example_notebooks/Accessing_Ivy_Glioblastoma_Atlas_Project_Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5ce25ec8",
   "metadata": {},
   "source": [
    "# Accessing Ivy Glioblastoma Atlas Project data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4580c9a",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "The Ivy Glioblastoma Atlas Project is a collection of data from glioblastoma brain tumors. The project is a collaboration between the Allen Institute for Brain Science and the Ben and Catherine Ivy Foundation. Glioblastoma is an aggressive brain cancer. Survival after diagnosis is just 12 to 15 months. An interactive atlas is available at https://glioblastoma.alleninstitute.org/ and consists of:\n",
    "\n",
    "- Images of in situ hybridization experiments identifying where key genes are expressed in the tumor tissue (20x magnification)\n",
    "- Matching histology images using Hematoxylin and Eosin (H&E) stain\n",
    "- Gene expression masks for all ISH images\n",
    "- Annotated mask images of tumor structures for all ISH and H&E images\n",
    "\n",
    "The project also comprises additional data modalities that are not currently available from the AWS bucket. These are:\n",
    "\n",
    "- RNA sequencing data for 270 samples from 44 tumors\n",
    "- Companion clinical database hosted at https://ivygap.org/ (registration required)\n",
    "- Accompanying MRI/CT scan data for the patients is available at [The Cancer Imaging Archive](https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=22515597).\n",
    "\n",
    "The project has been published in the [May 11, 2018 edition of Science](https://science.sciencemag.org/content/360/6389/660)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcd3a346",
   "metadata": {},
   "source": [
    "## Accessing Ivy Glioblastoma Atlas Project data with AWS S3\n",
    "\n",
    "The image data for the project is being made available as an Amazon Web Services (AWS) public dataset to enable computational scientists easy access to a rich, well-annotated data set for training and validation of machine learning, classification, and developing computer vision applications such as image segmentation. The data are free and publicly available from the AWS Simple Storage Service (S3) s3://allen-ivy-glioblastoma-atlas/ and/or https://console.aws.amazon.com/s3/buckets/allen-ivy-glioblastoma-atlas (needs at least an AWS free account to view).\n",
    "\n",
    "The root of the S3 bucket contains 3 metadata \\*.json files (`donor_metadata.json`, `specimen_metadata.json`, and `section_metadata.json`) that can be used to explore the dataset and determine download links. \n",
    "\n",
    "The relationship between donors, specimens, and sections is as follows:\n",
    "- Each donor can have one or more (tumor tissue) specimens\n",
    "- Each (tumor tissue) specimen can be sliced into multiple sections\n",
    "- Each section can have multiple sub-images that show histology, gene expression, annotated masks, etc...\n",
    "\n",
    "The dataset is comprised of 42 donors, 946 tumor specimens, 20470 sliced tissue sections, and a total of 135138 microscopy/expression/annotation images. The total size of this dataset is ~8.5 Terabytes. The following sections will show some examples of how to obtain and interact with metadata as well as microscopy image data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bf00ee7",
   "metadata": {},
   "source": [
    "## Exploring donor metadata\n",
    "\n",
    "Let's start by looking at the donors for the dataset. Before that, we need to set up a client that will access the AWS S3 dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a4c747f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from open_dataset_tools.aws_utils import get_public_boto3_client\n",
    "\n",
    "\n",
    "# Set up a boto3 client that can access public S3 data without needing AWS credentials\n",
    "s3_client = get_public_boto3_client()\n",
    "\n",
    "# If you have already set up and would like to use AWS credentials you could do:\n",
    "#\n",
    "# import boto3\n",
    "# s3_client = boto3.client('s3')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "138e0acd",
   "metadata": {},
   "source": [
    "Let's also import some useful utility functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8a52e773",
   "metadata": {},
   "outputs": [],
   "source": [
    "from open_dataset_tools.ivy_gap_utils import get_donor_metadata, get_specimen_metadata, get_section_metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9ceb06f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "donor_metadata = get_donor_metadata(s3_client)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "97ba579e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age_in_years</th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>egfr_amplification</th>\n",
       "      <th>extent_of_resection</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>initial_kps</th>\n",
       "      <th>mgmt_methylation</th>\n",
       "      <th>molecular_subtypes</th>\n",
       "      <th>surgery</th>\n",
       "      <th>survival_days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>66</td>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Classical]</td>\n",
       "      <td>primary</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>64</td>\n",
       "      <td>10926</td>\n",
       "      <td>H366-0013</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W2-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1096.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>59</td>\n",
       "      <td>113597455</td>\n",
       "      <td>H366-0049</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W42-1-1</td>\n",
       "      <td>70</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Neural, Proneural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>61</td>\n",
       "      <td>113597961</td>\n",
       "      <td>H366-0050</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W43-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>No</td>\n",
       "      <td>[Mesenchymal, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65</td>\n",
       "      <td>12102</td>\n",
       "      <td>H366-0018</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W3-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Classical, Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>982.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age_in_years   donor_id  donor_name egfr_amplification extent_of_resection  \\\n",
       "0            66      10865  H366-0012b                Yes            Complete   \n",
       "1            64      10926   H366-0013                Yes            Complete   \n",
       "2            59  113597455   H366-0049               None            Complete   \n",
       "3            61  113597961   H366-0050               None            Complete   \n",
       "4            65      12102   H366-0018                Yes            Complete   \n",
       "\n",
       "  external_donor_name  initial_kps mgmt_methylation        molecular_subtypes  \\\n",
       "0              W1-1-2          100               No               [Classical]   \n",
       "1              W2-1-1           90              Yes       [Classical, Neural]   \n",
       "2             W42-1-1           70              Yes       [Neural, Proneural]   \n",
       "3             W43-1-1           90               No     [Mesenchymal, Neural]   \n",
       "4              W3-1-1          100               No  [Classical, Mesenchymal]   \n",
       "\n",
       "   surgery  survival_days  \n",
       "0  primary          105.0  \n",
       "1  primary         1096.0  \n",
       "2  primary          197.0  \n",
       "3  primary          300.0  \n",
       "4  primary          982.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donor_metadata.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "557628d5",
   "metadata": {},
   "source": [
    "The donor metadata table contains metadata pertaining to donors of glioblastoma specimens in the data. For detailed descriptions of the column names please refer to the `CLINICAL DATA CATEGORIES` section on page 11 of the `Overview` PDF found in the [Ivy GAP documentation page](https://help.brain-map.org/display/glioblastoma/Documentation).\n",
    "\n",
    "\n",
    "For now, let's see how many donors there are in the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "40eaa296",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 42 donors in the Ivy GAP dataset\n"
     ]
    }
   ],
   "source": [
    "print(f\"There are {len(donor_metadata)} donors in the Ivy GAP dataset\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5b2a8c0",
   "metadata": {},
   "source": [
    "When analyzing data, we may want to limit our analysis to donors with certain conditions. Let's try finding donors who had no evidence of disease as indicated by initial Karnofsky Performance Status (KPS)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d091cbf4",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age_in_years</th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>egfr_amplification</th>\n",
       "      <th>extent_of_resection</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>initial_kps</th>\n",
       "      <th>mgmt_methylation</th>\n",
       "      <th>molecular_subtypes</th>\n",
       "      <th>surgery</th>\n",
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       "      <th>0</th>\n",
       "      <td>66</td>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Classical]</td>\n",
       "      <td>primary</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>65</td>\n",
       "      <td>12102</td>\n",
       "      <td>H366-0018</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W3-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Classical, Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>982.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "      <td>12105</td>\n",
       "      <td>H366-0022</td>\n",
       "      <td>No</td>\n",
       "      <td>Sub-total</td>\n",
       "      <td>W7-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>437.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>44</td>\n",
       "      <td>12111</td>\n",
       "      <td>H366-0025</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W10-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Proneural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>57</td>\n",
       "      <td>12112</td>\n",
       "      <td>H366-0026</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W11-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical, Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1076.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>76</td>\n",
       "      <td>12996</td>\n",
       "      <td>H366-0033</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W16-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Neural, Proneural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>353.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>57</td>\n",
       "      <td>13988</td>\n",
       "      <td>H366-0036</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W26-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1293.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>68</td>\n",
       "      <td>14220</td>\n",
       "      <td>H366-0037</td>\n",
       "      <td>None</td>\n",
       "      <td>Sub-total</td>\n",
       "      <td>W28-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Mesenchymal, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>73</td>\n",
       "      <td>14221</td>\n",
       "      <td>H366-0038</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W29-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Classical, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>260.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>64</td>\n",
       "      <td>15400</td>\n",
       "      <td>H366-0047</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W40-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>No</td>\n",
       "      <td>[Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>36</td>\n",
       "      <td>292023102</td>\n",
       "      <td>H366-0065</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W35-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>52</td>\n",
       "      <td>292023109</td>\n",
       "      <td>H366-0066</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W55-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age_in_years   donor_id  donor_name egfr_amplification  \\\n",
       "0             66      10865  H366-0012b                Yes   \n",
       "4             65      12102   H366-0018                Yes   \n",
       "5             60      12105   H366-0022                 No   \n",
       "11            44      12111   H366-0025                 No   \n",
       "12            57      12112   H366-0026                 No   \n",
       "16            76      12996   H366-0033                Yes   \n",
       "18            57      13988   H366-0036               None   \n",
       "19            68      14220   H366-0037               None   \n",
       "20            73      14221   H366-0038                Yes   \n",
       "29            64      15400   H366-0047                Yes   \n",
       "40            36  292023102   H366-0065                 No   \n",
       "41            52  292023109   H366-0066               None   \n",
       "\n",
       "   extent_of_resection external_donor_name  initial_kps mgmt_methylation  \\\n",
       "0             Complete              W1-1-2          100               No   \n",
       "4             Complete              W3-1-1          100               No   \n",
       "5            Sub-total              W7-1-1          100              Yes   \n",
       "11            Complete             W10-1-1          100              Yes   \n",
       "12            Complete             W11-1-1          100              Yes   \n",
       "16            Complete             W16-1-1          100               No   \n",
       "18            Complete             W26-1-1          100              Yes   \n",
       "19           Sub-total             W28-1-1          100               No   \n",
       "20            Complete             W29-1-1          100               No   \n",
       "29            Complete             W40-1-1          100               No   \n",
       "40            Complete             W35-1-1          100              Yes   \n",
       "41            Complete             W55-1-1          100              Yes   \n",
       "\n",
       "          molecular_subtypes  surgery  survival_days  \n",
       "0                [Classical]  primary          105.0  \n",
       "4   [Classical, Mesenchymal]  primary          982.0  \n",
       "5              [Mesenchymal]  primary          437.0  \n",
       "11               [Proneural]  primary            NaN  \n",
       "12  [Classical, Mesenchymal]  primary         1076.0  \n",
       "16       [Neural, Proneural]  primary          353.0  \n",
       "18                  [Neural]  primary         1293.0  \n",
       "19     [Mesenchymal, Neural]  primary          300.0  \n",
       "20       [Classical, Neural]  primary          260.0  \n",
       "29                  [Neural]  primary          184.0  \n",
       "40                        []  primary            NaN  \n",
       "41               [Classical]  primary            NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donor_kps_filter = donor_metadata[\"initial_kps\"] == 100\n",
    "donor_metadata[donor_kps_filter]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a754e960",
   "metadata": {},
   "source": [
    "One might want to filter on multiple conditions such as donors with minimal evidence of disease (KPS >= 90) and who had tumors where the O-6-methylguanine-DNA methyltransferase DNA repair gene was methylated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "39998a09",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age_in_years</th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>egfr_amplification</th>\n",
       "      <th>extent_of_resection</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>initial_kps</th>\n",
       "      <th>mgmt_methylation</th>\n",
       "      <th>molecular_subtypes</th>\n",
       "      <th>surgery</th>\n",
       "      <th>survival_days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>64</td>\n",
       "      <td>10926</td>\n",
       "      <td>H366-0013</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W2-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1096.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "      <td>12105</td>\n",
       "      <td>H366-0022</td>\n",
       "      <td>No</td>\n",
       "      <td>Sub-total</td>\n",
       "      <td>W7-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>437.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>44</td>\n",
       "      <td>12111</td>\n",
       "      <td>H366-0025</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W10-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Proneural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>57</td>\n",
       "      <td>12112</td>\n",
       "      <td>H366-0026</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W11-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical, Mesenchymal]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1076.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>52</td>\n",
       "      <td>12997</td>\n",
       "      <td>H366-0035</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W22-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical, Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>57</td>\n",
       "      <td>13988</td>\n",
       "      <td>H366-0036</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W26-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Neural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>1293.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>56</td>\n",
       "      <td>14737</td>\n",
       "      <td>H366-0041</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W32-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Proneural]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>36</td>\n",
       "      <td>159992499</td>\n",
       "      <td>H366-0053</td>\n",
       "      <td>No</td>\n",
       "      <td>Sub-total</td>\n",
       "      <td>W18-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[]</td>\n",
       "      <td>primary</td>\n",
       "      <td>903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>26</td>\n",
       "      <td>180682564</td>\n",
       "      <td>H366-0059</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W50-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>54</td>\n",
       "      <td>268091642</td>\n",
       "      <td>H366-0061</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W53-1-1</td>\n",
       "      <td>90</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>36</td>\n",
       "      <td>292023102</td>\n",
       "      <td>H366-0065</td>\n",
       "      <td>No</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W35-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>52</td>\n",
       "      <td>292023109</td>\n",
       "      <td>H366-0066</td>\n",
       "      <td>None</td>\n",
       "      <td>Complete</td>\n",
       "      <td>W55-1-1</td>\n",
       "      <td>100</td>\n",
       "      <td>Yes</td>\n",
       "      <td>[Classical]</td>\n",
       "      <td>primary</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age_in_years   donor_id donor_name egfr_amplification extent_of_resection  \\\n",
       "1             64      10926  H366-0013                Yes            Complete   \n",
       "5             60      12105  H366-0022                 No           Sub-total   \n",
       "11            44      12111  H366-0025                 No            Complete   \n",
       "12            57      12112  H366-0026                 No            Complete   \n",
       "17            52      12997  H366-0035                Yes            Complete   \n",
       "18            57      13988  H366-0036               None            Complete   \n",
       "23            56      14737  H366-0041                 No            Complete   \n",
       "31            36  159992499  H366-0053                 No           Sub-total   \n",
       "34            26  180682564  H366-0059               None            Complete   \n",
       "35            54  268091642  H366-0061               None            Complete   \n",
       "40            36  292023102  H366-0065                 No            Complete   \n",
       "41            52  292023109  H366-0066               None            Complete   \n",
       "\n",
       "   external_donor_name  initial_kps mgmt_methylation  \\\n",
       "1               W2-1-1           90              Yes   \n",
       "5               W7-1-1          100              Yes   \n",
       "11             W10-1-1          100              Yes   \n",
       "12             W11-1-1          100              Yes   \n",
       "17             W22-1-1           90              Yes   \n",
       "18             W26-1-1          100              Yes   \n",
       "23             W32-1-1           90              Yes   \n",
       "31             W18-1-1           90              Yes   \n",
       "34             W50-1-1           90              Yes   \n",
       "35             W53-1-1           90              Yes   \n",
       "40             W35-1-1          100              Yes   \n",
       "41             W55-1-1          100              Yes   \n",
       "\n",
       "          molecular_subtypes  surgery  survival_days  \n",
       "1        [Classical, Neural]  primary         1096.0  \n",
       "5              [Mesenchymal]  primary          437.0  \n",
       "11               [Proneural]  primary            NaN  \n",
       "12  [Classical, Mesenchymal]  primary         1076.0  \n",
       "17       [Classical, Neural]  primary            NaN  \n",
       "18                  [Neural]  primary         1293.0  \n",
       "23               [Proneural]  primary            NaN  \n",
       "31                        []  primary          903.0  \n",
       "34                        []  primary            NaN  \n",
       "35               [Classical]  primary            NaN  \n",
       "40                        []  primary            NaN  \n",
       "41               [Classical]  primary            NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donor_compound_filter = (donor_metadata[\"initial_kps\"] >= 90) & (donor_metadata[\"mgmt_methylation\"] == \"Yes\")\n",
    "donor_metadata[donor_compound_filter]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc0c74b2",
   "metadata": {},
   "source": [
    "If we just want the donor ids for our previous query we can just do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6d91fc2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    10926,     12105,     12111,     12112,     12997,     13988,\n",
       "           14737, 159992499, 180682564, 268091642, 292023102, 292023109])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donor_metadata[donor_compound_filter]['donor_id'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e38a9de0",
   "metadata": {},
   "source": [
    "## Exploring specimen metadata\n",
    "\n",
    "The specimen metadata table describes tumor specimens and information about the donor source, study, as well as a specimen page link where more information about the specimen can be obtained.\n",
    "\n",
    "For now, let's take a look at how many specimens exist in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2bd3127b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>specimen_name</th>\n",
       "      <th>specimen_page_link</th>\n",
       "      <th>study_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>264712561</td>\n",
       "      <td>W1-1-2-AB.2.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>264712748</td>\n",
       "      <td>W1-1-2-AB.2.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>264712751</td>\n",
       "      <td>W1-1-2-AB.2.03</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>264713700</td>\n",
       "      <td>W1-1-2-K.2.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>264713760</td>\n",
       "      <td>W1-1-2-K.2.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   donor_id  donor_name external_donor_name  specimen_id   specimen_name  \\\n",
       "0     10865  H366-0012b              W1-1-2    264712561  W1-1-2-AB.2.01   \n",
       "1     10865  H366-0012b              W1-1-2    264712748  W1-1-2-AB.2.02   \n",
       "2     10865  H366-0012b              W1-1-2    264712751  W1-1-2-AB.2.03   \n",
       "3     10865  H366-0012b              W1-1-2    264713700   W1-1-2-K.2.01   \n",
       "4     10865  H366-0012b              W1-1-2    264713760   W1-1-2-K.2.02   \n",
       "\n",
       "                                  specimen_page_link  \\\n",
       "0  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "1  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "2  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "3  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "4  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "\n",
       "                     study_name  \n",
       "0  Cancer Stem Cells ISH Survey  \n",
       "1  Cancer Stem Cells ISH Survey  \n",
       "2  Cancer Stem Cells ISH Survey  \n",
       "3  Cancer Stem Cells ISH Survey  \n",
       "4  Cancer Stem Cells ISH Survey  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "specimen_metadata = get_specimen_metadata(s3_client)\n",
    "specimen_metadata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e99cfc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 946 tumor specimens in the Ivy GAP dataset\n"
     ]
    }
   ],
   "source": [
    "print(f\"There are {len(specimen_metadata)} tumor specimens in the Ivy GAP dataset\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9a435b5",
   "metadata": {},
   "source": [
    "Let's take a look at the studies associated with all the specimens:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f107f806",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Cancer Stem Cells ISH Survey', 'Anatomic Structures RNA Seq',\n",
       "       'Cancer Stem Cells RNA Seq',\n",
       "       'Anatomic Structures ISH for Enriched Genes',\n",
       "       'Cancer Stem Cells ISH for Enriched Genes',\n",
       "       'Anatomic Structures ISH Survey'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "specimen_metadata[\"study_name\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adeb1927",
   "metadata": {},
   "source": [
    "If we are interested in specimens from a specific study, for example, the \"Anatomic Structures ISH Survey\" we can filter the table like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a6349015",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>specimen_name</th>\n",
       "      <th>specimen_page_link</th>\n",
       "      <th>study_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>706600</td>\n",
       "      <td>W1-1-2-K.1.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>706601</td>\n",
       "      <td>W1-1-2-K.1.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>706602</td>\n",
       "      <td>W1-1-2-K.1.03</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>706603</td>\n",
       "      <td>W1-1-2-K.1.04</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>10865</td>\n",
       "      <td>H366-0012b</td>\n",
       "      <td>W1-1-2</td>\n",
       "      <td>706604</td>\n",
       "      <td>W1-1-2-K.1.05</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>12165</td>\n",
       "      <td>H366-0029</td>\n",
       "      <td>W12-1-1</td>\n",
       "      <td>706864</td>\n",
       "      <td>W12-1-1-D.2.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>12165</td>\n",
       "      <td>H366-0029</td>\n",
       "      <td>W12-1-1</td>\n",
       "      <td>706873</td>\n",
       "      <td>W12-1-1-E.1.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>12165</td>\n",
       "      <td>H366-0029</td>\n",
       "      <td>W12-1-1</td>\n",
       "      <td>706874</td>\n",
       "      <td>W12-1-1-E.1.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>12165</td>\n",
       "      <td>H366-0029</td>\n",
       "      <td>W12-1-1</td>\n",
       "      <td>706875</td>\n",
       "      <td>W12-1-1-E.1.03</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>12165</td>\n",
       "      <td>H366-0029</td>\n",
       "      <td>W12-1-1</td>\n",
       "      <td>706876</td>\n",
       "      <td>W12-1-1-E.1.04</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Anatomic Structures ISH Survey</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     donor_id  donor_name external_donor_name  specimen_id   specimen_name  \\\n",
       "32      10865  H366-0012b              W1-1-2       706600   W1-1-2-K.1.01   \n",
       "33      10865  H366-0012b              W1-1-2       706601   W1-1-2-K.1.02   \n",
       "34      10865  H366-0012b              W1-1-2       706602   W1-1-2-K.1.03   \n",
       "35      10865  H366-0012b              W1-1-2       706603   W1-1-2-K.1.04   \n",
       "36      10865  H366-0012b              W1-1-2       706604   W1-1-2-K.1.05   \n",
       "..        ...         ...                 ...          ...             ...   \n",
       "418     12165   H366-0029             W12-1-1       706864  W12-1-1-D.2.02   \n",
       "422     12165   H366-0029             W12-1-1       706873  W12-1-1-E.1.01   \n",
       "423     12165   H366-0029             W12-1-1       706874  W12-1-1-E.1.02   \n",
       "424     12165   H366-0029             W12-1-1       706875  W12-1-1-E.1.03   \n",
       "425     12165   H366-0029             W12-1-1       706876  W12-1-1-E.1.04   \n",
       "\n",
       "                                    specimen_page_link  \\\n",
       "32   http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "33   http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "34   http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "35   http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "36   http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "..                                                 ...   \n",
       "418  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "422  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "423  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "424  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "425  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "\n",
       "                         study_name  \n",
       "32   Anatomic Structures ISH Survey  \n",
       "33   Anatomic Structures ISH Survey  \n",
       "34   Anatomic Structures ISH Survey  \n",
       "35   Anatomic Structures ISH Survey  \n",
       "36   Anatomic Structures ISH Survey  \n",
       "..                              ...  \n",
       "418  Anatomic Structures ISH Survey  \n",
       "422  Anatomic Structures ISH Survey  \n",
       "423  Anatomic Structures ISH Survey  \n",
       "424  Anatomic Structures ISH Survey  \n",
       "425  Anatomic Structures ISH Survey  \n",
       "\n",
       "[96 rows x 7 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "specimen_study_filter = specimen_metadata[\"study_name\"] == \"Anatomic Structures ISH Survey\"\n",
    "specimen_metadata[specimen_study_filter]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f100d9e",
   "metadata": {},
   "source": [
    "There may be analyses where one only wants to look at specimens from donors with certain criteria. Here is an example of finding specimens from the \"Cancer Stem Cells ISH for Enriched Genes\" study from donors with low initial KPS values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d326a687",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>specimen_name</th>\n",
       "      <th>specimen_page_link</th>\n",
       "      <th>study_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>15350</td>\n",
       "      <td>H366-0046</td>\n",
       "      <td>W39-1-1</td>\n",
       "      <td>293591387</td>\n",
       "      <td>W39-1-1-O.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>15350</td>\n",
       "      <td>H366-0046</td>\n",
       "      <td>W39-1-1</td>\n",
       "      <td>293591503</td>\n",
       "      <td>W39-1-1-O.02</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     donor_id donor_name external_donor_name  specimen_id specimen_name  \\\n",
       "728     15350  H366-0046             W39-1-1    293591387  W39-1-1-O.01   \n",
       "729     15350  H366-0046             W39-1-1    293591503  W39-1-1-O.02   \n",
       "\n",
       "                                    specimen_page_link  \\\n",
       "728  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "729  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "\n",
       "                       study_name  \n",
       "728  Cancer Stem Cells ISH Survey  \n",
       "729  Cancer Stem Cells ISH Survey  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "donor_kps_filter = donor_metadata[\"initial_kps\"] < 70\n",
    "selected_donor_ids = donor_metadata[donor_kps_filter][\"donor_id\"].values\n",
    "\n",
    "specimen_study_and_donor_kps_filter = (\n",
    "    (specimen_metadata[\"study_name\"] == \"Cancer Stem Cells ISH Survey\")\n",
    "    & (specimen_metadata[\"donor_id\"].isin(selected_donor_ids))\n",
    ")\n",
    "specimen_metadata[specimen_study_and_donor_kps_filter]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83fb5d06",
   "metadata": {},
   "source": [
    "## Exploring section metadata and interacting with images\n",
    "\n",
    "The section metadata table includes information about sliced tissues sections obtained from specimens including primer sequence data used for in situ hybridization experiments.\n",
    "\n",
    "As before, let's take a look at how many tissues sections there are in the dataset.\n",
    "\n",
    "NOTE: The section metadata table is ~56 MB, so may take a little time to download and load."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c18764b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>entrez_id</th>\n",
       "      <th>forward_primer_sequence_data</th>\n",
       "      <th>forward_sequence_length</th>\n",
       "      <th>gene_acronym</th>\n",
       "      <th>gi</th>\n",
       "      <th>ncbi_accession_number</th>\n",
       "      <th>orientation</th>\n",
       "      <th>predicted_sequence_data</th>\n",
       "      <th>predicted_sequence_length</th>\n",
       "      <th>reverse_primer_sequence_data</th>\n",
       "      <th>reverse_sequence_length</th>\n",
       "      <th>section_data_set_id</th>\n",
       "      <th>section_thickness</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>sub_images</th>\n",
       "      <th>treatment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10865</td>\n",
       "      <td>2064.0</td>\n",
       "      <td>CAGTTACCAGTGCCAATATCCA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ERBB2</td>\n",
       "      <td>51480411.0</td>\n",
       "      <td>BC080193.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CAGTTACCAGTGCCAATATCCAGGAGTTTGCTGGCTGCAAGAAGAT...</td>\n",
       "      <td>974.0</td>\n",
       "      <td>ATCGTGTACTTCCGGATCTTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>265850294</td>\n",
       "      <td>20</td>\n",
       "      <td>264712561</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 265...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10865</td>\n",
       "      <td>2034.0</td>\n",
       "      <td>CACATCTTTGGATAACGACCTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>EPAS1</td>\n",
       "      <td>262527236.0</td>\n",
       "      <td>NM_001430.4</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CACATCTTTGGATAACGACCTGAAGATTGAAGTGATTGAGAAGCTC...</td>\n",
       "      <td>931.0</td>\n",
       "      <td>GAACCTGCTCTTGCTGTTCTC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>265850345</td>\n",
       "      <td>20</td>\n",
       "      <td>264712561</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 265...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10865</td>\n",
       "      <td>1749.0</td>\n",
       "      <td>AAAGCTCTCAACCCCTACCAGT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>DLX5</td>\n",
       "      <td>84043959.0</td>\n",
       "      <td>NM_005221.5</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AAAGCTCTCAACCCCTACCAGTATCAGTATCACGGCGTGAACGGCT...</td>\n",
       "      <td>767.0</td>\n",
       "      <td>AGTTTTCCGAACTTCCCCATA</td>\n",
       "      <td>21.0</td>\n",
       "      <td>265850396</td>\n",
       "      <td>20</td>\n",
       "      <td>264712561</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 265...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10865</td>\n",
       "      <td>57291.0</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>DANCR</td>\n",
       "      <td>194394211.0</td>\n",
       "      <td>NR_024031.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...</td>\n",
       "      <td>512.0</td>\n",
       "      <td>ATAGCGCCTAGATAACGGTTCA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>265850447</td>\n",
       "      <td>20</td>\n",
       "      <td>264712561</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 265...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10865</td>\n",
       "      <td>1490.0</td>\n",
       "      <td>CTTACCGACTGGAAGACACGTT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>CTGF</td>\n",
       "      <td>98986335.0</td>\n",
       "      <td>NM_001901.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTTACCGACTGGAAGACACGTTTGGCCCAGACCCAACTATGATTAG...</td>\n",
       "      <td>953.0</td>\n",
       "      <td>CTTGACTCAGTCTCTTGATGGCT</td>\n",
       "      <td>23.0</td>\n",
       "      <td>265850498</td>\n",
       "      <td>20</td>\n",
       "      <td>264712561</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 265...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   donor_id  entrez_id forward_primer_sequence_data  forward_sequence_length  \\\n",
       "0     10865     2064.0       CAGTTACCAGTGCCAATATCCA                     22.0   \n",
       "1     10865     2034.0       CACATCTTTGGATAACGACCTG                     22.0   \n",
       "2     10865     1749.0       AAAGCTCTCAACCCCTACCAGT                     22.0   \n",
       "3     10865    57291.0        CTCTTTGTCAGCTGGAGTTGC                     21.0   \n",
       "4     10865     1490.0       CTTACCGACTGGAAGACACGTT                     22.0   \n",
       "\n",
       "  gene_acronym           gi ncbi_accession_number orientation  \\\n",
       "0        ERBB2   51480411.0            BC080193.1   Antisense   \n",
       "1        EPAS1  262527236.0           NM_001430.4   Antisense   \n",
       "2         DLX5   84043959.0           NM_005221.5   Antisense   \n",
       "3        DANCR  194394211.0           NR_024031.1   Antisense   \n",
       "4         CTGF   98986335.0           NM_001901.2   Antisense   \n",
       "\n",
       "                             predicted_sequence_data  \\\n",
       "0  CAGTTACCAGTGCCAATATCCAGGAGTTTGCTGGCTGCAAGAAGAT...   \n",
       "1  CACATCTTTGGATAACGACCTGAAGATTGAAGTGATTGAGAAGCTC...   \n",
       "2  AAAGCTCTCAACCCCTACCAGTATCAGTATCACGGCGTGAACGGCT...   \n",
       "3  CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...   \n",
       "4  CTTACCGACTGGAAGACACGTTTGGCCCAGACCCAACTATGATTAG...   \n",
       "\n",
       "   predicted_sequence_length reverse_primer_sequence_data  \\\n",
       "0                      974.0       ATCGTGTACTTCCGGATCTTCT   \n",
       "1                      931.0        GAACCTGCTCTTGCTGTTCTC   \n",
       "2                      767.0        AGTTTTCCGAACTTCCCCATA   \n",
       "3                      512.0       ATAGCGCCTAGATAACGGTTCA   \n",
       "4                      953.0      CTTGACTCAGTCTCTTGATGGCT   \n",
       "\n",
       "   reverse_sequence_length  section_data_set_id  section_thickness  \\\n",
       "0                     22.0            265850294                 20   \n",
       "1                     21.0            265850345                 20   \n",
       "2                     21.0            265850396                 20   \n",
       "3                     22.0            265850447                 20   \n",
       "4                     23.0            265850498                 20   \n",
       "\n",
       "   specimen_id                                         sub_images treatment  \n",
       "0    264712561  [{'bits_per_component': 8, 'sub_image_id': 265...       ISH  \n",
       "1    264712561  [{'bits_per_component': 8, 'sub_image_id': 265...       ISH  \n",
       "2    264712561  [{'bits_per_component': 8, 'sub_image_id': 265...       ISH  \n",
       "3    264712561  [{'bits_per_component': 8, 'sub_image_id': 265...       ISH  \n",
       "4    264712561  [{'bits_per_component': 8, 'sub_image_id': 265...       ISH  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_metadata = get_section_metadata(s3_client)\n",
    "section_metadata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "04f31931",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 20470 sections in the Ivy GAP dataset\n"
     ]
    }
   ],
   "source": [
    "print(f\"There are {len(section_metadata)} sections in the Ivy GAP dataset\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a644a97",
   "metadata": {},
   "source": [
    "Let's take a look at the section metadata for one of the two specimens we found in the previous Exploring specimen metadata section:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "873e1f57",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>entrez_id</th>\n",
       "      <th>forward_primer_sequence_data</th>\n",
       "      <th>forward_sequence_length</th>\n",
       "      <th>gene_acronym</th>\n",
       "      <th>gi</th>\n",
       "      <th>ncbi_accession_number</th>\n",
       "      <th>orientation</th>\n",
       "      <th>predicted_sequence_data</th>\n",
       "      <th>predicted_sequence_length</th>\n",
       "      <th>reverse_primer_sequence_data</th>\n",
       "      <th>reverse_sequence_length</th>\n",
       "      <th>section_data_set_id</th>\n",
       "      <th>section_thickness</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>sub_images</th>\n",
       "      <th>treatment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15882</th>\n",
       "      <td>15350</td>\n",
       "      <td>3485.0</td>\n",
       "      <td>GATGACCACTCAGAAGGAGGC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>IGFBP2</td>\n",
       "      <td>10835156.0</td>\n",
       "      <td>NM_000597.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GATGACCACTCAGAAGGAGGCCTGGTGGAGAACCACGTGGACAGCA...</td>\n",
       "      <td>642.0</td>\n",
       "      <td>CGTGTGTCAGAACTGGAAAATC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215254</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15883</th>\n",
       "      <td>15350</td>\n",
       "      <td>960.0</td>\n",
       "      <td>AAATGGTCGCTACAGCATCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>CD44</td>\n",
       "      <td>48255936.0</td>\n",
       "      <td>NM_001001389.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AAATGGTCGCTACAGCATCTCTCGGACGGAGGCCGCTGACCTCTGC...</td>\n",
       "      <td>907.0</td>\n",
       "      <td>GCTTGTAGAATGTGGGGTCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215306</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15884</th>\n",
       "      <td>15350</td>\n",
       "      <td>4843.0</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NOS2</td>\n",
       "      <td>24041028.0</td>\n",
       "      <td>NM_000625.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...</td>\n",
       "      <td>807.0</td>\n",
       "      <td>GAATCATACAGGGAAGACCCAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215359</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15885</th>\n",
       "      <td>15350</td>\n",
       "      <td>57291.0</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>DANCR</td>\n",
       "      <td>194394211.0</td>\n",
       "      <td>NR_024031.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...</td>\n",
       "      <td>512.0</td>\n",
       "      <td>ATAGCGCCTAGATAACGGTTCA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215412</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15886</th>\n",
       "      <td>15350</td>\n",
       "      <td>2146.0</td>\n",
       "      <td>TAAAGAACTCACCGAACAGCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>EZH2</td>\n",
       "      <td>322506096.0</td>\n",
       "      <td>NM_001203247.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TAAAGAACTCACCGAACAGCAGCTCCCAGGCGCACTTCCTCCTGAA...</td>\n",
       "      <td>938.0</td>\n",
       "      <td>AGCGGTTTTGACACTCTGAACT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215463</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15887</th>\n",
       "      <td>15350</td>\n",
       "      <td>8842.0</td>\n",
       "      <td>CTGGGGCTGCTGTTTATTATTC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PROM1</td>\n",
       "      <td>224994187.0</td>\n",
       "      <td>NM_006017.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTGGGGCTGCTGTTTATTATTCTGATGCCTCTGGTGGGGTATTTCT...</td>\n",
       "      <td>813.0</td>\n",
       "      <td>GACCCTTTTGATACCTGCTACG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215514</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15888</th>\n",
       "      <td>15350</td>\n",
       "      <td>10631.0</td>\n",
       "      <td>AGAATACACTTTGCTGGCACCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>POSTN</td>\n",
       "      <td>209863033.0</td>\n",
       "      <td>NM_001135936.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AGAATACACTTTGCTGGCACCTGTGAATAATGCATTTTCTGATGAT...</td>\n",
       "      <td>804.0</td>\n",
       "      <td>TAGACAGTCACGGGGATTTCTT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215565</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15889</th>\n",
       "      <td>15350</td>\n",
       "      <td>5156.0</td>\n",
       "      <td>CCGTGCTAAGGAAGAAGACAGT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PDGFRA</td>\n",
       "      <td>61699224.0</td>\n",
       "      <td>NM_006206.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CCGTGCTAAGGAAGAAGACAGTGGCCATTATACTATTGTAGCTCAA...</td>\n",
       "      <td>975.0</td>\n",
       "      <td>GATATCCAGCTCTTTCTTTGGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215618</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15890</th>\n",
       "      <td>15350</td>\n",
       "      <td>3397.0</td>\n",
       "      <td>AGCACGTCATCGACTACATCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ID1</td>\n",
       "      <td>341865545.0</td>\n",
       "      <td>NM_181353.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AGCACGTCATCGACTACATCAGGGACCTTCAGTTGGAGCTGAACTC...</td>\n",
       "      <td>806.0</td>\n",
       "      <td>AAACAGCCCCACAGAACTATTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215669</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15891</th>\n",
       "      <td>15350</td>\n",
       "      <td>10215.0</td>\n",
       "      <td>CTCACTAGAACTCATCCGACCC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>OLIG2</td>\n",
       "      <td>17978474.0</td>\n",
       "      <td>NM_005806.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTCACTAGAACTCATCCGACCCCCGACCACCACCTCCGGGAAAAGA...</td>\n",
       "      <td>749.0</td>\n",
       "      <td>GTGAGCAAACAGCTTAGCATTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215720</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15892</th>\n",
       "      <td>15350</td>\n",
       "      <td>3655.0</td>\n",
       "      <td>CCTATGGTGGATCCAAACTGAT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ITGA6</td>\n",
       "      <td>119395741.0</td>\n",
       "      <td>NM_000210.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CCTATGGTGGATCCAAACTGATCCAGTATAAGACTACTGAATCTGC...</td>\n",
       "      <td>983.0</td>\n",
       "      <td>CCCATTGCTTTGGCACTAGTAT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215771</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15893</th>\n",
       "      <td>15350</td>\n",
       "      <td>3091.0</td>\n",
       "      <td>TGTACCCTAACTAGCCGAGGAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>HIF1A</td>\n",
       "      <td>31077212.0</td>\n",
       "      <td>NM_001530.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TGTACCCTAACTAGCCGAGGAAGAACTATGAACATAAAGTCTGCAA...</td>\n",
       "      <td>908.0</td>\n",
       "      <td>GCAACTTCTTGATTGAGTGCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215822</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15894</th>\n",
       "      <td>15350</td>\n",
       "      <td>7128.0</td>\n",
       "      <td>GAAATGCTGCCCTAGAAGTACAA</td>\n",
       "      <td>23.0</td>\n",
       "      <td>TNFAIP3</td>\n",
       "      <td>26051241.0</td>\n",
       "      <td>NM_006290.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GAAATGCTGCCCTAGAAGTACAATAGGAAGGCTAAATAATAATAAC...</td>\n",
       "      <td>822.0</td>\n",
       "      <td>TCTAAGGGGAAAGTGTGCCTAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215873</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15895</th>\n",
       "      <td>15350</td>\n",
       "      <td>332.0</td>\n",
       "      <td>AACAGTGGCTGCTTCTCTCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>BIRC5</td>\n",
       "      <td>59859879.0</td>\n",
       "      <td>NM_001012270.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AACAGTGGCTGCTTCTCTCTCTCTCTCTCTTTTTTGGGGGCTCATT...</td>\n",
       "      <td>728.0</td>\n",
       "      <td>AACGTGACAGATGTGAAGGTTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215924</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15896</th>\n",
       "      <td>15350</td>\n",
       "      <td>7048.0</td>\n",
       "      <td>AACATCAACCACAACACAGAGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>TGFBR2</td>\n",
       "      <td>133908633.0</td>\n",
       "      <td>NM_003242.5</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AACATCAACCACAACACAGAGCTGCTGCCCATTGAGCTGGACACCC...</td>\n",
       "      <td>860.0</td>\n",
       "      <td>CACTCAGTCAACGTCTCACACA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215975</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15897</th>\n",
       "      <td>15350</td>\n",
       "      <td>2122.0</td>\n",
       "      <td>GAGGCCAGTGAGCTCTTACAGT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>MECOM</td>\n",
       "      <td>29789001.0</td>\n",
       "      <td>NM_005241.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GAGGCCAGTGAGCTCTTACAGTCAGTGCCCTCTATGTTCAACTTCA...</td>\n",
       "      <td>662.0</td>\n",
       "      <td>GGGCACTGGTTTCTTCATAGTC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294216026</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15898</th>\n",
       "      <td>15350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>294218209</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>H&amp;E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15899</th>\n",
       "      <td>15350</td>\n",
       "      <td>5266.0</td>\n",
       "      <td>ACACCTTCCTGACACCATGAG</td>\n",
       "      <td>21.0</td>\n",
       "      <td>PI3</td>\n",
       "      <td>208879450.0</td>\n",
       "      <td>NM_002638.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>ACACCTTCCTGACACCATGAGGGCCAGCAGCTTCTTGATCGTGGTG...</td>\n",
       "      <td>526.0</td>\n",
       "      <td>ATTGGAAAGTGGATGAGAGAGG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221462</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15900</th>\n",
       "      <td>15350</td>\n",
       "      <td>10630.0</td>\n",
       "      <td>TGAGACTACAGGTTTGGAAGGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PDPN</td>\n",
       "      <td>54792061.0</td>\n",
       "      <td>NM_001006625.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TGAGACTACAGGTTTGGAAGGCGGCGTTGCCATGCCAGGTGCCGAA...</td>\n",
       "      <td>706.0</td>\n",
       "      <td>CGATCCAATGGTCCAGTGTTAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221513</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15901</th>\n",
       "      <td>15350</td>\n",
       "      <td>3398.0</td>\n",
       "      <td>GTGAGGTCCGTTAGGAAAAACA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ID2</td>\n",
       "      <td>33946335.0</td>\n",
       "      <td>NM_002166.4</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GTGAGGTCCGTTAGGAAAAACAGCCTGTCGGACCACAGCCTGGGCA...</td>\n",
       "      <td>827.0</td>\n",
       "      <td>CAGCATTCAGTAGGCTTGTGTC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221564</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15902</th>\n",
       "      <td>15350</td>\n",
       "      <td>4609.0</td>\n",
       "      <td>CAGCGAGGATATCTGGAAGAAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>MYC</td>\n",
       "      <td>71774082.0</td>\n",
       "      <td>NM_002467.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CAGCGAGGATATCTGGAAGAAATTCGAGCTGCTGCCCACCCCGCCC...</td>\n",
       "      <td>979.0</td>\n",
       "      <td>GTTTTAGCTCGTTCCTCCTCTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221615</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15903</th>\n",
       "      <td>15350</td>\n",
       "      <td>4233.0</td>\n",
       "      <td>GACATGTCCCCCATCCTAACTA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>MET</td>\n",
       "      <td>42741654.0</td>\n",
       "      <td>NM_000245.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACATGTCCCCCATCCTAACTAGTGGGGACTCTGATATATCCAGTC...</td>\n",
       "      <td>785.0</td>\n",
       "      <td>GGGTTGTAGGAGTCTTCTCCCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221666</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15904</th>\n",
       "      <td>15350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>294217897</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>H&amp;E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15905</th>\n",
       "      <td>15350</td>\n",
       "      <td>5266.0</td>\n",
       "      <td>ACACCTTCCTGACACCATGAG</td>\n",
       "      <td>21.0</td>\n",
       "      <td>PI3</td>\n",
       "      <td>208879450.0</td>\n",
       "      <td>NM_002638.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>ACACCTTCCTGACACCATGAGGGCCAGCAGCTTCTTGATCGTGGTG...</td>\n",
       "      <td>526.0</td>\n",
       "      <td>ATTGGAAAGTGGATGAGAGAGG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220391</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15906</th>\n",
       "      <td>15350</td>\n",
       "      <td>10630.0</td>\n",
       "      <td>TGAGACTACAGGTTTGGAAGGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PDPN</td>\n",
       "      <td>54792061.0</td>\n",
       "      <td>NM_001006625.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TGAGACTACAGGTTTGGAAGGCGGCGTTGCCATGCCAGGTGCCGAA...</td>\n",
       "      <td>706.0</td>\n",
       "      <td>CGATCCAATGGTCCAGTGTTAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220442</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15907</th>\n",
       "      <td>15350</td>\n",
       "      <td>3398.0</td>\n",
       "      <td>GTGAGGTCCGTTAGGAAAAACA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ID2</td>\n",
       "      <td>33946335.0</td>\n",
       "      <td>NM_002166.4</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GTGAGGTCCGTTAGGAAAAACAGCCTGTCGGACCACAGCCTGGGCA...</td>\n",
       "      <td>827.0</td>\n",
       "      <td>CAGCATTCAGTAGGCTTGTGTC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220493</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15908</th>\n",
       "      <td>15350</td>\n",
       "      <td>4609.0</td>\n",
       "      <td>CAGCGAGGATATCTGGAAGAAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>MYC</td>\n",
       "      <td>71774082.0</td>\n",
       "      <td>NM_002467.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CAGCGAGGATATCTGGAAGAAATTCGAGCTGCTGCCCACCCCGCCC...</td>\n",
       "      <td>979.0</td>\n",
       "      <td>GTTTTAGCTCGTTCCTCCTCTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220544</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15909</th>\n",
       "      <td>15350</td>\n",
       "      <td>4233.0</td>\n",
       "      <td>GACATGTCCCCCATCCTAACTA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>MET</td>\n",
       "      <td>42741654.0</td>\n",
       "      <td>NM_000245.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACATGTCCCCCATCCTAACTAGTGGGGACTCTGATATATCCAGTC...</td>\n",
       "      <td>785.0</td>\n",
       "      <td>GGGTTGTAGGAGTCTTCTCCCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220595</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15910</th>\n",
       "      <td>15350</td>\n",
       "      <td>3485.0</td>\n",
       "      <td>GATGACCACTCAGAAGGAGGC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>IGFBP2</td>\n",
       "      <td>10835156.0</td>\n",
       "      <td>NM_000597.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GATGACCACTCAGAAGGAGGCCTGGTGGAGAACCACGTGGACAGCA...</td>\n",
       "      <td>642.0</td>\n",
       "      <td>CGTGTGTCAGAACTGGAAAATC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220646</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15911</th>\n",
       "      <td>15350</td>\n",
       "      <td>960.0</td>\n",
       "      <td>AAATGGTCGCTACAGCATCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>CD44</td>\n",
       "      <td>48255936.0</td>\n",
       "      <td>NM_001001389.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AAATGGTCGCTACAGCATCTCTCGGACGGAGGCCGCTGACCTCTGC...</td>\n",
       "      <td>907.0</td>\n",
       "      <td>GCTTGTAGAATGTGGGGTCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220697</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15912</th>\n",
       "      <td>15350</td>\n",
       "      <td>4843.0</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NOS2</td>\n",
       "      <td>24041028.0</td>\n",
       "      <td>NM_000625.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...</td>\n",
       "      <td>807.0</td>\n",
       "      <td>GAATCATACAGGGAAGACCCAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220748</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15913</th>\n",
       "      <td>15350</td>\n",
       "      <td>57291.0</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGC</td>\n",
       "      <td>21.0</td>\n",
       "      <td>DANCR</td>\n",
       "      <td>194394211.0</td>\n",
       "      <td>NR_024031.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...</td>\n",
       "      <td>512.0</td>\n",
       "      <td>ATAGCGCCTAGATAACGGTTCA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220799</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15914</th>\n",
       "      <td>15350</td>\n",
       "      <td>2146.0</td>\n",
       "      <td>TAAAGAACTCACCGAACAGCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>EZH2</td>\n",
       "      <td>322506096.0</td>\n",
       "      <td>NM_001203247.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TAAAGAACTCACCGAACAGCAGCTCCCAGGCGCACTTCCTCCTGAA...</td>\n",
       "      <td>938.0</td>\n",
       "      <td>AGCGGTTTTGACACTCTGAACT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220850</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15915</th>\n",
       "      <td>15350</td>\n",
       "      <td>8842.0</td>\n",
       "      <td>CTGGGGCTGCTGTTTATTATTC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PROM1</td>\n",
       "      <td>224994187.0</td>\n",
       "      <td>NM_006017.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTGGGGCTGCTGTTTATTATTCTGATGCCTCTGGTGGGGTATTTCT...</td>\n",
       "      <td>813.0</td>\n",
       "      <td>GACCCTTTTGATACCTGCTACG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220901</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15916</th>\n",
       "      <td>15350</td>\n",
       "      <td>10631.0</td>\n",
       "      <td>AGAATACACTTTGCTGGCACCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>POSTN</td>\n",
       "      <td>209863033.0</td>\n",
       "      <td>NM_001135936.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AGAATACACTTTGCTGGCACCTGTGAATAATGCATTTTCTGATGAT...</td>\n",
       "      <td>804.0</td>\n",
       "      <td>TAGACAGTCACGGGGATTTCTT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220952</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15917</th>\n",
       "      <td>15350</td>\n",
       "      <td>5156.0</td>\n",
       "      <td>CCGTGCTAAGGAAGAAGACAGT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>PDGFRA</td>\n",
       "      <td>61699224.0</td>\n",
       "      <td>NM_006206.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CCGTGCTAAGGAAGAAGACAGTGGCCATTATACTATTGTAGCTCAA...</td>\n",
       "      <td>975.0</td>\n",
       "      <td>GATATCCAGCTCTTTCTTTGGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221003</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15918</th>\n",
       "      <td>15350</td>\n",
       "      <td>3397.0</td>\n",
       "      <td>AGCACGTCATCGACTACATCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ID1</td>\n",
       "      <td>341865545.0</td>\n",
       "      <td>NM_181353.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AGCACGTCATCGACTACATCAGGGACCTTCAGTTGGAGCTGAACTC...</td>\n",
       "      <td>806.0</td>\n",
       "      <td>AAACAGCCCCACAGAACTATTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221054</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15919</th>\n",
       "      <td>15350</td>\n",
       "      <td>10215.0</td>\n",
       "      <td>CTCACTAGAACTCATCCGACCC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>OLIG2</td>\n",
       "      <td>17978474.0</td>\n",
       "      <td>NM_005806.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CTCACTAGAACTCATCCGACCCCCGACCACCACCTCCGGGAAAAGA...</td>\n",
       "      <td>749.0</td>\n",
       "      <td>GTGAGCAAACAGCTTAGCATTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221105</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15920</th>\n",
       "      <td>15350</td>\n",
       "      <td>3655.0</td>\n",
       "      <td>CCTATGGTGGATCCAAACTGAT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>ITGA6</td>\n",
       "      <td>119395741.0</td>\n",
       "      <td>NM_000210.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>CCTATGGTGGATCCAAACTGATCCAGTATAAGACTACTGAATCTGC...</td>\n",
       "      <td>983.0</td>\n",
       "      <td>CCCATTGCTTTGGCACTAGTAT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221156</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15921</th>\n",
       "      <td>15350</td>\n",
       "      <td>3091.0</td>\n",
       "      <td>TGTACCCTAACTAGCCGAGGAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>HIF1A</td>\n",
       "      <td>31077212.0</td>\n",
       "      <td>NM_001530.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>TGTACCCTAACTAGCCGAGGAAGAACTATGAACATAAAGTCTGCAA...</td>\n",
       "      <td>908.0</td>\n",
       "      <td>GCAACTTCTTGATTGAGTGCAG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221207</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15922</th>\n",
       "      <td>15350</td>\n",
       "      <td>7128.0</td>\n",
       "      <td>GAAATGCTGCCCTAGAAGTACAA</td>\n",
       "      <td>23.0</td>\n",
       "      <td>TNFAIP3</td>\n",
       "      <td>26051241.0</td>\n",
       "      <td>NM_006290.2</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GAAATGCTGCCCTAGAAGTACAATAGGAAGGCTAAATAATAATAAC...</td>\n",
       "      <td>822.0</td>\n",
       "      <td>TCTAAGGGGAAAGTGTGCCTAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221258</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15923</th>\n",
       "      <td>15350</td>\n",
       "      <td>332.0</td>\n",
       "      <td>AACAGTGGCTGCTTCTCTCTCT</td>\n",
       "      <td>22.0</td>\n",
       "      <td>BIRC5</td>\n",
       "      <td>59859879.0</td>\n",
       "      <td>NM_001012270.1</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AACAGTGGCTGCTTCTCTCTCTCTCTCTCTTTTTTGGGGGCTCATT...</td>\n",
       "      <td>728.0</td>\n",
       "      <td>AACGTGACAGATGTGAAGGTTG</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221309</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15924</th>\n",
       "      <td>15350</td>\n",
       "      <td>7048.0</td>\n",
       "      <td>AACATCAACCACAACACAGAGC</td>\n",
       "      <td>22.0</td>\n",
       "      <td>TGFBR2</td>\n",
       "      <td>133908633.0</td>\n",
       "      <td>NM_003242.5</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>AACATCAACCACAACACAGAGCTGCTGCCCATTGAGCTGGACACCC...</td>\n",
       "      <td>860.0</td>\n",
       "      <td>CACTCAGTCAACGTCTCACACA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294221360</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15925</th>\n",
       "      <td>15350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>294221411</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       donor_id  entrez_id forward_primer_sequence_data  \\\n",
       "15882     15350     3485.0        GATGACCACTCAGAAGGAGGC   \n",
       "15883     15350      960.0       AAATGGTCGCTACAGCATCTCT   \n",
       "15884     15350     4843.0       GACCACATCTACCAGGAGGAGA   \n",
       "15885     15350    57291.0        CTCTTTGTCAGCTGGAGTTGC   \n",
       "15886     15350     2146.0       TAAAGAACTCACCGAACAGCAG   \n",
       "15887     15350     8842.0       CTGGGGCTGCTGTTTATTATTC   \n",
       "15888     15350    10631.0       AGAATACACTTTGCTGGCACCT   \n",
       "15889     15350     5156.0       CCGTGCTAAGGAAGAAGACAGT   \n",
       "15890     15350     3397.0       AGCACGTCATCGACTACATCAG   \n",
       "15891     15350    10215.0       CTCACTAGAACTCATCCGACCC   \n",
       "15892     15350     3655.0       CCTATGGTGGATCCAAACTGAT   \n",
       "15893     15350     3091.0       TGTACCCTAACTAGCCGAGGAA   \n",
       "15894     15350     7128.0      GAAATGCTGCCCTAGAAGTACAA   \n",
       "15895     15350      332.0       AACAGTGGCTGCTTCTCTCTCT   \n",
       "15896     15350     7048.0       AACATCAACCACAACACAGAGC   \n",
       "15897     15350     2122.0       GAGGCCAGTGAGCTCTTACAGT   \n",
       "15898     15350        NaN                         None   \n",
       "15899     15350     5266.0        ACACCTTCCTGACACCATGAG   \n",
       "15900     15350    10630.0       TGAGACTACAGGTTTGGAAGGC   \n",
       "15901     15350     3398.0       GTGAGGTCCGTTAGGAAAAACA   \n",
       "15902     15350     4609.0       CAGCGAGGATATCTGGAAGAAA   \n",
       "15903     15350     4233.0       GACATGTCCCCCATCCTAACTA   \n",
       "15904     15350        NaN                         None   \n",
       "15905     15350     5266.0        ACACCTTCCTGACACCATGAG   \n",
       "15906     15350    10630.0       TGAGACTACAGGTTTGGAAGGC   \n",
       "15907     15350     3398.0       GTGAGGTCCGTTAGGAAAAACA   \n",
       "15908     15350     4609.0       CAGCGAGGATATCTGGAAGAAA   \n",
       "15909     15350     4233.0       GACATGTCCCCCATCCTAACTA   \n",
       "15910     15350     3485.0        GATGACCACTCAGAAGGAGGC   \n",
       "15911     15350      960.0       AAATGGTCGCTACAGCATCTCT   \n",
       "15912     15350     4843.0       GACCACATCTACCAGGAGGAGA   \n",
       "15913     15350    57291.0        CTCTTTGTCAGCTGGAGTTGC   \n",
       "15914     15350     2146.0       TAAAGAACTCACCGAACAGCAG   \n",
       "15915     15350     8842.0       CTGGGGCTGCTGTTTATTATTC   \n",
       "15916     15350    10631.0       AGAATACACTTTGCTGGCACCT   \n",
       "15917     15350     5156.0       CCGTGCTAAGGAAGAAGACAGT   \n",
       "15918     15350     3397.0       AGCACGTCATCGACTACATCAG   \n",
       "15919     15350    10215.0       CTCACTAGAACTCATCCGACCC   \n",
       "15920     15350     3655.0       CCTATGGTGGATCCAAACTGAT   \n",
       "15921     15350     3091.0       TGTACCCTAACTAGCCGAGGAA   \n",
       "15922     15350     7128.0      GAAATGCTGCCCTAGAAGTACAA   \n",
       "15923     15350      332.0       AACAGTGGCTGCTTCTCTCTCT   \n",
       "15924     15350     7048.0       AACATCAACCACAACACAGAGC   \n",
       "15925     15350        NaN                         None   \n",
       "\n",
       "       forward_sequence_length gene_acronym           gi  \\\n",
       "15882                     21.0       IGFBP2   10835156.0   \n",
       "15883                     22.0         CD44   48255936.0   \n",
       "15884                     22.0         NOS2   24041028.0   \n",
       "15885                     21.0        DANCR  194394211.0   \n",
       "15886                     22.0         EZH2  322506096.0   \n",
       "15887                     22.0        PROM1  224994187.0   \n",
       "15888                     22.0        POSTN  209863033.0   \n",
       "15889                     22.0       PDGFRA   61699224.0   \n",
       "15890                     22.0          ID1  341865545.0   \n",
       "15891                     22.0        OLIG2   17978474.0   \n",
       "15892                     22.0        ITGA6  119395741.0   \n",
       "15893                     22.0        HIF1A   31077212.0   \n",
       "15894                     23.0      TNFAIP3   26051241.0   \n",
       "15895                     22.0        BIRC5   59859879.0   \n",
       "15896                     22.0       TGFBR2  133908633.0   \n",
       "15897                     22.0        MECOM   29789001.0   \n",
       "15898                      NaN         None          NaN   \n",
       "15899                     21.0          PI3  208879450.0   \n",
       "15900                     22.0         PDPN   54792061.0   \n",
       "15901                     22.0          ID2   33946335.0   \n",
       "15902                     22.0          MYC   71774082.0   \n",
       "15903                     22.0          MET   42741654.0   \n",
       "15904                      NaN         None          NaN   \n",
       "15905                     21.0          PI3  208879450.0   \n",
       "15906                     22.0         PDPN   54792061.0   \n",
       "15907                     22.0          ID2   33946335.0   \n",
       "15908                     22.0          MYC   71774082.0   \n",
       "15909                     22.0          MET   42741654.0   \n",
       "15910                     21.0       IGFBP2   10835156.0   \n",
       "15911                     22.0         CD44   48255936.0   \n",
       "15912                     22.0         NOS2   24041028.0   \n",
       "15913                     21.0        DANCR  194394211.0   \n",
       "15914                     22.0         EZH2  322506096.0   \n",
       "15915                     22.0        PROM1  224994187.0   \n",
       "15916                     22.0        POSTN  209863033.0   \n",
       "15917                     22.0       PDGFRA   61699224.0   \n",
       "15918                     22.0          ID1  341865545.0   \n",
       "15919                     22.0        OLIG2   17978474.0   \n",
       "15920                     22.0        ITGA6  119395741.0   \n",
       "15921                     22.0        HIF1A   31077212.0   \n",
       "15922                     23.0      TNFAIP3   26051241.0   \n",
       "15923                     22.0        BIRC5   59859879.0   \n",
       "15924                     22.0       TGFBR2  133908633.0   \n",
       "15925                      NaN         None          NaN   \n",
       "\n",
       "      ncbi_accession_number orientation  \\\n",
       "15882           NM_000597.1   Antisense   \n",
       "15883        NM_001001389.1   Antisense   \n",
       "15884           NM_000625.3   Antisense   \n",
       "15885           NR_024031.1   Antisense   \n",
       "15886        NM_001203247.1   Antisense   \n",
       "15887           NM_006017.2   Antisense   \n",
       "15888        NM_001135936.1   Antisense   \n",
       "15889           NM_006206.3   Antisense   \n",
       "15890           NM_181353.2   Antisense   \n",
       "15891           NM_005806.1   Antisense   \n",
       "15892           NM_000210.2   Antisense   \n",
       "15893           NM_001530.2   Antisense   \n",
       "15894           NM_006290.2   Antisense   \n",
       "15895        NM_001012270.1   Antisense   \n",
       "15896           NM_003242.5   Antisense   \n",
       "15897           NM_005241.1   Antisense   \n",
       "15898                  None        None   \n",
       "15899           NM_002638.3   Antisense   \n",
       "15900        NM_001006625.1   Antisense   \n",
       "15901           NM_002166.4   Antisense   \n",
       "15902           NM_002467.3   Antisense   \n",
       "15903           NM_000245.2   Antisense   \n",
       "15904                  None        None   \n",
       "15905           NM_002638.3   Antisense   \n",
       "15906        NM_001006625.1   Antisense   \n",
       "15907           NM_002166.4   Antisense   \n",
       "15908           NM_002467.3   Antisense   \n",
       "15909           NM_000245.2   Antisense   \n",
       "15910           NM_000597.1   Antisense   \n",
       "15911        NM_001001389.1   Antisense   \n",
       "15912           NM_000625.3   Antisense   \n",
       "15913           NR_024031.1   Antisense   \n",
       "15914        NM_001203247.1   Antisense   \n",
       "15915           NM_006017.2   Antisense   \n",
       "15916        NM_001135936.1   Antisense   \n",
       "15917           NM_006206.3   Antisense   \n",
       "15918           NM_181353.2   Antisense   \n",
       "15919           NM_005806.1   Antisense   \n",
       "15920           NM_000210.2   Antisense   \n",
       "15921           NM_001530.2   Antisense   \n",
       "15922           NM_006290.2   Antisense   \n",
       "15923        NM_001012270.1   Antisense   \n",
       "15924           NM_003242.5   Antisense   \n",
       "15925                  None        None   \n",
       "\n",
       "                                 predicted_sequence_data  \\\n",
       "15882  GATGACCACTCAGAAGGAGGCCTGGTGGAGAACCACGTGGACAGCA...   \n",
       "15883  AAATGGTCGCTACAGCATCTCTCGGACGGAGGCCGCTGACCTCTGC...   \n",
       "15884  GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...   \n",
       "15885  CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...   \n",
       "15886  TAAAGAACTCACCGAACAGCAGCTCCCAGGCGCACTTCCTCCTGAA...   \n",
       "15887  CTGGGGCTGCTGTTTATTATTCTGATGCCTCTGGTGGGGTATTTCT...   \n",
       "15888  AGAATACACTTTGCTGGCACCTGTGAATAATGCATTTTCTGATGAT...   \n",
       "15889  CCGTGCTAAGGAAGAAGACAGTGGCCATTATACTATTGTAGCTCAA...   \n",
       "15890  AGCACGTCATCGACTACATCAGGGACCTTCAGTTGGAGCTGAACTC...   \n",
       "15891  CTCACTAGAACTCATCCGACCCCCGACCACCACCTCCGGGAAAAGA...   \n",
       "15892  CCTATGGTGGATCCAAACTGATCCAGTATAAGACTACTGAATCTGC...   \n",
       "15893  TGTACCCTAACTAGCCGAGGAAGAACTATGAACATAAAGTCTGCAA...   \n",
       "15894  GAAATGCTGCCCTAGAAGTACAATAGGAAGGCTAAATAATAATAAC...   \n",
       "15895  AACAGTGGCTGCTTCTCTCTCTCTCTCTCTTTTTTGGGGGCTCATT...   \n",
       "15896  AACATCAACCACAACACAGAGCTGCTGCCCATTGAGCTGGACACCC...   \n",
       "15897  GAGGCCAGTGAGCTCTTACAGTCAGTGCCCTCTATGTTCAACTTCA...   \n",
       "15898                                               None   \n",
       "15899  ACACCTTCCTGACACCATGAGGGCCAGCAGCTTCTTGATCGTGGTG...   \n",
       "15900  TGAGACTACAGGTTTGGAAGGCGGCGTTGCCATGCCAGGTGCCGAA...   \n",
       "15901  GTGAGGTCCGTTAGGAAAAACAGCCTGTCGGACCACAGCCTGGGCA...   \n",
       "15902  CAGCGAGGATATCTGGAAGAAATTCGAGCTGCTGCCCACCCCGCCC...   \n",
       "15903  GACATGTCCCCCATCCTAACTAGTGGGGACTCTGATATATCCAGTC...   \n",
       "15904                                               None   \n",
       "15905  ACACCTTCCTGACACCATGAGGGCCAGCAGCTTCTTGATCGTGGTG...   \n",
       "15906  TGAGACTACAGGTTTGGAAGGCGGCGTTGCCATGCCAGGTGCCGAA...   \n",
       "15907  GTGAGGTCCGTTAGGAAAAACAGCCTGTCGGACCACAGCCTGGGCA...   \n",
       "15908  CAGCGAGGATATCTGGAAGAAATTCGAGCTGCTGCCCACCCCGCCC...   \n",
       "15909  GACATGTCCCCCATCCTAACTAGTGGGGACTCTGATATATCCAGTC...   \n",
       "15910  GATGACCACTCAGAAGGAGGCCTGGTGGAGAACCACGTGGACAGCA...   \n",
       "15911  AAATGGTCGCTACAGCATCTCTCGGACGGAGGCCGCTGACCTCTGC...   \n",
       "15912  GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...   \n",
       "15913  CTCTTTGTCAGCTGGAGTTGCGCGGGCTGACGCGCCACTATGTAGC...   \n",
       "15914  TAAAGAACTCACCGAACAGCAGCTCCCAGGCGCACTTCCTCCTGAA...   \n",
       "15915  CTGGGGCTGCTGTTTATTATTCTGATGCCTCTGGTGGGGTATTTCT...   \n",
       "15916  AGAATACACTTTGCTGGCACCTGTGAATAATGCATTTTCTGATGAT...   \n",
       "15917  CCGTGCTAAGGAAGAAGACAGTGGCCATTATACTATTGTAGCTCAA...   \n",
       "15918  AGCACGTCATCGACTACATCAGGGACCTTCAGTTGGAGCTGAACTC...   \n",
       "15919  CTCACTAGAACTCATCCGACCCCCGACCACCACCTCCGGGAAAAGA...   \n",
       "15920  CCTATGGTGGATCCAAACTGATCCAGTATAAGACTACTGAATCTGC...   \n",
       "15921  TGTACCCTAACTAGCCGAGGAAGAACTATGAACATAAAGTCTGCAA...   \n",
       "15922  GAAATGCTGCCCTAGAAGTACAATAGGAAGGCTAAATAATAATAAC...   \n",
       "15923  AACAGTGGCTGCTTCTCTCTCTCTCTCTCTTTTTTGGGGGCTCATT...   \n",
       "15924  AACATCAACCACAACACAGAGCTGCTGCCCATTGAGCTGGACACCC...   \n",
       "15925                                               None   \n",
       "\n",
       "       predicted_sequence_length reverse_primer_sequence_data  \\\n",
       "15882                      642.0       CGTGTGTCAGAACTGGAAAATC   \n",
       "15883                      907.0       GCTTGTAGAATGTGGGGTCTCT   \n",
       "15884                      807.0       GAATCATACAGGGAAGACCCAA   \n",
       "15885                      512.0       ATAGCGCCTAGATAACGGTTCA   \n",
       "15886                      938.0       AGCGGTTTTGACACTCTGAACT   \n",
       "15887                      813.0       GACCCTTTTGATACCTGCTACG   \n",
       "15888                      804.0       TAGACAGTCACGGGGATTTCTT   \n",
       "15889                      975.0       GATATCCAGCTCTTTCTTTGGC   \n",
       "15890                      806.0       AAACAGCCCCACAGAACTATTG   \n",
       "15891                      749.0       GTGAGCAAACAGCTTAGCATTG   \n",
       "15892                      983.0       CCCATTGCTTTGGCACTAGTAT   \n",
       "15893                      908.0       GCAACTTCTTGATTGAGTGCAG   \n",
       "15894                      822.0       TCTAAGGGGAAAGTGTGCCTAA   \n",
       "15895                      728.0       AACGTGACAGATGTGAAGGTTG   \n",
       "15896                      860.0       CACTCAGTCAACGTCTCACACA   \n",
       "15897                      662.0       GGGCACTGGTTTCTTCATAGTC   \n",
       "15898                        NaN                         None   \n",
       "15899                      526.0       ATTGGAAAGTGGATGAGAGAGG   \n",
       "15900                      706.0       CGATCCAATGGTCCAGTGTTAG   \n",
       "15901                      827.0       CAGCATTCAGTAGGCTTGTGTC   \n",
       "15902                      979.0       GTTTTAGCTCGTTCCTCCTCTG   \n",
       "15903                      785.0       GGGTTGTAGGAGTCTTCTCCCT   \n",
       "15904                        NaN                         None   \n",
       "15905                      526.0       ATTGGAAAGTGGATGAGAGAGG   \n",
       "15906                      706.0       CGATCCAATGGTCCAGTGTTAG   \n",
       "15907                      827.0       CAGCATTCAGTAGGCTTGTGTC   \n",
       "15908                      979.0       GTTTTAGCTCGTTCCTCCTCTG   \n",
       "15909                      785.0       GGGTTGTAGGAGTCTTCTCCCT   \n",
       "15910                      642.0       CGTGTGTCAGAACTGGAAAATC   \n",
       "15911                      907.0       GCTTGTAGAATGTGGGGTCTCT   \n",
       "15912                      807.0       GAATCATACAGGGAAGACCCAA   \n",
       "15913                      512.0       ATAGCGCCTAGATAACGGTTCA   \n",
       "15914                      938.0       AGCGGTTTTGACACTCTGAACT   \n",
       "15915                      813.0       GACCCTTTTGATACCTGCTACG   \n",
       "15916                      804.0       TAGACAGTCACGGGGATTTCTT   \n",
       "15917                      975.0       GATATCCAGCTCTTTCTTTGGC   \n",
       "15918                      806.0       AAACAGCCCCACAGAACTATTG   \n",
       "15919                      749.0       GTGAGCAAACAGCTTAGCATTG   \n",
       "15920                      983.0       CCCATTGCTTTGGCACTAGTAT   \n",
       "15921                      908.0       GCAACTTCTTGATTGAGTGCAG   \n",
       "15922                      822.0       TCTAAGGGGAAAGTGTGCCTAA   \n",
       "15923                      728.0       AACGTGACAGATGTGAAGGTTG   \n",
       "15924                      860.0       CACTCAGTCAACGTCTCACACA   \n",
       "15925                        NaN                         None   \n",
       "\n",
       "       reverse_sequence_length  section_data_set_id  section_thickness  \\\n",
       "15882                     22.0            294215254                 20   \n",
       "15883                     22.0            294215306                 20   \n",
       "15884                     22.0            294215359                 20   \n",
       "15885                     22.0            294215412                 20   \n",
       "15886                     22.0            294215463                 20   \n",
       "15887                     22.0            294215514                 20   \n",
       "15888                     22.0            294215565                 20   \n",
       "15889                     22.0            294215618                 20   \n",
       "15890                     22.0            294215669                 20   \n",
       "15891                     22.0            294215720                 20   \n",
       "15892                     22.0            294215771                 20   \n",
       "15893                     22.0            294215822                 20   \n",
       "15894                     22.0            294215873                 20   \n",
       "15895                     22.0            294215924                 20   \n",
       "15896                     22.0            294215975                 20   \n",
       "15897                     22.0            294216026                 20   \n",
       "15898                      NaN            294218209                 20   \n",
       "15899                     22.0            294221462                 20   \n",
       "15900                     22.0            294221513                 20   \n",
       "15901                     22.0            294221564                 20   \n",
       "15902                     22.0            294221615                 20   \n",
       "15903                     22.0            294221666                 20   \n",
       "15904                      NaN            294217897                 20   \n",
       "15905                     22.0            294220391                 20   \n",
       "15906                     22.0            294220442                 20   \n",
       "15907                     22.0            294220493                 20   \n",
       "15908                     22.0            294220544                 20   \n",
       "15909                     22.0            294220595                 20   \n",
       "15910                     22.0            294220646                 20   \n",
       "15911                     22.0            294220697                 20   \n",
       "15912                     22.0            294220748                 20   \n",
       "15913                     22.0            294220799                 20   \n",
       "15914                     22.0            294220850                 20   \n",
       "15915                     22.0            294220901                 20   \n",
       "15916                     22.0            294220952                 20   \n",
       "15917                     22.0            294221003                 20   \n",
       "15918                     22.0            294221054                 20   \n",
       "15919                     22.0            294221105                 20   \n",
       "15920                     22.0            294221156                 20   \n",
       "15921                     22.0            294221207                 20   \n",
       "15922                     22.0            294221258                 20   \n",
       "15923                     22.0            294221309                 20   \n",
       "15924                     22.0            294221360                 20   \n",
       "15925                      NaN            294221411                 20   \n",
       "\n",
       "       specimen_id                                         sub_images  \\\n",
       "15882    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15883    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15884    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15885    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15886    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15887    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15888    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15889    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15890    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15891    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15892    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15893    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15894    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15895    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15896    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15897    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15898    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15899    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15900    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15901    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15902    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15903    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15904    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15905    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15906    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15907    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15908    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15909    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15910    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15911    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15912    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15913    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15914    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15915    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15916    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15917    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15918    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15919    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15920    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15921    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15922    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15923    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15924    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15925    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "\n",
       "      treatment  \n",
       "15882       ISH  \n",
       "15883       ISH  \n",
       "15884       ISH  \n",
       "15885       ISH  \n",
       "15886       ISH  \n",
       "15887       ISH  \n",
       "15888       ISH  \n",
       "15889       ISH  \n",
       "15890       ISH  \n",
       "15891       ISH  \n",
       "15892       ISH  \n",
       "15893       ISH  \n",
       "15894       ISH  \n",
       "15895       ISH  \n",
       "15896       ISH  \n",
       "15897       ISH  \n",
       "15898       H&E  \n",
       "15899       ISH  \n",
       "15900       ISH  \n",
       "15901       ISH  \n",
       "15902       ISH  \n",
       "15903       ISH  \n",
       "15904       H&E  \n",
       "15905       ISH  \n",
       "15906       ISH  \n",
       "15907       ISH  \n",
       "15908       ISH  \n",
       "15909       ISH  \n",
       "15910       ISH  \n",
       "15911       ISH  \n",
       "15912       ISH  \n",
       "15913       ISH  \n",
       "15914       ISH  \n",
       "15915       ISH  \n",
       "15916       ISH  \n",
       "15917       ISH  \n",
       "15918       ISH  \n",
       "15919       ISH  \n",
       "15920       ISH  \n",
       "15921       ISH  \n",
       "15922       ISH  \n",
       "15923       ISH  \n",
       "15924       ISH  \n",
       "15925       ISH  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "specimens_of_interest = specimen_metadata[specimen_study_and_donor_kps_filter][\"specimen_id\"].values\n",
    "section_specimen_filter = section_metadata[\"specimen_id\"].isin(specimens_of_interest)\n",
    "section_metadata[section_specimen_filter]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f501585b",
   "metadata": {},
   "source": [
    "Let's take a look at the histology images for the two specimens:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fdfeb0b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>section_data_set_id</th>\n",
       "      <th>section_thickness</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>sub_images</th>\n",
       "      <th>treatment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15898</th>\n",
       "      <td>15350</td>\n",
       "      <td>294218209</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>H&amp;E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15904</th>\n",
       "      <td>15350</td>\n",
       "      <td>294217897</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>H&amp;E</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       donor_id  section_data_set_id  section_thickness  specimen_id  \\\n",
       "15898     15350            294218209                 20    293591387   \n",
       "15904     15350            294217897                 20    293591503   \n",
       "\n",
       "                                              sub_images treatment  \n",
       "15898  [{'bits_per_component': 8, 'sub_image_id': 294...       H&E  \n",
       "15904  [{'bits_per_component': 8, 'sub_image_id': 294...       H&E  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "histology_filter = section_metadata[\"treatment\"] == \"H&E\"\n",
    "histology_sections = section_metadata[section_specimen_filter & histology_filter].dropna(axis=1, how='all')\n",
    "histology_sections"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "370e7b1a",
   "metadata": {},
   "source": [
    "Now that we've narrowed down the number of sections that we are interested in, we can use the following `section_image_loader` utility to download and view the images:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "58925077",
   "metadata": {},
   "outputs": [],
   "source": [
    "from open_dataset_tools.ivy_gap_utils import section_image_loader"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01866755",
   "metadata": {},
   "source": [
    "The `section_image_loader` expects at minimum, a section metadata table (can be filtered or unfiltered), and a `section_data_set_id` (whose value must exist in the section metadata table if it has been filtered) which can be obtained from the section metadata table.\n",
    "\n",
    "Let's say we are interested in the images where `section_data_set_id == 294218209`.\n",
    "\n",
    "NOTE: Set `verbose=True` to get a feel for what is being downloaded at any given time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d5771996",
   "metadata": {},
   "outputs": [],
   "source": [
    "section_image_table = section_image_loader(\n",
    "    section_meta_table=histology_sections,\n",
    "    section_data_set_id=294218209,\n",
    "    verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "98741302",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bits_per_component</th>\n",
       "      <th>sub_image_id</th>\n",
       "      <th>resolution</th>\n",
       "      <th>section_number</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>primary</th>\n",
       "      <th>annotation</th>\n",
       "      <th>boundary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>294218391</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>2</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>294218373</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>5</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>294218355</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>8</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>294218337</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>11</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>294218319</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>14</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bits_per_component  sub_image_id  resolution  section_number  width  \\\n",
       "0                   8     294218391      0.4945               2  15040   \n",
       "1                   8     294218373      0.4945               5  15040   \n",
       "2                   8     294218355      0.4945               8  15040   \n",
       "3                   8     294218337      0.4945              11  15040   \n",
       "4                   8     294218319      0.4945              14  15040   \n",
       "\n",
       "   height                                            primary  \\\n",
       "0   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "1   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "2   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "3   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "4   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                          annotation  \\\n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "1  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "2  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "3  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "4  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                            boundary  \n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...  \n",
       "1  <open_dataset_tools.ivy_gap_utils.ImagePromise...  \n",
       "2  <open_dataset_tools.ivy_gap_utils.ImagePromise...  \n",
       "3  <open_dataset_tools.ivy_gap_utils.ImagePromise...  \n",
       "4  <open_dataset_tools.ivy_gap_utils.ImagePromise...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "section_image_table.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e371eaf",
   "metadata": {},
   "source": [
    "The section image table contains data as well as metadata for sub-images within a section. Images are loaded in as instances of a custom `ImagePromise` class. When the `.load()` method is called on an `ImagePromise` class, image data is downloaded from S3 and a Python Image Library (PIL) `Image` class is returned. For more details about the `Image` class, please see: https://pillow.readthedocs.io/en/stable/reference/Image.html\n",
    "\n",
    "Let's take a look at the `ImagePromise` class returned by looking at the first row of the section_image_table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4b9a9295",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accessing the 0-th row of the 'primary' column of the section_image_table gives:\n",
      "<class 'open_dataset_tools.ivy_gap_utils.ImagePromise'>\n",
      "\n",
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/primary/293591387_02_294218391.jpg\n",
      "\n",
      "After calling 'load()' on an 'ImagePromise', what is returned is:\n",
      "<class 'PIL.JpegImagePlugin.JpegImageFile'>\n"
     ]
    }
   ],
   "source": [
    "print(f\"Accessing the 0-th row of the 'primary' column of the section_image_table gives:\\n{type(section_image_table['primary'][0])}\\n\")\n",
    "\n",
    "image_promise = section_image_table[\"primary\"][0]\n",
    "# Note how downloading only happens when you call `load()` on the ImagePromise object\n",
    "print(f\"\\nAfter calling 'load()' on an 'ImagePromise', what is returned is:\\n{type(image_promise.load())}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a69d4ce5",
   "metadata": {},
   "source": [
    "Now, lets try viewing some of the images described in the section_image_table using matplotlib:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1cb052dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/primary/293591387_02_294218391.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# This line sets matplotlib to plot inline in the notebook\n",
    "%matplotlib inline\n",
    "\n",
    "# Notice that we can just index into the `section_image_table` and call '.load()' directly\n",
    "# without needing to set an image_promise variable\n",
    "plt.imshow(section_image_table[\"primary\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ad73a6fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/annotation/293591387_02_294218391_annotation.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(section_image_table[\"annotation\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "51d3a45e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/boundary/293591387_02_294218391_boundary.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(section_image_table[\"boundary\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81785447",
   "metadata": {},
   "source": [
    "Looking at the specimen metadata table which these images are from, we can see that we have successfully programatically accessed a subset of the images shown on the website link:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "80905842",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>donor_name</th>\n",
       "      <th>external_donor_name</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>specimen_name</th>\n",
       "      <th>specimen_page_link</th>\n",
       "      <th>study_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>15350</td>\n",
       "      <td>H366-0046</td>\n",
       "      <td>W39-1-1</td>\n",
       "      <td>293591387</td>\n",
       "      <td>W39-1-1-O.01</td>\n",
       "      <td>http://glioblastoma.alleninstitute.org/ish/spe...</td>\n",
       "      <td>Cancer Stem Cells ISH Survey</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     donor_id donor_name external_donor_name  specimen_id specimen_name  \\\n",
       "728     15350  H366-0046             W39-1-1    293591387  W39-1-1-O.01   \n",
       "\n",
       "                                    specimen_page_link  \\\n",
       "728  http://glioblastoma.alleninstitute.org/ish/spe...   \n",
       "\n",
       "                       study_name  \n",
       "728  Cancer Stem Cells ISH Survey  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reverse_lookup = specimen_metadata[specimen_metadata[\"specimen_id\"] == histology_sections[\"specimen_id\"].iloc[0]]\n",
    "reverse_lookup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7a534623",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'http://glioblastoma.alleninstitute.org/ish/specimen/show/293591387'"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reverse_lookup[\"specimen_page_link\"].iloc[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1722e0bc",
   "metadata": {},
   "source": [
    "Another common set of analyses to perform with this dataset is to look at in situ hybridization (ISH) to localize genes of interest to a location in tissue. Here is an example for viewing ISH images for the gene `NOS2`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8a0323ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>donor_id</th>\n",
       "      <th>entrez_id</th>\n",
       "      <th>forward_primer_sequence_data</th>\n",
       "      <th>forward_sequence_length</th>\n",
       "      <th>gene_acronym</th>\n",
       "      <th>gi</th>\n",
       "      <th>ncbi_accession_number</th>\n",
       "      <th>orientation</th>\n",
       "      <th>predicted_sequence_data</th>\n",
       "      <th>predicted_sequence_length</th>\n",
       "      <th>reverse_primer_sequence_data</th>\n",
       "      <th>reverse_sequence_length</th>\n",
       "      <th>section_data_set_id</th>\n",
       "      <th>section_thickness</th>\n",
       "      <th>specimen_id</th>\n",
       "      <th>sub_images</th>\n",
       "      <th>treatment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15884</th>\n",
       "      <td>15350</td>\n",
       "      <td>4843.0</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NOS2</td>\n",
       "      <td>24041028.0</td>\n",
       "      <td>NM_000625.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...</td>\n",
       "      <td>807.0</td>\n",
       "      <td>GAATCATACAGGGAAGACCCAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294215359</td>\n",
       "      <td>20</td>\n",
       "      <td>293591387</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15912</th>\n",
       "      <td>15350</td>\n",
       "      <td>4843.0</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NOS2</td>\n",
       "      <td>24041028.0</td>\n",
       "      <td>NM_000625.3</td>\n",
       "      <td>Antisense</td>\n",
       "      <td>GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...</td>\n",
       "      <td>807.0</td>\n",
       "      <td>GAATCATACAGGGAAGACCCAA</td>\n",
       "      <td>22.0</td>\n",
       "      <td>294220748</td>\n",
       "      <td>20</td>\n",
       "      <td>293591503</td>\n",
       "      <td>[{'bits_per_component': 8, 'sub_image_id': 294...</td>\n",
       "      <td>ISH</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       donor_id  entrez_id forward_primer_sequence_data  \\\n",
       "15884     15350     4843.0       GACCACATCTACCAGGAGGAGA   \n",
       "15912     15350     4843.0       GACCACATCTACCAGGAGGAGA   \n",
       "\n",
       "       forward_sequence_length gene_acronym          gi ncbi_accession_number  \\\n",
       "15884                     22.0         NOS2  24041028.0           NM_000625.3   \n",
       "15912                     22.0         NOS2  24041028.0           NM_000625.3   \n",
       "\n",
       "      orientation                            predicted_sequence_data  \\\n",
       "15884   Antisense  GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...   \n",
       "15912   Antisense  GACCACATCTACCAGGAGGAGATGCTGGAGATGGCCCAGAAGGGGG...   \n",
       "\n",
       "       predicted_sequence_length reverse_primer_sequence_data  \\\n",
       "15884                      807.0       GAATCATACAGGGAAGACCCAA   \n",
       "15912                      807.0       GAATCATACAGGGAAGACCCAA   \n",
       "\n",
       "       reverse_sequence_length  section_data_set_id  section_thickness  \\\n",
       "15884                     22.0            294215359                 20   \n",
       "15912                     22.0            294220748                 20   \n",
       "\n",
       "       specimen_id                                         sub_images  \\\n",
       "15884    293591387  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "15912    293591503  [{'bits_per_component': 8, 'sub_image_id': 294...   \n",
       "\n",
       "      treatment  \n",
       "15884       ISH  \n",
       "15912       ISH  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ish_gene_filter = section_metadata[\"gene_acronym\"] == \"NOS2\"\n",
    "nos2_sections = section_metadata[section_specimen_filter & ish_gene_filter]\n",
    "nos2_sections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "eae6ba7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "nos2_ish_section_image_table = section_image_loader(\n",
    "    section_meta_table=nos2_sections,\n",
    "    section_data_set_id=294215359,\n",
    "    verbose=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c1ae9e65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bits_per_component</th>\n",
       "      <th>sub_image_id</th>\n",
       "      <th>resolution</th>\n",
       "      <th>section_number</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>primary</th>\n",
       "      <th>annotation</th>\n",
       "      <th>boundary</th>\n",
       "      <th>expression</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>294215361</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>21</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bits_per_component  sub_image_id  resolution  section_number  width  \\\n",
       "0                   8     294215361      0.4945              21  15040   \n",
       "\n",
       "   height                                            primary  \\\n",
       "0   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                          annotation  \\\n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                            boundary  \\\n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                          expression  \n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nos2_ish_section_image_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bbbc0862",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/primary/293591387_21_294215361.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(nos2_ish_section_image_table[\"primary\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2b8aa4a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/annotation/293591387_21_294215361_annotation.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(nos2_ish_section_image_table[\"annotation\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6aeb8e6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/boundary/293591387_21_294215361_boundary.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(nos2_ish_section_image_table[\"boundary\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "819b6195",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading image from: s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/expression/293591387_21_294215361_expression.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(nos2_ish_section_image_table[\"expression\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be7f316d",
   "metadata": {},
   "source": [
    "## Downloading data for local use\n",
    "\n",
    "In many cases, needing to redownload image data for new analysis sessions will be costly in terms of bandwidth. The `open_dataset_tools` repository package provides some useful helper functions that will download images (and their S3 storage structure) to a local directory of choice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "925eef31",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "from open_dataset_tools.ivy_gap_utils import local_section_metadata_loader, section_image_downloader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d4ac28ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading section_metadata.json to /local1/IVY_GAP/section_metadata.json\n",
      "\n",
      "Saving image from s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/primary/293591387_21_294215361.jpg to /local1/IVY_GAP/donor_15350/specimen_293591387/primary/293591387_21_294215361.jpg\n",
      "\n",
      "Saving image from s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/annotation/293591387_21_294215361_annotation.jpg to /local1/IVY_GAP/donor_15350/specimen_293591387/annotation/293591387_21_294215361_annotation.jpg\n",
      "\n",
      "Saving image from s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/boundary/293591387_21_294215361_boundary.jpg to /local1/IVY_GAP/donor_15350/specimen_293591387/boundary/293591387_21_294215361_boundary.jpg\n",
      "\n",
      "Saving image from s3://allen-ivy-glioblastoma-atlas/donor_15350/specimen_293591387/expression/293591387_21_294215361_expression.jpg to /local1/IVY_GAP/donor_15350/specimen_293591387/expression/293591387_21_294215361_expression.jpg\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Change this to a location on your computer with ample space\n",
    "local_save_directory = Path(\"/local1/IVY_GAP\")\n",
    "\n",
    "section_image_downloader(local_save_directory, 294215359, verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c74ae5f3",
   "metadata": {},
   "source": [
    "Once downloaded to a local directory, one can use the `section_image_loader` function introduced in the previous section by providing a local save directory as a `local_save_directory` parameter like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d49fb648",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading section_metadata.json from /local1/IVY_GAP/section_metadata.json\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bits_per_component</th>\n",
       "      <th>sub_image_id</th>\n",
       "      <th>resolution</th>\n",
       "      <th>section_number</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>primary</th>\n",
       "      <th>annotation</th>\n",
       "      <th>boundary</th>\n",
       "      <th>expression</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>294215361</td>\n",
       "      <td>0.4945</td>\n",
       "      <td>21</td>\n",
       "      <td>15040</td>\n",
       "      <td>18080</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "      <td>&lt;open_dataset_tools.ivy_gap_utils.ImagePromise...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bits_per_component  sub_image_id  resolution  section_number  width  \\\n",
       "0                   8     294215361      0.4945              21  15040   \n",
       "\n",
       "   height                                            primary  \\\n",
       "0   18080  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                          annotation  \\\n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                            boundary  \\\n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...   \n",
       "\n",
       "                                          expression  \n",
       "0  <open_dataset_tools.ivy_gap_utils.ImagePromise...  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "local_section_metadata = local_section_metadata_loader(local_save_directory, verbose=True)\n",
    "\n",
    "from_local_section_image_table = section_image_loader(\n",
    "    section_meta_table=local_section_metadata,\n",
    "    section_data_set_id=294215359,\n",
    "    local_save_directory=local_save_directory,\n",
    "    verbose=True\n",
    ")\n",
    "\n",
    "from_local_section_image_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "99bcc6ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading image from: /local1/IVY_GAP/donor_15350/specimen_293591387/primary/293591387_21_294215361.jpg\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.5, 15039.5, 18079.5, -0.5)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KMexwrqUUK39EHCVPwFK3q4JOdv0ZmIYdaKHgoZ4IIVLznurWtmGJUEqGmpbNZ1i+NhgIoBnKQBpvaDd/RWg/g/jXFK4opdi2qArlkbj6KT6sSNNbapkIzTXgEBcRkkHSpRC6l9QyUsbfUjUgLiPeeJXQXuAEajmg8wfA4eIGFcV3r6l1/kS4CULUB+On4ucggnMtEBAyJQ841yHMVFkhVGoZ0PyRUsZlSwffXPwRluGPlkn20LvQUosscKpQNeJI9tBUXYicBFIpVUC81dFV8GFl7C1KDDMigg+eSsBqcAzTVpYd32G/djZ0iQaVhqaJdkOqonW20kvVYLVaF8zB2kGpBdWldKt5qakF5xQXVoa+LN/rXESXheNjaycCitRqD2EBJCJlQjFky1hjv5R/BRfXeKlWXhAXiHgACtRClYiywuHBX5PzgFYo+Y48H6hybqBE6BGd8W4CLYT2ypAVaReARal1wku261scKhAaAyfErT5tGjVl6nxjDxaCdw1IS5lnDJ2zndctAEZ1Pc4HXFgToxAaIU0TNd0Zpy3CnKDm+6XssoVbF9WBC1s0fkG7+ozYXOOk2EMpZzgyof0c8RtKMeKvLo0/4u3Z8S+R8kipyuHxzfIAVqoqJRekPuD8yvo4nYzkCxtEoiFa7gLxHS6+gHKCUqHOtqkDSEMMzY9fDE/McB5uceEc316gGogx2m6smZwGa4hlgUC9HYu4DhdWKM6aPhXERXIJn6QKAM77pTZ1KJ5aE5B/z5KiOIeVJ1RKrVT1CGEh7oRS7SisCs7JUjKZhMI5g+qc/P57VRUvVrcbqedxrrOm1AW0ZnDRkBLxlAxVIARvD4ZTK/WcoOSFifb4sEbJIBHvOsBKM3ErnExGAmkixjWhO182imTXq1rDmvNg5YEYN4Gy7HTH5Z541K3x4dxKr6p43xniVUeqBECR5pmVaG6F0wRuC5KQeIbUE44Z58+tVBRvCFC+Q8tEPv0GV+/ouob19X9hQIUqTdviXIumR1SFEK8QCWjeoeWdNfP5Eecj6IQTpVQHdaaOv8UHh5NHVEDLiXL6B0L7nJpOuHoi1xWPt2/oVhefZBiC2kL3z5G4wko2j7qOWublOzIurBA8IW5s0aV3lHRcTmoQH9B086csBiiqtOtnqI44IirtAjcGak340JHTEXGC1hmqyRk0n6jlSPAbSvVUnRFRQrS6z/lgzV1lkQwIVa0+V7wtojoZCiUBXKQQERexumxAXMDHLaWkBX5dThjyIgMpuKUUytnqfXv4n2QVgmpCq9oFXviPXKyJr6U+qROAjjSfrNwqBgpXAsoarUoVjxIADy5S0wMhrpcFEah4qnTWgIvph0SE6XRHpaXWmZyNwc7Z+gknQp3f0fQvEZlBxaDDWsF5SjmiKCkVSnWIzoRgDKv3jtC/pNYjOOOAqBPSXFA1GP+xNNfW1w3gn1PyRwqdySKaSyun8g7VSuhf2CPjIlIfrTehmL4ovjD4GmU+fQC3otaZfn1hTX3YUsuM95fofGensYrBuc7hfENoLzg/v/qEJC3IKrHdIiHgnr4gLaJ7qAOn3S11OiDhHC2n5aSJ4LfLez99QsN8/7M/bTG4hSgS51AfQJPV2eKo5USebpaeQBCpiA/UMtoD7xy5TpSiJrqrBVFFXY9IsyAlilIR11LzDAS8t/863+IX7Q61GmokCvlIoUfrTFWHd35ZgE83p110VJ2dLy4sEGg1sqiqIUxgOypWTmkt5JIX1jxSqi5IVcLF3hY8FS/VWGoVKoGidTmpIPjOEKbmOaWaYE9rhTKRUgI9kmtBc0ZrIHRnuNDj4wVOjE+ZxslQFWlRhDQfqNpRq5GJLD2HD+eIBNDTUkZ11ksg1DKTx7dGbKkBEMgZTjPiMIZYd6AZoeDjZtlgLvDNMyvRVKl5h/huIRoeqZpxzRUuXhKbK9CK+DW1JJzfkHOBsoNyZ9dBsp1cfovzW0BxzXPytMf3n1HTyTa6MiCaiP01OT0uSJBQ80xVQWu2z7pou/LpG2ugyw3CgI9nhObC9GQKofkMkUo+/B0Amh/J6U9Ck8SQoPCMWqLh53VCXSSnhA+Rtr8yjUm6RWW11OcRFzpqHcl5xIdKrRGRnlQS3gks+LA9kHFhpI2HKHmAopSSl97CjlXvPXl6xPuVIU94VAslHRDEfmcxUZ7grb4sIyCL+E5wXgghUCpMkzW8zrmlr6nW0ziHuMDTQS0uUnM2EZ5r7XSUGZWAdxXn1tRagZ6KX+Qc0R7aag26a54Tm0CpfkF3rHl2AjUf7RrUe6oW+h7QgizloslIlDzfGTOuR+pCaKpWezh9Z/Wz9Fh5a2rdGJ9TRmt2cRvwAZFMnW8ZhyNVGlwwDQ8SSYdf4t2TCDGhOpFKYyRkKTgJeKm/r901IzoyHN4hOGreEdpnhP4vDMTAo24FrkXLCZWGqhmYcfESXENNDwZTO4XyAP6cJ4VzziPiV4ha72O8FLgYQBq6bk1119Yv+I48vkfrhLgV0CLx2ha1OggXf8Ji+CQxBscRnfdIWONwVj+L/yR9qHTgnGmJltpCAKczPhgKVcsOJ4maHqh1xruA6ADlgGKIiXMe5wIVRcRKMVXA9eScDdNf1KCGdnlCs11wccH7hdhTQxVqnXHiKfXpBkKtFRcC0zgvTLL1Fs5H/lDeLE4WosxONe8cpSg5PzWhBYgL8uGoahIUVTs5VQNS90aAqcHQ3m+tF/Id+BXUI7E5R9VTtcH5NeLW9vDUkVpHqkJoLvAugGScRERHTIXqjaUv1TgH3y4bw9pOYDdRZY1wAirObeyahAvwa/yirs3DbxDf0Wx+SuGSKq31USXh8h15/EhcvbJyy23tZ0mEMqB6omk8+IamOQe3MgDDteB6nF8tUpRCmR+p6Q3it3jnKdMP5PkOHFRsEfpF1wfgQ2t6K/V2+tWM+A24Zwyn98z1itN+WJS+LGBDJsQekYHQvCSnPfIH9/ZHLQbFoNM675mHCXRGayLPA+iESMBJi5aE+GZBNFq7+WW0ujduDCplxrkVooKLF/hwhuIM/nRrQKliZU1Vkx0475cdzy27EPjYUNSRphM1n0w8px6tdXmAPVJH6sIruLA19KrUhTBy1kA7oW2FWgtaRoTCNJ3Q+nTJKrVmnAg5J9xys2S5Juo8FQ8SqPmBqpVSC04cOVdKmYyziK8WKXXAh+fkMlq/Ukbb/aWxXqkckXC1bApHNN+jVAMfimHvVWw3LLSmxXLWd9UymRdDFK3D0o/EpQ+qi0q4g7LDScWRqFrwcYUuD6gE4yvUnYNO1Pl35PTIdPiW2F8zHO+Yh/f40KOkZedNlLTD+y0uXlHyCWECH9H8SE17Trf/LWn8gJZMcG6RfQjOGYlZ8y24njLvSKdvcc0l1LJA9/YUlrTHda/R5RrXdKAcf0fTX3Hc/T2n3TvSvAetJu70F1YeiyeVEa0Ddf7IcXf34xeDiDGYuQaKtFay6IQLspQFZoopLJJZoOYDOr2xUkCMBKs4cC2VajfQqvSlYY4MY6YWKCXB4qFQtUYVdNHbCKIzedyZwEw6RFYYxr2Yc/xCuok9qM45SlVSSsY2LxdY68x+d6BfbamlUNSjEql5Wm6CgBqDjiY7wVxjWigfTMZQzdgk4nB+gxPF6wl9Kq4WxqiqydCdE1RMglIruHhOqRXxrZ2UWhcZAbhwbt8bLnCxW4xJgg8bNO3sgdcGMz1VfGzR8kiaHqj5wTYynZdn6glAAJX10ph3iMzE4ClpD743fVOdlpM04+Nnpjxef0k6/ArnN/j2hd13FTTdUqZ7kJVJSepEPvyKNLxBNFPLhG/O6bY/o8qKmh9R8Qbzhg2hObPrUwJ5usOFa9r+lZU4TGBFEeJayrS3f0eo6c5UtrMirmN99oJx9xua9gJECKFBRBkPb/DxFX5h4XHrT1Drj1oMLFV96M5pokP8Cs23/J4R1aV2hZynRSjXo/G5Ye9OqCUxHY+IBDvmUWoZrezwnjLdkLMRaF23MLhhjeO0GFLETiRpTfkaO5zzi1TDvAsi4HxDrbPh0urwIuRc7H3WivfetDpaSGlmtbb6vpSJkostJrGSEM0LmlUNJvXBWNu5WBnktvY+nSPnhEoDBFw8M7GfmIRZ1Vmj6xfwAKWJVu6VPC9EYEX8ZmFxj5T0CLWQ5wRlQkvG+zVVizXYbrXojMyso3igNfDCrWyDWNA577LpiXhcHqxArYE035NOvyHPD0i8xLmFp6kD87D/BIuKXxPaV6hE+s0lTgtl/IiWEde+QuIlob+2E1g8Uo/41c+ZpnEpZw0hDOxAwlKK9abWXbbEMpqgLo/31Fqo5UTJgz1XTw9o/rgoGAB1tshjQ0kP+Njw/Mv/3NAnFN9ckPNEOn5jtVZYI75lfPxXrM4v/5TFsKBbOiG+AU3koggjLkT75fESGImxs0Wi2HFbTohrQGZjjLVaE0PCFKtCmo+I71mvO6omniyRJSdCe7UgPoL3/fJennQ3Twt1kSpoRcuEVtMdGer05DQzA4mWAkszajJtqCmhZUKct7/jm4W+t78vOGrNJivRYrqjak40Y7obYmysqRXrRbQOdoqJQ8veDpcyL2y5INLTtL0J9RbnmbG3BSSa6tWZitcQGOMrcjpZGejXRpTVyT5bTWi+RWSNl2gLU0ycdnx8i5Q7tDqDZvELIepwkhCJOGbq/EhOM4We1cZ+Xxr3iKvkNJKyLIjbhO9eo9JR055aHinTDSFuGQ+/JKx+CjqRsyK+x4nHu4nYf45vnlG0UOePHA7TE0hK3PyETE9/9pV5IvIDqjO6nNLz/IDrf2Z9lsAwnAj9l+TTPZqP3L37gX5tD7mq4J2nDr+iPf9byvxImR8oxYMGNB35x17/hEAARUu1o1AiFKGkAm5tNbUPeLeYMACcoprI6WQKU5SmiYjocuF3VgosikL82vQ5Pppza3m452lGUOb9W0rNT5eOJ9C45iO1VEKMi6BQydnY5vl0Z9g5kCcz0MRols80Z2ouC/k2EbszSk6UmonBgxbydGswrBOcxKW0wiQNi/EHKinNyyYceXIWZ41WYiGYr4GFzzDLZtVKrYp3aqVlWFPrwgEAEjqqerzvDTkRodYRx5GcTojrMYNiQ0n3dnL6c5CG4+7mU5PoRGn7Blwgz0fD7uuAasF3r0AN7hZNlDxQxm8RhZr2aJnAt2h+RFyx5riMSHNpYIimxUvhENeTxjfE/idIPKewout7xtMtWkayXhgxhxCb54iLrFYNOZlHI67+hn793E531+GaK0K8oOZHu4b5nZGT2DO23j7n+PD3rJ/9C3xY8eqr/5wniyjL0xFWr0GnZVMLDKcj7eV/xpw3P34x6PKAz5jbjTqbayqeGavI0gSpSSvQyXBnJ9YoizMZQM3kccc8V8SfLadEwTmTizpnh4LWAmreBx8cuVQ7hnHUUqiI1fdq/IA4ZzyFCt4Haq3k4ZbQnOO87T1zSgjFmOtSccFD+kgIjlIi8+meedyTj2+Y55FxPJCmAU0PjMPDUqop3lsZJ6JLSAELd5KpZXFtCaRUSdlqdZgXvZHJicUFI/m0Gh4vdsp4GXHxmloNk7dNoqFoMNFZeUBlg+YdNe14gp+VgJZMLXvQmf7qr6k6IYtsXcSh+ZHu7KUhTtJYGejPTTCoJ3I+4vsv8U2PMNi9qQ70EXOkNYBf+oLFdZZHJKzJWex350dc+8pKVq1M4w7vqpFxLi33WBC/opYjsblCxAST3iVw2YCZ6mA5TcVFUP2933tZ5d53bDZb2tU5oX1mEu+8s71HlJIGEIdv1gYHo2zProlxxebiBf/Y64820E+KTDsqC0JaIE8WO+ORos9I2WBHZIPgDZtHwJ2hTLjYk/NTY+rNzwwGV2bDacS3pHGPotT5HsGBC/ZztUIdicEzz8YPVJRSC3m643g40LYtoQnGzubM3fsfaLtmwaYDPjjGw0dWl1+jVYlNoFudUSvGOqfE8f4tLjwDv0LSyYw4AsfDcdnly9IDgHcY5EcFadBa6LqIc0IuI6VUIwNVqWWmVqFqSwge58TMUcCc5dMuBt0iDQHvWmptUNkgVCRukbBFpSE0zyh5okrLPDuDJedFR4ShVSIVCefUoqbrqUe7FlqBRNEW8efk8QeQxog3f0Hs+sUP4AFDu3CQp3cgaiSkNIjvIb7Cb/4WLTM1PyybztE+X81Lv2dlY5ne2+KqxwWscJR8D+nepCi1YT69M8Ss2idxoovExsInStkzHX+HFoVyS8n3dv3rEuwgHk1vbfOs2UokF5YF+Y8XQv8ECbcjhEgUxUuLK+ZYQlqcRGo90nUNpQzUUu0YFVvJtUwm0UBQ19OvGgg9gjeITNUWTB2pKjze3xJiZ81ePAcWCYJiEG8xIR9lsAVTYZ5mqJXhdDKfgDun5IwPLW3f03TnHA977j68Zdq9oWlXDKe98R2q7O4/QhkJYc00e5rVC3zAmmoJHG5/TU2Zw8OvefjwDc4FxuPDonnxdsOdp9aySM75veTE9SBCTgUfOtNO+YD3cSlTTPTnmRiHPaUqEjqgodAQQovSUmuglLxYaNeLfiqBW+PdinZ1hpOKhEBdJBq5FGPH04TIxtAl7D0bXO3Jw3sUT50/IguJOezfk8e3Jg+ZH0nD79Baie0LHt/8d5R0wAVblMGNxNigeUdJd8zTzjJE8j21nBDfkYe31Dxa/RJfGMjgIkZw6iLm66lloo0WClHLSAgr+7Nwjnzq4YxZb8//I6gjEl+Q8wTOk5Z+QJxH5xsrO92apuuoZWA8/ePs8z9hMdhr2H2k6mSkUnyJ1gGYqeKQMpLnB9r+khD7RVmKMYriTbRVnmh/W52K4KQhDW9Ndq1mDLl89gJ1wW5Emgmx+1R+TJMhKylNhHaDViU46NoeCRuunl9TVZiHG0QK3kPTdEzTiRgj3WrN/jBZ3b0YZ3JKTMc7xsm81t4Xxv0HToc75v035HkmNhtqnbh89hecX71k//Hf4oPxE2l8JMSw9CyV49H4DRCcE3wwtEjBcHbvLETAUAYrWxBwHU1sTP48PRrMWwTwqM64eGZoDdWk47D0NMbaigpKNEO8DrA0mz5cIeUeFQfhtXkjVIFCngdijOTxQLP+C0OP6sT2/BklVZxrCGFD7D+jWb9EpOHis39BSQd8s14ssz15eqTUTNP0CB3eJ7rtK2L/FZoeiOufkedHlOWkKwXqSKmGDjl9BGlJ40dyblAULY/G5dQJykRsX3zSF+n8Hq3FhIj5wQAM6Yzkw5BH1/2Ukt7StGtqek/JB0I0GPpPWwwKq4ufmbtMTBcOASdqb1Y6XIh43y71sIAPPDXCiHmWnfMUDD1xgmHs4RoEYowLAZBxzhNCi3eRmu7RMtjp5E2sl+bJakov4Byx9cSmxbvAfLrHuUDwTw65GS+VnCy/qetmNB9I2fDreXhgnM/w+sDpNKEV1mfPcRIIq1eoTpQ6sL9/y3C65zTNxNXXeB+Yj7fM4x2Ptx8MZUsnum6RRteMd+FTAxyCmV8qgo9bENPoajmidbakiwWNK3lE6kAMDUpA1Fk6BwkVK39yOiAUnGRKTXa6uIaaZ7TsF0jxEnREnYf80Yin03emyKUl1y21DvYzCItBf7D0j9VfgttQa6JO7xfmfSR01zTtGSiMj7/k8O7/TK0nk7TEa/rNC2p6iwtn9rO9R8rDJ4i9pgfq/MFIT2+GI80Phg6md3g/m40znBlx6CK4M3AeRSnlYCcOdgKU8e1iJyjWL8y3C990vpygDnEbRHeM++94uP3hxy+Gp2Av5xyugPozSnaUNCxG9DWIoTN5PhpJJUqed1QCzkczWCwnhdNMKbZC0zwucoxk9aF46nRvsGWF0DQmG48rci5kNbjO+wUGxTEezctQtYDzNKtzjo8/MA87ptGgXUENmao7Vuc/I/ZfMBweGIYjAmzOr9hc/Qwn2fiF+sjuYcc46kKMbVhtnyOSkHpkGnbM0wnXnOO7V6y2PcPuHTFGqj6JCZ3xABjc6kODb9cLb2EaKVxA/JmVWmUyREowmbysETHEy8VL8jwuHufZnGtkU2mCOQQp5Jx4Kj1YSDqqiecMmBhN6kFjHmcacGukfUYQbzE2mhhPJ4QDOe9xzRUSt9Ri/U2ebpinGyu5ams+Aq143xviFSKh+0tqOiJ40vCeOr2j5h2a9xTWSPMMlsa+TB8J/c8o6Q7xARFLGIm+IU8fqGkwrdIiv8lpWLwLC7vuL6n5iPoGrUfS+B7nO9yigjDhqzMEMz5je/7yxy8GWxB2M4u0ONcTAoawuBbNOxBPKQec7xadiwnTVM3YMs/zAk2a5dP7iGoiBDPwQ8QHkzlUOTOfdOFTel+pAEpwupxGJr3Ow44Q47KbVur0kZs33+Db13SdoTa7xwcU2KwnDg8fGI4PjIffYW6viroO1YlcDNVJ056sLbXsKQnm02CXSAeGoWcaKnP2nIZASY/Mw5FaIA13DDf/VzRb71NKxoljOnz/KQallGI76BMNTkCcw7vANOXF2ipotWuqNDhMsuHCZkmma1F1hHhlO3xNpLku3MGIhBU1G7lX88w8z5T5ncF14nH9K9R7JKwRyah6JN+YMNGvUQptfw7unODX5NNvUVaUfLS/Hza0669wvmV9+TXN6rXJVMoBLU9lsMltajmQ3SvSvEfa1zipVgHMN1DvF73QlsKVmbniM0JzQexfG1eiswn0wmefnsXYXeOdUue9nQ4yErvP0JIgPZrGrRaTBLm1Qet5j/MXhKbBx/jjF4MJ4jxpHnG+NzZXIsEpWk8LEVJwvrFjXjxaBsTJ4qn1tG0kFbFggSU4QHPG+c42MOfQYri8Cw3zPFn2EIVaHFIHRIScEojD+YUIjKZQ1XxCtKLxirOrl2zPVxRZ0TQb1r3l6uweBuZ6RS0n5jTThJF5VMp0R5lnDg8nDrs90+nE97/8O0oauf/4HYdjpuTMYR/QOjFNGe/BqTn0gq/kDHH1Gg2vOD3+D6R5ZPfxOzM8NdvFyK8LZBx+3y+oLPi70vUbgreEQReuLc2CaAZ3ItQBF9bkkvCxQzEeQlyP44Sqs9NFFYJB1+KF0J6Dv6RW4xOQ3qDImgmrrylscWFFVjFHHkJotuh8i9Yd0ny1bHweLQ8gzZK3BBJamvULfLhA3HaR53hyGsjDd4hraUKl23yGUKnuwjaF9AEnHSFumA5/Ty2PZv8tCXwP/pySDuwfH0njA1puzJq6XEPnPC7EhW/uoT4iYYtvXgAV1RNFHbiNNd1uTbP5iuDbT33Hj1oMT1EuTdvh1ERYaXqkaAeu53Cq1DLjyhGl2AeqBe87gyBDT0rQ9FfgOkJcCBtvqRLUJdjLGcdgTjNTn6aklhvkjSixG2I9SUoT3ge6VU8uhZIf8c6yPMVHqDPTdGCeJ/b7Awq04R6RjrZ/Ta6mEFXWwIFKS652w7vOkY7f0MSOxt2h9UClcHtzxOnEw8f3OBkYx8g8K2W+w3cX+NXniCRq/oFuY5xBbC9J08EWshpE+EkGWBK1Pp0YgZJPVmosDLJSFn6iIJpwiNkWVUFnap1MUewDqoNxNnpCfL/wMCCY/Nk7ligaAEHnR6QW2kYZjx+NPGOCcUfJjzg3Mx3ekud7atqDqAEhzOS0I03G/rol/qbmB7uH+RGcM1Kv7PHNBdJ8DuVkKJEmiJ9Rl4wlccFgbJwRbs4Zs50+Mg0F6gGJz6h5T04nyrxnLp0lCYogoQccwrwEuu2M/8oD4owY1bIDPA8ff8Wn3NYftRis6jXUYbqzaA7XLikRjs32wvQwzRmUEQRCu+HJrllqxkfTI1lESzXlpwvkXBZc3eJbKhUnFuo7TYPtok9yDOeZxiOK8MN37wjBds1aT8R2Q+xfATAOt6TpwDQfSNMd0+Ge436gb09U2XI6Htg/DmiGx8cTN+/u2D0cmMeBNDxyHDfgrrl8/R/Sr45062um4y15euTZ8xbnLd3isDvyePsrSq5MU8/Dx3donWjWP0VK4rR7w2n3lnE0qXctpqatacZ5k4KoCDmN1DpDXR6sqksGkSwEXGuyj7CI+pyjlmEJbm5M1SstlHFRCbeAOemENYJD8wE0EXxFpKWkI4QLVI/M0z3eJ5yANF/g+xfkdAQJFM5wLuKbLTgh52rhDWGzbEpmFfVhtTDZIyWPONeTh2+X/79Dk6lvRaAOvzWlQRnBXxkYU3aGcvmVqVvFU8aPrLeWqO18T003RjZKi18IOhRcHXFhbT1K85Kw/c/I0w1O5gXZBImXTIdvcR5+HzL9IxbDUpiZsIyOYZisRpTG4j5cNtm2LHBp6EBNCyTOE0SXsK26yLIt/OtJc1SfSgUxQ0xV4we6bm3+WS04p/jg2JxdgU48f/2a4/FACJH5eETI7B8fKPNAGt9ippjKdCzkAuuNI+uakm6Yp4luZYRhCI5+syb2L4hhIrYdaTpwdnlOXH2J734CriF2z9Ga2W4bmvac86trtpfnXD+/JoaRqrpknq6sfg/X9JsLU2d6oWl7mrY13zhPydfgnMeHaHZL19vJGTqqrLDgNA8STYfkoi2KmgjNmnz6DSIVLWXxMJjsQnQ0aYwdLeR0i6pJVKqcmU6qDiCVkveUeaBqZDw+AkrKhfnwK0L3FW1nvd047HBEi/aRiAur5ZocUbeENCxCSt89Q2vGuUimMdbbnVGTZZz67iUiQpnemYFo3qH0uHhuG2V+QPOIb6/ozl7ZZxJMFRxWHB5/oOY9aXoPKOIvrCwP58bxlB0SL1FtefK8BBdwwdO0Dffv//7HL4ZP8wIEQtsRmzNyVTQ9gHhysewiXYicWjNVxyXHSFExNtiInqd8o2qK1WiokPlw1Ugrv5j8xcoHqiJiIrmcZnzsaEJkGhI5FVbnL3ESSdOBdHxHbK8o847x+MhwfEe/MqGe9w7VFSE0aHXcfjySU+X+/kCaTiCVrqlcv/ycdrUmyA7HiX695fKq4fVP/xmx27C9fMHZ5TWr7Tnd6gxE6deZIHvmaSDPO2K7RiUQYoV6pKT7pRRRq3X1qX+IBkO73pA2Z/1DHh4WeHYJ6wXQBWBQZxtI+xOgUDXhw5YqLTEEIKB1ZB7fUfIep4KXsjTMBecjzjWU6lBZU8pM0z3jeDL7bgxCe/bPDYiqrfVH9d7UwPkeLXWR0gi+2RorXkfLeS0PiFTLQ5IVzp/ZvXQBFvi1loGKJTDiG3yzNfhaJyhHkIbxcItrv1w2x0IafjDkiMR6e4aLVxZlI8LuMUN8juYDeTyaREcWn8cCqI2jIY7zcEOM/Z9wMvBpLYAI3iuupiUUoAFxS6bq4n/GLYxxAnXLA52WcLCMakGWmQ1mBi88zYCYhoFpmKk5f+olcsqkaViMOY6SPbFtOL+6Yvfxdya8S4nNZoPGM2oN5FLJWVhvLtEq5OGG+5uBtnuGc8owFDMI5ULbmmfYuw7xPbFZm0PKe2J3QdOb7j6lwmloOB2PTHNGpMU312wuvmC1viLEQsknYv8Z+90R7xuGwTEND5z2b2i7fmFAHftHi2I0MMLTtmv7vGCml9gv+UyekhN5fgAKLrSkNJLSjPMtVS04TcsO8sE83O6MKmu0PKBpB/Ea1zxb7stAmg/WJ1XF6YRbcp+22zUln5iP7/Dx2mLxo7eTsf8C6gkf1/jmjDzfGzjl1tR8Yj7+EucCeTqg871B6/UCTXeEeEbO3qyuCt41OL+xlJTpgyVpNGdIVSoRT6LfnqP5jjp9xPse77Fc12lv0TDhkpr3qFb6s2fk6SM13YGrFkBWjtTpB8q0x+ZqjIyHD3RtR7f9U0LElnZPRNB0oqpFKPqwDCtZhm7Y8JLWmizXkYsshIctz1zqIlU23J/FC2HtvelWnHPEp9Ni0a3ExpxyIUCIgZwnhtPAfDrRbl7zBA/E1RnHh/eUMqF5pvEnQpxpNj8lrL5ktd6i9ZGcrfYttbLdCLHxtKuXiIN5uCf4CS0HSh6pGhhPA+rWOPGsVh373USaB7RmcnpYdr5If/4VbW/lzXQ6snsciHGzBAQLc/YMxzvQyvZ8a9uLYNEp3nb9nO0EFN8v8GBjVydsjIiqlba7IDAu11xI40h1V/j4HPCIHkBMTBjaS5RKzSfyfMdTcgnOW7q2eNr+ktPj76DcE5pX4K8o+ZaadktQXL8QrS85HhrjAEKPaKFM90aetS+sNKk3EC7J83tr3kNnqXv5o9lYUUvq0IKPa/BnJsPIR5wr1OmNGbb8itBeU4pS0w057fDxlWmypm+AyaTxCDEoojAXY6BD+wKtR3z7E9L8wHS6oeuf4eMKF18wnu5//GL4tCicJ9cVfoHlRO2GsLDJKg3TdGROZvQJvkHVBHi1zNagiQBlMb+D5e09EURK060AlpgUZwjLUqWl0cKGf/OLf4cn45tI20dSSsyTEYCbdUsa7jAPbeU0OPJ0YBoySqZoRy2RmpVhd0vsNtR0JKcRF3pCt+Z4mMCfsz57yXoV+P5331t/owb3vvr8JaVUizAsynTaU4spRJvGpOw+npvaVSagJc/vqGWg2zw3aFmsbyglmTw7VyS0jKcTeXrEucJT/LxbeilcswgTheq2i3q00q+aTyiPSkPJFc0TWmabwlOO1DoTgkcxT4l3s/2z/wlOjsTuiioX4D3eZ8SdIc6Rp4+g3hL8JLDarJnHO5CGkm5xjYEnZfgeoRDCBTlXhrt/hdcD1Mn0VK4sng+Mk0qmewpxbaSqmFHMBQsxQzbU+dYa4DpQ6xrLzupQ2TLuH/Dd5wAL43xitXnGPE8gE1UtNd41G+bTPcf9PRDIdaTrr3/8YlCWvNJqLimzOlrKQskTWiaqNpbX471JJiyoEdViMgTcgqtnUDE/rljQbQgNSl7OB6tFXT1ZWK1nUbZW5tMJEc/ls+dUHE0TOB5PCJV2tUFqIec9hOf49hrXfkHTPyfnBig03YrY9pw/27A563nx+hXTcGS1DjinpOnEzfs93u3JaWA4PuJDz1d/8TVl2lPyvLjzBs7Or5iSh9AbM6pKyRnNI23bsD03yUmeTzzcHWm2/8xCAZxbykILMRPxlJJRMZlLKhncGd63hpbN9+hiGAKLP0HNDgkHQ3zyEcsaNcSusLIT2Z/hFnWtxem3UJOx6G4LmsnzDsqRUhvy4e+Y9r8wjwVWstVaOe1+QPw5NiMt0nQXlGwScoum9/j1XzKP96i/oOSZuHppWsp5b31SvLYTCnB+S+Wcmh5x8ZI6/4DWSplvcPFyYcbNw63iKGU2HdT0hppn3r95y82H2yVyBuY54WNLaC7pYiUPb/DNOfn4W7wEVKBpHP35VwyHR2K//fGLAbCFICyxLQXSYWGFMf2HeHK1fb7kmbJ4gy07SUEtqcIvrjFDlczCWBdWFiCNe0Jslgx9W0Bl3DFPhXazQUSRcuLjhx/Y3b+laSI4z3CcmYa3zOWMYfeWPM2k5KhlJrQNeZ7IJZBOD4zHI46R9cWFkULdpRF6GbYXz1H3guG0W1L/zCrqQ6RfX5n8uhps6YMZbNrVtSEz84P9jmwR/m3rySXawygRdCQf3/A0XgmUWpTT/n6ZvSC0bWc22FKYUwF/BmrRNeLaheBsESysTOtsRJNmarU4yrbfLqcwpg9zjUHUvlvAkMZykFwgjzuKf0VsPEU60Mw8vINierN2dU3XXyDlQJl39sAv9/ipGXZqEHpsz1H3jJwH03W158T+mfEqZU+plt1U5qPpz5qXFjmUJ3z7GeLPqOkBdWvjoRDKtKNZ/xQfz3DxklL3bC5+ysPjQMm2ORx3O6ounhjf4uIaKaclIhRCu0XETFNnz/8Dfs/y/MjF8Omvz48AhO3XOCmUZA1xTQNadNH3CzaDQZcyKYNUqJUqYniymA7JsnkWs0h9mtriyHlk/7hD84HQnZPmkabbIAIvvvwbnr98zXjY0TStzVaII/v73zI8/o71Zo0LLTHMlGLyEDPAzAxT5LjbM8+VvAQEOElstiu61uOY2D3ck1Lk+HhPmvb4xi0x75Wm6fDREKCu65aTzLwDhDNqUdrOZASbbcvh4YEQFZEVGl9T88cl0dtuXikjq+3VklkEIo6mcZT5jjSnJe0Cy4UtI5YvOlkCOj2KbQYsGjDxK+r0DpFAnnfk6RbBm44s7Qy0cDYfIo33dNvPLPXPt/Rnr9HqKGRDelwkZSW0HRI6tDwSY8O8/wd8syXXDaVAdUo6/QrnOjyPtK01x2V8YzMmtFLTLZqOpNMHfP8KH9c8TYl1/U+pdSKPPxgXoQYJaz3iYkc+fUDcFudXzEMhNoH/3f/+/2AGLRTNByQ/mo+9lsXDMDIlv4Q1WHR+yqPFjP4RCvqP9wxiEKsPztIqqpDmZE4t14BY/mgphZROaJko+WiMMYo4R0l7hiFDMYjNL6dBrYmSzUXm49q+33dsz85AIjihaRtDnsAw83Rge3HJxzffUbIRUaU+x7cvTPSWJ0quhGVgis0L85ydB9ab3rJgEc4vz0gpcToeOB4mYiOcnfeIKvN05O72REkjaU6keWYYEmmayHmyvkENORPXEGJkdf6cWjzzdCI0a0IY6fozhv0dh7u3hNVPmQdr4NJ8QlSZTh+YhnfM6WSyCvH45oJVb7qvWiYLNcDiKfO4Q8QSOeoSmygSltNWzLKpIxa7eUGpBwMAXIs6IU8PIAnv6jJMsjIffkeajkg8o+n/ijz9jjI/EJorBBsnEPsvURzN2d+Yt4CjeUdKwnefU+qJMn+A8p0pbeMzUPOOlzqQTt+inIh+i7hzSxoZvkXFdnSwwZVl/mBmJG0pw28obgXOs7t/R9Padf7f/G//1wv9JYzzGdJ8vgj41kh8TZUV3eY1LppywTUv0PTeZtT9KXIM+P1aynO1qZx4VM3cXmu1m1Tqgok3aBVUHU9gUS0OF84ZTwNTdmiZQYSUT5TqyanYCUK1sonKOM2W0gCE2Dxhu4hUq1sr9Ns1H96+YzzuyWmm6Z+BRI77HSXPfPxwx3jYk6ZEpdqD5K3OFh7wwdNvzmm6FevLa9p+xWa7ol8F1psVMcLh4ZeU6RtOu9+wWrV8ePM9x93dQpo94eD3FpiwEGr96iXiVpydRU6nkXZ9RduCk0jJAw8370ETvu3p1tfk6UgeD+QslGy7mThPCMbuxmCbSp12xPVLQnuNE0sUr7Wi6c5GipXJlJ9hhYuvqGVievzd0q9YBmytEc0V114vjPYaac5pulesz35KzRO1row05SmF3FL1SkqIgpBBB9uYNJkxKx0Rv15kOBVcR5keEAxEieufQD1ZBH4aKOmDeaynW3zozQTlVvYAFyU0l0C/MPIzTbglxkpwiTYWyrwD4PUXL9D5jWni5o9Inah1ITPJhBigsqScy6eS/EcvhqeXNFeIj6gGnM/UXFEcTpNdOG/SZJubYPHwqpBTYU4jTdcQw9P85IqjEqOj6xucOJP4lsw8zdSSCN01eZ6XoDCb3BjbFdOc8d6xPb/k4npLqR7nEmkcSNOJbn3O/UNm3WdSTsRmi5dCaKBtM5dXE9vz58Q44v1E31lZU0rldBKci/TrHu/Mq9tvPifPiZJHXrz+gq7fErzDB4f3jsPh3soagTnl5UGGdvuKto3kNKPujPH0kdBsaTsHBGqeGA47fPvS6mIx2DGNj8z7b8C1yxRLGI4HfLMx6bYscwuWSZ+EMyotIXa49otlQVVkGezi4iU1n+zBrgr+zNhrw6bI04OZoB7/H4gDL0eoiVoGYEPonuHjFnHFTPyLLLxWm+zj4zmh2VpZFy/J0w4pjzinhNjRbH5GVSsjh/0PlsoRXiwn2kxKI+rPjAwsgeoc0+GBJF8gJNCJZvW1IWo+4jkyHN5aiV0NDRQdEbcmnb7DSzbDURoo+WiB11oXC+qfUCaJiAUPIOQaSOPRdg3p8XLCCeCEEFqmwfy8WgZcMNxX64gPSowdfW9TZNL8sETSBxyK9/JpJps4RwhK13Y4Bw6LZDnsHkz6jGO7PWOehfF4awngww39Alv6uGV/f8t6e0a/3rBZWTPa9w1NG/HBI35Dmh8RjszDB0RmyB9YbXqaeCA04ENPv3lh0G2G0F1y3H/AeWj7RYsjQpr2XDz7mlIKSuW7334HTpgPP1CmW4McfaHfXFFnK7OqdKTZzDm723d4H0jH7xC1mczDIBA2lJI5nUbG00TXLxOG6mw5TUuQMSTydP8pSIFajJArB5ysLZqlDCgdtc6sNtcErwjdEnLcLCrRW6psPmW6+vYZtTbUOlGGbwwFW8ZWIRH8xpSAWihlMsAk3aPzA7HdoFTC5p9bf4iwv/kHnO6IrWWuio6WJxW3iM6UdDKRH4407BHv6DpPzroYvI6Ap6Q7C2bYvrDT2QdKtn4LaQjd1dJrWRBaOf5AHj+iZW8i0j/y+iNyjCefiBhSpIGUEtY2rnCSwPVUzTT9ympWotW5+YD3Lc4JTXjK6QmEZoOr9uFUsR3KGfTq9GnSSjVl6tMYJk1LzwDOO1abCx5uH0nH3xEbR9tdMe5/4LS/Nb5juCcEx+HU48o7irLwD5mcLMFjPLyn37xCXU9N96ThPbFRRHdUCj4Gur5H9IRj4HQ4sbv5H9A6WW5r2RG8Qb8xtpz2N1xfwzw+LirPHscj82RxK6mMPNw90K82xO6Kptvw6qufIy7Snn9FGh7xIdCtG3yzgpppu0gIhTxPn9AsJ7oMd0k2N0Kbhd0VcMbqi2byfEfsn9tsBt8S4zVlnsjzYSEOEz72uPoRXL8Eoj1YvV+TRU+qfc48/oAw2jRXHDr8EtHBVLauX5Ctl+Qygzi03FLSDSzQ/OWrvyF0P0Fcz3gwuUnNjzjXUdMt7fo1uYIPgVIjLnYogUBB3BYVD9WM/1UCTffMULNwYYEP6YbYXeKbZzgmfNiYbdYHHMYRudD/ARr0IxaDrWt71bomePA+4iXQryzfp9bKPB55uPlITgXE8j9dMNvgeLoj5ZFaLDW6ql/cSmLM72ymEFyL+GWxiNiFydlkBjUvAjwjm7pVRxMs66jpzsjzO06D53ispNJzuPst43BHt1nh4jWeW9rVNXUZKOKaZ7T9uf0eF+jO/4p2dQnqGY8f6fprxv0b0pRxqvh4xtn5lm51zXS65bi/4/bdNxyPO46Pv+N4eLdM6pko84FcG3C9LYSaKMNbVHsuXn7OOOz53a9+h7jAcDrgBNJ4R1x9gaqhbILj4eOvib5DdLaGsU7kPFvaQ00cHgdOjzef4hRrmanZJitp3tluXk7kksx3roWS7sjzzhS08wCaCTKYGy9emudBLbe10tiUo8ZSvFUaak3Mx18b+bY01/Pw0aQV5c7Y8vyI+CvqfGMTd/wZ0ziQ51uoibab0fn7Jed1tvkJdUTzCd88o04/ADNp+Jb+/CdIuED8GSmNiC6ToxYjVNNcUmW1nFR+Gbhp5VzsrrAZejaP25IS/6TFIE+CCbq+Q1lx3H+klMQ0Ywl06US7uuDi2Ut8Z/MCTPjdgHTE5iktI5DmkVqhlkotSk55gSjB+YbjbuLT/Acq8zQxnR6s5n1alsuwkW5zSb/+jONJORyFbvsMdOLDuwe6zVcoK07HExJ6JFxQ1SQXrjwiosTuC1zo8M0WHzfMpx3d2ee025/jvWNz9Vf06y0aX6K64nSqVtJVNR1Se4l3CecbGq82X8GtGIfHhXM5Ulmj0lP0mqaprLqO1eqcr//ya7RW+vUF43BkOBzwTW9KVh8ZjwP99jOm4dZSz71jPD2wu3uPeM88jYiDdr21htkF0vRATrMNIHTP8U2PD+2ik1wb0x2vUXfG8fGjzdSQnhJ/vszPSLg6UtLI+PBLG3lcjogLVH9NnW3mgudIe/GfGJnnNty+/Qfa/ic4vyGEc3z7fCHkzm1Dm+/w3mY7z8MD0+kA8TW4l+zv78z+mW/48M2vydMD66uf4so97eoV8/ENOT+QF/hWaanzB+b5YIuinvBSeLj5BsHmglc2ps+qJ9rtz1F3bUPSqz7JHn/cYlCMwFGtbC4/N5g1TwsjO5s+3HfkaaSUgtOZUmZEbLaAc4oQzJGmNgfBSaXOt+ZdEBY8WNBqGv/T4/vFVQch5MUYtDUmW3VpIEGXIKvLZy+ouTDsb2kbz4tX58zHdziykTL5znavNLNaPUfiGd7blKFSPdPxHcfHj5w9+5LgJtqmUqZb0uktaX6klolS5mXwiJ1c3o00fcTHFbE5p6ow7G9x8RzvLxjGif2pWRLHz8jzW5RqsSmaGY870jxSkk3aCc0lsVmbNyBEfGzQPLJ7PJJTomlXNI1je9Yu0LRDiYjLzOOOqiaejE1PaF7gnY3CmtOEuDPS6QcKDSKVEFb0q8V/QiXNH3FxDaUyTzf4/qe06xek6QjlHsoD3tclOK7SrF4xn763E4SZ65evKTpaOaOTyW2WFHYwWN6iO3uqE8LqSygDw/BAf/EzDo877t+/4fKzv6YUzzTucd3PQAtzUlx9MIl8PVGlJ25+znR6gAW2l9CzPrtGgRAsFaRp1rYBVBhv/xXImjnt/1iV9E9VrQree6DQra5J2bykeTxy8+bXSGgWj3OkDTYv2Lr3DAzMyTKSUjripeDbS6ZxwEmlaaJl7Yiw3m7w3TW5jBa7SmQaRoKbWUD1ZXWCb1fkfGQ8jPZgVc/xOHO29Zwm8xc/f3lBbC5YXfyEw/1vGEaP81tynqnVEZsG59Z0vQVzzbkj13YZj5sRzXQttI3SNhmkkKY7hIb5eGQ8HRbUTIjuSJlOwETVNZQE7pyUK6o903TkeLxhd/Mtm4trmm6N857Y2kPsXODh4/eg0K3WhP6Ki6tzRDLDaUTiGYdDYRpH7u5uiEGZhpHYbkjzCV0slzUfQNaGDHkL/3Xta5xzlvIdWryf7GHVQtt0RDcizQW++ZJy/NfUesDV70j5gapC073ExSvyuLdh6uGCPH5EKPj2FXW+Q9WT8wGwST4pJ/L0gdBc4+IV4gK7uxuCH8njHdMwLBEylfdvDqzPnlHzgba7ps43KIl++wIJ5wYNuxYH1LynaVuUZZxwujHZjxbAM5/u8d5MTGl6IKxfg0ykYccfs7r9EwIB7J/H4wnnAqVm7u8eiW5mOD6wvbgwNnEJDC5qrK9QLakueeYh2w7X9IvRXzkep2VSj2WWIjYPrO1aa+amgYqnaSMpVaz70aXvwCydH3/J/c0bPry9wftAu3oJ2tL2wnA6Mp12JqefvsXHjn6zYZpnpIL41ij9oy4J14H94yNtNE4lJTjt94T2jP1uTz39AsGTppF5nkEg+Mhx94gLl8T1VzT9OS48W1j1npwr5JEQqtXfEthcfvHpwvpgc5AtY1ZxoTW0SJXVek27fobEHsTZuDBxNG3Di8+/Irb9J/83bgXYdFDxFdWAamQal2Y/fTTZRplJ84lSKqWM1HRPlY55sr7MNWdUv0H8NT6sScMIYipaXMQ1HdNwMn1ZfEGe74ndC1x8hugE+R7xl6icIepIpzfIEuhcysD183M03ZFpkHrk3a//Jb/6H37H7YdHxAWa1ZqSJyvNqs0DEXGW3FdG08XNN2gdmE435nPwV5/kKq65RuMrFCjzAe9smhJuS9et+WMd9B8V6j0JS8fR9PDeVy6fXSNxS7N+TpXWQnxrwQcz8oTYEIJDMQJGxBMDZnZZplaeXzRLdOPCMuMIzroNkw5ExvGEzu9oN5f8vvuxo1Dm78n1mu15z2bT8uGHb/EyMwwzw6CEkJlmT9dHJL6m7T/Hx56uX+Hbc0qp5PlI3zwSvJ10ZxcXnIYRJxPt+jXN5nPSvMwaW31BkMz67BU+bCglIN6sl8fH9+Q5kecT4/7dkl+0w4kyHd8TumeEuMW5QIzNH3yW5UQ821JKYbVZE4JlxooI8zShRehXa0qObDZbLK07gHM0q3NK2RODJfnZ0BKLfSzqydMBCTbA3TKgJkq+wyGE9jkSNpZgMpkfe7z7BXnaU+YbyvSOtmmo4xsDN+rI8fYX/Pbf/EtLw5AeH85Iwz15+gDhjNheAMJ8+Ib+/CubFz3uLP1iiaqp2tG0kfPrn+Hbl/zNf/w/5b/4X/1XVHWkaTR2evqAsIFFd1TzxHi6sWej/4zY9OauU+X2xoSjVZU87U31WwswIJJx7TWnh+9tutOf0jOILA8e8M0vv8WHFT6Y8i+EiGOga1uoYjOUvUkmnjZx5wXv4ey8QVxFZRnPVJKdCqrUsiNni1uvWtFaKMu8OK9H5rLEr39a1IuUo8w0rR37Vc754qc/4fHhjsPDb+i6jmmAthc0TRRtWZ+ZkaWkI8fD0Xao8UhsL1ACx/09Tiptf8HpNOJDQ7++5OH9r7m4OifniIYtDx++oe0i67NLHm/eEf1AbM8pdcfh8SO1PpLnAzGumccDWk/kOVOqzWG2D2Kf4dNnXpx+4/CIloxzQskD85iZhzvrExpHbC2KpaZH8wo4U6M6UXyzRsIaJTBPt4gWYtejBFJuLdW67EBb8A0ixSpPMvP4gDihv3xG0z2zktivkdBRxrdWGrnI/vZ7vvwP/ytKbdjdviMNHzjc/Rrffg7SMg53TKeBsHrOOBwo+dFk/s7Yb5uvlrh9/4C6ntdf/xVnz/6K7dXfsP/495B3dP2GmgeTlfgWIViuUvOc0L1mGis1740jUaWMO6h7tGbSNKG5sL97g4RrQvsTQmjpNs8Mnv0jr39Sz6CqnI6D2RSlNYVltPFQ4jpiE5hG08p4by41VcvlCY3l/bvlzVj65GJflILK+WLHs9AsEVBnjXq3uWJ99pLY2pQXM0KaZLbpnpPLidPxyGqz5u5uoOiay2dneJmp9DTOgn5jsLkJWmdiXDHuvjeFp8uEdosTpenW5JTJ80C7viKXhNbM+fUrdrsjTWfDzt9+/5H7D+/I4zva7pyiZ0BBKHTrK1JuWG16vNwT5AO1DMzjPXfvvuNwMJebbTRPkTFwOjwQYkO3ekaaRh5u35HngX4Vaftz5tOO2JgZZj68I432WXzoKbWh1EyeH6jzR4bTkeAErRNeE3V8T9P0Fq7gLnHNM6pGSvWUvDf1bv8CQQjNXxDba7PZlpY872i2XzMcPqJ4Ll69oOta8rzn4XEmtJ+zff5TRKIJ4fJxESc65sOvKJxZnE7aE9pn1DKD71j1asl/tOTxe/J8ZHX+OfOcF3usLWJN96TpFudWNE3HePyOpj9DNDHubbTX1YtLarHprU1/RdMFthfPKXlmGm54fPev8WG1bEB/Spm0RNKLCP/5f/kfsLs3TYjWRJpPNN2W8WQyCu8qKWdUG9K0Yxk6BHUy0q4MoErwzRLQO4KmT34A0QIsUe2LrmlYEvP2998uwVxPPZAQ+0vW26vFID5wdvEM7yE0L5mT+RgIK0JTmIc985zJk+mKLl//pf2M1TNyHkmpEmLDdHpHiIEQbIG40BCaDTrd0KxeUEvg5//pv+Ds+iV3H+/pN0IbDzStIiUwjwfWm2cgDZUzSlHa9XOmObM5e8b28uuln7AgNFQtijJ0zNOJGBtivwa1QOM0viM0HalkfOipecZ1VzTr5+TpAVmmnxoZucaHS9pmTZ4+4tyKSm9+BCy12/wMkTw9kuYjJSkurGj7DSo94/4XBoOjtOtXNKsvgUgb88J6b/C+p19fcH3doXQg50zD3m5MeGYPMQ1x9Rm+ubKhhsWRp/e07Tnz8S3N2ZfLjXSIf4aPPaIj/TIMvaQTTk+oFpxfMc2WcK7zgdhsIF7QbV8AQr/9kuq2pPnAcXfH4813SOzwrrC7vWHz4j82JPITUfBjF0OtNnZXoWnXOK+UMtscg8NHYrNhvWkWpMLhFmOISbwnRK351XJEpKE+WTx9u8wVC5R8u5jki0k/FJrgcS7jQ8NweM+qbznu/nC6u9Jtv2B/94aua1mt15R0QMtIrZPVlPWRGIWH97+xmta3NKvXTMNpyfuBuoQQax35+PZburZF8kecPzHs31tj6zs2L/6Wh5s31DKQphnHwOWzC0KzJfYvyeMH+vOXnJ1VRBK1PFJpOO12rLafsz17AQLbszNr9JYJmwDj4QYtBe/k00TS7eWFNY2ck8Y9m7MrBCHNcPfml6TTB3K20U9tf0UtB6aHXzOfPiD1Hh+u0fKRuH7JNClaJnINaK0c7r9lnjJtf84P3/6W3f0dNd2STjZwZD78O0puGB/+zmJl/HoZrRtYvfxfgk7klNhevqLm96Y8nm9IebYSj5F8+gHSHq93NhCxKi5YAIHvPkfTO8D0XaQ3UAeb9SEW5ZKnW0DxzRVKoF2f4+I1zfolWhPHu9+RhvdYikgkHd4iKKuzS1zobahMueP69V9CtSwvAyH/hJPBZpxZ3xBjQ+BILD/Qdh133/8dNY/UGui6sJBDSh534FfUMpLLibbrmYYjpRaolfl0T8kjuYD4ntA+Zx4f0TKQpjs038OCQDhX6FYvqbXSr69+n9axvELsqfIK74V5fMB54bB7oGlNXh5DIvYXxNXXNLG15rQ8cv/2XyOuYx7e48KKNH7E6UTsX1IrxGaLC57j7sPi0a2cXb6maDT/Lo529RpHIA0fie2Waf8d4+nIhzdvmIZ7+vZId/4lIbRsztZcPvvMIN08ATBNJ+ZpAgk4GRn37zk9fg8Ch/s3NO2afnNBv74yj0JOrLdbus1L7m8fiG1n4WLBkacj/cXn+LjBhUuqi9zfzpAfGY97cMI0JIbD3kxR+SPD40devH5O8C3iNwgTOn+glIZ29ZmVPs01ZXyLcGI+vSHPe9Kk1sMtcZbe24lVhm+Iq9dUdYS4At1R8sT+5t8QYkc5vWV3955hf0epV5z2d5R5RH3PNHzAy4QTa4pXV/8T8K2V23VEdMDFDTmdQDy72+/wMTDsbwDBNw2lZIbjSLu6wIlnHB15vkHELVle+j96fv6/XAxQn44W7/D6gcwK1ZYXX/6ceXjkdDww7H7DsPvemMzmkhCv8LFH0x1pPnDa3aPzG8bHXxL6c0u7cMLw+FscmW5zRVE1kVzT4n2wWJU6AzP4LS5Y4BjwyRR0f/tbpumB1WZFrpHIPaUI0/EO1cjD/YkXP/k5Z+fXxBBtJwnRxGy1gGyYxwPt5pq+z6jO5GoDA2NzQdtfotWhtLSrM4KfEMnE7opxLDaUUDa0269xIdBvPufLv/w52/MrfHfB9vIZte65f/N/s3KhZubpcWmYM8PxDu8D06S0m5fsHk6k6cDmcpmquWgIjscB1NK1z69f0W3O8WGLiyumw0fjKXQyC6gXojwQg6PkExfPriHvCSETmhUuXODbCyQEuvUL2jbTra+Jqy/w7RXt5q+BSqkmo3fNZwgZcS1eEvuTMI8DSmPS63yD5y3OneFw7G5+IK4+Y042T+N0+z11foc2L2n7SIwjp1NnvpOCBVZjgkJx/bJZeJCO+fQRFy8tXQXl9PgOJ46L55+BRMbjx0WZkPBy4OzqirazpI/QnhPaK4bTtIwFkD9GM/zT0jFs5kKF/ktcXBN8hnDNcHykD28pdaLvt2boqRNopl29InTPUBz9+UvSNNNunjMPtzinTPsfUDWmMs8z4tZ4f05JFh9Tph0+OkIMlJxs4MWnRWof7NXrl8z7tyiO6yvPOAtOBnx0XF40MH/H+29/wX534Ob9e1DBhUvWZ1ugEPtLcsYQsvAMJdKun1sogRqjWdMRLfbgdpvXCDN5fM9qHXFOiW1gPnyLb855//1vcM4+e9udsz1/zuHxA5vn/4JuFTnt7hdFbyY2HW2/5nQ44LjFSeHF519BvoUyMR4emMZHcp5pG0WlW0YDOzbbK0D5+O49cXVpUma1GP48H8mlIfgRVRiPB2o5UssDx7tf4r3NpPBkdnffojqRxnfmVOy+QEJDTreE/mtUHxn3vwL/HHFQZcXlVU8MFe+cjdqVLe3ZP6PUlmk6EmIx3sm1fHj7hrjaQHiOzjtKOgAtm4sN4/47yjwQmi01Z45HG6p42P3AOM340OHimml4oKQHKCfazkYVx+454lafgoRLNlNUHm+Xqa8jbRPJaaLrIx++/Tv+qDDpjy2GTwtCTZLhnIc8UMujmS36l6RyQYxb5uNvCL4h7f+Bx9u3jIff4hvTuofQQniGOJtKA5XYCt36OTnZ2FgfV0xzIrYXzNM9ebzDsot/P3nl98fcAq+6NefXG8YhcXbe8/zlhuvrjs1qotYEYYOLG1abFat1sMzTeqJmITRrSDcLdl9pO9NQ1ToCI+KczYroLoxLOBgB5FwDvmM+/IaabslzJa5eI/XI+dUFNsk0mn5IhLOrz/GhpWl68nRPmg4cH38ALTgHF88/p+g5uSRLkPNrpqnSbS5AR3IazV+QLAABydgYqB1NE1CJkPc83ryziacacM7x5rvv2D/cEuQOqUdiXNFtv0S80m6uuL/7BtVAocFJY/fWRUh3OHHE/poyPdJtv2Yc98zDA8Put+D6T4niWgeG445aTsQ44ENhntTKGb9h3P9Au/0pu9tfImHDafeB7vyvyfNEt/KUgjHGFKK3JHJX7vHxEi2Jmg94PVJKQz59b6qDdEJcWmBXWww+bHn88Eucazne/RKpFWQmHb+n4hmPdwZW6J9EurGUE9Z8uLCiEqjVM05LNlLzDGmeU3IlzXesrv4563VA3AW1TGZ8iZYM7cLG4hFLwMWXuLgiFQUypRRqMcNQmXdI3DAeb6k1cffmv+f+/Xc8DeReoq05v/oKic/RWmk2XzONCd+0NP0zYvTcv3/P6y/+ghA8PpiH2TdrurMvyPMB114hcc3w8AscdVHpRh4+vOW03y89biUE4fL6kpILvlmjVYjrz4mrz1FmpsN3+PYlTWeBuq6O1uBppWnXTMcd1ELsznDO0/RXjI9/T62JnI+03Zo8jXgHoX3Gar0QRGrecglLflFoGHbf4xqLVdmeR7QcKaxpW0eaB5oYeLz7wJd/9XMOu1s7VTln2N8ZUTWf2N+85/L6GatVg/fnFk42PDAPH1FpQc6p85H+4j+gpBlXBkJzyXr7M6gDabyxAfHOEcPeclJP35CmmeNQoZ7ot18ynWam/d+zWq1499t/SxMT6EwbC8qWdm3I1s3bX9FtvsSHCd/2NN2WWosFJrjIdPqIa14bQlYTTjyHh3vafo0KlDrQn33Ncf8ecc7CCzThY8TVWz7/q/90KZP+JA/0ovMTYZ5n8vCeXJU07okxLsIoQSjE7ed4p+TpjtA/x4U1qo4gifn4npwgTQer2+ojzjlKEZommgQhj4QQySkTV58jWvFBcb7j7PraoksOdwtcbFzDdLoHnTm7iHz4/jecX39JmiyrSWulDQeeLKOh6ZmGe0rKi+Y+4aRS5nua/pp0ekstj4zDIxcvPmO9OeN03FFzAk2weC1QiM3GjClUfNwS+ueA4P2a2LScdr+g3zwz0VnoiI1QFDwnahlJ84Fm8zUWSgz59AYt95Z7BIjzpDTZQEMtTPvv8M0Z6fgdNm54zXz6SC3g/dYML6sOic9tQaw/x3vlxWevcfE5x4MFQB8O5mBz8YxaO5QN73/4gWF0hP6SMn6g1BWQ2d0/4JpLXPd6YbXbT/Et6+u/Zh5vGIbAdPiBpv8Js/4EH55x/eqv+eaX/w7fbLh4/jNm/Zz7d9/Snv0EcZ4yDeCEzdkFWh15PnH9+V+Ry0SI1/zwu4+UfGAaJ7bP/gb8OauzlzSrZ8BEnnfLIgScglY84NxM0/aEbku7vialjHOzqWjVjD1/slDPLxMSvfeQZ6K35glAtTANJw77TJpnynxAnC2g/cMDTWtapNBc4oNjTsvgjmo6ERGLeIzNCnTi8dH099SEupZSbKzT6vxLGv8AeYlmXE6GnCe894gkzi63VDHCxTk4DonVxqPLRE3Vwu2HvcmrZ3PslaI4MiodfvUFVXuatqGWwnA68PDDf4/3FS0HbLiIoPkjLtgQxlqdZTtJjwuVuLpkHt7Rnv2cNN7gnFlY1fcMD7/ChxbVlthsGU8H5uEe0R1xdUFszni8+S1OYB4eCaGxmjpGtO4RncjpQL/9Amqm6V9YqbfMcKtqjsOUoAkzZfhAbC+h7knjO5r1NdfPrywa1CdwjhBbnKt06wukjKh/heiJmh85u7qk5pnHd/+K9z/8hjrf4WMPeURLIbbnePeesPrSvN9xz7D7nvF0z/r8JWn4CGHD/e2JfvuMmibKfGQ+fc/h/nskXBO754TmjDzbBjvPwrOXZ0Aktivy/IHYnVtV4gQtM14y4zAhuluUxQP92efEuEGl4jkuYc5nOLdiPnxLGnZmVPpT/Ay/r9BtBWpc0bRn9CsIXpnngYvrK84vtjTNFt99ZmaQPCL1QE6TOcxCYHP+OcMwUWvAkZjnSskjRZWcLVHtbOsRshUs5Yi4lpLuwK0J/StKTYupW5d6/Cdsr75kHEa0nGhDpSLc3w30ncPHC/LyIUQ8Lz57wZvf/QN33/5L89c6T+hfErpn5JSotdJ0l+TpwOmw4/O//p9RtKFoS057c4C1L1CUlCs5FY7H47JAHdNxR1x/YQ9K+9oicuqIqw807dq0S6cPjGPChRWhWQHBfBXtS1brFXnaE7qtBSKonc1x9RWqE0TLSbIhjg7qyDwd+Id/898RvOC9GZ/KdE+7/ZLx8bfEJrC9eomTjjS8IUa4uzly8/3fc9i9x+stTYRxuCMEJQQjvWpJSDVfxeWrfw7imU9vTFLhWqbxyO2HmWb1nLuPH6jSs1o7Lp+/5PJ6Q9s/4+L5F3zxhdBvr1hte6ZyiQ+VtjdhIXpiHh/J6SPB7/n1L/41SGt9YhK++fUP1DzYc5IOKB25NrTra9puQ+yek4YPuBAoNRFcS3XnIA2u7ijV5C+ueYrR/xMHHOryv6fDI6IZxTD8qpmm6ZinEa2J6bRjHBLTkEzxqJ6SEqHp0DzY8bry3H58Awhl+kAaB8q4M0NKhTLeGG497SxdeZF/kI9sL15SU/n3sGIj+zyrPvK4n5j3vybNmTI+2AxmEr/+t/8nuwiqDPt35pLbfmYI1pJ+XdPBRHG5kqcDMbCk92GZp9UxjZMN1xNdZCdCCMpq1Vn4GdBtn1lo2TwteioBjYz7O3LxtJvXxO4CJ5nd/a2dpL6lpIFcE7Jk2GoF8ZYGMp5OaB2p2hqypSMicLj5O+bpnnS84cu/+BlTsnG0tx8eQCL3H98xT8o8JUIU5v0v2d/+wDxPvHy14flXf8vl1YqLqxek4T3d+gWaPjKPt3YCpjfkZCam1apnmk6E5hL1KzQ/0q6ukHDNsDtQp3vEPyNNdzx8+A2abkyeHgUIhCD0Z1/imgva7V8goeX4eMvND7+kX0VC9yXKhr/62/+U2D3n//5/+a953O14/ZOfkmeDm+fkcEFoOlNEl3w0dfN8s6j7ZxAlhAsj+ZotoduCbAjxnDLfcPvumx+/GAQQharC9vycrpnI0w6b+eDo+nP61ZY8D0ypw1fzm3rvGY4D4zDhg4DfotW0RueXW4ZhYnP5U1M15sx0+AamH4wcOnyL1h06fyR0F9QyIy6BW7G5fM142v1B5Idw2r+jauXzr37Oae7g8P/k/NlzXH1AHGzXeWnePdvzL3j+k79he/U3xPaCPI9LJlRLaBokNFR1NN2lmZDyQJnuGYcHm3UmkTLvMZ+RgPhlptmMUuz7Z5OV+NgvSdlKaBtCu6aWI+vNNXl84PrlT/Cxw/meNB2p4y2hvaaWPfPwHilHnC+0rQfXkqaTzdbLAyUdUVYwPxBCYDoNHPY76nSg6yKIeRc2z3/KXDe8f7vDx57zZy9p2jVtnPDlwDwLobsk9teWPhGemUJVlBjPKemB2K8JTUcpF3jfm3dgiRx9/dXf0PQN/aZDVZjzmv7sM1JuKLUy7n+JqpLnGxwD6/YDNT3w7tvvmefM9vKK7vw/QegQvaHpzphOO7746gXBJZxkYntBaM4tYqhOlpYnVkHc3/xA7J6DwHz4LT5EICPeo9raeDSt1JJI8z3n169+/GIAPj144gLT6Y6qkMd3iLPJMzmNlKp8+O4b4uY5URLTOPDy86/ZH0YOD7cMB2t6Qoisttf0fUueBsQLTdez2jxDgkfF0TRmgPft1qbA15HYveTNd99Y7Ere8YeYcbe+JPiJ86trvvpn/3PG1BH1G3bf/9c0skfHj6DJIgmdgyXloZSRtmsXlKajX19CPTHub1DX2+xkGghr1ptXoMo03KPqF5RnNCefNEsgV4M4R7c5J/jBojTpqLUSu3PS8JHT/sh4fIvIMqOsHpnmkWb1CmFiOr3HhiDaEMI03IKYarPM91hvYLMH6v+LtD/rseRa0zSxZ61ls9met88xMTge8gx58uRQVZ3ZVdUtQQ1Igu70AyVdSBeC1BetHpClzsxSZVVW1pkPx5gjfPY9b5ttDbowJ7MBAdktMgACJAiCHuF7uS37vvd9HlPS2iHB4IhWO7I0YHl7QV0sKPMSz7c4vUN3JUnUb/ydCHAypdMRXbPrdweuomsrbH1OWzcI118FjRggvQFXr5+xvv6a9eKaVst+6qX68XEUhfd9hT70mM0+xmqB7/f7DT9+yHByQL43dF2L7SytDnj80c/xZE3bNvjxFOn5aDNE+Rl+5DGbj4myIVLkdLqja3T/+/dnGCt6gp4LsS4gHjxGIEEM0brC2RII0O0WXE2QniKEYHd3jffD/Azf6TJASLquJ3AH0RhMvxq31qK1pbMRWI2fHpDf/h6BYTafIGTMYDqh62qa4g7T1vjxkKbVfdy47jBMWK4DPH+A885wck5bWrqmwo+OMdUV86MULwgw3b63wn/7G5Ahbbnrsz4C8I56JS8x+13Dpj7tZePG3NdPJWUBpr2jLq6w1t3Db0uUnzCYHmGdI19forzgvrLoqKsdUTQAW/T7D9f0hDoMbbXB2fa+/2176IHoMThat0gZEyUHDKdnfeLUBTjdIP0DlOg33178ACUjrJv0UGMswj/tt+26Q9cFdb6i3JzT5Guazsf3DVr7HJx9RBAGhKElHSQ4m2NsTKdTPE+QDVIwG+pK49o7lC+RfowQPk4bqn2OcXEPUAjSvrUoDOX2LZvFknJ/h5KaL379W+4uvqKrDcZ2VPkbouSAIIipa8P29hVJOsOKKVW1wHrH7POUwewDpBzggqf44RBtFNEg4u7t8x4v2d6w32z6yaRdIzzJ/u5r6tIQhCGSbT9GdR3Pf/8fqfcbvHDAYCC/SzH7vkApDyEihM2RsmW/2+H5GdYaorhB33dpvt9h+JYYDb1nwJ6htURId1/s1+i2JEknGNfXQgWScPiE7dU/UJcbIGe7zvGDBCFDquKKplyT70u6ao/y+i5EHPXmnsXVW5ztKIsOL57QlBsakxIGA3SzAu+wh47dvzv015Beri6F5ODJz1HDvyA+/T8SzP9XfPon/xXch+M8P8CTLWGcIKRPlB5jTEfbllhrqXbXvHv2NTfv3oAcoLuix8xL1ScrVQwixLkaR4QREdZWfYf4PqHrbIGQUT/CtQYl214Dpnfk2wXx6BHp+AFGlzin2W46lPLQ9Qo/UEALTlCVd0ghEbJnFvlRhnUBVWWo24g4kUh/glIOP0j6JZ9r8IIRg+mHSOkIgpowkLRVjWk2mA4u3rzGuoiqqGn2LxFeSpgkSGXBeUiVoYsrqnxDkj2mqpte/xV5zOZz8p2h0wUeOcrv4Whad1grGMweYVyHlCVKv6Mp9gSRD84QxCPCANpyi25LsA3HDx/QVdt+OhYmNNUaLzrG6pbh7DHOSbo2JxoeI7yYenPLk09+RhhPcaZBeel3n1NtwLmeAoIMMe0OT/UKgDBKcTKl3r79AYdB9Btocd/Wubl1/YTH+fe475g4m6L8kPc/fkxTN+Srb/oSf3iM51X44YTt7ev+C7cN6fAM3aw5OD5ivbyl7TratsIPUnTbMjuaE0Q+s5MDsOI+GTqiK95QVhpdverTlN9+iUKiu4pvOUxpNub6as/J058xPTpD3I+GhVA9mJYYP4z6wnyzpql2mGaBNRuEyzl+eMbZe09JkwipQnbrLX33e4x1HdoInKBf6Og9DnlP64777bYD01wjpAZT4PsRddW7ndNBhpT0yy/6fFUaG2xzjfLD+5/IHaYr8T0fq1dYU+OFY6Q/IRkkjObHDIb9N6fel1y9ecF+9QoVxPjpMbq+YbtaUmzfsLp6DWaH7lqi4VMGkyHTk5/RFRt22xrtfJLhQ3RziwyOeqiDTFDJGUXRsLq75ej0hLz0WN4tem1wKDG6Z+vWuwvQDejLnhWrm97p3TxDyY5BopGywnU3SCmodi8QSmG7t0j/AEvIiy/+wOtnt1g8TLPGD2c4p9gs1ghp+h8UbdlvpJ3rqeGmxjqD0QWm66+cdVlhrUOpsAdOyBDpTfsf5MrD8322t998/8PwbZfh25MxmYb4ovcVYDVIEMpHVzcod4Hw4l46IR2hsr0cxDqSwRGrxS2oqD+1LsU5TTo6xJMlbdXdb7o9tPaREpQKwDV4fsh+eUXTCqRI8JMp+9Xbb4sNAGQHP+Lu3W/unxaWwTChyCuCIPzH6ZOArtnRtppy/c39XdyCzelaBWpK1xRI6XqRuZTorkW4Xe+mFj1e3g8l2ADXrfCTMUZ392adFuGnCBn2rCYZ4ISPtQ1h2CM0+1xSi9EGT9b3EkN5P7qt+/4vJSoY4pwEk4PTOL2/F4lIwmjQ56aiATLwGc+OME5hicBa/PiIwPdQ3oAwewxqTjIc0JRrqrx/wRb+iDDyieL+iSbdBtfdoXyfYv2OrnVURcOLb94SpYcUrc/s9BOiOMGPJnRVQVO3CPqoiFAZcRoTRUD7Dun3h154Q2z1hs1qx+/+418TDw7xwwSpRpi2YHVzzniSMRo3OFOyvv494EiGDxhODxhMH8O9yMRYRTI6urdCdVjr4YzBdAVCSNKM/n2wucUBKjroCX7QT5dkzD7ffP/DAP01RAiBdXBw6NG0HQK/3yXcr7idiFFh2qMCrektneEYaXr04XSe4XTRg2+tZTiaIYVlMMhwRMRxhhQp5fYGz9OocIbWLX4Q0DQ59e4tQjR0xTmmWSP9vvL3LSxDqYh0eoaUCikkD947xfdd/7u7v1JJW4DNUbIiGw7wRI013T3upUFJgeenCG9AXdV0dU2zf00yOKStG9pqS9dYnIW2WqKCDN3WBJ69Hw13dF1130Pu77Lu3nKk/OS7R7fDo+sM0otRUlEWNbZdYE3Z49PbrtdRWYdzHdb0ND1sjnM++b6gbRT7TQ4iQ3oBm8UOYSu8aMh2fcvbV+/wgnt6uS1RQYofR6xvvkQ3VwRexfx4ghRLEJJ09ueYe89y1+4RUiCcRzY6oshzfvTpp9y8e02+ucYh2e4MRd6w2U+oKk3bOrr8SywKGZ0i1EHfsVYS61qmJx+Tb26RXsp+vSAIRtycvyBOQoZjn9H8hMF4wOjwE6rdHV/8w/9ImAxA+PfhR7C64PU3zzBdS53fsbt7Tlt3NNWq//6Gj9kt3iGkDwhM+Y4//MOvgP6dEBUTJ9n3Pwyivyf1rrH7za8XZb3VHairAqu7/p4mFMpP2N+dQ7ela9c0+WtMW9DUWwaTOdLz8JRHXbcUle4jHibEup6IoKIjlK8w2uArDycEgorpycdYKwmzA3SbE0ZjrDGYrhd9e54iGxz0pAjRl5KiJOVbHzVA25U9bkQUVLs3OCEJ4yHCaWQwASmoGtu34QQIUeOFA7wgxlndSzFcgcMnTg57dpS7TzOFcf/uLjRKeggZYru83xV4o/7FUPkor39x7sl7K4zOyZIKGWT4QUrXrvCDrBep1wuUF+H54779501pqg1t1eIFPpdvLjC6ZLtaM5pNuLm4pS022Lbk4DAjLzzWizVSebR1wTe//RztUpze4Ce9IQh3Tz9UAc7uaYs7BpNDdHnOYP6IvNihu4q7y+cUu0uef/UVm+Ud2WCC8hKMrlivc9riDssEREJb3GBcD5BT0iLDh5j6az77xWcgDJOj92m1IEnnjI8+QamAIJrTdj7OtDT1iizzKbeXCDqEjNksF3i+z8OnHwIdxtheLjkYESZ9gtfpmngwoa2u+nc2vWV+NO9/mEuJcC3D+aMf9mToD4W8f2uQOFP2I09/hNWGtl7jewrbaN69fMVg/hBrSzx/RDT/F/eldx8hArq2Jt9t2CzOCcOwh/gqSRR0dN2OrljijMO0K5CO/eI3CBy63RAkp1grMXbGyy+/ospv2axu769BDpD34Kpesfvtr16M0aH8CVbn1A148VGPHtEVddsrumx9wfjglK5eIUWPnFdK0jU5vQ+5BBFiraZuSxwRnp/eE/YMVu+w7eZeAeyQfu9dFm6LadZYXdy/7KcEancPWGtp2qbfpYgAKXzaVmCaNUF2SF1s6bSirBWmMygVYdtrnv3hKx5/8CH71SV1ucPRMRhHKM9ivBFdJzh69AmDyZhqv8K5lGQwYjaz/c4Hh256K1LX7voApAQve4xua/LS7zvTriTJxnzr53v83gFpaJDBAD/MyLIRaRainUO7BKcLVHBCu3+FUA7lT1DSR3ljotCjq3vhu3Ab0sGQqthjMexWt2xWBUbnrK7fEY2eko6OcMJjMo9wWvfAgiRDqoBsfNpjR4VPue0bkG+eP0MIn6Y24MWUy9ecPPnoPoIh8ONDmrL+//ls//9xGNx3BRNje4x8W1xjbNA73HzAmf6+6zy6aoHWDV31Fi+IkDLA6oIwHuIHPqGyBGGADEYIeql3FIVcX1wShBHZ/BFa9x3p3eoVSoUob4jngdEdCE25f006cP1dPAr/J1+rxTiPuu71WcY093pZgW5LFm8/p7MZwhZIf461Xn+AmhVtfoPwxhTrN0TDs75zocChsHpHkg3wRY4feAjX9P1o2d/3kQmoEGN8kAlttaBXNm3BafJd3vuObUe9+7Lvj3eCuq7p8q8JA7+PjXQl2qWUu1u2i95YE44+QNiSJE5QUiMpKSqPD3/8I/woxTBkMJ5Rbrc0lWO/a5iMR0wOJjT5DYPpCSoYgq2ZzDKi7LgvK+kW6YUE8QjP7xVh0lRI6TD1JXF2gm5KhrHm/OULumbJex//KePZKU75/Jv//q/AWowTlPuKarcHXfXZILGntafodoczHfnmnNvLHfvFM4SK0NUSUBTF9l6EaFFe/z6KGjOZRERRS7lfo4srvHDA+OAQ3XaU+0XP57I9kLlrNt9tnOZzn6a46H9kCx8VDhDuH6l+1f6aKP2hTjfX0/CkFOSbG5oyJxkMMLanWfcYk4woG/H445/fJzP7OmRPkysRoqPKr3vNqycZTVLaaotzlmLzkigZ9qV8zyMIBaZrUVR4yUOQMcuFxvN8gtBjdbvB9wKUKPsRp+tpsNY59pv1vaHFoWSAvR8NSy9CSEdXXGJNhNEGGR71SyhraOsap+/IBqMekuUprJVYG1DXUNeaZHxGV61oWot1AUa3ONNhWtEv3vwUoQb9pKMtQXpAiOGw9+E5RZCcoesb4uyUKD3Bi99HBkdI0Tf7TLMlHWRMH/yYutrT7O/QzQ7lK6zrXwqPTyb4QYSnOiZjj/3tc4SriSIfX1RURYn0JzRtiFKSMPYQ3hBnKq7evCP0BeW+6UkjJkd3Nbvl71HRY4S+RfgJdAtMV3D65FOqcs3Jkz8iGcZk/ht0teGzH/+Urmtpaks8mOFHRxirewK4f0iYTfDCYxwWz1f4kSKdfYyUGZ5v6doaZw1V3eElxyTDEZ6f4Ps+QSBIxw/xlKEz/r2DTtHWGxQ7dFN8d3VVXkaYDqiKNZ43wIgZ0fhDPC8hmf9pHyESIKQgiGYIu/v+h0HwbexAoLXBC2NGpz9Gd1s80WG7PVKGmHaL56f4vsaPZqjoFNPu8VVDmRuMqWnrjrqq6BpLtbtkt3hFEIZcn9+SjSbodk+1u6PcXtE2Jbqt74v0ltHsCBVESCV5/OEHeD60naVr/7HwIxDU5f47XVE/+24R91eeMHJs777sU7O6ocxLTH1J10iK3RJjAjqjCMNJP8r0EvwoxFmJkJI3n/81ZVGB7ceKzhS09bd4d4t0DZ0x7NY1QkUIlbJZrQhVSS859Gl0hAxGfb206wsqui0BaIs74nQINAThiLbaIsgp84o+xZlh2ht019E1e8Dj/NU3zM4+om09PM+j05rr8wuuXr0kCPr07ep2R9cphgefsbhdU9Y5StWYzuKFj6j3L/FUfwXGdni+j9VrhpMRiIjBwKepVtiuoDHHNNoHvUR6EW1j+OIPz6lrg/DGvdvZGqLIp09CtCTDR4zHIIVCSU2dX+P5Adn8jMEoRaLxolPatsHzPWSQYNolXmgZzj9kc7fAGk2x3+Kl7yHDI9qyoMwNr/7w9+yW1/z+P/41weCM0SgGk2NMQdOGxHEf4ANBNDjrDaff/8kg7uMBPQY8GZ0i1QzlT0D1ceCyXAMaZ+oeTe4kdGuk8slX10TJFNeV+D5g1xTLPxBEEwbzB1Tbl0ynU5pqT+D3L8xWTokGA8JkhBDQ5m+JIolHDqYgHR1R7N71y792SbG/o0+xwvGj9+kTpPdkbxlgrSPP9wgBs9Of9V+f6AjDnkHatWvS4QQrp31XVqr+IOkG4QxaC3zPJx0dEoQK35e0rcHanjYu/b65hwqxXX/9UF6A54X9h1tN+uUlGs+PyddX6K65r77e9qk8KUClWBETJId03ZZsNKUtb4niDkSJ7lr86AQvCNBdg2kvMVYQRgHKz9DdDj/KKPc3TGYBkh3rxRKHQskVXb3m+HiI7gSmeklTrum6As9PCeKHOCGxaozwDgjijOvLHdponnzypzz/4gWLqxuublrG0znv3lwSBB7TownHpw+YnTzAmQbpaorV73E6R3oJVZXjvAlOTNjf/oGu033PPRoimhV109DUFabd4fsS0+2oiy1Khff+OslwdsZ+8RZPWKqy5vrVP7Bd74kHY0bzY/wo44Mf/zlC+X1zrum5r85scRhMs7vP2Inezvp9D4O7h2s45/A8D2ErsPo+7mCwZod1SX+V6m4I/KSfx4cP8fyUwfQY/L58IgVYMUD5Pp4Pplni5JBwcESUDqmriiCMMKbCNjeY+rKPSje90ByZ0mxfYJ0kHX9E4APeuDfeWAdO9pl3Z9G6vS+K3dObqlf9KFg4wiQDo+iaPV6YMD/7lHj8BPQ5WIeSpuf5f8sy8iry9WsG8wcUJWzvvkYJQ9eUFPstXduCFL3XIZmRjQ8wuul3CUrgJHT1DrAoKsLAx+o9tiuQvkKp/n1It3Xf/KsrdF0ghCGZvIfyJ+im91PrtjfnhHFM18U8/eRTbi4uaLuCZDDn6t0tXhgTJgOMbYljRbkvQETgDL5v8MUtnREEUYCQIbpe4EyJwuFMgdU50tM4V+LHc1a31xycvM+2gCTLkN4QPx5y8fIryv2C+TxieXuNJabav0CFDxDBFFxJV2/RZU8EdCpFqBDwMG1DntdsFzd4EsrNc6wVePEjwnRA07UsF1uctSyvr9htKtbLFZdvXhAlCTeXN2zXNVW5Y3N3RVNssW2N63YE0RjrLFE65Obdc7aLV72XDvCjBz/gySDEfQa8t30qrzetdM0dbXGBsxVC9KNVgYdTGUJfIhVEwzNQAUkaIryEN68v+7ShGuD5U5ApfjwlG8+RXkoYh5T5msiv8cPpfYei/8BbY9ltS1Y7j3p3w2hyjO9ZfC9H0vS7jntmk7OuZ4l6st/2SgG0xIMprlv0P7WjgCieYp1iv73BVrc4EozzcKZDt1uU24GrCeOYquojEXESEyUj/EgRhAnJYIbpE3Cs7wq2qw1KSS7fXNLWBcYJfA+8aAoioimWBNkDvPAAFY5R4RG6q/H9iCSbgxB0RhEPz0AEIEf9NzYMwHb90rBeYw04U2F1gfJ8JrMUYTXDyZwn759R7O5wZAShTzKY0OzfYk3J+ORHeEHAcBjiB330wtk72mqJcYNea9utUd6E8XTM7375GwajQ4yxdM2eb37373jxu3/Lx599TN15OKsIwpjheAhCsN1KoO0tQ0YQhBGdlmjtMTn9E5r8HOcUUXLK7PiIycSn2O6oS8fN26+RKqSpJM5KBuPH/dP85EOOn/4xg/ljhsOY9ari7uoNg9kjsskRfpiSr1/SmQ4/PcV0feGrX/zuie/H8UIIkMEPOAzWfRfHsMbR5s9waohPgQoypJSU2yXKj7CmxpqSsmhxVlPtl99NRsrKMZk+pMwN641EKkWSHSFswx9++Su6tqHTHrrTvS5LVxg3IN9t8MMxUgms7VCeBbembVaI4BBjfZSK+9Sl7dGEnu8hlewJfP1ICBWfIeQIvCG6LfqJRLdCV0v8aEjbdGwXK6JI0bXr3rdQVv0W2PZPLCwEvsQLh/cLv54jmyYSYR3T42P2uzusccRpikADBvBoyhzTbPr2XptjCXBW0dYtu9UO3TUIL8MahycdusnR9Rrh9+xU3TmkrBFI0tEZXuAhpY8XjZgcjImjlLLYY+p3BH6/P9ndveL64pY4XGM45uZi0e8/hI/zpjgnMO0rhBwSJCdESYoUkIw+xuiGZOjz9OmMKJFYOmZHD5kcfcxwNiFfXzGZDdnuKvLtiigQSLdjMBr1Jh2zQ0pN1+yw7YIgimmLG6zNMF2L7XZobYgnP+bubs9m1XJ4nCGE5O6mRHcNu+U1zlniZIj0vHtJoePhkwNOHjwmCCMG4zmjUcL06IwwHpDvVqxuF2wW15SF7TNNyusx/dDHhL7/k4HvKGRNtUMJjbANnRY9Zj04YDidgvDx0qdYMULGTyhzQ9MKhPAYjmfo8oJkGBPFEcMB6OqaavsK5zyefPiYIPCI4oj58RnJ+HEf5Q0VtnnXlzlczXAyYzg5Q3gTlOpjIlUVIkRFvX2O7mqq8pqurfq0qVIsrs/R3Z4ojGmKJabRPdoS8JKHvbXzHog8OTrEGMfu7gbjUjzVRxKsKYnjDuVJOu3QWtIVb6mbuuf2eBHb5VsQPrrNubt6Q5QELG+uKLc3bO5uWd3doVSKCg/pDGhdcXd1g8AwPnoPL5z0oj6nMabFj+d4foJrdyTZGF33HXKtBW21xOoKP57geWnPT1KCMBkxPnzCy+dXyPAQ4Y8w1QIvOkUqhYoPaOucZPA+9X6FEwm7dYEMTxA4tpsFRpcY3avBFHvG0xFtoxlNj1DC8ui9hwznjzl88CFpotgsb3DCoy6uMJ2lq4q+RmtDbLcmToK+62x27Pc16fiAfPMW095Qbc8x9R11tWZ2dEpVerR1xfER/Orf/QeyQUK1e0uVb1hePCfOAqYH/feorkriJKXJF+y3KxbXC4JwSBj7HD3+OabdEqiccnONFwTsd/2QQop/+uP+P1/7vI8AGV31ZXGT43FDm7/AmTXSXQItztR4yhLGKUkWIchxTtB1NX40IE0HfYIwGYGQJJPHSKX7a5EPcSTBtZhmBcIjSB8Sj96/Z7DWOLPHkwovPkHKGIEkHs7pXEoQZr2kcH9OubtBdzXOWeriBqN7u02QzAiyox4xIiOK3QLhZ3gqJh2PcdZD0BEkad9ZCKeMZ3P89CnGDdhef4GSfWRByJDN4hwvyACB1hKrLQ+ffkYYQLl6hwoStMso97dsVjuWN28wXcdmucEZSTSYUTeA8Ngsr++ZU2UP0RKSri6RUtJWdxh1ghdEKNUQRBnWhUiV9kUn5VNXDZvlNXW+5+TsCeW+pGv2HD9+RFs3JEnEF3/4DcXmmjq/o7UPsLojjpN+Ky4A0/b/fxuwW91iupoocYSBRThLVTY4a7i8WLC5vWCXax4+PqatC4Q3JYgDvCDCNrd9QsE7RIgBVtd0dsz08Iim7jfcwp+hggc4l/Pe+wfEic/k5L37PYDj8OwJXWdpq4a/+q//z+wXXwMOIRUXr8/58LMPaesdfpQwPnyA73lYYykWX9CVC24vr/CiKVF6gGlrssGYb8Fz3//J8O1ZEA7PC2hbSZA+wBmJ8I57NqoY9KE6NM4Y0Hf4vk+UpGTjQ9JBSJSMybc3eGKFlDVOeP2OQPdISKsr2jZHdzle2KPjnQjomj1SeVSVwrgIL32MUj3TBxFgq3coNG1TIKSPig6wes/t+Qu6pmR28hFS9YKNziaE8RgpJHW1Yzg97KdN0se0JWEy6cXeEtLUwzQlQgZU+R4hA8ZnP+PtyyvC7BgvmrJZ7pGipSvvSLMYKTrq8hZtHH4UkKQZd2+/Zn76PmdPPyTOZui2Jo4ETX6DtZYwlnTNDs+P8ENJW7d01Z58t0D5/SRMCMft26/YLAv8+IS2uiNfX6GCXsXVVDXb9Y4gCimqhuvLS+piAdaxWpR4nqDcr/nP/9U/5+5mwe35BSApl79F2B2m00jpE/prsBrl+cjwlNaM8KMhttsSBo5nz15T5jlnxxm6WTA/PCKMx8RxgJQBXb3tY9jdCOkN0E2BNQZtapIkxFgPRYmfPEQqn2RyiJAxXjjEWMPm9qp3/mE4PlQkmUJFQx49OeTFs1f827/6T7x7fQHOEcQD3n39b3n+h89xJuf4vU+wFoLkED+Oefj0QwSaePyQri0I0j6y0ery+x+GfpLU/53nRwRR32Mw0OPMRa99/RYM5nR/bVCeQEoNrqXJz9HNhmQQEQ/mSNG/lCrVI0mQYxAOIXrmp+lKlDfEtA1Cplhdkg0HaC1o6gonEro6R3eGfP2Stq5o9ADdeVhGKD8iG49pqvz+a2t6aTglOE3XbgjDEKl82jqn3l/ibEuVX1KunyHDMc71zgMvSGnKJWEy6UnhVmN01X8zBzGdVjgRYJoltrvDasPq7i3jgycE0ZA4G3B3uyDf3FIWO3RnGUwf4SUnKNnzmYzWBKpls7y8f2H22N6+7OuzfkpbOybTmKpYsVveoJvdPepF8Nv/8Nc0+2u26z3LRYsxCXXREKbHjOZP8OMH3F4uub6+RHctQRgSDw/xoxQvOqXYLSjXryjzG9qqoaocXbvG8/1+HCkHeIGHwePs0Sn7fYn0LE4Ose2GOOkNsD3pT9NqyWAyJV++Ybve0DYVbTdG19eU+xUqeIK+JyriDH4Q4YdjhLD87pe/RUnBzbs7dLdEyCHp8JAPPvsZ6eCYwCsp8paT9z7DmZrB5Jinn/4Ldotz1tcv2K1X4Gq211+Ciqn2V6yunpEMJv2H2YHrNt//MHz7VHEOpJ/0qdBg2KP9VB/gs2QIGWGtAv+ob3sJRxj1VcYwPSRKp71V3imUN8LpBuv6QB3OYY1C+UEvPZQR0DfopFIIFSGFR5LGeJ5CSB8ZTOm6jsHRv8bKEYGfo2SBr7ZIz8P3HLgGnKHeXZOND3sROwrn+g4teo9UBtwO5QmE01jToKTq9bVtSbV/y2g6Y3X1FVYbTt/7iK5agakZTQ8RQqH8XuwBAVWZ8+jph/3LqS45ePCEyXSK5wn8cIQ2vUrKWkkQJCxvNlgXUlcdX//6c77+3W/66dDhAzobUe4uEa5CRXPS8TFCWKSak41GKCWZHr9HGEc8/fhHRKGm3F2RDUOacstqXfHFr/+OZDwnyU54+/xLzp58hrQF+/U5d3d7pD+ibg3f/P45nbb8/ldf0GtnV/jiBtNtaMrXSDSnpxOS2MePZ0TZlGK/6Ntw+y1NccNundPmV+y2BU6moIYof0Cz+R1tFxDFIVa3fXBRJXRNjbYKGc4QCP7sX/2XvH31jKMHJxg36UOV0qftGn7yz/6cP/7nf0YUR2SjQ4yTpFmGE+BHU7A585MzrHpCvX+H74dIb0Ay+gBr+k5Evj6nzn8oEIB/TK/qtvdqKb/Xngo0mBuMLhCy/0mq7kUTulmB7OfKQsZoY9C6xPNTmjrH6hIZTNGmva8m+CBCPBX2OSg/A9M30Jp63zfH9Iq2uMNo2wvTRYvnmx4Q1rZ97NnueyG2c1jd3n/QS6SX4IQDAupy2ydXdUOWjrG6wOqKZDBFmLynZihJnd/S5DdM52N0uyWKfKI0Y/nmbwgjRVe8RXeOeHjMfq+ZHn+E9GcYU9MU16yuLxGuJYkDdFPj+TFd5xA03F684dGHH/VYFt1Rd5r5ycN+0y4KgmiMHyR02tBUe+I4JPAV0s9Q0mKs4sHTD6nyNe9e/JqufMd8LoizIfvVFfl+wwefPCZfXxFHLb4/5tXzK4w8pKtqZsePOH9d3JOvDV0nePzoFCVTiuWvkdKimx1JNu+1Us1b4mxOnd8xnc8oio6m2CGCAXUrcSLCTx/iTMfm7pIgNDRlAyLGD+Ysr27w78WEzf4bfNXhSQ3dNenkFN/3iIK+cFSXhrIoAYcwBWksqfKa04fH7Bbf0LUS7QYoWZEMjzAu7L/f7TV+ekYQJeSrN7x7+RzTrMk3C/bLz7l8ff39D0Pf7un/ksB6L9H75/3iTWVo3WBdBLbtVUW6f8lyKGR0gJApRte9RUZK2iakax1aC7RJMDZAqZSmqns5ojEY02FMQblb07UN+eI5Zb7j5vwtde1jjU/XtUh66Xc/Jq1pmgAnfXzvCIRBeRbd1bRNR9dUSKloqhwhLEp5OP8xSJDRSU+fTjKkihGiQNiKuoV48pRw8BjoxYRSWhbvvsGPT3HNlnR6gqSgyleMD8/6HrUyCOGRDA+YnzzCiohqv2AwTtktLthvb8k3N4xnM5CSZDhD646f/OJPqdYvAXj97BrfC2irAhVMaNuIxc0OS0RVVnTaYtoG12748te/YTg9RmtNkTuy4YDhZELs1wzHCZODI4xLmB/NSLIR23VOkW+5fv2GJHU4rXn0ZMTN+R2D8Yhm92Ufqx58TFVplD9EuBwVzWibijiCP/z672nyFfvtBVY7RuMpwhuz2xTk+wrlB7SN46/+u/8RKw+pmxo/PqJp9ujqLSp8fG/xGaLLN0gKgjDtySMiYzKbkqQZzjnqfMNqscQ5izEd/+Hf/C1352/YLRcYHXB3cX6v74J0fEJXF5S7cyYnHzEagvBmxNmY0SzjyWf/8vsfhn+8JvVYgNnEA3+AFz3oP1DWIKTXB9F013uhhQfOw2iLdY62bvqaoJXEsURbyX6nqUvNfrOn7TRN3cPGTNe7CUy1Z79+w3az5u6uQBvFiy9+SVVcUVctuimp69297DoEY0kHIVL4lOWqv7I5hXOSIHlAVVjqcov0B+SbJcqLqYvy/p1E99VC7Sjza/BmhMOn+J7DFG+oiht8f4gjoNMVBw9/RjIcIj2FsxJjIAgEzlQ0VU3TOpTv09Y1bbXn5vIC403ouo6mLik2twTRhHevXmObHdZYVDRCdyVRGrFZXjE7GHN38Q3Kj9FNjtU546HhzYsLdNt3rLvynLa8YzofECZDZqefMT06pskXbNcFOEeUzjl/8Q1+0KMn0yzg0UcfUpYCI+dEaUZeKBbXN5w8foCw5+T7kiAJKNcXDGenOBdRtkPC5JjAq4lHT3jywVM2uaDrem1ZU5YMRmOGkzlKlFy+/ZrNtuMnf/zH6K7CtFvS0Zhi/Q1SzbCmApkhVYo2CkRA1+2YnnyI0ZpocMjq7iVGtwSDEzzpmM4TpvNj0tTx4P2PGc2n3F08J8rGzA6PaKs1YAnTFKX6RevR40/RusbqnGL1Aj/8p8s93j/1L8V3J6I/FkH2IV2zxjiDra/wojFdB36YIWSI65Y4M6JtOmSQYI2haRzCc5TbLXGaUVc1xS5nu9gSpQprD/BwFPm6n7WLlO16CXIARCQJrG43BPEx0eABTb4Dt+PiYsOjx/3cOUmnSJmBVOhuQb78mvHxj6jKks3qjtnBA/Z3b4lnp3QmZL2q8WWHlGO6tsCLh0iVMJh9gtG6V/bahDACX0vK8gZHQBQPsaLvZ9h2jbUHCHr/sJKmv9aZEpNGOCPwAsnx2SFOr7AWxvMJKhjyxe++5MNPHuLFc6r8liCOCPyOUB30L7H1GuUlXJ+fs93se0K4hMPTE0bTAZ0O2S5XJMMR0yPo6op8/Zam1tRVifJCwtGMYnPJ/GiGCjN2d++YH/WdguOzOU5o9uscYzX56h1NlzFJ3yCCH+HaFTAgcQKomR2kvHn2W6J4jDaCg+NHdLUgDDS3N7eMpwd4psPaAj+OGYwfEXiKg8OU7bomHj7A6Jqq8YmTAtNcstsPODgVBMOPexz+fWPSIfBUx2B0zM3lOaPhDOH2oHycUHzw07+g2l8QRiFnH/2Earfm7uaSw0OFJeOL37zjX/xvfoxxGk95XL54xvHpJTI8QHk/ZAP9bc9Y9EiAtt7geRbbFXQGpEwQ3qRHHTqLUwfkm0vazlJurmiKPV3n+MM//C3Fbk2+XdO2Nc51GNvSNZK6auisT1MJnLZsVjtevFyxXuVsN1u08xmMZswODyj3FW9ffYG1CSenRygvpCoKrAvotMPhSEcPGB3/jMXdimJfMJqM2e12eMkxpmkZTA6J4iE3Vxfozva4mrJE3k+yPFFgbUld1gg1IUjmBMkxFkmVL9hstj02vuqrm6iAzjiMFahAMZg/QNoORIOQPnWxxlmJEprzN+e8/uZrhoOEbDhjt14RhClttSMIU5a3yx4NmR6y2yw4P8+ZTEOEDKiLnCq/Yrd4g9M5o4MDgjBifPQ+5W5JPBihAsXpez/h0Uc/Ic8bNjfPCAOBJwuyLAQRUxSasoYiz5kdnZBOzhjOHrC6eUU0/hhfNWTjEdlkSrnf4OyWtlwyGnioIOWr3/wD4HH84IxXL14QJXP2+4LlzVtu3n7FfrXg6OF7zI4fgxpg9B7brdHVguH0AzqdEWTvkQ48/HAK7Rop+k5MUy5JsgBjK4yG0QCaVoJZ0uQrdL0lSkLi4YR83wEeuqmYTA/ZbhdE6Yyf/vO/wLqQ8u4ldXHHow8+w4mQt6/X37Uev99huP/17XhVSoV1Cm0jnDzAuCGbxRqpMpqmxemuL+5Ih/BjPC+hLnd8/PN/yW63Z7vuw1tekJANAqrasV7mrBdLinzPer3n7va2D+HhyLc72qbj+vKC0WzM9eUNx49+2ssR0X1nQPosbq948/Xfk2+WLK4v+ntjaXBOsF9v2S8uuTl/xXa9odj1UvBsOCXfrek6w267xRCgvJTGzDG65PD0AW3VL/B0u8JXHXF6xPzoAYaEZNBHUKRMESiqfE8yeQ9nCvLdHcpPKcuGwBf94Xc+hwcDXLcmCGF9d0uSpew2N5jO8O7FV3ihh5Up52/f4WTI4eGYMAiZTDOOHrzHu1dvuXjzluX1CzaLNVYMe4mgsWSjE9JshBQtQahY3d4gvbCXh7Qbqvwd+z20VU0QRPhe7+iO/ZqjBw/56Z//GaaD3fqWID1ABEfgOqwdEaVDRkcfEIYB8+M5bVPTNA1N7Sh2d1jdIL2Y87dvsKZmt214+/IZXb3D83s1mBeECFcg/ABnBdOjnyH9CBmMMU71cGHRgEjQXUCSZdTlhsFoRphOGR5+yvruJZgGKSAdJETRmNHBKUE8Y3L4Pl3b4KxDKYnuGopdjh8PEVYzzizfbZC/32FwfR8YcR/aa8F23L35FZ4KqPINnuoodlfopkBrg65qrl59znqZs1rcUW6vqfI9w9GYdJjQ1QXJYMZul2OMRuCh/BF/+PUfWC+3HBw/xriEo7OnhKGP1QVvXl2QjY44PDrFakvVtKyWW7TxCQNFEiccP/wJbdMRhBlF3jKbZWyW5yTZmMMHT5idPCJKp+hmRV3uEcLHWI/N3RLTGt5883s6k1KWOzA51e4t1in8cIp0BUHg4UUBZb5ms1zj5AwvkL3C1e5JshCjG5yWOFuwX7+l2i7Yb25wTuJHfWXx8PSU8XTC5vpz2nLF+vqSwA8xzYpyv6HYbXn2+e/IRiecPXmP2dnPUaLBDzw++NEHDAYpURIRpcM+jrB5x3B2xptXCy7e3BBFMU255ad/9qcI6fX2JOf1qrBmw2ji0TUrZnNY3l3RdR1CdSxvSqyuGIwHlNuLe6ha77oQdkOXXyLslrNHH3L19pt7KnhJEAZkacj67prpbE6UnrBe3pGlHpfvXpOOUgSw367wfUkUyHtitsBpDWqIH80Jwhg/PkTIlGRwRJCdEGbHBFFCU25oq1t8vyMZHxKoligdoTyPqtyxW1/dIzgL0qwfyY9OPkbYBmc1yAGz4wm6y7//YfhWYyXuXx66thcaJpOnFOuv0G2HUjVVvu+JaosL8sIwPHhEtXmF7bZE6QSLYHV3Q1Mt8YKMpu4ZRQiH9KGtSx48fkJRajaLC+IwId+sSLOEbHzEB598xOrmAhX4+GFKWWhevrxCd20/j/ZcDyYwNdZoHJqmLpgfP6SqDVIFeErQNjuU5+H5Ifm+YXX9Dco3qDAhiEZsV3c0RUlXr5FscXg4vSbfbdDWx1qF7ixRKBGiRgpJ00JdVuwWN7x99ht22zv85JgoykiHEenwAVL6/YIpHmBdwN3554zmTwijkJMnHwEN+d6xurshiEP++b/+32HbNc55fPm7v+/fy6KQKImYHD8kCON+7Jk4BmlLmnkcnQz59Oef0TY7fvl3v8W0OeP5GbtNThCB76dE2QzPSzl9/AHIKbODIYHakYY1jz96Sjr9gDiqCbKfYrXG9z2sXiBUjB+PiJIBXXneUzRMxI9++idMjx4RpkMePDkmGx0hnObwcIjyQy7eXuDaPdolJKNHWFPhpI/VC5riFTjdDyKMxo+OCOIDgsD0pX7XsdvpHiHk9SneID4D12CsBmvZb7dUeUWahDz7/a/6yVx5ixP9CHo4P8JajRcqytJnv3r2/Q+D++5A2Pt/HtDpgK5eY3RFXa549tu/oyg6tuua1XLDbn1OV+1p6pZkMMWPD1je3HB0+oDR7CF+oPC9gGT4mPnhFGsM+/UbpLCcPjwkToc8ev8h61VF1/lY5zEZ99HpMAqIkphXz1/w8ac/5s3Xv+fudo+QCUifIDnAGo0SBcW+b8tFSQwiQDcLAt8nTGe8efE1m9WWg7OPaJuKptyyvLlkt16jZIuKn+CHB8SJh2mvkabG1hu6ekUUVoR+Tpg9om06lITB5JTR4SOmUwl4BOGQbP4+8aDniNrmjrbuzZ7ZIGZ2OGM4P6EoBdu7c1599RVHpwdkWcZ4MiBLFXyLUO/W2HbBbl3170j5HuWHlGWH8DNc53C2wDZXmK6kqXM+/dnHeJ7EWOjairoE40J26xVS+bx9eY5pN1y/e4PKPqbpfDa3z7H1AhmM6WxCXdzQlAW71R5jJVJukKIEJJPDx/z+H/6O1c0bosDDNDuKXLPZ7LFiSF137DZ7Hj05RUWHGG25fPsW5Y2x7R4nIsL0KU6v+omeoMftNDc4vcOYDl3fEPmCYvOaZHSEF6Z44QiIsLZFxSPSLGAwGSHDCC8MUVJgRQrdDmFbuq4HxzX5nrqpSMYff//D0B+He2WotUi7ZL/4hmzU7xAuXn3F/OgJ+eqKplwwOzwhLzuEl3D85I/Yb2uuLq/wRM3F62cIIbFO8fbVS/arW3CaIPTIRmNaa8m3C4T0ubq4oahKtusVt5fXlGVLke9ZLW5pqoYoHVLt7hD+BMWe1d01Xatp6wV1seqx9kYiXEFX7RESVsuaqtyzvDwniiPaZkdVVwTxlCQdMRzEDGZnIDO2qxwvesD27gJHxujsT+g6je8n4CRB+hBkdL/JXrG8fo3nD4jSQ7q6pNi+6zHzzQrpduzX19S7O8bjAD+K8YIR2I4wknhewaOP/5iuNcTZGOtgu3zBYHbC17//JWdPHjE+fMzq+iUCgW4aknTI7PAIbC9uD+IRvldjmw3T+ZhsIFG+7iMs+Qol9ijpc/bokKbeEviSaPCQo9MHSNEQDk4ZTU/wIg8hJZ49x5cbrM4pq4YgOSFMZn0MGw/d1vzoZz/n6m5HuVtyd/mWB0/e58nHP6Grb8FqqmrD5PgT6s6nawrGkzFa10jR0Gyf0TUrdLvpP2JGg/RxeISDp/jxHNtVOH2HtQIl+yCoQ/QJXwumrbi9vCAIBYvrLY+ePMI5R5idYGwfJYmSGN1VCOnwpc/y/KsfcBjux6rintZ1+eLXLO+uyXcbiv2G2cEjtBNkoxPGswPefPX3BJ4AfDptCeKYURaSjE5JxodU+ZpkOOGDH/0EVNwLMYTj+OFHHB0fEvsty5tzzt9eMBmPieKO0djD8wx317cEwQiLoyxy0uEh88M5g+kxYeD18pRyj/RT8sJy/PAxiAjBjrYpQAUMxg+I0ozZ/JCjs8dEUUS133Hx6jfE2ZBic4eQEj8YUdd1j0C0EY6Y7OBTjO1Q4REIRVuco4IQK6cMRhN0V6K8EZOjYwbjA0xbIEQP/g2zKXW1Q3cdVdmAFOS7/h3BGEWx3dJVNwRBRhzHVGWBCmM++vQD1rc7hDdmcvSIIAo4enjaR7bjAcrz6bqKptjjh2OCwRnGxtR1S7t/S5gMOXnyPl58SpR6CDRlvsHzY5QoGYyHKFljtcRYQ1tpguyP6PbfoFhjir9lejABZ1HBIX76BNvtcFbx5sUzxrNDnPSR0QnIkNF4RBAlaK15/fIGIRT/3f/rf2C/2xAmY+o2pG5DnHdKVzxHBhOs3oHruyO26+P3XWMwThBECts1ONuQbza45hYlLco75PXzLYgQJSOUWSJli5OCrtnjBwla98ylctcDlwfzE5Lx0Q95Mnz7cBBY4OiDf0lTt7R1TZnXWBFTbK559tXnFEVJOHwPbT18T3D+4jc4XSK8FN0s2a/eEccRTbmj2i/7CPZgxmw+py53jCdjjEiJB1NOjjIUG6YHj8kGIaNRv+A6f/k1+/WeT378U3abBVGcIQhIxsdYp7FywHj+gDDut+NheogQAVY7lBQ01ZYgjMmLmvnRvJ+O2Z61ZLsChKCuerHKN7//B4RQGCcptqsedRlNwObU69+jjcJaQ5KECLfukZSups3fUWyXbFc3+FGGUgLpzYgiUCrDVzUKixIV6ShmdvyU2ekp67Xpq53acnD2IfvNDuVlxIMBTu8YDL17pmsCWDy/j3V0rUb5IXXZUazfIf0YP5iQzD4jSUD5Q9B7gvgAISXTacrZ4wn7zQovfkgYB3i+xDmN8A7ptI/xP6AzMUH6ENd8Tb39TR+hD2M85fBDycHRAe8/fUDbtvhix5vnX+FJx/Litxw/eMTjx8d4ns9f/Is/Isk8Ll5+jpSWtpH0/ooZQkic3lBvX4GKEV5GW9WEsY8XHxDEI7LJEW15xWA8wckQ6zy8IGY8SZhMNLpdMX/4MVL0zZvOzEEGRMkAZ2uy8QTbFZS7W+wPMfc48d1FCWcdbdsxOzxlcnBENjoDoTBijPFmKCWodlc8+eDHfPPll8TpFOlFIC1d1/D0k1+wXd/SlDVROqZpG/JtQRAExNmIYrthOJ6Sb/L7VOgQP4rYrRq61jA9SBlPBkjXsLy+o+vgq99/xatvnlEVBbpaIGnJ9+te3r3d9AIREdPUBVHoUdUa06yYzg5Yr1a0dcNgNMC4GAP4siNKD7l+8xuUjCjyiqboX543q5x2/456+xV++qjnlApASvx43n8IoxmoEcqH8ewQ0y4xTjKaHyCkx83lW8LQYaxiOBtCt8VTNUrkHJydMTp8SpDMCZMxi6tzNotrOhvj+QrTVrRNR9s0aC0wWoM3JBk+xI9GxIMReD0oLclClD/u4V1pRBAF6GZDpwNUdIwIj8iGUU/J0D5SCtpyTTI0mPIr0jhHhp+hggGYCzoj8OPHKLdgdPQZ5faObDhls9oghCLOplgX8H//P/1fMAbKfMv8+ITN8pa2uKLaVxycPQUnadsKbTya4gZtapoGgvQI1y5ApVTFAiWje06qRHoxWocI5SGkoykvkCpidhAgRILRYT/69+aAIBuGCGzPtlUBy6tnjI8eIH2Js+b7Hwbhvn2BdlxfnnPx+gKrbynWF3h+zdX1DqUCTg5jRHfH4ckZ+fotjx+NCH3BzdUbhqMxbRdidcdXn79G+R7WwdnjU6SSnL/4Ha+//orF7Y6vfvc5Rre0dUMYj8k3W26ub3EywTlHmgX3TCSH7gxp1KCbFc8+/5yq8dksFtycv6OsNHE2oakqtps9UhrCJCXJBgTpMVW+YDzpV/NCBCjpaHTIeP4AScvs5CMevveIzWrDdlOyWdyxX11S1gFefIqwW7pWgM5p8le9+E8Iyn1OU99hu+29p1hQ5xusbQnicX8le/2O4WRKsWvACZZ3W7Z3F8yOj/G8mma/wnQlZ48eMj56nwdP3sdPHlKVHeVuhfQEyoNw8ADlpVjbAI50/JDR7DHKHxClRwgZY7qOqgIVnuJHQ8JkxPrmgsDzCOJjvHCKUo6u3hJlp0j/MU76NMU7FK+p9lt0tWE4/ykIQWOPaKoN0wnku1U/IBCazbqh3G756Z/9c4YHT9muF7x+9gV3dwtWa4uxkjDyqMuG/fqWrimIhp8i1QG+qlDBBF0vexaV7VB+RFctUeEh5fpLurbCaE1XXKBcRVNtkSpAeAOC9AjlD5ES8tUzcE2PO0VQlSWzk0coKVFmQZSE/9TH/X/Z0g0hmE5nnJwMUcEJ1ptR7DSRX9F1NV44odYTbm82eIFku6tpOksUZURRSuj1neQ/+rNf4JxldfeOzfUF7149RygFpkagmUxCqqrACxXC7rHVOWlqqfa3tNWKz3//mqpqODg9IxkmfPKL/4xf/OX/mqvza9q6IIiG+KpPYMZRSODDwfFZT8lwmjCOSYYj8u0tN1drwshHqoijBw+IvZK8yLl8/juMczgRcHTymOt3bym2r8hGx6yu37FYGqqyQbie5hYP38NTvSAk8FsGs0+RMsJ2O4SfMpi9h8ARhAmPPnrMo4//HN3WmGZJkB5y+e6OdHKCMYowiVFhQBilhL7B6IZi964ne8gIzw/pl40R1liEAKtzgnCMc4YoGxEPz3BO3APbAgKvwraXSC9Fio6Dxz9D+QnK72PUUiRIZ6lqH9+TWNcricM4Rore6mmbG8Axmp2BbQjTEZG/JQoTjJU8+ehThBK8e/GcJB0QpXOCeMx0OsYy4vjBe+i2Zb08RxufIJnStRVVfktTbXGuI8ie0u7fUFV9I80h6eoFXhCRjQ7u+bk9SEK43jGIa3qdrmkROOqiwzqvv54LR5wMcN0e4aU9XvSHcZPufznYLG6IhqeEgcSTkqrcMx6mDCZPSCJDFEsOTs9Q3oy2hdH8hMPTBzTVmmp3yeXrZyzOn7O6fs32boUTPsPRkPH8ISfvfUI2HjGfj/j5n/6cycjR2gHDgye8/+kviJMhUTrh6HiG7hpefvUF5W7HZnFLWTccPXjIaKSI05g4DtjenlOVNdLLCKMY6zx0V1JvrmmrDfMHH9HVJbvNgtXNOzwvQmtN1zkq7THMMhY3NzghMCjS7PBeCpKSZUOsd0LbKJqyQPlDivW/Z3G9wI8nBGGCYdDXM+uLnnF0rxwN42O68hpjOoI4I99c8dFnn9JUOzyR44cThFK9D1oN2K3u8JVASY90mJKNZwgR0xZ7hCupK0tZhVjb4YcTnHMUuz1YTVPe9DZRdUKYPcLaPV4wxbXLXvnrj5FBhvSnIA1h0NDVNwTSEo4+QDe3PX5fgaCjKa9piwukbGnLa5Qn2S1fEPge1+9ekmQZDx7M2a72XL15xenZUzzf4+OffEiRN5T5jsPDA0K/oi41dbm7V3IN0FWvE5bBGaPJEcvbKxASRYufvNdTQ+oNViQE0RTP0zjXoNsCa2pMfY4QktHhCW21Qnqj/kC5tldhFa85//rvCZOzH34Yej6GpNrf0tQ5XdswnJ8SD0ckqSTJYjxlcN2WME6Ioohyc4fyBMZYjp58SjI6woghcRYznk2JYsnZwwNMk/c06uGQwXTev9A6R5O/IcqO2K2ukCokG01JEseTjz7gox895tGTR7z4w1+zvLzi4ZOHxIMZWeawznJzc80Xv/kV0vMp8y2DQYTDIxlOCaKYd8+/Zn50yHBySjSYsry7RRsfJTSjcQZe3E/7PI8kkWzWG26vL/l3f/M3NMWCMIpYXX1Bs7/GOkk4+IxsmOJ5EWCJszFNte+z9emUrm1Rfkxb7/HjQ5JBj4gcTk5oO4czgJrTVQX77QYvHtHWDYdnc1ABzlVINaApluw2BuX7WBSe6shGI6yp6PKXWGvZLpcsL1/ixyfYTtNUHbbbokTPSJJS0Gw/R7oCTzpkkCBlSJAe4oUThJegggf48XuE6VO8+Gf3uKAY6QX4YW/sVJ7A8wPiwYww8ml1x3KxxYoIJyL+/V//N/h+TJLGbFdLtssFVe1TFJo4HVIWfcnJjzOcjHDdnqLcEiQBUWTIV9f3ZMIQ4QRBADgPi48MZn2Xxm7xgiF+OKGrr6m3FyTZFGN6HbEKJnjxEUF8wmiS9hm6H3oYHA4ZBKSDKft9jtV7pO3j10bX6KZkffOGttrTtb2Vcn7yEN0VNE2/JfY8RzqIGY7GDDIPEQyp6xo/6B9nbb2nLFrevXzHaqMIk1OQgmfP34EMCALBYDSjLFZE6QzPt3z8R/+S0TQhjEJ0s8Y6Q9dJHjw6Ix32DSolQPgDonRGlI5oijVZ2oPGrGkZT2e8+fLvyIY9nfro4QfU+1smsxHCOZbXbzl9cAxW8NlPf4yQgmq/5eDsU+LBIc6UWOvwwyFtvQDbQrcgSiZI4WHbHHtvOoIOIbp7UFdKUdziXEk6PsZ0NWW+Rtc1Uqi+CiuHRPHs/n4/Jpl8SJQNCOMxWN1fL8IZOIURQ4QriMMVUXCH7Ura+pIkLXEiwhEgpIcI5jjvGCsHgIfRNSr+AD+cgyn71mJ3ibYh2sSI4DFID2tylGyAnp+1vn2N8lrqRiM9weHJA86ePuXycokXRjx48jFRnGC1YXZ8RqVD/m//1/+aIB5T5kvCOMKaEunNQHh07ZY4kuhmTRANyCYP0SamqTaoIMOPz1B+BK5A+QO8MEPKlGb/CqEmKJUhRQ225L/5f/4/ePH1lzT1Gmc0TsYkk1MarX/AYRCul24AgQf77ZLH731MZyWrm1vKPMdXBXWxZzB7zFcvV3z9u3+P5wuiOMIP+prldnXH/HDK0dlD/GSE8EKmsxlF3tC1LU21JAgDylpye32FbguCOAMcn/34R1T7O5Z3d2TjY6SETrcEyQipegFhFIdUdUTVZISR5OjsfU4fPUJJaLuOplyTDgZU+Yp0dIIXpPhhQhinXL19zid//F8Q+B6+H7Fb32Hbiv32juvLtxw9/gl103Bw8ojj01Nur69Z3C4oiobXz5734TMvoVw/x+gW4Q3Q1uBEjBCCtl4R8Ja2OCeIBnSdoa1yylIQxyMGg96U6VxDFA7JxocU22vi7IB8t0P5CcY5pOjJfMPRuF8kCR+pgnsocd97lv6E4XhKNPsM/z5iovwDrFU4NNZYrKmIsjFWbzC6IQgnvXFJKoQ/+I5cYdsVghy9/xLdNkhn6LqIurzCCcXxo8coct6++Ioy36KkoCoL4rDB9yStkWhjaJoWz4uYTMb85V/+nPFkiACCeI6nIpQSuG6F9NL+Sdn0SrIoHXP+7JdI4XB0WNuxvvyctjG9yMZPKVbPsWQ0xZK2vkPFDzFG8hf/+n/LwycfoGSMUBl1scHzM+rd63/y4/5P9hm+1Vj1HegIW2+ovSlOV9RtiW8dppMILyZOBvz8Zx9RNo40Tbm+eM3hyQlpZsmGKcXuAr+Bu6uvOHnyExa3F4wmE5IkYJ/X7BZLrO746NP3yYYjTHPH5e0GIQJOHn3QGzeLBl8JrG1xxrBfvWF++jG77ZIwilndXDCaHmFpmR+ecP3ua3zfx+BT5musq/ny13/D5PAJUhrK3S27XUE6GOP5HtpJxrMZbbnCNznZLMR5D2gbzbvXz5lNQ3w/Iwol7159zocfv9d3q60liGd9JkZYutaA2OIHEW2xJEhPe4SjPyQIa/zY4dU7WjslTmK0iXCuAQ+aIsf3BF4YMQqCXhKYzTHOoIIJ0vNwXY9vCZM5pivpx+e2f6IEJyAMyKz/M9tf4DD4yRitd3RVzuT4R1Rdh/LCfokmovsmmSEIBLgA60bgHaGCCtlu+5CbWOAHR+wWXyJdTVNc8eFH/4K2E2hdMT14gLWCq+slm9WGq/OYdDTn5t0FH/zoQ7JB1sMZ5I7biy+Yz2d0lcOZGinBWIF0DbgO05Y8+uwvoL3lzbPXnD15RJRN8MMY7AbpTUmmHyGCCc4WSJEhZAquYzIb4XkeWL+3KwURhiPK9dX3fzJ8y1kFRzYcc3e76I3z4YjJwSFR0jOIstGQtjwHIZlM5/jhgPn8ANPVvHn+iq7a4UcHdNU1Z48+4dVXXzKIAqSEtmupy47hKOLh0w+ZHR0RJxFpNiVNfaLI0FY7dKdRQch2W+JHA+qqxA98PD+gLjY4UxFnGbgaTEPX5QTxkKapyQYjnAHbGWQ05Ve/+pIwjFhevWA4GrBf33F7+RYpA7747S9Z3Lzt/2jUGCU63rx+w8HJexR1iPQCtPaYHz4hzE6xWrJfX6M8H6VC2vICJXv8pFR+3w0Pp8TD93tFrr6mYwxySJL1MvJ8d9NfKWyI6xYEUUaVb7GmRfpDNjfv+lAiEmMsnj/swQao3rpKn8GRUtJ0HcigL8x4EeDwgzFS+DijyaZP+++rDWjLBWVRo+srjL7viTuN9Me0jcIZC9ZhrSWIxigZ41yO8n2UJxif/BlCf03XrpDCY7de4ocJ08mI9d07TGvIkiEnDx/z8utviLMDAt8jDFPmh4eocMB+9QzljejqBV11gfBDlJfRlNe4doVzlqPHP6YqKuJsAmZPU+6pyy3CC7G66OHYaojVNaa5olw/v4c9Q9d2vQ5Mtz9stPotXFLep1anx+8xGA7JUsPB8SP+8J/+A8PpIVEU0lmPwTjFtlc4Z1itN7z++rccnh4ThD7Lm9fUJkVX12RZRDg4JN+8Q6keMVPvrtjcPUfS4vmKfH+HdQnGCBY3X1GXe6ToUEKzX73FWc1o+oi22pPEiqurO5riGj8akI0m5Js1o9GQOPaRQmMcpMMZDx8e89Mff4TVLdZ6DEcDNusFYZRR59ccHs5BxCxWLTfXdwgZ8PhsRFfnBL6jM71R0vcFVZHjhVN8T/X3cQKq3YJocIqTA5rijrIbAZqmWtDWG2R0jLAtQqUUuzuafMN+8ZLFzSXl9h2dHVKsX+P7Hl1bUhV78u2KfH3N+u6CtrimqUoQGV3XAAFRlPV+B93g+14vAFGSpslxIkSFI6w1ePHZ/eJJEKU9eG11c4lxCU3+AkyFdRFdq+msR1V3Pf/IjSlW36A8D2clQXKKsQAeQfo+URxwd/EFYdD1ocyzJ/ziz/6EweyE3eIdw1HG/OiI3eqO/ebiHrBc91xU/xCLQ7k9iARJAELgKYHyPWQwI4wSBqMY3d4ivQg/nKJEw36z7t/92hylAsrdElTaBzat7YcFnUZ3FS446PdBP+TJAOK7DnQYVJh2iXAB+23Fz/7kx1RVTmNCnGm5fvU5zgV0bcHx2RHD+SOy4ZAgmXH23mfEgQIvZjYfYrRhdvIjPD/m8OxHbHNDGIUEUUaxvWK/vsa5huHslGz68b1WNSQdzXDVG7LRhDJf0mgIkiM+/OwXDA4+wtkSLwzxlGN1+w5rPbabNW9efYF1kncvP+8lfes1XhIRBD6zw/eQnmKfW6bH7xGnE9LU4803v6Qu11hbYJ1jcX3DcBgTJTGj+Rm+V9NVd0g/o84XVOWWePI+pt2h246ug2xwgHRVD+Zd7+nKLSqaIoXr6X00jA8+5NXrDcKLcO2S/XbJfvmCcrfBmg7pT6irGi/MuLl8RV1WLC5/Q7m9QigBeOzXO9pqjxABQvZSdmshjiLy5XkvW/Qyyt0C7o1Mwh8yPZyjjfiuD6CrJU3TILwE6FDBDOGN8ZKP6LoWpH//nwdgG5RKaYt3HD/4AOgXgtY0fPjZH+NR8PCjn5CNxjhb8fvf/Z6mWLNZXROlk5527md05RXOf4Rp7tBtSVdvCAePqXcrXJfjXIW1CZYZpmtA9hj+rtoSRSO61iCVT9fscCJB0CsFnBPE8RzPz9C1RIU/BEn/HY9P4hy8fXnF7c2Sqq7AdUyPH+CsY7+5onUZo/kZ6fgI3xcIIRlkEYurmx68JTpGkwTrfKpOIBQIYcGBFAalAoQTdEay2xZM54dM5ifE6YwoCtjvt3hBTDKcIKMnfPO7/8hgcoQUljgZ8OKbzyn2Kxwedb5GeR777YpOG27eviZWsF1ckI0e4egoG3j36h377R2Tgxm79YK6WPPmm6+YHR7je5JNYWnKPbrzyAYZ5l5mGMYJ1hmaFozMqPOXhNkxUmi6eo/04l5IojvqpsAS0O4vOPvgpwgvA10jgzHFvgI5xjrDRx8/oSwkb97taLoJYfYYJzz+4e9/jVB9y1AiGU4eUxcbwvQh1iU0+ZJqf0uSRAglsLZBtyVttSAbTtC6IptM8Dyf27dfEQ8P+ndAqairLelwTrF+yeJqT9e1WFvhqxpPGiTgbEsYxfjxkK7aUWxe4fQWvAHFvqHTBWmSsbh6xvW75wynJ2jj8IIIJyM2q1uWdzdINWC5uCaMRrRtwH7vqMuctlxgXIitrwmjkLpa44UZRb4hSKb9EKK4wSLRBKhghvQUdRMwPf0pXbu4v0L2UvZ8+TW66a1R/RwUijomShOs+yFPBvGPDmUl4MkH7zE7PmGzLtjmjrvLK+pyg232ZJFgcvQeRjfoVlPkOc41DEZjJBZnJU2t2e0qhPSxpqLYrri9fIsxNcdnB33FssmZzM8o9jX70pFv79B6x3j+gLYuaLcX3N3cMT06ZXV3w/WbL+namjhsyTcrNotLQGO7ms22YzKfEaYJdyvNi5e3xHHIcJDguQ3vv/8ew+ljllevOHv8MSePHzOapPzVf//fEiVj5kfvEWcTdrs12ApPOnY3X7HfLfCEBzKhXH3DxXnL4uqSfHNBU7f40RTJBlN9RRZVSC8iTAd95Jr+mnJ5eUUymJAM56RZSBRo4sQxnYw4OH1IsVmwXtzxwUcfYIwk33cUux1N2Q8RnDVo61E3is1O4lwf3vP8BOc6/GiK1Q1emKLLXgZ+cHrKd5dfIRByzGb5jvVyR7FdcPH2mmJfUa//Him7HvJgDRKNqc9R4Yxs/CF+fEiUHpEOM6wVNE2JVIrjhz9mNBqgsNRVQeBL/ubf/C2j0YDJbMLPfvYztvuW7XJBkoDnJ5i2d1kYJ7DOI04Hvdzcy3Aqw5iSulohlSX0Hc5s8aSPH8B6teHiXU42PsM6hzGawDc4MhwVAFGcsb56i5QS+CGj1W//tXNYY/G8lmL9jmK/IRudIVXKegu6qwniCbar2a0uiUKDbTZIL2a/vsALU5CKMDvA6JaTB0/xZUc6TPGjFOsc67slm3Xe37PzDQcPPuT8zQuklKTZAcV2yW//4/8H4xTT2RA/HCCEx/ToEVWVc/rkMybzg16KYgElOXt4DNbw5MNPOJiPOHtwjLM112+/xrR70jShLa/IBiGb1Yb94gVYy/vvf8TVxSVPThXruxsGk1Nury44PjnAT0/JBjHbbcnVm+d0WhInGdfv3pHva9aLzf0LakpTKawRfROwstTVGm0k1f6i/6lbvwXTEiSHGJnx2//0OZNpQFNrRJAQRRmeB2AZTWdstxvevjlHBDO6RqPbgjAwxGmMExrTge46jOk1M127xWiLDObU5RrT5pj6rg+dAdPDh9S7l8yOH3D2wc+ZzQ9Q4RTnf4Rpcvb7O4qiwgmF0f31xDmJLt5S764w2lDsS4SMOX/+O/wwxRkYTidIKRjNTnn08BRkjLGO64uXrO8WvHr+mipf4fmKbHJAkJwh/WN0dYkfDTFdg+lymmKHMy1RGBPGUxAhbWsodufgGg6Pjzk8PcU5jTUd6eiMIJ4hVYlw7XfX+8cffwhCEqcH3/8wOBz3MD3KIicaPMa0mra1xP6CMDshSxom8xlG79mt7wgCH+N84uGMIBozPnyI7jrKYoXWLWGUslrc9GQ5leB78ObZ55y+9wnHDx6DGnP+8hlFfs3Z2QF+nCGk6k0zNifKpmgtyRJBECjS4YRqv6JrawLVz+V3qx3ZcI4TPkI4NnfXnD55DK5GeT6D8Yzh/EPy/Y7rN8+xeCSDlCLvm2FPnj7hYOrR2oAgMAgBX3/5JSoacfX2S9piyd/9278iHRxR7iv2u6bfwrYJTVXx+tkz8t2ezmXsl1/RaYlzguXlF3RtQzJ+jO+BcZLN4iWmXZMkHj//81/gx8dY06JcCbZmv13je5KLN1+jVMBwFKObNVrvCaKErisJwpC6LLDENJXBj4YIIQjTOU4vEWpM15Qkw7O+Rnn/NugcrG5XjGbvI70UPz7E86fke0OxfU2SCKQC3d4Sjz/BC+ZI6SNkRxBF+L7Btje8/OobHn/wIUoabq4uubm8pNjvefP8GR9++lPWiyuUtIzHh6yWt/z4x8coL2KzFQjnCJL7GIqIwAgEGuFKoixB+BlhdoYQHovLV/hhzHqxBKcp92vasuobfXWFFIL93oGcIPB7t1/XYU2F8scY80NSq/8Y4Ga721HutgRRyvGBwukWJStGowHrddPHoE3FcPYYIRVSRSSDAV1xR75dYI1jv7phND2iqwvy9RW75S1xnHB89ojL11+BMFiz5+zJU6xL8YOQJBtwdX6OVClPPvo5+WbJ5GCCF8QEYYTvCSazGUa3xMMzpHJkw5hie4WShqZYkwxmLK6vyQZDhBSsFgv+9m/+hqLI+eCP/ksGk4c0+xv+3d9/wd3NEuM029xwenKMMYLROOYv//V/TlPu++i0Srm9vgZTgjBM51NGsyN+87uvefHyirs3v6Xc3RAmhzj/KbZ+w/LmLQdnnzKeHaG1JY5jnJiRjk7Z3L1FRTPSJEFIn+nRAcHgFIvm9NEnDMdjzh4/IQgqfL+3CwkvoiuuwMUIt6YqLMrzSLIAicW0G4Tw6HSHF2QIvUDrHX58zHftRSEo8xIhBF21oK1rLl58Q9d2bHc+gdwzmhxhtMJ0FaurP1DkFWUVUJVb6i4mHR5w9PAn1K3CtreMxhOEg+HkAGMMq9WS63cvccKn1Yb50YjtpmN5s2J6dMb1xRJrapqqpKkGtDZF+Uk/DEAiVIQTknJ3R5xG6GbJ8aNPaaqKen9LGEDbNt95tm8vXlDte8unaXfsl9+wvbvF6RKtfxAdA3D9ePXw+BjnHHHag2PDZIAnexCA6dYou+4RjnXOdl2y22zZr++wKiObnKC1QSjLsz/8ksl0RDJIyAbQacFmvWE0PWJ9/Q2j+ROOzs7A1ui25u7iK+I4ZLd8R5O/wZiCJJtSFQVxktFVK7QVeEFG1Qim80OcKdBtThx5hMNT6nLL7OiAqtzRVgVROuW/+t//H5gfHWO05tWX/w6pFD/60fu8Pr+ja0o6G3N3+Zz58RMuL+4I0wOSbMSDxz+mqiqefvCYzXZFU1QI1aMygyjmg6dj4mxMGA+o9lsu377jt3//S+rWo21K8t3tvaQdTHuJ8nycnNM1JavFW7LJIZ4S/UGzHZvVW6I0xleC4ShlcXUOzjEYjvF8gR8GSDzCYEO7/5rd5gbdXIAzOOtIRu/T5a/x0wNMs+6XVvfvDM5akoM/Q0hJmByg2JHnd+jyLcePP6Mqlwg0WnsY06uAu7Zgt7yhzDu2ywX7zRVWL0gT797DAQenJ7R1zsP3PmR2eHSfy8rJRiMevPcTpIJ8v+fu3TOmJ0/oiuuegucn2G4NpiZKR2B7Y0/XSiAgCMYob4IxFV40xIsiZGBIU4mKxqyuv+Lg7FOE26H8DGtLomRAGPdKM91sfuBhEPb+lUuSry9JJo8ZHX2ClUOqoiOKQ+ann+EHHm3T4d+3pqLQ0pY7wgBcu2A0ShlPDgljiQrHCC+hawVVfs1wFNB2lnj0ENMVvXc5y5BS4axA2Zp9pZkc/4QoHtIvnzq00WgNpu0w1Ybp/JDFzTnV7hyhfPbrNeV+jZIO3w+JwgDpD5gdzLGm4eZmw/LmAuMdEw8f8NEnT/lnf/4puu0Yj5NeWaUsWeqzuPwa2yx6QocXkAQ185P3yGZP+dv/93/Lbn1FGmhuzl/zy998zmLV8fuv3/Hq7Q3X2whJy/rqJfvVJWE8Ihmc4NpLTLcnSUKu3r5GKYdwLZYQP7CMDx4xn0d0XY4IR2ALTh7MSAcdVq+IswnL63d0XUs6nOIHca+TDQ9oW4s1DdZs8dJHeOEIFZ8icIhvdcESxhMfIQXWtPjxAZ/94p8xn0d98NCP0LrCU3u0zgnTCXEc48WHpOMnpNmAKDthWyhao6hrTZRO2a52SCS79aLvrTeWyXQKSLwgJswOmB8MycYzsDnV/pwqX5BmCYvrK7pO4+QIi0b5Kbg9RVkQxiFSdEgV9XsIUfW7AzVCqQAVhAzGU9r6Bmugrjb30feUWmuC/xm85P+CoF5Px9ht7sg35xT7G+6uX7K/+wNdveDN89dU67eEUUg8GHFzdcl45COlR9cJ6nJHvnrH4mbF5u4Njz/4KaatuLneIryEbBAyGM3QTYOwfem+61q0MQgvoikq9mXLxz/5KW9fvWEwPqGuCpqq5vrdS4JkQl1c03Utd5fvCJOU0dHP2K5u2e/WSFqy6SFNU1Hsl1hj6KoVtrnhbpGT7/bMhoauXmA6h+/3MpMsi1jfXfEPf/s/oJuKpnjJfn3N4dkTPKV48PARcWCxpuSzTz/l2TcXCASzoxOiZMhmcc6b1284PZzwz/78M7a5x6tnF9xdnmOtoWtzsvFTqv0NQtScPv6EKDmg2l0Txz5hPCcdJAjRIWmQ+oogGhJFjnh4SpQc43mWo4en0LxGCYEIj7G2Q4oIZ6ueh2sMbbXGdDVtfsX27vV3LC2BRKqU3eoaC3StZb1YkB7+FNMJMIL96g2oIfn6GoFlt1n1iBfh0+QXfPPFC2bzI8I45NU336DChPnxCdl4TFfvaeuOH//8J9xeXfHhZz9lMMz63rWc8Kv/8J8Q3gTtDlBqgG72hL4hjCdIDKZ8jnMCP5zxzW9+BSLqO+SuwrQFXnyIp1KUUhizw1c+fjRkdPhztO4wboD0EjxfEfgRqOj7HwbRzzxASLLhhOOnf8zi4iuCICFNI1qd0tmQIMnYrpfoekuSZCxv3/ZSkiAnCHyE8hmMY6r9ivXiDtNt8H1FFAV44RF+eIgfDNDtju2uoyqWbBbXhJ5DehAGhu3V73jywRPWq56LI0RLMj7GOUs2fcSLL3/F5OCYzc0rnLXMTz9lMptRVzmrm0u2t1+QDMYIVyO9mDid8pf/6o+ZH0yJooT9ZoHnCbq6JIozNotznnz8R3z84/+M0WzCbrlCeBGvv/6S4WxEvte8Od9hbIfD49NPT5jMJsyPTvjZT95nOrL8Z3/6U4aZR1527LclBw+fEqRH5JtrtstL8t2OZHRENnnCYJjieYZOO3brK6wp0d2uR6lYgRfP8MKY6cnP2O0kCINzCikq4skHfQTDNHj+mKa4QHd7nBPcXS/QVuFs2yuChaNti+++x7qr2e0Mu1VOvitZXK+omoCuuqaq816uXt8SJ0PK7TldW9O2rteaiTFPPnhI4HnsFms++cVfgtEoBZvFAi9MaJucYl9x8ugJYeQxHI4Yzd/DGkk6OmJ9++o+KbvGWEEQD9lvb0CGBMOPEUjePL/k45//OV2zIEoClPB6waby6bocrQ2mK1DK0pS3NLVBiI4gUHRt74GwzRJP/QC85P9UVqI8n/Vqy3qtKQrJ7W3B/OiQ+UmvgxrPZ7x7c02QjIizB3TVHmP65VvXFfiiIEpGjAaattPMDo64ePklt7cr6t0V2Sggm5wQ+A1JHDKephTlnjD0CYMQrQ1NneO6HU63NHVB4Al2t1/jdMXjDz9CKMn44BQ/Sih3WwbjA8YHT8gLQ5w9IAwahpMRi2XBN19+1Zvthabc50yOnuCHCqEUo2HMi5c3WASBX9GVS4ZHf4r0xtSVYnn5NYPxgOOTGZFnqHYXJGlKlA4otj22pmkls+MnpGnEiy+/JEpDNotLLi4WLK9ec/7s1/zhd1/TlDnrm6+p64bVzVtMV7C42dM1OfnyDdZo6s3n+EFEvf49CMN4muAHHigP5LifGHkxttvcl1ti4uyMZn/JZH4AekVXrwizQ6JsSLX54j6LDJF3RxgG3F5eoE1JOp6S331Nnjd44WOkGiBV1hPTTUJVe4TJmDAeEaYpXjCjriu8cMDd5TlS2P8va//Za1l65ndjv5XjzunkU1WnUlcnhuGQMxpJHlmyLMmAIcCwHwP2C8MfyZ/BBmzDsgFDfqznEUdDjmZIDmOzu6srV528c1o53bdfrEpNzgxHpFcDVYXd++yzz9nXte4r/AN5FrCYj9nZ28M0bdaLGZZtYeg6y/mYbs9jdLRLu9NGiJJwGxJkPeaTJUXloKoWqgLxdsH12WM0OUVRwbQddF0nDsYU6RJZ5pSFoAxfkKUOit7B9XdRNAdRZjVcRtOQxYrytXnj750Mb8TDkBJNVTHY0O33yeIZp2cxV2dnnD7+W1zf5PGXz/FcE7Va4fsGqtGlLCJs18Zr7RIEAlSNolSwTAspJZ3d2+RJhKopKOSUpSQMQmS5QlNNWk0XUW4RosDr3CRPY7ar2sqpKACZE+cGm1WIIguKZIPf2ifPYvKy4tEXj7k+fcbhzRsYlsN8PGE5m+N7gp29Q6gSKvF6jl5lWLZLkpRMr55x+84Jr549Q+Dg+R7h5gopCg5vWCRRgWOpGEqCZvcoq1rW/tadEyoBhrLFcyNk+pJcdPjmd/+Uo5t3MAyXvNIJN9e0Oi0MJeDhZ7+qVTjyiObgHu3duyhiiqbrqGaXJJqhaD2yaIrdOESRIUq1qDf21PqhRfSKKjqvhZLtHqrRQBEplcyR1br2kM6hTEOUfIXpn6DIekqoah5Kcc7BjQ6+G6ApCYrZx/J3Mew+4eqSNBPEcY3u3T04qCU8t1PW0wuEKMjTDd3hDQy5IEsSkCp7B8dkaUIUBlxdnHF1eomq6vQGI7bbhCIJ8Rp23TupGpZloOsOqqZQZglFWdBoj2h1D1B1sz6JqnrfVWZLpFKDRA3TYT7f4nkaVbEgTTMM20ZRLXy/iaIamN4+qu6RZ+kfkgz1VcO4FRzX4qtf/xzbEhzdvIGtTdk7vk8YbrHdJp3BDlm0JdymZFlJUapsVzOml9dcXccIkZAXDsHyAlFsUasZpuUg9QZZBtH6kvnkGsPeIdk8RZYFtj9C0xVsx2By+nl99BYF/eGIKl+wd3iCbhQoeod08wiJJAleYJsxD77xDTq9NtHyDN0QqGoTWa2RlU4UbBBC4PoDFvNZjSitBIae4w/ukCQpt++e4DgOlxdTDo/38Vvma2Hb17NrTYdqxv27A/LgGZrZwm7dxm01Mb27KIaLZihomqTZHjDY3UMrVvzqi0tMy6c9OGQ5X/HVZ5+xXb3AshRWV79iuVjURuKDm5h2n9V8zPhyUn+oqkYlnbo3IKfKrpFKgzCMqZJXZNH5a6vchDwNkVLD8o/xWruUVcX1xRVJFBEFIUWaI7QuKE1kFVMWFroSY1qNWpEu2+K2D0jDOa4jUAlJgmsWk+esFgE6Ifn6GXEUEEUh+7e/jel6PPn8pyRRiETh4Og2w90R08k1WZby/NlTdvdqoa/hXs0/uLqYMr74ClWRlOmSy7OXqEg03cT2GgwPPsIyVFQREEYVtjvEtJuUZYnrNfCcjDzfIISBqmqU2y8pk1eU2ZSyCFDVmh1nWX8Q060G6dUaYhLNHvHH//SfEMcSx1wxWxkcntxjOT4j3ixJtpdUWCTJkqcPf0Wr5ZOmKuFmju1o+J0jsniK7vTJ0oCiVBju9MiiNbrpkJYGXqOBYZlEkUKlehTxlCS3SMIUu7nDfHyNoZVkBaThEqolzc4uhmmjO/tsp48ZX66YzWKi7RS/2UEqCrrh0e7bOP6AydUL+qMd1vMZKAb9wQCRh6TbUyx3F9tqsLMzJMtDsmRLmmdkWYCqKCTRFInCs0efs54+w9RipN5lHbq1gWHDwG0/oLt7l+Hxd/CbI5JUsJp8SVVs2dsfcPPkPoaRo+kuTvOQZmefi/MFm+UWicHRgVeT8NUGtreH22xjGQVZdAZooGqk8YpgsyLLDLLCpShUKvqkSUiRSYo8QtObSFqEqwWVsKiqgtXWZDmbM7u+BkVgO01KKUnCJaqas9mmJHGI1Fy2y3PyXMdxHdKkIolzpEjpD3fRLRfdO8JuHeP4fXYObzGZrJnPF4wO7zDYP6Q76CFlQbPVIU0yXj5+yY3b91B1ne//f3/A1dklk3FAr+PR6R3x7PEXqEaTZrfH5PQn5FlClc3RVFEz3KwRfrNLifVagE6poRtWnzIv2SwnqCooxi7r8RM0e4BhNVhML6jSRT2Z+geuf5Dc81ZND4kQkjxe8uvPn1HGCyz3PllacP3qIZbbwXU1Xjx7hNs22B3Y7O66oKjoWsntBx/w4skZZdqo9xRK7ZusmW2qUqIoKpqq0emMePXsS8JNSW/3NnlwCaqPoSokUcDe8T1csxaqVdS47gUyePr4M46P9nB8FxSXW/dryqmQJuPLl2hKhWXXG9br08f0d25h+nuYiQIU2I6J6Y0Yv/gF/VGP2VXA5eWCw4MBYVxwcvsQIfVaszMc0x59im5YtPu3yONTTKfBjTt+vfBqHlPlFVmRMb96Rp5bdNo+k0lMEZ+jYDEcDvjbH/8MIRU+/uQWAsnzXz/HMiw0o8totE9RSIL556hmj/XGwLHaSNkiCaZoakVZdXj1Yo7IvmC4d0gUrXEatdFJt39AJSWaUhFsrvB8hTRtYVoeh7fukucFipSsZjViQNVsMGsP5p3dDo++/DX3P/kOnZ1PCDcrXDPCchxavT5pHCC1Fpp6jRAZzcFtNMNlNTnD9z0qIZBVRVVVuJ7NV1895HC3z+HNW+wf7KKbBlJK/vX/8l+A1DANkzAKCTdTZBGxmk2wLZ1Wu0USrhDFGq/TwtX3SINH6M5tZDGhJMWwhqTxGlXv4fo+hu1TFCmVtPAHH1EVGaJMUERAlQuKovsHnAzy/dNB4bNffsHdu3dYrzP6g12Ob3/ID7//n2h0Djl9ccXJvQ+QQrBahixXJZvVCkVVCEJouAp5sqHR6jG+vEI1PHRVI4wj8iwiCTcEm2XtQj+4y/L6KarhIcoIx2lgmbImsJCSZBLfb6AQEYcxDz58gG63iNZTkihEUVVsbw9FhWZnD9NQUMkQZcxw7zadboPJ6a9AVCRRyq8/+wKVknZ/iOV4NNst9vZ7qBqvRbESsiRDVQWmu0sar/Fat7AaIwz3Fo3OPra/y69//H3yNGJ+9SXrq79FM9sU2SnXZ19yfvaco5O7uK0RmpgwGrb58OO75KXDl7/8FbduDnjy/Irl9Au2yyWff/Y5m/WcLLqmymY4rkYUa6xWBc8fPqIodSqhsw0UHL9Dr6vTahToukaa5Bimj27aTGZrttucsqwwzA66YWAaJlII0jhmPp3jNbv43WNsf4fNOkIqOooMyeIxVR6Q5A66aVPlAUJt8PjzX7KaTnD9AZvlCl1zSbOKoihYrXJUzeLixRMkCn/+L/8F/YMbPH/0mPVqQ5EXlEXBaHef1XJBJStUBLbtsXt0kzTJENKkrFw2qwjD7SNFjFRVTGdAnoYIdQ+kQVVW6IaNbmiomoWsNq97xxmaaYFqo6oGmtFBt3skweIPSAaF11iW+to9vI3j2tz+4ENmkysW0xUffuNPmF8+5NGTzzG9AWWyIC1VknDD2fkVqqaTB9fYzSZBYpKES0DQapsICprNLhKVi5dfEQRrklQi1QbtwQGIiDguyJItdmu/dvqUNv1RHylLuqO76LrCfHKFyEKizTWj/duowHJ6gUhOUZWcq+stly+/xPJGCKGi6CpJUqDILbbb4fjmAWW2Qrd6lHTRDQ1bW+D6AzxH0uzuE0cbpGaRbq8p0zlZukFXVbJkCVKlKhN0JWcz/SWWrbANodk0cY2E3uiAvZ0OupJg6JLO8DaGaSIrgUpCUhi8eLngW5/epD9o1SbeEqR0uDxf8PTLr7DsPouLh+RphOHt86O//C/85K//ktv37qIoNm7ndm1La1ssF1MqYTKbTCizkCyvsXnzyfnrYXnFcjHGazXx223SOKXR7GE5Hdr9XY5u3qaqCrJMxfRGqIqGpntUtFgt5pzcPmHn+C5FuiaOAvJSZbuNcN0WhtySxOu6MQdc32Nnb4edvV1mkxmPH36JrusIIXBcB1WBcLPk9NkXSKON6XbJS5PldIzX0EmjiLKQSCyKrCDarNC1gqLSmE/WGKZDmsZsF08QlYZuubQGJ/idEyyng+2PMCwd0+nitXf+gGSA19DXOjHOXj3h+aOfMxoaDAZDFDVGU01sGwohGL/6isPjAxxbpT/a5/b9P0VWEKUq0/EcVYZcXY2JgxWvXp6zuH7GevaMF08fs5i+xGsNsS0LReQIKShKvfaKRjAfn2G6O+iWx/h6SyVUfvyDv6EqYip0kmBKHOnk+ZZ4O6cIz2iOPibeXqKIOiBePvwFtuNQZhGO166NWJQCT4+w/V0UmYJYI0SJ7e2TBKeoqsV2dYUsM6piQ3e0Q15ZxMEl86vPWE1fsV0+I5h8ycGtexhKQBqu6Q0PUHQHzWyjaDb9TokQJoZREKxDzq8LNNOh0d5n/3CHTtNjNXlIkjXJoi07+zd5+uwU3/e4//HHvHz8GM320F6PGL/13e/wv/j3/x7bb+B4HpWoSKOcICh59OSKy7NT9o7u0ezuMNo/RNNKbNsljiMs2yBcXzOdrOj0R2RZTJ5lLBcLVL2JYXpItUl35yZFUZHEIZPxkuV8Qbuzi6KarFdrDKePplSomsZod4imqdh+myycc3RyBNScGAXI0phgE7CZTbk8PeXhL3+Gplm1ujs67W6ffrfLeLLgV7/6guU6o8gL3OYIUYQoIsX0Dujv38EwfVRV0t/bRVEUNLklWp3R6N4ki1bk8ZwsvEaKAlBwG/tIqb11Zfu9k+Et302BYdvh4PYH/ORHv6LZNti/cZ+Hn32f7XrFv/qXf8JmM2U+j/FbPaIoo9Wu/ZRN26PX79HuuGzXC1rdIctVQRynmKbO4Y0P6e9+gmV7yKpgMT5ns9qCqEiTBUVe0PBdnj/8FY3ODuPLp8TBlOFOF7+zy2C4i2Z3yLOQUmQ8eviURu+APIlpdE+4/eF3GR2cUCaXROtLNqsFna7HcnZFvHnE+USSJytMu4tju5Rp8ZprvYdrl4gqQLNapKlJsj1luHcb22tjOxad4YjL559j2gZ5FrCab1HtXXQlYnz6Ard1i2Z3h0rooJZIVFr9HY72W+hGA0RKuJqQxGsysYvfMBE02Dva44//5J+wd+MDusMevZ0dgm2GVG3anT7dwYBOfw/X3yEMchA201nM5HpDuz2k268Vp7ebEE2BRmeHMt+yXa25PL/k4eMzOt0WZ08fE60u2CwXJMEVimZzdXFJJSRFVrKzO+D2J39cB6ZrIaqylnyvSn7213/Bcp2i6RqKkjKfXhBuxvQPH2BaJvI9BfeTB/exLRvVMFnPxvyf/y//PavFildPH7NcLkhildnVc2w9o9XQ2N9rMTq4i+t5KJqDRIBioGkqlttB1zVUavegoqjYbCSqquL4I8JIQTM7SCHJ0hgpBXlyzcWzX/zDkf6OzfbbV5pEsu4Z6n3DD/5f/yf6A42nz0O6g0P29zukwZQghhsnt5nPIr745c84urmLZdisVgEffHyPIFRp9zyKtMBtNLh8dYZhFSRBSKvb5sVZwY3jHVzfIAk2uM0dZuNzOs0SNB8wmI3nJHHM3Y//iP/wf/sP/E/++Xdw3A7bcIkiQuaTF7R6t4g2U/ZufECWK2TRCsdzQERolBRlTFGZjA4ekKcxaTRns5jQ6B6hKgLbcXD8BkUpKdII2xsRL3+OUPuoei2UloZTBE0op2h2F9v1WU+uafZ2UNQtwWLNfJlzeORxflFy6+QYyyrYLi9xXA/VtPFaHxCHC9JoA1IhTWIq6WJ7DVzPQ9V0bMcnSwL8dq1SLivQTIssDevT2LUo85AkBqloRKsrKrXBcvKKg5sPiKKYssjYP9yn0e2BEKwWSxbzDc1mizhZo1KhaR7r5RLbtPBaDkmUsl4uafoamu3R7Y/oDAYUec7k8pqriyv2DveRVc5sOiUrJHfuPeDVsye4rktVJii6zkff/PbrO/E7uPjPf/RzdvcPkCLi5Ysrul0Pw/SwbJ08LYi2EYcnB5w++iXtboMbH/4J6uvb+WZxTau3yxvEbRZNQHdQpIYQGVUe4HdvIMqc6XSFrYav5YB8hKLUonCypNU/+HvPh985Wn3DjAIwjQrVHLG/O6A/6NVeBo0bPH56CSLHMjUOjnfoDvdp9/cpkmuqSrBdLVgtFqTBhCBYkUQpq2VEszcgSRXu3D7m5Vd/waun1+imBdWMw5O7qGaLojTxWx1294e02xb/+T/9Bf/6X3+b8fWKzTag6cPi6jHt9pDJ1Zzd/X10taDb7ZKnS37xk5/S6N4GxaQ7usVyvuHq+c+pqhhdM/A7e/zqpz9DM03yPEUzPDS9g5QKq8sfUGkH2N6QKg/RlTW90QGjgwOk1Ii2W5JEolltymxRw0oMj9v37+A6Po6ZMbv4ks1yi9v5BKntkMUVwWbF7OIV0WbCehVRKS3cRpdWu4HbaGGYLnm6xGv1a0ZbaaDqBgqgGw5CVkhZEoUp6+UVeXRNqzMijmLQ2tiOiShi+qMh4TbmRz/8CYvpmPViztnzlzz76teMLxbkqaz1SpHohkYW14Joy8W45mOLklfPn/PZT39FEm24ODvj8OgGwXpLKaDb36Hb6YMCg51dbMfEtk1avv16Cqm8/ruOpXsf3X6tiFLywYd3EbKizALm1+cE2wn7tw5I4pDBwS2qMkdT1bev47d7r5NKkiUBWTSnygJM20fTPZIoII3WaLpJt61guS6GVXOlNdWu9Xz1f3h4+o8ok+TrnBBEwYZgE2E6NiJ6wqsnXxKvp/ybf/fvKEXtlOP6I9azZ7x6+hUnDz7mq0eXjA73afkNDKdHkUSMDvbYPbzL7HrOs8dnWLbK8PBjLLNgfv2U1WLD6ZOnaEpJshmzHD/m8cMvGd24zYMPjvibnzym2Wuw3SxQtBY7N/+Uy7Nz0spCt7u1qJUO83lEazDiZz/+CRU628UZvY5NXgg8r4VmdijSmO/86R/jN3to5OSFRrC4pEqeINHpdBRm45fY/pAoWFHkCZenL5GKwGs0mF89x7RMbLdLlkFaFKznG/LCoD/ssnvyLRqdIzSldiZ1Gn0MPUHRPQyzIsnAaezjNxu1iWQ+RYqSsjJJwg1JssQwBWURU1XVa6XvlDyr3YhU3UIqDn/1Vz/H1HU2mxDdsOkMRhRFjVxtNZtcnM6YXE3YO9yn3eky2umjqCr/w3/6S7xGi9l0QlZAVQYoig2o2I7Hzv4OvX6bolC59+ABuqVTiZyyqCV4bMfBcSwUTSHYbuuEfNtnKm+1txRF0mi22DkYcnjjBr3RgI+++W0Ob95CYjPcvYkoMqpCoCiC/ZMP3+PgSzSt9nCWosByGjSGH+I2D8izFMtyMGwXKWqEtap7BIFCHOcIWVJWOQolSTD9Q5KhdnWr35TKq8uI1WqOWi2JwpjhzgGqphBHEXG0IYkT9o6O2Tm8h9fskZZdXCNmfv2UUug02gOanX00w0M3G1h6yAcPbrAYv2Lv8IDFZEyn7eO1buI1OoTBGtPWMJ0RR0c9trMXNBo2/W4bpQjpDnZZTU6hmvGN730X1zGINyuqCrbLSz759nf57//j3zAamFh6iqIPKKTBYPcm26Dg2ZNnmGbJejmmKmsp9OnFYyBDyAaN/m3SBFyzwrAsMI4pKpUiD3Hbd9HtDnm6od0f1jATd0CaKgSJgt/doxQaZWVCdc1m8Ywyj0nDM8L1gunlQ6Qy5PYHH1JkMavpJdOrS7bLJRdn5+TplqpYEW8jkigiL0yKLGa7vKTIcpI4IdwskJVKnGq0Gzq90S4ff3KDLz/7JZv5mKuzr8iyjKaroRLjNdsU6Ri/YdXBsV3wZ3/2z5AIsixnuLsHOOzsdHAaPobVYL1ak4YryjwhL1KkKBnu7tHujPjy17/i6OQIr+Gxs7uD32zg+W3Em/XV6+aZ1wnx5qQwTLNOECCOSwajGt8WrK4x1CmrZYmiOu9OldfPzbIUFLN+HSle04VPkUh0wyaPrkjDZc1wK8FrDsjTCE3REFWG+oeYotcZ/fqoU8CyuhTxjMl0RVw6qEaT0d5+Le8YJPhNhyK5Ilpd4zUNRrtDhvt38BtD4iQmTApWixmbxYqqTDGdAVLx0ewhi+mKRtvBbt5k/PLXlFmGbjgUpUqRJzx5Nke1DnHskulkRm90xGL8At/XsWyfZ8+XUITYvovX7DC+eM7nv/wF/7M//4hGZ4TbvYVlWzRaI1qDW6AIdgYqncExo/0jkiijkirDgYdrJ5RCQaKCZhFnEpGtKPMloohZzubEqwscx2X/1reJNxMkDmfPvmL/5sdMrmfMxxeowM//5j/z05+9wGt2WU9+TRxKwgiEdQfT2SHYBiynY4Q0kfmUySRE021ePfqc1SLlh9//Ad//H3/IT/7rX7GZX5KXFl7DJc9SOoPDmvYaZ9y8+wFREGK5Lfq9HmVVsH9wg8VkRZFv2Du+yWh/F8cdUmQb2r0ulmMy2Othmiond2/xq5//FMfR6e0eU5QKeVGyf3Sb9vCQ8WSOqjr0d3Zw/CaNlsvJ3Xtv4yQvci5ePEO3NDbbGgP0ToTubUz/ZoChqoLHDz8jDuZgNIgijaYXspo9fcvVzpINRV4z8jStDtkiC6nyjEarS1EUiFJgNw9RdRtNd+kOXaTI0E0XXddxWkck68vfPxl488O8rpT2D9q0mwqy1LBtm+V8SZ4uWc/PamittcezR09Yb30W04o8S1ksNjz88oLLiymL61OanT6DnRbTy6f4rQFZobIYn+MYKU8fnyKkwmi/yWKV15ksJY7b5u79ewSrMevA5nvfu4+qppRSIBQb2+8SbWd4bklVmTi2x2h/n5t3P8Dr7GObLlevXmI3BqiqhmE5eI5FVjrMFgXz65eU2ZrtckolXMoiRyVFkZBsp/R6LfIsodluoxkeN07uYDkWQmpUWMznG14+/gEFJrZjcLijUlVwfX3Np5/e4cGHH7JdXZAkGm7nLoruYWkV68UVy8kZ2ygiCjdsg5y8rPjRf/0rVM1is17SbA0ZDgbcuH2C29qnyrckYUJZVMyvTymSFQ17TZFucFwX9bVOqZQOs1nAnY/uU1Y20WbB5OxZTb4JBYqIcf0GoohJ0wK/PeDm7ZtoVpOiqHAtjSSJGF9c4jVcPvrGp7RaFlEQY5oGttvk4PjgbT85vbpg5+AI09Q5uXPydor05u7+JiWU9x4r8pwsL9k5OEK3LH761z9BtQbYts3k6oJwPaMqC3TTI4tWr3VXIQmXaIZLWUZYjk8WLzDdus8zNAVUhSKOyZItoiyR9Qydzu6Hv38yCPHG8rb+r9lsoGgex3fvkoRrBsM+23VcS55rDfJ0w/2PPsRyVBpeRLDZcPPmHt/5029wejrDdptA7b558uDbeM0uL149pTfsMp3OOLn/Lc5fvESUMXfuNdBQ6e3eQyg2s/EVcaoThyGWO6RIluzvtPirH/yY81dLTMPEax5QZHPyLMDSDBQKWt0OqlrU6hLLLS9fvGK7nCJFhVQ8LENl//b38LqHGJaB7u5gePfQrQEKFUUuiaKQJI7YrBIUzUQ3dfLKZz4+JdpOefjolPbom5zcGLBdB7SHIxyvT5LrLAMdzRyhGSMGe58SBRFVnvL4i1/y+NErfvyTx+RZgeW2+eGPnvHo2YSjgx0Md0iZxXzw0T3ufvAJIk8RVcpg7wam260plDd2yHMN3ezT7XXQ1bRW1hO1dP92cU2ezFivpuRZgOepmGZJv2sjNZM0DlnOpzQbNp7vcvP2CZpeousVUgo8R6PR7hKHaW2q6DYIt2t0rRYpU1T1tTIR3Lxzj3avw/OvnhGuJ19b1sJbPtG7k0KpJe17wz6HN29iOU3+2b/481qg+sanDHdO8Jp9VM1A13SQ4vXJUo9Yk2iOouqomkmRLGv5G82mqHLKrMTyWkhqCdM0DRBSIqT2+yeD8rVzTcFzbdq9I5I45GBPQSEjS0tWK6UWtnI8nj38FY2Gj0LOq6cvyeIVZbbhow+GiLKgzHPmkxWaJhhfXvLHf/QxL19csA0Mej0Hw7apaGNqKVkWsrr6Gc+++Cn9nRt0ey1MQ+GXv/gV642gMxzRaduMdpqc3LlNnJRMlylZmhKmDpeXM6LVJVFUYZoacbhkvVwTra9YLxeMdkYIKZhdnpOnMWi7tYmgpmPZFnGcs91E6EYLzzdIM4gjkzhc0+v79AYDPEfhj7/7AScPPiHNAvKsIsstvvr8CbeOOizna7I0RdEbeO0RWZLQ6gz56NNPOD4eEYQhsox4+OWX/Nk/+S5/8t0P6PXbCCG5cf9TWt02XsNkZ2+H7XJKWUgsM8OwPbzWiChV8DptDLdHEp6xXY7ZORjheg7f+JM/I88Kdnd9FNXCcgYYBuiGzfxyTGtwQJ4pJGHKdhNw/vwCTXeJw5Tx1TlC6oiqYD2/Jo7q0me4OwLl3Z3+/aXscj5ns57WO5U3J8LfMbp/0y+oqoLj2nS6HfYORuzfOKLVbqEoCrvHJ7WfggJSCuzWPrpRN/aO55NlCqJKUFUN0+mj6Votc5puMEwDKSo8v4WiQFkJNAVU7Q9Iht9MiutZhaYGbLcrcjkiWE25vJywe9AgTHKqPODux/+UYL2mMzzk0+9+hxfPTpkvQzyvoixiXj76AtOIKZM1vdEeUki+8e377O7vs1rN8WwQUiHeTnH8Lu3+AY4t6A37KFVIf2DxR99+QG+wg6po3L73KbOrLymESVqUjPpNHj8+I02WmLrJ/W98kyQOWS82uA2P/qDLYpUg1Bam6aAoBn57F9Py6HQbUC3J4itsW7KdPcXyTDRlRaV0sPQVRfiMNB/yix/9NYpqYRgqVILF5ALHtcnSGF1TGQx3cTrf5k///N/R6zfYLsYk0QzLsbk6e4JpuxzcPGF31GX/xgnf+OanuK6FYThYpkan18Y0dNzWiDKZoukmvX6H9eyUNC2Jtys6gx4N38EyBEIU2I6DaTdrH7mqYLO8Yr0qAZf1YsbF2RgpdTy/SZpl2I7DYDSkN2oSr66I4whRSvymTbvTZb1csl3OXv+uVRQFDNPCMAx+s/yXUmJZHvc//pSr09PXz1d+44b6hg7wXoLU46b6/6nK20lULZpcnyiKoqKqCqC+/r4qumbiNXaQ1I2yplsoioLbOkJRQDddSlGwXV5jmDZlEb9GM/yByfDmh/j2n/1LwkQninM8V9D0Kz789D6W2+bhV5fY/j7zq19imjlZGrO8eobUGjh2i+VaYJgCRW/zox/9ktn1OaaW8OjXP6FIc7yGzf0H9yhyQVmWSK1BEq0oy4y940PizSluo1NPNeIJlqsRhgXtrkGre8hqNuXs9JJeb4879z9kcn2JbTkkQczuwR7nlwt0o8XRyUeMdof817/8C5bzp6TphmbLQ9MEeXhak4Z0hzhMcZsjeoMDbG8X3XTpDo8ZHt2j2zW49cGHhKsJURBgul1G+zcRpUkWXaEbHrPpKTuHu9iOzdNHZ+yf3CNLQxaTVyQ53Lj/KUGQML4cs5lPWc7qgHe9Bm6jRx6tiMMVcRiQFS7R8gLNHdEbOkipI0VCkdXq5WURIssAxRghK0G8uSLLK778xZfoloGqK3QGh3TaGsHinLNnL/BcCLYpmpZj2j6m7XLjzg32j3fYO7rFwa173P7gA4YHR1QSVO1NaH79Bvm2/s9KNMPF0FW8dvNtgvD3LHXfJUn9HCkl4Wr+tSR7x7R8p+wIvBYo68FrYWxF1eqSTYIUkrISJMGcNFxguH1MywYULp9+/g/G+D+qTCryWp0sjBL8ZofDg9rA7noqEOqAJDH41icDrl9+Dlqf2dVzou0CzXFo2CmqmmFaPrLK0ZWSO7c/wG+3WE2eYTePiLYrnj/5gun5U3R1SZwrnL6YsJ5ekEZr5pMpy9kGRbVAH+LYEttusJhOodoyvb4kjSd893vfYjbbUBYJJ/e/RbPjs9kK7MYurlWQh2OysNb0/Pf/3X/HcvyEMMjYrudk8QTVGZKmMUV0ieP3sLwWuq5g2z5lLlBVi6IoMSxQZEZndEhZlJR5zvj0IWGwZrgzxGv3ODgc8fLxVyRpgmPFzK9f4vkeo4Mjjg73SaOEr758zv/2//i/5/jkhFa3je21SbMSyyywfQ9DlygiQ9EsMBqsZpes12BZCut5xFe//JyLsxlpopEmIZvVisvTp2S5y3K2xrEtGr5KVmo0ewM8T6LoLTaBBNXiF3/7Myp8TNtneHCM47pvP3fTMnE9j+6gS6PVwLGdt4H5/p39DaJZQSJkLQA82nkn8Fvkydee+/ofb1EN708sTedNEn0t9mvJefVdqL4ps2qZTO31c+tnCynQNQ2vOaBMI2zXQVN1DNPj+MEf/f7J8PaHeI0x2d3bwbRqp3lRJrw6H7/WSVpiuU3CJGW7mrBZJ7QHR7x4viKlSxQLHLfD1dkFveEQv2GhKjpFAbfv3yQKc+7cvUu4uWL/5Nt4esRg0Gb/7r+iEha6VvHw4SuiKKAstpyfTanygJ29DuPrJaoqGOzfp90dEQZzmr0DZLVF1yW/+NufIIqCZmefcLsiDEMMw0BkIY3eTW7fGSKrFETJ4vIpth6gGiYqMZalYpgO0XZSy9orLVy/RZlsyLOczWqB2zwmL3Isu0maluSFShKM8Zt94mBMHCzwml2kYqEbbSy7Q5LmFGXCt7/zIXmaIEWC7bYRZYJpGiyXIdPLC7JMUJUZmlbht0Z0ugMqaZLEEc1ui6pKybMti3lARYfpeE2vJ5lNZxTpisO7D7DdJn7DpcxD3OY+XmvA7fu38BstPvnGAxRy5tMlVfXb/GBFUdBUFVV71yi/WaK9cQh/85hhaoz2BmSFRFHtt8FflcVvB9TrncP7lxAS037jn/Cbp4ny3p+vn6GAVNT33oNEVDmKAtvVlqIUWJbGG+tm0GoDk3/g+h0q3PVbMF9zllVVo4wmOG4fMPjokwdo1ZLL86ckYcBgd8jBrSP2j2+yWiZ8+OFtNN0ly1YEy1O+88//p2hayWJ6VSvSKTZluuXGvQc8eXyGYXURePWGNd1CNSUuHNptj1bT4MWTl8gy5+pyhaoV6KZDlNpYdpvx2UvK9IpHXzzh2Rd/S56s0LWSO3ePUXWN4U4Lpzmk04Si0FivQg5vfkAcxuTJGBVJb/8TKqljOW2ePg/QNJNke45qtlFQqfKIx1/8LaYhMS0djQqhqrQ6Q0Bn9+gmnpfjt2+gGy6aZrJZbCjLnE7H5/rynCJLCNZXrMZP0GRAsJ4xv3yBWo0x1AzHNWl1DugOd9lsXifBYIjf8pBIvEYPzWjQ6gxo9fcY7Q7ZOajV0G+c7JJlJd1WhmFppMECVXNqkkw2Y3z1iiq7RlVSVF3H0EKQML14wvjiJXGUUJXV28B/c+m68bZK0NSvh8ybJFI1g+16hahKDKs2SVEUpRYDexPSfw9sVFGgLMrfet67v+s/vr6zqLfa7zKkFmNWFZVWt4EiUxr9uxjG68Tk727m37/+ERvody+iIFHdT8hKH0U/5PD4Fmma0+24jPZ2aLUGFLkkjiJGB8cYlsnNG/uYiuDW/Q9JkxhN07DcFpfnU3IBiiqZXF1TFjGW32I9/QKlXNLotPn8V1+xXKwRwINvfIePPt7Bsm2ODtzadTTbMhjtoiolO/sjygp2j+5jOh6a0WKzLegNBkiRMpuGqJrCNqpwnIrFYkyRRq+nRgVO64DZ+AW6bqLIhL3DG1SVxLCHlMWaNMtQZECrNWCzlXjtW1TSoNHo4Pq92qzRaqCYh1yfvSSKUzptH8ezafd2KJKAwbBLHIfcuLVDt2tTCB+v4XF875sIQc09VkEzbKQQeI0a7BiuNiArtsspnY5X2+uWOf1hB9M00PUS31OwHYuGL2kPDjBNhVZbBbVE0yy85ojR3g3KsgQEWV7htXdRZEx3eIBpN0ijNcvZ9PVd8F3gvClR3i+RpITFfMPDn/+YxXiMFIJWu4fTbKPrtZff3xd6v/m4lGBaxrsH/o5JlPIbX6coKu91HSiKgm66r9+rUpsh/sYG+zdPo9+8fmeZVO9O3r1olpW1U2W4JMtgvVqxf3xEmgmSTDKfLji8dYRKTBxtScJLppMNqmbXMudai2CT0Ood1OpsFCTrV/i+R2d4QpUtsVo3MA24f9KAKkTVXQxDQzW69S9F7ZEkINHZ2dtB0yqytODxo3NEOUE1bAb7d4g2K9bbvOb62gJRFvi+T5m+wrZVojBE001ufvA9VFVnZ6eHordqf7FsTJpkbBcPyaIZZbYgzRSizRwhK6DC8Xy2y3O+/PkPKJIZokqRlQRVx7FidEtF1y2SYIyqVhhWj52DG6y2TSr6KKqCYbawG23cxg5eZ58kKtGNnMH+Ce2WRpGcousFUsQ4dsB28ZRgu8F2LIpkCwqU8YQkCUBzaQw+IEkrijRgua7QpKBIYyqpsl1cYNouhpFiaQXJdoVmetgWhNsNUtburW+Cpsjj34gFBSnLt0HquyrNdpNo/YrTZ79E0wVHx4e4rksN8Kx3VW+S6O3i7b3XfNNzfH3C9PV0eXszfv9kkfJtzqqKAvL980xB1eqFbV3RfT25/77rv2HPUH+TJEnQlRBdzQCDGx/8KZq2j2F1MNUcwz+k2x9hGB6q3LDaKJzcu49mSNA8CqHw4KMTFrNr8nhGXtm0d+7UQrzVGsdt0O37hEECRgdbi/FsE8s2sC1QtIxbH/8xnu+iaaAZTVA9JClPHn9Fu23Q8kp+/MMfYXo9tvNTVuMXPPnqlKafslqlaOYh/b6LECpW4xbbdUmSxEh0ynTJejkjDjaMp3O85j6lbDDY/xDbsWn0j+j2u6giZrOY0mg0MEwN2xJE60ukKOjt7KFbAwy7iyQnDnPs1iGaDllW0mrbmN5urS5ueVSlQDfb2JZE0yBcjzG0GNPyaPUO0A2TKlsh1S6j/WP+h//P/4NKKKwXU6LNBRg9vEaPz376M5Jwg+83Ma0Gg2Gf8elXtQDw9Rf09u9zfXGFohqohkORbylLBanY6LqBqIrXs/wak6Ybf5cC3bu6O1yfkUWX6IaKSs71k/8IQBwnrJdzpJTEwfpts/z2VPmNGJNCfq1B/l0xKd5v4HmvpHq3z+O3upLfQeyB/6bRqloLDzd22G4rLL9PHs8xSJCKQl6qNDstRn2Pz376C54/ecHf/Ncv6XZ9PN8jjXIQkp/86JeUVcmduzcZHHwLr92gPxry/OU5mu6zWU5RNQ9V1VjMVty6fx+plBRFBYpJHEuy7XPOnn2J4+9SpAF7Nz5mPp7wz//p99CNJpah0GpJjo67nL66YHyxRFMEm1XJjZNjkrjEdI5o9o8osg1lUaCpFqqqU4kK026T5ZJOyyRPBUJIFuOXWE4DWaZoVhfNbON5AkXV6LRdqkqlqjR0U4IQ6IZBHKVsZmdICtaL8WvTQZ12f0S728SybUxTQZElqpaTJSEKIUkUAAWbzYr5+JIsvACtjd/oEKwn/K//d/8HomDJztEJTqODYVpUouKDD++gWb3aeqvKybOSRn+Xdn+IqrfJwiWjoYWqNQmDCMfvMr96ihQlftNhOX7K5ctnbxEH70zEJUkcvBcLNR345ZOf02qWaMqWZsvCsm02yzHr2TXLyYRws2IzH3P+4hWb1YZwvSYMY9bzCUWRUZX1KSMVqMr87wz8r5VMb8v1dwH+phh7u654jZRFAfnaqbYuqd691u+dDHU2v+Y1KAo7ex08WxCuYtxGnyKPyIJnWJZGmkQ0+3v0hns0mx6Ht+5gmA5lco0UkiTY8OmDA7LoisHeEavpOZPTZ8SbKZ98OCKLrriewMsnz0B16Q2aGG6Tii7L2SWq0aW3cwDWEa3BXcZX12w30xrIVcHh7dsk4YQsWeMYFev5hn/1r76F4VrcOhmgqhVQICpJJQqSaM7s8gopQlbLNcFmTVE2MZwDmu19Gq1DHn72C/o7h1huA78z4vbHf4bX3iUOJggp0cwWhuVhujvYXh/N6JOFZ2hKQry5xnFUVL2N6+9R5GsanT6a5gI5lq1TlQGIBEXT0W0bzWyyf/MWRVZS5SWurRNGBUkcoaqS1uA+88kZzaZPJStsE9JogywDGs0uskp48egXRFFMlW8p4iXIhOHBnfr3lKYs5ht6oz0U6htYnmZkSUar00c35DtZ0d8obOR7I1EhKnZ2PPxWG3SDzeSX5JXB6Vc/Ilg+Jwmv+PKn30eUEVl0ydnzz1jNx8TbFdOrU148/AWXZ1fMr8+Igs3bm+3XEuFtmL977E1Z9eZd1RXSe73tbyz05HtHwt/XwP+jk+E331ASJDheiWoUJPE1WdWhpI9pD+s3UiUc3b6L56ncvXcX3bRQrF0uXr0CrcHo8BZe52OqbEm712V4cJfNZkua6URBRbu3z80PPiXKPITQWU6WiEIQbALS4IIXj56zmV8RLKf8+ic/ZJu4zCdnfPtP/oTp5St6o0PSosnoxic4fg/dNHGtEt20aPf2iaOC+XTK+GxGFIRoak4azXEbFqZt0e1bVEUKpKTxmv7uMX7rkN39I0zLBQVEnnL5/FfkuQqk2G6DPE9I04TF+ILtaomsCizHJUkU9m7cR4oEpdxSpUuicE2ZhRTxOZaZs1mdo+smRZpTCp1ws+Hi9IJKhBRFQaPVJVnXihiiiijTmCLbEq9eoWmQhldsF89IgjNU3eDOh/8Ex60N0v32gCSKWI4/w2u4CKNNpz9kPbsmDS9odg5rqHccEG6TeoQsqnp2+ebTlxLbeadgLaqS2cUTbEejxH39NQW218M2tji+x2Bo0em1QDVRFPlaALlWRLRdj20g2YyfUpQqp08f8+LhzwmD8B0e7k2z/hv9w5uE+LuHr++VS1KiqG8a5zqx//6W/h+VDPJ1ZtXHDYrC9Yufk8YZKBrtrkV34DGfjMnSBM0aEgYJVZFT5BFC1HPeaLvi4KiB7+ugaCiax2atkiUVcQztwS385g6mOyRJMuLNBteKyEq4uJ5h+l1avk60XbNzeBNNETiOwujgFuvFDKdxQBZHtPrH2LbJ7vEdWp0DqnzCaj6l2btNs/8hUqm5ssiUg5sDPLuiPbxNs3eLZmcf2/ZJ4zOe/vqva1ukhsfRyQlShKRpxtXLx2xXU86fP+TgzjcxHYc8XuK4JmWRoVC7B1VaGyEyhFCopEKZzzCNCN0SqLqGaRZUxRxVM9HNNrKsanPyqmB6/ghRxRzevkOzNaK3c4N4fYlu3UAIyezyFYalYbgjgsjl0WdfEQYBjVYTzekwubhA1RRMI0UiiMItrfaQNIzRDZMyy0mDMUW6IY5yUHVaHY9mt4+qWbQ6baYXz5FSvI5DiaLIt9KMeZqxXU3ZrFagNCgLB1V1aXb3Wc5ivM4ujttCN1to5i5Os4/jGLS6e6SFZHo9p8gVpCwIMnBsSaPpUaQbXj15QRIHyPca3jofvj7VfDMdepswv3liKO/BPt62Esrftwx/l1D/0Ow1SyMp37tDCFERbabMTv8rm82G23cPKNRbTC6uGe7uk0QBfntIVa4hn9XNtnePJJzR7nogMlZLFcPtMjl9SG/nAEVEzMZTdg6HSLUNVYaqWyBCZrMAz4PJ+Zz73/iYNFNItld4fhNNFSzntd+a1+qwXmwxdAOn1UWWEXkaEC7HoEg6u9+qUZRijWp00JUtUnrkeYSi+liujaoKwsUFebJEqg5+w6EoSmynw2wyxm00MXSdxfVXtAY3KLIN4XbN3tEJaB3WiylltsZ3Nbz+h5RZDppOlS/Ikw2uX5ukUy5Q9DYShXATY7s2ZVWhyRineUwSLEmSNc3WgM12Q6PZRArBcrLA8SSWd0BV5fjtXdbTFxSFgqaGKGKDYXexnA7rRYBpgWr4bBZjnjy94sFHDzCMDFEUzBdrhsMB52djDm9+gMgXtDpDNMujzNY4zX2ycIrl9fCabdI4YDG5wnYtgvkLbG+EqBQ855q86lHkCVm6pTm4S5WsUfQW6+WKzugmsszYzH6N6d4gTTYEocLtDz5guxqjmT7J+qp24kzHoNqsNiX3Pv4ORVHgeg6abvB+96u+hl38BoYUUZb17/e9u/+bJHi/4LIs+++tlX6Hot6b6e67nsFvj1hcdmtPhKpLtLkkS1esNkM8r02VvEDoQ2SV4LaGKIaDSDNW84pWy6LKE3QzYO9wB932SMOURu8At7VPkW1pd2+xnJ5iejucdA9qNKniI/CwrZzG/l3yPCbPCjSri+vvUQoFx9PJ0xki32LYHaoSpLzGaw4oshCqAKF4VFnKcHfE7PwllRT0dtpEYYLvm/jtXcrGHpqhkwQBihKhqjbd3TusJ4/xR0M0o4EqA1y/yXI6oypiijSn01bIYhXDPSYJZ5R5SSUybEti6CZpIoANrt8HTUdXNAxzjWm1sPUmcTClqkoUzaTV7lOUCc3OEdHqJW5zxNX1jOMjj6I4pzs6ocojVE3SbPaoCpN4k5EuJkQu9Adt0jQmDqZ0+wM+8ncgO8N3hmyylDsffo+z559z4+Qehu2APaSiQmQRokxIggXjs+d0d5Vak2h+iaKUKKWCVHtU+JT5JaXdx9Atku05jr9Dup0gsVhPX9BqtknCNVksCdMOXafEsm10x6bIc9r9Xc5enrMz2iVNNtjNPkKYmPGWv/7+f6HfU2l1OjQ6+whpYNo6fqMFhoHytlp5F+6Kqv2difAmjuUfXibxOgXfJER9bI3Hc4R1gy9++XMQWxSlh99ogKITBjlFEqPZXa5Ox2wXp1T5FsNq1XdEVcNydDSzNlIvKw3HbUK1rTm+cY5mNrG9Jrrpkhclg1GbZrvDfLZkvbimyFRkFaEbLkIKlHKBIkLSRGM6XrBZhizH5ziuSZIkaEQ4vkOclGhqThzMqcoATUm5fPGIIo0pKwXLaeC3GqhqDUF2/AaGJbBME9sxQbExbBe3OcIwPQ5u7OF3buI3ugi1ie1o2J6LKha0Bh1MPaXZGeA1B7jNPlIaCKUFVUZZqSD02utAKOhqyezynPViSyF0gvWCqiopypIknNNpaXQGRzRbLpVUSaIATdUp4ima7tHsnGD6IwwVitIgz00czyOKMpotn3Z/h+Uqotl2OPvqL2i4CutthGl5WI6HYTYxLRXLbSNFxt6tB8wm1yRxQppkaIaP3b5BFKkk20sMu00hGsTrc4TaBW0EoiJYPqfR6OI2hwSLUzbLOb1Bi1Z3jzyJ2C5XzM6/JFqPabddos0EUUxAqITbkNUywHUrmv1bRKEA1SSNN6znc7767CcsJsv3ln/K10qk365y3k+A3z1b/Z2m6F8bY71egXtOye7QxGsfIPIxx3c/pshKZuMV11MVIW3K0mDn+A5lCYrWRFVyZtMYzWojhU6RF0ilQXdUO+DE4QLPbaBrAkXTCLYbsiSnyGt1iNnVGTuHRzQ6+7iejeWNUGTK5cuH5HFMmmyRskRTcsL1OYbTpKo0uoPdWqJQ6WBbEseRKIqF3xiiaD5+c5dmu0mebQijmCzLSaMVUsQEQYnljZBSodE9RlQ5jtdG0RoYpoHb2CfPBPlrWqLp7KCQoOkWKrWCeLSNqISgiOeYlksaTlAUnVcvXtDoHSFExezqAqk6VLLEa1qkm0v8RreWoXearNcFu8fHVFW9iS5zFcO2MTSBbvoUyQLQyAuVOEkxDBvTaRAHU1rDIzRi4sQkTUHVe+ye/DH9g0+4efsuuiZrM/JUo8wDikJhNVmyXq4Y7u2RJDmDvVsUyQYpNKim6KZDVRQUmQD3NkW6ZXn1CKHYBIFEt0zKIqW7c5/B7g7xdktRlFR5jO+qNBqgaSVSCiyvia6aaHaLVrfFjTs36PXbZPGa7mBAmW9J4w3NdgfX8zh//hXT6xlREPEG8fruvq18LW7r2/jryZgUv+Nc+Ecs3X472xRU1aTIUspiQxwJyjzj/HSCFBLKDFmtSIM1iuoiSoNC2swnCzazMdE2wrBaxEEIMiJPSxRTJ422JGmBphtkSYKmKZRFSHewR5oLGu0+eZJhux6KYaNqNrloMdzbIU1D8hwcW8ewXieYLbG8JmkqWM4WaLqGZfugtZFI0jzDa/hoRs2nLeJzosUzVtNHqKpCEJQ0Wi3icIPtWWRJjKzWKGLFYvKUIi/I84SiiGqYNBVFEbGZXZIXTbIkItrMSaINVVWSJAkKEvc1l2AwGpLGGRcvn9HqDwhWM0b7xzS6XVqjO1Q4oOioer0hTuOMihZZXuJ6Bnm8we3eRpRbLLeJ6Zr0Rgc0O8fohoEulzh+l3B+geHuIUTF8Z17pGmO6/iE6wmarlKWCaqiUZYZWa5jOm2k5qLLGFXkmFpEWcTYjsf06hl5kbNezvHaA8LVOVW2obvzEbphsVkuOPnwT8mSlBKHPNug6TEoGoalUJQKipJi+0OyeEmrbREsZ+h2hypPSOMcKWKKLOYXP/khcZyiypgiq1UtDKNNq+Pzq5/8DbPxGCEEebrht2BD7/Eoqqpm7cl68fD7J8P7ScF738jvHrEcv+TGcRvFbJOEL+n1fTqDFo1Ok4sXzyAfs5lfoVDf2V3PpzPskwQrFuMx/YP7LKcXdPptkCZ26xaKbrFepzg2mIZTu8+nAbZtsJhd4Tg28eYSXa3QdY1+v0mRBvR29nC8Ls3eAKoNVZWg6rVmqyJSesMOWbJC01TWi9nr0sxGlmPK5AwhVfz2XSynjed1mI9fEYcBpmNi2B7h8hJDryiykEbvEMtuURQBZVGhKhXIEkSJeA0RcDyXJMlI4hi/vUOVXZNlJWkSkEQxqD6dbp/t4iGu55GFazrD2xR5yPTVLxBCYOigEpPFMxwnA8VhOZ1ge30W40fYXp94u8ZrHiExakHfbIbtGkTbOaWw0I2a4SbLDS+fviLaXCMpKSuFVn+PsshqqHOl4HomltcjTwK6ww667WPZHrqWsl1PUI0Gmmaye/wRquEzOfuCUmq8eHZOGNRG7HvHHyOKBMuCYDnGNhUsp43tdSizgCKPMXQdRERn50OS7TWNhsdsckVZhpT5CsMw8RpNdveP0XUVzRpydT5ncf0UTa1o93d48I1v0Gh3SZIMw2ryFtX6Gg1biXcYqjebbUWRvDXf+UOS4d3pUB88caIy3N9jfLWiv/8NyugJwx2b6YufcXE2x3AP0N09NuOvcJs9dMOi0Tugv3fM8b37GJZBGmdItctqPoVizeTiBY5r0vAq8jRGUSuEkGxmZwSbFYvZguePvkCqHVTdo9lpoZs2puOT5yaGCecvn9Ea3aDR6pMXDkU6we/0sUyL7ugAr+njNboYugClpCw08tLDbbSJ1q8o03Oc5j6D/QfcONmnykNEtsGwbCyvhe0MkAJs1wQJ4eaaNIoJlheoqoooBFIWXL34Wy7PrvGbfYpKILR9+qN9DEsDKanSK/J4TJJomG4T2zXJ4hnrxZRGe0BVhAA8fbbA7xxgmC0Wyw2Xl2sWkzPcxghJTlUmaIaHadqYToskilF1C8fvkIRrpGLheDaq6nLvw7voukGzXVNd480YTVVJwlXtbaEKllcv8RodNA28Zp/57Ay/c6vezutNNLXANFXOXp6D6tFs2uwfdNGNmM16Q1UVTMfnjM8nHNy6TykMNssZi+kFL55e0BuNaHddltc/Zz2foisBulHQGtzCNAy81ogiXSNFxu6ujqpJojBkvspYLmqi03/8f/6/URUFVS0p8pxoW2/G36FS5VsVvrpceuc+9buufwRQ7+vcIynhb37wQ7z2LTTdIQ6uWa4ShLCJt1MO9nsc3n6A7uyiWR2W4+cEqxmaUpAnIY1Oi95owHJ6iW1ZZHGC1Rwx2r/JcvKCKFxhGCVuo0Wz06GUNlfPfkm/63D3429hmiqqBk+/fIgiM4oSECsQKQ3fwXV9bNdjuHeEIiWVtHGaXRRUguUM07IQxQJN5mj2DdzmCAWJ1Tyhd/g9hJDYjolhKBRZSByuUGRBvD6lqDLyLCFPCtbzM4Sw0A0dr30Meofl7BLdsOiMbnDj9kc0ezsYholtVURRgsQCuaYoBCU+jXYXz3MAFdNu0+l2cZsHhGHFan7N4UGPNIqRWpcsuuaDjx/QG9aI1NVszHIZI6qIOFqjKgWyyIiCJZqm4TWGqKpNlqSgKBi6Sfha5VygIxQPTbcwLQ9FBd32GewfgqZiOk1EGXJxmRJuQiosyvSKYL1kMZlw8+QmYGC6ezS7Q0zbpDsYUpYVjaZPGMOLJy/IkghdLegNeuweHqGpOWVV0t75HpoaY3c+RogK2yoINktEJajya1AdfM+m4Vv4bsH+rodtVahWm3/6L/4chQLD0FGkJNgua7J/Vb2DYvBu//D1Gewf5NzztbR4+69/+7/637CZPWN6ccF6ek6jfcxm8Yr+4YdohoXf8FB1H8PxCSPJ8b1PcP1uDY+ugeDsHh2hGRDHGbrh4vstNK2JaUCRxUzPnrKZn9Fst7j7jX9Kq3/M2ctT/FaH7SpgcnVOEKR4zT6GM8JrH2A7Cut5bQiuqhLT6eM3bbJ4y2a5RlF0qrJECJ/x1StUTUO3NLJ4RlWkxFHC4uoFSTghDa/JohlJWhDHGWkS1B9msmI5v2R08CF+s8dqcUpWKKhEtEe36yUaGq5nEwYh4fKUOFwwvn6B5Xgo2oiitIg2FzQ7HTRNRdNV0mhSLySNJqYhqdI5y+USIRPKomR0fE/FFgAAdW1JREFUcJdwOUdKHfQ2hm7QH+3U32M9I89SBCqOZSPQSYsS027Q6u1QFgGVSHD8Pao8wXF0JAbbTUJRSqLNgjxLUZXaPGQ5uUYzW3z40X3SNME0dTSrw2DvFr29Y14+f4llW5i2ThxusewW8+mWIguoMFiu1iyuH2HaJroOzc4QVaa4DR9NSXG9HFSLKJSgNjBNj0bDptHycBrHiDLF731AlqwxvR4ffuubjPaP6PR8fM/Db/VQUFjMrqmqiu1qSbBZUxXZb4ft106EP2i0+g77pyjveoZur8dyA167wWwWEUY6fquHZWvYvg8iwnQ8BqM+mpKhIKikxG+1KNIAqhDXdVjPp/RHA65OLwm2Ea12E7txwHqxxWv1GOzd4uXzU67OF2wXpxzcOOa//I9/yWp2yceffkAcXJFnCk6ji+04oDhIUbFZzCmzAL85JNqu2SwWlEVYA9jyOZUo2L31PRABq8kllrtDHM4RxZI8WaCoBgKLaPUM2/H42Y9+wnypkKcleSlA81BUlzLfcP7inCrfsF2tUaRCsF6xXqwpigJdU2j1DjDsPi0XkAWWJbFsA01vE67PUBTB7OIJKDaqbjO7fEKRF+jeTUajIctlQBFfoCgmtt/GcBokwZjOzjG6EhEuxxh2j3QzQdVsLLdDVUpsW7BZXlMVUX37UR1MA1RdY7OYUWRLNF1DCInluGiqhlRssjQERSNcvMTxXHSl5jsEi+fkRcHi6pSTOzfwWgOS7QbDbhNvAu598jEvnz1FVAp//Kd/jOX10HUTp9HHdkwazQrL7aKZTWQl0FQNy5K1FM3mEQB5FoACfsPAtA0avR6ijJlfvsJ0GlRZgGpAvH7O+asX+A0Py4BXL16i6Rq8x3F4lwh1My1Rfud09R9B7qlnuFX1rvlYzq7Z2d3B0FSaDZMij9FNl6KQXJ1eoigmlAlJlDLcO6YsCwzDIFpPsdwWjt9nu3hJr+9QlgJZxuwe7SEVlSSK2T/5JvOzz1nNLhkOOnS7YHtNyjxHkRpRsGC9mmA7Lo7noiqgqBq6boBQyAtJJQzyLEaKEiF1imxNs38Ttzmg1Rli2i666SGlQRpP8Rs+y+kF3dENTl88R1cFzcFdZBVz8uBTHNdEs/fwWvu0Oj3Gly9xGk1u3z7CdrtIqbNcTLl89YhGw8XxW6BIppMxstzS7N5ElAVJtGZ2eY5llIhSBakj0XH9JlVe4jd9HL9Nd7iHqto0my1WiwDPs1kvzlF1h2C9QFQly8USRdNxXR3T7XJxuaz7F61CFjGd/g6KplOJgizLQXfJggtkmeA3BjU6ttqiajqabqObFtvVms6gj9MYoCjQ7OySRQuyAmSxxWu2aLWbhOsltmOhGyam46LpOif3HjDY3aPZHXH79gi/Uy888ywAVLJkjqK6BJsttlVgmSqa4dLsfoTu+LitI3RNwfFaqDIgjzbk8ZTd49s4zUN0w6OIr2kMbtEdjHBaAzTT4uTOrVp6RtfrmH2PKfemSlL/UAj3+5iQ99lOu/tHnL14itca4bkKO8OKYPGM3YMhy3E9nUmiNavJK0rFxvaa5FlBVtXrcgk4fh+v3SUKUyppM72eUaQbyqxGZza6HSQ6hye3UbSawRRs1xyfHNNs7zPY/4D5fEu4OqXMQ7KsIAgS/O4Otq0QR1uyLGV+vUBWCZvpKaal8sUvfsx2NSENF5TFlv7AJgvPKbMlUayiGwb9XpfFxuTqfIHMIxqeQbfjU2QrgvWSzfgZvudxfXFBJhpsZ5e4fgulCti9+Smq2UYKQVUWNNttvvziOXG4ANVmOd+yf/MBRWVhNW9g2h5JKijKDNU0cbwRttdhdvoLVMOmP9wHRWG7mrN7cJfHv/pbvOYQTVXRZIwUBeHynDiYcu/DBxTZltnlM5KqQRFfsVqG2HYPRWYE6wlRDFkhMB2vFnoQCs8ePSGNA3RVodEekMQZqgZxMEU3oSgyDm/dx3S6tHtDdE1g2jqG7aDIgmh7jaYLOsMjNss5qqpi+vv1rmY7p0iuURXBZrlF0Xdx2vdRVYU4XJElSxQlR2ZnKFLgNns4jRGCFlbjiCJboeg9FLFhswnQNQWkSaPTQxEVptvFa7TRDIMqr81JlN+I3zfX78qH32Fj9XX4a92PqEgUesMhqtHHsDuY7g6z8QuSJKA7GFBVEsdvcvPTP8d0HN6MtF5+9TnI2svXsLuUaUC2fYbjFCymK6aXVximIM9B0dukcYJhWkRBjfXfLqc0fYnb7OL6Pvc++RbL+ZyLl88JFpes51ckSU1QsWyfPE8wtYhwc47bOuDl46+4cXIHUUUEmzmqpgMqmr1HGKvs3biH2xrit4bsH+2zWks2mxm62WA+XvDy8Vc4Zkyj063LMKtE1Wz83h5C5BSlTX90iKFLRKVi2TZ5vKXbG2LZFuvJU1r9A/IsYbNNsUybotI5unWTNANFtZhcvkBTSyyvT5mHtad1IVB1H8ez8DyVPJyzDQLSLKI9uskmqNDNNnmyRDMHpJmKoRugWnVTWuXEwRLPdxju38Rr1uoVjmORFRWdXgtZRUhVxXpDylds/M4BVaWjyBiRb/F8lTi4RjUcmi0XWca4DQuJQpmFaGpJr9+sOc3JlKpw6I8OafZPWFz/mk7Hf4sfklWKbYNh2RhWD9OtRRyyeEUcXVOVCwxDpdm9TxaeQxUy2NvBbu6jENdlXTFnPX4FCCzL+bpI2HsTpTewvz8Qwv11vtAbFKOUgtU6ojdqohs6V6dPmF89xzBb+A2Ly1cv0M0Gpt1E5BtW0ym6ZbBdLyjyHE3XkFJQVRXZ9hW6ZnB484BWx6y/zjIpShVEyOXLZ3S74DZ6dEYHGKaN62lMx0tsy2V0eJfuzk1MW6O/MwIhOHv2mCKP0bQSxRpSVQq2KdA0i0ZvH8Puspxeoygalu0QBQs0pUTkC86fPmIxOeP65UOOb+3SHhxRFhGaVvDBp38E+oBW7xDTbaF7x5iWgue3MS0PVRFkcUApVMoyIotDqqpitDck3KS4rRs0O3Ug7uztEW5eoGo6aVKQhCGmYWN7Xaoixm12MCwDTa3o9U10NWa1mHJw+9volo9SRnRGt5FVxWDvJi+e/II0N2h2++zfOGazHBMFEbZVMLm4wG+PKJIYx/VASOJghqprNNsDFCSG6VGVFUWWYdsum/UWREmeBhhOD1QDw7RRlQDHb2MYBrrtU1URtuNgWC5C5BimA9UVQrZQSTFMg3gzY3Tzn6GZJqpWYOgVhruLZrqoqo5UDYRQgBKrcYLtHmJaLUQ2QTMNvFYPIRRUpUBBw7TbVMUW0/Hp7+2TxbWp5W+S5d4XFpCydqz9vZNBeV8O5D2IrESh3WkTreekaUlaehze/oTnv/4h8eSvyFOBqmogBZ1um1/8zX9BBYb7x1yfvQQpKYuSJFbZu/tthGKxmC6wvBHxdolhGjRaLbLcYLB7QG//Ae3BPv3BEMt2CdcbdEMnSWIoZqhSYDeHtHqHiKrg1v1PSMIQpcoI1wvcxi5O5y57N25QFgWKrHCtgmg9Y7WYoeguXrNZQ0SqmJ3j22TpBlXJMEyLxfgavzWgyCLKQmE1PyPcrl97JmjE4RrV8Onv3WN6+QSFkmi9ZLVc4zVGBNstTmsP02lSlhGIAtNxefF8TRqtUFSd3mDE5OzXlFnE+cvnmHYHTVUQEhqNAc3BCYvxmDxe0x7ukhUqumERra9J05LjO9+m0XDYLs6IgwTX0enu3EDXdMoiI4lDvPY+wWbKcvqKNKjZcGEQYegO2+2WqqxYLqYU+ZaGB2WZoqgmV6cvcFqHr9l7kjw6RTEaKDIhXV9gGhVKtabKA1BtwKHRtdH0GFXTydIEWW3raiC5wGkMMSwfRIoockQVozv7qOaAsqxQNQdFdaikSpWPMbwReWWgaQbZ9guyZAuKRp5XWE4Tx++8Dvr3tJV45w0hhahv6X9IA/2+EMCbhHjzTWUJcaJgEHE1nvPq6RmG3WH/43/H9OJzsjQHFKpKw7MUrs9qP+bd49tEYYRAIlWXNM4oyxS/YWI6XSzHYTm9wmt26IwOUTWz5gUIQFVRNQtFNWk0XZIo5Opigum4hOsQUSagFGiGgdfeRdU9uqNdnEYPVVNAVsTrM1AS5tsGuu0hsVjNN5TZEl0V+O0B49Nr/M4xfqNFmpZ4TQ3LtpnOI9aLKV99/gzDaqNUAcHmmtn4gtX4c6aXL9lulkgRI0Rti2XYNp7XwrRdrl4+pEhCFKNFmcfcuHMPUYGq5qTxFsM7ptUZ4LVvYtgWSSqQUsX0d6mKgmb/FmEsqYqMcH2FYZmUpUKj1eLq9DkqgjguQFHxGi22qzlVWdHqj0jTBFGVqLKg0ergtXp4nkur08BwXVyvLjMUKYjDnAofTbNptIe4rQ6yrMGM3Z172P4hIJGqim67FHmEorvodo+qSlnM5yByqjKnTK/x24coehtViTHMBoooUBQdVXdQNBVECiIGKgxDIMsJVTYDKTCtfaSo8H0LZIJu2mhafbO1LIeqSECpAXlSVpRvxquKeEf1VOpx/h9UJr2DyH4d71HXfDGLyTmK2abrlbS7Fn7TIE1ydnZtzp58SVHm2H6HWw8+4bOf/gxdhSQISOKMaLPFNCq26wApdTRNUKRrdNPmxdNTijxH13WSNCdNUxQUdF3j+vKSPAu5fPZLXjx6wjYCKYpaHjLP0cweSZwQrc6w/bqxyrKEzfyayflX6LqK5e5wfPMQlRLDNBkNbVAHlMUCKSMc32YzO0M1OqhKha7B5asv8PwO6/WSdVggygBNl3i+y2oRotsDbFtlMNxhvdxw+uzXlGlOkUVUhUShor93A9vr1x+66fLi0RfEUYyq+bjNNnm2RSgKzVaTxfUFEp0omLFdztA0ld5wwHI6QeRb2t0BZZ7SGR1RZiG90R5pBr3hDr5vIrBQdRvd9inziG7PZ3p5gW6YOF4HRW8QhCnb5YTxqye4fpfteo3X7NDqtHH9Bsv5hMU84Ojm3TroqgzTUDFsD00VqAgcfw+/vY+iNjAMkyw4QwgTobhoukeZS2aXM1TNQtWHSJlRZpcgC6RIEWWIajRQlBKqDCFLFM0iTUtUo8tmG6MqOkJqSNVB0QcYTgdkhqI7CEldcpcZoszeaT7JdyjrN/H7u5B6v6NMejdBevegUtPpNEnTqxhfXjHY2cfWNhQliGKL1+oTrM559fBzFMBtDeh1ffIiJthG/Ppv/jNZkhJvriikj4JGVcQEmyWW26nftChpthtkaYqu6GRpSLRdYJomO0fHFIXEd3O++UffItiGmE4D1fCxbRuNnO36kvk0oshikjDC9yS9nX1EFaGoKpYlUY0WZZEQbGM0Zc0yaHF99orx+WNWyylZfE2ZlxRJSppquJ5Hgck3vv0tJuMIqe/h+CN2j27R6o9oDY/o791iuHOLQm1TqRZuc0Sj0waZYhoShazmH0sJqs3u0S00s8l2G9FoNmqRtJcPabWb+A2fRnNIo9MnTUu2izENN8b02rR7e1h2i1/87DNEVbB7cAuv1SDLCgy7dhLdLKagwOR6jKI1Ge512S7PiKMY09KYj69BVvSGB5y9fIUiUhQKTLdBJSSe3+RvfvB9qgpMd4BuOK9FC3Q0VYPXChplVYJMqEQOio5htQkXZ1TlEsv1aXZrCfsyegpaE2l0KcotSA3D3UdVShSZgaJgWj1Uo43b2sWwexRF9BqpO4UqAhkhq5Q8qU8OVdMRQiKEQNGcWljgNTm6Zh+8WwnI31En/cMnA+L1i35doUBKyfT6ktagT3c0oghfMJ4ldHrHuK0bfPX5E47ufkgaLQi3IY1Wn8PbD5DpFKoxtz/6FllR8vSzH4EosFyL6fU1q/mMNNrg+waL65coqkKn22IxW/Ozv/o+Qkh2D/exHBvXt2n1jymyNZqaQ1WQbCY8+eJXJMEZzfYuUpbkuVLjYa5eoCsVltcn2VyiKgXLyTU//MsfM59MqITJYNjDsGq72Fa7RZXH2I5Os3+To9u3KfMIqpQsuGa0v0+Vz/ni5z/j4sVPqfKY7WqJaraJ05j7907I4zWqotYftmJgOgOKAjTdZLMa8/EffQtRSa4vXtHvdZBYaJqG0+qwWlzWAwihE28DvJaH6dgM9m+xWW3QrXrB+EfffkCzN6LME3TdwvJanD1/gUSwf/MO12cX7B3eIg5i0ixjOstRlaSW1R92UTSbOFxiWxphuCFanrKczZGVQJFw94MPSaN6uxxnKnm6Jg7mqIaLoptEqxm6kqFgUqQRQuRoSlXb1RZX6GYTQ4vJg6eg+ygiZXb6FaoiULQOFAvKPEQ324gqhSpFlim6YaMoku7wJsgMwz7AtJpomkmRrLGcHqKK0TS9FlR4vQ/TdONrPOp3u4b/f5B73ghASflWEAoJndFNqhwoU7x2D12tiOKM9WrJ/q0TltNTOl2f+fiS7WaN5zucv3iFFC6aphAsXnDy0bdxvAa2XRHEBd2ux2L8ktFuj+ViThZtMUyDLM/48Bvfpt0bUhQly/EZlmVQFhmWZdIdHqIqAr/V5/B4hOUPaPX79Poanm9SpS9JChXV6qFSYvkDpMgxTYVvffc7OH6PKAq5ePoTNE2j3W6BTJhdnRGGOavZS1BU4ijg1u0jmt0uiippdA7Q7AYn9z5lsxzjWKDIECkkAo1mu8v8+gVhXGK7HoahvTYvLDEdh2arzWp6RlboxEmFaeSkaY371+wReZqSlwnd4Yjt/IxgE6AaDdxGFyFKiiwiSwOKvEKgcHF2jud7tHtdNM1EkRnScHj4xVNa3TabxZr9mx/w4nTL1YuHeF6DOIy4vJyxnp8h8wi/exNESZasUVXQdYU8z4iCAEWm+N1jNE2nKmIoSqzGLmkSkWUrDNN6bRslUFUF3dlHM9vYjodm76GoKnmWQZVT5gWKIhCKgxAOEgXDGlLka4QoEEVEmW2gCqikQNN9ovUpKBp2cw8pUhSgzFa1DkUZAbUbqvpeI/1GCiDZnv4upZj/VtTqu9Ph7GzKJijI8gJV9XjwQQ/PsymyFa1WE8vW0KwR7Z5OuB7z/OFX3PvmdxCKgQQOb+ygO3s0/JQsXnHvw0/Jc0GRlyxmW3QD1osFVVWxe9AhjiPiOHuNRCxYL5fMx9e4jQFVKdEsl5ePv8T221yeXZPnGkWeo2oqhWjT2fmA2dWzWrCggjwHUS7pNgqOjtus12uyQsNx+0jNYLBzXFsquR7xdgqKg2VAlWcUSYYCaJrPN7/5AKk2EZUgLyUoLv1BC8sysFyP9WqFbWkIoVAWBablEa6uQRiURUlnsMP+yGBy/pLHn31Wl4thSafTIopjGs0mRaWhUrF7fBNVUbBMg6rIENLAdh1URVIKQbLdogJeo0VVJFSVia47DHf7nL18itts4zgG+zseR3e+QbhZoio5N05u0en1SOtlB5pWsJxPEBI8RyKlhuv3MUwTUVVYTgsUhSzNUVSJ1biJivbaqLzEbe6g6gZS2yNPZpTFFoUKIXQMLWb31gdIrYekYrkI0I0cRdFqb4ZKYFhdVL2FFEndABdbVA2StEKzOkihoFsdNMMHKdF0D1X3atkYUQP23gmK1Uhr3XDenhi/dzL81hbv9cz29q0hzQbouglSZTKRvHjya4ospdUboKo2P/vRD1BFhqZJDm8O6Yz28dwMQ92iKmDaoKg2soygDBACbFviNdp0+nuE2w1xtKWMFuS5ZD1fc/r4M8BGNRp88M1vE4cBsgy5fP4lBzdPyOOEbrdJGk0o85AvfvkLFMXCdVWi5QWGqSPKjMkkxW8dklUuSVEh8ojlckUSztFMg7NXl8SxYHJ5gdk8IVrPQfWI4gqBTp4JonBOlq7wfZNGe5dOrwdlSFFqxOGcqixodTwkOqqhk6YJSbTA9gaUQiJEyXRyjWE52LbOR9/9F4yvTun1WxRpiqEraIZDsHiF19rh0cMv0XQTUYYIqWNYGvNFWm/0HQvTEIiqINpOqUpBGi85PBiwO+yiGU082yZYTfHbu6iqIErrsaOuFKRpxf6tj0iiDZrZpMwy4mCFVBr8xX/+PigSKVQ0TUUqCkkww/ZcNFVBVgGm20CICqt5G1EJ0rTGQ2m6haq3EdkY3WgilQ5SaphGPfzs9X1UBGW6RqFCNRSqfFsbQigVoohRFIcyT2i0jxFlRo1iqKEXb1BCpuWRxJvfmoC+Ww1AGv0B1rfvaqx3ID0pJZWokEKlSNZEScl4tuGv/+rnRNsNitFmef0Q13Pp9kYspzMsq5Z5kVJDN1u1ynYyozPoURYCNBMhEtqDLogE2y4pi6I+qhWF6WxGd9BEZFdMJ1NW80uObt5GSAu32SaJMlrdIWm8RjdMvNYuWaZRpBmff/GYKIzZLs/YJiaXF3PC9RhXv0aKBMex2SwiDk/+iJ29QxrdA1xLJQorRjs+aRLSbHUphYmuVwz6Nge3PsW0albYNnZIkhKvNSDPBJUoMC2fVvcAVbfxO0cUyRbPqw3PvfY+//f/639A5BFhsKDZ8lAUB6/ZYHz+GL+9y2DnAEU1KNMZwWZJo9PDsJscHQxZzNdkWc3lLouSdrdJHCdIUdIbOKyWcwQ2lq3g+j6GZaCogl6vJiS1B0esFxuCMKPd8hnu3+L0xTlpmpEma8oypipTHLvk0RdP6A2H/Ot/8z9H1xU24y+oCkG0ucZpHr5O+hnIEikEotiiqhqyPKfhaSiEiALKokKzhgiZIUSKVDWkiECCrlmgOmhmD5GvUFUHqdkgMhQMdE1FMdpU+RZFzGvKab4AUZAnW4LVEilTyqpCVaAqS94shoV4rdgnwXR7mE7r90+G6u3G7uv0T103ME2Jah3Qajex9JJmp83d+wPyZE4YgaqbKFqF29rh7OmXzMaXTM6+IFjPyHIVw90nXM1oDg7RdRMpBXla4LRvU6GBLMhLlbKsuLiYkqwekeUlh7ce0OnVNX+z5SMFJMkWRa0oixLbcyiyEAUNp3nMv/13/5YwXKFIQa/ncvrqvCbrOA3G5y/JoktGOz1EEbC3P2A1u6S3c4Obd484e/aQ/nAfXVfJ4jW27eE0dtCNeoJh2w47Q4/uaAcpS9r9PWzXRTM0RFknmt/wcVttgs2cqioR+YZ/+2/+jN7uEd3+PpOzUypZIoTFehXjOQp5FrMNIkynhyhSqgqizRK30ScNJ1hOkygsiOMU03BIo4A8LWj0T2opSaUi3o5fcx62pIWJYdpsNwFFFuI3NDzPIY2XpGnK8e2b9EZ7oMDV2ZSySHj4eM5ot8nLz/8LaVoQr8d43SPSNGV6dVZzt1/9BEVrIKVGGk3QNJ0sfIVumahKUo9Wyw2VUCnTNapY1eVSelVjt4oZaTJGlgFoCqKKqWeYGSKf1QBMzSRYTtHsNqqqUhUBotpQJFN0w8JymoiyQBQJpt2qSyEJICiSab18kxIpFDTd+f2T4e9qON7UYGmW8eXnX/Do819zebXg+MYNFEws02M1u6YSKTdv36TIcw5v32J4eAvb64Bq0mz5FFnAdjmniNfYXo8qj7i+mHD6/AkqsF3PaLbaXD5/xO07R9hWE9vzmV88QdUtyrI2v9us5qAIqlLS2blJFKyRUsdt+BTxC8Yvf8zuXo0g3T24yfGuxWqxxPZ3qNQR46sN4fqSoszJMsjThM30DCFUVLP5/2vvT38sS9L0TuxndvZz982v7x57RmZWVlXW0s1u9jIkZzQkSAwFjSBAXwT9Z4I+CaIAQpAIDIbDafZa3dVdW2blFhmbh6/3+t3vuWc/ZqYPJ2rpqu5ms0qfpLIP4XCP8AhEhL3nmL3v8/weKiWpsg23Fy+J0x2r5RKtc3rDA87PL5C2hyU9XL/Jdh0h7Baz2wssL2S1WlNkJUJ6LBcL4s2C7WJGGIYs7+6oipL9k2M8r0FvNCIvNd3RGapS9EdDGq0BzXaH2e0Nq/mUPC1otPps5+e0+yOUsZCOx8HxCUGrh9YO29WG2WRGZ+8R7cE+ltFcXFxhKAlaY+5uXtVEu8UCg0caXWM5FqbKCcMeNjuazR7//F/+SwyG/YffpNlqsFxssN2AKl/R7u2xnb1h7/432EUpjtvDawxBSLTxSHYR2pToKkZVJY5dYjfOyNefIL020h0jrYAkVkirTRY9R8gQ6exjUBTZlqrKkN6IqthgeQEYjXC7GBMgZKt+WxibwE2RdkBZrmu5kJRoo0ErpF0TEFWV1XeJXyef4W3j6KdF8LOhmyAvHI5PjxBG4/suN7OIaLvk7vYN+8dn7HYZyeaSJJpjyjvy7YRoPUcKDSbG9TsY4ZMlW6LVNbbjMru55uzBE4JGl7DZIWiGaJXgWBVxknL5/HOavRG2F/Li82cYA8l2Sm90itYF8XrKxYsfs5l8gUqviTYFp4+eEEWGXZSwupsQ9h7Sbikqpdk76BA0BljeHq12i6DRoSoyLt+8Zjm94f7jJ2iV8qd/9Md8+7/5V1hCs13dEcUljufx8PFDLKfFan5NtlvT7HZIou3bOUlJp9sjjSek0RpTZtzdXuE0R2jjsdvcMbl4RZntqPIIKQVnp32KbAWiZgCluzVxqlHaI2i2ybMtebLD8ptUVUXoO7iOi1YFtxfn+IFLUVTc3s6JtxvyOCJLlrz73mOk1WJ8dMTZk2+yns+4mWwJWwMwDt/7s/+VyWT9U43PZhVx8+Y1fmPI8u4Wy7ZoNFtsNxGqUnieBWSoStdFpTOMLijLAssOCNqPMFh1q9N18TuPqBTYjffB2Fh2QJW+odEKsZ0Wjn+v3sBYSOkiTY7TuA9C4jYfYHFLvn2BKnZIqRAoHK8BlAg7oCo32E6IMQlKFbUGSdpIq1EzlXRBmSd/99P9H1sMQojaTsfP/KV1KUC3mZKsXzA86PPoySHDXkBRNTg+rb3OtsixrKr2HLseh2enHN1/TFXEOF6TmzdXbLcRru/h2DmzyZLx8QllUVEUMUEQIE3B/ukpqIIsntHqHXD26DHNdo/jh4/J0gTH7+L6Psg+TtCj28zJiwjP97n3/m/RbA+IdxGdbgvHMfi+jROc4jgBUm3Y2++htSbZxUDG8f0TGs0hrY5Pkij2j++zN+py9foVzc6I8eFjLCEoypxke4cRCmNqA1OZ13CzMAyQsu4+Ndp7hK0e11fnnD35oE4/qlKE3lGpDZ29BzR7Y5Z35xSlfvv0KrFtiyRVdLodTh49ot0JqEpF2B2D8KjK2iGY5ym2E2DKDCEFabzm4eN7hM0OrcEYx2uSbFc0WyFJtEZVKdPJlIN9D8cDv9Hh/a895c/+5DvEmWZ8dEhVrHG8Fp5riLcpi+k1luuhTABWTTvM04iL5695+O47LO4ucfwDhGUhbR/H1gRBEyEE0SoClaKzLzFqTZlM0G+lEapcU1URxpbofFmbDozC9g+YX36MEFY9uTYa2x8i7S5COigj0FWOZVlU2sIokNKro3BNxac/+nHtaKw2aK0QUmE5zt9BevmvKAb4GV2gRm787Ovnbxa0+qccHj8k2tkgA25vNlhOl3h5Rbye1UZ1zyLdLplcvcAL9+mPD4iXF7R6ezx654xPfvgp2a7OWjs4OWM+fUYaZSSJIk1TpDBvJQQDPN+gqzq3y3EEy/kEzylZTG+xHQupFrQG7+EETZRpMrv8gjRZc3A4xPGHfPSjl1zfTsjSBFNFSEviOg69YR/PEzS7hzR692l1Airt0Wx3cPwO7377nxO0enjNEf39Y7rDPrYFbtAhT3dvlaYbLGnR7nZxG11UFSPcNnGUYNsWWtvk8QbHyrEt6y1R/Anr1RatKoLWmItnP2K3SdDGoywKwkYTVeZU2aruxeuKIisQumQ1myOlJs8qtvM3DA+PsWybsNlhu1rghyHR8o4gDNBVzmY5ZX57wS7a8N5Xf4vRwUMCzyda3eA2xvzTP/g98nTFZrXk7va2Hv61xgwOxkidUuVr8nRFtrvF8ffo77/LyaMzjAEvbKOqDSp+Tbr6BIRLlqWo7ILeqEeZzUliie0fYzs2VHOQAVhtdPYKKRogWxijKJVLmW/o9Ic/fZA74RGWANTureq5SVWs0fklIBEmwXICdJVhOwFP3nsHowukZVOpEmVcMNWvp036+W+23mrFDaCNodE9oTc8Q0ifIk958PCId95/QrSZcX5+Q6G7vHo5I4/f4LUOGY3avPr8byiSO9brCkFGtNny3tfeI0229Ec9bLnl6N77+IFDf++Ixd0EKW2kO8Bvn+G5DlrX+pMi3VFkOabasl1c1/3m4AjbgypX5NkcxxZ49q4eHjkuju0wHg3YLi5ROmAXK3bbJbO7BMfvo8oV8WZHo3PM4f33ai9uu8nx6T0ePX0Hx3GxJKgi5uL1FdpIHLuJJRWW41EVCVWZUxUpwmpSZimO45GlEd/8nd9js06JtiXaaNK0QuiC9WJKVZW8fv4J+4cjhFVgWaLOp1guWc5mpMmWv/7L7+CFHaYXrwibTYp8Bwji9SXSaxPvtsTbJY1GyGD/gOn1JZdvLrCckMnNNdJyiTYJvg2vvviE9XJBtFnR6Ixx3BatlsvBwRC/NWR8dIhlSWwJzbCD5QVoMaDRaNMbnRBtZhhT67qq4g7bbqIUCLuB37yPMGntL3DHZMkWg0Nn9KQekOkUYTKk5aDyFcpIdLVCqBVGFbiei3SaOOHbaFtBnYgkXeKdxnbreYJle2hCdDGphX3lFssZoFWEZdUdJWk3kRKMriiTKcb8GnOGvzPU+u3Xj0/3SaKIeHPDX37nExqdM/zWgP7ogP3jezz79CMOjh9wfbUlTT2Wt6/o9DvE61vyZFkn1QuB64eMjr5Op9fHcjyWk1cIu4FOz7n/+DHbxTWqXDC/fYEfOBTJmsuXX1DkO3r9FtJuMr73FdrdJkW6ZPLmnGanj+cFTK8uWa7aSOmSJxHttiH0FUnh4jeaRDuJGwzpjwZoVWJZFrsoZrPN3woCa+dUkabcXl1TFSmzyQ2r+YTBaEgYhtiujRABWW6Y3t5gdImQFmkSEzRaLGfnlHmGVimdjstisaQoodkUbBbXDHr1EO76Zkurf8zk5g6tKlSlODoa1Rl4js3xUR8/dGh2B5TKYe/gkHh9g+M1KEtDVWryJCNPUxqNFrv1HU8/+JC7yR3HD9/DdXy6vfrSWaa3bDdros2iTg2yNPHyNV6jlsiPT95hu1mgdUqWTOkO92n3mhiVYBD0hqdoI5CssPQa15NIabCdNsJ2MDgoXbGafA6qRLDBEhHSthDkGFr1nMQfYdldtMrr7Ih0h9E5Vf723oXBGIGqYky1xXVTtE6pKkWZzRF4WE4b4T+kKrZoo1EaVPoGy65RQQirZltZHlr9ciDKP7oYfr4gfukVIwOizZS/+avv8W//x/+O69cXWNUdaXRDvNnwe//i3/Cf/+hPKCuJkArp91gvd3QGI/xmiG0ZtEnBGJbTS4o8I1qt6fQ6FNuPMSJAChslQpQWjA/20CrHYoMqK0yVoLTD/O4OiSbe3oHw6O3dw/I6PP/iNaOjEwYHe0gp8Jt7DMZnJLHi6fvvUmUrHjy6h2VXWLLCDxpk0YR222G41+bhkyck8YqrV5+TJBndXgulNFW6xbIsmk2XMs9xPI+yKPEDH6RHpQTJdk1vOGI+mzEYP0BKi2SXE29u6fVCPM/Gdjs44ZA00ziuz9c/fI/NWtMfHeF7IYvZjN36jlZvRFkoxvtH2LZP2G5h2S7xdk1aGBaTF9iOQ6cXst7kaA1CCrp7D1jf3SCloCoVd5MLhgcHJMmOwdEjWu0mll0XR7rbcPbk62xWC5SyWc4mdJs22eYNlhMyv/gh15dXeGEf1x8gLQvHsXAb95BOA1Neo7PnaGFjdK1n07qiu/8OrltSZDuyeAZ2DyNHaFWhtUapCsvtg4EyW6JURJHNa+GdKTFGke52IJv1pnYChLQRJHj+gCJbUZUxqtohTYmgQkobt/EArQsMIVV8gVYZTjAg301/9WKo0TMCKcXfKgohBL5j8ezZM37r936faP45/WGPjz69w3b7CJHz5ac/5p3HRzx8sgcawt4HOC6kSYnttYmWr8mykunNnOHhQyy3x2wpKYuKPFO8efUFZaFod/awLQe/0cQOxrh+F0sUOG4Dz44ZHr5DvF2y3SxxRISuNJbT4sGjMZ4f8Orzv0SXGeef/zWNpsfg4AGvv/gBCENVzMjTDdIkZGmMHR5he21cmZNGdwz2hqTRlptXP+Ly8pzN/A630cV1HCzLRdoOs+vXLKYvmM8ifFditCZs9cizHYvpa4pkRtDssFmu8MMOBpvJ+UcIDJvZOZalyVL48rOXDMdDut2AeHvLZhshbZ80jpG2Ww+QlMazDNqA7QYk0Ry/MUCrgizN2dsf4TgV8+kN04svafb3mF1fYlu1B8UNOghhMT4+JU82NJohjVYT6bXxwyaW1HR7Izazc4Rt43XfpdXbQ+mQk9N9pCVJthO0sVDVljK9RgsfSYoqE4xsIKTBqB3CqknoMnyI4zWoipxofgVqhxICy7JqJP1mQlXZ2F4f19UUyZw0npAla6p8Uacj2R6VaSLtBtIYbHeExkaQ4QQHWG4f4eyhshuEcCni5whyoAKrjbQcLMvH8cJf783wsxirt3eIt8Xg+C1avRMwNoP9x9ie5OhggEEzPLiPZMfx0YA8F/jNJtHyAsdrkKQSzylYLDO8cJ/esE2yfoljCx49OUYISak6nD75XeI4wbLAdhyqSmJwEF4LZIgq52B5FMkd2gha7QHC7vI//6c/Jd2tcT2HMluTFG2ybEe351OVkMfXNLqnNFpdEM0aNLzbYFklnmvx+sXn9dPH8imShNHBIW7gMLm6JWh2ePXlc8ocpONTZhGe79LsnWKKNa3eiKoquLy4QFUVZw8e0+js11NZndPZO8OYnN7eGdpUtLqHeJ5Hsr3i8eMjJDWdu6pKjo+GzGYrVss1SZxyO90gLKi0YrOcsrj9hNCHwd4Z6IKby0uEUGil6XYCTh8+okgT3v/mt9lu54z2D6nKhGarQ55rLNuhtzdks5rx0d/8BVmaYrstNps7+sMuQWuIJQ1FFmH7DeY3z3EciVaCdDdBa4Xt9TG6BGEjAWlyQCGkW1tWbZ8sWiBkC8ttELS6CFFgOQ2SaE6ZF8TRHcbYGFWh8RFWi2azga5SVLbAdQqESSjTGUYlVFVMkW3Q1QLX75Csz7FMikGgVYGqdhS5j5Dttw9um6qojV+WP/x1isH83I9vv+FtMXQG++yPBMYUlNn2rdE74zt/9QmmSmm1bJS2KPKKKnmOqeasJy+pyhlpsmNw8BDHdoiXX2K5IVW+oUpvQVgEzRZGJ1T5HKSDcDqYKkFSoUro741Jdzl5tsPIJjYV8WqC0grHDcjSBdPrGX77jLMjhcFGU08zlbHp9muNUZFc02j2MM6AaJvVfuX9Y6oyAl3iNA5B2rR7Iz742lcwJuXxkyMsR2K0YnL9CjcckO+WFHlGWRnOn/2Ys3tH6DJlevkapWF+e8nxg6f4foP9kwd1ftrgkCAMKLMFg6N77FavSZIl88kEhIe0BPvjAYeHbfzA59E771CWBUI6vHnxJUFzgBuMSeM168WK03tHCCkplWQ6WWGQFMWWmzdfMj68D8DrLz/HbzQp8pjXX77AaEVVGt57/ylVEbNdr0miLVp0wQh2y9dMrs5rV1yzS1kWNHtDHK9J2DrFaI3j76GruB66qQ3F7g1VcotKZ0jbxvVcisJGKYUgRdgDtFIIabNbv8FvHlGWFUH7AKMyvOYRltMkbJ0gpIUuM4qiwPGHtSBPeFTZoj5GuwO8RpeqjDHFBDu4D8LCaexhdImqUopkhtZ1YpTR6tcphr+jPH4i6cbQ6/bwg6BG02uL4WiP9z54j10U4fs+ija+G+P4I7LcI2ju0eo+olJt+v0+t28+oSws0rKFMSnrxZbp5SssaSOlxrIUVb5hOZ1QlAqjYqJVRLSa0WjvoYqYzWqJMYrhyXvE2yX7wzZ5prm4nJEla4R7H4uUPBcUhUW0nLKa3lHkBdE2J40zjClpttpgclqdJmkSk+5WxJsFtxfnhGEbxw0pK4FSGV5zgBSSZqvHZz/8Ad3hAd3RPmWRcHDygKpIQUianSF/8Sd/gtKaLNmw265QeUmz5RCvp6yXd1xcLJnfTjl6/C2CsInjKIpkiipzhCUQlk/QCCmzmNnNFUWy4MHjh4Rhh/bwBK0KeqODGp2vS6YXn3I9XTG7eUFvdMS9J+8T73YUZYG0HOJoi+cIjk9PiFYzlFK0B2c0O3sUeYTvWcRRwm4bUVY2/f0zrr78S2zPJ2j0MFojpf3W+CVQ1RasFgYbOzzF2Kco6ljdfPM5nt/ED5r4QQMtmmiVUGy/QBcpzW4Py7ZxXAdjdjUhBEAY0DlFnhNtduTJ9q2EQ1HGFwhTM2VBgdEY42KEBSZBawdLZAghyHZzEDZJHNddUPVrF8Mv92aFENi2TRxtiNYrPv7eR1hWQFVsuHfSZ7Pa8fL1BqlnhJ0HXJ9fMjx+j+5gQLS8Ye9gj+nla6SE6WROsjwnjkuybEfv+D22myl5WtLfe5egtc/o6BQvGFGVNenODQZoXZJlEttM0KYijiLavUOOj3qc3jvmybsPsB2PZlNSKUjjHXk6Y3DwmLu7CNcuWG9SXL+BZTdqTYsIEFIym07ICklZLOj2+6SZId3NUPkObULi7YzddkV3sM/ewQF5FpMlG2zbwmC4u7mswVyW5vE7T5GWi+s7KJWTxTtKZVNkU4yu6PV7dHp9snjHbldg+3s0umdsNhkf/+AjMAVFFpFnMYdnDzl/fUPYbHJ9E5NnCW5zD9uW7Oav0QrCVp9vfP19eoMxs9tbkDZVfMH/8h/+X3QaiqDZBW3jhzab1ZzxwR5psiHabtk7OCZJIgZ7A/J0VReYKonzBpYTku4WFOkdQkiS6LyWXZsK2/Mp02ukbBI2mjheCz8c4Hee1IPbao3Smt1qDlaXSnXwwg6W1cFr9NmuariYwcYAqsyw3RaWY2HbWxr9RyS7hCqfYbkd3HCEAMo8o0xnCFEgAa00VTYn2dVkPstKUUVEu9ejzJL/Ytb0P6IYav/C33K7UYtoFR6vX71ivN/G9TTLuzt22w39QY9Gs0NZ5mw3OctNwRcffwfLdlmucjA7mt09mt0h48OD2vBfRATtE7aTH2NUijAF0pbsNtcUyQbLlriNFo1WqzZ/SwtbVmyTPlnhsri9Yrue0+v55Mkd/eEejheQRTOSKGJ0OCJa3rBeRjx6Z5/FfEmr3eHq5aek2znr2R0351+yW80Y7Z2x3mRYVhPL9plev8YYhbAkQro02z1cP8RybILAJWy1CMIuy/kdncGIvaPHzK4vmU5XtdFeOhSZwrEdbM/FsSVZruj09+gODmn1xhhTcHM9w3MMVbFjOAx4+v5XMMrgBl1W82vSeEGv36cq4ez+CNcCle/Yrpc1I6mM6Q7HXF+f0+nv0Wy3iHdLgkab//5/+Ld4QZM4SvAbAe3BKX6jR55u0dUO27KJt1MajQBjFI3OPq9efIbJNxwdesxurgC4Pn9JnkZYjl0/naUHqsIJ9jC6IN1e1YI4IQAbbQRaa6Q1wHGboHYEvUcobZNuJpTJnDCwiTdvsF2fKlsCLkV0jtbguiAoaA9PKIs1drBfC0i1AZNRlBZC2ORphEpekm9f47j1XUGVKY7nk24mYLl/m6v0qxTDT0Xcv2TwEYxGAZbdYr42SHx+9OMJ08kEY3LCUNAdnOJYEUZrHjx6TGd4yPvf/KcsZwuKZE283RJvZrTaLpbdYjl5TtDo0usPwFRUlcG2XJTWqCqh2N2RJXOqMkIrTdg54sHT99gsZ+wft+gOuiAKqqrk1RefcfHsb8AkjI9OkLgMxnuU6ZSysGj3D+j2ejhuHWTR6u/R6Q1ZzCNcH86OO6TxBqRDsotJNhOibUmy21Eka/I0o0i3+IFPmqQgfZrtPVarDbbrokSDwahHtz+g2e3ghy2EFaBVxfT6DY1mF9trcH09IY6WIEOkZUjTjLDdRsuwHhLZAdHyjt5whDAVSlv8+3///8RrDJACbNvmy8+/xA0DVqsdm22KZ3toJEZDtJiSV5K7qxd4rQMskaHfusLa7Rau3+HudsbtzSWqUlTKA+ESNFoMRyMWiw1O0KXbH2K5Tbod2GzWVHlGuvkClTwnz+7Q+R1ap/jtU1R2gVY148jgsF3O2C1fETYskE0khuX0nDxe47g+lt/HGIMlMhzPRTh9jGWTxjuqIiFa3qGrBY7bRqPRZUy0vqaI59h2SJ6sa1efkCBrn4PWJdi9eoDnegjUz7H2fpViEL9MIftZexWincfhwYBu2yNJIv7wv/3njPY6zOcpT7/xT1FC873v/pjt/BbHDZndXLKefIGx9pFOAzfo1llnImR2tyRstqmyGVlWkG2eUVUJtmVY3z4jzyuk1yQIe6ArgmanlgMXM4ajfcrCocgKlkuDMobe8Jh2r4fjtvj4r7/DfHpHnqf094b12Xl9yWKxpL93RKvbJS8rmv1D7j1+F0SH6zdvWMc2y+lrAKJYkUVT0t0SYQUU+Y7dZoPtOPh+nZ9miYIyjXnx5Usc20IXW1SZEG9mrOYTvveXf47WFWGzQ1WU2LbDYDSgylcs53N6vR6uK1DK5vb8Bcu7N8TrS2yvB9rG9kY0As2/+Tf/muV8ibAcvCDgq9/8KvFmUfOBtKYzGDC5vCLe7chzRat3iMFlOXmO6zkY6bNdXGIsF8u26fbGWJbC8UKiuCAMQ3a7LYdnT6iKHGm3MNKDqkK6xwSug1YeuthheQdIbKS3T634r7Es0vKoqilaaZqjx3T376NFo0a5SGj19wjaLaqqwmt0cVyf9d0Vqohw3YCq0ARhm91mixu2al2SZaGLGCEKXBfc1hg76GAosBtHVEVO0L2PUQXx8hzkCDBYwQGmrL0av3ox1AkQf2+l5NFrRgc9lCrYLs/J0zWzyRZhw82LH5FsIn73X/xLvPaIN1/+gCyNCLp7NFoh0rJ48/wTHCdgu97huC5KKxrdE5LcRXpnOGJLGs9xgy6VcjHlisX0DYu7BXmuWU7OydOImzcfs5pNSTa3BL6iEUo6PU2Zbyl0wOjkHrpaMuh3mN/NKfIV81nEZ598QZI5zG6vqUrJZnHFH/0vf4xWFWfvfMBXPrhHb9Dm4PiAw3vvs4otbMdhs7qj1e6y3mYIDGW6QVIh2NIfjDg+GbN3OECpiqJQZPGWJDGM98ZE2xWNdptGq4sqdlgiJdnFtBoeh2f3affGnL/8Aj90Gewd0GgNUcWS1eIcadnYfhdHxOyNu6yWW4osxW+EOK7g5MEjvvuXfw06p9Hy+c6f/BmtTrOGEPe7uH6bsijeEr1HqDwmWV/iNz08r8ns6hmNZoPddokfhChV4PoWYWNAulsQRxMsZ0yj08f2u/idd7CcRj1so4EQTp1ghCHfvcGyPdLVx1TpgqpSVPkKvzlCWpKg0SRotrBdn/XsNUVeYtsCo6mlHmEHJ2jT2/82QbiHoaKqJFIq8kIinS62Bcn6DRJNmW5xW/frWYIIsRyHsNGgyuYUaYQbjmvl6q9cDH9HbcDPjkyjgzN22zX9/hAvbNPt2tx7fILndWrmqVWRbFd845/8Id3RPTzfplKCdreDdCVP3v8qs9mSRrtPf9BiPZ+yns9YTj6n1IokqYFQfsPHtVIsr0O0i+iPx+h8guc5rCZTnn74B7x4fkGj69MftEijDFXU2WFXLz4lTSviXcxsnvDRj16yuD2n2Q45PexQ5iX7x/eAgrA1JounqKrkr//yu8ync26va/smJufB6R6Nzj6e76GNYNAPamOS9IiTnLIUqOwcYXKyZEuzfYRjC5ygR5Km7B3dw/E7vHr2EmP5VFoTuIaiklhWhmMZLs9f0mp4oDPcoENZKbSp2MQWs+kVnmOTlZL/8O//H6yWM1zfZTPbkiaCixcf8/TpKXc3bzDFjHeePsQozV995y9BwGqdsVosKZJb0njN4u6G2fSOssxId7d0Bnt0+3v4foPdeoFnu3jhIbvVDaac44dNhKzQWmIU5HlOFb/CDQ7I45dIUqTro+IJlg1VaSHskMAvkULR6L2L1rDbbBBWgGX3MDqn1+3guuD4LabnPySNl+TxFmNgdn0JqFqgqVe1FNwJiDYl0mrieynS7rJZr9FVhmUFaCReOELlW/zWQ7zQI42mLG+e/5rF8PPwYX4evyHqKaCwce0tN9dzXj87x3FbnJzdY//wkDxP2a2u2SzeUCkFRjC9eIXRBYHfwbYFD979KmF3jzjaYQho93tUZYwtKqL5JVluM7v+EmH5KB3Q7Q+wHRtph/jtAc3BEXl8R7fbhDJGaeiMTgmafcrK5uzRE25v5njBgLubC4JWG88TxLnP6OCMe48/YLNJ6PVHTK5e8fj93yLZrTg9O8EPBxhtMMbh7vaOxTLCciTPPn1Onifsls+RbkCRFzSbDfqjA3LVIUkqhJRoY4ijNbpIePT0MbqKmU2ndHodVvMJ56/ekGcFhycP62lsktNoNvHDXi2CFALPa3B5E0FV8PrNDcL2SZOCdvuA/cMxs8kEYdtkaX3kywvFeL/DNnbZO2zj+B3uP3qfaBNzdv8ILwjrc/w2J2juMzx8jO+3GO4/QGmbKl1hOTYWGcoogqaL57toZYh3JRfPvstyvgXLwgs6SPcQNzzD8Q8oK4lWEttvEi1mCL0jaAyQTg9jHBY3z7FttzbnV1CVW5LtnDy9IY23zK4v6B+8R5GsKIuUdP2SbWrItl9iSYkbHGBLges4dHoeZVViu3tgMnRZ65ZUEWPL+t9fuN3ar56VlHnG8Ojhr1kMv3hx/rmPWRIT+B7Sv4cqS4yqSLc33F29IYkjGr13WC43NDoHOG4DjUNnMMKyQiaX5xR5ys2LH7Gc3lDlCfcePmK7XHN0/0O8wEV4e3T3jggbfZJkx2rygk7/kDLP2c6nNa3ajlA6ZHxSe3lVVVFmM7armOUy5f/+7/4zH37jfcaHPU7vnzAetuiM3uPs3hC30SPZXBIEIUWpWE7e8OTdx2BgtDdgNn3F3nhMHG84OBxw9vAM2zJ8+M13sWVBa/CUT3/0Ed3hAVU2xxgHSUVvuAfC4fknPybNas9AvJliMDx8/A6DvRGW3eDeg4fc3d2xnr9BlTnX5y8Zjnp873ufMbl4ye3FK+JowYOzQ/aPT/it3/42eVqQRjf0+z6NVhvfE3QHQw7PHmLbHu9/9X2C1gntToN294QsXpFuZ3S6IUVWEC2viLYpnd4Ax6oQwmK7WuM4DfywRZ6nKF3S7B+S7Hbc3VxRKougOca1Na6jse0EKTRFugTLrwFfMsB2g1re4vZpjb6CtJtvL7UeUmja/SGqyglCF8drIr0xfusQbVxavRP2jh6zXq25fHVBI2wi7Q6P33uMbUlK41Hmm9pPYQpUkdfhMKsdttuju3eM5e0hbOctCUMgqWrXorFp9MY1ZODXKgZ4+3b45cDpPCv44rPnbLcJ/fED7r/3DfIsJ823PPviNa5d4QT7RHffxxIlzWaDZPkl8W5FpQ1VkZKXkk9//GOavVNsp6LRG9Du7GGwiLY7JtcTnMY+/fE9hkdPcRyLsNPn7Ok3iFPFdpPgOhmBtcYJRuRVwGy65Pxigm1JPnj3DMdt4/j7uF6DVnfAanHN1YvPEGrDxcU1UhQEvs3+yfusZxP643soZXFy7xQtHYbDMXFiuJtMkHaTUhuqPMdvdrm5Ome7XuG39xACOv0htiXw/RZZsqXd63J5/py8tLAtw/PPP6YsoSxj4u2MbSRodo/AKBzbYITNt3/7KyjjMNwbEDS7JPGKdnfAcnJJniwYHz7hybsPEDolbA/QZYLKE6LNDMfxMVpT5AWzq5fcXF+htCGN10jLpigiKpXS8AocP2Q+q032RghWiwVZsqXISzbLFbYtuP/4q2yXc5LCQVolg6MnZNGWIp0Sb+7QxgXjYlsKTO14U8bGcnywPGw7pCojqnyDJXOi9YYy26GFoExm3L5+jsQmT+7wA0Gj1UCS4/ht0qSkTNdgOyTbOUiDKiLKymB5LVQRkWZbymxec2LRxNstSKiUYru4wm/1cR0wZYIU/98ohl/UJ1F/miQl+0f7rCfPiKKUq4sZQeAxnc44ODji1bMXnNx/RNA6wfGaaNmiO36PUjk0O2OC9ilhs8nZ6Zirl9/H9fsksUZYBZqQJ1/9bUK3IN/dkSdbouUr0miGURVxFJOnFa3eIVk0wbIURZZhWRbt/h7t3hBhubzz9CFZlrFdL/jy2QWDnoPttrj36AFZoVisYrB8Xr+6IE1LPv/x56TJGsfWfPHsNa7fYLfbUBVbDo9G2Db4jTFe0CJar/mDf/aHNeYdlzzfIl2f1eoO24Zv/v6/oMojjk9OsSzJbrvhva99m2g1xxaGoL3P8f37ZNElk7sNre6YIo35wfc+pzfokCdLsjiiLEEbC0xMmiVkOey2EdIOSVNBlkmU9sh2K9bzK6Ttsl6uaA8OefjofY5P9+jvPWR+F/HgnW/QavXZJYqr16+IltdURY6pco7O7jM+ecByNkNjUeYRZbmjLGKKZM1mndBoDRgdHtextE4LdIa0XIQzrukWIsaoCmFiTH6DFh7SauGEBzjeAD+Q2I7k9uVH2F6Dk8dPMSbFshywLBq9I8YnI6Tt4ngVtg1VLmi1PZbTGZZdiyQxAssL6I9PcfwhRidIy2Ize/1TQJnf6OB4HsKSaFOQp+tfvRh+Isz7eR/0zwpEIC2f6Z1m7/R9RLFA6Duur5e895WvU+UJB/ceYusYr3lMmmak6ze8Pr+j0WzRHzbxfYs0yRmfvMvRg0dcXS1J0xTLbdPun7GYnDO9ucBtjEiiFOx9LK/Ddjnj9qa+QGuTsksEllQ8eHJU4xK3Mw4PRgyHPl6zSVXB3VJz79F73FzPsOWW7Srj4tVrHj5+RKPZwnMrOt2Qr37z23h+i6yyqQrF3fVrhBvS7J6QZhWvvnzGj7/7Z+R5Trvbw/JCsmjH7Pw75OkOS0h63W49dfYsFpMJneEeWm0Z7p9gOS5C5jQ7HVwbDo8GOG7I/Sdfw3ZdwOMP/8Xv47gdevvvcnH+klarR5HucMOjev5Ahe00idaX2FbB9eUbFtNLNqs55e6a119+TrN3QLPTI8/mtAZHaATaZMTbBQhFb3TI8b17uL5XM15NSVkmeF6IaytUvub2aoJte3QHYzr9EbcX5wh2+I0hZb4mbPXAlGhToooYTIkb7KPKuPaCyBBVrKnSc4RJqIolghiVr+n0PD767l+jqy2uG6BNQJksyVafkWd1loIUgngTUZUlljOmPTzF8kc4XhvLkghhYbseRme4bhchXBrtAUJYGBVjuT66uKs7VPhgub96MfyEnid+4Ws/KYrB+AHXly9ptAfsHZ7R23uKUhXr2Q333nmCKWMcz5BnCbYFYbPJ+195hC0y0AItJMvpG4JGA8d2OX1wn72D+wRBg6qqKQ1ha4TSAXmWU+U7wMIJ+pw+eEijs09R+AwP7lHSIk8z4t2a9UYxm0wokiXp7pKqzECnoA33Hz9gs9zgt1rcf3ifhhdz8fIFl6/OiTZrMHX/fnn9Bfv7A4Z7Y/K8JEkzbi6u8X2f/YMhSbxGVaoe/Zucij6B71HlGdJp1qDdIubg/rsIKenv3SdPpghyTh58QGewz3qzo8xrM5DJV0yuzvGCJqu7S/xGk4/+5q8Imz3+9C9+RKUKgsDlcNylzCN6e0ckSU3Pu/fgkKARcnT/A4Tdo9Ptsn+4z/T6giLPWE6vkZbDYraiM7xPu3OAUQnR+pyDk3tEqwvC1ohO74AkybAsj7JMaXa6eGGL9d05jXaXbq+D5XRZL+9w/DGCiqrSFLtZrVdy98jTDV7QxfF7tZ/Z9sg2rxHSRdMhTSuyLKPR9Dk+u4epNhjhUKVTpG3XAZT5HK1W2G5IHr9ht50DAs+K3/pYFKraIIVDUToYUyLcJmW2ozM6I88LouX0rQ/fr/PcrBDw/sFiEP+QSTrPkl/6yZ8UgwFefPo5rWBHWRW8+fJjTh9/jWi7Y7HcIYsph09+D1sUvPryUyyvhaNynnzjd1hPX+IFXaLtDs+3MQqy0uLo/iMskZHFO4psjhPsc/PmhrLMCUOPIk/otG0OHvwWWVYyv/6CTm9IVWYsZ69xPMHV9QYV3/HmJuXdr3yN3XpOb9jn3tmQzz/+IV//3X/F3XRJIyi5vrjj8Qcf8IO//oyDwwFhs8/HP/obPvzG18jTHOyQbnfAbrtAWi5VXvf1pddj//CALIsoM0jiJf3xITqb4jX3cf2QeDPHclwQFp7frC98lkYI2O5KPFtjCclyPsWSEG83WLZit/NodUBa++T5iv2jEyql6l8TRQShz/T6Db1+F6UEyXbO4Oghrl9PWifXN+zWtRPPCBcpbco8x/UCkjhieHBEme1Iog2NdgvHbZBESxASI3xWd3cMDsZcvnpB4GjG999lPb2m3d9ju17SaLh4gUuRxzTbvdqX4DRQ2QTpdkm35wSdx1TlDopL0ALhOCjtgmgjbBfPa1Ekr9hu/RqCtj7n4+9+n2/8/j8hT+6Qsk3QaiDtAWl8S+BWyPADTLVB2n5t3FElabTAyBa2rVEqw3cNxrQoaeP7Tu3FsQOEtEg2MywLuqMHf+8Y+r/iAv32G34idjKG/eMet7c32I6H034XKX0KVaMVsXuofMrNxRtGoyH74z0EGcu7LY1mi1a3RX+vz3Y5pz08YW88Jt1coI2H45RIq028WtHueZw9fsjR2SmNZp9dojl/9gnpbkmZF0ipqfIbGq0O09sIz2/SajY4OdljeXdLp+syHgqKvODh+98gTZa0Wx7SthgdHPHD731Mt2NR5VvSeMdXvvoheeUzmy1QVUUcTdGqtqc2m02UTvHdlN1ujS4Lmu2gPps6YHk9pKkAG781IGwN8PwAy3Fwg5CySMmSGFRSe3mlxLLB9V0O7t9ndHBGEFq4/h5ZuqDV2SNeXfL6s7/Asn2a3T5FqXBdlziOsJ0AZXfRxqDK2lqKVuyNGygtOH9xgeu5dIb7SFnguhb//t/9e5Joi9ECgcXi+jNAcHl+g87ndPshWsPDp0/ZxprVbEJv/z5VHuE4Ei/oI3SBFFVtuinXFHn8FtOSU+kWBhedX5LmBtwRdvAANzjBmB2WXlHEz7G8Q1qtDK3qfOhv/sHvIqQk20UErS42BYIYLZoYu0O0fAHCoyzWtSg0uUOYAj+QOG6AFw6R7h7C9vCDoP77CYGQEnSF7Rgsx/kHt/k/qhh+8Zj0k49S2pw9+ipeY8iDdx5iB018v4kqJaODE1rdA+49+Sq4Lap8S3u4h1AzhDvg2aevcP0e+0djoMS2Cmyp0Lok3kaU2S1BM2AwPiNsNLG9DsePnlJsX1CULggYn95nt5lguQF+94jJzQ3vPj2jO7rP0ckRuyyl1T3Ab44JO0OCoIfXOEEbF2kM3/v+D0nThI++/30sJ2S4f8D0doquMpaLCa6VURaGTq/Dqy9+gO2HrGfnBI0etqzwwjbaGKLNEsuq31x22AGhsS0Hy7JwXB9TpViOTat7QNjeozs8xrZtHNcmDB3ChkeepAini9toU1Up+8dH5Mma1TJlNDom2UzBUEd8dccIAizLIIVifvUpujLMbi5wHMl6I/FbA568u8/N+afMplO8oIUXhuwNAvxWH8tRJPEWKxiQ5hWn949Yr1Icz2V6dY4UksPjEb1et7aOqregtNlLXnz2fSyni1FpjY6UFVZwhGW7OP4AKQVu44xm50Gd8qQj8uQK2yox5Nj+KdIKavsuW6qqwvFa2F6TwfHXatn19gqjSnzXQRd3SJFRZPM6y0NZtZyndYrt9pCOi+M0kE6LNN1g2TZeo4Pj1ZnTSme16lj9WgGHv1wAP18hQaOP1gVSOgR+iOf32T++h1aC6zcvmd3cUuVLLl88Y3BwxuWLHzM6ekieVQiVs5lfUZWa2c0rlE5xwj3yNKNSJX5rH8sx6HyL0RJdblBVRWv0BEes8N26Ndgd9PDDPo7VpDfYJysFo+N99g6/xuH+IYNBkyLbQhnht7p4vo/lSObTGV9554Tf+q0PubxcYbTm5bMXPHz8mE6vje+HROslrf4elTI44YA8jkmKAT/83g9r34Vl2C4mHJ+d4XoezfaA3fIaKR3iaM2XP/6YIl0jLQchalaQYzvYUoC0KfMdfrNPnlcs76ZU5Q6p5kTRiu1mg5QKWyYE3WPcwOPVF5/y/OPvU+Uz2r2QeLdAlxG94RhDhTaaRrNFs91hcfUcjE93eIhROW7QxHY8Hj9+zGZ+hXQ6eEFAvEtxLIExFcODA4QMOLl3wvmLFyzmMbbXQqJIs4LF3Q1xXnLy+NtUZQLCwXbbgEsWrSnSDV7QAFNSFTG62qKKLVVVImQDbSSGLtluzmb2inizII5qOrdWFULvQMWk0QVF6SKsNlo6FGUHL+hh2U02088oqxKl5Ntwki2mKustKQR+2INqQ1kklNldLYLEBiPfclh/1WL4OVHeT/6wn3SYpBAYbegMzvCbXao8ZvLmUzAlxw8fYrsOjWaDSrv0hgMc1+adDz5guYxx7JzD0wPC7hFGeAxGh6hKk2ynBI2AsBEgdE6lA5ygT5blKKtJVSmStEUZvUJaVg3KNS2EcDBG8OjJCY5dcP3Fn7OZvcRUCX/6H/8D0fqG5dagqgytFdJqYbshq53gs48/53d/70Na3R6u45GlMX/15z/k7N59/vTPP0GXG/7sj/4zlCts3+Pr33qPh49OCVp97m5vKco6cP3m8iWr+Q1ZvCDPaumCQ8R2E/H8k08oi4x4e/c2TqlCIN4eVwqCoEUjKLEtSat7QLzdIZBUKuOvvvs5yW6NrhS27XLy6Clu2MPxBxhsuv1e7fHwQoxRLGdvUGX2FrzQx7Zt9g8PSaIFWbxgMD6k2fRwxI7F5Ip2p02eZVyeXxE2uxRZzhfPruj2Wpzce4BShs16i++HjA4fEgZ2Df41MWVZoI1C6wrLKnGDUR36WO4QokBVS2xbkMe3OHaOZTdqyLBjYcpb/EYXUWZYtlUDwSofrRR++yHN0fsIO0Rqjdu4R1W6WHaP3tHv4PvNGjWpMnR+iVEx0nJR5QZptpRlDioFFeEHdcKQ64Nnx79GMfysqfrTYvhJhwlEDYLVhjcvX7FZfMFg2CDb3bFbXHF0+oDNage64ODoiKvzF2xXK6ZvPmazjnEbParsjs1qw259RZ4rws4B6NqtNLnd1hdH20HqDCkEuopwZU5j9FV26y1GVWTpjjJLmE2m/PF//F/RlaLZe4DRW4YDh0fvPCLsvsNyrSjThGR7w2Jxh20bHjx6QKfXp9k9YnbzmlfPPyFstPjga+8Tb674t//jvyLfLej1HCwqNssVi9kaoy3iKMNzBTeTCbvVHEsogkaHVv8ey6sfYoCDB0/o9Pocn7QpswgpDUqXzCbn6CqlUB5CWFT5iv7BO5SlwnZbPHnngPntK3w/4F//7/4NvUGPxd1rHFeRbO9QSrJeTGl328S7nOnVNZvFLe3OAUFjSKNpY1l15FTQ7LGLNiwmr3Fsh9vLN9xerdmu1kirtoD2Rvv09k5Zz6fMphd02gGzeYxSFY7jEDZCimxKtL6lPThlu1rS7L+D0Fv8YEhVZRjjkmUxwkRU+QrL28foqo4NE27NTY0+RhCzmb4mbIYIvQSpkVaAkTaWI5GOj5RguSF5VmG7LWzHwfb3MKbWOFm2g+M4WBYIdwx6jtYVqtigq4QiuQNTgD2gSmeYao0uV+hfa+hmfmbzhL/dVq2LA+aTGZ7rs3f6W7QG97i6fM3J2T7C8umODljPzmuD+/13a+TJ0Qm2ZRPNr9mt14z2OxhSbi4vUbog2S4xwmd0eIil5vU53GviuYJ0/RrbCwmaTRRt1vMdrtsgKyyE0Hh+yPMvb/nBj17w+edX+GEPt3FEs7PHO+/eJ9pE2I6HpdYYGrx+9oK7ux2DQYfB+JjBeJ8//+M/4T/+v/8dx4++zfzmiqDZpjs8pdk9xnXry5jjFuztd9GqInR2bBOJ6wVsVxN26xvysgVGvTW4u2h8prd3KGVR5RFh6DO5+JLeoENV1rlkWRaRbCbkWYrlnzI+PqEoAV0yuXpO2NqnOzwmDD3mkytanQGf/vhLhLQ4e/wOWbIk2a1xXcV8OqOsEl6/eEW6nbBcrAi79/DDPjevP6HbtSkKxW49wQs6JNGKXq8Flk9veMRnnz1nOGjhhyGCAi9ookVIfzikzHaEjQbR/Hl997JttCrh7VGwLCXCHWBJD4SDDE6wZY4UHlbjKZbdpDNqI6WH2zqgNbhPlqy5fn2NJT20aZCnBRgXVWmKokLnc/xGg91mRaW9OtIWQZnvqLIE4R5hTIHl9rDcLmH3PkI6GL1BmDocs6xqQsevXgw/t/5OMp+AixcvUFWBsFykHeI6Di9fXBCEHaJoy+jwjKJ0iBYTOoMeQcMmS9doo2n399A6p9W7T69XB31XCsJmDR5e3XxEka1QBtI4ZzZX7J0c4PoeliPpjU9Y3c3QVYxRKVHuocuIm+s1q82G88stZVHWOcHSpj04oChdLMdhtytwrJjBsIFl25QF9FuGb/721/id3/kGyXqCqioW8y2L6YR4u0BK6A4P2K62OI5DUSikUfiOQpWKjz9+TXtwRqs74vyLH7Hb3BGv3lDmOeOT+7hekzRNKbICVWZUeX22NdLGsmzagzFG5FTpBN8VhEFGkW9ZLnc02z183yFJFELkLCZfMhrtMdo/5ur1c26vL/CaQ4R06PRGvP7icx6/9z7Res58ugBhkWUx/dEJ0h0SpwX33/sWVZYAGt9zaTU9LMvh4PCAIAyQArZRRJ4s6HbbqKJGYV5f3NIZPMTxQyzLQ1qKOM7QVYXtgC7W6HKCG57Ucyrpk64+RlVF3eWRLZS2gADptvEah4xP9sHqYrTG9bsgXRqdIXkhyZWgqnKavQG2Xc8KlE6RrOtMP6eDlBZ5vESbClNtqSpQZY7l95F2SGv0Hp7f+jWKQfx8FfwdIDEEp48esl0tkLI+9wXNIe99/Wv1BNBsqIolvudg7C5e0MZvjlH5hMV8RpFHSGeAlA7DvT4anzjaUcRTVL7lbm7Id2smFy+ZT1fYXpvdJqplD1KR725xwhZBo0eR5wy7DXqDFsPDEYFbMhrYnN7bp8x3WNJhF+fE2xWrdUoQgiXh4HBAlcy4m5yzmEUEYZdCB8yn51TFkttJxPruGiEFeVaP+TvDUww1oe3ek69TpluE2+Bb33yAtCTolP2jI+JtTJKAFgHxakK8i6iKCjvoU5QG2x/RaB+RZxVVXpDstrhOQKlt7MYh6eaO6e2U+4+eYpCU+ZZGe8Bg75gkjkEXpLmg1+8y2H+AH/hE83Pa/TGj/T10sSFojzk6OaHM1xTpgkZvQLPT5PDoCDD4YYDjesS7BDdokkZT7p0MUGWGMZq76wl5mmM5LvN5QV5JHjw+I9m+IdtcYADL7uHYEksmgIsdjClUSFUUGKUwoo9wuthuF9SKNDV4zXtoNEU85e7iFZY7qJ/mwgIdo8qc9eoOzwfLamFJie3YCNumSDfYbhOlDWHDx6gdWmtcx0aKAGH3kORIWeNqhHDQ1Qac/j+43e1/8GcRP1Wt1q8m81Ow2E+OTsdnJ8yndwgM1+efEvqQJwm7OCPLbJotGyE1yW5DuVtgtKTZGeMVGUZVVPmMMldUZYkRMa7fJt7OmM5Sjh+9R5qHSDNjvdIcHg9wPJciAWkr/PaALE1JtgscS/LVb7xLksPv/+FX2cyeMx4P2GxSBmPNZjljevmKx08f0R+2mFy+5N77f0hVxMxnX3B9t+bxWZ+bN88Yju9RZD5DP+BmsmbwdEgcxTWKPTAsl5Jk85rH7z4hyzc4wYDZdMGw66FViRv2cIM2fafFbnVNo3VMtLrF6IKw1aVIt3gOJNEaKS2K3Rwv7GCKGNk9wDITbBGwi0rywkOKDK0k0mmzvH6NYye0+seYco3FAte32Gu0MbqiOXxIpQVJmpNmGlVqxodHFGU9Z3jx/Hu0OwM832G9XNDt9bEdh9vLFwhpKIoKVdwg3RHwhtG4zm5OogVh6OC4Hn64j6aBYy0Bg+P2qIoM2xIIy0ZYNmW8xWn0qUrJ7O6W8UGAqlIsy8P1PKoSgsY9inxNZ+RQJHd4/cc1ClKGaF0PWl239TakJMVy6lCbMs+Q8m2GnF3ro1SVodQOiYt0baTjoooVWrlYtsCoEq3eQKP79+72/8Kd4WfxVeJnn/5ci1WjtaLTCdjMX3D34j9x/vw1eZpi2wJLVqSpxWr6ml6/TWv4iNvrCa7rYNsucVwSLW5YrGKuLm/oj0YEoUteBqw3W9rtNkWxY+/4ISenfYTwKHJNVdadFcvzCYIGYadJuxtwe33H5etLvvjhd5FS8/mzCR9/9DdYlkuz3ee9b/4ulu1yef6aLFujqpxXz1/Q7B3zu7/zIZvYoTcaUyR3dPt7/Of/9U84PDnADbp4YZf1YkqSFPQ6DY7PDpFSEm8Ve0cHtJo2pbYp0xm2lDWEOL0i311RZmuUqbU0Vy8/o8xSjh5/iCUVqDW7OCZLt+w2C6L5NW6jSRzFjE8fc3rWr/Ppyghdrjm494igOWQ939a81HWCtBss5xNAUynYTF/Q63VIog2t/ghdRcRRjhCC+48fofMFu2hDFO1w3IA0XmE5DYJmC60Enf338AIH6fRwXYfNJsX1h7R6B+w2V1heB4GhKhJUVdUgYK+NdAdI28OYHK85ROU7qmxOZzAAXWJwkJaL3+jj+GFNupPQHhzi+mHdprFchNVEKYmUAWWxQxtDka4okiVa7ZAiA+rcaEQTIUPI5zhuD8txUMlrQGJMH6MitMqwpEK6vxZE7Gebv2Ylwd+ScgvJD/7quzjmht3yDUnRxLM3WK5Pf++QMl9h2y5hq4fjGLoDl8OTMbqM8FoHlPma/sFDzu4/YHx4TFlIjDHs1hO+/U++TdA+Znx8TLxbE2/ugARUQqMz4u72Bq2hzCaAoTQdHr/7lKMDiydf+xbnr+/YH2p++7e/TlXUgDAhJaqKSdOMTmfI9M2P2c5vuLl6w49/9Dl/+kd/yn/6D3/EZx/9NYvJLd/+J98kCBzyTCDNjtH+Pt/5q2cYU9Bo+txe31IVM3bbDNf3UNkUMNiOjS0NTrDP4cNvUyYz2q0Ay6pod0doyyXZ3uH6dQro/tEZndE98kqQ7Ga1DLpYETZ76ErjBWNst4Prd3BcF4Gg39dsoopWZ49KebR7R+iqIN1taXRGTK5v8UMflW9B1ErRLIlwrRjjdPFcl/G4x8Wrz9mulzTbfZSqaLQ7SGFodTogbCqtiZKK64tnOI5ksHcP2/Zw/RDba6HyBaq8Q6gVUghUlddP4ewCy22T5QLfUVjuEC/cQ9o9VDZDSButNEa26rAWK6zZq5YHeoEXNLFtahunKfAaAwwFKIWqVphqi8BBV0u0CFDaIJwxUhdgtVEqq4NN3P36tG/kr5fcA39bqVoDnurPta5Dsxc3z6lUyfTigqOz+zS6h8TLF2wm3wUj8b2CXZSyvFtSVjZalyRxwctPv8vo4AHbdcr553+NIyvSZIsXtnnnG/+M3WZOtrtmcf0xju3hhSMkEj9sUBaGbreDLhO0aCJEE88PEaLih9/7lCKZcO/+AbdX1zR7p2w3Kfnulmw7QVghJ0fNOrdAtNjb69AdHVFViqfv36M36PDw6VN2cY7jWGS7HcO9EXmR8/LZl3zrW48psgXpbkYYGDrDB/hujcnxggGb5YSyShFSIExOEU/x22PKPEWYFMepcGxDsp3WxHFLkSQb7s6/z/j4mNF+F60dFpMJqswQlku7NybPC5azO948/yG9vRO2UcHXvvE7ZMma5aRuYliWRavTQGsIGj5SFIStIVWZYtkGbSTCatBqtamUJk8jenv7eOGAZHuFJTy6vRZVVWA7TYJGk/Xskvc/eMqDd94ljaYEzR6qrJ/MRV5QJrdIUWA5fbRaI4Rdx4/bh1h2wGBvjOPZ6HICKkJXO0ChqqQeMpqM3foKKd+eQqSFQCLMFoyqOUqqoszWNUKIHbaJEPYY2ztGSg9RXeE0n2JQCP8IKQ3SamK5AZg6jTTP7yiTV79eMdTtVH46gPvJi0FKicHw7X/2b5AWnD79bVQxYzA+oNORhA2P3ngPIxsUysFxBavJBeu7N9iNMcf33kVYFnl0TnvwiNK0CRpdbNtw8fz7VPFL5tNbNmvFixevaHS6WH6PIk2o8gVFntTuOeOwWm6xbEESl3zw9Q+5vrigO9jj8Oy0hiLv7dHffwhVilERXtgnWs34/McfYShR6ZLDccjTR0MwGXlasolSXL/H5OIjom3MaK+JE47oDfb4+OMXlJXPiy+v2GxjShHQbDaZ303J8gbR/AVFrsAovNYJRmUU6aKem/hdjM5x/ZBWb59ovSNPMqIowbYcsqRC4NHud9BqRaPRI88jHFux224YH56C7dDpH2J7LkZXHJ4+oNUZcXf5gt0uQlcZg9EeSiu2qwlu0OHTH/yQqkiRto/BkKzeoFRRM49kjiNLlos7qjxDFRHKKLSG7mAPgcZ1QbohlutRFAlVGeE3Ovit+2CNQK/Jsy1QYrR+m/1c3zm1EVhuB6UzqnyNsIOf5jQYtaU1uI+0WkjLRpfzOkO62pFGc0yVUmULbK+NsGoGk7HbSCkwUoLVoSgrdLVCCoUq5xiTgVAggxpRavdxGw+xvPGvXgy/iKL/xTkDCMJGg9lkgS6u8TyDLiMWK0WcWjTDIVWxI2x2aff3iTczLFFgs2Uxn2GUxgofIUzMwVGPdLtkM78kaO0RJQLHgrPHp7z7lfcRso5XtYM2jc6AsLPP6u4Nvlthyx3bxWt8r6I/PiMMQ+aTW6YXryjKHqrYsttFKFViu0OS7Q1FLvBdw3rrMhy2aA+Osdwh733lMY5V8eTJGbObL/n8izlF/Ibtasfx2UMmV1/y1a+9z9989wd88OFXWC2mfP7d/4nV3Qui7QqJwA/bvHn9BqUqVJWRJVP8pk9VbOsc5WqN7QjyLCVotGn19ukNT6jKDD8MEDKnyFOMNUSpLUl0i+W06PdAWB7z2xnCxNi2w2p2yzbKmC82bGKDqSyyTGHbPmWmCLv7JNsJH3z9CVevnxHN31CVKd3xCZYUqDJDGXDCPSQlSrhsl2ukUTWNrrtPUWqkdHC9JqpYEzQCPM9gWTlKl6hyiq4qhBVi2S2MCFH5NdIUNT28jBGmQggfqDBY5HkBSJR2KLOrt0EiGsc/Jl5eY0QHN+yyW73EqATHa+P4h2gVo6q4Ph6pHF3cIXRUa6IsH2EMQjgIU1Fm07dRvEt2sx9j9D/cL/pHQcTM34GM+Unqp+t5VEVMtPgRVbbg9s0XnD18yOT2ji8++S6z22v2Rz43V1NWiwtaw3s43hjbDTHCQakUq3FAtpvR3T+m0Rmxvjtn7+RDLMcnL2zcoMlueUO+e0kZX6BKQ56XdIcHKOPSG43pdpsICfn2Gb2999Da5d57f8B2M2O5THn+0ffxe49J4xVJ3iFoH/L0a/+UXbxhOXtNstvw5//5zxCiJGx5VHnCfJ7w9L1jNrFNstvSbNQPhyrPaDZ87m4vMFXM/skD0mTDwfEZYajR9j5n944xKuXm9TO8YIQxIVlcsVnc1VDlUuB6Po1WC9fvs15eo5VFWWouvvgzvCAki2aU2qcoPHR6g+0fkcdT8mSCRFAVKY1WnRzU6Q94+PR9ttuYMlsiLYvJNEVll1hWgy8+ecbhyUNKpcnSCjc4oDk4rrsx+SXSbeAFLRrtTp2aur3FdkOqYoF4+//vuhZCShwnBA2qmGCAoiywHIklW3WooSwJOx9QqowymyGkQZdzLLuFHRyD8AiCHsbkGFNhO13K5A1VXoc7Bt1TbMsghKLRHv60g4m2QVegS3SVIYzA8sYI56iWoJsSg0BabbTWOG4HrS0gJIosllef/nrF8BO0pIFfekv8ZPawmb0Gq0m8ntJoNYl3CdHiHKUlj97/FkK4XL95zvjgGMsZslnPef7Zj9BVweWbW0I3IWiPmbz5Aonh7NETVB6xXm/p9EYsZjcErQP89jFOeESWOxTZCsvK8Rs9osUt8eYWr3GI19hnPn0FwhAtXpPFW5rtDgf332N2+YLtas1ydkO336VUBUcnJzQHT6nSK+49eY94mxBvEybXL+j2uvzoRxdsNmvmywzUjvndlLLccf9el7u7NVIobq7vGAzHWI4HjsvLzz8jS2cUZUmr3UPpnM36Bil2uK6LHdzHsiDf3WBJm93ySw5OHpFuvyRaR+ydfQtDA799hut2kdKlrCzybIMfttk7PKMzHKOqjL3TdxF2gyrdIYViMGzQGZ6SJRFP3nuE6/XRVco77z8hbIUMxocEYR3eWKQFULLL2ri2IAhr7b/tWnSG9ynyNXnloMoFWuWg6+NRUVVsl8+AFlIKPLeN9Oo876rKKHJBVW7Jtp/jNe8hnD2QYHSO0Rm2SN6eMgKkSdDlAiFsbLePLq6QtoN0AqTlI5127adGIB0XyQ6n+QjL8hDSpsq2GJ0CEqNLymSNNvVbyuDjBAMUIQf3ntI9fvdXL4a/Jdd+WxC/bAYSHN1/n5vzN5Rasl7MydINZw/u0+60asZNvODdd08Am1a3xejghN/5Z/89t29e8eE338Vt7JNEK168XLLd7BB2k6LyefzuIyxb0QrrVHghPEw2AxS9wYjVvGJ2e0N7MMAO9tHJlyS7NbeTW8aH+3hhn9evrllMX/Hj7/05SifMV4q9/WOUkbSbDvO7a158+YzXLy4Zj7vMZ3PW65jhuEevXfI7v/t1PvzGu8hqRZEb+v0Wnu+z3sDNxS1H996h2R0RR2uSzRuSzYZev8d8llIpg3Rc8qTgxz/6HmVWIvWcMo3QusRvHVKVSxx/gG2VKLlPbzTAcjqErS5VHgEllq2JE8lmucN2POLNhPXsDbvtDtdvIIwmje7IixRph9i2BUIiBOS5poI6s05LVFlRFiWNpodt197qw3vvUqQ7DIIi29Bstkh3W8JmB12lNHsnWF4bZRyE0UjhEnYeIqWNqTYgQsroBVk8wbIs/AB0foPbOMYStTFJWIM6I8EOqbI5GMNm/hrL6WN5+6h8QVVuEDJEq4oyOUdUc4SpcLxuvVmlgzYSSxQkaYHKJ2gcpE5R+RajNV6zixE26AKlY7I0QeoNxiT8l8Zq/0jV6ls6xi/dGer14Ov/W+698xV2sabdHzMcH3Jyb5/9s3eZTecsbi8wWhOtLpBOj2i7xHUkYcNQJHOS9TVeEPD0cRcvbKCqlEbDwRiL6+d/RdAa4DdGbCYvKPEoizna2FgyZbeZkiQCpQrKbMX47B2+8t5Tlos5jc4+73/whP/r/+X/xuN336czPOX03inKQFmUiGqHJQSH+yNOH3+LKEqYr20kJdq0qPKEVivn7uaG7sDDsgX79/8pN5cT9o8O+MP/7veZ3d1RKkVvMMALB3geNJuaTiugO7hPkReEnTHtzj5+a0yRV7VNUfh44R55AVornPCAdsdls44QOqFMC3xfUWY7/MBDWobheEQaregO7+H6bRqdBnm6pt0b0BrdZzObgiqpKo2qUqoqQVUKVQocR5InOV7QIFu/YDZd4ngh7U6Tu+tXVMqmKgpcLwSjQChUtaXd6yGlRhdbbEu83WgRRrQw1j4YENKpjylSUCWv3lIyIjAVSm1RBnbzj5FsQMfI4ARd3tTyE72jqgyON8SUc8p8iW0HSGeAlv16AKfSn95X7fBdsEZIy8NpPqwz9Jxu3UmyXHS5Q+fTWjKPwXZrwnpVRlgi+zWK4e0yPzeF/sU3gxCC2XzJ888vOTwa0munFBlcXa7I15dkWcT4oM9mo+gffYt0NyNaTdBYdPqtn8amVlmC5dUdJccJsBybSnnsHT1AlSvSeIvlugStI/YOD1nNFxhdcXDQwXVDwsCn0h7zq3OMZdMdDthFa8LWId1WEwtFmlZ8+fkzlHb46PvfIUl3FEnCdDKl0W5xeLzHyXGT/v5p7dFoDjh/teTyzRtw7rNep0TLc/YOTnj25Ut0lfDF588Zj/co8oJKOzR7+wRBSJqVrKbPa2egzui2QhrdfWy7wguaZGnCZvI50mqg0ldUpUGpDHT+NhdNs4siBCUYRatR4vn14C7LUqQs0cYjS2LSeI3nOZw+fB+tNZ7n4PgNqjTGsjKk1GzXa3r7+2ijafaPmd1+yermI3bL14QNG8jBZJRlidEpnh/gBR0cx0MXcyzLoUjmtYkpmyDKKbqaYnn7Nd3aqLpD5I7QxQyv/T6W9FGVxlQ5VvA+SnbQxsaUK4yhDkyUbaQl0DpBG8jTDVplSKtJtLzDmAIpBSDqsEOVUSZf4vt+nfHnNilKHyMshK4wVh2pi1EIK0QXWzA5QkiUKn/1YvjFd4D8e3J0w0YDYQX4rX1wj4mXr+h0ukhHUqQr2v0T9u89YHzykPVsyvjgPpIMI1pkysVv3efy1TMGR4/J0wytFGUpKcsSabdJN7d1CkvhIlAYrRnstSjSCMtrgLQplEQ4bQQVo/EhruMShi6ru2f8H//P/6e3CttLLLHh4PiIzbbg+asZjXaDpl+yXU+Z3d6SRBva3RF+YGiN7jGbzGm299k7HJCVDo4b0O7Y9DsB63XMO48OKZM7Gr37dDpvp7ZeC8+rwzyKbE2RrhiPe2RJjHAHOEGH3WaK133Mej7FDo8piwTp7COlRxrvCLuHBO1T3EYPVSmc8AhVLoAUy2zZbVZYUrFZx4TtASAp8hiwmF1+DxQ0+6cUyZpGo8cf/8//E4vbK7TSYNkcH+5hOR0q06LZOyZstZBWjjAp0vFx3ABVKaBCOD20jmtptWVwbB/h9LDdfap8gUpeI6SN57cw2TOEcAGBcLpY0kLYPnZwgGX3UFWK7Q0Rdgth9zG6wJKA1cSUm/riTI4RhrBlIUSIkC5gEMLUv7eoaoGjWuF4DSzLxbJcDGX9wK52YBKESTFmia7mUE3RBL96MQA/vTj//PvgZ0clAxhajYCbywuKoqxH92GDeDvDdizGh/d58cUz/vxPfsDzz54xn1yzmN+xiyTTmyuS5Q2SiPHZV1hP37BZXiOlzeXVgiK6Is9ymoNTPNfG82F6/Yqq3HF1fo3XOsK2AyolcB0b1x/heh7rxZw8uiPPIz55viPPYooyJdstkM6Ql19+zr/+3/8fePLet8gKm6tJDqLDl89umc0jvv8Xf4Ln+Uyvzzk8PuTJVz7k7nbO9cvv4fsd8jSi021jOQFZmqKrmHgzo8x2lNmcaHWNFzSYz3ZYFnjNExp7X0OppJahLG8w1Q5bJkjHJVq+QsgGbliHsOA0yJI1Uq0psgQ37CJFgRMc0O4foVVOdzBgN3/GcLxPtHhDHK2JtlvyYocTHmE7HrvNFXawR1mu+Z0//ANMlZJHS7SxqKoUabdpter2qtE2yHp4mSUZqlwjKTFVAjqD4qqWXEiBdIYYHYNOsJ0GxmpTpueYclMPY50a2+L6XYTbx1Q7LLGlyGvpiFIFjtvHsl1UvgBVIoXEDo7xwlOMbCGMQkoPKQ1Fcv3Tx7NlB1jOMbbbxGiDyidU5RRVbcjjG2y3j+2N0aJNGV/VedbuECd8h2bn5Ncrhp9jhv2tQqg/1K8v1w/54Bsf8jff+R66iEirJr3xMa8+/5RW2+b08Yc8POvQ6bZpD08xGKRasH8wptn20NomaDawXQ9htZjfPmc4bBF0TuvLk9JYbogfOpgKDA5HB5p2r4Wwmnz5yUdIp4VlKYLOACEqVuuc9SLm7LDJdrnCD0K6/T3Go5DBsMPd1QsmN2/YP9znv/nf/LeUZY6uUr712095/P775LkhaPQ5fvRV3rx8zclxm7PHXyfJc5RoMb38gqPTM2zbe8sIvU+VZ1RVSWv4Do3ugEZnj7BZn7m/+PQzXH+IkAFBe5/9+99it13RH+7TaB+wvHvJ5OqaOIpRpSKPc4rKwnMsdLEgSerLp+W0cMM2Qob0Dt4DChzPxxgLrSqG+8e4fkhndFjj4DsHOG/zDyojyJIlaEmebQlbbdygj2VLGq0WjphiOx6uC5ZlYbs9jOXV3RpnjFHr+umqIoTdrTGP1eZtn38fr3GGKXdIq4dRWR06WK2w3P7b6KsMVExVlJT5JUK4eOGgDr4pEpDy7f0kJtlcsVteUxYRjndc57EZg2WHFNFHmDJCawOihWtlWHaPoPUAKX2kXQfUe+0P8FtP8FqPcIMDfvms819ZDD/Jb3uLHf65O8PPm3wEw0GLTsOhP9D0e1AVWy5vpixnE5LlJ1i2y2gU8vknn5KVktHxE7zmKW7jkMnNBabMmN1ekicbpOWwujunrCqqMiNLI7abLb6nGez55LslWdHHtmAxnfDht7+KtFKUMhhVkex2KKXojB7iNUYMR20uz6foovYSuG5AkWvaQd2FWUxecO/BGf/iX/8PdIb3kWrD5esv8IM6C7nZNITtHscP7tXGonyDG+6xms0Y7R9y/ORbxMtX7LYrhLCJls+JF68ZH4T4jTHx8g1Pn4zxXMXi9iWu65DFW4Jmg3x7TRRV9EbHtP0trU6fTqeD32gSRzuqcou0XVq9PRZ3a4xOah+B0wKTcnezxFSGdrdBEd/h+yGdjodtC/rDEXl0TpUt6Pe7uI6gM35INH/D+N6HYCIs20HYPkqlSO+AIn6BbTuk0S1K56jsBq12IFyEM6TOUMtwHB9VJdheDyF9hBVS5jMIP0SplHz7YzAGQwNjdghhI0xFkVwhiDFVSlmsqMoSpRRKtCjja5SqkM7bo5HdQdid2gNSpPVekxK/+yHS7RO07uE3jgh6v4MbjOq3guViOy0anRNs23ubPQfmbQbdP7T+wV7TTxxFxuj6mCQMQsifFkA9Naz/gC9+/Cn9vUOk3SGJpsyvzvEcQVkqprd32HaX189L7j84RIqKdDclrzpYIsFxBI7f5eS+RbzdoHSTg8OALLqj0T1isYjotMO3l0xdtyzFhs2iJEsapKHAa3SRVkIS7Tg4fcLzj/+E2bXhxRefMRp8kydf/Sp5VuF5gu3yhsHeA65eblgslnz1m++xWCZ0WhmOc4Db2KPFDl1k9PYOaBQV0mqxnV3RaA/wPYkyQ4p8B6JiMBpii4D1OiGaXdIbd7HDJ6wWt/T70Bw8JNnOCBtNGs02RZHh+G0azR6F26Z32MboEjkco6qCMttR4WG7NkGjicquyJOYwJcgJJbTxnIM20XK/r6HE46Qes7oIEQSUyExlDhBG4Om3dkn302wM5cquaE33icIG+SZAiFwpKHKN0ihwao3ot86whQzLP8UXawQpkSlcyzvGG0U0mpisKlKcIMTsmSB7bo4xkOrNXb4AGNAlxG2O0JIg+W0UVWJdEdU2Qzf30cKQVkW2I7Gdg8wdSMYt9+uQcHG4A0f/OSpiwBc7xDkLwjvDBjeEuJ5Owbg54/4P0Ok/n3rH4aI5elPBg1/e+DGTyh7PykI+Ogv/xMi+WPaozOkcPB6H/Cj7/yQr/32B8xvb1CmQX/YwnMdtOxhWTCf3eG7ks38DcPjr9Fq2liOYLeYUOiQVnvAxz/4IY+ePibLCnR6xej4CR//5Z8SdPfwgyZ7R+8iJGzmrxjtuSxXgpvLKfv7XbKk5pR2uiG313f0xwe4MuPV6wu6/VO63Rau7/Dq+UsOxnvYriBs+nhhh936DsftI2VFnICptmhlaLZ7QIETOPzVX3zBN79xROjGGKvLav4GR7q4YYeilATtPV5+8SmPnjyiyFLC1oCyMnT6+7XuH7Bs7+1/nkEbQxZvcIMmAoVSCqNLjCnAOJhy9ZbWZyHdDqrM0dlLbG8AwiPP1njhuH56ozHSQ6q8Fs5hsOwAlS3qqbNlU2QbbNsj2a4IW112m5h2v1Of4+0mkgwrOCZZfoLXOKJMpriNQzQazx/ULU8tsR2XPIux3aDWrBn9lgZSw4CN+RlUot5ubzem4Kcb9xfR1r+4bX/+PPLz2/pn3yvA6J96bX46KP5bv6/Edd2/tyL+wWL4zfrN+v+n9V+dA/2b9Zv1/6vrN8Xwm/Wb9Xb9phh+s36z3q7fFMNv1m/W2/WbYvjN+s16u35TDL9Zv1lv1/8H/776TNc1BJgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(from_local_section_image_table[\"primary\"][0].load())\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54d04006",
   "metadata": {},
   "source": [
    "## Downloading the entire dataset\n",
    "\n",
    "Below is an example which downloads all the image files from the dataset. Be aware that this will take ~8.5 Terabytes!! So make sure there is ample space (and time) before attempting to run the example below.\n",
    "\n",
    "NOTE: If space is an issue, it is entirely possible to use the filtering techniques shown throughout this example notebook to pare down the `section_metadata_table`. The new subset of `section_data_set_id` values in the pared down table can then be used with the `section_image_downloader` function. This will be left as an exercise for the reader."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59710d6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "local_full_data_set_save_directory_with_more_than_9tb_space = Path(\"/local1/FULL_IVY_GAP\")\n",
    "\n",
    "local_section_metadata = local_section_metadata_loader(\n",
    "    local_full_data_set_save_directory_with_more_than_9tb_space, \n",
    "    verbose=True\n",
    ")\n",
    "\n",
    "for section_data_set_id in local_section_metadata[\"section_data_set_id\"]:\n",
    "    section_image_downloader(\n",
    "        local_full_data_set_save_directory_with_more_than_9tb_space,\n",
    "        section_data_set_id,\n",
    "        verbose=True\n",
    "    )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:gbm] *",
   "language": "python",
   "name": "conda-env-gbm-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}