFhup0DwC6484qFBbTBhEUq3nnfoOmS4EQ16ZVFo3f04VLeRlicW7UAWQXseaqrNSrLcrqXrNhaoZhb070COxEcoXcOgpWTEnn5wi8shRmlFpT8nAmNUiyojCHsuIzIlZV6RDHE7hjMQ2d98BwAB7GIMKkdqISAfUEtDmJSx4+1NvvZXKpG9ekBh07Aer1sgzMeVOZIzDibLP2oO2YypIZvDRUxNgrazQD7EGnttK98GiYXSOmzk6x57MaTeI2Lurh0RxlBPs/ptLZAgUB3bygwqOHnSrrMTqiMoipsp0pgEflfaeML5tl2cn6EJNRVZQR9DbrkAI46rZILdxoZ9W2R//oVlHWD1yL4DPFeuXdo5gueCTLvGhhHvQIoCBxtFUXGYh0Wt9WZrBxDXcyp4f0yzltbLN+8h60nd8JHvTCwByvWxDqcQ3a3CrCmPGw6iSYSYZoCeTlIbiqyniUcfDfeNwqHnxKL018LnrfBEv3niwIshCkU5eu4MgNsd9g4OCHxxg9sFG6XyjMjS4dZSONZ7hTsY9lBg/7IZGOWFDF8gnAbY7hTuT0nX59CX5QFdZgIY0pXTAQ9BPT5AoSISaAakZ1bCP1qX55EDcV+YL8AkipheUG/MoIfklSSkciG+t2m+OQqjcSdL82Sru1k9VaHsm4zmWZ4VfC+9TpY4750CX3q2T0CGl9YwrjOJ745UHu2OL7HVLketBm1iMvD8GDXiCYsiJKgeD6pR7G6yFKBldA/+gY1alxcFeI1xVXh3qpwngttgcHDB7ZRrUxDkRckRdihh9UGO8fhmQWBPSPxXCbccWSmUHjSIA3J3AnNhKx5eVhcE+IK5rs8ntFW6GtcxXfn6Vwb4nkdT1H7L0utdW0O60v5QmKPMtI5t22WvnuuXKSJu2GgfFaDxsXZ/q1/JkJ+icmDatpODZe6+PEpb00Jq08MEH/5KS06iLIsrW/j+OXxayDANbumWD4cNBnSi4RSbKbeLgT26E9M6NeH4WsZwLl3kAxDnpaxZmR0heYEz1G7OyuIGFQNrcxuSeHK+sduhy8upSJrVhCKwc6tVWWvfpKMEn2Cy59sDY2y7KXXQqMBjHUCbL7AxDqvfe+oizvX8vyisuE1Hv/A6W8a8tFiDDxE6aNzTL94OWXhRiHenYT3Sno2Mkyre9VV8D3l2dscYkK9/OhcAB49AnAG771l9L3//33fxBLUwJwPHrY4Ree++r0/cdf83yM/kHWQpAIIVNH+t2n3ox6uIQuNMv2nnozJqNctiCjzdTCT725CGumLdP9o1vgd3+wKLspZZXVlzjW+96cLbB/601J3k5LLuZLjwCmpvXtWuZvpfq85qoQ4qdj+Z+2J8BDj6af6aIDwXojpESBNrdQ33FX+MIevauvRD2KYahcOZi5jc2WDH59Oa2spLZeMx58cg//9L2/ioocava45ZUvwqF7UVh5hfgcuaGP//Dd/w0VPGo4vPw3vgWPewCzO+F50KUipW5jG+6zj6RB0V98AOgPkJe+XWpz7sQW6o9+IlVTXff4FPorWV5lDDzRkapXlyVKpNSd2ET98U+FMI8A3HXXoF4dQvZVaKLZkuH6awPJZYAkKVAkz+74ZjtV76BK914Qi5NteSejLG8T86DLFJ4LAJ1sv+NYGYIrZHJHwT+3arbfKw+F8GN6NTNie98Aj1yfs0gd+BhQnRoH/9do3RXCM97Xx8Nx0kcMHPwIsLQxLmWOG9zqlT6OX9ZPJGrtLqD/yGbhbiHk2Z3YwOTTd6U6qsPXgKul3M5lddN39DdXXQHurwAzRst50KVesq9ObLXT+h5Yahu0fCCNlZp4TvYvFW4EelPXxsU9PPgvJG0646K3D7DvxCSXV64HJ7+gh0e/Khsy8LYR9t8RDRBiiY+P7PjlPex71n0gYjATjv7ppRgeGYcJSGNFrTq+hfpDH823feN18BeoMIxE2QJce1TH873V68McjaMDc6HHiN3Zk7tm0NpyKRbfaZjUwKCvXB+qFFO3dZb4zBKFXaniKiDHGnJxz+WsMDpiQ6ve0GGkDXOcl95omslfofA3btzb1GvKuUzY3msn7Dg4NsmbL3ZqoWUZbVk09fnSr81eTZzqolBAdwK7qHMqpumiUd805/vZVc+BHpEHet7FLtfCmtu437RZoqPulo95XAHpjHJAFFZGdGgjbakRsh3diUohlHyyhOfCvbEDqriJp6JojVduFcWmNAYqJZgu273xbH50WYTQ0joS30BF5qdCPddiqbWrOai60rVFjkS6XVpta7o7pHO6+nzpE3qyIsLJPaGA51Q2EXjZzNuxySk9p86Yx3uvy+SL2+UaU7kcFkzCiYl7QfO5qDFOUgV3Zj0jgDySq2AiuE1/S8S2EFhHjn3dc2BW1nZVlqJ1kBFdIarSgl+IoTeei6Vf2mWzv+lVO/a586DLhC6Opv1WxSLfMa6GsmgT3OQmostlS2wTFCeJHJsGFz520sZZhQRrni+TDnXelIl/4Xer63cdupevKiFIcXiO9LizuwLQrWztU5McsBv/C2Rp37kYO5FA22PwqCO3sQs+SzSOG8d6FeDFJ7jpTBh9jkQZKgpCq6zn4Mtb19AhwNJLoNHMJd+bQnClrCwrTSFY8zSraRJNR3kJJf08i7NzJr4zw3EBaiJRXrcz0oLq/HYKOdbycZIyXcRV+/vtUI++/mPFktsJZcFthtbSSJtSigExdmpNP071vSDOTeIqn6U4USavHUS75ScW5aE4MNTskyU3TVSE6GprdTxWx4pIBqHG/SUxMR+6TH6sTf86aTvaVzd+TD6SGj1tFU2VxBS87X5TI/l2qlCNZQFVZzreQUalrmaGNqCT3DRj9RbhyDRisgswOtPVzoUuhWB2ZsDpeOeZOyd9Qoh1tCA/7MFtieUOSH7bceziftgMTeM6bfjSmy+FKKHnkBJJTDy4H2Lbyqqy3g8hG+OSdZqnMCN5tzwgSi+SWujb9gwf+42Zrid7rcsUU3gXZdXejuY9hQkeCosoTRjco/I10V/EghsjO6TNo7FJkZTV6ujy++WQrCNNNjQhnpJtrgW5n2kxcaMPcWeyHcyBHiNmk1yVmYyXhsGVIHamPOhnEiwztEgEud8rUt/yKC65yeYS50A9hM9SLxAc21eWskM7gJTNrOeAlaVQNs52eRRTy2lFxk6QV5ezDDEdb9pABuQMbETg4SCUjZZm7vfyS9F4gXg0yDL0qpQ2Mc2mO8Ag1Hu9nKYa4/6PBhcFIXP7P9YmooJ9n/D48dc8P3//pC8JYDyHeHoK4GbEAyZVFgCYMVkb5LKNNlikCybCeN+UTGkMjNeHuV4g1KvvS43RrTTE6zHr3ZQ+YB70CJSdqV8etVPfKnKnY8jq1LepLJA3h6hb434FunB/LMjBT7Dj+gDAoyHcVYcSadbpd9NgruXtkkHLGq9x0fsnuOWVL0rv5kXvn5S+cIrIHrx9jJ/7zeek9+fgR8ul2dYznBNdpg2xAHjQQ/0FF6SJtx9UZf9D2fKWUupG+JVhPA9l5AJH7fS7o0GeEAopRSQhK0NU11+T3qeUvlPauSSGAOCXh630u0lOcNGX+JVRKe96zn6WIPWuL4UUwHGPREhZHKvudFeYE11Ogr8rr4xQHb4GFMdHP+oXIcKSDycAv2+lbA8ro7SSIal0AQDMGBwb40BcXaaaMTyyVUwKwsTTg8Y1hke2cPAjSARkcGwc+wGfXZKiFXZwdBvrsf35iuA265IcMScLtF9fTmm5uVeFlMUigrRND6AC/NpSSDnuGajrnC7YoRzjFeZGl/He69Uhqhuvy+1hbViSPt0XupCuV1BMyOKEXFy9lj8zwUXv6KfJ6/KDk8JFQe+7WPnMBHhbrnflgUnbQBPlXbt3gqN/GvgUMWP9nkn0G1blYt2T9ZCGOAjL7ZTF8frwYTXHrw4goQjT5HvaStm86BE7klyZ4jHQ74H3rRYvfoqdm8za0ZpZVeDVnPc+leVgmU0+YzUHorh/rbRkSJiwtFs3KqbfA+9fUzuBlXWVWcX1jQRUfHCZMyHXocv0Ms3qElIWNIF0CkCwAo/j7tiV6OPZK83x1LSYSN289zHjdJzYpYcmWHoYJaEVItiwuI4erjF6OD+TgoRy+ZtOAdzleqAtBSEF8FJ33NqGDM10wal+h9b5fuCCD64mtvo+1eeulMWzMA96TJDXeFih7q92FmlGWGBUU3xwG5a9OrRPXh6oMmWdVCt/PUkt3OHb20RKLdx1rEGel+45iUP3tO9Dd6xiVR49sIFLH8i/ddVXXGtedKmsoZJK2SfrpzpOZVk/6seNW8p6CigrYV7i50EPfKDKvrdd4Q4jOeZ+VaTflWOpmLL0+lEv+eCKjLJBJY8LsexyP5dV/UeXjvyggj+wnPtnzoS5q/xc6FIiSSC40PH6Un5P0zK+cvGTiAODXkjVCyTLGIAQcsuHzk3SArvNMZZObhcbt5L7g04h7ByqjTGWN8ZpnGuFEpS4tRMP9mETcErN24u+9zLOq4mWH/VT5rUi+YQQd5bNSS68n8PVfO9q8t1pscec6FKtPhTpbDsmnJpHMCE/E4fwTHR5IPVb/RMT7NuYtEmi1lO0evePT7D/5KRtvRUog9zwyDhsNNPRH5wqp87litppiGt1n6r9yb11xtntWimbBz1G7OyTqxUppE/Ir7yokzoMohWBauSYtzokmAMAAmoPTmG5YqOP5DGR2uT2UC6RCpElvaSmQ3sB2UIr56WwJirrmq57rGIHJvcM1bl6jpvQ5Il1W1fS507s/aymFYqrOc51EMIui21XSLEu7JSUQa7VdY1yUO2QVervkKe4vwZZnlbXrLBhjZJ7rkcArQ1lncfEGqSsLF2ZwYrzIorkEY1yrDrIThn0OV1yNiy26ZwG8oYodPsea3eMBlJIwplkd050qSaX2r+4sMpy3uyXY95OIX7KzYG89NsI5wsBJVVWWUiFwEpEhCJ2r8ga5UvfSRMbahNpRia8uo9x0oAbz4ORybEm2WmS3tXh7L0um0lXysgmqlPr5b0m7FxO4iDiK7IYjC7RsBKjN/hBFZN9xPLM2TKr33ch182xSayQ0VVC+wgngpZuKp8jSShSdr6U5Y6L8sl9kFXih66+Zlr/NQe6bCFaMxOHkXsqMpdhOvEjynGphfwCZTazKWQ4cS9NPgVdfbC2BMu5XsY/VXczecQsaGNg1wDaqa750eNskjtWYaW01VKyf0mc2bjMT54SKSwykKV0uIGQJoLrORBlcQ+ofW6c45hFJfryAuF3apJR7dNWqUaqrx8tCymJRXMW1rDIhpfKh5eokgxnFMguYmdSewBcXn8KyQ3Fd2RQ5xSy5Ltjxq8mMZxCimdlMNP1aHLZdd2CAHfIMNPndxfXL7ALQq7lapWbAz220LBsAnGAbW40aJLerjrkXBkktV9rc9DcoWPUMVgFmowV19H1ydiJjrLqXopz9DKpIthFPN0G5k2X7EK2LJlgJ5Ia2qX7/gAAIABJREFUPxdEOLo4FKRGE0+pMyXVaV4sfyySMBTkFZlsAnEDklPHkMmnI7DPBDSN18nq7zNZl3uJZDvH/UX2C5bYvqkPiQSB0D2pmQNdFqH4vMraJhujhVB6lSiBKEdGIAc4LtuVWFalbu2+IOS0ZvAwWlajZTaMTyg2OhXkyCG7LTg1bmnLnRBt2TAnWdwS4XXpXjNZ8im7W74vUsaqbPSa5uM7D7psEUmBTECkrxHy2SyrCWbkGcklaKLaNFCSXs0jhIQ2ddPFMZoTE+E2+pb0aZqQNwmv/ObVvRSGkh34g1xvHvQYMZvkavI5qYO7wKAXwgsxB4UJifUxkUKlUv4KWUzxOFx2H5DEDkTBDaBypSuBSrYg9YmlgCTWrlhxE+lEtiKkWUy0PDtVropy6aQOOnavvCjb4/AMfHi5kzVZv0BC1KdaccOAvdemeyGRs4gmgILgdh5vYCpBjOeknb3pYPm9yEqGSMJ1OU2WP4c207X5rRXrVx3v3ni293oEMJ3oAXFAapBUIag6nFfTwuKQdkU3s47l8jNmHNo64zMZ0RvUxMVhZka05vcuUt60BquA88mNwpflm5gbXUaQjxuIlAW02HSm0SS/KJ9HEdy9af0BIG4FzaxlRXKB6C4mfpspHFgXmZYusxHCpLAMo30cQLYWc+M3Xb/yGe4kufOgy+iPC+fAfRcmLGMP7quJCRAJhpBZTqEys8tfNs5Qg0CStrym60m7jX2aWsWQEGGF26H0BRROSM82nks1FxEV0j0lgxbgq6pIWsF9CmRe+9kS5Q1o8v7J5rgpk5XwROZAl9pQVhBb6uxL0jld7gSaTKbVJ+T6vXo35FSJZ6uQXFS0Ma3Luit1yPjWtJo3V6D15jpZlZnwVJeEFLmFeWZCjLnQY8SO7gqJlEpWszi71C9u+L+hLMlEppUdB1AoX1rthlAQ1soBoJzdjBsZ1eSazc865S5zttLKuUKkexUwQVaYkGM9qFYS8oQTyc/WXzWTjUtPVE/fjun32tLQuLz2aW2iuXzf5XrQSTinjMmlIGU9zd812S7I8hRXgy7Zm8S667fWtTvO6cJe6zGhobdWxINm2aaVKP2evyYf22kWX31dmZSobGQFOkh4kW5Xl9vB9aIzta+WYeLLQdO3y3RhLnTJylLZWi6h1O/pjUCtLGJAsuamoO3IbUZbS1suDvE4gGT5ZWVsyCHGUFwvpw3m1Ie0wqFxLq/Pbd5f8uUFyut19A/TMA+6DG2BQYgWzKoqJ5liBdU6kVUWSaUbXRgkAVKxsSxOSkhcINL34BqgU3IH9xTKpFogfQFz8vVNm+JiqLIsV+wzJOmTvH+1Mg6pfkCPjSyEl7VcahI9xScXmA9dtqyZ08qIy4HGNEsw0CaP2uKry8h5UUcpQ5p+Nl3WXVbtSMuuy+pV7Ia8hc+tWHmb+pjmqtbAXOgRM4eAgDSbjEv1aXkiLpkhLTu6/LDEqqqUx5oURhLL0Tqb6haI36sQbPmb1PmvcqXCfENpelOajnqQlluzjNxX8fvEktKrsquEoxyeTN+f1F37qZvO5JKT2hV/uwERPYOIPkpEnyCiH5tS5puJ6HYi+hARvW7nSqNMccBjh2QFSPJ2EGJNfKe6KnRZeqa85zoDWWfUnSYJbtSVQt3o86mst+tazWu0/Awb9RQyd+hxN7o8J3p0jf+BdigXp/6a5+nPXp0brUDJCqyswamjLawS+UGRGvQKVwd0/ObUdbSM+v8ZVl1NrFvkuYvkNzAvumxaYMMHJSQjLflTHZc5xK+2yxLr4uYxpZdWaCPlKiDHi1BfjspnqttystAnv5JIyFBaLCmfJyQs1Q9l3Ih1FFbrxj2lttnpjzsf/WuaZHJcqnfotnSJ9VO5MwTjDyArjxTdHZKPrPfBDcF70NhnAgKEd6JuTGBlPO657NaQLMXIOhRCTEhGKknFnOtBbk9i5JL7iG2Qah+IufjjSnrjWIcQW4pW0c7Jrno8e63Lou/purxqNwWJ5TjZaL6mHnkTmn6mTTcD/RfPC4aeeK7eyCZ9rSbULSNgo29skm99b7G+goRrt4aOumcR3TPtX4Gz38fOtuRqNwBm0MlTSH6ygz6SO0Jjyb/et4STh5ZTJ7d87yZ6j8Y0h0JGPYMcA9vjkCY3WkF5bSVaWWO8W9XgJhet4cTlo2SFXL17E70jJ8Nx7erAjPEl6zh2zVLqhNc/tYneQyeytVhusd9DvTLExmUhRAc7wsrdp0K94j8scATa3A5uDNJRrCxleTuWDYAwq/an6YRNRBWAVwL4GgD3AHgXEb2RmW9XZQ4D+HEA/5yZHyGii2fWGYljSr8b72G8b4h60JaPGJgsOWyv5uXD4bEabksFt1YkMaXJlXolTW6qEGnAKlLqemCyP6f1bUZmcGOParNWMlUh3SkaZJRVWt8kwyCkAO5QTT0ibK+4VG//pIfb5s6yofr50GM8CQDDbU6Are0ifFeImxnLSUdUBbcgt7GZOlu/OkpJWcooDMFX0B0/lZ6jXx7FGTwlgipuB365j60Dg/yOPLyV43qKDKpTFB93QIiZS9eGh0qRGe9NlsyXRyllcXPwobqGOxGyArEj8GgYl/+7H9+86FIT0JOXLeGhW6q0gnHhP9VYul+lbE7+/8F/t5n6NqXUFWtv9ImmiYc7uZVW1vzaCDyosquAtEsOaUndya1EKP36UnAxaRoB4jWSBc9FUqY3nDXgtutgeWQ1+Eo5IfPMMXXsVrqOX1+C71fTd+TPgS65UoaeSUh3LOnn/eoyuOrFDWVCckJZ2p6Edib1LA3hR71G3Q7wwMYVK3jwyTll68XvnmDp/pMx3q3PfrMc0kPTxmZ6P3h5FOoVw5Cy8LmNcSvVNob9mDwikxyaBEJdHT2eyDevLoeUxdq1Qt5JSeEb3VHc9iTH352SPGoedKl9ZN1WjerYZiLrfnUQUmJzJLPK1cRNYlaw+H2yPionj8kgp9IFx2db71tK9WrXB3YEN65zvUBIvyt9W2MCm2SQetdH8DJZ0rJ4gHuEyUp2Kag2PZysRjdIrB9UmCxXYTLrgP6JGm7i8/03cCZ6DKKd/T52NsmNcQpROdCJzTKl7pWHAsEjyqG8IoE8ecUy7n06J7Zy2dtGWH90A8l3V1lh6cRGmX7XqVS9ekZZe5w4NMIDX7+dyj7uTUPsezA2uOjUL3Ifv2qE8TcdSWWPvf4ADj50olS0C4PjyctHuO+rcm972V+MsBZfFPI+Ro+ICtset1ML74shnJob2ASMMrPY7vDPAHyCme8I4tIfAngWgNtVme8C8EpmfgQAmPmzsyoUEYqUukQhnW0jTa6U315zePS6XMf+j1ZY2pq0fHiBjvS7t96EephDf5FHWkJtlu099WZMlpaaVYZjp2r073k46+6yg9ju53AmWt7e8W3Q7XeEH7xH75bDqAej4v4F2ysOx67ODXH9U8DoSCbTLcyJHoMsQUA6tdVK61sfWGlbSIHOFMAppJhyKwAAd6KdmrTel0N/ab/XrYMDPPik3JVc/D7G6D5FcpV1lupIjMAtS0ha1oxWha57I7FSNsirO16mEK2uvTqENZuGedGlakcP3VLhn77zFXAgeDBu+c0X44r7ou9snMQL4XfHTpWpb6+/NpMjbbwhQnVyC/WHP16WPbgCIJNhgTu60Uq/OzmwDO1CIK4KNGHQqRCP2DGjXhlkC2+jf6CJB21OQGLBGvRKoiNcyjlUj2x0pyxuWHnzTc6BLl2Og9vZzvorpdtJ9G91xzbKdnb1lcDSWgyvGcoRADjgs1/Yw0e+69dS2RvrF+KKewHoSAvhZkAnT5Xpd6+9GrwyyBEPlKWVNrfabX0QNo9zDeXOQqgeLdP69q6+EhRJVPGecrDYTlZzwqfeCUJ1MrwvNJ46+9x7XUIZhI5tFml9q5uuh79wObuCMKdn2UyT27vp+hCiC8jkVeo5vlm2yWZKXQFzd/rdg8vZKqw2jnXKe1D1g8r4MVmqcOpCmRiH0KJO64WzMWuyXOHYlbmPX78TGBxVK/Ytuc9Ij8A50OVsqi3L9FOyeXHPZedyGZxkSU2XI+QdonozgpBoDalHjhf+Jh0yNs3pacbUFBbZiisuD8yZvGqrJJAc91PWtV6Fzqxr+tpTLLkA4Gsq/naBywDcrb7fE3/TuA7AdUT0N0T0d0T0jGmVJdLWei7cKtfyuaXG/50XmHGsuJ6U330DmBYmrElwgSnkVIPQ0nU6pFd+pojX1OMudHlW9QigvdTVEhKZuMrr2vVuFqsUyJ0m0LK0FN9VE6COtlbEWNX+W3qZVM7VS2PNe2jKLMRelurE5aED5LlF8puYC10CxYYdB0JFDi5GEwDkOSFZOzs37cS4uEkfKvpC5zI/IVnucpug9nsVV96C1Vb17V061zF/dSKhxhJscZ6kjPVZ7haRLaI6dOt7r/tXWaqGb7ed4JeqVvrSZibXzuAW3R2SO4drtJOiLMJx8eXV7ayjfHKJiNeBbNJslBVf6xA3OSRimhpzOq7EhBjP0T943DGuy/XleqfRLneBs94uu1KeFxBXAZlwa1eCZjkgP+NpdRY8Z4dBrKmLHZ5nKiaJSNKYoP4ANTHlZCXW7bgoI23xNDjPXuly98kgmjcTG3TaSOZcijmbCVX3wJisv/FzgeSrVJWDIdoEJnUmuqNgBnoVfK+j4UoEBSHu2sUgWimAYHFM7hLJgdtnAt18Rs7NZFfMALdN9xcS0bvV91cx86umVtKNHoDDAL4SwOUA3kFET2TmR1sy6JdTT0qSZRuQTV7pezq58b9C16auaSgiHHSlCtxFHXLNznoFM/yjZ11jp4nnFD0Cn7sud61HQCyeUaYOy1ZnCLFpKJalFHlsEKNEGhsW32C9aQqQiSyUr688/FYq7aZvbXOzBPL3Vra1WZsgOqzZ6bw50SWATFA94MEA+/g/On1uw5cOMqrqY3JTYspGcPyHpQ/ndpxUABLqMQ12jrLqZLKRBKTUvpOPt66u6YsZyxUTlSltcFpkBRFjr/vXIv5sU77KJbcgxCgFfkp2zHSOcisoJglNxHaVQnLVAFObFEv2tSJ2fRUmWKRDhQI5aYWTtNBIm9NacvaqdE/co/xOdBFzVpEbphly50GXQhpn9Su63LS0twJtbZ2yvJ/KNTf91miNZ61Ntsx5A9wM40f2e59yfcZUvRVlZAw/fT0C51uX2IHkpuQJ0aend3km1DlNbmgQXBFo0AeYsXzfKVz2trj8zcDK3RulMztzIMT9HnhtBT13abYW6wgGQJHMYeXuU/iCN+eMWiv3nCo3oKlZ6v5PnMLRNxxM113/1KlAWCUlMMVQZMxYuWcTl/5/o0TYlu87Fe5rHOtUbgi8toJedWl6oXhpmF+CWS9Y+2V4iJmfOuPx3wvgkPp+efxN4x4Af8/MYwCfIqKPISj/Xc3KtJ/reH3YTmfbfO/j9+GxGvs/Gu+fgMGJZoPLn8f7R0VKXUmT26yXOPjg9nSq3q6yEfWowvjyC5LldrKk9JFmn+HYeG2A/hMPp2Mpra+6JyHJgxMe++5Aqrd/chYbjFV0F5mly7OqR6Ds5Hh52EqT2xmNwCGl9ZUd2bw0bPnLhkrQTr+7Omp3aLEPGz68jYs+IAIBw0e2i+P6vLDRVKXCjlbCrji4Wl4AKeWpbJQr/Ii75G1cu4l50KVYZwHggg/WuOVVLw6/E3DBh+qp7dKvxpS6sd/za6McWzdacyWigl8d5jS5FNL8FmHEiIIbAQN+bdSqV1+3yNDWc2DXz5EWmhvGAOT4tgDEn5pViCRC8MlWvsF+dRTkFb/glWG6l6n+8nvdv0qMWIQ2WR2+Jt/rahwLhfxx8H1mCr7jvauvjJUQ/NpSimgkbiTic3vJuye4oX5hSLjkgAs/OEkuQGAVjgyx7Vx1RTlOabKkiItfX84yAPArS4lgJz364DbBK0voXXkojbl+NEw+tsQoVyW2JujL+4jok91I1NKFvdal7g/r9VFI6xuR0lwLxPXDx7I3XZ/6tJQCuLn5i8K+peqGw4n31CuDou/Tn+u1UK+cP1kbNqyr+XO9Nsxl4/d0T0nmoLtqy2Pp4UkirtWWWBuim0IvN9L+yQnW70QaS3sb9WzjCc6ofwXOQR87k+QWyRP6vZQMIUESOjRm89WxTaz/40kkdwAhlzpbWiTEqBz8gfU00NF4Ejs38UVyKapB78hJ7Ncb2FKwc87fY+PrPXQCFzx0AmLZDUS8SqQ5RY1wDr0jJ7FPNrBJ+QbZBiIxdi774KYDnIh+J5jgd7mzUOFdAA4T0dUISn42gOc2yvwpgOcA+F0iuhDBjH8HOqDJYEp9OwXaBcBtMZa2JnFQLEltkzzWg5gmVw9G8ln9xgRMRhUmo45UvR2P0Pcdtvvt59cszxRT9Q5HZUG5vrZWE+DGjOEjU1IWd2EO9BjkzASP+1X2lW1aWuV73PXNVVWmEI0DZFdGMR5WqIcr3cS2cY3q1BhLp8YtUp2uIfLG39IKjVxLvkuqUq/uLfoXF+mEtUU33oMf9ADxSW3I3DmgzokudXaw5fs3sXyfOqaIoN6YBYRnM7lgBclPVUJwRbcBPRHygx68+FhOIYuyCc33q+ivq64/BZLdLFkdGamtNTfccJUtgTrRBRgpmkAi8D2XUgvr+2+FFcuC7LkuJSNZCJVXlWl95TkAifCl9jusUC+t5zi0qY6cupciOVy6fwNX3e2T8YkHveDyENaWc1snAg/7qC9Yy9Y9vTEs+voCQT4e9lEPo++s9zlWrkQ/Eo++msMms+VBHhu9T6HH9H2R94H0bozTdbIvcCa+7Qe597rUPq6+X5W+sk0XL9XX+H4FfyCOq01ra1qlipODnoO/cDXXI+4OOoFN1L8fVPBxb0sRA7vDuMaVw/iAGtu1tVm/gxQ3r27nPSili5G6NwfQhDE4Ps73o9GlrjPTI3AO+tjZUkQSmBpKlzk8do60NSlniv0eMOgHYiyNTO0+LWLlymctjU7gEMmwTtbA/V6529ZRkRmtkC9anGUndyonkSN6yl9YZ02Te5fz6zrfo15yTR3JjGcpjq5Tg8w2ijNPALwIwFsAfBjA65n5Q0T000T0DbHYWwA8TES3A/hLAD/CzA/PqrdY6p/OydsuAOgQe0pdOW6mKqPKdoXymkowZzyqTteKKddo+R51856d0dTjDiedCz1OW7al5pKpvI/ih6X9dBuEswXVwXXW2QWn/hQRbpJYoCTqRWgw8dFsDibNc5SchRXY57Kpzmn3OAe6TJZRPRkESr9UNUkr3Be8RDjwhW90IrIo6yyeAzXKIZdL7mGNJA2pvqItlXVqObS7RHDH4PJ3TYj1fVOHzuL9T3XB2Ov+VfwYBV2fo9GH+1URXozGNdzmJJBFZRnkKoaDUyl0NenU9acJoosEVuThEMHh/2/v3WJuSa7zsG9V9779t3POnJkhh3PhDK8mh5ZgiVEe/OAAliD5RXpIgsiOgFwMJIBDIICRBEISKIECBHACJE+KEUE2YBuJFctPRMSIshg7gZBYEUNFsTmUxLs4N5JzObf/tnd3rTxUrVWrqqv3/8/hmfk3//QCzvn37l1dXd2ra9VXq1atzwLR4Knj7HuoJzQ0eGZdivGOOIDJ1G3PK9oAabcllJC/5bWrz/KKdTlqLzjhASABU0mtCESWVBqGSXnkzGbFpKfaDC7KAsG7asNBiramMdH8ZkG21Muc4qOx5THH+xvtd9sQ5Du0r+Fyj97Gbg9XiGBQvJ9KDFE+4Ejrqzdh4o1s0LwNf0iDKOmLQ53PyRvEEyzHiLKXTDt2JIygTZefJ9excbUSG+XMSKydnPMUY+qpJsAzeNGCrIfCnMsXxFhd5NqvCTN/DsDnimO/ZD4zgL8e/22VwYayOKhu817abAijsawFiC3Tf21tA4blxkgiLDAtN5uNAdaMMphMHXLfY9fcJlesRwBD4yn12IGzBITOHFfjxsO6SnDri7/GQ5sBZhSfbdmifVk+3wsArIJx49ka1F+5fkZoMaazHdClXdZX0h2Je7WgV+qPZAkSn0vWg2uBvYsdlygH0lqgeOZiU4tBV1O82Tp08JTORAmwWjIHzwjEA+a4BQmmT8t3oQAe/H4BLrpqXQpJUrmPROl6DTDk1sWc05zGMKKknkjfy00T7JdRHLEHIzp0ImkEN4GWmXqO+06QiCcioxZLyjJZCZmFugOrXWybrLYKAIoUtJL2K+vPAniNh5bJqceYzjcYBOtnut9icK+6X47ZM8v1VIJTaxNLu6O2F2CY+3exTm++y3le+gyn38aeC3NlTOQUM8vGkDhoGEy5T6qsU3FbpGrOykv9ZT3lM3kIedQ29sJwBZ41YAQ2r2yzWLmUv5gnAGtfgC7S/boIcCVPbpv4u7Oy4klVxrJ4PclyIOEGJpQi7UQlwDWpDQbgctNk8UsSvgBEEC8b0+Ta0g4n9+uHg6w8B+cGg0MmDPDldha+azLGGDYIP+Ditwp4fUdyCTA9eurIOWNMbVvPlXupDKyXbt8O6BHAwKBm8akIx8ZYyyyoEY777HhpTGtztxHvbnXDWyW8YbBxAgnEMihvv/UIW5pQb+67cn0b01gPV9gNXWpuWDabu2rgjpB5VmV5X8GjC0DHgimlB7WTQX3fi3dGQKrYU7KDIev1bWhCxtRGUDpgJaVoXOa1DWEmed+l3pu0YzS0UxFUJ0dLzSBcvS65DZS1JABS7kFiMo1e3OlGN/lZHMjOxKrDxfvmBDKNzngWni33MM8vjW1AmsxmTlsZ0zjQt9pUYnIudR7wfRofmRMbmrTDUQonhI/3KdeAcSYh9eFmOBkYPsir16VOqh3ny/wl7imBZMmQps4yirpDjnciuM1CEHqbg74oK9dwxW8wgNiKxgMXtn1gt2Wst4DaTKxGNtaVE+v8xx3QY5Tt7scyp56AwCK2I83yKSxryDK/HJO/RCnswC55WHYyGxYhzGfMKR5YPKa+ON+2gzmlJ4sAOQBsmBfPJwXZMIda1gcBzQK8Y92669X+NiLkKfv3nkutaVuaUc1gcJnLlG+UDp553cpUVk4gqf45a38NkNrBvDguYL3KeMZQ1resrhEp9XglurQgU5brrWdVxFeOmXKS5H8w4IgR9ZU6xuosPbg1b8gFfwXoDtjXYhmdoJZg2RXfY116nyMD6k7o0oqYQImXHPSNAIA1pZgIIdrqCII51ZWBYxk4a33HXD/zpBZts3VnLGWAAlw95nJGNsjmpNj+4IV0w4mnvSZDvbs2breUK9ejhNcpOYZL7zGn91nGtuB1je+69Cc7QZFxDcj3emSexVBeGeXEG9+JI6gYU+P5VWdNvC5LjHXRl3RMN8As8+SVdl9CLFzwAIsjilu3ldI33M/V98lsozyQ7q/8LjK2H6fEP0DScyXsJEz0TNmMebAA0VLHZbzi9h0rPLLZ2Fc4OTS0wf4er6nv7og6d8W+bg9XWLTIYkkEnMZOrOEHMY0I9wgB55COKV6B0Ek0VUmZBkfAaOOA3gdAG0GtdA4918bPAiGMYBbYZLK8kAKQzXWyfINiECxAlrCEWZu80jZXr6bRwbA+G8s7eJCEAf/zFUkt5Vd5rObVrBEvVL2gFSCZHTKgsxxsB0suRVsG4QdWLgHKsx3dW84dD83YET0aD2k1tnUE1KrXd2zQLJejtv1efKda+RrQ9cVvhYHMYg598haoh1ju2VeyMtTuybYtv9BO6JJiWkPZxJXlibV9VMISkIO9WmotsmClmBwqZaw8V5jnKCC4iJ1VbzGgoJljWFctzETr5tS+BH5Z25UY3AwYjOB44D3eJjugS1rL+OSSY8aGD/mwkSt4ST2yLD8mHFBDCmQjm4iZ3AHxvZHNaps0RnHrwMIG2cnYlpxTtInOGE7617AHilk2YluyDBkweiWXxs9Nr6A4ZFiI77GwYUWjbldc4LbE5e6ALlmwhIDC0uElE2gbc1zaNZnQoFKHdUoA2USQMxyDPI7XXttey9ZPlEK7bD1SVkIu5JikHgPyugW3iU1Qh+bWR5dkB/Qosj1Pbuyc6GMuvfO1dhZezkFKx0mgDqkzRVpDEV4uzCCYzxLR9aDztRpWXs7DtUTxMoN0sezd06SA1QJom+SljSENPGtB52vQ/WOgDRvfeDHTjA7cNKntzMCmAz04CWWj8eb5LNQrOXVFYZsu0CUC+hwwn6W6xqQf/+m9FCZgc+Bw/FRaJ9t/3WN2vx94VIiB9VGDB08lb8vBa6GsBa+amuywwYMPOF2O1HpNfXKOUgtH2dxYBvpdLRzrtmVjZ9Oytr3xc61ePzc5Hs39Nece7YPEoNcdzhO98Vj/3BE9Cljt5zN0h4ZV6P4mUP3Wzjnvlb4TQEbrCyANeh5KkytxnwO6YEANpV+0WN9Iqdrmd9Zwp11er4QR9D3o5Fxzcfq9JXjRJPBtjD9t+kBDHIVXC/Cy1TZaD/b69hL3XgjpfZiAG99YY/722XajvAO6tJ5Mt07UxPAMf7iEnzcJEJqJITcOm8NWM57M7m9inGdanlaAuenRnCTb7ffmIYOBACMBoYxI/bzO2sDzSOdpY0N7j37Z4vxWePeIGfO7HZrTLvVLC4zXPZq7p7oK5m/uw7cugj/T2eMkuN8P90bMcGuvoHd0AnrVuhRPs4QtHAf6bPIc+llMn8YMgBqlrqZN7JNRlH5XlGi8rm7dgY5PIftN/OEq1GvDDIwHsj9I6a6as7Bfha2Hte9Bmx793jzYEB9yNTenHdy6A5OLm+EMCFr3cHfPQ97dvoe/sR9CNODC29FzALoI/Zfun0evnw/tlTRrY55P4Mp1aQGuW/eJfhdAf7CAX9SzuLhNogAGM7obq2zToHWQ+cah33f6PrdnfWAQLDcPE6FfuIx+d/aghzvv8+fkAMQJsJ8nI+3WXlcNMiKOnnHyviXe/JQAWeDxP/TY+17s+1J3vBfX+dB/pU3d+db7AAAgAElEQVRCLWzDNEq56j4ZZXtMrjB+NQ446YZ0tkeG5pNijA5FSsGXU2qz9pmn4W8egtBHL6tLHfP4NK/3mafBh3tp9pDNQru83qcjBbAlauh6UNsEStDXv5uXjWCUbHiEZ9DJWU4t/Owz4OUsLR80cYba9aCS1vfZZ+CXlVx0VhhXvxRqBojjpxq4n3wTRAxmwvHv3MbN+8OcnEzAgw847P10eo4Pfut9uHW/r3pUj9/vsPip74OZQMQ4/vwTuHWv105kq8+ohQHMPv2pjFrYFh6U/fEX0T8ZqEZLT++sQi189mRB7xqfRftgDfeVbwUjzYz2E8+jv70cep9Nm65cj8i9t93hDG9/ZK6TyJtfZcxHQK47Kah6X/gg+pspjY0CXOZA61ujAAaSF0AA5s053vzkTD3xj30FWJ4HYhgU+Wzd3VhvPNa+8EH0i/1hbC0R3HFO1dt+6PmUaxXIAPHdD83x+L8WiHKIGG/8/efw+JtnKb63lB3RpQgxB6peS2f7iY/Cz/YU2KreGej2Wzx4Oj2Lg5fD5MKCQfGU0nkPfvn1kBfcM9yzT8HfXAXb14d4TwGwzb3TnNY3UupmaetiPeePzfDWx9Pg+9gfEfbi5EaAq3j53IPzwb3ZNGHWo82tw/qGrOQBi7c3cGc9JA54IDugS40X9z5Q9Zq+03zswwpyw1J/nzZ1Vyh1adaYHKVG1pshVe8sPf9EssDghcP5Y2nyu3gLaB6sUzpBAjBrIsht8eCpWJaAw+8gTJSb6F22FMAn5+i/9s2svZqTmgOzG6MBWlftv/5oD4N9O9mDvHpdWg9uc7zOaXI/+bEAcqX9cbICogGlbvvix7F5fC8He9Fe+ZXD6e3Uf/e+D7SdrHQjA9Cbwxb3nkt6vvEtYLE24ZjM2ga/cji7ZfrOnQ6NAGITukAMvPFnCS/927+i9b74a5/B6h+njYjqVe4jZbGlIRZ649EUTTugxyjbg2MkxZZdUtIzXfKyAtH76uovL3PatNaajWHMQF/AfYobwnRgdKkdZd2yFCPtEPrdWhskfKG8l9KzLNcxbntNv9KYtthmxE15YwHaoZ7i33stVbXk923DBTKKW1NOY2ljOfuOM6Wy+rcoEyrZ0k4DWC8jGgMsYHebN33k2mzPuej6pR6vQpcw3gYjZYwqgOHSVlYJDcsBFz9DYOhxyBqCtNRWC0uQPlgsp6Ud6TS+uaKI/yXmeG4At6QvZ+W+au28al1G+1OSKQBA2mOABFoxAvRsPxMwKMUcFOBq8d4rsJTzq/SxZPu+cQzY+s3vAsKzNGFj6YeyvRyk3molFpAqTBsHNLgiV65HB4lTHGyO8z70BQEP83Y0ljGwo0U9S/YCTUmVnyCb0rK4y1g2bUazbYSWp94DXZ6fODQAiYVO+q8dryvthemvIXdvOKfUFTvS9GR2BWlYKa5Wl2WYSE2kX/SVPmPPlbAFmSiMPMuQ6QI5wJWQEP1b1N8YO2ltualT893aNjqZAEs19T6lMbemLdm92Xjy6v1X/l2BbI/JncUE4q0bYoNBXK3xjo4A3TTriE/FIYQI1OoFEmh2xXkifZ8IHozBZudA5YsXNy9Q18Myn1UpYCMoZ+diblzOcsqVZSWF2agwQDuy07AUMj1nbNNXWSbbAT2Yd/AAFDMQB1EBolsaVADtwUa2cJHhobGy5nepXtshoCF6cqGD7Egbd0iPg5RR8t3lxuzSMVRS1gGMkckqUn0ZBa+d9ERJcZ4EuEtYNxt/S0VMWa0NLp2DuGTviOGZwvsn+IlHYjp3RZd2Gb4Eg8w58JdYT4mVM0KiB+vFlWfQM7j3ahOZ0uYWu1GMiXKKdNsUE9KwVQzQ1u+MIYCHOcYmswRkE1U4N63SxFCaMU/uFeuS1p06XWqU2GkCEDMTjPVNimOT98k7bB1JVuykpHCwDNI0SvaSGFKhWYoMgNLUjzLeyoqrtFNwKSW9wYWNZJoBQldkahMx0k1x27IrXLUuNTb1QsdA8T6O4INqLGtRlhi5Q6IApsTpLxn7V8b7ilNJwpiIoeEJel8KXMOfnn2qOzoN9N7M+zeQbZTqu6DHKNtjcuNSH627ROtLBHRdWPq3qbaMl5NXi1BWDPRqEb0VcYnGAtLVItAPAsEA7IWljzSbDQ+aWwfsr9A+/QF96LxaDMGl/HYQ6Qc9B4Oxvxq+tDG8gfeWaJ99Rjc88GqRqBXjkg4QwDOkLDPQuDzeeAvQvSjl1bst1vu6/1qP4390O/4QYmfrJwH7r3kc/9b7dLA6eC2VLcMV9l/3OPn8EzpA7b9m2FRgByygO1qg/fSntCMJra+CVQOINzeWiYaYCJsbIxTAUrZSr722tmF/hvbFF8IBz+j2ZnqfY57cq9YjkA8Qs3tr3PpaNGg9Y/YgZx7LlplXBYVojapXltP2VzlN7uEqA8L2vPndNW5/Of+u3tgiJ64/WKL5cKiXeg8f+7uC1tjv2RP8/grNR15Q0OCXi9xrZfrzjW+s8b3/Qe4NuPGt9TjAlWezA7pUcYFuV+l3Gwe/N883fQEBKHiP9rTHwcvxEAPtcacg1KYVAzP8agb37FPJNi7bUbDq9yMFMKAxuSk+nhJoRQgjuP1StPGOML/bZVTBFuj6/UhDrBTNi6Qb01Yw4DYeizsbBdbUcX5PFblyXcpYN2vg95ZoPvqhGArSwK/mWa5RIo6eXwbvL9F85AV16PBqHoCygMFZSrWpVL1AAJfLEHNLfZ/GSA7e3eZ0g8WdBELceVfdoAhmzO6d4/BPw2TLNxT2KfQMzBAnQj5mWAg0xM2Hn9fUb7xow4Q0AljJp0udD5TFlkZ8Phtukq3IVesyhF4y0HOi9Y0TlP5wkYPRHjrW9PvzUFa+Hy0TKC7uqTnvsXojfXfrqO8md17AAe2DHje+GdvmgPa4Qqkbn2ez9li8HSZDxKFevZ8CHD/+zxgv/tpndCC//eU+vzfDviaUxXpv9jmM4J6r1qPI9pjcTZ8tKfH+SsMB2LlBbKsSKbg2gGDJbRs7k5a3IQvOKQiW76E+pBCHPlL8tk2IA46AWXYKExDPNXlvfQTMkgWCY1C35NqNhoMX8xBHdLDSskAyALSJmx7AwQvcuFBvxeMxRghBjMA3foViwejs2OPm1319oLOeVgbm93rM79UbX3oL5vd6zO/3+nJvI4Polg36xWrocTDXl/L9woUY3Mpv6vGJx0LZlbZf2dScHtLz/cxhfXMx8EyPAtwd0CMANWiyMWT+/dP8N4ch/a1H2NCyLCipx5ZNhdYXqa4xgOlOOyzX4yn08gwQDv5wLw+TsIOANYytg7+xl1/PJ++TzbAwf/NMY3DVI11Zwktt2hFdAuGdi567XuJUXdisI+83eU4LZURw5z3m530+iRGiCMlIIJODWQM+WgaQYil1AY3Flb7lZw38zb18oI0eHns+g+A2HsvvxU2EgMbUapUmM4KfN+Bbe9r+Ye7e6Mxw4bywYaYghgCqoQ+7oMuwKTO8bLxy4NVMyRJ0Q1j2nicQy4d7KbZTlv1jLCxJSIHjQL/7+FHysPWcAK5Jg8kxfVlzElhIpf+mbAlIqyDx+bYP1qmdFHL9ivdPwLNb92Hj57JVwgq9f8nHGtvhFy5uTjww2ZmQwpxG9LULurSrSL51idaXeei9NBMHv2jhV+2o48ACR9p4zDrjHIu2KsvqgFC+2Xg0ZxIyaSYJFmTGLAnUe7Qd53bPeoXlHCLsvXqGvdeobotNG6hDoiyueW8rmwh3QY8i2z25JtZG41/jcX3BbZaCMqarcTkI1RhfzhSbXQ8J3Gq4gCOUoQMKQmMn19RiIhKSYFnOAJQEFBqHRpQZgsxV72OIg6ROEZAuwFxYXraFLOxIELaKDC7yGZXPRrbS7hbnj4U9bGM6k2vY4yU72+hSqQBd8cL6kety5VhxXH4bjcndET1Sz+DWLEECWRaDqgdz28y69P5aDvXy2rXft7z7WR7fi9piDG7GzBYNcJkybUAaUda/9Z53QJfm3dQ8uJ5D9JfxdGZeT3NeSEGVe6zLTAxSTmNl7W+mTEbMAHNNR+A4UGb7DmI4BbcuSxVWppzK+525D0JWHgi7+zXvb/mMys9WdkGXMgZ66MAf+qlLn2VMKVf/JEQOLoQF2CwExTgDIMX3xo1n1Pm0Usqc5aKV/qepv3xKGZZSS4XsJmTSkSmJhTf1xO+aGrQETw6hfqR6ddINMpvjtshV67LEMfLdEj+Q+WzvqQw5kPOB8RCAmn2Mz5qbFOIxSPFly1qxK27y3cYOl+EQUpZ5+OzJhEbZMI7L2PKr1mOUi0Fu+TDXmwDyJF5WwKsFfgWhQsi/57K0IRp7xxzqrABVuxFCwSyMsojyF9LG1/rokvOcYons7+KVdSHeWNtichhmQeL2peGiDUDKQjH2KHfEdQ8g81payTab1QBpCWhjHQ/Nhob83G3sa2PtLD3PZRaHrfl7t7R57Led0KMAoH4E8MUyg9l8FPXo2BgtCy7HlhTdBb9f8tkMBthYF/U1xjQetq1WNjunaMuYN3cXdBkly5UpseICXglDW1yIZEkAouewlifXjqsFMC6JGbIwCbtaZ+uKnlc7EGaTK6nLOADKnLwaG194jiVlWQaC4wSgev9XrUuPMM4YEMKLJnhzI9CzGRh0eb+hjBGNmJVON40zsb8SgWfBEBN8YggEkidXAK7UZ1dhmvQ9A89AcmZJPWas5pmLGxU5W57P4vKBnABCxtrG2ClvAPi2d/mqdSnPpQSVNqesbb8FkHqccjCpNswc58huNhKCY2OYq3GxYxMGAd+ehoCWObWtPMdeWtgSrch9WiC/ZePdlesxyvaNZ0S6WUHB3nwGZSiT8AKb09YCSfG0xuNqoCIg1kczaxNjGFHaRCZ/hc1l1upmuEw6k/3AeoiJgCaFVegGMQPOCaHcwDMtYjM7eOTtskB3LKsDEIDgjrjurdj4VwDqwRyQPoiwOa+c8FXqyAuk823c6yjQtNey16T0XctV2pjdIw0/145dKLukxwqYlXQvQAE2ROyAI+eKSD122RRFXWOzeHOMovchA88+P2cwOMb7ydpszys9Ex7ZhHnghd6avkMasSO6ZAP8gNRPyAx+DKjXVDaM9Sm/rBzTUIJZA1iPLVeuVxA8lB5WkQyUlvWNgN9E/5vAst1UCBSDqNRDRWOjB9lmbRjfRLj9Mb/bIhuVLahwZ13yqJL0q3h/FcIHGyKgQMt4QkkcSnaMEmdTmwArOwJtOEtVpiFO0h5piwXnjhX8pjCJdB2m2B47mULeF9WuOjMWN0ieZ3kOY7IDugyb9JDbp8yLWdipPlJoW7Aq4E/0awGytYX2HC7OKR1p1haWYLMElNbjX9rbvqhf6kCqU/Wo1OAGB9r6SmeF3svV61Hk4jy5peseCEZNbsxuPrNGz/CRp7+cgKjUK9kOpDybMvYFEIad+FXDIMK3VE6AtucQZtA2iS7U5NxFDIKnvh++XNYTLfcmQNowoOnyUC1DQ/kst/Tr91JGPafIj416MiugsPZ9AHqzApe/hv1bElCMZWsYnG/G74vu5SLZBT0KmK2FAVTjUEvjNva7B/QpWQMqf0uvrz0u14+Dwdimryy2tyYVUJyB2JKxjSgM1tazXXpxR663C7q05A1lKMJ4eA5nADjLSBG9ohmQlT7CUT8yEWrK8ANTFoUOy8mkCJnrmZU7OV+B6ch9Snyv3Feqt/h+gVy1LpX2ljkt/QLp/RRw0JtnJauGkulAU3olIKwxugST7SCMQdwgeIqNJzg4bHIQo2EQ4MxDq2EVREAb2dC8BzdpzGRPcHGM5FmTriW6tmQHzIkNz1xf9+NY7+8WuWpdliE52ecS4AJJP5nOkUCgxVAWa9hj3kxs7PUGQLSQWohBfNeCTcAQrAN52IV4d7fZ5XfQF0WuWo8i4+vrQAB0dpZeziAFBFrvqHPDZXud0ZkOYbi2FTiKQrs+v47keJTy2VJBDJVQmt9CU5K/VgC7obXU5s2aYKR6n9pWenTlPs21aNNtj8PVCyCw95h/lxEi+hki+mMi+hoR/eKWcv8yETERfXp7hRim2Rogvy2nv8OXdhQwG+B5KbkE8B4NtYiDtjxzLUf1+sq6Mqno8TK6fNR6ZKosFSKBCwWJFpTafyLG+6qpY5z5jmHZav0iI+ENAylBcumpHbNKpQcXgK6w1LxD2+rbEV0KMKAxRi/xERhvppYXcxhzXg50xkh2UesBxEucXbMAuHr5aLuzHLr2HEv9a9os7U3vJOcb3iIYCzlxGaX32NZlc3qOk0FcsX0t30tvwL5utuK0YhG9szpeFRO5QZhgBM5pchP0wQsT4tdzAL1j3rWY6kvrtuAYEbCKNxpxEmQ3l3PIGS/ZFLJ8vtImj6RnOde5MMaW9qkmu6DL/AQMvKY1caYskJcvJ/ulUy0eC/2R8n9SxhV1ir0uwyTM9QdgvWx7FkZR1B2vn/bFFJMjAclj8pD2NVzq0ery4jy5QtbQ9YHONj54Xi1S6ILMRqNRo/UGdHqe0orNZ2AhapDY1djBNk8c4OSphQKLvVfP0L59koc+xIdJ55sQv4toZ/eWKVsCpYwLYEb3+AEePBvSE5EH9r9zivZOqFfje4kAz+hurXDvg0tdZrvxjVO0bx2HawuIjt7p7uYKJ0+ltDp7r52H9gLj2RWAd+y6J6IGwK8A+CkALwP4fSL6LDO/VJQ7BPDvA/i9rfUx1OvpNiEFkUi3auBnYtny85q1R3u80Q6zOQrUt2U4AzHQrRzWh6mexb0ebs25xzS2YRutbwk+mzNTlkJasH7hqiC6em9C62vbIW24n2h9N4dz9As3CnJ3QY8AMvDWH8zx4OmFerb3X12jvXueA0cBs72hjQWUqrcEjtyEpVYn/R2oUgADEawU9LtKAVwxav3+DOtbiW508eZ5RgFchk2UoEZY2TQuV4BErQ2LYjOqkV3RJfkwqebGwW18oNSN9+z35oHWFxgs95/fXuDOh2e6UnHz6x0Wb54n8KPvOcOddnAn56neo1Wg5BSwagYyt+7g7p9pPf5gEbIqRFtpH6A77eCO05ig9cb22tAF6n3ccR3b0CY7Ycke1IscgRNxmtgM2pCacuW6pE2fNoGdF+/iwRIEl9KIufw89+BMx1F/tBfq6XzKZxvHQXd8HsZVzeKwgF/N8jrjszp+7gBv/Nmk4ye/1GH1ynG+0tKH8u74XMd2bhywt9B7kRAKimCVNnFsF50frkIZBXhef3NnXSgLKGbwC8M6WnuOuHpdWpvpZy7RzVMYi5w6zCzAJD1XV1WAPGzBrGpT59HeTVlx+qNl6hO2zQzQusuohZUuOAtXCNegntHeS/23358nGmJpSwSyg7KHC+2/JYCV5yBjeXPu4Xo/vkqGd67H8GgevY3dHq4g8bRAoMm1lLrPPhPShJnUJQACwD05G1D1YpkGNlW4Z5w8tcCrfzE90Gd+e4nDO1H5mk6Mg0fifD2kAD7ah6b4MrOfB88u8frPbCCI5an/eYkbbx0D8CncIoZG3PvgEt2/+mZsGuHubzyG228d57OpaIhP37/EKz+Z2vv0FxY4iiB31KtrPInvQH4CwNeY+RsAQES/DuDnALxUlPsvAPwNAP/htsrssn572mP28pv6XPnZ2wnkErJE0u3xBs1L3wp1MKN98QX0i0W+nyW++OtDhzsfT8dv/lGD1RtdNa53K61vMfgOqHoLCmAbR9ye9pi98la8FgPP3MZ6Xjces/tr0Je/Hrz7zGh/9GPol8s85jd7iFevRwAZeH3w9ALf/ekI1Jnwvs/PcePuedX4uPtDms3+xn51eZ9Oh3SjSusL46ViDnTBlsb0Iy+AZ3v6ux1Y17fm+P6PJrPzxB8Cq1c79TyotycOrLRJ4USWwnRwbycVGuLZfrqnUnZEl2FTLkB9ALj89W+r3XMvPAs/a5JX1JDdvP3RGf78v/4lref/+Hs/hiffPI/9K/cKu+Mz9H/ydS3bfPwj4Ft71VAEd/8sp9/92Ifh5weQjWKSLoyJ4O6fZBSvQgEMiBdQNhjGGFFDN+1WszS54lQejkBrHxwaCpzSRKzKeLYDurRgsPYu+qO9fLXBh3PcnUrfubGXv7MxrIBOzwe0vli2efhSHK/e+JEGX/l3/zst+8m/+dfw3CtIntpNQiB0cjakC751EOyik8lVANwDu/D8cymtWXiQySl1ep4/h+efA1azcO8jDqFd0KVdVeqXDidPGvrd73UB3Nnl/RgqJU4+ACnfbRlKEG1hW1AAN5/8WEpVJiCbQzxs++A8pwv+5Mewub1vgGgErkK/++U/zuudh0mIxtfGdrf3zvKyL34c/rG9BMYNnukXDqePp+ewerODuz9chVB5OD0C74KN3R6uAIRZZFeB5N4Dmy5/udU7WtyddeNfIEwI3lO5pgBMQyGc1RuBqmZmEFaYAqkoi4t4kl0Mgeh9zEEZmZKAFOBvQavMnh1gl9vJh/aOdlqR4RLv40T0RfPv3ynOeBrAd8z3l+Mxc/v0YwCeZebf3H7xERnZ1ZmYbxC8TPY5xGXSaniABYZbVjLqF7UVInmXgPpSNBVlpL1lXUDGBlXdUFdhyBuN1S31eLEuH70eByEnVM00MKD+Le9RN4yaesXA1yZslZCHWtytLlc24gHcPgEcSGxDVnclfIKF1rJWraXAHTO2u6DL2FbdcS52TgZMZ1Ibhrl8KMeAQ9FnStHJYqEjk3lBQwXK5dN0QxCPrAJceW8q1KxSJi29pmPh2kjpsYz9seEXWVha/FfdcGblqu1rXA4uN5PJffp5o+/qNvr34NnPGrG9LFGKi3WAUgiXl4hAOYznMWRvVu88IT9xmFBoVoXYlsEkw7yv6uiy4QuVstVwqLKtVz1WjoVUMAJBldjJ4nFcGL540TJ/KTX9W8+wTBSjjgYrXyZWPAspakb6e3mdsRhqObXyDFTeuX0F3gVdbk8hJlIDQxJ+IMKs6bgGVL0mEJ1nbdoAZqgc9QY4Xs9z2tTmGboMYqUI3Nd2ASEo3wiJsZcsCJrixA0MKHnTZonFBSLwRQbCwoaAy9D6Do6+wcyXiwuqCBE5AP8NgH/zHZ1XG8csp72vAzzm6CkXb5KAzMylO/K5uHa2W3OkjVptrRgnoC3kEtL2QVHK2zq4N3mHNAVP3ta8sqoegR9Alw+lR7tMpfXIh3Qs25hWMURkNpBmuW+zCivXLg3bKIBlvX4tZ2pZJ8Pk/bV2IfMsFMBWxlNX9uFwbnUjHrA7uswrSO8jBKAHEGrTgQWa2PDZgeFBWV/Und7yrAf7FKRgeObq/R0zYSxeQiT7N9J+BXljdfrwH1OTQDZiOwhp8JaBvIwFHmnfrtjXGk089T7kn3VImwQ5OA+odCCZGF3qe+Pt5ip41lUOCYVoHUA8tF8OKaxBwXZcbu4rbWaEkAkgtaHP46rDb2Z8lPz2supQ2hBm3Vy3ddVzV3Q5ItxGz63NFR7TdZVhRSqStWbM4WdtnKT+MunaBiLZHmqZEmy1ZR8SqQL4ik78yFgIjO+5AN4V+wo8nC63g1wJEwDAi1mivu09eGZOjQ+SfPCSalkxYKuFlstSeHnG/ndO8fTvLBU47r18Ao0bKQBsRi3MHBjY5BqRhle+H377DO43l6FcQ9j/zmlomwTfm9iUG18/wd3feEw73uG3TrNr87wN57QN9l85xdNfWIF6gB2w/8rppWZmD+G6fwXAs+b7M/GYyCGATwH4J9EL+X4AnyWin2XmLw4bAAV53aoBnrmtS/zdqsxPDA1v6A7ngfo2vgubg1kqWNz24l6Pm3+U4sAW9+tvOTGwOVokql4Emt8MiJoBdXMrUvUCADM2N5apjeqtCn/svQFAvzSxh8iB9uZwjvZHPqqTqu4whdQ8wjy5j1aPhRy8cg789kKfwf6r6wTqNNQGIUpnbxlofSXOdm9ZB8AegUI00vqyI/i9Rfa79QTUKIAVNBde38Vb53ji/0F6R946zzY/2HAFALlnLHqFAdNmmZtEelSKm1jV5myRndClvGeMQAv6oecgXtx+b6a/aVkO+rjxjQ6/+3d/XM+/+dWNVlluAvNHq0CpCwDM8AeL4UAcJxX+cBlofWN/9ybMLMvbC8AfRKpeoZ09WgE+eel0wHcEnjdw5npKIOFCfCIh7crnhgATmpLFKo6Y2ivXpckb74/2Qn/gcE/+IFHKKzEDQv/xN/ZD2IGMafOocylDhJAr2sEf7qf+ywy/L/2X86wjzHjiDzp88m/+Ne3fT35pA9moVKYH4yNTr/eBwtv7FK7YJ3voD1eFDVmkNFUeIbyodUCk7G6ffw7cNoHC+3CVLeePyZXr0oDC9rTH3vfkePg+AHbindVU/hz+lpNxA2T7w0WgyY3SH0Z7ZR0T8Xt/uMiohbujZfa7LS/1ynPuD+ZaJptceKA/MG1gRn+QcJpmZ+DAtNie9Vi9Ce1/7Vmfxo6RlYmHDFd45DZ2O8gVTy1zyFHbmCwGyl6WBjv9PJ8FECx83NYzQYmCkNCjvXuKozsnwagWdL+D9GINBQpEUy9Fz4cGsnPIh9veOcWNt09SO2PIA236lOc2tqN9+wS3v3SWPMfykks7O6+GvLl3hqOvnCfwLcsBF6QRewiF/z6AjxLRCwhK/nkAf0V+ZOa7AB7X+on+CYD/YHQwNSDPzxzWsxREnhUrvvdzh36xGAwutXPdOWN13g3KlGUzqt5KG8v29kuHfrHSQT6rr2iX3Ft2fXk1KG9Hv3DoF0uUsi2LxJXrEcb75QnNvTVu3IsxudY42pCDGC4QqHoPtIz1ppQED4wmi8EdbGQTr5APQLS/tZ9fWz4Xx9xph9VrXfrNDgQjnoEy12cmPpXhw+J9cnmZUnZBl9mqUBs2toa25WnCsr9EWL5xhuUbApqMDTblJGewX7Tw8zYD1PpZzo3eVz9v4Od7WR3hQ9SDeGkdwc9b+Mda/d1eOyOikJx01qEAACAASURBVNdQ4/7DpDKFy+SgnBE9wqbORCAy4rG6Yl3Spk8AtnXoHztIDpi47J+97/LeNgS+ua9AkTa9SfkFkI+0vRT77/IwHBegKrmvZ4au3gOr147x3GvI+jpLWfECEoHYh3djfpCWpmOIDzfNYDmcZw36mwcByEbaYrEHYmPk/njWwN88SMQTNoXh1jCM0Z/G5NH2S0OyQB1jdt9sjLUrDSLidTXPVVadUmwujO4p0OQ+tqeAUoGyPCdTv581KV5XrifPSDy/8Vyt17ZV7rsAo37Rhk1ppadXwk6Ml5g8Y3bc5e3c5snFQ4PcR25jtweS2tgo52LO2ch2VnpyPSegJy+B5P+LXl4xkiSzRHmwEeDqMmXZATZdenGk3t6nHLd2KUeOKwilxNAWzwvHXbpeGfJglw66WJfnPO7W3qPEAY8uGeAdp9Jg5g7AZwB8HsBXAPwDZv4yEf0yEf3sxTXUGjIEpluLl4OrPVZ+r9Rrr1WGFsg5o4CSTHuLdlTvYQswHVx3TC4oU9PjRbp8N/Q4WAorwwfE+Mi/8hwBsmUaMpefk0kJWmu/u8rn8vzK8ZBKqbiXy8Z52TpdAmU6sNTagt3RZcpsgADmsthUpDRf9l+5cqRx8rajIqXnstep9OlB3xEQHOvQmN0s1Zl5zvY8R/m7Zjy7sMDXnMOO9DqyHF6mLGObfrKQXbCv2pfiagN1Xt9r2qRxEEAYbySe3E4YjRNIJ7KtU3Cq9ccUY2HviNW52Zwpqx4NAa1hGzUAU2PBbWx7zzHfMlIOXdkEKtez8ZzmWXPrdFwMzidoTH5wB7oUBzyy+rkLuhzdl2DBuTwveSalTZb3QGxbzbaOgUtG1K8pZ8/xw/PlnNG67Xti7etYOIRNY1e2XbCYlKmc/zD2NTTn0dvY7Z5cfZEZYQ2TEzuZjblxLqEVAYZE6oHlhkBnHWgWHo4yj2XX8CHmUwA1kK6hcbSxg2kMEaWNZF0gfshy9IrBsIBawi0skJW6LZuZbUP8O0h7Yr3ZliCjIg8zq2HmzwH4XHHsl0bK/kvvuP53AHjLcwYeWk7fLyRZML9dxHimp0idNPztorYOrl2AdmV9MyB6NI3YjuhxAFDHQGR5rOJN0jK138rjth6fgxxJ6p/t9jZShjBo1oAiQb16nex9Fu2tUgN7JG/aJXjTd0WXGj/sSJ9hznaGHKQSBim6AAMEDehN8c3aqjxemTkH2nIsAlZzM+a6qTEMgut88NIS4qYl0n4mYQkp3hYJIFtqYdvf4nWyumDaVn2G259xTR65Ls1kiymGxUkaMBjApw4YBMpchnpgQ8hCA0gMb2c2NXsEw9RQcDYxpxj2OI6ReFdjmINuwDROGXaBSEnjayNwIh/SoGVYiQCnHumiT8XNkupVTg8rtDmbuJrVNfFsj8hO6FI8slYsmLWAL1SqJCuWHY06u2KB4blyntgyu8kPnL/vEfiy3asguinNnaX8FU+z9RqLlCvxOtkpviOdT11iK9w21j8sre+j1uUlYnIRwGMMkNe8uQIgbbJoy3RmwCaZdCVZaIECSkoANrQ8ElH4PGQiXlezIwiwJQJmhbLiORS9wDxrUlujN1nbIHl7AYD9cFBXj0IBjAWESyYGGkG5/PAKf5RSbirbSuFbfq+Bw5GXuwS6g3JSz5aOsrXz2N/G6h4rX/w+do9j3uJd0ONgmWjEW1ktG8sPQKIvypafgSrItIObDLjVnfAV4Dmg/43LpwPWssozH2yqK8BuFnNa09mu6JJhmMkEGZqfSxAo72gZogAMvmehDDIRLyWzaeFCYZLhUn0Csu11TXu8xNdSohbWzWrmb0YRTGlSlNoCqPe6eEbhhzGDswO6lFAOQ6PKJpZYwagz5XWTmU8rLuU5AnALVrOUlx7qqc2IHgS4wiePruQejl7WcG2klZ15m0Crc4GO15lJqIshCuB6yEHh3c0Z8zi9h2X/zurYAV0CCRDWvLSlTZX7sl7NWGa40RnDflt7r21dHJ+3N8xqFpOUuEeuY9sq5Spe4MHk0QJ8eZ/j9eExpCKuya7oEZeJyWVOqcIkRMEhkEM05gadA3yfytmYVfsSAOm7EDkI0BRw27hgTJsiXsR2NuZEuQskwB0/i0gbs2U1uS/nco+07HR1yYhYYVmGkXMNaN7mZQCwEzzONYBrj9fAri13ESXw2LXK3LtjgHOsDdlvJfi1A3AJWEcuMwDQRR3bOucu6FHBUOmhLWUsZmrM01nWa0FkAYIta1NJ51q9duGhza4nYgfFbfdVSgnQbVvGngF2Q5fU+7jMC13az+h4CTlA1XfVzjjjcQM8LQkDW0BMCXQqeCwAtKWWzbytQAK45hoZYBXQLm01kg+O9ecxujtdrj0CdK9cl5I2qw3EM7TxCky5iSudsf0BRIbibt1HprEEQNTTbsMFOp++i/cuemSDM0cAszQoB5yqTzkXlFZiutAuNqRKslyvm7QLEosQ7hffgbYY48UDHQF72BQHBbhkHVoVuXJdGkA38LBaz2v5PgootiQRtYl2GX5S1MvlhK6cFFjbBiDL8iAiYLqWMUc8uyLWlpSgfsxRYDzIg0mpnHrVeoyyHeSKp3TWZoMagOSpFcDpfVrul3NdGGF41qQNX8J6Bs68vtw06nWVejNu9XJmA6RrNS6kYpHNZTE8IS3zcEJPMpPsIqmzrdNybpvZkcRIKcC1v0s+SJtOrZQdmdWUntuLT8gBaclaVsqo53cEHNs43UHMbgGEq55eF8EzUlkFybaOEkuNtXPL9bT+HdCjzuxFjOdyABBc/ruUzyQubZaeGHv+mGd34A2utAkwn7O6udquzMtctsXWnaXwwfCz1Fnzcu+ILgNAMOBDAGg2CePhRE7e0wiINd1YDHmQ4zaVE3mzrBzrG4DYrHHIPbq2r4gX0YJx+clLpoT65F9Y3gBoiIVsktMy9n224Lg2oO6CLtuwqZm7yIgFpM1jAJIXTTZ++XjvAQyGcc4n5jTZ2NUS0CCwk0UPLvUBWOqQFjdGKyNhrd8QAW0EsjJmgzX1mMZA24mnR1hZaSPoteF6nY8kJgbA9mnvjVIESyiDXV0twxus7IIurTeeCkrr0gMqfyNI1XACouGGMl1RQTqvCFEAkIU71FehBP9U6hl7rrYu66m11xVwL+2Uc/riuxWiQbrW0MYd0GOUi2l94+xOqXplB+dqCV6YdFKeIw1wZKuROFhmYDGP8bIxLYXEvEbDTMenoBhXy3vL5MH1BM0bGUMC6PhUOyPvLTWVmdAOSp0Aw90/AbqwKYwP4+5EfZFCWXYOdL7OKYv3loGyOErYyMbQ8Aeb1my5iLl8vcYdlULYjVmNgMl+QVgfOB205sce7pyrAHhz0OD4/em+9l/3mFVSgxED66MGD55K9R68ZsoWg/PmMNXLDjh4tShrvEsZrS9CurFu2eTAO4pbj9MFl1JSC0u9YxOBXdGjigfcOlJnRsPn91fAoskNGoKx5kWDzVFKCdXe38Ctu2EKGIdENxoNntDkUl+kBnNI9J2mDcpVr8t2YRWk359jfWOe3r2760Dra72wcYAZ0KPuLcHLNsQa+lQ39Qx0Hi7aBnYE3l8m6suKsd0ZXUaAyo7gNh7NvcCeCEfw+4uM8az00DZ3TtSe+b0F/LId9B0gAN3NQatgtD3u4c77BHTNRMN10X4jPFe/Nw8ZACoTKLfuAg1xXH3zB0v4mUueY4aurnV7M6xvttr+xdsbNGddHvbiAnB2Z32iFmaGP1ile6uM4bugS82uAISsAkKXHT23bt0ZPUZvbhOecfPmHa3HH8Sd8d5DculK/3SnG+1n3DbgvYVuTCO4tLLiGtD5BnQWqGDJB0pdScfHLfJ81A3QLWcRODOak8BSSQ7h+sYD7ZctNgez4FxwQHvcwZ11kJdONp+xI9DGo7l7nEIr9pbwyzaFKdWeI65elxaI8oywPmwhhELtSQ8X46UVwDYEeEJzFvtDFKXJVRCaLuE6j+ZetG29R39jleh3RWL9PHPoF0KXbSh1pYz45jhkDNocRHppH/v6us8BcRRuSCnvicPYSaUXOdr0k/fP8caPpnH09j9j7L96ntpQPkLsgB6jXJ7W9/g0p9R96v1K1Rs2d8U7nbWBfvfbibSiffYZ8MEqdJSYqQAunOfuHed0wU9/AHzzMIRDRM+vAGM6Oc/b8PxzyYMaZ7kAgmf37oO8bPtMBNAuV6ID6P4xute/q4ea9z0JPHYjdMzWhRfcRQt72qP7zsup3meeBt8IVJajacSix+RKJQ5oTMD6wOHeC+mFPfomsDyvv5EPnnJof/INMBOIGMe//ThuVsAoE/DgAw57Px2eIzPh+LeexM37PTJyB1Pv/KfeCNUQ4/jzT+DWvX7oLeYhBXD74y+iX+zpdW35rXTBhdTq7ZZFvVZ2QY9AbthOzob0u8uD4JkFdGmMmLE+muPOh9Pk7ebXgfn3TXocU797UFCTvvBB9LOD3HMby5ZtaD7yAjjqJ4tFZML6xhxvvjjTScRjLwHL8y6/p3jOVqpeeQ4IALqpPYdboWw18fyu6FKEAXf3ZEi/e2OVvJ2mvc2dYVm/ShN+m8Jrc9DiwTPJ1B+8AszPZbUrr5dON6CXX4MwHbrnPoD+cJHCKnR1huFO1ui/8tW8DTHVkbBeycaz9c0Wb/0Z2V8B3PoTYO/VPgPu8CG/qLt3mt/bJz4KXpjsO5Vnd9W6tB7RfjHD5jD1s/bBJk30OFLkAqCNh7t7nFHqav+V0J7oWSXmMK5aCuCPfgjYX4YJZZyYhsYw3HFB4f38c+CbB/r8NMTAe/QHc5zfmqlulx3DnYcQxdR/A9jdHM3x4Kl0b/vfdVhE6m2N5WUGeaC5ezxs79yEPFYf5NXrEoC2r9tvcP+ZlCbv6FvA/L5P9qpP5d3Jekipa2lyTd1NjdZX0nnZdGQAumWTU+q+0cGdGKwhdtARNgcN7n2w1fHrxreAxZuxkXazsgP83OH8Ziq7emOTcwgYj+8bP+rw0r/1K3rJF3/tM9hP8Goou6JHXJLxLIDM4q2UpRHv06qwxLGWOyfN0r9u2Or6PA2ZFQl9kOWZMRd8Gb6QgdeivV03PEe9ugUZgjOEmT7WVaM2tvWNGWApdtWu+4d53xgxlCwAXABDT4r1HJmyRGkHZi3MIaMFjgUGcbLbmla2Y0v5sbjiYUFKbRx75a5aj8AgS8FAbD7KGNowlm2gGt5QLVicX4sRk6+GmtRuLrM75bM4cLs019CoftgZ4xvbamOCB2JAcPWWdkCXmklgZEAI8ZzxM2xKsJpLMwBFDaFCAvjZ6oQBqhnBAyM+32CjyQyeEkuZZTso7Xx0INCmDzvoJX63Ik5oSO19201yVuI9Udb44tavWpecGbTseSuzIMXsGbbPFfeqExp9r30IXVh3w3eESEMf4NMKiO4TqbQvhQxxWgnpcj35mYNbU6LnBdSrWOZazTa7Sd0CoEfaMGBXLOTKdQkY4Bi/23FBPLie0j1vE63D3HP5jpf92o+Uk7ZImTKEoChOPo55bd7ObMNwHBO5oWH2BdMfmzg569nn9zUiO6FHXARyxYs76qHkPEaKeRwMmjRkPGtB6Ov1lrGtQvwwa4adPF7LbjoLDa68GBqf67WMdvjBTMtpmjPNJlHG4mrZtJtcy5bCgNsR1/3WeFxx/tjVCkICuLVT/BA0cnnAeGXLegdlkZfbKrHei2KNSyKKS6Uhq/2+U3qMA0X1XUcKKzDlB1KLxxwzTBIHfFnDZeN0K+fZDYZZyjEL0AtR8JwNGpd4WUZicndCl/IcmkojuYhZpgB0qxMwyVBD8XN8NCkmuugj9neC2jbqgweXqAGcV49wvlNe6qgDFV0WF6+hGhZTxi6bbnEO6L0pnXjdXly1LjWzSFPca63fAWEyJ/mBUZSXepwDrTtwazyv9ppZfvY0saRa6FzT6G+awWEQXwnVdQhrcNomGon3JIZ6/zTtX3zPyneavMlq1I4gpB3QZUqjZQcspH5nY1cBnQCO6rp8zjUbajfoF23RyVKxQlPdi2CcSJmTqcinTFxxQplrpv0RCDHGHMCtAN1ssK3GDe+AHqNc7MmVF34xC5S6QHihVwtocHU8Zn/L6HdXi5Q9wfvk8QXA+6tULxBCCmreVgB8uIf2g89CNo7x3jJ5ki2IJRrSEO8tUyo0R8CmC97ptkntBYA+1it19T7zOPP+KrRBXuqmSXl4x3YZYndmNUwhBvfom+E7MTCTpY/MOIc/+697nPyjx/XY/ut9VsaCxoPXPB58/kn9+eDVPqtLrscUyh5//gk1HvuvFT3C4JfuaIFWaH2BRL9rgJLI5makAI4GZ3NUoXdlU/bHX9R3bHM0ZHYrm7QLerSZAyz9Lpjh95Y5xadPxnF2b42bXxUQSWhPutwbaoybUgAjDFZ+uRgaM1eUje3yh3l4iPW2zu+scfulNDma39uot7fMuXsRtbCmG5M2fOh5TWHl95ZZ2VJ2RZe6scpHSl2h33UU4mFd8qBaoKmUuqZsqJBS3mcAIGB20uHgFeiEsD3t0qDNUDvtYswlffDpUIeHMlhl4FIw1dEKzcc+nPS+N1cvMICUo9Uzlm+tcfulmdazuLMxGwzlXQ0gPbs3hHc8yzhRPkNcvS5tGA/1HvN7kWbZc4h7F+9pFGX/XC4CHXVkgOO9Bcr0YCJ+fxWW/MUruxA7yHk/lvH6+efCz7MWfjFXoKzlJJSp91i8udYNg81Zl2VH4FkDOAZtejQnHQ5fDrfCDmhO4p6XCMrR+eAUYQYvF2oX2BH8wUrDOsYmSLugSwDq/Jrd73GUoknQWFpfo3MGoT9a5jS5RxUsE3XX788DfXZcAe5qZaO4jcfqjU5xpVv74WYwiRa93+Po29A+2p6YvVEGjDMIzdpjcSeFq7m1ifM1K0AAcPufM178W/+eHrj9z/shMYiRndEjLkEGwW1Maj1rwYt52m0Yf9eMCdbdPp8lDm5TV2BNi2UE6LZNiGntYvoxzwB7ZVcT7yhtQnwwH+yFsvNgTLlpUuowogA6vQcWc92UpmW8TxkU5sngkmmv3J9uZPOcWM+IQiaI/VVqq3hQZGl4RHYlPgUA3JoHMbg1YgcAWNztsbjbD2d71okWy8/v9bglMbhUKYd0fPagx60/qdRbOadbNuiWOa2vbbPNzNDP3WgMbnmf/TynFr5M1omd0KPxZHIT6XdLx4iZ4StJw6bH/M1S76x/2ZOm+VL6zhq7kf3rwiDYP3aAgVehobRJLB53px1WJwEAlIQWWQYXH+u11MKF2HRkg7LGk1z1YmM3dKmhCp6VJrf0mnLjMq87SdnbbQZmARiQmQZK2njM315n1837bxzQGgK3bYibzGwB5+A1epP9zME/cYhh2EPw/ATvX6jDnfdYfjcf9RS4C9AW8LycBarZuBEtY4EbDT25el0KMCTPoJNN7swhyqhwtU+0Dv5wL4WVyKZLJZJA6oOtg5+tUpoysX8bn9LzEYGbNox5i1ncABqAt2Q10DG8C+fQeY9mE8AQdRvjkQ5tChvLECZCZx2a000+6SKKG96gHmpiAi8J/ewgMadJP3So2315jletS7Na5NY95rLRzIoAUWPzlFLXbkrjCASN2SVGpNQ9SHXZOi3Y7QHnfQCgFmPZFGzG8+w2PsXgVsIjNGwhxuI3p32qI7PfOXjdf+UM+6/HSZE6t8z9V+TK9Rhle3aF6B1VoKuKlZgMl2cWMMrKctVawghTjmdNivuxA5EuscngmjqHSkxrRuJtlZyB0pm6PpFGiGgO3iI9mWyGaxKdYkZUYTuo1CGzKJNTELUlRyAY/Mr+niuRAkBKXljxyMrnQU5bKS7HCqA5GvNqB2HrPRp7/6lyjqmrlqt3G6HFhVJeY5vskh6BxBcf32XxzuimnzK+K0rGKIbcUGkIjxg9mx+ztjwm9dkYOzkuqYJcfjybKFsR76GG//AACGef/fDc0rMxGo+8I7rMnkOcMOcAAtHuQt9T9WpyqkPidbOcuBZ8Ahlwlb5oiRsy8giY6xGFVFbSZh/TfdkQCZi6Kd2X5tG1y6xakXlHAeiyu7H7A0xbe292RJdAArr6LmeMfT7PkQqkMax4DtwgKxfinGOmDUR7x2zsHum5WfwtB+CjwDXmd2dDXMSzONEyoULCShYmnCE9GclvFEMIvQCntEob+mA8LrTSOnYaezUGgHZIl1UxXs7M41qyoVmgWHiuuaVhXVb/ClrlhDr4zcRMgMdCYILuKGRQ2BZCYT3V6gQBOHq3NUXatvC1HdLjBTG5SDs2LYiVWb3E35YptDim2nKJfjA7H0gP0CpQAGU264tP0hh/uZ6CWsuKJi+CyaJAxmsssWJZAL3cj86mG5B9oeSa1pAIMBYrIwxtNeHdmdUMBhoLSguAmnkLLJjdAgxLsFy9Lg0PWfCr16zE+2ZlzXc1/JW2lcB4bPPZRXmAd0aPMhMXA2TDDexGLNlYwvkxRnr/szy2Nj9jlDBBLah34zUBDI2tLJs2lMBlpVsImM5CFCwYteDUAmtzv6OkAXbptrifdLEd0WUUBQoG6KYfgycui3HMfqas/1RjdgkpfEDABkxMqPadHOBm2Q9kKVxBdiqbE1hQZlO0ngy4579ltptLkDwE3vnDu3pdUlz1BFGaGBINxz317MVjQtEL5MQLVqrAnhNolHGxB5gElJjQBUMqkcYoA6DNNbRf6oyUFVwDUJAcvIkRfKvbE+ohBMf1I9v/ZFWJKrHIel9Xr0sACYDafmjBXykWLwDI8s0W5Sz+yJwzY6CxUkdVBIBuOT+sUGN4f/Je2utb2yybfoFEEbyNOn1X9IiLUohtktubYy44EkMsYQpauACtcbkjeWOTt1Q9r6b+8NAQl3T6FKclADl2oPSA06wzi3exRlG8sfYaQhYBpPZImT51XkBmPUh1ST2Abp4DYLzG44QQuxKfAhQd65JlMk+t/K2B3gJMlp9LIK1iAOq2rAzWi1yey/Fzre16zBWnl3VtAfDAjujReDwHg1wBVMeW6gFkQCrtukbu2ZW+F49rOEMBSAf1Wq9q8bcEp1neTOuJLT3IEh6hgL743bSda4NTITuhSxiAaL2oJX2ubCZTb5HRqwDLxvwmfcnExWZhQwKY7QQ/gmm7mRaA8cKmOpS8wbZTATFSPzJgV4kp1DtUgHm5J4KG2IRz0/ExuWpdWjYynRjaMclmKnCc3u2yfwoIEQpdWXGR1FtdytygwFp0QSYjgvcxSxAl51ODNM5KWBAS8Mx+BzRkSMv0aXwPXtpQTCcknlJogty7eKQbqS+Gc2wBQFetS5XShliva7E6VT0H5hxj41RHDaVQneig0BAACzrttSor3nlKR8rbaaUWC80m/MDWNaaDipd3PIRopI73WEbW16MYzyUJm4l1mwvws0v5WUoYl7y9RMkbar2isoGrbQyLmnloWs4n75HQ8VYoedOym8vrsEsMhimNnWmL5qMMXtmM4axxqX1iyORet7GdIRgB1+f/LiNE9DNE9MdE9DUi+sXK73+diF4iov+XiL5ARB8cryx9zJjFKr9vKzMKUO1nAzJLsLs1nKAAyuVxMgA2K1cBpoOMD3JtU5dWU7Z/RGp6vIwuH6kegboBYh4CVW/6A4bHs96vlNlFvTWjV3hWR9tUhknIoGpjaUsvg/XuevOvbIfPz83aa/+NyM7o0ooFuCYNGGDuVdJpcQSy8k6LHWXWnOU23Zj12Mu1gveIUn3x2gP6XSkXgVXmkTXA1ALgbOCTOrIVungdA4Izib+R5zyVVUV2wr7KOX0I1eMmLdXrBjJ5J2V8su9+zwoo4RE2cMlStziPECe2vR/sls82CwnbmNRV0s+brAnZcrrqJlWt70JvGD8RJ0MRZAshhZTT0AV7vjR188Ojy4H9sF5PsUtGN5lYh5vtC87UE5f/s9Avb/RU2PKsDXKN2rXHQKctatphdZxdq5ywmElOdh+VNjysfQ3Nf7S6vBjkyvJEfKHVC2pCBEIyapeAoABbs/w2AJldnwNim3ORiodr6X5tfK9sCnMuZECwqcQEOOsSmzEqbQM4p6nH1CjIPVgjTZTOLdN8WMMhXuCxR+nzfxcJETUAfgXAXwLwSQB/mYg+WRT7AwCfZuYfAfAPAfxXoxUWoM5u3qIITEsQOdiIZb5nIPISgLmULJWR/JNDvgJopS5X1E+p7fZ69v5q19ha5xYp9XiRLh+5Hsu2R4OTeVwl36G0Qb1DGAemcemTSo56DzO5RB5PK4C0ZozluuY6ZQaH7BrGq1cFrzII2NUhKyaUYRCrO2LldkGXWayqfBYAW96rvMvmPBKvrQGZ3LiUnsrWF38L925ynjrSfLxsw7zMeeEA8rRXGXhNOpRsEfY8pfK19yh91N6D1CuxwtGZsS3nbqjjau0r9QEESDyuzU4ggBAUVi+FhldXKWXCZgGEg+YttToBkDtw4nU1W4NJ36axwXEs5Sburel8uKYZE+2qqu3vtPEpLEL25kgf05ClpJiwRyalHCOO92KXuy2grj3Lqx4rxzynpefSPFv9fQxRxbqoK+oQ8Oigm/bSikDl2vmNJzBsba+0q2gPm7h6dRzY924MtNp7kvKX0cs7tK+h+kdvY7dvPGtMSEHXJ5rcpgEf7iXPpyB8IM30TiIto2fwch6oeolC526bFNfT9YGqNyqUl/MAWEkogJ3+1h8ucPJU3DlPwN6rp4EazwbuMysNL52dB/DZ98DhfozlZQXiZJKXZ/l92ybl3uUi5KKMzRWxHO+DB4lhnNXF8hMAvsbM3wiXol8H8HMAXtJqmf+xKf9PAfzCZSp2a4/2Qdpt3R3O0Rt6Pxs24DYe7Wl6Nt2qgZ+5NKjaR7D2aO+vdWKzOZrDz53WpUIBWIYBM7Zpk55PlgIJoQ3NWcyywaYNFdDdrxxOH0u/rd72aM78YICUXdtukzxTfrYlVgzYLT3G57a+vcLd5xODRhwe4QAAFNBJREFU2I1vrDF76ywPYwAAD3Q3Fzh+KrIUEnD48jmae2utz8bA0iZS6sbz/f4qpJOy5ULj08BsxSdAbMEtbXq4+6dqLDMK4NgOZTxbd8E2OKfplbiprJp4wO/NcH4r3BsxY35nA3eyGY9z2yVdyrkE8LLRd9Cd9xiEMcTn5jZ9oBCN3/uDRQBDEWxSl7yt61tzvP2RmO2GgFt/ssHijbNA26oDYxjk3HkHd3yuTgd/tArUpBKqEPsNE8GddXDHkQ69cSHl2azQT9Srn7nQZyH9LqyUMSgB/Qh0uXHo9po4BoQUaLQZ9uH04HD1umRWEgSho2YZ5xbzmC0C4f2VzAVEoNMN3IMTBRn+MPQHSc+kWRY4ZDaQ/gAgpOqzY1DPYYOgD2CTJCuCZ/CiDeN2wXrF5OAXLU7ftwg2mYC9187RnHVmvHZgIZwoc+zKBDUOBNlm9fNN6OvMSkMM58Clpz97jrh6XRpR+t3Y//ob0h8wCGHw8wb9UrzkQHvapzhrIIDYeI5QKMPn+lB7RSm+1p13aO6faT390RLeUrenm0S/1+L8RqPjwfxeHzIo2GvF5+9OOzQPzlO9h4tYb6EbH5/D/fN0naNloiyuerLxMHoE3gVdbo/J7bzGbNHpeU5n++wzAegWxheeh2WfeTq8/G3KuUjOBUN5UqH1PdgL15Q6I4A8fnqFV34qzSKe/sIKR28dpzhfAaDMoAcnQ1rfwz0AnGJoxRO76QInuHh995ZhFmXrlY7JDKw35inFYCN5BiNyWVe9kacBfMd8fxnAv7il/F8F8L9cWCsB7ckG7ivf0kPtJ55HfzvkFc1iXil01NnLb4bvnoHnHsfaAEy7Oay9v0bzR98O9TCj/dSHsJ7Nh23gMIHqVglYU+/hOkbN69ue9pi98lY6/ZnHdMAEkG2OO73l8NafS73/sS85HLzqYT1dIm7DmN090++bG0v0C9I6a7Izeoy3ePf5GZ74+T/Vw2/8j8/hiTdP9buN0X3wgTm+91ObNHH//AI3ZLJD5gE51Cl1F8MUXQyXpwiSgTEa6ywswgHuTkE3+sIHQ6oypMFS8+aeng8pT2/sZwBe/p7fmuONH0nm7Ik/BJYnmzzUoZCd0WUEjr5tAr1qlPkdBLAhjgOf+oc7WYO/9bIm+XcffDrQ7xqPuCx3v/2RGf78L3wJPRMaYvyff+fH8ESZUixew909Qf/Vb+jh5hMfhX9sH9YbLOLONwP6XX8r0pgSNLQCjuBnDusbiR518fYG7qyoMwLdbr8NVKrxlTx4BTHv7Li+rlqXuukM9b6DZat9TLOONLFs+Y7fPoTQ6AbvX3S2FP2h+eiHwDf3Ae8TA2Lse/TgHPzK66C2BTOD3v+Elg2T0jRunzy1wHf/hdRJ3v97C+x/exOAVoyhRWwv2KwAAMljLCA/pkgDc6AGL+i+/c1oQ7Z4cq9al3ZTVnP/fEi/e9vYQTNp6JcOJ08mG7T3XWB2v0CiDgDM5D/iZVkJyDBE/NwcF/TZL34cvjUTHJkwMbA+avDWJ9JE8/ZLwOrUrKyLMKN5cB7qjce1Xn0Oqf4qDfFje1k7S3kIPQLvgo29ME9uiH2tjBJluiztPIRBloG2yeJs1UNau2ZJ9atudwehACUmMAV+7BTnm9zt3DoMqIBlADZAOLtG6a638cNShWxaK+uWzRsjyiZGLdD+cSL6ovn+q8z8q9UKLhAi+gUAnwbwFy4s65EvJZo2lt5WKpdrgMFGs5JpLLAlhQkKmRCUMktDTdSDe1HfIFLDO2AzA5JXCEgA5xJ1ps/14iN6BB6RLt+JHi1wc8TwTHBGEdmSv3oHKvUICJSlrSLkQOtzJk2ZPQ9IfcuucJglTy0PDJm9LAjuzbExhTlA0p6NhjdwKkt98jJll90lXTJSjKs5FitCtrTPPHyGsn8AyAAuN04HUQBo4vuhsbh24i7XLG29xvqm6+vfktZXnqc6PiIwl2Ki1vhPPYCErHz5DGQSPJZ6bmfsq903YsW2Wd5f+alcOZIwBo+4fC0hB8MxmOzqYxmGRJRYzqRv6jKzWZ3cbAZdjSnWAR/GgKIPZ44t2WDec/D2xiVwWncoxw4y70f1OWGHdDm2dG8n80BuP8tmZ/2ZkW0KK7LVZBtpy+ODMbjAGrEuLyvrZqzN7sG23RW/2fuzbZZJTGljbRsq8PDdtq+hCZfT5XaQO6ZoILCImSV9LSexrVYk5MDJZ+vCL8p2PbCqPFAkgMUacIl0LbNJjDoOIQqliOfW3BfPGtCaQxiGDBBdr0QSek/A0MDK97YZNcChHFIsTpI3mPnT9RMAAK8AeNZ8fyYey4SIfhLAfwLgLzDz+Zb6cokp38g+W6kz9ldN+CwiO2rN4FPbTMbyHAy9qC2ftZ+RAeda5odqui/ZNW7qzgsUf2tSGqGLpK5HYLsu3109GvFsQJ8FeHFJUWOi1H0uJyI3VDWj5RneGrURMKzPsRwYTT2D8gKA7WC8LbYtLutloNvemlzLphEbtHO3dJk2hAGybB9ipCXXMKVXNBtkjf2ldH6g0k0Dr4sfYuLFlJJMve+sG6UyYdbcmyHGl6qTZL2PyJol187IdaSNUrVsZpPcnuWgLPdCqZ5qvPYO2Fel9a21jyiL0VXpK1kGVLecYjU9gue1cB5xY8ZSozcbXsfmWPIgU8qWYEMYtGxqtzWgsn+FTeeUOF2WyVRsazWsSO55m63dAV1m2WBq+pTVMX3O4w4uAHl/HdUVBjmUq2GRZRuZAzi2ef9RjKM6UeaL22lBsE8T5mrZMRsNPKx9Bd4FG3uxJzcu22dUvY7Ai3nyapr8uADAe8tAKSg7MBeGTUw6pQkNUJpcR4F5zG7wioCTvMfea2d4+gvLaBiBvVdOzIvGmbc4o9/tukDVW75sgDKpYW+Vgr6LZQC9hiWYkHir3odwh1m7BShtT5kyIr8P4KNE9AKCkn8ewF+xBYjozwH47wH8DDN/78Ia4zjSHczRvvihcMwRNgezYVEG2IWlQ372th7vl0PjJUC1O5yjffGFcNAzuv3ZAGSmHLiM9tTrQEaeM8BrCSr6vRbrZx5LbVg1owB79bbHY3/gtJMv74xHu/uWsLmx1E6sgfmjqtoRPRojfONbG3z3739QAeyNb8ZlaBMzB4S+t//qGu/7fAof2X+tWLI2YFdocvWnveUwvjUDspXnLPF6xrto62VHgS7Y1mv6kND6KlXvwTIzrDbWd/H2Gk/8Ievx+dvr8Y1uodRO6DIROABu7bF4e6PJ8t15n4MmY7P8agb3/DN6zO/NYTd/2TjJW1/d4Hf/7o8rwLzxzQ6a4zubTBL8/jJQ9Ubng9+bF5vc0glKQ+yoKMvaFqlX700dCT5rr64MOUJ70uPglTSJbc77bLI8lKvXpU0h5veWStUbnstSiY8Gk7LVAu3zz4X4XSBQ9XIiTQCQwnhWi5zCe3+poJLipjfa9MH7O5+BnnpSx2deJobPciK5991zvP+fxlj9Blh+7zzzICqAlxjMSNsLj3rmC4/Azra/Cs8hbsr2R3shvndrtoyr16W1nf3hIlD1RizQ3VgmOtsidrU599j7fqfnN+c+6y/JXppcuSVQtHgj2q7uaInmU39GV2v6g/nwnHjN+Z0Ot/4oHuZA86tlbBv6EMev9wYkGuLSZvYcnsMnP6Z19fvzNF48OvsKvAs29oKNZw2Iosd2RuCjfYj7OstxizTTFiDIq0Wi5Y0vOUkckMwYJCB+P8WBqHdYyjnS7+3dMxy98SC0wYY1SM5eAZ2NA+8vU25COW7d9XbWQnEHa9zwpr+Z+0sN5Nz7bD0qow8So8szo6cwd0T0GQCfR1h0/NvM/GUi+mUAX2TmzwL4rwEcAPiN6JH9U2b+2W3tAIB+4dAvQgxu6V3NljoY8A3BH862DjJSvp879POFglRb38Ab61PMzoCoAcg2n0kbam215xMDzanHwelQF7VwCXYUYnAr91aNyd0VPZrbm795mmJwi9suSSHau+e4cTdNegeeMevBaF2Kfy2ShG/1kPq8HrtJjYmAWRMGO2CwCWYAzC1lcVkmenO16WcbLF/dpN8ukh3RZZZCrfdwnnO9yLspXlkKHjyehY0uStQgLFNxqTrlvSTM76zx5BfXqT4gD3mIdhbM8MsWfnUA8e6q2Cw5sU3cOnSP7SPbGKc3E8uI4yGC9sHSuGwGjhNdjl7P+Z3Q3kHWjZojagd0SV1a2eRZA55Fqt7Ohw2bNsyDWTP6eNcCqyP19Nr8s+GEyH5GBJ63YTIjP9nYWMmnK1TArYO/FWPdldAp1EObPmUU6jzat09xEO2CtCF7VgUtr4QuEXOu9tL+LMJzsNcO4+c2b+LV69LaGz9r4B+P9kqAablaFdvr1j2cUABHLytlfUAbDGGsy0gjNKyHUr0Rb3U3w3itXmTx4lqvMhGajcfe62u9jgqZNsTjftHCz5shsK3k0/WzJsQiWw+yeJHHVlceIib33bCx2zeeMaeYoI41BsvmX9QQARseIOUoAsu2SWnDbHYCcQCbWFcyyy9ZOIRsAIubwaiPHlhJXt4EvuxgWTkoypJK5E8ytQWIRroAq3bptOvDPbRN2hRjl5VM/tzRZ1nGr11CmPlzAD5XHPsl8/knL12ZPIZykCmBX/E9FazUZ46V7GYDIgdK3tlRMoro0LEhEfaytXhgPXUErNtMEbb+i9jNxuKGr1yPMB6ychdsESIwurw7JubWFFhUWNCyuE8xkMX5tXapR8gaauS/aXkLZr0pI96t3lxbdquX55b1FrILuszeZwGq0llN3xl8N17SIdhIX+QeS++uhCtoeEG8vpJGDCal5YBpYp1Lj02Ntc2A7iwcQdOHhUwrpfdnFNgWcuW6FCeP3FtDYHIZeNHnYUGeZCOQ2NZNAC7cuhiuYBxDyPuA0nkj/m3jmNVSiI/lBJJCXRJGYhw8DQHsNPUYYCb4oudI8au3Kk2y+XZlUitlOw9LV6yEE3Z8HXuUV61LAJouEZwAq/ZDYxMtIFTnHWm5bBwR22TfA/luAavUC6RQHhH7aGoOOJj+Zb3C5aq0PVfAqhyP5XScHJuU2Puu/fwQegzVPVpdbg9X8D4YHcmJa2NPFcn79HvsNJpPzz5UYLjZgUyKstD68MfmtFUvrVFOBpQp1VOELGSbzKSNElohngoHDclQQCuhB8whR28TU4oxD9OllaxvNWE8bDqNRydbLj/Iecs5ELzMprHy/MFnhnpnR72xY+DXtMHG925r/7Z2loA8q3+b7IIeAQy8r0A9jCDGalnO+EFZFOcZ8GlBkZ5nQORgE1oZq2uv44vyUn8Eqho7vAWU2nPza/Pgd5HRunZElwA03jYDeBF8DnQQASH1XskUeECZDgWqGeVvvFYI0TIxrhJekPULrntoBZiatg/Y18TbCxQAIFSgYFrKy+/2MiW4tTallB3QpW7O6eIkwizJa7+LXmp51wGfYnXtpE7ETt488phes+JIwgJKFFYvJezKgmRAy2tbLSiPKcKyjU4SP+sNQDZjd7ai2xD8rIHrzOY7ymOUpSyTfSHLB4kr1+UA1DpAX7zSdtpOU9LiAvl7XfPaGqDMdrU71q00vTVAWfP+bvss363e5bAd/3QCjdQumcjYekrQnt03rl6PUbaC3N/68n95iTn0JBcJgVMIxhXJ//6b/9Gkyx9QdkGPAPDb//d/PunyB5Rd0eXv/O5/OunyB5Rd0OVv/1//2aTHRyC7oMsv/G//8aTLH1B2QY8i2z25kzwaYdQD9Cf54ZJJj9dHJl1eH5l0eX1k0uX1kB3S4wRy3xPh7RvTJvkhkUmP10cmXV4fmXR5fWTS5fWQ3dHjBHLfC9mh+JRJfgCZ9Hh9ZNLl9ZFJl9dHJl1eD9khPU4g970QRs5OM8kPp0x6vD4y6fL6yKTL6yOTLq+H7JAeJ5D7nsjuuO4n+UFk0uP1kUmX10cmXV4fmXR5PWR39DiB3PdCGEOe90l++GTS4/WRSZfXRyZdXh+ZdHk9ZIf0OIHc90KYga676lZM8oPKpMfrI5Mur49Murw+MunyesgO6XECue+V7IjrfpIfUCY9Xh+ZdHl9ZNLl9ZFJl9dDdkSPE8h9L4QZ6HcjCHuSH0AmPV4fmXR5fWTS5fWRSZfXQ3ZIjxPIfU+EA13wJD/kMunx+siky+sjky6vj0y6vB6yO3qcQO57IQzwjsxqJvkBZNLj9ZFJl9dHJl1eH5l0eT1kh/TorroB/78QCcK2/y4hRPQzRPTHRPQ1IvrFyu8LIvqf4u+/R0TPP+KWT2KlpsdL6HLS4w7KpMvrI5N9vT4y6fJ6yEPaV+DR63ICue+JMLjvs38XCRE1AH4FwF8C8EkAf5mIPlkU+6sA3mbmjwD4bwH8jUfc8EkyGerxIl1OetxVmXR5fWSyr9dHJl1eD3nn9hV4d3Q5gdz3QhghCNv+u1h+AsDXmPkbzLwG8OsAfq4o83MA/k78/A8B/EUiokfV7EkKqenxYl1OetxFmXR5fWSyr9dHJl1eD3k4+wq8C7qcQO57IMwMv+myf5eQpwF8x3x/OR6rlmHmDsBdALcfQZMnqUhNj5fQ5aTHHZRJl9dHJvt6fWTS5fWQh7SvwLugy2nj2Xsg9/H253/H/4PHi8NLIvqi+f6rzPyr72W7JnlnMqJHYNLlD51Murw+MtnX6yOTLq+H7JJ9nUDueyDM/DMPcdorAJ4135+Jx2plXiaiFsANAG8+VCMnuVAmPV4fmXR5fWTS5fWRSZfXQx5Sj8C7oMspXGF35fcBfJSIXiCiOYCfB/DZosxnAfwb8fO/AuB/ZWZ+D9s4ycUy6fH6yKTL6yOTLq+PTLq8PvLIdTl5cndUmLkjos8A+DyABsDfZuYvE9EvA/giM38WwN8C8PeI6GsA3kJ4ISbZIZn0eH1k0uX1kUmX10cmXV4feTd0SdNkZpJJJplkkkkmmWSS6yZTuMIkk0wyySSTTDLJJNdOJpA7ySSTTDLJJJNMMsm1kwnkTjLJJJNMMskkk0xy7WQCuZNMMskkk0wyySSTXDuZQO4kk0wyySSTTDLJJNdOJpA7ySSTTDLJJJNMMsm1kwnkTjLJJJNMMskkk0xy7WQCuZNMMskkk0wyySSTXDv5/wDJWaEyZXxHhQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Endmembers alignment\n",
        "\n",
        "---\n",
        "\n",
        "At this stage we need to align the endmembers and the abundances to compute the RMSE and SAD metrics."
      ],
      "metadata": {
        "id": "4959l5EXctIe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Select a criterion to perform alignment\n",
        "criterion = MSE()\n",
        "\n",
        "# Select an aligner to perform alignment\n",
        "aligner = Aligner(hsi=hsi, criterion=criterion)\n",
        "\n",
        "A1 = aligner.fit_transform(A0)\n",
        "E1 = aligner.transform_endmembers(E0)\n",
        "\n",
        "# Plot alignment\n",
        "hsi.plot_endmembers(E0=E1)\n",
        "hsi.plot_abundances(A0=A1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 631
        },
        "id": "VPtAyShNbEkT",
        "outputId": "7c35f18a-9592-4f3c-c155-c32ab5614619"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 12 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Quantitative results\n",
        "\n",
        "---\n",
        "\n",
        "We are now in shape to compute the abundances RMSE and endmembers SAD."
      ],
      "metadata": {
        "id": "PKiN4CjMc-rq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Instantiate metrics\n",
        "rmse = RMSE()\n",
        "sad = SAD()\n",
        "sre = SRE()\n",
        "\n",
        "# Compute final numbers\n",
        "print(f\"RMSE => {rmse(hsi.A, A1):.2f}\")\n",
        "print(f\"SAD => {sad(hsi.E, E1):.2f}\")\n",
        "print(f\"SRE => {sre(A1, hsi.A):.2f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SlgRqCN4dH0w",
        "outputId": "64bf7c27-4262-4b83-c253-0bb21d49899f"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "RMSE => 6.10\n",
            "SAD => 6.63\n",
            "SRE => 9.66\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Results for each Material"
      ],
      "metadata": {
        "id": "_vkAtybYvlBj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Change the following line if you change dataset!\n",
        "# Either comment out or describe each material name.\n",
        "hsi.labels = [\"Road\", \"Tree\", \"Roof\", \"Water\"]\n",
        "assert len(hsi.labels) == hsi.p\n",
        "\n",
        "for ii, label in enumerate(hsi.labels):\n",
        "    a, ahat = hsi.A[ii], A1[ii]\n",
        "    print(f\"RMSE ({label}) => {rmse(a, ahat):.2f}\")\n",
        "\n",
        "print(\"-\" * 15)\n",
        "\n",
        "for ii, label in enumerate(hsi.labels):\n",
        "    e, ehat = hsi.E[:, ii][:, None], E1[:, ii][:, None]\n",
        "    print(f\"SAD ({label}) => {sad(e, ehat):.2f}\")"
      ],
      "metadata": {
        "id": "dtwBVUxEvjZd",
        "outputId": "bee08538-2a8f-4c0b-eecb-cce5979f4824",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "RMSE (Road) => 17.41\n",
            "RMSE (Tree) => 21.55\n",
            "RMSE (Roof) => 26.79\n",
            "RMSE (Water) => 42.65\n",
            "---------------\n",
            "SAD (Road) => 5.20\n",
            "SAD (Tree) => 7.67\n",
            "SAD (Roof) => 3.94\n",
            "SAD (Water) => 28.88\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "vSzpevufvjIw"
      }
    }
  ]
}