{ "cells": [ { "cell_type": "markdown", "id": "9f71e66e-0109-4657-bae9-35d5dd337315", "metadata": {}, "source": [ "## Preprocess\n", "This section performs preprocessing on the ATAC-seq data. Steps include quality control, cell aggregation, normalization, and log transformation." ] }, { "cell_type": "code", "execution_count": 23, "id": "abe5e839-ff73-4822-bfc7-fa84a7611dcb", "metadata": {}, "outputs": [], "source": [ "import scanpy as sc\n", "import os\n", "import subprocess\n", "import sys\n", "from src.data.atac_preprocess import quality_control\n", "from src.data.atac_preprocess import deepen_atac_data" ] }, { "cell_type": "code", "execution_count": null, "id": "ad86eb60-5147-4835-a954-b3171819a296", "metadata": {}, "outputs": [], "source": [ "# NOTE: adata.var must contain the columns '#Chromosome', 'hg38_Start', and 'hg38_End'.\n", "ATAC_FILE_PATH = \"sample_data/PBMC169K\"\n", "sample_file = \"atac_pbmc_benchmark_VIB_10xv1_1.h5ad\"\n", "adata = sc.read_h5ad(os.path.join(ATAC_FILE_PATH, sample_file))\n", "adata.var['hg38_Start'] = adata.var['hg38_Start'].astype(int)\n", "adata.var['hg38_End'] = adata.var['hg38_End'].astype(int)" ] }, { "cell_type": "code", "execution_count": null, "id": "b36780ad", "metadata": {}, "outputs": [], "source": [ "ATAC_FILE_PATH = \"sample_data/PBMC169K\"\n", "sample_file = \"atac_pbmc_benchmark_VIB_10xv1_1.h5ad\"\n", "adata = sc.read_h5ad(os.path.join(ATAC_FILE_PATH, sample_file))\n", "adata.var['hg38_Start'] = adata.var['hg38_Start'].astype(int)\n", "adata.var['hg38_End'] = adata.var['hg38_End'].astype(int)" ] }, { "cell_type": "code", "execution_count": 28, "id": "629c14c6-315b-40ff-9009-d6db5b465c95", "metadata": {}, "outputs": [], "source": [ "# Preprocessing parameters for quality control and data aggregation\n", "# - min_features: Minimum number of features (peaks) required per cell\n", "# - max_features: Maximum number of features allowed per cell\n", "# - min_percent: Minimum percentage of cells expressing a feature\n", "# - cell_type_col: Column name for cell type annotation\n", "# - num_cell_merge: Number of cells to merge during cell aggregation\n", "data_args = {\n", " \"min_features\": 650,\n", " \"max_features\": 16500,\n", " \"min_percent\": 0.01,\n", " \"cell_type_col\": \"celltype\",\n", " \"num_cell_merge\": 10\n", "}\n", "preprocess_data_path = os.path.join(ATAC_FILE_PATH, f'{sample_file.split(\".h5ad\")[0]}_qc_deepen_norm_log.h5ad')" ] }, { "cell_type": "code", "execution_count": 29, "id": "69017dbd-d0c8-4c5e-a8c7-4c6ef1b432ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Before quality control: (2763, 411835)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ " FutureWarning:/cpfs01/projects-HDD/cfff-c7cd658afc74_HDD/jiaoyifeng/miniconda3/envs/scgpt_env/lib/python3.10/site-packages/episcanpy/preprocessing/_scanpy_fct.py:88: The specified parameters ('min_counts',) are no longer positional. Please specify them like `min_counts=None`\n", " FutureWarning:/cpfs01/projects-HDD/cfff-c7cd658afc74_HDD/jiaoyifeng/miniconda3/envs/scgpt_env/lib/python3.10/site-packages/episcanpy/preprocessing/_scanpy_fct.py:88: The specified parameters ('min_counts',) are no longer positional. Please specify them like `min_counts=None`\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "After quality control: (2595, 264533)\n" ] } ], "source": [ "# quality control\n", "print(f\"Before quality control: {adata.shape}\")\n", "adata = quality_control(\n", " adata,\n", " min_features=data_args.get(\"min_features\"),\n", " max_features=data_args.get(\"max_features\"),\n", " min_percent=data_args.get(\"min_percent\"),\n", " cell_type_col=data_args.get(\"cell_type_col\", \"cell type\")\n", ")\n", "print(f\"After quality control: {adata.shape}\")\n", "# cell aggregation\n", "adata = deepen_atac_data(adata, num_cell_merge=10)\n", "# normalize and log1p\n", "sc.pp.normalize_total(adata)\n", "sc.pp.log1p(adata)\n", "# write file\n", "adata.write_h5ad(preprocess_data_path)" ] }, { "cell_type": "markdown", "id": "ac9fc1a7-c6a4-4f47-8e79-1c5409f59f43", "metadata": {}, "source": [ "## run inference\n", "This section runs inference using a pretrained chromatin foundation model. The embeddings for cells are generated and saved to the specified output path." ] }, { "cell_type": "code", "execution_count": 30, "id": "d1e33490-9a9c-4dea-ab29-542986d7f594", "metadata": {}, "outputs": [], "source": [ "# Configuration for running cell embedding inference\n", "# - pretrain_checkpoint_path: Directory containing the pretrained model checkpoint\n", "# - pretrain_model_name: File name of the pretrained model\n", "# - pretrain_config_file: Configuration file used for model architecture and settings\n", "# - batch_size: Batch size for inference\n", "# - device: GPU device ID for computation\n", "# - output_path: Directory to save the inferred cell embeddings\n", "inference_config = {\n", " \"pretrain_checkpoint_path\": \"checkpoints\",\n", " \"pretrain_model_name\": \"model.pt\",\n", " \"pretrain_config_file\": \"chromfd_pretrain.yaml\",\n", " \"batch_size\": 16,\n", " \"device\": 1,\n", " \"output_path\": str(os.path.join(ATAC_FILE_PATH, \"cell_embedding\"))\n", "}" ] }, { "cell_type": "code", "execution_count": 31, "id": "3553e31a-d4e3-4f59-a672-cc3ad4e527a2", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:root:Reading h5ad file from sample_data/PBMC169K/atac_pbmc_benchmark_VIB_10xv1_1_qc_deepen_norm_log.h5ad\n", "100%|██████████| 163/163 [09:55<00:00, 3.65s/it]\n", "INFO:root:make directory sample_data/PBMC169K/cell_embedding\n", "INFO:root:Embeddings shape: (2595, 264533) saved to sample_data/PBMC169K/cell_embedding\n" ] }, { "data": { "text/plain": [ "CompletedProcess(args=['/cpfs01/projects-HDD/cfff-c7cd658afc74_HDD/jiaoyifeng/miniconda3/envs/scgpt_env/bin/python', '-m', 'src.cell_embedding', '--local_rank', '1', '--data_path', 'sample_data/PBMC169K/atac_pbmc_benchmark_VIB_10xv1_1_qc_deepen_norm_log.h5ad', '--output_path', 'sample_data/PBMC169K/cell_embedding', '--pretrain_checkpoint_path', 'checkpoints', '--pretrain_model_file', 'model.pt', '--pretrain_config_file', 'chromfd_pretrain.yaml', '--batch_size', '16', '--cell_type_col', 'celltype'], returncode=0)" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_command = [\n", " sys.executable, '-m', 'src.cell_embedding',\n", " '--local_rank', f'{inference_config[\"device\"]}',\n", " '--data_path', preprocess_data_path,\n", " '--output_path', inference_config['output_path'],\n", " '--pretrain_checkpoint_path', inference_config['pretrain_checkpoint_path'],\n", " '--pretrain_model_file', inference_config['pretrain_model_name'],\n", " '--pretrain_config_file', inference_config['pretrain_config_file'],\n", " '--batch_size', f'{inference_config[\"batch_size\"]}',\n", " '--cell_type_col', data_args[\"cell_type_col\"]\n", "]\n", "\n", "subprocess.run(train_command)" ] }, { "cell_type": "markdown", "id": "c25b9515-ce62-420b-a680-083c07edc12e", "metadata": {}, "source": [ "## metric\n", "This section evaluates the quality of the generated embeddings. It uses clustering metrics such as ARI, NMI, AMI, and FMI to assess performance." ] }, { "cell_type": "code", "execution_count": 32, "id": "7eb6fea9-b697-4f62-bf99-ceb8e9b23efa", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "from sklearn.metrics import adjusted_rand_score\n", "from sklearn.cluster import KMeans\n", "from sklearn.metrics import normalized_mutual_info_score\n", "from sklearn.metrics import adjusted_mutual_info_score\n", "from sklearn.metrics import fowlkes_mallows_score\n", "def calculate_cluster(mat_in, true_label, random_state=23):\n", " num_label = len(np.unique(true_label))\n", " kmeans = KMeans(n_clusters=num_label, random_state=random_state).fit(mat_in)\n", " return kmeans.labels_" ] }, { "cell_type": "code", "execution_count": 35, "id": "403e9873-6888-423d-88b8-e5392f6d5d4f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " ImplicitModificationWarning:/cpfs01/projects-HDD/cfff-c7cd658afc74_HDD/jiaoyifeng/miniconda3/envs/scgpt_env/lib/python3.10/site-packages/anndata/_core/aligned_df.py:67: Transforming to str index.\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAssAAAGvCAYAAACthZgKAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd4VEXbwOHf7qb3XgglJCEBQu+9K6AgKEUEEQREBQEVFSvtlWb5BKRY6IINkF6k9957S4EkpPeeze5+f8QsLLsJCYT+3O/F9XLmzJmZswnus7PPmVHodDodQgghhBBCCCPKRz0AIYQQQgghHlcSLAshhBBCCFEECZaFEEIIIYQoggTLQgghhBBCFEGCZSGEEEIIIYogwbIQQgghhBBFkGBZCCGEEEKIIkiwLIQQQgghRBEkWBZCCCGEEKIIEiwL8YT57bffqFq1Kubm5jg5OT2UPsPDw1EoFCxatEhfNn78eBQKxUPpvyR27dqFQqFgxYoVD7yv0ty7QqFg/Pjx+uNFixahUCgIDw9/MIMTQghRpswe9QCEECV36dIlBg4cSKdOnfj000+xsbF51EMSQgghnmoSLAvxBNm1axdarZYZM2YQEBDwqIcj7kH//v3p06cPlpaWj3ooQgghSkCCZSGeIHFxcQAPLf1ClD2VSoVKpXrUwxBCCFFCkrMsnjgDBw7E19fXqNxUHqlCoeC9995j+fLlVK9eHWtra5o2bcrZs2cB+PnnnwkICMDKyoo2bdoY5ZHu3buXXr16UbFiRSwtLalQoQIffPAB2dnZRmOys7MjNDSUjh07YmtrS7ly5Zg4cSI6na5E9zVnzhyCg4OxtLSkXLlyDB8+nJSUFP15X19fxo0bB4C7u7tRLqwply5donfv3ri7u2NtbU1QUBBffPGFQZ2oqCgGDRqEp6cnlpaWBAcHs2DBghKNuaQOHz5Mp06dcHR0xMbGhtatW7N//36DOoU/vytXrvD666/j6OiIu7s7X331FTqdjoiICLp164aDgwNeXl58//33JvvSaDR8/vnneHl5YWtry0svvURERMQ9jQlg3759NGzYECsrK/z9/fn5559N9pubm8sHH3yAu7s79vb2vPTSS0RGRhrVM5Wz7OvrS5cuXdi3bx+NGjXCysoKPz8/lixZYnT9mTNnaN26NdbW1pQvX56vv/6ahQsXGrV57NgxOnbsiJubG9bW1lSuXJlBgwaZHLsQQoiiycyyeOrt3buXtWvXMnz4cACmTJlCly5d+OSTT5gzZw7Dhg0jOTmZb775hkGDBrFjxw79tcuXLycrK4t3330XV1dXjhw5wo8//khkZCTLly836Eej0dCpUyeaNGnCN998w+bNmxk3bhz5+flMnDix2DGOHz+eCRMm0KFDB959910uX77M3LlzOXr0KPv378fc3Jzp06ezZMkSVq1axdy5c7Gzs6NWrVpFtnnmzBlatmyJubk5Q4cOxdfXl5CQENatW8ekSZMAiI2NpUmTJvoPFe7u7mzatInBgweTlpbG+++/f4+v+i07duygc+fO1K9fn3HjxqFUKlm4cCHt2rVj7969NGrUyKD+q6++SrVq1Zg6dSobNmzg66+/xsXFhZ9//pl27doxbdo0li1bxkcffUTDhg1p1aqVwfWTJk1CoVAwZswY4uLimD59Oh06dODUqVNYW1uXakxnz57l+eefx93dnfHjx5Ofn8+4cePw9PQ0us8hQ4awdOlS+vbtS7NmzdixYwcvvvhiiV+na9eu0bNnTwYPHsyAAQNYsGABAwcOpH79+gQHBwMFH2zatm2LQqHgs88+w9bWlnnz5hmldMTFxenH/emnn+Lk5ER4eDj//PNPiccjhBDiPzohnjADBgzQVapUyah83Lhxujt/pQGdpaWlLiwsTF/2888/6wCdl5eXLi0tTV/+2Wef6QCDullZWUb9TJkyRadQKHTXr183GBOgGzFihL5Mq9XqXnzxRZ2FhYUuPj6+yPuJi4vTWVhY6J5//nmdRqPRl8+aNUsH6BYsWGB0j8W1V6hVq1Y6e3t7g3EWjqvQ4MGDdd7e3rqEhASDOn369NE5Ojrq7z8sLEwH6BYuXGg0luJotVpdlSpVdB07djToNysrS1e5cmXdc889Z9Te0KFD9WX5+fm68uXL6xQKhW7q1Kn68uTkZJ21tbVuwIAB+rKdO3fqAJ2Pj4/Bz/Xvv//WAboZM2aUekzdu3fXWVlZGbyGFy5c0KlUKoN7P3XqlA7QDRs2zOD++/btqwN048aN05ctXLjQ6PesUqVKOkC3Z88efVlcXJzO0tJSN3r0aH3ZiBEjdAqFQnfy5El9WWJios7FxcWgzVWrVukA3dGjR3VCCCHuj6RhiKde+/btDdI2GjduDECPHj2wt7c3Kg8NDdWXFc5EAmRmZpKQkECzZs3Q6XScPHnSqK/33ntP//fC2dq8vDy2bdtW5Pi2bdtGXl4e77//PkrlrX+Sb731Fg4ODmzYsKEUd1sgPj6ePXv2MGjQICpWrGhwrjBVRafTsXLlSrp27YpOpyMhIUH/p2PHjqSmpnLixIlS9327U6dOcfXqVfr27UtiYqK+/czMTNq3b8+ePXvQarUG1wwZMkT/d5VKRYMGDdDpdAwePFhf7uTkRFBQkMHPqtAbb7xh8HPt2bMn3t7ebNy4sVRj0mg0/Pvvv3Tv3t3gNaxWrRodO3Y06LOw7ZEjRxqUl2Zmvnr16rRs2VJ/7O7ubnSPmzdvpmnTptSpU0df5uLiQr9+/QzaKsxpX79+PWq1usRjEEIIYUzSMMRT785g0dHREYAKFSqYLE9OTtaX3bhxg7Fjx7J27VqDcoDU1FSDY6VSiZ+fn0FZYGAgQLFr6l6/fh2AoKAgg3ILCwv8/Pz050ujMMCqUaNGkXXi4+NJSUnhl19+4ZdffjFZp/CBwnt19epVAAYMGFBkndTUVJydnfXHpn5eVlZWuLm5GZUnJiYatVelShWDY4VCQUBAgP5nUNIx5ebmkp2dbdQeFPysCgNkKPgZKpVK/P39jeqV1J33DeDs7Gzwe3f9+nWaNm1qVO/OlVFat25Njx49mDBhAj/88ANt2rShe/fu9O3bV1bhEEKIUpJgWTxxitoMQqPRmCwvauWBosp1/z2Qp9FoeO6550hKSmLMmDFUrVoVW1tboqKiGDhwoNGM6JOmcPyvv/56kYFjcTnRpenj22+/NZgNvZ2dnZ3Bsamfy91+Vg9iTLm5uaVu+36U5T0Wbs5y6NAh1q1bx7///sugQYP4/vvvOXTokNFrLoQQomgSLIsnjrOzs8EqEYXuZQa2OGfPnuXKlSssXryYN954Q1++detWk/W1Wi2hoaH62WSAK1euAJhcvaNQpUqVALh8+bLBzHReXh5hYWF06NCh1GMvbOfcuXNF1ilctUGj0dxTHyVRONPq4ODwwPq4U+HMcSGdTse1a9f0gX9Jx1S4gsid7UHBz+p2lSpVQqvVEhISYjCbfGe9+1WpUiWuXbtmVG6qDKBJkyY0adKESZMm8fvvv9OvXz/+/PNPg1QXIYQQxZOcZfHE8ff3JzU1lTNnzujLoqOjWbVqVZn2UzjTd/vMnk6nY8aMGUVeM2vWLIO6s2bNwtzcnPbt2xd5TYcOHbCwsGDmzJkGfc2fP5/U1NRSrahQyN3dnVatWrFgwQJu3LhhcK6wD5VKRY8ePVi5cqXJoDo+Pr7U/d6pfv36+Pv7891335GRkfFA+rjTkiVLSE9P1x+vWLGC6OhoOnfuXKoxqVQqOnbsyOrVqw1ew4sXL/Lvv/8aXFPY9syZMw3Kp0+fXib3VKhjx44cPHiQU6dO6cuSkpJYtmyZQb3k5GSjGenCWfSHPWMuhBBPOplZFk+cPn36MGbMGF5++WVGjhxJVlYWc+fOJTAw8L4fSLtd1apV8ff356OPPiIqKgoHBwdWrlxplLtcyMrKis2bNzNgwAAaN27Mpk2b2LBhA59//jnu7u5F9uPu7s5nn33GhAkT6NSpEy+99BKXL19mzpw5NGzYkNdff/2exj9z5kxatGhBvXr1GDp0KJUrVyY8PJwNGzbog62pU6eyc+dOGjduzFtvvUX16tVJSkrixIkTbNu2jaSkpHvqu5BSqWTevHl07tyZ4OBg3nzzTXx8fIiKimLnzp04ODiwbt26++rjTi4uLrRo0YI333yT2NhYpk+fTkBAAG+99VapxzRhwgQ2b95My5YtGTZsGPn5+fz4448EBwcbfFirU6cOr732GnPmzCE1NZVmzZqxffv2Imd879Unn3zC0qVLee655xgxYoR+6biKFSuSlJSkT1FavHgxc+bM4eWXX8bf35/09HR+/fVXHBwceOGFF8p0TEII8bSTYFk8cVxdXVm1ahUffvghn3zyCZUrV2bKlClcvXq1TINlc3Nz1q1bx8iRI5kyZQpWVla8/PLLvPfee9SuXduovkqlYvPmzbz77rt8/PHH2NvbM27cOMaOHXvXvsaPH4+7uzuzZs3igw8+wMXFhaFDhzJ58mTMzc3vafy1a9fm0KFDfPXVV8ydO5ecnBwqVapE79699XU8PT05cuQIEydO5J9//mHOnDm4uroSHBzMtGnT7qnfO7Vp04aDBw/yv//9j1mzZpGRkYGXlxeNGzfm7bffLpM+bvf5559z5swZpkyZQnp6Ou3bt2fOnDnY2NiUeky1atXi33//5cMPP2Ts2LGUL1+eCRMmEB0dbRAsAyxYsAB3d3eWLVvG6tWradeuHRs2bDB6kPR+VKhQgZ07dzJy5EgmT56Mu7s7w4cPx9bWlpEjR2JlZQUUPOB35MgR/vzzT2JjY3F0dKRRo0YsW7aMypUrl9l4hBDiWaDQ3cvTI0IIAwMHDmTFihUmv9YX4kF7//33+fnnn8nIyJCttIUQooxJzrIQQjxB7txqPTExkd9++40WLVpIoCyEEA+ApGEIIcQTpGnTprRp04Zq1aoRGxvL/PnzSUtL46uvvnrUQxNCiKeSBMtCCPEEeeGFF1ixYgW//PILCoWCevXqMX/+fFq1avWohyaEEE8lyVkWQgghhBCiCJKzLIQQQgghRBEkWBZCCCGEEKIIjyRnWavVcvPmTezt7fWL6AshhBDi8abT6UhPT6dcuXIolTLfJp4NjyRYvnnzZpku1C+EEEKIhyciIoLy5cs/6mEI8VA8kmDZ3t4eKPjH5uDg8CiGIIQQQohSSktLo0KFCvr3cSGeBY8kWC5MvXBwcJBgWQghhHjCSAqleJZIwpEQQgghhBBFkGBZCCGEEEKIIkiwLIQQQgghRBEkWBZCCCGEEKIIEiwLIYQQQghRBAmWhRBCCCGEKIIEy0IIIYQQQhRBgmUhhBBCCCGKIMGyEEIIIYQQRZBgWQghhBBCiCJIsCyEEEIIIUQRzB71AIQQzyadTseyi8s4cPMAnjaefNTwI2zNbR/1sIQQQggDEiwLIR6JhecX8sPxH/THK6+uZG6HuTT3af4IRyWEEEIYkmBZCPHQxGTGMOXwFEJTQ4nKiDI4p0PH8O3D2f3qbhwtHR/RCIUQQghDEiwLIR64reFbmX16NqEpoejQFVlPo9OwOWwzr1Z99SGOTgghhCiaBMtCiAcmIy+Dz/d9zs6InSW+JjI98gGOSAghhCgdCZaFEA9ERl4GHVZ0IFOdWarrglyDHtCIhBBCiNKTYFkI8UD8cuaXEgXKHtYeAKi1arpX6U4Xvy4PemhCCCFEiUmwLIQoUwnZCSRmJ5Kdn33XunXd67LkhSUPYVRCCCHEvZFgWQhRJtQaNUsvLOXHUz+i1qrxsfNBpVCh0WmM6r4a+CoNvRrSsXLHRzBSIYQQouQkWBZC3LeknCT6b+zPjfQb+rKojCg6VOzAnsg95Gnz9OX1POrxZdMvH8UwhRBCiFKTYFkIcd9+Pf2rQaBcyExpxpaeW/jp1E9cSLpAy/Iteaf2O49ghEIIIcS9kWBZCHHP1Bo1m8M3czzuuMnzLlYuuFq78kXTLx7yyIQQQoiyIcHyYyTvxg1ip04j+8wZ0OmwqVcPr4kTMHN2BkCn0ZB95gwKMzOsa9Z8xKMVz7prKdd4c/ObpOSmFFnH38n/4Q1ICCGEeAAkWH5ENCkpRAwbTvbJkyhtbXEbNZLkJb+hjojQ10nfupWskyexqVsH25atSN+8mcwDBwBw6NoVn2+/eVTDF0+4fVH7GLd/HOnqdLoHdOezRp+hUChKfH14ajhD1g1Fk6VEYalApzDela+uR11e8n+pLIcthBBCPHQKnU5X9N6zD0haWhqOjo6kpqbi4ODwsLt/5FI3bCBm3Hi0GRn31U6l33/Hpl7dMhqVeFZk5GXQ5q825Gpz9WUf1vuQN2u+WaLrt1/fzux/ltD6Sl/MdObE2oWzodpc8sxyAPi80efUcq9FoEsg5krzB3IPQohH41l//xbPJuWjHsCzJnXtWm6O/ui+A2UAXV7e3SsJcYcv931pECgDzDw5kyx1lv44V5PL2pC1/HP1H9Ly0gzq/t/R/6PV1T6Y6QoCYc8MX2rfbKc/H+QSRLBbsATKQgghngqShvGQxc+YWex5pZ0d2uxs0BivTWvA0pKEOXPIOnIYt3ffRWEugYm4u9CUULZHbDcqz9flczHpIvU966PWqnlry1ucjDsJwMJzC/n9xd/Jzs9mzbU1pGanY661NLjeKt8WgDeqv0E9z3oP/kaEEEKIh0SC5YdIm5ODOiam+Dq5uQWBslIJWm3RFXNzyTpyhKwjR9Bm5+A55pMyHq14GukoOuvK1coVgNNxp/WBMkB4Wjj/O/g/TsafJCaz4Pc3xPUk/okFKUAaRT5X3Y4xuMZg3q///oMbvBBCCPEISLD8EGWfOXP3GWO1uuD/iwuU75D02xIU5uZ4fPjBfYxOPAv8nfwxU5iRr8s3KH854GV8HX0BsFBZGF23KXyTwfHWKou4ErCfivHBhNqfo25wVYbXGf7Axi2EEEI8KhIsP0Qqe/sH03C+hsRffiF9x3ZcBgzAuVevB9OPeCyotWoSsxNxtXYtUV7wybiTXEy8yIm4E4SkhHDnM7213GoxsflE/XENtxoEOgVyJeVK0Y0q4LriKlTJY1P3daVaSUMIIYR4kkiw/BBZVauGc7++JC/7/YG0n3cthJivxqK0scHxxRcfSB/iwYjPimdT2CYsVZa8FPAS1mbW+nNanZa03DQcLR0JTQ3l7a1vE5sVi6eNJz91+IkA5wCTbUZnRPP21rcJSwsrsl+VQsXklpMB2By+mT0Re7iQeIGQ1BCDemZKM6xV1qSr0w3Kr6ddZ23IWroFdLvXWxdCCCEeaxIsP2ReX31FbmgYWQcP3rWuwsYGXVbWXevdKXHefAmWnyAJ2Qn02dCHuKw4AKafmE6AUwD9qvWjsmNlhm0bRlx2HP6O/thb2BObFQtAbFYsU49MZV7HeUZtRmdE89qG10jMSSy2b41Og525HZvDN/Px7o9N1ilnW47OlTsz/9x8k+fD08JLcbdCCCHEk0WWjnsEPD4ajbIwJUOhwGXgQNyGD0fl6mpQz651a1wGDSp1+7kXLxL33XdlMVRRhnQ6Hd8d/Y7nVzzPq+tfJTI9EoAdN3boA2WADHUGp+JPMWbvGD7Z/Qlx2QXnQlJDCEkxnPFNyEkw6ud62nV6rut510AZwNvWGydLJ3ZF7CqyzstVXqaaa7UizzfyanTXfoQQQognlQTLj4B1cDB+a9fgM306viuW4/npGGybNkGTmWlQLy80FPeRIzDz8Ch1H4kLF5F99lxZDVmUgbmn5rL4wmKiM6O5kHiBl9e8jFqjxsbcxmR9rU5LfE68QZmVmZXBcUhKCNOOTNMfR6ZH8tHuj4zWRi5KU++m/Hn5T1JzU02eD3IO4tWgV9kUtsnonLu1O9+2+pam5ZqWqC8hhBDiSSRpGI+Iubc35t7e+uPIUe9DTo5BndzLl0nbvBmfGdOJ+uBD8uPisKpZk5zTp+/egUbDjYEDqfjbb1hXL3pWUDwYeZo85p+bT2R6JM3KNeNFvxfZEbHDoE6OJofF5xdjrir6Ib1m3s349/q/+mNTs8VLLy6lXcV2nIw7yY8nfyzVOP+59o/+7zZmNmTlZ2FrbsvYJmOp5FCJKs5V2BS2ie03bq3NrEDBzHYzaVOhTan6EkIIIZ5EEiw/BjIPHkSTaPor86yTp1BHReHyxhs49eyB0t6eyFHvk7Fly61K5ua3lpy7jTYzk/DevSk//QfsO3R4UMMXJnyx7ws2h28GYG3IWqIzo03m9u6N3MvJ+JNG5QDv1n6Xd2u/S6MrjTgSfYSwtDCuJJteoeJS4iVmnZx1X2POyi/Ij89UZ7I+dD1zOswBICU3xaCeDh3ett53Xi6EEEI8lSRYfgzkhl8v8lzqX3/p/x4/cyZOvXrh8+035L49FHVUFPlxccR+PanoxvPziZs+XYLlh2xnxE6D4x9P/IgW47WzozOji9wo5ErSFbLzszFXmrP1xla0uqLX3v7m2Dd3HdOXjb/kcvJlll9Zfte6e6P2kqXOwsbchjYV2jD39Fwy1QVpQtVdq+Pn5HfXNoQQQoingQTLjwEzd/cS1dPl5JD8228orSzxGD0a6+Bgso4fv/uF2qJ3bRMPhpetF9fTbn0IMhUomynMiM6KLrKN7RHbafZHMxwtHYsNlE1RoqSiQ0XyNHkADKk1hF6BBetvty7fmhknZnA15WqR19uZ2+nzoys5VGLZC8tYF7IOG3Mb+lbtW6L1nYUQQoingQTLjwHr6tVAoQBdyYLa7FO3cpZt6tfH9d13SJz7k+nKKhVuw4aVxTBFKUxrNY1+G/qh0ZnesbGxd2MORx++azsanYaknKQS99uvaj/K2ZWjQ6UOlLMrZ7JO6wqtuZB0gaunDIPlWm61OJNwBltzW6a1moZScev5X38nf9nKWgghxDNJguXHgHm5ctg0akTW4VvBk8LKCp1WC3l5RvUtq1U1OPYYNQqVqytxd6RjWFavhiYhkeSlS7EKCsSySpUHcwPCSJY6y+RssEqh4vvW3xOfHV+iYLk0vG29ebfOuzhaOt61rrOls1HZ540/p4JDBWzMbDBTyn8ahBBCCJCl4x4beRE3DI4VFhZY+Poa1VPY2ODx4YdG5bqsbKOy3AsXyY+LI/vUKSLeebfMxirubsWVFUa5yAoUTG45mfaV2tO5cmcq2lcsdbtu1m4G7b0S8AqdfDvxVs23WPrC0hIFygDtK7Y3aKu2e20CXQJxsHCQQFkIIYS4jbwrPibM3T3Iv3krf1WblkZemvFauSpHR5RWt9ba1aSnEzH0bbJPml5RoZA6KgpNRiYqO9uyG7Qo0u3bVUNBDvCmVzbhZOUEgKOlI390+YM9kXvYEraFnZE7jdpQoDAKuAOcAuhbtS+xWbG0qdCGFj4t7ml87jbu/Pnin0w/MZ1LSZeoYF+BlJwU3G1Klj8vhBBCPCsUOl0JE2XLUFpaGo6OjqSmpuLg4PCwu38s5V69SsQ776KOiiq2nsPLL4NajS4vD+fX+5GxezdJ8xfctX3LwCr4rV1L5pEjJP46DxTg9s672NSrW1a3IG4TnRHNm5vfJCozCnOFOdVcq6FSqni+0vO8Xv11g7pJOUm0/autyYcATdnZe6fBrPC92hu5l2Hbb+WzBzgFsPKllQa5ykIIcTt5/xbPIplZfkxYVqlCwPZt5CcnE/rSS2jib21jrLCzw6JiRWybNyPpt6X6zUvSd+zAumbNErXvPXEieTduEDH0bXT/XZ997DiV169DEx+PLj8f69q1UZjJr0RZOBJzRL9NtbnKnDMJZwA4GXcSJysnuvh1YW3IWuaemotSocTJyqnED/LFZMaUSbB8KPqQwfG1lGskZCfgYVP6HSOFEEKIp5VERo8ZM2dnKv76K+G9X0X338N9uowMci9cQOXoaLjLX36+UfqFdYMGZB8/briyhrU1llWqkL5rlz5QBtBmZRHSrv2tavXrU2nhAhQWFhy4eYBjMcfwd/LnRb8XH8zNPqWSc5IZf3A8+dp84NZmH4W2X99OgFMAX+3/Sv8QoAIFZkoz8rX5uFq54mDpQFhqmFHbNmY2VHasfF/jy1Jn8cmeT9gTuceg3NHSESdLp/tqWwghhHjaSLD8GLL089MHyre7fbUMk9dVqUKlBfPJ2H+AqPffR5ebCxQE4IXtolSC1vTX/dnHj5OyciUHGjvw6d5P9eWHow/zbu138baTXdtKIjU3VR8om3I89jihKaEGq2Xo0JGvzaeLXxc+b/w5Wp2WhecWkqHOAApmgZ0snZjUfBK25veXd/7r2V/ZHblbf6xAQUWHikxsNhELlQUAGq2GlVdXEpURRQufFjT0anhffQohhBBPKgmWH0MKCwus69Uj+8QJwxNFBLmF8qKiuP7mIJxe7q4PlAHyb94kY/duHF54Ae9Jk0iYPZv8+HiDOoUydu9mtavh2sCrrq1i9bXV+Dr6okBBmwptGFVvlOS2FqG8fXmCXYM5n3je5PlMdSbBbsFYqizJ1Rj+DNaHrufD+h/ibuNeJusaX02+yoGbB/C29eZ53+cBiMowzItXKpSs7b7W4Oc54eAEVl1bBcCi84v4sd2PtCrf6r7HI4QQQjxpJNp5TJWfPQur2rVKdY0uK4vs48eJnWa89XHi/PlcqlWbpEWLqPDLL7gOGWyyDfPy5U0uP6ZDR1hqGKGpoSw4t4Av931ZqrE9S8yUZlSwr1Dk+WDXYAZuHki+Nh8LpYXR+XWh6yiL525Px5/mtQ2v8d2x7xi9ezRTDk8BCnbwu10LnxYGgbJOp2Nd6Dr9sVanZX3o+vsejxBCCPEkkmD5MWXm7Ezlv/7C+Y03iq2nsLbGzNvLoEybnm5Yx8aGnPMX0OXlkXv5MpEjR5C0dJlRWyonJ1zeeIP3671Pebvyxfa7LnQdSy8sLdXucs8KjVbDlvAtBmX1POrRPaA7vQN7cyr+FAnZCWh0GvK0eUYB8w/Hf2Da0Wn3PY6VV1YazFz/ffnvgpxoa1fszO1QoMDP0Y/JLScbXDflyBSjNBJTm5gIIYQQzwIJlh9zXp9/hvto401IMDcHhQJddjb5MbHFtqHLMnzALO/6DbSpqbcKzMzwnjaVymvXYFGxIuXtyzOt5TQsVZbFtjvt6DReWfMKEekRJb6fZ4VCoTA41ug0/K/5/9D997/buVi5UNXZcFfGdSHruF93rvVsobJAp9Px4a4PyVBnoENHaGooq64WpFuotWp+Ov0Tf1z6w+A6b1tv3q799n2PRwghhHgSSbD8BLBv167gwbzbKG1sbq14Ucqv7M29PA2OFWZmOL70EuYet5YM++PyH0b5tKYk5iTSe11vGi1rxOsbX2dD6IYySSF4UqXkpPDK2lfQ6Azzvk/Hn2bE9hFEpkcaXdPIuxGBLoEGZWqtmvDU8Psay+Cag6nkUAkoSA35ssmXJGQnkJ5n+M1DdGY0aq2at7e+zexTs43aSc9Nl1UyhBBCPLMkWH4CWPr7U+HXXzHz8dGXGcwMAyoPD7hjNtMU64YNcX1rKCoXl4IChQKPD943mgktzcN7GeoMsvOzOR1/mk/3fsrYA2NLfO3T5qczPxGaGmry3K7IXdhb2BuUKVDwRaMvGFl3JN62t1Ybyc7PZujWoSX6wFIUDxsPVnRdwZ9d/uTfHv/i5+hHl1VdjPpv5dOKgzcPcjTmqMl2MvIz9KtyCCGEEM8aCZafEHbNm2EdHGz6pLk5msTEEs0wZx89SszYsVjVrInPnNlU/mclLgMGGNUbXGOwPk9Vwd2D8NutvraaLHXW3Ss+he6Ww22hssDLpiDH3ExpxtctvsbGwgZPW0+6+nc1qBudGc3V5Kv3NR4rMyuCXYPxsPFg9O7R5GlvLUmoQMGP7X6kmU+zYtuo7lodBwvZqUsIIcSzSYLlJ4jKycng2MzDg/Jz56C0sACNxvRFRcjcvRszZ2esqlUzed7PyY9V3VYxteVUJrWYhLnS3OB8Facq9KvaD39H/1L1+7R7ruJzRZ5ToGB96HpismKwVFkyq90sXvJ/CYBt17cRlxVndM2YPWPIVGeWydhMzQ5Xd63O4ejDJOYkolKoTF7XybdTmfQvhBBCPIlkneUniPuI98g+eZLcq1dR2ttTbtpUbJo0QadWG1YsZuMRA3eps+raKmaemIkOHXXc65Cam4oWLW/VfItuAd0ASMhO4K0tb3Et5ZrBtYnZidiY25Tq/p505xPOM/7geJPn6rjX4VzCOfJ1BatM5Gpy2Ri2keY+zZl0aBJ/Xv4TAJVCZZDvfCP9BkdjjtKmQpv7Hl+7Cu30aydDwYN7XVd3vWswfjj6MG/WePO++xdCCCGeRDKz/AQxc3en8upVBOzcQZU9u7Ft2pTcixcxL1dOX0dhaUmlpUvxnjwZC39/LKtWpcKvvxJ46CCWt80i27ZogXWdOkX2dSPtBjNOzNCv3HAq/hTv1H6H9S+v1wfKAG7WbrxV8y2Dax0tHXG1di2ju34yhKeGM2DzANLy0kyeP5dwzmgVDHOlOXmaPP66/Je+7M4HAwHszO0Mdvu7V3Xc6xgcx2fHl2jWev/N/WwO23zf/QshhBBPIplZfsIoVCrMvQseBFPHxXF94Jto0/4L0MzMKP/jTGzq1cWmXl2cXnnZ4Frf35eRsXsPCgtzbJs2RafRoFCZ/urdVNCXGBtOvls66ogbmJcrp99G+wW/FwqWILu2CgcLB8Y2HfvMzSrvidxT7MN4hTPKhTxtPBlScwhKhbIgaL4tlzjAKUA/U/9ywMssOr+IwVsG427tztfNv6ZJuSalHt+msE1Gs95qrdp0ZRO23dhGp8qSjiGEEOLZIzPLT7CcCxduBcoA+fnkhocXWV9pbY1Dp46oo25yuVFjLteuQ+yUqSbrBjoHUs3l1ky0fRb4jvqRq82bE96jJyEdniPz0GH9+ffqvsf2XttZ1W0VdT3q3ve9PWnu3EK6OI4Wjqzqtory9uUxU5rxaeNP9fnClRwq8evzv7LplU1s7rEZN2s3dkfuRqvTEpsVy1tb32LmiZmlHt/8s/ONZrYtlBZF5infyc3KrdR9CiGEEE8DCZafYBYVKxmVJcyeQ9bRo2Ts2UN+kvHKDLmhYcROngxqNeh0JC1eTMbu3QZ1tHl5ZK1ez/epnRhReQC99sPkxfm4pVFwHaDNzCR20qQHcl9PIlMP5xWyMTOcZU/NS2Xu6bn6416Bvdj4ykaWvbCM5V2X42btRnn78vjY+XAz86ZRe7+e/ZUz8WdKNT6V0jAotlRZ8mP7H3mn9jslur6Lf5e7VxJCCCGeQpKG8QSz9KuM0tYWbeatvFNtairX+xdska1ydaXSb79h6VeZsNQwlAolbvHxRkvMqeNuBXo6jYaIt4aSdbhg1riNuzuaeMMUAn1fWc/m8nCmFJej7WDhQFa+4Wu15toaPmn4if64nF05ytmVu/NSWpdvzYbQDUblyTnJpRrfqHqjGLVjFDmaHKzNrJndfjbVXKrxzlbjYFmBwmAW2trMWr+5iRBCCPGskWD5Cefc9zUSf51n8pwmMZH4X3/hx85aNoZtBODV8i/Rp3x51JEFO8kp7e2xqVOHyA8+IOvoMcy9vMg5d+5WG/HxWPj7kRdivNGGc79+D+COnkyvBr1q8KDe7WKyYozKzJQl+6fXuXJndkXs0v/8oGAVizoedUo1vmblmrHu5XWEpoTi7+TPutB1vLf9PaPUDMCobFjtYUabqQghhBDPCgmWn3Aeo0eTsmIlmmTTM42XEi+yMSxEf/xX5FpemP4DPuuOoVPn4dSnD0lLlpC+qWC1A01CglEbLm8MQJeXhyYlBfNKFdHEx2NZpQp2rVo9mJt6wuyO2M3o3aNLdc3gGoP1f1dr1fx0+ifOxJ+hmks1htcdjqXKEoD0vHT+Df/X4Nou/l1wtHQs9Ti9bL3wsvViT+QeZpyYUeLrGng1KHVfQgghxNNCguWnQMUliwnv2QtdrvFqDGYBfkCIQVmmkyWen30KQOL8+aQsX2FwXmFlhS4nBwCbxo1xfLl7wcYnwqSpR6YarIRxZxrD7QrP/Xr2V+p71SfYNZgZx2ew+MJiAA5FHyJdnc64puOAgm2vjZaTu/tGjcUKSw0r9nyQcxCXky8D0D2gOzXcatxfh0IIIcQTTILlp4BVlSoEHj1CxNvvkHXwoL7czMOdOm+8T8UDl7mRfgMoWJasvmd9APJu3CDuu++N2rNr0wb3kSPQZmdjVbVqkcvLiQJ3LhlXVKB8+7mU3BR+OP4D856fx5GYIwZ1jkQf4UbaDbztvDkRe4IK9hWISI8ACh4W7Fy5c4nHNvf0XBaeW4iFyoK3a71Nam4q8VnxxQb06XnpjG0ylhpuNajmanqHRyGEEOJZodDpdPc5T1V6aWlpODo6kpqaioODw8Pu/qmWGxZG+patoFTg2K0b5h4epOSksC50HUqFkpf8X9Lnn2afPUt4r94G11s3aEDFn39CaWv7KIb/RFp4biH/d/z/Sn1dLfdaLHthGZ/u/dTgIb7CXfycLJ1IyU3Rl7ep0IYP6n2An5Nfido/cPMAb299u9TjArC3sGdrz63YmsvvgRDiFnn/Fs8imVl+ylhWrozl20MNypysnOhfvb9x3aAgLKtVI/fiRQCUjo6UmzpVHyjr1GoSfvmF3GvXsKlXH+fX+6FQKB78TTxh3qzxJlVdqvLjyR85m3DW4Jy/oz9NvJuw7NIyo+v6Vu0LwGeNPiM9L52z8WfJzM8kT1OwQcntgTJAUk7SXQPlmMwYJh+eTExmDO7W7vd8T+l56cRlxVHZsfI9tyGEEEI8DSRYfoYpLSyotGQxyct+R5ubg1O3bliU99Gfj/nf16T8/TcAqZs2c/LCKbLcXPCpXpO6nbpI4HybpuWasv36doNgWalQ8mP7H6lgX4EMdQZrQtYABakwXzb5Up8O42jpyOz2swFo8nsTfbB8J0eLuz/UN3LHSC4mFXz4uchFzBRmRrsHloRSoTS5lJ0QQgjxrJFg+RmnsrfH7R3TX9Vn7Nmj//v58u5EhF6CULhy5AB5qSk06WM8W/2sytfmszdqr0HZWzXfooJ9BQC+bvE1A4IHcDr+NOGp4VxJvkIVpyo4WBp+jflywMssvbgUKHgY0M7CjvS8dMrZluPjhh/fdQyFgXKhRt6NcLRwxFxljlanZX3o+hLdTznbcvoVOYQQQohnmQTLokjm5X3IjylYIzje3nAXuqubN0iwfJuE7ASj3fYORR/ivbrv6Y9Px51mwqEJ+uPJhydT0a4iz1d+nsj0SBp7N+aThp9Q3bU619Ou09i7MbXda5OQnYC7tTvmKnM2h21mwbkFmCnNGFlvJE28m+jbM1OaEegcyJXkK/qyZuWaMSB4gP74k4afsObaGr4/bvxgZyEbMxvGNh17X6+HEEII8bSQB/xEkfKuXydy5Chyr13jYGUvkm2t9OfKpWTg/8JL1BnyNhaP0cOAqbmpnE04i7u1O0EuQQ+tX7VGTdM/mhotIXf89eOYKc34bN9nJnfiu5Ovgy+TW0ympntNo3MXEi/Qd0Nf/VJy1mbWrO2+Fi9bL32dyPRIhm0bRmxWLH5Ofsx/fj4xWTEsPLcQrU5L/+r9qeJUha/2f8W60HVGfQQ6B7Kg44J7WsdZCPH0k/dv8SySYFnclU6n48onH7P78mkyrCxwzsyhXngMFhot+RYW+M2fh23Dho9sfOtD1vPzmZ8BSMtLIyknCQA/Rz/S8tJws3ajRbkWnIg7ga25LUNrDWVD6AYiMyJp4dOCftVu7USo1WlRa9WlTkHYfmM73x79lqiMKIPykXVHsuraKv3SbyWhUqiY33G+Pqc5S51FpjqT7de3M+nIJIO6Pz/3M83KNdMfLzi7gB9O/KA/blexHafiTulfE3tze1a+tBJvO29upN9g/P7xnIw7Sb4uH2dLZ+Z2mEuwW3Cp7l0I8eyQ92/xLJJgWZSITq0m5IUXyYuI4M7H+lRengTu2vVQx6PRajgYfZDNYZv1D86VlLnSHLVWrT9+M/hNPmzwIVvCt/Dl/i/Jzs+mc+XOTGkxBZXScI3pDaEb+L/j/4dWp2VoraG8VvU15p+dz/QT0032VbgMXGm18GnBV02+4nT8ab7c9yV52jysVFbkaHL0daxUVqx/eT3OVs4svbCUaynX2HZ9G9mabH0dWzNbMvMzDdqe1nIaL/i9oD/Ozs8mOjMaLxsvbMwN022EEOJ28v4tnkWSsyxKRGFujnOfV4n79jujc9qkZDT5ak79u4H0xHj8GzShQnXjNIKyotVpGbVzFLsjd9/T9bcHygCLzi+iSbkmfL7vc30axaawTTTwbEDvoFvrUIenhvPlvi/1q0tMOTyFYNdgVlwx3AGxkKXSklyt8a6KJbEvah/dVndDo9Pox3t7oAwwuOZgfrvwG79d/A2tTmuyHSszK6NgOUOdYXBsbWaNn2PJ1m4WQgghnjXKRz0A8eRwGTQI908/JcvNxaDcoXMnNsz8ll1L5nF8wxqWT/yC8DMnH9g4TsefLjpQLsH3JMo7fu116NgQusFoJ76o9CjCU8P15RHpEQbLsOnQMfHgRLLyswyu83fyp235tuRrS79k2+1yNDlGgf3tYjJjWHxhcZGBMkBabppR2ffHvidLnWWithBCCCHuJMGyKDGFQoHbwAHU37cf59EfYFauHBa+vtg89xxXDx/Q19PptFw+sLeYlh4QHXglWNL8tAuBDv4FY0aBr4MvfYL6UN6uPEHOQYxvPh7FHckk5e3KE+x6K1dXpVDx15W/6Lq6K11XdeV62nWquVbDwcLwa8fLyZf1+cCF3K3c2Rm5Ew2lT78oXGru9nEUun3MgU6BnIg9cdf21DrjYDsrP8sot1oIIYQQpknOsii1/MREQl54EW1qakGBuRmHqlcmiVsznCpzC5r16kujbj3vu79MdSYLzy0kKSeJzpU7U9+zPqN2jGJX5C6gIHfXJkdF0EVLgiLtafLKqzTr/TqxWbHYmdthZ2Fn1Obm8M18ue9LcjW51POox9wOc1Fr1Sw8t5C0vDQORR8yeCivfcX2TG87nUtJl/jlzC8cjz1uFCTfrxquNRhYYyCf7vnUaCMRc6U5Par04M/Lf+rLHCwcSMsznjm+XVXnqpgpzTiXeM7gun97/GvydRFCiOLI+7d4FkmwLEot89Ahbgx806DMbMibbDxzmPxcw1SGXl9NpmKNWvfcl06nY+DmgZyIK5hFLVwpoq5HXQ7dPIRaq6ZJuSaYY0ZCxHUsrKxx8vIuUdtZ6izS89LxsPEw2o3w+RXPE50ZrT8Odg3G1tyWTHUmr1V9jQuJF/j90u/3fF93auzVmG9bf4uzlTPLLixj6cWlRGZEGtS5cw3lkqjrUZdXAl7hUPQhDsccxt3anbFNx1LDrUaZjV0I8eyQ92/xLJJgWZSa+uZNQjp1Rpf337bMCgWVli0jzgxWTvrKoG5cZRW1rAKxs3OkVb83cfb2MdFi0RKyE2j7d1uDsgHVB/BRw4/u6x7u5qfTPzH7VMEW1AoUWJtZ63OTFSiY1X4WK66s4EjMETRajcHDd25WbthZ2BGeFl7i/hwtHJnccjLWZtYM/ncwujuSr1UKFc19mrMnck8RLRRvboe5tPBpcU/XCiFEIXn/Fs8iWQ1DlJp5uXL4TP+BuG++RadW4/rWEGzq1cUrIwMbRyeyUlMA0Ch0uIflE0PBFsyxYSEM+uFnzCwsStyXvYU91mbWZOffWg7N3ca9TO/HlHdqv4Ofox/XUq7hYuXCpMO31jfWoWPnjZ3MbDcTKFjbefqx6ZxOOE2gcyA9q/TkrS1vlaq/1LxURu0cxWtBrxkFyu7W7rxf/322hm+95/s5HntcgmUhhBDiHsgDfuKe2Ldrh//mTQRs34Zznz4AWNnZ0XvsFCK9crnumUVouQyDh9LSE+JJS4grVT+WKkumtZyGrXnBLoFtK7Slb9W+ZXcjRfj78t8sPLeQ0/GnqepcFSuVlcH5DaEb9CtKOFg4MLbZWFa+tJIpLacQmhZq8sE6paL4f2752nw2hW0yKLMxs2H9y+tRKpT6HO1CChT4OZRsyTdZGk4IIYS4NzKzLMpMZkoyUZfPk+xrznGXGCpF21Alyl5/3srWjlwrHSk5KThZORXblkarYenFpVxJvkJt99oceO0AOfk5RW6aodNqORhziJCUEOp61L2vnNw9kXv436H/6Y+vJF+hXcV2bAzbqC/L1mSTnJtscjy+Dr4GxwoUVHetTk23mqy4uqLYJeUSchIMjpt4N8FCZcH5hPNGdUc3GI2njSdj9o4xWj7O1swWN2s3svKz6BbQja7+XYu9ZyGEEEKYJsGyKLULe3ZwZvu/WNrY0Or1Qbj6VCA9KYFln39IZnISwSjA35kk+1zinHKpmO+GhZsjEfUseX5dwc5xw2oP49067xbZx/fHv+e3C78BsDZkLWl5aQypOQSArde3cjj6MJUdK/OCRwfW/zCVuGtXSbLLY2e9eNJt83GxcuH71t/TwKtBqe/vcPRhg+OE7ARcrFyM6vXf2J8abjVoW6Et3QO66x8SbOjVkI8afMS8s/OwUFpQzr4cp+JOcT7xPBbKkqegAPjY+fD21rc5EnPE6Nx3x77D2szaKFB2tnRm6QtLqehQsVR9CSGEEMKYBMuiVK6fOcWm2f+nP467Hsag6T9zYc9OMpMLllJToqBmiAPtB7+LbS8fvro0lfOJ++G2DejmnJ5D+0rtCXQONNnPzhs7DY8jdjKk5hBWXV3F2ANj9eUHT82n8s2C2V2XdAuan3Vlc5NYknKSGLVzFDt778RCZTpA1Wg1RttZAyZnfv++/LdRWXx2PDsjdrIzYiehqaGMbjAaKNhh8HzieVJyUwpeo+xbqSd52jyTYzHFw9oDH3sffrv4W5F1bs/lBqjlVosZ7WbgZu1W4n6EEEIIUTTJWRYlpsnPZ/uCuQZlGYkJpMXHkZORri/LM9MQ65hD2JkTjF3/MecTjVMIAE4e2Io6N8fkOS9bL8Njm4Ljf8P/1Zc5ZJhRLs7SoJ5t9q3Pf2l5afqA9XaxmbG8tv416v5Wlx5rexCZHmkwO1uYH327uwW5S84v4Y9Lf5CvzWfL9S1Gucf3Ik+bR2pOaonrmynNGFlvpATKQgghRBmSmWVRIjqdjl2/bSQlznDWVWVugb2LK1eP3NrBzyJfhU2eltCjh0lqmGKyPcd0c8L+3cDCDUcZ+P0cLKwNc3/HNxvPiB0jCEsNo7prdcY0GgOAq7UrAEoNPH/EE8t8w5nhSI9b2ziXty9vMnCcemSqfpOOK8lX6L+xP8m5yViprJjQfALmKvMSviq3aNEy+fBkjsYcpbFX4yLrKVGi/W/zFjOFGX6OflxJMb12ckpuChvCNhTbb2PvxvQJ6kNURhSNvBpRzbVaqcf+qB2LOcZfl//CQmXBO7XeoYJDhbtfVIw8TR57o/aiQEFLn5b39PMUQgghCsk6y6JEtsw7x9VjBekE6qydaHJP6s+5VqhIYsQNg/o6dChQcKV8Ogdq3drpzkpjRlCILdWv22OpLgh0Ww0eyk0/HXnaPJ6v9DyOlo76+mqN2iDYSchO4N1t7xIVcY0euw3XbI52zWFLw1h0t31f0iuwF+ZKc3zsfOhbrS9mSjNeXf8qFxIvmLxPM4UZLcq3YFfErlK9Prf756V/GLh5oH53PX8nf75s/CUzTszgVPwpAOzM7RjfbDyLzi0y2F3vThZKC4NZ7QaeDfiw/oecjj+NjbkNXf26PtHB4NXkq/RZ30d/j542nqzuttpgd0G1Rk1CdgJu1m7F3us/V/9h6/WtXEy8SGJOIlDweg2uOZjzCecJcgnCz9GPn8/8TE5+Dn2q9qGhV8MHe4NCPGXk/Vs8i2RmWdzV+b1R+kAZwNymLaBDk3sKgMSIGygUSnS3pTIULhkXGGmPZZ6Kc/6pxDvnkaPKBwX6QDndWs3Y+B+JjI4BYOG5hfzx4h/6gPnO4MjN2o3lXZfzx5llhB5YipX61szypYrpBoEywPIry/V/3xO5By1aUnOLTm3I1+WjvI/sJHOlOa7WrjhaOOqDZZ1OR742Xx8oA2SoM5h/dj4Xky4W2VaAUwD25vacjL/1waSBVwNqutekpnvNex7j4+RozFGDDwOxWbFcS7lGHY86AISmhPL2treJyYzBw9qDOR3mEOQSZNTO6murGXdgnFH5sdhjHIs9pj+2M7cjQ50BwK6IXQyqMYjw1HB2ROxArVXjbOnMsheXUd6+fNneqBBCiCeW5CyLuzqwKuSudXR3rMhwO+cMc5Icbq07nORQEBxFuGexqnU0kfkx+nMR6RHsjNhp1MadovNi2dYwjgSHXNKt1ZwITOG6d1ax1xyOOczRmKNEZURhobSgfcX2+lzo2+2J3FOqgNlSVZA3baY0Y2zTsZyIPUFERoT+fGhqqMmguLhAGSAsJYx36rxD6/Kt8XXw5bWqrzG01tASj+tJcGdQaq40N8hXn3Z0GjGZBb8fcdlxjNw5ErXGeA3rWSdnlai/wkAZCnLCfzrzE5uvbyZPm4cOHUm5SXRf3R2NVnMvtyOEEOIpJMGyuCt1nmHgoNUkoskzDvSsHZ1MXp9uk49GdSvbp2WjLjTo8grnG2txTjMnINIWx/RbM8j/d+z/GLh5IDfSClI7ErITOBB1gIj0ggD0QuIFVl5dSYJTHutbxLCy7U3OBJT8QTgoCJR6Bvbk1aBXUWGY95yvy0eLFi8bLxwtHIto4ZYRdUewrvs6dvTaQfeA7libWRvVCXYNNthBr6pLVaM6d45Dg4bojGhmtZ/FupfX8XnjzzFXPrkpF6a0Kt+Kd2q/g42ZDS5WLkxuMdkgWL7zAc2bGTcNVkMBSM1NJTYrtszGlKvNJSE74e4VhRBCPBMkDUMUKfpaCpt+OYcu3zCt3cHVgmpd+3Fs3Uqy024Fqdn/bXN9p8wAOyAOBQpalW/FmNZfolQoWfztcqofs0WBAo1Sx/b6cdx0zyE5N5njsccZuWMkk1tOZsiWIaTnpWOmNGNay2n8dOYnfYrDvbJQWhCdEc2MkzOKrBObFUuzcs0IcgkiNrMgGHOycsJCacHi84vRoqV5ueb0rdrXIF2kWblmdPbtzKbwghUxXvJ/iUbejajvWZ/9N/ej1qhp7tOcL/Z9wZbrW/TXNS/fnH2R+/QPACpQUMW5yn3d55NgeJ3hDK8z3OS5l/xfMsov335ju8GxjZkNViorcjSmV1ZxtHAkNS8VW3NbMtWZdx2PAsVdN80RQgjx7JAH/ESRFn+2n4zkXP2xk5cN1Zp6UbtDRVQqJX9P+IyIC2dNXnsyIAVzjYIYl1wiPbN5r857DK01VL9xB8AP77yKNvlW8JLqpWRVvTCDdmq61uRs4q0+fOx8SMtNI12dzr1SoKCjb0cORx8mOTf5rvVb+rRkToc5BmWpuansjtjNwvMLydfm82aNN3mlyiusDVnLyssrMVeZ06dqH/wc/fBzMt5qOiQlhJ5re5KvM72bn5XKii+afEH3gO73dI9Pk3e2vsP+m/v1x74OvvzT7R9iMmNwtXLFxtyGrde38vnez8nR5BDkEoRWqyVHk0OAUwB25nZUcqzEa0GvMWbvGPZF7Su2v2mtpvFC5Rce9G0J8USS92/xLJKZZWGSTqsjM9VwbWH3CvbU6+irP27aqy8xUycYrZWsQ0eoTyZWeUp9rvK1lGsGgTJAliYbq9uOrS0M1ze2UFoYBMoAWflZBnmnxZnWchqVHSsz/cR0Dty8tbSdg4UDm8M3G9U3V5ijQWO0I97l5MtGdbPzs5l4aCK5moIPE+MPjCc9L53vjn2nr3M09ih/dzXezARgX9S+IgNlgBxNDl38uhR/g8+Iaa2mMXLHSE7EncDTxpNPGn1Cz7U9CU0Nxc7cjv9r8388V+k5Wvq0JEOdgauVKwqFgqlHprLs4jJ9O2fjz5Kvzaepd1MUKLiefp18bT6pualodVr6Vuur31hGCCGEKCQ5y8IkhVJB5VqGaxT71XE3OK5QvSYD/28uL48ZR/NX+6NQqThfOY3ddRKoEmlL50NevHDAE5UGzsWdZeaJmfrd8XI1uRwIiEGjLPhiI89MyxH/OPpX609t99oEOAWY3AjEzcoNHcZfhii0YJGnwCqn4Fe6mks1OlXuRDXXanxRaQTNzWrjY+5JuwrtSM0znd+s1qmxUdnwkt9LBuV1Peoa1b2edl0fKEPBB4SDNw8a1NHqtEw/Ph1TX9542HiYHEMhpUJZopSBZ4GjpSOLOy/m2OvH2NZrG9uubyM0NRQoeGBv/IHxAFiZWeFm7ab/ULbt+jaDdnZH7uZQ9CEORh/kZPxJojKiiM2KJV+bz4KOCyRQFkIIYZLMLIsiPTe4Oie33CA9MQffmm741XU3quPg5o6Dmzt+9RpysFwkRy8vAiAcyLHQkmOhRaOCyKwofj37Kzp0jKo3CkuVJfn+zqxyuIlDphnJ9mqyrTRk3NjKxlc28suZX7iWcs2oP08bT66mXNUfW6os0WWr6XTYE5d0C3ToyGlVgfdenYpSoeT62VP8M2UcVTQaArAkoLMvOxRGzepl5GeQp81jYPBATsSdoIpTFT5q8JFRPX8nf+zN7fXpIGYKM+p51DNIF4CCpc/qL62PlcqKz5t8rp8t7uTbiSMxR1h5ZSVKhRI/Rz+D+yrcMrtZuWZFD/YppNPpWH1tNRHpETQt19RgHeTCVUfuXPrP1C6NAJ62nkU++Hf7NuH5uny+P/49izotQqmQ+QMhhBCGJFgWRTIzV9Hwxcolrn8o4YjBcaR7tsEqGFCwW9vNjJvYW9gzs91M+m7oy02bW2kcMZkxrL26lk6+nfjlzC9GKRG13GuRlZ/FibgTWJtZM7XlVC6v/5es9IIttRUosNl3E5vBBYHVuZ1bSbXIYUf9eJLt1bilLgOn4u8jJCWEb1t/W2wdN2s3fnruJ348+SNqrZrXq71ulNqhQMHNzJsAqLVqvtj3BRHpEfQK7IWbtRvjmo5jWJ1hjNo+yijdRIECTxvP4gf6FPnx5I8sv7ycXE0uWfkFSwDOOzuPD+p/wJs13jSo+5L/S+y4sUP/DUObCm1Mtjmu6Th6rO1Rov5Pxp3kj0t/0K9av3u/CSGEEE8lCZZFmfGx8zFYucAu2wydAjKtby09F5EeQceVHVEpVHTz72Yy1eJ/h/7HZ40/MwqUndLM+fXsr2zpWbCChL2FPZYqS8wcr3OU8/p6Oq0WdV4us87NZa3DatKbp5NnURBYJTjl4mrlqt/hTalQ4mjpSHLOrQf9SrJldEpOCu7W7vzU4SdUShWLzy/m3/B/9ectlBb0DurN0otL9WVanZY5p+bwz9V/+PPFP3G1dmXphaVGgbK50pzRDUbj7+R/13E8Db45+g2/XfjNqFyHjv87/n9cSrrElJZTmHZkGpvDN+Nm7caXTb7ktwu/EZ4WzsawjVxLvsbyrstRKm/NDAc6B9KjSg9WXl2pL1MpVGh0ptdQvpR0qexvTgghxBNPgmVRZj5r9BmxmbGcSziLR449nrlWnHePN6hTGKRqdBr+ufaPyXY0aEjMTjQqb3jJmRiXHBKzEw12cQtu04Ez2zaTm1WQ41u9ZVtWR21g4fmFoAAsDNvxsvWiT9U+xGfF075Se/wc/fhg5weEpIZQ16MuHzf42Kjv0/GnycjLoK5HXVZcWcF3x77Tz2zWdq+tnw0tlKfNo1X5Vvx56U+jB/liMmPYGbGTnoE9ic8yfH0A1nZbS3mHZ2cHueWXlxd7fmPYRg5HH9b/7iTlJDHj+AzS1LeWD7yScoWJhyYyvtl4oCDwTchO4P3671PXoy4n406yIXRDkcvLgem1r4UQQggJlkWZcbdxZ9mLy4hMi+TNf9/kpFWMwXkFCqOH88wUZiZXhWhdsTUKpYI5J+eAAqqF2+OTYI291hpfR1+Duq4+FXh96gxCTxzFxtGRoCYtGHdwfJHjbF2hNe/Ufkd/fCX5Ci7WLlibW9MzsKfRGru3r6pQ0b4iN9JvGJw/HX/aqI/abrWZd3ZekSte5Gvz+fbot2y7sc3o3Cd7P+H3F38vcvxPk+iMaMyUZnCXDfMKA+VCtwfKhQp3RPx0z6dsCNsAgLetN0s6L2H1tdXFBsoAjb0al2LkQgghnhUSLIsylZ2fTb9N/UjKSTI6p18VovABOx0mV7bo6teVYNdggl2DsVsbSsSlc1jmF+xuF1yprv5Br9s5eXpRr3NX/XFt99qsurZKf2xlZkXzcs1p6NWQvlX76svT89J5a8tb+vEeizlG/+r9+bD+hygUCuKy4gyWH7szUDalk28n3qr5Fj3Wmc6XbeLdhJ9P/0xCjuld4s4lnEOr0z71D5vdubQbFKSgfNTgI5ZdXFai1/p2dT3q8tPpn/SBMkB0ZjTjD4w32tjkTvYW9njaPjs54kIIIUpOgmVRpsJSw0wGygCWuQpyrW4LjhUFKRcOFg5kq7NRa9VUTfNggMWtDSG6DHmfVdMmkBx9E7cKleg0ZESJxtEjsAfnE8+z/ErBV/w5+TlEZ0bzWtXXDNZ7vp523WC8OnQsubCEVddWkZGXgbetd2luH4B367yLq5WrUX7s0FpD6ejbkXPx5xgXPa7I6+3M7R5ooJypzmTe2XnEZ8XzvO/ztCrf6oH1VZQz8WeMAuURdUfQK7AXzlbOdAvoxo4bO5h2ZFqRS/3dzt/RnxOxJ7icZLwm9p0rlNzJ09qTaa2nYW9hX7qbEEII8UyQYFmUKQ8bD8yV5qi1asMTOgwD5f/KUEBaXhrVwu1pdMEbBQrWHJxKWA834izSaVOhDe/98DP5eblkJCWy9/fF5OflUqdjFyrVrFPsWO4Mfi4kXiAuKw4vWy99WTm7ctiY2RjlHKfnFSwJdzOzYOWOwuM73Zla8kb1N/Bz9CMjLwMXKxfiswtykt2s3Xi71ttYqCz438H/FTvudHU6YalhVHYs+UokJaHWqrmafJWvD33N2YSChwrXhqxlToc5tPBpoa+39MJSdkbsxMvWiw/rf4irtWuZjgMgI894Y5mw1DBG7hiJu407nzT8hJpuNY1/j4oQnRFNlibLqNxU6s/tOlbqyHdtvivyvBBCCCHBsihTbtZuTG4xmQkHJ5ClzsLfyZ/47HjjtXC1oNSBtiC7Aq9EKxT/5WeotGC29zpX6iVwJfkKVior3gjoy98TPiMjuWAW+Nqpo7w68RvK+wVRlDtnhW3MbHC0dNQfp+amMnDTQKNA+U5arZY57eeQmJ3InNNziM6MBgrW/R3fdDwrr64kV5PLG9XfoFPlTkDBQ2mFgTJAQnYC4WnhBDoHEpURVWx/gH7zlrKSnZ/N0C1DORV/yqBch44dN3bgZOmEjZkNp+NPM+3oNP358LRwlr2wjLJWx6MOAU4B+rW0nSycWB+6Xn8+JKXgYcu7/WwKmQqUHSwcsDW31f+8bvdKwCu84PcCjbwa3eMdCCGEeFZIsCzKXKfKnehUuZM+R7n2ktoG5xW6gh33tLf99jlkGv4qOmSaF/xFB6s3zkOXd1YfKJ/xS+VkYAqL9/ZiSMoQuvh1YW3IWqzNrOlbra9+RrlXYC/OxJ9hY9hG7CzsmNxiMtZm1kBBoNxnfR8iMyLvej+tK7SmZfmWADQp14QfT/5Iam4qb1R/g0bejejiX7JtqeOy4gh0DsTP0c8gkL6TjZkNAU4BJWqzpFZdXWUUKBfaH7Vfn65yZ79n4s+g1qgxV5mXqr9t17ex9OJSrMysGFV3lNFyfDbmNkxoNoEdN3bgYOnAteRrrAtdpz8fmhqKlcrqzmZN8rHzQafT6de0Bvi88edUsK/Au9veNXnNxaSLTGg+oVT3JIQQ4tkkwbJ4YApzgyvYVzB4WKuqazX9ygWFktx1ON/2zfxNt/92WFPADe8s9l4+QS0cSXbI40TVlP9q6fj17K8sOr9I/3X931f+ZkP3DViZW6FSqpjccjITm08sWHHhP5nqTPpt7HfXQNnLxouXq7zMkJpD9GWHow+zMXQj+bp8ItMjWdBpAS5WLkbXvlD5Bf649IfBLoTv73yfDhU7oNPpUKJEi9boOiiYBb6cdJmqrmW3lFlxK0HcHmTeuWtiRfuKpQ6Uz8af5aPdH+nztc8nnGf9y+v1s/o6nY5P9nyi38SlZ2BParrXNAiWAS4kXcDO3I4MdcEvRkffjvSq0otfzvzCkdhbG+BEZUQxu91sVl5dSUpuCl39u9IzsCdbwrcUOcY8jfH63kIIIYQpT83j9pvDNtP6r9Y0XtaYWSdnPerhiNvMaDuDKk5VsDazpk35NkxvO90gwFQpVOwLiuFUQAoR7lmcq5rJ8aAUgzZOBaWyo348eY7Gn+9uz2uNy4qj4e8N6bC8A6fiTpGlzuLrQ1/zytpX+GLfF8RmxtJvQz+up103akf53z8HS5UljhaOZKgzSM5J1gfaGq2G/x36n345uJDUEBaeW2jynu0s7FjSaQkqhUpflqvJZUPYBo7EHikyUIaC1Ihe63sx+N/BRKbffea7JF6o/ILJoN6UjpU64m7tTk23msxsN7PYuml5abyz9R3q/1afXut6cT3tOmcSzhg82JiSm0J4Wrj+eG/UXoPdDldcWYESJXU96hq1/33r7/mm1Tf81vk3vmv9HY3LNaaTXyejeuUdyjOj3QwWd15Mz8CeADTyamSQn15IgYIBwQPu+joIIYQQAAqdfj2vhyctLQ1HR0dSU1NxcHC47/ZiMmPo/E9ngzxPRwtH/u7yN+Xsy913+6LsRaRH8MelP1DoFPx28TeDh7AslZbkanNNXjcl4HN+iJpHXHYcUPyObB7WHrSq0IoVV1boy6o4VeFqylWjup42nsxuPxtvO286r+xMWt6tdXxH1BmBo6UjLtYujN412mCsvQN781XTr0z2r9VpabSsEbka0/dSEoHOgax8aeXdK5ZATGYMW8O38sOJH4p8cK6aSzW+bPIltdxr8cPxH1h5dSV25naMazqOpuWaGtWfeHCiPoUDCrYj7xPUh8/3fa4vszazZuMrG3GzdiM7P5ulF5Yy86RxEG6mMEOr0+o/SNRwrcFPz/3ExtCNLLu4jAx1Bh0qdeD9eu8zdOtQ/UOKrwa9ypdNvjR5P3FZcSy/shwFCmq71yYqI4pA50DqeNQp8esmhLilrN+/hXgSPBXB8qm4U/Tf1N+o3ExhxpLOS6jpXvO++xAPRpY6i+Z/NC9y8447rem2BkszS5ZeWMqZhDOciT9TZF0FCoKcg7iUfGsbY3tze9LVhitbvFj5Raa0nIJCoSAmM4bnVjxn1E5hgOxp40lsVixQMAP983M/U9+zvsn+LyReYMaJGRy4eaBE91bUPZzsfxKVUnX3yiU06dAk/rz8p/7YztyOQTUGseTCEv2DmNVdqxusTWymNKNN+Tb0CupFs3LNWBuyll/P/EpkRqTBh9TbP+hYqazwsfOhR2APGnk1Yk3IGpPbWpviZePFqHqjGHtgrFFg/3GDj+lTtQ+n409jY2ZDsFvwvb4UQohSkmBZPIueimA5Iy+D7mu664OYO3Xz78bXLb6+735E2Svqg44pvQJ7MbbpWKAg7/WFf14oNu+4ebnmeNl6sfLqrZnZJt5NOBZ7TB/gtfRpyfhm45lzag6Xki5hb27PmYQzxa7C0KJcCyIzIglPC8dCacH4ZuPp6t+VK8lX0Gg1BLkEcTHpIm9sfIM8bUFurMnl9O5gKo+5plvN+9rN73radc7En8HP0U8fVB6JPsI7297Rj8fazJp8bX6JlmkzU5gxodkEvjrwFVpd0akkhXzsfEq0+sedCldGMbXsW48qPfTbWgshHi4JlsWz6Kl4wM/Owo6FnRbSa20vMvMzjc6vCVmDhdKCsc3GPoLRieIUtX7xnb5r9R0dK3fUH6+8utIoUK7jXofnfZ/nQNQBqjhX0W9prdFpOBt/lmqu1fi88eeEpYaxM2In7tbudK/SnT7r+xCWGlbiMe+7uU//9zxtHuMOjOPAzQP6pc/K2ZajtnttfaAMBXnVlR0qE5ZWdD93BsoKFLxd6+0Sj+tOR2OOMmzbMHI0OShQ8FXjLzFXmjH24HiDIDQ7P7vEbebr8tkVuatEgTJwT4EymA6SCxU1ky+EEEI8CE/FzHKhpOwkuq7qSpo6zeT5+c/Pp5G3rKv6OLmSfIUea01vC3277b22czj6MKfjTxPoHMj1tOssubDEoE6vKr1YfrUgf7a6a3UWdFyArbltse3eSLvBi6tevPcbKMKdm2GYKcyKTDVxtHAscpc6BwsHprScck+77A3fPpw9kXv0x65pkK/UkWqnKOaquxtdfzQzTs4o87Wg78bRwpH36r5Hn6p9Hmq/QohbZGZZPIuemtUwAFysXdjTZw8WSguT51ddW/WQRyTupopTFTr63poxLmqb53ln5vH5vs/56/Jf/O/Q/4jJjDE4X8G+gj5QhoJ84dsf7CuKlcoKM8X9fcFiqbI0KtOhw83aDShIwajhVqPI64vbzjktL43Ru0YTn1X0usxFufO1VGp1aO/xX7yl0hIzhRlNvZtyOObwfQXK9dzrYa4s3XJ0z1d6nr199kqgLIQQ4qF7qoJlAJVSxa5Xd+Fo4Wh0zt3a/RGMSBRHoVDwbatv+anDT/zQ5gd29t5pcomzPy7/YXB8MekiU1pOIcg5CKVCSUR6hNE12fnZ/HXpL2acmMGpuFMAJGYn8tnezxiwaQALzi3gi/1flPjhwqIUtdpFQnYCUPAA3d02GSluWbccTc49pTO8U+sd7M0LNmhRaXT03aWlx/6i0yda+7TWL59nRFGQgnEw+iD7ovaZrlMC9ub2zGw/k+9af6ffIKaxd2M+bfipyQ8d9ub2vFfnPb5v871+3W4hhHgaDBw4kO7du+uP27Rpw/vvv//IxiOK9lTkLN/J3sKefa/tY9qRaSy9uBQo2JnMx86H/x38H0EuQfQK7CVvvo8JhUJBc5/m+uO/u/xNv439iM+KR6FQmFwazt3andblWzNu/ziT+bMqhYqjMUc5ElOwecWic4v46bmfmH1qNifjTgJwIu7EPY23qOXqvG29SchOQK1VG6RhJOcm33X5uE8afIKPvQ/Dtg8zyuN2sXLBz8mv1OMMdgtmdffVnL9xDOXoSXiEFOyA6JGczze9VHDH7//eqL3YmNvoNwG53b0sf2elsqJ7QHc8bDxYE7IGGzMbxjQag6OlI+0qtmN/n/1kqjNxsnICoF/1fiRmJ/LtsW+JTI+khU8L3q71tvw7FUI8UAMHDmTx4sX6YxcXFxo2bMg333xDrVq1HuHIxOPiqcpZNiU5J5nk3GR239jN/534P335oBqD+KD+Bw+0b3H/uq3uRmhqqFH5cxWf42bmTc4nni9xW90DurPm2hqDXOLi1mkurbdqvsXzvs/z16W/WHl1pUE/zcs1Z//N/UVea2dux+LOi1EpVPx56U9iMmNIV6fjYOHAe3XfI9A58L7GlhcRQdLCRYQmX2NcwBli7B58vnGgUyAru5XNGtFCiMfDw3j/1mh1HAlLIi49Bw97KxpVdkGlfHAfmgcOHEhsbCwLFxZsMhUTE8OXX37JmTNnuHHjxl2uvr9+U1JSWL16NVAws1ynTh2mT5/+wPoU9+apS8O4k7OVM36OfmyP2G5QXtxWuOLx0dW/q8nyrTe2lipQhoIHxPwcDWdog5yDStWGk6WTyXKVQkVj78a8uflNVlxdYRAoO1s607p862LbzVBn0GNtD6Yfn84XTb7gx/Y/sqjTIma2m3nfgTKARYUKeI39imY/LKZpHdOvaXHK25UHCh5c7BXYi3YV2tHEuwnjm43H18HXqL5SoZTVZ4QQpbb5XDQtpu3gtV8PMerPU7z26yFaTNvB5nPRD7RfS0tLvLy88PLyok6dOnz66adEREQQH1/08yJarZZvvvmGgIAALC0tqVixIpMmTdKfj4iIoHfv3jg5OeHi4kK3bt0IDw9/oPchHoynMg3DlDvzld2s3VBr1Px46kfOxJ+hmks1RtUbhZWZ1SMaoTBlSM0hnIw9yZ6oPXevfBdvVH+DXkG9GLt/LDczb1LPvR67IneV+Po57efw9cGvSSHF6JxGp2Hb9W1GKQxDaw7levp1/r7yN65WriTmJBbbx67IXcw+OZvhdYeXeFyl5W3nXeK6KoWK4XWGMyB4AFeTr+Jo6Uh5+/IGdV6o/AKXky5ja27LteRrpKvTaVuhLe428oyAEKLkNp+L5t2lJ4wWjoxJzeHdpSeY+3o9OtUo+X+/7lVGRgZLly4lICAAV1fXIut99tln/Prrr/zwww+0aNGC6OhoLl0q2ARLrVbTsWNHmjZtyt69ezEzM+Prr7+mU6dOnDlzBgsL0wsRiMfTMxMsf9LwE8JSwwhJDcHGzIbozGia/N5Evxbu8djjZOVnMaHZhEc8UnGn+l717ylYvj1vuLVPazxsPQBY3LkgN23iwYnFbj5yp0/2fEK22vSaxEqFkky18Rrfyy4uM1j721plTbam+HWN993c90CD5UE1BnEp8RK7InfhYuWCvbm9yfWfVQoVf3f9Wz+zXdROedZm1vrto6s4V3lg4xZCPL00Wh0T1l0wucK6DlAAE9Zd4LnqXg8kJWP9+vXY2dkBkJmZibe3N+vXr0epNP0FfHp6OjNmzGDWrFkMGDAAAH9/f1q0aAHAX3/9hVarZd68efrnLhYuXIiTkxO7du3i+eefL/N7EA/OMxMse9t5s/yl5fRY04OwtDCTQdKxmGOPYGTibnoF9mJD6AauJF8BCtYeTssrWEvb1PrFTbya0CuoF/YW9uyM2ImHjQf9qxvuEhidEc2qq6VbStDUg2+FtDot60LXGZXfuUnO3QJlgMoOlUs1rtKyVFkyo90MNFoNKqUKrU7LtZRrmCvN0Wg1LLu4DLVWzaAag+7pwUIhhCitI2FJRKfmFHleB0Sn5nAkLImm/kXP9t6rtm3bMnfuXACSk5OZM2cOnTt35siRI1SqVMmo/sWLF8nNzaV9+/Ym2zt9+jTXrl3D3t7eoDwnJ4eQkJAyH794sJ6ZYBngZsbNYndQu9vyXuLRsLewZ9kLy7iYdBF7c3vK2ZXjUtIl3KzdMFea03NdT33wXNG+IjPazcDG3AaApuWammzzRvqNe14yztXKlTxtXol3HyyN6i7VGd1gdJm3a4pKqQIKZsVvz4se12zcQ+lfCCEKxaUXHSjfS73SsrW1JSDgVgwwb948HB0d+fXXX/n666+N6ltbWxfbXkZGBvXr12fZsmVG59zdJUXtSfPUP+B3OxcrF/3arqYU9TCZePSszKyo61GXAOcAbMxtqOdZj4oOFfG28+a3F36jf/X+DK4xmMWdF+sD5eIEOAXgYHHrSW4lSt6o/gbVXaob1HO2dDa61sfOh92v7qaqS9X7v7HbdA/ozl9d/8LVuuxnTYQQ4nHmYV+y54VKWu9+KRQKlEol2dmmvw2sUqUK1tbWbN++3eT5evXqcfXqVTw8PAgICDD44+hovA+EeLw9U8GyvYU937T6psiNF3ZF7Lqn9WTFo+Xn6McnDT/h/frv63fNuxtXa1d+ef4XWvq0pIl3E2a1n8XHDT9mfsf5tC7fGkuVJYHOgSzqvIgxDcfoN8ywMbPh/frvY640p4l3k7v2Y29uT3WX6qhQ3bWul61XicYuhBBPm0aVXfB2tKKobGQF4O1YsIzcg5Cbm0tMTAwxMTFcvHiRESNGkJGRQdeupifRrKysGDNmDJ988glLliwhJCSEQ4cOMX/+fAD69euHm5sb3bp1Y+/evYSFhbFr1y5GjhxJZGTkA7kH8eA8U2kYAG0qtKG+V32Oxhw1OrcmZA1hqWEs7LQQC5U8qfq0C3YNZk6HOQZldhZ2zGo/y6DMz9GPTpU7EZYahq+Dr36Vh+F1hpOQncDh6MN42HgwIHgAHjYeZOZlkpCdgI25De0rtsdcZc6Uw1P4/dLvRY6loVdD3gx+s+xvUgghngAqpYJxXavz7tITKMDgQb/CAHpc1+oPbL3lzZs34+1dsNKGvb09VatWZfny5bRp06bIa7766ivMzMwYO3YsN2/exNvbm3feeQcAGxsb9uzZw5gxY3jllVdIT0/Hx8eH9u3bP/D9JUTZe+o3JTHlTPwZ3t76dpEPbM1uP5tW5Vs95FGJp9mKKyuYcNB4pZUufl34tNGnOFrK13JCiMffg37/3nwumgnrLhg87OftaMW4rtUfyrJxQpjyzM0sA9Ryr8XGVzYSnhbOzfSbfLrvU4PzKsXdvzIXojS6BXRjT+QedkbsRKVQ0SeoD50qd9IvuSaEEAI61fDmuepeD3UHPyHu5pkMlqFgZz9nK2dqudViQ9gG9kbtBaB1+dYlykUVojTMlebMbDeThOwErFRW2FnYPeohCSHEY0mlVDyQ5eGEuFfPbLBcSKVUMav9LE7GnUSBgjoedVAqnqnnHsVDVNIHEIUQQgjxeHjmg2UoWGe2vmf9Rz0MIYQQQgjxmJEp1GJEZ0RzJv4MWeqSb4kshBBCCCGeHjKzXIRVV1cx4eAENDoNFewrsKjTIjxsPB71sIQQQgghxEMkM8smaHVaJh+ejEanASAiPYKuq7ryf8f+j6iMqEc8OiGEEEII8bBIsGyCRqchT5tnUJaVn8XC8wvpvLIzv53/7RGNTAghhBBCPEwSLJtgrjTnlYBXTJ7ToeObY99wOenyQx6VEEIIIYR42CRYLsLYpmOL3Zxk2pFpD3E0QgghhBCPzvjx46lTp47+eODAgXTv3v2RjedhkmC5CAqFgh/a/lDk+aOxR/nmyDcPcURCCCGEeBBiYmIYMWIEfn5+WFpaUqFCBbp27cr27dv1dXx9fVEoFCgUCqytrfH19aV3797s2LGjyHYTExMpX748CoWClJSUMhlrmzZt9OMw9adNmzZl0o+4RYLlYrSt0JblXZcXeX7pxaWk5qY+xBEJIYQQTzmtBsL2wtkVBf+v1TzQ7sLDw6lfvz47duzg22+/5ezZs2zevJm2bdsyfPhwg7oTJ04kOjqay5cvs2TJEpycnOjQoQOTJk0y2fbgwYOpVavWXccwfvx4Bg4cWKLx/vPPP0RHRxMdHc2RI0cA2LZtm77sn3/+KVE7ouRk6bi7qOpSlW09t9FjbQ9S8wwDYx06svOzcbR0fESjE0IIIZ4iF9bC5jGQdvNWmUM56DQNqr/0QLocNmwYCoWCI0eOYGtrqy8PDg5m0KBBBnXt7e3x8vICoGLFirRq1Qpvb2/Gjh1Lz549CQoK0tedO3cuKSkpjB07lk2bNpXZeF1cXPR/z8nJAcDV1VU/ruIsWLCA77//nmvXruHi4kKPHj2YNWsWACkpKXz00UesWbOG3NxcGjRowA8//EDt2rXLbOxPKplZLgFPW0/2vbaPr5t9jfK2l6x5ueZ42ng+wpEJIYQQT4kLa+HvNwwDZYC06ILyC2vLvMukpCQ2b97M8OHDDQLlQk5OTndtY9SoUeh0OtasWaMvu3DhAhMnTmTJkiUolY9HqDV37lyGDx/O0KFDOXv2LGvXriUgIEB/vlevXsTFxbFp0yaOHz9OvXr1aN++PUlJSY9w1I8HmVkuhW5VulHDvQZbrm/BydKJHlV6oFAoHvWwhBBCiCebVlMwo4zOxEkdoIDNn0LVF0FZ9MP3pXXt2jV0Oh1Vq1a95zZcXFzw8PAgPDwcgNzcXF577TW+/fZbKlasSGhoaBmN9v58/fXXjB49mlGjRunLGjZsCMC+ffs4cuQIcXFxWFpaAvDdd9+xevVqVqxYwdChQx/JmB8XEiyXkr+TP+86vfuohyGEEEI8Pa4fMJ5RNqCDtKiCepVbllm3Op2p4Pze2imcPPvss8+oVq0ar7/+epH19+7dS+fOnfXHeXl56HQ6VqxYoS/7+eef6devX5mMLy4ujps3b9K+fXuT50+fPk1GRgaurq4G5dnZ2YSEhJTJGJ5kEiwLIYQQ4tHKiC3beiVUpUoVFAoFly5duuc2EhMTiY+Pp3LlygDs2LGDs2fP6gPfwoDczc2NL774ggkTJtCgQQNOnTqlb2PmzJlERUUxbdqtZWk9PcsuzdPa2rrY8xkZGXh7e7Nr1y6jcyVJRXnaSbAshBBCiEfLroSBYUnrlZCLiwsdO3Zk9uzZjBw50ihvOSUl5a7B4owZM1Aqlfo1h1euXEl2drb+/NGjRxk0aBB79+7F398fKAheb88XdnFxIS0tzaCsLNnb2+Pr68v27dtp27at0fl69eoRExODmZkZvr6+D2QMTzIJloUQQgjxaFVqVrDqRVo0pvOWFQXnKzUr865nz55N8+bNadSoERMnTqRWrVrk5+ezdetW5s6dy8WLF/V109PTiYmJQa1WExYWxtKlS5k3bx5TpkzRB7qFAXGhhIQEAKpVq/ZIZ2nHjx/PO++8g4eHB507dyY9PZ39+/czYsQIOnToQNOmTenevTvffPMNgYGB3Lx5kw0bNvDyyy/ToEGDRzbux8Hj8YimEEIIIZ5dSlXB8nAA3Png/H/HnaaW6cN9hfz8/Dhx4gRt27Zl9OjR1KhRg+eee47t27czd+5cg7pjx47F29ubgIAA+vfvT2pqKtu3b2fMmDFlPq6yNmDAAKZPn86cOXMIDg6mS5cuXL16FSjYiG3jxo20atWKN998k8DAQPr06cP169fLNB3kSaXQlVV2eymkpaXh6OhIamoqDg4OD7t7IYQQQtyDB/7+bXKdZZ+CQPkBrbMsxN1IGoYQQgghHg/VXypYHu76gYKH+ew8C1IvHsCMshAlJcGyEEIIIR4fSlWZLg8nxP2SnGUhhBBCCCGKIMGyEEIIIYQQRZBgWQghhBBCiCJIsCyEEEIIIUQRJFgWQgghhBCiCBIsCyGEEEIIUQQJloUQQgghhCiCBMtCCCGEEEIUQYJlIYQQQjzTYmJiGDFiBH5+flhaWlKhQgW6du3K9u3b9XV8fX1RKBQoFAqsra3x9fWld+/e7Nixw6i9kSNHUr9+fSwtLalTp06xfV+7dg17e3ucnJzK+K6eXuPHj7/r61qWJFgWQgghxGNDo9VwNOYoG0M3cjTmKBqt5oH2Fx4eTv369dmxYwfffvstZ8+eZfPmzbRt25bhw4cb1J04cSLR0dFcvnyZJUuW4OTkRIcOHZg0aZJRu4MGDeLVV18ttm+1Ws1rr71Gy5Z337Fw4MCBjB8/vlT3JsqGBMtCCCGEeCxsu76Njis7MujfQYzZO4ZB/w6i48qObLu+7YH1OWzYMBQKBUeOHKFHjx4EBgYSHBzMhx9+yKFDhwzq2tvb4+XlRcWKFWnVqhW//PILX331FWPHjuXy5cv6ejNnzmT48OH4+fkV2/eXX35J1apV6d27d5nf18CBA+nevTuTJ0/G09MTJycnJk6cSH5+Ph9//DEuLi6UL1+ehQsXGlx39uxZ2rVrh7W1Na6urgwdOpSMjAyjdr/77ju8vb1xdXVl+PDhqNVqfZ3k5GTeeOMNnJ2dsbGxoXPnzly9etWgn/3799OmTRtsbGxwdnamY8eOJCcns2TJElxdXcnNzTWo3717d/r378+iRYuYMGECp0+f1s/0L1q0CICUlBSGDBmCu7s7Dg4OtGvXjtOnT9/3aynBshBCCCEeuW3Xt/Hhrg+JzYo1KI/LiuPDXR8+kIA5KSmJzZs3M3z4cGxtbY3OlyQ1YtSoUeh0OtasWVOqvnfs2MHy5cuZPXt2qa4rbR83b95kz549/N///R/jxo2jS5cuODs7c/jwYd555x3efvttIiMjAcjMzKRjx444Oztz9OhRli9fzrZt23jvvfcM2t25cychISHs3LmTxYsXs2jRIn3ACgUB9bFjx1i7di0HDx5Ep9Pxwgsv6APqU6dO0b59e6pXr87BgwfZt28fXbt2RaPR0KtXLzQaDWvXrtW3FxcXx4YNG/Sz9aNHjyY4OJjo6Giio6P1M/i9evUiLi6OTZs2cfz4cerVq0f79u1JSkq6r9dRgmUhhBBCPFIarYapR6aiQ2d0rrBs2pFpZZ6Sce3aNXQ6HVWrVr3nNlxcXPDw8CA8PLzE1yQmJjJw4EAWLVqEg4PDPfddkrHNnDmToKAgBg0aRFBQEFlZWXz++edUqVKFzz77DAsLC/bt2wfA77//Tk5ODkuWLKFGjRq0a9eOWbNm8dtvvxEbe+tDjLOzM7NmzaJq1ap06dKFF198UZ/fffXqVdauXcu8efNo2bIltWvXZtmyZURFRbF69WoAvvnmGxo0aMCcOXOoXbs2wcHBvPfee7i5uWFtbU3fvn0NZryXLl1KxYoVadOmDdbW1tjZ2WFmZoaXlxdeXl5YW1uzb98+jhw5wvLly2nQoAFVqlThu+++w8nJiRUrVtzX6yjBshBCCCEeqRNxJ4xmlG+nQ0dMVgwn4k6Uab86nXFwfq/tKBSKEtd/66236Nu3L61atSqyzrJly7Czs9P/WbZsGZMnTzYo27t3b7H9BAcHo1TeCvU8PT2pWbOm/lilUuHq6kpcXBwAFy9epHbt2gaz7M2bN0er1RqkmQQHB6NSqfTH3t7eBm2YmZnRuHFj/XlXV1eCgoK4ePEicGtmubjXZ8uWLURFRQGwaNEiBg4cWOxrfPr0aTIyMnB1dTV4jcLCwggJCSn2dbobs/u6WgghhBDiPsVnxZdpvZKqUqUKCoWCS5cu3XMbiYmJxMfHU7ly5RJfs2PHDtauXct3330HFATbWq0WMzMzfvnlFwYNGsRLL71kEHCOGTMGHx8fRo4cqS/z8fEpth9zc3ODY4VCYbJMq9WWeOxFtVuaNqytrYs9X7duXWrXrs2SJUt4/vnnOX/+PBs2bCj2moyMDLy9vdm1a5fRuftdaaTUwXJ2djbHjx/HxcWF6tWrG5zLycnh77//5o033rivQQkhhBDi2eFu416m9UrKxcWFjh07Mnv2bEaOHGmUt5ySknLXQGvGjBkolUq6d+9e4n4PHjyIRnMrpWTNmjVMmzaNAwcO6ANge3t77O3t9XXs7e1xcXEhICCgxP2UVrVq1Vi0aBGZmZn612L//v0olUqCgoJK3EZ+fj6HDx+mWbNmQMEHisuXL+vjxlq1arF9+3YmTJhQZDtDhgxh+vTpREVF0aFDBypUqKA/Z2FhYfD6AdSrV4+YmBjMzMzw9fUtzW3fVanSMK5cuUK1atVo1aoVNWvWpHXr1kRHR+vPp6am8uabb5bpAIUQQgjxdKvnUQ9PG08UmP6aXYECLxsv6nnUK/O+Z8+ejUajoVGjRqxcuZKrV69y8eJFZs6cSdOmTQ3qpqenExMTQ0REBHv27GHo0KF8/fXXTJo0ySCIvXbtGqdOnSImJobs7GxOnTrFqVOnyMvLAwoCyho1auj/+Pj4oFQqqVGjBs7OzmV+jyXVr18/rKysGDBgAOfOnWPnzp2MGDGC/v374+npWaI2qlSpQrdu3XjrrbfYt28fp0+f5vXXX8fHx4du3boB8Nlnn3H06FGGDRvGmTNnuHTpEnPnziUhIUHfTt++fYmMjOTXX39l0KBBBn34+voSFhbGqVOnSEhIIDc3lw4dOtC0aVO6d+/Oli1bCA8P58CBA3zxxRccO3bsvl6XUgXLY8aMoUaNGsTFxXH58mXs7e1p3rw5N27cuK9BCCGEEOLZpVKq+LTRpwBGAXPh8ZhGY1ApVUbX3i8/Pz9OnDhB27ZtGT16NDVq1OC5555j+/btzJ0716Du2LFj8fb2JiAggP79+5Oamsr27dsZM2aMQb0hQ4ZQt25dfv75Z65cuULdunWpW7cuN2/eLPPxlyUbGxv+/fdfkpKSaNiwIT179qR9+/bMmjWrVO0sXLiQ+vXr06VLF5o2bYpOp2Pjxo369I3AwEC2bNnC6dOnadSoEU2bNmXNmjWYmd1KeHB0dKRHjx7Y2dkZzdr36NGDTp060bZtW9zd3fnjjz9QKBRs3LiRVq1a8eabbxIYGEifPn24fv16iQP9oih0pchu9/T0ZNu2bfrkcJ1Ox7Bhw9i4cSM7d+7E1taWcuXKGU2N3yktLQ1HR0dSU1Mf6FOgQgghhCg7D/r9e9v1bUw9MtXgYT8vGy/GNBpDh0odyrw/8Xhr3749wcHBzJw585GOo1Q5y9nZ2QZRv0KhYO7cubz33nu0bt2a33//vcwHKIQQQohnQ4dKHWhboS0n4k4QnxWPu4079TzqPZAZZfH4Sk5OZteuXezatYs5c+Y86uGULliuWrUqx44do1q1agblhdPzL730UtmNTAghhBDPHJVSRUOvho96GOIRqlu3LsnJyUybNq3EDxY+SKUKll9++WX++OMP+vfvb3Ru1qxZaLVafvrppzIbnBBCCCGEeLaUZoOXh6FUOctlRXKWhRBCiCePvH+LZ1Gp11kODw9n69at5OXl0bp1a2rUqPEgxiWEEEIIIcQjV6pgeefOnXTp0oXs7OyCi83MWLBgAa+//voDGZwQQojHXF4WRJ8CTR6cXQnxF8AtCNp8Bk4V7nq5EEI87kqVhtGiRQvc3NyYO3cuVlZWfPnll6xatarU6wbK1zj3JjVLzfDfT3DsehJBnvbM6luPCi42j3pYQohnVVYSLOwM8UVsFVyxGfRZBjYuD3dc4oGR92/xLCpVsOzk5MSBAwf02xVmZWXh4OBAbGwsrq6uJe5U/rGV3uZzMXz77yVC4jP1ZXUqOLJ6eAv9cb5GS1aehoOhieSoNbSt6oGDlbmp5sRDEJeWg0anw9vR+lEPRYiydWwBnF0O0WchL734uvXfhK7TH8qwxIMn79/iWVSqNIy0tDTc3Nz0xzY2NlhbW5OamlqqYFmUjE6nY9XJKObuCuFqXIbR+XNRaRwISWDL+RhORaRwLiqNfO2tzz5+brasGtYcRxsJmB+2r9dfYN6+MADc7Cxws7OkZ/3yDGnp94hHJsR9OrsC1n9Q8vo3DsD51VC9GyhMb2UshBCPs1I/4Pfvv//i6OioP9ZqtWzfvp1z587py2S95bLx1ZpzLD1U9FbiGq2Ovr8eLvJ8aEIma8/cpH+TSg9ieKIIpyJS9IEyQEJGHgkZeXy94SKh8ZlMfqXmIxydEPfp4rrS1Y+/DMsHgGsAOFWEoBeg0VsPZmxCCPEAKEt7wYABA+jevbv+T3Z2Nm+//bb++OWXX34Q43zmaLU6/joaUWydkuTPaDTashmQKLHUbHWR5/46dgOt9qGv1ihE2QnddW/XJV6DkB2w8SM48VuZDkmI+xUTE8OIESPw8/PD0tKSChUq0LVrV7Zv366v4+vri0KhQKFQYG1tja+vL71792bHjh1G7Y0cOZL69etjaWlJnTp1TPap0+n47rvvCAwMxNLSEh8fHyZNmvSgbvGpsmjRIpycnB5af6WaWdZqJfB6WJRKBbaWZqRkmQ68lAooScz1v/UXsDRXAgrc7SzpUN2zbAcqDKg1WmqXd8Td3pL49Fyj8+ZKBUqlfBUtnmB5mabLXQMKAuKSCN8L9Yw3txICQKfRkHXsOPnx8Zi5u2PToD4K1YPb7jo8PJzmzZvj5OTEt99+S82aNVGr1fz7778MHz6cS5duPcA6ceJE3nrrLfLy8ggPD2fp0qV06NCB//3vf3zxxRcG7Q4aNIjDhw9z5swZk/2OGjWKLVu28N1331GzZk2SkpJISkoqcpzjx48nPDycRYsWlcl9i5Ir9cxycbRaLevXry/LJp9p03rUwkJlOrCq6ePIqw3uviyTRgef/XOOz/45y5Alxxj5x8myHuYzLyolm8OhiUzecIFqX22m/tfbaBlgOoe/TkXnhzw6IcqYlaNxWftxMOI41O5bsjbcqpTtmMRTI23LFq6178CNAQO4+dFH3BgwgGvtO5C2ZcsD63PYsGEoFAqOHDlCjx49CAwMJDg4mA8//JBDhw4Z1LW3t8fLy4uKFSvSqlUrfvnlF7766ivGjh3L5cuX9fVmzpzJ8OHD8fMz/ZzKxYsXmTt3LmvWrOGll16icuXK1K9fn+eee67M7mv8+PHUqVOHBQsWULFiRezs7Bg2bBgajYZvvvkGLy8vPDw8jGazb9y4Qbdu3bCzs8PBwYHevXsTGxtr1O5vv/2Gr68vjo6O9OnTh/T0Ww/75ubmMnLkSDw8PLCysqJFixYcPXrUoJ/z58/TpUsXHBwcsLe3p2XLloSEhLBnzx7Mzc2JiYkxqP/+++/TsmVLdu3axZtvvklqaqp+pn/8+PH6fj/66CN8fHywtbWlcePG7Nq1675fyzIJlq9du8bnn39O+fLlJQ2jDHUM9uLoF8+xbkRzGlRyMjhXq7wT03rWYungxrxSt1yJ21x7+ib/HI9g9ckozkWllvGIny2p2Wq6z95P86k7ePWXQ/yyN4x8rQ6NVsc/J29S3dve5DWShiGeSOociDoOdia+nfJvX/D/3WZD15nQ4gOwKuqDoaLkQbV4pqRt2ULUqPfJvyNIyo+NJWrU+w8kYE5KSmLz5s0MHz4cW1tbo/Ml+ap/1KhR6HQ61qxZU+J+161bh5+fH+vXr6dy5cr4+voyZMiQYmeW70VISAibNm1i8+bN/PHHH8yfP58XX3yRyMhIdu/ezbRp0/jyyy85fLjg+SetVku3bt1ISkpi9+7dbN26ldDQUF599VWjdlevXs369etZv349u3fvZurUqfrzn3zyCStXrmTx4sWcOHGCgIAAOnbsqL+/qKgoWrVqhaWlJTt27OD48eMMGjSI/Px8WrVqhZ+fH7/9ditdS61Ws2zZMgYNGkSzZs2YPn06Dg4OREdHEx0dzUcffQTAe++9x8GDB/nzzz85c+YMvXr1olOnTly9evW+XsdSP+BXKDs7m+XLlzNv3jz2799Py5YtGTt2rATLZeBMZArbL8ay41I8SZl5NKrswvQ+dRm7+hyXYtKo4ePEh89VITYth7FrzxEaX8TXokX4aMUZtLqCVI5vetamZ/3yD+hOng6xaTmEJWRSztGKNadvcjkmnXZVPVh+LJJTESlFXnc9Mcuo7GJ0OjN3XOX9DoEPcMRClLGsJFjUBeLOk6e15kjGm6Rr3KlsdYSq1rvgzN/gXQuUSqg/AC5thH0/FNGYDtJugqPPw7wD8ZjTaTTETp4Cplaz1elAoSB28hTs27cv05SMa9euodPpqFq16j234eLigoeHB+Hh4SW+JjQ0lOvXr7N8+XKWLFmCRqPhgw8+oGfPniZzoO+VVqtlwYIF2NvbU716ddq2bcvly5fZuHEjSqWSoKAgpk2bxs6dO2ncuDHbt2/n7NmzhIWFUaFCwbfXS5YsITg4mKNHj9KwYUN9u4sWLcLevmBSqH///mzfvp1JkyaRmZnJ3LlzWbRoEZ07dwbg119/ZevWrcyfP5+PP/6Y2bNn4+joyJ9//om5ecGKXYGBt94XBw8ezMKFC/n444+Bgg8XOTk59O7dGwsLCxwdHVEoFHh5eemvuXHjBgsXLuTGjRuUK1cwifjRRx+xefNmFi5cyOTJk+/5dSx1sHz06FHmzZvHn3/+ib+/P/369ePAgQPMmTNHv/6yuHc7L8fx1uJjBkvArToZRVhCJueiUsjXws3UWE7cSKFOBcdSB8pwK9dZq4MZ269IsFyMvVfjGbrkONlqDQpuPVS5/kw0d0s9zszTmCzffy1BgmXxZDn8M8SdB2BTyhgi82oDEJrbFCUaAg/NAhffW6tcXP236LZsXMEt4AEPWDxpso4dN5pRNqDTkR8TQ9ax49g2blRm/ZZiq4m7tqMoxdKIWq2W3NxclixZog8S58+fT/369bl8+TJBQUHs3btXH2wC5OXlodPpWLFihb7s559/pl+/fkX24+vrqw9oATw9PVGpVCiVSoOyuLg4oCA9pEKFCvpAGaB69eo4OTlx8eJFfbB8Z7ve3t76NkJCQlCr1TRv3lx/3tzcnEaNGnHx4kUATp06RcuWLfWB8p0GDhzIl19+yaFDh2jSpAmLFi2id+/eJmf/C509exaNRmMQdENBasb9Lm9cqmC5Vq1apKWl0bdvXw4cOEBwcDAAn3766X0NQtyy9OB1g0C50J0zmAkZuey9mlDidpWAFrA0U5Kbf+tBTdVt/7gLZ1ADPOxws7Ms7dCfOnn5Wj78+zTZ6oKg986fyr1mU/i6Fv2PXYjHkrrgWxKNTqUPlAvdyK1LoPVe2PIluAWCX+uCJeJuvxwbkhUB2Hm4YPPy12AtufvCUH58fJnWK6kqVaqgUCgMHuIrrcTEROLj46lcuXKJr/H29sbMzMwgsKtWrRpQMEMaFBREgwYNOHXqlP78zJkziYqKYtq0afoyT8/iH9q/MxhVKBQmy0q7gMP9tmFtXfxmXR4eHnTt2pWFCxdSuXJlNm3adNfc44yMDFQqFcePH0d1x7cPdnZ2JR6bKaUKli9fvsyrr75K27ZtZRb5AbG2KPnXS7cHvcUxUyrYPKolKdlqstUa3l16gozcfMxVCj7uWPDV0+7LcQz97Ti5+VocrMxYMrgxdSo43cstPDU+/eeMyRUtblejnANhCZnYW5nRsYYXsak5bD4fa7KuSgEtqrjx5Yvyb0c8Yeq+DscXo8pNxU4ZR4bWQ3/Kwey/2cD8HPi7P3wcCk3fg+gz6C6tJzPfiS3JHxCtro4yVkGvrr64FdGNeHaZubuXab2ScnFxoWPHjsyePZuRI0cazVympKTcNW95xowZKJVKunfvXuJ+mzdvTn5+PiEhIfj7+wNw5coVACpVKtgbwdramoCAW9/CuLi4kJaWZlBW1qpVq0ZERAQRERH62eULFy6QkpJS4rjP398fCwsL9u/fr78XtVrN0aNHef/994GCydfFixejVquLnF0eMmQIr732GuXLl8ff399gptrCwgKNxvDb27p166LRaIiLi6Nly5alvfVilSpYDg0NZdGiRbz77rtkZ2fz2muv0a9fv1J99SCK9+FzgWy7GEuOunSf8tzsLLC3NMPbyRoFEBKfSUxaDiqlggndggnwvPV1ydYPW3HhZhqV3Wzxc7dDq9XpA2WAtJx8vtl8id/falKWt6an+a8flVmZLsZSujFodUzeeJFtF2Mp52jN1B41cbQ2Z9rmy1yMTqOZnytbzhfzlSAQXM6B9SMN/0H+dfRGkcGys40FX7xYXXZUFE8e9yDSXl5PxpKhdHCczs6098jQuFLZ+iT1bf+5VS8nFXLTwMYFei8m8nwia388rT+t1eqIv5GOW3njh1/Fs82mQX3MvLzIj401nbesUGDm6YlNg/pl3vfs2bNp3rw5jRo1YuLEidSqVYv8/Hy2bt3K3Llz9akDAOnp6cTExKBWqwkLC2Pp0qXMmzePKVOmGASx165dIyMjg5iYGLKzs/UzxNWrV8fCwoIOHTpQr149Bg0axPTp09FqtQwfPpznnnvOKI3gYerQoQM1a9akX79+TJ8+nfz8fIYNG0br1q1p0KBBidqwtbXl3Xff5eOPP8bFxYWKFSvyzTffkJWVxeDBg4GCB/F+/PFH+vTpw2effYajoyOHDh2iUaNGBAUFAdCxY0ccHBz4+uuvmThxokEfvr6+ZGRksH37dmrXro2NjQ2BgYH069ePN954g++//566desSHx/P9u3bqVWrFi+++OI9vy6lCpZ9fHz44osv+OKLL9ixYwcLFizQfzpatGgRQ4YMeaQ/5KdBZq4GeyszctR5pbru77eb4uduR1ZePmcjU3G0NkOpVOJkbY6Hg5VBXW9Ha7wdb30FMnfXNaNZ6gs303j154PYWKj4pFNVqnk73PtN3ebIulCObQwHhYJGXSrT4AVf/bm4tBx2XYnHydqc56p7olAoSMtWc/x6ElfiMohLy6VTDS8a+roYtJmYkYtSocDZ1qLE45i/L5T5/+2ydz0xi6FLjqFUKrkYnQYUpL3cLSe5ex3jVUjSc/KLrJ+QmceXq8/x99tNSzxOIR6pxBBY9TaXrnuxI2EgOt1k7JQJvOzyBQ5mcVD3DTh52+xO+UYFgfJ/nLxtMTNXkv/fh3+FAlx97u/rUPF0UqhUeH7+GVGj3i/4Rbk9YP5vQs7z888eyHrLfn5+nDhxgkmTJjF69Giio6Nxd3enfv36zJ0716Du2LFjGTt2LBYWFnh5edGkSRO2b99O27ZtDeoNGTKE3bt364/r1q0LQFhYGL6+viiVStatW8eIESNo1aoVtra2dO7cme+//77M7680FAoFa9as0Y9LqVTSqVMnfvzxx1K1M3XqVLRaLf379yc9PZ0GDRrw77//4uxckILl6urKjh07+Pjjj2ndujUqlYo6deoYzB4rlUoGDhzI5MmTeeONNwzab9asGe+88w6vvvoqiYmJjBs3jvHjx7Nw4UK+/vprRo8eTVRUFG5ubjRp0oQuXbrc3+uiu8/s9tTUVJYtW8aCBQs4ceIENWrUKHIB7kJpaWk4OjqSmpqKg0PZBGFPg3yNlqZTd9z1q//bKRQw+rlA3mtXhaTMPHr9dICQ/x76+7hjEMPb3v3rmmZTt3MzJafI8252Fuz4qA0OVvc3Ixodkso/3x43KOv5aQM8fR2ITM6i++wDJGQU3LuHvSXpOWqyTcywT3+1Nt3rFjyUOHbNOZYcvA7AO639+bRzQVrJ+jM32XQuBk97K0Z1qIKjteHY3//zJKtP3byv+zFXKTg/oRMWt82QR6Vk0/XHfSRlmv6w4+tqw9IhjfFxspZvZMTjI/Y8LH8TksOhynPwyq9gYQM/tYCYs/wau5Q83a2vp6vb7aJti4SCZeKubYXzq8DWHVp9DNZOBk3fuJDIodWhaDVa6nWsRGAjL8ST60G/f6dt2ULs5CkGD/uZeXnh+flnODz/fJn3Jx5vgwcPJj4+nrVr1z7Scdzz0nGFHB0dGTZsGMOGDePUqVMsWLCgLMb1TErJVt81UFYpFGj++3zTvqoH3/aqjct/M6qLD4TrA2WA77Zc5o2mlbAvJshduD+s2EAZICEjj+sJWdQsb2IzglLITDG+t8Ky5cci9YEyQFwxr8M3my9zNDyZ64lZ7Lt26yHHn3aH0KmGF7FpObz3+63NVw6EJPBOa38a+7noZ9TrVXI2CJZrlXfkSkw6OUXkgSsVUNnVlpCEW6+vWqMjX6vF4rblyn2crFn7XnPWnY7mUkwa2y7EGqyKEZ6YRYtpO3muuidz+9XDTPXoUlGE0Fs+EBIK8iW5tB52T4XnJkL8FXQ60OgM/xuicfCF4FZw4wD4tYWgzkZNFqpY3ZWK1e/vSXTx7HB4/nns27d/qDv4icdPamoqZ8+e5ffff3/kgTKUQbB8uzp16jBz5syybPKZciYyBQuVkjyNYcCmABpVduHXNxpwIymLLRdi8bC3pE/DCgbB1p3X6XQFAd3tDoUmciQskcsx6WSrtRwMSbzruOwszfBxLv7J1ZIoV8UJa3tzstMLtvC2cbDA278gADcvYqdCU2LSclh2+IbJc8mZeWy/GGdQdikmnff/OoWjtTkr321KgIc9/ZtUIi1bzdaLcfg4WdGqihtnotL462gEGhPLXGh1GATKAK81qoiNhfE/ofLONrzbxp9JGy4UuXzc1v9n77zDoyjXPnxv3/TeCaQQeu9NmgiIIKCiIAqIvZ1j16Mey7Efy2f32LuoCCLSkS691wAhJKT33rZ/f7xJtm8SCH3u68rFzsw7M++Eze5vnnme33Mknz/25XC9ZNsncSFQmm6/XCJSlIi/AtmJv+jl8we7q6cBoJTV0a3uY/ix3uQ/qhfctgzUksuLROsgUyha1R5O4uJj8uTJ7Nixg3vuuadVuxqeLi0Sy6NHj25yjEwmY82aNac9ocuV4/mV3P39bidxO6ZzOHdckUCAlwp/LxXdYgLoFmON8BZU1HE8v4r4MB+m94/l5x0ZlNYIMXpjvzaNUed1xwr4bMNJtp5sWhw78vykLo3HORO8/dVc93hfDqzLQiaDnqNj8fITx71lUDs+WJuCzth0VpAny7ZlB3NYc9S1tVB5rYGvN6fzytTuyGQyHhidxAOjk/jXwgM8tfAQAH4aBS9c24WiagOvLXNtJaSQy3jrhh5M6e25qUJxlee88/Jag8ftEhLnjMQr4fhy63JCff7l9V/CmhcZVHKSqPyfqCwsJ0Z9iCClTQpT7j7Y/zP0v/2cTllCQuLSpTVaVLcmLRLL69evp127dlxzzTVurT4kWk5lnYE5X+1wEsoAG44X8ld9pPTantG8N71XY67r7lOlzPlqB5U6IxqlnP/d0pdl/7yCDccKCfZRc1UX4b+47mgBc7/d6bLAuDm0DfY+vR1dEBjuzfCbnItAA73VPHRlB95YeeyMjj9/d7bH7QqHqr2KOgPzdmQ2LlfqTHy7NYORHcK4pnsUSw/mOh3DZLYwpH1okznHk3pG8/u+7Mbfe6C3irL6G5lAb1Xj/4+ExDlBVwkaNy4U138hUi9yD0D+IVj6CBxeCDd9DxNFJ752Wz4QXsquMLsvbJWQkJC42GmRWH7jjTf4+uuvmT9/PjNnzmTu3Ll069btbM3tsmHFoTxyyl3nDdsK6MX7c5jWtw0HssvZn1nG0bwKKnXiS0pnNPPGiqOseGg40wfYNwRYfij3tIWyj0ZBYvi5qV6/d1R70oqrmb9LRJ5DfdUUVLbMFcQT4X4a7rwiwW6dSi5HIZfZpV4cyCrnQFY5HSJ8uWdEAv/bcNJun2HtQwn3a7ppy6hO4fxw+0DWJBcQE+TFpB5RfLTuBAWVOqb1bUNsK96ESEi4ZM93sPUjKD0FxloIioeZvzl30NP4wtiX4ePBUFP/9Cl9E6x9Ga6pr84fdB+UnITkJWDUga5crA+Kg243OJ97/y+w+V2QK2HMC9D+yrN0kRISEhJnl9Nyw9i6dStfffUVv/76Kx07dmTu3LncfPPNza6Mldww7Pl9bxYP/7K/6YHA+G6RrDjk2v83IcyHtY+OdFr/zqpjvL/2hN06hUyGSiGjf3ww0QFe/LJLRFe9VQq6xvhTZzDjpVbw5PiO9G0X7HTMs4nOaEKGjNlfbWfryZLG9a7yuZvD69d1J8JfS6/YQJf2cl/+ncbLS4+4vKEYnhTKRodOiYdfGIuPm6LJOoOJ/1t9nGP5lfRrF8S9I9ujkMtILaxkxmfb7QoXO0T48tOdg6RuiRKti64K9v4ABUdgz7fO2+OugDlLXO/7WqzwSW4gaRzM/NV5nNkEx5aBvhqSxtrZxQGw7yf44z6r/ZfSCx7cDQGeU5ckLnyk72+Jy5HTKvAbPHgwgwcP5r333mP+/Pl89NFHPPbYY+Tk5Eh/PKfB1d2i+HFbBrtOlXocF+ClIrWgyuU2mQzuHZHocts9IxPZm1nGppQi/LVK/jWhMxO6R9nZqd0/qj0VdQY6RvqhOs8ODRqlqHqePSSObSdLGttMPzG+Iz1jA3n3r+NsPtG83OtgHxXX9Ijy6Ahy+7B4RncKZ8mBHN5edbxxvUwG3WIC7MRy5yh/t0IZ4NlFh/htdxYA648VYjBZuL5PGya+v7mxbXYDx/OrePK3A3w5p3+zrkVCAhDRXblStJQ26mHdy5CzF6J7C+u2z0ZBcYr7/SvzwGSA9M2wfx6YdNB1KnSZLFwtDvxiHevO5UKugM6TnNcXHodfZlqdNRow1oo5+UaAolXryiUkJCTOOmf0qbVnzx42bNhAcnIy3bp1k/KYTxOtSsFPdw7i042pdmLNkfJag5NrxMD4YK7rE0PHSH+37am91Uq+v30gNXojXiqFy1zbtiEXXkrA+G5RLLhvCLvTS+kQ6ceIDqLN6fdzB/LzzkwyS2sYlhiKt1rBM4sOcSTXGhGTARYgNsgbeTP8jONDfXhgVHvSiqpZuCcbuQz+dXVnbh8Wj8li4a8j+cQEefPKFM9pR5tP2EehP9t4kiO5FU5CuYGjeZVNzk1CAhBR2gV3wKHfxPLAe4RwTlklltM2wqktnoUyQNIY+GocZNt4nh/+HW7+Fa79ALyCoOwUdJoEvWc2f36GWvh+MlS48C9X+8KWD+H7qeAVDO3HQEgi9L/DOSotISEhcYHR4jSMnJwcvvnmG7755hsqKiq45ZZbmDt3brN7hoP0GKeBhkf2yw7m4qdVMaR9CF9sSvO4j5dKTveYQPZlldE9JoCPbu5DZIDW4z6XC/szyziYXc4rS4/YNTNpH+7Ls9d0xmKBhXuzWHU4n3B/De9N702ftkFOxymt1qNSyvHV2N9L1tULXq3K6vf5x75sMoprGJoUSp+2Qcz8YptT1NtT+sjkXtG8N733aV+zxGXEseUwb7rnMSpvMNS43670gq7Xw/4fnLd1vR5UWtj3o1jufQtM/qj58ytKgQ9dtMP1i4IO42D3N87bQjvAXesl27mLCOn7W+JypEViecKECaxbt46xY8cyd+5crrnmGpTKlgenpT820aL52g//JruJhiCO9G4byO/3DW164GVKtc5I1+dXNmtsqK+Gnc9c2axOeq8tT+azjSeRAY+OFZ0RX1pypLFltkIu46s5/UkK92Xs/22kSufZHUAhh+n92/L0hM74aKTH0hLNYOdXsPRhz2MCYqHc6u6CylukWOz/GSyun254ZPYSiL+ieWN1VfBuN6i1SSdT+8HdG2Drh7DLTcOqQfeLtI2yDOgwFsa8KNI8JC5IpO/vi4e4uDgeeughHnroofM9lWYjk8n4/fffmTJlCunp6cTHx7N371569ep1XufVouTUFStWEBwcTEZGBi+++CIDBgygT58+Tj8STfPZppMtEsoKGQxOCOGDGVIU0hM+GiUjO4Y1a2xRla7J7oUgOgB+uuEkFovweH5z5TEO55Tzk01jFJPZwq+7MokO9OKu4fFNHvOa7tG8MrW7JJQlmo9t4Z0ronvDjJ8hJEksq31FakXna09PKIOwm2suGl+4eT5E9RTR5G43iKI+ryAoSHa/37aPRMvsomOw5QNY99rpzVVC4gzIy8vjwQcfJCEhAY1GQ2xsLJMmTWpR34iRI0eeljA93f2aYufOndx1110t3m/9+vXIZDKPPxeaD/LZpkXf1M8991yzonASQjytPJxHakEV3dsEMLR9qF3hnM7QfFcHuQwWPziMrtFn1m76cuHTW/ty1TsbySjx8Di6nkfn7+P163rw+vKjVNQZmNavDfGhvuw5VUrHSD+Gtg912YK8oFKHWim3y0XOKa0F4EBmucdzxgRqeeP6Hi28KonLmrxDsOY/7rdrg+D2v0Tx3KzFsOwxqCkShX9tXKRGNAffCBFV1tdAykpRVNhhPCg81KbE9oe7N1qX6yrgo/6iqLC5/P0OhCaJgkOVlGJ2OWI2W8hNKaO6QoePv4aopEDk8rOnPdLT0xk6dCiBgYG8+eabdO/eHYPBwMqVK7n//vs5etR1g6oLnbCw5gWOHBkyZAi5udYeA//85z+pqKjg66+/blwXHHx51Rq0SCy/8MILZ2kalw4ms4XlB3P4anM6ezLKGtf3iAng13sGN+a73tgvlvm7MhvbIWuUcnRGIaDVChnTB7alTYAXcrmIQkYFnnm76csFjVLBkn8M44M1KeSW13E0r5IT9S4iXiq5XT7zzrQSrvtkCyXVws95a2oxMpm1S2C3aH+enSg6GDaMiQ7Q0ic2iLbBXhzMtnbhyyytwWAy89dR+3bbjvxjdBJeaukxs0QLyN3vOTpcVwqZ2yBuGMyfBVk7xfrM7dD1Omg3RBT/gfBaDooTQrY4xX3EWqECmQI+GymivgBhneGev5vvaPHb3JYJZRDX+ftdsOZFuPV3COvYsv0lLmpS9xaw6ZcUqsusQQqfQA1X3JREYu/ws3LO++67D5lMxo4dO/DxsebPd+3alblz5wIwd+5cCgoKWLLEartoMBiIiYnhtddeY9OmTWzYsIENGzbw3nvvAZCWlkZcXBwbNmzg8ccfZ//+/QQHBzN79mxefvlllEolc+bMOa39vvvuO+677z727t1LUlJS43WsXbuWPXv24O3t7ZSGUVZWxpNPPsmiRYsoLy+nffv2vP7660ycONHu96FWq4mMjGxc9vLyQqfT2a1zR1ZWFo8//jgrV65Ep9PRuXNnPvroIwYOHAjAH3/8wYsvvsiRI0eIjo5m9uzZPPPMM6eV0nsuadHsgoKCXEaWAwIC6NChA4899tgF0cP7fFFUWceQ19eid9GJ70B2OQv3ZHPzQNEwpEu0P38+OIwNxwsJ99Mytks4v+/NoaRGz1VdIkgMOzeNQC5V/LUqnrlGFJ3W6k1M/2wL+7Mq7IQyiGK9BhEMwkHDNov/UE4Fc7/ZyeiO4VTpjSSF+3Lb0HgCvFVEB3pxMNsqNHw0SlQKOVqlnDqj+ycHv+3J4iaHxjESEh4J69z0mLJMYQnXIJQbOLzQfrk0TbhQRPeGmL5CXB93kedfngWb3rYKZYDCZNj2CQx90PUc9s0TAj2iqzhH5jbPc/ZUkFiRLToGzpzv+RgSlwypewtY8ekhp/XVZTpWfHqI8Xd3a3XBXFJSwooVK3jllVfshHIDgYGBANxxxx0MHz6c3NxcoqKiAFiyZAk1NTXcdNNN3HDDDRw/fpxu3brxn/+Ip0BhYWFkZ2czYcIE5syZw3fffcfRo0e588470Wq1vPDCC7z33nuntd+sWbNYsmQJM2fOZMuWLaxcuZIvvviCrVu34u3t7G5lNpu5+uqrqays5IcffiAxMZEjR46gULRe4KaqqooRI0YQExPD4sWLiYyMZM+ePZjN4vtw06ZNzJo1i/fff58rrriC1NTUxjSR559/vtXmcTZokVh+9913Xa4vKytj9+7dTJw4kd9++41Jk1z4b17ibDlRxM1fbPc4ps7BPiwhzJcEG1F8Y//YszK3y531xwrYn+U6etYQ2fdEjd7Ekvq211d2Cie6Psr/yFUd2ZVeSnG1Ho1Szr/rxXlTqUrn28da4iKkOZHc6N4iGhyS1LR93KpnxL8h7UWTEneUZzmvKzjseuzWj2Dl09blsgzwjfSc9zzmBZHesewxsLi4wcw9AJk766/two48SZwZZrOFTb94ft/+/WsK8T3DWjUl48SJE1gsFjp16uRx3JAhQ+jYsSPff/89TzzxBABff/0106ZNw9dXfI+r1Wq8vb3tIrAff/wxsbGxfPjhh8hkMjp16kROTg5PPvkkzz33HAEBAae1n1wu59NPP6VHjx784x//YOHChbzwwgv07dvX5fz/+usvduzYQXJyMh06dAAgISHB5djT5aeffqKwsJCdO3c2pmm0b2/tFvriiy/y1FNPMXv27Mbzv/TSSzzxxBOXllhuuEB39OrVi9dee+2yFMv3/rjH4/YgLxUTe0ado9lI2NKUM0VL+HN/LrcOjgOgY6Qfax4dQUpBFbFB3o0WfhH+GtKLrdGyXrEBHM6pwGCy4KdR8shVHVptPhKXCcFNfKlF9oDw+i/7GfNg/hzId47QlRjbYLYoCFGeQiYDik+IH20g1JXZD1b7wtB/Cl9ns83fUPsxrudw5A/75cO/g6+HKGDCKOg7B5Qa6HEjZGyHn6bZi+aqPPhyjBD0tywEpXMHTolLg9yUMrvUC1dUlerITSkjpqOz5efp0hL33DvuuIPPPvuMJ554gvz8fJYvX87atWs97pOcnMzgwYPtgihDhw6lqqqKrKws2rZ1/ZSxOfsFBQXx5ZdfMm7cOIYMGcJTTz3ldh779u2jTZs2jUL5bLBv3z569+7tNp95//79bN68mVdeeaVxnclkoq6ujpqaGpcR8QuFVg1xTZw48aJNhD9TavTuBZmPWsFv9w4h3E8qVjkfdIn2p7UCEaF+atYdLeCdVcdYcSiPQG81/eOC7byu35zWk0BvUQTVKdKPWwfFEVMvph++qgP94i6vwgiJM8BigZx9QtBe838ihxggKAHGvyZEdHhXmPCm/X5Vznnz68rvZV7RB/xS/C7Lyv6F2WLz8V9XBoMecD63Txjcugh8wsW5vUPApMclvhH2y4Za+8YntvjHwLRvhFAG0PiJZinhXV2PT98ERxa53iZxSVBd4Vkot3Rcc0lKSkImkzVLu8yaNYuTJ0+ydetWfvjhB+Lj47niimZaK54lNm7ciEKhIDc3l+rqarfjvLzOft1TU+eoqqrixRdfZN++fY0/Bw8eJCUlBa32wtZHrSqWdTodavXleeffJcreb1KtkDEsKYSpvWNY/OAwEsOlHOTzxdurjjcW7DUXP60SV/q6W3QAt32zk/fXnuCeH3bz6YZUQORFL9yTxcI9WXSN9mfH02PY8cyVfHprX55aeID0omryyut4eekRDmZ5dsuQkADAbIb5s+GzEeJn87v2RX5bPxId/AoOw483QukpsX7jW1BtL5bz9UkcqR3buJyuG0CaboD9+Wrsu09iqBYiPTQJ9NXi3DXFsOg+kRrhyPjXrLnVgW0hoI37a6vIdu3uMe0bkXKh9nPelrLa/fEkLnp8/DWtOq65BAcHM27cOD766COXYrOsrKzxdUhICFOmTOHrr7/mm2++4bbbbrMbq1arMZnsU/s6d+7M1q1b7SLYmzdvxs/PjzZt2pzRflu2bOGNN97gzz//xNfXlwcecLjhtaFHjx5kZWVx/Lj7LsFnSo8ePdi3bx8lJSUut/fp04djx47Rvn17px+5/MJOT2zV2X355Zfn3Tj6fPHrPYMZ1TGMqAAtV3WJ4MAL4/jh9kH83029pGK980x2vaVbAxH+GiKa+MCtrDOiUdn/eajkMlYeybdb9+uuTOoMJm76bCuP/LqfR37dz42fbsVssRDup+Wd1ccx2BR8mi1wNK8Jv1yJy4eqQiE+v70Wdnxuvy1tvX1qQ9kp6+vSk/b5xLpySNsgXhudI28Gi/P73ei4Lqwj2N4iavxFk5MNbwjh3IgF8g44X0tAG7h/GzyVAQ8dhC7XOo+xJXmxfTUtQGh70dHvyXQRzbbl8EKok240L1WikgLxCfT8uewbJGzkWpuPPvoIk8nEgAEDWLBgASkpKSQnJ/P+++8zePBgu7F33HEH3377LcnJyU6pqXFxcWzfvp309HSKioowm83cd999ZGZm8uCDD3L06FH++OMPnn/+eR555JFGgXg6+1VWVnLrrbfyj3/8g6uvvpoff/yRX375hd9++83lNY4YMYLhw4dz/fXXs3r1atLS0li+fDkrVqxotd/jjBkziIyMZMqUKWzevJmTJ0+yYMECtm7dCgj74e+++44XX3yRw4cPk5yczM8//8yzzz7banM4W7QoZ/mRRx5xub68vJw9e/Zw/PhxNm7c6HLMpY5GqeDr2wY0PVDinDO6czjH8q1FRuF+WuJDvVm8P9fDXlBnMKOQyzCZLchk8OLkbqw4bG+DFeClYktqEQdsosWHsivYeLyQzlH+/LEvx+m4PWMDz+yCJC4d5k2H7F3iddoGkSfca4ZYdiF6PVJdAosegKN/Om2KUh8lXJVCgUFYTPkrcmmn2WU/6Phy62u5Eq5+A/78B6Q6NGWQKUSked4Mkes8+hn7KLK23g9+2CPC7eLUFuGOcXQZ5O23mW+haFYS0cX++CVpcHQJBLazj5CbjfD1NXD7KlBfuLmNEqeHXC7jipuSXLphNDDsxqSz4reckJDAnj17eOWVV3j00UfJzc0lLCyMvn378sknn9iNHTNmDFFRUXTt2pXo6Gi7bY899hizZ8+mS5cu1NbWNlrALVu2jMcff5yePXsSHBzM7bffbicQT2e/f/7zn/j4+PDqq68C0L17d1599VXuvvtuBg8eTExMjNN1LliwgMcee4wZM2ZQXV3daB3XWqjValatWsWjjz7KhAkTMBqNdOnShY8++giAcePGsWTJEv7zn//wxhtvoFKp6NSpE3fccUerzeFs0aJ216NGjXK53t/fn44dO3LvvfcSH9909zKpXabEucRstvDF3yf5ZH0qpTXCF1mlkNlFfAE6R/qRnGdfuT9nSByTekYTE+hFZICWlPxKbv1yB3kVdYT4qPnmtgFkllZz34977fYbnBBCZmkNWQ5RbZVCRsorE87CVUpcdBjq4BWHPN9et8AU8cWCvga+HAv5B5t3vOAEkZbh7nRmDcfrhmO2KEny+hutvInufB2uthfQIPKS+86BDf9FGC0CwYlw3zbn4rtN78ChBSLvecKbcGItrHjCfswDu0U0uYHiVPh8tHOxoS2BbeG2FRDgLAYkzj5n+/vblc+yb5CGYTeePZ/lllBVVUVMTAxff/0111133fmejsQ5okWR5XXr1p2teUhInDXkchkTukfx6jJrAYfBZEGjlKEzWgVzkI+aIYkhbEktBoSwvbZXNH3aWiuvkyL8WP/4SPLK64jw1+KlVvDBWnu7Iy+Vgq0ni13OxTG3XeISpSwTyjMhvItwd6guguB4++53Kq2IntqmV4TZVKqrvWHuCtj1FWz/FCps0i6C4kQkWV+f0iNTeBTKACq5jq7eLcj7tZhBqQWjTUv4gfeIwj1sbjRLUkVahm2nwP2/iKYiDXw+Gu7bDgfmia6CIHyYbYUywMH5noUyCEu6DW/Ate83/1pAdEG0mIRziNSJ9oIlsXc48T3DzmkHv+ZgNpspKiri7bffJjAwkGuvbSLNSOKSQjKulLgsCPBSoVbK0ds0C+kQ4c/BbGv6xND2ocwdGs9Xm9MortJzTY9IO6HcgFalIC7Ual5vm+IBYHbxsEarktMlyp8Pbu7TGpcjcSGz+X1Y8wKYTaDyEe4RZoNwepj9J/iEWMfO+BkW3QsVOdDpGhh0v/2xNL6Qsc1eKEd0h7nLofAYrH1JNCLpeTMsdti3KTw1BJHJYeg/oOdNIqfaWAfxw4VYPrTAefzBBfZiOcfBSlNXAb/MFBHh7F2g9oHInpC6Fox6SBgBKi+xvjm4E9RmE+QfFteGRTQ1qasQIjmz3ge/4zVw0/cgl7poXqjI5bJWtYdrDTIyMoiPj6dNmzZ88803F3zHOYnWRfrflrgs8NOqeHtaTx6bvx+d0cy4rhG8eUNPPlibQkpBFQPjQ7h7eAJyuYz7R7Vv+oDAwaxysstq6BYdwCkbX+UQHzU55XX2gy3wv1v7SvaBlzq7voLV/7Yu2xbGFRyGv9+BcVaPUSK6wN0bPB+zwqExiEknrNba9INZNgWA6RvhwC/Nm2dAG9EGe4ub6Kw2EBbeDcFxQuD6RwvPZJkMuk6FxY5V9w4NRaJ7Ox8zZ48QzXHDhED+9VaRmwwQ1QtuWw795oqiRscuhI5oApzXGfXw4w3WQkdk2EXAGzi2VHQs7CSlQ0k0n7i4uBZ5MktcWkhiWeKyYVLPaMZ3i6TWYMJfKx6HN7TEbimfbzzJK8uSAQj0UnJtz2hOFVeTW17nLJSBOqOZwa+t5aXJ3Rpbnktcgqx42vP2miIRCbZNx2iKjtdArk1hXEc3Im/KJ8Jd46SbJgkR3aH9ldB7pujyp6+CQwudxThAbYn4qciC76fAP/YKoX9ksfBI7na9NcKs9oOksfDXi0JM978Dek4X21NWWY+p9hUOG6uehS0fYSewc/cJkdxrhhDnq5+DbR+5/524anZycL6NUAaXQrkBY637bRISEhIOtKjAr7WQCvwkLhQq6wzsySgj2FtN9zYuolUusFgsdPr3CnQ2KR1B3io0SgV5Fc5C2RaFXMbmJ0fbNTGRuEQoz4b/83TzVR/pVHrB5A+h+w3NO67FAju/EA0+onrCgLvBlSepUQel6cJezSsIvEJg9bMiLaFNfxj7skhfKDwqxHJADBSfhM9GCus5Twy63168hneBEU+K5icxfeCXW6Cy3l1GrhTXGjdM5DwfXy4iwdd9JtI7fprm+hxTPoFeN4vX1cXwxZVQmuY8TuMPd6yxz+/WVcKal2DHp56vA8A7FO7fYZ8OI9FspO9vicsRKbIscdlSVKXj+k+2NKZQPDi6PY+O7di43WAyU15rIMRHbddy1BXCZcPQ5DlNZgsl1XpJLF+KeEodUPsIuzUQUc1F90HSVVabNU/IZDDgTuBO92OWPykEtdko8nVnzBPNRKZ8bB1zaiv8OA30lWLM9B8hcTTcsxF+udW1dzKI4sFKBwvEgiMimqz2Fm2tK21sGBtaY59cBwPugmfyRac+mUykqbgisgd0mWxd9gkRfsu/3SbymhvnIoeeM2D9ayKFZehDUFMCX41zLaxdUVMESx+BG79t3ngJCYnLHkksS1wyrDiUy9bUYtqH+zJzYDu76ulavYlTJdVE+XsRUN+K+vutp+xyjT9Ye4I7hiUQ4K1iR1oJd32/i7IaA12j/fl27gB81Eq+2pxGSbWe6QNi+XbLKac5NEXnKH/aS90cL01kHno86avtl006qC1tnlhuir0/wPb/WZcNNfDnQ/DPffbj1r4khHLDmL9eEGI5KE4I0x2fici0xg+2fChEvdJLuE7UlglR3EBIe6vXsU+Y+7nt/wVCO0CfOaBUQcJIkY6hrxLbZQpRfFdbIlwuwjtb9y08Zi+UQTh0NESPDy+EyjzxO2yuUG7gyCL4bjIMe1jMSUJCQsIDkliWuCT4afspnv7damafWljNC9d2BSCtqJqZn28jp7wOX42ST2/ty9D2oS5dK0z16x75dR9l9Z7Mh3MqeGfVMU4WVbPtpGjjqVLIGJ4UwsYU1xZxDXirFdx1RQKVOiM+agW3D0tArbyw23pKtACzSeTm1pSI1x6xKTiL6Se647UGeS6aOLhyizAZ3C/LFTDoXnEd2z+FgXdDr5nWVAeLRUSPk/8E/yiY+K5Yf3Sp67bVDejKYdlj4iemn4hm37YcFt4hxHBD++7yLNHkxFbg5x92Pl6DuG7g2MqmOwW64+R6EW2/d7OIwktISEi4QRLLEpcEr9UX2zXw+96sRrH81spjjUV3VToj/150iLWPjWT6gLb8vDOTwkphft+nXSCK+mh0cZXe7ngnCqrZkW7td28wWThZ5MZ2q55B8cHMu2tQkykcEhcxv80VUUpo2vas/VXCXUIbCEMebL51WXk2bHoLdFWiIUjcUPvtbfrBdod9+sxxPs6QB0Vag9lYbw33kP12fQ18NR6Kjonl3d/APZtEExCZDMY8L34ayD0Av86ypl00RfYukS7Sb64Qyo6UpkHBMQjvKPKut37oPEahti/Oq8gUudRypfM85Erod7uIWAe2FefP3m0/xqSDrF2SWJaQkPCIFOKSuOj5afspKnX2UT2zTaF9pc7+S7Sqfjkm0Iuf7hhIUH1axp5TZUz73xZq9EZGdrR/tHwox7kASqXwLII1KoUklC9lKvOsQhmcUy0aUGqgw3i4/jPRyW70M6BtZmGUvga+uUbk+h78VThT5DrkFne/Aca/DqEdRXrE+Dfgqhecj9XlWrhzHVz7Adzxl/BQtiXvgFUog4hOb/lQFM+5ImdP84VyA4VH4dRm99s/Hykivnu+F81OHDHW1hcQOmA2gn+s87rCo3DjdzDhv6Io8PbVILPdXwZhHZGQON+MHDmShx56yOOY9PR0ZDIZ+/btO+NjnU0czx8XF8e777573ubTGkiRZYmLng/XnXBaV6kzctOnWwn11XA4217ozhzYrvH1kdyKxhbYAMfzq9h9qpRBCSEsP5TXuL5G7/yIPa2JyLLiPHeckjjLKDUiQmsxex7nGwU+oaCvhaWPQspfYlkmEw4WfWbDiMdd71t8wj4f16QXYjKqh/24QfeKH4B1r8J/E0Ru8MR3oP0Y67ioHs77NuAdgpM38Y5PIbVeZHoHC/G+9FHI2AJ+0c7jm6LwKGw46v73ZqiBBXfCYA8NVtwJ9IpM53VpG2Dn5yI3e/GDUJErcpQzt4pz+cdA/iHhsOHYTVDismHOnDl8+60o+FQqlQQHB9OjRw9mzJjBnDlzkLtynzkPxMbGkpubS2hoKADr169n1KhRlJaWEhgY2Dhu4cKFqFQtsKeUaJIL4x0gIXEGFFXqXa7fnlbC0oO5FFdbt4f6qpk7NK5x2U/rfL/oq1Hadeg7HVQKGXcPTzijY0hc4HgFwZgXEYIRm38dKEsXRXhfjhH5zbpyETUtPiFaYq97WXgMg2iWMf82IUirCsEvEhQa++MFevDpTv5TtIKuKRZttH+ZJfKQm0NoElxlez31FJ+wulisfg72/yQKATO2iII8hdrzcb1DoP1Y+3UWs/N5Gqgphh43QUAr+ZFX5MBPNwq3koosSP1LPAWwWESu9OIH4aMBsG9e65xP4owxm01kHj5A8uYNZB4+gLnJeoAzZ/z48eTm5pKens7y5csZNWoU//znP5k4cSJGYwufoJwF9Ho9CoWCyMjIJrsHBgcH4+fnd45mdnkgiWWJi54gn+bfQRdV6Zny0ebGTkyjOoYzpVd04/Y5Q+Lo3TaIER3CeGhMEl6q5rfEVchg5sC2PHxVEqseHsHABMnH9ZKnz60iwgw0RliVGtdjK7LdHyf/CKRtgnnThcvDzi9EyoU2SLSCRiZ+uk2DrlOg6ASsfRk2vSPaOTdQdNz+uIZqe1s3R06sgf8Ng48Gwr6fYOg/4QEXFngNUeB8h2LCunJ4+LC4cXBHTXG99Z0D3ae5dhDpNFEUEd69AaZ+JqziYvqL4r6WIpOLNt1lGZ7HWUz2nRclzhsp27fw+f238+t/nmbZ+2/y63+e5vP7bydl+5azel6NRkNkZCQxMTH06dOHp59+mj/++IPly5fzzTffNI4rKyvjjjvuICwsDH9/f0aPHs3+/damQS+88AK9evXi+++/Jy4ujoCAAKZPn05lpTWdqbq6mlmzZuHr60tUVBRvv/2203zi4uJ46aWXmDVrFv7+/tx11112aRjp6emMGjUKgKCgIGQyGXPmzAGc0yB0Oh1PPvkksbGxaDQa2rdvz5dffun2d9HU+EOHDnH11Vfj6+tLREQEt956K0VFRS39lV9USGJZ4qLn6QmdW5TykFpUzX0/7sFstiCTyXh3em/+emQ4P905kIfHJJFWVE1BRR0PjenATf2b71hgssC4rpH888oOxJ9hZFriIqH0FBgdGtF0GC9SIBzxDnV/nHaDRbqDbWpC/iHY+n59FzyL+EnbAEeWiEjoxjdhzYvw7STR6hkg7gp7URkQC0Hxrs9Zng0/z4S8gyI9YtF9kLVbRJh732od5xcNvW8Rr9v0sz9Gm/4iml1b6v7aVN5inK2PcmBbGPcq9JjuPH7cy+Jf72Bx07B/HmTvFILWJ1w0W2kO4V3hlgXi/0Ll3fR4o86+2EHinJOyfQuL33mVqhJ74VVVUsTid14964LZkdGjR9OzZ08WLlzYuG7atGkUFBSwfPlydu/eTZ8+fbjyyispKbE+wUlNTWXRokUsWbKEJUuWsGHDBl5//fXG7Y8//jgbNmzgjz/+YNWqVaxfv549e/Y4nf+tt96iZ8+e7N27l3//2/5mLjY2lgULRBfNY8eOkZuby3vvvefyOmbNmsW8efN4//33SU5O5tNPP8XX172FqafxZWVljB49mt69e7Nr1y5WrFhBfn4+N954YzN+oxcvUs6yxEXP5F4xdI32J7WwmmAfFX/uF5G06AAtr69wUXUPLD+UxyvLjtA7NogesQHc/u0uThXXoJDLMJktyGTwxLhO+Hs1P2rtp1XSKUp69HV54SJfN/lPUDncLHkFwZwlsOn/4OAv9ts6XC3yaEscvILVfkLQ2lJdAL/faW+flrsPNr0JgXEQ2R1u+FqkSqh9RTGh2o1QLD7h0PbZIgR6m76iw2CXKUIEJ44SOdYAo58TgjJjq+jiN/412PG587G73yh+Dxo/UVDoHQQ3fCO6+emqREMW72BRnLh/nvX3GNEd/NuI10Y9ZO1wvv7BD8LWD1xfky0Fh+GHaYC56bxyAF0F/Hg9zPgFlE2klki0OmazibXffOZxzLpvPyOx/0DkzXWSaQU6derEgQOiqPbvv/9mx44dFBQUoNGIJ0hvvfUWixYt4rfffuOuu+4CwGw288033zSmQtx6662sWbOGV155haqqKr788kt++OEHrrzySgC+/fZb2rRp43Tu0aNH8+ijjzYup6enN75WKBQEBwcDEB4ebpezbMvx48f59ddfWb16NWPGiPqFhAT3KYJNjf/www/p3bs3r776auO6r776itjYWI4fP06HDh2cjnkpIIlliUuC9uF+tA8XH0z940TkyWS2sPVkCRuOF7rc58u/04F0FDIRFW7YB0Q64xsrjvLLnQP56m9lo4OGK5LCfYkO9OLhqzoQ7id15rusCGgLchWYbTyLLWZr848G4q4Q+b0jHhdpFg3j5Sq4+g3x2i8Ku4K5btcJobrL5nGpTyhUu3jcueG/1tcqHxFRbTfYeVzOPpEn3aY/HHAQ7XIlRPe2LieNwQmlGsZbvyTR19SLXRsSRsLUT+F6BxEtl0Ona0RKxNJHRVqKUYfdDUdYR3i7gyjiG/YoLtn3o8iTNrmuVbDD0sJc09S1wnWkIZIucc7ITj7sFFF2pLK4iOzkw8R2dVOkehawWCyNrkb79++nqqqKkBD7pxu1tbWkplrdW+Li4uxyhqOioigoKABE1Fmv1zNw4MDG7cHBwXTs6OzK0q9fP6d1LWXfvn0oFApGjBjRKuP379/PunXrXEamU1NTJbEsIXGxoZDL+GpOfzamFFKjM/Hh2hSS85xtsEweivnnfruLahdOGAB+GiU3D2rLU+M7SRZxlys+IRAQIwre3CFXQr/bxOvQJLj5Z9j4lsinHfkUBNW7s+z8HDvhuPcn0fSjAU2Aa6HsiKEavrsWBt4LPaaJaDPA1o9h5b/Ea5W3cIOwZdxrVqeM2lKRCx0QK0SuOzK3QXGK/bqeM9zvYzLAt5Oh9KTr7Yd+s75e/azwpHZssKKrtL85OR08iW13FoASZ5WqMg+pPKcxrrVITk4mPl6kMlVVVREVFcX69eudxtlGdh2dKGQyGebTSPHx8TnzdD4vL69WHV9VVcWkSZN44403nLZFRUW16FwXE5JYlrikUchljOoYDsCIjmH8vieLNckFrHcTbXbEnVAGuKprBP+6urPb7RKXASaja6EcOwgG3SecMOKH20ds24+xt3NrQOnwVMJigBobcaxz9vp2Py89bHkPtn0IwYnQZoBw4mjAUSgDRIgmPqx6VvgrYxFOHP5RcNV/7HOOG9C48It2V+yXsrq+pbYboewKV8I1oE3L21t7BQurPplCzK88y7VY9gmHzpNadmyJVsE30EOR6GmMaw3Wrl3LwYMHefjhhwHo06cPeXl5KJVK4uLiTuuYiYmJqFQqtm/fTtu2wvGltLSU48ePNzv624BaLdKFTCb331Pdu3fHbDazYcOGxrQKTzQ1vk+fPixYsIC4uLgmXTkuJaQCP4nLBl+NklsHx/HWjT0J9D5zD8resYFnPimJi5vKHOd1UT3h1oXQdbJwl7AVyp4Y/axzrnOTNPERbjYJh4x9P9SnPLjBN0LkHiX/CVs+oDHCbdKJm4HfbocSG5FbWybcOA78KnKbG+h2AySNFbZ3v86GDwfAWx3g5Uj48Yb6YsVmotS6jiAPvNu1i4YrFFoYdD90nSpcOaoLROMVg6MIl4nuiF2nwseD4J2uwsZP4pwR07krvsEeimABv5BQYjp3PSvn1+l05OXlkZ2dzZ49e3j11VeZPHkyEydOZNasWQCMGTOGwYMHM2XKFFatWkV6ejpbtmzhmWeeYdeuXc06j6+vL7fffjuPP/44a9eu5dChQ6ft5dyuXTtkMhlLliyhsLCQqqoqpzFxcXHMnj2buXPnsmjRItLS0li/fj2//vqry2M2Nf7++++npKSEGTNmsHPnTlJTU1m5ciW33XabR9F+sXP53BZISNQT6qth0xOj+HBtClmltRzLq+REofjylMvA7CYtQ62Q0T7cF7lcxlWdI7llUDvXAyUubUxGODhfpCoEOBfl0PPmpltfuyK8syh42/Nt8/dRqp3dONzi4jGwTwSY6qAqH769BkLd5BuaDVB8EoITxPV/N1kUFoLoiDfxXZEHjUVEsLd8CLl7mzetgFghfstOWdfJ5KLQbv4sYU9nS/wImLtSeD875ks7YqoT7bDdeTo3YiH1iI7sfAXBykF09VqJbN508I8WTwGuflMq+jvLyOUKRs+5i8XvvOp2zKjZd5214r4VK1YQFRWFUqkkKCiInj178v777zN79uxGISuTyVi2bBnPPPMMt912G4WFhURGRjJ8+HAiIiKafa4333yzMZ3Bz8+PRx99lPLyFjw5qicmJoYXX3yRp556ittuu41Zs2bZ2dw18Mknn/D0009z3333UVxcTNu2bXn66afdHtfT+OjoaDZv3syTTz7J2LFj0el0tGvXjvHjx18wzVvOBjJLg+HsOaSiooKAgADKy8vx929m21cJibOEwWRm1eF89CYTSeF+3P39brLLau3GqBQyFt0/lK7RAedplhIXBJvegfWvi4griJxata9odgEiF/jujSI3+XTI2AbfTLRGVBUakf9raHg/trBjXlO0HSycLZpC7QcP7hJNUopOwId9z+y8Km8Y9jBoA6DXTJFLvec763aFBp7JEy24vxwjcp0bGHS/KDKsLYWPB3v2kW4mR2rGsK7C2jWwp/dihvl/bR0w/HER+Zc469/fKdu3sPabz+yK/fxCQhk1+y6SBg5p9fNJSDQHKbIscdmjUsi5poe1MGHzU6PJKqnh/p/2sD+rnPhQHz6f1bfRbUPiMuX4KuFrbEtdmYgkYxaCtu+c0xPKuio4vgIUKpj9p7BY840UqQOb3rIZ2Mqxjdoy53X+baziv4GxLwmhDMLyrTltvl0hV4mOfpM/FPZxDQy6396vufMk+LCfsMjTBon0iQbSNop/vYJE8aQdzbiZCO8ixHq29bF5St0wuyEpdcPsxXKeQzMWibNG0sAhJPYfKNwxykrxDQwipnPXc2oXJyHhiCSWJSRc0CbYmz8eGIbRZEapuHQfLUm0AMfueA0UHIbZi0//uLpK+HKcOA4I67VbFoJcAX88cPrHbQ7BiULwN0Rn+98BfW+Dz0Zao9veofbFfd7B0HkyHPm9+ecJaCvO4xcFN3xpdehoILwT3LdNRNYP/GrviuFIw82IrlLY4NkS0Q3yD7rfV6GFGfMgsB38fnejfZ5XSCDYBKi9lA45zW0HInHukMsV59QeTkKiKSSxLCHhAUkoSzQS4iZiXGFT5FeZD9v/J5wW+t4Goe1d71NTAtm7wT9GdNBrEMoAJ9dD5g4RVS1Idr2/NsCay+sdCqOeEakMxjpADl4BoPKyn5sjXkGiaYlvuDind4jwdQa4+RdxHUoNjHxaCGRbrnlLzL+8iTbSDTSM01XA51fCEydBU+/TajaLVtNH/hAR3yL7RkJGi5p8r9GoddmEJYTDhPpIu8YPfMKg2sbZxlANs5fA4gftHTMUGiGkxzwPQXFi3XWfwfAnQCZjiLwNxR/soySnGm9/NaNvvxIO3ySKGhNHw5B/Ol9TwVFY+bT4f+h9i9UesAUY9SbMJgsqrYKq0jp2LTtF1rFSAsK8GHVLJ/yCJd92CYkLASlnWUJCQsIThlrRSW/RPZC103l7/AiY8TNseht2fCoiniDE6D1/OxcBFqfC11eLojpkwpd4/0/2YzpOFKkYFg/V5Sov0VGv2/XgFyE6ABYcgbBOEJIoIrQL73S9b2hHke7h1/yiJCfqyiHlL9FlTxsItSWi615QO+HpXFMvYr1D7S3wAG5fDbEDxOsdn8Oyxxo3mS1ydlVfjwITSdqNLCt7lmKjKKbtPbYtQ66rvwHJPwKfj7IvcFR5wzO58FZHqMqzrm83DG6z8ax2gcVioa7agMZbhVzeREGgoQ7e723vhnLzfOgwtnGxMKOSrKNC+Cb0DrM7j8UCB9ZmsmXBCdx9A8vkEN7OnytndyYo8sz9dlsL6ftb4nJEiixLSEhIuKPgKHw/1bVFHIjIZqdrhDuEY2vm2lJIXQd9brWuK8uAH6fVC2UAi+joFzsYMusL7VTecGyJi5M55OMaaiGkvVXwBseLnwZ63Ailp4QQL8+2FiWGJAlruzMRyiCi292vFz+O9L4VTq4T/sb75zmnVQQnWl8XHLHbJJeZ2V89Gb3Fh/01k6g1BzZu27sqgx7DQvHVp8If9zs7gcTUFx7GDxed+BqIv6LJy5HJZHj5NtPxoiLb+T2RvatRLGceLWHJB/sx13c86jOuHYOnJnJoYzab56dgNDSd720xQ35aBfNf28nct65AqZJydiUkzheSWJaQkJBwRWUe/PkP90I5foRIRVj+hPtjbP1ICLr+dwif46/GC6Fli9kEs/+AzO2QtRvWvOB8HLkKbvoBfp5hLaxTqN2neTQw4nHxY6gVkVjfMAhs63mf1sA3TIh1gLaDhJAsTRfh0mGPQM5ekQ4R2l44cuz6qnHXYkMseouIpNoK5QbM30+Dyh1O6/GNgGnfiNeT3hOtwQuOiKjyFY+06uXhF+UcMbfJwz62/iiJqg0YlRrSdP05uD6LzkOi2DDvWItrNA06Mwc3ZFFZrCP9QBF+wVpG3dqJwHDvVroYCQmJppDSMCQkJCQc2TdPRC4d0yBUXiKanHilKIo7vqJ5x+s5Q6RfOEafAZDBTd8LB4iM7fDVWPvNXkFwzdsi3WLvj7Dxv8IF4srnocu1p3V554XaUhHp/n6KeC1TwJRPoOdNsP1TOPgbxoIUlPpSqkwhLC99kgJjEl6yUmotomtbkvdWxvr/1/XxJ7wFA9yknZwNcvbCsidE4WLvW0QDGoCaEmreGYa3UdwUpdYNYqP5WToMjGTf6kz3x2sBwdE+zHju/BQdSt/fEpcjkliWkJCQsMVshpfDXXePu+o/VlE0bwYcW9Y659T4w7/qhdSqZ+u76CFaZo9/rXXOcb5JXQfzbrLvJOgbAY/Vu4wse0LkfNdTaozmeO1wunsvJ0PfB7WsmnjNDmSO6cTdroeEUfbpLueT7Z86PW3IHL2M5QuNGOqa7nAmk+E2j9k6CO79aFTTudVnAen7W+JyRErDkJCQkLDFbHQtlBNHW4UywBWPQtom0Fee+TkNNdbXY18WqQrg7EJxkWA0mKgq0eEdoEatVYrCv19nO7fcNhlER8CaIii393YO1JYwUL0AzAY6ea2zblCorE1K+t4Gk949uxfTUlz4AUd3DMVQl+1isD2+wRpueLIfuSfKWPn5YbfjVBopf1lC4lwi+WJJSEhI2FKRBV4hzuvLMqHaJke1TT+4b6t9sdrpEuHgO+wdfNEK5bL8Gn58fhs/Pr+N757ZQt7JcuGcoXPRzrfPbHivJ7zd0VrgWI8sfgQMe0gUEjbgEy48qK/+L9z43YUnlAF6TIeontblvnNQRHQkKNJ9jnFAmBdj5nTmxqf74xOgoX3fCKKS3HcLNdSZKMpshZs0iYue9PR0ZDIZ+/btczsmLi6Od9991+32kSNH8tBDD7kdL5PJWLRo0RnPtbX55ptvCAwMbFx+4YUX6NWr11k5lySWJSQkJBrY+RV80Bdqi523FafAjzfYrwuMtfr2NheljXeuNhCSxokCv0sBo44tny6lqkREkHXVRtb/dEwU2zU4VTQw/jVR+NfQLbCmRHgh974FOk+i+ugODOvfB+RCHE/+CO7ZJJwuBt5t3yjlQkLjC3NXwaw/4I41MOk9zCYz5YW1bnfpPrINSf0jMBstmE2igHPqI30IjHAvsI2GplM6JJrHnDlzkMlkvP7663brFy1ahMwp78czjsLzYmDhwoW89NJL53saFzRSGoaEhISEUS/yZVf9Gzu7AtvmHyCKumpLRdEdCCeLuormnye6L8xZKlwavIPtrd4uBZY9jq6wPWCNzOtrjSIRd8r/YNE9nCqO4ZTPNPyretGj6vvGiE22vitHM6fg49WXnL3HyNXNRY6RDl4bGHjiEL4zPzgvl3RaqLSiE2M9FjOYzc6JyEq1HJVGwZHNOexalkZdtREvPzVTH+1NUKQPM54bwLf/2kJNhd5p3xWfHeKWFwej9rr0vsYtZgu6tHLMlXrkfmo08QHIznJ+tlar5Y033uDuu+8mKCjorJ6rOej1etTqZloZniHBwWf3Kda5vJazhRRZlpCQuLzJ3gvv9xSFdY6+XgqNw2CZcKRooCgFsl00KrHbRS72i+knXC/UXtCm76UnlAFS19LF+y+7VV2GRolOeN9OIjVVxZL02zh42JfNv51gbZXIzS4wJLCm7AH6yL8kMPldSvWRAJhRcrT2Sn7ZOp6KIveR2QsdhUpOj5FtnNYb9WZqKw2U5FRTV20EoLZSz9KPDwAgV8jxDXZ8DwpqKwzkprpIbbnIqT1URN4bOyj6/CAlPx+j6POD5L2xg9pDRU3vfAaMGTOGyMhIXnvNfUFtcXExM2bMICYmBm9vb7p37868efMat8+ZM4cNGzbw3nvvIZPJkMlkpKenO6ULgHPUuiGF4IsvviA+Ph6tVjyBWrFiBcOGDSMwMJCQkBAmTpxIamrqGV3rF198QWBgIGvWrAFaHg3PzMzkxhtvJDAwkODgYCZPnkx6enrj9jlz5jBlyhReeeUVoqOj6dixo9tj/fnnn/Tv3x+tVktoaChTp05t3KbT6XjssceIiYnBx8eHgQMHsn79+pZebqsgiWUJCYnLl6NLRRc4d22hB90LXabYrLDAqmfg1BaxqPbQWc07VKQPPHwEni+FO9dAQExrzfzCJDiBjl4buDboBfr7/Mz4npvpl3QCPhoEVXmcqBtqNzwlMxgmf0JG+L0M9fuGIGUunbw2MCvsHmLVexvH1Rm9OL4jz/FsFxVX3NSBMbd1adbYCpuUjbjuoW7HaXwurahy7aEiin9IxlRuH0k3lesp/iH5rApmhULBq6++ygcffEBWVpbLMXV1dfTt25elS5dy6NAh7rrrLm699VZ27BCWkO+99x6DBw/mzjvvJDc3l9zcXGJjY5s9hxMnTrBgwQIWLlzYmINcXV3NI488wq5du1izZg1yuZypU6diNjfd2MYV//3vf3nqqadYtWoVV155ZYv3NxgMjBs3Dj8/PzZt2sTmzZvx9fVl/Pjx6PXW/7c1a9Zw7NgxVq9ezZIlrposwdKlS5k6dSoTJkxg7969rFmzhgEDBjRuf+CBB9i6dSs///wzBw4cYNq0aYwfP56UlJSWX/gZcmn9pUlISEg0F7MJfpuL2y4R/eaKZhYn18ORRfbbik9AuyEiZ3nUM7DuFbHeJwxi+kDX66HbdcK54XJi8ocw/zZiC44QGxsMN7wubkbquweqZfZFaXJTHct/LqFY3Zsp6lcb16vkdQz3/5wfiz5uXKdQXvwOEB0HRpK2v5DUPYUex8nkMgw6EyqNgo4DI9mxJM3pbdptZBsi490XAV5sWMwWyv70HDEt+/Mk2i4hZy0lY+rUqfTq1Yvnn3+eL7/80ml7TEwMjz1mbc3+4IMPsnLlSn799VcGDBhAQEAAarUab29vIiMjW3x+vV7Pd999R1iYtT369dfbd8j86quvCAsL48iRI3Tr1q1Fx3/yySf5/vvv2bBhA127dm3x/AB++eUXzGYzX3zxRWNk/OuvvyYwMJD169czdqzwiffx8eGLL77wmH7xyiuvMH36dF588cXGdT17iuLYjIwMvv76azIyMoiOjgbgscceY8WKFXz99de8+uqrLo95tpDEsoSExOXJ3h+c2yUD+EbCAztBW+8hG9EdvEOgpr7oT6mF2EHW8SOegJ7TQV8NoR1cWoddNgS2FRF0W/RWWzyNzP73bcSLk+VdAB21IYH4Kkobt2kVVY2vw7zz6Nr9HHQePAeMvb0rR7vmUVupx6Azk7q3AJlMRnlRdaNjodlkYcGbu7n+8b4UnKpEpVFgqDMhl8tI7BfOkOsS8Q3Uej7RRYYurdwpouyIqVyHLq0cbWLgWZvHG2+8wejRo+1EceP5TSZeffVVfv31V7Kzs9Hr9eh0Ory9W6ebYrt27eyEMkBKSgrPPfcc27dvp6ioqDGinJGR0SKx/Pbbb1NdXc2uXbtISEg47Tnu37+fEydO4OfnZ7e+rq7OLj2ke/fuTeYp79u3jzvvdN1I6ODBg5hMJjp06GC3XqfTERLiwq3oLCOJZQkJicuPkpNwYL7rbVc+bxXKAD4hMHsJbHhD+PsOvg/C7D/Az0kL6YuVgXfB2pcBMOJe4O2oms6EwNeRyUQItdQQyc2h96Mz+xCmSkOxuCvcvfGcTPlsIlfI6TI0GovZwrJPDlCWJ24m/EI0VBZbfaiLs6o4ui2XTb8eb2wkaTZbkAHefmry0ytQquWERPueh6tofcyVnoVyS8edLsOHD2fcuHH861//Ys6cOXbb3nzzTd577z3effddunfvjo+PDw899JBd+oEr5HI5jv3fDAZnL3cfH+e0rkmTJtGuXTs+//xzoqOjMZvNdOvWrclzOnLFFVewdOlSfv31V5566qkW7WtLVVUVffv25ccff3TaZiv0XV2LI15eXh7Po1Ao2L17NwqFfQDC1/fcv+clsSwhIXF5UZYBn18JtSWut4e5KEaJ6AI3fnt253WpMvxxiOwBRcdJkg3g8A81mE3OqS+5+k6NQhkgVJmBSm7TxKTw2LmY7TkjP72C9INWi0JbodyArsbo1HH9+I58KkvqyD0hivt6XhnLsGlJZ3Wu5wK5X/PcEpo77kx4/fXX6dWrl1Nh2ubNm5k8eTK33HILAGazmePHj9OlizUXXa1WYzLZ/6eFhYVRWVlJdXV1o4j05IvcQHFxMceOHePzzz/niiuuAODvv/8+rWsaMGAADzzwAOPHj0epVLqMnDeHPn368MsvvxAeHn7GHRx79OjBmjVruO2225y29e7dG5PJREFBQeO1n0+kAj8JCYkLj0MLYdPbkLW79Y99fKV7oTz8ceFUIdG6dBgHQx4kavBApj7ahz5jYxkwxERklFVUOLpo2AllIEffhaUfH6D2LEcWW4Oyghp2LElj06/HyTlR5npQE2m3PoEaTu4tdJmf2yCUAfavyaQ0r/oMZnthoIkPQBHgWQgrAjRozkGedvfu3Zk5cybvv/++3fqkpCRWr17Nli1bSE5O5u677yY/P99uTFxcHNu3byc9Pb0xbWLgwIF4e3vz9NNPk5qayk8//cQ333zT5DyCgoIICQnhs88+48SJE6xdu5ZHHnnktK9ryJAhLFu2jBdffNFjkxJPzJw5k9DQUCZPnsymTZtIS0tj/fr1/OMf/3BbGOmO559/nnnz5vH888+TnJzMwYMHeeONNwDo0KEDM2fOZNasWSxcuJC0tDR27NjBa6+9xtKlS09r7meCJJYlJCQuLFY9C7/dBmv+A1+NhRN/Nb1PS/By4aF6x1p4KhNGP9u655JwIjIhgMHXJdF/1lVc//xV3PfJKO58dzgDZw6xG1dj8mdr5c1k6bpxuGYMywofJv1AEWu/P3qeZt48irIq+fml7excksaBtVn8/tYe/v7NuXo/Is4fn0BncTh6VifadQ+hukxHYUYlFhf+zI4YDafnjHAhIZPLCJzkuRtm4KSEs+633MB//vMfJ8eJZ599lj59+jBu3DhGjhxJZGQkU6ZMsRvz2GOPoVAo6NKlC2FhYWRkZBAcHMwPP/zAsmXLGu3mXnjhhSbnIJfL+fnnn9m9ezfdunXj4Ycf5s033zyj6xo2bBhLly7l2Wef5YMPWu5d7u3tzcaNG2nbti3XXXcdnTt35vbbb6eurq7FkeaRI0cyf/58Fi9eTK9evRg9enSjswiIwsFZs2bx6KOP0rFjR6ZMmcLOnTtp2/bcp73JLI6JNOeAiooKAgICKC8vP+MwvoSExEWAoRZ0lcItoqmOWK9Eg8EmUtZlSuukQJRliEf5wQnw8SAw2UQor35T5NZKnF/Wvgz7f0aHP8uy55JT5VyI5BcoZ9brI8/93JrJys8OcWJPgdP6O98djlprzXysqdDz9RP2j9R9AjXc+tJgfn1tJyU5zY8WT36kN206nJtGGmf7+7v2UBFlf6baFfspAjQETkrAq5t7Gz0JibOJlLMsISFxdjmyGBbeBcZaiLsCbv7Fsz+xxs9eLGtaoZgjdS3Mu1nMQeVlL5QBSs7M5F+ilRj9LIx+Fg0wvkpPcXY1xzedIHmX1XLOt/YIlCddsJ7VBZmuOzqWF9QS1tbqIFBX5Vzg1WlwJAqVnJAY3xaJ5T/e2ct1T/QlKuHit5Lz6haKtkvIOe/gJyHhCSkNQ0JC4sypKoRF98F3U2DXV9b1JgP8frcQqQDpm2DrR56PNeldUNZXSQfFw8h/nfn81rxknYOhFlQOVk8Jo878HBKtipevmjYdgxjQNQMF1pubPF0SBfsOnMeZuWf3inQqCp3tCBUqOX4h9k4g/mFa/ILt15XmVWMymgkMt7oEePmpCIpu2pps+ScHWiSwL2RkchnaxEC8e4WjTQyUhLLEeUeKLEtISJw+R/6E/INw8DdrdPbkOlD7QY9pUFsKhhr7faqb6MLV8Wp45AhU5omUCVUr+MmajfbLwYmikK+6CLpOhY7jz/wcEmeFCllbTFgjyxYU5FcEEX4e5+SKglMVbFt00mm91lfFuDu6ovWxb1Czcd5xKkvshfXJvUVsXZTK/jWZjetqKw30vyaeQxuzPYrh2koD81/fyU3PDiAwvHV8fyUkJASSWJaQkGg5uQfg+ynWRh2OpG8SInS+gyWQTA5dpzR9fO9g8dNaDH9MdOszG0GuhJFPQudJrXd8ibNGQOceKJWbMBobHoRaCOnUHgqPw+rnRC583zni5uw8Ul3mbP3WfWQMw6c7WxGajGaObs11eZyS7Gqnbn1GvZkxc7qw4L+7MBnFRq2vyimVw6gXxx002XOhnISERMuQxLKEhIRnqgqhPANC2sOpLbD9f5C1U3Ssc0doEmTtglMOnqAWsxDa7Ya43u9s0WUy3LUB8g5CVA8IiIVjK0AbAO0Gn9u5SLQInwANE+7vw+YFJzAZzPQaE0t0OzV8MBkqc8SgU5vBNxwSRpy3eUYmBqD1UVFXbRWwKbsKGHhtAhpv+6hy9vFSZHIZFhd+0yW51ai0omMfgMZbSWKfMPxDvZj2r/6k7S/Ey09NUv9w/vzgAHmp5Xb711Y650JLSEicGZJYlpCQcE/qWvj5FlFwpw2EujL3Y9W+ohV050kw6D5Y94rrcSuegg2vw9TPoMPYszFr10R2Ez/VxfDZCNHFD6D/nXDNW+duHhItJrZzMNOfHQBASU41+1ccwa+wDQnaerGMBVLXixz5gDYQ3umcz9HLV023kTHsWpreuK6uysDB9dkcWJeJQW+m56g2ePmp+Xu+vZWcxluJl7+Ksrzaxgi1QikjtkswAybG4x8qcphDYnwJifFtPHZZvkOKE9BhQMRZukIJicsXqcDvMsditlC5IZOirw9RtuwkFoOp6Z0kLg8MtbDwTqszhSehrFDDHX/BE6miQE+u8OB4YRG5zL/dJs5xrtn7nVUoA+z8HMqzz/08JFpM3sly5r+2k7+XVbC87F9srpht3bj7S/jxevhkMOz84rzML7p9oN2yXClj59I0aisNGHUmdq84xe7l6XZjIuL9mf3GUKcos8loIf1AMcv/d9AuWt1AYValUxpGYu8wYs6RhZyExOWEJJYvcyrXZlC+PJ26Y6VUbcymdIGzeb7EZYjFAj/d1HQxXgP+0RDe2bpsqAPvUBFtbkCmsN9HXyVEsyO1ZSJCeLZwaS1/zu3mJZqgulxHWUGNXVOOwxuz7RpwHKiZiN4rFnNUb6irT0ewmDGv+Pe5ni4gIuCDr0vE21+Nf6iWQZMTnFt7Oxg7GPQmPv/nRspduGgAVJbo2PTLcaf1fsFaJ5eI7qPanNH8JSQkXCOJ5csMQ2ENhrxqLGYL1Xvyqfgrw257zZFiSuYfp3RhCsbi8xD1k7gwqMyDtA3NHx/awfp674/wXg/48x9CEAOEJMGN34kCvwaie4NvpHXZqIefpsMb7eC1WNHy+mzQ+xbwtXlUrdS6Fu0S5429qzP49qnN/PjcNha/vw9TvUBWqu1vuMwo+TztfU5mhdivNxopL3ROUTgX9Bnbjtv+O4xbXx5C1yti8PKzz1fuNjwGpUZch8ZXRUlOdZNd+lJ2FWA22XeTCwz3ZvStndD4KFFpFQyakiBFlSUkzhJSzvJlROkfJ6iur8DWJAWiO1HmPEhvpma36HVfe7SEyIf6IK8vTrGYLRiLazGV6ZD7qFBHt0KzCIkLE42vSK1wbN7hiFwJbQbApPdExHbl07DtY+dxxSmQthFm/iZs5ryDhUOF3EY87/oSji8Xr421sOheSBor5rL/Z9j0tjjfmBegw7jTvzbfcPCLhKr8+nPVwap/w6xFp39MiVajukzHloUnGoP9WUdLSd6SQ7cRbeh7dTsyjhRTUWQfhd1dOoHY4C1o5EIg76q6gZT399NnbFsS+4Q72badLQ5tzCZlZz7e/mqGXN8ev2AtKq3SruiuKKuKW18aTEVxLXVVBpZ+1LRntMVswWyykJ9WxtHteWi0SvqMb0enwVF0Ghx1Ni9JQkICSSxfFpj1JirWZDQKZQBdSlnT+1Xoqdqag7nWhCJYQ82+QgwZVr9T734RBN/QwcMRJC4KTqyBlNUQ2BYG3AUKpXCK0Pi5t4ZrYMiDQryaDPDTjZCyyv3Y8kxof6X4cUWDeG3AWCcerRcdF8LZUh9Z++VWeGAnBLVr9iXakbrO+Vwlzv64EucHfZ3RKStGVyt8sn2DtEz/90AObcxiywJr18UiYzy/FP0fUeojVJrCyTV0gepa1v94jD2rMpj2VL+zLphP7C5gw0/HGpeLs6u45oEeGOrsPb4NOhPe/mq8/dXo64x4+ansHSxkuMwKWvNdMid2FzRuSz9YxPR/D0CukB4QS0icbSSxfIljMZkp+uIgehuR2xIqVme43VazKx/fQVGo2/i5HSNxgXN0Gfx8M43fwDl7hQ/ywjua3rftEBj2iHi9f55noQwiSuyJTpNgy4dgrhcObQeLXOiT661CGcCkE5HqlojljO2w5GEoTbdvpd1A2SkoShGWdxLnnroKOPgrWCwEdL2emA6BZB8vA4RTRPu+1hYkKo2CrsNi7MQyQKU5nMo651YlFYW1HNyQRUi0L+Ht/PANsm9yc3xHHruWpSOTyxh4bQIJvcJO6xJyHJ7UlebV8MOz25zG+QVr0dUa0XgpUWuV3Ph0f1Z+cZiS7Cp8gjREJQZy5O8cp/1O7CpwOv5nD23Ey09N+77h9L8mDrVW+kqXkDgbSH9ZlzAWs4WyJWmnLZRl3kosNUaPYywGs8ftEucZfY3Ix/WLsqY85B+G4hMiZ/jQAuzCWId/B41/08e99kPoc6t1ua7CeYw2UAhetQ8kjobeMz0fs01fuG2ZSNMwGaDndJDJxDzlKquIVvtBeFfrfjl7RRqFrhIG3Clykh1/B/NuajovuTxLEsvnA30NfH015B8CQL79Uybe+RdHdlWhrzPSvm84AWH2HenUXkqG3tCezb+dAEDro6Su2v1n1Y4/08Ai2k6Pu6Mr8T2FIC7MrOSvb5Ibc4ZXfnGIm58f6HS+BixmC7mpZQBEJgYitymwC4l25/5iT/KWXDKSSxg8NQGzEdp0CuL6x/s2bjebzChUclJ3F1BT4TkNymQwU1VSx77VGeSfLGfqY32QyaTW0BISrY0kli8xLCYLZr2Jqo1ZVG3JwaJrgRWcUibyTk2At0KY5nsaLwN1WymqfEFReExEeH0jQe0NC+4Q7aZj+sEtC+DYMvjjfhGpVfs6R3u9QyC0vedzdJlqL5RBeCtvessqSKN7w23LQeUlIsNHFkNFtkjbUAnPWLJ2ifkaa2HnV4AZ+t4GZRkid3n3V9BzBkz9H0z/Ef5+V6SIjHoG/OvzNOvK4fvroLZELP9xv2g8MuZFa5vsqvzmFfAteQjmrgI/yaf2bFJXbWDDvGMUZ1URmRjAFX0yUdULZQCKU1BmrKfHqCkej9NrTFtiuwRTmldNTPtAju3IpyC9gsBIbypK6ji2JQ8QfsUNXe9MBjPLPz3INff1JLydH4c3ZtsV15mNFkpza1yKZbPZwvJPDpB+UKQmte0azDX398RkNJN5pASfQA29xsRyYH0WZqPngr3qUh1/fZUMiMj5dY/3JThKiG25Qs7wmzowcFI8v7y806kltjtyU8spK6ghKKJ5ol1CQqL5SGL5IsFcY6BsyUkMBTVoEgIIGBeHzCFXrXp/AaXzj0MTH9S2yH1UmBs8PI0WVG18MeTVQI0JM00IbZXcaQ4S55GcfSJCZ6h3AbCNxmbvgjX/geMrrSkN+iohNmP6QvZu0c3uus8gbhgcXyFELggHC9s0CO9gMJuE0LUYQaYU3fyC4kUBXuwAGPuKOHbmdvh+qnX/jK1w6++w62uRFuF4O7b8Cfvl/fNEK+MO41wX9ZWmW4VyA9v/J34XY1+GsA5iHr4RznnKro61/Am48VvP4yTOiHU/HOXk3kJApBIoa9VcYREPERooK5cTYLY4WaPZUpJTzZ/v76e6TIeXn4pJD/ai15i2jdt7jW6LyWhm2ccH7CK0FjMs+XA/So0Co0MwQalRENLGuXC5LL+GdT8kk5Ni7ZaXcbiEk/sK2b08naJM4foS3zMUlUaBzuj5iZwtuhojK784RG2lAd9ADaNndSa0jS8abxXXP9mXA2syOXW4mOJsDx0z69n3VyajZp77hiwSEpc6kli+gDHkVWMoqKF6dz769IrGKLEhqwpjcR0BV8dRuuAEFp0R7/4RlC8+6dEuVtXGB0N2td0Ys0PxibGgBozOqRV1Jgtahf0Xlzo+4PQvTqL1KDkJ2XtE9NZgY5dldvAq3vWlve8xgEIFd64VXe20/mLZYhHHa8Di8H7IPwzfTYb0TdZ1toL66FLxA0JA2+6fulYI2b9eoNnexp4alwS2c91ZMHMbfDkGVD7WHGWlFqJ6QuKVIsq9x4UoLjvleS7pm8WYtoMhOL5585cAwGKxUFdloPCUfcrOoX0WjvAbXbTLucLvS07UDWXVdz7E7TvI1fd0t0t1sGXzbymN3e5qKw1s/Pk41z9hTWfwD9Wi1irpOyGOTT87+xQ7CuWIeH+GXCccLGzR1xlZ9H97G89lS25KWaNQBkjb7+xL3uCW6PhnZEtJvRCurdCz9OP9zH51KABevioKMiqbJZQBKoubF4WWkJBoGZJYvgCxGEyULU+neotzkUcDdYeLqTtaAvWG9+V/eK7mVwRrCbmlC0VfHRaCuAEHw3x1rB+6tHJw+GDXKmQYLRaUDeEfGfgPlwzwzzub3oY1L9Fs4amvsgpbtS8MfkAIY59Q8Kn3qjUbRf6vO9TeQvTa4k4JlKY57OsDX09wXWTXgH+MELMg0jnaDnY/1itQ2NF9O1G4Zzhiex5jnTjeyCfFcsIoWP0clNsUsSZ5sKTb+Basfan+OnxhzhJxPIkmqanQ8+cH+yjKrMIxpdZitmBCwcGaiZysG0i1WeQTpx8oYsuCEyhVcqKSAmnX1d5L2bGrna5GLBdmVrLs4wNUleoIb+fHNff3JP1AEZlHHJ5AODDuzm5OQhlEVNmVUA5v50dwTNMpD/0mxNFpcBRp+4o4ujWXoqwqu+1KtRyj3vr3U1WiIz+tnPB2/uSmlpN1VPIAl5A430jP0C8wdKcqyHl1u0eh3IhjZyhXKGT4Do0h6on+KAO1+F0R43KYKsYXn0FRhMzqQvCNHVG4+NJQB2pRBGmQ+6vxG9MObWJg0+eXOHtU5sPal2lx97kBd8GkD0RO8fIn4fNR8F5P2P6Z2K5QQY8breNlCojqDRHdRc5x7MDTm6/GH+JHeBbKIR0gOBGUXqLY7oZvrLnH7ojtDxHdmjeHBt/oynzQlcOY52D0v6HrdTDuVRjxpPt9N71tfa2vgm2fNO+clzlGvYkl9UIZrA0UlWrnr58GodzA/jWZ7F5xiiUf7OfYtly7bZ2HRtsvDxHLa75NpqpUiNuCU5VsXZTKiBkdUKjszydXWlV7zzGx+AVrqa3Ss/a7ZBa/t5eD67MAYVenUNor/C5Do5j6aB86DIgkvJ21biO2S7DTzUDbLiH4h3jR88pYht3oXECa1M85R/63N3az7JOm/ZcdMZulgmsJibOBFFm+wChZcBxLbQuK8pog6LokfPpGYLFYMORUo4r2xatnKLWOjwvNFgInJiBTyvHuFY53r3D0WZVUbc4BhQyvbqEU/5DcmKJRufoUcq0Cv6GuxbfEWcaoE0LZ07Ndd2z/n0hd6DoFCg6LdRYzrHhKOEmovWHKJyKie2oLHF4IuXsBGdSUQGU2bs1gA9uKqLRjQV1kT2H1dnyl57n5RUD6RvG6KAVW/kvkHlcXQWR3a2qJtj4FaOcXsPcHIX6bg8oHKnLgs1FQJQrA6DQRbvrBmjRbmi6i7aFJ4pwNyB0+LuXnptHFxc6Kzw9RmFnltN42mtpAUKQ3pXmuO+9tXZRK+34RKJRC9HYbHoNvoIb89ApCY31J7C1s4xyjwNVlOgLCvJnySG/2rDhFYUYlWj8Vfca2w9tPjdpLSVh9ofLi96yiPjO5FKVaQechUbTtGmKXYlGYWdXYTXDqY33IOlqKQimnTccgUnbns2VBKmaTmX4T4ohMsKaruUopads1hLC2fhzdlkdBujVFJf1gMR0GRpLQK4yT+wpd/k4cqa3Qk32slJiOUic/CYnWRBLLFxDmOiOmwma0mFbLwcUXjSvK/jiBV+8wSn8+Ru2B+g97rcJpnCG3Gn1WJXJfNdW785CrFPgOiiL4po4AVKzLdMplrliTIYnl88WC2yH5z5btY9uRr64M0jbZb7eYhIcx3iBXQL/bYOObIi1DDKgXyvWvXVFXATfPhz8fhMKj1vV5+8WPJ2QKyDtkv+7EWjjWR7zWBkFdvQgf8qAQ0PvneT6mIzu/AMxWoQxwdIlIDTHpRXHirq9EyoZMDtd+YLWiG/uSKEq0mMEnHIY93LJzX4YYDSZOHWyisY0NUe0Dad83nF3LTzm1gK4u07NjSRqDpyQ2rovrEUpcj1C7cYm9wzi8yfpkrsE3OTI+AIVSTlWpjqpSHau+OExkgj/dR7UhrK0fGYeL7PKPAXKOl9JpcCRmh6d4ZflWQa9UKYjrbp1Dh/6RdOgfiSsiEwNo3zdcNBcBYjoEEt8zFIVSjlKtYG26fT63UW9m/F3dyDlRxoafjrm9kWigJKeGxe/tY+pjfexEuoSExJkhieULiOrtec4axFUAz0UBnqZ9IPrMSierOIvBTPX2PKtQBqhzHbmu/DubukPWL7aa/YWE398LuVqBwtdFFE3y8zw/mIzWAroW7efg2RrQRkRkDfUCIbQDKDT2Y6rsGyE0SV0Z/DQN7t0CJ9eJeR5b5nps92kQkggb/isEqMVkFcONc7bJQ7bdtuUD18dMGivSPQ4vsD7vt8VYC6ecG0VYTm0Rb+fsXTYrzbDuVatY7jsH2g0V1nbRvYUriIRHFEo5ai8l+trmuUMc+TuHDgMinIRyA4XN8IwfPqMjgREiQh3TMbBRuFrMlkaR2kDeyQryTh5h47zj+AZpnI5lNlv44uGN6B0+M083ciuTyRh7R1d6jI7FbDITlRjQ2IEvbb9z9DggTMvevzIw6kxNCmXbOR/dmiuJZQmJVkQSyxcQFhciGEAZ7oWxwCbibBYFe6Z6/01VG19CZ3dBn1tN0RcHsdhEnWUqBeV/pDoe0glNxyA7oQxgzK/BkFWFJiEA774R1OwvRNfQpUoGgRPiMeuMlC9JQ59bhaatPwET4pEppVT4s4pCKQrlHIvwvENFLq2rQjdHVN4w8l9wcL5wyQDRVnrpI8LXuAG/SNGmuiXUlUHWjvqUDh/3Yrk8B7yCTi+VxBVeIXDjd4AMDv3mflxwvBDmufsA2F11Pcm1o5kW8jgaeROCJDRJalzSAmQyGRHx/k0W19lidiOUASLimm6YI5fL7CzkGucilwnveBfH19UYG1tqN6BUy0nZmW93zxUU5U2bTsEMmpzQ5DzcIZPJiEp0FrKurvv3t/e6PY5PoAaD3oi+xjn4cXRbHt1HtSEk2tkGT0JCouVIYvkCwrt3OBWrHayrLIDCOYJrNpsJntkJLODVORiZSoGmrT+RT/Sn7lgJxlIdutQy9GkuOqs1oBDn9Bkcjf5kObpjzlXXch/xFpHJZYTd0R1DQQ2GghpU4d6owr0p/vkotfX5dIasKiGiJyU6HUeiFbFYQBvsLJZNeuGRfOIv6zqFpj61woaksTD+dRHV/et5+23pf9sv974F1r9mXe5+E2AWXfY8FRbmHYKuU6HLFOgxHQ787DzGWAOHFro/RktQqOGW30TDE7NJ2MS5umnQBoj0idAk1v33Z/JyLJQYhbDK0XchXrvLfvzwx1pnfpcxao1z2pcn0g8U4eWnorbS6nYREO5FXI9Q+l0Td0ZzCYn2cXKjaKS+w5+pviupq5zqhJ5hDJpydj7feo6ObTJlpaEoMioxgKyjpS4fnoBovjL/tV1MeqCnlL8sIdEKSCHACwhlsBa1i0dnxlznaJfcIsO7exjePcKQqaxfRgpfNd49w5EBRsfOT0qZ9X9cBkFTktC0DaDw4/2UL01zejf4jWyDyrEblExEnOtSSqnelU+dQ8RId5qttSVawO/3QLkLP2CzUeTYth0iWkInjoa71okosi0dxguhDCL1whbbZUMtbHrHfntYEvS/Ayeh7OjfvPcH8a9MBoPudZ6rTCHaVNc4+9K6PKbaB276Ea54FOKH24+TK0U+8+rnRIpEdaF9y261j8ijvuEruHcrRHYDpYasmqRGoQyQahxln4bScYI4zidD4KPBsOVD93OVcItfqGc3k8gEf3wC1Y3LRr3ZTiiDKIIbdkMSijNsgqR1lU5Wj9pLyfWP92XcnV1dbpfJcMqPbk2CIr2bzGwLjvbFP9SLvJMVboVyAyaDmb9/c/aXlpCQaDlSZPkCwlhShz6tvOmBgN8oe49jU5WeuqOlyLUKag4VNUZ77fYZ3gbvXuFU78hDn11J7dES6o4UW3WPWTQaUQZp8B0Wg9rhEZ6hsIaCD/d5bKEtk8uoPVqCNikIi9GEXCO9xVqV4lTXUVoQEVP/aJi73H799B/h93tFp7seN4qW0g2Me0U4V2Rsg4guMPkj0FWJ1s/pfztHpWtKwctFrm5YR9EFsIGqfCEuhzwAq561H6vUQOwgSNvg+Vrb9Id2Q4TzR59bISgOOk8Es1lExI8tB5MBytKhOl/8/DRDeDvb2tPpq4Vg7mDf2jupfwS7l1tvOiImzoHuM0S7cK9g0Y57we3WHVY9AwExImIu0SxqKvQcWJPlcltUUgAd+kfSaXAki97ZS3WZTU69Q62Gt7/aaf/TQePl/vOo34Q4wtr6ERDu5XL7VXO7ntU84OKs6iYFcElOlcuIt/vxNejrjKi10uewhMSZIP0FXUCYqvTNssz1GRyF7yDhKWosraN8ZTp1h4qtOc8u7ImU4d4EjI1Dn1lJ1ZYccJMXqM+oQH8K5F5KJ7Fce6DIo1AG0J+qoPibwyJKbQZtlxBCbu4k5TG3FjIXv8fOk6H/7ZAwwnlb1i4RHQ5sC1e/IezibNEGCDFtyx8PilxmRxQa6Ha9aCF95XPWZig9ZwgB/t21NqkPFiEud30F5Q5iKSgRwrs4i2WZQuQSN5xr2EPiend8LgrtRjwp0itWPSMKEwfcKVpyl6Vbj1FwGNd/RM7rBk1OJCDMi6KsKqIShQsDALnh4ubC8UYBhKWcJJabTW2V3nUOsgz6Xx1PbBdx4+UY8U3sHcapwyUYdSZiOwfR68rYVplP/4nxpB8qbky1sKXh/1+tVdJ5SCTJW6yOKT4BahJ6hznt05oc3Z7b5BhHoezlpyIkRkSbj/zt7M1vNlkoy68hvF3Tud4SEhLukcTyBYQq0gdlqBfGovpiPrkMVTs/DA55x15dRCcrs95E4WcHMJU6fKm7+HIyFtRQ8L/9qOP83AploLHRSdXmHDTxAXh1sz52lHuIyji5dtR/ptcdKaZqWy5+wySLuTOmuhgWP2Cfh6wNAF2F6yK8guR6S7T6sb/tFqI5po/7c5ScdI5cawNE6kXnSaK7nq5KpEP0u11Edn3rRcSoZ2D1vx2O56K4tN8c6HET5B2EU3+DTwSMf1V01Cs8CsUpovGJxQyfjrB6K6dtAq0fFB4TyxlboNsNDgd38d5uO9htF8CGRhaNVOTCgjutot2RYCkfv0VYQOOtRFcjiudkchkxHYPoPiKmUSibTWYyHIqL1V5K7njnCgx1JrQ+rednHRLjy8wXBrH4g32U2bhLxHUP4e/5KYRE+9D36jiG3diBo9vyGmtPq8v17F11in4Tzl6L84zDTRdBymT2Ji/6OiPDp3cgP63cpVhWquT4BjXR1EdCQqJJJLF8ASFXKwi7uweVm7Kw6M1oOwZTtsRebHh1D0XTPhAQAthJKNcj0yqwONgd6dMr0Gc65BTLQRXti8JfI1IybDDWm/tb6j+dffpHUnukuNERo8GRQ+6rwlxln2Nod5zC5lkeSTTBj9MgZ7f9urpyYdF2cp1INWiIeupr4Ifr7aOjFhPs/BzW5AoXijEviEYhtqx/w9liTq6CAXeL1Ixjy0SO8DXvQN/Z9uM6XSPyhj09HrnicRh4t3h921KRF62yeey9Z7vwTt43T4h0s837qjIHHFPiqwtg5NOiqFHlA2nr7c8f3hVmLxG+0a7Y8z0UHBH+yp0nww83uBfKAH89J24aGlqDS7hFV2Ng8fv7rEJZBmPndiUyMYDti1NJ3pJLp8GRtOvm/Lssy69BLpO1qlBuwC9Ey8wXBlFXraeuysix7XnsWpYOwMm9haTsKsAnUONk0rJ9cRoyuYy+4+NafU4AcheF3I70Ht+OPTapQyaDhWPb86gp1zuN9QvWMnx6h1ZLYZGQuJyRxPIFhsJPTeAEYUtU9P0RTMXWIj1luDfBN3dCVl8FovBXN6Y72OI7PIaAsXEU/ZiMLtkhWmGyoIrywVhSJ1IqzMLFQhYnR+arwmIremVQuTGL8lWnkMnAf2wcoXO7YSqtQ6ZRoPBVYyippfTPVPTJzk4aDeiamYct0QT1VmduObkB2o8RjTNObYGKbOcx+36yP979O0R7axBFeUeXOO9TUwS/zISsnWLZbBQWc52uAR+bgqeQRBj5lL17hiNdrrVfthXKhxbCmhc9XqKTy8WpLXD9V5CyEtLWIR5x1D/maDcUZi0WVnuuWPuyaLoCsO1jGPUsFBxyPbaBunLh4TzgLs/jJCjOqbYTcRYL1FbqWPze3kbP4PSDRfQaE+uUq5t7opwtC08w9IazZ9On9VGj9VGTfdz+s6ssv8au6Ygt2/44SWKfcALDvV1uPxO6j4xh55L0xuWwdr6ERPtybHseKo2Cwde1J6lvOHtXnLL7fSmUcowOtqNKlZxZrw5p9TlKSFyuSGL5AsYxWmsxmBqFMoDCX4MyxAujTdc/ZahXo9gOubkTOf/e4nRcdRs/NImBVP1tFVP69AoUIVpMNucsX5EO9bl9FqB86Un0mRUEXJuIXKukdHEq1VucH/05Yiyqw1xjQO4ttQc+M5pIaA9NguVPuc43BtFy2raLXslJeDkSYvvDkH/CHw+4P4djO2mzEUpP2YtlEGK587VwbKkQo7aEd4WIbs7H3v2NiAxXNP1ecpqf2Sii5Y3FhRZABvdth/BOng914Ff75f0/uR7nyNFlklhuBn7BWuQKmV33O5VWad9cw4JbK7fUPYVnVSw34B/qRe6JZt7QW2iMlLc2AyYmoPVVc3JvAYHh3gy+rj0aLyWjb+2MzKYOZegNSWz+LQWLBVRaBTv+TEOtVdh5SPce6+wzLSEhcfpIVVcXKBajGVOl/aM1r+7OBSaOAlSmtH6oylUKZN4O90NKOb5XxKDwc3g0JwNTqYPVnIsimJK9heS+tI3s5zY3SygDYLZQsjCleWMl3KPxc16n9gVtIPSZBQPvcd9Suu9tMOge5/UWI2RshQ2v4VGMx/Z3XufuXBFdoO1Q4X1sS8FhWPGU/bo938Gf/xStu7MdUkxkLlInzA4pEhp/F536LCJq/ussmH+bcwvtBnwc/p5c+TLLXdzgnVznXLQo4YRfsJYxc7rg5adCrVUwYFI8iX3CUTvUPrTrGuIyVaCypI5ti5puqHSm9L8mHi+/5t3Ih7X1IzTm7DX66DGyDVMe7sPImZ0anTtkDgXbPa+M5dZXhtBpSCSG+lQ7fZ2pUSgr1XI6DHTdbltCQuL0kMTyBYoutayxQ18DGhcVzX4j21iblsjBb5R9RCH4po7I1EJ0KII0hD/YC1W4N75Do9F2qrcAayjOa8KRSG+2sKHKyNZqk120qDkYm9mqVcIDjkJRoRH5xWaDKLrTVUKMg6gNToSnc2DSu8Iezh0FyYg3Qj0afxFt7jIFrn4Thj7kvI/StcUWFbnw83Tn3GeAQwvsl20bqDjiKnc4rLP9sq4Ckq5yHrfoXjjyBxxeCN9OhIo84Qry4zSRV22oE78TvygxPiBW+Co7YnaTi7/7W/fzvswpzq5i/uu7+PZfm8lPr+C2N4Zx57sj6H9NPCqNgkFTEhr9hBUqORXFtYy7sxv9JsQ5idbdK045pUm0FlWlOtb/eJTF7+6183VuaPxhS0LvMAZPTWTKw71RqM7/16ZfsNbtZ7BRbyZ5c9POGhISEs1HSsO4UHFh/+bq1sarcwgR/+iNPqcaVYS3k92bV8dgop4diLnGiMJf3RilkCnlhM7pillnIvf17VhqPVvCAdSYLCRq5PgrZFSaLAQoneeoCNaKiLhDVNpVsxWJFmCxOIvPhuI9k16IwqJj9R32bChJhdwD0G4w7Hfjz9xwDIDgBOF4ceXz1miyxQI1JdBnNuypF4nthkK361wfK3u3yO11hTbQfjkozv2cHInuLdw3bNH4QZiLdAvb6qzaUiGQD/4illNWQXURTPkYJrwFv90u3ERO/AW+kVCVZz22Y5fEBhRSSpErLBYLSz7aT1WJeG/uX5OJf6gXPWx84Q9vzGl8GGAymDm4Lpvj2/O58en+RMT7s/SjA3bHrC53XcR8JhgNJhb93x7KC2qdtvkEaugzrh0b5h3DbLTQeWgUo27pZJcCd77JSSnz2O1v35oMEvuESZZxEhKthCSWL1A0iYFoOwZRV9+CWpMUiLaDi2YQgCrCB1WED4bCGqq25KAIUOPV1cbyTa1ArnbtBiDXKFDH+qOzid6o4/yRKeWNrhcN+ChkBNpGVeSgDPVGFe2D3/AY1NHWNIHqffmULUrFYrSg7RhE0JT2Lf0VSNgik4lUih2f1i/LcSrXzz8M+c8577v4AZj1p3CxcOUdbEv7q2DCf63Lpafg66tFsaDKGya8CVG9ILqP+8I5bQDOXoL1VGaLZidxw8TyiCdFo5WU1aKhSlWecMhwRUgSHHTIM9ZViuK8XjNh34+u9wPRLdCWg/OFVd3Kf4Gp/glOabrwjG4/RkTWf57h+ljeodBvrvtzXaaYDGY2zDvWKJQbKMmxz0muqXR+4qCrMXJyXyGdBkfhE6ihut6JR+ujIiap9ds1lxfUuhTKAFHtA+kyNJqOgyIxmyyo3Hx2ni8sFgsrPjvoMXfabLSwe3k6V9/T4xzOTELi0kUSyxcoMrmMkNldhZOEBTTxAcg8WAvps6so/HQ/lnrTet8h0QRe20xPWIecT2WIF8HTOpD7xg47azon6WMW9nUWkxllqDeGen9oVagXPr0i8OkV0bzzSzSPq98QFmdlGVB0XFisNYfiE/C/ofZd7dwR2d1++Y8HrK4ahhpY+Qzcvlq4SGj9hWi0dbQoPAbzZ+M2/9lQC3+9CHesFstqH/umKHmHhGOH2kfkPK9/TaRjdJwgotmOYhlEpPiONUIQFxxxfV6lQ06sSQ8L7xQ3ELYYddC93rs5diCc2my/3SsYbl/lXNgowY4lJ0ne4vz4PzzOPrrZoX8E+9c4+4JrfVVofVRc93gf9q/JxGKGHqPa4BOocRp7pnj7q1Go5HbNSRRKGVGJgQyfLlq+KxRyFBeWTgbETYljO3BX5J0spyirktA2LmodJCQkWoTMYmmqwWbrU1FRQUBAAOXl5fj7S4+JWoPS31Oo3m7tOIUMYl4a2qzOeY6iWBXlI4oAAzVUb87BWFqHukMQpfsLUbvxddZ0DEJXHwX37hdB8A3iC8dQUAMWC8pw7wvqMeZFT+o6+H5K6x1PoYaB98LY/9ivf7e7EOe2KL3BWJ+D3m4YzP4T5PXvs99uh0O/eT5XVC+4u4lW1w2YzSJvWKkRjhyfDremSTTORyNys698Dja/D/mHQF/lHHnX+IscZ1va9Lda4snkIk/7qhfEcnURrHxauIb4hEHcFSL1xE8qnnIk90QZSz8+4DLaOf3fAwiJ8aWiuJatv6dSW6nHL1hLeWFtowtFQq8wxt3ZFbni3OUDp+4tYN0PR9FV2885qV8EY+/oes7mcTr88e5eso42ncut8VYy/d8DWrUxifT9LXE5IkWWLwIsBhMWkwW51vV/V+2hIgx5DlFDhcx13rMLNPEB1JQWNC4b8qop/fU4yCBwSnv82vhR9PUh1FUGcVwZYLS5x5LRKJQBanbl4907nNp9hVTvFMLGq3sowTM6OVV2S5wmcVeIn/RNYlmuFDZqp0O364W7g6FGNDM5tgzSNkJoB4gfAXu/tx9vtCnWPPW3aFtdkCzEafKfns8lU8DQfzZ/bnI5yOsji34RcOda2P4/OPibaFICIhpccEREwR89Cpnb4ZuJzsfSVTj7NA9+AI6vFLZxFjNs/j8R1R7xuIgeX/dZ8+d6mVJRVMsf7+7FZHSOu8hkYNCbMJvM/Pn+fjv/4mvu70HkPQEYDabz0mUusXc4AWHe/PLyDrv1Kbvy6TjIdbOUC4Wr7+nO7uXpHFiX5dQC2xZdjZG8kxW07yt18ZOQOBMksXyBU7UlR3TxM4N33wiCbkiyi9BW/HWKir8cIn9yCLw20aMwrdqeS9WWHOQaBf5j45B7KTHkVmMs11kboVigcm0GikCt1fPZZEHTIQhVqBdVW3NAIcenbwTV2+0fv+qzKhuFMkDtwSLq+pTg1fnC/QK6qFAo4dbfRa6vxSQ8lDe/C7u+bPmxGhwqMrdD7n7IshEPfW8TecwnVrvZWS4alug9pHjIlXD9l6LoL6onRPdq+RwbCIiBsS9Bjxvhf1dgl+5RUyQKEY8uxW0aiEJtL5YbUlpsOfCzEMsSzSI3tcylUAaR4bXsk4Nc+89eTo0+clLKiOseCpy/Ykm/YA1KtdxJcFYUucmbv0BQa5UMntoek9HiMqXFFv9QSShLSJwpkli+gDGW1FH2Z2rj937N7ny0HYPw7mH1h61yEKmqWD9CZnRCGez+A7LuRBllv59oXC769jCRD/dBGexF0beH7boGIpNhrrXPjzPXGAi8thsBE+JBLsOiN6FLLcNY/wWjDPNCGepsK2bxEAGROA0UKuhkY3d2zdui0YbejYNDc3D0Tk5eDHdvhP9z9VhaLgr10je6PpZMLgrvhj/u3Fb7TMjaXe/X7CDQAtqIZijHlrnf1zENoyAZvB1u4ByXJTzSVAFcbYWe2nI9Wl8VdTZNj4KjfFp0npwTZeSnVRAa60tsJ9fFzi1F460iIi7AyZ4uINyNLeIFxtDr26PxVrJ7eXrjDUu7bsHknBC1LgOvTZAcMSQkWgFJLF/AmKsNTnpAl1aOuq0fykAhhuUaJWZbj9BAjUehDGBwqE7HYKbgk/34DW+Duo0vdSfLQGcGuYyAq+MxlekoX57WONy7pxDrDfnQMq2S8Pt6Ur1HpHL49AlHppKjivLBkCsijspQL7QdWr+qXcIGmUy0oD7gwiJOpnDwLZaJKGtUD2vOLoiUBlv8ooSVXHhX0VTElqmfCCcLd2J51DMw/LHTuhS3FKfCt5NcFCvKhJPFkoc97x/ZA/JsrMnihkLbwVCYLKLMflHipkOi2Wh8PUeG5QoZAeFeXHNfD9b/eJTaKgMdB0bSaXBUs89xfEceq78+0vh5OHx6B7qPbON5p2aQe6LMSSjL5DLC214cAlMml9H/mnh6jo6lKKsKn0A1AWGt34pbQuJyRxLLFygWswWLxSJ8i22ak1RvzaV6Rx4hMzrh1S2UwCmJFH+fjEVnQhGgwX9cnMfj6nOr0ec6t5c1VxooXyoEsbqdP74j22DIrqJibQYytQL/se3QZ1dRd7SE8qVp6DMqCZ7eqdGhQ+6twm9YjN0xw+7pQc3eAjBZ8O4djtxLeruddZRunAOcGnxYhJPFqH/BL7eKvGNHNH4w8G4hwse8AD9Ns99ekQN9Z4u0h4LDIpI88l8QFA+BsdB2UGtckT1pG924eljg7/c979t2CEz7RnguV2QLh43et4htD+6F6gJRyCd5KDcbg87Eqi8Ou92u0igYdUsn/EO98A/1Yvq/Bzb72Hknyzn8dw4qtYK8k2V2gYMD67LciuX0g0VUFtcR0yGI4Gj30WuTyUzGkRKn9QOvjUfbxA3AhYbaS0l0UuD5noaExCWLpF4uQCwGM0VfH0J3UlSKq9r6Yiysw1JbX8BlslC25CRe3ULRtg8i6qkBmMp11J0oo3JtBqooX3yHRjvlLOtzqyn8eB8WF22s7cadqkCXWkb139Z21oaCGjCYGrv81R4sojoxF99B0W6PI9coPW6XOAtoWxAR2/sdXP06DHvYtVjWVYpW1NpA6DxJdPM7ssi6fc2Lwr5u1mKoyhfpC4GxZ3gBTeBo9WaL2Y2HtEwh/JwH3w8aX7juU+cxCqXweZZoETkpZdSUu+jUCMT1CGXcHV1RNpGmYTFb2PtXBnmp5YS08aXf1XGU5dfw+zt7MNenFsidbDNd50hvX3ySXcvSAdEd8Np/9iK6faDdmKyjJaz68jC1lQan48pVMrqNOPOItYSExKWFJJYvQKr35jcKZQBDhotIcK2R3Nd3IFPJCZyUiD67koqVp+q3FmCq1BE4IQFDYQ0yuQxliBe1BwqbFMqNc9iaY79C59zhz1Th+ktS4jzS+VrY9j/3bZpt0VfDqn/DyKeEIK4rcx5jMcOe76DLtSIqe3K9vWVd0XHhljHiiVaZvkeKTgif55ai9oaRT7b+fCRQaV0LYaVaTqf6ph5NsXNZOjuXiKdaafuL2LPiFDI5jUIZcDpOWX4tRZmVhMYKD+Hs46Xoa43ssyl2NhnM7F2dYSeWLWYLy/53EEOdyeVxA0K80EhPwCQkJBw4/03uJZxoTiGcRWfCVKbDWFhL0XeHqdlfaLe99nAxxfOOkv/2bvLe3EXpohPIvVvwJdB092tMpTrM+mYMlDh3rH/NXigrHfLXFQ7NOXZ+KRqJuBLKDZgNwqqtLAPCOztv3/O9ZzeM1uLI76BzbKPt8BHWYbxIpbBlxFP2yzn7hM3ckkdEh0KJ0ya6fSBdhjrnHhv1ZlZ8doj5r++irtrzjVvmEfu2zWaTBZOhaZG9a3k6pXnV/PHeXha9s5dlnxy0azICkL6/iG+f3oKx/nNKV2NsFMquKM2r4fCm7CbPLSEhcXkhieULEO/uocj9rDlzMofojcKxUttowehgyyRTK6i1EdDV23KFR3ILUHnI9wOo2VtA6fzjHsdInGNqHRoVaPwRxtgI/+CO19hvN9bCgjucjyOrf89pg+DkBlhwO3w8CErSoOfN9mPLM2DrR60yfZf89SK8HAmbHAvvZDTmBTXM+brP4aGDMPrfouDvlt9hyAPWMSUn4ZtrRDR815eilXedowCXaAqTwcyqLw7x6T/Wk3agyO24svwajm3Lc7sdwD/s9Jwnasr1/PTidrKSre95Vy22qkrqWP/TMTFvU9OBiGPbPc9XQkLi8kMSyxcgigANEQ/0JmBSAkHXJxF8cydQy7EABq0S/6vjnf/nbL4klOFe+PQNdzqusVuEXgUAACfkSURBVKjOaZ0nTFVNP8qvc6gklzjPOArZ2hIa3xz6auEEYRtttpihJNX5OBYTtBkAZr11f0MNfDsRaoqdx1e7F0xuqcyD9L9FZz5HSk4KH+X/hMLf7whRb6ilUfjL5MLFwnHOJ/4S7beHPwZT/wftR9uPSdskuvs1UJEtvKUlWsTuladI2VWAUd+M1stN3KMPm5ZEZELL3CfkChnlhbUuU5ddpbVXFgtby8zDLt67Dmh9Lq7iPgkJibOPlJx1gaII0OA3VLhL5H2wh20levKNFsBAzHfJDI72wZBT7fRlEfFQH1SRPphrDFRtyW100lBGeOPVI5TqbTl2wThPmF3lJMuwF+YhWkwVOkr/SMVUUoe2QxD+4+KkTn3ni4F3iUK17N0Q0dU5auxKGLsja4fzOrMRUlbar5MroetU8bosA7Z+LIRr/zshrIPrY6dtgnnThXBVqKHLVJH3HNpebF90n73FWyMWmPYdtBsMZZnw1Tj7tJNF90LsQNG8xBUBDsVbMrmwxpNoEeWFNU0PAoKifOg0yHN7cC9fNdc/0Y8TuwvYvCCFukoDPoEaug6PJiLOn5P7isg4UoxJb8YnWENknD8dB0Ux/7WdTsfyD/MiJMrHKdrdcaBIFclNdf0UQSYX943+YV4MvSGpWdcmISFx+SCJ5YuAvKxq8o0W/OQwwEeJr8WCIdt1jqiivluT3FtF+H09hXWbTIZPvwjkWiUhN3emclM2+uwqMJ5GkxAHca6K9SPv//Y0OnUYcquReSnxH3mWXREk3NN5ovgB2PSOsz9ya9JnDvS6GdoOFN3zPr9SWLAB7P0BHtzt2mXir+etEV6THg7+AikrRAOUoDiR7uGKgFhof6VwtfANh6H/sE/PMNaJqLStWLZYYNvHkLoOQhJh8IOiZbZcCeNfE+skWkTbLiEc3+7iiYANnYdGMWxaEmqt/deMxWKhvLAWlVqBT6DV6rB933Dau3giFp0UBDgLWI23ihqbG3qfQA03Pt0fuULGhnnHSNtXiFwhp+/V7egyLJqj23JJ3VfodByAxF5hDJ3WAW9/FXKF9MBVQkLCHkksXwQoI72hvJxe3gp8m8o7ttG/Cl81flfYR9K8uoUKgfuai6jhaVCzI89JQOuzKqncnI0hqwpVG198h0TbteiWOIfMnA+fDhetoAGUXiKloTVQecP4V6GuQqQ/lGdbhTKItI31r8O178OCOyH5TxFFHvoQFBx1Pl5dOXw+GiZ/JATxvh+t2yK7Q1Qv0Q1Q42td33UqbH5PRLxBuHqEdbI/7vb/wcqnxesTq0Xe9rP5IpwovS9Pi9A2vk2OkctlTkLZZDKz/H8HOXVQpEMMmBRP/2viT2sOPUa3Yduik43L/SbENTpZjJndBWZbxxZlVbL222S7nGa5QoZcLiMyMYDhMzri5edQ/CohISFRjySWLwI63dGdo6/uxMvUtPNEzcFCfPt6fuxZ9kcLHsUDMrUclHIsNUbnjS5yBo1FtdQdqs8N3FuAucpAQBPNUiTOEgExMPYlkZ4ArSeUFWoIbAcf9BNC3KR3nSy6/2fRvOTEauv5177o/rg1xTB/Dty7TUSkC5Kh3VAYdK+IEDu6YUR2h5t+hK0fioYsHcYLb2iVl7DEC00Sdne2pG0AuWfvXwnPNOfmN6ajc8fOlB35jUIZYMefaXQYEHFaXef6jo8jIMyboqxKIuMDiOsR6nZsUWaVU/Gf2WTBL1jL1Xd3Ry3ZxUlISHhA+oS4CFD6qZn68mDSXt8JlZ69jSvXZTYplo0O+YYylRxlpA+GzEqX4y16c2Nr6yaRgTHP/vjVe/IlsXw+Sf6z6TEqXzA4+3m7xaQXLaJtMbu4mTLprEK5uRjroCoXRj9rXZe5E36eAdWFEN0bZv4GPvXiqON48ZN7QESmG3KYT22G+7dDSHv740tpF2dMcLQP7bqFcOqQfcGcXCEjMiGAjoMiSeoX4bSfrtb5PaKvPX37SXepGwC1lXp2LkmjrtqAwY3FZXlhLTknyojr7l5oS0hISEjJWRcJCoWctnd0A5Xn/zJTUR2Fnx+gLrXM7RhNYqDdss/AKAInJoAHQWypcyGEAK8+4chsO3S5iDSby/VU7/Gc3yhxFpE1I4oakuC+O55cAQo3bbTPBt4hzqkUv98thDJAzl5Y+7Lzfqe22Bf7VebCgd/ALwpiB4EmQAjt6786e3O/TDixu4AMG2eJToMjGTYtiZkvDmLqo33oMtR1N8SEXmF2raQjE/wJjvFsUXk6mM0WFr+/j4MbsknZVUD6AfcuGJL7hYSERFNIkeWLCHWEDxEP9CL///Z4HKdLLUefcZiIh/qgDHH2MA2cmIBcq0CfXYW6jR/+Y9oiU8iJeLAX+e/vBVddt9zUAvoPb4MySEvlmgzXA+qp2pJD1eYckEHAVe3Qdgz2OF6iFbniETi6BHctggHQ+MENXwv3DJNO2MsZ660GzSbQ+or1ZxOfcGjTH0Y9Dd4O74+qAodlFzdfoe2d1y17xPp62CMw5vkzn+dlzt/zU9i/JtNuXX56JVfO7tLkvn7BWqb9qx8pO/NRqhV0GRaNopUL6kwmMyk78inKbPpJSc8xsUQmBLTq+SUkJC49pMjyRYYqwgefAZ7TLAAsBjOGXNeOGTKlnIDx8YTd3p2AcXHI6r+sZEo5mJvunNWAd59wVJE+aDsENflOMmRVYciuwpBVRdH3yRiLWyl3VqJpYvrAjd+J/N6Atrg0vo0fIVpa/7sAnisVtnO2+EaIwrgGQSt36AyYeKVzd0BXeIdAr5mieYhd9FgGN34LM36CyG7O+3Wd4rA81XlM+zGiEYk7/n4Xfp4pGqi46l4h4ZGclFJ+fG6rk1AGkX7RXPxDvOg7Po6eo2NR2TyVqqnQY9CdWUdQk8nMn+/tY823yU7b2vcPt5vngEnxDJNs4iQkJJqBFFm+CAm6Lglt1xAq12eiT6twPUgOyvCWFc2ULU1zGXxUhntjLKjPQ5aB35Vt0SYEoqmPyGja+RN4bSJli5pZOGg0Y8ivcRn1ljhLdLlW/ABkbBNd+fIOgFEH7YYIh4oG5HLofwdk76HxDTHgLhhwp3XMsRWiaFBXAT1ugms/FJZt2btB7Q2rnxPLMgVoAyBhJMQNE2JWXf++jB8h2nPXlYn17Ya4n//EdyG8i/CJThhltcZzpN/tsH+em4OYRYT96BJx3Vc84machCPV5TqWfHjArZhN7B3mcn1zMBlFa+z0A0XIFTJGzuxI5yGu0zhcYdCbUCjl6KoNbF98kuzjZc6DZDD2tq5UXFtLXmo5AeHeUkRZQkKi2Uhi+SLFq2Mw5cvceNEC3v0iUIa2TIyaqx06ccmE1VzQ9UnUHS3BWFSLJikITTsX3bZa8ihVBvrMSrSdgqXmJeeDtoPEjyd63Sw8jbN3i4h0+yvtt3ccD0+miRSNBmeJ0PbWVIhOE4UI1ga6t2fzi4BJ7zZvzgolDL6v6XHFqTh1znHFiTWi8C9jO3QcB/HDmzePy5TSvBqPUV/fIA0moxlFMwqB66oNGHQmfIM0yGQyjvydQ3p9ExGzycL6H48R3zOsyVxis8nM6q+PcGJXAUqVHKVGQZ2brqMKhRyZXEZAmPdpOW9ISEhc3khi+SJGHe2LMd91J62aHfnoUsqIfLx/swWpd+9w9KeskWq/0W0JuKqd2NbLdcV5A4acZjgpNGgYi3DtsBjMorBQ4sIk/grx4wl3FmwyGXg5W4edVXIPwB/30qRQBuEH/eut4vW2D2Hca80T45cpQZHeKDUKjG4E89rvjrJ/TSaTH+6Nl6/7dJwD67L4e34KFrOFtl1DmHBvd2odHH7MJgu6GqNbsVxdrkMul5G6t5ATu0Quu9Fgxmhw32Rp0FTpc0ZCQuL0kcTyRUzg5EQsRjO1B4tcbjeV6ij8/ADKAA1e3cPw6hri8Xi+g6JQ+KnQnapEFeWDT2/PAtkWs5uIjidqjxRLYlmi9dj3o+hZ7A7/aKgupiJiHDuS4zGaJ9PVexWxmv2w8b9CLJekwx/3Q/5BaDMArvvMudjwMsQnQEPvq2LZuTTd7b1IcXY1e1dlMOQ6F4WWCJH796/HG9PFMw4Xk7wll4Te4exdldEodmVy+O2NnYTHBRAc5UPvq9ri7a/GYrGw9rtkjm7NAyAwwvOTs/4T4/AP1RKZEEhgC1PSJCQkJGyRxPJFjFyrJGRmZ2oOFlEy76jL4jx9WgV6oGZfIcGzuuDdxbNg9uoailfXlnuOmmudxbLMV4XFVkQ7TE/hL3XMkmhFVC4EkSYQ9BUgV4FvBIabfmfRRyVU1gqnjzRdf64PeYpwTRG81cHeZePEatH5b+r/zs38L2B2Lk1j55L0Jsfp69ynauhrjU51lXXVBkLb+HLd433ZuSSNtANFWMxQV2Uk41AxGYeKOXWwiBuf7k/GkZJGoQxQlu++SLj7yDYMkG7EJSQkWgnJDeMSwLt7KL7DY5ocVzrvKPrsFjSeaAEKfwcfXpUMbVKgwzo5qijhqaoM0RJ0nVSJLtEKGHVgMsKQB0URIIjw5NCHYPC9Itps0kHOXsrmPUVlSV3jrmZUZOu7i9bcruzosveem2u4gDm0MZsdf7qvj2hEJvyWzWYL6QeLOLm30K4ZSEC4N1HtrUV1Kq2isTAwrK0fEQkuaiEQ+dK5qeWs/+lYs+Z707MDGD69Q7PGSkhISDQHKbJ8ieA/ui11ySVuc5hB2MmVLkwh4sHerX5+v+FtqE0uwVLfoStgbDw+/SIw5NdgzKkGlZyQmZ3x6hSMWW9CrpbaDUu0Aksfg51fCNu6q9+AO9dB0THwDhWtvufPsRvuU74XhcKCyWTN4w9Q5LruPghQ2gyReImTeaSkWeMUChlYYOlHBxobloTG+nLdY33R1xnZuzKDwHAvwtv5odIq6dA/gqBIa0OSmI5ByOQyLC6ekC1+b1+z5uAbpCG0jW+zxkpISEg0F0ksXyLI1Qoi/tmHkp+PUnugCOQg91djLrMvnjFVtG5jCVOVnsq1mZhrjQRNSQS5DGWQFnUbPwAiHuyNudKA3EuBTKVonKuEhEvMJihKAbUPBMZ6HntkMez8XLw26WDpo8K1I6qndUzcFXD498ZFb0UZY/1eZ0PF3RgtGrr7ryVBu8P9OUw6qCwAv+bn719qKDXN+3s1GS38/vYezDZNjYoyq0jZlc/eVRmU1d/IK9Vybny6v51QBoiMD6DPuHbsW30Kk8nSrDpNAJlchkwGAeFejL3dhUe3hISExBkiieVLCJlcRsjNnTFNNiBTysn/v93OYxQyqvcW4NU15IxFq8VkpvDzg43R7Jr9hYTd3aNRKAPIZDIpN1mieRh18OMNkLZRLI96FkY87n58Za79ssUkOv0FtrWu63+7OO7Kp2lQXwnaHZ4FsiN1pZe1WO4yLIrj2/OaHgh2QrmB6jJdo1AGMOrNZBwucRLLFcW17Fl5ymVk2R2T/tGTtk3UYUhISEicKVLO8iWIwkeFXKNAFeFc8GQq01P6yzFynttC7n93UrO3wGmMsaSOyg2ZVG3LxWJ07y5gKtXZp32YLdQdL22Va5C4DNn3k1UoA6x7Gcqcu8U1knglqGwEl2+E6BDoyMB7PJ+37WDRPMUlcqjIAb379KZLnej2gST2aX7TEZVNJDoi3p+kfhFO9pU+gRqqy3T8PT+FDfOOUZxdRUVhbbOFspe/iitu6iAJZQkJiXOCFFm+hAm8NpHCLw5hKq1zud1UUkfJL8dQBGnQxInCG0NhDQUf7sNS76dava8A46hY/MO88Qu2b3Es91WBQgY20SRlkEOhn4REc9FVOq/Tu27ZDogGKHOXC6u3vIOiQO+LK+H21RCSKATu0SVibMer4dgy52N0nAA3/QhfjOH/27v38KjqO4/j7zOXTO6ThASSAOEeLglgKApKEVREVGiltVa5rIru9vHZPq61u7W1rtvt4m63dteua9e9NIDbKgrVxXopli0oF28LGAUpchfCJRASMkkmyWRmzv5xkpBh5iQBgVzm83qeeZhzzu+c8zt5hpnv/OZ3vl+ORf8SA2H41W2QMQTufRO8gy7kyno1wzC46U+LKd9dTWNtgPXP7ybYZP8lesL1gxg0OpNQyGRQYSZOt4OZC0ez8cU9hINhiq4dSEFRFi8t/RBfpfXetOeDE3z1OyU4nEbM0Wmw7tkcWJjJ9DsLyTpnVFpE5FJSsNyHufolkfuXk2k+Uc/JZ8sgGPtDyP/RSTxDvYQDIU79cmdboAzQfMjHH/6ljAaHg9n3FzH8inYjTGHTKjTS3vlU8hNpr+g22PJz8Fs3hzF0OmR3kjEluxBO7Dy77D8NW562bvI7/D5tE1/zS2D2E3DqMytwTu5nFU7JGQub/snKhtGRM5/Dv02Fb22CrGEXeIG9l2EYDB6bxeFdp20D5cFjMxle0p+i6fkY51RtHDctnzFX52GGTJxuB0f3VLcFymClnDt1uJab/rSY35d+Sqg5jMPlwJPkpMkfZMSk/txwz1icen8RkW6gYLmPM5wGCQNT6bdoHNWv7CXsC0S1qf/gBEnjswmebiRcE3kDoGmahEwIBcNsXr03IlgO1QaiAnC7UWyRTmUUwJ+9DZ+uAU8qXLEwdoXAU3tg8z9bGSwm328Fve0T+H6+GU7vi9zn2Ecw4xG45ttn15kmPDcPDm1qWdFJmeymWvjvr4InHQZOgtlLrSkanlSor4RDm60S2qPnXNj19wKVR+xTT56p8GMYRAXKrZr8zfhrAlRX1NNQ2xz1507J8DB0fDb3/9N0fJWNpGR68CS5ME3T9pgiIpeDguU4kTQmi6RHpxAor8W34QiNLamdWjV8ehr3OVWuWj+kpqS6eLcuSKC6kdotR0mbZuV0dmUl4cpOIljZUhzAYeAZmXE5Lkf6qowCmPag/fb607D8ZvC3VK3c/QaMvwM+edFadqdA9eex922ohopdkDPaCsLrTrYLlAFMyBwK1YesRU86NPkij3Gm5dgVO2DPW1AX48a3mT+Amd/v5EJ7p/5DY+dCBqitauLt5z8jMy+F/HPeBz7ddJR3Vn4WUWAxY0ASvspGwmGTidcNZuh4qxiSK8FJVv7ZaRYKlEWkuylYjjMJg9Lot2Asx378XsR0C6fXQ+L4bHh1f9u61g8pr9Og0OPABGpeP4AZMvF/eBwzDClX5RI63Ui4KUjK5Fw8BfYfpiJf2PGPzgbKYE2f+ORFazpGzhj4429j79dvJKx5wHo+7FpY+BvwpIErCYLtKsFNvg+GXAMb/h72/6HjvsQKlAHe+7c+GywPGp3JgGHpVBz02bY5XV4XESw3NQTZuHJPVCXyMxUNfOXBK8gb5cXlVjpJEem5NAEsDhlOg34LxmAkWt+VEsdkkfblgbhSE6LnILdwOwz2NoU5GQjje/MgwcpGQlWN+NYeInFcFv0WjCWxMPMyXoXEJW8BMV+klXvg5C6qgwPZ6LuPzb57qQ33h0l3w9eXRU7LOLjRyryRkGyVsnYlWetH3ghTvgUOV+eBckccfXsMYu63JzKkuB8OZ+w3i+zBkUVBgk0hwjZZLpxuQ4GyiPR4fftdXWwljs4i/2+mQjCM4XYSOFZHuL4Zw+3ADEQOAZmmyYnmMAETtvpD3JxuRPw02vjHKpLGKoWTXIDyreCvgoKpkNiFXyVyCq2R4YPvRG0KnDrKy6f/gybTyvO9P3gd37zhFhLr9kYfpzXLRtFtVkaM5npIavmyZ4ai27eXkAaBGJk7Wg2d1vl19GKJKW7mfnsiwUCINU99FDXK/O7L+7ntOyU43dZYTLI3gYKifm1V/VoNnZBN3oiMy9VtEZELpmA5jhmGAW4nvj8cxrfOZp5nS7u6lnROzSYEAXe77e68C0vj1PS5j6oXdxOqDZBcnE3mNwoxdLd7/Fj3OGz5F+t5UpZVPMQw4PrHYOoD1g1z6/7GWn/1n8MVd8HaR2MGygBHA+PaAmWAukAaJw/5KBg7uiXAbsnhnJxtBcmtXAnWo1XuREgfBL7y2P3uLJiOmAfdd7kSnNz+yGRe/ulWThw4GzCfOFDDb58u45qvjWTAsHQMw+CWB8aza/Mx/LUBUr0evP2TGFiYGZV/WUSkJ1KwHOfCjcEOA2WA5rBJXctgc7bLwN1uVNlIdpEyOfe8z2uaJqd/tYtwXTMA/rJTuPNSSZsRf3ls41J95dlAGaCh6uzztT+A7NGwajEEWrIvtM433rrM9pBuIzrTS7LXY93Mt/A31tSLQL0VKHeUL/njlfaBMnSeZq45fjLC+CobIgLlVsf2nuHlJ7dy52NTyMpPwelyMH6m/m+LSO+kYDnedaVilgGDEwwSDYNRiZEjv6Y/SP22E6ROze/0MKHaAFUrdxM4Wod7UGpboNwqWNVgs6f0Oefe7RW5Ef742tlAuXXdmo4r8Q3y7GBSyitsr78NA5Op/d8ke9D11kaXBybfa79zKAi71ljp4Q5tsW9nODsfWb7yvo639yGtUy1iMcOw4fk/8vW/mnwZeyQicvEpWI5zjmQ3yVcNwP9hhW0bt2FQkmz/Ugk3dhI8tKh+ZS9NB2oACOyvwfA4MNsVONANgnEktb+VeWJrafQ2VzJssx9B7sjVab/iqtSVgIkzNQt4qvOdTBNeWgh71nahbSev9cFT4KYnutLVPiHF6yFvlJfje2tibq846MMMm5puISK9miaICllfKyTjtpE4zylnHUtSSQ6e4d62ZUeyi+SW/KidacvH3MI8pxJY7dvlhOqif0qXPmruP8Pi/7HyJLfPcBH8Yr8wOI0gTiMEk5d0bYfKPV0LlDvjTrYKlcSZzAH29yyYYSt1nIhIb6aRZQEgdWoeqVPzqN9eQe2GI+Aw8M4Zin9rBQ0td7EbHifp1xXgykqkfmsFZlOQpPE5uLoQZAN4RmQQPGUfCAWO1HJ61Wf0XzL+olyT9AI7XoYdq85Z2YWpQR1JH2iVti6eD4DvdAP7t50iIcnJmKl50VMHnAkxDtJFX7oXiuZD9UEYMq3z8tx90PCSHHZtPhZzW8aAJBJT3DG3iYj0FgqWJULKpAGkTBrQtpxYmIX/owrC9UESi/rhzrZy0qZOzTvvYycUpFH//vEO2zTtOYPv8xrSBqfrp9u+rnIflP364h/Xd6yt5LSvsoHV/7CVxnprfvy+bSf5yoNXRL62sobBNQ/Cu093/RyDpsAt/wj5JS0rZlykzvc+Q4r6YTgMzHPufxhYmMGN9xV1U69ERC4eTcOQDhlOg5TJuaTNGNQWKF8osws/xx5tCvG7n27jvUc20bi3+gudT/oYTxrc/CRM+GbH7QyH9cAKjlsDZYDy3dWcORkjm8Xsv4MH3oMZP+i8HwOK4Z7X2gXKcvX84W3PDQNm3z+O2x6eRIrX0429EhG5ODSyLJdN4th+GOsOYzZaQbMjLYFwXaDtV/eqYJiyhjAhoLI2SPO/f8K1P7s2ogCK9CHZI2HCnVa56q5oqoVNP4O5P7fKW2944mxWDcNx9vkNf21lvwDcHqs6nEGIdOdJBiTsJnXjS9B/GEz7C3C3+wI4YByEmuCdnxBzKog7BWZ8D7780AVdbl9WcuMQ8kdm4jvdQN4IL6mZXZuaJSLSGximaX7BCYLnz+fz4fV6qampIT29C1W7pM9oPuXHv60Cw+Ug9Zp8qlbtoXG3lWP3vbogJ4NnX44pDph3TR79Fo3tru7KpbTjN3D6ABx5//zKS7sSrbLU7fM0gxVE519hVQX0HYVRNxHMv4q3nt7ClVUP0d+9v61pyHSyL3kxNUUPMWpyfzJT6uC1v7Bu9kvLhaqD4K+EUIwbTuf/J0zsZHRbpI/S57fEI40sy2XlzknGO2dY23Lm7aOoWvUZ/j1naDhnzqMJNOysJBwI4UhwXuaeyiW19lF4/xcXtm+wERrPKTftSoRxX4W134dPXrLWbX4K13U/5JaJTRib90c0dxohRvhfYM1bYyn737F8Y8wyMk/8ztpYtR9GzoYD62Off+/vFSyLiMQRzVmWbuVMTSBnyXiG/GQ6zcnuiBfk6Jaf0HdvOto9nZNLZ9vyrrVLyrLZf5k1d9jpsdp8/ZfWnOYdqyPbvf0TjNrYrx+XEWBM0nqaG0PsP5QWuXHf7yFsM8c+a0TX+i4iIn2CgmXpMW74k7H0c8GkJAczUl0UeBycbg6zYfU+tr/VcUlu6WU8aZ23GXEDXPeY/faKnXDFQhg23cqA4XBZI8ztmSEY+CXb9HCBsDVn2ZPVtVzhDBgP0x/uWlsREekTFCxLjzF0QjbTH5pE0lW51DoMdjYE2VJvVUw7+PGpbu6dXFTznraKeHQkuxAyh3TcZtsy2PUq/O57Vuq3WT+K3J7otfIg37cOcqPzd39SfyuDE8oYd+tUqzhK3hXWPufyeKFwjpUFw62b10RE4onmLEuPkjcyg7yRGfzPMT/H9p5pWx8KXvb7UOVSGj0HHt5l3Yz3/O2x2+x+Aw6+Y38MpxtCZ9PCsXcd3PM6pOfDe89AQjpc/0NIybYeI66HEzvamodNg6/1e5Q0ZyVG0qvw9f+Cyr3w0a9hy9NA2BqtDgehqcaq8rf6HviTVy/Kn0BERHoHjSxLj3TdojF4ks9+lzt1uFZTMfqapEwYdSOk5MTeXnMYTu6Kve2Wn1mjwO1ltIxCj50HS96CRaut7BgAr/752ewZLVMyHIZJuusURnouDLkGtj0Hz1wJW34OhKH/OMgeHXmOAxvP8yJFRKS3U7AsPVLGgOSoMrn7P9JUjD5p6PTzaz/yRkjOguLboX+RNfo77FqrsEgsB96xRotbnZsOrvY4NPvhrUeJyK98cld0sO7QW6aISLzRO7/0WCkZkdW/Uryxb9KSXm7ez2HQVdbzRC+MuqmDxg4ruP3NElj7iDU6/cMKuPs1K4COpe5kJx0wIBS0CpJEOWf6j9MDH/5XJ8cTEZG+RMGy9FgzF47Gm2NlK3C6HJTvrmbtf+6gORDq5p7JRZXohfvXwePV8P3D8I3lUHizNWKclgeOdjm2h8+wsmC0+nwzfL4FGmusIief/Q7C4cjj1xyJPqfR7naNL38HVt4ZOf/ZTnM9vPmX8O4z53eNIiLSa6mCn/R4L/ztB1Qfr29bnnTTEK6er1y3fZ5pgmFA+TarQIi3wCpjvfruyHYLVllTKE7vs5bHzIVv/toqj718DlR82vF5POnQ5Itc50yIXb2v1bAZcPdvz/+aRHo5fX5LPFI2DOnxfKcaIpZ3bTnGlK8Mw+HUDyN9mmFY/w76kvUAa/R36HQ4tMlaHjsPzhw+GygD7H7dCpBf/07ngTJEB8pg5WvuKFj2KEgQEYkXijakx8vKT4lYbqxrZsX3t1B9ot5mD+mznG5YvAbufh3uXQt3/MqarnEufxWUf/gFTmR0vPnI+9Dc0HEbERHpExQsS4+XMyS62ltDbTO//+WnNDXYlCSWvsvpsqr2DbnaGn0e/w3Im3h2e8ki8Fee/3FTciA5G0oWQ2FHNxkC9aesqoEiItLnaRqG9HgDhqaxa1P0+sryOlZ8bzM3LilieIlNrl7p+zypVl7lw+9ZVQELpsKRTkaVnZ7o7BczfwBX3mc9D/ghKQP2/S9UHYjePzUX0gdelO6LiEjPppFl6fFGXZlLYkrs73XB5jB/+G+bwhUSP9xJVoW+gqnW8uCr4Pq/xvYtLm8CfO2X1txkgHFfhUntbhxMSIZbnoQHP4LZSyFrhBUcZ42wcjovfkVlr0VE4oSyYUiv4Kts4KUnPiTQEDtt3Lf+dQYutzPmNolj4RCsexz+rxTMsBVUDyiC256FzCHWDYPBRvBET/URkWj6/JZ4pGkY0iu4Epy2gTLAjrfLKblxyGXskfQKDifc9IT1iMXpth4iIiI2NA1DegVPsouEJPvvdu++vJ+9WysuY49EREQkHihYll7B6XIw51vFOJz2Kb2O7Kq6jD0SERGReKBgWXqNwWOyuP2RyRg2U5PTs5Mub4dERESkz1OwLL1KTkEa3/zhVYyZmktSqhuH08BwwKgrB1Ayu6C7uyciIiJ9jG7wk16nX34qN9wzrru7ISIiInFAI8siIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNBcsiIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNBcsiIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNV3ec1DRNAHw+X3ecXkRERC5A6+d26+e4SDzolmC5trYWgMGDB3fH6UVEROQLqK2txev1dnc3RC4Lw+yGr4fhcJhjx46RlpaGYRiX+/QiIiJyAUzTpLa2lvz8fBwOzeSU+NAtwbKIiIiISG+gr4UiIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNBcsicWjmzJk89NBDUetXrFhBRkYGAD/60Y8wDIM5c+ZEtXvyyScxDIOZM2dGbSsvLychIYHi4uKY5zYMo+3h9XqZNm0a69evb9u+ceNG5s2bR35+PoZhsGbNmgu5RBERkYtCwbKI2MrLy2PDhg2Ul5dHrF+2bBkFBQUx91mxYgV33HEHPp+PDz74IGab5cuXc/z4cbZs2UJ2djZz587lwIEDANTX1zNx4kR+8YtfXNyLERERuQAKlkXEVv/+/Zk9ezbPPfdc27p3332XyspKbr311qj2pmmyfPlyFi9ezIIFCygtLY153IyMDHJzcykuLubZZ5+loaGBdevWAXDzzTezdOlS5s+ff2kuSkRE5DwoWBaRDi1ZsoQVK1a0LS9btoyFCxeSkJAQ1XbDhg34/X5mzZrFokWLePHFF6mvr+/w+ElJSQAEAoGL2m8REZGLQcGyiHRo7ty5+Hw+Nm7cSH19PatWrWLJkiUx25aWlnLnnXfidDopLi5m+PDhrF692vbYfr+fxx57DKfTyYwZMy7VJYiIiFwwV3d3QER6NrfbzaJFi1i+fDkHDhygsLCQCRMmRLU7c+YMr7zyCps3b25bt2jRIkpLS7nnnnsi2t511104nU4aGhrIycmhtLQ05jFFRES6m4JlkTiUnp5OTU1N1PozZ87g9Xqj1i9ZsoQpU6awc+dO21HlF154gcbGRqZMmdK2zjRNwuEwe/bsobCwsG39U089xaxZs/B6veTk5FyEKxIREbk0NA1DJA6NHj2a7du3R63fvn17RFDbqqioiKKiInbu3MmCBQtiHrO0tJTvfve7lJWVtT0+/vhjpk+fzrJlyyLa5ubmMnLkSAXKIiLS42lkWSQOPfDAAzzzzDM8+OCD3H///Xg8Ht544w1WrlzJa6+9FnOf9evX09zc3JaHub2ysjK2b9/O888/z5gxYyK23XXXXfz4xz9m6dKluFydv+XU1dWxb9++tuWDBw9SVlZGVlaWbbo6ERGRS0UjyyJxaPjw4WzcuJHdu3cza9YspkyZwqpVq1i9enXMIiQAKSkpMQNlsEaVx40bFxUoA8yfP5+TJ0/y5ptvdqlvW7dupaSkhJKSEgAefvhhSkpKePzxx7t2cSIiIheRYZqm2d2dEBERERHpiTSyLCIiIiJiQ8GyiIiIiIgNBcsiIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNBcsiIiIiIjYULIuIiIiI2FCwLCIiIiJiQ8GyiIiIiIgNBcsiIiIiIjYULIuIiIiI2Ph/Gir+DhkCOlwAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "adata = sc.read_h5ad(os.path.join(ATAC_FILE_PATH, \"cell_embedding\", \"embeddings.h5ad\"))\n", "obs_df = pd.DataFrame(adata.obs['celltype'].tolist(), columns=['celltype'])\n", "adata = sc.AnnData(X=adata.obsm['X_embedding'], obs=obs_df)\n", "sc.tl.pca(adata, n_comps=10)\n", "sc.pp.neighbors(adata, n_neighbors=15, use_rep='X_pca')\n", "sc.tl.umap(adata)\n", "sc.pl.umap(adata, color='celltype', title='umap of cell embeddings')" ] }, { "cell_type": "code", "execution_count": 45, "id": "aa27d252-f7f9-4b48-ad66-f424a9fb97a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ari: 0.7573429535020857, nmi: 0.842267548775634, ami: 0.8416228114166705, fmi: 0.811748902937001\n" ] } ], "source": [ "cluster_label = calculate_cluster(adata.obsm['X_pca'], adata.obs[\"celltype\"])\n", "ari_norm = adjusted_rand_score(adata.obs[\"celltype\"], cluster_label)\n", "nmi = normalized_mutual_info_score(adata.obs[\"celltype\"], cluster_label)\n", "ami = adjusted_mutual_info_score(adata.obs[\"celltype\"], cluster_label)\n", "fmi = fowlkes_mallows_score(adata.obs[\"celltype\"], cluster_label)\n", "print(\n", " f\"ari: {ari_norm}, \"\n", " f\"nmi: {nmi}, \"\n", " f\"ami: {ami}, \"\n", " f\"fmi: {fmi}\"\n", ")" ] }, { "cell_type": "code", "execution_count": null, "id": "bdbfc3c0-bfba-4d98-9e2e-6e6a8e61845b", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "scgpt_env", "language": "python", "name": "scgpt_env" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.15" } }, "nbformat": 4, "nbformat_minor": 5 }