diff --git a/notebooks/hackathon_2023.10/All Covid Model Comparison.ipynb b/notebooks/hackathon_2023.10/All Covid Model Comparison.ipynb
deleted file mode 100644
index 4d90ef2fd..000000000
--- a/notebooks/hackathon_2023.10/All Covid Model Comparison.ipynb	
+++ /dev/null
@@ -1,347 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "52780839-3713-42d9-b349-afff3f15e988",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: MIRA_REST_URL=http://34.230.33.149:8771\n"
-     ]
-    }
-   ],
-   "source": [
-    "%env MIRA_REST_URL=http://34.230.33.149:8771\n",
-    "from mira.sources import biomodels\n",
-    "from mira.metamodel.comparison import *\n",
-    "from mira.metamodel.template_model import *\n",
-    "from mira.metamodel.templates import *\n",
-    "from mira.sources import biomodels\n",
-    "\n",
-    "from itertools import combinations\n",
-    "from copy import deepcopy\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import pandas as pd "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "d97a0a41-0801-4ad9-9933-f7d5bac2241a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "COVID_MODEL_LIST = [\"BIOMD0000000955\", \"BIOMD0000000956\", \"BIOMD0000000957\",\"BIOMD0000000958\",\"BIOMD0000000960\",\"BIOMD0000000962\",\n",
-    "                    \"BIOMD0000000963\", \n",
-    "                    \"BIOMD0000000964\", \"BIOMD0000000969\", \"BIOMD0000000970\",\"BIOMD0000000971\",\"BIOMD0000000972\",\n",
-    "                    \"BIOMD0000000974\",\"BIOMD0000000976\", \n",
-    "                    \"BIOMD0000000977\", \"BIOMD0000000978\", \"BIOMD0000000979\", \"BIOMD0000000980\", \"BIOMD0000000981\",\n",
-    "                    \"BIOMD0000000982\",\n",
-    "                    \"BIOMD0000000983\",\n",
-    "                    \"BIOMD0000000984\",\"BIOMD0000000988\",\"BIOMD0000000991\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "17af85da-9dbd-4cc1-912a-afcd4b81c2c6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "rc = get_dkg_refinement_closure()\n",
-    "\n",
-    "tm_covid_grounding_list = []\n",
-    "for covid_model in COVID_MODEL_LIST:\n",
-    "    tm_covid_grounding_list.append(biomodels.get_template_model(covid_model))\n",
-    "\n",
-    "model_id_name_mapping = {id:tm.annotations.name.split(' ')[0] for id,tm in enumerate(tm_covid_grounding_list)}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "9261a57a-4541-4d53-9cf3-789a08eb2bb1",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Comparing model templates: 22791it [00:00, 96096.12it/s] \n",
-      "Comparing model concepts: 14196it [00:00, 119257.12it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "tm_covid_comparison = TemplateModelComparison(tm_covid_grounding_list,refinement_func=rc.is_ontological_child)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "b2665459-92ca-492d-8163-f009bfd43911",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "grounded_scores = tm_covid_comparison.model_comparison.get_similarity_scores()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "b1bb4211-fa75-4db8-bf1a-0a3693b4d330",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tm_covid_no_grounding_list = [] \n",
-    "for tm in tm_covid_grounding_list:\n",
-    "    copied_tm = deepcopy(tm)\n",
-    "    for template in copied_tm.templates:\n",
-    "        for concept in template.get_concepts():\n",
-    "            concept.identifiers = {}\n",
-    "            concept.context = {}\n",
-    "    tm_covid_no_grounding_list.append(copied_tm)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "39c265c8-4a2e-4af3-90b5-dfd17222adcf",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Comparing model templates: 22791it [00:00, 138074.63it/s]\n",
-      "Comparing model concepts: 14196it [00:00, 246501.10it/s]\n"
-     ]
-    }
-   ],
-   "source": [
-    "tm_covid_comparison_copy = TemplateModelComparison(tm_covid_no_grounding_list,refinement_func=rc.is_ontological_child)\n",
-    "ungrounded_scores = tm_covid_comparison_copy.model_comparison.get_similarity_scores()\n",
-    "\n",
-    "list_of_both = []\n",
-    "\n",
-    "for grounded_score,ungrounded_score in zip(grounded_scores,ungrounded_scores):\n",
-    "    list_of_both.append({'Model1':model_id_name_mapping[grounded_score['models'][0]],\n",
-    "                         'Model2':model_id_name_mapping[grounded_score['models'][1]],\n",
-    "                         'sim_dkg':grounded_score['score'],\n",
-    "                        'sim_no_dkg':ungrounded_score['score']})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "ad9b2311-2302-4743-9557-ff6f55c5e846",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Removing groundings led to a decrease in pairwise similarity scores for 231 or 0.84% of the 276 pairwise model comparisons.\n"
-     ]
-    }
-   ],
-   "source": [
-    "after_sim_lower_count = 0\n",
-    "after_sim_higher_count = 0\n",
-    "after_sim_same = 0 \n",
-    "for model_comparison in list_of_both:\n",
-    "    if model_comparison['sim_no_dkg'] < model_comparison['sim_dkg']:\n",
-    "        after_sim_lower_count += 1\n",
-    "    elif model_comparison['sim_no_dkg'] > model_comparison['sim_dkg']:\n",
-    "        after_sim_higher_count += 1\n",
-    "    elif model_comparison['sim_no_dkg'] == model_comparison['sim_dkg']:\n",
-    "        after_sim_same += 1\n",
-    "print(f\"Removing groundings led to a decrease in pairwise similarity scores for {after_sim_lower_count} or {round(after_sim_lower_count /len(list_of_both),2)}% of the {len(list_of_both)} pairwise model comparisons.\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "abe29402-b3e3-407a-969c-b23925139a07",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Removing groundings led to an increase in pairwise similarity scores for 11 or 0.04% of the 276 pairwise model comparisons.\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(f\"Removing groundings led to an increase in pairwise similarity scores for {after_sim_higher_count} or {round(after_sim_higher_count/len(list_of_both),2)}% of the 276 pairwise model comparisons.\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "766431b2-74c6-4e10-86c6-923366e7664b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Removing groundings led to no change in pairwise similarity scores for 34 or 0.12% of the 276 pairwise model comparisons.\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(f\"Removing groundings led to no change in pairwise similarity scores for {after_sim_same} or {round(after_sim_same/len(list_of_both),2)}% of the {len(list_of_both)} pairwise model comparisons.\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "b5de93b1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "diffs = []\n",
-    "for model_comparison in list_of_both:\n",
-    "    diffs.append(model_comparison['sim_dkg'] - model_comparison['sim_no_dkg'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "55afca09",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "e1b265b5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(0.5, 1.5)"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.boxplot(diffs, showmeans=True)\n",
-    "plt.ylabel('Model comparison score difference\\n (with DKG - without DKG)')\n",
-    "plt.xlabel('COVID-19 epidemiology model pairs')\n",
-    "plt.xticks([])\n",
-    "plt.plot([-1, 2], [0, 0], 'k--')\n",
-    "plt.xlim([0.5, 1.5])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "c9c403df",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(0.5, 1.5)"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.boxplot([abs(d) for d in diffs], showmeans=True)\n",
-    "plt.ylabel('Model comparison score difference\\n abs(with DKG - without DKG)')\n",
-    "plt.xlabel('COVID-19 epidemiology model pairs')\n",
-    "plt.xticks([])\n",
-    "plt.xlim([0.5, 1.5])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "07a30953",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "276"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "len(diffs)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3e2a11e8",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.10.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/notebooks/hackathon_2023.10/Model Comparison.ipynb b/notebooks/hackathon_2023.10/Model Comparison.ipynb
deleted file mode 100644
index 9d081e373..000000000
--- a/notebooks/hackathon_2023.10/Model Comparison.ipynb	
+++ /dev/null
@@ -1,648 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "8ca68279-4097-4dc7-ab8c-91947663eb26",
-   "metadata": {},
-   "source": [
-    "## Load up the environment variable needed for module imports"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "0d94ee13-ab8e-4709-9a13-772e27bf85d3",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: MIRA_REST_URL=http://34.230.33.149:8771\n"
-     ]
-    }
-   ],
-   "source": [
-    "%env MIRA_REST_URL=http://34.230.33.149:8771"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "66d4c677-9450-4074-8160-b250d791c127",
-   "metadata": {},
-   "source": [
-    "## Import modules"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "f8dbb0dc-44b3-414a-be6d-9b6b3b82381e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from mira.sources import biomodels\n",
-    "from mira.metamodel.comparison import *\n",
-    "from mira.metamodel.template_model import *\n",
-    "from mira.metamodel.templates import *\n",
-    "from mira.sources import biomodels\n",
-    "\n",
-    "from itertools import combinations\n",
-    "from copy import deepcopy\n",
-    "from tabulate import tabulate\n",
-    "\n",
-    "import pandas as pd "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0aadd1b5-f099-45e7-9e88-a147844c8de9",
-   "metadata": {},
-   "source": [
-    "## Define the Covid epi models to be compared and add them to a list "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "bcf47a4b-090c-4c1f-b564-3bd8d9bfd290",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "COVID_MODEL_LIST = [\"BIOMD0000000955\", \"BIOMD0000000956\", \"BIOMD0000000957\",\"BIOMD0000000958\",\"BIOMD0000000960\",\"BIOMD0000000962\"]\n",
-    "\n",
-    "rc = get_dkg_refinement_closure()\n",
-    "\n",
-    "tm_covid_grounding_list = []\n",
-    "for covid_model in COVID_MODEL_LIST:\n",
-    "    tm_covid_grounding_list.append(biomodels.get_template_model(covid_model))\n",
-    "\n",
-    "model_id_name_mapping = {id:tm.annotations.name.split(' ')[0] for id,tm in enumerate(tm_covid_grounding_list)}\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "48aab7a4-998d-461b-bc05-cd951557bb7c",
-   "metadata": {},
-   "source": [
-    "## Compute pairwise similarity scores between each grounded model"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "87b357ac-db72-4c62-9ce8-d9d208bd7d76",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Comparing model templates: 946it [00:00, 135281.68it/s]\n",
-      "Comparing model concepts: 595it [00:00, 232257.88it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Model1</th>\n",
-       "      <th>Model2</th>\n",
-       "      <th>Similarity Score</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>0.7500</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>0.8750</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.5000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.5000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.1250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.1250</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Model1        Model2  Similarity Score\n",
-       "0   Giordano2020  Bertozzi2020            0.6250\n",
-       "1   Giordano2020      Roda2020            0.7500\n",
-       "2   Giordano2020   Ndairou2020            0.4375\n",
-       "3   Giordano2020     Paiva2020            0.4375\n",
-       "4   Giordano2020      Zhao2020            0.4375\n",
-       "5   Bertozzi2020      Roda2020            0.8750\n",
-       "6   Bertozzi2020   Ndairou2020            0.5000\n",
-       "7   Bertozzi2020     Paiva2020            0.4375\n",
-       "8   Bertozzi2020      Zhao2020            0.6250\n",
-       "9       Roda2020   Ndairou2020            0.5000\n",
-       "10      Roda2020     Paiva2020            0.4375\n",
-       "11      Roda2020      Zhao2020            0.6250\n",
-       "12   Ndairou2020     Paiva2020            0.6250\n",
-       "13   Ndairou2020      Zhao2020            0.1250\n",
-       "14     Paiva2020      Zhao2020            0.1250"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tm_covid_comparison = TemplateModelComparison(tm_covid_grounding_list,refinement_func=rc.is_ontological_child)\n",
-    "grounded_scores = tm_covid_comparison.model_comparison.get_similarity_scores()\n",
-    "\n",
-    "grounded_scores_df_list = [{'Model1':model_id_name_mapping[d['models'][0]], 'Model2':model_id_name_mapping[d['models'][1]], 'Similarity Score':d['score']} for d in grounded_scores]\n",
-    "df_grounded = pd.DataFrame(grounded_scores_df_list)\n",
-    "df_grounded"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "98c57c49-7ffa-4452-8657-4fa7c23248db",
-   "metadata": {},
-   "source": [
-    "## Print the names for the selected grounded covid biomodels to know which ones we are comparing\n",
-    "\n",
-    "We select the third (BIOMD0000000957) and sixth (BIOMD0000000962) grounded covid models "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "96cc1518-9fd6-4f71-b9b2-7c92b565f37c",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Roda2020 - SIR model of COVID-19 spread in Wuhan\n",
-      "Zhao2020 - SUQC model of COVID-19 transmission dynamics in Wuhan, Hubei, and China\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(tm_covid_comparison.template_models[2].annotations.name)\n",
-    "print(tm_covid_comparison.template_models[5].annotations.name)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "11bc51ac-337c-41ab-a5bb-4512fb6aa3c0",
-   "metadata": {},
-   "source": [
-    "## Create an image comparing the selected grounded models"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "c6c27191-6089-4c4c-aee0-378dff952537",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "TemplateModelDelta.for_jupyter(tm_covid_comparison.template_models[2],tm_covid_comparison.template_models[5],\n",
-    "                                               rc.is_ontological_child, args=\"-Grankdir=TB\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a06764fe-cc15-447b-8ff8-7395a58ee737",
-   "metadata": {},
-   "source": [
-    "## Create a list of covid biomodels without grounding "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "18a52915-eb78-4762-bc6b-9be649b09ecf",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tm_covid_no_grounding_list = [] \n",
-    "for tm in tm_covid_grounding_list:\n",
-    "    copied_tm = deepcopy(tm)\n",
-    "    for template in copied_tm.templates:\n",
-    "        for concept in template.get_concepts():\n",
-    "            concept.identifiers = {}\n",
-    "            concept.context = {}\n",
-    "    tm_covid_no_grounding_list.append(copied_tm)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5e0019a0-2ac3-4eb5-b8c1-f44457ff5826",
-   "metadata": {},
-   "source": [
-    "## Compute pairwise similarity scores between each ungrounded model\n",
-    "\n",
-    "We compare grounded and ungrounded model similarity scores side-by-side"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "79475119-ca7c-460c-9477-41477a65597a",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Comparing model templates: 946it [00:00, 147343.44it/s]\n",
-      "Comparing model concepts: 595it [00:00, 244883.81it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Model1</th>\n",
-       "      <th>Model2</th>\n",
-       "      <th>sim_dkg</th>\n",
-       "      <th>sim_no_dkg</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>0.7500</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>0.125</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>0.125</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Giordano2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>0.125</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>0.8750</td>\n",
-       "      <td>0.750</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.5000</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>Bertozzi2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>0.5000</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.4375</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>Roda2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "      <td>0.250</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>0.6250</td>\n",
-       "      <td>0.625</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>Ndairou2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.1250</td>\n",
-       "      <td>0.125</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>Paiva2020</td>\n",
-       "      <td>Zhao2020</td>\n",
-       "      <td>0.1250</td>\n",
-       "      <td>0.125</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Model1        Model2  sim_dkg  sim_no_dkg\n",
-       "0   Giordano2020  Bertozzi2020   0.6250       0.250\n",
-       "1   Giordano2020      Roda2020   0.7500       0.250\n",
-       "2   Giordano2020   Ndairou2020   0.4375       0.125\n",
-       "3   Giordano2020     Paiva2020   0.4375       0.125\n",
-       "4   Giordano2020      Zhao2020   0.4375       0.125\n",
-       "5   Bertozzi2020      Roda2020   0.8750       0.750\n",
-       "6   Bertozzi2020   Ndairou2020   0.5000       0.250\n",
-       "7   Bertozzi2020     Paiva2020   0.4375       0.250\n",
-       "8   Bertozzi2020      Zhao2020   0.6250       0.250\n",
-       "9       Roda2020   Ndairou2020   0.5000       0.250\n",
-       "10      Roda2020     Paiva2020   0.4375       0.250\n",
-       "11      Roda2020      Zhao2020   0.6250       0.250\n",
-       "12   Ndairou2020     Paiva2020   0.6250       0.625\n",
-       "13   Ndairou2020      Zhao2020   0.1250       0.125\n",
-       "14     Paiva2020      Zhao2020   0.1250       0.125"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "tm_covid_comparison_copy = TemplateModelComparison(tm_covid_no_grounding_list,refinement_func=rc.is_ontological_child)\n",
-    "ungrounded_scores = tm_covid_comparison_copy.model_comparison.get_similarity_scores()\n",
-    "\n",
-    "list_of_both = []\n",
-    "\n",
-    "for grounded_score,ungrounded_score in zip(grounded_scores,ungrounded_scores):\n",
-    "    list_of_both.append({'Model1':model_id_name_mapping[grounded_score['models'][0]],\n",
-    "                         'Model2':model_id_name_mapping[grounded_score['models'][1]],\n",
-    "                         'sim_dkg':grounded_score['score'],\n",
-    "                        'sim_no_dkg':ungrounded_score['score']})\n",
-    "                    \n",
-    "\n",
-    "no_ground_df = pd.DataFrame(list_of_both)\n",
-    "no_ground_df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c1bafd46-f1d6-4fa5-a3da-ed7348b53b45",
-   "metadata": {},
-   "source": [
-    "## Create an image comparing selected ungrounded models"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "6713a2a3-0413-4045-a07c-8f8c847b2bd1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "TemplateModelDelta.for_jupyter(tm_covid_comparison_copy.template_models[2],tm_covid_comparison_copy.template_models[5],\n",
-    "                                               rc.is_ontological_child,args=\"-Grankdir=TB\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "aeb80a35-5d32-4990-b33a-4505cd9eaf91",
-   "metadata": {},
-   "source": [
-    "## Reasoning on difference between grounded and ungrounded models"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "19ba61d4-b7a9-4709-8d60-ff0fdd9f5091",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The similarity score between models 2 and 5 when grounded is 0.625. The similarity score for the models when ungrounded is 0.25. The reasoning for this is because the refinements dissapear and the confirmed concept node is no longer the same between the two models\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(f\"The similarity score between models 2 and 5 when grounded is {grounded_scores[11]['score']}. The similarity score for the models when ungrounded is {list_of_both[11]['sim_no_dkg']}. The reasoning for this is because the refinements dissapear and the confirmed concept node is no longer the same between the two models\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "16c8f7ca-d135-4974-88a8-5d452e43e83b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Out of 15 pairs of models, 12 pairs of models have different similarity scores when using the Domain Knowledge Graph\n"
-     ]
-    }
-   ],
-   "source": [
-    "diff_count = 0 \n",
-    "for model_comparison in list_of_both:\n",
-    "    if model_comparison['sim_dkg'] != model_comparison['sim_no_dkg']:\n",
-    "        diff_count += 1\n",
-    "print(f\"Out of {len(list_of_both)} pairs of models, {diff_count} pairs of models have different similarity scores when using the Domain Knowledge Graph\")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "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": "3.10.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/notebooks/hackathon_2023.10/dkg_grounding_model_comparison.ipynb b/notebooks/hackathon_2023.10/dkg_grounding_model_comparison.ipynb
new file mode 100644
index 000000000..a7971f79a
--- /dev/null
+++ b/notebooks/hackathon_2023.10/dkg_grounding_model_comparison.ipynb
@@ -0,0 +1,989 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a519e72a-f8ee-47c7-9b96-3209c2cc1863",
+   "metadata": {},
+   "source": [
+    "## Measuring the effect of DKG grounding via model comparison\n",
+    "\n",
+    "**Introduction**: When comparing models, MIRA finds exact equivalences between concepts (analogous to \"states\" in Petri nets or \"stocks\" in stock and flow models) or ontological refinements between them. MIRA then extends these comparisons to the template level (analogous to \"transition\" in Petri nets or \"flow\" in stock and flow models) to find equivalences or refinements. The result of this comparison is summarized as a graph which can be visualized to show the relationship of the two models, as well as a heuristic similarity score between 0 and 1 with 0 corresponding to no relation and 1 corresponding to exact equivaence.\n",
+    "\n",
+    "**Model comparison method**: When MIRA compares concepts, in case the concepts have grounding (which are generally terms from the DKG), the grounding is used to do comparison. If grounding is not available, the string name of the concept is used for comparison. For example, assume one model has a concept called \"S\" and another, a concept called \"Susceptible\". The name-based comparison would conclude that these are not the same, whereas if both concepts were grounded to the DKG term \"ido:0000514\", they would be considered equal. An example of refinement is, for instance, when one model has an \"Infected\" concept grounded to \"ido:0000511\", and another model has \"Infected_Asymptomatic\", grounded to \"ido:0000511\" with context \"ncit:C3833\" (asymptomatic). Here, \"Infected_Asymptomatic\" would be a refinement of \"Infected\".\n",
+    "\n",
+    "**Approach to measuring impact of grounding**: Given the above, we expect that if models \"in the wild\" are using consistent naming conventions are align with each other in simple ways (i.e., refinements are not common), model comparison without using grounding would work sufficiently well just based on string names. If, however, grounding plays an important role, we will be able to observe that model comparison graphs and model similarity scores will differ between the conditions where we use grounding and when we ignore it.\n",
+    "\n",
+    "**Model set**: The BioModels database contains a number of published COVID-19 models. Each of these models is available in a structured format: SBML. We first process 6 of the models to compute pairwise similarity scores with and without grounding (this allows us to show all the results in a table that wouldn't be possible for the broader model set due to the large number of pairwise comparisons). We then extend the analysis to all pairs of 24 models and present statistics of how similarity scores change. In the first round of analysis we look at six selected models available [here](https://www.ebi.ac.uk/biomodels/covid-19)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f8dbb0dc-44b3-414a-be6d-9b6b3b82381e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: MIRA_REST_URL=http://34.230.33.149:8771\n"
+     ]
+    }
+   ],
+   "source": [
+    "import time\n",
+    "from copy import deepcopy\n",
+    "from tabulate import tabulate\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from mira.sources import biomodels\n",
+    "from mira.metamodel import *\n",
+    "\n",
+    "%env MIRA_REST_URL=http://34.230.33.149:8771\n",
+    "rc = get_dkg_refinement_closure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "bcf47a4b-090c-4c1f-b564-3bd8d9bfd290",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "SUBSET_MODEL_LIST = [\"BIOMD0000000955\", \"BIOMD0000000956\", \"BIOMD0000000957\",\n",
+    "                     \"BIOMD0000000958\",\"BIOMD0000000960\",\"BIOMD0000000962\"]\n",
+    "\n",
+    "tm_covid_subset_grounding_list = []\n",
+    "for covid_model in SUBSET_MODEL_LIST:\n",
+    "    tm_covid_subset_grounding_list.append(biomodels.get_template_model(covid_model))\n",
+    "\n",
+    "model_id_subset_name_mapping = {id: tm.annotations.name.split(' ')[0]\n",
+    "                                for id,tm in enumerate(tm_covid_subset_grounding_list)}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "48aab7a4-998d-461b-bc05-cd951557bb7c",
+   "metadata": {},
+   "source": [
+    "## Similarity scores for initial model pairs with DKG grounding\n",
+    "\n",
+    "We convert the subset of COVID-19 biomodels into MIRA template models. We then compute pairwise similarity scores between each grounded model.\n",
+    "\n",
+    "Similarity scores between template models are calculated by comparing the concepts of each template model. First, we sum up equivalences and refinements: if two concepts are equivalent, then we add 1 to the sum, if one template model's concept is a reinfement of the other template model's concept, we add 0.5 to the sum. We then normalize this sum by dividing it by the number of nodes in the larger template model to get the overall score. This is a simple heuristic that works well for ranking by similarity.\n",
+    "\n",
+    "Below we show a table of all similarity scores (with grounding) for pairs of the 6 selected models. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "87b357ac-db72-4c62-9ce8-d9d208bd7d76",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Comparing model templates: 946it [00:00, 119927.81it/s]\n",
+      "Comparing model concepts: 595it [00:00, 203076.81it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Model1</th>\n",
+       "      <th>Model2</th>\n",
+       "      <th>Similarity Score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>0.7500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>0.8750</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.5000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.5000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.1250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.1250</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Model1        Model2  Similarity Score\n",
+       "0   Giordano2020  Bertozzi2020            0.6250\n",
+       "1   Giordano2020      Roda2020            0.7500\n",
+       "2   Giordano2020   Ndairou2020            0.4375\n",
+       "3   Giordano2020     Paiva2020            0.4375\n",
+       "4   Giordano2020      Zhao2020            0.4375\n",
+       "5   Bertozzi2020      Roda2020            0.8750\n",
+       "6   Bertozzi2020   Ndairou2020            0.5000\n",
+       "7   Bertozzi2020     Paiva2020            0.4375\n",
+       "8   Bertozzi2020      Zhao2020            0.6250\n",
+       "9       Roda2020   Ndairou2020            0.5000\n",
+       "10      Roda2020     Paiva2020            0.4375\n",
+       "11      Roda2020      Zhao2020            0.6250\n",
+       "12   Ndairou2020     Paiva2020            0.6250\n",
+       "13   Ndairou2020      Zhao2020            0.1250\n",
+       "14     Paiva2020      Zhao2020            0.1250"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tm_covid_subset_comparison = TemplateModelComparison(tm_covid_subset_grounding_list,\n",
+    "                                                     refinement_func=rc.is_ontological_child)\n",
+    "grounded_scores = tm_covid_subset_comparison.model_comparison.get_similarity_scores()\n",
+    "\n",
+    "grounded_scores_df_list = [{'Model1': model_id_subset_name_mapping[d['models'][0]],\n",
+    "                            'Model2': model_id_subset_name_mapping[d['models'][1]],\n",
+    "                            'Similarity Score': d['score']} for d in grounded_scores]\n",
+    "df_grounded = pd.DataFrame(grounded_scores_df_list)\n",
+    "df_grounded"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98c57c49-7ffa-4452-8657-4fa7c23248db",
+   "metadata": {},
+   "source": [
+    "## Drilling down into a specific example\n",
+    "We visualize the difference between the third (BIOMD0000000957) and sixth (BIOMD0000000962) grounded covid models\n",
+    "\n",
+    "Below, the graph can be interpreted as follows:\n",
+    "- Orange nodes: exact equivalence between concepts\n",
+    "- Green nodes: one of the models' templates (rectangle) and concepts (oval)\n",
+    "- Blue nodes: the other model's tempaltes (rectangle) and concepts (oval)\n",
+    "- Red arrows: refinement relationship between pairs of concepts or templates\n",
+    "\n",
+    "As can be seen below, this comparison is **using** DKG groundings, these are shown in each node."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "96cc1518-9fd6-4f71-b9b2-7c92b565f37c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Roda2020 - SIR model of COVID-19 spread in Wuhan\n",
+      "Zhao2020 - SUQC model of COVID-19 transmission dynamics in Wuhan, Hubei, and China\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(tm_covid_subset_comparison.template_models[2].annotations.name)\n",
+    "print(tm_covid_subset_comparison.template_models[5].annotations.name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c6c27191-6089-4c4c-aee0-378dff952537",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "TemplateModelDelta.for_jupyter(tm_covid_subset_comparison.template_models[2],\n",
+    "                               tm_covid_subset_comparison.template_models[5],\n",
+    "                               rc.is_ontological_child,\n",
+    "                               args=\"-Grankdir=TB\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a06764fe-cc15-447b-8ff8-7395a58ee737",
+   "metadata": {},
+   "source": [
+    "## Similarity scores without DKG grounding for initial model pairs\n",
+    "\n",
+    "When removing groundings from each template model, we expect the pair-wise template model similarity scores to potentially change due to any of the following factors:\n",
+    "- refinements dissapearing\n",
+    "- equivalences not recognized due to differing naming conventions\n",
+    "- false equivalences recognized due to overlapping names for non-equal concepts\n",
+    "\n",
+    "Below, we re-run model comparison for ungrounded models and present a table summarizing the similarity scores with and without grounding."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "18a52915-eb78-4762-bc6b-9be649b09ecf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tm_covid_subset_no_grounding_list = [] \n",
+    "for tm in tm_covid_subset_grounding_list:\n",
+    "    copied_tm = deepcopy(tm)\n",
+    "    for template in copied_tm.templates:\n",
+    "        for concept in template.get_concepts():\n",
+    "            concept.identifiers = {}\n",
+    "            concept.context = {}\n",
+    "    tm_covid_subset_no_grounding_list.append(copied_tm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "79475119-ca7c-460c-9477-41477a65597a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Comparing model templates: 946it [00:00, 156545.87it/s]\n",
+      "Comparing model concepts: 595it [00:00, 235279.62it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Model1</th>\n",
+       "      <th>Model2</th>\n",
+       "      <th>Similarity Score with Grounding</th>\n",
+       "      <th>Similarity Score without Grounding</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>0.7500</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Giordano2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>0.8750</td>\n",
+       "      <td>0.750</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.5000</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Bertozzi2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>0.5000</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.4375</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Roda2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "      <td>0.250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>0.6250</td>\n",
+       "      <td>0.625</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Ndairou2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.1250</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Paiva2020</td>\n",
+       "      <td>Zhao2020</td>\n",
+       "      <td>0.1250</td>\n",
+       "      <td>0.125</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Model1        Model2  Similarity Score with Grounding  \\\n",
+       "0   Giordano2020  Bertozzi2020                           0.6250   \n",
+       "1   Giordano2020      Roda2020                           0.7500   \n",
+       "2   Giordano2020   Ndairou2020                           0.4375   \n",
+       "3   Giordano2020     Paiva2020                           0.4375   \n",
+       "4   Giordano2020      Zhao2020                           0.4375   \n",
+       "5   Bertozzi2020      Roda2020                           0.8750   \n",
+       "6   Bertozzi2020   Ndairou2020                           0.5000   \n",
+       "7   Bertozzi2020     Paiva2020                           0.4375   \n",
+       "8   Bertozzi2020      Zhao2020                           0.6250   \n",
+       "9       Roda2020   Ndairou2020                           0.5000   \n",
+       "10      Roda2020     Paiva2020                           0.4375   \n",
+       "11      Roda2020      Zhao2020                           0.6250   \n",
+       "12   Ndairou2020     Paiva2020                           0.6250   \n",
+       "13   Ndairou2020      Zhao2020                           0.1250   \n",
+       "14     Paiva2020      Zhao2020                           0.1250   \n",
+       "\n",
+       "    Similarity Score without Grounding  \n",
+       "0                                0.250  \n",
+       "1                                0.250  \n",
+       "2                                0.125  \n",
+       "3                                0.125  \n",
+       "4                                0.125  \n",
+       "5                                0.750  \n",
+       "6                                0.250  \n",
+       "7                                0.250  \n",
+       "8                                0.250  \n",
+       "9                                0.250  \n",
+       "10                               0.250  \n",
+       "11                               0.250  \n",
+       "12                               0.625  \n",
+       "13                               0.125  \n",
+       "14                               0.125  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tm_covid_subset_comparison_copy = TemplateModelComparison(tm_covid_subset_no_grounding_list,\n",
+    "                                                          refinement_func=rc.is_ontological_child)\n",
+    "ungrounded_scores = tm_covid_subset_comparison_copy.model_comparison.get_similarity_scores()\n",
+    "\n",
+    "list_of_both_subset = []\n",
+    "\n",
+    "for grounded_score,ungrounded_score in zip(grounded_scores,ungrounded_scores):\n",
+    "    list_of_both_subset.append(\n",
+    "        {'Model1': model_id_subset_name_mapping[grounded_score['models'][0]],\n",
+    "         'Model2': model_id_subset_name_mapping[grounded_score['models'][1]],\n",
+    "         'Similarity Score with Grounding': grounded_score['score'],\n",
+    "         'Similarity Score without Grounding': ungrounded_score['score']}\n",
+    "    )\n",
+    "                    \n",
+    "\n",
+    "no_ground_df = pd.DataFrame(list_of_both_subset)\n",
+    "no_ground_df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c1bafd46-f1d6-4fa5-a3da-ed7348b53b45",
+   "metadata": {},
+   "source": [
+    "## Drilling down into the same example model pair without groundings\n",
+    "\n",
+    "We previously showed an example model comparison graph with groundings. Below we show the comparison of the same two models without grounding. We observe that \"Susceptible\" was still correctly recognized as equivalent due to name matches but all refinements and one additional equivalence was missed.\n",
+    "\n",
+    "This explains the change in similarity scores with and without grounding, as printed below the graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6713a2a3-0413-4045-a07c-8f8c847b2bd1",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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VRDxf/GLY9Bj0OQ9+5e2uplCOHz/OjTfeiDGGPXv2cObMGerVq0etWnlvU3lpmXr16lG+fHni4uKoWbMmgYGBGGNIT08nJyeHuLg4GjRokG9P7YSEBBITE4mMjMz3TjmnT5/m6NGjNGrUKNcA63/4wx9YtWoVhw8fZu/evVSoUIGbbropz/MdDgfZ2dm5nluQkydPcuzYMRo1akRQUNBVl79ajR7vxBr4ugs8mghlvaxTkoibKVyKiHfYMwUORcFDB+yupMS5FC6PHz9udyneK+0YfFkLOm6Aqvm3LRUpLdTmUkS8Q3oCBOU94ye/X1paWp52k3KNyt8IPmWsz6lIKadwKSLewZHiFYOmexOHw8F7773Hhg0bOH/+PBMmTODYsWN2l+WlfMA/xPqcipRy6tAjIl5ErXjcyd/fn+HDhzN8+HC7SxGREkRnLkXEO/iH6qyQeDADjvPW51SklFO4FBHvUP5GSP3Z7ipE8pd2DEwOlK9pdyUitlO4FBHvEBpphctsdTwRD5T8o/W9QqS9dYh4AIVLEfEOYXda925O3GR3JSJ5nfoGQm6GgEp2VyJiO4VLEfEO5W+EGxrDiVV2V5KvuLg4oqKi7C7DI/z888+MHz+eiIgIt63j66+/5ttvv3VPgUUhIRqqd7G7ChGPoHApIt6j1qNwZB44HXZXksuSJUuYPn06AwYMsLsUj3Do0CHWr1//u4Y1+u062rdvz969e3nzzTfdVab7nNsNSTutz6eIKFyKiBepOwQyE+HYl3ZX4rJr1y6mTp3KjBkzKFOmjN3leIT27dvTpk0bt69jyJAh7Nu3jzVr1vyudbvdgQ+sS+Lh99ldiYhHULgUEe8RVAdq9bJuBekBY17m5OTw6KOP0r9/f7tL8Tj53dvcHet49dVXGTZsmOfcUSjtOBz8CBqOAnzsrkbEI2gQdRHxLo0nQvRtcGQuRNgb6pYtW8bx48fp16+fa9qCBQtwOp34+/vTu3dvABYtWoTD4SAwMJCePXsCcODAAaKionjllVc4ePAgX3zxBVWrVmXw4MG5QlVaWhqfffYZp06dolGjRtx///2Ehobi6+uLj48PBw8eJCoqikmTJhEdHc3evXt5/vnn8ff3JzMzkw0bNrBhwwZq1KhB165dqVevXpHU6XA4WLp0Kf/73/+47777cDqdeV6vlJQUFixYQGxsLHXr1mXw4MEEBwdf0zpq1qxJSEgIL7/8Mn/729+u+71zmz2ToWxluPkpuysR8RxGRMTbfPuUMYvDjclMsrWM9u3bm9tvvz3XtJSUFNOmTRsTGhrqmpaQkGCaNGliqlWrZowxJioqyoSHhxvA/Pvf/za9evUyPXr0MICZMGGC63mJiYmmXr16Zvbs2SYrK8uMHTvWACYiIsLcc889Zvbs2aZatWoGMFFRUaZZs2YGMJs3bzbp6enmvvvuM/PnzzdJSUlmxowZJiQkxCxevNjtdZ47d87cf//9ZtKkSebMmTNm9uzZJiAgwJQpU8a1zP79+82DDz5oVq9ebXbu3GkaN25s6tWrZ5KSkgq9jkuGDRtm6tSpc71vm/uc/taYub7GHJlrdyUiHkXhUkS8T+ZZK1xuGWBbCU6n05QrV8507949z7wRI0bkCm3GGPPHP/7RFdqMMa6guGzZMte09u3bmwYNGrh+fu6550xoaKhxOBzGGGPi4+MNYF566SXXMuPHj3eFS2OM+emnn4zT6TT9+vUzQ4YMyVVD7969TWBgoImPj3drncOHDzc9e/bMtZ4HHnggVzDs1KmTWbp0qevn6OjoXCG1MOu4ZOLEiQYwZ86cyTOv2DguGLO8kTHrOttXg4iHUptLEfE+ARWh1cdw+HM4NNuWEk6cOEFGRgY1atTIM8/XN++v1t9OCwoKAqB79+6uaY0bN87VwzouLs51+RusS8I333wzmzb9OtZnYGAgAH379gWgYcOGpKens3DhQpo1a5Zrm08//TTp6el88sknbqvz1KlTzJo1i86dO+d6XtOmTV2PT5w4QUxMDFu2bGHcuHGMGzeOlStX0qJFC9LS0gq1jstVrVoVgJ07d+Y7v1hsGwGZp+Cuj+yrQcRDqc2liHinGt2h0Rj4/mkIbQCVWxfr5n/55RcAQkOv717S+QW7oKAgsrOzXT/fc889rFy5ku+++47WrVuTmZlJQkICDzzwgGuZS8Hzclu2bMHhcODnl/tXfP369QHYv3+/2+r84YcfcDgcVKtWLdcyl9cVFxcHwNixY6lcuXKe9cXExFx1HZe7tI59+/bRoUOHQu+L2+ybBoc/hXuX6XaPIvnQmUsR8V63vwHVOsI3PeH8gWLd9M0334yPjw9nzpwpsm08//zz9O7dm7Fjx7J27VrGjBnD3XffzSuvvHLF5+Xk5ABWyLzcpVDWoEEDt9V4/vx5wDo7WZCAgAAAduzYke/zC7OOy13qKR4eHn5NtbrFsS9hx5/htjfgxgeuvrxIKaRwKSLey6cMtJkLQRHwVQe4cKjYNh0SEkK9evU4depUnnmhoaFkZmbmmmaMcYW+wvLx8aFGjRpMnToVp9PJM888Q0xMDCEhIVd8XrNmzShbtiybN2/ONT0xMRGAtm3buq3OW265BYDo6Og88y719m7YsCFlypRh4sSJZGVl5apnzpw5hVrH5RISEgC46aabCl2nWxxfAZseh5v/BJFji3fbIl5E4VJEvJtfMLRfDeWqwlftISW22DbdrFmzfMNlnTp1yMzMJCYmBmMMCxYsYMuWLSQnJ5OcnExOTg5nz54FID093fW87OxsHA6HK/C9/fbbbNiwgfj4ePz9/UlOTmbv3r25Lp07HNbdii4/g1q1alVGjhzJ4cOH+frrr13Tv/zyS/r06UO7du3cVmdkZCRdu3ZlxYoVrttfZmVlsXPnTowxxMfHExISwrBhw9i6dSvt2rVj7ty5REVF0b9/f/r27VuodVy+zwkJCdxwww2uUFos4hfDxt5QdxC0nFl82xXxRnb2JhIRcZvMM8asvtuYhZWMSdxcLJucO3euKVu2rLlw4UKu6ampqaZx48YGMOHh4Wb27Nlm6NChpmLFimbMmDHmo48+MhEREQYwo0aNMocOHTLz5883N910kwHMCy+8YH755RezfPlyU65cOYM1Yrzrq3bt2mbNmjVm0aJFpmHDhgYwffr0MT/88IOrhpycHDN69GhTpUoV8+KLL5pBgwaZxx57zKSnp7u9zpMnT5q2bdsawDRo0MA89NBD5oknnjDBwcFmxIgR5tixYyY1NdUMHDjQtQ+hoaG5eo8XZh2XtG7d2owePboI39nf2DfDGnLo+5HGOHOKb7siXsrHGGP/bS5ERNwhJx0294OEaGj+V2gwosg32b17d55++mkefPDBXNONMezZs4d69epRvnx54uLiqFmzpqt3d2EsWrSI7OxsOnXqxJkzZ0hNTSU5OZk9e/awePHiXGclC5Kens5PP/1Eo0aNKFeuXJ757qjzkoMHD5KTk0P9+vU5cuQIYWFheTo8nT59mqNHj9KoUaN8t3G1dcTGxtKsWTP27t1L3bp1r7nGa5KdZvUKPxRlte+NfLFotydSQihcikgJY2DfdPjfC1CjhzVkUUDFIttafHw8gwcPJiYmJt+e1dfrwIEDtGnThuPHj+fp9X3q1CnGjBnDp59+6rbteYvRo0fTuHFjnnzyyaLdUMo+2PQYpP4MrT6CWo8W7fZEShC1uRSREsbHus9zhxg48x1EN4Mz3xbZ1mrVqsWIESN488033bre+Ph4Tp06xYABA/jmm2+Ij48nPj6etWvX8uyzzzJx4kS3bs8bzJ8/n8DAwKIPlvGLYfVd4BsA3f6nYClyjXTmUkRKroxfYEt/OLUJIl+AW1+CMtd+ubcwDh8+zI4dO3j0UfcFkTVr1rBixQrWrl3L4cOHqV+/Pl26dGHChAnXPb6mt9q4cSNpaWl06dKl6DaSdhx2PA9HF8Etz8Htb4Gv/9WfJyK5KFyKSMlmcmD/TNj1MpStDC1mWAOwexljTIGDisvvZLJh3wzYPRHKVoWW70L1IgyxIiWcwqWIlA7pJ2Dni3D4M2vw6xYzIaiO3VWJ3c5ut+7ylLQTbhkNTSZBmbwdn0Sk8BQuRaR0+WU9fD/cGnC97iArTARWt7sqKW7JP8Let+DIHKh6L7R8D0Ib2V2VSImgcCkipU9OBsS9b4WL7PNQf7jVJrNsFbsrk6KW/CPsnmx12rmhqfXHRc2H7a5KpERRuBSR0is7DQ68D3vfhuxUa1zMW0ZBuWp2Vybudm43/Pg6HP0CKjSGJhOh1iOA2rGKuJvCpYhIdhrEvQex70DWOSt01B9uXS4V7+XMgvglEPdPOPUN3NAYGr9sDS3ko5H4RIqKwqWIyCXOTDj2bzjwIZxcC6ENoe4QuHlokQ7ELm6WnmB13No/03oc3gEaPmt15NKZSpEip3ApIpKfs9uts5lH5lljHdbqBXX+D6rdDz5+V3++FC9HChxbBj/PhxOrrfazN/8Rbv4TlK9pd3UipYrCpYjIlWQlwaHZ8PM8644/ZStD7d5Q+3Hrsrkur9onOw0SVsDPCyDhP2CcUL0zRDxhNW3wDbC7QpFSSeFSRKSwLhyygszRBZD0AwTWsM5o1ugKVe8DvyC7Kyz5Mn6BkzFwfCUcXwE56dZl7zr/ZwVKNV8QsZ3CpYjI9Uj5yboEe2yZFTR9A6DqPdadXap1hopNUfs+N3BmQeJmOLHGutydtNNqplDlHqj9KNTqDeWq2l2liFxG4VJE5PfKOPlr+DkRA5mJ1sDs4fdD5VZQ5W64oYnaahZGdiqc3Qan/2uFyl/WQ/YFCKlvBffqXSC8vc4Si3gwhUsREXcyTkjaYQXNXzbAmW+tziZ+QVCpBVRuffHrLigXbne19jt/wAqSZ76FxC3WeJQm22pyULm11YGqehcIrmt3pSJSSAqXIiJF7cIhSNxk9UBP3AxJ/7NCaEBFqBAJFW799fsNjUvmIO5ZSdbdcZL3Wt/Pbodzu8Bx3jqjG9rAutRdpQ1UusN6LUTEKylciogUt6wkOPM9JO9xha2cpH0cTgjj5vADVris0AiCakP5Ohe/17K+B9WBMoF270FeWUmQFg+pP1tfafGQehQuHIaUWHCkkOMDh8KqUN+vKYRGwg23WrdgrNgMypSzew9ExE0ULkVEPMBLL8GHHzg5vPVrQrJ3wvn9ucNaduqvC5etAuVrWN8DKkHZStZ31+OK1uNL7RL9Q8GnjPU44AasjkY+4B9iXbIHcDqsto1g3Xs9J9167EiGzLOQdfHrt48zT0PaUesMpKu+ypeF4QgrKIdG8nrYGv5R5gO2sY3a1C7CV1NE7KRwKSJisxUr4KGHYNYs+MMfClgo66x1JjAtHlKPQPoJK9hlnrXOGl4e+C6FRHe6FFgvD68BlS4GyZoXg+TFM61+5fNdxQUu0JrW+OHHZjZTnvyXExHvpnApImKjI0fgjjugRw/49FM3rdTpsILmpbOd2ResaWDdOx1jtfnMPg/+Fazpvv7gF2w9LhP462Vq/wpWoHTTsEqHOUxLWtKNbnzGZ25Zp4h4FoVLERGbZGRAmzaQkwP//S8EemBTyqKwhjV0pzv/4B+MYITd5YiIm+m+ZSIiNhk+HA4fhiVLSk+wBOhMZyYykdGMZgMb7C5HRNxMZy5FRGzwwQfw9NNWsOzZ0+5qip/B8BiPsZGNbGMbNalpd0ki4iYKlyIixWznTrj7bhgzBl55xe5q7HOe87SiFSGEsIENlKWs3SWJiBsoXIqIFKOzZ6FFC6hbF1avhjJl7K7IXvvZz53cycM8zGxm212OiLiB2lyKiBQTpxOeeAKys2HePAVLgAY04FM+5XM+5wM+sLscEXEDhUsRkWIyeTKsXQvz50OVKnZX4zke4iH+wl8YyUg2stHuckTkd9JlcRGRYhATA926wcyZMGyY3dV4HidOHuZhtl38dyM32l2SiFwnhUsRkSJ29Kg1UHrnzjBnjt3VeK7znOcu7uIGbiVJr48AACAASURBVGA96wkgwO6SROQ6KFyKiBShjAxo2xYyM2HrViivOx5e0U/8xF3cxRM8wbu8a3c5InId/OwuQESkJBs5Evbtg+++U7AsjFu4hdnMphe9aE5z/kBBN1sXEU+lDj0iIkXk88/ho4/gk0/gllvsrsZ79KQnL/IiIxjBd3xndzkico10WVxEpAjs2gWtW8Ozz8Ibb9hdjfdx4uQBHmAnO9nOdqpT3e6SRKSQFC5FRNwsKQlatoTatWHNGvBTA6TrkkQSLWlJNaqxjnXq4CPiJXRZXETEjYyBJ5+E1FSrZ7iC5fWrSEWWsISd7GQsY+0uR0QKSeFSRMSNXnsNVq6EhQuhuq7k/m5NacqnfMp0pvMJn9hdjogUgi6Li4i4yVdfQZcuMHWq1Utc3GcMY3iXd9nIRlrQwu5yROQKFC5FRNwgPt4aKL1DB+v2juJeOeTQgx7EEss2tlEF3T9TxFMpXIqI/E4OB7RvD6dPW+NZhobaXVHJdJaztKQlEUSwmtX4aahmEY+kNpciIr/TqFHwww+wZImCZVGqRCWWsIStbGUc4+wuR0QKoHApIvI7zJ0L778PH38MkZF2V1Py3cZtfMiH/I2/MR+1PxDxRLosLiJynXbvhlat4Omn4a9/tbua0mUUo5jFLDaxieY0t7scEbmMwqWIyHU4fx7uvBMqVoT16yFA43sXq2yy6UQnjnCE7/meylS2uyQRuUiXxUVErpExMGSIdSeeRYsULO3ghx8LWEAOOfSlLznk2F2SiFykcCkico3efhuWLYMFC6BGDburKb2qUpVlLGMzm3mZl+0uR0QuUrgUEbkG69fDX/4Cb70F7drZXY00oxkf8AFv8AZf8IXd5YgIanMpIlJoJ09C8+ZWW8ulS8HHx+6K5JLhDOczPuO//JfGNLa7HJFSTWcuRUQKweGAxx6DkBCYPdu9wXLv3r2MGjWKli1bXnG5s2fP0rBhQz75RPfY/q1pTKM5zelFL85xrli3rfdPJDeFSxGRQhgzBnbssAZKr1DBves+fPgwq1at4vTp01dczs/Pj7CwMIKDg926/czMTLeuzw7++PMFX5BGGo/zeLF28NH7J5KbwqWIyFUsWADTp8N778Gtt7p//T169KB586uP1RgaGsqWLVvo06ePW7c/fvx4nE6nW9dph3DCWcQiNrCBV3m12Lar908kN4VLEZEr2LcPhg6FZ5+FgQOLbjv+/v5Ft/Ir2L17N++//74t2y4KrWjFP/gHr/AKi1lcbNvV+yfyKz+7CxAR8VQXLkCvXtZtHd955+rLb9q0iejoaGrVqoWvry9Dhw5lwYIFOJ1O/P396d27NwCLFi3C4XAQGBhIz549AfDx8cHnYkPOVatWsWHDBpo1a8Zjjz3mWn9mZiaLFi0iLCyMrl27uqanpKSwYMECYmNjqVu3LoMHD8516TUjI4OFCxfy448/0rp1azp37kxgYCCbN2+mX79+pKamMn/+fPz9/d1+Vs0OwxjGDnYwhCE0ohGRFO6+nHr/RNzEiIhIvvr0MaZqVWPi46++7NixY82cOXNMamqqmTdvngkODjbGGJOSkmLatGljQkNDXcsmJCSYJk2amGrVqrmmDRw40ERERJiXXnrJtGrVytx4440GME888YQxxpj9+/eb3r17G8BMmTLF9bz9+/ebBx980Kxevdrs3LnTNG7c2NSrV88kJSUZY4w5cuSIadu2rZk1a5aJj483999/v6lbt65JT083GzduNP379zeAWbFihVm9erU7XjaPkGWyzD3mHtPQNDTnzLmrLq/3T8R9FC5FRPLxt78Z4+trTGH+v87KyjJhYWFm3759rmmjRo1yPR4xYkSucGKMMX/84x/zhJOQkBDz3XffGWOMycjIMB07djSAWbNmjTHGmNOnT+cJJ506dTJLly51/RwdHW0AM2HCBNf8oUOHuuavWLHC+Pj4mCVLlhhjjJk8ebIBjNPpvPqOepkEk2BqmBrmYfOwcZqC90/vn4h76bK4iMhv/Pe/MG4cvPYadO589eX9/f0JCQmhY8eOfPDBB3Tr1o3x48e75vv65m3ent+0ypUru4azKVu2LEOHDmXt2rWsWbOGTp065ellfOLECWJiYrj99tv59ttvAbhw4QItWrQgLS2NAwcOEBMTw3/+8x/Xc3r06MHJkyepWrVqoV4Lb1ad6ixkIe1pz2u8xl/4S77L6f0TcS+FSxGRy/zyC/TpA126wIsvFv55M2fOZMCAAXTv3p3WrVsTFRVFlSpVflctnTt3xs/Pj4SEBCBvoImLiwNg7NixVK5cOc/zly9fDpAn1JSmYHI3d/NX/spzPEczmtGDHvkup/dPxH3UW1xE5KLsbHj8cQgMhE8/vbaB0nv06MGBAwd47rnn2L59Oy1atCA2NvZ31VOhQgUCAwOpX79+vvMDAgIA2LFjR55558+fJzAwEIDVq1fnmZ+YmPi7avMmIxnJYAbzBE9wgAP5LqP3T8R9FC5FRC76f/8Pvv3WGtfyhhsK/7zU1FRmzZpFpUqVmDp1KuvXr+fChQvMmzcPsMY3/O1A18YYcnKuPND3yZMnOX/+PPfee2++8xs2bEiZMmWYOHEiWVlZrumJiYnMmTOHyMhIfH19Wb58ea5tHTx4kG3btuVa19Vq8Xbv8i71qc+DPEgKKbnm6f0TcS+FSxERYNky+Pvf4Z//tO4ffi2cTicTJ04kIyMDgNatW1O/fn3XZdU6deqQmZlJTEwMxhgWLFjAli1bSE5OJjk52RUM0tLSSEtLc633nXfeYfDgwXTo0CHf7VasWJFhw4axdetW2rVrx9y5c4mKiqJ///707duXGjVqMHDgQHbt2kWfPn1Yt24d7777LhMmTHANhXOpxu3bt7Nx40bXPpQ05SjHYhZzhjMMZjAG45qn90/EzeztTyQiYr/9+42pUMGYp5++vuenpKSYwMBA06RJEzN9+nQzadIkM2TIEJOVlWWMMSY1NdU0btzYACY8PNzMnj3bDB061FSsWNGMGTPGnD592mzevNm0atXKNGzY0EyePNkMGTLEjB492qSlpbm2k5WVZQDz2muvuaalpqaagQMHGsAAJjQ0NFfv4+TkZPPII4+45kdERJjvv//eNf/QoUMmPDzcVKxY0fzrX/+6vhfAi6wz64yf8TNvmjdd0/T+ibiXjzHG5B87RURKvtRUuOsuCAqCb76BsmWvfR3GGNLT08nJySEuLo4GDRrk6YRhjGHPnj3Uq1eP8uXLExcXR82aNV3t6i45efIkx44do1GjRgQFBeWa53A4CAgI4MMPP+Spp57KNe/06dMcPXqURo0a5VknQEJCAomJiURGRua5m4zD4SA7Ozvf55VEf+fvvMALrGAF3eim90/EzRQuRaRUGzQIVqyAbdvgppvsrubK0tPTKV++POvWraN9+/Z2l+PVhjCEZSzje76nHvWKZZt6/6S0UJtLESm1ZsyAzz+HOXM8N1gePHiQkSNHkpCQQHx8PE2bNuW+++6zuyyv9x7vUZe69KIXqaQW2Xb0/klppHApIqXSt9/CmDEwaRJcdptnj3PhwgVWrVrFHXfcwcyZM1mxYoXrHtZy/QIJZDGLSSCBp3jq6k+4Tnr/pDTSZXERKXVOnYI77oDbboN//xvyudmKlBJf8RVd6MLbvM1oRttdjkiJoHApIqWK0wndusG+fbB9O4SF2V2R2O0t3mI841nJSrrQxe5yRLyewqWIlCrjxsE//gGbNllnL0UMhr70JYYYtrGNm/DQBrgiXkLhUkRKjRUr4KGHYNYs+MMf7K5GPEkqqbSiFX74sZnNlKe83SWJeC2FSxEpFQ4cgJYt4cEHrfuGi/zWEY7QghZ0oxuf8Znd5Yh4LYVLESnxMjKgTRvIyYH//hc01rQUJIYYutGNqUxlJCPtLkfEK6mPpIiUeMOHw+HDsGSJgqVcWSc6MYlJjGY0G9hgdzkiXklnLkWkRHv/fStcLlkCPXvaXY14A4PhMR5jIxvZxjZqUtPukkS8isKliJRYO3fC3XfDCy/A5Ml2VyPe5AIXaEUrylKWTWwiEJ3yFikshUsR8VrHj0P16vkPgn72LLRoAXXrwurVUKZM8dcn3m0/+7mTO3mYh5nN7HyXySADBw5CCCnm6kQ8l9pciojXeukl69aNZ87knu50whNPQHY2zJ+vYCnXpwEN+IzP+JzP+YAP8sw/xjHa0pbP+dyG6kQ8l8KliHilzEyrHeXatdC0KWzb9uu8SZOs6fPnQ+XKtpUoJcCDPMgEJjCSkWxko2v6N3zDbdzGNrZp2CKR39BlcRHxSsuXWwOig3Vm0tcX3nkHIiOt2zvOnAnDhtlbo5QMBkNverOFLWxjGytZyXCGA5BDDj74cJjD1KGOzZWKeAaFSxHxSgMGwIIF4HD8Os3HBypVgs6dYe5c+2qTkuc857mTOznDGRJJzDXPH39e53XGMMam6kQ8iy6Li4jXycyEpUtzB0sAYyA52eolfvCgPbVJyZRMMj74cIYzeeZlk82n6LZPIpcoXIqI11mzBtLS8p+XnQ1xcdCsmXUvcZHf61L7ygMcwIkzz3yDYTe72cteG6oT8TwKlyLidRYsAD+/gudnZ8OFC9CrF+zYUXx1ScnzH/5DBzqQRBIOHAUu548/X/BFMVYm4rnU5lJEvEpmJoSFQWpqwcv4+sItt8Cnn8IddxRfbVLyGAyf8AnP8zzppF8xYEYQwWEOF2N1Ip5JZy5FxKtERxd8SdzfHwIC4PXXYdcuBUv5/Xzw4Ume5DCHGcQgfPDBt4D/Oo9whB3oVLmIwqWIeJUvvsj/krivrxUmd+2CF1/UwOniXpWoxCxmsY51RBCBH3k/hAEEMI95NlQn4ll0WVxEvEZGhnVJ/PIzl5fOVr72Gowcmf+tIEXcKZ103uItXuM1fPDJdam8ClU4yckCz26KlAb69IuI14iOhvR067GPj/XVoQPExsKoUQqWUjwCCWQSk9jBDm7jtlxBMpFENrHJxupE7KdfxSLiNb642BnX3x9uuAHmzYNVq6BWLXvrktKpCU34lm+ZxjSCCCKAAHzwYS4awV9KN10WFxGvkJ5u3Sc8LQ3694dp06xL5CKe4DjHeZqnWc5ybuAGTnEKf/ztLkvEFgqXUmolJMC6dXZXIYW1bRvMmQNDhkDTpnZX49lat4Z69Ypm3QtYcMXheEq77WznUz7lSZ7kNm6zuxwppBu5kfa0t7uMEkPhUkqt6Gjo3t26xCqezxirjaVcmcMBH30ETz5ZNOsPJpgMMtRh5SoMBh/0gfUGOeTQmc5EE213KSXGFe5xIVI6nDkDISF2VyHiHsHBRb+ND/mQJymi9CpSzIYwhJOctLuMEkV/eoqIiIiI2yhcioiIiIjbKFyKiIiIiNsoXIqIiIiI2yhcioiIiIjbKFyKiIiIiNsoXIqIiIiI2yhcioiIiIjbKFyKiIiIiNsoXIqIiIiI2yhcioiIiIjbKFyKiIiIiNsoXIqIiIiI2yhcioiIiIjbKFyKiIiIiNsoXIqIiIiI2yhcilyn48eP849//INnnnmGl19+mXXr1pGens6+ffvYu3ev3eUVKDs7m8WLF9OxY0emTZtW4LTr8fPPPzN+/HgiIiLyne+tr9m1SEpKIjIyktmzZ9tdisfx1vdfx0zR0jFT8ihcilyHN954g1atWpGZmcnQoUMZNWoUDoeDbt260bZtW/bv3+/2bWZmZrplPceOHSMhIYGvvvoKh8NR4LTrcejQIdavX8+xY8fyzLPjNbODn58fYWFhBAcH212KR9Exkz8dMzpmSiQjUkr95z/GgDEpKdf2vKlTpxp/f3+zadOmPPPS09PNXXfdZT7++GM3VfmrP//5zyYnJ8ct6zp9+rQBzDvvvHPFadfjhRdeMGXKlMk1za7XrDQKCjLmo4+KcP0myHxkrm0DOmauTMeMvQabwaar6Wp3GSWKzlyKXIN58+bx/PPP8+qrr9KmTZs888uVK8eMGTM4e/asW7e7e/du3n//fbetz8/Pr1DTroe/v3+un+16zcQz6Ji5Oh0zUtK458gQKSWmTJkCQPfu3QtcpmXLlhhjXD9nZmayYcMGNmzYQI0aNejatSv16tVzzT9w4ABRUVG88sorHDx4kC+++IKqVasyePBg/P392bx5M/369SM1NZX58+fj7+9Pnz59OHjwIFFRUUyaNIno6Gj27t3L888/j7+//1W36ePjk6fu/KYBpKSksGDBAmJjY6lbty6DBw/OdfnK4XCwdOlS/ve//3HffffhdDptf81WrlxJSkqKa78eeeQRypYty44dO9i3bx8APXr0IDQ09Ir7d6XXeNOmTURHR1OrVi18fX0ZOnQoABkZGSxcuJDw8HA6d+7stn3yVjpmdMzomCmF7D1xKmKfa70sHhcXZwDj5+dnMjMzC/Wc9PR0c99995n58+ebpKQkM2PGDBMSEmIWL15sjDEmKirKhIeHG8D8+9//Nr169TI9evQwgJkwYYIxxpiNGzea/v37G8CsWLHCrF692syePdtUq1bNACYqKso0a9bMAGbz5s1X3aYxxiQnJ+e5nJfftP3795sHH3zQrF692uzcudM0btzY1KtXzyQlJRljjDl37py5//77zaRJk8yZM2fM7NmzTUBAgOsSn12v2YkTJ8wdd9xhgFyXFZ1Op+nevbuZN2/eVffvSq/x2LFjzZw5c0xqaqqZN2+eCQ4ONsYYExsba3r27GkA89Zbb7l1nwrLky6L65jRMeMNx4wui7ufwqWUWtcaLmNiYgxgbrnllkJvo1+/fmbIkCG5pvXu3dsEBgaa+Ph4Y4wxY8eONYBZtmyZa5n27dubBg0auH6ePHmyAYzT6XRNGz9+vOuXuDHG/PTTT8bpdBZqm4X9j7JTp05m6dKlrp+jo6Nz/fIePny46dmzZ65tPfDAA67/KO18zS5te86cOa5pmZmZplevXoXev/xe48zMTBMWFmb27dvnet6oUaNcj48fP57nP0p37VNheFK41DGjY8YbjhmFS/dTm0uRQrrW9lVpaWksXLiQZs2a5Zr+9NNPk56ezieffAJAUFAQkPsSWOPGjfPtPXq5wMBAAPr27QtAw4YNSU9PL9Q2C+PEiRPExMSwZcsWxo0bx7hx41i5ciUtWrQgLS2NU6dOMWvWrFyXsQCaNm3qemzna9axY0caNWqUq93dkiVL6NOnT6H2D/J/jQMCAggJCaFjx45ER0cDMH78eNc2ftvjtag/B55Mx4yOGR0zpZPaXIoUUv369QGIi4sjPT3d9Uu0IFu2bMHhcOT5z+LSei4NI+Lrm/dvvKCgILKzs6+4/vzaexV2m4URFxcHwNixY6lcuXKe+TExMTgcDqpVq1ZgXXa/ZiNGjOCZZ55h165dNG3alKVLl/LZZ58Vav9+uy+XmzlzJgMGDKB79+60bt2aqKgoqlSpkm9tRf058GR2v/+/pWMmNx0zUlR05lKkkG688UZuvfVWcnJy2LNnzxWXNcaQk5MDWL8oL3fpl3KDBg3cXqM7txkQEADAjh078sw7f/4858+fB6yzGQWx+zUbOHAgoaGhzJw5k9jYWOrXr+/ar6vt35X06NGDAwcO8Nxzz7F9+3ZatGhBbGxsvsva8TnwFHa//4WhYyY3HTPiDgqXItdg8uTJgPWXe1ZWVr7LJCYm8sknn9CsWTPKli3L5s2b88wHaNu27TVv/9Iv3YK4c5sNGzakTJkyTJw4Mde+JiYmMmfOHG655RYA12Wuy13e+9XO1yw4OJhBgwYxZ84c3nnnHVfv1MLsX0FSU1OZNWsWlSpVYurUqaxfv54LFy4wb968fJcvis+BN9Exo2NGx0zpo3Apcg0effRRpkyZwoYNG3jqqadITU3NNf/o0aO8+eabDBgwgKpVqzJy5EgOHz7M119/7Vrmyy+/pE+fPrRr1w7ANVZdenq6a5ns7GwcDofrDiOXLh9t376djRs3kpGR4boryJkzZ1zPK+w2L1y4AJCr/t9Oq1ixIsOGDWPr1q20a9eOuXPnEhUVRf/+/enbty+RkZF07dqVFStWEBUVBUBWVhY7d+7EGEN8fDzZ2dm2vWaXPPPMM6Snp3PmzBlq167tmn61/QPyfY2dTicTJ04kIyMDgNatW1O/fn3Xe/Tb17Eo9smb6JjRMaNjphSyszeRiJ2u9w49xhizaNEi07hxYxMYGGjatWtnnnnmGfPUU0+ZSZMm5Ro+JCcnx4wePdpUqVLFvPjii2bQoEHmscceM+np6cYYY7788ksTERFhADNq1Chz6NAhM3/+fHPTTTcZwLzwwgvml19+MYcOHTLh4eGmYsWK5l//+pdZtGiRadiwoQFMnz59zA8//FDobSYkJJinn37aACYyMtJ8+eWX+U4zxpjU1FQzcOBAAxjAhIaG5uopevLkSdO2bVsDmAYNGpiHHnrIPPHEEyY4ONiMGDHCHDt2zLbX7HKdO3c2q1atyvM+Xmn/CnqNU1JSTGBgoGnSpImZPn26mTRpkhkyZIjJysoyR48ezfU6RkdHF9k+FcSTeotfTseMRceM5x0z6i3ufj7GXDYKq0gpEh0N3btDSgqEhFzfOlJTU9m9ezc333xzgQ3cwfrL+qeffqJRo0aUK1fuurblcDjIzs6+agN/d27zktOnT3P06FEaNWqU7/YPHjxITk4O9evX58iRI4SFhREaGprvuorzNbskPj6emjVrFtjZ4Gr7dzljDOnp6eTk5BAXF0eDBg0KfU9kd+5TQYKDYfp0ePLJIlk9wQQznek8yfVtQMeMRceM5xwzQxjCSU4STd7mCnJ9FC6l1HJHuBTxNJ4eLkU8jcKl+6nNpYiIiIi4jcKliIiIiLiNwqWIiIiIuI3CpYiIiIi4jcKliIiIiLiNwqWIiIiIuI3CpYiIiIi4jcKliIiIiLiNwqWIiIiIuI3CpYiIiIi4jcKliIiIiLiNwqWIiIiIuI3CpYiIiIi4jcKliIiIiLiNn90FiNhtwQIoV87uKuyTlGTtf2Cg3ZXkZQykpUFQkN2VeI/s7KLfxla2EkBA0W/IS+WQgy+++OBjdyl5JJNMIIF6/y5ziEOUp7zdZZQoCpdSavn6gr8/DB9udyX2ys4GHx8oU8buSvKXnQ1++k11TYryvQwggKiL/yR/zov//Dz0v9hssilDGY8Mv3bpSle7SyhRfIwxxu4iRKT4GQP9+8Pq1fDtt3DzzXZXlL+aNaFRI1i5EgJ0skU83ClOUZ/6vMiLvMRLdpeTr7u5m+/5nld5lRd4gTJ46F+W4rXU5lKklHrtNVi40Pry1GAJUKECrF0LvXsXzyVfkd9jPOMJIYTneM7uUgr0AA+QTTbjGc+93MvP/Gx3SVLCKFyKlELLlsHEiTBtGnToYHc1VxYebn3/z39g2DDrjKuIJ9rLXqKI4k3e9Og2fN3pDliX77/neyKJ5EM+tLkqKUl0WVyklImNhVat4NFH4eOP7a7m6vr2hS++AKfTaif7zDMwfbrdVYnk1ZWunOIU29iGrwefuzEYqlGNU5xyTfPBh1704kM+pBKVbKxOSgLP/fSLiNudOwcPPADNmsEHH9hdTeFUrvxrhx6nE2bOhDfftLcmkd9az3pWs5qpTPXoYAlWkHyYh3P1GDcY/s2/uZVbWc96+4qTEsGzjwARcaunnoKMDOtMoL+/3dUUTliY1Zv9EmPgpZe8JxxL6fAar9GBDrSjnd2lFEp3uuPAkWuaAweJJNKBDjzLs2SSaVN14u0ULkVKiX/+E5YsgdmzoWpVu6spvLAw64zl5YyBp5+G+fPtqUnkct/xHWtZy3jG211KoXWiU75DJeWQg8HwHu9xG7exi102VCfeTuFSpBTYuxf+/GcYPx46drS7mmtTuXL+vcSNgSeesDr6iNhpClO4i7vogIf3jrtMEEHcwz0FXsLPIYeDHKQlLXmXdzGoe4YUnsKlSAmXnQ2DB0PTpvDyy3ZXc+3CwgruIe50wiOPwDffFG9NIpf8yI+sZCV/4S92l3LNHuKhK7YPzSYbBw4mMIGd7CzGysTbKVyKlHBvvAG7dsFHH3nnnW4qVy54njGQkwPdusGOHcVXk8glU5hCE5rQgx52l3LNutOdbAoePNYXX9rSlt3sphnNirEy8XYKlyIl2O7dMGUKvP463Hqr3dVcn7CwK8/PyYH0dOjSBeLiiqcmEYCTnGQxixnDGK+8lWIDGlCHOnmm++GHL76MZSxf8zU3cqMN1Yk3U7gUKaGcTqvTS7Nm8Jzn3izkqq505tLX1+pJHh4OL7xw5WVF3C2KKIII4lEetbuU69aTnrmGJPLDj5rUJIQQHDg8flgl8Uz61IiUUB99BFu3Wr3Efb34SA8KyntP8UvDKNWpA1FRcPQojB0LFSsWe3lSShkMH/MxgxhEIIF2l3PdutOdLLJcZ14HMYg97OF1XmcGM9jHPpsrFG+kO/SIlECnT0PDhjBoEPz973ZX8/uFh8OpU1aodDqhVy84cgQiIqwxO0WK29d8TQc6sJOd3MZtdpdz3TLJpCIVCSCAT/iER3gEsDrzNKc5dajDcpbbXKV4Gy8+nyEiBXn1Vets3+TJdlfiHlWqQGioNZzSkSNWoBwyBFauhLQ0u6uT0mgWs2hFK68OlgBlKctkJvMjP7qCJViXx//KX1nBCjaz2cYKxRvpzKVICXPoEDRqBDNmwNChdlfjHmvXwt13Q/nyv0775ReoUcMaGP7hh+2rTUqfJJKoQQ1mMpM/8Ae7yylS7WlPDjl8g8b7ksJTuBQpYR57DPbssYYf8sahh67FPfdA/frwySd2VyKlyWxm8yf+xClOEUqo3eUUqU1soi1tiSGGjnjZHRjENrosLlKC7NoFixZZQw+V9GAJ0LkzxMTYXYWUNktYQic6lfhgCXAP99CFLrzGa3aXIl5E4VKkBHnjDYiMhIcesruS4tGxI/x/9u48rqoyf+D4jCBTXQAAIABJREFUh11EEVwAV1RUEqk0lzI0Nc01S0sycW8a09LKxiynLLOmqWmqsX41jTaFNpnkvpLimmLuu6ggqKAIArLJ5oX7/f1x4AqCinjhcC/P+7x4Xe65Z/new33O/fKc8zzPpUsQGal3JEpNkUUWm9jEMIbpHUqVeZM32c529rFP71AUC6GSS0WxEtHRWq3l7NmW3fXQ3ejWTWvos2WL3pEoNcUOdpBHHoMZrHcoVaYvfXmIh/gX/9I7FMVC1JCvIEWxfv/8J7RqBSNG6B1J1bG3h8ceg61b9Y5EqSm2sAV//GlMY71DqVJv8AZLWcolLukdimIBVHKpKFbg2jVYvBheeQXs7PSOpmp17w779+sdhVJTbGELfemrdxhVLpBA3HFnEYv0DkWxACq5VBQr8L//gcEAY8fqHUnVe+ghuHBB6zheUSpTJpkc5ziP8ZjeoVQ5RxwJIojv+R5BdTKj3J5KLhXFCsyfr3VBVL++3pFUvS5dtMfDh/WNQ7F++9mPESPd6KZ3KLp4gReIIYad7NQ7FKWaU8mloli4M2e0xGriRL0j0UfDhtC8ORw6pHckirU7wAGa0ISmNNU7FF08wAP4488KVugdilLNqeRSUSzcsmXa2Ns9eugdiX7at1fdESmV7yQnLX64x3s1lKFqrHHljlRyqSgWbvlyGDas5jXkKa5lS23McUWpTJFE0o52eoehqyEMIYYYTnFK71CUakwll4piwS5cgCNHYPhwvSPRl7e3Si6VyqeSS3iER2hIQ9axTu9QlGpMJZeKYsG2bwdHR+jVS+9I9NWyJcTFQUGB3pEo1iqbbK5yFW+89Q5FV3bYMYhBrGe93qEo1ZhKLhXFgoWHa62la9XSOxJ9NW2qdcWUkqJ3JBWTn5/P8uXL6devH/PmzbvlPEU/V7gCgAceOkeiv0EMIpxwrnFN71DuiSp3lUcll4piwcLDK68hT15eXuVsuBK4uGiPWVlVu19zHaOLFy8SHx/Pli1bMBgMt5yn6CcZrSPVhjSslO1bUnl7lEfJJ59D6NNFgyp31Z9KLhXFQqWlwenT2gg1leGdd97BaDRWzsbNTK/k0lzHqGXLlgQFBd1xnqKfolq6utStlO1bUnnzxpvGNGYf+3TZvyp31Z9KLhXFQkVEgNEIHTuaf9vHjx/nu+++M/+GK4keyaW5j5G9vX255in6yCcf0O45NDdLK28AXejCfqp+3FVV7iyDOoKKYqHOnAFnZ60D8eLy8vLYsWMHO3bsoEmTJgwcOBAfHx8AQkJCMBqNODg4MGLECACWLVuGwWDA2dmZYcOGER4eTlBQEFlZWSxZsgQHBwcCAwMByM3NZenSpZw8eZLu3bvTv39/nJ2dy7VvgPPnz/Pjjz/y9ttvk5iYSHBwMJ6enowaNQo3Nzeio6NZunQpjo6OTJw4EXd39xLvLSMjg5CQEE6dOkXr1q2ZMGECderUwcmJwviKHu8tzrNnzxIcHMzcuXOJjo7m119/xcPDgwkTJuDg4HDLYxQdHU1wcDBz5swhNDSUiIgIpk+fjoODwx33aWNjU+pvXNa82x0H4LYxKBVXgNZa7ObksiaWN4CudOVHfiyxvCp3qtyZiKIoFumtt0QefLDkvJycHOndu7csWbJEUlNT5euvv5a6devK8uXLRUQkIyNDAgICxNXV1bROfHy83H///eLl5SUiIjt37pTRo0cLIOvWrZONGzeKiMj58+elZ8+esmDBAomLi5O+fftK69atJScnp1z7/uWXX6RZs2YCyNKlS2Xs2LEyevRosbOzk2eeeUZ27Nghzz//vIwePVrs7e1l8ODBJd5bZGSkDB06VDZu3ChHjhwRf39/8fHxkdTUVImJEQGRffvuPc7g4GDx9PQUQNasWSPPPPOMDBkyRACZPXv2LY/RwoULxcvLSwAJDg6WTp06CSDh4eF33KeISHp6ugDy2Wef3Xbe7Y7D7WJQ7s1W2SoIckWumObV1PImIvKb/CYIkiiJZolXlTvropJLRbFQw4eLBAaWnBcUFCQTJ04sMW/EiBHi7OwscXFxIiIyderUEl92IiIvvvii6ctOROSDDz4QQIxGo2neE088IZMmTTI9X7dundjY2MiKFSvKve+i7a5evdq0zMsvvyyALFq0yDTv3XffFUDS09NL7H/lypWm56GhoaYvnmPHtOQyIsI8cc6cObNUnH369JF27drd9hi98847pi8YEZHTp0+L0Wgs1z7L+yV3u+NwuxiUe3NQDgqCREqkaV5NLW8iIgmSIAiyVbaaLV5V7qyHuudSUSzU5cvQrNmN59nZ2SxdupROnTqVWG7KlCnk5OTw44/aJSxb29LFvqx5xZ09e5awsDCGDRtmmjdkyBASEhIYPnx4ufdddAnpscceMy3z4IPacHo9ijV7v++++wC4dOlS4Xu9TFhYGLt372bWrFnMmjWL9evX06VLF7Kzs7lW2CNKcrJ54nQpvIlz8ODBpmX8/f25ePHibY9T0SXAUaNGAeDr60tOTk659lkedzoOt4rhVpf5lPJzww2AdNKBml3eADzxpA51iCHGbPGqcmc91D2XimKhkpOhYbFeUXbv3o3BYCh1M3rbtm0BiLyHwbdPndKGeiv6siri4eFxV/su+lItftJ1KrphshhHR0cAU1cgUVFRAMycOZOGDUt3BbNpk/Z48aJ54yzOxcWF/Pz8UvOLK+vLxJx/lzsdh1vFoNw7L7ywwYaLXKQLXWp0eSvSilbEEIPHKQ+zxlucKneWSdVcKoqFSk6GRo1uPC8oHJ5m9+7dJZYrOhm2a1fxYeuK/ivfuHFjqdeSkpIqdd9w48vv0KHS/eplZmZy7hzUqweNGukbZ1nMuc87HQel8tSmNk1pShRaolGTy1sRH3yIIUb3eMuiyp2+VHKpKBYoPx/S06FBgxvzOnXqhJOTE+Hh4SWWTUpKAqBnz54AuLq6luqEWERMJ+Piiub5+flha2vL2rVrSywXHR3NgQMHyr3vivL19cXOzo7333+f69evl9j+zz//TFQUtG2rT5xlHbfizLnPOx0HpXK1ox2RaDVeNbm8FWlNa6KJVuVOKUUll4pigXJzQUTriqiIh4cH06ZN49y5c2zbts00f9WqVQQGBtKrcAByb29v8vLyCAsLQ0QICQlh9+7dpKenk56eTkFBAY0Kq0QPHjzIzp07qV+/PuPGjePYsWMEBgaydetWvvnmG2bPns3AgQPLve9rhTdHZhXrkLLoUlxOTo5pXtFlsKLl3N3dmTx5Mnv27KFXr14sXryY4OBgRo8ezahRo4iKgnbtoEmTJmaJ8+rVq2XGZDAYTInCzccoNzfX9F5Sio1DeS/H5uZ5dzoOxY9niqWOhVmN3c/9HOQgULPLW5HWtCaGGFXuUOWuFH3bEymKUhGpqVrr6E2bSs4vKCiQN954Qxo1aiRvvfWWjB8/Xp577jlTdyAiIllZWeLv7y+AeHp6ysKFC2XSpEni7u4uM2bMkOTkZImJiRFPT09xd3eX77//XkS0FpTDhw8XQABp2bKl7N+/v9z73rRpk2m/kydPljNnzsiGDRuka9euAsiYMWPk2LFjsnXrVunRo4cAMmLECImIiDDFPW7cONP+XV1dTa0377tP5P33xSxxrlq1Slq2bCmAvPbaaxITEyNLliyRVq1aCSBvvvmmJCYmljpGy5YtE19fXwEkMDBQjh49Wu59xsfHy5QpUwQQPz8/WbVqVZnz7nQcbheDcu+WylKxEztJkzQRqbnlrchyWS4Ikid5qtypcleCjYhI5aaviqKYW1ISeHjA1q3Qp0/p13Nycjh9+jTt27enVq1apV4XEU6cOIGPjw+1a9cmKiqKZs2alejw2GAwkJ+fX2IeQHx8PElJSfj5+ZXZQfCd9n2vkpOTiY2NpX379jg7O5OSoh2L1avhySerNs5bHaNbMeexufk4KJUvkUQa05gNbGAgA03za1J5K2472+lDHxJIwBPPKotXlbvqTyWXimKBEhKgcWP4/Xe4x9urLN7SpRAUBCkp4OqqdzSKtXuQB+lJT/6P/9M7FN0d5zgP8AARRNCe9nqHo1Qj6p5LRbFAhY0XKXZveY21bRt06aISS6VqBBLIr/xqGmu8JqtPfQCuclXnSJTqRiWXimKBCvsaptg96DXWli3w+ON6R6HUFM/xHEkk8Tu/6x2K7hqgdVeRgmrEopSkkktFsUBOTmBvr5LLEycgMhIGDdI7EqWmaEc7HuZh5jNf71B0V6twSiVV71CUakYll4pioVxcVHK5eDG0aAEBAXpHotQkL/MyK1jBJS7pHYrunHDiOur+HKUklVwqioVq0EAbpaemEoElS2DUKFAjrylVaSQjqU99vud7vUPRnR12FHD7Ds2Vmkcll4pioRo3hsuX9Y5CPzt3wrlzWnKpKFXJCSf+xJ/4ju/IIefOK1gxe+xV4yalFJVcKoqF8vLSuiSqqebPh65d4cEH9Y5EqYle5VXSSecHftA7FF2pmkulLCq5VBQLVZNrLlNSYPlymDRJ70iUmsoTT/7En/iUT2v0PYeq5lIpi0ouFcVCtWgB58/rHYU+goO1vj6ff17vSJSabCYzSSSRRSzSOxTd2GKLEaPeYSjVjEouFcVCtWsHFy+W3WLcaMXn+uvXYd48mDgR6tTROxqlJmtOc17gBT7ggxp772UuudTC/MNOKpZNJZeKYqHattVaTEdHaw1bFi2CP/0JfHy0Mcet1f/+p91rOn263pEoCnzAB6STzld8pXcousghB2fUGNtKSfZ6B6Aoyt07fRp27AA7O+jdG1JTwdZW65KnoEC7H9MaGY3w+ecwZgx4e+sdjaKABx68zut8yqf8mT+bhkQssoc9nOMco7DObg1yyVXJpVKKqrlUFAuxdy8EBmr9W7ZvD6++qiWUqYWDYxiNWmIJ1ptcrlypJdYzZugdiaLc8CZv4ogj7/GeaZ4RIx/zMQEE8A3f6Bhd5SmggOtcV8mlUoqNiIjeQSiKcmcpKeDrC1evapfDb8XREXJzrbNj8a5dtRrLZcv0jkRRSlrIQl7gBfawhyY0YRSjCCccI0bssCOJJNxx1ztMs8oiizrUYQMbGIQag1W5QdVcKoqFaNAA/v3v2yeWAA0bWmdiGRYGBw6oWkulehrHOHrQg9GMpgMd2MMeUytqQfiN33SO0PyucQ0AF1x0jkSpblRyqSgWJDAQhg0DB4dbL2Otl8Q//BD69YNHHtE7EkUpLY88mtCEKKLIJBMDBtNrttiyhjU6Rlc5kkgCoBGNdI5EqW5Ugx5FsTD//rfWDZHBUPo1Gxut/0trs2IF7Nql/ShKdRNBBCMYQSSRAKX6fcwnn/WsJ5987K3oa7couWxIQ50jUaobVXOpKBbGywu+/LLsS9/29tCkSdXHVJmuX4e334agIHj0Ub2jUZSSlrGMTnTiDGduOwxiJpnsZncVRlb5kknGFttSLeQVRSWXimKBXngB+vQpfXnc1tb6Lot/8w3ExcHf/qZ3JIpS2kAGMp7xGDFie5uvVEccWce6Koys8iWTjDvu2GGndyhKNaOSS0WxQDY28MMPWk1lcfn51pVcpqZqSeX06apfS6V6qkMd5jOf3/iNBjTAgbJviL7OdVawooqjq1zJJNOABnqHoVRDKrlUFAvl7Q0ff6zVVhaxtg7U587VOop/6y29I1GU2xvAAE5ykoEMBMCG0vetRBPNWc5WdWiV5jKXaYwVnXAUs1HJpaJYsFdf1fp+LH553FqSy7Nn4dtv4YMPoF49vaNRlDtrRCPWsIZf+RUXXErVYtpjz3rW6xSd+V3gAt6oSwpKaSq5VBQLZmurXR4vzstLn1jMSQSmTNE6jX/xRb2jUZS7E0ggJzhBN7qVuA/TiJHVrNYxMvOKJZYWWGH3FMo9U8mlolg4Pz94913tdzs7aGQFXc4tWgRbt8J335W+r1RRLIE33vzO73zBFzjggD32GDHyO7+TTrre4ZmFSi6VW1HJpaJYgVmztPHG69fXEkxLlpwMb74JU6eqrocUy2aLLa/xGnvZiw8+2GBDAQVsZrPeod2zNNLIIEMll0qZ1NjiimIljhzRLiX/8Qfk5GhjkF+9qrW4Lv57Rgbk5WnrXLt2ozP2jAytQVBxdeveqDmsV+9G4yF3d+21+vVv/Li7a0NUurnd2/sYPVrrLP3ECW0fimINcsnlbd7mK75iPOP5kR8rvK1UUskllxxySCedPPK4xjUyySSPPDLIIIssrnOddNJLdOouCGmkldheAQVkkHHbfdahTol7SPPI4yQn6UpXXHEFtEZMbrjhgAN1Cqda1MIVV2pTm1rUwg03alELZ5xxw63Mhk+K5VPJpaJYmNRUiI3Vfi5c0PqAjI3VHs+cgawsLbm8WVEy6OZ2I2EsnjwW/71I8YTz5t/T0rSE9eaE1NZW20/jxlqL9hYtoHlz7bFFC21e48ZlX+7+7TcYNAhWr4annqr4MVKU6moLW3iTN9nABtJI4+pNUwopZc5LI41ssskj77bbt8WWetTDGWdqUQsXXHDEscQyrriW6pvSHffbbjeNNIQb6YIRY6nL+/nkk0km17lOFllkkkk++bfdriOOuOBCPepRv3BqQAPT72VNRa/fqtsnRX8quVSUaiouDiIitBq8U6duPGYUq2Bo2PBG8laUyDVqpNUiFq9VrF//9uOR34v09Bs1o0U/KSlw6ZL2Hs6f1x4vXbpRS2pvD61agb+/ds+ov7/2fNQo6NYNliypnFgVpTJd5zqJJBJHHAkkcIlLXOYyl7hEfOF0mcukklpqXWecb5lENaABbrhRm9o44YQ77jjhRG1qU496OOFkqimsbglXUcKZRRZ55JFGWola11xyySKLdNLLTK6LnmeTXWrbrrjSlKY0prHpsUmxqWieE046vPOaTSWXiqIzEa3Gcc8e2LsXjh7Vksr0wkoBLy/o0OHGT8uWWjLZsiU4O+sZ+d0xGuHyZa22NTYWTp/W3ufJkxAVpSWetrZaktmxo9bF0iOPQJcu4OKid/SKAumkE0MM0UQTUzhdLJwSSCCRRNOyNtjggQdeeNGMZiUSoEY0KlVD54wFFWYd5JJbqkY3iSRT0l48eU8kscStAA1piBdeNKc5TWlK68LJBx9a01oNX1kJVHKpKFUsPV1LIvfsufGTmgq1asFDD0GnTiVr9OrXgPPe9esQGXmjpvb4cdi3D+LjtVrO+++H7t21ZPPhh6FdO70jVqxRAQXEEWdKHG+eUkgBtEvPzWiGDz60oAVNaWpKIouSGE88q10tYk2RTz6JJHKJSySQYEr+44jjIheJIYZYYk2X7N1wMyWcN08taKH+jhWgkktFqWQFBVpjm82btZ8dO7RausaNoXNn6NEDAgK0GrpatfSOtnqJj4eDByE8XGvkc/Ag5OaChwf06gX9+sHQodbTcbxSdeKJJ4IITnLS9HiYw6bLr044lajlKj61pz21qa3zO1DuRT75xBJb5j8R0USbGj3ZY08LWuCHHx3ogB9+dKYz93GfGlP9NlRyqSiVIC4ONm7UfjZv1hq/eHvDgAHQv7+WTFpDZ+dVLS8PDh3S+sDcuFFrGW80aon5gAEwcKBWs2np3TEp5nOBC0QQwQlOcLJwiiDClER6440ffvjjTwc64IsvrWmNBx46R67oKYUUookmiihOcML0GTrPeYwYqUUt2tO+xGenAx1oRSvVAh6VXCqK2Vy6BMuWwdKlsHu3VgsZEKDVrvXrp9VSKuaVlaUlmGvXwpo1WuOh+vVhyBAIDITBg1WiWZOkkcYJThBOOLvYxX72m+6DdMe9RO1TBzrQkY40pKHOUSuW5DrXiSKqVK33aU5jxIgrrtzP/XQunHrQg9a01jvsKqeSS0W5B0lJWkIZEgI7d2rd+QwbBs89B48/ri5zV7XTp2/8PU6cgGbNtL/FyJFaK3TFemSSyUEOsr9w2sc+LnABgDa0oWvh1IUu+ON/x652FOVeZJDBSU5ygAOmz2QkkRgx0pSmps9jN7rRhS64cY8dAldzKrlUlLtkNMKmTfDNN1q/jE5O2n1/I0dql2VVQlk9nDihJZlLlsDZs9CmDUyaBC+8oHX2rliWFFLYwQ62sY3tbCeCCIwYaUxj0xd30aRa/yrVQQYZpmRzH/vYz37iiMMGG3zxpRe96F04eWFd90mp5FJRyik1FX74QRvvOjoa+vSBP/9ZSyxVVznV28GDsHChNmZ5Xh48/zy8/LLW3ZFSPaWRxu/8zrbC6TjHscGGTnSiN715lEfpSlea0UzvUBWl3BJIYD/72cMetrOdfewjn3z88KMPfehNb3rRi0Y00jvUe6KSS0W5g+PHYd48WLxY64h83DgtMWnfXu/IlLt17Rr8/DN8+y0cO6Yll1Onap23V1Yn80r55JHHdrYTRhjb2c4RjiAID/AAfQqnx3iMetTTO1RFMZtrXGMXu0w18gc5iBEj/vjThz70pS/96GdxvROo5FJRbuH4cZg7F1as0PqcfPllGDNGjXdtLXbt0pLM5cu1ezPffRfGji17WEqlcqSQwnrWs5a1bGQj17hGBzqYksle9FKXuJUaJYMMfud3trOdbWzjCEdwwol+9GNo4WQJl9BVcqkoN4mIgE8+0Woq27eH996DESPARvUuYZViY+Hzz+E//9H6y5w1S7svUyWZleMc51jDGtaxjh3sQBAe5mECCeQZnqE5zfUOUVGqjWSS2cAG1rGO3/iNTDLxw49AAhnKUB7ioWrZ9ZFKLhWlUGwszJypdSXk7w/vvw/Dh6uksqY4dw7+9jftvsyWLeHjj7V/KpR7d4Yz/MRPLGc5pzlNAxowmME8xVMMYAB1UZcDFOVOcsghjDDWFk6JJNKa1gxnOOMYxwM8oHeIJiq5VGo8gwG+/FK7BN6smZZgPPOMSiprqpgYmDMH/vc/rWP2//s/8PHROyrLk0YaIYSwkIX8wR80oxnP8RxP8RQ96KFGN1GUe2DEyF72soY1/MqvxBBDJzoxnvEEEaR7gyCVXCo12s6d2r2U0dFareWsWVrXQoqya5f22YiKgrfegrffVt1M3YkRI1vZyiIWsZzlGDEylKGMZSyDGIQ96l4DRakMBznIfOazhCVkkUUf+jCJSTzN0zjiWOXxqORSqZGuXYPXX9e6Fho4UKudal3zBlFQ7sBg0HoKmDMHmjaF4GDo3l3vqKqfOOL4lm9ZyEISSCCAACYwgUACccVV7/AUpcbIJpsVrGAhC9nKVupTnzGM4RVeoQ1tqiwOlVwqNc6JE9rQgCkp8O9/w7PP6h2RUt3FxcHkyRAWpjX2mj5d3TYBEE4485jHSlbSiEa8yIuMZzw+qPsIFEVvccTxEz+xgAXEEssQhvAqr9KXvpXeCMi2UreuKNXMokXwyCPg6gr79qnEUimf5s1h3Tr47DPt8vjTT8PVq3pHpZ9d7KIvfelBD2KI4Ru+IYYY5jJXJZaKUk00pzl/5a9EE80qVpFDDv3pT0c6sohFFFBQaftWyaVSI+TmwoQJ2s+0aRAerrUIVpTysrGB116DrVvh8GHo3Fkb+acmWctautCFnvSkFrXYxS4OcIBJTKIW6oZURamObLFlKEMJI4yDHKQtbZnIRB7kQZawBMH8F7BVcqlYvdRU6N8f1qzRap/+/nfVh6FScT16aMllu3bQuzeEhuodUeX7gz94jMd4mqdpTnMOcID1rCeAAL1DUxTlLnSiE8tYxnGO05GOjGY0XenKFraYdT/qnkvFqiUmQt++kJmpJQF+fnpHdHeOHTvGsWPHSsxr3Lgxffv2vavtXLlyheDgYPbu3UteXh7Tpk1jwIAB5gz1rl24cIH58+fz888/c/78eV1jqYj8fJg0CX76SRu3PChI74jM7xKXmM50lrGMx3iMT/mUh3lY77BMVq9eTWZmpum5jY0NXbt2pV27dgDk5uaycuVKCgq0y3+2trY8/vjjeHlV/xFOKktqaioBAQG89dZbjB8/vtL2U5Hyrc53Ve84x3mLtwgllEEM4mu+Ns+tLaIoVurKFRF/f5F27UTi4vSOpuJOnTol9erVE0AWLVok+fn5d7V+VlaWBAQEyKVLlyQ/P1+efvppqVu3ruTl5d1TXLm5ufe0/tatW+XRRx8VOzu7e9qOnoxGkTffFLGzE/nlF72jMZ98yZd5Mk9cxVXaSBtZK2v1DqlMeXl58t577wkgXl5ecuTIkVLLpKWlybhx46R9+/YSERGhQ5T6urmcZmRkSI8ePWTZsmWVut+Klm91vtPHFtki/uIvzuIsH8qHkif3drxUcqlYpcxMkYceEvHxsezEskjnzp3FxsZGCgoK7nrdn3/+WZo1a2Z6npOTI+Hh4fcc01/+8pcKxVPcm2++WW1PtnfjL38RsbcX2bBB70ju3Tk5Jz2lpziIg7wqr8o1uaZ3SLd17NgxAeTJJ5+85TJLliyR119/vQqjqj7MUU4rqqLlW53v9GEQg/xL/iV1pa74iZ8clsMV3pa651KxOgUFMGoUXLwImzZpo+5Yulq1amFnZ4et7d0X2cOHD1OrWO/ftWrV4tFHH72neI4fP8533313T9sAcHBwuOdtVAf//CeMGQMjR8LRo3pHU3E/8AMP8ACZZHKYw8xjHi646B3WbTVo0AAAV9db96fp6OhIvXr1qiqkasNc5bSiKlq+1flOH/bY8xqvcZSj1Kc+3enOl3xZoQY/qlmDYnXmzoXNm2HbNuvuGP3s2bMEBwczd+5coqOj+fXXX/Hw8GDChAk4ODhw+fJltm/fTnh4OFlZWfzyyy8AjBo1CoCMjAxCQkI4deoUrVu3ZsKECdSpU8e0/dzcXJYuXcrJkyfp3r07/fv3x9nZmfDwcIKCgsjKymLJkiU4ODgQGBhYrm0aDAZWrlzJ4cOH6d27N0ajsQqPWOWaPx8uXNCGDj10CCwplzFg4FVeZT7zmcEMPuRDXUb1qCp3KjvFbdiZWkrAAAAgAElEQVSwgT179mBra8tzzz1HaGgof/nLXwgJCcFoNOLg4MCIwkHoly1bhsFgwNnZmWHDhpm2ERUVxYYNG0hLS6Nbt24MGjTI9Fp0dDTBwcHMmTOH0NBQIiIimD59Og4ODrdd707v4VbltKhce3p60r9//7s6HnqWb3W+qzqtaMV2tvN3/s5MZrKXvfzAD9Smdvk3YsYaVUXR3bZt2v1v336rdyTmFRAQIPb29qbnwcHB4unpKYCsWbNGnnnmGRkyZIgAMnv2bBERuXLliqxevVp69OghTZs2ldWrV8vq1atFRCQyMlKGDh0qGzdulCNHjoi/v7/4+PhIamqqiIicP39eevbsKQsWLJC4uDjp27evtG7dWnJycmTnzp0yevRoAWTdunWycePGcm0zLS1N+vbtK3PmzJGUlBRZuHChODo6VuvLRHcrIUHEy0tk5Ei9Iym/VEmV3tJb6kgdWSkr9Q7nrl26dEkACQoKuuUyK1askPfff19Eyld2RETS09Nl2LBh8q9//UsuXrwoK1askDp16oijo6OIaPcuBgQEiKurq2md+Ph4uf/++8XLy8s0b9q0adKzZ09JTk6WTZs2iY2NjXzyySciIrJw4ULx8vISQIKDg6VTp04CSHh4+G3XK897KKucnjp1SoYNGyaAfPrpp3d1PKqyfKvzXfWxWTZLfakvnaWzxEt8uddTyaViNbKzRdq0ERk2TO9IzO/mk62IyMyZMwUwnUBFRPr06SPt2rUrsdzIkSPF19e3xLwnnnhCVq68kUiEhoaWOFE/8cQTMmnSJNPr69atExsbG1mxYoWIiHzwwQcCiNFoLPc2X375ZRl20x/nySeftLiT7Z1s3ChiYyOyapXekdxZsiTLQ/KQNJfmclSO6h1OhdxtcilSvrIzefJkefnll0tsZ+LEiabkUkRk6tSpJZJLEZEXX3yxRHJZr149+eijj0zP/fz85JFHHjE9f+edd0zJpYjI6dOnxWg03nG98ryHsspp0fEqSi7Lu62qLN/qfFe9nJWz4iu+0k7ayUW5WK511GVxxWp88onW9dD27XpHUjVcXLR74QYPHmya5+/vz969e2+73uXLlwkLC6Njx46mZa9du0aXLl3Izs7m7NmzhIWFsWHDBtM6Q4YMISEhAQ8Pjwpt88qVKyxYsIB58+aVWO+BBx4g1Mo6iuzfX7v/8tVX4YknoPZdXEmqSumk05e+pJPODnbQilZ6h1Rl7lR2EhISmD9/fqnPpqenZ4nnZd0TePO89evX0759ewD27duHiJCTk2N63dnZGbhx+dbX17dc61W0/Be/bFvebVWH8q3Od/rxwYftbKcf/ehNb3ayEy9u352XSi4Vq5CcDF98Ae++C02b6h1N1Sjri83FxYX8/PzbrhcVFQXAzJkzadiwYanX165dC5T+ErrVibY82wwLC8NgMJTqX9DGSgfo/uwz8PHRxq7/y1/0jqa0AgoYxSiSSOIP/qAFLfQOqcKKGm9cv379lsvk5OSUaORxp7Jz4sQJjEajWfrDDAgIYOXKlaxYsYIBAwbQsmVLLl26ZHr9VmXgTutVtPyXJyG+eVvVoXyr852+vPBiK1vpQQ+e4Rm2svW2o3Kp1uKKVfjiC62GaOpUvSOp/hwdtYYahw4dKvVaZmamqSZl48aNpV5PSkqq0DaLOrq+fPlyxYK2MJ6e8Mor8I9/aEOPVjezmc02trGKVRadWIKWFNja2t7yswmQkpJialVeHmlpaQAkJibec3wzZ87khx9+YMGCBYwZMwYnJ6dKXa8yWHL5Vuc78/HAgzWs4RSnmMa02y6rkkvF4hkM8N//wssvg0v17jWlWvD19cXOzo7333+/RG1PUlISP//8M35+ftja2rJ27VrTyCagtWo9cOBAiW0VvX6nbd53330AZV4SspQWlHfr9dfh6lVYsULvSEo6yEE+4zO+5Eu60lXvcO6Zo6MjHTp04ODBgyUuGxe3ZcsWunYt/3tt06YNACtXrrztcq6uruTl5ZWYJyKmcnHw4EE+++wzXnnllRI1p3KHgfEqut6tFC/HFWHJ5Vud78zrPu7jv4VTGGG3XE4ll4rFW78eUlJg4kS9I6k8mZmZ5Ofnc+3aNdO8q1evApT4Qs3Pz8dgMJT4wktNTSU9Pd303N3dncmTJ7Nnzx569erF4sWLCQ4OZvTo0YwaNYomTZowbtw4jh07RmBgIFu3buWbb75h9uzZDBw4EIBGjRoB2pfgzp07cXZ2vu02/fz8GDhwIOvWrSM4OBjQLmMeOXIEESEuLu6Ol7csTePG8OSTUPh2q40pTCGAAF7iJb1DMZvvv/8eg8HAxx9/XOq12bNn07p1azp27Giad6ey8+CDD9KtWzcWLFjAl19+SUJCAmFhYYSFlfwy9fb2Ji8vj7CwMESEkJAQdu/eTXp6Ounp6abaxlWrVpGfn8/mzZs5evQoqampREVFce7cOQwGA6DVrhapXXij7u3WK0/5v7mc5ubmms4hWVlZ5T4edzpnmLt8q/Nd9fZM4TSFKeRzi/dROW2LFKXqvPiiSPfuekdROY4ePSpTp04VW1tbAWT06NGyadMmWbVqlbRs2VIAee211yQmJkaWLFkirVq1EkDefPNNOXXqlHzxxRfi5ORkWm779u0iog2RNm7cOAEEEFdX1xItH9PT02X48OGm11u2bCn79+83vR4TEyOenp7i7u4u33//fbm2mZCQID179hRA2rVrJ0899ZSMGTNG6tSpI1OnTpWLF8vXCtGS/PSTiKOjSEaG3pFoNstmQZADckDvUMxu8eLF4uXlJZ07d5Zp06ZJUFCQ9OnTR6ZPn15iCMHylJ3ExESJjIwUX19fAcTe3l7++c9/yttvv12itXhWVpb4+/sLIJ6enrJw4UKZNGmSuLu7y4wZMyQ5OVnGjh0rtra24unpKd9995189NFHYmtrKzNmzJBly5aZ9hEYGChHj95osX+79cr7Hm4up7GxsTJlyhQBxM/PT0JDQ8u9raoo3+p8ZzliJEbsxV4Wy+IyX7cRqWA9u6JUE61bw9ix8MEHekdieZKTk4mNjaV9+/ame4+Ki4+PJykpCT8/v1KdSxsMBvLz80utd6dtRkdHU1BQQNu2bTl//jwNGjS47egqluzKFfDygnXroFgjV90MYxgZZLCVrXqHUikMBgORkZFcuXIFX19fmjRpck/bKygo4OTJk3h7e1OvXj1mzZrFF198UaKmTEQ4ceIEPj4+1K5dm6ioKJo1a1bis5+UlISbm5upDKWmpuLu7n7H/Vd0veJuVU4rypLLtzrfmdfzPE8ssexmd6nXVHKpWLSMDHBzg9WrYehQvaNRlNK8vWHKFHj7bX3juM51GtCAL/iCP/NnfYOxUGUll4pSU61iFc/yLAkk0IhGJV5T91wqFi0yEkSgsDs4Ral2/Pzg9Gm9o4B97OMa1+hHP71DsVjZ2dkYDAbTfZKKUpM9zuPYYMNOdpZ6TfVzqVi0onvgGzW6/XKKopdGjbRW43qLJRYHHGhJS71DsUghISFs2LABGxsb/vrXvzJt2jRatLDsbpyqSlxcHBPL0eJy/PjxjB07tgoiUszBFVc88SSW2FKvqeRSsWhFDR5VF0RKdVW3LsTF6R0FXOUq9amPDZbbkbOeRo4cyciRI/UOwyI1a9aM9evX33E5e3uVkliahjQkmeRS89VfUrFoRV3A5eWBOi8p1VF2NpipLcU9qUtdMsjQOwylBrKxsdG1E3il8qSTTj3qlZqv7rlULFq9ws90aqq+cSjKraSl3fic6qkxjckhhxRS7rywoijKHRgwkEhimeOMq+RSsWg+PtpjZKS+cSjKrZw5A23b6h0FdKMb9tizne16h6IoihX4gz/IJZdHebTUayq5VCyalxc0bAhHj+odiaKUlp0NZ89qLcb15oYb3ejGKlbpHYqiKFZgNatpQxt88Cn1mkouFYv32GOwZYveUdxaVFSUaQiwmu7ChQu88847tGzZ0mzb2LZtG3v37jVPgGa2fTvk52uf0ergRV4khBDiqAYtjGoQdQ64oaadA6xVBhn8l/8yiUllvq6SS8XiDRoE27ZBZqbekZS2YsUKvvrqK9W9RqGYmBi2b9/OxYsXzbaNPn36EBERwSeffGKuMM1mzRp48EG4x4FizGY0o2lEIz7iI71DqTHUOaCkmnYOsFb/4B8IopJLxXoFBmqPS5boG8fNjh07xpdffsnXX3+NnZ2d3uFUC3369CEgIMDs25g4cSJnzpxh06ZN97Rtc8rJgZAQGDNG70hucMSRz/mcBSyw2iEgqxN1DiitJp0DrNUJTvAZn/ERH5XZUhxUcqlYgXr14Nln4auvwGjUOxpNQUEBzz77LKNHj9Y7lGrn5jF7zbWNDz/8kMmTJ5NV1PmpzoKDtQSzulVYPc/zPMmTvMALXOGK3uFYLXUOuLWacg6wRhlkMIpRdKELr/DKLZdTPQMqVuGtt+CBB2DZMnjuOb2jgdWrV3Pp0iWCgoJM80JCQjAajTg4ODBixAgAli1bhsFgwNnZmWHDhgFw9uxZgoODmTt3LtHR0fz66694eHgwYcKEEifU7OxsfvrpJ65cuUL79u3p27cvrq6u2NraYmNjQ3R0NMHBwcyZM4fQ0FAiIiKYPn06Dg4O5OXlsWPHDnbs2EGTJk0YOHAgPoVN780dp8FgYOXKlRw+fJjevXtjLOM/gIyMDEJCQjh16hStW7dmwoQJ1KlT56620axZM+rWrct7773H559/XuG/nTnk5cHHH8OLL4KHh66hlCmYYB7mYZ7hGbawBSdUH4Tmps4BNfscYI0KKCCIIFJIIZRQbG9XPymKYiWCgkRatxbJztY7EpE+ffpIx44dS8zLyMiQgIAAcXV1Nc2Lj4+X+++/X7y8vEREJDg4WDw9PQWQNWvWyDPPPCNDhgwRQGbPnm1aLykpSXx8fGThwoVy/fp1mTlzpgDSsmVL6dGjhyxcuFC8vLwEkODgYOnUqZMAEh4eLjk5OdK7d29ZsmSJpKamytdffy1169aV5cuXmz3OtLQ06du3r8yZM0dSUlJk4cKF4ujoKHZ2dqZlIiMjZejQobJx40Y5cuSI+Pv7i4+Pj6SmppZ7G0UmT54s3t7eFf2zmc1HH4nUri1y8aLekdxahESIm7jJQBko2VINCo2VUecATU09B1gbgxhkpIyU2lJb9sieOy6vkkvFaly6JOLqKjJrlr5xGI1GqVWrlgwePLjUa1OnTi1xwhYRefHFF00nbBExfUmsXr3aNK9Pnz7Srl070/PXX39dXF1dxWAwiIhIXFycAPLXv/7VtMw777xj+mIRETl9+rQYjUYJCgqSiRMnlohhxIgR4uzsLHFxcWaN8+WXX5Zhw4aV2M6TTz5Z4kvhiSeekJUrV5qeh4aGlviCKs82irz//vsCSEpKSqnXqkpUlIizs8gnn+gWQrkdkANSX+pLX+krGZKhdzhWQ50DavY5wNrkSI48K8+Ki7jINtlWrnXUPZeK1WjSBD75BP7xD/j9d/3iuHz5Mrm5uTQpo4mwrW3pInfzPJfCgdIHDx5smufv71+idWVUVJTp0hdol4PatGnDrl27TMs4F445OGrUKAB8fX3Jyclh6dKldOrUqcQ+p0yZQk5ODj/++KPZ4rxy5QoLFiygf//+JdZ74IEHTL9fvnyZsLAwdu/ezaxZs5g1axbr16+nS5cuZGdnl2sbxXkUXoM+cuRIma9XtuvXYfRo8PWFN97QJYS70pnObGELJzlJd7oTQ4zeIVkFdQ6ouecAaxNPPL3pzRa2EEooveldrvXUPZeKVZk8GTZu1L7gDxwAT8+qjyExMREAV1fXCq1f1kndxcWF/Px80/MePXqwfv169u3bR/fu3cnLyyM+Pp4nn3zStEzRl05xu3fvxmAwYH/TQOxtC4eQibyLoY7uFOfRo0cxGAx4eZUcGqx4XFFRUQDMnDmThg0bltpeWFjYHbdRXNE2zpw5w+OPP17u92Iub70FERHaZ88MbRaqREc6so99PM3TdKMbC1nIEIboHZZFU+eAmnsOsCa/8ztBBFGHOuxlL+1oV+51Vc2lYlVsbOCHH8DZGZ56Shshpaq1adMGGxsbUlIqbwzn6dOnM2LECGbOnMnmzZuZMWMGjz76KHPnzr3tegUFBYD2BVNc0Qm5XbvynzzuJLOw49HLly/fchlHR0cADh06VOb65dlGcUWtRD11+K/iP/+BefNg/nyt5tKSNKc5u9jFYAYzlKG8wivkkKN3WBZLnQM0Ne0cYC0MGPgrf+VxHqczndnDnrtKLEEll4oVql8f1q+H6GgYOVK7VFmV6tati4+PD1eulO7mxdXVlby8vBLzRMR0wi8vGxsbmjRpwpdffonRaOSVV14hLCyMunXr3na9Tp064eTkRHh4eIn5SUlJAPTs2dNscd53330AhIaGlnqtqKWnr68vdnZ2vP/++1wv9odKSkri559/Ltc2iouPjwegVatW5Y7THFauhKlTYc4cKLwCaXFqU5tFLGJx4dSRjmyhGg99VY2pc4CmJp0DrMUe9tCNbsxjHt/wDatZjRtud70dlVwqVqltWy3B/P13LcE0GKp2/506dSrzi8Xb25u8vDzCwsIQEUJCQti9ezfp6emkp6dTUFDA1atXAcjJuVFzlJ+fj8FgMJ3s//GPf7Bjxw7i4uJwcHAgPT2diIiIEpfNDIVvunjtiYeHB9OmTePcuXNs27bNNH/VqlUEBgbSq1cvs8Xp5+fHwIEDWbdunWnou+vXr3PkyBFEhLi4OOrWrcvkyZPZs2cPvXr1YvHixQQHBzN69GhGjRpVrm0Uf8/x8fG4ubmZvpCqwurV2mfspZdg9uwq222leZ7nOcYx2tOefvRjDGNIIEHvsCyOOgfUnHOANbjKVSYzmQACqE99DnOYl3ip4hs0f7siRak+du0SqVtXpH9/kczMqtvv4sWLxcnJSa5du1ZiflZWlvj7+wsgnp6esnDhQpk0aZK4u7vLjBkz5L///a+0bNlSAHnttdckJiZGlixZIq1atRJA3nzzTUlMTJS1a9dKrVq1BCjx06JFC9m0aZMsW7ZMfH19BZDAwEA5evSoKYaCggJ54403pFGjRvLWW2/J+PHj5bnnnpOcnByzx5mQkCA9e/YUQNq1aydPPfWUjBkzRurUqSNTp06VixcvSlZWlowbN870HlxdXUu0HC3PNop0795d3njjjUr8y5b0448iDg4iU6aIGI1Vttsqs1pWSwtpIXWkjrwn70mmVGEhsnDqHFAzzgGWLkdy5FP5VNzFXbzES/4n/zPLdlVyqVi9AwdEPD1FOncWKexlo0oMGjRI1qxZU2q+0WiUY8eOSVZWlohofbxl32XnnEuXLpVffvlFkpOT5cyZM3Lo0CHZtm2bfP3119K7d+9ybSM7O1sOHTpU4gvF3HEWOXv2rJw5c0aMRqPExMRIenp6qWWSkpLk4MGDt9zHnbYREREhTk5OEh0dXaEY74bRKPLBByI2NiLvvGOdiWWRbMmWv8vfxU3cxEM85F/yL8mSLL3DsgjqHHCDtZ0DLF2e5Ml8mS/Npbm4iIu8K++atTsylVwqNUJ0tIifn0jDhiIbNlTNPmNjY+Xxxx+XgoICs243KipKPDw8TP3bFZeYmChjx4416/4sxfTp0+W///1vpe8nKUlk0CARR0eR776r9N1VG8mSLG/IG1JbaouneMqn8qnqG/MO1DmgalXVOcCSZUu2fCVfSXNpLo7iKC/JSxIv8Wbfj92cOXPmVPyiuqJYBnd3eOEFOH8eZsyAq1ehXz+ws6u8fdarVw9XV1dWrVplukneHI4ePcq3335LVFQUHh4e2NrakpGRwf79+/nb3/7G3LlzqV+/vtn2ZwmWLFnC1atXmTFjRqXuZ/9+6N8fEhO1e3oLR8GrEWpTmwEM4M/8mRxy+JzP+YqvSCGFdrSr0E3/1k6dA6pOVZ0DLFUCCXzGZ4xhDOtZTxBBhBDCaEZTl9s3AqsIGxERs29VUaqxH37QWvZ26QI//QTe3pW7v3PnznHo0CGeffZZs21z06ZNrFu3js2bN3Pu3Dnatm3LgAEDmD17doX71rNUO3fuJDs7mwEDBlTaPgoK4J//hHffhcGDIThY+4elJrvKVf7Df/iGb0gggeEMZwpT6E3v2485XAOpc0DlqopzgKXazW6+4ztCCKEe9XiJl5jKVDyp3K6aVHKp1EjHj2stfGNj4b33YPp0y+n0+mYicssOhZV7t3cvTJkCJ0/Cxx9rI++ow32DAQPLWc485rGHPXjjzVjGMo5xtKWt3uHVCOocoBQXSyyLWMRP/EQkkXSkI9OYRhBB1KJWlcSgkkulxjIY4NtvtdqoJk3gm2+0S+WKApCWBu+/r30uevTQPit+fnpHVb2d5jRLWEIwwVzgAp3pzFjGMoYxNKCB3uEpitXKJZe1rGURiwglFFdcCSSQsYylBz2qPB6VXCo1XkyMdpn8t99g/Hj46CNo2lTvqBS9FBTAwoUwaxbY2sLnn0NQkN5RWZYCCtjEJhaxiFWswgYbhjGM53meJ3gCZ5z1DlFRLN51rrONbSxhCctZTh55DGYw4xnPYAbjiKNusankUlEKLV+uXfK8cgUmTYK334bGjfWOSqkqBQXwyy/w4YfaPxyTJ2v/aNSrp3dkli2NNH7lVxaxiN3sxhlnnuAJnuIphjKURjTSO0RFsRippLKBDaxhDb/xGxlk0IUujGUsQQTRkNLjs+tBJZeKUsz161pjjQ8/1JLMCRO0S6NNmugdmVJZjEbtH4v33oPISHj2WS2pNOMQy0qhJJIIJZR1rCOUULLJphOdeJInGcpQOtNZ7xAVpdq5wAU2spG1rGUTmyiggEd4hKEMZTjD73rc76qgkktFKUNeHsyfD598ot1796c/wcsvgxpRzHpkZ8PixfDll3DmjDYm+OzZKqmsKllkmb4w17GOZJLxxZeBDKQPfXiMx3CnhjfJV2qkTDLZyU62s52NbOQYx3DDjYEM5GmeZhCDqEf1vqSikktFuY3cXC3JnDcPzp2Dxx/XksynngJ7e72jUyrizBn47juthjonR+s1YNYs9Y+DngooYDe7WctaNrOZoxwF4EEepDe9Tclmdf9CVZSKuMY1drGL7YXTQQ5SQAF++NGXvgxlKL3ohQOW06WJSi4VpRyMRq3Bz7ffQmiodpl80iStRlNdMq/+rl+Hdevg3/+GLVugZUt46SXt79ewetyipBSTSiq/8zvbCqcTnMAGGzrRid6F06M8qmo2FYuUQQZ72MMOdrCd7exjH/nk05729KEPvelNL3rhgYfeoVaYSi4V5S5dugQLFmiJZkoKdO8OgYHw/PPgWbn90ip3wWiE3bth6VJYsgSSk7Wa50mTYPhwVfNsSTLJZC972Vw4HeYwRow0pjGdC6ce9KA73XHBRe9wFcXEgIFIIjnIQcIJZxe7OM1pjBhpTWsCCKAHPRjEIJrTXO9wzUYll4pSQbm5Wi1mSAisXavVjvXtqyWZw4aBmxoNr8qJQHi49jdZulQbpvGhh7S/yciR0KKF3hEq5pBEEvvYx/5iUxJJ2GOPH350LZy60Q1//C3qcqJiuQooIIII02dyH/s4znEMGHDH3fS5LPpsNsZ6uyNRyaWimEFWlpZghoRoCaeI1vH2gAHaWNQPPqhGdaksyckQFgabNsHGjXD5MnTocCOhbKsGiakR4onnYLFpN7u5ylUccKAtbelAB/zwMz3ex33YYad32IqFiieeCCI4yUnT4xGOkEUWDjjwAA8QQICpZr097WvUsKgquVQUM0tP1+7vCw3Vkp4rV8DLS0syBwyAJ56ARqprvwrLz4c//tASyU2b4OBBsLPTbk8YMEBrbOXvr3eUit4KKOA0pznIQU5ykhOcIIIILnABQXDG2ZRsFp+88cYG9Z+gooklllOcMn1+jnOcU5ziGtcAaEYz/PDjfu7HDz8605kOdMCemn3fjUouFaWSnTwJX3yhJUPJyVo3R40bazWbAQHQuTM8/LDljm1e2dLTYf9+2LVLSyR37dK6h2rVSkvU+/XTHtVtCEp55JHHWc5ykIMlap7OcQ5BcMSRZjSjdRmTL77UoY7eb0ExIwMG4ogjpowpkkgyyQTAHfcSNd8d6MADPGDRjW4qk0ouFaUSGY1ah+xz52r9KM6bp9W6Ff3s3w/XrkHdutCtm1b71qmTdlnXx6fmNTpJTobjx+HECdi7VztGMTHaLQXt28Mjj2jHqFcvdblbMa900okggkgiTclFNNHEEEMiiQDYYEMTmtCa1vjgQ2ta4403TYpNbqj/cqqTTDK5yEUSSOASl4gltsTf9iIXMWIEoCENS/xtW9OaNrTBH3/qU1/nd2JZVHKpKJUkI0Mbq3zdOm3El7feKr1MQYGWSO3eDXv2aD9nz2pJqZOT1vdi+/Zw//3aY4cO4O2tvWbJEhK0/iYjIrT3f+qU9piUpL3u7q4l2488cuNH1Uwqeskiy5SMFE9MYoghllhyyTUt64wzTWlKYxrTlKZ44UUzmpkePfHEAw+VrNyjdNJJLJyKkseLXCSRROKIM83PIsu0jhNOJWqliyeRPvjgiquO78i6qORSUSrB4cMwYoR2CXzpUq22rbyys7Vk6+RJLfk6eVL7OX9eayhkY6Pdw+ntDc2bay2gW7S48bxRI6hfH1x06JElPx9SU7Uumi5dgthYuHBBe4yNhbg47TG38LvYzQ38/LSkueixQwfVd6hiWa5ylctc5hKXuMzlWyY7BgymdWywoQENqH/TdLt5tahFbWrjiqvFN0YyYiSddHLIIZdcrhabUkgp8byseQUUmLZljz2eeJaZzBd/VOPYVx2VXCqKmS1aBFOmQNeuWv+KXl7m2W5WFpw+rSVrcXFaslk8YUtMLLm8k5OWZBb/cXfXLsHXrq0t4+wMtWppv7u4gKNjyRWtvgQAACAASURBVG2kpWkJrYj2O2i1rRkZ2r2QV69qieTVq9pPRkbJ9Z2dtQ7Lb06CW7TQLms3bWqeY6Mo1Z0gJJLIFa6QSOIdk6miqXhCWpw99tSlLi644IQTbrhRi1o444wbbjjhhAsu2GBT6lK9E07UpnaJeXWpe8tGKAUUkEHJwl2UFBaXTjpGjGSTTR55pJJKHnlkk00GGeSSy7XC6Vbvyw672ybaxV9rRCO88MITzxrVEtsSqORSUcwkLw9mzoSvv4Zp0+Dzz6v2nsncXC3JLJ7spabe+L3oeXY2ZGbeWCcnR/s9K0vrq7O4evXA1vbGZfo6dbQE1MVFq3V0d4cGDbTHm5PYJk1Uq3hFuVcZZJgSzTzyyCKLDDLII49MMskii1xyS9QCFk/qDBhMLZuLFCV/xaWRhqClA0W1gsVrR91wK9GK3gGHUo2bXHDBEccyk1xXXHHCibrUpQ51cMKJetSjNrVxwsmUNKohPq2DSi4VxQzi4rRReiIi4Mcf4dln9Y7IvP75T60xUlyc3pEoilLZXuAFEkhgAxv0DkWxUKoeWVHu0bZt0KWLdpl4717rSywB2rTR7qHMyrrzsoqiKErNppJLRakgEfj0U62fxX794MABrUW3NWrbVnu/MTH/z96dx1VV548ff7FcEBfMFXMp09QkrExNDU0bl1yyURNLcS2zxRyrKa1vmVnOVGP9arL5VmOjWJka5paKSmP5NcwW1CxX3BVcQBGUHe7798dHrlzZ4XIvcN9PHj7gnnPuOZ97/HzOed/PdlydEqWUUpWdBpdKlUFSEgwfDq+8An//Oyxe7JrR2c7SurXpexkT4+qUKKWUquzcbIpmpcov7zRD//d/pZtmqKqqUcOM7D50yNUpUUopVdlpzaVSpfDZZ+axjS1amGZwdwgsc7Vpo8GlUkqp4mlwqVQJZGTAtGkwYQJMmgTffuu4+Suriptv1mZxpZRSxdNmcaWKkXeaofDw6jkavCTatIH1OjOJUkqpYmjNpVJFcIdphkpKpyNSSilVEhpcKlUAd5pmqKR0OiKllFIlocGlUtdwt2mGSkqnI1JKKVUS2udSqTzccZqhktLpiJRSSpWE1lwqdYU7TzNUUjodkVJKqeJocKncnk4zVHI6HZFSSqniaLO4cms6zVDp6HRESimliqM1l8ptbd6s0wyVlk5HpJRSqjgaXCq3kzvNUL9+5p9OM1RyOh2RUkqp4mhwqdzKtdMMffGFTjNUGjodkVJKqeJon0vlNnSaofLT6YiUUkoVR2sulVvQaYYcR6cjUkopVRQNLlW1ptMMOZ5OR6SUUqoo2iyuqi2dZqhi6HRESimliqI1l6payp1mKDlZpxlyNJ2OSCmlVFE0uFTVyrXTDP3yi04z5Gg6HZFSSqmiaHCpqg2dZsg5dDoipZRSRdE+l6pa0GmGnEenI1JKKVUUrblUVZ5OM+R8Oh2RUkqpwmhwqaosnWbIdXQ6IqWUUoXR4FJVSSdPwj33QFiYmWbon/8Ebwd38ti7dy/Tpk2jS5cuRW534cIF2rVrx8KFCx2bgEqsTRvHBpd6rpWqXrRMuzftc6mqnM2bYdQoaNAAtm+vuNHgR48eZcOGDWRmZha5nbe3Nw0aNKB27doOPX5GRga+vr4O3aej3HwzxMWZ6YgcMWhKz7VS1YuWafemNZeqynD2NEODBw/mzjvvLHY7f39/tm3bRkhIiEOP//LLL2O1Wh26T0dx9HREeq6Vql60TLs3DS5VlXDhAgwe7PxphiwWS8UfpAC///47H3/8sUuOXRIVMR2Rnmulqhct0+5Lm8VVpVfeaYZ++OEHIiIiaNGiBZ6enkyePJlly5ZhtVqxWCyMGDECgOXLl5OVlYWfnx9Dhw4FwMPDAw8PDwA2bNjAli1b6NixIyNHjrTtPyMjg+XLl9OgQQMGDBhgW56cnMyyZcvYt28frVq1YsKECXZNP+np6YSHh7Nnzx66d+9O//798fPzIyoqitGjR5OSksLSpUuxWCwO/1ZfXoVNR6TnWqnqRcu0KhNRqhJbtEikZk2RXr1ETp8u/funT58uixcvlpSUFFmyZInUrl1bRESSk5MlODhY/P39bdvGxcVJhw4dpEmTJrZl48aNk5YtW8r//M//SLdu3aRZs2YCyJgxY0RE5ODBgzJixAgBZM6cObb3HTx4UIYMGSIbN26UXbt2SVBQkLRu3VoSExNFROTYsWPSs2dPmT9/vpw8eVL69OkjrVq1krS0NNm6dauEhoYKIGvXrpWNGzeW4cxVvD/9SeSxx66+1nOtVPUwUSbKQBmoZVqVmQaXqlJKTxeZPFnEw0PkL38Rycoq/T4yMzOlQYMGcuDAAduyadOm2f5++umn7S6OIiKTJk3Kd3GsU6eO/Pzzz1fSlS59+/YVQDZt2iQiIgkJCfkujv369ZOVK1faXkdERAggM2fOtK2fPHmybf3atWvFw8NDVqxYISIis2fPFkCsVmvpP7iTPP64SO/e5m8910pVHxNlogzIHKBlWpWZNourSufkSdMMvn+/mWbowQfLth+LxUKdOnXo27cvn3zyCQMHDuTll1+2rff0zN/luKBlDRs2tE2n4evry+TJk/n222/ZtGkT/fr1yzfK8fTp00RGRnLHHXfw008/AXD58mU6d+5Mamoqhw4dIjIykvXr19veM3jwYM6cOUPjxo3L9mFd4OabYe1a87eea6WqFw+Lh5ZpVWYaXKpKJSICxoyBgADHTDP04YcfMnbsWAYNGkT37t0JCwujUaNG5dpn//798fb2Ji4uDsh/QY25Mspl+vTpNGzYMN/7v/nmG4B8F9WqdmG8djoiPddKVS9aplVZ6WhxVSnkTjN0//0wcKDjphkaPHgwhw4d4plnniE6OprOnTuzb9++cu2zbt26+Pn50aZNmwLX+/j4ALBjx4586y5duoSfnx8AGzduzLc+Pj6+XGlzpmunI9JzrVT1omValZUGl8rlKmqaoZSUFObPn0/9+vV57733+P7777l8+TJLliwBzPxqGRkZdu8REXJycorc75kzZ7h06RL33HNPgevbtWuHl5cXs2bNsptAOD4+nsWLFxMYGIinpyfffPON3bEOHz7Mr7/+arev4tLiSnmnI9JzrVT1kpOSo2ValZkGl8qldu6ELl1g924zzdCMGY7bt9VqZdasWaSnpwPQvXt32rRpY2vWufHGG8nIyCAyMhIRYdmyZWzbto2kpCSSkpJsF6bU1FRSU1Nt+507dy4TJkzgT3/6U4HHrVevHk888QTbt2+nV69efPnll4SFhREaGsqoUaNo2rQp48aNY/fu3YSEhLB582b+9a9/MXPmTNtUHLlpjI6OZuvWrbbPUJnknY5Iz7VS1YtYRcu0KjtXjiZS7q280wwVJzk5Wfz8/KRDhw7ywQcfyGuvvSYTJ06UzMxMERFJSUmRoKAgASQgIEAWLVokkydPlnr16snzzz8vCQkJEhUVJd26dZN27drJ7NmzZeLEifLcc89Jamqq7TiZmZkCyN/+9jfbspSUFBk3bpwAAoi/v7/d6MekpCQZNmyYbX3Lli3ll19+sa0/cuSIBAQESL169eTTTz91/MlxkNzpiPRcK1V9TJSJ0i+5n5ZpVWYaXCqnc8Q0QyVhtVolJSVFkpOTJTo6Wi5dulTgNrt375aUlBQRMfOr5b3w5Tp9+rT88ssvcvny5Xzrci+O//73v/Oti4+Pl+jo6AL3KSISGxsru3btsl2wr91vYe+rLHKnI9JzrVT1MVEmykDrQC3Tqsw8REScWlWq3FreaYYWLCj7NEOVSVpaGjVr1mTz5s3ce++9rk6OU73zDrz/Ppw65ZzjufO5VspZHuERznCG9awvfuNy0jJdPWmfS+U0ERFwxx1w6ZKZZqgqB5aHDx9m6tSpxMXFcfLkSW677TZ69+7t6mQ5Xd7piCqKnmulqhct09WfBpeqwlXUNEOudPnyZTZs2ECnTp348MMPWbt2re0Zuu7k2umIKoKea6WqFy3T1Z82i6sKdeGCmRQ9MhLmzHHsaHDleunpZtqo8HAYPtzVqVFKOYIzm8VV9aRP6FEVZudO078yM9NMM9S9u6tTpBwt73RESimlFGizuKogn30GPXpAixbw668aWFZnbdpocKmUUuoqDS6VQ2VkwOOPw4QJMGkSfPuteU64qr7atDFP6VFKKaVAm8WVA+WdZig8vGqPBlcld/PNsHatq1OhlFKqstCaS+UQ1WmaIVU6zpiOSCmlVNWhwaUql+o4zZAqHWdMR6SUUqrq0OBSldmFCzBoELzyCvz97/DFF2ZaGuVeWrcGT0/td6mUUsrQPpeqTHSaIZVLpyNSSimVlwaXqtQ++wyefBK6dIFly3Q0uIJWreCnn+Drr02QGRNjBnZ17Qrvvuvq1CmlCnPkyk9eccSRSCLf8q3d8mY0oz3a70kVT4NLVWIZGfCXv8D8+TB1qgkavDUHuZ3YWNMFIjeAjImBc+fMupUrwccHcnIgO1sHdilV2R3kIAMZWOC6fvSze72ABRpcqhLRxz+qEsk7zdCCBRo0uLO0NLjpJhNQFnf1+P576NXLKclSSpVBNtk0ohEXuVjkdhYsnOMc13Gdk1KmqjId0KMAEyS8/37BwYJOM6Ty8vODV18FD4+it/PwMPlGKVV5eePNaEZjwVLkNoMZrIGlKjENLhVgaiOffda+f5xOM6QK89hjZhCPZxFXkBtvhLp1nZcmpVTZjGIUWWQVut6KlTGMcWKKVFWnzeKK06ehXTtTM+npCZs3Q4cOEBpqHt84Zw7MmOHqVKrKZuFCePTRgmu7vbwgJASWLHF+upRSpSMIzWlOHHEFrq9JTRJIwA8/J6dMVVVac6l46ilITzd/e3jAn/9smjP37IEfftDAUhVs3Lirc1xey8sLOnVyfpqUUqXngQdjGVtg07gFCyMYoYGlKhUNLt3c11/DqlWQdaVFJCfHPMbv0iX48UczlYxSBfHyMrXaBdVcZmZqcKlUVVJY03gWWYxmtAtSpKoybRZ3Y0lJ0LYtJCSA1Wq/zsvL1Gh+8IFr0qaqBhHThWL/fvPFJJeHB5w/D/XquS5tSqnSaUc7DnLQbtl1XEc88XjrzIWqFLTm0o098wwkJuYPLMEECvPmmQnTlSqMhwe8+aZ9YAnQvLkGlkpVNdc2jVuwMIYxGliqUtPg0k19/z0sWnS1ObwgHh7w+OOm76VShRkyBDp3vjqhvqendqdQqioazWiyyba9ziKLUYxyYYpUVaXBpRtKTYXx44ueRgZMk2d6OgwbBsnJzkmbqprefNM8kQdMkNm5s2vTo5QqvVa0oiMd8bwSGlzP9XSnu4tTpaoiDS7d0KxZEBeXvykzl5eXqbX08TEjx994AyyFz6+rFH37Qs+eJu9kZkLHjq5OkVKqLMYxDk88sWBhPOPxoJinJShVAB3Q42Z++QW6dSt4AI+I+d23Lzz8MAwdCv7+rkmnqnq2bYPgYPN3fDw0bOja9CilSu8MZ2hGM6xY2c1uOtDB1UlSVZAGl24kKwtuvx0OHjS1lrkBpacn9O8Po0eb/nMaUKqyGjAA/vgDTp1ydUqUUmXVm96c5jQHOODqpKgqqkzB5blzps+eqloOH4aYGPO3hwc0aABNm0LjxlcHY1QFDz4IkyY551grVsD8+c45VnVw6ZLJZ/pMccd4/33z9CxVes/yLPvZ7+pkVEmnOEUmmbSilauTUiU1pjGLWOTqZLhUmUKKtDTYsME8c1qbvqqGpCQ4dswEk61awQ03mD6VVc3atRAY6LzjHTkCW7eaRxmq4jVpYr601K/v6pRUbSkpEB4OFy+6OiVV1za2kUIKXeji6qRUOfWpTyaZ1Ka2q5NS5ey58uPuylVf9corOuVIVbFrF3z6adW/6bsiv9Wvb56jrZSzHD9ugktVPvdxH+/yrquTodzIO7zDB+jTR6pQY6gqD22mVEoppZQz6FRESimllFLKYTS4VEoppZRSDqPBpVJKKaWUchgNLpVSSimllMNocKmUUkoppRxGg0ullFJKKeUwGlwqpZRSSimH0eBSKaWUUko5jAaXSimllFLKYTS4VEoppZRSDqPBpVJKKaWUchgNLpVSSimllMNocKmUUkoppRxGg0ullFJKKeUwGlwqpZRSSimH8a7oA8THx7Nx40bb6379+hEQEGC3TUZGBitWrCAnJwcAT09PBgwYQP369Ss6eSWWnZ3N6tWr+eijjxgyZAjTpk3Lt01sbCzh4eHExMTQoEEDevfuTffu3Tlx4gQ5OTkEBga6IOWOlZiYSHBwMDNmzGD8+PGuTk6lonld87qqmrTsatlVjlXhNZeNGjWif//+bN26lbFjxzJ06FAyMjLstvH19WXgwIFERkby0Ucfcc8995S4wF67r4py6tQp4uLi+O9//0tWVla+9W+++SbdunUjIyODyZMnM23aNLKyshg4cCA9e/bk4MGDTklnRfP29qZBgwbUrl3b1UmpdDSva15XVZOWXS27ysGkDI4dEwGR7dtL97527doJIBMmTChw/RdffCGvvPJKqfb517/+VXJyckqXkDJKSEgQQObOnWu3/L333hOLxSI//PBDvvekpaVJ165dZcGCBU5JY3V3110izz3nvOPNnSvSokXp36d5XZVHWa+x6qq75C55Tkp/sdCyq8pjrsyVFlKGm0Y149Q+l7Vq1aJ79+6EhYXx/vvv51vv4+NTqm8av//+Ox9//LEjk1gkb+/8vQiWLFnCs88+yxtvvEFwcHC+9TVq1GDevHlcuHDBGUlUlYTmdaWqJi27SpVfhfe5vNaKFSvo0qULzz//PEFBQfTt27fI7WNiYli/fj0XL17krrvuYuDAgQBERUUxevRoUlJSWLp0KRaLBavVitVqxWKxMGLECACWL19OVlYWfn5+DB06FIDDhw8TFhbGa6+9RkREBHv37uXZZ5/FYrEUejwADw+PfOmbM2cOAIMGDSr0M3Tp0gURsb3OyMhgy5YtbNmyhaZNmzJgwABat25tW3/o0CHCwsJ4/fXXOXz4MF999RWNGzdmwoQJWCwW1q1bR3Jysi1Nw4YNw9fXlx07dnDgwAEABg8ejL+/P8nJySxbtox9+/bRqlUrJkyYYLswFnUefvjhByIiImjRogWenp5MnjwZgPT0dMLDwwkICKB///4O+0zVkeZ1zevukterGy27Wna17JZTWao7y9pkc+edd4qIyK+//ip+fn5Sv359OXTokG39V199JW+99Zbt9dSpU6Vnz56SkJAgmzZtEg8PD9v6rVu3SmhoqACydu1a2bhxoyQnJ0twcLD4+/vb9hEXFycdOnSQJk2aiIjIokWLpEmTJgJIWFiYdOzYUQCJiooq8ngiIklJSXbNDTExMQKIt7e3ZGRklOgcpKWlSe/evWXp0qWSmJgo8+bNkzp16sjXX38tIiJhYWESEBAggKxZs0aGDx8ugwcPFkBmzpwpIiKnT5+WTp06CWDXxGG1WmXQoEGyZMkSERE5ePCgDBkyRDZu3Ci7du2SoKAgad26tSQmJhZ5HqZPny6LFy+WlJQUWbJkidSuXVtERPbt2ydDhw4VQN5++22HfqaSqirN4prXNa+XJ69rs3j5lbVZXMuult3ylF1tFjdcElyKiHz55ZcCyK233irJyckikr/Q1q1bV+bMmWN7HRgYKN26dbO9nj17tgBitVpty55++mm7QisiMmnSJFuhFRF5+eWXbZlVRGT//v1itVqLPd61hTYyMlIAueWWW0p8DkaPHi0TJ060WzZixAjx8/OTkydPiojI9OnTBZDVq1fbtrn33nulbdu2tte5x168eLFtWUZGhgwfPtz2ul+/frJy5Urb64iICLuCUtB5yMjIkAYNGsiBAwds75s2bZrt79jY2HyF1lGfqSSqWnAponk9L83rJaPBZfmVN7gU0bKbl5bdktHg0nDZPJejRo3ixRdfZM+ePYwZM8auOj7XunXrePLJJwH4+eefERHS0tKK3K+nZ/6PdO0yPz8/WxoA2rVrh4eHR6mPV1DflqKkpqYSHh5Ox44d7ZY/+eSTpKWlsXDhQsD0+QH7JoygoCBOnTple923b1/at29v15dnxYoVhISEAHD69GkiIyPZtm0bL730Ei+99BLr1q2jc+fOpKamFnoefHx8qFOnDn379iUiIgKAl19+2XaMa/saOfIzVVea16/SvK6qEi27V2nZVaXh9D6Xef3tb3/jjz/+YM2aNbz66qvcdtttduuDg4NZuXIlK1as4L777qNly5bExsaW+7gF9Ukpy/HatGkDmP42aWlptkJQmG3btpGVlZWvsOfuJ3caiIIuPLVq1SI7O9tu2dNPP82UKVPYvXs3t912GytXruTzzz+3pQlg+vTpNGzYsMD0FHYePvzwQ8aOHcugQYNsHdsbNWpUYNoc/ZmqK83r9vvRvK6qCi279vvRsqtKwqVP6PH09GTx4sW0b9+eOXPmEB4ebrd++vTpLFiwgPnz5zNmzBh8fX0rND2lPV6zZs249dZbycnJ4Y8//ihyWxGxTb67bds2u3W5hapt27alSu+4cePw9/fnww8/ZN++fbRp0wYfHx8A2+8dO3bke9+lS5eK3O/gwYM5dOgQzzzzDNHR0XTu3Jl9+/YVuK2jP1N1pXnd0Lyuqhotu4aWXVUaLn/8o7+/P2vWrKFevXp2hTY6Opq5c+cyZcoUatSoYVteULNEbsbJ3d+1E9bmLTCFKc3x8po9ezZgCnxmZmaB28THx7Nw4UI6duyIr68vUVFR+dYD9OzZs8hjXat27dqMHz+exYsXM3fuXNtIOTBNB15eXsyaNcsuXfHx8SxevLjQfaakpDB//nzq16/Pe++9x/fff8/ly5dZsmRJgds7+jNVZ5rXNa+rqknLrpZdVTpODS5jY2Nt/Sjyuvnmm/nqq6/w8vKyLatZsyYAq1atIjs7m2+//ZbffvuNxMREYmJiOHr0qK0KPDo6mq1bt5Kens6NN95IRkYGkZGRiAjLli1j27ZtJCUlkZSURE5Oju3JBefPny/V8S5fvgyYjJ3rwQcfZM6cOWzZsoXHHnvMbh3AiRMneOuttxg7diyNGzdm6tSpHD16lO+++862zapVqwgJCaFXr14AtrnG8vajyc7OJisrK98FacqUKaSlpXH+/HluuOEG2/J69erxxBNPsH37dnr16sWXX35JWFgYoaGhtr4rBZ0Hq9XKrFmzSE9PB6B79+60adPGdq6vPQcV8ZmqA83rmtfdJa9XN1p2texq2XWAsowCKu1Ixh07dsikSZMEkJCQEImMjCxwu/fff99uFN7YsWPF09NTAgIC5OOPP5Y5c+aIp6enPP/88yIicuTIEQkICJB69erJp59+KiIiKSkpEhQUJIAEBATIokWLZPLkyVKvXj15/vnn5ZNPPrE9gSEkJER+++23Eh0vLi5OnnzySQEkMDBQVq1aZZf25cuXS1BQkPj5+UmvXr1kypQp8thjj8lrr71mN/1DTk6OPPfcc9KoUSOZMWOGjB8/XkaOHClpaWkiIrJq1Spp2bKlADJt2jQ5cuSILF26VG666SYB5IUXXpCzZ8/aHbt///6yYcOGfOczJSVFxo0bJ4AA4u/vbxuVt3z58gLPQ3Jysvj5+UmHDh3kgw8+kNdee00mTpwomZmZcuLECbtzEBERUWGfqTCVfbS45nXN647I6zpavPxKO1pcy66WXUeUXR0tbjh1KqKSiI+Pt3t97tw5yczMtL2+cOGC3frMzExJTU21W2a1WmX37t2SkpIiImYerWu3KUxxxyvO5cuX5ccff8z3Oa6VmpoqO3bssGXs8jhx4oTdNBfXio+Pl+jo6BKdA6vVKikpKZKcnCzR0dFy6dKlEqfDkZ+pMJU9uCwNzeul5y55XYPL8ivrVEQloWW39Nyl7GpwaXiIFNNZowDHj0PLlrB9O3TtWtp3K1V2XbtCjx7w7rvOOd4778AHH8CJE845nlKg11hH6EpXetCDd3HSxUIp4B3e4QM+4ATufdNw+YAepZRSSilVfWhwqZRSSimlHEaDS6WUUkop5TAaXCqllFJKKYfR4FIppZRSSjmMBpdKKaWUUsphNLhUSimllFIOo8GlUkoppZRyGA0ulVJKKaWUw2hwqZRSSimlHEaDS6WUUkop5TAaXCqllFJKKYfR4FIppZRSSjmMBpdKKaWUUsphvMvz5mefhbp1HZUU93D6NFit0KyZq1NSNR04AD16OPeY8fEwcKBzj1ldHDsGdepAgwauTknVkp7u6hRUDytYwV72ujoZVc4ZzpBDDs3QG1VpHeWoq5NQKZQpuKxdGyZMcHBK3MT+/eZ3kyauTUdVNWwY3HWX844XFAQPP+y841U3P/8MPj6a38tiwgRo1MjVqai6hjCEwxx2dTKqpMMcJpVUOtHJ1UmpcprQhAbot2kPERFXJ8KdPPCAqe39/HNXp0SpitelC9x7L/zjH65OiVKqpB7hEc5whvWsd3VSVBWlfS6dLD0datRwdSqUcg6LBbKyXJ0KpZRSzqTBpZNlZGhwqdyHBpdKKeV+NLh0Mq25VO7Ex0eDS6WUcjcaXDqZBpfKnVgskJnp6lQopZRyJg0unSw9HXx9XZ0KpZxDm8WVUsr9aHDpZBpcKneiwaVSSrkfDS6dTJvFlTvR4FIppdyPBpdOpqPFlTvx8dE+l0op5W40uHQyrblU7kRrLpVSyv1ocOlEIqYWR4NL5S40uFRKKfejwaUTpaebAFODS+UuNLhUSin3o8GlE6Wnm986Wly5C+1zqZRS7keDSyfKyDC/teZSuQutuVRKKfejwaUT5dZcanCp3IUGl0op5X40uHQiDS6Vu9HgUiml3I8Gl06kwaVyN/pscaWUcj8aXDqRBpfK3fj4aM2lUkq5Gw0unUhHiyt3o83iSinlfjS4dCIdLa7cjQaXSinlfjS4dCJtFlfu71+ZFAAAIABJREFURvtcKqWU+9Hg0onS08HDw/RDU8odaJ9LpZRyPxpcOlF6uqm19PBwdUqUcg5tFldKKfejwaUT5QaXSrkLiwWsVvNPKaWUe9Dg0onS03WkuHIvFov5rf0ulVLKfWhw6UQZGVpzqdxLbv9ibRpXSin3ocGlE2mzuHI3uTWXGlwqpZT70ODSibTmUrkbDS6VUsr9aHDpRFpzqdyN9rlUSin3o8GlE1VEcJmR+9gfpSqhiuxzqXlfqapDy6t70eDSiSpitPjLL7+MVed5UZVURTaLa95XqurQ8upeNLh0IkfXXP7+++98/PHHjtuhUg5WUcGl5n2lqg4tr+7H29UJcCd5B/RkZGSwZcsWtmzZQtOmTRkwYACtW7cGYNmyZVitViwWCyNGjABg+fLlZGVl4efnx9ChQ4mKimL06NGkpKSwdOlSLBYLISEhAKSnpxMeHs6ePXvo3r07/fv3x8/PL086Cj82wLFjx1i4cCEvvvgiZ8+eJSwsjICAAEaNGsV1113H4cOHCQ8Px8fHh4kTJ1KvXj27z5mcnMyyZcvYt28frVq1YsKECdSuXbsiT62qpArqc6l5X6mqQ8urKhNRTjN4sMj48SJpaWnSu3dvWbp0qSQmJsq8efOkTp068vXXX4uISHJysgQHB4u/v7/tvXFxcdKhQwdp0qSJiIhs3bpVQkNDBZC1a9fKxo0bRUTk2LFj0rNnT5k/f76cPHlS+vTpI61atZK0tDQRKf7YS5YskebNmwsg4eHhMnbsWAkNDRUvLy8ZPny4bNmyRR5++GEJDQ0Vb29vGTRokN1nPHjwoAwZMkQ2btwou3btkqCgIGndurUkJiZW9OlVldCxYyIgsn27ea15X6nKb6JMlIEyUMurKjMNLp2oTx+Rxx8XGT16tEycONFu3YgRI8TPz09OnjwpIiJPP/20XYEVEZk0aZKtwIqIzJ49WwCxWq22Zf369ZPJkyfbXq9du1Y8PDxkxYoVIlKyY+fud/Xq1bZtnnrqKQHks88+sy175ZVXBJCkpCS7469cudL2OiIiQgCZOXNmCc+Sqk7i4kxwuXWrea15X6nKLze41PKqykr7XDpRejp4e6cSHh5Ox44d7dY9+eSTpKWlsXDhQgA8PfP/1xS0LK9Dhw4RGRnJ0KFDbcsGDx7MmTNnGDZsGKmpJTt2brPAPffcY9vm9ttvB6BHjx62ZbfccgsAsbGxAJw+fZrIyEi2bdvGSy+9xEsvvcS6devo3LkzqampRaZdVU95+1yWNP9p3lfK9XJSc7S8qjLTPpdOlJ4OCQnbyMrKwtvb/tS3adMGgIMHD5Z5//v27QPI12ekcePGAGzbVrJj514YPDw8bNv4FjDM3efKPDNZV0ZrxMTEADB9+nQaNmxY5s+hqo+8fS5Lmv/KQvO+Uo51cdtFLa+qzLTm0olMzWUOYApPXrkZvG3btmXef25H6I0bN+ZbFx8fT05OxR0brhbgHTt25Ft36dKlcu1bVU15ay4rMv9p3lfKsSRHAC2vqmw0uHSi9HS48caO+Pr6EhUVZbcuPj4egJ49ewLg7++fb9JZEbEVurxylwUGBuLp6ck333xjt93hw4f59ddf6dixZMcuq3bt2uHl5cWsWbPIzDM8OD4+nsWLF5dr36pqyjuJeknzn+Z9pVzPv6O/lldVZhpcOlFGBjRo0JipU6dy9OhRvvvuO9u6VatWERISQq9evQC48cYbycjIIDIyEhFh2bJlbNu2jaSkJJKSksjJyaFRo0YAREdHs3XrVurXr8+4cePYvXs3ISEhbN68mX/961/MnDmTAQMG0LhxyY59+fJlAFJSUmzb5DYnpKWl2ZZlZ2fbbVevXj2eeOIJtm/fTq9evfjyyy8JCwsjNDSUUaNGOfx8qsrP2xs8PExwWdL8p3lfKdfzaeyj5VWVnStHE7mbhg1F/vUvkZycHHnuueekUaNGMmPGDBk/fryMHDnSNgWDiEhKSooEBQUJIAEBAbJo0SKZPHmy1KtXT55//nlJSEiQI0eOSEBAgNSrV08+/fRTERFJSkqSYcOGCSCAtGzZUn755Rfbfos79qZNm2zHfeKJJ+TAgQOyfv166dKliwAyZswY2b17t2zevFl69OghgIwYMUL27t1rS/e4ceNsx/f397cbkafcj8Ui8vnn5m/N+0pVfrmjxbW8qrLyEBFxXijr3urUgX/+Ex55xLxOS0tj//79tG/fnhoFPLpHRPjjjz9o3bo1NWvWJCYmhubNm9tNMpuVlUV2drbdMoC4uDji4+MJDAzEktvxLY/ijl1eCQkJnDhxgvbt2+dLm3IvtWvDvHkwceLVZZr3laq8HuERznCG9awHtLyq0tPg0oksFli0CEaPdnVKlHKeevXg7bdh8mRXp0QpVRLXBpdKlZb2uXSSnBzIzoYCZklQqlqzWBz/bHGllFKVlwaXTpKebn5XQK2+UpWaxWL/bHGllFLVmwaXTqLBpXJXPj5ac6mUUu5Eg0sn0eBSuSttFldKKfeiwaWTaHCp3JUGl0op5V40uHQSDS6Vu9LgUiml3IsGl06SG1zqaHHlbnx8dECPUkq5Ew0unST30atac6ncjdZcKqWUe9Hg0km0WVy5Kw0ulVLKvWhw6SQaXCp3pcGlUkq5F29XJ6A6Sk6GmBjw9wcvL6hVCxISzDoNLpW78fKClBRITDR9L1NSzPK6daFBA9emTSl3l0Ya6aTbLcskkyyySCTRbrkPPtSiljOTp6oofbZ4BThzBpo1A6u14PVeXuDnB56eMHSoed64UtXBRx/Biy/C5cuF5/9cCxbAxInOSZdSqmCf8znjGFeibd/mbaYzvYJTpKoDDS4rSNeu8MsvUNzZDQuD8eOdkiSlKtyZM9C8OeTkFL2dlxecPas1l0q52iUu0ZCGZFL0lA4eeHCMY9zADU5KmarKtM9lBQkJMTfQotSsabZTqrpo0gT69gXvIjrceHpC794aWCpVGdShDg/wABYshW7jiSfd6KaBpSoxDS4ryIMPQnZ24estFggNNQGmUtXJI48UXXPp4QEPPeS89CilihZKKNkUfsPyxLPETedKgTaLV6j27WH//sLXb99ums+Vqk4yM6FRIzOwrSCennD6NDRu7Nx0KaUKlkkmDWnIJS4VuN4LL+KIozFaaFXJaM1lBRo50tRQFqRNGw0sVfXk42Nq5X188q/z9ITgYA0slapMfPBhBCPwIX+h9cKLvvTVwFKVigaXFWjYsILn9/P2hieecH56lHKW8eMLfuSjpyc8/LDz06OUKtpoRhc4qEcQxjLWBSlSVZk2i1ewFi3g1Cn7Zd7eEBurtTeqemvTBg4dsl/m4WHKQ9OmrkmTUqpgVqwEEEACCXbLffElgQRqU9tFKVNVkdZcVrCQEPvmQW9vuP9+DSxV9ffoo/ajxj08TFcQDSyVqnw88SSUULumcW+8+TN/1sBSlZoGlxVs2DD75sHsbHjsMdelRylnGTfOfiJ1b29tEleqMhvFKLum8RxyCCXUhSlSVZU2i1cwq9XUUp4/b143bgxxccXPgalUddCvH3z/vflS5eEBx47BDTpVnlKVVktacpzjgJkDM554fPF1capUVaM1lxUs9xGPFov59+ijGlgq95E756WHB9x5pwaWSlV2YxmL5cpPCCEaWKoy0eDSCYYPN6PGs7PNzVYpdzFsGNSqZR6DOmqUq1OjlCpOKKFkXfnRJnFVVtos7gQZGVC/PnTsCD/84OrUKOVckyfD/Plw5AjcdJOrU6OUKk4ggSSQwGlO44U2tanSK+IJwMpR0tNh8GAzSlwpdzN+PERH6wwJSlUVD/MwZzmrgaUqM625LERWlpmL8uRJiI+HxES4cKHgf7mPuUtJuToy/NKlwp8t7u9/td9l3bqmX6avr6ndrF8f6tW7+nfe182bm3kz69at+M+vFMDZs3DihPmdm9+vLQu5r3NyTP5PSTHvTU+HtLSC91ujBvj5mb9r1jT539Oz8Lyf+69RI7jxRmjSxPTjVModZJLJec6TQALnOU8yyaSSSjLJXOISqaSSQgoXuUjqlZ8kkkghhVRS7R7rmEKK3YjwbLILfezjtWpRK99URXWoY7e+JjWpQx388afmlZ961LP97Y8/talt+7shDWlAAxrSUPt3ViNuG1xarXD0KOzbZ36fPGluoidPmhGtZ87YT6Pi729/k8v7z9/fbFOnztV5/a79Oy3tarCZnGxuxHn/zsgo+Iad+y9voFq3rgkyW7Y0v1u0MAMl2rUzzzOvVasiz5yqThIS4I8/TJP1iRNw/LgpA7nlIT396rY1auTP+3mDPy8vEyTWrHl1+9wAskYNEwzmBpt5A8/cv0UK/wKXmAipqVfT4uNjn/dvvNH8vukmuPVWE3wqVZmd4QynOEUssSSQwDnO2YLHvL/PcY5kkvO93wsv/PGnDnWoSU1qUYu61LUFcddxnV1Al6sGNfDDz/baAw+u4zq7fdeiFp545gs6k0kmhxzb63TSSePqN8hLXCKNNC5zmSSSSCWVNNJIJNEW9CaTzGUuk0X+x9fVoQ4NaUgjGtkFnQ1oQCMa0ZjGNKUpLWhBE5rggX7DrKyqfXApYoLHvXthzx7zb+9eE1Tm3qwaNTI3prw3qty/b7jBrPd2cQeCpCRTk5p78z9xwj4YOHXK1LZ6eJigMzDQ3GRz/7Vvf/Wmr9zP+fMmiNy3z/zeu9f8jo8362vWzP9lJTdga9ECrr/e9fknPd186cvN97lfBk+eNK+PH4fLl8229etDUNDVchAYaF5r07xyhgQSOMUpTnKSE5wglli7v09xigwybNvXoQ6NrvxcG1Q1pjENr/zkLvfHv8rX8mWRRRJJ+YLp+Cs/1wba5zhHEkm291uw0IxmNKc5N3ADza/85P7djGY0Qb9lukq1Cy6Tk+Hnn83Ameho2LbN1HyAqWUJDIROna7ecG6/3dQsVgdxcVeD6NzfO3deDaJbtYLgYPP5e/QwA4w8db6Aaic7Gw4cgKioq+Vg716zzt/fPJYxb9B1662mxq86NDMnJtrn/9wg+swZs/76603+zy0Dd9/t+qBZVU0XuchhDnMkz88e9vA7v9vVNNagBk1pSqsrP9dzve319VzPDdxg17SsCpdJpm2g0RGOEEdcvr+PcQwrptnRBx+a05xAArmVW23/B7k/quJU+eDy0CH49lv48Uf46SdzUwVzA+3Wzfy7805Tc+eOfRWzs02T5+7d5vxs326CjbQ0uO46c366doV77jE327yPqlRVw8WL8N//mmBy+3bYscN0s2jQwPzfdusGd91lAskWLVydWtc4fdoEm7/+evVacfasmXv2jjvMObr7bujbFxo2dHVqVWUhCEc5yi52sZ/9xBDDAQ4QQ4ztGdy++NKa1rSlLW1oQ1vachM32WrR8jZBq4qXTrqtu8ERjnCQg8Tk+cltxq9HPdv/V1vacgu3cAd30JrWeOosjeVW5YLLy5dh82bYuNH8O3zY1DzedRd07371Zqo3iMJlZcGuXSYQ+eknU7t79Kjpq/mnP8F995l/N9/s6pSqglitJkjKLQM//WS6f3ToYMpA7heGdu1cndLK7cgRUwZy/+3cac5tp05Xy0C3bq7vEqOcI5109rCHXeziN35jF7vYzW6SSMITT1rS0i4YyQ0mb+AGHVVdRQjCSU4SQ4wt6Mz9snCUo2STTW1q04EO3M7t3HHlpwMdqIk2cZRGlQguDx+G5cvNjTQqytTGdewI/fubG8Ddd5saCFV2R49eDVY2bzbdC1q3Nuf3gQegTx+9ybpScjKsWQPr1kFkpOlD2azZ1SCob1/Tz1CVXXKyqQHetMmUg6NHTWtHnz4waJCZEF7PcfWQQQa/8ivb2c5OdvIbv7Gf/WSTTS1qFRhc1EJHSlZn6aTzB3/Y8sNv/MZudpNMMl540YY2tjzRne50oYsGnEWotMHlyZPw1VewbBn88osZVHPffTBggHlesXbMrzjZ2aY2MzfYjI42NcEjRsBDD5kmdO2rWfFSU2HtWli6FCIiTK1ar15XA8qgIFensHo7eNDk/w0b4LvvTLno39+UgT//+eosEaryO8c5fuRHfuAHtrGNaKLJIIMAAriTO7md2+lIR27ndm7mZq2JVICp6TzCEXZd+fmN39jJTk5xCgsWOtKRu7mbYIK5m7tpSlNXJ7nSqFTBZXy8CSaXLTM1lNddZ2oLHnrI1B7oM7ld4+hRE+AsWwa//QZNm0JIiHmcX9eurk5d9ZKVBevXm3O9Zo0ZIf2nP5kyMHy4GZSmnO/SJVi92vy/bNpkvlwNGmT+Xx54wEy1pCqPAxxgK1uJIoptbOMgB/HEk0ACCb7yczd305rWrk6qqoJOctL2RWUb2/iN38ghh5a0tOWte7iHINy3BqBSBJfR0fDvf8Pnn5vXffrAuHGmdkAHmFQuR4+aGuWwMNi/H265BZ54AiZN0vk1y+PMGVi0CP71LzPlVPfuJoB/6CGds7GyuXjRBP7h4aZms1Ytc7165hl9vKWrpJDCj/zIN3zDGtZwjGPUohZ3cAc96GG74TeggauTqqqhFFLYyU6iiLIFnRe4QGMa04te9KUvQxjC9Vzv6qQ6jcuCy9RUWLIE/vd/zejWO++Ep54ytWE6NUjV8NNP5v/vq69Mzc348eb/sG1bV6es6tiyxQSUq1aZWslHH4XHHzdzTKrK7/Rp+PRT+OQT8/egQTBlimk+164jFceKlR3sYOOVnx/5EUHoTGfu4z4GMIAudMFbn3CsXMCKlZ3stOXPbWyzy5/3cR9d6Vqtu184PbhMSID/9//g449NgBkSYi7G3bo5MxXKkRISYMEC83967JjpE/vKK9Czp6tTVjnl5MCXX8I//mHmYOzWzZSBkBDzhBtV9WRnm2bz//1f0z+zdWv461/hkUe09cVRMslkE5sIJ5wIIognnqY0td2s+9JXayZVpZRMMv/lv7Zg8xjHqEc9+tOfEEIYxKBqN2WV04LL8+dNUDlvnqnleuYZeOwxM1BHVQ9Wq+kv+O678P33pnvDa6+Z+TOVCSqXLoU33jAzIIweDdOmmVp7VX3s22eucwsWmC4N//M/MGGCBpllkUkm3/It4YSzilUkkUR3ujOUodzHfdzGba5OolKldoADbGADa1jDFrbghx/3cz8jGclABlKDqt+Ju8KDywsX4IMP4P33zXRBU6bAc8/pSMvq7ocfTGD53/+apwK98Qbce6+rU+UaVit8/TW8+qoZgfzggzBnjnYfqO5OnYK5c01/8saNzXXviSe0dro4OeTwIz8STjhLWco5zhFIICGEMJaxOghHVSvnOc861hFOOBvYgAULfehDCCE8yINVdgqsCgsuc3JMX7JXXzVB5fPPm8Cydu2KOJqqrL77DmbNgq1bzcj/9983z6t2F1FRph/qnj2mpnLmTPP0KOU+TpyAN980NZk33ggffmj6ZCp7RznKJ3zCAhaQQAJd6MJIRhJCCDfgRhcN5bZOc5rlLOcrvmIb2/DHn3GM4wmeoD3tXZ28UqmQ4PLnn+HJJ01/shdegBdf1KDS3W3cCH/5ixkJPWuW6RZRnSe+T0iAGTNg4UITSPzzn/rEHHd3/Ljph/n11zByJLz3npnWy53lkMN61vMRH7GRjTSlKY/xGOMYR0taujp5SrlMLLF8wRf8m39zlKP0ohdP8iRDGYoPlb+PjUPHM168aPqQ3X23eSTjzp2m+U8DS3XffebLxt/+BrNnmwnAv/3W1alyPBH47DPzHO+ICDNl04YNGlgqU2u5fLnpKrJ7t+kW8fbbZjCQuznLWd7mbW7mZv7Mn8kii6Us5QhHeJVXNbBUbq8ZzZjBDGKIYRObaEQjQgnlBm7gRV7kKEddncQiOazm8rvvIDTU3Fzfecf8rVRBDh+GqVNN0PXMM/DWW9VjsMPZsybfb9kCTz8Nr79uvmQpda20NNNU/o9/wB13mMnZ3WH6qYMc5G3e5gu+oA51mMhEHudxbuZmVydNqUrvBCeYz3w+5VPiiSeEEF7ipUo5sK3cNZdWqxms0a+fGRW8b58GlqporVubUeWffQbz55vHSR4/7upUlc/335vn3R87Btu3myZPDSxVYfz8zJePnTtNoHnnnfDNN65OVcXZwx4e5mECCeQHfuAjPuIUp5jLXA0slSqhG7iBN3iDE5zgcz5nL3u5gzt4gAf4lV9dnTw75QouExJg8GDT1Pnuu2Yy7euuc1TSVHU3Zox5OlNaGtx+u+mLVtWImP6U/fubR2H+8gt06uTqVKmqon178zCCMWPME8mmTYPMTFenynGOc5wJTOB2bmc/+/mSL9nHPh7hkWox3YpSrmDBwihGsYtdrGY18cRzF3cRQggHOODq5AHlCC537DABwcGDZkTstGmOTJZyF23bmpq+Bx80k4i/+qoJ2KqCS5fMl6sZM8wcritX6rO/VenVqGG+oCxaBP/5j5kf9vx5V6eqfC5zmRnMoB3t+IEf+JzP2cEORjIST8d29VfKbXngwRCG8CM/sopV7GMfQQTxFE9xgQuuTVtZ+lxu2gQjRpiBO0uXam2lcoz//MfMMhAaaprLvSvxk9vOnjWP+ouLM8+Z7tLF1SlS1cHevXD//aYP8oYN0LKlq1NUektZyvM8TyqpvM7rPM7jWKjGU0MoVUnkkMNnfMZLvEQOObzJmzzCIy75Qlfq4HLDBhg61Eyl8Z//VK7pZKKiojh69OoIKg8PD3x9ffH39ycoKIim7j7vB3D8+HH+/e9/s3jxYo4dO+bq5OTz7bemFrNPHzPIoTLlr1znzkHv3pCRYcpDZZ63MjY2lvDwcGJiYmjQoAG9e/eme/funDhxgpycHAIDAx1+zHPnzhEWFsZPP/1ERkYGY8aM4fXXX2fGjBmMHz/e4ccrq8paFs6cMTXi586Zvrytq8ic4Wc5y+M8zhrWMIYxvMM7NKaxq5OVz/79+4mKimLXrl00bNiQTp060adPH/z8qv7j9xITEwkODq7wslaWsrN79252795tt+z666+nT58+pTr2tdeXqVOnct9995VqH45W2a4lSSTxJm/yHu/Rmc4sYpHz+zZLKUREiPj6ikyeLGK1luadzmG1WmXDhg3i4eEhDRs2lA8++EDee+896dSpk3h6esqzzz4rqamprk6mS23evFnuvvtu8fLycnVSCrV1q0jt2iIhISLZ2a5Ojb2zZ0Xatxe55RaR06ddnZqi/f3vf5fmzZvLW2+9Jbt27ZKEhATZsGGD9OrVSxo1aiQrV650+DFTUlIkODhYYmNjJTs7W/785z8LIHfddZcsX77c4ccrj8pcFhITRbp0EWnRQuTIEVenpnjhEi4NpIG0klbyf/J/rk5OgTIyMmT69OkSFBQkq1evluPHj8u6detkzJgxEhgYKLt27XJ1EkstPT3d7nVycrL06NGjwstaWcvOvn37pG7dugLIZ599JtmlvMAXdH2pU6eOZGRklGo/17r2PJZWZb2WREu0BEmQ1JE6Ml/mO/XYJQ4uf/1VpFYtkQkTRHJyKjJJ5Ve/fn1p37693bLRo0cLILNnz3ZRqiqPF154odIVgmtt2SLi5ycyZYqrU3JVSopI164irVuLxMa6OjVFe++998RiscgPP/yQb11aWpp07dpVFixY4PDjLl68WJo3b253rKioKIcfx1Eqc1m4cEGkY0fzRebCBVenpmCZkinTZJp4iIc8Lo/LJbnk6iQVyGq1St++feWmm26Sy5cv51v/0EMPia+vr/zyyy8uSF3Z/fWvf5UcF92Qy1p2OnXqJB4eHmVKd0VdXxxxHivrtSRd0mWGzBBP8ZSxMlZSJMUpxy1RQ3xsLAwZYqYamj8fPCt5f2yfAiZNfPTRRwFYunSps5NT6VgqY1vzNe65Bz7/HD76yDyb3tVEYNw4OHTITKNUmXtYLFmyhGeffZY33niD4ODgfOtr1KjBvHnzuHDB8R2+d+7cSY0aV0cB16hRg7vvvtvhx3GUylwW6tWDtWshJcV0Falsk63HE8+93Mt/+A9f8iUf8zG1qZxPzJg/fz7ffvstM2fOpFat/M9qXrBgAd7e3kyaNInsynaiC/H777/z8ccfu+z4ZS07NWrUwMvLC88yBBIVcX1x1HmsrNcSX3x5i7dYd+WnO905wYkKP26xQyZycswzkevWNVMNVeZBFkXx9/cH4Kabbsq3Ljk5mWXLlrFv3z5atWrFhAkTqJ3nsULp6emEh4ezZ88eunfvTv/+/e3652RkZLBlyxa2bNlC06ZNGTBgAK2vdJRat24dycnJgOkDOmzYMHx9fdmxYwcHDpgpAwYPHoy/v3+R6Th8+DBhYWG89tprREREsHfvXp599lksFkux6c/KymLlypXs3LmT3r17Y7VaHXx2K8aDD5o5VF94Abp3d+2gmXnzYPVq0ye0bVvXpaMk5syZA8CgQYMK3aZLly5Inu7WReVhgEOHDhEWFsbrr7/O4cOH+eqrr2jcuDETJkzAYrFw+vRpvv/+e6KiokhJSWHJkiUAjBo1ylZ+AgIC6H/lodqF5efY2FgWLlzIiy++yNmzZwkLCyMgIIBRo0Zx3XXXcfjwYcLDw/Hx8WHixInUu2Z4fnUrC02bmvkvu3eH114zTzyrDI5xjAEMIIssfuInAnF8311Hevnll/Hw8GD06NEFrq9ZsyYdOnRg+/bthIeH4+npidVqxWKxMGLECACWL19OVlYWfn5+DB061PbemJgY1q9fz8WLF7nrrrsYOHCgbV1R1+2i3ldceYuKimL06NGkpKSwdOlSLBYLISEhBZa14vaVy5VlpzzXl5KkvbB7eGHn0dXnoyIMYADRRPMADxBMMBvYwK3cWnEHLK5qc84ckRo1RH77zQn1qA7SpEkTu2bxnJwcGTZsmAD5+pkdPHhQhgwZIhs3bpRdu3ZJUFCQtG7dWhITE0VE5NixY9KzZ0+ZP3++nDx5UvowglV4AAAgAElEQVT06SOtWrWStLQ0ETHV8r1795alS5dKYmKizJs3T+rUqSNff/21iIicPn1aOnXqJIBdE6XVapVBgwbJkiVLik3HokWLpEmTJgJIWFiYdOzYUQCJiooqNv0XL16UPn36yGuvvSbnz5+XRYsWiY+PT6Wsvi9ITo5I//6mKTrFObX5+ezebfoav/GGa45fGjExMQKIt7d3ifshFZeHw8LCJCAgQABZs2aNDB8+XAYPHiyAzJw5U0REzp07J6tXr5YePXpIs2bNZPXq1bJ69WrZt2+fDB06VAB5++23RUQKzc9Tp06V5s2bCyDh4eEyduxYCQ0NFS8vLxk+fLhs2bJFHn74YQkNDRVvb28ZNGiQ3eeozmXhk09EPD1NdxFXOySHpJk0kzvkDjktlbzjsYicOHFCAGnatGmR202ePFkAeeGFFyQ5OVmCg4PF39/ftj4uLk46dOggTZo0sS2bOnWq9OzZUxISEmTTpk3i4eEhb731logUns+joqKKfF9JytvWrVslNDRUAFm7dq1s3LixwLJWkn2JOLfsBAcHi7e3t+11ea4vJUl7Uffwgs6js8+HsyVKotwj90h9qS87ZWeFHafI4PLgQRNYzp1bYcevEE2aNJFmzZpJWFiYvPHGGxIYGChdu3aV8PDwfNv269fPLuCMiIiwy9T9+vWTyZMn29avXbtWPDw8ZMWKFSJi+nJOnDjRbp8jRowQPz8/OXnypIiIREZGCiCLFy+2bZORkSHDhw8vcTpefvll20VKRGT//v1itVqLfd9TTz0lQ4cOtUvf/fffXyUKQa64OJG6dUVefNH5x87JEbn7bpFu3Sp/X2ORq3ntlltuKfF7SpKHp0+fLoDtgi4icu+990rbtm3t3vfQQw9Ju3bt7JbFxsba3fBECs/Ps2fPznecp556yjYAINcrr7wigCQlJdmWVfeyMHiwGUxWzrEL5RIrsdJKWkln6SwX5aLrElIKufmga9euRW734YcfCmD70vL000/bBZciIpMmTbILLuvWrStz5syxvQ4MDJRu3brZXheWz4t7X0nKW25ZseYZXVtQWSvJvpxZdq4NLkuaRpGCry/lvYcXdB6r+7UkTdKkr/SVAAmQg3KwQo5RZCP3s8+aJsBnniljtagLWSwWbr75ZtasWcPevXtZt25dvmbC06dPExkZyR133MFPP/0EwOXLl+ncuTOpqakcOnSIyMhI1q9fb3vP4MGDOXPmDI0bNyY1NZXw8HDeffddu/0++eSTLF++nIULFzJz5kz69u1L+/bt+fjjj23NMitWrLBVvxeXDsDWDJ/bDNCuXbti33fu3Dnmz5/PP//5T7v03XbbbURERJT/JDvJ9dfD3/9u8uGjj8LNTpxR4Ysv4Oef4ddfK39fYwDvUvZbKWkezu2nlrcMBQUF2fJdUfI2JeUqKD/n3faee+6xbXv77bcD0KNHD9uyW265BTBTLfn7+7tFWfjwQ7j1VtMH+fnnnX/8dNK5n/vxwYcIIqhLXecnogwaNWoEmPxQlNy8V7NmTYAC+wReu2zdunW0b98egJ9//hkRIS0tzba+sHxe3PvKWt4KKmvF7asylJ2yft7y3sPLss/qcC2pQQ1WspI+9GEgA4km2uHludA7UXS0GbgQEVE1+1n6+fkRHBzMrbfeSnR0NBMmTGD37t00adLEtk1MTAwA06dPp2HDhvn28c2Vh/1eW2BzM+W2bdvIysrKd0Nvc2Xiw4MHD9qWPf3000yZMoXdu3dz2223sXLlSj7//PMSpQNMf81rFfe+yMhIsrKy7D5zYfuq7B5/3NxU58yBsDDnHDMnxzzadNw48zSqqiA378XExJCWllbs3H0lzcMF3Whr1apVosEPBb23sDyYu23e9b6+vvm2yx20l5WVBbhHWWjZEv7yF3j7bVMenP3s+ud4jiMcIZpoGlLwdaoy6tChAz4+Phw/frzI7XLXty1Fp+rg4GBWrlzJihUruO+++2jZsiWxsbG29YXlr+LeV9byVpKA+Np9VYayU9bPW957eFn2WR2uJQC1qc0a1tCRjjzKoyxnuUP3X2hdzN//bp6V7OK5ScvtuuuuY/HixVy4cIHx48fbDWLIvUHt2LEj3/suXbpkuzFv3Lgx3/r4+HhycnIAc4POKzdD5r1IjRs3Dn9/fz788EP27dtHmzZtbMcvLh2FKe59ue89ffp0ofuoKry84JVXTE3iyZPOOeby5XDkCLz8snOO5wjNmjXj1ltvJScnhz/++KPIbUWkVHm4MnOXsvDXv0J6Oixc6NzjbmITH/ER/+E/tKaKzOp+hY+PD7fffjuXL1+2e8jGtQ4cOICHhwcjR44s8b6nT5/OggULmD9/PmPGjCnwi5Aj31cRqnLZKe89vCz7rMzno7QCCGAJS1jFKr7gC4fuu8Dg8uxZM0Lx6acdeiyXCQ4O5tVXX2XTpk288847tuXt2rXDy8uLWbNmkZmZaVseHx/P4sWLCQwMxNPTk2+++cZ2EwYzAvDXX3+lY8eO+Pr6EhUVZXe83Ezbs2dP27LatWszfvx4Fi9ezNy5c5k8eXKJ01GY4t6X23RYUFV9ZR/ZVpCRI6FBA+fVXM6fbx7x2KqVc47nKLNnzwbMDSxvvsgrPj6ehQsXlioPV2buUhYaNoSHHzZ501myyeav/JXhDOdBHnTegR3o/fffx2KxMHfu3ALXnzx5kuXLlzNy5EhbNwx/f38yMjLstsv7hSw6Opq5c+cyZcoUu+lxpJiH3pX1fYXJe28qi6pcdsp7D88rd31VPh9l0YtePMZjvMALJJPsuB0X1BFz3jwzgKIqPswmKytLvL29pVmzZnbLs7OzpWfPnuLl5SVr1661LZ8yZYoA0q1bN1n8/9m78/CoyvP/4+8EkhAggbAFlU0QMBCVKC4ICC4gS2lRQMuOG0KBKhRBSxVU/NnKV23dqlVLsGUTRFxYY0FEEFFQ9iUsEiCAYUvIvt2/Pw4ZGBIgwEkmIZ/XXFzJnHPmPPcM82Tuec6zTJ1qkydPtg4dOtjx405n9UGDBhlg9913n/3vf/+zt956y3r37u3p/Dt69GgDbMmSJZ5z/uMf/7BevXp5dRA2czpz+/n52W9/+9t8cZ8vjgkTJhhg8fHxF/S4Tp06GWCTJ082M2cgUd5IvLi4OMvKyrqYl9lnRo50JpUuagcOmPn5mRXBIjbFYuLEiebn52cDBgzIN2n0nj17bNSoUZaZmWlmhXsPjxw50gBLSkryHDN69Gjz8/PzWt2iY8eOXgMezJwZEwB77rnnPNvO9n5+8cUXDbD9p81S//777xtgmzZt8mybNm2aAbZy5UrPtrJSF1auNANnFoPiEG3RFmiBtstKwVJB5/DOO+9YUFCQLV++3Gt7amqq/e53v7M2bdrYiROnJoHPe98tXrzYcnNzbcaMGda8eXMLDAy048eP24YNGwywxx9/3LKysiwmJsauvvpqq1Onjm3fvt127dpV4Pt88+bN531cYerbO++8Y4CtWrXKvvnmG0tLSyuwrhXmXMVZd66//noDvF7rS/n7cqmf4QW9jmXlb0meBEuwUAu1Sebe6O0Ck8uuXc1OG8hcanzzzTfWo0cPAwywIUOG2OrVqz374+LiLCwszMqXL2/du3e3mJgYS0lJsQEDBngeExoa6jVKLDEx0TONEWANGjTwWsUhJyfHRo0aZTVr1rSxY8fawIED7YEHHvBMVXSmjh072sKFC/NtP1ccs2fPtqZNmxpgvXr1snWnzQt1vvgPHjxobdu2NcCaNGliv/3tb61fv35WuXJlGz58uO3bt+/iX3Af+Oor54O1qJfEmzLFLDDQ7ETJXHCkUGbPnm2RkZEWHBxs7dq1s2HDhtljjz1mEyZM8Jqm6Hzv4blz51qDBg0MsCeeeMJ27dplM2bMsKuvvtozdcuWLVvstddes6CgIM9xX3/9tcXFxdnQoUMNsGbNmtmCBQvO+n5evHixRUZGeurutm3bbP78+XbzzTcbYP369bP169fbkiVLrE2bNgZYz549bfPmzWZWdupCTo5ZzZrFN4vHLXaL9bbexVNYEZs/f761bNnSBg8ebP/6179s/Pjxdvvtt9u4cePyfQlLSUnxvB/Dw8NtypQpNnjwYAsLC7PRo0fb4cOHrX///ubv72/h4eH27rvv2sSJE83f399Gjx59zr/b53pcYerboUOHbNeuXRYeHm5hYWH2wQcfFFjXCnuu4qg769ats+HDh5u/v78B1rdvX1u8ePEl/X3J+3+6lM/wM1/Hwpzzcvlbcro/2h+toTW0HHNnWpR8yWVurtNq+dZbrpy/1EhISLA1a9acde3x/fv3288//+xp7TlTamqqrV279qxJZZ64uLh8LZoXEsfFPm7Hjh22bds2y83NtV27dnlN4VKapKc7c06eNitNkXj0UbM77ijaMopLcnKyfffdd5aQkHDO4wr7Hi7pykJd6NXLrFu3oi9nl+0yDPuf/a/oCysmOTk59vLLL1u5cuUMsAkTJpz12NzcXFu/fr2lnJxkd/v27fneV7/++qvX58LRQq7VebGPO11mZuYFf1acS2muO5fyGX6217E0vx4XaoNtMAz7zr5z5Xx+Zt4dPfbtg7p1YdkyZwk+kZLm+uuha1d4+eWiK6N1a7jxRmdlHpGS5oUX4KOPnOVIi9JkJjOMYRzjGEH4btBJUfjqq6/o27cvx44dY+nSpQUulSpSllzFVfyRPzKWsZd8rnwDevIG0xXnXIIiF6JxY2cUd1HavVt1QEquJk3gl1/gIseAFNpP/MSN3HjZJZYA99xzD7t27eJvf/sbjzzyCG+99RZHjhzxdVgiPnMbt7GW/KPkL0a+GSwTE52fVau6cn4R11WtCvHxRVtGYiJUKR1zREsZVKWKMw9rcnLRznf5K79Sm9rnP7CUqlSpEiNHjmTYsGGsWrWKjz/+mMjIyFIzS0JJsHfvXh566KHzHjdw4ED69+9fDBHJxapNbTaz2ZVz5Usu80ben5zqSaTECQpy5vorSpmZqgNScuXNYJOeXrTJZRpphFDMs7X7QGBgIHfccYfXylBSOHXq1GHevHnnPe5CVw+T4leRiqSQ4sq58v1v501kn5ys1kspmZKSIDS0aMuoXNmpAyIlUdLJ6eiKuh5UpzoHKP2TRUvR8fPz8+kk8OKewxymFmdfvehC5OtzeXIZVg4edOX8Iq47dMiZTLoo1azplCNSEh065CSWRf2ZXpe67KCIRw2JSImwgx3Upa4r58qXXDZtCv7+sGWLK+cXcd3mzRARUbRlXHut6oCUXMVRBwDa0IYd7GA/+89/sIiUWqmk8gM/0BZ3+hvnSy4rVnRG465e7cr5RVy1b58zmKdFi6Itp0UL+P77oi1D5GKtXg0nVyksUq1pTWUq8wmfFH1hIuIzn/M5OeRwJ3e6cr4C1xbv0AEKWOe9xIiNjSW6uBaYLuH27NnDuHHjaNCggWvnWLp0Kd+X0Mxq0SIIDoY2bYq2nA4dnOmOinoewYulOnBKWasDx445yWWHDkVfVkUq0pe+vMu7GEU879FlTPX1lLJWX0uLd3iHbnTjCq5w5XwFJpfdusHPP8P27a6U4ao5c+bwxhtvaEqDk3bt2sXXX3/Nvn37XDvHnXfeyebNm/nrX//qVpiumTnT+VDNGy1bVG67zenXOXNm0ZZzMVQHvJW1OjB7NgQEFE9yCTCCEWxnO//hP8VT4GVG9dVbWauvpcFCFrKc5TzJk+6dtKBle3JyzOrVM3vqKVdWAXLNunXrrE2bNr4Oo8R56qmnrFy5cq6fY9CgQbZo0aJLOq+bdu0y8/c3O22J1yI1cqRZw4ZOfSgpVAcKVlbqgJnZLbeY9elTvGUOsSF2hV1hx+148RZcyqm+Fqws1deSLt3S7Vq71u63+109b4Etl/7+8Pjj8K9/OZdgSoKcnBx69OhB3759fR1KiRMQEFAk53jxxRcZMmQIKSnuzHt1qV55BerUcZZ+LA6PPw579sDHHxdPeeejOnB2ZaUOLFniXBL/wx+Kt9wXeRHDeJRHi7fgUkz19ezKSn0tDUYxinjieZVXXT3vWWc1HT4cXnsNJk2C//f/XC3zonz22Wfs37+fPn36eLbNnDmT3NxcAgIC6NmzJwCzZ88mKyuL4OBgunfvDsCOHTuIjo7mhRdeYOfOnXz88cfUqlWLQYMGeb1BU1NT+c9//sOvv/5KREQEd999N6Ghofj7++Pn58fOnTuJjo5mwoQJLFiwgM2bNzNy5EgCAgLIyMhg2bJlLFu2jCuvvJJOnTrRqFGjIokzKyuLTz/9lJ9++on27duTm5ub7/VKSkpi5syZbNmyhYYNGzJo0CAq501iWshz1KlTh5CQEJ577jlefdXdN96F2r0b/v1vZ61vF/4uFUrTpvD738Pzz0OPHsVX7tmoDpTtOmAGzz7rXA4v7mWwa1CDaUyjAx14jdcYxajiDaAUUn0t2/W1NPgv/+Wf/JOZzKQBDdw9+bmaNV97zSwoyGzbNldbSy/KnXfeaS1atPDalpSUZK1bt7bQ0FDPtvj4eLvuuuusdu3aZmYWHR1t4eHhBtjnn39u999/v3Xt2tUAe/bZZz2PS0hIsEaNGtmUKVMsMzPTxowZY4A1aNDA2rRpY1OmTLHatWsbYNHR0RYVFWWArVixwtLS0qx9+/Y2Y8YMO3bsmL355psWEhJin3zyietxHj9+3O6++26bMGGCHTlyxKZMmWKBgYFelwe2b99u3bp1s0WLFtnPP/9skZGR1qhRIzt27Fihz5FnyJAhVr9+/Yv9b3PNb35jFhFhlplZvOXGxppVqGD2yivFW25BVAccZbUOREeblStn9sMPvothkk0yf/O3/9p/fRdEKaH66iir9bWkm2/zLcAC7Ckrmv6P50wus7LMWrQwa9fOt/3OcnNzrUKFCtalS5d8+4YPH+5VAczMHn30UU8FMDNPpfvss8882+68805r0qSJ5/6TTz5poaGhlpWVZWZme/fuNcD+/Oc/e44ZN26cp6KamW3dutVyc3OtT58+9tBDD3nF0LNnTwsODra9e/e6Gucf/vAH6969u9d5fvOb33hVsg4dOtinp3VMXLBggVeFL8w58owfP94AO3LkSL59xWX6dDM/P7Ovv/ZN+S+8YFapkpNo+orqQNmuAwcOmNWsaTZ8uM9C8HjKnrIAC7CZNtPXoZRYqq9lu76WdItskVW0ijbIBlmu5RZJGQX2ucxTvrxzKXLVKnjppUtuJL1oBw4cID09nSuvvDLfPn///E/hzG2VKlUCoEuXLp5tkZGRXqPVYmNjPZcSwGlev+aaa/j22289xwQHBwPQu3dvAJo2bUpaWhqzZs0iKirKq8yhQ4eSlpbG5MmTXYvz119/5f3336djx45ej7v++us9vx84cICYmBhWrlzJM888wzPPPMO8efNo2bIlqamphTrH6WrVcpaC+vnnnwvcX9R27YIhQ5w+Zu3a+SQExo49dYk8I8M3MagOlN06kJsL/ftDlSq+/Tuc52/8jWEMoze9eYu3fB1OiaT6Wnbra0k3jWl0oxs96MH7vI8ffkVSznlXko+KcvpdjhwJLVtC585FEsc5HTq5Dl/oRS6kW1AlqVSpEtnZ2Z77bdq0Yd68eaxevZpWrVqRkZFBfHw8v/nNbzzH5FXi061cuZKsrCzKl/d+KRs3bgzA9guYz+l8ca5bt46srCxq167tdczpccXGxgIwZswYahSwRmJMTMx5z3G6vHNs27aNu+66q9DPxQ3JydCzJzRoAP/3f8VatJfAQJgxA266yemL/P77xR+D6kDZrAPg9LP85htYsaLo1xIvDD/8eJ3XCSecP/JHtrGNV3mVQAJ9HVqJofpadutrSZVLLuMZz0u8xJ/4E6/wSpEllnCWeS7PNGKE8835wQdh3boii+WsrrnmGvz8/Dhy5EiRlTFy5Eh69uzJmDFj+Oqrrxg9ejS33347L7zwwjkfl5OTAzgV9nR5b/AmTZq4FuOJEycA55ve2QQGOn/g165dW+DjC3OO0+WNugsPD7+gWC9VTg706QP798OcOUU/r+X5NG4MU6fC5Mnwt78Vf/mqA46yVAfAeb+9/DK8+67z5b4keZqnmcEMoommPe3Zy15fh1RiqL46ylp9LakOc5gudGESk3iXd5nEpCJNLKGQySXAe+/BLbfAvfcW/5rLISEhNGrUiF9//TXfvtDQUDLOuFZpZp4KVFh+fn5ceeWVvP766+Tm5jJs2DBiYmIICQk55+OioqIICgpixYoVXtsTEhIAaNu2rWtxXnvttQAsWLAg3768kXNNmzalXLlyjB8/nszMTK94pk6dWqhznC4+Ph6Aq6++utBxXqqcHBg0CL76CubOhYYNi63oc+rWDV5/HZ55xvmwL06qA46yUgcAZs2CwYPhz3+Ghx4q1qIL7QEeYDWrOc5xrud6PuIjX4dUIqi+OspSfS2p5jKXSCLZylaWs5zBDC6WcgudXAYGOh/011wDd90FmzYVZVj5RUVFFVhR69evT0ZGBjExMZgZM2fOZOXKlSQmJpKYmEhOTg5Hjx4FIC0tzfO47OxssrKyPJXnlVdeYdmyZezdu5eAgAASExPZvHmz12WIrKwsAK9vo7Vq1WLEiBHs3r2bpUuXerbPnTuXXr160e5kR0E34mzWrBmdOnXiyy+/9CwllpmZyc8//4yZsXfvXkJCQhgyZAirVq2iXbt2TJs2jejoaPr27Uvv3r0LdY7Tn3N8fDxVq1b1VPCilp3tJJaffAKffw6tWhVLsYU2YgS8+KLTB/Sf/yzeslUHykYdAGdlqD59YNgwmDix2Iq9KBFEsIY1DGQgD/EQv+N3asVE9bUs1deS6BCH6E9/7uM+utCFdazjZm4uvgAudARQUpJZ27ZmYWFm33xz6SOKCmvatGkWFBRkycnJXttTUlIsMjLSAAsPD7cpU6bY4MGDLSwszEaPHm0ffvihNWjQwAB74oknbNeuXTZjxgy7+uqrDbCnnnrKDh06ZF988YVVqFDBAK9/9erVs8WLF9vs2bOtadOmBlivXr1s3bp1nhhycnJs1KhRVrNmTRs7dqwNHDjQHnjgAUtLS3M9zoMHD1rbtm0NsCZNmthvf/tb69evn1WuXNmGDx9u+/bts5SUFBswYIDnOYSGhnqNxCvMOfK0atXKRo0aVYT/s6ckJ5t16eKMzF68uFiKvGgvvuiMYB8/vvjKVB24/OuAmdk//uGsRDVypFlu0QzkLDJLbak1tsZWySrZS/aSpVu6r0PyGdXXslFfS5osy7I37A2ralWtrtW1L+wLn8RxwcmlmVlamtn99zvz/33wgdshnV3nzp3t888/z7c9NzfX1q9fbykpKWbmzJmVmpp6QeeeNWuWTZ8+3Q4fPmzbtm2ztWvX2tKlS+3NN9+09u3bF+ocqamptnbtWq8K6naceXbs2GHbtm2z3Nxc27VrlyUmJuY7JiEhwdasWXPWMs53js2bN1tQUJDt3LnzomK8EDt2mN14o1mtWmarVxd5ca54/32z8uXN+vY1O3GieMpUHTjlcqsD6elmw4Y5X1pKwryqFyvd0m2iTbSKVtEaWSObbtOLbLqTkk719ZTLrb6WRJ/ZZxZpkRZogfa0PW3Jlnz+BxWRi0ouzcyys83+/GfnG3b//k6rU1GLi4uzu+66y3JcnnQzNjbWatWq5Zkv7HSHDh2y/v37u1peaTFy5Ej78MMPi7yc2bPNqlRxksvS9jdh0SJn/sGICLMNG4q+PNWB4lVcdWDnTrObbjILDXXqw+Vgj+2xATbA/M3foizK5tt8X4dU7FRfi1dx1deS5mv72lpba/MzP+thPWyb+X7lm4tOLvP8739mtWubNW1qdlqre5GZM2eOvfTSS66ec8mSJQbY73//e1u2bJnFxcVZXFycxcTE2IMPPmg7duxwtbzSYPr06V6T8RaFrCyzsWOdlpr+/c0u8guxz+3b53QVqVDB7O9/L/ryVAeKR3HUATOzuXOdbkZRUb6dqL+obLAN1s26GYbdZDfZJ/aJ5ZgPV+UoZqqvxaO46mtJssAWWFtraxh2t91t39v3vg7J45KTSzOzvXvN2rQxq1jR6S+Une3GWc9u165dNtvlr/eLFi2yESNGWEREhFWoUMGuu+46Gz16dIFN95e7b775xhYuXFikZfz0k1nLlmYhIc4KPKXd6Ylynz5mBw8WbXmqA0WrOOrAsWNmQ4Y475khQ5zuRpezNbbGelgP8zd/i7AIe9vetkQrG+8t1deiVRz1taRIsRT70D60G+1G8zM/62ydbbkt93VY+fiZmbkxMCg7G154wZkDsHlzZyTtrbe6cebiZ2ZnnaBVLk1SEjz3HLz9tvP++Pe/wcVp1XxuwQJnRaETJ5zVVB5/HAqYZ7jEUx0oOmbOnKmjRzv333gDHnjAtzEVpy1s4VVeZTrT8cefPvRhKENpQQtfh1Zqqb5e/raylXd5lylMIY00etKTP/Enoog6/4N9wLWPvfLlneRy0yaoVcuZQmbAADh82K0Sio8qadH44guIjISPPnJW3Pnmm8srsQRnBastW+CPf4Qnn4Sbb4bvv/d1VBdOdaBoxMY6cwUPGAAdOzp/L8tSYgnO1EUf8AEHOMCrvMp3fEcUUbSkJf/iX6SS6usQSx3V18tTJpnMYhYd6EAzmvEJn/AET7CXvfyX/5bYxBJcTC7zXHMNLFwI//0vxMQ4rZhvvAHp6W6XJKXFd9/B3XfD737nfLDGxsITT5TOFr3CqFgRJkyAtWuhUiVo3dqZDHvPHl9HJr5y8KCzhG5kJBw96nzh+OgjqF7d15H5TiihDGYw61nPUpZyDdcwghHUox5/4A98zdfkkn+SbJHLmWF8x3c8yZPUpz696U1FKjKf+exhDxOYQE1q+jrM83LtsnhBEhOdCaf/+U+oWtVZ2eSxxyAoqKhKlJLk+6Hw1lQAACAASURBVO+dJGvhQmjTBl55peRNil7UzJwvWuPHO0tZPvyws+JK3bq+jkyKw6+/Ou/7vL+Bf/mL80WjXDlfR1YyHeIQk5nMDGawjnVcwRX0oAcP8ACtaY2/++0hIiXCalbzMR8zi1nEEce1XMuDPMgjPEJdSt8HRpEml3kSEuDVV50WzJAQGDXKabny9XrRUjTWr3dWFZk9G267zflS0a2br6PyrawsmD7d+bIVF+esQvTss1Cnjq8jk6Jw5Ai8+aazXGhQEPzpT05XieBgX0dWeuxmN5/zObOYxQpWcBVX0YMe9KIXrWld5GsjixS1TWxiFrOYxjRiiaU+9fkdv6MXvWhDG1+Hd0mKJbnM8+uv8NprTpIZGup8wA4dCvXrF1cEUlRycmD+fOf/9n//c9ahHzdOSeWZ8pLMF16AvXudrgKDBzvdBtRtqvRbuxbee88ZsBMc7AzaGTHC6SohF28zm/n45G0LW6hJTdrTnnu4h6505Squ8nWIIueVTDJLWcqXfMkiFrGHPdSjHt3pftl9aSrW5DJPfLxzmeiDD5wBP926OWs16wO29Nm/3/kw/eAD58vDb37jrIfcoYOvIyvZMjNh2jR45x344Qe4/nqnDvTtC5Ur+zo6uRDp6fDxx87/5fffO/0q//AHZ9BOpUq+ju7ys4ENzGMei1nMClaQTTZRRHEv99KRjtzO7QQQ4OswRcghhx/4gUUnb6tZDcCt3Mq93EtnOhfvet/FyCfJZZ7MTJgzx/mjvHw5NG0Kjz4KDz6oPmklWUaG04/yo4/g88+dQQmPPOJMu1Ovnq+jK31++MGpAzNmOJdQ+/VzkszbbtOXrZJs7VrnC0J0tDP11H33OUnlHXf4OrKyI68lKO/Dewc7CCGEu7mb9rTndm4niijKU97XoUoZkEMOG9nIt3zLMpbxFV9xjGPUox73nrzdzd1UpaqvQy1yPk0uT7d+vdOaOXMmHD/ujLB98EHo1QvCw30dnWRnw1dfOf8/c+c681W2besklD16QGCgryMs/Y4cgcmT4cMPYetWp7vIgw/C738PUSV3xokyZfNm50vAzJmwfTtcfbUzSOvRR6F2bV9HJzvZyWIWs4hFfMu3HOEIlajEzdxMa1pzO7fTilaEEebrUOUycIITrGIVK1nJClawilWc4ARVqEJrWtOBDnSiE9dyra9DLXYlJrnMk5kJixY5f7w//xxSU6F9e+dDtmtXuPJKX0dYdmRkOC3Kn3ziDM45fNiZ+PzBB525+a5SN6ci8/PPTh2YORN273bmA/3976F7d2jRQi2axWnjRvjsM+f/YsMG533/wANOPSitC0WUBYaxla2eD/6VrGQb2/DHnwgiPMlmFFFEEKFL6XJOOeSwne2sZS3f8R0rWMEGNpBDDg1p6Hk/taY1zWle5mc2KHHJ5enS0pxBIjNmwLx5zv3rrnPmSrz3Xmd6G404d9e2bU5yv2gRLFsGKSlwww1OYvPgg05LjRSv7793EptZs2DfPqclv0MHpw507OgsWiDuOXrUaaXPqwf79zuvcc+eTh1o0+bynaP1cpdEEqtZzbd8y4qTtzTSCCCAxjTmJm6iOc1pRjNu47ZSMZ+guO8EJ9jOdjaxiTUnbz/zMymkUJ7yNKEJbWhDa1rTjnbUR6OSz1Sik8vTpaU5yc7ixU5/vy1bnBGY7do5H7Bt2jhJUIC+fF6Qfftg5UpYssT5IP3lF2c+vrvvPpXEqx9lyWAG69adSnpWrHBGn0dFOf9Pd9zh9NOsevl353HViRNOv9dly5zX9ccfnZbhW289VQdatlRCeTnKIoutbGUd6/iZnz0/D+MsLdeABtzADbSgBc1pTmMa04QmVETD/y8H6aQTe/K2mc2sYx0/8RO72IVhVKUqLWjBDafdIokkEPUDO59Sk1yeKS7u1IfskiVw7Jgz9UfLls4HbKtWzs8rrvB1pCVHRgasWQOrVjmr5qxa5SSX5crBTTed+iC99VZnOU8p2ZKTYelSpw4sXuysfOTvD9de67z3b7/d+RkRocQoj5nTVzKvDnz3nbMEY04ONGhwqkX47ruVpJdl+9mfL+HcyU5yyAGgLnU9iWZjGtOUpjShCQ1ooMvrJUwOOexhD9vPuMUSSxxx5JKLP/40oIFXItmCFmqRvASlNrk8nZnTknn6B8aWLZCb6wyKuOkmaNbMmSIkIsL58L3cB6Ds2+cMPti0yfm5YQP89JPTp7VmTSfpyEtAWrbU9DeXg0OHvOvAjz86fZarVHH+j5s3d/41a+b8DLvMxzQkJTl/BzZudOrAxo3Ol6sjR5zuNDfeeOqLaKtW6kMs55ZJJrvYxTa2eZKTWGLZxjYOcACAAAK4mqtpSEPqnLzVo57X75XQ/FRuSiONOOLYz372stfz+z72sYtd7GQnmWQCUJOani8CeV8M8n4GoaUD3XRZJJcFSUx0+qqtWuWMRN+0CXbscEY9ly/vrIHevLmTbDZq5Fz6rVvX+Vlalqc8cMBpwd2711m3etu2U8nk8ePOMbVqOUl18+Zw883Oh2njxr6NW4pHdrZzGf2775wvFhs3OsnWiRPO/iuvPJVwXnON896vX9+pB6Ul8UxKct7/v/zi1IWdO089z7g455iKFZ163ry504XgttucxPJy/4IpxSevj14ssWxnO7vZzT72sZ/97GEPqaR6jq1KVa+k8yquoiY1CSec6lSnxslbdaqX2SmUcsnl8MnbEY5wmMMkkMCv/Eo88ew9edvHPo5wxPO4ClSgHvW4iquoS13qU5+mNPUkkWVhCqCS4rJNLguSmekkYHmtGFu2OL//8ovTpzNP7dqnks26dZ0ErVo1Zz7HatWcf2Fhzs+QEHfjO3bMGVBQ0L+9e51/eQllRobzOH9/5/J/kybeLbSRkU7MIqfbs8e7Dmzc6IxIP3z41DEhIaeSzXr1nPdX3nu+oH9ujl4//T1/Zn04dMiJf88epw7kfYkCJ76GDU+1zOb9bNBA3QLEt45y1JNo5iWdccSxl73EE08CCRzlaL7HVaOaJ9nMSzhrUIOqVKXiydvpv1ehCpWoREUqEkIIoYRSjuJdyD6XXBJJJIUUUknlBCdIIonUk7fjHPf6PS95PD2RzOvzeroqVCGccK7gCq/EvB71qEtdT5IuJUOZSi7PJSHBuxUw78Nr3z5nX94H3ZkCApxLynk/wWn5zFvuLTjYuQRnduqDMCfHaXEBZ0BGcvKpn2cKDj71AX7VVaeS3vr1T7Uy1amjgUxy6VJTnS9ap3+ByasLv/56KsHLysr/2KpVnQQz72fe7+D06Q0NdX7Pe6+Dc3UhN9f5Pa9uHT/u1JXTlS9/KrGtVetUwntmXVDXDinNssn2JFd5P3/l13xJ1xGO5EvQjLN/jAcS6LkUX57yhODdInLmnJ8hhHhaTHPIIYkkr/1nlpdMMlk4lTqNNNJJP+fzPDMZPjNxrk51alEr33b1ZS1dlFxeALOCW1WSk70TxsxMZwofcD6w81oY8y41nv5hm5eIBgR4t4jm/dNUS1LSnDiRv0Xx2DGnfiQlOXXh9C9T2dmnLsVXqnTqcnSVKk6L4umJaNWqTmv76fUgr66ISMHSSCOVVBJJJJlkUkklmWQSSSSVVNJwLs1lkOF1if5syeM2tpFJJpFEnjP5BAgmmAo4H1QVqJCvNTWUUEIIoSIV1d+0DFFyKSIiIh4P8zAHOch85vs6FCml1BNJRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSRERERFyj5FJEREREXKPkUkRERERco+RSREREXLV582aeeOIJbr755nMed/ToUZo2bcrkyZOLKTIpDuV9HYCIiIhcXnbv3s3ChQvJzMw853Hly5enevXqVK5c2dXyMzIyCAoKcvWcUnhquRQRERFXde3alRtvvPG8x4WGhrJy5Up69erlavnjxo0jNzfX1XNK4Sm5FBEREdcFBAT4pNwNGzbw7rvv+qRsceiyuIiIiBTo22+/ZcGCBdStWxd/f38GDx7MzJkzyc3NJSAggJ49ewIwe/ZssrKyCA4Opnv37gD4+fnh5+cHwMKFC1m2bBlRUVE88MADnvNnZGQwe/ZsqlevTqdOnTzbk5KSmDlzJlu2bKFhw4YMGjTI69J5eno6s2bNYtOmTbRq1YqOHTsSHBzMihUr6NOnDykpKcyYMYOAgADXW0Xl/NRyKSIiIvmMHTuWuLg4xo0bR9WqVfnTn/4EQJcuXXj77bd55JFHPMe2bt2al19+maFDh3qdw8wYN24czz//PP/5z3948MEH6d+/PwCxsbH069ePfv36sWbNGs9j8rbXr1+fgQMH8t5779GiRQuOHz8OwJ49e+jYsSMZGRkMHz6cN998k8jISNLT0zEz2rZtC0CVKlWoUqVKkb5GUjAllyIiIuLFsowPP/yQli1bUrFiRX7/+997ksmQkBCioqK8jr/iiiu49dZb853nyJEjdO/ene+++46dO3dyzz338N///peYmBgaN25c4OXrYcOG8fDDD9OxY0duuOEGJk2axM6dO3nttdcAeOyxx4iIiODRRx+lTp06jBw5kt27d7NgwQLatGlDkyZNACcJ7tixo9svjRSCLouLiIiIF78AP0JCQrjnnnt477336Ny5M+PGjfPs9/fP3zZV0LYaNWp4piMKCgpi8ODBfPXVVyxevJgOHTrkGyV+4MABYmJiaNGiBd9//z0AycnJtGzZktTUVHbs2EFMTAzz58/3PKZr164cPHiQWrVqufLc5dIpuRQREZF83nrrLfr370+XLl1o1aoV0dHR1KxZ85LO2bFjR8qXL098fDyQPyGNjY0FYMyYMdSoUSPf47/44guAfEmpEsuSRZfFRUREJJ+uXbuyY8cOnnzySdasWUPLli3ZsmXLJZ2zSpUqBAcH07hx4wL3BwYGArB27dp8+06cOEFwcDAAixYtyrc/ISHhkmIT9yi5FBERES85KTm8//77VKtWjddff52vv/6a5ORkpk+fDjjzU2ZkZHg9xszIyck553kPHjzIiRMnuOOOOwrc37RpU8qVK8f48eO9JmBPSEhg6tSpNGvWDH9/f7744guvsnbu3MmPP/7o/RzOE4sUHSWXIiIi4sVyjfHjx5Oeng5Aq1ataNy4seeyeP369cnIyCAmJgYzY+bMmaxcuZLExEQSExM9iV1qaiqpqame806aNIlBgwZx1113FVhuWFgYQ4YMYdWqVbRr145p06YRHR1N37596d27N1deeSUDBgxg/fr19OrViyVLlvD222/z7LPPeqYyyotxzZo1LF++3PMcpPioz6WIiIjkc/z4cW655RYee+wxjh49SuvWrRkyZAgAffr04R//+AcdO3YkPDycV155hdatWxMfH8/EiRN5+umnefzxx9m+fTs33ngjffr04ZdffiEsLIx33nknX1l582ECvPLKK5w4cYKPPvqIVatWERoaypQpUzzTCv3jH/8gMTGRTz/9lE8//ZQGDRowa9Yszzk6depEeHg4nTt3ZtKkSZ6piaT4+JmZ+ToIERERKRke5mEO2kFmp80mJyeH2NhYmjRpkm8QjZmxceNGGjVqRMWKFYmNjaVOnTqefpF5Dh48yL59+4iIiKBSpUpe+7KysggMDORf//oXjz32mNe+w4cPExcXR0RERL5zAsTHx5OQkECzZs3yrQaUlZVFdnZ2gY+ToqfkUkRERDwe5mEOcpD5zD//wZcoLS2NihUrsmTJEu68884iL0+Kh/pcioiISLHZuXMnI0aMID4+nr1793L99dfTvn17X4clLlJyKSIiIsUmOTmZhQsXctNNN/HWW2/x5ZdfevW5lNJPA3pERESk2Nxwww2eydLl8qSWSxERERFxjZJLEREREXGNkksRERERcY2SSxERERFxjZJLEREREXGNkksRERERcY2SSxERERFxjZJLEREREXGN1hYXEREpo77kSz7iI69tP/AD6aTTlrZe27vRjf70L87wpJRScikiIlJGbWUrEUQU6tglLOFO7iziiORyoORSRESkDLuO69jEJoyzpwM1qckBDlCOcsUYmZRW6nMpIiJShg1gwDmTxgACznuMyOnUcikiIlKG7WUv9al/zpbLH/mRm7ipGKOS0kwtlyIiImVYXerSilb4nyUlqE99JZZyQZRcioiIlHH96Y8ffvm2BxLIIAYVf0BSqumyuIiISBl3lKOEE0422fn2bWZzoUeUi4BaLkVERMq8alTjbu72GrTjhx/XcZ0SS7lgSi5FRESEfvTzGtRTnvIMZKAPI5LSSpfFRUREhBRSqEEN0kkHnJbLOOKoQx0fRyaljVouRUREhEpUohvdCCAAf/xpRSsllnJRlFyKiIgIAH3pSzbZ+OGndcTloumyuIiIiACQSSY1qEEqqRziENWp7uuQpBQq7+sARERE3JZEUoHT6sj5/ZbfcpCD+OHHUY76OpxSpxzlqEIVX4fhU2q5FBGRy86t3MpqVvs6DCmD6lKXOOJ8HYZPqeVSREQuSz3pyeM87uswSp1ccskiiyCCfB1KqTOLWSxgga/D8DkllyIiclmqRz3u4R5fhyFlyM/8rOQSjRYXERERERcpuRQRERER1yi5FBERERHXKLkUEREREdcouRQRERER1yi5FBERERHXKLkUEREREdcouRQRERER1yi5FBERERHXKLkUEREREdcouRQRERER1yi5FBERERHXKLkUEREREdcouRQRERER1yi5FBERERHXlPd1ACIiIr6UkJDAokWLPPc7dOhAeHi41zEZGRnMmTOHnJwcAPz9/enUqRPVqlUr1ljPJTs7m88++4x//vOfdOvWjSeeeCLfMfv372fWrFnExsZSvXp12rdvT6tWrYiLiyMnJ4dmzZr5IHJ3HTt2jNatWzN27FgGDhzo63DKJLVciohImVazZk06duzI8uXL6d+/P927dycjI8PrmKCgIDp37kxMTAz//Oc/ueOOOwqdWJ55rqKyb98+4uPj+d///kdWVla+/S+//DK33XYbGRkZDB48mCeeeIKsrCw6d+5M27Zt2b59e7HEWdTKly9P9erVqVy5sq9DKbOUXIqISJlXq1Yt3nvvPZo2bcqqVasYMmRIvmOqVq1Kx44dueuuu6hTp06hzz1u3Dhyc3PdDLdADRo0oE+fPgXu+/vf/8748eOZMWMGY8eO5YYbbqB69erce++9LFy4kIYNG3Ls2LEij7E4hISEsHz5cnr06OHrUMosJZciIiInVapUiVatWhEdHc3f//73fPsDAwMvqEVsw4YNvPvuu26GeE7ly+fv7TZ9+nRGjhzJiy++SOvWrfPtr1ChAm+++SZHjx4tjhClDFCfSxERkdPMmTOHm2++mdGjRxMZGck999xzzuNjY2OZP38+x48f55ZbbqFz584ArFixgj59+pCSksKMGTMICAggNzeX3NxcAgIC6NmzJwCzZ88mKyuL4OBgunfvDsDOnTuJjo5mwoQJLFiwgM2bNzNy5EgCAgLOWh6An59fvvgmTpwIQJcuXc76HG6++WbMzHM/IyODZcuWsWzZMq688ko6depEo0aNPPt37NhBdHQ0L7zwAjt37uTjjz+mVq1aDBo0iICAAObNm0dSUpInpvvuu4+goCDWrl3Ltm3bAOjatSuhoaEkJSUxc+ZMtmzZQsOGDRk0aJAngT/X6/Dtt9+yYMEC6tati7+/P4MHDwYgPT2dWbNmER4eTseOHV17TnIBTERE5DJzi91io2zUBT/uxhtvNDOzH3/80YKDg61atWq2Y8cOz/6PP/7Y/vrXv3rujxgxwtq2bWuHDx+2xYsXm5+fn2f/8uXLrW/fvgbYl19+aYsWLbKkpCRr3bq1hYaGes4RHx9v1113ndWuXdvMzKZMmWK1a9c2wKKjoy0qKsoAW7FixTnLMzNLTEw0wCZNmmRmZrGxsQZY+fLlLSMjo1CvQVpamrVv395mzJhhx44dszfffNNCQkLsk08+MTOz6OhoCw8PN8A+//xzu//++61r164G2LPPPmtmZgcOHLCbbrrJAPv22289587NzbUuXbrY9OnTzcxs+/bt1q1bN1u0aJH9/PPPFhkZaY0aNbJjx46d83UYM2aMTZ061VJSUmz69OlWuXJlMzPbsmWLde/e3QD729/+5upzKoxJNsnqWt1CH3+5UnIpIiKXnUtNLs3Mpk2bZoA1b97ckpKSzCx/clmlShWbOHGi536zZs3stttu89x//vnnDbDc3FzPtuHDh3sll2Zmjz76qCe5NDMbN26cJ6kyM9u6davl5uaet7wzk8uYmBgD7Nprry30a9CnTx976KGHvLb17NnTgoODbe/evWZmNmbMGAPss88+8xxz5513WpMmTTz388qeOnWqZ1tGRobdf//9nvsdOnSwTz/91HN/wYIFXgldQa9DRkaGVa9e3bZt2+Z53BNPPOH5ff/+/fmSS7ee0/kouXSoz6WIiEgBevfuzdNPP82mTZvo16+f12XjPPPmzWPo0KEArF69GjMjLS3tnOf198//0XvmtuDgYE8MAE2bNsXPz++CyyuoD+a5pKamMmvWLKKiory2Dx06lLS0NCZPngw4fVPB+1J7ZGQk+/bt89y/5557iIiI8OpzOmfOHHr16gXAgQMHiImJYeXKlTzzzDM888wzzJs3j5YtW5KamnrW1yEwMJCQkBDuueceFixYADiDpvKc2SfWzeckhaM+lyIiImfx0ksvsXHjRj7//HOee+45rr/+eq/9rVu35tNPP2XOnDnce++9NGjQgP37919yuQX1nbyY8ho3bgw4/ULT0tI8ydrZrFy5kqysrHxJad558qYrKihBrlSpEtnZ2V7bhg8fzrBhw1i/fj3XX389n376Kf/5z388MQGMGTOGGjVqFBjP2V6Ht956i/79+9OlSxfPAKyaNWsWGJvbz0nOTy2XIiIiZ+Hv78/UqVOJiIhg4sSJzJo1y2v/mDFj+Pe//837779Pv379CAoKKtJ4LrS8q666iubNm5OTk8PGjRvPeayZeSaJX7lypde+vOSvSZMmFxTvgAEDCA0N5a233mLLli00btyYwMBAAM/PtWvX5nvciRMnznnerl27smPHDp588knWrFlDy5Yt2bJlS4HHuv2c5PyUXIqIiJxDaGgon3/+OWFhYV7J5Zo1a5g0aRLDhg2jQoUKnu0FXT7PS3DyznfmxOqnJ3ZncyHlne75558HnMQ0MzOzwGMSEhKYPHkyUVFRBAUFsWLFinz7Adq2bXvOss5UuXJlBg4cyNSpU5k0aZJnRDc4l7jLlSvH+PHjveJKSEhg6tSpZz1nSkoK77//PtWqVeP111/n66+/Jjk5menTpxd4vNvPSc5PyaWIiMhJ+/fv9/T3O90111zDxx9/TLly5TzbKlasCMDcuXPJzs7mq6++Yt26dRw7dozY2Fh2797tuVS7Zs0ali9fTnp6OvXr1ycjI4OYmBjMjJkzZ7Jy5UoSExNJTEwkJyfHs8LOkSNHLqi85ORkwEnA8vTo0YOJEyeybNkyHnvsMa99AHFxcfz1r3+lf//+1KpVixEjRrB7926WLl3qOWbu3Ln06tWLdu3aAXjmxDy9v2d2djZZWVn5Eudhw4aRlpbGkSNHqFevnmd7WFgYQ4YMYdWqVbRr145p06YRHR1N3759PX0sC3odcnNzGT9+POnp6QC0atWKxo0be17rM1+DonhOch6+G0skIiJSNC50tPjatWvt0UcfNcB69eplMTExBR7397//3Wu0eP/+/c3f39/Cw8Pt3XfftYkTJ5q/v7+NHj3azMx27dpl4eHhFhYWZh988IGZmaWkpFhkZKQBFh4eblOmTLHBgwdbWFiYjR492t577z1r2rSpJ5Z169YVqrz4+HgbOnSoAdasWTObO3euV+yzZ8+2yMhICw4Otnbt2tmwYcPsscceswkTJnhNU5STk2OjRo2ymjVr2tixY23gwIH2wAMPWFpampmZzZ071xo0aGCAPfHEE7Zr1y6bMWOGXX311QbYU089ZYcOHfIqu2PHjrZw4cJ8r2dKSooNGDDAAAMsNDTUM3p89uzZBb4OSUlJFhwcbNddd5298cYbNmHCBHvooYcsMzPT4uLivF6DBQsWFNlzKohGizv8zM7Tni4iIlLK3MqttKENr/Kq6+c+fPiw1wCUhIQEqlat6plo+9ixY4SFhXn2Z2VlkZ2d7TWYxszYuHEjjRo1omLFisTGxlKnTp3zDrgpTHnnk5KSwoYNG7jmmmvOOpAGnBa8rVu3EhER4XUZ/mLs3buXOnXqnHWAzuHDh4mLiyMiIuK8r4GdHCGfk5NDbGwsTZo0KfSqSW4+p4L8H//HG7xBHHGun7s0UXIpIiKXnaJMLkXORsmlQ30uRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDXlfR2AiIhIUUgnnaMc9XUYUoakkebrEEoEPzMzXwchIiLiplu5ldWs9nUYUgbVpS5xxPk6DJ9Sy6WIiFx23uItEkn0dRil0v/xfxzjGC/xkq9DKZUqUMHXIficWi5FRETE42Ee5iAHmc98X4cipZQG9IiIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIMEnUawAAIABJREFUiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiIiIhrlFyKiIiIiGuUXIqIiIiIa5RcioiISJHKyMjwdQhSjJRcioiISJEaN24cubm5vg5DiomSSxERESkyGzZs4N133/V1GFKMyvs6ABERESmZMjIyWLZsGcuWLePKK6+kU6dONGrUCICZM2eSm5tLQEAAPXv2BGD27NlkZWURHBxM9+7dWbFiBX369CElJYUZM2YQEBBAr169AEhPT2fWrFls2rSJVq1a0bFjR4KDgwtVNsAvv/zC5MmTefrppzl06BDR0dGEh4fTu3dvqlatys6dO5k1axaBgYE89NBDhIWFeT23pKQkZs6cyZYtW2jYsCGDBg2icuXKRf2SlglquRQREZF80tPT6dSpE8eOHeOpp57CzIiKimLOnDkAdOnShbfffptHHnnE85jWrVvz8ssvM3ToUADMjLZt2wJQpUoVqlSpAsCePXvo2LEjGRkZDB8+nDfffJPIyEjS09MLVfaMGTNo27YtL7zwAvPmzeO5555jx44djBgxgkceeYRvvvmGv/zlL2zcuJGxY8fSr18/r+cWGxtLv379qF+/PgMHDuS9996jRYsWHD9+vGhf1LLCRERERE56yB6yztbZ+vTpYw899JDXvp49e1pwcLDt3bvXzMyGDx9uoaGhXsc8+uijVrt2bc/9559/3gDLzc31bOvQoYMNHjzYc//LL780Pz8/mzNnjplZocrOO+9nn33mOeYPf/iDAfbRRx95tv3lL38xwBITE73K//TTTz33FyxYYIA9++yzhXyV5FzUcikiIiJeclJzmDVrFlFRUV7bhw4dSlpaGpMnTwbA3z9/GlHQttPt2LGDmJgYunfv7tnWtWtXDh48yH333Udqamqhys67hH3HHXd4jrnhhhsAaNOmjWfbtddeC8D+/fsBOHDgADExMaxcuZJnnnmGZ555hnnz5tGyZUtSU1PPGbsUjvpcioiIiJfjK4+TlZVF+fLeaULjxo0B2L59+0Wfe8uWLQD5+jfWqlULgJUrVxaq7Lwk1s/Pz3NMUFBQvvICAwMByMrKApxL4gBjxoyhRo0aF/085OzUcikiIiJeLMcAJ9E7XV4y1qRJk4s+d96gnUWLFuXbl5CQQE5OTpGVDaeSzbVr1+bbd+LEiUs6tziUXIqIiIiX0KhQgoKCWLFihdf2hIQEAM8gndDQ0HwTpJuZJ0E8Xd62Zs2a4e/vzxdffOF13M6dO/nxxx+JiooqVNkXq2nTppQrV47x48eTmZnpdf6pU6de0rnFoeRSREREvATWCmTEiBHs3r2bpUuXerbPnTuXXr160a5dOwDq169PRkYGMTExmBkzZ85k5cqVJCYmkpiYSE5ODjVr1gRgzZo1LF++nGrVqjFgwADWr19Pr169WLJkCW+//TbPPvssnTp1olatWoUqOzk5GYCUlBTPMXmXvtPS0jzbsrOzvY4LCwtjyJAhrFq1inbt2jFt2jSio6Pp27cvvXv3dv21LJN8PaJIRERESo680eI5OTk2atQoq1mzpo0dO9YGDhxoDzzwgKWlpXmOTUlJscjISAMsPDzcpkyZYoMHD7awsDAbPXq0HT582Hbt2mXh4eEWFhZmH3zwgZmZJSYm2n333WeAAdagQQP74YcfPOc9X9mLFy/2lDtkyBDbtm2bzZ8/326++WYDrF+/frZ+/XpbsmSJtWnTxgDr2bOnbd682RP3gAEDPOWHhoZ6jR6XS+NnZua71FZERERKkod5mIMcZD7zAacVcOvWrURERFChQoV8x5sZGzdupFGjRlSsWJHY2Fjq1KnjNSF6VlYW2dnZXtsA4uPjSUhIoFmzZgQEBOQ79/nKvlSHDx8mLi6OiIiIfLHJxVNyKSIiIh5nJpciF0p9LkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENUouRURERMQ1Si5FRERExDVKLkVERETENeV9HYCIiIj4xk/8xA/84LVtG9tIIol/8S+v7c1pTmtaF2d4UkppbXEREZEyajnLuYM7KEc5/E9ezMwlF8Drfg45zGQmD/CAz2KV0kPJpYiISBllGHWoQzzx5zwumGCOcIRggospMinN1OdSRESkjPLDj370I4CAsx4TQAA96anEUgpNyaWIiEgZ1pveZJF11v1ZZNGHPsUYkZR2uiwuIiJSxjWhCbHEFrivKlVJIIHyGgMshaSWSxERkTKuP/0LvDQeQAB96avEUi6IkksREZEyrg99yCY73/YssuhNbx9EJKWZLouLiIgIUUSxjnUYp9KCK7iC/ezHDz8fRialjVouRUREhAEMoBzlPPcDCGAgA5VYygVTy6WIiIhwgAPUoY5nEnWAdazjeq73YVRSGqnlUkRERLiCK2hDG0/rZSMaKbGUi6LkUkRERABn1Dg4l8QHMci3wUippcviIiIiAsBxjlOLWmSRxXa205jGvg5JSiFNXCUiIiKAM2H6vdxLPPFKLOWiqeVSRETkMpNy8pZMMsc5jmGkkUY66Z5jMskkhRTP/RxySCKJH/mRRBK5m7upTGWvydUrUpEggjz3gwiiIhUBJzGtRCUqn7xJ2aXkUkREpARKIIHDJ28JJHCIQ55tRzlKMsmkkMIxjnklk8c4dtFlhhGGnbz5408iiV6jxy/Emclm3v1KVKIa1ahJTWpQg1onbzWo4dnmryEhpZqSSxERkWJ0nOPEEceek7c44tjHPg5wwJNIHuYwOeR4Pa461al58lad6p5ELYwwz+9nJnEhhFCFKvjjTwABXi2K5ShHKKEXFPsJTnit5JNKKhlkYBjHOe5JeAtKeo9z3HP/CEe8nuvpE7f740+Nk7ea1KQ2tbmKq6h/8lbv5K061S/yf0CKmpJLERERF6WRxraTt1/4hbiTt7zfk0jyHFuDGtSjHnWpyxVc4Ukea1CDcMK97l+u63vnkutJMs9soU0ggQMcYB/7iCOOQxzyPK4SlfIlnA1oQNOTN12a9x0llyIiIhfhIAfZwha2sY2tJ2/b2MYe9mAY5SlPHepQj3qeJKgudb0Sobz+ilI46aR7Wnvzbqff38teMskEoC51PYlmBBE0pSnXci11qOPjZ3H5U3IpIiJyDhlksIENrGUta1jDOtaxjW0c5zgAVajiSWCu5VrP741o5DUYRopeNtnsZrdXsr+FLWxlK0c5CkAIITSlKddzPTdxEzdyIzdwA8EE+zj6y4eSSxERkZPSSGM961nDGtaevG1kI1lkEUIILWhBFFFeLWFXcIWvw5ZCSCDBq6X5p5O34xynPOW5lms9yeaN3EgLWujS+kVScikiIv+/vXsPq6rO9zj+5i4qpHnB0NJERYgxSW1SwEumOV46jkIlaGpnctRQ08pMx7zUnGzOlJnVNDkzYg2IiamJ8iiOiYpl5QVsQEXxsr2CiKiwhc3me/5Q9mEPmoAbNuD3tR4f97r+PvsHz8N3r7V/a92zznKWHexgJzvZxS7SSKOYYu7jPgIJtCo2OtFJRzHXM4KQSablw0Tp/5e4hCOO+OJLEEH0vjm1pa29I9cJWlwqpZS6ZxznODvYQRJJ7GQnRzmKM850oxvBBNODHjzGY3SgAw442DuuspMTnGAve/mJn9jJTn7kR4oo4iEeog996E1vQgjBF197R62VtLhUSilVb2WTTQIJbGELSSRxmtM0oAGP87ilQOhFL738qX6RESN72MOOm9P3fE8++bSiFSGEMJCBDGYw3njbO2qtoMWlUkqpeiWFFDaykXji2cMeXHAhhBD63Jx60IMGNLB3TFWHmTBZzmomkcR2tmPEyGM8xhCGMJShdKPbPfs1Ci0ulVJK1WlGjGxjG/HEs5GNGDDQilYMuTkNYICemVTVqvR3cOPN6RSn8MLL6nfQAw97x6wxWlwqpZSqc0ooYTe7+ZIvWclKrnIVf/wZxjCGMpRe9Lpnzxop+8skkw1sIJ54kkjCCSee4ile4AX+i//CFVd7R6xWWlwqpZSqM37gB2KIYRWrOM95nuAJIohgJCP1lkCqVrrIRdaxjmii2cEOmtCEMMKIIIJgguvlwDEtLpVSStVqJzlJFFHEEMMRjuCLL+GEE0EEPvjYO55SFWbAwEpWEk00qaTSlraEE844xtGJTvaOZzNaXCqllKqVdrGLJSxhHetoTnOe53nCCacHPewdTam7dpCDRBNNDDGc4Qy/4TdMYxpP8VSdP5upxaVSSqlao4gi1rOexSzmO76jG92YylRGMUofpajqpRJK2MY2lrCEjWykAx14mZf5Hb+jEY3sHa9KtLhUSilldznk8DEf8xmfkUMOoYQyjWn8ml/bO5pSNSaFFD7iI2KIoSENeYmXmMrUOnf/TC0ulVJK2c0lLvEBH/ARH+GGGxOYwGQm05rW9o6mlN1kk83nfM4nfMJlLvN7fs8sZuGFl72jVYgWl0oppWqcESMf8AF/4k+44MJrvEYkkXo/SqXKuM51PudzFrGIPPKYxjTe5M1af89MLS6VUkrVGEGIJZZZzOISl5jJTF7hlVr/x1IpezJi5FM+5Y/8EVdceZu3eZEXccLJ3tFuSYtLpZRSNeIYx5jEJP7Fv4gggvd4T+9NqVQl5JLLe7zHh3yIP/4sYxnd6GbvWOXo4wuUUkpVKzNm3uVdAgggm2y+53u+4AstLJWqpKY0ZRGL2MteGtKQnvRkNrMposje0azomUullFLVxoCB0YzmB35gAQuYwQyccbZ3LCtnzpxh9erVZGRk0KxZM/r27UvPnj05deoUZrMZf39/m7eZlZVFVFQUe/bsobCwkNGjR7Nw4ULeeOMNxo4da/P2qurkyZN8/vnnREdHc+LEiQrtk5qaSmpqqtWyBx54gP79+1eq7f/soylTpvD0009X6hi2VpX+qC4llPBX/sobvEFHOhJDDL742jVTKT1zqZRSqlpsYhOP8igXucge9jCTmbWusHz33Xd54oknKCwsZMKECUybNg2TycRvfvMbQkJCOHLkiM3bLCgoYMSIEYwePZqvvvoKZ2dnRo0ahYeHB40b164BTZmZmWzfvp3Tp09XeJ8uXbrQvXt3IiMjGTNmDCJC3759K9XurfooLCyMoqK7O0NXWFh4V/tXpT+qiyOOTGIS+9iHM850oxsxxNg71g2ilFJK2dh78p44iZOMk3FSIAX2jnNLixcvFhcXF9m1a1e5dUajUX7961/LP/7xD5u3Gx0dLW3atLFqKzk52ebt2Mrrr78uTk5Old6vW7du4uDgIGazudL7Vlcfvfrqq1XKU1ZV+6M6FUmRzJAZ4iAOMktmiVnu7j3eLT1zqZRSymZKKGEiE5nNbP6X/2U5y3HH3d6xylm5ciXTp0/n7bffJigoqNz6Bg0asHTpUi5dumTztvfv30+DBg2s2urVq5fN27EVF5eqPRmpQYMGODk54ehY+VKjOvro4MGDfPbZZ3d1DKh6f1QnF1x4n/dZznIWs5hRjMKEyW55atf1CaWUUnWWGTMv8iKrWMXXfM0zPGPvSLf1zjvvADB48ODbbtOjRw+kzLCEwsJCkpKSSEpKwtvbm0GDBuHj42NZf/ToUaKioli4cCHHjh3jq6++omXLlowbNw4XFxfOnTvH9u3bSU5OJj8/n5UrVwIwatQorl+/zurVq/Hy8mLgwIEAHDt2jKioKObPn09CQgJpaWlMnz6dM2fOsHz5cmbNmsWFCxeIiorCy8uLUaNG0aRJE44dO8bq1atxdXVl/PjxNG3a1Op9XblyhVWrVpGenk779u0ZN26c1eV4k8nE2rVr2b9/P3379qWkpOTuO9wGfVSR7KX9+O9//5uePXsycOBA3N3dSU5OJjw8nPz8fGJjY3FxcSEsLMzu/WFrYxlLO9oxjGGMZCSrWY0bbjUfxK7nTZVSStUbv5ffS0NpKJtls72j/KKMjAwBxNnZWQoLCyu0j9FolL59+0psbKzk5ubK0qVLxcPDQ9asWSMiIlFRUeLl5SWAfPPNNzJixAgZMmSIADJ37lwREcnKypL169dLcHCwtG7dWtavXy/r16+X9PR0GT58uADy3nvviYjIihUrpFWrVgJIVFSUBAYGCiBTpkyRNm3aCCCrV6+WMWPGSEREhDg5OcmIESMkKSlJnn/+eYmIiBBnZ2cZPHiw1fs4cuSIDBs2TDZv3iwHDhyQgIAA8fHxkdzcXBERuXz5svTv31/mz58vOTk5smLFCnF1da3SZeCgoCBxdna2zN9NH1Uk+4kTJyQkJESWLVsmBoNB+vfvL+3btxej0Sg7d+6UiIgIASQ+Pl42b95c4/1Rk76T76SJNJFQCbXLJXItLpVSSt21d+VdcRInWS/r7R3ljhITEwWQzp07V3if8PBwGT9+vNWy0NBQcXd3F4PBICIiM2fOFMBSDImI9OvXTzp16mS133PPPSe+vr5Wy86cOWNVXIqIzJkzx1JciogcOnRISkpKZMGCBeXamTx5sgDyxRdfWJb94Q9/EEDy8vIsywYMGCBr1661zCckJFgVd5MnT5bhw4dbZRs6dKhNikuRu+ujO2UfMGCATJgwwbI+Pj5eHBwc5OuvvxYRsfRbSUlJhY9py/6oaUmSJG7iJjNkRo23rZfFlVJK3ZUd7GAOc/iQD2v1pfBSzs6V+9NXUFDA6tWref/9962WT5o0ibi4OJYvX87cuXNp1KgRYH2pPSAggD179tyxjVuNEnd3v/Fd1dJLwr6+vlbb9u7d27Lto48+CkBwcLBlWefOnYEbt1ry9PTk3LlzJCYm0rVrV0uma9eu0b17dwoKCsjKymLZsmUsWbLEKkeXLl1ISEi443uoiKr20Z2yHz16lMTERDZt2mTZZ8iQIZw/f56WLVtW6Zg10R/VqTe9+Qf/IIIIgghiBCNqrG0tLpVSSlVZHnmMYQzP8AxTmGLvOBXSsWNHADIyMjAajZYi7nZ2796NyWQqV5SWHqf0dkW3GrjSqFEjiouL75jpVvs6ODj84rZl17u5lf9enaurK3DjO4Nw4/0CzJw5k+bNm5fbPjExEZPJRKtWrSqUoyqq2kd3yr5hwwagfJF+u8KyIsesif6obuGEs53tTGACT/AE3njXSLs6WlwppVSV/Q//Qz75LGOZvaNUWOvWrXnkkUcwm838/PPPv7itiGA2m4EbRWZZpQVJp06dqieojZUWm/v27Su37urVq1y9ehW4cUavtrlT9tIPCJs3by63Pjs7u0rHrM39URmLWYwnnsxhTo21qcWlUkqpKjFg4CM+4i3eojnlz/zUZgsWLABunLW63Y25s7OzWb58OYGBgbi5uZGcnFxuPUBISEj1hrURX19fnJycmDdvntV7zs7OJjo62nIZ/VaXfO09QvpO2f39/XF0dGTDhg2WDwNwY8T9Tz/9ZHWs0vV1uT8qoxGN+CN/5Au+4CAHa6RNLS6VUkpVyed8zv3cz0Qm2jtKpY0cOZJ33nmHpKQkXnrpJfLz863Wnzp1ikWLFjFmzBhatmzJlClTOH78ON9++61lm3Xr1hEWFkafPn0ALPfENBqNlm2Ki4sxmUxWT4bJzc0lLy/Pqr1r164BWOUovZydk5NT4W3/s+2y2zVt2pSJEyfy/fff06dPH2JiYoiKiiIiIoJRo0bh7+/PoEGDiI+PJyoqCoCioiIOHDiAiGAwGCp0ib/U1atXKS4utuS9mz66U3Zvb29eeOEFUlNTCQsLY9u2bXzyySfMnTuXQYMGAdCiRQsA9u7dy86dO3F3d6/R/rCn53keP/z4mI9rpsEaH0KklFKqzjOLWVpLa5kts+0d5a7ExcVJQECAuLu7S58+feTll1+Wl156SebPn291myKz2SwzZsyQFi1ayBtvvCFjx46VZ599VoxGo4iIrFu3Ttq1ayeATJs2TTIzMyU2NlYefvhhAeT111+X9PR0+eCDD8TNzc2y3fbt2+XUqVMyadIkAcTf318SEhIkLi5OfH19BZCwsDBJSUkREZEtW7ZIQECAADJx4kQ5fPiwbNq0SXr06CGAjB49WlJTU2Xbtm0SHBwsgISGhkpaWpqIiOTn58sLL7wggADi6elpNVr6/PnzEhISIoB06tRJnnnmGRk9erQ0btxYIiMj5fTp03fs05SUFImMjBRHR0cBJCIiQrZs2XJXfVSR7Hl5efLb3/7Wsr5du3by448/WtZnZmaKl5eXNG3aVP72t7/VWH/UFh/Kh+IhHnJNrlV7Ww4iZe4Qq5RSSlVAKqk8yqPsZz9d6WrvOHctPz+fgwcP0qFDh1sO7ihlNBo5dOgQfn5+Vk+QqWsuXrzIqVOn8PPzu+WApmPHjmE2m+nYsSMnTpygWbNmeHp62iFpeXfKfvbsWbKzs/H39y/3NB2TyURxcXG5/epyf1TUWc7SmtZsYQsDGFCtbWlxqZRSqtL+wl+YxSwucQknnOwdRylVAT74MIYxzGd+tbaj37lUSilVacc5ji++WlgqVYf44cdxjld7O3qfS6WUUpWWQw73c7+9Y6gaZDAYGD9+/B23Gzt2LGPGjKmBRKqyWtCCC1yo9na0uFRKKVVpTjhhxnznDVW90aZNGzZu3HjH7Sr7BCRVc4opxgWXO294l/Q3QCmlVKU1pzk/8qO9Y6ga5ODgcMsnAam6I5vsGnlKj37nUimlVKX54ks66RRSeOeNlVK1Qiqp+OFX7e1ocamUUqrSggiikEI9e6lUHZFBBuc4Ry96VXtbWlwqpZSqtA50wB9/YoixdxSlVAVEE00rWvE4j1d7W1pcKqWUqpL/5r+JIYY88u688T0sIyPD8vjAe93JkyeZM2cO7dq1s9kxvv32W/bs2WObgPVUEUX8nb8zlrE1MqBHi0ullFJV8iIv4owz7/GevaPUWl9//TUfffSR3prnpszMTLZv387p06dtdox+/fqRlpbGokWLbBWz3vmUT8khh0gia6Q9LS6VUkpVSROa8Af+wId8SAYZ9o5T66SmprJ48WKWLl2Kk5PebB5uFIJBQUE2P8b48eM5fPgwW7Zsuatj10fnOc87vMMrvEIb2tRIm1pcKqWUqrKXeRl//IkgAhMme8epNcxmMyNHjiQiIsLeUWqd/3zet62O8fbbbzNx4kTy8/Pv+vj1hSCMZSxNacpsZtdYu3qfS6WUUlXmggvRRNONbkxnOh/zsb0j1Qrr16/nzJkzhIeHW5atWrWKkpISXFxcCA0NBSAuLg6TyYS7uzvDhw8H4OjRo0RFRbFw4UKOHTvGV199RcuWLRk3bpxVUVVQUMCXX35JVlYWfn5+9O/fH09PTxwdHXFwcODYsWNERUUxf/58EhISSEtLY/r06bi4uFBYWEhSUhJJSUl4e3szaNAgfHx8qiWnyWRi7dq17N+/n759+1JSUlKuv65cucKqVatIT0+nffv2jBs3jsaNG1fqGG3atMHDw4O33nqL999/v8o/u/pkAQv4lm/ZxS4a0/jOO9iKKKWUUncpTuLEURzlz/Jne0epFfr16yddu3a1WnblyhUJCgoST09Py7KzZ8/Kr371K2nVqpWIiERFRYmXl5cA8s0338iIESNkyJAhAsjcuXMt+2VnZ4uPj4+sWLFCioqKZObMmQJIu3btJDg4WFasWCGtWrUSQKKioiQwMFAASU5OFqPRKH379pXY2FjJzc2VpUuXioeHh6xZs8bmOS9fviz9+/eX+fPnS05OjqxYsUJcXV3FycnJss2RI0dk2LBhsnnzZjlw4IAEBASIj4+P5ObmVvgYpSZOnCht27at6o+tXomSKHEQB/lcPq/xtrW4VEopZROLZbE4iIMslaX2jmJXJSUl0qBBAxk8eHC5dZGRkVZFm4jI7373O0vRJiKWQnH9+vWWZf369ZNOnTpZ5l955RXx9PQUk8kkIiIGg0EAmT17tmWbOXPmWIpLEZFDhw5JSUmJhIeHy/jx460yhIaGiru7uxgMBpvmnDx5sgwfPtzqOEOHDrUqDAcMGCBr1661zCckJFgVqRU5Rql58+YJIDk5OeXW3UuiJVqcxVlmy+w7b1wN9DuXSimlbOIVXmERi5jKVBZx747cPXfuHNevX8fbu/xj9hwdy//Z/c9ljRo1AmDw4MGWZQEBAVYjrDMyMiyXv+HGJeEOHTqwa9cuyzbu7u4AjBo1CgBfX1+MRiOrV68mMDDQqs1JkyZhNBpZvny5zXJmZWWxbNkyBg4caLVfly5dLK/PnTtHYmIiu3fv5s033+TNN99k48aNdO/enYKCggodo6yWLVsCcODAgVuuvxcsYxljGMN0pvMO79glg37nUimllM3MZCYNacg0ppFBBn/hL7jiau9YNerChQsAeHp6Vmn/WxV2jRo1ori42DIfHBzMxo0b+eGHH+jZsyeFhYWcPXuWoUOHWrYpLTzL2r17NyaTCWdn6z//HTt2BODIkSM2y5mSkoLJZKJVq1ZW25TNlZFx4y4DM2fOpHnz5uWOl5iYeMdjlFV6jMOHD/Pkk09W+L3UB2bMzGIW7/M+85nPW7xltyx65lIppZRNRRLJetYTRxxP8iQGDPaOVKM6dOiAg4MDOTk51dbG9OnTCQ0NZebMmWzdupXXXnuNXr16sXDhwl/cz2w2AzeKzLJKi7JOnTrZLOPVq1eBG2cnb8fV9cYHj3379t1y/4oco6zSkeJeXl6VylrXZZPNMIbxMR/zJV/atbAELS6VUkpVg6EM5Tu+4xKX6EpX1rDG3pFqjIeHBz4+PmRlZZVb5+npSWFhodUyEbEUfRXl4OCAt7c3ixeTL08dAAAJiUlEQVQvpqSkhJdffpnExEQ8PDx+cb/AwEDc3NxITk62Wp6dnQ1ASEiIzXJ27twZgISEhHLrSkd7+/r64uTkxLx58ygqKrLKEx0dXaFjlHX27FkAHn744QrnrOsSSeRRHiWNNJJIIgL73/5Ki0ullFLVwh9/fuInwggjlFDGMIZssu0dq0YEBgbesrhs27YthYWFJCYmIiKsWrWK3bt3k5eXR15eHmazmUuXLgFgNBot+xUXF2MymSwF35/+9CeSkpIwGAy4uLiQl5dHWlqa1aVzk+nGfUfLnkFt2bIlU6ZM4fjx43z77beW5evWrSMsLIw+ffrYLKe/vz+DBg0iPj7e8vjLoqIiDhw4gIhgMBjw8PBg4sSJfP/99/Tp04eYmBiioqKIiIhg1KhRFTpG2fd89uxZmjRpYilK67M88pjMZJ7maXrTmwMcqJHnhleIXYYRKaWUuqd8I99IG2kjzaSZLJflUiIl9o5UrWJiYsTNzU2uXbtmtTw/P18CAgIEEC8vL1mxYoVMmDBBmjZtKq+99pr8/e9/l3bt2gkg06ZNk8zMTImNjZWHH35YAHn99dflwoULsmHDBmnQoIEAVv8eeugh2bJli8TFxYmvr68AEhYWJikpKZYMZrNZZsyYIS1atJA33nhDxo4dK88++6wYjUab5zx//ryEhIQIIJ06dZJnnnlGRo8eLY0bN5bIyEg5ffq05OfnywsvvGB5D56enlajxytyjFI9e/aUGTNmVONPtnaIkzjxFm9pIS0kWqLtHaccBxERO9S0Siml7jFXucoc5vApn9KNbnzABwRxd48CrM0GDx7MpEmTGDZsmNVyEeHnn3/Gx8eHhg0bkpGRQZs2bSyjuysiLi6O4uJiBgwYQE5ODvn5+eTl5fHzzz+zZs0aq7OSt2M0Gjl06BB+fn40aNCg3Hpb5Cx17NgxzGYzHTt25MSJEzRr1qzcgKeLFy9y6tQp/Pz8btnGnY6Rnp5OYGAgaWlptG/fvtIZ64L97OdVXmU72xnLWP7Mn2lGM3vHKkeLS6WUUjUqhRRe5VW2sY1QQlnAAvzws3csmzMYDIwbN47ExMRbjqyuqqNHjxIUFMSZM2fKjfrOysritdde44svvrBZe3XFjBkzCAgI4MUXX7R3FJvLJJOFLORLvuRxHucDPqAnPe0d67b0O5dKKaVq1KM8yla2sp71pJNOAAFEEMFhDts7mk09+OCDREZGsmiRbe/5aTAYyMrKYsyYMezYsQODwYDBYGDr1q1MnTqVefPm2bS9uiA2NhZ3d/d6V1ie5CQv8RKd6UwyyUQTzW521+rCEvTMpVJKKTsShHjieYu3SCWVJ3mSqUxlKENx4Nb3Mqxrjh8/zr59+xg5cqTNjrllyxbi4+PZunUrx48fp2PHjjz99NPMnTu3yvfXrKt27txJQUEBTz/9tL2j2Mxe9rKEJcQSizfezGY2L/IiznXk9uRaXCqllLK7EkpYxzqWsIQd7CCAAKYyldGMxp3Kf8fvXiIit72puKo7iijiK75iCUv4iZ/oQQ+mMpXneA4XXOwdr1K0uFRKKVWr7Gc/H/ERK1lJYxozgQlMYhIP8qC9oyllcxe4wF/5K5/xGdlkM4IRTGMavehl72hVpsWlUkqpWimLLJaznE/4hDOcoSc9CSOM0YyulSNklaqo61wnkUS+5EvWsY6GNGQsY3mVV3mIh+wd765pcamUUqpWK6KIjWzkn/yTTWwCYBjDGM1oBjHonnt2uaqbzJjZylaiiWYtaymkkIEMJIIIhjO8Xn39Q4tLpZRSdcZlLrOGNfyTf7KDHTShCc/yLKGE0pvede67aap+M2PmO75jDWuIJZbznKcnPQknnOd4jha0sHfEaqHFpVJKqTrJgIGVrCSaaFJJxRNPBjKQwTcnL7zsHVHdgy5xic1sJp54NrOZHHLwxZdwwokgAh987B2x2mlxqZRSqs47wQm2sIWtbCWBBK5xDX/8GcYwhjKUXvTCUW/trKpJJplsYAPxxJNEEiWU8ARPMIxhPMVTdKObvSPWKC0ulVJK1Sv55PMv/sVGNrKJTZzmNF540Yc+hBBCH/rwCI9osamqLJ10drKTHewgiSROc5qWtGQwgxnCEAYyEE/urfuNlqXFpVJKqXpLEA5wgC1sYefN6QpXuJ/7CSbYUnAGElhnblCtalYJJRzkIEkkWQrKLLJoRCN60Yve9GYgA+lOd/3AcpMWl0oppe4ZZsykkMKOm9NOdnKRi3jgQS960Z3uPMZjdKMbbWlr77jKDs5whn3sY+/NKZlkcsmlCU0IJpje9CaEELrTXT+Q3IYWl0oppe5ZgpBGGjvYQTLJ7GUvRzhCCSU0o5ml0Hzs5nQvDMa4l5zkJPtuTnvZyz72cYELOOBAe9rTjW4EEURvetOFLnpmsoK0uFRKKaXKuMpVDnDAUnTsYx/ppGPGTBOaEEggnW9Ofvjhi2+9uPF1fXaWs6STzmEOk046hzjEfvaTQw6OONKRjlYfIh7jMe7jPnvHrrO0uFRKKaXuoIACUkhhH/tIIYVDHCKddC5yEYDGNMb35uSPv+W1Dz40pKGd098brnOd4xznEIesishDHOIKVwBoSlPLh4IudOExHqMrXfHAw87p6xctLpVSSqkqyiWXTDL5N/8mjTTL68McxowZuFHQPMADeONN+5tT2fl2tNPLrRWQSy5nOcs5zpFZZipddoITlFACwAM8wCM8Qnva44+/5fXDPIwDDnZ+J/WfFpdKKaWUjRVSSAYZnOAEJznJqTLTCU5wnvOWQsgNNx7iIbzwojnN8cKLlrSk+c2p7HwLWtSbQSRmzFzkItlkc5GLnOe85XU22ZznvOX1SU5ixAiAAw60ohUP/cfUjna0pS0d6ahni+1Mi0ullFKqhpkwcZrTnOIUJ29OZYusskVXMcVW+zajGfdxH01pSqObU2Ma04QmlnkPPLiP+yzzZe+56IILjWl823lXXHHAgUIKLcsKKPjF+atcJf/mdJnLXOOaZT6XXMvra1zjMpe5whUuchHh/0sQRxxpQQtLEd3y5tSc5rSlraWIfJAHccPNNj8IVS20uFRKKaVqsYs3p7LF5xWuWBVxpUVb6euy82WLwOpUWqTequhtTGOreQ88yp2RbU5zvWRdT2hxqZRSStVjJkxc45pl/jrXLZeYbzdfQonVpWU33H5xvhGNcMW1ut6CqmO0uFRKKaWUUjajw9OUUkoppZTNaHGplFJKKaVsxhnItXcIpZRSSilVP/wfmILTl+4QEooAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "TemplateModelDelta.for_jupyter(tm_covid_subset_comparison_copy.template_models[2],\n",
+    "                               tm_covid_subset_comparison_copy.template_models[5],\n",
+    "                               rc.is_ontological_child,\n",
+    "                               args=\"-Grankdir=TB\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "19ba61d4-b7a9-4709-8d60-ff0fdd9f5091",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The similarity score between models 2 and 5 when grounded is 0.625. The similarity score between the models when ungrounded is 0.25.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"The similarity score between models 2 and 5 when grounded is {grounded_scores[11]['score']}. \"\n",
+    "      f\"The similarity score between the models when ungrounded is \"\n",
+    "      f\"{list_of_both_subset[11]['Similarity Score without Grounding']}.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a8187a5c",
+   "metadata": {},
+   "source": [
+    "## Summary statistics of score changes for the 6 initial models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "16c8f7ca-d135-4974-88a8-5d452e43e83b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Out of 15 pairs of models, 12 pairs of models have reduced similarity scores with groundings removed. 0 pairs of models have increased similarity scores without groundings. 3 pairs of models have the same similarity scores with groundings removed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "lower_count = 0 \n",
+    "higher_count = 0\n",
+    "same_count = 0\n",
+    "for model_comparison in list_of_both_subset:\n",
+    "    if (model_comparison['Similarity Score without Grounding'] < \n",
+    "            model_comparison['Similarity Score with Grounding']):\n",
+    "        lower_count += 1\n",
+    "    elif (model_comparison['Similarity Score without Grounding'] > \n",
+    "              model_comparison['Similarity Score with Grounding']):\n",
+    "        higher_count += 1\n",
+    "    elif (model_comparison['Similarity Score without Grounding'] == \n",
+    "              model_comparison['Similarity Score with Grounding']):\n",
+    "        same_count += 1\n",
+    "        \n",
+    "print(f\"Out of {len(list_of_both_subset)} pairs of models, {lower_count} pairs of models have \"\n",
+    "      f\"reduced similarity scores with groundings removed. {higher_count} pairs of models have \"\n",
+    "      f\"increased similarity scores without groundings. {same_count} pairs of models have the \"\n",
+    "      f\"same similarity scores with groundings removed.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81463d12-b776-439f-9a86-7acc9e073135",
+   "metadata": {},
+   "source": [
+    "## Statistics of score changes over all COVID-19 models\n",
+    "\n",
+    "We now expand the analysis to compute pairwise similarity scores between 24 of the COVID-19 models in the BioModels database. \n",
+    "\n",
+    "The entire database of models can be found [here](https://www.ebi.ac.uk/biomodels/search?query=submitter_keywords:COVID-19&domain=biomodels). \n",
+    "\n",
+    "The comparison table is too long to present so we calculate summary statistics of the differences with and without grounding between the similarity scores."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f3456e7a-ed18-4c88-8df6-cb218a126e4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ALL_MODEL_LIST = [\"BIOMD0000000955\", \"BIOMD0000000956\", \"BIOMD0000000957\", \"BIOMD0000000958\",\n",
+    "                  \"BIOMD0000000960\", \"BIOMD0000000962\", \"BIOMD0000000963\", \"BIOMD0000000964\",\n",
+    "                  \"BIOMD0000000969\", \"BIOMD0000000970\", \"BIOMD0000000971\", \"BIOMD0000000972\",\n",
+    "                  \"BIOMD0000000974\", \"BIOMD0000000976\", \"BIOMD0000000977\", \"BIOMD0000000978\",\n",
+    "                  \"BIOMD0000000979\", \"BIOMD0000000980\", \"BIOMD0000000981\", \"BIOMD0000000982\",\n",
+    "                  \"BIOMD0000000983\", \"BIOMD0000000984\", \"BIOMD0000000988\", \"BIOMD0000000991\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "9f8ba516-0fda-45d4-81c8-81c080970a13",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tm_covid_all_grounding_list = []\n",
+    "for covid_model in ALL_MODEL_LIST:\n",
+    "    tm_covid_all_grounding_list.append(biomodels.get_template_model(covid_model))\n",
+    "\n",
+    "model_id_all_name_mapping = {id:tm.annotations.name.split(' ')[0]\n",
+    "                             for id,tm in enumerate(tm_covid_all_grounding_list)}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ad1d2fba-ee22-4e2f-b936-6d126491d2ad",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Comparing model templates: 22791it [00:00, 109978.70it/s]\n",
+      "Comparing model concepts: 14196it [00:00, 206874.97it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Comparing 276 pairs of models took 0.45 seconds\n"
+     ]
+    }
+   ],
+   "source": [
+    "ts = time.time()\n",
+    "tm_covid_all_comparison = TemplateModelComparison(tm_covid_all_grounding_list,\n",
+    "                                                  refinement_func=rc.is_ontological_child)\n",
+    "all_grounded_scores = tm_covid_all_comparison.model_comparison.get_similarity_scores()\n",
+    "te = time.time()\n",
+    "print(f\"Comparing {len(all_grounded_scores)} pairs of models took {round(te-ts, 2)} seconds\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "859bcd00-53e9-45ce-a8a4-4593c3afe472",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tm_covid_all_no_grounding_list = [] \n",
+    "for tm in tm_covid_all_grounding_list:\n",
+    "    copied_tm = deepcopy(tm)\n",
+    "    for template in copied_tm.templates:\n",
+    "        for concept in template.get_concepts():\n",
+    "            concept.identifiers = {}\n",
+    "            concept.context = {}\n",
+    "    tm_covid_all_no_grounding_list.append(copied_tm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "b92f42e6-2684-475d-9774-f9bffc2544f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Comparing model templates: 22791it [00:00, 133258.77it/s]\n",
+      "Comparing model concepts: 14196it [00:00, 241374.82it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "tm_covid_all_comparison_copy = TemplateModelComparison(tm_covid_all_no_grounding_list,\n",
+    "                                                       refinement_func=rc.is_ontological_child)\n",
+    "all_ungrounded_scores = tm_covid_all_comparison_copy.model_comparison.get_similarity_scores()\n",
+    "\n",
+    "list_of_both_all = []\n",
+    "for grounded_score,ungrounded_score in zip(all_grounded_scores,all_ungrounded_scores):\n",
+    "    list_of_both_all.append({'Model1':model_id_all_name_mapping[grounded_score['models'][0]],\n",
+    "                         'Model2':model_id_all_name_mapping[grounded_score['models'][1]],\n",
+    "                         'Similarity Score with Grounding':grounded_score['score'],\n",
+    "                        'Similarity Score without Grounding':ungrounded_score['score']})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "a56b6969-25c5-4785-8da2-dd1d11ae7198",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "after_sim_lower_count = 0\n",
+    "after_sim_higher_count = 0\n",
+    "after_sim_same = 0 \n",
+    "for model_comparison in list_of_both_all:\n",
+    "    if (model_comparison['Similarity Score without Grounding'] < \n",
+    "            model_comparison['Similarity Score with Grounding']):\n",
+    "        after_sim_lower_count += 1\n",
+    "    elif (model_comparison['Similarity Score without Grounding'] > \n",
+    "              model_comparison['Similarity Score with Grounding']):\n",
+    "        after_sim_higher_count += 1\n",
+    "    elif (model_comparison['Similarity Score without Grounding'] == \n",
+    "              model_comparison['Similarity Score with Grounding']):\n",
+    "        after_sim_same += 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dece640b",
+   "metadata": {},
+   "source": [
+    "## Summary statistics of score changes\n",
+    "A summary of score decreases/increases/no change is printed below. Interestingly, we found at least one example where the score did not change but there was actually a change in the comparison graph (one equivalence missed, one falsely added without grounding, resulting in an overall unchanged score).\n",
+    "\n",
+    "These statistics clearly show that groundings play an important role since overwhelmingly we get different comparison results when removing groundings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "624d75cf-2baa-4487-a9b1-1959580cd05b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Removing groundings led to a decrease in pairwise similarity scores for 231 or 84.0% of the 276 pairwise model comparisons.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Removing groundings led to a decrease in pairwise similarity scores for \"\n",
+    "      f\"{after_sim_lower_count} or {round(after_sim_lower_count /len(list_of_both_all), 2)*100}% \"\n",
+    "      f\"of the {len(list_of_both_all)} pairwise model comparisons.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "12f6bec1-f3c0-4293-9dbb-8fe06b672a6a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Removing groundings led to an increase in pairwise similarity scores for 11 or 4.0% of the 276 pairwise model comparisons.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Removing groundings led to an increase in pairwise similarity scores for \"\n",
+    "      f\"{after_sim_higher_count} or {round(after_sim_higher_count/len(list_of_both_all), 2)*100}% \"\n",
+    "      f\"of the {len(list_of_both_all)} pairwise model comparisons.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "7d4d7098-939a-4200-b1a6-e303ada9ade1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Removing groundings led to no change in pairwise similarity scores for 34 or 12.0% of the 276 pairwise model comparisons.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Removing groundings led to no change in pairwise similarity scores for \"\n",
+    "      f\"{after_sim_same} or {round(after_sim_same/len(list_of_both_all), 2) * 100}% \"\n",
+    "      f\"of the {len(list_of_both_all)} pairwise model comparisons.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "09c95e30-9cb1-4492-a097-72eed6cc5e0f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "diffs = []\n",
+    "for model_comparison in list_of_both_all:\n",
+    "    diffs.append(model_comparison['Similarity Score with Grounding'] -\n",
+    "                 model_comparison['Similarity Score without Grounding'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "304ea6ca-32ab-41da-9497-ac0ecae4b8e8",
+   "metadata": {},
+   "source": [
+    "## Plot the distribution of score changes\n",
+    "We now show the distribution of score changes to quantify the magnitude of change as box plots summarizing the underlying distribution. The first plot shows the actual score changes, the second plot the absolute value of score changes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7f169538-631a-404c-b532-aee2ebeb6f2f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.5, 1.5)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.boxplot(diffs, showmeans=True)\n",
+    "plt.ylabel('Model comparison score difference\\n (with DKG - without DKG)')\n",
+    "plt.xlabel('COVID-19 epidemiology model pairs')\n",
+    "plt.xticks([])\n",
+    "plt.plot([-1, 2], [0, 0], 'k--')\n",
+    "plt.xlim([0.5, 1.5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "cf854bd9-1c00-4ce9-a005-88950696410d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.5, 1.5)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.boxplot([abs(d) for d in diffs], showmeans=True)\n",
+    "plt.ylabel('Model comparison score difference\\n abs(with DKG - without DKG)')\n",
+    "plt.xlabel('COVID-19 epidemiology model pairs')\n",
+    "plt.xticks([])\n",
+    "plt.xlim([0.5, 1.5])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}