{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Evaluate Model Performance\n", "\n", "This notebook demonstrates how to evaluate the performance of a sparse tensor decomposition model fit to simulated data by comparing the model components to the ground truth components used to generate the simulation. Model performance is evaluated on the basis of five metrics: \n", "\n", "1. Relative sum of squared errors (SSE)\n", " - Measures how closely the model matches the data\n", "1. Factor match score (FMS)\n", " - Measures how closely two component matrices match one another\n", "1. Precision\n", " - Proportion of test cluster membership that adheres to the ground truth\n", "1. Recall\n", " - Proportion of ground truth membership recapitulated by test clusters\n", "1. F1 score\n", " - Harmonic mean of precision and recall\n", " \n", "SSE and FMS consider the model as a whole, whereas precision, recall, and F1 score deal with clusters derived from the factor matrices of a particular mode. In this case we derive clusters from mode-0, and determine cluster membership using the indices corresponding to non-zero weights. Note that the precision and recall metrics implemented in Barnacle are calculated according to the formula proposed by [Saelens et al. (2018)](https://www.nature.com/articles/s41467-018-03424-4), in order to accommodate overlapping clusters. For more on these metrics and their usage, see the article published alongside the Barnacle library. \n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import scipy\n", "import seaborn as sns\n", "import tensorly as tl\n", "import tlviz\n", "from barnacle import (\n", " SparseCP, \n", " visualize_3d_tensor, \n", " simulated_sparse_tensor, \n", " pairs_precision_recall\n", ")\n", "\n", "# helper function to calculate f1 score from composite precision & recall scores\n", "def composite_f1(precision, recall):\n", " '''\n", " Calculates F1 score from precision and recall.'''\n", " numerator = precision + recall\n", " if numerator == 0:\n", " return 0\n", " else:\n", " return (2 * precision * recall) / numerator\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "axis0=%{x}
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# generate simulated data\n", "\n", "true_rank = 5\n", "true_shape = [20, 15, 10]\n", "true_densities = [.2, .4, .6]\n", "\n", "# re-seed simulated data until all factor matrices are full rank\n", "full_rank = False\n", "while not full_rank:\n", " # generate simulated tensor\n", " sim_tensor = simulated_sparse_tensor(\n", " shape=true_shape, \n", " rank=true_rank, \n", " densities=true_densities, \n", " factor_dist_list=[\n", " scipy.stats.uniform(loc=-1, scale=2), \n", " scipy.stats.uniform(), \n", " scipy.stats.uniform()\n", " ], \n", " random_state=9481\n", " )\n", " # check that all factors are full rank\n", " full_rank = np.all([np.linalg.matrix_rank(factor) == true_rank for factor in sim_tensor.factors])\n", "\n", "# visualize noiseless simulated data tensor\n", "fig = visualize_3d_tensor(\n", " sim_tensor.to_tensor(noise_level=0),\n", " shell=False, \n", " midpoint=0, \n", " show_colorbar=True,\n", " label_axes=True, \n", " range_color=[-1, 1], \n", " opacity=1, \n", ")\n", "fig.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'll fit a series of models to the simulated dataset, spanning a range of different numbers of components and sparsity coefficients. Then for each model, we evaluate it's performance in comparison to the simulated dataset. Note that the sum of squared errors (SSE) and factor match score (FMS) used in this evaluation are different than the SSE and FMS scores used in the [previous example on cross-validation](https://barnacle-py.readthedocs.io/en/latest/notebooks/cross-validation.html). In the previous example, cross-validated SSE was calculated by comparing the model to held out replicate data, and cross-validated FMS was calculated by comparing two models fit to different replicate datasets. \n", "\n", "In this case, we are evaluating all metrics in comparison to the simulation (a noiseless version of the simulated data tensor in the case of SSE, and the factors used to generate the simulation in the case of FMS, precision, recall, and F1). This type of experiment is only possible with simulated data, and allows us to ground-truth the effect of parameters on these different aspects of model performance." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fitting models with rank=1 and lambda=0.2\n", "Fitting models with rank=2 and lambda=0.2\n", "Fitting models with rank=3 and lambda=0.2\n", "Fitting models with rank=4 and lambda=0.2\n", "Fitting models with rank=5 and lambda=0.2\n", "Fitting models with rank=6 and lambda=0.2\n", "Fitting models with rank=7 and lambda=0.2\n", "Fitting models with rank=8 and lambda=0.2\n", "Fitting models with rank=5 and lambda=0.01\n", "Fitting models with rank=5 and lambda=0.02\n", "Fitting models with rank=5 and lambda=0.1\n", "Fitting models with rank=5 and lambda=0.4\n", "Fitting models with rank=5 and lambda=1.0\n", "Fitting models with rank=5 and lambda=2.0\n" ] }, { "data": { "text/html": [ "
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RankSparsity CoefficientReplicateSSEFMSPrecisionRecallF1
010.200.3844720.8701120.4393940.8529410.580000
110.210.3975290.9108330.4393940.8529410.580000
210.220.3840200.8488420.4393940.8529410.580000
310.230.3908810.8683230.4363640.7058820.539326
410.240.4003580.8693430.4363640.7058820.539326
...........................
6552.000.5064890.1358751.0000000.0294120.057143
6652.010.5096460.1471981.0000000.0294120.057143
6752.020.4854760.1603291.0000000.0294120.057143
6852.030.5122470.1363091.0000000.0294120.057143
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70 rows × 8 columns

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" ], "text/plain": [ " Rank Sparsity Coefficient Replicate SSE FMS Precision \\\n", "0 1 0.2 0 0.384472 0.870112 0.439394 \n", "1 1 0.2 1 0.397529 0.910833 0.439394 \n", "2 1 0.2 2 0.384020 0.848842 0.439394 \n", "3 1 0.2 3 0.390881 0.868323 0.436364 \n", "4 1 0.2 4 0.400358 0.869343 0.436364 \n", ".. ... ... ... ... ... ... \n", "65 5 2.0 0 0.506489 0.135875 1.000000 \n", "66 5 2.0 1 0.509646 0.147198 1.000000 \n", "67 5 2.0 2 0.485476 0.160329 1.000000 \n", "68 5 2.0 3 0.512247 0.136309 1.000000 \n", "69 5 2.0 4 0.535860 0.139017 1.000000 \n", "\n", " Recall F1 \n", "0 0.852941 0.580000 \n", "1 0.852941 0.580000 \n", "2 0.852941 0.580000 \n", "3 0.705882 0.539326 \n", "4 0.705882 0.539326 \n", ".. ... ... \n", "65 0.029412 0.057143 \n", "66 0.029412 0.057143 \n", "67 0.029412 0.057143 \n", "68 0.029412 0.057143 \n", "69 0.029412 0.057143 \n", "\n", "[70 rows x 8 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# evaluate performance metrics on models fit with different parameters\n", "# NOTE: this block of code takes a minute or two to run\n", "\n", "# set parameters to explore\n", "ranks = [1, 2, 3, 4, 5, 6, 7, 8]\n", "lambdas = [0.01, 0.02, 0.1, 0.4, 1., 2.]\n", "params = list(zip(ranks + [5 for l in lambdas], [0.2 for r in ranks] + lambdas))\n", "\n", "# evaluate metrics for each set of parameters\n", "results = []\n", "for rank, lamb in params:\n", " print(f'Fitting models with rank={rank} and lambda={lamb}')\n", " # instantiate sparse cp model\n", " model = SparseCP(\n", " rank=rank, \n", " lambdas=[lamb, 0, 0],\n", " nonneg_modes=[1, 2], \n", " tol=1e-5, \n", " random_state=21158, \n", " n_initializations=5\n", " )\n", " # fit model to 10 replicates of independent noisy tensors\n", " for replicate in range(5):\n", " # create data tensor with 2:1 signal:noise ratio\n", " noisy_sim_tensor = sim_tensor.to_tensor(noise_level=.5, sparse_noise=True, random_state=replicate)\n", " # fit model to noisy simulated data tensor\n", " cp = model.fit_transform(noisy_sim_tensor, verbose=0)\n", " # calculate SSE in comparison to noiseless simulated data tensor\n", " sse = tlviz.model_evaluation.relative_sse(cp, sim_tensor.to_tensor(noise_level=0))\n", " # calculate FMS in comparison to factor matrices used to generate simulation\n", " fms = tlviz.factor_tools.factor_match_score(cp, sim_tensor)\n", " # extract clusters from model and simulation\n", " model_clusters = cp.get_clusters(mode=0, boolean=True)\n", " sim_clusters = sim_tensor.get_clusters(mode=0, boolean=True)\n", " # evaluate precision, recall, and f1 score\n", " precision, recall = pairs_precision_recall(sim_clusters, model_clusters)\n", " f1 = composite_f1(precision, recall)\n", " results.append({\n", " 'Rank': rank, \n", " 'Sparsity Coefficient': lamb, \n", " 'Replicate': replicate, \n", " 'SSE': sse, \n", " 'FMS': fms, \n", " 'Precision': precision, \n", " 'Recall': recall, \n", " 'F1': f1\n", " })\n", "# compile results into DataFrame\n", "results_df = pd.DataFrame(results)\n", "results_df\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# look at effect of rank on model performance\n", "\n", "# arrange data in tidy format for plotting\n", "rank_plot_df = results_df[results_df['Sparsity Coefficient'] == 0.2].melt(\n", " id_vars=['Rank'], \n", " value_vars=['SSE', 'FMS', 'Precision', 'Recall', 'F1'], \n", " var_name='Metric', \n", " value_name='Score'\n", ")\n", "\n", "# visualize cross-validation data\n", "ax = sns.lineplot(\n", " rank_plot_df, \n", " x='Rank', \n", " y='Score',\n", " hue='Metric', \n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is a minimum in SSE that corresponds to the true number of components used to generate the simulation (rank=5). Recall and the F1 score peak at 5 components as well. FMS is mostly flat up to 5 components, after which it starts to drop off, and precision shows a steady increase with the number of components." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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qIMWN5EhnambQjLo+xWI1nmTC6iMA9rX6TIigQ7D2wtNPk7nrLpwdOwBQTJPYlVeSfOc70eeRSXa44ZdK+Jk05nHHYS5btmjuRM/3SNtpRkojjJRGKLklwkaYuBHfryykfVO937PqPfz+6t+ftu6yWyZrZzmx9US6ol37fS0Syf4gxU0dpLiRHM3MtPoEf2dYfVwX4U6x+kwRPQfD6iN8n9Jvf0v6rruoTLRg0XVil1xC8t3vxug6Mr9I/WIRP5vBXLUKc+nS/RI4RadI2k6zN7+XbCVI54+ZMSJGZI4jG5t7tlTvCSbibJYnlrOyaeVhH/slOfqR4qYOUtxIjmVqWn0qlaCWTrWa87jLS/hBNeepVp+pImgx1iME5ZdfJn3XXdjr1wcbVZXoBReQfO97Mfv6FuU8B5OgLlEuEDh9ffMSBb7wydgZhkvDDBeHKbklQnqIuBlftAJ3+6Z6f+bMz3B6x+kzxg0WBmkNtbKmdc2MdgwSyaFAips6SHEjkcxONb6nUtvqEzQwdaZYfUDRjUWx+pQ3bCBz112UXnyxui1y9tkkb7gBa+XKxbrEg4JXKCAKeczVq7GWLJlzfNktkyqnGCwOkiqnEAjiZpywHl5Ui8m+qd5/fvaf05/snzEubadRhMIp7acQN+OLdn6JZH+Q4qYOUtxIJAtD+P70gniOMz3WZ6rVZzzDS9ENtObmeWV12Vu2kLnrLorPPFNtUBo+/XSS730voTVrDsi1HQi8fB5RLBI6fjVGb++M/b7wydpZRkojDBWHKDpFLMMiYSYOSBuCeqneU5mIs1nTuobOaOeir0MiWShS3NRBihuJ5MAwvbt3YPVxh4ZwR0fRWtvmXcCvsnMnmZ//nMKTT1YrJ1snnkjTDTcQOu20IyIGxMvlEOUSoeOPx+jpASaL4Q0UBkjbaXzfJ2bFiOgHrtHpozse5TuvfmfWVO/qen2PwcIgK5IrWNG04oh4jiXHDlLc1EGKG4nk4OHbNpUtW6js2oWaSC6oro0zOEjm7rvJP/roeLVnMFeuJHnDDUTe9rbDJt19NrxsFmGXcVYuIZ3UGCwMUnSKGJpBwkwc0HiWfVO9L+y9kE+c9olZLUOD+UHaIm2c2HoihirjbCSHF1Lc1EGKG4nk4CI8j8quXVS2bgVVC9xUC7AIuKOjZO+5h9xDDwXVgwGjr4/ke99L9PzzD8uChq7vkK1kGR3eQb6QwV7RRaR7CVEjesCtIq7v8u1Xvs3jux4Haqd6TyVVTqErOie3nUzMjB3QtUkkC0GKmzpIcSORHBrc4WHKmzcjCgW09o4FixEvkyF7771k778fUSwCoHd1kXz3u4ldfPFh0PRSUHALZMoZxsopim4BXdWJlgSGUGFVP7Q1H9AVFJ0iX3v+a7w28tqsqd5TKbkl8pU8a1rX0BHpOKBrk0gWihQ3dZDiZhEQYrzR4JQO0tVfg0qNbXW2S5/+MYWXz2Nvfgt3aAittRXVshY+V6FA7v77yf7yl/i5HABaayvJd76T2BVX7NfcC8H1XXKVLGPlMbKVLK7vEtLDhPUw6sT7PJMLummsWgatB0bgNJrqPXXdw4VhVjSvoD/RL+NsJIctUtzUQYqbKfje+M0FMf7X96c8Ht/mueBVwLPH/zqBsBkP8mTaZ+EcwmVWwTP1sTJ5X1FmHqNM2bfv2IbH1TlGaWAdcwq3eYq8AzbHlO2zfWkteI4G1qFqoE8XGaJSwd66DWfnDpRoDC2+f6nGfrlM7qGHyP7nf+KNjQWnTSRIXH89iauvRo3sf9G7uSi4ebZntlNwCmiqRsSIYs4Ws5LKgqrA6n5oXtx2Btuz2/m7Z/6OlJ2iyWri82d/vmaq9wRCCAYLg3RGOzm+5XgZZyM5rJHipg5Hnbjx/SnCZEKo+Ps89qYIlCk33xsXKN7kfeFSU3SoGigqKBqo43+nNeib8jaa7S1V3T51v6h5d/b5asw92/5Z39pijuNmWUfN4+b4lasoU8Yr+05e78DJsQueg+lzTJt7jvtKrW2NCBv22a5BKA6RVjBjYMXACCN8n8qePVS2bAFfoLW27rfFQDgO+UcfJXP33bhDQwCo0Sjxa68lcd11+y2i6rErt4u9hT00h1omrTT1SGVA1+C45YsmcF4efplvPP8NSm6JJbElfP7sz9Meaa97zFh5DFM1Obnt5JrZUxLJ4YQUN3U4LMXNhJtnmgVlXHDsK1w8Z9yC4oBrT1pYhD85Xngzv/8UJgWJqo2LlKmPpwgWaZY+OmlIBC6ieITgPeuUwA0CgDHCgcCJtIMVw81XsLftxstl0ds7FqXysfA8Ck8+SebnP8fZtQsAJRQifuWVJN75TvTmxXUHOX6FN8beQEElYoQbP3AsDYYexOA07d9n0bqd6/jOK9/BEx5rWtfwZ2/7sznFStEpUnSKnNR2Us16NxLJ4YYUN3U44OLGrYyLkamunX2Ei+eMjxsXKBPiRfhTxIpX48tDzBQm+1pSJvZLgSI53BA+OGVwS8FfACOE72qUh4q4qQJaRw9qLLmPVXChp/MpPvssmTvvDDK1AAyD+GWXkXjXuzA6FidwdrQ8wpb0FlpCLfO3Po2mwDTh+H5IzN+yJITgjk13cOebdwJBqvcfn/rHc6aXu77LcHGYlU0r67qtJJLDCSlu6nBAxU05AwOvBB/cVUuKP3OcotYQJDUsKovwAd8wE188TnHKrQSVfR47xcltwp9co6IyPWal1l913JuhzjJuylzVeBl15lyKMj7HLPtnrGOONdbaP+u17LvG2c7VyBpneT4WtMaJueqscWoc0uGAEOAG7zlRKmDvGcEZSqNE42jtvYEbywiBEdmv/wUhBKUXXyRz113Yb7wRbNQ0om9/O03veU/N6sHzmJ0305vJVbI0WU0Lm2IkBWErsOAkGk/BnpHqfdx7+P3jZ0/1rq5YCAaLg3RFuji+5fgDUg1ZIjkQSHFThwMqbopjsOPXEG4BVZ8ULAcCIYK4mQnhUZkiPqrbSo2JlYn7kmODgynm4t3QfgJ0nADtJ0K4adZlCd/HHRigvGUrolxEb4qh6FYQkBxKBmLHjASuLWX+/1dCCOz160nfeSflV16prjty7rkk3/terP75WzAKbp5NY5uIGJGFB+MKAaNpiIQCgROfO/al6BT5+vNf59WRV1EVlT86+Y+4fNnlDZ1utDRKSAtxctvJi9JhXCI5WEhxU4eDIm7iPbV/IftufUvIVLFRS6zsK05qWYX2F0UNfikbkckvkonHxvhjMwJ6eFy4ieDDWYgp9yfWNX5fAPgzxzFlrPD3mWP8/rTH43MJf585RO1zMcvYec21zxrrXe+s55rH9c6Yq8a8RzLxrkDkTIidtlXBe2oKbiaHvX03XjaHnoii4AYWHuEHPxqMEFgJsOKT7895Wh/szZtJ33knpeeeq24Lr11L8oYbCB1/fMPzDOT3sjO/k9Zw67zOPwMhAgtONAKrl0NsdoEzWhrlK89+hR25HViaxWfO/AxndJzR0GkKToGyW2ZN6xoZZyM54pDipg4HTNyMbIbHvgLp7cEH1QzLSDGItTkQTBMg4frixJxFrEw81szDy3Uhmcm8hdIChGFNcdmomBufy3eD/4ehN2B4A6R3zLwWRYXmfmg/HjpODKw8Lf34FQ97+26coVG0RBQ1HArGe+NCxy0H2X2qBnooEDqhRCC6jQg02NKgsn170L/q17+uljYInXxy0KTzlFPqunhc4fLG6BsI/MXJNJoQOLFIkCYenWlV2Z7dzlee/Qpj5bGGUr2nrXc8zmZ182qWJpbu/3olkoOMFDd1OGDiZudz8K9XNDZWM+uLjaowaUCsGKH9ikeQSA4alTwMb5wUO8NvQGFk5jjNgrZViLbjcfVu7FICEelAr5VR5HtBrJhnB/dRxsVOLHBlTfy/aPWbdjp79wb9qx57bLJ/1apVNN1wA+Ezz6wpctJ2mjdTb9Icam4s/bsRhICRsSD25rh+iE5atRaS6j05bVDPpjvazfEtx6MdKHe5RHIAkeKmDgdM3OSH4NlvB3/jXWBGZxcrMoBPIgkoDAciZ0LwDG0EpzBjmNCieOE+RMsq/OQK/Hg/mLOIHdcez0J0ADUQO2ZkPG4nGjzWQzWX446MkPnFL8g/8shk/6ply2h673uJnHvutJYR2zJbGSmP0hJa3NRyfD8QOE2JoA5OJLygVO+pjJRGiOgRTm47mbA+j3R1ieQwQoqbOhzSmBuJRFIf4UNmZyByhjcEomd087hQmY4fasOP9yMS/fjxfvzYspmixfcDq45rT7qFdSv4oRFqmvzRoVswpTChl06T+eUvyd1/P6IcpK3rPT1B/6qLLsLG4Y3URizNwprDKrQgfB+GRxFNSe7QX+LOrb8AGk/1nkq+ksf2bE5uO5mWUMvir1UiOUhIcVOHY0rc1I3NWEig7z7HTFxjzXfQPhtnfT5qba+xbdans9bYBuecdcp5HN/w69zoOmcb2+C4eZ+r1uGNXv9sz8nU++p4HNd+uE69Coxuwd/7GmL7izD2JlplaMYwgYKI9gZCJ9GPH1+BiPZMt5QKMS507MnCgroZxOqEmsYtruHxIGcFL58n91//Rfbee/HzeQC0tjbUd1zG7tN7aEt2L/y65sD1Knx758943F0PwLuPezfvO/5986ql43gOo6VRVjevpi/Rd6CWKpEcFKS4qcNBEzfAfgmLugGfDa5noobK1PTdmjVfpqb7AsqUNPZphQHVKSnuKjO/3GosbM5WDFMf7ztWzDKu0XOJGttnOV7UOFfdcyzyWme7/n2Pb0RIznaO2Wik0vBCzj/xvvVs8EXQT0kbT+3WzAUFrwvPpzIwRGXrW2j2bnR/EC23FTW7FaWSmjleNfFjSyetO4kViFD7dGHu2eNByuNiRzMCsRNuAiMKZhjfgdxDDwf9q9JpAPxEFK6+GC4+N6hTs4gUvTJfH/gRr5beQkXho63Xc8XaG2AezUB94TNYGKQ31svq5tUyzkZyxCPFTR0OuLjZ80KQJTVR92NewkKhdmG/KWJD1aYcp0w5bupjdZa5axwzY9thYHGSNEatf915CZVaY+cjlBoYK8YDft1yUMbAzkClMG49qQRjVW3cemIF4qcBl4s7lqa8bReiWEZrTQaxMHYKNbsVNTd+y25F8WbWbxJ6tGrZ8cdFTzV+RxCsayJuBx9Us1prx1dCjDz+BLlfPoCWygaHRMKIKy6AKy+EyP7Hs4y6Gb6y53Z2VAaxFJPPdPw+ZxTbob0ZVi4HqzE32HBxmLgR56S2kwjNEmMkkRxJSHFThwMqbnwPSuO/HmsJi7qCRAoLyTGC5062YHBLYOfBzo73oBpvRwKg6eNixwzEzz6B+F6hiL19N+5oCq05iWruI4qEj1IanBQ82S0o+Z0owp2xJN9qxU/0IyYEz9T4HXe8Tcp4rZ0dlTSDlTytb2RRHn0BZSjoRC56OhFf/G8QXriQ2G7v5St7fsCYl6VJi/H57g/TH+oFzwuCjNvb4LhlsO+17kO+ksfxHU5qPYnmxQ54lkgOEVLc1OGwbJwpkUgCt9BU0VPOBZaeavaTF/wA0IzAkqJbCF/F3jWAs2cQJRpGq1EbZhq+g5LfVbXsqLktKMUBlH2sUDPjd/oR0V4qAt7IvoXmeYQhSBvfsAflvudRciXEyasRn/7IuNt2frxS3MzX9/6IkrDpNdr5Qs8f0m5MESbuuMDpaoeVS8GoLXAqXoWx0hjHtxzPkviSea9DIjlckeKmDlLcSCRHEBP9p9zyeO+zUtDDrZKrBgYL16MymqayNw2KjtbSgqKbjceQu0XU3HbU7BbU3DaU3BZUu1b8jkEl2suw2YpIrKAUXYJjtQACtu1G+fZ9KI6HuOwcxAffO68Y9nXZ5/nO0N14+KwJ9/O5rv+HmFbDxeV6MDoGXR2wom+GwJmIs1kSX8Lq5tWosgaW5ChCips6SHEjkRwF+P50K0+liDu4C/vNzXjZLHpTOIjDmbD0aCaoRuDqagQ7hZrbNi54Zo/fcbUwpegSStFexva2In78dLC8910Bl1865/mEENwx9ivuTP0KgAtip/GJzvdiKHWOc92gm3hXR2DB0SfHDheHSZgJTmo7CUtrLPhYCIHwBb4v8L3p9ycee56P5/p4jo/nCgxLo7UniqpJ8SQ5eEhxUwcpbiSSoxc/m6X85nrc3bvQkhFUxQsqI7uV8QBmLxioauOBwnrwdy43kvAp5XYwMvICzaUhosU9hIp7USfmA1w9wubd5yMeXY/QVMTHroPTTg+qJdfAFS7fGfoFj+VeAODdzRfz+y1XNGZtcdyg2WZvB/QvBV0jW8ni+z4ntZxE3EgE4sQXCG+KWPF9hC9wXYHvTAgWD1+A7wUZf74n8IUIDE8ChDKeRKkqqKqCoio4tkfbkhjJdtl4U3LwmM/3tyyVK5FIjhrURILwqWdiJ9twtm9HhMJoXSuCAn7VYn422EVwxkWPmw9S1hUlCFqesPRoxmSQv6IypscYaDoRp+PcYJPvYpUGCRd20TL8HKHSAMv7XmDrKcejvLod/u1BRFSDpcdBtHWagCr6Zb6+dyLVW+Wj7ddzRfLsGdczUaFgojrE5F8DEWpCbB7Dz2pU2pvJ2CX6In3kcz5ZP43wBWJcrOxLkM8wIVaC+4apooyLF1Wt71NTVYX0UIlQ1MCKLLAbukRyAJGWG4lEctQhhMAdGKC8eTPCcdHb2lBmWGfEZLCy54ynq+fHm9xWpjW6dRWVN0qDCE0fb3sw/ctfc/Ks2PAvmJUUebOHHY+0oeweQXQ2If7ocmhuh3gXQgsz4mT4/w/8gB3OAJZi8qmWD3CKeXxVvPge+L6C700RM0KZ3qcUEazB8xDZHPmkRvPy4+lr6kPTJkQKVUvLfAr/NUohbRNJmLQvjUv3lOSgIC03EonkmEZRFIzubpRQCPutLbiDA+ht7SjTAnCV2n2mJgoPTggft0wuv5eSV6EZFbz0uLZQgjgeVcfVIrzV/xFWbb6VWGUPnRfFGPjPCOpgGvenL1B452X4gyPstBy+5f+MNFkSxLlJv5EluV5y09Y+YVkRwSkUQBXVcleTOkUAKhnVo6Xk0uuphCJ6DRF3YAjHDfJpGytq0NQh3VOSwwspbiQSyVGL3tyMetIa7Le24Ozdg5ZsQo3M8UWsqEGF4mqDSUEKF1VXUfVoYNHxK+DY41Yeh1IGivlmSs0f57SRf6JVbKJw2Vry91UwNm/FfOJlnr94Cd/xHqCsOHQr7fxJ7CO0ac0oysKN5yW3hG5ZtCW6EANDOKqBsaT3gFhq9kXVVKywTmY4cE+FotI9JTl8kLZEiURyVKOGw4ROOB5r5XH4+Rxuamaadz1KbolMJUvEjIMRglAcIq2Q7IG247CjqylqK9DDFpVIC5u7/h8ECksjLxC6NOg9FXnut7y+4T8pKw6r/U4+719Hu6fPJ1t8Bo7vUvEcOqOdRCJJ1EQSZ88e3D17OFjRBmZYx3d9MkNFPM8/KOeUSBpBihuJRHLUo+g6Zv9yQiedFGT7DA4iPG/uA4GsncXxKzW7f7sVKOQMVNNESzQBglTkeLa1vweA/tZn2HBuEoCP/ZfHe3b28hn9BqLokNsL+aHJiszzwBeCvJOjLdxK0gzmV00TNR6nsms37p69DbcW21/CCZN8yiY3Wj44J5RIGkCKG4lEckygKApGZyfhU05Bb0riDg3iVyp1j/GEy2h5tGZvJt+DQkbFcxWMEEGTzVATVEoMJs9je9OlfKmthf/fJXmePkFB9+F9dw1hpgugR4JYn1IKMnuCflvzIFfJkjAStIbamBrcrFoWajyOs3sX7sDBETiqqmBFdDJDJcoFZ+4DJJKDgBQ3EonkmEJLJAidfDLmkiV4o6N4hdmFRa6Sp+AUCevT43SEgGJWwS4qaKpgy4sm218zSWfb8JQwJTfDnzdX+EU8hgLEzssjOptRiyWiP70b7EoQjByKB5lZ2b1QHA0U0xwU3AKGatAeba/Z6Vu1LJRoDGfXLtzBgYMicMywju8LUoPSPSU5PJDiRiKRHHOoloW1ejXW6lWIUhF3bKxmnErGTqOgoO1TWM8uKJRyKmZIsGO9SWqvzshOnbdeivLSb1ezbkMSde9yWssd/F3a4PdLGZafvxMRC6MNjxK5+76gyjIKmNGgpk5+BHIDQdXlWaj4Dq7n0RHtIKzNHhithkIo4QjOzl24Q4MHReCE4wbFTEW6pySHBTJbSiKRHJMomoa1bBlaJEJ582a8wQG09o6gbQNQdsuk7TQRY3qPJ8cO3FG6IUgPaKQHdFAEbUs8UiMCr2TQkTmOjsxxsA32hMus059glf4YXReOMvCwgfHmFkKPPkn58ouCSTUzaNVQKUCuDOFWCCWn5n3jCZ+iU6A93F6Ns6mHGg7jC4GzcycoKkZH+6I9dzXPpypYEY3MkMyekhx6pLiRSCTHNHp7O+FwGHvzW7iDg2itraiWRd7JYXs2MWOyfYLnQiGtIgR4rsKO9UGQcc8qh9SyDfxr7t8JlZo4OXMWZ46djZ1NUC6FeJ0reZ0rMZUCHRdsJP7Gq7T+dj1GWyvOaSeNz66CGQ+KCeYHgyahkZagAzqQr+SImzPjbOqhRiL4gLN9O4oSXOuBxAzpFOwKqYEiHcvjaLK4n+QQIcWNRCI55tFiMcJrTsQOh3F27sCPRhl1RjE0s1ozRvhQzKg4ZQUzInjzGQvfVYg2e2zpfYZ/y9+Fp/gsTUT43e61RMt53Mx2ssV2MmMxsqkQFTfKLmUtnLgWhE9i93biqkKiXyMcrQSGGj0UWHLsbCB0oq0UFA1Ts+iMdNSMs6nHhMCp7NgBioLe1rb4T+AUwnGDQtomN6LT1Bk9oOeSSGZDihuJRCIBFNPEWnUcSjRC6o1XKKb3EOvsre4v5RXKBQUzLBjaqpNPaaiaQD1pC7eV7wDgbOM0boz+btDVO2ShO0VajCFa2otBG4WREZRdO9lhr2XEXUE20U82A7tfAsN0SbYUSDYXiTeV0KwEuCUq6Z24RoQlbWuwtJlZW42gRiL4vk9l+7jAaW1djKes9rlUhVBkorifSSgm3VOSg48UNxKJRDKOoqpYS5aQrwzhvb4DbTgNrc3YFZ1iRsUwBeW8wp5NwRd235oKP1UfBQ/OMk7lj6K/P9nVW1Uh3By4lzwHRTNQ2ttoCe3ivME/I2u38dxrVzFiHc9Yywk4FZORgSQjA0kUxSfeVCbenEeLD9KjeSQKI0HgsbWwnnhqLIafz1PZvh0UFb2leZGetZkYIZ1K2SY1WKQjFEfTpXtKcnCR4kYikUimYHs2wyEb86QTYXcad88YRb8ZRVNRVNj6soUQCk2dLqJ7hJdy6wG4QlyOV1FRzClxwGYEIs1BJpSmAwpj8dPZ5mVZPnIPF53wYzY/shRvvc/ImosYOvlyMqkoFdsgm4qQTUWADsaiHp3NRbpa9tDcXUCNtwcdzOeJGovh53LjAidoT3GgiCRM8mmb7IhOc5d0T0kOLlLcSCQSyRRS5RRFt0hnohPfSlLIhXB3pLCSFXZtSVLOq+iWYNkpFX5eeRqB4HjlOFY1t2MXwS4qmCFBNTQmlAR7vNu4EXzJDzRdhOWk6OYJll6wl+2/aqfztV/RFM9SuuwiyiWD4RGTQipOKR8hX9DIF+K8tSuO8bpHe9sInUvCdCyJY1nzs4qo8TheNktl23YURUFralrcJ3AcZdw9lR0pEYoZhGMzKzxLJAcKKW4kEolkHCEEQ8Uh9HGrSCkDdrSV0GqT3IYUQ9sCd9TyU2xcw+aJwnMAXBk7n3BCYEUExZyKXVBQVYFugaLqQS+q3B4QHiiB6tnedj2ml6GVV+g6J8vgr2NYT/8Wr62Vyimrae7JcPJKsPAYHtEZHNEZGtGpOBp7BjX2DHrwfIrmVp3ObpPOHoNEUmuoaaaWSFQFjtmvoCXnTi1fCEZIp2LbpAeKmMt16Z6SHDSkuJFIJJJxck6OtJ0mYSawMz7FUQ8rpuF5SbZtDirhtXcWSLb6PGq/QIky7Uor5zSvQlGCkJhYs48ZUihmFOzxAGTVjIGVhFI6qEqMAorK5o4PYLh5WpZuwc6YpF83Cd/3MNmERetxJxI3gkJ9vd0uvd0uQkAqozE4rDM4rJLNG6RGPVKjJd54rUQorNLZbdDZY9DWYaDrswsdLZHAy2SobNuG2d+PllhYLM9cROJB76nscInmbumekhwcpLiRSCSScVKlFI7noNg6hSEH3VRQdNj+qwJOCaykwpLTFfxMlkfUpwC4Kn4ehjlpkVAUsCIC3RQUcwp2Xg2sOKFmFKcIrh2kewNCNdjYfSMn7fomXScPYee6Ke3w6Pj5Q0RuWg3W9PUpCrQ0ebQ0eZy4CkrFAoN7PQbTUUZSFuWSz/YtNtu32KgatLUHQqez2yASnZlCriWTeOk0le3bMZcvR4vHF/05VVSFUMwgM+Geikv3lOTAI22EEolEAji+w0BxgBBhCoMOwhPoYZWxjRXSbzmgQv+VcdTlPaxvSTEoRgljcXnL2przaTrEmgTxVh9FA9u28K2WoJcUk/2XPC3CGz0fx9ETLD17AL1FQS2WqPz7DxG2XXfN4YjK8pUG55yS5ppzdnHOGWWWrzAIR1R8D4YGHF59ocjD92Z49IEM618pMjrs4PuT/Ri0piaEXaGybRt+Lr8oz+W+GJYGYrz3lCN7T0kOPFLcSCQSCZCxM+TtAko6hFMUmHEVO+ux44mgsWbP28JEO3TQVB6q/AaAi61TiaQK432iZjJhxUm0+YQSPg5JKjQh7OkiomI080rXjfiGyfIL9qKGVfyBAco//SlilrmnYUbQIlE6owOcumwPV1wuuOTqBCeeEqalTUdRIJfx2PxGmacezfHAPWme/02eXdttKraP1tyMX7axt23Dzx8YgROOm5SyFbIjpQMyv0QyFemWkkgkEmC4OIyTBi0bCBsEbHukgO9AtEuna23gStpT3M36wqsoKFx72g0wUIKhUWhtAqN2wboJK45pQXGsCXu0gqk4qGYw3sMnrTezrfdjrNx1K0svGGTbox14G9ZTeehBrKuvmfsCNB3CLVDJoaS2k4i1kzi+g1UnhqnYPkODDoN7HIYGHJyKYPeOCrt3VECBlladju4wbdESSbYSWrECNbq48THSPSU5mBxyy823vvUtli9fTigU4pxzzuHZZ5+tO/4b3/gGxx9/POFwmL6+Pj772c9SLssutBKJZOEUnAIDIyNo2TBGWEHVFAZfKpPf66Ia0H95FEUNgnMf3vsgAGs71tLZsRyOXwm9nTCWAded9RxVK06XQbg1glNyqdgKvhDk3SJNRhyj+SzG+v6IcJtDz1ljADiPPYbz4guNXYgCWHGwIpAfgNQ2qOQwLZUlSy3OPDfGNe9s4oLL4qw6IUQ8qYGAsRGXN14t8eRv4JGHbX57zyZ2rx9adBeSdE9JDhaH1HLzk5/8hM997nPceuutnHPOOXzjG9/g6quvZuPGjXR0dMwY/6Mf/YgvfOELfO973+P8889n06ZN3HjjjSiKwte+9rVDcAUSieRoYCg9QnavTbMVRbNUisMue54N3Cd9F0axkkEwbraU55nckwBcu+La4GDLhP6l4PkwOAIdrdO6ee+LpkO0K4FBhmKmSKpgELFCtIeaURWFYvMFaM4YTdyBnTEY3RDDvusu1NZWtKXLGrsgzQysOOUsjG2DWAdE2kDVUFSF1jaD1jaDE0+FYsFjaK/D4F6H4SGHchm2b/PYvm0Hmr6TjmUJuo9L0r0ySSRpzXnquQgnguypzEiJFpk9JTlAKEIIMfewA8M555zDWWedxTe/+U0AfN+nr6+PP/mTP+ELX/jCjPGf+tSn2LBhA4888kh125/92Z/xzDPP8OSTTzZ0zmw2SzKZJJPJkDhAqY8SieTIoVJxePqVF8hnbFra4ggPNvwsQznl09RvsOKaGIqiIITg3h338ouxn9AX7+OrF311ek2ZYgk2bIaKC80NfLaUc+QHN5GvxGhWlhIzQoQsEegiIWje8wOiI79i11Ot5HdZKNEY4f/231DnW1XYtaGSh1AzxLqCqsmzDXUFo0MOA3sdhnaXKZWni7Rke5ju45Icd2bHfrmVHNvDsT06liWIJKR7StIY8/n+PmRuqUqlwvPPP88VV1wxuRhV5YorruDpp5+uecz555/P888/X3Vdbdmyhfvuu493vOMds57Htm2y2ey0m0QikUBQtG/X7iFSYwWSzREURWH300XKKR89orDskmhVwJTzLk/kgh9W1/ZfO7NYXiQMy5aA50GpfpYTgGuEscNhVkRdlrUb6JqgUFQDz5aikOr5A8rJM+g9Zwyr2UMU8pT/7QdzZlDNQLcg1BRYcdJboTgatDivNVRX6OwxOe3MKJdf18Tbz/E5YY1Ja08EFMgMl3jj6QEe/eHG/XIrGVZgCUsPFnEdb8HzSCSzccjEzcjICJ7n0dnZOW17Z2cnAwMDNY/54Ac/yF//9V9z4YUXYhgGK1eu5JJLLuGLX/zirOe55ZZbSCaT1VtfX9+iXodEIjlyyads9uweQYuArutkdzoMvRqIh+WXRtHDwUek5wheyb3ImDNC3IhzYe+FtSdsbYIlXZDNBSJnFnwhyFQytLesoiPeQ0RN097mkYh7VCoKpbKCQGV06U04yRX0XTiCFhJBBtXPGsygmoqqQaQJUCC9HTI7wa0fq6hqGk19LazoLnP+uRrXf+JEznlnP6GYQSFts+HpvfNbwz6E4walfIXMSJlD6ECQHKUc8oDi+bBu3Tq+/OUv80//9E+88MIL3HXXXdx77738zd/8zazH3HzzzWQymept586dB3HFEonkcKVccBjcnSIvssQiYdyyz7ZfBWnQ7SdbJJcF7hIhBE7B5/FCEEh82bLLMLVZXCmKEgQXtzUHAcazkK1kiBlxepr6UZuWguug49Kc9Glv8zAMQaGo4PgWI8s/C81tLLlwBFTw1q+n8tBDC7toMxL0uiqOwdhWKKWA2YWFoqpozS146TQM7aZvVZwzrlwKwMbfDJAbXXgyh6IohGMG2eEipZyz4HkkklocMnHT1taGpmkMDg5O2z44OEhXV1fNY770pS/xB3/wB3zsYx/jlFNO4T3veQ9f/vKXueWWW/Bn+SVjWRaJRGLaTSKRHNu4FY+xPQWyxRyeUcFSLbY/VsApCKwmlSXnTcaluCXBXnawKb8RTdG4atlV9Sc3DFjaC5YBNYriFZ0SCipL4r2YmgXRNoi1QSmFokA4JGhr8UjGfSqOQsFNMLz8z7C6wvScnQLAeWwdzosvLuziVQ3CzYAHqe2Q2T1eWLA2iqqitbTipVLY27fT0x+ha0UC3xO88OD2/bK66GbQCys9UJDuKcmicsjEjWmanHnmmdOCg33f55FHHuG8886reUyxWERVpy9Z0wLfrTRrSiSSRvB9QWqgQDFnUzAz6JpBapMzWYX4ihiqEcTT+K7AcwSPFx8G4Jzuc2gNt859kng0EDglGyqTVgnHdyi5RXqi3cTN8R9aigqJJUFLhvHifroGTUmf9tbAipPxuhjo+yzxfo/WE3MA2D+/C2/HjoU9CQpgxsCKQmEQUlvBnj0esSpwxsao7NzJ6Zf2oGoKQ9ty7HojtbA1jBOOG5QKDpnhkvwclywah9Qt9bnPfY7vfOc73H777WzYsIGbbrqJQqHARz7yEQA+/OEPc/PNN1fHX3/99fzzP/8zP/7xj9m6dSsPPfQQX/rSl7j++uurIkcikUjqkR0pkRstIyIOBaeAXrJmViEep1LwqUTy/Gb410AQSNwwHa3Q0wljafD9IM7GztAe6aAjuk+pCzMGiR5wiuAHFowJK077uBUnr69kT/ef0HZqgVhvCVyX8g//DT+dXviToRlByrhrB26q3F7wa9fqqQqc0VHM3BAnnBdY2F96eCeOvXCry6R7qkQxO7sFSSKZD4e0zs373vc+hoeH+cu//EsGBgY4/fTTuf/++6tBxjt27JhmqfmLv/gLFEXhL/7iL9i9ezft7e1cf/31/O3f/u2hugSJRHIEUcjYpAeLWBGdYXcM1/MYfNSeUYUYwC35aIbCr4vrcH2XlU0rWdW8qvGTqSr0dUOhCGMZ0jFImEl6Yz0otX5XxjqDGJhSKnBVjaNp0NzkEwoJsuapDDo30nvu99n2iI6dDjKown/8CRRzgSnVigKhRCBwcnsCgRXrDATXvkNVFa2pGW90hONOWMmO1y3yKZvXn9jD6VcsPFlDNzUqZa/62uiG/LEq2T8OaZ2bQ4GscyORHJtUyi5D27J4ro8eVdk4+gYjL7sMPxdUIV7z+8lqsT7hCeycT6hL4X+88GnSdppPnfGp2bOk6pHOUnj1FXxdY2XPycTMOp23y2kY2gBGGIzQjN2eB7mCirHtbpI7/5OtD7bh2RrampMIffCDKOp+GuN9H8q5wC8WHS/8p8yc08tkUMJh0noHT96xBUWBKz6yhqbO2WvozIUQgnzKpqkjQktPdGaqveSY54iocyORSCQHC8/1Se0tUCl7hGIG+UqO9GCJkecDF8zUKsQAlbyPmVB5sfAMaTtNs9XMud3nLujclXiIUlcTXSJBVJkpWKYRagrcU+UM1PjdqWnQlPBRV72Tcu8FLHn7GIoq8Na/TuXhhxe0vmmoKkSSgAaZXZDZAe7MRpdqPI6fzdDe5LHkhGaEgBce2L/g4qp7akS6pyT7jxQ3EonkqEYIQXqoSD5lE0magMJofoyRJxSED039Bq0nTLp0XNtH0RXCrRr3b78fgCuXX4muzt+L7wuf0dIonStPoaP/RNyR4bkFQKwrSNcuz55KHg6DctKHUFecQNdZaQCcdY/ivPTSvNdYEzM8njKeCmJximPTCv8pqooaCuMMDHDaRV3opsro7gLbXhnZr9PqpoaqKUFxv4rMnpIsHCluJBLJUU0+ZZMZLhGOG6iqQtktseWpNE6aGVWIhS9wS4Jwi8rW8ma2ZLZgqAZXLL2i/klmYbQ0Slu4jf6WlYRWrESLJ/BSc2QX6RYkl4Dngjt7/RfN0BGn3kTs5A5aTxjPoLrzDrydC8yg2hdVg0gzIMYL/01PGVeiUfxiEaOc4aS39wDwyq92YRf3r2ZNKGZQLrhkhosye0qyYKS4kUgkRy3lgsPY3gKGqaKbgdtp25tDZNYHX5pTqxADOAUfI6oQatL5r63/BcAFvReQsOYfn5e1sxiqQX+yH0uzUCMRrJUrwHPxSzNdPdOItAYWnNJcQiiEc+pnaD3LCjKoPI/SD/4NL5We93pnxYwGncaLw4EVp5wBBIqioEZjOENDrDgxTrI9TKXs8eq63ft1OkVRCMd1sqNl6Z6SLBgpbiQSyVGJW/EY21tAeAIrYgBQLNq88VDgOplahRiCFgsChUi7wZgzyrMDQQ+7eaV/j2N7NiW3xMqmlSStZHW71taGuWwZXmoMUac9AyiQ7AEjAuWZhQCnYSVxzvgs3RdWsJIOFPKUfvADKoVFFAaaHqSM+5Wgy3huABCo4TA4FfyRYc64KqhcvPXlEUZ3zbHmOdANDVVVSA0UcaR7SrIApLiRSCRHHROF+kq5CuFEIGyEEDx33xbc4swqxEGLBY9ws4oZVXlo20P4wmdN6xqWJZbN79zCZ6w0Rl+8j87I9N55iqJg9vWhd3biDg/Vn8iIQNOSIKDXr/8FLyLdeGs/zZJLsmiWB4N7qdz5U/IFwXzbUM2KQmDBMUOQGwI7cIUp8QTu6AgtTYLlpwYFDp9/YDu+v38upVDMwC46ZIake0oyf6S4kUgkRx0ThfoiCbMaT7P9tVGG3iyAMr0KMYBTFOhhlVCLju3ZPLJjsvv3fBkuDtMWbmNZYlnNdGbFMLBWrEANh/EyswcNAxBtD9Kxi3NXAfaTxyHe9jF6L0yhqALeeB39qYcolhScxWzdpFvBN0d+CHwP1TQRgDM4yCkX92KGNDJDJTb/dg7xNgeBe8oI3FMZ6Z6SzA8pbiQSyVHFRKE+M6Kj6cFHXCFt8+KDQaBtx5nGtCrEvisQriDSpqMZCk/uepK8k6cj0sGZnWfO69xpO01IC7GiacXszTUBLR7HWrECUSri2/bsEyoaJHsDt1ClOOf5/fYzMc7/vWoGlbvuUaJbX8TzFQpFZfGsOGYc7AyURgHQ4gn8VAq9kueUS5cA8PoTuynl9k+U6IaGpiukBqV7SjI/pLiRSCRHDZWyS2pvAUUBMxQIGOELnv3lVtyKj9Uh6D0zWh0vhKCS97GaNcy4ihCC/9oWBBJfvfxq1BoF7Gaj7JapuBVWNK0gYc4dgKx3dWH0LcUbG0XUUx1WIug9ZedoRJ14vZcTvegSWk4I4l6KP/0Zydw2wiFBsaRMbXW1cFQV9DAUhsEpoug66AbO4BDL1zTR0hPFrfi8/MjO/T5VKGpQKTmkpXtKMg+kuJFIJEcFnjdeqK8UFOqbYOMzA4zszKMa0HWJjqpNfuy5JYFmKYRbgu7Ur428xq7cLizN4pK+Sxo/t++RKqdqxtnMhqIomMuXoTW34I2O1h8c6ww6edepfTMVd8UNtFxxIrGeMsL1SX/ndpqUMZqbfPzFsuKYEXArgcBBBIX9Mhm81Bhrr14GCuzckGJwa2Nrno2guJ9JbrRMIS3dU5LGkOJGIpEc8QghSA+OF+prmoyzSQ0Uee3xPQC0ngPNLZP9knwv6PgdadPRreCjcCL9++IlFxM1ojRKyk7VjbOZDdWygvRwTcPL5WYfqBlB7RvfD3pAzYWi4q75I7qu6cBKOni5EiP/fDtxs0x7q7d4VhwrHsQDlTNBYb9wGHdoiKZmjePODJqDvvDADjx3/5SUZqhoukJ6sLBfTTolxw5S3EgkkiOefQv1AXiOzzP3bEH4gpYVFpGVoKnTWyxYcQ0rEXwMDhQGeHHoRQCu6b+m4XO7vovne/TGejE0Y+4D9kFvbsbsX46fzyPqRf6GmyHeBaU0NOKdUXXctZ+i92oTzfKo7Bpi5Ps/wdQ92lo8WhbDiqPpQU+I/CD4TrWwnzsywslv7yEUNcinbDY+M7DAE0wSihpUym7gntrPTCzJ0Y8UNxKJ5IimVqE+gFfW7SI3WsaK6rScL4iYUzp+l31UQyHcpqGMi6H7t96PQHB6++n0xHoaPn/GztASaqEl1LLgazB7ejB7uudoz6AEwcVmLAjmbQQ9gn/+Z+m51AVVUHxpI+n/fBhVhUTcn27FqSywUaUZg0oeCmNTCvsNo3k2p10eBBdv+PVe8qkGLE51qLqnxsoUZPaUZA6kuJFIJEcsE4X6/CmF+gAGtmSqqcgnXNmKo5cJ6YG4Eb7ALQvCLRrGeHXiolPksV2PAfNL//Z8D8dz6In1TLMKzRdF0zD7+9ESCbyxsdkH6iFI9gVtGTy3sclDLehXfoaus4Nsq8x/PU7huZcBsEwxacURkF+IFUdRwIhCcQgqxWphP3doiCUnttCxPI7vCl58aMd+BwRrhoquq9I9JZkTKW4kEskRie8LUoNFSrkKkcSksLGLLs/duw2AlWvbUbpsdE2vZj5V8j5mXCXUNClG1u1cR8kt0RPr4dT2UxteQ8bO0Bxq3i+rzQRqJIK1YgX4Hn6xTtp3tA1ibXO3ZpiCiPYSedcf03JCAYCR2+/A3hpkMk214kTDgmJ5AVYcIxSIreIQCD8o7DcyishlWXvVMhRVYeCtDHs2pec3bw2sqI5dku4pSX2kuJFIJEck2ZESuZHStEJ9QgheeGA75bxDvDXEcW9vIe/kqsHBXkWAohBu1VG14Bhf+Dyw7QEgsNo0GhDs+R62Z9Mb611Qx/Ba6O3tmMuW46VTs7dnUNQgNVy3wC40PLfffAJN73vfeAaVYOhb38dNZav7LVPQ2jxpxZl3LE4oAcU0lNKopgmKgjM4RKzZ5IRzuwB48eGd+93tW1EUIonx7KnM/rm6JEcvUtxIJJIjjmK2MqNQHwRViHe9kUJRFc65vp+CX8D1XAzVCFosFD3CLUGLhQleHHqRweIgUSPK23vf3vAaMpUMzVYzreHWRb02s28Jemcn3shwnUExSPQGsS5ztGaYit99Lh0fvCTIoMpXGP6//4JfmYxfUVVIxHw6Wl0i41Ycu1ErjqqBrgep4V4FNRF0QPdSKU44v4tI0qSUrbD+qb0Nr3c2NF1FN1VSg0Uq5Qbdc5JjCiluJBLJEUWl7DK2T6E+mF6F+KQLu4l3WYyWR6qxNk5BYERUwi3TrSwT6d+X9V1WHTsXvvCxXZve+OJZbSaYaM+ghMN46fTsA2OdQffwebinAPyV19H9eyeiWR72ngyj37ltRhFB04TWZo+25mB7oag2ZsUxYuDkoTCComkopokzOIiG4Iwrg8aam54dJDM8R1f0BrAiOpWyG/Seku4pyT5IcSORSI4YqoX6iu60Qn3CFzz7n0EV4tYlMU44r5t8JU/JLRM2wviOQPgQbtNR9UlLxM7sTl4beQ0FhauWX9XwOjJ2hiaradGtNhNU2zPY5dnbM6h6UPtG0cApNz65osCZH6b7ug5QBYVXd5D5+S9mTq9CLOrT3uoSjXiUSg1YcRQCq1JxFCp51FgMP5vFHR2hZ1UTPauaEH7gOtzf4GJFUYjETXJjNvm0dE9JpiPFjUQiOSIQQpAeKpFP20SSxrTYmI3PDDCyK49uqpxzfT+KqpAqp1EUUFCoFHxCzSpmbPpH3oTV5qyus2iPtDe0jqrVJtaLoc6/rk2j6J2dGEv68EZHZ4+/CTVBvDuoXDwfsaCo6Jd/is63WwCkH3qewtNP1xxqGtDS5NPaMmnF8epZcXQrKDaYH0JRQI3GcIeGEOUyp1/Zh2aojOzMs+O1OllhDTLhnkoPSfeUZDpS3EgkkiOCfMomM1QkHDOmtVCYWoX49CuXEm2yKLllMpU0USOKWxLoIYVwiz5NEGUrWZ7Y/QQwv/TvbCVLwkrQFm5bpCurjaIomP3L0VtbcMfqtGeId0Mo2XBrhiqaQfh3P0fzSYEoGvnhvdhvvVVzaC0rTl03VSgWrKeUQgmH8UslnOFhokmLNRd0A/Dyr3ZSKe2/IJko7ifdU5KpSHEjkUgOe8oFh9RAEd2YXqhvahXi3tVNLD8lcBPlnRwVt4KBiecIwm06mjndpfKrHb/C8R2WJ5ZzQssJDa3DFz4lp7TgasTzRTVNzBUrUDR99vYMuhW4pzw3qH8zH4wYyY9+mmivi/Bg6Fu34dapszNhxQmHRH0XlaqBbkJ+EMWvoMYTuCMj+Pk8q8/uJN4awi66vPbY7vmtdxake0qyL1LcSCSSwxrXCQr1ea5PKDpdUExUIQ5FDc68Nujr5AufkeIolm5RyfuEkhpWfPpHneu7PLjtQWB+6d+5So6EeeCtNlNpqD1DpBViXfMOLgYg2kHbJz6GmXTxioLhb3wT3549hkdVIR4L0sVn85YBQWE/twz5YVTLRDgO7tAQiqqy9uoguPitF4cZ29N4OvtsVN1TMntKMo4UNxKJ5LDF9wWpgSKlnDOtUB9Mr0J81nXLqxWK806evJPHdEJohkK4dbLFwgTPDjzLWHmMpJnk/J7zG1uL8ClWivTGezE1cxGurnHmbs+gQLIHjAiU8/OeX2k/js6PvwfN9LGHKoz98zfrBvyGQ4Jo2Kdk1xGFCmBNCS5OJHHHxvAzaTqWJVh6UlD48IUHti+KOykUNXDKHunBIr50Tx3zSHEjkUgOWyYL9U0PIN63CnHXymR1X9pOI3wQjkq4TUcPzfyYmwgkvmLZFQ27l/KVPHEzflCtNhMomoa5YgVaMjl7ewYjAk1LwC3Nq/bNBNpx59D5wfNAFeTfSJP9j3+dfT0KxGMCTQWnnqFkQgTmh8bjpBScwUGE53HaZX0YlkZqoMhbL9ap6TMPwomgUWdBuqeOeaS4kUgkhyWzFerbtwrxqZctqe6reBXS5TSGbWEm1GrH76m8lX6LN1NvoikaVy67sqG1CCEoOAV6Yj1YmrX/F7cA1HA4aM8g/NnbM0TbIdIGxQW4pwDz3OvpuGYFAKnHt1F89J5Zx1qmIBbxKdtq/UQtayK4eBQ1mcRLZ/BSKUIxg5Mv7gXgtcd2Uy7MM16oBpquYlgqqYHiogQrS45cFrf61FGE53k4s/m3JYcdhmGgaQtvXCg5vJgo1AfTC/XBzCrEujH5uucqOYoFm6TZRGRKi4WpTFhtzu85n6ZQU0PryTk5Ykas4XTxA4Xe1oa5dBn2W5tRTBNF3+cjXNGCzuF2BipFMCPzPkfk+o/SNPAPpF9IM3zHM/R0dGCcdG7NsbGYT7GsUnEULHMWhaNqQcPPwgiKFQ8K+w0MoCWTrDyjnW2vjJAaKPLyIzs5550r5r3efbEigfUmPVSkrS+Oqs6zT5bkqECKm30QQjAwMEC6XmVQyWFJU1MTXV1dDQeHSg5PPM8nNRAU6os2T49tmVaF+O09NHdHq/uEEIwUR1AdnUinhhGZabVJlVM8vSeo59Jo+rcQgkKlwOrm1Q1XMD6QmH1L8HJZvOFh9K7umQOsBMR7IbUlEBXqPA30ikLyo5+mMnILxR0VBr97D91/3obWfdyMoYYO8ajPWFrFNAJ3Ve1FRwJrUn4ENdGLNzqCOzKK0d3F2quX8cjtG9jx+hj9p7XRsSwxv/XWIJIwyI+VCcUMEq3h/Z5PcuQhxc0+TAibjo4OIpGI/KI8AhBCUCwWGRoKgku7u2t84EuOCKqF+lI20aQ57f9vRhXi8WaMExTcAul0nkQySqi59kfbQ9sfwhMexzcfz4qmxqwEeSdP1IgecqvNBIphYK1cSalQwEun0ZqaZg6Kd0E5FbiDIs3zP4du0Pann2bgf/89lbTK8Le+R8fnP4canxlvFI34FMsKZVshHKrjn7LiUBxFCSWCwn6Dg2hNTbT0RFl5RjtvvTjMCw/s4Ko/WjOtjtFCUDUVI6SRHiwRihiYYflVd6whX/EpeJ5XFTatrQemrLrkwBAOB7/OhoaG6OjokC6qI5RCunahPqhdhXgqqVwaX/gkOsLTWixMUPEqPLz9YWB+Vpt8Jc+qplWE9cPHAqDFYlgrVlB+/XX8chk1tI9FSTOC2jeDG8C1g1o480SNJWn/k4+x96vfpjyikvrnf6TlszejGNNdXZoWNNscHtXw/TqGIk0PduYHUVtW4I6mcIeGMJct5eSLe9m1MUVutMymZwc54bz9/4Ey4Z5KDRZoX5qQ7qljDBlQPIWJGJtIZP5+asmhZ+J1k7FSRyblgsPY3pmF+qB2FeKpOJ7D0FiKRFsII1r7S+zXe35NtpKlNdTKWV1nNbSmglMgokcOG6vNVPTOToylS/HGxmq3Zwg3BxacUhoWmBlt9C6j42M3gCLIbRHkf/B18GcG6oZDgkhYUCrPISDMGFRyUBxFTYwX9svlMcN6NTB8/VN7KWQWJ9spkjAopGzyY/PovSU5KpDipgbSFXVkIl+3I5dqoT7Hm1Gob7YqxFMZTaVxjDLNHfGa7wMhRDWQ+KrlV6GpjVn2cpUc3bFuIsbh94NHURTMZcvQ21pxR0dqjQiCi81YEGC8QEKnrKX1vRcCMPpcifK9/zSjj1WQGu6jKODWS1JS1aC4X3EYVfEQvoczNIQQgmUnt9LWF8NzfF56eOeC1zvtdJqKEdJJD5WwZfbUMYUUNxKJ5JAyWaivQiQ5szjeK4/OrEI8FbfikyqkCbepGGZt0bJhbAPbs9sxVZPLl17e0LoKToGwHqYz0jn/izpIqKaJtWIFimHUbs+ghyDZF7Rl8Bb+5R6/8loS5wUBxYP3D+A+85MZY0KWIBYNUsPrYoSC9RSH0OJxvLFR/HQGRVFYe/UyFFVhz6Y0e95ML3i9U7EiOm7FIz1YwK/b8VNyNCHFjWRWFEXh7rvvPtTLkBzlZEdKZEdKRBLmDOEysCXD5udnViGeSiqdxY7kaW6Jz3qOCavN25e8nZgZa2hdOfvwtdpMRWtqwupfgZ/P41cqMwdE2yDWtrDWDFNo/tAfEF7ZivBUhu58CVJbZ4yJR30MQ1CZyzMcSkAxheIWQNVwBgcQnkeyPczqswMx+eJDO3Cd+RcjrMWEeyon3VPHDFLcHObceOONKIrCJz7xiRn7PvnJT6IoCjfeeGNDc61btw5FURpOc9+7dy/XXtt4t2SJZL4UsxUyQ0Ws8PRCfVC/CvHkGIeyUoSkQ9ioHfA7VBzitwO/BeCa/msaW5dTJKSHDmurzVSMnm7Mnm680ZGZbRMUFRJLgqBie+F9nBRNo+2Tn0ALq1RyOoVffH9GJWTDCLqHVypK/cJ+qga6EVQujoTwMhm8sUB8rbmgm3DCpJip8MavBxa83umnm+KeKsqYvGMBKW6OAPr6+vjxj39MqVSqbiuXy/zoRz9i6dKli36+yvivv66uLizr0FRjlRz9TBTqE4IZqbr1qhBP4Hs+5ZJDKZYhGp09k+mBbQ8gEJzSdgp98b6G1pa1s3RFuoga0bkHHwYoqlq/PYMZg0QvVPILas0wgRYJ0/TOKwAYfd5FefO/ZoyJRXwsk/pdwyGIvXHyKHYK1QrhDAwgHAfd1DjjiuB1euM3A+RGF8faYkV0fNcPek9J99RRjxQ3RwBr166lr6+Pu+66q7rtrrvuYunSpZxxxhnVbb7vc8stt9Df3084HOa0007jjjvuAGDbtm1ceumlADQ3N0+z+FxyySV86lOf4jOf+QxtbW1cffXVwEy31K5du/jABz5AS0sL0WiUt73tbTzzzDMH+OolRyMThfrsokM4PtPVVK8K8QTFrIMfrVAJFYgbtV1SZbfMozseBRpP/y46RSzdojN6ZFhtJpjWnqFQw0IT6wy6h++neyp28YWYnTF8RyV976Mopel9oTQNEnEPzwW/noZQlEB0FUdQTPALBdzhYK6e1U10rUwifMELD26v28RzPoTjBvm0dE8dC0hxc4Tw0Y9+lO9///vVx9/73vf4yEc+Mm3MLbfcwg9+8ANuvfVWXn/9dT772c/yoQ99iMcee4y+vj7uvPNOADZu3MjevXv5x3/8x+qxt99+O6Zp8tRTT3HrrbfOOH8+n+fiiy9m9+7d3HPPPbz88sv8+Z//OX7dTy+JZCZCCDKzFOqD+lWIJ6iUXDRDxYkVUFRl1uynx3c9TtEt0hXt4vSO0xtaX7aSpSPS0XBszuGE3taGuWwZXiaD2DdtSdWD2jeKBs7Cv9wVVaX5/b8LQOrNEOKZ78/IngqHBOGwoFyvazgErjLPQymMoEbDuEND+KUSiqJwxpVLUXWFoW05dm7YP0E2gaqpWOHAPbUYvawkhy+yiN8Rwoc+9CFuvvlmtm/fDsBTTz3Fj3/8Y9atWweAbdt8+ctf5uGHH+a8884DYMWKFTz55JP8y7/8CxdffDEtLS0AdHR00LRPVdNVq1bx1a9+ddbz/+hHP2J4eJjnnnuuOs9xx80sxy6RzEUhHfT9qVWob64qxBBkV9lFl2iXxi4xNqsI8YXP/VvvB+Ca5degKnP/liu7ZUzVpCs687xHCmZfH14+jzc4OLM9Q6gJ4t2Q3h4IiwWWTwifeByRk/opvr6VkceH6Dzhabyu86v7VTVIDS+XNVwP9HqZ96E4lFOooSRuxccdGsJYuoxYs8WJ53Xz+hN7ePnhnXSvSGCE9v8rywzr1WKR5tL4fldDlhyeyFf1CKG9vZ3rrruO2267je9///tcd911tLVNlkLfvHkzxWKRK6+8klgsVr394Ac/4K233ppz/jPPPLPu/pdeeokzzjijKmwkkoVQr1AfzF2FGKCUrRBJWrjRMiW3NGvl4FeGX2FPYQ9hPczFfRc3tL5MOUNHpIOEuf/9jQ4Viq5j9a9AiUZxUzUsHvHuoP9UeeG1bwCaf/9doCrk94SoPPEzqGSn7Q9ZgmjUx54rNVzVAqGVH0QNW0Fhv3yQ1n78uV3Emi3KBYfXntizX+udyoR7KrtI8TySww9puTmC+OhHP8qnPvUpAL71rW9N25fP5wG499576e3tnbavkaDgaLR+4OREewOJZKFMLdS3b4VhmLsKMYBjeyiqQqLD4s3SVizdmrV440T69yV9lzTUOqHsltE1/Yi22kygxaKzt2fQraD2zfAbQb0ZfWbMUyMYnW3ELz6b3KPPMPRbk74T/wP35D+u7leUIDW8VFZxnCCTavbJolAaRXWzuH4YZ3AQNRZD01XWXr2Ux3/8JpufH2L5KW00d+1/av6EeyozVCIUNWYUjpQc+UjLzRHENddcQ6VSwXGcatDvBGvWrMGyLHbs2MFxxx037dbXF2QemGZQIM2rVap9Dk499VReeuklxmplYkgkcyCmFupLzCzUN60K8fG1qxALISgXHJJtYRyjTNpOz2ph2Z3fzcvDL6OgcM3yxtK/s3YQa5O0ZqacH4noHR0YfX212zNEWyHWBeX0fp2j6XcuRw2b2BmD/G9eRR19Zdp+0wxSw+25UsMVwIpBYQQtpOCPjeGNl6zo7E/Sd2IzCHjhgcULLjbDOr7nkx4q4snsqaMOKW6OIDRNY8OGDaxfv35GY8h4PM5//+//nc9+9rPcfvvtvPXWW7zwwgv83//7f7n99tsBWLYsqO76y1/+kuHh4aq1pxE+8IEP0NXVxbvf/W6eeuoptmzZwp133snTTz+9qNcoOTrJTC3UV8PVNK0K8TUzqxADlPMOoahBoi3MaGkU3/fR1drG54lYm7WdaxvKerI9G1VR6Y4ePR3lq+0Z2ttqtGdQINkDehjKjX8O7IsWjdB0/ZUADL8aR33t38Cd7uqJRXxMo4HUcC2w1CnlMVBVnIHBalD0aZf3oZsqY3sKbH25VquJhRFOmEFxP+meOuqQ4uYII5FIkEjU/rX6N3/zN3zpS1/illtu4cQTT+Saa67h3nvvpb+/H4De3l7+6q/+ii984Qt0dnZWXVyNYJomDz74IB0dHbzjHe/glFNO4e/+7u9k923JnNQr1AeNVSF2HQ/fFzR1RnBVh6HSEFGztis1X8nz+K7HgcbTv9Pl9BEfa1OLuu0ZjAg0LQGnuF+1b+IXn43e2Ypna6ReqmBs+/m0/boepIa73hyp4RBYb8oZVMPFz2bwxmOGwnGTk94euNtfeXTXohXiU1UFKxK4p2T21NGFIhbLxneEkM1mSSaTZDKZGSKhXC6zdetW+vv7CU31UUuOCOTrd/hRKbsMbc/hVrya7ii76PLgv75OOe+wcm07a69eNmOMEIJC2ibRFqa1N8ZQcYhXR16lM9pZMwPqP9/6T/59w7/TF+/jqxd9dc6GqhWvQtbOclr7aTSFmhZ8rYczzu7dlNZvQGttRTWnvA7Cg+FNUBwNWjQskOIrbzD0Tz9EUQX97xhGXPQFRGJFdb/vw/CoRsVRCIfm+MqpFINjzE4wQ4SOPx7FNPF9wcPfX09mqMTyU9s467rlC17vvhQyFUIxg45lcTSZPXXYUu/7e1/kqyiRSA4I1UJ9pdqF+oQQPH9//SrEEAggM6STbA8CSQeLgxiaUVPYeL7HA9seAAKrTSOd4tPlNG3htqMm1qYWenc35pLeme0ZFA0SPaDpVVGxEMKnHE/ohJUIX2H45TjmxtvAn6yzM5Ea7guYM+TPjIBbRqEwXthvZHwOpSp+t70ywsiuGo1CF7r+uEExUyE3Upp7sOSIQIobiUSy6Pi+ID1QCAr11WiICbD91VF2b6xfhdhzfdyKT1NnBMPSyDm5uoHEzw8+z0hphLgR58LeC+dcZ8WroCgK3bHuhoTQkYqiqpjLl6M1NeGNjk7fGUpCvBfsXAN+o1nmVxRafu9aUBRyO8OUtw2h77x/2phwSBAN+5TmKuwHYMVRimOohsAZGsIvBsKrbUmM/tMCC9ML9+9YtDYKgXtKIzNcppyX7qmjASluJBLJoiKEIDNYJDNUIhI3axZJK6RtXnyofhVigFLWIdZsEU0GwaapUgrHczC1mS4umEz/vnzZ5bOOmUraTtMebqfZam7o2o5kqu0ZYGZ7hngXhJv3q/aN2dtF7MKgXtbgiwm0rfegFCcbXyoKxGMCTQXHnW2WcTQDVBXVy0K5iDs4VM22OuWSJZhhncxwqRqrtRiYIR3fF6QGZfbU0YAUNxKJZNEQQpAZLpEaLGJFDTRj5kdMI1WIIXBH6ZZGU0cERVVwfIeB4gARo3adk22ZbWwY24CmaFy17Ko51+p4DgjoinYd1VabqeitrZjLl+Fl92nPoBlBawbfB9de8PzN11+BErIoj5nkthoYG28HMSkULFMQi/iUbbV+ajgEfafsLIru4Y6O4OeCIoFWROfUS4Pg4tef2EMxW1nwevclHDcoZm1yw9I9daQjxY1EIlk08imb1N4CZljDsGpn0jVShdj3fCpll2RHqNoxPGNnKDiFWdstTFhtzuk+h5bw3JW003YQa9McOvqtNlMxlyxB7+rCGxmeHn8Tbg4sOKU0LDDNREvEaLo2qAY99EoCZXQT2t4np42JxXxMQ1Bx5hCUqgp6BNVNI5wSzuAgYtxttvzUNlp7o7gVn5cf2bmwxdY8pUIoopMZKUn31BGOFDcSiWRRKGRsxvYEosWcpQdQaqAwZxVigFLeJdpkEW+ezHobLg6jKErNQOKMneGpPU8BjaV/u76LEILuWHdDPaeOJqa2Z5golDe+B5K94xaThbun4pedh97ahFvSGH0jivHWT8CePI+hB5WLHWdGv82ZmGFwK2iajT+Wqq5XUcaDixXY9UaKgS3710piKkZIx/fG3VOudE8dqRxb/9USieSAUMpXGN1dAIWadWpgogrx1rpViAGcsouqKjR1RKrxOgWnwGh5lLgZr3nMw9sfxvVdVjatZFXzqjnXm7bTtIRbaAkdm73SgvYMK8F18EtTXDB6KGjN4DrgzRUYUxvVMGh+b1AVevSNBG7Oxnzz36eNiUZ8QqEGuoZDEFxsZ8Ev4QwOIcYDdpo6I6x6WwcALz64Y1GFSCRhUszaZGX21BGLFDcSiWS/sIsOo7vy+K5HODZ7EG8jVYiFLygXXBJtoWn9ftJ2mrJbrtkjyvVdHtr+ENC41cbzPXpjvcec1WYqekc7xpIleKl92jNE24KaN6UaTTcbJLL2JKzjliFcGHoliTbyPOrwC9X9mgaJmI/vN5CgpemgaagU8NMjuGOT2V4nvb2XUMwgn7LZ+JuBOpPMD0VVCEUNMsMlSvnFi+mRHDyO3f9siUSy31TKLiO78ji2R7hGkb4JGqlCDFDKO4QTJom2SRHj+R4D+YFZm18+vedp0naaZquZc7vPnXPNaTtNS6jlmMiQqoeiKFjLlqG3t+OOTGlpoKiQWBI02LQLs08wx9wtvxsIzey2MKUxA/PNH4I7WUsnHBJEwoJSuQHrjRlDcQuooow7NISwg6Bnw9I4/fKgd96GX+8lP7Z4bRQMS0OIoCeadE8deUhxI5FIFoRb8RjdXcAuuESStWvZQJD19Ny92wBYubadrpW1i+W5FQ8hBE0dkWltGjKVDJlKpmYgsRCiGkh85fIrZ+01VT3HFKuNpsrWIcp4ewbVMvGy2ckdZgwSvVDJL7g1g7V8CdFzTgNg8OU2sNMYW+6cPLcSFPZTFHDn8oApSiBwRB4/PYIzPFzdteTEZjqXJ/A9wQsP7li0xpoAkbhJKVshK7OnjjikuDmKGB4e5qabbmLp0qVYlkVXVxdXX301Tz0VBFq+/PLLvPOd76Sjo4NQKMTy5ct53/vex9BQ8It627ZtKIpS8/ab3/zmUF6a5DDDc3xG9+Qp5WyiTbMLm0arEAshKOUdEm3hGdWMR0qBVaGWcNmU2sSWzBYM1eCKpVfMue6MnaEldOzG2tRCSyax+vsRxQJ+ZYoLJtYJkdb9ck81v/sqFMOgNKiQ2xVC3/MoanpTdX/IEsSiQWr4nOgWiu+jKoH1ZqJWj6IonHHVUlRNYXBrlt0b0wte774oqkIoZpAZKVHKSffUkYQUN0cRN9xwAy+++CK33347mzZt4p577uGSSy5hdHSU4eFhLr/8clpaWnjggQfYsGED3//+9+np6aGwT0Gvhx9+mL179067nXnmmYfoqiSHG77nM7Y3Tz5lz9rle4JpVYjfWbsKMUC54GBFDJJt4WlCqeyWGSmOzJn+fUHvBSSs+r1mPN/D8Ry6o93SarMPenc3Ru94e4aJIBhVD2rfKBo4C3P36M1JElcFlaIHX+3A98DYdDv4k2nW8aiPYQgqjWReh+Koogj5UdzBwWq2Vbw1xPHj9ZJeengHjr3wRqD7YlgaiPHsKUe6p44U6ttwJUcM6XSaJ554gnXr1nHxxUGdiWXLlnH22WcDcPfdd5PJZPjud7+Lrgcve39/P5deeumMuVpbW+nqql1YTXJs4/uC1ECB7GiZSKJ29eEJZlQh7qpdhdhzfTxX0NYbQTeni460nabklui0OmccN1Ia4dmBZ4HGAokzdobmUDOt4dpZWscyiqpi9vfj5fN4Y2PobeNNNENNEO+G9PYgBmcBxQ6TV72d/JO/xc3kGHurlbbVe9G334vb/24ADANiUZ9UWsXQRf1TqBroBopbwh0eRGttRUsGbs4Tz+tmx+ujFNIV1j+1h9Mu65v3WmcjHDfJp4LsqdmqaUsOLw655eZb3/oWy5cvJxQKcc455/Dss8/WHZ9Op/nkJz9Jd3c3lmWxevVq7rvvvgO2PiEExYp7SG7z8R3HYjFisRh33303tj2zwmhXVxeu6/Lzn/98UX3SkmMHIQSZoaCtQjhuTIuL2Re/wSrEAMVchXhLaEbXcF/4DBQGMDSjptvroW0P4QufNa1rWJaY2U1837kqXoWeWM+ccTnHKmoohLVyJSjgTbXmxrvBSiy4NYNqmTS/+0oARl6P4pZV9B33ohR2V8fEIj6WCXalAfFkxFCxoZQKUsPHLU2aoXLGlUsBePPZQTKLGCcz1T21mBWRJQeOQ/pf/pOf/ITPfe5z3HrrrZxzzjl84xvf4Oqrr2bjxo10dHTMGF+pVLjyyivp6OjgjjvuoLe3l+3bt9PU1HTA1lhyPNb85QMHbP56rP/rq4mYjb1Euq5z22238fGPf5xbb72VtWvXcvHFF/P+97+fU089lXPPPZcvfvGLfPCDH+QTn/gEZ599Npdddhkf/vCH6eyc/qv4/PPPR1Wnf3Hl8/lFuy7JkUlmuERqIGirMJt7CYJ07ud+uXXOKsQQpJGblk6yPTxjTK6SI2NnarqbbM/mkR2PAI1bbZqsJmm1mQO9pQVz+XLsTZtQTRPFMAKLTbIPht8I6t/otTPd6hE953Syj/6Gyo49DL25nJ5TtmBuvA37jJtBUYPU8LjHyKiGH7SVmh0FMGOolRLe4C681hb01uB17T6uid7VTezelOaF+7dzyYeOX7TWGoal4ZRd0kNFrLBes7WI5PDhkL46X/va1/j4xz/ORz7yEdasWcOtt95KJBLhe9/7Xs3x3/ve9xgbG+Puu+/mggsuYPny5Vx88cWcdtppB3nlhyc33HADe/bs4Z577uGaa65h3bp1rF27lttuuw2Av/3bv2VgYIBbb72Vk046iVtvvZUTTjiBV199ddo8P/nJT3jppZem3STHNrmxctBWITR7WwWYDCDe8foYigJnX98/axVi3/Nxyh7JjnDNisZj5TFc4dZsgPnkrifJO3k6Ih2c2Vk/HswXPmW3TG+8F0Od/xfzsYbZ24vR3RPE30xYeSMtEOuCcnpBcyqqSsvvvQOAzHqbUjaKmn0Lbfej1THhkCAcbrCwn24FyQ5uFmfPnmphP4DTr+hDM1RGduXZ/uponUnmTzhhUspVSMvifoc9ijhEPopKpUIkEuGOO+7g3e9+d3X7H/7hH5JOp/nFL34x45h3vOMdtLS0EIlE+MUvfkF7ezsf/OAH+fznP4+m1f7AtW17mpsmm83S19dHJpMhkZj+i7BcLrN161b6+/sJhYKy70IISs7iBafNh7Ch7fevjo997GM89NBDbN++fca+SqXCGWecwdve9jZuv/12tm3bRn9/Py+++CKnn376fp33UFDr9ZPsP4WMzcjOHKqmzFqfBoL/lRcf3MFbLwyDAue+awV9J86elVRI20SSJu1LE6j7WG0cz+GFwRcQiphRlVgIwf94/H+wK7eLP1jzB1y34rq660+X05iayentp2NoUtw0gpcvUHr1FYTroTeP1wNyCjC4Ibgfqh3gPRdD//IfFF98nfCKZpad9TroFvZZf4sYz14rlRWGRzRMS6DPFfPte4hiGk/EMU84HWNKnODG3wzwyqO7MMM61/7xydX+ZIuBW/GwSy6dy5MzXKmSA0s2myWZTNb8/t6XQ2a5GRkZwfO8GS6Rzs5OBgZqV5rcsmULd9xxB57ncd999/GlL32Jf/iHf+B//+//Pet5brnlFpLJZPXW1ze/IDNFUYiY+iG5LYY5dc2aNTOyoSYwTZOVK1fOul8iaaStAgSC4+VHdgXCBjj7d/rrCptKyUXV1aDFQg2XVcpOkXfyRI2ZwZuvjbzGrtwuLM3ikr5L6q7fFz4lt8SS2BIpbOZBtT2DU5lsz2BEoWkJOMUF175pfu/VoGuUtqTIZvpRPBvjzX+rNpkKWYJo1MduJDVc1VDMMKpfwN29E1GezOhadVYHibYQlZLLq4/trjPJ/NHN4EdnerCIe4h++Erm5ohyGvq+T0dHB9/+9rc588wzed/73sf//J//k1tvvXXWY26++WYymUz1tnPn4nWQPZwYHR3lsssu44c//CGvvPIKW7du5Wc/+xlf/epXede73sUvf/lLPvShD/HLX/6STZs2sXHjRv7+7/+e++67j3e9610z5hoYGJh2K5cXr/Kn5Mig0bYKQghee2w3bz43CMDb3rGMZSfPHtsifIFd8ki2h2sKJiEEw8VhNFWr2R5hIv374iUX1xQ/U8lWsiTMBG3htrrjJDPRO9oxli6d3p4h0ha0ZygurPaN0d5C4tLzABh+PowvNLTRl9GGnwPGC/tFfTRN4DSSGm5EUAwff2wPzni9LgBVU4PGmsCWF4cZ3b24MYPhuEEpXyEzXJIJGocphyyguK2tDU3TGBwcnLZ9cHBw1jTk7u5uDMOY5oI68cQTGRgYoFKpYJozP4Aty8Kyavv8jyZisRjnnHMOX//613nrrbdwHIe+vj4+/vGP88UvfpG9e/cSiUT4sz/7M3bu3IllWaxatYrvfve7/MEf/MG0ua64YmYxtP/4j//g/e9//8G6HMkhZmpbhUiyvul9/ZN7eePpwNp6xlVL6T+tve74Yq5CJGESb63tOiw4BcbKYzWbZA4UBnhx6EUArum/pu55fOFTqpRY3rZcWm0WgKIoWEuX4udyuCPDGJ1dk7VvKrmgNYM1/7TopndcQv43L+IMpxkdPYv2tt9gvPkjvOY1YMQwzSA1PJ1R0edKDVdAsRKolQzu7u3oLS2oscBl1r40zrKTW9n+2igvPLCDK248sW5NpvmgKArhmEF2pEQ4Zkr31GHIIbPcmKbJmWeeySOPPFLd5vs+jzzyCOedd17NYy644AI2b96MP6XT2qZNm+ju7q4pbI4lLMvilltu4fnnnyedTlMoFHjjjTf4m7/5G8LhMCtWrODb3/42GzdupFgskkqlePbZZ7nxxhurcyxfvhwhRM2bFDbHDo22VQB44+m9rH9yDwCnXb6E486cmeU4Fcf2UBSFps4w2iw1clLlFLZnE9Jnip/7t96PQHBGxxn0xHrqnitXyRG34rSH64styewopom1ciWqFcLLjKeCW4mg91SlsKDO4Wo4RNP1lwMw9vQwjtaN4mQx3vppdUws4mMaDaaGawZqyEBkB3AHBphqSDn1siUYIY30YLHqMl0sJtxTqYGCdE8dhhxSt9TnPvc5vvOd73D77bezYcMGbrrpJgqFAh/5yEcA+PCHP8zNN99cHX/TTTcxNjbGpz/9aTZt2sS9997Ll7/8ZT75yU8eqkuQSI4qGm2rALDp2QFeXRfEM5xySS+rz65f+FEIQbngEG8Lz+rmcn2XgeIAYWNmk8yiU+SxXY8Bc1tthBAUnSI90Z6a2VaSxtESCawV/YhSEX8iOSPeBfGOoDXDArwy8QvOxOjpwC+UGNp+EgIFfeBJ1NR6AHQ9SA13vQa6hgOYcVTTw92zBT+Trm4ORQ1OubgXgFcf373oHb7DcYNywZHuqcOQQypu3ve+9/H3f//3/OVf/iWnn346L730Evfff381yHjHjh3s3bu3Or6vr48HHniA5557jlNPPZU//dM/5dOf/jRf+MIXDtUlSCRHDfNpq7D5+SFefmQXAGsu7OGE87rnnL+cdwhFDZJts2eyZewM+UqeuDHTJbVu5zpKboneWC+ntp1a91w5J0fciNMRrW9JkjSG3tWFsWQJ3thYUDRP0YLaN3oY7PkX91M0bbJr+K/foBQ+HwBj4w/ACwRIJCwIW6Ix642qoobiUBrD2bVtMkYIWHF6O81dEVzb45Xx9+xiUXVPDcvifocbh7xU56c+9Sk+9alP1dy3bt26GdvOO+882cRRIllkgrYKRbKj9pxtFba+PMyLDwZtFU44r4s1F84tbFzHw/MEbZ2RugUAJ5pk7tv7yRc+D2wLimle039NXYuSEIJCpcDxzcdjaUd/vN3BQFFVzOXL8fIFvNFR9Pb2IHuqeRkMbwS3Avr8LGThNasIn7ya0mubGPqtzrIzmlHLQ+jbfoG78vdQ1aBr+PCYhufBLNU+JjHDqKEi3t5teJ29wRoJqgufec0yHr5tAzvWj9F/Whsdy+unEc8H3dRwbI/0YFDcb98WIpJDwxGVLSWRSBafybYKRcJxvW5bhe2vjvLb+4KaSavO6uTki3vnLFkghKCcd0i0zmyxMJWiU2SkVLtJ5otDLzJYHCRqRHl779vrni/v5IkZMdojMtZmMVFDIawV/aAqk+0Zom1Be4ZSChbglmm+4RpQVUqvvklGuwoAfecDKLngPRYOCaJhn1Ijhf0AJZxE8Qo42zcjpqRbNXdHWbk2eD+88MAOfG9xG2CGYhPuqaJ0Tx0mSHEjkRzjZEcaa6uwc/0Yz967FYCVa9s57fIlDdVisosuZkgn2R6pOz5tpym7ZcL6zHibifTvy/ouqxloPIEQgnwlT0+sp+44ycLQW1ow+/vxM5lx148SZE+FmqCUnvd8ZncH8YuC5r4jD76J03omCj7mxtvA94LU8JhAU8FpJHZZ01FjUfzh7bhD0+ulnXxxL1ZEJzdWZuMzg7NMsDCq7qnRsnRPHSZIcSORHMPkxsqM7Zm7rcLujSmeuWcLCOg/rY0zrlrakLDxXB+34pPsiNSd3xc+Q8UhTH1mEPPO7E5eG3kNBYWrll9V93wFp0BEj0irzQHE7OlBb2/DGxsLNugWNAUNK3Hm35ag6XcuQ42EcHYPkBo9FaFHUPPb0Xc/BIBlCmIRn7KtNmQcUkJxVN3D3fYGfmmyPpcZ0jnt8qCI64an9lJIz2wwvD/opoaqjhf3q8jsqUONFDcSyTFKIWMztqeAbqp1y9Pv3Zzm6bu3IAQsO7mVM69Z1nD17FLOIdZsEZulv9QEWTtL2k7XDCSesNqc1XXWnKIlV8nRE+upaf2RLA6KrmMuXQpCTGZPhZsh0Qvl7LyrF2uxCMl3XApA6r6nsJe8FwB9690opaAwXyzmYxqCitPA+05RUOPN+KkB3F1bp+1aelIL7UtjeK7Piw/tmNc6G0G6pw4fpLiRSI5BJtsqiLptFQa3Zvj1XW8hfMGSE5t523XLGy6EVi446KZGsiMy5zGjpVF8359RbC9byfLE7ieAubt/5yt5wnqYjojMkDrQaC0tGL09eGNTGlMmeoIKxguoXpy45Bz0jlb8bJ6xF128phNQ/ArGpqA1g6EHlYsdp8HQHiOEGjFwd72Jn81WNyuKwtqrl6GoCns3Z9jzZnrea62HoiiE4waZEemeOtRIcSORHGM02lZheEeOp+54C98T9Kxu4pzr+2v2gapFOe8gfGjpjmLN0bTQ9myGSkNEzZnVbn+141c4vsPyxHJOaDmh7jy5So7uWDcRI9LQGiULR1EUzCVLUCMRvFwu2KjqgXtKN8GeX7sDRddpeW9QuyjzyK8ptr0HoehoqdfRBn8NQDTiEwo12DUcUOOtiEIKZ/umaVaURFuY1WcH5UZefGjHoruQdEND0xRSA0Uc6Z46ZOyXuKlUKmzcuBHXnX+VSolEcvCplF1GdxdwbI9wncylkV05nvjpm3iuT9fKJOe+a0Xd9PCplHIVhIC2JTFizXOnYqfL6SBWZh9R4vouD257EIB3rHhHXVdYwSkQ1sN0RjpnHSNZXNRoFGO8PUO1rowVDwSOU5p39eLwaScQOr4fXJex+1/AXR70vDM2/xgqWTQNEjEf32+wsJ+qoSUTeLvfwh8dmrZrzQXdRBImxUyFDb/eO8sECycUM7CLDpkh6Z46VCxI3BSLRf7oj/6ISCTCSSedxI4dge/yT/7kT/i7v/u7RV2gpDFuvPFGFEWZcdu8eXN13yc+8YkZx33yk59EUZRpbRiGh4e56aabWLp0KZZl0dXVxdVXX81TTz11EK9IsthMtFUo5526bRXG9uR54idv4jk+ncsTnP/elXXTw6dSylVAUWjrixGdI84GguymoeIQhmbMaJL57MCzjJXHSFpJzuuu3ZJlgpydoyvSNWcjTcniYnZ1obW04KWmuKKiHRDrhOLYvKoXK4pC8+++AxSF4m9fJV85ET/ah+IWAoFDkBoeCQtK5cZTw/HLOFvXTyvsp5sap18ZBBdvfGaQ7Mj8A6HnupZI3AyypzLSPXUoWJC4ufnmm3n55ZdZt24dodBkuuUVV1zBT37yk0VbnGR+XHPNNezdu3farb+/HwiqO//4xz+mVJr8Jy6Xy/zoRz9i6dKl0+a54YYbePHFF7n99tvZtGkT99xzD5dccgmjo6NIjkw8t7G2CqmBIo//5E3cik/70hjn/27jwqaYraCoKu19caLJxorn5ZwcKTtFwpxZVG0ikPiKpVfUbXxZdIqE9BCdUWm1OdgohoG1bCn43mRwsaJCUx+YsXlXL7b6uomdvxaAsTsfxF71h0FrhqHfoI6+Mp4a7qMo0JDDQAG1uR1vcBfe3ukBxD2rmug+LonwBS88uGPRLSyaoaLpCqlB6Z46FCxI3Nx9991885vf5MILL5z2IXnSSSfx1ltvLdriJPNjwsoy9TbRQX3t2rX09fVx1113VcffddddLF26lDPOOKO6LZ1O88QTT/CVr3yFSy+9lGXLlnH22Wdz88038853vvOgX5Nk/wnaKhTmbKuQGS7x+I834ZQ9WnujXPh7q+rWvZlKMWOj6SrtfbF5dUhOlVI4njOj/9Nb6bd4M/UmmqJx5bIr686RrWTpjHTWLP4nOfBobW0Y3d34qbHJjXo4cE95LrjzS7lueucVKJZJZdsu8huzuEuC19/Y9G/glglZglg0SA1vBMUMoRoaztbXEeXJ1HBFUTjjyqWousLw9hw714/VmWVhhKIGlZJDWrqnDjoLEjfDw8N0dMzMSCgUCg2niB4xCBF0vz0Ut0X+Z/joRz/K97///erj733ve9UmpRPEYjFisRh33303tr24dSAkBx8x0VZhuFS3rUJ2tMRjP9pIpeTS3B3h7b+/qqEy8kIICmkb3dRo74sTjjcubBzfYaA4UDMAeMJqc37P+TSFmmado+SWsDRLWm0OIYqiYPT1oYRCePkpgcTR1iCDqpSe12eZnoyTvOYiAFJ3P0il93fwQ22o9ijG1uDHWTzqYxiCilNvpilrbGnHTw/j7nxz2vZok8Wa84P2IS89spNKeXHjR4Pifia50TKFtHRPHUwW1FvqbW97G/feey9/8id/AlAVNN/97nc577z6vvEjDqcIX+45NOf+4h6okUEyG7/85S+JxSZ/vV577bX87Gc/qz7+0Ic+xM0338z27UFp86eeeoof//jH03p46brObbfdxsc//nFuvfVW1q5dy8UXX8z73/9+Tj21frNCyeGFEIL0RFuFhDGreyk/VuaxH23CLro0dYa56H2rMUJzfzQIIShmHYyQTtuSGKHo7K6jWmTsDAWnMKN2Taqc4uk9TwNzp39nyhn6En3EzZn1cSQHDy0Ww+jrw964ETUSQVFVQAlq39i5IP4m2trwfInLLyD3xHN4Yxmyv3oO/bwPY73yNbTdj+B2noORWEks6pNKqxi6YK7f1IqqocYSuNveQOvsRU20VPetPqeLba+Nkh+zef3xPZxx1dI6M80fzVDRdZX0YAErotctZilZPBZkufnyl7/MF7/4RW666SZc1+Uf//Efueqqq/j+97/P3/7t3y72GiUNcumll/LSSy9Vb//n//yfafvb29u57rrruO222/j+97/PddddR1tb24x5brjhBvbs2cM999zDNddcw7p161i7di233XbbQboSyWLQSFuFQtpm3X9sCno/tYe56P2r6xb0m0AIQTFTwQxpCxI2AMPFYRRFmRFI/ND2h/CEx/HNx7OiacWsx5fdMoZm0BXtmve5JYuP0d2N1tI6PbhYMwP3lKJBpdjwXKpp0PyeqwHIPPA4FXUpbud5KAjMjbeD7xKL+FgmjXUNh6CwXzmPu3XDNBeRpqusvXoZAJtfGCK1t9DwOhvFiurYJZf0cOPPgWT/WJDl5sILL+Tll1/mlltu4ZRTTuHBBx9k7dq1PP3005xyyimLvcZDixEJLCiH6tzzIBqNctxxx9Ud89GPfrTahf1b3/rWrONCoRBXXnklV155JV/60pf42Mc+xv/6X/9rWlaV5PClkbYKxWyFx/5jI6VshXhLiIs/sLpuQb8JAldUBSui09YXn7OOTS0KToGx8tgMi0vFq/Dw9oeBxqw2vfHemsHIkoOPapqYfX2UX3sVv1JBNcddlKGmoP9UakvQqkFtzHIRfdsp5B59GnvLTtK/eAj9A+9HG3sVtbALfef9sOx3SMQ9RkY1fAPUuX6qK6A2t+Hu2YrWvRSto6+6q3N5gr41LexcP8bzD2zn8g+f2HCxykZQFIVQ1KCYqeC0e9J6cxCYt+XGcRw++tGPoigK3/nOd3j22WdZv349P/zhD48+YQOgKIFr6FDcDkD80jXXXEOlUsFxHK6++uqGj1uzZg2FwuL/opEsPo20VSjlKzz2o40U0hWiTRYXf3B1Q9aXCWETihq0L1DYQNAks+SWZrRJ+PWeX5OtZGkNtXJW11mzHl92y+iaLq02hxl6ext6Z9f04GKAeBdE2gP3VIMoikLL770DgPxvXsIeyOEc94HgPNvuQSnuJRwShMPzKOwXjiKEwNm2HuFOD9g57fIl6KZKam+RLS+PNLzORtFNFbfiUS40GCgk2S/mLW4Mw+DOO+88EGuRHAQ0TWPDhg2sX7++mkk1ldHRUS677DJ++MMf8sorr7B161Z+9rOf8dWvfpV3vetdh2DFkvlQbavA7G0VygWHx360KcieSppc8sHVDQUCC1+QT9mEYgZtfbGG3Fe18HyPgfzADGEjhKgGEl+1/Cq0Or/wM3aGjkiHtNocZiiqirm0DwwTf+qPIVUP0sP1MJRzDc9n9fcRPetUEIKxn92H234OXvPJKMLF2Hg7quITj/kgwG0w21prbscf3IO3e/O07eGYyckX9QLw6rpdiy5CFEVB01UKGVtmTh0EFhRz8+53v5u77757kZciOVgkEgkSidpfCrFYjHPOOYevf/3rXHTRRZx88sl86Utf4uMf/zjf/OY3D/JKJfNhWluFWcSKXXR5/D82kRstE44bXPLB44k0UJNG+IJ82iaSsGhbEsNsIOB4NjKVDJlKZkbq9oaxDWzPbsdUTS5fevmsx9uejaZodEW6jr7szKMALZHAXLIEL5NBTC0lbMagaUmQGu42Lhya33MViqFjv7mN4ssbcFZ/GKGaaJlNaHufIGQJolEfu+HUcBNCEZxtbyBK04XWyjM7aOoM45Q9Xn10V8NrbBQzrGEXHJyyrHtzoFnQJ9SqVav467/+a5566inOPPNMotHpGT1/+qd/uiiLkzROvWDfuQKBpwpVy7K45ZZbuOWWWxZnYZKDwtS2CpFkbWFTKbs8/pNNZIZLhKIGF3/w+IaqCPu+oJixiSQDYWM0kCJej5FSYPLX1ekfPxNWm4uWXFS3Zk2mnKEr2kXSSu7XOiQHDqO3B3dkGC+TQW9untwR7YByHvJ7gvsNaFO9pYnElReSuW8dqTvvJ/K/Po3T/17Mt36M8dZP8VpPIx5tolRWcRwwGohtV5ta8QZ24u3YiL76bdV1qGrQWPNXP3iDba+Osvy0Ntr7Fi8TTzc0yjmHcsFZsOVT0hgLenb/9V//laamJp5//nmef/75afsURZHiRiI5iExtqxBtrl192LE9nvjJm6QHilgRnYs/uJp4S6jGbNPx/aCOTazJorU31lDtm3qU3TIjxZEZ4mWoOMRvB34LwDX918x6fMWroCoqXVFptTmcUS0Lc9kyyq++inAclAnFoaiB9aaSg3Iawk0NzZe86u3kn3oedyRF9tHfkLzyCvyhZ1BzWzHf/Hc4+ZPEoj7pjIreUGq4ihprwdnxJlrHEpTmydit1t4Y/ae3sfWlEV64fztXfnRNw33VGkEzVfJpm3hLaFGDlg83hBCH9H90Qa/Y1q1bZ71t2bJlsdcokUhmYaKtQjE7e1sFt+Lx5E/frGZPXfSB1STawjVmm47v+YGwabZoXbL/wgYmA4kj+vRMwAe2PYBAcErbKSyJL5n1+IydoS3cRpPVtN9rkRxY9LY2tM5O3LF9goj10Hj1Yg+ccu2D90ENWTS96woA0vc9ipcvUTn+DxGoaCPPow6/QCziYxqNp4Yr8Rh+2cXdtn5Gk89TLl6CGdbJjpR587dDs8ywMMyQTqXkYpeO3obTQ9kymwYaj606EOy3HBVCyOAoieQQMLWtQjRZu62C5/g8dcdmRnblMaxA2DR1zF1iwPd8CpkgRbytN95wG4a6cwqfgcIAhmZME2Flt8yjOx4F6qd/V7wKQgi6Y93SanMEoGgaVl8fiq7hF/ep7xJpgWQvlDMNtviG2LlnYPZ1I8o26f98BBFbirs0eL+Yb/4QnSKJuIfrNTaloiioTS04A7vxh7ZN22dFdE69LBDZrz+xh2J28aoLa7qK7/lHbdZUqeLx1nCefOXQircFi5sf/OAHnHLKKYTDYcLhMKeeeir/9m//tphrk0gksyB8QWqwflsFz/V56s7NDG3PoZsqb3/fKpq75q547bk+hXQgbFp7YmjG4pjkc5UcGTszo7bN47sep+gW6Yp2cXrH6bMen7bTtEfapdXmCEJrasLo7cXLpPf5ETxevTjSCsXUrMdPRVHVamp47onnqOwZxF12PX64E6WSxthyB5GwIGyJxgv7RcKAjrt9A2KfLK7lp7TSuiSG5/i89PDOhuZrFN3UKKRtfP/oMgwIIdg6mmcod+hb9yzoU+trX/saN910E+94xzv46U9/yk9/+lOuueYaPvGJT/D1/4+9846zq67z/vuU2/udO71lkkw6BAihhS7SFFFBEV3Bsuizu+oqrj64IiLggyKrrmJb1gI2EDsgICAEEiDUQCDJTNok09vt7dzTnj/OzCST6WGGtPN+ve5Lufec3/ndycy5n/ttn+98Z7b3aGNjsw/DtgrJ3oltFQzd4Nk/7aB3VxrJIXLG+5spq53aWFLXDPLpEsGYm7La2RM2APFiHM3URplkGqbBw7seBuDCeReOmVY8jKqrYEK1r3rCY2wOTZx1dUiBAEZqP4dwyQGhepAkUKY3Q8u9qAnvccus1vDfPwySE3XR1QDIXU8ip1sJ+A0M08p6TQchEkWLJzC6t43ywBIEgRMuaEAQoLMlQfeOmTmcT4bTLVmpqfyRFb3pTSt0Jgr0posYBzmjc0B3ie9///v86Ec/4pvf/Cbvete7eNe73sVtt93GD3/4wzEj/21sbGaXYVsF9wS2CoZh8txfdtG9PYUoC5x++UJi0+j40NVhYeMhWuuf0IvqQFB1lb5cHz7H6MjRa/2v0ZXrwiN7OKv+rAnPTypJyjxlRNyRCY+xOTQR3W6cjY0YhQKmtl+qwh2yBE4pN6buZSIi770AJIni5m3kX2/FiCxBq7aMNh2td+FxlvB5DArTHezncGA6fKh7dmBmR9fXhCu8NK+2TFlf+fsedHV6KbQprymJmCYUM0eOuMmXNHb2Z+lMFPjGQ1u56f4tFNWD1/J+QHev7u5uTjvttDHPn3baaXR3d7/pTdnY2IxPJl4k3j2xrYJpmDx//y46WxKIksCayxZSMW/qQXeaqpNPlwiVeyir8SHNYncIQEJJkFEzY8TNcPv32fVnjxnqN7I3Q8M0TWr8NXbU5jBFrqhArihH239yMVjTiwMVUJheespRUUbwnFMASPz+IUxdR53/PkxHEDHfjWPPAwT8JpII6jTLPqRQECOnoLe3gDa6vmbZ6TW4/Q5ySYWtz87e55vDJZFLKej67Aimg4lhmLQN5BjIKfx03S4ME4IeGfcs1OodKAd0p1i4cCG/+93vxjx/77330tzc/KY3ZWNjM5YRWwXH+LYKpmny4t/aaN8cRxAFTn3PAqrmTz0LRivpFDIq4Uov0WrfrLa9Du+rP9+PLMqjxElntpNX+19FQODCeRO3fyeVJFFPlIjLjtocrgiShLOhAUEQMAqF/V+0ojeyB4rpaa0XuvhsRL8XtaefzNMvgMNHqfmfAJD3/A13qR2/16CoiEwnOyJIEniCqN2dmInRw/scLonjzrN8qLY+10MmPr0Or6lwuiVKRR0ld/h3TfVlFDoSBZ7Y2kd7okDI4+CaM5oO6p4OaM7N1772Na644gqeeuop1qxZA8D69et5/PHHxxU9NjY2b45iVt3HVmHskD7TNHn54d20bRpEEOCUS+dT0xyecl2tpFPMqoSrfEQqvYhzMHdjIpPM4VqbVZWrqPRVjr8/Q0M3dGp8NZPaMdgc+siRCI7aWkptbQhu9+iON4fPag8faLWmF8uTT+KTvB7C73wb8XvuJ3n/P/CtXgnlq9DLjkMa3Iiz5Rf4j/1P8kWRkirgck6tcES/F30gj9bRiiMQA/feiGfdkgiVTUF6d6V55e97OOOK5jfdsSeIAoIAhYyCNzi1/cmhynA6qiNR4C8bLZPpj5w6j4B7GtMU55AD+op22WWXsWHDBmKxGH/+85/585//TCwW4/nnn+c973nPbO/R5hBFEIRp23DM5Fib0SgFjYHOLPoEtgqmabLx0XZ2bhwAAU66pIm6JVNHOVRFp5jTiFT5iM6RsAFIFBMouoJb3js0MFvK8lTHU8Dk7d8pJUXUHSXqjs7J3mzeWpy1tYh+P0Z6nAiNv9xKURUSTCfcEjjjRBzVFRi5PKmHngRBoNT8T5iSGzGzE3fvPwj4DFR1WssNDfYLoA0kMPvbwNybLhIEgRPOb0CUBHp3penYOr0U2lQ4XBL5tIp2EGtT3gzD6aj+rMLP1lvpqLMXl7Oq8eBHWQ84/rxq1Sp+9atfjUwp/tWvfsXxxx8/m3uzmQEf+chHEAQBQRBwOp0sXLiQm266CW3/Ar5ZpLu7m4sumviD6UCPtdlLqagx2JFFLWrjfrszTZPXnuhg+0tWIeTqi+fRsLxsynVVRUfJa0SqvIQrvXM2KVUzNHryPXgco+tpnmh/AkVXaAg0sKxs2bjn6oaOZmjU+O2ozZGC6PXiamjAyOUwx7QzCRCqsyImheSUawmSRORyK52ZfuI51N4BcEdR578PAMeuP+AX+3G7p+8aLnjcGKYDtXMn5EY7g/ujbpacak0y3vhYO6ry5gWJwy2hFrXDNjU1nI56fEsvHYkCUa+TT5wx/2BvCzhAcfO3v/2NRx55ZMzzjzzyCA899NCb3pTNgXHhhRfS3d3Ntm3b+PznP8+NN97It771rTHHlUqzM5CqqqoKl2tqb6KZHmtjsa+tgjc0/vThN57qonVDLwCrLmxk3rGxKdctFTWUvEa02ku4Yu6EDViRl2wpS8CxNyWlGzqPtFn3jwubLpwwvJ9SUkRcETtqc4QhV1Yil8fQ959cDEPTixutUMs0phd7ly/Cs7wZdJ3EH63fKb3mLPTgQgRdwb3jlwR9OoYxg8F+fh9auojRvX3MHpacUo0v7KKYVdm8rmta73eq6wmiQD598OfCzJR8SWNHf5b2wTz3v2oVWv/bOQsJuB2ohoEsHtzi/wO6+nXXXYc+zhAB0zS57rrr3vSmbA4Ml8tFVVUVjY2N/Mu//AvnnXcef/3rX/nIRz7Cu9/9br7+9a9TU1PD4sWLAWhvb+f9738/4XCYaDTKpZdeSltb26g1f/azn7F8+XJcLhfV1dV86lOfGnlt31RTqVTiU5/6FNXV1bjdbhobG0eZb+6fltq0aRPnnnsuHo+HsrIyPvGJT5DNZkdeH97z7bffTnV1NWVlZfzbv/0bqnrktE5OxnRsFTav72LLM9ZN5fi3NzD/+PIp1y0VNEpFnWiNj9AcCxvYa5K5b+Tlpd6XGCgMEHAEOL329HHP0w0dRVeo8deMMdi0ObwRZBlnQwOYJoYyzoe6J2JFcIopMKaOjkQuuwhEkfyrWyi07ARBRF18NaYgI8Vfw595Hq/HpFCcZmu4ywWCC62nCzPTDfuktCSHyPHnNwCw7YVekn35CVaZPk6PTD6jzkok6K1ipDsqq/DT9bswgXOXVHBSU5SiqmOaUB2a2rtuLjkgcbNt2zaWLRsbSl6yZAnbt29/05s6lDBNk7yaPyiPN2tr4fF4RqI0jz/+OC0tLTz66KM88MADqKrKBRdcQCAQ4Omnn2b9+vX4/X4uvPDCkXN+9KMf8W//9m984hOfYNOmTfz1r39l4cKF417re9/7Hn/961/53e9+R0tLC7/+9a+ZN2/euMfmcjkuuOACIpEIL7zwAvfddx+PPfbYKOEE8MQTT7Bjxw6eeOIJ7rrrLn7xi19M6XB+JDAdW4WW53p44ynrm+Ox59ax8MSKKdctFTRURaesxkeo3DPnFgZ5Nc9AYaxJ5nD799sa3zZqoN++pEpW1KbMM3WKzebwQ4pGcdTWoMcHxz8gWAPe2LSmFztrKgicsRoYag03DExfLVrjO6zXt/+GoCuNIMB0s/RCwIdWMDG6dlgGn/tQvSBE7eIIpgkvP7z7Td+nZaeIVjq87BiG01F/f6OXrlSRqM/JNWfMxzBNBnMKDVEv5YGDG6k/oK9EoVCInTt3jvnw2r59Oz7f1OPdDycKWoGTf3PyQbn2hg9uwOuY2gdof0zT5PHHH+eRRx7h05/+NP39/fh8Pv73f/8Xp9P6MPnVr36FYRj87//+78iH3M9//nPC4TBPPvkk559/Prfccguf//zn+fd///eRtVevXj3uNffs2UNzczOnn346giDQ2Ng44f5+85vfUCwWufvuu0d+X+644w4uueQSvvnNb1JZaXXORCIR7rjjDiRJYsmSJbzjHe/g8ccf55prrpnxz+RwYZStQmh8W4VtL/Ty2hNWu+qKM2tYfHLVmGP2R8mraKpBWa2fQJl7zoVNQSuwPbmdglYg5Nrbjt6WamNLfAuSIHF+4/njnmuYBoqm0BxutqM2RyiCIOCorUMbGEDPZJAC+w2ZFGWre0rNgZIF1+TTtcOXnEv2+VcptXeTffYVAmtWoTVcjNT3AmK+C3/HveSq/pl0RsIvT52fEh0yuuxAjScRy9oRXAHYJ/p43Hn19OxMMdiZo+21QZpWTp0OnghBEJBkgXzKMqk91H3ThtNRbQM5/rbJihx/+tyF+F0yA1mFsNdJQ5n3oL+PA4rcXHrppXz2s59lx44dI89t376dz3/+87zrXe+atc3ZzIwHHngAv9+P2+3moosu4oorruDGG28E4JhjjhkRNgCvvvoq27dvJxAI4Pf78fv9RKNRisUiO3bsoK+vj66uLt72trdN69of+chH2LhxI4sXL+Yzn/kMf//73yc8dsuWLaxcuXKUEF6zZg2GYdDS0jLy3PLly5GkvTeU6upq+vpm16H3UGI6tgo7Xukf8blZuqaapWtqplxXyavomkmsLkAw9tZEbFriLfTn+6nwVoy63nDU5uTqk4l6xq+lSSkpwq6wHbU5wpH8PhwNDRiZzDjFxYArYM2/UfNTTi+W/D7CF58NQPIvj2IUFRAdqIs/gomA3LOOsLoJh8OkNM0AiRjwoSug97RDrn/Ua96gk+VnWH97rz3RgZJ/cwXBTrdEMacd8qmpvemoIj9b34YJvH1ZJSc2RsmXNHTTZEG5/6AO7xvmgL4W3XbbbVx44YUsWbKEujrLObW9vZ0zzzyT22+/fVY3eLDxyB42fHDDQbv2TDjnnHP40Y9+hNPppKamBlne+8+7f0Qtm82yatUqfv3rX49Zp7y8HHGGxWAnnHACu3bt4qGHHuKxxx7j/e9/P+eddx6///3vZ7TOvjgco+ckCIKAMU0H4cOR9ECBRO/Etgq7Xhvg5Yd3A7D45MqRm+tkFHMqpmFaEZvo3OfAM6UMrfFWkkqSCl/FqKF9SSXJ+q71wMTt38NRmwWhBTjEgzsnw2bucVZVofX2oScSyLFxoh/+ClAykOmx/v8kujx49ilknnoerT9O6pGniFz6dozQQvSac5C7/oFnx934l95CIu3BIZtMpfEFUUJwulBTRaSBNgR3CPbp+ms+sYK2TYOk+wtsWtvBiRfNO7AfApaRZiGrUsypON2HbrSyN1OkI1Hg4dd76UkXifldfHxNE4ZpksiXWFDuJ+Y/NGb2HHBa6plnnuHRRx/l1VdfxePxsHLlSs4444zZ3t9BRxCEA0oNHQx8Pt+ENTH7c8IJJ3DvvfdSUVFBMDj+eP558+bx+OOPc84550xrzWAwyBVXXMEVV1zB5ZdfzoUXXkg8HicaHf0NfenSpfziF78gl8uNiK7169cjiuJIsfPRRjYxZKvgGt9WYc8bg7z4YBtg3VSPOaduyghMMatimlBWG8Afmfv8d0pJ0RJvIatmxwgbgMd3P45maCwML6Q5Mv4k83QpTdAVJOY58DC/zeGD4HDgamygsGkThqJYxbyjDpCs4mIlA0rK8qKacC2ZyHsvpP8nvyH92HoCZ6xGjoZR51+GOPgKYrGfaP+fyQeuRCkJuF3TGOzn9aAnNLSBfhzBLoguGBFYoiSy6oIGnvhVC7s2DtB0bGxa5rQTITtEcgmFQMQ954X+B4I1rC/Hrv4cD73eA8Bnzl2IzyXTlylS5ncdEumoYWb09fzZZ5/lgQceAKwP/fPPP5+Kigpuv/12LrvsMj7xiU+gjFf9bnPI8aEPfYhYLMall17K008/za5du3jyySf5zGc+Q0eHVc9x44038l//9V9873vfY9u2bbz88st8//vfH3e9b3/72/z2t79l69attLa2ct9991FVVUU4HB732m63m6uvvprXX3+dJ554gk9/+tN8+MMfHqm3OZrIpRQGO3NI8vi2Ch1b4zx//y4A5h9fzsrz6qe8gRQyJUwgVu9/S4RNvBhny+AWclqOCu9YYaMZGo/ufhSYPGpTUAvU+mtxSHbU5mhBisVwVFdjjOc7BeDwWu3hmgra5J8v3uOW4mqeh6lqJP40lBqXPajNH7aW6niEiLgTXZtma7goInpcaFkdc3APFEcXOMfqA8w7xkqfvvTwbgzjwIuLnR4ZpaBRKh56M29GhvVlivx0vXUvunB5Fcc3RMiXNAQB5sd8uOSDn44aZkbi5qabbuKNN94Y+e9NmzZxzTXX8Pa3v53rrruO+++/f1T7r82hi9fr5amnnqKhoYH3vve9LF26lI9//OMUi8WRSM7VV1/Nd7/7XX74wx+yfPly3vnOd7Jt27Zx1wsEAtx2222ceOKJrF69mra2Nv72t7+Nm97yer088sgjxONxVq9ezeWXX87b3vY27rjjjjl9z4ci+9oquH1jP9C7tiV57i+7ME2Yd2wZJ1zQMKWwyadLCKJIrM6PLzT3wmagMMCWwS0ohjKmxmaYZ7ueJakkibginFw9foF+ppQh6LSjNkcbgiDgqK9HcLvR9xkHMQpfGYRqreF+k3QnCYJA9H0XgyCQe+E1ijut+jQjdhxa+WoEDIK7f47HrU17sJ/odWNoJmoiC8mOMfU/x55bh8MtkeorsOOlA68JlGQRQzcoZA+9rqnhdNRDm3royyhUBFx8dM08dMNKRzVGfZT5D605ZoI5gz626upq7r//fk488UQAvvzlL7N27VrWrVsHwH333cdXv/pVNm/ePDe7nQXS6TShUIhUKjUmHVMsFtm1axdNTU243Qe3R99m5hxu/35KQaN/TwZV0cYVIT07Uqz/w3YM3aRhWZSTLmmaMlydT5cQJUvYvBV+NT25HrYltiEIAhH3+CPXTdPky+u+zM7UTq5YfAXvaR5r0WKYBr3ZXpbGllLrr53rbdscgii7d6O0tCBXVSOMV/OnKTDQYqWofJMXmw/c/Ueyz7yMq6meqi9+whLcSgr3C19G0PLkG95Pu/OdOF0m0wk2GKUSZlHBXeFBrFtuCa192PFKPy8/vBvZKXLhJ1aMa5MyHYo5FUkWqV4YnjM7lJmSL2m8sifJq+1JbnvEavi45d0rWFkXpi9TJOx1cExtGOc4DRCzzWSf3/szo90kEolRaYO1a9eOGqm/evVq2tvbZ7hdG5ujj6lsFXrb0qz/oyVs6pZEWD0NYZNLKUgOkfKGuRc2pmnSle2iJd6CJEoTChuA1kQrO1M7cYgO3tYwfvddtpQl4ArYUZujGEd1NVI0ip6YYLaN7LLawwUJSpMPzwtf+nYElxNlVzu5F1+znnSFUBdcAYCn488E5R4UZXofgaLTiakZaBkNM90JpdERpvkrY0SrfWglg1cf75hglalxuiVr0Oab7L6aLYbTUX3pIj9f3wbAO46pZmVdmKyiIQkC82P+t0TYzJQZ7aiyspJdu6x8W6lU4uWXX+aUU04ZeT2TyYzpcLGxsRmNVtIZ7MpRyJbGtVXob8+w/vfbMTSTmuYwJ7+radJvcaZpkk+VcDglyusCeOa4W8E0TToyHbTGW3HJrlFzbMZjuP17Te0agq6x37ZM0ySn5qjx1eCSDq3Qts1bh+h04qxvALWEOdEkcnd4b4HxJNOL5VCA0AVWg0vij3/HGOr/1qtORw8vRTBKxLp/gSRaxprT2l/Qh5YrYSQTkOoelR4TRIETLmwAAdq3xOndNY4x6HSuIYmYBhSys2OR82YZTkc9uKmH/qxCVdDN1ada6ahUoURjmZeI79DojtqfGYmbiy++mOuuu46nn36aL33pS3i93lEdUq+99hoLFiyY9U3a2BwpjNgqpBT84bEDuwY7sqz73TZ01aBqfpBT3j1/3EF+wwwLG9klEasP4PbP7ZcLwzRoS7exLbkNr9NLwBmY9PiBwgDP9zwPTFxInFEz+B1+yr1T20fYHNnI5THkquqJJxeD5Rzuq5hyenHwvNORIiH0RIr0Y9YIAgQBddFVmKIDR2oz5crTKCVhWq7hoiyDKKBmDMuWIT96j5EqHwtPsCaFv/z33ejagY2tcLhFckkFXT+4Yy9yitUd1dqb4bEtln/dv7+tGY9TYiCrUBl0Uxc9dDuJZyRubr75ZmRZ5qyzzuLOO+/kzjvvHDUY7mc/+xnnnz/+1FEbm6OdEVuF+Pi2CvHuHE/9bhtayaBiXoDT3rtw3EF+wwwLG6dHprzeP25B8myiGzo7kzvZkdxB0BXE55h6GvmjbY9imAbLypbRGBw7tdo0TXKlHDX+GtzyoV8nZTO3CKKIs6EeHE6MXG78g0QZwvWWyWZxggJkQHQ6iLzH+jxKPfIUWioDgOmtRJt3KQChzt/iEdIopWkWF/u96LkielaBVAdooyMsK86sweWTycYVWjf0TGvN/XG4ZUqKflCdwofTUb3pwkg66l0ra1hRGyJTVHFIVjrKMckXr4PNjHYWi8V46qmnSCQSJBIJ3vOe0YWBwwXFNjY2o5nKViHZm+epe1rRFJ1YvZ81ly1EckwubHJJS9jE6gO4vHMrbFRDZXtyO7vTu4m4I9MaMKnoCo/veRyYOGqTVbP4HD47amMzghQM4qyrQ0+lMCfq13b6IVwHWtFqEZ8A3+pjcTbVYSolkn95dOR5re58DF89gpajKv5LNH26reESglNGTWuY2Thkeke97nDLHPe2egA2P9NNNjHz0SiiKCBwcFNTvZkiHckCD7zaw2CuRHXIzYdPaUTTDdJFlXkxH6E5vue8WQ5IdoVCoVFj8YeJRqOjIjk2NjZT2yqkBwqs/W0r6pBb9+nva0Z2TtzCYZomuUQJt99BeX0A1zizcWYTVVfZnthOe7qdqCc67QjLuo511kA/bwWrKleNed00TbKlLDW+mhlP47Y5snHU1iCFguip1MQH+SrAX2XNnpkgrTTSGg5kn30FZY9lNosoUxqyZnDHNxAtbZx+9MbrwSgU0ApAtsuq/9mH+mVRyhsDGJrJK4/uOSBjTYdLIp8uoatvfWoqp2js6M/R0pPhHy19CMBnz1uE2yHRn1WoDnmoDR/6f6+HbkzJxuYIYTJbhcxgkbW/aaVU0IhUeTnjiuZxJxQPYxom2aSCO+AgVucfd+jfbKLoCi2JFjqzncS8sQldvMfs0zR5qM0qJL5g3gVjhvoB5NQcXtlrR21sxiC6XDgbG0EpTlxcLIhW9MYZGOPcvS/u+Q34TjwGTNNyDR8SG2awCa3u7QDEeu7C1IuMZ3E19rIioseNlsxj5HOQ6gRzrwgRBIETzm9AEAV6dqTo2jbx3ibC4ZZQizrF/Fs788YwTHYN5OhNFfjF0LC+S4+rYVl1kFRBxe2QaCr3IR/C6ahhDv0d2tgcxkxmq5BNFFn72xaKOZVQhYczP7BoUl+ZYWHjDbgorw/MuQdNXs2zNb6VnlwP5d7yaU8N1g2dn7/+czoyHbglN+fUj2/fkSllqPZXHzb2JjZvLXJ5OVJlJVp8gsnFYNXdhBtA160U1QRE3nM+gkOm2LqL/KtbRp7Xmt6D4Y4hlQapSd1HYbqD/TxujFIJLY9lqpkbGPV6MOZh8cnW2JRXHm1HK83MEFMQBATBmlv1VtKbKdKZLPDXV7uJ51Vqwx7+6ZRGVN0gV9JoivkIug/tdNQwtrixsZkj8unShLYKuZTC2t+0UsioBGNuzrpy0aRRGMMwyaUUfGEXsXr/pNGd2SCn5miJtzCQH6DSV4ksTk9I5dU833zhm/x9tzX6/oNLPziueMmpOTyyh0rv0We3YTM9BEnCVV+PIEsY+Unm2nijQ9OLUxMWzshlEYJvWwNA4g+PYGpDxbqSC3XRVQD4Bx7Dp+xAnWYdr+j3oiWzGCXDKi5WR4urpWuq8YacFNIlNq/vnt6i++D0yBQyKuoMhdGBMpyO2tKdZm1rP6IAnz2vGZcs0Z9RqA65qTkM0lHD2OLGZtYQBIE///nPALS1tSEIAhs3bjyoezpYFLMqAx1ZxrNVKGRKrP1NK/l0CX/UxVlXLp60INjQDXJJBV/IRazWj2OSepzZIF1Ks2VwC4liYlwDzInoyfXwlfVf4bX+13BJLq5ddS3nzxu/ezKj2FEbm6mRwmEctbXoqeQktSsCBGvBE4XCxO3hoQvPRAr60foHST+5YeR5I7oCrfJUBEyq+39KsWhMrzXc6cTUdau4uJiG7OjuKNkhcfzbGwBofb6X9EBh6kX3Pd8poioaSm7uU1PD6aieVIG7nmkD4D3H17KkKkgyX8LnkmiK+ZAOkanJ08EWN0cIH/nIR4ZCmQIOh4Ompia++MUvUixOHKq1mRuUgsZAZxZd08eMYS9mVZ78TYslVsIuzv7g4kln0xi6QS5Vwh9xUVbnn7TQeDZIFpNsHdxKppSZkbDZMriFr6z7Cp3ZTqLuKDeediMnVZ807rF5NY9bdttRG5tp4ayrQ/T7MSYrLpYcVnpKnHh6seh2Eb70PACSDz6Bnt3baq4u+ACmw4+j2EFl+kFK6vQ+xKWAHz2VxtAckOm2okf7UNMcpqY5jGmYvPzI7hkVFwuCgCQJ5FJzb0bdky7SlSzwl1e6SORV6iMePniSlY4qqDpN5X4Ch0k6ahhb3BxBXHjhhXR3d7Nz506+853v8JOf/MRuzX+LmcxWQcmrrP1tC9m4gjfo5KwPLprUg2ZY2ASibmK1gTHFyLPNYGGQLfEt5LU85d7yKQ06h3my/Uluee4WMmqG+aH53HL6LTSFmiY8Pq2kqfJWTWtOjo2N6HbjmjcPo1DYm04aD3cIQvWgZMeYWw7jP/UEnPXVmIUiyfv/sfcFZwB14ZUARAf/jJDrnlb0RpAlkETURM7aW7pzzOTk486rR5JF+vdk2fP6JPVD4+D0yBSzc+sUnlM0dg7k2NSZ4untA0PpqEU4JIH+bJGasIfq4OE3g8oWN0cQLpeLqqoq6uvrefe73815553Ho49asx0Mw+DWW2+lqakJj8fDypUr+f3vfz/q/DfeeIN3vvOdBINBAoEAZ5xxBjt27ADghRde4O1vfzuxWIxQKMRZZ53Fyy+//Ja/x0OZyWwVSgWNtb9tJT1QxO13cNYHF03q2K1rBrlkiWCZm7Ja/6Qzb2aD/nw/W+NbUQ112sLGMA1+veXX/PjVH6ObOqdUn8JXT/sqUXd0wnPyah6X7KLSZ0dtbKaPXFGBXFGOlphCHPgrwV8xYXpKEEUil1szlzJPv0Cpa6+Lt15xCnp0BYKpUTP4M4rF6UVZRL8XPZNFVyRranGuf9TrvrCLpWuqAXj9qU6MGUwelp0SWkmnOEepqb3pqDx3P7sbgMtOqGNRZYBkQcXvctAU8x0yJp4zwRY3U2CaJkY+f1AeBzIfYZjXX3+dZ555ZmTu0K233srdd9/Nj3/8Y9544w0+97nP8U//9E+sXbsWgM7OTs4880xcLhf/+Mc/eOmll/jYxz6GNvRNKZPJcPXVV7Nu3Tqee+45mpubufjii8lkMhPu4WhC16zpw+PZKqhFjafuaSXVV8Dlkzn7g4vxRyb+JqRrBvl0iWC5h2iNf9IpxbNBT66HLXGrg6TMM7nb8jBFrci3X/w29++4H4D3Nr+Xz5zwmSm9odKlNJXeSvxO/5vbtM1RhSBJOBsaEAQBozBJ7crI9GIPFMf3d/Isno9n5VIwDBJ/eHifiwiozVdhik48+RYCybXTHuwnupyoAylM5KHi4tF7XLS6EpdXJp8u0bF1ctuI/ZGdIrlk6U19HkzEcDrqjy93kSqoNEa9XHlSA4qmU1R15pf78Lnmtitzrjg8d/0WYhYKtJwwdgDZW8Hil19C8E6/4PKBBx7A7/ejaRqKoiCKInfccQeKovD//t//47HHHuPUU08FYP78+axbt46f/OQnnHXWWfzgBz8gFApxzz33jJifLlq0aGTtc889d9S1/ud//odwOMzatWt55zvfOQvv9vBl2FYhM1jEFx5tq6AqOk//bhuJnjxOj8xZVy4mUDaJsFGHhE2Fh2i1D2kO50mYpklXrovtie04Jee4ppbjMVAY4FsvfIvd6d04RAefPPaTnF53+pTnFbQCTtFpR21sDgg5EsFRW0uprQ3B7Z44uujwWfU3Ay3W9GJ5bK1I9L0X0Pl6K4U3Wim8sQ3P8mYATE8Mtem9OHfcQ+XgPez0HYcrGJ5yb4LXg55IoWUDOPwqpLsgugCGtig5RJpPrOD1p7rY+lwP9cui0077Ot0ySl6lVNBmdRL5cDrq1fYkz+wYHElHyaJAV0qhIeqhMnD4paOGsSM3RxDnnHMOGzduZMOGDVx99dV89KMf5bLLLmP79u3k83ne/va34/f7Rx533333SNpp48aNnHHGGRO6uvf29nLNNdfQ3NxMKBQiGAySzWbZs2fPW/kWDzkms1XQVJ11921jsDOHwy1x1pWLCJVP3EqpqTr5TIlwpYeyORY2hmnQnmmnNd6KW3ZPW9hsT2zn+nXXszu9m5AzxFdO/cq0hA1AqpiiwltB0Dm9a9nY7I+zttYqLk5P4brtL4dAtZWeGifi4aiMETz7ZADiv38Ic5/pfXrdeRiBJkSjQGX/L5mszGcYQRAQPR60eBIDr2XLUBwdoVlwQgWSQyTVV6Cvbfqu4ZJDRNdMCtnZS00Np6O6k3nufs5KR73/xHoWVvhJ5FVCHpmmmP+wTEcNY0dupkDweFj88ksH7dozwefzsXDhQsAyMV25ciU//elPWbFiBQAPPvggtbW1o85xuaw0gmeKa1199dUMDg7y3//93zQ2NuJyuTj11FMplQ6e/8nBxjRNUsO2CoHRtgq6ZrD+99sZaM8iuyTO/MAiwpUTR+G0kk4xqxKu9BKpmtsct27o7M7spi3VRsAZmHY79jNdz/CjjT9CNVQaAg18YfUXpj1duKgVcUgOqnxVb2brNkc5oteLq6GBwhubEf1+hHFsgCwECNVBKQuFJHgjY44IXXwO2ec2onb3kVn3IsGzTh46VaS0+CO4XrqJQO5FUoMvY1aeMPXePC60eAotlcMRcSAkO8EVsFJlWMXB81fG2PZiH1uf66GyKTTt9+1wiuRTJYIxz6zcG3rSRToTeX7/UieZojWc7/0n1lNUdUq6wZLqEJ457syca2xxMwWCIMwoNXSoIIoi//mf/8m1115La2srLpeLPXv2cNZZZ417/LHHHstdd92FqqrjRm/Wr1/PD3/4Qy6+2PJpaW9vZ2BgYMxxRxPpwQLxYVuFfW4EumbwzB+209eWQXKInPn+ZqLVE3cGaSWdQlYlXOUjUumdU2GjGRptqTYr8uIOTcvTyTRN/rjtj9zXeh8Ax1ccz2dO+MyM/KDSSppqfzUh1/Rv6DY24yFXViL39aHH48jlk4hr2Q3hRujbYg3Yc4xOsUg+D+F3nkv83gdI3v84vtXHInmt32nTX49WfyGOPQ9SNXgX7aHFyO6pu/tEvxctnkQK1iIV45Dtg2DNyOvNJ1Wy/aU++toyJHpyRKqm1zHo9EgUMlZqav+5WTNlOB21sT3Fhl1xJFHgc+c1I4kCfZki88p8VAQmr507HLDTUkcw73vf+5AkiZ/85Cf8x3/8B5/73Oe466672LFjBy+//DLf//73ueuuuwD41Kc+RTqd5gMf+AAvvvgi27Zt45e//CUtLS0ANDc388tf/pItW7awYcMGPvShD00Z7TmSySaKxLvG2ioYusFzf95Jz840kixyxvubKaubuHhWVXSKOY1olY/oHAsb1VDZkdxBW7qNiGd6zt4lvcT3X/n+iLB5x/x38IXVX5iRsFF0BUmUqPZVH/DebWyGEWQZZ0MDmCaGMsUMGE/EiuAUU2NatAECZ67GUVWOkc2TemjtqNe0xndheCqRtSThnvumOdjPgWmaqIMpTNkLqS4o7Z2n4wu5qF9qdRO2bOidaJmx60oihmlSzLy5SPlwOqorkeeXQ+moD6yupynmJ5ErEfY6mRfzTbse6FDmkBA3P/jBD5g3bx5ut5uTTz6Z559/flrn3XPPPQiCwLvf/e653eBhiizLfOpTn+K2227jS1/6El/5yle49dZbWbp0KRdeeCEPPvggTU3WPJKysjL+8Y9/kM1mOeuss1i1ahV33nnnSBTnpz/9KYlEghNOOIEPf/jDfOYzn6GiouJgvr2DxkS2CoZhsuGvu+jalkSUBNZcvpDyhsCE66hFDSVnGWaGK72jCpFnm5Jespy9M+2Uecqm7GoCa6DfTc/exDNdzyAJEp849hN8eNmHpz3Yb991yj3ldq2NzawhRaM4amvQ44NTHxysAW8Z5Md2KQmSROSyCwFI/+NZ1P591pMcqIs/AkAk/QRCsnV6ewv4MFJp9CKgFSyBs48yWnyKlZrt2BInl5z+gD6nSyKbKs2olXx/htNRv3uxg6yisaDcx+Un1FEo6WiGyfxyH+45nqf1ViGYc9FfNgPuvfderrrqKn784x9z8skn893vfpf77ruPlpaWST8829raOP3005k/fz7RaHRk7P9UpNNpQqEQqVSKYHD0zbZYLLJr1y6amppwuw/fKvGjlbfi36+YVenbk8E0jFED+EzD5PkHdrHnjTiCaAmb6gUTp2BKRY1SUSda7SNU7pnTb0pFrcj25Ha6s91U+Cqm5RO1O72b256/jcHiID6Hj2tXXcvy2PIZX7ukl0graVaWryTsDh/A7m1sxkfP5ii8uhFECSkw8ZcIAJQ09G8BQQLX6EiqaZr0fv8uipu34z1+GRWf/OCo1x0tv0DufgrFUU1P802I8sSDN0f2ls4iuF24GyoR1CxULLUE1hBP/baV3rY0C1dVcPz5DdN6v4Zhkk+XqJ4fmnT450RkFY2NexI8vW2Anzy1E1kU+M77j6OhzEt3qsD8mJ/mSv8hHbWZ7PN7fw565Obb3/4211xzDR/96EdZtmwZP/7xj/F6vfzsZz+b8Bxd1/nQhz7E1772NebPn/8W7tbmaGYiWwXTNHnxod0jwubU98yfXNgU3jphk1fztMRb6M31TtsA86Xel7hh/Q0MFgep9lVzy5pbDkjYgBW1iXlidq2Nzawj+X04GhowMplR3U7j4gpCqAHU/JjpxYIgEL3sIhAE8q9spti6a9Tr6vz3YThDuNRufD33T2tvot+Lkc2jZYogyZBqB31vt9Nw9GbXawMo+elNHxZFAUzIH0DXlGGYtA3k6Ezm+dUGKx115UkNzIv5GMyWiPqcNJR5D2lhM1MOqrgplUq89NJLnHfeeSPPiaLIeeedx7PPPjvheTfddBMVFRV8/OMfn/IaiqKQTqdHPWxsZoqq6OPaKpimySuP7KHttQEQ4OR3NVG7aGxnxjBKXkNVdMpq5l7YZEtZtsa3MlAcoMJXgSROHm42TZP7d9zP7S/cjqIrrIit4OY1N1PtP7BamZJeQhAEavw1R9RN0+bQwVlVhRSNoiemMRjPX2FNMC4kYL98hbO2ksAZq4Gh1vB9p/c5fKjNHwKgLP4gQq59yksJoojocqD1xzEFrzVQML3XWLNiXoBwpRddNdjxct8kK+23T7dEPqWgazNLTfWki3TEc/zuxU5yis7CCj+XnVBHvqRhCibzy/1HTDpqmIMqbgYGBtB1ncrK0UO9Kisr6enpGfecdevW8dOf/pQ777xzWte49dZbCYVCI4/6+vo3vW+bowtN1RnozFLIjbZVME2TVx9rZ8cr1rj1k97ZNFIsOB5KXkVTdcrq/ARjcyts0qU0W+JbSCnWbJmp6mQ0Q+N/Xvsffr3l15iYnNdwHteddN0BTxLOlrIMFgap8lURdoUPaA0bm6kQHA5cjQ1g6FMXFwuS5T3l8IIy1oQzfMnbENwuSnu6yD63cdRrRmwVWtnxCOiUdfwczKnFheD1YBQUtETKagnPdlm+V1jRosUnW59721/qQ1enJ1Ycbgm1ODM7hqyisbM/y0t7kry0O4EsCnzuPGtAayJvTSWO+Q//7qj9OehpqZmQyWT48Ic/zJ133kksFpvWOV/60pdIpVIjj/b2qVW3jc0wumYQ7xqyVQi5RgmbTU92su1F61vXiRfPo3HFxNYFxZyKrpnE6gIEy+ZW2CSLSbYMbCFbylLuLZ9S2GRKGb7+3Nd5ov0JBASuWnYVHz/m49NKYe2PaZoMFAZQdIXFkcU0h5vtqI3NnCLFYjiqqjCm8p0CS9iEG63JxdpoMSQFfIQvPhuA5F8exSju87ogoC76J0zJg0fZgafv8SkvJQgCos+NOpjE0ETQSpY1w5AwqlsaxRtyouQ12jZNb6yGIAgIAuSn2TU1nI5qj+f59QZr4Oo/ndJIQ9TLYFYh5nfSED0yDWwPqriJxWJIkkRv7+iWuN7eXqqqxg772rFjB21tbVxyySXIsowsy9x999389a9/RZblkWm7++JyuQgGg6MeNjbTYZStQmi0rcLmdV20PGdFF0+4oIGmlROL7WJOxTRMYnV+AtG5LVQfKAyweXAzRaM4LQPMzmwn16+7ni3xLXhkD1886YtcPP/iAxIkqq7Sm+vFK3tZEVtBfbB+ylSYjc2bRRAEHA0NCG43ejY79Qm+MquDqpAcM704eM6pyLEIeipD6u9Pjz7PFUGdfzkA0b77EJWpO7VEtwtUDW0wjumJWKaaGeu+IYoCi06yojctG3oxjen19jjdEoW0ilaaos4I6B5KR937Ygf5ks7iygDvPq6WnKIhijC/3I9zjr3rDhYH9V05nU5WrVrF44/vVcGGYfD444+PeCDty5IlS9i0aRMbN24cebzrXe8asR2wU042s8Vktgpbnulm87puAI47r54FJ0zc1VfIljANiNUFJjXLnA368n20xFvQTZ2YJzalQNnUv4mvrPsKvfleyj3l3HTaTRxfcfwBXTun5hgoDFDjr2FFbMWkzuA2NrON5PfjqK/HSKdG18uMiwDBWmsGzn7u4YJDJvLeodbwR9ejxZOjXtdrzkILLkQ0FcIdd41r7TDmagEvWjyNUSiB02cVFw+ZejYdG8PplsglFTpbk5MvNITsktBKGsXc5IXIWUVjV3+WF9oSbGxP4pREPnue5aGVLJRoLPMR9c286+pw4aBLtmuvvZY777yTu+66iy1btvAv//Iv5HI5PvrRjwJw1VVX8aUvfQkAt9vNihUrRj3C4TCBQIAVK1aMOGDb2LwZhm0VUn2FMbYKrc/38PraTgCOOaeW5tUTm0AWMiVAIFbvxxee25x2T66HrfGtAEQ9UwuLv7f9nVufv5W8lmdxZDG3nH4L9cGZfzkwTZPBwiBFrciiyCIWRRbNaMCfjc1s4aiuRopEpldcLLssc03EMQ7e3uOX4Wqeh6mqJP786OjzBBFt8UcwBRlf7lXciQ1TXkp0ODAxUQfi1mA/XYfkHtA1ZKfEglXWl6Otz3VPy/lbEAREUSCfnrjGyDBMdvXn2D2Y4zfPW6UYHz6lkbqIl4GsQnnARX308Ju8PxMOuri54ooruP3227nhhhs47rjj2LhxIw8//PBIkfGePXvo7u4+yLu0OZrIDBaJ9+ZxeeVRtgrbX+rj1cc7AFh+Rg1LTpm4iyifLiGIIuX1AXyhuRM2pmnSnm5na3wrDskx5SwZ3dD5xeu/4Gev/wzDNDij9gyuP+X6A2rV1gyN3lwvHtnD8rLlNAQb7DSUzUFDdDpxNjSCWsJUp1Fw6w4PTS9Oj5peLAgC0cut1vDc86+i7OoYdZrpq0FteCcAke5fIWpTp8KkgA8jmUFPZyyfq0Ic0h1gwsJVFYiyQKI7z0D7NNJqWD5VhaxKqTh+9KY7XaQzkePeFzooqDpLq4NcsrKGbFFDlgQWlPtxzKEx76HAIfHuPvWpT7F7924URWHDhg2cfPLJI689+eST/OIXv5jw3F/84hfTHuBnYzMV2USRwa7sGFuFnRv7eeXvVkHektOqWLpmEmGTUpBkkfJ6/6i28dnGMA32pPewPbkdj+yZcgJwXs1z2wu38XDbwwB8YMkH+Nfj/hWHNHOvmryaZyA/QJWviuVlyynzTFxMbWPzViGXx5CrqtEGp+l7F6gCXznkRxcjuxpr8Z18HADx+/42JqKiN16M5qlF1jMEu3475WUESQKHbEVvDBPcIWtycSGO2+dg3jFWzd5wHd9UyE4JraSPOyNnOB313K4Er3WmcMoin31bsxWRLpaYV+Yl7D3ysxyHhLixsTkUmMhWoW3TAC89ZA2+WnRSJSvOrB23nsU0TXIpBckpEav3H9AU0emiGzpt6Ta2J7fjd/qnbNnuzfVyw/obeLX/VZyik8+t+hzvXvjuGRcOm6ZJvBAnr+ZZGF7I4ujiabuK29jMNYIo4myoR3C6MHK5qU8QZSs9JbuhODpqEnn32xGcDpSde8i/9PqY87TFV2MiEEiuw5V5Y+pL+TwY2Tx6JmddTxKt9JRaZPFQYXH3jhSp/sIUK1lIskgupYwSXoZhsrM/y+7BPPe8YH0Zu/rUedSEPQzkFKqCbuoiR8ffqy1ujhA+8pGPDLUJjn5s376dp556iksuuYSaGmuYmh3pGksxqzLYmQXMUa677ZvjvPBgG2CFj489t25CYZNPqzicEuV1ATz+uRM2mqGxI7WDncmdhN3hKcXFlsEtXL/+ejqyHURcEb625mucXH3ypOdMdN3efC8uycXy2HIaQ40H1C5uYzOXSMEgzro69NR0iosBpx/C9ZYPlLY3nSWHg4QuOAOA+B8fwdgv1WWGF1KqOheASMfPEYzJ5+wIooggD0dvDCstpmQg1YE/4qJ2sTX8s2XD9KI3Lo+MklMpFfem1LqHvKN++/weiqrB8pog7zy2mnRBxSmLNJX7kY/wdNQwR8e7PEq48MIL6e7uHvVoamoil8uxcuVKfvCDHxzsLR6SDNsqaOpoW4WOlgQb/roTTGg6LsZxb6+fWNikSjhcErH6AG7/zNM800XVVbYnt7MnvYeoJ4pbnrwDa237Wm557hYypQzzQ/P5+ulfpynUNOPrjqShvFWsiK0g5pnenCkbm4OBo7YGKRRET40d1jcuvgrwV1u1MPtkoIJvPx0pEkSPJ0k//syY04yF70V3RHGo/QR7/jzlZUS/24repHOAYHVsZXsg2zcy1G/PG3Hy6ann2EgOEU01UIYG+g2no57dEef1rjRuh8hn37YI3TDJKBpNZT5Cnrm7Nx1q2OLmCMLlclFVVTXqIUkSF110Ebfccgvvec97DvYWDzlURWewc6ytQte2JM/9eSemCY0rylh1YePEqahkCadHprzePyrqM9uU9BKtiVY6Mh1TOnsbpsFvt/yWH736I3RT56Sqk/jqaV+dVifVvuybhloQXmCnoWwOC0SXC2djIyjF6RUXCyKE6ywPqmJy7zpOJ5F3nw9A6qG1aKnM6PNkD0rzPwEQGHgYR75tistICLKENpiwam8kh5WiSrZTVg7lDX5Mw2Tbi72TrjNyeadINqmgaQY7+7PsGshx74tWd9RHTmuiKuSmP6tQHXJTe5Sko4axxc0UmKaJqugH5XGQDduPeDRVZ7ArSyE72lahZ2eKZ/+0A9MwqV8aZfU75k0qbNw+B+X1AVzeuRM2Ba3A1vhWunPdlHvLcUoTp72KWpHvvPQd/rLjLwC8Z+F7+Oyqz04qhsZjuBtqOA01LzTPTkPZHDbI5eVIlZVo8WlMLgZLZITrrVZtrTjytG/1sTgbazGVEsm/PjbmNKHiOIqRkxAwiHb8DMzJh+uJfg9GNoueGarxcQWslFiyncUnlQOw85V+1Ak6ofbF6ZZR8irtfdmhdFQ7imZwbF2Ii1ZUkSqoeJ0S88t9SOLRNSncvlNNgVYy+J9/X3tQrv2J/z5rVMfOVDzwwAP4/XsLSy+66CLuu+++udjaYc+wrUIuqeAP77VV6NudZv0ftmPoJrWLw5x0ybxRk4mHMU2TXKKEO+AgVufH6Z67P6W8mqc10cpgYZAK7+QGmIOFQb71wrdoS7chizKfPPaTnFF3xgFdM6WkqPJVMT80347W2Bx2CJKEq74ePR7HKBQQPdOYv+Qtg1AtJHeDzwmiiCCKRN93MT2330n2mZcJnnMKzrrR3ZL6oivRX3wDZ3E3gf5HyFRcPPG+RAkkES2eQAr6rXuPrwxy/VSV+wnG3KQHiuzY2D/puAmwiorzRZ2u9hTru1Js7k7jcUh85txmdMMkp6gsrw0RcB896ahh7MjNEcTwpObhx/e+972DvaVDkolsFQY6Mqy7bzuGZlK9MMQpl84fNZl4GNMwySYVPG+BsMmWsmwZ3GIJmymcvXckd3D9uutpS7cRdAb5yilfmbGwMU2TeHFvGmpJdIktbGwOW6RwGEdtLXoyMc1IuGBZM3iiVv3NEO6FjXhXrQDTJH7fQ2PWEj0hCo1XABDs/ROSMnlaSfR5MdJZjMxQR5cggTuIkO5k8QnWSIdtL/RN6f5tmNBfLLGzK8vvXrLSUR9dM4/KoJu+TJHqsIfq0NE5VNOO3EyB7BT5xH+fddCuPRN8Ph8LFy6co90cGYzYKgyMtlWId2V5+t5t6KpBZVOQU9+zYFxhYxgmuaSCN+giVuefUWRtpqSUFK2JVjKlDBW+yZ29n+t6jh9s/AGqoVIXqOOLq79IhXdiW4jx0AyNgfwAfoef+WXzKfeWv9m3YGNz0HHW1aH192OkUkjh8NQnSE6rPbx/C5Ty4LTEfeQ9F5B/dSvFlp0UXtuKd+XSUaeJdWso9j6HO7eZaOcv6G/6IkwwakGQJBAF1HgSMeCzojeyB9QCDZUJXvc7KGRV9myO03TsxMX7g1mFuFLid1u7KWkGx9WHuXB5Fcl8Cb9LZn65/6hLRw1jR26mQBAEHEMD3d7qh+2mPLuYpkmqf8hWwb/XViHRk+Ope7ehlQzKGwOcdtmCUZYLwxiGST6l4Au7iNXPrbBJFBNsHdxKTs1R4Z1Y2JimyR+3/ZHvvvxdVEPl+Irjuem0m2YsbApagf5cP5W+SlaUr7CFjc0Rg+h242psxCgUMLWp61gAa8heqB6U7Mj0YkcsQuhtpwEQ/8PDY9YSRAGl+SoMwYE7uxlvYv3k+/L5MNIZjOw+83g8EUQ1RfNyK+7Q8lzPhBGnfEmjI1ngma4UO1IFPLLIp89diKqbFFSd+eV+/K6jN35hi5ujgGw2O5KqAti1axcbN25kz549B3djbzGZwSLxntG2Cqm+PE/9thW1qFNW5+f0yxciO8aKFkM3yCUVfCEXsVo/DufcCZvpOnuX9BJ3vHIHv2v5HQAXNV3EF1Z/YcZppEQxQbaUZX5kPouji/E5fG/6PdjYHErIFRXI5eXTLy4G8FeOmV4cuvBMxIAPrW+Q9Nrnx5ziDFeQqXo3AOHu3yCqE7eiC7KECWjxFOZI/7nVHj6/PonsFMgMFunePnYNw4TOZJHdiTx/abFSYB9cWkOZx0F/tkhdxENVcG6Neg91bHFzFPDiiy9y/PHHc/zxluPztddey/HHH88NN9xwkHf21pFNKMS7c6NsFdIDBdb+tpVSUSda7eOM9zeP8pIaxtANcqkS/oiLsjr/uMfMFr25XrbGt2JgTDpLJqkkufm5m1nftR5JkPjnY/6Zq5dfPWnqan90Q6c324ssyCwrW0ZTsAmHePQVHtoc+QiyjLOxAUEUMArTmwBsTS+ut9JFRasFXPS4ibzrPABSD/4DPZsfe615b0dxNSDpOcJdv578En4veiqDse86khOH28GCZkvwjDfUbyBbpDdV4J7N3aiGybGVAdZUBhmMFwm4HcyL+RCP0nTUMLa4OUKYzGPr7LPPxjTNMY/JPLuOJCxbhSyiJIzYKmTiRdb+thUlrxGu9HLGFc3jppmGhU0g6iZWGxg3qjMbmKZJd7ablkSLZdznnngezZ70Hq5fdz3bEtvwOXx86eQvcV7jeTO6XlEr0pfrI+aNsSK2ggpvhZ0GtTmikcJhHNU1MyguZmh6cYPVGj40vdi/ZhWO2iqMfJHkg/8Yc4rDJZNp+hgmAr7UBtzpjRMuL8oypmmiJ/aN3gDuIM0LCwgiDLRnGezYaw2RL2l0Jous60iyM5HH65C45oQGdNOkkC2xoNyP13n0pqOGscWNzRHNeLYKuaTC2t+0UMyqhMo9nPmBRaO8pIbRNYNcskSwzE1ZrR/JMTd/LqZp0pHp2Ovs7QpPeOxLvS9xw/obGChYppU3r7mZFbEVM7pespgko2SYH5nP0rKlU/pS2dgcCQiCgLO+bqjWJT39E30xCAxPLzaHWsMvAiCz9nlKPf1jTnGXN5CKXghApPMuBH3iaJHo96Al0xjZfY8R8JRFaWy06nqGozfD6ahd8Rx/bbXSUVetrCXqcZLVdCKiSNk497KjEVvc2ByxjNgqlPbaKuTTJZ78TQuFjEqgzM2ZVy7C5R1f2OTTJYLlHqK1/nELjGcDwzTYnd7NtuQ2fE7fhM7epmny4M4Huf2F2ynqRZaXLeeWNbdQ46+Z9rV0Q6cv14ckSCyL2Wkom6MP0evF2dCIkc9h6pMP2xtBECFUZxUZF5IAeJYswHPsEjAMEn94eMwpkgRa06WU5HJkNU6o5w8T78nhwNQN9GRydPRGlFl8jHVv6mxNkhksjkpHaYbJ8VVBzmiIki6oBAIuoi4Xpfw039cRji1ubI5Ihm0VSgUNb8gSNoVMibW/aSE/VD9z1pWLxrVL0FWDfKpEqNxDtMaHNEdGc7qhsyu5ix3JHQScgQkLeTVD485Nd/LLzb/ExOTchnP50slfmlHEpagV6cv3EfVE7TSUzVGNo7ICORZDn0lxsey20lOmAao1vTh62YUgihQ2tVDYvH3MKR6fk0TdRwDwDz6GMzf2mGFEvxctmcHMF0c9H6wIUF1riZXNz3TSmSyytj1BW7KAzyHxzyc0oOomumlSH/XidonkU5MbeB4t2OLG5ohjX1sFX9iyVSjmVNb+tpVsQsEbcnLWBxePMsnc99x8pkS40kO0eu6EzbCz9670rkmdvbOlLP9vw//jH3v+gYDAVcuu4ppjrpmRDUJSSZJW0jQFm1gWXWanoWyOagSHA2dDA5gmhjIDIeCJWhGcYgoMHUdljMDZJwMQ//1DYyJBogiOqmWkAmsQMIl0/hyM8VvRRacDNB0tMbYzavFx1pee9s0JtneleaC1D4Crj6sj7HaQKpSoDLoJe5043TL5rIqq2NEbW9yMg+3pdHgyXCid6i+QS5bwhyxbBSWv8dRvW8kMFvEEnZz9wcWjTDKH0Uo6xYxKuNJLpNo/7hC/2UDVVbYntrMntYcyT9mEzt5d2S6uX389mwc345bcfGH1F7h4/sXTjrjohk5vrhcRkWVly5gfno9DstNQNjZSNIqjpho9PjizEwM1lkVDPgFA+B3nIHo9qF29ZNe/NOZwt8sk1/ABNDGAs9hBsO+vEy4t+D1oifSYbq5YlUwoamIasPnFHnTT5MSaEGvqI6QKKn63g+qQG0GwBr9qJZ1ibhpmoUc4trjZB4fDuvHn82Pb+2wOfXK5HIZmUkho+EIOBFGgVNR46p5WUv0F3H4HZ1+5CF94rIGkVtIpZFVCVT4iVXPXRqnoiuXsne0g5o1NaIC5aWATX1n/FXpyPcQ8MW5acxMnVJ4w7esMp6HKPGWsiK2g0ldpp6FsbIYQBAFHXT2i14ueyUx9wjCSw0pPyQ5Qskg+L+F3ngtA4v7HMQqj00qCAL6Qj4HKDwEQ6vsLvvhT4y4tOp2YmoYWHx29KeoG4Sbrb7cpIxCWJT5+fD0lzcQwTeoiXpxDNYGCIFh+UynlqP+SbpdV74MkSYTDYfr6rLCf1+u1PxAOA0zTJJfL0dvTh6C58IXdiJKIqug8fc82kr3W4L6zPrgIf3RslERVdJS8RrTKR7jSO65R5mxQ0ApsS2yjL99Hubd8wtTSY7sf42ev/wzDNGiONPMfJ/4HIVdo2tdJKSkUTWFecB6NwUY7WmNjMw6S34ejoQFly1ZEr9eyRJgOrqA1vXhwB8huAmedRHrtBrTeAZIPrSX63gtGHe50Qr7qZAbzuylLPUSk42cYko9CaNWYpUWfGy2ZRi4LI7rdGCYMZEr0eTUSokjEEPlYwEnQKTGQK1EX8RL2jP77dnokijkNtaiP2wV6tHD0vvMJqKqqAhgRODaHB7pmIKguwv4okmyFZp/+3TZrcJ9H5qwrFxEsG2sgpxY1lIJOtMpLqGLuhM10nL0N0+CXm3/JQ7seAuD02tP5xLGfmDC6M975/fl+3JKbpWVLqfTa0Robm8lwVlai9fahJ5PIZWXTP9FfCUoasv0IvnKil11I3w9/RfofzxA4YzWO8tFzqvw+k76qDyCbWULppynb80P6m/4Dxb+fP5XLhZYroCXSOKvdJPMlBrIKv9ipE3YZXFBw4u3WyQ52E4pWUzWUjtoX2SFRzKgUc6otbmz2IggC1dXVVFRUoKp23vJwIJsokupVcPudOFwSmqqz7r7tDHZkcbglzvxAM6GKsQW7paJmTSeu8REq98yZEMiUMrTGW0kqyQkNMPNqnu+9/D029m8E4IrFV/Duhe+e9p4UXSFeiBPzxJgfnj9hS7mNjc1eBKcTV2MDhU2bMBQF0TU2ZT3+iRKEGkDJgZLCc8xi3EvmU9y6k8SfHqHiE1eOOlyWIRg06NI+hsPM4c28TKztu/TNvw7V2zTqWNHnQU+kyAf89Gd1Huoy2JMzyPgEJB2UooSyq48FdZU4JqgLlJwiuaRCIOqesy9shzq2uJkASZKQphumtDloZBMK2QENl9uBwyWhawbP/GEH/XsyyE6RM69oJlI1tsW6VNBQS5btwlwKm5SSoiXeQlbNTihs+vJ93PbCbXRkOnCKTv71uH/llJpTZnSN4TRUQ7Bh2pEeGxsbkGIxHJWVqN3diFXV0z/R4R1yD29BkFWil19M19d/QP7lNyhua8PdPG/U4V6Pidcj0V7+rzQa/4U7t4XyXf9F34L/RHPvnVclulyUMkninQO0EuCvHVaH1ceWuKiOi3RsNkjsdhJY3Q2BAIwTBXa6ZZS8hlLQxh13cTRgFxTbHLbsb6tg6AbP/mkHvbvSSA6RM65oJloztu1ZyWuoik5ZjX9OhU28GGfL4BZy2sTO3i3xFr687st0ZDqIuCJ89bSvTlvYGKZBX64P0zRZWraUBeEFtrCxsZkhgiDgaGxEcLvRs9mpT9iXkenFCZy1lfjXWHU08fv+hmkYow4VRQgFDUSHk67af6fkmYekZyjf9S2k0uiurYIok+iJ8/PtGoYJaypkTqt04K3WESXIpiV6d8QhM9Z3CkCSRQzdOKq7pmxxY3NYUsyNtlUwdIPn/rKT7u0pRFng9PctJFYXGHOeklfRVMsBPBibO2HTn+9ny+AWFEOZcGDeUx1PcfNzN5MpZZgXnMctp9/CgvCCaa2v6Aq9uV4i7ggrYiuo8lXZ9TU2NgeI5PfjqK/HSKfGiJLJEYamF4ehkCDyrvMQ3C5Ke7rIPf/qmKNdTpOA30DRvfQ2fh7VVY2sxinf9S1EzbKEUDSdhCnyQNZHR8Ek5BD458UuiqqO0y3Q0GwlXFpaXZDugML4zuOyUyKXVDCMo7NryhY3NocdpYLGQMdeWwXTMHn+/jY6W5KIksCayxZS0Ti25qSYU9E1k1hdYNzi4tmiJ9fD1vhWTMxxnb0N0+C3W3/LDzf+EM3QOKnqJG487UbKPNMraEwraZLFJA3BBpaVLZtRJ5WNjc34OKqrkSIR9ERiZifKLog0AgKSRyJ04ZkAJP70dwylNObwgM/A4zHJ6yH6m76A5ojiULop3/VfmGqBRE6jNS9wf8G6h31ioYRfFimUNGJ+J8tWuhAE6OuGxIAByT2gj43QON0SpYKGkj86oze2uLE5rFAVnYF9bBVM0+SFB9to3xJHEAVOfc8CquaP/bAvZlVMA2J1fgLjtIPPBqZp0pXtoiXegiRKRNyRsfvQinz3pe/yl+1/AeDShZfy2VWfnXCQ374Md0MZpsHS6FIWhhfaaSgbm1lCdDpxNjSCWsKcaTOJOwzBOiimCZ5zMnJZGD2VIfX3p8deR4RQwEAQoCiW0d/0BXQpgLPQRrTtu6TyeX466MNE4Ax3jpNcBTJFlaDHScTvxBcQqZ8/HL3xQDEB6U7YL0AjSiKmAcWMLW5sbA5p9rdVAHjp4d3sfn0QQYBT3z2fmubwmPMK2RKmaQkbf2TuhE1HpoPWeCsu2TVuNCVeiPO1Z7/G8z3PI4sy/3rcv3LlkivHrcXZn5JeojfXS9gVZkVsBdX+6mmdZ2NjM33k8hhyVTXa4MDMTw5Wg68cUc0SeY816yb993XjWiq4XUPpKUVAddXQ3/R5DNGFv7CV2ODd9JYgLBl8NFak1B9HMjQqAi7kodTz4mOt+1/7Lo2cGoJ0F+TH7tnhFsmlFHR9Jqm2IwP77mhzWKBrBvGuHLlkCV/Iatfc+Gg7uzYOgAAnv2s+tYvHRkoKmRIgEKv3jzuZeDYwTIO2dBvbktvwOr0EnGNrfXYmd/LldV9mV2oXAWeA60+5njPrzpzW+ulSmkQxQX2g3k5D2djMIYIo4myoR3C6MHK5mZ0sytZwP9mFd8U8XAsaMFWVxJ8fHffwgM/A4zYpFAUUdxOt5f+GhsxxxsvcKv8v/6eyiM/joJQrUGaU8Dr3dkWFyyQqayUwoXXL0LWTe0ZMPYdxumVKRR0lN76n1ZGMLW5sDnkM3SDekyMzWLRsFQR47R8dbH/JGrR40juaqF8WHXNePl1CEEXK6wMjgmi20Q2dncmd7EjuIOgKjuvsvaF7Azc+cyMJJUGdv46vn/51lkSXTLn2SBrKMFgSXUJzpNlOQ9nYzDFSMIizrg49NdPiYsAVgHA9glYk+t7zAcht2IjS1jH2OhIEA9b6yZxKm7mAL+ufQjcF3i+v5d3aveRLGr6gD18hh6mNTi8NR292tagoBKCUg2S75Vw+hCAKCAIUMkefU7gtbmwOaUzDJNFXIN1fwBtyIogCrz/VSevzvQCsuqiRxmPGFuLmUwqSLFJe7x/XJHM2UA2V7cnt7E7vJuKO4JFHFymbpsmftv2J77z0HUpGiZXlK7lpzU1UeCumXHs4DRV0BlkRW0GNv8ZOQ9nYvEU4amuQQkH01PidSJPiqwB/Ja4KL76TVgJDreHjeD25XSYOt0Z/2uTPKS/3qidxk3ENAFXpR5lXeJRI1A8FBS01uk29okYiXCai67BjswreCGR7IDt6ur7DJZFPW12iRxP23dLmkMVy+M6T6s3j8TuQZJEt67vZ+ow12+H48xuYf1z5mHNySQXZKRGr9+MJzI2wKekltie2055uJ+qJjikILuklfrDxB9zbci8AFzVdxBdXfxGvY+yk5P3JlDLEC3HqA/Usjy2301A2Nm8xosuFs7ERs1iceXGxIEK4HlwBIhedguBwoOzYQ/7lN8YcappQ1Au0qgaPpKx7VW3lyewOXw5AU/ovlGWeRnQ70AYTmNpegSIIwkj0ZttmFd2Qwem1ojfKXjNQh1uybGbyR1dqyhY3NocsmcEi8R7L9FJ2Smx9rps3nu4CYOXb6li4anQExDRN8mkVh1smVh/A458bYVPUirQmWunMdlLuKx+TKkopKW557hbWda5DFEQ+fszHuXr51eP6Se2LYRr05fvQDZ0lZVYayiXNTTrNxsZmcuTycuSqSrR4/ABO9kC4HjngIXieNZQz8ceHMfYTSol8if5iibuTXkwEzgmqnODX2ek+h+7QRQBEOu/CW9qEkSugp0c7mNc1yXj9AqWiSVurCk4/6IolcAxLzAiCgCAK5FNHV2rKFjc2hyTZhGKZXrokHC6JbS/0sumJTgBWnFXLopOqRh1vmib5VAmHSyJW55+zkeN5NU9LooWeXM+4zt7t6XauX3c9rYlWfA4fXzrpS7y98e1Trjuchgo5QywvW06tv9ZOQ9nYHEQEScJVX48gSxiFwswX8JZBqI7Q6cuRQgG0wSTpx58Zebmg6vRnS9zXF6SnJBGTDa4MqRRKOg5JJF9zOdnoOQiYxDp+gkffhjqYwNT3Rm9EUWDRMdaXq5bXS5iGCd6o1TmV6h45zumRyWdU1NLRk5qy7542hxz5dInBrr22Cjte7mPjY+0ALDu9mqWnjfZ/sVJRJZwemfKGwJwJm5yaoyXewkB+gEpf5Rhh80rvK9zwzA30F/qp8lZx85qbOab8mCnXzZayxAtx6gJ1LCtbRtgdnpP929jYzAwpHMZRW4ueTIxbMzM5AgRrEEOVRC4+FYDUg0+i9g5gGNCfLvFqSuSBAatW73NNefwOg6JiEvE6cTpkErVXkQ+dhGDqVPT+D474ZvT06NqbpkUOnC7IpU06d2uWqac7ODS9OAmA7BTRSgbKUWTHYIsbm0OKYVsF07BsFXa9OsDLj+wBYPEpVSw7vWbU8cPCxu1zUF4fwOWZGy/YdCnNlsEtJIqJMQaYpmnyt51/47YXbqOgFVhWtoybT7+ZGn/NJCvu7YZSDZXF0cUsiiya1jA/Gxubtw5nbS2i349xIMXFkhPCDfhOPAb34nmYqsrAXX8gni3Sk1X5cadVT/eOcoXVYRVDKuB1OPHKQ/cxQWSw/pMU/CsQzRKVgz+BrtdHRW9kh8DCZVb0ZutrJUuEyR4QgGQbaAqCICDJArmkcgAi7fDEFjc2hwz72ip4g052vz7Ii39rA6B5dQXHnF07yj/JNExyiRJuv4NYvR/nHAmbZDHJ1sGtZEqZMcJGMzT+d9P/cvfmuzExObf+XP7z5P8cd9bNqPc6lIYKOAIsL1tOXaDOTkPZ2ByCiB4PrsZGjEIBUzuAolx3CCHSQOzycxDcLpSd7ST+vo57+gP0lCQqnTrXNOTJqTo+r0BVmURR3edeIMoMzvsMincBkpGnYve3oX/XqEssXOZAlCDRbzDQMyR8PBEoZiDVAaaJ0y1RzFmmwUcD9t3U5pBgf1uF9i1xnn/A+gNecHw5K99WP0bYZJMKnoCDWJ0fp3tuhM1gYZAt8S3ktTzl3vJRe8iWsty64VYe3/M4AgIfXvZhrjn2mjHpqv3JlrIMFgapC9SxPLZ8XJsGGxubQwe5ogK5vPzAiosB/JXItfOJXHIGANITT7N5ZxKAa5vyODFQNZ2qkIvysIlDNlGUfe53oouBedeiumqRjRTRV29AKOx1End5RJoWWen4ra8N+1kJlsBJd0FuANkpoan6UeMUbosbm4POiK1CxrJV6NqWZMNfd4EJTStjHH9BwyhRYQwJG2/IRaw+MGfCpj/fz9b4VlRDHSNsurPdfGX9V3hj8A3ckpv/WP0fvGP+OyZ15jZMg4HCACW9xOLIYprDzXYaysbmMECQZZyNDQiicGDFxaIMkQbUVasoNdUj6jqff+keLo3lOD6okVE0oj4nIbcDhwNCAR1Ng31nCBqyn775X0BzxHCofYSf+78I6t76m0UrnCBAT7tOKj4UnZEcILshuRvUPLJDJJcsHRWpKVvc2BxUdH3YVkHBF3bRszPNs3/aiWmYNCyPsurCxjHCJpdU8IddxOr8OFyTt1cfKD25HrbEtwCMcet+feB1rl9/Pd25bmKeGF9b8zVWVa6adD1VV+nL9eGTfSyPLac+WD9la7iNjc2hgxQO46iuOcDiYsjoTvbI9fzilA+ScXhoTnXyzzseI1vS8TgkygNuhjPTXo+Jz2dQKI7+iDYcEfrnfxFdDODItRF6/nrQLcsFf0ikbt6QoeamfdzI3UFQC5DYg9MloORVSoUjf+aNLW5sDhqGYZLoHrZVcNK/O8Mzf9iOaZjULYmw+p1NCOI+wkY3LGETcVFW68fhnH1xYJomndlOWuItOETHmM6lx3c/zq0bbiWn5mgON3PL6bfQGGycdM3hNFSNv4blseVE3WOtImxsbA5tBEHAWV+H6PNhpNMzONNkIFtke1+WVxICfyqU84OV7wVAXrseo6OLiqAbp7z3XieKEPQbyLJJqTQ6Gqy5Kulr+jyG4MGZeJ3QSzePzLQZHuq3Z7tGPrdP2McbhVw/UrEfQzcoZI/81JQtbmwOCqZhkujNkxqyVRjszLH+99sxdJOa5jAnv6sJcX9hkyoRiLgpq/Ujz4GwMUyD9kw7rfFW3LKboCs46rW737ibOzfdiW7qnFZzGl859SuEXeGJ36NpMlAYQNEVFkUWsSiyaIxFg42NzeGD6PXibGjEyOdGdSxNhGGadCQK7OzPkddMfr7dGqQXPPUUzGOPBcPA/9f7CQpjPaycTgj4DUr7pacANF8TvZWfxBAcuPo2EHz1W2AaRMslyqskTBO2vb5P9EaUweWHVDuykSefVDCMIzs1ZYsbm7ec/W0Vkj151t23DV0zqFoQ4pR3z0eU9v5q6ppBLlkiEB0SNo7ZFza6odOWbmN7cjt+px+/0z/yWl7N860XvsXfdv0NgPcteh+fPv7Tk5pYqrpKb64Xr+xlRWyFnYaysTlCcFRWIMdi6FMUF5c0nV0DOdoTebxOiXt3KwwoBtVekaua/STeezWmz4/ZnyD5lwdBGxtN8XsNvEPO4fujlh1Lf9nHMAUJd+fj+N/4IZgmi1da96WdW1VKyj4CxuEFQ8NZ6ETJFSgd4XYMtrixecvJxIdsFTwS6cEiT/1uG1rJoGJegNPeuwBJHi1s8qkSwZglbCTH7P/KaobGrtQudiZ3EnKFRvk/9eX7+OozX+WVvldwiA7+/YR/57JFl01aOJxTcwwUBqjx17AitsJOQ9nYHEEIDgfOhgYwTQxlfEuDrKKxoz9LX6pIyOPgT3tKPNqpIAD/vjyAYBpoPj++f7ZMMlNPvkyxZQuU8qPWEUUIBQ0kCUr7aR9Bksh7VzBY+3EAvG1/xrvtV1TVSQQjIpoKO7eWRp/kiSKqCcx07xHvFG6LG5u3lGxCId6Vw+GUyKVKPHVPK5qiE6v3s+byhWOFTbpEsNxDtNY/6rXZYtjZuy3dNsYAsyXewlfWfYX2TDthV5ivnvpVTq05dcK1TNNksDBIUSvaaSgbmyMYKRrFUVONHh8c81oip7C9L0OmqOHzOLl9U47f7LBEy5ULvCwLy6SLKlVBNxVnnIbvzDPBNBn43RMYuczIVOFhXE7TSk+VhDHpKcnvIyseQ2rhJwDwt96Ft+0vLB6yZNj2hoqu7xO9EURwh3AoveR6etH1semwIwVb3Ni8Zexrq1DMqaz9bStqUaes1sfp72selW7SVStiEyr3UFbjQ5Jm/1e1pJfYFt9GR6aDMk/ZKJPKdR3ruPm5m0mVUswLzuPrp3+dhZGFE66lGRq9uV48soflZctpCDbYaSgbmyMUQRBw1NUjerzoGcvM0jBNupN5tvVnMQwoCTJffCHFs30lZAH+fbmfKxd4SRZUgh6ZqpAbEIh+7GNI0Shabz/JJzeDIEO2f1ShTcBn4PGYFJXREWNBljCBtGcN2UVXWce+cQcLPU/j8QoU8yZ7tu+XfpLdONwSpf4OlORMCqMPL2xxY/OWsK+tglrUWfvbFkoFjUiVlzPe3zyqpVsr6eQzJcKVHqLVvlH1N7O2nyFn765cF+Xevc7ehmlwb8u93LHxDjRDY3Xlam487cYx7eD7klfz9Of7qfJVsbxs+aTH2tjYHBlIfh+OhnqMbIaSqrJ7MEdbPI9HltiVN7l2Q5LdWZ2IU+DW1SHOq3VTVDXApDbixSlLQ+v4Kfs//weA9COPUxzEGr6X6x+pwxFFCAUssaPup1VEnxc9lSFT/V7y8y4FIPLaN1k6zzLObHlt7Fwb0RsCJUehfcfYauUjBFvc2Mw5pYLGYKdlq2DoBk/+pgUlpxGu9HDmBxbh2GcIn1bSKWZVwpVeItX+ORE2eTXP1vhWenO9VHgrRiYKK7rCf7/83/xp258AeNeCd/G5Ez834aC94TRUXs3THG5mcXTxqHodGxubIxtnVRUlf5Cd2zvpSRUJuR38vVvlhpfTZFSTRUGZ75wSZknYgWGYZIoa1SE3Yc/oZgTvCSfgf9vbABj4yc8wfPUQrIViYqQOx+0yCQYMFEVgX60iOmRM00RPpsks/1eKtW9DMHVOiF+HQzbIpAy69+zf2SXgDIXI9/agx9vn8kd00LDFjc2cMmyroOQ1TEzW/qaVYlYlGHNz5gcWjfKDUhWdYk4jXOUjUuUb1Qo+W2RLWbbGtzJYHKTCVzGSOooX43ztma+xoXsDkiDxf1b+Hz649IMT+j1phkZvvhe35GZ5bDmNocYpbRdsbGyOLAYUk1Y5TDpbJCDBD7bm+d+WHIYJ59a4uHV1iDK3hG4YDOYUwj4HVcHx6/CiV1+NVF6O1tdH/Nf3QHQ+RBeAplh1OOZQeso9Nj0l+j1oyTRmvkR65RdQKk7GRYoVngcBK3qzPw6PA9X0UOzYMabO50jAFjc2c4am6sSHbBUEEZ767Tbyaaul+6wPLsbldYwcqyo6St5KU0UqvXMibFJKii3xLaSUFBXevQaYu1K7uH7d9exM7STgCHD9Kddzdv3ZE66TV/MM5Aeo8laxIraCmCc263u1sbE5dDEMkz2DOV7vTFLyhzEqq/nyyxn+0aUgAv+82Mdnl/txSgKqrhPPlYj5XTTFfMgTRKNFr5fYv/0bANlHH6Xw6mtW9Ca2CESHNYRPMAgGDEwT9vXwFB0OTN1ASyRAlEmt+gql6ApWuv+EiMpAr85g7+jojSAICC4f+XQRBreDfmQN9rPFjc2cMGyrkE0qiLLIU/e0jlgsnPXBRbh9+wibooaS14hWewlXeEdNJZ4tEsUEWwe3klNzlHvLR4TN893Pc+MzNxIvxqn113LL6bewtGzpuGuYpkm8ECev5lkQXmCnoWxsjkJKmkFrb4atPRlcskR/rsTnX8jQmhfwy/C1VUEubfQgCAKFkkYyr1IdctMU8+GWJ4/uelasIHDRRQAM/PCH6LkceMugfDF4rCnDbqmE32dQVMTR6Sm/Fy2ZwcgXQHKTWn0LzkiUxZ61ALRszIy5ntMlUDDDqIPdEG+btZ/RoYAtbmxmnX1tFWSHwLp7W8nGFbwhJ2d/cBGewN58c6mgoRR1ojU+QnMkbAYKA2wZ3ELRKBLzxBAEAdM0+fP2P/Ptl76NoiusLF/JzWtuptJXOe4aw91QLsnF8thy5oXm2WkoG5ujjJyisbkrRdtgnojXyYadcb70x03ECxoNAQffXqhyXMS6L2QKKgVNpynmo7Fs4ojN/kQ+9CHkqir0eJz4z39uPen0Q6wZgrUISpKgK4vLOTo9JTodoOloiRQApsNP6qRbOabsGQA62wUy/aO7o2QHqJqEIoQgsRNyA2/2R3TIYIsbm1llX1sF2Sny9O+2kx4o4gk4OOvKxXhDe9utSwUNtaRTVuMjVO6ZdDDegdKX76Ml3oJu6iPCRtVVfvTqj7hn6z0AXDjvQr64+osTRmGGu6EqfZV2GsrG5ihlMKuwqTNFT7pIzOfk7mfb+O9/bEMzTE6dX8a3LjuW6vIwZipJPKeACAvL/VSFZnZvE91uYp/6FIgiuSefJP/CC9YLknOoDmc+slki5IhjGKDtk20S/B60RBqjYJlpGu4owpnXMs/zCiDS9uQLoO11NRcEAUmCXMkDmNDfCmpxFn5aBx9b3NjMGqZpkhookOrNIztE1v9+O6m+Am6fJWz8kb3CRsmrqIpOWY2fYGxuhE13tput8a0ARD3WlOC0kuaW527hqY6nEAWRj634GB9Z8ZFxZ9KYpkm8uDcNtSS6xE5D2dgcZZimSWeywKbOFDlFw++SuenBzdz/mtVq/cGTGrjuoiV4/R606hoSqRw+0aC5PEDU55pi9fFxL1lC8JJLABj4yU9GZukgiFYdTvkiPF6ZgDBIsWCOpKdEpxNT09ASeyM0hreaBac0AbAtdRyO574Fxt76GqfLmodTcsQgPwCDO+AAXM8PNWxxYzNrZOJF4t05RAme+eMOEj15nB6Zsz64iEDZ3nZqJa+iayax+sCcCBvTNGlPt9OSaMEh7XX2bs+08+V1X6Yl0YJX9nLdSddx/rzzx11jOA3lFJwsK1tGU6jJTkPZ2BxlqLrB9r4sm7tSyKJITtH5/H2v8lpHCo9D4j8vXsqVJzUgCgJFVadX9hNprKVRKuF3v7n7RfiKK3DU1WEkkwzeeefoFz1RhMrFBMsDOPUkSmFvdbHoc6MlkhjFvRGYyPw6YlEFHSct7fUEX/kGmFbIR3YIaKqJUhTAXw7JNsh0v6m9HwrY4sZmVhi2VRAE2PDXXZbFglvirCsXEYztbX0s5ixhU1brJxAdf37Mm8EwDfak97A9uR2P7CHotJy9N/Zt5Ib1N9Bf6KfSW8nNp9/MseXHjrtGQSvQnxtKQ5WvoNxbPuv7tLGxObQplHS2dKfZ0Z8l5HbyemeKL/z+VXrTClVBN9+6/FhOnW8N7MwqGvGcwrxyP4uOX4Lb68HI5d7U9UWnk9inPw2iSP6ZZ8g988zoAxw+5MpmQlUx9GIRvWClm0SXC1NVR0VvBEFg0QkhAF7PX4jYuYHApu+PRGhkGXJpA1Nygeyy0lPK2ALkwwlb3Ni8aYZtFUzT5MUH2xhoz+JwSZz1gUWEK/emcYpZFdOAWF1gToTNeM7epmny0K6H+Obz36SgFVgaXcotp99Crb92zPmmaZIoJsiWssyPzGdxdDE+h2/W92ljY3Nok8yX2NSZpCtZIOZ38YdXOvjGw1tRNIPj6sN8+/0raSyz7g3xXIm8qrGkOsiiygDuaARnXR16KoX5Jqf/uhYsIPTe9wIweOedVqv3vkgOvLWN+KoqKShAMQ0miF4PeiKFqeydb1PTIOMPCSimn82Ft+PZ8wC+Fqtg2ekSKBZMSgpWV1Ypa7WHG/sP/zt8sMWNzZuimFMZ7MqiqTovP7ybvt0ZZKfIGVc0E6neKwwKmRImEKv3j6q9mS00Q2NHagc7kzsJu8N4HV40Q+Onr/+Uu964CxOTs+vP5sunfJmAMzDmfN3Q6cv1IQuylYYKNuEQHeNcycbG5kjFNE26UwVe60iRKWqEPA6+9UgL975gTfG9dGUNN16ynIDbgWGa9KaLiCIcUxOisWzv4FFHbQ1SKIieSr3pPYUvuwznvHkYmQyDP/nJGCsFQZQI1VThiNai6G4oJBCdMkapNNI5ZR0njBhqvqJ+EN2U8G3/DZ6dv0eSBXTDQCkYIAjgr4BkByT3vOn9HyxscWNzwAzbKqgFndce76BnZxrJIXL6+5spq/WPHFfIlEAQiNX58YVmX9iouuXsvSe9hzJPGW7ZTbaU5RvPf4PHdj+GgMCHln6ITx77yXHrZopakb5cHzFvjBWxFVR4K+akwNnGxubQRTdMdvbneKMzjQBouskX/7CJDbviOCSBz53XzD+fMR9JFNB0g+5UgaBH5tjaMBXB0ZFo0eXC2diIWSxiqm9uOJ7gcFjpKVmm8OKL5NauHXOMwykSqgyj+eownCEoJhFdMlo8OSp607jQgcsjkC+6eSP6nwAENv8Yd/vfccgC2YxhiSfJAe4gxHdAPv6m9n+wOCTEzQ9+8APmzZuH2+3m5JNP5vnnn5/w2DvvvJMzzjiDSCRCJBLhvPPOm/R4m9nFMExKBY1cUmGgM0shq/Lak+10bUsiygKnX76Q8vq9kZF8uoQgipTXB+ZE2Ci6QmuilY5MBzFPDKfkpDvbzQ3rb+D1gddxSS4+f+LnuWTBJeMKlmQxSVpJMz8yn6VlS/E7/eNcxcbG5kimqFr1Ndv7MwTcMjv7c1x730ba43miPiffeO+xnLukcuTY3oxCdcjDMbVhQt7xI7xyeTlyVSVa/M2LA2djI+H3vx+AwZ/9DG1wcMwxXp+IL+yl4KgFfxWCUMLIpdFSe2tvJFmgebm139d6TyTX9D4AAq/dTiD5LErRRCkORYbcQcu4c3AbaGPtGw51Drq4uffee7n22mv56le/yssvv8zKlSu54IIL6OvrG/f4J598kiuvvJInnniCZ599lvr6es4//3w6Ozvf4p0fHeiaQTGnkokX6e/I0NWaoGt7kt62FMWsyuZ1XXS2JBElgTXvXUjFvODIubmUgiSLlNf78Qadk1zlwChoBVriLXTnuin3luOQHLwx8AbXr7+erlwXZe4yblpzEydWnTj2fQ2loSRBYnlsuZ2GsrE5SkkVVF7vTNERzxPzuXjkjR6+9sAb5BSdJVUBvvP+41hUaX1hyxatwuH5MR/LaoJ4nGNHSAwjSBKu+noEWcIoFCY8brqELr0U58KFmPk8Az/84Vinb1EgGJKQnA5KriqEcKMVvenaMyp6s2CpE0mGVNxgR/BjFOouQDANwhtvwRl/lWJ+nzohfzlkeiG+67BrDxfM/X9CbzEnn3wyq1ev5o477gDAMAzq6+v59Kc/zXXXXTfl+bquE4lEuOOOO7jqqqumPD6dThMKhUilUgSDwSmPP5owTRNNNVCLumVimS1RKupoJR3TMBEkAdkhIjslREngxb+10fbaIIIocNp7F1DTHB5Zp5BWkZ0isboAbv/si4a8mqc10cpAYYAKr2WA+Y89/+Cnm36KbuosCC/gCyd+YaQNfF+KWpFEMUG5t5wFoQV2tMbG5iilL12ktTdDUTUIemR++OQOnmzpB+DtSyv5l7MX4BiaLBzPldBMg4Xlfuoj0/e/K27fTmnXLuSq6jed7i51dtL9hS9glkqUfeITBM4fO8oindKID2h4fSKCmkHfvQVnzI+jcQEIlhjb+FyRba+rVNRInHWhi9BLN+HqXY8heRlY/S1iK5btfX+lPChpqDkBAuNPcH+rmMnn90GN3JRKJV566SXOO++8kedEUeS8887j2WefndYa+XweVVWJRqPjvq4oCul0etTDxmLfFFOiO0f3jhRd25L07Ewx0JmhkFURRPAEnfijbnwhFw6XRKq/wIsPDgkbAU65dP4oYZNPlZBdErH6uRE2mVKGLYNbGCwMUumrRBAEfrn5l/zPa/+DbuqcVnMaXz31q+MKm6RipaGagk0siy6zhY2NzVGIbpi0DWR5rTOFboAkCvznH1/nyZZ+RAE+eeZ8Pn3uQhySOFI4LI1TODwdnLW1iH4/xiwUFztrawlfeSUA8bvvRu3tHXOMPyDh9YkU8gaCK4hY2YxWEDATPZbDOLBohRNBgL4unUQcUid8mVLZcYh6nrKX/pNS7+59LuoFUYKBVkvoHCYc1KlkAwMD6LpOZeVoNVhZWcnWrVuntcb//b//l5qamlECaV9uvfVWvva1r73pvR4J6JqBqgxFZfIqSlZF1wx0zbDGcMsiDqeI2yePfMPIp0v0taUZ7Mwx2JUj0ZPD0PYG+066pIm6JRFgr7BxemRidf5Rrt+zRUpJ0ZpoJVPKUOGrQNEVvv/y93m572UALl90OZc1XzbmG5Ju6AwUBvDIHpaVLbOLhm1sjlIUTWdHf5b2eIGg28GeeJ5bH9pCMq8ScMtcd+ESjq0LA6DpBr2ZIlGfk8WVwQnrayZD9HhwNTZSeGMzot+PMIV55lQE3/EO8i+8gLJ5MwM/+AFVN96IIO6NU4iiQCgsUyqqqCUDORhBV0pogguHkgbDjdcfoH6BzJ7tGi2vlTjlXA+pE79G+Lkv4Ei1wmNfgPf8wOqaAvDGIN1pTS+uXA7iQa9omZLDeuTqN77xDe655x6efPJJ3O7x56Z86Utf4tprrx3573Q6TX19/Vu1xYPGmBRTrkSpsE+KSRSQnSJOj4wkW7+omqqT6MkT78wx2JVlsDNHMTu20t/plojW+llwfPmoiE0uWcLllYnVB3B5Zv9XK1FM0BpvpaAXqPBWMFAY4FsvfIs9mT04RAf/cty/cFrNaWPO2zcNNT80f9xWcBsbmyOfTFFlW2+WvkyRcr+bJ1r6+PHaHWiGybwyL19+xzKqhjqfiqrOYM4qHF5UGZi0vmYq5IoK5L5+tMFBHJVvLrUjiCKxf/s3uj7/eZTNm8k89BDBd7xj1DEut0ggLJIY0JFlAdHrR1ME5PJKhGwX5AdZfEyIPds12ndpHJMx8AV8JE/6f4TXfw5Hvh3zwf9AuPR74A5b7eG+ckjtAU8Ywof+Z+hBFTexWAxJkujdL7TW29tLVVXVpOfefvvtfOMb3+Cxxx7j2GPHnzQL4HK5cLlmv0vnUMMwTLShqEypoFHIWd5NumpgYiJJIrJTxBN0IoqWK3Y2odCzI20Jma4cqd78mJoxQYBQpZeyGh9lNX6itT78EdeoqIdpmuQSJdx+B7E6P845EDYDhQFa4i1opka5t5xtiW3c/sLtpEopQq4Q/3Hif9AcaR5zXlJJUtJKzAvOozHYiEOyi4ZtbI5G+jMKrb0ZsopGzOfiZ+t38eAmy2ZgzYIyPnveItwOS8BkixoZRWV+zE9TuW+k7uZAEWQZZ2MDRjaLNjiIXFb2ptZzVFYS+fCHid95J4lf/xrPccfhqB09mDQQkCkWTAoFA4/Xiz44gK5VIccWQ3IXYSNOZa2P3k6D1k0ljj/NjekKkzzlG0TW/Ttyag889H/hHd+xUlOyCxxeGNhudVK5Q2/qPcw1h0RB8UknncT3v/99wCoobmho4FOf+tSEBcW33XYbX//613nkkUc45ZRTZnS9I6WgeN8Uk1JQKWb2pphguPBXRHKICIJAqagR78oR78ox2Jkl3pWjVBw7fdLtd1BW66esxke01kekyovsmPgbi2mYZFMKHr/TEjZv0k9lPHpzvWxLbsPEJOqOsq5zHT959SeohkpjsJEvrP7CGKduwzToz/fjltzMD8+n0ltpp6FsbI5CDMOkI5FnR38WAQFJFPjmw1t5vcuaZ/OhUxp5/6q6kftDPFdCHyocrptB4fB00AYHKW7dillSkcvfnK2LaZr03nwzxddew7VoEVU334wgjb5XFwsGfb0qDoeAVMyCLOFevAQBDRJt9O0cYO0TbiQJ3nGlD5fbEnGl3jZqXv08YillFRJfeKslbgDSXeCvhOrjQHpr4yMz+fw+6OLm3nvv5eqrr+YnP/kJJ510Et/97nf53e9+x9atW6msrOSqq66itraWW2+9FYBvfvOb3HDDDfzmN79hzZo1I+v4/X78/qmLQw9HcTPdFJPslJBkEcMwSfcXLCEzlF7KDI61sRdlgUiVz4rK1PqI1sysZds0TLJJBW/QRVmtb9aFjWmadOe62ZbYhizJBJ1Bft/6e/647Y8ArKpcxaeP/zRueXRKUtEVBguDlHvKmR+eP+IvZWNjc3RR0gx29mfZE8/jd8n0ZxRu+dsW+jMKHofEf5y/iJOarCiKYZr0ZxTcDpFFlYExg/lmCy2RoLh1K0ahiFxe/qa+dGkDA3Reey1mPk/kQx8i9J73jDkmmVBJxnW8XjAScVzzFyCXx8DQMJPtPPa7fpIJkeUnOFl2giVg1JKJlGyh8uUvIGgFmHcGnPdVEGUwNEh3W7U3ZQsOeO8Hwkw+vw96zc0VV1xBf38/N9xwAz09PRx33HE8/PDDI0XGe/bsQdyneOlHP/oRpVKJyy+/fNQ6X/3qV7nxxhvfyq3PGaNSTEWNQnafFJNpIsmjU0zFrMpAR3YoKpMj3p1DV8d6mvgjLqL7pJfCFR7EAwi3GoaJrhooeRVvyEWszo/jTeSjx8M0TToyHZYBpsODU3LyvZe/x3PdzwFwyfxLuHLplYjC6P2nlBSKptAUbKIh2IBTmv35OjY2Noc+OUVjW2+GnrRCmc/JC21xvvv4NkqaQXXIzVfesYz6qOV9ZxUOK5T5nSyqDBDyzF36Wo5E8CxdSnFrC1p/H3L5gTc3yLEY0Y9+lMEf/IDEvffiWbUKZ0PDqGMCQZliwUBRTJxOF2p/H1IkjCDLCJEmlpwEzz0yyLY3FBYd60CWRWQH5NyLKJ5xC56nroO2p+Hpb8OZX7AEjidsFRe7w+B7cym2ueKgR27eag7FyM3+KSYlq6Kp46eYDN0k2Zu3RMxQrUw+NXZ6pOwUR4SMFZXxzbh7yTRNDN0SMlbKy8QERAEkh4TbKxOt8SHPsrAZdvbemdqJ3+mnpJe4/YXb2ZHagSRIXHPsNZxdf/aYcwbyAzglJwvCC+w0lI3NUcxgVmFbX5ZkvkS53809L+zhvpc6ADihIcwXzl+CfyjSPFw4XBP20Fzx5gqHZ4KeSlFsaUHPZJArDvx+ZZomfd/4BoWXXsLZ1ET1rbeO6cgq5HX6ezUcDhMhHce1cOFI3Y9hmDz0o1fJpzVOWFViwcoQiDK5jIEvIFJRehYe/SqYBhz7ATjl/1iLZnoscVNzPDjmJsq1P4dVWuqt5mCLm31TTFpJpzA8KE/RMQwTcZ8UkygJ5FMlBrtyxDstIZPszWPoY//JQuUeorVDUZkaH8EyN8IMcsWmYaJrxoioMg0TEJDkoRZxt4TLI+NwyUgOEYdTQnLMfjugbui0pdpoS7cRdAXpzffyrRe+RbwYx+/wc+2J17KsbNmocxRdIV6IE/PEaAo1EXId2oVuNjY2c4NpmnSlimzrzaAbJl6HxH892sqLuy037fceX8tVp85DGro3DhcOzyvzzUrh8EzRMxkrRZVKIVVUjmrpnglaIkHX5z6Hkc0Set/7iFxxxajXTdMkEddIJzXcRg7R48G9qHmkRmf7i3288ugefAGBiy7KIXhDqIYLTYPqBhnnrodh7TetxU76BBz3QUvspDqhbCFULLW6T+aYwyotdaQzkmIqDXUxTZJi0lWDRM9Qammo8FfJa2PWdA1FTIYLfyPVPhyu6X/b0DVjJBpj6OaIqBJlEYdDxBty4nTJyE7JEloO8YDSVzNFNVR2pXaxJ72HiDvCpoFN3PHKHSi6Qo2/hi+u/iJVvtFddGklTUEr0BBsYF5wnp2GsrE5SlF1g7aBHG2DOTwOmUJJ5Ya/vEFnsoBTEvn0uQs5e3HFyPGDWQUDkyVVgVkvHJ4uUiCAeyhFpff1HrDAkSMRov/8zwx897uk/vhHvCeeiGvB3noYQRAIhmSUooFa8uFIJ9FTKeSh4bfzji3jjXVd5DIaHYkq6qV+HLJKUfWhFEyciy+yphQ/9yN4/n/AFYSl7wRfDBJt4IlAsHq2fiyzgi1uZpnppJgcThGXVyIbV+htS49EZVL9Bdi/FVsUiFR6h6IyVtGvL+ycVgjTNPdJKakGumGCCZJspbhcPsdQNEayhIxjb3fVW82ws3dnppOoJ8rDbQ9zz9Z7MDE5JnYMn131WXwO38jxhmkwWBjEITpYGl1Kpa9yTP2NjY3N0UGhpLOtL0NXskDU6+KN7hS3P9JCrqQT8zv58sXLWFhhNZyMFA47JRZV+qkIvDUplYmQ/H48S5dQbGlB6+u1anCkmafGfGvWkN+wgfyzzzJwxx3U3HYbgmNvKYIsW8P9+ntVDFFG6+1DCoUQJOv+v/CEcjav76bldY26y5oRknuQSgly6Qj+oAPh2CugmIaNv4Z13waXH+afDWreml7sCljPHSLY4mYWKRU0+tszlAraqBST0yOjlYyRGpn4UNGvqoxtxfYGnSNCpqzGT7jKOzJkbzIM3RIwmmagq6ZlcjZUGyM7RNx+Jy7PPiklp4j0FodgJ0LRFbYnttOd6ybkCvGz13/G2o61AJzfeD5XL78aSdz7x17SSwwWBu00lI2NDcl8idbeDPFciQq/i7+82s3dz7ZhAkurg3zpoiVEvFZEV9UN+t6iwuGZIPp8uJcMCZzeXuTKyhkLHEEQKLvmGoqbN6O2t5O4916i//RPo47xeEUCAYl0wouYTqOn08gRa8L8whMr2Lqhh0R3nv64m4rKRTjZhTI4QCkaw+Vzwup/tgTO1vvhH7eA0w+1q6z28MHtUHWMZdVwCGCLm1nE0E2UvIrb5yAzWLSEzFB6KZtQxhwvOUSi1V6iNUNzZWp8eAKTp1VM0xyKxFj/a2gmCCaiJCLJIk6XjCvqGIrGWLU7sizOqP7mraSgFdiW2EZfvg+37Oa2F29ja3wroiBy9fKruWDeBaOOT5fSFNQC9YF65oXm4ZKO/AGNNjY2YzFNk54h40tVM4l6nXz38W08tW0AgAuWV/HJM+eP1NHsWzi8qDIwMrDvUEH0ei2BI7bujeDM0KpBCgYp++Qn6b/tNtJ//Sve1atxL1488rogCATCMsWigZKUkPqGojeiiMvroOnYGDte7qfluR4qrliEXL2EgrILZbAPlyNiDfM7/bNQysDOJ+Hv18M7v23V3aQ6rPRUpHF2fzAHiC1uZolET45NT3TQ0ZIgNVAY5b80TCDq3huVqfUTLPdMmucdbrkeTisNl35LsogkC3iDTlxex0hdzPCcm8OFnJpjW2Ibg4VBSnqJW5+/lb58Hx7Zw2dP+CwrK1aOHLtvGmpJdAlVvio7DWVjc5Si6Qa7B/PsGsjhkkUEweS6P21iZ38OSRT45JnzuWjF3hqQTFElq2izNnF4rhA9niGBI6L19CDHykellqaD76STyJ95JrmnnrLSU7ffjrjPlH6HQyAUkekv+lDjKRypNFIkDMCikyrZ8Uo/PTvTpPryhCq8yBXzyCoeAoV2BK0I3iic85+gZKHzRXjoOrjkv63nB4emF3sis/ljOSBscTNLFLIqm9Z2jvy3wy2NRGOGO5gmsiWYquVadkr4Qk6cHseIiJEdh240ZjpkShla460klSTd+f/f3p3Hx1XX+x9/nXNmzUwy2ffuTdOmhZZCWwooXCgWQQHt5dfrgiwKiqB4UbkqvRYU9IoXwQv1qtwHFrgiWJV9EeSy2QJl6YalSVtKt+z77Ms5398fk0wySdqmJe2kyefJI3TmnO/5nu9McjLvfL/fc04D//XufxFOJO8ZdeOCG6nMrkyV7R2GynflMy13mgxDCTGOReImO5oD7O8Mket28EFLkP94bhtd4Tg+t53vnTeTORV9vyN6Jw7PKsumIjczE4cPh+504qquJqrpxOvrkxf6O8yAk3/llUTee49EQwMdDz1EwRVXpK3P8uh4fQ669+vYW1vQc31omoY3z0VldR77tnVQ+2YTCz89BUeWg4hVSjQvF1dgO3Q3QnYxfOJH8PR3oHkrPPNduOju5JzR1u3JqxfbMntyh4SbEVI0MZuZi0uxuwzKp+eSXeAacmLuoU65dnntx+SU60zqinZR215LIB5gY8tG7v/H/SgUM/NncsMpN6RdUdgf8xOMBWUYSghBVzjO9iY/rf4oxTku/vZ+E7959QNMSzG10MNN589KXVl4tE0cPhy6w5E8VVuD2P79ySGqwwg4htdLwTXX0HzbbfiffpqsBQtwz5mTWq9pGr5cg2jQS7i5C3tRF0ZuLgDVi0rZt62DPVvbmXNmBVk5DpRSRPQCXBVeaN6WPAU8uwTO+w948pvJM6ae/g586q6e6998CEUzRvQ9OVxynZsRFAnEqd/RgSc3eWPJ3ns9mfGhT7l2eGwZOeU6k9oj7dS11xGIB3hm1zO8sPsFhlU5CQAAMyVJREFUAM6sPJOvnPCV1I0tLWXRGm7FoTuY7JtMmadMhqGEGMeae+bXROIWuVl2/ue1XTz3j0YAPlZVyDfPrkrNoxmtE4cPl4rHie7YQWzvXoyCwrThpeFo/fWvCfztb9iKiym/4w50tzttfaDbpGlHK94yH+6q6ak/yF/+fS0te/zMWFjC3HMmEAnGMWw6ZdN86FYUWuqgcw9k5SXPlnriG8lQUzAdlv40eQ2civngLR6qWUdMrnOTYb2Th0fjKdeZ1BJqoa6jju5YNw9ufZAtrVvQ0PjczM/x6WmfTr0f/YehpvqmkuvKzWzDhRAZY1qKve1BdrQEses6DpvODx//B1sbkje+/NLiySybX5H6/THaJw4fDs1ux1lVBbpObM8eyC84rICTf9llRDZvJtHcTPsDD1D41a+mrc/y6niLswk2duEs9WP0BIbqU0tp2ePng40tzDq9DIfLINQdJxpO4Pa6oXQOODzJISibHc7/z2TAadsB//dj+Nh3oHPviIebwyF/Co8gw6HjK86iaEI2pVN9lE/Ppbwql9IpPvJKPXjzXLg8dmwOY9wFm8ZgI9vat9EUauKud+9iS+sWnIaTG065gQunX5h6PwKxAO3hdiqzK6kpqJFgI8Q4Fk2Y1DZ1U9sUwOOw0R6MccMfN7K1oZssh8EPP1XDP/e7o7c/EqcjFGNakZeaspzjOtj00mw2nNOm4Zg8GbO9DSsy+CbIB6K73RR8/esABF54gfDGjenrdY28IheGDqF9zamTVkqn5pBT5CYRs/hgQ0tqRCHij/dsaCRvmlk+DzBAM5JDVHYPNG6Gdb+ExPDbeTRIuBlBdodBQbmXnEI3Hp8Th9s2aq4lkylKKeoD9dS217Kzcyc/f+vn1AfqyXflc/NpN7OgdAGQHIZqCbUQt+JU51czI2/GoLt9CyHGD38kznv7u9jdGqLQ4+TtD9v5tz9vpjUQoyLXzR2XzOWUyfmp8m2BKNGEyayyHKYXe7GNod+9ms2Gc+pUHFOmYHZ0YIXDw97WPWcO2eefD0Drr36FGQymrXc4dXzl2YRbO0l0dyf3p2lUL0revHr7W82YCQu70yDYFe25IC3J2y3klEHFSeDOB3tWcpKx4YD978Brd4A1+AbOx8rY+e6LUUcpxV7/Xmrba3m76W3uevcuAvEA03zTuO2M25jimwIkh6Gagk1k27OZXTCbyuxKmV8jxDjW4o+yeV8XrYEYxdkufv/mbu54oY6YaXHKpDzuuGQulXnJO3pbStHYHcZm05lTkcuE/Kwx2TOuGQbOqVNxTpuK1dWJFQoNe9u8L3wBW1kZZns77ffdN2h9ToEbt1MR2N2U6r2ZWJOPO9tOJBhnzz/acLgMYmFz8C2B3LnJHpy8KeApgbO+n+zJCbVntPdGPkHEUWEpiw+7P6Suo46ndz3N6n+sxlQmp5adysrTVpLnSl4HIRAL0BZuozK7ktmFs1PLhRDjj2Up9rQFeW9/J/GERbbDxm3PvM9fNiQvs3HJyZWsuKAGjzM5XTRuWjR0hsnLcnBipY+i7LF9NqWm6zgmT8YxfTpWdxfWgF6YA9GdTgqvvRZ0neArrxBavz59va6RV+FD+buItnUllxk6VQuSvTe1bzaBBpoOYf/gC9Jid0FJDZTMTt5E8+PfgU/8OHnRvwyRCcVixJmWya6uXdS21/Jw3cNsbN4IwLKqZSybsQxd07GURXukHR2d6rxqyr3labdYEEKML7GExQctAfa0h/A6bXSG4vzg6S3Ud0Vw2HS+dU4VH6sqSpWPxE3ag1HK847/icOHQ9N1HJMmJScZ79iRvAGz99D3dHLNnEnOpz9N9+OP0/qb31Axc2ZqAjGA2+fGm9VFoL4FZ34Omq4xdV4R769twN8WoWFHF4UTvIS64/iKTWwD32/dgIKpyUBjcyW/Mkh6bsSIilvJG2BubN7Irzb9io3NG7Hrdr5x0je4pPoSdE0nbsZpDjbjsXmYXTibCTkTJNgIMY4Fowm21nfxYVuIvCwH7zd08+01m6jvilCU7eT2ZSemBZvucHLi8NQxNHH4cGiahmPCBBxVVahQENPvH9Z2ucuXY58wAauri7Z77x20PqfMhz3aRaCxEwC702Da/OT7vu2NRuxOg3gkQTSYGLRtSnZp8jTw3AmH/bpGkoQbMWJiZowdHTv4+76/c9e7d7HHvwef08cPF/+Q0ytOB5LDUK3hVsq95cwunE2+K/8QtQohxrK2QJQt+7to7I5Qku3kiU313Pr0+4TjJrPLc7jz/81jWpE3rXzMHJsThw+Hpmk4KitxVVejImHMrq5DbqM7HBRedx3oOqHXXye4dm3aervHTY7bxOzqTN3YefopxeiGRtu+AG37g2iGRqh7iKGp/ly+ZMjJoPH5UyFGXCQRoa6jjid3PsmqTavoinUxMXsit51xG1V5VSilaA23EjWjVOclz4Zy29yHrlgIMSYppdjfGWbL/i6C0QT5WQ7+84U6HnxjNwo4/4Qybr1oTuoCfL0Th+1jfOLw4dA0DXtFBa6ZM1Hx+LACjnPaNHzLlgHQdu+9JDo60tZnFeeSFe8g1NqNUgq318GkOQUA1L7ZiMNlI+SPp8LPaCXhRnxkoXiIbe3bWP3eah58/0HiVpz5xfO55fRbKHQXEjfjNAYbybJlMadwjgxDCTHOxU2LHc0BttZ3YdN1lIIb/7yZtTtaseka1/3TdK45c1qqV6b/xOETxsHE4cNlLyvDNWsmykwMCitDyf3sZ3FMmYIVCND2m9/Q/0YFutuNx5HAHu0m3HNdmxk9p4XX13US9sdIxCwiwfjReTEjRMKN+EiC8SBbWrbwi3d+wV93/xWAT039FN9Z8B3cNjfBeJDWcCsV3grmFM6RYSghxrlwzOT9hm52tgTwuRzsaQvyr3/cyIdtIXLddm77zAksnV2aVr7ZH6EyP4s5FT5yXMfnrRSONntJCa6ZMwFFor39oGU1uz05PGWzEX77bYKvvJK23pHnIyvegRkKk4iZ5BS4Ka/KBaDurSYMm0aoK8povnuThBtxxLpj3bxR/wY/fuPHbGjegKEZXH3i1Xyx5otoaLSF24gkIszImyHDUEIIOkMxtuzvpL4zTLHXyYvbmljx+Hv4IwmmF3n5xf+bR01Z3xk83eE4XZEY04u8zCwdP2dEHSl7cTHuWbPQdJ1EW9tByzomTSJ3+XIA2u67j0Rra2qdnpWFkyhu5ScciKOUovrUZO/N7i1tWJZFJJggHhm9Q1NyKrg4JNMyiVkxYmaMuBUnakaJxCO82/wud2+4m45oB167l389+V+ZXTibhJWgNdRKjjOHqb6pFLgLMv0ShBAZpJSisefGl/GEotDr5L9f/YAXtjYBcNaMIq47ezpOm5Eq3x6MATCrLIeKXPe4n18zXLbCQlw1OpFt20i0tGArKjpgWd+FFxJav57Y9u20/upXlPz7v6feZ8PnIyvchunOIxKIU1iZTUGFh7b9QXZtamXyCYVEgnEc7tEZI0Znq8Qxl7ASqfASM2PErBiheIhgPEjUjJKwEsStOHEzTiQRobazloe3PUzUjFLuKefGhTdS6iklFA/RFe2izFPGFN8UsuyZu4iTECLzEqbF7rYQu1qDOG06dkNjxWPvsa3Rj67BZYsn85mT+m58aVqKZn8Ej9PGjJJsmV9zBGz5+bhmzSKybRvx5mZsRUVDhkPNMCi67jrqv/tdIps343/+eXKWLgXA8HiwurvwEKDTzMWMW1SfWsq6P+9k57stTJ5TQLAzSna+C00ffcFTws040htOesNLzIwRSoQIxUNEE1Hiqm99W6SNjmgHnZFO2iPttEXaaAm10BJuIZzou6/JCYUncP386/HYPbSF21BKUZVbRUV2BTZdfryEGM8icZMdzQH2d4bIdTvY1xHmJ8+8T1swhsdpcOMnZjJ/Ut9VyeOmRXN3hMJsJzNKs2V+zUdgy8vDPWsWkW21JJqbsRUXDxlw7BUV5H7+83SsXk3Hgw/injcPe0lyCErPzsHub8JbmovfH6Nsug9vvpNAe5T92zuZWFNANJzA5Rl93yf59BljUj0vvV9WMsAEY8G0npnuaDetkVY6o510RDpoi7TRGm6lNdxKR6QDxcEniuU6czmj4gz+Zea/ANAUSt4bamruVArdhcfipQohRrGucJztTX5a/VGKc1y8tr2Fe17aQdxUTMhzs+KCGspz++bhhWMm7aEolflZTC/2yvyaEWDk5uKqSfbgJJqbsBWXDBlwcs4/n9D69US3bqV11SpKb74ZTdfRPR4SjQ1kWX5i7lxiYZPqRaW88+xudrzTQvn0XCLBuIQb8dEppZJDSFaMqBlNBhYzTigeIhAPELOSASYYC9IWaaMt3EZ7tJ2OSAftkXZaw620hFqIWbGD7sdpOCnJKqE4q5iirKLU45KsEoqyinAYDiB5Gnh3tJtST6kMQwkhAGjqjrC9yU8kblGc4+KB1z/ksY31ACycnM+3PzGDLEffx093OE4onmB6sZfJBZ5xe2G+o8HIyUkOUdXWYTY1YhSXoOnp76+m6xReey313/420a1b6X7mGXyf+hSapqF7s6G1kZwp+bQ2xamcmcd7r+4n3B2jebcfd7aDnEI3+igbmpJwMwoppdLmvsTMGNFEtG8IyYwSs2LJnpZQa2oIqT3STnu4nZZwC92x7oPuQ0OjwF2QCi0Dv3IcOQecwNcbsLqj3VjKYlruNCqzK2UYSohxzrQUe9uD7GgJYtd1shwGP3pqKxv3dgKwfMEEPr9wInrP7xalFG3BGBoycfhoMrKzcc2cSWTbNszmJoyiYjQjvWfMXlJC3qWX0n7vvXQ+9BBZJ52EvaIC3esl0dCAI9ZFdn4e/rYoVaeU8N4r+9m5oZnSqTlEQ3HcXkeGXt3Q5NMoQ5RSqeDS+xU1owQTQcLxMDEzRle0i6ZwE22htmRwibanel/awm2Y6uCn4XnsnlRPS2+vS294KXQXDhlGLGWRsBJEzAgJK4FpmSRUgoSVAJUMRQCGbpBlz2KKb4oMQwkhiCZMdrYE2Nsexuey0xqIcuvT79PYHcFp0/nXJTM4fXrf74reicNep40ZpdkUemXi8NFkeD24Z80kUlfXN0Q1IOBkf+IThN58k8jmzbTccw9lt96KZhjJgFNfT3ZNIeGAQeXMXN5f10B3S4SWPQHySjwSbsYTS1lpvS9xM07YDBOKhQiZIcLxMC2hFppCTckhpEhbcv5LODn/JZQIHbR+QzNSwWVgeClyF+F1pN8ptjeomJZJKB5KhRbLslJldE3H0A1smg1DN/DYPbgNNy6bC7thx67bsek27Lodp+HEboy+sVYhxLHlj8Spa/LT3B2lONvFO3s6uPOFOsJxk+JsJysuqGFKoSdVPm5aNPuTN8WcUZJNtkwcPiZ0jyfZg1M7dMDRNI3Cr3+d/TfcQGz7drqeeILcz3wGPTubREM9ur+D3JICWvckmDK3kB1vN/Ph5lYqZuSSU+zGGEXDiRJuRlDcitMSaiGSiBCIBwjFQ3REO2gKNtEcak4FmPZwsgemPdJ+yIm7PqePYnfPcJGnZ86Lu4gSTwn5rnx0TUcphalMElYyrCRUItkLFAym1W9oBjbdlvrXa3hx2Vy4jGRw6Q0t/f/VtdHzwyqEGH1a/FHqmvwEoglKclz86Z19PLR+DwAnVvi48byZqftDQXLicEc4SmWeTBzOBN3txjWzmohG8iyqoiI0W18UsBUWUnDllbTecw+djzxC1vz5OCZNQvd4ie/bR9a8Ijx5Tiqr89j5bgut+wK07A2QX+4lK2f09N5IuBkhjcFGntr5FJtaN9Eabk2ePh1uI2oe/O6pDt0x5JyX/hN3E1YiFV76DxM1B5vTholsug2bZsNtuHE6nbhtbhy6oy+wGHZsWt+/MrYthDhSlqXY1xFiR0sAHY1cl52f/7WW1z9IXhn30yeWceXpU9ImB3eF44TjCaYVycThTNJdrmQPjq6TaGjAVlSMZu8LoJ4zzyT4xhuE336b1nvuoewnP0n23jQ1otpayS0uJhJMUDEjl33bOti1qYWJNXkSbsaiff59/HLDLwct19DIc+UNOXG30F2Ix+5JzXMZOEzUGek8rGGi3n/lppRCiKMplrD4oCXAnvYQXqeNYNRk5ROb2d0ewqZrfP2saZxb03d/qNTEYQ1qyn2U+1zyx1WG6U4nrupqoppOfP/+5HVwegKOpmkUfPWr1G/bRmzXLjr/8hfyli9Hd2cR27+frKIifEVuJs0pYN+2Dhp2dtGyN0BusQfDPjoCq4SbETIpZxJnVp6JoRlMyplEYVYhBa4CfE4fmqYle1ysBAqFhoZCYSmLcCIsw0RCiONCOGYSiCbY3xGisTtKgcdBbaOfnz23DX80QV6WnR98chYz+90fSiYOj166w4FrRhWaBrF9+zGKitAdyd4XW14eBVddRcudd9L15z+TdcopOKZMIdHUSKK1lZySUkqn+SiamE3LHj/b32piwqx8PL7R8f2VcDNCirKKuPX0W9nSuoW4GU8bJrIbdhkmEkIcdyJxk2A0QSCaoC0YxR9JEImZGLpOSbaTp7c0cN/aXVgKZpR4+cEnZ1HQL7zIxOHRT3M4cM6YAbpObO8+KChAdya/h57TTyf45puE1q2j9e67Kbv9djSXO9V7k1ucxbT5RbTs8bOvtoOOxqCEm7HI6/Ayq2AWhmbIMJEQ4rgTNy0CkWSYaQ/G6I7EicRNLKVwGgZZDht5bgdxU3H3Szv4v23NAJw9s5hrz5qOw9bXsxyKJegMx2Ti8HFAs9txVlWBbhDbsxvy+wJOwVe+QuQf/yC+bx+djzxC3uc/T6K5iURbG67SUqbOLWTr3+vpbo3w/toGSqb4sDsy/72WcDOCbLpNrvkihDhuJEyLYM9QU2cwRkc4TiRmkrAsnDYDt90g22vH6Hf12bZAlJ88+z51TQF0Da48fQoXzi1P63lOThw2ZeLwcUSz2XBOnwa6RuzDDyE3D93txsjJofBrX6P5Zz+j+4knyFqwAFtxMbF9+7EVFpJTlMXMU8tY/9Qudm1uZUFHhNwSzyH3d7RJuBFCiHHCshTBWIJg1KQzFKMjGCcYT2CaCpuhkWW3Ueh1poWZuGmxozHAtsZutjX62bS3E380gddp49/Om8m8CbmpskopWgMxdB1qynNk4vBxRjMMnFOnJoeoPtgFJE8dz1qwIHkG1SuvJM+e+tnPMDs6SLS1YS8poeaMcrb03JJh69p6Fn9mesa/7xJuhBBijFJKEYol5810R+K0BmKEYwliCQtd18myG+RnObD361lpC0TZ1uhnW6Of2sZudrQEiJvp1+OalJ/FTRfMoszXd+NL01I0+SPkuGzMKMlOm3sjjh+aYeCcMgVN04l9sBOUQs/KIv/KK4ls2UKisZHOhx/Gd/HFybOsCgvx5DqpOb2Md57dTe0bTcw/bzKurMzOr5JwI4QQY0gkbuKPJAhE4rQGYwSjCaIJC10Dl80gx+VIzY2Jmxa7WoOpXpltjX5a/IOvzZXtslFdks3MshxmlmZTU5aTFohk4vDYouk6jsmTkkNUO3eilMLweCj8+tdpuvVW/M8+S9Ypp0BJcbL3priYeUsmsuWlfYS6Y2xf38QJZ1Vm9DVIuBFCiONYNGESjJoEIskzmrojcaJxCwW4bQYeh438LB1N02gPxnh7d3sqyOxsDhAzrbT6dA0mFXiYWZrNzNJsqktyKM898PBS78ThiflZTC2SicNjhabrOCZNSg5R7diBqRTuefPwnnsugRdeoPXXv6bkppuSvTcFBbg8dmrOKGfj3/ay+aV9zP54ObqeublWEm6EEOI4EjctgtEE/kjyjCZ/JDl517QULpuB22GQ63ZgWiqtV6a20U/zUL0yThvVpX29MlXFXrIcw/to6J04PL0om8mFnrS5OuL4p2kajgkTkgGnbjumUuR/6UtENm0i0dxM9xNPkLvss5jt7diKijjpExPZ8vJ+OptC7N7SxpS5RRlru4QbIYQYxUxLEYgmCEYTdARjdIbjhHvOaHIYBlkOgyKvna5wPG146UC9MhPzs5hZmtPTM3PwXpkDkYnD44emaTgrK9F1nUhdHVgOCr7+dZpuvpnA//0frpoajMJCjIICsnKcVJ9ayta/17Pxb3sl3AghhEjqf0ZTVzhGeyBOKJEgkVDYdA23wyDHZWNvR5h3Gjup7Qk0B+2V6QkyVSXD75UZimkp4qZFeyiGz2WnqsQrE4fHCXt5OWgakbo6HJWVZF9wAf6nn6bj97/HMXkSjspKbAUFzF86kW2vN2Bz6pimlbE7hUu4EUKIDFJKEY4n58x0R+K0BWKEYglipoWu6bjtBijY3RZM9crsGKJXRgMmFWRRneqVyaYi131EPSqmpYgmTOKmIpawiFsWGgpd07EbGiXZTqaXZON1ykfIeGIvKwNdJ1JbR/YnP0n43XdJNDTQ8cc12CdNwsjLw1eUxeU/Ox23N7M30ZSfTCGEOMYi8eSF8/zhOG3BGIGeM5o0wG5oNHVH2dkSpLbRz7bG7oP2ylT39MrMOIJembhpETctogmLeMIioSxAw9A1HIaOw6aTm+Ug22XHZTdw2nSctuS/usyvGZfsJSWgaUTr6si79FJa/vM/Ca9fT+CFv+GoqMCWn5/xYAMSboQQ4qjrPaMpGE3QGkjeoykcN0Elg87ejlAqzIx0r4xSKtkDYyYDTNS0sJQCpbDZdJyGjtthUJTtxOu0JQNMKsjoMpdGDGIvLkbTddA0ss89F/9f/0rHH/5A1qJFeE5bPCp+ZiTcCCHECEuYFoFov3s0heOEY8lekqbuCLvbQ3zQEjjgXBnvgLkyw+mVsVTPEJJp9fyrsFCp3iC7zcDjMihzuXA7jGQPjF3HZTPS7gklxHDYCgtx6Tq+z36G8ObNJBoaaF11D85ZM7Hn52e6eRJuRlo4ZqJQaKQn10MF2f7rD7XtwKoGpuTB6w9cVghxaEoplALV+xhQKhko6Hkct5I3newMJ29rEI6ZtIei7GkLs7styM6WIDtaAsQSg3tlkmcwJYNMdVmyV0Y/wLHaO6k32hNk4mbymjY6GnZbcjgpN8uB15W80WX/nhi73ONJjCBbfj7uE0+k4Oqrafrxjwm/u4GuNWsouPrqjH/WSLgZIZG4SV2jn50tARKWQtOSv7R0TUPXkqFCAzS973FyndZTVsPoXddv2zSHCjGDnmsHXHmwwKRp6SFoqLDUu1rr/U9LX9+7Xeqx1tsard+ynjL07S+t3rR6tLR1B3odaXUM8RqGCpHaUG/TMMsNdx9oQ6078nYyzHLD3keGfhH1hgarX2BQ9ASJ/o97yloKGLDcSgUP1bOu/7J+waTfdqalUChMK1mnpRSWlWyDZYGFlfy3Z5+qZ79Wci/Qv709j6Omye7WEB+2hviwLcjO5gBNQ/TKeJwG1SV9w0szSrLxDDExN2FayaEkMzm5N2EqNK1nUq9Nw2EY5LgdZDttuBwGrp6eGKfNkOvNiGPGlpeH7/xPEt60ke7HHqf1N78l+5xzcE6fntl2ZXTvY8jWhm4++6t1I1pnbzjQegNSzwd+b+hJhaaedbo2dPnebfqHhL7n/YJX77b9yqXX3VeufyhL28fA8gPbBmh6v33Q115S7e7/GtLrSdvPkK+7LzimyvR8GZre876lt7nv9ap+dfTfXsPol1F0XU9/DwFd11L7SL1HerJtae+93tMWvd+yft/vvu+9Nmjh4Qav/gsH7mOo4Duwjv4/G/2r7H3fe+vRDrI9kAoHllI9oaInXPQPKqT3iKSCSv/19IUM01IkLIuEqTCVImEl6zYtq+dfRdyyMC0wTYWpLBKpxyr1r2WlPzcHPE9YyTJ99avUvs1+y2MJi32d4SF7ZSakemWSPTMVeem9Mr0X5eudE5OwFPT8jDiM5LyXfI8Lr9PeE150XHYDhyGTesXoYPh8lNx4I+ENG4nv3k3Dzbcw6cEHMtp7I+FmhOiahtdpI2FZPX/hDfirtOevyMPR98tcYaaWiLGkf1gcGLrSQp6WHhjTQ9kQddAX4gYG0YOWGRSkB4fQwc8Hh8zeOs2B4UCptFDQFyLSw0LCHHpZb7CwRumh0L9Xpro0m+qeXhmleif0KjpDcWI9k3o1wGYkQ4zbYVCc7cTjtKV6YGRSrzhe2PLzKf/Zf7D7i5cSfvttOv7wB/I///mMtUdTSo3SXxNHR3d3Nz6fj66uLnJycka07o5gjLc+bE/+VTv4D280+v46tVCgtGR4QaXCUO9fq1ZP9zn0/uXbN7bft65/d/vArvvev3Z7AxY9dffsi77w1dum5L4G1KlUWr2p9que9qPStukdXrB6uv2V0vr2qdSA+vvCX6runmBoWWrAdv3b1le+//L0facvT6s/bXnfPlX/oQnV974lHw+1LT2vf3CbxLHVGxJsuo5N1zD6PU4uTz43+j83etb3PDZ0DbuuYQxY3vvY6P98QJ12Q6PM56Ys10XC7Dext2c+jAY4DB27Tcft0Ml22nE7jLTTq2VSrxgLWu5ZRes996D7fFS98jK6yzVidR/O57f03Iwgt8Ogqtib+tCD9DH53s+83g/33lL9JyvSr0yqbO9/asC6Q2xLqlzf2gGrUoWH3DeKgSvVgAep1zmw/rQKSTOwfqWSf/EPbNPASSZaqoQ2VLXJ8EhyaEmp3jDZW3dykrdSpAXP3vV9daSn0kFDRlp6OW2IENv/ZaRCj9Y3DJM+v6QvZKUNw/QGWyt9nofVb31v0EqW6zfJNRV6k+Gwd5+QHvR6Q7DVL8ha/bYbGH6HCphpwbKnbabVt42ukQwARk9w0PW0YJAMDWD0Bo/eENETUAxdw6bp6HoyvBhachu9Z7veOjSt56djwPvX9/OoUut7/0n9wcCAn8ne9yOtvOr72VGA1nfSQG8tGhqt/hh2m4bTMMjzOPA6bT1nJumpIGOTSb1iDCu85mvE6/fj++xnRzTYHC7puRmj+vf0pJYNXJdWvrfM4O0OVWY49Q4KQ4fY9kAB64DrD1bnMMLVwN6r/uX6gsHgtg4MlwcKpUMF0qFez6FC48Aweqj3aTgBd+C+B+xqyBDa2wsJHDKE9kXL3nr7Kuo/XNavgr75WalFyQVa7/p+4VLreTBk+d7ht9Qcp54hPPR+84f6r+83T2rIobzBk+f7nyCQPDNJJvUKcTRIz41IjdEPPVQvv3RHo4FhbLjBbzjhLbXuEHWOVAjt/1BL/a8vHPQGiVQY0dIDSe8maZPdB/aWDQgbg8rLPBUhxi0JN0KMEgcOpPIhLYQQh0MGf4UQQggxpki4EUIIIcSYMirCzapVq5g8eTIul4tFixaxfv36g5Zfs2YNM2fOxOVyccIJJ/DMM88co5YKIYQQYrTLeLh55JFHuOGGG1i5ciXvvvsuc+fOZenSpTQ3Nw9Zft26dXzuc5/jy1/+Mhs2bODiiy/m4osv5r333jvGLRdCCCHEaJTxU8EXLVrEggULuOeeewCwLIsJEybwjW98g+9973uDyi9fvpxgMMhTTz2VWnbqqacyb948fv3rXx9yf+PlVHAhhBBiLDmcz++M9tzEYjHeeecdlixZklqm6zpLlizh9ddfH3Kb119/Pa08wNKlSw9YPhqN0t3dnfYlhBBCiLEro+GmtbUV0zQpKSlJW15SUkJjY+OQ2zQ2Nh5W+Z/+9Kf4fL7U14QJE0am8UIIIYQYlTI+5+Zo+/73v09XV1fqa+/evZlukhBCCCGOooxexK+wsBDDMGhqakpb3tTURGlp6ZDblJaWHlZ5p9OJ0+kcmQYLIYQQYtTLaM+Nw+Hg5JNP5sUXX0wtsyyLF198kcWLFw+5zeLFi9PKA7zwwgsHLC+EEEKI8SXjt1+44YYbuOyyyzjllFNYuHAhd911F8FgkCuuuAKAL33pS1RUVPDTn/4UgOuvv54zzzyTO+64gwsuuICHH36Yt99+m9/+9reZfBlCCCGEGCUyHm6WL19OS0sLP/zhD2lsbGTevHk899xzqUnDe/bsQdf7OphOO+00HnroIVasWMEPfvADqqqqeOyxx5gzZ06mXoIQQgghRpGMX+fmWJPr3AghhBDHn8P5/M54z82x1pvl5Ho3QgghxPGj93N7OH0y4y7c+P1+ALnejRBCCHEc8vv9+Hy+g5YZd8NSlmVRX19PdnY2mqYBsGDBAt56661Dbnuoct3d3UyYMIG9e/eOiyGv4b5vY6EdI7mPj1LXkWx7uNvI8XBk5Hg49nXJ8TB6HY2fQ6UUfr+f8vLytLm4Qxl3PTe6rlNZWZm2zDCMYf2wDbdcTk7OuPjhHe77MRbaMZL7+Ch1Hcm2h7uNHA9HRo6HY1+XHA+j19H6OTxUj02vMX+F4uG49tprR7TceDFa3o9j0Y6R3MdHqetItj3cbeR4ODKj5f2Q42Fkt5Hj4chk+v0Yd8NSR5OciSVEHzkehOgjx8OxJT03I8jpdLJy5Uq53YMQyPEgRH9yPBxb0nMjhBBCiDFFem6EEEIIMaZIuBFCCCHEmCLhRgghhBBjioQbIYQQQowpEm6EEEIIMaZIuMmAvXv3ctZZZ1FTU8OJJ57ImjVrMt0kITLqM5/5DHl5efzzP/9zppsixDH31FNPUV1dTVVVFf/zP/+T6eaMCXIqeAY0NDTQ1NTEvHnzaGxs5OSTT6aurg6Px5PppgmRES+//DJ+v5/777+fP/3pT5lujhDHTCKRoKamhpdeegmfz8fJJ5/MunXrKCgoyHTTjmvSc5MBZWVlzJs3D4DS0lIKCwtpb2/PbKOEyKCzzjqL7OzsTDdDiGNu/fr1zJ49m4qKCrxeL5/85Cd5/vnnM92s456EmyG8+uqrfPrTn6a8vBxN03jssccGlVm1ahWTJ0/G5XKxaNEi1q9ff0T7eueddzBNkwkTJnzEVgtxdBzL40GI481HPT7q6+upqKhIPa+oqGD//v3HouljmoSbIQSDQebOncuqVauGXP/II49www03sHLlSt59913mzp3L0qVLaW5uTpWZN28ec+bMGfRVX1+fKtPe3s6XvvQlfvvb3x711yTEkTpWx4MQx6OROD7EUaDEQQHq0UcfTVu2cOFCde2116aem6apysvL1U9/+tNh1xuJRNTHPvYx9cADD4xUU4U46o7W8aCUUi+99JJatmzZSDRTiIw4kuNj7dq16uKLL06tv/7669Xvf//7Y9LesUx6bg5TLBbjnXfeYcmSJalluq6zZMkSXn/99WHVoZTi8ssv5+yzz+bSSy89Wk0V4qgbieNBiLFqOMfHwoULee+999i/fz+BQIBnn32WpUuXZqrJY4aEm8PU2tqKaZqUlJSkLS8pKaGxsXFYdaxdu5ZHHnmExx57jHnz5jFv3jy2bNlyNJorxFE1EscDwJIlS7jkkkt45plnqKyslGAkxoThHB82m4077riDf/qnf2LevHl8+9vfljOlRoAt0w0Yj8444wwsy8p0M4QYNf72t79luglCZMyFF17IhRdemOlmjCnSc3OYCgsLMQyDpqamtOVNTU2UlpZmqFVCZIYcD0IcmBwfmSPh5jA5HA5OPvlkXnzxxdQyy7J48cUXWbx4cQZbJsSxJ8eDEAcmx0fmyLDUEAKBADt27Eg937VrFxs3biQ/P5+JEydyww03cNlll3HKKaewcOFC7rrrLoLBIFdccUUGWy3E0SHHgxAHJsfHKJXp07VGo5deekkBg74uu+yyVJm7775bTZw4UTkcDrVw4UL1xhtvZK7BQhxFcjwIcWByfIxOcm8pIYQQQowpMudGCCGEEGOKhBshhBBCjCkSboQQQggxpki4EUIIIcSYIuFGCCGEEGOKhBshhBBCjCkSboQQQggxpki4EUIIIcSYIuFGCHFUXX755Vx88cWZbsZHEgqFWLZsGTk5OWiaRmdn55DLJk+ezF133TWsOlevXk1ubu5RbbcQ45WEGyHGgJaWFq655homTpyI0+mktLSUpUuXsnbt2kw3jV/+8pesXr069fyss87iW9/61ojU3d3dzU033cTMmTNxuVyUlpayZMkS/vKXvzCSF1+///77ee2111i3bh0NDQ34fL4hl7311ltcffXVw6pz+fLl1NXVjVgbAV5++eVU0BJiPJMbZwoxBixbtoxYLMb999/P1KlTaWpq4sUXX6Stre2o7jcWi+FwOA5axufzHZV9d3Z2csYZZ9DV1cWtt97KggULsNlsvPLKK9x4442cffbZI9YzsnPnTmbNmsWcOXMOuqyoqGjYdbrdbtxu94i0TwgxQIbvbSWE+Ig6OjoUoF5++eWDlgPUr371K3Xeeecpl8ulpkyZotasWZNW5sYbb1RVVVXK7XarKVOmqBUrVqhYLJZav3LlSjV37lx17733qsmTJytN05RSSq1Zs0bNmTNHuVwulZ+fr8455xwVCASUUkpddtll6qKLLko9ZsANBj/44AM1bdo09fOf/zytLRs2bFCA2r59+5Cv55prrlEej0ft379/0Dq/36/i8bhSSqn29nZ16aWXqtzcXOV2u9V5552n6urq0sq/9tpr6owzzlAul0tVVlaqb3zjG6n2n3nmmWntPfPMM4dcppRSkyZNUnfeeWeq3o6ODnX11Ver4uJi5XQ61ezZs9WTTz6plFLqd7/7nfL5fGnteOyxx9RJJ52knE6nmjJlirr55ptTr6P3e3jvvfeqiy++WLndbjV9+nT1+OOPK6WU2rVr10Fv3ijEeCLhRojjXDweV16vV33rW99SkUjkgOUAVVBQoO69915VW1urVqxYoQzDUFu3bk2V+fGPf6zWrl2rdu3apZ544glVUlKifvazn6XWr1y5Unk8HnXeeeepd999V23atEnV19crm82mfvGLX6hdu3apzZs3q1WrVim/36+USg83nZ2davHixeqqq65SDQ0NqqGhQSUSCXXbbbepmpqatPZ+85vfVB//+MeHfC2maaq8vDx19dVXH/L9ufDCC9WsWbPUq6++qjZu3KiWLl2qpk+fngptO3bsUB6PR915552qrq5OrV27Vp100knq8ssvV0op1dbWpq666iq1ePFi1dDQoNra2oZcplR6uDFNU5166qlq9uzZ6vnnn1c7d+5UTz75pHrmmWeUUoPDzauvvqpycnLU6tWr1c6dO9Xzzz+vJk+erG6++ea072FlZaV66KGH1Pbt29U3v/lN5fV6VVtbm0okEurPf/6zAlRtba1qaGhQnZ2dh3x/hBiLJNwIMQb86U9/Unl5ecrlcqnTTjtNff/731ebNm1KKwOor33ta2nLFi1apK655poD1vvzn/9cnXzyyannK1euVHa7XTU3N6eWvfPOOwpQH3744ZB19A83SiV7Qq6//vq0Mvv371eGYag333xTKaVULBZThYWFavXq1UPW2dTUpAD1i1/84oBtV0qpuro6Bai1a9emlrW2tiq3263++Mc/KqWU+vKXvzwoJL322mtK13UVDoeVUkpdf/31qd6ZXkMt6x9u/vrXvypd11Vtbe2QbRsYbs455xz1k5/8JK3Mgw8+qMrKylLPAbVixYrU80AgoAD17LPPKqWUeumllxSgOjo6hn5DhBgnZEKxEGPAsmXLqK+v54knnuC8887j5ZdfZv78+WkTeQEWL1486Pn777+fev7II49w+umnU1paitfrZcWKFezZsydtm0mTJqXNLZk7dy7nnHMOJ5xwApdccgn33nsvHR0dh9X+8vJyLrjgAu677z4AnnzySaLRKJdccsmQ5dUwJwu///772Gw2Fi1alFpWUFBAdXV16nVv2rSJ1atX4/V6U19Lly7Fsix27dp1WK+jv40bN1JZWcmMGTOGVX7Tpk386Ec/SmvHVVddRUNDA6FQKFXuxBNPTD32eDzk5OTQ3Nx8xO0UYiyScCPEGOFyuTj33HP593//d9atW8fll1/OypUrh73966+/zhe+8AXOP/98nnrqKTZs2MBNN91ELBZLK+fxeNKeG4bBCy+8wLPPPktNTQ1333031dXVhx0MvvKVr/Dwww8TDof53e9+x/Lly8nKyhqybFFREbm5uWzbtu2w9jGUQCDAV7/6VTZu3Jj62rRpE9u3b2fatGlHXO/hThYOBALccsstae3YsmUL27dvx+VypcrZ7fa07TRNw7KsI26nEGORhBshxqiamhqCwWDasjfeeGPQ81mzZgGwbt06Jk2axE033cQpp5xCVVUVu3fvHta+NE3j9NNP55ZbbmHDhg04HA4effTRIcs6HA5M0xy0/Pzzz8fj8fDf//3fPPfcc1x55ZUH3J+u6/zLv/wLv//976mvrx+0PhAIkEgkmDVrFolEgjfffDO1rq2tjdraWmpqagCYP38+W7duZfr06YO+DnUm2MGceOKJ7Nu3b9ine8+fP5/a2toh26Hrw/tV3dveod5fIcYTCTdCHOfa2to4++yz+d///V82b97Mrl27WLNmDbfffjsXXXRRWtk1a9Zw3333UVdXx8qVK1m/fj3XXXcdAFVVVezZs4eHH36YnTt38l//9V8HDCj9vfnmm/zkJz/h7bffZs+ePfzlL3+hpaUlFZoGmjx5Mm+++SYffvghra2tqV4HwzC4/PLL+f73v09VVdWgIbSBbrvtNiZMmMCiRYt44IEH2Lp1K9u3b+e+++7jpJNOIhAIUFVVxUUXXcRVV13F3//+dzZt2sQXv/hFKioqUu/Nv/3bv7Fu3Tquu+46Nm7cyPbt23n88cdT78uROvPMM/n4xz/OsmXLeOGFF9i1axfPPvsszz333JDlf/jDH/LAAw9wyy238I9//IP333+fhx9+mBUrVgx7n5MmTULTNJ566ilaWloIBAIf6TUIcdzK9KQfIcRHE4lE1Pe+9z01f/585fP5VFZWlqqurlYrVqxQoVAoVQ5Qq1atUueee65yOp1q8uTJ6pFHHkmr67vf/a4qKChQXq9XLV++XN15551pk157TwXvb+vWrWrp0qWqqKhIOZ1ONWPGDHX33Xen1g+cUFxbW6tOPfVU5Xa7FaB27dqVWrdz504FqNtvv31Yr72zs1N973vfU1VVVcrhcKiSkhK1ZMkS9eijjyrLspRSfaeC+3w+5Xa71dKlSwedCr5+/Xp17rnnKq/XqzwejzrxxBPVbbfdllp/JBOKlUqeaXXFFVeogoIC5XK51Jw5c9RTTz2llBr6VPDnnntOnXbaacrtdqucnBy1cOFC9dvf/ja1HlCPPvpo2jY+n0/97ne/Sz3/0Y9+pEpLS5WmaXIquBi3NKVG8DKeQohRS9M0Hn300VF9K4TXXnuNc845h71791JSUpLp5gghjlNyhWIhRMZFo1FaWlq4+eabueSSSyTYCCE+EplzI4TIuD/84Q9MmjSJzs5Obr/99kw3RwhxnJNhKSGEEEKMKdJzI4QQQogxRcKNEEIIIcYUCTdCCCGEGFMk3AghhBBiTJFwI4QQQogxRcKNEEIIIcYUCTdCCCGEGFM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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# look at effect of rank on model performance\n", "\n", "# arrange data in tidy format for plotting\n", "lambda_plot_df = results_df[results_df['Rank'] == 5].melt(\n", " id_vars=['Sparsity Coefficient'], \n", " value_vars=['SSE', 'FMS', 'Precision', 'Recall', 'F1'], \n", " var_name='Metric', \n", " value_name='Score'\n", ")\n", "\n", "# visualize cross-validation data\n", "ax = sns.lineplot(\n", " lambda_plot_df, \n", " x='Sparsity Coefficient', \n", " y='Score',\n", " hue='Metric', \n", ")\n", "ax.set(xscale='log');\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "SSE is fairly flat up to a sparsity coefficient of 0.2, above which there is a steady increase in model error. Conversely, FMS is high up to a sparsity of coefficient of 0.2, above which it steady decreases. Precision and recall show inverse trends, with precision increasing with greater sparsity and recall decreasing with greater sparsity. The F1 score balances precision and recall in its quantification of cluster accuracy, and its peak coincides with the inflection points of SSE and FMS at a sparsity coefficient of 0.2." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.8" } }, "nbformat": 4, "nbformat_minor": 4 }