From 59393f057d24261a931d20746f55e469719c893e Mon Sep 17 00:00:00 2001 From: Johannes Hjorth Date: Tue, 1 Oct 2024 16:16:45 +0200 Subject: [PATCH] Example --- .../schizophrenia/create_network.ipynb | 509 +++++++++++++++ .../schizophrenia/create_network_d2oe.ipynb | 604 ++++++++++++++++++ examples/notebooks/schizophrenia/input.json | 46 ++ 3 files changed, 1159 insertions(+) create mode 100644 examples/notebooks/schizophrenia/create_network.ipynb create mode 100644 examples/notebooks/schizophrenia/create_network_d2oe.ipynb create mode 100644 examples/notebooks/schizophrenia/input.json diff --git a/examples/notebooks/schizophrenia/create_network.ipynb b/examples/notebooks/schizophrenia/create_network.ipynb new file mode 100644 index 000000000..b4652fe62 --- /dev/null +++ b/examples/notebooks/schizophrenia/create_network.ipynb @@ -0,0 +1,509 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d75f0e83-fc1b-41ea-91f5-9e1ec1a056ad", + "metadata": {}, + "source": [ + "# Setup and simulate Schizophrenia network" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "8432056a-edb2-4d63-92fd-1aa7345f3579", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Legacy config creation.\n", + "Creating config file\n", + "Network path: network/d2oe-0\n", + "Adding Striatum with 100 neurons (stay_inside=False)\n", + "Using cube for striatum\n", + "Neurons for striatum read from /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum\n", + "Adding neurons: FS from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs\n", + "Adding neurons: dSPN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/dspn\n", + "Adding neurons: iSPN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/ispn\n", + "Adding neurons: ChIN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/chin\n", + "Adding neurons: LTS from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts\n", + "No directory $SNUDDA_DATA/neurons/striatum/ngf, skipping NGF cells.\n", + "Adding GPe with 0 neurons\n", + "Adding GPi with 0 neurons\n", + "Adding SNr with 0 neurons\n", + "Adding STN with 0 neurons\n", + "Adding Cortex with 0 neurons\n", + "Adding Thalamus with 0 neurons\n", + "Writing network/d2oe-0/network-config.json\n" + ] + } + ], + "source": [ + "from snudda import Snudda\n", + "\n", + "network_path = \"network/d2oe-0\"\n", + "\n", + "snd_wt = Snudda(network_path=network_path)\n", + "snd_wt.init_config(network_size=100, \n", + " snudda_data=\"../../../../bgmod/models/optim/schizophrenic/BGDATA/WT\",\n", + " honor_stay_inside=False,\n", + " overwrite=True, random_seed=1234)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "9344757d-210c-41ed-abf4-80d99705b604", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Placing neurons\n", + "Network path: network/d2oe-0\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "No n_putative_points and putative_density, setting n_putative_points = 780\n", + "(this must be larger than the number of neurons you want to place)\n", + "Generating 780 points for network/d2oe-0/mesh/Striatum-cube-mesh-0.00010749824478388102.obj\n", + "Filtering, keeping inside points: 129 / 300\n", + "neuron_name = 'FS_0', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e160628_FS2-mMTC180800A-IDB-v20210210'\n", + "neuron_name = 'FS_1', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161024_FS16-mDR-rat-Mar-13-08-1-536-R-v20210210'\n", + "neuron_name = 'FS_2', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161205_FS1-mBE104E-v20210209'\n", + "neuron_name = 'FS_3', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161205_FS1-mMTC180800A-IDB-v20210210'\n", + "neuron_name = 'dSPN_0', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/dspn/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026-ctrl'\n", + "neuron_name = 'dSPN_1', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/dspn/str-dspn-e150917_c10_D1-mWT-P270-20-v20211026-ctrl'\n", + "neuron_name = 'dSPN_2', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/dspn/str-dspn-e150917_c6_D1-m21-6-DE-v20211028-ctrl'\n", + "neuron_name = 'dSPN_3', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/dspn/str-dspn-e150917_c9_D1-mWT-1215MSN03-v20211026-ctrl'\n", + "neuron_name = 'iSPN_0', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/ispn/str-ispn-e150908_c4_D2-m51-5-DE-v20211026-ctrl'\n", + "neuron_name = 'iSPN_1', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/ispn/str-ispn-e150917_c11_D2-mWT-MSN1-v20211026-ctrl'\n", + "neuron_name = 'iSPN_2', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/ispn/str-ispn-e151123_c1_D2-mWT-P270-09-v20211026-ctrl'\n", + "neuron_name = 'iSPN_3', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/ispn/str-ispn-e160118_c10_D2-m46-3-DE-v20211026-ctrl'\n", + "neuron_name = 'ChIN_0', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/chin/str-chin-e170614_cell6-m17JUL301751_170614_no6_MD_cell_1_x63-v20190710'\n", + "neuron_name = 'LTS_0', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts/LTS_180118_morp_9862_updated_20210301'\n", + "neuron_name = 'LTS_1', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts/LTS_180118_morp_9862_updated_April2022'\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 17.3s\n", + "Touch detection\n", + "Network path: network/d2oe-0\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "No d_view specified, running distribute neurons in serial\n", + "Processing hyper voxel : 21/64 (99 neurons)\n", + "Processing hyper voxel : 17/64 (98 neurons)\n", + "Processing hyper voxel : 20/64 (97 neurons)\n", + "Processing hyper voxel : 16/64 (89 neurons)\n", + "Processing hyper voxel : 5/64 (82 neurons)\n", + "Processing hyper voxel : 37/64 (60 neurons)\n", + "Processing hyper voxel : 4/64 (55 neurons)\n", + "Processing hyper voxel : 1/64 (51 neurons)\n", + "Processing hyper voxel : 36/64 (44 neurons)\n", + "Processing hyper voxel : 33/64 (42 neurons)\n", + "Processing hyper voxel : 0/64 (37 neurons)\n", + "Processing hyper voxel : 22/64 (27 neurons)\n", + "Processing hyper voxel : 25/64 (24 neurons)\n", + "Processing hyper voxel : 32/64 (23 neurons)\n", + "Processing hyper voxel : 18/64 (21 neurons)\n", + "Processing hyper voxel : 24/64 (16 neurons)\n", + "Processing hyper voxel : 6/64 (5 neurons)\n", + "Processing hyper voxel : 9/64 (4 neurons)\n", + "Processing hyper voxel : 38/64 (4 neurons)\n", + "Processing hyper voxel : 41/64 (4 neurons)\n", + "Processing hyper voxel : 8/64 (3 neurons)\n", + "Processing hyper voxel : 40/64 (2 neurons)\n", + "Processing hyper voxel : 34/64 (2 neurons)\n", + "Processing hyper voxel : 2/64 (2 neurons)\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 25.6s\n", + "Prune synapses\n", + "Network path: network/d2oe-0\n", + "No file network/d2oe-0/pruning_merge_info.json\n", + "Traceback (most recent call last):\n", + " File \"/home/hjorth/HBP/Snudda/snudda/detect/prune.py\", line 1780, in big_merge_helper\n", + " next_row_set = next(file_mat_iterator[h_id], None)\n", + " File \"/home/hjorth/HBP/Snudda/snudda/detect/prune.py\", line 2334, in synapse_set_iterator\n", + " or (read_buffer[start_idx - buffer_start, :2]\n", + "KeyboardInterrupt\n", + "\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'tuple' object has no attribute 'tb_frame'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/HBP/Snudda/snudda/detect/prune.py:1780\u001b[0m, in \u001b[0;36mSnuddaPrune.big_merge_helper\u001b[0;34m(self, neuron_range, merge_data_type)\u001b[0m\n\u001b[1;32m 1779\u001b[0m \u001b[38;5;66;03m# Get the next set of synapses from this file from the iterator\u001b[39;00m\n\u001b[0;32m-> 1780\u001b[0m next_row_set \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mfile_mat_iterator\u001b[49m\u001b[43m[\u001b[49m\u001b[43mh_id\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 1782\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m next_row_set \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1783\u001b[0m \u001b[38;5;66;03m# More synapses in file, push next pair to heap, and pop top pair\u001b[39;00m\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/detect/prune.py:2334\u001b[0m, in \u001b[0;36mSnuddaPrune.synapse_set_iterator\u001b[0;34m(h5mat_lookup, h5mat, chunk_size, lookup_iterator)\u001b[0m\n\u001b[1;32m 2331\u001b[0m syn_mat \u001b[38;5;241m=\u001b[39m read_buffer[(start_idx \u001b[38;5;241m-\u001b[39m buffer_start):(end_idx \u001b[38;5;241m-\u001b[39m buffer_start), :]\n\u001b[1;32m 2333\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m end_idx \u001b[38;5;241m==\u001b[39m buffer_end \\\n\u001b[0;32m-> 2334\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m (\u001b[43mread_buffer\u001b[49m\u001b[43m[\u001b[49m\u001b[43mstart_idx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mbuffer_start\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 2335\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m!=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mread_buffer\u001b[49m\u001b[43m[\u001b[49m\u001b[43mend_idx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mbuffer_start\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m)\u001b[38;5;241m.\u001b[39many(), \\\n\u001b[1;32m 2336\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mWe missed one synapse! (1)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2338\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m (syn_mat[:, \u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m==\u001b[39m syn_mat[\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39mall() \u001b[38;5;129;01mand\u001b[39;00m (syn_mat[:, \u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m syn_mat[\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m])\u001b[38;5;241m.\u001b[39mall(), \\\n\u001b[1;32m 2339\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSynapse matrix (1) contains more than one pair:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{syn_mat}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: ", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mSystemExit\u001b[0m Traceback (most recent call last)", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43msnd_wt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_network\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/core.py:264\u001b[0m, in \u001b[0;36mSnudda.create_network\u001b[0;34m(self, honor_morphology_stay_inside)\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdetect_synapses()\n\u001b[0;32m--> 264\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprune_synapses\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/core.py:522\u001b[0m, in \u001b[0;36mSnudda.prune_synapses\u001b[0;34m(self, config_file, random_seed, parallel, ipython_profile, ipython_timeout, h5libver, verbose, keep_files, save_putative_synapses)\u001b[0m\n\u001b[1;32m 511\u001b[0m sp \u001b[38;5;241m=\u001b[39m SnuddaPrune(network_path\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnetwork_path,\n\u001b[1;32m 512\u001b[0m logfile\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlogfile,\n\u001b[1;32m 513\u001b[0m logfile_name\u001b[38;5;241m=\u001b[39mlog_filename,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 519\u001b[0m verbose\u001b[38;5;241m=\u001b[39mverbose,\n\u001b[1;32m 520\u001b[0m keep_files\u001b[38;5;241m=\u001b[39mkeep_files \u001b[38;5;129;01mor\u001b[39;00m save_putative_synapses)\n\u001b[0;32m--> 522\u001b[0m \u001b[43msp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprune\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 524\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m save_putative_synapses:\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/detect/prune.py:245\u001b[0m, in \u001b[0;36mSnuddaPrune.prune\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 243\u001b[0m \u001b[38;5;66;03m# From the hyper voxels gather all synapses (and gap junctions) belonging to specific neurons\u001b[39;00m\n\u001b[1;32m 244\u001b[0m merge_files_syn, merge_neuron_range_syn, merge_syn_ctr, \\\n\u001b[0;32m--> 245\u001b[0m merge_files_gj, merge_neuron_range_gj, merge_gj_ctr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgather_neuron_synapses\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 247\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msave_merge_info(merge_files_syn\u001b[38;5;241m=\u001b[39mmerge_files_syn,\n\u001b[1;32m 248\u001b[0m merge_neuron_range_syn\u001b[38;5;241m=\u001b[39mmerge_neuron_range_syn,\n\u001b[1;32m 249\u001b[0m merge_syn_ctr\u001b[38;5;241m=\u001b[39mmerge_syn_ctr,\n\u001b[1;32m 250\u001b[0m merge_files_gj\u001b[38;5;241m=\u001b[39mmerge_files_gj,\n\u001b[1;32m 251\u001b[0m merge_neuron_range_gj\u001b[38;5;241m=\u001b[39mmerge_neuron_range_gj,\n\u001b[1;32m 252\u001b[0m merge_gj_ctr\u001b[38;5;241m=\u001b[39mmerge_gj_ctr)\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/detect/prune.py:1462\u001b[0m, in \u001b[0;36mSnuddaPrune.gather_neuron_synapses\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1459\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39md_view:\n\u001b[1;32m 1460\u001b[0m \n\u001b[1;32m 1461\u001b[0m \u001b[38;5;66;03m# Run in serial, save as a list to make result compatible with parallel version of code\u001b[39;00m\n\u001b[0;32m-> 1462\u001b[0m merge_results_syn \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbig_merge_helper\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneuron_range\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marray\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_neurons\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1463\u001b[0m \u001b[43m \u001b[49m\u001b[43mmerge_data_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43msynapses\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m]\n\u001b[1;32m 1464\u001b[0m merge_results_gj \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbig_merge_helper(neuron_range\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39marray([\u001b[38;5;241m0\u001b[39m, num_neurons]),\n\u001b[1;32m 1465\u001b[0m merge_data_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgap_junctions\u001b[39m\u001b[38;5;124m'\u001b[39m)]\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/detect/prune.py:1825\u001b[0m, in \u001b[0;36mSnuddaPrune.big_merge_helper\u001b[0;34m(self, neuron_range, merge_data_type)\u001b[0m\n\u001b[1;32m 1824\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwrite_log(t_str, is_error\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m-> 1825\u001b[0m \u001b[43msys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n", + "\u001b[0;31mSystemExit\u001b[0m: -1", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/interactiveshell.py:2121\u001b[0m, in \u001b[0;36mInteractiveShell.showtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m 2118\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m exception_only:\n\u001b[1;32m 2119\u001b[0m stb \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mAn exception has occurred, use \u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mtb to see \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 2120\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mthe full traceback.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m-> 2121\u001b[0m stb\u001b[38;5;241m.\u001b[39mextend(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInteractiveTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_exception_only\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2122\u001b[0m \u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 2123\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2125\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcontains_exceptiongroup\u001b[39m(val):\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:710\u001b[0m, in \u001b[0;36mListTB.get_exception_only\u001b[0;34m(self, etype, value)\u001b[0m\n\u001b[1;32m 702\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_exception_only\u001b[39m(\u001b[38;5;28mself\u001b[39m, etype, value):\n\u001b[1;32m 703\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Only print the exception type and message, without a traceback.\u001b[39;00m\n\u001b[1;32m 704\u001b[0m \n\u001b[1;32m 705\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 708\u001b[0m \u001b[38;5;124;03m value : exception value\u001b[39;00m\n\u001b[1;32m 709\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 710\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mListTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:568\u001b[0m, in \u001b[0;36mListTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, context)\u001b[0m\n\u001b[1;32m 565\u001b[0m chained_exc_ids\u001b[38;5;241m.\u001b[39madd(\u001b[38;5;28mid\u001b[39m(exception[\u001b[38;5;241m1\u001b[39m]))\n\u001b[1;32m 566\u001b[0m chained_exceptions_tb_offset \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 567\u001b[0m out_list \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 568\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 569\u001b[0m \u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 570\u001b[0m \u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 571\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchained_exc_ids\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 572\u001b[0m \u001b[43m \u001b[49m\u001b[43mchained_exceptions_tb_offset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 573\u001b[0m \u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 575\u001b[0m \u001b[38;5;241m+\u001b[39m chained_exception_message\n\u001b[1;32m 576\u001b[0m \u001b[38;5;241m+\u001b[39m out_list)\n\u001b[1;32m 578\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m out_list\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:1435\u001b[0m, in \u001b[0;36mAutoFormattedTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1433\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1434\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtb \u001b[38;5;241m=\u001b[39m etb\n\u001b[0;32m-> 1435\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mFormattedTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1436\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\n\u001b[1;32m 1437\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:1326\u001b[0m, in \u001b[0;36mFormattedTB.structured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1323\u001b[0m mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode\n\u001b[1;32m 1324\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mode \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose_modes:\n\u001b[1;32m 1325\u001b[0m \u001b[38;5;66;03m# Verbose modes need a full traceback\u001b[39;00m\n\u001b[0;32m-> 1326\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mVerboseTB\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstructured_traceback\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1327\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\n\u001b[1;32m 1328\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1329\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMinimal\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 1330\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ListTB\u001b[38;5;241m.\u001b[39mget_exception_only(\u001b[38;5;28mself\u001b[39m, etype, value)\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:1173\u001b[0m, in \u001b[0;36mVerboseTB.structured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m 1164\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstructured_traceback\u001b[39m(\n\u001b[1;32m 1165\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 1166\u001b[0m etype: \u001b[38;5;28mtype\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1170\u001b[0m number_of_lines_of_context: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m,\n\u001b[1;32m 1171\u001b[0m ):\n\u001b[1;32m 1172\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Return a nice text document describing the traceback.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1173\u001b[0m formatted_exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mformat_exception_as_a_whole\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1174\u001b[0m \u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1176\u001b[0m colors \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mColors \u001b[38;5;66;03m# just a shorthand + quicker name lookup\u001b[39;00m\n\u001b[1;32m 1177\u001b[0m colorsnormal \u001b[38;5;241m=\u001b[39m colors\u001b[38;5;241m.\u001b[39mNormal \u001b[38;5;66;03m# used a lot\u001b[39;00m\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:1063\u001b[0m, in \u001b[0;36mVerboseTB.format_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 1060\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(tb_offset, \u001b[38;5;28mint\u001b[39m)\n\u001b[1;32m 1061\u001b[0m head \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprepare_header(\u001b[38;5;28mstr\u001b[39m(etype), \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlong_header)\n\u001b[1;32m 1062\u001b[0m records \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m-> 1063\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_records\u001b[49m\u001b[43m(\u001b[49m\u001b[43metb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnumber_of_lines_of_context\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m etb \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[1;32m 1064\u001b[0m )\n\u001b[1;32m 1066\u001b[0m frames \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 1067\u001b[0m skipped \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n", + "File \u001b[0;32m~/HBP/Snudda/venv/lib/python3.9/site-packages/IPython/core/ultratb.py:1131\u001b[0m, in \u001b[0;36mVerboseTB.get_records\u001b[0;34m(self, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m 1129\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m cf \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1130\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1131\u001b[0m mod \u001b[38;5;241m=\u001b[39m inspect\u001b[38;5;241m.\u001b[39mgetmodule(\u001b[43mcf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtb_frame\u001b[49m)\n\u001b[1;32m 1132\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mod \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1133\u001b[0m mod_name \u001b[38;5;241m=\u001b[39m mod\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n", + "\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'tb_frame'" + ] + } + ], + "source": [ + "snd_wt.create_network()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bb0f9b11-114d-49be-9642-de15b78e46d7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network/d2oe-0/network-synapses.hdf5\n", + "Assuming volume type: cube [cube or full]\n", + "Only using 20000 neurons of the connection data\n", + "Creating figures directory network/d2oe-0/figures\n", + "Number of neurons: 99\n", + "Synapse row 0 - 0.0 % time: 0.0007832770006643841 seconds\n", + "Created connection matrix 0.006037343000571127 seconds\n", + "Created gap junction connection matrix 6.583200047316495e-05 seconds\n", + "Creating population dictionary\n", + "Done.\n", + "Warning: the analysis cube specified by sideLen is too large.\n", + "!!! Setting sideLen to None\n", + "Calculating synapse distance histogram\n", + "Creating dist histogram\n", + "n_synapses = 5843, at 0\n", + "Created distance histogram (optimised) in 0.005171401000552578 seconds\n", + "Saving cache to network/d2oe-0/network-synapses.hdf5-cache\n" + ] + } + ], + "source": [ + "from snudda.analyse import SnuddaAnalyseStriatum \n", + "nas = SnuddaAnalyseStriatum(network_path, volume_type=\"cube\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "74a2d8e4-a904-453a-910d-317557197323", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plotting connection probability dSPN to iSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2304.]\n", + "P(d<5e-05) = 0.07248322147651007\n", + "P(d<0.0001) = 0.05535390199637023\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-0/figures/Network-distance-dependent-connection-probability-dSPN-to-iSPN-synapses-3D-dist.png\n", + "Plotting connection probability dSPN to dSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2256.]\n", + "P(d<5e-05) = 0.2030812324929972\n", + "P(d<0.0001) = 0.18117977528089887\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-0/figures/Network-distance-dependent-connection-probability-dSPN-to-dSPN-synapses-3D-dist.png\n", + "Plotting connection probability iSPN to dSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2304.]\n", + "P(d<5e-05) = 0.23221476510067113\n", + "P(d<0.0001) = 0.19827586206896552\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-0/figures/Network-distance-dependent-connection-probability-iSPN-to-dSPN-synapses-3D-dist.png\n", + "Plotting connection probability iSPN to iSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2256.]\n", + "P(d<5e-05) = 0.3740053050397878\n", + "P(d<0.0001) = 0.29981634527089074\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-0/figures/Network-distance-dependent-connection-probability-iSPN-to-iSPN-synapses-3D-dist.png\n" + ] + }, + { + "data": { + "text/plain": [ + "({5e-05: 0.3740053050397878, 0.0001: 0.29981634527089074},\n", + " 'network/d2oe-0/figures/Network-distance-dependent-connection-probability-iSPN-to-iSPN-synapses-3D-dist.png')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dist3D = True\n", + "\n", + "nas.plot_connection_probability(\"dSPN\", \"iSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[3 / 47.0, 3 / 66.0],\n", + " exp_data_detailed=[(3, 47), (3, 66)])\n", + "nas.plot_connection_probability(\"dSPN\", \"dSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[5 / 19.0, 3 / 43.0],\n", + " exp_data_detailed=[(5, 19), (3, 43)])\n", + "nas.plot_connection_probability(\"iSPN\", \"dSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[13 / 47.0, 10 / 80.0],\n", + " exp_data_detailed=[(13, 47), (10, 80)])\n", + "nas.plot_connection_probability(\"iSPN\", \"iSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[14 / 39.0, 7 / 31.0],\n", + " exp_data_detailed=[(14, 39), (7, 31)])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "da809425-6011-4c7b-8faa-1aa6714c9bca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Setting up inputs, assuming input.json exists\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "Missing input config file: network/d2oe-0/input.json\n" + ] + } + ], + "source": [ + "snd_wt.setup_input(input_config=\"input.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "866b469c-2706-4c69-8c6d-c3ae8b961918", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MPI Rank: 0, Size: 1\n", + "Using input file None\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "NEURON mechanisms already compiled, make sure you have the correct version of NEURON modules.\n", + "If you delete x86_64, aarch64, arm64 directories (or nrnmech.dll) then you will force a recompilation of the modules.\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT from network/d2oe-0/network-config.json\n", + "Warning: No external synaptic input file given!\n", + "MPI Rank: 0, Size: 1 -- NEURON: This is node 0 out of 1\n", + "0 : Memory status: 73% free\n", + "Empty mod_file field for ChIN -> dSPN synapses. This channel is IGNORED.\n", + "Empty mod_file field for ChIN -> iSPN synapses. This channel is IGNORED.\n", + "0 : Memory status: 72% free\n", + "Added 0.0 gap junctions to simulation (0 total)\n", + "Warning: No channel module for 21 between neuron 20 and 5, did you miss specifying a mod file?\n", + "Warning: No channel module for 20 between neuron 20 and 33, did you miss specifying a mod file?\n", + "Added 5843 synapses to simulation (5843 total)\n", + "0 : Memory status: 72% free\n", + "No input file given, not adding external input!\n", + "0 : Memory status: 72% free\n", + "0 : Memory status: 72% free\n", + "Running simulation for 1000.0 ms.\n", + "Running simulation for 1.0 s\n", + "Running Neuron simulator 1000 ms, with dt=0.025\n", + " 1% done. Elapsed: 11.5 s, estimated time left: 1138.4 s\n" + ] + } + ], + "source": [ + "snd_wt.simulate(time=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7b57be40-17bc-463f-bcbc-b5799b13ef86", + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Network path network/d2oe-0 specified, but no file network/d2oe-0/network-synapses.hdf5", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msnudda\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m SnuddaLoad\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msnudda\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m SnuddaLoadNetworkSimulation\n\u001b[0;32m----> 4\u001b[0m sl \u001b[38;5;241m=\u001b[39m \u001b[43mSnuddaLoad\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnetwork_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 6\u001b[0m sim_file \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(network_path, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msimulation\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moutput.hdf5\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 7\u001b[0m network_file \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(network_path, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnetwork-synapses.hdf5\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m~/HBP/Snudda/snudda/utils/load.py:50\u001b[0m, in \u001b[0;36mSnuddaLoad.__init__\u001b[0;34m(self, network_file, snudda_data, load_synapses, verbose)\u001b[0m\n\u001b[1;32m 48\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39misdir(network_file):\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39misfile(alt_file):\n\u001b[0;32m---> 50\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNetwork path \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnetwork_file\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m specified, but no file \u001b[39m\u001b[38;5;132;01m{\u001b[39;00malt_file\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 51\u001b[0m network_file \u001b[38;5;241m=\u001b[39m alt_file\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mload_hdf5(network_file, load_synapses)\n", + "\u001b[0;31mValueError\u001b[0m: Network path network/d2oe-0 specified, but no file network/d2oe-0/network-synapses.hdf5" + ] + } + ], + "source": [ + "import os\n", + "from snudda.utils import SnuddaLoad\n", + "from snudda.utils import SnuddaLoadSimulation\n", + "\n", + "sl = SnuddaLoad(network_path)\n", + "\n", + "sim_file = os.path.join(network_path, \"simulation\", \"output.hdf5\")\n", + "network_file = os.path.join(network_path, \"network-synapses.hdf5\")\n", + "\n", + "sls = SnuddaLoadSimulation(network_simulation_output_file=sim_file)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "11488b57-05ed-4b23-809e-983bc18690e7", + "metadata": {}, + "outputs": [], + "source": [ + "from snudda.plotting.plot_traces import PlotTraces\n", + "pt = PlotTraces(output_file=sim_file, network_file=network_file)\n", + "# Use trace_id to specify which traces\n", + "ax = pt.plot_traces(offset=0, time_range=(0,0.5),fig_size=(10,4))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/notebooks/schizophrenia/create_network_d2oe.ipynb b/examples/notebooks/schizophrenia/create_network_d2oe.ipynb new file mode 100644 index 000000000..456ef67f4 --- /dev/null +++ b/examples/notebooks/schizophrenia/create_network_d2oe.ipynb @@ -0,0 +1,604 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d75f0e83-fc1b-41ea-91f5-9e1ec1a056ad", + "metadata": {}, + "source": [ + "# Setup and simulate Schizophrenia network" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "8432056a-edb2-4d63-92fd-1aa7345f3579", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Legacy config creation.\n", + "Creating config file\n", + "Network path: network/d2oe-10\n", + "Adding Striatum with 100 neurons (stay_inside=False)\n", + "Using cube for striatum\n", + "Neurons for striatum read from /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum\n", + "Adding neurons: FS from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs\n", + "Adding neurons: dSPN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/dspn\n", + "Adding neurons: iSPN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/ispn\n", + "Adding neurons: ChIN from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/chin\n", + "Adding neurons: LTS from dir /home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts\n", + "No directory $SNUDDA_DATA/neurons/striatum/ngf, skipping NGF cells.\n", + "Adding GPe with 0 neurons\n", + "Adding GPi with 0 neurons\n", + "Adding SNr with 0 neurons\n", + "Adding STN with 0 neurons\n", + "Adding Cortex with 0 neurons\n", + "Adding Thalamus with 0 neurons\n", + "Writing network/d2oe-10/network-config.json\n" + ] + } + ], + "source": [ + "from snudda import Snudda\n", + "\n", + "network_path = \"network/d2oe-10\"\n", + "\n", + "snd = Snudda(network_path=network_path)\n", + "snd.init_config(network_size=100, \n", + " snudda_data=\"../../../../bgmod/models/optim/schizophrenic/BGDATA/d2oe\",\n", + " honor_stay_inside=False,\n", + " overwrite=True, random_seed=1234)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9344757d-210c-41ed-abf4-80d99705b604", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Placing neurons\n", + "Network path: network/d2oe-10\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "No n_putative_points and putative_density, setting n_putative_points = 780\n", + "(this must be larger than the number of neurons you want to place)\n", + "Generating 780 points for network/d2oe-10/mesh/Striatum-cube-mesh-0.00010749824478388102.obj\n", + "Filtering, keeping inside points: 133 / 311\n", + "neuron_name = 'FS_0', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e160628_FS2-mMTC180800A-IDB-v20210210'\n", + "neuron_name = 'FS_1', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161024_FS16-mDR-rat-Mar-13-08-1-536-R-v20210210'\n", + "neuron_name = 'FS_2', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161205_FS1-mBE104E-v20210209'\n", + "neuron_name = 'FS_3', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/fs/str-fs-e161205_FS1-mMTC180800A-IDB-v20210210'\n", + "neuron_name = 'dSPN_0', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/dspn/str-dspn-e150602_c1_D1-mWT-0728MSN01-v20211026-d2oe-opt'\n", + "neuron_name = 'dSPN_1', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/dspn/str-dspn-e150917_c10_D1-mWT-P270-20-v20211026-d2oe-opt'\n", + "neuron_name = 'dSPN_2', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/dspn/str-dspn-e150917_c6_D1-m21-6-DE-v20211028-d2oe-opt'\n", + "neuron_name = 'dSPN_3', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/dspn/str-dspn-e150917_c9_D1-mWT-1215MSN03-v20211026-d2oe-opt'\n", + "neuron_name = 'iSPN_0', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/ispn/str-ispn-e150908_c4_D2-m51-5-DE-v20211026-d2oe-opt'\n", + "neuron_name = 'iSPN_1', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/ispn/str-ispn-e150917_c11_D2-mWT-MSN1-v20211026-d2oe-opt'\n", + "neuron_name = 'iSPN_2', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/ispn/str-ispn-e151123_c1_D2-mWT-P270-09-v20211026-d2oe-opt'\n", + "neuron_name = 'iSPN_3', num = 12, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe/neurons/striatum/ispn/str-ispn-e160118_c10_D2-m46-3-DE-v20211026-d2oe-opt'\n", + "neuron_name = 'ChIN_0', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/chin/str-chin-e170614_cell6-m17JUL301751_170614_no6_MD_cell_1_x63-v20190710'\n", + "neuron_name = 'LTS_0', num = 0, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts/LTS_180118_morp_9862_updated_20210301'\n", + "neuron_name = 'LTS_1', num = 1, neuron_path = '/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/WT/neurons/striatum/lts/LTS_180118_morp_9862_updated_April2022'\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 0.1s\n", + "Touch detection\n", + "Network path: network/d2oe-10\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "No d_view specified, running distribute neurons in serial\n", + "Processing hyper voxel : 21/64 (99 neurons)\n", + "Processing hyper voxel : 20/64 (94 neurons)\n", + "Processing hyper voxel : 17/64 (88 neurons)\n", + "Processing hyper voxel : 5/64 (87 neurons)\n", + "Processing hyper voxel : 4/64 (64 neurons)\n", + "Processing hyper voxel : 16/64 (61 neurons)\n", + "Processing hyper voxel : 1/64 (52 neurons)\n", + "Processing hyper voxel : 37/64 (50 neurons)\n", + "Processing hyper voxel : 25/64 (42 neurons)\n", + "Processing hyper voxel : 22/64 (37 neurons)\n", + "Processing hyper voxel : 0/64 (29 neurons)\n", + "Processing hyper voxel : 33/64 (26 neurons)\n", + "Processing hyper voxel : 24/64 (23 neurons)\n", + "Processing hyper voxel : 36/64 (22 neurons)\n", + "Processing hyper voxel : 9/64 (18 neurons)\n", + "Processing hyper voxel : 18/64 (17 neurons)\n", + "Processing hyper voxel : 6/64 (15 neurons)\n", + "Processing hyper voxel : 8/64 (9 neurons)\n", + "Processing hyper voxel : 32/64 (9 neurons)\n", + "Processing hyper voxel : 2/64 (5 neurons)\n", + "Processing hyper voxel : 26/64 (3 neurons)\n", + "Processing hyper voxel : 41/64 (2 neurons)\n", + "Processing hyper voxel : 40/64 (1 neurons)\n", + "Processing hyper voxel : 38/64 (1 neurons)\n", + "Processing hyper voxel : 10/64 (1 neurons)\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 6.8s\n", + "Prune synapses\n", + "Network path: network/d2oe-10\n", + "No file network/d2oe-10/pruning_merge_info.json\n", + "Read 95926 out of total 95926 synapses\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 7.4s\n" + ] + } + ], + "source": [ + "snd.create_network()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bb0f9b11-114d-49be-9642-de15b78e46d7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network/d2oe-10/network-synapses.hdf5\n", + "Assuming volume type: cube [cube or full]\n", + "Only using 20000 neurons of the connection data\n", + "Number of neurons: 99\n", + "Synapse row 0 - 0.0 % time: 0.0008830070000840351 seconds\n", + "Created connection matrix 0.0032698589993742644 seconds\n", + "Created gap junction connection matrix 6.120899979578098e-05 seconds\n", + "Creating population dictionary\n", + "Done.\n", + "Warning: the analysis cube specified by sideLen is too large.\n", + "!!! Setting sideLen to None\n", + "Calculating synapse distance histogram\n", + "Creating dist histogram\n", + "n_synapses = 2582, at 0\n", + "Created distance histogram (optimised) in 0.002497602000403276 seconds\n", + "Saving cache to network/d2oe-10/network-synapses.hdf5-cache\n" + ] + } + ], + "source": [ + "from snudda.analyse import SnuddaAnalyseStriatum \n", + "nas = SnuddaAnalyseStriatum(network_path, volume_type=\"cube\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "74a2d8e4-a904-453a-910d-317557197323", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plotting connection probability dSPN to iSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2304.]\n", + "P(d<5e-05) = 0.025089605734767026\n", + "P(d<0.0001) = 0.026504941599281222\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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PFW5A2Lt3r4t6ZLvhw4ebBXq7du2qsKAwUWUYLBFZ0ahRI7PnSqXSruMVCoUTe2PZvffei4EDB5ptS0lJqfHrOkoqleKtt94SnxsMBrPckrrK2e+Jsou+uoPw8HCMGTPGbJs7vN8AVBi95OgS2YrBEpEVTZo0MXtuz+35paWltTZSUjYfA3CPqR0AePrpp83yoDZs2GDz6vKuUv42e3sT6q9cuWL1fO7AXd9vQ4YMMZviO3DggFuMipHrMVgisqJ79+5mz0+cOGHzsefOnYNOp3N2lyzy8DD/KNubR+MqXl5eZnVvSktLa60OjkQiqdZx5ZOOjx07ZtfxSUlJVs/nDtz1/QZUHF0qO7pJVBkGS0RW9O3b1+z5li1bbD528+bNzu5OpcqPxjRt2rTWru2op556Cvfcc4/4fMuWLTh79myNX7fsnYTFxcU2HxcbG2v2/T1w4ECFuyYrk5eXhz179ojPGzVqhA4dOth87brCnd9v999/P4YOHSo+T0pKwo4dO1zYI3IHDJaIrGjbti169OghPv/9999x4MCBKo/Lzc3FZ599ZvN1HAkObt26ZfYLGIBNVcbrCg8PD7NcJUEQauWv/bJ3peXm5ppVKa/KuHHjxK9LS0uxZMkSm45bvHgxDAaD2XmqO8LliHPnztn1estSq9XYunWr2TZ3er8BlkeXHC1/QPUbgyWiKrz44otmz5999lmrIwklJSWYPHlyhVvMrZk5cyZ69+6NXbt22fWftlqtxtixY82m+1q3bl1h+rCuGz16tFl5gv/85z81fs2y9Y4MBgN+//13m4994YUXzO5A/PTTT/HTTz9ZPeann37CJ598Ij738PDAjBkz7Oix8yxfvhwdO3bE5s2bUVJSYvNxJSUlePrpp5GZmSlua9SoERISEmqimzWmR48eeOyxx8TnycnJSE9Pd2GPqK5jsERUhYkTJ5pNx12/fh39+/fH/v37K7RNSUnB0KFD8fPPPwOoeOeUNcePH8fDDz+MVq1aYdGiRTh16lSlf/0XFRVh06ZN6NKlS4Vf8suXL3fJaIUjJBIJFi9eXKvXLF/LZ9KkSfjqq6+QnJyM1NRUs7XLyueetWzZ0mx9vNLSUiQmJuK9995DUVGRWVudTof3338fiYmJZj/PV1991aVTcJcuXcKTTz6J6OhovP766zh69Gil05ElJSX46aef0LNnT3z33Xdm+xYsWGDTWoZ1zeLFi93uc0Iu5IIlVojczuXLl4XQ0NAKa1e1atVKGDFihJCYmCh0797dbN+zzz5r81pdZduVfchkMqF3797CsGHDhPHjxwsjR44UevbsKfj5+Vls/+abb1p9HeXXbouPj3fq98mWteGs6du3r8XXVRNrwxmNRuGee+6xaY0yS2vuGQwGYfDgwRZ/ZkOGDBHGjh0rJCQkCHK5vEKbBx54QNDr9U5/Tba+3yZNmlTpem89evQQHnnkEeGpp54SRo8eLfTr18/iawAgjB8/XigtLa30OuXXbrNnvTpb2LI2nDVPPvmkxdfFteGoPC9HAi2ihqJt27b49ddf8dBDD5lNwV27ds1iOYFhw4Zh1apVNk9PtGnTBocOHaowBadWq2262yowMBDvvvsuXnjhBZuuV1ctXrwYgwcPrpVrSSQSbN68GY8++mi1pmC8vLywY8cOTJo0ySyZX61W49dff630uFGjRmHjxo3w8fGpVr+doWXLlvDy8qowBafX63Hy5Mkqj5dKpXjjjTfw1ltvVbgzzp0sXLgQW7durXb+FjUc7vsuJ6plXbt2xYULF/Dss8/Cz8/PYptWrVph5cqV+PHHH+36Zfh///d/uHXrFj799FOMGjUK4eHhNh3Xpk0bLFy4EJcuXXL7QAkABg0aVKHAZk3q2LEj/vrrL3z66acYNmwYYmNjIZPJbJ6ekUql+Pbbb7Fz50707du30uMkEgl69eqFHTt2YNu2bdVeYNlZ5s2bhzt37uCbb77BuHHjzCqpWxMVFYXXXnsN58+fx4IFC8zyttxR27ZtMXHiRFd3g9yARCj/pywRVUmlUmHfvn1IT0+HVqtFs2bN0LZtW/Tq1ctpeRC3bt3C5cuXkZqaCoVCgaKiIvj7+yMwMBDNmzdHt27d3LKgYX2WnZ2N33//HVlZWSgsLERQUBAiIiIQFxdntnBwXXTnzh1cunQJ169fR2FhITQaDXx9fREYGIjIyEh06dIFUVFRru4mkUswWCIiIiKygtNwRERERFYwWCIiIiKygsESERERkRUMloiIiIisYLBEREREZAWDpWoSBAFKpZKLLxIREdVzDJaqSaVSISgoCCqVytVdISIiohrEYImIiIjICgZLRERERFYwWCIiIiKygsESERERkRUMloiIiIiscOtgSRAEbN++HQMHDkTTpk3h7++Pdu3aYdq0abh+/XqF9kqlErNmzUJMTAykUiliY2Px2muvQa1Wu6D3RERE5A4kghsXCpo9ezY+/PBDNG3aFI899hgCAwNx5swZ7NmzBzKZDH/88Qc6duwIANBoNOjfvz+Sk5ORkJCAbt264fTp09izZw969uyJQ4cOwdfX1+ZrK5VKBAUFQaFQIDAwsKZeIhEREbmYl6s7UF1ZWVlYsWIFYmJicObMGQQFBYn7PvroI8yaNQsffvghvv76awDAsmXLkJycjDlz5mDp0qVi2zfeeAPvvfcePvroI8ydO7fWXwcRERHVbW47DZeWlgaj0Yi4uDizQAkAhg0bBgDIyckBcHe6bvXq1ZDJZHjrrbfM2r711luQyWRYvXp17XSciIiI3IrbBktt2rSBj48Pjhw5AqVSabZvx44dAIBBgwYBAFJSUpCRkYG4uDgEBASYtQ0ICEBcXByuX7+OmzdvVno9vV4PpVJp9iAiIqL6z22DpZCQECxduhTp6elo3749nn/+ecyZMwcPPfQQ5syZgxdeeAEzZswAcDdYAu4GWJaYtpvaWfLuu+8iKChIfERHRzv5FREREVFd5LY5SwDwyiuvIDIyElOmTMHnn38ubu/fvz/GjRsHL6+7L0+hUABAhek6E1OCtqmdJXPnzsWsWbPE50qlkgETERFRA+DWwdKiRYvw9ttvY9GiRRg/fjwaNWqE5ORkvPLKKxgwYAC2bduG4cOHO+VaUqkUUqnUKeciIqL/yc3NRVFRkau7QQ2Uh4cHIiMjrbZx22Bp7969mD9/Pl555RW88cYb4vb+/fvjp59+QsuWLTF79mwMHz5cHFGqbOTIlH9U2cgTERHVjNLSUly+fBkKhQIeHm6bGUJuymg0ws/Pr/4GSzt37gQADBw4sMK+iIgItG/fHqdPn4Zara4yJ6mqnCYiIqoZGo0GRUVFCA4Ohre3t6u7Qw1McXExtFptle3cNowvLi4G8L/yAOXl5OTAw8MD3t7eaNOmDZo1a4YjR45Ao9GYtdNoNDhy5AhatGjBHCQiolqmUqlgMBgYKFGd5rbBUlxcHADgww8/rDC99vnnn+PWrVvo27cvpFIpJBIJpkyZArVajcWLF5u1Xbx4MdRqNaZOnVprfSciorsUCgUkEomru0Fkldsud1JaWooHH3wQhw4dQnh4OIYPH45GjRrh1KlT2LdvH/z8/HDgwAH06tULwN0RpLi4OJw5cwYJCQno3r07Tp06JS53cvDgQfj5+dl8fS53QkTkGKPRiKNHj8JgMEAul7u6O9QAmabhTHUZK+O2wRJwt1DkRx99hC1btuDy5csoLi5GkyZNMHDgQLz55pvo0KGDWXuFQoEFCxZg27ZtyMrKQtOmTZGYmIj58+fb/UFlsERE5BilUonjx48jICAAPj4+ru4ONUANIlhyJQZLRESOycjIwJkzZxAWFsapOHIJW4Mlt81ZIiIi92bKV2KgRHUdgyUiIqp1RqMR+fn5LPZLboHBEhER1TpTfSVfX19Xd4WoSgyWiIio1rG+ErkTBktERFTrmK9E7oTBEhER1SrmK5G7YbBERES1SqPRQKfTMV+J3AaDJSIiqlUqlQrFxcXMVyK3wWCJiIhqlVKpZL4SuRUGS0REVGuYr0TuiMESERHVGq1Wy/pK5HYYLBERUa1hvhK5IwZLRERUa5ivRO6IwRIREdUKQRCQl5fHfCVyOwyWiIioVpjWg2OwRO6GwRIREdUKU76Sj4+Pq7tCZBcGS0REVCuYr0TuisESERHVOEEQWF+J3BaDJSIiqnEajQZarZbBErklBktERFTj1Go185XIbTFYIiKiGqdQKACA+UrklhgsERFRjWK+Erk7BktERFSjuB4cuTsGS0REVKNUKhX0ej3zlchtMVgiIqIapVKpWF+J3BqDJSIiqjGm9eA4qkTujMESERHVGK1Wy/pK5PYYLBERUY1Rq9XQ6/UMlsitMVgiIqIaw/XgqD5gsERERDWC+UpUXzBYIiKiGlFUVMR8JaoXGCwREVGNUKlUKC4uZrBEbo/BEhER1QilUglBEJivRG7Py1knys7OxtmzZ5GWlob8/HwUFRXBz88PwcHBiI2NRZcuXRAWFuasyxERUR1mylfiqBLVBw4FS3v37sX27duxa9cu3Lhxo8r2sbGxGDp0KEaOHInBgwfzrw0ionqK+UpUn0gEQRDsOaCgoACff/45PvvsM9y+fVvcbstpygZHzZo1wwsvvIDp06ejcePG9nShTlAqlQgKCoJCoUBgYKCru0NEVKfcuXMHp0+fRmhoKP8wpjqruLgYWq0WgwYNstrO5mBJpVJh+fLlWLFiBdRqtVlw5O/vj549e6JDhw4IDg5GSEgIAgMDoVAokJeXh/z8fFy4cAF//vkntFrt/y4ukSAgIACvvPIKXn31Vcjl8mq+3NrHYImIqHJXr15FSkoKwsPDXd0Voko5NVhat24d5syZg+zsbDFZr1+/fhg9ejQGDBiAzp07w8Oj6lzx0tJSnD17FocOHcK2bdtw5MgR8Xzh4eFYtmwZJkyYYPurdCEGS0RElgmCgOPHj0OtVqNRo0au7g5RpZwaLJkCocDAQDz33HOYNm0aWrVq5XAnr1+/js8//xxffvkllEolPDw8UFJS4vB5awODJSIiy4qKinD06FFIpVL4+vq6ujtElbI1WLKpdIBMJsPChQtx48YNLFu2zCmBEgC0bNkSy5YtQ3p6OhYsWAB/f3+nnJeIiFzHVF+JlbupvrDpbrirV6/W6LxzYGAg5s2bh+eff77GrkFERLXDVF/JlvQMIndg0zu5thL0WIeJiMi9CYKA/Px8jipRvcKwn4iInEan00Gj0bC+EtUrDJaIiMhpVCoV9Ho9gyWqV5y23IklR44cwaFDh3Dr1i0AQGRkJB544AH079+/Ji9LREQuolKpmK9E9U6NBEuXL1/GhAkT8Oeff1rc3717d6xfvx7t27evicsTEZGL5OXlMV+J6h2nh/63bt1CfHw8/vzzTwiCgIiICLG6t5+fHwRBwJ9//okBAwaII05EROT+ioqKmK9E9ZLTg6VFixYhOzsbnTp1wu+//47bt28jKSkJ586dQ05ODj744AN4e3sjJycHixcvdvbliYjIRdRqNfOVqF5yerC0c+dOeHp64scff0S/fv3M9vn5+eGVV17Byy+/DEEQ8PPPPzv78kRE5CKsr0T1lc3v6CeffBI5OTlVtsvOzkZwcDBiYmIqbdOjRw8AQG5urq2XJyKiOi4/Px/e3t6u7gaR09kcLG3ZsgUdOnTA119/bbVdeHg48vLykJ6eXmmbkydPAmARSiKi+sJUX4lrwVF9ZHOwNGTIEOTn52Pq1Kl48MEHkZKSYrHdww8/DKPRiJEjR+L48eNm+3Q6HVauXIkVK1ZAIpHg4Ycfdqz3RERUJ6hUKuh0OuYrUb0kEQRBsLXxhg0bMHv2bOTk5MDX1xf/+Mc/MGfOHHh5/a8Cwe3bt9G9e3dxiq1Zs2aIioqCRqNBamoqtFotBEFASEgITp06hejoaOe/qlqgVCoRFBQEhUKBwMBAV3eHiMilUlNTcenSpVpbHovIGYqLi6HVajFo0CCr7ezKwhs/fjwuXryIiRMnQqfTYd68eejevTuSkpLENpGRkThw4AC6dOkCQRBw+/ZtHDt2DOfOnYNGo4EgCOjcuTP27dvntoESERGZy8vLY74S1Vt237IQHByMNWvWYO/evWjZsiXOnTuH/v37Y8aMGVCpVACADh064NSpUzhw4AAWLVqEadOmYdq0aVi0aBH279+P5ORkdOrUyWkv4vvvv8eQIUMQEhICX19ftGjRAmPHjsXNmzfN2imVSsyaNQsxMTGQSqWIjY3Fa6+9BrVa7bS+EBE1NDqdDmq1mvlKVG/ZNQ1Xnl6vx4IFC/DBBx+gtLQUkZGRWLlyJUaMGOHELlZOEARMnz4dX375JVq1aoWhQ4dCLpcjIyMDBw8exMaNG8WlVTQaDfr374/k5GQkJCSgW7duOH36NPbs2YOePXvi0KFDdn3QOQ1HRHRXbm4uTp48iZCQEJYNILdi6zScQ8udSKVSvPvuuxg3bhymTp2K48ePY/To0RgxYgQ+/vhjNGvWzJHTV2nlypX48ssv8cILL2DlypXw9PQ0219SUiJ+vWzZMiQnJ2POnDlYunSpuP2NN97Ae++9h48++ghz586t0f4SEdVHXA+O6juHRpbKEgQBn3zyCf75z39CpVIhMDAQS5cuxfTp051x+gqKiooQGRmJxo0b4/Lly2ZJ5pb6FhUVBaVSiaysLAQEBIj7NBoNIiIiEB4ejmvXrtl8fY4sERHddfLkSRQWFqJx48au7gqRXWokwdsaiUSCl156CRcuXMDf/vY3KJVKvPjii+jfvz8uXrzorMuI9uzZg4KCAowYMQKlpaXYvn07li5dis8//xxXr141a5uSkoKMjAzExcWZBUoAEBAQgLi4OFy/fr1CjlNZer0eSqXS7EFE1NDp9XrmK1G9V+1g6erVq0hKSsJff/0FnU4nbo+MjMSPP/6ILVu2oEmTJvjjjz/QrVs3zJ8/H8XFxU7pNAD8+eefAABPT0907twZo0ePxty5c/H888+jXbt2ePXVV8W2pppQbdq0sXgu0/bKakcBwLvvvougoCDxwTv5iIhYX4kaBruCpZKSEixatAhNmjRBu3btEBcXh65du6JRo0Z44oknkJaWJrZ9/PHHcenSJTz33HMwGAx4++230aVLFxw6dMgpHc/OzgYAfPjhhwgKCsLx48ehUqlw6NAhtG3bFh988AE+++wzAIBCoQAABAUFWTyXaRrN1M6SuXPnQqFQiA9ro1BERA0F85WoIbD53W0wGPDwww9j4cKFyMnJgSAI4qO4uBjbtm1Djx49cOnSJfGYwMBAfP755zh06BDat2+Py5cvY+DAgXjuueesBia2MBqNAAAfHx/88MMP6NmzJ2QyGe6//35s3boVHh4e+OCDDxy6RllSqRSBgYFmDyKiho7rwVFDYHOwtHLlSvz2228QBAGDBg3CTz/9hAsXLuDQoUOYPXs2vL29kZ+fjylTplQ4Ni4uDsnJyZg/fz58fHzw1VdfoUOHDtiyZUu1O24aJerRo0eFu+46duyIli1b4tq1aygsLBTbVhagmfKPKht5IiKiivR6PVQqFafgqN6zOVjasGEDJBIJBg0ahD179uDRRx9F+/bt0b9/f7z//vviKM7Ro0fNpuNMvL29MX/+fJw+fRr9+/dHVlYWxo0bV+2Ot2vXDgDQqFEji/tN24uKiqrMSaoqp4mIiCpSq9XMV6IGweZg6cqVKwCAsWPHQiKRVNg/duxY8WtridLt27fHwYMH8cUXXzg0lTVw4EAAsHinncFgwNWrVxEQEICwsDC0adMGzZo1w5EjR6DRaMzaajQaHDlyBC1atGDSNhGRHUz5SuVr3BHVNzYHS6Y6RpUtDVI2CLFW88hk6tSpZvlN9mrVqhUSEhJw9epVrF692mzf0qVLUVhYiJEjR8LLywsSiQRTpkyBWq3G4sWLzdouXrwYarUaU6dOrXZfiIgaovz8fJv+vydydzYXpYyPj8fhw4fRrl07nDhxAjKZzGz/jBkzsGrVKnh4eODOnTsICQmpkQ6Xde3aNfTr1w/Z2dnitODp06exb98+xMTEICkpCREREQDuBnNxcXE4c+YMEhIS0L17d5w6dUpc7uTgwYPw8/Oz+dosSklEDVlxcTH++OMPeHp6wt/f39XdIaoWW4tS2hwsbdmyBU8++SQkEgmaNGmCiRMnokWLFsjPz8eOHTuQlJQEAHjiiSfw73//2/FXYKObN29i3rx52LVrF/Ly8hAREYHhw4dj3rx5CA8PN2urUCiwYMECbNu2DVlZWWjatCkSExMxf/58yOVyu67LYImIGrK8vDycPHkSjRs35jQcuS2nB0sA8Nprr4mJ3GXzlkyn6NatG3777bdKk67rEwZLRNSQpaWl4eLFixX+KCVyJzWy3Mn777+P3bt3Y8SIEWjSpAk8PT0RGBiIPn36YMWKFTh69GiDCJSIiBo65itRQ2L3O33IkCEYMmRITfSFiIjcQHFxMVQqFdeDowaD9emJiMguXA+OGhoGS0REZBe1Wg2j0cjEbmowGCwREZFdmK9EDY1NwVJiYiKuX79eox3566+/MGLEiBq9BhEROaa4uBhKpZJTcNSg2BQsbdu2DR06dMDTTz9tcXkRR5w7dw5jxoxBt27d8NNPPzn13ERE5Fym9eCY3E0NiU3B0oMPPgiDwYB169ahY8eOGDBgANasWYOCgoJqXTQ3NxcrV65Ejx490KVLF3z33XcwGo148MEHq3U+IiKqHSqVivlK1ODYVcF77ty5SE1NFQtSenp64t5770WfPn3Qu3dvtG/fHsHBwQgJCYFcLodSqUR+fj7y8/Nx8eJFHDt2DMeOHcP58+dRWloqFrNs1aoVlixZgsTExJp7pU7GopRE1BAlJycjJycHwcHBru4KkcNqpIJ3SUkJvv76a3zwwQdISUm5e4IylbxtZbpku3bt8Oqrr2LSpElulyzIYImIGhqDwYA//vgDEokEAQEBru4OkcNqpIK3l5cXnnvuOVy6dAm7du3Ck08+CZlMBkEQbH4EBgZi/Pjx2LNnDy5evIhnn33W7QIlIqKGSKVSQa/XM1+JGpxqRSkSiQQJCQlISEgQ/9I4duwY/vrrL6SlpSE/Px96vR5SqRQhISFo0aIFOnXqhD59+qBv376c6yYickNqtRqlpaX8P5waHIeHdLy9vREfH4/4+Hhn9IeIiOqogoICBkrUILEoJRERVclgMKCwsJBTcNQgMVgiIqIqqdVq5itRg8VgiYiIqqRSqZivRA0WgyUiIqoS85WoIWOwREREVpWUlDBfiRo0BktERGSVqb4SF8+lhorBEhERWWXKV2IBYWqoGCwREZFVhYWFzFeiBo3BEhERVcqUr8QpOGrIGCwREVGl1Go1dDodk7upQWOwRERElWK+EhGDJSIisqKwsBAeHvxVQQ1bjf2pUFhYCJVKBblcjkaNGtXUZYiIqIaUlJSgoKCAU3DU4DntzwW1Wo1PPvkEAwYMgFwuR0hICGJjYxESEgK5XI6BAwdi1apVUKvVzrokERHVIK4HR3SXU4Kln376CW3atMHf//53HD58GBqNBoIgiA+NRoNDhw7hpZdeQps2bbBjxw5nXJaIiGqQSqVCSUkJ85WowXM4WFq3bh1GjRqF7OxsMTiSy+Xo2rUr4uLi0LVrVwQGBor77ty5gxEjRmD9+vXO6D8REdUQ5isR3eXQp+Dq1auYPn06SktLIQgCRo4ciaNHj0KhUODUqVM4fPgwTp06hcLCQiQlJWH06NEAAKPRiGnTpuHatWtOeRFERORcpaWlXA+O6L8cCpY++ugj6HQ6SCQSLFu2DNu2bUPv3r0ttu3Vqxe2bt2K5cuXAwD0ej0++ugjRy5PREQ1RKVSQafTsRglERwMlvbs2QOJRIIHHngAr776qk3HzJo1C/Hx8RAEAbt373bk8kREVEPUajVKSkrg7e3t6q4QuZxDwdLt27cBAI8//rhdx5nam44nIqK6hflKRP/j0CdBJpMBAJo0aWLXceHh4WbHExFR3VFaWsr6SkRlOBQstW7dGgCQnp5u13E3b94EALRp08aRyxMRUQ0wrQfHfCWiuxwKlsaMGQNBELBp0yYIgmDTMYIgYOPGjZBIJHjyyScduTwREdUAU30l5isR3eVQsDR9+nR07twZp0+fxiuvvGLTMbNmzcLp06fRpUsXTJs2zZHLExFRDWC+EpE5hz4NUqkUP//8M3r37o2PP/4Yffr0wXfffYeCggKzdoWFhdi6dSv69u2LlStXom/fvvj555/h4+PjUOeJiMi5TPWVOAVH9D821bBv2bKl1f0GgwGCIODEiRMYM2YMAKBx48YICAiARqMRgydBECCRSJCeno64uDhIJBIWpiQiqkPUajWKioogl8td3RWiOsOmYCktLQ0SiaTSvCSJRAKJRAIAYpv8/Hzk5+dXaAcAGRkZYuBERER1B+srEVVkU7DUvHlzBjZERA0A85WIKrJ5ZImIiOo3U30l5isRmeOfD0REBADQaDQoKipiMUqichgsERERANZXIqoMgyUiIgIAKBQK5qcSWWBTzpKtcnNz8fPPPyMpKQmZmZlQqVSQy+Vo1qwZevfujUcffRShoaHOvCQRETmB0WhEfn4+p+CILHBKsKTVavH666/j66+/hl6vt9jmiy++gFQqxZQpU/Dee+/Bz8/PGZcmIiInMK0HFxAQ4OquENU5Dk/D5ebmomfPnvjss8+g0+kgCEKlD51Oh08//RQ9e/ZEXl6eM/pPREROoFKpYDAYuLICkQUOjyyNHj0aFy9eBAD4+flh7NixGDp0KNq2bQuZTAa1Wo0rV65g9+7d+Pbbb6HVanHhwgWMHj0aBw4ccPTyRETkBEqlkvlKRJWQCJWV5bbB999/j9GjR0MikaBr167Yvn07YmJiKm1/48YNPP744/jzzz8hkUiwfft2PPbYY9W9vEsplUoEBQVBoVAgMDDQ1d0hIqo2o9GIo0ePwmAwcJkTalCKi4uh1WoxaNAgq+0cmob79ttvAQBhYWH49ddfrQZKABATE4Ndu3YhPDwcALBp0yZHLk9ERE5gqq/EYpREljkULB07dgwSiQTPPPMMgoODbTomJCQEzz77LARBwLFjxxy5PBEROYEpX4n1lYgscyhYys7OBgB07tzZruM6depkdjwREbmOqb4Sc5aILHMoWDLdNVFcXGzXcab2zv4r5r333hM/8ElJSRX2K5VKzJo1CzExMZBKpYiNjcVrr70GtVrt1H4QEbkLU30lTsERVc6hYKlZs2YAgMOHD9t13KFDhwAAkZGRjlzezLlz5zB//vxKa4RoNBrEx8fjo48+Qvv27fHKK6+gXbt2WL58OR588EHodDqn9YWIyF1oNBrodDoWoySywqFgacCAARAEAevXr8eZM2dsOiY5ORkbNmyARCLBgAEDHLm8yGAwYNKkSejatStGjhxpsc2yZcuQnJyMOXPmYPfu3Vi6dCl2796NOXPm4MSJE/joo4+c0hciIneiUqlQXFzMfCUiKxwKlqZMmQKJRAKDwYDBgwdj+/btVttv374dQ4YMQXFxMSQSCaZOnerI5UXvvPMOzp8/j6+//hqenp4V9guCgNWrV0Mmk+Gtt94y2/fWW29BJpNh9erVTukLEZE7MdVXYr4SUeUcKkrZvXt3TJ8+HZ999hny8/ORmJiIli1bYsiQIWjbti0CAgKg0WiQkpKCX3/9FdeuXYMgCJBIJJg+fTq6devm8As4deoU3nnnHSxatAj33HOPxTYpKSnIyMjA0KFDK0zTBQQEIC4uDrt378bNmzcRHR3tcJ+IiNwB85WIbONwBe+PP/4YSqUSGzduBABcv34dX3zxhcW2pvqXTz31FFauXOnopaHX6zFx4kR07doVr7/+eqXtUlJSAABt2rSxuL9NmzbYvXs3UlJSKg2W9Hq92bp3SqXSgZ4TEbmeqb6Sv7+/q7tCVKc5vDach4cH1q9fj82bN6N79+5W14a77777sHXrVqxbtw4eHg5fGvPmzUNKSgq++eYbi9NvJgqFAgAQFBRkcb+pArepnSXvvvsugoKCxAdHoIjI3anVauYrEdnA4ZElk8TERCQmJiI9PR3Hjh1DZmYmVCoV5HI5mjZtit69e6N58+bOuhyOHj2K5cuXY8GCBejYsaPTzluZuXPnYtasWeJzpVLJgImI3BrrKxHZxqFgad26dQCAiIgIJCQkAACaN2/u1KDIkpKSEkyaNAmdO3fGG2+8UWV704hSZSNHpim1ykaeAEAqlXJen4jqDeYrEdnOoWBp8uTJkEgk+Mc//iEGS7VBrVaLeUimwpjl9e3bF8DdxX5Nid+mY8qrKqeJiKi+0Wq1zFcispFDwZJMJoNGo6n0LrSaIpVK8eyzz1rcd+jQIaSkpGD48OEICwtDbGws2rRpg2bNmuHIkSPQaDRmd8RpNBocOXIELVq04LQaETUYpvpK1kbUieguh4Klpk2b4urVqzAYDM7qj038/PwqrYs0efJkpKSkYO7cuejTp4+4fcqUKVi0aBEWL16MpUuXitsXL14MtVqNN998s8b7TURUV7C+EpHtHAqWBg4ciKtXr+LEiROYMGGCs/pUI15//XX8+OOPeO+993D69Gl0794dp06dwp49e9CzZ0+8/PLLru4iEVGtEASB+UpEdnDo/v1p06bBw8MDa9euxe3bt53VpxoREBCAgwcP4uWXX8bFixfxwQcf4NKlS5g9ezZ+++03+Pn5ubqLRES1QqPRQKvVMlgispFEMFWKrKZly5bhjTfeQPv27fHtt9+ic+fOzupbnaZUKhEUFASFQiHWaSIicgdZWVk4ffo0wsLCOA1HDVpxcTG0Wi0GDRpktZ3DpQMiIiLw8MMPY+fOnejevTv69++P+++/H1FRUTaN1kycONGRLhARkZ1MZVQYKBHZxqGRJQ8PD7MPm2ndN5svLpGgpKSkupd3KY4sEZE7EgQBSUlJKCoq4p1w1ODVysgS8L/13ip7TkREdYdWq4VWq2WeJpEdHAqWvvnmG2f1g4iIagHrKxHZz6FgadKkSc7qBxER1QLT8k7MVyKynUOlA4iIyH0IgoC8vDyWDCCyU7VHlm7fvo2zZ89CoVAgKCgInTp1QlRUlDP7RkRETmRaD87X19fVXSFyK3YHS8ePH8crr7yCpKSkCvv69OmDjz76CL169XJK54iIyHlUKhX0ej3v4CWyk13TcHv27MGAAQOQlJQEQRAqPI4ePYr4+Hjs3r27pvpLRETVpFKpuB4cUTXYHCypVCpMmjQJOp1OLA/QunVr9OvXD61btxbb6fV6TJo0SUwiJCIi1zPlK/n4+Li6K0Rux+Zgaf369bhz5w4kEgl69OiB8+fP48qVK/j9999x5coVXLhwQZx+y8nJwfr162us00REZJ+ioiKuB0dUTTYHSzt37gQAhIaGYvfu3ejQoYPZ/vbt22Pnzp0IDw83a09ERK5nyldisERkP5uDpbNnz0IikWDixIlo3LixxTaNGzfGxIkTIQgC/vrrL6d1koiIHMP6SkTVZ3OwlJ+fDwDo2rWr1XZdunQBAOTl5VW/V0RE5DSsr0TkGJuDJY1GAwCQy+VW28lkMgB358eJiMj1mK9E5BhW8CYiqudM68ExWCKqHgZLRET1nEqlgiAIzFciqia7gyV+2IiI3EdJSQmys7M5qkTkALuXOxkxYoRN7QRBgKenp9U2EokEJSUl9naBiIhslJubC6VSieDgYFd3hchtVWshXVMFb0vKltK31o6IiGqWIAjIzMyERCKp8o9XIqqcXcGSLcEPAyQiorpBoVAgLy+vyruYicg6m4Mlo9FYk/0gIiIny8rKgsFgYL4SkYN4NxwRUT1UVFSErKwsBAQEuLorRG6PwRIRUT2Uk5MDrVYLf39/V3eFyO0xWCIiqmdKS0tx+/ZtSKVSlnshcgIGS0RE9Uxubi4UCgUTu4mchMESEVE9IggCMjIyWC6AyIkYLBER1SNKpZLlAoicjMESEVE9kpWVxUVziZyMwRIRUT2h0+lYLoCoBjBYIiKqJ7Kzs6HVahksETkZgyUionrAVC7Ax8eH5QKInIzBEhFRPZCXl8dyAUQ1hMESEZGbY7kAoprFYImIyM2xXABRzWKwRETk5u7cucNyAUQ1yMtZJ8rJycHevXtx7tw5FBQUQKfTVXmMRCLBV1995awuEBE1ODqdDpmZmVwwl6gGORwsqdVqvPrqq1izZg0MBoPdxzNYIiKqvpycHGg0GoSHh7u6K0T1lkPBksFgwNChQ5GUlARBEOw+nre3EhFVn6lcgFQq5f+nRDXIoWDps88+w9GjRyGRSCCTyfDiiy9iyJAhiIqK4tw5EVENM5ULaNSokau7QlSvORQsffvttwCAoKAgHD16FO3atXNKp4iIyDpBEJCZmQkA8PJyWvopEVng0N1wFy9ehEQiwfTp0xkoERHVIpVKhdzcXMhkMld3hajecyhYKi4uBgB07drVGX0hIiIbZWVlQa/Xw9fX19VdIar3HAqWoqKiAAB6vd4pnSEioqrp9XpkZmZywVyiWuJQsJSQkAAAOHnypFM6Q0REVcvOzoZWq2VtJaJa4lCwNHPmTPj6+mLt2rXIyspyVp+IiKgSpnIB3t7e8PDgIgxEtcGhT1qbNm3w+eefQ6PRYOjQobh27Zqz+kVERBbk5+dDoVBwHTiiWuTQ/abr1q0DADz++OPYvHkz7rnnHgwbNgx9+/ZFaGioTX/1TJw40ZEuEBE1KJmZmRAEgeUCiGqRRKhO6e3/8vDwMKsaKwiCXVVkJRIJSkpKqnt5l1IqlQgKCoJCoUBgYKCru0NEDYBSqcSJEyfg6+vLu+CInKC4uBharRaDBg2y2s7hP03Kx1oOxF5ERGRFdnY29Ho9K3YT1TKHgqVvvvnGWf0gIiIr9Ho9MjIyeAcckQs4FCxNmjTJWf0gIiIrcnJyoNFoEBoa6uquEDU4vO+UiKiOMxqNLBdA5EL81BER1XH5+fkoLCxkuQAiF6mRYOnOnTtITk7G4cOHkZycjOzsbKdf4/bt21ixYgUSEhLQvHlz+Pj4ICIiAqNHj8axY8csHqNUKjFr1izExMRAKpUiNjYWr732GtRqtdP7R0TkLBkZGSwXQORCTvvkpaen41//+he2b9+O9PT0CvubN2+Oxx9/HDNnzkR0dLTD1/v444/x3nvvoVWrVkhISEBYWBhSUlLwww8/4IcffsCmTZswZswYsb1Go0F8fDySk5ORkJCAsWPH4vTp01i+fDkOHjyIQ4cO8VZcIqpzVCoVcnNzIZPJXN0VogbLoTpLJt988w1mzpwJrVYLwHL5AFP9JX9/f3z88ceYPHmyQ9fcvn07QkJCEB8fb7b98OHDGDRoEGQyGTIzMyGVSgEA8+fPx6JFizBnzhwsXbpUbP/GG2/gvffew5IlSzB37lybr886S0RUG65evYqUlBSEh4e7uitE9Y6tdZYcDpa++eYbPPvss5BIJGJRyvbt26Nt27aQyWRQq9W4cuUKLl26JAZREokEX331lcMBU2WGDh2KPXv24MSJE+jRowcEQUBUVBSUSiWysrLMVurWaDSIiIhAeHi4Xcu1MFgioppWXFyMpKQkGI1G5isR1QBbgyWHcpYyMzPx0ksvic+nT5+O1NRUnD9/Ht9//z3Wr1+P77//HufPn0daWhqef/55eHh4QBAEvPTSSzW2+K63tzcAiPP7KSkpyMjIQFxcnFmgBAABAQGIi4vD9evXcfPmzUrPqdfroVQqzR5ERDXJVC6g/P9bRFS7HAqWVq1aBa1WC4lEgv/7v//DqlWr0Lx5c4tto6Oj8emnn2L16tUAAK1Wi1WrVjlyeYvS09Oxd+9eNG3aFJ06dQJwN1gC7i78a4lpu6mdJe+++y6CgoLEhzPyroiIKsNyAUR1h0OfwN27d0MikSAhIQHPPPOMTcdMnjwZDz30EARBwK5duxy5fAUGgwETJkyAXq/He++9B09PTwCAQqEAAAQFBVk8zjSNZmpnydy5c6FQKMSHtVEoIiJHmcoFMLGbyPUcCpauX78OABgxYoRdxz322GNmxzuD0WjE5MmTcejQIUydOhUTJkxw2rkBQCqVIjAw0OxBRFRTsrKyYDQaxbQCInIdh4IllUoFAAgODrbrOFN7Z9U3MhqNeOaZZ7Bp0yaMHz8en3/+udl+04hSZSNHpvyjykaeiIhqk1qtRnZ2NkeViOoIh4KlkJAQAEBqaqpdx6WlpQGwP8iyxGg04umnn8batWsxduxYrFmzpsL8flU5SVXlNBER1aY7d+5Ap9Ox9htRHeFQsNSxY0cIgoD169fDaDTadExpaSnWr18PiUSCjh07OnJ5MVBat24dxowZg/Xr14t5SmW1adMGzZo1w5EjR6DRaMz2aTQaHDlyBC1atGDSNhG5XHFxMTIyMuDv7y/WpyMi13IoWBo+fDgA4MKFC3jhhRcsFqMsSxAEvPjiizh37hyA/+UuVYdp6m3dunVITEzEhg0bLAZKwN26TlOmTIFarcbixYvN9i1evBhqtRpTp06tdl+IiJwlJycHarWa5QKI6hCHilLqdDq0bdsWt2/fBgB07twZr776KoYMGWJWbTYnJwd79uzBBx98gDNnzgAAoqKicOXKFbHCtr0WLFiAhQsXQiaT4e9//7vFNZNGjBiBrl27Arg7ghQXF4czZ84gISEB3bt3x6lTp7Bnzx707NkTBw8ehJ+fn83XZ1FKInI2o9GIkydPQqFQOCVNgYiss7UopUNrw/n6+mLbtm148MEHodVqcfbsWUycOBEAIJfLERAQAI1GIyaCA3dHlwICArB9+/ZqB0rA//Ke1Go13nnnHYttYmNjxWApICAABw8exIIFC7Bt2zbs378fTZs2xezZszF//ny7AiUioppQUFCAwsJC/gFGVMc4ZW24s2fP4qmnnsL58+fNT/7fJVDK6tSpEzZs2CAWjHRX7jaypFKpqnX3oUwm4zILRLXk3LlzuHnzJteBI6oltTKyZNK5c2ecPXsWP//8M7Zv345jx44hMzMTKpUKcrkcTZs2Re/evTF69Gg88sgjTFp0gT///BMHDx60+7j4+HgMGDDA+R0iIjOmcgH844So7nHKyFJDVF9GlnJzc7F9+3aMGjUKoaGhFfZzZImodly7dg1XrlxBWFgY/6AkqiW1OrJEdZ9cLrca9ISGhqJp06a12CMiMjEYDMjIyICvry8DJaI6iKszEhG5mKlcACt2E9VNdo0sXb9+Ha+++ioA4N57761Qs6gq//znP3HhwgUAwIoVK9C8eXO7jiciqm+MRiMyMjLg5eVVYfUBIqob7AqW/vGPf+CHH35AQEBApbfrW/PUU0+hV69e0Gq1CAwMxJo1a+w+BxFRfVJQUID8/Hy3yH0kaqhs/jMmMzMTW7duhUQiwUsvvYQOHTrYfbEOHTrg73//OwRBwKZNm5CdnW33OYiI6pOsrCwYjUZ4e3u7uitEVAmbg6XNmzfDaDTCx8dHnIqrjtmzZ8PX1xelpaXYvHlztc9DROTuNBoNsrOzmatEVMfZHCz9/vvvAIAHHnjAoTL8jRs3Fuv2HDp0qNrnISJyd3fu3EFRURF8fX1d3RUissLmYCk5ORkSicQpBQrvv/9+CIIgrhNHRNTQmMoF+Pn5sVwAUR1nc7CUm5sLAGjWrJnDFzWdIycnx+FzERG5o5ycHKhUKk7BEbkBm4OloqIiAHcXpHWU6RxardbhcxERuRtBEFgugMiN2Pwpbdy4MYD/jTA5Ii8vDwDQqFEjh89FRORuCgoKUFBQwFElIjdhc7AUFhYGALh48aLDFzUVpuTK2kTUEGVlZaGkpAQ+Pj6u7goR2cDmYKlnz54QBAG7du1y+KK7du2CRCJBjx49HD4XEZE70Wg0uHPnDkeViNyIzRW8Bw0ahDVr1uDq1av4/vvvMXLkyGpdcPv27UhJSYFEIqlylV+i8lQqFdRqtd3HyWQyqwsJE9WW7OxsFBUVcWSdyI3YHCyNHDkSoaGhyMvLw4svvogePXogOjraroulp6djxowZAICQkBCMGjXKvt5Sg/fnn3/i4MGDdh8XHx/vlLIXRI5guQAi92RzsOTv74/XX38dr7/+Ou7cuYMHHngAmzZtQt++fW06/ujRoxg3bhyysrIgkUjw2muvwd/fv9odp4bpvvvuQ7t27Spsz83Nxfbt2zFq1CiEhoZW2M8pD6oLcnNzoVKpHCrsS0S1z66FdGfNmoW9e/diz549SE9Px/3334+HH34YEydORFxcXIUaTBkZGThy5AjWrl2LXbt2QRAESCQSDB482KElU6jhksvlVqfTQkND0bRp01rsEZFtTOUCPDw84Onp6eruEJEd7AqWPDw8sHnzZvztb38Tlz/55Zdf8MsvvwAApFKpWA6gsLAQer1ePFYQBABAXFwcNm/ezCFoImpQCgsLkZ+fz9w5IjdkdzW0oKAg7N+/H6+++ip8fHwgCIL40Ol0yMrKQlZWFnQ6ndk+qVSK2bNnY//+/ayvREQNDssFELmvapWO9fT0xLJly3D9+nW8+eabuO+++yxWofXw8MB9992HN998E9euXcP7778PLy+7BrOIiNyeVqtluQAiN+ZQ5NK0aVO8/fbbePvtt6HVapGVlYW8vDwIgoCQkBBEREQ4ZXkUIiJ3lp2dDa1Wy3IBRG7KacM8/v7+aNmyJVq2bOmsUxIRub2SkhLcvn0bvr6+zNUkclNcwbGO0Gq1OHv2LLKyslBaWurq7hCRk5jKBXAKjsh9MYGojtDr9cjKykJGRgZCQkLQvHlzhIWFcUVyIjfGcgFE9QODpTpEEAQEBQWhoKAA+fn5CA0NRXR0NEJDQxk0EbmhwsJC5OXlsVwAkZtjsFTHeHl5ISQkBAaDAbm5ucjNzUVoaCiaN2+O0NBQp+c8qD76CI++/z5UGg2aLlvm1HMTNXQsF0BUPzBYqqO8vb0RGhoqBk15eXkICwtDdHQ0QkJCnBI0ZS5eDNX770MCQPX++8iUy9H0rbcc7zwRoaioCHfu3OEdwUT1AIOlOs4UNBUXFyM7Oxs5OTkIDw9HdHQ0goODqx00ZS5ejIx588y2mZ4zYCJyXHZ2NoqKihAWFubqrhCRgxgsuQkfHx8xaMrKyjILmho3bmxX0GQpUDJhwETkOFO5AKlUynIBRPUAgyU34+Pjg7CwMOj1emRkZCA7OxtNmjQRg6aqWAuUTBgwETkmNzcXSqUSwcHBru4KETkBgyU3JZVKER4ebhY0RUREIDo6GkFBQRaPsSVQMmHARFQ9pnIBEomE5QKI6gkGS25OKpUiLCwMOp0ON2/exJ07d9C0aVNERUUhMDBQbGdPoGTiTgET7+qjukKhUCA/P9/s80dE7o3BUj3h6+sLX19fFBUV4caNG8jKyhKDJvWKFXYHSibuEDDxrj6qS7KysmAwGFgugKgeYbBUz/j5+cHPzw9FRUVITU1F/rJl8F2zxqFz1uWAiXf1UV1SVFSErKwslgsgqmckgiAIru6EO1IqlQgKCsKRpk0hc0J1baPRiGKDAR4eHnDavTMazd2Hk3jI5fCsQ1MLpUoljCpVpfubLVrEgIlq1Y0bN3D+/HmEh4fzLjgiN1BcXAytVotBgwZZbceRJQcZMjNhcNK56noqqFGlshqc1DUcYaLaVFJSgoyMDPj6+jJQIqpnGCw5yLtpU3hzZKlWVTWiVBYDJqoteXl5UCgULBdAVA8xWHJQx0uXnHLXS0FBAY4fP363KrczF81dvRr4/HOHT1NXprTq+1195J5YLoCofuNS9vXdlCnA9OkOncKdAyWTjHnzkLl4sZN7RHSXQqFAXl4e5HK5q7tCRDWAI0sNwZQpd/+txghTfQiUTOrqCFNl91hY2l5TbQHAw8MDXl78L6EqRqMROp0ORUVFKCoqgkajgUKhgMFggFQqdXX3iKgG8G64anKLu+HKszOHSSKTwTMoqOb6UwUBAATB+YnlAQF3H/b2xWyD4x8bh89QAx9diURy9z0okdxNUpZIIPnv9urwjohAh5MnndvJWiIIAvR6vRgUabVaqNVqqFQqGAwGFBcXi229vb0REBAAb29vF/aYiOzFu+FqSX2+G05Qq1GiVru6G85XjcT3mggY6+r9UgKcEMi5GYPBIAZFRUVFUKlUUKlU0Ov1MBgMKC0tBQB4eXnBx8cHvr6+kMvl8HBmfiER1VkMlhxUp++Gq0xVwcJ/R14EAILRCEEQ4OHhAQ9T4up/RzSE8v+W2WciPrM2CvLf0YtKt2k0kGi1Vl+SXaoxstRQVfgZl/k5mkabrI1GeUdE1HqfrSktLTULijQaDZRKJXQ6HYqLi1FSUgIA8PT0hLe3tzhixKRtooaNwZKD6vzdcJWp7C656dPFHCfJfx9GoxEKpRLFxcWQSCT/C57++wuy7L/lvy77vEb6a68yr4+qJin3r4nRaERJSQkMBoP4r9FoBPC/QMPHxwcBAQG4evUq/Pz84OvrC6lUCl9f3xrPjRIEwSyvSKvVQqlUQqPRwGAwwGAwQBAESCQS+Pj4wNvbG3K5HF5eXqyRREQVMFhqqCwlfVcSSHh4eKBRo0a106/KOJCkLnIwUDIajSgtLTV7mIIGa/tMX5tGXiwFlFUFnrZs8/T0NNtXkzw8PODj42Nx/TNT8GQwGJCTk4PMzEyxP97e3vDy8oKfnx/kcjn8/f3FdQ2lUimkUqldfRcEAcXFxRWm0NRqtTiFZgriTCNF/v7+8Pb2ZlBERDZjsNSQTZkCnU4H6Zo10E+eDN+6PuIyZQp0JSXIXb0auQCyAeQAyP3vQw/ACKC03MMIoKRJE5QePgzjwYPVDnjcjT2Bl6enJyIjI9GqVSu0atUKLVu2ROvWrasVJHt5eVkcOSo7GqVWq1FQUFDpaJRMJqswGgXALChSq9VQKpXQ6/UoLi42yyvy9vaGVCplXhEROQWDpQZOP2EC9sbG4v7774evC/tRUlKC3Nxc5ObmIicnx+IjNzcXSqWyehe4c+fuowExBSK2Bno5OTlITk422xYSEiIGUKZHixYtIJPJ7O6Po6NRAMRpP9NUsGkKzc/Pj2UPiKjG8H8XqlFGoxH5+fkVgiDT8+zsbOTm5qKgoKDS+j/O5OnpKT5MdYVMIyvl93l6elrd7+XlZda2qv2m74fxv0nzpaWlEARBfF52X1Xbyu6z57jy20x90Ov1yMvLq/D9ysvLQ15eHo4fP262vWnTpmajUK1atUJsbKw4AmQvW0ajAEAmkzGviIhqHYMlqhZBEKBUKsXAJzs72ywIMn2dm5vrlCksHx8fhIWFiY/Q0FCEpaYiLCkJYQBCAfjhbvkF08PjmWfg9cwzYsBSG7k87kylUuHatWu4fv06rl27hmvXruHq1asoLCys0DYzMxOZmZn4/fffxW0eHh6IiopCq1at0Lp1azGYio6Orvaoj7XRKCKi2sJgqYHQ6XTQ6/UVtqv/W0dJXa6ekiAIUCgUyMrKwu3bt3Hjxg3cuXPHLCAqW5Svujw9PREaGorQ0FCEh4ffDYLKB0VhYQgMDLQc6NhwV19tsXabvaVb7ss/L7vdFUGdXC5H165d0bVrV7Pt+fn5YvBU9qEpV37CaDQiPT0d6enp2L9/v7jd29sbsbGxZqNQrVq1QrNmzZhPRERugcFSA3Hjxg2kpKRU2G40GlFYWIjNmzebjQbl5uaiqKio2teTSCQIDg42C35MAVHZIKhx48bV+oUpJmCPHw+P4mL4fP21uK9o0iToRo+GkJ8P4G6gYilwsTTtZwpSTLeVW2LaV/748sFOZcFP+ePK989Sm/LXK3++8n0t39baFKfpWNPUYdmHp6cngoODERwcjJ49e5qd/86dOxUCqNTU1ApBucFgQEpKSoX3n6+vr1nwZBqNCg0N5QggEdUpDJYaiPDwcKhUKvEv/5s3byI9PR23bt0S80FsFRQUVCEIKjsaFBYWhpCQELunXsrfjVb+uUQiEW8HN+UBSSQSeI4aBV+tFkHffgvVuHHApEnwLjPlJpFI4Ofnh4CAgAq375d/mNpb22ZLm8qOszT65OptpvwlU9l/vV4PnU5ndhegRCKpEEg1adIEERERiIuLE3+GpaWluH37Nq5fv46rV6+KQdSNGzcqTMfqdDpcuHABFy5cMNseGBhYIR+qVatWCAoKYhBFRC7R4NaGO3HiBObPn48//vgDBoMBnTp1wqxZs/DEE0/YdR7T2nAKhcLpRSmrOzUhCALy8/ORlpaG1NRU3LhxQ/w6KyvLrnOFh4cjNjbW7NGsWTOEhobalcRrSiKuLAgqO0pjyisyJUl7eXmJt41LpVL4+Pjg7NmzOHXqlL3fGsTHx2PAgAF2H9cQlZaWQq/Xiw9THSOtVgutVivekWa6Kw24Oyrl7e0tlgAwjUqZGAwG3Lhxo8JI1O3bt21O7JdKpQgJCTF7hIaGVngeHBzMHCcisgnXhrNg//79GDp0KHx9ffHkk09CLpdj27ZtGDNmDG7evInZs2e7uos2KSkpQUZGhhgIpaWliYGRPbfWe3p6onnz5hWCotjYWARYWQ7EdDdVZUGQqQCjKRAqf6dY2UKEPj4+Yl2cso/K7o4KDg5Gjx497P6eVedW94bK9DPy9/evsE8QBBgMhgrBlFarhUajgU6nszgq5enpifDwcDRr1gwDBw4U7zLU6XRITU2tEETdsVDmQa/XIyMjAxkZGVW+hsDAQIvBVPkgKygoiHlTRFSlBjOyVFJSgvbt2+PWrVtISkoSk1gVCgV69eqFtLQ0XLlyBTExMTadrzZGlrRardnoUFpaGtLS0nDz5k27ps4CAgLQokWLCgFRZGQkPDw8KtyCbulRdgSobCFD08PHx0ccBTLVvikf/Jj+5VRK/VVaWori4mKzQEqn00Gj0UCr1YrFI03LjQCWc6W0Wq14V97169eRlpaG3Nxc5OXlWbw7r7o8PT0tBlNlgypTYOXn5+e06xJR3cCRpXL27duHa9eu4emnnza72ycoKAhvvvkmJk+ejLVr12LevHm13rfs7GwkJSXh119/RXZ2thggWfrr2pomTZqgefPm4iMqKgqRkZFo1KiRWY6KKegpKCj4X95Pmdvry470mG7bNv0SKx/8mL7mX+cE3A0+/Pz8LAYWgiCgpKTE4hSfWq0WF7PVarUoKSlBs2bNKoxESSQSlJaWorCwEPn5+SgoKEBeXh7y8/ORn58vfp2Xl4fc3FzodDqr/S0tLUV2djays7OrfG3+/v6VBlWNGzeu84vtBgUFoVOnTq7uBpFbajDB0oEDBwAACQkJFfYNHToUAHDw4MFKjzf9525S7UrSFsyePRsbNmywqa2XlxciIyMRFRWFqKgos+AoICDAbK2x8gGPKafElE9S9uuy/7IeEdUEiUQivictTYsajUazUSnTwzTFZ1qSxsPDA40bN0ZQUBBatGghTgsDqPC1TqcTg6qCggKzr8s/TMdVxpSzdfPmTed/c2pB9+7d8dlnn7m6G0R1iq11ABtMsGS6bblNmzYV9kVEREAmk1m8td7k3XffxcKFC2ukb+3bt6+wTSaTISYmBrGxseI6XW3btkWLFi0glUotBjnlAyEGPOROPDw8xFw2S6qqSG7L15a2maYFy1aVL1tGw1TF3DRiVb4mmbsoKSlx6hQmUX1hKT+zvAYTLCkUCgB3h6ItCQwMFNtYMnfuXMyaNUt8rlQqER0d7ZS+DRgwADNnzkSLFi3Qvn17dOjQAU2bNuXK6ERlmKZ6XTHdVTbIKioqQmZmJrKyssRHTk5OrSzX44jo6Gj07t3b1d0gqnNsSSNpMMGSo6RSKaRSaY2cOy4uzqxWDRHVLWXv6vT29kZgYCDatWvn6m4RUS1pMFm5phGlykaPTHe3EREREZXVYIIlU66SpbykrKwsqNVqi/lMRERE1LA1mGApPj4eALBnz54K+3bv3m3WhoiIiMikQRWlbNeuHW7fvl1pUcrLly8jNjbWpvM5uyglERER1U0NJsHby8sLq1evxtChQ/HAAw+YLXdy48YNLF++3OZAiYiIiBqOBjOyZHL8+HGLC+mOGTPGrvNwZImIiKhhaHDBkrMwWCIiImoYGkyCNxEREVF1MFgiIiIisoLBEhEREZEVDeZuOGczpXoplUoX94SIiIgcIZfLra7FymCpmvLy8gDAaYvpEhERkWtUdbMWg6VqCg4OBgCkp6dzTTmicpRKJaKjo3Hz5k3eLUpUBj8bdZNcLre6n8FSNXl43E33CgoK4hueqBKBgYH8fBBZwM+Ge2GCNxEREZEVDJaIiIiIrGCwVE1SqRTz58+HVCp1dVeI6hx+Pogs42fDPXG5EyIiIiIrOLJEREREZAWDJSIiIiIrGCwRERERWcFgiYiIiMgKBkt2OnHiBB555BE0atQIAQEB6NOnD7Zs2eLqbhE51YYNGzBt2jT06NEDUqkUEokEa9asqbS9UqnErFmzEBMTA6lUitjYWLz22mtQq9UW2xuNRnz88cfo1KkT/Pz8EBYWhrFjx+L69es19IqInOP27dtYsWIFEhIS0Lx5c/j4+CAiIgKjR4/GsWPHLB7Dz0c9IJDN9u3bJ3h7ewtyuVyYOnWqMGvWLCEmJkYAICxfvtzV3SNyGtP7OjQ0VPz6m2++sdhWrVYLXbt2FQAICQkJwpw5c4SEhAQBgNCzZ0+hqKiowjFTpkwRAAj33nuv8Prrrwvjx48XfHx8hODgYOHKlSs1/OqIqm/OnDkCAKFVq1bCs88+K7zxxhvC6NGjBU9PT8HDw0P49ttvzdrz81E/MFiykcFgEFq1aiVIpVLh9OnT4vbCwkKhbdu2go+Pj5CWlua6DhI50a+//iq+n999912rwdK8efMEAMKcOXPMtpt+qSxZssRs+759+wQAwgMPPCDo9Xpx+y+//CL+QiGqq7Zt2yYcOHCgwvZDhw4J3t7eQuPGjQWdTidu5+ejfmCwZKPdu3cLAISnn366wr41a9YIAISFCxe6oGdENctasGQ0GoVmzZoJMplMUKvVZvvUarUgk8mEli1bmm0fO3asAEA4ePBghfMNGDBAACDcuHHDqa+BqDaYRoxOnDghCAI/H/UJc5ZsdODAAQBAQkJChX1Dhw4FABw8eLA2u0TkcikpKcjIyEBcXBwCAgLM9gUEBCAuLg7Xr1/HzZs3xe0HDhwQ95XHzxK5M29vbwCAl9fdNer5+ag/GCzZKCUlBQDQpk2bCvsiIiIgk8nENkQNhbXPRdntpnYajQaZmZlo0aIFPD09q2xP5C7S09Oxd+9eNG3aFJ06dQLAz0d9wmDJRgqFAgAQFBRkcX9gYKDYhqihsOVzUbadve2J3IHBYMCECROg1+vx3nvviYEOPx/1B4MlIiKiajIajZg8eTIOHTqEqVOnYsKECa7uEtUABks2MkX6lUX0SqWy0r8GiOorWz4XZdvZ256oLjMajXjmmWewadMmjB8/Hp9//rnZfn4+6g8GSzayNleclZUFtVpd6bw0UX1VVQ5F+ZyNgIAANG3aFKmpqSgtLa2yPVFdZTQa8fTTT2Pt2rUYO3Ys1qxZAw8P81+p/HzUHwyWbBQfHw8A2LNnT4V9u3fvNmtD1FC0adMGzZo1w5EjR6DRaMz2aTQaHDlyBC1atEB0dLS4PT4+XtxXnumz9MADD9Rsx4kcYAqU1q1bhzFjxmD9+vWVJmTz81E/MFiy0aBBg9CyZUts2rQJycnJ4naFQoElS5bAx8cHEydOdF0HiVxAIpFgypQpUKvVWLx4sdm+xYsXQ61WY+rUqWbbn3vuOQDAW2+9heLiYnH7zp07ceDAASQkJCAmJqbmO09UDaapt3Xr1iExMREbNmywGCgB/HzUJxJBEARXd8Jd7N+/H0OHDoWvry+efPJJyOVybNu2DTdu3MDy5csxe/ZsV3eRyClWr16N33//HQDw119/4dSpU4iLi0Pr1q0BAP3798eUKVMA3P0LOS4uDmfOnEFCQgK6d++OU6dOYc+ePejZsycOHjwIPz8/s/NPnToVq1evxr333otHH30UmZmZ2Lx5M2QyGY4ePYq2bdvW7gsmstGCBQuwcOFCyGQy/P3vfxdrKpU1YsQIdO3aFQA/H/WGq6tiuptjx44JDz30kBAYGCj4+fkJvXr1qrAWEJG7mzRpkgCg0sekSZPM2hcWFgovv/yyEB0dLXh7ewvNmzcXZs+eLSiVSovnLy0tFf71r38J9957ryCVSoWQkBBhzJgxwtWrV2vh1RFVX1WfDViods/Ph/vjyBIRERGRFcxZIiIiIrKCwRIRERGRFQyWiIiIiKxgsERERERkBYMlIiIiIisYLBERERFZwWCJiIiIyAoGS0RERERWMFgiIiIisoLBEhEREZEVDJaIiIiIrGCwRFRPpaWlQSKRQCKRYPLkya7uDtWww4cPQyKRwNPTE2fOnHF1d2rEL7/8AolEAqlUiitXrri6O9SAeLm6A0QNnUQisbjd29sbgYGBCAwMRGRkJLp164b77rsPf/vb3xAcHFzLvayosLAQK1asAAB07doVI0aMcGl/GrLS0lK8+OKLAIAJEyagS5cuLu5RzXjkkUcwYMAAHDhwADNnzsSuXbtc3SVqICSCIAiu7gRRQ1ZZsFQZqVSKUaNG4e2330bLli0rbZeWloYWLVoAACZNmoQ1a9Y40s1aPz/Z7uuvv8azzz4LDw8PXLp0CW3atHF1l2rMvn37MGjQIADA3r17xa+JahKDJSIXKxssff/99+LXgiBApVKhsLAQ586dwx9//IHz58+L+wMCArBy5Uo888wztdpfEwZLdYPBYEDr1q2Rnp6Oxx9/HFu3bnV1l2pcz549cfLkSfTp0wdHjx51dXeoAeA0HFEdUtVUVlJSEt544w0cPHgQGo0GU6ZMgb+/P5588sna6SDVOZs3b0Z6ejoA4Pnnn3dxb2rH9OnTMWXKFCQlJeHIkSOIi4tzdZeonmOCN5Eb6dOnD3777Tc899xzAO6OPj399NO4efOmi3tGrvLpp58CAKKjozFw4MBK2+n1enh7e0MikWDAgAFVnrdPnz6QSCSQy+WoaxMQTzzxBHx9fQEAn3zyiYt7Qw0BgyUiN+Pp6YlPPvkEPXv2BADodDosWbKkQjtb7oYzGo3YtGkTRowYgZiYGPj5+cHX1xeRkZHo0qULEhMTsWrVKuTl5VU4r2kKDgDWrl0rXqvs48CBA2bX0+l0+PHHHzFz5kz069cPYWFh8Pb2hlwuR5s2bTBhwgT8+uuvVX4PDhw4IF5jwYIFAICMjAy8+eabuPfeeyGTyRAYGIhu3bph0aJFUKlUVZ4TuBtQrF69GqNGjUJsbCwCAgIglUoRHR2NRx55BMuXL0dGRobVc+h0OnzxxRcYNmwYoqOj4evri6CgIHTs2BEzZ8506l1cly9fRlJSEgBg1KhRVvPfLly4gJKSEgB3E/KtMRqN+OuvvwAAnTt3rnBeS9//q1ev4u9//zvatWuHgIAAREREICEhAXv27Klw/j/++APjxo1Dq1at4OvriyZNmiAxMdHmu/jkcjkSEhIAAD/88AMUCoVNxxFVm0BELgVAfNjjP//5j3hcQECAUFxcbLY/NTVV3D9p0qQKx+fm5gp9+vQxu35lj/fff9/ieat67N+/3+yaLVq0sOm4xx57TFCpVJW+9v3794tt58+fL+zevVsIDg6u9Hxt27YVbt26ZfX7uW/fPiEyMrLKvnXt2rXScxw4cKDKc3h6egpLliyx2hdbLVmyRDzv9u3brbZds2aN2Pabb76x2vbSpUti2+nTp1fYX/77v337dkEmk1X6mt9++21BEATBaDQK8+bNq7Sdt7e38J///Mem1/7hhx+Kx/373/+26Rii6mLOEpGbGjZsGBo1aoTCwkJoNBqcOHEC/fr1s/n4qVOniqMS0dHRePLJJ9GmTRs0btwYGo0GKSkpOHr0KA4fPmx2XHh4OL7//ntkZ2dj2rRpAICBAwdi5syZFa7RsWNHs+darRaNGjXCgw8+iG7duiEmJgb+/v5QKpU4e/YsNm/ejMzMTPz444945plnsGXLlipfR3JyMpYvXw6DwYDJkyejf//+kMvluHz5MlatWoWsrCxcuXIFTz/9tMVRDuDu6ERiYqI48tK2bVskJiaiXbt2kEqlyMzMxPHjx/Hzzz9XOiW1c+dOPPbYYzAYDPDw8MBDDz2EwYMHIzIyEjqdDidPnsS6deugUCjw5ptvAgDmzp1b5euzZvfu3eLXffr0sdr27Nmz4tdVjSyVHeGpqgzBqVOn8N5778HT0xMzZsxAr1694OnpiQMHDuCbb75BSUkJ/vnPfyIuLg6nTp3CokWLEBMTg8mTJ6N9+/bQaDTYsmUL9uzZI/4ML1++jNDQUKvXLft6d+3axbw9qlmujtaIGjpUc2RJEARh6NCh4rErVqww22dtZOnOnTuCh4eHAEDo16+fUFRUVOk1srOzhQsXLlTYXtXIlSW//PJLhRGwsjQajTBixAjxvIcPH7bYruzIBgChWbNmwrlz5yq0y8zMFKKiosR2f/75Z4U2aWlpglwuF9ssXLhQKCkpsXjdoqIiYceOHRW2Z2RkiCNb4eHhwtGjRy0ef+vWLaFjx47iCNPFixcr/V5UpaSkRAgICBAACNHR0VW2Hzx4sDh6o9frrbZ98803xe/HH3/8UWF/+e9/bGyscP369Qrt1q5dK7bp2LGjIJVKhUcffVTQarUV2k6cOFFsu2zZsipfj06nE3x8fAQAQrt27apsT+QI5iwRubGYmBjx65ycHJuPu379OoxGIwDgqaeeEpNlLQkLC0OHDh2q38kyHn74YXh7e1e639/fH2vXrkVAQACAu7lQttiwYQPuvffeCtsjIiLwj3/8Q3y+c+fOCm2WLl0q5jS98MILmDdvHjw9PS1ex9fXF48++miF7e+//z7y8/MBAN99912lozyRkZHYunUrPD09UVpain/9619Vv7hKpKamQqPRAADat29fZXvTyFKHDh3g4+NjtW1ycjKAu2UtOnXqVOW5N27caJbDZjJx4kSx5tO5c+cQFBSETZs2wc/Pr0Lbt99+W8yNsqXYpFQqFeuMXblyBTqdrspjiKqLwRKRG2vcuLH4ddkk7KqYghEA+PPPP53aJ0cFBgaKv6BN04TWdO3a1epdYEOGDBG/PnfunNm+0tJSbNq0CcDdX76mZGV7CIKAdevWAQD69u2L+++/32r79u3bo1evXgDMp9HslZaWJn5dVUX3O3fuIDs7G0DVU3DA/6bhWrZsCZlMZrVt9+7drU7/lr2tf+LEiQgMDLTYLjo6Wgz+L1y4UGUfgf+9bkEQxPIJRDWBOUtEbkwokz9jTyXwe+65B5GRkbh9+za+/vprlJaWYurUqejTp0+loyrOUlBQgI0bN2LXrl04d+4c8vLyoNFoLOYC3bp1q8rz9e3b1+r+qKgos2uXdfbsWSiVSgAQ786z14ULF8RAtXHjxvjhhx+qPMb0PU5NTYVOp7M6slcZ00gWAISEhFhtWzZfqaocpLy8PNy+fdumtkDVuVIRERHi16Yg0VrbtLS0Cj+nypR93WW/H0TOxmCJyI2V/aVS1S/Msjw9PfHll19i1KhR0Ov1WLt2LdauXYvAwED07t0bcXFxGDx4MPr162f3cizW/Pjjj3j22WdtHgUzBTLWVJUILJVKxa/LT9WUDcbuuecem/pUXtkRnl9++QW//PKLXcfn5+ejWbNmdl9Xr9eLX8vlcqtt7UnuNk3BAXfLBlSlqvdd2e+/rW3LvjZryo5SFRUV2XQMUXUwWCJyY2V/Uds7KvLII4/g5MmTWLhwIf7zn/+guLgYSqUSv/76K3799VcsWLAALVq0wKJFizB+/HiH+3r06FE8/vjj4h1nnTt3xuDBg9G6dWs0btwYUqlUDMz++c9/4vz582JelTUeHtXPJigbjFU13VSZwsLCal8fAIqLi6t1XNkgpKqgsqbuhAPs+/478rOypGx9JUt5UETOwmCJyE0ZjUYcO3ZMfN67d2+7z9GxY0ds3boVGo0GR44cQVJSEg4fPozDhw9Dr9cjNTUVEyZMwLVr1zB//nyH+jtv3jwxUPr000/xwgsvVNr2nXfecehatio7MqFWq6t1jrJB1qxZs/DBBx843C9b2DMFZQqWoqKiqsxvKpvDZsvIkiuVHaGs6nUROYIJ3kRu6qeffhJHFGQyGe67775qnysgIAAJCQmYN28efv31V+Tk5GDx4sXi/nfeeQdZWVnVPr/BYBCred93331WAyXAfMSsJpXNZ7I1qdjaOWpz2Zmyd59ZC5ZKSkpw8eJFAKjyrkaj0Sj+nORyucU73OoS0+uWSCRmd4YSORuDJSI3ZDAY8Pbbb4vPJ0+eDC8v5w0Uy+Vy/POf/8Rjjz0mXq/8nWllp1QsJWeXlZubK44qtW7d2mrbEydOIDc3tzrdtlvnzp0RFBQE4O4SHPaUXzDp2rWreI79+/fbnG/jqNjYWDFXyRQMWXLlyhWxT2XvgrRk165d4nIulpY5qUt0Oh1SU1MBQCweSlRTGCwRuZnS0lLMmDEDJ0+eBHA3V+ONN96okWuVHVkwBTsmZaefTPV+KlP2l/TVq1ettnV0us8enp6eeOqppwDcTSquTumAsufIzc3Fhx9+6MwuVsrDw0NcH/DWrVuVrllXNl/JWlCl1Wrx+uuvi8/r+hTcqVOnxHyvqu7II3IUgyUiN3L8+HEMGjQIX375JYC70w9r165FZGSkXefZvXs3PvroI6u3aGdnZ2Pbtm3i8/LJvsHBweKISnJystXRpcDAQLRt2xbA3ZyY7777rkKb0tJSvPLKKxYLR9akOXPmiLlLq1atwqJFi1BaWmqxrV6vt9i/N998E40aNQJwNzl9xYoVVpPTNRoNVq9ejX//+98O9f2hhx4Svy6bv1ZW2WDp8uXL+OSTTyq0ycjIwLBhw3D+/HlxW/PmzR3qW00rO9I5dOhQF/aEGgImeBPVIeVr9KhUKhQWFuL8+fM4cuSIWVFFmUyGTz75BImJiXZfJzMzE7NmzcKcOXMwYMAA9OnTRyxAmJeXh7Nnz+Lf//63GEw98cQTYiXmsgYNGoTt27fj2rVreOKJJzBq1Cg0atRInL7p1auXmHj78ssvi7lKTzzxBMaMGYP4+Hg0btwYV69excaNG3Hx4kV07NgRUqm01oplNm/eHGvXrhXXhps/fz42btyIxMREtG/fHj4+Prhz5w5OnjyJHTt2IDo6Gg8//LDZOSIjI7Flyxb87W9/g16vxyuvvIJVq1Zh5MiRuOeeeyCTyaBSqZCamoqTJ09i37590Ol0Znlh1TFy5EhxNGjfvn0YOXJkhTamYEkqlcLDwwMvvfQSNm7ciJ49e8LPzw+XLl3Cnj17oNPpxNpbAPDVV1/h2rVreOqppzBgwACH+lkTDh06BOBuVfXyPw8ip3PlWitEZL42nC0PX19fYezYsRbX4irL2tptZVegr+rx+OOPCxqNxuI1zpw5I/j7+1d67P79+8W2RqNReOaZZ6xeq1OnTsL169eF+Ph4q+vllV/13tbvcXx8fKVt9uzZI0RERFT5/ejWrVul5zhx4oTQrl07m76vnp6ewv/93/9V2feq9OvXTwAghIWFWVx3Lzo6Wuz3woULK+3Pc889J3z11VcVtt+6davCOe35/s+fP9/i+8GSqn7uJiqVSvD19RUACGPGjLHalsgZOLJEVEd5eXlBLpcjMDAQUVFR6NatG3r06IHhw4ebLXNSHRMnTsQ999yDvXv34tixY7h48SIyMjJQVFQEf39/NG/eHH369MGECRMQHx9f6Xk6d+6M06dP48MPP8ShQ4eQnp4OrVZrcUpOIpHgq6++wqOPPoovv/wSJ0+ehFKpREhICNq1a4fExEQ8++yz1apm7QxDhgzB9evX8c033+Cnn37C2bNnkZubC4lEgiZNmqBTp04YMmQIxo0bV+k5evTogQsXLmD79u348ccfcezYMdy5cwcajQYymQzR0dHo1KkTBgwYgOHDh5tVt66uF198UUxO37lzJ4YPHy7uKywsFO/Qu/feezFv3jxER0fj448/xqVLl+Dv74+uXbti+vTpePzxx6HT6bBjxw7s3r0b0dHRGDdunN1TvLVhy5YtYoHRGTNmuLg31BBIBEv/qxERkVsoKSlB69atcePGDYwcORLbt28X9x06dEgMdpcuXYo5c+a4qptO1atXL5w4cQK9e/e2af1AIkcxwZuIyI15eXlh3rx5AO4uJ1M2r61scnfHjh1rvW81Yf/+/Thx4gQAmJXPIKpJDJaIiNzcpEmT0KlTJxiNRjFwAsyDpXvvvdcVXXM6U1J8QkICBg8e7OLeUEPBYImIyM15enri008/BQB8//33OHXqFID/BUtyubxeVLj+5ZdfsH//fvj4+ODjjz92dXeoAWHOEhFRPSQIAuRyOTQaDXN7iBzEkSUionro2rVrYmX1+jIFR+QqDJaIiOqhv/76S/y6viR3E7kKp+GIiIiIrODIEhEREZEVDJaIiIiIrGCwRERERGQFgyUiIiIiKxgsEREREVnBYImIiIjICgZLRERERFYwWCIiIiKygsESERERkRUMloiIiIis+H9QAt5aMlZIIAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-10/figures/Network-distance-dependent-connection-probability-dSPN-to-iSPN-synapses-3D-dist.png\n", + "Plotting connection probability dSPN to dSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2256.]\n", + "P(d<5e-05) = 0.09249329758713137\n", + "P(d<0.0001) = 0.061808118081180814\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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DB1BYWIivv/4aPXv2rFL2008/rfLPiKsCAwMRGxuLrl27YsKECfjyyy9x+fJlzJgxw6VJYaujUCjw0ksvSfd1Oh3eeOMNt49LjQvDEjV5lSfcCw8Pd2n/iIgID9bmGplMhv79++OTTz7BoUOHqnzQ/fbbbzh37pxTxxoyZAjEtS53m5tarcbFixexefNmvPnmmzZzSHlCaGgoZs2aJd3X6/V4/fXXPXqOuuLp10RxcbG7VWqQr1MAiIyMxKRJk5CRkYHZs2dX2f7RRx85fawtW7ZUeZ0ajUbk5+fj6NGj+Oabb/Doo48iLCzMk08BTzzxhM36d1988QUuXrzo0XOQb2NYImrgOnXqhF9++cVmokAhhEuzMnvL1KlTkZSUJN3/8ssvnQ555FtkMhnmzZuHcePG2Ty+adMmL9XIecHBwXjllVek+waDAfPnz/dijaihYViiJi8yMtLmvkqlcmn/0tJSD9bGvm7dumHYsGE2j50+fbrOz+suuVyO1157TbpvMpkwb948L9bIOZ5+TVhn03aHL7xOAeDpp5+2uX/58mWfWPZm8uTJaN26tXR/2bJldTY2kHwPwxI1ec2bN7e5f/bsWaf3NZvN9dZS0qtXL5v7nujaqQ+PPPKIzfiaFStWOL30hrdUHPALwOUPzVOnTjk8Xm1UXrPNldcp4PpzqK3Kr1PAN16rQUFBNt2I5eXlmDt3rvcqRA0KwxI1eX379rW5v2/fPqf3PXLkCPR6vaerZFflq35cHbPiLQEBAZgzZ45032w229yvS7UdANyvXz+b+3v27HFp/927dzs8Xm1ER0fbtHwcOHCg2kV97XHlde0Oe1en+cprdeLEiejYsaN0/4cffsCxY8e8WCNqKBiWqMm77rrrbO6vXLnS6X1//PFHT1enWpVbY1q0aFFv53bXgw8+iK5du0r3V65ciczMzDo/b8UrCY1Go9P7tW7d2ubnu3Xr1ipXTVansLAQGzZskO5HRkaiS5cuTp/bkYqv1YKCAmzZssWp/UpLS7Fu3TqP1KEmlV+nCoUCCoWiXs7tLn9/f5tuYovFYnfQOjU9DEvU5HXs2BH9+/eX7v/555/YunVrjfsVFBRUWfndEXfCwaVLl2w+gAFg6NChtT5effPz87P5EBJC2IxlqisVrwArKCiA2Wx2et8HHnhA+t5sNuPNN990ar8FCxbAZDLZHMcTl7gD10JnRc5eXfjuu+863QJ69epVp4OhPV999ZXNfV96nQLAuHHj0KNHD+n+6tWr3Z7+gHwfwxIRgCeffNLm/mOPPebwA6O8vByTJk2qcjm3I8888wwGDhyIdevWQQjh9H4ajQbjx4+3+bBr3759le7Dhu6ee+6xmZ7g3//+d52fs+J8RyaTCX/++afT+z7xxBM2VyAuXrwYv/76q8N9fv31V3zyySfSfT8/Pzz11FMu1NixW265BW3btpXub926Fe+9957DfZwpU9Hx48fRtm1bvPTSS1XmdqrJqlWrqvwDUfnquIZOJpPZXAknhKjx906NH8MSEa6NVajYxZGVlYXBgwfb7eY4ffo0Ro0ahd9//x1A1auUHNm7dy9uueUWtGvXDvPnz0d6enq1rR1lZWX4/vvv0atXryof8u+9957HWivqi0wmw4IFC+r1nDfeeKPN/YcffhhffvklMjIycO7cOZw/f166VW55adu2LV5++WXpvtlsxtixY7Fw4cIqV3fp9Xq8++67GDt2rM3v8/nnn/dYFxxwLXwtXrzY5rEXX3wR06dPr3K1m8lkwmeffYY77rgDBoPBpdepTqfDwoUL0bJlS4wZMwarVq1yOLHm8ePH8fjjj+O+++6zef59+/a1aaHzFaNHj3ZrxnNqhLyyyApRA3Ty5EkRGxtbZf2pdu3aidGjR4uxY8eKvn372mx77LHHnF5/rLp1sBQKhRg4cKC4/fbbxUMPPSTGjBkjUlJSREhIiN3yL7/8ssPnUXnttiFDhnj05+TM2nCOXHfddXafV12sDWexWETXrl2dWmfM3pp7JpNJjBgxwu7vbOTIkWL8+PEiLS3N7qLIN954Y41ro9XWM888U+V8crlcDBs2TIwfP17cfPPNNmvzKRQK8dlnnzm1NpyjtQXbt28vbrrpJnHfffeJ+++/X4waNUokJSXZLduyZUtx9uxZh8+j8nuipnUPXeXM2nDVWbduXbU/B64N1/QwLBFVcPDgQdG8eXOnPlxvv/12YTAYnA5LkydPFjKZzOXFQq238PBwsXjx4hqfQ0MPS5s2baq3sCSEEIcPHxatWrWqVVgSQgi9Xi/GjRvn0u/q7rvvFmVlZXXyfIS4FgKnTp3qVF3CwsLEhg0bqvzeqgtLhw4dsvtPgyu3ESNGiHPnztX4PBpyWBJCiBtuuIFhiYQQXEiXyEbv3r1x7NgxPPbYYwgJCbFbpl27dvjoo4+wZs0aBAUFOX3sL774ApcuXcLixYtx9913V5k3pzodOnTAvHnzcOLECTzxxBNOn6+hGj58eJUJNutS9+7dcfjwYSxevBi33347WrduDYVC4XQ3plwuxz//+U+sXbsW1113XbX7yWQyDBgwAL/99htWrVpV6wWWnSGTybBkyRL88ssv1XbzBQYG4p577kF6ejpGjhzp9LF79uyJ3NxcbN68GTNmzED//v1txm5VJzg4GHfffTd+++03bNy40WaaA1/lK8vzUN2TCeHCSFOiJkStVmPz5s3Izs6GTqdDQkICOnbsiAEDBnhsvNClS5dw8uRJnDt3DqWlpSgrK0NoaCjCw8PRqlUr9OnTxyMTGpLn5OXl4c8//0Rubi5KSkoQERGB+Ph4pKam2iwcXJ8yMjKQkZGB3NxcKJVKtGzZEqmpqYiNjfXI8XU6HU6dOoVTp04hLy8ParUawLX5k6Kjo9GtWzd07doVAQEBHjkfUUPDsERERETkALvhiIiIiBxgWCIiIiJygGGJiIiIyAGGJSIiIiIHGJaIiIiIHGBYqiUhBFQqlUtrfBEREZHvYViqJbVajYiICGm+ESIiImqcGJaIiIiIHGBYIiIiInKAYYmIiIjIAYYlIiIiIgcYloiIiIgc8OmwJITA6tWrMWzYMLRo0QKhoaHo1KkTpk6diqysrCrlVSoVZsyYgeTkZMjlcrRu3RovvPACNBqNF2pPREREvkAmfHiioOeeew4ffPABWrRogbvuugvh4eE4dOgQNmzYAIVCgb/++gvdu3cHAGi1WgwePBgZGRlIS0tDnz59cPDgQWzYsAEpKSnYvn07goODnT63SqVCREQESktLER4eXldPkYiIiLwswNsVqK3c3Fx8+OGHSE5OxqFDhxARESFtW7RoEWbMmIEPPvgAX331FQDgnXfeQUZGBmbOnIm3335bKvvSSy9h4cKFWLRoEWbNmlXvz4OIiIgaNp/thjt//jwsFgtSU1NtghIA3H777QCA/Px8ANe665YuXQqFQoHXXnvNpuxrr70GhUKBpUuX1k/FiYiIyKf4bFjq0KEDgoKCsHPnTqhUKpttv/32GwBg+PDhAIDTp0/jypUrSE1NRVhYmE3ZsLAwpKamIisrCxcvXqz2fAaDASqVyuZGREREjZ/PhqWYmBi8/fbbyM7ORufOnfG3v/0NM2fOxM0334yZM2fiiSeewFNPPQXgWlgCrgUse6yPW8vZ89ZbbyEiIkK6JSUlefgZERERUUPks2OWAGD69OlITEzE5MmTsWTJEunxwYMH44EHHkBAwLWnV1paCgBVuuusrAO0reXsmTVrFmbMmCHdV6lUDExERERNgE+Hpfnz5+P111/H/Pnz8dBDDyEyMhIZGRmYPn06hg4dilWrVuHOO+/0yLnkcjnkcrlHjkVERP9TUFCAsrIyb1eDmig/Pz8kJiY6LOOzYWnTpk2YM2cOpk+fjpdeekl6fPDgwfj111/Rtm1bPPfcc7jzzjulFqXqWo6s44+qa3kiIqK6YbFYcPLkSZSWlsLPz2dHhpCPslgsCAkJabxhae3atQCAYcOGVdkWHx+Pzp074+DBg9BoNDWOSappTBMREdUNnU4HvV6PqKgoBAUFebs61MQYjUbodLoay/lsjDcajQD+Nz1AZfn5+fDz80NgYCA6dOiAhIQE7Ny5E1qt1qacVqvFzp070aZNG45BIiKqZxqNBkajEYGBgd6uClG1fDYspaamAgA++OCDKt1rS5YswaVLl3DddddBLpdDJpNh8uTJ0Gg0WLBggU3ZBQsWQKPRYMqUKfVWdyIiusa63JRMJvNyTYiq57PLnZjNZtx0003Yvn07mjVrhjvvvBORkZFIT0/H5s2bERISgq1bt2LAgAEArrUgpaam4tChQ0hLS0Pfvn2Rnp4uLXeybds2hISEOH1+LndCROS+ffv2QaVSITIy0ttVoSbI2g1nnZexOj4bloBrE0UuWrQIK1euxMmTJ2E0GtG8eXMMGzYML7/8Mrp06WJTvrS0FHPnzsWqVauQm5uLFi1aYOzYsZgzZw6USqVL52ZYIiJyj8FgwK5duxAQEODSP6tEntIkwpI3MSwREbmnsLAQ+/fvR1RUFPz9/b1dHWqCnA1LPjtmiYiIfJtWq4XFYmFQogaPYYmIiLyitLSUQYl8AsMSERHVO7PZjJKSEq6MQD6BYYmIiOqdVquFwWBgWCKfwLBERET1TqvVwmQySQueEzVkDEtERFTv1Go1AE5GSb6BYYmIiOqVEAJFRUXsgiOfwbBERET1Sq/Xo6ysjGGJfAbDEhER1Svr4O6goCBvV4XIKQxLRERUrzQaDYQQ8PPjRxD5Br5SiYioXpWUlPAqOPIpDEtERFRvysvLoVKpOF6JfArDEhER1RuOVyJfxLBERET1RqPRoLy8HIGBgd6uCpHTGJaIiKjeqNVqTkRJPodhiYiI6oUQAsXFxRyvRD6HYYmIiOpFWVkZysrKOF6JfA7DEhER1QuNRgOj0ciWJfI5DEtERFQvtFothBAcs0Q+h2GJiIjqRXFxMa+CI5/EsERERHXOZDJBrVZzvBL5JIYlIiKqcxqNBgaDgeOVyCcxLBERUZ3TarUwm81cE458EsMSERHVOZVKBT8/fuSQb+Irl4iI6pTFYkFxcTHHK5HPYlgiIqI6VVZWBr1ez/FK5LMYloiIqE5ZJ6NkyxL5KoYlIiKqU2q1GgA4GSX5LIYlIiKqU5yMknwdwxIREdUZo9EIrVbL8Urk0xiWiIioznAySmoMGJaIiKjOaLVaWCwW+Pv7e7sqRLXGsERERHWmpKSEk1GSz/PYvPN5eXnIzMzE+fPnUVRUhLKyMoSEhCA6OhqtW7dGr169EBcX56nTERFRA2exWFBaWsouOPJ5boWlTZs2YfXq1Vi3bh0uXLhQY/nWrVtj1KhRGDNmDEaMGMHLSImIGjGtVgu9Xo+wsDBvV4XILTIhhHBlh+LiYixZsgSfffYZLl++LD3uzGEqhqOEhAQ88cQTmDZtGqKiolypQoOgUqkQERGB0tJShIeHe7s6REQNTm5uLg4ePIi4uDj+c0wNktFohE6nw/Dhwx2WczosqdVqvPfee/jwww+h0WhswlFoaChSUlLQpUsXREdHIyYmBuHh4SgtLUVhYSGKiopw7NgxHDhwADqd7n8nl8kQFhaG6dOn4/nnn4dSqazl061/DEtERI6dPn0aZ86cQbNmzbxdFSK7PBqWvvnmG8ycORN5eXkQQkAmk+H666/HPffcg6FDh6Jnz55ODeAzm83IzMzE9u3bsWrVKuzcuVM6XrNmzfDOO+9gwoQJzj9LL2JYIiJybO/evVCr1YiMjPR2VYjs8mhYsgah8PBwPP7445g6dSratWvndiWzsrKwZMkSfP7551CpVPDz80N5ebnbx60PDEtERNXT6/XYtWsXAgMDERIS4u3qENnlbFhy6npOhUKBefPm4cKFC3jnnXc8EpQAoG3btnjnnXeQnZ2NuXPnIjQ01CPHJSIi79JqtZyMkhoNp66Gq+s+5/DwcMyePRt/+9vf6uwcRERUf6xjWznHEjUGTr2K62twHudhIiJqHEpLSzlrNzUajPxERORRZrMZJSUl7IKjRoNhiYiIPIrjlaix8dhyJ/bs3LkT27dvx6VLlwAAiYmJuPHGGzF48OC6PC0REXmRRqNBeXk5AgMDvV0VIo+ok7B08uRJTJgwAQcOHLC7vW/fvvj222/RuXPnujg9ERF5kVqt5ozd1Kh4vBvu0qVLGDJkCA4cOAAhBOLj46XZvUNCQiCEwIEDBzB06FCpxYmIiBoHIQSKiooQFBTk7aoQeYzHw9L8+fORl5eHHj164M8//8Tly5exe/duHDlyBPn5+Xj//fcRGBiI/Px8LFiwwNOnJyIiL9Lr9SgrK+N4JWpUPB6W1q5dC39/f6xZswbXX3+9zbaQkBBMnz4dzz77LIQQ+P333z19eiIi8iKNRgOj0ciWJWpUnA5L999/P/Lz82ssl5eXh+joaCQnJ1dbpn///gCAgoICZ09PREQ+QKvVcjJKanScfjWvXLkSXbp0wVdffeWwXLNmzVBYWIjs7Oxqy+zfvx8AJ6EkImpsioqKEBBQpxdaE9U7p8PSyJEjUVRUhClTpuCmm27C6dOn7Za75ZZbYLFYMGbMGOzdu9dmm16vx0cffYQPP/wQMpkMt9xyi3u1JyKiBqO8vBxqtZrjlajRkQkhhLOFV6xYgeeeew75+fkIDg7GK6+8gpkzZ9r8F3H58mX07dtX6mJLSEhAy5YtodVqce7cOeh0OgghEBMTg/T0dCQlJXn+WdUDlUqFiIgIlJaWIjw83NvVISLyupKSEuzduxcRERFsXSKfYDQaodPpMHz4cIflXOpUfuihh3D8+HFMnDgRer0es2fPRt++fbF7926pTGJiIrZu3YpevXpBCIHLly9jz549OHLkiNSX3bNnT2zevNlngxIREVWl1WphNpsZlKjRcXkEXnR0NJYtW4ZNmzahbdu2OHLkCAYPHoynnnoKarUaANClSxekp6dj69atmD9/PqZOnYqpU6di/vz52LJlCzIyMtCjRw+PPYmff/4ZI0eORExMDIKDg9GmTRuMHz8eFy9etCmnUqkwY8YMJCcnQy6Xo3Xr1njhhReg0Wg8VhcioqZKpVJxMkpqlFzqhqvMYDBg7ty5eP/992E2m5GYmIiPPvoIo0eP9mAVqyeEwLRp0/D555+jXbt2GDVqFJRKJa5cuYJt27bhu+++k5ZW0Wq1GDx4MDIyMpCWloY+ffrg4MGD2LBhA1JSUrB9+3YEBwc7fW52wxER/Y8QArt27YLBYODfRPIZznbDudVWKpfL8dZbb+GBBx7AlClTsHfvXtxzzz0YPXo0Pv74YyQkJLhz+Bp99NFH+Pzzz/HEE0/go48+gr+/v8328vJy6ft33nkHGRkZmDlzJt5++23p8ZdeegkLFy7EokWLMGvWrDqtLxFRY6XT6VBWVoaQkBBvV4XI49xqWapICIFPPvkEr776KtRqNcLDw/H2229j2rRpnjh8FWVlZUhMTERUVBROnjzpsI9cCIGWLVtCpVIhNzcXYWFh0jatVov4+Hg0a9YMZ8+edfr8bFkiIvqfvLw8pKenIzY2ll1x5DPqZIC3IzKZDE8//TSOHTuGO+64AyqVCk8++SQGDx6M48ePe+o0kg0bNqC4uBijR4+G2WzG6tWr8fbbb2PJkiU4c+aMTdnTp0/jypUrSE1NtQlKABAWFobU1FRkZWVVGeNUkcFggEqlsrkREdE1Go0GQggGJWqUah2Wzpw5g927d+Pw4cPQ6/XS44mJiVizZg1WrlyJ5s2b46+//kKfPn0wZ84cGI1Gj1QaAA4cOAAA8Pf3R8+ePXHPPfdg1qxZ+Nvf/oZOnTrh+eefl8pa54Tq0KGD3WNZH69u7igAeOuttxARESHdeCUfEdH/FBcXIzAw0NvVIKoTLoWl8vJyzJ8/H82bN0enTp2QmpqK3r17IzIyEvfddx/Onz8vlb333ntx4sQJPP744zCZTHj99dfRq1cvbN++3SMVz8vLAwB88MEHiIiIwN69e6FWq7F9+3Z07NgR77//Pj777DMAQGlpKQAgIiLC7rGs3WjWcvbMmjULpaWl0s1RKxQRUVNiNBo5GSU1ak6HJZPJhFtuuQXz5s1Dfn4+hBDSzWg0YtWqVejfvz9OnDgh7RMeHo4lS5Zg+/bt6Ny5M06ePIlhw4bh8ccfdxhMnGGxWAAAQUFB+OWXX5CSkgKFQoEbbrgBP/30E/z8/PD++++7dY6K5HI5wsPDbW5ERHRt7KfRaGRYokbL6bD00Ucf4T//+Q+EEBg+fDh+/fVXHDt2DNu3b8dzzz2HwMBAFBUVYfLkyVX2TU1NRUZGBubMmYOgoCB8+eWX6NKlC1auXFnriltbifr371/lqrvu3bujbdu2OHv2LEpKSqSy1QU06/ij6lqeiIioehqNBmazucoVyUSNhdNhacWKFZDJZBg+fDg2bNiA2267DZ07d8bgwYPx7rvvSq04u3btsumOswoMDMScOXNw8OBBDB48GLm5uXjggQdqXfFOnToBACIjI+1utz5eVlZW45ikmsY0ERFR9VQqFfz8PHa9EFGD4/Sr+9SpUwCA8ePH273aYfz48dL3jgZKd+7cGdu2bcM//vEPt7qyhg0bBgB2r7QzmUw4c+YMwsLCEBcXhw4dOiAhIQE7d+6EVqu1KavVarFz5060adOGg7aJiFxksVhQXFzMLjhq1JwOS9Z5jKpbGqRiCHFmXaApU6bYjG9yVbt27ZCWloYzZ85g6dKlNtvefvttlJSUYMyYMQgICIBMJsPkyZOh0WiwYMECm7ILFiyARqPBlClTal0XIqKmSqfTwWAwMCxRo+b0pJRDhgzBjh070KlTJ+zbtw8KhcJm+1NPPYVPP/0Ufn5+uHr1KmJiYuqkwhWdPXsW119/PfLy8qRuwYMHD2Lz5s1ITk7G7t27ER8fD+BamEtNTcWhQ4eQlpaGvn37Ij09XVruZNu2bS7NPMtJKYmIgNzcXBw8eBBxcXGcY4l8jrOTUjodllauXIn7778fMpkMzZs3x8SJE9GmTRsUFRXht99+w+7duwEA9913H3744Qf3n4GTLl68iNmzZ2PdunUoLCxEfHw87rzzTsyePRvNmjWzKVtaWoq5c+di1apVyM3NRYsWLTB27FjMmTMHSqXSpfMyLBERXZtz7/Tp01X+3hL5Ao+HJQB44YUXpIHcFf+DsB6iT58++M9//lPtoOvGhGGJiAjYt28fVCpVk/i7T41PnSx38u6772L9+vUYPXo0mjdvDn9/f4SHh2PQoEH48MMPsWvXLr5hiIiaCIPBAK1Wy/FK1OjVPBK7kpEjR2LkyJF1URciIvIhGo0Ger0e0dHR3q4KUZ3ixBhERFQrWq0WQghORkmNHsMSERHVSmlpKYMSNQkMS0RE5DKz2YySkhKOV6ImwamwNHbsWGRlZdVpRQ4fPozRo0fX6TmIiMgztFot9Ho9wxI1CU6FpVWrVqFLly545JFH7C4v4o4jR45g3Lhx6NOnD3799VePHpuIiOqGVqtFeXm5Uys2EPk6p8LSTTfdBJPJhG+++Qbdu3fH0KFDsWzZMhQXF9fqpAUFBfjoo4/Qv39/9OrVC//6179gsVhw00031ep4RERUv9RqNWQyGWftpibBpRm8Z82ahXPnzklvDn9/f3Tr1g2DBg3CwIED0blzZ0RHRyMmJgZKpRIqlQpFRUUoKirC8ePHsWfPHuzZswdHjx6F2WyWJrNs164d3nzzTYwdO7bunqmHcVJKImqqhBDYs2cPdDodIiIivF0dolqrkxm8y8vL8dVXX+H999/H6dOnrx2gFv9VWE/ZqVMnPP/883j44Yd9rimXYYmImqqysjLs3r0bQUFBCA4O9nZ1iGqtTmbwDggIwOOPP44TJ05g3bp1uP/++6FQKCCEcPoWHh6Ohx56CBs2bMDx48fx2GOP+VxQIiJqyrRaLQwGA4KCgrxdFaJ6UauUIpPJkJaWhrS0NJhMJvz111/Ys2cPDh8+jPPnz6OoqAgGgwFyuRwxMTFo06YNevTogUGDBuG6667jvBxERD5Mo9FACAE/P84+Q02D2006gYGBGDJkCIYMGeKJ+hARUQNXUlLCHgFqUvhvAREROa28vBwqlYrzK1GTwrBERERO43glaooYloiIyGkajQbl5eUIDAz0dlWI6g3DEhEROc06GSVRU8KwREREThFCoLi4mOOVqMlhWCIiIqeUlZWhrKyM45WoyWFYIiIip2g0GhiNRrYsUZPDsERERE7RarUQQnDMEjU5DEtEROSU4uJiXgVHTRLDEhER1chkMkGtVnO8EjVJDEtERFQjjUYDg8GA4OBgb1eFqN4xLBERUY20Wi3MZjMXQqcmqc5WQiwpKYFarYZSqURkZGRdnYaIiOpBaWkp/Pz4/zU1TR575Ws0GnzyyScYOnQolEolYmJi0Lp1a8TExECpVGLYsGH49NNPodFoPHVKIiKqBxaLBSUlJRyvRE2WR8LSr7/+ig4dOuDvf/87duzYIV1ear1ptVps374dTz/9NDp06IDffvvNE6clIqJ6oNPpoNfrOb8SNVlud8N98803eOyxx2CxWCCEAAAolUq0a9cOYWFh0Gq1yMrKgkqlAgBcvXoVo0ePxtdff40JEya4e3pyklqtrlWrnkKhgFKprIMaEZGv0Gq1MBqNiIiI8HZViLzCrbB05swZTJs2DWazGQAwZswYvPjiixg4cGCVsnv37sW7776LVatWwWKxYOrUqbj++uvRrl07d6pATjpw4AC2bdvm8n5DhgzB0KFDPV8hIvIZarUaADgZJTVZboWlRYsWQa/XQyaTYeHChXj++eerLTtgwAD89NNP+OCDD/D888/DYDBg0aJF+OSTT9ypAjmpX79+6NSpU5XHCwoKsHr1atx9992IjY2tsl2hUNRH9YioAeNklNTUuRWWNmzYAJlMhhtvvNFhUKpoxowZ+PXXX7Ft2zasX7/endOTC5RKpcPutNjYWLRo0aIea0REvsBoNEKr1XK8EjVpbg3wvnz5MgDg3nvvdWk/a3nr/kRE1DBZJ6NkWKKmzK2wZO2iad68uUv7NWvWzGZ/IiJqmDQaDSwWCyejpCbNrbDUvn17AEB2drZL+128eBEA0KFDB3dOT0REdYyTURK5GZbGjRsHIQS+//57adqAmggh8N1330Emk+H+++935/RERFSHLBYLSktL2QVHTZ5bYWnatGno2bMnDh48iOnTpzu1z4wZM3Dw4EH06tULU6dOdef0RERUh7RaLSejJIKbYUkul+P333/HwIED8fHHH2PQoEH417/+heLiYptyJSUl+Omnn3Ddddfho48+wnXXXYfff/+dU+cTETVgGo0GJpOJ0wZQk+fU1AFt27Z1uN1kMkEIgX379mHcuHEAgKioKGkGb2t4EkJAJpMhOzsbqampkMlkOHv2rJtPgYiI6oJ11n9ORklNnVNh6fz585DJZNWOS5LJZNKbyVqmqKgIRUVFVcoBwJUrV6TgREREDVNRURF7AIjgZFhq1aoVgw0RUROi1+uh0+k4XokILrQsERFR06HVamEwGDgfHhHcHOBNRESNk0ajgRCCcywRgWGJiIjsKCkp4azdRP/FsERERDbMZjMnoySqwKkxS84qKCjA77//jt27dyMnJwdqtRpKpRIJCQkYOHAgbrvtNsTGxnrylERE5GHW8UpKpdLbVSFqEDwSlnQ6HV588UV89dVXMBgMdsv84x//gFwux+TJk7Fw4UKEhIR44tRERORhGo0G5eXlnIyS6L/c7oYrKChASkoKPvvsM+j1egghqr3p9XosXrwYKSkpKCws9ET9iYjIw9RqNaeLIarA7Zale+65B8ePHwcAhISEYPz48Rg1ahQ6duwIhUIBjUaDU6dOYf369fjnP/8JnU6HY8eO4Z577sHWrVvdPT0REXmQEIKTURJV4lZY+vnnn7Fjxw7IZDL07t0bq1evRnJycpVyvXr1wtixY/Haa6/h3nvvxYEDB7Bjxw6sWbMGd911lztVICIiD9Lr9SgrK+PgbqIK3OqG++c//wkAiIuLw8aNG+0GpYqSk5Oxbt06NGvWDADw/fffu3N6IiLyMI1GA6PRyJYlogrcCkt79uyBTCbDo48+iujoaKf2iYmJwWOPPQYhBPbs2ePO6YmIyMO0Wi0noySqxK13Q15eHgCgZ8+eLu3Xo0cPm/2JiKhhKCoqQkCAR2eVIfJ5boUlazOt0Wh0aT9reU9flrpw4ULIZDLIZDLs3r27ynaVSoUZM2YgOTkZcrkcrVu3xgsvvACNRuPRehAR+SKTyQS1Ws3xSkSVuBWWEhISAAA7duxwab/t27cDABITE905vY0jR45gzpw5CAsLs7tdq9ViyJAhWLRoETp37ozp06ejU6dOeO+993DTTTdBr9d7rC5ERL7IOhklwxKRLbfC0tChQyGEwLfffotDhw45tU9GRgZWrFgBmUyGoUOHunN6iclkwsMPP4zevXtjzJgxdsu88847yMjIwMyZM7F+/Xq8/fbbWL9+PWbOnIl9+/Zh0aJFHqkLEZGv0mq1MJvN7IYjqsStsDR58mTIZDKYTCaMGDECq1evdlh+9erVGDlyJIxGI2QyGaZMmeLO6SVvvPEGjh49iq+++sruwo9CCCxduhQKhQKvvfaazbbXXnsNCoUCS5cu9UhdiIh8lUql4mSURHa49e9D3759MW3aNHz22WcoKirC2LFj0bZtW4wcORIdO3ZEWFgYtFotTp8+jY0bN+Ls2bMQQkAmk2HatGno06eP208gPT0db7zxBubPn4+uXbvaLXP69GlcuXIFo0aNqtJNFxYWhtTUVKxfvx4XL15EUlKS23UiIvI1QggUFxezC47IDrfbWj/++GOoVCp89913AICsrCz84x//sFtWCAEAePDBB/HRRx+5e2oYDAZMnDgRvXv3xosvvlhtudOnTwMAOnToYHd7hw4dsH79epw+fbrasGQwGGzWvVOpVG7UnIioYdHpdCgrK+O6nUR2uD2Rhp+fH7799lv8+OOP6Nu3r8O14fr164effvoJ33zzjUfm8Jg9ezZOnz6Nr7/+2m73m1VpaSkAICIiwu728PBwm3L2vPXWW4iIiJBubIEiosZEq9XCZDJxMkoiOzw2im/s2LEYO3YssrOzsWfPHuTk5ECtVkOpVKJFixYYOHAgWrVq5anTYdeuXXjvvfcwd+5cdO/e3WPHrc6sWbMwY8YM6b5KpWJgIqJGQ61WS8MkiMiWW2Hpm2++AQDEx8cjLS0NANCqVSuPhiJ7ysvL8fDDD6Nnz5546aWXaixvbVGqruXI2qVWXcsTAMjlcvblE1GjVVJS4vG574gaC7fC0qRJkyCTyfDKK69IYak+aDQaaRxSdU3G1113HYBri/1aB35b96mspjFNRESNmdFo5GSURA64FZYUCgW0Wm21V6HVFblcjscee8zutu3bt+P06dO48847ERcXh9atW6NDhw5ISEjAzp07odVqba6I02q12LlzJ9q0acNuNSJqkrRaLYxGIyIjI71dFaIGya2w1KJFC5w5cwYmk8lT9XFKSEhItfMiTZo0CadPn8asWbMwaNAg6fHJkydj/vz5WLBgAd5++23p8QULFkCj0eDll1+u83oTETVEGo0GZrPZ4YUyRE2ZW2Fp2LBhOHPmDPbt24cJEyZ4qk514sUXX8SaNWuwcOFCHDx4EH379kV6ejo2bNiAlJQUPPvss96uIhGRV6hUKo9coUzUWLn17pg6dSr8/PywfPlyXL582VN1qhNhYWHYtm0bnn32WRw/fhzvv/8+Tpw4geeeew7/+c9/OLcIETVJFouFk1ES1cCtsNSnTx+88cYbUKvVGDlyJDIzMz1Vr1pbtmwZhBA2XXBWERERWLRoEbKzs2E0GnHhwgW89957UCqVXqgpEZH36XQ6Lp5LVAO3pw6Ij4/HLbfcgrVr16Jv374YPHgwbrjhBrRs2dKp1pqJEye6UwUiInKDRqOB0Wh0OHUKUVPnkakDAEAmk8FisWDHjh3YsWOHU/vLZDKGJSIiL9JoNJDJZJyMksgBt2fwtq73Vt19IiJquIqKijgZJVEN3ApLX3/9tafqQURE9cxgMECn03G8ElEN3ApLDz/8sKfqQURE9Uyj0UCv1yM6OtrbVSFq0DixBhFRE6XVaiGE4GSURDWodcvS5cuXkZmZidLSUkRERKBHjx5o2bKlJ+tGRER1qKSkhEGJyAkuh6W9e/di+vTp2L17d5VtgwYNwqJFizBgwACPVI6IiOqG2WxGaWkpxysROcGlbrgNGzZg6NCh2L17N4QQVW67du3CkCFDsH79+rqqLxEReYBWq4Ver2dYInKC02FJrVbj4Ycfhl6vl6YHaN++Pa6//nq0b99eKmcwGPDwww9DpVJ5vrZEROQRWq0W5eXlCAhwewYZokbP6bD07bff4urVq5DJZOjfvz+OHj2KU6dO4c8//8SpU6dw7NgxqfstPz8f3377bZ1VmoiI3KNWqzkZJZGTnA5La9euBQDExsZi/fr16NKli832zp07Y+3atWjWrJlNeSIialiEECgqKkJQUJC3q0LkE5wOS5mZmdLyJFFRUXbLREVFYeLEiRBC4PDhwx6rJBEReY5er+dklEQucDosFRUVAQB69+7tsFyvXr0AAIWFhbWvFRER1RmtVguj0ciWJSInOR2WtFotAECpVDosp1AoAABlZWVuVIuIiOqKRqOBEAJ+fpyXmMgZfKcQETUxJSUlvAqOyAUMS0RETUh5eTknoyRykcthiZeZEhH5Lut4JYYlIue53A47evRop8o5szijTCZDeXm5q1UgIqJa0mg0nIySyEW1erdYZ/C2p+IkZ47KERFR/bNORklEznMpLDkTfhiQiIgaJiEEiouL2QVH5CKnw5LFYqnLehARUR0rKytDWVkZwxKRi3g1HBFRE6HRaGAwGBiWiFzEsERE1ERYJxfmmCUi1zAsERE1EcXFxQgMDPR2NYh8DsMSEVETYDKZoFaruR4cUS0wLBERNQHW8UrBwcHergqRz2FYIiJqArRaLcxmc42TBRNRVQxLTZx60SLcNncu1IsWebsqRFSHSktL4efHP/lEtcF3ThOWs2AB1O++CxkA9bvvImfBAm9XiYjqgMViQUlJCccrEdUSw1ITlbNgAa7Mnm3z2JXZsxmYiBohnU4HvV7P8UpEtcSw1ATZC0pWDExEjY9Wq4XRaOS0AUS1xLDUxDgKSlYMTESNi1qtBsDJKIlqi2GpCXEmKFkxMBE1DgaDAXl5eVzihMgNDEtNhCtByYqBicj3XbhwASUlJVAqld6uCpHPYlhqAmoTlKwYmIh8V0lJCS5evAilUslpA4jcEOCpA+Xn52PTpk04cuQIiouLodfra9xHJpPhyy+/9FQVyA53gpKVdf8Wr73miSoRUT0wm804e/YsTCYTIiMjvV0dIp8mE0IIdw6g0Wjw/PPPY9myZTCZTC7vbzab3Tm916hUKkRERGBnixZQNND/2MwqFSz/HdjpCX5KJfzDwz12vLoQGB+PLvv3e7saRF536dIlHD58GNHR0QgI8Nj/xUSNitFohE6nw/Dhwx2Wc+sdZDKZMGrUKOzevRu1yVyN4coMU04OXI+IvsmiVns0fBFR3dDpdMjKyoJcLmdQIvIAt95Fn332GXbt2gWZTAaFQoEnn3wSI0eORMuWLZvMlReBLVogkC1LDUZgfLy3q0DkVUIInD9/HhqNBs2aNfN2dYgaBbfC0j//+U8AQEREBHbt2oVOnTp5pFK+pPuJEwhvwAHCE2OWACBh/nyOWSLyAYWFhbh8+TIiIiIaRes9UUPgVpPI8ePHIZPJMG3atCYZlHxBi9deQ8L8+W4dg0GJyDeYTCacPXsWFouFS5sQeZBbYcloNAIAevfu7Ym6UB1xJzAxKBH5jkuXLqGoqAhRUVHergpRo+JWWGrZsiWAazPEUsNWm8DEoETkO9RqNS5cuIDQ0FD4+/t7uzpEjYpbYSktLQ0AsJ+XavsEVwITgxKR7xBCICsrC2VlZQgLC/N2dYgaHbfC0jPPPIPg4GAsX74cubm5nqoT1SFnAhODEpFvyc3NRW5uLiIjIzmom6gOuBWWOnTogCVLlkCr1WLUqFE4e/asp+pFdchRYGJQIvItBoMB586dg7+/P4KCgrxdHaJGya2pA7755hsAwL333osff/wRXbt2xe23347rrrsOsbGxTq1FNHHiRHeqQLVkDUQVpxVgUCLyPdaFcuPi4rxdFaJGy63lTvz8/GyafIUQLjUBy2QylJeX1/b0XmVd7qS0tLRBz7NUk1MvvgjVu+8i/IUX0PGdd7xdHSJyQXFxMdLT0xEUFITQ0FBvV4fI59TLcicAqixz4uZSc1TPlNOn44ewMDz++OPergoRucBsNiMrK4sL5RLVA7fC0tdff+2pehARkQuuXLmCvLw8REdHe7sqRI2eW2Hp4Ycf9lQ9iIjISTqdDufOnUNwcDAXyiWqBw1zBVgiIrKr4kK5SqXS29UhahIYlhoIrVaL/fv34+LFizCZTN6uDhE1UAUFBVwol6ie1UlYunr1KjIyMrBjxw5kZGQgLy/P4+e4fPkyPvzwQ6SlpaFVq1YICgpCfHw87rnnHuzZs8fuPiqVCjNmzEBycjLkcjlat26NF154ARqNxuP1c5XRaERhYSEOHz6M/fv34/Llyz57pSAR1Q2TyYSsrCwIIbhQLlE98lhnd3Z2Nv7v//4Pq1evRnZ2dpXtrVq1wr333otnnnkGSUlJbp/v448/xsKFC9GuXTukpaUhLi4Op0+fxi+//IJffvkF33//PcaNGyeV12q1GDJkCDIyMpCWlobx48fj4MGDeO+997Bt2zZs3769QfzxiY6OhkajQWZmJqKiopCcnIxmzZpxrSciwsWLF1FUVISYmBhvV4WoSfFIWPr666/xzDPPQKfTAbA/fUB2djY++OADLFmyBB9//DEmTZrk1jkHDBiArVu3YsiQITaP79ixA8OHD8ff/vY3jB49GnK5HADwzjvvICMjAzNnzsTbb78tlX/ppZewcOFCLFq0CLNmzXKrTp7g7++PqKgomM1mqFQqHDp0CNHR0WjVqhWaNWvm1ESfRNT4cKFcIu9xa1JK4FpQeuyxxyCTyaRJKTt37oyOHTtCoVBAo9Hg1KlTOHHihBSiZDIZvvzyS7cDU3VGjRqFDRs2YN++fejfvz+EEGjZsiVUKhVyc3NtFprUarWIj49Hs2bNXFquxdOTUhYXF2Pv3r2Ijo62CUTl5eVQqVQwm82IjY1Fq1atnJ4d3Rk5OTn4/PPP8fjjj6NFixYeOSYReZbFYsHhw4dx5coVxMXFcawSkYfUy6SUOTk5ePrpp6X706ZNw0svvYRWrVpVKXvx4kW8/fbb+Mc//gGLxYKnn34aN998M+Lj492pgl2BgYEAIF1Se/r0aVy5cgWjRo2qsiJ3WFgYUlNTsX79ely8eLHaLkKDwQCDwSDdV6lUHq+3PQEBAYiOjkZ5eTmKiopQWFhoE5r4R5Oo8bt69SoXyiXyIreaJz799FPodDrIZDJ88cUX+PTTT+0GJQBISkrC4sWLsXTpUgDX5gn59NNP3Tm9XdnZ2di0aRNatGiBHj16ALgWloBrC//aY33cWs6et956CxEREdLNE+OuXBEQEICYmBhERESgoKAABw8exKFDh1BYWMhZ04kaMYPBgKysLC6US+RFboWl9evXQyaTIS0tDY8++qhT+0yaNAk333wzhBBYt26dO6evwmQyYcKECTAYDFi4cKHUr19aWgoAiIiIsLuftRvNWs6eWbNmobS0VLpdvHjRo3V3VmBgIGJjY6FUKpGbm4v09HRkZmaiuLiYoYmoEbpw4QJKS0ur/ftFRHXPrW64rKwsAMDo0aNd2u+uu+7CunXrpP09wWKxYNKkSdi+fTumTJmCCRMmeOzYACCXy6XB4g1BUFAQ4uLiYDAYpGUP4uPjkZSUxHWiiBqJ4uJiXLx4EUqlkhd3EHmRW2FJrVYDgMtrE1nLe2p+I4vFgkcffRTff/89HnroISxZssRmu/U/supajqzjj3zxPze5XI5mzZpBr9fj0qVLyMvLQ/PmzdGqVSuPDDwnIu/gQrlEDYdbYSkmJgZXr17FuXPnXNrv/PnzAFwPWfZYLBY88sgj+OabbzB+/HgsW7asyn9gNY1JqmlMky8IDg5GcHAw9Ho9Ll68iLy8PLRo0QItW7ZsVEsiqNXqWoVshULRqH4O1PhxoVyihsOtsNS9e3fk5ubi22+/xfPPP+9UM7HZbMa3334LmUyG7t27u3N6m6A0btw4fPvtt3bnH+nQoQMSEhKwc+dOaLXaKlMH7Ny5E23atKn3Qdt1wRqaysrKcP78eeTk5CAxMREtW7asciWgLzpw4AC2bdvm8n5DhgzB0KFDPV8hojrAhXKJGha33oV33nknNm3ahGPHjuGJJ57AZ5995vCyViEEnnzySRw5cgQymQx33XVXrc9t7Xr75ptvMHbsWKxYsaLaidpkMhkmT56M+fPnY8GCBTaTUi5YsAAajQYvv/xyrevSEIWEhCAkJAQ6nQ5ZWVnIyclBQkICWrZsidDQUG9Xr9b69euHTp06VXm8oKAAq1evxt13343Y2Ngq2xUKRX1Uj8htQghkZWVBo9GgWbNm3q4OEcHNsDR58mS88847uHz5Mr744gvs2bMHzz//PEaOHGnzJs/Pz8eGDRvw/vvv49ChQ5DJZGjZsiUmT55c63PPnz8fy5cvh0KhQMeOHfH6669XKTN69Gj07t0bAPDiiy9izZo1WLhwIQ4ePIi+ffsiPT0dGzZsQEpKCp599tla16UhCw0NlULTmTNncOXKFSQlJSEhIQEhISHerp7LlEqlw+602NhYTq5JPq2goABXrlzhQrlEDYhbYSk4OBirVq3CTTfdBJ1Oh8zMTEycOBHAtQ+1sLAwaLVaaSA4cO2/prCwMKxevdqtq8us4540Gg3eeOMNu2Vat24thaWwsDBs27YNc+fOxapVq7Blyxa0aNECzz33HObMmeOTwcFZMpkMYWFhCA0NhVarxcmTJ3Hp0iUkJSVx2QSiBsS6UC6ABrFWJRFd43ZneEpKCnbu3IkHH3wQR48elR5XqVRQq9VV5v7p0aMHVqxYIU0YWVvLli3DsmXLXNonIiICixYtwqJFi9w6t6+SyWRQKBQICwuDRqPBiRMnpG0mk8mLNSMi4NpKB9ZZ+omo4fDIyMGePXsiMzMTv//+O1avXo09e/YgJycHarUaSqUSLVq0wMCBA3HPPffg1ltvZdOyl8lkMqnlLycnBwBw5MgRAECLFi2k5WKIqP6oVCpcuHABYWFhbPElamA8dpmFTCbD7bffjttvv91Th6Q65ufnJw18Li8vx5EjR3Dp0iW0atUK8fHxvAqHqJ5YLBZkZWVBr9dzUDdRA8QpYQnAtavF4uLiUFZWhsOHD2Pfvn24cuUKzGazt6tG1OhVXCiXiBoeNh2QxM/PD5GRkTCbzVCpVDh06BCio6PRqlUrNGvWjF0DRHXAulBuQEAAF8olaqBcCktZWVl4/vnnAQDdunXDggULXDrZq6++imPHjgEAPvzwQ7Rq1cql/al++Pv7IyoqCmazGaWlpTahKTY2lt1zRB50/vx5lJaWIi4uzttVIaJquPSp98orr+CXX35BWFhYtZfrO/Lggw9iwIAB0Ol0CA8Pd/lqNqpf/v7+iI6ORnl5OUpKSlBUVASlUonExETExcU1ihnBibypuLgYly5dQnh4OBfKJWrAnH535uTk4KeffoJMJsPTTz+NLl26uHyyLl264O9//zuEEPj++++Rl5fn8jGo/gUEBCAmJgbR0dEwGAw4fvw49uzZgyNHjiA/P5/jmohqoeJCuY15njeixsDpsPTjjz/CYrEgKChI6oqrjeeeew7BwcEwm8348ccfa30cqn/+/v6IiIhAXFwcgoKCcOnSJaSnp2Pv3r3Izs5GWVmZt6tI5DOsC+VGRUV5uypEVAOnw9Kff/4JALjxxhvdWgU7KipKWtB0+/bttT4OeY9MJkNISAji4uIQGRkJnU6HI0eOYM+ePTh27BgKCwthsVi8XU2iBosL5RL5FqfDUkZGBmQymUdWbr/hhhsghMChQ4fcPhZ5V0BAACIjI6Wr5bKzs3HgwAHs378fly5dgl6v93YViRqUigvlOlrnkIgaDqf/pSkoKAAAJCQkuH1S6zHy8/PdPhY1DDKZDKGhoQgNDYXJZIJKpUJhYSFCQ0MRHx+PZs2aITIykrO3U5NnXSiX7wci3+F0WLKOR/HEFVDWY+h0OrePRQ1PYGAgoqKiYLFYoNPpkJWVhezsbERHR6NFixaIjY3lfDLUJJlMJpw9exYA3FpInIjql9NhKSoqCvn5+VILkzsKCwsBgLPVNnLW5VQUCgWMRiOKioqQl5eHsLAwJCQkIC4uDuHh4fzvmpqMixcvoqioiAvlEvkYp8NSXFwc8vPzcfz4cbdPap2YkmsgNR1BQUGIjo6GxWKBVqvFqVOncOHCBam1KSYmhgv4UqPGhXKJfJfTYSklJQVHjx7FunXr3D7punXrIJPJ0L9/f7ePRb7Fz88PSqUSSqUSBoMBeXl5uHr1KhQKhdTaxEGv1NhwoVwi3+b01XDDhw8HAJw5cwY///xzrU+4evVqnD592uaY1DTJ5XLExsYiOjoaJpMJJ0+exL59+5CZmYm8vDxOdkmNRm5uLnJzczmnEpGPcjosjRkzRupnf/LJJ3Hx4kWXT5adnY2nnnoKABATE4O7777b5WNQ4+Pv74/w8HBpssucnBykp6djz549uHDhAi8EIJ+m1+tx7tw5BAYGsquZyEc5HZZCQ0Px4osvQgiBq1ev4sYbb8SuXbucPtGuXbswZMgQ5ObmQiaT4YUXXkBoaGitKk2Nk3WyS2trk16vx9GjR6WlVQoKCjjZJfmcCxcuoLS0FOHh4d6uChHVkktTx86YMQObNm3Chg0bkJ2djRtuuAG33HILJk6ciNTU1CpzMF25cgU7d+7E8uXLsW7dOgghIJPJMGLECLeWTCHX6fV6GAyGKo9rNBqbr5XJ5XJpeRo/P796u3LNurRKeHg4ysrKcPHiRVy+fBkRERFITExEbGws19OiBq+oqIgL5RI1Ai6FJT8/P/z444+44447pOVP/vjjD/zxxx8Arn2wWqcDKCkpsflwFkIAAFJTU/Hjjz/ycvF6duHCBWmsmD0HDx60uW80GpGdnY3S0lKcO3cOx48fh1KpREpKClJSUjBgwAC0bNmyrqttM9lleXk51Go1Dh8+jNDQUDRv3hzNmzfnOBBqkKwL5ZaXl3OaFCIf5/KiRBEREdiyZQtmzZqFjz/+2CYQ6fV65Obm2t1PLpfjqaeewltvvcW1kLwgOTkZ8fHx1W43Go04evQoMjIykJGRgRMnTqC8vNymTElJCTZu3IiNGzcCuDYTuzU4paSkuLVmoDMCAgIQFRUFIQR0Oh3Onz+PixcvIioqipNcUoNz+fJl5Ofn1/n7gojqnkxYm3xqIScnB4sXL8b69etx8ODBKuNJ/Pz80KdPH4waNQpPPPGER5ZKaShUKhUiIiI8NhahuLgYe/fuRXR0dL0015tMJhw5cgT79+/H/v37cfjwYRiNxmrLt2rVCkVFRdV21wFAhw4dpPDUt2/fehmTZjQaodFoUFpaiqNHj2Lo0KFo27YtwsPDoVQq2fVBXqHVarF//35YLBaOVSJqwIxGI3Q6XY1X57sVlirS6XTIzc1FYWEhhBCIiYlBfHy8R5ZHaYh8LSyVl5fj2LFjUjg6dOiQ3TFMVq1atUK/fv3Qv39/9OvXD7GxsSgvL8eJEyewd+9e7Nu3DxkZGTCZTHb39/f3R48ePZCSkoKBAweie/fuddqiWFxcjJ07d6JHjx4ICQlBQEAAQkNDERsbi8jISISHh3OME9ULIQSOHj2K7OxsNGvWjEMOiBqweg9LTU1DD0tmsxknT56UwlFGRobDS/ATEhLQv39/KRw1b968xnPo9XocOnRICk/Hjx9HdS+nkJAQ9O3bVwpP7dq182goLC0txY4dO3DDDTcgIiICJpMJZWVl0Ov1kMlkkMvlCA8PR2xsLMLDwxEeHs5ZlKlO5OXlISMjAwqFguu/ETVwzoYlDh5qJCwWC06fPi2Fo4MHDzrsMmvevLnUctS/f/9adZEGBwdj4MCBGDhwIIBrgeXAgQPYu3cv9u7di+zsbKlsWVkZdu7ciZ07dwK4ttagtctuwIABHu+itc5pEx4eDovFAoPBgOLiYuTl5cHf31+aosDa6hQaGsoWAHKbyWRCVlYWAC6US9SYsGWplrzdsiSEQFZWlhSO0tPTUVpaWm35mJgYKRj1798fLVu2rPNwkJubi3379knhybqAsj2JiYlScEpJSXH56iH9J59AvmwZDJMmIfi/E59Wp7y8XGp1EkJALpdDoVBIC/uGh4dz8kCqlbNnz+LkyZOIjY1lyyWRD2A3XB2r77AkhMCFCxewf/9+HDhwAAcOHEBRUVG1x4uMjLRpOWrdurVXW06s4W7fvn3Ys2cP0tPTodVqqy3fsWNHDBw4ECkpKejTp4/j8UZLlwJLlvzv/rRpwOTJTtfLYDBAr9fDaDTCz88PwcHBiI6ORnR0NMLDw6FQKNjqRDVSqVQ4cOAA/Pz8oFAovF0dInICw1Idq+uwJITA5cuXpZajAwcOID8/v9r9w8PD0bdvXykctW3btkFfCWYdcG5tdcrMzKwyVYFVQEAAevbsKbU6devW7X+DxSsHJSsXAlNFZrNZanWyWCwICgpCaGgo4uLipEky2b1ClVksFmRmZiInJ4cL5RL5EIalOlYXYem3337DmTNnkJ6ejv3791c7ZxUAhIWFoU+fPlI46tChg083+5eVlSEjI0MKT6dOnap2sHhYWBj69u2LAWYzUv76C+0A2G33qWVgshJCSAPFDQYDZDIZgoODERUVJbU6cXqCps1sNkOr1aKwsBAnT55EZGQku3CJfAjDUh3zZFh6/fXX8eWXX+L8+fPVlgkJCUHv3r2lrrXOnTs36sk9S0pKsH//fik8Xbp0qdqyMQBSAPQD0ANAW1RY9NDNwFSRxWKBXq9HWVkZzGYzpydogqzzelnn9rKuVGAymRAcHMw5lYh8DK+G8yH5+flVgpJcLkfPnj3Rr1+/ql1PTUBkZCRGjBiBESNGALi2zqB1ioJ927ejqKxMKlsIYN1/bwCgwLXQ1BNAzyVL0N1oRNgTT7hdJz8/P2npFQBSq1NWVhanJ2iErDPFa7VaqNVqFBcXQ6PRwGAwwGKxwN/fX7o4ICAggOPaiBoxtizVkidbln755ReMGzcOnTp1kgY1d+/evUGNjTGbzTAajQgICPDuB8PSpRBLluAsgD0A9gE4AKDMwS5+ANrHxKDnsGHo0aMHevXqhcTERI8+B+v0BHq9HiaTidMT+KDy8nJotVpoNBqo1WoUFRVJA/+FEAgMDIRcLodcLmcIJmok2A1XxzwZlgwGAwoKCnDkyJF6W+7EWUajEWq1GhaLBcHBwTCZTDCbzRBCwM/PD4GBgQgICJDmNarTMFDNYO5yAEcBZFa4VT9JwTXR0dHo2bOndOvSpYtHw6l1egJrK4RcLkdISAjCwsKkyQqDg4Olr02p1bChMBgMUpdaSUkJSktLYTAYUF5eLrUUyuVyBAUFMeQSNVIMS3XM2/Ms1SUhBMrKyqDRaBAQEIDo6GgkJCQgKioKRqNRGrej0+mgVqtRVlYGk8mE8vJyCCEgk8mkABUUFISAgAD3n1N1V73Zqz+AK/hfcDoE4AwAi4N9AgIC0KVLF/Ts2VNqfYqLi3Ovztb6/Hd6AqPRKIVNAJDJZFLYlMvlUCqVCA0NlUKUNUixFcN9FoulSpeaVquV5tqydqnJ5XIO0CZqQhiW6pg1LO1s0QIKD4Qbi8UCo8kEPz8/+1d21QMBQFgsUuDx8/eHv5+f05NkVrxZ/vsV1q//Zf0PvfJXh7Taazc3aFGh9cnfH5kWCzQ1vPRb+PmhZ2AgegYGoldgINoHBCDAgy0MArj286n0FQAgk117Hfz3q5+f37Wf1X/vy2Qyn2jtCIyPR5f9++v9vOXl5VKrUeUuNQAICgqSWo0YRomaLg7wriemnBzYX0rWdd7+ky1D1Uvwzf+9eeJY3hQGYMB/bzCbYQFwDsBhXGt5ygRwodI+ORYLcgwGrP/vgsPBALrj2uDxXv/9GuFGnWSVvjoi/nujqqwtd/a61Mxms9SlFhISgoiICJ8ImUTUsDAsuSmwRQsE+mjLkhACFosFkMngJ5PB398ffv7+9XJ+m5Yo/K9FS9hrYdHp4OdgEWCXhYXBLywM7QC0AzD6vw+XWCw4bDIh02TCIZMJR00mGCrspgew/783q9b+/jatT8n+/vCr4w9ja0td5a8AqrQ8VbzB+n2d1s5WYHy8x49psVig1WqlLrWioiLodDoYDAYIIaRuzYiICI4FIyKPYDdcLfnqmKWKYzfkcjni4uKQkJDQYMZKWa8os96s3Sjiiy8g//pr90/iwrxL5eXlOHXqFDIzM6Wbo4lCgWszqffo0UMa99StWzdpqoH6YDabpfFjlceR+fv7SwPxw8LCEBYWhuDgYGmMlHWsTsU/Cd763t42g8EAlUqF4uJiaQwY8L8uNblc7vXXMBH5Fo5ZqmO+FpasYziMRiNCQ0ORkJCA+Ph4KJVKj5+rLhiNRlyePx9Fb7xR+4N4YILKq1ev4vDhwzh06BAyMzNx4sQJacC2PX5+fujQoQN69uyJtm3bIiEhAYmJiWjRokW9Tg0hhKgSpKxXNVqDVMWxO9X9WXAUbupyX5lMJl2BWXEgNrvUiMgdHLNEAK5dHq1WqwEAERER6NixI5o1a9ag5nByRlBQENq8/jqC5XJcmT3b5f11EyfCPG4cggwGBAYG1jqQNm/eHM2bN5cmy9Tr9Th+/DgOHTqEw4cPIzMzE8XFxVJ5i8WCkydP4uTJk1WOFRsbi4SEBJtbYmIiEhIS0Lx5c492IVmvULR3TCEEysvLr3XJVihf3XFqeqwu9iUi8iaGpUao4szDgYGBaN68ORISEhATE+PzV/60eO01AHApMIVMn47ASZOgUqmg1+uhUqmkFoygoCCbKQ5c/bAODg5Gnz590KdPHwDXfvaXLl2SWp4yMzNx9uxZuy0mBQUFKCgoQGZmZpVt/v7+aNasWZUQZb3FxsZ6rAXSOoUBERHZx264WmqI3XBmsxkajQZ6vR6hoaFo0aIF4uPjER4e3uj+Y89ZsMCpwJQwf74UsCqu7VZWVgatVguVSgWdTgeTyQST6dp1jdaxPdYg5W7A1Gg0OH78OC5duoQrV67Y3AoLa5o+076goCDEx8dLIapFixbS94mJibzqi4jICeyGa0IqzrIdHh6Odu3aoVmzZo16UVdnWpgqBiWg6tpuVtbZtnU6nTQZp0qlgsFggFarheW/V+pZB0dbQ5SzYUShUCAlJQUpKSlVtun1+ioB6vLly9L31i7UyoxGI7Kzs5GdnW13u3VcWsUQVbGFKiwszKm6ExERw5LPqjzLdkxMDBITExEbG9tkLpd2FJgqByVHAgICoFQqbQa7W6++srZC6XQ6lJaWQqvVSi1RFZd8sQYoV3/2wcHBaNu2Ldq2bWt3u1qtthuirDe9Xm93P51OhzNnzuDMmTN2t0dERFQZL6VUKqWr40JCQmxu1sebymuLiKgi/uXzMRaLBRqNBmVlZQgJCUFycjLi4+MRFRXVJLtd7AUmV4JSdWQymRQQoqKipMfNZrMUoKxdeaWlpdDr9dDpdNKVcQEBAVKAcmdAuVKpRKdOndCpU6cq24QQKC4urjZI5eTkoLy83O5xS0tLUVpaiuPHj7tUn8DAQClAWSd6rByoanqsusd56T8RNVQMSz7CZDJBrVajvLwcCoUCnTt3RvPmzdmdgmuBSa1WQ/Xuuwh/4QW3g5Ij/v7+UCgUUCgUNo9b+72tIUqlUknjxyoOKPf390dAQIB0qb71fm1CgkwmQ3R0NKKjo9G9e/cq281mM/Lz86uEKGu4ysvLq/ZS/epYx3apVCqX6+uM6gJYaGgooqKipOcbExMjfY2JiUF4eDiDFhHVGYalBs7a1ebn54fIyEgkJiaiWbNmvHqpEuX06fghLAyPP/64V84fFBSEoKAgREZGSo9VHlBuven1eml1e71eD7PZDIvFYrNeXsVAZf1eWh/OSf7+/oiPj0d8fDz69u1bZbvJZEJubi6uXLmC3Nxcm7BnnRS0cr3tPeZonilXGQwGGAwGlJSUuLSfv7+/FKasQapimKr4eEREhM9fFUpE9YthqQGyzrKt0+kgl8ulMSUNYZZtcl51A8qBa79jayuN0Wi0+VoxmJSXl0vde9Z1zqwTSdprofL393c6UAUGBiIpKQlJSUluPU9rna31rvi1uu8dPVb5qzOtX2azWZqKoSZ+fn5VglXlgGX9PioqisGKiBiWGpqSkhKUl5cjNDQUHTp0QPPmzX1mlm1yXsWZqKtjnSzSXqCqOPjcet8aqiqGC092+1XHOi7LE1NoVGYdaK/T6VBUVCTdCgsL7X4tKiqqsaXLYrGgsLAQhYWFOH36tMOy1hZde0GqYtCKjY1FdHR0kxw3SNQUMCw1ENYBxXK5XOpq87VZtsmzrJNFBgYGOlxfzrqMib1AZW2dsXb7Wb9au/2sV/RZg5Sfn5/U3Wf9vuL9+lZxoH10dHSN5S0WC1QqlRScCgoKqgSsiverGwBf8XjW8jWJi4tD9+7d0bNnT/To0QOdO3dGcHCw08+ViBouhqUGIjw8HD179kR4eDib/R1Qq9XQaDRVHrd2v1TXDaNQKBptC5016Dj6YLbX7Wf93hqojEajFKSEELBYLNJNCCHdrK0n1hasyuGquu/rI3RZW4IiIyOrnY7BSggBtVottTLZC1UVt1knLa1Ofn4+tmzZgi1btgC49nvp1KmTFKC6d++OxMREtj4R+SDO4F1Lnp7Bm5yzdetWbNu2zeX9hgwZgqFDh3q+Qo2MdcFdi8UijZOqeLP3uLWrsPIivZ4OXRW7Er3xc9FoNNWGqsuXL+Po0aPQarUOj2O9ctEanrp169aoJ48lauicncGbYamWGJa8o7qWpZo05palhqim0GVvW02hy1qm4oK/FcdkWRcKdmWQuyeZzWacO3cOR44cweHDh3H48GFkZWU53Mff3x/t2rWTwlOPHj3QqlUrtj4R1ROGpTrGsERU96whyRqUjEajdLMOctfpdNJYLGvZiq1VlYOUpwe4O6JWq3H06FEpPB0+fLjaJWysIiIipODUo0cPdOvWrcq8XkTkGQxL1di3bx/mzJmDv/76CyaTCT169MCMGTNw3333uXQchiWihsNisdgEKWuYss6srtfrpZaqigPcAVSZeqEuW6csFguys7Nx+PBhZGZm4siRIzh79qxNa1llMpkMbdu2lVqfevbsieTkZE4jQuQBDEt2bNmyBaNGjUJwcDDuv/9+KJVKrFq1ChcuXMB7772H5557zuljMSwR+Q4hhDSg3V7rVMUrBq2tU9b96rp1SqvV4tixY1J4Onz4cI2TciqVSnTv3l0KT926dePfIaJaYFiqpLy8HJ07d8alS5ewe/du9O7dG8C1NbIGDBiA8+fP49SpU0hOTnbqeAxLRI2L2WyuEqasVwtaZze3hqnKY6cqtkZVvPqv8mB1Z1qrhBC4dOmSTdfd6dOna5w/qk2bNjZTF7Rp04ZX1hLVgGGpkg0bNmDUqFF45JFH8NVXX9lsW758OSZNmoR58+Zhtp0V7O1hWCJqWmpqnbLOuG4dlG7vBsDuVYD2glXFm8FgwIkTJ3DkyBGp9amwsNBhfcPCwtCtWzebq+8qLsdDRM6HpSYzz9LWrVsBAGlpaVW2jRo1CgAcXpJuXbPKqq4WEiWihkkmk0lrADri6ArAylf/WScUrXyzWCxS65X1lpycjFatWuHWW28FAFy9ehUnTpyQbmfPnrWZZFOr1WLv3r3Yu3cvACAqKgpr167llXZEFTi7tmWTCUvWZQ06dOhQZVt8fDwUCoXDpQ/eeustzJs3r87qR0SNg7U1qLaLXVvnprIXrCreunbtihtvvFEKWNYr7w4dOiS1QFWcpLVTp04oLS311NMkajQcrZBg1WS64dLS0rBx40acPn0a7du3r7I9MTERGo2m2j8m9lqWkpKS2A1HRA2ONWxduHABu3btwt69e9GjRw+MGzfO21UjanD8/PxqnIevybQsuaumRU+JiBoKa+tW+/bt0b59e0yYMMHbVSLyaU1moo6IiAgAqLblyDpgm4iIiKiiJhOWrGOV7I1Lys3NhUajsTueiYiIiJq2JhOWhgwZAuDaFAKVrV+/3qYMERERkVWTGeBdXl6OTp064fLly9VOSnny5Em0bt3aqeNxniUiIqKmockM8A4ICMDSpUsxatQo3HjjjXaXO3E2KBEREVHT0WRalqz27t1rdyFdVy+pZcsSERFR09DkwpKnMCwRERE1DU1mgDcRERFRbTAsERERETnAsERERETkQJO5Gs7TrEO9VCqVl2tCRERE7lAqlZDJZNVuZ1iqpcLCQgBAUlKSl2tCRERE7qjpYi2GpVqKjo4GAGRnZ3NNOaJKVCoVkpKScPHiRV4tSlQB3xsNk1KpdLidYamW/PyuDfeKiIjgC56oGuHh4Xx/ENnB94Zv4QBvIiIiIgcYloiIiIgcYFiqJblcjjlz5kAul3u7KkQNDt8fRPbxveGbuNwJERERkQNsWSIiIiJygGGJiIiIyAGGJSIiIiIHGJaIiIiIHGBYctG+fftw6623IjIyEmFhYRg0aBBWrlzp7WoRedSKFSswdepU9O/fH3K5HDKZDMuWLau2vEqlwowZM5CcnAy5XI7WrVvjhRdegEajsVveYrHg448/Ro8ePRASEoK4uDiMHz8eWVlZdfSMiDzj8uXL+PDDD5GWloZWrVohKCgI8fHxuOeee7Bnzx67+/D90QgIctrmzZtFYGCgUCqVYsqUKWLGjBkiOTlZABDvvfeet6tH5DHW13VsbKz0/ddff223rEajEb179xYARFpampg5c6ZIS0sTAERKSoooKyurss/kyZMFANGtWzfx4osvioceekgEBQWJ6OhocerUqTp+dkS1N3PmTAFAtGvXTjz22GPipZdeEvfcc4/w9/cXfn5+4p///KdNeb4/GgeGJSeZTCbRrl07IZfLxcGDB6XHS0pKRMeOHUVQUJA4f/689ypI5EEbN26UXs9vvfWWw7A0e/ZsAUDMnDnT5nHrh8qbb75p8/jmzZsFAHHjjTcKg8EgPf7HH39IHyhEDdWqVavE1q1bqzy+fft2ERgYKKKiooRer5ce5/ujcWBYctL69esFAPHII49U2bZs2TIBQMybN88LNSOqW47CksViEQkJCUKhUAiNRmOzTaPRCIVCIdq2bWvz+Pjx4wUAsW3btirHGzp0qAAgLly44NHnQFQfrC1G+/btE0Lw/dGYcMySk7Zu3QoASEtLq7Jt1KhRAIBt27bVZ5WIvO706dO4cuUKUlNTERYWZrMtLCwMqampyMrKwsWLF6XHt27dKm2rjO8l8mWBgYEAgICAa2vU8/3ReDAsOen06dMAgA4dOlTZFh8fD4VCIZUhaiocvS8qPm4tp9VqkZOTgzZt2sDf37/G8kS+Ijs7G5s2bUKLFi3Qo0cPAHx/NCYMS04qLS0FAERERNjdHh4eLpUhaiqceV9ULOdqeSJfYDKZMGHCBBgMBixcuFAKOnx/NB4MS0RERLVksVgwadIkbN++HVOmTMGECRO8XSWqAwxLTrIm/eoSvUqlqva/AaLGypn3RcVyrpYnasgsFgseffRRfP/993jooYewZMkSm+18fzQeDEtOctRXnJubC41GU22/NFFjVdMYispjNsLCwtCiRQucO3cOZrO5xvJEDZXFYsEjjzyC5cuXY/z48Vi2bBn8/Gw/Uvn+aDwYlpw0ZMgQAMCGDRuqbFu/fr1NGaKmokOHDkhISMDOnTuh1Wpttmm1WuzcuRNt2rRBUlKS9PiQIUOkbZVZ30s33nhj3VacyA3WoPTNN99g3Lhx+Pbbb6sdkM33R+PAsOSk4cOHo23btvj++++RkZEhPV5aWoo333wTQUFBmDhxovcqSOQFMpkMkydPhkajwYIFC2y2LViwABqNBlOmTLF5/PHHHwcAvPbaazAajdLja9euxdatW5GWlobk5OS6rzxRLVi73r755huMHTsWK1assBuUAL4/GhOZEEJ4uxK+YsuWLRg1ahSCg4Nx//33Q6lUYtWqVbhw4QLee+89PPfcc96uIpFHLF26FH/++ScA4PDhw0hPT0dqairat28PABg8eDAmT54M4Np/yKmpqTh06BDS0tLQt29fpKenY8OGDUhJScG2bdsQEhJic/wpU6Zg6dKl6NatG2677Tbk5OTgxx9/hEKhwK5du9CxY8f6fcJETpo7dy7mzZsHhUKBv//979KcShWNHj0avXv3BsD3R6Ph7Vkxfc2ePXvEzTffLMLDw0VISIgYMGBAlbWAiHzdww8/LABUe3v44YdtypeUlIhnn31WJCUlicDAQNGqVSvx3HPPCZVKZff4ZrNZ/N///Z/o1q2bkMvlIiYmRowbN06cOXOmHp4dUe3V9N6Andnu+f7wfWxZIiIiInKAY5aIiIiIHGBYIiIiInKAYYmIiIjIAYYlIiIiIgcYloiIiIgcYFgiIiIicoBhiYiIiMgBhiUiIiIiBxiWiIiIiBxgWCIiIiJygGGJiIiIyAGGJaJG6vz585DJZJDJZJg0aZK3q0N1bMeOHZDJZPD398ehQ4e8XZ068ccff0Amk0Eul+PUqVPerg41IQHergBRUyeTyew+HhgYiPDwcISHhyMxMRF9+vRBv379cMcddyA6Orqea1lVSUkJPvzwQwBA7969MXr0aK/Wpykzm8148sknAQATJkxAr169vFyjunHrrbdi6NCh2Lp1K5555hmsW7fO21WiJkImhBDergRRU1ZdWKqOXC7H3Xffjddffx1t27atttz58+fRpk0bAMDDDz+MZcuWuVPNej8+Oe+rr77CY489Bj8/P5w4cQIdOnTwdpXqzObNmzF8+HAAwKZNm6TvieoSwxKRl1UMSz///LP0vRACarUaJSUlOHLkCP766y8cPXpU2h4WFoaPPvoIjz76aL3W14phqWEwmUxo3749srOzce+99+Knn37ydpXqXEpKCvbv349BgwZh165d3q4ONQHshiNqQGrqytq9ezdeeuklbNu2DVqtFpMnT0ZoaCjuv//++qkgNTg//vgjsrOzAQB/+9vfvFyb+jFt2jRMnjwZu3fvxs6dO5GamurtKlEjxwHeRD5k0KBB+M9//oPHH38cwLXWp0ceeQQXL170cs3IWxYvXgwASEpKwrBhw6otZzAYEBgYCJlMhqFDh9Z43EGDBkEmk0GpVKKhdUDcd999CA4OBgB88sknXq4NNQUMS0Q+xt/fH5988glSUlIAAHq9Hm+++WaVcs5cDWexWPD9999j9OjRSE5ORkhICIKDg5GYmIhevXph7Nix+PTTT1FYWFjluNYuOABYvny5dK6Kt61bt9qcT6/XY82aNXjmmWdw/fXXIy4uDoGBgVAqlejQoQMmTJiAjRs31vgz2Lp1q3SOuXPnAgCuXLmCl19+Gd26dYNCoUB4eDj69OmD+fPnQ61W13hM4FqgWLp0Ke6++260bt0aYWFhkMvlSEpKwq233or33nsPV65ccXgMvV6Pf/zjH7j99tuRlJSE4OBgREREoHv37njmmWc8ehXXyZMnsXv3bgDA3Xff7XD827Fjx1BeXg7g2oB8RywWCw4fPgwA6NmzZ5Xj2vv5nzlzBn//+9/RqVMnhIWFIT4+HmlpadiwYUOV4//111944IEH0K5dOwQHB6N58+YYO3as01fxKZVKpKWlAQB++eUXlJaWOrUfUa0JIvIqANLNFf/+97+l/cLCwoTRaLTZfu7cOWn7ww8/XGX/goICMWjQIJvzV3d799137R63ptuWLVtsztmmTRun9rvrrruEWq2u9rlv2bJFKjtnzhyxfv16ER0dXe3xOnbsKC5duuTw57l582aRmJhYY9169+5d7TG2bt1a4zH8/f3Fm2++6bAuznrzzTel465evdph2WXLlkllv/76a4dlT5w4IZWdNm1ale2Vf/6rV68WCoWi2uf8+uuvCyGEsFgsYvbs2dWWCwwMFP/+97+deu4ffPCBtN8PP/zg1D5EtcUxS0Q+6vbbb0dkZCRKSkqg1Wqxb98+XH/99U7vP2XKFKlVIikpCffffz86dOiAqKgoaLVanD59Grt27cKOHTts9mvWrBl+/vln5OXlYerUqQCAYcOG4Zlnnqlyju7du9vc1+l0iIyMxE033YQ+ffogOTkZoaGhUKlUyMzMxI8//oicnBysWbMGjz76KFauXFnj88jIyMB7770Hk8mESZMmYfDgwVAqlTh58iQ+/fRT5Obm4tSpU3jkkUfstnIA11onxo4dK7W8dOzYEWPHjkWnTp0gl8uRk5ODvXv34vfff6+2S2rt2rW46667YDKZ4Ofnh5tvvhkjRoxAYmIi9Ho99u/fj2+++QalpaV4+eWXAQCzZs2q8fk5sn79eun7QYMGOSybmZkpfV9Ty1LFFp6apiFIT0/HwoUL4e/vj6eeegoDBgyAv78/tm7diq+//hrl5eV49dVXkZqaivT0dMyfPx/JycmYNGkSOnfuDK1Wi5UrV2LDhg3S7/DkyZOIjY11eN6Kz3fdunUct0d1y9tpjaipQy1bloQQYtSoUdK+H374oc02Ry1LV69eFX5+fgKAuP7660VZWVm158jLyxPHjh2r8nhNLVf2/PHHH1VawCrSarVi9OjR0nF37Nhht1zFlg0AIiEhQRw5cqRKuZycHNGyZUup3IEDB6qUOX/+vFAqlVKZefPmifLycrvnLSsrE7/99luVx69cuSK1bDVr1kzs2rXL7v6XLl0S3bt3l1qYjh8/Xu3Poibl5eUiLCxMABBJSUk1lh8xYoTUemMwGByWffnll6Wfx19//VVle+Wff+vWrUVWVlaVcsuXL5fKdO/eXcjlcnHbbbcJnU5XpezEiROlsu+8806Nz0ev14ugoCABQHTq1KnG8kTu4JglIh+WnJwsfZ+fn+/0fllZWbBYLACABx98UBosa09cXBy6dOlS+0pWcMsttyAwMLDa7aGhoVi+fDnCwsIAXBsL5YwVK1agW7duVR6Pj4/HK6+8It1fu3ZtlTJvv/22NKbpiSeewOzZs+Hv72/3PMHBwbjtttuqPP7uu++iqKgIAPCvf/2r2laexMRE/PTTT/D394fZbMb//d//1fzkqnHu3DlotVoAQOfOnWssb21Z6tKlC4KCghyWzcjIAHBtWosePXrUeOzvvvvOZgyb1cSJE6U5n44cOYKIiAh8//33CAkJqVL29ddfl8ZGOTPZpFwul+YZO3XqFPR6fY37ENUWwxKRD4uKipK+rzgIuybWMAIABw4c8Gid3BUeHi59QFu7CR3p3bu3w6vARo4cKX1/5MgRm21msxnff/89gGsfvtbByq4QQuCbb74BAFx33XW44YYbHJbv3LkzBgwYAMC2G81V58+fl76vaUb3q1evIi8vD0DNXXDA/7rh2rZtC4VC4bBs3759HXb/Vrysf+LEiQgPD7dbLikpSQr/x44dq7GOwP+etxBCmj6BqC5wzBKRDxMVxs+4MhN4165dkZiYiMuXL+Orr76C2WzGlClTMGjQoGpbVTyluLgY3333HdatW4cjR46gsLAQWq3W7ligS5cu1Xi86667zuH2li1b2py7oszMTKhUKgCQrs5z1bFjx6SgGhUVhV9++aXGfaw/43PnzkGv1zts2auOtSULAGJiYhyWrTheqaYxSIWFhbh8+bJTZYGax0rFx8dL31tDoqOy58+fr/J7qk7F513x50HkaQxLRD6s4odKTR+YFfn7++Pzzz/H3XffDYPBgOXLl2P58uUIDw/HwIEDkZqaihEjRuD66693eTkWR9asWYPHHnvM6VYwa5BxpKaBwHK5XPq+cldNxTDWtWtXp+pUWcUWnj/++AN//PGHS/sXFRUhISHB5fMaDAbpe6VS6bCsK4O7rV1wwLVpA2pS0+uu4s/f2bIVn5sjFVupysrKnNqHqDYYloh8WMUPaldbRW699Vbs378f8+bNw7///W8YjUaoVCps3LgRGzduxNy5c9GmTRvMnz8fDz30kNt13bVrF+69917pirOePXtixIgRaN++PaKioiCXy6Vg9uqrr+Lo0aPSuCpH/PxqP5qgYhirqbupOiUlJbU+PwAYjcZa7VcxhNQUKuvqSjjAtZ+/O78reyrOr2RvHBSRpzAsEfkoi8WCPXv2SPcHDhzo8jG6d++On376CVqtFjt37sTu3buxY8cO7NixAwaDAefOncOECRNw9uxZzJkzx636zp49WwpKixcvxhNPPFFt2TfeeMOtczmrYsuERqOp1TEqhqwZM2bg/fffd7teznClC8oallq2bFnj+KaKY9icaVnypootlDU9LyJ3cIA3kY/69ddfpRYFhUKBfv361fpYYWFhSEtLw+zZs7Fx40bk5+djwYIF0vY33ngDubm5tT6+yWSSZvPu16+fw6AE2LaY1aWK45mcHVTs6Bj1uexMxavPHIWl8vJyHD9+HABqvKrRYrFIvyelUmn3CreGxPq8ZTKZzZWhRJ7GsETkg0wmE15//XXp/qRJkxAQ4LmGYqVSiVdffRV33XWXdL7KV6ZV7FKxNzi7ooKCAqlVqX379g7L7tu3DwUFBbWptst69uyJiIgIANeW4HBl+gWr3r17S8fYsmWL0+Nt3NW6dWtprJI1DNlz6tQpqU4Vr4K0Z926ddJyLvaWOWlI9Ho9zp07BwDS5KFEdYVhicjHmM1mPPXUU9i/fz+Aa2M1XnrppTo5V8WWBWvYsarY/WSd76c6FT+kz5w547Csu919rvD398eDDz4I4Nqg4tpMHVDxGAUFBfjggw88WcVq+fn5SesDXrp0qdo16yqOV3IUqnQ6HV588UXpfkPvgktPT5fGe9V0RR6RuxiWiHzI3r17MXz4cHz++ecArnU/LF++HImJiS4dZ/369Vi0aJHDS7Tz8vKwatUq6X7lwb7R0dFSi0pGRobD1qXw8HB07NgRwLUxMf/617+qlDGbzZg+fbrdiSPr0syZM6WxS59++inmz58Ps9lst6zBYLBbv5dffhmRkZEArg1O//DDDx0OTtdqtVi6dCl++OEHt+p+8803S99XHL9WUcWwdPLkSXzyySdVyly5cgW33347jh49Kj3WqlUrt+pW1yq2dI4aNcqLNaGmgAO8iRqQynP0qNVqlJSU4OjRo9i5c6fNpIoKhQKffPIJxo4d6/J5cnJyMGPGDMycORNDhw7FoEGDpAkICwsLkZmZiR9++EEKU/fdd580E3NFw4cPx+rVq3H27Fncd999uPvuuxEZGSl13wwYMEAaePvss89KY5Xuu+8+jBs3DkOGDEFUVBTOnDmD7777DsePH0f37t0hl8vrbbLMVq1aYfny5dLacHPmzMF3332HsWPHonPnzggKCsLVq1exf/9+/Pbbb0hKSsItt9xic4zExESsXLkSd9xxBwwGA6ZPn45PP/0UY8aMQdeuXaFQKKBWq3Hu3Dns378fmzdvhl6vtxkXVhtjxoyRWoM2b96MMWPGVCljDUtyuRx+fn54+umn8d133yElJQUhISE4ceIENmzYAL1eL829BQBffvklzp49iwcffBBDhw51q551Yfv27QCuzape+fdB5HHeXGuFiGzXhnPmFhwcLMaPH293La6KHK3dVnEF+ppu9957r9BqtXbPcejQIREaGlrtvlu2bJHKWiwW8eijjzo8V48ePURWVpYYMmSIw/XyKq967+zPeMiQIdWW2bBhg4iPj6/x59GnT59qj7Fv3z7RqVMnp36u/v7+4osvvqix7jW5/vrrBQARFxdnd929pKQkqd7z5s2rtj6PP/64+PLLL6s8funSpSrHdOXnP2fOHLuvB3tq+r1bqdVqERwcLACIcePGOSxL5AlsWSJqoAICAqBUKhEeHo6WLVuiT58+6N+/P+68806bZU5qY+LEiejatSs2bdqEPXv24Pjx47hy5QrKysoQGhqKVq1aYdCgQZgwYQKGDBlS7XF69uyJgwcP4oMPPsD27duRnZ0NnU5nt0tOJpPhyy+/xG233YbPP/8c+/fvh0qlQkxMDDp16oSxY8fiscceq9Vs1p4wcuRIZGVl4euvv8avv/6KzMxMFBQUQCaToXnz5ujRowdGjhyJBx54oNpj9O/fH8eOHcPq1auxZs0a7NmzB1evXoVWq4VCoUBSUhJ69OiBoUOH4s4777SZ3bq2nnzySWlw+tq1a3HnnXdK20pKSqQr9Lp164bZs2cjKSkJH3/8MU6cOIHQ0FD07t0b06ZNw7333gu9Xo/ffvsN69evR1JSEh544AGXu3jrw8qVK6UJRp966ikv14aaApmw91eNiIh8Qnl5Odq3b48LFy5gzJgxWL16tbRt+/btUth9++23MXPmTG9V06MGDBiAffv2YeDAgU6tH0jkLg7wJiLyYQEBAZg9ezaAa8vJVBzXVnFwd/fu3eu9bnVhy5Yt2LdvHwDYTJ9BVJcYloiIfNzDDz+MHj16wGKxSMEJsA1L3bp180bVPM46KD4tLQ0jRozwcm2oqWBYIiLycf7+/li8eDEA4Oeff0Z6ejqA/4UlpVLZKGa4/uOPP7BlyxYEBQXh448/9nZ1qAnhmCUiokZICAGlUgmtVsuxPURuYssSEVEjdPbsWWlm9cbSBUfkLQxLRESN0OHDh6XvG8vgbiJvYTccERERkQNsWSIiIiJygGGJiIiIyAGGJSIiIiIHGJaIiIiIHGBYIiIiInKAYYmIiIjIAYYlIiIiIgcYloiIiIgcYFgiIiIicoBhiYiIiMiB/wcqrx9QWbJMjgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-10/figures/Network-distance-dependent-connection-probability-dSPN-to-dSPN-synapses-3D-dist.png\n", + "Plotting connection probability iSPN to dSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2304.]\n", + "P(d<5e-05) = 0.08602150537634409\n", + "P(d<0.0001) = 0.06693620844564241\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-10/figures/Network-distance-dependent-connection-probability-iSPN-to-dSPN-synapses-3D-dist.png\n", + "Plotting connection probability iSPN to iSPN (synapses)\n", + "Centering in None : Keeping 48/48\n", + "Counting connections\n", + "Requested: 10000000.0 calculated [2256.]\n", + "P(d<5e-05) = 0.1930022573363431\n", + "P(d<0.0001) = 0.17570009033423667\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/hjorth/HBP/Snudda/snudda/analyse/analyse.py:1439: RuntimeWarning: invalid value encountered in divide\n", + " p_con = np.divide(count_con, count_all)\n" + ] + }, + { + "data": { + "image/png": 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A4cOHbdgj0zRo0ED8WqlUml0w9O5pt8rKRdirl156Cd7e3gb7EhMTbdQb03Xs2NGgGGdcXBy2bt1qwx5RXcFgicgBhIaGlitoae9TO3qOWAenbMKxIAhISkoy6/iEhATxa1dX13LTcvbOzc0N7dq1M9jnKD9v8+fPh4uLi7i9cOFCm1crJ8fHYInIQdydN+Pr62ujnphnwIABBtXA//vvP+zdu7fGr2vJreh315gyJ9cqOzvboGp5ZGSkWcvG2AtH/XmLiIjA2LFjxe0bN27gm2++sWGPqC5gsETkAHJzc5GTk2Owr+yitfbuo48+MtiujTo47u7uBtslJSUmH1t26hAAdu7cafKx3333ncFdWPfdd5/Jx9oLrVZbbjTNkX7e5s6da7B0yocffgiVSmXDHpGjY7BEVAsKCwstWiNt06ZNBr+AO3bsWG5azp717t0bjz/+uLh95swZi8sfVOXuqa+MjAyTjx0wYIBBcPDnn3+Wq71UkcLCQnzyyScG+0aPHm3yda3JkrpWP//8s8ECwv7+/ujSpYs1ulUrmjdvjokTJ4rbqampBsvXEJmLwRJRLcjJyUG7du0wefJkJCcnm3Xsf//9Z1ARGwBGjRplxd7VjkWLFhlMjdV00UBPT0+EhYWJ29HR0SbfGeXq6orJkyeL2zqdDmPGjEFubm6lx+h0OkycONGg4nXv3r3Ro0ePavTecl27dsWoUaMQGxtr1nFxcXGYMmWKwb5hw4YZ5AE5gvfee8+gBAKLVJIlGCwR1ZLS0lKsX78erVq1wsMPP4ytW7caXUri5s2bmD17NgYOHAilUinuDw0NxdSpU2ujy1bVtWtXDB8+vFav+cADD4hfJyUlYcSIEfjzzz8RHx9vsHZZRf8PM2bMMCguefXqVURFRVV4N9+NGzfw5JNP4vvvvxf3ubm52XQ0QxAE7Nq1C506dcJ9992HL7/80miielZWFpYsWYKePXsajMJ5e3s75GLIISEheP31123dDaojHOtPBaI6QBAEHDhwAAcOHAAAhIWFITw8HEFBQXBzc4NMJkNcXByuX79ergKxn58ffvrpp3K3dTuKhQsXYs+ePWbfil9dr7/+Onbs2CF+H3/++Wf8/PPP5do1b9683Iifp6cnvvvuOzz44INikcr4+Hj0798f4eHh6NixI9zd3XHjxg2cOXPG4P9KIpFg1apViIyMrKFXZp4TJ07gxIkTAIBGjRqhTZs2CAoKgpeXF+RyOa5du4aEhIRyI29ubm74/vvvrV5AsrbMmjUL69evr9aCwERlMVgiqgVeXl5o2rRphSMYt27dwq1bt6o8R7du3fDtt986VO7I3dq3b4/nn38e27Ztq5Xr3XfffVi+fDlmzpxZreKEXbt2RXR0NJ544gmkpKSI+5OSkiodpfHw8MD69esN7siyhTZt2hiUMNDLzMxEZmZmlce3bt0aX3/9Nfr3718DvasdQUFBeOutt8qVryAyF6fhiGpBw4YNkZKSghMnTuDdd99FVFRUubu1KuLi4oJBgwZhx44dOHXqlEMHSnp318GpadOmTcPFixcxY8YM9OnTB8HBwSZ97/U6deqEq1evYtGiRWjSpEml7Xx8fDBu3DjEx8fbPFAC7oyCXbx4EYsWLcLAgQNNGo10cnJCVFQU1q9fj0uXLjl0oKQ3ffp0hysKSvZHInClQSKbKCkpQWJiIhISEpCWlgaFQgGdTgepVAp/f3+0a9cOHTt2hIeHh627SmWcP38ely5dQnZ2NkpKShAcHIxWrVohKirK4HZ1e6PRaJCUlISEhASkpqZCJpNBo9HAx8cHDRo0QEREBLp06eKwU7xENYnBEhEREZERnIYjIiIiMoLBEhEREZERDJaIiIiIjGCwRERERGQEgyUiIiIiIxgsVZMgCJDL5eUqLBMREVHdwmCpmhQKBfz8/FhGn4iIqI5jsERERERkBIMlIiIiIiMYLBEREREZwWCJiIiIyAgGS0RERERGOHSwJAgC9uzZgwEDBiAkJAReXl5o27YtJk2ahOvXr5drL5fLMW3aNDRv3hzu7u5o0aIFZsyYgcLCQhv0noiIiByBRHDgQkHvvPMOPv30U4SEhODpp5+Gr68vLly4gP3798PHxwfHjh1Dx44dAQBKpRJ9+/bF+fPnMWjQIHTt2hXnzp3D/v370aNHD0RHR8PDw8Pka8vlcvj5+UEmk8HX17emXiIRERHZmIutO1BdGRkZWLVqFZo3b44LFy7Az89PfG7lypWYNm0aPv30U3z77bcAgGXLluH8+fOYNWsWlixZIradPXs2li5dipUrV2LOnDm1/jqIiIjIvjnsNFxycjJ0Oh2ioqIMAiUAeOKJJwAA2dnZAO5M123YsAE+Pj744IMPDNp+8MEH8PHxwYYNG2qn40RERORQHDZYioiIgJubG44ePQq5XG7w3O+//w4AGDhwIAAgMTERaWlpiIqKgre3t0Fbb29vREVF4fr167h161al11Or1ZDL5QYPIiIiqvscNlgKDAzEkiVLkJKSgnbt2uHVV1/FrFmz8Mgjj2DWrFl47bXXMGXKFAB3giXgToBVEf1+fbuKLF68GH5+fuIjLCzMyq+IiIiI7JHD5iwBwNSpUxEaGooJEybgyy+/FPf37dsXzz//PFxc7rw8mUwGAOWm6/T0Cdr6dhWZM2cOpk2bJm7L5XIGTERERPWAQwdLCxcuxIcffoiFCxdi9OjRaNCgAc6fP4+pU6eif//+2L17N5566imrXMvd3R3u7u5WORcRUW3Ky8uDUqm0dTeI7JKTkxNCQ0ONtnHYYOnAgQOYN28epk6ditmzZ4v7+/bti99++w2tWrXCO++8g6eeekocUaps5Eiff1TZyBMRkSNLTExETk4OnJ2dbd0VIrui0+ng6elZd4Olv/76CwAwYMCAcs81btwY7dq1w7lz51BYWFhlTlJVOU1ERI5KpVKhuLgYfn5+8PT0tHV3iOxKSUkJioqKqmznsAneJSUlAP6/PMDdsrOz4eTkBFdXV0RERKBJkyY4evRouaFopVKJo0ePomXLlsxBIqI6R6lUQq1Ww83NzdZdIXJYDhssRUVFAQA+/fTTctNrX375JW7fvo377rsP7u7ukEgkmDBhAgoLC7Fo0SKDtosWLUJhYSEmTpxYa30nIqotSqUSOp2OU3BEFnDY5U60Wi0efPBBREdHo2HDhnjqqafQoEEDxMTE4N9//4WnpycOHTqEnj17ArjzgREVFYULFy5g0KBB6NatG2JiYsTlTg4fPmzWEDWXOyEiRxAbG4vU1FQEBQXZuitEdkc/Daevy1gZhw2WgDuFIleuXIldu3YhPj4eJSUlaNSoEQYMGIB3330X7du3N2gvk8kwf/587N69GxkZGQgJCcHIkSMxb948SKVSs67NYImI7J1Op8Px48dRWlpq9mccUX1QL4IlW2KwRET2TqlU4sSJE/D09GTpE6IKmBosOWzOEhERGadUKlFaWsrkbiILMVgiIqqjlEolBEGARCKxdVeIHBqDJSKiOio/P19c9omIqo/BEhFRHaTRaKBQKJirRGQFDJaIiOogpVKJkpIS5isRWQGDJSKiOkipVEKj0cDV1dXWXSFyeAyWiIjqoMLCQiZ2E1kJgyUiojooPz+fU3BEVsJgiYiojlGr1SguLmawRGQlDJaIiOoYpVIJtVrNYInIShgsERHVMUqlEjqdDs7OzrbuClGdwGCJiKiOkcvlcHLixzuRtfDdRERUh+h0OhQUFHAKjsiKGCwREdUhxcXFUKlUrNxNZEUMloiI6hBW7iayPgZLRER1iFKpBAAWpCSyIgZLRER1iEwmg4uLi627QVSnMFgiIqojNBoN5HI585WIrIzBEhFRHcFilEQ1g8ESEVEdoVQqodFo4OrqauuuENUpDJaIiOoIfXI3EVkXgyUiojoiPz+fU3BENYDBEhFRHaBWq1FUVMTkbqIawGCJiKgOYHI3Uc1hsEREVAcolUrodDo4OzvbuitEdQ6DJSKiOkAul8PJiR/pRDWB7ywiIgcnCAIKCgo4BUdUQxgsERE5uKKiIqhUKiZ3E9UQBktERA5OqVSipKSEI0tENYTBEhGRg9MXo5RIJDbuCVHdxGCJiMjByWQyuLi42LobRHUWgyUiIgem0Wggl8s5BUdUgxgsERE5sKKiIqjVaiZ3E9Ugq43bZmVl4eLFi0hOTkZeXh6Ki4vh6emJgIAAtGjRAl26dEFwcLC1LkdERLiTr6TRaODq6mrrrhDVWRYFSwcOHMCePXuwd+9e3Lx5s8r2LVq0wODBgzF06FA89NBDTEYkIrJQYWGhrbtAVOdJBEEQzDkgPz8fX375Jb744gukpqaK+005TdngqEmTJnjttdcwefJk+Pv7m9MFuyCXy+Hn5weZTAZfX19bd4eI6qlTp05BoVCgQYMGtu4KkcMpKSlBUVERBg4caLSdycGSQqHA8uXLsWrVKhQWFhoER15eXujRowfat2+PgIAABAYGwtfXFzKZDLm5ucjLy8OVK1dw9uxZFBUV/f/FJRJ4e3tj6tSpmD59OqRSaTVfbu1jsEREtqZWq3H8+HG4uLjA09PT1t0hcjhWDZa2bNmCWbNmISsrC4IgQCKRoE+fPhg+fDj69++Pzp07m7QmkVarxcWLFxEdHY3du3fj6NGj4vkaNmyIZcuWYcyYMaa/ShtisEREtpaXl4fTp0/D39+fC+gSVYNVgyV9IOTr64tXXnkFkyZNQnh4uMWdvH79Or788kt89dVX4iKQGo3G4vPWBgZLRGRrt27dQmxsLBo2bGjrrhA5JFODJZNKB/j4+GDBggW4efMmli1bZpVACQBatWqFZcuWISUlBfPnz4eXl5dVzktEVB/o/8gkoppl0shSVlZWrfzlkp2d7TDlBTiyRES2JAgCjh8/DrVazc8gomqy6shSbQ3xOkqgRERka0VFRVCpVCxGSVQLOH5LROSAioqKUFJSwmVOiGoBgyUiIgekVCrFu4mJqGbV6DLVR48eRXR0NG7fvg0ACA0NxQMPPIC+ffvW5GWJiOq8goICuLjU6Ec4Ef1PjbzT4uPjMWbMGJw9e7bC57t164atW7eiXbt2NXF5IqI6TaPRQC6XcwqOqJZYfRru9u3b6NevH86ePQtBENC4cWOxurenpycEQcDZs2fRv39/ccSJiIhMV1RUBLVazeRuolpi9WBp4cKFyMrKQqdOnfDff/8hNTUVJ06cQGxsLLKzs7FixQq4uroiOzsbixYtsvbliYjqPKVSCY1Gw2k4olpi9WDpr7/+grOzM3755Rf06dPH4DlPT09MnToVb7/9NgRBwB9//GHtyxMR1XmFhYUAwORuolpicrD07LPPIjs7u8p2WVlZCAgIQPPmzStt0717dwBATk6OqZcnIqL/yc/PZ74SUS0yOVjatWsX2rdvj2+//dZou4YNGyI3NxcpKSmVtjlz5gwAFqEkIjKXWq1GUVER85WIapHJwdLDDz+MvLw8TJw4EQ8++CASExMrbPfoo49Cp9Nh6NChOHXqlMFzKpUKq1evxqpVqyCRSPDoo49a1nsionpGqVSyGCVRLTNpbTi9bdu24Z133kF2djY8PDzw3nvvYdasWQZJhqmpqejWrZs4xdakSRM0bdoUSqUSN27cQFFREQRBQGBgIGJiYhAWFmb9V1ULuDYcEdnCrVu3EBsbW2vLUBHVZVZdG05v9OjRuHr1KsaOHQuVSoW5c+eiW7duOHHihNgmNDQUhw4dQpcuXSAIAlJTU3Hy5EnExsaKFWc7d+6Mf//912EDJSIiW1EoFHBy4uILRLXJ7HdcQEAANm3ahAMHDqBVq1aIjY1F3759MWXKFCgUCgBA+/btERMTg0OHDmHhwoWYNGkSJk2ahIULF+LgwYM4f/48OnXqZLUX8dNPP+Hhhx9GYGAgPDw80LJlSzz33HO4deuWQTu5XI5p06ahefPmcHd3R4sWLTBjxgzxzhIiInsmCAIKCgo4BUdUy8yahrubWq3G/PnzsWLFCmi1WoSGhmL16tUYMmSIFbtYOUEQMHnyZHz11VcIDw/H4MGDIZVKkZaWhsOHD2P79u3i0ipKpRJ9+/bF+fPnMWjQIHTt2hXnzp3D/v370aNHD0RHR8PDw8Pka3MajohqW1FREU6cOAEPDw8meBNZganTcBZVNHN3d8fixYvx/PPPY+LEiTh16hSGDx+OIUOGYM2aNWjSpIklp6/S6tWr8dVXX+G1117D6tWr4ezsbPC8RqMRv162bBnOnz+PWbNmYcmSJeL+2bNnY+nSpVi5ciXmzJlTo/0lIrKEPrlbKpXauitE9YpFI0tlCYKAtWvX4v3334dCoYCvry+WLFmCyZMnW+P05RQXFyM0NBT+/v6Ij483WslWEAQ0bdoUcrkcGRkZ8Pb2Fp9TKpVo3LgxGjZsiKSkJJOvz5ElIqptycnJuHr1KpO7iaykRhK8jZFIJHjjjTdw5coVPPnkk5DL5Xj99dfRt29fXL161VqXEe3fvx/5+fkYMmQItFot9uzZgyVLluDLL7/EtWvXDNomJiYiLS0NUVFRBoESAHh7eyMqKgrXr18vl+NUllqthlwuN3gQEdWmgoICLnFCZAPVDpauXbuGEydO4NKlS1CpVOL+0NBQ/PLLL9i1axcaNWqEY8eOoWvXrpg3bx5KSkqs0mkAOHv2LADA2dkZnTt3xvDhwzFnzhy8+uqraNu2LaZPny621deEioiIqPBc+v2V1Y4CgMWLF8PPz0988E4+IqpNWq0Wcrmcyd1ENmBWsKTRaLBw4UI0atQIbdu2RVRUFCIjI9GgQQM888wzSE5OFtuOGDECcXFxeOWVV1BaWooPP/wQXbp0QXR0tFU6npWVBQD49NNP4efnh1OnTkGhUCA6Ohpt2rTBihUr8MUXXwAAZDIZAMDPz6/Cc+mn0fTtKjJnzhzIZDLxYWwUiojI2pRKJdRqNRO7iWzA5GCptLQUjz76KBYsWIDs7GwIgiA+SkpKsHv3bnTv3h1xcXHiMb6+vvjyyy8RHR2Ndu3aIT4+HgMGDMArr7xiNDAxhU6nAwC4ubnh559/Ro8ePeDj44P7778fP/zwA5ycnLBixQqLrlGWu7s7fH19DR5ERLVFqVRCo9FwGo7IBkwOllavXo1//vkHgiBg4MCB+O2333DlyhVER0fjnXfegaurK/Ly8jBhwoRyx0ZFReH8+fOYN28e3Nzc8M0336B9+/bYtWtXtTuuHyXq3r17ubvuOnbsiFatWiEpKQkFBQVi28oCNH3+UWUjT0REtqavByeRSGzcE6L6x+Rgadu2bZBIJBg4cCD279+Pxx9/HO3atUPfvn3xySefiKM4x48fN5iO03N1dcW8efNw7tw59O3bFxkZGXj++eer3fG2bdsCABo0aFDh8/r9xcXFVeYkVZXTRERkayxGSWQ7JgdLCQkJAIDnnnuuwr9snnvuOfFrY4nS7dq1w+HDh7F+/XqLprIGDBgAABXeaVdaWopr167B29sbwcHBiIiIQJMmTXD06FEolUqDtkqlEkePHkXLli2ZtE1EdqmkpARKpZLBEpGNmBws6efJK1sapGwQYsqc+sSJEw3ym8wVHh6OQYMG4dq1a9iwYYPBc0uWLEFBQQGGDh0KFxcXSCQSTJgwAYWFhVi0aJFB20WLFqGwsBATJ06sdl+IiGqSvhglk7uJbMPkopT9+vXDkSNH0LZtW5w+fRo+Pj4Gz0+ZMgXr1q2Dk5MTMjMzERgYWCMdLispKQl9+vRBVlaWOC147tw5/Pvvv2jevDlOnDiBxo0bA7jzYRMVFYULFy5g0KBB6NatG2JiYsTlTg4fPgxPT0+Tr82ilERUW27fvo1Lly6xGCWRlZlalNLkYGnXrl149tlnIZFI0KhRI4wdOxYtW7ZEXl4efv/9d5w4cQIA8Mwzz+C7776z/BWY6NatW5g7dy727t2L3NxcNG7cGE899RTmzp1b7oNFJpNh/vz52L17NzIyMhASEoKRI0di3rx5Zi8fwGCJiGrL1atXkZKSgqCgIFt3hahOsXqwBAAzZswQE7nL5i3pT9G1a1f8888/lSZd1yUMloioNgiCgOPHj0OtVvOzhsjKamS5k08++QT79u3DkCFD0KhRIzg7O8PX1xe9e/fGqlWrcPz48XoRKBER1Zbi4mKoVComdxPZkNnVzR5++GE8/PDDNdEXIiK6iz6529xUASKyHqstpEtERNanVCohCAKcnPhxTWQrfPcREdkxmUzGJU6IbIzBEhGRndJqtZDL5cxXIrIxk4KlkSNH4vr16zXakUuXLmHIkCE1eg0iIkeiVCqhVqtZjJLIxkwKlnbv3o327dvjxRdfrHB5EUvExsZi1KhR6Nq1K3777TernpuIyJEplUqUlpZyGo7IxkwKlh588EGUlpZiy5Yt6NixI/r3749NmzYhPz+/WhfNycnB6tWr0b17d3Tp0gU//vgjdDodHnzwwWqdj4ioLiosLIREIqlwPU4iqj1mVfCeM2cObty4Ib5xnZ2dcc8996B3797o1asX2rVrh4CAAAQGBkIqlUIulyMvLw95eXm4evUqTp48iZMnT+Ly5cvQarViMcvw8HB8/PHHGDlyZM29UitjUUoiqmmnT5+GXC5n/TqiGlIjFbw1Gg2+/fZbrFixAomJiXdOUI2/ePSXbNu2LaZPn45x48Y53DAzgyUiqkklJSU4duwYnJ2d4eXlZevuENVJNVLB28XFBa+88gri4uKwd+9ePPvss/Dx8YEgCCY/fH19MXr0aOzfvx9Xr17Fyy+/7HCBEhFRTdMXo2RyN5HtVStKkUgkGDRoEAYNGoTS0lIcO3YMJ0+exKVLl5CcnIy8vDzxDo7AwEC0bNkSnTp1Qu/evXHffffB2dnZ2q+DiKhOUSqV0Gq1/LwksgMWD+m4urqiX79+6NevnzX6Q0REABQKBRO7iewEi1ISEdkZQRCQn5/PKTgiO8FgiYjIzhQXF0OlUrFyN5GdYLBERGRn9MndDJaI7AODJSIiO6NUKiEIApyc+BFNZA/4TiQisjMymYx3wRHZERY4qicUCgUKCwvNPs7HxwdSqbQGekREFdFqtZDL5UzuJrIjDJbqibNnz+Lw4cNmH9evXz/079/f+h0iogoVFRVBrVbD29vb1l0hov9hsFRP3HvvvWjbtm25/Tk5OdizZw+GDRuGoKCgcs/7+PjURveI6H+USiVKS0vh6upq664Q0f8wWKonpFKp0em0oKAghISE1GKPiKgi+ulyFqQksh9M8CYisiP5+fkcVSKyMwyWiIjsRElJCZRKJZO7iewMgyUiIjuhL0bJYInIvtRYzlJBQQEUCgWkUikaNGhQU5chIqozlEoltFotaywR2RmrjSwVFhZi7dq16N+/P6RSKQIDA9GiRQsEBgZCKpViwIABWLduXbVq/RAR1QcKhYKJ3UR2yCrB0m+//YaIiAi89dZbOHLkiFiqX/9QKpWIjo7GG2+8gYiICPz+++/WuCwRUZ0hCAIKCgo4BUdkhywOlrZs2YJhw4YhKytLDI6kUikiIyMRFRWFyMhI+Pr6is9lZmZiyJAh2Lp1qzX6T0RUJxQXF6O4uJiL5xLZIYuCpWvXrmHy5MnQarUQBAFDhw7F8ePHIZPJEBMTgyNHjiAmJgYFBQU4ceIEhg8fDgDQ6XSYNGkSkpKSrPIiiIgcnT65m8ESkf2xKFhauXIlVCoVJBIJli1bht27d6NXr14Vtu3Zsyd++OEHLF++HACgVquxcuVKSy5PRFRn6NMXnJx4kzKRvbHoXbl//35IJBI88MADmD59uknHTJs2Df369YMgCNi3b58llyciqjPkcjnvgiOyUxYFS6mpqQCAESNGmHWcvr3+eCKi+kyr1UImkzG5m8hOWRQs6RdZbdSokVnHNWzY0OB4IqL6rKioCGq1mvlKRHbKomCpdevWAICUlBSzjrt16xYAICIiwpLLExHVCUqlEqWlpVwTjshOWRQsjRo1CoIgYMeOHRAEwaRjBEHA9u3bIZFI8Oyzz1pyeSKiOkFfrJcFKYnsk0XB0uTJk9G5c2ecO3cOU6dONemYadOm4dy5c+jSpQsmTZpkyeWJiOqE/Px8jioR2TGLgiV3d3f88ccf6NWrF9asWYPevXvjxx9/RH5+vkG7goIC/PDDD7jvvvuwevVq3Hffffjjjz84P09E9V5JSQmUSiWTu4nsmEkL6bZq1cro86WlpRAEAadPn8aoUaMAAP7+/vD29oZSqRSDJ0EQIJFIkJKSgqioKEgkEhamJKJ6TV+MkguOE9kvk4Kl5ORkSCSSSvOSJBKJONeub5OXl4e8vLxy7QAgLS1NDJyIiOozpVIJrVbLGktEdsykYKlZs2YMbIiIaoBCoeDnK5GdM3lkiYiIrEsQBBQUFDBficjOcREiIiIbUalUKC4u5s0uRHaOwRIRkY3ok7sZLBHZNwZLREQ2olQqIQgCnJz4UUxkz0zKWTJVTk4O/vjjD5w4cQLp6elQKBSQSqVo0qQJevXqhccffxxBQUHWvCQRkcOSyWS8C47IAVglWCoqKsLMmTPx7bffQq1WV9hm/fr1cHd3x4QJE7B06VJ4enpa49JERA5Jq9VCJpMxuZvIAVg89puTk4MePXrgiy++gEqlgiAIlT5UKhU+//xz9OjRA7m5udboPxGRQyoqKoJarWa+EpEDsHhkafjw4bh69SoAwNPTE8899xwGDx6MNm3awMfHB4WFhUhISMC+ffvw/fffo6ioCFeuXMHw4cNx6NAhSy9PROSQlEolSktLuSYckQOwKFj66aefcOTIEUgkEkRGRmLPnj1o3rx5uXZdunTByJEj8cEHH2DEiBE4e/Ysjhw5gl9++QVPP/20JV0gInJIhYWFAMCClEQOwKJpuO+//x4AEBwcjL///rvCQKms5s2bY+/evWjYsCEAYMeOHZZcnojIYRUUFHBUichBWBQsnTx5EhKJBC+99BICAgJMOiYwMBAvv/wyBEHAyZMnLbk8EZFDKikpgVKpZHI3kYOwKFjKysoCAHTu3Nms4zp16mRwPBFRfaJUKpncTeRALAqW9G/0kpISs47Tt7f2EPTSpUshkUggkUhw4sSJcs/L5XJMmzYNzZs3h7u7O1q0aIEZM2aIuQNERLWhqKgIWq0WLi5WLXVHRDXEomCpSZMmAIAjR46YdVx0dDQAIDQ01JLLG4iNjcW8efPg7e1d4fNKpRL9+vXDypUr0a5dO0ydOhVt27bF8uXL8eCDD0KlUlmtL0RExigUCiZ2EzkQi4Kl/v37QxAEbN26FRcuXDDpmPPnz2Pbtm2QSCTo37+/JZcXlZaWYty4cYiMjMTQoUMrbLNs2TKcP38es2bNwr59+7BkyRLs27cPs2bNwunTp7Fy5Uqr9IWIyBhBEJCfn88pOCIHYlGwNGHCBEgkEpSWluKhhx7Cnj17jLbfs2cPHn74YZSUlEAikWDixImWXF700Ucf4fLly/j2228rXDpAEARs2LABPj4++OCDDwye++CDD+Dj44MNGzZYpS9ERMaoVCoUFxczuZvIgVg0Yd6tWzdMnjwZX3zxBfLy8jBy5Ei0atUKDz/8MNq0aQNvb28olUokJibi77//RlJSEgRBgEQiweTJk9G1a1eLX0BMTAw++ugjLFy4EB06dKiwTWJiItLS0jB48OBy03Te3t6IiorCvn37cOvWLYSFhVncJyKiyiiVSpSUlEAqldq6K0RkIouzC9esWQO5XI7t27cDAK5fv47169dX2FYQBADACy+8gNWrV1t6aajVaowdOxaRkZGYOXNmpe0SExMBABERERU+HxERgX379iExMbHSYEmtVhuseyeXyy3oOVWXQqGoVkK+j48PfzmRXVAqlRAEAU5OFq82RUS1xOJgycnJCVu3bsVTTz2FpUuXIiYmptK29957L2bPno3hw4dbelkAwNy5c5GYmIizZ88aXblbJpMBAPz8/Cp83tfX16BdRRYvXowFCxZY0FuyhrNnz+Lw4cNmH9evXz+r5cgRWUImkxn9vCIi+2O1+1ZHjhyJkSNHIiUlBSdPnkR6ejoUCgWkUilCQkLQq1cvNGvWzFqXw/Hjx7F8+XLMnz8fHTt2tNp5KzNnzhxMmzZN3JbL5Zyys4F7770Xbdu2Lbc/JycHe/bswbBhwxAUFFTueR8fn9roHpFRWq0Wcrmc+UpEDsaiYGnLli0AgMaNG2PQoEEAgGbNmlk1KKqIRqPBuHHj0LlzZ8yePbvK9voRpcpGjvRTapWNPAGAu7s7P+DsgFQqNTqdFhQUhJCQkFrsEZHpioqKoFar4eXlZeuuEJEZLAqWxo8fD4lEgvfee08MlmpDYWGhmIdU2e239913H4A7i/3qE7/1x9ytqpwmIiJr0Cd3G/vDjIjsj0XBko+PD5RKZaV3odUUd3d3vPzyyxU+Fx0djcTERDz11FMIDg5GixYtEBERgSZNmuDo0aNQKpUGd8QplUocPXoULVu2rJfTaoqVK/H4J59AoVQiZNkyW3eHqE7T35zAgpREjsWiYCkkJATXrl1DaWmptfpjEk9Pz0rrIo0fPx6JiYmYM2cOevfuLe6fMGECFi5ciEWLFmHJkiXi/kWLFqGwsBDvvvtujffb3qQvWgTFJ59AAkDxySdIl0oRclcdKiKynoKCAqsv80RENc+iYGnAgAG4du0aTp8+jTFjxlirTzVi5syZ+OWXX7B06VKcO3cO3bp1Q0xMDPbv348ePXrg7bfftnUXa1X6okVImzvXYJ9+mwETkfWVlpZCqVQy95HIAVlU6GPSpElwcnLC5s2bkZqaaq0+1Qhvb28cPnwYb7/9Nq5evYoVK1YgLi4O77zzDv755x94enrauou1pqJASS9t7lykL1pUyz0iqvuUSiXUajWXOSFyQBYFS127dsVHH30EhUKBhx9+GBcvXrRWv6pt06ZNEATBYApOz8/PDytXrkRKSgpKSkpw8+ZNLF++vF4VKzQWKOkxYCKyPqVSCa1WCxcXq1VsIaJaYnHpgMaNG+PRRx/FX3/9hW7duqFv3764//770bRpU5NGa8aOHWtJF8gMpgRKepySI7IuhULBxG4iB2WV0gHAnbs7dDodjhw5giNHjph0vEQiYbBUS8wJlPQYMBFZhyAIyM/P5xQckYOyeDxYv95bZdtke9UJlPQYMBFZTqVSobi4mMndRA7KomBp48aN1uoH1RBLAiU9BkxEltEXo6xP+ZFEdYlE4FBQtcjlcvj5+eFoSAh87HT1cK1cDp1CYbXzOUmlcP7fosP2piAwEAeHDcPD0dHo888/tu4OkYGbN2/i6tWrCA4OtnVXiKiMkpISFBUVYeDAgUbb8bYMC5Wmp6N2S3Lajk6hsGrwZU0ane7Ovzk5Nu4JUXlyuRxOdvpHFRFVrdrBUmpqKi5evAiZTAY/Pz906tQJTZs2tWbfHIJrSAhc7fRDsD6NLLkEBt75NyjIxj0hMqTT6SCTyZjcTeTAzA6WTp06halTp+LEiRPlnuvduzdWrlyJnj17WqVzjqBjXBx87TSAAKyTswQATRYutOucpfT0dBz86iu03LbN1l0hMlBUVAS1Wg0vLy9bd4WIqsmsIZH9+/ejf//+OHHiBARBKPc4fvw4+vXrh3379tVUf8lMIR98gCYLF1p0DnsPlIjsmT65m2vCETkuk4MlhUKBcePGQaVSieUBWrdujT59+qB169ZiO7VajXHjxkEul1u/t1QtlgRMDJSILFNYWAgALEhJ5MBMDpa2bt2KzMxMSCQSdO/eHZcvX0ZCQgL+++8/JCQk4MqVK+L0W3Z2NrZu3VpjnSbzVSdgYqBEZLmCggKOKhE5OJODpb/++gsAEBQUhH379qF9+/YGz7dr1w5//fUXGjZsaNCe7Ic5ARMDJSLLlZaWorCwkMndRA7O5GDp4sWL4vIk/v7+Fbbx9/fH2LFjIQgCLl26ZLVOkvWYEjAxUCKyDqVSCbVazcrdRA7O5GApLy8PABAZGWm0XZcuXQAAubm51e8V1ShjARMDJSLrUSqV0Gq1cHFhSTsiR2ZysKRUKgGgynL9Pj4+AIDi4mILukU1raKAiYESkXUpFAomdhPVAfZZTZFqRcgHH0A6YwYEANIZMxgoEVmRIAgoKChgvhJRHcCx4XpOOnUqvvP2xiuvvGLrrhDVKSqVCsXFxcxXIqoDzB5Z4pAyEVHV9MndHFkicnxmjywNGTLEpHaCIMDZ2dloG4lEAo1GY24XiIjsnlKphCAIXECXqA6o1jScvoJ3RSQSiTj6ZKwdEVFdJpfLq/yDkYgcg1nBkinBDwMkIqrvdDodZDIZp+CI6giTgyWdTleT/SAiqjOKioqgVqvh5eVl664QkRVwMp2IyMqUSiVKSkq4JhxRHcFgiYjIygoLCwHw7mGiuoLBEhGRlRUUFHBUiagOYbBERGRFpaWlKCwsZHI3UR3CYIlMolAocPv2bdbFIqqCPl+JlbuJ6g4ud0JVysrKQlxcHAoLC5GVlYU2bdqICyYTkSGlUgmNRgMXF368EtUVfDdTpXQ6HZKTk3H9+nUAQEBAADIzM6FUKhEREYFGjRoxgZXoLoWFhXxfENUxnIajCqnValy5cgXx8fFwc3ODv78/XF1dERwcDLVajYsXLyIxMZHTckRlCIKA/Px85isR1TEcWaJy5HI54uLikJOTA39/f4MPfolEAn9/fxQXF+PatWtQKBRo06YNpFKpDXtMZB/UajWKi4sZLBHVMQyWyEBmZibi4+NRVFSEoKCgSte28vT0hJubG7KysqBUKtG6dWuEhIRw+oHqNaVSCbVazZw+ojqG03AE4E5+UlJSEi5evIiSkhKjgZKes7MzgoODodFoEBsbi/j4eJSWltZSj4nsj1KphCAIcHLiRytRXcKRJQIAJCUlQalUwtvbG97e3iYfJ5FI4OfnB5VKhevXr0Mul6Nt27bw8/Orwd4S2SeZTMZAiagO4ru6ntMvy5CZmYkGDRqYFSiV5eHhgaCgIOTm5uLcuXO4ffs2BEGwZleJ7JpOp4NMJmN9JaI6iMFSPZaeno74+HgAKJfIXR36aTlBEHD58mVcvXoVarXaGl0lsntFRUVQq9UMlojqIKtNw2VnZ+PAgQOIjY1Ffn4+VCpVlcdIJBJ888031uoCmUir1eLGjRu4ceMGtFotAFht6kAikcDX1xdqtRrJycni3XL+/v5WOT+RvdJX7uYUNFHdY3GwVFhYiOnTp2PTpk3VSu5lsFS7VCoV4uPjkZaWBh8fnyqTuKvL3d0dwcHByMvLw/nz5xEeHo6mTZsyn4PqLKVSCQC8I5SoDrIoWCotLcXgwYNx4sSJauWn8EOldslkMly9ehV5eXkICAiAq6srZDJZjV3PyckJQUFBUCgUuHLlCuRyOVq3bg0PD48auyaRrRQUFMDV1dXW3SCiGmBRsPTFF1/g+PHjkEgk8PHxweuvv46HH34YTZs25by9HREEAenp6UhISIBKpUJwcHCtjvBIpVK4u7sjJSUFCoUCbdu2RUBAQK1dn6imlZaWQqFQsBglUR1lUbD0/fffAwD8/Pxw/PhxtG3b1iqdIuvRarW4fv06bty4ARcXFwQFBdlkRM/Nzc1gWq5ly5Zo3rw5p+WoTtDnK/n6+tq6K0RUAyz6TXX16lVIJBJMnjyZgZIdKi4uxqVLl3Dt2jV4eXnBz8/PplOf+mk5Z2dnxMXFITY2FsXFxVY5t2LlSjw+fz4UK1da5XxE5lAqldBoNHBxYek6orrIond2SUkJACAyMtIafSErys/PR3x8vEF+kr3w8fGBm5sbbt++jcLCQrRp0wZBQUHVPl/6okVQfPIJJAAUn3yCdKkUIR98YL0OExmh1WqRn5/PHEyiOsyikaWmTZsCAGvp2BFBEJCamooLFy5AJpMhODjY4kApIyMD8+fPx+effw65XG6Vfuqn5QoLC3HhwgUkJSWJZQzMkb5oEdLmzjXYlzZ3LtIXLbJKP4mM0Wq1SEhIwK1btzgFR1SHWRQsDRo0CABw5swZq3SGLKPRaJCYmIjLly9DEAQEBQVZnBOkVqsxbdo0/P7779i4cSOGDh2KH3/8ERqNxuL+Ojk5ITAwEK6uroiPj8elS5dQVFRk8vEVBUp6DJiopmm1WsTHxyM5ORl+fn68qYWoDrPoN+mbb74JDw8PbN68GRkZGdbqE1VDcXExYmNjkZSUBC8vL6v9lbty5UokJCSI2zKZDEuWLMGYMWOsFiR7e3sjICAAaWlpiImJQVZWVpXHGAuU9BgwUU3RB0o3b95koERUD1gULEVERODLL7+EUqnE4MGDkZSUZK1+kRny8/Nx/vx5pKWlwd/fH56enlY5799//40ff/wRwJ0ikw8++KD4XGJiIiZPnoyZM2ciNTXV4mu5urqiYcOGUKlUuHDhAq5du1bp6JUpgZIeAyayNgZKRPWPRQneW7ZsAQCMGDECO3fuRIcOHfDEE0/gvvvuM3kKaOzYsZZ0oV7T5yclJiaipKTEqvWTbt++jQ8//FDcnjFjBoYMGYLz589j+fLliIuLAwD8+++/+O+//zB69Gi8+OKLFgVqEokE/v7+KCoqQmJiIuRyOdq0aQMfHx+xjTmBkp6+PZO+yVJlA6UGDRqwrhJRPSERLFga3snJyeAOEEEQzLojRCKRWCX3xRbkcjn8/Pwgk8lsktip0WiQlJSE5ORkuLm5VbsPMpkMR44cwf333y+uaVVSUoKXX34ZV69eBQA88sgjWLRokfh/q9Pp8Ntvv+Hzzz9HXl6eeK6GDRvijTfewCOPPGLxnUEajQZ5eXnw9vZGmzZt0KhRI2R8+KHZgVJZTRYuZMBE1abVahEXF4eUlBQGSkR1RElJCYqKijBw4ECj7SwOliwhkUiqdQeUPbBlsFRUVIS4uDhkZGTAz8/PpOVDVCpVhXctFhYW4ty5c+jatas4grN27Vr89NNPAICwsDBs27YN3t7eFR77zTff4LvvvjMIejt37ozp06ejQ4cO1X2JAO4E3zKZDFqtFiF//IGS1astOh/AgImqR6PRIC4uDrdu3WKgRFSH1EqwtHnz5uoeKho3bpzF57AFfbB0NCQEPrVYhVqn00Gj0UCn05Ub2TOmtLTUpFG86NJSvKdSAQDcAHwtleKeKqbWbmo0WFVYiCP/q7ul96SHB1739kaQhYv1CoWFkJhxl1xVnKRSOPM271rh2rgx2jv43bIMlIjqrloJluozfbB0CIBPVY0dRBqAFwAo/rc9G8AIM44/BuBTAMll9nkDeAnAc7gTfFH94hoais63b9u6G9XGQImobjM1WGJtfgu5hoTAtRZGljQaDTRaLSSwfPqzIqWCgHfz86H43+jTQ+7uGO7rC5iRe9QHQE9BwA/FxVivVKJQEKAEsAbAz87OmOrjg/vd3MzPZ1Iq7zyshCNLtce1cWNbd6Ha9IFSSkoK/P39GSgR1WMcWaqm2spZUiqViI+PNys/qTpWrVqFbdu2AQBCQ0Oxfft2g7vQzJWfn48vvvgCP/30E8r+iPXu3RvTpk1Dq1atzDvhhg3Al19Wuz969T1nSRAEaLXaCh8eHh4V5qbVRwyUiOoHm07DZWZmIj09HQqFAlKpFE2aNEHDhg2teo3U1FT88MMP+PPPP8Vk54CAAERFRWHmzJno1atXuWPkcjnmz5+P3bt3IyMjAyEhIRg5ciTmzZtndmBQG8FSTk4O4uPjIZfLERAQUGOLdB45cgRTp04FALi4uODbb7+1ODlbLz4+HitWrEBMTIy4z9nZGc888wwmTpxo3vfOwoDJkQMlQRCg0+kqDXQqek6fp1ZaWip+rW+r0+nEc+ofnp6eCA8PR5MmTWpk9NJRMFAiqj9qPVhKSUnBZ599hj179iAlJaXc882aNcOIESPw5ptvIiwszOLrzZ49G0uXLkV4eDj69++P4OBgJCYm4ueff4YgCNixYwdGjRoltlcqlejbty/Onz+PQYMGoWvXrjh37hz279+PHj16IDo62qxRm5oMlgRBwK1bt8TCjAEBATW2SGdGRgZeeOEFyGQyAMD06dPx7LPPWvUagiDgn3/+wapVqwwqvfv5+eHVV1/F0KFD4WxqEng1A6aG8+ah0bvvmn2cMea+dSob1bk70NEHOHcHOmUDnLsDHQDiz4i+X/obAJycnMp9XdFzhYWFUKvVaNq0KcLDw61W3NSRaDQaXL16Fbdv32aOElE9UKvB0saNG/Hmm2+K63pVdEr9B7mXlxfWrFmD8ePHW3TNPXv2IDAwEP369TPYf+TIEQwcOBA+Pj5IT08Xq+vOmzcPCxcuxKxZs7BkyRKxvT7o+vjjjzFnzhyTr19TwVJpaSmuXbuGmzdvwsPDA1Kp1GrnvptGo8GkSZNw4cIFAED//v3xySef1FhgplKpsG3bNmzcuNGgjEFERATeeecddO/e3bQTmRkwqV98ESV2UPy0bIBTNui5O8jRBzFVBTdlv7bW/1lJSQny8/Ph5+eHiIgIBAcH19jPg73RaDS4cuUKbt++zRElonqi1oKljRs34uWXX4ZEIhE/+Nu1aydWXi4sLERCQgLi4uIMfhl88803FgdMlRk8eDD279+P06dPo3v37hAEAU2bNoVcLkdGRoZBXoZSqUTjxo3RsGFDs5ZrqYlgqbCwEPHx8cjMzESDBg1qfBmFzz//HBs3bgQAhISEYPv27bVSMyojIwNr1qzBvn37DPYPHDgQb731Fpo0aVL1SUwMmEpffhmaGvo5M1dFwY49BiI6nQ4FBQUA7owIt2rVCq6urrbtVA0rLS0VR5QCAgLq/OslojtqJVhKT09HREQEioqKIJFIMGnSJMyePRvNmjUr1/bWrVtYsmQJ1q9fD51OB29vbyQmJqJxDdwt88QTT+CPP/7AuXPnEBkZiYSEBLRt2xaDBw/G3r17y7V/5JFHsG/fPqSkpFQ6RahWqw1GQ+RyOcLCwqwWLBUXFyMmJgZyuRyBgYGmT0tV0/Hjx/HGG28AuJND9M0336Bjx441es273b10CgC4ublhzJgxGD9+fNXTQFUFTJMnAxMmWKm39U9xcTHkcjmCgoIQEREBf39/W3epRjBQIqq/TA2WLMriXLdunRgoff3111i3bl2FgRJwpxL0559/jg0bNgC4U4V63bp1lly+QikpKThw4ABCQkLQqVMnAHcWfQXuTPdURL9f364iixcvhp+fn/iwRt5VWSqVCoWFhbUSKGVnZ2NumWVD3njjjVoPlAAgMjISmzdvxvvvv4+AgAAAd35wv/nmGwwfPhx79+41nhc0YcKdgKgiDJQs5unpiaCgIOTn5+PcuXO4ceOGw1bcrwwDJSIyhUXB0r59+yCRSDBo0CC89NJLJh0zfvx4PPLIIxAEocJRHkuUlpZizJgxUKvVWLp0qRh06JOX9Wuf3U0/MqRvV5E5c+ZAJpOJj1u3blm173o1PS2j1Wrx3nvvIT8/HwDQt29fPP/881Uep1KpkJWVhaKiIrMTm41xdnbGkCFDsGfPHowZM0a84y8rKwvvv/8+Xn75ZVy5cqXyE1QUMDFQshpnZ2cEBQXB2dkZcXFxuHTpEgoLC23dLasoLS0Vc5QYKBGRMRYFS9evXwcADBkyxKzjnn76aYPjrUGn02H8+PGIjo7GxIkTMWbMGKudGwDc3d3h6+tr8HBEGzZsEG/jb9SoEebPn1/lbeJarRYymQwNGzaERqNBVlYW5HK5eBeWNfj4+OCtt97Czp070bdvX3H/xYsXMW7cOCxYsAA5OTkVHzxhAlTjx0MAoBo/noFSDfDx8YG/vz/S09MRExODtLQ0qwbNtU0fKKWmpjJQIqIqWRQsKRR3FsbQT6GYSt/eWn+h6nQ6vPTSS9ixYwdGjx6NL+/KY9GPKFU2ciSXyw3a1VWnTp0Sp0GdnZ3x0UcfoUGDBlUel5eXh+DgYHTu3Bm9evVCu3bt4OrqipycHOTl5aG0tNRqfWzevDlWrVqFzz77DM2bNwdw5y6x3377DcOHD8eWLVtQctcadACgHjMGf8yfD7WVg2T6f66urggODoZGo8GlS5dw9epVqP63jqAjYaBEROayKFgKDAwEANy4ccOs45KTkwGYH2RVRKfT4cUXX8TmzZvx3HPPYdOmTeVGSqrKSaoqp6kuyM3NxQcffCCOBkyePBmRkZFVHqdQKODu7o42bdrA1dUVXl5eaNWqFXr16oUuXbrAz88Pcrkc2dnZKC4utlp/o6KisHPnTkydOlUsGKpUKrF69WqMGjUK0dHRDj2y4agkEgn8/PwglUqRnJyMc+fOVT7iZ4dKS0tx+fJlBkpEZBaLgqWOHTtCEARs3brV5CkZrVaLrVu3QiKRWJxUrA+UtmzZglGjRmHr1q0VJkdHRESgSZMmOHr0KJR3rTGmVCpx9OhRtGzZ0upJ2/ZCq9Xigw8+QG5uLgDgvvvuw7hx46o8rqSkBCqVCuHh4eVG3VxdXdGkSRN0794d3bp1Q5MmTaBWq5GZmYnCwkKrTNG5uLjghRdewJ49ezB06FAxn+vWrVuYNm0a3nzzTbMDdbIOd3d3BAcHQ6FQ4Pz582IBVXtWUlKCy5cvIy0tjYESEZnFovUznnrqKRw4cABXrlzBa6+9hi+++MJogrIgCHj99dcRGxsLiUQi5i5Vh37qbcuWLRg5ciS2bdtW6V1kEokEEyZMwMKFC7Fo0SKDopSLFi1CYWEh3rVydWd7snHjRpw6dQoAEBQUhAULFlSZpyQIAvLz8xEaGoqmTZtW2s7JyQlBQUEICgqCQqFARkYG0tLSkJ2dDXd3d0ilUovv7gsICMB7772H4cOHY8WKFTh37hyAO+UPnn32WTzzzDMG1dqrQ6fTGVTL1n9tbF9Vbe7eFgTB4AHA4N+KnjOlvSnHV3Wsq6srHnvsMTz00EMmf8+cnJwQGBiIoqIiJCQkoKCgABEREXY5nV1SUoIrV64wUCKiarGozpJKpUKbNm2QmpoKAOjcuTOmT5+Ohx9+2GAtuOzsbOzfvx8rVqwQq0U3bdoUCQkJ1S68OH/+fCxYsEBMDK5o3bQhQ4aIU01KpRJRUVG4cOECBg0ahG7duiEmJkZc7uTw4cNmLe9g7aKU+fn5OHXqFAICAqy6LldMTAwmT54MnU4HJycnrFu3zqRK2fn5+fDw8EC3bt3g5eVl1jVVKhWys7Nx+/ZtyGQySCQS+Pr6WqUisiAIOHDgAFatWoXMzExxv6+vL8LCwsRaQKYGMGXXTCNg6NChmD59utnvS61Wi9zcXHh6eqJVq1Zo2rSp3awvVzZQCgwMrLE1FonI8dRaBe/Tp0/jwQcfFJc60ZNKpfD29oZSqRQTwYE7v+y8vb1x6NAh3HvvvdW+7vjx47F582ajbTZu3GhQJVwmk1W6kK65y4o4QrCUn5+P559/HtnZ2QCASZMmYeLEiVUeV1xcjOLiYnTu3BmNGjWq9vW1Wi1ycnKQmpqK3NxcaDQa+Pj4wNPT0+ISCSqVClu3bsWmTZsMioWS5dq3b4+lS5eaVkn9LgqFAiqVCiEhIYiIiDA70LY2BkpEZEytrg138eJFvPDCC7h8+bLhyf+3BEpZnTp1wrZt28SCkY7K3oMlnU6Ht99+G8eOHQMA9OjRA2vXrq1ySkwf4ISHh6NNmzZWqfskCAIKCgqQkZGBjIwMFBcXw9PTEz4+Pha/1oyMDKxevRr79++vtI2zszNcXFzg6upq8NDvc3NzK/e8sfbmtNHvc3FxgbOzs/j9LPtv2bXdym5Xt62xryt7/vDhw1iyZIkYePr5+WHRokXo06eP2f8n+vXlfH190bp1azRq1Mgmy7roc5TS09MZKBFRhWo1WALu/EL8448/sGfPHpw8eRLp6elQKBSQSqUICQlBr169MHz4cDz22GN2uR6Wuew9WNq0aRPWrl0L4E7Oz44dOxAUFFTlcdnZ2QgMDERkZGSN5HUUFRWJeU0KhQIuLi6QSqUWXyslJQWHDx9Gnz59xF+M+kClpiui1xUJCQmYOXMmbt++DeBOMDVx4kRMmDDB7J9JfYCs0+kQFhaG8PDwWl2YloESEZmi1oOl+saeg6ULFy7glVdegVarhUQiwdq1a9GrV68qj1MoFBAEAd26davxJN3S0lIxr0n/S1U/RVcdMpkMR44cwf3332+XCcaOQqFQYN68eYiOjhb39enTBwsXLjSpJtfdVCoVZDIZAgMDERERYZVyIVVRq9W4cuUKAyUiqlKtrA1H9qegoADvvvuumLD80ksvmRQoGSsTUBNqo/QAmU8qlWL58uWYMmWKGLQfO3YMY8aMMb7sTCU8PDwQHByMgoICnDt3DtevX6/RZHq1Ws0RJSKyOgZLdYggCFiwYIF4l1i3bt1MSujWlwkICQkxWiagJuhLD3Tu3Bk9e/YUC4NmZ2ejoKCAd6nZgJOTE8aPH4/PP/9cvLswPT0dL7/8Mvbs2WN2MVD9/7Grqyvi4+Nx4cIFg5s+rEUfKGVkZDBQIiKrMitYun79OoYNG4Zhw4bhgw8+MPti77//vnh8SkqK2ceTcTt27MCRI0cAAA0aNMCHH35o0i+MgoIC+Pr6IiIiwqa3e0ulUkRERKB3797o1KkTvLy8kJeXh5ycnAqXOKGa1aNHD2zfvh2dO3cGcGfq9OOPP8aCBQuqtcyJt7c3AgICkJmZiZiYGNy+fdtqI4gMlIioJpn1m/G9997Dzz//jL///tuklerv9sILL+Dvv//GL7/8grlz55p9PFUuNjYWa9asEbcXLlxoUOuqMsXFxRAEwS5u89Zzd3dHWFgYevbsia5du6Jhw4YoLCxEVlYWioqKuMxJLWrYsCHWr1+PZ599Vtz3+++/46WXXsKtW7fMPp+LiwuCg4Oh0+kQGxuLK1euWLxMDgMlIqppJgdL6enp+OGHHyCRSPDGG2+gffv2Zl+sffv2eOuttyAIAnbs2IGsrCyzz0HlKRQKvPvuu+JyE+PGjTPplm+tVgu5XI5mzZqZFFjVNmdnZzRq1AiRkZHo0aMHWrRoAY1Gg6ysLMjlcuY11RJXV1dMnz4dH330kZiAn5CQgDFjxuDw4cNmn09fpNTPzw8pKSmIiYmp9meBWq1GbGwsMjIyEBQUxECJiGqEyZ8sO3fuhE6ng7u7O6ZPn17tC77zzjv49NNPoVarsXPnTrzxxhvVPhfdyTdauHAh0tLSANypov7qq6+adGxeXh6Cg4PRqlUruy7nIJFI0KBBAzRo0ADNmzdHZmYmUlNTkZOTI5YesJayS4HodLoKvzalTdm+V7Z999cSiQROTk7laiKVfeinSatqVxMGDx6M1q1bY+bMmbh58yYKCwvxzjvv4MUXX8SkSZPMDlTc3NzE5O8LFy6gWbNmaNWqlcllJFQqFS5fvozMzEwEBQWxRAQR1RiTP93+++8/AMADDzxg0e2//v7+6N+/P/bt24fo6GgGSxbatWsXDh48CODOkh8ff/yxSb+0FAoF3N3d0aZNG4daJ8vLywstW7ZE06ZNDUoP6BOGi4qK4OTkVGmQo9PpxCClbFBxd9BSUfCi/9rJyQnOzs4VPvQFKJ2cnMo99NfR6XTlHlqt1uhDf5x+9LCi4E2/z9jrq+g16l+Tm5tblaUbwsPDsWXLFixcuBD//PMPgDuV8mNjY/HRRx+Z/dng5OSEgIAAFBcXIykpCTKZDG3atKmyTAEDJSKqTSYHS+fPn4dEIkH//v0tvuj999+PvXv3iuvEUfXExcVh1apV4vb8+fPRuHHjKo/Tlwno0KGDw9Yk0pceaNy4MfLy8sTb2p2cnODq6lougCn7b0WBTGX7K3vU9khcZUFWZfuNPV9RMKbRaCCXy6FSqdCgQQOjr8/b2xtLlizBjh07sHr1ami1Wpw+fRqjR4/GkiVLxIRwc3h6esLNzQ15eXmIiYlBy5Yt0axZswqDIAZKRFTbTA6WcnJyAKBa60XdTX8O/ZplZL7CwkLMnj0bpaWlAIDnn38eDzzwQJXH6csEhIaG1nqZgJqgvy09IiICBw8eRGRkpFV+Ru2NRCIRg7+akpWVhYSEBGRnZyMgIMDoCKVEIsELL7yADh06YM6cOcjJyUFWVhYmTpyIqVOnYtSoUWYHlM7OzggODkZhYSHi4uIgk8kQEREBb29vsQ0DJSKyBZMTvPV3rJT94Kou/TnuXnyXTCMIAj766CNxWYp77rnH5OlMeykTUFPsOffK3jVs2BBdu3ZFo0aNkJuba9Jdal27dsW2bdvQrVs3AHduGli+fDnef//9ar+/fXx84O/vj/T0dJw9exZpaWkQBAEqlQqxsbEMlIio1pn821JfnE4/wmSJ3NxcAKjW8gkE7NmzB3///TeAO79YPv74Y5PyjuyxTADZF29vb3Tu3Bnh4eEoKiqCTCarslRDUFAQ1q1bhzFjxoj79u3bh/HjxyM5Obla/XB1dUVwcDBKS0tx6dIlXL16FbGxscjKymKgRES1zuRgKTg4GABw9epViy+qzy+xx9vV7V1iYiJWrFghbs+dOxehoaFVHmfvZQLIfri4uKBNmzbo1KkTnJ2dkZOTU2UldRcXF7z11ltYtmyZOHJ8/fp1jB07FgcOHKhWP/R3QUqlUiQnJzNQIiKbMTlY6tGjBwRBwN69ey2+6N69eyGRSNC9e3eLz1WfFBUVYfbs2WI162eeeQYPPvigScfm5eUhKCjI7ssEkH2QSCQICQlB165dERAQgJycHKjV6iqPe/DBB7FlyxaEh4cD+P+f2ZUrV4p38pnL3d0dDRs2RMOGDRkoEZFNmBws6VfkvXbtGn766adqX3DPnj1ITEw0OCdVTRAELF68GDdv3gQAtGvXDm+//bZJx+rLBLRt29ahygSQ7fn6+iIyMhItWrSAXC6HXC6v8pjmzZtj06ZNePTRR8V927dvx6uvvlrtafyarB9FRFQVk4OloUOHIigoCADw+uuvV2upg5SUFEyZMgUAEBgYiGHDhpl9jvrqt99+w19//QXgTl7J4sWL4ebmVuVx+jIB4eHhDlsmgGzLzc0N7du3xz333APgTt5iVdXTPT09sXDhQsyaNUu8q+7cuXN44YUXEBMTU+N9rk2lpaU4d+4cYmNjbd0VIqohJgdLXl5emDlzJgRBQGZmJh544AEcP37c5AsdP34c/fr1Q0ZGBiQSCWbMmMEkYxMlJSVh6dKl4vZ7772HsLCwKo/TlwkICQmpE2UCyHYkEgnCwsIQGRkJPz8/ZGdnV7m4sUQiwciRI/H111+jUaNGAO7c3PHqq69i69atDrvGn1arxdWrV7Flyxa88cYbGDBgACZOnIjNmzfbumtEVEPMWp9g2rRpOHDgAPbv34+UlBTcf//9ePTRRzF27FhERUWVq2+TlpaGo0ePYvPmzdi7d69YVfihhx6yaMmU+qS4uBhz5swR80WGDRuGQYMGmXRsXS8TQLXP398fkZGRSEhIQGpqKry8vODj42P0mE6dOmHbtm147733cOrUKWi1Wnz22We4dOkS5s6dW+XxtiYIAm7evIlTp07h9OnTOHv2bIXTkWfOnIFWq2VeFVEdZFaw5OTkhJ07d+LJJ58Ulz/5888/8eeffwK4k4ipLwdQUFBgkBCq/ysyKioKO3fuZP6BiZYtW4br168DACIiIjBt2jSTjqurZQIUCgUKCwvL7dfnwlSWE+Pj42PVNeTqMw8PD3Ts2BFSqRTXr19Hbm4uAgICjL6n/f39sWbNGqxfvx7ffvstAODff//FtWvXsGzZMrRu3bq2um+SjIwMnD59GqdOncKZM2eMFtANDg5Gjx490KNHD+h0OgZLRHWQRKjGWLhWq8WcOXOwZs0ak+6QAe4EUlOmTMHixYvrxMrgcrkcfn5+kMlk8PX1tfh8+fn5OHXqFAICAsRRoD/++APz5s0DcCcHZOvWrWjRokWV59JqtcjJyUF4eDjatGlTpwLTQ4cOVWul+379+lllqR4ylJOTg/j4eMhkMgQGBpr03j5y5Ajmzp0rrufn4eGB999/H4888khNd7dS+fn5OHPmDE6fPo3Tp08bzcn09fXFvffei549e6JHjx5o3rx5nXqPEdUnJSUlKCoqqvKGs2oFS3rp6en4/PPPsW/fPpw7d65c0qeTkxO6du2KwYMH47XXXqtTy1DUdLCUnJyMMWPGiFWUFy5ciMcee8ykc+mXq+jatWudu/utspGlqnBkqeYUFRUhISEB6enp8PHxMWkk8/bt25g5cyYSEhLEfc888wymTp1aKz+zSqUS586dE0eOyvbjbh4eHujWrRu6d++Onj17IiIigqNHRHVErQRLZRUVFSEjIwO5ubkQBAGBgYFo3LixVZZHsUc1GSyVlJRg/PjxuHbtGgDgySefFEeYqqJQKCAIArp168a736jWaLVa3LhxAzdu3BCLSVY12qJSqbB06VL89ttv4r6OHTtiyZIlJi0IbQ61Wo1Lly6JI0eXL1+utNCmi4sLOnXqJE6tdezYsc790UFEd9R6sFTf1GSwtGTJEuzZswcA0KpVK2zevBmenp5VnqOkpAQymQwdOnRAs2bNLO4TkbkyMzMRHx8PpVKJwMBAk0Zgfv75Zyxbtky8u65Bgwb4+OOP0bNnz2r3Q6PRIC4uTgyOLly4UGnKgEQiQbt27cSRo8jISJPeb0Tk+EwNlhw/eaiO+fvvv8VAyd3dHYsXLzbpg1tfJiA0NJRlAshmGjVqBG9vb8THxyMzMxN+fn7w8PAwesyQIUPQtm1bzJo1C2lpaSgoKMCUKVMwefJkjB8/3qQ7OQVBQFJSEs6cOYNTp04hJibG6HRtixYt0KNHD/Ts2ZOjsERUJQZLdiQtLQ0ff/yxuD1z5kxx2YiqsEwA2QsfHx907twZSUlJuHnzJtRqNXx9fY1Oy7Vv3x5bt27F3LlzcfToUeh0Oqxbtw6XLl3CggULKhy9TU1NFUeOzpw5Iy7QXZFGjRqJCdk9evQQ17okIjIFp+GqydrTcBkZGejbty+SkpIAAI8++igWLlxo0l02xcXFKC4uRufOncXif0S2JggC0tLSkJiYCJVKhYCAgCqn5XQ6Hb799lusX79eLDcSGhqKZcuWISgoyCA4Sk1NrfQ8DRo0QI8ePcSptaZNm/KONSIqhzlLNczawdIrr7yCr7/+GgDQrFkzbNu2zaS7iupymQCqG2QyGeLi4pCbmwt/f3+Tluk5ceIE3nvvPchkMgCAs7NzpQnZwJ0VBrp16yZOrYWHh3OElYiqxGCphlkzWNq9ezdGjBgB4M46XJs2bUKbNm1MOrYulwmgukOtViMxMRG3b9+Gh4eHSWUc0tPTMWvWLFy5cqXcc66urujSpYs4ctShQ4c6Ub+NiGoXE7wdhE6nw4IFC8TtadOmmRwoKRQKuLu7o23btgyUyK65u7ujQ4cO8PX1xbVr15CTk2NQgLUiISEh2LBhAz777DP89ttvaNmyJXr27Inu3bujS5cuVSaOExFZC0eWqsmaI0u5ubkYPXo0iouLsWzZMpNut2aZAHJUeXl5iI+PR35+PgICAhjoE5HNcGTJgQQGBmL79u04evSoSTlHLBNAjiwgIEBcjDctLQ3e3t51tngtEdUNzIC0ExKJxKTEV4BlAsjxeXp6omPHjmjTpg1KSkqQl5cHDnITkb3ib1oHU1xcDEEQEBERYdLdckT2ytnZGeHh4ejcuTM8PT2RnZ0NjUZj624REZXDYMmBaLVayOVyNGvWDA0bNrR1d4isomHDhujatSsaNWqE3NxccfFoIiJ7wWDJgeTl5SEoKAitWrViPSWqU7y9vdG5c2e0bt0aRUVFKCgo4LQcEdkNBksOgmUCqK5zcXFBREQEOnXqBBcXF+Tk5BgtRElEVFsYLDmAkpISqFQqhIeHc8FPqtMkEglCQkLQtWtXBAYGIicnB2q12tbdIqJ6jsGSndOXCQgJCWGZAKo3fH190aVLF7Rs2RJyuRxyudzWXSKieox1luwcywRQfeXm5oZ27dpBKpUiMTERWVlZBs87OTlBIpGU+7eifXf/S0RkDgZLdoxlAqi+k0gkaNq0KaRSKRQKBbRaLXQ6HbRaLTQaTYUPQRCg0+mM/qs/d9kkclMDrYqCMwZgRHUbgyU7pS8TEB4ezjIBVO/5+fmZnK+n0+nEgMqUf/VfVxWAGQvE9Hx8fODp6cngiaiOYbBkp1gmgKh6nJyc4OTkBBcX63y86QOiqgKv3NxcZGRkQKFQwMvLC97e3pw6J6ojGCzZIZYJILIfEokEzs7OcHZ2Nvp+bNSoEZo1a4bMzEykpqYiJycHbm5ukEqlJi2OTUT2i8GSnSktLYVKpUKHDh1YJoDIwfj4+MDHxwdNmzZFVlYWbt++jby8PDg5OUEqlZq8/iMR2RcGS3YmPz8fTZs2ZZkAIgfm7u6OsLAwNGnSBNnZ2UhNTUVeXh60Wq2Y10REjoPBkh2RSCTw8/NjmQCiOsLZ2RmNGzdGo0aNkJ+fj7S0NGRlZRnkNTEnkcj+MViyIz4+PggPD2eZAKI6RiKRICAgAAEBAVAoFMjIyEBaWhqys7Ph7u4OHx8f5jUR2TEGS3bC19cXbdu2RUBAgK27QkQ1SCqVQiqVIiwsrFxek6+vL2/qILJDDJbshLOzMwIDA23dDSKqJR4eHmjWrFm5vCadTgepVAoPDw9bd5GI/ofBEhGRDbm4uCAkJETMa0pNTUV2djZkMhm8vb2Z10RkBxgsERHZAScnJwQGBiIwMBByuRwZGRlIT09HVlYWPDw8mNdEZEMMloiI7Iyvry98fX0N8ppyc3Ph4uICqVTKvCaiWsZgiYjITnl6eqJ58+ZiXtPt27dRUFDAvCaiWlbvivmcPn0ajz32GBo0aABvb2/07t0bu3btsnW3iIgq5erqiiZNmqB79+7o1q0bQkJCoFKpkJmZCaVSCUEQbN1FojqtXo0sHTx4EIMHD4aHhweeffZZSKVS7N69G6NGjcKtW7fwzjvv2LqLRESVcnJyQlBQUIV5TZ6envDx8WFBW6IaIBHqyZ8kGo0G7dq1w+3bt3HixAlERkYCAGQyGXr27Ink5GQkJCSgefPmJp1PLpfDz88PMpkMvr6+NdhzIqLKFRUViYv3KhQKuLq6QiqVwsWlXv0tTFQtJSUlKCoqwsCBA422qzd/gvz7779ISkrC888/LwZKAODn54d3330XJSUl2Lx5s+06SERUDV5eXmjZsiV69eqFzp07QyqVoqCgADk5OVCr1bbuHlGdUG/+9Dh06BAAYNCgQeWeGzx4MADg8OHDlR6vVqsNPnjkcrl1O0hEZAFXV1eEhoYiJCQEubm5SE1NRU5OjlivicngROVptVqT2tWbYCkxMREAEBERUe65xo0bw8fHR2xTkcWLF2PBggU11j8iImtwcnJCcHAwgoKCIJPJkJ6ejszMTBQUFNi6a0R2yZT1WOtNztKgQYPw999/IzExEa1bty73fGhoKAoLCyGTySo8vqKRpbCwMOYsEZHdKy4uRklJia27QWSXnJycIJVKjbapNyNLlnJ3d4e7u7utu0FEZDZPT094enrauhtEDqveJHj7+fkBQKUjR/q724iIiIjKqjfBkj5XqaK8pIyMDBQWFlaYz0RERET1W70Jlvr16wcA2L9/f7nn9u3bZ9CGiIiISK/eJHhrNBq0bdsWqamplRaljI+PR4sWLUw6H4tSEhER1Q/1JsHbxcUFGzZswODBg/HAAw8YLHdy8+ZNLF++3ORAiYiIiOqPejOypHfq1CnMmzcPx44dQ2lpKTp16oRp06Zh1KhRZp2HI0tERET1Q70LlqyFwRIREVH9UG8SvImIiIiqg8ESERERkREMloiIiIiMqDd3w1mbPtVLLpfbuCdERERkCalUColEUunzDJaqKTc3FwAQFhZm454QERGRJaq6WYvBUjUFBAQAAFJSUrimHNFd5HI5wsLCcOvWLd4tSlQG3xv2SSqVGn2ewVI1OTndSffy8/PjDzxRJXx9ffn+IKoA3xuOhQneREREREYwWCIiIiIygsFSNbm7u2PevHlwd3e3dVeI7A7fH0QV43vDMXG5EyIiIiIjOLJEREREZASDJSIiIiIjGCwRERERGcFgiYiIiMgIBktmOn36NB577DE0aNAA3t7e6N27N3bt2mXrbhFZ1bZt2zBp0iR0794d7u7ukEgk2LRpU6Xt5XI5pk2bhubNm8Pd3R0tWrTAjBkzUFhYWGF7nU6HNWvWoFOnTvD09ERwcDCee+45XL9+vYZeEZF1pKamYtWqVRg0aBCaNWsGNzc3NG7cGMOHD8fJkycrPIbvjzpAIJP9+++/gqurqyCVSoWJEycK06ZNE5o3by4AEJYvX27r7hFZjf7nOigoSPx648aNFbYtLCwUIiMjBQDCoEGDhFmzZgmDBg0SAAg9evQQiouLyx0zYcIEAYBwzz33CDNnzhRGjx4tuLm5CQEBAUJCQkINvzqi6ps1a5YAQAgPDxdefvllYfbs2cLw4cMFZ2dnwcnJSfj+++8N2vP9UTcwWDJRaWmpEB4eLri7uwvnzp0T9xcUFAht2rQR3NzchOTkZNt1kMiK/v77b/HnefHixUaDpblz5woAhFmzZhns1/9S+fjjjw32//vvvwIA4YEHHhDUarW4/88//xR/oRDZq927dwuHDh0qtz86OlpwdXUV/P39BZVKJe7n+6NuYLBkon379gkAhBdffLHcc5s2bRIACAsWLLBBz4hqlrFgSafTCU2aNBF8fHyEwsJCg+cKCwsFHx8foVWrVgb7n3vuOQGAcPjw4XLn69+/vwBAuHnzplVfA1Ft0I8YnT59WhAEvj/qEuYsmejQoUMAgEGDBpV7bvDgwQCAw4cP12aXiGwuMTERaWlpiIqKgre3t8Fz3t7eiIqKwvXr13Hr1i1x/6FDh8Tn7sb3EjkyV1dXAICLy5016vn+qDsYLJkoMTERABAREVHuucaNG8PHx0dsQ1RfGHtflN2vb6dUKpGeno6WLVvC2dm5yvZEjiIlJQUHDhxASEgIOnXqBIDvj7qEwZKJZDIZAMDPz6/C5319fcU2RPWFKe+Lsu3MbU/kCEpLSzFmzBio1WosXbpUDHT4/qg7GCwRERFVk06nw/jx4xEdHY2JEydizJgxtu4S1QAGSybSR/qVRfRyubzSvwaI6ipT3hdl25nbnsie6XQ6vPTSS9ixYwdGjx6NL7/80uB5vj/qDgZLJjI2V5yRkYHCwsJK56WJ6qqqcijuztnw9vZGSEgIbty4Aa1WW2V7Inul0+nw4osvYvPmzXjuueewadMmODkZ/krl+6PuYLBkon79+gEA9u/fX+65ffv2GbQhqi8iIiLQpEkTHD16FEql0uA5pVKJo0ePomXLlggLCxP39+vXT3zubvr30gMPPFCzHSeygD5Q2rJlC0aNGoWtW7dWmpDN90fdwGDJRAMHDkSrVq2wY8cOnD9/Xtwvk8nw8ccfw83NDWPHjrVdB4lsQCKRYMKECSgsLMSiRYsMnlu0aBEKCwsxceJEg/2vvPIKAOCDDz5ASUmJuP+vv/7CoUOHMGjQIDRv3rzmO09UDfqpty1btmDkyJHYtm1bhYESwPdHXSIRBEGwdSccxcGDBzF48GB4eHjg2WefhVQqxe7du3Hz5k0sX74c77zzjq27SGQVGzZswH///QcAuHTpEmJiYhAVFYXWrVsDAPr27YsJEyYAuPMXclRUFC5cuIBBgwahW7duiImJwf79+9GjRw8cPnwYnp6eBuefOHEiNmzYgHvuuQePP/440tPTsXPnTvj4+OD48eNo06ZN7b5gIhPNnz8fCxYsgI+PD9566y2xplJZQ4YMQWRkJAC+P+oMW1fFdDQnT54UHnnkEcHX11fw9PQUevbsWW4tICJHN27cOAFApY9x48YZtC8oKBDefvttISwsTHB1dRWaNWsmvPPOO4JcLq/w/FqtVvjss8+Ee+65R3B3dxcCAwOFUaNGCdeuXauFV0dUfVW9N1BBtXu+PxwfR5aIiIiIjGDOEhEREZERDJaIiIiIjGCwRERERGQEgyUiIiIiIxgsERERERnBYImIiIjICAZLREREREYwWCIiIiIygsESERERkREMloiIiIiMYLBEREREZASDJaI6Kjk5GRKJBBKJBOPHj7d1d6iGHTlyBBKJBM7Ozrhw4YKtu1Mj/vzzT0gkEri7uyMhIcHW3aF6xMXWHSCq7yQSSYX7XV1d4evrC19fX4SGhqJr166499578eSTTyIgIKCWe1leQUEBVq1aBQCIjIzEkCFDbNqf+kyr1eL1118HAIwZMwZdunSxcY9qxmOPPYb+/fvj0KFDePPNN7F3715bd4nqCYkgCIKtO0FUn1UWLFXG3d0dw4YNw4cffohWrVpV2i45ORktW7YEAIwbNw6bNm2ypJu1fn4y3bfffouXX34ZTk5OiIuLQ0REhK27VGP+/fdfDBw4EABw4MAB8WuimsRgicjGygZLP/30k/i1IAhQKBQoKChAbGwsjh07hsuXL4vPe3t7Y/Xq1XjppZdqtb96DJbsQ2lpKVq3bo2UlBSMGDECP/zwg627VON69OiBM2fOoHfv3jh+/Litu0P1AKfhiOxIVVNZJ06cwOzZs3H48GEolUpMmDABXl5eePbZZ2ung2R3du7ciZSUFADAq6++auPe1I7JkydjwoQJOHHiBI4ePYqoqChbd4nqOCZ4EzmQ3r17459//sErr7wC4M7o04svvohbt27ZuGdkK59//jkAICwsDAMGDKi0nVqthqurKyQSCfr371/leXv37g2JRAKpVAp7m4B45pln4OHhAQBYu3atjXtD9QGDJSIH4+zsjLVr16JHjx4AAJVKhY8//rhcO1PuhtPpdNixYweGDBmC5s2bw9PTEx4eHggNDUWXLl0wcuRIrFu3Drm5ueXOq5+CA4DNmzeL1yr7OHTokMH1VCoVfvnlF7z55pvo06cPgoOD4erqCqlUioiICIwZMwZ///13ld+DQ4cOideYP38+ACAtLQ3vvvsu7rnnHvj4+MDX1xddu3bFwoULoVAoqjwncCeg2LBhA4YNG4YWLVrA29sb7u7uCAsLw2OPPYbly5cjLS3N6DlUKhXWr1+PJ554AmFhYfDw8ICfnx86duyIN99806p3ccXHx+PEiRMAgGHDhhnNf7ty5Qo0Gg2AOwn5xuh0Oly6dAkA0Llz53Lnrej7f+3aNbz11lto27YtvL290bhxYwwaNAj79+8vd/5jx47h+eefR3h4ODw8PNCoUSOMHDnS5Lv4pFIpBg0aBAD4+eefIZPJTDqOqNoEIrIpAOLDHL/++qt4nLe3t1BSUmLw/I0bN8Tnx40bV+74nJwcoXfv3gbXr+zxySefVHjeqh4HDx40uGbLli1NOu7pp58WFApFpa/94MGDYtt58+YJ+/btEwICAio9X5s2bYTbt28b/X7++++/QmhoaJV9i4yMrPQchw4dqvIczs7Owscff2y0L6b6+OOPxfPu2bPHaNtNmzaJbTdu3Gi0bVxcnNh28uTJ5Z6/+/u/Z88ewcfHp9LX/OGHHwqCIAg6nU6YO3dupe1cXV2FX3/91aTX/umnn4rHfffddyYdQ1RdzFkiclBPPPEEGjRogIKCAiiVSpw+fRp9+vQx+fiJEyeKoxJhYWF49tlnERERAX9/fyiVSiQmJuL48eM4cuSIwXENGzbETz/9hKysLEyaNAkAMGDAALz55pvlrtGxY0eD7aKiIjRo0AAPPvggunbtiubNm8PLywtyuRwXL17Ezp07kZ6ejl9++QUvvfQSdu3aVeXrOH/+PJYvX47S0lKMHz8effv2hVQqRXx8PNatW4eMjAwkJCTgxRdfrHCUA7gzOjFy5Ehx5KVNmzYYOXIk2rZtC3d3d6Snp+PUqVP4448/Kp2S+uuvv/D000+jtLQUTk5OeOSRR/DQQw8hNDQUKpUKZ86cwZYtWyCTyfDuu+8CAObMmVPl6zNm37594te9e/c22vbixYvi11WNLJUd4amqDEFMTAyWLl0KZ2dnTJkyBT179oSzszMOHTqEjRs3QqPR4P3330dUVBRiYmKwcOFCNG/eHOPHj0e7du2gVCqxa9cu7N+/X/w/jI+PR1BQkNHrln29e/fuZd4e1SxbR2tE9R2qObIkCIIwePBg8dhVq1YZPGdsZCkzM1NwcnISAAh9+vQRiouLK71GVlaWcOXKlXL7qxq5qsiff/5ZbgSsLKVSKQwZMkQ875EjRypsV3ZkA4DQpEkTITY2tly79PR0oWnTpmK7s2fPlmuTnJwsSKVSsc2CBQsEjUZT4XWLi4uF33//vdz+tLQ0cWSrYcOGwvHjxys8/vbt20LHjh3FEaarV69W+r2oikajEby9vQUAQlhYWJXtH3roIXH0Rq1WG2377rvvit+PY8eOlXv+7u9/ixYthOvXr5drt3nzZrFNx44dBXd3d+Hxxx8XioqKyrUdO3as2HbZsmVVvh6VSiW4ubkJAIS2bdtW2Z7IEsxZInJgzZs3F7/Ozs42+bjr169Dp9MBAF544QUxWbYiwcHBaN++ffU7Wcajjz4KV1fXSp/38vLC5s2b4e3tDeBOLpQptm3bhnvuuafc/saNG+O9994Tt//6669ybZYsWSLmNL322muYO3cunJ2dK7yOh4cHHn/88XL7P/nkE+Tl5QEAfvzxx0pHeUJDQ/HDDz/A2dkZWq0Wn332WdUvrhI3btyAUqkEALRr167K9vqRpfbt28PNzc1o2/PnzwO4U9aiU6dOVZ57+/btBjlsemPHjhVrPsXGxsLPzw87duyAp6dnubYffvihmBtlSrFJd3d3sc5YQkICVCpVlccQVReDJSIH5u/vL35dNgm7KvpgBADOnj1r1T5ZytfXV/wFrZ8mNCYyMtLoXWAPP/yw+HVsbKzBc1qtFjt27ABw55evPlnZHIIgYMuWLQCA++67D/fff7/R9u3atUPPnj0BGE6jmSs5OVn8uqqK7pmZmcjKygJQ9RQc8P/TcK1atYKPj4/Rtt26dTM6/Vv2tv6xY8fC19e3wnZhYWFi8H/lypUq+wj8/+sWBEEsn0BUE5izROTAhDL5M+ZUAu/QoQNCQ0ORmpqKb7/9FlqtFhMnTkTv3r0rHVWxlvz8fGzfvh179+5FbGwscnNzoVQqK8wFun37dpXnu++++4w+37RpU4Nrl3Xx4kXI5XIAEO/OM9eVK1fEQNXf3x8///xzlcfov8c3btyASqUyOrJXGf1IFgAEBgYabVs2X6mqHKTc3Fykpqaa1BaoOleqcePG4tf6INFY2+Tk5HL/T5Up+7rLfj+IrI3BEpEDK/tLpapfmGU5Ozvjq6++wrBhw6BWq7F582Zs3rwZvr6+6NWrF6KiovDQQw+hT58+Zi/HYswvv/yCl19+2eRRMH0gY0xVicDu7u7i13dP1ZQNxjp06GBSn+5WdoTnzz//xJ9//mnW8Xl5eWjSpInZ11Wr1eLXUqnUaFtzkrv1U3DAnbIBVanq567s99/UtmVfmzFlR6mKi4tNOoaoOhgsETmwsr+ozR0Veeyxx3DmzBksWLAAv/76K0pKSiCXy/H333/j77//xvz589GyZUssXLgQo0ePtrivx48fx4gRI8Q7zjp37oyHHnoIrVu3hr+/P9zd3cXA7P3338fly5fFvCpjnJyqn01QNhirarqpMgUFBdW+PgCUlJRU67iyQUhVQWVN3QkHmPf9t+T/qiJl6ytVlAdFZC0MlogclE6nw8mTJ8XtXr16mX2Ojh074ocffoBSqcTRo0dx4sQJHDlyBEeOHIFarcaNGzcwZswYJCUlYd68eRb1d+7cuWKg9Pnnn+O1116rtO1HH31k0bVMVXZkorCwsFrnKBtkTZs2DStWrLC4X6YwZwpKHyw1bdq0yvymsjlspows2VLZEcqqXheRJZjgTeSgfvvtN3FEwcfHB/fee2+1z+Xt7Y1BgwZh7ty5+Pvvv5GdnY1FixaJz3/00UfIyMio9vlLS0vFat733nuv0UAJMBwxq0ll85lMTSo2do7aXHam7N1nxoIljUaDq1evAkCVdzXqdDrx/0kqlVZ4h5s90b9uiURicGcokbUxWCJyQKWlpfjwww/F7fHjx8PFxXoDxVKpFO+//z6efvpp8Xp335lWdkqlouTssnJycsRRpdatWxtte/r0aeTk5FSn22br3Lkz/Pz8ANxZgsOc8gt6kZGR4jkOHjxocr6NpVq0aCHmKumDoYokJCSIfSp7F2RF9u7dKy7nUtEyJ/ZEpVLhxo0bACAWDyWqKQyWiByMVqvFlClTcObMGQB3cjVmz55dI9cqO7KgD3b0yk4/6ev9VKbsL+lr164ZbWvpdJ85nJ2d8cILLwC4k1RcndIBZc+Rk5ODTz/91JpdrJSTk5O4PuDt27crXbOubL6SsaCqqKgIM2fOFLftfQouJiZGzPeq6o48IksxWCJyIKdOncLAgQPx1VdfAbgz/bB582aEhoaadZ59+/Zh5cqVRm/RzsrKwu7du8Xtu5N9AwICxBGV8+fPGx1d8vX1RZs2bQDcyYn58ccfy7XRarWYOnVqhYUja9KsWbPE3KV169Zh4cKF0Gq1FbZVq9UV9u/dd99FgwYNANxJTl+1apXR5HSlUokNGzbgu+++s6jvjzzyiPh12fy1ssoGS/Hx8Vi7dm25NmlpaXjiiSdw+fJlcV+zZs0s6ltNKzvSOXjwYBv2hOoDJngT2ZG7a/QoFAoUFBTg8uXLOHr0qEFRRR8fH6xduxYjR440+zrp6emYNm0aZs2ahf79+6N3795iAcLc3FxcvHgR3333nRhMPfPMM2Il5rIGDhyIPXv2ICkpCc888wyGDRuGBg0aiNM3PXv2FBNv3377bTFX6ZlnnsGoUaPQr18/+Pv749q1a9i+fTuuXr2Kjh07wt3dvdaKZTZr1gybN28W14abN28etm/fjpEjR6Jdu3Zwc3NDZmYmzpw5g99//x1hYWF49NFHDc4RGhqKXbt24cknn4RarcbUqVOxbt06DB06FB06dICPjw8UCgVu3LiBM2fO4N9//4VKpTLIC6uOoUOHiqNB//77L4YOHVqujT5Ycnd3h5OTE9544w1s374dPXr0gKenJ+Li4rB//36oVCqx9hYAfPPNN0hKSsILL7yA/v37W9TPmhAdHQ3gTlX1u/8/iKzOlmutEJHh2nCmPDw8PITnnnuuwrW4yjK2dlvZFeireowYMUJQKpUVXuPChQuCl5dXpccePHhQbKvT6YSXXnrJ6LU6deokXL9+XejXr5/R9fLuXvXe1O9xv379Km2zf/9+oXHjxlV+P7p27VrpOU6fPi20bdvWpO+rs7Oz8PXXX1fZ96r06dNHACAEBwdXuO5eWFiY2O8FCxZU2p9XXnlF+Oabb8rtv337drlzmvP9nzdvXoU/DxWp6v9dT6FQCB4eHgIAYdSoUUbbElkDR5aI7JSLiwukUil8fX3RtGlTdO3aFd27d8dTTz1lsMxJdYwdOxYdOnTAgQMHcPLkSVy9ehVpaWkoLi6Gl5cXmjVrht69e2PMmDHo169fpefp3Lkzzp07h08//RTR0dFISUlBUVFRhVNyEokE33zzDR5//HF89dVXOHPmDORyOQIDA9G2bVuMHDkSL7/8crWqWVvDww8/jOvXr2Pjxo347bffcPHiReTk5EAikaBRo0bo1KkTHn74YTz//POVnqN79+64cuUK9uzZg19++QUnT55EZmYmlEolfHx8EBYWhk6dOqF///546qmnDKpbV9frr78uJqf/9ddfeOqpp8TnCgoKxDv07rnnHsydOxdhYWFYs2YN4uLi4OXlhcjISEyePBkjRoyASqXC77//jn379iEsLAzPP/+82VO8tWHXrl1igdEpU6bYuDdUH0iEij7ViIjIIWg0GrRu3Ro3b97E0KFDsWfPHvG56OhoMdhdsmQJZs2aZatuWlXPnj1x+vRp9OrVy6T1A4ksxQRvIiIH5uLigrlz5wK4s5xM2by2ssndHTt2rPW+1YSDBw/i9OnTAGBQPoOoJjFYIiJycOPGjUOnTp2g0+nEwAkwDJbuueceW3TN6vRJ8YMGDcJDDz1k495QfcFgiYjIwTk7O+Pzzz8HAPz000+IiYkB8P/BklQqrRMVrv/8808cPHgQbm5uWLNmja27Q/UIc5aIiOogQRAglUqhVCqZ20NkIY4sERHVQUlJSWJl9boyBUdkKwyWiIjqoEuXLolf15XkbiJb4TQcERERkREcWSIiIiIygsESERERkREMloiIiIiMYLBEREREZASDJSIiIiIjGCwRERERGcFgiYiIiMgIBktERERERjBYIiIiIjKCwRIRERGREf8HYods9wushqwAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wrote network/d2oe-10/figures/Network-distance-dependent-connection-probability-iSPN-to-iSPN-synapses-3D-dist.png\n" + ] + }, + { + "data": { + "text/plain": [ + "({5e-05: 0.1930022573363431, 0.0001: 0.17570009033423667},\n", + " 'network/d2oe-10/figures/Network-distance-dependent-connection-probability-iSPN-to-iSPN-synapses-3D-dist.png')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dist3D = True\n", + "\n", + "nas.plot_connection_probability(\"dSPN\", \"iSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[3 / 47.0, 3 / 66.0],\n", + " exp_data_detailed=[(3, 47), (3, 66)])\n", + "nas.plot_connection_probability(\"dSPN\", \"dSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[5 / 19.0, 3 / 43.0],\n", + " exp_data_detailed=[(5, 19), (3, 43)])\n", + "nas.plot_connection_probability(\"iSPN\", \"dSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[13 / 47.0, 10 / 80.0],\n", + " exp_data_detailed=[(13, 47), (10, 80)])\n", + "nas.plot_connection_probability(\"iSPN\", \"iSPN\",\n", + " dist_3d=dist3D,\n", + " exp_max_dist=[50e-6, 100e-6],\n", + " exp_data=[14 / 39.0, 7 / 31.0],\n", + " exp_data_detailed=[(14, 39), (7, 31)])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "da809425-6011-4c7b-8faa-1aa6714c9bca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Setting up inputs, assuming input.json exists\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "Writing input spikes to network/d2oe-10/input-spikes.hdf5\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "!!! Warning, combining definition of cortical with cortical input for neuron FS_3 50 (meta modified by input_config)\n", + "Writing spikes to network/d2oe-10/input-spikes.hdf5\n", + "stop_parallel disabled, to keep pool running.\n", + "\n", + "Execution time: 13.8s\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "snd.setup_input(input_config=\"input.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "866b469c-2706-4c69-8c6d-c3ae8b961918", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MPI Rank: 0, Size: 1\n", + "Creating missing directory network/d2oe-10/simulation\n", + "Created directory network/d2oe-10/simulation\n", + "Using input file network/d2oe-10/input-spikes.hdf5\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "NEURON mechanisms already compiled, make sure you have the correct version of NEURON modules.\n", + "If you delete x86_64, aarch64, arm64 directories (or nrnmech.dll) then you will force a recompilation of the modules.\n", + "Reading SNUDDA_DATA=/home/hjorth/HBP/bgmod/models/optim/schizophrenic/BGDATA/d2oe from network/d2oe-10/network-config.json\n", + "MPI Rank: 0, Size: 1 -- NEURON: This is node 0 out of 1\n", + "0 : Memory status: 72% free\n", + "numprocs=1\n", + "Empty mod_file field for ChIN -> dSPN synapses. This channel is IGNORED.\n", + "Empty mod_file field for ChIN -> iSPN synapses. This channel is IGNORED.\n", + "0 : Memory status: 72% free\n", + "Added 0.0 gap junctions to simulation (0 total)\n", + "Warning: No channel module for 20 between neuron 16 and 27, did you miss specifying a mod file?\n", + "Warning: No channel module for 21 between neuron 16 and 81, did you miss specifying a mod file?\n", + "Added 2582 synapses to simulation (2582 total)\n", + "0 : Memory status: 72% free\n", + "0 : Memory status: 71% free\n", + "0 : Memory status: 71% free\n", + "Running simulation for 1000.0 ms.\n", + "Running simulation for 1.0 s\n", + "Running Neuron simulator 1000 ms, with dt=0.025\n", + " 1% done. Elapsed: 8.2 s, estimated time left: 810.4 s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "IOStream.flush timed out\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 20% done. Elapsed: 162.7 s, estimated time left: 650.9 s\n", + " 40% done. Elapsed: 325.9 s, estimated time left: 488.9 s\n", + " 60% done. Elapsed: 487.6 s, estimated time left: 325.0 s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "IOStream.flush timed out\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 80% done. Elapsed: 649.5 s, estimated time left: 162.4 s\n", + "100% done. Elapsed: 818.7 s, estimated time left: 0.0 s\n", + "Neuron simulation finished\n", + "Simulation run time: 818.8 s\n", + "Simulation done, saving output\n", + "Writing network output to network/d2oe-10/simulation/output.hdf5\n", + "Using sample dt = None (sample step size None)\n", + "Worker 1/1 writing data to network/d2oe-10/simulation/output.hdf5\n", + "Program run time: 831.2s\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "snd.simulate(time=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "7b57be40-17bc-463f-bcbc-b5799b13ef86", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network/d2oe-10/simulation/output.hdf5\n", + "WARNING. Depolarisation block in neuron - neuron_id: (name, parameter_key, morphology_key):\n", + "61: (LTS_1, paf75a0ec, m265f1bc4)\n" + ] + } + ], + "source": [ + "import os\n", + "from snudda.utils import SnuddaLoad\n", + "from snudda.utils import SnuddaLoadSimulation\n", + "\n", + "sl = SnuddaLoad(network_path)\n", + "\n", + "sim_file = os.path.join(network_path, \"simulation\", \"output.hdf5\")\n", + "network_file = os.path.join(network_path, \"network-synapses.hdf5\")\n", + "\n", + "sls = SnuddaLoadSimulation(network_simulation_output_file=sim_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "8698ba27-275f-41da-8ea7-ae3e0f4e94b6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading network info from network/d2oe-10/network-synapses.hdf5\n", + "Loading input info from network/d2oe-10/input-spikes.hdf5\n", + "Loading network/d2oe-10/simulation/output.hdf5\n", + "WARNING. Depolarisation block in neuron - neuron_id: (name, parameter_key, morphology_key):\n", + "61: (LTS_1, paf75a0ec, m265f1bc4)\n", + "Plotting traces: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98]\n", + "Plotted 99 traces (total 99)\n", + "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/schizophrenia/network/d2oe-10/figures/Network-voltage-trace--FS-iSPN-ChIN-dSPN-LTS.pdf\n" + ] + }, + { + "data": { + "image/png": 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XveEiVmhjxIgR41vAr2+biWmf5bagZoOWlnRerbg0rv3ZVOX7pqYUXv/36kAY0hv/XoO//HFeKP2qdfbimErpL1C/u3N2qICsi7mztmul85UodT3LFlz3BMnWlgwevPcbjH1i6S4XNvXK8/lXslcsq8dVF32u5TlZv05vX5rbFmH15wqO7e0Z/OaXX+PuO8KNFy3NrHemrrY9kmf99humY8qnm0LTGfSmNQAT/rsWv7szN6/ifCf8N9/96pLhn2LsE6yxwx3u7lfofLMKyaTjjdKMmIiKt19fi9uun45rLpmSM63//GuVcp9yS0saX07p+JDniRPWAfAPBLrhsmkAglEmE/6bH+V8x/Y27b63eEGNUClxFcMdIVe/8HDXv3ysg7U1csOXN/cQIJO28OxTy3Dfb+bg4T8vAABMmlDlrWUrltejqSmFO0bMwNOPLfFouM7QMKXdXVNFIb6/vm0m0wfd9eXzT9TjkEiqh/HQStow4RhrdZTJKy74HHeMmME8+yKLMdHammEiCuI9tDFixIjxLWD2zG0Ydf/88IQONm9s1hbiZfjqy2oMP/lD/PiE9/HRextyotXYkMKML6oj5Xn52ZX455hKrF4R9MZaGovO6hWOtTfivpwd29uwfl0jFi+s0Ur/4rjl+MkPPohUBo1Ewl52ZOFYLly5gBdCEo7AnkpbMJD/ULJc8PNz1SGjUVGzvc0L5X7936uxfl0TtmwO97zpCsOu0SCsLVzhZ+E8u4+EhbPW17Vj+A8/xPvvVnnP7rzlK9x05RdafAHAovk1+PuocI+XuxdvaWUtTj/+PQAAyVER/dVNtgCZrbCXyRB8+uFGoQA9bw5r+AkYsF5dk1WZHtxxkxsVKb5NL+TYx5fg93fNVoadAvLx/+K45Vi/Tt1XN1SFrxv+OGFrddvWVtTX5TdawbIILjrrEzz7lH/GQPWWFox9Ykmgr2zZ1ILbrp+Of78QNKBt3mQrZmH7S3m486vOmsPj5edWBPq3DK4n07II5n+zA/96doUXVcB/Jz0/VVHrvNsuvx05S1nW3x6wlWSZEkrjnv+zjXVha4psjqX30Mrmj0SO+1effSp6BNBt132J807/KKvydhfECm2MGDF2Ccz4opo5aEFn8XFx2U8/w1UXfe793dqawTP/WOIpAy+OW85YdkVYsqjW++2GOGWL0X9ZiHtGzsKG9fpKdqtjZU4JFtIoC182YZJXXTQFt103XSvtC88s93jNBr7nVc2oq0TxX+4qxE8+WolFC2wFK0pfiYIPJ62P5DGr3qwX7l1X2651IMiFZ32Ch+6zvfOmp+Db/77zxlrUSYTpMAXVhbaH1mC9oGGsNzba43jOTF+4XSUw1IhgWcRThHUMFa5g/NGkDZ4QblnARWd9gueeVh88psNLNvjg3fX48++/wdczgqHPsms/3CoOuxbERSZtYcni2sBz0+A6SpaQ9c98nWOjs8+7Zofdvy844xM89Kd5WLW8HksW1+LUYZOwtdpWfm66chp+fML73t80nh+7HL9XeOvXr2vElRd+jg8nrZemAXyvGx9munF9c+hJ2Om0FenwH9cYM5e6zuaxvy3Cqy+uCng8W1vTDh/Bdcb1NKZD5lkeuXjuxj+5DCNv/ipSObTi7HZdXpm2LOIZL2ljlcHNSzRaWzN47ullSKct72oaWZgwjbpau1+GjcNf3jhDuDYwpxyHKLRRjQ1eflP+3TLw8693vdCe46CNFdoYMWJ0PFIpC/eMnIXRf1ngPSNZzLQ7ttuW/PcmVOHfL6zywtWeH7sc//mX/rUYuYbhuHvharbrh3u5C0zN9nb8/NxPsWN7mycIRRGsCSEghGDVcvkddNli/abtSBbkZ9kIrWN3veXkMXcd/uJzP+xqZ4UcP/Sn+fjTb/T2o+qitqYN5//4Y0yaUBWeGMAsRylyQ2vXrW3EJWd/gkcfWoQxf1kozGNZdh9QheJ9M3s77v21Xmiu63WQec15JChF+a3X1mDR/Bpmb5kKUz7djL/db88DOsqdO24StGfEItixvQ0vjV+hV6gEsj5KCAm8y1CKi3sYTmNDiskjosmXYGkqIP9+cRVuueZLVG9hFTlPKcjByEMIwWnHvhc5n+h05dlfbfXmwf/8axV+crId3fHmq+Lw3OamNJ75xxI0NraD1lc+nLQBjzy4wFNOXAF9+VJ7ntu0QRy54Nb322+sxanDJjFzxY7ttoK4ZqXai6sy/DTUqz20P/3Rx3hxnF4//GLKFm+PKF2W27fTaQszpm3Bv55dwfAl6jLuu6h3TLtGYP5bCSH4cNJ6VG9uwZUXfOattdmCPhTKVUxdQyk/Rmhe6KnHNHlDG8HML6tBCMFHk9bjpfErMOsr3zAQxfCpE+Xx1mvBPkx7aGXWn1zDfem5TgdrVgWNid48sRufcM8jVmhjxIixy6B6iy8QZeN1u+isT+y8EAuPKtCLo2hBjbKAR11w7PLtfxd8swPVm1vx1ZfV3noY1UM77bMtuOHyaVi8QC+M2MWaVfU466T3hWF0Tc2t2P/Ym5DJ5Hb6pWeoCPkk0zvIg00oMspHue+vsTGFtatZAXbH9jbPG/jgvd/g1GGTpPnXr2sSCgi6aHK8l2GHjriCrevJdoW+yR9uxLZquy/Kro7IZAjefn0dzvrBB1Jv+isvrPQ8Pm4dz5+7QzhmeO9wWG0bVDjh4w8vxu03TA8InzIwp2VrNGtLi/19NH3aw3PRTz7xfmcyakNP1dpGvPDM8tDyX39lNX50/HtevaXTFn50wvt46zVbaXKjPRbM3UHt33N4C+mrumN9s3Odldufjjnr17j0F6M9w0cuV4Jkk3Xml9W4+CefYsUyu34zaQsP/G4ufn3717jzNttr98LY5Wj12ktM5/mxy/DvF1bh17d9HegztPLDKxyyU9bdZP/912oAwNJKfx83HfbKY8Wyeiyab8+fvucwSD/M6NLclMYLzyxnDlITedY3rm/CvXfNxui/2h5fWkn1DshLE9zzf7O9cGTay8lHa7jfRh+ipIMXxtr9n6+TVSsa8NCf5uPvoxZhw/pmTJ8afR/n1Mmbvf3pbssS4n+H25cD62+GeOsGq9Cy9GfP3Ibf/GoWPv1goxclQu8lj2Ik1xkDojG2nrpXV0bCCNG8Vq1QG6N151IXH7yrjkDYUxArtDFixAAAXHDGxx1+AAd9AqhrOVy7uiHyHklDogzp5AGCoY4vP7cCF531ibZw4IXLRhAMeS8YvahH8bYQQjDf2cc07XPxwVrpdAbt7UFl6I//by7a2ixPKKXR2pZyeMne9VO5fD0+mersZwpz0DqrE5+OPwQIiGb8+M0vv8a1P5uCxkbfe3bRWZ94oYOfhFylcNVFn+O6n6sP+AKAT97fgL+PCnpQXeE07PCud96wD6Jxw9Jc4Y3upzKDjWURzHLuZhUpvVs2tTBhxITYytyvbpohvGLK7ZtuWGdY2wnDCTWFMJNxcGQ3fmns2OYbol59cSVuuHya0Di1Y3sbrr54CqvQSjBlsj2u3Pp3v9MNQfzGGX/vvLkOc2ayYceBb+L+1NFn33x1jZfOnau+WbQa/5043as/fpiOun++9qFcutU++aON3py4zhHk3bMM1lc1Y/JHdn1srGrGNRd/zgjyMqNfm3Po2crl9Zg6mZ2/MhZgJuzflsUdfiYLkXYqyg29baQ8qq6xR6TQ3njFNNx+w3T7pGCHp3TaClxFo9tH3b26s77ailuu+TJwv6+rkLtXuYhCcemivpyyxRuXjY0pnP+jj5nDgtzxlmoPTo6EEKnhZLszXvhwWLevu2dDZONd/OPdc7z96e5HVW9uCRgpA9EPFr0W+r95xc6d67ZtaxPuU42yTuiMQ9FSWF9PR2Ww7wghqN7S4oewW77hnQ7B//VtM5XlmhEN5qL0Xp3vOQ7aWKGNESOGjdqadjw/Nrc9Z9lCFI5HLHuRv/ZnUzH2cfH+119c8wXuujW4Z8cV/l/71yr86bdztHigrb0N9SnGS7nQsdS3C4QDEbLZxsYrwcQivlfHqZf/vrJa6T0E7EWyyTlhdvtWsVf5hxf+Hp0G/zzw3D1wQyTseApDdOezh++e9itcf+c/AAA1IadvyowSouKjeLCXOR6ac0/9iDFc0HvW8oEH/zAPb7++LvDcV9TVPHvKkpPMrQ9a+JPtQyaEeIozn2bxwhpcet5kpn8T4ns6tziHydBw++YTj1T6GRTwQyGpsEmFQjvhv2u9fk0rvnwp/3p2BV6Tbh0I7wOuAkSHAgPAF59v9qI7GIqS79zsHF7D9zvPg0c9bm7OOLTA/CuFxqTxxOjFWOp4+SoX1mLkzTPgjQzJuPng3fXe4Tih0Jy4HvjdN3hpnBv+6ma187qnLQNAe8rCurVNjAJCK7R0e7j9PJ0ShHVnLCZygz43gZ8C3LbmT5F2DaWEEPw/5/5ivpxPP2SNWu7psC+NX4HhJ3/IvNOd4919uq4xhY5GAoLKGX34myFYUL76strL454ovpTy/Lp7TkVK1+uvrMbpx70XyWCU5JSifG3z+OrL6lCFllj0+JEbyWjvveiU/EgHeGm5aNWvly+pQ3t7BqtXNuDsUz7EK8+vxM/Pmewpr24RTz9WiXNO8Q9sCiuaHjtbNreEemBFtj5eqd4TECu0MWLE8JDL3tG1qxtx6rBJOd1rSodvZSziWddFHkMAWLq4DnO+Dp6q6E7WK5Y1YMonQS9lJkMCd2nSi+PiBbW481bfShp1z0tUCyoQFPgtC97K5oZKyYV5H4SwexhF+Gqu2gslOuFScf6GFtrbMzCR8AStpZV1SoGKl+FaWzMghAg9fVEWZVoYoPeX6R7Gkyt8gTwsnf2vOwY8gwv1+bLDnwjxv3PTlhoUDbwIX82xjVXu+KT3XhJClHsv+RC5MN5Fe79VYXaTnGtR3n59DZoozznvUXn2qWV4Sna4m0b/lJ0uKjuwSvSdTz1WibraNocOm04U0uiWlWpnFVu/DPaBexDS6pUNyiua3P7691GLMG/ODpQXdAdAK5aC75GMkwn/XYs3/7PGT8e9lx0+BgC1zjzKC8iMB9YhSCtt9Dg+9zRfmFeFU1oZPx/fT/nvdZVdV4F1+csIovT5/iDz0s+cHjwsUNfr5+7llM3NMm8jIDaQ2qG67HOapmvIEu2RnDrZ9uTKwrSBYB/g591cFSH6m/joCtU6y4Qcc13FCyEnxDM60Z5mmRwRVo4MYftPxz+5DGMfX4oPJ61Hc1Ma8+bY4datzazla/o0tl+FrbXuwYgA8Pu7ZitvhGioT+H1V9YEnnv1ry5qt0Ks0MaIESOwzysbuKF1C+er9wb+4dezg9e+CKyvxCKekOounrqLaNiCMO4fS3H+jz9mnvECxUpq8UsIQihdvPXamkBoacLztkaoUI7nr77ww8dcMolkuNRuWcRTqLM1UIiq2fB3PWVFc8Tl03B878vZchTCIO+h/ckPPsBzTy8Xtm0U4Yo2NtAKSNipy9mCDy30D7sK4ZlTfN36oEOFVXuHXYVi8TLbev/ux7OY567i5JZhKvqswXXOcIXW+ZeqUtWJpO67v49azBy0YlmW/pjX0WglXgkZb6KSX/vXarjbyPk29BVcQj1z+q/j2QubE2p2tMOyCK6/dKraoxqIXHA9+L6Xyk/qevvFZT/2t0V44pHFMtI4/0cfY2llrZgNy1UY3QcOPwLFlK5mWXdQzd22h9b+PfYJzrAhDTl2CTs0rOBax/cHPhza4P5l6GvOh5s3tmDZkjrmMCRVmUz5IoWWOvkXgvHmjW+FgUqljAe2enDs0Wvh1uoWYYSDGr6nPGgw4zy0IMJvDPQV50FjfYox0Ph09bnTOSwpLMoIsA2H7txqUAo3zQ//HWF7ZOn0YfeSr1xeLzZcxCHHMWLE2JORi0Krq0RN+3xL4KAaUTgeIfAmWysDzPl6G04/7j3vMBQVwvbrzZu7PcCrKovq3rjHH14cCC3VERh48CGlM6dv89ca18Oh4SblD9l47x2903QZGqqQ4yxRtTZ4tYRKWREJcZ99JN7fGqWeacGRzqfqt7p3K4pwz//NjnTatQvfYyrweDmQnYhLiC8Uzvmi2XsGAImkeNlXemi5onXnCdUBLjToPa30ycyZDISCqQg6e3Rl+8Z0T2Dm4SlHLllPUPV5CRjBAh5alzn/mXuQzSLFoW6yJhB5aL3f2u0WTLh2lfgkYD4k3v87mNbtw3NnbcOq5WKvuFKYJ347u9fS8HzwqHHusPXOJnC2GQjrR8aDp5AEeYuyZn40aYNfT1y/UEb1CDquRXxlmo6IuO36L/G7//PvZX31Xyvx1GOVbFka13U1NnARTLwXlZonpk+tzuLUY99gF3otGGGjINatacRbr60JdDK3eVKUV1a3eQLRTxoZXS+wCpZFPAO3F53DRXbwBvAoa61r5G6oT+HKCz9j95VD3sYGVf97CmKFNkaMPIGkcjvGviMh2p8SFVEvC9+yqQWnDpvEWP6D4Xj2vxmLeKfCVq0Lv9s17J429y0TEqnIEtXj6VnOTf369MqnI/UEir79t5wuIcQTWBbM24GHdffNURDvoY1MJrwcRX0KvRIQL/ZRTjlmTsNlQvTkNJYsrtOmL0I7ZSF393GFeQACxgtB/UtJ+A4NbN7A7hcVKcZ0nxF6aHnvjEVw7mkfYmllLV55YaWwfPsfenzJ6dN7KPl6ERlCRDCM8D7gKXt8Xtl8EdJGbv/lI1wYD61MgVXATbNlU0tgP6eMDu+h/eeYoMdV+zw3AY8yvvmQeO9vwTh16/nOW2bifcm+P9U8Q6CY2yUMeoeqeYpkeFaZhzbSGBTAsohXT7wtSmWsFBmb6DMW3AQZi2DxglomhPWbWTvwmnPCc4AfBfOvPM8qeAGjluJwJho6BzqGemgZbzpw160z8fjDiwM8iQxWujINv5Uhl2uvaBDLlx9cTgIeWi6M3j34TAb6uwscA+WyJbXYUNWMiRNY4zp/08HT3HfmIvPtaogV2hgx8gCyfCqsW0tAtq8NT7wLQzS3ba1u0bqmxL8rT2+CdI+mnzWD9kSK88ruoZMiTPkShOWpPDyiU1s1yAMkSPPxhxcJ7/9UnbnkKQYCJS+Q1vLbIpurj4AQxd1ghfhHHhQrzGtWNWDV8npsqGpiD7KiVmOdsC66jexrO4JpIoUcSxRanhXmWp0cF326HFe4bOAOJuIhO+WZ5l+qZIC+3sRN61r/RfyJQ1V9ZoKZGhvSuOOGGRj3j6XC8nn+TE5ok5GPYrxhaehYXMRGN1nOsKLTXCifV3cKgToQoioogx4XL41f7p2QqwO3GurqqP4ls4xJIEomG6u+TmWw6QSVqtNEqnYkRL4XO0wBMTxFknOP8b8h99ibOWq0hJDIhl8geG0WIPZI6873nrEwwvrA1wlTvKJd3XuDA/CUOhJoc9EcQKj0bt0FFFrXk04/J9kZY6Nc8aOCRRkLPbHArXd3Tnb7pntFW4gAQ9eXdzuC5JwPntJ/OE/0HqTPxgptjBj5AFk+xZ4Z1ss35+/K8Pe8BWe3n509WeuaEjf0JaN5xY7IAxcIRXb+tTLUoqcxA4eF5vqXiutwqheixRbA/MPgrdfW4ovPFdcjMdepBAVkAGhuSnHKGO0RohbQLL2qoiqWCR2TJohDmq/7+VTccPm0wJ2vNHTqk05BLAi/ze23mzc2h9KUhRzzdfzLG2f4fOa46NOGEF1jg8xBy3w3l4f2FHrCE+c1FHcJQh2oEs6Li9D7lilaBs8QU4CCRB4FLlnIscyYFarQum42zwPKGnuyoQmwfWPdmiY8LTrlPUCHFWxFSXX7sTCZJK/btwPTsyB9WOQMIFdYbdpB5SeEPZoyAKqNVHllHV7AW5TuSW8H+WgS66FWKlBi12OgL+meA6C7njEnoavoKRYaWRH+IWKCdZ8/8Isqn65DXvETGoOJ5EUIsjUGi+jwHmx/T7v9d4Iz9oXdU0t/j/fTU5K58mV87UmbZx3ECm2MGPlAcQUAgLTqn6K3S4EEF/moiLrH0he8fOsrf5UBvTdIFi4oph3y3rNQk8AzZXpdfda9eiJC3JKw/jjHipvm3NM+xovjxCdxEkscvhwFWoqmpnSs2p+oFBoERhbaS0TXl2UR1Ne147KffhZ+EjRVJ3SosmqBzzUsi8mv2Zdk44np27LQPOKH4AZsIgK6hNAhwWq+aMj2/am2MIjIM4IpL5Dl8VAoL6yaf57lOHHvEubrmOnWAauD8k87P1dv27e2YvpU1ggWuM7K3YMvoKcyWIogajfZnODy6tWtakxr1LPSGKnytoV0XM+IqXGVuPTAKlGxEaxd9Cnt69ZE97rTy4l9Cj6bbrPmDQO669nFP/nUz8O9Y6/PURCRFULx8CvKeOjS5r2s3k/qSp4AScFAXrm8Lqtl0LII/vz7b7Bta2t4YhUdQoLeba5K+AiwKIdC8Z01UN2yzqyYo3dXxAptjBj5QFGZ/W97+IFFuzJymdtUDhhhespCGwZbmFKEREpoS9+71nrtcEb736j1k1EIT0GBlP03DF9O9fdJBfbThexJCoM6tNp+16Z5Jy+/ONN/6ex9ZSIDKWWd/kbLAtqc0x7D9rvSis+l536qSMmWmwtE/SCs79H94JvZ2/HRexsAsAcoSUOOiS/5815Dod2EUhSEB4JJePROUl5Q420hoPkSKUFCnml9lkugHRShsYfWo8mHHGep0fL7A4nAS8K3s05INd/fliyuw+/u5LYpyJyIwoOLIhosBQml3dU1tvEnuAqI6Bgd1B5a+fwYGnLs7jPNhB8KJeNSNnZ0oeJfRIc/JIi5BSCC0YGH7h2k9Om4gZS0jS7PERaWqJ6I/84zpBlsfYjW6TdeXZvVftjGxhQ+/XAjXn5uRfTMFOjbGoIv2TnZbY9QhVZAULrGh7TxHqTPxgptjBh5QWGp/W+bvtV1V4Ln2MkhtjK6F9NNT1RxMQBsBUt1v2KAtmYCbUVFFqsYllxRn7zSKFJoM9yhMzRU4WXBQ3zkvIqgqmN30f3qi+CdjEJelPdKKryibhpCC+TB/Uguv+7dfFGuKqIVTdU357roM4ePeUTVeWijzLNPLkO9syeyqdG/nzKoHGmRDoDdmydQREJCjm+7fjpuuGxa4D19YrFKYVYVpu1V1NBJpSHH2UYyZPx+CVDGAwXPOqF+GZ0By32wdygUJ9XdfcfXeP2V1Qx/oaQVyhUP7yAbbg92mOFCBp2T3EUIM9rx6xNRabRSGkHeoiyZlhWq2wififqtZQWNVNrzFKdA6UA219jkFHO8zLOvKpvT/Am1BoDx3rJpqL/ktHWhMMpFIkNn59rJI81Fx4QNAfq91/ZeeZwBTVIXqiia3RXJjmYgRow9AUai0J422ndPhdYFP7eNvHmGOKGSiF4y01tUVZ4m6g83vY5CqykTZRhFQ55JFPKlLN/5V+WFy2QIEiEzsOjORL8MdjH3fxOPA0PwTAcirnkvj+4BWUF9Vsx3sLxgImL52W3h0kvEfascUg+JSgnJNeSYpq0pfNJ86tw/zJRHC3ec4CL8fuLvx8vL3jFOUAP8ezGFfVkSXij4UwrV+HX3XvonObPvs1Wi+PBVlVLiP5C8p8ew1iTn/GPIlQtCCL6esRVfz9jq0A0na7MSLF8293kCv84cqdOYKm+fcltACFkFf7phmsKnEeaGqPMIsQhgGsLtNoQQSolx+NPsxtkcCiXttwgJOdakR4NX/Nl7neWh30bUsy40kA9jZvD8CfG6rj7ngAKVwOSsHUGaYmp7kiLrIvbQxoiRFziTw+7qoXXZ5y7pnjdnhyC1BJ6lUHOiFIRRyUBATdx5mIi1vUU8HyHJVyyrZw7FUi2s/GnQoj1wag+m3PLKC+iTuKP884Ft1Xp7i1T3K+ooxbZ13klv+Ypr4HojXSd6BOu3x2ceBSQvdD5U8fYZofeM0QaC4Im5rlaKwId4J4MKymJNFUJmlLwG6CkEszDHHf9N+nto5ek8JYaOCqHzZikJ8ddveHRVCrrG5+js8/QIcwNCdWK07haLKB5aF2GCNcVi1rAddzIBXZ3X4Ns+m+6e4z20RDAu/ZfBR37XFxtilJkV8K4wisy8uEzloVChSrPQfBrox8wYE83RBFKDVTZQRhpEALNmubQ5SwTvZd2wPsLWNa9fRxsXlMN7j0Gs0MaIkQ+4s8Ju6qF1F/namvaQlHJEPVTGOyiBKJQzSjji72pTMxPyOqKF2iVXubBGmqaxIYUbr5iG58Yu1/JW8MKEUJFSpWHN9fKCAPx91GLlex5q4dV+N1ZwXYsIqv3MKoHKPwmSMIuvUPGPoHCGyZPZ7qdUgeZO1y4jCiuz/5AQpv4kJChEiYn5vKj4kR6SE1JVQlE17BjlLBRAWVk8EYP9U1h8FHj9jnB/B4um/pY0GsWDjqLhhRhzfzOGnnx6qjSvxfGUcVEza5QT9XBBFw317Vi5XHEoI6fQMlEtAR6UJBhEUQqJ5Noxmi8+Pc0P3568UqJbc96VYBE8tKqupN5DK84ouj2JfhfoByHVzO4vVqfVgTeX5hxy7Ld5MGqGfe6WFbZtRrg2eP1abngQIV/37e4KiEOOY8TIC1yFdvc+FCoXRJVDAvcWOpAtTAELuwbtSGUrsrjk/vaA+M5VwF+E1qxsQLLAlhiyCb+jVRGiWPRlpAgBmpvTqiKyQrZCQs4HhlBpLIuIvWm0cBqmKMourvH2AnKn1GrQjAJfqAkRWqjvNCQarZIEpzgrD4UKuedZ1oRhV6gIhfRQwZT9O5d9nzw/ka/filqmwOsR2NMmK5rOo+Gh9Z13BmQjPeuvFGSUR4S4/So/hiAlGQJpZxz3z6VobEjj4xlnyigD0BPg5eHrwoqRItsDzvj0Xr+VdJ6o81PUQxHDylQZAaUewizDx2Veevp6nHyMbw1HfiQ67LOgUUWWVgS6f4YZSEPlpT3IRRt7aGPEyAOIu0qmcjvivcOQxzlNe1KmJmJWABTRJMLL5XNFvu6aA/zFlLGuKgoILLrC+EzW6moEXwmyEGzZZBtWdPe5Bolk/TIA1YmNSuu35/UCUw9CTxSTLbcOIjz4ZSceDCLlg/5ATV1B5MkO0BUptHTeCPUXemJrBMVIBn0PgirskVW6gnWfnTLGhyWKFISwrxXVR0ZrYhJT5q+zygZCr5lsLokiSOcj5FjyrrEhLXkjLpo3AqoS++9Fc4O8zIDCovLQip7xHlmqLMIO2kjwven6GVWGmew8tCqFlm1oer8wUx5t7CTiU47tDHL+wpCrvEEIAhUUmGv5mOMQsB5ag8mqqyTvQXqsh1ihjREjL3Bmh3SbOtkuirxObprEvImYu0+PyU4LxppXDUQBe6+pIqGG98EVEjIZf2FVCjuBIoJlZHQ9tHz95UFwzBeC1/ZQHkYVD5Lf0j2urpAQen0HVw4fqiVS+HIWaqh+5j4LzyV8qjJq0Ad3BU91dfJnEXIcKQYz5L2ofdhvyrayw40jUaI8dOCHTUZRDDTSaCnxEoMFQ0iHjqD8LOrHl8n9Pphv5GqsAiTfFvK9qhPlo04OSxbVaqd11ydvPWGil0hAMdJ1kmfjyeTTMnOaomBpX1YNV8LtQiD0PE3PofTCJ/dWZrUcyjTELOh43+Ipn6whQtS+SohCjt3iJGuCgr09BrFCGyNGPuBOtrurh1YA3UN/XETdQ8sLQB5CQo5dWO/8EZfu9bKStgze4RHUYqvKoyUoCLxw6qsJuDK8f4k0jc7K7J7omm9kqwSE3SsZWi7Y/iALOdbmLsSruBOqTlh+2N4sug3le2gV5nfulaXSkmx3j4IXyXMlvQivjJD3GlA1m3cQr+Tqr5z30IKlKzTKeWnkni4XOvczy0B/S4CMJllRMnnoqF46XYSGHOcIv43E64yIBy/qRqQLa5TlIp228NzTy7XSAv5+ZMb4K8zs/qPXkT2FUFBmvue/0DBpUZ1ahDloih1PYkXaotY9S2WA0IQsLDgq2GtoWZq8wVsdai3+7qDcFT6/0PTyuc++oxErtDFi5AXOpLCbKrSiKW3Gl3r3jLrIZSFkPIyi96Jn7/4BV/T+V1blubzqCo5a+iwlKHl7lFT30HLvRFFHrhIi2qfGemVZ4Szba0g8Gtq+03CorlNRKz4yw4bh0GU50hVAglco+DR2GhjimoYfJuJYXIcBEpRCZZjsszUrG+XsKRSwbODVqfCQpOCzfMjQOsKgL/zlp7W9e2eVfOkJmEwajVBQg/tXSEeicIczoJlOQXMnRBwrQ+lDwXvvFN8YKEKRNvQ+VfmfyrT2I6ffmuzfbvJg9IWCvl6R8pBohfKVjRFCNe8SQBH2TRdI1YeVv3Edxl80QhH6k2ZXEkYpZaxAOkBuBBEa33ZzxAptjBj5gDsr7KYKrQiJiKe9RtwG4iPgwaB/58dKKoP2HiINSYG1oLrPVBkkZVDPLZXAIrECEIKdGnIctSlUVae1P5JwdStKQgt6IRxKQ7Q0letskE1uxikb4lVWPXd/zp29TUpLJBwzvMjaMGRcCIXVkMrItq6VQ83pZzLPVLY6kics6us0Wu917Gw6tZRtt82lvyvHU87zknwPahj8thcpjlxa2WFnURXGaMml+eUeVdagEr3Z9DOoaEdtkyWLapV9zArsNSbML+9dxt83zcxh0dgRwqvTPHowXbZ9Q5hraHOeR41sofLqHiAZoBst+S6NWKGNESMfcGeT9O6p0ObzAI/IIcecwsIqJ8H0erR1EzMl6BegokhZZFUKszQUi/7NLVJ6nuLshT4hE94jDdeGCAFeeN+qhAVawQppJts67//OBqo6zqdBxQ0pD92/Jgkzpk8U1TqoRUNYJyBZCayybqZSjsPmmoCHQbu/KfoS2MbNV3tasvA+RTir9NoeCmHXdijBhBxnaRwQjv+QYjWseMpoDZ6OjK88zW2s0Uf9dcq3eepLwmrzDJmCiB9moVAMuIhl6q6duYyhW6790u+bku9mzlrg1wAH1ocP+b8VYy4b5MuDSWDRm2jZd56hLTxqh5k3BMZzHXlCTDckwW6EWKGNESMf2N09tFG8MqG09GZIJnw2hJeoHgNd3qMq30pagmcRotEknjM2kex6BH6ty3UP7be1yGmFX3KCinfIFK8E6balhImcBRddD6/2XnNZW0uE2sCfhiiJuC+TsDEWeROtkD9AIkTLjqyW0IjIjC84SpSubMeLa7DSubfZ+0unz2tdLSN5bsjrMlRxUygZ8mgA1sukSt+hsjPX9PyBQkzSCN09yhwfFXzIMa3QMvdzRyWssj1Ivp3/zpzDexXZg1f5+e1FG4xRt9lPQ189pnODQCh/+VkXADr4iqXJH0So8gYzfNAGTs7YEeA3ZNzuSRptrNDGiJEX7OYKrQA61nQmfcRDoWRg8hPu3zxB5xRiUXol6PXBExg0lRyI11w+pFEhq1J0fS9gODp2MdPVAwjVD8TXzhBKWAj5Jl7wDuVSDyoDhchzGsYnezWD/9vUPCU6io5GjwPhHlepKzaEsK5ixHgVQ2hmAcKNn7y1eWBfIQnQD3poxXnCngXSSJ4zh0JFrEzv1OYomSTfl23Qz84+lC2rk5KVSqv+HK/2wAmeCTx4dIgpPS9mgyhjnQQ6e3Zl+vRC3kn5IN47JtbHUve9yPx5/+ZGjD140lE+Je2mXA4Zryy9ONj/eHN4hD6n8353QqzQxoiRD+zmHlpx6FE0GjkJIhJjeT4PeaAhOhwm11OO2X2ertVUlZ4rQ+B95b0J0kOhuEy6e716F2wWPlfvM4vWJnzdMUKIpoAnTkbVBX8/Yw4Qeus6eNGXXXXkfmttTRuuvPAzbKtuoTMFM6igEI6lHiup0OmSykZZiyaQ6YC//iRAM8u5K+AV0VHgNb5HJ1Q4go1NH55XStcSEREaTKvmWsY7lyVEew2DxijFpBUgqP8uiieffsL0W2EkD/uvLkKjJVR5cygDgH+Hs/Bd0CDIGAUF0ScE+ZUXcjUWeHTgfwtfs8L2ldGR3MjgG+dl9Skmugc6aGOFNkaMvMCdFXbXPbRCKTYajXx5P3QO7eDeSnkJg74HQ78y6D2sUSzyIs+dZbEnF7KLvJi4fU1AfoWSXKCuAw0OGMXWv5qBVYyJ9gItO+XYTxDOkpBNSXvaLwXpQ+jR2eWKo03l6xnbsKGqGTOm+SeTG55S6TMoq28ingHCEabQZqEXZS9gqTqa/U++okhcyPYBCqNMvD85hV1EV2MPrZfC254nMIhF9dBmIeTKvd/RytbyShOiPbfxCLS9orhgVcozZVNX+undyvX/9u1U2YccK8eBbExLohFoelFAz0vBdySw1oV5/Om1PDAXR+bO/758RJzxCjjhDGG+111emOwNf6NCIAJEwZf9fs/RaGOFNkaMfMCd7XdTD60IkRepiFdiyA6CEoWaEviCDE++wEgja2jO5XoeWv9fb4FS3IenI2zyoUnyPbRspQWEXQkyJCGmp8gTefkLKIxiL3Mwm7h/hJ3SG4bgXj+ifO/SD0WAjvg7ZYc15QK3WzARAZyGQSBXlJhwPcF72VwQplyIFdoQA1SW9aJqo4Dhim+r7IqUX4sTwZCVbRodRPUOq/bQSvNIPOpRo36+rXoRRw3kl142dFXGH3qLDGss5Y0juRsRop6orsqj4knV1WwPrYwRqj4oFYZWeqOG2svKofnMCZyH1h8jkvlDxA4tL9Gk3SudpNfzhA169evdCbFCGyNGXuDMCrupQpvXaDJNWr4FlLW+qrwbIhSZWdS5uyCKFA1N6JxWqjwwhGeJ2hslSyRlMcv606Hn09WQ1iNCe6+gwFggThhOcydv0fPLCfOmh7qSxb+Fyp/Auy8KUs5YYk+H7M7fAEt85YV6aKMrDwEdTHdyUsXZ84pBnrqwzp7TgEAv0a3px5FCjnNUnpn03vfkrvQ1N0czNPr01SM012t7RIpKuCIYDHH18kaY41UQ0vH6ra/FGpyhKpQJAVRGNen0qrYJRYem8uaVRY2TcKNjdswx0VFeeTl+qHAOlGnzCuMIHXJMtRIfchyVr3wZz3YFxAptjBj5gDsrZFIgVqZjedlNINtfynjmNOgUGu2BZ2HeZZ0QH1F6Gkp91vVWq0KIuHcib5cfRkSCfEhI2yHHHlElTCPLO24iQLlgRn1HANFHWZYfThu6QAdctCHpNaH8FJESmW05AuXTPfmZ6VKBsHci39NNNBVH7a2FhPo/9yasGN2YOR6Kvh7YQ8uPvSy1JNooJ08jzqOC7mF1AALeH5aOvgcI8Ks6m/7K1+HSxXUhOTj6GgazfOyR9PfQMhotA9kWWmFEQiTFLBr/3tkJzt+yQINsbY2RFO4Qw0xUhN25yq513HYJ93ClPJ+jIDwcLw/rA9+fLG4ft39SsZwGXf+i6Soj2y8g4V811ndXxAptjBj5AD0rtLfI0+2qiGCplUFn3yhTpOROvajOrCJTpNCqyxYdKqFMH2F/Gr2HNtKVDl4eSmHhDnqQnXJM+D9yNirnbuH2nimY0bEn8OHEoiv9cgoZ5IVZQc/XsdIH6DAhx0FNM5KDVtKh+cPCwgw0Vka8j5Z4/5PwIlOastADw3jMh6IffOf+yvMe2sC+QlXZzt9hCaBnaJOliBrhIio3p1BZT0qPWLbmXJBriIWW95vfZx/GkyZU1zEp+w4dqypaJyS6TCg/ogyaIcfa67xMoQqpC+kBiJL+bZEIRk1puXIjR7YQRhU55YiuJ1LRccEecsxtLeFohPX3PWkPbbKjGYgRY88ArdA2A8XlHcdKFqDnvKbtKdSua8/6lGPdxUSxvZTiK9xKWmi26RVIQXSvX1QvDc8Sf4CTMBH9iqsoURhYwIqqwWMUoU92vY86LFWhoFpAQrwtV1JOuBJCCHtkkWJrVShNVf68I0ThDuOTUYFDhExDIOTy+7UA15MtpqOqv8hjQyFgi75adsVRvsBHOOTrNFRegBZd28N/kLRoetxnFTghiFyI6CHMytMnUXSy3cIRaowMSWAbFAVpFIEZMuNigLbwmWqSl7/SgciDR49rf3nM1gAZfKa7h1ZnTlaWTccQB8oiAZpBkyBAmD202Sv2LkQHS+U6VTDZ+Xk6aN2S07HEqcJCjqUGhWzG+i6O2EMbI0Y+QM82qY710GZSuYWRTrxrLd7+5ZocLOHRTLeEzyGzxkqE0SJByHEYhPtVI34vv4C4keaUEd0PAxIg6NELPvfvlmPTBGghuBDrwDDyu5qJ94oGSlW8U9Oi7yDkn+sKIKERx6I61qimKGGnsmcyegxLAoOJbn+W9ccwz4T02h7xY0pYErVhCKWA4Jw7Aoo/N0XqCuTSEFKeSdkcJkgrqo+MlkbrKIDOX/6hednNBYAvaGd7N66APf3kgut0gjxo0JGk0dlz7KWVeNTk2yD0eAl0hTDrJz++CbuHlu9/2k0kmi/CkG9LUwRvNeGeibYR0wfeZW2wYsatfCxIs0vnO7UXVTYv0e9E1wIC8A6KlF7bE1HR3Z0RK7QxYuQD9OzQgQptY3UKT59WidVf1EfKR0+WDVtSAHLZVwYsnLAD/75yhTIdrazR5VfNbESSE5VVk2+hIOQ4VKnxQo71ZnXhHlrlNQZuGjl92X4ZYcgxIVg4YQcybWJhlfALMSEoRgIV6QJp+UA0D633TrnHLSotDdCWd4j7pWX5BYUu1LxCK/OURwVXLn0gtfCU5hA+pfupBKF4oms4hN8hs9ZbWQqB2VzXIRgTslD6fMEbqzIPrbZCy/7NH5egw7vWyaZ52toe9doehdNMnsUT0jmBWtA3VGuKny+cPxXCDscReccCc0Bgs7hB/8OylOVcyecV0RHen6yon8inHAvSy04uVxpmcri2R2gjUIwR9rRfWoVRGDU12RPugopQpVJjCrdNho/s8Odv+dwoq25eGQ7MUTL+ddfL3QixQhsjRj5AzwoduIe2aZutjG6Y0xQpn2hOix4y5v/7xWObUbNWHQos29vx2X0bcWRBd4Yx1UJdRIUcH13Qw+FBPUuLPFru5+5jlmFAooxLL9pXyYK/YiecD16RCq5cdPapozdhx5rwE50JsUl0N4tC08pXa5mlOYSaYPUMCovyd9LyaEUtLLGmMSMKslr0JWG0KmePlBRzXRMt0KmUcV7JJUphX+nh5gQy/nGQllxYCq1LHYUvPJuQn1zvoZUJi8Gra+g2ig6dfZ5BCOaPqOWq9tDKjCGSF8IbxpTjnW0jWVmyOUP3tFedQ6FU5Qee5eDBC4/SYP+2LOoeWnei16DDg993qQNVGcoZVdZvFAQtyz/oziucmjj9LRaccS9HJU12rkdOkHpt/f6ks12LMNujqN/Ov1FDjv33e45GGyu0MWLkBdSk0IEeWjPhCGw5HLSci2fW5yM8veoi9FLD3t6vtDg7hdCnHPczS8MLRjBMh0YPswhHOYqxCsQiyNBhTs5vQq24qn3C0rAjEqwX75EVvrnLXfudpVL5DaYk5DjbNS6yQ0hrHzXLj+iAIkqWib6fLE/ruY5CFfaMTeD/DBuSIgVSFGJp16WAFxBlPXj6bFi4NvdC/IkhCofybXYZ3X5paio92kVqHKLEvwumFbSHlofWEP7F6GlZnnKsEsLDoOzXKmWV214hpq1RvjSyIZS8n1QmGUsMNLJvDmv70PBwoSHG/028ZNkpckrjVSBtdoYmGSzfGiQqTLqv3vZSu3XgJ2IjWliiuhKNyBMc5TNDPbRuOok3VdweAiMceyqU81486cp4IoEfuz9ihTZGjHxgF/HQGo5CS+8n0YJIYcjlKguNrJGESlHSpO2BFIUcS8mIQrg0ipKFmv3nX6u8vzOUUOGlV5zDr2NRtZyVz32k4910Q44BotEMWaxmKsu6oN8FkwdDZiMVLdBoLUufVkC4kBgWooIvXnZKp+oZDa3hoVKOOAHeVvrlh0L5FIIJ3G/hqyasqkSfEHoljULozxouDUnjard5QFjkmdXIE70YWao80aHSZ3HKcaAsdVXL8+vUDEHoZ4ubgHheSZEXOjh2w1lh6UdgRicf914Uciysr4hzYJQD4PiUuuNSlkw1D1jUd7o0REZNwqwlfo1EuvaKKTdoYMh1+iFWsE5lh0IJ28N7KXjG5GX/DZQlSb8nIVZoY8TIB3aRQ6G803ujKrQMkeyyRbaJEslvKjc9SQf2HroKLeWhJVw+Hu5Cx4RtiVkQM0TTIgTVm/22Zk5M9tKwedR3H7ruIyqJ57VQt2fAgh0kL4Q8ZFT0LNxinY89XCIe6MNPhHtQiS/phi3UWZ3ImcXqzxgf6I6guYdW7G4VJ1Ebn6g+rryHVk5BSj48YCD4TvAyP3toFYYWi/+bn630OgVfAn/1o2iMBL5Xw4OiOkxOCvck3HSKoh1xPGYhxEdJq+ylOvqsxCAD0NtIJEY1/j2drGFreOF0ITxtCYJtz78nwt98fvZQKP8d31758NDqrgm56kNh203oMWmHmgvSccZRfhxG5klwl20kWtLOyacT01YVJVNM3dBs6aFqWRiAdlfECm2MGPkAPYt0pEKbrTKaRy8Io3wq4Ibr6goEAa+qo70XminowvvOqB5aITFun49gQVGFFMmUXXrhkt2VDvCLLysY2epdeJsastNnsuwOka8b0RFiuS8RWqeRg1DHm2I09kvb5fDCiEJAo+lLyuWhd0cvYf+lyxEozpbCQ+vykw8FxffWCWtOTSnrqShcqTc9pSbbMljwhkOd+URWv4wSrNX47J/eQXev3ubzF/E7fd7kypWMDy1ntaps19ioOHldPa85Cr1CMeR/u7BWTucoyTQQAU8KJVvFB8D1QyENb7Hz8tPjOsocpAsphYiKUhi8Q4yEfU3VB3w11qKv7VHsf9Wtluz2rkuLlZbNRwmoPeZyOnYCNm9wP7+MWcLwsicgVmhjxMgLiOcxJO3NHcdG1gotRcKbFbK0chI9Plhnpbos8QJnP4vmobVf+Pf6yRdBGuKTdQmj0Lohx7TUERA4mH3DGgsP4RY++pWMYeIKfuHNkGVQufyNRFmSQX1IUVDBYu4nlOyx0nHRdkr4p4BnK8OEWcJle8BEex3DCjAkCp+ONZ7qcbYALSjYIkQ93GX7D0P39gafhSlZWmG8mmXxZYr2qUeB1EClaIewcR51zHiQecfb/AMBdcpi3ytVTq28vpAeZFDtoc1NsBZeXeUTD0TlsFMGW3bw2h7JczjfK+E9TOHUnQJo77M0QCULiOZf6dVwiv3Yyl4jqxvFRBAwihO/FFu+CO6hpZsh665Ef5Nqj29Ekt6SFaKcCj3mgsMi2S20rizjJONvX5B8QD58GLsakjuL8MKFC1FVVYWamhqk02lcccUVO6uoGDE6HoQAyUIgk+rQPbQ+P7lkdvbLZbmPSHQpugiqQ6H8F4r3zsxdwOyhJY7FXK7sAWF7aPUWeQIwh4d4IT9U+kCoo0oZcdPo1Av3jhduwvQTF9JreyJazV2IvSPRFGABM6EfQyzqyoYQcgaAYRVf4aOa0yIwIS5TfJSrW5DBpqUZAMK/SSLAROWWNwiIE0l+u+VL5gS5hzZojFDxoJov9JsnQj9TGB+UJUgUFOXY0OWfoqHlNZEmYfcVRoHOXbCBPDKFXSidK+h4/8oTuXObCqK6ox/5US90urCO7XtIoyBUYaXnetF7br1iPo2eF3UnP7D0ojRRrt7LID3nh2iOsIjWHlraQ2tZfqJsObUE7RFtLAiegbo72OtHYuOPKnLEkvRX3rurjAIQMh3yfjdCXhXatWvX4qGHHsIrr7yCuro65h2v0G7ZsgW33XYbCCE46qijcNddd+WTlRgxvmU4drjCkg4OOc5u4RVa/6Iu3gr5QJheMdEa3MRPE/WeOO8KDWrPGM+HhEfVvW8ShoK0LIIEpdAwe2gl+7lUe6ZE1uVswoEsQgBLbzerLLwva6+lbP8aXabufkWBIiYTaHUEXa98rnje6KB7f2tARwp8pySt5hgV3l3LUVbREEYVSAwdYWGT8j206k202Rxck3XfU9K033qnm6saKwL4vkMb9fhnct5EdLOphGj7O4W8RIy+iPpcOTfrKvGyZCojZYT2AML2pAdpS0lGaHtlfdFKC/Wb1wmZ1dJQfKvq87Ix7mQxaFXnfFhEHuECQitxrKXPV0Kzm0T4cux/ctf4ZGtO0GMvtzDIDJy8rBEMORYLWjl7s3dB5E2hfeWVVzBixAg0NTUJwjeCI2SvvfZCdXU1Pv/8c0yaNAk333wzysvL88VOjBjfLizLnlkKSndLDy0rcDvPIiu0vpVYJRC4C63oRMFo5dj/FhjsHlqVYMRfVG9J9qHq8cF+p0ihDbASUQbgkxgG9VCw+Lq/bdqETZ8nZCP05pJe5olmeaL+H0LTMFjPtM4+Qx2lI1AvMoFM+VDntdwooqJDCJGODdsgEF5/tjEiQicW1ZsoS5YKJVOUSlly3knDUnX7LZfO2wsXmVBIMVmQ8e2QksgADVhZeGi9srw88sw6nviwsGQZb96+SpFRjTloL9jPhfOsiLgwckW/voLLQdgc4K5XvgdPZLTOVjkRzh9SFy2fV/xbF8ppl5CA4ZNR6DzjNrX+6iwUIRAZnLOSTdiHgv7D0VY4EUIdDHxEMp8u5JiMfCjsuwrysof29ddfx2WXXeYps126dMEZZ5yBwYMHK/Ndd911AICWlha8//77+WAlRowOArHjTws61kPrc5P9JOXdikL4BUWPJgGUUgkf7qQ6qt63uFL0LfYHfW0Pcf+TsEq4vXTiOzkFPEu8H8x9hYxQ4XqC2DyW6Ds4AkzYk4ZyLuKLEL01XRpyLFmXw5AXgSqErjBHROmK3Z+VrfQTUgaTlgSeRyo1DwqfzYZcIVBWQ0QPrYqU8moKwXvduUwZ2h7xPlZ5GeIyg8+jlCVSkjQMFe4PI/BDSjnK3cdRwddFticsq2CRcLrCuQsIGmqZNgobYKq+peJF0TG4vMpTjp2/LcLfz5qbMiLWZ8V1oVJAs2KD2qIjosdus6C2lFAZLMZ4k33fo2n4ZWZDQC+ZLCpIaIxxvoVZ76nKMThZg//00IjjPUefzV2hra2txfXXXw9735yBe++9F5s2bcLEiRNx2mmnKfOeffbZSCZtJ/Enn3ySKysxYnQc3Bl4F1FooyJMyLTT6NMyqN9BwoJ9JBGEbD7QqpDz0CoPGgIrIegKnuLDQNhDoSxqRfGtqrwgTSmrgdAg7wVFM8AJlUFM1yLOucAa7SVTaNWNrVCyFQsyXapOMaorjoLlQijwCCG7E9B7rac9Bk+p5sth+eMRqlvQ8oukzgI0RDIPlz7MWKG7h1wFpXdjJwlQauMP/3d2Cm6guhVeK3kucR46lY5nVWqYoH4HogjCxpGi3aIKvtFPWM6tYwgP+nNpUxebiuvWUPwFr1LlxiDxixB9VmMOsBMwY1nES54MNIC+7SySgVsAf72UvJPs2SAg1PrNzYtZeFWZchkPrfNvjieis7yw7lSvfRV7tEWihDDk2Pt2vpOFMBYrtD6efvpp1NbWesrsvffei6KiIq28nTp1wpAhQ0AIwbx583JlJUaMDoSzYBaW7JYhxwwE4bhANAHcm7cFi4EoNCzc6h5caNwfvIfWDrmVCBgOP6YhF250q45Y7JrLH8VvPxOXz/+moQrFljkWeeHG99CGiCcRFBUtT5mGIKzyxoWWS3kYeTq6Cm1wPxOv0IayZJcT0Gi5cmgllHnuPAv7dIkAE9nzpRFeHbbHUKbkh9WViFbY4TJZe0+VNNmxGfDYZjlhWhqdTvt76HkjC3aEbRSRjraBSZSHq4qsPbTqhgz9JJmnMxAZpAoUl/RrcRUTOc+hCi2RphU9YxW94EF4unVugKsMDShPOc5i0IYZbej+TNyFnadBX9sTwQAq5UlgJIgyN0gNeIT+I2g4Uh7SFXI0cmAbBd9nJOxrG4B3I+Ss0E6aNAkA0L17d/z617+OnP/AAw8EAKxatSpXVr5VrF27FiNHjsRBBx2EsrIydOvWDUOHDsWoUaPQ3Jy/a1vee+89nHfeeejXrx+KiorQr18/nHfeeXjvvfe0aaTTaTz55JM48cQT0bNnT5SUlGD//ffHiBEjsGjRorzx+j8N2kPbgdf2EH6F087n//b361hcGj2ixNHtebo+feedYkHz12x/4g94nNxTjg32lGOLWUAEvFE8iE8dVphJmZLYdHR1SQ+FYpQLvn55PtR1rhQwNdvflAQkKQVblYdWp48EBBVJOQL5hLHCB9Lrd3raM61jgVeFAyoKESfWVZilvMj5Eubh00u+RfU9iqhWNY+a9abyimt7T5UxkSytqJ4yP51YqNftx7rvtbybMgWQ8lpFPZnWn6+yUFACylfU/DaB0H22MtYkhljAvX/ZXUtEihHnoZVuohWEdefgwdPVZ+llndlDyxsPmHU8vHzhEizRCoLzbTh9YUavbMU6YgWNeCIPJbNfnJrDsr1a1cr4jZnVHlrRM8HcKp+H1HXigmlaLjIhQGEPUljDkPOhUEuXLoVhGDjxxBNRWFgYOX/Xrl0BIHAq8q6Md955B5dddhnq6/27DJubmzFr1izMmjULzzzzDCZOnIhBgwZlXYZlWbjhhhswbtw45vmGDRuwYcMGvPXWW7juuuvw1FNPwTTldolt27bhzDPPxNdff808X7VqFZ5++mk8//zzePzxx739zDGyBLF8hTbd1oF8OP9EncTo9BLvqrZgRqejQr088s5JRcyBTGE0heXYPwpN7pRjnX2nCqunKLdIOLAscBHAtPItDiGi6zQgeJFgGtW3iKzJ9nPn6iJo6B8ypTgsn4xcxNBanX5qCwTBhKx3nEofQo/bGa4l/Oh4GlXfwh4+Fp7efu8nMEymo2nRCl5fSGDpnH6to9hq0ghTsD26jPCqzw+TTJEus2ExyIHDqLRZ9vCA0hbeB5TXiMmKiSKRc9YGXsiPVG42nrbAOLD/FiksOodChW1nlfHo2TtFdUfYfah0efZrfo3is6vrRVZtYUpg1P3AzD20kvk/CoTzhmSUB9Pmpil5B5AJy1Jc3kTECq1FX92W5fjOiNaRfCqEIgsF/VoofAQZEYcci2mERVbEh0JR2LFjBwCgV69eWeXPZDI2IwqlbFfC3LlzcfHFF6O+vh7l5eV44IEH8OWXX+KTTz7B9ddfDwBYtmwZzjrrLDQ0NGRdzm9/+1tPmT3iiCPwyiuvYObMmXjllVdwxBFHAACeeeYZ3HPPPVIamUwG5513nqfM/vSnP8V7772Hr776Cn//+9/Rq1cvtLW1YcSIEZE8vjEEcN2SBcUgqdaOZSNPRIIhx2GLL63QKfjh9nyIIbCEe9ZXVnMuZDy0Youo984RdsT3xEaV/lhLvpUJUlEJvFIeqRd8Gh2FghAEwqGliHBtj9hLKRZmVcQMWZiYLBsJrzfb86hIwDDg14wJS0v4ESYJERxkYcKe4SNUSBYLMIwc644J1XVJGoJvqNIVIQRTyAOFfN9nqSrLK/O5K4Eln0jntqwVAsE2gzBeAjSE40ojnwbTQaOkngIVjX+XH/6FPK2KjuqzVHO756ENKVd41y6fJ8pWDCJvibD5kZ3X5POr+4YxopJge+msLwAd7aQxsbnIYi2z32lq+zxtbg8t/Y2+wVhT+Va0JzO3MiFbLi39wSA7ZJJ/7m8fJgx/QsOtQJaiFXm/KZ2+YvFl6Y35PQE5e2g7d+6M7du3o7GxMav8GzZsAGCHLO8OuP3229HS0oJkMokPP/wQxx57rPfuhz/8IQ444ADcddddWLZsGR5++GH84Q9/iFzGsmXL8Le//Q0AcNRRR2HKlCkoKSkBAAwdOhRnn302TjrpJMyaNQujRo3CNddcI/QGP//885g2bRoA4Oabb8YTTzzhvTv66KNxxhln4Mgjj0R9fT1uu+02VFZWeod0xYgKAvuU4+IODTnOFsx+IllIsObEZ9MyHRrB98IJWqK4CS2uzOoe3ENrKQUM+19TS6mmeQ6uiPyJk/ShUD4/8sUlk2Erh/bwitKrwCo5ennO73Ymykk2hkQ5/aihXkpWIwr60fRZO1HSSAf6uVhJCxLN7q5QilSOShRNQ0egtceGzCAgGWthvEgVZFUmbfKRILtv0X5ngqybC0L2c/6WC+fqMqL9HZW+C62+FZgzjcDjqN+Zi3AbENoF36D00HLGxqhQeWjtNUEcNQOwCoKYObcQPYXFe5drfQfGJLu2BA4W1BxcwegN+qWMFTltLUMFh4zUEmJ/L7OHFuI6tngPrZwNLYjEjFwVPrqVZDRDtskCEG9pEuUN0Ajrg9muY7sgcnaL7r333sj2UKdUKoXp06fDMIzQK352BcycORNTp04FAFx77bWMMuti5MiRGDJkCADg0UcfRSqVCqQJw5gxY5BOpwEAjz32mKfMuigtLcVjjz0GwN4fO3r0aCEdVynu1q0bRo0aFXg/aNAg3H333QCAFStW4M0334zMawwHttkQRkEx0IEe2mxDjpn0/F5VUZoQHlT7ZL3QL8+7IZGyA0xQ6am/+XtobWtuiIDh7TtRl8jzzNOSeeFE911SehTLC/c3ETwTQXaoFiG+YqkS006sGIr9cKT4paJgpdIkESYZaO6h9dMQtt48Oiwfut4lus2SRjrrkOMwuYE1dgjSRRB2OWcF9dsZE5pCCZFotPqCNftYpnyQwFiNUFaO6cX8gNkKEhx7mvXHKxABRUP8vVEV/Cz0WXGayHXttlvutCLvoeX+laaTGQ1U7+k1SaFIuZCF3Ub1Ooch7DA2/hG/t9RPJ2g31eQv2RKjQmC+08wrNc54/UMwZpR33tJKPbeWeP1X/8OkB+5l07CSvueV5T6KENlhCAQygzascAdcBo3oElYVY313Rc4K7cknnwwAWLRoEebPnx8p77PPPuvtQ/3hD3+YKys7HW+99Zb3++qrrxamMU0TV1xxBQD7SqPJkydHKoMQggkTJgAADjroIAwbNkyYbtiwYd6BWhMmTAgM4GXLlqGyshIAcNFFF6G0tFRI56qrrvJ+xwptDnC1mw5WaH35KodZSmItjBS6ItmHC/jeTpXAw6/FwnWGWMgQk1FoCYjSu2FxXoAwgULKEIJKBK1Q+SFR1CIETgmV8KkOOQ5XBt2FPUtHh5S2/0zOnyifUrBVKc7Mb4HyTvcJK/o+RcDx0HL5RN54oWIWIYJBFGGQteAu6B+q9qLfScewrhwXtVMJ+0PwYbbXArF05ektmEAm5Ss9efJKBIIyclB4CNefdcEHH/L7CqPwko2nzU/AphOPR3lDq+pQWJCEsrhviMaMWDECVP1RMDeo2ipKfavGiqBu7HlenldrSAnqSrqHVlPJFOQUPlXJEwQCRTOow3EKrWItV85pPg1nB6TDn4SWAmF2eZ6m+69/bY+8IRkDJ30PbZiH9n8IOceX/vznP8eYMWMAADfeeCMmT56sdW3PwoULcdddd9lMJJO47LLLcmVlp8MN3y0rK8ORR0o8GwBOOukk7/cXX3yB008/XbuM1atXY+PGjQE6snKWLl2KDRs2YM2aNdh3330DvIbR6d27NwYPHoxly5bhiy++0OYzBodl62H+exvI9fUAOk6hTc6fheHfjMSGwb8D0F87HyHA4MbluL5qPBpSF2G/lW9j+2eXY3CjPcNfXzUexuxuwAliAwsAdFo2D6Mq78aqtfeguNbA4d+MAmY/CvyAzTOoYRmuXPEMGqaNwKjKp7Ck6jcgZF+v/B19LsbgzW9geLoOxf+9E6Mqn8CLg69H5xWtGFX5O9SvuB/AAKCaIDEDGHDoOi9vJ6MIyX/fiIqWvTCq8jd4tc9PcfGmNzC2/zW4vmo8knP/AZx+PHpvWIRRlX9BeulfgNP6AgC6rJyPUZW/wxd7X4bhG/+Lk9M7gFm9gKOOQo91CzGq8k9YU7IPPupxqk1r3uPosXYrRlX+EdUFPVA+6SKMqvwHJna5BT2rOmNU5QNYMm8EBjemcH3VeHRur0Nizsser2WTbgCO/YVXL3b5v0dlnytwZuULmNn5SJRXml76lYN+gyNrv8IPtn2Ct3oNx/nL3gVmPQMcdRTTftZnV+A787fjkhVf4/OKw3Dyto9RXdDD+xYA+F7bDvRsWIhhKx/Bwr0vxnXrn8fY/tfglG2fYL+Wtahe/UcA+wfa+HttOzB862z8ePsUzO10KDCrJwY3LkdFuhYXb3oDyTfuAO6wjX1em0y6HqMqx3ptUE2AXls+xyt9LkJpZRI4Tjw/llZ+g1GVd2PKPr8EcJhHr+WLyzCq8iX8a+AVOKBmEY6um432pQ+iqLEUoyrvxrtdfgHgRGk/3WfrEvSu3oJRy+/GttKuMOYN8GhjVi/sX7cUd1c+hZpkZ/y3z/m4vmo8KvcbAeA7zHeZc/4JnHIc27cbV6As3YjLNr2Kfw+6ApeseAH1iXKULbvH62d9vpmMUZVj8e7A8wHI72p3+8OsiiPQd94g9F6/GN9pWITpOAdnr5yOt/f6CUYseRaY1R2dllVjVOXdWLfmdxjcuAHXV43Hovm3YXBjI0ZUjkOqpQr/qjgIRQt+hNK6doyqvBuv9vkpvr/9C/Rp34KPe9+G4kVNVH0fw/DSfe0CjKq8D+/1ORPrk71xfdV4lGSa8VrRLbi1cjze7nkWzt460etjxQvnYlTl3Xih+A50a6zH9VXjMbf8EBzRuAglE28DvnstQ/+gLXNwZ+WLeKvXcJxb/Q5KMs14c6+z8eNtH2NazxsADGXq3prZE4lj7GffqVuAKza+jI1dz8LgVbMxsdeZuL5qPMb2vwaAPXd1XVELHL4WXVrmY1Tlvdi28o8A9vPKr1gxH6Mqf+v10dpEOV7re5HXJ9xxQ4+zkkwz1k6/DbjmAI+3G5c9i0ldT8GBTcswsGUd5nY6DPtNPxS49k4MbFqDQpIK0nTyDmxeg9O2f4o3e52N0pVsOf8YMAJXr3/R468k04x/4WbcVfkc3ux7Hs7b+CaeqDgUl279DMnpgzCq8W7M63QoShYVeXQ+6HEqzlz6CTCrm1e2V/8Nlbh2/QtIvnkHMPJqFMyfjXuX3Y9X+l6M66vGoyDThlVrHwAw2G8DGCjLNGHS3ncDGObM/79B1ZrfAxiMPl+8i7tWTMBbvc/BDevGodhqwetFv8Ctlc9iQq+zcEjDYgxqWY25nQ7D0NrZSM59Ctj7RHReswiDG9fg+qrxmNfpEBzesAgrSvbFyrL98aNtH6N+2i8wqvIJLOh0CGZ0Ocarj4l9h+OHWz5B8pvHgAHfZ+ov8eo9OGj1FlxT+S9U7nMNgMMBAMdv/xLnVr+Dzwccz9RH302LMaryIXxdcQSG1s/Fh20/xemr3sDUgotQ2FCCn1S/h3f2+gluWDcOH+51GkBOY+YQun73bVqNApLG9VXjsbj0HJRtJ6gp7IJr1r+AxNwngNNPAAAUL5yLIQ2VuGb9C3i/xyn48bZPUPzO7cDB16Db6gUYVfkH7FjxJxyzeTZOWz0BH5Vdi6KFbRhVeTdeN67BnZXj8VXRhSCNnXB91Xh81POHOG3rp/i8y/E4qfYLhq8+GxdhVOVfkah8CDjhR8y3H7XlC/xopb9muvnKltjr+5t7nY3D6+ehZf3P4M6JnZbNw4OV9+DZ/ld6edz6SH92BXDhSGb8pmFi46zrMaryKXzW7US0mUVYV7IPOqXrccmm/6Jt8i3Yd4eFC1a9gb5tmzFj0EgULmjEqMq78e9DbkCfrWW4rHI0lnfZF6Nq78bcToejy7urYfTZH6Mq78bkztfi+DWfOv3rcGwq7YMzt7yPl/tcFGifwY3LkEy14soNL6Ng/qM4Yds0nLN1Il4bdAUuXPECJu99BzMfut8wq9PhOKZuDvDCNsBxYgHA92rn4GebXsPKkoGoS3ZGU2YgKpY3YlTlPZjb80qcX/k81s++CqMqn8NHvW4DcBz6bl6MUZUPo3Dx34BjTsN36hegzSzG9VXj8cneP8IpGz5Act6jwH4/AAD02FCJwY2bcX3VeGzqdxFOqfwP1s26FqMqx+HL/X4FYKjH57riUzG88mO81/N09G3diCGNlcCsXihfug2jKu/G5/2D8/1uC5IHnH/++cQwDGKaJjn++OPJggULCCGE3HLLLd5zF83NzeSxxx4jnTt39t7dfPPN+WBjp6NHjx4EADn88MOV6Xbs2OHazsiFF14YqYx33nnHyzt69Ghl2kceecRLO3HiRObdyJEjvXdz585V0jn77LMJAGIYBmlsbNTmta6ujgAgdXV12nn2VFhnDSUEINYZR5D07w/qMD6aLr+JEICsOebqSPk2b2omb+w1nBCAbC0/gBCA7Bh4OHljr+He8/abblHSWHf21YQAZN6Jl5HF+19GCEBSI4J53t77bJvH/Y8mBCBzjr+UrF/X6JdfNtiN0iNtQw4lBCAT+p1LVvz4SkIAsuKMq4hlWSRziJ0mMxhe3iazmKQOPYys+YnNy7QuwwgB9f46e66ZfezPCQHIunOu8fhy6c/qeqxXPrntNkIIIYtOvtzmubi/R6v+qptI5Q/t55sKe5Ftg79HCEA+Gnw+mXfCpYQAZMa+p3vp25Akzdff7OcfdChTL8tOv4IQgCzpexQhAPmm06Gk6txrvfTz9v45+bKLXWezKw5n+Nta3eKlqxkwhCzrfCBpKOxFvnDSbyrs5aUlhJDHOw0i8/a26+DNXmd5dbS6ZB+bh9OuDLTb+k3byeOdBnk0l5buT9K33k7e2Gs4+aDHDwkBSN0hR3npve/c/xCmDaoLuhECkIk9TyMbL7hO3icvvI4QgEw57CKyZbPfP3f0P4gQgEzqeTqZ18mmvfbsa0jNZTd49a/CZ4dcQOb0PMxu/5K+ZOM1v/Rok9tuI5MGnmv3w4Ju3vM5A38Q+K6WG37B0K3Z0Ur+0/tc8km379v89TqdEIBsT3Zh+tmiAccTApCvug1V8rnsR1fa7V5+CNncezCpLLPH5bwuh5M1Jf0ZntcMt/v7wpMv955PHnyunwYg7xfvRbZfOoJsPP9aQgDyedfjyIai3nbagy8kWy7y65vHwpMu8/odTfOTvqd5PNL9cdvP7LZ45sCb/HZLdrbrdcjRAfpT9jrJpt/pcI/2orIDCQHI1H1OC9R95pZbvWcfdD/ZHptdBpFlpfuSN/YaTiynv7npm80iYp1xBFl6mj3Glp5+JVP+qjOvYvrouqK+TP26aKhvZ75/1UD7W9aubvCeLy/Zl6wp7kcIQBaUDyHb9j6IpFMZMm7vy4Q0VyyrI2/sNdwbV7Mqvkvm/eRmppx3e/6I4Y8A5MM+dv+a0cWeLz4vH2Lz5IzhReUHkupLbmD44st28U7PHxMCkFpn/NZePoLsSHb25y4jSRaefDnTBk1mMbEA8vmhtozjzrmLnHRVA48gVcV9GZ4n9zmFEIDM7XQoWVkywO6z5QeRdiNB6q++iRBCyNzT/DlvYbndB1aWDPT4XzHoBEIAsrhsMNsWpQPtOejKGxk+CUCaD/0emdP7GLtN+h9HCCFk44YmMqfTd+w+3/1Ypj5mDr3EaT97rvmqqzMn9zyKvNXrLLKqZIBfr6X7kuamlLBtq7c0kxf6XuK9W999EJldcTh5q9eZzHpECCHbf36D93xJ6SB77jjY7l+Vp9jrzLIfXUnmd7F5/mzv07xx9n4fu/0W9/yuV9aKkoHMvzRfXx/zM0IAsuH84Pw7p+sRbF9z8lWde409v3b/AVlesi+ZdezPvTzrzrmGtBtJJo837gcM8dK5zxrNErJ4X3senNH5KLK8xB63U5y1d/Xg48hHB/yUrHfmpy+OuJjUXD7CHgsDziVTv3Mh0z8WlA8hTQccQtafZ89tU/ud4vWvBeVDyAJnbEzseVqg/7/V52yv/2+74iZvLnvPmb8/P5SdD91v2FzY0/5WSh9obGwnn3U93umzA8j88iFkcddDyUpnfpm3t/19K/sfSQhAPh1yASGEkC+PuJgQgGy68HpCCCEf9Pih37/K7b5Qe8WNXjlfHH+V935Lb1teWjrA7t/Tvnsxw+fG8v7efL+w/CBSk6wg5LbbyPrz7Pb8/DvB+X5XQhQ9Iy8KbU1NDRkyZIinoJqmSQ499FCy//77e8/OPfdcMmzYMFJcXExM0ySGYRDDMMiRRx5JWltb88HGTkVLSwtxFcSzzjorNH1ZWRkBQIYNGxapnH/+859eOa+99poy7WuvvealffLJJ5l3F198sfdu69atSjq/+MUvvLRLlizR5vV/XqFds4aQWbMImT2bWJ1LCQGI1bmUpK/uYz9fs+Zb5yPTzZ5kW8u6EzJ7djgf06YR8uKLpO6PozyBMwPD+dckjUYRqUuU2393qiBk9GhC3nnHp0mV3dapiy08lFSQ5kJbabG6OXy8847937vvkvqkTa/NLLTTF5aTzZfd7JVvOeXbv+EIT0WkpbSCEIC0lFQQ674/EavASZPwheW0k6e1qMwTugjgfUO6UwUhY8aQ5mKbVlunLoSMGUPIr35FWorLHeG32CufFBURcumlpKXI4RlJv6ySUtLilNOOBEnBJAQgDcky0pKwv21zsjtVryCZZJI0w36XMUy77D/9iZC//pW0lnSy286plyazhLQXlZBmFNh8JStIQ8LuZ62G/YyUlhIyciTZ8Zv7qfoDaYdB0jBJo1li82ck7W+57jpCfvITUocEaU7adVBvlnp11GrYZbcUd/Lbeto0QsaNI9tuvIVsNwpIQ6LMEXILSCpZQJpRQOqcZ2kjQchNNxFy3XWkNtGJaUO3DVJI2At0soK0F5fZdeD2Kao/tXftYQs/RZ3ItvvHMN9nC0XFpNkosuujqJykiu1vrS+sCPb9NWsIGTeOkJEjSXOyhDQlnHpBkuwo7eHxSoqLSa1TLykkPJ5bjEJCzj2XkF/9ym/PHj39vv3Xv5Kmu+8ltWap1+dqkzbNlJEg7YXFhNx4IyEjR5IW532zWUTISy8R8uKLdh27fL7zDiEvvURaSjt7fTgDkBanzVuNArKhqLfHBykrI21Fdhu2FHUijU6drC3s46cBSD0SJJUsIO3O+Go2i0mbkbTbJtmJtCftfA1FFeyYHTfOGy/NZpHXX+g2bXfokE6dCBkzxmuL6mSXQLu1wyTk4osJufVWQn73O0LGjPH7NZIebZdmg1lCyMiRhNx3n0+rS1dC7ruPkJEj7fewla6tyS6k0bDrqy5RzpRtJUzSUmj305byroS8+65d9+PHk7ZS+zvcflCd7OrXXVGR3fYXXECabhnJ1Gk7EoTceCPZ+PObmXHe5nxHi1FELICkfvxjsrpobz9v1672+Lr1VlJ7wRWkySjy6qANSVJd1IMpp9HtU24/BUiT084tzph1684dw81mMWkvKvHqJ+POaV2dbx83zubhpZf8Pm8mCfnZz0gqWRiovzYjScigQR4PaRjEAkiLWUTIxReTVmd+bi7pTMj115N2mGRLQTeG53pv7kgydZQBSLrQrufaogqvXzWbRd43ufy3eN/nr03096UKbDp0/WVcPt38F1xA6n5yIWlzxlR9ooxYv/oVIZdeSsgFF5DmwnJmnnXHdCsKSDMKyXpq/GVgkLZLfk4aDWfd6NWLkPHjCbnuOlJ3wRVkbVFfbm7259x0Wbld5nXXkVRxCalx0rlzZAoJQkaOJK2FNu224nKK53KSKrbpNDlrSjtMai00/PEGEKukxFbmXnqJNJZ2tel16WGP9WeescfiyJFeu3j1V1BAyLBhpK2wxF8nkCStyWKb99tuI+1l5aQdCb+ty8pYeWLkSEJuvJHUmWWB9mhIlBILIM0oIC3Od7QZSdJsFnrf2lDUmaScMVqXKCPNCbs+XBqucaU9WeCNhVZ33TQKvbmkNllBSHk5Ib/6lT3/jBlD6pLlpM5pj9biMm9OdOfv5oJSQm6+2Z6/L7kkICcRgJALLiDk3HNJ23EneGtuq1Folw2QdtPt6wXe2kkAUlfYmZAxY0hTsV1We3EZITfeSBrNkkA7pkrKCPn97wm57z6yvbhHQF5y+W5JFhNy/fVUftObQ1qQJCmAkMJC0lZst0V9cRc9WbGD8K0rtIQQsnnzZnLyySd7iqqr2PL/ue8NwyCnnHIK2b59e75Y2Kmorq4mrtJ38cUXh6bv1asXAUAOPfTQ0LQ0HnroIa+c9957T5l20qRJXtq//e1vzLszzzzTe9fS0qKkc9ddd3lpZ82aJU3X2tpK6urqvP+qqqq0O9oeCXcygy+sWdQzgrwNrwh8GMy/oXzofIPq20LSymiJ3unkkb3XpaXDj275Yemy5UVFX+edbp3l2m5Reci1nbP+vtmzs6qrbNonSrsH8nN8Rh6PWaTZad+SZRrdZ1HTR/3ebOo91/aI0t/z0aZR2jdf9ZCvuVOHhs635GPNyWdfysd42lljMp9t921+a7ZtlW2Z+a7/ncWHch2aPZuQpqZvR34NQRSFNm+Xv+6111745JNP8Pzzz+O73/0uCCHC/wBgyJAheO655/Dhhx+iW7du+WJhp6K11d8XWVhYGJre3Ufc0tKy08qh9yrz5eSLDo0HH3wQnTt39v7r319/j+YeiZdeApxrjtwt+t5W/WTSfv+t80GYf0P5uOkm72fgGzh4z03Tp0mVLUrL5OHumubLCStfli8KLeXBjxHL1z3HJiovKvo671Q0w6DzbdnyEKUM0fusv09w3kEu/SDXfiLNz/GpPR41eAh7n/dvyTKN7rOo6aPwoqKXzXPdNFH6u04ZUfLnMl/qPleVk036fMwf+Vhz8tmX8jGedtaYzGfbReVhZ83FO6PMfNf/zuJDuQ4deSSwZImCu10TeVNoAcAwDFx++eWYM2cONm7ciNdffx2PPfYY7r//fowePRovv/wyVq5ciUWLFuGKK66Aaea1+J2K4uJi73d7e7sipY22NvuKAP7KnXyW45YhKidfdGjcfffdqKur8/6rqqpS0t3jcemlwFdfid999ZX9flfn4x//iK54f/21T1NVNp/n66+jlfO/gvvu62gO5HjpJWD27J1vnHHLyWdZNM2d+Q0vvZQb7fvu+3b4jIpcvysM993X8X0/Svk7g9eO/P6XXur4+t/VcMEF+aNFGYt3efwv9oWo3xvWN/LZdzoC/Hp50EEdzVFk5HzKsQy9e/fGeeedt7PIf+vo1KmT97uxsTE0fVNTEwCgvLx8p5XjliEqh6dDK7hR6NAoKirSOsH6fxHEAAwCEMOA4UQjZGthz40PEwaxQGDACLszgIMFA6ZzQYoBeP9asC1f7t/ysu1vB+CV7/LDlsPSc//myw/Qd/ly65hKJ+M98A1cXpZnNo+obFFZsveQpJfVp4x3Vd3BMOxAIQlfqrbj+RHWwZAhwPe+p+ZBWrb6u5l6EpTjto2qf4jqyqMroMl/u4gX3fb1+rZz7zhfP7L+HOB5332FfMr6g7D+BHxCkkaUXvT99Hd541lCX/aNojTMd3tpgn1K2TamCcO5p0fWz0TfHxj3Dg/KenDhpJXVaVbtoagDET1VGWHzR2DOoNpXPveHj2uPvje3sn0lytiS1UXYmBfVh7TtBbS8tD17KsvXmd9gmvYdUn37BupX9n18OlW54noN9nkl74YBkxB/HDBjXV1/qj4Y1tb0e531J2xc6q7ZQt6ZsSfiy37m8ef1DYmcIuk7Ip5kZWjNmyHvZesPXc/COlGsl7sLdh8XaQejuLgY3bt3BwCsX79embampsZTEqOG5fbr18/7HVYO7SHly8mGjmEYTL4YGujVC+jdG9ivN6wzegIHDQQpAdCtS4fwkT7ku/j8gN+jrs93bL569QrPO3gwiGFiWdkgjB54C9oTJWhLlCFtFIIAWFUyEKMH3oJMstCetHmaTtn1gw7D2H5XIWMmsL3sAHx+wO+ROewInw8n3dryfdFklqK+pDtGD7wF23rshwz88tNmMdoTpagu6A4CoMUoQhomaors9DX9h4AYBtANaDmwAMSAl7e2sDcIgLpkBUYPvAWbC3vBor4hNeggwDSxrfdgjB54C+r2/479Td27o6aoG0YPvAXVhXuhLVGG6oLuQCIBGAa2FfW0v43is62gBBYMjO13FeoSnUCc32tKBiBjJNCCAhD4vGWQAAGwvqi3zUtxmS38fPe7QO/eqO1/EJrMUtQmO2P0wFuwtrg/LBhIw0CLUYSMkUBVyb4YPfAW1Cc6odksAQ47DOjWDRkzQZVjL80ZGFjnpG9IlNuh4d26Ad26IQUD28sGoy1RhtXFA9FsFCONBKqK+2H0wFuwvagH29a9eiHTpQvaYWCVk6Y+0QkEQBoGVpbuZ9eJWWwLzN26+e1ZVOK1QZNZivpEKUYPvAUrS/eFlUgE+5TTT5oOPByjB96CTd0GIWMm/e8rKILllLumZB+7HZMVIImEXf9dB4v7fq9eQLduIAC2FPd06qUMGRhYVjYIY/tdBSQSWO30lRbTrpOx/a7ClkKHVvfuHh+pw77L9G2rS1cQAJsL90KTWYo1JQNs/gt7w0okgS5dAMPA9pK9nH7W027/wYODfPbsibrCrl4/IAB2JLtg9MBbsCPZBSnY7f3ogJuARAJWIomx/a7C9qLuSMNEC4qQMuw6e2Kf67AmUYoUDFiwBRu7f5hYX7Q3Rg+8BetK+sEyTYztdxXW9zwoMGa39hnslN0VaSTwcu8L7b5cbOevTXZGk1kKcpA9vloPOARv9jyL6f8WTFjOeIZh2N89eDBgmthU3NfudwVd0WwUw4KBJqefbCjtZ6en6t767veA7t0Bw/D6bH3S7o9ri/t5/dlNT5xv3uHMIdsHHGp/42C7r9QNOAjNZrHXD1KGnxeA3XaDB8Pq6vdre26xRcx0F/v5EwNuAAG8eWFNyT5e2e1GgU8zmbT7/eDBSHfuAgJgY1Efe35LdvH6pFtO2qk7/hkBsLWgB0YPvAVbk11gAd78saZkH2f+sNu11SxCU6LUnjPc9h08GMQ0vfmxtaQzAKCtdz80Jkr9vm4kPRXGfbaxqDcyMJCBCRgG6gYcbM/nfez+3FJQhoZEGZaVDcL4vS9HBgY2ON/YmChj6igDA8RM2HVpJr25YnuBPSdXFe3t1CtQU2CPg60FPbzx6a4VzUYxWvfZHzD8+nPf7XDybSvZC3DapMYZU1XFNn0cfTTQsye2FvWyy092QZNZii2FPb1+nobhjb8xA29Gq1nk9bvRA2+xwzV79wa++11kDJNpd7cvrC521iOjwO5b3brBSiSxvHR/b15qMkvRWlwBAKjtvb835tz2dXl+ufeFWFfc3xnb/ne3mCVoMkvRaJba5e6/v93nevbElr52WzUMZvsCDAMNpl2211dNu32bzRJn3t7Pbi93XPTsiYaBQ9Do5Bnb7yqmn6QKS+3x26WL9z4DA/WJThg98BasLhno1Ytbz3XO2rKp0F4rNxT3BXHmOLf8FrPYaz96nL3Z8yxkYKI22dkrq8UswuiBt2BFqXMVXbdu9vf27Im0kcCK0mD9riodCAvAls4D7Do6+mjmu9oc+QiFhXYdHX00iGGgurCXPacW9/fGrQWg2SzG9qLu9hpYZPO9rssBgGliS88DMHrgLWgaYI+dNC0PIYFmsxitgw+x269bN6TNAmZsNpmlqC3uhiazFFsr+jF8tpjFaDJLsZbiBwAaCp1+1ONAfVlxF4dB3I2tMULx/e9/H1OnTkVZWRlqa2uRFOwdBIDp06fjuOPs+wl///vf449//KN2GatWrcL++9uDbsSIEXjyySelaUeMGIGnn37ay0ffQzt+/Hhce619198rr7yCSy65RErnwAMPxLJly7DPPvtg7dq12rzW19ejc+fOqKurQ0VFhXa+PQ5tbbDeuQdk3gSY5zwA68mLYD5WC8MRDr5NPjYvT+PNW9Zg3+PL8ePf9wY0PeobF2/CFVfPAQwDl+43EO3r27D3paV4+un5aE7aC9J/3zoBXboWiWm2teHDj6rx0P0LcN45vdF1fhnqNqXx85cGoXNP+Hna2vDT4Z+jpbYFl904BM8+vQJnDO+HC87ojGtvWggYBs4v7I920op32qsxdvxQ3Hz1dBQUGrhyxEH45xMrcMMtB+LCH5fB+k0fTKk9Ad/vNA0/WvguYBg4raAPrnxqL8yZ34BHxqwELAulViuaEyWAYWD8Kydin+4Ef39yLd5+owp33HUIfnJWbwDA6/9Zi38+sQIHmp1wWLIcr7VtxMefnwK0t+PZF6vwrxfXoiDTjpRZABgG/vn0UMz5chPGPrceiUwKd//uUNz/56Xo378Exx7TFW/+Zy1OO74Mk75sAwwDpekU/jl6X1z5f1WAYeDX9xyK077fBaioANra8OqrVXju8UU48vi9MGP6DoAQ3DVyX4wetQwwDJxb1B9fpuuwgbQgkUmhuNjAhCnDgfZ2bFlXh0sv+xowDFx/RV9880UVNqxIAmYRNpJWJDIpfDD1R3BvYe90wM/w0L5/gklSeK11AwpgnxHqftvlVw7Eldfsz7T1ulUbcMgPbsXBe52BTom9kcik8PbrR+Pc87/y8j3xzyNx4P4lQFERTv3+x4Bh4Dd/+A7G3PMVmhMlKCBpfFPzOQ7pfipgWbj3j4fgxB/2DfaptjbM+LoW9/zfbBz23a74vzv2wxVXzgIMA1deuz9ee2oBkuWFqG+xDQ533LwPBh3SA7f8Yg727leC5/91nLSf/uYXU9F9w1t4r+ZMfKd4Hm7804X4xZ1LAcPAx5/9ED87fyq2bk8hmWmHASCVKMRpp/XCr+8czHzXC699H317FXjlbN9Qh6vP/tD+TmTQqXsJdtSkAUJw552D8aPh+wBtbRj9+GpMfHsDiosMvPvO8Xb7C/h85aXVGDd2FUAIzvtRF0x4fzssM4mBA0qwZeV2tCRKYCYMfPjpD/He2+vw8CMrcOFF/fDWK6sAw8AZP+mLtydWI1Fg4LOqZ9GnYG+88fTtaG438MhvpqPFLEYqUQgYBgb1L8C1vzgId/+/BTjsu13xyKPfY8bsU0+txGsvr0FJMoN0WwapRCEq2mrRbXAfrFnbAlgWCpDBu18OR6K5EfNXpPCrm79C3+ImbGxxBNp0GqVoxz1/G4ajv1fhf3d9Pa64ahY2bmz16IAQWATIJAtxxJHdMOrBg5m6f+ujU1FeSIC2Npx66hTANHHKab0x+52FqC3qjgKSZvrzn/vejSOP6YNXu43B+HGrcPk1++PKKwfa39jWhrcmbMRTf5uPlJEEDIMZ5x+/fRTQuTNQVITazfW44Jypnpfzogv64IYRg7Cqqg03XDMTJaVJpBuakSAZtBaUAoTg4ov64oqL+uDcn87waX72Q5tGURGWz6/GyKs/R0ui2FbqLAsjLumGp16t8copyLSjABlvHgMh6NkFaNtaj5bSzkilgVV1M1HX9A3GfS+Fxzf/AiAED953EH7/2wV2O1sWSgstvD3VnjPc9s3U1OFHP5oKmCb+/tQxOLivheXbC3DbFZ979QHLwmUX9MBVP++HU8+f5/NlpTDk0M545NEjMfGTGoz+6yJcfNm+uP7iHnj2v9vxn2eX2jQAFFgp9B1QjrXr25FItyNJMmgrKPHoPP7scdh/n2K88PwavPBSFQpIGhli2MYgqg6uvO0w/PMfK2BaaSSIZX8bIehUlEFrK8HDz5yIgwcmceppfju98OTBeGjMaixc2ooTvt8Lf7hnMNavqsFVNywATBMHlyzCo38/DsZ3jgfa2vDQnxdh8ntVSCGBAmTQuUcJtu1IY/+BxVi3sh5JkkaL2xaWhbf+/T2c+7O5dttOP8Or381Lt+Dqy6Z77X7EfhZWLq5DfVEXwDDw3Ljvod+grgCARfO24/ZbbRrIZFBgWPjLP47D4QOAF96qwQvjVuC6S3vjzfe2Y/uOFPbdtxS33bgPfvnrJejatQBtW+vQ/4AuWLrKXm8SBoGZSSNFTFRkGvGvaRegJGGrM38btQTvv7sBv/3T4Tj5pB7+WK+vx88v+RI129q8tv/4sx8C7e34+MNN+MvfVnptcdopPfCrP9lK3ocfV2P0H+f4eT44HqeePs2bry+/uA8zfgsy7ThzeF9MmLQNIASlqSYkSRr1BRWAaeLWG/rj80mrMb/Knt+PPKIzrh2xP26+cQ46dUrgkANKMHtWDb5f8Rk+aTwNIAR/+t1gpFJp3PfX1RiyfxFWLK1HKlmEonQLTAN2exGCjz88ASgu9sb+uad9gMY2u5xH7tsfv/rtcsA00alTEpmaeuzznd54/MmhdvqtW3HqT2Z681mF1YQ3Zl0MNDYCFRWor9qGC386DRmnTxZYKezdzcLwnx2IJ/+xAocO7YWFX1fj1OED8N7Ejdhv/3I8/c/v4g8PLMO0z6tx75+PwInfSeKMM6Z5c3O30gwaGi08PO5EHDy4DADw94cW4O13twCGgR//eC98Mmk9Tjt3ID56aw0OPrIXHv7TII/PYUM7Y/ZX25AykiiwUgAheG/S8Zg8qwUP/GkRhhzSGY/94yhtWfHbRhQ9I/bQRsAJJ9gXYDc1NWH27NnSdJ9//rn3+/jjj5emE2HfffdFXydUhaYjwpQpUwAAe++9NwYOHCjkNYzO5s2bsWzZsqx4jeHAnQgMAygsARIAUq3KLDuND0dhITCiTVAVFV5eJE1YZiGsgmI0F5T5NAslyixXdiZZCCRMhw+weYqKYJgmUmYBmKDsrt398k0TGdOezElRMVJmAdKJQpBkgf9tnToBBtBGiuyNE25ewwDp0gWkuMSj5SrkHj/Ut3r8FRUBBQ59w4DllI/iYqCiAiRhC2XuImPXRyFIqb3AZBIFSBcVO/lNZJKFSJkFaCn3v8tKFoEM2N//G6Yv1BcVgcCw68XxVMAwkCnphFTCpmUlqDpOFCDl8lhUBJR38vkq74Tmsu7IcOm9RbyoCO2mLXhYpm1dTpkF7LclksG2pvK5NEmvXlydFNnfxPRFvw1SZoF/OJhpwiosFvcpKj8Mt739/tGcLEU6Uew/61QBy6Oj6PtFRUgV+7SMhAGrO9X3iouBpOMpShTa3+bWR+C72HJIYZE9Xpz6NBJUOxY431lRAeIuu4YpVmbd73f6OwwDqbIKWKbdB4mZQIvbp50+mil0+l6ywOsv6YJipg7bEwUgZeUgRcWoL+yMVJL6lpISu+3c+ubGrBvsZjn0AdhCufuN3piG8402Ggo7U/NKEs3JUpDCQva7KyqYPuH2xUyy0OeHq3uvjam8xDBQW9zD62d0v7SKCoBORSCOEdoi1DdSY89NT+dFr15MWrpO08lihjcCIJUsspVZJ00mWQz07MnSLPb7vVVQiOaCMn/cmybauvRkykkli5h5DIaBdKII9YWd/bozDDSahSAJP02mtNxrL7tuC4Pt26mTR8OCYXuBDLY+YJpIlXUB+vVj+UoUIpVw+rXbl4hNw6Lr1ElLnDbNJAttZZaiQwrtuswUFHnlW868S9cBceZpy0z632YYyCSL7DwE7HpmGLC697LnGjjjtqIC6NadqTt0KffbOJHw5qqUWQBi2G3j9v8Wui1M06szj5Zbv506Me3eVtoN9cVd/X5ZVu7NyVYhNV6d8olh03bHU3tJJxhJav7s1Nn7puZkKTOmkXDqP5FAfWFnu12csgwRr7DrzUoWMG1PnHFmOWud2xZtxZ38tZPvL539cU8E4zeVKESmyG//5sJyez5x+2F5JzSXdvNpJJMgzvoKw0SmsMRu66TfPzJlnWCV2/WRThbZdQGgLVnC9DXXOOW2dZpeJ7tQfcKpU6aO6HZOJv3x58xnpKLCVmbdekoUoqmoC6ySMmd+tPuTZbjykV03hknJSz17Mu2YLrBlILr90nQ7FxR48pQnV1F8WgWFXtukEoU27V69fHmHYJdVZqMi5z2011xzTU75TdNERUUFunTpgiFDhmDo0KEB5WxXwbnnnosHH3wQAPDss8/imGOOCaSxLAsvvPACAKBLly44+eSTI5VhGAbOOecc/POf/8SSJUswY8YMDBs2LJBuxowZWOKcQnbOOef4E5SDwYMHY8iQIaisrMR//vMfPPzwwygtLQ3Qee6557zfe9Ke528dxAJgAAXOpNsRCi0AZBlvQcdpeD2JyNOoaFiWT4RkguncrmoxW2slxAlFm1B/OL/bLH4iJiAWkVYDTYLnQfl9gnd8cAvJsPuNhGmovy22AsRlceXSo5wmTdMlEn6jQFUXDHtcwozgmyzFN1j8SxkT9PeR4DPLIn5fkVOkiQMAEkYGPMvcVCqlGQhuUhRs5RwI5TNF2AZgylbWJ+y2EAZlEfmYYdOpX/Pli+tNp6Bo5UgL814ZQCbtV1dIPUnpcNk8Prw+KcqjWbeKcnTSuDIAbSgM1JPmHJ7V/OFVhTyzaGz5ZZOsi6aJi+uOnh9JIJ3dP/zDM3k+3aQy9mXtxT8OTBkRP5Y+m4NaBoUF8ryK2kVcvhFIYxgIfAw7D0lZDsz/6rJ9enQb8N/qvpOtRVHqlS6HnqetbPpjiJzg9XGPNi8fKEizHTaQh8jEiZC5Lg/T8S6DnBXa5557LqBM5Yphw4bh17/+Nc4+++y80s0VRx99NE488URMnToV48aNw5VXXoljjz2WSfPwww+jsrISAHD77bejwLGCuPjss888JffKK69kFEoXd9xxB55++mlkMhnceuutmDJlCnP6cEtLC2699VYAQDKZxB133CHk9//+7/9w7bXXYseOHbjrrrvw+OOPM+9XrlzpKeiDBg2KFdpc4M76nkIb7bqmfLJB/xs1H6CnjAlpUFOjv+iGa4miFAYM9h2VyCLwZu82wl5JReu9IgQEbkFi3aojBDDMoKKhWlgJ/x2CckWKqnCGlQkKFvFoGFIRTA1hvWh0LtGiGkytx5NEn6XIsHWv2+cNA94BICYyUkGAZSb4SGaP8AsS5/cF6hDlk+og7BIb7F9+21CpeGXLMfaIIDOOBN6HNR3fRUQCnoCHqL00qqJMYABWWp5fe9CHvFbVnTSPHp1wBGsxOP+o57uoRj1hHk/AjvYNgi6sWaD72H4uMnYQQq0psgLS/m0PMs07aqsEbV4KDVSYX6DwCKZh8dTMaqHMPOcp/+FfRCwCmIbyW7QVMY3ngK1MBpqAnutchZaI14Ao48eQGQvdZ1kavxganKzDz4++kV8+N0r0We+Fp4CL+oyKtz1Io81LyLHorlnZPbQ672fMmIHzzjvP2wO6K+HRRx9FSUkJ0uk0Tj/9dDz44IOYMWMGJk+ejBEjRuCuu+4CYHtIR44cmVUZgwcPxp133gkAmDVrFo4//ni8+uqrmDVrFl599VUcf/zxmDVrFgDgzjvvxAEHHCCkc+WVV3phxE888QQuuOACfPDBB5g5cyYef/xxHHfccaivr4dpmvj73/8u3RMcQweOQpvsaA9tHmYnd7EIKH/aTFA0BOQFHtooHglCrepBD63j+ZTR4xZ+1sosl8KFArTFW5EpiYz4aVwYMJjFxsrw9RtckALeQ0F6nj9fmc0e2m3NpeO/CQCIQvPTa3fCpBMr1vTaoqZnGIZXOQnDgsV1UpERQEdR4YVVqSdaV3CXQCXICoV5mg+FUuLTyJIxBX2+rACUnjvBM+F3ygsnxACsDNzaCHqS9VqDT+XSUeqBJLqCqtMGUpKUkM/TESvPdLnh3yMjwI+/qFEJXtlhhtMsBHR7SSDebz4dgQGkVR5aO7EhHT/ZjeawNZB/ZjnKZbBM4QoVzOvA+z5BNn4o+naxwISnBVGUFhCmBCNgsKR/+x5acTRCpNagPbSi9SsCMZnBiBctAmuVarEWRB6wMgK7oATHvPgDfJ72HI02Zw3m2WefBWCflPvAAw+gra0NhmHghBNOwDHHHIN+/fqhvLwcTU1NWL9+PWbOnImpU6eCEILi4mL89re/xV577YUdO3Zg/vz5mDhxIurq6gDY3t8ePXrgr3/9a65s5g1HHHEEXn31VVx22WWor6/Hb37zm0CawYMHY+LEiczVOVHxwAMPoLq6GuPHj8fcuXOFhzpde+21uP/++6U0EokE3nrrLZx55pn4+uuv8frrr+P1119n0hQVFeHxxx/HGWeckTWvMeDMsmaHhxx7U1PkSYpaDGTKqKYgYS84gpggB4YyNMxJE6DJKQTOrN1uBT20lmQBBQRe0RCPhTodq2jRwqCv21JCBPhFScwj+1wlpMufE69EMUxTre7qCmgBgUtUTwGlnBZUwr9PmoQWRBjBMEyjhXtGJxJGJkBfGHIsFDZJSBq5QGb/ULNJ9x2mvRSCL63oCauBMw4wZTkvxN8vZjYg+GsYwfJxDqWO8M+8gwFkUlQ95cwCU6aqbDocXsKc3rOQRKIRreNdyte5oAFFNtslKMe2EX9PcAAyczfhFFpJdqKeNkXMSNkAwtsn0L8IuzbyilGwR4iVPG95FhXPj+kwhQgCZZeC1Iim+HZikYCxWDjmTVaF8eojQh9iQ45pHlya+rSEECiiPG13TRR6aBXeW5q8RbgHXpkh7O05+mzuCu2VV16Jr776CiNHjkR7ezvOOeccjBkzBgMGDJDmWbduHX75y1/izTffxJgxYzBx4kQc7RyJ3dTUhLvvvhuPP/44CCEYM2YMRowYgf322y9XVvOG4cOHY/78+Xj00UcxceJErF+/HoWFhRg0aBAuvPBC3HLLLcL9qlFgmibGjRuH888/H08//TS+/vprbNu2DT169MDQoUMxYsQILSW0R48e+PLLLzF27Fi8/PLLqKysRFNTE/r27YtTTjkFt99+Ow455JCceI0B2LPILrSHNuIkxUxqEuttqBeDXnxVITTcO9o7FOSLSsPwav8l9NBmFIswN+tH9RKztNhMovWGt5bS9SHb38Yqyfa/QmGV/s0pwWFCatg2EWHosEYFZQQWbpW3SUfwoNubfcH+1lUU6U83kWH2Pqt5CH8mY5D1pmdnLFA/J1yJ1G+uP8nkfb3+z/cb9u9A2JvIwJEHASorhZZSWKLsXWPTsQl19gxnAx3vpsyAQj/Op5dU2h8lD6K2sy6vslRuTxTNN/QzsV5gaIUcyz5K91NV+q1sbzudj6+jQBaVgTAkesNFINLXVb4Uxipl00kmeeXxCRwfAQ+t29cNX4UJNRxJIIyygj9HRCEpNhYGDRMyI6qwqkIMrLzRn5/b5FE5bN/aE5CzQrtjxw5ccMEFqKmpwVVXXYVx48aF5tlnn33w+uuv47rrrsP48eNxwQUXYN68eejatSvKysrw97//Ha2trXjmmWeQTqcxfvx4pSeyIzBgwAA88sgjeOSRRyLl+8EPfhDJInrmmWfizDPPjMoeg2QyiZtuugk33XRTTnRiKGBZ3B7ajlVoc5mjPH1WI1xN9t5bJHQmaBJUwCTbZ/xynPRtpIhLR2BZYmsuTwfQX+RlniaZRVck0BsccZmAoD0/SCQKy7lo1IBYEY5KOvCO+c19g44iTIeSqXiQ8CP1MCreM8Xbwd8AANOwtMJkhfyFeiPVHlpdA1HwsVzZUHuq5YaO8PqVMaVuf1FpYQdXBXkTfW80Rdn20LZJPbTZDDmaD9EeZheq+UhWdi5h30TS7+x3wgxKXvxk6r4T/DfiwMpSEfbgeR0l/YV4f7AFwu0f7YF8fn6uEE2E1X/omipIL4pwUtiP/DT09hfJtiL7pZgHtdIqfyUd7kpeResytZa6RnHn9GmeXiB6Rl4UY9xloru0PjzApOQ5O08QrrMrAtooQ03I+KMcBOx7Nf97kD6b+x7aZ555Bhs2bECnTp3w2GOPRcr76KOPoqKiAhs2bMAzzzzDvHvggQdQWGiHE3722We5shkjxk4GcRRa5/CudAeFHAfX6mj5AD/kmF8UNIUs2kMrmks966pkAmaJ+UT9dMRjpo0LOQbE+2C8d1yZ2UzmdLgWs5eFF27BL+YG87fO6Y/+IhZ+4Iv/PNwHaIZ5aBWNIrOcA0BGeCAL+0y2D1iQUVoOEFR4deUO+tMTsAQKt4gVkYAV9kCSX3OM0q/5Ez+D9OUv6eJsD61YGcx27hDxoSNgR6XJPBMZThRaYMayPXDewUF5ckt4fERUWJn3wuiD6PyJ9n4Ho0DUhgCl1yaUJV5ojwaX17C2CasaUTeg9VlL0DcJDJCU76GVTY/SaVNjLhe+D9kiEPC+UTcIsGuiABLFNAp/NI9B5VyvhWXrceh2E2YPLdWAlHwB2kNLIJ13dM0QIsNorlMFk5+fH93nKgODkA4J/JbyGya35Wku3BWQs0L7+uuvwzAMnHzyyZHDbMvKynDyySeDEIL//ve/zLuePXti6NChIIRg1apVubIZI8bOhavFOR5a0lEe2jxAJtiGH9bhCzQqC7BnXRVM9FQq5jEhPmMWFerbbvEeWoBkFB5a3jMjOEhCmFUmbNDrCnU4g2hxsffQUsquhofWpSkMOQ6uaUp+aYQrtIJnond8H5GcMMpCvR9UWjBHj1GMmXZUEzUoqdA0rKy9YaGexjAlNLQAP0XoTQIkkEU4jlUnjir5EdS56InFCVci5OJ95MuhoZ6e2JDjyK4yST4dMnbdRhMaMxEOhQpGs4gPypHxp/teu4qUE2ke8mmuQ4EswgmMgsJD6ykNIayFIoLnEAjOp4RQ1/bQfGk0DtsX3PVVsD7z+WRjWrX+iJNx/Mjz8Kccs8YH4nupKQ8tfV1fUPnWg1AeiNDoYtnBl0c8mlJvqiC/wMHAGr25ZxwRqYHIXTPydJ7AroCcFdrVq1cDAPbaa6+s8vfq1YuhQ2PQoEEA7LDmGDF2bRD7UCjnMu8OOxRKQ6AU5/N/O3d+R14U2Mna9cIKEnITtGIOF/JHn3KcIsFdE8o9m2DrR6yT6AnLlkXC9+DyAgyjAGuUG5pCxBcYI7YIhqGe+rP1YGUEB3Ip20NTgNYRxHUPBDEMP4FpCDy0Agi/ISCMyOmwnhhOuokIsXIcFGz1jAvUC288RlUWqXQ612JFVkYF5YjGo4JGBiazRzKqouel4+pG/5RjJVFxJk14KQVGD6096kx6ed+U9u+Ah8j+EXUO8ZNnNzD8rTKC/kUpO8JTjrlDoZTjRPhYmkHxV7hRjK8S124eYIWre0C0hmqOO64fydoluCaLIden1Fqwzj20dMgxvQYEJ2d5UcyhUAKLYBRjlNRgyJIMpPcOhRLkVx7gRdHINjIi+i3Zuy5yVmgbGxsBAJs3b84q/5YtWxg6NIqLi5l/Y8TYZUHsGdhIJAEz2eF7aKPPUYLVMYd9Zp5SrPDQ0l5MufxAKwJBZiySQLvl3/VMAGTSFmQUg3vngvRDP5NZ7/3UfDizzR+djb22RxSeG+ApSpi3l0fjUKiwIKwIbU2DvwLHTsMmosvWOvzG9rsL6LF7cXX7p2kQz4uVENxDK/aGBokHDmjh3ksPNdFjk/O2BgUtpmwifcVwKNvPKR1noeDqwAvBVSlGUehLShUqLfL0FjGBdLtmPUXhw6WnEOiz2KStpQxyUrLf37hQTTpLWNtrFBfML/43uoc2OH+qygvAO2xQ8N2Cctj33KFQgfdcIdmCV2hCTmfnh5HFTSR8VesaCFXX9gTySU771e43snGpGq8Wt0YRcf2AUmitLOcwZg+taJ7Oca4QKf78VTt0e8jWS6FRlKIhm9tkBuVsx+mujJwV2j59+oAQgsmTJwuVUhUaGhowefJkGIaBPn36BN7X1NQAsE/qjRFjlwa9uaWguOMUWg/Zz1LECE6g9oMwScP+h3LQCrOIJ2g+jTw/IfBWSQKgndD7aAkgO8kVQaFJW2EUiDS8cuALH9SdqBabjylPImyyaxUvrMo5pH+FNZUZMvUL7zPV8LaJD4VSFKQpgAm9EfQ3h11XQ8Gk29IgAeVB+9qeCKFaovD6KEJXiD7rPbME9UAE6QL5LUup7Mmt/+KQYxXEp7lGSy9Krrw6BAkmpDTKoTEsL2rehN7tkALEfUujHpUmFBta4YR031KdaxDGEtd/ourx2eYL0gkabexxwc39fCImJJ1v6LAy2fJ1yYQeZicg4Os+cqVGyKPm3JxNyLEKsjlBPVcQsPosW09eHfCHQmXRd5j5XqDRRgnJlcsd3HvB3GyXpX+gpZfHeWPxxsSwjJLkuzNyVmhPPvlkALaH9Re/+EWkvLfccgsaGhoA2Kf/8li0aBEMw/DCkmPE2GVBiD8zFhR32KFQ2QjLsvTByTaMhl+47KRkQBBCo8ksk9wTsI2gh1ZxKJRSIJUK7eKHhHAKhEiZCJTn/+b5FAl0uospYfK4f8jV4JBraLNe5ESKMP+MvYc2nKZuGt1TVU3D8ppT6KHV5EHVtqrEunUbSbARCJ1EIDXZwr5A6RIoAdmAV6KFZYkE64iSqEjhU4VvEsA5FMpNy73Psk1kgiqTJgsNTYsfyTAnkt86kEWNABqnrHoKY3aLkO7p1/JUTtimbHuAoq3c/iErg0jfCIoK0dOYP0PXVPdfV2khjLFYZLSS8SHed64zuYrpEekfXLqQfiOCe2kEnZZpN7cOaA8tpQxmO5fRe9c9EjlOjLS8whj96cfU60BxgvNIhAZer4+w2WWGg4ji126BnBXaESNGwDRtMi+99BKGDx+OlStXKvOsWrUKZ599Nl566SUAtsv/xhtvZNJs2LABixcvBgAcdthhubIZI8ZOBqfQdtQe2mzz0Yu74QgmGns8RbAoZ7X6WgB6gtaX3gltbYfBeGgJAJKRT9IWt5JkdyCCe20CW4jw9Exu1VeFaYn2Vka++sLN78g9styh99Aqy2VDfWmIjAnq/VXh7xhhRlAmYC/avGAtg2FYcE0u9rU92Y2aAO8Kb53uXm0VPVU279vDBGRZND6t6AoFXzE9vhsFIiBERalZ1Co7qgfRIgkn5JhTuqKCVxIUe069LERefzJedPgjgR/uvERfQxI+wbHGMJekfh8IzmPq9GF8hBkAZHVjUO9Fyhyh3gtzZzT20EqZovkT/+aS2XxpnnIsox3IE9IP+d+yqhDxqApfV/VXqUIVMiZUJ7u765dlJoRpooxv2T20Mi+qEpJ5XrY2BSOcgo0qvKaJXlu4bQ8BFoT9StFJd2PkfA/t0KFD8ctf/hIPP/wwDMPApEmTMGnSJBx99NE45phj0L9/f5SWlqK5uRnr16/HV199hZkzZzKW4jvuuANDhw5l6D777LNOpzZw6qmn5spmjBg7F4T4G0c7MuSYcP/mkUbYvEdP2oYZnIRdeIuRZG8OIA45ZiZs6kWKu7pH6akJfJNIoNAT5ghhFWLRKcf0Ym7voaX4lF5nQNN086rB0CWORqtA2KFQ4u8VrPA6fYR/ZkTz0DJlSxPo06K90yYsvfBOXaWKgXgvYzYHt7GGEEH/FL0TCNMWIUgIDw8iTLps+AL0PJ+RDqsKKZc5NVyp0BpAJiXlU8WAK4eI34Vmd64TifaBkQxthvuPoF01imXCORXRLXICbH/OXqHNUbCm9tAKNUmeP+Y1dwo2zxv3rwr2d0jWv4jf6CvhPm1fwRHMKQoOxeMu+CzQ1SUkdffdy4xsYQdJGRKNls2XYJ7zhz7qQHYPbVbzdIjsEDDacIque6Ajw5/LWxgffGfx/gzhKYTs7oScFVoAGDVqFDKZDMaMGeM9mzlzJmbOnClMT1fw7bffjr/97W+BNF27dsW9994LADjrrLPywWaMGDsR/iKGZDGQaukYLvIhTLjKaJZXPjAHXShDjlWzqmgjI53PXcANtBMq5Jg4fIcswpK5X8wKzyvlfWYE6pA9SgbCLfL8Cz58WCOLlnJnhiq0CgIK7VqkpPMLsSFR9BTMMB8uysMIsWHfDgvuZcuiPbRSHgJl6o+PKPttvTwy2grlWrmXmBAQ/9O5V3rCaRDciaj8HkwFr7rQNiaoBGQnGI24x3AHhD55+ZYFJBJuOrGwqD6xVf3Botc64bcysgTRDEZBYxgk7ab5HQJjgw4N7bVLOrf7ZfBJ2Hk3qKhYhDsUSqQQq8oW8BGWjudLp6MzawwJvmf+DERPBDkRjyPJvni+SsJO+GeLCj6OMGToTyWgZAgm5Dj63AL4fgibdnAejGJokY9J9kdA/qAS6MgFQiVZMn6ETUzJLrnakXYl5EWhBYBHHnkEZ511Fn772996HlgVhg4digceeEDqfY26HzdGjA4FvemjQz20Wc5OgsUuqofWBX2HnPCUYzcd5aGVzuEyi6c3GZtotwphwD25lsDKyAVM/huEgiOnPPHeGeaASDqtwHXJfH8glIvVclzecj0UxXKuqOBDjulvydce2qCHTtBeETzmsnca4n1oChcGdbymCUvrW7NJk+spxzLlVKXMhaUj3jgJ5ucVEhFCIwVC3gOSEMSIfV4U3aG819JVaB0XTKQxRtzRJFJI3DSKsgVeF60iI8Kbp+hrSHQ8rkwdRh+rAUVWlV413nOd+ByIDtYhJExhNvSu7dEA+x2aRgBJSl7h4Q1PGkOWSi9ZS3nwirDTx4Onuut9p6xZo5wMbrcf8dlzeWQMs3SF8GVJi2INrBrXs6kg6/OywyiD14AJ6oWOPBCWSbh/w5mSnqC/myNvCi0AnHLKKTjllFOwePFifPbZZ/jmm2+wdetWNDY2ory8HD169MB3v/td/OAHP8AhhxySz6JjxOhgkF1CoY2ywInyMc8CD8OIUoqwp9AKknEeWuXl7iIBnVZoYZ9ybBgEhBh2WKXqUCiFB0m0FrreGWH9WKx3zy2XFp74r6IFRll4Juv1pRZxJTjlR1A+7WkK89Aqvc0KpUnn4JGoHlqN9ZlRGsJImvD30BoGAeHvzhVUts5hVzwYcU9gXY82RvUEY5EXhnligY7SY/hTGxfc8Ray95rbSC4kGVGfFfeR8H5GwyJOf8+kWT41yreIsMqEOcVOtugCo+4BSUKY9JkCGuOLUWiDz0TpRM99YV0iWCOknV0eQlgOq04iUgoE+dkwfnYPbRiPQZrB8a1DIKxv8FfBEUrMEA115RgQelQVa6+XQkxT10MrPRRKec0Wu4eWNrjZ4oWzbQliD60y9JozUtPlZARGxFCph6YnWpvotdnzjAfb1csvkbtkfcw7DEry7UKbPWMNCb7fXZFXhdbFwQcfjIMPPnhnkI4RY9cEZcXfJfbQRs1GT5ASZTT8lGM3HRGHFTsQ7UeLIvTRe0QJDKSoU44BV6CR5RXRUsBtV4mAxwqDaqXHAFfPkjtxs/LmSZRMEkjkKnL5ctGyf4aFXfNQ9Smpt1GyQIsEVUmpHgkTwUOhxP1TzZ+QMZmQq1u1sjYVGQ0E78SKv+qUY7ki4iLMsBLcmyrmIQpkBgz+nVKo9q4KywjZ0j24LGDAUSiATJ6w94GH8vTyjM43Jvz5UGcvLmNAU54QL1FMvLmYY0vYzxR8iE7VE/KhfG2P50A7CfZXMmueqT7lOIIVSnUfqqz/aJIGodZWXsnTyB18IprXuL9lfVw19kT7e3XKpt9pjW02XlhrDqONAjYNacpQWoB6SwJHivLMcs9d2UlgWBQeCiX4LerXsg9gjBFijndL5HzKcYwYMQDQHtpkMUgHX9sT0f3DTcTiVVJb6SSAHycTfG3wCrOArPhQKCq9dw+tgRQpgEEJVSKBWXZVkOhiezq3+qAZMe/2PbQUr9Q3ibyvVEaGD5u/6MuNG3LHB0my0c9q1SRbB5FYqeef0Id9yGmFCkVc39CVOQ0qo2EEhd8wXmTP1EJUuIDHI2x7nYi+pRRUFHcchgjWOp4Pmg/C/c1yIcoYTjP8mZxGhrB7aKOMK+Xd0dwJsCKqFhEbEXySgjGj0UeoXuz83xlXJn2mQBQ6tEIQoX7F01hkRd1TnLI6eZ4tQ6lIChkz1SHH+vpsyHzCzxlh48nNFexftqGEZUzXeKiaK2WHQgW2lygKo8sKu+5J+E4Rcmyz5Mx3tIeWEHXfk7wzmUOhrEC68AMJab5E7+X9UfScpyGShXj6NJ8qowmdxVOi8xTqvysgVmhjxMgHCPGshUZhSceFHAsUKb2M9E9J+IzmvG4RKPd9+Kf20UK+jKZEsKJM0/S1PQBAMgrBXWtRDiof4mRcyLFAYAjsO6L+lAoETBr73yinHPsPuAN7qERmFh5aHeVE5yRNWpnWEtwJW5AoiyW47kBO0L9XyoSlvHvTyyJ4phuxwP9W0WTzi8eHqsuqDloj7vsQjVLS1UN5BDQ9lqI+ogoRVIa/0+NPQcPtc45Cq+NJ1nglvKorEgFJXi2ljgR+2H9F9NDS2VVjQd4H1P+yRanaSBfqlLRi4+Wg+4m/dPjvDROEPhRKUmJYHbjli57zZfLvVYYk729L7JXVqTvdU455au73yJR8IQNhSh7UfUFi6/VJuw8oDy19GKT63AZuPVJcDxQoPITXsDb05AnXEAbuX2EETfBUa7pQvn10lkGmfvQH3i6PWKGNESMfINyhUO0dc8qxx04umSXhwrrHxtt7StxngkxcCA2vsNhJRAqXO3H7yguBYR8K5d6dC7Fyw3tohYq/SFBQ7AG2uDs9SaikYbAH/fAhx86/zFqjuddP6fkVlGeGTP3qtpbvgZVZg9nsEU9hlX0P94dunzeoTbOGZkahYqAwVvB/C0+31hxPQuIyVkKEK+lJoETvUChpuf4TxV+RyUeiobOH1g85Vrcd805xcrSOB1R0SFEYtMaF94vz0CbYU9/DywrOSbI+EkLIoWH/K967p8juCfm5QbSHll5jRF5ownloQzVRVfmiNUFCh4RoQ/yawp83FRj3IQYtvigdBY6/YsYFM6cFlGA6v6AMQKl0BrZGEMLVq5OOWsdssSC8DwXWR0P8TldB1PHgBo09XJ3Sf/Lk+OiyAH3nH8l9wcKoKYXRZXfGTtlD29jYiHnz5mHbtm1oaGgInOYpwxVXXLEz2IkRY+eD9oglCrUOmNg5bIgXn9B8gr9kezxDaVG6vfLaHt39Z9xvQs36Fky0UyHHAGHukmMLJYFFNCzcxrd+ioUN9pCnILN0NgPsQh/03gZXUO3FhhOi3N5IxEmie3w1Iby2h6tj5qwPDY+QYfDfIV6gdQUQAxYs10NrEL31SUA04EVQKXcqIVdaJC0wqvN7Ah6TRyEgC/Kr+ZLk4wVZbxuBfB4KCx8PvFKcnC0S0kWwDE6hjRDWqvKiac1hWYT0afUREvhh/2XSHtpo8buq+VB+Wq3436iTSEDYD0kngyW4to1YRFZd9iODPRRKVkaYUmGXpeaPhm7XoOuWVlxURrRAWSHrk/dKUrZqvlMZemRROOp1n18b6X5Fv6GjfTSVUO4dbTwXtV1YFJFqS4JfHFvfsnajPfA+f/47liaXV3P9c9Pw3uE9AXlVaF9++WU89thj+Prrr7UXbReGYcQKbYzdGITaQ1sIZFIdxgYQbVEFuAVEpu2EDGlvXwsh4VZFsBOpXICQCO/Uc/vaHp9F0aLggjc2CxVmlslAOtr5zCwsQu+kn8IAZ2XmlD/hguQqdexlQUrQ3gjmOX1AVdg9tJrhafwjvStZDPkrSXmqUFrAqXuF8YEpnaFrMGM1ygEmGoZ5D1p33fL5qd+ivV2i1Ew1ifqjJRNgwsdiKJPQU94i6rMh3Krpeu+MIvtfN+RYIDDLYIkGpJcvvM/J9trzNJg8EZRgwzFdeYfHUAqtjqxKF68Mvw8T7L1k7joQjYROXapo0NtDAgoDxaA4TNwEUuEhxzpQhv3LtEVJGbySTyvmomLU86neQ6lyKjPAivKE3EUv5ccBH0lCr/nMAXYcQVoxlNLmXtHBYLnO0+I6lj8Krp9yBTPMyCIzCAnn24iHke0uyItC29LSgosuugiTJk0CoJ6QDMOIrOzGiLHLgxAwHtp0x3ho+bAq7WwixY4/5VhX0CDww4oFHruAh1axDAv5ojQ2/lAoAMJ7H/1rgPQFWUD9zbziKNqWwh/SozyFViA36Aq2jPJDX2HD8+sgbA+tul7khzqJFWF5fqUCJGh7GW/RlDD/7lkLJgh3GIyoaoT368oaUFRkCP/iTPp5RGM2yLN90qu4/ggl8Ou0ofg5rywIQ9Aj3vWoUvjYelUIsW4YrtRDG70f0n8zcx+fnYj3dIpOL/X41egkQQ9Ldqcc63oXpSxxiqi/j1pnzATpZ3solN/nSGBNsUK8aAjz0IYo24xxVsmjnC/puKRoMpEodFlinVNatkyhYl5yaZRGIP6dnA1ZFvZdYKsN16JeHbAeWi3a3EtGoc3iHlrVlgQ3e8Aw4Y0VEngu410WJuy3JWEeGIadTrZ2qeas3RV5UWivvfZaTJw4EQBQXFyMk08+GatXr8aSJUs8z2tDQwPWrl2L+fPnI5VKwTAMlJWV4ac//Wn4FRIxYuzqIAQwHa9XoqDjQo7df6MKBaLFgF+kNGlahHhnNWgtLAQBAcSjJTsQxlsA7D203jsgeK8o/EWLP7RGONm7eRAm4LEhx/T9iyKjtgGD+TsjERBEi1UYeOGCwIuy9kAviGFzbrZGx4xQgVEoGsr+Qf9BP1cv0GGs0/fQEgAklV2ooUy5Ef2dzTUJjGEjTKgSCJ1CRckS92m6z6rBHzTG0REomoGyIkpQugqwcqyajofWVWgj9G/h/mf3nYZRQ7QFgjacCNtJtG0iQETyPIdTjkWGAu+dVNDm6HGCtbQwno6u8S7UsCpQCojAs8nMs/y1PdlL+bLQUKZsilc1Mcm/3G/h9oIAX3LyKshOn1Z7aP0HvNImy8OXyc//YiWOP89BXBbLG/t3ziHHzGvR2hTsc4Fy6Oey4rg13v/JjlmdNs3KwLobIGeF9quvvsK///1vGIaBQYMG4cMPP8SAAQNw6623YsmSJQCAZ5991ktfX1+PsWPH4k9/+hMaGxtRXV2NV199FZ06dcqVlRgxOgyEOjkVyY730EZdj9nFwpkgAwuYHg1WkBdP8IF/pYoEHWppJ7L3SPnP7VOO2Qlerpjwi6poUbZ/0PfGysJtQxcGWokEJ+zIQrGo364wEMXkZ4c4Om0IcXlmWMixhgLH05clCtzzqjhUiqWt/zzawTu+tkCIqRlyTLWjY/kOC68VjanAC2V+scAobhtqbAjye8+Ep2iCEfjFXsZwHiVZA9A6OCzknWhvu46H1g45NkONEbLyZfnU/ThY57wBKpAngiLqhRwLPbQadOg6VBkFQq0qLr0gXS6JEtneIuIbKYMF0WHfYsMhfyiUmLaOwSuKshDWD4QRD3T9RtBiRMYu8ZzO80iEaVVXhDHGOGnIsWLMCMYLzbNY1tCbWoP3jtPvomv9oQcsEWp+5miK5hP+mehWCCZPhp0LvWSGW7aA55B1YndFzqccP//8897v8ePHY8CAAcr0FRUVGDlyJGbNmoU+ffrggw8+wNVXX50rGzFidDCIPzMmOm4Prb/wRZukhIpPYLINEeBdS6xFlN4HXuDhPZ0sTVF+f5a2TzkuoJglwjBnvmz3h0q4NmCoQ44lB0wx/CkEZ1FYlU2IkbSEvAV44aQo4bpKpckl5Jg51IlLlxHUfYAWHbEc4gEX0pAIYbo93t5D63poDRAqmiLKnYlRDoXKZs+SVNhV9kmKP8EJ2YLzcqKQB587KOQSQSpFYTqF6kjdYSTcPbTOgA/UjSqvQvjjPdJCVoUeWoqmoMyoocI2gvfQRj3vzD1ESme/vP+cqwOVl15ldJB48qJC5qF1K0ysaOd4KJRmGtl4kafnlBWIT/v1HqnIifqmxhYRqYFCMWewK5AlThPWFyT0aXmBnSL9ulH2e4nC6JXLJw9rc+25008QWDu81wKDo0CWYsYsN/e4+f2zPtQL5h6kz+au0E6bNg0AsP/+++P444/XznfAAQfg+eefByEEb775pheyHCPGbglKSLYPheooD607o0fNJyflInTxFeTTOcVWZJX0yhQpEpZfmgUDKcKGHKvuJBXtKxT/Zj2qMhlcesqxhKLy9EfBAqMt3PELHGE9oTzd8FOO9cpVWe1laVQKMZuR/kkrFYKkluSFEJTXHwaQooxPsn5IH6hliq01Ki+ccu+0BKyioWZRZMgSKdhEotHaY1Dd18N4BKC1LSGqB07pYdAUJj0PrRvLG4EHlbKv05ai6SgsH9HQRGUkoh4KBUk/CySTdgL3vUNDpgCFsCMzpAb5UPNnCa7tYT2bbjHUWDEM5lAohe4WypMqakBnD7GoYN9YIF5nhcqJav32FORwRmRroNrYGyQXZa4ghG2fgJDg8c9dAafoex7filOhpAZ0BdRzLhwFnKdPvHd0PiKcno0Ab0wz8/O29zKYz+NZ0Ud3Z+Ss0G7cuBGGYeCII45gntNx6e3tYuH+lFNOwSGHHAIAeOmll3JlJUaMjgMhlIe2oONCjh1E9tAyClFQWOTTCGmI9pAq7u+ULXRs0uBiYS9c7h/sHloAIBmBEsVpcCpLLhGkYyZ9dz8uZ00VKehMqCpYvmQh3ZZAeYsUckyfiMvQp78huofWzy8/1EkW5spCM+SYae+QMggRt5UAJvFr2IIBYvkKrUXEdS0yBgT6jrIfi3+rIBOMVQonI6hIDCxiRUMoSUnLkT0gTKNp0ohaZoRnLiyDPRRKemVWSPnB/i7+lylbIKWGHSQTZfr25gjBKcdaIccUc34ot4CnUB3byav00IblzgHemiM4hIui7ykAjIJgch5avsEkz0VsRLm2J/RQKLZcwllH+KVa94BF/5l4jhD9rYxqCIwn/3dGsh9cVZP8FhLaDkeI2KBFHwamlCm4v01KC8rGQ0sUf7lP+MO9pEq+WKP13yme84qtd26IqN0tOQ+7M3JWaOvr6wEA3bt3Z56XlJQE0ojwve99D4QQzJ49O1dWYsToQBB4JyF14B7aoJVON59AwFIsUqqy6cVIuIi6/1IhylFCPfmQY/qUY7nA7vPGPFcIlvQhTjLhjF6sQ0+RNDiPrlQZ8J956UM0Wl62ECuWDCtqepoSNZ9Mz0NLnUyptcdP8jdhn2kv0IQ6FIqYQIoTZAXKPnvlEZWWTqPgO1ehQTs0kQk5FqSziOS5fNxLnwkeqw4VonnQJO+8k6dn6lglzJtJwDA9z2e0e2iD4zrwTv0BykdRlXMpM17IcVKeRESG5iULD61MSFfN/UI6Tr8I7+uS586/YgE+OM+z32Mwa3ZQnw3OzVL6bGgJm06kwIiTMrTopYFePwP9j7C5ZWUr5QTNMa0ysgk9gFGMSIFre1iZwv9cSRRSlPkn5JTjULknxDglCu+V1aVw7RYYmUS/PfnL02jlTOlcmbg7ImeFtrS0FACQSrF7Brt06eL9Xrt2rTS/23ibNm3KlZUYMToOxNo19tByp/hq5xMshDJhVQZLMMuK9rPyay99FUGApkgQoU74IDDQTqhTPWE7YWSc8vWjEiJsj6orZAl4I6wiHnZFCa8mye/ni77Y0HkyjjmbO+SY+c2HIwfoKd/Sm2A5IUXQR4L9Rs/fLFt0RYKQRQl3YXVm0IdCAeyhUJbYeU3TlF23ohofonC/METad+sKMyGHfdDh+oLsgd+BZwFBn/tb49M0ZOhQmjIvvQwWMYFkoXcPbZT5UbkvWa3n2HkygmtkQjRa0V50AWfMv578Sim0UQ1GqvQ6czRAe3mFDRdKP+sQSHp9EOgEPH3WGGKwpxxH5CHMkCSjy/wpNEKyvPJ7S30IjHDc36K2FfMq6eOKuT5AmQTTRZkrhNFP9N+u8YPpu3p9KBujjQo6xik/6s2pC8kmWtHhhqJvYrYu8d5q51+FPsuE5UeN5tuVkbNC279/fwDA9u3bmeeDBw/2fk+fPl2af/HixbmyECNGx4MQMHtorbTWPqidxk4Ok5THdpb7cOlFVyWM+gqqghdBuJJFLW4EQMqi9oyBqPft+qmcsuXKI3Ntj8TLIjswxv/JCXu04MMLCIKi/N8Gk0bEC01IlI7ZBxqiVIr3AwsEb4kwK+UNvIdWzoNMifWVCEnbhXV9yz+RnMAEoRVaEPE9tIxGKyhT4++w54F0UoU+mNZtB539XDKhK5twPZmArqQhdKEp0iv0IuaVqi8ZJpAohHtquvJOzQBrjObD5YteZwA75wmzavSRYJJgyHFUAV2p0Gp6TlVG1TAlBgj/dLmn2FVyRKdKC+YPplnVHlrVemaXKW7QMCWOvd5GQDdwLC41TgV5iPQPWbrw+Vqm+KiMjGwkkpqukD8ruDaLygtc25PNeAyZW8PGUJixFWDvDhaVw/RJWR9j7lIO5pVtF8h2ftkdkbNC+53vfAeEECxdupR5fvTRR3uW7KeffhrpdDqQ98MPP8ScOXNgGAb222+/XFmJEaPjQAh7Dy3QIV5awlvrsqHhTpC8shLmoaUEGW/i1rCGigQQn2bw2h570nefC0KOBYeCeDS8MGeHvkK2pk85lu1DkSoQnhDA5WGszOKCmQXSoR9pDy3z/TR/NIMRYpg5MKdCZsL7iNrroyd5CBW6UEFCAspKYhEj4KEVVQ3jaZeFHCs02rDQQhFocmF3IYrCAmX7waQKrdf/woVc/4WYDxWiOkF0vbGqoglMoKDI2yMg2wsrgupALv5ea3F+gdclJORPy2vCJRFd26MVWi2YbyLVL9dv3L6qdeK5kI6S2/D8gutb7L/ZMcLWscEYoaXGKMnoJRJDpdIjC7ZOZZEnDM/U4mqPWR3thaXFPgumCyrd4ucMOZ60oE+FlcO+405zlpzVwC+5vHIngkoxz2oPLWsZCb6nnqvmWPd5oCq9B/4b4RVMsogvUbtT+WMPLYXvf//7AIClS5dix44d3vP+/fvjhBNOACEEixYtwjnnnIO5c+cilUqhrq4OL774Ii699FIv/fDhw3NlJUaMjgMtCSecQ4o64KRjoeciQj46t8qaLKZBCUOe0iHXGOmJmD0cg55sgzzSB2NYxFZoWT4hrYCANVPb6xBctAghjIcybG9g4FAombCjWB+l+wQ55YcQUXk0LyEeWk2pMrgnWcAaT4s+VVIp1EjfCNP6fV/NuwFCWfYNxkNrWURYNzqe58AhX3R+RdiqFsIEX0d5oA0MUm+D8DmEz1V8AEElhz+gREgiosYiVviCtFR0M0jYHtoQhUXMAF2uUFNSEhQZEcIUTd3xx7Fng95Dq0GGmW8Vn6OrmPBGQ1VaGqKDfnTK857T7xVrl3hJcsa8s2aHKaI8MgIFQ8ykWDGT5XPZpk/JJdSHBvMo+mHoPmIxpAeFKXhnFSZxWWFGJH6XhmrttPMQpdjhZ+b+ZMa3Ip+MnEa0BR+GLzNwqYzxjCwkWE/8CAeunoU8a9bVboacFdozzzwThmFfR/Huu+8y7/7yl794Xtr3338fRx11FIqLi9GtWzdcddVVngLco0cP3HHHHbmyEiNGB4J4h0IZSVeh7YB9tO7kFHFiFgo1qnAmIQ3/X88DqjhF2JuILSKdVUXX4liMxGIwIcd22XJOfUWW5dn+7S4ILmVKOBPQIoQNiaYXfpFVNXBtj8R7yypCxONFxkfgOyQKfaRDoYQfHMzNf4NIEPfSGO4/uqcci+teZLQhlBcsdIGmLga1YMBgQo4le2ip73Tv8A318hHxH7rbAYhEgBHBreOw6xhsQTH4nOmzss6OoLDEf3TUe0+9Z3rxkUEi2sKYs4fWEu+hVe+/pQcX/y6cDZERgSlO1B7Z1KPolGMNaZUfR/S/yvK8/KyQ7hkNhTRU411dTigNSknjU2SY+YFad7yszqB3wo7l5xvImKJ+KpRnlQFQGd3CrC3+vBhlaxE7HYkVK1XG4L3rAXLCv0WHHYaVTYcP21mJuJ9SIccIm8NcvpVGhWDGkAsBQqMtGHHFHRsSBVdo/EKw/tj5g33myTbu65CxnPWe9V0QyfAkauyzzz741a9+hfXr12Pr1q3Mu2OPPRZjx47FjTfeKAw5BoCePXtiwoQJ6NGjR66sxIjRcbCo02RchbYDTjpWXpmgyieaLCMKq/5Jq9QMrphMRSHKcHL6V6PQigD1r7eoiz20MuXCp+EINQors2HQyr1YOBPxx6bh/maUFHEj5bL/2c5vSZQW/1mYh3bL4mZ8fP96VPQtRHtTBqlmCzU1zbisx3nYnChHG4CeRhG++ec2HFPQww93nE7wXvU6EAIcV9ATAJD4Gji+oJdHu6r8MKxzGiT9WQZvr1gDK03QsCUFwwAShQYSBSbq69pxemFfFG4w8f7v1nn5C6cYOLWwD2amtqHdsdys/qIB3RcX4qTCvWAQAxPuWA3DNGAYjp3JMGCYdpsaVQdjY4t9Kn9V03FIzO0FwFZqpzyyEY3V9u99zDJ0N4sAAOU1BZj66CYYJpBJ2bwv/bgWpWsT9rcbwLatrTgk2cWuBwBrU40AgB5GEcxlBr5+thoA0LLRVqrKkMSsF6q9/J7C7/xbs7LV/l6YKNuUwAGJCgAEhZkE2hMWCg0TJoAZT20BFhMcnOyCrjsKkUzYAfgFW3179Q8qjkVRohypJRk0lwL7JcqxOdOCZueArIyVwKYFTQCAtqYMFr29wxcQCUHNWvvAnCIrgTTstfygRAWqm+znPY0i9EqUoOq9BqTnZ7BlbTOGJDujnVhYmWmw6wFF6JEoRtv8NGa/tNX7TsMAEq32H52NAvQyiwEAtVY7tpI2tDVmMP/17aBniVVfNKB4cwLtqQyKYKINFowGYGCiHAQEKWJho9XipW+v74PlRaeirqYcANC0I4Xln9TZPBhAZp2Fvc1SbLCawWP97Ea0rcnAMICNa5u85z2NIpQ1JVH1dSM2zffz7WOWodZqQz3SKIKJ8voCVE1vRHejCNuJXV+rptWjvMyet2oq29DXLEG11Yq0841mnV9+X7MEBLYXsJrYfWKAWYYiM4EM7D3f6QRB14K9UFb2HezYUgo4bVS7th39zFJmfl35eb333QaAHTvakISBNAjqqtqxdkYDNi9pAY1eZjEK6gysn93IHDbXwyhCr7ZiLPuwFttX2bw116Sxemo9impN9DH92y4IgPaU2/cTIACakUESBrqZRWhZm8L6WY0gO3xuXb4AoBsKYRgGGrekvHcVhj/3J2AgbRCktmawfXkLuhmF6GWWoNhIoPqTFpg1zhzVCMz511ZsWN+MvYxibCGtSKUSWLDjMphv1MAoSaG0OoF9E+Ue3zusNrTDQqLFwD5mGZpJGtucttzbLMXGmc3o63zrplnNaF9nf+emKrY/dWkvRMI0vRpsXNWOtV81wADQuDIFE7YtutxIotRIonVNGlWzGmFsB3qaxSisN1CcTth8ZYCmNSn0MItgGgYsg6BTpgA74HqZ7TINAN2MItRUtmGNMxYT2wz0NkuQWpdB5aQaEAswE/Yd271SxSgxE14bV89tQXFtAjvW+odmlSKBHo2FWPiW7ZRqX5LBfk59AUDlG360ZuFGE189swVp6jq5AWYZMlv9vwcnKpCAgULDhAEDZSsS6N9QBsskWG01oqU2g3n/2eal77GxBEckE6irbwTQjhIkkJ6fQXNxOw5NdkGSmNhoNKOatKIECXQ1C735YMYzW9CtUxGMhL0m9KsvRedkAQiAlvmsE+KgRAWK0wl/nqZcgCaAQYkKLJlQi42dm+w1oLoVpUh482ohTPQ3y2CttLBvohzlbQUoTSRRUGf3xUw7wZL3a1FencR3kl2QmZfBvNQ2lCCBFodGe6NdT1WzGzHP2AYYQOEWn5HmGnusp2sz2DdRjtJUApUTazynhtnmr/UFMLCXWYL10xuxdbVdH1aaYNVUak4wDFT0KUC3fYuxuyFnhRYARo0aJX13zTXX4Nhjj8Xo0aPx6aefYuPGjTBNE/vttx+GDx+OO+64Az179swHGzFidCCIf22Pt4e2A0OOc7C6uTlV+z9VZdMOV6UVlvLQypRlNoSSVkJ9hTZN6GsqxIdCBazznILr8uFSARylT2HJJoTfQ+tbXUXtEDh1WMNire2hZfbX2N9leDuL/ecuTEMdnNNan8GO1a3YOK8JReUJFJSaaE1Z6JKsgGu2NGEg3WIh6azyBARwD/MwqLINIEOZqDPUUcKkACjunICZMND7O6UwDHuRT7dbaFudwabNzagoLcTBw7oC79gUMj0Jtta3wjL8DyosN1HYPYHGdWkkYaCsR4HntfXCuFxDB4F96i2ADClAut2vi4bqlKewFhsJdDELYQAobE9g0/xmu22dity6vBWrNzU47UbQ3mahv1kKV1NY5yi0nc1CJNbDFjIAtG2zBZUSI4GFb9b4Leh2a+ezahvs+aPQMFGxpQAHJTvbeq8FkCTQTixYILaCUkOwT6IMBU0GOicLYMDAtppW77t+1OX7MGEiM99CIywcnuyGZlKNZstVaJNY+n4tAKC5NoOpY+xbB2whx0B1qy38FFkmXJWut1mCLe12GZ2MAvQ3S7H9m1Y0Lk6hpSWDgYlyNJO0p9B2SxRi/2QnpJZamL92u/etBEDSUWi7GIUY4hgF1mQasTXdhraGDGY8tYUZ14sn7MD2hM1TqZFEG2lHotbEEQXdAACNVgob232lLLV1CCZvPxwbUtsBNKJmTRs+vm89aBxT0ANvtK0Dj89GbUS54/XcbvlC/dGFPVG8JYF371yLTRlfcRla2AOLUrWoz9Shi1mIfarL8PXfqzEk2RnTUrZRY/JfN6DISHh5ji3shY/bNqKO2AJ10Tr2HQC0kDQmtW0AAOyTKENXswimaY9zs8AACroDZQdhwcIaAPZViRtnNuKYQla++vDeqsA3lhgJNJA0qqY2YtL0ddicYRXaEwv3AlYA74xcCxOGN54PTHZG75YSfPLnDVidstt5+6pWvP+7KvRCMXoV/n/2vjvOkqJc+6kOJ58zeXZ3Ngd22SXnqEQBFQMomBGzV72Gq+A13HvVa8TsNWIC1E8EFVBAEElK3F1YYJfNeXZnZ3byzIkdqr4/qqu6Op2ZBbyId19+y8yc011dXV1d9T7v84agUvzXSj8AYI6eBwOw2Z1AgZh4UWoGhm6u44837wJR1uRWkpLA8bT0DKSIhnV/4e9MC0nhzPTM4I0YQOMOF3+5Yy/OSs+CzSgqzEFlqw1NTNwKw5M3DsOxKGboGQw4dTiWhlVDHwSuK4OxClptE0cb7fx9IwSPWoOYgI1UWcMJqU70uVUM2XwlPMnsxBM/GJLPadW398vujCjzBQAOr7VBS/kAY//va7j99/6cS3tAZrFexBKjhLHbGrj1tl3IQseLUzOA7UDdcdGHGtAA9l5fwRkpfwxYjWEH+LpDvHcrAx1npmdi6zXj2ApuKSnAwGmpbjgPUNz3QF+gjyvQCiil3Tf8bBQbMIqd3vMF+Ps+ZzyPB7/Hnyd1GY402uX3G28Z8x/JhIYtfxmHrQDaHj2HgTF/jh2iF8EIX9MYALOigbp+UR5KGerjPimWbnCQOukYACwYRAP2ApbGDVMAME4sgAEGIcjCf5+GNtVR0x2ZA6OtkUJJM0EAWL3BLJQL9AJ0V8PTN48G2HGAG1CWGSVsusm7V08fKGimXFezRMeRWhvYk8AxRjtInQAmsH2Qj6XdoLj3y3vRSkwYGgEGgL5yFWloPqCt8p+9q8tYtW4QjAK5ur9nlQf5mmENUZxidoFYBPd9tU8CWrPsz7ccMXBSqguPf38I2x3eB8diuPM/gmvCEa9px+n/OgsvNHlOAO1Usnz5clx99dX/G5c6KAfl+RFGpXu9jKF9PmrRSjR6gKepTKVgeUNJPabCyAH3qBjAGL5WwO0m4F6ktKn8IeNVmd8ZBsBiJtR6dGr6/ui1g32IY6ZVy3asK6dyHyrgDobZxnUgCLYTY2ViWeMpIK3yMaUsPoHLARg58l0mLv3pksBn6zf34m3nXYujOy5E0ezEAKvjiPd34Mfv3CyPedWJ8/Cyj80HAHzj5HUAgAuOnI1HdvveO3ur6zE7fxi/qxMJzvvQ3Ng+/PH3u7D20TEsKBVw0QULJaC1ljI8uWkUZkqDqMAz4/AcZp6cx89WbkFG1/GFT5+YeG8/eM/vMGPnfmy2XoRZuUew5Mh5wF08K/8Fn5+Hez/Yj+FtDWx2J7DZ5cBgXk8eH/vpUQCA687YCqfBcPK7ZuD8C+fIdtc+MYKPvPcR+Xc2pwNVYJs7iUNe3IL3f2oZAODJ940CjwNDrIHLb1qW2M/9n3sSG24fR5k56D28itWPcoYinzdQqfjK3V2/eim++eV1uOOWvVgwp4Cd27hCu2xFC+AVEfjE7q+gJTUTX/jQ+9DamsKP/mdj4FqaZuPFH52Fx78ygtJME++96bDA9+OfexI7b69gQrcF+Yf77AG0d6SBYWA7LWO7VcYXrzgeJ57ajfv+sg+f//SaQBub3UlsdifxpjcuwdveszTw3W0v3QOMArtoBbsalcB32S4D775lBVyX4cbTeAnAC740Dyed2o2JcQu/PZ9/1uhx8bve+BKBqYUP4e2H/D9Mbn0Ldm6chxmHZ/GObx8qWehf/HQLfvvrHbHnXvS9hejp4Szn+nVjuO/jXIm/u9GHhYtL+OLXj8eap4bx0H/yOX5TfZfPbtE61s4dxRWfPBLvfdsDss03/GIJWtvSYIzh0YcG8eXPPAlHWbTLS23gaf77H+tc2VTXlL/Z+6HrBK7LoBsErsMwUu/FpvH78PXL34HNf+LHLX55C275gw+YCICb/vwSn30HsG9PFb9/Jx+3RRe24LJ3LsWqlYN48HM+MPtTYw+OOKodH//Po/C7i/0xftjej87WDK777Zm45urN2Pirccw4LIvLv7YMn/n3x7D2idGAL0impAMTwFZ3Un4+zizcXt+Dy999CF7y0jn45lXrAK8wxgjzAeE9jT4QQnDWy2dh060TGGUW/tzok/ela4BLgZe9ci7OPGcWPv6hlZhkDigYPvb2I/DAdfuB3QDrBN5286FY9cggfvPhnXx+5CjevuREaJ/fBtK1CJ/48CqsesRfs0xTAyhQbnPw++HgHLulsRvf+sEp+Ld/eRQEwLevPgVz5uXBGLBxwxju/bd+f7xy+zE26rOA7/rAMpxz/myAAX+7tx/1b/IFbb0zhs3OBN7w1sW48NXzcPX/bMBf7x3AYUe0YteuMjAOkAww750FXP29TdC8sL9C0QC8IWOeBbUOF39u7MVHPn0Ejj+FGze++eW1eOivA3jVpfPxzg8dCqJBZhZ+4yvvwdio7TmNEHz+a8djxeGt+OmPN2Hr7zgIGmB1PDZzBD+7nufQ+cVPt+DaH2+R9/WLX5+J31zMx3Z8sYU3X70U9bqLX5253Zs3gzhkWQnwcsneZu0NjOmph3Vjb28VuybKct6c8PYZuP0T/Ljdcyexdu0E5s5wgQEdk8wGXkJQak/jxu/vhGlqsL3Ne5I5mGRl2fYFX5qHntk5+fdbXnMf9u3lBqlXv2o+cKPfjzusPuQLBm75/Xnys1+dzO/BBsMfG3vwi1+fiVk9vL3NG8dxw+U75bHjzMYtdi9efcl8/P43u9DRlcbwYAOLlxSBrYCZ1fDuPy/Hpz/2GFY9OoiLz1mAcy6Zg2tfs1W2kes0Ud3v4sR3dOOSN/HkuR//4KPASv59+6I0xrfZSC/Q8fvtu1FqMfG7O87FzafvBlyg1uoCI35/bq7vxvd+dhrWPjmCNd8egZ4iuPxmvg8J7zc9/ayjUZ8X+V8BtAfloPzTC1MY2ucxhvaZ1haLi+mKxvtM0aZgaBVA2axEhxrHyiIHkEgfYmNuGY+hFYCWedeMZjJkwZ8xiSrix4wFfgQ+YohNCiVYwXD7PIbW/8tl8X2Mi5VpVlMu8rkH+MOMsMqCT+VynG2Pbg2ifyTms7hryM8ifVaND8lzKikeKu7zQGzZFMCdUAoKwdDqAFViaFl8xu2A4UP+nL7BR/0uHOdKEoK0EktCITrmMhuqQjDEeirQZJZfvnNx9y/7Efo8/PzlGtDsucZ81zxFceTicR4gTcdfA4wUUWoQE6RyPmsDE9K1NSzpko5cB2doMy3+OXVQ2DpFcWYK5hZfAQxX13AJYOQ0qNyPmdeRLvK2jCyBHbJAUmVKWEnWyZCNi4HBYS40Q7kvLXpfmVLw3U5N+O6leoZ7N4i+CakyF06KodSTCnxOvX9GWoNmeB3SCLKtBhyNRfouWGkX6nwGanChFTSUZqWAtLImK+dWwAuMm3nd+45xICP6DsBlAGklaFmQkmw3wI2z4XCc2L1JJIWK7EhM9jV8lgtAS/vPMFXUkG3lY5zKB4FBnVDUlZmg5zUUuvjcMkqabNsGgw0XJA+UZqVAM0CVObBNBsfzTGEE0Fs1VJjDXY4ZgxYX/w8O6syShpy3rrsG4276KQJN5ycRHYBOQEMeNXqWP09iBBtvltCKxSSna1baJyxho3SYHY0r2zNVDe6kzk6ZMGwqtSfQz5iDSTThGZXHA7qpgSp6RrhyQJwKog5d2OjOGAJ7SnS+MhgZAt3zFGAMcr6+0OVZ38Vf//pXAMDs2bOxePHiAz5/x44d6O3lFkiRMfmgHJQXnDCquBw/nzG0wZ/TPi9GYQ/rUVPh2UAdwRBoVUXWzFTAZez1EXI5DiRy8toQLsfq+W50Y5Hu0KHFPzZG1/ubgPjHxzHNNLyJKv1OcFVulmAmBs9GXI6nI5yhjUOD/u9TuRybuej3/r0qSoSTdIxy1dBnwaRQyX1QQUug3Zh7Y5TJ55cEEJVeSkXIZTrg+jcRG3+N+OccSZqWMOdE/5TLK+0CehA7NL1m+HfxgcxynODpoPYxvowDiS39I7+PKcESd2yzpEJJ5yR9Jq8t14vodYLzokkbHNFCZHELg/a4etfT6lvCex48P9nAltxu068BxK0JJPJNXOmcqChzxo2OtexTUsy/AvbUX2LDSJp1R5w3RZfDta/DTceVSaJMsYvEdIUKYOQE408jjSc8N1dxp53qXQ3+GVzDwhJJ8MP89Eiq4RTKZ0kSBEHR9SKxz3ENILw+hb5TQ2DkmjDN68Bbz5sYm+NqFgeMmslNN01kON0SYeG+qn0IC1E+97eu4PjL9ZuyyDsbzE0Svab0VjuAbNIHYgB+Icmz5pXPPPNMnHXWWfj2t7/9jM7//ve/j7POOgtnn332s+3KQTkoz59wsxj//XmMoZVKwbQUGfW8qCIcrZM6xcIuFX0WuwgLoSGllyYo2eqxQHDR9zvHk0JRGccpFMiEvoUW/yDLFwZezRd9hpDLsfe7phH5u3oaCV0vUUFMAkLB04P3o27+zJuO4RjaZ1CSIO5aqrihSRJnjY+cRlSretMryvNjAaVyJFVBw5QpnH2GlkILoPJAO+opAc0p5rOYvwPfBfo6vZPiDCSRxrz2At4L4rCE+4hXcEii4hm8/lTz0e9TkhxwDdkmc2pKdkQKAYw0RF3r6LNr9hySFes49iR6fnSeB5LDxT6PA1cyfcJ2egajuGPEcnYgWY4Rej6+sTA6kZoCjRgjY+zlkr6XfY/2lQYY2hiAIH51Gk2vkTQGrprtPsarKOn8ZpmC1fMD3j8KKEoE3nES9/5MI5FhnEFpqmvFGaIPpK696oQVKzHvv+syRXlpcmoY8E2RaTr4rk5vb5jymiz5Z9I4BfUC5ftQm0llkgLXp76OdIDOfP/Q8g/hKJ3k5nVQDsoLRlSG9vnMctxko2omQYNfvGIxZZZjlUEVi2sM8xEu6aOWXIF/qhfD6n8RH0PLAW1AiROJieL6KBXu6CYtNw7vb01xEY5TnLmrp/+5MNIToj4HtR8kFphF/g4o0OJM36ValTgGmd9/FNcdSJbjpiUk1DYjinp08w2fp157ei7HQcNBYB7Ig/3PpyJoCXPlfIkwtImAL6qkRli+BLADhJVnpa1pADkg+B5F9Erm10MO1LuNU5BZUnS3+v4mP+fIN5E5HAULSW2FTkw8Pg5ox5ZeaTKWLgRDGwQ18vtpMspJyn5TwwSNGuymKvVxIAZJ2ZZItKZ4X0ynneDaEb/2J32mfh7JIN8kf0KcxK+ZUUlinQOGj/BzUt/r2DXd+yWBofWXooQxUPs0nfkS0158ybPgeqqyzyzmnGbYKq4WdnxZpwTwFWFJ/d8jrGLMuxp+x5oaAEPvTDhxZHivjvR1mobC8N+x72Iz42zoWnHfB/QBsT6G1kmqrEtJRhC1H4FwpfCaFprf8cb46a3VLzT5hwC0B+WgvOCFsWjZnucjhlYsbgfI0AZcphLclqd0vYG/sIojqdNskxabaoyiDA4oY5UtBXUwFpflOGmjji7i8e5CzLt+1EIeaizEiPHOqgytuomTUGRWtI5pdJOOxq3G78YBVoAFlZ7o/QXB7nTdmf3eK4A0ZLBwQwpY+Pfw+U2VGrmRhxTBmHGidPoggDCqZDnWwajqchw/GeMMGkku45HjIucrvzcFUooC46ovQug4GgUTccfJY2MVHC322QlJ9iYIKbleP6YLEJt9Fv4ubi4HY4ubCQF0pQ5tWDlvMnemE5s3Vf/Dw0FjFP5pNygOifzix8TJ60yjnfhM7VOeppwTbEdi/Ng1s0k7TYCwKlN5tlDKIvOPKqXM1HUl0q0kr6opxkMFGHFG0iQJrgXR79XSdpHjmbKPxYGXJutROKYzqU/qec3Wt6hLcLS98Ds2VVhC+H2P3QNY0L1+OvM3ypaq9xHfl2Z9Dg5587mZ9NOV3mcx4xS3AMYYLsPAN27OyHMUA8GBvOv/6PK8A9pqlWcXy2ReeDWPDspBkRIXQ/t8uBwr3TkQcewgIOJthBfW6V2TUsjFNw7QuiF33LA1VvymIbi4y/OofxT/PwlsbIyyxJi48CIeZ331r08inwXPDVqmVYY2bgwJSMjqHOqbGz0nYq0N3w+LOc4DLTwpVHxbz4ahVc90I76U3o8myk6wzSYTVZkfbsA6H/ye/+obF6bcoJmaFEoDUQFtQn+DFvTgZ/LciKKknJ8wHs36GmD/Y8pXxfV5KvBFk6xH8EFzU3YuotSG/1bf0XiJU/qm4/Iby5JP4S4ov2MaiJGK9SCI+zvU4cTjmjGa/jkxIRVTzNEDDH0FEO9yHO8+HwIfMWtS0hxo5nIpDSIhYNuky8H249ayGJlqb2MMoG7wIHVP8gGC8q6Iw+1G0z4kzRN1n2u29jU3ejVZd1RjsbIpRW6lydDFgecpwyug7pmhe1HfvbBhUxn/JFfyZsYWDriCYxNbUSBwTyyiW8RJ9P7UeRAzHjTmuoH2YuaR+j2iY+eD0PDaFjXG+IYa9fwYvUV5/6ZijVVjSPgeXsjyvAPaxx9/HADQ2dn5PPfkoByUZyMMUqUQMbTPa1KoA1ugYhna0CY1tbXZ311FG64dPSesfAfcwXgDAASgjFFiucbCf5exs2oMbZMFOrS5BkBH6P54KYT478S5rqOOm982CwFnIJhkSr3P8PWDfRLnJtxOjEItQEs4hhahvjST+E3Q+5AkM6zN7iHu2s3xrD8/gvWIY45VEnRNNfeJkhSKIpwUKqpQqNcMMiRTKKsJfwQVpOZKXdzv4TO4AUfMA/X8+HaTLunGGJ+mOifCdMq4rCZtTSNuL+672POmaxyABhhpaRgJP+JmyZNowrMD/GfR7Pw4j5GggSPunOmv3/6RIjN8MPwiLEmGNPW6Se+YY0cblOtyCEzE7hfNbkuszVPc+lSJrnhinehnYZtMgCWXjU/lcpzQp4R5OFUt9yljaN1gpwMVBBA1MEx7PWnCZEb2TvFcwsclGEuBkAEu0QCY2FX+HQv+HZe8SW2CsmhCpThp1o+4s5u9/0DIqB13fUW/SXILVtfv5FCv6Jjy74PPkqH52Ip+xLHoL3Q5oCzHu3dHi44LmZycbPq9KrZtY+/evbjxxhvx6KOPghCCo48++kC6clAOyj+WUApo/wgxtEK5OLDzbEVReSZZCdXv+elBJUeVuJirONdBAhJQFAKuNd4NukwPnCPaS4z3Cm0kcbE+/vWVDSxm02OUxY8bi2Zy5u0Fd+mwsiOU7XjQFB9DG94Q+TE8yzEBgtkm1ZOnCDRtxhaogDS8gYtrOCrQD7cVAMRNFDCFsZ5KGVNZ+an2ZsJcUPB3lJft8V+WJNflsBU8fP3wd/z7+GcdeO5NOpuoKMXom767cFTp4+KXwZoqFjKWnRPPIvx5pC/+M0uSpJiuqY5nMe9OUClrck0QwEhFWES/ven1N3q/3udNATGLrqUJxgr/s8Tmov3yfoj30qXTYWiVdzju3YrrEwuud+F+REJJ4t6jJk9aMrRu85ufyo2asXjQEgUTMe+nSAqVgGgTXc4T2K6pjF5ociwQ3a+4sdi/j2cKRJoytGGDh3eIarwNHxcBYTEeJWGdpDmgZUEAGwJ6flZ3dS+a2ujO20p+Jm7M3JuKoW2WBMxrIQo6Q3uY+n2Sy3FSmEJ4bQ7nEEnKiRDJmhxX8+kFJgcEaBcsWBBbEoExhuuuuw7XXXfdM+7IG97whmd87kE5KM+/sIjLMXPtAyq38lx1A2iuUMaJo5RfketfUixHgqgKjVyoYxjacPIZNeZTFY2QeEskZRCZaUUsZIChpUjcLMMbSDOmRANRkkdFAQUDYFv+SWoMYizTwQAn4JoWvJ7PcEQ3SN+dMKQ4xLAa8j5ICOgHwHVzaWa5DzCsCXNEBWBRhjamrzEidAs3DMJY5BcwqC6PyW3y6/sxtBSajKsULcVZ2ePcKJMUv2g/w2AsCiDiJE6BA2LmDWOSXZ1KuWJNWIxm7nqyn2E9P0E5bO5mHtevxMNjY/rjgHNzN2cN0FO+0WOK+0jqW7Skhvd5s/WWNWeF4g0ozxCpILwWTD3WsRlpY99/wIoFtMFryTjqOHAwBYhJ6nNSf2O/p9E5Huc148a8U8yxQBDnrZD8bgDJDO1UYTux63ao34GfzD+O7zOhXjZ5B+LWhngQHX45vDXdSb6X8HjHrf+RBFbNDFChe+MVBaLtB+53mgxteFoG19n4vvjfx4yXGhrixM/5SJiVOkeYGs8aV6EhRi+I6ZPqrZU0H9XPpirx9kKUZ1SHNj6O4pkPyRve8Aa8/vWvf8bnH5SD8rwLo5CquvH8xdCqyh+jDGSaVjd1IZabXdiiOgVQEGCNMf/cODfGcEZWRkOMnvdTQ0hRUEFiyOVY6WXEmhu8h9BGGNpYvBa86ysxtAlugZaljpvfjtzElTEkILGWa//8qNIkfk98ikKZDLXLWLDsULhdHX7x07iRSmJoAIAoWVTtBKu9+tyjzyIY75wkKpMfjKWmkX6rzONUCrFGbRlnSJkG5gYZ2lhAK+eBqgTEK35xfyaxGc3eqYBS2ExRY76HRTDu1v+dSIY22WXTjTGoTNXPJGDY1JU8dsI1mQcxRpIw0xH+PdI80T2GNv7Y6TK0EZYqpm+R/sesR1PFmE+PoQ3+LcgGdwqX4/A7FxefHZ/8hgXW6fA1XNc/DgjmZfAPjn4UbWdqwNpMYhlaxQsojkGWY+l5VTlJ7vcJHweykKvvYBNmPnBdJL13ofkVYi6bZTmOtqX0N87gGnMcP5b/jAJadU0Ofhf00PHaiRgZkvvK47WDfVKfaZzxzU3wrom0nfAO8+vGd4oxBkJIrAEy0K+EcArXCc69AEimwecRNgTFgeDgNYNtMoSMAbGAliXuSS9kOSBAO2/evAhDu2vXLhBCUCgU0N7ePmUbhBBkMhl0dHTg8MMPx2te8xqce+65B9brg3JQ/tGEMd/lWMbQNp6XbghxbQYjPT1AG7cBhTMlT+XqJZQ9VaGIzXIcUpzVZA6qaCAhYCR+Mh/QMj1wDoMAlPF9lcpxDPiJMrT+xhCryLEgYxFwG4qxgBMCOG50nOPOl5+JcSH+/cXdTySBBmWRGFq1L9pUMbRxn8UwtGGlVfRDHa8wCJhuDG2g2Ly6gYs5Ebg5RFyvkoRQC66S5Tis2DZjzNwm8yWp9rF6PhBieZt0NrZUEaJAmlIGq0Hl7/KcBGCeFCvr2p7XQ8wzkUpTpL3wGhH/ebC/0c+aLi3ed05svPr02mBeDG1cmSsgXhH1r6Ucl8DQNjc4RD1Qgop48nybjigrDO+Lun7Ekg/Bv2OTQiWAK7sRHajwGiTacGJdjpMljjmNkynLxzHWHDzFXIcxxj2svD3bCYOKUB8jfVLX9UCsY/x8ifs+rm0xpr4Hhj8fWcy8amowiOnHdEorSQNFDOsd93u43UTmfSqGNmSsUp+XWAsCTTI6LUNQ+JBAOEiTZJK6Hm8gCtaij+9AlKENbgKq91nUuwCBc8PnywzJij4VF28cbDMUfz395eYfWg4I0O7cuTPymeYp8W9961vxne985znp1EE5KC84URhaQgigGc9L2R511eOAdnqnuTFZGiOL9xSLntjwGGUSDMe5HIcVH8pCyoXCkAaAkbopJDK0AGgTpUcox7YPvuVXkqHlQpRCO3EWe8ZYwOXYZ5CTM+66AUt+aOOKsTr7DK1IYhRSNlSQL9rxlB6C4CNTn6cmXLQTlIpYhlZ+5o95GOiL5tTxagoWmgIfXxGaCqipx0zlbq9RG65X6omCBKzyjE2RFIrGfOhJ1OgRr6wGs3VOff/AFDG0AGzbiylX32PlvmQdY8ZiXUH5uU5s+7wtFvtdREcVz6xZkqRpgKy4a0zN0DZpAzqgN2Fom/bX/z28DvjAoMlzZNE5G1Si4+ZzYnPRfoXXmCliaJvVT/YBevR6lCI2hhbhMRAAKMEImCRxsYJxMqVLcgwjzteHQHej4R9GWnpVRYw+cvrHXztcBzypr82SODl2dNDDcz+8t0zVfuC7absch84TfUhY69X2hMQlhQqvO80eY9goTVn8ehh0vY13cw9LZP9Q/kwKHRBx57EMrapzJTG0blDfCIwdC+pCqk6hHpwUXhF2v2YsvE/F92mqmuUvRHlOshz/s6R8PigH5RmLsPAKMdOyBMD/djeExGUYThJ7GnVop2Jofaspky7HcTGWYSUwiaElCCodPghlEBcQTJtsH3xjS1qTfPYgymiFgZAawxvHajEWn0wraEVX74cEXbtD7bk0utuFY2gjgFaOpfqhwprAP199fgLQJuL+mOGTfVG8dKKJQvgxgYRGzRjaJnNKNWDExU8F+wYkGRHCojEbtgdoXaZHFPp4F9Cokh4+LIm9C//eDJwmtRebkVX8TZn0FAgYgNRh955Z0rsGAFQwtLEW/fg+JsbQNrmvWKDTZCAkQ6R6a8R81tzlWPNcjqO1Wqc8N4YNUb6M/zx0fhQIRt/x6fYnSYjiRi/bTsi6qkpwnjUBo4g37Mm1JgQy4tfMZuPUpM/q9aZ0OY7Ocb7vBNeHiGunnpJ7dpLLcZLrfTBmMf69Va/tf+D/ascZf10xv3xApLafZFCMk7jSYVOVqVGPbba+hZ9ZXNkeywqd3+Q58jCk4DoZ73Ks7iV0Wq6zYc+zQF8TAW1yn2mTvc7/XPQ3Bpyq4D1mrZDXVtuLMU4EjdpBI23c/Uw3XOOFJM8ohlaVHTt2AABKpdKz7sxBOSgvWGE0mDnWSD8vLscB9ucAAK1KJsuN7wBjaF0lhlZuxGGX1BjliTLAUZlO76cGEigTIeI1OWBMZmiZE3U5U74FEB/fJTdJeX1FwYsxvVIaZGjV+qh+Jt7w5qlsIgmKg/ppVPEO9UGyGsFxDTO0JNSwRkQSrQRwE6cHe9dq6nIsFPwYZl0IUZ5Z0yQmistxQJlR5pnatzC4iUtgCAhAy8MCKLSguyCNnztxzHP4WSTG3SH4rKejQIW/o01AMGOA3aDIZPSgC3wc8GfJ4It6DG1zdj567WD7QXATe50m4xt7DWlUiqJ6VflrztByQCsUvUgcaTPlWvkqCUA0j8GNlruZqn7uM9MvBaBNzkLOvw/de0xG8lgwSlnsuukDxKCyHp8xNrn3000K1ay8lLh+HCPuXzsBoKkMbQLTl2SAi2O5eV+bA051HlhhZg7K81DcSlW7ZySuNbZ30WuHjQ/N+igkzkgg24t4G0WPs0MMdLPHrCa6E+2r64YTtwe47pRzAwDc0A3GGaXDEsm9EfhO6XfC/Jbea2K9UPutGGMphQwfkW3GvBeBsYnx7Aok+YzpTzj51FS63QtFnjWgnT9//nPRj4NyUF7YoiaFAp4/QKssZAfE0CqbjVzcprIuh0RuMtTf0NT+AICtuqIqClCjEXW30ggJxs3YCkgMle2RfQQDc1hs/BagMLQSHEc3SXl9FbjFMRMhxclVGOpEl+NAHGDou5BCqPYviaGNy2otrK+qy7TaFv8j3oU50EhIZFIoBZAmWZODLschQEuau0SGz+PjTCOfB/oWY1zQ9chhAACd2XAEoGVaxPWqGWMWAFCh45qxJUkMbbN3yo15V9S+qG1YNkW+YKA+5K856n0Q778kBhoAqMPfqSQFKE4ifQm9X3HSLIt0s2sEmETB0AYAbZM2oPM6tKzunR/8Pi7WX36X5PqtXHMql+XIexIwVjS/5oGK6nLcLMGZkADz7XUznOwNQHLZnhBDFOci7l+72TiLn83vPdbtOdDPaBtq6a+4NQoAmJ6ZMilU0jx1EgwrkaR5kXdX3X/ijaZAaG9Q2w+PRbN3QDnUjgGESX30s1ZH1x0h0SzH0fGwFYZW06Z+ZwL5JhAP6IIgfXoMbRhsT6d2t2g2zqChAuTkcA7hsuX9UPdr+G7GDMkMLUL36l8zBvA2ydUhPptuPfQXkjwnLscH5aD8nxfq+MmgAJ7p+HmoQxtwf5li41fFUgCl3NCeocsxg18rL6woBkGHUICC2YLFZTQEN3lHzeQaKtujCnOjjIjftqcgKOA73L4aw+sn5Yi2F7ak+pkoVXCvgopQDG04uU9MUiMB3gS4DvdC9i/swsS860mXYxLc2ISSgpDFQbYb/SyWoQ0rhXGuuaFj1PObsmqKohwoj5SUoEtlOJo0rLocM2ghdiU+oZg0hKjW/AjT1URZV9mMJuA00F5MEpQ4EbHc+XzQPh2+DwLS1OVYxPDFJz5JunboOAn8p3dfSe0EvhP9i2HHw26JiW0Qr2wP9WOJVYkrRxMnEcZNfD6Fy3EEDKhtPlcuxzLLsf9ZLBseulXbic7HpGzGcWCShp6FZGgTwjSSZDoZo5P6JiRfMOA60fF2KYtkg408Ez0ljdBJzzkJL8W5bQNRDxaGoKEtAH7jxjYEJsPrcnifa7qequBZ7HXT8A7w98xkcB6ew3HVCay6v4iYpjaFV0SQoeWJjtT2vc+Vc6hLp1W2R3XHDe9fSSA7bLQJfJcQGqJKOIN8wNhJfRDLaJSp99l05fmF5ls6rSXOwbh1kdJg4qh/lqRQBwHtQTkoz4W4dgjQPl8MrQpop79K1ZXNRnWdDcgUzbkBhjYB0Ma4REYVJR/EqYu0PEZhaMMuxwwAc5Kt+NJaHAKvQNSaTpTj4yz24Y1HdQsTACy8/7kxscrh8+Ncw3xAG9Y2gufydplngvUfmXov/G/eXoPFJy6Lc0WeTgxtnDU/4nJMVJfjJiBQmR/qWCclhVK9DJoZ6jlDK2Jow4A2QSmJU/RD12imaAcSj8QkTIkTtb04g4/ahtWgyBXMwOfqffjxlcmAtmF5gDaOhUhgHiKHyvflABnaZkAnhvWN+6zZM5dle0Td6jCoi3H3lO02ZWi9z6dwOQ6vR80yxALN2aupRH1WcZ4qYUNMo64aM73zElyLrRhPGnGSZJkSACP/rvk4AVO8R2ju2l8smbBtGgv0Im7m4bXLSEsjdFLioKTuJ82fKIMK6Lpq0FP2n5gM0uGcBOHxi3iFxHcv8qUs8xVzQ1FAi0AfhKjrS/j+aYzLa63uf6gbWmCOh71pGI16sqjPS7jUBt1mpwdoA0bsyP6VAGib6AHBvS6BoQ0Zq4NZ7xVAywDbCr5jcQxtOL9CNmckuiTH3RFjyUaYF7JMy+V40aJFf+9+gBCCbdu2/d2vc1AOyt9FXBvQldfpHwDQHkgMbaOuuvd454UZ2qlim5RNV26CTRha1WIeYG4VVlFVTAKp+l0HDISX41D7yHiG5dgaiMo9xFm8JcPgtaMR0pSxCCt3alyPnWABT4q1ApRzYti8JJdjmXBDUYaYh2fDlXmCafoJXObCTgK0TRjaQJbjBBdM9blFN/lplu0R4JiyKQEtoyw0BslzNYW6BLQUWmgOxHdIPDaVeYywJdNlaKfp6qW+O80Al0spqlUHbW2pwOeRhE0AwjWfVbEbohRWzHfTZDBlzHmT46ejdIbbDJdiiZtnzYQRAzBSfux0aNyb3V+QRYsHOk0BMYtZj5Q/n2mW47AIo0VcfF3StQGgXvOBRtOkUIwFDJ/hvlqWmD/caBKfGT65/83id1Vp9syLRROW5aIRAofc5Th0nfDY6BkZQzsVUxcW1Riqvt9x7qOargFegooAKGzC0NKY/YqfE29giZO4fiUZVQNt0oTxUv6MGHfVpETer5WyP89MgwTO0bSg91KcrqEaXhxR81j5njo0Ng45LOp2FJ5rieEYTdYb9ZSkdUB6ryk2eSEBfYExaViMXEfdN0L9LhRNVCv++AY8TmKNFsE16Z8Dzk4T0O7cuTMxwcZzIc0SeByUg/KCkH8UhtZlMDIanDo9IIZWjWFlLgMIQCKW2ikUDaUOLaMMukkiC69lqUywD4ADDJSHl7jLsX++jKGlDLBrYEY20gcXPMNyXAwYP5n/iAOPARAG5rkce3/HMbRh1kWJcwqzFfKcJqBLfKd+rLocMxblTcUGGWC+PUCr5IaJMrSUwGUUVoLLcdyjdjyNQ1MY1iRrsqp8RJNCKYC2yVYqM3uGwOp0Mk4nMZ+MMWS1ig9omRaIObTq8SfGA6hgP5IyXIr+yeOmGUNrB4wCyecIRaY1BGiDrKGf3deJYYIA/92MU9qbATZV4jISh6VZcpkkoW4wtkycos6LpomZNAPESMOiXh2zBGNS7LlK/8JGLPFdOPwgcAyNYWjVdecAgV+y8Gesgk6XMhASbC88TtWqvwYkGSLFearSHOyv/3yaH5fce591n2qfSf6+WDJhWzSwzwCeoVNcPLQHyGN0f8+2E66R1P9g2TulrzGAVtcUhlZ5FnFu7zLJngC0TWJVeYPx/ePXjhrIovtTcumgZnM4fF7AqOIdV6mEGFrVONLM+Cr6HPP+qwDfdSkaDReGQZobF5Uxa+Y5EeiPNNrEGR38c8KGFHkdOd4s8JP3J6gvNJL2IOX3cJLKQtFEf19VuV7U6yLQVmS//OeAtNN2ORZpz/8e/w7KQXnBi/sPEkPrAGaWv9bPFNC6LkMqp8UA2uZt1GvC6sxAXUBPkwhLLBZuTSeBLLYBQK3xz3VC4Dj+57bK0Np1roCEhDIGOMlWfKHkx8UQScAMH9DGupqK/oQ2L0cprRAHmIHgOIet7WKzjKsxpxES7zrkfRrc7INH6iAASOBzAgIKCjsCaKMbrhDbdqEh6BtWr4eVHPG58txCz2K6WY4txW1bVVDjMk6HWdykqWrbFFmtGgC0FvXtumFFWIhMlhPIiBk8ZtpZjkOxYUkyXVa0WuV9bgkBWlX5JeBufYyxRKVLKKVx7/l0YkzNlBY7TmEJK+XTYVVsh4VcY3kbdXXdaOa+DgPQU2gwPkZhhrYpIFUOFWuc/E6c3+QeGFjThGHxzNyB60UyjEBdyx2KdCbszxn8s1aJjmGsQZAhEaiq2Vldh6FSPvAa7LTJWqtKs+8LJROWFWXqeCZZ73fvs/AzZ57LMWMs3rW6iSStv3HPVq3up64ZcXPQj0f2xpaG352QcahJHwNAWxqfk/cn/zzPaBMZU6Xvoe/Uv8X7rjK0mhbyBGFBRBvnoRC3bgUNhRRWI2a+hyTJNZe3Efw7lfLK23kXasR4KATGIWHeCJAqk0uFgLi0tVCG8sTUXlNu6DLFognqGa+AYAKuWL2BBtekfxYYNi2GVpTmOSgH5aAkyD8KQ+swmFmC2ijgWtNfpQIuxxQwMhpIObjJTJXaXYAYRkU/dDihPgjFWE1iQGlQUaSEbyA6CBp1KhkGGZfqMg5otSig5Qxt0J2GaLxPmYwO6vKF3HEYUmktuMlLoMRgMwodRG5AYnxUtiPsGuSnzw/GxAhhYMH7DCkncSBYbJYaAKrHsSb8p7qR+oCB/0xBg4tgNkcNGmdoEx5qLEPruNBIUFkIb/ASaCj3GVZ2phtDqz5vtY3Y+D4aZBGT2m3UKXKkJrNju9BhuQZMU4Nt01iFTvQBCMVxhgapeeIm5Ti3ubLhtze999dnaIPvQ0A5I4QbkWh8RnEgOK6UMmgKkxQ35poOUJcbp8AYNJLEZAclrDTWEkBSsG80Ns4/4C7bjJ3SPZdjmkImTSJrWVOGVmm4XndhmETJuM4/TxpTfn4MEFYuF2dEeSaMiXivfGDEYNsM2aweXHdC8zaOoU1yrSwnAFXXpXIMHYcG2Dghuh5VxANtOCzwM0maJoXKmxjYV4sYGylV3tcYoxsAMI0nhbJtesAKvpsADqZmmxW2MGYeiHkuwFwks3qoFE5ThlYZEjF/w3tQLGgURqowoFV+D4PxOO+SWjU4JwIJE0PUWpxBp1lZIwBgLoVFXWSyegA8hyUpxETXObOr7vG5vM6v6/1dq0Xbnar0EuCvD/KemfqdAv4ZMDkZT4QEknCFGdqSAcqAXM5AteIE1pQ44zRlyZm5X8gyLUB7sDTPQTkoU4hrA1owhpY9b4BWk79PV4LKIoORIdBAAot7s8QnAFfasjkdzLtupmRgYl9wcRabYjqty8XfcULKKhhcMOjQ0Gi4KLWkMD5mSeXVdRlg1+DqmUDbBAAljCeFUjaqbMZAteqg6FnvhXKXyxkBJVgu8AywQaETnhWWMSY3MjXWp151kU5raDQ46I6LoQ0rGEGGNmxtdyPugZKhBYGrMNfQvO+8YwMKhGyXAxKDaHCYG9jYDBiwmQ3bi+XSQUCVVFCxbqe2A40Et4yIUuh1o1bn95LNGbAt3yghygnJ45tMKVU5sBout+rTqCEB8JVo8TySYlPrdQdZvSpjryl0NFwT+YKBsVELtVoCoKVBC71pahFgFhdfGL7PcD3FZsBlKqZKiAC0kRjaQNMEus4zXSexCJbNIOaM41CkUr7xIg7wpVIa6jUK0+S1fInmZ9JuBhDD68jk5NRsnq0AWqIUVS5PKmCsaWImAhicoU2ntagxqSnD6kuj4aJQMDE2aomGAQTnasTlUVk//I9UVidGUU/sTUIfGZOeD2KNIWCwLBfFoonREX8dbjZvxXdhAM6/oygnAAXH5kYnM6XBcVgsoMjlDUxOxJ9PiD9npoqxTmLTCeFz0mpEDVM8Dpv/LsY+fAzT02CO1ZStT5JAPKIaqzqFi6o6b2px7J/SV0KizGWSt0VYTFMLJPqzYgyuvL8xfYjxAgKCnhZho0xczgPhSSLPb7L4xwHaqKcPBaU+EnYdbqDNpKdgaNWkaSFA6zoUmk6kUSWbNTA2asv+xL0XatbkJMNWI+T9EnDXDrHZ5XJ8G0lhKwBnaMGAXE5HteIEDZBxw8xYIP76n8VT9mCW42cg1WoVV111FU444QS0t7cjn8/j0EMPxUc/+lHs2rXrOb3WunXr8J73vAeLFy9GNptFV1cXXvSiF+GHP/whHKe5Zfuaa64BIWRa/6655prntN//5yTC0KaeH4bWZc/I5bheD84lPavBAJEsjaaRpjGCoo1C0ZSLbaZFh1OngcVSKE+ZjA7XoSgUDTg2DbiyUQAOKAyPoS0UOYiq1Vx+vEMBuw6XBBV4HQQgHMirSrtu8nsolkw4DpXKZTZnBJQPaQUHYDN+fQauQIlbUGP9azUHhZLpfc6Vl1zeCLDJYVAhrqFp0U1JuEsFLbHMO5OAeoDWIERmyqQxCrUosSLaSQnwplxPANoGYyCIbgRxM8eOY2i9mCV5bWXjT2d0pFIabIsik+XnOawRYGhpQlZIfk/+M6xVXRSKfKytBoVpBr0HHIehUrHlMUn7c6PmIKf7sUaM6GiwNAoFQ14nTgQYF0pZqcWMMEn1mptY+1Y8C9UwAjRP/hNmd5LSTExOcLDS3hn1WBDnEO9d5gxt/EXV59QsmZsQ4Y5nGgS6oXG3eOX5q/NCFRpaR0aGG4G+xonjUDTqLjSdBFyb1XWjmU7mugxMT8HyGNqwNHWRVr6q11zkcr5RR1xTXW+yuaDRh4HPK3XOPluXY9OMvrEitl2sBcSraSnWKCHheaWy3IL5qcU8P9dhKIeMD2IO2A6PW83n+Xo+OhJ9ps1cQdNpXRoUkzLF+v31xjr0GAkBUmnuaRFJUhSTDZsbpxSl3kgDrtXUMJUkAc8Nta/1qI6WVI6rHrP2+AwtZx5lLXDv8VcrTmQuxL1Hpum/M5blBsJ9VGnK0Ibmqev6IYPh8Y7LoVALeQIEvCRC0z0W0Ib6ltXqkdhwMU5A8noSfD6KIcozUqqeKaItcZ0wywxM7TYO8PEQ71Mmq3MPGG8PFx4q+YIBx6WJ7LIafxv2mBH7nlibrCliaCnlc0/sQ1N5371Q5CCgPUDZunUrjj76aHz84x/H6tWrMTo6imq1ik2bNuEb3/gGjjzySNx6663PybV+/OMf47jjjsPVV1+N7du3o16vY2hoCA888AD+5V/+BaeddhqGhoaek2sdlGcujDGeHdHwARZRSgD8bwq1eVIoAHCnmcgFCLocUwYgxeM2xWaZSmlNa0sCXNEoFk3A03kyJZ27HyvnicW6UDThuAyllhRsJ+iK64LBZQw6IbAaFMUSH1fGgJaWFN9YrQpsZAKbuQEN0AHm+m50hAAa4T+zWc4WSobWA59CBNhgABxwl2dGg5k9xSZpmhpqinJLCIFtU5QU5VHTQvs08S21uq5FGDjb5rVE4xlawBEMLYjcDIViEpc9WvQ644FQNdGJSUzYzEEdLtLQA6yppsVvglYMQ9uou4EyFCrDk8no0pU37VnNHWpBIz5ob+aCqCoHk5M22trT8l7TISu8bXNFQALahKnfGBtBIMsydDRoBoUCby/OpUy9t2rVASF8/objDOt1F4YR3VJV1l0AZl9pSn6nXIcGxla0pf4EgNFRC5oGdM/gSdLUc3RPiSIgPAm7ZGijA1S3OFAHosqrrSg/ftseoDU16BoBUeLiqlUH2Vw8gAkztAFAK+4vdC3x3mYyugTmAAKMYTMQ6DgUDlKg0JFKxSRGqjhS4YwowsrL0Ki7AWDmu/xTpNO800IJVk+vVR0YyloVZulSqXAMIYtVyMVnYmxNb8shGqSxSV0LHJspyq73DoaercqcCeW8VnMCir1gUMMxtJmM32al7KDUkoLjMAwN1iL9T5tNAG1Gk+tTEkMr2pNx0yz8Pd+vbIsbLdX3QAWWvtHFgaa8B0zjYUJxcZIA5PONk4bnhaK2D8QbyALMprLGxa09PL6Sx49ns74BVtxbve4g7xnjxDsTXjP4l36/1D6FxzqOYfRrsfvHijVNBavq+lCp+IYPcd6kEhsafsKRmt5i39N841/DcgPPIKvXIjG0jXpMDG1oOFQAqgJUw+BlApVprwBab87EJGxSjSWJMbQNKp9TNsv1oqzXtnDPb21NwbFZrLs+EHU/V6XUwheCjPeOS0BL4vdyBv4+Cy+cZmz5C0kOAtoDkMnJSbz85S/Hli1bAADvete7cPfdd+Ohhx7CF77wBRQKBUxMTOB1r3sdnnjiiWd1rdtvvx3vfe97YVkWZsyYge985zt49NFH8ac//QkXX3wxAGDlypW46KKL4DbTCj258847sXbt2sR/r371q59Vf/9Pi1Xlq0am6H/2PMXQOg2KVF4H0RCJX20mdc9FFOAuv4INzHhKq26Qpi6QIi61UDQlOEqXPGWnoQJavqnl8jpch6FUMkFdFoyF865vQEO94QRAYrElBcemYOVh1LUW5PI+wNIJ4RmSXYZalVtECeGKjmFwZsd2qHQrzeWCbGit4vI2PJdng2iR+F4xSKk0B7SZjO4nYrBpIDGP2MCkMN8Kb5gkoNhQypWWfMFU2GAP5BYM3i/dB7RCaRGbs7qRuiLbqKescUDL/ERYjMEkBixmo0aBlKcJid6YRjRxD78/F7oHaIWSUau5IGqspTdHypM2iiVTul8KAEqZCw0amNe3xGzU3niK+yxP2jKLr3BtVMVxPEBbEAxtwtzvW4sazQHg40uhoUYzKBZ4e3EuZWp/ahUH2awhFWdV6jVXAkhVhKIE+AqUAL5JDC1jvPSJypIx5gPhAKAdbqC1LS0VOVMBR+mUYCv85CaNBoUWA6QrNa5UAUGlz/WycIaZIPHYdYOAaJwBlkpzzUUuH2QGZXshhnBsVKyTvlnFCCnlts0NS8JIIvpXVRTnZJ2MMxqVBp+7xVw4zpG7MycxiCr2rVQcpDPRGPBKxZZKZTH03lPKUKu58UADHICaKT10TvydCEY0m+XX0HWxPvvJ1oKAlnIjI4CMd04Y0KoJnMSzqVXdwBzTdQ6Ow8mexJg16i7qNVe+o/v7G/xdUNsw4+8f8Bla26aJ9y7WnDCwUn9PpXRYlovyhB0Yb2GwVY11jUodKrRytAzgRBlazXs0YUOFKvWaK/cidW7FJccKMHoKkxYHVET5I0p9Zg8ATG/9qFVduT8Kg0WcUU01rgpjb7EU9TKJYxjjSjmpex6l3MVcfX/EOkqIb8CanLDkfGCeC7g0AiQwtIQQOcfF/iikaFYD5zgOQ7nM9x21zfCsU41J6rPWNL5Oq15YYg0TBtJqDEOrGvqTYswBH8C2tKbgUibfYWEkKrWmYFsUk+NRIoQbjqJMt5D2Dv7e5XO8v+UJ4QkU/84xyvUBsY/+k+DZ6cXQHqjcdddduPfee/H4449jaGgIk5OTKBaL6OzsxLHHHouzzz4b55577t/j0n9X+epXv4rNmzcDAK666ipcccUV8rtTTjkFZ555Js444wxUq1V8+MMfxn333feMrmPbNv71X/8VlFKUSiU8+OCDWLx4sfz+ggsuwPvf/358//vfxwMPPIBf/OIXuPzyy5u2uXTpUixYsOAZ9eegTCH1SQAAST//gNauMeTaNZhZDXZt+gxtveZKJZ2CwSb83JS3mWgeA5kkwvra3pGWeXAzHqC16xTpom+NzOUMuWkIJbBW92MkHTAwHdAdgnrNlawRALS0mtjby4DKMKpaC7I5HZMTfIHWQEAJAIcv+rqhgdnccq7rmrw/sYHk8gbGx3i/RZysSfjO7zIKnRjcXVAB22KvKxRMTIxbmD0nJ+PGGAPalMQ8haIZiBmjYPKZqEo5wDdKxvj9qeLY3I3ZqGtwDc9qzYgETkLJmFRiCcVnLrjFUvcyJAtFttGwkSImbGqjoQEFoqPOXF7aBwTpVHwmYdtxJAukewmGJifsgFIpFKSxMQullpQEK0LZYaAgRJdxWc3c2C2LW9urFQflSRtz5xfkd0YIXDk2Ra3qIF+MKpWqGLsfxbBT4uOoEVCmoewUsLjVm59N4jlti9d7zeZ1/sxD70Ot5kSUJ9FXVwJ9/pxSaQ31upsIvGtVF4zxcVMVXTHWKks5OmKhvSMtlZNM2kC9xpWiXN5ApeJA88AOo1zpIqBAKGN1tUHQ0uqx4Mq9ifmfTgf7omlEAgTxU+iKtaoTMDapEi6JMi7iURVwoRskoCg6DsXkBFdWJ8YtCdrEeArGKByD7o0aV3br/H5LBYD1K0Y2bz1IpTRU4jqsNDgxbqHFA/08UyuT/WhtS2Fwfz3i4uu61GP2o675AAc1YWOBUPgDd0H8+SBANa9pSmGagGUJ918GHvlI4LhUKvhCoQ4bkcqTjsK48e/qNSdg8iAaNwaGY2jFez3hrf9ibIYGa1BCnQHEM4fiuoapBUJPdJ1EmVpCgg0i9KwJz7Rt27yf6rok5rChGKLKY5XA++oQvmcLt2rZN4PAcpncL+LmmAC0lbITMIDExRyr56quunHMsG1R+Xkmo2N8jH+eyeqo1bgRoas7C6CCTMZApewindEC8eb8vfCNTRJAtZiRPT3MDhLixwfHJbhybAbX5XuXaWqoeX5BAsiLeFTGGH8mQIA1NAz+vMIeNSJsBoTPBdvme2RLa0p6dLSny9ipYFrbZp6+EAxFivRZjVv2wKHm5RcI70fCwCfm4lQGionx5P0jXzSBfXW0d6TRu7sivSwESG5tTWF4uBHbRr5gSENPOM+DYRDJtAqD+pgHinWNxBqnqVcVIJUW+8I/B6J9Thnam2++GUuXLsUFF1yAr3zlK7jrrruwZs0abN26FWvWrMFdd92Fr3zlKzj//POxbNky3HLLLc/l5f+uYts2vvOd7wAAli9fjo9+9KORY0499VS84x3vAADcf//9WLVq1TO61k033YTt27cDAD7xiU8EwKyQr371q2hra5O/H5TnUTxAG2Ron58YWqdOYWQJzNyBAVrLiz0h4C6/VZsvsqZnFida8+yT42N8Ae3sykD3lpVMiy77JKRa4S5SYoPo7OaJnXjMnecqzSiIQWAQgnLZQUeXn/yptS3NN+HyECq0hFzOgKYRGBrnJ5jG4Drcqq0qUIZJYJgclIu+trallaQbPE5W91R9B4zH0HqgTYo3BEKhyGR1pNO63BDaOnxAm/cUet1Tmyg4g24YJKKwCVdsFbyL5FKFggkDBJZnZEhDh+YBWqGcTShWXQEEKGjAPVkkAqnWLcnQNhiRWZAFE5EyozE6AI+hNby4ZbGBTkxYAeVcgOmJMQutbSmpxBsGLxtEGYVGNDBPg2mWBbTuxUwDXDFU66zGMXjcIOCVZUlwWyxt/yOeLB8JQAASggm3iPZWjwluknHXcTjzn8v5WZHD/RVXVZVp0/TdKUVsYRybo4qYc4IVMkJkpwqOhgfr6OrOSPYurTBJYj4Rj6V3Xa70xRWBsmxNKkQqWBdz0/DaF5d2KYNuaLAs6jO03g1Vq44EUGHX07AhYHxcGJV8uBJmFsR729Ka4uDHm2dScU5gIuQ1HYqJGh/zUj6Y8Vvcn2CCwqIeOz5myXXFMDQ5z8qKS7xgQoW4DsP4qBUYB/W5i3jz4DWjz4cQSE8HAYBFzLZp2ND4285rkesAgwbbYujy1tiMdDkOtq3GYUrmu+oGQIam8ecWjqEVRpTJEKDt+bKAMwABAABJREFU21PxMgv7x6pGqLDrPCF8fRKAyohhc6d6xgReUiiL9zMYTsJBQCqly88nxi1QRQW2wcOExL2IvuneHijcq0lMPxoNJbaaRdf1SF8FwxlIfBcNMXAcP0QmmzUk4BLj3mi40mAh1gqVxfSF+eEAEtCmInt6uGQMIQSWTaXHSFgcm8pzTFOT9yVAmaGExgijLVHWCeGBEmbl5fxnkPtXpezI+WXqDsxI2Ak/Jx8ypKkeT0Cw1JcYW94PL1GS8gg6OoWBjx83GVNSR2Wuw++HKqJf7Z0ZMMrk+qgytFbDjd0T83lDyU8RzMOQzRnSgNHW7gFaz0gY9x4JqVUd5AUDnXjUC0ueM0D70Y9+FK95zWuwbds2TKf27JYtW3DxxRfjYx/72HPVhb+r3HvvvRgfHwcAvPWtb4UWDijyRGVKb7rppmd0rZtvvjm2PVVyuRwuvfRSAMD69eslc3xQngepT/CfKqBN5bgr8v+y2HUKI+0xtNXpA1rbptJdmIJhtOpZ+JjHBGjNGVoBEjs60xLAZUqei5sCaCcneOIesZF2z/AAreLy5zIGLcWBoG1RqZCJ4x2bAsM7MeTORLFkgmgEBvg+xIi/8UoXaspgmprHqjGMjXKltFTy3XtFYgadkUCWZUqZvDfDJBH3K8MgyGR8JalnTk72VSiJhgS0DK7FkM7okuEUIhRzscEIBtZ1KEotJnSioQEKU9dgEk0qd+KZqBupYFksUOjQoOkIMLS1uoWUxmNoKTTspzW48GP2sika615er1swvFJJOc+tsjJpBxQd0Z/xcc7Qqi5lzHPmJvAzbjZzY69UbGkhr1YcdHT5xgLNiAIeAJgxk8eRxjHMbMPdKI09icerJ/I2dM7QTrgltOUdaDoJuLAKUd3rJsYtFIrclTocU16etGNjd1MKmyvYBRHXmAS8J7xET0IJEsqyOFqNeRror2HO/Lw0MmQUcCRAll/Sxcu2Gcslx7scC4VLuj97Pxybu0TX666MU5eueRUHqUjiIu+80DMfGqzzPjH/BsNA37EpJsZtlEpmwJggmEEV7PhxkX4jrktRrvH+lHJOgBn3QXFsd/3M34xhYtzPeGooiXZ4jLdn7Andt0u5gskY5NiF3/1sNgxoo/0ghEgF1Qff3t+o8O+991ONye30DIK5XHx8dGDt9ebj+JgVmGMaIV4scJAdEvcqEpMJo1PvrkoEAAkjjKYpRg4F0KoMbTTpVfOkYUJMLwldedIOjLFg4gQrxhjD+CRktnMAcEgGcC0JxqR7v4xNFXth9Lr1uu9yHDSWxAMccS9Bl+MoU2/bTK4FpRZTPhPxrtdqrgxtEWybavhTPTpUY5NoL8zWi2vJ8zWPJQ7X7PWG1rJ91l5TwLgAfsJIbXkeNLwv/hiFPW2E+CX9fMN0pWyj5HkwFYxGpMqBMBqGw1GEiD01HLcsDEXCgKzOG2GgtqThOAbQKu9Ts4zt4h3r6EjzCDXP8DUxbsM0NRQKhmTjiRbMI1AspeSaLEC4mI/ZrC4Bbclbv4XXS5z7OcDHv1r1585BhlaRq666Ct/85jcBePFZpolXvOIV+PKXv4zrr78ef/zjH3H99dfjy1/+Ml75ylfCNP04p29+85u46qqrnotu/F3lgQcekL+fccYZiccdf/zxyOW4Uvvggw8+q2stW7YMM2fOTDxO7cczvdZBeQ5kfB//WVKeVWmm//n/ojh1CjOjIZXTp83QctdHrsxq4Mpy/ygH40Rpohn4kAxtdwamt4vmOvhiadf9xXJ4sI6OrrQEHCKRjW352Ywtyu/B8FZ0oZARAnR0Zrh7b6OK3vostLalQcBL03BHVr+2qshMS12+cZqee5NgetSYP7ERmR7Ychgv2+M4DGPevbW0pORmJ5RCy6ISnADAbAXQCkt+ynPTpWBgNlAqmdAVdgfwLfmCgcmKZCte4iwDBA3qIpvSYSixhqIflUByHP6z4dXS1XXNA7SeQlNrIKtlUKf8nh0ieUUAQEa3YutQlit1GCQFh1oSYLmu365aumh4sIF2b+MW/WTMBWUUBBoIEQxtE0BbdqQLLAD0zM7L37WQdivamdnjzacQ2GTlYdBfvAMD+WPRhyW8DY3ApQQNmkGRDsA0CKqVqNsfkQCOBtx7w30fG7VkvJjaPcPwjx0cqAHwgWpSDLFQCIsi2YcAPN5tqczK8FADc+cVoOtEZnoVMnMWHw8NnD0Rig8NuRsLEaBMvTcBMgQgUcdDxhITX2lu1F2e1TcdZHSFhBmIkeFGhJkKA33HYdxI0pri7vre/JycsHniGJ3fFRhDyRj3zvLbdB1gwubvZnH/o2COA2bVZBvNhEp3Q0fGNAIc4FPKMwmrro4RVoQBoyN1nlU0FtA6kczISSKegVDaZZZwaxQAkCJ8rSz4yxBK1Y38vj0mLzxvecIhP7u11XBRrTgBJVcm5gklvRFeASJ0o90DAHHJc8QzU4GPeI+JRrxyP4LZaw5o4+JZGeP9YYwb1IKAlvdbgL1K7w5YNBTeAe5yPDlhBWLhwwncwmsPIOI7hdeF6oIanxhSD3nYNOouXJdFMvRyVtxn8IQrrgDPVsPPYi3AS2dXEOiJ9oSxSYCd9o5MZJ2X5ajEeeDzRXiWCBG36HhGPnGs+LxS5knWVBAp4ph13d934wwXgCgbRmQ4A+C5HHvvWE4rw9J4CIp43wSgTSUAWgmuFUBbnuTJw4RR2rbcAGsuGGFpQIt5nqqBqBlDK+611MITP4rY59HRhtxThOEg5SXaA7gXRiqtrHneNVJKErq6MFJ4CTSFzpIUt88YC4SF/LPE0D5rQLtnzx585jOf4T76jOFVr3oVduzYgVtuuQVXXnklLr30Urz85S/HpZdeiiuvvBI333wzdu7ciYsuuggAH9jPfvaz2LNnz7O+mb+nrF+/Xv5+6KGHJh5nGAaWLOEK04YNGw74OuVyGb29vVNeJ/z9VNd629vehp6eHqRSKXR2duLkk0/Gpz/9aezdu/eA+3hQgsLG9nKNqkUBtG1zgPok2MT+/9W+2HUKI6vByGqwE0qQhGXrJq4AzuzJeQwtsG+IK3uOt8AKC3qSjI5wpbS1LQXTU5bznUagDQAYGmqgozMjNwG11IiIP61TF+m8LpleyTDkDbmIu9CxaWIBV1AIoEOHRiioXUXDi+NxHZ5gxHa4O7OIrxr33GFB/Jg/sZFniA4K7nZtgPANe4wrOCpAE+WExsds6dapaf4GCPhWZlk2hzEQCnTNyHKXY0XhEhuhcOvMeyDZdRlaWk2eIIu6SBkaDOI7jIpxrIZKIgBAjTnQCYFu8kRX0uW42kBWy6LKErJ5lnfDtqPxnZOVGgwtDZfZsRlsRWknq+FiaLCOWbOzMvFEpWyDwgVjLgghsmRznGszwJ9dveYGkmyp7HcY8IixlgytWjR+dA/o188EGhX8qf1LUrHRdCKZytLfvggTdZQnomECwjAhFLu29jQ3jqilkijDxIQtgabonUiYJO6zv98DtAWRoCf+/kc9JrfDAwiGEcy2GZZ5C3ywbypWeaGwEKLxLNujI17/4hWd7kc+CyCopAk3UJmoRdaqVUpcMM4oUOq7VQuFLOzyF45TGx+zIkxNOBOyZVEMD9XR1p72XI59timdIjgs8xTajDEwcNY9LK5LMTRko2BUkd3/BJjdAP3vo8D6N2JkqBG45/AQi7k1uJ8zyYLlNkwNlDF5voydjXlErsvvQSiY6typKBmWk1jisIh2XBcgYGAWX8NNj7VSaxLP/MObocNBLh/Ncuw6vMRNq7f2Og6VynCAJSZRdgvwWSfxzIUBJU4Ey6URRKwcBHz8BVsfl1xN/SRccxmAjOMEgJGhBij1WS5hyBGAe+TGr0TOt5EC9m/F2Op7YGh+DLOm+fOdXyf6gGs1H2ypifrigD3gJ2sTc06MuTB0acqaM6kytN57UVASj4lzxJqoMrR+T32GdmS4gWLJRC6nR4xLYeAKwufqvj2egTtinPKfmcrIV6s8SZR4jvu9dU/Tgga+JJdY12EoFPl9iHXEtpi8txIZRp1xQCuMMeJeMgnJ3UTZLLWO+dioBUKINCTYDg28/4IJF/M+DrAKEFqvu7EGUcBLjuX1TyxtrcI9eLiB9s40TFOD5dUbzihjZ5hawIgnDBLivgtFU86fokcKiMRSSUCVMf6M4owwL2R51oD2Jz/5Cep1PqHf8pa34KabbkJPT0/Tc2bNmoXf/e53uOyyywAA9XodP/3pT59tV/6uIgB3Pp9Ha2tr02Pnzp0LABgcHESjcWBxlCqwnzNnzrSuA0CC4CS57777sG/fPti2jeHhYTz66KP4whe+gCVLluBHP/rRAfXxoIRkcBvQNgdE8xdSsuxsIJUD/dmbwRqxqUaec6Eug1WhSBc0pA4ghnbtk9y6v2RpCRoIXDDUPbDDvPWbu+MkL3r9fTXMmJVFKqXDJAREB7KtntKu9GN4qI6OzjSsBk9IoJZfEfG0lusi12JIIDjDU5LyecOP9WpbhB0jbZxRYtw1Wjd0wKnKvouNxrEZdA2STRoarKO9M+3FsXoKhZe8KOdl8bUZhUE0NBouRkYaYJS7U4t1v17nJSqGB+tyk017GVgBvslMjFnQAJ5oCpyhNQjB3Hl5GIYWcE8dHm5wVzzvb5Eciroc0JuEoOo6MDQNJtElKHBs7h4cTuahA6h6iZ50gwNg29vIR8bLyGlZWJIdCT5LI18CpQTuTZ8MfF6p1GFqaTjUio3TEgxt/z6uvPTMzsO2KTIZzWMvbVBwhtZMNXc5VksZCOmZ7QNaqRwrMVqtbSnJdPFEIy7oI78E/dyRQG0M2sf+im0jbb7ro6JLzXzFW2G4VQzv7o/0RYAM22YYHfGt6WHLPHWZV8cQfqy1lwVb3OfeXq4YtrdHky+p0rubrxnC5U0ofnGuqJoGHLKsRf4t3cyIkvQEOohroT42AvlljHSnBnm/9u+Sn014ypIAcqrbvXCBZIwzV5QyjI54x9v+d4DCOoWU6MqkE2FVwrF9taqD4cEGZvZkYRo8/MHatRYrzMfQid1YkX4SVZfPjwm3BWFxXYbBgRq657ZDe9m/g+oZQDdBv3Iq6I5VKBSN2AQ+vC980Pv7+LOrKK6TjAKD+/l8F2uZAE/hmsSuwyRw98EzzxCrujELiatpHGccyOkVUM/jQbgcd85u89s5+S3I6nW0j67yru2P7YgAop5ng+uyCEsn+im+V68vmOJRAZI8cNXSEl0f5Pxh/uyTerRnMN29sxxoP+neRSk3VShlch6JOSbAkNWgHlDg/du3OprfxO1eDmgG9m/egQXGpsi9+nVyo/vg5KQt9y9x3GjMOAoRhgAZoiEASUsw5MSxmXSrLyohMqpXkNhzBLstwgwAn5VVE1mNeEY5NRZdyPBQPdJX26bYtnUi0G//O4ahwTqKJTOQIV4kcxRrUe8u/lzbO9I8UVGo/FBYKGW+MU45RtxbqzGGKuVzVmS2h23hqkM+BTYxKO9ZlTA4BYCxsQYoZV5NegrXQeBcaYCK8YSSY+DtRUP7o2MnpKU1JTMgi+sL48roaAMdHWmZICuT1WGkNDl26bTOk5k5/rzSdYJU2ge0wqgmOl4uO4EQqbC4NoXVoMjnDjK0AbnzzjsBAIVCAd/73vcO6Nzvfve7KBS4leWOO+54tl35u8rkJE/8I/rbTPJ531peLpef0XWmc63pXGfRokX42Mc+ht/97ndYuXIlVq5cieuvvx6XXHIJCCGo1+t473vfi6uvvnrKvjUaDUxMTAT+HRSA9a4B5h4T+IyUuqG9/4/A9odAf/RasKRaBM+hNCZdgAGZFuOAYmjXrOK1jGfPy0MnPIZU8wzthhpj1MQ9dF9fFbN6cjBMghR0mDkNKa+2Z6PMNzrbphgeaqB7RhZWw+ULtcImzZ3H57MNhny7iRTRYKaIl1yIbwq6xvtgr3gVxsYstLalQSlDBjrMTAosW+KutsrK5niKpOlt4H17quiZneO1db3NaHTEgqYRZD122fJAsVWm2L2jAkoZZimASjC0grEDOHgRCmmxxcD4mAUCIsviUG88VxzZJt0VhQwP1tHWkZYbZouSqbGrO4s00THZcKAxeMyxxwJYnjsYC7m5ikRP8AGZAIFDwxPIaRlYMcs/IQCbdRgf4z99DfRef00vV+tIaVnYrC5LRBAvdpIzkVzZ2+OBsZ7ZOTQavFwJY4BNRT8JUlkBiuJ3UgFoBUPb1pH26y0qrrMZkaWRAbPn5mRMn7Xq96CfWQH287eArDgP2qefAJm1HP19NfnM1cRKMy9+H8xSG8oNrhypMYiCLalVHYyONNDRyZVBFYyqIEDcL8AVQBGbBQAD/R6g7QzGZoVlby8fQ1kaRyOJdTBn9uSQzugydMDw+p4yNfT317171YDqMBqkEAuUAD5/W/6FG5at334SrMINXcPDDeQLhpyb4t4o5YYE0+Sx5mJMBMszMRY25vqskyrVqoNMRoNiD4woWELRnjkrC8OZgL32z9C/eCTSmoViewm3Vl6HBou6WspSLy7D/v46untKMDvnwHYAcsUDwMxDcfrat+CYrm2RMkxChCLZv68GM6WhPMkz3WqeV5pgbsW1hEtgnNEnnHzJavBSNWJ+qMA+XPaLUiYHRoIrx0W3uR+01AUAyOg8j4MMfSDA0/M/BJdpSO+8Fy9q+Vtg/AVIn7+w4PWLYngwqphPpfCOjVryvQCAzhnRZyHclRllkjmU4NB7R/r28v7EvRcS+xIgkw2+CwKwhV1YDTneLnJGA0cPfBcAMLDoDZH2nQWnQftuFYPd56Ko+7qNWKcny8JTIXr/lbKDjs60LLUG+F4WcSKere2V1hPrh2DKBWPvuDx2PJc3YBqal/lcC7hcywy8HjtYKMW7r8us6MPcKCcAlCr7+0PP3nsuu7Zz/TLsmePYFEP76+jsSge8hCyLoqMrI/f39U+PAQAWLy3x3AVTxGxSyuR6p67T3TP5vCrlKGqWl+TN2yttpLEgsxunb3kfABpJIibGTI1bHt5fh+t65QOVLskszGFAG5M0UBhqhGErTlpaUzL+VrwHQm8YHmqgszsjPU90nSfYE3M5ldZgmESuGeOj3GNMfJ/PG9gvru31u1pxkErpiTkaxP4pczn8/dXT/xV51oB2x44dIITgrLPOmhbYU6VQKOCcc84BY0xm9f1HFcFCp1LNU4IDQDrtW8hqteRJ3uw607nWVNe56KKLsHXrVnz1q1/FxRdfjBNOOAEnnHACXve61+GGG27AH/7wBxnP/JGPfAT9/VF2QpUvfelLaGlpkf9Uhvj/qjC7Dmx/BGTBiZHvyKFnQ3v3jcDTdwBP3vJ370t93FPyS/q0y/a4DsWGdWMAuLumDgKHMeRLJigYUooPXLOkUP19NY894UmL9KzGF92chvoE71ffngqoyzB3fh71motUSgu4HC07pJVfh1G0dKdgQkNLyc+UWyyZMLb8BQAwuOgSUJeheyaPqc0RHemMBmamUWcuinoVwTIgHNBaFpXgW00uMzbaQDanS/DZEHVSy660LgulT0jKSwoj2A0zpUlFJJfVUfVcvk3hcgwGExpOOrVLuisKGfZcscc8ENDe6SuEnd1ppJiGybqNWtWFBj9Bl+MwDA/yc9RyBaLckssA4YEpNrGhx/4GjWhwNZEQgn/PGE8MJZQN+qIPgN3wYbC9awEAI2MVpPU8bFqTbl2iXIuhExDCaxVv2jCO1rYUWtpMVCsOiDeHam5Zou6sZ4uLYzsAYGzETzIGAD2zsyCEx4jm8n7yjKyS0XLO7BS0R34GALBu/xrQczi0f38E2ruuByl0gDGG/r4KajUn4NopYqiMbAYW49drT41BzB9hpR/YVwOlwByPYVddNwUrDQSTkmQzvNaxYzO4DsX4qIVMRpOsgtWId1Hb5wENlU1QlVi1/8IQJICkiPHLFwz0buVshQYNJJ2DrReRSYjXbG1PwSxxZs8tT4Dd+G8AgJEh7oUQZ3xwXYa29hRsm3IDkU0x0F+DaWrYPxAGRkGWD+AxabzerhbJTqqKcFmc+YfXw+hbA7vewLZTv4NHJ05A+9KlsGg69jxdYfB7d5fR45XZAgA31QLtQ3einyzF68xvRU+WzBzv797eCmbNyqJWcbmy7IGo/QN1ZHO6ZMNFnF0+7z8vUWZHAFbfkMafmYgvzCnPJpzQhTHPOGcQmbWXMgIXJtwUv/+C0QEAWHRIyTsJ2LO7ggZysGccjSvnfR2Z4adlm1s3cwP6oiVFnsnYYejbW424giYyPd6zHB7mhkoRI97enpYunkJEn10XEYQsjD7iOavJdfzkftT7CclOhY/RQoxfWrNR0seRc4exLP00ii4PARrouRCplBaocW7bDEQ30T/EsL26CABgwE96F84ArIpjswjrKcC5MPoJyeZ06Ukij/UMWMIjRde5u47rMA8wZuQz6OzKSKZU14lcCwVDW6/4JXuEMPgu1IP7uZeUaZJIGNGIZzhS65PaNpXrkRmak7ZNMThQR2t7OmL0WLS4KPfDdU9yz5Bjj++AbhA/z0NMqSJxXbmOKg2nNW+vmzdfgkuRLNBmJm4qfQWzG09gpjkQmbPCCKsaroa8+21pS8V7v4QSScXVKRfGl4gxQJFSS0q+66INkcBpcKDO9xSv8oHjMJmxG+BGGlPZb0ZHG9A1Ip9vLm9Izx+hU1SrDorFaNIvIeL98qsy/HNQtM8a0I6Ocitus+RFzaS7uxsAMDY29my7AgCe0vPs/l1zzTWRdjMZzx3SSnYjEaK6GWezyTElcSKuM51rTXWdlpaWgHUrLBdeeCH+8z//EwBQrVandPv+xCc+gfHxcflvKjfn/xOy9nagUQY56lWxX5PDXwosPQP0ji/93eMUBHDMtOhIFTTJjDaTVY8MolZzQTQer6eDwAG3Crs6Q3uBL3iMNY937N1Vxtx5eZgpDRmiwSzweZcp6bJfu3d6zN2cHKpVh8e1Khb1mR1eQh9G0Tk7A0II2kppVCq8BEN7rgJj5c8BAL212QB8d6MiMTm4IUCF2ejQxrCsuEO2rWncWt+o89p9PXPzMiMmAOzrqyGb1aWbs0gs1Si7GBlucICmJCjKFwxUvY1JsKnq/bje0PNsyZ5S7RkIWtvSvIyNstcMDXIlY9ADASI5DwB0tKRhEZ59kbq83q5QhIQLNcCBrxDd0JCBDhtUAlqr4YLtXoPRh/7K+0MM6IavL/AEHH45Iefl/w10LwH9xbvAqIu9faNI63k4pKZkReXnGqbGXU5dho1Pj2Hp8hbs3F7mLJ5D0TUjg4Y7CcOjB0vtgjmJ33BHhvk9iSzYM3s440Q0gkLBkEpEXgEAPWu/BfP+r/N+XfYL6O/9HcjCkwJjbFm8ZEtLa0rep1Cc1LWy6A5AIBph6d+3jysNs+fmOXhTAF5/X1UqGCoQyXrlFmyHs0+UAp3dWVlaJ05BAoB9e2sgxI+tq9WCGVBVl0MBXgQjxN3oGY7IPI7dHiNczKaBbAmOwxJr/3bPyPgM4snvAnv4GrDN92NkuBFbU5YQPqe6Z2bh2MyLAeMeEDN7stGMoAKYKID2yce5omvb1DfIyMfA0GlwALL3nttQ0sfRVbRhLjga7rLz8ZT5chCioWdOLlEdU5muvj1VLFxSlPdoWxQkU8RXR7+IzfQ4AIAGpea091MYj7ZunsD8RUVYFi+9JVjB3TvLmDu/gH19HIxNeAmSRAwg4BubpKup9wxE1mthbFJZ2TiWUmTCbZ94XPaytzEXdZu/L1mj6Hmz+PNj965J7p1y6EuxpzEHK1a+T4bBPP0UH//Dj2yHrmtwXYa+PdUAsAYQm70b8J/l4EAN8xYUsPIhz91TU0fQux/FOBPeCqln9BkZbsA0g+EY/rzxPwq7pOs6gQEbrb1/xgnFVcjqnhu4NYi01kDZLaDacQTWrfgSAGCgv450Rg/E5Ts2Rb3uYnSkgRG3HVmtBlPzAW2S8U1Ia1vKSzzIjxOeKmHpnpH1awJ7c2v7tknvPvgxhkGgewaGwYEaumZkpOvxvPkFGYPLa5fyZy8A2eCg8BhQvEyIX490b28FPXNyXiyrf0+uQ32WV8RWeuMy4BkawrHttucm3tHh661iHVx+WKtkyHu9vf9FZ8/yMvzzY5LqtnIjqYZ0RgsA0/K9vwAAFFecINdOsTcAQPqwM/CkdRJSmhWZYyKrsGqYHx7i5bTa2tIyUZUavy3jd71z4oz6llfSZ9eOsp8JPiTZnCaTe4k4XBF24jgMc+flpUtyveZyrzNvrTAMzavTzPsnvCrE7aVSmtQbZPbpBkV7ZzrR60QY3UQfpprbLxR51oBW1EKdit1LkoGBAQCYMi71+ZZikbvyTMeFuFLxF7IDZa3FdaZzrWdzHSHvfve7pSJ3//33Nz02nU6jVCoF/v1fFkYp6J+vAhafCtKzIvE47YJPADtXARvv+bv2pz7OF8xMyUC2xUBtbGpAe/sf9qC1LYVZPTmkMpxdpWCo113YhKK9JAAtSwQfvbsraDQoDjm0BYapIUsMmCW+GKdLOhoeoN26eQKtbdxSSalXG1Yk6NEA3fI2D1B09HixYKU0tmzk7l/njn4JRooran17q5wd9PpQIinkiwYoYygzBwWD4KzOh2UfCeGWTmERPmRZKcDQ7ttThalp0DyG1tV4yxPDnEE64uh2qFbMtva0dDMTVl7DIHIDHxluIOu5xQlA64IhZ/BNVSjVYrPu31vFjJlZyVCocVD5lIlxKtwYuRO4YGoEI0Y0BMobNRwXXVoaDbhwvSzGjcEB0G+fh0HK61ozYkqmlPeFA0ahbLgwob3lJ8DOlWC3fhaDQ5MwtQxcVAOxz+J+COEb41NrRnD8SZ14+qlREALU6i4OXdEKi1aR8jxCWj1Am1TbeHioEShtNG8+X98IggxorrZbPpe5xx+F1Cd4hninMDvS5tZNvhthz5ycVPCEEhKo5ZvuQJih7eutIJc3uGulQQLKwr6+qjxOtSGWSiaoy5XCTRvGAADLlrfILNaipqAqtZqD8TELbe0p7PAUXZFhV4iafKzLA/0jww3ktTLmjNwJgCDf6IVF+T13dXaBUh5vnaTkdHVnfQC49Fxg8amgv3ovhvbXApldM1nPpTmlwXWBeQsKsG0q6zzv7a0E568XeiBaUBXUx1dxADQ81EB7zmOHCJ/rP1r6XvxyxdtAQLGvPgOHrGiHccX9MNq64dgMO7bzsenozCQyiILJoy5nqBapgNahcB2KnXsYHut8H3TiYm5aMdIqsZOUMmzbMiETuaQzukyOtXP7JBYsLMj4TxGLW1KeEU/CYyCV0mRNV8AvWSQyLavvlVCAVWnUbKToJLqdLfIzxoCqB1BTWg6ZnIY9u/2Scds2TSCd0WG7Gr6y5+PI1PaCXn0JmN3Ajm1cCW/rSHNXUA/QhiVsjJVZbh3fZXZmTxb338Mz+w/sq8lMtXESse1SL+nasBVxtRbLrliXNM03BABAUZ9AFhN4SfvdWHjXm2EQBzmjAQKGzMx5GHS6YbMU2ubOhum9d7t3lKHrBD1z8oGyXLt2THp947XCKTQYbnL5PfVd5wytz3ru3jkp71W93xWHt0jXXbH+7drB587kpF8Ch3jGxf376+juzkgj39IVLZLxL7WZEswIEc+PaH4iJF3n72alYmN0xMKcuXkYBgns6fuVGFDB3DHGkwkKL6BqKIa0VnWwr68qE46pMrMnJ9eThldjt3tGNmDwa1aH3HYoSiXf8FjIMvSuWsP7QX0Q2624t89bUMB1uy/GkN0JQoJtC2OSMBSVyzYadRed3ZzxFmA9ldKgi5LCoi9WsBav+tzFerpz+yQQYuOF6IpLjXjX1fjhOfML0mgAcNfmXEEkmyQwTSKNYPv21gKGSRF/DQTX1lKLGX3PRB88UC3Y7YMux54sXLgQjDHce++9BxwvWqlUcO+994IQgoULFz7brgDg2X6f7T+RgVkVkaCpUqlMySYL5rKrqyvgFjwdmT3bV8SmyvysMqTP1P23u7sbHR3cTelgxuMDE3bPd4Adj0J71ReaH7jiPGDuMaB3fOnv2p/yfhuaQZBt1ZFtM2BXKdwE5RXgm+jDfxtAe0cas+fkMdhfgwkNlPDMuhXLQSkrSmwls2mbN44D4PExpqEhCx1GMcrQrn1iBIcf2YaNT497blgkkESpOuzFKBkMZctLClRIYcPqXchodSzTVyH1Gj7W+/ZU0T0zK2MNS5qJTIGnw68wBxbtxHyy3mvbgOswmCZBw6Joa0+hqzsDM8Vdhl2Hu1S5Nb8qITU8RcOzLJ/38tmB8h6dXRlMTthYcUQbtm/xFBfKZOKliXEbundvTDAMjCGfDgJax+EgY693P0IZFiWMAMAaoxhnFgiAY0/tlOBCAIjeXRWYhhZIlFJzXXToaVAAtsc6WWsfAWYsxUTmKE9B1ZDKBZ8pIT7r4jgUZMlpIK/6Aqw/fh6O5bEKqEr3SqHIpDM6COEKmOtSnHbGTKx8aBCtbSlYDYqjjm1Hwy3D0FJgjKGtK1j3Miwjww3M6qTYunIjAIZjrJtAf/dxMOrCGvTXxZztG1IXv+lfYLZzTyE7RlHasmlCKniHrmiRxgxdI9iwbkwCiExGw0CjyzuLoZ3wa+zcUcbyw1q9eqDBhCq7dpThONz91nX9mr4trbzUE2PA+rVjAICly1uQ9tiCeozLsZhPM2dlJctTqzmBGDXhiq0RBufpu0F/8gYcfvMp+P0Rr0NLZTPSpI57Jl+KuUt1MEbR3lICZTzrt5tg5+rsSktl03UB7U0/BIa2Y9/WPj4XvHtq9TwVBJMhXPFF0rU9vZUAUzFzpqd8erQbdVy4nz8G7hWzsPb2v/FobwbM2v8nAABhFHmtjIcmTsPndv8HiKZhT6ULx55xiLyOZVOsXzsGxnisNo1RNAEfIFLKDSELFxWlQcS2KPr31biibxlgREeDZiANGV4cve15oNSqrrxO3vMGAfizX7CogF07Jr2x48eo7qy6TjB7bg5mSuc1vS2foTVMIksjxbkIFrRx+XvDArKkisdrJwWOqTY8l1AtjdY2UzKvANC3t4Z8wYRlUfTTBVh5xA+BjfeAfud8DPdPyOQ0Ikne9m0TEXZYtRdkA/GbIrkVZ6qFW3F/Xw2MAdlsPLMv781b56jn2lqvu8jnjYQ4by/2MGehb9eY/LSoT4IQDU+VD8fOtz6OhydOxgRrRyZnIJVNS0PKokOKMsZ+T28FjYaL2XNz0r3asSm2b/VzmJTtDCxqwnZCcbne3CZakAWd6YWxiHVh/boxxMmKI9qQ9WoCi/J1A/uqnps+f44aId7z4AxtZ3cGfZ5b6fIVrTLBUUdHhgMpRUSIDGN+HLemEVgWlW3MnpsPsH4ApEEG4GsBwF/ZWtWRa2Ut5FHS74VhaBqRFQgEiJoxKxvwKhFseFIiqLDUqg5aWk0JelvZXuxIv4jf486KnEczZ/reidmcgXWVw1CleczPB8smphTPDIDPUQBYemgLTJN7TBHC3aBFzWZKeZI/y3ID+796DyIOetuWiUQvtoblyphgyUoT0WcdXd0Z7NzmP8eaUiNW14kMcWnUeQUB20vqBPBEg+0dXoZthUFOqkELcPd5M6VJz5FmFSxeSPKsAe15550HgLOJH/7whw/o3I985CMyCdL555//bLsCgJeyebb/WlpaIu2uWOEzcBs3bky8vuM42LZtGwBg+fLlB9z/YrEowWmz64S/fybXEtLMLfmgxAtd9Ruw334U5Nx/A1l2ZtNjCSHQXvoJYOPdYNsf+bv1aXLARqHbBNEIMq1e4fUmLO11P9mCzu4MbMvFnHl5/P6GXUhBg8MYDj2sFQ3mopD2AC1liVmOn1ozggWLCigUTBgmQZYY0It8ackUdTQmXdRqDjauH8PhR7fj6adG0eop/q7nR9Y9M4PqkAMNQMpw4f7liwCA0sCT2HDzrVic3Y47F/wU5pxlADi4WLK0hB3bJqETApNoyLcYoC6FBYqG1YZq++EAgLaCC9tmvHaoTXHkMR0BMD062sDIcAOswiRY1HSe7XlffxWaRnDyad2BkgaGQVCrOjj8qDZs3sAVTttmWP0oT7C1dHkL6l4MrWA3KBiynqYmlGrHZti3t+rFEapBTz7bN9FnYZQ2wAC89JK5kvEVDHPvLg6mGiFlo6fE6VdtbBO/VnEZtH+7F41RghFW5fNSD1rcNeK7lYlNjlzw79j5os8hZ7QCAGrWIHZs48xfsWSiqzvD4328eNoXnz0TpRYTax4bRirNmdsTTulC1RmHQVJgYMjlfeWHUgZm18E23Qf6h/+C+/1X4ZVPnI2fzrwQT91yF5bnNuKQNZ9EY9VNoIygTvMQoKPtxHMgNAMzpQfASljWPjECEAIzpaFnTt4H0xrw5c88IY877Kg21GpUtruAPQkA2L1jEiuO4GOgJhQDgI1e0pNDD2tFo05l5uhMVpdW8yceGwYAHHlMu1Ru4mLIHls5CEIYunNj6DYHvGfB0KhTLM/x+McFe3/J+0EasJ+8E2ykF9vMU/E/g1fixqFL0WAZ2A5Q7G6AgcE0UrBt/1piyVeX/q4ZWb+mo01BZh+B+ht/gaFKDqdUfyoBqQBq1APu7Uom5mrVQd+eqoznAxhOdX7Fr8U8gxUDyMKTQV78XvQ585BKaZg7i0A7modtWCyNulbAtf2XYXXtVFmj9NQX8fAkw+DlLdTkY2JtUuOMzZQmPSYYAw47og2ptJ+J3LYptnis/b4+rpj327PgVdSEgQYABueJ2/H4n1bBNIl098sVTAmU6jUXpdYUKmU3MJ6qm7bVoOiZk4dpaCCaz7YM7KvJ8QN4xmcuLjI6X2/OaP0bHz9vzudmz0d/jRuhxTyarIrswBpmzklhzephqFIqmZJF7yudDu3Dd6G+dzsadQcn9ewAo9yN2nV5TL6I7Rb3o9akVb0DHG9OaYQBD/4Y/3bKfQBEhnmGvDPgHem/K2lT/M7Qnff6bVfQTrm3ha656PAU9BTqcv08pcj3zjbaC5v6YztM5oJmWrHXmoNaYT4AbjCYMTMbyBp97AmdkrG3GhS1qovFh5Sk4m87FFs3TQTihxl0WCyYy0T1xBDEWy5v8Dh8z+V4YtwKxFSqpWQyWUPGczoOA2M8M3hHVxoD+4TrKIOucQODYFT79nIAtnBJUSY2KpZMTE7wOSPWPpGkjLpMZpvm7xCVXg1z5uelUU6M7/q1o17/dFnPFODeEwAka6nKnt0cWDYaLjqVvA+GQdDlJToScszxfM6qLKJquA3L6FAdLaky3Dq/744SsJUeBUKA7VsnZLx05wwf0G7ZNC6fz5mFP6NFH5PfaSH34W2bx2W/DEOThkdKEQB6Yp8VccRA0EvIdigG99fkOMWxooMDdSz2QkOkJ5B33Jy5edgWld44AvinTBHyAlm2RxjwAZ9l3bungpNOm8Hr0db9NWhwoBYA3uraVC47aGtPBdbCfwZ51oD2He94h4z7/PnPf443vOEN2L+/ee3NoaEhvPnNb5Yxm+l0Gu985zufbVf+rnL66afL35u55q5evVq6Ap922mnP6lqbNm1q6sqt9uOZXmtwcBBDQ1wJn6rc0kHx3Iz/+Bmwn7we5MQ3grzmqumdeMzFwJyjQK97B5iV7ML0bKQ8YKM4k29g2Ra+UdTG40tRbNsygfvv3oc3vHUx9vXV0Nqewl2370WKaHAZQ7GYgp4l0LzTRSxNWBhjeGzlEI47sRMAYE240AmB5sXQplt01McdPPLAflgNipNP78ZjK4cwew5fxDdv4ArlgvkZTGzqBQHBYn0d5u39KSijcCccPFk5CvtTy9BvHCqVj907yzhkWQu2bpqA6QWJ5loNycy1aimkX8nLzhzD7kA32warwWvMnXw6V4zFYr5pPd/YijDheoqXYWqwQVG1HMxbkAchBJs3+i6rkxM8rndWTxZ7PRevasXBT3+wGQBw8uldcByGNDSZMZoC0KkWuLbt+KUqRCIkMa5ChnbWMEItlPIMS537JMsorLa7dpZBKcOmDT6T00ZSmN3C12Hbq71E8wvQP1JB3ipigNa964fi9AmRrkwCJBBCcNvoKcgbrdBQRb0+hq3ruavoK/Wr8dGer8Co9MPwamG+/tR+PHnTnejGbkyMWV72Z4qaOwnCDAAMrhIkZ/3s7aD/1gH6jbPA7vsuYDfwBD0DN6Y/j9WVk7G7PhePXroTe9++GgBBxUlLxbSl1VeiHJvKpCXhuVqrOXjqiWHYFsWRR7cjldKl4lGetAMlNoQrKVcACPZljwUANBoMp/T9N9iam6ATV6kh2ZBW9yWHlPjnilIj3Ap7d1WQTVMs3PA1GPd8jffrvms4W/kfh8C9YibcDxbw2K9vxqmlh/GJxoX47ILPynZM0sDyHDdijtc8EGRm4L78v6Ff+QCur30Qq+j5aLh8DViwqIgtO3eDgQFUg+34gFbUdlYZprZ2haH1+tzffQEfZzYI4b/QWuZJwup1Kl35AZ7IZnzMQkarod7LjSglfQwjdAZ/5hAxshq0N/0AG+Z/EJajwXYJznnFEozU/XAbERstSnx0zchg7nzBBBP5/qlhB0CwrmU2pweMREcd2+6d7xs9Nj49hu4ZGQzsCyt/BI7uxfTv3YTHbr4fKzJrsWDXT0HAUGCj0KiXhEsDahWHu4l6WmM6TQL9Ghlu8MQvJoFG/HwEvbsqMhGQBgejA+Id1jCzWAHA8MAY39s1nSedI4r7Ik/GQzE8MeqPQdrB+JjPJs2ek0O+YMCyXLlmkENehD8s/T1slsIrq58F/exhODS9Vroeip/iPVOVdJM0kNXrMIkFe8caELjoNAbx3u7v4qTGr+VxM8z96Ku0ihGF5jGsulORn3VVngAA5Ce34IMzvg6AoNrXi44y/7zDHIIwLD1VPpJff+ExAbfkQtE3Luze4bOMRx/XwZk3r+8rjmiLlIdaurzF95axGZ5cMwzXYZHyNKoIPEYg8q5wYAlAuhwLA5f4TA0ntm0qmVPXZdw7yGWYv6Agsx27LoOuxLjOmpOTpeU0jUhXdVVEcjjx7Bjj8wPggJbvt+OYMy+PQsGUWZOF18HqR/iafviRbZJtBSCzXre0pGSWYSG7dpQxf1EB/X01v+SQTtDSypM5uso6zMN2grHU4cztc9K90MDn7mTZxYy+2+B4Okhh+bHo3V2FbhBugPL6vb/f16fWrBqSXgFnz9sAgyhsqBJCAAAPP8D3xxefPZOXtvOe66IlRT+BlGcIty3f+AUEk7fZFsXaJ0blvcfJvr1VHHp4KwDfXZ56K0TPnBzuv3uf3G8FoBVrM4Gnjzgs0IeaZzAvTzo45fRuZLM6hgfr8j62bZkM6BEqYzs+ZnH3b8VT7J9BnjWgnTdvHj71qU/Jgbvhhhswf/58vOY1r8HXv/51/Pa3v8Wf/vQn/Pa3v8U3vvENvPa1r8W8efPw61//2suqSfDpT3/6Hz5j7plnnimZ22uvvTYxwY+aUCrOdXk68upXvzq2PVWq1SpuuOEGAJw9Xrp06TO61tVXXy3v5YwzznhGbfxfETa8C/Tb54Hd9jmQV/43yOXXBmrPNhOi6dDe8f+AoR2gP3sLmBsPNJ+NTA7YKM7wAK3H0NYTGNprf7wFPXNyWLy4CMdh6N1ZRsEwYBANRAM2bxhD5+wMGpMis2R8DO32rZMYHKjjuJO4i2Z5F7emLt7/P3A/swLZp3+GSn8Z992xG4euaEF5vIGxUQvz2iZgVSrY+pufAwCO2vgpDK3eBAKgqnfgrZuuQUOjqBSOQ8UykW0pwXGoXJRrVReLDiliw7oxFDUTjk6RyelwHa52z8hk0dBaAQDd2TF8puU9qD90PQBI8C2Utc0bx2GmNHSTDNJtInskUHVt1JmLk0/rlscJEa6Cm9aPy3imiQkbbV6ZmdH9FeggKBIT4zUv4zKhML0xVJnETevH0daewvrHfVda9xHOwDFG8bffPoY6XLy97dugP7gIWcYVD70xhsnH7pJAeKC/Bt1zL15ipNBZ48mfxgvcVZNVGFY/uQ09qW4MuxYYoxgfpQG2jlEmwYyaPOj2OzYib7Qj156ChTRsj7UYc0roSo3ArtYwYXEAMOP3r8UJ91+Iy2b+CrUaRcYexKYPLuZj4HIa17n1v6WCa29bBXLBJ6B9+gloXxuE/qE7cPXed+Axei5ACCq0ANsl0oLtuooFXemjbSt1PkNz9ZEH9ssag2+4bFGAOXAd4MJX+/uPSFTEBwWopb0EZFmKReZm0B9eDOOOz8CpTIDe9nn85Ud/9A51URmb5KWlqFfiZt0dcKsT3rMEzir8GeSRa6GPbOX9THWALDoV5OiLQc78ACbP/QI2VA/DfqsL/7H9v7D5hG94HWEAA34/dDEAIP2iy/g1dR2Oyx/g7l3lgEvgwiU5PLVxh3c6gWX5a87xJ/F3QF2+eA1dIuPtAD+xzff3vV8et32/H3j9xq5fQn/ohwAAfeeDSO1+CDcc9gbsKfP2WzMW1rhnAfAVRvHz/1271bsucO4FswM1MIve8+VzkscdCzFTGsbHbKTTGmbNzmHfXl+hVZmG1pZUQIk76dQueb44dsO6MRl7vvRQPycE0Qi4ekRQP/l9eKJxEpYub8Hu6mzMy+5Buv9x5MY5aF+U240nb7gJh7QPglEKAor2bAVu/3YAQJpUMTlhY9lcCy3GGAjxQxP29k4g1eDv84L0DjSoYMYI3Ja5SKV0jNM2b9wYCkUz4NbY1Z1G3S3Dpf6z3fD0EA5d4Y/XcSd1SqVcdYm94+4yiAbM+4/fADOX4/QUd/lO6z4YzuV1L/kVv6YGF8P9k1iQ3gEGArswBwwahu02/OHMLch+dYc8d8CegUIx5bGYBJk8vzc33eo/r8VnAQDGs4fgK7s+Bg0uhpxujKaXAACGmB+CVWHc4LF/oIGFS3zjR6nFlGBFNTq+5GWzA8/fNDWldqcRCD3RdYLJCQs7t5V5AsKOlKx/Lq+je544suyXz3oVi34oie1QPPKgT+qccfasQPI312F+Rm8GPL6Ss+nzFxUCscm6xsGmpgGT47b8jsep8zk/PmbJPqw4gs8T1Ugl4ks1jZ+3eeO4fJeEsUcYgbd5oQ7nvXxOIIu0CIOxbIYTT+mCKnt2V3DYEa3YvHFcMpgqwN+luDEffhTvX6XM96sTi4/CnNglRgUFvYySNgGmwJK5r74MDszAuGuEyOz6APDLn2+Vx697cgTlsgNCgJ3zLseEw99ptYyfuN/168aQzxto78gEss2/4jXzA2tEKqXDsig2rPWNRsJLgWh8D3rcK30osgxrIWTlOAyHHc7vv+EB+n3e2uo4DD/5/iYsXsINdiL/gDCcOJ73lmNTbNk0Lt3BhZgpDSec0oVszsBDf/PnHWMsEHeuGikmJ2zPRV6w1v6acvcde7Fx/RheiPKsAS0AfOpTn8L73vc+ueg1Gg3cfPPNuPLKK/G6170OF154IV73utfhiiuuwE033YR63Xcjef/7349PfvKTz0U3/q6SSqXwwQ9+EACP0/3a174WOebhhx+WrPMZZ5yBE044IbYtkU15wYIFsd9fdNFFWLRoEQBeKke4MKtyxRVXyAzTV1xxReT7nTt3Ys2aNU3v6dZbb8XnPvc5ADxL8tve9ramx/9fFObaYL1PgN71ddDPHQEMbIL2oT9De/mnA5by6QjpWQHtXdcDT97Ck3LUJ6c+abr9ZAyjuxpomcMX2mwb3zCrI1HgvPHpMTz01wG85R2HYPOmCRgGwYP3D2BBVwEauDV5964KFh1RRM2La2U03i3lrtv3orUthWMXV0B//+8Y/9GnYZAq5g3/CmTRqci32KhXTKx8cBBnT34Nj37qA8hrZcze9CPY9QZ2eBiOnPgmjLLDwQDsteehZpuwDYbGqIu29hTyBYNbS02fPSsUTdTrLmbqGTSyHOy6LkMaOvKagV1eUo6+5R/AzeOvR/cw92hI/+xVoHd8BW2DD6HVGMWWjRPIZnW0amnMO5xvKvU6xQizYIPhmOM7UJ60pSsXAIyNVJFPU9x0/VbMauEgfkluGz7TxdeIXX+5EwZxUNRMaNooOI/kop1NwP38MZi5/VfIaRUUv30s1t/8Bxxi/w1Pr5uEcM1z+jZ7V9LQb7WDAKgc/15oV/Uh19UKADBYDfv3jokZgBcv3AnXq6M7V29D/qL38rYE61IF7r13PbqMDkwwBzatw66ZgdqClPlxXQIU7t5Zxuade1BMdWPGbMP7nj+HG/tfjfuO+BX2NWbwUhMA9r59Fd6z8bv4ycQV6OliQLYVf+t5G9IaAaCDgcGZf7JfUuXjj/H3ae5RIJqGuhcntHnDOM45nyu0jsOw7skRqSiI+oAqmHEc6gOykMvxLb/dBUJ47OPRx3eiPKnWjQUefmBA/h5ISsN8xWn2gjYYn3wU2uc2wTzyfNiujnU3/QHX3cJwQnEVrl/xJvz5lm04tfggKHgbLjHhEh+cXX7NF6F/eTcy7/gZAMA65CXQ3vg9aK/5CrSXfxoP0ItAGUEvW4ZtmRfhyFed53WEwEZajrswIGmEKzqjww0MDzZknFexaGDX4C7UGzYINDBKYNv+WnCKcN9VND3BXKigZ8e2SWgaL+klZMjm1zY0BycVV8LYx12yjWweI7QLn+n7ClyY0HWCidQcDO6vRxQ8SinWrBqGrhOceEoXZszKyjInAGRZk3qd8usr4MIwNJTLNgpFE/MWFDhr4enwdaX2dqFoBmL45i7wY30Bzsxv3jiOES+UYJ73Pa8x6/d1T28F9QbQlzseT9RPwrKzT4Z5xEtQyfM9euE8A4/2H4LTZjwFBp6kqGjtgbvpPgBAd4oru8t+dxo+1XgpOtluWH/6Gpz3pfGDlvNR2bcXAMMg7QnUV93bWwm4UFPK72my7APO1rY0au4ETG+OMcbQu3ccr7pkgTzmuBO7pFIuagWvfWIEe3urmL+gAH3JKdD/5ff4A+NGi5RmQ/DehfI2MMWbgkJHleYxlD8KDjNRYSUABIW2HC563cJI3N4rXzM/UJMZCGb2ZgZ/rg7SGLBnwkyb0DRgvM4/142gS6phEAwPNVBQ3LlFQjrAd+vXDYJDlrVI+l4YbkSSKtdhOOm0bh56YmjQNBKIn6Uuw5x5fi1fAFiS346gcEKGMT+jtWFosC0X997F4zeJBjy9dlTOf1GnVnVHX/kQByGTE/6aJBhaUf/83r/0ye9sy8Uuz3V4p5fESteJdN8VurWuE1nXFoyhUXexdfMElgpAK5lpHjct2OATT+lCWmGyhYGzPGHjlGW+UVcjFCPDDfQM3I5K2cEp2m28PYeiaO/F3h9/Ela5DAIXs9oa6Lj3E9j20TNR9d5RnVD0W7NEa+iaPxPra4eBeXvYrJ4sWub4XoMTEzZ65mThODSwHvQqoNm2PfCW0rDKPddbM4O1wR2vVvbIUAOLl3LDyIDiHn7uBT2B8loiN8DWLdxYkkr78cLEa+9v93JPSvGqhJnnTFaX1xJy3938nAfvH8DCJUUsWcafSyqloa09JbMh2xaVNYM3bxxHh+faLRI6zfJilR2HYs/uiry2aqDrCiXjKpcdzOrxPxNrf63m4DtfexoP3j+AF6JMWyO/7rrrUK0mu0p+97vfxfXXXy9BGmMs8R/Ak0n95je/wXe+851ndwf/i3LFFVdIJvTKK6/Ee97zHtx777145JFH8KUvfQnnnXceHMdBNpvFt771rWd8HdM08T//8z/QNA0TExM47bTT8N3vfhcrV67EnXfeide+9rX4/ve/D4C7J7/lLW+JtLFz504ce+yxOPXUU/GlL30Jt99+O1avXo3Vq1fjhhtuwKWXXopXvvKVsjTQ1772tUBCqv+LwhgDG9gC+uivQH/zYbhXnQb6oRLo548B+92VIMddAu2/1oEsP/cZX4Mc9Upo770J2Hg36BeOBVt3x3PS98l+G3aVomMJX+yMtIZMq47yQDQt/s+v3oz5Cws4+7werFk9jPbONBzHwUSfBR080UfOtLDMvQ2MAlnosqyCKpWJGvbccxu+dNhVIP+5GOyvP8Rw/nxMMAf3nvkwtMt+gtLrubGllEnhvHeciwe11+GE43LIvOLjsEgOqye4O6c160y4DY99rbk489xZcFMUrAqc8qIZSKd57VGxCc+Zl8fjK4dACDBXz6OedmGYPAbMgAbWALZ57syZQh7X7XsjvruHA7waK4Dd/t9Y8qeL8OsVb8GmVVuhl0eQ1wzM6f8xAKBeszGOMgiA5Xt/gLu+8K2A392x2ZVwqhXU6gy7B7gicVzxcWyvzAUBxTb3cDSYjhIxscfOgxANLnTU3E7QOSdBz2RhMxPVuWdic+1QZBcfBZulsHAB36i3LPkwAL5AjzMbOUPHWG45SMss5GZw1y29Yy6GOs8AiFduZ96JAAhMEBBomLGcK+gyVrQGbPorV67roKjRURgkI2MiGQsztPzndT/dgrpTRkrLYGRsAgwMs2b7CsXtt/RC14kEgr+73cKAvgTDExpOPmchbKTw590mWlKLuTFPI3AXny4zVquZLq2Gi1/+jGdwdSnDW9/NmRrbcvH4qmFptRbxSr27/JgiYXAxU8GETWtWD2Hdk6NgDHjFxfMA8LhvIYwBvbuq3lgBRx7dLl3OAL+e5M4dk/jMxx/DLX9NwVl0Bixq4pPb/hvETIEygh/r34Oj59GXUwyZS8+GTXlbhx/Vhvauguwj4Fvrhdz75z6kUrxe8sWXLghkn1TdJYWCTjRueNi8aVzeC8CzlD61ZQMOXTIbGtHgWIBJuIKezmgynosoyE0myTKItNg//LcBUBpMBiNcC7OFLP5163egX8bfGTb3OOypdOHxYR7n/upL5kPz2F6VNQKAu+/sg2VRuC7DG966GLt2lKULHeDHHFLKkCsYsk4rwLOU2hZFteJg6aEt2LBuTDIwKuOsGyRQgkPMZwFo168dg21T9PfxpDu7lWQ66rjs3lHBsuUtWPXQfrgu40lkclk0vPEcKx0JYpjofs2HARDUjXaYS07EOpO7a+9t9GBWJ0P7R3+L3+S/jorWCWfZ+dh70ufwo753oddeBIBg0s5LIM/vPVieCQAMk5dnIp4LZb5goOqModsD1xatYdbsDI47sUOeI8ox2RaF6WXn/t431oMQ4LyX+Xt+1fNoqdI8iEZgGkCuuwsBf03whGTZPO+XcJ988VmiHEtwPh+ytKSUEol6C4l5JuL2zZSGpctb/Jq1oezVuk5gmATbtvhMrBwM+B4F8+bnoWlExiuK+Tfg1cmt1Vyc8qIZ3pjyzNNbN09wo1fBwEB/HYsWewDE68Jm6zB+Oc/oqMOWv5daTNnW0GBdGpbmzstjaH9dvseEcMCnAtoNT48hk9Wx6uEhyfpyQMtB2Ioj2rD6kSEJorZtmZTZkEeG+P21tpnYu4ffuxhv3SDSIEIIwchIA1aD4sjOXtBVv4G+ngNQ69Yv4/pPXA0Ciovm3IXcI/+DI8Z/jZd33I52ne8XGly0G8M45vYz/AFhDAQU5hgH+qfNFew8Qam2DeN//T0sxvWRM82bwJ64CTcMvh4a4YPxuHWaYugi0qAkZMmyloBBan9/DXPnF0BpsCbwv33yyMB5lHIAue4pf47ozCfRHIfij7/fDYCz5wDw2KOD8thMRkcqpUvjg+nV1xYx0YsWFwP9mpy0USk7AWNUPh98b3tm5yTrLdbxR70SV2946yJ85dsnYsc2vv4MD/K6tANebXPVELVx/ThKrdxYKFj+rplZDA/VMTzYwIxZGblHMuWdXXpoKRD326i7mOUlMRNjAgA3/HI7GnUXF756Hl6IkhyRHZLLL78cH/jAB/Da174Wl112Gc4888zIMZdeeikuueQS/PnPf8Y999yDNWvWYHBwEOVyGYVCAV1dXTjmmGNw9tln47zzznvBJSMqFou47bbb8LKXvQxbtmzB1VdfjauvvjpwTKlUwq9+9SscffTRz+paL3vZy/DDH/4QH/jABzAwMIB//dd/jRxz4okn4qabboIenxIQAGeNH3744cTvc7kcvvnNb+Ld7373s+rvC1HYxACw41GwHY+C7VwJ7FoNVMf4l12LQRacABz7Wv5z7jEg6XzT9qYr5KhXQPvkatBfvRf0f14KLDwJ5Ix/ATniQpBCx9QNhO+DUgxv5Gx9e3EP2M4ykG1BaWYKE/3BGMmn1ozgsUeH8J9fPAau46K+9m68p+02/Kl6LjKN02FqI2BOCqfM2oyWbTcAOBOnl57CXytLYU9WQX/6ZrCxPcDoHphDvfjsTAtueinIhf8DcvJl6L+8DwMYwQJPUTFa+IJ55ulzMLzsVGzf9ze89SPHYWLMgusOA+AuVeXdvJ+McNfKt757KX742NMosRTOvWA2bvx/21GrOTJu5pBlRdx+Sy80RpCFgUGzgfFRPxENAOzZxDd43eQZHgvFAqxJB/XXXwttdhrbH16D7//XXRh3WtBJuLWzuKgEPA10picw5rSgU0sj9fAP8cc1X4Cq1O0hy1GhBZgmwee/dhw+/qHV+O3QJXAHOMtX8Qy+KWg49DCeOEqUg6hf8B00KtthP7Udj/T8O6rWOgyzTmjaGE4+Yw527Nwmk8/kYWCA1tBaTEvAUejw2D+X8cyIjLtRP/RXbunPQgc0YMahHvshwJ0DnEFORy+4db/mjKPFnB2IF3NdFqi59+Tjw/jzHduQM1oAMGzewhWcE0/twi03cqVA0wmWLm+RyuT99+yDrmt4+avnYVZPDmOVMTyyZTOObOeJ/wgIHMczTtRcODa/5u239OL/XbsVIx5Y/eYPT0L3jBx0naBvT1WysYWiITMS9+/zSx2oDKNgaBlj+P43N/DrEuDi1y/Evr0VOVZAsGRBe0cae/dUMGdeXrovCsCdyxmYmLDxw29vgOuVgclkNIyNmhideybWPF3G5e9Ziuuv245U2oXVYHzOeu2/7JVz5HWEZVyNJxvor+GpNSNgjLuHXfCKufjMv6+W36uZZ0V9REIIHJvhqceDSYB0A1i/azM++M4L8PBNQKXios1znb7gwjkYHhYJTISLnF/CQyQgGR1uYPvWScxbmEfvzgo0jY/VjBkZTI7byGZ1TE7YUikaH/NrPxICvOltS3D3n/vkHIHDQDTOYvz6Ou51tGxFCw4/qg0/+f6mQP9FO9msjnRKD5Q3EqWtajUXi5YUceP/2y4zN2uEyNg0x2FKcqqgwQMA1j45gnRGQ6NO8YF/W44v/teT8lhC/Njc/QM1LD+cu1UyBhx+VDu2bZ6QTOOax4bx2jcslIzL3Pl56DpB/37+PYWBJUfMAFlxHHbkO1En++F29eB++2j8pbYNjks5EGcI9HfZcp6JW4xZKq2hd2cVjPE4Yt3QAEYwaQ9jaSvPelx3J/HKc+fJup8ALwEilHLD1LB92yS2buZzW4A6wAecwgC2aFkLhobSAPxkeADwiovn469eeR7q9UvELT7xmG8omreggO9+Y738u173x1+8n7KetmCIqi7a2nyXyrCnRcOimDs/H7g/y3IDGcABoGcO36tFKRSR7G+zly8hm9Wl+yyPcSXYs7sCxoAjjmrDyocHZfypkHLdi3XWebkqjTqYgb3YR2aitbEdrH4ITJN4Y8AA8Da7ZmQxOW6hWnVBCDcWqRmwR0csLFxcwI5tZRyyrIQd2yfhulS+47Pn5nDX7RaOPKYdT60ZwZ239sp3EQBe9dr5eGzlEHZsCXp8aRqR3jdsvB+j+y2UdBMLbrgQjDDolVMBfArb7v0r7t/9r3hlxx9xWdcNYLe6OLZRx7GzXTw4fgo4Ew285EUmzHc/BPLGYf5+ajw77zW7XoNUimHRZ34NXHQfAGB1+Xg87Z4MollgVMdTXe/EG9dehuEhXx9p1P1wF4An1Lv/Hj9nzKIlxQCrODJsyXwXk5OOrAN9yDLfvT6X01Gt8kzZe5QESim3CrZvI4B22BbFrTfxveuk07px6027Awyt4/C4WQFoUykNjYYrGdNTXjQTT67h6y0hkPtVvebPVTNUrqp7RkYuarpBAMt/Rl3dWfTtqWCLZ5Tc11fD0uUtWPck1+lsm8I0CawGBXUZL9njMuz3yjUZOsE3v7QORANmzMxhYF8duZweCJGav7CArZuD82NmT84P0fESTl3/i+249E2LIu72LxSZNqAFeMmaa6+9Ftdeey3mzZuHyy67DG95y1uwZMkSeQwhBOeff/5zlrX4H02WLFmCNWvW4Hvf+x5uvPFGbN26FZZlYe7cuXjZy16GD33oQ5g/f/5zcq13vetdOOWUU/Cd73wHd999N/r6+pDP57F8+XK86U1vwjvf+U4YRvwjPO644/DLX/4SDz/8MFavXo19+/ZhaGgIjuOgra0Nhx12GM455xy8853vRHd393PS3390YcO7wDbc5WUbfhgY9uI3SjOABSeCnPtRDl7nH/+MgOWBCJmxFNpH7gbW3gZ697fArrkcjGjA3KNB5h4NtM/nC2CjDDQmgfokd1GuTwD1Sf9fYxJoVLB/6H1I629A9lsvAvXW0vzkLzG5fQVYmVtJWXkYP//mNiyZbePUwatQ+48/4UvzNuGO4Zdg9cRxeGNPOx4b0gGUceEn34nS7PcAl+xBhpg8htZywUZ2gbTNQWPmcbjutzV0nfRiXHTlpSCahvJ+G5P9NsopR7Itd9/PS0GdcHQ37vvLPuQLBk44uRN/UzauQtFAeaeDKnNAGXcr65mdw5hlYxbJYdnSFuRyBgb317HuSa4wGYaO4aEG5pg5MDBMGDbWr+MbQMOLzax77tICNJz1kln44+97Ua06IHoemLEMT1a4lXS2lkO6U8d1u84BMAbSOgNjAw0cYxSw4fXrsPtvwezUg402ABSfvep4HHdSF2dIZQkawmvgMV579s1vW4L/+vfHJRgvDzrSQv/4ymGUWkysXzsGShlOPq0Lv/nFNuzczq21aaJjkjnIt+lwvGyK9zzNlUlRdgAANnnKtq4DaaojN8NA1mNMZa1It4w5qW482OgDIYBBcoBhYXLSV9wY85msatXBD761AZOsD12ZhcgXdEwSHRgDlh7qW9O//r2T8L1vrg/WZOxI4Z3vX4YH7h3A3omtKOQzKJrd/Bimw3aodDnetGEMP/3BJvTtqeKc83vgOBQ7t5dxyLJWABxgrX1ilNfisxkyWR3Vqg3qEjikAoPlA/fJs1Ly3+/44x7pNnvGObNgNVx84B0PxZYLyuV0pNMatm2ZxPLDfSVJKI+ptI5v/OBk3HFrL77+hbWBa1oWw+JDSjjp1C787AebUWwxYFsONq73lYqFS3wXMAGqVJB66027pWvZJW9ciF/8bAvWPjEm+7B4aUnWZFaNwbZN8Zc7fJdEABgY70OtUcOrzj8RK2/ZjIlJivY0jxN+xcXzZYkZkS2Vx9h5RiiDM9xf/twTYAw47oQO7N5RkSBzbCxoJBOAds9u3/Xv4tctQKklBcemKLWYPvurEziUYfcOrmy+7T1LQQjBnbftkQqqpkG6VBaKBkBIgCEWNX9dl6FWc1Gt+N+pbL+j1M/k3/mAHQCeWD0Ey2KY2ZNFV3c2YFwgCCZC2rO7jJ7ZOUxM2Fi0pIhszpAZqtva0nj9ZYtxycvuBgAsPqSEtU+Myj4CwKGHtQWubVsUjzwwgLb2NGrVGsC4y6gs6QHghJO7sPKRQYmsheshNzoxFEsGXEphkBR0ZMAYQ8OtYtnyIn55jR9XWKs6kvXXdIL1a8cwa3YOhHBPFyGidJCQGTMz2LRhXD4XgDPgF140F7/7jR8r296eRs0zOPz6Wj88qqMzjd07yxJkiHVFTdgmfhdj77oM/fua1H0FjycVomk8EVQ4pcmjD+3HTTfslPGfDDwnwLqn+B5xiJIMyjQ0WadYMMDLVrQGytgAQLFkYHLCkcaTBstikrVCJy60TXeBfvh1eHP1GHy8+lkABCaxMCs1gM+2fAY/sj+CR6qHgzAH1rp7MCdVx6HZBjbWeHWKXs8YeOFF8/D9b62HbVHYXsz7+gfWAzBxwdxVeGrNYqx8aD+KaQsTjQx04uBdp69Hec0e3LtjKXS4cIVa79rI3PNFAK8BbdQwQTtw4lGA8amngPa5SD1lAR9ahW8PfRIuarhl+FVY8cH/xDnnz8Yfb9jpGSM4MKfQ8fIPvBJkdg6a9ie4Lo/PJN67ecY5swI1lF2XwrapfN83bixjzrwCKhUXrW0p9PfVYJiAoziQiQzyQhYsKsps8ULGRi1ksjqvH9uVCYQBATx7s21xQ6JtcUMRdQE9lwftXwPgJFTKDiYmbHR0pDG4v45vf3VdoA2RPI144Ry5vIHRUd9Yd84Fs7BBSfrVaFDoBsG8+QWZ52FfX7BfWzeP4/LX8ZAnYTgqFE1Ztu+Pv9+NbM5AteJgoJ8b0NSYabEmL1hUkMbuurf+7OurYffOMpYuL2HT+jGA8DJBjPrG3545+UhCtJ45OZgijtqm+PZV69DensYb37YEL1SZNqA1TRO27c++Xbt24fOf/zw+//nP45RTTsHll1+OSy+9FKVSqUkr/xySz+dx5ZVX4sorr3xG5ycllIqTww8/PMICT0eKxSLe9KY34U1vetMBn/vPJGxgC9jKX4Gt/g3Qv5H76C04AeTY14IsPAlYeBLQNvd58RYghABHXgj9yAvBxvrA1t4GbH8YbPcaYO3tfLdOF4B0Ecjwf6R1Nv89XeTfeZ/3X3MkZvVo0P/1fiBTBNu/BcVvb8fObW2gH+VuvasnjsXaHf+Nzy38AshTw9g8uQQ37HwrNjjH4vDDS7C2G5hw/MU23VmAmdWw2ToRDsbgmDnoV/ASEt/9/FN4qDKAa957howl3r1yEkQDGgUXtaqD8TELN/5mB84zZ4PUGO69ax9Oe/EMpFK6zEaazekoFFOo73EwRLkrnW7wuoz9lRqWmy0Y77XkYi8yEz6+agjZnI6j29oBRlB3HWxbzxd6CwzQgRwxANbA014yhxedOZMDWk9xUzMSzjZysNqorBVaq7rQCDBHz+G263ejUDBgpjSMjvAkHJZXKF5Y+XWDgFq8fq/IMNpB0hhjFto60hzwegpdZdCWFvqVDw1i8dIi1j4xio7ONJYf3oZ0RseYxzY7oGjJppArGNjbW8W73/wAPI8tGACECipc3GbNzoHsAQqLTDmnHYdBN4C7Rx9G96uPReVuhq4Zadj7ZqHYaWF0IMjACJBz5617sL+/huHKAA5pORWVMkU6w7eMH/+AM2qZjC7LkYhVjVLgE585Gvm8iXSGoL+6GRecdSxGn9blc7Qt3338C//xBJYsK+FHvzgdi5aU8N7LHsCyFa2yP7oBbNo4BsfmDN/QUAWj9X60peZg3+QWzC0cDQDo2zeKx369BoPVXljWHIwONyRDxBjwxssX4/P/8QRqNRczZmYDhewB4KzzenDPnX3IZHTJBAA8AcjYqIWJcQt/vn0PvvHFtTjq2A488dgwFi4uor+vhn17q/jBNafhgfsHYBiEsysEGFIUroD7sAQ2fKz7eiu46Yadsq7nTTfsCgAMSoG3vH0J/vPKxwEE6/fu7a1gcoIzFied1oVHHhjEjsHNKOWKOGT+XLh0E8B0lFLcVV242QKQibII8cGFYRJs2TiBxx7lLMSjD3KjT/fMDPb31zG0n88X4Q4q3HrFvNd0gne8j7sd12su5s7PY1BhE0TowtJDSzj+pC5s2jCGsRELyw9vxYZ1Y16MrAPDJDIuW9Q9btRd9PfVeLmgzjRu/H87AmyVEEJ4jGxFGUMBmgSQsbz6kR/71JGBxDIiBk2UF2lpS2Hr5knMnZ/H0cd1eMYrKsHzJW9ciC0bx2FbnHHSNYKBfVV0dKYx6I2VSBaXSusA4+/r5o0TSrx2NOnecSd34vHVQ1KxzRcMUMpAKQFjDC2tKYxPTmJmdgn0lAPXMmDTGrZtHceaVb6uVhUMrUVRrdqwLRfVioNzLuiRa8TO7ZPSMCAA7MMPDGLW7Cz27fXfk8OPbMPjq4YDoLKjK41a1cGD9/dLVgng8azFkolSiynD1cLPynG4h46Yz90zMhLcAQgYBQD/XRSfU8afl+v6ITHLlrdgcH8d31PYYUYZHnloUN7jYiWpFHex550645yZeOTBQVzyxgW45be7A8+jrT0tS+QAPN/AmNMGEMA54XLQM0/EFz5VgCj7ZLMUDuvai3WpC9DSWQCGODSsb3kcs0Z/gCvnz8LbN/4EBBRZWoaRAs7e8BaMtc3Ez/e9FbXhYQAlPL4eyGpV/O1BviadVFqJJaVe/HLPJZif3gXz5x/EoupFuJ8tggOdl/JiBqjtINvODSlOaR5q+xs44WVHgMzmhi0zxY3DYi0gBDjxFE5u+F47fH6cfuZM9MzmLvZEA+Dy44Vb7GlnzMDosGI8sgHHdqSR8/wL5+Cu2/tw2bsOwU037AQA5HKmNOBkc3og5ADgBoQbf+UbTjSdoFg0kUoR1GsujjimDffcuQ8DimF3cKCOs87rwR1/4Mk5dI2Augx6rgRaOhSYBMqTDRi6htPOnIFvfnkd5swLMv48bpZIhrZQMNG/1//+B9/aiKc9w7owbhg6wT7vGMMgAcMaANRqFC956RzcdnMvXvaqufjj73txwsmdWP3oECYnbNx6826ccc4s3PHHPajXXEyOWyi1mpgYs6WnCWPAy145Fz/5/ia+1p/ahUceHMSe3WWcc/4sPPrQEBoWz7Av1vWW1hTKkw40QgJu7rpOZC1zQoCnHh/B46uG8cVvnoDHVg6hZ3YOCxcX8UKTacfQ9vf347vf/S5OOskv6C1iYh9++GG85z3vwcyZM/HGN74Rd9xxxwGBtoNyUJ5rYZvug/vt80H/cynYX74BsvAkaO/5LbSvD0H/90egvfZrIMddAtI+7x/C9Z209kB70bugvfVn0D/9OPSv7oP+lb3QP7cJ+qdWQ//ovdDf/wdo7/gVtDf9ENprvwrtFf8F7SX/BnbSOzDQW0TPixeCLH0xyLxjoB1/KUqvfifKdB7wrt+CvPt3uBafx/JlGZx87f3oe/eT+PiaD+Gx8aNQrbi45PyFYBSY8Eq8lCdtEEJQ6kmhqJtgzGc4nnhsGHfeugfv+JdlgZqE2++fxKwjczALOsplG9++ah0IIehclMHOp8rYs7uCs8/nSR6e9izlRxzdjlLKhFnR0O/WUCqZYBS487ZejLsWGBhGdtSR84DQo14CjeGhBqyqi8yEDr2HYHTUCsT4VjQHM/J8A97qpbrPeO5Xwq3v7js5ezyvJY8sMXDP0314/WWLvft3UMybSBEdGx4ZhWFqaPc2AJ+t8OeNAChiLhEAM/UshmkDjs2k+5jFKMb7LJmlt1p1UK260DSCs8/vgeZtwEImmY2Zs7LYs7uKNauHccTR7bjiiiMAAGnFO4MxnvE0YxrQCEF+ke/S5tgUDrWg6Sns2ckZGV0nMLQ08oVouIKI63zw/gG0dgEFowOM8Z17YozvlOLSgmk00xqq3riecnq3LNGwav3TsGgV81t4He92z42v0fAV+ONP6sS3rz4Fi5aUUC7b2L5tEsu9EgcAt7A7NgMIkMkBoAZKWc6gHrrUTxryzo/+EO//5I/x0I4/4Ya7bsenr1iNRp2P7UtfORerHhnCpg1jsBoURx3XFrjn9s402jvSqNVclFpM+awBP46xVnVx1eeewvkXzsXb/4XnUlj7xCgG99fxtvcsxaJDSrj/7n2YPZfXuGUUgVjcQNF7b77U6y6u+8lmvO31f0W95oJSoKs7g1rVQUurCRFNousERx7je40I8OTYFE947saMAW9462IQw8H2/ZuxZMYKvPvND4BRwNQzsL0yM9WKI5N+zOwRZTh8l+NUSsOax4YxY2YW8xcWZP3Lj37Sm3ce4BMGmnqo/vGbLl+MVErHvr4qHIehrT0tQa9qRPr4fx0NALjmhzwB2stfxRVt26bIZHkcm6ZxBVowtE+uGfHYIYbOzjS2bVZiKUMyPNwI1LkUjIbKJM9fWMCKw1ux8iE/hq61LSVdygGu8LW0mujbU8VhR7bhN7/Yhltv7pXHt3WkcfON3NsnlzewacM4NI0EWEMBmHI5A5Qx9O+rQTeAiscgLl3eEmCaAaC1NSVjxAnh5XdqVReuy9A9I4tc3vj/7P11eBxXuu6B/gqaQcySLcmSZZkZY4fsxGGaMHMyYWaGCdMkE85MmCYMTmInhtgxg2zLKFnM3ExVdf+o7pLazt77nHv33HPm7HzPM8846q7qVVWr1vrg/d6X7bubcZmz0FQRTdOIaVEWL2qmvMJlHBeIV2iDwRi93WEys6wM9Ec47Aj93dE0jTde2j2oORsf9/hJ6Un6qQATp2bw0jM7SE0bXF/sDpmenjCP3V+V1KenaXDjneOS+g33Tzz0GtB3/b9z821J6/j+fmQgEEOWBdLS4/uOpjvtiWNGj0uleIQLl9s0KHsS70n96O0a4xqH9nR7h/RjTp+VRcAfw+E0GRI6CUvsG0NJ9JS4FnOv38yN7442WHVBoGykmx9bZ1Fxy/M4Jx2i/67JQmjWVQQf83LD3scBMMkaftXF6bPbseQMo1Up1q81zuoc00yY3Sms6dUT08Gyo1ii6CznoYwxaE92827PRTidEiAQw4zZLKGIVpwn6BwWiWBxzrxcY+zdXcHEUAEor3Ab7MRDGcdBX1cSZmi1i4IBrR01OoVbrtFRTJKkP5/sHKtR9d6z04PJJLJxTZcB0R2KRlBVjTtvXJ/0m7dcvc7oMxUEnajrnAvL8MSf14T4evjGyzuNY/p6IxQU2nUUljAEtWMW8Zr1vlBVE1CVGNatH9Lc6KV8mJCsKxvXnhUEfZ11umQahgS8fb3hJMQI6L5RYi7Y7FIysWD83ubl2+P3Xb+3k6ZkIMsCG9d2IwgCx58y2Lfa2OBn9JhUQJ9jK+KkU7MOziYS0eUHjz5hkJl//ZpuHRI95HWpGO2mM94zHg4r2O2yMf91fXidnFaWRZb/0sb8hflMnpbBs3/Zxk/fDSou/DvZ/3JAm5aWxp///GdWr17N7t27ufPOOw1obSKwDYVCfPzxxxxzzDEUFhZy2223UV1d/S8b/B/2h+1vWl8zyiunoD5zKHjaES56D/HJDsQL/oEw+RQER9p/fZJ/M2uvDqJENPInJPf4ppVYURUBT9axrByYxZ46jYuuGY9otvHlpw1Ikp6dPvzIfEINMYJaDNmtr3iJzTu9xIJLi9PmR1VWLW/nobs2M35SOkcdP7igBnqitGzyMeJgN2aLyG8rOljxSzujx6ayqqeDL9c0YLVJfPtFI/fdttHIfs86KAubRyedcleYsDl0Ft3XXtyNgoZXjbH4/RZMZgGPJ2L0qbhcJsZmpKPFQCoR8Q5EkzQnO4JB0mXd6UnPSDCAxq/NH2PNyg4+fk/P/hYrDnxEGT7JxRnn6uQqkiRgsonEUHHIMv19ERrr/caGYLWKSZWDBGFHwgnSgEzJwoAWjfeu6Qf2q2H66sM43fqGVzjMQc1uD6qqccIpw2lvDegQJklnWlWA3fsGUFWNkaNTuP+xSfz4sx6IS7KQxB57weUVKAEVRdOwFCTIQCAcCxGMBEiz5lBf69P7+1pDxAjS325ieEkyGUfCh0xPt1Bdu5dc+0g0TaNidAoWs37eU87UN1/j97XBitfMOINuLKbw3lc/4jblUKMjdHHF9ZEDAyID8Xt19oVlRq/Ulg09qIpmSCupqkY4QSajQe9APxoaqfH3+MwTB/XBr77gWDqq/s6U4QexdONqftu8DUkSyCuwcd4l5bzz+h7Q9ErjT98lQ3TPOLuUzRv0wLCzI8TBh+cN+XQwuFlwVD433jEWVzzIFQRd3/S0c0qp3+eloc7HiHLXYLVhSK7snx/U8Y/X9rBxXbcR4O2q7ue9t2qMuSSK+vwcOyGNgf6oUQHQHSXZ+HfCYQsGFV0RStCd+THj0vEK9ShqDNk33OiFkgUz7YHdaJpK1aZedmzvB0iCCSYgx35fjEhYIRiMGfC4gkI72Tn6uUaMdMefr/4uvrAfZO+8S3SZqATjrCvFjCk+b/zxoG302BSGlziJRRU2beghL9/G5o2DfWmSJOhOZTzwSATNa1d14nTJqCrUxzVH9w+SQJ/DkbDK2PGD633AHzOgdQm748EJPPvYdhRFIzd+r9IzrUZ1FsDTH2HkqBQURePjd2t565U9OJ2DAV1vT5jVv+oJgrR0Mw11PkZWphiVRP3e6oO02SVURa8kpbiHJANrvJhMQpIj/LdndxjBltNlwuuNoWmQnasHs7Ks0Nch4Iv2osb090cSZJqbfFx6daUuU2MWCQR0Z7a/L2K0RhQOcxjyLb/81MqaVZ1JAXh6hoW0DLNBVAP63Ny1vZ+AP2bMBf3vAtVbe5PYxQVBr8AfdHBOEkohd7/ePK8nmvT8dlbrVcicvLh0yX7PNhJWUbVBKRmbTTICJIAFRxVgs0k0N/opGq7vh5qm/29n9YAhY5Oo+EciCq1xHfHiUie/reykpMzF+0Mq9onrSfymEUzHLRbT+G1FJzvj7xToUM+mBh8nnjqc0nK3sV4gQEuTj3ffbmRA0QOy4vI03KkWjr3/GsSL3mVtVCedHErqM9AfNRj+S0a4De4A2SSxYWuMUETEExABAVUTsDn0pExC7zYYimG1SUbAqigaH74dZ22OP/dD5ufT3Ojj5ed2JEHHAcpGDiIvE0kGRdGwWCRGVqbw5EPbGIgnO/PybQz0R8jJt2Ox6oHhvhpdE7VxCInfUAuH1AOe9VBqGE3TEQpTZmYaBHElpXrAX1c7eE5RElge72VPSdET8YKg9/cPtn8IzJmg8lXddE7M+pZdq3ejRQeTFyGPL55wFIjGVPr7Iga6Y+KUNHZV9xuBsojKiLQuXjr1F1LpQEDF64lxeN4g9wGAxdvA9vUtCAKGZq1s1tm1d1b3c8a5peTk6gGv3SHT1OBnTHztikVVo9VkWZw9e/S4VD77qB7Q3xHPQFTfn62DDkFhkZNofE8OBpWkRMzQ3mRV1RAQuPL60WxY00V/X4R5hw8mPv6d7H85oB1q5eXlPPzww9TV1bF06VIuuOACXC59ciWC27a2Np566inGjx/P1KlTefHFF+np6fkvzvyH/WH/35kW8qH++ATq/aOh9jeEiz/QdS1nnI1g/vdscP9ftbqVHhyZMpllyaLnmSP0/96+upenHtnG7Hk5TJqaid8f5Ydvm1AU3d++6MoKdi8boEcKk5VjRRAwCAfSSyzYlIQcANx32yYqRqdw76OTkqot27/uIyIovL24hh3b+unrjWAyibS1BmjrDRCLqRQWOQiHVHzeKKlxCN7fntuJ22OiSw1x71OTiURUVEXPjI4odxGwxwg3K3z7ZRN+XwxR1J1djyfKGHsqw2c4qdqpk1QcdMjgItynRTAF9OVt4XE6GU8sqmK1Svy6tJ27b96IqmhYEcmMWqlRvdx01zhqa/SNIzvHSiSi4lWjuNLNejbaNFh1SUu3oCqaEYgMrSMIAtgFifQc3SmLxVQjcOhTw/TUhYzKUsJxPvXsUnLz7bzyvJ5tzs62GWyFV980WmfITTfz1aeNrFyhO8+e0KAzaHfIzF+YT2RAxa/FiCoJx1KgLbAbRYtiE/WqqcOpV75U2UvIJzNtP23BhPn8EdIs+UTUAKeeVU5PV5gp0/XvNtQNMsICbFzXbRwXDinsrWvj8ltfZve+ZkpdUw0SJ3uc/bF9l9uYP0MTAxvWdlNQaDey2auWtaOqujNtcgaQBQtog8yW4pCIfvyoUpwOG5lyBRmWYURiutN3xwMTuemqNTopjYDBfDrUentDBlxy1JiUpKpN4l0AmHtoLoIgGFl2WRa5/f4JiKJg9IhnZFkNh2do1W3d6k4+fX8ft127jnNO/MW49sQztFhEbHaZ7Fwr2Tk2bHYxfo260ywIOnunySyyeFGLcV8SDvtpZ5eyZ1c/e9q3kWEdzrCCDAL+oSznAiDwzht7jb80xHtZFUUlGlHw+aL09YbJzrXhGYjSFofzXXPzaH6Lz7uE3mXiGvcPehIohS0berDbJZSYagQQCZsdrxS9/cZeFEXDapX4Od4HnJpmIRRUMFvilSBBb0HQNI11q7vIigclkbCKLAvY7Qe6MYIA6elmiofA5gL+KB/8o4Z9Nfp48wvtbFzTzeJFeoIoUSFJSzMnOdeKArt36s7w+EkZvPHBXKN/FvTAXVX1ynbi71nZ+hywxVlmE6gHm10mFlPxeqP0xvWjBR2dTjSqGRVbgKp45V2U9MRVggxr5kFZhMMKqzftxSI4ERGNd0kSTJSUOZk8LRNJ1itPfl8UVdWIxgmV+nrDHH6kDjfetaOfZ/6yDXeKKakH3uOJsGRRa5JskNUmsW1LH/MX5jMwpI+6ZreHSFgzAj7Q5+MFl43ko3f3Jf19f5h/SqopqU8yERD390X5PUtJM6EqmpHg0MnMBtcPu11m/eouFEWLv6uDx0qSwAOPTwEGK/6P3ltlrGGFwxysXdmJwyEb8PmhlgikWpuTr2Eok3bCLBaJzGwrF1yqIzkSgWU4pLJhbY8RjADs3eXhtHNKsVolvN4IXu+Bv33MiUV8+M3hAKz4pd0IbkMhhU/er0OUBAQG23gSDLgJ+R0lRlK1/dsvGo1+z8QS+tuvHVxw2goWL2o5IMmZ6JH2DESMxJcg6Mm3/t4wW7f0GonjcFgPTjvadFkoHSavkZJmNpIM+5ssC9zz8KSkv809LC/Jxzh0QR5LvtffVafLRGQI4iUxh9IzLGzd3IvdIaNqeqJZ0/QERmb2IOrGb87DmerksIfuozVaQEwbTCT5HpqHtOUTUKP49lSxydjbNKTdizk18xPybXrlOMPURY6yF9vWD+iJZqBqImWuJg6RPhkcGyrT/W+zdWMHEhF83hgCGm8/uZS+7iAiCnn1HyD++AgAdjmMKMKkAj0wFzSFI+fp8+fT9/VWnzqvQNXmXuQ4u9SNo96hov8LwiEFuxTgtYorObvzLI7L/gEBjcCqT7B3bIxrv2tki82oa96l+vOvUBSNqeMl3MFafvxwPSYT/+9XaP8jO/jgg3nrrbfo6Ojgvffe48gjjzRYdxPB7ebNm7nuuusoKCjgpJNO4ssvvyQWO1Af8w/7w/5/Me3bBxCmno74wE7E6Wf+XwEl/u+0cEjhuy8befWFnXz3ZSNeTxRN06hb6aXkIHeS1ASANUVGShP465s7yM61ctt9ehDw6Xt1xuZ83iXlDDSGEXxQcWgqVpuM3S4bULeMUiuSKuAQ9AX/pjvH8cjTUwf17YCO5iCL3m7kO18Lmzf1IEpQWOTg61+OoKDQgSUqMc+Sy03XjcPlNrF1c68huzKmOI1M0UqfO0J1VZ+RbT/17BJKRrhQMzUcyNgUfWOSTXpldGpBBuEuBfcMCzu3687miafqiJGKyhR61DBSfINPSdHH6vPFcLpkVv/aychKN+4UExPldAIozD4nh6wcG3+L912ZLSKegSh+IUZLXwBV1aioTDWuOVEtU2Iq/X1ho9oom3Rnrkx0UXZIivHcEj1J/VqU/sYIi7/VN+aWpgCpaWYuvHwka1Z2sDIOBXXH9A1MBCRJpHprH2tWdvHSszs4+fRiRCF58b7w8nLatwZRQhoBYoYDIogqXcE6XJZUhPgRngG90mNS0nFlB5JYIodaMKgQUUOccGoBU2dk0t0VYuoMvfq6d68e/MWiKt983oBnIBp3PjTe/foHxh12Pd8s3sATd1yIy5yFxSpitUnE4j2jkYCJvEI9aB3Krrr61w6mz9Z/Q1U1nn+yOv5v2NFShUm0YbPJzI6zsw6VaWls8HHXTesJ+BVGphxEnqOCsL2Wq6/6luYGP1H8nHN5AaGgeoAu6kfv1hmkJEccU8DaVYMsyAniJlHUq4KxmMpzj+vjOuqEQrKybWiaxvKf25gzL5vVQ8Tth1oopBqBjSfei6eqevLkgsvKCYd1IpWrbhzDsiVtiKJe3UjMnUAgZjA4797Rj8kkGIFXZraFrs4gF57/Lf7oAMNSRtHVGaRlCNNnnr0CQdQMJIPVJjFrbpYxjuU/t/P9l4062QuDjq7dLmMyS7z9ug4NTs/Q36f9GWgFQT9PJKygxFTWr+kiI9NK7V5PUqAGuoPc2xM2euQ62oPYExXoeE+lNqwAVZYRRV1ypLHeR1tLgPAQuJ/NJhEZAlFNLPmyrMtD2YfI4NTs8fDBP2pJSdXfrdIyJ6+/pDuIs+Zm01DnQ5SS4YeJc3oGopxw6nDueWQS7W1BA74MgzqiE6dm0NMdJr/Qzq7qAQN+KAjgHYjwy0+trPi57QACI02DjCw9SE8EKgCOeFXPZpOIRjUjcOvuCNHaHMCspqGavNhNqUZSSBJkDjokJ34uPUHSE9d0Bj3QUlWYf1QBjfU+7rxhPQ6n3ss4dFyxqMaMOVmcfEax8TdJ0gmAjjq+KImMp2dIhXQogiUYjPHmfuzVZrOYdH9DQRVtv8ockCTTlHx8Qq8KnE6ZQDCWFBCvXNZOS7zi+stPySgMRdEMqHhLc4CXnq1m5bJ2Y7ytzTo6ZmgfcMKG3ptJU5MJI5X9+iVFSb8n02ZmYbNLaJpmJPwEUX+fh7YimMwiBx+Wy9uv7+G0o38x+h9z41Vqq03i8msqjbaW3p6wEVR6PVG2bu5FVTSjOldY5MAST0QMXecSwWFfb5i/v7KbgiJ9/U2sIdur+khJ0bWdExJWCUv083/0zr6kcWuqDqHNybNhscrIsoDPG8Vul+hsDzG81GWc/5D5eVRt6mV/k2UdjXHw/LykBMTGtd3MOVify5Ksv8uLvtEl4mRZ4LnHddiPxSpiilcce7pCSJJAYZENrydqVFYLhzuSzr1pfQ9XXFfJ2rUeJFkgM3uwGBCYdytmpws0lV3belDjD98teXh0xH2Mce2mNaivm0Epgw3B2Vy46w3UuH7uxQ+exDv2V43zCYLIp/6LCagOYpqJhLKDxWpCRUASVB75YSpnPT8e0PB7Q4y1VZH5wXH68xfDTGl5FACPRwRZQjhkFrZDJxJDxm0NMX3BaH7ungcI5Dv72eSdSHV/MVaXnkAIenzYgo0ImgIIjBCqUN86j1derEEiRnHD3wndO56W6npS6OLUlHcPeE7/Dvb/c0CbMKvVyllnncWiRYtoamriiSeeYNw4vecmEdhGIhG+/vprTjnlFPLy8rjuuuvYuHHjf9cQ/rD/wSZYnYjP9CCe+zqCPfX/9HD+W02JqfzyUyuXnP0rzz9ZzaoVHTz/xHbO+9MyPnu5Dl9HlJK5Bzbwx2Iqq0NdBIIxHnpyKqoCTz+y1SBAKatwc/o5pfz8RgtRVE6+rgSzWcTpNrF0cStbNvaQPdqGhkaWqC/4k6ZmJCUK+nrCPHrRZn4LdVEw3MEHXx7CUccVYbFJfPZhHWtWdfLnBypBgGdu2krVph4uvrLCOF7YBzFJpS7g5a9PVRsbcFqamdaWAPUBPzWyhy6v7jRFIyoZbgvDvA7yp9l59tVtuvMqQG6evkGXlDnxalGsGXrPiMmsVzDqa7309UZISzfT2hxg5oRsCmQH22K9nHNRGd992UjNHi+CoFeuZFlgQIzQHgiSnm42aPCdLtmAEHZ1BPnzBasMh2f02DQEoEh2MOOk+KYXULA7EhXaCGpUY6B+sMJx/W1j8XmjPPOX7brYuQCN3XogogIvPVONJAnk5Nl46MkpnH1hGaoGaYIFEwJlFS5OPLWYje92YXVIxESNQBzy2hdqYXzGQgQGIbKAvoGLCmml3QeIwIO+ZgdjHuxFDdxy6xx++LaZ4lInJSN06Nnunf2Azqb416d3xKtIGnsGVvH9qqXce8OpNK5/jfNOPVR/blEVi0Vkaxxu5crvIyXeR5wIDrZt0RMdhx6Rx+pfO7jy/JX090WQZYiofrKduuyM2SLi80YRRcGQCgL4/KN6NqzRHUdZNIMcYUfDHrRAGoKgEXbs4B9/q0fTNGMOJ6DgC48rJC3e39vUEEiq0Djiz85kEqnd4+HOG9fT0qTDz/MLdIehrsZLU4Mfp9OUNKahdsiCXG65e9wBFZ3jTh5uVGyuumE0q5a1Y7GI+H0xps3KMqr7n39Uj9cTNfqth+KZi0tcvPTMTtwFPVhNVuxkI8mCAQNXNYW1XZ+gCTpUWRD1/t6E3IogQFdnkHffrCE710pPd9hwRA9fmMc9N280mHr3r6wnHOlEX7jfF2NbVR+egSgms0hbSzApUAOoq/Vy1YWrdMIySa9OJs7T640761nZDMyZiT8jk2hE5del7QgiRk+vLAt4vTFiUc3QAR0zLs3oD4vFtCRd12+/aCIrx8JAfxRJFvgtnniwOyRuumscG9Z2Y7VKB1TwNU0nqLn86lEA/PxDS1KPdeI+5eXrSCCLRaKjPRhnbNZRHZ9+WMej924xKvtD7eqbRmOzSWRkWoxABaCvJ0Juvg0Bkircv/3aiYZKu7gWWUkxnp8gCMiCibR4pcxq1St1rS0BquK6y00NfmzxqvktV6/V73d3mP2V/6bPzuLBJ6bSMgQiGgzEyMmzsa2qj/1ickCH4iYqulabzMN3bzE+SySeIhEVZQj51dDEAHBAoml/C/h1lA7x5KamkhQQ/7qsw/h3a3PggORBQq5lz84Bvvi4Ycg4VOpqvUlBj3k/6RXQ73OiNeH3LCXVhKrA7Hk5fPlpA08/uo1XX9jJmjiZIZqe8BFEwWCdtdtlLjn7Vz58p9bYVwDa2/Q978LLRhoVx8QYEvcz0dowotxpoEEKihxGwJxoWZAkPSH24J2buOC05fh8MVqaBtmkJ0xO5+qbKjnqhCKsNslo7THFkdIBf4yWJj+ff1w3yNAeDxZVFa68rpK2lgAWi0QwqCDJIi63yajkWywiH72z74BkkcOpJ6wiUZWN67qT5pXHEzV6d80mkc0beujrjaAoGv19EZob9fGHQ6qRdNQ0fV2q26ezsufk6n5LY52frv3IDz96p4bPPqpDUzUOHgKx3SXOZZc0l5hmoi5UYuwVYdXMmXs+4qnuB439PBSTiURheBz+LMkwdWYWra1D9gBBoL0/gRIUGDU6FavdRE8kHVEUKCxN56BDcxlWkQsIBFUHu6ITubbpDf0Zq1Zeyte1vtE03A6R4Ncr0fY2gckMrnTu/uUIYrJ+rW2mcl5pvZyn665GmnM+GgKR8WfgOPhcVFFfG1YrR7P2zCZ2Bipxp1pQ51zBfcGPqAsVk5qTxk+eo/l3tP+2gHao5ebmcvPNN1NVVcWmTZu47rrryMnRMy2J4Lanp4cXX3yR6dOnM3bsWJ566ql/xVD+sP9BJpis//WX/s1s145+LjpzBY/eu4XCIgdvvD+Xd/55CB9+fRgHHZzD2g86UUwa9uG649bTHWLJohZWLW/ng7draen3M13K5KUnqrngtOX8Eu/BcLpknn1lJqGgSmiPgqlED2Ttdpm8PBv5hXZuvmotjzy4mV41Qk48oB1KhlC/z8tdl6+j1uMlJ93G396eQ3aunZw8G+2tAd7/Rw0Ljyvk/fdr6VPCZIlWhpU4Wbms3YDllpicZMyyEggq9PVGDOfwrVf3sHN7P22tAbYH+hkuOnAh88TT05khZaJpsLil1XBcNQ3McYd4+ZJ2Fh5XSMXhqYiaQDSskpFl4del7cgmAc9ABL8vhrwZmhQ/Wo4OYf77q3sYNzENTdN7Bs1mkZawvmlOGJ1hZKndKWZDk+6C01ckQVLbW4NkiVYCJoWUXAuiJBAMxoxKkZ8YUU2lwKoH37IsMOugbF54sppoVKW3J0ypw01QUwyHJyPLyiGH52GzScyam8Mn7+tZcrcgUyA5eO7V2dT96qVlkx93oQ7h8wxE+OGHPTikXCJKyMjua5oOWezqCNEa3MqSHxu4/3adOXd/Z7I3Ws+nf7+Wvp4wvy3v4Kjji9AUfXOPxCUllJgeVh17YhH7+qvoCNZwUPkC7rz2T1itZoOVWlX0PrBEtXFfY6dR5enuCrFpfTev/nUnZovIzX9eyz23bKQ2rqsYjWp4Iz24Rb1n2zMQ5ZSFS1BVjW+/aBo6ZEaPS8XpkpEkgUMPG86krIUIgsCFl1ZQkTGPmKqTnRkOX7y6UjTcaVRRvvyk3gh0AaMPSRAF1q/ppmpjL1arREGh3ZBQ+PlHHZ757ZdNSTDNhEMIMHlqJst/bsdmk5IcqDdf3k3AH2PqzExmzc3m+6+bDEbK628da8BW33ljLy63CadLprkxkOT8bljbzdkXjWBHwy5S5CIEQTTG7XKb0FBRtRjRmIrLbWbMuDSsNtkgx9E0XfcxGNQZyofK7Kxc3kHhMDv3/0Unpfnm82T210Q1LRGQ9vSEePv1PWRkWthXoz/DRKCQIJH5bcXg81dV3UH3hOLw/UgMURSwrtmMULUbf6aeGHrvs/ak4GXeYbnces94Y04AjJmQis0mI4g6emBohbarMzTYk4w+J0URHn9hOj1dYXq6w9jtksF0PtRGlKfw80+tbFjTxbIlbUmMrpqmV9G++7IJl9tEQ72P4lIdspnQtywd4eL1Dw464LxTpmcwfmI6tXu9ScE36GObMj3TIIFJ2Iw5mUSViJHggUHEiCyZicUv0mqTsFol9g2pkCc0aa+/fDUBfwzPQBTZJBj3JXHcHfdPRJIEQwoNIBaD/AIb333ZyKjRB6I6+nojRoDVH5c5ySuwYbdLRs+epv1+z3PCVHWQ82CoJeZPwK/rOqel62uwvF+iRJYFbr577O+e+7iTisjIGkxECALcfNc4Djk8Nwm6nzCzRTrgHJqm753764yCniDyeaM4nBLzF+YzaWo6P3zTzD8/rOeEPw0zjrc7ZGJRFTV+IzwDEcorUoze1ARRX2I9ziu0c8s1azlxwU/GOaQhaKyMLIvBBm42C1isotHakSBRVBQ9+N24rhu/L5YUuJtMAg88MYUTTy3hkj+PwuU2G58nEl5+f4yXn9+ZpPGdsFPOKCbgjyUF2qFgjIMOzjFg8+GwyuTp6UnHZuVYKS5xoWoaSkzjtmvXJfXu2O2yLkMDIMDe3Z6kPtCEHXV8QdJ/X3/bWAMynXj/8gqS287OOK8Uk1km4NeJ+D77sN747O+v7mFndZ8xFxKIlrBmozfowjMQNVqFEkDTuhovsixQMSqV7q4QnUN0bRPfTTzPXTsG8Pti+ONzeV+Nl+qtvbQOYVK22iQ6vfqYNUEiaNYDZtkkEAzEmDXGSqipB8Fpw+OJUrOjD2WMzl0QKcrHetI8nLNGYU7V/YyAP4rdIRvXFImofPR+IyNHpWBzWmjssbOpxsbI0WnUNMsMmzDygPv872D/koB2qE2cOJFnn32W5uZmvv32W0499VSs1rguZjy43bFjB7fddtu/eih/2B/2b2XNjT5uv24dTpeJl9+ew1+em8awYn2hzsi0cu2NYylzuGlQfVx81q9cffFvnHHcLzz2QBX33baJd17fiyyIZAlWLAMSRx5TSH68inDeJeXYbDLf/bUBKxKHXaEzXlrtMoqq8dyrszj+lGGsWdVFZ2qIPNGOCR1Gtnf3ANdduprLzvqVrtYwggRPvj7dCFZy8+z4fTEURePHb5vZVT1A2K2SI9ro7wmzZ9cANpvEaCmVNjHIj7viJEeSDiMD+Pibwzj93FJy8qy89eFcSiQXh1nyWPdAB+aIxBZTL3UtXtIzLMZmpSoaoiQQCimccV4paVMtCEBrtZ/UVDO1ez2cdnYpkiiSKeg9sJuiPZSOdPL849sRBAzdxfa2IIGAgleN4RBktlf3YrfLpKWbMZl0+R7ggApAZ0eIkZKbXncEQRCwWvWMtdU66Kx2qkFGZaQCcVbUXQP8ulTvixqZkUK9T4d7JQhijjiqAIfLRCAQw++L8mk8oA2gUCmnULt0gB/+0kiVq5etO/uIRTX++eE+Hr9vJxElgFV2GlBXgDUr9f4fKZZCmrnQuIahjqaKwqwJ48hIc/HKCzux2iTa2wI8cMeW+PwbdBCOP3kY9e0N1Hu3MMwxAcFbwNef1dPaEuDNl5Ihh5GwgoaGw26mJ16t+utTO7j1mnXs3eUhElaTtFlBrzylWQoRBIFjTypCEHToYlJHQfzfLY1+fN4Y7lQTa37tRFF0J+CnH1roaA0hi2b6wi30DeiBaOWYVERJYMOaLqMvT9NIEpZPBHfhkC53oiga84/Kp2i4k107Bmht8fPZx3WEggo5+bYk1t8hSnd89lEdmzf0cPPd49mysddAFoBedb71nvF88UkDoNHdFaaswk12rg2ny0RqmpmRlSlMmqo7hUMJaBLz6M03NhDzu5haPtX4uyjplWU5XoKTJejvCzNrbo7Rz5mwRAJhqDRJQZEdJaZx5fWjeTYO8UsQxg21nFyrkdi54rxVbNvSZ0BRrVbRYGhOBNmgPxdB1APpf34/nxPvO1wfoKqiqhoDvWH82xqILdUJVmI9+vhki/5enHp2KZ0doaR5EPAr2GwSgqATugx1gN2pMl0dIVxuk96TLMJNd41n+c/tPP7AFiRJoLsrfEDrBujat08/so3br19vJNCGWtFwB7GYphN5xVQD6p0V79tzOGWuvvC3pOSX1SZy+/0T+fmnVlxuE/194aRrmTIjE4dTNt6HxGch+pAEE4I3x3CSE8k2s2gnFhuU3/F6owYRF8CIchee/qiuCxuvsMeiWtJ9mjojE5fbxNrfOg3ZIdCRCoGATqI0snKQJGj/6nvCjj9lGP19EUrL3ElVWYv1P28F6u3ZT+fYLBiogMR9HzUmlVhMS2JEBp2ZecUvHcb1u1IGM0rLf2k3WloEAT765jAWHleE1S4dEGTf99hkTjqtOHmNQU8OzTk4N4mJPmGp6RZMZolwSOXBOzfT0xVm3IQ0JEkwqrqCoCMYwmHVCIZUVUenKDE9IZeotCbWoCceqGLn9v6kZE50CMy5pyvMnjhp0LASF6GgapBQffnPwSo0DLJqaxoGqqFybKpBctbU4GPZ4kGotjUe0L79+h7WrOxMWpsTz725McDbb+wlI9NCOKRitug64BrJ0PFN65Lhxjm5Vmx2yXiGt947Pulzq1U0WjsSiZJxEwdJ3qbOyMRqFY39DPREx5x5OdTu1e9H2Ug9EByqMQ16e0Bzow+rVSItw0zmkEQHYIzJah3UNLfbJUwmkTPPG8G5F5cnfV+UBFwpJkrL3Sz5ofV3kQaqqlfwyypcxudZ2VZKy1x4B6JGctVqFfF5Y5gmjdSZITWN7PoaY1ySLBKNaRQWOdD6vBCOcvblldx6gh5XRWtaULsHUEsK+Wiz/l77AirpmRbj/QmH9D1kz64BWpsDrFzegSBA0TA9AP4yLq3072b/8oA2YZIkcfTRR/Pxxx/T3t7OZZddBiQLxP9hf9gfplsspvKX+6tISTXz+AvTf7fPseaXAdSIxnUvjmXmnCxS08zcfNd4PvtxPguOLsBsETnu9OGklpiZkpfJuElp1O3zUTTcwXEnD8fTHqF9SYBAaoyKGfpGYbPpenCiqGvzmcwie/s8eNUopZKTdb91cv1lqxnoC5PvstOvRrjtzvHkxDXqYDDDHgnr9PePPz+NE64fjhgTCDUqHHRILqcdV0qN4mW1v4uUVDMZmRYcTpPB7BcK6dWVcEhl6c9trBW7aHMF6c+IsjW1j7peH0ccU8i+Gi/Hnaxnv8MhXRvWZBa5/rI1XHvdamJofPNzI011OgSpc2+QSFQlz2RjaaAdRdDo6gixcnkHDofJGPPQjK7VKtHVF8Yfr2gkCJESlppqMoJPCYFuNUS7EuDOG9cTCsb46p8N1Nd5je83iD6aOnSH1+eLcstVa3WHzQuhnhgR9M03UQV2p5ix22WCAYWnHt5qOF/dqu4cL3uslVWRTjpCIcZPSkeSVQIRL6IgY5PdSMJgMD10uc1xlJLlLDxgXmmoaJrGnBllrPutk59/bCUW1fjhm2Zmzs6hMvUQgv0W41yff1LHj4v3MDH9GIbFNWFfeHIH552yjP4h5DEJfUvQsGnZenJGwOjlStj+EOgW/w5CiofSMhffftGEpsGjz07VEygCOBwybrf+DAYGogiCDtcMBhUkScDtNtPSpEvIiIjs6V+FR9pDSqqZ9Ew9sbE/jLC/d9CRT9zvhDNgMgl8+0UTdbVedlX3c94py4lFdW3fhJ6hJ9LJPs967BlDnnudn8qxqXz1zwb8vqgOmdT06w+HFO66aQNffFKPy6W/P5fFIa52h8ykqRn89Y3ZFBQ5DTh5wkwmgXMvLsMkOKlMPQRP52CF64rrKuntGYQP6wQtunPW2x1i5RCI5u8p7TXW+8nNs3HTn9ewe+cAFovIjDnZB3yvoyPE/jjUlFQzBx+ei8ksUbVZv785eYMomlhUw2yWeODxKXSGZH7cJRoyOzfeOZb0TP06lKHtt7KEvGAaoDu5SxY16/3gcTSDzxvFFpeniMW0JO3FYEC/CV6PPkcKiuw8+dBW/vlBHftqfCiK3l+8//xzOmXe+/wQps7QmbclSeC0s0uMz3PyrHR1hDjy2EJy8myoKhx78jA9sI4Hx1s29uoakUPsrPPLaG8L8PVnDUiigC/OYpx4r8ZPTOfHbwfJWRL3ZvvOJkRBwiI5kiqroAe0noEId9ywjsZ6v8Hgm7BE0kKWBKMimF9oS9IADQYVNqzt4v7bNiU55tm5NlqbAhSXOvl+iGzRpKmZSQzzCSsc5iAYUBheMjhOk1ngiKN1pMV/5votODrfSJBarTKSnPxMerpDRpV0KHEQYEgwCQJYh1RZ73hgAnnxfcqdYiIj00pne4Af43wGifFMmZ7JpKnprPut64B3oqDIztbNvQfcd9AhzqGgQiymUVzq5ILLR/LMKzO55KoKGuPrQuJ8U6Yn9+EmKre93WHjOwmSMp8vlpQkGz0ulRtvH6uTyNmkpOvPyLTg8USMtoehUmH7WwLVsHVzHxectpzVKzt4JA4TP3SBzvJuten3PaFJbR2S+EgEehvXddLZHqS7K0wkohrB4w/f/OfEQn09EYNtHZI1uwGOOXEYpUP0goeOw2IROe2cUsIRNUmv2++L8fiDVUbwX7NHn+9D+7wBXnxqBz5vjFBIweU2EwwqeqLUIlA5NsVAroSGBOTDSpy4U0ycckYx38XnvzWOSlHjMOgR5S4+/6jOWG9N5kG9V6tNZPS4NJob/agqFA23UzzCRX6BnZf+PttIUiRItdR+7+A4PIP35uDDc1m/uguLbZA00CrE+ORdnZlajISJbtlL8KOfGWHSr393WjFWxxC4UNyGJqM0DZb8oCP4hup3/zvZ/98CWoCWlhYef/xxZs+ezeuvv/5HMPuH/WH/gX3+cT17d3u44/6JSRIRCdNUjS2fdOMaaebp57fx84+trFnZycfv7eOjd2r5+YdWzr90JFdeV8mEUzJoXOPlb/dV6+yfGRbuunY9j56/mUA0xvTLBx1UPXCK0dEe5KfvWjj3ojJy822sUbqokNz89I8WTGGR9uYgXd4Q11w6moOOyUsa24/f6fT0WTlWPvz6MEaMdPPoU1W0iAFku8jKZR384+O9iPGKbO1eDxlZVv729zmkxQlnAv4YNps+lm+/aOLghXnMuyKPxfta2dfixeWWWfFLO/MX5jN2vM7eu3tnP9H4hiqKAhMmp2OxiKTLFtKiZmxI/LhCd162hvsJo0P5du/0MKLcTVtrgNIyF3kFdgqHDbI89gTDjJJTMAkC4yemJWkYyrJAf38UJc4qLAK7FA8dHSH6+yI4nCYiYSUJgjQgxdii6BuzqsQZUBXojUTYG/YaTng0qiGKAl1dQWx2GZ83apBGySYBQRb4MdxK95QwXaEwf3luGmUj3USiMaySC01TDYfEmDea7gDe8cBEUkbvQirabkDcHA5Zd3I1AVmU8HpiPPHQVgRBz4y/+cE8upok0syFiLJiOLGCIJJuKcRpSkcQ9GrK0KXd5ZIZNyGNtHQ9Q6xqCmrEqsNRNZJ6uYCkanJTaCO9kSbyMrO47b4JxnmffHib7uRpGIkGvy+GJc5qqc9lCQ2dBCXBhJuRaaU8bxS7uzYzEGkfooOpUTTChN0pYbWJPPbXyfvdt0HPtnmgBilnH+4hWpyCAF0dYQQReqL7qOr9Hk+0gx+rP0NDQ9N0pqUd2/vYvL6HWGyQqfXmu8YxdUYWNXs8hIIKPd1hLFaRB+/cxIkLfqKu1su+Gi9Vm3qo2tTN/haNarz6wi6CygD24fswmyWjJzIRYEvxyKSsXE8YPf9ENX29kSSG2P/I6mq9HHRIDhdePhKLVWLV8vYDv6TBtJl6wHfBZeVceV0lLrfM8l/a8XqiRmW2oy3Zaf3z9ZXk5Nl55VfIc0N2pt6HWb21n+ElB/ICyILK+BS9h/bpZ3bRHJ87515UBuhzwWbXEx2qovHiM4OygdEh5F4ut4nmhgCSJHDldaMQBDj59GIcTpPRP53ooYxGVb7+rJENa/V7P3tejvHvxDUN9Eeo2tRDb3eI1DQzV90whnMuLkt679GSGXE724Ncc/FqggElKfGTsH+8tjdJq9Pvi6GqCrEeHa7+e9BdUZD44t0uo5fcQACYdabkBCGWxaoTTZnNgsHaWzlGT5puXNvNHdevR1FUTju71CBdkiQBr1fvix6KPPB4ImQNIdVJJPcWfdPMmHFpRlChPwM9MZaA+P5H1t0VNqTQbDYpKbAWBNiz02PMqUuvHoRHbt7QY3xXkkX+fEOl8dn3XzXR3RXCatP70zet7+L8U5cfMI5Zc7M447ilBrP10KTIruoB2lqS16uhJpt0NvyMTCsP3rmZu27cwNf/bDiA3XdXXJ4I9KpiSoaVymMr6ewKY4v/3lAm5IS5U0w01Pl45i/bdXh2poXyCrdRYV+7qovN63vYu1s///4a0UNNlHR4cl6BneZGP/fcvJGavR7SMiwGcqOxPvla/d7kQOf3oNr/lSVaE9raAoRDcfJCAX7ej8RroD+SRE5lMotxqSCdYPDOG9brnB+uwXU4GlWNd3P/RGnCBAGaG/3YHRJZ2VbOv7gMvy9GcakTh8NEZpZtMEEtCcYxu6oHOO6kYTzx0FY62wODJyO+d6o6+39fb4RRcQ1Zu102KuGjx6axfk0XoaCuId7UEGD96i5WrejgzhvXG+uTpoFp8kiUli7U+HPo7hpEFvzyUyuCMJh0VVX44O1auuLoD2lUCbZTDiH73MPYs1Ffq0MmK8/9eGCQOrRnXxySGJm8H/HZv4v9ywPaQCDAO++8w4IFCyguLubOO+9k505dmiIBObbb7Zx11ln/6qH8YX/Yv4WFQwqfvr+PhccWGgtjwjRNo601wDsP7qG/IcLXWxvQNLj2lrHcfPc4Rlam8M8PdObQRHazYLYTvxjFFNSd/YHmCC1b/Wwc6GGp0o5iGlzUbHYdIvvTd82YLSInnV7MDbePw6/G2K14qJBSCKKQZjJjQ6YrEk4a22cf1bH4+xYEQeCJF6bjcpt49i/bCAZjrAl04fFGGC+mcWZFCYeekIfPF2PClAyefXkmufl2Qycv4I9htUuEwyrdXSGOO3k4C48t4uW353DKmcX4vDEiEYVLrx5l9Cw+/kAVoDO+jih3IQiCrlkoxigtdHPVn0YhD1m0x4xPNXrdEhClWXNz0DSNro5BaYaZ07IYLaVw/LRhnHbOiCSNykRAUJym3+ts0cqMOVmYLSIvvTWbjEwLfl/MIIwBHQYaUlWKRDtzTFnMMWWz0JyPXZKw2SWef22GwY6qqhqfvFfH4nglKuE4xKJxySBR49ffOvjTGcW4U00sX96IiImgMsB1t4zjyGMKQcCQOzKZBJ5/bSaHH5lPLKpRva2H3HwHaelmVE2jLVRNSPECIt9/3UR/XwSbXSYrx8pNV62lsS6EIIioMSkOK9MIi92YTRJC3PNNSTMnOTiBoEJKqpmjjterwc6sQFLVOGF2u977WjTcwaHz8zj+zEzq+7eRbS1DUVSefGirwUbZEddh3B/aNTQYDgQUNFXD6ZLJzLZhsYj09kR44bHzObj8GAiks2Nbn0ESVbvHQ8CnEAhEmXXs7fqY4uQfTb6taJqGqqmYTDLLqn5lxYZBQkNNg1GjU5g8y8Xu3t/483lHc/KMMylzz0JRozQFtlEbXArCoFORCBRuuGItTQ0+I+gQJYGxE9L405klnH7uCEwmkcZ6nwHLBugK1rOzbylRJREwaZgEO67YSMwWkRHlOiT02y8asVhFNE1AQKK5IblSMbS643LLzD10MLklxOdNNKqx4pcOHn9gK56BaBIkeeh3N67vwWwRWbakjZef36kTwmgHfi9hqWlmjjimkC+3QnUbXHYQOBwm3Ckmfvy2mc3rDyTfkUSBde9vAaBlbz8AmVkWjj5Br/r190Ww2WS0OCTU5z1wrA6nbKAfbrprHOGwjkQ5+oQiQsEYcnxqjhylB3h6wmCnURH8dWk7aekWxoxLM65HFPX2ghNOLUZTNd55Y88BWqag92wnjkkw7goCSRXOxLujKMnQZl2mSaInrFe+0tIOTHQCpJgKktoIrDaRlDQLqooRrCdaJmTT4AuUCOAcTpnSchcWi0R6huWAaldiDiasfp/XkHfKK7AxdYbe81xX4yWv0GacN2F5BTZycm0HEFENtc3re/DGg3mfN5pUQR56T2RZIOBXkz5LSOSMHJVCbv5gULNudTdHH1+E1SYTi2nces36JIde0/SA/8WndxIKKlxyVQXlFa4kOKr5dwj0jLHEkRKKovHY89N44IkpbN7YQ1trkAsvH2kkEyC5AtbXG2GgJ8TGj7ehxlSC8c+6O5PfVV1yLIo/AtYTDkLKScUT0Ni9c8CYq4me4v1RJcYphMEeXUHQkGURryeKeUglsbc7bGil7m9D39+0dDOf/7SAmQflIAjgdP8nD3SIJdQIVAUOXZAfP5eFhn3JyKffVnQkQcoT1eZxE9PxDEQZPymdcRPS6enWE4miiLEOTJiczpsfzuPVdw9ClgVSUs088/JMhHgAbrGKmEwihx6Rx6cf1jN+UjrDS3Sf4del7cb6YMjyxYfxj9f3snfXgIGeSSQ60zJ0vgx9vZW48HIdkiyKAuGQHsBuWt9jnEjT9PXfapOwO2T64++jxSoileZjGl/G2DkFxv6WqASLop4UOu6kYfT2RPTrMIt8teQIopIMFhO21jb4bDF9X61GS9H9kuCyLQT9vy+FBfo7n5Wl+02iKFCxn9/572L/koBW0zQWL17MeeedR05ODhdeeCG//PILiqIYQSzAvHnzePPNN2lvb+fdd/89aaL/sD/sv9t+/K6Zgf4Ip59Tavytoz3Ikw9VcerRP3PNKb/RuzRELEPl/ten8Nyrszj2pGEsPLaIyVMz0DS9p+vOG9bz3GPbuOScFfzka6NRDTBZTmfcQBqTijMQBT34ePjuLdz05zX0doew2WUCgRiLF7Uw79BcbDaZ8ZPSmT03m92Kh9VqJ5WVqby5aB6nXl3Kh2/XsjTec/P6i7t5+bmd2OwSC+I9hou/b2HVik7CYZWL/1zBsy/M5NJ7R3H+axWce+VI7nxwIg88PsWAlyWYb33eiEGKVDk2lbKRbqJRlc8/quPzj+rj2nIKZ5+0lFuvWQfowczEKRl89PXh/OW56Tz10gzKRrqZtyCXcx4uJ1CkElM0zBaRuYfm8vxrsznnIn3jSY07h+//vYbGer8BzQNYu6GLNjGIq8vET98mw6jcbpnTTiyhvS1AimCCfIH5CwuIhFV++bGVpkY/oiRw1U1jAH1DSjjZATWGpukQ5Z9irQQUhZxcG48/sJVgQCE9w4LJJDCi3EXTfjIKiY054bh88n4d552ynK62GBoqGe50JEmkv08PKlRVJw959/NDGTUmjYY6H9u39CNKGk+8MJ3KsakE/DGafTsIqfuxfVpElixqjVcmNDRN4ciT0jj2lHwEBCxqJoI66PR5ByJGMmXytAyUmEbNHg/v/12HRDV3N9IdSu7tAp2F87pbx/D3jw/mkAV5vPL3X5BFE3OnjMfnVdhX48Eed8bcKSbGTkhj9twcnn995u9CHgFDOqWtRZfkKCiy8+DtmxGCmfSpe/m1/R3Wdn6E2e3HLNuwO0Tsdpm5I04AoKhCwRPpxBvrQhAETLJIYUoph5ecS669nIGwTroystLNOReX8cmiJVitJu676VROP7eUuROnYbeZccmZiFEXkTB4I3qgZooHE2npZro6Q4RDemD93Kszefz5GZxzUTlnnjeC2fNyKBnh4vxLy4lGNSKqn0Z/Fc400OIRY114FWaLQEdLjIJCh6G/qmkYMP7RaYcd0HM4VAPY64nx69JByaHX3z+IH1cdZUD6f88S1ZbjTxnGsOEOImGV+rhj6vXEjKz/6eeWGuNJWH9fhEvvb+Tvq6Fc6eKjJ9eyY3sfne2hpKoYYJB4aWhkZVuSqgnzTiwjJdWMKOqSJrIsGFBBrydyQI9nZpYVVdXv/+pfO/j4vX0cMj+PZx/bjiSLRm/jsHiyS1U1XCkmoyJ41Q2jefyF6cyal21cz8QpGbzw+mwiYYWBgSjvvFGTpEGcMF3GRf+3Ox7gaJqeGDsoLlGyP4GN/h1t8P+HONGJZzDvsByGFTvYN7AeheRqbyioGpWwpPuQbTXGeN6lZTz14gxAb3ep3eNlxkHZvPbiLgPlkZZ+IFlT4vygO+evvjOXex6ZxIKjdKKeJYtayc1Pvp75CwuwWKUDgi3QHevDjsjHnTL4/KPRA7+YWJ9iMY3vvkomKfP5ojicMqGQklQ5DocUwmHFCB4SVjR8MOj1eKLIssCJpw7n9HNKsdhkAy4MkJFhISvbasz7oXbXQxPJzbWjqvpelJdvIxpVSUsz8/Ddm5OY00URjrpqqnExiespKLIb586dU54cQcZvg6gqpG6pItTSi7cniCZJ7OnSv5d4v3+PPEn/XQG/T2H0uFSmTM/C79Ml3g4+PI/TzinlwSencMs94xiaicrOsTJuUlrSfQc9ED/7xKWsivdfTp2e3Iow9B4NZYwe2t6RkEBKsCEnWIlhCEw4fmhivtTu8aBpcPv9Ew2UZ16+HUkSDc3YP98wGlnWE3sVlSkM9Eeoq/UYWryKove7b6/qY1d1P5OnZVBQZGegP0xKqonU9OSeWtDnf2qamVBIMZImib7X5kY/qqJLa6VnmA0t4f6+CG1tAfLjEnXpGVZMJpHyCjcOh0xamjnON6L/RjiiYZpcgdbUjsnrM8jUEuuZougIu6otPYwod+N06gRjb75VR6A3ANEY3m4/x59UxIJDMqFVh99rfR6i6/RCItbB99gaT9j6fTE62nWkSW6+zeBq+Xez/9aAtrq6mttuu41hw4axcOFC3n//ffx+f1IQW1payv33309tbS3Lli3jwgsvxOn897x5f9gf9t9tXk+Ud97YyyHz8yko0mFKSxe3cslZK9i+uo8Fmfkcbskjr8TORa+OYvRYfaNRVX1jf+Yv25hzcA6vvz+Xcy8u49svm3SqezTy8m1MuiCT9HMtLGloRdFgYCCMwylTtamX04//hbWrOgkFdeKPBUfrFbV9e3UILYDdKfPYy9OxO02cdnYJhx6Rx9OPbGPR10188v4+FhxdQDCgcNLpJXz7RQNPPbIVgMuuGcWZ541g2DQXFUekIltEnE4Thx2Rbzj2gFGhbWrw89lHeqX5zPNGEAjEOOekpSxe1IrFKpFXYGPESBfZ2TY9aIvbgqPz2bfXw4fv1PLovVvYt9fD4u9buOK8lfztWX1BLy5xctNduqTYvMNyefTZaTicJl3i53cITjQNLONlBtoi9C7br8/n+GHEtqn0a1G8WpSBgYhBmvOX+6twu02UV7iN7HfOEOeuhwi/xTrZrXgQ4r9bv89HzR4vWdlWIhGVaFSjdq8Xv2/QOS4tc3Hr3eONaoEsC0ZVKawEEAWRYEDluSe2s/znQXjoi2/OJjPLSmO9j5uvWoPNZiGvyEJKqpmRo1IwWfTjraLbcB5GjnITDChJxDSbe75h9FQz36/7juq+JYybZmGohIwoCrS2+BFE2LpFhwB2dgQZUa4HWQOeEPXejcb4s7KtjCh3oWoq69a18dgDm7jlpqW0+nczungUPZ2Dmq0NtbpzefGVFaRnWggEYvz8Q6sR2A2t+kyYkh7XRdUdDatNwmQWufrmMZx6VimZljJKXdOZmLuATz47kTfen0t2rh0lJmC36O/e7k3gMmUyKnUehcMcOJwmAgGFceOyiNnaCCr9qJrKnp0err/2JzpCe7jpiuNITXFw+JEFnHtJOZEw5KYUMWn4bExmkW29i2gOVhGOS5YkoL+yLKAoGn+5r4rlP7cZe+aAz0tX9+D7UO/ZzPVnnc/MoqORRf19KTRNQ4jZMJtFavZ4+Om7FuM+bFqnO5DplgIQdJhp5dhUQ4P2P7KnHt7G4kUtXHFtJfMX5sfvr8Cw4kH4ZEGhHVkW+PozvTIx99BB9uZRY1J47V2d2Td7iKNqzBNJoL0zTGj5Fra+t56N6wYd3aEyNaD3444Y6eaVt+diMokGKY9kkVkaKWBPp4DTZcIzEGFfzWAF0W43MXHKIHyuYnSK0QMfi6ls3dyL3xfjp+9a2LNzgPMuLosfJyXpi6bHHdyi4Q5OPG04AX+MzesG+/na2/xcctYKvv5MD64EAeYvzE+qyunXNfgeD+39Kylz0RlHhbS1DKJDEqyxmhghpkboCO4lw6onGPbV6NcRDqls3tBLT1eI3kgzjd4qps1Mhgx6Bg4MaLs7Q0bf4ClnlBjSI+GQiskksHxJG+kZFiNgnTAp3TjWWpAGpsGXLb/Qzsv/mKPLy6gae3YNGJXN9tbB60lJNbFpfTf1+3xGMi4RMJvMOhT44MNzSUm1GPcxGlUP6LfVK7FxwhtvcuVJU6Gk1Elrsx93iilJKmbR183IsmAEscUlzqT9R1N1wrk1VT5OuqaGPc4iLAumYT12NpgktKw0uqMmzruknIXHJfMPjKxIRYmjd669dBVXnr8KNOjriyRFgoIEmiCy6G86wiM314rNJiGbBFqaAoyP32dzS+vvYnnVmEZ7gxcxOx1MMtajZxHqT4YGBwO/DzVOJLBamgOs+60LQdCDssWLWnn5uZ3ce8tG/vrkDvp6B+/pM6/MYk+cLHF/mHsCHVU4zMGyJW3J41RVyit0pMgZ5+ryO5dfM4qeOHzW4ZT57deO+Hf1cR12RL5xvHHpWjLsuy++3zucMh6PHoCNm5COIEBba5D8QjvFpS6+/6qJG69cQ2tLAEHUyQdD8V7Zo44rwmQWqav1gqDD+9//e62OYgho9JGchLE7JPp6I8w8KJtxE9N56lGdIO/3WjbaWoI8fNcWQF/jNFVvq5FNAt1dIabMyGTKdF01ob8/giBA8Qgnkixw6FUzkV1Wnr4ygydfnMHUmfoanSCXA50Vu7M9FG/B0VF3H7+xCzQwxRO77W0BJk5J55a740RbMRU0DbPLgv2M+VhPOhj7aYchnnokUn4mYoYbqbKY7t4obT6RV/6294Dr+newA3Ff/5vW2dnJBx98wDvvvENVlQ750/Z7Cd1uN6eeeirnn38+Bx10IHX9H/aH/WG6vfPGXiJhlcuuGUVLo58H79pEX02Y8XIaBYqdQCCGrzCGa66Z/mAEBybCIYW7b1nP5vU6i+Cq5R3ccMUaw0EC3enKyLLy7rs1KIpOk3/epeWcff4IJFlk47ouHrlniw6LiVsgEOOLj+t5/W+7yMq24ooz7Sbeb0EQuPGOcVxbu5q/Pl3NiHIX7a0BRlam8NG7NSxbrAdTl1xVwWlnl/Jf2UB/hE/e0xl8X3lhl/F3d4qJi89YQU93mJPPKObSq0YlOSF7dg3w5wtWAfDeWzW0tQSx2kSsFplwWCeKcrpkI0Pe0R7k0/frOPmMYmw2iSWLmo0+zulzsvF5otTVepP615atbWOYaCeGhoRAgWClUQvyzw/qyJVspKWa6euPkJNn57nHqxkzLpVZc3Po6w2zZlWnIbPQEXfuLBYRu0Nm/MR0lv/SzoKjCigudfLxu/vo7QnrMLv/oP/JbBV54qGtaEDJCCeSJLB+9ybaB1qYlHvYIJHFfnvtNRev5vhThvHZR/WkpJpZMKWYxSs3o2kae3YPEAkrpJhzsMmu+PMFVQNR0EhNM6OqGnc+PJY5p77Nt4vXs3x9FaNSDmbb+jBjx6eyfWs/kAz7zcy1oaoane0ho+ptkk1ImoYzRaO3E7qCdXR15dDg28Rf3k/0PGoIiIj9wwhoyc64O8XEvhovdrtMwz4fm9b3kJ1rpbNdl2URBP3+9vVEMFtEI+EhSQKTpmTw8Tv76OoKMX1WDuoqgfMvHYnTZcLpMvHSm3N48elqFn3TrEskiG109/eRZ6ukpcnPtJlZrFvdRfX2fqRADjm2HFqC23BIWdR4fiPDncnVFx6rP+u2IE88WEV6poXe7jDhUASTSeTso4/nne8/p2x4AaFOve/UZBK44rrRjJ+Uxht/281Dd21m7IRUxs8W+OCLFeTbxyAgoGhRZow8iFVL+nVyJ5uFUEgh1WXHbJUQBYH+vkGoot7PrBlVR1EUqBybxsNPTWXJDy2s/rXLIOsSBHC6TMRiKsGAwr4aL088uJWnHtmGqmiUjHBSV+vD6xl8L/bV+LjxzrHMX1iA2SwRjapcdeFKIhGVp16aiSQJOJwyf31yhz53LeIg42hBNuqOfaiKRkGRnVvvmcBbr+yialPfAX58W2uQ407OYvfOAbxDYMRFRTbSciQe+B4KKtLZua4jiZm3uNTJ+jWD/a67dwwginq/7/o13Qz0Rzny2AKysm1MnJLB+EnpuFPMrFjabpAFgS4ZAnp1tqszxO3XrTP6d8NhlZ7uSFK/4p0PTKRqcy/RiEbhMAf9fWECASWJHTdRTbNYRIKBGIp5ELI/EJ+zavyUombBF+sk3VKEySQYz1MQdJKg6vi7Z7U7KSosY9u2AR31omlJ7yPo5FI+b4zsXCvdnSHOubAch8OEpmlYrRKhkMJhRxTw43fNdHaGyC7PoHNvD9sjKYgZQb2iOH8mNkUlsmEX2t5GfN4oTQ1+ioY7+eeHdUbSQJYFneAmHrAM9EfZsjGZ7fbQBfks+rqZaETF7pCNc40od9FY79NbG36nmptI8g1l0k1YYi2655aNDBvuMNaewmEOioY7WB3XIH7o6Sls2djL049s0yVpoiqRzAwGZk4BRcHk86P6gsiBCGGrhS6/iO2Eubzb6ieyfnvSb373VaMhqbZv7yCiRhTB4TLhDagQ0Ym/JJOIEtYfYntbENkkEIvqc2X9an2+Dq0Mg95LrKiazhFRkInmDUI0RujrlUZyQXDa0BQVwhFQf+emxceTmF8ms4DDISNJotGnOVQb2GwRuefm9YRDKi63iZxcGyNHpfD91zpcvqcrbDA3AxQW2Y33wmYzocYf3K4dOqHcyacXc/SJRZz/p+VkZFlYs7LLuHaAI48r4MN39iVdc3auLYmI0WoTCQVVLj37V1qbA9z10ERq9niMpOsh8/O47dp1bNnYw8w52ZSMcBl+TWIerf61g/ET09m0vpsbbx9LaZmLxx/cSqtiwzxvEkpbN5Glm/X7JQl8/sN8vvuqiVf/uouiYQ5mz81h1fJBQr2hZo+3bWkaSUkxJc6OvmZlJ2tW6n8zxYkBLRaJaXNy2RZOY+FoKM2VWLmsHY9HfyZD1zRV1QgGFD5+p5beHj3BLk8oI1ZVQ3q6mY72EKuWdRj+V8IEh5VIIELsp3XIxXmIsSjhPh9qUGd2l0fko+ysxzx9NAPu/42m6P+LTND2jz7/FywcDvPll1/yzjvvsHjxYhQlIXcwpMFYFJk/fz7nn38+J510kiHV84f9v2Mej4eUlBQGBgZwu93/9QF/2H9qLU1+Ljpjhd5josCmz7sZLjnJEC1IKQLuyWZC2Qp7azxs3dxLMKBQOTaVtHQTq1d2YTKJvPjGbBrrfbz5ym7aW4PGAv7oM1OZPjsbryfKlRespL0tSG6ejTsfmMjocXqVNxJWeOyBKlb88jukL0BKislgkR01JpUjjy3kqGMLWf5LG4/eW0XhMDvNjQEEASObe9Txhdx4xzgEQSASUWhpCujsshkHQnruv20jWzb24ItvjiaTQDSq6SQkEZWjji/kpjvHH3Bca7Ofe2/bQH28enfI4TnU1vhoahh0CMxmkUhERZYF3Ckm+nojSJJARpaVro4gqgqnnV3MZdeM5qG7NhmVzVPPLmbx961JVeAKyc1Ii5vvAs2YRJGwqnLsSUWs+KWdE08djtUm8+bfdjOyMoXpszJ5+/Ua0tIt9PWGqRybys7t/UiSwItvzaa8IoWvP2vg1Rd26oRKssDhR+YblZ6hduFl5XR3hfnmC/2z7FwrJ59WzIJjCjn/hmcIBMLceM5FPPXwNiRJr2r19kS47d5xPP7gNiNwSUs3c9AhuSz6bTlrdqxjYcU5bKvfRp5jFAVlUaZPKmPZz2309UYQRR2a2N8b4aGnpjBpaga20jNw545g9KyF2CKFaL1eMl0CwYEAnga996qgyM4TL0wnJ0+vhAz0h3nnjb0s+qaZur4qGn3byLGVU+qaRpNvK4WOMYhpHbS1+dA0jZNOHM1xx1bS0yawfk0n61Z3MfeQHDwDMTZv6CYa1XC5TXg9Orww4I8lOb0Wq0hamoXUNDO7dw1QUOjA4ZTo7gozaUoGZ55fxvASJz5fNIl0TdWguQ9WLWnmzWe24k4xUVRsp6M1RCikJPVkpqVbUFSFau831Ld0YDe5GZOygJJh2Rx3ynB++q6ZQCDGIYfn8cn7enXVZBb44MvDuPsvn/Lh5yuZnHX8EPZnvSKXnm4mENDlVoQDQFQaIJCeaeGCS8s5/MgCXn5+ByuXdTB1RiZtLQGqt/UzcpSb9rYgnoEoFouIIAqEggo2O9xy9yRamwP88lMr+2q8ZOVYmT03h6/iEh93PDCBRV81sWWTrrebnmGhqzOIompYLNIB1Z97HplEd1cIi0Vi25Zeli1p4/nXZzFqdCoAy5a0sWVjN9991aRXwNw2Ir4QuaWptNf0IUl6ZTo1zYzDKRvJpdnzsvEMRNhe1Z/0eza7RE6eDafDxJ5d/eQMc2NZOBNfQKX/w6WEggdWI0tGOHn8hek01PnoaA/y/BPbUWJ6D2EkolJa5uLya0YxJd7/uWl9N089sjWJ1EkUobjURXOTn1hUNdaxaESlvS2IBogmibA/ijXdTrgvwJ9vGE1Oro1339xLKKTg9UR55OmpXHPJb6iqDuf8xycHY7ZIBIMxjjtU1xrNybPR0RYko7SXrtpUsnMsXH7NaJQYjBjp4tKzVxrjMpkEoqIJqSCT8L4GJGRMlcVY7TK+jbW4U0x4PFGsVj0QsNpEJk7JoLqqn+GlTp7463TMZj0g+vjdWhZ900xLkx9TugNxxnhUf5DI8i2Y508lsmQD1vw0Xn1rBjc93UqgoJAR0gCO3XtZs7KTmXOyWLNKhzk60mykHTuNoGxFFUQCHR5iuxtRapsR96v2ORwyfn+MU84sZsuGHtIzrDhdMh1twaRgJWEpqSZKy9zs3tlPwK9gMiVLZO1vsiygAQ8+MZlnHt1OT3eYOfNyuP62sVx05gpmzMmmsyPA9toI1hPnMcbh446T7bjjVeAtG3u4+aq1AFz12ByWtdqp98hMlzpY+uYmYw4nTJL0dfOJF2bw/jv7+On7FgQRTOKBEjKGCXplua01+LtkTpIkoKqDwb1gNaGFBi/ane3A2xfSPxcEiMbA7cBhE/B3JLesmEwiZrOY1MvrTjElJXGT7neaiYG+KC+8MQtRFLj6ot8O+E7i+LET0the1ccZ55XyUTw41YkF03nm5ZkAXHvpb4bec06ulY72ELn5Nt77/FCOnveD8bxzcq0EAgrHnjSMD9+uZdrMTARBYN3qQame8RPT6O4OJzF6y7LAVTeO5riTh7NrR78x3kQwbNxyQW/J2Lt7gEhEv7eCzYIWGHzvJaeVd784jGwX1OzxcNdN67GYRVqHICkA0jPNukatQhLPxv4mCPp1tbeFktZ+S3k+rjljuGWGj1ee2k5drRdJ3o/lPW7ZOVb6eiOGpJyYn4na2v0ffj+rwEFXix/TlJGMNvVSNSTJd4DZzEydmc1jfznQ1/o/Yf87ccb/VkC7YsUK3nnnHT777DM8Hj1juf/hlZWVnH/++Zxzzjnk5+f/3mn+sP9H7H9aQNtQ5+W9t2rYXtVHOKz354ysTGXuoblMmZ55gHzA/6qpqsbKZe2898ZeIi0qeaqdAtGGKAikVViYeV4OxbNchgSEEmfv/O6LxiSn4MrrK7FYRF5+fmdS1johZXPqWSWkpVt44clqrrt1DEsWtbJzRz8XXFrO6eeOQJIEtm3p5YYr1hywQcuywPASJ7V7vYgijBqdys7qfpxOEz5f9Hcz6OkZekBVNtLF5OlZ/PxjiwE3mjIjk2tuGm2wCdfs8XDFeSu5/rYxPPd4NbJJJ3JIfD87x8o7nx2CLOuQypXL2mlvDbCv1qvDhrQD0VnZObo2ZkqqGa9HD2BFUSAcVg1459Bjyirc9PWEjd6ditEpvPTWHOr3eXnq4a3s2qGTm5xzURnnXVLGyUcuMQIcd4qJgiIHGZkW7n9sCju39/PIPZt1wg2rSHGJi80beoxq3VHHF3DoggLGTkjDbJb45adWHr13izEWu0MiJcVskK2A7sQlqmPX3DKGrZt7Wbm0A4UYv7V+wJ/PPZ6T5x/K3Tdv5MhjCljyQytjxqfy5IszOe6wHzn7gjK8ngjLf2nDbJJoDexixY5fMIs2bJKb8RlHcfk1o/jg7VrCIQXZJBzQB1hWmcIaYYCiqQtRA0G9iuochGepAz7CSzeh9fvIzrEyY042Rx1XyMjKVECvwl9zy0d8vPhbXKZMJmbo1UxNUzGZJFRV444HJhpkIfub3x/luktX09ocMJweWRaIxTSKhjt49pWZDAxEuevG9bS3BpFlgVPPLuWCy0b+p+9nZ7/Cc5952B2wEzXpyZbodytR+3woMZVjTxrGVTeO5pIzV9AyxHFKSzdz8dWlLFlSh7fLTFODn0hENZI+1982lswsKy8+Xc3SxW1UVLrJybOzclk7qhBBi8kohLHaRayyIz6fhjitAgyFc191QyWzD84lJ/fAPstQSOGck5YydWYWt983gb27BrjyglWGg6lpGu50AW+fDtcbUe7muJOHcfDhufz0fQtPPazD6P656HBS0yxUberh8Qer6O4KY7NJByQNfs9kWeCam8dwzIkH9t1ecPYqmht8OMty8cW1p90pJuYdlssP3zYbVRpBgBlzslmzspND5uexbEkbki5Py/GnDOOrfzby4BNTKB7hYveOft7/ew0t3TEy/jQXs6hwfFY3bz5XfQDCobjUycLjCvnHa3uYNCWTOx+aiNUqUbWpl3fe2MvWzb0UlzopKHIwclQKRx5byFkn/DIIjbVKhMOKDnzQdAc2N9fOju39yCYBNS2VlMMm0PfRMgDEFAcPPDEFczjEqy/sZF+Nl/sfm8zseTlccd5KurtCvPvZIUY/HsA/XtuDqmicenYJz72ymIf/9jbXnHU+VUt19nCX24TFKtLeOqT1IeEVW0x0+/bR629iVNlRmMcUE1quo+ZS00z090XjRF+Da/uxJxVx+bWV2GwyP33fzFMPb8XlNhMQzNiOm43LKsBvW2jZPliNuvL6Sk45o4QNa7v4dkOEKjmfWcUq6ftq+OhtvU/emWFHOXwms0ZbKc4AiwzvftWFmpuF0tpNQUsN9Tt7jXt7/CnD6OoIseDoAh68czNPvjidDWu7+fjdwWpdwiRJYNQYN9VbBzj4iHy0SZXUDJjobRwgWl2H0tBuBC4Op86UP3SfFCWBYcMd3P/YZN5+fS+b1vdw6z3jueumDdiPmkHeiDT+dpaIFM8laZrGjq19PHjXZnzeKO99fijuNAtv/AbfVqmE3vvBQDjkF9qNhMz1t4/l2BOH8dFG+HRNlOdOE1jyeS0fvF2LLItMmpqOqsCGtd1JVcqhZrPrCaSRlW7qarz6+yeJxMJD5rYYh9JIItLIIkxqTE/25RZy2Cw3a/ZBrjlM+ycrDR1e0NeAyjGpbN3cSzSeoLFYRC69ahS9vWE+fLsmCXo8Y3YWM+ZkUb21n59/TGYkTlhxqROfN0J3V4STTy/mq3/Wo+poV865qIwLLtMZqT95fx+v/XUXI0e52VfjJRbTmDknm4efnsqpRy8hElEZNSaV6q29PP/abIaX6OilI48txGQSOWXhEmBw7R86N866cATLf26jsc7PUccVcv5lI3nyoa1xP0hg1fJBngCrVTQQTWJ2GlJeBqPlPkpKnWzZ1EN9rY/0uZW4JpTw2AmQ5dI1qW+9Zt0BbNeSDKeeVcoZ547A643y7F+2sWl9j44YiieTLvnzSL76rBFV0Q6QEgKQSvPRVA2ppYOzLhjBnINzuOwcPXk1vMTBg09MpbcnzLOPbdMr+JIIioogiZhN+n12ukw4nTJXXFtJT0+Ypx/Zht2hJ31tJ89D9QaJ/LwBTdUoq3BTs9tjtAckqvSJ5ML/DfYvCWhLS0tpaNAzuAlWyMSh6enpnHnmmZx//vlMnTr1PzvNH/b/kP1PCmh37ejn5qvWkp5hYd5hudjtMh3tQbZs7KGlKUDRcAcXXVGR1EP2v2K+7igv3lqNd2+EHNGGSRDxqFFsoyQueLACd+5gA380qlK9tY+ff2hh0TfNXHTFSLZu7mHD2gPZQEHPEmflWHn+tdl8/lE9X3xaTySsctAhOdz3l8moisbbb+zlw7drmTglgxtuH8sd16/HEe9FCwUVzrpgBC2NAb77qpFYTEuCFI0Zn0ZjvRevJ0ZKqgl3itmoiopigpUzORM/vMRJyQgXVZt7GOiLMHlaJvMXFvD5x3XU1njJzLTQ3xchHFapHJMKaOyr8RqET+Gwws7t/ciygM0u4/VEycqxMWZ2PkcekYtNVLj+8jXG740Zl0Z7WwCfN0okomvMPvrMVH5d1kH9Pi87q/uTMuY2m2iQelSOSeHUs0sNdt1wWCdq+usbs3W49ZVr2Lq5N84gLCLJAnaHzMffHIYgCPi8UZ5+dBu/Lm1n9jzdQVdVkrKyTqfMGeeP4J8f7CPgT+5VHRrU5ORa6e4OG06PySyy8NhCTjptOK+9tYon33mLyRknMLK0gJamAAuOKuDnn1r5x8fzyC90cPm5vzJqTCo33D7OuNZvFm/gT5c+gdPi5tt37+Sea3WY94TJ6bS1BuhsD+Fy65vj/KMKWLG2n7b8EhBFlPp2nF2tWE0yHb1RBIsZwWGj9NjxtMZsRFdvI7p7UKsyv9DOXQ9NpKIylR+WbuaEC/9CcW4RRRwOQFm5G0kWOOvCMubMy/lP35lvv2jgucerkSQMMo3KsSk8/9osvN4YD9+1me1b+1h4bCHff9VIabmbmXOycbvNTJ6eyfCSZM6GX3ZrvPCziqJopPt6URvb6WgLYDELBBt7EGURNabiHpWHX5URG1qIxueM0ynj88UMojGrVWJFXKoGASZOzmD67Cx27+jn16XtWG0yYrxKM312FmNnSlTt2cHfP/6FWEzBjJsMuZzSvBJkwUr5yBROP7eEhjo/FaNTflePOmFfflrP357bydufHkxenN31mktW0d4apL8/QkwN40yBhx6dl9RXClC1qYeb/rwWq1Xi22VHGn/3+aL88E0zSkzFMxDl4/cGAwwh1YkzP4UMU4yWHZ1EoxoOh8xVN45mwdEFBmGLosKKGnjplxiB1n6OSOni20/rEAR46+N53HvLRvr7wuQXONi9c4BjTyrikPn5tLX4eeHJHRQNd3D1TZWs/rWLTz+ow2aXmD4ry0BRuFNMDCt2sn1vgJST5pKVJtHz4TL6esJJFYuh71R5hZuRlSnMX6gnlVqa/Fx98W/4vDGDEVxRtKS1a0S5m0Aght8X5cY7x7FmZSdLFrUQM5mxlucjTx7F6DyofnEJfm8U+4IpaNkZhJdvpsSuVwQnTc2gZo+Hl57ZwZMvTmfS1MzffZb/+GQ1V97xV3Ir5zDmqCvRtuwmsr0Oi1VKqt7NOSQHZdIYdveZ+NtZApdd9ySLV2xDFqyk24ZTMepIhKI8orsbEPu9DC9xsK/GZ0D0RRFS0yzY7TLNTX6jUjr6ysMIylae/RPs2NjJnTduAPRg8Iuf5hsQ5WhU5YGX29hqLiC2u5HommrGHVNBTepwzpwpc9a0wWvasa2P5dsifN+ZSopNYExfLT9/qSMXPv3ucNIyLNx6zVq8nih/+8ccvvuqiece244k6cnUfTWDRH2SJHD1HeNZFSugtltD2d1I2GpHKshCbGojuGIrNquIzxtl7qE5qKreiuOMk0UletZjMY0pMzJobw3RFjZjPXoWdxwJs0r03/H7ozz32HaWLm4z5oTl0MnYh2UwcbiMzazx49vbUerayM+x0BoPcgS3g9PvnYsgivy8G+aOgPMmRznt2J+JhFXGjE+jr1dfzzvag5RVuDn48Dyqq/pYs6oTUYTTzinlh2+ayS+08/xrs/D7Y6zZHeOxa5ZhmjoKV2Ea2vYaPD0hpNw0IruawGzCumAaUoqDfFuUloiVIyphQwMM/LqdYE0bsXAMh13C74tRMsLF4Ufm8/F7tXg9MU4+o5iTTy/m5x9a+fTDOoLZOcjDc9E0DaWxA6W2hWHD7YTDSpIE1zkXjuD7r5vp7QljsYiEwzpEuXJMqlFNfeKv05k8LZOoAjWdGqISoyAFrrxgJW0tQabPzuLRZ6ZxxXkrqdmjF8xuuH3sAcmxcEjhlKOWEAoqlJa56OkOMdAfNRBddz88kaIx2fy6vIMv3qxOkhoaugYMNVNOCvLC2dw8O8TBE/Rk4a4d/eyq7ueghcO5/WsBiwx/OQHcVli5vJ37b9tkHD9xSjo33jme/IJBgrFnH9vGd182YbGKmE0SXm+Uy64ZRUqKmScf3gpmGVNeOtEGPcCWKopQdjeBKCBnuon1ePXFc8icHzshjfxCO8t+bjfYsI3PZYF7Hpmk+x2PbOOpl2bw8Xu1rPttsBorDs/BcvAklJoW2FBtJF9lWVeEUGIaWM1MHu/iiRdmHHij/g/YvySgFUUxKYg1mUwcddRRnH/++Rx77LGYTL9PIf+H/b9r/1MC2lhM5ZKzfsXhlHnqpRnYbIOt55qmsat6gHfe3Mv61V3MnpfDHfdPwGb//fZ0TdPoqQ3TsNpLw2ovHTuCaJrGgBilQwvSEvVz5jVlLDyukK6OEI0NPvbVeNle1cv2qj6D8VGWdTbdH7/T5VycbhnfEDmNRJ/U+EnpPPb8NMxmCZ83SnOTn/KR7iSh+i0be/jL/VvwDERRYirZuTaUmMajz05j6eJWdm7vp3CYnZo9XnZu7z8gSM3Js/LOPw/hnTd0YoUE5Di/0KFDmywie3cNMLzUhaqoNNT7D+jvBL2ietiR+ezb66V6ax9+f4yMLAvp6RYkSWDPrgFUVScRSvSYmiwS0vQxCKUFSKLAsKY97F1eSzSqIUkCeQU2mht1J0OSwWqRKRjm4KEnp3DbtesMRtbERjd1RiZ/vn4Ut1673shWJj43mUVGjU6hpytMVo4NTdWo2tzLrfeO5+3X99DZrsO9br1nPIcdmY8oCrzx0i4DbjrU0jMsRKNqUj9iwjKyLPR0hTnx1OFUjk1lwuR0MrNsvPh0NYsXtfCX56axeX0Pn3zSgFxWhCU7yKZVX/L2PVfw2Uf1Rr/QsGIH9z46meJSF4/epxNkPfPyTNxxJuk1v7Vx9qWv89h9f0IsH82nGxQiUY3Q1lrUmmZiPv36z7ltKtuaNHZU9RLdURevhmtIsogsC6SlW+jtDuFym3WHZlwJ0qQKcoK9RNdV09LoN5yIMcdUEiouoq0/jN1mweTxURjt5dFbSw8gftnfImGFf7y+h0/frzvAKRlZmcIhh+fy8Xt1qKrGg09MATAy2ZIkIEoC0YjKpKkZXHj5SEaPS2N3B9z6hUa0tpXbT7Qwb04mvX6Nl7/z89uiesI7GzHNGouMSnDNTgSXHdluJtreR3aOFdkk4nTK7Nnl4ajji7j2ljEIAjz2QBXLFrdRNNxBS3OAvHwbJ59eTGm5mxsuX8Mtd4/nyGMHSWUaW7q5+q7XyUp38cjt55Cbnfqf34z9LOCPcfGZKxg7MY27Hpxk/P3pR7ay6JtmzrmojA0Ny3n9/cXMnFzBl2/dQVrqoPPl9UQ570/LOObEIkJBhf6+CJVj9bYCp9NEMBDj0nN+pbM9SMWYNIqOGsfKzsHEwIgMjaZVNfSvrQFNIy3bzn2PTMDnTOO9ddDYB7NLNTb8dRmpLommRj+yDCUj3LS3Bnnu1Vk0N/l55J7NBqRZEPXAs6XRj9Uuc/1tY7nv1o1GouzaW8cyoszNom+a+P6rJkaOctPSpxHOyCC2o94YWyLxUVBop6U5gCwLjJ+cQUdrgJbmACNHpdDfF8Zskbj/scl89c8Gvvm8EVEa7GEFOOm0Yr7+rIGnXprBuInp9PZGePaHKFUeOwJweIXA/AqNTVv76eoMs3ZJI97CYYiF2UR+rUKpGyTNSUkzU1GZgihC4TAnC48tpDhOyrR87R6OPONessumMmfkEfT5RFR/ELV5EGaJIGCZORp55DBUYHyBwHkz4fHH/sb7ny/DYrISiUZIteQz8YzbMKenEVy0Bq3fx/ASBzfdOZ7W5gDPPb6dUEgxdMNLR7jIq8jkR7WEP8+KsWCsxG03b2bLaj15IIrw4BNT+PmnVlYu60AUBMIRBXn6aMyVxaiBEKJdby+bUgTnzIBQax+/reigpdlPc6Of1gEwzZ9OaqoJedUmGrZ3UTk2FRw2asQMho1K57Apdrxb6vjiqzbEkjwWLMilY80+tq/RK4Nhiw157iREh5XwkvUonf1UjE5hxrmT+KrGRooSpPGDlYgxHVWQmWXl+FOG8eN3LTQ3+ika7qCzPUhKqpmBfj2Bal8wlcIxWbx4uoAowN5dAzx892b6eiNcd+sY7Hkp3HP5CtwLJhNs7kbp9aJ2D2CaOgqpIAvbqvWkOiXknFSaSyqxyCCbJQJRgYNLVbb/fSVNdT5uv38C8xcWGI/yivNWUlbh5ua7xtPU4OOiM1agaTB6fBr1NV7e+HAu2Tk2WvvhsgcaCK3ZweVPH0aPYmFnO0wuArmmjr+/uNPYx6Q0J2JlMXJJPoJJxilG8XgVRIf+bFRvgHQpghSJ0N4wgNLSTZYcMjgebDYJ1+ET8WXm4JKiZDoF6gYkRJ8f/y9bKMtOlm866/wRXHD5SKo29fD0o9sMIrBrbx3DprXdbFjXzZeLF9DYL/LID9AVR0BX5mqMCrXw/nM6eaQl1YYajBANK5hMAkceW8gxJw6jvCKFxl7Y2AQr3tvKrrUt3PnAJCrHpHLtZb8l6z2j94uapo+mdEI2o4ItfP/3avLy7Ywamwpo2KwSX3+ut+6osgnbnw4hVtdGen0NSkzD748xotwVZ0iOEtQktikZOImiVO8zZOMS9tc3Z1FUlsbqfbCzHVoHIFzXzo7Pt6DEYcHjp2ezdZ0evApZqZgDfooKrYhpbhps2UQ370XtT4aGDzXXjJFIpfl4lm1DbYsXMRxW8A+5dpuZiVOyqN3WSdAfi7fjKESjKlJ5IZY54ylI0WjuipG2o5rWLcmVdnl4DrG2HpwFaXz54TT+b7B/WUALMGnSJM4//3zOOussMjN/P7v4h/3PsP8pAe2SRS089kAVr757kKHvCDpz645t/aSnm/n7a3sM7TarTeLuhyYx8yCdxj4WVmnZ5Kc+HsT6u2KY7CKWIpHl1e20xYJERT2QPPWsEr7/qilJNub3soo5uVb6+yOEQypWq4QoCvz5hkp83hhtrX4Wfd1MXr6N1pYgYyekcccDE3+3bzVhjfU+Ljn7V1RFIyvbyuPPT+P5J6t1SvvpmWyv6iUcUph/VAGLv282+pVMZoFoRId7Njfq1dn0TAsvvK738i5b0kZbZ4QdOz3EvKH4MaIhIr6/VY5N5Y4HJmAxS1x3+eokhsz0TDMlpS42ruuhYnQKs48dwbufthGra2PkmDTGHj2Kz59bD9EYRx5fxIIj87jjhg3Gb82el0PlmFQ+frfW6NMFGD01mwknjeHr1SFiUQWlvo3YnmbdEY7DmWw2CUHU2WFLSl00NfrYsKYLi1XmtLNLOHxhAS88ud0g9JCkwV7d33t+TpeMqoKiqIRDKpKMrp+pwYdfH8q7b9bw6ft1HHlsIUcfX0TBMDvnnbycE08dzkVXVuALw03/VGkbAC0aQzCbOH2qwOmTNRbOWQRg9JgWFNnp6gwRCevZ2GmzspgwOYOP362laLiTGRdN46MtMsPVPvYuqyXW2Al2KyT6iJw2HdIWCDF1djbHnZzL9qp+Pv+wKYn04obbx/L263vx+6JYR+QSmTwOk8fDWF89v/3ShpjiwHzYFDSPn7JMjew8B41hK21BE5man2nmbg6a4mLM+DS2benlg3/U0t4WoKTURXaejaWLW+nr0XuZi0sceDxRolENb1xqIxbTGFHuYv7CfH5c46OxIUBpusph8/P4+xt7KZ47ghFjM9ixtI7GLe1MmJFNQ9k4gv0Bjk/v4PKrRtEXgJs/h0AEilwx9m1uJ9jtQxo7ArW1i/CaamzZbsJhFaWzD3eKTFa2jZJSF8uWtDFuYjr3PjoZh1PmlRd28vlH9QZEXRRF7rppPS1NAd78YG5SUul/1zRNY6A/gqbpFYvXXtzFutVdvP7+XHLzbPT3RthX6+G+WzeBABarRFaWmU27drK1cyljJ57JiHFTKR9m4cJj3IzIN7NxbRf33rYRp8tEQaGD6q29mM0Sufk2PJ4ofWEZqbyQghkl9IREZqZ6WPzSOqacPp6dYjaiAAcVRVnzwRb6a/TgS8hNp3J+OWccYsNtl3jknwG8khVXfw9dK3dDMMyIkW4kEfbs8jBpWgaRsEL11uTEWaLqkzBJEhg3MZ37H5tMJKLy1iu7WbKoBVUDVdEQ7Ba0gJ6Q+dvfZ1Nf5+OFJ6sJBRVy82x0tAc5/9JySka4eOKhrfh9McZPSuOK60aTl2+nqcGHwynT3RXi8Qer6O2O67bKAukZFl32I7cA0+SRRDfsJlbbjJzhRhpXhpirs9QKgkCsoQMhFkMqzefgtD5+fGHtf9hfN3laBmddVc5hp9+DZHNz4cJz2fRDPbl5NjzeKHJhNqHMTNQBP6ZUBxTnE91ag2CSkSuLQVForV7O9h9f44nH78DqD3DLY3/j2AUzyTrkajpb/agrNtHTojvNRcUOyivc7KoeSO4/rByOaWol2o5aTCMKUOx2wj+sQWnvpWxUCrW7B7BYJGYelK0z2wq6fnLu9GLU8RXkSkG0XfU09gn40zPQer2YPR6sQpRUu0AsEKaxLYrlyBmIZpnQ8i2IGW5MkyoGtchkndBKEEW0mKJH0qKA4A8S6x5AKspG8wUJ/7IRbcBP+qgcghPGItgsmEUVDQHFF8T/4wa0gcEgYcbsTA6en8/PP7Ti80a58IqRPHLPFnyYsZ18MPZde7hogZ1gSOHV53dSNNzBn84qYW+HxpJgHr6PljJnbharl7WhqvEKvlmGmIJgtVA6PR9lbAVRT5C2j35F1cA+sQxtVAlqRy+FTXt54JEJhj6upmk8fM9mtlf1MWdeDqt/7cTnjZCRaaO5yc+Jpw7n6pvGEFPgli+g+u3fyEg38eHbg8FG9dY+brt2HUcdX8Txpwzj9Zd2UbVJZ+8WzCbkSeUINgt2USF7fAGtAwK5ygBNbRHMbisxkxnBakEa8KBt3oWvvhvHwmlouVm4rRBTIKrCcWNhS7NGQy+wcQfebY1kVuZQNrOIjeu6GV7sJHt8AdtbVAIb9hLbUY9gljGNLELOcCOoCtrwfEQ0UiwalcNMbN0XxqvIRLfvI7azAUL6eybmZ5KS6yTW2o23O0TeEWPw5uSj1rYQWLEVefJInAEP3ppOlJjKYUfkc8yJhdz+th8xKwVlxWZiniDmYdmIM8Yg1jYi1+pQX5NZTNqXzYdNQcxMIfTlCojofoFsEgwSp/1NcNgQQ6HBliwBEEUsh05GLMgykCkASs8A4W9Wgc2C7dTDMHV2Eez0sPCYQkZLvTz3xHaiVhtCdjrKrgZuv288peVunn1yBzur4uRpcVixc1IJQksn3k7dz5IcFt7+YDbnnLB0cHBWM9YTDkIbCBD+cS2FY7Np3tEFisq4YyqYNjePL7eL9P2wCa3fi5DqQkqxE6sdDGzl3DSOuGQiNx57YFvL/wn7lwS0t9xyC+effz5jx479bxnkH/bvb/8TAlpN07j83JVkZll59NnBTWTV8nYevnuL0ZQvSQJXXldJMKTwj9f2YIqJzBuTQ6ZiJdykgAKWDIn6gI+aAQ9dasgoUtodep9M4k38zwI+0Kt7vT2D1cPhJQ4qx6bxy4+tB0BWE/C5aFQjv9DOnHk5nHZOKWn76aw9/8R2li5u5ZGnpzK81MUP3zTz6gs7ufXeCXzwj5okgiWLRURDIxLWcLpkzrmojDf+ttuAwz789BR27xjg3TdrKC510qVaCXV6UAJxYiVBYFhlBn86MReXy8zLz+2gsyOU5MBKsr6hpKaZ8QxEDpALyCty4MnOp/KgIk4d4ePl53YY1VYxxU7W1BLuuyQbb5eP265d//s3UgDzzLHIFcNAVRnhjtDc6CeUlo7W1Udk+WbMaoxYVKWiMoVHnp2K0zkIAe/qDPLxu/v47qsmrFaJU84oYdeOftas7DzgpyoqU2hr8yMg4BmIIogCdruE2SJy/MnFTJ+VyVUX/YYoCVx/21hW/NLO+iHEF4IIaLDgqAIysm1stg2nRzFzVnkdd177PQXTFmCePJJDRwqU9Tfy69I2mpv8B2SubTbJ6C0cVuzg1ItH8fKeTKI76olu3G18z+w0E/FFkuZSapqZhccVkpNr48O3a+nsGDy3URmQ4a0P51FQ5OSH1R5e2WBFUQXEvn6Cq6pRfQFMsoDFJhFwpCKmu8AkYS7JA4eN8G/bcfd309cbISfXSkmZm+qtfYOVbKuJtHw3vqY+491LMpOM5fApSLk6pFaIRkkLewjYXYREM4KmogkiFq+HgCoiuh2gqqj1bRxZGiFSVkxVi8izfwKbEOWZR7ex/Od2hDQXtoUzsGtRDrK0sajJQWTTXjRfUPf40Em4YjGVjAwLDz8zjbx8G+//vZZ/vLaHk88oZvK0TO6+aQN3PTSRyQfl8/VW2NOpQ9hmlsDsUoy+vf/Mtm3p5bEHqpKqBKIocMPtYxBFkQ/erjH6+IZa5ZhUZh+cw4cNMciqwBoNERRkEESGhbto/WkbI0a4eOipKbrO47Xr2LG9X2e1TXMZgcGI2cM587RCynNFPvqwnkVfNFJx5gzSS9LZ1goXzwa7v59n7t5A2Bc5YByDgxYwOy3MnZWG2SIjmwRWLm2nrzdiJCgS68BQczhkLrxiJP94bQ/uFDP9fWGdVTQ+HURJGGQTNsm88cV8tq3t4OWlCs7CNPzdPthRR7i1N37v4OTTi1m2pC0JlTHUBEFfR80WkVhUI2q2YD1xHlpNA1owiuawE91ao88HAcwuK445o4llZ6GEotDRA8UFRNbv5IqFVt5/u46BvggZw1Iwq1FaGrx0hxppCe3AH+1ncumZWL3gTjPr7Mh2G+pAAPMhk5CH6ZB8TVERunoILt6AJSsFpo9FSHEQbtiDJKZiDfgIdW3kl9Wfc9jEBUQ7ChBMMiaHBa2iGMFuRe0eQGxt56ApbtxuE6EorHeXExBMCKpKrL4dt6+P2QuH8cvSbkKNXcRaewYFH2XZCAL+S5PjMj8xBcFuIbUyH2lMKQHRYlwPogAaBl+E/oGGqCmogTDYbSCKZDtUTszswKTE8LrTeWeHg1RPN/69bQRMNuRRwxBMJr2S7fPg3dGC1tqJ4gkgoiHazGiZ6QguO4LNjFxWiGAxg6ahtPUQ3VqL2h6vgllkzNNG68H3LzrM1GrT2bo1DfLL0ugwuTEVZkN2OggQ+molmie+ZwogZqVhXTANNRgmtqcJR46TmDdEtHOAaLcHzRckJ89Gty0N84h8VFGCrj6iuxq49e6xbFFzWL7RS/CLX7nitgn86aQCFEXjw7dreOfNGkaNTuGx56YnydssXdzKUw9v1RNBkoj1lEM4c7aJvrDEj9sUrEtX09fioeSgYvoqRhOJoxHUAR9iihOxtx81PZUUG7iifmpX1WPyB9BKCpBK8tFiCoIsYZY0BE0jHAOtz0uszwvBMEKqk9iOer2amOLAMns8QoZb/8xpQ+3sI7x4PZajZiFluIls2IW9rYVwSCUcVnS47dBXP77JHJAgliVKj6jkhBPyeeU3icK+ZlpW7CHQH9bnkyxhnj4aKTuV8IbdqE0dxnnlyuGYZ4yBVVsI1baitygn9+UKei6F+UcXEJRtrPiyluxR2dx200gefrMDraSQkD+C4HIQ29dKdoYJNTeLgag+32P7WrHmpjJ8mJ36Xg1FFSASRY3GIBIltGgtRAaRWuWj3Bx/8nBW9rlZ/+l21O6B5PdIAKdDZs7BOdxyzwTO/dNyehQL0vgRBJduRrBbsVYOI2YyE12lV75RVGx/OgRVFpGsVjRVJdTbicXsIrJpN2p9O4gipnQHqsnEicfmceXFw/+XXut/tf3LSKH+sD9sqP1PCGi3V/Vy/eVrePyF6UyZriMSujtDXHTGCiZPz+Co44u468YNOJ0yTkXm2JnDUNs0BuojqJpGk+qnRw7TFgwQQve40tLNuFPMtDTrUMhwSD1gkZ4yPZNTzy5h6eI2fvy2mYeenEJqmgWfL8rUGZk8fPdmo4fMFtdMTEk109UZ4pgTi6je1kdLow517OoKoaoaFZWp1O71YDKJ3HbfBKbFNc4a6rxces5KLr6ygtPPKSUSUTj7xKUMK3Gxd9cAWdlWrr5pNJvWdRuU+g6HzNRZmSxfciAjcgKqd8Z5pTT0Caz+sREiUUpGOBFFgdq9XgSXHc0XGNxYZMHIeO9/L1JSTSiKlsQwO9TyC21Mm5nNN180oCrJ0iBWu0wooPfFlZa76GoPMTCg9zeaJpZjnlDGKaMibPh0Kzs3dyHmZyFlpyKPHIbVLFDZXcPanxpQlDjp0KuzSEkxJ/1+d1eIj9/dxzdfNCQTewiQl2fjiGMKGFHu5t5bN/HXN2aTkmrijZd3s+LndkaUu7j06lHU7vXy1su7mTw9k/Wru3Tt1nANKVIBJlHPlFosIukFLnxlZcRys1CXbsCmNbF67yoOP/wyOtqCWOZNhKY2gsuqsFklwuG4aLskIhVmI1hMaF39ZNsV2loCmGeOxlxWyMjaLWxa3TnIL2MVycm1c8Z5pcxfmM+uHQMs/r6FpYtb8XljpKaZsTtkFh5TwFuvJmvWFQ138MjTU8kvdNA5oPLQ273s3d7LhPQAFjXGbys6EWwWvXIw4NV7vxQVyW5BGJaLYDUT3VaLoKr/MQmRSSI11cxAT9AIZADM00ZhqhiGbWs1/u4AsYJcpOJc1M4+lKq9aN4AQkE2ponlCGku6Bkg1tiBPGo4WPTnmhfsZlSsgy0beujvi3Dl9ZV8/2Uju/12LHPHI4SjDO9roKbPhFLfpgcFQ5Ix6RlmFEWHZo4Zn8ZX/2zgxaersVhF8vLtHHHmKL5qzyCkCORKQSKyifaQmeIMuOZgKM/+D64Z3Ul99L4taCrk5duYMDmdnu4wWzb2oGm6LuKkqRm0tgSSAl67QyYUjDH5/Ons1DKo+vJZ5pdlUFE4lfW9DgLDi1Cbu5Cr95CXArX7vGiqgGlMCVJGCkpHL+a+PlxOic76AbQhhHGYZNA0LMfOJq/QSadPgD0NBFZX43TKxGKqwSwqiHFSopimBzgxBUeGnbwcCzU7+pg2K5OcHBvfftlEWrqZvt4ILrcJq8tCj2pBCEdwEmKgN2owl/+uyRKWWWOQSgtAENBUDU1V0Dp60VQQUhyonb0I/iD52WY61+4jqIi6JmM0SnlqhAnjUhlZmYISU3no7i2ceNpwHA4TdbUeNpqKENPdBL9fjfXwqcRqW5DqGgkHFOO6UgvcVB5Wxh5LDn5vBEHTEOxWYjXNRKvrMM+bgJTmRlVVdn7/Ks3bl+Ky5VBim0SKOddYQ9DAlmLltocmUz4qlZd/hd0dcN/RUJEDv67p5al7NpKabsE5q5JmcwYaGlptC5FdDdQ0L6XVu4OzDrmQpm4X1sN0OL7a60HM1hnuoxt3E9vdCGYZ658ORdhdT7jby7BxWbT/VkOoJ2C8d2JWGmprMktqXqGNSEilrzdstA5kZluxjSykzZqB4LSBzYK5uRW1eh++rniwJwqYZ41FGlGAIIootS1YqnfhnDOG/vQcMmJeeiSnvk2oGqkEyci00eSVyHNrVIZa+dGbQ6y+nZK+Rjx9Ydpag9jcFmxzxhDKyUX1BxGsZgRJ0lvmQhGwmPTqbySqk+rYLMT2NlGWqVGnpiBkpGBqbSPw63aiwcFgQyWKoMmAhiSJzJqbzZyDc7GV5vDsEo2oKBPdtg+xs4fIQADBJKOFI4guO2Jmavy/oyh1rWihiJ5N0fTAzVSahzxtNNqAD7cNAq5UFE2ngxZEgUj8GbkcInMOzqWp3s+O7X2cfWEZ515UZiA+OtqCvPz8Dna0qETzsvHvbUdt60HMTcdy5Axmp3nYumgvA9l5qB4fsapaTLlpKJKMmJehV+XrW4ms3cmsBYUoef8f9v473LLsru+EP2vtdHK6OYeqWzlXdc7qoICQEEYEgcHG4DBOLwzG+LUZPPaL7WFsbLB5sceACZZHRgghlLulljp3V3flXHVzzveefHZc88c6996q7mrBzDPTBk//nqefru576p5z9l57rV/4hnZOf/o8GBKRiiNiDkJKzJN7MFIJgtFZ2sMSa+k26q9fhbq7I1QVd/Q+7javYZOPJDIJlBcgHAv7kSOIYhU51M3BWIkrz4/RqAV3Quz/FCHbcthPnCC4OYN1aJjg1gz+G1d3ft5RIGq4iCDEeeoUquYiu1oJrk3iv3mNWMwgCCNMQ5JMmSRTJtOT1W2k03bYFvEf+AAxt46dsPngIckfXDYJV4sYrdntYtWIOzzZ3+B6JcHsplanx/PwrkxhZ2P49YBwapFoWSP73i5wBbqxI6QgCiKIO1q9fHcntfPj7H2wj0x3jvNvrUBLFip1gqU1govjCNvCfvoeaHh4r19GbZSJfexhsEy809cQcRtr7wAyn0bVXOp/8C2so7sxDw0RX1vjQwcUP/5931nL4r2K9wva9+M9if83FLS//M8vceaNVX7vDx9HSs0h/59+9gxXLm7w4Y/28vnPTOE1ifspYZIQJk5csudojhszRWZndiabUmoY2u3qwbdHJmsxOJzmxD0tHD/VysJ8jX/xjy/w4KPt+J5iY8PF9yI2N1yKmz4trQ7/5n97gHNvrvEf/u01kimT/+H/c4B/9c8u0dUd57GnuvnKF6ZZW3U5dCTPW2+ssntPGidmcu3KJj/9Dw7x8OOd/P2/c5pK2ec/fvoRbNvgj/9wil/9Je0H2tOX4Pt+aIhSyeO3/8Mtnni6m/auGJ/5nXeqT27FHQrJUiKEoq83wZMf7mZ12eXi+XVmpqpElrUNMXq3yGQtfvv3HyOdsbh+pciLzy/w9a8vUFprvOvfkYbAtuWd1geOBe6dh1LyBz/Ak0M++1njK1+c42bbLoyupliOUlgiwrEEf++hBv/+F88wdquMYWjIYUtbjHsfaOO7Pt5HImnyK790mW98bZ5k0sSPwIu0kubCZAnfi3BikhCXZXGGp+55iA8/fZhM1uJ3f2OUKxc3EAIGBlOsr7uUSz5RpIX3Uq0NXrz+LN/7zKMUl/rZmC9hHNsF4hrHMjlee34dW8bIDhSoCgulBNbDRwgujhJc0vdo5L5u6scOse6aqChCSIm1skpwfZLoweN4F0YJr05CENJ2sJNHvncPLe1JPCVYLIIbwJEeeGofWCJifq7GT37qRf7mTx/gv/zOGCfvaeHalSIzU1V6+nZUPg8fy5NvcQgDxRuvLOuJ2/5BjPYc/pvXNCRUQGdfmlq+hZqnCCYXoe5i9LeTxKNRDfDWKohMEtXw2D0YJ540uXR+XTdDpKC11SaZtFjf8CmXfFJ9eX7gE5387m+OcXhfEgScPb2mc0cFopDFeeoUCIG9uES6EGOtHBFJA5FNaQ5gw8Wo10nJgPZExK0VoLsd1fAQjp78xPwGqlShslBCbU2pwpBwdoVU1KDeCPn7/9NRHnuyi7/xYy/r9dPfgf3wEVS5hvvNMzjKp1EPMdtz5J86RsOJ82P3Cz5+BG5DrgFsK2HbtuTv/fwRHn+qCyEEr7y4xC/+/HmEUFrdXIBIxMge6kX2tFOT2oYiuDVLODoLMZv1jVEW6jfZ3/IQtowTRNzpW5mIQdyCNU19EMkYxB3U1rRgG69n6oQ1aCpO5xKo1jz2g0eIZpdwXzivC4ZEDFVvvIM7b9gGZJIoIbFEiLtSvuM1wjYw9g1hHRpC2FqnI1ot4r1xhWhlk0TSxLK0AFtPX5L52Rr7jrdyq203MpfCe/0KlKuEm1U9SX+XdEfmUhhDXZi7exDJBML3aZy+jrOwoJPrZt3c0pMmcbCfte4Bgsuj+GMLqGIFa6AD45FjtC/PsfD8Fdp6UyRjBrdGy8Q/+hA4NuHsMrK3HeloQSWjWEQtbbA2dZlrF7/CwAe+l97YMLUbc1CsIE2D9uG8tsNaqfEjf3k3T33fbv7WZyU/dh8cTpT4nc8u8uak0r//yjjZhOAf/OJJrlST/PFVE0dGNCYWGL1+mvbMHpxjezFNQcyR2JubLJ2eQHS1Yu3tJ5hcxHv5gr7OqRhqeXMb7ohlahsYdJKthNC1iVKoZAKjqwXlekSlGjIRI98W4/DBDK+OwUAuZOy56yggChQkHL3vN9ebaM1iHRzG8ev8kx/LMbSvwE9+Gh4bgb/6kOJv/fxNZrt3o5o6LuFGCVWqYXQUwLawCPnePXVu3axQ36xTHFti7IouEoyhLuwHD6PKNfwrE7qYaj7f4ewyIpMi9sw9JJYWWf36+e31YI70Yt2zH1V3cV+9jO2uc2P2LXJWDzmnSxfGloHZo7tP4eI69v0HdJHmeigEwdQiaq2I7GpBBSFqs6KfacdGtuexDg6RED6Vkoeq1PHP34IgJJEwUZEinjTJDxaY8RN4Y3NQ98i0JiicHGJxooi7sgnlOiIMEUqRSlvsGkkzNlElOjBEODRIVKnh1yqIxTLBuZvI1qwuMqVEBQHR4vodwkPbz10ihnlwCJlNgmMjDIlqeIRzKwQ3Z8APiA+3Y5w6QOg4qIaP+/xbqLUSIhnD/q4HiTVqlL99kcgNsO/dj3f2xp18T8A8MKin47k0qu4iYhb+5QmCcze395l4fyvxvT3ax9f1MfraidZLulh1XUglEZmELtrzaexHjhIuruOfvkrMhnjC3KaqAGT3dpLtyTK/7NNlNWgzNSpjbqbK0ttsurq6E4SRYnG+rr2Dm6gg6+Ag1j0H8K9PYQ5168+ejOG+eglndw90tuKfu4FsLyCTMfz5Fez9gwjTJFzZxP3qa/TvztE6nOfs1/Q57cQM3EZIOmvjjgwRlusYU3P4oUL5ESQcZDKOuW8AY6gbEfgoaejp+8Ii9YpH2q2ycnV+O68SuTTCsZGDnVh7+qh/7RXMQoFsV5rvPiI4d32B1789S9y3+Rs/e4xPX0vip9LE/Tq//9Ppu+6V73W8X9C+H+9J/Pde0AZBxF/40Df4+PcN8ON/fS8AX/zDKT79L0dpkzHGgjJxYbDbzOD0GsT6DKYXq4zdKiGloH8wxfd8coAXvjnP2TfXOXAox4/+5Ai/9stX3wHhdd2Ihx7rYHW5wY1rOxCTrbzxbjzMo8fz3LxRol4LefKD3fztnznIf/y163z7GwvsGslw4+rmdscvDBV/6SdH+PbzC0yNVxgYSjE5XiGTtYgixf/yq/fSP5Di8sV1fv5nzmz/vdvhz/mCzZHjBSxLsrHucua0hmRJCcdPtnDfw618/UtzjN26u7CBlFpSvlT0MS1BMh+nuFp/VwP4rTAMwfd83wAf/GgvLT1pfuSnb1C/MI5j38mre/v1GtmfY9eHDjB1bp6r35rEycTwc1mi6SXMw7uwju2m/vvfAtcj/4EjNLo6eVDOM3FmnrVMK95QP9gWIoxovXWd2Ten3jlBFgKjtw2kpCMrWE23Yu7uaWKEQRIRzK7gnrvO2RufAcOj5tU4WvgI+WQbQ7tS3Ly2I66hiBBIyv4quXgriYSF07bKaL6Hzv0P4b11jejaNOR9Lo99Gz9q8MDIR1B1S0/623IaGrpVYJkG5pHdmCO9ZL0Ka2+N42TiqAPDkExgCEXly6/p5BUwW9OojladqJoGTmuGrr2tLDUssnH4aw/DrW/e5A8+O82jf2Evz35hko5Wi8WFOklHUF19J9TVSZi0FGxqWJr3Wam/4zX6WqKTJ4Hu6DfXhTHUhcymUELoyUaxgkw6tBwboLp7NycLNawrN7ns9FC8sYB7YxZjdy/2g4cYKkB+YYqr12tUDAcjbiF29SGkJKVcMjkbKQRJW3FzCZQQRNU6+AFSgGFJAtNGlWr41ydRE/OoXBr73gO6QLJMPf2JORrOLCXCMgnG5vDevAYND8uRRL1dWAeHkIUMYmGZj/UWyadNrl7eAAVO3ODsmQ02e/qxDg0zkmrw159xuLKgBWq8mstv/sY40jL5ub/Ry8OH4wgB125W+NnfLiP6OrEMaMyvo7wA2Z5HOFaTz6WQ6MspGi6Nb7xJ2CxUlVIoIqQ0kN2tGO0FlOcTrBdhpYh1Yg81VUZRJTvWwAsEUczW6yVuQ93bmcbcfiubiaWIIsK1IiLmoKp1/NPXkH3tWGvrePU7bYCS7Umq6w2M1iyiNUsy4+D194BlEtyYJrgxjUglsI6NIFuydFRX+Ls/1EpHGn7vP97k4s0aD390mBfXM5RdgXt5gmB0TkM/w4jscBv13h49KHnruk6uDal5b1ISzixDFGL0dxDb30/U0UqXqjD5mVfpP9VLefdu6k14bDC7jNHZQji7gnl9jNpikSc/2k8sZfPa2TIbJR+qDazjezB627endFHDQ3k+RiaJcn0aX3udcL2IFHIbZrv/RBsf+3gvjz7ahu0YeF7If/29cX7vt0Zp+eBxZF8HHxTj/O6/v7Hz3Ch00WFIbKH48b82wumLFS7LdoxuvT8JKQgm5gmnFrEO70LkUqgwRNo2Yb2ONC2UH+BfGiO8NnXnc5lJIoIQVXPp6Y3Ts7eVm+0jpHI26zWa9sjvVHULF1bxTl/DrFS3KQJmawYx0IVsyyE3izTGF7f3HwB7Xx+it4OexQmkipiIMliGgN4ORHtBv5kX6GLb0EUuQhBMLuKfva4hzX6AiiJUqBC5FM4TJxFxG+/FC4SzTUpI3MF54ji2irgnmuaF55cIb0PYiHQC56lTiGQc9+XzRJNLCKEIVYjf4pF64hmslM57/CsT+G9d3zkYTEMXrYeGMLrbiAcNqt8+j7tZR/a0Yt97AGEYWFLRnVFMf/smnmmjag3U8jpWFJJOGawv1wjdUH9ntXOv7xbKlFj7hzB39YBt4s8v4b98CS+sEcu2IdtzROMLyL52jD19UG0gU3GizQrBjWlUuYZlSwInhvPB+xCGJFze0I3gMKRtKE8xliF0fcKxWczdfRr9MDpDlE4iknGQQl/3YhXvtcsIx8J56h5kJomqu3TICkvPXqK+VkNkUxTyFukEzEZpFGjhNNfX91YpiBSGoVEd8YTJrj0Zrmw6GCf2byNDRPPf0VoR99nTuqnQkkGtle64Pom0Sd1OotZLGkXRbNCkMxaJpMnyYv1dEUFmzCRo6NcbtkHoh5iHd2Gf2KubG15AVKrqBkCkaLx+CfvwCDKf1jcsUviXxzE7C4j2PMH1KUR7Hu+bb0HdI3uol9JiGbVa1M3bUvWOe330sV6mZxsc2B2jZ38HX1prI1wvEk4vYW9scurDuzjjt2JKGMn5dM+M8sefndTruC2L/dgx1NIm3ksXSPa3kHz8KDVlUXv+DFl/jeevfYGuvUN0x58kml+h50Qvv/NvD9/1WrzX8X5B+368J/Hfe0G75cn6737zAUwkX/t3MzSuhNQJeNlbxkJy5HCenn1J/vgPpym0Ohw4lOfcW6uaJynggYfbyeRsvv3cgubW1EOyWUvDXmEbVufs6yM73MbK184xuL/A0nyV2sad3UwpwbQkUagIAoXtSO57sI2/8jf20tufolLx+eSHv0EUsW3A/nY/2T37M5y8t5XP/e8TBIGG+P7E/7AHIQS/8xu37rCwyWQtjhwvMLI3S70esLrisraixRDGbpWoVnYOhLup9f5fiVhMwwiVgpZ2B6EEK8u3cTWlhg+Cpm+F7zJ0SWcsqhWftvY4a2sNHn6sg2OnWvk3/+Iy0jGJ/eDTFPwyK3/4Kl4oMPYOMNTj8Ov/s/ZrWFys81t/vMHVDZtSuqCLqZll5JkreMkU1r5+iNmIVGJb1RPAinyODhpsrtS58cY8oRvg7O8jSiQoX3qBvtWIr53/PCmrwLG+BygX7779mpZAmSahH2Ed2YV1ZDdepYR7fZSEmcS9On0H72b7+mSSiFQc2duG2dmCf3OG8MaUhiuN9CJacmBodeKoJUd4bRL/zE0MA1JbDYa7hWWA31SfbcthDnbiXxqHhocx3I11ZBcimyIqVVHFKsHEPNHc6s5njDuIZAypFGGxAsG7c8TviKbgCqYJvv82ThUI08DY24/d34FqzSFqDcKGj9ooI2cXCGwH4jFEzMZsz0CLhliKICRyfWQqxpbPa1SuwXoRhQDLROZSmme4WcE7ffUdMEuRTWHv7WPvSBLPDZlOdOBPLiKKZYx9g6AUwfQSRn8HMhFDLK6SW1tg4ezsDsfzLmEe3Y11dLcW21FKQ87Q696QECFoS0Ecn+lFH2yLT56AP/zsFF4+j8ynMVAMiCJ/6/vyDHZYmFLxe59f4g9uJlDpJP6b1wmuN4sW09DczN52ItdDOjbh/CruyxdI9OS4evk5DF/QmzpI//fsZSU2gH/uJuGNabAtfY8dSxdsxSoEgd6s7jL5wZAYu3sxWrNE8ysEE4vEE3oy0TeQZN4uYN53UE+QwpD0+iqPdFQpLZZ57ivau9Z2JNHuAayju7entreHUgpVrCASMYRtEc6vkp+dZPHqMjKbJPHkCUQ2xYl8lTenBSqZANfDuzBGtLSOqrvbHEBz3wCys6Dfx/XxL4wSrZdQ5RoyZtGSNYg5EgyDuekKkWHgtKRQ1QZBIkHsg/ehgpBorYh/eZxorQS1BsZIr4bZxiyuvvR7DPh7MKthE14qOXFfG3/5J3ax70BOr81I8QfPbvCfx3P4Z2/gX55AWAaxw0NkHKhPLlFaKL/jWuwsVoFxYJBodhlVrqEiRdlfYbT8BrldB9j9xKdw4mmEaRLVXRp/9NKd+4ttkXrqOKIlR+2li3ziyRyZw/185rzehL0rE5h9HViFFEEE/rmbRBtlZEtWf/6NMo5bIzx+AFyfcHQGY6SfaHmD4OrE3ddK83NvFx8CzMO7sfb0agSBAv/yONZIr35NpMC2UGtFolIVo6sFcXMSZ2YOLEntwH6M/k5SM9Msv3D1XfcgaUmiZvEtWrM0RlLk9x7Fm5xFTa6gogj7nv2EXoOJr3+Ggf77CUcXMfYPYA7q6a1RSNM/P8bs+XlqoUFcuTz0aCcPP95J53CWz39xkRfKreA4NJ4/g1paByFI37eHcO+wLhSVIphZwv/W2XcWsZaJ7MhjDHZh9rRpBNKWTdbMEkJqikm4uIb34jmiqrsjVmSbxD7yoEZdqCb0Xwii1SLhxDzmoWHwAtyvvwGui2CHTiESDtbJfZi7elCej7AtVBQRLW1o8bOuFiLDILg8TjC5gPPkKYRjES5tEC2sEU4u6Iambd6BmHp7w9750H0Iy6Tx3Jvb08aevgS2bTAxVib74ZP4He3ATgfbvzmD/+qlnV8SsxH5NJZl4M0sgwIZsxGDHVD3CacW9R5rG0SuzmXsPb3I/UMQ6WsfXZvY/hnAkx/qpF6NuHajRO3UcWQ2iX99GmGZiGSMqOESXp9GVeu66SIFIDCP7cY6tKvpZSj0/tYswr2XL6KK1XdFj9z5PEDsY4+gPJ/7/Ck+/NEeXvjmIi8YQyjTRBiS+ue+rZs6Arp7Eqw6WYxHjlP5yosYtRBiNtQaOA8dQXS3EozOsjx2lsvnP83+lg/wS//s4zz1dCdSvrNB9d8i3i9o34/3JP57KWg3N1wmxyt0dSfo6Ipz7coGz399nvGxMjcvFzkQy5KqWQhgNqoxHlUY2JXikz80xONPd4GCr31plue+Okel7PPAI+0UWhw+//tT2zy2u01Yu3oTLMzWkP0dYBpEEwvIzjzO0/fqDc8P8G9MEZu8wWMP9/Dw410M787Q0hrj1vUin/5Po7z8whK7RtL85b+2h2tX9P/bEkX5mz99gImxMqM3S6ws1++A3ezek6Z3IMn1K8VtJeHbORy/8M+P88gTXcxOV/jNX7/JmdOrSKk3yEKrw+svrxCLSwwpqFZ3oL3tHTEef7qTz/3+DKGQkEnAyttEDb5DbF+nrT/EHYzuVqJKXR/6/zfE8b9wiBvpfuqffxEr9PEt3RnH1YrAZkuGhVwX5mAXALJeQ9oWgTS1B7eUhCubCEtDVEVzqqdcD5lL68/th4iYTbhWZOLF38fqbGfggY8TTMzjvXwBbitotny9t/8bNLel7kLDQ3a2YI70agjbZkVDdW+v5KVAdhQwDw0Rzq0S3mr6v/oh5kgv5q4e3DeuojZuS3i3ivDau0O374i7TQYMiTHcg/PQYZTv4V+aJBid1YlwECLyaa1GWneJVos772+Z+qC/HQJuSp2QfqdpvWXqKcO6Fh3R312TV2VnAWO4B5FP0dfpsNYw8CyHYHaZ6NIYkRA4T5xAuT4ykySYW9EwteUNwvEFqNaINqt6stKRx25JY2fiuIUCwrGQyTjR/AqUqvhrJcJbs5BLEf/Q/dsQZBWGet2ul6i/cJ7Ydz2AcGzUZhn3pQuY1Sp+04PyysUNRMzi4A+d4taGSXR9imBpQyeIQYAARFsec28/waUxwpllzM48XfcNU3aSegAfj6EqdSI/wLw6Sm1yGfPoCH/7aYsPf6yP1ybgzSmozm8y+tx1pq+v09IRo9g7iDAl/lvXkbkUzofuB1MnoaniKuVkHmv/IMr1aDx7GplJEi2sMefdYGLzNMc/9GMci/cxXTVxz49pGPWjx8CQqLpLcH2K4PK4Xi9xR09LZpYhGdOQx9Ui0e3Qw+baMoa6tEfiahFhSp2Qzq9QP30N4fpNkTvNte/uiTM/34BcEjMdx0lYRF5IkEwQXpvClCAMQdDRhnV8DyKV0Nfx8hiRAuvUfqz9A5pDaZmazxiGRBtl/Jkl1OyKfr7qHs4z9yLbcrgvntd8N/fdm3fSECAlkR9i7+vD2DtAFEYcXhvl0tnVdyBKoNmEKqSJylUo1rZFxkRrDrMjhwhDgmIN++GjqEoN92tvgGUgju1h/8MDDLcKbizBzFgR/+Y04eTCDkJD6s9jP3Mv/rVJ/NI1JmYvklHdtCd2gYJ6WOJC+Vke/KFfxElk9ZQrjJAdecz9QwTnbmhoKiAKGewHD2O0ZnXjoNZA+SGUqwQTC6hyDYSCYnWnEDDepbnRfKaN4W7MwOdoe8D1ZA9uMk1UqRKNL9xhdYRhYLZlSAy04ezroyr0tNzeWCc0TIJUmnB+FYsQ2dlCYJiEcyuEY3OIVJwDpzroG8nzrZsAClVzcU9fRS1vIlsyYEjChbU77m/JW+bC+lc4ft9P0vrgYwjL2p6kq1IFf3yB4Pwtkvt6eObJFr5e7ARTnxNqo0w4vYR/fQrpe7S3x7VieNFjfLRC7+4slWNHcJ0Y7gvn9IPg2JgqJJ8UrI+v41e39rkt1T0D66HDGAOdCD/QQlZAGPgYpm7uBOPzeK9fRhYy+rkEii+/xtzKWeJGlv6nPoFZKOx8j9sSEyEE4VoJ97nTNPxNiqkaZn8n4sYS6UYKK54C1yf2iUe3aSDh7DLReolwfB68APPQkFasRp+VACoICW5OI6cX8DGIVjfJpQ02N7aEItk+X4xmg8I6vAuCkPDl8/jLzRwiFSf2zD3ITKr513Y+e2JikuLr1/FchShksE7txWjNgWEQ3pjEH51DrZfBkNhP34O0LIK3rhE0LXBEzCaWi1NfKmkaPBq9oTbKKNfDfuAwUVFTIoy2HLI9T3h1HGPfIO6zb2AcGCa8MU20vIEx0ktUqu3kLKaB/fgJjLYsmMYOnxsIJhbwX7mIbMth7uohnF8lnF1B6MkEXT0JlhbrhIFCZBJYR3bjX5lAbZTJtsYZfHQXtzL9gMLc2KSxWqEvrxg+3sXEumBqYhMZCt2g2AopkK1ZYkd3QU8Hwa0Zzn7935LMeoy+/K/vyEf+W8f7Be378Z7Efw8F7ed/f5Jf/zdXd9R1m56FAAaCHpmgqDyKaueQO3wszz/71/cQj5ssLdb5hZ89s20EDlrEqFTy7xCrkVIXjJ73p3jcHBNyKbw2i9ThQ/hulYkv/2cGGiMIIejtS9LVG6enL0k6ZfHmGytcv3Jn0ZhMmlSr31l9UkiBQL1DQRggFtMKvKXin2Ly+rZiRwhQhoEx0EE4ufjuycxtISVETZhu94O7yAVlbs4pgtmVbdEM4I5J4Xea0H6niH33Q6i6i3dxDByL2AdO4r1+hXBsTn94P9DFU1cB6+geZD6lGwxNvLFaL9F49jTx738S/9okYqOEGOgkWi8RzaxoyKppIFIx7ON7MToK+FfGiVZL2A8eIipWKT37bWRrHmulrotbAepIB8m+AfzlMv6b1wAw9g+ilje2hSMwDWRbDqOzRQtr+AHRyqaGS96Nj2w0C77hXmRnjuDVy/pamgbmnj7MkV7CpQ38168ge9uIljc1N+fdbpnTnIi5PkiB9dARjN52/DeuEI7PI3vakC0ZPR1LxRGmgaq5GuaVcDT3Rwi8ly8SLqzqjnUyDk0YciJtUSt/hzVnGhj9Hfqf7laUIYmmFvHP3mwqzDYTv5iNubsHc98AIhnXidriOiKdIFpax3vx/J2XaVe3Vnk8sgvDsfDH5gmX1glnVyBSmHv7sU/uwRSK2uvXCOdXifW2Up9bw/nQfRi2hXPxKqEw8I/s2/6swcQ85oBujERrRaLmvTQ7coi+DvwzN/S9U+hiTwqiSl1Pj5oTafPAIMQdgrM3IGZr4aJCFklErrhKbbFEuehhP3aM6NokvZmQcnsnlXgWcXWUxsLmznUxpP5zGGIM92A/cFA/fEGI+823tKJmpDAPDGKd3KthsV98BZmOIw4OMXrx88xdeYF7nv4f+anv6ee/vNCgZjjEMjH6++KMbxiozTL1589CbUcx2BjqwnroCP7pq4RzK3R2x0ns7mI+3YmwTfwrk1iHholWNvC+8SYqiIjn4/hdHci+doK5FaLLE+++LkB/ry2ooiF3ijpDYh3ZjXFoCLVWwjt9FeF62E/fg0gnm39VaHuYLQgrOgkPZ5cxBjpxn3uTaHkDkU1hJSyijbL2aW7ufU7cQEqoN5t7IpPQv6/mYlriDrE40dWimxtVD+KOhn0216ZszRFtljVtINIiUsZIL9bBIRAC99tnNfJh67omY3zvDw3yV/7SIBGSl89V+KVfnyIYncUoZAg3q9gPH9GQ0vWSbtwptH9lw9vem92whtPaBhUXhMA6PoK1f5Bos7K9NwfXpwiuTSFiNtY9+xEtGfxXLxMtrTf51JaGoVcbEIRk8jbZjjTl4UFq1RCRSqBqDfyzNxD1OnKol1TeppbKaXTAZgWRTeoGYbGK8jzMWo3o3A3qRRfZkkH5gYZjmibmPg3P3yrqtkL5Af7VcQiVLorCSIvvVGoavZJKIDtbUJ5PtLqpxfK2EnilEGGIt7CG0Zrljf/094nbCe7p/wjF+TIINJw/q6f3RiFDsLZJ9a0LJA8dIJxZJpyY34EHh9F2g+LtYRgCZUisx04gu1rwz97Q/slbTT0B2JZGT3Tppq77jTdRlTr2qT2Y+4aonD7Hm6/8Gse/56fJtA4QVRuaWwwQhJrzH7P1edT8jlEU4U3PEb51k6hWp5qtEz9xhGzfXqIwJAo8xp//fWqNVbx6mbbh47TtPkkskcFMZHAXl3A6O2gszGMUckhp4o9OE71xE2OgA5JxrL39iEwSgpBoaoGo7mHuH0QYEmdzg1pdw8KDJb0fRpU6yc40R58cJjXQysvjAuV62/toOLtCtF7COjCom4Suh391kuDCKDgW9sm92pN5cY1gflWL/rkeRhAQppIoIBibw3/jit7vXB9jTx/2fQeIilWMsWnq44taCyHS+YYopHUTVgFS6qZpXztGf4dec1GEsC2yM5MsXJyHjTIEIda+fqxjI4RfexW/rRWZcIjmV4lWmvuwANnThrGrB7O3/Q5peyEEweIa0eVxwmJFN4uaImYEESIdR2151dpaoR7XQ6QTGAMdBGPzxGISZVugoEFA8iOP0/jGm0SzK1i5BH3DGWanq3ir5Z3zdKgLVYjz4v/2d/i+n/i7/MKPHmW44/+6rdz/nfF+Qft+vCfx572gHb1R4q//2MtYtuTEPS2M3Siy2vQbHHCSiADmwhohighdkP7Uzx3iiWe6sW2DC2fX+Mc/dxbTFHzsewd45eV5Rkfr21CmLZuHRj28e9HVhOktz19mtnSRQ4VnEIbEUAZiVydLa9cYSfXj33OEKJnEqFZJryyz+Mqtd+XRbE2/Yh97GGkaxGIGXiQI6h7BrVmCi6N3F4Fo0Z1DtbzxjgrRcQSer9h/MMe1y5t3/lhKjKFOZH8HCeWTWF5i4dqq3vzrdfzNGn39SWamq9w1bFMXqE3YkLGrB/PgoObcFSsEY3OE43PbRd+7QRkdR+IF6k711XdcGwPz8G7sI7uIyjVkuukFGIS4z54mWi1intiDOdil/Q3XdZNCZJOah9qcpDe++DLmcA/mwSEaL5yFYg1ZqxO6b2sgJGI0vBKOk8Rsa9XfNYw057KQaSa8dWQqoXlPcucAUWGEf/4mweUJrBN7IPCR/V3IfJqoWCG8MYNsz2EMdukEyJB4r11mQG0CsG5ncPfvQaTiqEjtdOMbHtFmGVnIgGngn7lJcHUc2dWK/fhxhFL4F8c0d6lpDxIsrBJen9rhrW1dfymQ7QVUEKDWy1gPH9aQrmRcJzN1l6hSxzAloVJ4L10EL9Cqpn3tBLdm8N64eteEb5sLnU1qONbt/xPN0TR39WDu7gVbi6iEkwtE86u6QGzyo7AtzOFuDfPKpDD39NJ47k3MoS7807fBDqXYhjc6HziJ0VHQUNH1EsGtGdJxQdmX2EdHwLEIJ+bxXr6or70UmIeGMQ/vgnPXCS0b89iIhq3dnNZiHpmkTkiawh5RpYb7ldeBpjDKcDdYpv7sYaj5aKZBOL9KcFmrVpon9hAtrukmkRSYB4e1oErMRmdgYvseCctENVzC+TWc2Xn2dsGZaw3Ueglzbz/GoSFkKqGRBPaO1ccWnP+O6Y1SzZxOq8LOXXmR6toce5/8iyjA9l0ai0Wd6MdsbbpKbTcAAORISURBVAnx9dOopXXNdU5LVpfqpIbaCe49TLi0gffqJd0UiVlY9x/GHGiutZszOqms1gmX1nXy1mxQyHSCaHXz3fe+u6AIZGdBi/uUavhnruumRzM5Nff0IXs7CMdmtdBMsUJwYRT7seN66t7wicrVJqc6JJxb0cqrUiB727B3d5NcW6Mxu0p1ZWd/MzJx6GnX08r51Xf4zop0HJnPIAu6QAtGZ/V+5wfaoiYVh0SMaK2o13Gz0Laaayy+uU7j1jxifoVqUReoMh0n8ZH7ieJaET2YXsR7/izGvgHsoU5Ehxa7ixoe0dI6/rmbqFJVI0GqDT2hTsV00bmyCZapi4JkHMIQ0zHp251l8lYR//yobrAZEpFNIltzmHv7kYYgcfYS67Ml8k8fw+/uwjSgPQ0/9YTiP/zmBNfT/XpiNj6P99plZHse+9Q+vV9srbnNCiKXwq7V8GMxBIrYuausXZkD20KqAHIZoi3kjyF1wh9GGCN9yFwKc0gjp7YaFFvNCqKI4Mok4fwyzlP37jRAlEI0GuAFqFRS7/PldRZPP0/HSg6U0s0400AtrhE2+Zkin8J6/ARGOkFwaRzv4iih6bK2OY1tJsjHenQRNNQNQYB/flSvi7cv3ZYsMhUj2qzqgl0pRHsO2ZZHpuIa/bG6SbiwhijkcJ6+B3d0kjee+1/Jdw1w+BM/u01hjomIhpJsUSm2UnxVaxBcGCWYWgL3zuanuX8A68huRPwuXvVRBE3EWLhZxkjpZk0wuQD9bchQYRay+HNLJPs7aElELGxE1L95BvvQMLK7FTk+Q6PUwD44dAdN4O3oJNBgna6MYnpNaV74ba9RUYR/bZLw5gyqWEV2tejPHISQimMf34OwTMKlddxnT4NtYYz0aDGl3b2oJm0gXFxD2Bp5Y92zD5nc8VwNN8r4p69qu6GYrfcCQDUbNd8xYjbx73sC/8o4wblb3/m1zRDZpD4TO1sI5lZ0s7WJEhAtGez7DmK057fvY7S0TrRZIZxc1NZSQmjXiIaL16hQD4okzTyGMIk9cx8kYzQ+/yJOzMRzQ2RvO90fOcbqfDO/mltBlWpa4K8rT2l1isP7d/Mb/+7Yn+rz/z8d7xe078d7En+eC9ooiviBjz7P5obHb3z6EYSEn/jUS8QTJj+wf5DNSx6X/A3u/YttrKy4PPvlOQxDn5GtrTEajfDO6aVlYnS1YPS2I9tzBNcmCG7M3v3NBRgPHcYe7KbxpVcoxorkTt6HHU8TLa9TOXseq24gItXM6tHJarNw2UqiHUsQhRF+s/u/lfybh4cBiPW0ECSTusiNFCJuQxjpid7SOqCQ3W3IbEo3Dm1Lm9Wfvko0vQToIj4MFYnEOye+IpdEJOJE86sYmQTG0RHkQAcLF76Ne/kWnWrgnV89ZqJsG0r6ULc6csi2HP5aWXf6/wSBqNuv4fY1+T8TjoUx2Ik51EVUrmu/0iBE5tOEa0VkPkPY9B8UcZtwepFwZmVH3bUpgCN723Qi2ITRylyK9AP7KL18FXdzjTV3hq7MXtiS4Zey2VHVNgy4vu6ODndj7OrBSCcg5rAF09o6xKNyDe/VS8iWLKI1h9ookTwyiG/oqYR/bRL/jauYh4b1RG1hBdlooIb6MJoSU1ETnisTMaImfCpcWCO4MqEPaFuvj60k1tzT987rFkWEU0sYg52oSp1wtYgqVlANb1sII6rUsU/u1cVUM4FUdZdoeVNzsVpzeC+cR5WqmMdGsI7u1uqep68iWrKIbIpwYp5odhkQGHv6kHFHQxk3m2q7/R2YA526eG3aOsi2HKKjoEVrGi6kE0jTJLg+pQV4BjoJ51eJf+JR/Zm8gMYfvwxBgDQNrCdO4l8aI5q5zT84l8Ia7MI8NKSFg+oNItvWBcHUEub+AWh4hKUq4dgc0dKGLs4ODmP0tMF6UatUDnQitvw30QWj8n28b59DRRHOY8dR5ToqDDHa8zphdj19fZt85HBtU8PMqw2MwS6cEyOo5mQxWiuBFBiFzA4ywDK1hsxGGVIxZExfQ++FcxoOeHKfhkK+dhnnQ/fpNRl3kLaF8vU1VA0PmUlqm6fmWrz93/rLNItd1yeYWiK8PI7V24pxeBfEHMzpWf7t3++lkBD8s1+b5vQXtXKpeXgXcqCLaGENkUloj9tqA1V3dTEnhG78NK09vNevwNomUQj4PnbKxrnnALVijfDKBCLmYOzuIbjNogNoeoxqMSpVbWwXFqreIJxa0kVZzG42hSLC6UVEKgENTyevb0+NTEOLrm2U746GkJp7vQ1ZjdnI1hwqjFALq8iBTuxHjiKDAHd6lpm51+kPhghWKtgPH0WqCGdpifL4CpF7G188FYOKhmjLTALzgcPIbJLg8jhhrYFwfb13NvdDYTepEXEH52OPoFY3daOgCammWEW0ZDEGOjHachhdLYRL63ivXtLNo9saR8bhXRgqQu4b1Pemed+j2SXc07pBYO4bQBTS2sc6ijAGuxi0qvDAURaCGElb0Dt9g3NfH0fEbZyPPIBMJYj8QK/3Sl3zOf2m5ZEURGslwuklorkVsCTGXv28+W9eRZPnBS2He/HLDUrjKzvNjOZ0Xna2aNXqbm21p2oNokqdYHxeC761ZEnv72XXcJLLFzYI1zbvaJSGyxuaM/+dzpfbxNCMgU6sh49A3cV77TLTM68ysfoaRzs+RkYUENkk8UePofIZwitjeOdubVNqoihEhQGG7ejGxloJkUuBY2toa1sO2ZEnmFggGJ3FfvoE3tISfPsaC94Nhn74J5Hx5DaHdms83JOF+WKzrl9cofyt8yAE5q4enEwMqy1DrejivXp5m6OMIXXDJ5NC9rQS62vlUGfE8vUV5qZKhC0F7GMjWlxseoloaQNVa2A8fhhnsE9/pzBCfftNTuy2OHqihRfmY4xFOa010Wxct8ZDatVAK7ArpZ+/2RXCqUV9HnYWthu84jalx5hfp3JrkajhaaRSdxvi9gmnigiKNdR6STdtyrVmXS8QKV28mv2dd9xGFUaE8ytEmxXwA02XiNk4jx3XVkvN3x9VGzqvuzzxThh9zNYF9f5BjO5WvAuj2qLr6iTSd+k/0ct8wyK7ssjKokYjxbMOjbKrbcTSCYzBTqwjuwF0k6s1p6H9lToi4TTRYyHRepHgxrR+lmOOtsQq17ZRXCEhQoE51Evs8eOUn3sFc7649ejqcCysY7uJNqpEc8tahFFKrX8QKYRj8twLz7z72n8P4/2C9v14T+LPW0Fb3PSYHC+Tydr83m/e4sXnF/nBvzjM9//IMD/+gy+yueHx3SN9WLOCG8kS1zeKfOi7e/nqF2dJxA0qlQDT0vzULZiuUoqICLOtoI3hb+cpAsbuXlTcRk0vaa5WszASqTh2ewY3Fydx5ADBzBJqo4LR3w6WReOl89DkLX1HqeO3hcinmwp5AmO4W0NSZ5d1spB0MA8MY+3pA8PQE5yZJYJL46hKHdmSRXa36kJnK0G4Gx4ZNH/wg/cSlevkLlwkZgumJiqEFpjxhL4WkSJuRpw8WeCt02t4pk1Uaejp0t5+zBHdMTXachr6XGnQ+OZbqHIde1enTg7WKhoG2pYnmF7AXFjBSDqEB0fwLo4RrRWxOvJYlQq19RrJuOTw0Tzn3lrTfLVsEmukl6hcI5xexhzu1n6Lb++0moZOgIa6kJ16mqFKNa34ObN8p0CKFBqyVm2wpXIs23L4cyuwtE5ULCNoFqVbDQhDaj5h3NGD5u5WPS24NauFlfo7MPb2gWVitmaRtRooQZRM3DG53VoHAghWNwmuTuoiTkqM7jbMff3bvKVos0xwbQo1Potlg9fdjdnbjqrWCS5PaPihFMQ//jDEYprj1NWii+coIphcQDU8jOEeZNzZLmTe3lHfPkL8AOV6iHiTn7s1/fCbcNbmgWsMdRFOLupn4OHDqLpHcG2KaEnDLs19/Xoa0uzki+akMlzewDq8i3BuBe+lCztT2NvuIam4hrp6PqK7FcM2CSYXka1ZrPsPIs5dx08kiCYXcD7xGDLuQBRpiKNlErx1jXBqSXerbUsXwJW6Tl5uS2Kcjz1MvCWFp+6EZQUzSwSXJzS8LIrA0lww8/Cu7WLQvzRGtLSB8+QpDVszDcKVDbxvnyM+3Em0ZxCRihOOz+Ofv6Uhhs/cg6o2NBRdgbm3D2egjailoOHUK5u4X3kVGbMhl8Ic7MbY3YMwDKJqncYfv4xsy+M8eZJwfJ5oYRVjoAvZ28ZAQRGEAjE+w60vXcZ+7LhucjS8Zvc/rhEStoWIW/q6bK3J5vXYKsSjhTWizTJWPokY6KbF9AlXNlhfqtMWldmcKVJaKGl16C0rH+8u99GxoeFuEeq11UsTli66W7GPjejEuVzTTarOFqKNEu63zkIQ6olYc+8SjqWfr/Y8w06V8Xkf1VZArZXwr08Rzizr53QL/lusoGoNfc9sU8NV59fAEGBZGuKXiDfhu2+bvubTmId3Ea5uEt2Y1nt2EGIMd2M/dBhjcZWG60JnDjG2gn/mBs6TJzH6OvTaOHOD4PI45qFhYu0Z6vMbmpvYnN7eEekERiGD8n2ihfWd5mc6sd0wREr9uf237XeGgTHYidHfQbRRxtzVoxPw6QXKL75CXKS3p/X2R+5HxhzcZ08j4zb3/YX9LM43WC0GsLBKZXyZKIgQhYwupmuu5p33tCENQbisKREim9INlV1Nb+DmXqKUQjU8grFZwqklZDaFOdiJbNNK3eGaVnNVdZeoWIEwwnn0mG64qIiw5uKfu6UpI1Loaa0X7HCRcyn9fhtlPQlNxnRD1/Uh7kDdRVoG0pQEftjUN1D6/EvFdcMMtIjQ7QVuzNYiSGtFPeEyDcz9g1jHR0iuLPHiH/4qaVroSx5EmlKLK/b3stLSDUHI6tRFrj73WzRKujEXz3VwMv1diFDpoiIV1+do3dXooqFuzL39eMJj+fOfJ2kUSKRaiH3vYwC0e0UWJ4sY+wZRdRfVcEnGBMnFRaZfHAXLIPbRh5CZJIZQJExFZnGWW9+8pZ/F1SKyJcPI/hyLUyWK8yVNV2nJ6mIvFcd54DDCNml85VVELq2n4Xv7USJg5uw36bjnCRK5doLRWbw3rmgEiATTlKQ+ci9uJo+MApRp8sRQQDKo8aWptIaSNxXioZlXLa4Rzq8RFSuaMtCa1T+Lom04dTA+T7hZRiZiyEIaVXUJrk1ua09s8WhVFJF0q0QbJWqpHMRsosV1wplFZEsWc1gjpILrU6gowjo4vF3IWgY8NuDx7G9eoDG1gr1/gMQD+/USW1zXzdW1EiKdIPb4cTpVib/7pORzv32Tl7612Pw+YMdMnnymk8NH8/zLX7y0I7TVTOscR/LAjx7nTa8NJW5Da0URsVKRyvwmsi2P0ZZD+QHeW9cIb8xsvy6MSaz2Nj2trddxHjhEf6xE38Is89M1ymWfudkqYu+A1oAIQjAMZGdB6ySslfS5pSKM3gJf/+z9/FmI9wva9+M9iT9PBe3vf3qc3/z/37hD8deyJYPDKWamqjTqISPxNEdUgcvmBrfq5e+oRArNTVdEGLG4Tv5MgygKERHIZIzEsWG8SGKkY0Shwn/jKiIVxzw6QnhtUnMI/ZDQERjube+1VQTd5dFUgPXQYdis6MITIBXH3KOtSEgnEIk44cQc4bXJnS7/bXA80xKEyaSG9m2JAjXFQwhDWvsyqEdOUjdjRFfHaZy9tdONNCWiPY812IUx1E3jCy9ptdd792vD+PE5DU9yPfB0N1FVG1rhtrMFYZuYewcQWT1hCqcW4doEpi2pLZf1+0TROzrj5pFdGgJXb2guZHuBxue+jbG3X6tZWqZO7DYqCMvUfo9JRxNt0fwZmU0ik3Hqn/2WnpIfHEKmkwjb1FPr6aXtBFnEbFSxqjlsw93IQgb/5jRqcR37Q/drL9WzN4mW1vSU7PbPK4WGvqUT+h4rUCpCJuJamTWdQFUbRBslLQYzu0pwdUK/X2sWc6RXNxdasrSOXUP6EYud/fo2JuIIywDENiz09vXY/AOEIfXPvbAzSXo7zzkZwzw2grkFo4sUqlLT9gq3i4S4HpEbIDKJ5gQkQjXFSLbq2k7bY8k1iZRkRwhEkQxdalWfKK0FPIKb2ujeOLUXmUkSXhwjWtnQkMm2nFa/HerS0Nbbuu5sQaaF0FDdr76hVSTfLYSG0IUzK6hyDWPfANHcSrMBgZ7+dRawhzpxWtL4hsWeWJUrX7i0bc1w1+ZRU4AKQGSSWCf2IPs79OeNIl2MXJlAtueRuRThemlnst9cFwj9nMU/+YRuKkURqlpvFtZKc7lnliARw+hswRjoQOTSGOkE7ukrCNtGFStaLMexkIUMsjVLOLcCHXmYXt7+niKfQRTSUKpqf9C+DoxCGmN3H+7zbxF77Djh4hrG6YtEocJVBrIlS+r+vQTZLKZQ+F6IsEyiYhX//C3ND0TfL/vJEwjb3hF+iSJ98ZuNnHB1U8PrEzGiqxO0rs6xtubTKLuao96a1QVGPq3vSdzWzY2rE9s8MSvp0DqcZ3F0HeX6mIeGCcfn77B+EnEHkU3qaU1nHv/1q3qib1tYR3djDPfQvjZH0UriFVq2YYzKCxC22fQ2LUOtQXx9jb3ZBm++uIBCbPvrEne2v5ezuwtacoi+TsK1ouZvbylgN9eNSCd0EVXSUGSrI0OYy6ASDsILcdeXsSrgPHhIT5E9n+DGDOHYHNY9+zUCwPWQtokyTCI/0KiK61N3vpcht+2jgHc2ebbOkpgu+pWURLNL2lz6tgmj7GvXUGtDUl2dJe4UaL91jZlLyxh97WA34fCenuQJw8CyJemsxeZKnTDSyBPZnke2Zomqdc31bUJBrSO7NTz+tj0rqVxa8xZTmxIaLsq2EGeukhloYfH5KwgpaH3iIJ4bUV2pEM6vaiuWKEIkY/r+xR2M/naUH2p+/GaFaHJB7xk9rfr1bxe+cyykaRDVGlp86MReZHcraqNCODGPP7XAXOUSA11DOFGeejUgX7BJZyymp6rInnaNTKhphI5sz7NnT5Lxs4t4Na2/YJ3ah+xpxX/jKutL1zGP7eHKN38DJ5lj+MFPkOvZi53MsnT+JRLTq3jrAUJBwshomPyxPciOvOZUzq0SLa3p5mfd1XSVhgs1V0/8O1twv/oa+58cZjzK4r1+VRcmt29dPW04jx8nnTRI+TWmX7hJMLeKc2AA59hubKlY/+IbGk0Ts7fzGZFOQNRUDU/GsI7uJphebqJo0GeRZaLqLoahGK+8RtjVxbA6pAXOmmrGWwgi4/UL9Fo1Js0WxEHNbw7G5jD39muF/HKNYGyOaH4F2ZJD9rRg7urV/PFvvKURN61ZZFuecHUTwgj7xAjCtvXzZhpEM8tkVhboPdTO5XEXo6cdo7CTnyqlEHUX4XkEShLNLeNfncA6MIh5YGh7P3Oa2oW1eoj30nnCqSVi+/uQx/Y2tSSajcTn3sR+8JBuFgvtkx2tbGqKwv8Z1BnQ2hbjA9/Vx2aulVe+MomtAgbaDM6/uriz3xUyyISj9R0cC1NCUPdoqBoxoeHy5q4ejMEuXfCPz+3kb808QDoWyrbeAX+3e1sRJ/bQb1f49Z/p/VN/7v8n4/2C9v14T+LPS0H7wjcX+Kf/8Byf/NQQC3M1Xn5hiVhMkt/XyeJkEVX3ae/t5uG5iEmjwvnGuoa3/WniNpGiO0KKnQMhjHSCFrP15ub5mBZs+itYUQpHxt/592+LeMKgkUhhHBtB3ZwhmF7COrUPoyOHf/aW5pUFkZ4wHh9BphKaE7qwtq14/B2jmXSq9RKikMH5yP3IplIjoCGIi+t4o7NQbSBasjgPHyFRKRIm4niGQ1SpMX7mS5hLVTpzBzUEs7eAcWiQ6Ow48Q/epyFmfgCmgXdpDOEF2p7EMDTcre5uF4PhtUmi9ZKmBmYSGN1tKD/Q9jAxWyf+4/Pv+pVkdyvW4V0YXXraKitVolQS9/RVwtFZ3YUPQ0RnAaOrBZlLI3vb4euvoBQE8ThGVyvC93CvTGHu011NWUjjPHqMSCmi1SLBlQmi+VVkd4sWQsokMQ8M6usXKZ0Y2OYdsNNgboVoeQPryK5mkaYhkbgewfUprShqGvoQ2oLQtWQ1tChmIwsZzD49yQ9nlgjH5xH5FPaxPfhvXcMfX8DY20d47tadhVkiplW0XB+juwXrwSMa6sedU1cVhndMhW/nL73da1KtbSIKOd0g8Fzs9XU2L88hcymsE3tRpSru6as4Dx9BJjUXLJhYbPJXA6yjIxhDXVpMJlR6wnjHG+iJtCUV5vIKtWRW+5JeHse/PI4IQyhkNCR3S/l4q3hPxfVk7OgIwfgc/ulr70z40XAvVanR0p9jz1MjXL1exm/JE9R8gsvjWiipOY0RuRQyGce/NKahgam4hlc3xUSMkR6sQ8PElpYx+zuoYBNcGtNTg2ZiY53Yg3lgiMYfvqCnfABxG+eRY1royvUJl9Y157NYBVvTGcJ53QDDMpADnVrxerOygzZwbK1+G2nBlcjful8K+5l7tZCYENuQetmSRX31ZVDg+npKJluzyGxKQ/pScYKbM/qZ7GvHOjpCOL+iGxFhhGzL4jx8tFmkC4RhEC6s4X7rDObBYayDQ9sekfpWNgv2mzN3XP/IFJjdGjmg1rRHpLGvHyOXIpxd3bZgsUZ6ibemCZdWKV+cxuxrxxju3k5At9ZotFIkuDGlm2WhtskwDg7pvcMwwPVRUiAdG0oVzXe7NYdwLCLT0Pfy3ZSMYw40XG0Hcu9+TVkAovUS7vNn4fZGy12aIs15885L4g6GUAQ1DwT0PrQLa98AS4EDaCRGLh6RET4zVZNIGIRrRdxvn4NyDdGWw+hpwzw8rNXXl9a1l6VjNeGIMQ3ndn3wPIy+DkTcIZxbRQmB//wZLebU5FQqU+riN5vB6GlFCanFyJpCedvPT8JBWBaqXNXFYzpB7okjKBVR9yVGp+agB2NzBFfGUaUasj2PeWiIuAyJ2loInR27M6WUtqEul3DGJ6FaZ2mqpJuuQCxpQTqBH08w0G1TnFxnbVn7RWNIfX6Va/ped7fCZpmwchcF9ybXliDE2N2LdXKvtjJyfWRHAaMth1cpsv7yS6QXJQLo6U+STBrcvFbCMAUhkpNPD/IDH2lhpRTxmd+8ydxUmf6BJJZjcOt6E+cbs7H2D7IpV5l8+Y/oSu7FxGSzNEstLDI8/CR2ubkgXB9sE/uhI/gpj1i+FyElG5fP0+Zew+08SNE3SKsc4a05DYe2Lcw9fVq87PrUznO4tSdVG4hcUtsjrW4SLa0jk3GM/g7MPf130AlQESpSuC9eIJpa3EYUUXMhGcPa3Uu4sKY5m7ev37ctcaUUblTDkg61PSnajj0I1RqiJUtwbUp79W5F3ME+vgdjpPeO8ydc2SQYnyNcL2G0ZInmV3eEkOA7043iDkZnAWOgE6XA6m3FMgXVl68QlatI0yBYLWKE4fZwQ3bkGXxkmLaBHKNFh3qAFuar1IiqDb3XV+rYDxwinrZx59cJEJiDXdrVwPPJZS026wqmFwkChdFZQCRiugEaRihDEI4vaPpMXSNPVKm2o0DqWNriqlInKlURAoZ2panVfBbn37mOZTaB3NOHGGxHWjaV69fI7D+k6R83p/W+3fC0E8FQl/aitgzk+ibe4ibR4hp2wqK3K8b46J2oQiHg6IkC//LX3p/Qvh//L4o/LwXt3/zLrxCGCssWXLtcpKcvTs2IsTFb2k4GDQSObdPoyOoEtu7eeYCDtqAp1bTSXCGJaM/DlWmdTEuByKW1kNBdxEkAFE3xidvgJN8pTFsSeLdBHTMJEBLqDYz+TqxjI8hUnLBUJbg4Rji9qO1SknFtkv7AQe2t6YdkdrfhpTMEZZdocZVwfEF3qL1Ab6a5FEZfB8beAYLLY4RTi8iOAta+AWQuhXI9guklpAoxhnubctARqqnap1wXGY8T1RuY0/M01muYR3bdIbagvIBgdEZ30pc3NOxtTw9GIoFSitBrYDpxLT5xdQzv3BgIsB4+qmFqaK9QFQQY+QzhzBLS91DdHeAHiDDUv2elSHB9ErVeJtnfgnl8D14up+Ftrqc5lF95VW/4Cq0k+d0PUFwZ58IXf4X9T/84XQceIqrUCcdmiUo1opVNVLmG/cwpzK423FcvE96chpiN/dBhzD4tahP6PtIwtn00EVJ7524l9WG4XewGt2a21YxFNqknyK05sE3t2be8qQ9nKfAnF5BhSLjFyRUgh7qxDg6hipVtMZGoVNX3pdhMABJNwQwv0CqqPW0amlWpE04uYnS3aqhg3N6eBMKOWIfaKpYMqS1uJhaaFgb68BTJGP65WwQ3tGiUSMSQA516ta8WNazWkDSeP4PZ344x0o//4nnC2WWcp+7ZbjhExTLRaql5+EvM3jaQEn9sDiOd0MVXGCJWNpB97SjDbNpazRDOLpEcaifq6UBIiTs6tw3TVDVXf9+4o5/Num4wbHkEikxyJ1lKJ7D2DeDs7iZyHMLZJfwrk6RxEdJgc66IaMvhPHECYjbhzRldJKMn3kSRbkxYpuaB9bcTXJvCbArVNL74CiIZJ/bRBwmvTuCdvbn9bIhkDOu+g5h97dtbhwxDwmoDeXWM+uw6qlrHtA2EihD3HsIY6KTx9TcQqQTW3n4tIDU2p/eu2zLNREuCoLcL4+iIviZK+zHq4m8T/63runkURrq5ZRgaCrwlEBW3dUG0lUDGbIz2vF5rShH7yAP6rYIA9+untbDWM/cgYs5OM0QpvJcuEE4s6EJwVw/u3DyMLzenaDuKyNvXJJfSfPeRPoRp6vsvpW4Umtr2QrguYamO0ZJFRgHMLhGmU4jWPCqMiDZKGprahK8HU4t4L11ANm09ME3cr7ymn5Hb9+3m5y4M5FifK+00LS1DQ7WPDmGmUsxdehHDMunc96Bex9NLhItrWqRseklP1PJplOdrpIohsXb3IId7CGeWUGGkGwGLa6hilbZH99Ho7SEUBlnhUioFRFvqwOduQhhpzmpLhuD8KMHlcT0tv/8g4fIG/tmbyHSc9L0jlF65jirXtLCTFLrgs0y9Hnta9XXIJIk9cw/m9Cyl126CH9CIysSyrU3FY4lMx+hIw8JsTTcogmDHWs2QyEyCaKNMPG5SrwUIU2I9dQ/mVrHvB9gLS/hXJ6kv7iAWYimLRl37YoowxNjTr1WJhcC/OEpwaXynWjIN2g90EPMbTI+WcD5wAtlRIJhexn/t0k4DQgpdSEipOcKOiTez8g7LN5FLYfe1oRZWCFMpvS+9cUXbq5zapxtLTZqJ8gK9hzcV5YPJBdqp0d0VI5m0iCcMymWPWzfKrC43SKVNKuUAYYqmSKHQDU/H1k3Opr2XbCJ1wskFrWR9ch+xhWlmL1yh7bu+i+rcJKd//58Q4KOaHfYnf/CnsAbuI9isEtya0c1ZL7hjTyMRQzQbK0rplEEAliXvtI1KOE07LK2mTRih6i75o/2UFsuEK0VEwtFoKz9EtuU0bX518x3Pqr6oILIpZC6lz8vqDvpL5DO6+fF2egFATvN/hW1hdBQQUYQKFeHUop78pmNElg3JGGptE6ou2BbOM/dA3dO0qZszGu7uWPrsLVb1PtzXjjHYhWzL6uY4ENVcLBVQO3OT/e2KH/2r+7hJgf96BvqdOovPX2X95tL2x0v2FZD5NOXLM3dQsEQ6gdHThuxuxejIYQgQL7xB55E+lhoWrhsSlerYpSK1pRLK9cn0ZKkqExWxI/oGOzleU7iMredri2omBYW83sPWV/VeqVA0ZJXMw/dgDg3q8zqKCC+NospV5O5+PVCREjxf855vzeqC2jS3aVSJvhZiymd9toQTk7iNiNaOOJ/5whN3v8/vcbxf0L4f70n8eShoJ8fL/MSnXgL0c93Tl8TzI5bmb4Oscdf6U/+sPY95fA/h1Qk98ewo4Dx5UkNgnnuTaLWI88QJZGdBQ3MWVnDP3EBVNY9PAUZvO8ZAB/7oDN7CIqawkKLpQ9bkQ941EjbGYLeGet0GDTH3D2Dfd5BgbA4VRXpqZFtEZV2AKdfD3N27Y5Fy7gbBxXFEwkGkEoiWjJa/T8YJr08RleuY+wc0zDYIQQqCmzOaa6oijP5O7ON7dAFx5gYiGUPEbMx9g4RLa4QXR6mvLGEm0jgHdmlomWVuG69vhaq7hAuryL52hLnFlYmQ8nbRnBAQeN86S7iyqadOxQrWsRGso9qXLphdIZxbxb7/IKpax7+sE59wenk7WdgSOxKOrfm6+weJSmVkOoV/aUzL/Sec7UTa2NPHeOUt3OoGSzde59CxT5FfiYECO5/Aq/mgFNbBYcyRXtzXL2PuHdD8y4U1ItfHPDKIkdLwWrVe0hYUW56EDQ/RPGyjal2LtCyuEUVavEWtbOjmQN1DtGQwh7p1Aj82g1/8DvDardia/kfRtjAHlonR24ZIaUl/2ZK9469s8ZSC69PIbAr75F4tDvP6Fa002prFvu8ARmuOcGVDF5WlGuHSOtbefl0Qza/qpDzuEJWrhKNz2zArkUuhpMDsaYMgwtlYo7pehyDEeeIEIpMiXN1EJmJNPvcy4cIasQ/eh7AMgpfOE2xW9bVryRL78P13TLrvFrcrYoaVOv6Wd+jWI5UwqNVCzTOs1EEpkoU4j//gPl57bpb1WyuIuEN+MM8nnsjwgWd66OiM88ItxS/9lw2SRohKxMjFFJOffVNPYe47gFreBEMgW3OEkwu6Q96Eecm+dszOArKrFVnIaD7311/j5PEsp8+WtCerIfWEaFcPxkCnTgIjhUDRPjNOazzkQj1LcGkcYRrEPvIA3umrICUiGSe4MYWIO1j3HYRKHf/axB32LjgWTnsWv+5jP35CN6Gqda1Yu7imhc76O7AfPoL77JvITAIRBhiHdmkrmZVN3RxzfShkMPIppGMTrpcIR2exjo0QrZdxXziH84GTyJYM4cQCwfSSho8XK5pndrif+JF9CMvEFEqLTAuhLZJmlpriaRaqUiNaKaI2SttryRjqQna1odaKhHPLRItryHwGY6hLi4o5lha4Qwu9qOazEI7Pa6/Mqgubd04jbg/RRIRv5ayxo8OI/UNg2+T9MgfSNV79zGW8rMB49BGK41coTl5n/PJXKHSPcODBv4IzoBtv4cIqYbkGdQ9/YREVRsTvPYLRlgPAP3Mdrk/S2hlntb0H6/Bu3RCJIoJrU3p/aO75dncBeXK/hpqOz9J45TIdR3poHD+EWNug8q0LBGVdPORbHcLBHsqjy9qipi2PLKQxetq2aRXBzRktjGQIDMvAd4M7DkA3rCCFQeHjj+MvbOKOzt0xITP29Gk12bhDslpi7etn9RoOI8yUQ8tD+yh39RCfnWXtxWvg+TgPHmTwvgHaGxuMfvUKC5M7Nnc7NyDQBXMqs40WMvf1E1VqhBfHNVTcNHGeOoUsZBCGpC0eMuguY5UrHNmbYPeeNL/wG2tU+/s09cULEDEb262jGh6+beNdGNOwdS9ASoFpCvxCFuexE6haA5lL6aaO5283UKJyjajWIByd00XkFl/53RKHmI3R26ah7FIiQdsS2aY+07bOBCk1nWZvP1GtQbRa1O/vWNQ+9wJ4HumWBO2dIRNj6+QSBf7+Pz3JhUaeL1zSzYLw5gzRegkRtwmuTUEYEYsZuO473RW2wAzvkMa4fdS6BZtPxDRlQeq9yexpRebSRGtFelem6Iz5nLlQxO/o0CKJTd/dqFzDyCWJ7e0lMG2iSvOMrrnb181yTPxGgGjJ7DRgFbogty2Eaei8pi2PbYIsV7TVj2MjlNIK9Evr+h625Whpi1NK57WSMVqpOJxa1Pe5XNNc0WyCjoOdrLomIpvSNAfLwMwlUTGHxPIKa9+8AKbBwEPDHBiweeOmz/qVWVTTMkiOaGpXtFHWe8rU0nbjQ8Qdva/WdpBCMhlD5DPke7P83R9q4+vTDi//y29hpmyGPnkvM+tiu5mlXE9rOdQaTf0CELkMZOKohXVdgJoGsqNAotPk+sVXGSzsxXryMQ37LlVpfOM01LUPPFLo4Ubd3eGTt+VQvq+ttXyNxJLDXZpnvlHRopHrJfJ72vjs797zLov7vY33C9r34z2JPw8F7f/3p9/k9KsrGIbO9+ORpMaf7It6txCZJLGPPQxo8Rf/hfPYjx9HtufwXr6koaD7BhAJh2i1iPvV1zD2DjQNx5sdZNNAdLVovsd6EUwLSpU74TOmJuoThERLG5gxXRSFjYB4fws8fg9+sYhYKmn/0O7W7UmTsPThq0wD+/AurbjaTOy2/PpUqH+vargYve1gmUTTS1iLi9RDQ/Pzbp9MmwYiGdOJajali9K2HCC2C4yoUiMcmye4NQNS4nzwXhCC4PI49r0HcF+5qA/F5qR1B8baLEAR2wIh3sw84fMXsB8/rqFDZ6/RuDQJQhBPGkRODF+aOE+f0gqBjkUwOofpe6h8GrJphOshYhbKMLSQS8PTKqrlCi3xkPlLWr24yfrTn8kyNK/R9xGhIkwYOMf2E7x5HRGzMDsLmPccIFzeQMZsgqlFguvTOI8dxb8yDg/sxTAtrER6h4fa7LpGC2u4z59B5tN6wgeoUhXRnm8WuQ2i6UXSfpWNW8tEDV/7kpom0czSdgfX3NePeWo/MopQ1Rretel33C/hWCjPp/vRPazUtN+sc+ka3rGDIASmVIy0CzZqgpXqFrJZC5Go9aJWZlUKwxBE6rZ2i1I6mZBa7OlUfB3DNjhdymq+YRQRLW9oHq5p4H3rrLY+aNrhEIZ09yawDJgli/3QYb1+Gi4Koe1nmk0eFYY6uWvJ6v9GIZtm9KL5c2EYzTUUae7cyibh5DzW8T2IVILGF15ksDtGvmBzzwNt1Oshzz87z9zMlmCO0BDSWuMO3pjOiHQCkM5YpNqTrCcL9PfG+djjWf7dZ1ZxL4whEo4uvpO68SFUiBIGanKB+osXEOkEzr5exP7h7YQiFpOoYoXymTGitZLmHLZkdmxhltbBsRGG5m86HziBbC/o5GxmiXB2We9BkcJ77bIu1pvNC339ImQ6ibmnF1rzRJfHiCbmCb0QYUrM4W6MoyOoINTWFHOrxDqz+DUP+3seuwO+C5DeWMF/6zpeqY7rRvjezt5pJB1UNg1+oEVjmsq6GBJZyGIdHiKcWcY9ex2hdp5vIQXxgTYiw8SdWgGhwDCIPX2KerRJdX6Clu5jGq0QhNpubFQnlTiW5miuFhG2pWHCa02hvXxaT9ZMA2ugS3Ph444uRK5PE1wa0xSR8G0cfcvUXMpjI1owa0sxWLCt/i07C3rPMyQkHFx3nUw6Q1fGIbpykRcvXcZsbyERayFdiiOqOqkNIo8zq58nbbVxoOtDej+uuxo+vjVpbnjIlgzGnn5kR14/z65PTPhU5orNiVWkFUilRKbiGB15ku1pNl+6utM4MdBUGSmwHz+B2d+x3VSMyjWC8TnMwKdxXQvCOMOdKMfRcg3FCuHSOumUyWbgUatvkuvZQ9KrMvToLm7VEvizq5pPm4zjffssIpUgdmqPViJf3tSNrUJW+y/fmsF//coda6lzfxsVZVG5Po9ozUGtvp38K70DvOPP25GKa2G3YyOIdIJgcYWF15/DcuL0PvAkYSGHrDcInnuD0I8Q9x6EWgNrb7/eP5TCfekC0fg8sqcVOx3HW9zQ63ZrPfe0YhzZjcgnSVy6zsalOT0c6+tAtGa1ZkUYYezuQbYXMPo7NEx+o4KSAooV/PEFKFW194xSGrUSdzRqJelgDvdgJONIoTjSLVgqw0plxz2sudGCAmN1jac7y1x4cZaxW2Va22JIA9Zdg+7ve5Bk2qLSUKzVBI6rp+/1c6P6rNz6TobYhtbeUbNKMDMJomwGY7ibTzxTYOHNKd58ZZH6Wu0O0UR7dzfW8b384CMOq5fnePacR+DEsLMxotYChoBT/YpeWeWNP77J6PllXedbpt6jY7Z2fzg0iFGuEyxvaE2DYgVlGE2fXJNoYYVkxqZaqaN8ubMCbv/gTYqXSDg4Q50ElQZhua4L4jDaeb7R983oaiHarGj0UrkK5XdpDm9NSGM2AoVq7FAOcr1Z8qeGmPj6VWQ2hfPEST0RL5YJxuaRI334Z28gM6kdHnk2qX3YDYNY6FIPhdZYuDm7/V2EIRFtOc1v7ioQ5jJNEcmIcHGdaH6FcGlDI1iU0orwmZTWjzAk1v5BrdAuBOrWFD98IuS3//0NwhBsR+LdPo23TEQ+heO73HtvgRe/Pkc2b1PcuFOtXfa2ER/u5CP3xPhrn2y7+7V6j+P9gvb9eE/iz3JBe/q1FX7tl6/sJK/vEiKbRNU9XXDGbOwHDmL2tBE/e5HNDY/BbMB6KWKzJnCeOA4KgqkFwpszGqYTc7SwjR9g3X9QWxukE3rqVKmj1otEXohsSYMbEC6ubYuayI4C5v4BZHsB99WLqPk1rJN7UA0f1XB1NzKdaCrHOloReLBL13+OQ3V2HG9qlpRVwOhp06IoTXGQqFglGJ3Fn11ADLaS7GqnMbbSLFiyGD3t2ji85urD1zAIb00TXBzXPLqBDsLROS1UlEnqLmTDw9jVjXVsj+78NTy801cQYaSnUINd2vonUijXw/3mGaxjuzFac9Q/8w1iH3sYkUsRhT6G5WDLENsyqHmKaHqR+s05Yo8cRYUR9VfPE3/8JNIwicKIYMt0fstOYncv5r5+ZDZFslGmKh0UQiuVhhHqNiN5lMKYntP2Rp2tGqa9sEpw+SbB/Cbi9h1QCC18FXdQZT3BQ+r0ytzdg/XgEfbPXSVYK3Hx/AZGRx7rkePUGutYsSSN8jq9A4OU3kZ7UUqhZhZpfOs8dksa54ED+MIkuDWrOYK9bZiDXahaA++Nq3dMFZFCw5oGujD723UH+7bvJjwP9xtvYdcq9A8m8TxFZ1eCn/mfT/KXfjeicWmC7GAryc4Mv/JJgaPzdwB+7o/gwqtzWMM9gMLwfQLD3LYOArQ9zdI6KgiRmaT2RVTQl/SYWYOHj8U50Gfyn17w8VeKRDWXaGaJYGpJC9y4ddxFDT+OimXSF6/g3XuUIJOhJQGb2m0GN9hiGCpipqIRaHGpU5kyx2KbrCULvLScZLWqX5O0BZ+6RyPQzk5FXF/UhZEKI5LTk5xo9bj0+iILczUSSd0UqteahWrapFYL7xCJE1JojZ3gTzgShcDc04exp09PEjJJbbFUqpJdWWD19VGGDraweOyUtk2q1nEuXGX4RCezRp6qGd+GtOpnxcUhxI8nCVeLeG9dQ5gG5t4BLQzTFJMShoEKQoRp4L51nXB+VdtPLW0QzS5jpRwKg3mqJV8rYuZSehprmwTnb2neZKmyPVUShuCpD/fw3JdmsXZ3Y+0b4On7Ujx7FU7KJRYuzjN2aZV8i0MsZrC22sBzI6QB6YxNaNvUQkmtukDP8eNUfEk6qrM+tamF0rZg9jGT5foEjx44SN9AkovnN1he1A9ILGESxGNYzzxAtF5i+Stf5uLKl0nFE9xz5AnE0NNYrVmCUhUhJcHEwo7q7x33hDunZbap1WlNifJCbYFUve2hNA0tBCQEamYJ6+Q+SMYI3ryGyCRxnrlX39ONMsH15sRU6QTR7OvQCsjJGGqjTLRWxNw/uI1GCVc3aZy+hFivUOwI8XMGR9sHKF9epLTS/AzpBLGnT4E08F6/ootoX4tUWQMdhK6Gt6omL1wUMhi9bdoea6OkxXuaVitmew6zkKYxvghKEf/ACURHC+bSCvmggpWNs2mlqcVSujGwUcY4MMSpfTHmN2GxObROmhG7GwuUrs5yeUbD7I21kqY5OBbOY8e13oCKSLhViuuuVoTfpp14WNUqmcV5ls7P4sQk3/WxPuZmq7z64vJ2TeI4GvoqpSCXt/nwpxz+4T/5I5458QyzUy7lxiaW4RAzUiA0RUfd3oBo3mvVLPyEEMi4RhcpgHwaihXsew5oHbtag+j6FNFtsHaRSSLbcpj7B/CvTmg+Y83dVn6/Kz/TMpFdLdqaLBknGJ3BbMtDPq1V52/NovwAo6cNkU2hVKQ9Q2dWCCbmoeEhEjHie3s4+EAPV2oppIAHhuB7jsJ/eRPONZ3+tp5zgGxccTBZZWa6xrSf0L87CImW10l359jTa3FhVpG5dYuFV0exT+zhiWNxrn5jlNb2OPV4krmygR9EODEDN5tDdLZo6gvw3YfgJx7aqhsVb7yyzK/98lWWlxoc+/h+JlsGEFHE5otXdcP69nAskn0tqJ4OVFcbImYTNVz8SxOE1yb0dUwnMPJpRCqhc4t8mqhSw3v50jv8cIPIAwSGMHXB157TasrS0BoSQYDIJvGuTBDLxBEPHiWaWyXyAwhD/LduvON33r5uRDKu6T2FLFZLiiiR0MJJ16f0udqaQS1uaOGxfApzz4BuDoKm2wjdeA3GZjEcG/PUPoJbs/jXJrGP7sK/MIr9yDFkPvMOD92o2sA/cwOZT2na1VoJe26eesmFZJzYdz+sG98vnIMwQtoGvUe6KA8PU10qaVujuRVNKTENZCENQuqG3l38cXt3Zfj+nzrJ7z7fYP30GGq9pNe3Y+n70txDt55H6559WhQLyCcFv/Ojd7+M73W8X9C+H+9J/FksaJVS/Oav3+Azvzu+/f8kYCFx3z6Z3TIRr7saOvjAQcz+Tp3IrJcI5lcwutowWjKoMESpCCEk/oUxgkujiHwGmdbJvXVCG3rjBdrTdGl9uyD1z90gu77M0H193Aqz1NbrBJfHdTHp3UV8JO4gkzEtvb+VhP0pLHuQQsMWOwqoVAyjv0MfWuUKIpHQn29L8t7UPM+oXNNdwZhNtKz5QeHMkoakCIH1yFHMwU6C6SX8Vy9pafpn7iPaLOM+96b2cO1qwfnASTANwkodKlWC09eINivEPv4I/sUxLbyhlJ5KODbpnizO8T1UzTj3DYLp1vn2NxcJVzexj+0hciTuygrWcoNgdAZqrlZG9kPNTfXuYmMB2+qpRmcB2VHQYkqWSU+wwe7qLK9eqFFN55G72jEzOcLAQ7gharOixXL8EKo1bTXRaBB0JEgc3IvhxDXkdnGVxjfPvuNtRTZJIx7QcuQwif4WSkVfd1JdT0NMF9aIZpY1x7RXH/x4AVG1TpyA3qxifKKKX/W0R9y9B7SwSs3VTZCpRa2Ya0is1gyDXRZVK87KeoA8MITMpnC/+RY5r8L6msv/8qv3ckW18qVL8ExPmT+eSpM6f5F/8XPD9A+mmFiF33kD3rpU0R6oLVkEEVFzkhbDpyMeMlez8JUkuDaJf/bGHd57IpvEOrxLi5CUqgTXJok2mhMPQ2Lv6yN2ZBeBE9OT20YD1dOhGwRCkLAVv/XDuqD99T/a5MxLC7R3JVjvHQDEdl55qBv+4r2wr0P/91tT8G++pf/c8OGH74W/cEwvh889t8Z/+tUrBOsVZFuO7o8dJ764zOLpCarrdVKtcf7lL59keFeajfUG//pfXObVl5YpHOxh/cYSBAG2Y+hJZDpBoivHSDusT28yn2zTDazxWYyuNg35d31dVOztx77/EP7VSfzTV7GP7sI8tgdjeZWgvRVcX9/zJg/UNODBYfjR+wTT6/BPv6oQAu5jjhdGIVpYR7bn9LPcTDxEMq5/BxAtbRDcnEY1PG0TJSWqXEeakoGDrTz2RAeVWsTXvjyL29mp4c65lH6OXzz/nfeRre3ElETN0VG2Jcb9T/bS0uLwlf96i82G1BPXap1QBWQKgsF79jJGgYLpYtsGizWDyPVQtoX0dbEhCxmEUpi1Gp5pEW1UMPvaacmZ/Mr3C/AD3jh/hc995XV++/e/xc/85CdZuNLJUs8Q5nAPu9YnKWfzzE3XcJaWiTUqrM2UdiCUGa1arjYqO4IrgEw4UMhi7OrWa/jyKP6mbnYmdncS1Dy8+XXMmMmpHz1FZFi4xSoT6xK/ow1Zq1I+dwWLGLLZPDQtSSQkW6JlnzoZcubcPGdXU1ipDOFmGbM1r/fYZAyCUKM7knHklpVMwyWYX0Mtb4ApUTWXaHFNT2TRMEaFQngBxnC3VohPaZ0BVarqZL5U1XSGfBqzKZIVlyHVaqi58bf5k0oBphR4zUuTjcNPfwCSDvzWq3B1Uau7ur7iyhd/mUMf/tsMLY9zkxaM1izh8gaqXMMc7tbN3ckF/OtT2EdHtlVVjUJac5SlIhMTxCyFubzK3LevU1rYgXwPH8xTONjL6T++hGwec4mkSTpjIZ06p2++iujt5sD+D1GxLIwahLemiIr1O87NCIVQ8HY7MYTA2N2D0ZYjKteIqQC/RzcNw8kFPSWPFMZIr6aveAGNZ1+D9erbfg+ImE3u0YP47W34K0WEYyPzabxLY1B3tUJ7Pn0H79HQ5TQhWgU9WlwnGJ8nmlpA+SF2IUXrvg7WkgWM9hyxuMn376nyn//9dcR9hwhNi4z0qRkOQaS/W9KMKE2tEV68RbC0CQKyeZuyjINp0JaIcDJx5hs2yaBOcXzljuJcWAaiRXvbiiAkXC8Sc+uk44KOzjgDQykOHM4zsjfDN742x2c/PUFrf5ZiTdFYKZN88ABqsIe0E1GaL+HPrhLOrWxrhxiZBMq271BZNk1BImlSqq9T9Fb54U88yle+MEPPYIbHnuigszPG7r1ZPvu5C3zmMxc5uHeQAx86xMubeaxYWu+vUvcZwggiILW0QCWRRQYBhzZGOXRfJy943SyUoHNzgdK5CZYnNXJDpuOQTSMTjuZMl2/LqSzNJZW9bbpJFYaoSOnzam6JsFglNDTv3Nw3oJvhyxsEN6a1G0E2Rf0PX9jx8VX6/eRwD/bxPUSVGiIRhzBABCHEY4DiI4N1fvRRh0+/6fHrn36ZrpEThKFk/Iu/ywfuy/ETf+dH+I+vGiyUIGyUKJTPkqrd5MsvjZNrP05rYjeWD+HihraoS8aQLRntdhF39H0wzO3GKSidLkXRNrIpKtdQE3PE5hcoLVd10yjhYHS30ZcO+I1fP/HOQ+G/Qbxf0L4f70n8WSxo/9UvXuSrX5z9k19oGhjZJOFaid6+BLMzNWgqfBqtWYzuNmQ2qZPJMEKhCM7dJCpWiRbXiVSIFAayrx3ZktGCNp72JxSZBNbBYVTDI1xcw9zTp6XcN8sYPe00Pn/bBtgMkdPquSRjSHtHfTCq1onWSjudY6kTKLtSpjOjmA7i+IurpPwqFdfCjkLUZhXfj3BVjcR+bR8wO3ua2sY8ewYfBRJaFGh6ccf+4m4Fs2lgSqUVEQ/swjQUoWWjAPeFC0RTC5hHd2EMdOnkanGNcHEd68AQsrOAKlUJ5zRsBs/XBfzbyDuiLY99ah8ik8A7fVXzlPNpzU1d2kBYBsZQN8aePl2cbk22gpDU+jJuNcCTJvs7oRZKxkfLxIublGfW9GSGEJEGa9deEr0FvFz+XXmYasuSZZtopKezlbU5Epl2pGViqIj02BiLr42R//Bxqk6GaHWTcH6NcE771crWnFYq3gopkYU0Qikt+OQGuotsmk0xIQVBSLI1QdTZRtTf9Q7op1IKVakTXJ/S9hUbZYRlIPs6dHJSrREWNSLAsA2Sg+3Ukmns1gxhJoUtItwvvYpfadD26H6K3VpZ0js/qrnJt71PcHWSYHSWzr4Mi1cX2fU9x1nNttORgac6K3zupRolLGjNbwuJiKbCrnI9zY9uZh+G5xIlk03xG7kzeWh41L/0CtTqmsPmKeIpm0Y6xdF7OzD3DXB1Sd4xLGlJwt97Cg50wc0l+EdfgowDyxUYaYOffQY60lCuBPzMP59gLtG+zRvWBYLa5saZy6tUz2nYb2tbjNWVBh1P7Gdtoaph5J1Z9nz3EeZI4/rQloblsuLB1Drf+tos1sIyjWozqRZoYbGHj2D2dRC5noZ5Lq3jvXmNRNwgHBkgP9KBiBT1szcRs0uUKiFRJqVh/9kk0ZT2qjbackSlKuHEvBY3AYjZxD/+CNF6Cf/SOPbDRzQapLluo6UNgtllwrF57d96W6SH2kg8fpRSYBAubmgLpjAknFkmOHOjCXsXRMUqhiHItcbZ8A1kOqltgdpyiGxqx3Kl4WImLPriHi3Xr/FHz76MDJNkrY7t51NkU7q51teGbPovIwVZ4bE+vYkx0KmtU/wAA0VoWezrMvAjECg6HY9LL36Fl87f4CM/9lMslC0ar15mSJb4e//oCHN+jF9/CaqRRXd9mbQRMBcmCb2I2kYNhnppvHCO2PIyvX1JImkwNV7WvD0Be/dnmZ6uUavoe2gUUsiRXsyRgTv2BxWE2DLCw7jzmYwUXamADd8iCN8OGd1+mG5LKN/2oyDQha6UyGxKi1W9clFDVJuNItmWw/36G2BZxJ8+BTEb/+okyrYwetuJFldBGphDXW8r5hRRsYbMJkmYER/cE3Hh0iZjoW7uITRKw20OuVOO1n8C6MzAUhnanBqf/v/9VX7q5/8x19zdBKE+j/w3rxGisAa7CK5N6eZnczpkP3QEY7gH/+Io0UYJa1c30YYWL1KVup4y7+3DVgGNiWXsx47jfv0NVBAQ+8ApYoUkH+h3+bEnE1R9wT/8QshSxSD0GwRuHSeRRnkR98TX+akfbuUb31ziP39hhUZfn0ZauS5cmcCvusjWnPYHb8+j1ksYuRSmKXi4z+fFmyGBHcMMA6LRWXzTwhjsovGNN1FLGxiDXdqGpVTCXa9qRfl4TOtVlKs4uQSuum2NqKZ2gWw2eZpK/ihtYZaTLj3ZiIkVQdXQ9k/RWgn/yoS2v9marjXPd5FOoDyP9kf2Uu7ogUqNjtoq/vQKq9NFIj/AkgI/amqV+VrwT8QdcGwt2iSARAxzsEvz2Jc3sLoKqJYc0XoJtbJBOmnQMtzCbJikKx0xYNeZGi8zPambkoUWB8eRLMzXQQiyHzyJ39nO3g74hY/odVNtKH7hf69wfcMiuD6NKlaQrsuphzrYOxjjrW9Ocfm8RhuFSi84Q5h87w8O8ZN/cy8vvXmD//S5V1maX+Dl05f58Mc+RuzoD1Fu7Agpwo6QpmwyAbaANZkY1Lyd5+8OoIbrk1hfpTSxQlB1tX9rFCEqNQqGRzUQuLWAUEgtBHqXKafsbdPWdrYWIVTVOlZ7HjpaAIVtCNqsGssX5yhemMG+9wDmQCcqipi78C2uP/tbpPI97P/AD5IdPABmbHtfcAzF+soiwjCIp1vpsZfJRwv8yi/9Kz78+BEUgm+8McFDz3wU1XYMM1nAUTUe2pfk9RkHP4SkpSjW1LZnrtDkHyKlKUD4gaawgG6gRZE+g7fWmpQoz6fx5nVEECAdm+DWDPGEyRefe+que9d7He8XtO/HexJ/1gra//CrV/nsf5n8073YkIDQXXwpd+x3mh53xGzMg0N6ApnP4H7t9TumU8C2sqDIpnAeO4a83essirRwwMIq0pAYewdACPyzNzWXC8hkLWrVgKi1gPPUKZCS7hwslPTnioKQ4OxNzQXp1pYbIghQfoD7Ry8QbvHZHAuRiBGUyxjNJCWIPGJJiyi0iDxtbYAhwQ8w9g1ANo2RihHNrxJcnUShUIbE3jeI2d1KWKoSbZSRy2vbkwyRTiDbcts2JjLhaIP6uob4WCO9mKf2gWnq6WST17ed5KLoSka01tYpTa0xemkFb+VtkvFxGyPhoBJxZF8bhV1p7j9Y4KVRRSMQ22IaUa2OLGjlwmBiDvwQc08/8QuXaQs2+MKZz2CEcYbb9yOjHCLIaIVXKSh7y9Rtj4EPfAzRlkc4Nt6FW4S3ZjB26eTI7O/QdhC3cX1VzUOVqygvQAUBG6s3qVU26L/vw7Qsj1O9vsrmck0bte/tw7sxDWta/MS674DmVwOG0F37PyksA3qyMFfcEVndbnQUK4STi6jJecLNCrFcnCCZJDJM8H2icn3HY05Kcl0pzEKazaUKwXIRp78Ncd8hVLlKtFzEOrIL9+WLhGNz+vAOQi2akUngfPA+nHRcI5Ui+P6T8LlzeqqzVIJIKRJ+jcbUCmE6rQ/MbEqreG7xhW5TuwXtCxycvaFFHZNNFeNKnXB2BaEish0J4h99mGJg0pKAtduYA991EH7gsMd//INVXvK77uhCH+xUrFQly2UwV9epXp/V0PStwnazTDCzjDnUrX2CJxfg6jheTVuayJ5W/Zy+dhlVd7E6cnQe7Wato0/vFyoimF3Fe+saRnsea/8gspBB1V2CsVmiIMI+untnPd+loFHVuk5kS2W82bWdovVtIVqzGP2dhDemsJ88pfnr86ukrZDSzCb+9ALxjzxIVKohbEs3gmB7whCMzWI7Bhzbpz2AL45u+xI7cUOnPqZJ16cew3QMwkjz+bYiZcN9Q3CwE86MubwyZer90tYejG0p+Mv3Q6oxyePf949oNHwSZo64lcUa6MZw4pw8eZwnHr+X01Ow1vyaUaVG7NI13FNHtcftRlnTN2wTEYZ6fcP2JKGxscA/+lCKjljI//pPLzI5XgEhiB0cwBjpI8qkdhS5pUBIiSEUH+8r4o0v8eWvzGsxsqYqb9epAQYTLjeKNpVcXhdayS11b43CiYoVVKWO0Z4Da6fB2AQPolRTQarhEt6YIt1XoGIn9BS9ec+7MrBQUlBvgBIYMZNQNtWaGx5huYadTxE6jn4uPH+bXxhOLmqIajLG0R9/iFN7HT54AP7rGwFfuWGyK+2SiyvOLMc0/LTJIVSej5FLE64VETEH6g12V+Z46gNtpFoS/MqLkqilQMxUBEiUglwCvvdIhFrZYPzMPKVYhgvxPtZnb7BHXma565Pc1fktCkEaRJ6PWi0SzC7rZvBQN95rl7ftmYx9/VhHdmuvZbFTqPhnb+BfGuPi+pf56FM/zlq6EzXQra24mqKBbXaDldVFjEQbfl3Qk474kaf1Ov+jC3BrRT/3KooQt4kLCvRx9z8+HlK8Ns+XvjzPVOewti9xPY60+6hkkoUirFYV4coG/rVpjNYs5r5BTFO847jffn6bvtiq1iDyfIxsCpTCXl2lNreBd2EM2ZLVTadMkigIkY51+28AmtchjIhKVfzzNzHa8hq63lTwjhbWNLppowSu1lRo3dXCsV02N5dgbiOiO6sY3p1hlDxrvkVXImChZgGKtBlSL7l4dR8jk0RZFoMF+BsnqnzpM2M8++VZdo1keOZHD/Jfp/LsaoWf/wj4NY/LFzf56gsbzC77mJ0FlnMdRJEiujWNvbcfWyq6Ez7CsSkHBsvlnX64YygNoJL6OYqW1mntzWClHEZv3GBp9AJ9gw/gZRTJtgFMOwYqJClquDKFIQTubaLja5MXGWp32GQA/42rGsV1z37MwS7C+VWs5RV6j/dQdDIUb2MVKKXICRc7YbNS09xUpdgu/rZf14QoS0tDsKNqHe+VS4iC1jaw79mnxbyiAKSF49WpLpUwOwtYQZlv/9bPgZPi3h/5p5hOgqUbb3D5K7/OfcdH+Ot/7VN86YtXOP/yKJuVFWJ7h2nZfYK2Xcd3NAWa+4UhdKEeEy4XvvkZ2lvzdB37IJ6yeWhYsKsNZjfhfJOGe/8QfPkydKQgGYPlElSaaGvbUBqFoWgWsqp5QXUxLYQgcn3dgGjReauqe6gwIrgyTibv8Nlf2XP3B+A9jvcL2vfjPYk/SwXtm2/M8Q/+7oU/+YW2ue1BujVZQbEDYTIksj2H7GlHJByMbIrGV17TG4FqijUMdSNbtfelCHyMQ7sRtokoV/FvTqN8LS5gDHVre4tyjeDmDDKTxBzp1YWi56Gk5gaJZjKvif9Josl5UptrVCaWcRsRziceRSZi2xtgWKoSfOkVnTw/cmRbzRjQSsKrm9p3bqXY5Pc2q6HbhE6UUkhLoAJw9udRvbv0Jh6EGAeHsQ8PY1uCnBWwPFvGmFumOr1KVKziPHkSo6tVv19zQodSukCYXca/PkXswUPb8Bq1vK5l+03NzRRN2Q+AnmRAZXYDt9Tgr35Pnltukm/c0MlEFO1MOMymZsPtm5VSerIpTAOE0HCu185zdeN53JTFQ/d/CtXWQ5DPo6IIb2EBo+QRzC+jVsrvhHubBrKnTXdYq3VtGdPThtGe1/6wC3d68N0RQmAMduLs7yVqbUE2pznRRplgcoFYfwuRE0fZloY5RYp01MDOxFiv3724zYQ1Vp+/TLi0QWu7w7FndjGb62Z60yDWLC7du1ggC6A9DYtrPrJYxiiWqC4WtRDYbWrZoqkubD92XK/TS7eIKnUSFnSlFaPzAcGKhm3ZQx3Ih46QMKCBScxUVOY2MS7eIDq6RxekF25yMFHmzOurfOi7e3g96MRrb79zSrXFq0SvQ4TQyWEU6W6x7xPMLGsPYCkQ60XoauPJIY8XpjTcNohALK8ReQGiuxUQBAtryHQCmUliRz7e4gahG2jF4IaL9+J5IiFxPnASu17jeKHGmcs1/P5uZCLWXMvhdnElbAv/4hjB9UliH7pfC92MzWkOYWtue4qnlGoK6mxoDnkzcfUu3CKcX0PELIzWHMoxiWZWwAswDw1j9rUTzq/ivnheC0ApthtqRl874fIG1qFhDTHd7r5HhKHSHrMNn+DcDUQ2hdHVQnBhlMgPtEWNY2P0d2B0txIVq3hn/w/23jpOruu8//9cGp7ZWWaSVitmsGQmmSGGJk6axMGGG3TjNP06DjiOk+bXpE2apE0aqmsHaowhZpAtWWAxrBa0zDQ8c+n8/njunZlF7QpWknveL8ta7dy5cO6Bh08DzLZebLq8HDfcUIqIKuC/tjCEkoDXr2BesQhXwIW+hIyuCBlxPnUhGVKefmkQkR2NYJoOzyWrwHL8UCTg/euBvx4GukNAWQ7w/lVhHG4ewC/+tAPtb+9AkBWg2F0Hp+SFlOPFvGV5iOoyRorKaJsoQUgX0Up3DcPI9AmrfbVQP17+xRcwz7cOV23chI0XFeFAF8MBfw1MUcrs6zq+jwmWOGxtgbHSG0GtOoCiJSV4tNWPkTiDppMSJI90I6ewAEO6Y4IBZgzWZ/mpUYzGTBh5eZn5yL6mboBpVAgo24jDYol05AIbjUJr6kS+GUXFBfMxEgU6Dg9CAKO9giuLIQlACYvgI5c4sGGJC3EV+JeXgLdagQvnATvaGFKGAJgmrl5g4KW3Qoi8uh+mXfRGAAIbF0JcWANDN5F44wDQ0YuVa/PR5CuHVlkOaWQURk4ALKVB3X4IxrEelFV5oSoujKgylIuWQ9dTUByesVEtduE2TQdGwjAlCVI4CnUkCqnEGh8OGdqRNkgFOVZxLx1MkijfT5EhBrxAUkXswCEMjzSgctMNEHoHoUvkLQVAecvRBJSlNYAsw2ckkfJ40+G3AJDrIcPL1id/C9Phx7xNt8AwBVTkAl+5EqjNJw/eXw4A/72dIUfWEdJlu9cAABYWaHjwx/fi+lv/Bq6yVWgbYciVVIykJECW4YhHsaaCodv0oW9IQ0pyQG5pw/xkPy6/tRZNyMP2RgODR3qhvbEf7iVVQF0V1LePQKwsocJUdlVkCBDjcajDUdov1+5r1tru7e/D3XcW4Fd/jaE16YHgVBAMD8KvmOhwF1Hfsupk2ChW+oJHAZ45RIp8voshuvUgBne300FOBcry+Vh7VQ0+e6mIkgBwYO8IHvjmHvR0J+DxKdDy81A8LxdlYgxHBkWkSoqRU+qHkdQQ6xpBcmcDxJQKlBVSipFdElwQwKIJmCNRCCIglhcBqgpzNAoH06F2DpHRw+uBXFMAIZADQRQRG+qGPjyIwor58PoVjOiOrLEL+I0EPJ0d2P7qH3GstxnrSm+CILrgXj4fus6o+F1tKcyUCv1AC1w5blxxdRm2dLsQTxi01jEGMS+AYFcbel48CFeBH9qCGtpmT9WhDwwD0QSJRpoB5AYg15aOMbwAgKGrMNQUHB4fWEKFGY4hFR/Fjmd+iLrzbkH5msuhCBrMhAHT40VesgPvqQO2vtaPN1/rg88nIxrVEchRsPqiXPx5+yso3PR+eIJFKM0RkdCASNJSaBUgqdG1vU4BpQFgXRVw1WKggOpO4dfbgMf30e/f7shEMfmcgEMChuPUjBfX6th1MI5oCmA+L9V8ECzZyjCBeIIWY7dzzI4U4vAIHvvH3Ilz4BmAK7ScOeFsUmhvvfo5hEOT7HFmIdaUQtmwCBiOQm/tAQQB8sJKSAVBAIBpmmQZ7xqA2d5H4bHWmicE/XBdsxEOmSF+oA2aVe1QXlQNZU19OtTIGAzBbGiDdqwHgt8D3+UrkewNQbD2Q7NPaBcLAEAeEysvDiaDORqBvr8ZRs9QZm89AA63DMXrhOF0Qvf7weIJSHWVFA4lCFSpNRQBSguRjI5A0E04g/mWwB2DORKmsEu3E5LbiURbG0Ya92I03Ipv/tPH0evKwauHGPR9LTC6BshTZZjkKdB0EjI9LsgXLYdcnE/7G1ohjxAEQNWh7jhMWxo4ZLjefTlEyVI0j3bA6BlEwboaRLy5YLoBSQTK9VEMOgJIQYYEhnwvw/IKEUf6BXSOMICZlsBLoT1qlpeSLiuMWQCpPSNIGSac3py0RRYAzM5+SJVFVNRBEGCaJjAahdk9CM/QAGKaAD2aJMPCZKFHhUGoRU60NryEob4jWLD+NpQuvYCqJ2s6WCIFcyQMxwaqJJzX047h0irUFQHNQyLyUiGsdwxgYY0bPRHg+R4/Rhx+EuwNg8L+dDGt6DPLgMIGQ6gqkaFGU+htGoIwGkXlylJ055Sm+6ddiVgWgVw3ecJs54JPNqDGVKQYVZO0lTY2HIEZitI7XVJDoeFb98HUTLDJ9goc1xZmKEbh1dUlkGtLaf9Aq6Is9hyBqywPanUlFMFEajAMsSCXcoE7BiDPLxsbzWBtRyBpGkyHVYkbgNE7BPNwK4SKIij1VXCERpHoC0MfjdK2IYoMvaULuWoYkUWLUOHWoIbj6BnQKOpCpq0M5KEhlHkMFLp1HBsWEVqxHAEzie+/W4YgCvjCt1sQCuuQq0sgluZD290Io3uQQuELghBkkXKm6ispZDmpwhgKwewaBEskYbT2QvC74bxyPVVgPdYN/VAreUyTKozOfipeE/RDqiwkD7ZDgbJyAcyhEES/B3AqtN1WYxuihzvgvHgVxKJcoHsAKC+CZOjk3UskYTR2Un58XiAdws0SKRgjEYgHm+BxAMPdETjWLYJYkg/B64Le3IV8l4ma1aXYN6DQuLCLzVnGBLvfSfsaUFwgY7RlCENto5CX1EJZWQcWjkFsbkPOeQsRMhTIIglQo4nMuBQTSZguJzxMQ5UjjpZnDiDUbUVhOBUoATdWXlSOo4Eq6JDsL6YVUGYbsRiD3kCViZlDxqjag5y4D8qqhVBW1o31+Fses/RcBCt9QMiqrCwItE3W/kb460sRq6qyPrM8sokUFeJzuyA4ZAwe2wuXLxey2w9m6HDnFGbOl7Iqpgf96SrCjDGaEyUBgtMJlh3dYV8/noQZS0IUBdqChzFoO45AP9xKe8UKoGKBLhlCSSG8l6yAyyXiqsUCntprkAJrKT/2xFZXYKJpSIQEhk1yL5775R4sWpoD5nKhYVcfxMIc5Fy5Gimnh8b7vqMQRkMwqsohrayH3k4V1OXyQlKWLOPgmPu25iLRNCGIAlL7mqEkEyhaW4Nhh5+2ud7TBONQM21P4/VA2bQMUnEezKEw9L2NMDoH4HDLMIvzIeQHkZccxWh5JcSSggnGA2alp4g53gkh2zLTISsSRetkUZeXxIM/+ja+9bnNiBReiteagGuWMMwrEPD77VQ4rjgA9ISA0gBDfwQIiBoW5qjY3RNHylkEh8SgGRnbtZhMgjW2w4QAAyKk4iDEkgIUi3FoSQ39fUma96xCiIIowBgYgVQYxPoqATvaAY+ZQmw0CVM3oe8+AkkUgYU1kKuKIWkaDJEKMiI96wmQDA2GJNuTO/1WN+BNRRHzBWk/3COt2LxMQqKiAo0hBaGkAC3t1WRwpxIYeXIbLr6hFtvCQawxu7FtxwjkgAdKbQlWe8No3NGDvt4Eyio8GOhLQDfI0CwvnUfVpC1Dmr2fOosloDd1Ql5cDRZJQFBk2nN2cBSp1/fRlkfFebQtnwBobx+1tp+xkmA1A3A7MRw/hrwaEXUFC9FRuAhSST6YbkBv7qLcbFlC6qW3IY6GgPwgFIkh2twF3Uhh7/Cz2PiJ70NyelDkV1CSJyEUB3rDgGnHT4RiMDr7Ifo9VEV4aATqziMwYilrH2AquGRChOB3w7ewHMmUCe1YNzAcgVCaB+f5yyH6vWCMIdR9FE5vEO5gMfThUQgGKOJH1WgesFKkmCBAP9wK9A5Bj6XAhkLIK3ThvR+qw/KLKiEmknjyD814+uVhKBuXQSzOo/aNJeCPjKC2zIEhby66I9Qfiv1UPyKpkdKqGcAF8wBBBF45Cly/jDy01y6laJAtzdSFeiMMqZSJ+Kt7kWrrT0cWygE3ltywBG2GH7FD7TDDcRRfsQyf26ygqWEUL+5NoasrASnPjxKfiV99pWiy5X/O4QotZ044mxTa2JCKD1//KlIwIFoFoNimJZDryimMMeChPAxrCxpBoL0P9fY+sNEIpKoSyAsq0uEZRkcfCSgmQ8GyMnz+agUOPYWvP0ULvtbQDogilBXzoR1pBRuJkjInS1RaPaWm944V/G5IdRUQS/LBhsPQD7VCKiuAvKSGwjqDVPiAJVUSKCQR2t4mGMd6IC2bB2g6XB4FuigBBUGIXkuRtARAFkkg9dxbELxuSH435I0USqod7YRjw+JM7pe1UudrEfQMJeAoK8kIxJpOW6Moyph2TStWhmlZ9wSMtjcgMCIgNRiG65LVgEDhgfqxbnhSMai1VWAOB7SDLRAkCUp9lRXibZ3TNKnolM8Ns38EZjwFgZkQ83PIcg8Ax7oQe+MAunO6UXvt30JWnOlnyPbKUJgOec6ZlbNkt40d1iVEYnC4ZKgOyxOnauQl1Q0oAoMuy5AEoDwo4P6bgUQ0hd/8sQevNQKpBmu7kKAHyup6qLIORXRCdnsBgUEIWPvO9o9ALMgBE0Voh45BcLugFAfxnx9349iQgH99OoF4Uw8WeeIY6YniWHME0tJaCjFTZGoT04TQ2QdWRlsp2SFXk3mLjOEw5VCKIpgVRioIoG0H7O1trF9mhzWBMfKsKDJYJE7GhbwAtKMd6bBco6kDRlsvCvwCPF4JbS0TQ2IFj5MqCtseX0GgfKN5ZVQoySowoW3ZC+gmpJoSOM5fAZZIIvXKbrBkCq4bLoDodcOMJ5F6cRdtveBQoCysgrysFiyWhPrmfpi9w3BcsY6qvI55x9YjWWkDgjV2KR+UlPVsb4YYicIRGgXLy0HK7QNTNQqfV2RI+QEIzISxqwFa1yCMcBzKivlQ1iyE3tYLuboEevcg9IY2sHCc9uW0ls5A0IHbvn4R/nDQidzwEELbj0IzAKMwD441C5HaegBm9yAEpwLlvCWZdu6jKtnmcJgUXo+LPLzjlCGWVKG+tAtM1eC8ZDXtZZtIwewehDkSgVRZBLGQ8mAZY9CbOuEuy4Xu8UJv7IRYUwLRoaTHDuw+ZTIwVaV9MQHANKE3d8HsHYYQ9EMuL4AQ9EEQRRT6AGNgBN0vHYYZisJzxVqgJN8eiZnxZjLM9yaR5xOws1MEFBm+wT4MvHqYCty5HBAdEpzXng8zmoA5HCYPlj3XmCZthaLqkAool1hraIfR0A7IMty3XpweG+mrWrlhFWIUBeV+tA8DI3HATGkwB0YgVxRllMCssZQc7IccM2mLjYA3vcUWGMAMHaGGvRBVEYFlK8CSKlKv7YY8r4xSB6xq2mmhX9Uo8iY3AIDBHBilvGOvK93ejDGaS9yUR8nilNenNbRDO9AMeUUdxKAf2vZDYAOjsCsYiwtrINWUUL9njLbvkWWy2YAhlTKoTQQBYjIJRVNhuF0wJQlGUofROwwWS1Akj1OBtqcRemMHHEtrIC2dn3kGK+LFjCcz83BWf9FjMSSOHMViWcP77pyPZETF97+9D+KCKoiFQeiHjlH1ZYCK162sgzS/PL1tmdHYATOhgiVVyAsqIC2thuS05mSTwRwchd7SDbmsAFJVMYzeIehtvTBHInBdsY6MhqEoxBw/BKdM+7p6XPD4ZAimiYTkwlDDDhQ1x5AI5sNx3lIqTicy5LpN9EUEaK/tgRGKQqqvogJaTgdGOxqgt+zDOn8lDh0KoWTjfITLygGPtc4aJvUz2xBtmtRXkir0Y90wh0OQasoBZsJdXQRNkq2uZqXIxJPpMaY3d0EZGIR39XzEvAEAAnKdJgpjg9j77FE4L15N255Z74JFE5AUAabXqqQ+GoW66wik8kLIdSSvmCNhCLpB6TOMAb0DYPlBKG4Fpm5C1jUYLlc6zYWlVOhtfcg1YnjfraW44vwcqHEV3/+PbuzzVdMxSZUKlh3thBjwQK6vAkskob55gPa8DXjhPH859LZeOOaVgvk8NJ+MRqDuPJKJZvK4IBTngh3rsVIVABgGxNpSONYvsUJ5WSZ6DIDS0o7wjkYyuBUEqRiinapS5kXgqkuw+7/vQ33V1XAUFIANhSAxA6LfC1WnHROEoA/elfNg5OeCaQal0SRVFPtM6NEkena2wWjuhuRxQPS6IMYTcDkERMLkSZaqiqjir5UyxQwD2taD0JuoPotQkAO5vpLy3/e3gAmg0HJRhNk1AEGWoFy8igqHvbobcCpUVEoAhNICsHgK2tsNMIfCkApzIC2qpv6iKFRUSgCYIEAEUOxUMWooiOuZdW9dFdDQB2gkNkAzAa+DcuEZY5QCc7gVTq8DhtsFxhhy+nvRf3QQMAz4Ny6CXl87eUoMY/DFw3joyzkTPjsTcIWWMyecTQotYwxbftyLgnoXWLkb//CaDFGRkdqyjzygDBB8TuhvHYZQVQRBkqjqrFOB4/zlkMqpaqm6uwGOC1ZCKslLF3gwB0dRUujAwKgB5vWAGSaMjn7Ii6pIONjbBAAQXQrMpEZ7Jeb6IRs6HHoCYn4u9AvW4vaVBt5oYujqTNAekqEo3O+6GIwxuJMxJLx+Egh0A/K8MgSQRJg5xwhhjDGyejokQKCkfr1nCOpLOwHdgGNxFaTaMsj5ARgCKd/q9kOQNRVmTTmksokWcfu8Y7wZqgZmMsr9yRKuj217HHl5dQguXEa/MxmMnn6IPi8txNb5BMYyu7jb1zAMGG190A600EblGxZDXlQDs2cQ+rEeyIsqUWJGoDEJo4WlgGEg32VgUHfC1FKQLIUUIE/kiOUZEvuHEX/7KO3r6nVDLMmDvKCSPJImowqg1jOYQyHIr26HMb8KwsqFVq4obdiOUIQqiIpjvRTa20ehH2lLe6rtkvnyohqIQR+EHO+kRZwEQaBw7AONSB5qBxNF2i4i4IWc54OR1KA3dlIRmKXzINWUwhwYgfr6XnqHS2oB04DodVP16a4B2tw9N0BRBrJk7TNsCVmWwWH8u5zwrk3ahzPx55fhunYjBJ8bid//derBJYlQVtRBWlwNNkBbsshLa0lx1HRo+5rJO9HRDzYSGRPaDpcDjnklcFrVjmGSR0wwdNrSZigEqSQfRt8wUi/tIu+4YULMD8B1+RrA64ExEoH68tuQl9RAWVSdycM9dIzyXi3hO53bllZwAYFRjm96Y3mJiqrZnvqsF0Z/6QaUwUGkHG6IeQEY7X2QKosoHNpSYMyUhtS2A2DtfenCYc5rNkKQRCSf3AIwwFPog+v8ZYj0RaAsqoaZ0kioCtHm9VJxHik2VjEZ6AZYPEn9UdNpKyC3kzyADIAsgSWSkHv7oUpO2p9Z18gAlbXF0hjPpWX5EcbNH+P/DUwStjsJgqZBcsjQ2eTHZZ+bxZMo72/Fxe9agD/vk6AZDF5oSPWHoDmcYBKFcDtX1MFMqTCTKUgBH4yuAcoHLsnLKA4ybVdkDoUhFecCDDCOtkOsLoHXJSJXC6O7T4MZ8EOQRIiKBNMqhMIAGF2DEBwypKJMCF1ssBvS4X5I+UHIi6rBwlEIXjeSz+8AC8co3HteGWD1a3Xn4UwVJQFwXnc+xFw/tD2NMENRODYto63adIMq3w6HIeRR+KIY9Kf7GAMoXPHZtyCIAuRl86HUV5DnKGv8skQKRmMndKswmOua8yisXxDG5AAy00yHrAqpFJjVH7LfR/acbkYSEHN9VE25bxhiWQHltk7yLsf3J9twkO35NvuHwaJJMnAxAIqE7qY3kF+1DO7iCuitPRBkK0LJMMCSGgS/h3JHB0fBdBNG3zAcS2so59e6ltk/Cv3QMbB4krbD87iQfH0vXJeupv6eSMHoGiCPmG5AWVQNuTII058DkQHa9kPQjvVCKs2HNL+c9oxNaWDhKKSiPIp40A3A6UQi1A/p6FHMYwKcDhFHDoVQVOyCtyIfLUk3HMvnWW2aNqVCb+yA+sZ+Sh9YWYc1vjAqpBj+0p1DezOrGlJb98Ns76cIAq8L0vxyKItrqHgTQLsYNLYhua+F8igUCVJxPpTzl0Fv6wWGwxQxUVsGqSQP+uE2yIvJmJI2TmmGtQcbo6gu3aA13jLkjfGyG1Y4vCBQoaD0eGfwpaKISG5AktJyj6DIdB9NbdAlBY4NSyB6XDAGR0muGo1Sc0gSbSWUUskr6nKCJZJg8RRc12+C4HRQdBijqCttZwP0hnbatnD1AohuB8SczN7tbDSK5HNvpWtz2IileXBevBrayAhe/f2XUOCuwcKSK63940WqRTAu8VksyIFz83qwWBLJLftwy2fXYNsvtyO/1IML3r0Ef/5tI4YO9ZDMVpQLqSQfWkcr2GAKgmFCKCuA84IVYKEoUq/soWKOdr0VgPL+PW6qGWIX+pQlwOOCFPRCWbcEgtcFo7WXKrwHPAgM9+O6jV48+moE8RQDi6XAIlGYPcNgkuWxV2Q4L15JbZegxGDR55kwTuuLGPK9Ana0AjoDmGEi9dx2uC9aDubzAswkly5jYLoBY38z1IPHoEjA4qvq0e4vRRIS2FAYysAgTEWGVFmMKo+KH38mf8L1zgRcoeXMCWeTQgsAbZ0xSF4vPvWTUSDXDxaKQvB50nltAFknzaEwhfr53FSh1zCg7joCo6MfiCUh+D1Qls+DXFkIuN1jrmHGEhAb24BldeSx2d0IaX45xGQSHplhzaUVKKv2o3FQxL4uy3NomnBLDLogQWcCgpKGxf4YdnbJUBUXkk++AcHnor0ITQapNA/KJWsguhzWhCSAmaCtBvY1wgjHIRblAYxBXlMPqSgXgl09WKIiHXaBA7+owfv2Phzb20+hZQurIC2qpoVnfKiXriMx1AdTMuErqITROwRt5xHkeUwk162EGQhAjYYghTUq7x70Z3IfsxdOZDwSUHUqguJ2gkUTUN/cDxaJQywKwtAMyEW5UOorSRB8cz9YQiVLtAA4L1wOKUihebv+eD/WXf13QLCAzicIYKoObfdR6A3tVECnvBDmaARm5wB5qxdWQllckxbAzHgSqVd3g/WPwHHZGshVJfTcWSGL2dPh+EJGLBQl4djvgVxVDDMSIyFMzOwRykJRKGoCegEJFWY8ieSjr0EqJUGFxa39hT3OdBvpzV1wNzYj5vTR9hGMIfXcdrBInLwqpfkUYmoyqG8dBGQJjvOW0N7BgyEIkkCbugsgwYsh7a3Lfo5s1G0HIZbkUY4pY0jtPprO+xULcyAE/aRIqRrgcwOxJIyeIcovzw+SsiGJSD71Jj3bijpSPGKWcCsIMDr7oTe0w+wepCrAK+dDnlcGI0yeOTOWgBT0AbIMuaoY+rFuCsVUdagv7wLiKbhW1EJYUU+h6229MI52kLHJ74ZYVQLBMKG394KlNCh1FenwfUEQYBoG5fiZDFLAR8KH3Vcx1vttC3DZSpne3AXB7YRYmg8hEgMCXohgUFv7oG49QMOtrgKCLMKxeiFSb+xLhwM7L10NdW8T9H3NUC5dTUXGQIqe+iZ5bJULlkOeXz6pwskMk47d2wjnxmUkFDsy3mZmGBAkCUb3IMxwFIKiUD8sCELKKsYFTYfR0UehnQ4Z2s4jQGk+7Qspy7SnmQlS+EWBPIq2wmK1iRlLUOSIQvsmKyOjUGUF0rwySHk5FCWSTGUUo3GGAgbQ/GRVaNfb+6C+vhfOS1dDCPqQfOx1ur7lQRWCPsiLqiHXVYxJz0jXEOjoh/rK2+nEMam8AMr6xRQCbBU/GT92YZrQGtqQQAxJOYni+vUwR6MQgz5oDe1QFlYh9dIuGO19gCjCu6gcK1flYsdbg9CauynyQZYgCoBnfT30yjKkXtgOp88F34XLEDcoXSA7x5FZe8ZqexrBwnHIi6tJSRYEpLYegLJsHqS8wBil1IzEYXQPQZ5XmlZwTauKeOrZbVRlddUCMmgkVAh+q9L1UAjwe2nNsK7NVI22DZElyq22FV3ThDkwCjOWpJSVrD27s8PPAUAfDMFo6YIY9EFeUJluS4gimEr75gqCAOg6TEOF4Misl92v/wWRfQfRl2xG7aabUXn+9RAEAYnBPkRe2Qpf3AmYDGJxHgoKHRjoT8F97XkoZDEMxQSYft+YOYsxBmg6KbGyDKm2lPYEPdIGbU8jeQgrC+BaVgcpPwdM0ykK63ArWEKF87I1kLwuXLXQwB2rGdxOAR+9+2m0SMUoXrQRRu8Q1DcPgIVjgEOGb1EZPKvrEBVc6eub/SPQmzphtHRDqi6B46KVYEmV2t02mg6HkXx2G20tZyMIEEvzINWWUTXxZBIoyoNUVwlzaBTqq3vStSjGbLOT64f75otg9A1DzA9AkGXofcMwjrRBSKkQnQpYZUlWpWvruwwwrRDy7Pdpzy969wBYNAF5fgWVDs6KfBFBRkDtUCuYYVCVX5974nqY0mivWEWmqCdJGmtssQwzgkMZWzlc02G095GRmAHyivmQq4phNHcitauBZIWhMCmGugHZIQFuJ+TL1kJ0KFA7+5GKtkCuWwZ3oAAsmYK6qwFG4+S7Wwi5friu2kBRFs/vAIsnUVrhwdoNBcgJOvCXPTpSdfPIIGWaMNr7oLV2AwOjYHEVYAxSbSmUpTVYV6fg7VEf1hRr8DhFvHk4hcQTW4D8AOSiPAhWsUGWSFEUlGbQVkkOheSDSJyiXrLnfN2gyBDdgNE3DHMwBBaKgckSpMpCGI1dQDIFBlAaSX6OVe5ZSEcBAAAMA8mn3oA5EoNj1XyIS+aTsg9QJKAkoshL83EqriGsS2BW1IcwLuy9Oo/h3949vYFzruAKLWdOOJsU2uvu6YNUWkSTeFKF4PMAYFSU52gHee9cTgi5fohBHy0ObieV7lcUK+pFoHL6exthtPeR0lGSD7GqGEo1KT9pT184BqN3GI66UlwwX0RhQMSLDZTY77W2QWC6TjKabXm3yqgzVaP8DE2HZ6APoc4QCc75OYAkwujohWN5HU02Mm2FknpmG+UDLq+DsnxeWmgyh0OAw5EObbM9RhO8MIaZVniyFU9biDSHw2QBlAT0N+6CmDJRULEYRlIFG4nATKYgeF1QFtbQd6SMcAQrJ9AOzTF6hqHtaQAbypQ+FII+OM5bAqm0ANrhVhKsTQapugT+lVUQcwNIYly4cyJFm4AzZMLiTJPyso51UxiiIMCoyEGyXEFB3RrYYdX2BM00HUZnP1VNVXVoWw9AXl0PZcX8Me9zgtDcOQC9oQ1iYRBSaQEZDUIRaMMRyLVl0Nt6absV0dpLsqkLgstBhYHGFe1gsQRMAZAcCuV1WkKF1tkPfdvB9NZJYmEuhIIcKEtrIcgSUi+/DbN/JLNgORRI80opVK4gCDYcoX48zhubft92m+lG2jNpRuJIvbgTklWFM9sYkd1HxrRHtlfGyncVRBF6Vz+kkgJAFCANDAKHaK9XpmokzGVv0eRUKCfc+lusKAQSKhWJASAvq4WydhEk04RphUwbzV1Qtx+C6PfCuXkdWf4toYBCQxnMSBzmwCjthahpkBZWU4j7cIiqpRblUTTGcJj6Ra4/3Z/09l4wVYdSV0EhypanVxAEaK09MBra4br6PFK0HTLMgRC0Ay1U+byiCI6NSyG4HdRe8SSSj78OCAIc5y8HXAq0tw5Drq+CXE+hgdANaK09EIM+sKEwtF0NEFwOOKwK6UZbL211ZCm/kCSY7T1YmKOiMVidVnoySi95s1lKg36kLR0CxzSdlEc7r1SnYlOpF3bCjMbhvHQN5YTvPALjUOuYvqpsXAJlUQ3MpArBqUBv6oTgckKuLEpXEWbRBEVjmCZ5Pp7YQl5lrwvy0nmQaktorrW9eCOWkSnHS8KeFfIv5efANAywoTDM/mGqJhxLgI3SHsJSeWH6fdkVOlksAe1AS9orb7T20p6XToUE4XAMQsAHeXE1zfN+LxlYLNR4GDBMKL6c9PxnDoZoC6ODLWOUCRqUQjoM2XPJSrDyogkKAhggxBPQh8OQC4PpYni2N48lU9AOtUFv6QKSKpxXnwexIBPOl/bKxpO0z3BShba3EWJxPhm0RDLGsUQK+r5m6ifpFyZBmkceSLm8kPaJFQQIjLyCgseVjuAwRyIUUeJQ0tEG2tF2oGcQck0JVY1lAEAGFfWNvTBaeiBVl0BaUEHFzRij9cxW2nUD2tEOKPWVtJWdnImGAWOQTAMmY2CyguGDu+EZEeBctwRQJGiHWqHvb7aEfROuGzYBhonk41sAAfCtrYO5pA7GcBhSwAshmUT8mbew9MJKjFZWYzgGMIm8czAZ7cc5SU44ABg9Q9B2HIayuh5SRSHUbQdhHO3A/uG/QoCAled9BMqahTTOR8jQYVcbBmNIvboHbChE4cMMkKqL4dq4BEwhRUWww/ZBRnO5vRubF+gozZex480BbN86AP+FS4C6qkzor2kCfUNgwQBEWULyld0wuwYy79blgOumCyE4aByCWVu3HTxGsonHBTMSp/m0MAixpgTKktox87bR3gejcwDyompIBTmwc861I63Q9zWTR3deOQSPEyyWhNE/DEGW6R373BCLcmn7LcFEbmgQ83wp9HXF0OUthi47YIxESElzOWie6R+GFHBDuHgNRNMEg1X0TxTBonFKlxIEyyBq7YcaS0Df30IKLkCG9yW1kFfWQdtxmNI1Al5IJXmUptA/AqkkD1o4hFBfC7wVNfBvWAexuw/G7gboeXkQa8sg+twwo3EYh9vBUiqcV62HIGXWVbGsAMqGRZCCAejRKMzWfugHWqi6eNCXjsYRHAqtOYYBqa4C7tV1qCx3Q9cMDD63G2r3CDSnC+KmFZlq+qZJ4ygap3YdHIVcVwHR7UwbI7NTFsyUSsZuy3BGaUgMZs8g7V2dG4BUlk+pUgBYKAb1QBOUukqIRXlgKRXJR16h3R5WLYCyfH56DAqylN6SkCKBUtR/rBBwltJgDoUoesznhhmKojjch1/dl9nO70zCFVrOnHA2KbS3fLsdRmFVxgLZNwzt9b1pZUGaXw7HBSsynrhxlmhmmmDMhCiRtVFr7LT2axsFAMgr50PMD0D0uNObcQuOTDguYHt9JvG22JOJdWxaGI3EAb8nXWhGYgZMlytTOVM3kHpzPxWnsa4lyBLMaJwqswpC+limahCdjjEe06wbySgkJgOLxGC094EJAilP2crvuHaxz62390Fv64Ggm1BWzAeLxKF3DsB5/nIqaBOztlzxuqji6nAYUnUJCRgpjRQ6nwfyggoSslIqtO2HoXcN0IJcWgAh3w8zkoSyuIoUZJcDgttJeX0jERIc/S7IpQXkjUmpMKJxwO+E7HBn8oFNE0bfCMzuAegN7WMs5dKCSjjOXwY7t4kZZlo4HqPo6wYgSdD2N0M/2AIxNwBlZR0VDdrXDHNoFM7zV8CMJykXpmsAUCTIaxZBDHhhHOuG2TUIIegjYbOuIp0baedHaVaxFGlxDeTygnRIETMM8n4oErS3G+CIRpGIapR/l4XjwhWQ6yomKLOT/Wz/O13wKtsro2rID4gYTpKAoYiA3wVEkgyaOS6EGRTWNMY4YphIvbobZu8QHNXFqHbEEQ+nEI7oSG1YCRaKwWjrg9k7tkq0WJoPeWEVhIIciFnbnTDTBOJJCD4PjFAU2o4jMDv7oWxcSqHkAuUfGoMhiAFvZtucxk7oLV0QC4JwnL+ctlgyTPIyRuNAOA7GGIUtW3v/Gt0DZEwqyoW6/bDliarItFk0AbN7AJ7KfCSiGlJ/fYuqnFcWQXQqEIvzIIgizGSKBMWtBwBFptx1lzPTdpYVXgAgGAaYLEFv7YH6Bnl6laW1kFfUwewfgfr6Hso3FahiqOP8ZRSmmLXXJRjlz2sHW6DUV0JwOeFnSajhBFI5uZnw65QKM6VBb+qE0tUH+eoN0HXQHrfhOKS6ctr+CgzQDAguyn3XdjVACFpRLl435IVVkBdWZfqwaYIlVSSffAMAg2N1PaT55WQ8CMco1FSSyPhih1gaJlVddzvJY2idR2top3ZxOyllwOuiMPHRKBWeyQoVNqJxGI2dMAdG4bxkNZhhQG/thdneSxEuk0kzsgSxvADKqgU0b0TiNP9ZoaqwUhKYptM2I6MRijRwOWn85lDlaAbQ+9l+iDxTuQEIsgS9pRuCIkGuq4RUWwI54IXJKCukIodhqDuGgQPk1WO6DufVGyAGfOmIAL2tF4JuQK6rgDkaofxYn5sE2fwcitKRJEDVYPQMwRyNkfKt6WS8zPXDtXkDjP4RqC/tyjy31wX39ZsAh4PyLL3udEXvMXOCplMoch4VqdOOdUPbdhAwTDjOXw7RTr8xTOjHuqEsmzd2rILyq+XifBLCwzHaF1XMhCYze4uQgmDa657+zPo5O1qCqRpErzut6ButvTA6+iAvmwelJA8FYgIhuJFiAs3vipTeVzM9h2pGlsea1jXTzs/O9UM70gZ1eBByfRWcBYVj2wSgSKKAF+rOI9APtFDkwIIKSDVlEB1yRrmwoilYPJnOgYRdBT0URUVqCNHiUoThzKQtDIfp3eX4xszX0HSwwy1IHmgDJBHuv7kM2p4m6Aea031bri6GtLoeiCRg9g7CiCTARiNg4TiEwiDVK1g6L604YTiEcq8GVVLQfXgQkmV01Vq6aVsqq+8jlgSLxGFG42CaAcQSgEhFosSAl5Tp9l4Yx3og5vrBQMYauaaUKlMLIKVIltMyR1ZPg6t/AKNvt0AsyIGybD6gSBB7BmAebUOiYyj9fIIASB4HpAtWUSXoUAQs4BtzTqOzH+q2g1DDI1BEkoWkkjxINSWQa8oo3Shr/TMTKehH2uh8TgfMwRFIRXkQ/B6k3twHs7ELpoOq3EmQaf7VdQhuF8TyQoqIGApB298CMS8A16WrADtEPpmitUBVEX+7EZBllFT6UVniwMGwC5rDRfObdU+2N9yMJWF09dP62NFPkQEARRmJAqSqYiiLqsnQapITgaVUmN1DZHAJ+qE3WWkJvdR+QsADx9XnZSr3h6Iwh6kon97USdFSAK0tRXkQnAqMroF0qLZYlAtlTT2U4WE89q8LJplM5x6u0HLmhLNJof2nR4G9vXaYnQGWsgosidb+q9b+hMxkEDUVsiJCT+pItfTAsDy4SYcK/+pVYJJECoZVfImpGrRDrZRL53RA29UAX1Uu4HAgVZBPyqamW9UOTRhDIUj5OWOsxOPDPvXOPqgv7wYACF43WCRGE1JxHlxXrbdCN10UYtU3Arm6OOPtHBfiO95Dp7VY3sLSgozCm0jB6B4k62OOjzwumk4W8Re2k8fYMGH2jUAQBYilBZBqSynHKqtoiBlNUGU/pwNijhdmUiUPzMAIIArQ97cAogjnxatgplRIQT+EnEyBEcHQ4e3oQCSnAEKOF9quozCaO8nSzhhcN1xAYWyaBuZ0whwchViUC6NnCENtBxBcsQpOb3DqXMDxYdSMwegdhvbWQbDRKJy5HrDF8yHWlVOOjCVUUgGOOMxwPO0hMwdGkXruLYj5QTjOWwLB64YxOEpVbRUJjg1LkHh6KzAwQt50K99PLM2nXJxDxyh8fVE1eT8GRiG4HOSlsrxd2Yu+3tEP40AL5JV16S0d7GcyRsjbbXT2Uw5mRRGU+eVpgS/1ym4IgkD5YlY/tT31ZkqlfKimTmi7GuC8fB0ElwIWT0IqLUiHqNPFslvP+odtkJkitNyMJSB4XHBqSaiyA+ZoDOK2vai8bCG63IWo6WnCkf1DQDWFYwlOBYIsWmHSAsxwDGJLBxRZgJaXC1ZSYI1VSwhNqRSitqcRLKFCXlQFqaoYensfzPY+nH95KQZr69E+gkzus21wyn4a+zPDhNHWC7EgJ12AJe2Zb+2BtreJQkNdTkC1oj1MBm3nYQheD5xXbxi7jUl2f7PvORKnvCyHAjORhOBwgKkqBMsLKbic0PY1kVJfUQThWAdS3SOQ1y6CoEhg1hwm+jykAKRUCE4HjHAMolPJeIQmCI4AQB56ZlCYMmNWBV7LSMQSKRKsreJ4E57B8jrShJRRSoyeIegHWmhP0VwfBKeDqlo7FYiWV10/eAzariMUfuhxQiwMQlm7KKNIsUxhKmg05sS8APT2Pmi7GqgwGADIIpxXrIdYlAt9z1FoTZ0waoIIucIoX34pPbNhgoVj6TQSo7UH5mAIZq4LzhWLILgdMAZHwXpHYA6EKP/NqZCnpDQfTBAg5/og+9xT7jmabg8AelsvtFd3Q15VD0hU9V0qyoXRNQizrQdG7whgUv43FBkIx2AmVcBkkN0K5OoSCIuqIQQDMDv6oLV0Qa4shlhbBqRUmFafFez8RtOkc8gyBJdCBjZrH3OxKBdwOWAOjMB50SoIQR/UHYchROKUhuBzQ6ophbJ2IVLPbYfgdiKv1IcKKYaGI2HEIyqUJTWQl9RkisjZhhfDhDkUooJ9sURGqDYozzMdMSPY223RtlPmaBRslCJYjN5hmCMhyPMrMp4ge/7qG6FogoA3E32SrSBn9Tk7jFYRAdnUIY6MItQRgrS0Nn2fsiwBbgf0aBJ6Uyeajj4H76J61Jx/M7SmTsDpgFyRpbBaSq29bzN0A4Iiw+gfoSgCk4E5HeQZjyXIOzswQu9UFAGHDGVxDa2PWUarqfpOer5kDCyWhJlIQSoIptNCJn7XKvZoedLYM1sgLa6FnhskA4/PDSMag7i3EYZVF4MlUlRYz4p48RT5gfOWo6Q6gIAbOPRKK9RdR0lRWlwNx6r6dASHIAhAKoXkK3sgVRSlQ7lJQwXcogF/Kop+5qF3aZowDZMKzVljeuIcNKEhMu+YMQiMUWFDr5uM3lZ4OASBwvPrymlcRxOQS/IhxOIoOrgPvTklwIIqSoWRZWj7miBVFcMcCkNtaoMwSPNHyq2DJVS4/AVkwBYEmM1dMKMJKEtrKUdfFKG+sR/QdVLaC3LGGHmFRBKmwahCsyDSrg461Wcwh0LQdh+FWFEIZX4FRR7pBhm3hyOQ66kIqGDle4t5Aag7DkNv6oRYEIRUGAQDyCMsipBK8uDI88JUFBiqDkFRIFWXUAX8cRihKBmzNB1icR7M4Qj0g5bBZQlFd4ExJJ7ZCljb7gEUei0vrYVYlIvUs9uAeGrMeYVcP1Xy97lRiBh+e9+86d/pHMEVWs6ccDYptABw48/GhY12D0H0udKhhNmfQTfS4VMMVuXXkSiF2fg8lMvUO0R5SooEeX4ZoCgwBkcpJMTlgOh2wYzEoL62l6pa5vohlReRN1eRM7kRAE12jZ0QNB3S/DKIPg9YSkXi2bcg6AZNeoVBqmA6GqVKeUW5cF65DqK1LcR4BZbFEuTVs/JsbQXEHI3S87gU6DuOwAxF4bx8LYUjmibYsS4oxbkwvBO3RQAoBAgpjQQLvycdHiRIYtoLao5EoO5qgNnZj6zGhVhphWIqtOciRBFmKALR7SIvR0oFZAnG7qNAYS7k6hKYyRT0jgEolUUAGPSmLijL5sGMJUnxSmqWEiSR5d2qoiu4HGMrwlqKF3k3ZRK6shdSywMjeN0Q3c50WGW6PZMpyiuUJCoUZSu7mk65U220hZFj0/J0Xra9KTuTZbD+YRhdgzC6ByAV5VFVw6CPBP2WLhgtPZAXVZHS63VT2yK7+SgkWNvXCAdMsGULIOZYVZQNw6o0LdP7tjx1DglIJXXkhwagtHWg7dAQLcIAhW7VV1J+qyJD29cMo6sfgkOBOTAKeUEFlHWLoTe2QVlUS+0TjUP0e6nfagYgC6gtEFEcELCzDbBPnb1smEMhKuQT8EAAoIgMmgkwJkDdfRRyYyvk8kKYaxZnKoeOh1HkAIvEYcRSlBNmhV2lPY2xJPSGdhgtXSRYOB2klOb4aD9dRYSygXKLdWZ5MRMp2m83K0/RuiBEMJiYqKSbg6MkAPUMQdvXTMIDKGzeddUGq0ot3fMYoXAKmGnC6B6CunU/pKI8OC9ZNe7RJwq1tjfcYWowY0loHi8Z3Z58A2AMzgI/zCXzKMQ9K6JCEhnMUBzacBhCzyB03YSyoo76mqrBCMchOB0Q/e4x1zQTlAOrD4ch+d2ATLmRsgjopgkzlIAQ8Fjhywx6UwfM0Sid26lAP9ZDykpHP8SyfHiqi6DnBSHkBmB0D8Bo74eQ66M8Zys9wRgYpUiXwiAkB1WGdZoaapQoujQ3oqIT4r6jiHcMw7V+If7xg3n4+tfvh7HgPfAX16YLddnvwfaUU9EcwBwJkyfDUv7NZApm/ygVeEqoVk4rhVva3jaYDMwwMsK63dctr8pkESz2HMM0naredg/R+1MkGB39cMLA4pV5iC1ZhC4E0ucUk0loL+yALkhwXL42vXdtemwZpCx6RAPRV/dBWDoPQkEuWDSO1PbDMDv6KGqhvoo8NUfaILicUBZVW9vEMTgSCVSVKLh4iYI/7qJu63cBPX0pBGUVIcWHjBWLqtmb0STl/UkitZ2d/5z1rNNhjNJ8D0Y5/4LLCdfyGph2PYrxfd2qiTChiKBpwrTWYEikUIg5vgkpHXZ72pFPpq5DdDig7jsKs7GborQUCY6LVpGxb5KIJL2lC0bvMOR5ZZBK8mn3g1gCcnUJGQ5GomR0FqiPmOEYBEWBsqQGxsAImG5g/XwZam8IRwYAvbZy7A1a4yadx2/vuWytqaIswQsVcdFBM5M9/iWA6To0kYzlAoRMKgHGzh1mKAp1XxPYYIi2XkukyJgsU9EfsSQP8rpFkHP9WbsOCLT/MRgSB1sRRBKR8kqKZGCZSvmTMTYthWUUdAAwNAgUdQsmW/KLVVjLJdO8klAZDDssP6WCAelxx4Cx6zoDWCoF0eMmxbChHY4LlkOuLaM0lESKCjrGkzDaehHevgNu+CAqIjxBF6IDlLvqum5Tuiiinds76fxrmABY2tgDk2XkCZMKLGmHjsFo7KAtpioK4Vi7iDzXlnyZ9sK7nIBhwAzFYA6OklwZitGe5Aur4N+wACmJDAiCaYKJJMu5ZCCpI/18yed3wHnxynRYsyBQuhO5tCWobx2E2TMEsaKIjDSyBLEwSOHeAyOAIEBeUWcZTHWor+yhVA/DhLSgglJlrOdUtCT+93NjoznOFFyh5cwJZ6tCm810giZgeR0NHUKUtgSwlTgp109KoSRlwpSzQ6GylFWje5DydBMpwDTh2LAYYmFWmFz/MESvh/IT4lSxDppOQmaWNZolVdqrcGAURks3TLt4UXUJKZl2XpxuQvRmJhszHIN2oAXyggraxB4UKqm+sY/C8FwOONYvhlhWkLb+M5O8saIiwhgKQyzJJyXJ64YIE6YgUlhn9wAVZqgpBVwOuq+RCMSKQipoklTJm+x20tZI44U9ixyHiWhUg65kco3GhEIzBkFAOmzb6BmkNtR0KvTUO0x7BA9ZuZAeF5zXbiSh6Y39kKoprNfeE1JiJvLVEAYFL5jDAXtTe/ud255F0euG0TdMW6b43ICmU4Gwo52QV9ZBXjYP4rhFz4wnIXpctNXGgkpAlqjQ2OAoRJ8bYnkhhV4mU5ZiL47pi+kFVZZgpjRIkgBmhWllL+TQdfhkhihkAOP7MeXoKSJQHgQGokBMRabgRks3hRcx8tLJK+ogL6kBiyWhN3VBzPVBqiwGiydoD0wISD65haoUiwLkxdVQVi6grXmiceob1vZCgiBAcDvhEXWEdrVALCuAVJw3UTBgDKaqQwADHEo6jNZ+F+PDH6eCMZa2yAsSKRUwLKV+XBESAOlQbpZIQcrLgZDvh5QfhJifA8nrAGOCpY9ansxoHEzVScnweyhE1tqmioQZyhO3FbGpogOy3/GUz2HhYDqcLgVRNfOZINA2DefVMCRCCTT3GYhIHphJFc6ObiQPtsKUJJgJFUYqE0YvL6mGWFkCOYfmEybLkwr9U90TS6kQXU6YoxFS/pMqjLePAJXFUKqKAUWhHPugZVyxQ55jCah7m63K235o+5pREADKipw4NiIixmR43RISLg+NL1GEGY1DP9pJqQ5OBQLYmDSNqfBbxd4jSQMmE2GaBtTuHgzv2Y6O4d0oXrQB1euuh2AZerREHIm+TrhFDxwlhWAOJ+wxM0bkSWmZUEDd8op73RAETLyv8eMTpGyweIpCbK12gSBYz0Vd3QkDSWZVTk8ksaBMQuOIQn1P15EbH4EpigiJXsDnttKFM3OjPd9MeHe6bhm4MvdlhmOAIFLY6wzJ89CyMhgD7CSWZb4YqirceOoIRSLUFwF9YSCUpGNEMMoF1WhcApjQZrbx0+jsJ+OTJYhDQHp8jcejAAmNoVSIof2lI1Db+iccI3hdEPKoBobo96Co1Iuw4obuIeUNSRWJV3cBvaOU/1tRSEZKXac1uygIOCTITveY+wRordb2NUMqLYCytPa4Y9uMxKHuOAyzvQ+QJciLa+BYUw+vmUJMoqrXxlAYolOmMeBQ0rnvQpaHsyzai+FXDmF4WIVnw0KIi2vT+6rOlOyxZKY0mN2DZGQKReFYtYBqPozD9ohnPyNLqlZesgm9c4DSBgQBRjQGAYK1XtgNkDGujkl3yfa0W+kJglU4a3w7mpoOF3Q43QrihghjfBX1cd5dMKufCkJmPDIGwTSo90pkiNZiYSgePwRRhKGmaG4Qqf6DaRoQRfJkIpmC1tIDMxSDsqqOikONeZZM0UioGvS3D8NwOqnOiWnQRrGiQAZ73QA0jQw62XPwOENQ+jms9BNBECiyL+jL7Etsf4cxeAUNUZaVnw5mfSTAbSu+IOOy3tAGx8oFgP0cojju+nafFiAaOm2llZ3ywxgUXcUjn5tY/fxMwBVazpxwViq0lhTBNH2Mld2GhFgDgiyncxVZMgUYDGKePzNxhmJkqc/1p8MikVIhFeVlQqeiCcjlhVQBcMIWNSb0hnZoe45Sjo9I4aDywio61qr4CZcjU73Uso6lJ9N4AsztAovEkXzkVfLsFeRArC6lrR4icaTeOgjBoGqa0EjodmxaSoWLOvpgjkYhzy+H6HHBHImQEi0KtAdpSoe6uwFScR6UlXUQwlEYogjJ50GlPgL9WDfaDC+kskIYDe1U3XdBJVnLmQmIk4ddArZiOqH1AWuvyjFr2lQWYE2HfrSdwqBzvJCK81BUG4RsGuhNUbEovaULUnkR7clqo6owNSNrv97JYSlSxlPbDoL1j0DI88OxdhGk8kIyXljFVASHnFUF0P6ylWfFGDx6EkU+Bj0UR4/qhOHz0nYvpQUZYRmZ6AABgAwTTqeIXLeAoTi9Oo8DiKsMupkRjKcLZzsetpUZoghJFBCQDSSZiKQ+cWGrzafX0NKt0nM7lLEFo0Ceb9oeSARLajD7hmEMjMKxYj6Fx09/N+lr+WQD86UwVtcpcOf58FoT0DEChJOZo70OQDUAzcjkpqcNEUMhuL0yUi43ADH9Luz2AgCYjPaxbGiH2TtMCjEAOBSIQR+ksgJICyoguF3Wvp5SxnMiCBnvX1aBNVsBtsMt05PNLHHKtAOMAGBTLfCulcCf3gZ2tE9+vEtmuGapgD3tJlpHLCPaUAjsQCPUY/10L04FSKpU6GT5fEhFOZZgRH1JEgwYTEq303gcEtkITMascHgRxv5mpPY2Q66vhLx8HnxBGk9xzXqfjIQ9MGpruaKIlDRRIKPKgRYy8uTnQMgLQPR7IM0rI6U5pUF2OTBNpO+sSOdhwuppjAECIDEGU9dh2sWKND2d32j3FxZNgPUPQSjIpWgeywtjDoxQTqDXDWYY8LklFHpNdAwaMCQlbYS096rMHrN2pfE0pgnJ0FCohTE4akAtyLfWp+w+xOAWDDiTcUQHY1CdblLcpjASzrZ9bNI9d5p5xYwlIcgiBEmC1twJV44Hl16YhxtWSphvRe8+cxD4xZaJdbSmuzYAmIO0w4D69lGY/cNU7Xl+eXr8mSORTCiqNQYBWJWwAShWkUWD9iw2h0Iwh0JgKZ2Mb4IAeXENVUNXZPtpoYZDEBWZ9hBHZjyzpErznV0R1vbG0UHHD6cFrEJsQibHHaQTFniAPiuKnpkmREOHqMgwIEI0SPYw3ZRvDGbSvuigc+R5gKEYRbyaAGQBqMgFmgczc6nXYW2Jq096V8juW5POVZMYaSY7hi43g7mOjd3rOjts3J6LxpBlaD45Ms836zWTMXjNJJIDEWheL6VfjYuIm+l57DsBJrapSyZjTboGQvYxk7UxY5BFBp1NHP+K5dvQDEw5h0oisLgYCLqBHW1AyqB78DuBgYlby4/BqwAPfXT6Y+YKrtBy5oSzTaG96ef0t5lIQnS7YAyHrI3uMXkxHMsqn67YaBgw+0fAIgnKo3QqVChFFtPWQBaOwWjtgbywGrA26xbczrHexkQK2pE2UmLLCslz6VDADAajoQ16aw+cF67IhJOmVJiROFmc7WJP2YoEYxBGwzB6R2AyRtc2DLIAmgwAo5Co0QiEgSHoAu1PmrbIWltZsL5hmO19YD7PmGItgOV9jidJwLdD7CxljMUSEK3qe3keAbpJlvrxOCRgWRktK/u6aLPvyclafDSd2tBheZUYswRxOsYhkWIz6VkYg0sR0huLT/Y5i8RhhmKUM5wl9DpEE0lrW1mfAkRCKRh9I5A9DjC3C7CK1swGUQB8DqDAbaBlVLJCb8eewysZWFAioqFfQMLWsSTArUzeptaDUPcSp78fwboHYxYzuihMFEhlEbhiIbCkyMBz+zQcGXHAgGhF2zHKfdQ0Et5cjlm1kwAg6AFCieMLwhPvjdn/pRWG8eNkgiJh/d4cCpHXNpmCmB+kFIJxOdTp/petnFiVydPelBM0LoxnQSFQGgDeaCHBQ7WEDUUCIqnJvyMIQI6LYSRk7SWpyBASSWhDYYi6Dj2lQy4vyHhQxntPgIx3XAB8zrFGBEkAAm5gJJ5RejwKgyQAETXLiwOgMheIq5bAnbUto81kKRIwTAhRygmdbE/F04s952QEa2b9OKZ9QIqHvaen6HEiUJGLmJopwOeQANNkE/bjnUr4PRmj1JRKybh+Ouk1kaVMWsdMfR9jFR7GGIREEurBY3D39CIynITbI2HteYXwrZqHASUAiCIa+xl0ExAY4BZ0xDHRiDzZvbF4ipRPSUyHcoORh4mZDHJV0Qz7yFiv+6RetazravEIUqFBuHNLITkcoL3cs9ZZ+4wnMc7taKPsd2WmVIhOx5TvKvvexz/byTOujcb+b0bfG1M3wVbcJvG2nv1k2lQ2VEipFFKKi6IMhIn9JXt8jZHH6BcTPPhj23jythlj7J9gUBj7znNcZOjuDU/mIJgcSaStl7JlInsoHG/NtfE6gIc+MsMLnma4QsuZE842hfYT/22iJyqmJyJBFMGSKuVw5uXA7B2C3t4PYzQE1R1H9ZIlGA0UkMdA1TIFpCYRAsYXqxgPG4mAGSYl+9tegLTkTd8TDJ08Tel8JMAcjUDKC5BC63Mfd4GwhXaWUmk/Plgbbrsd6W0qAMtiLIBC0jBOOciyotrPl54uGcgrCQYmTR626FGANVXA+9YBf34beKlx4jFuBWmFbTIEMASdBnLcAiIpAUmNwdR0JOM6TJeb3t+4kDTymprpLYImnnPspE/b640LaTRti//MFmJ7m87x15mp4uh3AmU5QOsweeXGE3STcjfVqcY/kySQ0cDtAIajpEj0RjJtPf74yZ6B8iIzf0+HQwZy3aS42MdW5gI3raDF9ldvAn0R6hMmy3gKZJEWxbg6nWHjFDFDL0qW7fwEvntqmcyQoFhtltSn8rjMBJb1mNnPZQI4eU/feBwSsIR2NMPerol9TxIshygjD8H4z1xkM5zSaDUer4PGUY4LWF+VwustDsTUk3x/M/FSzeAcaY9vKAbBpVCV5Akh1ZZxaoyR4QSua3uRUykI7rHFvSYLiZ/wbIYBMxwDk+X0vsXp8GYBVBDN+o5LZqgPpFA60o03et2IFJXA7BmEWJxnKdXIbKtmkHd/OqVJtH49I+E6y+uV7fk0TJD3yrROxlgmfDbrWU1dhSBKiI32wRssgihNHrU1xmsGjDmHnct4/Fs9juFiBnPNpO8OmLItJ72GboBlrf0ng9My3mhkN59xX51sHTo3yTaEYWIbpN/pSRgfxveLmUYFpOXcmcszM8XjAB7mCi3n/xJnk0I7EoqiZOVHcNVX/5BW0JhVlMAcCkF96xCkknzIi6rGhKJOWZAl2xpnf55VHCNbaU7/G6DS/QDlZvYMUtXckjwqXGNbOq1QUDOeguhxgg2GIBTlQhAESDNUlOxrskgcZu8wbTURT0GqLoZYWQwxSxmcbEEmQZMhpWe8FRM8gFkTa7GfhPCeMAmVMXXsoU4JKM8FSvzA4V5gJDH286CbvjPekzPFg2Wsn5oBY3iUqkYrJIz4FBISY5YS53dRGKdV4HCqk2b+SnuOgOMtBKJAzyZZYV9xddrD098xGVDkJ4V2NAGEE9MrdsdTLj0KcHEd8LcbgJxxkdQmo5CiH7008b3MFEEArloMBJzAnk7g2BB19/mFQNMAPdPiUuATFwBVlhz77CHg318DPnsJfZcxyuVtGaS/+yNkWTZMoG2YfjdVW9ko4uwU4NmMl+mYTMGcCZNFEFQE6VknM2DMBkW07EtsZvd2os8wW2ZiCDmVTCYcj/9diZ8iHKYzos3qmgKQ66FxO9Wzju+r2V7eTOgxg2BaipJdGXgSj9yYdYZZW9lYIf9MpQJ9E0OUrUuBwS9oiBgyGUsZgwwDpijBHJ+POAEGp8jgSCUQkT0zNwxlGU3sfOHx9zXmORnL+ngGwrpp0v7CEGjPXjG71sLY75uJFG0RlLUXLGCPB2YVfpLglgxoTJpR3xVBRkNKe5itgpaJAsgoO4D93AEXzdPTVda229helyd4SafwJgqGQfs522J9WuHJXP94uCRAEI9nkCZRaPpneOfikgDVzMy300WSzZhpFNuMvAJMGGeGCb2jD4IiQy4rgACqCu5zAUldtFJEAJA7BXYNCSF7jhIzhcggCBDB8Ngnzw7vO1doOXPC2aTQ6roBb917cePf/wCqp3rK4wxdgyAIEMd7H7NDuLJ/bf09dT7FOI9IlnfXnixYIgWmGRRW63JMmhM1JnSFMUAU4ZAzW6iKoAWEFmNrwdT19HY35nAY2ttHoaxbCCkvZ5qWyiCACoKMJJgVucwAQZykIqyVxzNDwVoRgQVUaA9HB4CSACk2J2e1ncS7NkucVntmxC9h0vsRASwtpcc/2Dtx0S72AyvKgU3zgCIf0D4M7Gyn8NFsJWYqQVyYgeLhc5B3dHRcaK4AYF01KZZF1pDTDOBbT5OH7FQoG5JIimL2Au1WgJ+/l4R8ADjUA/zTk6TI3km1ueBxTH6+hAb815vASw1TK6t5HiDPKrpdnUtFaFqHSbnuDtExsiVAzdSbne8FosmJnsHZMv68ogDU5APLy4Dnj1BBcEUio9HSEqA7TGG7OZb33WdFGk4VSpx9DQFAgY884vZ7z36ndu8/XYu2rUTPpcJ6KplJ//c5gb9ZA0gA/ryHxth43AqN7c7RsQaTqeYwScjMzzTtM4j2sWPWDArhLgsCCwoFbG9FujDYRKae86YzXvidNHZTOkVT3LicDFWaAYwmgZePAq2DdPaT7UcehQyK/ZGx5yrwMqRUExFVHLMWjln7sr3ahklbHjkUMN0qxghkGR9tw2tmfT1Rj7pHAeYXkHF28Di5hMfDadUVUk/reGGQNQ2mYcJ0OCZUg570G1OGMZ88CwqBxgFAEQCNzS7iZzbM5HxlOWTItteqi+to7G5rpbn3VHIi8ktlELhgHvD4/oyBQLZeiT7uZBnjLJvgCZ4oe2Ybthjc0JBSAVOWx/SP8erd+KKNY34WRZgjEcDrQlBU8d+f9eJsgCu0nDnhbFJoASB38QfwT1+8A6+a1097HGMmBGGsZ/VEJ/5swUKGQam6kpTeQH1G58/2SI47NjuPY9JznKKQSfs5fA6GYq+JgbiEaGrqggM2LhlYXEJ/Hxui8NfZ4LbsColx3qwVZSQo7e5AloXx9CGLZGUFaOGxl4t5+UBEJYHNbiOHbBW+NUmBuWYpsLGWzrGnE/jDTuDIxOKcEARSlk/EoygKlgA67ruKLURjordSRKb+zXjrsUPMCGHlAWBDLQkHARctvod6gIvmA4U+4PVm8jjan+e4gf3dFIqsSKR4AhQGurAYWFUBnD+PFFTDBL75NHCkF7h9DX3/+SNAYz+1r8fy9rsU8uIbJimD4wWZkgAJKn4XMBoHOkYntsXpxiEDF80DDAC72khB9buASFYeqlsBCrz0WShBnzOQklGTT5+93Q50hmZ2zdnmPk3G8QQxp0TGEYdIyrgteBX7geXlwJULySjw8hHqC5P1XxHAbWuAhl7qGydyu5I1vrK/OxMhUrTsiPZx470l9ux46yoK19/SDLzaSIab8+cBLQOk2CR16s9BV2YeE0HpdVawyHFxK6RImoyeJ+gB1leTIc0hU6Xgo/3U5+1ncylUKBWg/jEUO/4z1+RRtMa2Y2Q4HE2QYS07MmZVBXDDMqDeKgyTzd4u4NE9FE2T0MhAV1dorwHk7X7mID3P6gp6jif20/3ZSuAJKTDMhBhPwGAiMGEf5Ine58kQwCCJwrTGrfGIABxZ7TxTJht/Aij/PWXQu8o+djbjdLq+7XEAy0uB/ii9V3vMCaB+NL+Arudx0DV3tU8cN/Z8KYuZ0P7e8OSeRFGgcTOT0GoBNHame/ezVf6y1y6vQj/PJu1Ctr6ffU3Fyu23/x6PaEVhlAeBkRitKRuqyOjTNjTREJr9ft0KjenZrOWLi2nsTBapNOF5LOOtIACmYVJlecxUTs2kNWR+xaiooyTQtpNWHQUg8wyiwCAKQIHbxK0rTFyz8vj58HMBV2g5c8LZptDWbPgEPv63m7H2itvx71smfm7qGgn+0tgCAKJA+7BdUBJHu+pBy9CpqyqZHUbmVASYjJQQ1ZiBMDAul3c22AuK3wlEU6feo+NRaME53SGODonaKeCkhcZeVE7EWmrnkioSUF9I3teZ4nEAm+uBRWXAng4SirPDe0UAOR5S7IdjU3sFpwqpzRaEx+OQyGtX4CXlvjs0feizCMBjvXeAhIXKXOAzl5Dn861W4PUmoDKPBOPnDpOHebyAKgrUVuNDZ7MX9lwPcNsqUnI7R0lxPdhDi/GSEjrf0X5S5iSRztUxQu0kChljhUumY3WTBIyKHFIKYypZ4MeHUgfdwCULgFB8ciUrzwsUemmcjcbHCvpOGfj391BIoVvJ5OQZ1vVNRn/HU8CRPrrfFxpIQbWfPeACSnPod/0RYF4B8DerqV/s7aJiS3ke4IL5mTzp5kE6n2GScYAx8hJNJQhP5eG3x3W+F2gfoe+KIKG1JIcK+XaM0nnfv56iJb75FPWJ0hwSrHrCwN7OyYVGv5P612TCWsBFz2YbSwTM3AM+1ZjN9wArK+h6O9tmFjYfcFIBq5Q+UUAMuKhPPnOIxkA0lUm7yHUD1y2jKIetLcDzh6lvKBK9k57Q7EIHnRIpxYtKgK5RGkuCAFxSR+dpHqTxqhnU18pyqF/0hS2jDCiFY14+4HcDB7tJmcyOzinLIUGYMXo3w/HM9T0OUmhVg963AEspddJ7sc9RnQesqaTaB50jVJ3YnnOK/dQfssnzUPRF0wDNDUE3vXefAwin6Dq2ouCUyQv14tGxfVkA9b2eECnNuklVvS+cB7zWDCRVIJxiaBsGHJKAm1bQZ82DwO5OUr56w2Q8zPfRZ+tqaFwKVpTEE3uBh9+m6+W46bn7wnQtpwR4XRQeOhib+r16HaQghpI01k1GzxZw0TMk9UwaQbYCC9D7MBlw6QKaI1J2sWNh8vW9Kpfm4uE4PVfARUp2JEXPOlMlzq3QPOl3kRHVjuiWRJr7BqPADcuBOzeM3T3GMGm+GolTykhvmN5hTzizpshiphL7bA0WDqtPMFBf+fgF1A+3HwP2dI09n8fqf9nzzPGicFaWASsqaI051GMZoURaH+21KmHVbRBAzkp7HcxW2stzaM4ZiNK57GcPuqldi/x0PkWkscMAvHSUjF+rKskQZJ83YBk1GWh+yfWSgmyvOZME/kGANV8HqP/JEq0RA1E6b76X+nLnyNj2OZEUG1uGGr/G2EaP4gBdyw6tbx8BLq0HPnHh7K5zuuAKLWdOONsU2pVXfhFXXrQS/3zPh3Dn78aHko0rxnEKQ3GqcmmCHIiSkDJV7txkeRaC9XuTTZ87KMJEdS5Qnitidyctgvk+mvyylRu7EI89qBdbBVsO99IiVeQjL8zZkvuSLQCV+knJMky6x77wOMu4QJbx82tpUt/bBbQOnbhSHXABP/obEqwKfZTn+dRBOmf7SKaNxgvi2YuKwwo506dZhMcrLLJIAvVInK5l95fKILC6kt5t0wB5Pqd6tqkKlQTdJDza28LYX7e9oT4n/fE66RxOOSM87+0kYbUyl4RzAaQ0BN2ZcOK+CCmIkgicV5NRim5bReFeokiCxl8O0LPpJi2aqyqovSURWFIKbKyh67YMAA88T4KVbfV3SsdXkkpzgI9tAn77FinF+ZZn6+7NJJy1DtE5h2IkzMoCUFcErK0E/vNNGq/3XDcxH3kqNIME++cPk7BtmPTuJZHOecda8rr+xxYaf3+7ngTKrG1yAQCxFPB2B7C9LaO8zTRMtsxSoPvGRUEEXPQuFhTRe/r/XqT3MZogb7goUHj0PdeRkNYTAh7dS6GnuklzRiQ1ucd7fGRArpsUuDdaxs6vdnit3Z6VucBtq8m7l06hFKgdQ4lMauHWVlLiGvrpOdZXA7X5FJ5u526n9Ey4dnUe8P+uJYHTJmq1aXM/RVO80Uztfmkd8PShjLfUIR8/x9YhUY74khKgOp/e56JiSkH4n52k/LkUGh+6VV9OEklRW11Bc/Ije6wCWdnRElMYLWrzqa2GYsDRPloDsucXj4PGqccBfOkKEpzfaAa2t5KBz2YyY4FbJu9svpf62dF+mnMA6geySG25rIz6RFylwv7RFPDsQeofFbnAxmrgz3szz6NYWzwxNtZTp0jAe9cBK8tp/vzF6/T7RSXA5y4FdrcD//46tcP8QvKE7++hvlOdR/OdqtNn3aMzj8yRBGoAyeqrARfNpboV7dEdGjsPlgTs1BOKKLltFY0dQaD0gcYB4FAvcLiHDFAxlfrF+mqax/68B4gmyHjUGwbuvxl4sQF46gDwD5upb7zWRBFLQCYfN3t7HQGTp54olkJngq4ZcNGfkgAZD1M6nb9jZGKoelkOfZ6tdMsihdffvpreTzaN/TSO4yr1wZXlNDaPDZFXuHmQ5lHDMpDMy6e2aB7MnNuwQo0NZkUvSTTONCPTxjZVuWSU1Uxqjz0dpHx/+mKSnX7xOn0WdAOXLySjkD1P5HppHDiylHPGaF54/jApm0mNDBNXLAI2VGf8ANEU9e8CH537YA/w39vpHV9cR3LGcJzm7N4w0BUig0AoQXOcLV/leYC7ryZDxNceB65cRGOnfYTWk7VVmZQcxqjftY/Qu2obIsNDJDV7pVQS6dntfO4x/cVag7IjD+y5JtdD/X9dFY0/r5X60h2i/rmjNWMQHc8ldcCXr5z5PZ5OuEJ7monH4/jJT36CP/3pT2hubkYqlUJlZSWuv/56/P3f/z2qq6tP+hodHR3Yvn07duzYge3bt2PXrl0Ih8mM+o1vfAP33nvvrM730EMP4de//jX27duH0dFRFBcX46KLLsJnPvMZbNq06YTu8WxTaG/44H1wuxz403/chb4I8PEH6ffH8+ble+ig4Vgm/Gumg0KyvFiqMXFisBdYO4zL7aCJWxZJILeto7bAJwm0YM4roHupLaDFbEszCdP2+esKga9dTee56xFauG9dCfREyPtmF0fK9WSEjvXVNMnrJhXyma6y7olgC+X2ZG17Q7Nxy7Qw2Ypinpe8C82Dk0+qQRcpVJ2jJHQIAgmuTQMkOHsctFCtKCerKqwFbkM1sKGGFIYn9lEer40iAX9/KQn4QU8mpGw8mkFGgBcb6O+ByOwto4poFc4WqH2iKil3/3Q1cKiPBIrhOC0q9oLkVkhhuG01Cc8NfSSIHuim5w4nx4Y91RWSINM5Qs9pmKTc3LaK+k9fhNpoKEbKVFSlv2MpEn5SOv2ua4SELb+TFv7LFwKX15MHYDy6kQm9jqWAP+2mds5WyuYV0HuoL6KFPtt+ZDLg5QZgXzcp1MtKqQ3+d/fUbbyomKz9XgcJxfu6rDaWyBgxEs8I58ejeQC492kSVOYXWN5YlYS2paV0jiI/jR+/ExMCJBIaKfI724H9XWO9W+urybKdrXBNhW5QWOcv36S29FvGBgbqly6FhKf+aGabI1EgwfOaJRTaawtbx4ZI+LSbryaP5pvDvXT/VbnAJy8iRejJ/XSda5YA1y+jsaTq1Nf/Zwf1g+o8qqI9GM94a9wK/RmOk0fq5hXUv370El0jodF7/9j5mRz04xFXM/nXgkBj/auP0nUuqqP+3jRAisdF88lAJ4n07Ae66RwOmYTWkTjdZ2mAxsyhHupPLoUEwm9cR+33p900pxb6aD6+bRXNF4U+6vvZ7O8CvvEU9ZGbVwAf2UT3aZjAK0eBX22l95jrGbu1RqXliROQMUIMROne3r2GlOURa//paIrey652ul+nFUCU1Oi+GcYaSfO8dExPiNq7dYjmgIQ2VpmRBCoME7HmDLtCtMsyMN20gsbVVLQMAj99jeYpAHjXcgpB7wzRfHZeDZ37318jY+D33wXMK8x8/9gQcPdjdF+20VYQ6N0aJvCxC+i415tI2HdKFOUSSWa89HbfkwRSzgPWVlNdIfrb66D3ct1SWitah8hA1jWauY/yHHqvrcOZtgBobdUMur/6IuDO8+j5sjEZtXO+l9oNoEJhX/xfep8f2EAGkPuepX5/04rMd3vDZBR45Si9l+N5/j2WMdrvpBSWba00v1bmUnsPRjNbuwmgNc8p0/pZ4KV+dOUiWg/nFwKvHgUe3EltneOme72snsb677cDTx8kJS3HTUoXAxkaq/PJ+HC4j64VdNM60DlC17tmaWbLsX1dpOhevICOGY7Re28ZpOdPP5tCBgqvg96F10H3+P4N1B8AGicPPEfX/cSFND9NR0oHPv+nTI2F7P5SX0TFCmvyJ/+uycho9ostdPxNy4GPnD9WHmCM+uWeTnp3lbmUVvPz1+nnb9840WA5HSYjo8dvttG87nGSjFAcoPutK6T33zJI75QxGr9ehYwsg1HyKgfdpGgLIO+7bhkP7LU9rtL4uW4ppW797HUad5+9hOY5mxcbgF++kRlrDomOX1pGa/ZUbTfXcIX2NNLU1ITrrrsOjY2T7FUCIBAI4MEHH8QNN9xwwtdoa2tDTU3NlJ/PRqFNJBK4/fbb8fTTT0/6uSiKuOeee/CNb3xj1vd5tim0n/36f+Ktt49ixzM/AAD868sUBhQd7EAyNICC+WtO6LyiQBPZSIIEjDwPLWbjPaoehSY6l0KTRFKjySWcJIFIAE1G8SwPWmkOTWRXLiQh7IWGsQuBUybFxucEIACryknZUSTgu38lheefbyVhDKBJsC9CgmxDHwmI7cMTC5+cV0NC6Q9eoAUl26ubTWWQPGp7OzN5Zba3z/be2KE3y0opnKl/XAjgvALg+qW0t+n4ehbbjtFzfOwC4I+7qO3es4aE0W2t1MZfuYIWeJtYCvi3V+jzz11CFtnp2NoCfP95ug+/i5TiW1bSAj9uZ6ApiaWAZw+TN6kkB1hURJbeba1j9+2cCskKQxMEWhwdMuXf5nlJMJlXQO96fzd5R0YTpGz87fqJxZYSKnkODvaQINk2TN+9qI76Ud4UtRzah0lxdEiZcLW324H/eIN+d9dmUkQYo0W1c5SOWVQ8dcEnm+EYHW8y6q+KRH15JEbKnS1kDUbp3e3tokU8oZEwVeAlL9dLR0lIKPaT4jQvn8KfLpw/VkHa2wX8+CXyvpYHgbuvIiVspnSMkCB+sCfzu0IfKXPZObFOme6z0EcCQzRFXsqNtRRmKUsk4Db009ywrGxmitxInATC379Fbex1kCCY56FzJDRS2FI6CaHvX5/Jx3XKY8+lGSR0PbSTBPobltF4Hk1Qu1XlAT94npQAp0zzxy0rJ54HoOf7zzdIEF9XRWO2cYDGkK24OyXy3Hkc1H5LSoB/vIYE3v94gxTQgCvzXDX5JCCtr8qMt/1dwK+30bEAzYsrykl5kkTg+7dYc14WsRSFlz9/mO4pYOUHqgYdm+uhfzcP0vOX5VC7LSunomkdI8AXLyeD0aEe4DvP0vPeuorG2XgPFgD8ZT89kyKRN/Xe68fe10gc+Omr5HG/bAH11fmFdG/ZhBKktL7UMHmqQ2UucM1iaoOAZaxr6KP5ceuxjKKa66Z+6FKAv7uAwu4P9QD/u4cqPa+rpnOFk/TdlxpoPlakzFbs2Z7BPA8dbxtwcj00NzFG69ef3qa+qFkeWYdE84vt6dctZenLV5CSbKPqwLefofmsJp/ONRSj/ry+yurfPWOaYEykQo4b+OJlFLESSVKkwSN7qP9/aCOweRG9OzvCxH4XX/pfej+fuZjG06N7M+tprge4ejGtufMKyMhjsszYOdpPRrwPb5oYuTGaALY00brud1GRO5+TrqlIdJ//ePX0Yz+aon5yqIfmcKdMSnZFkOaYnhCNh8YBaofqPODrV9N6k30fI3GKtHLIwKcfprY0TOC7N1MfzaZrlJS2vZ0ZQ5ldK+ID55HSI4k0tl5sAF44QvKDZoWwf2gTcO0SOmYkTsawJ/ZRH/3IJopOcSkZA8xrTfTOnTK1cUWQjMH9UTLELSyeXgnUDTISPXWAFNqPXzD5uDRM4FMP07u9uA64dinJHluaqeK/rZiuqSS5xCowjnCS1pXhGCnCvWEy/rUOk5zzmYutkPAY8ONXqIZHnjUm+iPUX6pyqa3Hj/GZ0jlK625SI1nwSC95i7NrAZQEaA3sHKVxU51HSv5MDLYmI2PFb7fRvPrhTfRed7bTfP6RTTRfPLKH1pabVtB13+4AXmskGeHqxZSidDbAFdrTRCQSwbp163D06FEAwMc//nHccccdcLvdePnll3H//fcjGo3C4/HgjTfewKpVq07oOq2traitJQleEATMnz8fZWVleO211wDMTqF973vfi4cffhgAcNlll+Hzn/88ysrKsH//fnz3u99Fc3MzAOAXv/gF/u7v/m5W93m2KbT/3388ge/86E/o3/cbyLIE3QBu//cowqMjaH7xP/GBz38dhwac0E2aJJeV0oQxELUKBLhpIdEsD9TGWhLEVlfQBJ7UaNGVpUz+23CMhF1ByPw9HsZoAvndW/RvRSKBZWkpeRFdClkqNy/KKImmSQvygR5gMELKdOsQ3W9NPglPv95GAtpl9ZO3x1AM+NdXaFIGaIJcVwXcsooWnE89TAvpP11DC8kDL5CXQBZJybUF3+zQnacOAI/tzVj1JEtJUyRaWPM8dH8eKzfDrQA72kk4W1pKSuSSUvpuXCULa2kO8K0baHH55lMkeHsdlMN1/bKx3q64Shb4/V0U3pWt6E7H2x1k/S3yk+fwkb0kFKyrIoF3aenUC9S2Y8BPXqXF0CbfS9ZwEcBDuzK/V0QKsQNIeYsmKTdOAClLownqDxfVkeJekTvxeppBQsPDu6gdPngeCcpTeZOPRyRJbWZ7NcdzXjXwucvo+YeiwA9eJKHLRhIpzPumFSSQHI9tx6jf2cptTyjj/U3pNJY+dwkJgQAp2n96G9jSQkrIt2+YWinPRjOoXy0omlw5m4qOEeD/PUl96d1rafF+vQl4bB/1waWlGSu4qpPCJIt0T14HCUJH+0kJv2MdCQmzsdT/ZT/t35sOK1XIM7R5Ec039rlSGvDXw+RRVHW61o3LxhphdrYBP3qZ+mZdIQmAdppBNkmNjBQVuTMTxLa3kndO1WkMep10P6pB/dfOTa0vHntPJiNhrWWQFK9IktqqY4Ta9KL5JNy+1Up96bql1LbHhoAXj9A8l+OmtigJZK7TEyJBVTdpPr5hOQmrk823pnV/2c+Z0qhPvt5M93thHfD1J2isHumlOehzl2TGLkDz7ZcfIUXzsoXAN/5CffefrrEiQiwYo9zZX75J89+XrsiMk5ROCsVLDRkl0vYieRz0jAMRiizxOek96SYJ0MtLgauX0Bw1GCNlv3mQjrtq8dTvsTdMXhl73gesUNscGl8tg6Sc1OTT/B9N0Vw1HKd0guxIiyUl9G6uWUKGkReP0PeTOj1H0E3zvGrl31XlUh9+sYHWkm9cl/F6agYpPA/uoOtcXk+hsLkeMnQqUma82QbTbEIJ4L+2krFlqaV82POnqgNff5La8ge30Jh59hB5HDfUkLHpd9vpOW9bTdfNnjNMRkL/b7bR+7xxOfX5aIrmp+1tmXdnR0VkpxCtqaTIn5nMW8dDNyis+Y+7qJ994TIykmRjmMA/v0BGMVkEvnn9RO9yNkmNlPC/HqF39sXLKBc0mz2dZMzqGCGD999dmDGUZ9MbpuN2tJHyV+CluaxpgBT1+mJ6H23DdG9XL6Y2n03bPHeYPKHlQWrXBUWZMN5YCvi3V+n81y2lyJNsOkao4NlLRzP1NhxWpEPASfeR5yFP8Xk15PXc2wX87DVSWmvzSc5yK6TUrbMijFSdrl/kJ4eBbYyrzCVjzvGMvuOxi3n9eiudtyRAMmXASfLglYsydSdms77Z9IRIKT/cQ/NlRZD6t25SH/vwJopusJ0dduG41iGazysnkU3OBFyhPU3cc889+Pa3vw0A+P73v4+77rprzOdvvvkmLrnkEui6jksuuQSvvPLKCV1naGgIP//5z7FhwwasW7cOubm5eOWVV3DZZZcBmLlC+9JLL+GKK64AANx444149NFHIUkZaWhwcBBr165Fe3s7gsEgWlpakJs78158tim0b719FBff+k947ZHv4Lw19Xj25d34wN0P4rw7H0CBF/jl+yX0R4HvPEMTh8NSwgp9wH030YRyujjQTQKUx0Eer7+/jBbyoSgttC8fpXL4n7qYBNPJYIwm0v/eToquQ6Iwy5WWZVw3SCDc3UF5Vnu7SOj55EWkPNihPQAJd9uOAT+7I2ONZoysdo0DwEc3AYVThE3qBuWmvdFMwo4dLhtw0aToc5IwcmyIFN+qXHqmfd0kUJQGSOBrGiAh6l9uI4ESoPfRPEDH2yFeQ1FanA72kFCnm2QNt597prQPk1cmnARuXk6C9YHuTE7i8jISFDfWZhaQ54+QB2ZDNVm0cz004b/WRKFkdlGKq5fQIvDy0YnbBRT5aIufqxfTYvrXw8Dje0moXFRCRpGhGLXf4hJSdtdX0+f/tRV4s4XatMCXKVSi6hQyPb+AvrOkdHKlajBKIZMjcRI82oaBK+oBp4PasmmA7vvCedSev3uLzv+pi0loHI2T4PLsITI0rKsib9Z4AQvWPf1mG+XPbqyhvB2/i/pLQz8pOpIIvGvl5It/SqN7mY1yOFuSGvCFP2eEwPwsgc0wycL/+D4SIux85LZhEsZXVwA3r6S/D/cCv9lK1azzvfRMly4gYX9XO3nQ3Qr183XVwEIrR++vh0hRtLebeOBdk7dlNtEUhQI/fZDGyUc20Xt4bC+197pqMhSd6hCxSJIU77daM+GitjC/rJQErgvmz0zYahsGnjtExYCcMt3vxXUZhTShAZ98iOaK0hwyMMRUMiB4Le/rxhpq4/xJhOyZwBhV6v39duqr5TnAD28jIfbfXqGxcMNyujcBpMwKAvDDW0kg7hql0NKROPXt8+fReeNWNE5CBf7lZRpXmxeTMP7MQXrPH9hABZnCCeo7+T56fkWiPvPNp2leMkx61iUlND819pNR6OYVFImSPYdPxkAE+MqjtDb8zRqaL0YT5B2z51jDJI/7gztIkL60nsZ0kX9s3q8gUL97ZA8ppv/2KvWJy+vpXNFURgl2KaTUNPaTwiMKZHC02yiblE5998+7SdH8wHmzMwrt7aToioEoKaabaqmfHuylXPaWQeqzn76Y5vPs6/55N6U2FPiAT12UMarZhBPAf+8ghcqOqLG3YrLxOChE1eukd5PSyZihG7SF2eZFJzaHJTRak+3aA5JAz9EXoXf57jWZ/vLjl2l9LfKRAcU2Eh+P5gHgX16i9/6362neEgRSnh/aSR7AD5w3fSi6zZ7OzDiVBOoTmxeRgQOgNe25w2Sc1QxKY1lRTuud7USoyqV1Z3yoP0DP9+OXqT1WlNMcYueAA7RO3jVNnqdh0nf/9RX67u2rgfesndzjOxSjvrHtGL0H2/h2aX3GeJXUyCD2x130TvwuMmiHknTOi+bT/DGV/AZkIs+O9gPHBulai0uor1bn0Xt5cDtdpyRA/fmSBSe+JhomedV/v53kXFmkSBoTNN4TaqY+gR2NdMkCigQsOo3y8GzgCu1pQNM0FBYWIhQKYfHixThw4ADESfYD++QnP4lf/OIXAIDt27dj/fr1p+T6J6LQXnfddXjmmWcgyzKOHTuGioqJGsDDDz+M9773vQAmV9Kn42xTaDVNx4ILPoOq8gKsWTEfv/3jy7jsgmW46oN34elDIhaXUAEHVacF8dXGTPhVsZ+s0JsXkRX+ZOgNZ/LZcq1zfftZCm351g2TT06HeoCfb6HiAdcuJQvd+JA7gCao324jb5Jt6fc5M5ZtmwIfTfi3rZz4PEd6gX94jBb0a5ee3LPaVnfNmLiQ6wYV0HnlKPBWG92jXVDE9laUBCgc+dJ6UqztkOmOEatdeoEn99F5F5fQhHvxArI2ngjZIZVrK8nrGE6SYru3i96dUyaFMqECuzqoX3ziwonv7X92kGfxR7dT3hFAi153iAQ1CCQE72onRSmcpIX5yoUkDD2xL5OfZhdqSmh0D7aX6tolJDTu7SQhYH83nV/AxC0KavMzoeQFPrIyf+MpancB1Ne/ciXdg81wjLwpzx2mdq8rJA/UeGu6yegZHtpJz7Sxlqr6Liiiz+MqcO9TpBR85Hx6p6dhC8ST5tdbqfDXj28f62WbjrhKgs6T+8lDluuxcplNEuTHFxoq8JJgmNRIyI4kSYGtL6I5xy6a8uUraIzOlGODFI63r4ver+1tev/602sEyCacoNC1l4/SePE5ScG5Zsnk0QbjmWyXsWNDZBw40EMGtiJ/Js/+dDxXf4Tm52VlGcOKYZKy++B2MhTZnvgf3kqeSZtYioTsba0kIMbUjJLvcVCKRk94bDQHQO98XRWN6VUVmec60E1KcqGfwkvDSZpTtrVaVZEDVCCty5pTrrLCkodi9C48DurHC4tpDviHR0lA/edbJ27VMx7dIIPdQzvpOW5YRoqTz0nt8WIDeckWl5AAXppDhsTpDL+M0b2KAvX56RiKUlG3VxopPPX96yfm209FKEFGiB1tE1M9fE7KF5xMmQZIoP/Z6zSXXjQf+Oj5Y+e7aAr44Qs09y8vI4VrXj69I9MkhW28QS6SJOPjiw30Pu5Ym0lJsDFMMmZ0jdI929vqeB1khH5yP727kgC9y74Izd128aWAmwwdb7Vmii/9x/tm7xlUdTJmPLaX5nuHTPLHe9dRxMqJRgJNRTRFRs6nDtB7c0jUlrqR2b+4PEht3BumcWcyeid1BfT5aJzWt74ozcU3LKNolJn0lWyPd2kOvW+7WF1CI2PtwzupzddXU8RMV4jGpp07W5lL63hKz6x9dYV0jr4wrY3PHCQj1JISkivOq8mM86RG/ePZQ7Q+LCohY/SyMloXxj9HyyCNy7daaRzduooKNTmPY9Caio4R4J6/jM2xFwTLYGj1n1AiU7SsMhf46XtO7FqnGq7Qngaee+45XH311QCA733ve/jqV7866XHbtm1LF1n62te+hu9+97un5PqzVWgjkQgKCgqgqiquueYaPPPMM5Mep6oqCgsLEQ6HsWnTJrz55pszvqezTaEFgOdf24u7vv1bGIaJ9avq8JP7Pg63y4l/ejKTz3PxfCqWsL6ahMqWQZpotlD0NVZXkqDfG6bFpDqPvFUrymnysRepbKHLzkH48+6xeXk2VblUNe6VoyQcGCZNrivKyHKf66Hf/eUAKUoOmTwxly7IeEbeaiVhp3OUBOlFRRSKZlvISwKZQktH+kgRKg9SSPJlC2gRaR+m8FOnTKFZcyUI21vS2AVBhmLU7q82ZjxAC4pISM+edB0y8K4VFPrsnUTBP1G2HiMhOrugjyxmKrECmTygyxbQAlSZm2mv7lHgc38iS/2dG49/Pc0gj/Yzh0ioASjsaU0VCZ4j8UzOsyjQ7yIpepd2dc1nDlGf/OAG2nqkeZCME3bBqJH42L04DUaWc9UgYfqzl0wd9mUyEvTKcqbPKzZMEkD/uIvabmU5GUUe20uL5r3Xzyws+XgYJilOzVZYV4GPvAYVuZMLXIZJfXs4Ts9eFqT2zRYUukeBz/6RPB13rJv9PTFGY/utVooy2DSPxm1SJa/7Y/uo766vJgPZ4V7q49kLrADyVNy2+sSMMoyREP9mC4VSTiW0zwXdIfI4v9hAitjyMlJsN9ZO7gXJxjDJEPbUAZoP8zzA5y+b6DGba2wPSVQlAX8yTxVjNH8c7qVxWuCjucKuV8BAQm0oQQYL3aTQ8FebSJEu9JF3O+gmz97iElIUsxWT9mF6z40DQFP/xLoEAF1TN6kt7SJiqk7z+vG8/tkkNBq/j+6h8ZLvJUVDNTJV829cTkZW1wkK1NNxpJeE/SN9pCT8zRqKiJlqbdrVTl63kTiNocpcGlMLrKgep3z8dY0xmsf+603KD37PWkqr6BylEPFoimSDtVWze5bmAVIWd7ZTn75yEYUjtw5R5MdU23Q5JPLq37oyExllMpo/3u4A3mwGWobo93Ye7Fevmv39ZXOoh6K9Ujq929M99jSDjMR+V2ZeDifJQLe3k9aP0hySWWSRFPojvbTOySK9U5NRCs5Ny2dvMG0bJkfG4V6KMKnIpTkoqVH01AfOG+tESGlkkH+rlcbjebWkVBZPIeoaJoWmP76P2rbIT+kNZUGKIBiMUeTbNUtmfu9NA6Rs72ij+eHyeppT6otnbnjQDZJtf/QyOQOuXpxJd8iO+GCMxv22VhpLM/X6n264QnsayA433rp1KzZunFyK1XUdOTk5iMfjuPjii/Hqq6+ekuvPVqHNDje+//77cffdd0957NVXX43nnnsOsiwjHo9DUWa2ap2NCu1UGCZZwne2078vXUC5GdnCezhBFuud7TTYy4M0CTcN0ARll++XRPq9btK/iwNkoR1NkMJ743JSfkWBFt3+iCUoWYrqqnK6bsdIRmBfWEyC4MYa+vfPXicPSKGPJh274E6plWfx/902fWiLYZIC/1IDCV8pnSbY/ggttN+6Yazn4UwSTlAu0N4uUgSWlZG11rYgnqhV8njoRqZQTsBF7cwA9IZIyD7SR3/srYHsENLafFJORRH417+ZvZA3EKFiEFW5Exe2gQh5Bna2UXvY+xqajBb1G5eT9Td/EsXUMGnxfe4wKccOme715hWnTliJq9TvFZHu88+7SejyOIBvXU8L7YmS0MigsbuDDDu9YeqrAI0tk5EwtKyU8sWWl9Hnzx+h4wfHCf1+JxmwavNpvG5pof70b39zevqUraQ9soeut7CYlJWgm96zgLFewXcKmkEK9rOHSOHPcZMgf+VCMpCM7+NDMSpSdaiX+uW1Vp7oTAu0naswKyT3r4cpVDOpk4fwC5cf3wAQV8mz19hPSm73qJXuYXlUclxUNXVpCRnfVN0qFsRISM9x0dxaFpw88gegteqZg2QgPTZs5acXAp++hLxJpxPGSLH5wy7y1Ns1Ci5dMDaS4qUGUmZXV1AqzVTKxUyJJMlL/MKRjJJZX0SRLCeTgnRsiIw9rzTSuxMFMj7dZIWkSiK9u2iSDJd2Osl0RFMU5jscI6XG3iLmnc5AlLaYiarUH2ZSQX4qGCP57g+7qD03zQOuWzJ1etWJ0jRAEVivN9O6UF9E4/xEI8t6wzRvvHiE1sJcD82ZS0ppjSkNTJxnI0laF58+SMa1dVVkODvX5lmu0J4Gbr/9dvzv//4vAGBkZATBYHDKY1euXIl9+/ahsLAQ/f39p+T6s1Vof/KTn+Bzn/scAODRRx/Fu971rimP/fznP49//dd/BQAcPHgQS5YsmdE9nUsKrc3eTspziqcojMMu/nA8DJME90O9mf3W4ioJcs2DGaUjz0NW02VlJGDv6SSLoG6SZe5DG8cKtKMJYFcbWcV2d5IgYp/LtsCNt+a+ew1ZVGeKHTLZNECeg/Nm4EHhZEhqJEge6SMhr2WQvMkf3nR6865VnYwSh3upv7UNk3FCN8lzvLoSqM4lr2vQTaGSk20zc7K0D5OStqs9s20EQH3djgqoziMFrjJ3omd0OpoHgcf2AHu6MrnHkkg5vTetyIQ0JzTap/NgD+ViH+3LFK+RRcpHvHKRldNmkPBvb2VzbJCO21BDnv5TUbiFMzntwyTIv3SUDICFPjLuLSwmA85ogox1skj5b2eLF2CuSemkQBb7T3y8Gib18+ZBmtubBmhuSuk0X7gUWkOiqbGFnvwuMjSUBsgjVpL199tWkRrNpEiQq5fMXRSPTWM/GalebaRxX5ZDESomI6PJVYsox/9U3lc4SUbrAh8p76dqDtUMeif53snzRDnvbOx84QVFpyaU2zBJBtl6jGRLOyLE5yRl2a5BMBwnI41h0rp49WLaxu9cZDZ6xgnUzvq/SWdnJwDA6/VOq8wCQGVlJfbt24eBgQGkUik4nacwVnKG2PcLYNLc2WwqKzPum46OjikV2lQqhVQqlf63vS/uucTKCuAn76bQ3T++TdWHL6ojz+iK8qm9bZJIk9KCIhIY/ns75bz4XVQg5NIFFB6zvY1ChJ4/QjlPK8opp3B1xeQ5e0E3Ffu4YlEmxCWUAOqKaHKyKz/2RygEh7HZhxl5HNa+ogtn9z0O4bKq0E5XRfJ04JDpXWe/70iS+tfONtrLdTg+9juSSN6YoMdSci1F1+e0/lhFdux/ex1ksbU3aBcFWgRVg7wH/7uHhMhCH+XvVefTsbEUWY17QkDHKHmG7VBtjyOTd1SZS/24JJDZO1gUyEjw0E4KzyoJ0IJbHiTre0Vw4rYZboXG7soK4H2gsXK4j8bF+uqJ3oqKIOUwceaWqjzg4xdSWOCeLqpGvq+bcm5tw9zqCuCLVxw/x/OdjFM+eWOYJFJ7V+VlKt3b7olshYwxMmra+Yn2n94wCcXjt3S7qI5CI8+U4cdeZz+6ifrQzjYyRIeSlGf7N2tOvdEu4Jp5xfzZoEinJgWDc26S5z2140gSyQhoGwKjKZI7W4asiL9BinZzyJSWdNPy/zuefIArtDMmEqFSqD7f8c1sXm+mB0ej0TOi0Nr3Cxz/nsff71Tcf//9+OY3v3nyN3eG8TnJu3bTClI8X2oga5YkkgBem08VMPN9lMAfcJNA7VbIIv6TV0m5/MAGqmpnV/m0lZ6PgsJovc7ZWZGdyuSLqkOmfI+ZFF3hvLPxu6gK4SUL6N9xlUIERxPWn3E/d4coqiCWIo/ZeG//eMbnd3kclCN8w7LpvfqGmSnmZf9pHaLQypQ+9vx25WPNoEiDd62YfRiUUxm77yXn7MKpkEHBNipohpU2YUUXnI0Fw94JTNaugkBr0fzCyXNr4yoVtukJk+HKjoo404zvQxwOZyw+J1W5X1d9pu/k7IArtDMkmaRYO4fj+AlQ2QpsIpGY5sjTh32/wPHveab3+7WvfQ1f+tKX0v8Oh8NjvLvnGvleqkb4njUk+O/tovDEY0MUXjm+UqVNXSFtNTNdDurJVkrmcGaCx0F/yoLHP9ZkVJQjmqJ8pGjKyok1MvsvGyYprg6ZwhaXlMysL0sihQaW5YwVQE1Gofd9YcoVCycpAoExqmx9OkO2OWcPdhVuztmHx0HhiOdqSCKHw+EA70CFVjgFpt9f//rX+NCHPjTmdy4XZeyrqnrc72eH5brdZ0azse8XOP49z/R+nU7nGfE2n24EgcIdx4cEqzoVMIkkKZcnoZHgvqZy7vOKOJyTRbQ8NV4nMFdRcKJAYcQnU8iDw+FwOBwOZzrecQrt6cLvJ4lsupBcm1gss+/ITEKUTwf2/QLHv+ez4X7PRhwyJdjbG9JzOBwOh8PhcDics4t3nEJ7+PDhkz5HaenE0osVFRV46623EIvFMDo6Om1hqI6ODgBAYWHhGfNoZheC6uzsxLp1U2+8aN8vgHM6hJjD4XA4HA6Hw+H83+Idp9AuWrTotJx3yZIl6W17jhw5Mu0+tM3NzQCAxYsXn5Z7mQnZlYqPHDky7bH257IsY8GCBaf1vjgcDofD4XA4HA7nVMEzAWfIhRdemP751VdfnfK4nTt3pkN4L7jggtN+X1Oxfv36dDGo6e5XVVVs27Yt/R1FmWLfGg6Hw+FwOBwOh8M5y+AK7Qy59NJLkZNDyZS//e1vwdjk+1/85je/Sf98yy23zMWtTYrf78cVV1wBAHjhhRfG7EubzSOPPJLeT/ZM3i+Hw+FwOBwOh8PhzBau0M4Qh8OBv//7vwdAebr//M//POGYrVu34le/+hUA4JJLLsH69esnPZcgCBAEATU1NaftfgHgK1/5CgAKg/7MZz4DwzDGfD44OIivfvWrAIBgMIiPfexjp/V+OBwOh8PhcDgcDudU8o7LoT2d3HXXXfjDH/6Ao0eP4h/+4R/Q1NSEO+64A263Gy+//DK++93vQtd1uN1u/OhHPzqpaz377LPo7e1N/zs7D3bPnj1jPME+nw+33377hHNcfvnluOOOO/Dwww/jiSeewObNm/GFL3wBZWVl2L9/P+677z60t7cDAB544AHk5uae1D1zOBwOh8PhcDgczlwisKliZzmT0tTUhOuuuw6NjY2Tfh4IBPDggw/ihhtumPIc9l651dXVaG1tnfSYSy+9dNrc12ymO08ikcDtt9+Op59+etLPRVHE//t//w/33nvvjK6VTTgcRk5ODkKhEAKBwKy/z+FwOBwOh8PhcDjjmY2ewUOOZ0ldXR12796NBx54AOvWrUMwGITH48HChQvxxS9+Efv27ZtWmZ1r3G43nnrqKTz44IPYvHkzioqK4HA4UFlZife9733YsmXLCSmzHA6Hw+FwOBwOh3Om4R5azgkTCoUQDAbR0dHBPbQcDofD4XA4HA7nlBAOh1FZWYnR0dF0Yd6p4Dm0nBMmEokAACorK8/wnXA4HA6Hw+FwOJx3GpFI5LgKLffQck4Y0zTR3d0Nv9+fzgs+k9iWHO4x5pwIvP9wThbehzgnA+8/nJOB9x/OyXK29SHGGCKRCMrKyiCK02fJcg8t54QRRREVFRVn+jYmEAgEzoqByDk34f2Hc7LwPsQ5GXj/4ZwMvP9wTpazqQ8dzzNrw4tCcTgcDofD4XA4HA7nnIQrtBwOh8PhcDgcDofDOSfhCi3nHYPT6cQ3vvENOJ3OM30rnHMQ3n84JwvvQ5yTgfcfzsnA+w/nZDmX+xAvCsXhcDgcDofD4XA4nHMS7qHlcDgcDofD4XA4HM45CVdoORwOh8PhcDgcDodzTsIVWg6Hw+FwOBwOh8PhnJNwhZbD4XA4HA6Hw+FwOOckXKHlnDW0tbXhy1/+MhYtWgSv14u8vDysX78eP/jBDxCPx0/ZdZ555hnccsstqKiogNPpREVFBW655RY888wzp+wanDPD6exD8XgcjzzyCD71qU9h/fr1yM3NhaIoyM/Px6ZNm3Dvvfeit7f3FD0J50wwV3NQNvF4HPPmzYMgCBAEATU1NaflOpy5YS770AsvvIAPfehDqKurg9frRU5ODurr63H77bfjZz/7GaLR6Cm9Huf0Mxf9p7W1FV/96lexdu1aBINBKIqCvLw8nH/++fjWt76F/v7+U3IdztzR39+Pv/zlL7jnnntw7bXXoqCgIL2mfOhDHzot13zooYdw1VVXoaSkBC6XC9XV1Xj/+9+PrVu3npbrHRfG4ZwFPPHEEywQCDAAk/6pr69njY2NJ3UNwzDYRz/60SmvAYB97GMfY4ZhnKKn4swlp7MP7d27l/l8vmn7DgAWCATYww8/fIqfjDMXzMUcNBlf/vKXx1ynurr6lF+DMzfMVR8aHh5mN99883Hno927d5/8Q3HmjLnoP7/73e+Y2+2ett/k5eWx55577hQ9FWcumO593nnnnaf0WvF4nF133XVTXk8URXbvvfee0mvOBK7Qcs44b7/9dnqC9fl87L777mNvvvkme/HFF9nHP/7xMZN5OBw+4evcfffd6XOtXr2aPfTQQ2z79u3soYceYqtXr05/9rWvfe0UPh1nLjjdfej1119Pn+OCCy5g999/P3v++efZ22+/zf7617+yT3ziE0wURQaASZLEnn766dPwlJzTxVzNQZNdV5Ik5nK5mN/v5wrtOcxc9aHR0VG2du3a9PluueUW9uCDD7Jt27axHTt2sEceeYR9/vOfZxUVFVyhPYeYi/6zZcuW9DoliiL78Ic/zB577DG2fft29uc//5ndeOON6eu43W7W3Nx8ip+Sc7rIViirqqrYVVddddoU2jvuuCN97ssuuyzdh371q1+x+fPnpz/7xS9+cUqvezy4Qss541x00UUMAJNlmb355psTPv/+97+fHiDf+MY3TugaDQ0NTJZlBoCtW7eOxePxMZ/HYjG2bt269H2cDk8M5/RxuvvQG2+8wd797nezgwcPTnnMY489xgRBYADY/PnzmWmas74O58wwF3PQeHRdTysm3/rWt1h1dTVXaM9h5qoPfeADH2AAmNPpZI8//viUx5mmyTRNO+HrcOaWueg/119/ffocP/3pTyc95ktf+lL6mM985jMndB3O3HPPPfewJ598kvX29jLGGDt27NhpUWhffPHF9HlvvPFGpuv6mM8HBgZYVVUVA8CCwSAbHh4+Zdc+Hlyh5ZxR3nrrrfTg+MQnPjHpMYZhsMWLF6cHiKqqs77Opz71qfR1tm7dOukxW7duTR/z6U9/etbX4JwZ5qoPzYTbbrstfS+7du06LdfgnFrOVP/54Q9/yACwhQsXslQqxRXac5i56kPZkSI/+MEPTva2OWcJc9V/cnNzGQCWn58/5TGjo6Ppe1mzZs2sr8E5OzhdCu21116bNrx0dHRMesxDDz2Uvvb3v//9U3bt48GLQnHOKI899lj65w9/+MOTHiOKIj74wQ8CAEZHR/Hyyy/P6hqMMTz++OMAgEWLFmHjxo2THrdx40YsXLgQAPD444+DMTar63DODHPRh2bKZZddlv65ubn5tFyDc2o5E/2nra0N99xzDwDg5z//ORwOx0mdj3Nmmas+9JOf/AQAkJOTg89+9rOzv1HOWclc9R9VVQEAtbW1Ux6Tk5ODgoKCMcdzOAAQiUTw4osvAgCuvPJKVFRUTHrcrbfeikAgAAB49NFH5+z+uELLOaNs2bIFAOD1erF27dopj7vkkkvSP7/xxhuzusaxY8fQ3d094TzTXaerqwutra2zug7nzDAXfWimpFKp9M+SJJ2Wa3BOLWei/3z6059GLBbDBz7wAVx66aUndS7OmWcu+pCqqmnD7ObNm+FyuQAAhmGgo6MDra2tSCaTs711zlnAXM1BtsH+2LFjUx4TDocxODg45ngOBwB27NiRNnJMJ0s7HI6042jHjh3QNG1O7o8rtJwzyuHDhwEAdXV1kGV5yuMWLVo04Tsz5dChQ5Oe51Rfh3NmmIs+NFNeffXV9M+LFy8+LdfgnFrmuv88/PDDePrpp5Gbm4sf/vCHJ3weztnDXPShvXv3phXW5cuXIxwO4wtf+AIKCgpQVVWF2tpa5OTkYPPmzXjllVdm/xCcM8ZczUGf/OQnAQBDQ0P4+c9/Pukx3/72tyccz+EAJyZL67qOxsbG03pfNlyh5Zwxkslk2hI4VeiCTW5uLrxeLwCgo6NjVtfp7OxM/3y861RWVqZ/nu11OHPPXPWhmbB371489dRTAEjg5Art2c9c95+RkRF84QtfAAB873vfQ2Fh4Qmdh3P2MFd9KFuYNE0T69atw49//GOMjo6mf6+qKl544QVcfvnleOCBB2Z1fs6ZYS7noI985CPpsOXPfOYz+PjHP44nn3wSO3fuxCOPPIJbbrkF//zP/wwA+PrXv44rr7xy1tfgvHM522VprtByzhiRSCT9s8/nO+7x9kQ+283iZ3Md+xonch3O3DNXfeh4pFIpfOxjH4NhGACA++6775Sen3N6mOv+c9ddd6Gvrw+bNm3Cxz/+8RM6B+fsYq760PDwcPrnBx54AI2Njbjmmmuwfft2JJNJ9Pf342c/+xlycnLAGMPdd9+dDlHmnL3M5RwkSRJ++9vf4k9/+hNWrlyJX/7yl7jpppuwfv163HbbbXjsscdw2WWX4fnnn8d3vvOdWZ+f887mbJeluULLOWNk5/vMpCiK0+kEACQSidN2HfsaJ3IdztwzV33oeHz2s5/Fzp07AQB33nknbrzxxlN6fs7pYS77z2uvvYb/+q//gizL+PnPfw5BEGZ9Ds7Zx1z1oVgsNuaamzdvxl/+8hesX78eTqcThYWF+OQnP4m//OUvEEUS7b72ta/x4oZnOXO9hh0+fBi/+93vsH///kk/37p1K371q1+hq6vrhM7PeedytsvSXKHlnDHsohbAzKrp2QV33G73abtOdlGf2V6HM/fMVR+ajvvvvx+//OUvAQDr16/HT3/601N2bs7pZa76TyqVwt/93d+BMYbPf/7zWLFixexulHPWcibWMYC8tJMVnrvwwgtx6623AiDlZSrFhXN2MJdr2Ouvv45NmzbhySefRHl5OX7/+9+jt7cXqqqio6MDP/3pT+HxePDwww9jw4YNOHjw4KyvwXnncrbL0lyh5Zwx/H5/+ueZhCTYFuqZhOWc6HWyreCzvQ5n7pmrPjQVv/jFL/CP//iPAKgIwtNPPz0m1IZzdjNX/ee+++5DQ0MDKisr8c1vfnN2N8k5qzkT61hhYSFWr1495bFXX311+ucdO3bM6jqcuWWu+k8qlcJ73/tehEIhlJSUYNu2bXj/+9+P4uJiKIqCiooKfPrTn8Zrr70Gl8uF7u5u3HnnnbN7GM47mrNdlp66nBqHc5pxuVzIz8/H0NDQmGTzyRgZGUkPkOxk85mQnbx+vOtkJ6/P9jqcuWeu+tBkPPTQQ/j0pz8NAKiursbzzz+f3r+Pc24wV/3HLtBz5ZVX4sknn5z0GPvcsVgMDz/8MACgqKgIl19++ayuxZlb5qoPZR8/m4IsAwMDs7oOZ26Zq/7z7LPPpsOIP/e5z6GkpGTS45YuXYr3v//9+OUvf4ldu3Zh7969WLly5ayuxXlnMl6WXrdu3ZTHnglZmiu0nDPKkiVL8Prrr6OpqQm6rk9Zsv7IkSPpn2dbPXbJkiWTnudUX4dzZpiLPjSeJ554Ah/84AdhmiZKS0vx4osvHlfI5JydzEX/scOzfv3rX+PXv/71tMcODg7ive99LwDa648rtGc/c9GHli5dmv7ZLj43FdmfT7cNDOfsYC76T/Y2P2vWrJn22LVr16bTaI4cOcIVWg6AE5OlZVnGggULTut92fCQY84Z5cILLwRAXoldu3ZNeVz2/p4XXHDBrK5RW1uLsrKyCeeZjNdeew0AUF5ejpqamlldh3NmmIs+lM2LL76Id7/73dB1Hfn5+Xj++ecxf/78Ez4f58wy1/2H885jLvpQdXU1qqqqAACtra3TFntqbm5O/1xeXj6r63DmnrnoP9lKsq7r0x6radqk3+P832b9+vXpYlDTydKqqmLbtm3p7yiKMif3xxVazhnlXe96V/rnqTwXpmnid7/7HQAgGAzisssum9U1BEHAzTffDICsRvZAG8+2bdvSVqWbb76ZVyE9R5iLPmTz5ptv4uabb0YqlUJOTg7++te/jvGccM495qL/MMaO+6e6uhoAKS7271555ZUTeibO3DJXc9Btt90GAAiHw3jxxRenPO6RRx5J/2wrS5yzl7noP7W1temfX3/99WmPzVZWsr/H+b+N3+/HFVdcAQB44YUXpgyRf+SRRxAOhwEAt9xyy5zdHxiHc4a56KKLGAAmyzJ78803J3z+/e9/nwFgANg3vvGNCZ+//PLL6c/vvPPOSa/R0NDAJEliANi6detYPB4f83k8Hmfr1q1L38fRo0dPxaNx5oi56EO7d+9mwWCQAWBer5dt2bLlFD8F50wxF/3neFRXVzMArLq6+oS+zzmzzEUfamtrYy6XiwFgy5cvZ6FQaMIxv//979Pnuf7660/2sThzxOnuPyMjI8zj8TAAzO/3s3379k16H08//TQTRZEBYOXl5cwwjJN9NM4Z4NixY7Nek379619P28cYY+zFF19MH3PTTTcxXdfHfD4wMMCqqqoYABYMBtnw8PBJPsnM4bEEnDPOj3/8Y1xwwQVIJBK46qqr8I//+I+47LLLkEgk8PDDD+M//uM/AAD19fX48pe/fELXqK+vx1133YXvfe972LlzJy644AJ89atfxfz589Hc3IwHHngAu3fvBgDcddddcxbzzzk1nO4+1NzcjKuvvhqjo6MAgO985zvIycnBgQMHpvxOUVERioqKTuh5OHPLXMxBnHc2c9GHqqqq8K1vfQv/8A//gP3792PDhg346le/ihUrViAcDuORRx7Bz372MwBAIBDAv/zLv5yy5+OcXk53/wkGg7j77rtxzz33IBKJ4Pzzz8fnPvc5bN68Gbm5uejr68Pjjz+O//zP/4RpmgCA733ve+k9jTlnN1u2bEFTU1P634ODg+mfm5qa8Jvf/GbM8R/60IdO6DqXX3457rjjDjz88MN44oknsHnzZnzhC19AWVkZ9u/fj/vuuw/t7e0AqBhibm7uCV3nhJgz1ZnDmYYnnniCBQKBtOVn/J/6+nrW2Ng46Xdn6h0xDIN95CMfmfIaANhHP/pRbpE8RzmdfSjbcjnTP1NZODlnJ3MxB00H99Ce+8xVH7r77ruZIAhTXqeoqGhSLx/n7OZ09x/TNNkXvvCFafsOAKYoCvvBD35wGp+Uc6q58847ZyWfTMZMPLSMUUTjddddN+W5RVE8I/IPN71wzgpuvPFG7Nu3D1/84hdRX18Pj8eDYDCIdevWpb2ndXV1J3UNURTxq1/9Ck899RRuvvlmlJWVweFwoKysDDfffDOefvpp/PKXv+QWyXOUuehDnHcuvP9wTpa56kP3338/3njjDXzgAx9ATU0NnE4ncnJysH79enz729/G0aNHsWnTplPwRJy55HT3H0EQ8C//8i/YsWMHPvnJT2LZsmXw+/2QJAk5OTlYu3YtvvSlL+HAgQP4yle+cgqfjPNOwu1246mnnsKDDz6IzZs3o6ioCA6HA5WVlXjf+96HLVu24N57753z+xIYm6ZUHofD4XA4HA6Hw+FwOGcp3BXF4XA4HA6Hw+FwOJxzEq7QcjgcDofD4XA4HA7nnIQrtBwOh8PhcDgcDofDOSfhCi2Hw+FwOBwOh8PhcM5JuELL4XA4HA6Hw+FwOJxzEq7QcjgcDofD4XA4HA7nnIQrtBwOh8PhcDgcDofDOSfhCi2Hw+FwOBwOh8PhcM5JuELL4XA4HA6Hw+FwOJxzEq7QcjgcDofD4XA4HA7nnIQrtBwOh8PhcKbk3nvvhSAIEAQB995775m+HQ6Hw+FwxsAVWg6Hw+Fw3gG0tramFc9T9YcrsBwOh8M52+EKLYfD4XA4HA6Hw+FwzknkM30DHA6Hw+FwTp5AIIDPfOYz0x6zfft27NixAwBQVlaGW265ZdrjN2zYgO3bt5+ye+RwOBwO51QjMMbYmb4JDofD4XA4p597770X3/zmNwEAl1xyCV555ZUze0McDofD4ZwkPOSYw+FwOBwOh8PhcDjnJFyh5XA4HA6Hw+FwOBzOOQlXaDkcDofD4UzJTLbt+c1vfpM+5kMf+hAAwDRN/M///A+uvfZaVFZWwul0ori4GLfddhu2bt064RyqquL3v/89rrjiClRWVsLlcqGqqgp33nknDh8+PKt71jQNv//97/Hud78b8+bNg9/vh9frRW1tLd773vfi0UcfBc+44nA4nHcGvCgUh8PhcDicU8rg4CDe85734KWXXhrz+/7+fjzyyCN49NFH8atf/Qof/vCHAQBNTU246aabJiiuHR0d+N3vfoeHH34Yf/jDH/Cud73ruNd+5ZVX8LGPfQzNzc0TPmttbUVraysefvhhbNy4EX/+859RXl7+/7d3PyFR/GEcxz9rgYaaf8BEsNoSFczwz0FdQxMPdhGELmESS+jBUwQdQy/ejPDQIVDwIuLBVTxlZOJBTZfqoCCFYBKrkh7aVcHNdWs7/eZnmm3a5vqN9wsWnmGemXlmT/th58/RTxQAEHUEWgAAEDHBYFA3b97U+Pi44uLidP36dV24cEGfP3/W6OiofD6fQqGQmpqalJ2drZycHFVXV8vj8ejs2bOqrKxURkaGVldX9fLlS21tbSkQCOj27duam5vTpUuXDjx2f3+/GhoatLOzI0k6c+aMysrKZLfbFRMTo/n5eU1NTSkYDGp6eloOh0OvX79Wenr6cX09AIAII9ACAICIcblc2t7eVl1dnTo7O3Xu3DlrndfrVV1dncbHx/Xt2ze1trYqKSlJHo9Hzc3Nam9vV2JiotW/tLSkmpoavXv3Tn6/X21tberu7v7pcefm5uR0OrWzsyObzaYHDx7o4cOHSk5O/qHvw4cPcjqdmpiYkMfj0d27d/Xs2bO/8l0AAP4+7qEFAAARs729raqqKg0MDPwQZiUpJSVFPT09OnXqlCRpbGxMQ0NDcjqdevr06Q9hVpIyMzPV1dVlLbtcLgWDwZ8e9969e/L7/ZKkx48f69GjR/vCrCRdvnxZz58/V15eniRpeHhYbrf7yOcLAIguAi0AAIiojo4OK7TudfHiRZWXl1vLsbGxam9vP3Bf165d0/nz5yVJm5ubev/+/b6emZkZ637doqIi3b9//5fzxcfHq6WlxVru7e39ZT8A4OQi0AIAgIjJyspSYWHhL3uuXr1q1RUVFfv+yd0rPz/fqhcXF/et333JcH19vWw2W9g5q6urrXpiYiJsPwDgZOIeWgAAEDG7w+dBUlJSrPrKlSth+1NTU616Y2Nj3/rdrwEaGxvTx48fw+5z92t7PB5P2H4AwMlEoAUAABGTlJQUtuf06f9/fhy2/78nGO+2srJi1cPDw2H3t5fX6z30NgCAk4FLjgEAQMT8zuW+f9L/M+vr63+0/devX/94BgBAdBBoAQCA0eLj4616cHBQoVDo0B8AgJkItAAAwGjp6elW/enTpyhOAgA4bgRaAABgtNLSUquenJyM4iQAgONGoAUAAEarra216sHBQa2urkZxGgDAcSLQAgAAo5WUlKiqqkqS5Pf7defOHQUCgd/aNhAI8JRjADAYgRYAABjvyZMnSkhIkCSNjIyosrJSbrf7wP75+Xm1tbXJbrdzmTIAGIz30AIAAOPl5+err69Pt27d0tbWltxut8rKypSVlaXi4mKlpqbqy5cvWltb0+zsrJaXl6M9MgAgAgi0AADgn1BbW6tXr16psbFRb9++lSQtLCxoYWHhwG3sdrsyMzOPa0QAQIQRaAEAwD+joKBAb9680YsXLzQ0NKTJyUmtrKzI5/MpNjZWaWlpys3NVWlpqW7cuCGHwyGbzRbtsQEAR2QL8TZxAAAAAICBeCgUAAAAAMBIBFoAAAAAgJEItAAAAAAAIxFoAQAAAABGItACAAAAAIxEoAUAAAAAGIlACwAAAAAwEoEWAAAAAGAkAi0AAAAAwEgEWgAAAACAkQi0AAAAAAAjEWgBAAAAAEYi0AIAAAAAjESgBQAAAAAYiUALAAAAADASgRYAAAAAYKTvCxseS7nJpr4AAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from snudda.plotting.plot_traces import PlotTraces\n", + "pt = PlotTraces(output_file=sim_file, network_file=network_file)\n", + "# Use trace_id to specify which traces\n", + "ax = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "1c223754-f2f9-42eb-a8a0-d316af32c759", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving figure to network/d2oe-10/figures/spike-raster.png\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from snudda.plotting import SnuddaPlotSpikeRaster2\n", + "fig_file_raster = f\"spike-raster.png\"\n", + "\n", + "time_range_zoom = (0,1)\n", + "spr = SnuddaPlotSpikeRaster2(network_path=network_path,\n", + " network_file=network_file,\n", + " simulation_file=sim_file,\n", + " snudda_load=sl, snudda_simulation_load=sls)\n", + "\n", + "spr.plot_spike_raster(fig_file=fig_file_raster, time_range=time_range_zoom)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eff17e02-ddf2-48dc-a83c-bd4ea9331dd3", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/notebooks/schizophrenia/input.json b/examples/notebooks/schizophrenia/input.json new file mode 100644 index 000000000..1c312f93a --- /dev/null +++ b/examples/notebooks/schizophrenia/input.json @@ -0,0 +1,46 @@ +{ + "dSPN": { + "cortical": { + "generator": "poisson", + "type": "AMPA_NMDA", + "synapse_density": "1.15*0.05/(1+exp(-(d-30e-6)/5e-6))", + "num_inputs": 200, + "frequency": 2, + "population_unit_correlation": 0.0, + "jitter": 0.0, + "conductance": 5e-10, + "mod_file": "tmGlut", + "parameter_file": "$DATA/synapses/striatum/M1RH_Analysis_190925.h5-parameters-MS.json" + } + }, + + "iSPN": { + "cortical": { + "generator": "poisson", + "type": "AMPA_NMDA", + "synapse_density": "1.15*0.05/(1+exp(-(d-30e-6)/5e-6))", + "num_inputs": 200, + "frequency": 2, + "population_unit_correlation": 0.0, + "jitter": 0.0, + "conductance": 5e-10, + "mod_file": "tmGlut", + "parameter_file": "$DATA/synapses/striatum/M1RH_Analysis_190925.h5-parameters-MS.json" + } + }, + + "FS": { + "cortical": { + "generator": "poisson", + "type": "AMPA_NMDA", + "synapse_density": "1.15*0.05/(1+exp(-(d-30e-6)/5e-6))", + "num_inputs": 120, + "frequency": 2, + "population_unit_correlation": 0.0, + "jitter": 0.0, + "conductance": 5e-10, + "mod_file": "tmGlut", + "parameter_file": "$DATA/synapses/striatum/M1RH_Analysis_190925.h5-parameters-FS.json" + } + } +}