04_Experiments.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# eLABJournal and jupyter : experiments\n",
    "Access to your eLABJournal experiments from jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the elabjournal package, create an object to access the API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome Matthijs Brouwer\n",
      "Package 'elabjournal', version '0.0.15'\n",
      "Your active group is 'PB Mushrooms' (1056)\n"
     ]
    }
   ],
   "source": [
    "from elabjournal import elabjournal\n",
    "eLAB = elabjournal.api()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "<title>projects</title>\n",
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     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "#visualize\n",
    "eLAB.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In eLABJournal, experiments are organized by project. Projects organize a collection of studies, which, in turn, organizes a collection of experiments. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "      <th>name</th>\n",
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       "      <th>projectID</th>\n",
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       "                          name  numStudies\n",
       "projectID                                 \n",
       "25851      Metadata definition           0\n",
       "22534              testproject           1"
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   "source": [
    "projects = eLAB.projects()\n",
    "#projects.show([\"name\", \"numStudies\"])\n",
    "projects.all([\"name\", \"numStudies\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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   "source": [
    "studies = eLAB.studies(projects.first())\n",
    "#studies.show([\"name\", \"description\"])\n",
    "studies.all([\"name\", \"description\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experiments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An **experiments object** can be created that describes all the experiments. By providing parameters (see `help(eLAB.experiments)`) this set can be filtered and sorted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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   "outputs": [
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       "<g id=\"a_node1\"><a xlink:title=\"number of objects\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"79.3313,-52 22.6687,-52 22.6687,-16 79.3313,-16 79.3313,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"51\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">3 items</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x123b5e630>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiments = eLAB.experiments(sort=\"experimentID\")\n",
    "experiments.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The available fields for the experiments can be listed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['studyID',\n",
       " 'projectID',\n",
       " 'groupID',\n",
       " 'subgroupID',\n",
       " 'userID',\n",
       " 'workflowStepID',\n",
       " 'name',\n",
       " 'description',\n",
       " 'notes',\n",
       " 'created',\n",
       " 'statusChanged',\n",
       " 'dependencyExperimentID',\n",
       " 'due',\n",
       " 'deleted',\n",
       " 'template',\n",
       " 'experimentStatus.experimentStatusID',\n",
       " 'experimentStatus.groupID',\n",
       " 'experimentStatus.color',\n",
       " 'experimentStatus.status',\n",
       " 'experimentStatus.experimentStatusType']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiments.fields()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A method is available to browse the experiments, optionally restricting the output to a set of fields and defining a custom page size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "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>name</th>\n",
       "      <th>studyID</th>\n",
       "      <th>projectID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>experimentID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>373184</td>\n",
       "      <td>Testexperiment</td>\n",
       "      <td>74113</td>\n",
       "      <td>22534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>389036</td>\n",
       "      <td>labjournal</td>\n",
       "      <td>74113</td>\n",
       "      <td>22534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>417242</td>\n",
       "      <td>Arduino</td>\n",
       "      <td>74113</td>\n",
       "      <td>22534</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        name  studyID  projectID\n",
       "experimentID                                    \n",
       "373184        Testexperiment    74113      22534\n",
       "389036            labjournal    74113      22534\n",
       "417242               Arduino    74113      22534"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#experiments.show(fields=[\"name\",\"studyID\",\"projectID\"], size=3)\n",
    "experiments.all(fields=[\"name\",\"studyID\",\"projectID\"], maximum=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single experiment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get only the first experiment of the (usually filtered) set, the `experiments.first()` method can be used. This results in an **experiment object** describing the experiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       " -->\n",
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       "<g id=\"clust1\" class=\"cluster\">\n",
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       "<g id=\"a_clust1\"><a xlink:title=\"experiment\">\n",
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       "<g id=\"clust2\" class=\"cluster\">\n",
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       "<g id=\"clust12\" class=\"cluster\">\n",
       "<title>cluster_section_8</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"70,-160 70,-212 394,-212 394,-160 70,-160\"/>\n",
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       "<g id=\"clust14\" class=\"cluster\">\n",
       "<title>cluster_section_10</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"62,-16 62,-68 400,-68 400,-16 62,-16\"/>\n",
       "</g>\n",
       "<!-- experiment_name -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>experiment_name</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"330.0987,-780 227.9013,-780 227.9013,-744 330.0987,-744 330.0987,-780\"/>\n",
       "<text text-anchor=\"middle\" x=\"279\" y=\"-757.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Testexperiment</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_1 -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>section_1</title>\n",
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       "<text text-anchor=\"middle\" x=\"279\" y=\"-685.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">1.</text>\n",
       "</g>\n",
       "<!-- experiment_name&#45;&gt;section_1 -->\n",
       "<g id=\"edge6\" class=\"edge\">\n",
       "<title>experiment_name&#45;&gt;section_1</title>\n",
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       "</g>\n",
       "<!-- study_name -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>study_name</title>\n",
       "<g id=\"a_node2\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"440.9654,-780 371.0346,-780 371.0346,-744 440.9654,-744 440.9654,-780\"/>\n",
       "<text text-anchor=\"middle\" x=\"406\" y=\"-757.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Teststudy</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- study_name&#45;&gt;experiment_name -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>study_name&#45;&gt;experiment_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M371.0138,-762C360.7847,-762 350.5557,-762 340.3267,-762\"/>\n",
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       "<!-- project_name -->\n",
       "<g id=\"node3\" class=\"node\">\n",
       "<title>project_name</title>\n",
       "<g id=\"a_node3\"><a xlink:title=\"name of experiment\">\n",
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       "<text text-anchor=\"middle\" x=\"518\" y=\"-757.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">testproject</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- project_name&#45;&gt;study_name -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>project_name&#45;&gt;study_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M480.7031,-762C470.8807,-762 461.0583,-762 451.236,-762\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"451,-758.5001 441,-762 451,-765.5001 451,-758.5001\"/>\n",
       "</g>\n",
       "<!-- section_1_name -->\n",
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       "<title>section_1_name</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"415.5995,-708 324.4005,-708 324.4005,-672 415.5995,-672 415.5995,-708\"/>\n",
       "<text text-anchor=\"middle\" x=\"370\" y=\"-685.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Text example</text>\n",
       "</g>\n",
       "<!-- section_1&#45;&gt;section_1_name -->\n",
       "<g id=\"edge5\" class=\"edge\">\n",
       "<title>section_1&#45;&gt;section_1_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M306.0156,-690C312.0142,-690 318.0127,-690 324.0112,-690\"/>\n",
       "</g>\n",
       "<!-- section_2 -->\n",
       "<g id=\"node9\" class=\"node\">\n",
       "<title>section_2</title>\n",
       "<ellipse fill=\"#ffffff\" stroke=\"#000000\" cx=\"279\" cy=\"-618\" rx=\"27\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"279\" y=\"-613.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">2.</text>\n",
       "</g>\n",
       "<!-- section_1&#45;&gt;section_2 -->\n",
       "<g id=\"edge10\" class=\"edge\">\n",
       "<title>section_1&#45;&gt;section_2</title>\n",
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       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"282.5001,-646.4132 279,-636.4133 275.5001,-646.4133 282.5001,-646.4132\"/>\n",
       "</g>\n",
       "<!-- section_1_type -->\n",
       "<g id=\"node6\" class=\"node\">\n",
       "<title>section_1_type</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"233.5158,-708 134.4842,-708 134.4842,-672 233.5158,-672 233.5158,-708\"/>\n",
       "<text text-anchor=\"middle\" x=\"184\" y=\"-685.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">PARAGRAPH</text>\n",
       "</g>\n",
       "<!-- section_1_type&#45;&gt;section_1 -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>section_1_type&#45;&gt;section_1</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M233.7266,-690C239.7394,-690 245.7523,-690 251.7652,-690\"/>\n",
       "</g>\n",
       "<!-- section_1_id -->\n",
       "<g id=\"node7\" class=\"node\">\n",
       "<title>section_1_id</title>\n",
       "<text text-anchor=\"middle\" x=\"70\" y=\"-692.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">expJournalID</text>\n",
       "<text text-anchor=\"middle\" x=\"70\" y=\"-678.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">3847613</text>\n",
       "</g>\n",
       "<!-- section_1_id&#45;&gt;section_1_type -->\n",
       "<!-- section_2_name -->\n",
       "<g id=\"node8\" class=\"node\">\n",
       "<title>section_2_name</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"444.0565,-636 323.9435,-636 323.9435,-600 444.0565,-600 444.0565,-636\"/>\n",
       "<text text-anchor=\"middle\" x=\"384\" y=\"-613.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Datatable example</text>\n",
       "</g>\n",
       "<!-- section_2&#45;&gt;section_2_name -->\n",
       "<g id=\"edge9\" class=\"edge\">\n",
       "<title>section_2&#45;&gt;section_2_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M306.0703,-618C311.9556,-618 317.8409,-618 323.7263,-618\"/>\n",
       "</g>\n",
       "<!-- section_3 -->\n",
       "<g id=\"node13\" class=\"node\">\n",
       "<title>section_3</title>\n",
       "<ellipse fill=\"#ffffff\" stroke=\"#000000\" cx=\"279\" cy=\"-546\" rx=\"27\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"279\" y=\"-541.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">3.</text>\n",
       "</g>\n",
       "<!-- section_2&#45;&gt;section_3 -->\n",
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       "<title>section_2&#45;&gt;section_3</title>\n",
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       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"234.1549,-636 139.8451,-636 139.8451,-600 234.1549,-600 234.1549,-636\"/>\n",
       "<text text-anchor=\"middle\" x=\"187\" y=\"-613.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">DATATABLE</text>\n",
       "</g>\n",
       "<!-- section_2_type&#45;&gt;section_2 -->\n",
       "<g id=\"edge8\" class=\"edge\">\n",
       "<title>section_2_type&#45;&gt;section_2</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M234.4375,-618C240.2399,-618 246.0423,-618 251.8447,-618\"/>\n",
       "</g>\n",
       "<!-- section_2_id -->\n",
       "<g id=\"node11\" class=\"node\">\n",
       "<title>section_2_id</title>\n",
       "<text text-anchor=\"middle\" x=\"76\" y=\"-620.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">expJournalID</text>\n",
       "<text text-anchor=\"middle\" x=\"76\" y=\"-606.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">3847643</text>\n",
       "</g>\n",
       "<!-- section_2_id&#45;&gt;section_2_type -->\n",
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       "</g>\n",
       "<!-- section_3&#45;&gt;section_3_name -->\n",
       "<g id=\"edge13\" class=\"edge\">\n",
       "<title>section_3&#45;&gt;section_3_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M306.0703,-546C311.9708,-546 317.8713,-546 323.7718,-546\"/>\n",
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       "<text text-anchor=\"middle\" x=\"279\" y=\"-469.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">4.</text>\n",
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       "<title>section_3&#45;&gt;section_4</title>\n",
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       "<title>section_3_type</title>\n",
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       "<text text-anchor=\"middle\" x=\"198\" y=\"-541.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">CANVAS</text>\n",
       "</g>\n",
       "<!-- section_3_type&#45;&gt;section_3 -->\n",
       "<g id=\"edge12\" class=\"edge\">\n",
       "<title>section_3_type&#45;&gt;section_3</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M234.0703,-546C240.0375,-546 246.0048,-546 251.972,-546\"/>\n",
       "</g>\n",
       "<!-- section_3_id -->\n",
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       "<title>samples</title>\n",
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       "<!-- section_10_type&#45;&gt;section_10 -->\n",
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       "<title>section_10_type&#45;&gt;section_10</title>\n",
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       "</g>\n",
       "<!-- section_10_id -->\n",
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       "<title>section_10_id</title>\n",
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       "</g>\n",
       "<!-- section_10_id&#45;&gt;section_10_type -->\n",
       "<!-- storage -->\n",
       "<g id=\"node46\" class=\"node\">\n",
       "<title>storage</title>\n",
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       "<text text-anchor=\"middle\" x=\"653\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Storage</text>\n",
       "</g>\n",
       "<!-- storage&#45;&gt;samples -->\n",
       "<g id=\"edge44\" class=\"edge\">\n",
       "<title>storage&#45;&gt;samples</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M638.6165,-95.8314C630.0417,-85 619.186,-71.2876 610.5772,-60.4133\"/>\n",
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       "<graphviz.dot.Digraph at 0x1254b8c18>"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Experiment 'Testexperiment' (373184)\n",
       "|\n",
       "|  Available methods, use help() on this object for more detailed information:\n",
       "|\n",
       "|  add(data, title, order)\n",
       "|    Add a new section to this experiment.\n",
       "|  data()\n",
       "|    Get data.\n",
       "|  id()\n",
       "|    Get id.\n",
       "|  name()\n",
       "|    Get the name.\n",
       "|  section(id)\n",
       "|    Get within this experiment the section object with provided id.\n",
       "|  sections(*args, **kwargs)\n",
       "|    Get object to access sections.\n",
       "|  show()\n",
       "|    Show the content of this experiment.\n",
       "|  title()\n",
       "|    Get the title.\n",
       "|  visualize()\n",
       "|    Show visualization."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "firstExperiment = experiments.first()\n",
    "display(firstExperiment.visualize())\n",
    "firstExperiment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is also possible to get an experiment directly by id."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "373184\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"Experiment 'Testexperiment' (373184)\""
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "firstExperimentID = firstExperiment.id()\n",
    "print(firstExperimentID)\n",
    "experiment = eLAB.experiment(firstExperimentID)\n",
    "experiment.title()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sections"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From an **experiment object**, we can get an object describing all sections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<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>order</th>\n",
       "      <th>sectionHeader</th>\n",
       "      <th>sectionType</th>\n",
       "      <th>lastEditUserFirstName</th>\n",
       "      <th>lastEditUserLastName</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>expJournalID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3847613</td>\n",
       "      <td>1</td>\n",
       "      <td>Text example</td>\n",
       "      <td>PARAGRAPH</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3847643</td>\n",
       "      <td>2</td>\n",
       "      <td>Datatable example</td>\n",
       "      <td>DATATABLE</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3847679</td>\n",
       "      <td>3</td>\n",
       "      <td>Canvas example</td>\n",
       "      <td>CANVAS</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3848414</td>\n",
       "      <td>4</td>\n",
       "      <td>Excel section</td>\n",
       "      <td>EXCEL</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3899288</td>\n",
       "      <td>5</td>\n",
       "      <td>nieuw</td>\n",
       "      <td>PARAGRAPH</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3985199</td>\n",
       "      <td>6</td>\n",
       "      <td>Specimen &amp; Materials</td>\n",
       "      <td>SAMPLESIN</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4001258</td>\n",
       "      <td>7</td>\n",
       "      <td>ttt</td>\n",
       "      <td>PROCEDURE</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4004282</td>\n",
       "      <td>8</td>\n",
       "      <td>file</td>\n",
       "      <td>FILE</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4005431</td>\n",
       "      <td>9</td>\n",
       "      <td>Output Samples</td>\n",
       "      <td>SAMPLESOUT</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4007636</td>\n",
       "      <td>10</td>\n",
       "      <td>Plaatjes</td>\n",
       "      <td>IMAGE</td>\n",
       "      <td>Matthijs</td>\n",
       "      <td>Brouwer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              order         sectionHeader sectionType lastEditUserFirstName  \\\n",
       "expJournalID                                                                  \n",
       "3847613           1          Text example   PARAGRAPH              Matthijs   \n",
       "3847643           2     Datatable example   DATATABLE              Matthijs   \n",
       "3847679           3        Canvas example      CANVAS              Matthijs   \n",
       "3848414           4         Excel section       EXCEL              Matthijs   \n",
       "3899288           5                 nieuw   PARAGRAPH              Matthijs   \n",
       "3985199           6  Specimen & Materials   SAMPLESIN              Matthijs   \n",
       "4001258           7                   ttt   PROCEDURE              Matthijs   \n",
       "4004282           8                  file        FILE              Matthijs   \n",
       "4005431           9        Output Samples  SAMPLESOUT              Matthijs   \n",
       "4007636          10              Plaatjes       IMAGE              Matthijs   \n",
       "\n",
       "             lastEditUserLastName  \n",
       "expJournalID                       \n",
       "3847613                   Brouwer  \n",
       "3847643                   Brouwer  \n",
       "3847679                   Brouwer  \n",
       "3848414                   Brouwer  \n",
       "3899288                   Brouwer  \n",
       "3985199                   Brouwer  \n",
       "4001258                   Brouwer  \n",
       "4004282                   Brouwer  \n",
       "4005431                   Brouwer  \n",
       "4007636                   Brouwer  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sections = experiment.sections()\n",
    "allSections = sections.all([\"order\", \"sectionHeader\", \"sectionType\", \"lastEditUserFirstName\", \"lastEditUserLastName\"])\n",
    "allSections"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen from this list, there are multiple *sectionTypes*. For each of these types, we get the first id."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "paragraphSectionId = allSections[allSections[\"sectionType\"]==\"PARAGRAPH\"].index[0]\n",
    "procedureSectionId = allSections[allSections[\"sectionType\"]==\"PROCEDURE\"].index[0]\n",
    "imageSectionId = allSections[allSections[\"sectionType\"]==\"IMAGE\"].index[0]\n",
    "fileSectionId = allSections[allSections[\"sectionType\"]==\"FILE\"].index[0]\n",
    "datatableSectionId = allSections[allSections[\"sectionType\"]==\"DATATABLE\"].index[0]\n",
    "canvasSectionId = allSections[allSections[\"sectionType\"]==\"CANVAS\"].index[0]\n",
    "excelSectionId = allSections[allSections[\"sectionType\"]==\"EXCEL\"].index[0]\n",
    "samplesInSectionId = allSections[allSections[\"sectionType\"]==\"SAMPLESIN\"].index[0]\n",
    "samplesOutSectionId = allSections[allSections[\"sectionType\"]==\"SAMPLESOUT\"].index[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype FILE\n",
    "A **section object** can be of type 'IMAGE'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "<!-- section_type -->\n",
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   "source": [
    "sectionFile = eLAB.section(fileSectionId)\n",
    "sectionFile.visualize()"
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   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
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    "## Sectiontype IMAGE\n",
    "A **section object** can be of type 'IMAGE'"
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  {
   "cell_type": "code",
   "execution_count": 14,
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    "scrolled": false
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       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x1254b8da0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionImage = eLAB.section(imageSectionId)\n",
    "sectionImage.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img title=\"eendje.jpg\" 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\"><figcaption>eendje.jpg</figcaption></figure><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img title=\"eendje.jpg\" 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\"><figcaption>eendje.jpg</figcaption></figure></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionImage.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype PARAGRAPH\n",
    "A **section object** can be of type 'PARAGRAPH'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"544pt\" height=\"178pt\"\n",
       " viewBox=\"0.00 0.00 544.00 178.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 174)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-174 540,-174 540,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_section</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"section\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"14,-88 14,-162 158,-162 158,-88 14,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"86\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">expJournalID 3847613</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust2\" class=\"cluster\">\n",
       "<title>cluster_experiment</title>\n",
       "<g id=\"a_clust2\"><a xlink:title=\"experiment\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"166,-88 166,-162 305,-162 305,-88 166,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"235.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">experimentID 373184</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust3\" class=\"cluster\">\n",
       "<title>cluster_study</title>\n",
       "<g id=\"a_clust3\"><a xlink:title=\"study\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"313,-88 313,-162 412,-162 412,-88 313,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"362.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">studyID 74113</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust4\" class=\"cluster\">\n",
       "<title>cluster_project</title>\n",
       "<g id=\"a_clust4\"><a xlink:title=\"project\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"420,-88 420,-162 528,-162 528,-88 420,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"474\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">projectID 22534</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust5\" class=\"cluster\">\n",
       "<title>cluster_content</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" stroke-dasharray=\"5,2\" points=\"8,-8 8,-76 140,-76 140,-8 8,-8\"/>\n",
       "</g>\n",
       "<g id=\"clust6\" class=\"cluster\">\n",
       "<title>cluster_sectiontype</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"16,-16 16,-68 132,-68 132,-16 16,-16\"/>\n",
       "</g>\n",
       "<!-- section_name -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>section_name</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"title of section\">\n",
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       "<text text-anchor=\"middle\" x=\"74\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Text example</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_type -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>section_type</title>\n",
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       "</g>\n",
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       "<title>section_name&#45;&gt;section_type</title>\n",
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       "<g id=\"node2\" class=\"node\">\n",
       "<title>experiment_name</title>\n",
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       "</g>\n",
       "<!-- experiment_name&#45;&gt;section_name -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>experiment_name&#45;&gt;section_name</title>\n",
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       "<g id=\"node3\" class=\"node\">\n",
       "<title>study_name</title>\n",
       "<g id=\"a_node3\"><a xlink:title=\"name of experiment\">\n",
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       "<!-- study_name&#45;&gt;experiment_name -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>study_name&#45;&gt;experiment_name</title>\n",
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       "<g id=\"node4\" class=\"node\">\n",
       "<title>project_name</title>\n",
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       "<!-- project_name&#45;&gt;study_name -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>project_name&#45;&gt;study_name</title>\n",
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     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionParagraph = eLAB.section(paragraphSectionId)\n",
    "sectionParagraph.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we can view its content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"border: 1px solid #067172; padding: 10px;\"><p>This is a <strong>text</strong> with <u>markup</u>!<br>\n",
       "And a list</p>\n",
       "\n",
       "<ol>\n",
       "\t<li>one</li>\n",
       "\t<li>two</li>\n",
       "\t<li>three...</li>\n",
       "</ol>\n",
       "Testing character encoding: α β γ<br>\n",
       "<a href=\"/members/experiments/browser/#view=experiment&amp;nodeID=389036\">labjournal</a><br>\n",
       "<br>\n",
       "<br>\n",
       "&nbsp;</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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     "execution_count": 17,
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   "source": [
    "sectionParagraph.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype PROCEDURE\n",
    "A **section object** can be of type 'PROCEDURE'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "<title>metas</title>\n",
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       "<title>study_name&#45;&gt;experiment_name</title>\n",
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionProcedure = eLAB.section(procedureSectionId)\n",
    "sectionProcedure.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we can view its content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "<div style=\"border: 1px solid #067172; padding: 10px;\"><div class=\"pageSectionBody\"><h2>qPCR (Copy)</h2><div class=\"step\" data-stepid=\"469673\"><div class=\"stepHeader\"><div class=\"stepTitle\"><h6>Mastermix</h6><i class=\"fa fa-pencil addEditIcon editStepNameIcon\" style=\"display: none;\"></i><span class=\"stepNameEditor\" style=\"display:none;\"><span><span></span></span><i class=\"btnSaveStepName addEditIcon fa fa-save\" style=\"color:#666; margin-left:5px; font-size: .8em;\"></i></span></div><div class=\"stepMenu\"><ul><li class=\"btnEditSave\" style=\"display: none;\"><i class=\"fa fa-pencil\"></i></li><li class=\"btnMoveStep\" style=\"display: none;\"><i class=\"fa fa-arrows-alt move\" title=\"Move step by drag and drop\"></i></li><li class=\"btnRemoveStep warning\" style=\"display: none;\"><i class=\"fa fa-trash-o removeStep\" title=\"Remove step\"></i></li></ul></div></div><div class=\"stepBody\"><div class=\"stepContents\">Number of mixes needed&nbsp;<span class=\"protVar protVar_240578\" data-varid=\"240578\" data-varname=\"Field5\" title=\"number of sample 2\"><span>10</span></span><br>\n",
       "<br>\n",
       "Syber green &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240581\" data-varid=\"240581\" data-varname=\"Field7\" title=\"\"><span>100</span>&nbsp;<span class=\"protVarUnit\">µl</span></span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<br>\n",
       "25mM Forward primer &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240584\" data-varid=\"240584\" data-varname=\"Field8\" title=\"\"><span>4</span>&nbsp;<span class=\"protVarUnit\">µl</span></span><br>\n",
       "25mM Reverse primer &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp;<span class=\"protVar protVar_240590\" data-varid=\"240590\" data-varname=\"Field10\" title=\"\"><span>4</span>&nbsp;<span class=\"protVarUnit\">µl</span></span><br>\n",
       "dH2O &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240593\" data-varid=\"240593\" data-varname=\"Field11\" title=\"\"><span>42</span>&nbsp;<span class=\"protVarUnit\">µl</span></span>&nbsp; &nbsp;&nbsp;<br>\n",
       "Add 5µl template, (1/5 diluted cDNA)</div><div style=\"clear: both;\"></div></div></div><div class=\"step\" data-stepid=\"469676\"><div class=\"stepHeader\"><div class=\"stepTitle\"><h6>Programme</h6><i class=\"fa fa-pencil addEditIcon editStepNameIcon\" style=\"display: none;\"></i><span class=\"stepNameEditor\" style=\"display:none;\"><span><span></span></span><i class=\"btnSaveStepName addEditIcon fa fa-save\" style=\"color:#666; margin-left:5px; font-size: .8em;\"></i></span></div><div class=\"stepMenu\"><ul><li class=\"btnEditSave\" style=\"display: none;\"><i class=\"fa fa-pencil\"></i></li><li class=\"btnMoveStep\" style=\"display: none;\"><i class=\"fa fa-arrows-alt move\" title=\"Move step by drag and drop\"></i></li><li class=\"btnRemoveStep warning\" style=\"display: none;\"><i class=\"fa fa-trash-o removeStep\" title=\"Remove step\"></i></li></ul></div></div><div class=\"stepBody\"><div class=\"stepContents\"><table width=\"307\" cellspacing=\"0\" cellpadding=\"0\" border=\"0\">\n",
       "\t<tbody>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td width=\"136\" height=\"20\">initial denaturation</td>\n",
       "\t\t\t<td width=\"64\">95<font>°C</font></td>\n",
       "\t\t\t<td width=\"64\">3 min</td>\n",
       "\t\t\t<td width=\"43\">&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">denaturation</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">anealing</td>\n",
       "\t\t\t<td>X°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>40x</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">elongation</td>\n",
       "\t\t\t<td>72°C</td>\n",
       "\t\t\t<td>30 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">final elongation</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">meltcurve65</td>\n",
       "\t\t\t<td>65°C</td>\n",
       "\t\t\t<td>5 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>0.5°C</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t</tbody>\n",
       "</table>\n",
       "<br>\n",
       "Anealing temperature is primer dependent.<br>\n",
       "&nbsp;</div><div style=\"clear: both;\"></div></div></div></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionProcedure.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype DATATABLE\n",
    "A **section object** can be of type 'DATATABLE'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 174)\">\n",
       "<title>%3</title>\n",
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       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_section</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"section\">\n",
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       "<text text-anchor=\"middle\" x=\"80\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">expJournalID 3847643</text>\n",
       "</a>\n",
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       "</g>\n",
       "<g id=\"clust2\" class=\"cluster\">\n",
       "<title>cluster_experiment</title>\n",
       "<g id=\"a_clust2\"><a xlink:title=\"experiment\">\n",
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       "</a>\n",
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       "</g>\n",
       "<g id=\"clust4\" class=\"cluster\">\n",
       "<title>cluster_project</title>\n",
       "<g id=\"a_clust4\"><a xlink:title=\"project\">\n",
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       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust5\" class=\"cluster\">\n",
       "<title>cluster_content</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" stroke-dasharray=\"5,2\" points=\"17,-8 17,-76 143,-76 143,-8 17,-8\"/>\n",
       "</g>\n",
       "<g id=\"clust6\" class=\"cluster\">\n",
       "<title>cluster_sectiontype</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"25,-16 25,-68 135,-68 135,-16 25,-16\"/>\n",
       "</g>\n",
       "<!-- section_name -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>section_name</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"title of section\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"140.0565,-132 19.9435,-132 19.9435,-96 140.0565,-96 140.0565,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Datatable example</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_type -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>section_type</title>\n",
       "<g id=\"a_node5\"><a xlink:title=\"type of section\">\n",
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       "<text text-anchor=\"middle\" x=\"80\" y=\"-37.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">DATATABLE</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_name&#45;&gt;section_type -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>section_name&#45;&gt;section_type</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M80,-95.8314C80,-88.131 80,-78.9743 80,-70.4166\"/>\n",
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       "</g>\n",
       "<!-- experiment_name -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>experiment_name</title>\n",
       "<g id=\"a_node2\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"280.0987,-132 177.9013,-132 177.9013,-96 280.0987,-96 280.0987,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"229\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Testexperiment</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- experiment_name&#45;&gt;section_name -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>experiment_name&#45;&gt;section_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M177.6858,-114C168.6169,-114 159.5481,-114 150.4792,-114\"/>\n",
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       "</g>\n",
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       "<g id=\"node3\" class=\"node\">\n",
       "<title>study_name</title>\n",
       "<g id=\"a_node3\"><a xlink:title=\"name of experiment\">\n",
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       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- study_name&#45;&gt;experiment_name -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>study_name&#45;&gt;experiment_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M321.0138,-114C310.7847,-114 300.5557,-114 290.3267,-114\"/>\n",
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       "<g id=\"node4\" class=\"node\">\n",
       "<title>project_name</title>\n",
       "<g id=\"a_node4\"><a xlink:title=\"name of experiment\">\n",
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       "<text text-anchor=\"middle\" x=\"468\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">testproject</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- project_name&#45;&gt;study_name -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>project_name&#45;&gt;study_name</title>\n",
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       "<graphviz.dot.Digraph at 0x1254ea978>"
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     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionDatatable = eLAB.section(datatableSectionId)\n",
    "sectionDatatable.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can get the data from this section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "    .dataframe tbody tr th {\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Sample 1</td>\n",
       "      <td>1.34</td>\n",
       "      <td>23.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Sample 2</td>\n",
       "      <td>2.54</td>\n",
       "      <td>53.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sample 3</td>\n",
       "      <td>3.45</td>\n",
       "      <td>33.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Sample 4</td>\n",
       "      <td>2.55</td>\n",
       "      <td>34.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Sample 5</td>\n",
       "      <td>1.59</td>\n",
       "      <td>32.9</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0     1     2  3\n",
       "0  Sample 1  1.34  23.3   \n",
       "1  Sample 2  2.54  53.1   \n",
       "2  Sample 3  3.45  33.8   \n",
       "3  Sample 4  2.55  34.2   \n",
       "4  Sample 5  1.59  32.9   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sectionDatatable_data = sectionDatatable.get()\n",
    "display(sectionDatatable_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The do further analysis within python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "#make numeric if possible\n",
    "sectionDatatable_adjusted = sectionDatatable_data.apply(pd.to_numeric, errors='coerce').combine_first(sectionDatatable_data)\n",
    "#add column with average\n",
    "sectionDatatable_adjusted[3] = sectionDatatable_adjusted.loc[:,1:2].mean(axis=1)\n",
    "#create plot\n",
    "sectionDatatable_plot = sectionDatatable_adjusted.set_index([0]).plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Results can be stored again in eLABJournal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "      <th>0</th>\n",
       "      <th>1</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Sample 1</td>\n",
       "      <td>1.34</td>\n",
       "      <td>23.3</td>\n",
       "      <td>12.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Sample 2</td>\n",
       "      <td>2.54</td>\n",
       "      <td>53.1</td>\n",
       "      <td>27.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Sample 3</td>\n",
       "      <td>3.45</td>\n",
       "      <td>33.8</td>\n",
       "      <td>18.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Sample 4</td>\n",
       "      <td>2.55</td>\n",
       "      <td>34.2</td>\n",
       "      <td>18.375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Sample 5</td>\n",
       "      <td>1.59</td>\n",
       "      <td>32.9</td>\n",
       "      <td>17.245</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0     1     2       3\n",
       "0  Sample 1  1.34  23.3   12.32\n",
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       "2  Sample 3  3.45  33.8  18.625\n",
       "3  Sample 4  2.55  34.2  18.375\n",
       "4  Sample 5  1.59  32.9  17.245"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set adjusted data\n",
    "sectionDatatable.set(sectionDatatable_adjusted)\n",
    "#show new data in section2\n",
    "display(sectionDatatable.get())\n",
    "#return to original data\n",
    "sectionDatatable.set(sectionDatatable_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype CANVAS\n",
    "A **section object** can be of type 'CANVAS'\n",
    "\n",
    "For example a generated plot can be added as a drawing on a CANVAS section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"538pt\" height=\"178pt\"\n",
       " viewBox=\"0.00 0.00 538.00 178.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 174)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-174 534,-174 534,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_section</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"section\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-88 8,-162 152,-162 152,-88 8,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">expJournalID 3847679</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust2\" class=\"cluster\">\n",
       "<title>cluster_experiment</title>\n",
       "<g id=\"a_clust2\"><a xlink:title=\"experiment\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"160,-88 160,-162 299,-162 299,-88 160,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"229.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">experimentID 373184</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust3\" class=\"cluster\">\n",
       "<title>cluster_study</title>\n",
       "<g id=\"a_clust3\"><a xlink:title=\"study\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"307,-88 307,-162 406,-162 406,-88 307,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"356.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">studyID 74113</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust4\" class=\"cluster\">\n",
       "<title>cluster_project</title>\n",
       "<g id=\"a_clust4\"><a xlink:title=\"project\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"414,-88 414,-162 522,-162 522,-88 414,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"468\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">projectID 22534</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust5\" class=\"cluster\">\n",
       "<title>cluster_content</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" stroke-dasharray=\"5,2\" points=\"28,-8 28,-76 132,-76 132,-8 28,-8\"/>\n",
       "</g>\n",
       "<g id=\"clust6\" class=\"cluster\">\n",
       "<title>cluster_sectiontype</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"36,-16 36,-68 124,-68 124,-16 36,-16\"/>\n",
       "</g>\n",
       "<!-- section_name -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>section_name</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"title of section\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"134.1348,-132 25.8652,-132 25.8652,-96 134.1348,-96 134.1348,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Canvas example</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_type -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>section_type</title>\n",
       "<g id=\"a_node5\"><a xlink:title=\"type of section\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"115.7611,-60 44.2389,-60 44.2389,-24 115.7611,-24 115.7611,-60\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-37.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">CANVAS</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_name&#45;&gt;section_type -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>section_name&#45;&gt;section_type</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M80,-95.8314C80,-88.131 80,-78.9743 80,-70.4166\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"83.5001,-70.4132 80,-60.4133 76.5001,-70.4133 83.5001,-70.4132\"/>\n",
       "</g>\n",
       "<!-- experiment_name -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>experiment_name</title>\n",
       "<g id=\"a_node2\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"280.0987,-132 177.9013,-132 177.9013,-96 280.0987,-96 280.0987,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"229\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Testexperiment</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- experiment_name&#45;&gt;section_name -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>experiment_name&#45;&gt;section_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M177.8586,-114C166.6984,-114 155.5382,-114 144.378,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"144.1289,-110.5001 134.1289,-114 144.1289,-117.5001 144.1289,-110.5001\"/>\n",
       "</g>\n",
       "<!-- study_name -->\n",
       "<g id=\"node3\" class=\"node\">\n",
       "<title>study_name</title>\n",
       "<g id=\"a_node3\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"390.9654,-132 321.0346,-132 321.0346,-96 390.9654,-96 390.9654,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"356\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Teststudy</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- study_name&#45;&gt;experiment_name -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>study_name&#45;&gt;experiment_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M321.0138,-114C310.7847,-114 300.5557,-114 290.3267,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"290.0977,-110.5001 280.0977,-114 290.0976,-117.5001 290.0977,-110.5001\"/>\n",
       "</g>\n",
       "<!-- project_name -->\n",
       "<g id=\"node4\" class=\"node\">\n",
       "<title>project_name</title>\n",
       "<g id=\"a_node4\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"505.3112,-132 430.6888,-132 430.6888,-96 505.3112,-96 505.3112,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"468\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">testproject</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- project_name&#45;&gt;study_name -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>project_name&#45;&gt;study_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M430.7031,-114C420.8807,-114 411.0583,-114 401.236,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"401,-110.5001 391,-114 401,-117.5001 401,-110.5001\"/>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x1256f8be0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionCanvas = eLAB.section(canvasSectionId)\n",
    "sectionCanvas.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set from figure\n",
    "sectionCanvas.set(sectionDatatable_plot.get_figure())\n",
    "#get from eLABJournal\n",
    "sectionCanvas_image = sectionCanvas.get()\n",
    "#show\n",
    "display(sectionCanvas.show())\n",
    "#set from png\n",
    "sectionCanvas.set(sectionCanvas_image)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype EXCEL\n",
    "A section object can be of type 'EXCEL'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"538pt\" height=\"178pt\"\n",
       " viewBox=\"0.00 0.00 538.00 178.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 174)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-174 534,-174 534,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_section</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"section\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-88 8,-162 152,-162 152,-88 8,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">expJournalID 3848414</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust2\" class=\"cluster\">\n",
       "<title>cluster_experiment</title>\n",
       "<g id=\"a_clust2\"><a xlink:title=\"experiment\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"160,-88 160,-162 299,-162 299,-88 160,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"229.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">experimentID 373184</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust3\" class=\"cluster\">\n",
       "<title>cluster_study</title>\n",
       "<g id=\"a_clust3\"><a xlink:title=\"study\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"307,-88 307,-162 406,-162 406,-88 307,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"356.5\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">studyID 74113</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust4\" class=\"cluster\">\n",
       "<title>cluster_project</title>\n",
       "<g id=\"a_clust4\"><a xlink:title=\"project\">\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"414,-88 414,-162 522,-162 522,-88 414,-88\"/>\n",
       "<text text-anchor=\"middle\" x=\"468\" y=\"-146.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">projectID 22534</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<g id=\"clust5\" class=\"cluster\">\n",
       "<title>cluster_content</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" stroke-dasharray=\"5,2\" points=\"33,-8 33,-76 127,-76 127,-8 33,-8\"/>\n",
       "</g>\n",
       "<g id=\"clust6\" class=\"cluster\">\n",
       "<title>cluster_sectiontype</title>\n",
       "<polygon fill=\"#eeeeee\" stroke=\"#000000\" points=\"41,-16 41,-68 119,-68 119,-16 41,-16\"/>\n",
       "</g>\n",
       "<!-- section_name -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>section_name</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"title of section\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"125.5244,-132 34.4756,-132 34.4756,-96 125.5244,-96 125.5244,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Excel section</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_type -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>section_type</title>\n",
       "<g id=\"a_node5\"><a xlink:title=\"type of section\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"110.6036,-60 49.3964,-60 49.3964,-24 110.6036,-24 110.6036,-60\"/>\n",
       "<text text-anchor=\"middle\" x=\"80\" y=\"-37.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">EXCEL</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- section_name&#45;&gt;section_type -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>section_name&#45;&gt;section_type</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M80,-95.8314C80,-88.131 80,-78.9743 80,-70.4166\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"83.5001,-70.4132 80,-60.4133 76.5001,-70.4133 83.5001,-70.4132\"/>\n",
       "</g>\n",
       "<!-- experiment_name -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>experiment_name</title>\n",
       "<g id=\"a_node2\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"280.0987,-132 177.9013,-132 177.9013,-96 280.0987,-96 280.0987,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"229\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Testexperiment</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- experiment_name&#45;&gt;section_name -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>experiment_name&#45;&gt;section_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M177.7483,-114C163.7846,-114 149.8209,-114 135.8572,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"135.6895,-110.5001 125.6895,-114 135.6894,-117.5001 135.6895,-110.5001\"/>\n",
       "</g>\n",
       "<!-- study_name -->\n",
       "<g id=\"node3\" class=\"node\">\n",
       "<title>study_name</title>\n",
       "<g id=\"a_node3\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"390.9654,-132 321.0346,-132 321.0346,-96 390.9654,-96 390.9654,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"356\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Teststudy</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- study_name&#45;&gt;experiment_name -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>study_name&#45;&gt;experiment_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M321.0138,-114C310.7847,-114 300.5557,-114 290.3267,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"290.0977,-110.5001 280.0977,-114 290.0976,-117.5001 290.0977,-110.5001\"/>\n",
       "</g>\n",
       "<!-- project_name -->\n",
       "<g id=\"node4\" class=\"node\">\n",
       "<title>project_name</title>\n",
       "<g id=\"a_node4\"><a xlink:title=\"name of experiment\">\n",
       "<polygon fill=\"#ffffff\" stroke=\"#000000\" points=\"505.3112,-132 430.6888,-132 430.6888,-96 505.3112,-96 505.3112,-132\"/>\n",
       "<text text-anchor=\"middle\" x=\"468\" y=\"-109.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">testproject</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- project_name&#45;&gt;study_name -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>project_name&#45;&gt;study_name</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M430.7031,-114C420.8807,-114 411.0583,-114 401.236,-114\"/>\n",
       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"401,-110.5001 391,-114 401,-117.5001 401,-110.5001\"/>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.dot.Digraph at 0x1256f8470>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionExcel = eLAB.section(excelSectionId)\n",
    "sectionExcel.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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+996Nf3X0xtADvws98DuFWoVhGIZhT548gReTk5PLli07d+6c0Wj08fH5wx/+AMO7uroeP35MChkaGhodHV26dOlHH30EA//t3/7Nx8cHrsbt6urCfgUep0MMwTDsr/7qr44dO4Zh2MjIyNKlSw8dOgTD+/v7fXx8/uVf/gXa/Pa3v/3ll18wDPvzn/8MAOjo6MAwbOfOnX//93+PYdhf//VfP/vssxiG/Z//838AADCG1atX4/kcHBwEAHz99dcwtg0bNsDY/uVf/gUAcO7cue+//35kZASKAAD44YcfMAwbGhqaN2/eN998Q1vAkZGRv/qrvwoODn78+DGxONTIoaSrVq0qKiqCNuvWrRscHITFnD9//h//+EeiFLR1YU09u8nt3LkTvpg2Go379u1bsGABVG/79u3bt28nxnb+/PkFCxZAHUj5/Pnnn728vKACMJ+268t2ndKKjN9I9bqhoSFaTYhpffPNN8HBwV5eXq+++iqu0ltvvfXb3/4WLyBtDFSz1atXFxcXw2qlZmZgYMBawW24HK0Dk9IludOPP/7IYrHq6uowDBsfH1+yZMlHH3304MEDAMDdu3ex/8orr7yyYcMGDMPeeeed3/zmNzDQrjEpRSgmXju//8M/hB74Hfynx48f45k5d+6cj4/PypUr4T9t3ry5uLiYWBf4xejo6JIlS3Cv/uMf/4hr4nGEHvjd7//wD7TNkImb0fqADX2s+SqxymzcDquAmltrXZmNqIjd7MaNG6Hr2mjCePZsdBGYzcZC2z0+VYyMjHz//feY9SqwpjNmpdFhGPbo0SMAwJ///Gfs1/b+xz/+0ZnKoj4TrXmm3YeIteLgOjj03MSsd4m0XkHb6J4qcB2sPaapLm1NHPyJ859/bmCYutu+mPb391er1bdu3YIz5FqttrW11Wg0btu2DRqEhIQolUpSiK+vr1Kp7O/vV6vVFRUVFRUVbW1tRqNxYmJi5cqVO3bs+PLLL+Evp5CQEFIIEYVC0d/fn56eDv8UiUSJiYn476TU1FQ+nw8AgFPWpE/ATp48ee/evevXrzMsaUpKCoxNLBYDAPBEwa/n6sJPTc1ms8Vi4XK5tAWEP9Go701oI2ez2VFRUfgCsm3btsGpPpFIFBsbS/3ZRK0La+oxSe6LL74QCAS+vr43btyoqalhft4Xns+goKCNGzcS82m7vmzb0IqM30X1OvjOgqoJMa34+HiFQnHq1Kna2lqxWAzne+yqalcBamb6+vrsFpyKbQfGIbpTWFhYQkLC5cuXAQC3bt0yGAw7duyA0lGbz8TEBPVlDRNjqgMTawdHKBTGx8fX1tYCAOrr6/fv39/Z2dne3q7X6xsaGohfTRHp7OwcGBjA/xUuGPBobHdiEGtuRvUBG/rY8FW8yuzKS82tta6MSU2dPHny/v378NpGE8azx6SLoMVu9/j0YE03G48MQNfoAAARERG//e1vr1y5AgC4ffu2wWCIiYlxprKoz0RrTmX3IWK7OMDx5yZg3CUCZo3uKcFaVqkubU0c0hOHCW4bMhYWFkZHR5eXl9+8eRN+fmUymQAAsF4h1BAAAPS83t5epVKpVCr1en1xcfEzzzxz7969+Pj4HTt2xMbG9vX1eXt7k0KokRDfmfL5fPgmlAhcCkN6nq1fvz49Pb20tNTR3VWoT9mAgIB169alpqbu378/MTExMTFRLBbTFnD58uUAAPiZBZPIORwOrbv7+vrC931EqHVhWz3byb3wwguNjY3d3d1KpRJfK8PhcEjymkwmLy8va8Xx9fUlvndmUl/WbGhFJmYDUHyMVhMSXC4XLv3x9fU9ceIE1cBuDFSomWHoqNagdWAckjtlZGTU1NSYTKYrV65s3bpVIBBAr+vu7ibdqFQqw8LIJ8UzMaY6MF47/f3/5ROZ1NRUuKDz9u3bu3fv3rhxY21t7ZdffhkQELBx40ba4kCRqVXpudhthoCBm+E+YEMfG5HgVWZXXmpurXVlTGpq/fr1+LI5G00Yz56TLQVC2z0+PVjTzcYjA1h/aqSnp1dXV09MTFy7dm3r1q2w4FOuLOoz0a5nWnuI2C4OcPy5ScR2lwiYNbqnBCZZhS5tTRxrjz8buGddp1wuP3369MOHD2HLj4+PB78+cpRKJfzugTYED8zMzIR34fD5/Pfff//w4cPx8fHl5eXHjx8XCoWkENw4JCQEAKBQKPCfX3K5PDExkWH+jx8/HhERAadkIDweD28VzPup1tbW7u7u6upqmUwG11iw2WxrBZwy0C0g7e3tpCcubV0AAGyoZxtfX1/4pQKRkJCQO3fujI2N4QvSW1paYC3Q5lOhUBDzyaS+rNnQiozfRetj1jShEhAQEBsbi8+w4uNm2zEQR/M8Hm9oaMhaZmwUfAouZ/tHc1paWl5eXnV1dU1NzSeffAIAEAqFq1evrqqq2r17N27W0tLy3Xff7d+/n3S7Q8Y4eO0U/d9yMD6Kh6ekpBQXF1dVVUF32rJlS21tLdzYyNojUCQSAQA6OzuhaI4OF55OaJshQzcjYU0fhpEwkZeUW/hxA7UrY1hT+O4ttpswxHYXYaOx2O4enyqs6Ta1R8auXbsKCwu//PLLmpqajz/+2FokDCuL9Ex0yDNJWMsJPokwXc9Na14x5WffzEObVapLWxMHf+IwT9E9s4zwBw2srevXr8P3ehEREb/5zW+kUqlGo9HpdKWlpcPDw6SQlpaWsLCwTZs2SaVSnU4HADAYDLW1ta2trbdv3wYAcLlcb29vX19faggxA+Hh4XFxcSUlJX19fWNjY2fPnpXJZNnZ2Qzzv3z58oKCAuI3YmKxuLq6WqPRdHd3p6WlsVgsJvFwOBy4RlWr1SqVSji9TFtAhhmj5f3336+urobF7O7uJr1ZoK0L2+pNgdzcXL1en5WV1dvbq9frP/7448uXL//DP/wDKZ/Xrl2bmJg4e/asSqUi5pNJfVmzoRUZv4vqdS0tLbSa4Fy5ckUqlSqVSrPZfPPmzfr6ejgdIhQKVSqVTqfTarU2YiCaAQDEYjH+GQc1MwaDwVrBHXU5UrpUfH1909LSCgsLORwOvkL88OHD//Ef/5GXlwe/uqivr9+6dWtcXBz+OTMRh4wheO2QfvdHRkauXr0afoINANi6deudO3e++OKLlJQUa1GFhob+5je/OXHihF6vV6lU27ZtY9gMn1pomyFDN6NiTR+GkdiVl5pba10Zw5oKCgqCF7abMMR2F2GjsdjuHp8qrOk2tUeGSCRKSkoqKCiwWCxbtmxxsrJIz0SHPJOE3eJM13OT1ium/dnnOqxllerS1sTBnzjME3XPkDEmJiYnJycpKSkoKOjs2bOJiYlsNpvNZldVVanV6sDAwICAgKamprCwMFJIaGgoAKCqqspisQiFwoCAAJFIBP/csWOHv78/DMnLy6OGAABgKjAPVVVVAIDly5fzeLyTJ0/euHEjIiKCZMNms1ksFvyTGA4AKC0tjYiI8PPzg39KpVI2my0SicRicW5urq+vL/UuPASPJCgoKCQkhMPhjI2NKRSKrKwsuLCDWkBqBmxHTvyn1NTU0tJSLpdbUlJSUVERFRVFNKCtC7vqWUuOmklIWFjYjRs3mpubg4ODFy1adPjw4YqKCuI0IZvNLiwslEql3t7eBw8e/PDDD0n5ZFJftDbWRGb/CtXHaDXBbxGLxfX19atWrVqwYEFaWtr+/fv37t0Lfl1BEhAQkJycbC0Gkhn0HLwLps2MtYIzdDncgUnp0tZUZmbmwMDAjh078Mng3bt3X7x48YsvvggODl64cGFKSkpycvLNmzfhSyVSJA4Zwz/x2sEwjJSZbdu2/fzzz3DIGBMTIxQKx8bG8L0haF3u0qVLbW1t/v7+MTEx+/fvDwgIsDYl6RHQNkMmbmbNB2j1seGrpCqzJi80o80tbVdmNyqSDrabMG5mraUA640FWOken1qs6WZNZ9pGh/+5Z8+ejo6OXbt2wfbuZGURn4kMPRPQPURs5ATi0HOTmijeHGi9gtaNn06sZZXWpa0NKuATBwBw685dJv+xVCrVzBTvhXPZAIAviypXBa6AIcPDw8PDwyKRaGJiglipWq2WzWb7+/vj91JDAAAmk0mr1QqFQrgU2mKx9Pb28vl8fDkLNWRsbIzD4RC93GQy6XS6oKAgPJBkYzabYfxwFoS4/AJuIkMM0Wg0fD6fy+Xib2BpY2trawsPD+dyuUeOHKmvr8c3u75y5Up2dja+ywOpgNTMW8sqMbcxMTFpaWmlpaW9vb0BAQE8Ho/2Xmpd2FWPNjmqSiQMBsPExASsSlwHGLm3tzdM1EY+7dYX1caayKQbqT5G1YR4i16vHx4eJuYEuoRGo/H394e1b83DSWZKpZLP5xOXqFMzQy04hKHLUdOl6gZzEhERAdfHkCpOo9GYzWaRSETcDtNisUxMTFA3yKQ1JqUI/zx69CisneRT2Y/UXT+d+r/EeEwmE+4JExMTFosFjxCPjRTtxMSEWq0OCAggauJxPFP4+9WiFTcLK6nNEDBwM9tNlVYfWl+lOgnt7bgZbW4BpSuzERWxA9FoNAaDITw8nGETxtOibSmArrFY6x6fKsxms1KpjI6Ohn/a8HCqzrSNjtRbcrlcUsgUKgtCeiY66pmk2Eg5wXVw6LlJLTUxUUDnFdbc+CmB6A/UrNp2adrKBQDcunMXMMOde1T6+vrCqVTSCIO4qsxaCACAx+MRF8Ox2WzS2jhqCPX5wePxSJqSbHBlqcMg6g9i/KmPR2ItNgifz1coFDdu3IiMjOzr6ztz5szWrVutFZCaeRuRk3JrVwpqXdi9hTY5u7ueWltpCyO3m6jd+qLaWBOZdCPVx6iaEG8RCATUDgX+ZrURA60ZFWpmqAWHOORyxHRpx1KVlZXh4eG0i4Fotzhms9m08dAakyzhn3jtjI7SfHZALDJJQ2vl5XA4+Jp3Dx0vEqG2CMDAzWw3VVp9aH2VKiDt7fgFbW4BpSuzERVtB8KwCeNpWRv5URuL7Ww/ndjwcKrOtI2OdAs1ZMqVRXomOuqZTHICHHxu2k4U0HmFB/mDtaw61BIhiQnPMknx6d3WfC6Qn59vsVhOnDih0+lEIlFqampBQcH0JhEZGYkvCZqbzIDIs4a2trbCwsKZTBGvncdr54OFHj/CQ7gC1zVh1D16IqhLt4GrXdqdL6bnLMQXsnMZpAOE+mJ6DkL7YnrOgr+YdndG3An+YtrdGXEzpBfTcxakA8QVOty6c5fpLOMMHyj+dcu3o8FDM5ni04lDn7XPYpAOELPZrNFo3J0Ld2I2jwIAnin8vbsz8rRgNo/CQ63mOEgECNIBgnSAuEsHzvr162coqf8AAICgpUvRr0alUrlixQobG1nPEZAOkJ6eHh8fH9LXXXONWbDucHrx9vae412lTqczGo3BwcHuzoibGR8f7+rqmuPOAJAOvzI+Pq5Wq1etWjWNcTrw+Qu+TYyr+fjVf2592Pr8mlju/Ln+IhIA4OXlhV7IAqQDAAAAFovF4XDmuA4fv3a0o1Pp6+s7x4fOAACdTjc8PLwqbK6v2eBwOCwWa46LgIN0gCAd3MvMff7y17+Jt/QN+cxfMGMpIhAITyFk8dKxQSNa0wkA0LAWGLwMIYuXujsjCAQC8V/w4H1uEQgEAoFAIBAzAxoyIhAIBALhLBaLBd9QGoGYlbh/yKhWqxsbG9va2vBDZs1mc29vb29vL+kwXDwcQvzC1GKxtLa23rt3j9RiacMdMoZMTEy0tbWRDja1YT8FkA4eh16vv3fvnlwuJ52PPAVhIVqttpeCXq/XarUkHzCZTPj2WLg/qNVq6tm7iKcWhg1neHi4qamptbWV5GZUUlJSKioqpjWPMwfDzFP7yZmEtgPEKS8vJ+4pPTXs6jBH/IEIbUGY62AtBsRUwBgzOjra2NhYW1v7/fffM7+LyJdffkn88+HDh5s3b2axWIsXL/by8vLz8zt27BiGYa+++iqevaVLl3700UfQnhgOAFixYgUM7+joWL169aJFiwIDA318fK5evWoj3CFjyHfffbdu3ToAQEdHBx5ow94u33///cjICNKBpINnUVRUNH/+/GXLls2bN2/t2rWPHz+G4VMQtqOjA96+evVqagvduXPn9u3bt2/fTkz9/PnzPj4+8JroD4GBge+9994MFN8V4DrMBWz4w+PHj/Em9tlnn/n5+QUGBi5cuDA4OLinp8dGnH/1V38Fuw5PhJp5og6Y9X5yxqDtAHEmJydXrlx58eJFJ1Oh6jAyMoI/c+eOPxCBBZmyDtgskgLDsJGREYVCMb1x/uefGxhaOjDLeOLEiR9++AEAcOXKlUuXLjG/kRaZTCaRSLy9vVUqlVarNZlM1dXVcKshk8n08ssvYxg2ODiYkZGRk5MDT5M0mUwvvfTS+K/gO0qmp6eHhISo1eq+vr6srKzMzEydTmct3CFjAEBlZWVycrJEIiHl35o90mFqOngcXC5XqVT29vbK5XKlUnnq1CkY7qiwRGQy2cjIyMjIyIYNG3JycuD15cuXbecE95OhoaGCgoJ9+/bdvn3bBSVGTCdM/MFsNmdmZh48eFCtVut0upMnT1LPTZ4j2OgnZwZrHSBOU1OTSqVKTU11XR6QP0CQDu6E+Ti0t7cXXmi12oyMDLPZ7MAgFsOw/zrL+Pzzz69du3ZycpJqtnPnTvgIxDBscnLSz8/v0KFDpHAcOIr95ptv4J+PHz8GAFy9epU2/MyZM8yN4e/+urq6gYGB+/fvA8KPSxv2TCDOriEdGBo/zaxdu/aVV17BHKwF4gQkaXYtLi7u9ddfx/+0PctI8hMvL69333132ss4A8ydWUbb/oDPrnV0dAAAvvrqK2oMjx49Onbs2L59+86fPz86OgoDiVMpg4OD58+fP3DgwDvvvIM32E8//fTRo0fffvttcXHxuXPnhoaGYPjFixcfPHgAr0dHR0+fPg0rAtrfvXu3qKjo3Llz8DfMBx98cOjQofv371NzxdD++++/P3ToUFFRUV1dHR5IzDwsXU5ODp5zG/0knu7nn39eVFQEJ5xo9bFRzB9//PH+/fvFxcVvv/02rRPSdoBE3nzzzU2bNjmkA60UpPmwR48evfXWW3B2zeP8AccZQTDKLKOjOhClcK8O04K1WUZnWp9LZhmXLVsGLxYuXIhhmDNLSfr6+r7++uvCwkK7Pw4sFovFYhEIBNYM2tvbWSxWbGws/FMoFAYGBioUCtrw5uZm5sYKhQIAkJSUFBAQwDBRh0QASIdZQVNTU3t7e3JyMnCwFlwhlEwmGx8fj4qKmvaYEdMIQ38IDQ1dunTpwYMHSWd0Xb9+PSYmBq7iKisrk0gkZrOZdK9EIqmtreXxeA0NDdHR0TCGU6dOZWdn79q1S6fTlZWVbdmyBRofP368vr4eXptMpgMHDsDMQPuMjAydTldSUrJnz56EhIT6+vp79+5JJJLW1lZSokzsq6urJRKJwWDgcrk7duzAp+eppZucnIQhdvtJmO7+/fvlcnlnZ6c1fWwUMzc3Ny0tzWAwXLhw4bnnnqOuLqXtAIk0NTWJxWLmOjCXQiaTwT89zh9IFeS8IJ6ug0uZltZnl6nsy3j37t2wsDAfH58p3Atpb28HAMAHm8VikUqlcEFxUFBQfn4+bmYymaRS6cTEREpKCgy5desWfrTi2bNnExMTNRoNj8fjcP5fQQQCgV6vpw0fGBhgbqzX663l31F7pMPsQ6PRZGZm6vX6lpaWo0ePpqenA+uCuFqo1tbW3NxcnU5XX1+/b98+59fgI1wKQ3/gcDg1NTU7duyIjIxMT08/cuRISEiI2Wzeu3dvYWHh0aNHAQClpaXh4eGVlZXEHgMA0NDQADdFt1gsISEhtbW1eXl5AIDh4eHW1lY+n5+enr5582alUmn7OA2TydTc3Mzn88Vi8RtvvHHu3Lm8vDyLxRIZGVlVVRUTE+OQfVRUVH5+Pny2AQDWr1+fnp6el5eH789MLB08Yxow6yc7Ozubm5uFQqHZbA4LC7OrDwmtVtva2ioQCNRqdWhoaFVVVW5urg17KkqlMjExkbluY2NjtFLgMeBSlJaWwoNVPdEfnBcE943R0VF44dE6uBQnWx8THB4yfvvtt//xH/9RWFjo6I1U8CPCzGbz2NiYTCaTy+Wwgr/44guBQGAwGMLCwmpqavDKi46Ohg4BAIC1MjY2RoqWzWbzeDza8Hnz5jE35vF41nLuqL1tkA6eCOxcDAZDaGjo4cOH+Xz+3r17HaqFaRSKx+OJRCKFQsHlcjMzM6crWoSLYO4P8fHxCoWisrLy+PHjNTU1d+7cAQD09/fDnygAAJFIlJiY2NjYSHo0+vv7q9VquVyu0+l4PB7+xX1qaiqfzwe/9hu9vb22H40pKSnQHk6hwXTZbHZUVJRarXbUXqlU9vf3q9Vq+PmqVqs1Go2dnZ34vLhCoSCWjoiNfhIAkJWVBTeBJ8VgTR8S27Ztg+9wRCJRbGxsS0uLDWNaDAYDLDgTHQAA1qTAY6CVwuP8wXlBcN/o6OjABzeeq4NLcbL1McGBIaPFYrl27dpPP/30P//n/1y0aJFjRfmvwMpobm4Wi8VsNhsurSsvLz9y5Ag0eOGFF8rLy319fZcvX068USgUJiUlEUMEAoHJZBobG8M7FK1WKxQKacM3bNjA3NjGKRSO2iMdZh9cLnfXrl0AgOzsbIFAUFBQkJGR4VAtMBeKw+GQpqBMJhPxUOaIiAjoM8nJyVlZWY2Njc4WD+FKHPIHLpebn5+/e/fumJiYEydOZGVlwRhwAz6fT32RWlhY+MknnyQkJPj7+9POZ8Okma8vIs6Jwj9t7+hEaw+f0L29vXiGi4uLiZ0bNCCtwLHbTwIA8HfW1Bho9bGBr68vdUxvFw6HQ3uXNd2mJgXwWH+we6NdQZ48eYKvjgOer4NLmVrrYxQzc9NLly5hGHbw4EHqHJWjhISExMXFlZWV7d69m3ZS1NfXNzIykklUkZGRGIa1tLTEx8cDAFQq1cDAQFRUFJ/Pp4bHx8dfunSJobGNobe1RJEOU9PB04mOjh4fHzeZTA7VAnOhQkJC7ty5QxxhtLS00P4IPnz48LPPPtvY2AgTQjydTKHhBAQExMbGqtXqkJAQAIBCocCHmHK5nPhKFIacPn364cOHcLLBrjPweDz88Tk8PDzFUjEAPp8yMzOtZYlaOsCgn7QdA66PjWKaTCb8ur29fePGjY4VDICAgACHNotgLgW+5pWU3CzwByJ2BQkODqaOxmafDq7DrsJMYPr5y8DAQHNz8549e5wfL0I+/PBDjUYTHx9/+/Ztg8HQ2dnZ1NRk9y64gzGkr68PALB+/frVq1cfOXJEq9UaDIaCgoI1a9YkJCTQhr/22mvMjRMSEgAAZrNZq9VCv9HpdFqt1mKx2LBHOkxNB8+iu7tbKpXCzbQVCsXZs2c3bdoUEBDgUC0wFyo3N1ev12dlZcGdvT/++OPLly+XlpZSLSUSyZo1a9CmtU85DP3hypUrUqlUqVSazeabN2/W19enpaWFh4fHxcWVlJT09fWNjY2dPXtWJpPBxUk4cLoLttbr16/j309YQywWV1dXazSa7u7utLQ0Fos1naUlEBYWtmnTJqlUCkdXBoOhtraWaEAqHR7OvJ+0oY+NYr7//vvV1dXQvru7G75AIELbARINoqKi5HK5K6To7++HIbPPH4jYFSQsLAxezG4dXIddhZnAdMio0WiGh4f/8R//MftX/uM//sPRxIisX7++sbFRJBIlJSX5+fmtXLmyoaGhpKQEAMBms2m/jPP396+rq3vmV+D0G5vNvnbtmkqlWrJkiUAg6O7urqmp4XA4tOHe3t7MjeHUbmlp6ZIlS1588UUAQFxc3JIlS1paWmzYIx2mpoNnIRAImpubw8PDORxOZGRkaGjolStXgIO1YEMoUtWHhYXduHGjubk5ODh40aJFhw8frqiowHeAIxlnZ2dfu3aN+qkg4umBoT+IxeL6+vpVq1YtWLAgLS1t//79e/fuBQBUVVUBAJYvX87j8U6ePHnjxo2IiAhA8ISYmJicnJykpKSgoCD4eRwMJ7oKm81msVjwT6lUymazRSKRWCzOzc319fWltQeE97+0vRMT+6qqKovFIhQKAwICRCIRLAvJAJYuNDQUj9lGP0nNjDV9rBUTAJCamlpaWsrlcktKSioqKqgzvrQdINFAIpHgo1iGutFKQTIAAKxcudJD/QHHGUGokTuqAx6D23VwKc60PgdwfFegqUM6/QUyMjLS1dX15MkTPATuUO1o5P39/bT7adGGO2Q8hURtQ7sfIdLB4zAajV1dXcTdv3AcEpa6H+Ho6CjtFnS//PIL0UMgVD/xUFXnzr6MOLT+QDr1ZHBwsKenh+oPRqORFE5ym6Ghof7+fgzDxsfHYTjJgOQnjx8/hiG4S9uwp+2dmNvDtkM0IN1rNBofPHhA3QGR2k9S78VjoNWNWky4ad/k5GRXV5fRaMSmxE8//QQAgBsHOqQbSQpqWXQ6HfHENQ/yB2s5cUgQ/Hbi6S8O6UDKgBt1mBas7cvoTOtjvi8jC8Ow6Rrk2qWurg7+SpvjtLW1hYeHO/Rl+6wE6QBRKpV8Pn+OfDZkA6QDBG4uY/uDzbnAjOkQExOTlpYmlUqdjCc5ORl+ijEtucIxm81KpRLfVW3OgnSAmM3mnp6eVatWTWOct+7cTUx4loklOmYHgUAgEHOXyMjIoKAg5+M5evQoWhCCmN3M/mVnCAQCgUBYAy5Edp6NGzdO4VNrBMKDYMEVGDNDV1fX4sWLZyw5BAKBQCAQiNkEi8Ui7svrPD39GoYvpjnTMiHPELuH8MwRlErlihUrvLy83J0RN4N0gPT09Pj4+MBjrOYySAeITqczGo3BwcHuzoibQTpAxsfHu7q60KMT6QAZHx9Xq9XTu5axp1/D0JIzvWNV22AYhr51gHh5eSEpANIBAAAAi8XicDhIB6QDhMPhsFgspAPSgQjSAYJ0cC/o8xcEAoFAIBAIhB3QkBGBQCAQCAQCYQc0ZEQgEAgEwlksFovBYHB3LhAIF+L+TXbUarVKpfL19Y2MjIRHZsHTPAEAXC43ICAAt8TDId7e3viuvxaLRSaTmUym6OhoPp+P29CGO2QMADAYDG1tbf7+/hEREcSzgKzZIx3mCHq9Xi6XCwSCiIgI4mlvjgqLo9Vqqfu6+fr6TkxMAACIPmAymTQaDTxRDfcHDocjFArddVwVwlEYNpzh4WG5XO7t7R0dHW37NM6UlJQtW7bk5ua6ILMuh2Hmqf3kTDIxMdHe3h4VFUXbysrLy6urq+/cueNMEnZ1mCP+QAQWJCMjgxjIXAcwi6RwP8yPqXny5MmtW7dqa2uphzgxhHRg4MOHDzdv3sxisRYvXuzl5eXn53fs2DEMw1599VU8e0uXLv3oo4+gPTEcALBixQoY3tHRsXr16kWLFgUGBvr4+Fy9etVGuEPGGIYVFxd7eXnNnz8fALBu3bqff/7Ztj0TSAflIR08kaKiovnz5y9btmzevHlr167Fj31zVFiMcFDe6tWrqS10586d27dv3759OzH18+fP+/j4wGuiPwQGBr733nszUHxXMKcODLThD8QDAz/77DM/P7/AwMCFCxcGBwf39PTYiBMefOfafLsMauZJByda6ydnjO+++27dunUAANon4OTk5MqVKy9evOhkKlQdiAflzR1/IAILMmUdsFkkBWb9wEBnYH5goAMTEp988oler5+YmCgvL6+vr2d+Iy0ymUwikXh7e6tUKq1WazKZqqur29raAAAmk+nll1/GMGxwcDAjIyMnJ6ehoQGGv/TSS+O/0tnZCaNKT08PCQlRq9V9fX1ZWVmZmZk6nc5auEPGAIDh4eHm5maz2fz111+3tbUdP37cdqJIh6np4HFwuVylUtnb2yuXy5VK5alTp2C4o8ISkclkIyMjIyMjGzZsyMnJgdeXL1+2nRPcT4aGhgoKCvbt23f79m0XlBgxnTDxB7PZnJmZefDgQbVardPpTp48OWenkG30kzNDZWVlcnKyRCKxZtDU1KRSqVJTU12XB+QPEKSDO2E+DsVPvL5//75UKnVgBPsrxFnG559/fu3atdQzxTEM27lzJ3wEwkT9/PwOHTpECsf54YcfAADffPMN/PPx48cAgKtXr9KGnzlzhrkxdcJsw4YNf/3Xf20jUYY6EGfXkA4MjZ9m1q5d+8orr2AO1gJxApI0uxYXF/f666/jf9qeZST5iZeX17vvvjvtZZwB5s4so21/wGfXOjo6AABfffUVNYZHjx4dO3Zs375958+fHx0dhYHEqZTBwcHz588fOHDgnXfewWfFPv3000ePHn377bfFxcXnzp0bGhqC4RcvXnzw4AG8Hh0dPX36NKwIaH/37t2ioqJz587B3zAffPDBoUOH7t+/T80VQ/vvv//+0KFDRUVFdXV1eCAx87B0OTk5eM5t9JN4up9//nlRURGccKLVx0Yxf/zxx/v37xcXF7/99tu0TlhXVzcwMHD//n1gZZbxzTff3LRpk0M60EpBmg979OjRW2+9BWfXPM4fcJwRBKPMMjqqA1EK9+owLVibZXSm9blklhEfyE9OTvr6+k51jAoAAH19fV9//XVhYaHdHwcWi8VisQgEAmsG7e3tLBYrNjYW/ikUCgMDAxUKBW14c3Mzc2OFQkHKSW9vb1hYmI1EkQ5T08GjaWpqam9vT05OBg7WgiuEkslk4+PjUVFR0x4zYhph6A+hoaFLly49ePAg/iYBcv369ZiYmNbW1omJibKyMolEQl0CK5FIamtreTxeQ0NDdHQ0jOHUqVPZ2dm7du3S6XRlZWVbtmyBxsePH8dfHJlMpgMHDsDMQPuMjAydTldSUrJnz56EhIT6+vp79+5JJJLW1lZSokzsq6urJRKJwWDgcrk7duzAp+eppZucnIQhdvtJmO7+/fvlcnlnZ6c1fWwUMzc3Ny0tzWAwXLhw4bnnnqN+xZKUlERcTEylqalJLBYz14G5FDKZDP7pcf5AqiDnBfF0HVzKtLQ+uziwfHhoaOjHH398/PhxU1PTnj17HE2JSHt7OwAAPtgsFotUKrVYLACAoKCg/Px83MxkMkml0omJiZSUFBhy69at6OhoeH327NnExESNRsPj8YirXwUCgV6vpw0fGBhgbqzX64l5rqmpUavVmZmZAAAm9kiH2Y1Go8nMzNTr9S0tLUePHk1PTwfWBXG1UK2trbm5uTqdrr6+ft++fVu3bp2umBGugKE/cDicmpqaHTt2REZGpqenHzlyJCQkxGw27927t7Cw8OjRowCA0tLS8PDwyspKYo8BAGhoaIDn6FgslpCQkNra2ry8PADA8PBwa2srn89PT0/fvHmz3RO5TCZTc3Mzn88Xi8VvvPHGuXPn8vLyLBZLZGRkVVVVTEyMQ/ZRUVH5+fnw2QYAWL9+fXp6el5eHr4/M7F0Go0GDt2Y9JOdnZ3Nzc1CodBsNoeFhdnVh4RWq21tbRUIBGq1OjQ0tKqqytFPJZRKZWJiInPdxsbGaKXAY8ClKC0tVSqVwDP9wXlBcN8YHR2FFx6tg0txsvUxwYEho8FgaGxsHBwc9Pb2Hh8fd7g0FPCDZ8xm89jYmEwmk8vlsIK/+OILgUBgMBjCwsJqamrwyouOjoYOAQCAtTI2NkaKls1m83g82vB58+YxN+bxePifarU6Pz8/Pz8/Pj7eRqLMy04E6eCJwM7FYDCEhoYePnyYz+fv3bvXoVqYRqF4PJ5IJFIoFFwuF47mEU8zzP0hPj5eoVBUVlYeP368pqYGfo3b398Pf6IAAEQiUWJiYmNjI+nR6O/vr1ar5XK5Tqfj8Xj4Hgupqanw62zYb/T29tp+NKakpEB7OIUG02Wz2VFRUWq12lF7pVLZ39+vVqsrKioAAFqt1mg0dnZ24vPiCoWCWDoiNvpJAEBWVhbcOIIUgzV9SGzbtg2+wxGJRLGxsS0tLTaMaTEYDMTP3u3qZk0KPAZaKTzOH5wXBPeNjo4OfHDjuTq4FCdbHxMcGDIuW7YM/vBSKBRnzpw5c+bMlI/ugZXR3NwsFovZbDZcWldeXn7kyBFo8MILL5SXl/v6+i5fvpx4o1AoTEpKIoYIBAKTyTQ2NoZ3KFqtVigU0oZv2LCBuTG+c43BYNi6dWtUVNTJkydtJ4p0mJoOngiXy921axcAIDs7WyAQFBQUZGRkOFQLzIXicDikKSiTyUQ86jMiIgL6THJyclZWVmNjo7PFQ7gSh/yBy+Xm5+fv3r07JibmxIkTWVlZMAbcgM/nU1+kFhYWfvLJJwkJCf7+/rTz2TBpuH8TE0j7mHA4HDjV55A9fEL39vbiGS4uLiZ2btCAtALHbj8JCOumqDHQ6mMDX19f6pjeLhwOh/Yua7pNTQrgsf5g90a7gjx58mTZsmX4n56ug0uZWutjFPMUchMRETE5OanX60Ui0RRuBwCEhITExcWVlZXt3r2bdtwJt91iElVkZCSGYS0tLXDeS6VSDQwMREVF8fl8anh8fPylS5cYGsOht8lk2rp1q7e39/Xr1/H+3VqiSIep6eDpREdHj4+Pm0wmh2qBuVAhISF37twhjjBaWlpofwQfPnz42WefbWxshAkhnk6m0HACAgJiY2PVanVISAgAQKFQ4ENMuVxOfCUKQ06fPv3w4UM42WDXGXg8Hv74HB4enmKpGACfT5mZmdayRC0dYNBP2o4B18dGMU0mE37d3t6+ceNGxwoGQEBAgEObRTCXAl/zSkpuFvgDEbuCBAcHU0djs08H12FXYSYw/fzFYDAMDAzA65aWlgULFjg5mfThhx9qNJr4+Pjbt28bDIbOzs6mpia7d5lMJtWv9PX1AQDWr1+/evXqI0eOaLVag8FQUFCwZs2ahIQE2vDXXnuNuXFCQoLFYklLS1OpVGfPnoXzukql0mKxWLNHOkxZB8+iu7tbKpWqVCoAgEKhOHv27KZNmwICAhyqBeZC5ebm6vX6rKys3t5evV7/8ccfX758ubS0lGopkUjWrFkD3zsgnloY+sOVK1ekUqlSqTSbzTdv3qyvr09LSwsPD4+LiyspKenr6xsbGzt79qxMJoOLk3DgdBd82l2/fh3/fsIaYrG4urpao9F0d3enpaWxWKzpLC2BsLCwTZs2SaVSOLoyGAy1tbVEA1Lp8HDm/aQNfWwU8/3336+urob23d3d8AUCEbhhPpRUp9NptVrS8CUqKkoul7tCiv7+fhgy+/yBiF1B4DeXYLbr4DrsKswEpkPGkZGRsrIyqVRaWlpaU1NTUFDg5E5I69evb2xsFIlESUlJfn5+K1eubGhoKCkpAQCw2WzayP39/evq6p75FTj9xmazr127plKplixZIhAIuru7a2pqOBwObbi3tzdzYw6Ho9Ppvvzyy56eng0bNqz6lba2Nmv2SIcp6+BZCASC5ubm8PBwDocTGRkZGhp65coV4GAt2BCKVPVhYWE3btxobm4ODg5etGjR4cOHKyoq8B3gSMbZ2dnXrl2jfiqIeHpg6A9isbi+vn7VqlULFixIS0vbv3//3r17AQBVVVUAgOXLl/N4vJMnT964cSMiIgIQPCEmJiYnJycpKSkoKAh+HgfDia7CZrNZLBb8UyqVstlskUgkFotzc3N9fX1p7QHh/S9t78TEvqqqymKxCIXCgIAAkUgEy0IygKWDhxtBbPST1MxY08daMQEAqamppaWlXC63pKSkoqKCOuNbWlq6ZMmSF198EQAQFxe3ZMkS0npHiUSCj2IZ6kYrBckAALBy5UoP9QccZwShRu6oDngMbtfBpTjT+hyA+W5AExMTT548MRgMzG8hQTr9BTIyMtLV1fXkyRM8BO5Q7Wjk/f39tPtp0YY7ZDyFRG1Dux8h0sHjMBqNXV1dxN2/cBwSlrof4ejoKO0WdL/88gvRQyBUP/FQVefOvow4tP5AOvVkcHCwp6eH6g9Go5EUTnKboaGh/v5+DMPGx8dhOMmA5CePHz+GIbhL27Cn7Z2Y28O2QzQg3Ws0Gh88eEDdAZHaT1LvxWOg1Y1aTLhp3+TkZFdXl9FoxKbETz/9BACAGwc6pBtJCmpZdDodfuoJ5lH+YC0nDgmC3048/cUhHUgZcKMO04K1fRmdaX3M92VkYRg2XYNcu9TV1cFfaXOctra28PDwKX88NGtAOkCUSiWfz58jnw3ZAOkAgZvL2P5gcy4wYzrExMSkpaVJpVIn40lOToafYkxLrnDMZrNSqcR3VZuzIB0gZrO5p6dn1apV0xjnrTt3ExOeZWKJjtlBIBAIxNwlMjIyKCjI+XiOHj2KFoQgZjezf9kZAoFAIBDWgAuRnWfjxo1T+NQagfAgWHAFxszQ1dW1ePHiGUsOgUAgEAgEYjbBYrGI+/I6T0+/huGLac60TMgzxO4hPHMEpVK5YsUKLy8vd2fEzSAdID09PT4+PvAYq7kM0gGi0+mMRmNwcLC7M+JmkA6Q8fHxrq4u9OhEOkDGx8fVavX0rmXs6dcwtORM71jVNhiGoW8dIF5eXkgKgHQAAADAYrE4HA7SAekA4XA4LBYL6YB0IIJ0gCAd3Av6/AWBQCAQCAQCYQc0ZEQgEAgEAoFA2AENGREIBAKBcBaLxWIwGNydCwTChbh/kx21Wq1SqXx9fSMjI+GRWfA0TwAAl8sNCAjALfFwiLe3N77rr8VikclkJpMpOjqaz+fjNrThDhkDAPR6vVwuFwgEERERxEO9rNkjHeYIjgpiVyitVkvd183X13diYgIAQPQBk8mk0WjgiWq4P3A4HKFQ6K7jqhCOwrDhDA8Py+Vyb2/v6Oho26dxpqSkbNmyJTc31wWZdTkMM0/tJ2eSiYmJ9vb2qKgo2lZWXl5eXV19584dZ5Kwq8Mc8QcisCAZGRnEQOY6gFkkhftx8KwaDMMwhULR3d09hRtJBwY+fPhw8+bNLBZr8eLFXl5efn5+x44dwzDs1VdfxbO3dOnSjz76CNoTwwEAK1asgOEdHR2rV69etGhRYGCgj4/P1atXbYQ7ZIxhWFFR0fz585ctWzZv3ry1a9fip3tZs2cC6aA8pIMn4qggNoTCD8pbvXo1tYXu3Llz+/bt27dvJ6Z+/vx5Hx8feE30h8DAwPfee28Giu8K5tSBgTb8gXhg4Geffebn5xcYGLhw4cLg4OCenh4bccKD71ybb5dBzTzp4ERr/eSM8d13361btw4AQD3GEMOwycnJlStXXrx40clUqDoQD8qbO/5ABBZkyjpgs0gKzPqBgc7A/MBAhyck9Hr9H/7wh7t37zp6IwmZTCaRSLy9vVUqlVarNZlM1dXVbW1tAACTyfTyyy9jGDY4OJiRkZGTk9PQ0ADDX3rppfFf6ezshFGlp6eHhISo1eq+vr6srKzMzEydTmct3CFjAACXy1Uqlb29vXK5XKlUnjp1ynaiSIep6eBxOCoIE6FkMtnIyMjIyMiGDRtycnLg9eXLl23nBPeToaGhgoKCffv23b592wUlRkwnTPzBbDZnZmYePHhQrVbrdLqTJ0/O2SlkG/3kzFBZWZmcnCyRSKwZNDU1qVSq1NRU1+UB+QME6eBOHB2NVlZWlpSUfPbZZ47eiP3XWcbnn39+7dq11DPFMQzbuXMnfARiGDY5Oenn53fo0CFSOM4PP/wAAPjmm2/gn48fPwYAXL16lTb8zJkzzI2pE2Zr16595ZVXbCTKUAfi7BrSgaHx04xdQWwLRZ1di4uLe/311/E/bc8ykvzEy8vr3XffnfYyzgBzZ5bRtj/gs2sdHR0AgK+++ooaw6NHj44dO7Zv377z58+Pjo7CQOJUyuDg4Pnz5w8cOPDOO+/gs2Kffvrpo0ePvv322+Li4nPnzg0NDcHwixcvPnjwAF6Pjo6ePn0aVgS0v3v3blFR0blz5+BvmA8++ODQoUP379+n5oqh/ffff3/o0KGioqK6ujo8kJh5WLqcnBw85zb6STzdzz//vKioCE440epjo5g//vjj/fv3i4uL3377bVonrKurGxgYuH//PrAyy/jmm29u2rTJIR1opSDNhz169Oitt96Cs2se5w84zgiCUWYZHdWBKIV7dZgWrM0yOtP6XDXLKJPJfvnll9jY2CmPUCF9fX1ff/11YWGh3R8HFovFYrEIBAJrBu3t7SwWC8+SUCgMDAxUKBS04c3NzcyNFQoFMaGmpqb29vbk5GQbiSIdpqaDR8NEkBkTSiaTjY+PR0VFTXvMiGmEoT+EhoYuXbr04MGD+JsEyPXr12NiYlpbWycmJsrKyiQSCXUJrEQiqa2t5fF4DQ0N0dHRMIZTp05lZ2fv2rVLp9OVlZVt2bIFGh8/fry+vh5em0ymAwcOwMxA+4yMDJ1OV1JSsmfPnoSEhPr6+nv37kkkktbWVlKiTOyrq6slEonBYOByuTt27MCn56mlm5ychCF2+0mY7v79++VyeWdnpzV9bBQzNzc3LS3NYDBcuHDhueeeo37FkpSURFxMTKWpqUksFjPXgbkUMpkM/ulx/kCqIOcF8XQdXMq0tD67OLB8WK/XX758ubi42PnXXu3t7QAA+GCzWCxSqdRisQAAgoKC8vPzcTOTySSVSicmJlJSUmDIrVu3oqOj4fXZs2cTExM1Gg2PxyOufhUIBHq9njZ8YGCAubFerwcAaDSazMxMvV7f0tJy9OjR9PR0GGjNHukwBR08EYcEcbVQra2tubm5Op2uvr5+3759W7duna6YEa6AoT9wOJyampodO3ZERkamp6cfOXIkJCTEbDbv3bu3sLDw6NGjAIDS0tLw8PDKykpijwEAaGhogOfoWCyWkJCQ2travLw8AMDw8HBrayufz09PT9+8ebPdE7lMJlNzczOfzxeLxW+88ca5c+fy8vIsFktkZGRVVVVMTIxD9lFRUfn5+fDZBgBYv359enp6Xl4evj8zsXQajQYO3Zj0k52dnc3NzUKh0Gw2h4WF2dWHhFarbW1tFQgEarU6NDS0qqrK0U8llEplYmIic93GxsZopcBjwKUoLS1VKpXAM/3BeUFw3xgdHYUXHq2DS3Gy9TGB6ZBxcnKyoqLib//2b6fxkGj84Bmz2Tw2NiaTyeRyOazgL774QiAQGAyGsLCwmpoavPKio6OhQwAAYK2MjY2RomWz2TwejzZ83rx5zI15PB4AAPqQwWAIDQ09fPgwn8/fu3evDfspgHTwRBwSxNVC8Xg8kUikUCi4XG5mZuZ0RYtwEcz9IT4+XqFQVFZWHj9+vKamBn6N29/fD3+iAABEIlFiYmJjYyPp0ejv769Wq+VyuU6n4/F4+B4Lqamp8Ots2G/09vbafjSmpKRAeziFBtNls9lRUVFqtdpRe6VS2d/fr1arKyoqAABardZoNHZ2duLz4gqFglg6Ijb6SQBAVlYW3DiCFIM1fUhs27YNvsMRiUSxsbEtLS02jGkxGAzEz97t6mZNCjwGWik8zh+cFwT3jY6ODnxw47k6uBQnWx8TmA4ZL1++zOVyg4ODe3t7DQbDxMTEwMDAkiVLHC4TAAAAWBnNzc1isZjNZsOldeXl5UeOHIEGL7zwQnl5ua+v7/Lly4k3CoXCpKQkYohAIDCZTGNjY3iHotVqhUIhbfiGDRuYG8MOiMvl7tq1CwCQnZ0tEAgKCgoyMjJs2CMdpqCDJ+KQIE4KxeFwSFNQJpOJeNRnREQE9Jnk5OSsrKzGxkZni4dwJQ75A5fLzc/P3717d0xMzIkTJ7KysmAMuAGfz6e+SC0sLPzkk08SEhL8/f1p57Nh0nD/JiaQ9jHhcDhwqs8he/iEhg8RGF5cXEzs3KABaQWO3X4SAIC/s6bGQKuPDXx9faljertwOBzau6zpNjUpgMf6g90b7Qry5MmTZcuW4X96ug4uZWqtj1HMDO3UavXw8PBHH30EAPjll18sFouXlxdpnyTmhISExMXFlZWV7d69m3ZSFG67xSSqyMhIDMNaWlri4+MBACqVamBgICoqis/nU8Pj4+MvXbrE0Jg69I6Ojh4fHzeZTNYSRTpMTQdPx64gDIW1RkhIyJ07d4gjjJaWFtofwYcPH3722WcbGxthQoinkyk0nICAgNjYWLVaHRISAgBQKBT4EFMulxNficKQ06dPP3z4EE422HUGHo+HPz6Hh4enWCoGwOdTZmamtSxRSwcY9JO2Y8D1sVFMk8mEX7e3t2/cuNGxggEQEBDg0GYRzKWg/XhgdvgDEbuCBAcHU0djs08H12FXYSYw/fyluLj42K9s3rz5ueeem/J4EfLhhx9qNJr4+Pjbt28bDIbOzs6mpia7d5lMJtWv9PX1AQDWr1+/evXqI0eOaLVag8FQUFCwZs2ahIQE2vDXXnuNuXFCQkJ3d7dUKlWpVAAAhUJx9uzZTZs2BQQEWLNHOkxZB8/CUUGcFCo3N1ev12dlZfX29ur1+o8//vjy5culpaVUS4lEsmbNGvjeAfHUwtAfrly5IpVKlUql2Wy+efNmfX19WlpaeHh4XFxcSUlJX1/f2NjY2bNnZTIZXJyEA6e74NPu+vXr+PcT1hCLxdXV1RqNpru7Oy0tjcViTWdpCYSFhW3atEkqlcLRlcFgqK2tJRqQSoeHM+8nbehjo5jvv/9+dXU1tO/u7oYvEIjADfOhpDqdTqvVkoYvUVFRcrncFVL09/fDkNnnD0TsChIWFgYvZrcOrsOuwkxw225G69evb2xsFIlESUlJfn5+K1eubGhoKCkpAQCw2WzaL+P8/f3r6uqe+RU4/cZms69du6ZSqZYsWSIQCLq7u2tqajgcDm24t7c3c2MOhyMQCJqbm8PDwzkcTmRkZGho6JUrV2wkinSYsg6ehaOCOCoUqerDwsJu3LjR3NwcHBy8aNGiw4cPV1RU4DvAkYyzs7OvXbtG/VQQ8fTA0B/EYnF9ff2qVasWLFiQlpa2f//+vXv3AgCqqqoAAMuXL+fxeCdPnrxx40ZERAQgeEJMTExOTk5SUlJQUBD8PA6GE12FzWazWCz4p1QqZbPZIpFILBbn5ub6+vrS2gPC+1/a3omJfVVVlcViEQqFAQEBIpEIloVkAEsHDzeC2OgnqZmxpo+1YgIAUlNTS0tLuVxuSUlJRUUFdca3tLR0yZIlL774IgAgLi5uyZIlpPWOEokEH8Uy1I1WCpIBAGDlypUe6g84zghCjdxRHfAY3K6DS3Gm9TnAVPYFmiqk018gIyMjXV1dT548wUPgDtWORt7f30+7nxZtuEPGRqOxq6uLuMmT3XhsQ7sfIdLB45iCILTh1P0IR0dHabeg++WXX4geAqH6iYeqOnf2ZcSh9QfSqSeDg4M9PT1UfzAajaRwktsMDQ319/djGDY+Pg7DSQYkP3n8+DEMwV3ahj1t78TcHrYdogHpXqPR+ODBA+oOiNR+knovHgOtbtRiwk37Jicnu7q6jEYjNiV++uknAADcONAh3UhSUMui0+nwU08wj/IHazlxSBD8duLpLw7pQMqAG3WYFqzty+hM62O+LyMLw7DpGuTapa6uDv5Km+O0tbWFh4c79GX7rATpAFEqlXw+f458NmQDpAMEbi5j+4PNucCM6RATE5OWliaVSp2MJzk5GX6KMS25wjGbzUqlEt9Vbc6CdICYzeaenp5Vq1ZNY5y37txNTHiWiSU6ZgeBQCAQc5fIyMigoCDn4zl69ChaEIKY3cz+ZWcIBAKBQFgDLkR2no0bN07hU2sEwoNgwRUYM0NXV9c07gSOQCAQCAQCMadgsVjEfXmdp6dfw/DFNGdaJuQZYvcQnjmCUqlcsWKFl5eXuzPiZpAOkJ6eHh8fH3iM1VwG6QDR6XRGozE4ONjdGXEzSAfI+Ph4V1cXenQiHSDj4+NqtXp61zL29GsYWnKmd6xqGwzD0LcOEC8vLyQFQDoAAABgsVgcDgfpgHSAcDgcFouFdEA6EEE6QJAO7gV9/oJAIBAIBAKBsAMaMiIQCAQCgUAg7ICGjAgEAoFAOIvFYjEYDO7OBQLhQty/yY5arVapVL6+vpGRkfDILHiaJwCAy+UGBATglng4xNvbG9/112KxyGQyk8kUHR3N5/NxG9pwh4xxtFqtTqcLDw/HD+GxbY90mPXo9Xq5XC4QCCIiIoinvU1NWACAVqul7uvm6+s7MTEBACD6gMlk0mg08EQ13B84HI5QKHTXcVUIR2HYcIaHh+Vyube3d3R0tO3TOFNSUrZs2ZKbm+uCzLochpmn9pMzycTERHt7e1RUFG0rKy8vr66uvnPnjjNJ2NVhjvgDEViQjIwMYiBzHcAsksL9MD+mpr+/v+lXWltbmd+IQzow8OHDh5s3b2axWIsXL/by8vLz8zt27BiGYa+++iqevaVLl3700UfQnhgOAFixYgUM7+joWL169aJFiwIDA318fK5evWoj3CFjnJ9//nnhwoUAgG+++YaJvW1IB+UhHTyRoqKi+fPnL1u2bN68eWvXrsWPfZuCsPhBeatXr6a20J07d27fvn379u3E1M+fP+/j4wOvif4QGBj43nvvzUDxXcGcOjDQhj8QDwz87LPP/Pz8AgMDFy5cGBwc3NPTYyNOePCda/PtMqiZJx2caK2fnDG+++67devWAQCoxxhiGDY5Obly5cqLFy86mQpVB+JBeXPHH4jAgkxZB2wWSYFZPzDQGZgfGOjAhERjY+O///u/t7a2tra2/uUvf2F+Iy0ymUwikXh7e6tUKq1WazKZqqur29raAAAmk+nll1/GMGxwcDAjIyMnJ6ehoQGGv/TSS+O/0tnZCaNKT08PCQlRq9V9fX1ZWVmZmZk6nc5auEPGeG4PHjyYkJBAzL9te6TDrIfL5SqVyt7eXrlcrlQqT506BcOnJixEJpONjIyMjIxs2LAhJycHXl++fNl2TnA/GRoaKigo2Ldv3+3bt11QYsR0wsQfzGZzZmbmwYMH1Wq1Tqc7efLknJ1CttFPzgyVlZXJyckSicSaQVNTk0qlSk1NdV0ekD9AkA7uhPk49PLly3V1dQ4OXv8LxFnG559/fu3atdQzxTEM27lzJ3wEYhg2OTnp5+d36NAhUjjODz/8AAiTXo8fPwYAXL16lTb8zJkzzI3x3/1ff/21n5/f999/j9vYtrcLcXYN6cDQ+Glm7dq1r7zyCuZgLRAnIEmza3Fxca+//jr+p+1ZRpKfeHl5vfvuu9Nexhlg7swy2vYHfHato6MDAPDVV19RY3j06NGxY8f27dt3/vz50dFRGEicShkcHDx//vyBAwfeeecdfFbs008/ffTo0bfffltcXHzu3LmhoSEYfvHixQcPHsDr0dHR06dPw4qA9nfv3i0qKjp37hz8DfPBBx8cOnTo/v371FwxtP/+++8PHTpUVFREfKAQMw9Ll5OTg+fcRj+Jp/v5558XFRXBCSdafWwU88cff7x//35xcfHbb79N64R1dXUDAwP3798HVmYZ33zzzU2bNjmkA60UpPmwR48evfXWW3B2zeP8AccZQTDKLKOjOhClcK8O04K1WUZnWp9LZhlNJpOPj8/UB6cE+vr6vv7668LCQrs/DiwWi8ViEQgE1gza29tZLFZsbCz8UygUBgYGKhQK2vDm5mbmxgqFAmYgPz//yJEjIpHIbqJIh6np4NE0NTW1t7cnJycDB2vBFULJZLLx8fGoqKhpjxkxjTD0h9DQ0KVLlx48eBB/kwC5fv16TExMa2vrxMREWVmZRCKhLoGVSCS1tbU8Hq+hoSE6OhrGcOrUqezs7F27dul0urKysi1btkDj48eP19fXw2uTyXTgwAGYGWifkZGh0+lKSkr27NmTkJBQX19/7949iUTS2tpKSpSJfXV1tUQiMRgMXC53x44d+PQ8tXSTk5MwxG4/CdPdv3+/XC7v7Oy0po+NYubm5qalpRkMhgsXLjz33HPUr1iSkpKIi4mpNDU1icVi5jowl0Imk8E/Pc4fSBXkvCCeroNLmZbWZxcHlg8bjcavvvrqL3/5yzPPPPP88887swd4e3s7AAA+2CwWi1QqtVgsAICgoKD8/HzczGQySaXSiYmJlJQUGHLr1q3o6Gh4ffbs2cTERI1Gw+PxiKtfBQKBXq+nDR8YGGBurNfrAQCVlZVjY2N5eXnwT4gNe6TDFHTwRDQaTWZmpl6vb2lpOXr0aHp6OrAuiKuFam1tzc3N1el09fX1+/bt27p163TFjHAFDP2Bw+HU1NTs2LEjMjIyPT39yJEjISEhZrN57969hYWFR48eBQCUlpaGh4dXVlYSewwAQENDAzxHx2KxhISE1NbW5uXlAQCGh4dbW1v5fH56evrmzZvtnshlMpmam5v5fL5YLH7jjTfOnTuXl5dnsVgiIyOrqqpiYmIcso+KisrPz4fPNgDA+vXr09PT8/Ly8P2ZiaXTaDRw6Makn+zs7GxubhYKhWazOSwszK4+JLRabWtrq0AgUKvVoaGhVVVVjn4qoVQqExMTmes2NjZGKwUeAy5FaWmpUqkEnukPzguC+8bo6Ci88GgdXIqTrY8JDgwZt2zZYjabh4eHb9261dTUVFxc7OQCAnzQaTabx8bGZDKZXC6HFfzFF18IBAKDwRAWFlZTU4NXXnR0NHQIAACslbGxMVK0bDabx+PRhs+bN4+5MY/H0+l0Uqm0urqa9EGWNXumJf+vIB08Edi5GAyG0NDQw4cP8/n8vXv3OlQL0ygUj8cTiUQKhYLL5WZmZk5XtAgXwdwf4uPjFQpFZWXl8ePHa2pq4Ne4/f398CcKAEAkEiUmJjY2NpIejf7+/mq1Wi6X63Q6Ho+H77GQmpoKv86G/UZvb6/tR2NKSgq0h1NoMF02mx0VFaVWqx21VyqV/f39arW6oqICAKDVao1GY2dnJz4vrlAoiKUjYqOfBABkZWXBjSNIMVjTh8S2bdvgOxyRSBQbG9vS0mLDmBaDwUD87N2ubtakwGOglcLj/MF5QXDf6OjowAc3nquDS3Gy9THBgSFjREQEvPjtb3+7f//+np6eFStWML+dCKyM5uZmsVjMZrPh0rry8vIjR45AgxdeeKG8vNzX13f58uXEG4VCYVJSEjFEIBCYTKaxsTG8Q9FqtUKhkDZ8w4YNzI2FQuGpU6d8fX3b2tra2tqGh4cBANXV1RMTE9bskQ5T08ET4XK5u3btAgBkZ2cLBIKCgoKMjAyHaoG5UBwOhzQFZTKZiNP8ERER0GeSk5OzsrIaGxudLR7ClTjkD1wuNz8/f/fu3TExMSdOnMjKyoIx4AZ8Pp/6IrWwsPCTTz5JSEjw9/ennc+GScP9m5hA+rnI4XDgVJ9D9vAJ3dvbi2e4uLiY2LlBA9IKHLv9JAAAn7+gxkCrjw18fX2pY3q7cDgc2rus6TY1KYDH+oPdG+0K8uTJk2XLluF/eroOLmVqrY9RzFPIzfz58xcuXEhdJcCckJCQuLi4srKy3bt3006Kwm23mEQVGRmJYVhLS0t8fDwAQKVSDQwMREVF8fl8anh8fPylS5cYGkdFRXG53NjYWPj9KewOWlpaIiIi1q9fT2uPdJiaDp5OdHT0+Pi4yWRyqBaYCxUSEnLnzh3iCKOlpYX2R/Dhw4efffbZxsZGmBDi6cSan9i4JSAgIDY2Vq1Wh4SEAAAUCgU+xJTL5cRXojDk9OnTDx8+hJMNdp2Bx+Phj0/4m9BFwOdTZmamtSxRSwcY9JO2Y8D1sVFMk8mEX7e3t2/cuNGxggEQEBDg0GYRzKXA17ySkpsF/kDEriDBwcHU0djs08F12FWYCQ68WdZoNPCipaXFZDJNeYoR8uGHH2o0mvj4+Nu3bxsMhs7OzqamJrt3mUwm1a/09fUBANavX7969eojR45otVqDwVBQULBmzZqEhATa8Ndee425cUJCQlZWVvWvXLhwAQBw/Pjx7Oxsa/ZIhynr4Fl0d3dLpVKVSgUAUCgUZ8+e3bRpU0BAgEO1wFyo3NxcvV6flZXV29ur1+s//vjjy5cvl5aWUi0lEsmaNWvgewfEUwtDf7hy5YpUKlUqlWaz+ebNm/X19WlpaeHh4XFxcSUlJX19fWNjY2fPnpXJZHBxEg78XQefdtevX8e/n7CGWCyurq7WaDTd3d1paWksFms6S0sgLCxs06ZNUqkUjq4MBkNtbS3RgFQ6PJx5P2lDHxvFfP/996urq6F9d3c3fIFABG6YDyXV6XRarZY0fImKipLL5a6Qor+/H4bMPn8gYleQsLAweDG7dXAddhVmggNDxlOnTpWWlpaWll67du2f/umfHFoySWX9+vWNjY0ikSgpKcnPz2/lypUNDQ0lJSUAADabTbtK0t/fv66u7plfgdNvbDb72rVrKpVqyZIlAoGgu7u7pqaGw+HQhnt7ezM3Jk3twizh/7drj3SYxQgEgubm5vDwcA6HExkZGRoaeuXKFeBgLdgQilT1YWFhN27caG5uDg4OXrRo0eHDhysqKvAd4EjG2dnZ165dc+YlAMLVMPQHsVhcX1+/atWqBQsWpKWl7d+/f+/evQCAqqoqAMDy5ct5PN7Jkydv3LgBVw3hnhATE5OTk5OUlBQUFAQ/j8MbLO4qbDabxWLBP6VSKZvNFolEYrE4NzfX19eX1h4Q3v/S9k5M7KuqqiwWi1AoDAgIEIlEsCwkA1g6eLgRxEY/Sc2MNX2sFRMAkJqaWlpayuVyS0pKKioqqDO+paWlS5YsefHFFwEAcXFxS5YsIa13lEgk+CiWoW60UpAMAAArV670UH/AcUYQauSO6oDH4HYdXIozrc8BmO8GNDExodVqf/nlF+a3kCCd/gIZGRnp6up68uQJHgJ3qHY08v7+ftr9tGjDHTImZtUhe2vQ7keIdPA4jEZjV1cXcfcvHIeEpe5HODo6SrsF3S+//EL0EAjVTzxU1bmzLyMOrT+QTj0ZHBzs6emh+oPRaCSFk9xmaGiov78fw7Dx8XEYTjIg+cnjx49hCO7SNuxpeyfm9rDtEA1I9xqNxgcPHlB3QKT2k9R78RhodaMWE27aNzk52dXVZTQasSnx008/AQDgxoEO6UaSgloWnU6Hn3qCeZQ/WMuJQ4LgtxNPf3FIB1IG3KjDtGBtX0ZnWh/zfRlZGIZN1yDXLnV1dfBX2hynra0tPDzcyWnaWQDSAaJUKvl8/hz5bMgGSAcI3FzG9gebc4EZ0yEmJiYtLU0qlToZT3JyMvwUY1pyhWM2m5VKJb6r2pwF6QAxm809PT2rVq2axjhv3bmbmPAsE0t0zA4CgUAg5i6RkZFBQUHOx3P06FG0IAQxu5n9y84QCAQCgbAGXIjsPBs3bpzCp9YIhAfBgiswZoaurq7FixfPWHIIBAKBQCAQswkWi+XM8XtUevo1DF9Mc6ZlQp4hdg/hmSMolcoVK1Z4eXm5OyNuBukA6enp8fHxgcdYzWWQDhCdTmc0GoODg92dETeDdICMj493dXWhRyfSATI+Pq5Wq6d3LWNPv4ahJWd6x6q2wTAMfesA8fLyQlIApAMAAAAWi8XhcJAOSAcIh8NhsVhIB6QDEaQDBOngXtDnLwgEAoFAIBAIO6AhIwKBQCAQCATCDmjIiEAgEAiEs1gsFoPB4O5cIBAuxP2b7KjVapVK5evrGxkZCY/Mgqd5AgC4XG5AQABuiYdDvL298V1/LRaLTCYzmUzR0dF8Ph+3oQ13yNhkMhEPm/f39+fxeLbjQTrMEfR6vVwuFwgEERERxNPeHBKWiFarpe7r5uvrOzExAQAg+oDJZNJoNPBENdwfOByOUCh013FVCEdh2HCGh4flcrm3t3d0dLTt0zhTUlK2bNmSm5vrgsy6HIaZp/aTM8nExER7e3tUVBRtKysvL6+urr5z544zSdjVYY74AxFYkIyMDGIgcx3ALJLC/Th0Us3ExERzc/ONGzdu3749hVNxSAcGPnz4cPPmzSwWa/HixV5eXn5+fseOHcMw7NVXX8Wzt3Tp0o8++gjaE8MBACtWrIDhHR0dq1evXrRoUWBgoI+Pz9WrV22EO2SMYdjf/d3fERN96623bNszgXRQHtLBEykqKpo/f/6yZcvmzZu3du1a/Ng3R4XFCAflrV69mtpCd+7cuX379u3btxNTP3/+vI+PD7wm+kNgYOB77703A8V3BXPqwEAb/kA8MPCzzz7z8/MLDAxcuHBhcHBwT0+PjTjhwXeuzbfLoGaedHCitX5yxvjuu+/WrVsHAKAeY4hh2OTk5MqVKy9evOhkKlQdiAflzR1/IAILMmUdsFkkBWb9wEBnYH5goAMTEmNjY3/4wx+++uorb2/vrq4uJ7e5l8lkEonE29tbpVJptVqTyVRdXd3W1gYAMJlML7/8MoZhg4ODGRkZOTk5DQ0NMPyll14a/5XOzk4YVXp6ekhIiFqt7uvry8rKyszMhPNhtOEOGcNSv/XWW4O/gh8qZc0e6TA1HTwOLperVCp7e3vlcrlSqTx16hQMd1RYIjKZbGRkZGRkZMOGDTk5OfD68uXLtnOC+8nQ0FBBQcG+fftu377tghIjphMm/mA2mzMzMw8ePKhWq3U63cmTJ+fsFLKNfnJmqKysTE5Olkgk1gyamppUKlVqaqrr8oD8AYJ0cCfMx6HXrl374x//SD0FnDnEWcbnn39+7dq1tLHt3LkTPgIxDJucnPTz8zt06BApHOeHH34AAHzzzTfwz8ePHwMArl69Sht+5swZ5sbwd//LL7/8zjvvMEyUoQ7E2TWkA0Pjp5m1a9e+8sormIO1QJyAJM2uxcXFvf766/iftmcZSX7i5eX17rvvTnsZZ4C5M8to2x/w2bWOjg4AwFdffUWN4dGjR8eOHdu3b9/58+dHR0dhIHEqZXBw8Pz58wcOHHjnnXfwWbFPP/300aNH3377bXFx8blz54aGhmD4xYsXHzx4AK9HR0dPnz4NKwLa3717t6io6Ny5c/A3zAcffHDo0KH79+9Tc8XQ/vvvvz906FBRUVFdXR0eSMw8LF1OTg6ecxv9JJ7u559/XlRUBCecaPWxUcwff/zx/v37xcXFb7/9Nq0T1tXVDQwM3L9/H1iZZXzzzTc3bdrkkA60UpDmwx49evTWW2/B2TWP8wccZwTBKLOMjupAlMK9OkwL1mYZnWl90z/LaLFY/vznP2/fvn1ahvN9fX1ff/11YWGh3dgsFovFYhEIBNYM2tvbWSxWbGws/FMoFAYGBioUCtrw5uZm5sYKhQL+qdPp2tvbieuabdsjHRzVwaNpampqb29PTk4GDtaCK4SSyWTj4+NRUVHTHjNiGmHoD6GhoUuXLj148CD+JgFy/fr1mJiY1tbWiYmJsrIyiURCfecjkUhqa2t5PF5DQ0N0dDSM4dSpU9nZ2bt27dLpdGVlZVu2bIHGx48fr6+vh9cmk+nAgQMwM9A+IyNDp9OVlJTs2bMnISGhvr7+3r17EomktbWVlCgT++rqaolEYjAYuFzujh078Ol5aukmJydhiN1+Eqa7f/9+uVze2dlpTR8bxczNzU1LSzMYDBcuXHjuueeoX7EkJSURFxNTaWpqEovFzHVgLoVMJoN/epw/kCrIeUE8XQeXMi2tzy5Mlw9rNBoMw5RK5UcffeTl5ZWYmLhhwwZHE8Npb28HAMAHm8VikUqlFosFABAUFJSfn4+bmUwmqVQ6MTGRkpICQ27duhUdHQ2vz549m5iYqNFoeDwecfWrQCDQ6/W04QMDA8yN9Xo9AIDL5ZaXl1dUVAwNDcXFxVVWVorFYhv2SIcp6OCJaDSazMxMvV7f0tJy9OjR9PR0GOiosNNCa2trbm6uTqerr6/ft2/f1q1bpytmhCtg6A8cDqempmbHjh2RkZHp6elHjhwJCQkxm8179+4tLCw8evQoAKC0tDQ8PLyyspLYYwAAGhoa4Dk6FoslJCSktrY2Ly8PADA8PNza2srn89PT0zdv3mz3RC6TydTc3Mzn88Vi8RtvvHHu3Lm8vDyLxRIZGVlVVRUTE+OQfVRUVH5+Pny2AQDWr1+fnp6el5eH789MLJ1Go4FDNyb9ZGdnZ3Nzs1AoNJvNYWFhdvUhodVqW1tbBQKBWq0ODQ2tqqpy9FMJpVKZmJjIXLexsTFaKfAYcClKS0uVSiXwTH9wXhDcN0ZHR+GFR+vgUpxsfUxgOmT85ZdfxsbG5HJ5Tk5Of39/RUUFn8+nXa3PHPzgGbPZPDY2JpPJ5HI5rOAvvvhCIBAYDIawsLCamhq88qKjo6FDAABgrYyNjZGiZbPZPB6PNnzevHnMjeEXwfiJ9Z2dnbt27UpLS1MoFDbspwDSwROBnYvBYAgNDT18+DCfz9+7d69DtTCNQvF4PJFIpFAouFxuZmbmdEWLcBHM/SE+Pl6hUFRWVh4/frympgZ+jdvf3w9/ogAARCJRYmJiY2Mj6dHo7++vVqvlcrlOp+PxePgeC6mpqfDrbNhv9Pb22n40pqSkQHs4hQbTZbPZUVFRarXaUXulUtnf369WqysqKgAAWq3WaDR2dnbi8+IKhYJYOiI2+kkAQFZWFtw4ghSDNX1IbNu2Db7DEYlEsbGxLS0tNoxpMRgMxM/e7epmTQo8BlopPM4fnBcE942Ojg58cOO5OrgUJ1sfE5i+ZYbN9e///u+XLFkiFosTEhLgqo6pASujubkZAMBms8+cOVNeXr5jxw7c4IUXXmhsbOzu7lYqlfCVH0QoFCb9CvytIBAITCYTsQvWarVCodBauEPGxDyHhYWVlJR0dHR0dnYysUc6zG64XO6uXbuys7MvX76cnZ1dUFBgMpkcrQWGaXE4nOHhYWKIyWQiHvUZERFx5MiRW7duicXirKws50qGcDkO+QOXy83Pz29ra/P19T1x4gR8yBHXqPD5fJJ7AAAKCwujo6PLy8tv3rxJO58N/Qfu38QE0j4mHA4HTvU5ZA8z39vbq1QqlUqlXq8vLi5evnw5bkYtHWDQT8JwazHQ6mMDX19f6pjeLhwOh/Yua7pNTQrgsf5g90a7gjx58oR4o6fr4FKm1voYxczQbvHixQAAFosF/+TxeM7sWRoSEhIXF1dWVrZ7927aSVG47RaTqCIjIzEMa2lpiY+PBwCoVKqBgYGoqCg+n08Nj4+Pv3TpEkNj6tAb+h+Px7OWKNJhajp4OtHR0ePj4yaTyaFaYC5USEjInTt3xsbG8GFiS0sL7Y/gw4cPP/vss42NjTAhxNPJFBpOQEBAbGysWq0OCQkBACgUCnyIKZfLia9EYcjp06cfPnwIJxvsOgOPx8Mfnw6NrhwFPp8yMzOtZYlaOsCgn7QdA66PjWKaTCb8ur29fePGjY4VDICAgACHNotgLgW+5pWU3CzwByJ2BQkODqaOxmafDq7DrsJMYDrLCF9D/+d//icAYGRkpLGxEV/qOzU+/PBDjUYTHx9/+/Ztg8HQ2dnZ1NRk9y6TyaT6lb6+PgDA+vXrV69efeTIEa1WazAYCgoK1qxZk5CQQBv+2muvMTdOSEjo6+u7dOmSwWCwWCytra1lZWV/+7d/KxKJrNkjHaasg2fR3d0tlUpVKhUAQKFQnD17dtOmTQEBAQ7VAnOhcnNz9Xp9VlZWb2+vXq//+OOPL1++XFpaSrWUSCRr1qyB7x0QTy0M/eHKlStSqVSpVJrN5ps3b9bX16elpYWHh8fFxZWUlPT19Y2NjZ09e1Ymk8HFSThwugs+7a5fv45/P2ENsVhcXV2t0Wi6u7vT0tLwqYFpJywsbNOmTVKpFI6uDAZDbW0t0YBUOjyceT9pQx8bxXz//ferq6uhfXd3965du0jRwg3zoaQ6nU6r1ZKGL1FRUXK53BVS9Pf3w5DZ5w9E7AoSFhYGL2a3Dq7DrsJMcODz51dfffXOnTtSqbSkpGTDhg1ODhnXr1/f2NgoEomSkpL8/PxWrlzZ0NBQUlICAGCz2bRfxvn7+9fV1T3zK3D6jc1mX7t2TaVSLVmyRCAQdHd319TUcDgc2nBvb2/mxnBq9+TJk35+flwuNz4+/rnnnvv4449tJIp0mLIOnoVAIGhubg4PD+dwOJGRkaGhoXCtp0O1YEMoUtWHhYXduHGjubk5ODh40aJFhw8frqiowHeAIxlnZ2dfu3bNyW1TES6FoT+IxeL6+vpVq1YtWLAgLS1t//79e/fuBQBUVVUBAJYvX87j8U6ePHnjxo2IiAhA8ISYmJicnJykpKSgoCD4eRwMJ7oKm81msVjwT6lUymazRSKRWCzOzc319fWltQeE97+0vRMT+6qqKovFIhQKAwICRCIRLAvJAJYOHm4EsdFPUjNjTR9rxQQApKamlpaWcrnckpKSiooK6oxvaWnpkiVLXnzxRQBAXFzckiVLSOsdJRIJPoplqButFCQDAMDKlSs91B9wnBGEGrmjOuAxuF0Hl+JM63MAhzYEmpyc1Gq1xO2OHIJ0+gtkZGSkq6vryZMneAjcodrRyPv7+2n306INd8h4cHCwp6eHdkswa/HYhnY/QqSDx2E0Gru6umibg0PCUvcjHB0dpdX5l19+IXoIhOonHqrq3NmXEYfWH0innlhrd0ajkRROcpuhoaH+/n4Mw8bHx2E4yYDkJ48fP4YhuEvbsKftnZjbw7ZDNCDdazQaHzx4QN0BkdpPUu/FY6DVjVpMuGnf5ORkV1eX0WjEpsRPP/0EAIAbBzqkG0kKall0Oh1+6gnmUf5gLScOCYLfTjz9xSEdSBlwow7TgrV9GZ1pfcz3ZWRhGDZdg1y71NXVwV9pc5y2trbw8HCHvmyflSAdIEqlks/nz5HPhmyAdIDAzWVsf7A5F5gxHWJiYtLS0vATraZMcnJyTEzMiRMnpiVXOGazWalU4ruqzVmQDhCz2dzT07Nq1appjPPWnbuJCc8ysUTH7CAQCARi7hIZGRkUFOR8PEePHkULQhCzm9m/7AyBQCAQCGvgm846ycaNG6fwqTUC4UGw4AqMmaGrqwtu1oNAIBAIBAKBcBQWi0Xcl9d5evo1DF9Mc6ZlQp4hdg/hmSMolcoVK1Z4eXm5OyNuBukA6enp8fHxgVuyz2WQDhCdTmc0GoODg92dETeDdICMj493dXWhRyfSATI+Pq5Wq6d3LWNPv4ahJWd6x6q2wTAMfesA8fLyQlIApAMAAAAWi8XhcJAOSAcIh8NhsVhIB6QDEaQDBOngXtDnLwgEAoFAIBAIO6AhIwKBQCAQCATCDmjIiEAgEAiEs1gsFoPB4O5cIBAuxP2b7KjVapVK5evrGxkZCY/Mgqd5AgC4XG5AQABuiYdDvL298V1/LRaLTCYzmUzR0dF8Ph+3oQ13yBgyNjamVCoNBkNUVJTdeJAOcwS9Xi+XywUCQUREBPG0tykIC9FqtdR93Xx9fScmJgAARB8wmUwajQaeqIb7A4fDEQqF7jquCuEoDBvO8PCwXC739vaOjo62fRpnSkrKli1bcnNzXZBZl8Mw89R+ciaZmJhob2+PioqibWXl5eXV1dV37txxJgm7OswRfyACC5KRkUEMZK4DmEVSuB+Gp8Rotdqm/4pKpWJ4Lw7pwMCHDx9u3ryZxWItXrzYy8vLz8/v2LFjGIa9+uqrePaWLl360UcfQXtiOABgxYoVMLyjo2P16tWLFi0KDAz08fG5evWqjXCHjCH/+q//umjRohUrVjzzzDOLFi2ya28X0kF5SAdPpKioaP78+cuWLZs3b97atWvxY9+mICx+UN7q1aupLXTnzp3bt2/fvn07MfXz58/7+PjAa6I/BAYGvvfeezNQfFcwpw4MtOEPxAMDP/vsMz8/v8DAwIULFwYHB/f09NiIEx5859p8uwxq5kkHJ1rrJ2eM7777bt26dQAA6jGGGIZNTk6uXLny4sWLTqZC1YF4UN7c8QcisCBT1gGbRVJg1g8MdAbmBwYynZDQ6XStBD755JNHjx4xvJcWmUwmkUi8vb1VKpVWqzWZTNXV1W1tbQAAk8n08ssvYxg2ODiYkZGRk5PT0NAAw1966aXxX+ns7IRRpaenh4SEqNXqvr6+rKyszMxMnU5nLdwhYwDAl19+mZub+/HHH6tUqs7Ozvb2dtuJIh2mpoPHweVylUplb2+vXC5XKpWnTp2C4Y4KS0Qmk42MjIyMjGzYsCEnJwdeX7582XZOcD8ZGhoqKCjYt2/f7du3XVBixHTCxB/MZnNmZubBgwfVarVOpzt58uScnUK20U/ODJWVlcnJyRKJxJoBnEZJTU11XR6QP0CQDu5kCgPS3t7e/fv340d0M4c4y/j888+vXbuWeqY4hmE7d+6Ej0AMwyYnJ/38/A4dOkQKx/nhhx8AAN988w388/HjxwCAq1ev0oafOXOGuTH83f/f/tt/+8d//EeGiTLUgTi7hnRgaPw0s3bt2ldeeQVzsBaIE5Ck2bW4uLjXX38d/9P2LCPJT7y8vN59991pL+MMMHdmGW37Az671tHRAQD46quvqDE8evTo2LFj+/btO3/+PN4VE6dSBgcHz58/f+DAgXfeeQefFfv0008fPXr07bffFhcXnzt3bmhoCIZfvHjxwYMH8Hp0dPT06dOwIqD93bt3i4qKzp07B3/DfPDBB4cOHbp//z41Vwztv//++0OHDhUVFdXV1eGBxMzD0uXk5OA5t9FP4ul+/vnnRUVFcMKJVh8bxfzxxx/v379fXFz89ttv0zphXV3dwMDA/fv3gZVZxjfffHPTpk0O6UArBWk+7NGjR2+99RacXfM4f8BxRhCMMsvoqA5EKdyrw7RgbZbRmdY3/bOMRGpqav77f//vzmzo2NfX9/XXXxcWFtr9cWCxWCwWi0AgsGbQ3t7OYrFiY2Phn0KhMDAwUKFQ0IY3NzczN1YoFGNjYw0NDVu3btXpdG1tbfjSZmv2SIep6eDRNDU1tbe3JycnAwdrwRVCyWSy8fHxqKioaY8ZMY0w9IfQ0NClS5cePHgQf5MAuX79ekxMTGtr68TERFlZmUQioS6BlUgktbW1PB6voaEhOjoaxnDq1Kns7Oxdu3bpdLqysrItW7ZA4+PHj9fX18Nrk8l04MABmBlon5GRodPpSkpK9uzZk5CQUF9ff+/ePYlE0traSkqUiX11dbVEIjEYDFwud8eOHfj0PLV0k5OTMMRuPwnT3b9/v1wu7+zstKaPjWLm5uampaUZDIYLFy4899xz1K9YkpKSiIuJqTQ1NYnFYuY6MJdCJpPBPz3OH0gV5Lwgnq6DS5mW1mcXh5cP9/X1/fjjjzk5OY7eSAS+1oQPNovFIpVKLRYLACAoKCg/Px83M5lMUql0YmIiJSUFhty6dSs6Ohpenz17NjExUaPR8Hg84upXgUCg1+tpwwcGBpgb6/X6vr6+8fFxqVSqVCr5fH5fX9/evXvLy8ut2SMdpqaDJ6LRaDIzM/V6fUtLy9GjR9PT02GgQ8JOV2ZaW1tzc3N1Ol19ff2+ffu2bt06XTEjXAFDf+BwODU1NTt27IiMjExPTz9y5EhISIjZbN67d29hYeHRo0cBAKWlpeHh4ZWVlcQeAwDQ0NAAz9GxWCwhISG1tbV5eXkAgOHh4dbWVj6fn56evnnzZrsncplMpubmZj6fLxaL33jjjXPnzuXl5VkslsjIyKqqqpiYGIfso6Ki8vPz4bMNALB+/fr09PS8vDx8f2Zi6TQaDRy6MeknOzs7m5ubhUKh2WwOCwuzqw8JrVbb2toqEAjUanVoaGhVVZWjn0oolcrExETmuo2NjdFKgceAS1FaWqpUKoFn+oPzguC+MTo6Ci88WgeX4mTrY4LDQ8a6uroXXnhhWs6MwSMxm81jY2MymUwul8MK/uKLLwQCgcFgCAsLq6mpwSsvOjoaOgQAANbK2NgYKVo2m83j8WjD582bx9wYD09PT8/Pz+dwODdu3Hj55Ze3bdtmzd5hCQAASAfPBHYuBoMhNDT08OHDfD5/7969DtXCNArF4/FEIpFCoeByuZmZmdMVLcJFMPeH+Ph4hUJRWVl5/Pjxmpoa+DVuf38//IkCABCJRImJiY2NjaRHo7+/v1qtlsvlOp2Ox+PheyykpqbCr7Nhv9Hb22v70ZiSkgLt4RQaTJfNZkdFRanVakftlUplf3+/Wq2uqKgAAGi1WqPR2NnZic+LKxQKYumI2OgnAQBZWVlw4whSDNb0IbFt2zb4DkckEsXGxra0tNgwpsVgMBA/e7ermzUp8BhopfA4f3BeENw3Ojo68MGN5+rgUpxsfUxw7MX06OhoY2NjQkKCQ3dRgZXR3NwMAGCz2WfOnCkvL9+xYwdu8MILLzQ2NnZ3dyuVSvjKDyIUCpN+Bf5WEAgEJpOJ2AVrtVqhUGgt3CFj2Ilv3LgRzgekpKQsXrwY/hiltUc6TE0HT4TL5e7atSs7O/vy5cvZ2dkFBQUmk8nRWmCYFofDGR4eJoaYTCbiz7aIiIgjR47cunVLLBZnZWU5VzKEy3HIH7hcbn5+fltbm6+v74kTJ+BDjrhGhc/nk9wDAFBYWBgdHV1eXn7z5k3a+WzoP3D/JiaQ9jHhcDhwqs8he5j53t5epVKpVCr1en1xcfHy5ctxM2rpAIN+EoZbi4FWHxv4+vpSx/R24XA4tHdZ021qUgCP9Qe7N9oV5MmTJ8QbPV0HlzK11scoZoesZTJZUFAQHKM4Q0hISFxcXFlZ2e7du2knReG2W0yiioyMxDCspaUlPj4eAKBSqQYGBuCugdTw+Pj4S5cuMTSOiooKCgpasGCBXC5/7rnnAABjY2Mmk0koFFpLFOkwNR08nejo6PHxcZPJ5FAtMBcqJCTkzp07Y2Nj+DCxpaWF9kfw4cOHn3322cbGRpgQ4ulkCg0nICAgNjZWrVaHhIQAABQKBT7ElMvlxFeiMOT06dMPHz6Ekw12nYHH4+GPT4dGV44Cn0+ZmZnWskQtHWDQT9qOAdfHRjFNJhN+3d7evnHjRscKBkBAQIBDm0UwlwJf80pKbhb4AxG7ggQHB1NHY7NPB9dhV2EmODbL+PDhQ3wJnZN8+OGHGo0mPj7+9u3bBoOhs7OzqanJ7l0mk0n1K319fQCA9evXr169+siRI1qt1mAwFBQUrFmzJiEhgTb8tddeY26ckJDAZrNTU1PPnDnT29trNpulUimXy92yZYs1e6TDlHXwLLq7u6VSqUqlAgAoFIqzZ89u2rQpICDAoVpgLlRubq5er8/Kyurt7dXr9R9//PHly5dLS0uplhKJZM2aNfC9A+KphaE/XLlyBS4gNpvNN2/erK+vT0tLCw8Pj4uLKykp6evrGxsbO3v2rEwmg4uTcOB0F3zaXb9+Hf9+whpisbi6ulqj0XR3d6elpbFYrOksLYGwsLBNmzZJpVI4ujIYDLW1tUQDUunwcOb9pA19bBTz/fffr66uhvbd3d27du0iRQs3zIeS6nQ6rVZLGr5ERUXJ5XJXSNHf3w9DZp8/ELErSFhYGLyY3Tq4DrsKM8GxIeOPP/74zDPPOJoGLevXr29sbBSJRElJSX5+fitXrmxoaCgpKQEAsNls2i/j/P396+rqnvkVOP3GZrOvXbumUqmWLFkiEAi6u7tramo4HA5tuLe3N3NjOLV75swZgUAQHBzs6+t748aNL774wt/f34Y90mHmj2SYeQQCQXNzc3h4OIfDiYyMDA0NvXLlCnCwFmwIRar6sLCwGzduNDc3BwcHL1q06PDhwxUVFfgOcCTj7Ozsa9euUT8VRDw9MPQHsVhcX1+/atWqBQsWpKWl7d+/f+/evQCAqqoqAMDy5ct5PN7Jkydv3LgREREBCJ4QExOTk5OTlJQUFBQEP4+D4URXYbPZLBYL/imVStlstkgkEovFubm5vr6+tPaA8P6XtndiYl9VVWWxWIRCYUBAgEgkgmUhGcDSwcONIDb6SWpmrOljrZgAgNTU1NLSUi6XW1JSUlFRQZ3xLS0tXbJkyYsvvggAiIuLW7JkCWm9o0QiwUexDHWjlYJkAABYuXKlh/oDjjOCUCN3VAc8Brfr4FKcaX0OMJV9gaYK6fQXyMjISFdX15MnT/AQuEO1o5H39/fT7qdFG+6QMYZhAwMDP//8M3N729DuR4h08DiMRmNXVxftBqUOCUvdj3B0dJR2C7pffvmF6CEQqp94qKpzZ19GHFp/IJ16Mjg42NPTQ/UHo9FICie5zdDQUH9/P4Zh4+PjMJxkQPKTx48fwxDcpW3Y0/ZOzO1h2yEakO41Go0PHjyg7oBI7Sep9+Ix0OpGLSbctG9ycrKrq8toNGJT4qeffgIAwI0DHdKNJAW1LDqdDj/1BPMof7CWE4cEwW8nnv7ikA6kDLhRh2nB2r6MzrQ+5vsysjAMm65Brl3q6urgr7Q5TltbW3h4uENfts9KkA4QuHXRHPlsyAZIBwjcXMb2B5tzgRnTISYmJi0tTSqVOhlPcnJyTEzMiRMnpiVXOGazWalUTteSMM8F6QAxm809PT2rVq2axjhv3bmbmPAsE0t0zA4CgUAg5i6RkZFBQUHOx3P06FG0IAQxu5n9y84QCAQCgbAGXIjsPBs3bpzCp9YIhAfBgiswZoaurq7FixfPWHIIBAKBQCAQswkWizUtx6ng9PRrGL6Y5kzLhDxD7B7CM0dQKpUrVqzw8vJyd0bcDNIB0tPT4+Pj4/x2p54O0gGi0+mMRmNwcLC7M+JmkA6Q8fHxrq4u9OhEOkDGx8fVavX0rmXs6dcwtORM71jVNhiGoW8dIF5eXkgKgHQAAADAYrE4HA7SAekA4XA4LBYL6YB0IIJ0gCAd3Av6/AWBQCAQCAQCYQc0ZEQgEAgEAoFA2AENGREIBAKBcBaLxWIwGNydCwTChbh/kx21Wq1SqXx9fSMjI+GRWfA0TwAAl8sNCAjALfFwiLe3N77rr8VikclkJpMpOjqaz+fjNrThzI0tFgs8wZmISCSC+bQWD9JhjqDX6+VyuUAgiIiIIJ725lAtENFqtdR93Xx9fScmJgAARB8wmUwajQaeqIb7A4fDEQqF7jquCuEoDBvO8PCwXC739vaOjo62fRpnSkrKli1bcnNzXZBZl8Mw89R+ciaZmJhob2+PioqibWXl5eXV1dV37txxJgm7OswRfyACC5KRkUEMZK4DmEVSuB+HTqp59OhRbW3t/fv3aU8zswvpwMCHDx9u3ryZxWItXrzYy8vLz8/v2LFjGIa9+uqrePaWLl360UcfQXtiOABgxYoVMLyjo2P16tWLFi0KDAz08fG5evWqjXCHjB8+fEhV7LPPPrMRDxNIB+UhHTyRoqKi+fPnL1u2bN68eWvXrsWPfXNIWPyf4O2rV6+m6rxz587t27dv376dmPr58+d9fHzgNdEfAgMD33vvvRkoviuYUwcG2vAH4oGBn332mZ+fX2Bg4MKFC4ODg3t6emzECQ++c22+XQY186SDE631kzPGd999t27dOgAA9RhDDMMmJydXrlx58eJFJ1Oh6kA8KG/u+AMRWJAp64DNIikw6wcGOgPzAwMdmJD493//9wsXLgAAvvrqq/fff99isTC/l4pMJpNIJN7e3iqVSqvVmkym6urqtrY2AIDJZHr55ZcxDBscHMzIyMjJyWloaIDhL7300vivdHZ2wqjS09NDQkLUanVfX19WVlZmZqZOp7MW7pCxWCweJPC///f/ZrFYsbGxNhJFOkxNB4+Dy+Uqlcre3l65XK5UKk+dOgXDHRKWFKdMJhsZGRkZGdmwYUNOTg68vnz5su2c4H4yNDRUUFCwb9++27dvu6DEiOmEiT+YzebMzMyDBw+q1WqdTnfy5Mk5O4Vso5+cGSorK5OTkyUSiTWDpqYmlUqVmprqujwgf4AgHdwJ83Ho3r17f/rpJwzDRkdH//Ef//Hnn392aBiL/ddZxueff37t2rW0s5U7d+6Ej0AMwyYnJ/38/A4dOkQKx/nhhx8AAN988w388/HjxwCAq1ev0oafOXOGuTF1wuxv/uZvXnrpJRuJMtSBOLuGdGBo/DSzdu3aV155BXOwFogTkKTZtbi4uNdffx3/0/YsI8lPvLy83n333Wkv4wwwd2YZbfsDPrvW0dEBAPjqq6+oMTx69OjYsWP79u07f/786OgoDCROpQwODp4/f/7AgQPvvPMOPiv26aefPnr06Ntvvy0uLj537tzQ0BAMv3jx4oMHD+D16Ojo6dOnYUVA+7t37xYVFZ07dw7+hvnggw8OHTp0//59aq4Y2n///feHDh0qKiqqq6vDA4mZh6XLycnBc26jn8TT/fzzz4uKiuCEE60+Nor5448/3r9/v7i4+O2336Z1wrq6uoGBgfv37wMrs4xvvvnmpk2bHNKBVgrSfNijR4/eeustOLvmcf6A44wgGGWW0VEdiFK4V4dpwdosozOtzyWzjFwuF66pwjAMADB//vwpj1P7+vq+/vrrwsJCuz8OLBaLxWIRCATWDNrb2/EZLwCAUCgMDAxUKBS04c3NzcyNFQoFKaGbN2/m5+fbSBTpMDUdPJqmpqb29vbk5GTgYC24QiiZTDY+Ph4VFTXtMSOmEYb+EBoaunTp0oMHD+JvEiDXr1+PiYlpbW2dmJgoKyuTSCTUJbASiaS2tpbH4zU0NERHR8MYTp06lZ2dvWvXLp1OV1ZWtmXLFmh8/Pjx+vp6eG0ymQ4cOAAzA+0zMjJ0Ol1JScmePXsSEhLq6+vv3bsnkUhaW1tJiTKxr66ulkgkBoOBy+Xu2LEDn56nlm5ychKG2O0nYbr79++Xy+WdnZ3W9LFRzNzc3LS0NIPBcOHCheeee476FUtSUhJxMTGVpqYmsVjMXAfmUshkMvinx/kDqYKcF8TTdXAp09L67OLA8uGcnJxPPvlk3bp1crl827Ztzhz9197eDgCADzaLxSKVSuFr7qCgIDgWgZhMJqlUOjExkZKSAkNu3boVHR0Nr8+ePZuYmKjRaHg8HnH1q0Ag0Ov1tOEDAwPMjfV6PTHPZ86ciYqKSkpKAgAwsUc6zG40Gk1mZqZer29paTl69Gh6ejqwLoirhWptbc3NzdXpdPX19fv27du6det0xYxwBQz9gcPh1NTU7NixIzIyMj09/ciRIyEhIWazee/evYWFhUePHgUAlJaWhoeHV1ZWEnsMAEBDQwM8R8disYSEhNTW1ubl5QEAhoeHW1tb+Xx+enr65s2b7Z7IZTKZmpub+Xy+WCx+4403zp07l5eXZ7FYIiMjq6qqYmJiHLKPiorKz8+HzzYAwPr169PT0/Py8vD9mYml02g0cOjGpJ/s7Oxsbm4WCoVmszksLMyuPiS0Wm1ra6tAIFCr1aGhoVVVVY5+KqFUKhMTE5nrNjY2RisFHgMuRWlpqVKpBJ7pD84LgvvG6OgovPBoHVyKk62PCQ4MGdva2ry9vb29vfl8fltbW0JCgpMnx+C3m83msbExmUwml8thBX/xxRcCgcBgMISFhdXU1OCVFx0dDR0CAABrZWxsjBQtm83m8Xi04fPmzWNuzOPx8D81Gs2lS5fKy8vhn3btHQLp4InAzsVgMISGhh4+fJjP5+/du9ehWphGoXg8nkgkUigUXC43MzNzuqJFuAjm/hAfH69QKCorK48fP15TUwO/xu3v74c/UQAAIpEoMTGxsbGR9Gj09/dXq9VyuVyn0/F4PHyPhdTUVPh1Nuw3ent7bT8aU1JSoD2cQoPpstnsqKgotVrtqL1Sqezv71er1RUVFQAArVZrNBo7OzvxeXGFQkEsHREb/SQAICsrC24cQYrBmj4ktm3bBt/hiESi2NjYlpYWG8a0GAwG4mfvdnWzJgUeA60UHucPzguC+0ZHRwc+uPFcHVyKk62PCUxfTCuVyv/8z/88ePDgSy+99MYbb0xOTn711VcOF+hXYGU0NzcDANhs9pkzZ8rLy3fs2IEbvPDCC42Njd3d3UqlEr7ygwiFwqRfgb8VBAKByWQidsFarVYoFFoLd8gY//PDDz/09fXF3dGuPdJh1sPlcnft2pWdnX358uXs7OyCggKTyeRoLTBMi8PhDA8PE0NMJhPxB1tERMSRI0du3bolFouzsrKcKxnC5TjkD1wuNz8/v62tzdfX98SJE/AhR1yjwufzSe4BACgsLIyOji4vL7958ybtfDb0H7jWiAmkfUw4HI7tLyBp7WHme3t7lUqlUqnU6/XFxcXLly/HzailAwz6SRhuLQZafWzg6+tLHdPbhcPh0N5lTbepSQE81h/s3mhXkCdPnhBv9HQdXMrUWh+jmBna9ff3BwQE4GP85cuX9/f3O5QSkZCQkLi4uLKyst27d9NOisJtt5hEFRkZiWFYS0tLfHw8AEClUg0MDERFRfH5fGp4fHz8pUuXGBrjQ2+z2fzhhx9mZ2fjWbWWKNJhajp4OtHR0ePj4yaTyaFaYC5USEjInTt3xsbG8GFiS0sL7Y/gw4cPP/vss42NjTAhxNPJFBpOQEBAbGysWq0OCQkBACgUCnyIKZfLia9EYcjp06cfPnwIJxvsOgOPx8Mfnw6NrhwFPp8yMzOtZYlaOsCgn7QdA66PjWKaTCb8ur29fePGjY4VDICAgACHNotgLgW+5pWU3CzwByJ2BQkODqaOxmafDq7DrsJMYDrLuGrVqr6+vp9++gkAYDAYmpubIyIippwqAODDDz/UaDTx8fG3b982GAydnZ1NTU127zKZTKpfgZtLr1+/fvXq1UeOHNFqtQaDoaCgYM2aNQkJCbThr732GnPjhIQEmOilS5f0ej1xlYlte6TDFHTwLLq7u6VSqUqlAgAoFIqzZ89u2rQpICDAoVpgLlRubq5er8/Kyurt7dXr9R9//PHly5dLS0uplhKJZM2aNfC9A+KphaE/XLlyRSqVKpVKs9l88+bN+vr6tLS08PDwuLi4kpKSvr6+sbGxs2fPymQyuDgJB053wafd9evX8e8nrCEWi6urqzUaTXd3d1paGovFms7SEggLC9u0aZNUKoWjK4PBUFtbSzQglQ4PZ95P2tDHRjHff//96upqaN/d3b1r1y5StHDDfCipTqfTarWk4UtUVJRcLneFFPjszOzzByJ2BQkLC4MXs1sH12FXYSYwHTKKRKK///u/P336dGlpaUlJyW9/+1snpzHWr1/f2NgoEomSkpL8/PxWrlzZ0NBQUlICAGCz2bRfxvn7+9fV1T3zK3D6jc1mX7t2TaVSLVmyRCAQdHd319TUcDgc2nBvb2/mxvjULnwJEhQU9P9Us2mPdJiCDp6FQCBobm4ODw/ncDiRkZGhoaFXrlwBDtaCDaFIVR8WFnbjxo3m5ubg4OBFixYdPny4oqIC3wGOZJydnX3t2jXqp4KIpweG/iAWi+vr61etWrVgwYK0tLT9+/fv3bsXAFBVVQUAWL58OY/HO3ny5I0bN+APeNwTYmJicnJykpKSgoKC4OdxMJzoKmw2m8ViwT+lUimbzRaJRGKxODc319fXl9YeEN7/0vZOTOyrqqosFotQKAwICBCJRLAsJANYOni4EcRGP0nNjDV9rBUTAJCamlpaWsrlcktKSioqKqgzvqWlpUuWLHnxxRcBAHFxcUuWLCGtd5RIJPgolqFutFKQDAAAK1eu9FB/wHFGEGrkjuqAx+B2HVyKM63PARzaEGhyclKr1Y6Pjzt0Fw7p9BfIyMhIV1fXkydP8BC4Q7Wjkff399Pup0Ub7pDxyMiItf3ArMVjG9r9CJEOHofRaOzq6iLu/oXjkLDU/QhHR0dppf7ll1+IHgKh+omHqjp39mXEofUH0qkng4ODPT09VH8wGo2kcJLbDA0N9ff3Yxg2Pj4Ow0kGJD95/PgxDMFd2oY9be/E3B62HaIB6V6j0fjgwQPqDojUfpJ6Lx4DrW7UYsJN+yYnJ7u6uoxGIzYl4Cs4uHGgQ7qRpKCWRafT4aeeYB7lD9Zy4pAg+O3E018c0oGUATfqMC1Y25fRmdbHfF9GFoZh0zXItUtdXR38lTbHaWtrCw8Pd+jL9lkJ0gGiVCr5fP4c+WzIBkgHCNxcxvYHm3OBGdMhJiYmLS1NKpU6GU9ycnJMTMyJEyemJVc4ZrNZqVTiu6rNWZAOELPZ3NPTs2rVqmmM89adu4kJzzKxRMfsIBAIBGLuEhkZSVxvM2WOHj2KFoQgZjezf9kZAoFAIBDWgAuRnWfjxo1T+NQagfAgWHAFxszQ1dXlzJkxCAQCgUAgEHMZFovl5EEqJHr6NQxfTHOmZUKeIXYP4ZkjKJXKFStWeHl5uTsjbgbpAOnp6fHx8YFbss9lkA4QnU5nNBqDg4PdnRE3g3SAjI+Pd3V1oUcn0gEyPj6uVqundy1jT7+GoSVneseqtsEwDH3rAPHy8kJSAKQDAAAAFovF4XCQDkgHCIfDYbFYSAekAxGkAwTp4F7Q5y8IBAKBQCAQCDugISMCgUAgEAgEwg5oyIhAIBAIhLNYLBaDweDuXCAQLsT9m+yo1WqVSuXr6xsZGQmPzIKneQIAuFxuQEAAbomHQ7y9vfFdfy0Wi0wmM5lM0dHRfD4ft6ENd8gYADA2NqZQKEwmU2RkJBN7pMMcQa/Xy+VygUAQERFBPO3NUWFxtFotdV83X1/fiYkJAADRB0wmk0ajgSeq4f7A4XCEQqG7jqtCOArDhjM8PCyXy729vaOjo22fxpmSkrJly5bc3FwXZNblMMw8tZ+cSSYmJtrb26OiomhbWXl5eXV19Z07d5xJwq4Oc8QfiMCCZGRkEAOZ6wBmkRTux6GTatrb22tra5uamqwdHGcb0oGBDx8+3Lx5M4vFWrx4sZeXl5+f37FjxzAMe/XVV/HsLV269KOPPoL2xHAAwIoVK2B4R0fH6tWrFy1aFBgY6OPjc/XqVRvhDhljGPb1118vW7YsODj4mWeeWbBgwf/6X//Ltj0TSAflIR08kaKiovnz5y9btmzevHlr167Fj31zVFiMcFDe6tWrqS10586d27dv3759OzH18+fP+/j4wGuiPwQGBr733nszUHxXMKcODLThD8QDAz/77DM/P7/AwMCFCxcGBwf39PTYiBMefOfafLsMauZJByda6ydnjO+++27dunUAAOoxhhiGTU5Orly58uLFi06mQtWBeFDe3PEHIrAgU9YBm0VSYNYPDHQG5gcGOjAhcfny5atXr1oslps3b1ZWVjK/kRaZTCaRSLy9vVUqlVarNZlM1dXVbW1tAACTyfTyyy9jGDY4OJiRkZGTk9PQ0ADDX3rppfFf6ezshFGlp6eHhISo1eq+vr6srKzMzEydTmct3CFjAEBubm5qamp3d3dnZ2dJSUleXh6c8rFmj3SYmg4eB5fLVSqVvb29crlcqVSeOnUKhjsqLBGZTDYyMjIyMrJhw4acnBx4ffnyZds5wf1kaGiooKBg3759t2/fdkGJEdMJE38wm82ZmZkHDx5Uq9U6ne7kyZNzdgrZRj85M1RWViYnJ0skEmsGTU1NKpUqNTXVdXlA/gBBOrgThkPLnp6e119/3Ww2Yxg2Ojqan5//008/OTqSJc4yPv/882vXrqWdrdy5cyd8BGIYNjk56efnd+jQIVI4zg8//AAA+Oabb+Cfjx8/BgBcvXqVNvzMmTPMjeHv/vnz5+PTe3/605/mzZs3MjJiw54JxNk1pAND46eZtWvXvvLKK5iDtUCcgCTNrsXFxb3++uv4n7ZnGUl+4uXl9e677057GWeAuTPLaNsf8Nm1jo4OAMBXX31FjeHRo0fHjh3bt2/f+fPnR0dHYSBxKmVwcPD8+fMHDhx455138FmxTz/99NGjR99++21xcfG5c+eGhoZg+MWLFx88eACvR0dHT58+DSsC2t+9e7eoqOjcuXPwN8wHH3xw6NCh+/fvU3PF0P77778/dOhQUVFRXV0dHkjMPCxdTk4OnnMb/SSe7ueff15UVAQnnGj1sVHMH3/88f79+8XFxW+//TatE9bV1Q0MDNy/fx9YmWV88803N23a5JAOtFKQ5sMePXr01ltvwdk1j/MHHGcEwSizjI7qQJTCvTpMC9ZmGZ1pfdM/y9jb2xsUFDR//nwAgLe3d0REhDPHxvT19X399deFhYV2fxxYLBaLxSIQCKwZtLe3s1is2NhY+KdQKAwMDFQoFLThzc3NzI0VCgUAYNeuXWVlZa2trRqN5siRI3v37uVyuTbskQ5T0MGjaWpqam9vT05OBg7WgiuEkslk4+PjUVFR0x4zYhph6A+hoaFLly49ePAg/iYBcv369ZiYmNbW1omJibKyMolEQl0CK5FIamtreTxeQ0NDdHQ0jOHUqVPZ2dm7du3S6XRlZWVbtmyBxsePH6+vr4fXJpPpwIEDMDPQPiMjQ6fTlZSU7NmzJyEhob6+/t69exKJpLW1lZQoE/vq6mqJRGIwGLhc7o4dO/DpeWrpJicnYYjdfhKmu3//frlc3tnZaU0fG8XMzc1NS0szGAwXLlx47rnnqF+xJCUlERcTU2lqahKLxcx1YC6FTCaDf3qcP5AqyHlBPF0HlzItrc8uTJcP+/v7q9XqsbExb29vi8Wi0WicOTamvb0dAAAfbBaLRSqVWiwWAEBQUFB+fj5uZjKZpFLpxMRESkoKDLl161Z0dDS8Pnv2bGJiokaj4fF4xNWvAoFAr9fThg8MDDA31uv1AIDKysq8vLzY2Fgej7d79+73338fAGDDHukwBR08EY1Gk5mZqdfrW1pajh49mp6eDqwL4mqhWltbc3NzdTpdfX39vn37tm7dOl0xI1wBQ3/gcDg1NTU7duyIjIxMT08/cuRISEiI2Wzeu3dvYWHh0aNHAQClpaXh4eGVlZXEHgMA0NDQAM/RsVgsISEhtbW1eXl5AIDh4eHW1lY+n5+enr5582a7J3KZTKbm5mY+ny8Wi994441z587l5eVZLJbIyMiqqqqYmBiH7KOiovLz8+GzDQCwfv369PT0vLw8fH9mYuk0Gg0cujHpJzs7O5ubm4VCodlsDgsLs6sPCa1W29raKhAI1Gp1aGhoVVWVo59KKJXKxMRE5rqNjY3RSoHHgEtRWlqqVCqBZ/qD84LgvjE6OgovPFoHl+Jk62MC0yFjeHj4smXL3n333XXr1ikUipGRERaLNZUyEcAPnjGbzWNjYzKZTC6Xwwr+4osvBAKBwWAICwurqanBKy86Oho6BAAA1srY2BgpWjabzePxaMPnzZvH3JjH4wEAmpubv/zyy8zMzOHh4U8++SQmJiY3N9eG/RRAOngisHMxGAyhoaGHDx/m8/l79+51qBamUSgejycSiRQKBZfLzczMnK5oES6CuT/Ex8crFIrKysrjx4/X1NTAr3H7+/vhTxQAgEgkSkxMbGxsJD0a4Y98uVyu0+l4PB6+x0Jqair8Ohv2G729vbYfjSkpKdAeTqHBdNlsdlRUlFqtdtReqVT29/er1eqKigoAgFarNRqNnZ2d+Ly4QqEglo6IjX4SAJCVlQU3jiDFYE0fEtu2bYPvcEQiUWxsbEtLiw1jWgwGA/Gzd7u6WZMCj4FWCo/zB+cFwX2jo6MDH9x4rg4uxcnWxwSmQ0Y2m11YWPjtt98+fvz4b/7mb27durV48WKHC/QrsDKam5vFYjGbzYZL68rLy48cOQINXnjhhfLycl9f3+XLlxNvFAqFSUlJxBCBQGAymeD0JwzRarVCoZA2fMOGDcyNhUKhRqPZsmXLiRMn4C/OCxcuvPbaazExMdbskQ5T08ET4XK5u3btAgBkZ2cLBIKCgoKMjAyHaoG5UBwOhzQFZTKZiEd9RkREQJ9JTk7OyspqbGx0tngIV+KQP3C53Pz8/N27d8fExJw4cSIrKwvGgBvw+Xzqi9TCwsJPPvkkISHB39+fdj4bJg0/YmMCaR8TDocDp/ocsodP6N7eXjzDxcXFxM4NGpBW4NjtJwEA+Dtragy0+tjA19eXOqa3C4fDob3Lmm5TkwJ4rD/YvdGuIE+ePFm2bBn+p6fr4FKm1voYxczcdN68efB7sYmJiT/+8Y9/93d/51BKREJCQuLi4srKynbv3k07KQq33WISVWRkJIZhLS0t8fHxAACVSjUwMBAVFcXn86nh8fHxly5dYmgcFRV17969X375Bf/hkpmZmZeX19LSsnHjRlp7pMPUdPB0oqOjx8fH4Y6VzGuBuVAhISF37twhjjBaWlpofwQfPnz42WefbWxshAkhnk6s+YmNWwICAmJjY9VqdUhICABAoVDgQ0y5XE58JQpDTp8+/fDhQzjZYNcZeDwe/vgcHh6eYqkYAJ9PmZmZ1rJELR1g0E/ajgHXx0YxTSYTft3e3r5x40bHCgZAQECAQ5tFMJcCX/NKSm4W+AMRu4IEBwdTR2OzTwfXYVdhJjjwaTq+kuDatWurVq1ycjLpww8/1Gg08fHxt2/fNhgMnZ2dTU1Ndu8ymUyqX+nr6wMArF+/fvXq1UeOHNFqtQaDoaCgYM2aNQkJCbThr732GnPjhISEiIgIFot14cIF6KlXrlwxm80bN260Zo90mLIOnkV3d7dUKlWpVAAAhUJx9uzZTZs2BQQEOFQLzIXKzc3V6/VZWVm9vb16vf7jjz++fPlyaWkp1VIikaxZswa+d0A8tTD0hytXrkilUqVSaTabb968WV9fn5aWFh4eHhcXV1JS0tfXNzY2dvbsWZlMBhcn4cDpLvi0u379Ov79hDXEYnF1dbVGo+nu7k5LS3N+0ZE1wsLCNm3aJJVK4ejKYDDU1tYSDUilw8OZ95M29LFRzPfff7+6uhrad3d3wxcIROCG+VBSnU6n1WpJw5eoqCi5XO4KKfr7+2HI7PMHInYFCQsLgxezWwfXYVdhJjgwZCwrK3vrrbfeeOMNrVbr/Hqp9evXNzY2ikSipKQkPz+/lStXNjQ0lJSUAADYbDbtl3H+/v51dXXP/AqcfmOz2deuXVOpVEuWLBEIBN3d3TU1NRwOhzbc29ubuTGHw4mKiqqoqCgrK+Pz+Xw+v6CgoKKiIjY21po90mHKOngWAoGgubk5PDycw+FERkaGhoZeuXIFOFgLNoQiVX1YWNiNGzeam5uDg4MXLVp0+PDhiooKfAc4knF2dva1a9eonwoinh4Y+oNYLK6vr1+1atWCBQvS0tL279+/d+9eAEBVVRUAYPny5Twe7+TJkzdu3IiIiAAET4iJicnJyUlKSgoKCoKfx8Fwoquw2WwWiwX/lEqlbDZbJBKJxeLc3FxfX19ae0B4/0vbOzGxr6qqslgsQqEwICBAJBLBspAMYOng4UYQG/0kNTPW9LFWTABAampqaWkpl8stKSmpqKigzviWlpYuWbLkxRdfBADExcUtWbKEtN5RIpHgo1iGutFKQTIAAKxcudJD/QHHGUGokTuqAx6D23VwKc60PgdgvhvQ+Pi4RqPBtyyaAqTTXyAjIyNdXV1PnjwhJjQ+Pu5o5P39/bT7adGGO2Q8OTn5+PFj5vZ2od2PEOngcRiNxq6uLuLuXzgOCUvdj3B0dJR2C7pffvmF6CEQqp94qKpzZ19GHFp/IJ16Mjg42NPTQ/UHo9FICie5zdDQUH9/P4Zh4+PjMJxkQPKTx48fwxDcpW3Y0/ZOzO1h2yEakO41Go0PHjyg7oBI7Sep9+Ix0OpGLSbctG9ycrKrq8toNGJTAu46BzcOdEg3khTUsuh0OvzUE8yj/MFaThwSBL+dePqLQzqQMuBGHaYFa/syOtP6mO/LyMIwbLoGuXapq6uDv9LmOG1tbeHh4Q592T4rQTpAlEoln8+fI58N2QDpAIGby9j+YHMuMGM6xMTEpKWlSaVSJ+NJTk6Gn2JMS65wzGazUqnEd1WbsyAdIGazuaenZ9WqVdMY5607dxMTnmViiY7ZQSAQCMTcJTIy0plthnGOHj2KFoQgZjezf9kZAoFAIBDWgAuRnWfjxo1T+NQagfAgWM6c++coXV1dzuzmiEAgEAgEAjGXYbFYxH15naenX8PwxTRnWibkGWL3EJ45glKpXLFihZeXl7sz4maQDpCenh4fHx94jNVcBukA0el0RqMxODjY3RlxM0gHyPj4eFdXF3p0Ih0g4+PjarV6etcy9vRrGFpypnesahsMw9C3DhAvLy8kBUA6AAAAYLFYHA4H6YB0gHA4HBaLhXRAOhBBOkCQDu4Fff6CQCAQCAQCgbADGjIiEAgEAoFAIOyAhowIBAKBQDiLxWIxGAzuzgUC4ULcv8mOWq1WqVS+vr6RkZHwyCx4micAgMvlBgQE4JZ4OMTb2xvf9ddischkMpPJFB0dzefzcRvacIeMYboymYzD4URHRxOXflqzRzrMEfR6vVwuFwgEERERxNPeHBUWR6vVUvd18/X1nZiYAAAQfcBkMmk0GniiGu4PHA5HKBS667gqhKMwbDjDw8Nyudzb2zs6Otr2aZwpKSlbtmzJzc11QWZdDsPMU/vJmWRiYqK9vT0qKoq2lZWXl1dXV9+5c8eZJOzqMEf8gQgsSEZGBjGQuQ5gFknhfhieEjM0NHT37l1iyI8//vjv//7vd+/eZX48DunAwIcPH27evJnFYi1evNjLy8vPz+/YsWMYhr366qt49pYuXfrRRx9Be2I4AGDFihUwvKOjY/Xq1YsWLQoMDPTx8bl69aqNcIeMMQyrq6sLDAwMDAz08/NbsWIFfmCRNXsmkA7KQzp4IkVFRfPnz1+2bNm8efPWrl2LH/vmqLAY4aC81atXU1vozp07t2/fvn37dmLq58+f9/HxgddEfwgMDHzvvfdmoPiuYE4dGGjDH4gHBn722Wd+fn6BgYELFy4MDg7u6emxESc8+M61+XYZ1MyTDk601k/OGN999926desAANRjDDEMm5ycXLly5cWLF51MhaoD8aC8ueMPRGBBpqwDNoukwKwfGOgMzA8MtD8hYTQav/zyy9LS0nv37uGBX3311YcffmixWP785z+///77diOhIpPJJBKJt7e3SqXSarUmk6m6urqtrQ0AYDKZXn75ZQzDBgcHMzIycnJyGhoaYPhLL700/iudnZ0wqvT09JCQELVa3dfXl5WVlZmZqdPprIU7ZKzX63ft2pWVlaVWqzUaTURERFZWlu1EkQ5T08Hj4HK5SqWyt7dXLpcrlcpTp07BcIeEJcUpk8lGRkZGRkY2bNiQk5MDry9fvmw7J7ifDA0NFRQU7Nu37/bt2y4oMWI6YeIPZrM5MzPz4MGDarVap9OdPHlyzk4h2+gnZ4bKysrk5GSJRGLNoKmpSaVSpaamui4PyB8gSAd3YndQ+W//9m8ffvjhF1988Yc//AGGjI6O/uM//mN3dzeGYWazOT8////f3r3HNXWlewNfCQmEABGRmyiIiEoZREodibRFx0NHTy+Wthz1bRnHWj9KrWPVarUctL7WWmut7VHbY3WmYzuO9TaOdaw6hdHWqoNIkaJFwYgEKMQAIQYSArm9f6zpfjO57oRAAv6+fyXLxdrPfrKys1x777WrqqrYjE/NZxkfffTRCRMmWD9T3GQyzZkzh/4Emkwmg8EwZMiQdevWWZQzbty4QQj55z//Sd/evXuXEHLo0CGb5du3b2df+dChQ6dPnyaEtLW10fKioiJCyE8//WSvPpskmP59dg15YFnZl02YMOGFF14wufgpmE9AWsyuZWRkvPLKK8xbx7OMFv2Ez+e/++67Ht/HfnD/zDI67g/M7NqtW7cIIefOnbNuobq6+q233lqxYsXevXu7u7tpoflUSnt7+969e1977bV33nmHmRX705/+VF1dffny5TVr1uzcubOjo4OWf/bZZ1evXqWvu7u733//ffpB0PoXL15cvXr1zp076f9hPvroo3Xr1l25csU6Kpb1r127tm7dutWrVxcVFTGF5sHTvVu8eDETuYPjJLPdI0eOrF69mk442cyPg928ffv2lStX1qxZ8/bbb9vshEVFRS0tLVeuXCF2ZhnfeOONKVOmuJQHm6mwmA+rrq5+88036ezagOsPjN4kxGQ1y+hqHsxT4d08eIS9WcbefPs8OcuYk5Pz8ssvmz+15fbt2yKRiK6wGhAQMGHChOrqapfGqU1NTd99992qVauc/ufAaDQajcbQ0FB7FW7evMnhcCZNmkTfRkZGRkVF1dTU2CwvKytjX7mmpoZeWMYEmZSURAiRSCT26ruUBORhcCgtLb158+bMmTOJi59CXySqsrJSp9MlJyd7vGXwIJb9IT4+fvjw4a+//jpzJoE6fvx4WlpaRUWFXq/ftGlTZmam9SWwmZmZp06dEgqFFy5cSElJoS1s27Zt0aJFc+fOVSgUmzZtevzxx2nlzZs3FxcX09cajea1116jwdD68+fPVygUa9eunTdvXlZWVnFx8aVLlzIzMysqKiw2yqb+0aNHMzMzVSqVQCCYPXs2Mz1vvXcGg4GWOD1O0u2uXLmyqqqqtrbWXn4c7GZ+fn5ubq5Kpfr0008feeQR67tYsrOzzS8mtlZaWpqamso+D+xTUVlZSd8OuP5g8QH1PiEDPQ99yiPfPqfcuXy4paXFfAQ5bNiw9vZ2l1q4efMmIYT+sBmNxsLCQqPRSAiJiYlZtmwZU02j0RQWFur1+lmzZtGSs2fPpqSk0Nc7duyYPn26XC4XCoXmV7+GhoYqlUqb5S0tLewrK5XK9PR0Pp+/devWDRs2aLXaEydOkJ/vPLBZ36UkIA8DmlwuX7BggVKpLC8v37hxY15eHi10KbGeCqaioiI/P1+hUBQXF69YseLJJ5/0VMvQF1j2Bx6Pd+zYsdmzZyclJeXl5W3YsCEuLk6r1S5ZsmTVqlUbN24khBQUFCQmJu7Zs8f8iEEIuXDhAn2OjtFojIuLO3Xq1NKlSwkhnZ2dFRUVIpEoLy9v6tSpTp/IpdFoysrKRCJRamrqq6++unPnzqVLlxqNxqSkpAMHDqSlpblUPzk5edmyZfS3jRCSnp6el5e3dOlSZn1m872Ty+V06MbmOFlbW1tWVhYZGanVahMSEpzmx0Jra2tFRUVoaKhMJouPjz9w4ICrt0pIJJLp06ezz1tPT4/NVDAtMKkoKCiQSCRkYPaH3ieE6Rvd3d30xYDOQ5/q5bePDXeGjFqt1nwbAoGAfoFdxdx1q9Vqe3p6Kisrq6qq6Ad88uTJ0NBQlUqVkJBw7Ngx5sNLSUmhHYIQQj+Vnp4ei2a5XK5QKLRZ7ufnx76yUCiMi4vbt2/f8uXLt27d6u/vP23aNEKIg/quZoBCHgYienBRqVTx8fHr168XiURLlixx6VPwYKKEQmF0dHRNTY1AIFiwYIGnmoU+wr4/iMXimpqaPXv2bN68+dixY/Ru3ObmZvpfFEJIdHT09OnTS0pKLH4aw8LCZDJZVVWVQqEQCoXMGgs5OTn07mx63GhsbHT80zhr1ixan06h0e1yudzk5GSZTOZqfYlE0tzcLJPJdu/eTQhpbW1Vq9W1tbXMvHhNTY353plzcJwkhCxcuJAuHGHRgr38WHj22WfpOZzo6OhJkyaVl5c7qGyTSqUyv+3dad7spYJpwWYqBlx/6H1CmL5x69YtZuAxcPPQp3r57WPDnYtGBQKBRqNh3mo0GgcnTG2iH0ZZWRkhhMvlbt++fdeuXbNnz2YqTJs2raSkpL6+XiKR0FN+VGRkZPbP6P8VQkNDNRqN+SG4tbU1MjLSXrlLlQkhzz//PL3no7Ozc/PmzYSQcePGOaiPPLiRh4FIIBDMnTt30aJF+/fvX7Ro0fLly+kXwdXEssHj8To7O81LNBqN+TpH48aN27Bhw9mzZ1NTU5k7k8BnudQfBALBsmXLrl+/HhwcvGXLFvojZ37IFYlEFt2DELJq1aqUlJRdu3adOXPG5nw27T90/SY2LNYx4fF4jmcKbNanwTc2NkokEolEolQq16xZM3LkSKaa9d4RFsdJYnbZDMv8OBAcHGw9pneKx+PZ/Ct7eXMvFWTA9genf+g0IW1tbeZ/ONDz0Kfc+/axatmNaKKjo5ubm41GI/2WNjY2PvTQQy61EBcXl5GRsWnTpueff97mpChddotNU0lJSSaTqby8XCwWE0Lq6upaWlqSk5NFIpF1uVgs/vzzz1lWZobeXC6XDssOHjw4ceLE6Ohoext1KQnIw6CRkpKi0+k0Go1LnwL7RMXFxZ0/f76np4cZJpaXl9v8T/D69esffvjhkpISuiHwTW58ccLDwydNmiSTyeLi4gghNTU1zBCzqqrK/JQoLXn//fd/+OEHOtngtDMIhULm59Ol0ZWr6O/TggUL7IVkvXeExXHScQtMfhzspvkkyM2bNydPnuzajhESHh7u0mIR7FPBXPNqsblB0B/MOU1IbGys9Whs8OWh7zjNMBvuzDKOGTPGz8+vtLSUEPLTTz/dvn3bjTP3H3/8sVwuF4vF33zzjUqlqq2tpQ06ptFo6n7W1NRECElPTx8/fvyGDRtaW1tVKtXy5csfeOCBrKwsm+UvvfQS+8pZWVlGo7GsrEyv1+v1+k8//fTDDz+kp4Pt1Xc5lcjDwFRfX19YWFhXV0cIqamp2bFjx5QpU8LDw136FNgnKj8/X6lULly4sLGxUalU/v73v9+/f39BQYF1zczMzAceeICedwCfxbI/HDx4sLCwUCKRaLXaM2fOFBcX5+bmJiYmZmRkrF27tqmpqaenZ8eOHZWVlfTiJAad7qK/dsePH2fun7AnNTX16NGjcrm8vr4+NzeXw+F4cm/NJCQkTJkypbCwkI6uVCrVqVOnzCtY7B1Tzv446SA/Dnbzww8/PHr0KK1fX18/d+5ci2bpgvk0pQqForW11WL4kpycXFVV1RepaG5upiWDrz+Yc5qQhIQE+mJw56HvOM0wG+4MGf38/PLz8+nHtnXr1vnz5wcHB7vaSHp6eklJSXR0dHZ29pAhQ8aMGXPhwoW1a9cSQrhcrs0748LCwoqKikb/jE6/cbncw4cP19XVRUREhIaG1tfXHzt2jMfj2Sz39/dnX5nH42m12lmzZgkEAqFQuHHjxn379tEbUOzVdyOZyMNAFBoaWlZWlpiYyOPxkpKS4uPjDx48SFz8FBwkyuKjT0hIOHHiRFlZWWxs7NChQ9evX797925mBTiLyosWLTp8+LD1rYLgO1j2h9TU1OLi4rFjxwYGBubm5q5cuXLJkiWEkAMHDhBCRo4cKRQKt27deuLEiXHjxhGznpCWlrZ48eLs7OyYmBh6exwtN+8qXC6Xw+HQt4WFhVwuNzo6OjU1NT8/Pzg42GZ9Ynb+1+bRiU39AwcOGI3GyMjI8PDw6Ohoui8WFeje0YcbUQ6Ok9bB2MuPvd0khOTk5BQUFAgEgrVr1+7evdt6xregoCAiIuKxxx4jhGRkZERERFhc75iZmcmMYlnmzWYqLCoQQsaMGTNA+wOjNwmxbtzVPDAteD0Pfao33z4XuLMukMlkMpl0Op1cLjdf+sgpi6e/UF1dXVKplFnzj7bM/okyjObmZpvradksZ1/ZYDA0NDS0t7e7tFHHbK5HiDwMOGq1WiqV2vwKuPQpWK9H2N3dbXMJunv37pn3EMq6nwzQrN4/6zIybPYHi6eetLe3NzQ0WPcHtVptUW7RbTo6Opqbm00mk06no+UWFSz6yd27d2kJ06Ud1Ld5dGJfn353zCtY/K1arb569ar1CojWx0nrv2VasJk3692ki/YZDAapVKpWq01uuXPnDiGELhzoUt4sUmG9LwqFgnnqiWlA9Qd7kbiUEObPzZ/+4lIeLALwYh48wt66jL359rFfl5FjMpk8Nch1qqioiP4v7T53/fr1xMREl+5sH5SQB0oikYhEovvktiEHkAeKLi7j+IbN+0G/5SEtLS03N7ewsLCX7cycOTMtLW3Lli0eiYqh1WolEgmzqtp9C3mgtFptQ0PD2LFjPdjm2fMXp2c9zKYmHrMDAAD3r6SkpJiYmN63s3HjRlwQAoPb4L/sDAAAwB56IXLvTZ482Y1brQEGEA69AqN/SKVS88fGAAAAAAB7HA7HfF3e3mtolrM8Mc3zyIQ8S04fwnOfkEgko0aN4vP53g7Ey5AHqqGhISgoiK55eT9DHiiFQqFWq2NjY70diJchD5ROp5NKpfjpRB4onU4nk8k8ey1jQ7OcZU2eZ8eqjplMJtzrQPH5fKSCIA+EEEI4HA6Px0MekAeKx+NxOBzkAXkwhzxQyIN34fYXAAAAAHACQ0YAAAAAcAJDRgAAgN4yGo0qlcrbUQD0Ie8PGWUyWUlJyfXr1/V6PS3RarWNjY2NjY2tra3mNZlySi7//xdsGo3GioqKS5cuWXxjbZbbq0wI0ev1169ft3h4qEuNuw15GHCUSuWlS5eqqqqYj4xyO1Gtra2NVpRKZWtrq0UfoA8Zp6+Z/iCTySw+MvBlLL84nZ2dpaWlFRUVFt3M2qxZswbu48VZBm99nOxPNg+MjF27dj355JO93ITTPNwn/cGczR1hnwd7LYA7WD4lpqOj4+LFi2wKHbB4YOAPP/wwdepUDoczbNgwPp8/ZMiQt956y2Qyvfjii0x4w4cP/+STT2h983JCyKhRo2j5rVu3xo8fP3To0KioqKCgoEOHDjkot1fZZDJ9//33Dz74ICHE/ClVLjXOksWD8pCHgWj16tUBAQEjRozw8/ObMGEC89g3NxLFPChv/Pjx1t/QOXPmPPfcc88995z51vfu3RsUFERfm/eHqKioDz74oB92vy/cVw8MdNAfzB8Y+MUXXwwZMiQqKiokJCQ2NrahocFBm/TBd30bd5+xDt7iwYn2jpP9xuaBkWEwGMaMGfPZZ5/1civWeTB/UN790x/M0R1xOw+mQZQKk/0HBvYG+wcGOp9lVKvVX3/9dUFBwaVLlxwXuqSysjIzM9Pf37+urq61tVWj0Rw9evT69euEEI1G8/TTT5tMpvb29vnz5y9evPjChQu0/KmnntL9rLa2ljaVl5cXFxcnk8mampoWLly4YMEChUJhr9xe5T179sycOTMzM9MiTpcaRx7czsOAIxAIJBJJY2NjVVWVRCLZtm0bLe9NoiorK7u6urq6un75y18uXryYvt6/f7/jSJh+0tHRsXz58hUrVnzzzTd9sMfgSWz6g1arXbBgweuvvy6TyRQKxdatW7lc758X8goHx8n+Ye/AyCgtLa2rq8vJyem7GNAfKOTBm5wOKv/6179+/PHHJ0+efO+99xwXOmU+y/joo49OmDDB+pniJpNpzpw59CfQZDIZDIYhQ4asW7fOopxx48YNQsg///lP+vbu3buEkEOHDtks3759u83KJpOpqKiopaXlypUrxOw/kS41zn6CzXx2DXlgWdmXTZgw4YUXXjC5myjr2bWMjIxXXnmFeet4ltGin/D5/Hfffdfj+9gP7p9ZRsf9gZldu3XrFiHk3Llz1i1UV1e/9dZbK1as2Lt3b3d3Ny00n0ppb2/fu3fva6+99s477zBf5D/96U/V1dWXL19es2bNzp07Ozo6aPlnn3129epV+rq7u/v999+nHwStf/HixdWrV+/cuZP+H+ajjz5at27dlStXrKNiWf/atWvr1q1bvXp1UVERU2gePN27xYsXM5E7OE4y2z1y5Mjq1avphJPN/DjYzdu3b1+5cmXNmjVvv/22zU5o88Bo7o033pgyZYpLebCZCov5sOrq6jfffJPOrg24/sDoTUJMVrOMrubBPBXezYNH2Jtl7M23z5OzjDk5OS+//LLFU1tsFrLX1NT03XffrVq1yul/DoxGo9FoDA0NtVfh5s2bHA5n0qRJ9G1kZGRUVFRNTY3N8rKyMpuVCSHZ2dnh4eG9aZy24xLkYRAoLS29efPmzJkziQ8kqrKyUqfTJScne7xl8CCW/SE+Pn748OGvv/46cyaBOn78eFpaGr2Ka9OmTZmZmdaPNs7MzDx16pRQKLxw4UJKSgptYdu2bYsWLZo7d65Codi0adPjjz9OK2/evLm4uJi+1mg0r732Gg2G1p8/f75CoVi7du28efOysrKKi4svXbqUmZlZUVFhsVE29Y8ePZqZmalSqQQCwezZs5npeeu9MxgMtMTpcZJud+XKlVVVVbW1tfby42A38/Pzc3NzVSrVp59++sgjj1hfXWrzwGiutLQ0NTWVfR7Yp6KyspK+HXD9weID6n1CBnoe+pRHvn1OeecZ0zdv3iSE0B82o9FYWFhILyiOiYlZtmwZU02j0RQWFur1+lmzZtGSs2fPpqSk0Nc7duyYPn26XC4XCoU83v/fkdDQUKVSabO8paXFZmV7cbrUuIN2kIfBRy6XL1iwQKlUlpeXb9y4MS8vj3gvURUVFfn5+QqFori4eMWKFb2/Bh/6FMv+wOPxjh07Nnv27KSkpLy8vA0bNsTFxWm12iVLlqxatWrjxo2EkIKCgsTExD179pgfMQghFy5coM/RMRqNcXFxp06dWrp0KSGks7OzoqJCJBLl5eVNnTrV6RO5NBpNWVmZSCRKTU199dVXd+7cuXTpUqPRmJSUdODAgbS0NJfqJycnL1u2jP62EULS09Pz8vKWLl3KrM9svndyuZwO3dgcJ2tra8vKyiIjI7VabUJCgtP8WGhtba2oqAgNDZXJZPHx8QcOHMjPz3dQ35pEIpk+fTr7vPX09NhMBdMCk4qCggKJREIGZn/ofUKYvtHd3U1fDOg89KlefvvY8M6QkWIePKPVant6eiorK6uqqugHfPLkydDQUJVKlZCQcOzYMebDS0lJoR2CEEI/lZ6eHotmuVyuUCi0We7n52ezsr0IXWrcQTuOIQ8DET24qFSq+Pj49evXi0SiJUuWeCtRQqEwOjq6pqZGIBAsWLDAU81CH2HfH8RicU1NzZ49ezZv3nzs2LHz588TQpqbm+l/UQgh0dHR06dPLykpsfhpDAsLk8lkVVVVCoVCKBQyd9zn5OSIRCLy83GjsbHR8U/jrFmzaH06hUa3y+Vyk5OTZTKZq/UlEklzc7NMJqO3r7a2tqrV6traWmZevKamxnzvzDk4ThJCFi5cGBkZad2CvfxYePbZZ+k5nOjo6EmTJpWXlzuobJNKpaI7ziYPhBB7qWBasJmKAdcfep8Qpm/cunWLGdwM3Dz0qV5++9jwzkWj9MMoKysjhHC53O3bt+/atWv27NlMhWnTppWUlNTX10skEnrKj4qMjMz+Gf2/QmhoqEajMT8Et7a2RkZG2iu3WWgvTlcbRx7cy8NAJBAI5s6du2jRov379y9atGj58uUajaaPEsXj8To7O81LNBqN+aM+x40bt2HDhrNnz6ampi5cuLB3ewZ9zqX+IBAIli1bdv369eDg4C1bttAfOfNrVEQikUX3IISsWrUqJSVl165dZ86csTmfTfsP+6VqzOdE6VvHKzrZrE+Db2xslEgkEolEqVSuWbNm5MiRTDXrvSMsjpO03F4LNvPjQHBwsPWY3ikej2fzr+zlzb1UkAHbH5z+odOEtLW1mf/hQM9Dn3Lv28eqZU+GyVpcXFxGRsamTZuef/55m5OiwcHBSUlJbJpKSkoymUzl5eVisZgQUldX19LSkpycLBKJrMvFYvHnn39uXdkjjbtxARnyMDikpKTodDqNRtNHiYqLizt//nxPTw8zTCwvL7f5n+D169c//PDDJSUldEPgm+z1Ewd/Eh4ePmnSJJlMFhcXRwipqalhhphVVVXmp0Rpyfvvv//DDz/QyQannUEoFDI/ny6NrlxFf58WLFhgLyTrvSMsjpOOW2Dy42A3NRoN8/rmzZuTJ092bccICQ8Pd2mxCPapYK55tdjcIOgP5pwmJDY21no0Nvjy0HecZpgNr92a/vHHH8vlcrFY/M0336hUqtra2tLSUqd/RVcwppqamggh6enp48eP37BhQ2trq0qlWr58+QMPPJCVlWWz/KWXXrJZmRCi1WpbW1tp/1AoFK2trUaj0aXGaTvIg3t5GFjq6+sLCwvpYto1NTU7duyYMmVKeHh4HyUqPz9fqVQuXLiQruz9+9//fv/+/QUFBdY1MzMzH3jgASxa6+NY9oeDBw8WFhZKJBKtVnvmzJni4uLc3NzExMSMjIy1a9c2NTX19PTs2LGjsrKSXpzEoNNd9Ft8/Phx5v4Je1JTU48ePSqXy+vr63Nzczkcjif31kxCQsKUKVMKCwvp6EqlUp06dcq8gsXeMeXsj5MO8uNgNz/88MOjR4/S+vX19XPnzrVo1uaB0bxCcnJyVVVVX6SiubmZlgy+/mDOaUISEhLoi8Gdh77jNMNseG3ImJ6eXlJSEh0dnZ2dPWTIkDFjxly4cGHt2rWEEC6Xa/POuLCwsKKiotE/o9NvXC738OHDdXV1ERERoaGh9fX1x44d4/F4Nsv9/f1tViaEFBQUREREPPbYY4SQjIyMiIiI8vJylxq3mApGHgax0NDQsrKyxMREHo+XlJQUHx9/8OBB4uKn4CBRFh99QkLCiRMnysrKYmNjhw4dun79+t27dzMrwFlUXrRo0eHDh61vFQTfwbI/pKamFhcXjx07NjAwMDc3d+XKlUuWLCGEHDhwgBAycuRIoVC4devWEydOjBs3jpj1hLS0tMWLF2dnZ8fExNDb42i5eVfhcrkcDoe+LSws5HK50dHRqamp+fn5wcHBNusTs/O/No9ObOofOHDAaDRGRkaGh4dHR0fTfbGoQPcuPj6eadnBcdI6GHv5sbebhJCcnJyCggKBQLB27drdu3dbz/jaPDCaV8jMzGRGsSzzZjMVFhUIIWPGjBmg/YHRm4RYN+5qHpgWvJ6HPtWbb58L3FkXyF0WT3+hurq6pFJpW1sbU0JXqHa18ebmZpvradkst1fZI407ZXM9QuRhwFGr1VKp1Hz1L4ZLibJej7C7u9vmEnT37t0z7yGUdT8ZoFm9f9ZlZNjsDxZPPWlvb29oaLDuD2q12qLcott0dHQ0NzebTCadTkfLLSpY9JO7d+/SEqZLO6hv8+jEvj797phXsPhbtVp99epV6xUQrY+T1n/LtGAzb9a7SRftMxgMUqlUrVab3HLnzh1CCF040KW8WaTCel8UCgXz1BPTgOoP9iJxKSHMn5s//cWlPFgE4MU8eIS9dRl78+1jvy4jx2QyeWqQ61RRURH9X9p97vr164mJiS7d2T4oIQ+URCIRiUT3yW1DDiAPFF1cxvENm/eDfstDWlpabm5uYWFhL9uZOXNmWlrali1bPBIVQ6vVSiQSZlW1+xbyQGm12oaGhrFjx3qwzbPnL07PephNTTxmBwAA7l9JSUkxMTG9b2fjxo24IAQGt8F/2RkAAIA99ELk3ps8ebIbt1oDDCAcegVG/5BKpW4/YxAAAADgPsfhcMzX5e29hmY5yxPTPI9MyLPk9CE89wmJRDJq1Cg+n+/tQLwMeaAaGhqCgoLokuz3M+SBUigUarU6NjbW24F4GfJA6XQ6qVSKn07kgaJ58Oz3oqFZzrImz7NjVcdMJhPudaD4fD5SQZAHQgghHA6Hx+MhD8gDxePxOBwO8oA8mEMeKOSB8lYecPsLAAAAADiBISMAAAAAOIEhIwAAAAA4gUV2AAAAAO5fZ89fZFON7ZCxs7OzsrIyMzOTvu3p6bl69apCoYiNjcVq7AAAAAAD0YQHxrGs6XzIqFarL168ePLkybi4OGbIuGXLlri4uKioqIMHD44bN27evHnuBwsAAAAA3mAwGFjWdD5kLCoqam5unjFjxo0bN5jCl156acSIEYSQyZMnr1q1as6cOQEBAe7FCgAAAAA+zvmQMScnhxBSUlJiXkjHi4SQkJAQk8mk1+sxZAQAAAAYrHp7x/TFixcTEhKCgoI8Eg0AAAAA+KBeDRkvX7781VdfLVq0yFPRAAAAAIAPcnORHaPRePjw4Tt37vz3f//30KFDPRsTAAAAAPgUN4eMn3/+uclkev311/38/DwbEAAAAAD4GndOTLe0tJSVlc2bNw/jRQAAAID7gTuzjHK5vLOz8+WXX2ZKnn766SeeeMJzUQEAAACAD2E7ZBSLxWKxmL7+xS9+sW/fvr6KCAAAAAB8TG8X2QEAAACAQQ9DRgAAAABwAkNGAAAAAHCCc+fOnX7bmFQqHTZsWL9tDgAAAAAcCA8PZ1mTFxMT06ehmJNIJImJif22OZ8lkUhGjRrF5/O9HYiXIQ9UQ0NDUFBQWFiYtwPxMuSBUigUarU6NjbW24F4GfJA6XQ6qVSKn07kgeqLPCiVSpY1ef7+/h7csGMmk0kgEPTb5nwZn89HKgjyQAghhMPh8Hg85AF5oHg8HofDQR6QB3PIA4U8UN7KA65lBAAAAAAnMGQEAAAAACcwZAQAAAAAJzBkBAAAAAAn2A4ZOzs7L126xLxVKBTnzp07ffq0RCLpm8AAAAAAwFc4HzKq1eqvv/66oKDAfMi4b98+pVKp1+t37dpVXFzclxECAAAAgJfxnNYoKipqbm6eMWPGjRs3mMLly5dzuVxCyPDhw7/88svs7Ow+jBEAAAAAvMr5kDEnJ4cQUlJSYl5Ix4uEEIPBEBwc3AeBAQAAAICvcD5ktKmjo+P27dt3794tLS2dN2+eZ2MCAAAAAJ/i5pBRpVKVlJS0t7f7+/vrdDrPxgQAAAAAPsXNIeOIESPy8/MJITU1Ndu3b9++fTse4wMAAAAwWPV2XcZx48YZDAb2z7QGAAAAgAHHnSGjSqVqaWmhr8vLywMDAyMjIz0aFQAAAAD4EHdOTHd1dW3evDkkJMRoNHK5XGbBHQAAAAAYlNgOGcVisVgspq+joqK2b99+7949Pp8fEhLSZ7EBAAAAgE9w8/YXPz+/sLAwz4YCAAAAAL4JJ5QBAAAAwAkMGQEAAADACc6dO3f6bWNSqXTYsGH9tjkAAAAAcCA8PJxlTV5MTEyfhmJOIpEkJib22+Z8lkQiGTVqFJ/P93YgXoY8UA0NDUFBQbg4GHmgFAqFWq2OjY31diBehjxQOp1OKpXipxN5oPoiD+yX1ub5+/t7cMOOmUwmPCSG4vP5SAVBHgghhHA4HB6PhzwgDxSPx+NwOMgD8mAOeaCQB8pbecC1jAAAAADgBIaMAAAAAOAEhowAAAAA4ASGjAAAAADgBNshY2dn56VLl6zLb9261dDQ4NGQAAAAAMC3OB8yqtXqr7/+uqCgwHrIqFQq33vvvYsXL/ZNbAAAAADgE5wPGYuKim7fvj1jxgzrfzpy5AiW5gYAAAAY9HhOa+Tk5BBCSkpKLMorKyvv3bs3adIknU7XF5EBAAAAgI9w8/YXpVK5f//+F1980bPRAAAAAIAPcmfIaDAYdu/e/cwzz+CsNAAAAMD9wJ0h4/79+wUCQWxsbGNjo0ql6ujoaGlp8XhkAAAAAOAjnF/LaE0mk3V2dn7yySeEkHv37hmNRj6fP3/+fA+HBgAAAAC+wZ0h45o1a5jXf/nLX3Q63dy5cz0XEgAAAAD4Fjz9BQAAAACcYDvLKBaLxWKxdflzzz3n0XgAAAAAwOdglhEAAAAAnMCQEQAAAACcwJARAAAAAJzg3Llzp982JpVKsfo3AAAAgI8IDw9nWZMXExPTp6GYk0gkiYmJ/bY5nyWRSEaNGsXn870diJchD1RDQ0NQUFBYWJi3A/Ey5IFSKBRqtTo2NtbbgXgZ8kDpdDqpVIqfTuSB6os8KJVKljV5/v7+HtywYyaTSSAQ9NvmfBmfz0cqCPJACCGEw+HweDzkAXmgeDweh8NBHpAHc8gDhTxQ3soDrmUEAAAAACcwZAQAAAAAJzBkBAAAAAAnMGQEAAAAACfYPjCws7OzsrIyMzOTvpXJZA0NDfS1v7//xIkT+yQ6AAAAAPABzoeMarX64sWLJ0+ejIuLY4aMJSUl5eXldPmDoKAgDBkBAAAABjHnQ8aioqLm5uYZM2bcuHGDKVSr1VlZWdnZ2X0ZGwAAAAD4BOdDxpycHEJISUmJeaFGowkKCuqjmAAAAADAp7C9ltGCWq0+d+7cjz/+OHr06EcffbQ/1wMHAAAAgH7m5pDx8ccf12q1nZ2dZ8+eLS0tXbNmDZeLm68BAAAABic3h4zjxo2jLx566KGVK1c2NDSMGjXKc1EBAAAAgA/p7dRgQEBASEiIVqv1SDQAAAAA4IPcHDLK5XL6ory8XKPRYIoRAAAAYBBz88T0tm3beDweIcRoNP7ud78TCAQejQoAAAAAfAjbIaNYLBaLxczbd955R6lU8vl8kUjUN4EBAAAAgK9wc5bRz89v2LBhng0FAAAAAHwTVsYBAAAAACcwZAQAAAAAJzh37tzpt41JpVKczgYAAADwEeHh4Sxr8mJiYvo0FHMSiSQxMbHfNuezJBLJqFGj+Hy+twPxMuSBamhoCAoKCgsL83YgXoY8UAqFQq1Wx8bGejsQL0MeKJ1OJ5VK8dOJPFB9kQelUsmyJq8/Hw9tMpmwHA/F5/ORCoI8EEII4XA4PB4PeUAeKB6Px+FwkAfkwRzyQCEPlLfygGsZAQAAAMAJDBkBAAAAwAkMGQEAAADACQwZAQAAAMAJtkPGzs7OS5cumZcYDIbvv//+b3/727fffqvX6/sgNgAAAADwCc6HjGq1+uuvvy4oKDAfMvb09Lz33nvnzp3z9/eXSqVarbYvgwQAAAAAb3L+jOmioqLm5uYZM2bcuHGDKfzyyy9DQ0MXLVrE5eLUNgAAAMAg53zImJOTQwgpKSlhSoxG47fffvvmm29ivAgAAABwP3A+ZLQml8tNJpNEIvnkk0/4fP706dN/+ctfejwyAAAAAPAR7gwZ792719PTU1VVtXjx4ubm5t27d4tEovHjx3s8OAAAAADwBe4MGekzBn/729/yeLyIiIisrKwrV65gyAgAAAAwWLlzMeKwYcMIIRwOh74VCoWejAgAAAAAfIw7Q0Z6Gvof//gHIaSrq6ukpCQ1NdXTgQEAAACAr3DnxDQh5MUXX/zggw/Onz/f0dExbdo0DBkBAAAABjG2Q0axWCwWi5m3w4YN27hxY3t7e0hICL20EQAAAAAGKzdnGQkhXC6XXtQIAAAAAIMb1uIGAAAAACcwZAQAAAAAJzh37tzpt41JpVKcywYAAADwEeHh4SxrcjQaTZ+GYqGnp6c/N+ebdDodj8djFra8byEPlF6v53K5eGI78kAZjUaj0cjjuX+h+eCAPFAmk0mv1/P5fG8H4mXIA9UXeWB/E3N/DxkBAAAAYMC53/8D57O++uqrrKyskJCQwMBAb8cCRKfT6fX6b7/9ViwWBwQEeDsc8Jqamprm5uapU6d6OxAAgP52v58DAgAAAACnMGQEAAAAACcwZAQAAAAAJzBkBJ+z7i87H3173vHv/+HtQPpbZWXl22+/7aDcaDTu2LFDJpNZVLBX7p6VK1fevXvX1fZ1Ot277777m9/85vz58x4JwynP7jUAADiG21+g/zQqZMU/liTFjBaPmeigWlunsrH9rrqnq98C8xHd3d1KpdJBOZfLDQsLo8srVFdXq9Xq9PR0i/Lea21tNRqN5iVs2j9//rxKpfrss89MJpNHwrCH2XHP7jUAADjmfJZRp9M1NDQwb00mU319vQcjaGpq8mBrHqHX61taWpi3BoNBLpd7MZ5B4/0zn/3fL/9X2upzn/gAkpeXR9fDP3/+fHV1tXV5X2/XHplMlpCQwOVy/fz8+i4M8u873td7DQAADOezjCaTSavVMq/r6up0Op2nNt/Q0NDV1dvJJJPJZDAYPLjiq9FobG9v53A4dEl0k8nU3t4eGRnpqfb7QYtK8eZfPwoWCJ9+8Ff/e+6wwWh45qHs2ZNnEEI+Pf/Xy7d/uKtSRInCFk7L/eXoFELIsbLiE1fPtXUqI0XDtvzX8ghRmEUJIcReg1092j+cP1Zae62rpzt5xJgl0+dGDRnGBPCfqY/+4fyx//vMK1/9cL609hoh5MA/v7oqvbll9grzgFs7lNvP7KuRSSfGjdcZ9Ex5V492V/EXpbXXQgTCZx7KfurBaUzLeZlPbT/zWadWs3Dac/HDYt4/81m7WvWfqY+8NPU5e1H13wdgR3l5+enTpxUKRWxs7Pz580NDQ7u7u7/44ouqqqqwsLCUlBSmpr3ynTt35uXlff3112VlZTweTyqVvvTSSxEREbR86NChOp3u+PHjFRUVhJAHH3zwmWeeoWO4nTt3zpgx48svv5TL5enp6XPmzKGLZluHZDNypn2b7Zw4ceLChQsmk6mlpeWVV14RCAT2Yvj1r3997NixiRMnPv744zt37vyP//iPL7/8UqFQPP3000lJSX/84x/lcvlDDz00e/ZsLpdrHduhQ4fMd/zgwYM0KkKIqzsOAAAucT7M4nA49PkcJpNJKpX29PR46oDb0NCg0Wh6Pyeh0+mkUmlCQoKnpjfo/ioUCvLzg3QG3G+Mukd7+toFfz/eP34siRkaWdV0u+R2Zagw5NcpmTuL/jw5ISVp+OiTFd98V1P+jzV/qKi/+drB9+LCoh8d91BV022VVl1W96NFiR/Xz2aD2cni33zyxvfSquFDwoX+gZ9fPHG68rszqz6hAQTyA85UXujo1qi6OhsVso4uNSGk+V6rP+/f1prXGwzP/+/qW/L6mNCIu9fbmpT/mtM1Go208afSpkpbm5b9+R0uh/OLkWNPX7sQwONfqb1uNBnrFbLrf741LDhUFBh8s/nO99KqtFEPPBiXZDOqsKAhXvgwzNy4ceOpp56Kior685//vG/fvuXLl2/ZskUkEr366qttbW0fffSRSCSiNe2VX7lyJTc3VywW19XVBQYGZmdn03+i5YSQrVu3+vn5LV68WK/X/+EPf2hpaXn55ZdpBZlMNn/+fELIO++8M2LEiKysLJsh2Yycad9mO+np6bdv39br9U888YRAIHAQQ1tb25NPPkkHeVeuXGlvb1+wYEFDQ8O2bdvGjx///PPPBwQEvP3226NHj87IyLCOzWLHmajc2HEAAHAJq5EQh8MxGo137tzp7u5mRpC9YTAYpFKppx48w+FwTCZTbW2twWDwSIOUyWRSKBRyuXzgPtFObzQcePm9v634aPG0/yKE0BtK/rH2D9v+z+q8zCczxkzs0nWX3fmx6qfbhJDEqFG/e+yFY8v+Z0xkrHWJvQbP3rj8vbRqfPSoc2v/WLzm9zNTHm7paN9/6SSt36XrLnw6//rbx5OGj94657X/+IWYEPLazN8eWbrdPM6zNy7fktePiYg9u+bTf6z5w9ioOFr+zc0r30ur/nPCI9v/z5r/ySsghBwqPUP/SWfQ789/98yqT4L8Bd163au//s3p13Y/Oi6dEHKtocZxVF70wgsvpKamikSiiRMnSiQSqVRaXV39yiuvjBgxIjU19dlnn6XV7JUzRo0aFRYWFhERkZycbL60uFQq/fHHH1esWBEXF5eQkLBixYq///3vzFM6n3vuubFjx44dO3batGk3b960GRKbvbBuZ+TIkREREcOGDUtOTm5qanIQw2OPPTZp0qQxY8bQt88888zIkSOnTJkSHx8/ceLElJSUsWPHZmRk3Lp1y2ZsHtxxAABwCduTuVwuNyIiwlPXHXK5XJFIxJzv9gij0VhbW+vZuUaTycT+2Ys+aFhw6Pjh8YSQB2LGEEJaOtqVmo5VX7z3bXUZ348XwPMnhLSrVU9MzPri8umzNy5nbnrhiYlZ7/zXCusSew3eultPCJkUnxLA9yeEpMcnn7l+8U5LI60fyA+gJ68duy1vIIRMTvhXI78YMbZaJiWEVMvqCCGnr10Yu+ZxWrNR8a87eUWC4BFDIwkhESFh6ram5JgEQkhc2HBCSJeu23FUXnT06NFz584FBAQEBgbqdLrGxsaRI0cyfSwsLIy+sFfuFP1DZiwVHh4uFApbWlpGjBhBCBk+fDgtDw0Nra2ttRkSm63YbIdlDLGxseaV6Sw+ISQkJCQqKop5Ta9XYR+bGzsOAAAuYTVkpLdAhoSEjBgxoqmpqfd3RHI4nKFDh3I4HA/eVkJHePQMde9bM5lMHA5n+PDhIpFIr9c7/wOfpOnu6tHr/Hl8aVsTIWR4aPi+C8fP3bzy+uMLFk/7r7f/tufT7/5KCEmKSTi39tOTFd/uPnvobxXf/mJE4uJfzbYomTHhEZsNDgsOJYTcVbXRLcrutRJChg/51zggkG/j2XpGq/5Dq7V1Kunb+rZm+kIUGEQIyU4WvzT1X9NsAT+f0eb++9Qvl/Nv8+WOo/KWioqKv//97x988EFwcPD169d37twZGBioVquZCszt0vbKnQoJCbl37x7zVqfTabVaehaYZUiu7JA7MbC/wdml2FzdcQAAcBWr21+YFTeCg4NjYmJ++uknj2ybXmjvkVEjHeH5+/vHx8d7qrXo6GjmAjKLNUcGCnWP9nd/entC7Lg9544QQp5Mm3b5diUh5FpDzZErfz9WVkyrfVFyihAycmhU0vDR9QqZzRJ7DT4YlyQSBJ29cfmtL3eHBAZ9UXLK348368Ff2YyHjuQOXT7T1dO9IOsZplw8JpXL4Zy9Ubr5b3u6errL6n6k5Y+OeyiAx7946+rkhAkjw6KqZXXTH8hgs+O/Svol+6j6jUKhCAkJEQqFRqOxqKiIEDJ27NjW1tby8vL09HSNRnPmzBl61ay9cnMBAQEqlcqicPz48T09Pd988820adMIIcePH09LSxMKhexD6j1XY3A1No/sOAAAuMr5kJHH45mfSwoODo6Li/PU5kNDQz1yHtmD40VCiJ+fX2RkJDNe5HK5A+t2aYZIEEQIef/MZzyu35Lpc3+dkjlqWMzfKr45fe3CtcZbUxInnr52gRAiU7buKP4zIYTH9Xsqbeq8h2ftPnvYouSuSmGzQULI71/a+N9H/odOWMaERryZsyQpJqHO1ko6czJmnrh67oeGatm9FvMhY1JMwtonFm47/ce93/4lZUTi5NEppXeuE0Lihg3/8IW1G/760eaTewkhYULRr3+RyWbHI0RhNqPqXTp7a/LkycePH1+yZIm/v/+kSZMIISEhIb/73e+2bdsWGRlpNBozMjLoDb/2ys1NmTJl/fr1P/744+uvvz5y5EhaGBAQ8MYbb3zwwQdHjhwxGAyRkZErVqwg9lmH1HuuxuBqbOY77vGNAgCAPRxP3YPiRfSasNGjR3s7EE/66quvsrKyQkJCAgMD3fjzutamX215MUwo+n7jkdYOZYhASK/qI4T06HVyVVv0kAie2WBdqelQdXUODRKFCIJsljhokKmvNxjCQ0IdB0a3PkQYwmyI0a3rae1U0isULdy910YIiQgZ6uqt6yyjckqn0+n1+m+//VYsFpvfdeEqo9HY1tYWHBxs/rEaDIbW1tbw8HCL/z7ZK2d0dXXpdDrm/zbmlEqlv78/m2k2myF5BPsY7LEXm0d23D01NTXNzc1Tp07to/YBAHzWYHj6C5/PH2TjRc+yGDD58/gjw6It6oQKQ0KFIY5L7DXI1GcTjM2tUwF8f5vjRUKI20sqsoyq39DbyCwK/fz8mDs/2JQzAgMD7Y3z7C2vyDIkj2Afgz32YvPIjgMAgEsG2HKDAAAAAND/BsMs4+Dm3lJEkUFDSwsPcDgcT61k5PEGB5a+fm4yAACAj8OQ0de5N1jhEBIcIHT7z/uhQQAAABhAcGIaAAAAAJzALKOP0hn1D7/3W71pQK4HOVj9emT6xIce7M0d0wAAAAMUZhl91DdNP2C86GvO/lTh7RAAAAC8YzCsyzgoSe7Wc/79mXjgC4YKRWHBQ7wdBXhNT0+PXq/Hc2UA4D6EISMAAAAAOIET0wAAAADgBE8ul3s7BgAAAADwaZyenh5vxwAAAAAAPo2DlZkBAAAAwDFcywgAAAAATmDICAAAAABOYMgIAAAAAE5gyAgAAAAATmDICAAAAABOYMgIAAAAAE5gyAgAAAAATmDICAAAAABO8LwdAAAAAAD0N4PB8Pzzz7e1tRFCOBxOWFjYoUOHHNTHLCMAAADAfcfPz+/QoUMjR47kcDgxMTGOx4sEDwwEAAAAuJ/Nnz9/3759TqthyAgAAAAATuDENAAAAAA4gSEjAAAAADiBISMAAAAAOIEhIwAAAAA4gSEjAAAAADiBISMAAAAAOIEhIwAAAAA4gSEjAAAAADiBISMAAAAAOPH/ACe6wJ6uMNs/AAAAAElFTkSuQmCC\"></figure></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionExcel.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['passport demo', 'additional information']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xls = sectionExcel.get()\n",
    "xls.sheetnames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#change content\n",
    "#sectionExcel.set(xls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>heterogeneity</td>\n",
       "      <td>germplasmDbId</td>\n",
       "      <td>accessionNumber</td>\n",
       "      <td>germplasmPUI</td>\n",
       "      <td>biologicalStatusOfAccessionCode</td>\n",
       "      <td>countryOfOriginCode</td>\n",
       "      <td>wild</td>\n",
       "      <td>standardisedName</td>\n",
       "      <td>group</td>\n",
       "      <td>...</td>\n",
       "      <td>taxonIds</td>\n",
       "      <td>speciesAuthority</td>\n",
       "      <td>subtaxa</td>\n",
       "      <td>subtaxaAuthority</td>\n",
       "      <td>donors</td>\n",
       "      <td>acquisitionDate</td>\n",
       "      <td>additionalStandardisedName</td>\n",
       "      <td>additionalInstituteCode</td>\n",
       "      <td>estimatedStandardisedName</td>\n",
       "      <td>estimatedWild</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>GPE000010</td>\n",
       "      <td>0.9990708</td>\n",
       "      <td>1232375</td>\n",
       "      <td>GPE000010</td>\n",
       "      <td>GPE000010</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>301712E</td>\n",
       "      <td>None</td>\n",
       "      <td>362213N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>GPE000020</td>\n",
       "      <td>0.9790449</td>\n",
       "      <td>1232376</td>\n",
       "      <td>GPE000020</td>\n",
       "      <td>GPE000020</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>30381.34E</td>\n",
       "      <td>None</td>\n",
       "      <td>37350.07N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>GPE000030</td>\n",
       "      <td>0.9968379</td>\n",
       "      <td>1232377</td>\n",
       "      <td>GPE000030</td>\n",
       "      <td>GPE000030</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>302115.99E</td>\n",
       "      <td>None</td>\n",
       "      <td>374541.88N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>GPE000040</td>\n",
       "      <td>0.9961142</td>\n",
       "      <td>1232378</td>\n",
       "      <td>GPE000040</td>\n",
       "      <td>GPE000040</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>30381.34E</td>\n",
       "      <td>None</td>\n",
       "      <td>37350.07N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>GPE000050</td>\n",
       "      <td>0.9982261</td>\n",
       "      <td>1232379</td>\n",
       "      <td>GPE000050</td>\n",
       "      <td>GPE000050</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>30381.34E</td>\n",
       "      <td>None</td>\n",
       "      <td>37350.07N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>GPE000060</td>\n",
       "      <td>0.9951850</td>\n",
       "      <td>1232380</td>\n",
       "      <td>GPE000060</td>\n",
       "      <td>GPE000060</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>30381.34E</td>\n",
       "      <td>None</td>\n",
       "      <td>37350.07N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>GPE000070</td>\n",
       "      <td>0.9942558</td>\n",
       "      <td>1232381</td>\n",
       "      <td>GPE000070</td>\n",
       "      <td>GPE000070</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>30381.34E</td>\n",
       "      <td>None</td>\n",
       "      <td>37350.07N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>GPE000080</td>\n",
       "      <td>0.9972966</td>\n",
       "      <td>1232382</td>\n",
       "      <td>GPE000080</td>\n",
       "      <td>GPE000080</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>302640.11E</td>\n",
       "      <td>None</td>\n",
       "      <td>373436.86N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>GPE000090</td>\n",
       "      <td>0.9833587</td>\n",
       "      <td>1232383</td>\n",
       "      <td>GPE000090</td>\n",
       "      <td>GPE000090</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>302640.11E</td>\n",
       "      <td>None</td>\n",
       "      <td>373436.86N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>GPE000100</td>\n",
       "      <td>0.9894381</td>\n",
       "      <td>1232384</td>\n",
       "      <td>GPE000100</td>\n",
       "      <td>GPE000100</td>\n",
       "      <td>300</td>\n",
       "      <td>TUR</td>\n",
       "      <td>0</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>Group 1 (melongena and closest relatives)</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>302640.11E</td>\n",
       "      <td>None</td>\n",
       "      <td>373436.86N</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Solanum melongena</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0              1              2                3             4   \\\n",
       "0        None  heterogeneity  germplasmDbId  accessionNumber  germplasmPUI   \n",
       "1   GPE000010      0.9990708        1232375        GPE000010     GPE000010   \n",
       "2   GPE000020      0.9790449        1232376        GPE000020     GPE000020   \n",
       "3   GPE000030      0.9968379        1232377        GPE000030     GPE000030   \n",
       "4   GPE000040      0.9961142        1232378        GPE000040     GPE000040   \n",
       "5   GPE000050      0.9982261        1232379        GPE000050     GPE000050   \n",
       "6   GPE000060      0.9951850        1232380        GPE000060     GPE000060   \n",
       "7   GPE000070      0.9942558        1232381        GPE000070     GPE000070   \n",
       "8   GPE000080      0.9972966        1232382        GPE000080     GPE000080   \n",
       "9   GPE000090      0.9833587        1232383        GPE000090     GPE000090   \n",
       "10  GPE000100      0.9894381        1232384        GPE000100     GPE000100   \n",
       "\n",
       "                                 5                    6     7   \\\n",
       "0   biologicalStatusOfAccessionCode  countryOfOriginCode  wild   \n",
       "1                               300                  TUR     0   \n",
       "2                               300                  TUR     0   \n",
       "3                               300                  TUR     0   \n",
       "4                               300                  TUR     0   \n",
       "5                               300                  TUR     0   \n",
       "6                               300                  TUR     0   \n",
       "7                               300                  TUR     0   \n",
       "8                               300                  TUR     0   \n",
       "9                               300                  TUR     0   \n",
       "10                              300                  TUR     0   \n",
       "\n",
       "                   8                                          9   ...  \\\n",
       "0    standardisedName                                      group  ...   \n",
       "1   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "2   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "3   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "4   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "5   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "6   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "7   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "8   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "9   Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "10  Solanum melongena  Group 1 (melongena and closest relatives)  ...   \n",
       "\n",
       "          13                14       15                16      17  \\\n",
       "0   taxonIds  speciesAuthority  subtaxa  subtaxaAuthority  donors   \n",
       "1       None           301712E     None           362213N    None   \n",
       "2       None         30381.34E     None         37350.07N    None   \n",
       "3       None        302115.99E     None        374541.88N    None   \n",
       "4       None         30381.34E     None         37350.07N    None   \n",
       "5       None         30381.34E     None         37350.07N    None   \n",
       "6       None         30381.34E     None         37350.07N    None   \n",
       "7       None         30381.34E     None         37350.07N    None   \n",
       "8       None        302640.11E     None        373436.86N    None   \n",
       "9       None        302640.11E     None        373436.86N    None   \n",
       "10      None        302640.11E     None        373436.86N    None   \n",
       "\n",
       "                 18                          19                       20  \\\n",
       "0   acquisitionDate  additionalStandardisedName  additionalInstituteCode   \n",
       "1              None                        None                     None   \n",
       "2              None                        None                     None   \n",
       "3              None                        None                     None   \n",
       "4              None                        None                     None   \n",
       "5              None                        None                     None   \n",
       "6              None                        None                     None   \n",
       "7              None                        None                     None   \n",
       "8              None                        None                     None   \n",
       "9              None                        None                     None   \n",
       "10             None                        None                     None   \n",
       "\n",
       "                           21             22  \n",
       "0   estimatedStandardisedName  estimatedWild  \n",
       "1           Solanum melongena              0  \n",
       "2           Solanum melongena              0  \n",
       "3           Solanum melongena              0  \n",
       "4           Solanum melongena              0  \n",
       "5           Solanum melongena              0  \n",
       "6           Solanum melongena              0  \n",
       "7           Solanum melongena              0  \n",
       "8           Solanum melongena              0  \n",
       "9           Solanum melongena              0  \n",
       "10          Solanum melongena              0  \n",
       "\n",
       "[11 rows x 23 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "section4_excel_sheet = xls[xls.sheetnames[0]]\n",
    "df = pd.DataFrame(section4_excel_sheet.values)\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype SAMPLESIN\n",
    "A section object can be of type 'SAMPLESIN'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
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       "<title>section_name&#45;&gt;section_type</title>\n",
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       "<!-- experiment_name -->\n",
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       "</g>\n",
       "</g>\n",
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       "<!-- sample_7278914 -->\n",
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       "<title>sample_7278914</title>\n",
       "<g id=\"a_node7\"><a xlink:title=\"sample\">\n",
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       "<text text-anchor=\"middle\" x=\"87\" y=\"-59.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Regexp sample</text>\n",
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       "<graphviz.dot.Digraph at 0x125efa400>"
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     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionSamplesIn = eLAB.section(samplesInSectionId)\n",
    "sectionSamplesIn.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "\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>name</th>\n",
       "      <th>owner</th>\n",
       "      <th>barcode</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sampleID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7278914</td>\n",
       "      <td>Regexp sample</td>\n",
       "      <td>Matthijs Brouwer</td>\n",
       "      <td>005000007278914</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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       "                   name             owner          barcode\n",
       "sampleID                                                  \n",
       "7278914   Regexp sample  Matthijs Brouwer  005000007278914"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionSamplesIn.samples().all([\"name\",\"owner\",\"barcode\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sectiontype SAMPLESOUT\n",
    "A section object can be of type 'SAMPLESOUT'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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       "<text text-anchor=\"middle\" x=\"144\" y=\"-203.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Output Samples</text>\n",
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       "<title>project_name&#45;&gt;study_name</title>\n",
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       "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"465,-204.5001 455,-208 465,-211.5001 465,-204.5001\"/>\n",
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       "<!-- sample_7278914 -->\n",
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       "<title>sample_7278914</title>\n",
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       "<title>section_type&#45;&gt;sample_7278914</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M127.5978,-117.8314C119.9585,-109.3694 110.7317,-99.1489 102.3793,-89.8971\"/>\n",
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       "<text text-anchor=\"middle\" x=\"209\" y=\"-59.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">test sample meta</text>\n",
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     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectionSamplesOut = eLAB.section(samplesOutSectionId)\n",
    "sectionSamplesOut.visualize()"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th>name</th>\n",
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       "      <th>barcode</th>\n",
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       "    <tr>\n",
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       "      <td>7278914</td>\n",
       "      <td>Regexp sample</td>\n",
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       "      <td>005000007278914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7627586</td>\n",
       "      <td>test sample meta</td>\n",
       "      <td>Matthijs Brouwer</td>\n",
       "      <td>005000007627586</td>\n",
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       "                      name             owner          barcode\n",
       "sampleID                                                     \n",
       "7278914      Regexp sample  Matthijs Brouwer  005000007278914\n",
       "7627586   test sample meta  Matthijs Brouwer  005000007627586"
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     "metadata": {},
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    "sectionSamplesOut.samples().all([\"name\",\"owner\",\"barcode\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add a new section\n",
    "Or we can create a completely new section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#import pandas as pd\n",
    "#new_data = pd.DataFrame([[\"one\",\"two\"],[\"three\",\"four\"]])\n",
    "#new_section = experiment.add(new_data, \"New section\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Show full experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Text example</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><p>This is a <strong>text</strong> with <u>markup</u>!<br>\n",
       "And a list</p>\n",
       "\n",
       "<ol>\n",
       "\t<li>one</li>\n",
       "\t<li>two</li>\n",
       "\t<li>three...</li>\n",
       "</ol>\n",
       "Testing character encoding: α β γ<br>\n",
       "<a href=\"/members/experiments/browser/#view=experiment&amp;nodeID=389036\">labjournal</a><br>\n",
       "<br>\n",
       "<br>\n",
       "&nbsp;</div><br /><h2>Datatable example</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><table border=\"1\" class=\"dataframe\">\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Sample 1</td>\n",
       "      <td>1.34</td>\n",
       "      <td>23.3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Sample 2</td>\n",
       "      <td>2.54</td>\n",
       "      <td>53.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Sample 3</td>\n",
       "      <td>3.45</td>\n",
       "      <td>33.8</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Sample 4</td>\n",
       "      <td>2.55</td>\n",
       "      <td>34.2</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Sample 5</td>\n",
       "      <td>1.59</td>\n",
       "      <td>32.9</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table></div><br /><h2>Canvas example</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img 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\"></figure></div><br /><h2>Excel section</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img 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\"></figure></div><br /><h2>nieuw</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><p></p></div><br /><h2>Specimen &amp; Materials</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"146pt\" height=\"98pt\"\n",
       " viewBox=\"0.00 0.00 146.00 98.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 94)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-94 142,-94 142,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_sample_7278914</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-8 8,-82 130,-82 130,-8 8,-8\"/>\n",
       "<text text-anchor=\"middle\" x=\"69\" y=\"-66.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">sampleID 7278914</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- sample_name_7278914 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>sample_name_7278914</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"119.9209,-52 18.0791,-52 18.0791,-16 119.9209,-16 119.9209,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"69\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Regexp sample</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "</figure></div><br /><h2>ttt</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><div class=\"pageSectionBody\"><h2>qPCR (Copy)</h2><div class=\"step\" data-stepid=\"469673\"><div class=\"stepHeader\"><div class=\"stepTitle\"><h6>Mastermix</h6><i class=\"fa fa-pencil addEditIcon editStepNameIcon\" style=\"display: none;\"></i><span class=\"stepNameEditor\" style=\"display:none;\"><span><span></span></span><i class=\"btnSaveStepName addEditIcon fa fa-save\" style=\"color:#666; margin-left:5px; font-size: .8em;\"></i></span></div><div class=\"stepMenu\"><ul><li class=\"btnEditSave\" style=\"display: none;\"><i class=\"fa fa-pencil\"></i></li><li class=\"btnMoveStep\" style=\"display: none;\"><i class=\"fa fa-arrows-alt move\" title=\"Move step by drag and drop\"></i></li><li class=\"btnRemoveStep warning\" style=\"display: none;\"><i class=\"fa fa-trash-o removeStep\" title=\"Remove step\"></i></li></ul></div></div><div class=\"stepBody\"><div class=\"stepContents\">Number of mixes needed&nbsp;<span class=\"protVar protVar_240578\" data-varid=\"240578\" data-varname=\"Field5\" title=\"number of sample 2\"><span>10</span></span><br>\n",
       "<br>\n",
       "Syber green &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240581\" data-varid=\"240581\" data-varname=\"Field7\" title=\"\"><span>100</span>&nbsp;<span class=\"protVarUnit\">µl</span></span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<br>\n",
       "25mM Forward primer &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240584\" data-varid=\"240584\" data-varname=\"Field8\" title=\"\"><span>4</span>&nbsp;<span class=\"protVarUnit\">µl</span></span><br>\n",
       "25mM Reverse primer &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp;<span class=\"protVar protVar_240590\" data-varid=\"240590\" data-varname=\"Field10\" title=\"\"><span>4</span>&nbsp;<span class=\"protVarUnit\">µl</span></span><br>\n",
       "dH2O &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<span class=\"protVar protVar_240593\" data-varid=\"240593\" data-varname=\"Field11\" title=\"\"><span>42</span>&nbsp;<span class=\"protVarUnit\">µl</span></span>&nbsp; &nbsp;&nbsp;<br>\n",
       "Add 5µl template, (1/5 diluted cDNA)</div><div style=\"clear: both;\"></div></div></div><div class=\"step\" data-stepid=\"469676\"><div class=\"stepHeader\"><div class=\"stepTitle\"><h6>Programme</h6><i class=\"fa fa-pencil addEditIcon editStepNameIcon\" style=\"display: none;\"></i><span class=\"stepNameEditor\" style=\"display:none;\"><span><span></span></span><i class=\"btnSaveStepName addEditIcon fa fa-save\" style=\"color:#666; margin-left:5px; font-size: .8em;\"></i></span></div><div class=\"stepMenu\"><ul><li class=\"btnEditSave\" style=\"display: none;\"><i class=\"fa fa-pencil\"></i></li><li class=\"btnMoveStep\" style=\"display: none;\"><i class=\"fa fa-arrows-alt move\" title=\"Move step by drag and drop\"></i></li><li class=\"btnRemoveStep warning\" style=\"display: none;\"><i class=\"fa fa-trash-o removeStep\" title=\"Remove step\"></i></li></ul></div></div><div class=\"stepBody\"><div class=\"stepContents\"><table width=\"307\" cellspacing=\"0\" cellpadding=\"0\" border=\"0\">\n",
       "\t<tbody>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td width=\"136\" height=\"20\">initial denaturation</td>\n",
       "\t\t\t<td width=\"64\">95<font>°C</font></td>\n",
       "\t\t\t<td width=\"64\">3 min</td>\n",
       "\t\t\t<td width=\"43\">&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">denaturation</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">anealing</td>\n",
       "\t\t\t<td>X°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>40x</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">elongation</td>\n",
       "\t\t\t<td>72°C</td>\n",
       "\t\t\t<td>30 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">final elongation</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>10 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"20\">\n",
       "\t\t\t<td height=\"20\">meltcurve65</td>\n",
       "\t\t\t<td>65°C</td>\n",
       "\t\t\t<td>5 sec</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t\t<tr height=\"21\">\n",
       "\t\t\t<td height=\"21\">&nbsp;</td>\n",
       "\t\t\t<td>95°C</td>\n",
       "\t\t\t<td>0.5°C</td>\n",
       "\t\t\t<td>&nbsp;</td>\n",
       "\t\t</tr>\n",
       "\t</tbody>\n",
       "</table>\n",
       "<br>\n",
       "Anealing temperature is primer dependent.<br>\n",
       "&nbsp;</div><div style=\"clear: both;\"></div></div></div></div></div><br /><h2>file</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"114pt\" height=\"98pt\"\n",
       " viewBox=\"0.00 0.00 114.00 98.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 94)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-94 110,-94 110,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_file_2508818</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"experimentFileID 2508818\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-8 8,-82 98,-82 98,-8 8,-8\"/>\n",
       "<text text-anchor=\"middle\" x=\"53\" y=\"-66.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">34 kb</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- file_name_2508818 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>file_name_2508818</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"filename\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"89.9209,-52 16.0791,-52 16.0791,-16 89.9209,-16 89.9209,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"53\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">eendje.jpg</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "</figure><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"114pt\" height=\"98pt\"\n",
       " viewBox=\"0.00 0.00 114.00 98.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 94)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-94 110,-94 110,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_file_2511299</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"experimentFileID 2511299\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-8 8,-82 98,-82 98,-8 8,-8\"/>\n",
       "<text text-anchor=\"middle\" x=\"53\" y=\"-66.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">34 kb</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- file_name_2511299 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>file_name_2511299</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"filename\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"89.9209,-52 16.0791,-52 16.0791,-16 89.9209,-16 89.9209,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"53\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">eendje.jpg</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "</figure></div><br /><h2>Output Samples</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"146pt\" height=\"98pt\"\n",
       " viewBox=\"0.00 0.00 146.00 98.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 94)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-94 142,-94 142,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_sample_7278914</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-8 8,-82 130,-82 130,-8 8,-8\"/>\n",
       "<text text-anchor=\"middle\" x=\"69\" y=\"-66.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">sampleID 7278914</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- sample_name_7278914 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>sample_name_7278914</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"119.9209,-52 18.0791,-52 18.0791,-16 119.9209,-16 119.9209,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"69\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">Regexp sample</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "</figure><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
       " -->\n",
       "<!-- Title: %3 Pages: 1 -->\n",
       "<svg width=\"150pt\" height=\"98pt\"\n",
       " viewBox=\"0.00 0.00 150.00 98.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
       "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 94)\">\n",
       "<title>%3</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-94 146,-94 146,4 -4,4\"/>\n",
       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster_sample_7627586</title>\n",
       "<g id=\"a_clust1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#067172\" stroke=\"#000000\" points=\"8,-8 8,-82 134,-82 134,-8 8,-8\"/>\n",
       "<text text-anchor=\"middle\" x=\"71\" y=\"-66.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">sampleID 7627586</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "<!-- sample_name_7627586 -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>sample_name_7627586</title>\n",
       "<g id=\"a_node1\"><a xlink:title=\"sample\">\n",
       "<polygon fill=\"#0b3b52\" stroke=\"#0b3b52\" points=\"125.8041,-52 16.1959,-52 16.1959,-16 125.8041,-16 125.8041,-52\"/>\n",
       "<text text-anchor=\"middle\" x=\"71\" y=\"-29.8\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#ffffff\">test sample meta</text>\n",
       "</a>\n",
       "</g>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n",
       "</figure></div><br /><h2>Plaatjes</h2><br/><div style=\"border: 1px solid #067172; padding: 10px;\"><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img title=\"eendje.jpg\" 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\"><figcaption>eendje.jpg</figcaption></figure><figure style=\"display: inline-block; margin-right: 10px; margin-bottom: 10px;\"><img title=\"eendje.jpg\" 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\"><figcaption>eendje.jpg</figcaption></figure></div><br />"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}