{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Step 5: Analyze final Barnacle model\n", "\n", "Use this notebook to compile and analyze the final version of your Barnacle model. This should be the version of the model that is fit with the optimal parameters you identified in step 4. There are several parts of this compilation and analysis notebook:\n", "1. Align the components between bootstraps of your final model.\n", " - The order of components is not fixed in this tensor decomposition model. Therefore, in order to compare between bootstraps, the components must first be aligned to one another.\n", " - The aligned bootstraps will be saved as an xarray.DataSet so that you can access them for further analysis\n", "1. Summarize the model weights for each component.\n", " - Each component can be understood to model a different pattern in the data. Depending on how you set up your data and your Barnacle model, each pattern might also be associated with a different cluster (e.g. gene clusters). This step separates out each component so you can more closely examine the pattern and/or cluster each is modeling.\n", "1. Visualize your model.\n", " - Effective visualization depends on your data type, size, dimensions, and the questions you are asking. A few potential visualizations are suggested below to help get you started." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "import itertools\n", "import numpy as np\n", "import os\n", "import pandas as pd\n", "import seaborn as sns\n", "import tensorly as tl\n", "import tlviz\n", "import xarray as xr\n", "\n", "from barnacle.tensors import SparseCPTensor\n", "from barnacle.utils import subset_cp_tensor\n", "from functools import reduce\n", "from matplotlib import pyplot as plt\n", "from tlab.cp_tensor import load_cp_tensor\n", "from tqdm.notebook import tqdm\n", "\n", "# set color palette\n", "sns.set_palette(sns.color_palette([\n", " '#9B5DE5', '#FFAC69', '#00C9AE', '#FD3F92', '#0F0A0A', '#959AB1', '#FFDB66', '#FFB1CA', '#63B9FF', '#4F1DD7'\n", "]))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part A: Align model bootstraps" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "File outputs of this notebook will be saved here: data/barnacle/model\n" ] } ], "source": [ "# USER INPUTS -- edit these variables as needed\n", "\n", "# path to directory where the outputs from your parameter search were saved (e.g. 'directory/barnacle/fitting/')\n", "fitpath = 'data/barnacle/fitting'\n", "\n", "# path to the normalized data tensor used to fit barnacle (e.g. 'directory/data-tensor.nc')\n", "datapath = 'data/data-tensor.nc'\n", "\n", "# optimal rank parameter (number of components) used to fit your final model\n", "optimal_rank = 5\n", "\n", "# optimal lambda parameter (sparsity coefficient) used to fit your final model\n", "optimal_lambda = 1.0\n", "\n", "# number of bootstraps used for final model\n", "n_bootstraps = 100\n", "\n", "# output directory where files produced by this notebook will be saved\n", "outdir = fitpath.strip('fitting') + 'model'\n", "if not os.path.isdir(outdir):\n", " os.makedirs(outdir)\n", "print(f\"File outputs of this notebook will be saved here: {outdir}\")\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "de6d09c83e9644ccb0e1e4cb7bdbcbc0", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Extracting sample names: 0%| | 0/100 [00:00\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
reference_bootstrapreference_replicatemean_fmsmedian_fms
097C0.6447110.65551
\n", "" ], "text/plain": [ " reference_bootstrap reference_replicate mean_fms median_fms\n", "0 97 C 0.644711 0.65551" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "All model bootstraps successfully aligned.\n" ] } ], "source": [ "# align bootstraps of final model\n", "\n", "# set up parameters and data structures\n", "input_ds = xr.load_dataset(f\"{fitpath}/bootstrap0/dataset-bootstrap0.nc\")\n", "replicates = [str(l) for l in set(input_ds.replicate_id.data)]\n", "bootstraps = np.arange(n_bootstraps)\n", "samplenames = {rep: [] for rep in replicates} # sample names\n", "cps = {rep: [] for rep in replicates} # cp tensors with all samples present\n", "subset_cps = {rep: [] for rep in replicates} # cp tensors subset to just common samples\n", "\n", "# collect sample names of each bootstrap/replicate pair\n", "for boot in tqdm(bootstraps, desc='Extracting sample names'):\n", " for rep in replicates:\n", " ds = xr.open_dataset(f\"{fitpath}/bootstrap{boot}/replicate{rep}/shuffled-replicate-{rep}.nc\")\n", " samplenames[rep].append(ds.sample_id.data)\n", "# compile set of samplenames common to all bootstrap / replicate splits\n", "samplenames['common'] = reduce(np.intersect1d, itertools.chain.from_iterable([samplenames[r] for r in replicates]))\n", "\n", "# import all fitted models\n", "for boot in tqdm(bootstraps, desc='Importing model bootstraps'):\n", " for rep in replicates:\n", " # put together data path\n", " path_cp = f\"bootstrap{boot}/replicate{rep}/rank{optimal_rank}/lambda{optimal_lambda}/fitted-model.h5\"\n", " # store normalized cp tensor to cps\n", " cp = tl.cp_normalize(load_cp_tensor(f\"{fitpath}/{path_cp}\"))\n", " cps[rep].append(cp)\n", " # pull out common samplenames and store in subset_aligned_cps\n", " idx = np.where(np.isin(samplenames[rep][boot], samplenames['common']))[0]\n", " subset_cps[rep].append(subset_cp_tensor(cp, {2: idx}))\n", "print(f\"Successfully imported {len(cps[rep])} model bootstraps, each with {len(replicates)} replicates.\")\n", "\n", "# find best representative reference cp tensor\n", "results = []\n", "combos = list(itertools.product(replicates, bootstraps))\n", "for ref_rep, ref_boot in tqdm(combos, desc='Identifying best reference model from bootstraps'):\n", " # limit comparisons to a random sample of 100 bootstraps\n", " if len(combos) > 100:\n", " combos = [combos[i] for i in np.random.choice(len(combos), size=100, replace=False)]\n", " for comp_rep, comp_boot in combos:\n", " # no point in comparing to self\n", " if ref_rep == comp_rep and ref_boot == comp_boot:\n", " continue\n", " reference_cp = subset_cps[ref_rep][ref_boot]\n", " comparison_cp = subset_cps[comp_rep][comp_boot]\n", " fms = tlviz.factor_tools.factor_match_score(reference_cp, comparison_cp, consider_weights=False)\n", " results.append({\n", " 'reference_bootstrap': ref_boot, \n", " 'reference_replicate': ref_rep, \n", " 'comparison_bootstrap': comp_boot, \n", " 'comparison_replicate': comp_rep, \n", " 'fms': fms, \n", " })\n", "# summarize overall mean fms \n", "fms_df = pd.DataFrame(results)\n", "fms_summary_df = fms_df.groupby([\n", " 'reference_bootstrap', \n", " 'reference_replicate'\n", "]).agg(\n", " mean_fms=('fms', 'mean'), \n", " median_fms=('fms', 'median'), \n", ").reset_index()\n", "# find the best representative bootstrap model based on maximum mean FMS\n", "best_ref = fms_summary_df.iloc[fms_summary_df.mean_fms.idxmax(), :]\n", "print('All bootstraps will be aligned to the following reference model:')\n", "display(pd.DataFrame(best_ref).T.reset_index(drop=True))\n", "\n", "# permute reference cp so that components are in descending order of explaned variation\n", "ref_cp = tlviz.factor_tools.permute_cp_tensor(\n", " subset_cps[best_ref['reference_replicate']][best_ref['reference_bootstrap']], \n", " consider_weights=False\n", ") \n", "\n", "# realign all the other cp tensors against the best representative cp tensor\n", "for rep in replicates:\n", " for boot in bootstraps:\n", " # permute components to line up with best representative reference cp\n", " perm = tlviz.factor_tools.get_cp_permutation(subset_cps[rep][boot], reference_cp_tensor=ref_cp, consider_weights=False)\n", " cps[rep][boot] = tlviz.factor_tools.permute_cp_tensor(cps[rep][boot], permutation=perm)\n", " subset_cps[rep][boot] = tlviz.factor_tools.permute_cp_tensor(subset_cps[rep][boot], permutation=perm)\n", "print('All model bootstraps successfully aligned.')\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d458550c601f480d823dc39e122e601c", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Compiling weights from each bootstrap: 0%| | 0/100 [00:00\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset> Size: 243MB\n",
       "Dimensions:            (bootstrap: 100, replicate: 3, component: 5,\n",
       "                        KOfam: 20069, phylum: 99, sample: 11)\n",
       "Coordinates:\n",
       "  * bootstrap          (bootstrap) int64 800B 0 1 2 3 4 5 ... 94 95 96 97 98 99\n",
       "  * replicate          (replicate) object 24B 'A' 'B' 'C'\n",
       "  * component          (component) int64 40B 1 2 3 4 5\n",
       "  * KOfam              (KOfam) <U6 482kB 'K00001' 'K00002' ... 'K26180' 'K26182'\n",
       "  * phylum             (phylum) <U30 12kB 'Acidobacteriota' ... 'Xanthophyceae'\n",
       "  * sample             (sample) object 88B 'G3.UW.ALL.L25S1' ... 'G3.UW.ALL.L...\n",
       "Data variables:\n",
       "    KOfam_weights      (bootstrap, replicate, component, KOfam) float64 241MB ...\n",
       "    phylum_weights     (bootstrap, replicate, component, phylum) float64 1MB ...\n",
       "    sample_weights     (bootstrap, replicate, component, sample) float64 132kB ...\n",
       "    component_weights  (bootstrap, replicate, component) float64 12kB 160.3 ....\n",
       "    percent_variation  (bootstrap, replicate, component) float64 12kB 0.4193 ...\n",
       "    fms_component      (bootstrap, replicate, component) float64 12kB 0.6783 ...\n",
       "Attributes:\n",
       "    rank:                 5\n",
       "    lambda:               1.0\n",
       "    n_bootstraps:         100\n",
       "    align_ref_bootstrap:  97\n",
       "    align_ref_replicate:  C
" ], "text/plain": [ " Size: 243MB\n", "Dimensions: (bootstrap: 100, replicate: 3, component: 5,\n", " KOfam: 20069, phylum: 99, sample: 11)\n", "Coordinates:\n", " * bootstrap (bootstrap) int64 800B 0 1 2 3 4 5 ... 94 95 96 97 98 99\n", " * replicate (replicate) object 24B 'A' 'B' 'C'\n", " * component (component) int64 40B 1 2 3 4 5\n", " * KOfam (KOfam) " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Component weight profiles saved in output directory: data/barnacle/model\n" ] } ], "source": [ "# summarize model weights for each component, and save summaries as csv files\n", "\n", "# summarize weights across bootstraps and replicates\n", "mean_ds = ds.mean(dim=['bootstrap', 'replicate']) # mean of weights\n", "std_ds = ds.std(dim=['bootstrap', 'replicate']) # standard deviation of weights\n", "med_ds = ds.median(dim=['bootstrap', 'replicate']) # median of weights\n", "support_ds = (ds != 0).mean(dim=['bootstrap', 'replicate']) * 100 # bootstrap support (percent of weights nonzero)\n", "\n", "# plot % variation explained and FMS for each component \n", "fig, axes = plt.subplots(2, 1, figsize=(min(15, len(ds.component.data)), 10), sharex=True)\n", "sns.boxplot(ds.percent_variation.to_series().reset_index(), x='component', y='percent_variation', ax=axes[0]); \n", "axes[0].set(title='Explanatory Power of Components', xlabel='Component', ylabel='% Variation Explained'); \n", "sns.boxplot(ds.fms_component.to_series().reset_index(), x='component', y='fms_component', color=sns.color_palette()[8], ax=axes[1]); \n", "axes[1].set(title='Consistency of Components\\n(Between Bootstraps)', xlabel='Component', ylabel='FMS\\n(Relative to Alignment Reference)'); \n", "plt.show()\n", "\n", "# extract summary of weights for each component\n", "for component in ds.component.data:\n", " if not os.path.isdir(f\"{outdir}/component{component}\"):\n", " os.makedirs(f\"{outdir}/component{component}\")\n", " for i, mode in enumerate(modes):\n", " # make dataframe summarizing weights\n", " df = pd.DataFrame({\n", " 'mean_weight': mean_ds.sel(component=component)[f\"{mode}_weights\"].to_series(), \n", " 'std_weight': std_ds.sel(component=component)[f\"{mode}_weights\"].to_series(), \n", " 'median_weight': med_ds.sel(component=component)[f\"{mode}_weights\"].to_series(), \n", " 'pct_bootstraps_nonzero': support_ds.sel(component=component)[f\"{mode}_weights\"].to_series(), \n", " }).sort_values(by=['mean_weight', 'pct_bootstraps_nonzero'], key=abs, ascending=False)\n", " # drop values with a median weight of zero (equivalent to 50% bootstrap support threshold)\n", " df = df[~df.median_weight.eq(0)].reset_index()\n", " # save data\n", " df.to_csv(f\"{outdir}/component{component}/{mode}_weights_summary.csv\", index=False)\n", "print(f\"Component weight profiles saved in output directory: {outdir}\")\n", " " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part C: Visualization" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Comparing KOfam weights:\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Comparing phylum weights:\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Comparing sample weights:\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Comparing concatenated weights:\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# compare weight profiles between components\n", "\n", "# make dataframe for concatenating weight profiles\n", "concat_profile_df = pd.DataFrame()\n", "\n", "# iterate through comparisons\n", "comparisons = modes + ['concatenated']\n", "for mode in comparisons:\n", " print(f\"Comparing {mode} weights:\")\n", " if mode != 'concatenated':\n", " # calculate median weight profile for each component in model\n", " profile_df = ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate']).to_pandas()\n", " # add mode weight profile to concatenated profile\n", " concat_profile_df = pd.concat([concat_profile_df, profile_df], axis=1)\n", " else:\n", " profile_df = concat_profile_df\n", " # calculate correlation matrix\n", " corr_df = profile_df.T.corr()\n", " # make clustered heatmap\n", " g = sns.clustermap(\n", " corr_df.fillna(0), mask=corr_df.isna(), cmap='PuOr_r', vmin=-1, vmax=1, cbar_kws={'shrink':0.5, 'label':'Pearson\\nCorrelation'}, \n", " xticklabels=True, yticklabels=True\n", " )\n", " g.fig.suptitle(f\"Similarity of {mode.capitalize()} Weights Between Components\", y=1.02); \n", " plt.show(g)\n", " " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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Gc5WLXne2bNkSo92bJUsWy2ny5ctngnwueh3SN4D0xlx169bNqlWrluU03APY03bJnj17Yu0xqddrp6Gte3/lojZu3Gi1b9/enD96POnDOqeh/WJP61ntee6Ntnk1buU02tPcVS76sEU70URvw+zdu9dct512H/3rr7+62zH6Fnd0Gp/S3vvJHTnRfZgO+HH8+HGPZcWLF5fvvvtO5s6dK3369BEn0gEsLl265J5//PHHTc47F81FFRAQIE6kox/v2bNHgoODbXMfao43pylQoIDJhaiDn2huSB0xGhLjHNE8va1btzY5aDVn2UsvvWQGSHSazJkzy7lz59zzjRs3lgwZMrjnIyMjHTn4n/7N0etd9fzzz5sciS1btpQvvvhCnIa6xfu4Ajly5PC6XscXuHbtmjhNsWLFZM6cOebzBx98YOoazZnp8vHHH0uhQoXEafRv1jFdlLbl7h1zQo8nJ+ZyPnv2rMmT71KwYEEzoJvr+qRjUGzatEmchnsAe08//bS8/vrrMcYrUbqsb9++Zhunoa1rz+4cqVy5ssltferUKZk0aZJv5S+OJ7Rf7JUvX17++9//2sYRNCf4yJEjzTZOox2WU6ZMaT7f+1PpQNdOa7/kzZtX9u7d665nopeHq0x84hxK6ig+4q5169ZWjx49bNfpky193chpPf9UtWrVYn1F/pNPPrHKli1rOY0r15Qr79T48eM91n/88cfmdT0nW7NmjXklTfO3pUqVytG9Re16odzLia+5aq42fY3TG03XUaVKFctptMejt3yH2qtLzycnXo9cqFv+Uq9ePeuZZ55xp+SITpfpOaZpcJxGe7Bpby5NJaA/tXdOoUKFrAoVKpjXW7UHU2yvS/srrVO1N6jmVv3www/N69CaT1PTaWlqLc2Jrq8EO03p0qWtmTNnetQx2jvUdV3Wtwud2OOaewB7rly8+oaLvj6v9axO+lmXlSxZ0qMHv1PQ1o17uTgR7Rfvb7Jkz57d9Kpu2rSpGYtCJ/2sy7RnsSstm5PoGy2amkTHbXnrrbesAgUKWOHh4e71//nPf6x//etflpOMHj3atOP07cqxY8eadKCuN5n1TTEdC8gXUvR5hv7hU9544w3ZsWOH1x5N2iP9s88+E6eZPn26pEqVyut6HT3bib30jx496jGfPn16j/moqCjTE8XJqlevLhEREdKxY0dJly6deRrqVEOGDIlxjNzLib255s+fL4GB3l/iypYtmwwfPlyc5pVXXpHvv//edp326tLeGLNmzRKnom7xvEbXq1fP9NgqUaKEOWfUmTNn5KeffpKiRYvK8uXLxWlq164tBw4cMO26smXLSr58+cw5NXXqVLl+/bq88847Uq1aNXEa7Ql68eJFqV+/vqlHtFfbM888417fqFEjGT9+vDhNv379pE2bNqbHbJo0aeTzzz+Xbt26ua/L69atM2+nOg33APZy584tu3fvlm+++UY2b94sp0+fNssrVKhg6hY9p2Jr2/gr2rr29I12fasDnmi/2CtZsqT8/PPPMm/ePFO/HDlyxCzXNzGHDRtm3kwNCQkRpxkxYoTUrVvXnE/6duHatWulQ4cO5vjR+vaPP/6QL7/8Upzk9ddfl2PHjplz5bHHHpNff/3VvHGoPdL1TQZ9e0zfvEzuAjSSntQ7AQAAAGfQ11fvDebozZa+Lu7UYA5ipyk6Vq1aZW7O9fjRm9AnnnjCpDFxqq+//toELTRFiT6E0Yd0LhcuXDA/9cYdABA/aL/gQWhqkoMHD0rhwoXNA7sbN26YDll//vmn1KpVyyx3ogMHDpgHTve26WrWrOkTDy4JovvZDcbixYvN0x3NN9SiRQvHPkXWnkq//fab6cmlFzO9wVi6dKk5SbUnl+vJMUTCw8NNz9nYcrw5iT4F1SfFeh7p8aM5Ip3ca1TPpeh//5YtW8z5pI3F2Hp7ObmxpD1Jn3rqqaTelWRBe+fo8ZInTx5xIq5FAJB012LN36x1b/78+U0PN1+4OU8KTm67cJ32TgNcP/74o8d5pIE/J/YqxoMjxgB/RRDdhzVr1sy8HvPss8/Kvn37TLBPG4d6gdNXI/SzpnSJPvCQE+jAmXXq1DHBG31VZMWKFebVK01nomWigb+VK1eaVxidVi52ypUrJ5988ok5blyvZDnJq6++anpwNWjQQH7//XfTODx8+LAZuFcHW9JjSHt75cyZU5xEG8z6IE57WuiT4SVLlsiLL75ozielvf/0dXF9coy/6OvSeqOuN2VOG2xJU7r88MMP5lqkqVt69uwp7777rql3n3zySfPKopNuvO7nWqS9mZw42FJ0dAD4K83EgAEDTFqOTJkySefOnc3gkC56HOmNqNPqFhcNaNn18NPleu126oM67QmpD7ej94isWLGi+elEen5oqhtNg6Q9/pTrVlePkcmTJ0vDhg2TeC+TH6e2XbhOe3+ooqm0XGlhtSyyZs1qBi4ODg42g0h26dJFnOrehwualkJ70DqpjRsdMYbYcbw8WFtYyynZt+mSOik74i5jxozWgQMHzOe6detazz//vHXz5k0zHxUVZQYy0MEvnKZ27dpmQAIdwKJ79+5m8IIWLVqYMrl165bVpk0bq2bNmpbTBxaNPrmWO3Hgv2zZsrkHO3nuuefMseEaMObChQtWgwYNfGKAi/j24osvmgEyly1bZrVs2dJ81sFPdHCU3377zXriiSesLl26JPVuJju7du1y5HnUtWtXKywszJo0aZIZFKZx48ZmELMff/zRDJCogxb379/fchKuRfZ0oKnFixe7B0HPkiWLGQi9YsWKpj7Wwan2799vOc2QIUPM36+DLg0YMMAKDQ21OnXq5F5/+vRpc512msuXL5vzRgdbzZo1qzVo0CDr9u3bHuXixDo3MjLSeuGFF8zfrgNDatnopJ91EFqtX65du2Y5Td++fU1d++WXX1qrVq2ynnrqKWvkyJHmfkmPnaCgIOubb75J6t1MdpzaduE6bU+vPdrO13LRAQC1jPr06WPqlNmzZ5tBjOfPn285sd7Vsoh+/6xtFq1z06dPb02ZMsVyImIM9jhe/PdaRBDdhwUHB7tHs9VRjyMiIjzWHzp0yNyEOfHhgusG/Pr166ai2rJli3u93rTrSNFOU6pUKTNiuN5I/Prrr2Y6evSoueHSGw3XMqfRG3MdDVrlypXL41hR2oDUII/TaJ2yadMm98MEvfivXr3avX7NmjVW/vz5LSfWL7FNISEhPnHxj2+5c+e2vvvuO/P5xIkT5njRIIbL8uXLrcKFC1tOwrXIHh0A7BUoUMDjnNHAhS576aWXrLt37zo2WNytWzerUKFC5sHLrFmzrLx585q2jOuYcerDBT1PChYsaK1cudLjoYJ+1iCxltnLL79sObHt8v3337vn9cG/Bitu3Lhh5t9++22rcuXKltPQdrHHddqe3vds377dPX/x4kVzv+R6MKfBv9KlS1tOw8MFe8QY7HG8+G8QPWVS94RH3OkrMZquRV8J0dc2NZ9bmTJl3Ot1Xl+5chp9OKQj/Kp7fyrN76yv/zrN1q1bpU+fPtK8eXMzEFX0Y0VfEdfX6J1IR4TWsnn00UfloYcekitXrsRIU+HE40VHDHelsNHUAmnTpvU4RgoUKGBet3IazZWpaUtKlChhu17r3bfeekuc5uzZs+aYcNUneu3Rc8ulePHicvz4cXESrkX2NMWCazyFXbt2yVdffSWpU6c287pcr1NOS7emTpw4Yc4TFz2fNGVW9erVTSqtUaNGiRNpKrEPPvjApIlSTZo0kfr165uUHMuWLTPLnJjnWtMs6LlTpUoVj+Var+jgdnPmzDFp6jS1lpNERkZ6pN/TlHNa52ibRu+VtA2sqSichraLPa7T3seHip5qQgdE1GWa5kXvB7SOef3118VpNN2apoR1Xatnzpxp2rxDhgwx6dd0sMjRo0ebdLtOQozBHsdLTJo2LDZaJr6AILoPGzRokLRt29bcdHbr1s3kn71w4YLJgX7o0CFzguqNl9OULVtWRo4caRqDs2fPNsHRKVOmmBsKpfkQo9+oOoUGKSZMmGDyezdq1Ej+85//SN++fcXp9LzRhqAOHKR5NPVc0mPEdR51797djD/gNJr7UIPkuXPnNvNdu3Y1wXQXvSFNly6dOE3p0qVNmbRr185rXlEn3ohmzpzZ5Mp0HS+NGzeWDBkyeAQ2goKCxEm4FtmjA4A9LYtffvnFDG7nosFAHehaB7fT/LROpPVK9BtwHa9k9erVZiwTzV383nvviRNpYM/18MmOrnNi8E+DxB9//LEZX0BpPl4NALpyxGuZOO1apGi72OM6bU9zwE+cONGUhdLPDz/8sJlcbTo9r5yGhwv2iDHY43iJaf/+/dKqVStT19rR2MPPP/8syV5Sd4XHP/Ppp5+aFBT35qHSV6569Ojh8YqnU2zdutW8eqdlonlW9VU8zbWqOahy5Mhh0uBET0vhRPr6s75Grzmu9VWrffv2WU42duxY80qVHhupU6c2x45ratKkiXX16lXLaRo1amRNmDDB63p9lbN69eqW0wwfPtx68803va4/duyYSb/gNHXq1LGmT5/udf3cuXNNXn0n4VpkT1P7ZMqUyRwTOuXLl8967733rA0bNlhz5swxqYF69+5tOTE9R/v27W3XaUoKTe3iC6+4xjdNA/XVV1/FWK7XZU3Loa+RO7FcNA1SmTJlYqRyVLqsbNmyJme602idqnnPK1SoYPKhaxt3/Pjx7vU65gBtl5ic2nbhOm1vx44d5jqt5ZAnTx5zb/Txxx973AO0bdvWcppatWp5jAel9YmmkIpe9zoxBWh0xBj+wvESk7ZNpk2bZnmzc+dOn2jTmSSCSR3Ixz+jI6lHRESYkX+1h4W+uqhP1jU1hVPpE76DBw9K4cKFzVM/fZVz/vz55hWRWrVqmeUQmTRpkunlpj0tcuXKJU526dIlWbVqlcd59MQTT0jBggWTeteS7at7+hTdiT10ENPFixfNiPPRe59Hp71TtHexKyWDU3At8p6KokePHnLy5EnzOr2L9hDt3LmzjBkzxrxG7yTaA1+PFe1hbUfLSq9R3nqS+it9O0x7Ji1evDjGOk23pufRtm3bTFvYSfRtMH0F/JtvvpGMGTOat8dcqbW0PaPH0YIFC7zWyf5Me1VrD3RNYaLloMcI4A3XaXta7y5fvtycR5pWrGjRouJ0Gm/RY0J7Xut0+vRpk25Me9aqqVOnmvsjXeZ0xBg4XuzoG/6agk/fXLCjb2S+/PLL5thJzgiiAwAAIFHRAQD3GyzWBwjFihWzXa+BdD2OqlatKk504MAB2bx5s7k5V5q2pHLlyhIWFpbUuwYAfoeHC3gQHC/+iSC6n994fPnllyZvutPoYf3rr7+a/H86QExUVJR88cUXpgLTHJqaU9OpNBftjz/+aCp17TmqeWl1gC56XHvSC93cuXMdOxjK33Fy/RIbJ5cL9W5MlAn+ybGjA4v+73//Mw8YtEeta0BWAN5R7z44J7ddlPYG3bRpk8fDKB20V3ODg+sR/p7WszoQuN15pOMkxTaGB+BrCKL7+euMOgKu015x1cEg9eJ+/PhxyZ8/v3z77bfSokUL86qeHu6agmLjxo2OCxrrK74aLN++fbsJnmvPPx3M7cSJE2bgrl69esmoUaPEaZYtW2a7XAcT1YF0XAMl6kAp+ItT65e/49Ryod6NiTKxN3bsWHn22Wd5QHkPDe7pgIihoaEmPZLOa2BHA346aHyhQoXk+++/dw/shv9z5swZmTFjhgwePFiceL3ZsWOHSZOldcy+ffvM6+HavmvatKnX1EBOqHePHTtmOolQ794fp7Zd9N6oefPmsmHDBsmTJ49ky5bNXa/oMaRpHTX9mCtdklNwPfr7elcH/NbBEal3xTxc0b9b3xqrWLGix3m0ZcsWk85F0zoWKFBAnIyHUX/R80XjUXbLf//9d1MfJ2tJnJMd/8Dly5djnX744QefSMwf3xo3bmwGRdyzZ48ZXLVIkSJmWVRUlHXjxg2rYcOGVps2bSynadmypRkkU48NLYeuXbu6B4VZs2aNGVgntoEk/ZUOxHvvwLz3Tk48j6hf7FEu9qh3Y6JM7GmdmiJFCqtmzZrWwoULrZs3byb1LiWbcjlz5oz5/Morr1hFixa1jhw5YuaPHz9uBmPq3LlzEu9l8rNr1y5H1rmfffaZOY+07ZY+fXpr1apVVoYMGcx5Vbt2bbNu/vz5ltNQ79qj7WKvefPmZoDigwcPxliny3RA9GeffdZyGq5H9qh37enfr/Ws1iX30mW67plnnrGcRgdYvXTpkvl84cIFM2ixnls6iLHWt2FhYdbZs2ctJ7l8+bLVokULK02aNFbWrFmtQYMGWbdv3/YYmNYXrkUE0X2YK7jnbXJq8E8rJh3ZV0VGRppy0Mahy4YNG8xI404TEhJiRp130bJJlSqV+4L30UcfWYULF7acpk6dOlb9+vXdjUUXp48oTv1ij3KxR70bE2ViT8th7ty55qZKr0F6M9q9e3frp59+spwsetBCr8VLly71WL969Wrr0UcftZxm9+7dsU6LFi1yZJ37+OOPW8OGDTOfP/74YxPIefvtt93rx4wZY5UuXdpyGupde7Rd7GkgNCIiwuv67du3m22chuuRPepde8HBwbG24fShpm7jNDyMiqlbt25WoUKFrMWLF1uzZs2y8ubNa+Iwrg41GkTXckvuUiZ1T3jEnQ6+NWDAAPPajJ3Dhw/Lv//9b3GayMhIyZQpk/mcLl06M+krMy6ankNfL3KaoKAgMxqyi75Co69t3r5928xrzjLNIek0+nrZ+PHjpVy5cjJt2jRp0KBBUu9SskD9Yo9ysUe9GxNl4p2+Gv7SSy+ZV+nff/99M/7E5MmTzcCiHTt2lFatWjlygFHXNVrzE2sqiuj0NWh9VdppSpcubcrFLvuka3n0to2T0pa88MIL5nPLli1NLusmTZq412tagTfffFOchnrXHm0X7/dGV65c8bpeBy7WbZyI61FM1Lv2MmTIYGIIxYsXt12v63QbJ9Mx6TRtrqYAUpriZuTIkabN6yRLliyRDz74wKShU3r+1K9f36QcdqXY9YU2HUF0H6a561TVqlVt12tl5cSU9zly5DB57Fy5lLTCip7LTvN/Z8yYUZzmySefNDlDteLSwT369+9vcmi6bjacWi6qZ8+eJredNox0YCUNqjsd9Ys9ysUe9W5MlMnf0/Lo06ePmX744QeZPXu2qY910mCY0+iDBQ3Y3Lp1S44ePSrFihVzr9OBupx4E6ptFD13atSoYbte89HqzZcTg6Kamzhfvnxy6dIl0yFC5130c/r06cVpqHft0Xaxp4HQdu3amXa/1jEhISFmuQbW16xZY8aLat26tTgR16OYqHftvfzyy+aBwqBBg8x5FD0nup5Hw4YNk1dffVWciIdRnvQaHH1MJB1nYfXq1SY/vHawee+998QXEET3Yc8//7z8+eefXtfriMhDhgwRp6lZs6YZQEiDxuqVV17xWK+DDLkak04yZswYeeaZZ0yjRyt07Z2zePFi9/oDBw6YBpNTaW83HXRVgzf62Yk3E9FRv9ijXOxR78ZEmdjz1sPkX//6l5kmTZokixYtEqfRQI5L48aN5fr16x7rdXA7vTY5jb6doDeZ3gai1UCGE6/XWr906dLFBCb0fNH2Xb9+/cxbHXqO9e7d2133OAn1rj3aLvbGjRtnBrLTt580IKqdjFRUVJSkTJlSOnToYO6fnIbrkT3qXXtvv/22iSuMHj1aXnvtNXc7T6/NWrf07dvXdJZwIh5GedIH3BpzcvXIdz2c0muznk/6NocvMAlnknongMSkFViaNGk8Xu90Cm0E/fjjj6ZxWKlSJfP0DzHp60Rr1641DaPoPZgAxI2T611vnFommkpMbxyoWx/MtWvXJEWKFOaYcZIvvvjC/O1t2rSxXa+9u/SaHT3o4wTaw+/FF1+UTZs2yRNPPGECOgMHDpSpU6eaAIb2eNN0dff2fHM6p9a7iJ32PNeONK5UPxr40wd4rp7p8OTU6xH17v3VsdrGc51H0YOlThMeHu4xX7duXXnuuefc8/pgYc+ePbJy5Upxim7dusmpU6c8OnJGT59Vq1Yt2bZtm0k5nJwRRAcAAAAAH3fkyBHTYSIsLMz0pAUAJCzqXcSFEx9G/fHHH+btwug98u8NpEdERHhNPZZcEET3cefPn5c5c+aYJ6LRn/rpIJH6+sjDDz8sTkS52KNc7FEu9igXe5SLPcolJsoE8eX48eMm3YIeTwC8o961R7nYo1weHNcjPAiOF/gbgug+TF910CT8adOmNTm67h3EQZ+IfvPNN1KuXDlxEsrFHuVij3KxR7nYo1zsUS4xUSZxw82Wvd27d5tczsn9FdfE5uTjheBfTNS79igXe5RL3Dj5ekS9++CcfLzExqntl/N+cA4RRPdhmtO6VKlSMn369BgDdel/a+fOnU2eJT1AnYRysUe52KNc7FEu9igXe5RLTJRJ3Dj1Zkvzev/d6+I6YJfTyuXvOPV4Ifhnj3rXHuVij3Kxx/XIHvWuPY6XuHFi+2Wbn5xDBNF9WHBwsOzcudPk37Kjo9OXKVMm1tHY/RHlYo9ysUe52KNc7FEu9iiXmCgTe9xseR9wVYM4sTXLdb3TyoXjxR7BP3vUu/YoF3uUiz2uR/aod+1xvNij/eK/5xAjH/gwfe1h69atXi/8us71dMdJKBd7lIs9ysUe5WKPcrFHucREmdhr0qTJfd1sOc0jjzwi06ZNk8aNG9uu37Vrl5QtW1achuPFew+2999/3/Zv12U9e/Y0wT+nod61R7nYo1zscT2yR71rj+PFHu0X/z2HCKL7sNdff106deokO3bskBo1asR4HWLWrFkyZswYcRrKxR7lYo9ysUe52KNc7FEuMVEm9rjZsqd/sx4r3srl727E/BXHiz2Cf/aod+1RLvYoF3tcj+xR79rjeLFH+8WPzyFN5wLftXDhQqtixYpWypQprYCAADPpZ122aNEi6+rVq5YTUS72KBd7lIs9ysUe5WKPcomJMompYcOG1qBBg7yu37Vrlyknp/n++++tr7/+2uv6yMhIa9myZZbTcLzYmzJlihUUFGR169bNWrp0qbV582Yz6WddFhwcbE2dOtVyIupde5SLPcolJq5H9qh37XG82KP94r/nEEF0HzZu3Dj356ioKOvkyZNm0s/qypUrVpUqVSynoVzsUS72KBd7lIs9ysUe5RITZWKPm62/P17scLzYc+rxogj+xUS9a49ysUe52ON65B31bkwcL/Zov/jvOUQQ3YelSZPG+uCDD7yelE888YRVuHBhy2koF3uUiz3KxR7lYo9ysUe5xESZ2ONmK27Hi5YJx0tMTj1eCP7Zo961R7nYo1zscT2yR71rj+PFHu0X/z2HCKL7sMWLF5tKS19/iE6f3uhFv2DBguagdBrKxR7lYo9ysUe52KNc7FEuMVEm9rjZerDjxRXI0ePlxIkTltNwvNgj+GePetce5WKPcrHH9cge9a49jhd7tF/89xwiiO7jZs2aZaVNm9Zau3at++B78sknrQIFCjiysnKhXOxRLvYoF3uUiz3KxR7lEhNlEhM3W95xvMTE8WKP4J93nEf2KBd7lIs9yiUm6l3vOF5iov3iv+cQQXQ/MHLkSCskJMRUWv/617+s/PnzW8ePH7ecjnKxR7nYo1zsUS72KBd7lEtMlElM3Gx5x/ESE8eLPcrFO84je5SLPcrFHuUSE/WudxwvMXG8+GeZEET3E3379rUCAwNNZXXs2LGk3p1kg3KxR7nYo1zsUS72KBd7lEtMlElM3Gx5x/ESE8eLPcrFO84je5SLPcrFHuUSE/WudxwvMXG8+F+ZpBT4rGbNmnnMp0qVSrJkySLdu3f3WP7555+Lk1Au9igXe5SLPcrFHuVij3KJiTKJXZ8+feTixYtSo0YNyZcvn6xbt05y5colTsXxEjuOF3uUiyfOI3uUiz3KxR7lEjvqXU8cL7H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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# compare top weights (mode 0) between components\n", "\n", "# USER INPUTS -- edit as needed\n", "max_elements = 20 # maximum number of elements visualized in any one component\n", "viz_components = [1, 2, 3, 4, 5] # list components you want to compare against one another\n", "heuristic = 'max_weight' # pull out the top weights across any component\n", "# heuristic = 'max_variation' # pull out the weights that vary the most across components\n", "\n", "# pull out the top weights\n", "mode = modes[0]\n", "if heuristic == 'max_weight':\n", " # weights sorted by maximum across all components\n", " idx = np.abs(ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate'])).max(dim='component').argsort()\n", "elif heuristic == 'max_variation': \n", " idx = ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate']).std(dim='component').argsort()\n", "df = ds.sel({mode: ds[mode][idx[-max_elements:].data[::-1]]})[f\"{mode}_weights\"].to_series().reset_index()\n", "\n", "# plot data, only including listed components\n", "g = sns.FacetGrid(df[df.component.isin(viz_components)], row='component', aspect=5)\n", "g.map(sns.barplot, mode, f\"{mode}_weights\", order=df[mode].unique(), color=sns.color_palette()[modes.index(mode)+1], errorbar='sd');\n", "g.fig.suptitle(f\"Component Weights of Top {max_elements} {mode.capitalize()}s\", y=1.02); \n", "g.set_xticklabels(df[mode].unique(), rotation=90); \n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# compare top weights (mode 1) between components\n", "\n", "# USER INPUTS -- edit as needed\n", "max_elements = 20 # maximum number of elements visualized in any one component\n", "viz_components = [1, 2, 3, 4, 5] # list components you want to compare against one another\n", "heuristic = 'max_weight' # pull out the top weights across any component\n", "# heuristic = 'max_variation' # pull out the weights that vary the most across components\n", "\n", "# pull out the top weights\n", "mode = modes[1]\n", "if heuristic == 'max_weight':\n", " # weights sorted by maximum across all components\n", " idx = np.abs(ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate'])).max(dim='component').argsort()\n", "elif heuristic == 'max_variation': \n", " idx = ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate']).std(dim='component').argsort()\n", "df = ds.sel({mode: ds[mode][idx[-max_elements:].data[::-1]]})[f\"{mode}_weights\"].to_series().reset_index()\n", "\n", "# plot data, only including listed components\n", "g = sns.FacetGrid(df[df.component.isin(viz_components)], row='component', aspect=5)\n", "g.map(sns.barplot, mode, f\"{mode}_weights\", order=df[mode].unique(), color=sns.color_palette()[modes.index(mode)+1], errorbar='sd');\n", "g.fig.suptitle(f\"Component Weights of Top {max_elements} {mode.capitalize()}s\", y=1.02); \n", "g.set_xticklabels(df[mode].unique(), rotation=90); \n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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0OCk8TK1fasoXvZlkCvPSzUFTtXkKy9MHHhVbqqRAPYV/ZRXiZSH65sy/7LVKN1pcV1VjNfHcUxuc1HomLel6p+r0dMPOq6++Om/1e01f841Jr+kOO+yQVWuvK50zfaix7rcr0nvk6KOPLl9PNwZN4Xb6QGRj/va3v2UBeqoynzp1anlgXlGqTk8tTv70pz9VapOSPlBJH0xUHPsi0jc/0rcJysL51N4nvefShxrpw40yX7QFzxdRndcufZiU2tOkm9Ru7L2WrlfaLy0pdB85cmR209MUrNfkex4AoJBp5wIAUMEPf/jDrLI0VZ2mMHxd7733Xtxyyy3Z72Uh1pgxYyrtU1b9mapYa9qtt95aqWo1rad+ySkAK5tTCowr7pfcfPPNWZiWWoV80fD6W9/6VtZXvKoK/dTaozrSa7xu64uNScF4Ol+qzk6V5yn8qxiip1A39Xbeaaedyj/U2Jz5p+rlFM7++7//exZclnnmmWeyMLW60nNP0gct64bFFaXnV1YlX1WbkjI1fc03Jr2mKdROr3XFliLp/XLfffdl16msNVKZ9MHUp59+Wr6e2qZ89tlnG51b6jmenl+q9E4V6Ou2NimTKtRT4PvrX/+6Ujume++9N7t23/nOdzZ4npdffjk717peeeWV7LqUta4pq8yuWDGefi/7N2FLqM5rlz40SK/Z+PHj19uW+sOXPddUUb+url27bvRvDgCg2KhEBwBYp4IzBYGpV3AKYlO1aQpSU0Vr6sOdbtiX2jaUtRhJLUJSyJUC0dQXOYVuqUo13XSxYvVoTUj9lVO7hXTOFCKndh+pBcMVV1xR3nc5VTCn86ZK0hRwpjmmtgwp8PzBD35Q6Saim+pHP/pRVpWazjl48ODsBqkpfEs35EwV0FUFcRvTrVu3rHI83ZT1kEMOyfo8p7lvSFl1efqWwDXXXFNpW6pST4HxSy+9lD1OxerbzZl/qsrt169f1jc69VBPPatTWJ3+JioG61/0uSfpRqDp5qYpmE29qNMHN2kuqZVG6pmdepn/4he/yELNit90WNeWuOYbc8MNN2TV1+mapGr5VAWeKuZT8HrTTTett396/6QPelK4mz7suO2227Jjv/GNb2zwPKecckr2nkr94d9+++1sKZP+ZtL7rMyNN96YfZiS3ofpZpx//etf42c/+1kW+B9//PEbPE8K21PLltRzPV2f9I2AdK677rore9+l91iS2rek1/PSSy/NQur0YUH6gGZz+v1vTHVeu9NOOy3rbZ5ulJr+9tPfb/qgJX1TII2nlkEHH3xwXHfddVk7l/SBX/rGQuqVnh4//f2Vvd8AAPjfygkAANbxzjvv5AYPHpzr0KFDrkGDBrkdd9wxd/jhh+d+8Ytf5P75z3+W7/fpp5/mrr322twee+yR23777XPt27fPDRs2rNI+yZe+9KVcnz591jtP+s+x73//+5XG5s6dm43/5Cc/KR87/fTTc02aNMm99957ueOOOy63ww475Nq0aZMbMWJE7vPPP690/CeffJK7+OKLc7vuums2p7322it7rLVr12703GVzTeer6KOPPsr2Tc8vPWbbtm1zxx57bO6OO+4o3+ePf/xj9pgPPvhglc/n7rvvLh9bsWJF7uSTT841b94825bOuTErV67M1a9fP9v/97///XrbDzzwwGzbj3/84/W2bcr8q5pnMnHixFynTp1yDRs2zO2///65Rx99NPetb30rG9vQNSuTxtN1KvPZZ5/lLrjggtzOO++cKykpybYnv/3tb7Nr27p16+xvbvfdd8+dc845uQULFmz0tdnUa37UUUfl9ttvv9wXlf721v2bmDlzZq5Xr165pk2bZn+PRx99dO7FF1+stE96LdPze+aZZ3Jnn312rkWLFtn+p5xySu5vf/vbRs+b/i7S8VUtVf3NPPfcc7nDDjss16hRo+z1Tdd8+fLlGz3Pf/3Xf+Uuu+yy3Je//OVcy5Yts7+zXXbZJfed73wne54V/fd//3euZ8+e2fNo1apV9u/EG2+8sd7fTtl7dl35rsG6/0Z8kdcuPWZaKlqzZk32XkjnSn+76fhu3bpl/14tW7Ys22fq1Km5fv36ZX836W8u/TzppJOyf/8AAPg/Jen/1HaQDwDAhqXq99/+9rfVrn6mZqXq8FT9vyV7YdcF99xzT1bB/+qrr2aVz2w6rx0AwLZDT3QAAMgj9aJO/acrmjZtWnbTxq997Wu1Ni8AAGDr0RMdAADySH2v0w0rTz311OxGo6mn9Lhx46Jt27ZZv2kAAKDuE6IDAEAeLVq0yG40OWHChFi8eHE0adIkuwljulnpTjvtVNvTAwAAtgI90QEAAAAAIA890QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAADAFvW1r30tfvCDH2zx8zz88MNx3HHHxU477RQlJSXx+uuvb/FzAgBQ9wnRAQCAOmHlypVxxBFHxI9//OPangoAAHWIEB0AADbD2rVr46abboqOHTtGw4YNY/fdd48bb7yxfPubb74ZxxxzTDRu3DirkD777LNjxYoV5du/+93vRv/+/WPkyJHRpk2baN68eVx33XXx2WefxWWXXRYtW7aM3XbbLe6+++7yY/7yl79kldYTJ06Mww47LBo1ahT7779/PPPMM5XmltYPPfTQbF677LJLDB06NHvcihXiF154Yfzwhz/MztO2bdu45pprKj3G0qVL46yzzoqdd945mjVrlj2XN954o3x72r9r165x7733RocOHaK0tDQGDBgQn3zySfnzS/O45ZZbsjmnJc1/SzjttNNi+PDh0bNnzy3y+AAAFCchOgAAbIZhw4bFj370o7j66qvjv//7v+O+++7LwvCyyuhevXpFixYt4tVXX40HH3ww/vCHP8T5559f6TGefvrp+PDDD+PZZ5+N0aNHx4gRI+LrX/96dtzLL78c5557bpxzzjnx17/+tdJxKWS/5JJL4rXXXosePXpE3759429/+1u27YMPPojevXvHIYcckoXet99+e9x5551xww03VHqMX/3qV9GkSZPsPOnDgBTgP/XUU+Xbv/Od78SiRYviiSeeiBkzZsSXv/zlOPbYY+Pjjz8u3+e9996LRx55JB577LFsSaF5ek2SFJ6nuQ0ePDgWLFiQLe3bt6/ytUzPs2nTphtcAABgayvJ5XK5rX5WAACoA1K1darQvvXWW7Nq7XWNHz8+Lr/88pg/f34WVCePP/54Fnan0DyF7alSe9q0aTFnzpyoV+9/a1w6deoUrVu3zkL15PPPP88qvCdMmJBVeadK7j322CMLqtPjJ6nCPI1dcMEFWWX5lVdeGQ899FC8/fbbWfV3ctttt2X7L1u2LDtXqkRPj/3cc8+VzzlVrqdq8/TYzz//fPTp0ycL0VM1e5lUdZ/OkarqUyX6T37yk1i4cGHsuOOO2fa0Lc39pZdeytbTeVK1+pgxYzb4eqbzLF++fIP7pHNvTNnrkz5cSOcFAIDNUX+zjgYAgCKWAurVq1dnldn5tnfp0qU8QE8OP/zwrAXM7NmzyyvW99tvv/IAPUnjqT1Lme222y5rBZNC5opShXeZ+vXrx8EHH5yds+zcaXtZgF527tRKJlW0p7YzyYEHHljpMVPbl7LzpAr2tH86d0X/+Mc/surzMqmNS1mAvu5jfBHpg4O0AADAtkSIDgAA1ZT6nNeE7bffvtJ6Cr6rGkvhe03b0HlSgJ4C8VQpv67Uu31THuOLSO1cfv3rX29wn4r95AEAYGsQogMAQDXttddeWZA+derUKtu57LvvvnHPPfdkvdHLqtFfeOGFrOp8n3322ezzp3YpRx55ZHk7l9SzvKzfejp3aueSujeWVaOnc6eK8XSj0k2R+p+nNi2pyj1Vm1dXgwYNsrYxG5P6sV966aXVPg8AAGwJQnQAAKimRo0aZT3GUw/wFBSndimLFy+OP//5z3HmmWfGKaeckt0k9PTTT896h6dtqWf5aaedVt7KZXOMHTs2C/JTYH7zzTfH3//+9zjjjDOybeedd17WgzydLwXrqX1MmsuQIUMqtY7ZkJ49e2YtYfr375/ddHTvvffOerlPnjw5TjjhhKx9zKZIAXy6cWnqVZ5uDtqyZcsq57C57VzSzU7nzZuXzTFJzzlp27ZttgAAQHVs2n89AwAAVbr66qvjkksuieHDh2dh9oknnljeD3yHHXaIJ598Mgt3DznkkPj2t7+d9U9PNyKtCenmn2lJfdfTTUAfffTRaNWqVbatXbt22U1MX3nllWx7apWSgv2rrrpqkx8/VbCnx0jV7oMGDcpC9HRj0/fff/8LfQiQqstTX/fOnTtnN2JNQfeWkJ7/QQcdlN0MNUlzTevjxo3bIucDAKA4lOTS9zsBAICCkSq699hjj3jttdeia9eutT0dAACo01SiAwAAAABAHkJ0AAAAAADIQzsXAAAAAADIQyU6AAAAAADkIUQHAAAAAIA8hOgbkbrdLF++PPsJAAAAAEBxEaJvxCeffBKlpaXZTwAAAAAAiosQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAACoCyH6s88+G3379o1dd901SkpK4pFHHtnoMdOmTYsvf/nL0bBhw+jYsWPcc889W2WuAAAAAAAUvoIK0VeuXBldunSJsWPHbtL+c+fOjT59+sTRRx8dr7/+evzgBz+Is846K5588sktPlcAAAAAAApfSS6Xy0UBSpXov/vd76J///5597n88stj8uTJ8dZbb5WPDRgwIJYuXRpTpkyp8pjVq1dnS5nly5dH+/btY9myZdGsWbMafhYAAAAAAGzLCqoS/YuaPn169OzZs9JYr169svF8Ro0aFaWlpeVLCtABAAAAAChOdTpEX7hwYbRp06bSWFpP1eX/+Mc/qjxm2LBhWdV52TJ//vytNFsAAAAAALY19Wt7AtuadAPStAAAAAAAQJ2uRG/btm189NFHlcbSeupt3rhx41qbFwAAAAAAhaFOh+g9evSIqVOnVhp76qmnsnEAAAAAAKhTIfqKFSvi9ddfz5Zk7ty52e/z5s0r72c+cODA8v3PPffcmDNnTvzwhz+MWbNmxW233RYPPPBAXHzxxbX2HAAAAAAAKBwFFaL/6U9/ioMOOihbkiFDhmS/Dx8+PFtfsGBBeaCe7LHHHjF58uSs+rxLly7xs5/9LCZMmBC9evWqtecAAAAAAEDhKMnlcrnansS2bPny5VFaWhrLli3LeqkDAAAAAFA8CqoSHQAAAAAAtiYhOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHnUz7cBgOKVy+Vi5cqV5etNmjSJkpKSWp0TAAAAQG0QogOwnhSg9+vXr3x90qRJ0bRp01qdEwAAAEBt0M4FAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEBdCdHHjh0bHTp0iEaNGkX37t3jlVde2eD+Y8aMiX322ScaN24c7du3j4svvjj++c9/brX5AgAAAABQuAoqRL///vtjyJAhMWLEiJg5c2Z06dIlevXqFYsWLapy//vuuy+GDh2a7f/222/HnXfemT3GFVdcsdXnDgAAAABA4SmoEH306NExePDgGDRoUHTu3DnGjRsXO+ywQ9x1111V7v/iiy/G4YcfHieffHJWvX7cccfFSSedtNHqdQAAAAAAKKgQfc2aNTFjxozo2bNn+Vi9evWy9enTp1d5zGGHHZYdUxaaz5kzJx5//PHo3bt33vOsXr06li9fXmkBAAAAAKA41Y8CsWTJkvj888+jTZs2lcbT+qxZs6o8JlWgp+OOOOKIyOVy8dlnn8W55567wXYuo0aNimuvvbbG5w8AAAAAQOEpmEr06pg2bVqMHDkybrvttqyH+sMPPxyTJ0+O66+/Pu8xw4YNi2XLlpUv8+fP36pzBgAAAABg21EwleitWrWK7bbbLj766KNK42m9bdu2VR5z9dVXx2mnnRZnnXVWtn7AAQfEypUr4+yzz44rr7wyawezroYNG2YLFLv07Y30finTpEmTKCkpqdU5AQAAAMDWVjCV6A0aNIhu3brF1KlTy8fWrl2brffo0aPKY1atWrVeUJ6C+LKAEMgvBej9+vUrXyoG6gAAAABQLAqmEj0ZMmRInH766XHwwQfHoYceGmPGjMmCvUGDBmXbBw4cGO3atcv6mid9+/aN0aNHx0EHHRTdu3ePd999N6tOT+NlYToAAAAAANSJEP3EE0+MxYsXx/Dhw2PhwoXRtWvXmDJlSvnNRufNm1ep8vyqq67K2k+knx988EHsvPPOWYB+44031uKzAAAAAACgUJTk9DXZoOXLl0dpaWl2k9FmzZrV9nRgq1mxYkXWxqXMpEmTomnTprU6J7Ye1x8AAACgwHqiAwAAAADA1iZEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHnUz7cBgOr5cMBtUehWrl1TaX3BGROiSb0GUch2nXhebU8BAAAAKEAq0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAmgzRp0yZEs8//3z5+tixY6Nr165x8sknx9///vfqPCQAAAAAANSNEP2yyy6L5cuXZ7+/+eabcckll0Tv3r1j7ty5MWTIkJqeIwAAAAAA1Ir61TkoheWdO3fOfn/ooYfi61//eowcOTJmzpyZhekAAAAAAFC0legNGjSIVatWZb//4Q9/iOOOOy77vWXLluUV6gAAAAAAUJSV6EcccUTWtuXwww+PV155Je6///5s/J133onddtutpucIAAAAAACFU4l+6623Rv369eO3v/1t3H777dGuXbts/Iknnojjjz++pucIAAAAAACFU4m+++67x2OPPbbe+M0331wTcwIAAAAAgMKtRN9uu+1i0aJF643/7W9/y7YBAAAAAEBdUK0QPZfLVTm+evXq7KajAAAAAABQdO1cfv7zn2c/S0pKYsKECdG0adPybZ9//nk8++yz0alTp9iSxo4dGz/5yU9i4cKF0aVLl/jFL34Rhx56aN79ly5dGldeeWU8/PDD8fHHH8eXvvSlGDNmTPTu3XuLzhMAAAAAgCIL0ct6nqdK9HHjxlVq3ZIq0Dt06JCNbyn3339/DBkyJDtH9+7dszC8V69eMXv27GjduvV6+69Zsyb+9V//NduWboKaboD6/vvvR/PmzbfYHAEAAAAAKNIQfe7cudnPo48+OqvsbtGiRWxNo0ePjsGDB8egQYOy9RSmT548Oe66664YOnToevun8VR9/uKLL8b222+fjaWgHwAAAAAAtlhP9D/+8Y9bPUBPVeUzZsyInj17lo/Vq1cvW58+fXqVxzz66KPRo0eP+P73vx9t2rSJ/fffP0aOHJm1nskn9XVfvnx5pQUAAAAAgOL0hSrRy6QQ+p577ompU6fGokWLYu3atZW2P/3001HTlixZkp03heEVpfVZs2ZVecycOXOyuZxyyinx+OOPx7vvvhvnnXdefPrppzFixIgqjxk1alRce+21NT5/AAAAAACKJES/6KKLshC9T58+WXV3utHotiiF+6kf+h133JH1b+/WrVt88MEH2Y1J84Xow4YNy/qul0mV6O3bt9+KswYAAAAAoKBD9IkTJ8YDDzwQvXv3jq2lVatWWRD+0UcfVRpP623btq3ymF122SXrhV7xBqj77rtvLFy4MGsPk26Guq6GDRtmCwAAAAAAVKsnegqfO3bsWPOz2cg5UyV5aiFTsdI8rae+51U5/PDDsxYuFdvNvPPOO1m4XlWADgAAAAAAmx2iX3LJJXHLLbdELpeLrSm1WRk/fnz86le/irfffju+973vxcqVK2PQoEHZ9oEDB2btWMqk7R9//HHWfiaF55MnT85uLJpuNApAfjuUbB/jdupbvqR1AAAAgGK0ye1cvvnNb1ZaTzfsfOKJJ2K//fbLWqZU9PDDD8eWcOKJJ8bixYtj+PDhWUuWrl27xpQpU8pvNjpv3ryoV+//PhdIvcyffPLJuPjii+PAAw+Mdu3aZYH65ZdfvkXmB2U+HHBbFLqVa9dUWl9wxoRoUq+wv8Gx68TzansKBSPd66JJSWFfbwAAAICtGqKXlpZWWj/hhBOiNpx//vnZUpVp06atN5Zavbz00ktbYWYAAAAAABRtiH733Xdv2ZkAAAAAAEBd6IkOAAAAAADFYJMr0Ss66KCDsn6560pjjRo1io4dO8Z3v/vdOProo2tijgAAAAAAUDiV6Mcff3zMmTMnmjRpkgXlaWnatGm89957ccghh8SCBQuiZ8+eMWnSpJqfMQAAAAAAbMuV6EuWLIlLLrkkrr766krjN9xwQ7z//vvx+9//PkaMGBHXX3999OvXr6bmCgAAAAAA234l+gMPPBAnnXTSeuMDBgzItiVp++zZszd/hgAAAAAAUEgheup7/uKLL643nsbStmTt2rXlvwMAAAAAQNG0c7ngggvi3HPPjRkzZmQ90JNXX301JkyYEFdccUW2/uSTT0bXrl1rdrYAAAAAALCth+hXXXVV7LHHHnHrrbfGvffem43ts88+MX78+Dj55JOz9RSyf+9736vZ2QIAAAAAwLYeoiennHJKtuTTuHHj6j40AAAAAABsE6rVEx0AAAAAAIrBJleit2zZMt55551o1apVtGjRIkpKSvLu+/HHH9fU/AAAAAAAYNsP0W+++ebYcccds9/HjBmzJecEAAAAAACFFaKffvrpVf4OAAAAAAB1VbV7or/33ntx1VVXxUknnRSLFi3Kxp544on485//XJPzAwAAAACAwgrRn3nmmTjggAPi5ZdfjocffjhWrFiRjb/xxhsxYsSImp4jAAAAAAAUTog+dOjQuOGGG+Kpp56KBg0alI8fc8wx8dJLL9Xk/AAAAAAAoLBC9DfffDNOOOGE9cZbt24dS5YsqYl5AQAAAABAYYbozZs3jwULFqw3/tprr0W7du1qYl4AAAAAAFCYIfqAAQPi8ssvj4ULF0ZJSUmsXbs2Xnjhhbj00ktj4MCBNT9LAAAAAAAolBB95MiR0alTp2jfvn12U9HOnTvHkUceGYcddlhcddVVNT9LAAAAAACoBfWrc1C6mej48ePj6quvjrfeeisL0g866KDYa6+9an6GAAAAAABQSCH6nDlzYs8994zdd989WwAAAAAAoC6qVojesWPH2G233eKoo46Kr33ta9nPNAYAAAAAAFHsPdHnz58fo0aNisaNG8dNN90Ue++9dxaqn3LKKTFhwoSanyUAAAAAABRKiN6uXbssML/jjjti9uzZ2dKzZ8944IEH4pxzzqn5WQIAAAAAQKG0c1m1alU8//zzMW3atGx57bXXolOnTnH++edn7V0AAAAAAKBoQ/TmzZtHixYtsmr0oUOHxle/+tVsHQAAAAAAotjbufTu3Ts+//zzmDhxYrY8+OCD8c4778TWMHbs2OjQoUM0atQounfvHq+88somHZfmWVJSEv3799/icwQAAAAAoIhD9EceeSSWLFkSU6ZMiR49esTvf//7rBq9rFf6lnL//ffHkCFDYsSIETFz5szo0qVL9OrVKxYtWrTB4/7yl7/EpZdems0RAAAAAAC2aIhe5oADDojDDz88C9IPOeSQLMxOQfeWMnr06Bg8eHAMGjQoOnfuHOPGjYsddtgh7rrrrrzHpIr5FOxfe+21seeee26xuQEAAAAAUPfUq26Y/Y1vfCN22mmnrKXKf/zHf8Tee+8dDz30UCxevLjmZxkRa9asiRkzZkTPnj3Lx+rVq5etT58+Pe9x1113XbRu3TrOPPPMTTrP6tWrY/ny5ZUWAAAAAACKU7VuLJpC86OOOirOPvvsrEVKaWlpbGmpfUyqKm/Tpk2l8bQ+a9asKo95/vnn484774zXX399k88zatSorGodAAAAAACqVYn+6quvxk9/+tP4+te/vsEA/bzzzsvC79rwySefxGmnnRbjx4+PVq1abfJxw4YNi2XLlpUv8+fP36LzBAAAAACgjlWib6pf//rX2Q09v0iInU96jO222y4++uijSuNpvW3btuvt/95772U3FO3bt2/52Nq1a7Of9evXj9mzZ8e//Mu/rHdcw4YNswUAAAAAADbrxqIbk8vlauyxGjRoEN26dYupU6dWCsXTerqx6bo6deoUb775ZtbKpWxJfdyPPvro7Pf27dvX2NwAAAAAAKibtmglek0bMmRInH766XHwwQfHoYceGmPGjImVK1fGoEGDsu0DBw6Mdu3aZX3NGzVqFPvvv3+l45s3b579XHccAAAAAAAKPkQ/8cQTY/HixTF8+PBYuHBhdO3aNaZMmVJ+s9F58+ZFvXpbtLgeAAAAAIAiUlAhenL++ednS1WmTZu2wWPvueeeLTQrAAAAAADqImXbAAAAAABQGyH6qaeeGs2aNduSpwAAAAAAgG2vnctzzz0Xv/zlL+O9996L3/72t9kNPe+9997YY4894ogjjsj2uf3222tyrsBWtEPJ9jFup76V1gEAAACg2FSrEv2hhx6KXr16RePGjeO1116L1atXZ+PLli2LkSNH1vQcgVpQUlISTeo1KF/SOgAAAAAUm2qF6DfccEOMGzcuxo8fH9tv/3/VqYcffnjMnDmzJucHAAAAAACFFaLPnj07jjzyyPXGS0tLY+nSpTUxLwAAAAAAKMwQvW3btvHuu++uN/7888/HnnvuWRPzAgAAALaCXC4XK1asKF/SOgCwmTcWHTx4cFx00UVx1113ZX2SP/zww5g+fXpceumlcfXVV1fnIQEAAIBasHLlyujXr1/5+qRJk6Jp06a1OicAKPgQfejQobF27do49thjY9WqVVlrl4YNG2Yh+gUXXFDzswQAAAAAgEIJ0VP1+ZVXXhmXXXZZ1tYlfd2rc+fOPqkGAAAAAKBOqVaIXqZBgwZZeA4AAAAAAEUdon/zm9/c5Ad9+OGHqzsfAAAAAAAovBC9tLR0y84EAAAAAAAKNUS/++67t+xMAAAAAACgLvVEX7RoUcyePTv7fZ999onWrVvX1LwAAAAAAKDW1avOQcuXL4/TTjst2rVrF0cddVS2pN9PPfXUWLZsWc3PEgAAAAAACiVEHzx4cLz88svx2GOPxdKlS7Ml/f6nP/0pzjnnnJqfJQAAAAAAFEo7lxSYP/nkk3HEEUeUj/Xq1SvGjx8fxx9/fE3ODwAAAAAACqsSfaeddorS0tL1xtNYixYtamJeAAAAAABQmCH6VVddFUOGDImFCxeWj6XfL7vssrj66qtrcn4AAAAAAFBY7Vxuv/32ePfdd2P33XfPlmTevHnRsGHDWLx4cfzyl78s33fmzJk1N1sAAAAAANjWQ/T+/fvX/EwAAAAAAKAuhOgjRoyo+ZkAAAAAAEBdCNErWrFiRaxdu7bSWLNmzTb3YQEAAAAAoDBvLDp37tzo06dPNGnSJEpLS6NFixbZ0rx58+wnAAAAAAAUbSX6qaeeGrlcLu66665o06ZNlJSU1PzMAAAAYBv34YDbotCtXLum0vqCMyZEk3oNopDtOvG82p4CAHVItUL0N954I2bMmBH77LNPzc8IAAAAAAAKuZ3LIYccEvPnz6/52QAAAAAAQKFXok+YMCHOPffc+OCDD2L//feP7bffvtL2Aw88sKbmBwAAAAAAhVWJvnjx4njvvfdi0KBBWVV6165d46CDDir/uSWNHTs2OnToEI0aNYru3bvHK6+8knff8ePHx1e/+tXyG5/27Nlzg/sDAAAAAMBmh+hnnHFGFpZPnz495syZE3Pnzq30c0u5//77Y8iQITFixIiYOXNmdOnSJXr16hWLFi2qcv9p06bFSSedFH/84x+zubZv3z6OO+64rIIeAAAAAAC2SDuX999/Px599NHo2LFjbE2jR4+OwYMHZxXwybhx42Ly5Mlx1113xdChQ9fb/ze/+c16bWgeeuihmDp1agwcOLDKc6xevTpbyixfvrzGnwcAAAAAAHW4Ev2YY46JN954I7amNWvWxIwZM7KWLGXq1auXracq802xatWq+PTTT6Nly5Z59xk1alSUlpaWL6l6HQAAAACA4lStSvS+ffvGxRdfHG+++WYccMAB691Y9Bvf+EbUtCVLlsTnn38ebdq0qTSe1mfNmrVJj3H55ZfHrrvuWimIX9ewYcOyljEVK9EF6QAAAAAAxalaIfq5556b/bzuuuvW21ZSUpKF3duaH/3oRzFx4sSsT3q6KWk+DRs2zBYAAAAAAKhWiL527drY2lq1ahXbbbddfPTRR5XG03rbtm03eOxPf/rTLET/wx/+EAceeOAWnikAAAAAAEXdE702NGjQILp165bdFLRimJ/We/Tokfe4m266Ka6//vqYMmVKHHzwwVtptgAAAAAA1AXVqkRPVq5cGc8880zMmzcvu+lnRRdeeGFsCalX+emnn56F4YceemiMGTMmm8egQYOy7QMHDox27dplNwdNfvzjH8fw4cPjvvvuiw4dOsTChQuz8aZNm2YLAAAAAADUeIj+2muvRe/evWPVqlVZiN2yZcvsxp877LBDtG7deouF6CeeeGIsXrw4C8ZTIN61a9eswrzsZqMp0K9X7/+K62+//fYs4P/2t79d6XFGjBgR11xzzRaZIwAAAAAARR6iX3zxxdG3b98YN25clJaWxksvvRTbb799nHrqqXHRRRfFlnT++ednS1XSTUMr+stf/rJF5wIAAAAAQN1WrZ7or7/+elxyySVZ1Xe62efq1aujffv2Wf/xK664ouZnCQAAAAAAhRKip6rzsrYpqX1LaqOSpKr0+fPn1+wMAQAAAACgkNq5HHTQQfHqq6/GXnvtFUcddVTWozz1RL/33ntj//33r/lZAgBbTS6Xy+55UqZJkyZRUlJSq3MCAACAggrRR44cGZ988kn2+4033hgDBw6M733ve7H33nvHhAkTanqOAMBWlAL0fv36la9PmjQpmjZtWqtzAgAAap4CGtiCIfp+++2XvcnK2rmkG4z+7ne/i86dO0fXrl2r85AAAABALdihZPsYt1PfSutAcVBAA1uwJ3p6c/37v/979vvSpUvjK1/5SowePTr69+8ft99+e3UeEgAAAKgFqeq0Sb0G5YsqVACogRB95syZ8dWvfjX7/be//W20adMm3n///SxY//nPf16dhwQAAAAAgLoRoq9atSp23HHH7Pff//738c1vfjPq1auXVaSnMB0AAAAAAOqCaoXoHTt2jEceeSTmz58fTz75ZBx33HHZ+KJFi6JZs2Y1PUcAAAAAACicEH348OFx6aWXRocOHaJ79+7Ro0eP8qr0gw46qKbnCAAAAAAAtaJ+dQ769re/HUcccUQsWLAgunTpUj5+7LHHxgknnFCT8wMAAAAAgMIK0ZO2bdtmS0WHHnpoTcwJAAAAAAAKt50LAAAAAAAUAyE6AAAAAADkIUQHAAAAAIA8hOgAAAAAAFDTNxYFAAAAgGL14YDbotCtXLum0vqCMyZEk3oNopDtOvG82p4CdZBKdAAAAAAAyEOIDgAAAAAAeQjRAQAAAAAgDyE6AAAAAADkIUQHAAAAAIA8hOgAAAAAAJCHEB0AAAAAAPKon28DAPDFfDjgtqgLVq5dU2l9wRkTokm9BlHIdp14Xm1PoWDkcrlYuXJl+XqTJk2ipKSkVucEAABQm4ToAACUSwF6v379ytcnTZoUTZs2rdU5AQAA1CbtXAAAAAAAIA+V6AAAAABFSis3KF7e/3W4En3s2LHRoUOHaNSoUXTv3j1eeeWVDe7/4IMPRqdOnbL9DzjggHj88ce32lwBAAAACqGVW9lSMVAD6jbv/zoaot9///0xZMiQGDFiRMycOTO6dOkSvXr1ikWLFlW5/4svvhgnnXRSnHnmmfHaa69F//79s+Wtt97a6nMHAADYlivRVqxYUb6kdQDqvh1Kto9xO/UtX9I6UOAh+ujRo2Pw4MExaNCg6Ny5c4wbNy522GGHuOuuu6rc/5Zbbonjjz8+Lrvssth3333j+uuvjy9/+ctx6623bvW5AwAAbKtUogEUp9S6o0m9BuWLVh5Q4D3R16xZEzNmzIhhw4aVj9WrVy969uwZ06dPr/KYNJ4q1ytKleuPPPJI3vOsXr06W8osX768RuYPANRtHw64LeqClWvXVFpfcMaE7P+hKmS7TjyvtqcAQB1VF/733//2Q/V4/xfX+79gQvQlS5bE559/Hm3atKk0ntZnzZpV5TELFy6scv80ns+oUaPi2muvraFZU6z8D3Zxc/2LV1259ulr/NHvP8vXd7nrrGjatGmtzqkQuP4Axamu/PtP8V5//9tf3Nef4r7+3v91tJ3L1pAq3ZctW1a+zJ8/v7anBAAAAABALSmYSvRWrVrFdtttFx999FGl8bTetm3bKo9J419k/6Rhw4bZAgAAUCyaNGkSkyZNqrQOAECBVaI3aNAgunXrFlOnTi0fW7t2bbbeo0ePKo9J4xX3T5566qm8+wMAABSjdCO59PXtssWN5QAACrASPUk3CT399NPj4IMPjkMPPTTGjBmT3TV+0KBB2faBAwdGu3btsr7myUUXXRRHHXVU/OxnP4s+ffrExIkT409/+lPccccdtfxMAAAAAGqfb6JA8fL+r6Mh+oknnhiLFy+O4cOHZzcH7dq1a0yZMqX85qHz5s2LevX+r7j+sMMOi/vuuy+uuuqquOKKK2KvvfaKRx55JPbff/9afBYAAAAA29Y3UYDi4/2/6UpyuVzuC+xfdJYvXx6lpaXZTUabNWtW29MBgK1yh/Z+/fqVr6fKBP9hVTzSfxqmb/pVrEbR1gEAAChmBVWJDgDAlqUaBQAAoEBvLAoAAAAAAFubEB0AAAAAAPIQogMAAAAAQB5CdAAAAAAAyEOIDgAAAAAAeQjRAQAAAAAgj5JcLpfLt5GI5cuXR2lpaSxbtiyaNWtW29MBgC0u/afBypUry9ebNGkSJSUltTonAAAAqC31a+3MAMA2KQXmTZs2re1pAAAAwDZBOxcAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAoNBD9I8//jhOOeWUaNasWTRv3jzOPPPMWLFixQb3v+CCC2KfffaJxo0bx+677x4XXnhhLFu2bKvOGwAAAACAwlUwIXoK0P/85z/HU089FY899lg8++yzcfbZZ+fd/8MPP8yWn/70p/HWW2/FPffcE1OmTMnCdwAAAAAA2BQluVwuF9u4t99+Ozp37hyvvvpqHHzwwdlYCsR79+4df/3rX2PXXXfdpMd58MEH49RTT42VK1dG/fr1N+mY5cuXR2lpaVbBnqrgAQAAAAAoHgVRiT59+vSshUtZgJ707Nkz6tWrFy+//PImP05ZEL6hAH316tVZcF5xAQAAAACgOBVEiL5w4cJo3bp1pbEUhLds2TLbtimWLFkS119//QZbwCSjRo3KKs/Llvbt22/W3AEAAAAAKFy1GqIPHTo0SkpKNrjMmjVrs8+Tqsn79OmTtYS55pprNrjvsGHDsor1smX+/PmbfX4AAAAAAArTpjUG30IuueSS+O53v7vBffbcc89o27ZtLFq0qNL4Z599Fh9//HG2bUM++eSTOP7442PHHXeM3/3ud7H99ttvcP+GDRtmCwAAAAAA1GqIvvPOO2fLxvTo0SOWLl0aM2bMiG7dumVjTz/9dKxduza6d+++wQr0Xr16ZaH4o48+Go0aNarR+QMAAAAAULcVRE/0fffdN6smHzx4cLzyyivxwgsvxPnnnx8DBgyIXXfdNdvngw8+iE6dOmXbywL04447LlauXBl33nlntp76p6fl888/r+VnBAAAAABAIajVSvQv4je/+U0WnB977LFRr169+Na3vhU///nPy7d/+umnMXv27Fi1alW2PnPmzHj55Zez3zt27FjpsebOnRsdOnTYys8AAAAAAIBCU5LL5XK1PYltWapgLy0tzW4y2qxZs9qeDgAAAAAAW1HBVKLXlrLPGFKYDgAAAABA3bLjjjtGSUlJ3u1C9I345JNPsp/t27ev7akAAAAAAFDDNtaFRDuXjVi7dm18+OGHG/00oq5KFfjpA4T58+drZ1OEXP/i5voXN9e/uLn+xcu1L26uf3Fz/Yub61/cXP/i5vr/L5XomyndxHS33XaLYpfeRMX8Rip2rn9xc/2Lm+tf3Fz/4uXaFzfXv7i5/sXN9S9urn9xc/03rN5GtgMAAAAAQNESogMAAAAAQB5CdDaoYcOGMWLEiOwnxcf1L26uf3Fz/Yub61+8XPvi5voXN9e/uLn+xc31L26u/6ZxY1EAAAAAAMhDJToAAAAAAOQhRAcAAAAAgDyE6AAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAAAAAAB5CNEBAAAAACAPIToAAAAAAOQhRAcAAAAAgDyE6AAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAABsUV/72tfiBz/4wRY9x6effhqXX355HHDAAdGkSZPYddddY+DAgfHhhx9u0fMCAFD3CdEBAICCt2rVqpg5c2ZcffXV2c+HH344Zs+eHd/4xjdqe2oAABQ4IToAAGyGtWvXxk033RQdO3aMhg0bxu677x433nhj+fY333wzjjnmmGjcuHHstNNOcfbZZ8eKFSvKt3/3u9+N/v37x8iRI6NNmzbRvHnzuO666+Kzzz6Lyy67LFq2bBm77bZb3H333eXH/OUvf4mSkpKYOHFiHHbYYdGoUaPYf//945lnnqk0t7R+6KGHZvPaZZddYujQodnjVqwQv/DCC+OHP/xhdp62bdvGNddcU+kxli5dGmeddVbsvPPO0axZs+y5vPHGG+Xb0/5du3aNe++9Nzp06BClpaUxYMCA+OSTT8qfX5rHLbfcks05LWn+NS2d96mnnop/+7d/i3322Se+8pWvxK233hozZsyIefPm1fj5AAAoHkJ0AADYDMOGDYsf/ehHWQX0f//3f8d9992XheHJypUro1evXtGiRYt49dVX48EHH4w//OEPcf7551d6jKeffjprO/Lss8/G6NGjY8SIEfH1r389O+7ll1+Oc889N84555z461//Wum4FLJfcskl8dprr0WPHj2ib9++8be//S3b9sEHH0Tv3r3jkEMOyULv22+/Pe6888644YYbKj3Gr371q6z9STpP+jAgBfgpjC7zne98JxYtWhRPPPFEFkh/+ctfjmOPPTY+/vjj8n3ee++9eOSRR+Kxxx7LlhSap9ckSeF5mtvgwYNjwYIF2dK+ffsqX8v0PJs2bbrB5YtYtmxZFtqnDyYAAKC6SnK5XK7aRwMAQBFL1dapQjtVPKdq7XWNHz8+69M9f/78LKhOHn/88SzsTqF5CttTpfa0adNizpw5Ua/e/9a4dOrUKVq3bp2F6snnn3+eVVpPmDAhq/JOldx77LFHFlSnx09ShXkau+CCC7LK8iuvvDIeeuihePvtt7MgObntttuy/VO4nM6VKtHTYz/33HPlc06V66naPD32888/H3369MlC9FTNXiZV3adzpKr6VIn+k5/8JBYuXBg77rhjtj1tS3N/6aWXsvV0nlStPmbMmA2+nuk8y5cv3+A+6dyb4p///Gccfvjh2Wv5m9/8ZpOOAQCAqtSvchQAANioFFCvXr06q8zOt71Lly7lAXqSgt3UAib16y6rWN9vv/3KA/Qkjaf2LGW22267rBVMCpkrShXeZerXrx8HH3xwds6yc6ftZQF62blTK5lU0Z7aziQHHnhgpcdMbV/KzpMq2NP+6dwV/eMf/8iqz8ukNi5lAfq6j/FFpA8O0lITNxlNbV1SvVCqwAcAgM0hRAcAgGpKfc5rwvbbb19pPQXfVY2l8L2mbeg8KUBPgXiqlF9XxRYpNTXX1M7l17/+9Qb3qdhPfkMB+vvvv5+1yUl93AEAYHMI0QEAoJr22muvLEifOnVqle1c9t1337jnnnuy3uhl1egvvPBCVnWebn65uVK7lCOPPLK8nUvqWV7Wbz2dO7VzSdXYZdXo6dypYjzdqHRTpP7nqU1LqnJP1ebV1aBBg6xtzMakfuyXXnpptc9TFqD/z//8T/zxj39cr4IeAACqQ4gOAADV1KhRo6zHeOoBnoLi1C5l8eLF8ec//znOPPPMOOWUU7KbhJ5++ulZ7/C0LfUsP+2008pbuWyOsWPHZkF+Csxvvvnm+Pvf/x5nnHFGtu28887LepCn86VgPbWPSXMZMmRIpdYxG9KzZ8+sJUz//v2zm47uvffeWS/3yZMnxwknnJC1j9kUKYBPNy5NvdzTzUFbtmxZ5Rw2p51LCtC//e1vx8yZM7Obm6bQPn0AkKTzpesDAADVIUQHAIDNcPXVV2eV2sOHD88C5tT+JLUlSXbYYYd48skn46KLLopDDjkkW//Wt74Vo0ePrpFzp5t/puX111/Pbrj56KOPRqtWrbJt7dq1y25ietlll2V92VOQnIL9q666apMfP1Wwp8dINykdNGhQ9iFA27Zts+r3L/IhQKouTx8kdO7cOeunPnfu3M2qbK/KBx98kD3/JN3EtKJUlZ5ubgoAANVRkkvf7wQAAApGqujeY4894rXXXlsvMAYAAGrWpn2PEwAAAAAAipAQHQAAAAAA8tDOBQAAAAAA8lCJDgAAAAAAeQjRAQAAAAAgDyE6AAAAAADkIUTfiNQyfvny5dlPAAAAAACKixB9Iz755JMoLS3NfgIAAAAAUFyE6AAAAAAAkIcQHQAAAAAA6kKI/uyzz0bfvn1j1113jZKSknjkkUc2esy0adPiy1/+cjRs2DA6duwY99xzz1aZKwAAAAAAha+gQvSVK1dGly5dYuzYsZu0/9y5c6NPnz5x9NFHx+uvvx4/+MEP4qyzzoonn3xyi88VAAAAAIDCV5LL5XJRgFIl+u9+97vo379/3n0uv/zymDx5crz11lvlYwMGDIilS5fGlClTNuk8y5cvz24sumzZsmjWrFmNzB0AAAAAgMJQUJXoX9T06dOjZ8+elcZ69eqVjeezevXqLDivuAAAAAAAUJzqdIi+cOHCaNOmTaWxtJ6C8X/84x9VHjNq1Kis8rxsad++/VaaLQAAAAAA25o6HaJXx7Bhw7LWLWXL/Pnza3tKAAAAAADUkvpRh7Vt2zY++uijSmNpPfU2b9y4cZXHNGzYMFuISO3y081cyzRp0iTrRQ8AAAAAUCzqdIjeo0ePePzxxyuNPfXUU9k4G5cC9H79+pWvT5o0KZo2bVqrcwIAAAAA2JoKqp3LihUr4vXXX8+WZO7cudnv8+bNK2/FMnDgwPL9zz333JgzZ0788Ic/jFmzZsVtt90WDzzwQFx88cW19hwAAAAAACgcBRWi/+lPf4qDDjooW5IhQ4Zkvw8fPjxbX7BgQXmgnuyxxx4xefLkrPq8S5cu8bOf/SwmTJgQvXr1qrXnAAAAAABA4SjJpcbX5LV8+fIoLS3NbjKaeqkXk1T5r50LAAAAAFDMCqoSHQAAAAAAtiYhOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAABQV0L0sWPHRocOHaJRo0bRvXv3eOWVVza4/5gxY2KfffaJxo0bR/v27ePiiy+Of/7zn1ttvgAAAAAAFK6CCtHvv//+GDJkSIwYMSJmzpwZXbp0iV69esWiRYuq3P++++6LoUOHZvu//fbbceedd2aPccUVV2z1uQMAAAAAUHgKKkQfPXp0DB48OAYNGhSdO3eOcePGxQ477BB33XVXlfu/+OKLcfjhh8fJJ5+cVa8fd9xxcdJJJ220eh0AAAAAAAoqRF+zZk3MmDEjevbsWT5Wr169bH369OlVHnPYYYdlx5SF5nPmzInHH388evfunfc8q1evjuXLl1daAAAAAAAoTvWjQCxZsiQ+//zzaNOmTaXxtD5r1qwqj0kV6Om4I444InK5XHz22Wdx7rnnbrCdy6hRo+Laa6+t8fkDAAAAAFB4CqYSvTqmTZsWI0eOjNtuuy3rof7www/H5MmT4/rrr897zLBhw2LZsmXly/z587fqnAEAAAAA2HYUTCV6q1atYrvttouPPvqo0nhab9u2bZXHXH311XHaaafFWWedla0fcMABsXLlyjj77LPjyiuvzNrBrKthw4bZAgAAAAAABVOJ3qBBg+jWrVtMnTq1fGzt2rXZeo8ePao8ZtWqVesF5SmIT1J7FwAAAAAAqBOV6MmQIUPi9NNPj4MPPjgOPfTQGDNmTFZZPmjQoGz7wIEDo127dllf86Rv374xevToOOigg6J79+7x7rvvZtXpabwsTAcAAAAAgDoRop944omxePHiGD58eCxcuDC6du0aU6ZMKb/Z6Lx58ypVnl911VVRUlKS/fzggw9i5513zgL0G2+8sRafBQAAAAAAhaIkp6/JBi1fvjxKS0uzm4w2a9YsismKFSuiX79+5euTJk2Kpk2b1uqcAAAAAAC2poKqRC8kHw64LQrdyrVrKq0vOGNCNKnXIArZrhPPq+0pAAAAAAAFpGBuLAoAAAAAAFubEB0AAAAAAPIQogMAAAAAQB5CdAAAAAAAyEOIDgAAAAAAeQjRAQAAAAAgDyE6AAAAAADkIUQHAAAAAIA8hOgAAAAAAJCHEB0AAAAAAPIQogMAAAAAQB5CdAAAAAAAyEOIDgAAAAAAedTPtwEobrlcLlauXFm+3qRJkygpKanVOQEAAADA1iZEB6qUAvR+/fqVr0+aNCmaNm1aq3MCAAAAgK1NOxcAAAAAAMhDiA4AAAAAAHkI0QEAAAAAoCZD9ClTpsTzzz9fvj527Njo2rVrnHzyyfH3v/+9Og8JAAAAAAB1I0S/7LLLYvny5dnvb775ZlxyySXRu3fvmDt3bgwZMqSm5wgAAAAAALWifnUOSmF5586ds98feuih+PrXvx4jR46MmTNnZmE6AAAAAAAUbSV6gwYNYtWqVdnvf/jDH+K4447Lfm/ZsmV5hToAAAAAABRlJfoRRxyRtW05/PDD45VXXon7778/G3/nnXdit912q+k5AgAAAABA4VSi33rrrVG/fv347W9/G7fffnu0a9cuG3/iiSfi+OOPr+k5AgAAAABA4VSi77777vHYY4+tN37zzTfXxJwAAAAAAKBwK9G32267WLRo0Xrjf/vb37JtAAAAAABQtCF6Lpercnz16tXZTUcBAAAAAKDo2rn8/Oc/z36WlJTEhAkTomnTpuXbPv/883j22WejU6dOsSWNHTs2fvKTn8TChQujS5cu8Ytf/CIOPfTQvPsvXbo0rrzyynj44Yfj448/ji996UsxZsyY6N279xadJwAAAAAARRail/U8T5Xo48aNq9S6JVWgd+jQIRvfUu6///4YMmRIdo7u3btnYXivXr1i9uzZ0bp16/X2X7NmTfzrv/5rti3dBDXdAPX999+P5s2bb7E5AgAAAABQpCH63Llzs59HH310VtndokWL2JpGjx4dgwcPjkGDBmXrKUyfPHly3HXXXTF06ND19k/jqfr8xRdfjO233z4bS0E/AAAAAABssZ7of/zjH7d6gJ6qymfMmBE9e/YsH6tXr162Pn369CqPefTRR6NHjx7x/e9/P9q0aRP7779/jBw5Mms9k0/q6758+fJKCwAAAAAAxekLVaKXSSH0PffcE1OnTo1FixbF2rVrK21/+umno6YtWbIkO28KwytK67NmzarymDlz5mRzOeWUU+Lxxx+Pd999N84777z49NNPY8SIEVUeM2rUqLj22mtrfP4AAAAAABRJiH7RRRdlIXqfPn2y6u50o9FtUQr3Uz/0O+64I+vf3q1bt/jggw+yG5PmC9GHDRuW9V0vkyrR27dvvxVnDQAAAABAQYfoEydOjAceeCB69+4dW0urVq2yIPyjjz6qNJ7W27ZtW+Uxu+yyS9YLveINUPfdd99YuHBh1h4m3Qx1XQ0bNswWAAAAAACoVk/0FD537Nix5mezkXOmSvLUQqZipXlaT33Pq3L44YdnLVwqtpt55513snC9qgAdAAAAAAA2O0S/5JJL4pZbbolcLhdbU2qzMn78+PjVr34Vb7/9dnzve9+LlStXxqBBg7LtAwcOzNqxlEnbP/7446z9TArPJ0+enN1YNN1oFAAAAAAAaqydyze/+c1K6+mGnU888UTst99+WcuUih5++OHYEk488cRYvHhxDB8+PGvJ0rVr15gyZUr5zUbnzZsX9er93+cCqZf5k08+GRdffHEceOCB0a5duyxQv/zyy7fI/AAAAAAAKNIQvbS0tNL6CSecELXh/PPPz5aqTJs2bb2x1OrlpZde2gozAwAAAACgaEP0u+++e8vOBAAAAAAA6kJPdAAAAAAAKAabXIle0UEHHRQlJSXrjaexRo0aRceOHeO73/1uHH300TUxRwAAAAAAKJxK9OOPPz7mzJkTTZo0yYLytDRt2jTee++9OOSQQ2LBggXRs2fPmDRpUs3PGAAAAAAAtuVK9CVLlsQll1wSV199daXxG264Id5///34/e9/HyNGjIjrr78++vXrV1NzBQAAAACAbT9Ef+CBB2LGjBnrjQ8YMCC6desW48ePj5NOOilGjx5dE3OkluxQsn2M26lvpXUAAAAAgGJSrXYuqe/5iy++uN54GkvbkrVr15b/TmFKPe6b1GtQvlTVBx8AAAAAoC6rViX6BRdcEOeee25WjZ56oCevvvpqTJgwIa644ops/cknn4yuXbvW7GwBAAAAAGBbD9Gvuuqq2GOPPeLWW2+Ne++9NxvbZ599sjYuJ598craeQvbvfe97NTtbAAAAAADY1kP05JRTTsmWfBo3blzdhwYAAAAAgMLtiQ4AAAAAAMVgkyvRW7ZsGe+88060atUqWrRoscGbTH788cc1NT8oSB8OuC0K3cq1ayqtLzhjQnaD2UK268TzansKAAAAANTVEP3mm2+OHXfcMft9zJgxW3JOAAAAAABQWCH66aefXuXvAAAAAABQV1W7J/p7770XV111VZx00kmxaNGibOyJJ56IP//5zzU5PwAAAAAAKKwQ/ZlnnokDDjggXn755Xj44YdjxYoV2fgbb7wRI0aMqOk5AgAAAABA4YToQ4cOjRtuuCGeeuqpaNDg/240eMwxx8RLL71Uk/MDAAAAAIDCCtHffPPNOOGEE9Ybb926dSxZsqQm5gUAAAAAAIUZojdv3jwWLFiw3vhrr70W7dq1q4l5AQAAAABAYYboAwYMiMsvvzwWLlwYJSUlsXbt2njhhRfi0ksvjYEDB9b8LAEAAAAAoFBC9JEjR0anTp2iffv22U1FO3fuHEceeWQcdthhcdVVV9X8LAEAAAAAoBbUr85B6Wai48ePj6uvvjreeuutLEg/6KCDYq+99qr5GQIAAAAAQCGF6HPmzIk999wzdt9992wBAAAAAIC6qFoheseOHWO33XaLo446Kr72ta9lP9MYAAAAAABEsfdEnz9/fowaNSoaN24cN910U+y9995ZqH7KKafEhAkTan6WAAAAAABQKCF6u3btssD8jjvuiNmzZ2dLz54944EHHohzzjmn5mcJAAAAAACF0s5l1apV8fzzz8e0adOy5bXXXotOnTrF+eefn7V3AQAAAACAog3RmzdvHi1atMiq0YcOHRpf/epXs3UAAAAAAIhiD9F79+6dVaJPnDgxFi5cmC2pAj31RgcAAAAAgKLuif7II4/EkiVLYsqUKdGjR4/4/e9/n1Wjl/VK35LGjh0bHTp0iEaNGkX37t3jlVde2aTjUuBfUlIS/fv336LzAwAAAACgyEP0MgcccEAcfvjhWZB+yCGHxKJFi+L++++PLSU99pAhQ2LEiBExc+bM6NKlS/Tq1Ss774b85S9/iUsvvTQL+gEAAAAAYIuG6KNHj45vfOMbsdNOO2XV4P/xH/+RtXJ56KGHYvHixdV5yE0+7+DBg2PQoEHRuXPnGDduXOywww5x11135T3m888/z6rjr7322thzzz03eo7Vq1fH8uXLKy0AAAAAABSnavVET6H5UUcdFWeffXZW3V1aWhpb2po1a2LGjBkxbNiw8rF69epFz549Y/r06XmPu+6666J169Zx5plnxnPPPbfR84waNSoL3AEAAAAAoFoh+quvvrpJ+5133nlZiN2qVavYXKkHe6oqb9OmTaXxtD5r1qwqj0k3P73zzjvj9ddf3+TzpJA+tYwpkyrR27dvvxkzBwAAAACgKHuib8yvf/3rWmuH8sknn8Rpp50W48eP/0IhfsOGDaNZs2aVFgAAAAAAilO1KtE3VS6Xq7HHSkH4dtttFx999FGl8bTetm3b9fZ/7733shuK9u3bt3xs7dq12c/69evH7Nmz41/+5V9qbH4AAAAAANQ9W7QSvSY1aNAgunXrFlOnTq0Uiqf1Hj16rLd/p06d4s0338xauZQt6WaoRx99dPa7Fi0AAAAAANRqJXpNS73KTz/99Dj44IPj0EMPjTFjxsTKlStj0KBB2faBAwdGu3btspuDNmrUKPbff/9Kxzdv3jz7ue44AAAAAAAUfIh+4oknxuLFi2P48OGxcOHC6Nq1a0yZMqX8ZqPz5s2LevUKprgeAAAAAIBtXEGF6Mn555+fLVWZNm3aBo+95557ttCsAAAAAACoi7ZoiH7qqadGs2bNtuQpAIAtcGPw1C6tTJMmTaKkpKRW5wQAAAC1pdq9T5577rksJE839fzggw+ysXvvvTeef/758n1uv/32aNWqVc3MFADYKlKA3q9fv/KlYqAOAAAAxaZaIfpDDz0UvXr1isaNG8drr70Wq1evzsaXLVsWI0eOrOk5AgAAAABA4YToN9xwQ4wbNy7Gjx8f22+/ffn44YcfHjNnzqzJ+QEAAAAAQGGF6LNnz44jjzxyvfHS0tJYunRpTcwLAAAAAAAKM0Rv27ZtvPvuu+uNp37oe+65Z03MCwAAAAAACjNEHzx4cFx00UXx8ssvR0lJSXz44Yfxm9/8Ji699NL43ve+V/OzBAAAAACAWlC/OgcNHTo01q5dG8cee2ysWrUqa+3SsGHDLES/4IILan6WwFa3Q8n2MW6nvpXWAQAAAKDYVCtET9XnV155ZVx22WVZW5cVK1ZE586do2nTpjU/Q6BWpPd5k5IGtT0NAAAAACi8EL1MgwYNsvAcAAAAAACKOkT/5je/uckP+vDDD1d3PgAAAAAAUHghemlp6ZadCQAAAAAAFGqIfvfdd2/ZmQAAAAAAQF3qib5o0aKYPXt29vs+++wTrVu3rql5AQAAAABAratXnYOWL18ep512WrRr1y6OOuqobEm/n3rqqbFs2bKanyUAAAAAABRKiD548OB4+eWX47HHHoulS5dmS/r9T3/6U5xzzjk1P0sAAAAAACiUdi4pMH/yySfjiCOOKB/r1atXjB8/Po4//vianB8AAAAAABRWJfpOO+0UpaWl642nsRYtWtTEvAAAAAAAoDBD9KuuuiqGDBkSCxcuLB9Lv1922WVx9dVX1+T8AAAAAACgsNq53H777fHuu+/G7rvvni3JvHnzomHDhrF48eL45S9/Wb7vzJkza262AAAAAACwrYfo/fv3r/mZAAAAAABAXQjRR4wYUfMzAQAAAACAuhCiV7RixYpYu3ZtpbFmzZpt7sMCAAAAAEBh3lh07ty50adPn2jSpEmUlpZGixYtsqV58+bZTwAAAAAAKNpK9FNPPTVyuVzcdddd0aZNmygpKan5mQEAAAAAQCGG6G+88UbMmDEj9tlnn5qfEQAAAAAAFHI7l0MOOSTmz59f87MBAAAAAIBCr0SfMGFCnHvuufHBBx/E/vvvH9tvv32l7QceeGBNzQ8AAAAAAAqrEn3x4sXx3nvvxaBBg7Kq9K5du8ZBBx1U/nNLGjt2bHTo0CEaNWoU3bt3j1deeSXvvuPHj4+vfvWr5Tc+7dmz5wb3BwAAAACAzQ7RzzjjjCwsnz59esyZMyfmzp1b6eeWcv/998eQIUNixIgRMXPmzOjSpUv06tUrFi1aVOX+06ZNi5NOOin++Mc/ZnNt3759HHfccVkFPQAAAAAAbJF2Lu+//348+uij0bFjx9iaRo8eHYMHD84q4JNx48bF5MmT46677oqhQ4eut/9vfvOb9drQPPTQQzF16tQYOHDgVps3AAAAAABFVIl+zDHHxBtvvBFb05o1a2LGjBlZS5Yy9erVy9ZTlfmmWLVqVXz66afRsmXLvPusXr06li9fXmkBAAAAAKA4VasSvW/fvnHxxRfHm2++GQcccMB6Nxb9xje+ETVtyZIl8fnnn0ebNm0qjaf1WbNmbdJjXH755bHrrrtWCuLXNWrUqLj22ms3e74AAAAAABRpiH7uuedmP6+77rr1tpWUlGRh97bmRz/6UUycODHrk55uSprPsGHDsr7rZVIleuqlDgAAAABA8alWiL527drY2lq1ahXbbbddfPTRR5XG03rbtm03eOxPf/rTLET/wx/+EAceeOAG923YsGG2AAAAAABAtXqi14YGDRpEt27dspuCVgzz03qPHj3yHnfTTTfF9ddfH1OmTImDDz54K80WAAAAAICirURPVq5cGc8880zMmzcvu+lnRRdeeGFsCanNyumnn56F4YceemiMGTMmm8egQYOy7QMHDox27dplfc2TH//4xzF8+PC47777okOHDrFw4cJsvGnTptkCAAAAAAA1HqK/9tpr0bt371i1alUWYrds2TK78ecOO+wQrVu33mIh+oknnhiLFy/OgvEUiHft2jWrMC+72WgK9OvV+7/i+ttvvz0L+L/97W9XepwRI0bENddcs0XmCAAAAABAkYfoF198cfTt2zfGjRsXpaWl8dJLL8X2228fp556alx00UWxJZ1//vnZUpV009CK/vKXv2zRuQAAAAAAULdVqyf666+/HpdccklW9Z1u9rl69epo37591n/8iiuuqPlZAgAAAABAoYToqeq8rG1Kat+S2qgkqSp9/vz5NTtDALa6XC4XK1asKF/SOgAAAEAxqlY7l4MOOiheffXV2GuvveKoo47KepSnnuj33ntv7L///jU/SwC2qnS/i379+pWvT5o0yQ2ZAaAOSx+Yp//9L9OkSZMoKSmp1TkBABR0JfrIkSNjl112yX6/8cYbo0WLFvG9730vC9J/+ctf1vQcAQAA2AofoJctFQN1AIBiV61K9P3226/8q/2pnUu6wejvfve76Ny5c3Tt2rWm5wgAAAAAAIVTiZ4qE/793/89+33p0qXxla98JUaPHh39+/eP22+/vabnCAAAAAAAhROiz5w5M7761a9mv//2t7+NNm3axPvvv58F6z//+c9reo4AAAAAAFA47VxWrVoVO+64Y/b773//+/jmN78Z9erVyyrSU5gOAAAAFAY3lgWALVCJ3rFjx3jkkUdi/vz58eSTT8Zxxx2XjS9atCiaNWtWnYcEAAAAaoEbywLAFgjRhw8fHpdeeml06NAhunfvHj169CivSj/ooIOq85AAAAAAAFA32rl8+9vfjiOOOCIWLFgQXbp0KR8/9thj44QTTqjJ+QEAAAAAQGGF6Enbtm2zpaJDDz20JuYEAAAAAACF284FAAAAAACKgRAdAAAAAABqup0LAABQd+RyuVi5cmX5epMmTaKkpKRW5wQAANsCIToA1JAPB9wWdcHKtWsqrS84Y0I0qdcgCtmuE8+r7SnANi8F6P369StfnzRpUjRt2rRW5wQAANsC7VwAAAAAACAPlegAAJTT0gMAAKAyIToAAOW09AAAAKhMiA4AAFDk98Soi/fDSNwTAzbOt9AANk6IDgAAAFCkfAsNYOPcWBQAAAAAAPIQogMAAAAAQB5CdAAAAAAAyEOIDgAAAAAAebixKAAAAABAkcnlctnNhcs0adIkSkpKanVO2yohOgAAAABAkUkBer9+/crXJ02aFE2bNq3VOW2rhOgANezDAbdFoVu5dk2l9QVnTIgm9RpEIdt14nm1PQUAAACgABVcT/SxY8dGhw4dolGjRtG9e/d45ZVXNrj/gw8+GJ06dcr2P+CAA+Lxxx/fanMFAAAAAKCwFVQl+v333x9DhgyJcePGZQH6mDFjolevXjF79uxo3br1evu/+OKLcdJJJ8WoUaPi61//etx3333Rv3//mDlzZuy///618hwAAKh7fAtp2+WbSGxp3v/bJu992DR6YkMdDNFHjx4dgwcPjkGDBmXrKUyfPHly3HXXXTF06ND19r/lllvi+OOPj8suuyxbv/766+Opp56KW2+9NTsWAKCm1IUQJRGkAAAUDz2xoY6F6GvWrIkZM2bEsGHDysfq1asXPXv2jOnTp1d5TBpPlesVpcr1Rx55JO95Vq9enS1lli9fXiPzBwAAAOqWuvAhug/QoXq8/4vr/V8wIfqSJUvi888/jzZt2lQaT+uzZs2q8piFCxdWuX8azye1frn22ms3e77+wS5urn9xqwvXf8WKFRH9/rN8fZe7zlKNUCTXPnH9q8f1L2514fq79tXn+hc317+4uf5QvLz/i0vB3Vh0S0uV7suWLStf5s+fX9tTAgAAAACglhRMJXqrVq1iu+22i48++qjSeFpv27Ztlcek8S+yf9KwYcNsAQAAAACAgqlEb9CgQXTr1i2mTp1aPrZ27dpsvUePHlUek8Yr7p+kG4vm2x8AAAAAikWTJk2ym4mWLWkdKOBK9CTdJPT000+Pgw8+OA499NAYM2ZMdhfhQYMGZdsHDhwY7dq1y/qaJxdddFEcddRR8bOf/Sz69OkTEydOjD/96U9xxx131PIzAQAA2PZClIrrANR9JSUlemBDXQvRTzzxxFi8eHEMHz48uzlo165dY8qUKeU3D503b17Uq/d/xfWHHXZY3HfffXHVVVfFFVdcEXvttVc88sgjsf/++9fiswAAANi2CFEAAOpIiJ6cf/752VKVadOmrTf2ne98J1sAAAAAAPhfvolWh0N0AAAAAAA2j2+i1cEbiwIAAAAAwNYmRAcAAAAAgDy0cwEAAAAoUnoiA2ycEB0AAACgSOmJDLBxQnQAAMqpRgMAAKhMiA4AQDnVaMXLBygAAFA1IToAAOADFAAAyKNevg0AAAAAAFDshOgAAAAAAJCHEB0AAAAAAPLQEx0AAACKmBsLA8CGCdEBAACgiLmxMABsmHYuAAAAAACQh0p0ANbjK70AAAAA/0uIDsB6fKUXAAAA4H9p5wIAAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyEKIDAAAAAEAeQnQAAAAAAMhDiA4AAAAAAHkI0QEAAAAAIA8hOgAAAAAA5CFEBwAAAACAPIToAAAAAABQ6CH6xx9/HKeccko0a9YsmjdvHmeeeWasWLFig/tfcMEFsc8++0Tjxo1j9913jwsvvDCWLVu2VecNAAAAAEDhKpgQPQXof/7zn+Opp56Kxx57LJ599tk4++yz8+7/4YcfZstPf/rTeOutt+Kee+6JKVOmZOE7AAAAAABsipJcLpeLbdzbb78dnTt3jldffTUOPvjgbCwF4r17946//vWvseuuu27S4zz44INx6qmnxsqVK6N+/fpV7rN69epsKbN8+fJo3759VsGequABoK5L/2mQ/reyTJMmTaKkpKRW5wQAAAC1pSAq0adPn561cCkL0JOePXtGvXr14uWXX97kxykLwvMF6MmoUaOitLS0fEkBOgAUkxSYN23atHwRoAMAAFDMCiJEX7hwYbRu3brSWArCW7ZsmW3bFEuWLInrr79+gy1gkmHDhmVhe9kyf/78zZo7AAAAAACFq1ZD9KFDh2bVbRtaZs2atdnnSS1Z+vTpk7WEueaaaza4b8OGDbNq9YoLAAAAAADFKX9fk63gkksuie9+97sb3GfPPfeMtm3bxqJFiyqNf/bZZ/Hxxx9n2zbkk08+ieOPPz523HHH+N3vfhfbb799jcwdAAAAAIC6r1ZD9J133jlbNqZHjx6xdOnSmDFjRnTr1i0be/rpp2Pt2rXRvXv3DVag9+rVK6suf/TRR6NRo0Y1On8AAAAAAOq2guiJvu+++2bV5IMHD45XXnklXnjhhTj//PNjwIABseuuu2b7fPDBB9GpU6dse1mAftxxx8XKlSvjzjvvzNZT//S0fP7557X8jAAAAAAAKAS1Won+RfzmN7/JgvNjjz026tWrF9/61rfi5z//efn2Tz/9NGbPnh2rVq3K1mfOnBkvv/xy9nvHjh0rPdbcuXOjQ4cOW/kZAAAAAABQaEpyuVyutiexLVu2bFk0b9485s+f7yajAAAAAAB1TLqfZklJSeFXoteWdGPSpH379rU9FQAAAAAAtkAh9YYKqFWib0S6eemHH3640U8j6qrUSz59gKASvzi5/sXN9S9urn9xc/2Ll2tf3Fz/4ub6FzfXv7i5/sXN9f9fKtE3U+q/vttuu0WxS2+iYn4jFTvXv7i5/sXN9S9urn/xcu2Lm+tf3Fz/4ub6FzfXv7i5/htWbyPbAQAAAACgaAnRAQAAAAAgDyE6G9SwYcMYMWJE9pPi4/oXN9e/uLn+xc31L16ufXFz/Yub61/cXP/i5voXN9d/07ixKAAAAAAA5KESHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAAAAAAB5CNEBAAAAACAPIToAAAAAAOQhRAcAAAAAgDyE6AAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAAAAAAB5CNEBAAAAACAPIToAAAAAAOQhRAcAAAAAgDyE6AAAwBb1ta99LX7wgx9s8fNcc8010alTp2jSpEm0aNEievbsGS+//PIWPy8AAHWbEB0AAKgT9t5777j11lvjzTffjOeffz46dOgQxx13XCxevLi2pwYAQAETogMAwGZYu3Zt3HTTTdGxY8do2LBh7L777nHjjTeWb0+B7jHHHBONGzeOnXbaKc4+++xYsWJF+fbvfve70b9//xg5cmS0adMmmjdvHtddd1189tlncdlll0XLli1jt912i7vvvrv8mL/85S9RUlISEydOjMMOOywaNWoU+++/fzzzzDOV5pbWDz300Gxeu+yySwwdOjR73IoV4hdeeGH88Ic/zM7Ttm3brJq7oqVLl8ZZZ50VO++8czRr1ix7Lm+88Ub59rR/165d4957781C69LS0hgwYEB88skn5c8vzeOWW27J5pyWNP8t4eSTT86qz/fcc8/Yb7/9YvTo0bF8+fL4r//6ry1yPgAAioMQHQAANsOwYcPiRz/6UVx99dXx3//933HfffdlYXiycuXK6NWrV9Za5NVXX40HH3ww/vCHP8T5559f6TGefvrp+PDDD+PZZ5/Ngt8RI0bE17/+9ey41I7k3HPPjXPOOSf++te/VjouheyXXHJJvPbaa9GjR4/o27dv/O1vf8u2ffDBB9G7d+845JBDstD79ttvjzvvvDNuuOGGSo/xq1/9Kmt/ks6TPgxIAf5TTz1Vvv073/lOLFq0KJ544omYMWNGfPnLX45jjz02Pv744/J93nvvvXjkkUfisccey5YUmqfXJEnheZrb4MGDY8GCBdnSvn37Kl/L9DybNm26wWVTrVmzJu64444s1O/SpcsmHwcAAOsqyeVyufVGAQCAjUrV1qlCO7UQSdXa6xo/fnxcfvnlMX/+/CyoTh5//PEs7E6heQrbU6X2tGnTYs6cOVGv3v/WuKS+3q1bt85C9eTzzz/PwuAJEyZkVd6pknuPPfbIgur0+EmqME9jF1xwQVZZfuWVV8ZDDz0Ub7/9dlb9ndx2223Z/suWLcvOlSrR02M/99xz5XNOleup2jw9dmqJ0qdPnyxET9XsZVLVfTpHqqpPleg/+clPYuHChbHjjjtm29O2NPeXXnopW0/nSdXqY8aM2eDrmc6TKsc3JJ17Q1KIn16jVatWZdX3KdxPHyQAAEB11a/2kQAAUORSQL169eqsMjvf9lQFXRagJ4cffnjWAmb27NnlFeup9UhZgJ6k8dSepcx2222XtYJJIXNFqcK7TP369ePggw/Ozll27rS9LEAvO3dqJZMq2lPbmeTAAw+s9JgpeC47T6pgT/unc1f0j3/8I6s+L5PauJQF6Os+xheRPjhIy+Y4+uij4/XXX48lS5ZkH2L827/9W1Zlv7mPCwBA8RKiAwBANaU+5zVh++23r7Segu+qxlL4XtM2dJ4UoKdAPFXKryv1bt+Ux/giUjuXX//61xvcp2I/+aqkDyxStXpavvKVr8Ree+2VtbFJbXcAAKA6hOgAAFBNKaBNQfrUqVOrbOey7777xj333JP1Ri+rRn/hhReyqvN99tlns8+f2qUceeSR5e1cUs/ysn7r6dypnUvq3lhWjZ7OnSrG041KN0Xqf57atKQq91RtXl0NGjTI2sZsTOrHfumll0ZNSmF++rYAAABUlxAdAACqqVGjRlmP8dQDPAXFqV3K4sWL489//nOceeaZccopp2Q3CT399NOz3uFpW+pZftppp5W3ctkcY8eOzYL8FJjffPPN8fe//z3OOOOMbNt5552X9SBP50vBemofk+YyZMiQSq1jNqRnz55ZS5j+/ftnNx3de++9s17ukydPjhNOOCFrH7MpUgCfWqqkXu7p5qAtW7ascg6b084lfVBx4403xje+8Y2sej61c0mvT7rBaro5KgAAVJcQHQAANsPVV1+dVWoPHz48C5hTgJvakiQ77LBDPPnkk3HRRRdlN7dM69/61rdi9OjRNXLudPPPtKQe4Kl9yaOPPhqtWrXKtrVr1y67ielll12W9WVPwXUK9q+66qpNfvxUwZ4eI92kdNCgQdmHAG3bts2q37/IhwCpujx9kNC5c+esn/rcuXM3q7K9Kqlv/KxZs+JXv/pVFqCnPu7pNU83TU095wEAoLpKcun7nQAAQMFIFd177LFHvPbaa9G1a9fang4AANRpm/Y9TgAAAAAAKEJCdAAAAAAAyEM7FwAAAAAAyEMlOgAAAAAA5CFEBwAAAACAPIToG5G63Sxfvjz7CQAAAABAcRGib8Qnn3wSpaWl2U8AAAAAAIqLEB0AAAAAAPIQogMAAAAAQF0I0Z999tno27dv7LrrrlFSUhKPPPLIRo+ZNm1afPnLX46GDRtGx44d45577tkqcwUAAAAAoPAVVIi+cuXK6NKlS4wdO3aT9p87d2706dMnjj766Hj99dfjBz/4QZx11lnx5JNPbvG5AgAAAABQ+EpyuVwuClCqRP/d734X/fv3z7vP5ZdfHpMnT4633nqrfGzAgAGxdOnSmDJlyiadZ/ny5dmNRZctWxbNmjWrkbkDAAAAAFAYCqoS/YuaPn169OzZs9JYr169svF8Vq9enQXnFRcAAAAAAIpTnQ7RFy5cGG3atKk0ltZTMP6Pf/yjymNGjRqVVZ6XLe3bt99KswUAAAAAYFtTp0P06hg2bFjWuqVsmT9/fm1PCQAAAACAWlI/6rC2bdvGRx99VGksrafe5o0bN67ymIYNG2YLAAAAAADU6Ur0Hj16xNSpUyuNPfXUU9k4AAAAAADUqRB9xYoV8frrr2dLMnfu3Oz3efPmlbdiGThwYPn+5557bsyZMyd++MMfxqxZs+K2226LBx54IC6++OJaew4AAAAAABSOggrR//SnP8VBBx2ULcmQIUOy34cPH56tL1iwoDxQT/bYY4+YPHlyVn3epUuX+NnPfhYTJkyIXr161dpzAAAAAACgcJTkcrlcbU9iW7Z8+fIoLS3NbjKaeqkDAAAAAFA8CqoSHQAAAAAAtiYhOgAAAAAA5CFEBwAAAACAPIToAAAAAACQhxAdAAAAAADyqJ9vA1DccrlcrFy5sny9SZMmUVJSUqtzAgAAAICtTYgOVCkF6P369StfnzRpUjRt2rRW5wQAAAAAW5t2LgAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAAAAAAB5CNEBAAAAACAPIToAAAAAAOQhRAcAAAAAgDyE6AAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AAAAAADIQ4gOAAAAAAB5CNEBAAAAACAPIToAAAAAAOQhRAcAAAAAgDyE6AAAAAAAkIcQHQAAAAAA8hCiAwAAAABAHkJ0AOD/Z+9foKyu6/3x/zWD3JyRASRAEQ8aJiIKhMIXL5nKERdKoKcWeMOw8BZmgiYoF69QVkQlSoJox/KA5gX/onih0EwUBfVoR3ApKKQgEMHI0AFj5r8+n/ObiQk20riHYc9+PNb6rNmf9/589n4NOzWe85rXGwAAAMhAiA4AAAAAABkI0QEAAAAAoL6E6FOmTIkOHTpEkyZNolevXrFw4cJdXj958uQ4/PDDo2nTptG+ffu46qqr4n//93/3WL0AAAAAAOSunArRZ82aFSNGjIjx48fH4sWLo2vXrtG3b99Ys2bNTq+///77Y9SoUen1b7/9dtx9993pa1x33XV7vHYAAAAAAHJPToXokyZNimHDhsXQoUOjc+fOMXXq1Nh3331jxowZO73+xRdfjOOPPz7OPffctHv9tNNOi3POOWeX3etbtmyJ0tLSagcAAAAAAPkpZ0L0rVu3xqJFi6JPnz5Va4WFhen5ggULdnrPcccdl95TGZovW7YsnnjiiejXr1/G95k4cWKUlJRUHckIGAAAAAAA8tM+kSPWrVsX27ZtizZt2lRbT86XLFmy03uSDvTkvhNOOCEqKiri73//e1x66aW7HOcyevTodGRMpaQTXZAOAAAAAJCfcqYTvSbmz58fEyZMiDvuuCOdof7www/HnDlz4uabb854T+PGjaNZs2bVDgAAAAAA8lPOdKK3atUqGjRoEB9//HG19eS8bdu2O71n7NixccEFF8S3v/3t9Pyoo46KsrKyuPjii+P6669Px8EAAAAAAEAmOZMiN2rUKHr06BHz5s2rWisvL0/Pe/fuvdN7Nm/evENQngTxiWS8CwAAAAAA1ItO9EQyq/zCCy+MY445Jnr27BmTJ09OO8uHDh2aPj9kyJBo165dujloon///jFp0qTo3r179OrVK9599920Oz1ZrwzTAQAAAACgXoTogwYNirVr18a4ceNi9erV0a1bt5g7d27VZqMrVqyo1nk+ZsyYKCgoSL9++OGH8YUvfCEN0G+99dY6/C4AAAAAAMgVBRXmmuxSaWlplJSUxMaNG20ySl7ZtGlTDBgwoOp89uzZUVxcXKc1AQAAAMCeljMz0QEAAAAAYE8TogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyGCfTE8ANffR4Dsi15WVb612vuqi6VFU2Chy2YEzL6/rEgAAAADIMTrRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyGaIPnfu3HjhhReqzqdMmRLdunWLc889N/7617/W5CUBAAAAAKB+hOjXXHNNlJaWpo/ffPPNGDlyZPTr1y+WL18eI0aMyHaNAAAAAABQJ/apyU1JWN65c+f08UMPPRRnnnlmTJgwIRYvXpyG6QAAAAAAkLed6I0aNYrNmzenj5999tk47bTT0sctW7as6lAHAAAAAIC87EQ/4YQT0rEtxx9/fCxcuDBmzZqVrr/zzjtx0EEHZbtGAAAAAADInU7022+/PfbZZ5/47W9/G3feeWe0a9cuXX/yySfj9NNPz3aN1JGKiorYtGlT1ZGcAwAAAADkkxp1oh988MHx+OOP77D+05/+NBs1sZcoKyuLAQMGVJ3Pnj07iouL67QmAAAAAIC9vhO9QYMGsWbNmh3W//KXv6TPAQAAAABA3obomcZ6bNmyJd10FAAAAAAA8m6cy89//vP0a0FBQUyfPr3aaI9t27bF888/H506dYraNGXKlPjRj34Uq1evjq5du8YvfvGL6NmzZ8brN2zYENdff308/PDDsX79+vi3f/u3mDx5cvTr169W6wQAAAAAIM9C9MqZ50kn+tSpU6uNbkk60Dt06JCu15ZZs2bFiBEj0vfo1atXGob37ds3li5dGq1bt97h+q1bt8a///u/p88lm6AmG6B+8MEH0bx581qrEQAAAACAPA3Rly9fnn49+eST087uFi1axJ40adKkGDZsWAwdOjQ9T8L0OXPmxIwZM2LUqFE7XJ+sJ93nL774YjRs2DBdS4L+XUlG0iRHpdLS0qx/HwAAAAAA1OOZ6L///e/3eICedJUvWrQo+vTpU7VWWFiYni9YsGCn9zz22GPRu3fv+M53vhNt2rSJLl26xIQJE9LRM5lMnDgxSkpKqo727dvXyvcDAAAAAEA960SvlITQ9957b8ybNy/WrFkT5eXl1Z7/3e9+F9m2bt269H2TMHx7yfmSJUt2es+yZcvSWs4777x44okn4t13343LL788Pv300xg/fvxO7xk9enQ6Mmb7TnRBOgAAAABAfqpRiH7llVemIfoZZ5yRdncnG43ujZJwP5mHftddd6Xz23v06BEffvhhujFpphC9cePG6QEAAAAAADUK0WfOnBkPPPBA9OvXL/aUVq1apUH4xx9/XG09OW/btu1O7znggAPSWejbb4B6xBFHxOrVq9PxMMlmqAAAAAAAkNWZ6En43LFjx9iTkvdMOsmTETLbd5on58nc8505/vjj0xEu24+beeedd9JwXYAOAAAAAECthOgjR46Mn/3sZ1FRURF7UjKrfNq0afGrX/0q3n777bjsssuirKwshg4dmj4/ZMiQdKZ5peT59evXp+NnkvB8zpw56caiyUajAAAAAACQtXEuZ599drXzZMPOJ598Mo488sh0ZMr2Hn744agNgwYNirVr18a4cePSkSzdunWLuXPnVm02umLFiigs/MfPBZINQZ966qm46qqr4uijj4527dqlgfq1115bK/UBAAAAAJCnIXpJSUm187POOivqwvDhw9NjZ+bPn7/DWjLq5aWXXtoDlQEAAAAAkLch+j333FO7lQAAAAAAQH2YiQ4AAAAAAPlgtzvRt9e9e/coKCjYYT1Za9KkSXTs2DG++c1vxsknn5yNGgEAAAAAIHc60U8//fRYtmxZFBUVpUF5chQXF8d7770Xxx57bKxatSr69OkTs2fPzn7FAAAAAACwN3eir1u3LkaOHBljx46ttn7LLbfEBx98EE8//XSMHz8+br755hgwYEC2agUAAAAAgL2/E/2BBx6Ic845Z4f1wYMHp88lkueXLl36+SsEAAAAAIBcCtGTuecvvvjiDuvJWvJcory8vOoxAAAAAADkzTiXK664Ii699NJYtGhROgM98corr8T06dPjuuuuS8+feuqp6NatW3arBQAAAACAvT1EHzNmTBxyyCFx++23x3333ZeuHX744TFt2rQ499xz0/MkZL/sssuyWy0AAAAAAOztIXrivPPOS49MmjZtWtOXBgAAAACA3J2JDgAAAAAA+WC3O9FbtmwZ77zzTrRq1SpatGgRBQUFGa9dv359tuoDAAAAAIC9P0T/6U9/Gvvtt1/6ePLkybVZEwAAAAAA5FaIfuGFF+70MQAAAAAA1Fc1non+3nvvxZgxY+Kcc86JNWvWpGtPPvlk/OlPf8pmfQAAAAAAkFsh+nPPPRdHHXVUvPzyy/Hwww/Hpk2b0vU33ngjxo8fn+0aAQAAAAAgd0L0UaNGxS233BLPPPNMNGrUqGr9lFNOiZdeeimb9QEAAAAAQG6F6G+++WacddZZO6y3bt061q1bl426AAAAAAAgdzYW3V7z5s1j1apVccghh1Rbf+2116Jdu3bZqg2oQ/sWNIyp+/evdg4AAAAA+aZGneiDBw+Oa6+9NlavXh0FBQVRXl4ef/zjH+Pqq6+OIUOGZL9KYI9L/tkuKmxUdSTnAAAAAJBvahSiT5gwITp16hTt27dPNxXt3LlzfOUrX4njjjsuxowZk/0qAQAAAAAgV8a5JJuJTps2LcaOHRtvvfVWGqR37949DjvssOxXmKM+GnxH5Lqy8q3VzlddND3tSM5lB868vK5LAAAAAADqe4i+bNmyOPTQQ+Pggw9ODwAAAAAAqI9qFKJ37NgxDjrooDjppJPiq1/9avo1WQMAAAAAgMj3megrV66MiRMnRtOmTeO2226LL33pS2moft5558X06dOzXyUAAAAAAORKiN6uXbs0ML/rrrti6dKl6dGnT5944IEH4pJLLsl+lQAAAAAAkCvjXDZv3hwvvPBCzJ8/Pz1ee+216NSpUwwfPjwd7wIAAAAAAHkbojdv3jxatGiRdqOPGjUqTjzxxPQcAAAAAAAi38e59OvXL7Zt2xYzZ85MjwcffDDeeeed2BOmTJkSHTp0iCZNmkSvXr1i4cKFu3VfUmdBQUEMHDiw1msEAAAAACCPQ/RHH3001q1bF3Pnzo3evXvH008/nXajV85Kry2zZs2KESNGxPjx42Px4sXRtWvX6Nu3b6xZs2aX973//vtx9dVXpzUCAAAAAECthuiVjjrqqDj++OPTIP3YY49Nw+wk6K4tkyZNimHDhsXQoUOjc+fOMXXq1Nh3331jxowZGe9JOuaTYP/GG2+MQw89tNZqAwAAyFUVFRWxadOmqiM5BwDgc4ToSZj9ta99Lfbff/90pMp//dd/xZe+9KV46KGHYu3atVEbtm7dGosWLYo+ffpUrRUWFqbnCxYsyHjfTTfdFK1bt45vfetbu/U+W7ZsidLS0moHAABAfVZWVhYDBgyoOpJzAAA+x8aiSWh+0kknxcUXX5yOSCkpKYnaloyPSbrK27RpU209OV+yZMlO73nhhRfi7rvvjtdff32332fixIlp1zoAAAAAANSoE/2VV16JH//4x3HmmWfuMkC//PLL0/C7LnzyySdxwQUXxLRp06JVq1a7fd/o0aNj48aNVcfKlStrtU4AAAAAAOpZJ/ru+vWvf51u6PmvhNiZJK/RoEGD+Pjjj6utJ+dt27bd4fr33nsv3VC0f//+VWvl5eXp13322SeWLl0aX/ziF3e4r3HjxukBAAAAAACfa2PRz5LNzWgaNWoUPXr0iHnz5lULxZPzZGPTf9apU6d4880301EulUcyx/3kk09OH7dv3z5rtQEAAAAAUD/Vaid6to0YMSIuvPDCOOaYY6Jnz54xefLkdMOboUOHps8PGTIk2rVrl841b9KkSXTp0qXa/c2bN0+//vM6AAAAAADkfIg+aNCgWLt2bYwbNy5Wr14d3bp1i7lz51ZtNrpixYooLKzV5noAAAAAAPJIToXoieHDh6fHzsyfP3+X99577721VBUAAAAAAPWRtm0AAAAAAKiLEP3888+PZs2a1eZbAAAAAADA3hei/+EPf0hD8t69e8eHH36Yrt13333xwgsvVF1z5513RqtWrbJTKQAAAAAA5EKI/tBDD0Xfvn2jadOm8dprr8WWLVvS9Y0bN8aECROyXSMAAAAAAOROiH7LLbfE1KlTY9q0adGwYcOq9eOPPz4WL16czfoAAAAAACC3QvSlS5fGV77ylR3WS0pKYsOGDdmoCwAAAAAAcjNEb9u2bbz77rs7rCfz0A899NBs1AUAAAAAALkZog8bNiyuvPLKePnll6OgoCA++uij+M1vfhNXX311XHbZZdmvEgAAAAAA6sA+Nblp1KhRUV5eHqeeemps3rw5He3SuHHjNES/4oorsl8lAAAAAADkSoiedJ9ff/31cc0116RjXTZt2hSdO3eO4uLi7FcIAAAAAAC5FKJXatSoURqeAwAAAABAXofoZ5999m6/6MMPP1zTegAAAAAAIPdC9JKSktqtBAAAAAAAcjVEv+eee2q3EgAAAAAAqE8z0desWRNLly5NHx9++OHRunXrbNUFANSRioqKKCsrqzovKipKNxUHAOon/+0HgFoI0UtLS+M73/lOzJw5M7Zt25auNWjQIAYNGhRTpkwx+gUAcljyl+gBAwZUnc+ePTuKi4vrtCYAoPb4bz8A7Fph1MCwYcPi5Zdfjscffzw2bNiQHsnjV199NS655JKavCQAAAAAANSPTvQkMH/qqafihBNOqFrr27dvTJs2LU4//fRs1gcAAAAAALnVib7//vvvdGRLstaiRYts1AUAAAAAALnZiT5mzJgYMWJE3HfffdG2bdt0bfXq1XHNNdfE2LFjs10jdWTfgoYxdf/+1c4BAAAAAPJJjUL0O++8M9599904+OCD0yOxYsWKaNy4caxduzZ++ctfVl27ePHi7FXLHpXsxl5U0KiuywAAAAAAyK0QfeDAgdmvBAAAAAAA6kOIPn78+OxXAgAAAAAA9SFE396mTZuivLy82lqzZs0+78sCAAAAAECdK6zJTcuXL48zzjgjioqKoqSkJFq0aJEezZs3T78CAAAAAEDedqKff/75UVFRETNmzIg2bdqkG1ACAAAAAEB9U6MQ/Y033ohFixbF4Ycfnv2KAAAAAAAgl8e5HHvssbFy5crsVwMAAAAAALkeok+fPj1++MMfxq9+9au0I/2///u/qx21acqUKdGhQ4do0qRJ9OrVKxYuXJjx2mnTpsWJJ55YNbO9T58+u7weAAAAAAA+9ziXtWvXxnvvvRdDhw6tWkvmoidz0pOv27Zti9owa9asGDFiREydOjUN0CdPnhx9+/aNpUuXRuvWrXe4fv78+XHOOefEcccdl4buSfB/2mmnxZ/+9Kdo165drdQIAADkl48G3xG5rqx8a7XzVRdNj6LCRpHrDpx5eV2XAADkayf6RRddFN27d48FCxbEsmXLYvny5dW+1pZJkybFsGHD0vC+c+fOaZi+7777phuc7sxvfvObuPzyy6Nbt27RqVOntIO+vLw85s2bV2s1AgAAAACQ553oH3zwQTz22GPRsWPH2FO2bt2ajo4ZPXp01VphYWE6oiUJ83fH5s2b49NPP42WLVtmvGbLli3pUam0tPRzVg6Qe5LfLCorK6s6LyoqSn/TCAAAACDf1KgT/ZRTTok33ngj9qR169alY2LatGlTbT05X7169W69xrXXXhsHHnhgGrxnMnHixCgpKak62rdv/7lrB8g1SYA+YMCAqmP7QB0AAAAgn9SoE71///5x1VVXxZtvvhlHHXVUNGzYsNrzX/va12Jv84Mf/CBmzpyZzklP5qNnknS6J3PXt+9EF6QDAAAAAOSnGoXol156afr1pptu2uG52tpYtFWrVtGgQYP4+OOPq60n523btt3lvT/+8Y/TEP3ZZ5+No48+epfXNm7cOD0AAAAAAKBG41ySzTkzHbURoCcaNWoUPXr0qLYpaOUmob17985432233RY333xzzJ07N4455phaqQ0AAAAAgPqpRp3odSUZs3LhhRemYXjPnj1j8uTJ6ZzeoUOHps8PGTIk2rVrl841T/zwhz+McePGxf333x8dOnSomp1eXFycHgAAAAAAUCshehJeP/fcc7FixYrYunVrtee++93vRm0YNGhQrF27Ng3Gk0C8W7duaYd55WajSS2Fhf9orr/zzjvT2r7+9a9Xe53x48fHDTfcUCs1AgAAAACQ5yH6a6+9Fv369YvNmzenYXrLli1j3bp1se+++0br1q1rLURPDB8+PD12Jtk0dHvvv/9+rdUBAAAAAED9V6OZ6FdddVX0798//vrXv0bTpk3jpZdeig8++CCdWZ5s4gkAAAAAAHkbor/++usxcuTIdHRKgwYNYsuWLdG+fft0E8/rrrsu+1UCAAAAAECuhOgNGzasmj2ejG9JZpEnSkpKYuXKldmtEAAAAAAAcmkmevfu3eOVV16Jww47LE466aR0o89kJvp9990XXbp0yX6VAAAAAACQK53oEyZMiAMOOCB9fOutt0aLFi3isssuS4P0X/7yl9muEQAAAAAAcqcT/cgjj4yKioqqcS5Tp06NRx55JDp37hzdunXLdo0AAAAAAJA7negDBgyI//zP/0wfb9iwIf7f//t/MWnSpBg4cGDceeed2a4RAAAAAAByJ0RfvHhxnHjiienj3/72t9GmTZv44IMP0mD95z//ebZrBAAAAACyLJk0sWnTpqqjcvIEkIVxLps3b4799tsvffz000/H2WefHYWFhWlHehKmAwAAuSX5S3NZWVnVeVFRURQUFNRpTQBA7Ur+259MnKg0e/bsKC4urtOaoN50onfs2DEeffTRWLlyZTz11FNx2mmnpetr1qyJZs2aZbtGAABgD/0luvLYPlAHAIB8VqMQfdy4cXH11VdHhw4dolevXtG7d++qrvTu3btnu0YAAAAAALLIOJ9aHufy9a9/PU444YRYtWpVdO3atWr91FNPjbPOOqsmLwkAAAAAwB5inE8th+iJtm3bpsf2evbsWdOXAwAAAACA+jHOBQAAAAAA8oEQHQAAAAAAsj3OBQCA+ifZTCiZjVipqKgoCgoK6rQmAACAuiREBwCgis2FAAAAqhOiA0CWfDT4jqgPysq3VjtfddH0KCpsFLnswJmX13UJANRT9eG///7bDwC7ZiY6AAAAAABkoBMdAAAAIE/ZD6Xm/CbK3slvolAbhOgAAAAAecp+KACfzTgXAAAAAADIQCc6AAAAAMC/wDif/BrnoxMdAAAAAAAyEKIDAAAAAEAGxrkAZJlf6do72aEdqE3+3b/38u9/AAA+L53oAAAAAACQgU50AACAPLdvQcOYun//aucAAPwfIToAAECeKygoiKKC3B/fAwBQG3IuRJ8yZUr86Ec/itWrV0fXrl3jF7/4RfTs2TPj9Q8++GCMHTs23n///TjssMPihz/8YfTr12+P1gwA1H/1YSZ2fZ2LbSY2AACQNyH6rFmzYsSIETF16tTo1atXTJ48Ofr27RtLly6N1q1b73D9iy++GOecc05MnDgxzjzzzLj//vtj4MCBsXjx4ujSpUudfA8AAABA/VAffojuB+j5zTgvqIcbi06aNCmGDRsWQ4cOjc6dO6dh+r777hszZszY6fU/+9nP4vTTT49rrrkmjjjiiLj55pvjy1/+ctx+++0Z32PLli1RWlpa7QAAAACAejnOq7BR1ZGcAzsqqKioqIgcsHXr1jQw/+1vf5t2k1e68MILY8OGDTF79uwd7jn44IPTzvXvfe97VWvjx4+PRx99NN54442dvs8NN9wQN9544w7rGzdujGbNmmXt+wHYm23atCkGDBhQdZ78O7a4uLhOa2LP8fnnN59//vLZQ/7yz39+8/lD/vLPfz3sRF+3bl1s27Yt2rRpU209OU/mo+9Msv6vXJ8YPXp0GphXHitXrszSdwAAAAAAQK7JqZnoe0Ljxo3TAwAAAACgvioqKqo23SM5J8dD9FatWkWDBg3i448/rraenLdt23an9yTr/8r1AAAAAAD5IJmBb3xLPRvn0qhRo+jRo0fMmzevaq28vDw97927907vSda3vz7xzDPPZLweAAAAAAByshM9kWwSmmwkeswxx0TPnj1j8uTJUVZWFkOHDk2fHzJkSLRr1y4mTpyYnl955ZVx0kknxU9+8pM444wzYubMmfHqq6/GXXfdVcffCQAAAAAAuSCnQvRBgwbF2rVrY9y4cenmoN26dYu5c+dWbR66YsWKKCz8R3P9cccdF/fff3+MGTMmrrvuujjssMPi0UcfjS5dutThdwEAAAAAQK7IqRA9MXz48PTYmfnz5++w9o1vfCM9AAAAAACg3s5EBwAAAACAPU2IDgAAAAAA9WWcCwAAkH1FRUUxe/bsaucA1H/+/Q/w2YToAABU8Rfp/FVQUBDFxcV1XQYAe5h//wN8NiE6AABV/EUaAACgOjPRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJDBPpmeACB/FRUVxezZs6udAwAAAOQjIToAOygoKIji4uK6LgMAgD1AAwUA7FpBRUVFxWdck9dKS0ujpKQkNm7cGM2aNavrcgCg1iX/16CsrKzaX6STH6wAAABAPtKJDgBU4zcRAAAA4B9sLAoAAAAAABkI0QEAAAAAIAMhOgAAAAAAZCBEBwAAAACADIToAAAAAACQgRAdAAAAAAAyEKIDAAAAAECuh+jr16+P8847L5o1axbNmzePb33rW7Fp06ZdXn/FFVfE4YcfHk2bNo2DDz44vvvd78bGjRv3aN0AAAAAAOSunAnRkwD9T3/6UzzzzDPx+OOPx/PPPx8XX3xxxus/+uij9Pjxj38cb731Vtx7770xd+7cNHwHAAAAAIDdUVBRUVERe7m33347OnfuHK+88kocc8wx6VoSiPfr1y/+/Oc/x4EHHrhbr/Pggw/G+eefH2VlZbHPPvvs1j2lpaVRUlKSdrAnXfAAAAAAAOSPnOhEX7BgQTrCpTJAT/Tp0ycKCwvj5Zdf3u3XqQzCdxWgb9myJQ3Otz8AAAAAAMhPORGir169Olq3bl1tLQnCW7ZsmT63O9atWxc333zzLkfAJCZOnJh2nlce7du3/1y1AwAAAACQu+o0RB81alQUFBTs8liyZMnnfp+km/yMM85IR8LccMMNu7x29OjRacd65bFy5crP/f4AAAAAAOSm3RsMXktGjhwZ3/zmN3d5zaGHHhpt27aNNWvWVFv/+9//HuvXr0+f25VPPvkkTj/99Nhvv/3ikUceiYYNG+7y+saNG6cHAAAAAADUaYj+hS98IT0+S+/evWPDhg2xaNGi6NGjR7r2u9/9LsrLy6NXr1677EDv27dvGoo/9thj0aRJk6zWDwAAAABA/ZYTM9GPOOKItJt82LBhsXDhwvjjH/8Yw4cPj8GDB8eBBx6YXvPhhx9Gp06d0ucrA/TTTjstysrK4u67707Pk/npybFt27Y6/o4AAAAAAMgFddqJ/q/4zW9+kwbnp556ahQWFsZ//Md/xM9//vOq5z/99NNYunRpbN68OT1fvHhxvPzyy+njjh07Vnut5cuXR4cOHfbwdwAAAAAAQK4pqKioqKjrIvZmyeaizZs3TzcYbdasWV2XAwAAAABAFiX7aRYUFOR+J3pdSTYmTbRv376uSwEAAAAAoBYaqXfVQK0T/TMkm5d+9NFHn/nTiPoqmSWf/ABBJ35+8vnnN59/fvP55zeff/7y2ec3n39+8/nnN59/fvP55zef///Rif45JfPXDzrooMh3yT9E+fwPUr7z+ec3n39+8/nnN59//vLZ5zeff37z+ec3n39+8/nnN5//rhV+xvMAAAAAAJC3hOgAAAAAAJCBEJ1daty4cYwfPz79Sv7x+ec3n39+8/nnN59//vLZ5zeff37z+ec3n39+8/nnN5//7rGxKAAAAAAAZKATHQAAAAAAMhCiAwAAAABABkJ0AAAAAADIQIgOAAAAAAAZCNEBAAAAACADIToAAAAAAGQgRAcAAAAAgAyE6AAAAAAAkIEQHQAAAAAAMhCiAwAAAABABkJ0AAAAAADIQIgOAAAAAAAZCNEBAAAAACADIToAAAAAAGQgRAcAAAAAgAyE6AAAQK366le/Gt/73vf26HteeumlUVBQEJMnT96j7wsAQP0jRAcAAOqVRx55JF566aU48MAD67oUAADqASE6AAB8DuXl5XHbbbdFx44do3HjxnHwwQfHrbfeWvX8m2++Gaeccko0bdo09t9//7j44otj06ZNVc9/85vfjIEDB8aECROiTZs20bx587jpppvi73//e1xzzTXRsmXLOOigg+Kee+6puuf9999Pu6xnzpwZxx13XDRp0iS6dOkSzz33XLXakvOePXumdR1wwAExatSo9HW37xD/7ne/G9///vfT92nbtm3ccMMN1V5jw4YN8e1vfzu+8IUvRLNmzdLv5Y033qh6Prm+W7ducd9990WHDh2ipKQkBg8eHJ988knV95fU8bOf/SytOTmS+mvLhx9+GFdccUX85je/iYYNG9ba+wAAkD+E6AAA8DmMHj06fvCDH8TYsWPjf/7nf+L+++9Pw/BEWVlZ9O3bN1q0aBGvvPJKPPjgg/Hss8/G8OHDq73G7373u/joo4/i+eefj0mTJsX48ePjzDPPTO97+eWX09Ekl1xySfz5z3+udl8Sso8cOTJee+216N27d/Tv3z/+8pe/VIXJ/fr1i2OPPTYNve+88864++6745Zbbqn2Gr/61a+iqKgofZ/khwFJgP/MM89UPf+Nb3wj1qxZE08++WQsWrQovvzlL8epp54a69evr7rmvffei0cffTQef/zx9EhC8+TPJJGE50ltw4YNi1WrVqVH+/btd/pnmXyfxcXFuzw+6wcaF1xwQfrncuSRR+7mJwgAALtWUFFRUfEZ1wAAADuRdFsnHdq333572q39z6ZNmxbXXnttrFy5Mg2qE0888UQadieheRK2J53a8+fPj2XLlkVh4f/1uHTq1Clat26dhuqJbdu2pR3e06dPT7u8k07uQw45JA2qk9dPJB3myVrShZ10ll9//fXx0EMPxdtvv512fyfuuOOO9PqNGzem75V0oiev/Yc//KGq5qRzPek2T177hRdeiDPOOCMN0ZNu9kpJ133yHklXfdKJ/qMf/ShWr14d++23X/p88lxSezJSJZG8T9Kt/lnzyZP3KS0t3eU1yXtnMnHixPj9738fTz31VPo9J53xySz2PT2PHQCA+mWfui4AAAByVRJQb9myJe3MzvR8165dqwL0xPHHH592TC9durSqYz3pmq4M0BPJejKepVKDBg3SUTBJyLy9pMO70j777BPHHHNM+p6V7508XxmgV753Mkom6WhPxs4kjj766GqvmYx9qXyfpIM9uT557+397W9/S7vPKyVhdWWA/s+v8a9IfnCQHDWRdMknXe+LFy+u9j0DAMDnJUQHAIAaSuacZ8M/z+5OQuCdrSXhe7bt6n2SAD0JxJNO+X+WzG7fndf4VyTjXH7961/v8prt58lvL+mmT4L7yh8OJJIu+2TcTdIBX5tz2AEAqN+E6AAAUEOHHXZYGqTPmzdvp+NcjjjiiLj33nvT2eiV3eh//OMf067zww8//HO/fzIu5Stf+UrVOJekG7ty3nry3sk4l2R6Y2VndvLeScd4slHp7kjmnydjWpIu96TbvKYaNWqUBtqfJZnHfvXVV9foPZJZ6H369Km2lsyjT9aHDh1ao9cEAICEEB0AAGqoSZMm6YzxZAZ4EhQn41LWrl0bf/rTn+Jb3/pWnHfeeekmoRdeeGE6Ozx5LplZngS7laNcPo8pU6akQX4SmP/0pz+Nv/71r3HRRRelz11++eVpB3byfkmwnoyPSWoZMWJEtdExu5KE0slImIEDB6abjn7pS19KZ7nPmTMnzjrrrHR8zO5IAvhk49KkGzzZHLRly5Y7reHzjHNJRs7889iZpEO+bdu2WfmBBQAA+Wv3/t8zAACwU2PHjk1HhowbNy4NswcNGlQ1D3zfffdNN7lcv359HHvssfH1r389nZ+ebESaDcnmn8mRzF1PNgF97LHHolWrVulz7dq1SzcxXbhwYfp8MiolCfbHjBmz26+fdLAnr5F0uyfd3EmInmxs+sEHH/xLPwRIusuTue6dO3dON2JdsWJFjb5fAACoCwUVye93AgAAOSPp6D7kkEPitddei27dutV1OQAAUK/pRAcAAAAAgAyE6AAAAAAAkIFxLgAAAAAAkIFOdAAAAAAAyECIDgAAAAAAGQjRP0My7aa0tDT9CgAAAABAfhGif4ZPPvkkSkpK0q8AAAAAAOQXIToAAAAAAGQgRAcAAAAAgAyE6AAAAAAAUB9C9Oeffz769+8fBx54YBQUFMSjjz76mffMnz8/vvzlL0fjxo2jY8eOce+99+6RWgEAAAAAyH05FaKXlZVF165dY8qUKbt1/fLly+OMM86Ik08+OV5//fX43ve+F9/+9rfjqaeeqvVaAQAAAADIfQUVFRUVkYOSTvRHHnkkBg4cmPGaa6+9NubMmRNvvfVW1drgwYNjw4YNMXfu3J3es2XLlvSoVFpaGu3bt4+NGzdGs2bNsvxdAAAAAACwN8upTvR/1YIFC6JPnz7V1vr27ZuuZzJx4sQoKSmpOpIAHQAAAACA/FSvQ/TVq1dHmzZtqq0l50l3+d/+9red3jN69Oi067zyWLly5R6qFgAAAACAvc0+dV3A3ibZgDQ5AAAAAACgXneit23bNj7++ONqa8l5Mtu8adOmdVYXAAAAAAC5oV6H6L1794558+ZVW3vmmWfSdQAAAAAAqFch+qZNm+L1119Pj8Ty5cvTxytWrKiaZz5kyJCq6y+99NJYtmxZfP/7348lS5bEHXfcEQ888EBcddVVdfY9AAAAAACQO3IqRH/11Veje/fu6ZEYMWJE+njcuHHp+apVq6oC9cQhhxwSc+bMSbvPu3btGj/5yU9i+vTp0bdv3zr7HgAAAAAAyB0FFRUVFXVdxN6stLQ0SkpKYuPGjeksdQAAAAAA8kdOdaIDAAAAAMCeJEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAAOpLiD5lypTo0KFDNGnSJHr16hULFy7c5fWTJ0+Oww8/PJo2bRrt27ePq666Kv73f/93j9ULAAAAAEDuyqkQfdasWTFixIgYP358LF68OLp27Rp9+/aNNWvW7PT6+++/P0aNGpVe//bbb8fdd9+dvsZ11123x2sHAAAAACD3FFRUVFREjkg6z4899ti4/fbb0/Py8vK0u/yKK65Iw/J/Nnz48DQ8nzdvXtXayJEj4+WXX44XXnhhp++xZcuW9KhUWlqavsfGjRujWbNmtfJ9AQAAAACwd8qZTvStW7fGokWLok+fPlVrhYWF6fmCBQt2es9xxx2X3lM58mXZsmXxxBNPRL9+/TK+z8SJE6OkpKTqSAJ0AAAAAADy0z6RI9atWxfbtm2LNm3aVFtPzpcsWbLTe84999z0vhNOOCGShvu///3vcemll+5ynMvo0aPTkTH/3IkOAAAAAED+yZlO9JqYP39+TJgwIe644450hvrDDz8cc+bMiZtvvjnjPY0bN07Htmx/AAAAAACQn3KmE71Vq1bRoEGD+Pjjj6utJ+dt27bd6T1jx46NCy64IL797W+n50cddVSUlZXFxRdfHNdff306DgYAAAAAADLJmRS5UaNG0aNHj2qbhCYbiybnvXv33uk9mzdv3iEoT4L4RA7tpwoAAAAAQB3JmU70RDKr/MILL4xjjjkmevbsGZMnT047y4cOHZo+P2TIkGjXrl26OWiif//+MWnSpOjevXv06tUr3n333bQ7PVmvDNMBAAAAAKBehOiDBg2KtWvXxrhx42L16tXRrVu3mDt3btVmoytWrKjWeT5mzJgoKChIv3744YfxhS98IQ3Qb7311jr8LgAAAAAAyBUFFeaa7FJpaWmUlJTExo0bbTIKAAAAAJBncqoTHQCofcnP15NxaZWKiorS3+wCAACAfCREBwCqSQL0AQMGVJ3Pnj07iouL67QmAAAAqCv/GCAOAAAAAABUI0QHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkM0SfO3duvPDCC1XnU6ZMiW7dusW5554bf/3rX2vykgAAAAAAUD9C9GuuuSZKS0vTx2+++WaMHDky+vXrF8uXL48RI0Zku0YAAAAAAKgT+9TkpiQs79y5c/r4oYceijPPPDMmTJgQixcvTsN0AAAAAADI2070Ro0axebNm9PHzz77bJx22mnp45YtW1Z1qAMAAAAAQF52op9wwgnp2Jbjjz8+Fi5cGLNmzUrX33nnnTjooIOyXSMAAAAAAOROJ/rtt98e++yzT/z2t7+NO++8M9q1a5euP/nkk3H66adnu0YAAAAAAMidTvSDDz44Hn/88R3Wf/rTn2ajJgDqWEVFRZSVlVWdFxUVRUFBQZ3WBAAAAJAzIXqDBg1i1apV0bp162rrf/nLX9K1bdu2Zas+AOpAEqAPGDCg6nz27NlRXFxcpzUBAAAA5Mw4l6RDcWe2bNmSbjoKAAAAAAB514n+85//PP2a/Er/9OnTq3UlJt3nzz//fHTq1Clq05QpU+JHP/pRrF69Orp27Rq/+MUvomfPnhmv37BhQ1x//fXx8MMPx/r16+Pf/u3fYvLkydGvX79arRMAAAAAgDwL0Stnnied6FOnTk3HulRKOtA7dOiQrteWWbNmxYgRI9L36NWrVxqG9+3bN5YuXbrDaJnE1q1b49///d/T55JNUJMNUD/44INo3rx5rdUIAAAAAECehujLly9Pv5588slpZ3eLFi1iT5o0aVIMGzYshg4dmp4nYfqcOXNixowZMWrUqB2uT9aT7vMXX3wxGjZsmK4lQT/w2WwsCQAAAAA1nIn++9//fo8H6ElX+aJFi6JPnz5Va4WFhen5ggULdnrPY489Fr17947vfOc70aZNm+jSpUtMmDBhlxufJnPdS0tLqx2QzxtLVh7bB+oAAAAAkC/+pU70SkkIfe+998a8efNizZo1UV5eXu353/3ud5Ft69atS983CcO3l5wvWbJkp/csW7YsreW8886LJ554It599924/PLL49NPP43x48fv9J6JEyfGjTfemPX6AQAAAADIkxD9yiuvTEP0M844I+3u3ltHPCThfjIP/a677krnt/fo0SM+/PDDdGPSTCH66NGj07nrlZJO9Pbt2+/BqgEAAAAAyOkQfebMmfHAAw9Ev379Yk9p1apVGoR//PHH1daT87Zt2+70ngMOOCCdhb79BqhHHHFErF69Oh0Pk2yG+s8aN26cHgAAAAAAUKOZ6En43LFjx+xX8xnvmXSSJyNktu80T86Tuec7c/zxx6cjXLYfN/POO++k4frOAnQAAADINxUVFbFp06aqIzkHAD5niD5y5Mj42c9+tsf/w5qMWZk2bVr86le/irfffjsuu+yydLPDoUOHps8PGTIkHcdSKXl+/fr16fiZJDyfM2dOurFostEoAAAAEOnfqwcMGFB1JOcAQA3GuZx99tnVzpMNO5988sk48sgj05Ep23v44YejNgwaNCjWrl0b48aNS0eydOvWLebOnVu12eiKFSuisPAfPxdIZpk/9dRTcdVVV8XRRx8d7dq1SwP1a6+9tlbqAwAAAAAgT0P0kpKSaudnnXVW1IXhw4enx87Mnz9/h7Vk1MtLL720ByoDAAAAACBvQ/R77rmndisBAAAAAID6MBMdAAAAAADywW53om+ve/fuUVBQsMN6stakSZPo2LFjfPOb34yTTz45GzUCAAAAAEDudKKffvrpsWzZsigqKkqD8uQoLi6O9957L4499thYtWpV9OnTJ2bPnp39igEAAAAAYG/uRF+3bl2MHDkyxo4dW239lltuiQ8++CCefvrpGD9+fNx8880xYMCAbNUKAAAAAAB7fyf6Aw88EOecc84O64MHD06fSyTPL1269PNXCAAAAAAAuRSiJ3PPX3zxxR3Wk7XkuUR5eXnVYwAAAAAAyJtxLldccUVceumlsWjRonQGeuKVV16J6dOnx3XXXZeeP/XUU9GtW7fsVgsAAAAAAHt7iD5mzJg45JBD4vbbb4/77rsvXTv88MNj2rRpce6556bnSch+2WWXZbdaAAAAAADY20P0xHnnnZcemTRt2rSmLw0AAAAAALk7Ex0AAAAAAPLBbneit2zZMt55551o1apVtGjRIgoKCjJeu379+mzVRx2qqKiIsrKyqvOioqJdfu4AAAAAAHkbov/0pz+N/fbbL308efLk2qyJvUQSoA8YMKDqfPbs2VFcXFynNQEAAAAA7JUh+oUXXrjTxwAAAAAAUF/VeCb6e++9F2PGjIlzzjkn1qxZk649+eST8ac//Smb9QEAAAAAQG6F6M8991wcddRR8fLLL8fDDz8cmzZtStffeOONGD9+fLZrBAAAAACA3AnRR40aFbfccks888wz0ahRo6r1U045JV566aVs1gcAAAAAALkVor/55ptx1lln7bDeunXrWLduXTbqAgAAAACA3AzRmzdvHqtWrdph/bXXXot27dploy4AAAAAAMjNEH3w4MFx7bXXxurVq6OgoCDKy8vjj3/8Y1x99dUxZMiQ7FcJAAAAAAC5EqJPmDAhOnXqFO3bt083Fe3cuXN85StfieOOOy7GjBmT/SoBAAAAAKAO7FOTm5LNRKdNmxZjx46Nt956Kw3Su3fvHocddlj2KwQAAAAAgFwK0ZctWxaHHnpoHHzwwekBAAAAAAD1UY1C9I4dO8ZBBx0UJ510Unz1q19NvyZrAAAAAAAQ+T4TfeXKlTFx4sRo2rRp3HbbbfGlL30pDdXPO++8mD59evarBAAAAACAXAnR27Vrlwbmd911VyxdujQ9+vTpEw888EBccskl2a8SAAAAAAByZZzL5s2b44UXXoj58+enx2uvvRadOnWK4cOHp+NdAAAAAAAgb0P05s2bR4sWLdJu9FGjRsWJJ56YngMAAAAAQOT7OJd+/frFtm3bYubMmenx4IMPxjvvvBN7wpQpU6JDhw7RpEmT6NWrVyxcuHC37kvqLCgoiIEDB9Z6jQAAAAAA5HGI/uijj8a6deti7ty50bt373j66afTbvTKWem1ZdasWTFixIgYP358LF68OLp27Rp9+/aNNWvW7PK+999/P66++uq0RgAAAAAAqNUQvdJRRx0Vxx9/fBqkH3vssWmYnQTdtWXSpEkxbNiwGDp0aHTu3DmmTp0a++67b8yYMSPjPUnHfBLs33jjjXHooYfWWm0AAAAAANQ/hTUNs7/2ta/F/vvvn45U+a//+q/40pe+FA899FCsXbs2+1VGxNatW2PRokXRp0+fqrXCwsL0fMGCBRnvu+mmm6J169bxrW99a7feZ8uWLVFaWlrtAAAAAAAgP9VoY9EkND/ppJPi4osvTkeklJSURG1LxsckXeVt2rSptp6cL1myZKf3vPDCC3H33XfH66+/vtvvM3HixLRrHQAAAAAAatSJ/sorr8SPf/zjOPPMM3cZoF9++eVp+F0XPvnkk7jgggti2rRp0apVq92+b/To0bFx48aqY+XKlbVaJwAAAAAA9awTfXf9+te/Tjf0/FdC7EyS12jQoEF8/PHH1daT87Zt2+5w/XvvvZduKNq/f/+qtfLy8vTrPvvsE0uXLo0vfvGLO9zXuHHj9AAAAAAAgM+1sehnqaioyNprNWrUKHr06BHz5s2rFoon58nGpv+sU6dO8eabb6ajXCqPZI77ySefnD5u37591moDAAAAAKB+qtVO9GwbMWJEXHjhhXHMMcdEz549Y/LkyVFWVhZDhw5Nnx8yZEi0a9cunWvepEmT6NKlS7X7mzdvnn7953UAAAAAAMj5EH3QoEGxdu3aGDduXKxevTq6desWc+fOrdpsdMWKFVFYWKvN9QCQ0UeD74j6oKx8a7XzVRdNj6LCRpHLDpx5eV2XAAAAQI7KqRA9MXz48PTYmfnz5+/y3nvvvbeWqgIAAMhdySjO5Ld8KxUVFUVBQUGd1gQAsLfIuRAdAACA7EoC9AEDBlSdz549O4qLi+u0JgCAvUWtzj45//zzo1mzZrX5FgAAAAAAsPeF6H/4wx/SkLx3797x4Ycfpmv33XdfvPDCC1XX3HnnndGqVavsVAoAAAAAALkQoj/00EPRt2/faNq0abz22muxZcuWdH3jxo0xYcKEbNcIAAAAAAC5E6LfcsstMXXq1Jg2bVo0bNiwav3444+PxYsXZ7M+AAAAAADIrRB96dKl8ZWvfGWH9ZKSktiwYUM26gIAAAAAgNwM0du2bRvvvvvuDuvJPPRDDz00G3UBAAB7UEVFRWzatKnqSM4BAICIfWpy07Bhw+LKK6+MGTNmREFBQXz00UexYMGCuPrqq2Ps2LHZrxIAAKhVZWVlMWDAgKrz2bNnR3FxcZ3WBAAAORuijxo1KsrLy+PUU0+NzZs3p6NdGjdunIboV1xxRfarBAAAAACAXAnRk+7z66+/Pq655pp0rEvy656dO3fWqQIAAAAAQL1SoxC9UqNGjdLwHAAAAAAA8jpEP/vss3f7RR9++OGa1gMAAAAAALkXopeUlNRuJVCPfDT4jsh1ZeVbq52vumh6FBU2ilx24MzL67oEAAAAAOpriH7PPffUbiUAAAAAAFCfZqKvWbMmli5dmj4+/PDDo3Xr1tmqCwAAAAAA6lxhTW4qLS2NCy64INq1axcnnXRSeiSPzz///Ni4cWP2qwQAAAAAgFwJ0YcNGxYvv/xyPP7447Fhw4b0SB6/+uqrcckll2S/SgAAAAAAyJVxLklg/tRTT8UJJ5xQtda3b9+YNm1anH766dmsDyDn2Fh272RjWQAAAGCPdaLvv//+UVJSssN6staiRYsaFQIAAAAAAPUiRB8zZkyMGDEiVq9eXbWWPL7mmmti7Nix2awPAAAAAABya5zLnXfeGe+++24cfPDB6ZFYsWJFNG7cONauXRu//OUvq65dvHhx9qoFAAAAAIC9PUQfOHBg9isBAAAAAID6EKKPHz8++5UAAAAAAEB9CNG3t2nTpigvL6+21qxZs8/7sgAAAAAAkJsh+vLly2P48OExf/78+N///d+q9YqKiigoKIht27Zls0YAAADYK300+I7IdWXlW6udr7poehQVNopcduDMy+u6BADyPUQ///zz08B8xowZ0aZNmzQ4BwAAACC3JPlOWVlZ1XlRUZGcByAbIfobb7wRixYtisMPP7wmtwMAAACwF0gC9AEDBlSdz549O4qLi+u0JoC9TWFNbjr22GNj5cqV2a8GAAAAAAByvRN9+vTpcemll8aHH34YXbp0iYYNG1Z7/uijj85WfQAA7EF+pRsAACALnehr166N9957L4YOHZp2pXfr1i26d+9e9bU2TZkyJTp06BBNmjSJXr16xcKFCzNeO23atDjxxBOjRYsW6dGnT59dXg8AkO8qf6W78tg+UAcAAMhHNQrRL7roojQsX7BgQSxbtiyWL19e7WttmTVrVowYMSLGjx8fixcvjq5du0bfvn1jzZo1O71+/vz5cc4558Tvf//7tNb27dvHaaedlnbQAwAAAABArYxz+eCDD+Kxxx6Ljh07xp40adKkGDZsWNoBn5g6dWrMmTMnZsyYEaNGjdrh+t/85jc7jKF56KGHYt68eTFkyJCdvseWLVvSo1JpaWmNav1o8B2R68rKt1Y7X3XR9CgqbBS57MCZl9d1CQAAAABAfe9EP+WUU+KNN96IPWnr1q2xaNGidCRLpcLCwvQ86TLfHZs3b45PP/00WrZsmfGaiRMnRklJSdWRdK8DAAAAAJCfatSJ3r9//7jqqqvizTffjKOOOmqHjUW/9rWvRbatW7cutm3bFm3atKm2npwvWbJkt17j2muvjQMPPLBaEP/PRo8enY6M2b4TXZAOAAAAAJCfahSiX3rppenXm266aYfnCgoK0rB7b/ODH/wgZs6cmc5JTzYlzaRx48bpAQAAAAAANQrRy8vLY09r1apVNGjQID7++ONq68l527Ztd3nvj3/84zREf/bZZ+Poo4+u5UoBAAAAAMjrmeh1oVGjRtGjR490U9Dtw/zkvHfv3hnvu+222+Lmm2+OuXPnxjHHHLOHqgUAAAAAIG870RNlZWXx3HPPxYoVK9JNP7f33e9+N2pDMqv8wgsvTMPwnj17xuTJk9M6hg4dmj4/ZMiQaNeuXbo5aOKHP/xhjBs3Lu6///7o0KFDrF69Ol0vLi5ODwAAAAAAyHqI/tprr0W/fv1i8+bNaYjdsmXLdOPPfffdN1q3bl1rIfqgQYNi7dq1aTCeBOLdunVLO8wrNxtNAv3Cwn801995551pwP/1r3+92uuMHz8+brjhhlqpEQAAAACAPA/Rr7rqqujfv39MnTo1SkpK4qWXXoqGDRvG+eefH1deeWXUpuHDh6fHziSbhm7v/fffr9VaAAAAAACo32o0E/3111+PkSNHpl3fyWafW7Zsifbt26fzx6+77rrsVwkAAAAAALkSoidd55VjU5LxLckYlUTSlb5y5crsVggAAAAAALk0zqV79+7xyiuvxGGHHRYnnXRSOqM8mYl+3333RZcuXbJfJQAAwF7qo8F3RK4rK99a7XzVRdOjqLBR5LoDZ15e1yUAAPnaiT5hwoQ44IAD0se33nprtGjRIi677LI0SP/lL3+Z7RoBAAAAACB3OtGPPPLIqKioqBrnkmww+sgjj0Tnzp2jW7du2a4RAAAAAABypxN9wIAB8Z//+Z/p4w0bNsT/+3//LyZNmhQDBw6MO++8M9s1AgAAAABA7oToixcvjhNPPDF9/Nvf/jbatGkTH3zwQRqs//znP892jQAAAAAAZFEyaWTTpk1VR+XkEbI0zmXz5s2x3377pY+ffvrpOPvss6OwsDDtSE/CdAAAAAAA9l5lZWXpxJFKs2fPjuLi4jqtqV6F6B07doxHH300zjrrrHjqqafiqquuStfXrFkTzZo1y3aNAACwV/to8B2R68rKt1Y7X3XR9CgqbBS57sCZl9d1CQAA5OM4l3HjxsXVV18dHTp0iF69ekXv3r2rutK7d++e7RoBAAAAACB3OtG//vWvxwknnBCrVq2Krl27Vq2feuqpaXc6AAAAAADkbYieaNu2bXpsr2fPntmoCQAAAAAAcnecCwAAAAAA5IMad6IDAAAAALmroqIiysrKqs6LioqioKCgTmuCvZEQHQAAAADyUBKgDxgwoOp89uzZUVxcXKc1wd7IOBcAAAAAAMhAiA4AAAAAABkY5wIAAABQAx8NviNyXVn51mrnqy6aHkWFjSKXHTjz8rouAahndKIDAAAAAEAGQnQAAAAAAMjAOBcAgCyoD7/OnfAr3QAAANXpRAcAAAAAgAyE6AAAAAAAkIEQHQAAAAAAMhCiAwAAAABABjYWBQAAAAD4F3w0+I7IdWXlW6udr7poehQVNopcduDMy2vldXWiAwAAAABABkJ0AAAAAACoLyH6lClTokOHDtGkSZPo1atXLFy4cJfXP/jgg9GpU6f0+qOOOiqeeOKJPVYrAAAAAAC5Ladmos+aNStGjBgRU6dOTQP0yZMnR9++fWPp0qXRunXrHa5/8cUX45xzzomJEyfGmWeeGffff38MHDgwFi9eHF26dKmT7wEAAACA3Gcmdn7NxCa/5VQn+qRJk2LYsGExdOjQ6Ny5cxqm77vvvjFjxoydXv+zn/0sTj/99LjmmmviiCOOiJtvvjm+/OUvx+23377HawcAAAAAIPfkTIi+devWWLRoUfTp06dqrbCwMD1fsGDBTu9J1re/PpF0rme6PrFly5YoLS2tdgAAAAAAkJ9yZpzLunXrYtu2bdGmTZtq68n5kiVLdnrP6tWrd3p9sp5JMvrlxhtv/Nz11odfHdm0aVPEgP9f1fkBM74dxcXFdVpTrqgPn39FRUXMLvt21XlRUVEUFBTUaU25oj58/v75z9/PPuHzrxmff36rD5+/z77mfP75zeef33z++c3nn998/vklZzrR95TRo0fHxo0bq46VK1fWdUlQJ5LAPPkXZ+UhQAcAAAAgH+VMJ3qrVq2iQYMG8fHHH1dbT87btm2703uS9X/l+kTjxo3TAwDyVfKbJ7Nnz652DgAAAPkqZzrRGzVqFD169Ih58+ZVrZWXl6fnvXv33uk9yfr21yeeeeaZjNcDAH4TBQAAAHKyEz0xYsSIuPDCC+OYY46Jnj17xuTJk6OsrCyGDh2aPj9kyJBo165dOtc8ceWVV8ZJJ50UP/nJT+KMM86ImTNnxquvvhp33XVXHX8nAAAAAADkgpwK0QcNGhRr166NcePGpZuDduvWLebOnVu1eeiKFSuisPAfzfXHHXdc3H///TFmzJi47rrr4rDDDotHH300unTpUoffBQAAAAAAuSKnQvTE8OHD02Nn5s+fv8PaN77xjfQAAAAAAIB6OxMdAAAAAAD2NCE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADLYJ9MTAAAAAADUT0VFRTF79uxq5+ycEB0AACDP+Us0QH7y7//8VlBQEMXFxXVdRk4QogMAAOQ5f4kGyE/+/Q+7x0x0AAAAAADIQCc6ADvwK30AAAAA/0eIDsAO/EofQP7xA1QAANi5goqKiooMzxERpaWlUVJSEhs3boxmzZpFPkn+p1FWVlbtL1JJsAYA1F+bNm2KAQMGVJ0noaofqgHUb/7ul998/gCfTSc6GelEBQAAqP/83S+/+fwBPptO9M+Qz53oAED+0Y0GAABQnU50AACq6EYDAACorvCfzgEAAAAAgP+PEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAuR6ir1+/Ps4777xo1qxZNG/ePL71rW/Fpk2bdnn9FVdcEYcffng0bdo0Dj744Pjud78bGzdu3KN1AwAAAACQu3ImRE8C9D/96U/xzDPPxOOPPx7PP/98XHzxxRmv/+ijj9Ljxz/+cbz11ltx7733xty5c9PwHQAAAAAAdkdBRUVFRezl3n777ejcuXO88sorccwxx6RrSSDer1+/+POf/xwHHnjgbr3Ogw8+GOeff36UlZXFPvvss1v3lJaWRklJSdrBnnTBAwAAAACQP3KiE33BggXpCJfKAD3Rp0+fKCwsjJdffnm3X6cyCN9VgL5ly5Y0ON/+AAAAAAAgP+VEiL569epo3bp1tbUkCG/ZsmX63O5Yt25d3HzzzbscAZOYOHFi2nleebRv3/5z1Q4AAAAAQO6q0xB91KhRUVBQsMtjyZIln/t9km7yM844Ix0Jc8MNN+zy2tGjR6cd65XHypUrP/f7AwAAAACQm3ZvMHgtGTlyZHzzm9/c5TWHHnpotG3bNtasWVNt/e9//3usX78+fW5XPvnkkzj99NNjv/32i0ceeSQaNmy4y+sbN26cHgAAAAAAUKch+he+8IX0+Cy9e/eODRs2xKJFi6JHjx7p2u9+97soLy+PXr167bIDvW/fvmko/thjj0WTJk2yWj8AAAAAAPVbTsxEP+KII9Ju8mHDhsXChQvjj3/8YwwfPjwGDx4cBx54YHrNhx9+GJ06dUqfrwzQTzvttCgrK4u77747PU/mpyfHtm3b6vg7AgAAAAAgF9RpJ/q/4je/+U0anJ966qlRWFgY//Ef/xE///nPq57/9NNPY+nSpbF58+b0fPHixfHyyy+njzt27FjttZYvXx4dOnTYw98BAAAAAAC5pqCioqKirovYmyUd7CUlJekmo82aNavrcgAAAAAA2INyphO9rlT+jCEJ0wEAAAAAqF/222+/KCgoyPi8EP0zfPLJJ+nX9u3b13UpAAAAAABk2WdNITHO5TOUl5fHRx999Jk/jaivkg785AcIK1euNM4mD/n885vPP7/5/PObzz9/+ezzm88/v/n885vPP7/5/PObz///6ET/nJJNTA866KDId8k/RPn8D1K+8/nnN59/fvP55zeff/7y2ec3n39+8/nnN59/fvP55zef/64VfsbzAAAAAACQt4ToAAAAAACQgRCdXWrcuHGMHz8+/Ur+8fnnN59/fvP55zeff/7y2ec3n39+8/nnN59/fvP55zef/+6xsSgAAAAAAGSgEx0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAABq1Ve/+tX43ve+V+vv881vfjMKCgqqHaeffnqtvy8AAPXbPnVdAAAAQLYkofk999xTdd64ceM6rQcAgNynEx0AAD6H8vLyuO2226Jjx45pYHvwwQfHrbfeWvX8m2++Gaeccko0bdo09t9//7j44otj06ZN1bqnBw4cGBMmTIg2bdpE8+bN46abboq///3vcc0110TLli3joIMOqhYMv//++2mX9cyZM+O4446LJk2aRJcuXeK5556rVlty3rNnz7SuAw44IEaNGpW+7vYd4t/97nfj+9//fvo+bdu2jRtuuKHaa2zYsCG+/e1vxxe+8IVo1qxZ+r288cYbVc8n13fr1i3uu+++6NChQ5SUlMTgwYPjk08+qfr+kjp+9rOfVXWHJ/XXluR7Tb6PyqNFixa19l4AAOQHIToAAHwOo0ePjh/84AcxduzY+J//+Z+4//770zA8UVZWFn379k2D3FdeeSUefPDBePbZZ2P48OHVXuN3v/tdfPTRR/H888/HpEmTYvz48XHmmWem97388stx6aWXxiWXXBJ//vOfq92XhOwjR46M1157LXr37h39+/ePv/zlL+lzH374YfTr1y+OPfbYNPS+88474+67745bbrml2mv86le/iqKiovR9kh8GJAH+M888U/X8N77xjVizZk08+eSTsWjRovjyl78cp556aqxfv77qmvfeey8effTRePzxx9MjCc2TP5NEEp4ntQ0bNixWrVqVHu3bt9/pn2XyfRYXF+/y+Czz58+P1q1bx+GHHx6XXXZZ1Z8HAADUVEFFRUVFje8GAIA8lnRbJx3at99+e9qt/c+mTZsW1157baxcuTINqhNPPPFEGnYnoXkStied2knwu2zZsigs/L8el06dOqVBcBKqJ7Zt25Z2eE+fPj3t8k46uQ855JA0qE5eP5F0mCdrV1xxRdpZfv3118dDDz0Ub7/9dtr9nbjjjjvS6zdu3Ji+V9KJnrz2H/7wh6qak871pNs8ee0XXnghzjjjjDRE334sStJ1n7xH0lWfdKL/6Ec/itWrV8d+++2XPp88l9T+0ksvpefJ+yTd6pMnT97ln2fyPqWlpbu8JnnvTJLO/H333Tf9c0iC/euuuy4N3hcsWBANGjTY5esCAEAmZqIDAEANJQH1li1b0s7sTM937dq1KkBPHH/88ekImKVLl1Z1rB955JFVAXoiWU/Gs1RKAuBkFEwSMm8v6fCutM8++8QxxxyTvmfleyfPVwbole+djJJJOtqTsTOJo48+utprJmNfKt8n6WBPrk/ee3t/+9vf0pC6UjLGpTJA/+fX+FckPzhIjppKfsBQ6aijjkq/ty9+8YvpDykyfUYAAPBZhOgAAFBDyZzzbGjYsGG18yT43tlaEr5n267eJwnQk0A8CaH/WTK7fXde41+RjHP59a9/vctrtp8n/1kOPfTQaNWqVbz77rtCdAAAakyIDgAANXTYYYelQfq8efN2Os7liCOOiHvvvTedjV7Zjf7HP/4x7TpPZnZ/Xsm4lK985StV41ySmeWV89aT907GuSTTGyu70ZP3TjrGk41Kd0cy/zwZ05J0uSfd5jXVqFGjdGzMZ0nmsV999dWRLUnHfTITPflBAAAA1JSNRQEAoIaaNGmSzhhPZoD/53/+ZzriJAm2kw08E+edd156zYUXXhhvvfVW/P73v09nll9wwQVVo1w+jylTpsQjjzwSS5Ysie985zvx17/+NS666KL0ucsvvzydxZ68X/L87Nmz0w1LR4wYUW10zK706dMnHQkzcODAePrpp9NZ7C+++GI6b/3VV1/d7TqTAD7ZuDS5f926dRm71JNRLsnM810du+pQTzZaTf78k/dJfrAxYMCA9J5kc1cAAKgpIToAAHwOY8eOjZEjR8a4cePS7u9BgwZVzQNPNrl86qmnYv369XHsscfG17/+9XSsSLIRaTYkm38mRzJ3PdkE9LHHHkvHlyTatWuXbmK6cOHC9PlkVMq3vvWtGDNmzG6/ftLBnrxG0u0+dOjQ+NKXvpTOHf/ggw/+pR8CJN3lyVz3zp07pxuxrlixIrItef3//u//jq997Wtpncn32qNHj3TT1O03RQUAgH9VQUXy+50AAEDOSDqtDznkkHjttdeiW7dudV0OAADUazrRAQAAAAAgAyE6AAAAAABkYJwLAAAAAABkoBMdAAAAAAAyEKIDAAAAAEAGQnQAAAAAAMhAiP4ZkpHxpaWl6VcAAAAAAPKLEP0zfPLJJ1FSUpJ+BQAAAAAgvwjRAQAAAAAgAyE6AAAAAADUhxD9+eefj/79+8eBBx4YBQUF8eijj37mPfPnz48vf/nL0bhx4+jYsWPce++9e6RWAAAAAAByX06F6GVlZdG1a9eYMmXKbl2/fPnyOOOMM+Lkk0+O119/Pb73ve/Ft7/97XjqqadqvVYAAAAAAHJfQUVFRUXkoKQT/ZFHHomBAwdmvObaa6+NOXPmxFtvvVW1Nnjw4NiwYUPMnTt3p/ds2bIlPSqVlpZG+/btY+PGjdGsWbMsfxcAAAAAAOzNcqoT/V+1YMGC6NOnT7W1vn37puuZTJw4MUpKSqqOJEAHAAAAACA/1esQffXq1dGmTZtqa8l50l3+t7/9baf3jB49Ou06rzxWrly5h6oFAAAAAGBvs09dF7C3STYgTQ4AAAAAAKjXneht27aNjz/+uNpacp7MNm/atGmd1QUAAAAAQG6o1yF67969Y968edXWnnnmmXQdAAAAAADqVYi+adOmeP3119MjsXz58vTxihUrquaZDxkypOr6Sy+9NJYtWxbf//73Y8mSJXHHHXfEAw88EFdddVWdfQ8AAAAAAOSOnArRX3311ejevXt6JEaMGJE+HjduXHq+atWqqkA9ccghh8ScOXPS7vOuXbvGT37yk5g+fXr07du3zr4HAAAAAAByR0FFRUVFXRexNystLY2SkpLYuHFjOksdAAAAAID8kVOd6AAAAAAAsCcJ0QEAAAAAIAMhOgAAAAAAZCBEBwAAAACADIToAAAAAACQgRAdAAAAAAAyEKIDAAAAAEAGQnQAAAAAAMhAiA4AAAAAABkI0QEAAAAAIAMhOgAAAAAAZCBEBwAAAACADIToAAAAAACQgRAdAAAAAAAyEKIDAAAAAEAGQnQAAAAAAMhAiA4AAAAAABkI0QEAAAAAIAMhOgAAAAAAZCBEBwAAAACADIToAAAAAACQgRAdAAAAAAAyEKIDAAAAAEAGQnQAAAAAAMhAiA4AAAAAABkI0QEAAAAAIAMhOgAAAAAAZCBEBwAAAACA+hKiT5kyJTp06BBNmjSJXr16xcKFC3d5/eTJk+Pwww+Ppk2bRvv27eOqq66K//3f/91j9QIAAAAAkLtyKkSfNWtWjBgxIsaPHx+LFy+Orl27Rt++fWPNmjU7vf7++++PUaNGpde//fbbcffdd6evcd111+3x2gEAAAAAyD0FFRUVFZEjks7zY489Nm6//fb0vLy8PO0uv+KKK9Kw/J8NHz48Dc/nzZtXtTZy5Mh4+eWX44UXXtit9ywtLY2SkpLYuHFjNGvWLIvfDcDeK/lPQ1lZWdV5UVFRFBQU1GlNAAAAAHUhZzrRt27dGosWLYo+ffpUrRUWFqbnCxYs2Ok9xx13XHpP5ciXZcuWxRNPPBH9+vXL+D5btmxJg/PtD4B8kwToAwYMqDq2D9QBAAAA8sk+kSPWrVsX27ZtizZt2lRbT86XLFmy03vOPffc9L4TTjgh7ar8+9//Hpdeeukux7lMnDgxbrzxxqzXDwAAAABA7smZTvSamD9/fkyYMCHuuOOOdIb6ww8/HHPmzImbb7454z2jR49OR7dUHitXrtyjNQMAAAAAsPfImU70Vq1aRYMGDeLjjz+utp6ct23bdqf3jB07Ni644IL49re/nZ4fddRR6UiCiy++OK6//vp0HMw/a9y4cXoAAAAAAEDOdKI3atQoevToUW2T0GRj0eS8d+/eO71n8+bNOwTlSRCfyKH9VAEAAAAAqCM504meGDFiRFx44YVxzDHHRM+ePWPy5MlpZ/nQoUPT54cMGRLt2rVL55on+vfvH5MmTYru3btHr1694t13302705P1yjAdAAAAAADqRYg+aNCgWLt2bYwbNy5Wr14d3bp1i7lz51ZtNrpixYpqnedjxoyJgoKC9OuHH34YX/jCF9IA/dZbb63D7wIAAAAAgFxRUGGuyS6VlpZGSUlJuslos2bN6rocgD1i06ZNMWDAgKrz2bNnR3FxcZ3WBAAAAFAXcmYmOgAAAAAA7GlCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJCBEB0AAAAAADIQogMAAAAAQAZCdAAAAAAAyECIDgAAAAAAGQjRAQAAAAAgg30yPQEA5KeKioooKyurOi8qKoqCgoI6rQkAAADqihAdAKgmCdAHDBhQdT579uwoLi6u05oAAACgrhjnAgAAAAAAGQjRAQAAAAAgAyE6AAAAAABkIEQHAAAAAIAMhOgAAAAAAJDNEH3u3LnxwgsvVJ1PmTIlunXrFueee2789a9/rclLAgAAAABA/QjRr7nmmigtLU0fv/nmmzFy5Mjo169fLF++PEaMGJHtGgEAAAAAoE7sU5ObkrC8c+fO6eOHHnoozjzzzJgwYUIsXrw4DdMBAAAAACBvO9EbNWoUmzdvTh8/++yzcdppp6WPW7ZsWdWhDgAAAAAAedmJfsIJJ6RjW44//vhYuHBhzJo1K11/55134qCDDsp2jQAAAAAAkDud6Lfffnvss88+8dvf/jbuvPPOaNeuXbr+5JNPxumnn57tGgEAAAAAIHc60Q8++OB4/PHHd1j/6U9/mo2aAAAAAAAgdzvRGzRoEGvWrNlh/S9/+Uv6HAAAAAAA5G2IXlFRsdP1LVu2pJuOAgAAAABA3o1z+fnPf55+LSgoiOnTp0dxcXHVc9u2bYvnn38+OnXqFLVpypQp8aMf/ShWr14dXbt2jV/84hfRs2fPjNdv2LAhrr/++nj44Ydj/fr18W//9m8xefLk6NevX63WCQAAAABAnoXolTPPk070qVOnVhvdknSgd+jQIV2vLbNmzYoRI0ak79GrV680DO/bt28sXbo0WrduvcP1W7dujX//939Pn0s2QU02QP3ggw+iefPmtVYjAAAAAAB5GqIvX748/XryySennd0tWrSIPWnSpEkxbNiwGDp0aHqehOlz5syJGTNmxKhRo3a4PllPus9ffPHFaNiwYbqWBP0AAAAAAFBrM9F///vf7/EAPekqX7RoUfTp06dqrbCwMD1fsGDBTu957LHHonfv3vGd73wn2rRpE126dIkJEyako2cySea6l5aWVjsAAAAAAMhP/1IneqUkhL733ntj3rx5sWbNmigvL6/2/O9+97vItnXr1qXvm4Th20vOlyxZstN7li1bltZy3nnnxRNPPBHvvvtuXH755fHpp5/G+PHjd3rPxIkT48Ybb8x6/QAAAAAA5EmIfuWVV6Yh+hlnnJF2dycbje6NknA/mYd+1113pfPbe/ToER9++GG6MWmmEH306NHp3PVKSSd6+/bt92DVAAAAAADkdIg+c+bMeOCBB6Jfv36xp7Rq1SoNwj/++ONq68l527Ztd3rPAQcckM5C334D1COOOCJWr16djodJNkP9Z40bN04PAAAAAACo0Uz0JHzu2LFj9qv5jPdMOsmTETLbd5on58nc8505/vjj0xEu24+beeedd9JwfWcBOgAAAAAAfO4QfeTIkfGzn/0sKioqYk9KxqxMmzYtfvWrX8Xbb78dl112WZSVlcXQoUPT54cMGZKOY6mUPL9+/fp0/EwSns+ZMyfdWDTZaBQAAAAAALI2zuXss8+udp5s2Pnkk0/GkUcemY5M2d7DDz8ctWHQoEGxdu3aGDduXDqSpVu3bjF37tyqzUZXrFgRhYX/+LlAMsv8qaeeiquuuiqOPvroaNeuXRqoX3vttbVSHwAAAAAAeRqil5SUVDs/66yzoi4MHz48PXZm/vz5O6wlo15eeumlPVAZAAAAAAB5G6Lfc889tVsJAAAAAADUh5noAAAAAACQD3a7E3173bt3j4KCgh3Wk7UmTZpEx44d45vf/GacfPLJ2agRAAAAAABypxP99NNPj2XLlkVRUVEalCdHcXFxvPfee3HsscfGqlWrok+fPjF79uzsVwwAAAAAAHtzJ/q6deti5MiRMXbs2Grrt9xyS3zwwQfx9NNPx/jx4+Pmm2+OAQMGZKtWAAAAAADY+zvRH3jggTjnnHN2WB88eHD6XCJ5funSpZ+/QgAAAAAAyKUQPZl7/uKLL+6wnqwlzyXKy8urHgMAAAAAQN6Mc7niiivi0ksvjUWLFqUz0BOvvPJKTJ8+Pa677rr0/Kmnnopu3bplt1oAAAAAANjbQ/QxY8bEIYccErfffnvcd9996drhhx8e06ZNi3PPPTc9T0L2yy67LLvVAgAAAADA3h6iJ84777z0yKRp06Y1fWkAyEkfDb4j6oOy8q3VzlddND2KChtFLjtw5uV1XULOqKioiLKysqrzoqKiKCgoqNOaAAAAcjJEBwCg/kkC9AEDBlSdz549O4qLi+u0JgAAgJwI0Vu2bBnvvPNOtGrVKlq0aLHLjqT169dnqz4AAAAAANj7Q/Sf/vSnsd9++6WPJ0+eXJs1AQAAAABAboXoF1544U4fAwAAAABAfVVY0xvfe++9GDNmTJxzzjmxZs2adO3JJ5+MP/3pT9msDwAAAAAAcitEf+655+Koo46Kl19+OR5++OHYtGlTuv7GG2/E+PHjs10jAAAAAADs3eNctjdq1Ki45ZZbYsSIEVVz0hOnnHJK3H777dmsDyDnfDT4jsh1ZeVbq52vumh6FBU2ilx24MzL67oEAAAAIF860d98880466yzdlhv3bp1rFu3Lht1AQAAAABAbobozZs3j1WrVu2w/tprr0W7du2yURcAAACwB1RUVKRjWiuP5BwA+JzjXAYPHhzXXnttPPjgg1FQUBDl5eXxxz/+Ma6++uoYMmRITV4SAAAAqANlZWUxYMCAqvPZs2dHcXFxndYEADnfiT5hwoTo1KlTtG/fPv0pdefOneMrX/lKHHfccTFmzJjsVwkAAAAAALnSid6oUaOYNm1ajB07Nt566600SO/evXscdthh2a8QAAAAAAByKURftmxZHHrooXHwwQenBwAAAAAA1Ec1CtE7duwYBx10UJx00knx1a9+Nf2arAEAAAAAQOT7TPSVK1fGxIkTo2nTpnHbbbfFl770pTRUP++882L69OnZrxIAAAAAAHIlRG/Xrl0amN91112xdOnS9OjTp0888MADcckll2S/SgAAAAAAyJVxLps3b44XXngh5s+fnx6vvfZadOrUKYYPH56OdwEAAHJLRUVFlJWVVZ0XFRVFQUFBndYEAAA5G6I3b948WrRokXajjxo1Kk488cT0HAAAyE1JgD5gwICq89mzZ0dxcXGd1gQAADkbovfr1y/tRJ85c2asXr06PZIO9GQ2OgAAAAAA5PVM9EcffTTWrVsXc+fOjd69e8fTTz+ddqNXzkqvTVOmTIkOHTpEkyZNolevXrFw4cLdui8J/JNfRx04cGCt1gcAAAAAQJ6H6JWOOuqoOP7449Mg/dhjj401a9bErFmzorYkrz1ixIgYP358LF68OLp27Rp9+/ZN33dX3n///bj66qvToB8AAAAAAGo1RJ80aVJ87Wtfi/333z/tBv+v//qvdJTLQw89FGvXrq3JS+72+w4bNiyGDh0anTt3jqlTp8a+++4bM2bMyHjPtm3b0u74G2+8MQ499NDPfI8tW7ZEaWlptQMAAAAAgPxUo5noSWh+0kknxcUXX5x2d5eUlERt27p1ayxatChGjx5dtVZYWBh9+vSJBQsWZLzvpptuitatW8e3vvWt+MMf/vCZ7zNx4sQ0cAcAAAAAgBqF6K+88spuXXf55ZenIXarVq3i80pmsCdd5W3atKm2npwvWbJkp/ckm5/efffd8frrr+/2+yQhfTIyplLSid6+ffvPUTkAAAAAAHk5E/2z/PrXv66zcSiffPJJXHDBBTFt2rR/KcRv3LhxNGvWrNoBAAAAAEB+qlEn+u6qqKjI2mslQXiDBg3i448/rraenLdt23aH69977710Q9H+/ftXrZWXl6df99lnn1i6dGl88YtfzFp9AAAAAADUP7XaiZ5NjRo1ih49esS8efOqheLJee/evXe4vlOnTvHmm2+mo1wqj2Qz1JNPPjl9bEQLAAAAAAB12omebcms8gsvvDCOOeaY6NmzZ0yePDnKyspi6NCh6fNDhgyJdu3apZuDNmnSJLp06VLt/ubNm6df/3kdAAAAAAByPkQfNGhQrF27NsaNGxerV6+Obt26xdy5c6s2G12xYkUUFuZMcz0AAAAAAHu5nArRE8OHD0+PnZk/f/4u77333ntrqSoAAAAAAOqjWm3bPv/886NZs2a1+RYAAAAAALD3daL/4Q9/iF/+8pfx3nvvxW9/+9t0Fvl9990XhxxySJxwwgnpNXfeeWc2awUA2Gt9NPiOqA/KyrdWO1910fQoKmwUuezAmZfXdQkAAEC+daI/9NBD0bdv32jatGm89tprsWXLlnR948aNMWHChGzXCAAAAAAAuROi33LLLTF16tSYNm1aNGzYsGr9+OOPj8WLF2ezPgAAAAAAyK0QfenSpfGVr3xlh/WSkpLYsGFDNuoCAAAAAIDcDNHbtm0b77777g7rL7zwQhx66KHZqAsAAAAAAHJzY9Fhw4bFlVdeGTNmzIiCgoL46KOPYsGCBXH11VfH2LFjs18lALDH7FvQMKbu37/aOVD/N5atj5vKJmwsCwBAnYToo0aNivLy8jj11FNj8+bN6WiXxo0bpyH6FVdc8bmLAgDqTvID8qKC3A/OAAAAoM5C9OQv19dff31cc8016ViXTZs2RefOnaO4uDgrRQEAAAAAQM6G6JUaNWqUhucAAACQj4xz2jsZ5QRAnYToZ5999m6/6MMPP1zTegAAAAAAIPdC9JKSktqtBAAAAAAAcjVEv+eee2q3EgAAAAAAqE8z0desWRNLly5NHx9++OHRunXrbNUFAAAAAAB1rrAmN5WWlsYFF1wQ7dq1i5NOOik9ksfnn39+bNy4MftVAgAAAABAroTow4YNi5dffjkef/zx2LBhQ3okj1999dW45JJLsl8lAAAAAFlXUVERmzZtqjqScwCyMM4lCcyfeuqpOOGEE6rW+vbtG9OmTYvTTz+9Ji8JAAAAwB5WVlYWAwYMqDqfPXt2FBcX12lNAPWiE33//fePkpKSHdaTtRYtWmSjLgAAAAAAyM0QfcyYMTFixIhYvXp11Vry+JprromxY8dmsz4AAAAAAMitcS533nlnvPvuu3HwwQenR2LFihXRuHHjWLt2bfzyl7+sunbx4sXZqxYAAAAAAPb2EH3gwIHZrwQAAAAAAOpDiD5+/PjsVwIAAAAAAPUhRN/epk2bory8vNpas2bNPu/LAgAAAABAbm4sunz58jjjjDOiqKgoSkpKokWLFunRvHnz9CsAAAAAAORtJ/r5558fFRUVMWPGjGjTpk0UFBRkvzIAAAAAAMjFEP2NN96IRYsWxeGHH579igAAAAAAIJfHuRx77LGxcuXK7FcDAAAAAAC53ok+ffr0uPTSS+PDDz+MLl26RMOGDas9f/TRR2erPqCOJCObysrKqs6TPRCMbgKA+mvfgoYxdf/+1c4BAIAadqKvXbs23nvvvRg6dGjald6tW7fo3r171dfaNGXKlOjQoUM0adIkevXqFQsXLsx47bRp0+LEE0+s2vi0T58+u7we+IckQB8wYEDVsX2gDgDUP8kPy4sKG1UdfngOAACfI0S/6KKL0rB8wYIFsWzZsli+fHm1r7Vl1qxZMWLEiBg/fnwsXrw4unbtGn379o01a9bs9Pr58+fHOeecE7///e/TWtu3bx+nnXZa2kEPAADAP34LcdOmTVVHcg4AwOcY5/LBBx/EY489Fh07dow9adKkSTFs2LC0Az4xderUmDNnTsyYMSNGjRq1w/W/+c1vdhhD89BDD8W8efNiyJAhe6xuAACAXPgtxEqzZ8+O4uLiOq0JACCnO9FPOeWUeOONN2JP2rp1ayxatCgdyVKpsLAwPU+6zHfH5s2b49NPP42WLVtmvGbLli1RWlpa7QAAAAAAID/VqBO9f//+cdVVV8Wbb74ZRx111A4bi37ta1+LbFu3bl1s27Yt2rRpU209OV+yZMluvca1114bBx54YLUg/p9NnDgxbrzxxs9dLwAAAAAAeRqiX3rppenXm266aYfnkg2IkrB7b/ODH/wgZs6cmc5JTzYlzWT06NHp3PVKSSd6MksdACAf7FvQMKbu37/aOQAAQD6rUYheXl4ee1qrVq2iQYMG8fHHH1dbT87btm27y3t//OMfpyH6s88+G0cfffQur23cuHF6AADko6QhoqigUV2XAQA54aPBd0SuKyvfWu181UXTo6gwt/+/wIEzL6/rEoB6pkYz0etCo0aNokePHummoNuH+cl57969M9532223xc033xxz586NY445Zg9VCwAAAABA3naiV+7e/txzz8WKFSvSTT+3993vfjdqQzJm5cILL0zD8J49e8bkyZPTOoYOHZo+P2TIkGjXrl061zzxwx/+MMaNGxf3339/dOjQIVavXp2uJ7vM22keAAAAgHxWUVGRZmuVioqK0t9MJD/4/Gs5RH/ttdeiX79+sXnz5vQPumXLlunGn/vuu2+0bt261kL0QYMGxdq1a9NgPAnEu3XrlnaYV242mgT6hYX/aK6/884704D/61//erXXGT9+fNxwww21UiMAAAAA5IIk1xswYEDV+ezZszWe5hGffy2H6FdddVX0798/pk6dGiUlJfHSSy9Fw4YN4/zzz48rr7wyatPw4cPTY2eSTUO39/7779dqLQAAAAAA1G81mon++uuvx8iRI9Ou72Szzy1btkT79u3T+ePXXXdd9qsEAAAAAIBc6URPus4rx6Yk41uSMSpHHHFE2pW+cuXKbNcIwB62b0HDmLp//2rnAAAAAPmoRiF69+7d45VXXonDDjssTjrppHRGeTIT/b777osuXbpkv0oA9qhkI5GigkZ1XQYAAHuABgoAqIVxLhMmTIgDDjggfXzrrbdGixYt4rLLLkuD9F/+8pc1eUkAAACgrhooChtVHck5APA5O9GPPPLIqKioqBrnkmww+sgjj0Tnzp2jW7duNXlJAAAAAPj/t3cvUFaW9eLHfzPgFUTFCxflogcTTBPRo6GmmSYqluSlk53yVlp5zNQyM8s0TlEdc5mZaR3NQ2aWLa+ZJt4yEVHBy9LULElRVEQEBEUU9n+973+xD3NkIw7OvM3+fT5r7cXs/c7Ao1/emc2zn/28AM2xEv2AAw6I8ePHlx/PmTMn3v/+98fZZ58dY8aMiZ/+9Kfv9hgBAAAAAKDrTKJPnTo1PvCBD5Qf/+53v4s+ffrEU089VU6sn3vuue/2GAEAAAAAoOtMor/66quxzjrrlB/fdNNNceCBB0Zra2u5Ir2YTAcAAAAAgLST6EOGDImrr746pk+fHn/84x9j7733Lh+fOXNm9OrV690eIwAAAAAAdJ1J9NNPPz2+8pWvxODBg2OnnXaKkSNH1lelb7fddu/2GAEAAAAAoBLd2/NFBx98cOy6667x3HPPxbbbblt/fM8994yPfexj7+b4AAAAAACga02iF/r27VvelrXjjju+G2MCAAAAAICuu50LAAAAAABk0O6V6AAAAAB0bWu3rBYXbPCRNvcBaMskOgAAwCqY8Ynzo6tbsGRRm/vPHfXf0aN19ejq+l9+bNVDgH96LS0t0aOl65/vAB3Jdi4AAAAAANCAleg0VKvVYsGCBfX7PXr0KF+hBgAAAADIwiQ6DRUT6AcccED9/jXXXBM9e/asdEwAAAAAUDXbueXays0kOgAAAAC8QyZR/zm5HgYdwZ7oAAAAAADQgEl0AAAAAABowCQ6AAAAAAA0YBIdAAAAAAAacGFR6AAuLvLPycVFAAAAAHinrEQHAAAAAIAGTKIDAAAAAEADJtEBAAAAAKABk+gAAAAAANAsk+g/+clPYvDgwbHmmmvGTjvtFPfcc88KP/+KK66IoUOHlp+/zTbbxB/+8IdOGysAAAAAAF1bl5pE/81vfhMnnXRSfOtb34qpU6fGtttuG6NGjYqZM2cu9/PvuuuuOPTQQ+Mzn/lM3H///TFmzJjy9vDDD3f62AEAAAAA6Hq6Rxdy9tlnx9FHHx1HHnlkef+CCy6I66+/Pi6++OL42te+9pbP/9GPfhT77LNPnHzyyeX9sWPHxoQJE+K8884rv7YjzfjE+dHVLViyqM3954767+jRunp0Zf0vP7bqIQAAAAAAXUiXWYm+aNGimDJlSuy11171x1pbW8v7kyZNWu7XFI8v+/mFYuV6o88vvP766zFv3rw2NwAAAAAAcuoyK9FnzZoVixcvjj59+rR5vLj/2GOPLfdrnn/++eV+fvF4I+PGjYszzzxzlcfbDCue58+fH3HAdfX7/S7+bPTs2bPSMXUV+ufWDP1pH+1z0z83/XNrhv6e++XuT/vpn1sz9Pf9v/30z6XLrETvLKeeemrMnTu3fps+fXrVQwIAAAAAoCJdZiX6hhtuGN26dYsXXnihzePF/b59+y73a4rH38nnF9ZYY43yBgAAAAAAXWYl+uqrrx7bb7993HLLLfXHlixZUt4fOXLkcr+meHzZzy8UFxZt9PkAAAAAANAlV6IXTjrppDj88MNjhx12iB133DHOOeecWLBgQRx55JHl8cMOOyw22WSTcl/zwpe+9KXYfffd44c//GGMHj06Lr/88rjvvvviZz/7WcX/JQAAAAAA1enRo0dcc801be7TBJPo//Zv/xYvvvhinH766eXFQYcPHx433nhj/eKhTz/9dLS2/u/i+p133jkuu+yy+MY3vhFf//rXY4sttoirr746tt566wr/KwAAAAAAqtXS0uJCos04iV447rjjytvy3H777W957JBDDilvAAAAAADQ9JPoAAAAvLu8nRsgJ9//YeWYRAcAAEjO27kBcvL9H1bO/24gDgAAAAAAtGESHQAAAAAAGjCJDgAAAAAADZhEBwAAAACABlxYlIZcoRkAAAAAyM4kOg25QjMAAAAAkJ3tXAAAAAAAoAGT6AAAAAAA0IBJdAAAAAAAaMAkOgAAAAAANGASHQAAAAAAGjCJDgAAAAAADZhEBwAAAACABkyiAwAAAABAAybRAQAAAACgAZPoAAAAAADQQEutVqs1OkjEvHnzYt111425c+dGr169qh4OdJriW8OCBQvq93v06BEtLS2VjgkAAAAAOlv3Tv8TgS6hmDDv2bNn1cMAAAAAgErZzgUAAAAAABowiQ4AAAAAAA2YRAcAAAAAgAZMogMAAAAAQAMm0QEAAAAAoAGT6AAAAAAA0IBJdAAAAAAAaMAkOgAAAAAANGASHQAAAAAAuvok+uzZs+Pf//3fo1evXrHeeuvFZz7zmZg/f/4KP/+LX/xibLnllrHWWmvFwIED4/jjj4+5c+d26rgBAAAAAOi6uswkejGB/sgjj8SECRPi97//fdxxxx1xzDHHNPz8GTNmlLezzjorHn744bjkkkvixhtvLCffAQAAAABgZbTUarVa/JN79NFHY6uttop77703dthhh/KxYkJ8v/32i2eeeSb69++/Ur/PFVdcEZ/61KdiwYIF0b179+V+zuuvv17elpo3b14MGDCgXMFerIIHAAAAACCPLrESfdKkSeUWLksn0At77bVXtLa2xuTJk1f691k6Ed5oAr0wbty4WHfddeu3YgIdAAAAAICcusQk+vPPPx8bb7xxm8eKifDevXuXx1bGrFmzYuzYsSvcAqZw6qmnlpPtS2/Tp09fpbEDAAAAANB1VTqJ/rWvfS1aWlpWeHvsscdW+c8ptmQZPXp0uSXMGWecscLPXWONNcrV6sveAAAAAADIqfG+Jp3gy1/+chxxxBEr/JzNN988+vbtGzNnzmzz+JtvvhmzZ88uj63IK6+8Evvss0+ss846cdVVV8Vqq632rowdAAAAAIDmV+kk+kYbbVTe3s7IkSNjzpw5MWXKlNh+++3Lx2699dZYsmRJ7LTTTitcgT5q1Khydfm1114ba6655rs6fgAAAAAAmluX2BN92LBh5Wryo48+Ou65556YOHFiHHfccfGJT3wi+vfvX37Os88+G0OHDi2PL51A33vvvWPBggVx0UUXlfeL/dOL2+LFiyv+LwIAAAAAoCuodCX6O/GrX/2qnDjfc889o7W1NQ466KA499xz68ffeOONePzxx+PVV18t70+dOjUmT55cfjxkyJA2v9e0adNi8ODBnfxfAAAAAABAV9NSq9VqVQ/in9ncuXNjvfXWi+nTp7vIKAAAAABAkymup9nS0tL1V6JXpbgwaWHAgAFVDwUAAAAAgA5YSL2iBdRWor+N4uKlM2bMeNtXI5pVsZd88QKClfg56Z+b/rnpn5v+eWmfm/656Z+b/rnpn5v+/5+V6Kuo2H990003jeyKkyjziZSd/rnpn5v+uemfl/a56Z+b/rnpn5v+uem/Yq1vcxwAAAAAANIyiQ4AAAAAAA2YRGeF1lhjjfjWt75V/ko++uemf27656Z/Xtrnpn9u+uemf27656b/ynFhUQAAAAAAaMBKdAAAAAAAaMAkOgAAAAAANGASHQAAAAAAGjCJDgAAAAAADZhEBwAAAACABkyiAwAAAABAAybRWWkvvPBCfPvb3656GHSwZ555JubPn/+Wx99444244447KhkTHe+ll16K2267LWbPnl3enzVrVnz/+98vz/lHH3206uFRId/7m99rr70Wd955Z/zlL395y7GFCxfG+PHjKxkX1Zs+fXocddRRVQ+Diuifg+f+LI/nf7npn5v+jbXUarXaCo5D3YMPPhgjRoyIxYsXVz0UOsBzzz0XBxxwQEyZMiVaWlrik5/8ZJx//vnRs2fP+jfS/v3769+E7rnnnth7771j3rx5sd5668WECRPikEMOie7du8eSJUtixowZ5QRbcf6Tj+/9ze2vf/1ref4//fTT5ff+XXfdNS6//PLo169fedz3/tyc/7np39w892dFnP+56Z+b/o11X8ExknnooYdWePzxxx/vtLHQ+b72ta9Fa2trTJ48OebMmVPe32OPPeKmm26K9ddfv/wcr7k1p9NOO62cND/77LPjwgsvjDFjxsQ+++wTP//5z8vjxSq0sWPHxlVXXVX1UOkAvvfndsopp8TWW28d9913X/m9/4QTTohddtklbr/99hg4cGDVw6ODXXvttSs8/uSTT3baWOh8+ufmuX9unv/lpn9u+reflejUFU+iilUIy/srsfTx4levRjWnTTbZpJwk3XHHHcv7r7/+ejmxWryV95Zbbinf0mk1SnPq3bt3TJw4MYYNG1Z2XnPNNWPSpEn1vwtTp06Nj370o+XbfWk+vvfn1qdPn7j55ptjm222Ke8XvY899tj4wx/+UG7x1KNHD9/7k57/Szn/m5f+uXnun5vnf7npn5v+7WdPdNpMpBUrT6dNm/aWW7ES5fe//33VQ6QDzZ07t77qpLDGGmvElVdeGYMHDy5XpcycObPS8dFxFi1aFGuttVb58WqrrRZrr712bLjhhvXjxcfFnuk0J9/7cyv2Qy+2blqqeML805/+ND7ykY/E7rvvXm73QvMqtu0pftYXW3ct71a8iErz0j83z/1z8/wvN/1z07/9bOdC3fbbb1/ufTxo0KDlHi/e5ueNC81r8803L9/Ws8UWW9QfKyZWrrjiinJVyv7771/p+Og4AwYMKH9YFv9oKiy7H/LSPTOXnVSnufjen9vQoUPLrVyKd6Is67zzzit/Ld6FQnOf/8V+yMW+yMvzdquU6dr0z81z/9w8/8tN/9z0bz8r0an7/Oc/X59EW55ib9Rf/OIXnTomOs++++4bP/vZz97y+NIn08OHD69kXHS8T3ziE21WG40ePbq+Mn3pnqlL3+pL8/G9P7ePfexj8etf/3q5x4qJ9EMPPdST6CZ28sknx84779zw+JAhQ8ptfWhO+ufmuX9unv/lpn9u+refPdGB0ptvvhmvvvpq9OrVq+HxZ599tuGrlTSv4u9Ft27dyrf5AgDQ9XnuDwDvjEl03lbxBGrhwoXRs2fPqodCBfTPS/vc9M/tqaeeigULFpTbvRQXHyIX/XPTPzc//3PTPzf9c9P/7XlWRN11110Xl1xySZvHvvOd75Qn0HrrrRd77713vPzyy5WNj46lf17a56Z/bhdffHGcffbZbR475phjyr1yt9lmm9h6661j+vTplY2PjqV/bvrn5ud/bvrnpn9u+refSXTqiifRxaqTpe666644/fTT45vf/Gb89re/LZ9Ejx07ttIx0nH0z0v73PTPrdgPd/3116/fv/HGG8s9EMePHx/33ntv+UT6zDPPrHSMdBz9c9M/Nz//c9M/N/1z038VFNu5QGGjjTaqTZ06tX7/xBNPrI0aNap+//rrr68NGTKkotHR0fTPS/vc9M+td+/etYceeqh+//Of/3ztoIMOqt+/7bbbaoMHD65odHQ0/XPTPzc//3PTPzf9c9O//axEp+6VV16JDTbYoH7/zjvvjD333LN+/73vfW/MmDGjotHR0fTPS/vc9M/ttddea3NRuWIlym677Va/X2zr8Pzzz1c0Ojqa/rnpn5uf/7npn5v+uenffibRqdtkk03i0UcfLT+eP39+PPjgg7HzzjvXj7/00kux9tprVzhCOpL+eWmfm/65DRo0KKZMmVJ+PGvWrHjkkUdil112qR8vJtDWXXfdCkdIR9I/N/1z8/M/N/1z0z83/duv+yp8LU3mkEMOiRNOOCG+/vWvxx/+8Ifo27dvvP/9768fv++++2LLLbesdIx0HP3z0j43/XM7/PDD4z/+4z/KybNbb701hg4dGttvv32blanFxQVpTvrnpn9ufv7npn9u+uemf/uZRKeuuJDAs88+G8cff3x5El166aXRrVu3+vFf//rX8ZGPfKTSMdJx9M9L+9z0z+2rX/1qvPrqq3HllVeW/a+44oo2xydOnBiHHnpoZeOjY+mfm/65+fmfm/656Z+b/u3XUmyMvgpfDwAAAAAATctKdJZr7ty59QsJFa9M2Q8xF/0BIJenn346nnvuuWhtbS0vKLnsBadobosXL26zAu2ee+6JJUuWxHbbbRdrrLFGpWMDAPhn4cKitPHf//3fsdVWW0Xv3r3LX5f9+KKLLqp6eHQw/fMq9kL77Gc/W761e+lFRpZ6+eWX40Mf+lBlY6Pj6U8jxYWGlp1co/mcf/755QUmN9tss/KiUsWemBtvvHHsuuuu9YtO0pyeeuqpcg/0YqJ83333jXnz5sWHP/zh8u9A8Xdh2LBh8de//rXqYdJBihdLihdQlvr9738fu+++e3nBuR122CHGjx9f6fjoWPrnts4668RnPvOZ8toX5OP8bz+T6NT913/9V3zpS1+KAw44IG655ZZ4+OGHy1vx8ZgxY8pjZ511VtXDpIPon9dll10WH/3oR8t3H0yaNClGjBgRv/rVr+rHFy1aFH/6058qHSMdR3/ejp3/mlfxc/073/lOnHzyyXHhhReWF5E644wz4vrrry9Xo++2227lxaVoTl/+8pfLiZSrr746evXqFfvtt1+8+eabMX369HKv1Pe85z1xyimnVD1MOsjIkSPjpZdeKj++7rrryn8DDB48OE477bTyXQjFBNtVV11V9TDpIPrntmDBgpg8eXL5gnnxgukPf/jDePHFF6seFp3E+d9+9kSnrliFVEykfvzjH1/u8d/85jflP7KKt/vSfPTPq/hBeeSRR5YXFin89re/jaOOOip+9KMflT9AX3jhhejfv3+bV6tpHvrnduCBB77t9l633367/k2qWH1erEQvViEXilXHxQrk4kW17t27ly+gF+9Ouemmm6oeKh2geMdB0Xb48OHlub7++uvHHXfcUU6qFKZOnVpOrC/d4o/mUmzdVLQt/h584AMfKLuPGzeufvy73/1uOblSvMBO89E/t6X9i23cinejF4tq5s+fH/vvv3/57tR99tknWlpaqh4mHcT5335WolM3c+bM2GabbRoeL47NmjWrU8dE59E/ryeeeKLN1beLF1KKH5onnHBCXHDBBZWOjY6nf25F64ULF5bXvljerWfPnlUPkQ7+2V+sQFtqiy22KCdTl65GK15Q8w+o5rX03C8UK9KLrZuKX5cqVqe/+uqrFY6QzlK8gHbwwQe3eeyggw6Kxx57rLIx0Xn0z2vbbbeNH//4xzFjxoy45JJLyucAxUT6wIED4/TTT696eHQC5/8748Ki1P3rv/5rfO973yv3vi5WHy2rWIH2/e9/v/wcmpP+eRX/SC5WGxcrEpfaY489yr3RiidRzzzzTKXjo2Ppn1sxgVo8US7edbA8DzzwQPl3geZUbNcxYcKEOProo8v7t912W6y++urlRcULa665ppVoTey9731vXHzxxTF27Nj4n//5n/Jispdffnk5qVL49a9/Xf4doXn95S9/KVcjrrXWWuXFZP+vYnsfmpf+ef3fn+3FtTEOPfTQ8vaPf/yjnBMoJtW//e1vVzZGOpbzv31MolN33nnnxahRo8p/OBV7YPbp06d8vJhcKd7aWfyjytt5m5f+ee24445xww03lBcSW1ZxcZFilWoxkUrz0j+34qKCxZYNjSbRi39UFauRaE6nnnpqfOpTn4qbb765nDC/8sory62dlv7jutjKZ+utt656mHSQYv/74ro3P/jBD8q3dv/xj38sX1C59dZby/v33ntv+RZ/mteee+5Zv+7FxIkT2yyYuf/++33/b3L657WiXZ2LvbGLF1dNoDc353/72BOdNl555ZW49NJL4+67767vf1hMqhYXHvjkJz9ZrlikeemfU3HRyOLK7MVkyvIUKxOLK3T/4he/6PSx0fH0z+31118v32209tprVz0UKlK8iFb87C/+LhQvpi9dlV5YetGpYoUyzalYcThlypTyBbVi4qRYPPGTn/yk3MZl9OjR5TuTaE5PPfVUm/vF9l3LnuvFz/7CYYcd1uljo+Ppn9uZZ55ZXu/M87+cnP/tZxIdAAAAAAAacGFR3taRRx5ZXmiCnPTPo1iNuqzJkyeXW/m88cYblY2JzqN/bvpDXs7/3PSHvJz/uen/zplEp+6hhx5a7u1Xv/pV3HPPPfX7NCf983ruuedil112Kfc+LvbBfvnll8t9sIttfD74wQ+W++EWn0Nz0j+3ou2uu+6qf1LFP5K++tWvxpAhQ8rrIxQXmVxWsbVHt27dKhsfHcv5n5v+ufn+n5vzPzf9288kOnXDhw+P7bbbrvx12VtxVd6DDjqofpzmpH9ep5xySvnrVVddFf369St/gM6bNy+mT59e7pW60UYbxXe+852qh0kH0T+3on+xs5/+ORVti30vP//5z8fee+8dJ510Unzuc59r8zl2fmxezv/c9M/N9//cnP+56b8Kij3RobDtttvWRo8eXXv00Udr//jHP8rbtGnTat27d69NmDCh/hjNSf+8+vXrV5s0aVL58UsvvVRraWmp3XzzzfXjt9xyS23zzTevcIR0JP1z0z+3IUOG1K677rr6/SeeeKJ87IgjjqgtWbKk9vzzz9daW1srHSMdx/mfm/65+f6fm/M/N/3bz0p06ootO4q3cxWrjmfPnh2DBg2KwYMHl8f69+9f3i9uNCf98yrevrXJJpuUH/fu3bu8SvuyrYu/F97O1bz0z03/3J599tnyLbvL9r799tvjrrvuik9/+tNv2SuT5uL8z03/3Hz/z835n5v+7WcSnbrVV189zjnnnDjrrLPiox/9aIwbNy6WLFlS9bDoJPrntfHGG7f5IXnccceVP0yX/SHbo0ePikZHR9M/N/1z69u3b/z9739v81jxj6rbbrst7r333jjiiCMqGxsdz/mfm/65+f6fm/M/N/3bzyQ6b7HvvvvGfffdF3/+85/LiwqQi/75FPvdT5o0qX7/e9/7XpsfonfeeWe8733vq2h0dDT9c9M/tw996ENx2WWXveXx4h1ot956a0ybNq2ScdE5nP+56Z+b7/+5Of9z07/9Woo9XVbh62ly5557bvlq9I9//OPYdNNNqx4OnUx/lm71U7zFa9m3fJKH/rnp39yeeuqpeOyxx2LUqFHLPT5jxoyYMGFCHH744Z0+Nqrn/M9N/+bm+z8r4vzPTf/GrERnhY4//vjyir3FBOrMmTPju9/9btVDohPpT6HYG//aa6+tehhURP/c9G9uxf6XjSZQCt27dy/3zSUn539u+jc33/9ZEed/bvo3ZiU6K+3BBx+MESNGuMhIUvrnpX1u+uemf27656Z/bvrnpn9u+uemf2NWogMAAAAAQAMm0QEAAAAAoAGT6AAAAAAA0ED3RgfI56STTlrh8RdffLHTxkLn0z8v7XPTPzf9c9M/N/1z0z83/XPTPzf9288kOnX333//237Obrvt1iljofPpn5f2uemfm/656Z+b/rnpn5v+uemfm/7t11Kr1Wqr8PUAAAAAANC07IkOAAAAAAANmERnpV1zzTUxfvz4qodBRfTPS/vc9M9N/9z0z03/3PTPTf/c9M9N/8Zs58JKGzp0aDzxxBOxePHiqodCBfTPS/vc9M9N/9z0z03/3PTPTf/c9M9N/8ZMogMAAAAAQAO2c2GlzZkzJy677LKqh0FF9M9L+9z0z03/3PTPTf/c9M9N/9z0z03/xqxEZ6U9+OCDMWLECG/pSEr/vLTPTf/c9M9N/9z0z03/3PTPTf/c9G/MSnQAAAAAAGjAJDoAAAAAADRgEh0AAAAAABro3ugA+Zx77rkrPP7ss8922ljofPrnpX1u+uemf27656Z/bvrnpn9u+uemf/u5sCh1m2222Up93rRp0zp8LHQ+/fPSPjf9c9M/N/1z0z83/XPTPzf9c9O//UyiAwAAAABAA/ZEZ6U988wzccwxx1Q9DCqif17a56Z/bvrnpn9u+uemf27656Z/bvo3ZiU6K+3BBx+MESNGxOLFi6seChXQPy/tc9M/N/1z0z83/XPTPzf9c9M/N/0bsxIdAAAAAAAaMIkOAAAAAAANmEQHAAAAAIAGujc6QD4HHnjgCo/PmTOn08ZC59M/L+1z0z83/XPTPzf9c9M/N/1z0z83/dvPJDp166677tseP+ywwzptPHQu/fPSPjf9c9M/N/1z0z83/XPTPzf9c9O//VpqtVptFb4eAAAAAACalj3RWSnFay033HBDHHzwwVUPhZ8Lv44AABCXSURBVAron5f2uemfm/656Z+b/rnpn5v+uemfm/4rZhKdFZo2bVp885vfjIEDB8bHPvaxWLhwYdVDohPpn5f2uemfm/656Z+b/rnpn5v+uemfm/4rqdjOBZa1cOHC2qWXXlrbY489aquttlqttbW1dvbZZ9fmzp1b9dDoBPrnpX1u+uemf27656Z/bvrnpn9u+uem/ztnJTp1U6ZMiWOPPTb69u0b55xzTowZMyamT58era2tMWrUqOjVq1fVQ6QD6Z+X9rnpn5v+uemfm/656Z+b/rnpn5v+7dd9Fb6WJrPTTjvFF7/4xbj77rtjyy23rHo4dDL989I+N/1z0z83/XPTPzf9c9M/N/1z07/9TKJTt+eee8ZFF10UM2fOjE9/+tPlK1AtLS1VD4tOon9e2uemf27656Z/bvrnpn9u+uemf276t5/tXKj74x//GI888kj5StQXvvCF6NevX3zpS18qjzmhmp/+eWmfm/656Z+b/rnpn5v+uemfm/656d9+LcXG6Kvw9TSxCRMmxC9+8Yu46qqrYsCAAXHwwQeXtxEjRlQ9NDqB/nlpn5v+uemfm/656Z+b/rnpn5v+uem/8kyi87ZefvnluPTSS+Piiy+Ohx56KBYvXlz1kOhE+uelfW7656Z/bvrnpn9u+uemf27656b/2zOJzjsydepUr0Ylpn9e2uemf27656Z/bvrnpn9u+uemf276L59JdAAAAAAAaMCFRVlpw4YNi27dulU9DCqif17a56Z/bvrnpn9u+uemf27656Z/bvo31n0Fx0hm2rRpsdlmmzU8Pm7cuJg7d26njonOo39e2uemf27656Z/bvrnpn9u+uemf276t5/tXKhrbW2NQYMGxR577FG/bbrpplUPi06if17a56Z/bvrnpn9u+uemf27656Z/bvq3n0l06m6//fb6bfLkybFo0aLYfPPN40Mf+lD9xOrTp0/Vw6SD6J+X9rnpn5v+uemfm/656Z+b/rnpn5v+7WcSneVauHBh3HXXXfUT65577ok33ngjhg4dGo888kjVw6OD6Z+X9rnpn5v+uemfm/656Z+b/rnpn5v+74xJdFaoeEVq4sSJccMNN8SFF14Y8+fPj8WLF1c9LDqJ/nlpn5v+uemfm/656Z+b/rnpn5v+uem/ckyi85YT5+67747bbrut/taOAQMGxG677Vbedt999xg4cGDVw6SD6J+X9rnpn5v+uemfm/656Z+b/rnpn5v+7WMSnbpi/6PixCmu0lucMB/4wAfKX/v161f10OgE+uelfW7656Z/bvrnpn9u+uemf27656Z/+5lEp2611VYrT5oxY8bEBz/4wfIk2mCDDaoeFp1E/7y0z03/3PTPTf/c9M9N/9z0z03/3PRvP5Po1C1YsCD+/Oc/l2/lKN7S8cADD8R73vOe8oRaemJttNFGVQ+TDqJ/Xtrnpn9u+uemf27656Z/bvrnpn9u+refSXQaeuWVV+LOO++s75H04IMPxhZbbBEPP/xw1UOjE+ifl/a56Z+b/rnpn5v+uemfm/656Z+b/iuv9R18Lsn06NEjevfuXd7WX3/96N69ezz66KNVD4tOon9e2uemf27656Z/bvrnpn9u+uemf276rzwr0albsmRJ3HffffW3dEycOLF8m8cmm2wSe+yxR/02aNCgqodKB9A/L+1z0z83/XPTPzf9c9M/N/1z0z83/dvPJDp1vXr1Kk+cvn371k+aYj+kf/mXf6l6aHQC/fPSPjf9c9M/N/1z0z83/XPTPzf9c9O//UyiU3fhhReWJ09xQQHy0T8v7XPTPzf9c9M/N/1z0z83/XPTPzf9288kOgAAAAAANNC90QHy2W677aKlpeUtj6+77rrlK1QnnHBCDBs2rJKx0fH0z0v73PTPTf/c9M9N/9z0z03/3PTPTf/2M4lO3ZgxY5b7+Jw5c2Lq1KkxfPjwuPXWW2OXXXbp9LHR8fTPS/vc9M9N/9z0z03/3PTPTf/c9M9N//aznQsr7bTTTou77747brnllqqHQgX0z0v73PTPTf/c9M9N/9z0z03/3PTPTf/GTKKz0h555JHy4gMzZ86seihUQP+8tM9N/9z0z03/3PTPTf/c9M9N/9z0b6x1BcegjW7dusWSJUuqHgYV0T8v7XPTPzf9c9M/N/1z0z83/XPTPzf9GzOJzkq78sorY6uttqp6GFRE/7y0z03/3PTPTf/c9M9N/9z0z03/3PRvzIVFqTv33HOX+/jcuXNjypQpcf3118cNN9zQ6eOic+ifl/a56Z+b/rnpn5v+uemfm/656Z+b/u1nT3TqNttss+U+3qtXr9hyyy3jxBNPjJEjR3b6uOgc+uelfW7656Z/bvrnpn9u+uemf27656Z/+5lEBwAAAACABuyJDgAAAAAADZhEZ6Vdc801MX78+KqHQUX0z0v73PTPTf/c9M9N/9z0z03/3PTPTf/GbOfCShs6dGg88cQTsXjx4qqHQgX0z0v73PTPTf/c9M9N/9z0z03/3PTPTf/GTKIDAAAAAEADtnMBAAAAAIAGTKLTRvHGhGnTpsWbb75Z3l+0aFH85je/KfdDmjVrVtXDo4Ppn5f2uemfm/656Z+b/rnpn5v+uemfm/7tVGznAoXHHnusNmjQoFpra2ttyJAhtSeffLK2/fbb13r06FFbe+21axtuuGHtr3/9a9XDpIPon5f2uemfm/656Z+b/rnpn5v+uemfm/7tZyU6daecckpsu+228cADD8T+++8fo0ePjk033TRefvnlmD17dowcOTK+/e1vVz1MOoj+eWmfm/656Z+b/rnpn5v+uemfm/656b8KVmECniaz0UYb1e6///7y4/nz59daWlpqf/7zn+vHJ06cWBs4cGCFI6Qj6Z+X9rnpn5v+uemfm/656Z+b/rnpn5v+7WclOnXz58+P3r17lx/36NGjvPXr169+fMCAAfHCCy9UOEI6kv55aZ+b/rnpn5v+uemfm/656Z+b/rnp334m0anr379/PP300/X7P/jBD2LjjTeu33/xxRdj/fXXr2h0dDT989I+N/1z0z83/XPTPzf9c9M/N/1z07/9TKJTt9dee8Vjjz1Wv/+FL3wh1llnnfr9m266KUaMGFHR6Oho+uelfW7656Z/bvrnpn9u+uemf27656Z/+7UUe7qswteTyLRp02LNNdds8zYP8tA/L+1z0z83/XPTPzf9c9M/N/1z0z83/RvrvoJjJLNw4cK4+eaby6vzFk499dR4/fXX68e7desWY8eOrXCEdCT989I+N/1z0z83/XPTPzf9c9M/N/1z07/9TKJTd8kll8T1119fP5HOO++8eO973xtrrbVWeb94u0exd9KJJ55Y8UjpCPrnpX1u+uemf27656Z/bvrnpn9u+uem/yootnOBwq677lq79tpr6/d79uxZ+/vf/16//8tf/rL2/ve/v6LR0dH0z0v73PTPTf/c9M9N/9z0z03/3PTPTf/2c2FR6v72t7/FNttsU79f7IHU2vq/f0V23HHH+Mtf/lLR6Oho+uelfW7656Z/bvrnpn9u+uemf27656Z/+9nOhbo5c+a02QfpxRdfbHN8yZIlbY7TXPTPS/vc9M9N/9z0z03/3PTPTf/c9M9N//azEp26TTfdNB5++OGGxx966KHyc2hO+uelfW7656Z/bvrnpn9u+uemf27656Z/+5lEp26//faL008/vbxS7//12muvxZlnnhmjR4+uZGx0PP3z0j43/XPTPzf9c9M/N/1z0z83/XPTv/1aio3RV+HraSIvvPBCDB8+PFZfffU47rjj4j3veU/5+OOPP15erffNN9+M+++/P/r06VP1UOkA+uelfW7656Z/bvrnpn9u+uemf27656b/KliFi5LShJ588snaqFGjaq2trbWWlpbyVnxcPLbs1XppTvrnpX1u+uemf27656Z/bvrnpn9u+uemf/tYic5yzZ49u7xib2HIkCHRu3fvqodEJ9I/L+1z0z83/XPTPzf9c9M/N/1z0z83/d8Zk+gAAAAAANCAC4sCAAAAAEADJtEBAAAAAKABk+gAAAAAANCASXQAAAAAAGjAJDoAALDKjjjiiBgzZkzVwwAAgHedSXQAAAAAAGjAJDoAAAAAADRgEh0AALqY3/3ud7HNNtvEWmutFRtssEHstddesWDBgrj33nvjwx/+cGy44Yax7rrrxu677x5Tp05t87UtLS1x4YUXxv777x9rr712DBs2LCZNmhR/+9vf4oMf/GD06NEjdt555/j73/9e/5ozzjgjhg8fXn7dgAEDyq/7+Mc/HnPnzm04xiVLlsS4ceNis802K8e57bbbluMGAICuxiQ6AAB0Ic8991wceuihcdRRR8Wjjz4at99+exx44IFRq9XilVdeicMPPzzuvPPOuPvuu2OLLbaI/fbbr3x8WWPHjo3DDjssHnjggRg6dGh88pOfjM997nNx6qmnxn333Vf+Xscdd1ybrykm2X/729/GddddFzfeeGPcf//9ceyxxzYcZzGBPn78+LjgggvikUceiRNPPDE+9alPxZ/+9KcO+38DAAAdoaVWPEMGAAC6hGJl+fbbbx//+Mc/YtCgQSv83GI1+HrrrReXXXZZufJ86Ur0b3zjG+VEeqGYbB85cmRcdNFF5cR84fLLL48jjzwyXnvttfpK9P/8z/+Mp556KjbZZJPysWIiffTo0fHss89G3759ywuLzpkzJ66++up4/fXXo3fv3nHzzTeXv/dSn/3sZ+PVV18txwMAAF2FlegAANCFFNui7LnnnuV2Loccckj8/Oc/j5dffrk89sILL8TRRx9drkAvtnPp1atXzJ8/P55++uk2v8f73ve++sd9+vQpfy1+v2UfW7hwYcybN6/+2MCBA+sT6IVicryYpH/88cffMsZi1XoxWV5sLdOzZ8/6rViZvuw2MQAA0BV0r3oAAADAyuvWrVtMmDAh7rrrrrjpppvixz/+cZx22mkxefLk+MIXvhAvvfRS/OhHPypXqa+xxhrlZPeiRYva/B6rrbZa/eNiZXqjx4pJ8vYoJu4L119/fZuJ90IxJgAA6EpMogMAQBdTTHLvsssu5e30008vJ8yvuuqqmDhxYpx//vnlPuiF6dOnx6xZs96VP7NYzT5jxozo379/fRuY1tbW2HLLLd/yuVtttVU5WV58TXFxUwAA6MpMogMAQBdSrDi/5ZZbYu+9946NN964vP/iiy/GsGHDym1cfvnLX8YOO+xQbsVy8sknx1prrfWu/LlrrrlmedHSs846q/y9jz/++Pj4xz9e7of+f62zzjrxla98pbyYaLGafdddd425c+eWk/zFFjPF7wMAAF2FSXQAAOhCiknoO+64I84555xyMrtYhf7DH/4w9t1333JC+5hjjokRI0bEgAED4rvf/W45mf1uGDJkSBx44IHlKvfZs2eXFyotVr03Uly4dKONNopx48bFk08+WV7gtBjX17/+9XdlPAAA0FlaarVardP+NAAAoMs544wz4uqrr44HHnig6qEAAECna+38PxIAAAAAALoGk+gAAAAAANCA7VwAAAAAAKABK9EBAAAAAKABk+gAAAAAANCASXQAAAAAAGjAJDoAAAAAADRgEh0AAAAAABowiQ4AAAAAAA2YRAcAAAAAgAZMogMAAAAAQCzf/wP9pE9Taqg6agAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# compare top weights (mode 2 -- sample mode) between components\n", "\n", "# USER INPUTS -- edit as needed\n", "max_elements = 20 # maximum number of elements visualized in any one component\n", "viz_components = [1, 2, 3, 4, 5] # list components you want to compare against one another\n", "heuristic = 'max_weight' # pull out the top weights across any component\n", "# heuristic = 'max_variation' # pull out the weights that vary the most across components\n", "\n", "# pull out the top weights\n", "mode = modes[2]\n", "if heuristic == 'max_weight':\n", " # weights sorted by maximum across all components\n", " idx = np.abs(ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate'])).max(dim='component').argsort()\n", "elif heuristic == 'max_variation': \n", " idx = ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate']).std(dim='component').argsort()\n", "df = ds.sel({mode: ds[mode][idx[-max_elements:].data[::-1]]})[f\"{mode}_weights\"].to_series().reset_index()\n", "\n", "# plot data, only including listed components\n", "g = sns.FacetGrid(df[df.component.isin(viz_components)], row='component', aspect=5)\n", "g.map(sns.barplot, mode, f\"{mode}_weights\", order=df[mode].unique(), color=sns.color_palette()[modes.index(mode)+1], errorbar='sd');\n", "g.fig.suptitle(f\"Component Weights of Top {max_elements} {mode.capitalize()}s\", y=1.02); \n", "g.set_xticklabels(df[mode].unique(), rotation=90); \n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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vv/7yJQYAQGxjXwQA8BL7GQA4N0eOHDGtW7cO3Z87d67JlSuXiXapTvRdd9115tFHHzWrVq0yV1xxRahGn2pGDB482Lz33nvxnuuFYsWKmU2bNpkyZcokSjaWK1fOk9cEACAc+yIgfdDVex3ou3LmzGnrSwFBx34GAOBLou/ee/+vMOKECRPsLanHRAdQp0+fNl7o2rWr6dGjh5kyZYp9nV27dtmagY888ojp37+/J68JAEA49kVA+hCUq/kkHJFa7GcAAL4k+s6cOWMiZcuWLbbDVJ8+fWwcjRs3NkePHrVD2uPi4uxO7/77749YfACA6Me+CEB6Tjgi+NjPAAB8TfRFUvny5U3p0qVNw4YN7W39+vXm0KFDtqhilSpVOFgCAHiOfVHsKDH35RQ/N+OJk6ZS2P3KH75izsRlTfHv72p9h0kLjBoD0j/2MwAA3xN933zzjVm8eLHZu3dvohF+I0eONF759NNPzZIlS+zt9ddfNydPnrT1KRo1amRvahRStGhRz14fAAD2RQgyRo0B6R/7mWDhAgqAqE/0DR061PTr189UqlTJ7mDCN3Jeb/C0U9NNjh8/br788svQTnD69Onm77//NpUrVzbr1q3zNA4AQOxiX4RYlZoRjuc6yjGtRjgC6RH7mWDhAgrSC5LS+NeJvtGjR9uCsJ07dzaRlC1bNntF68orr7RD2j/66CPz4osvmg0bNkQ0LgBA7GBfBADwEvsZIPhyZMhiJhb8T7z7kUBSGv860ZcxY0ZTr149Eykauv7VV1/ZqcO6qrVixQpTqlQpW5x23Lhxpn79+hGLDQAQG9gXAQC8xH4GSD80ai5nhpTX5QUCl+jr2bOnGT9+vBk1apTxm65maSenLlTauXXr1s3MnDnTFC9e3PdYAACxiX3R/zmTNYvZ2O2/8e4DAM4d+xkAgK+JPrVzb9mype0Gpa5PWbLEP7CfPXu28coXX3xhd3BuEVrt+AoWLOjZ6wEAkBD7ov8vQ4ZUdZUFAKQM+xkgfU2ZhX923TwhVc8/cuZkvPu7u7xkcmZM2fFriVn3mvRaPzFjan/hgQcesEPIL7jgArvDyZs3b7ybl/766y8zadIkkyNHDvPss8+aEiVKmIsvvth0797dvP3222bfvn2evj4AAOyLAABeYj8DpGLKbMasoRuNJxBUR/5//UT3Fp70C8SIPnV6euedd+yoPr8p69m8eXN7k0OHDpmlS5faxONzzz1nOnToYCpWrGh++OEH32MDAMQG9kUAAC+xnwEA+JroK1CggJ22G5SdoOLRLX/+/CZz5sxm/fr1kQ4LANLNsO6gSw/vB/siAOlJetiuIj72MwAATxN9gwYNMgMHDjRTp061w8n9dObMGbNy5UrbeUpXtJYtW2YPVEqWLGnbzatJiP5NLf3esGHDzJ49e0y1atXM2LFjTa1atZJ9/ltvvWX69+9vtm7daq+maUh9ixYt4h1A6T2aPHmyHXqvLsUvvPCCfW6s4WAS+HfDul1z5841uXLlMrEqiO+HV/siIDkl5r6c4udmPHHSVAq7X/nDV1JVS3FX6ztMNL0f5/qepIf3Ixq2q4iP/QySQj06pBesq+kw0TdmzBjzyy+/mKJFi5oyZcokasaxevVq45V8+fLZnVyxYsXszu3555+3BWrPZYThG2+8YR566CEzceJEU7t2bdtNuFmzZmbjxo2mSJEiiZ7/5Zdfmvbt25unn37atGrVynbAatOmjf3/vuiii+xzNKRe75OmOatblpKC+ps//vijyZYtm4klHEwCiDZe7IsAAHCxn0Gy9egy0AQLwce6mg4TfUpqRYpG3Wlnp0YgaWXkyJGma9eu5vbbb7f3lfCbN2+emTJliunTp0+i548ePdrWy+jVq5e9P2TIELNw4UIzbtw4+7sawaZkYb9+/UIJrhkzZtjE6Jw5c8zNN9+cZrEDAKJjXwQAgIv9DADA10SfpqRGSrdu3dL07508edKsWrXK9O3bN7QsY8aMpkmTJmb58uVJ/o6WawRgOI3WUxJPtmzZYqcA62+41I1YowX1u34l+pgyCwDpY18EAEA49jMAAF8TfS4lyNwisFWrVjU1atQw6c3vv/9uTp8+bUfbhdP9DRs2JPk7SuIl9Xwtdx93lyX3nIROnDhhb66DBw+ac8WUWQAAAAQVF6UBAAhIom/v3r12VJqKw6p+hKjhhIaXz5o1yxQuXNiLOKOa6v0NHjz4rM/Z/27/VP3NIydOxbv/xwdPmRNxKfu4C14/JOri0MHk0ZOnQ/dzZM2UqoPJ5GI5W4x+C0osxBG570x6WVdT85549X4AACKLi9IAAAQk0Xf//febQ4cOmXXr1pkLL7zQLlOTiU6dOpkHHnjAvP766ya9KFSokMmUKZP57bff4i3XfRW/TYqWn+357r9aVrx48XjPqV69epJ/U1OHw6cDa0RfqVKlzuH/DAkpyXf75K9D96d2rWVypiJZACDtpCb5Fnf4sDGT/3ciWKDV45wIAgAQAxj1CRiz6+YJKX7ukTMn493f3eUlkzNjyptilJh1r4k2OWK0A3CqMx3z5883n3zySSjJJ1WqVLFt3ps2bWrSk6xZs5qaNWuaRYsWhZqMqJ297nfv3j3J36lTp459/MEHHwwtUzMOLRd12VWyT89xE3tK3K1YscLcc889Sf7NuLg4ewMAAABSo8Tcl1P1/IwnTppKYfcrf/iKOROX8hPBXa3vSNXrAf8Woz4BnKsMMdoBONWJPiXCsmRJnAXVMj2W3mgknUYjXnbZZaZWrVq2Y652Km4X3o4dO5qSJUva6bXSo0cPU79+fTNixAjTsmVLO1155cqVZtKkSaEVSUnAJ5980lSsWNEm/vr3729KlCgR0Y7FAADAO2eyZjEbu/033v1Yx3uC9IKRYwAAr0ZaRmK0ZaoTfY0aNbLJLk3RVfJKdu7caXr27GkaN25s0pt27dqZffv2mQEDBthmGRqFp1GLbjONbdu22U68rrp165qZM2eafv36mccee8wm89Rx96KLLgo9p3fv3vZg4a677rL1C6+88kr7N7NlyxaR/0cAAOCxDBlSNSoqJvCeIJ1g5BgAIJqkOtE3btw4c91115kyZcqE6sht377dJrpeffVVkx5pmm5yU3XVdCShG2+80d6SoyuATzzxhL1Fm9QWtqe+FmId3xkAAIBgoe4ZgGiW6kSfknurV6+2dfo2bNhgl6leX5MmTbyID/8fyQIAABJjyl18TJf1D7Xxzu09iYX3I2hUU33YsGF2FlO1atXM2LFjbemi5Lz11lu2BNHWrVvtLKZnn33WtGjRwteYAQCp96/ajuoA+pprrrE3AACASGHKXQJMlwWQhDfeeMPWJp84caKpXbu2rUverFkzs3HjRlOkSJFEz//yyy9N+/btbZ3yVq1a2dJFqjeuAR/hJYsAAMHzv+Jz/+DTTz+13XXVQTahAwcOmKpVq5ovvvgireMDAMQwjc5S4sa96T4AAEidkSNHmq5du9qGgzqnU8IvR44cZsqUKUk+f/To0aZ58+amV69edvbWkCFDzKWXXmrLOAEAomREn676aOeQJ0+eRI/lzZvXdOvWze5ArrrqqrSOEQAQozSCPKZHZwE4Z0xnjj1+TqtOD1OIT548aVatWmX69u0bWqZmgyq9tHz58iR/R8s1AjCcRgCqCWFyTpw4YW+upAaIAAAClOhbu3atrcuQnKZNm5rhw4enVVwAAMQUaicBHmE6czwkPmPP77//bk6fPm2KFi0ab7nuuzXXE9K+KKnna3lyNM138ODBJj1ITYOMw6p93vr90P3iU+5Ms4uQQWnUQRzBjENYV6MjjsMefjbnlOj77bffTJYsyR8IZM6c2ezbty+t4gLOiuYkAKIJtZMA+IbEJzyiEYPhowA1ok+NHAEAAa3RV7JkSfPDDz8k+/h3331nihcvnlZxAQAQM6idBADwSqFChUymTJnswI1wul+sWLEkf0fLU/N8iYuLs2Wewm8AgAAn+jQdSFOEjh8/nuixY8eOmYEDB9pRBQgGCtgDQPrg1k5SraTU1E4Kf75oBGByzxfVTdLoivAbAER6CrF7Ywqxd7JmzWpq1qxpFi1aFFp25swZe79OnTpJ/o6Whz9fFi5cmOzzAQDBkeKpu/369TOzZ882F1xwgenevbupVOn/StaqroPqCqnuw+OPP+5lrEgFCtgDQPoQlNpJ6aGgvN+C8p4QR3TEofo8rV98O3R/Q4vb0uRYLSjvR5BiSW0cjuOYIy1uC93XBXIdS0cTTant1KmTueyyy2z9V5WIOHLkiB1JLh07drQzuLSvkB49epj69eubESNGmJYtW5pZs2aZlStXmkmTJkX4/wQAkGaJPp1AqCbQPffcY+svaIco2glqFIGSfQlPOgB3ZGH4fQCA/6idBACxe4G8Xbt2tp76gAED7EWh6tWrm/nz54fO37Zt22ZHk7vq1q1r679qsMdjjz1mmz6p4y51YIHg4tw7uHL6/NmkONEnpUuXNh9++KH5888/zaZNm2yyTxv9/Pnzexch0rVYOHACgPRSO0k3AEBs0qws3ZKyZMmSRMtuvPFGewOQPnDuHVwZfP5sUlyjL5wSe5dffrkd9k2SDwDSDvU1Yw+1kwAAAABEZEQfAMBbXImLTdROAgAgPqYhAsC/Q6IPAIAIo3YSAADxcfETAP4dEn0AAAQAtZMAAAAAnCsSfQAAIN1iahcAAADwPyT6EBM4EQSA6MTULgAAAOB/SPQhJnAiCAAAAAAAot3/KnsDAAAAAAAASLcY0QcAAAAAQBIoAQQgvSHRBwAAAABAEigBBCC9YeouAAAAAAAAEAVI9AEAAAAAAABRgKm7AAAAgMeo8wUAAPxAog8AAADwGHW+AACAH5i6CwAAAAAAAEQBEn0AAAAAAABAFCDRBwAAAAAAAEQBavQFkOM49t+DBw9GOhQAiAru9tTdvoJ9DQCkNfY18bGfAYDI7GdI9AXQoUOH7L+lSpWKdCgAEHXb17x580Y6jEBgXwMA3mBf83/YzwBAZPYzGRwuOQXOmTNnzK5du0zu3Llth7ZzyfZqx7p9+3aTJ0+eNI2ROIgj2uIIUizEkfZxaFenHWKJEiVMxoxUrUirfU00rSPEEd2xEAdx+BEL+5r42M9EbxxBioU4iCO9xHLQx/0MI/oCSB/Yeeedl2Z/TytRpL9cxEEc6SWOIMVCHGkbB6MrvNvXRMs6QhzRHwtxEMc/YV+TdtjPRH8cQYqFOIgjvcSSx4f9DJeaAAAAAAAAgChAog8AAAAAAACIAiT6olhcXJwZOHCg/Zc4iIM40k8sxBHMOBDcz4Y4ghlHkGIhDuJIT7EgeJ8LcQQ3FuIgjvQSS5yPcdCMAwAAAAAAAIgCjOgDAAAAAAAAogCJPgAAAAAAACAKkOgDAAAAAAAAogCJPgAAAAAAACAKkOgDAAAAAAAAogCJPgAAAAAx56+//jIvvfSS6du3r/njjz/sstWrV5udO3dGOjQAAP41En2IOY7jRDoEINBOnz5tfvvtN7Nv375IhwIglX755RfTr18/0759e7N371677KOPPjLr1q0zsWjHjh1mwoQJpk+fPuahhx6Kd4tVrCP/57vvvjMXXHCBefbZZ83w4cNt0k9mz55tE38IHh2bPPHEE75uPw4fPpxo+d9//20+//xzX2LYv3+/Wbx4cSgR/fvvv9t1Vu/D+vXrTSx+LseOHTNLly41P/74Y6LHjh8/bmbMmGEibfv27aZLly4xF0cQvjNBWlcjGouDqDF58mSnY8eOzpQpU+z9WbNmOZUrV3bKli3rDBgwwLc4vv32W+e2226zr5stWzYnR44czkUXXeT069fPOXDggC8xHD9+3Hn44Yedq666ynnmmWfssiFDhjg5c+a0t/bt2/sWy9ls2rTJadiwoW+v9/HHH9t1YdGiRfb+Z5995jRv3tzG4K43Xvvtt9/i3V+zZo1db+vWreu0bdvWWbx4seOXffv2Oc8++6zTpk0b54orrrA3/fzcc885e/fudYLAz3Xkgw8+sN+ZuLg4J2PGjPaWN29e59Zbb3V+/fVXJxa3Z0js1KlTzrBhw5zLL7/cKVq0qJM/f/54Nz8dPnzYmTdvnvPCCy84o0ePjneLxfdkyZIlTvbs2Z0mTZo4WbNmdX755Re7/Omnn7bbVz9t377dGT9+vPPoo486PXv2jHfzyyeffBI6BsmcObNTvXp1J1++fHa75ue+NyjrR9DWkc8//9zp0KGD3ffu2LHDLpsxY4bzxRdf+PL6jRs3dnr16mV/zpUrV+i9WLZsmVO6dGlfYkDqzzF0bOK1Xbt22e+rXitTpkz2vObQoUOhx/fs2eNLHCtWrLDbqwwZMthtxcqVK+1xUMWKFZ3y5cvb7/KqVaucWPlcZOPGjfb7qfdEr3n11Vfbz8vvzyZI70kQ4gjKdya9fC5+xJLZuxQi/DRq1Ch7dbZZs2bm8ccfN7t27TLPP/+86dmzpx2dM2LECFOyZElz1113eRrHggULzPXXX29atGhh6tWrZ6+K6ipCzpw5zaxZs8zrr79ur8AUK1bM0zh0JfaNN96wV6unT59utm3bZj744APz4osvmowZM5oBAwbY92vMmDEmknTF47PPPvPltV599VVz++23m0suucSMHDnSjB071q4f//3vf82ZM2fM3XffbXLnzm3ve6l48eJm9+7dpkiRIubLL780DRo0MHXr1rXry7fffmuuueYas2jRInP11Vd7Gsc333xjvy85cuQwTZo0sVf13asrWi+eeeYZuz5fdtllJhbWkVdeecXcd999dhuh9/7ll182nTt3NqVLl7bf3Zo1a9rPq2LFijGzPUPSBg8ebKe6Pfzww/Zz0me0detWM2fOHLtt9cuaNWvsvubo0aPmyJEjpkCBAnakg77T2r488MADMfeeaNTak08+aUeraXvuatSokRk3bpxvcWgbft1115ly5cqZDRs2mIsuusi+HxpRf+mll/oWh44FHnnkEfv56P1455137LrRoUMH07x585hbP4K0juizuO222+xnoe/yiRMn7PIDBw6YoUOHmg8//NDzGHQcoOPChLR/2bNnj+evj6RHWZ7Nxo0bffue6HxhxYoVdqSn7jds2NB8/PHHJn/+/L7NENK24sYbb7TH7VpX27RpY7ddkydPto/rHGvIkCHm3XffjYnPRR599FG7T1m5cqX9bB588EF7DrFkyRJz/vnn+xbHe++9d9bHN2/eHFNxBOU7E6R19btIx+JZChG+0kiX1157zf68evVqe+X6pZdeCj2un2vWrOl5HLparpEV4SPIFJucPHnSXj3t3Lmz53GUKlXKWbhwof1ZV2iVLZ8zZ068uPy4WptwhEnCW+/evX27qqDPxh3lolEOugo4cuTI0OPDhw936tWr53kcugLnjuq75pprnC5dusR7vEePHk6jRo08j6N27drOXXfd5Zw5cybRY1qmxzTKIFbWEX1PNWrO9c033zjnnXde6P1p166dc/3113seR5C2Z0hauXLl7OhPdxSMRp2K1leNlvZL/fr1na5duzqnT58OjcbZtm2bvbr/zjvvOLH4nmjE+ubNmxONUNqyZYsdqesXXdV3R966cejK/nXXXedMmDDBtzjCPwuN5Pvhhx9CV9H9HLEVlPUjSOuIjkmmT5+eKA5t8zXq0Q+FCxe2r5cwBh0jav8H/7mjtPRvwpu73I9johIlStjRdOEzhf7zn//Y9Xb//v2+jU7SKL4ff/wxdB6l1wyPS6P5SpYsGTOfixQpUsT57rvvQvd1nHr33Xc7559/vv0O+/XZnO09CX9vYiWOoHxngrSuZohwLCT6ooSSNuFT63Sw5h7Qys8//2wPcr2mqbo6WAzf+GbJkiU0pFrTNHRg5ff7oRjC3w/FqOk8XtMXWBu+MmXKJHnTY35tbMIP7t33ZO3ataH769evdwoWLOhroq948eLO8uXL4z2uz6lQoUK+rKv6f06OHtNzYmUd0Xcm/LsrSrDt3LnT/qydtx/bkCBtz5A0bTvdz6dYsWKhaUM6wM6TJ49vcWg604YNG0I/uydDX331lVOpUiUnFt8TnfBp2mHCxMXs2bNtsinWEmxKGLnrxYUXXujMnTs3FIf2ibG2fgRpHQnf54THoX/9SjjecccdtlyHEiiKQcdI+pxq1KhhLzrCfzoOffnll52tW7cmeVOpBj+OibR9+Omnn+It+/vvv+36cskll9hEk19xhB+bhX9XROurH8eqQflcJHfu3KHterj77rvPJuh1rulXYit8EElCKk0US3EE5TsTpHW1YIRjoRlHlNBUJU1dchUuXNjkypUr3nNOnTrleRya7hA+DFUFnzUttGDBgvb+eeedl2SBzrSmodvLly8PTc3IkCGD+frrr0OPa1ixYvWapj1qyuGWLVuSvM2bN8/4JUuWLObkyZOh+3FxcfHWEd1XcVs/HDp0yBw8eNBky5bNvm44LdNUPK9p+nj4OpGQHitatGjMrCNlypSx0yBc6jqoIfjue6BpkSqkG0vbMyRN23FNv5fy5cvbaRnutjbh99nrbZrWUdF0TJVokLx589ri07H4ntx88812WpOmHWq/p/3vsmXL7PTVjh07+haHynW4+xuVa9CxgEvTq/1yxRVX2HIhomnemjr71FNP2elueizW1o8grSPaB2/atCnRcn1emvLtB5WB0DGpth86/qlfv76pUKGCndKs9QT+U5kQlevQsVFSNx27+zH9T+tgwml3mTNnNm+99ZZ9rFWrVsYPpUqVijf1UqVUtE11abtSqFChmPlcpHLlyvGOV10qPdC6dWtbNsIPek9WrVqV7OPavvrxngQljqB8Z4K0rtaMcCzU6IsS2ujpy3XhhRfa+wlPclQjRyfyXtNB4p133mlrSujgVTUltMHNmjWrfVw12MqWLet5HKo3p/piqomjjZ+6qT322GP2fdCJ4QsvvGAP+P3a+N50000R3fiKDl71/1+pUiV7f+fOnfHq8+hETCcjfnDr4en/XTvrGjVqhB5T178SJUp4HoNOalTjTZ9P48aNQwkt1ehTfSnVP9F6EyvriOrz6burE08lW/XdUf2kTJkyhZLj7ucWK9szJE11WPUdqV27trn//vvNrbfeams6KtGmOop+0XZD66vqRuoEXbXOlERSvUnV74nF90S1zfRd1smh6llWqVLF/nvLLbfY2nB+J9j0HXYTbN9//72t2+tngk3HIO7FRdXJ08+q36t1Ro/F2voRpHWka9eupkePHmbKlCl2P6eTIV2g1b65f//+vsSgiwILFy6066r2OVo/VENSdXsRGTp+D7/Ql9SF/KlTp3oex7XXXmsmTZpk2rZtm2TiQsvVXdSPxLzbGVtatmyZqD5brVq1YuZzcbenqvmuY9Skkn26eDFx4kTP4+jVq9dZ3xOdd6lbcqzEEZTvTJDW1bsjHEsGDevz7K/DN7oaqyvo1atXT/LxCRMm2A1f9+7dPY1Do2yU5FPjBxVWVjH90aNHh642aZSU2p573WhBZs6caQ8a1ehBTTlUpFUnghot9p///MceSLqjQbyitu96veQaOmiElJvp95oK9WpkZXLvvZpPaGOkor5eSthYQlcmwxNIWl80EkQ7Lq/phE+j6ZRo04mOKLGl5JsKlSeXfIvWdUQJ8PDvrr4jSvrJzz//bN8jJeFiZXuGlPnqq69CjVq0bfWLLhJodLCKPetESBea3DiURElu/Ynm98Sl5LgSa0pcKCHqRxOdcBqBotdW8yftV5Toc98PJdj82J4FWaTXjyCsIzr9UNLx6aefDo3i1wViJfq8Pg4BUnI+o/UyT548yT6uC+aR3pYpRh23+j0yGEiv35lYQqIPQMxTMs2dTqaktKYEAkja559/bi+g6CptwoM4JS/8uJATNLwnwaTpQhr16ZYPcakjoEZu+dWNkPUjebqwpym8SjhqdGHCMg1eUyJaFyA1ujK8vIn42bkbZ6fvigYK+L1+EEf6iEN+/fVX+33WBWmvB3IQR/pbR04FJA4/Y6FGH3yhfLI7YgrGTJs2zRw4cCDSYQSKpsy6Nbb8psSeRhbqFpQkX6TWEe181q5daxYsWGBv+tmv2nwJJdxmaESwRsJoxCEiRyPo/vjjj0TLtb7qMb80atTIJmwSUv1PPRaL74loaoxGvfbp08eOTA6/+Zlg279/f6Ll+rz8qr8mW7duTfLYQ9sQjSyIxfUjKOuIS6VdlODT9EO/T8DWrFljp7Vp1odGiD/55JPmwQcftKVeRo0a5Wss+D/vv/++Pf4Jp3qJWjfy5ctnmjZtav7880/iiNE4RNP9E5ZeUCke7VsuvvhiW7rDjzq9xBHMdSQocQQiFs/afMB348ePdxo3buzceOONzieffBLvsX379jlly5b1PAZ113n88cedq6++2hkwYIBd9txzz9mOc1mzZnU6duzonDhxwvM41CH01KlTofvvv/++jUmdiWrWrOlMnz7diSR1vE2qY5SX1KmrS5cuoW57kXLw4EGnQ4cOzvnnnx9aH+69995Qi3F9TgcOHPAlFnVeHDJkiP3u6DsSTjHcfvvtTqysI6dPn7bfXXXITNgCXsv69etnn+MHdaLS9zRTpkxO8+bN7WfRpEmTUDzalm3cuNGXWJCYPoO9e/cmWq7PRN3w/IzD7eAdTsvUMToW3xPt+7W/veiii+x7UL16dfv9VVfihg0bRvyz2bNnjz0W8Jq66+qmOGbMmBG6r5u6y6o74wUXXODE2voRpHVEvvnmG6dXr15Ou3btnOuvvz7ezQ/169d3unbtavdtbjfTbdu22eOQd955x5cYEF+DBg2ccePGhe7rmFXHhk8++aT9TCpXruz07NmTOGI0Dqldu7YzZcqU0P2PPvrIbsteffVV29G8Tp06tqM2cfgbR1DWkaDEEYRYSPRFidGjR9sDNx283nrrrfZAeujQofEOrv1oJa1kQNGiRZ2HHnrIqVKlinP33Xc7pUqVshsbJddKlizpPPvss57Hof9X9yTjvffes/eVVFJC584777QbQB3sey1//vxJ3nTQr4Nq974f9JpVq1a1/2rDMnz48CRPPLzWvXt3+/pjxoyxG8DWrVvbE46lS5c6n332mV1vHnvsMc/jWLBggf2e6D1R0lEt0D/99FPfvzNBWUd0slW4cGFn4sSJzpYtW5yjR4/am35+8cUXnSJFiji9e/d2/NC2bVt7AqYE/U033eTUq1fPris7duxwdu3a5TRr1sxp06aNL7Hgf9wTcH0vWrRoEe+k/LrrrnPKlCljPxuvrV271t70HVm8eHHovm6rV6+2+77SpUs7sfSeuC6//PLQRTY3cXHo0CEby4QJE2ImweZeFNDnkvDChbb7ikHbl1hbP4Kwjrhef/11e0GrVatW9jPRv/pctN/r3LmzLzHotTZs2BD62b249tVXXzmVKlXyJQbEp+MQbcddOgkO/47MmzfPqVChAnHEaBxSoEAB57vvvgvd17mmjhtdOi7QtpU4/I0jKOtIUOIIQix03Y0SL774ou0Sqq5pcs8995g2bdqYY8eOmSeeeMK3ONQAQ9061UJbMajDq5a1a9fOPq7C/iqy3Lt3b0/jCC89+dxzz9nXU8Fnlzr/ark6N3lJUx7VDfLGG2+MF5u6myomtdX206effmp2795tPyMVwdb0FH1Wiqd58+a2853X5s6da6ZPn26nK6kDkzr9qmtYvXr17OP6XFS4XUObvTRo0CBb9Fuvo89k2LBhtkO0OkPpvfBLUNaRGTNm2G6lasIRTt1tNQVAxXPV7ODZZ5/1pZ7Vxx9/bJspXHXVVSZ//vx2mfteaN1VJ0/4Sx0q3fVTHbuzZ88eb/qduqmqk6bXtF5oW6VbUlN0FdfYsWNNLL0nrvXr19tuhKJ6cDoG0BQRHQe0bt3a7pe9pOMO0WfTqVOneI+pLIK2JyNGjDBeU7Med1+vGn1uQzC/BW39CMI64tJ2XM2w1AFY740acenz6tatmy2j4Qetk27tqiJFitjyIeoUrc/Nj6luSEwNlsJraqojcvjxUdWqVW2DMuKIzThE26zwhg+qc3rHHXeE7mvK6p49e4jD5ziCso4EJY5AxOJZChG+yp49ux15E+7777+3o+v69Onj2+ikbNmy2WkP4ffXr18fur9582ZfpqmETxvSSKSVK1fGe1xXcDVVxWs///yzvXqu0YS6Yu7SiMJ169Y5fko4ler48ePOzJkz7XRvrRvnnXee079/f8/jiIuLi7eOaCRq+DRMTdvUMq/lyZPH2bRpU7xlr732mpMzZ0470sOv70xQ1hG95+FXBBPSaCm9N37QNkLbCtGUKr0XmmYd/p75Pd0N/zNo0CDn8OHDEXt9bSO0v9M2TVP/dN+9acRneNmGWHlPXNrnu6OSLrzwQjuSTvT98ev7Kxo9kLAcQiRotFoQBGX9CNI6on2Oe9waPiJFsRUrVsyXGK655hq73xfN9qhVq5adgaIRF/oZ/itfvrwzf/58+7OOiTTaUzM+XJqKWKhQIeKI0ThEs4LcqfXaz6jMS/h5nso3aTtHHP7GEZR1JChxBCEWmnFECV2tTnj1UcU3NYJr6tSpno+gc+kqaHhxdHW105Xa8ALYfowakx9//NF899139gq6e3U/YdMBr6nIs66sFCtWzI5CWbZsmYmUhO97XFycLUD9ySefmF9++cV07tw5UcFQL+jKxr59+0L3NYJABUld6ryn2Lym10hYyF8jYjXaUSNQ3333Xc9jCNI60qBBAzvC0e0+HE7LHn30UfscP+gKl4oLi0Z/ap2ZNWtW6HGNRrngggt8iQWJDRw40OTMmTNir6/RpRoZpu36ZZddZu+7N40EypQpk+8xKZakvjt+0wgxXTEWjXp1R0d36dLFPuaXRYsWRWwUXcLtq0aPv/rqq7bDXaS/M9r36fPRLXw/GIvriEZqa7SDaLT2Dz/8YH/Wfvno0aO+jSp0Rw/qPVBMGtGoz2bSpEm+xID4NNpFDVE0w0CjXXVsFL5erly50s4WIo7YjEM0WlwjgTVDTHGpq2zNmjVDj+uYWufAxOFvHEFZR4ISRyBi8SyFCF+1b9/eefDBB5N87IcffrBzxP0YnaRCztOmTUv28TfffNMW2fdawto8zz//fKLaMKoF56dFixbZWnB9+/a1dWkiPaIvKWfOnPE8DjVXUB245EydOtWpW7euL1fyhw0bluRjGumoz8iP70xQ1hGNsnSLs9eoUcN+TrrpZy275JJL4o3E9JKufmk0sK586V/VblTtJo2wuOKKK+zVyjfeeMOXWJC0t956yzZ+UhForSPhNz9pVK7qfmpksm73339/opG6flBDA62XjRo1siOENGI6UiPYNPpWNIKsW7duzsUXX+zccMMNdsSjn/sb1dV85ZVXnGPHjjmRsmbNGueBBx6wx0CqwXbXXXfZ0Q1+O3LkiG3upHXEPS7RdlUNsvRYLK4jOm4dMWKE/fmJJ56wn5FG1am+pl/NOBA8qg1822232Vk3Gqn0+eefx3tc25VnnnmGOGI0Dnemh2Ygab+r49SEjev++9//Oi+99BJx+BxHUNaRoMQRhFgy6D/epRHhF41cW7Vqlbn99tuTfFxXSt955x17VdlLP/30k615ojorSVG9PtWEuemmmzyN49dff413X/VnwufIqx6ZqOaYn/bv328z+osXLzZfffWVb1cUZPDgwaZXr14mR44cJpL++OMPWxMnfBRfuI8++siOwvR69JhG7Knum2oEJbeuqu6lPqtYWUc0KmnBggX2dd16Hrr6VKdOHdsC3q1l5IetW7fabZquSmr01m+//WbGjx9vR3q0bNnSjtJBZIwZM8Y8/vjjdhSwRr1ov6NRwaqFpqvKXtfXdGldVV1NjYR1a3xqROzatWvN+++/b6655hrjpzVr1tgR9BpxqhHjN998sx0ldfnll5tY8+2334bei5MnT9pR0qoZVKtWrYjEo89DtWA1an3+/Pl2RLA+m9tuu80ULlzY89dX3TmNnh83blxoXdWougceeMCupy+88IKJNToW0CjLEiVK2H2P6vNq5EnFihVNv3797Og6v9aNJUuW2G2YRvVrFopqJqnmlY4dAQBIj0j0AQCAFNO0EF000tR/nRQrsaZizwMGDLAn70pm+KFGjRq2ecwzzzwTb3mfPn1sM5fVq1ebSFCDHSUalehSMlLvl5JcSoy6zRm8pKmPb7/9tk1c6OJOgQIF7HtRtGhR3xtARTrBlpDKh0yYMMH07dvXJiDVEEMXHtVkyMsGEJrGrM8k4QUsXdDR6/s9jTdI60gk6aKwmm+pCYfWDV2s1rasR48e9v7EiRMjHWJMO3DgQLyLjn5sP4McB4JL2xA1O9QFcW1DwgeX+OX06dPxSpd8/fXX9iKKjpX8KImE4KFGX5TSQZxGI/Xv39/WHNNOys8NzebNm0N18XSw9Oabb9oaWxqVE0kaeeJXp53kTnoWLlxoXn75ZVvDSO+V3xK+5ooVK+zINp2cBsGRI0dsPJGidVQ7bD8F8TsTyW0Igk3fj7p169qfNfrWrbOl5I3bzdOv7qHhneVcSiSpRmuk6PqptqdKJOlnjUxS8rNUqVLmjTfe8Hx0v5JpSlwNHz48VId09uzZNrnlN43gv+GGG2w3c8W0adMmWwtU74VG1OvEyA+qg3PvvffaZN7IkSNtDEpyaX+sYwLVivWSRiIriZaQOr36VY8uiOuIPgON3tNFg71794ZG9a9bt86X11dCT3U+//zzz3gdka+//np7jIbI0DFHlSpVbAJa/4b/rOPnWIvjww8/NHfeeaett679Xjitu0l1n4/mOP6JLj76VatXF45UH1gz2XRcpPpr2q5feeWVdlaKXxcsNPtFybxrr73WHDx40I4UVyyKSZ3EdRHDa0oshp9jfvDBB6Z+/fr24pG2s+5suliJQ3QxXMepGq0eEZ5NCoavVM9ENZPcmnzq4KJ6J6qfpE476mCWcM6+F1T3pXjx4ra2mep9uXW/1MktV65cTv78+X2pj6M4krqp7tm7774buu811Y5SB1fZvn27nZ+vGj36TPSv6uLs2LHD8YO6UdarV8++7tVXX+388ccfTsuWLUP1glQDTc+JNHX+86M23sGDB50OHTrYmnjqeHvixAnn3nvvDdV31Ht04MCBQHxnvv7665jZhsjJkyedXr162W5V6kj88ssvx3vcr47ISFrZsmWd1atX259Vc9WtublgwQK7vvpFncJV9zUh1W8sVaqU4zd1ubvvvvtsB1F9px999FHbIdo1ZswY2wXeS6pTqO+OaPvhdp1dtmyZrX3mN3VFvueee+x6oc/r8ccftx21VadGser77SXVgNP2VPv+1q1b2/2x6hmF075Z+0UvqXajalqG1ytU7R4t0/vgp6CsI0uWLHGyZ8/uNGnSxNZjdeN4+umnnbZt2/oSg76rGzZsSPReqBuwYoP/nnvuOduRuU+fPs7ixYvtcYdu+ln1i3VslFx95WiMQzVftX3S8fqVV15p6xarM7Tfx0NBiSOl5xE6lveaPv8SJUo4Y8eOdSZPnmy7mKve6EcffWTrsmn90T7Qa9pe1q9f3+7fbrrpJnuup9pvOr/UeZ26iLdp08bzOPT5u7Xg33vvPXtf51fjx4+39VdVl3b27NkxE4doPaxatar9VzmA4cOHO3v37nX8QqIvSuggev369fbna6+91rnlllts4sI9ab7jjjucpk2beh6HNiYq+vn99987PXr0sBs9Hcgqhr///tu59dZb7UGd3804wm/ucj92SEqQ6L0QbXz1/67W57J//36nVatW9v3yg3Y6anKhjV67du3sz1dddZXdEfz66692x6CT1FhJ9CkJq42uTr61Q9RJoE4I1fZczR/UrOWxxx6Lme9MULYhMnDgQPvd0UGUEgNuEf3wA0o/DuKQNK0LgwYNsj+PGzcudLKuYsNqLuCXwYMH29dUIWMljnRTkkDLdLDtJ7eRTYsWLezFpFOnTiV6jrb9Xq+3efLkCTUjCU9cqMlCXFyc45egJNgqVKjgDB069KwXsbSdO1sTsbSg7btOCAsWLGiTfrrp55IlS9oLK34KyjqixkpuM47wOHQxWO+LH7StcJtehcfwxRdfeJ6UR9J08fVszbZmzZrly4WcoMShBgujR48O3VdMSjK6zRX8SrAFJQ73wvTZbtq++hFLmTJlnA8//DB0f+PGjXa7rmN3USMoNf7zmi7Kq/GU/PXXX/Y4Q9sw16pVq+wxtZ9NH5UMVpI83FNPPWW3+7ESR3gsOrfVeacuLunClppfad3xugkmib4ooRMt98BNIwnc0RbhGx+dLPuRLHBH/ehqtQ7iw0fw6YBWG0GvVatWzV51UuJCB6+66QqtTsQWLlwYWuY1XfHS6AXRaIaEoxl18K+RU37QerF8+fJQklEbn08++SRex9dy5cr5so6c7aaTED920DpA+/TTT+3PO3futO+HO/pSPvjgA6dSpUox850JyjbEPTkP/yw0KkrLOnfubHeKQbpyHIuUsHEPZN0u5up2q6S5mxz2g9aFkSNH2qSAeyFHP48aNcqXDuLhlFj0a3T2Px3wu9/d8MTFxx9/bPdBfglKgi1I1F130qRJzkMPPWRvGgGibX6sriNKErjHRwlH0/mVcNQF2K5du4ZiUDyHDh2yiQLtb+A/HTefbfaAErN+jLYMShzh3xOXjl21vr7wwgu+HQ8FJQ7RuZwuSOs7mtTtuuuu8yUWjdjT9sql4w7F5u73lNzR++O13Llzhz4bHZ8pBr12+DG0nuNngk0XSjTLIZxGT+viSqzEkTAWOX78uDNz5kw7sl7rqPa56pjslcyRmTCMtHbJJZeYTz/91JQvX94WitV8fRXfdOl+eP0Rryh5rJo8kvBfUc0Etw6Z1/PzVUOibdu25tVXX433XqjDm+op+EF1cBSLajdonr7qJoRTbSs/3g+3foZbZFs1RtR9N/x9qFChgi/1klR/7p577jEXX3xxko9rXVWHYK+pHpD+n911Qt8PfV6uiy66yGzfvj1mvjNB2YbIzp077fvv0uekroiq/6I6cOrOiMhRsenwDszqLqub3zJkyGB69uxpb26dQG1nI0G1LINAXYifeOIJW+PTfY9UU/HRRx+1+0O//Pzzz//4HDXC6NSpk+exqAad9sPa5ifclqpOoF+0z1VH9UgLyjqSL18+e8yh46OE3av9aggyYsQI29BHNdfUAVhdd7XuqnmKn/VG8T/qUq4GS6qBF34sJKq7pdqSfnQyD0oc6v6sWs3h35OGDRvaumOtWrUyO3bs8DyGIMUhqjmnbVVSNXrdru+Ky2s6Z1CdV3e7ruZK2q/pGFqyZctmt69eq1q1qpkyZYoZMmSImT59um0Eohrf1apVs49rWxZ+fuMl1UdW4xqdLyR17qJa9bEUR4YEn7/qKKomrW5bt2612xc1K9M+2Qsk+qKETjJ0wJolSxbzwAMP2BOf/fv3243hxo0bbYdEnSB7TcVAtfNTokYrr3YIKkKuDZCMHTs23gm8V7ShHTVqlC3qrINaFeHWQazf9Dmo6LeKcKvItT4bvQfu56JC0CpU7gcVh9VBtYqgS/fu3W3CLzwRmDNnTs/jqF69uo0huRM8FdH1I9GnHaE6Hbrvh4qx68TDdfjwYV+6VAXlOxOUbYjoIElF2suUKRNaphM/HUTpwFLdS2F8L+CfmqSx3yKV4As/8dPBmgr4J5VQUhLdr8TFf//7X7u9P3bsmC1ArYPdOnXqmKeeesr4KQgJNnU/7tChg92e60Q1/KBbP3sZh7oNp5SOU/wSlHVEFwd0XKZGLfostI4sW7bMHjP5tX6cd9559phDTXL0r9YTJQ+0zvh1YQvx6fhHyVcdB1x99dWhJjZKMqlRm47v1VU9VuKoVauWPZdRY4Vw+t5q+6Ykmx+CEod73Kwu4ckl+nTsfv7553seh87rbr31VvPJJ5/YpJ4aGun42d3P6AK1H8fvgwYNMm3atLEXwXURdsGCBTb5qOMO3f/mm2/MzJkzjR8aN25sBzCItufhyXBdxPHjcwlSHM7/jyEpOsdRctarJJ/YYjGe/XX46p133jEPPvig7SAX/rFqg3f33Xfb7mpedyHSxkQdf5Q0UiJFJ+baEGs0kDY2Wq4dgr6AftFOWd12dQC3fPlyezCnq7d+UYc/JVH0mehkMPwqgg7uX3nlFZMrVy7P41AiSyOilFxMyvjx4+1OyutOc0OHDrUdKZU4SopG0Q0YMMBMnTrV0zi0nmrH2K1btyQf10m7us5qBxEr35kgbENEXd30+kl1tdNovwYNGtguxZHoWh2rtC7q4PWfDhn0HC8/F40yTekVcp0I+EUXTrTNaNmype3smjDG559/3vhJ2y03cXHppZeaJk2a+Pr6/5Rg++OPP3yJQ6MYWrRoYfc7GlHnp/BRr5LU98d9XyKxLYv0OqKu1Pfdd5/93uj/X6Om9K9G1WmZX10zETwaoa3ZOF999ZVNQosSbkpGa/3QNiVW4vjss89sx87kOmLrmFFdRL0+Zg5KHO7MIG0r/N6mJ0XJT60jikmJ4fBR27pYLjq295pGh6nLr5KgSiDp3FfnderqruMSXST3ms5bwuncNvz/3e126/WFnKDEIRrE0atXr4itqyT6oow2fDq50Umwro7qhENfej9HOxw5csRs2LDBVKpUyX65NB3itddes1eO1e5byyNhzJgxdkekEVK6iuv3yAYN7w7/XOrVq2cqVqxogkIjL7Qh8uPqUxDoRFMnYuGj+BLuvHVFX0mlWPrOBGEbop203g8dNCVFiUh9n/yY9oekD5zOxsvSCOGjffU9mTBhgr1woxMv0QnZunXr7Cjup59+2vhFU/108KikEiKbYAunUerff/+9KVeunIkkjfjQ6DW9H+66qguP/fr1s8u0nY9Vurinz0gJRyXy/Twu0jZCI7W6dOkSb7lG1GvEfyRmggAAkBZI9AEAgHRHIz+ViNbUh3AaLazkgTv93Q+q86lpOn7VwUmOpg2ppqX+TTgNbdOmTbakRSwl2FQaQ1NEb7rppojGoQtoEydONFdeeWW85V988YW56667zPr162NuHQkCjXzRlLa6devGW75ixQq73mzZsiVisSE+zczR1HJta2MxDl2EDR/lqnVUo8h04UAlV2ItjqDFEgRBeT+CEkeQROo9iT+vAFFL0//coapeU+5YB0fuFFVNz1D9E73+77//7ksMLtUn0Nx3NX/QFBFNo01JkXCvaQptakbIRNs6EpQ4grKuBiEO1W0K2joZ/v5oNK6mUqvAsqZ+w1+qN5bSm19U2yupqReqmaNp6H56+OGHzejRo/9xarPX9P+t0eIJKZHx9ttv+xaHRuOuXLnSREL4uqgpS5o2oxpGem8ita6q5mhSo8fz5s1rp1zF4jqiYvqqT5uQ6kzdeOONvsSg6Zi6WJBQ4cKFfWlOhqTrwSZ10ywHzTxx78dKHFoP9X1VCRXVw9MxsurhKUGgGSe6iODHuhqUONxYdNEk0rHoWFSNH3XhRDUME15c1PRZP0oQBOX9CEocQflcAvGeeNbPF4GiNtt+tBpXy+rSpUvb16pQoYJt912zZk3bll1tyAsVKuT89NNPnsehVta1atWycajNuP5VHMWKFXMyZcrk9OrVy/HD3Llzk7wphnHjxoXux9I6EpQ4grKuBiUOtYDXetmkSRNn1qxZzokTJ5xIufbaa52//vrL/rx//36ndu3aNr7ChQvb96ly5crO3r17IxZfLNL7n5Kbn9uQokWLOlOnTk20XMuKFCni+etff/318W558+Z1ypYt67Rq1SrRY36Ji4tzfv7550TLtUyPeSl8H/fSSy85559/vjNw4EDn7bffTrQPjLV19aqrrnKuueYaZ8+ePaFl+rlp06bO1Vdf7fgpkutIOO3bvvvuu0TLtcyP769on/vKK68kWj5jxgz7XYb/3O9mct9Zv767QYnjtttuc+rWreu89957Trt27ezP2p7s2LHD+fXXX5169eo59913X8zEEaRYtH/TcciwYcOcxx9/3B4D3HXXXfG28VpPYuX9CEocQflcgvCekOiLEgcOHDjr7YsvvvBlh9S6dWvnuuuuswdqDz74oHPhhRfaZSdPnnSOHz/u/Oc//3FuvfVWz+PQl6lNmzb2/12v2717d6djx472sUWLFjkFCxZ0Ro0aFdEDBb9PNoKyjgQljqCsq0GJQ+uiEiR67SxZstjvSI8ePZzvv//e89dOKhYl6+Wee+5xqlSpYhOgsn37dpsIvfvuu32PC8Hy9NNPO9myZXPuv/9+e7Kum7b1SpDrMa917tw5xTe/VK1a1Rk7dmyi5WPGjLHbllhLsAWFkmgXXXSRkzVrVqd8+fL2pp/1eSWVdIvWdSScvru60JXQ+vXr7WN+ePbZZ+2+bsqUKc7WrVvt7eWXX7bLhg4d6ksMiK9atWpOy5Yt7XrgfiZbtmyxF+0XLlwYWhYrcRQvXtxZvnx56MKntqGffPJJ6HGd05QrVy5m4ghSLLpQ8P7774fua1uuZdrnnzlzxiaU/NjfBeX9CEocQflcgvCekOiLEu7Bc3I3vw6uNeJmzZo19ufDhw/b11XixrVs2TJ7ld9refLkcX744YfQfcWi5IUSSaITwkqVKnkeR/Pmze2Bgpu0cOlAYd26dU4sriNBiSMo62pQ4ghPrulfnQBp5Jw+i8svv9yZNGmSc/DgQc/jSBiLvqcJRwBpJ8loi2A4duxYRF//jTfesFdI8+fPb2/6WctilZIU2bNndwYMGOAsWbLE3vr372+Tn/oOI3J0grFgwQJn9OjR9vbxxx/bZbG6jmi/Mnjw4CRHY1x66aW+xKD3v3fv3jax6B6D6H1IKi74Q7MJdJFRF/hWr14dsePmoMShdXPbtm2h+5rtEX5xQKOC9H2OlTiCFIteQ8nfcBqpdcEFFzgdOnRwdu7c6cv5TFDej6DEEZTPJQjvSWbvJgXDT+qI+fjjj5vatWsn+bjq0nXr1s3zONQ1rUCBAqFi3LqF1z8pVaqUnRvvNc2Fz5AhQ+i+uquqEKZbA021aPyoi6POrc8//7y57LLLbHdIzcuP9XUkKHEEZV0NShzhihQpYutb6KZi8S+//LLp2bOnvSleP7jfX9WzKF++fLzHVHdDnXcRGdqWqlOomgto3fzpp59s04X+/fvb4vZ33HGHb7GoyUKkGy2E27t3r9m4caP9Wd2y9V3yk7qHqsCzisW7TUr0mbzwwgtJ1jOMBYsWLbL7YbfhxYUXXmgefPBB06RJE1/j0DatadOm9hZJQVlHtL1QsxTVL1TdYvezev311239Tb8+E9UJVCxaP7Jnz267/uoYEpGRNWtW2xBGx8/XXXed7aAeie7HQYlD+xDV8NKxoHTv3j10zOgeI+m4MVbiCFIsxYoVs9svbT9dJUuWtDWlGzZsaDp37mxi6f0IShxB+VyC8J6Q6IsSl156qf1XhR6ToiLQfhQJVxeqbdu2mfPPPz9UVDn8RGffvn0mf/78nsehwpcDBgww06dPtzvrxx57zJ6Iul8uv+IQJUe0YenQoYN5//337QlHLK8jQYkjKOtqUOIIT4yHu+qqq+xtzJgxtkGIX7Qj1smWiuqqUUnVqlXjFVBPqrA9/KEEgbatWle7du0aWq6iwjox8jPRFxQHDx60DZ9mzZplE6GiYs/t2rUz48ePt00X/KLmU7pp26HERa5cuUysJth0ga1Hjx7mv//9r/1XvvrqK9OiRQsbmz4zr2ibqY662bJlsz+fTcIOuLGwjvznP/8xc+bMsRcN1AREcVxyySXmk08+Sfb4IK1NnTrVdtfV///ll1/uy2siZa699lrb0EddbpVsi9U4qlevbpYvX26bCsgzzzwT7/GlS5fa702sxBGkWHSBQl27GzdunOi4Xs0g1Wwhlt6PoMQRlM8lEO+JZ2MF4StNt9BUkORoPvqgQYM8j6Nbt27O5MmTk31cdZNatGjheRy//PKLrYGjIfaaspsvXz5bU8OlWmR9+vRx/HT06FH7/lSsWNE2PfB76m5Q1pGgxBGUdTUocYRPl420hPXNEk7FVDOdZs2aRSy+WKdtq1tjJFeuXHZ7K6plpG2tX06dOmWLLWsKoAovu9N33ZufbrrpJrttnz9/fqjeqH7W1HPVjPWLpmP6UTfqn4wfP97uf2+++ebQVNX27dvb/bEaUfmlZMmSSdajUwwlSpTw9LXLlCnj/P7776Gfk7v5XYYgKOtIEKjpR+7cuZ0uXbrYMhkIJm0/VHdbNXqJI74VK1ZEpJZyUOPwMxZtR7WfT46miE6bNs2JtKB8Nnwu/r8nJPrgKxXU37Vrly+vdeTIEVsPRwU59+3b5wSF6o2p6UJQkiqI/LqaHuIIEtUyjHRtuFimmiNuoiA80aeLF6o/4hfVFVOh4+HDh9uYhgwZ4txxxx22kP7ZLiZ4QXW9wmtruj7//HP7mF9UQF4Xkho1auS89tprtqFPJEQywRYuYT0clzqZ+7muBklQ1hE1SPvss8+cSPr777+d2bNn24ZYSkIrMf/MM884u3fvjmhcSJ6OnZ966qlIh0EcAY0jSLEQB3FEOhYSfTOhB0UAAEDjSURBVAAAIMVUKF8NjRIm+lTA/sorr/QtDnUq++CDD0JxbNq0yf7sjh7zU6lSpWzn7ITWrl1rk15+UuF4dSIuVKiQHWGpDtVff/21rzEEJcGm9eC5555LtFwjQf0caZmwAUQkmnAEbR1xO7yrG6JOdFQsPZI0m0AXDS6++GIblzrez5kzxzl9+nRE40J83377bSA6dxNHMOMIUizEQRyRjoUafVHk999/N1OmTLFzwVXDyi1IqcYTqndVuHBh4ojhOIIUC3EEM46z2b59uxk4cKCNM9KCFEssUv3TTp06mZ07d5ozZ86Y2bNn2wYUM2bMMB988IFvcei7cvHFF9ufVWPrwIED9mc1PVJxfT/169fPPPTQQ+aVV16x3103vl69evkeS40aNextxIgRti6s6pDVq1fPVK5c2dZP1DbF65qBKl7/7rvv2v//cHPnzvW1KVWVKlVsTcklS5aYOnXqhGr0LVu2zDz88MPxaud5XSdP349hw4bZhlNywQUX2PfntttuM34Lwjqi+nyqEajvjGp+apuu+o16/datW5ssWbIYPxUtWtTWd1ZzId2+//57u51TjVy9P37WdQIA4FxlULbvnP8KIu6bb74xzZo1Mzly5LAHSjpgEXVEVEHso0ePmgULFtjur8QRe3EEKRbiCGYc/2Tt2rW2kYrbaIBYYpu6MT/xxBP2s1AnZn0eSgD62VFUXW2VPFEHb52gK4HUp08f2zTm/vvvtx1w/aKkyaZNm2w3U7exjprsqKGMuniGW716tS8xnTx50ibblBBXAWpdOFC3am1bJk+ebBuFeOXJJ580w4cPt8mjpBJsefLk8SXBVrZs2RQ3I9q8ebNncYwcOdImfNVxT++JW4RbjVr0XqlpVyREch1JSN8LJdReeuklm7i/9dZbbafThN+ftKb/VyUb9dpaB9q0aWOTjdofHzlyxG7n1GTn119/9TQOpK/9P3EEM44gxUIcxBHpWEj0RYkrrrjCVKtWzUycODFR90x9xHfffbf57rvv7Igh4oi9OIIUC3EEM4733nvvrI/rBEgn6H7sGIMUC4JLST0ljNRVXck9JQbKlCljE2xKnCTsbualwYMHp/i5GrnkpVWrVtmkxeuvv24TjR07djR33nmnqVChgn187NixNrmkBEe0J9iCQu+H1hF9FuE0km3QoEG2s7ifgrCOhNu9e7dN2iumHTt2mLZt29oRw5999pnt7u1VIlSdf3UhTaMr9f+v96FAgQLxnqMLBhqlq9HLiLygnKQTRzDjCFIsxEEc/4REH1Ike/bsZs2aNXbaRVI2bNhgRxwcO3aMOGIwjiDFQhzBjCNjxoz2pPtsuwQ97seOMUixIP1QMlw3jQDSCXws0lRmbTM0srJr1672fciUKVOiUgFFihSJucSFuz1JeEHFD9myZTM//PBDKJHm0jRefWbHjx+PuXXk77//thd1lNz7+OOPzSWXXGKTbbfccktoxKdGG3bp0sX8+eefnsSgkXt6TXfUaXLrjS4elC5d2pMYEJ9KIJyNpnvPnDnT8/0/cQQzjiDFQhzEEfRYqNEXJXS18euvv042WaDH3CmBxBF7cQQpFuIIZhzFixc3EyZMsLWRkvLtt9+amjVreh5H0GJBYqpZlVSyRMuU0FAyQzW+br/9dl/j0sn62U7Y/RoptX79evtz1apVbZLeTzfddJNNjJQsWTLZ5xQqVMjXJF8kE2xBqY2n78Sbb75pR5+G00hUr6emBnUd0XZer9G+fXu7n6tevXqi5zRs2NDky5fPsxhefvnlf3yO1luSfP7Rhc9/cvXVVxNHjMYRpFiIgziCHguJvijxyCOPmLvuusueZDRu3DhRnS/VWlG9HOKIzTiCFAtxBDMOJc4UQ3LJtX8aYRetsSAx1eJTg4Nrr73W1KpVyy7Tifr8+fPNfffdZ6ch3nPPPebUqVN2xJCXlLxZvHixnV6XMDGhOP2i17/55ptt0wc3MfHXX3/ZRIXqe/nVUMfvxh9BT7AlVxtPJRE0as2v2niatqt6d59//nkoDtUr1DZeCUA/BWUdef75582NN95oLw4kR98lr6c16zPQLaltCA2f/KfteRAQRzDjCFIsxBEfcQQwFs/6+cJ3s2bNcmrXru1kzpzZyZAhg73pZy174403nEOHDhFHDMcRpFiII3hxfP75585HH32U7OOHDx923nvvPc/jCFosSOyGG25wXnjhhUTLJ06caB+TMWPGOBdddJGncUyaNMnJlCmTU7RoUadatWpO9erVQ7caNWo4frrpppucyy67zPnxxx9Dy9atW2eX3Xzzzb7FcerUKeell15y2rdv7zRu3Nhp2LBhvJtfRowY4eTIkcPp3bu3M3fuXHvr1auXXTZy5Ejf4ihTpowzffr0RMunTZtmH/PTqlWrnA4dOjiXXnqpvenn1atXO34LyjoSBIMGDXIyZszo1KpVy2ndurXTpk2beDcAANIrEn1RIvzA+eTJk86uXbvsTT/LwYMHnbp16xJHjMYRpFiII/hxJCVS62qkY0FiOXPmdH7++edEy7VMj8mmTZtsUsdL559/vvPMM884QZAnTx7n66+/TrR8xYoVTt68eX2L47777rOfgRKPPXr0cB588MF4t1hLsMXFxSW5rv7000/2MT9oW3777bc7mzdvdoIgKOuILtj069fPqVOnjlO+fHmnbNmy8W5+KFasmDNjxgxfXgtpY86cOUluW4iDOIIWC3EQR6RjIdEXJbJly5bsiqKDqXr16jmVKlUijhiNI0ixEEf6jEOJtaCsq37GgsRKlSqVZDJWy/SYrF271o6081Lu3LmdX375xQmCXLlyOWvWrEm0XCO2FKdfChYs6MybN8+JtCAk2KRq1arOU089lWj5kCFDPB9xmjARHJREX1DWEY10LV68uB31+fzzzzujRo2Kd/NDgQIF7EUJpB/a92sUZqQRRzDjCFIsxEEckY6FRF+UeOutt+zJsabHhNOUPyUKKlasaEcJEUdsxhGkWIgjfcXhJhsVx86dOz2PI2ixIPkps//5z39swkS36667zk4315RAGT58uB0x5KUuXbokOYU4EvT/f/XVV8dbL3fs2OHUr1/f1ymASpxs3LjRibSgJNjefvttu642a9bMeeKJJ+xNP2tdnT17tm9xdOzY0dcpy+lhHdFI16VLl0Y0BiUZtU4AABBtSPRFkcmTJ9upUosXLw6dFF955ZVOhQoVfD0pJo5gxhGkWIiDONJTLEhMJ+gakaNaeLrp52XLlvkaw9ChQ51ChQo5nTp1sonF0aNHx7v5adu2bbY2YJYsWZxy5crZm37We7N9+3bf4tD7cO+99zpnzpxxIikoCbag1MZTgjNfvnxO27Zt7XobyXU1KOuIpnCH17T0S8+ePUM3TV3W56Ikfffu3eM9phuC588//3Ree+21SIdBHAGNI0ixEAdxRDqWDPpPZNuBIC0999xzthvi3LlzbcfBnTt3ms8++8ycd955xEEcgYqFOIgjPcWC4Clbtmyyj6kz8+bNm32NR4dTn3zyidmwYYO9f+GFF5omTZp4/ro33HBDvPuffvqpKVCggKlatarJkiVLvMdmz55t/KLO2eqsun79+tD78fDDD5saNWr48vp///236datm+0ye7Z1JRbW1SCuI6+++qrdtk+fPt3kyJHD+EWdsFNCn4veJwTL2rVrzaWXXmpOnz5NHMQR6FiIgzgiHUtmT/4qIqZ3797mjz/+MI0bNzZlypQxS5YsichJMXEEM44gxUIcxJGeYkHSjh8/bk6ePBlvWZ48eXx57S1btpggUWLgmmuusTc/5c2bN97966+/3gRBzZo1bTInUpTAeuedd2yiL9Iiva4GZR1RklffE9emTZtM0aJF7fY9YcJx9erVnsSwePFiT/4uAABBQqIvSiS8WqsDpkKFCpkePXr4eqWWOIIZR5BiIQ7iSE+xILGjR4/aJOybb75p9u/fn+jxSFwldScnhCcRvDZmzBhz1113mWzZstmfz+aBBx7wLI6pU6eaoMmUKZPZvXu3KVKkSLzlWl+0zK91pE2bNmbOnDmmZ8+eJgiUFFfSr3z58iZzZv8OwYOyjujzCKrt27fbf0uVKhXpUAAAOGck+qJEwqu17du3Jw7iCGQsxEEc6SkWJNarVy87KuaFF14wt912mxk/frydVv3iiy+aZ555xtdYZsyYYYYNG2Z+/vlne/+CCy6w8Skur2laaocOHWyiTz8nR8lHLxN9Sdm7d6/ZuHGj/blSpUqJEm5eS64qzIkTJ0zWrFl9i6NixYrmiSeeMMuWLbMjDHPmzBnvcb8+FyXH77//fjtNVX766SdTrlw5u6xkyZKmT58+xm+RWEcGDhxoguTUqVNm8ODBNlF/+PBhuyxXrlz2c1GsCUcZAgCQXpDoixJBuVpLHMGMI0ixEEd8xBHsWJDY+++/bxNsDRo0MLfffru56qqrTIUKFUzp0qXNa6+9ZpNffhg5cqSdltm9e3dTr149u2zp0qXm7rvvNr///rvno7jCp2NGemqm6+DBg+a+++4zs2bNCo2a0+i6du3a2YRswiR6WnNHNiq5+dJLL9mkiUvxfP7556Zy5crGLy+//LLJly+frReoW6QSsH379rW1eFR+oHnz5qHlquE4aNAgXxN9kV5HElq5cmWojmOVKlVsQtYvSuhpZLjqwdapU8cuW758uf1MNPpUFzPgr38aHa2LSsQRu3EEKRbiII6gx0IzDgAAkGJK3vz444/m/PPPtzUTdaJcq1Ytm+y6+OKLQyNj/GhwoNE4HTt2jLdco6Z0ou5X8k1NH5S8+uCDD2zDiUhSsmbNmjVm7Nix8RIXmvZevXp1m9zxo+nEr7/+atcNJZBcGsmnWmwaYVe7dm0TS5QEf+ONN8wVV1xhcufObZN+GtGnGnUqxK3kW6ysI64dO3bY0doabalkrPz111+mbt26NgY/6rEqqanXuvbaa+Mt//DDD21sBw4c8DwGxJfSxjleb9+JI5hxBCkW4iCOoMfCiD4AAJBiSlDooESJPiW4VKtPiT6N9HNP2P2gGnBKCiSkZXrML5rep6YkQaBk44IFC8yVV14ZWtasWTMzefLkeCPJvOIerKqzqRLA+fPnN0ERiTqOrn379iU5NfbIkSO+xxPpdcR155132iS5RvNp6rBoKrFGCeux+fPnex5DXFycTT4ndXLm5xRzmMCNjiaOYMYRpFiIIz7iCF4sGSP66gAAIF3RibhGJImmHGq6n+rUaaqs6uP5RdOFlWRMSCOnVJvNT5oK+eyzz9qaX5FUsGDBJKdeapmfSTfVcHRfTwm2SE4e0TRzjTTNnj27vV1yySXmlVde8TWGyy67zMybNy90303uaXqzO6ou1taRzz77zE6NdZN8op810lBTvP2gaf9DhgyxtSNd+vmpp56yjyF4NBJUTZAijTiCGUeQYiEO4oh0LEzdBQAA/5qmaar+mRJvSqL45Z133rHTEFXnzK3Rp2mAixYtsgnA66+/3rdY9Fp6XU1rVlIpYdMHvzpET5o0ybz11ls2kVWsWDG7bM+ePaZTp062m3W3bt2Mn/Xx1KTEbZSi5OuDDz5oR2v5Jbk6jkpOP/nkk75149VranrorbfeaqZNm2Y/B01///LLL23Cy8+6dEFZR9Q459VXX7WjgcN9/fXX5pZbbrHTmv363mpkX7Vq1ewyXcRQd+TGjRvHey5d3oNBn4+mu0eiuztxBD+OIMVCHMQR6ViYugvgX1ENLF2NV+e+d99917Rp0ybSIQGIUP0x3fzWtm1bs2LFCptMmjNnjl2mGnlKFNSoUcPXWDRlWfFEmrbJSpBoWrVusm3bNpvI0PRRdUZ2rV692rM4BgwYYJNsanYQXgdOiTXFozp9ftDoML0n4XUcr7vuOlO1alW7D/Mr0adpst9++63tSq1E8Mcff2wP7vWe6H4sriPqlq31Q0lXjXh0G3OoVuDw4cNNpL63pUqV8uW1AQDwEok+IIZ07tzZFrt2T4rl7bfftqMMNFXl3nvvtScir7/+uh2lo6LhqrWkEyKdGLlUU0dF8JXgU3HxINVhAuB/57BwfnUyFY2E0qigSAtKp+igXHBRMkk139TQIDzBphGfSu74legLSh1HKV++vH1PIi0o64iOR44ePWobs2TO/H+nI5r6rp+7dOlib64//vgjqr+3AACkNRJ9QAxTfSDVlpo4caKdKtOoUSN7ZX/EiBH24Pu3334zTz/9tP35k08+sUk9+eWXX+y/rVu3jkhhcwD+0qi5lND2wM9En2hUsW5nzpyJt9zPacRBMXDgQBMEarLgjtJKmJj1s46hW8fxsccei2gdR3UfVmIxYUOO/fv322V+TiEKyjoyatQoExQayahGIG6dwMKFC0c6JAAAzgmJPiBGPffcc/aAf9asWbZOjQrJaxrRmjVrQrVqNB1PdbCU6LvjjjvMDz/8YEfy6SYZM/5fPx+V+vzmm2/syZR+Xyd51atXt8kBTU8KTwIoqajunJ9++qn9+1OmTLEH1arbpL+h11btII1+ABAMmnaYVAH/SFJdQNUV0wjjhOWGta3xu/6KRkcrqaSLJarxFc7LKZDJvTd6X0Sjsf2eynzbbbfZUX2avpuwPlyHDh18i0P7KtVxVHOHpOo4+iW5cthq/BCp7q6RXkf03Y00dT3WCFM1bHEvFCgpq6nemvadI0eOSIcYc1Qn8mw0K4U4YjeOIMVCHMQR9FhI9AEx6NFHHzUTJkwwH3zwQajg9MyZM80111wTSvK5lMxTHSOdnKlo6COPPGLKlCljO2+GT306dOiQPXDXwbFOajQqsEWLFrYQu6YAu9ThTid/uikOjSQsV66c6du3r60XpOk6Kpz+0Ucf+fiOADibAgUK2IL9Sspr5K8K06u+VSRpW6GC/mr6ULRo0YiOLtbU5scff9xOR5w7d67dPmrksy5eaNS0XzSy8eabbzZLliwJfT46kFQJBl3U8XOkkj4X1aJzR4KrnqKSoEqiPPTQQ6HnJUwGRlMdR3fKu9ZNjaBXsxaXEtFKQFauXNn4KUjriN4DfS7hCUdN8VayzQ9aD9UMRRcfw5u1aFTyww8/bJPV8Nc/XVDS4+E1N4kjtuIIUizEQRxBj4Wuu0AM0Umo6u9ptIlGNOiE3ZU9e3bbbS+p6TQapaeReZrudNNNN9kDc40CPNvmQ1fHdRKhBGKrVq1CJzv9+vWzyT756quvbKF2nRC69Xh0oqGT5GPHjnnwDgD4N3Qwou+rkiRK/mtaf6Snt+kCgrZNmp4ZaUrWaIS0atIpLl0U0QUMNaVQfbFx48b5EodGr23evNmOUNJnJeruqoswep+0/feDkkYpoX2CRndHq7Jly9p/VfP2vPPOi5fA0kg+XTRTvUKNmvdLUNYRNQTRxcCdO3fa6bKi6bNqhjFv3jxfRvUXKlTIjsRt0KBBvOWLFy+2xzqa0gsAQHrEiD4gxqhu1e+//25PSmvVqhVvhMG55P114q8knkYJaMSArtSr0LZGcCR8fZdG4Uh410EtO378uDl48KDJkyfPv44HQNpp0qSJTd64iQEl+pObcuhX4kajkZVQC0KiT9s5t+mDLppohLM7hVUj2vxK9M2fP9/WU3U/J6lSpYrtbNq0aVPjFyVKIkX7jpTyeh+zZcsW+6++OxoFG4TGVUFZRzRqTsk8XUDQiGG3ZqGag+kxJfu8pmMU9zgknOom6jEEi45Rtf7q4rAStMRBHEGNhTiIIwixkOgDYkzJkiXtBkUnHs2bN7dTZDUCRVPg3OkzCbnL9ZzkaDSADtJHjx5ta+/FxcXZ0XoJa1VlyZIl9LM71S6pZQkL6wOIHHW2nT59up2OqqlummIX6fpVmgqp7Y5qh1500UXxtiOiKYB+KVasmB25p22fShAoeaEyCEr0+DlxQtvNhO+DaFmsbFM1kvyfpnHrM/GzjmMkE59BXUe0HQlP8knBggXNM888E5pG6zUdo+iip0Y3ZsuWzS7TbALVdtRjCAZtR1XPedq0aXaUpS48EQdxBDEW4iCOQMWiqbsAYkOnTp2c1q1b25+3bdvmlC9f3qlbt65z8OBBZ+jQoU6GDBmcb7/9Nt7vnD592rnsssucKlWqOGfOnLHL3n33XZ25xnterly5nBkzZoTu6+/rOc8//3xome7rd11btmyxy9asWRNatnjxYrvszz//9OAdAHCuGjRoEIjv53vvvefkzZvXbrcS3jJmzOhrLHfccYczaNAg+/O4ceOc7NmzO02aNHHy5cvndOnSxbc4rrvuOufqq692du7cGVq2Y8cOp379+k6bNm0cP33zzTdOr169nHbt2jnXX399vJuXlixZkuKbX2644QbnmWeeSbT82Wefdf773/86fgrKOpI/f35n2bJliZYvXbrUPuaH77//3ilRooRTsGBBp1GjRvamn0uWLOn88MMPvsSApB0/ftx59dVXnYYNGzpZsmSx2/SRI0c6Bw4cIA7iCFQsxEEcQY2FRB8Qo4k+2b59u1OhQgWnTp06dmNTu3Ztp1SpUs6bb77p/Prrr87XX39tD/xz5szpLF++PPR7SSX6atSo4VxzzTXOjz/+6Hz11VfOVVddZU92SfQB0UvJf/cCgN9Kly7t3Hfffc6ePXucSNMFkb///jt0//XXX3fuv/9+Z8yYMc6JEyd8i0MXWKpXr24PJMuVK2dv+lnbZ23v/aL/f71uq1atnKxZs9p/L7jgApuY7dy5sxNrChUq5Hz33XeJlmtZkSJFfI0lKOvIbbfd5lStWtUeL7jbER1nXHTRRfZYxS9HjhxxJk2a5Dz00EP2NnnyZOfo0aO+vT7iW7lypXPPPffYiyS6yDx69Gi7jc+cObOzbt064ojxOIIUC3EQR9BjYeouEMNUHFw19TSNt1mzZrZD4nPPPWcee+wxWzxcU3r1mKbXaGrc2ajGwF133WWbdqiY9tChQ22HXgDRR1Pdhg0bZrtqu9P6e/XqZWvS+UWlAtQRPKkaW35TgxLdXOpqqpvftO1dvXq1rcG2YcMGu0y12PyepqLtvzrdquOw9iMq6aDGFGr4VLx4cV9jUUdZddlV7diEU1P96rx3+PDhJGtaarpsamoKRtM6oo7EmnqvKbLuVOJTp07ZKfdaX/yiEgRdu3b17fVwdmpMc//999vjTrdJC3EQRxBjIQ7iCHwsnqcSAQBA1BgxYoSTI0cOp3fv3s7cuXPtTVM0tUxTEfzSsWNHO/omUtauXZviW6zRuqAR21KgQIHQaDaN+C5WrJiv07tz585tp3NrNKGuqrs3v6aHyuWXX+4MHjw40fKBAwc6l156qRPLfvrpJ/s56fbzzz/7+trTpk1zPvjgg9B9bce0nmiWw9atW32NBf+nadOm9jt7yy23OB999FFoxLjfo3GII5hxBCkW4iCOoMfCiD4AAJBiY8eONS+88EK80VAahaMGHYMGDbKj7PygUYR9+/Y1S5cutZ27EzYYUOdOL1WvXt02dPinZht+Nn3QKKnkYlCzAXUovvrqq02mTJk8jUPdZd3Ow2oApYYp+ow0us7PbqYPP/yw6dKlix1hGMnmMf379zc33HCDbWbTqFEju2zRokXm9ddfN2+99VbE1oukeP29SahixYr2FglaL7Qtk+XLl9vu2KNGjTIffPCB3Y6pUzL8tWDBArN9+3YzdepUc88999jmKO3atbOP/VOTHeKI/jiCFAtxEEfQY8mgbJ/nrwIAAKKCEkZK3ChpFE7TeJXMOX78uC9xaCpocnQAtXnzZk9fX+UNUkrdeP16T9TFTck0Jdvkzz//tEmuXLly2emr5cqVs11gNYXTK7fccou57LLLzEMPPWSGDBlik8OtW7c2CxcutOUd/Eqg5MyZ03z//ff2/znS5s2bZxNL3377rcmePbu55JJLbMfX+vXr+/5dcdcRdSgWJWC1jhQpUsTz741LyW91HVTCM6lp1Z9++qnnMej/WdOX1Sn70UcfNbt377ZlCdatW2caNGhg3ydElrYZOkl+99137Tbrv//9r71pO0IcxBGkWIiDOIIWC4k+AACQYqrXqUSOanmGe/LJJ80bb7xhEyuIDI0QmzRpknnppZdM+fLl7bJNmzbZ2niqoVqvXj1bO7BYsWLm7bff9iyOP/74wyZ8S5QoYRM4qv365Zdf2pFb/fr1CyUhvaZRdPr/vemmm3x5vfRg5syZZsKECbaurlszaOPGjbZOndaTDh06+BJH9+7dbaKvZcuWtm5jwtENqvHoNSU2NeKiRo0a9qbEtOqMauRltWrVbG1FBIMuWLz66qtmypQp5rvvvvNtlDRxpI84ghQLcRBHUGIh0QcAAFLsnXfesVMPVLxfiSNZtmyZHZnz5ptvmuuvv973mNxDGT+nZbz33nspfq6mNvtByT19PppWHG7NmjWmbdu2drSWEm76WaOX0lpKG0vkyZPH+PG5aETWE088YW6//fYkp3f79bkEidYRJXmV2Aq3atUqO7Jgy5YtvsRRqFAhO3quRYsWJlKU1NSIPr0XSpJv27bNFCxY0K5DupChkcsIHjWTicRoHOJIH3EEKRbiII5IxkKiDwAApIqSAhpxs379+lDXTtVDS5g8iObuv+FddoNSo09TET///HM7bTbcN998Y6eIarrm1q1b7ahML0Yr6T1JSbLVy/cjiJ+LXkffFyXClUw6efJkohGQftE68tlnn5nLL7883nJ1JtZ0Vb9qKGq055IlS+x3NlI0ZVkjTFVDSfWTmjdvbpdrSrW6JD/++OMRiw0AgHNBog8AAKQ7I0eOtE0ONAXQHVmoxhzjx4+304j9agoSJJoGuWfPHjt11026ajSfpmVquq6aDLz//vt2tJIXU6yVQHLp8FKjtRSLGnKE86MuXZAMGDDAvg9KhiuxpASSEq5z5syxj/nZAOM///mP2blzp43HHUWgxL2mdutzSs1I1XMxYsQIO8JUDTD8LpCO9EsXlX766aeITrsjjuDGEaRYiIM4Ih0LXXcBAECqqO6aar8lVURfXV1jqftvkKjumkYz1qxZMzRN9dSpU6Zx48b2MVFTDiVZvJAwgafuvldccYXvzTDUyEEJ4K+++irRNOEDBw6YunXrmokTJ5qrrrrKl3hee+01M3nyZJuI1brZvn17O4VWDTkUo5+JPtUE6tSpkx31Gb6ONGvWzCb/vK6ZmPBz+uijj+x3NuG0aj8atpQpU8Z2ZdbUbi+b0yDlNHX8bI2Wnn76afsdJo7YjCNIsRAHcQQ9Fkb0AQCAFFNiQs041HU24SGEn9MhI939d8yYMXYUlOLQz2fjZyJHVHdMV4lFDRfcpgt+y507t1m7dq3viT4lfBs2bJhssleflzoPq/OdX91/Nc1d3V3VeEIdeDWaTiPaNPLSr5OOcFo/tJ5I5cqVfZlCq4RaSqkzoddGjRplG4JoO6L15Y477rA1RuPi4jx/bSQ/9V5dyvV5uLfzzjuPOIgjcLEQB3EEPRYSfQAAIMXU6EFJgcGDByfZLTNv3rwx0f1XV2lXrlxpi/ef7Yqt3h8ldGJRpBJ9OrCeP3++nRaTFCW4mjZtauvl+UGJVtWTrF27trnyyitNq1atTJ8+fex6ev/999uRsYhsMXQl/NSQQxcqtF3RSL+gFGuPJarb6N5WrFhh61lq+9GoUaPQiXLRokWJI0bjCFIsxEEcQY+FRB8AAEjV6CQlbxKOpPNbELv/BsGOHTtsnbWkmj6orqHfib7vvvvurIlQP0d7ujTtXKM+jx075ks8SuppCrGS0kru3XrrrXbaqD4jjTp85plnPH39hx56yAwZMsR+d/Xz2fi1jmhKk6YMV6xYMdGIXE3j1fvjt7///ttMmDDBPProo/ZnrSMajauRiNQR9J9GZatLuHuirIYx+lw0AnXdunXEEeNxBCkW4iCOIMZCog8AAKSYrkT27t071KEykoLS/TcolOTUtFVdMdaoNY16VNMHHeppdJJqovlZg02NP7S+KMHkZ/011b9THcI2bdok+bhe/5FHHonYSEtNf9cBv5Jcao7hNY0a0DTlfPny2Z+To2SW1+tIeD1HjZpTvcBwr776qq0VqBMhv+hkS++PpgsvXLjQ1pXUNF4lzdXcR+vwzJkzfYsH8emChS7iqJ7jiy++aDuGR6KQPnEEM44gxUIcxBGkWEj0AQCAFNMJsTqH9urVy454SVhEXw0GYk3btm1NrVq17EigcM8995z55ptvzFtvveVLHIrh2muvtdOq3WmzRYoUMR06dLCJ2XvuuScQNdi8rr+m6bBKFOm91+i+cBrFp/dJCa9/qq2YVvbv32+neMv27dttYw7FoSSfX81rgkYjHDVlNuGoS422VKOQv/76y/MY9PpaFzVlV7WU1NjnzjvvtCMsXBoZevnll/s2+hP/dyKsZLjqaLpT3tQsRd8V3ZQkVr1L4ojNOIIUC3EQR5BjIdEHAABSTCfESY0E0uGE1804Dh48mOLnJuy26qXChQvbkVBKfIZTnUBNLf7tt998iUPJvW+//daOaMufP79ZunSp7WiqhF/r1q3t6L5YoPdbIxjV9Vfdd91mJBrlqBFaWkeV5PG6To8+fyXzlNzT6L1Zs2bZhOuRI0fs90j/vv3228mOPIxmquWpk56Eo281SrdBgwbm0KFDnseg9eOaa66xo/f0GSS8aCH6jLQO+dEcBP83YlwnwprurxNgdcbWv6oHSxzEEaRYiIM4gh4LiT4AAJBi6rb7T40QvKLkSEprZfk5LSN79uw2wZawu60SS0pk+DUaqFixYvaqsaYwV6lSxdZ+01ReJfpUx1BTRGJpPdUIxgULFoS6Q2vdadasmU32+VE3UKMrM2fObGv0vfLKK+aDDz6wr68Rfe7IQyW2dLXfzynVZ+P1tGqXEqD63mg0nRJu7ndWdTeVXNO0Ji/ptTRNWN8PJcURDEq26iRYiVclfHVS7I6GJQ7iCFIsxEEcQY+FRB8AAEgXPvvss9DPGp2mBErnzp1NnTp17LLly5eb6dOnm6effjpR7S8vaSqoOqkOGDAg3vJBgwbZOnVK5vhBB5MtW7Y0Xbt2tTXo5s6da98fJW+UzPjkk09MrPnzzz/tdFAd7mpUnZ9JnUKFCtmRnprOriSrRplqOnHNmjVDiWDVg/N6mmpKp1SLXyPXfvzxRzttSXUDNcpBvvjiCztqV++Z6kt6TdO6Vd/T72YxSJ6SvFoPNNpTFy10AUVd3nWC7J4oawQ1ccRmHEGKhTiII+ixkOgDAABnpS6uGp2kq5P6+Ww0QsYPjRs3tvW02rdvH2+5iuZPmjTJ12L+SuZp1NQtt9xip2q4jTE0Wkn1+fyamqnmEkooKbGkA0w1JnGbPqibqpejLZH0CNQ9e/bYOoni1k1UsxR3inGJEiUiVhQ80nbt2mXGjRtn3xON7tN6q2myBQoU8OX1VQvw2WeftdsSBJOmcKsEgVvfSuuKtmeqnUgcxBGkWIiDOIIWS2ZP/ioAAIgaSlS5CYuzJa28rtEXTqP3Jk6cmOTJuxKAftI0xDlz5pihQ4fammtu0kIj6HTF1i9uAknU6Tap9wf+SjjVPKVTz722b98+s3HjRvuzppz7NcIhnJKc+s5EypNPPmlHvg4ZMsSOskzYHdrPOp9Imj4TJX5102hcTYV3u6wTB3EEKRbiII6gxcKIPgAAkO4oOaEGE+psG6537952yqqbxAAiOaJPI2Hj4uJCIz814tNNKJ04ccLMnz/f1xF9Gump2oAzZswwZ86csctUI08dZ8eOHWty5MjhWyyasvzyyy+HTnTUOKZLly62UYffjYXCE7B+NBZC0rROrly5MjTVbdmyZXadLVmypO2U7d68Hp1MHMGMI0ixEAdxBD0WEn0AACDFBy3Tpk2zNd9UI08nwxpF1rZtW3Pbbbf5Olrpww8/tK9boUIFU7t2bbvs66+/Nj///LN55513TIsWLUws0FXhlL7vf/zxh+fxIPW18fzs6NqtWzc70lRTZtWgRTSV6IEHHrAdaF944QVf4tDJjxqTaPSralyK6heqcc3HH39suyb7WfMzKX6OxsX/RlHqRFiNhdyTYNWyUidx4iCOIMVCHMQR9FhI9AEAgH+kwwVNUVWCrVq1aqZy5cp2mUbjfP/997Y2n6av+mn79u02MaGmBqJus3fffbcpVaqUr3Fo5M/zzz9v3nzzTbNt2zZz8uRJ3xJsaj6SUn42KEEwqUGIppfrZCOcRhvcdNNNdkqvH9SAQ0l6dSDW9CU5deqUnXavWpOff/65L3EgWF588UV7MqyC9cRBHEGOhTiII+ixkOgDAAApGnXUo0cPOy1WBy7h1CVTtfs0SkhTAGONuu2+9NJLtvlFv379zOOPP25HPCrxqcc0WgoIAk3NVRdoJcXDrVu3zo6s0+gDP2gk35o1a+wFg4TdeFVn8+jRo75NH9ZI4L1794amMrticVsGAIgOJPoAAMA/atq0qa0v1qdPnyQfV1F9TYVbsGCBL/H804ifq6++2vhF0zDGjBljWrZsaTurfvvtt6FlX331le0E7JdffvnFJmX17+jRo20DlY8++sicf/75tgYaYps6zBYsWNDW6MuWLZtdpumyGu2pkaea1uuHokWLmldeecVuV8Jp+6EEmzoSe001Ezt06GA7VWuKVfgUeP3MVHf/1ahRI8lSBKrbqFExDz74YKIkNXHEThxBioU4iCPosdB1FwAA/KPvvvsuUeOLcGo6oMSWXxJOPZTwAyo/C+mrI/HFF19sf86VK5c5cOCA/blVq1amf//+vsWhRKs+B9VeUyL0qaeesom+tWvX2qYHmrKJ2Kbkr2rjnXfeeXYKvmj9UMMQ1cbzS7t27cwdd9xhhg8fburWrWuXqVB5r169TPv27X2JQSNw1fxDFyn8bEKC5CXX1V0jL1evXm2qV69uR5C79SWJI7biCFIsxEEcQY+FEX0AAOAfZc2a1fz666+mePHiST6+a9cuU7ZsWdtJ1A9uMs31999/26mASqwpwaWRS352ANYIKTUFufLKK22CTyMf33jjDdvhVNMC/VCnTh1z4403moceesiOLFQCR81SNDXxhhtuMDt27PAlDgSbpsW+9tpr8WpbamSbptP6RXUsldSbOHGirc0nWbJkMffcc4955plnQp2KvaTux6ovqu8I0geVRdAo6UWLFhEHcQQ6FuIgjkjHQqIPAAD8o0yZMtmRa4ULF07ycU21K1GihK8j6ZIb1aZEl+qQ+UVJPU39e+yxx2xy79ZbbzVlypSxjTl69uxpExd+0GhCJS6UcA1P9KleoGqhHT9+3Jc4EFz79++3U3dF66dqS2rqrprpqEFGJJKOmmYumu7u58g6Jb9vvvlm24QE6YNqSapGrF8XT4gjfcURpFiIgzgiHQtTdwEAwD/SdcHOnTsnO9LGr5F8Kan9tXHjRl9fMzyRpymJpUuXNl9++aWpWLGi7VTsl3z58pndu3fbRF84jXQsWbKkb3EgeJQA1rqoTtVaL2fNmmWaN29um29kzJjRdo3W1O7kphqlNdWRVJJNiT132rsf3nvvvdDPqqmpUYVqAKIYNKIwnJKfCN4Fp4RNU4iDOIIYC3EQR6RjIdEHAAD+kYr1/xM/u1SqZmDCRKSSXEq6qe5JpEZJKZHy4Ycf2lFS6h7qJyVOHn30UfPWW2/ZeoU6gFTds0ceeYQOojGud+/eNpmlKbtqgqHp5Up0TZ482T6uKeb67viV6NMoWHXx1lRz1epz6/R5Lan/vyeeeCLRMn1/Ij06GYnNnj3bVKlSJdJhEEdA4whSLMRBHJGOhUQfAABI0QicIFEyTyfjCSuQXHHFFWbKlCkxOUpKTQW6d+9uO+yq7pkOIJWsuOWWW0y/fv18iQHB9M0339ii35dccoltwjFp0iRz77332vXUTfTpu+OXnTt32q6306ZNs411NMX89ttvtxcUihUr5tnrBmUkB5KWXEMn1WRVOYZ58+bZLuLEEZtxBCkW4iCOoMdCjT4AAJDuqDFIOCUsVD8wW7ZsvsWgDreZM2e2o5M0SuqDDz6wHU3DR0npYE7Flr2k5MWwYcPstEQ1OVAyp23btubw4cOmRo0aNgmJ2Kbvh2psqguzhNdwjHSNTb32q6++aqZPn24bhChZrlF+SqK7ici0pISnEuL6Xqq2ZsITMI0uVJOQSNQsjHUJyw649Dmp6ZFqnqrpEHHEZhxBioU4iCPosZDoAwAA6ZqaTPiZ4HMVKlQoNEpKSTUdvGnkVM2aNe3jSlpolNRff/3laRxDhgwxgwYNMk2aNLGdUxcsWGDat2/v28hGBJ8SZkqouc10lOjT9Hf3RCTSzXRWrFhh11cl+9TZ+88//zT58+e3I4k14i8tqfaeCqDrJCu5URiLFy827777bpq+LgAAfkn7y2QAAAAeU0JCCS41mVC32c2bN9vl/fv3Ny+//LIvMfzxxx+haYaKIWfOnDY54dLPhw4d8jyOGTNmmAkTJtgE35w5c+yUSNViY5oiwqmZjjrN6qbk+N133x2636VLF9/jUXJx+PDhpmrVqjaZd/DgQTsqdsuWLXZqr7rhpqQ2aGppJKNGDSanadOmvnbtBgAgrZHoAwAA6c5TTz1l63s999xzJmvWrKHlF110kXnppZd8i0N1As923w/btm0zLVq0CN3XyD7FsWvXLt9jQTApYaZpu3nz5rW3W2+91Y7gc+/rMT8btmhabqlSpex3uGvXrjax9/rrr9t1V5Q0f/jhh239Sy8SjAk77IbTdPx9+/al+evi3M2dO9de2Ig04ghmHEGKhTiII9KxMHUXAACkOxUqVDAvvviiady4cbx6Y5ouq5onmvrnx3RI1emLi4uz9zWSrlGjRjZJISdOnDDz58/3fDpkpkyZbP01d1pmUlMzgSBRDb4777zzrPWJdIqiJHbp0qXT9LXLly9vRowYkWyTHHVCVKdqd5QwgqNy5crm559/jnhHZOIIZhxBioU4iCPSsZDoAwAA6Y5q0SmppyRAeKLvxx9/NLVq1bI187ymLqFB6FicMOGYVNLRTWAAQaBRDO3atYu3zoqayah7tZejC9UkZ8mSJbaeZsLanseOHbPbD9XwS65jIgAAQUeiDwAApDtqeKFi+pqCGJ7oe+KJJ8zChQvNF198YWJFUBKOQGpGoe7evTvUBdi1f/9+u8zL0RaaunvppZfaGNR9V90PRRcOxo8fb1979erVpmjRop7FAACAlzJ7+tcBAAA8MGDAAFt3TLW91HRCo9U2btxoRwqpoH8sIYGH9EbjDJKqZ7ljxw5bM9BLSuB9+eWX5p577jF9+/a1sYjiadasmU32keSLHH0eW7dutTUcVS9RozzVAVmlEFSLVN3OiSN24whSLMRBHIGORSP6AAAA0pvPP//cadKkiVO4cGEne/bsTr169ZwFCxZEOiwAyahevbpTo0YNJ2PGjM7FF19sf3Zvl1xyiZM7d27nxhtv9C2eP/74w/n666+dFStW2J8RWRs2bHBKly5t148KFSo4mzdvdmrWrOnkzJnTyZEjh1OoUCHnp59+Io4YjSNIsRAHcQQ9FrruAgCAdOmqq66y03T37t1rjh49apYuXWqaNm0a6bAAJEMNMFq3bm1HOWj0nH52bzfffLNtsPPqq6/6Fk/+/PnN5Zdfbuvy6WdE1qOPPmqqVatmvv32W9OqVSvTsmVLc95559nmSn/88Ydt3qLyDMQRm3EEKRbiII7Ax+JZChEAAMAj27Ztc7Zv3x66rxE5PXr0cF588cWIxgXgn02bNs05fvx4pMNAwGh09po1a+zPhw8fdjJkyOB88cUXoceXLVvmnH/++cQRo3EEKRbiII6gx8KIPgAAkO7ccsstZvHixfbnPXv2mCZNmpivv/7aPP74475drQXw71SpUsWOckhoxYoVZuXKlRGJCZGnbukFChSwP6tjuG7FixcPPa46V2qmQhyxGUeQYiEO4gh6LCT6AABAuvPDDz/Y6Xby5ptvmosvvtgW2H/ttdfMtGnTIh0egLO47777zPbt2xMtV3MdPYbYVKJECbNt27bQ/eeeey5eZ+Z9+/b5MsWaOIIZR5BiIQ7iCHosJPoAAEC68/fff5u4uDj78yeffGKuu+46+3PlypXN7t27IxwdgLP58ccfzaWXXppoeY0aNexjiE0amb1hw4bQfXVGzp07d+j+xx9/nOR6QxyxEUeQYiEO4gh6LBk0f9ezvw4AAOCB2rVrm4YNG9rixmrA8dVXX9mix/r3v//9r9mxY0ekQwSQjIIFC5oPPvjAFiMPp1G5+k6rWDmQ0JYtW0y2bNniTX8jDuIIYizEQRyRjiWzJ38VAADAQ5oCoQ6ew4YNM506dbJJPnnvvfdCU3oBBJOS83379jVz5841efPmtcv++usv89hjj5lrrrkm0uEhQo4fP25HaKtDpWgdOXHiROjxTJkymSFDhhBHjMYRpFiIgziCHgsj+gAAQLpx5swZm9xTQk8HTDVr1jSjRo0y2bNnt49v3brV5MiRI14dFADBolp8V199tdm/f7+dritqzlG0aFGzcOFCW6QcsWfixIlm3rx55v3337f3Nc2tatWqoe27psH17t3b9OzZkzhiMI4gxUIcxBH4WDzr5wsAAJDGnnjiCSdjxoxO06ZNndatWzvZsmVzbr/99kiHBSCVDh8+7Lz44ovOvffe6zz88MPO9OnTnZMnT0Y6LETQlVde6bz33nuh+7ly5XJ++eWX0P1XXnnFueKKK4gjRuMIUizEQRxBj4VmHAAAIN2YMWOGmTBhglmwYIGZM2eOvVKqTrsa6Qcg/ciZM6e56667zPjx483w4cNNx44dTZYsWSIdFiJo06ZNtoO6S/WrMmb83+mqyjL40ayFOIIZR5BiIQ7iCHos1OgDAADpxrZt20yLFi3idTXLkCGD2bVrlznvvPMiGhuA5Gm6/bXXXmuTefr5bNwu2ogtqtMYXsNq37598R7XBZ3wx4kjtuIIUizEQRxBj4VEHwAASDdOnTplr4qGU+Lg77//jlhMAP6Zmufs2bPH1s/Uz8lR4v706dO+xoZg0MWaH374wVSqVCnJx7/77jtfLugQRzDjCFIsxEEcQY+FqbsAACDdUA+xzp07mxtuuCF0U2ezu+++O94yAMGi0Qtukxz9nNyNJF/s0mjtAQMG2G16QseOHTODBw82LVu2JI4YjSNIsRAHcQQ9FrruAgCAdOP2229P0fOmTp3qeSwAUk/JvGnTppnZs2fbLtkawVeuXDnTtm1bc9ttt9n7iE2//fabqV69usmaNavp3r27ueCCC+zyjRs3mnHjxtkR3WvWrLHdmYkj9uIIUizEQRyBj8WzNh8AAAAA8P+dOXPGadmypZMhQwanevXqzs033+y0a9fOueSSS+wyddJGbNu8ebPTrFkz211d64Ru+lnLwjtWEkdsxhGkWIiDOIIcCyP6AAAAAHhOI2179Ohh5s6daxo2bBjvsU8//dTW7tNIB3XgRWz7448/bNdKqVChgilQoABxEEcgYyEO4ghiLCT6AAAAAHiuadOmplGjRqZPnz5JPj506FDz2WefmQULFvgeGwAA0YJmHAAAAAA8py6DzZs3T/bxa6+91qxdu9bXmAAAiDYk+gAAAAD4Mn3pbIXH9diff/7pa0wAAEQbEn0AAAAAPHf69GmTOXPmZB/PlCmT7UQIAAD+veT3tAAAAACQRlQavHPnziYuLi7Jx0+cOOF7TADwb2l79tdff5k5c+ZEOhQgHhJ9AAAAADzXqVOnf3wOHXcBADg3JPoAAAAAeG7q1KmRDgEAgKhHjT4AAAAAABBYb7/9trn44otN9uzZTcGCBU2TJk3MkSNHzDfffGOuueYaU6hQIZM3b15Tv359s3r16ni/myFDBvPiiy+aVq1amRw5cpgLL7zQLF++3GzatMk0aNDA5MyZ09StW9f88ssvod8ZNGiQqV69uv29UqVK2d+76aabzIEDB5KN8cyZM+bpp582ZcuWtXFWq1bNxg34jUQfAAAAAAAIpN27d5v27dubLl26mPXr15slS5aYG264wdb9PHTokC0LsHTpUvPVV1+ZihUrmhYtWtjl4YYMGWJLA3z77bemcuXK5pZbbjHdunUzffv2NStXrrR/q3v37vF+R4nAN99807z//vtm/vz5Zs2aNebee+9NNk4l+WbMmGEmTpxo1q1bZ3r27GluvfVW89lnn3n23gBJyeBojQYAAAAAAAgYjdCrWbOm2bp1qylduvRZn6tRdfny5TMzZ860I/jcEX39+vWzyT5RQrBOnTrm5ZdftslDmTVrlrn99tvNsWPHQiP6nnzySfPrr7+akiVL2mVK9rVs2dLs3LnTFCtWLF4zDjUTKlCggPnkk0/s33bdeeed5ujRozYewC+M6AMAAIBnypQpY0aNGhXxvwEASJ80BbZx48Z26u6NN95oJk+ebP7880/72G+//Wa6du1qR/Jp6m6ePHnM4cOHzbZt2+L9jUsuuST0c9GiRe2/+nvhy44fP24OHjwYWnb++eeHknyiBJ4SiRs3bkwUo0b/KaGnacS5cuUK3TTCL3xKMOAHmnEAAAAAAIBAypQpk1m4cKH58ssvzccff2zGjh1rHn/8cbNixQpzzz33mP3795vRo0fb0X5xcXE2IXfy5Ml4fyNLliyhnzXCL7llSuT9G0ouyrx58+IlB0UxAX4i0QcAAAAAAAJLibh69erZ24ABA2xS79133zXLli0zEyZMsHX5ZPv27eb3339Pk9fUqMBdu3aZEiVKhKb8ZsyY0VSqVCnRc6tUqWITevodNQQBIompuwAAAPjX1LFQBcx107QpdT7s37+/LWzu0nQm1UHKnTu3nQo1adKk0GONGjVKVAB93759JmvWrGbRokWJXk81mnTCp4LqLtVI0jIVaBf9q/sLFiwwNWrUsN0P9Tp79+41H330ke24qOldKsau2AAAwaWRe0OHDrVNM5RImz17tt1PaFuuKbuvvPKKbdKh53Xo0MFu89NCtmzZbKOPtWvXmi+++MI88MADtvOu6vMlpP3bI488YhtwTJ8+3U7XVW1BjT7UfcBPJPoAAABwTnQSkzlzZvP111/b6VMjR440L730UujxESNGmMsuuyzUsVBTrdwaRypUriLlKmTuevXVV+3UJyXnzoWKqY8bN85O99IoD52gqdafXk/Tq9wpYACA4NKFmc8//9yO2rvgggtsYw3tV6699lrbUEP1+i699FJz22232WRckSJF0uR1K1SoYLv76nWbNm1q6/xp9GBy1OxDF7rUfVdJyObNm9t9TdmyZdMkHiCl6LoLAACAcxrRp5Fy69atC9U46tOnj3nvvffMjz/+aBtpXHXVVXbEhejQU6MhBg8ebO6++25b/FzToiZOnGgTcW7hdZ1cDRw40N7X33jwwQftTSP6dNKkpGH16tVDI/ry589vFi9ebOPRiL6GDRva7ocq4C7PPPOM6du3rx1lUa5cObtMr6+/p06KAACEXyhSN93w0eNAesGIPgAAAJyTK664IpTkExVC//nnn83p06cTdTvU85ToU3LQnRqlURhTpkyx9zXV6YcffjCdO3c+57gSdlnMkSNHKMnnLnPjAAAAiAY04wAAAICnwjsbusm+8M6Gmr6r0Xk7duwwU6dOtVN2VWg9KSqELuGTUv7+++9/fF295j/FAQAAkN4xog8AAADnRAXQw6kzoQqkZ8qUKUW/f/HFF9safpMnT7b189S4IzmFCxe2/+7evTu0jKlVAIC0nrrLvgXpFSP6AAAAcE7UBfGhhx4y3bp1C3UZVKH01NCoPnXfzZkzp7n++uuTfZ66KWqqsGruqVafpt6qMDsAAAAY0QcAAIBz1LFjR3Ps2DFTq1Ytc99995kePXqYu+66K1V/o3379rZzr/5V3b6zUT2/U6dOmZo1a9oGHU8++eQ5/h8AAABEB7ruAgAA4F9Tl1vV1xs1atQ5/R11vy1fvrz55ptvzKWXXppm8QEAAMQSpu4CAAAgYtRIY//+/Xb6rabkkuQDAAD495i6CwAAgIhZtmyZKV68uB3JN3HixEiHAwAAkK4xdRcAAAAAAACIAozoAwAAAAAAAKIAiT4AAAAAAAAgCpDoAwAAAAAAAKIAiT4AAAAAAAAgCpDoAwAAAAAAAKIAiT4AAAAAAAAgCpDoAwAAAAAAAKIAiT4AAAAAAAAgCpDoAwAAAAAAAEz69/8AP1w+qWhbVk4AAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# combined figure that looks at top weights across all three modes for a subset of components\n", "\n", "# USER INPUTS -- edit as needed\n", "max_elements = 10 # maximum number of elements visualized in any one component\n", "viz_components = [1, 2, 3, 4, 5] # list components you want to compare against one another\n", "heuristic = 'max_weight' # pull out the top weights across any component\n", "# heuristic = 'max_variation' # pull out the weights that vary the most across components\n", "\n", "# pull out the top weights\n", "combined_df = pd.DataFrame()\n", "for mode in modes[:3]:\n", " if heuristic == 'max_weight':\n", " # weights sorted by maximum across all components\n", " idx = np.abs(ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate'])).max(dim='component').argsort()\n", " elif heuristic == 'max_variation': \n", " idx = ds[f\"{mode}_weights\"].median(dim=['bootstrap', 'replicate']).std(dim='component').argsort()\n", " df = ds.sel({mode: ds[mode][idx[-max_elements:].data[::-1]]})[f\"{mode}_weights\"].to_series().reset_index()\n", " df = df.rename(columns={mode: 'Label', f\"{mode}_weights\": 'Weights'})\n", " df['mode'] = mode\n", " combined_df = pd.concat([combined_df, df], axis=0)\n", "# pull out just components of interest\n", "combined_df = combined_df[combined_df.component.isin(viz_components)].reset_index(drop=True)\n", "\n", "# plot combined data \n", "fig, axes = plt.subplots(len(viz_components), 3, figsize=(15, len(viz_components)*2), sharex='col', sharey='col')\n", "for i, comp in enumerate(viz_components):\n", " for j, mode in enumerate(modes[:3]):\n", " plot_df = combined_df[combined_df.component.eq(comp) & combined_df['mode'].eq(mode)]\n", " sns.barplot(plot_df, x='Label', y='Weights', errorbar='sd', color=sns.color_palette()[j+1], ax=axes[i][j])\n", " if not i:\n", " axes[i][j].set(title=mode)\n", " if not j:\n", " axes[i][j].set(ylabel=f\"Component {comp}\\n\\nWeights\")\n", " if comp == viz_components[-1]:\n", " axes[i][j].tick_params(axis='x', labelrotation=90); \n", " axes[i][j].set(xlabel=mode);\n" ] }, { "cell_type": "code", "execution_count": null, "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": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 4 }