diff --git a/Dynamic_Shimming_in_the_Cervical_Spinal_Cord_for_Multi_Echo_Gradient_Echo_Imaging_at_3T_analysis.ipynb b/Dynamic_Shimming_in_the_Cervical_Spinal_Cord_for_Multi_Echo_Gradient_Echo_Imaging_at_3T_analysis.ipynb index 59dcebb..bbf978f 100644 --- a/Dynamic_Shimming_in_the_Cervical_Spinal_Cord_for_Multi_Echo_Gradient_Echo_Imaging_at_3T_analysis.ipynb +++ b/Dynamic_Shimming_in_the_Cervical_Spinal_Cord_for_Multi_Echo_Gradient_Echo_Imaging_at_3T_analysis.ipynb @@ -1,22 +1,4 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "Dynamic_Shimming_in_the_Cervical_Spinal_Cord_for_Multi_Echo_Gradient_Echo_Imaging_at_3T_analysis.ipynb", - "provenance": [], - "collapsed_sections": [], - "toc_visible": true, - "include_colab_link": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, "cells": [ { "cell_type": "markdown", @@ -30,6 +12,9 @@ }, { "cell_type": "markdown", + "metadata": { + "id": "0_y7C0a_kVhm" + }, "source": [ "##Introduction\n", "\n", @@ -55,78 +40,1037 @@ "Polytechnique Montreal\n", "\n", "2022" - ], - "metadata": { - "id": "0_y7C0a_kVhm" - } + ] }, { "cell_type": "markdown", - "source": [ - "# Setup" - ], "metadata": { "id": "La2O5vM5fny9" - } + }, + "source": [ + "# Setup" + ] }, { "cell_type": "markdown", + "metadata": { + "id": "UjPRdK9eftEO" + }, "source": [ "Here, we import the necessary libraries and install the necessary toolboxes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "QFyfZnHHU87d", + "outputId": "a98bee1b-2a2d-4e5c-abe0-87e67e47ca8d" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Necessary libraries imported\n" + ] + } + ], + "source": [ + "############ Importing libraries\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import nibabel as nib\n", + "import sys\n", + "import cv2\n", + "import re\n", + "import pandas as pd\n", + "from os.path import join\n", + "import glob\n", + "import zipfile\n", + "import shutil\n", + "import logging\n", + "import subprocess\n", + "import fnmatch\n", + "import pathlib\n", + "import json\n", + "import time\n", + "import seaborn as sns\n", + "import os\n", + "import scipy\n", + "from scipy import stats\n", + "from scipy.stats import mannwhitneyu\n", + "from statsmodels.stats.weightstats import ztest as ztest\n", + "from scipy.stats import bartlett\n", + "from scipy.stats import ansari\n", + "from scipy.stats import wilcoxon\n", + "from scipy.stats import kruskal\n", + "from scipy.stats import friedmanchisquare\n", + "from tabulate import tabulate\n", + "\n", + "print('Necessary libraries imported')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PYCvEAtuJZEI", + "outputId": "7a363775-ec12-4f37-db00-2f7d27b3cf05" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "fatal: destination path 'osfclient' already exists and is not an empty directory.\n", + "/content/osfclient\n", + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Requirement already satisfied: osfclient in /usr/local/lib/python3.7/dist-packages (0.0.5)\n", + "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from osfclient) (2.23.0)\n", + "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from osfclient) (1.15.0)\n", + "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from osfclient) (4.64.1)\n", + "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (3.0.4)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (2022.9.24)\n", + "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (2.10)\n", + "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (1.24.3)\n", + "OSF client installed\n", + "fatal: destination path 'spinalcordtoolbox' already exists and is not an empty directory.\n", + "/content/spinalcordtoolbox\n", + "\n", + "\u001b[0;32m\n", + "*******************************\n", + "* Welcome to SCT installation *\n", + "*******************************\n", + "\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mChecking OS type and version...\u001b[0m\n", + "\n", + "Linux 8028705384cd 5.10.133+ #1 SMP Fri Aug 26 08:44:51 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux\n", + "\n", + "\u001b[0;32mChecking requirements...\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mOK!\u001b[0m\n", + "\n", + "\n", + "SCT version ......... 5.3.0\n", + "Installation type ... in-place\n", + "Operating system .... linux (unknown)\n", + "Shell config ........ /root/.bashrc\n", + "\n", + "\u001b[0;92mTo improve user experience and fix bugs, the SCT development team is using a\n", + "report system to automatically receive crash reports and errors from users.\n", + "These reports are anonymous.\n", + "\n", + "Do you agree to help us improve SCT? [y]es/[n]o: \u001b[0m\n", + "\u001b[0;32m--> Crash reports will be sent to the SCT development team. Thank you!\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mSCT will be installed here: [/content/spinalcordtoolbox]\u001b[0m\n", + "\n", + "\n", + "\u001b[0;92m\n", + "Do you agree? [y]es/[n]o: \u001b[0m\n", + "\u001b[0;92mDo you want to add the sct_* scripts to your PATH environment? [y]es/[n]o: \u001b[0m\n", + "\u001b[0;32mSkipping copy of source files (source and destination folders are the same)\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mInstalling conda...\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34mrm -rf /content/spinalcordtoolbox/python\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34mmkdir -p /content/spinalcordtoolbox/python\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34mwget -O /tmp/tmp.yf99pMypwy/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\u001b[0m\n", + "\n", + "--2022-10-30 00:23:46-- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n", + "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.131.3, 104.16.130.3, 2606:4700::6810:8203, ...\n", + "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.131.3|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 76607678 (73M) [application/x-sh]\n", + "Saving to: ‘/tmp/tmp.yf99pMypwy/miniconda.sh’\n", + "\n", + "/tmp/tmp.yf99pMypwy 100%[===================>] 73.06M 71.0MB/s in 1.0s \n", + "\n", + "2022-10-30 00:23:47 (71.0 MB/s) - ‘/tmp/tmp.yf99pMypwy/miniconda.sh’ saved [76607678/76607678]\n", + "\n", + "\n", + "\u001b[0;34mbash /tmp/tmp.yf99pMypwy/miniconda.sh -p /content/spinalcordtoolbox/python -b -f\u001b[0m\n", + "\n", + "PREFIX=/content/spinalcordtoolbox/python\n", + "Unpacking payload ...\n", + "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\bdone\n", + "Solving environment: - \b\b\\ \b\b| \b\bdone\n", + "\n", + "## Package Plan ##\n", + "\n", + " environment location: /content/spinalcordtoolbox/python\n", + "\n", + " added / updated specs:\n", + " - _libgcc_mutex==0.1=main\n", + " - _openmp_mutex==4.5=1_gnu\n", + " - brotlipy==0.7.0=py39h27cfd23_1003\n", + " - ca-certificates==2022.3.29=h06a4308_1\n", + " - certifi==2021.10.8=py39h06a4308_2\n", + " - cffi==1.15.0=py39hd667e15_1\n", + " - charset-normalizer==2.0.4=pyhd3eb1b0_0\n", + " - colorama==0.4.4=pyhd3eb1b0_0\n", + " - conda-content-trust==0.1.1=pyhd3eb1b0_0\n", + " - conda-package-handling==1.8.1=py39h7f8727e_0\n", + " - conda==4.12.0=py39h06a4308_0\n", + " - cryptography==36.0.0=py39h9ce1e76_0\n", + " - idna==3.3=pyhd3eb1b0_0\n", + " - ld_impl_linux-64==2.35.1=h7274673_9\n", + " - libffi==3.3=he6710b0_2\n", + " - libgcc-ng==9.3.0=h5101ec6_17\n", + " - libgomp==9.3.0=h5101ec6_17\n", + " - libstdcxx-ng==9.3.0=hd4cf53a_17\n", + " - ncurses==6.3=h7f8727e_2\n", + " - openssl==1.1.1n=h7f8727e_0\n", + " - pip==21.2.4=py39h06a4308_0\n", + " - pycosat==0.6.3=py39h27cfd23_0\n", + " - pycparser==2.21=pyhd3eb1b0_0\n", + " - pyopenssl==22.0.0=pyhd3eb1b0_0\n", + " - pysocks==1.7.1=py39h06a4308_0\n", + " - python==3.9.12=h12debd9_0\n", + " - readline==8.1.2=h7f8727e_1\n", + " - requests==2.27.1=pyhd3eb1b0_0\n", + " - ruamel_yaml==0.15.100=py39h27cfd23_0\n", + " - setuptools==61.2.0=py39h06a4308_0\n", + " - six==1.16.0=pyhd3eb1b0_1\n", + " - sqlite==3.38.2=hc218d9a_0\n", + " - tk==8.6.11=h1ccaba5_0\n", + " - tqdm==4.63.0=pyhd3eb1b0_0\n", + " - tzdata==2022a=hda174b7_0\n", + " - urllib3==1.26.8=pyhd3eb1b0_0\n", + " - wheel==0.37.1=pyhd3eb1b0_0\n", + " - xz==5.2.5=h7b6447c_0\n", + " - yaml==0.2.5=h7b6447c_0\n", + " - zlib==1.2.12=h7f8727e_1\n", + "\n", + "\n", + "The following NEW packages will be INSTALLED:\n", + "\n", + " _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main\n", + " _openmp_mutex pkgs/main/linux-64::_openmp_mutex-4.5-1_gnu\n", + " brotlipy pkgs/main/linux-64::brotlipy-0.7.0-py39h27cfd23_1003\n", + " ca-certificates pkgs/main/linux-64::ca-certificates-2022.3.29-h06a4308_1\n", + " certifi pkgs/main/linux-64::certifi-2021.10.8-py39h06a4308_2\n", + " cffi pkgs/main/linux-64::cffi-1.15.0-py39hd667e15_1\n", + " charset-normalizer pkgs/main/noarch::charset-normalizer-2.0.4-pyhd3eb1b0_0\n", + " colorama pkgs/main/noarch::colorama-0.4.4-pyhd3eb1b0_0\n", + " conda pkgs/main/linux-64::conda-4.12.0-py39h06a4308_0\n", + " conda-content-tru~ pkgs/main/noarch::conda-content-trust-0.1.1-pyhd3eb1b0_0\n", + " conda-package-han~ pkgs/main/linux-64::conda-package-handling-1.8.1-py39h7f8727e_0\n", + " cryptography pkgs/main/linux-64::cryptography-36.0.0-py39h9ce1e76_0\n", + " idna pkgs/main/noarch::idna-3.3-pyhd3eb1b0_0\n", + " ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.35.1-h7274673_9\n", + " libffi pkgs/main/linux-64::libffi-3.3-he6710b0_2\n", + " libgcc-ng pkgs/main/linux-64::libgcc-ng-9.3.0-h5101ec6_17\n", + " libgomp pkgs/main/linux-64::libgomp-9.3.0-h5101ec6_17\n", + " libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-9.3.0-hd4cf53a_17\n", + " ncurses pkgs/main/linux-64::ncurses-6.3-h7f8727e_2\n", + " openssl pkgs/main/linux-64::openssl-1.1.1n-h7f8727e_0\n", + " pip pkgs/main/linux-64::pip-21.2.4-py39h06a4308_0\n", + " pycosat pkgs/main/linux-64::pycosat-0.6.3-py39h27cfd23_0\n", + " pycparser pkgs/main/noarch::pycparser-2.21-pyhd3eb1b0_0\n", + " pyopenssl pkgs/main/noarch::pyopenssl-22.0.0-pyhd3eb1b0_0\n", + " pysocks pkgs/main/linux-64::pysocks-1.7.1-py39h06a4308_0\n", + " python pkgs/main/linux-64::python-3.9.12-h12debd9_0\n", + " readline pkgs/main/linux-64::readline-8.1.2-h7f8727e_1\n", + " requests pkgs/main/noarch::requests-2.27.1-pyhd3eb1b0_0\n", + " ruamel_yaml pkgs/main/linux-64::ruamel_yaml-0.15.100-py39h27cfd23_0\n", + " setuptools pkgs/main/linux-64::setuptools-61.2.0-py39h06a4308_0\n", + " six pkgs/main/noarch::six-1.16.0-pyhd3eb1b0_1\n", + " sqlite pkgs/main/linux-64::sqlite-3.38.2-hc218d9a_0\n", + " tk pkgs/main/linux-64::tk-8.6.11-h1ccaba5_0\n", + " tqdm pkgs/main/noarch::tqdm-4.63.0-pyhd3eb1b0_0\n", + " tzdata pkgs/main/noarch::tzdata-2022a-hda174b7_0\n", + " urllib3 pkgs/main/noarch::urllib3-1.26.8-pyhd3eb1b0_0\n", + " wheel pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0\n", + " xz pkgs/main/linux-64::xz-5.2.5-h7b6447c_0\n", + " yaml pkgs/main/linux-64::yaml-0.2.5-h7b6447c_0\n", + " zlib pkgs/main/linux-64::zlib-1.2.12-h7f8727e_1\n", + "\n", + "\n", + "Preparing transaction: - \b\b\\ \b\b| \b\b/ \b\bdone\n", + "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", + "installation finished.\n", + "WARNING:\n", + " You currently have a PYTHONPATH environment variable set. This may cause\n", + " unexpected behavior when running the Python interpreter in Miniconda3.\n", + " For best results, please verify that your PYTHONPATH only points to\n", + " directories of packages that are compatible with the Python interpreter\n", + " in Miniconda3: /content/spinalcordtoolbox/python\n", + "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n", + "Solving environment: - \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n", + "Collecting package metadata (repodata.json): | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", + "Solving environment: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", + "\n", + "\n", + "==> WARNING: A newer version of conda exists. <==\n", + " current version: 4.12.0\n", + " latest version: 22.9.0\n", + "\n", + "Please update conda by running\n", + "\n", + " $ conda update -n base -c defaults conda\n", + "\n", + "\n", + "\n", + "## Package Plan ##\n", + "\n", + " environment location: /content/spinalcordtoolbox/python/envs/venv_sct\n", + "\n", + " added / updated specs:\n", + " - python=3.6\n", + "\n", + "\n", + "The following packages will be downloaded:\n", + "\n", + " package | build\n", + " ---------------------------|-----------------\n", + " _openmp_mutex-5.1 | 1_gnu 21 KB\n", + " ca-certificates-2022.10.11 | h06a4308_0 124 KB\n", + " certifi-2021.5.30 | py36h06a4308_0 139 KB\n", + " ld_impl_linux-64-2.38 | h1181459_1 654 KB\n", + " libgcc-ng-11.2.0 | h1234567_1 5.3 MB\n", + " libgomp-11.2.0 | h1234567_1 474 KB\n", + " libstdcxx-ng-11.2.0 | h1234567_1 4.7 MB\n", + " ncurses-6.3 | h5eee18b_3 781 KB\n", + " openssl-1.1.1q | h7f8727e_0 2.5 MB\n", + " pip-21.2.2 | py36h06a4308_0 1.8 MB\n", + " python-3.6.13 | h12debd9_1 32.5 MB\n", + " readline-8.2 | h5eee18b_0 357 KB\n", + " setuptools-58.0.4 | py36h06a4308_0 788 KB\n", + " sqlite-3.39.3 | h5082296_0 1.1 MB\n", + " tk-8.6.12 | h1ccaba5_0 3.0 MB\n", + " xz-5.2.6 | h5eee18b_0 394 KB\n", + " zlib-1.2.13 | h5eee18b_0 103 KB\n", + " ------------------------------------------------------------\n", + " Total: 54.7 MB\n", + "\n", + "The following NEW packages will be INSTALLED:\n", + "\n", + " _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main\n", + " _openmp_mutex pkgs/main/linux-64::_openmp_mutex-5.1-1_gnu\n", + " ca-certificates pkgs/main/linux-64::ca-certificates-2022.10.11-h06a4308_0\n", + " certifi pkgs/main/linux-64::certifi-2021.5.30-py36h06a4308_0\n", + " ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.38-h1181459_1\n", + " libffi pkgs/main/linux-64::libffi-3.3-he6710b0_2\n", + " libgcc-ng pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1\n", + " libgomp pkgs/main/linux-64::libgomp-11.2.0-h1234567_1\n", + " libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1\n", + " ncurses pkgs/main/linux-64::ncurses-6.3-h5eee18b_3\n", + " openssl pkgs/main/linux-64::openssl-1.1.1q-h7f8727e_0\n", + " pip pkgs/main/linux-64::pip-21.2.2-py36h06a4308_0\n", + " python pkgs/main/linux-64::python-3.6.13-h12debd9_1\n", + " readline pkgs/main/linux-64::readline-8.2-h5eee18b_0\n", + " setuptools pkgs/main/linux-64::setuptools-58.0.4-py36h06a4308_0\n", + " sqlite pkgs/main/linux-64::sqlite-3.39.3-h5082296_0\n", + " tk pkgs/main/linux-64::tk-8.6.12-h1ccaba5_0\n", + " wheel pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0\n", + " xz pkgs/main/linux-64::xz-5.2.6-h5eee18b_0\n", + " zlib pkgs/main/linux-64::zlib-1.2.13-h5eee18b_0\n", + "\n", + "\n", + "\n", + "Downloading and Extracting Packages\n", + "zlib-1.2.13 | 103 KB | : 100% 1.0/1 [00:00<00:00, 5.98it/s] \n", + "sqlite-3.39.3 | 1.1 MB | : 100% 1.0/1 [00:00<00:00, 7.88it/s]\n", + "ncurses-6.3 | 781 KB | : 100% 1.0/1 [00:00<00:00, 3.50it/s]\n", + "openssl-1.1.1q | 2.5 MB | : 100% 1.0/1 [00:00<00:00, 5.79it/s]\n", + "libstdcxx-ng-11.2.0 | 4.7 MB | : 100% 1.0/1 [00:00<00:00, 4.83it/s]\n", + "certifi-2021.5.30 | 139 KB | : 100% 1.0/1 [00:00<00:00, 11.86it/s]\n", + "xz-5.2.6 | 394 KB | : 100% 1.0/1 [00:00<00:00, 10.69it/s]\n", + "libgomp-11.2.0 | 474 KB | : 100% 1.0/1 [00:00<00:00, 10.47it/s]\n", + "readline-8.2 | 357 KB | : 100% 1.0/1 [00:00<00:00, 12.26it/s]\n", + "tk-8.6.12 | 3.0 MB | : 100% 1.0/1 [00:00<00:00, 4.50it/s]\n", + "setuptools-58.0.4 | 788 KB | : 100% 1.0/1 [00:00<00:00, 8.50it/s]\n", + "libgcc-ng-11.2.0 | 5.3 MB | : 100% 1.0/1 [00:00<00:00, 4.30it/s]\n", + "python-3.6.13 | 32.5 MB | : 100% 1.0/1 [00:04<00:00, 4.79s/it] \n", + "ld_impl_linux-64-2.3 | 654 KB | : 100% 1.0/1 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indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Looking in links: https://download.pytorch.org/whl/cpu/torch_stable.html\n", + "Ignoring torch: markers 'sys_platform == \"darwin\"' don't match your environment\n", + "Ignoring torchvision: markers 'sys_platform == \"darwin\"' don't match your environment\n", + "Collecting absl-py==0.12.0\n", + " Downloading absl_py-0.12.0-py3-none-any.whl (129 kB)\n", + "\u001b[K |████████████████████████████████| 129 kB 7.6 MB/s \n", + "\u001b[?25hCollecting appdirs==1.4.4\n", + " Downloading appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB)\n", + "Collecting attrs==20.3.0\n", + " Downloading attrs-20.3.0-py2.py3-none-any.whl (49 kB)\n", + "\u001b[K |████████████████████████████████| 49 kB 7.1 MB/s \n", + "\u001b[?25hCollecting bids-neuropoly==0.2\n", + " Downloading bids_neuropoly-0.2-py3-none-any.whl (3.1 kB)\n", + "Collecting bids-validator==1.7.1\n", + " Downloading bids_validator-1.7.1-py2.py3-none-any.whl (19 kB)\n", + "Collecting bleach==1.5.0\n", + " Downloading bleach-1.5.0-py2.py3-none-any.whl (17 kB)\n", + "Collecting cachetools==4.2.1\n", + " Downloading cachetools-4.2.1-py3-none-any.whl (12 kB)\n", + "Collecting certifi==2020.12.5\n", + " Downloading certifi-2020.12.5-py2.py3-none-any.whl (147 kB)\n", + "\u001b[K |████████████████████████████████| 147 kB 54.3 MB/s \n", + "\u001b[?25hCollecting cffi==1.14.5\n", + " Downloading cffi-1.14.5-cp36-cp36m-manylinux1_x86_64.whl (401 kB)\n", + "\u001b[K |████████████████████████████████| 401 kB 55.1 MB/s \n", + "\u001b[?25hCollecting cfgv==3.2.0\n", + " Downloading cfgv-3.2.0-py2.py3-none-any.whl (7.3 kB)\n", + "Collecting chardet==4.0.0\n", + " Downloading chardet-4.0.0-py2.py3-none-any.whl (178 kB)\n", + "\u001b[K |████████████████████████████████| 178 kB 76.1 MB/s \n", + "\u001b[?25hCollecting click==7.1.2\n", + " Downloading click-7.1.2-py2.py3-none-any.whl (82 kB)\n", + "\u001b[K |████████████████████████████████| 82 kB 1.4 MB/s \n", + "\u001b[?25hCollecting colored==1.4.2\n", + " Downloading colored-1.4.2.tar.gz (56 kB)\n", + "\u001b[K |████████████████████████████████| 56 kB 5.3 MB/s \n", + "\u001b[?25hCollecting coverage==5.5\n", + " Downloading coverage-5.5-cp36-cp36m-manylinux2010_x86_64.whl (240 kB)\n", + "\u001b[K |████████████████████████████████| 240 kB 59.5 MB/s \n", + "\u001b[?25hCollecting cryptography==3.4.7\n", + " Downloading cryptography-3.4.7-cp36-abi3-manylinux2014_x86_64.whl (3.2 MB)\n", + "\u001b[K |████████████████████████████████| 3.2 MB 43.6 MB/s \n", + "\u001b[?25hCollecting csv-diff==1.1\n", + " Downloading csv_diff-1.1-py3-none-any.whl (12 kB)\n", + "Collecting cycler==0.10.0\n", + " Downloading cycler-0.10.0-py2.py3-none-any.whl (6.5 kB)\n", + "Collecting decorator==4.4.2\n", + " Downloading decorator-4.4.2-py2.py3-none-any.whl (9.2 kB)\n", + "Collecting dictdiffer==0.8.1\n", + " Downloading dictdiffer-0.8.1-py2.py3-none-any.whl (16 kB)\n", + "Collecting dipy==1.4.0\n", + " Downloading dipy-1.4.0-cp36-cp36m-manylinux2010_x86_64.whl (7.7 MB)\n", + "\u001b[K |████████████████████████████████| 7.7 MB 62.6 MB/s \n", + "\u001b[?25hCollecting distlib==0.3.1\n", + " Downloading distlib-0.3.1-py2.py3-none-any.whl (335 kB)\n", + "\u001b[K |████████████████████████████████| 335 kB 73.4 MB/s \n", + "\u001b[?25hCollecting docopt==0.6.2\n", + " Downloading docopt-0.6.2.tar.gz (25 kB)\n", + "Collecting docutils==0.17.1\n", + " Downloading docutils-0.17.1-py2.py3-none-any.whl (575 kB)\n", + "\u001b[K |████████████████████████████████| 575 kB 60.5 MB/s \n", + "\u001b[?25hCollecting filelock==3.0.12\n", + " Downloading filelock-3.0.12-py3-none-any.whl (7.6 kB)\n", + "Collecting future==0.18.2\n", + " Downloading future-0.18.2.tar.gz (829 kB)\n", + "\u001b[K |████████████████████████████████| 829 kB 68.4 MB/s \n", + "\u001b[?25hCollecting futures==3.1.1\n", + " Downloading futures-3.1.1-py3-none-any.whl (2.8 kB)\n", + "Collecting google-auth==1.29.0\n", + " Downloading google_auth-1.29.0-py2.py3-none-any.whl (142 kB)\n", + "\u001b[K |████████████████████████████████| 142 kB 60.7 MB/s \n", + "\u001b[?25hCollecting google-auth-oauthlib==0.4.4\n", + " Downloading google_auth_oauthlib-0.4.4-py2.py3-none-any.whl (18 kB)\n", + "Collecting grpcio==1.37.0\n", + " Downloading grpcio-1.37.0-cp36-cp36m-manylinux2014_x86_64.whl (4.2 MB)\n", + "\u001b[K |████████████████████████████████| 4.2 MB 38.0 MB/s \n", + "\u001b[?25hCollecting h5py==2.10.0\n", + " Downloading h5py-2.10.0-cp36-cp36m-manylinux1_x86_64.whl (2.9 MB)\n", + "\u001b[K |████████████████████████████████| 2.9 MB 35.8 MB/s \n", + "\u001b[?25hCollecting html5lib==0.9999999\n", + " Downloading html5lib-0.9999999.tar.gz (889 kB)\n", + "\u001b[K |████████████████████████████████| 889 kB 47.2 MB/s \n", + "\u001b[?25hCollecting identify==2.2.4\n", + " Downloading identify-2.2.4-py2.py3-none-any.whl (98 kB)\n", + "\u001b[K |████████████████████████████████| 98 kB 8.3 MB/s \n", + "\u001b[?25hCollecting idna==2.10\n", + " Downloading idna-2.10-py2.py3-none-any.whl (58 kB)\n", + "\u001b[K |████████████████████████████████| 58 kB 5.8 MB/s \n", + "\u001b[?25hCollecting imageio==2.9.0\n", + " Downloading imageio-2.9.0-py3-none-any.whl (3.3 MB)\n", + "\u001b[K |████████████████████████████████| 3.3 MB 38.5 MB/s \n", + "\u001b[?25hCollecting importlib-metadata==4.0.1\n", + " Downloading importlib_metadata-4.0.1-py3-none-any.whl (16 kB)\n", + "Collecting importlib-resources==5.1.2\n", + " Downloading importlib_resources-5.1.2-py3-none-any.whl (25 kB)\n", + "Collecting iniconfig==1.1.1\n", + " Downloading iniconfig-1.1.1-py2.py3-none-any.whl (5.0 kB)\n", + "Collecting ivadomed==2.7.4\n", + " Downloading ivadomed-2.7.4-py3-none-any.whl (155 kB)\n", + "\u001b[K |████████████████████████████████| 155 kB 46.0 MB/s \n", + "\u001b[?25hCollecting joblib==1.0.1\n", + " Downloading joblib-1.0.1-py3-none-any.whl (303 kB)\n", + "\u001b[K |████████████████████████████████| 303 kB 76.6 MB/s \n", + "\u001b[?25hCollecting jsonpointer==2.1\n", + " Downloading jsonpointer-2.1-py2.py3-none-any.whl (7.4 kB)\n", + "Collecting Keras==2.1.5\n", + " Downloading Keras-2.1.5-py2.py3-none-any.whl (334 kB)\n", + "\u001b[K |████████████████████████████████| 334 kB 76.7 MB/s \n", + "\u001b[?25hCollecting kiwisolver==1.3.1\n", + " Downloading kiwisolver-1.3.1-cp36-cp36m-manylinux1_x86_64.whl (1.1 MB)\n", + "\u001b[K |████████████████████████████████| 1.1 MB 66.6 MB/s \n", + "\u001b[?25hCollecting Markdown==3.3.4\n", + " Downloading Markdown-3.3.4-py3-none-any.whl (97 kB)\n", + "\u001b[K |████████████████████████████████| 97 kB 5.9 MB/s \n", + "\u001b[?25hCollecting matplotlib==3.3.4\n", + " Downloading matplotlib-3.3.4-cp36-cp36m-manylinux1_x86_64.whl (11.5 MB)\n", + "\u001b[K |████████████████████████████████| 11.5 MB 44.4 MB/s \n", + "\u001b[?25hCollecting mock==4.0.3\n", + " Downloading mock-4.0.3-py3-none-any.whl (28 kB)\n", + "Collecting networkx==2.5.1\n", + " Downloading networkx-2.5.1-py3-none-any.whl (1.6 MB)\n", + "\u001b[K |████████████████████████████████| 1.6 MB 55.7 MB/s \n", + "\u001b[?25hCollecting nibabel==3.2.1\n", + " Downloading nibabel-3.2.1-py3-none-any.whl (3.3 MB)\n", + "\u001b[K |████████████████████████████████| 3.3 MB 48.4 MB/s \n", + "\u001b[?25hCollecting nodeenv==1.6.0\n", + " Downloading nodeenv-1.6.0-py2.py3-none-any.whl (21 kB)\n", + "Collecting num2words==0.5.10\n", + " Downloading num2words-0.5.10-py3-none-any.whl (101 kB)\n", + "\u001b[K |████████████████████████████████| 101 kB 13.1 MB/s \n", + "\u001b[?25hCollecting numpy==1.19.5\n", + " Downloading numpy-1.19.5-cp36-cp36m-manylinux2010_x86_64.whl (14.8 MB)\n", + "\u001b[K |████████████████████████████████| 14.8 MB 376 kB/s \n", + "\u001b[?25hCollecting oauthlib==3.1.0\n", + " Downloading oauthlib-3.1.0-py2.py3-none-any.whl (147 kB)\n", + "\u001b[K |████████████████████████████████| 147 kB 78.3 MB/s \n", + "\u001b[?25hCollecting onnxruntime==1.4.0\n", + " Downloading onnxruntime-1.4.0-cp36-cp36m-manylinux2010_x86_64.whl (4.4 MB)\n", + "\u001b[K |████████████████████████████████| 4.4 MB 39.1 MB/s \n", + "\u001b[?25hCollecting packaging==20.9\n", + " Downloading packaging-20.9-py2.py3-none-any.whl (40 kB)\n", + "\u001b[K |████████████████████████████████| 40 kB 6.6 MB/s \n", + "\u001b[?25hCollecting pandas==1.1.5\n", + " Downloading pandas-1.1.5-cp36-cp36m-manylinux1_x86_64.whl (9.5 MB)\n", + "\u001b[K |████████████████████████████████| 9.5 MB 57.5 MB/s \n", + "\u001b[?25hCollecting patsy==0.5.1\n", + " Downloading patsy-0.5.1-py2.py3-none-any.whl (231 kB)\n", + "\u001b[K |████████████████████████████████| 231 kB 62.2 MB/s \n", + "\u001b[?25hCollecting Pillow==8.2.0\n", + " Downloading Pillow-8.2.0-cp36-cp36m-manylinux1_x86_64.whl (3.0 MB)\n", + "\u001b[K |████████████████████████████████| 3.0 MB 44.8 MB/s \n", + "\u001b[?25hCollecting pluggy==0.13.1\n", + " Downloading pluggy-0.13.1-py2.py3-none-any.whl (18 kB)\n", + "Collecting pre-commit==2.10.1\n", + " Downloading pre_commit-2.10.1-py2.py3-none-any.whl (185 kB)\n", + "\u001b[K |████████████████████████████████| 185 kB 80.1 MB/s \n", + "\u001b[?25hCollecting protobuf==3.15.8\n", + " Downloading protobuf-3.15.8-cp36-cp36m-manylinux1_x86_64.whl (1.0 MB)\n", + "\u001b[K |████████████████████████████████| 1.0 MB 55.4 MB/s \n", + "\u001b[?25hCollecting psutil==5.8.0\n", + " Downloading psutil-5.8.0-cp36-cp36m-manylinux2010_x86_64.whl (291 kB)\n", + "\u001b[K |████████████████████████████████| 291 kB 61.4 MB/s \n", + "\u001b[?25hCollecting py==1.10.0\n", + " Downloading py-1.10.0-py2.py3-none-any.whl (97 kB)\n", + "\u001b[K |████████████████████████████████| 97 kB 9.0 MB/s \n", + "\u001b[?25hCollecting pyasn1==0.4.8\n", + " Downloading pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)\n", + "\u001b[K |████████████████████████████████| 77 kB 6.5 MB/s \n", + "\u001b[?25hCollecting pyasn1-modules==0.2.8\n", + " Downloading pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 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requirements-parser-0.2.0.tar.gz (6.3 kB)\n", + "Collecting rsa==4.7.2\n", + " Downloading rsa-4.7.2-py3-none-any.whl (34 kB)\n", + "Collecting scikit-image==0.17.2\n", + " Downloading scikit_image-0.17.2-cp36-cp36m-manylinux1_x86_64.whl (12.4 MB)\n", + "\u001b[K |████████████████████████████████| 12.4 MB 47.5 MB/s \n", + "\u001b[?25hCollecting scikit-learn==0.24.1\n", + " Downloading scikit_learn-0.24.1-cp36-cp36m-manylinux2010_x86_64.whl (22.2 MB)\n", + "\u001b[K |████████████████████████████████| 22.2 MB 118.9 MB/s \n", + "\u001b[?25hCollecting scipy==1.5.4\n", + " Downloading scipy-1.5.4-cp36-cp36m-manylinux1_x86_64.whl (25.9 MB)\n", + "\u001b[K |████████████████████████████████| 25.9 MB 1.5 MB/s \n", + "\u001b[?25hCollecting seaborn==0.11.1\n", + " Downloading seaborn-0.11.1-py3-none-any.whl (285 kB)\n", + "\u001b[K |████████████████████████████████| 285 kB 63.3 MB/s \n", + "\u001b[?25hCollecting six==1.15.0\n", + " Downloading six-1.15.0-py2.py3-none-any.whl (10 kB)\n", + 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urllib3==1.26.4\n", + " Downloading urllib3-1.26.4-py2.py3-none-any.whl (153 kB)\n", + "\u001b[K |████████████████████████████████| 153 kB 63.1 MB/s \n", + "\u001b[?25hCollecting virtualenv==20.4.4\n", + " Downloading virtualenv-20.4.4-py2.py3-none-any.whl (7.2 MB)\n", + "\u001b[K |████████████████████████████████| 7.2 MB 43.9 MB/s \n", + "\u001b[?25hCollecting Werkzeug==1.0.1\n", + " Downloading Werkzeug-1.0.1-py2.py3-none-any.whl (298 kB)\n", + "\u001b[K |████████████████████████████████| 298 kB 42.7 MB/s \n", + "\u001b[?25hCollecting wquantiles==0.5\n", + " Downloading wquantiles-0.5.tar.gz (3.6 kB)\n", + "Collecting xlwt==1.3.0\n", + " Downloading xlwt-1.3.0-py2.py3-none-any.whl (99 kB)\n", + "\u001b[K |████████████████████████████████| 99 kB 13.1 MB/s \n", + "\u001b[?25hCollecting zipp==3.4.1\n", + " Downloading zipp-3.4.1-py3-none-any.whl (5.2 kB)\n", + "Collecting torch==1.5.0+cpu\n", + " Downloading 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filename=sphinx_jsonschema-1.16.8-py3-none-any.whl size=12621 sha256=fc84260bd444a7eb0ded957c75cf4a240ef86f8b2a7b3efa2325bf68d617376f\n", + " Stored in directory: /root/.cache/pip/wheels/52/f6/cc/50e111efd872dab6b56a1717e4ec81f6624b28dfb046fe5ca6\n", + " Building wheel for transforms3d (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for transforms3d: filename=transforms3d-0.3.1-py3-none-any.whl size=59373 sha256=af6fa551b0434e88db0ebbfe02fd352a7fd72162a850af2fa47991bf11d9ea14\n", + " Stored in directory: /root/.cache/pip/wheels/be/7a/eb/465e9bb085af816c4d504821d542cc0059cc3433f6e8edea3c\n", + " Building wheel for wquantiles (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for wquantiles: filename=wquantiles-0.5-py3-none-any.whl size=2508 sha256=f821a9b7946866c60fb805065b751ae1f64974b55da0f1e4eb307ed1df743b8d\n", + " Stored in directory: /root/.cache/pip/wheels/ee/ba/d5/bbbdc6118df5bb4ef1c56910c3c41a9af8001191bc1849e3c4\n", + "Successfully built colored docopt future html5lib pytest-console-scripts requirements-parser sphinx-jsonschema transforms3d wquantiles\n", + "Installing collected packages: zipp, urllib3, typing-extensions, six, pyparsing, pyasn1, idna, chardet, certifi, rsa, requests, pytz, python-dateutil, pyasn1-modules, packaging, oauthlib, numpy, importlib-metadata, docopt, cachetools, toml, SQLAlchemy, scipy, requests-oauthlib, pycparser, py, pluggy, Pillow, patsy, pandas, num2words, nibabel, kiwisolver, iniconfig, importlib-resources, html5lib, google-auth, future, filelock, distlib, decorator, cycler, click, bids-validator, attrs, appdirs, Werkzeug, virtualenv, torch, tifffile, threadpoolctl, tensorboard-plugin-wit, tensorboard-data-server, PyYAML, PyWavelets, pytest, pybids, protobuf, nodeenv, networkx, mock, matplotlib, Markdown, jsonpointer, joblib, imageio, identify, grpcio, google-auth-oauthlib, docutils, dictdiffer, cfgv, cffi, bleach, absl-py, tqdm, torchvision, tensorflow-tensorboard, tensorboard, sphinx-jsonschema, seaborn, scikit-learn, scikit-image, pytest-ordering, pytest-console-scripts, PyQt5-sip, pre-commit, onnxruntime, h5py, csv-diff, cryptography, coverage, bids-neuropoly, xlwt, wquantiles, transforms3d, tensorflow, requirements-parser, raven, pytest-cov, PyQt5, pyOpenSSL, psutil, Keras, ivadomed, futures, dipy, colored\n", + " Attempting uninstall: certifi\n", + " Found existing installation: certifi 2021.5.30\n", + " Uninstalling certifi-2021.5.30:\n", + " Successfully uninstalled certifi-2021.5.30\n", + "Successfully installed Keras-2.1.5 Markdown-3.3.4 Pillow-8.2.0 PyQt5-5.11.3 PyQt5-sip-4.19.19 PyWavelets-1.1.1 PyYAML-5.4.1 SQLAlchemy-1.3.24 Werkzeug-1.0.1 absl-py-0.12.0 appdirs-1.4.4 attrs-20.3.0 bids-neuropoly-0.2 bids-validator-1.7.1 bleach-1.5.0 cachetools-4.2.1 certifi-2020.12.5 cffi-1.14.5 cfgv-3.2.0 chardet-4.0.0 click-7.1.2 colored-1.4.2 coverage-5.5 cryptography-3.4.7 csv-diff-1.1 cycler-0.10.0 decorator-4.4.2 dictdiffer-0.8.1 dipy-1.4.0 distlib-0.3.1 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tensorboard-data-server-0.6.0 tensorboard-plugin-wit-1.8.0 tensorflow-1.5.0 tensorflow-tensorboard-1.5.1 threadpoolctl-2.1.0 tifffile-2020.9.3 toml-0.10.2 torch-1.5.0+cpu torchvision-0.6.0+cpu tqdm-4.60.0 transforms3d-0.3.1 typing-extensions-3.7.4.3 urllib3-1.26.4 virtualenv-20.4.4 wquantiles-0.5 xlwt-1.3.0 zipp-3.4.1\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", + "Found existing installation: tensorflow-tensorboard 1.5.1\n", + "Uninstalling tensorflow-tensorboard-1.5.1:\n", + " Successfully uninstalled tensorflow-tensorboard-1.5.1\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", + "Found existing installation: tensorboard 2.5.0\n", + "Uninstalling tensorboard-2.5.0:\n", + " Successfully uninstalled tensorboard-2.5.0\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Collecting tensorboard\n", + " Downloading tensorboard-2.10.1-py3-none-any.whl (5.9 MB)\n", + "\u001b[K |████████████████████████████████| 5.9 MB 8.7 MB/s \n", + "\u001b[?25hRequirement already satisfied: numpy>=1.12.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.19.5)\n", + "Requirement already satisfied: werkzeug>=1.0.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.0.1)\n", + "Requirement already satisfied: markdown>=2.6.8 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (3.3.4)\n", + "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.4.4)\n", + "Requirement already satisfied: requests<3,>=2.21.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (2.25.1)\n", + "Requirement already satisfied: wheel>=0.26 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.37.1)\n", + "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.8.0)\n", + "Requirement already satisfied: absl-py>=0.4 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.12.0)\n", + "Requirement already satisfied: google-auth<3,>=1.6.3 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.29.0)\n", + "Requirement already satisfied: grpcio>=1.24.3 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.37.0)\n", + "Requirement already satisfied: protobuf<3.20,>=3.9.2 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (3.15.8)\n", + "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.6.0)\n", + "Requirement already satisfied: setuptools>=41.0.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (58.0.4)\n", + "Requirement already satisfied: six in ./python/envs/venv_sct/lib/python3.6/site-packages (from absl-py>=0.4->tensorboard) (1.15.0)\n", + "Requirement already satisfied: rsa<5,>=3.1.4 in ./python/envs/venv_sct/lib/python3.6/site-packages (from google-auth<3,>=1.6.3->tensorboard) (4.7.2)\n", + "Requirement already satisfied: cachetools<5.0,>=2.0.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from google-auth<3,>=1.6.3->tensorboard) (4.2.1)\n", + "Requirement already satisfied: pyasn1-modules>=0.2.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from google-auth<3,>=1.6.3->tensorboard) (0.2.8)\n", + "Requirement already satisfied: requests-oauthlib>=0.7.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard) (1.3.0)\n", + "Requirement already satisfied: importlib-metadata in ./python/envs/venv_sct/lib/python3.6/site-packages (from markdown>=2.6.8->tensorboard) (4.0.1)\n", + "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in ./python/envs/venv_sct/lib/python3.6/site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard) (0.4.8)\n", + "Requirement already satisfied: chardet<5,>=3.0.2 in ./python/envs/venv_sct/lib/python3.6/site-packages (from requests<3,>=2.21.0->tensorboard) (4.0.0)\n", + "Requirement already satisfied: idna<3,>=2.5 in ./python/envs/venv_sct/lib/python3.6/site-packages (from requests<3,>=2.21.0->tensorboard) (2.10)\n", + "Requirement already satisfied: certifi>=2017.4.17 in ./python/envs/venv_sct/lib/python3.6/site-packages (from requests<3,>=2.21.0->tensorboard) (2020.12.5)\n", + "Requirement already satisfied: urllib3<1.27,>=1.21.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from requests<3,>=2.21.0->tensorboard) (1.26.4)\n", + "Requirement already satisfied: oauthlib>=3.0.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard) (3.1.0)\n", + "Requirement already satisfied: zipp>=0.5 in ./python/envs/venv_sct/lib/python3.6/site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard) (3.4.1)\n", + "Requirement already satisfied: typing-extensions>=3.6.4 in ./python/envs/venv_sct/lib/python3.6/site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard) (3.7.4.3)\n", + "Installing collected packages: tensorboard\n", + "Successfully installed tensorboard-2.10.1\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", + "\n", + "\u001b[0;32mInstalling spinalcordtoolbox...\u001b[0m\n", + "\n", + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Obtaining file:///content/spinalcordtoolbox\n", + "Installing collected packages: spinalcordtoolbox\n", + " Running setup.py develop for spinalcordtoolbox\n", + "Successfully installed spinalcordtoolbox-5.3.0\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", + "\n", + "\u001b[0;32mCreating launchers for Python scripts...\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mInstalling binaries...\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34msct_download_data -d binaries_linux -o /content/spinalcordtoolbox/bin -k\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d binaries_linux -o /content/spinalcordtoolbox/bin -k\n", + "--\n", + "\n", + "Trying URL: https://osf.io/cs6zt/?action=download\n", + "Downloading: 20200801_sct_binaries_linux.tar.gz\n", + "Status: 100% 78.2M/78.2M [00:01<00:00, 51.7MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002722.667692-3cgx29rv)\n", + "Unzip data to: /tmp/sct-20221030002722.667692-3cgx29rv\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;32mAll requirements installed!\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mInstalling data...\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34mrm -rf /content/spinalcordtoolbox/data\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34mmkdir -p /content/spinalcordtoolbox/data\u001b[0m\n", + "\n", + "\n", + "\u001b[0;34msct_download_data -d PAM50 -o /content/spinalcordtoolbox/data/PAM50\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d PAM50 -o /content/spinalcordtoolbox/data/PAM50\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/PAM50'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/PAM50/releases/download/r20201104/PAM50-r20201104.zip\n", + "Downloading: PAM50-r20201104.zip\n", + "Status: 100% 70.9M/70.9M [00:02<00:00, 29.1MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002729.319663-oyl04fhv)\n", + "Unzip data to: /tmp/sct-20221030002729.319663-oyl04fhv\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d gm_model -o /content/spinalcordtoolbox/data/gm_model\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d gm_model -o /content/spinalcordtoolbox/data/gm_model\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/gm_model'\u001b[0m\n", + "Trying URL: https://osf.io/ugscu/?action=download\n", + "Downloading: 20160922_gm_model.zip\n", + "Status: 100% 10.3M/10.3M [00:00<00:00, 11.5MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002733.182217-u2i77b3s)\n", + "Unzip data to: /tmp/sct-20221030002733.182217-u2i77b3s\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d optic_models -o /content/spinalcordtoolbox/data/optic_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d optic_models -o /content/spinalcordtoolbox/data/optic_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/optic_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/optic_models/releases/download/r20170413/20170413_optic_models.zip\n", + "Downloading: 20170413_optic_models.zip\n", + "Status: 100% 17.7k/17.7k [00:00<00:00, 45.0MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002734.488837-jpdbc771)\n", + "Unzip data to: /tmp/sct-20221030002734.488837-jpdbc771\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d pmj_models -o /content/spinalcordtoolbox/data/pmj_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d pmj_models -o /content/spinalcordtoolbox/data/pmj_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/pmj_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/pmj_models/releases/download/r20170922/20170922_pmj_models.zip\n", + "Downloading: 20170922_pmj_models.zip\n", + "Status: 100% 8.87k/8.87k [00:00<00:00, 27.1MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002735.758279-uexugdz_)\n", + "Unzip data to: /tmp/sct-20221030002735.758279-uexugdz_\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d deepseg_sc_models -o /content/spinalcordtoolbox/data/deepseg_sc_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d deepseg_sc_models -o /content/spinalcordtoolbox/data/deepseg_sc_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_sc_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/deepseg_sc_models/releases/download/r20180610/20180610_deepseg_sc_models.zip\n", + "Downloading: 20180610_deepseg_sc_models.zip\n", + "Status: 100% 58.7M/58.7M [00:02<00:00, 25.5MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002739.369772-lr1zdvtr)\n", + "Unzip data to: /tmp/sct-20221030002739.369772-lr1zdvtr\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d deepseg_gm_models -o /content/spinalcordtoolbox/data/deepseg_gm_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d deepseg_gm_models -o /content/spinalcordtoolbox/data/deepseg_gm_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_gm_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/deepseg_gm_models/releases/download/r20180205/20180205_deepseg_gm_models.zip\n", + "Downloading: 20180205_deepseg_gm_models.zip\n", + "Status: 100% 2.28M/2.28M [00:00<00:00, 3.64MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002742.176222-ft5ggkzp)\n", + "Unzip data to: /tmp/sct-20221030002742.176222-ft5ggkzp\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d deepseg_lesion_models -o /content/spinalcordtoolbox/data/deepseg_lesion_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d deepseg_lesion_models -o /content/spinalcordtoolbox/data/deepseg_lesion_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_lesion_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/deepseg_lesion_models/releases/download/r20180613/20180613_deepseg_lesion_models.zip\n", + "Downloading: 20180613_deepseg_lesion_models.zip\n", + "Status: 100% 16.0M/16.0M [00:01<00:00, 15.2MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002744.923359-avf7ug22)\n", + "Unzip data to: /tmp/sct-20221030002744.923359-avf7ug22\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "\n", + "\u001b[0;34msct_download_data -d c2c3_disc_models -o /content/spinalcordtoolbox/data/c2c3_disc_models\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_download_data -d c2c3_disc_models -o /content/spinalcordtoolbox/data/c2c3_disc_models\n", + "--\n", + "\n", + "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/c2c3_disc_models'\u001b[0m\n", + "Trying URL: https://github.com/sct-data/c2c3_disc_models/releases/download/r20190117/20190117_c2c3_disc_models.zip\n", + "Downloading: 20190117_c2c3_disc_models.zip\n", + "Status: 100% 8.94k/8.94k [00:00<00:00, 19.6MB/s]\n", + "Creating temporary folder (/tmp/sct-20221030002746.551504-z88lydja)\n", + "Unzip data to: /tmp/sct-20221030002746.551504-z88lydja\n", + "Removing temporary folders...\n", + "\u001b[0mDone!\n", + "\u001b[0m\n", + "Status: 100% 18.0M/18.0M [00:01<00:00, 16.8MB/s]\n", + "\n", + "\u001b[0;32mValidate installation...\u001b[0m\n", + "\n", + "\n", + "--\n", + "Spinal Cord Toolbox (git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92)\n", + "\n", + "sct_check_dependencies \n", + "--\n", + "\n", + "SCT info:\n", + "- version: git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92\n", + "- path: /content/spinalcordtoolbox\n", + "OS: linux (Linux-5.10.133+-x86_64-with-debian-buster-sid)\n", + "CPU cores: Available: 2, Used by ITK functions: 2\n", + "RAM: Total: 12985MB, Used: 1057MB, Available: 11698MB\n", + "Check Python executable.............................[\u001b[92mOK\u001b[0m]\n", + " Using bundled python 3.6.13 |Anaconda, Inc.| (default, Jun 4 2021, 14:25:59) \n", + "[GCC 7.5.0] at /content/spinalcordtoolbox/python/envs/venv_sct/bin/python\n", + "Check if data are installed.........................[\u001b[92mOK\u001b[0m]\n", + "Check if colored is installed.......................[\u001b[92mOK\u001b[0m] (1.4.2)\n", + "Check if dipy is installed..........................[\u001b[92mOK\u001b[0m] (1.4.0)\n", + "Check if futures is installed.......................[\u001b[92mOK\u001b[0m]\n", + "Check if h5py is installed..........................[\u001b[92mOK\u001b[0m] (2.10.0)\n", + "Check if Keras (2.1.5) is installed.................[\u001b[92mOK\u001b[0m] (2.1.5)\n", + "Check if ivadomed is installed......................Generating new fontManager, this may take some time...\n", + "[\u001b[92mOK\u001b[0m] (2.7.4)\n", + "Check if matplotlib is installed....................[\u001b[92mOK\u001b[0m] (3.3.4)\n", + "Check if nibabel is installed.......................[\u001b[92mOK\u001b[0m] (3.2.1)\n", + "Check if numpy is installed.........................[\u001b[92mOK\u001b[0m] (1.19.5)\n", + "Check if onnxruntime (1.4.0) is installed...........[\u001b[92mOK\u001b[0m] (1.4.0)\n", + "Check if pandas is installed........................[\u001b[92mOK\u001b[0m] (1.1.5)\n", + "Check if psutil is installed........................[\u001b[92mOK\u001b[0m] (5.8.0)\n", + "Check if pyqt5 (5.11.3) is installed................[\u001b[92mOK\u001b[0m] (5.11.3)\n", + "Check if pytest is installed........................[\u001b[92mOK\u001b[0m] (6.2.3)\n", + "Check if pytest-cov is installed....................[\u001b[92mOK\u001b[0m] (__version__ = '2.11.1')\n", + "Check if raven is installed.........................[\u001b[92mOK\u001b[0m]\n", + "Check if requests is installed......................[\u001b[92mOK\u001b[0m] (2.25.1)\n", + "Check if requirements-parser is installed...........[\u001b[92mOK\u001b[0m] (0.2.0)\n", + "Check if scipy is installed.........................[\u001b[92mOK\u001b[0m] (1.5.4)\n", + "Check if scikit-image is installed..................[\u001b[92mOK\u001b[0m] (0.17.2)\n", + "Check if scikit-learn is installed..................[\u001b[92mOK\u001b[0m] (0.24.1)\n", + "Check if tensorflow (1.5.0) is installed............[\u001b[92mOK\u001b[0m] (1.5.0)\n", + "Check if torch (1.5.0+cpu) is installed.............[\u001b[92mOK\u001b[0m] (1.5.0+cpu)\n", + "Check if torchvision (0.6.0+cpu) is installed.......[\u001b[92mOK\u001b[0m] (0.6.0+cpu)\n", + "Check if xlwt is installed..........................[\u001b[92mOK\u001b[0m] (1.3.0)\n", + "Check if tqdm is installed..........................[\u001b[92mOK\u001b[0m] (4.60.0)\n", + "Check if transforms3d is installed..................[\u001b[92mOK\u001b[0m] (0.3.1)\n", + "Check if urllib3 is installed.......................[\u001b[92mOK\u001b[0m] (1.26.4)\n", + "Check if pytest_console_scripts is installed........[\u001b[92mOK\u001b[0m]\n", + "Check if wquantiles is installed....................[\u001b[92mOK\u001b[0m] (0.4)\n", + "Check if spinalcordtoolbox is installed.............[\u001b[92mOK\u001b[0m]\n", + "Check ANTs compatibility with OS ...................[\u001b[92mOK\u001b[0m]\n", + "Check PropSeg compatibility with OS ................[\u001b[92mOK\u001b[0m]\n", + "Check if DISPLAY variable is set....................[\u001b[91mFAIL\u001b[0m]\n", + "\n", + "\n", + "\u001b[0;32mOpen a new Terminal window to load environment variables, or run:\n", + "source /root/.bashrc\u001b[0m\n", + "\n", + "\n", + "\u001b[0;32mInstallation finished successfully!\u001b[0m\n", + "\n", + "Spinal cord toolbox installed\n", + " % Total % Received % Xferd Average Speed Time Time Time Current\n", + " Dload Upload Total Spent Left Speed\n", + " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n", + "100 212k 100 212k 0 0 225k 0 --:--:-- --:--:-- --:--:-- 20.2M\n", + "Archive: niimath_lnx.zip\n", + " inflating: /content/niimath/niimath \n", + "NIImath installed\n", + "All necessary tools have been installed!\n" + ] + } ], - "metadata": { - "id": "UjPRdK9eftEO" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "QFyfZnHHU87d" - }, - "outputs": [], - "source": [ - "############ Importing libraries\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import nibabel as nib\n", - "import sys\n", - "import cv2\n", - "import re\n", - "import pandas as pd\n", - "from os.path import join\n", - "import glob\n", - "import zipfile\n", - "import shutil\n", - "import logging\n", - "import subprocess\n", - "import fnmatch\n", - "import pathlib\n", - "import json\n", - "import time\n", - "import seaborn as sns\n", - "import os\n", - "import scipy\n", - "from scipy import stats\n", - "from scipy.stats import mannwhitneyu\n", - "from statsmodels.stats.weightstats import ztest as ztest\n", - "from scipy.stats import bartlett\n", - "from scipy.stats import ansari\n", - "from scipy.stats import wilcoxon\n", - "from scipy.stats import kruskal\n", - "from scipy.stats import friedmanchisquare\n", - "from tabulate import tabulate\n", - "\n", - "print('Necessary libraries imported')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PYCvEAtuJZEI" - }, - "outputs": [], "source": [ "## Installing necessary tools\n", "\n", @@ -135,7 +1079,7 @@ "os.chdir('/content/')\n", "! git clone https://github.com/osfclient/osfclient\n", "\n", - "% cd osfclient/ \n", + "%cd osfclient/ \n", "\n", "! pip install osfclient\n", "print('OSF client installed')\n", @@ -145,7 +1089,7 @@ "# Github: https://github.com/spinalcordtoolbox/spinalcordtoolbox/\n", "os.chdir('/content/')\n", "!git clone --depth 1 --branch 5.3.0 https://github.com/spinalcordtoolbox/spinalcordtoolbox\n", - "% cd spinalcordtoolbox/\n", + "%cd spinalcordtoolbox/\n", "!yes | ./install_sct\n", "os.environ['PATH'] += ':/content/spinalcordtoolbox/bin'\n", "os.environ['SCT_DIR'] = '/content/spinalcordtoolbox'\n", @@ -166,6 +1110,11 @@ }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "oY6IeyTa0eJ1" + }, + "outputs": [], "source": [ "#Here, the various helper functions are defined\n", "#run_subprocess is a wrapper for subprocess.run\n", @@ -203,67 +1152,65 @@ " dataframe_mean['STD()'] = pd.to_numeric(dataframe_mean['STD()'], errors='coerce')\n", " STD_matrix=dataframe_mean['STD()'].to_numpy()\n", " return STD_matrix" - ], - "metadata": { - "id": "oY6IeyTa0eJ1" - }, - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "markdown", - "source": [ - "# Postprocessing: Registration " - ], "metadata": { "id": "KdaBlhc-fobP" - } + }, + "source": [ + "# Postprocessing: Registration " + ] }, { "cell_type": "markdown", - "source": [ - "##Downloading data" - ], "metadata": { "id": "mYFGRBR5Sv4c" - } + }, + "source": [ + "##Downloading data" + ] }, { "cell_type": "code", - "source": [ - "# Downloading data\n", - "os.chdir('/content/osfclient/')\n", - "! osf -p v4tdk fetch /Paper/SC_rt_shim.zip /content/osfclient/SC_rt_shim.zip\n", - "print(\"Data suscesfully downloaded\")\n", - "zipped_nifti='/content/osfclient/SC_rt_shim.zip'\n", - "with zipfile.ZipFile(zipped_nifti,\"r\") as zip_ref:\n", - " zip_ref.extractall('/content/')\n", - "# clearing up annoying _MACOSX directory\n", - "shutil.rmtree('/content/__MACOSX')\n", - "print(\"Unzipping done\")" - ], + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "SpqdHDXVjiuK", - "outputId": "d805ffd1-cdf4-4d33-d3fa-5f5e65f4752c" + "outputId": "c605a1fc-b2a3-45cc-b72c-bed91f19c662" }, - "execution_count": null, "outputs": [ { - "output_type": "stream", "name": "stdout", + "output_type": "stream", "text": [ "100% 181M/181M [00:01<00:00, 113Mbytes/s]\n", "Data suscesfully downloaded\n", "Unzipping done\n" ] } + ], + "source": [ + "# Downloading data\n", + "os.chdir('/content/osfclient/')\n", + "! osf -p v4tdk fetch /Paper/SC_rt_shim.zip /content/osfclient/SC_rt_shim.zip\n", + "print(\"Data suscesfully downloaded\")\n", + "zipped_nifti='/content/osfclient/SC_rt_shim.zip'\n", + "with zipfile.ZipFile(zipped_nifti,\"r\") as zip_ref:\n", + " zip_ref.extractall('/content/')\n", + "# clearing up annoying _MACOSX directory\n", + "shutil.rmtree('/content/__MACOSX')\n", + "print(\"Unzipping done\")" ] }, { "cell_type": "markdown", + "metadata": { + "id": "b1N67lxBC65Y" + }, "source": [ "##Registration of the T1w segmentation onto the MGRE scans\n", "\n", @@ -272,18 +1219,38 @@ "Then, the MGRE scans are registered to the T1w scans (MGRE-to-T1w), and the inverse of this registration (the T1w-to-MGRE warp filed) is used to register the segmentation of the T1w scans into the MGRE space.\n", "\n", "This registered segmentation requires manual correction, which is not possible within this notebook, and would require manual download of the data. " - ], - "metadata": { - "id": "b1N67lxBC65Y" - } + ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "id": "W8Mn9RCW05bm" + "colab": { + "base_uri": "https://localhost:8080/", + "height": 381 + }, + "id": "W8Mn9RCW05bm", + "outputId": "bed31d8a-ccee-4325-ce52-855aaef5210d" }, - "outputs": [], + "outputs": [ + { + "ename": "KeyboardInterrupt", + "evalue": "ignored", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[0mcsvfile_RTZSHIM\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'rtzshim_data_manual.csv'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0mrun_subprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"sct_maths -i {RTZSHIMfile[0]} -mean t -o {meanname_RTZSHIM}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m \u001b[0mrun_subprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"sct_register_multimodal -i {meanname_RTZSHIM} -d {T1wfile[0]} -dseg {segfilename} -m {maskfilename} -param step=1,type=im,metric=cc,algo=slicereg,poly=2,smooth=1 -qc qc\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 90\u001b[0m \u001b[0mwarpT1w2RTZSHIM\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mglob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mglob\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mRegistrationdir\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m'/warp_Lowres*rtz*.nii*'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 91\u001b[0m \u001b[0mrun_subprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"sct_apply_transfo -i {segfilename} -d {meanname_RTZSHIM} -w {warpT1w2RTZSHIM} -x nn -o {outfile_RTZSHIM}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mrun_subprocess\u001b[0;34m(cmd)\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mcmd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mtext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mcheck\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m )\n\u001b[1;32m 14\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0msubprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCalledProcessError\u001b[0m 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\u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/lib/python3.7/subprocess.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1017\u001b[0m \u001b[0mendtime\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_time\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1018\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1019\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_wait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1020\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1021\u001b[0m \u001b[0;31m# https://bugs.python.org/issue25942\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/lib/python3.7/subprocess.py\u001b[0m in \u001b[0;36m_wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1651\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreturncode\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1652\u001b[0m \u001b[0;32mbreak\u001b[0m \u001b[0;31m# Another thread waited.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1653\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mpid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msts\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_try_wait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1654\u001b[0m \u001b[0;31m# Check the pid and loop as waitpid has been known to\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1655\u001b[0m \u001b[0;31m# return 0 even without WNOHANG in odd situations.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/lib/python3.7/subprocess.py\u001b[0m in \u001b[0;36m_try_wait\u001b[0;34m(self, wait_flags)\u001b[0m\n\u001b[1;32m 1609\u001b[0m \u001b[0;34m\"\"\"All callers to this function MUST hold self._waitpid_lock.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1610\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1611\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mpid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msts\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwaitpid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwait_flags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1612\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mChildProcessError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1613\u001b[0m \u001b[0;31m# This happens if SIGCLD is set to be ignored or waiting\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], "source": [ "## Within this step, we apply the T1w segmentation to the MGRE scans\n", "# We first register the MGRE scans to the T1w scan, and then apply the inverse of\n", @@ -414,14 +1381,14 @@ }, { "cell_type": "markdown", + "metadata": { + "id": "YJF4-UUUCyrz" + }, "source": [ "##Registration of the MGRE scans onto the PAM50 template\n", "\n", "Note that the input of this step, i.e.: the MGRE scans registered to the T1w scan, has not undergone manual correction. " - ], - "metadata": { - "id": "YJF4-UUUCyrz" - } + ] }, { "cell_type": "code", @@ -532,17 +1499,22 @@ }, { "cell_type": "markdown", + "metadata": { + "id": "DD-RAEGjWeBp" + }, "source": [ "##Creating the mean image of the MGRE scans registered to the PAM50 template\n", "\n", "Note that the input of this step, i.e.: the MGRE scans registered to the PAM50 template, has not undergone manual correction. " - ], - "metadata": { - "id": "DD-RAEGjWeBp" - } + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "V1ZS3UQiW9En" + }, + "outputs": [], "source": [ "# Here, we create the mean across volunteers of the PAM50 registered scans for each shim condition\n", "\n", @@ -734,27 +1706,27 @@ "run_subprocess(f\"sct_extract_metric -i {outfile_staticzshim_PAM50_coreged_mean_meanacrossechoes} -f {PAM50_cord} -method wa -o {csvfile_staticzSHIM_PAM50_coreg_meanacrossechoes} -perslice 1 -append 1\")\n", "run_subprocess(f\"sct_extract_metric -i {outfile_rtshim_PAM50_coreged_mean_meanacrossechoes} -f {PAM50_cord} -method wa -o {csvfile_rtSHIM_PAM50_coreg_meanacrossechoes} -perslice 1 -append 1\")\n", "run_subprocess(f\"sct_extract_metric -i {outfile_rtzshim_PAM50_coreged_mean_meanacrossechoes} -f {PAM50_cord} -method wa -o {csvfile_rtzSHIM_PAM50_coreg_meanacrossechoes} -perslice 1 -append 1\")" - ], - "metadata": { - "id": "V1ZS3UQiW9En" - }, - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "markdown", + "metadata": { + "id": "q5jl39yqr7Pp" + }, "source": [ "##Applying the SC segmentation to the gradient images\n", "\n", "Here, we use the SC segmentation, as derived in \"Registration of the T1w segmentation onto the MGRE scans\" (i.e.:, the segmentation of the T1w scan, warped to the space of the no shim MGRE) to mask the spinal cord from gradient images. \n", "These images are generated by the Shimming Toolbox during the training session (as described in Methods: Data Acquisition: Shimming Toolbox). " - ], - "metadata": { - "id": "q5jl39yqr7Pp" - } + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "PQ72v5XvtLrH" + }, + "outputs": [], "source": [ "#Here, we identify the appropriate segmentation file, and then apply it as a mask to the appropriate Gradient files\n", "Subjectdirs=sorted(glob.glob('/content/SC_rt_shim/'+'*acdc*')) \n", @@ -800,44 +1772,39 @@ " run_subprocess(f\"sct_extract_metric -i {YSTATIC_name} -f {segfilename_noshim} -method wa -o {YSTATIC_CSV_name} -perslice 1 -append 1\")\n", " run_subprocess(f\"sct_extract_metric -i {ZRIRO_name} -f {segfilename_noshim} -method wa -o {ZRIRO_CSV_name} -perslice 1 -append 1\")\n", " run_subprocess(f\"sct_extract_metric -i {ZSTATIC_name} -f {segfilename_noshim} -method wa -o {ZSTATIC_CSV_name} -perslice 1 -append 1\")" - ], - "metadata": { - "id": "PQ72v5XvtLrH" - }, - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "markdown", + "metadata": { + "id": "JwOZuWe1foxE" + }, "source": [ "# Postprocessing: Statistics and visualisation\n", "\n", "This section is designed to be run independently of the previous two sections. We supply the manually corrected data within this section (i.e.: registration of the T1w segmentation onto the MGRE scans, and of the MGRE scans to the PAM50 template have been manually corrected) in order to faciliate a replication of our results. \n", "\n", "Should the output of the previous section be used as input for this section (i.e.: no manual correction is performed), the results may slightly differ from those presented in our paper.\n" - ], - "metadata": { - "id": "JwOZuWe1foxE" - } + ] }, { "cell_type": "markdown", - "source": [ - "##Rerunning the Setup, if necessary" - ], "metadata": { "id": "lG47XpzHRnB-" - } + }, + "source": [ + "##Rerunning the Setup, if necessary" + ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "af0ce237-0ebb-41c8-cbc5-dd833fe22813", - "id": "bkLS6VwuRsNH" + "id": "bkLS6VwuRsNH", + "outputId": "a5b427fe-5b9e-4703-c5e1-0bf28f617c57" }, "outputs": [ { @@ -846,14 +1813,6 @@ "text": [ "Necessary libraries imported\n" ] - }, - { - "output_type": "stream", - "name": "stderr", - "text": [ - "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n", - " import pandas.util.testing as tm\n" - ] } ], "source": [ @@ -878,6 +1837,7 @@ "import seaborn as sns\n", "import os\n", "import scipy\n", + "import statsmodels.stats.multitest as smm\n", "from scipy import stats\n", "from scipy.stats import mannwhitneyu\n", "from statsmodels.stats.weightstats import ztest as ztest\n", @@ -892,13 +1852,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "id": "WbU3qP4FRvQm", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "942e63eb-bc1e-40ab-be9e-89a60c6b6c62" + "outputId": "5064ff5a-38cc-417a-8195-64e4cf91e75f" }, "outputs": [ { @@ -908,20 +1868,20 @@ "Cloning into 'osfclient'...\n", "remote: Enumerating objects: 1403, done.\u001b[K\n", "remote: Counting objects: 100% (118/118), done.\u001b[K\n", - "remote: Compressing objects: 100% (64/64), done.\u001b[K\n", - "remote: Total 1403 (delta 56), reused 83 (delta 50), pack-reused 1285\u001b[K\n", - "Receiving objects: 100% (1403/1403), 432.44 KiB | 5.77 MiB/s, done.\n", + "remote: Compressing objects: 100% (63/63), done.\u001b[K\n", + "remote: Total 1403 (delta 56), reused 83 (delta 51), pack-reused 1285\u001b[K\n", + "Receiving objects: 100% (1403/1403), 431.94 KiB | 19.63 MiB/s, done.\n", "Resolving deltas: 100% (888/888), done.\n", "/content/osfclient\n", "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting osfclient\n", " Downloading osfclient-0.0.5-py2.py3-none-any.whl (39 kB)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from osfclient) (2.23.0)\n", + "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from osfclient) (4.64.1)\n", "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from osfclient) (1.15.0)\n", - "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from osfclient) (4.64.0)\n", - "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (1.24.3)\n", - "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (2022.6.15)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (2.10)\n", + "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (1.24.3)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (2022.9.24)\n", "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->osfclient) (3.0.4)\n", "Installing collected packages: osfclient\n", "Successfully installed osfclient-0.0.5\n", @@ -931,7 +1891,7 @@ "remote: Counting objects: 100% (500/500), done.\u001b[K\n", "remote: Compressing objects: 100% (434/434), done.\u001b[K\n", "remote: Total 500 (delta 77), reused 214 (delta 47), pack-reused 0\u001b[K\n", - "Receiving objects: 100% (500/500), 2.85 MiB | 12.10 MiB/s, done.\n", + "Receiving objects: 100% (500/500), 2.85 MiB | 17.67 MiB/s, done.\n", "Resolving deltas: 100% (77/77), done.\n", "Note: checking out 'e2e19bd02e2a99eab252ad3cca86eee5c5d63e92'.\n", "\n", @@ -955,7 +1915,7 @@ "\n", "\u001b[0;32mChecking OS type and version...\u001b[0m\n", "\n", - "Linux 959523934a3c 5.4.188+ #1 SMP Sun Apr 24 10:03:06 PDT 2022 x86_64 x86_64 x86_64 GNU/Linux\n", + "Linux dea7bfcdc463 5.10.133+ #1 SMP Fri Aug 26 08:44:51 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux\n", "\n", "\u001b[0;32mChecking requirements...\u001b[0m\n", "\n", @@ -994,26 +1954,26 @@ "\u001b[0;34mmkdir -p /content/spinalcordtoolbox/python\u001b[0m\n", "\n", "\n", - "\u001b[0;34mwget -O /tmp/tmp.u3fSsCjSS7/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\u001b[0m\n", + "\u001b[0;34mwget -O /tmp/tmp.nVE1iGiHgI/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\u001b[0m\n", "\n", - "--2022-06-27 21:05:32-- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n", + "--2022-11-14 21:46:10-- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n", "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.130.3, 104.16.131.3, 2606:4700::6810:8303, ...\n", "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.130.3|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 76607678 (73M) [application/x-sh]\n", - "Saving to: ‘/tmp/tmp.u3fSsCjSS7/miniconda.sh’\n", + "Saving to: ‘/tmp/tmp.nVE1iGiHgI/miniconda.sh’\n", "\n", - "/tmp/tmp.u3fSsCjSS7 100%[===================>] 73.06M 86.6MB/s in 0.8s \n", + "/tmp/tmp.nVE1iGiHgI 100%[===================>] 73.06M 202MB/s in 0.4s \n", "\n", - "2022-06-27 21:05:33 (86.6 MB/s) - ‘/tmp/tmp.u3fSsCjSS7/miniconda.sh’ saved [76607678/76607678]\n", + "2022-11-14 21:46:10 (202 MB/s) - ‘/tmp/tmp.nVE1iGiHgI/miniconda.sh’ saved [76607678/76607678]\n", "\n", "\n", - "\u001b[0;34mbash /tmp/tmp.u3fSsCjSS7/miniconda.sh -p /content/spinalcordtoolbox/python -b -f\u001b[0m\n", + "\u001b[0;34mbash /tmp/tmp.nVE1iGiHgI/miniconda.sh -p /content/spinalcordtoolbox/python -b -f\u001b[0m\n", "\n", "PREFIX=/content/spinalcordtoolbox/python\n", "Unpacking payload ...\n", - "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\bdone\n", - "Solving environment: - \b\b\\ \b\b| \b\bdone\n", + "Collecting package metadata (current_repodata.json): - \b\b\\ \b\bdone\n", + "Solving environment: / \b\b- \b\bdone\n", "\n", "## Package Plan ##\n", "\n", @@ -1106,8 +2066,8 @@ " zlib pkgs/main/linux-64::zlib-1.2.12-h7f8727e_1\n", "\n", "\n", - "Preparing transaction: - \b\b\\ \b\b| \b\b/ \b\bdone\n", - "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", + "Preparing transaction: | \b\b/ \b\b- \b\bdone\n", + "Executing transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", "installation finished.\n", "WARNING:\n", " You currently have a PYTHONPATH environment variable set. This may cause\n", @@ -1115,15 +2075,15 @@ " For best results, please verify that your PYTHONPATH only points to\n", " directories of packages that are compatible with the Python interpreter\n", " in Miniconda3: /content/spinalcordtoolbox/python\n", - "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n", - "Solving environment: - \b\b\\ \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n", - "Collecting package metadata (repodata.json): / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n", - "Solving environment: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n", + "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", + "Solving environment: \\ \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n", + "Collecting package metadata (repodata.json): / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n", + "Solving environment: - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n", "\n", "\n", "==> WARNING: A newer version of conda exists. <==\n", " current version: 4.12.0\n", - " latest version: 4.13.0\n", + " latest version: 22.9.0\n", "\n", "Please update conda by running\n", "\n", @@ -1144,67 +2104,71 @@ " package | build\n", " ---------------------------|-----------------\n", " _openmp_mutex-5.1 | 1_gnu 21 KB\n", - " ca-certificates-2022.4.26 | h06a4308_0 124 KB\n", + " ca-certificates-2022.10.11 | h06a4308_0 124 KB\n", " certifi-2021.5.30 | py36h06a4308_0 139 KB\n", " ld_impl_linux-64-2.38 | h1181459_1 654 KB\n", " libgcc-ng-11.2.0 | h1234567_1 5.3 MB\n", " libgomp-11.2.0 | h1234567_1 474 KB\n", " libstdcxx-ng-11.2.0 | h1234567_1 4.7 MB\n", - " openssl-1.1.1o | h7f8727e_0 2.5 MB\n", + " ncurses-6.3 | h5eee18b_3 781 KB\n", + " openssl-1.1.1s | h7f8727e_0 3.6 MB\n", " pip-21.2.2 | py36h06a4308_0 1.8 MB\n", " python-3.6.13 | h12debd9_1 32.5 MB\n", + " readline-8.2 | h5eee18b_0 357 KB\n", " setuptools-58.0.4 | py36h06a4308_0 788 KB\n", - " sqlite-3.38.5 | hc218d9a_0 1.0 MB\n", + " sqlite-3.39.3 | h5082296_0 1.1 MB\n", " tk-8.6.12 | h1ccaba5_0 3.0 MB\n", - " xz-5.2.5 | h7f8727e_1 339 KB\n", - " zlib-1.2.12 | h7f8727e_2 106 KB\n", + " xz-5.2.6 | h5eee18b_0 394 KB\n", + " zlib-1.2.13 | h5eee18b_0 103 KB\n", " ------------------------------------------------------------\n", - " Total: 53.5 MB\n", + " Total: 55.8 MB\n", "\n", "The following NEW packages will be INSTALLED:\n", "\n", " _libgcc_mutex pkgs/main/linux-64::_libgcc_mutex-0.1-main\n", " _openmp_mutex pkgs/main/linux-64::_openmp_mutex-5.1-1_gnu\n", - " ca-certificates pkgs/main/linux-64::ca-certificates-2022.4.26-h06a4308_0\n", + " ca-certificates pkgs/main/linux-64::ca-certificates-2022.10.11-h06a4308_0\n", " certifi pkgs/main/linux-64::certifi-2021.5.30-py36h06a4308_0\n", " ld_impl_linux-64 pkgs/main/linux-64::ld_impl_linux-64-2.38-h1181459_1\n", " libffi pkgs/main/linux-64::libffi-3.3-he6710b0_2\n", " libgcc-ng pkgs/main/linux-64::libgcc-ng-11.2.0-h1234567_1\n", " libgomp pkgs/main/linux-64::libgomp-11.2.0-h1234567_1\n", " libstdcxx-ng pkgs/main/linux-64::libstdcxx-ng-11.2.0-h1234567_1\n", - " ncurses pkgs/main/linux-64::ncurses-6.3-h7f8727e_2\n", - " openssl pkgs/main/linux-64::openssl-1.1.1o-h7f8727e_0\n", + " ncurses pkgs/main/linux-64::ncurses-6.3-h5eee18b_3\n", + " openssl pkgs/main/linux-64::openssl-1.1.1s-h7f8727e_0\n", " pip pkgs/main/linux-64::pip-21.2.2-py36h06a4308_0\n", " python pkgs/main/linux-64::python-3.6.13-h12debd9_1\n", - " readline pkgs/main/linux-64::readline-8.1.2-h7f8727e_1\n", + " readline pkgs/main/linux-64::readline-8.2-h5eee18b_0\n", " setuptools pkgs/main/linux-64::setuptools-58.0.4-py36h06a4308_0\n", - " sqlite pkgs/main/linux-64::sqlite-3.38.5-hc218d9a_0\n", + " sqlite pkgs/main/linux-64::sqlite-3.39.3-h5082296_0\n", " tk pkgs/main/linux-64::tk-8.6.12-h1ccaba5_0\n", " wheel pkgs/main/noarch::wheel-0.37.1-pyhd3eb1b0_0\n", - " xz pkgs/main/linux-64::xz-5.2.5-h7f8727e_1\n", - " zlib pkgs/main/linux-64::zlib-1.2.12-h7f8727e_2\n", + " xz pkgs/main/linux-64::xz-5.2.6-h5eee18b_0\n", + " zlib pkgs/main/linux-64::zlib-1.2.13-h5eee18b_0\n", "\n", "\n", "\n", "Downloading and Extracting Packages\n", - "libgcc-ng-11.2.0 | 5.3 MB | : 100% 1.0/1 [00:00<00:00, 3.45it/s]\n", - "python-3.6.13 | 32.5 MB | : 100% 1.0/1 [00:05<00:00, 5.47s/it] \n", - "xz-5.2.5 | 339 KB | : 100% 1.0/1 [00:00<00:00, 12.51it/s]\n", - "setuptools-58.0.4 | 788 KB | : 100% 1.0/1 [00:00<00:00, 8.73it/s]\n", - "libgomp-11.2.0 | 474 KB | : 100% 1.0/1 [00:00<00:00, 9.15it/s]\n", - "pip-21.2.2 | 1.8 MB | : 100% 1.0/1 [00:00<00:00, 5.07it/s]\n", - "sqlite-3.38.5 | 1.0 MB | : 100% 1.0/1 [00:00<00:00, 10.45it/s]\n", - "ld_impl_linux-64-2.3 | 654 KB | : 100% 1.0/1 [00:00<00:00, 12.32it/s]\n", - "tk-8.6.12 | 3.0 MB | : 100% 1.0/1 [00:00<00:00, 5.06it/s]\n", - "_openmp_mutex-5.1 | 21 KB | : 100% 1.0/1 [00:00<00:00, 13.13it/s]\n", - "zlib-1.2.12 | 106 KB | : 100% 1.0/1 [00:00<00:00, 12.49it/s]\n", - "libstdcxx-ng-11.2.0 | 4.7 MB | : 100% 1.0/1 [00:00<00:00, 5.40it/s]\n", - "certifi-2021.5.30 | 139 KB | : 100% 1.0/1 [00:00<00:00, 10.61it/s]\n", - "ca-certificates-2022 | 124 KB | : 100% 1.0/1 [00:00<00:00, 13.33it/s]\n", - "openssl-1.1.1o | 2.5 MB | : 100% 1.0/1 [00:00<00:00, 6.02it/s]\n", + "certifi-2021.5.30 | 139 KB | : 100% 1.0/1 [00:00<00:00, 7.82it/s]\n", + "setuptools-58.0.4 | 788 KB | : 100% 1.0/1 [00:00<00:00, 11.97it/s]\n", + "openssl-1.1.1s | 3.6 MB | : 100% 1.0/1 [00:00<00:00, 7.63it/s]\n", + "libgcc-ng-11.2.0 | 5.3 MB | : 100% 1.0/1 [00:00<00:00, 5.44it/s]\n", + "ca-certificates-2022 | 124 KB | : 100% 1.0/1 [00:00<00:00, 25.74it/s]\n", + "tk-8.6.12 | 3.0 MB | : 100% 1.0/1 [00:00<00:00, 7.77it/s]\n", + "ncurses-6.3 | 781 KB | : 100% 1.0/1 [00:00<00:00, 4.79it/s]\n", + "ld_impl_linux-64-2.3 | 654 KB | : 100% 1.0/1 [00:00<00:00, 17.64it/s]\n", + "python-3.6.13 | 32.5 MB | : 100% 1.0/1 [00:03<00:00, 3.47s/it] \n", + "xz-5.2.6 | 394 KB | : 100% 1.0/1 [00:00<00:00, 15.68it/s]\n", + "sqlite-3.39.3 | 1.1 MB | : 100% 1.0/1 [00:00<00:00, 18.97it/s]\n", + "libgomp-11.2.0 | 474 KB | : 100% 1.0/1 [00:00<00:00, 17.73it/s]\n", + "_openmp_mutex-5.1 | 21 KB | : 100% 1.0/1 [00:00<00:00, 15.41it/s]\n", + "libstdcxx-ng-11.2.0 | 4.7 MB | : 100% 1.0/1 [00:00<00:00, 6.25it/s]\n", + "pip-21.2.2 | 1.8 MB | : 100% 1.0/1 [00:00<00:00, 6.54it/s]\n", + "readline-8.2 | 357 KB | : 100% 1.0/1 [00:00<00:00, 12.98it/s]\n", + "zlib-1.2.13 | 103 KB | : 100% 1.0/1 [00:00<00:00, 23.89it/s]\n", "Preparing transaction: / \b\b- \b\b\\ \b\bdone\n", - "Verifying transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", - "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n", + "Verifying transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n", + "Executing transaction: / \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n", "#\n", "# To activate this environment, use\n", "#\n", @@ -1226,12 +2190,12 @@ "Ignoring torchvision: markers 'sys_platform == \"darwin\"' don't match your environment\n", "Collecting absl-py==0.12.0\n", " Downloading absl_py-0.12.0-py3-none-any.whl (129 kB)\n", - "\u001b[K |████████████████████████████████| 129 kB 5.1 MB/s \n", + "\u001b[K |████████████████████████████████| 129 kB 25.1 MB/s \n", "\u001b[?25hCollecting appdirs==1.4.4\n", " Downloading appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB)\n", "Collecting attrs==20.3.0\n", " Downloading attrs-20.3.0-py2.py3-none-any.whl (49 kB)\n", - "\u001b[K |████████████████████████████████| 49 kB 6.0 MB/s \n", + "\u001b[K |████████████████████████████████| 49 kB 7.4 MB/s \n", "\u001b[?25hCollecting bids-neuropoly==0.2\n", " Downloading bids_neuropoly-0.2-py3-none-any.whl (3.1 kB)\n", "Collecting bids-validator==1.7.1\n", @@ -1242,27 +2206,27 @@ " Downloading cachetools-4.2.1-py3-none-any.whl (12 kB)\n", "Collecting certifi==2020.12.5\n", " Downloading certifi-2020.12.5-py2.py3-none-any.whl (147 kB)\n", - "\u001b[K |████████████████████████████████| 147 kB 55.3 MB/s \n", + "\u001b[K |████████████████████████████████| 147 kB 78.6 MB/s \n", "\u001b[?25hCollecting cffi==1.14.5\n", " Downloading cffi-1.14.5-cp36-cp36m-manylinux1_x86_64.whl (401 kB)\n", - "\u001b[K |████████████████████████████████| 401 kB 32.3 MB/s \n", + "\u001b[K |████████████████████████████████| 401 kB 74.6 MB/s \n", "\u001b[?25hCollecting cfgv==3.2.0\n", " Downloading cfgv-3.2.0-py2.py3-none-any.whl (7.3 kB)\n", "Collecting chardet==4.0.0\n", " Downloading chardet-4.0.0-py2.py3-none-any.whl (178 kB)\n", - "\u001b[K |████████████████████████████████| 178 kB 49.8 MB/s \n", + "\u001b[K |████████████████████████████████| 178 kB 78.5 MB/s \n", "\u001b[?25hCollecting click==7.1.2\n", " Downloading click-7.1.2-py2.py3-none-any.whl (82 kB)\n", - "\u001b[K |████████████████████████████████| 82 kB 1.3 MB/s \n", + "\u001b[K |████████████████████████████████| 82 kB 1.5 MB/s \n", "\u001b[?25hCollecting colored==1.4.2\n", " Downloading colored-1.4.2.tar.gz (56 kB)\n", - "\u001b[K |████████████████████████████████| 56 kB 4.2 MB/s \n", + "\u001b[K |████████████████████████████████| 56 kB 5.9 MB/s \n", "\u001b[?25hCollecting coverage==5.5\n", " Downloading coverage-5.5-cp36-cp36m-manylinux2010_x86_64.whl (240 kB)\n", - "\u001b[K |████████████████████████████████| 240 kB 56.1 MB/s \n", + "\u001b[K |████████████████████████████████| 240 kB 98.4 MB/s \n", "\u001b[?25hCollecting cryptography==3.4.7\n", " Downloading cryptography-3.4.7-cp36-abi3-manylinux2014_x86_64.whl (3.2 MB)\n", - "\u001b[K |████████████████████████████████| 3.2 MB 60.2 MB/s \n", + "\u001b[K |████████████████████████████████| 3.2 MB 83.5 MB/s \n", "\u001b[?25hCollecting csv-diff==1.1\n", " Downloading csv_diff-1.1-py3-none-any.whl (12 kB)\n", "Collecting cycler==0.10.0\n", @@ -1273,45 +2237,45 @@ " Downloading dictdiffer-0.8.1-py2.py3-none-any.whl (16 kB)\n", "Collecting dipy==1.4.0\n", " Downloading dipy-1.4.0-cp36-cp36m-manylinux2010_x86_64.whl (7.7 MB)\n", - "\u001b[K |████████████████████████████████| 7.7 MB 33.0 MB/s \n", + "\u001b[K |████████████████████████████████| 7.7 MB 63.7 MB/s \n", "\u001b[?25hCollecting distlib==0.3.1\n", " Downloading distlib-0.3.1-py2.py3-none-any.whl (335 kB)\n", - "\u001b[K |████████████████████████████████| 335 kB 62.6 MB/s \n", + "\u001b[K |████████████████████████████████| 335 kB 80.5 MB/s \n", "\u001b[?25hCollecting docopt==0.6.2\n", " Downloading docopt-0.6.2.tar.gz (25 kB)\n", "Collecting docutils==0.17.1\n", " Downloading docutils-0.17.1-py2.py3-none-any.whl (575 kB)\n", - "\u001b[K |████████████████████████████████| 575 kB 59.8 MB/s \n", + "\u001b[K |████████████████████████████████| 575 kB 77.1 MB/s \n", "\u001b[?25hCollecting filelock==3.0.12\n", " Downloading filelock-3.0.12-py3-none-any.whl (7.6 kB)\n", "Collecting future==0.18.2\n", " Downloading future-0.18.2.tar.gz (829 kB)\n", - "\u001b[K |████████████████████████████████| 829 kB 75.9 MB/s \n", + "\u001b[K |████████████████████████████████| 829 kB 69.6 MB/s \n", "\u001b[?25hCollecting futures==3.1.1\n", " Downloading futures-3.1.1-py3-none-any.whl (2.8 kB)\n", "Collecting google-auth==1.29.0\n", " Downloading google_auth-1.29.0-py2.py3-none-any.whl (142 kB)\n", - "\u001b[K |████████████████████████████████| 142 kB 55.8 MB/s \n", + "\u001b[K |████████████████████████████████| 142 kB 74.9 MB/s \n", "\u001b[?25hCollecting google-auth-oauthlib==0.4.4\n", " Downloading google_auth_oauthlib-0.4.4-py2.py3-none-any.whl (18 kB)\n", "Collecting grpcio==1.37.0\n", " Downloading grpcio-1.37.0-cp36-cp36m-manylinux2014_x86_64.whl (4.2 MB)\n", - "\u001b[K |████████████████████████████████| 4.2 MB 37.8 MB/s \n", + "\u001b[K |████████████████████████████████| 4.2 MB 87.9 MB/s \n", "\u001b[?25hCollecting h5py==2.10.0\n", " Downloading h5py-2.10.0-cp36-cp36m-manylinux1_x86_64.whl (2.9 MB)\n", - "\u001b[K |████████████████████████████████| 2.9 MB 39.8 MB/s \n", + "\u001b[K |████████████████████████████████| 2.9 MB 64.4 MB/s \n", "\u001b[?25hCollecting html5lib==0.9999999\n", " Downloading html5lib-0.9999999.tar.gz (889 kB)\n", - "\u001b[K |████████████████████████████████| 889 kB 53.1 MB/s \n", + "\u001b[K |████████████████████████████████| 889 kB 63.3 MB/s \n", "\u001b[?25hCollecting identify==2.2.4\n", " Downloading identify-2.2.4-py2.py3-none-any.whl (98 kB)\n", - 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" Created wheel for wquantiles: filename=wquantiles-0.5-py3-none-any.whl size=2508 sha256=735717406e87e7befe6e3a6ea7f23c7d06eefe0254b92ed5b0ebb1f6a7271887\n", + " Created wheel for wquantiles: filename=wquantiles-0.5-py3-none-any.whl size=2508 sha256=f74d7ce703b7769e9451789ba8dff756d0b02066e4467650683a4b47bcfebb16\n", " Stored in directory: /root/.cache/pip/wheels/ee/ba/d5/bbbdc6118df5bb4ef1c56910c3c41a9af8001191bc1849e3c4\n", "Successfully built colored docopt future html5lib pytest-console-scripts requirements-parser sphinx-jsonschema transforms3d wquantiles\n", "Installing collected packages: zipp, urllib3, typing-extensions, six, pyparsing, pyasn1, idna, chardet, certifi, rsa, requests, pytz, python-dateutil, pyasn1-modules, packaging, oauthlib, numpy, importlib-metadata, docopt, cachetools, toml, SQLAlchemy, scipy, requests-oauthlib, pycparser, py, pluggy, Pillow, patsy, pandas, num2words, nibabel, kiwisolver, iniconfig, importlib-resources, html5lib, google-auth, future, filelock, distlib, decorator, cycler, click, bids-validator, attrs, appdirs, Werkzeug, virtualenv, torch, tifffile, threadpoolctl, tensorboard-plugin-wit, tensorboard-data-server, PyYAML, PyWavelets, pytest, pybids, protobuf, nodeenv, networkx, mock, matplotlib, Markdown, jsonpointer, joblib, imageio, identify, grpcio, google-auth-oauthlib, docutils, dictdiffer, cfgv, cffi, bleach, absl-py, tqdm, torchvision, tensorflow-tensorboard, tensorboard, sphinx-jsonschema, seaborn, scikit-learn, scikit-image, pytest-ordering, pytest-console-scripts, PyQt5-sip, pre-commit, onnxruntime, h5py, csv-diff, cryptography, coverage, bids-neuropoly, xlwt, wquantiles, transforms3d, tensorflow, requirements-parser, raven, pytest-cov, PyQt5, pyOpenSSL, psutil, Keras, ivadomed, futures, dipy, colored\n", @@ -1564,37 +2528,37 @@ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting tensorboard\n", - " Downloading tensorboard-2.9.1-py3-none-any.whl (5.8 MB)\n", - "\u001b[K |████████████████████████████████| 5.8 MB 4.1 MB/s \n", - "\u001b[?25hRequirement already satisfied: requests<3,>=2.21.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (2.25.1)\n", + " Downloading tensorboard-2.10.1-py3-none-any.whl (5.9 MB)\n", + "\u001b[K |████████████████████████████████| 5.9 MB 34.4 MB/s \n", + "\u001b[?25hRequirement already satisfied: numpy>=1.12.0 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.19.5)\n", + "Requirement already satisfied: google-auth<3,>=1.6.3 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.29.0)\n", + "Requirement already satisfied: wheel>=0.26 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.37.1)\n", + "Requirement already satisfied: markdown>=2.6.8 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (3.3.4)\n", + "Requirement already satisfied: werkzeug>=1.0.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.0.1)\n", + "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (0.4.4)\n", "Requirement already satisfied: grpcio>=1.24.3 in ./python/envs/venv_sct/lib/python3.6/site-packages (from tensorboard) (1.37.0)\n", - 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"Successfully installed tensorboard-2.9.1\n", + "Successfully installed tensorboard-2.10.1\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n", "\n", "\u001b[0;32mInstalling spinalcordtoolbox...\u001b[0m\n", @@ -1623,9 +2587,9 @@ "\n", "Trying URL: https://osf.io/cs6zt/?action=download\n", "Downloading: 20200801_sct_binaries_linux.tar.gz\n", - "Status: 100% 78.2M/78.2M [00:00<00:00, 136MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210905.280156-5iyukbqf)\n", - "Unzip data to: /tmp/sct-20220627210905.280156-5iyukbqf\n", + "Status: 100% 78.2M/78.2M [00:00<00:00, 81.0MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214830.605099-4v7xj38o)\n", + "Unzip data to: /tmp/sct-20221114214830.605099-4v7xj38o\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1654,9 +2618,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/PAM50'\u001b[0m\n", "Trying URL: https://github.com/sct-data/PAM50/releases/download/r20201104/PAM50-r20201104.zip\n", "Downloading: PAM50-r20201104.zip\n", - "Status: 100% 70.9M/70.9M [00:00<00:00, 120MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210909.264007-2rc2wo28)\n", - "Unzip data to: /tmp/sct-20220627210909.264007-2rc2wo28\n", + "Status: 100% 70.9M/70.9M [00:00<00:00, 127MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214833.831197-l_v6eyan)\n", + "Unzip data to: /tmp/sct-20221114214833.831197-l_v6eyan\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1673,9 +2637,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/gm_model'\u001b[0m\n", "Trying URL: https://osf.io/ugscu/?action=download\n", "Downloading: 20160922_gm_model.zip\n", - "Status: 100% 10.3M/10.3M [00:00<00:00, 52.7MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210910.992265-gpenmlyk)\n", - "Unzip data to: /tmp/sct-20220627210910.992265-gpenmlyk\n", + "Status: 100% 10.3M/10.3M [00:00<00:00, 78.2MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214835.541648-5gm3q7cd)\n", + "Unzip data to: /tmp/sct-20221114214835.541648-5gm3q7cd\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1692,9 +2656,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/optic_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/optic_models/releases/download/r20170413/20170413_optic_models.zip\n", "Downloading: 20170413_optic_models.zip\n", - "Status: 100% 17.7k/17.7k [00:00<00:00, 30.8MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210911.898676-psccb4jb)\n", - "Unzip data to: /tmp/sct-20220627210911.898676-psccb4jb\n", + "Status: 100% 17.7k/17.7k [00:00<00:00, 58.5MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214836.075136-vqkhgt23)\n", + "Unzip data to: /tmp/sct-20221114214836.075136-vqkhgt23\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1711,9 +2675,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/pmj_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/pmj_models/releases/download/r20170922/20170922_pmj_models.zip\n", "Downloading: 20170922_pmj_models.zip\n", - "Status: 100% 8.87k/8.87k [00:00<00:00, 25.4MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210912.651929-z9od011t)\n", - "Unzip data to: /tmp/sct-20220627210912.651929-z9od011t\n", + "Status: 100% 8.87k/8.87k [00:00<00:00, 39.6MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214836.537832-faq1j3xh)\n", + "Unzip data to: /tmp/sct-20221114214836.537832-faq1j3xh\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1730,9 +2694,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_sc_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/deepseg_sc_models/releases/download/r20180610/20180610_deepseg_sc_models.zip\n", "Downloading: 20180610_deepseg_sc_models.zip\n", - "Status: 100% 58.7M/58.7M [00:00<00:00, 117MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210913.953770-ggp5gdvp)\n", - "Unzip data to: /tmp/sct-20220627210913.953770-ggp5gdvp\n", + "Status: 100% 58.7M/58.7M [00:00<00:00, 211MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214837.326176-07mi1nd0)\n", + "Unzip data to: /tmp/sct-20221114214837.326176-07mi1nd0\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1749,9 +2713,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_gm_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/deepseg_gm_models/releases/download/r20180205/20180205_deepseg_gm_models.zip\n", "Downloading: 20180205_deepseg_gm_models.zip\n", - "Status: 100% 2.28M/2.28M [00:00<00:00, 40.0MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210915.559802-9qjgukj4)\n", - "Unzip data to: /tmp/sct-20220627210915.559802-9qjgukj4\n", + "Status: 100% 2.28M/2.28M [00:00<00:00, 160MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214838.375366-8azfct10)\n", + "Unzip data to: /tmp/sct-20221114214838.375366-8azfct10\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1768,9 +2732,9 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/deepseg_lesion_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/deepseg_lesion_models/releases/download/r20180613/20180613_deepseg_lesion_models.zip\n", "Downloading: 20180613_deepseg_lesion_models.zip\n", - "Status: 100% 16.0M/16.0M [00:00<00:00, 121MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210916.547332-pe4os3jf)\n", - "Unzip data to: /tmp/sct-20220627210916.547332-pe4os3jf\n", + "Status: 100% 16.0M/16.0M [00:00<00:00, 230MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214839.072757-e72xl8ly)\n", + "Unzip data to: /tmp/sct-20221114214839.072757-e72xl8ly\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", @@ -1787,13 +2751,13 @@ "\u001b[33mRemoving existing destination folder '/content/spinalcordtoolbox/data/c2c3_disc_models'\u001b[0m\n", "Trying URL: https://github.com/sct-data/c2c3_disc_models/releases/download/r20190117/20190117_c2c3_disc_models.zip\n", "Downloading: 20190117_c2c3_disc_models.zip\n", - "Status: 100% 8.94k/8.94k [00:00<00:00, 27.4MB/s]\n", - "Creating temporary folder (/tmp/sct-20220627210917.476975-pqm_aclp)\n", - "Unzip data to: /tmp/sct-20220627210917.476975-pqm_aclp\n", + "Status: 100% 8.94k/8.94k [00:00<00:00, 39.1MB/s]\n", + "Creating temporary folder (/tmp/sct-20221114214839.655075-0snud1k_)\n", + "Unzip data to: /tmp/sct-20221114214839.655075-0snud1k_\n", "Removing temporary folders...\n", "\u001b[0mDone!\n", "\u001b[0m\n", - "Status: 100% 18.0M/18.0M [00:00<00:00, 46.7MB/s]\n", + "Status: 100% 18.0M/18.0M [00:00<00:00, 196MB/s]\n", "\n", "\u001b[0;32mValidate installation...\u001b[0m\n", "\n", @@ -1807,9 +2771,9 @@ "SCT info:\n", "- version: git-HEAD-e2e19bd02e2a99eab252ad3cca86eee5c5d63e92\n", "- path: /content/spinalcordtoolbox\n", - "OS: linux (Linux-5.4.188+-x86_64-with-debian-buster-sid)\n", + "OS: linux (Linux-5.10.133+-x86_64-with-debian-buster-sid)\n", "CPU cores: Available: 2, Used by ITK functions: 2\n", - "RAM: Total: 12986MB, Used: 1048MB, Available: 11725MB\n", + "RAM: Total: 12985MB, Used: 1072MB, Available: 11690MB\n", "Check Python executable.............................[\u001b[92mOK\u001b[0m]\n", " Using bundled python 3.6.13 |Anaconda, Inc.| (default, Jun 4 2021, 14:25:59) \n", "[GCC 7.5.0] at /content/spinalcordtoolbox/python/envs/venv_sct/bin/python\n", @@ -1861,7 +2825,7 @@ " % Total % Received % Xferd Average Speed Time Time Time Current\n", " Dload Upload Total Spent Left Speed\n", " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n", - "100 212k 100 212k 0 0 639k 0 --:--:-- --:--:-- --:--:-- 639k\n", + "100 212k 100 212k 0 0 1270k 0 --:--:-- --:--:-- --:--:-- 1270k\n", "Archive: niimath_lnx.zip\n", " inflating: /content/niimath/niimath \n", "NIImath installed\n", @@ -1877,7 +2841,7 @@ "os.chdir('/content/')\n", "! git clone https://github.com/osfclient/osfclient\n", "\n", - "% cd osfclient/ \n", + "%cd osfclient/ \n", "\n", "! pip install osfclient\n", "print('OSF client installed')\n", @@ -1887,7 +2851,7 @@ "# Github: https://github.com/spinalcordtoolbox/spinalcordtoolbox/\n", "os.chdir('/content/')\n", "!git clone --depth 1 --branch 5.3.0 https://github.com/spinalcordtoolbox/spinalcordtoolbox\n", - "% cd spinalcordtoolbox/\n", + "%cd spinalcordtoolbox/\n", "!yes | ./install_sct\n", "os.environ['PATH'] += ':/content/spinalcordtoolbox/bin'\n", "os.environ['SCT_DIR'] = '/content/spinalcordtoolbox'\n", @@ -1908,6 +2872,11 @@ }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_VRVpDSER1Ms" + }, + "outputs": [], "source": [ "#Here, the various helper functions are defined\n", "#run_subprocess is a wrapper for subprocess.run\n", @@ -1945,236 +2914,135 @@ " dataframe_mean['STD()'] = pd.to_numeric(dataframe_mean['STD()'], errors='coerce')\n", " STD_matrix=dataframe_mean['STD()'].to_numpy()\n", " return STD_matrix" - ], - "metadata": { - "id": "_VRVpDSER1Ms" - }, - "execution_count": 3, - "outputs": [] + ] }, { "cell_type": "markdown", + "metadata": { + "id": "dTOMtIV_R73f" + }, "source": [ "##Downloading manually corrected data\n", "WARNING: this will overwrite the results from the previous steps" - ], - "metadata": { - "id": "dTOMtIV_R73f" - } + ] }, { "cell_type": "code", - "source": [ - "# Downloading data\n", - "os.chdir('/content/osfclient/')\n", - "! osf -p v4tdk fetch /Paper/SC_rt_shim_manual.zip /content/osfclient/SC_rt_shim_manual.zip\n", - "print(\"Data suscesfully downloaded\")\n", - "zipped_nifti='/content/osfclient/SC_rt_shim_manual.zip'\n", - "if os.path.isdir('/concent/SC_rt_shim/'):\n", - " shutil.shutil.rmtree('/concent/SC_rt_shim')\n", - "with zipfile.ZipFile(zipped_nifti,\"r\") as zip_ref:\n", - " zip_ref.extractall('/content/')\n", - "# clearing up annoying _MACOSX directory\n", - "shutil.rmtree('/content/__MACOSX')\n", - "print(\"Unzipping done\")" - ], + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "f1008274-7123-4f81-ef9d-c1ad23acb40b", - "id": "krJQiw6AU_IG" + "id": "krJQiw6AU_IG", + "outputId": "9c78de30-90e6-4ef1-c060-3b89721920e0" }, - "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "100% 2.44G/2.44G [00:18<00:00, 131Mbytes/s]\n", + "100% 2.44G/2.44G [00:17<00:00, 138Mbytes/s]\n", "Data suscesfully downloaded\n", "Unzipping done\n" ] } + ], + "source": [ + "# Downloading data\n", + "os.chdir('/content/osfclient/')\n", + "! osf -p v4tdk fetch /Paper/SC_rt_shim_manual.zip /content/osfclient/SC_rt_shim_manual.zip\n", + "print(\"Data suscesfully downloaded\")\n", + "zipped_nifti='/content/osfclient/SC_rt_shim_manual.zip'\n", + "if os.path.isdir('/concent/SC_rt_shim/'):\n", + " shutil.shutil.rmtree('/concent/SC_rt_shim')\n", + "with zipfile.ZipFile(zipped_nifti,\"r\") as zip_ref:\n", + " zip_ref.extractall('/content/')\n", + "# clearing up annoying _MACOSX directory\n", + "shutil.rmtree('/content/__MACOSX')\n", + "print(\"Unzipping done\")" ] }, { "cell_type": "markdown", - "source": [ - "##Statistics" - ], "metadata": { "id": "bMcg7vKN0NM3" - } + }, + "source": [ + "##Statistics" + ] }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "id": "okGdpGQzacsw" - }, - "outputs": [], "source": [ - "# Here, we extract the data from the CSF files, convert them all to a numpy matrix\n", - "# and normalize to the signal intensity at TE1\n", + "# Signal along the spinal cord for PAM50 registered TE6\n", + "csvfile_NOSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/noshim_PAM50_sc.csv'\n", + "csvfile_staticSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/staticshim_PAM50_sc.csv'\n", + "csvfile_staticzSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/staticzshim_PAM50_sc.csv'\n", + "csvfile_rtSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/rtshim_PAM50_sc.csv'\n", + "csvfile_rtzSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/rtzshim_PAM50_sc.csv'\n", "\n", - "Subjectdirs=sorted(glob.glob('/content/SC_rt_shim/'+'*acdc*')) ##EG, all the subjects in DATADIR\n", + "noshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_NOSHIM_mutual_coreg)\n", + "staticshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_staticSHIM_mutual_coreg)\n", + "staticzshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_staticzSHIM_mutual_coreg)\n", + "rtshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_rtSHIM_mutual_coreg)\n", + "rtzshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_rtzSHIM_mutual_coreg)\n", "\n", - "for subject in range(len(Subjectdirs)):\n", - " Anatdir = (Subjectdirs[subject]+ '/Anat/')\n", - " Registrationdir=(Subjectdirs[subject]+ '/Anat/Registration/')\n", - " \n", - " #filenames\n", - " csvfile_NOSHIM=Registrationdir+'noshim_data_manual.csv' \n", - " csvfile_STATICSHIM=Registrationdir+'staticshim_data_manual.csv' \n", - " csvfile_STATICZSHIM=Registrationdir+'staticzshim_data_manual.csv' \n", - " csvfile_RTSHIM=Registrationdir+'rtshim_data_manual.csv' \n", - " csvfile_RTZSHIM=Registrationdir+'rtzshim_data_manual.csv' \n", "\n", - " ## Load the CSV file into a Pandas DataFrame\n", - " dataframe_noshim_run1=pd.read_csv(csvfile_NOSHIM, sep=\",\") \n", - " dataframe_staticzshim_run1=pd.read_csv(csvfile_STATICZSHIM, sep=\",\") \n", - " dataframe_staticshim_run1=pd.read_csv(csvfile_STATICSHIM, sep=\",\") \n", - " dataframe_rtshim_run1=pd.read_csv(csvfile_RTSHIM, sep=\",\")\n", - " dataframe_rtzshim_run1=pd.read_csv(csvfile_RTZSHIM, sep=\",\")\n", "\n", - " ## Convert all the strings (123.4242, etc) of the WA column into actual numerical values\n", - " dataframe_noshim_run1['WA()'] = pd.to_numeric(dataframe_noshim_run1['WA()'], errors='coerce')\n", - " dataframe_staticzshim_run1['WA()'] = pd.to_numeric(dataframe_staticzshim_run1['WA()'], errors='coerce')\n", - " dataframe_staticshim_run1['WA()'] = pd.to_numeric(dataframe_staticshim_run1['WA()'], errors='coerce')\n", - " dataframe_rtshim_run1['WA()'] = pd.to_numeric(dataframe_rtshim_run1['WA()'], errors='coerce')\n", - " dataframe_rtzshim_run1['WA()'] = pd.to_numeric(dataframe_rtzshim_run1['WA()'], errors='coerce')\n", - "\n", - " ## Convert all the strings (123.4242, etc) of the STD column into actual numerical values\n", - " dataframe_noshim_run1['STD()'] = pd.to_numeric(dataframe_noshim_run1['STD()'], errors='coerce')\n", - " dataframe_staticzshim_run1['STD()'] = pd.to_numeric(dataframe_staticzshim_run1['STD()'], errors='coerce')\n", - " dataframe_staticshim_run1['STD()'] = pd.to_numeric(dataframe_staticshim_run1['STD()'], errors='coerce')\n", - " dataframe_rtshim_run1['STD()'] = pd.to_numeric(dataframe_rtshim_run1['STD()'], errors='coerce')\n", - " dataframe_rtzshim_run1['STD()'] = pd.to_numeric(dataframe_rtzshim_run1['STD()'], errors='coerce')\n", - "\n", - " ## Determine the number of slices, which is given by the maximum value of the \"Slice (I-->S) of the CSV, plus 1, because the index starts at 0\"\n", - " nSlices=int(np.max(dataframe_noshim_run1.iloc[:,3])+1)\n", - " ## Then the number of echoes is simply the size of the original data deivided by the number of slices\n", - " nEchoes=int(np.size(dataframe_noshim_run1['WA()'])/nSlices)\n", - " \n", - " ## Convert WA column of the Pandas Dataframe into a matrix for easier handling\n", - " WA_matrix_noshim_run1=dataframe_noshim_run1['WA()'].to_numpy()\n", - " WA_matrix_staticzshim_run1=dataframe_staticzshim_run1['WA()'].to_numpy()\n", - " WA_matrix_staticshim_run1=dataframe_staticshim_run1['WA()'].to_numpy()\n", - " WA_matrix_rtshim_run1=dataframe_rtshim_run1['WA()'].to_numpy()\n", - " WA_matrix_rtzshim_run1=dataframe_rtzshim_run1['WA()'].to_numpy()\n", - "\n", - " ## Convert STD column of the Pandas Dataframe into a matrix for easier handling\n", - " STD_matrix_noshim_run1=dataframe_noshim_run1['STD()'].to_numpy()\n", - " STD_matrix_staticzshim_run1=dataframe_staticzshim_run1['STD()'].to_numpy()\n", - " STD_matrix_staticshim_run1=dataframe_staticshim_run1['STD()'].to_numpy()\n", - " STD_matrix_rtshim_run1=dataframe_rtshim_run1['STD()'].to_numpy()\n", - " STD_matrix_rtzshim_run1=dataframe_rtzshim_run1['STD()'].to_numpy()\n", - "\n", - " ## And reshape it so it looks like a echoes-by-slices matrix\n", - " WA_matrix_noshim=WA_matrix_noshim_run1.reshape(nEchoes,nSlices)\n", - " WA_matrix_staticzshim=WA_matrix_staticzshim_run1.reshape(nEchoes,nSlices)\n", - " WA_matrix_staticshim=WA_matrix_staticshim_run1.reshape(nEchoes,nSlices)\n", - " WA_matrix_rtshim=WA_matrix_rtshim_run1.reshape(nEchoes,nSlices)\n", - " WA_matrix_rtzshim=WA_matrix_rtzshim_run1.reshape(nEchoes,nSlices)\n", - "\n", - " ## And reshape it so it looks like a echoes-by-slices matrix\n", - " STD_matrix_noshim=STD_matrix_noshim_run1.reshape(nEchoes,nSlices)\n", - " STD_matrix_staticzshim=STD_matrix_staticzshim_run1.reshape(nEchoes,nSlices)\n", - " STD_matrix_staticshim=STD_matrix_staticshim_run1.reshape(nEchoes,nSlices)\n", - " STD_matrix_rtshim=STD_matrix_rtshim_run1.reshape(nEchoes,nSlices)\n", - " STD_matrix_rtzshim=STD_matrix_rtzshim_run1.reshape(nEchoes,nSlices)\n", - "\n", - "\n", - " ## concatenate subjects to form one matrix for plotting\n", - " if subject == 0:\n", - " WA_matrix_noshim_last = WA_matrix_noshim\n", - " WA_matrix_staticzshim_last = WA_matrix_staticzshim\n", - " WA_matrix_staticshim_last = WA_matrix_staticshim\n", - " WA_matrix_rtshim_last = WA_matrix_rtshim\n", - " WA_matrix_rtzshim_last = WA_matrix_rtzshim\n", - "\n", - " STD_matrix_noshim_last = STD_matrix_noshim\n", - " STD_matrix_staticzshim_last = STD_matrix_staticzshim\n", - " STD_matrix_staticshim_last = STD_matrix_staticshim\n", - " STD_matrix_rtshim_last = STD_matrix_rtshim\n", - " STD_matrix_rtzshim_last = STD_matrix_rtzshim\n", - " else:\n", - " WA_matrix_noshim = np.concatenate([WA_matrix_noshim_last, WA_matrix_noshim], axis=1)\n", - " WA_matrix_staticzshim = np.concatenate([WA_matrix_staticzshim_last, WA_matrix_staticzshim], axis=1)\n", - " WA_matrix_staticshim = np.concatenate([WA_matrix_staticshim_last, WA_matrix_staticshim], axis=1)\n", - " WA_matrix_rtshim = np.concatenate([WA_matrix_rtshim_last, WA_matrix_rtshim], axis=1)\n", - " WA_matrix_rtzshim = np.concatenate([WA_matrix_rtzshim_last, WA_matrix_rtzshim], axis=1)\n", - "\n", - " STD_matrix_noshim = np.concatenate([STD_matrix_noshim_last, STD_matrix_noshim], axis=1)\n", - " STD_matrix_staticzshim = np.concatenate([STD_matrix_staticzshim_last, STD_matrix_staticzshim], axis=1)\n", - " STD_matrix_staticshim = np.concatenate([STD_matrix_staticshim_last, STD_matrix_staticshim], axis=1)\n", - " STD_matrix_rtshim = np.concatenate([STD_matrix_rtshim_last, STD_matrix_rtshim], axis=1)\n", - " STD_matrix_rtzshim = np.concatenate([STD_matrix_rtzshim_last, STD_matrix_rtzshim], axis=1)\n", - " \n", - " WA_matrix_noshim_last = WA_matrix_noshim\n", - " WA_matrix_staticzshim_last = WA_matrix_staticzshim\n", - " WA_matrix_staticshim_last = WA_matrix_staticshim\n", - " WA_matrix_rtshim_last = WA_matrix_rtshim\n", - " WA_matrix_rtzshim_last = WA_matrix_rtzshim\n", - "\n", - " STD_matrix_noshim_last = STD_matrix_noshim\n", - " STD_matrix_staticzshim_last = STD_matrix_staticzshim\n", - " STD_matrix_staticshim_last = STD_matrix_staticshim\n", - " STD_matrix_rtshim_last = STD_matrix_rtshim\n", - " STD_matrix_rtzshim_last = STD_matrix_rtzshim\n", - "\n", - " ##end of subject loop\n", "# normalize data to the mean TE1 across all slices and all subjects\n", - "mean_TE1 = np.nanmean(WA_matrix_noshim, axis=1)[0]\n", + "mean_TE1 = np.nanmean(noshim_coreg_alongcord, axis=1)[0]\n", "\n", - "WA_matrix_noshim = 100*WA_matrix_noshim/mean_TE1\n", - "WA_matrix_staticzshim = 100*WA_matrix_staticzshim/mean_TE1\n", - "WA_matrix_rtzshim = 100*WA_matrix_rtzshim/mean_TE1\n", - "WA_matrix_staticshim = 100*WA_matrix_staticshim/mean_TE1\n", - "WA_matrix_rtshim = 100*WA_matrix_rtshim/mean_TE1" - ] + "noshim_coreg_alongcord = 100*noshim_coreg_alongcord/mean_TE1\n", + "staticzshim_coreg_alongcord = 100*staticzshim_coreg_alongcord/mean_TE1\n", + "rtzshim_coreg_alongcord = 100*rtzshim_coreg_alongcord/mean_TE1\n", + "staticshim_coreg_alongcord = 100*staticshim_coreg_alongcord/mean_TE1\n", + "rtshim_coreg_alongcord = 100*rtshim_coreg_alongcord/mean_TE1" + ], + "metadata": { + "id": "hAnkTehALgmE" + }, + "execution_count": null, + "outputs": [] }, { "cell_type": "code", "source": [ "################################# Statistical tests ########################################\n", - "\n", - "WA_matrix_noshim_te0 = WA_matrix_noshim[0].ravel() \n", - "WA_matrix_staticzshim_te0 = WA_matrix_staticzshim[0].ravel() \n", - "WA_matrix_staticshim_te0 = WA_matrix_staticshim[0].ravel() \n", - "WA_matrix_rtzshim_te0 = WA_matrix_rtzshim[0].ravel() \n", - "WA_matrix_rtshim_te0 = WA_matrix_rtshim[0].ravel() \n", - "\n", - "WA_matrix_noshim_te1 = WA_matrix_noshim[1].ravel() \n", - "WA_matrix_staticzshim_te1 = WA_matrix_staticzshim[1].ravel() \n", - "WA_matrix_staticshim_te1 = WA_matrix_staticshim[1].ravel() \n", - "WA_matrix_rtzshim_te1 = WA_matrix_rtzshim[1].ravel()\n", - "WA_matrix_rtshim_te1 = WA_matrix_rtshim[1].ravel() \n", - "\n", - "WA_matrix_noshim_te2 = WA_matrix_noshim[2].ravel() \n", - "WA_matrix_staticzshim_te2 = WA_matrix_staticzshim[2].ravel() \n", - "WA_matrix_staticshim_te2 = WA_matrix_staticshim[2].ravel() \n", - "WA_matrix_rtzshim_te2 = WA_matrix_rtzshim[2].ravel()\n", - "WA_matrix_rtshim_te2 = WA_matrix_rtshim[2].ravel() \n", - "\n", - "WA_matrix_noshim_te3 = WA_matrix_noshim[3].ravel() \n", - "WA_matrix_staticzshim_te3 = WA_matrix_staticzshim[3].ravel() \n", - "WA_matrix_staticshim_te3 = WA_matrix_staticshim[3].ravel() \n", - "WA_matrix_rtzshim_te3 = WA_matrix_rtzshim[3].ravel() \n", - "WA_matrix_rtshim_te3 = WA_matrix_rtshim[3].ravel() \n", - "\n", - "WA_matrix_noshim_te4 = WA_matrix_noshim[4].ravel() \n", - "WA_matrix_staticzshim_te4 = WA_matrix_staticzshim[4].ravel() \n", - "WA_matrix_staticshim_te4 = WA_matrix_staticshim[4].ravel() \n", - "WA_matrix_rtzshim_te4 = WA_matrix_rtzshim[4].ravel() \n", - "WA_matrix_rtshim_te4 = WA_matrix_rtshim[4].ravel() \n", - "\n", - "WA_matrix_noshim_te5 = WA_matrix_noshim[5].ravel() \n", - "WA_matrix_staticzshim_te5 = WA_matrix_staticzshim[5].ravel() \n", - "WA_matrix_staticshim_te5 = WA_matrix_staticshim[5].ravel() \n", - "WA_matrix_rtzshim_te5 = WA_matrix_rtzshim[5].ravel() \n", - "WA_matrix_rtshim_te5 = WA_matrix_rtshim[5].ravel() \n", + "noshim_coreg_alongcord_te0 = noshim_coreg_alongcord[0].ravel() \n", + "staticzshim_coreg_alongcord_te0 = staticzshim_coreg_alongcord[0].ravel() \n", + "staticshim_coreg_alongcord_te0 = staticshim_coreg_alongcord[0].ravel() \n", + "rtzshim_coreg_alongcord_te0 = rtzshim_coreg_alongcord[0].ravel() \n", + "rtshim_coreg_alongcord_te0 = rtshim_coreg_alongcord[0].ravel() \n", + "\n", + "noshim_coreg_alongcord_te1 = noshim_coreg_alongcord[1].ravel() \n", + "staticzshim_coreg_alongcord_te1 = staticzshim_coreg_alongcord[1].ravel() \n", + "staticshim_coreg_alongcord_te1 = staticshim_coreg_alongcord[1].ravel() \n", + "rtzshim_coreg_alongcord_te1 = rtzshim_coreg_alongcord[1].ravel()\n", + "rtshim_coreg_alongcord_te1 = rtshim_coreg_alongcord[1].ravel() \n", + "\n", + "noshim_coreg_alongcord_te2 = noshim_coreg_alongcord[2].ravel() \n", + "staticzshim_coreg_alongcord_te2 = staticzshim_coreg_alongcord[2].ravel() \n", + "staticshim_coreg_alongcord_te2 = staticshim_coreg_alongcord[2].ravel() \n", + "rtzshim_coreg_alongcord_te2 = rtzshim_coreg_alongcord[2].ravel()\n", + "rtshim_coreg_alongcord_te2 = rtshim_coreg_alongcord[2].ravel() \n", + "\n", + "noshim_coreg_alongcord_te3 = noshim_coreg_alongcord[3].ravel() \n", + "staticzshim_coreg_alongcord_te3 = staticzshim_coreg_alongcord[3].ravel() \n", + "staticshim_coreg_alongcord_te3 = staticshim_coreg_alongcord[3].ravel() \n", + "rtzshim_coreg_alongcord_te3 = rtzshim_coreg_alongcord[3].ravel() \n", + "rtshim_coreg_alongcord_te3 = rtshim_coreg_alongcord[3].ravel() \n", + "\n", + "noshim_coreg_alongcord_te4 = noshim_coreg_alongcord[4].ravel() \n", + "staticzshim_coreg_alongcord_te4 = staticzshim_coreg_alongcord[4].ravel() \n", + "staticshim_coreg_alongcord_te4 = staticshim_coreg_alongcord[4].ravel() \n", + "rtzshim_coreg_alongcord_te4 = rtzshim_coreg_alongcord[4].ravel() \n", + "rtshim_coreg_alongcord_te4 = rtshim_coreg_alongcord[4].ravel() \n", + "\n", + "noshim_coreg_alongcord_te5 = noshim_coreg_alongcord[5].ravel() \n", + "staticzshim_coreg_alongcord_te5 = staticzshim_coreg_alongcord[5].ravel() \n", + "staticshim_coreg_alongcord_te5 = staticshim_coreg_alongcord[5].ravel() \n", + "rtzshim_coreg_alongcord_te5 = rtzshim_coreg_alongcord[5].ravel() \n", + "rtshim_coreg_alongcord_te5 = rtshim_coreg_alongcord[5].ravel() \n", "\n", "################################ Normality Tests ###############################\n", "# Shapiro-Wilk Test\n", @@ -2186,46 +3054,52 @@ "# H1: the sample does not have a Gaussian distribution.\n", "print(\"\\nShapiro-Wilks test\")\n", "\n", - "print(\"Shapiro no-shim TE1: \", scipy.stats.shapiro( WA_matrix_noshim_te0[~np.isnan(WA_matrix_noshim_te0)] ) )\n", - "print(\"Shapiro staticz-shim TE1: \", scipy.stats.shapiro( WA_matrix_staticzshim_te0[~np.isnan(WA_matrix_staticzshim_te0)] ) )\n", - "print(\"Shapiro static-shim TE1: \", scipy.stats.shapiro( WA_matrix_staticshim_te0[~np.isnan(WA_matrix_staticshim_te0)] ) )\n", - "print(\"Shapiro: rtz-shim TE1\", scipy.stats.shapiro( WA_matrix_rtzshim_te0[~np.isnan(WA_matrix_rtzshim_te0)] ) )\n", - "print(\"Shapiro: rt-shim TE1\", scipy.stats.shapiro( WA_matrix_rtshim_te0[~np.isnan(WA_matrix_rtshim_te0)] ) )\n", - "\n", - "print(\"\\n\")\n", - "print(\"Shapiro no-shim TE2: \", scipy.stats.shapiro( WA_matrix_noshim_te1[~np.isnan(WA_matrix_noshim_te1)] ) )\n", - "print(\"Shapiro staticz-shim TE2: \", scipy.stats.shapiro( WA_matrix_staticzshim_te1[~np.isnan(WA_matrix_staticzshim_te1)] ) )\n", - "print(\"Shapiro static-shim TE2: \", scipy.stats.shapiro( WA_matrix_staticshim_te1[~np.isnan(WA_matrix_staticshim_te1)] ) )\n", - "print(\"Shapiro rtz-shim TE2: \", scipy.stats.shapiro( WA_matrix_rtzshim_te1[~np.isnan(WA_matrix_rtzshim_te1)] ) )\n", - "print(\"Shapiro rt-shim TE2: \", scipy.stats.shapiro( WA_matrix_rtshim_te1[~np.isnan(WA_matrix_rtshim_te1)] ) )\n", - "\n", - "print(\"\\n\")\n", - "print(\"Shapiro no-shim TE3: \", scipy.stats.shapiro( WA_matrix_noshim_te2[~np.isnan(WA_matrix_noshim_te2)] ) )\n", - "print(\"Shapiro staticz-shim TE3: \", scipy.stats.shapiro( WA_matrix_staticzshim_te2[~np.isnan(WA_matrix_staticzshim_te2)] ) )\n", - "print(\"Shapiro static-shim TE3: \", scipy.stats.shapiro( WA_matrix_staticshim_te2[~np.isnan(WA_matrix_staticshim_te2)] ) )\n", - "print(\"Shapiro rtz-shim TE3: \", scipy.stats.shapiro( WA_matrix_rtzshim_te2[~np.isnan(WA_matrix_rtzshim_te2)] ) )\n", - "print(\"Shapiro rt-shim TE3: \", scipy.stats.shapiro( WA_matrix_rtshim_te2[~np.isnan(WA_matrix_rtshim_te2)] ) )\n", - "\n", - "print(\"\\n\")\n", - "print(\"Shapiro no-shim TE4: \", scipy.stats.shapiro( WA_matrix_noshim_te3[~np.isnan(WA_matrix_noshim_te3)] ) )\n", - "print(\"Shapiro staticz-shim TE4: \", scipy.stats.shapiro( WA_matrix_staticzshim_te3[~np.isnan(WA_matrix_staticzshim_te3)] ) )\n", - "print(\"Shapiro static-shim TE4: \", scipy.stats.shapiro( WA_matrix_staticshim_te3[~np.isnan(WA_matrix_staticshim_te3)] ) )\n", - "print(\"Shapiro rtz-shim TE4: \", scipy.stats.shapiro( WA_matrix_rtzshim_te3[~np.isnan(WA_matrix_rtzshim_te3)] ) )\n", - "print(\"Shapiro rt-shim TE4: \", scipy.stats.shapiro( WA_matrix_rtshim_te3[~np.isnan(WA_matrix_rtshim_te3)] ) )\n", - "\n", - "print(\"\\n\")\n", - "print(\"Shapiro no-shim TE5: \", scipy.stats.shapiro( WA_matrix_noshim_te4[~np.isnan(WA_matrix_noshim_te4)] ) )\n", - "print(\"Shapiro staticz-shim TE5: \", scipy.stats.shapiro( WA_matrix_staticzshim_te4[~np.isnan(WA_matrix_staticzshim_te4)] ) )\n", - "print(\"Shapiro static-shim TE5: \", scipy.stats.shapiro( WA_matrix_staticshim_te4[~np.isnan(WA_matrix_staticshim_te4)] ) )\n", - "print(\"Shapiro rtz-shim TE5: \", scipy.stats.shapiro( WA_matrix_rtzshim_te4[~np.isnan(WA_matrix_rtzshim_te4)] ) )\n", - "print(\"Shapiro rt-shim TE5: \", scipy.stats.shapiro( WA_matrix_rtshim_te4[~np.isnan(WA_matrix_rtshim_te4)] ) )\n", - "\n", - "print(\"\\n\")\n", - "print(\"Shapiro no-shim TE6: \", scipy.stats.shapiro( WA_matrix_noshim_te5[~np.isnan(WA_matrix_noshim_te5)] ) )\n", - "print(\"Shapiro staticz-shim TE6: \", scipy.stats.shapiro( WA_matrix_staticzshim_te5[~np.isnan(WA_matrix_staticzshim_te5)] ) )\n", - "print(\"Shapiro static-shim TE6: \", scipy.stats.shapiro( WA_matrix_staticshim_te5[~np.isnan(WA_matrix_staticshim_te5)] ) )\n", - "print(\"Shapiro rtz-shim TE6: \", scipy.stats.shapiro( WA_matrix_rtzshim_te5[~np.isnan(WA_matrix_rtzshim_te5)] ) )\n", - "print(\"Shapiro rt-shim TE6: \", scipy.stats.shapiro( WA_matrix_rtshim_te5[~np.isnan(WA_matrix_rtshim_te5)] ) )\n", + "pval_noshim = np.zeros(6)\n", + "pval_noshim[0] = scipy.stats.shapiro( noshim_coreg_alongcord_te0[~np.isnan(noshim_coreg_alongcord_te0)] )[1]\n", + "pval_noshim[1] = scipy.stats.shapiro( noshim_coreg_alongcord_te1[~np.isnan(noshim_coreg_alongcord_te1)] )[1]\n", + "pval_noshim[2] = scipy.stats.shapiro( noshim_coreg_alongcord_te2[~np.isnan(noshim_coreg_alongcord_te2)] )[1]\n", + "pval_noshim[3] = scipy.stats.shapiro( noshim_coreg_alongcord_te3[~np.isnan(noshim_coreg_alongcord_te3)] )[1]\n", + "pval_noshim[4] = scipy.stats.shapiro( noshim_coreg_alongcord_te4[~np.isnan(noshim_coreg_alongcord_te4)] )[1]\n", + "pval_noshim[5] = scipy.stats.shapiro( noshim_coreg_alongcord_te5[~np.isnan(noshim_coreg_alongcord_te5)] )[1]\n", + "\n", + "pval_staticz = np.zeros(6)\n", + "pval_staticz[0] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te0[~np.isnan(staticzshim_coreg_alongcord_te0)] )[1]\n", + "pval_staticz[1] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te1[~np.isnan(staticzshim_coreg_alongcord_te1)] )[1]\n", + "pval_staticz[2] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te2[~np.isnan(staticzshim_coreg_alongcord_te2)] )[1]\n", + "pval_staticz[3] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te3[~np.isnan(staticzshim_coreg_alongcord_te3)] )[1]\n", + "pval_staticz[4] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te4[~np.isnan(staticzshim_coreg_alongcord_te4)] )[1]\n", + "pval_staticz[5] = scipy.stats.shapiro( staticzshim_coreg_alongcord_te5[~np.isnan(staticzshim_coreg_alongcord_te5)] )[1]\n", + "\n", + "pval_static = np.zeros(6)\n", + "pval_static[0] = scipy.stats.shapiro( staticshim_coreg_alongcord_te0[~np.isnan(staticshim_coreg_alongcord_te0)] )[1]\n", + "pval_static[1] = scipy.stats.shapiro( staticshim_coreg_alongcord_te1[~np.isnan(staticshim_coreg_alongcord_te1)] )[1]\n", + "pval_static[2] = scipy.stats.shapiro( staticshim_coreg_alongcord_te2[~np.isnan(staticshim_coreg_alongcord_te2)] )[1]\n", + "pval_static[3] = scipy.stats.shapiro( staticshim_coreg_alongcord_te3[~np.isnan(staticshim_coreg_alongcord_te3)] )[1]\n", + "pval_static[4] = scipy.stats.shapiro( staticshim_coreg_alongcord_te4[~np.isnan(staticshim_coreg_alongcord_te4)] )[1]\n", + "pval_static[5] = scipy.stats.shapiro( staticshim_coreg_alongcord_te5[~np.isnan(staticshim_coreg_alongcord_te5)] )[1]\n", + "\n", + "pval_rtz = np.zeros(6)\n", + "pval_rtz[0] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te0[~np.isnan(rtzshim_coreg_alongcord_te0)] )[1]\n", + "pval_rtz[1] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te1[~np.isnan(rtzshim_coreg_alongcord_te1)] )[1]\n", + "pval_rtz[2] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te2[~np.isnan(rtzshim_coreg_alongcord_te2)] )[1]\n", + "pval_rtz[3] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te3[~np.isnan(rtzshim_coreg_alongcord_te3)] )[1]\n", + "pval_rtz[4] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te4[~np.isnan(rtzshim_coreg_alongcord_te4)] )[1]\n", + "pval_rtz[5] = scipy.stats.shapiro( rtzshim_coreg_alongcord_te5[~np.isnan(rtzshim_coreg_alongcord_te5)] )[1]\n", + "\n", + "pval_rt = np.zeros(6)\n", + "pval_rt[0] = scipy.stats.shapiro( rtshim_coreg_alongcord_te0[~np.isnan(rtshim_coreg_alongcord_te0)] )[1]\n", + "pval_rt[1] = scipy.stats.shapiro( rtshim_coreg_alongcord_te1[~np.isnan(rtshim_coreg_alongcord_te1)] )[1]\n", + "pval_rt[2] = scipy.stats.shapiro( rtshim_coreg_alongcord_te2[~np.isnan(rtshim_coreg_alongcord_te2)] )[1]\n", + "pval_rt[3] = scipy.stats.shapiro( rtshim_coreg_alongcord_te3[~np.isnan(rtshim_coreg_alongcord_te3)] )[1]\n", + "pval_rt[4] = scipy.stats.shapiro( rtshim_coreg_alongcord_te4[~np.isnan(rtshim_coreg_alongcord_te4)] )[1]\n", + "pval_rt[5] = scipy.stats.shapiro( rtshim_coreg_alongcord_te5[~np.isnan(rtshim_coreg_alongcord_te5)] )[1]\n", + "\n", + "# correct for multiple comparisons with step-down method using Bonferroni adjustments\n", + "print(\"\\nCorrected no-shim p-values across TEs\",smm.multipletests(pval_noshim, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected staticz p-values across TEs\",smm.multipletests(pval_staticz, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected static p-values across TEs\",smm.multipletests(pval_static, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected rtz p-values across TEs\",smm.multipletests(pval_rtz, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected rt p-values across TEs\",smm.multipletests(pval_rt, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", "\n", "################################################################################\n", "\n", @@ -2237,49 +3111,52 @@ "# than the Mann Whitney test, it has less power to detect a shift in the median but more power to detect changes in the shape of the distribution.\n", "print(\"\\nKolomogorov-Smirnov test\")\n", "\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE1: \", scipy.stats.ks_2samp(WA_matrix_noshim[0], WA_matrix_staticzshim[0], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE1: \", scipy.stats.ks_2samp(WA_matrix_noshim[0], WA_matrix_staticshim[0], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE1: \", scipy.stats.ks_2samp(WA_matrix_noshim[0], WA_matrix_rtzshim[0], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE1: \", scipy.stats.ks_2samp(WA_matrix_noshim[0], WA_matrix_rtshim[0], alternative='two-sided', mode='auto'))\n", - "\n", - "print(\"\\n\")\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE2: \", scipy.stats.ks_2samp(WA_matrix_noshim[1], WA_matrix_staticzshim[1], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE2: \", scipy.stats.ks_2samp(WA_matrix_noshim[1], WA_matrix_staticshim[1], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE2: \", scipy.stats.ks_2samp(WA_matrix_noshim[1], WA_matrix_rtzshim[1], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE2: \", scipy.stats.ks_2samp(WA_matrix_noshim[1], WA_matrix_rtshim[1], alternative='two-sided', mode='auto'))\n", - "\n", - "print(\"\\n\")\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE3: \", scipy.stats.ks_2samp(WA_matrix_noshim[2], WA_matrix_staticzshim[2], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE3: \", scipy.stats.ks_2samp(WA_matrix_noshim[2], WA_matrix_staticshim[2], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE3: \", scipy.stats.ks_2samp(WA_matrix_noshim[2], WA_matrix_rtzshim[2], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE3: \", scipy.stats.ks_2samp(WA_matrix_noshim[2], WA_matrix_rtshim[2], alternative='two-sided', mode='auto'))\n", - "\n", - "print(\"\\n\")\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE4: \", scipy.stats.ks_2samp(WA_matrix_noshim[3], WA_matrix_staticzshim[3], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE4: \", scipy.stats.ks_2samp(WA_matrix_noshim[3], WA_matrix_staticshim[3], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE4: \", scipy.stats.ks_2samp(WA_matrix_noshim[3], WA_matrix_rtzshim[3], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE4: \", scipy.stats.ks_2samp(WA_matrix_noshim[3], WA_matrix_rtshim[3], alternative='two-sided', mode='auto'))\n", - "\n", - "print(\"\\n\")\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE5: \", scipy.stats.ks_2samp(WA_matrix_noshim[4], WA_matrix_staticzshim[4], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE5: \", scipy.stats.ks_2samp(WA_matrix_noshim[4], WA_matrix_staticshim[4], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE5: \", scipy.stats.ks_2samp(WA_matrix_noshim[4], WA_matrix_rtzshim[4], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE5: \", scipy.stats.ks_2samp(WA_matrix_noshim[4], WA_matrix_rtshim[4], alternative='two-sided', mode='auto'))\n", - "\n", - "print(\"\\n\")\n", - "print(\"Kolomogorov-Smirnov no-shim/staticz TE6: \", scipy.stats.ks_2samp(WA_matrix_noshim[5], WA_matrix_staticzshim[5], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/static TE6: \", scipy.stats.ks_2samp(WA_matrix_noshim[5], WA_matrix_staticshim[5], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rtz-shim TE6: \", scipy.stats.ks_2samp(WA_matrix_noshim[5], WA_matrix_rtzshim[5], alternative='two-sided', mode='auto'))\n", - "print(\"Kolomogorov-Smirnov no-shim/rt-shim TE6: \", scipy.stats.ks_2samp(WA_matrix_noshim[5], WA_matrix_rtshim[5], alternative='two-sided', mode='auto'))\n" + "pval_staticz = np.zeros(6)\n", + "pval_staticz[0] = scipy.stats.ks_2samp(noshim_coreg_alongcord[0], staticzshim_coreg_alongcord[0], alternative='two-sided', mode='auto')[1]\n", + "pval_staticz[1] = scipy.stats.ks_2samp(noshim_coreg_alongcord[1], staticzshim_coreg_alongcord[1], alternative='two-sided', mode='auto')[1]\n", + "pval_staticz[2] = scipy.stats.ks_2samp(noshim_coreg_alongcord[2], staticzshim_coreg_alongcord[2], alternative='two-sided', mode='auto')[1]\n", + "pval_staticz[3] = scipy.stats.ks_2samp(noshim_coreg_alongcord[3], staticzshim_coreg_alongcord[3], alternative='two-sided', mode='auto')[1]\n", + "pval_staticz[4] = scipy.stats.ks_2samp(noshim_coreg_alongcord[4], staticzshim_coreg_alongcord[4], alternative='two-sided', mode='auto')[1]\n", + "pval_staticz[5] = scipy.stats.ks_2samp(noshim_coreg_alongcord[5], staticzshim_coreg_alongcord[5], alternative='two-sided', mode='auto')[1]\n", + "\n", + "pval_static = np.zeros(6)\n", + "pval_static[0] = scipy.stats.ks_2samp(noshim_coreg_alongcord[0], staticshim_coreg_alongcord[0], alternative='two-sided', mode='auto')[1]\n", + "pval_static[1] = scipy.stats.ks_2samp(noshim_coreg_alongcord[1], staticshim_coreg_alongcord[1], alternative='two-sided', mode='auto')[1]\n", + "pval_static[2] = scipy.stats.ks_2samp(noshim_coreg_alongcord[2], staticshim_coreg_alongcord[2], alternative='two-sided', mode='auto')[1]\n", + "pval_static[3] = scipy.stats.ks_2samp(noshim_coreg_alongcord[3], staticshim_coreg_alongcord[3], alternative='two-sided', mode='auto')[1]\n", + "pval_static[4] = scipy.stats.ks_2samp(noshim_coreg_alongcord[4], staticshim_coreg_alongcord[4], alternative='two-sided', mode='auto')[1]\n", + "pval_static[5] = scipy.stats.ks_2samp(noshim_coreg_alongcord[5], staticshim_coreg_alongcord[5], alternative='two-sided', mode='auto')[1]\n", + "\n", + "pval_rtz = np.zeros(6)\n", + "pval_rtz[0] = scipy.stats.ks_2samp(noshim_coreg_alongcord[0], rtzshim_coreg_alongcord[0], alternative='two-sided', mode='auto')[1]\n", + "pval_rtz[1] = scipy.stats.ks_2samp(noshim_coreg_alongcord[1], rtzshim_coreg_alongcord[1], alternative='two-sided', mode='auto')[1]\n", + "pval_rtz[2] = scipy.stats.ks_2samp(noshim_coreg_alongcord[2], rtzshim_coreg_alongcord[2], alternative='two-sided', mode='auto')[1]\n", + "pval_rtz[3] = scipy.stats.ks_2samp(noshim_coreg_alongcord[3], rtzshim_coreg_alongcord[3], alternative='two-sided', mode='auto')[1]\n", + "pval_rtz[4] = scipy.stats.ks_2samp(noshim_coreg_alongcord[4], rtzshim_coreg_alongcord[4], alternative='two-sided', mode='auto')[1]\n", + "pval_rtz[5] = scipy.stats.ks_2samp(noshim_coreg_alongcord[5], rtzshim_coreg_alongcord[5], alternative='two-sided', mode='auto')[1]\n", + "\n", + "pval_rt = np.zeros(6)\n", + "pval_rt[0] = scipy.stats.ks_2samp(noshim_coreg_alongcord[0], rtshim_coreg_alongcord[0], alternative='two-sided', mode='auto')[1]\n", + "pval_rt[1] = scipy.stats.ks_2samp(noshim_coreg_alongcord[1], rtshim_coreg_alongcord[1], alternative='two-sided', mode='auto')[1]\n", + "pval_rt[2] = scipy.stats.ks_2samp(noshim_coreg_alongcord[2], rtshim_coreg_alongcord[2], alternative='two-sided', mode='auto')[1]\n", + "pval_rt[3] = scipy.stats.ks_2samp(noshim_coreg_alongcord[3], rtshim_coreg_alongcord[3], alternative='two-sided', mode='auto')[1]\n", + "pval_rt[4] = scipy.stats.ks_2samp(noshim_coreg_alongcord[4], rtshim_coreg_alongcord[4], alternative='two-sided', mode='auto')[1]\n", + "pval_rt[5] = scipy.stats.ks_2samp(noshim_coreg_alongcord[5], rtshim_coreg_alongcord[5], alternative='two-sided', mode='auto')[1]\n", + "\n", + "# correct for multiple comparisons with step-down method using Bonferroni adjustments\n", + "print(\"\\nCorrected no-shim/staticz p-values across TEs\",smm.multipletests(pval_staticz, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected no-shim/static p-values across TEs\",smm.multipletests(pval_static, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected no-shim/rtz p-values across TEs\",smm.multipletests(pval_rtz, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))\n", + "print(\"\\nCorrected no-shim/rt p-values across TEs\",smm.multipletests(pval_rt, alpha=0.05, method='holm', is_sorted=False, returnsorted=False))" ], "metadata": { + "id": "Ry1tTcQOGQMr", "colab": { "base_uri": "https://localhost:8080/" }, - "id": "G7imz8PZ-fX7", - "outputId": "cd8d4d9c-d0ea-43fd-cd80-efc317011b7f" + "outputId": "c8c7e7fd-4585-41ba-f422-932bee00d657" }, - "execution_count": 6, + "execution_count": null, "outputs": [ { "output_type": "stream", @@ -2287,82 +3164,35 @@ "text": [ "\n", "Shapiro-Wilks test\n", - "Shapiro no-shim TE1: (0.9652987718582153, 0.0010411093244329095)\n", - "Shapiro staticz-shim TE1: (0.9677944779396057, 0.0018106092466041446)\n", - "Shapiro static-shim TE1: (0.974546492099762, 0.00872368086129427)\n", - "Shapiro: rtz-shim TE1 (0.9689107537269592, 0.002330321352928877)\n", - "Shapiro: rt-shim TE1 (0.9713160991668701, 0.004055242519825697)\n", - "\n", - "\n", - "Shapiro no-shim TE2: (0.9693750143051147, 0.0025904683861881495)\n", - "Shapiro staticz-shim TE2: (0.9691835641860962, 0.0024796787183731794)\n", - "Shapiro static-shim TE2: (0.9803386330604553, 0.03648284077644348)\n", - "Shapiro rtz-shim TE2: (0.9621898531913757, 0.0005332897999323905)\n", - "Shapiro rt-shim TE2: (0.9689111709594727, 0.0023305348586291075)\n", "\n", + "Corrected no-shim p-values across TEs (array([ True, True, True, True, True, True]), array([0.00042622, 0.00068763, 0.00068763, 0.00068763, 0.00047023,\n", + " 0.00045506]), 0.008512444610847103, 0.008333333333333333)\n", "\n", - "Shapiro no-shim TE3: (0.9714934229850769, 0.004226683173328638)\n", - "Shapiro staticz-shim TE3: (0.9683528542518616, 0.002053427742794156)\n", - "Shapiro static-shim TE3: (0.978032112121582, 0.0204778965562582)\n", - "Shapiro rtz-shim TE3: (0.9503465890884399, 5.037541268393397e-05)\n", - "Shapiro rt-shim TE3: (0.9665979146957397, 0.0013861077604815364)\n", + "Corrected staticz p-values across TEs (array([ True, True, True, True, True, True]), array([9.00529903e-06, 9.00529903e-06, 5.33506091e-06, 5.81484130e-06,\n", + " 9.00529903e-06, 9.00529903e-06]), 0.008512444610847103, 0.008333333333333333)\n", "\n", + "Corrected static p-values across TEs (array([ True, True, True, True, True, True]), array([1.91545783e-04, 1.91545783e-04, 1.91545783e-04, 1.01494843e-04,\n", + " 1.33792579e-04, 9.33815827e-05]), 0.008512444610847103, 0.008333333333333333)\n", "\n", - "Shapiro no-shim TE4: (0.9760855436325073, 0.012674431316554546)\n", - "Shapiro staticz-shim TE4: (0.9734691381454468, 0.006738336756825447)\n", - "Shapiro static-shim TE4: (0.9852957725524902, 0.12801550328731537)\n", - "Shapiro rtz-shim TE4: (0.9486023783683777, 3.640976865426637e-05)\n", - "Shapiro rt-shim TE4: (0.9593674540519714, 0.00029604637529700994)\n", + "Corrected rtz p-values across TEs (array([ True, True, True, True, True, True]), array([6.24550994e-05, 2.92959030e-04, 4.61710297e-04, 1.39380002e-03,\n", + " 1.39380002e-03, 1.05934491e-03]), 0.008512444610847103, 0.008333333333333333)\n", "\n", - "\n", - "Shapiro no-shim TE5: (0.978424072265625, 0.02257521077990532)\n", - "Shapiro staticz-shim TE5: (0.9809345006942749, 0.04240604117512703)\n", - "Shapiro static-shim TE5: (0.9890961050987244, 0.3229781687259674)\n", - "Shapiro rtz-shim TE5: (0.9609077572822571, 0.00040729917236603796)\n", - "Shapiro rt-shim TE5: (0.9551640748977661, 0.00012714364856947213)\n", - "\n", - "\n", - "Shapiro no-shim TE6: (0.979246973991394, 0.027728212997317314)\n", - "Shapiro staticz-shim TE6: (0.9778770208358765, 0.019704174250364304)\n", - "Shapiro static-shim TE6: (0.9879125952720642, 0.24431189894676208)\n", - "Shapiro rtz-shim TE6: (0.9720308780670166, 0.004793934058398008)\n", - "Shapiro rt-shim TE6: (0.958885908126831, 0.00026822503423318267)\n", + "Corrected rt p-values across TEs (array([ True, True, True, True, True, True]), array([5.83029796e-05, 5.83029796e-05, 1.41564044e-05, 8.02978548e-06,\n", + " 1.41564044e-05, 5.83029796e-05]), 0.008512444610847103, 0.008333333333333333)\n", "\n", "Kolomogorov-Smirnov test\n", - "Kolomogorov-Smirnov no-shim/staticz TE1: Ks_2sampResult(statistic=0.16666666666666666, pvalue=0.03646025028290547)\n", - "Kolomogorov-Smirnov no-shim/static TE1: Ks_2sampResult(statistic=0.18055555555555555, pvalue=0.018122331816097997)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE1: Ks_2sampResult(statistic=0.1736111111111111, pvalue=0.025889016751966105)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE1: Ks_2sampResult(statistic=0.1597222222222222, pvalue=0.050622064096640156)\n", - "\n", "\n", - "Kolomogorov-Smirnov no-shim/staticz TE2: Ks_2sampResult(statistic=0.14583333333333334, pvalue=0.0935118065526648)\n", - "Kolomogorov-Smirnov no-shim/static TE2: Ks_2sampResult(statistic=0.2569444444444444, pvalue=0.00013814565830984495)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE2: Ks_2sampResult(statistic=0.1875, pvalue=0.012505473374179999)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE2: Ks_2sampResult(statistic=0.14583333333333334, pvalue=0.0935118065526648)\n", + "Corrected no-shim/staticz p-values across TEs (array([False, False, False, False, False, True]), array([0.53424056, 0.53424056, 0.11051327, 0.13998261, 0.07893814,\n", + " 0.0070264 ]), 0.008512444610847103, 0.008333333333333333)\n", "\n", + "Corrected no-shim/static p-values across TEs (array([ True, True, True, True, False, False]), array([0.00948565, 0.00948565, 0.0070264 , 0.0070264 , 0.15215048,\n", + " 0.66475056]), 0.008512444610847103, 0.008333333333333333)\n", "\n", - "Kolomogorov-Smirnov no-shim/staticz TE3: Ks_2sampResult(statistic=0.11805555555555555, pvalue=0.26879778755049666)\n", - "Kolomogorov-Smirnov no-shim/static TE3: Ks_2sampResult(statistic=0.2152777777777778, pvalue=0.0024557542471025447)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE3: Ks_2sampResult(statistic=0.1736111111111111, pvalue=0.025889016751966105)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE3: Ks_2sampResult(statistic=0.10416666666666667, pvalue=0.4165474607267425)\n", + "Corrected no-shim/rtz p-values across TEs (array([False, False, False, False, False, False]), array([0.45645145, 1. , 1. , 1. , 1. ,\n", + " 1. ]), 0.008512444610847103, 0.008333333333333333)\n", "\n", - "\n", - "Kolomogorov-Smirnov no-shim/staticz TE4: Ks_2sampResult(statistic=0.10416666666666667, pvalue=0.4165474607267425)\n", - "Kolomogorov-Smirnov no-shim/static TE4: Ks_2sampResult(statistic=0.19444444444444445, pvalue=0.008506631146449378)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE4: Ks_2sampResult(statistic=0.1736111111111111, pvalue=0.025889016751966105)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE4: Ks_2sampResult(statistic=0.09722222222222222, pvalue=0.5055804801940361)\n", - "\n", - "\n", - "Kolomogorov-Smirnov no-shim/staticz TE5: Ks_2sampResult(statistic=0.09722222222222222, pvalue=0.5055804801940361)\n", - "Kolomogorov-Smirnov no-shim/static TE5: Ks_2sampResult(statistic=0.18055555555555555, pvalue=0.018122331816097997)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE5: Ks_2sampResult(statistic=0.1597222222222222, pvalue=0.050622064096640156)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE5: Ks_2sampResult(statistic=0.10416666666666667, pvalue=0.4165474607267425)\n", - "\n", - "\n", - "Kolomogorov-Smirnov no-shim/staticz TE6: Ks_2sampResult(statistic=0.09027777777777778, pvalue=0.6019586109019183)\n", - "Kolomogorov-Smirnov no-shim/static TE6: Ks_2sampResult(statistic=0.1527777777777778, pvalue=0.06929261213490762)\n", - "Kolomogorov-Smirnov no-shim/rtz-shim TE6: Ks_2sampResult(statistic=0.11805555555555555, pvalue=0.26879778755049666)\n", - "Kolomogorov-Smirnov no-shim/rt-shim TE6: Ks_2sampResult(statistic=0.11805555555555555, pvalue=0.26879778755049666)\n" + "Corrected no-shim/rt p-values across TEs (array([False, False, True, True, True, True]), array([6.64750559e-01, 3.64113821e-01, 2.61103130e-02, 1.90284818e-04,\n", + " 4.53967389e-05, 9.68018697e-05]), 0.008512444610847103, 0.008333333333333333)\n" ] } ] @@ -2371,152 +3201,109 @@ "cell_type": "code", "source": [ "# print tables with numerical results\n", - "# note : need to make these tables easier to read. ideally I'd like to have mean(std) together\n", - "\n", - "median_STD_matrix_noshim = np.nanmedian(STD_matrix_noshim, axis=1)\n", - "median_STD_matrix_staticzshim = np.nanmedian(STD_matrix_staticzshim, axis=1)\n", - "median_STD_matrix_staticshim = np.nanmedian(STD_matrix_staticshim, axis=1)\n", - "median_STD_matrix_rtshim = np.nanmedian(STD_matrix_rtshim, axis=1)\n", - "\n", - "table = [[\"no shim STD median\",np.around(median_STD_matrix_noshim,decimals=2)], \\\n", - " [\"static z-shim STD median\",np.around(median_STD_matrix_staticzshim,decimals=2)], \\\n", - " [\"rt z-shim STD median\",np.around(np.nanmedian(STD_matrix_rtzshim, axis=1),decimals=2)], \\\n", - " [\"static xyz-shim STD median\",np.around(median_STD_matrix_staticshim,decimals=2)], \\\n", - " [\"rt xyz-shim STD median\",np.around(median_STD_matrix_rtshim,decimals=2)]]\n", - "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n", "\n", - "median_percent_diff_STD_matrix_staticzshim = 100*(np.nanmedian(STD_matrix_staticzshim, axis=1)-np.nanmedian(STD_matrix_noshim, axis=1))/np.nanmedian(STD_matrix_noshim, axis=1)\n", - "median_percent_diff_STD_matrix_rtzshim = 100*(np.nanmedian(STD_matrix_rtzshim, axis=1)-np.nanmedian(STD_matrix_noshim, axis=1))/np.nanmedian(STD_matrix_noshim, axis=1)\n", - "median_percent_diff_STD_matrix_staticshim = 100*(np.nanmedian(STD_matrix_staticshim, axis=1)-np.nanmedian(STD_matrix_noshim, axis=1))/np.nanmedian(STD_matrix_noshim, axis=1)\n", - "median_percent_diff_STD_matrix_rtshim = 100*(np.nanmedian(STD_matrix_rtshim, axis=1)-np.nanmedian(STD_matrix_noshim, axis=1))/np.nanmedian(STD_matrix_noshim, axis=1)\n", - "\n", - "table = [[\"static z-shim STD median % diff\",np.around(median_percent_diff_STD_matrix_staticzshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_STD_matrix_staticzshim),decimals=2)], \\\n", - " [\"rt z-shim STD median % diff\",np.around(median_percent_diff_STD_matrix_rtzshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_STD_matrix_rtzshim),decimals=2)], \\\n", - " [\"static xyz-shim STD median % diff\",np.around(median_percent_diff_STD_matrix_staticshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_STD_matrix_staticshim),decimals=2)], \\\n", - " [\"rt xyz-shim STD median % diff\",np.around(median_percent_diff_STD_matrix_rtshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_STD_matrix_rtshim),decimals=2)]]\n", + "mean_noshim_coreg_alongcord = np.nanmean(noshim_coreg_alongcord, axis=1)\n", + "mean_staticzshim_coreg_alongcord = np.nanmean(staticzshim_coreg_alongcord, axis=1)\n", + "mean_staticshim_coreg_alongcord = np.nanmean(staticshim_coreg_alongcord, axis=1)\n", + "mean_rtzshim_coreg_alongcord = np.nanmean(rtzshim_coreg_alongcord, axis=1)\n", + "mean_rtshim_coreg_alongcord = np.nanmean(rtshim_coreg_alongcord, axis=1)\n", + "\n", + "table = [[\"no shim mean\",np.around(mean_noshim_coreg_alongcord,decimals=2)], \\\n", + " [\"static z-shim mean\",np.around(mean_staticzshim_coreg_alongcord,decimals=2)], \\\n", + " [\"static xyz-shim mean\",np.around(mean_rtzshim_coreg_alongcord,decimals=2)], \\\n", + " [\"rt z-shim mean\",np.around(mean_staticshim_coreg_alongcord,decimals=2)], \\\n", + " [\"rt xyz-shim mean\",np.around(mean_rtshim_coreg_alongcord,decimals=2)]]\n", "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n", "\n", + "mean_percent_diff_staticzshim_coreg_alongcord = 100*(np.nanmean(staticzshim_coreg_alongcord, axis=1)-np.nanmean(noshim_coreg_alongcord, axis=1))/np.nanmean(noshim_coreg_alongcord, axis=1)\n", + "mean_percent_diff_rtzshim_coreg_alongcord = 100*(np.nanmean(rtzshim_coreg_alongcord, axis=1)-np.nanmean(noshim_coreg_alongcord, axis=1))/np.nanmean(noshim_coreg_alongcord, axis=1)\n", + "mean_percent_diff_staticshim_coreg_alongcord = 100*(np.nanmean(staticshim_coreg_alongcord, axis=1)-np.nanmean(noshim_coreg_alongcord, axis=1))/np.nanmean(noshim_coreg_alongcord, axis=1)\n", + "mean_percent_diff_rtshim_coreg_alongcord = 100*(np.nanmean(rtshim_coreg_alongcord, axis=1)-np.nanmean(noshim_coreg_alongcord, axis=1))/np.nanmean(noshim_coreg_alongcord, axis=1)\n", "\n", - "median_WA_matrix_noshim = np.nanmedian(WA_matrix_noshim, axis=1)\n", - "median_WA_matrix_staticzshim = np.nanmedian(WA_matrix_staticzshim, axis=1)\n", - "median_WA_matrix_staticshim = np.nanmedian(WA_matrix_staticshim, axis=1)\n", - "median_WA_matrix_rtshim = np.nanmedian(WA_matrix_rtshim, axis=1)\n", - "\n", - "table = [[\"no shim median\",np.around(median_WA_matrix_noshim,decimals=2)], \\\n", - " [\"static z-shim median\",np.around(median_WA_matrix_staticzshim,decimals=2)], \\\n", - " [\"rt z-shim median\",np.around(np.nanmedian(WA_matrix_rtzshim, axis=1),decimals=2)], \\\n", - " [\"static xyz-shim median\",np.around(median_WA_matrix_staticshim,decimals=2)], \\\n", - " [\"rt xyz-shim median\",np.around(median_WA_matrix_rtshim,decimals=2)]]\n", + "table = [[\"static z-shim mean % diff\",np.around(mean_percent_diff_staticzshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(mean_percent_diff_staticzshim_coreg_alongcord),decimals=2)], \\\n", + " [\"static xyz-shim mean % diff\",np.around(mean_percent_diff_staticshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(mean_percent_diff_staticshim_coreg_alongcord),decimals=2)], \\\n", + " [\"rt z-shim mean % diff\",np.around(mean_percent_diff_rtzshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(mean_percent_diff_rtzshim_coreg_alongcord),decimals=2)], \\\n", + " [\"rt xyz-shim mean % diff\",np.around(mean_percent_diff_rtshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(mean_percent_diff_rtshim_coreg_alongcord),decimals=2)]]\n", "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n", "\n", - "median_percent_diff_WA_matrix_staticzshim = 100*(np.nanmedian(WA_matrix_staticzshim, axis=1)-np.nanmedian(WA_matrix_noshim, axis=1))/np.nanmedian(WA_matrix_noshim, axis=1)\n", - "median_percent_diff_WA_matrix_rtzshim = 100*(np.nanmedian(WA_matrix_rtzshim, axis=1)-np.nanmedian(WA_matrix_noshim, axis=1))/np.nanmedian(WA_matrix_noshim, axis=1)\n", - "median_percent_diff_WA_matrix_staticshim = 100*(np.nanmedian(WA_matrix_staticshim, axis=1)-np.nanmedian(WA_matrix_noshim, axis=1))/np.nanmedian(WA_matrix_noshim, axis=1)\n", - "median_percent_diff_WA_matrix_rtshim = 100*(np.nanmedian(WA_matrix_rtshim, axis=1)-np.nanmedian(WA_matrix_noshim, axis=1))/np.nanmedian(WA_matrix_noshim, axis=1)\n", "\n", - "table = [[\"static z-shim median % diff\",np.around(median_percent_diff_WA_matrix_staticzshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_WA_matrix_staticzshim),decimals=2)], \\\n", - " [\"rt z-shim median % diff\",np.around(median_percent_diff_WA_matrix_rtzshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_WA_matrix_rtzshim),decimals=2)], \\\n", - " [\"static xyz-shim median % diff\",np.around(median_percent_diff_WA_matrix_staticshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_WA_matrix_staticshim),decimals=2)], \\\n", - " [\"rt xyz-shim median % diff\",np.around(median_percent_diff_WA_matrix_rtshim,decimals=2),\"median\",np.around(np.median(median_percent_diff_WA_matrix_rtshim),decimals=2)]]\n", - "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n", + "std_noshim_coreg_alongcord = np.nanstd(noshim_coreg_alongcord, axis=1)\n", + "std_staticzshim_coreg_alongcord = np.nanstd(staticzshim_coreg_alongcord, axis=1)\n", + "std_staticshim_coreg_alongcord = np.nanstd(staticshim_coreg_alongcord, axis=1)\n", + "std_rtzshim_coreg_alongcord = np.nanstd(rtzshim_coreg_alongcord, axis=1)\n", + "std_rtshim_coreg_alongcord = np.nanstd(rtshim_coreg_alongcord, axis=1)\n", "\n", - "IQR_WA_matrix_noshim = np.nanpercentile(WA_matrix_noshim, 75, axis=1)-np.nanpercentile(WA_matrix_noshim, 25, axis=1)\n", - "IQR_WA_matrix_staticzshim = np.nanpercentile(WA_matrix_staticzshim, 75, axis=1)-np.nanpercentile(WA_matrix_staticzshim, 25, axis=1)\n", - "IQR_WA_matrix_rtzshim = np.nanpercentile(WA_matrix_rtzshim, 75, axis=1)-np.nanpercentile(WA_matrix_rtzshim, 25, axis=1)\n", - "IQR_WA_matrix_staticshim = np.nanpercentile(WA_matrix_staticshim, 75, axis=1)-np.nanpercentile(WA_matrix_staticshim, 25, axis=1)\n", - "IQR_WA_matrix_rtshim = np.nanpercentile(WA_matrix_rtshim, 75, axis=1)-np.nanpercentile(WA_matrix_rtshim, 25, axis=1)\n", - "\n", - "table = [[\"no shim IQR\",np.around(IQR_WA_matrix_noshim,decimals=2)], \\\n", - " [\"static z-shim IQR\",np.around(IQR_WA_matrix_staticzshim,decimals=2)], \\\n", - " [\"rt z-shim IQR\",np.around(IQR_WA_matrix_rtzshim,decimals=2)], \\\n", - " [\"static xyz-shim IQR\",np.around(IQR_WA_matrix_staticshim,decimals=2)], \\\n", - " [\"rt xyz-shim IQR\",np.around(IQR_WA_matrix_rtshim,decimals=2)]]\n", + "table = [[\"no shim std\",np.around(std_noshim_coreg_alongcord,decimals=2)], \\\n", + " [\"static z-shim std\",np.around(std_staticzshim_coreg_alongcord,decimals=2)], \\\n", + " [\"static xyz-shim std\",np.around(std_staticshim_coreg_alongcord,decimals=2)], \\\n", + " [\"rt z-shim std\",np.around(std_rtzshim_coreg_alongcord,decimals=2)], \\\n", + " [\"rt xyz-shim std\",np.around(std_rtshim_coreg_alongcord,decimals=2)]]\n", "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n", "\n", - "IQR_percent_diff_WA_matrix_staticzshim = 100*(IQR_WA_matrix_staticzshim - IQR_WA_matrix_noshim)/IQR_WA_matrix_noshim\n", - "IQR_percent_diff_WA_matrix_rtzshim = 100*(IQR_WA_matrix_rtzshim - IQR_WA_matrix_noshim)/IQR_WA_matrix_noshim\n", - "IQR_percent_diff_WA_matrix_staticshim = 100*(IQR_WA_matrix_staticshim - IQR_WA_matrix_noshim)/IQR_WA_matrix_noshim\n", - "IQR_percent_diff_WA_matrix_rtshim = 100*(IQR_WA_matrix_rtshim - IQR_WA_matrix_noshim)/IQR_WA_matrix_noshim\n", + "std_percent_diff_staticzshim_coreg_alongcord = 100*(std_staticzshim_coreg_alongcord-std_noshim_coreg_alongcord)/std_noshim_coreg_alongcord\n", + "std_percent_diff_rtzshim_coreg_alongcord = 100*(std_rtzshim_coreg_alongcord-std_noshim_coreg_alongcord)/std_noshim_coreg_alongcord\n", + "std_percent_diff_staticshim_coreg_alongcord = 100*(std_staticshim_coreg_alongcord-std_noshim_coreg_alongcord)/std_noshim_coreg_alongcord\n", + "std_percent_diff_rtshim_coreg_alongcord = 100*(std_rtshim_coreg_alongcord-std_noshim_coreg_alongcord)/std_noshim_coreg_alongcord\n", "\n", - "table = [[\"static z-shim IQR % diff\",np.around(IQR_percent_diff_WA_matrix_staticzshim,decimals=2),\"median\",np.around(np.median(IQR_percent_diff_WA_matrix_staticzshim),decimals=2)], \\\n", - " [\"rt z-shim IQR % diff\",np.around(IQR_percent_diff_WA_matrix_rtzshim,decimals=2),\"median\",np.around(np.median(IQR_percent_diff_WA_matrix_rtzshim),decimals=2)], \\\n", - " [\"static xyz-shim IQR % diff\",np.around(IQR_percent_diff_WA_matrix_staticshim,decimals=2),\"median\",np.around(np.median(IQR_percent_diff_WA_matrix_staticshim),decimals=2)], \\\n", - " [\"rt xyz-shim IQR % diff\",np.around(IQR_percent_diff_WA_matrix_rtshim,decimals=2),\"median\",np.around(np.median(IQR_percent_diff_WA_matrix_rtshim),decimals=2)]]\n", - "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))" + "table = [[\"static z-shim std % diff\",np.around(std_percent_diff_staticzshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(std_percent_diff_staticzshim_coreg_alongcord),decimals=2)], \\\n", + " [\"static xyz-shim std % diff\",np.around(std_percent_diff_staticshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(std_percent_diff_staticshim_coreg_alongcord),decimals=2)], \\\n", + " [\"rt z-shim std % diff\",np.around(std_percent_diff_rtzshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(std_percent_diff_rtzshim_coreg_alongcord),decimals=2)], \\\n", + " [\"rt xyz-shim std % diff\",np.around(std_percent_diff_rtshim_coreg_alongcord,decimals=2),\"mean\",np.around(np.mean(std_percent_diff_rtshim_coreg_alongcord),decimals=2)]]\n", + "print(tabulate(table, headers=[], tablefmt=\"fancy_grid\"))\n" ], "metadata": { - "id": "SdoJ_yh1-lo8", + "id": "ihIsVZ3aGUNL", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "9a308974-d31e-4170-b759-a79ef935c800" + "outputId": "146147a1-cd1e-4672-d8c9-038774f04b96" }, - "execution_count": 7, + "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "╒════════════════════════════╤═══════════════════════════════════════╕\n", - "│ no shim STD median │ [11.6 13.38 15.49 16.86 17.46 19.64] │\n", - "├────────────────────────────┼───────────────────────────────────────┤\n", - "│ static z-shim STD median │ [13.64 14.09 15. 17.58 18.52 19.38] │\n", - "├────────────────────────────┼───────────────────────────────────────┤\n", - "│ rt z-shim STD median │ [13.87 15.65 17.42 20.08 21.43 23.39] │\n", - "├────────────────────────────┼───────────────────────────────────────┤\n", - "│ static xyz-shim STD median │ [13.52 15.08 18.05 21.09 22.58 24.83] │\n", - "├────────────────────────────┼───────────────────────────────────────┤\n", - "│ rt xyz-shim STD median │ [13.86 14.79 16.8 18.75 21.09 22.99] │\n", - "╘════════════════════════════╧═══════════════════════════════════════╛\n", - "╒═══════════════════════════════════╤═══════════════════════════════════════╤════════╤═══════╕\n", - "│ static z-shim STD median % diff │ [17.56 5.33 -3.14 4.25 6.08 -1.33] │ median │ 4.79 │\n", - "├───────────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ rt z-shim STD median % diff │ [19.52 16.99 12.43 19.08 22.71 19.09] │ median │ 19.09 │\n", - "├───────────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ static xyz-shim STD median % diff │ [16.51 12.72 16.52 25.04 29.31 26.43] │ median │ 20.78 │\n", - "├───────────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ rt xyz-shim STD median % diff │ [19.45 10.58 8.44 11.2 20.76 17.06] │ median │ 14.13 │\n", - "╘═══════════════════════════════════╧═══════════════════════════════════════╧════════╧═══════╛\n", - "╒════════════════════════╤═══════════════════════════════════════╕\n", - "│ no shim median │ [98.7 94.55 89.76 84.76 79.77 74.88] │\n", - "├────────────────────────┼───────────────────────────────────────┤\n", - "│ static z-shim median │ [95.55 91.94 88.2 83.05 77.56 73.39] │\n", - "├────────────────────────┼───────────────────────────────────────┤\n", - "│ rt z-shim median │ [94.67 90.65 86.65 81.63 76.7 71.43] │\n", - "├────────────────────────┼───────────────────────────────────────┤\n", - "│ static xyz-shim median │ [95.16 88.84 84.84 79.49 74.57 69.38] │\n", - "├────────────────────────┼───────────────────────────────────────┤\n", - "│ rt xyz-shim median │ [95.38 92.19 89.18 83.3 77.64 73.22] │\n", - "╘════════════════════════╧═══════════════════════════════════════╛\n", - "╒═══════════════════════════════╤═══════════════════════════════════════╤════════╤═══════╕\n", - "│ static z-shim median % diff │ [-3.19 -2.76 -1.74 -2.01 -2.77 -1.99] │ median │ -2.39 │\n", - "├───────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ rt z-shim median % diff │ [-4.08 -4.12 -3.46 -3.69 -3.84 -4.61] │ median │ -3.96 │\n", - "├───────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ static xyz-shim median % diff │ [-3.58 -6.04 -5.49 -6.22 -6.52 -7.35] │ median │ -6.13 │\n", - "├───────────────────────────────┼───────────────────────────────────────┼────────┼───────┤\n", - "│ rt xyz-shim median % diff │ [-3.36 -2.49 -0.65 -1.72 -2.67 -2.22] │ median │ -2.36 │\n", - "╘═══════════════════════════════╧═══════════════════════════════════════╧════════╧═══════╛\n", - "╒═════════════════════╤═══════════════════════════════════════╕\n", - "│ no shim IQR │ [16.32 14.57 15.01 16.99 16.72 18.03] │\n", - "├─────────────────────┼───────────────────────────────────────┤\n", - "│ static z-shim IQR │ [16.31 16. 15.43 15.46 14.6 14.52] │\n", - "├─────────────────────┼───────────────────────────────────────┤\n", - "│ rt z-shim IQR │ [19.46 17.15 15.64 13.85 15. 13.98] │\n", - "├─────────────────────┼───────────────────────────────────────┤\n", - "│ static xyz-shim IQR │ [18.17 19.72 20.14 19.45 20.08 21.26] │\n", - "├─────────────────────┼───────────────────────────────────────┤\n", - "│ rt xyz-shim IQR │ [19.26 17.38 14.74 14.02 15.3 16.58] │\n", - "╘═════════════════════╧═══════════════════════════════════════╛\n", - "╒════════════════════════════╤═════════════════════════════════════════════╤════════╤═══════╕\n", - "│ static z-shim IQR % diff │ [ -0.05 9.82 2.82 -9.03 -12.71 -19.49] │ median │ -4.54 │\n", - "├────────────────────────────┼─────────────────────────────────────────────┼────────┼───────┤\n", - "│ rt z-shim IQR % diff │ [ 19.26 17.73 4.23 -18.5 -10.26 -22.48] │ median │ -3.02 │\n", - "├────────────────────────────┼─────────────────────────────────────────────┼────────┼───────┤\n", - "│ static xyz-shim IQR % diff │ [11.33 35.36 34.2 14.45 20.07 17.88] │ median │ 18.97 │\n", - "├────────────────────────────┼─────────────────────────────────────────────┼────────┼───────┤\n", - "│ rt xyz-shim IQR % diff │ [ 18.05 19.31 -1.79 -17.46 -8.5 -8.04] │ median │ -4.91 │\n", - "╘════════════════════════════╧═════════════════════════════════════════════╧════════╧═══════╛\n" + "╒══════════════════════╤═════════════════════════════════════════════╕\n", + "│ no shim mean │ [100. 94.97 89.7 84.29 78.79 73.18] │\n", + "├──────────────────────┼─────────────────────────────────────────────┤\n", + "│ static z-shim mean │ [99.11 95.07 90.84 85.69 80.32 75.13] │\n", + "├──────────────────────┼─────────────────────────────────────────────┤\n", + "│ static xyz-shim mean │ [98.52 94.4 90.04 84.88 79.54 74.15] │\n", + "├──────────────────────┼─────────────────────────────────────────────┤\n", + "│ rt z-shim mean │ [97.59 92.4 87.71 82.85 78.2 73.42] │\n", + "├──────────────────────┼─────────────────────────────────────────────┤\n", + "│ rt xyz-shim mean │ [99.06 95.07 91.16 85.98 80.73 75.79] │\n", + "╘══════════════════════╧═════════════════════════════════════════════╛\n", + "╒═════════════════════════════╤═══════════════════════════════════════╤══════╤═══════╕\n", + "│ static z-shim mean % diff │ [-0.89 0.1 1.27 1.65 1.94 2.67] │ mean │ 1.12 │\n", + "├─────────────────────────────┼───────────────────────────────────────┼──────┼───────┤\n", + "│ static xyz-shim mean % diff │ [-2.41 -2.71 -2.23 -1.71 -0.75 0.33] │ mean │ -1.58 │\n", + "├─────────────────────────────┼───────────────────────────────────────┼──────┼───────┤\n", + "│ rt z-shim mean % diff │ [-1.48 -0.6 0.37 0.69 0.95 1.33] │ mean │ 0.21 │\n", + "├─────────────────────────────┼───────────────────────────────────────┼──────┼───────┤\n", + "│ rt xyz-shim mean % diff │ [-0.94 0.1 1.62 2.01 2.47 3.57] │ mean │ 1.47 │\n", + "╘═════════════════════════════╧═══════════════════════════════════════╧══════╧═══════╛\n", + "╒═════════════════════╤═════════════════════════════════╕\n", + "│ no shim std │ [4.57 4.38 4.4 4.53 4.57 4.61] │\n", + "├─────────────────────┼─────────────────────────────────┤\n", + "│ static z-shim std │ [4.17 4. 3.95 3.94 3.99 4.16] │\n", + "├─────────────────────┼─────────────────────────────────┤\n", + "│ static xyz-shim std │ [4.56 4.61 4.71 4.44 4.52 4.5 ] │\n", + "├─────────────────────┼─────────────────────────────────┤\n", + "│ rt z-shim std │ [4.27 4.34 4.3 4.62 4.86 5.32] │\n", + "├─────────────────────┼─────────────────────────────────┤\n", + "│ rt xyz-shim std │ [3.89 3.56 3.41 3.5 3.81 4.3 ] │\n", + "╘═════════════════════╧═════════════════════════════════╛\n", + "╒════════════════════════════╤═════════════════════════════════════════════╤══════╤════════╕\n", + "│ static z-shim std % diff │ [ -8.72 -8.6 -10.24 -13.09 -12.59 -9.9 ] │ mean │ -10.52 │\n", + "├────────────────────────────┼─────────────────────────────────────────────┼──────┼────────┤\n", + "│ static xyz-shim std % diff │ [-0.17 5.41 7.05 -2.09 -1.13 -2.34] │ mean │ 1.12 │\n", + "├────────────────────────────┼─────────────────────────────────────────────┼──────┼────────┤\n", + "│ rt z-shim std % diff │ [-6.64 -0.86 -2.12 2.01 6.43 15.31] │ mean │ 2.36 │\n", + "├────────────────────────────┼─────────────────────────────────────────────┼──────┼────────┤\n", + "│ rt xyz-shim std % diff │ [-14.79 -18.69 -22.54 -22.89 -16.65 -6.83] │ mean │ -17.06 │\n", + "╘════════════════════════════╧═════════════════════════════════════════════╧══════╧════════╛\n" ] } ] @@ -2524,42 +3311,39 @@ { "cell_type": "markdown", "source": [ - "## Visualisation: violin plot\n" + "## Visualisation: PAM50 registered MGRE scans violin plots" ], "metadata": { - "id": "gh8JEG_6TKEt" + "id": "et-1JcV7GdjY" } }, { "cell_type": "code", "source": [ - "## Violin plot\n", - "\n", - "A = np.concatenate((WA_matrix_noshim[...,None], WA_matrix_staticzshim[...,None]), axis=2)\n", - "B = np.concatenate((A, WA_matrix_staticshim[...,None]), axis=2)\n", - "C = np.concatenate((B, WA_matrix_rtzshim[...,None]), axis=2)\n", - "D = np.concatenate((C, WA_matrix_rtshim[...,None]), axis=2)\n", + "A = np.concatenate((noshim_coreg_alongcord[...,None], staticzshim_coreg_alongcord[...,None]), axis=2)\n", + "B = np.concatenate((A, staticshim_coreg_alongcord[...,None]), axis=2)\n", + "C = np.concatenate((B, rtzshim_coreg_alongcord[...,None]), axis=2)\n", + "D = np.concatenate((C, rtshim_coreg_alongcord[...,None]), axis=2)\n", "\n", "dim1, dim2, dim3 = np.meshgrid(np.arange(D.shape[0]), np.arange(D.shape[1]), np.arange(D.shape[2]), indexing='ij')\n", "plt.figure(figsize=(30, 15))\n", "sns.set(font_scale = 2.3)\n", - "ax = sns.violinplot(x=dim1.ravel(), y=D.ravel(), hue=dim3.ravel(), palette=\"Set3\", bw=0.20)\n", + "ax = sns.violinplot(x=dim1.ravel(), y=D.ravel(), hue=dim3.ravel(), palette=\"Set3\", bw=0.5)\n", "ax.set_xticklabels(['2.3', '4.5', '6.7','8.9','11.1','13.3'])\n", "ax.set_xlabel(\"Echo time [ms]\")\n", "ax.set_ylabel(\"Signal Intensity [a.u.]\")\n", "ax.legend(handles=ax.legend_.legendHandles, labels=['no shim', 'static z-shim','static xyz-shim','rt z-shim','rt xyz-shim'])\n", - "plt.show()\n", - "\n" + "plt.show()" ], "metadata": { + "id": "Ru_8fXYvGlgu", "colab": { "base_uri": "https://localhost:8080/", - "height": 644 + "height": 912 }, - "id": "GSdtkF5B-p0S", - "outputId": "8b08912e-2cb8-4498-bc16-a0e240f696c3" + "outputId": "de22990a-1c57-41d0-b878-3c2225e81a3c" }, - "execution_count": 12, + "execution_count": null, "outputs": [ { "output_type": "display_data", @@ -2567,38 +3351,47 @@ "text/plain": [ "
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PW8Yb98VzqV69pvvr5ORk1a/f0KPbz8vL00svvaBff92tqlWr6o033laVKlVLXLZ27TpatWpdmbddp87Fuv/+frr//n5yOp1KTNyhL774TN9887Xi4r7V3LnX6q677vXUU8F5YFSQFxsbe87buPXWW3XrrbdWaF2LxaLevXurd+/e51xHZeMKahwGjqo6HGbUXLQDxeFwuNuJAeBC47oeGvB5BgAAAAAALjjR0dHq12+AMjIyNGvWJ1q79udij7umxTyTQ4cK7k8XGVmtxBBP0mnbLW0fFWmKiI6OVq1aUTp8+JBWrfrOff85T3njjfFau/ZnBQUFady4N1W37iUe3b6LxWLRlVdepREjRispaY+2bUvQ2rU/E+QZ5uw/MUAZuO5XZGJHnin3nisa5JnSRQgA3sDUmgAAAAAA+F5OTs4ZHw8JCZEkWa3FQ7Tw8ILpMYve++7PIiIKljl+/FiJnXfp6en6+OPppa7v2sfZ9nMmt9/eU5K0ePHX2rp1S4W2UZJPPvmvvv76K0nSsGEj1bx5C49st6KvB/wfQR48wj2Foo/rqAhTBoSLhnemhI+uT7qYMA0oAHOYct0GAAAAAKAymzhxgl566XnFxi4vFrZlZ2dr6dJv9Nln/5Mk3XBD8W62Bg0KpqlMStqjjRvjS9x206YtFBoaJqfTqZEjhykpaY+kgnHojRvjNWjQQGVkpJdaW7169dz3m/vqq7kVuvXPffc9oHr1LlVubq6GDn1aX375fzp5sjAUPHTooGbPnqkpU94u8zZjY5dr6tT/SJIGDHhct93Wtdx1lWbgwIf11luvad26NcrMzHB///jx45o+/QNt2LBe0umvB/yfUVNrwn+5r4NGTa35x3SghoRif55a0ywEebhwpKenac+e3Wra1DOfpsLpzLsGAgAAAABQ+eTl5SkuLlZxcQW3xAoNDVVAQKDS09Pcwdnll9fX4MFDi63XokVLXXbZ5UpK2qNBgwbKbrfLbo+QJN199326++6+stvtGjx4qCZMGKtNmzbqgQfuUmhomByOfGVnZys0NEyvvfaWhgx5osTagoND1LVrd82fP1cffDBZM2ZMVWRkNVksFl1zTRONGTP+rM8vLCxcb8V0i3sAACAASURBVL75roYNe1a7d+/SxIkTNGnS67LbI5SXl6usrCxJUvv2N5X5mP344yr3sZk79wvNnftFqcvee+8D6tv3wTJvOz09TXPmxGjOnBhZLBaFh4fL4XAWC/VuuaWTunf/W5m3Cf9AkAePcHfkGRXkFTBlQJipNQEzLFgwRwkJm3XppZeXepNinBvX9dCUe5wCAAAAAMwUGhqhd975wddlnLPQ0AivbPfhhx/VlVdepY0b45WUtEcpKSnKzMxQ1apVdfnlDdShwy3q0aO3goKCiq1ns9k0adJ/NGPGVK1d+7OOHDmsgweTJUlpaWnu5Xr27K2oqGjNmvWptm9PUG5urmrUqKlWrdrq/vsfOut95YYOfV5RUdFaseJb7d+/V4cPH5LT6VR0dO0yP8fateto+vSZWrRogWJjl2nXrp1KT09TlSpVdemll6t167YV7qo7dizljI9nZWWWa3ujR4/TunU/65dfNujAgf06dixFeXl5qlUrSldeebW6deuu9u07VKhW+JbFaWLyUgmlpKQbPSC5aNFXWr36e9kjIjTshVG+LqdMXn/9FaWmpqpbt5664Ya/+rqcs9q373e9//47kqTnnx9pREAwZ87nio9fq4vrXKwnnxp69hWASuD11/+t1NQTevbZF1W9eg1fl1MpLVmyUN9/v0JXXHGVHnroUV+XAwAAAAAwzMGDvyk6+lJflwGgkirvNcZqtahGDXvpj3uiKMAVB5uYC9OR5z0WS8ElxmI151KTnp6mpKRffV0GKgETr4emMLkLHAAAAAAAACgPc0bXYQSLgfdCM2UguGjHpik1WyyWYv83QUzMLE2bNkW5ubm+LgWGM+Xn1EROJ1NrAvC87OxszZ//5VmntwEAAAAA4HwiyMMFz5yOvPwiX5tRs9VaEOBZLeZcanbv3inJnK7Hyi4/P19ffz3PPU+6SQjyvIeOPADe8OuvO7VmzY+Ki1vu61IAAAAAAHAzZ3Qdfs3dcGVO45WbKR0dRcO7oqGeP7NazZta04WAwD+kpBzVTz+t0sKF83xdSrmZEribqDDI4xgD8BzXdfvUqVM+rgQAAAAAgELmja7DT/0xhaJRSZ5ZA8FFgyVTQiYTp9Z0MeW8qPwKzvX09DQf11F+nEPe4xpsN+VaCAAAAAAAAFQUQR4uWK7xX1O6ZooHeT4spBwsf0ypaaUjDxVk8stgSrevidwdeYZcvwEAAAAAAICKMm90HX6pcGpNczqvTAtqTOzIcwV4JgZ5pgS8lZ2JXW1M++h93CMPAAAAAAAAFwrzRtfhl0ycQtG0gWCCvPPLlGNc2Zn8OhAGA4BZCt9zzH3vAQAAAABUPuaNrsMvuadQJMjzmuJBnhkBgclBHiGMfzDl57MkJtfu71yH1slgOwAPMukDaQAAAACAC4d5o+vwSyZ25LmYOdhuxnF2BXgmnhcEef7B5NchPz/f1yUAACrEvN9bAAAAAACVF0EePMId2BjUeWVaR56JXJ2aJg6IcV74B5ODPM4hb3IW+x8AAAAAAABQWZmTusCvmdyRZ2DJxiicUtO80XaTA6TKxOTXweTaAeBCxAcwAAAAAAD+iCAPHmFigGeaoofYlMNts5nbkUcI4x9Mfh0cDqbW9DbukQfAkwjyAAAAAAD+iCAPHmG12iSZFegV1mpOzaaxGjTV6p+ZHCBVJia+Dq5ri4m1m8PcLnAA/ovrNgAAAADAH5k7yg6/Uth5ZR5zBoJNqbNQ4T3yzPuEO4N5/sHk7gjOIe+xWl1BnrnvPQD8j8Phes8x970HAAAAAFD5MAIGj3B1XpkXNZmjaOBoyuC12R15TIvoD0x+HfLzza3dFLznAPAkk99zAAAAAACVl7mj7PArrsDGpOYZczrxChQNxVzdKP6usGYz6i0qP59uKn9gcldbYWcHPM11/bYY/GEBAP7H5PccAAAAABUTH79O7dq1Urt2rXxdygVn0KCBateulaZP/8An65skwNcFoHIwsfPKPRBsSKBndkeeeYEGn8r3DyYPqppU+6pVcQoNDdN117XxdSllYsp1G4BZCq/bXGMAAABQ4JNP/quMjAxfl3HOwsPD9dBDj/i6DLf4+HXasGG9ateuo27denhlH8nJB7Ro0QJJ0oABj3tlH8D5QpAHj7BabZIkk8ZWXV1tpoSQxYM8Mw60yR15JoUwlZnJr4NJYfDixV9LknFBninXQgBmMPk9BwAAAN6RkZGhDu17+7qMcxb3/Vxfl1DMhg3r9dFHU9WiRUuvBnkffTRV0pmDvJCQENWrd6lXaoB3RUVFq169SxUZGenrUryOIA8eYUoYVpxZA8HFp9Y043ib0jlYEgbz/IPJU5xyDnmP69piyrUQ8ITNmzfq228X66mnhiooKNjX5VRKXLcBAACAC0/jxk00a9aXvi4DFTBy5L98XcJ5wwgYPMLkwVRTwiYTgzybzYw6S8Jgnn8wqautUMFUspxD3mNaRzXgCUuXLtLRo0eVnp7u61IqLTPfcwAAAAAAlR0defAIkwdT6cjzHlOObUkIYfyDia+D0+n6v3m1m6JwOmdzrzFAebmuh06nefedNUXhew7HGAAAACiPFSuWa9GiBUpM3K7U1FQFBQUrMjJSdevWU+vWbdW9+98UERGh5OQDuuuunu71Nm6MV7t2rYptq3//x9xTYZ46dUqrVq3UTz+t1q5dO3X06BGlp6epSpWquuKKK9WtW0/dcsutp9Vz5509dPBgsvvff95HixYtNXnyh5IK7tc3ZMgTkqRVq9aV+Pzy8vK0bNlixcYuU2Lidp08eVJ2e4Rq1YpSq1Zt1LlzV9Wv37BMxyohYYuefvpR5eXl6fHHn9aDD/Y/bZn09HT173+/kpP367rr2mjixMmyWq169NGHtH37VvXo0UsvvPBSqfv47bck3X//nZKk996bpubNWxR7nmdT9DUoq+zsbM2dG6OVK2OVlJSkzMwM2e12Va0aqUaNrlDbtjeccRpVp9OpBQvmacGCefrttyQ5nU7Vr99Affrcpc6du5W4zqBBA7VxY3yJ9brOgeHDR6ljx9s0e/an+vbbpUpOPqCwsHA1a9ZcjzzyuOrXbyCp4FyLiZmt5cuX6MCB/bLZAtSsWQsNHPiUGjZsVK5j4Q0EefAIU4Klkrg6O/yda+C64GszjrfJg+x8Kt8/mPw6OBwMBHuL69piyrUQ8CQTP+BgisJja+7vLwAAAMD59tpr/9aCBfPc/w4JCZHT6dSBA/t14MB+rVnzoxo3bqLmzVvIarWqevUaysrKVFZWlgICAlSlStVi2wsNDXN/HRu7TOPGjZFUMBYQHh6uwMBAHTuWop9+Wq2fflqt777rrFGj/l1sHDIyspoyMjKUlnZSklS9eo1i+/jzPs/k0KGDevHF55SYuL1IHXadOpWlHTu2aceObfr99ySNH/9mmbZ3zTVN9NhjT+o//3lX06a9r2uvvU5NmjQrtsyrr76i5OT9qlatul5++V/u8Y9eve7Qq69u1fLlSzV48FCFhYWXuI/58+dIki6/vL6aN28hSQoMDDztOBTlcDh04sTxMj2HP8vMzNSgQY8pMXGH+3t2u11ZWVlKTU3V77//pri42FKDPIfDoeHDn9P336+UzWZTSEiIMjMzlZCwWQkJm7Vv395yB4suGRkZeuKJ/tq5M1FBQUGyWq06dixFcXGxWrdujd599wPVqhWlZ58drB07trmXSU9P0+rV32vDhvWaMmWqGjW6skL79xSCPHhE0ZDJNKYMBJvYkVfIvECDgVL/YPLrQEee97iugaZMjQx4EtcW76EjDwAAACifTZs2ukO8e+65X/fd96Bq1qwpqaCrbPfunVq2bInCwkIlSVFR0Zo/f4mmT/9AH300VU2aNHN3xpUkIiJC99xzv/761w664oqrFBpasJ0TJ05oyZKFmj79Qy1fvkRNmzbTHXfc415v2rRPinWgzZ+/pELPLzMzQ//4x2AlJe1RWFi4Hn/8KXXq1MUdBB46dFA//rhKhw4dKtd2+/Z9SOvXr9OaNT9q9OgR+uijWYqIiJAkzZv3heLivpXFYtFLL41RjRo13et16tRZ7733ttLSTmrp0sXq1euO07adnZ2tb75ZKEn629/6uL/ftGnzMx6Ht99+UzExsxUYGKjWrduW6/nExMxWYuIOBQUF69ln/6mOHTsrNDRUTqdTJ04c16ZNvyg2dmmp68+ZE6P8/Hy9+OLLuvXW2xQcHKLDhw/pzTdf1Q8/fK+PP56u227rqksuqVeuuiRp+vQPFBYWptdfn6Q2ba6X1WpVQsIWjRkzQsnJB/T2228qIiJCx48f04QJk9S2bcEyW7cmaPTo4UpOPqBJk97Qe+9NLfe+PYkRMHiEKV1tJTElhDQ7yDPv/DA5QKpM8vPNex1cHwDjHPKewiDPx4UAPsDUmt7jum7TUQ0AAACUzZYtmyRJl1xST4MHD3WHeFJBR1bz5tfqueeGVbibqX37Dho8eKiaN7/WHeJJUmRkpO65534NGzZSkhQT89k5PIvSzZ49U0lJexQYGKhJk97THXfcU6ybLyoqWr163anHH3+6XNu1WCwaOXKMatSooYMHk/Xaa69Iknbv3qV33pkoSbrvvgfUtu31xdYLDg5R1663S5Lmz59b4rbj4r7VyZOpCgkJUefOt5epni+++EwxMbMlSS+88JKaNWtRrufjOg+6dOmm7t17uV8ri8WiatWq66abbtaYMeNLXT8t7aTGjp2g22/vqeDgEElSrVpReuWV11Sz5kVyOByKjV1WrppccnJyNGnSFF1/fTvZbDZZLBY1adLUPTXpxo3x+vnnnzRp0hTdcEPhMtdc00TPPz9CkvTLLxt05MjhCu3fU0xLA+CnzAuWCpkSQpod5JmHEMY/uKbWNHHgmoFg7ynsxDPj+i1JCQmbNWvWDK4tOGecQ95TGOSZO60zAAAAcD6Fh9slFUytmJWVdd73f+ON7SRJ+/btVUrKUY9vf+HC+ZKkrl27q3HjJh7ddrVq1TVy5CuyWq2Ki4vV7NkzNWrUi8rJyVbjxk00cGDJ4WCvXnfKYrEoMXG7tm/fetrjX31VMK3mLbd0cnf5ncmqVd/pnXfeklRwb7wuXcoW/hXlOg+OHUsp97qS1LRpsxK7AIOCgtSmzV8kFYScFdGhwy2qV+/S075/7bXXKSgoSJJ0880lL9OyZSv3Mrt2JVZo/55CGgCPMHl6M1NCMZut6D3yzOgiNBkDpf7B5NeB6e+8x2ZzXbfNCUtjYv6nrVu3KDc319elwHB8SMB7XNdtEz88AgAAAPhCq1ZtFBQUrJSUoxo4sJ++/PJz/fZbkkd/pz5+/Lg++miqnnzyEd1+e0fddFNbtWvXSu3atVLHju3cy3m6Y+rgwWQdPlwwZeaNN/7Vo9t2adWqje6/v58k6b33JikpaY/sdrtGjx6rgICS74pWr96latmytaTC0M4lKWmPNm3aKEn6299On3bzz7Zv36YxY0bI4XCoc+euFb4P3Y03tpdUEAr+4x9DtGzZYh09eqTM658pJK1Z8yJJ0smTqRWqrXHja0r8vs1mU9WqkZKkq68++zJpaWkV2r+ncI88eIQpYVhxBZ0cpoRidOSdX3wa3z+YPGDNQLD3mHgNzMvLk8R5gXPHhwS8x/XhEROndQYAAAB84eKL62rEiFGaMGGs9uz5VRMnvi6pcFrNW27ppI4dbys1lDqbLVs265///LvS0k66vxcaGqrg4BD32ICrC8zTHYEpKYXdZbVr1/botosaMOBxrVwZq99//02S9Mwz/1SdOhefcZ0+fe7U+vVrtHz5Ug0ePFRhYeGSCoO9hg2v0DXXnLmD8ODBg3rhhaHKyspS8+bXatiwl09b5tChg3rssX4lrn/vvQ+ob98HJUmdOnXRjh3bFRMzWz//vFo//7xaUsH0mK1atVGXLrerZctWpdbiqr8kruYW17hKeZVl297cv6cQ5MEjLAbfqMiU2ot35Jk3iG0aBtv9g7s7wsd1VIQp55ApdRZl4tSaLoQwqCjXz6rJncr+znWM+TkFAAAAyq5jx9vUps31iov7VvHx67Rly2YlJ+/XDz98rx9++F4zZ87QW29N1kUX1SrXdvPy8jRmzAilpZ1UgwYNNXDg02re/FrZ7Xb3Mvn5+brppoIpGT09vnG+how3bFinvXt/d/9748b4s05veeONf9VFF9XSkSOHtXTpYvXqdYeys7O1ePFCSdLf/tbnjOtnZKTr+ef/rpSUo6pbt57Gj39DgYGBpy3ncDhKnS4zKyuz2L8HDXpGffrcpRUrluuXXzYqIWGTDh8+pEWLFmjRogXq0KHjGTsNcWYcNXiEycFS0YDMnxU9xqaEj4XMCwpM7gSrTNwD1ka9HK6BYDOKNjEUMPk9x5TzAv4rP5+OcW9xXQ/5OQUAAADKJyIiQj169FKPHr0kFXR7LVmyUDNmTHN36o0b93q5tpmQsFnJyQdktVo1YcIkRUVFn7aMN+6L51K9ek3318nJyapfv6HH93H8+DH9+9+j5HQ61aBBI+3evVNff/2VWrduq44dbyt1vYCAAPXo0Uv//e+Hmj9/rnr1ukOxscuUlnZSoaFh6ty5a6nr5uXl6aWXXtCvv+5W1apV9cYbb6tKlaolLlu7dh2tWrWuzM+nTp2Ldf/9/XT//f3kdDqVmLhDX3zxmb755mvFxX2ruXOv1V133Vvm7aGQuSNh8CsmD6qaUrspdZbMtOCRQTx/4e5AMag7wrRTx8RQwOTroYnBKfyD60M8nEPe4+7I4xgDAAAA5yQ6Olr9+g3QXXfdJ0lau/bnYo+X5e/6Q4cK7k8XGVmtxBCvpO2Wto+KjPNFR0erVq0oSQX3fvM0p9OpV14ZpZSUFEVH19bkyR+qZ8/ekqQJE8bqwIH9Z1y/Z8/estlsSkzcru3bt2r+/LmSpFtv7XzGqSLfeGO81q79WUFBQRo37k3VrXuJ555UERaLRVdeeZVGjBjtvgfdmV4vnJm5I2HwK+Z1iBUyZUDYlHv5VRZMq+UfCqc5MycdM61mE+8HWXjdNuMYF2XKeQH/xTnkPaZdvwEAAABfy8nJOePjISEhkiSrtfjYcXh4wfSYRe9992cREQXLHD9+rMTOu/T0dH388fRS13ft42z7OZPbb+8pSVq8+Gtt3bqlQtsozezZn2rNmh9ls9k0evRYRURE6O9//4cuu6y+MjIyNGrU8DPel61mzYvUvv1NkqTJkydp8+ZfJJ15Ws1PPvmvvv76K0nSsGEj1bx5C488l4qeByg7MxIM+D2zgzwzAjJTAsfKgkE8/+B+HQx8PUw5h0zs7im8Hpr33mPi8YZ/KLxHnnnhuylc02qb1AUOAAAA+NLEiRP00kvPKzZ2ebGwLTs7W0uXfqPPPvufJOmGG9oXW69Bg4JpKpOS9mjjxvgSt920aQuFhobJ6XRq5MhhSkraI6ngb6ONG+M1aNBAZWSkl1pbvXr13Pd9++qruRUap7nvvgdUr96lys3N1dChT+vLL/9PJ08WhoKHDh3U7NkzNWXK2+Xa7rZtCfrwwymSpAEDHleTJs0kScHBIfrXv8YpKCj4j2XeO+N2eve+S5Lcx/DKK6/WVVddXeKysbHLNXXqf9z7vO220qffLK+BAx/WW2+9pnXr1igzM8P9/ePHj2v69A+0YcN6SaefByg77pEHjzAxyHNdvE0JyEyp02RF39BNCWEqO5O7I0y5Lpo4tabFYu71kCAP5yo/n3PIW5haEwAAACifvLw8xcXFKi4uVpIUGhqqgIBApaenuX+/vvzy+ho8eGix9Vq0aKnLLrtcSUl7NGjQQNntdtntEZKku+++T3ff3Vd2u12DBw/VhAljtWnTRj3wwF0KDQ2Tw5Gv7OxshYaG6bXX3tKQIU+UWFtwcIi6du2u+fPn6oMPJmvGjKmKjKwmi8Wia65pojFjxp/1+YWFhevNN9/VsGHPavfuXZo4cYImTXpddnuE8vJylZWVJUnuzriyyMhId3fbXXddaz3wwMPFHq9fv6GGDBmqN954VbNnz9R117VR27bXl7it665rrUsvvUy//ZYkSerV645S9/vjj6vcr8ncuV9o7twvSl323nsfUN++D5b5OaWnp2nOnBjNmRMji8Wi8PBwORzOYqHeLbd0UvfufyvzNlEcQR48wuSQyZSWXpOPsSkI8vyRs8h/zWBKgOdSNBRwOBxGXGtMqLE0BHk4V5xDAAAAAPzFww8/qiuvvEobN8YrKWmPUlJSlJmZoapVq+ryyxuoQ4db1KNHbwUFBRVbz2azadKk/2jGjKlau/ZnHTlyWAcPJkuS0tLS3Mv17NlbUVHRmjXrU23fnqDc3FzVqFFTrVq11f33P3TW+7sNHfq8oqKitWLFt9q/f68OHz4kp9Op6OjaZX6OtWvX0fTpM7Vo0QLFxi7Trl07lZ6epipVqurSSy9X69Zty9Xd9vrr43XgwH5FRkZq5MhXShzj6NXrTq1d+7NWrlyhf/97lGbMmKUaNWqWuL2bb75VM2ZMU3h4uG69tXOZajh2LOWMj2dlZZZpOy6jR4/TunU/65dfNujAgf06dixFeXl5qlUrSldeebW6deuu9u07lGubKI4gDx5h2sB1UaZMrWnyMTYrhilAjucf3K8DL4jXFJ2mz5wgz9zrIR8SwLliak0AAADg/AkPD1fc93N9XcY5Cw8P98p2L764ru68817deee95V63Zs2aeu65F8+6XNu215fakSZJq1atK/WxwMBA9es3QP36DSh1mZYtW51xG5IUEBCgnj17q2fP3met92xGjx6r0aPHnnW5sWNfL9P21q79WZLUqVNXhYaGlrrciBGjNWLE6DJts7yaNGmqJk2alnu9yZM/POsyAwY8rgEDHi/3+l98seCs2/bUMucDQR48xNxBVRMGrc1n7vkBXzNvak1X5m5K+F60u6cgIPD/Xw1MObYlIYTBuWJqTQAAAOD8eeihR3xdAlCqbdsSlJCwWZLUu/edPq4G3kSCgQueyQPC8KziYZE5wdEFwaifU5NqLX6PPFMCgsLrtnk/p0yLiHNFGAwAAAAAOH78uN566zVJUps216tBg4Y+rgje5P8fu4cRjBpj/4NrINhmM2NqTZxfBjWAVXKWIv81iykfEji9Iw/eRJCHc8U5BABmyc3N1bffLtZf/tJOkZHVfF0OAAAw3KhRL2rz5k1KSTmq/Px8BQcHa9CgZ3xdFryMjjxc8EwZbMf5xWnhH9yvg4EviMVixlts8SCPgMDbOMY4VwTuAGCWXbsStWrVSsXFLfd1KQAAoBJISUnR4cOHFBISopYtW+ntt99X/foNfF0WvIyOPHiIeYPsLtwjDy7FQ11zz+nKxdyOPKvVjKqLhgLmhUxmHOOizDvG8DemTIELACjg+l0rMzPTx5UAAIDKYPLkD31dAnyABAMXPFO6Zsxm3jyVBjaAVUqucNXEzllTai56b0jzQibzri1F70kIlIfrkmLez6k53O85fMgLAAAAAOBH+CsVHmLeYKqLKYPtZjPjGBc9Fzgv/IP7dTDw9TCl27dosGROQGDe+eBizjGu3LKysjRhwivavHmjr0spN6bW9B5XJ7XVoA95HTlyWPHxa31dBgAAAADAi8z5KxV+zWlujmfM9HfwPsI7/+N6TawGvjamnE8m3yPPxPce045xZZWWlqqTJ1O1YsUyX5dSbpxD3mNiF/jnn3+qOXM+V05Otq9LAQAAAAB4CUEePMTA0dQ/MLUmSmLSIF5l5upqM2maM1e4ZEpHXtGpNZ2GJWMm/pgytaZ/cJ3qpp3zkuRwmFezKUycWvPgwWRJBLwAAAAAUJmZ81cq/JqJA2EuBDYoCQGvfzCxO8KFIM+bTKnzdAy2+wen09zXweTa/Z3rvd/E9xwCXsAE/JwCAACgYswYZYTfM2bstwQmDtbA+zgv/IMpYVhR7ulArTYfV1J+5gR55uL+Zv7BxHPdVTNhsPeY/OERE89p4MJj3rUFAAAA/sG8EVL4KXMHD0wcrDGPeecH54V/MLkz0pQQsmh3DwPB3kcI4x9M7F5ynTucQ97jum6bcv0uik5NAAAAAKi8zPsrFX7J5EElApvzwbxjzGnhH6zWP14IAwMmUwaCi0+tadq13LwfVJPfLysT8851gvbzweQgj2sL4L+4fgMAAOBcmfdXKvwSgweobAh4/YPNVjA9pYmvh5ndhKYdZ/MGxni/9A8mvw4MCHuP2UEe5wXgr7huAwAA4FyZ91cq/JLJA2ImBgQ4Hzgv/IGJg6kuNpu5tZvDvJ9Tk98vKxMTX4fCgWAGhL3F9Z5j4gcxuP8m4L9MfM8BAACAfzHvr1T4JT5liMqGgNc/mBzkWa02X5dQRoXnOqe99zGY5x9Mfh34lct7XO/9Jl4L+V0c8F+F7zn8nAIAAKBizB0hhV8xeUCMwAYl4bzwD+aEYYVcg6nu+/sZxcSazcJgu38w8fcWOvK8z8T3HBcTz2ngQlH488nvWQAAAKgYgjx4BNP54MwYdETFmN2RZ0btRTNr8mvvI8jzDyb/3sIp5D2FUyKbdzHMzzf3nAYqO4J2AAAqt0GDBqpdu1aaPv0Dn6yPC0OArwtA5ZCfzx8nOBPzBsToyPMPJnZHuM4dc2q3lPI1vMHp5P3SH5g4qFo47SM/p95iygcwSmLiOQ1cKEz+8AgAQJr13/8oMy3V12Wcs7CIqur7yJM+rWHnzh367rs4RURE6O67+/q0FsA0BHnwCP44QUnoPMG5KuyOMI8pg+1FB67NnA7ULFwX/YPJH0Ay5dpiosLroXk/p/wujopyOBzKzMyQ3R7h61IqLYJ2ADBbZlqqHq0R6usyztm0FN+HkTt3Juqjj6YqOro2QV4RUVHRqlfvUkVGRvq6FPgxgjx4RF4egwc4nckDpQy2+weTuyNMqb1oKGCxmFFzIfN+Trm2+AcTQw868rzPlOt2SQgKUFHLh8LZOAAAIABJREFUly/Wd9/F6sUXxyg8PNzX5VRKTH0LAADOZOTIf/m6BBjA3L9W4VdMHBBzYVDVewrPC44xKsbkQVVTptYs3pFn2vE2L9DgPcc/mPhBExMDvH37ftehQwd9XUaZFV63zTvWBAWoqI0b10uSTp3K8nEllVdh0M7vAAAAAKgYOvLgESYPHpg4MGYKPh2Oc2VesFTIlGkqi3bhcT3EhcLkDyCZ9HP6/vvvKCgoWC+/PNbXpZSJye85/M6Fc8U55D2Fx9ac6zcAAOUxaNBAbdwYr/79H1O/fgP05Zefa/nyJdq7d6/S09M0btwbGj78OffyBw8mq127VsW20bVrd40YMfqs+4qPX6chQ54oU139+z+mAQMeL9dzyc7O1ty5MVq5MlZJSUl/TEFuV9WqkWrU6Aq1bXuDunXrUer6TqdTCxbM04IF8/Tbb0lyOp2qX7+B+vS5S507dytxnaLH78/13nlnDx08mKzhw0epY8fbNHv2p/r226VKTj6gsLBwNWvWXI888rjq128gSTp16pRiYmZr+fIlOnBgv2y2ADVr1kIDBz6lhg0bletYwL8Q5MEj8vPzfF1ChdEd4T0mB7ycF/7BlK62kpgyIFw0cDSlZuBcmfj+5Pr5NCnIk6ScnGxfl1BmJt8jz8RzGv7F6STI8xZCUgDAhSI3N1dDhjyhTZs2ymazKSws3P33S/XqNZSdfUoZGRmyWq2KjKxWbN3wcHuZ9hEYGKjq1WuU+rjD4dCJE8crVH9mZqYGDXpMiYk73N+z2+3KyspSamqqfv/9N8XFxZYa5DkcDg0f/py+/36lbDabQkJClJmZqYSEzUpI2Kx9+/aWO1h0ycjI0BNP9NfOnYkKCgqS1WrVsWMpiouL1bp1a/Tuux+oVq0oPfvsYO3Ysc29THp6mlav/l4bNqzXlClT1ajRlRXaP3yPIA8ekZdXEOSZlH0Q1HgfAS/OlWkD1kWZEorZbLYSvwYqMxMHVV3XQ1OuLSYqPLbmvfeYeE7Dvzgc/O7rLa6fT/6+AABUdl9++X+SnBo27CXdemsXhYSEKC0tTXl5uZo/f4kWLVqgcePGqFatKH3xxYIK7aNp0+aaP39JqY+//fabiomZrcDAQLVu3bZc246Jma3ExB0KCgrWs8/+Ux07dlZoaKicTqdOnDiuTZt+UWzs0lLXnzMnRvn5+XrxxZd16623KTg4RIcPH9Kbb76qH374Xh9/PF233dZVl1xSr1x1SdL06R8oLCxMr78+SW3aXC+r1aqEhC0aM2aEkpMP6O2331RERISOHz+mCRMmqW3bgmW2bk3Q6NHDlZx8QJMmvaH33pta7n3DPzASAI/IzXUFNub9ccIfVN7jCngZEENFmTxgXXTKSn9m9j3yzMN7jn8weWpNfk69x+Rja/I5Df9AR573uP6u4OcUAFDZZWVlauTIV9S9ey+FhIRIkiIiIlStWvXzsv8vvvhMMTGzJUkvvPCSmjVrUa71t2zZJEnq0qWbunfvpf9n782jJKuqtO/n3CkicqgsCgEVWmkUUSxAFMGJFpyYpBlae9mgL9IIdiNOPQgKSjGICGirjfqKTTu9y/JrkEJARIYCFIcqUKYGoUoGgaImKqtyiOHO3x83zr03IiPnjIy9I/ZvrVqZGVOeunnuGfZznr1LpRKA5FDlTjstw9vffjguuOBLk75/bGwUX/ziZTjmmL9FoZD8/3fddTdcdNGX8aIX7YIoirB69W1z+a/B8zx87Wvfwpvf/DaYpgmlFJYv3w9nn30eAOCBB/6INWt+j6997Vt4y1uy17z2tcvxmc+cCwB48MH7sXXrljn9fqHz8N2tCqQIAh8AEEmAUsgRBHqzyq9fiJBHA85BVS418vLpS/ldb35jC2eXaTeh0xByXLZwOSTAEc73p6xbhPkijrz2kQl5cp8KgiAI3c2ee+6Fv/mbwzryu++551f4xje+CiCpjXfkkcfM+jN0es/h4W1zasN+++3f0gXoOA4OPvhNAIAnnvjznD77sMPegZe97OUTHj/wwDfAcRwAwOGHt37N619/UPqaP/953Zx+v9B5JBIgLAjaeRUG/FIpijuifaQCL5PAQL4vyKlkGvATljK4BIR5O/J4XOM8XPpFt5MFU3nMT3m4HBLgCOf7U2rkCfNF3GLtQ885YSj7C0EQBKG72X//Azryex977E+44IJzEUURjjjiqDnXoXvrWw8FkIiC//qvn8Btt92CF17YOuP377vv8kmfe9GLdgEAjI6OzKlt++772paPm6aJoaGlAIDXvGb614yNjc3p9wudR2rkCQuCFvL8unDDCRHy2oeukcelVl6+L0hAjAb8hKUMLq6ZfF28vDtPaBd8hYJugrMrgvO4KLQPzn1aoIH0ofahDwjKQUFBEASh21msFJp5Nm3ahLPP/jSq1SoOOOBAnHPOFya8ZvPmTTj99FNavv8DH/ggTjrpQwCAd7/7SDz++GO45pqVWLPmt1iz5rcAkvSYBx10MI488hi8/vUHTdqWvr7+SZ/TsZdgjiaYmXx2O3+/0HlEyBMWBN9PBDyOg4FsWtuHTq2p+wd18v1XhDwacBHD8mhBmEuwnbcjjx+MDT9dRTr3M/qD6LMmIrgvBvwOecl6VpgvsvZtH/r+lAOkgiAIQrez2DGFcnkcn/nMJ7Ft2wvYY4+X4UtfugK2bU94XRRFk6bLrFYrDT+fddancOKJ78edd96OBx98AI888hC2bNmMm2++ETfffCMOO+ydWLHii7AskVWExUV6nLAg+L4HAAiYCDZ55GRk+8gEXh79Iu8c5ChKdyMc05zpNnNpe6MjT4S89sOjX3Q7aVCVSepnINMcTVPu0/bD7z4VIU+YL9KH2ocW8GK5xoIgCIKwYARBgPPOOxtPPvkEhoaGcMUVX8eSJUMtX/uSl7wU99xz34w/+6Uv3R0nn3wKTj75FMRxjHXrHse11/4Ev/jFTbjrrjuwatWBeP/7P7BQ/xVBmBESCRAWBC3kRVHERgDRQXYu9ds4ovuF73kdbsnMyPddLv242+FcC4qLkJcX77i0mTOc+3Q3oQPWnGpCiSNPmApOfVmgifSh9pEKeeLIEwRBEHocHXNYiDnxiiu+hHvvXQPHcXDJJV/BHnv81bw/sxVKKeyzz6tx7rkr0hp09967pi2/SxCmQoQ8YUHwvMxxxSWNokYcee1D9wUt6FGnMbWmCHkUEGGp/fAWBfgFxKRP00DP/RHDoCoX56wErBcXcVMJ8yUMpQ+1C31wNJJ9pyAIgtDjDAwMAADGx8fm9Tk//OF/46abfgYAOOecz+OAA14377YBgDeNEaFYLAKQA7pCZ+ARCRDIkxdquIg2Ggl8tA+dUpOLuJsX8nxfhDwKcBY9uLSdd5o+Htc4D8e6j91IGlRluAbgIr5Lva3FRYRTYb6II699ZKk15T4VBEEQepu99nolAKBcLuPWW2+Z02esXn07vvvdbwMATjvto3jPe45asPadccaH8dWvfhn33bcWlUo5fXz79u24+urv4P77/wAAeMtbDl2w3ykIM0Vq5AkLQv7EwnSnF6jBMYjHBd0XuAh5+XZyE6QFYa5wEQW6BS4Cb7eTih4MxQ8u4ruIAouLCHnCfBHxvX1oF7jcp4IgCEKvs/vue+Dgg9+EtWt/jwsvPA+XX34JhoaSunaHHfZOnHXWp6b9jN/97p50Tl216lqsWnXtpK/9wAc+iJNO+tCM2zc+PobrrrsG1113DZRS6O/vRxTFDaLeO97xbrz3vcfN+DMFYaEQIU9YEDzPhWGZiIKQnQAim9b2oWvj+UzqzXmem37PrR8LwlzhkqavWxAhjwac6xVxEd95p+nj1y849mWBFrzvWUEQBEEQuHDRRZfiBz+4Gr/97T3YuPF5bNq0EQAwMrJj1p81PLxtyuer1cqsPm/Fiktw331r8OCD9+P55zdgeHgbgiDArrvuhn32eQ2OPvq9OPTQw2bdTkFYCETIExYE13Nh9ZXgjY7Ddd3p30AIEfLah18XxsIwRBiGME3awcfUTaoUO2epQA8uQVUR8hYXud5UqAt5DAUbLn2Id8YDHoJ7/hrzvt4CBaQ+tCAIAj927NiOoaGlcliwzfQNDuG/to10uhnzpm9wqG2ffeWVV834tf39AzjzzE/izDM/Oaffde65K3DuuSvm9N7pWL58Pyxfvt+s3zeT//9pp30Up5320Vm//9prb5z2sxfqNQJtRMgTFgTP8+DsNARvdLzB1cQBSf3UPvJimO97MM1SB1szPbrvmk6JnSAt0EM2U0IrpF/QINXZ+el4LFNrxnEsfb8N5A+McDk8ItBFxODFQO5TQRAWjg0bnsW3v/11HHPM8Xjzm9/W6eZ0NSf94z93ugmCIAjgEQkQSBNFEXzPg1UqAuBXI0/SyLQPz/egPXgc+oVuo1UosWivIAj8EDGDBpzrFfFJrZkJeSIQCAJ95HCjIAgCL3bs2A4AeOqpJzrcEkEQBGExECFPmDdB4AMA7L7EbcXNySRpZNqH5/vot5KAIwdhTLfRLIgjTxB4wE+EESGPFpxSa+q+wyW1pgh5iwtDTVoghhxuFARBEARBEAS68IgECKTRgodVSoQ8Lqk19Sn8IJDTp+1A18UbqKcA4yDkuW4NAGAV++Ey6ceC0NvwE8VEyKOB/jtw/HtwFPKkHrEg0EUPg+LIaz8cXeCCIAiCIAgCDXhEAgTSaCHP7ufpyNOOQupwO83u+4lwlzny6PcL13WhDAOmU4TnurLZFuaF9B+hFRyFo+6kLuQxFIO5CHl5UUAEAkGgjwju7UOpZNzmMn4LgiAIgiAI9JCVpDBvUkdeoQDDNFNXExe4pNbkJuRpBx43R55pOTAsB3EcpWKkIAiC0F2II6/95Nct3NYwHNP28myzQIOk7/C7T/mQzTk8xm9BEARBEASBHrKSFOaNFu4M24Zp2wwdeTyEPC6CoyYV8uqOPA6iWK1Wg2E5MCwbAD93qSAI9OEoHHUj6Z+B4Z9DhLzFgF/HkLFFmCtRJEJeu+F8eEQQBA7IYR5BEIRewOp0A2ZKtVrFvffei0cffRSPPvoo/vSnP+HZZ59FHMc44YQTcOmll876M3/2s5/hM5/5TPrzHXfcgT322GPS1/u+j5UrV+Kmm27CU089Bd/38ZKXvASHH344PvKRj2DZsmVz+r9xR4sdpmPBcPgIeXof5fs8BDJutfyahTwujjxl2TAsB0Ai7A0OLulwqwRBEISFJg2qshRs+Al5krKvPTSKAvz6skADfa+KkNc+DEOEPEEQ2omMLYIgCL0AGyHvoYcewumnn75gn/fCCy/gkksumfHrx8bGcOqpp+Lhhx8GANi2Ddu28eSTT+LJJ5/EqlWr8L3vfQ+vfvWrF6yNXMg78gzLYpNaU29WudTIyzvy4jgmvxHUNfH609Sa9AXeak0LedqRx6MvC0LvIqdPhbnBuV6RDghTJy/eiUDQHvJrQS79QqCHrukbx3Kftgtx5AmCIAiCIAjzhVX0YmhoCIcccghOPfVUXHbZZXjVq14158+64IILsGPHDhx44IEzev2///u/4+GHH0ZfXx8uu+wyPPDAA7j//vvxk5/8BHvuuSeGh4dxxhlnYHx8fM5t4ooWO0zbhuFYqNV4iB++79e/0neKAY0pQDmcbNcOvH5GjrxqtZrWyNM/C4JADx10FIS5ogU8xVDI4+jIEyGvPYgoICwEmSNP5tZ2kQp5DOccQRAEQRAEgQZsVpIHHXQQ1q5dix/+8Ic455xzcNxxx2FgYGBOn3XzzTfj1ltvxRvf+Ea8//3vn/b1v//973HnnXcCAFasWIHjjjsOlpWYGQ888EB85zvfgeM42Lx5M773ve/NqU2cyVJr8qqRlwl5PBx5eSGPQ10/LZBmjjz6Ql6tVoVhOzDsRMgTR54gCAuNiJA00EFVg5EQovsOF/Em39fF6dN+uPSLXuCZZ55msx8CsntVBPf2wdEFHoYhxsZGO90MQRCmQPYVgiAIvQWblaRpmgvyOcPDw7jooovgOA4uvPDCGW16V61aBQDYY489cOyxx054fs8998RRRx0FALj++usXpJ2ccF0XSiko04Th2KgxED/CMExdbRwEJqAxtSaHdKCel7SxYChYhmIhmLpuDUbOkcfFXSrQRIKq7SO7tvyusTgeaMDZkcclENwo5HHr99zay8ep2e1s3z6Mq666Er/85U2dbsqMyYR2fv2eC3rc5jJ+A8D111+DL3/5QhYHSAWhVwlDOYAhCILQS/BZSS4QF110EYaHh3HmmWdir732mtF7fvOb3wAADj300EkX34cddhgA4LnnnsPTTz+9EE1lg+vWYDo2lFJ1Rx598SMvKnFJrdnYZvqimL6utjJgGwb56xzHMTzXbRLyJLWmIAgLjQRKKcBZaOfS9sbUmtz6PY9rnEdq5NFAHxB86qknOtwSgRIchbz7778PAI99pyD0KnIQQxAEobfgs5JcAG6//XbcfPPN2GefffCRj3xkRu/ZsWMHtm7dCgDYe++9J31d/rn169fPr6HMqNVqMGwbAGAwSa2ZF5W4OPLymygOJyN1e21DwVb0HXme5yGOYxiWDcNK+jOHviwIAi/4CRrdic70wEUUy8OlzbwdefwQRx4NOPZ13WSGTWcDRyFPI6mRBYEu2aEpHmtDQRAEYX7wW0nOkZGREaxYsQKmaeLiiy+GXReepmPz5s3p9y9+8YsnfV3+uS1btsy9oQzxPBdm/Xqajo0wCNK0lVTJi3cchTzqohjQKOQ5DFJraiepYTlQSsGweLhLBaG34Rd1lIAYDTgGUzU8hTzp9+2GS7/odnj29bjpq7DQpOmcGQruUjtREOgi96cgCEJvYXW6AYvFJZdcgq1bt+LDH/4w9t9//xm/r1wup9+XSqVJX1csFtPvx8fHZ92+nXcemPV7qBBFAQw76UramTc4aKO/v7+TzZqSanV7+n0U+dhll8EOtmZmPPNMdrsODNjk22zbgKEAE4CtFAwjJt3mMEzude3GMy0HSkWk29wL+P4YAMCyTDZ/C53ebOedB7BsGY82a7hc48HBZM51HItNmzX9/Q67NncjS5b0AQAs02Dz9zDNJADMZWx5/vls3bx0aR+L67xkSdLmQoHf2LJkSYldm7uRSiXpQ5zWLdrJUSzS319wZXCQ79iybFk/hoZ4tVkQeoW+viR2wXFsocKWLQYsi98hC0EQeGAYCxtv6Akh7+6778b111+P3XffHZ/85Cc73ZyWbNs2zjbd1vh4JRXwzLqgt2HDC9hpJ7qngzZvToS8wcEiKpUqtm4d63CLpueFF0bS77ds2YElS2i3eWSkDEsZUErBUgpjYxXS13njxm0AMiHPsGyMjIyRbnMvsH17IrAGQcjmb6HH8hdeGEMYzsz9TQUu13hkpAIA8LyATZs1O3aU2bW5G6lWkxTVYRix+XuEYbKu2rZtnMXYMjKS1ZndsYP2GkAzOpq02XX5jS3lsseuzd3I8HByoJPTukVTq/ns2syFajXJTOJ5/PrFli2j8DwJcgsCRUZHkz0Rx3ULFaIoQhDQjV0KgsCbKJpdvMEw1JRmr65fkY2Pj+MLX/gCAODCCy9EX1/frN6fd5VVq9VJX1erZSn4Bgb4uuvmQs2tTXDkUU9XqWufLVlSZFMHjVtqzSDwYdWdSZYCwoB2m3U/0EKeMnnUexToImnO2keWvpnfNZYUODTgmFpTxpTFhN/hOukfNOA4xuu+wzHtIxc4zjkanuliBaE34DjnCIKwsJx11hl429sOwtVXf6cj7xcWl6535H3jG9/Apk2bcOSRR+LAAw9sSJUJNApOtVoN5XIZpmmmqTJ322239Pl8vbxmNm3alH6/6667LlTzWeB5HsyliXipHXmeR1sA0e1bsqSILVu2dbg1M8P3edX1C4IQltJCnkIlCDrcoqnRop0y60KeZTUI9IIg0IF6HdZm8rXCoohX27sV0zQ73QSBNPxEMRHyaMAxqJoJedKH2oVh8J1zOPZpQegVsvuT3wEkbvz3D67G6BzKKFFjycAA/vGU0zrahvXrH8evfnUXBgcH8fd/f1JH2yII3Oh6Ie+5554DANxyyy245ZZbpnztMcccAwA4+OCD8aMf/QgAsHTpUuyyyy7YunUr1q1bN+l7169fn36/9957z7fZrPBcFwNNjjzqTqbMkVeC7/uIooj8Scm8eJcX9agShgHMnJAXEhfy9PU1zKQvK9NmIZgKdMmLN8LCwi2olG9vQHws7BWoz/lTIWOL0ApxU9GA2/wE8BTyHnzwjygWS9hnn9d0uikzQtc45QjHPi0IvYJOu87xABI3RsfHsfR17+l0M+bNjgdu7XQTsH79Onzve9/Fi1/8EhHyCLDbbi/Gy172cixdurTTTRFmQNcLeQvBW9/6Vlx//fX49a9/jTiOW25y7r77bgDA7rvvjj333HORW9hZPM9NBTydYpO+kJc4rZYuLdV/dlEqlTrZpGnh58jzU0eeqZKfKaOvr1F35BmmBc8tT/UWQRA6RObI4yFohGEm3omQRwPO7gguwfZ8O7m0mTNyjWnAUfTgKORdc82PAQAXX3xFh1syMzgfHuGWBUEQegmOc44gCLT4/Ocv7HQThFnQ9ULet771rSmfv+666/DZz34WAHDHHXdgjz32mPCaE044Addffz2ee+453HTTTTj22GMbnn/mmWfwi1/8In1tLxGGYeJms5KuZNa/UneM6ZSJQ0NayKuRF/I8z4Nl2QgCn4mQF8CqxwMspcgHr3WfVfU+bJgWfI+2+CjQRlwz7SMvjHEgCLIgmATEaMDZHcEFw8gLeXK92w0nEaab4TjGa5FJulD7yA6P8FsbilAgCHTJUvbzG1sEQRCE2cNKyBsZGWnYHOnvPc/D8PBw+rht2xgcHFyw3/umN70Jhx9+OO68806cf/75AICjjz4apmnigQcewNlnnw3XdbHbbrvh1FNPXbDfy4E0HaFOrWlZDY9TxXVdFAo2+vqc+s/0a6F5noeCU0QYBuSFUkDXyEu+5yDkTUytabG4zgJdRMhrH9l4wiPqKI48enB25HEhL96JyNR+5BLTgKPooYU8GRfbR+bI43ejSm1fQaCLnnOiSPadQuc566wz8MADf8Spp56OU045DT/96f+H22//JZ599lmMj4/hkkuuwOc+92/p6zdt2oi3ve2ghs846qj34txzV0z7ux555H/xsY99BEEQ4KMf/Rg+9KGJsfjx8XGceurJ2LhxA97whoPxH/9xJQzDwEc+8n/w2GOP4thjj8fZZ5836e/4y1+exsknvw8A8M1v/hcOOOB1+OMf78MnPvFPM7oep556Ok477aMzeq3GdV2sWnUN7r57NZ5++mlUKmUMDAxgaGgp9t77VTjkkLfg6KOPnfT9cRzjxhuvx403Xo+//OVpxHGMvfZ6BU488f044oijW74n/3drbu/73ncsNm3aiM997ny8853vwcqVP8Idd9yKjRufR19fP/bf/wD84z9+FHvt9QoAiWnmmmtW4vbbf4nnn98A07Sw//6vwxlnnIlXvrK3ypC1C1ZC3gknnIANGzZMePznP/85fv7zn6c/52vcLRSXX345Tj31VDz88MP4t3/7N3z2s5+FbduoVCoAgGXLluGqq67CwMDAgv5e6qTpCK1k46dSRx5tJ1OtVkOxaKNYtNOfqeP7iSPPsnjUbouiEAZ0ak1FfhPo+z6gFFQ9iJEIebT7sUAbjsE8LmgxjItYmhfvqKcZ7hU4pznjQl68y7vzhPYgYikNqK93W6HvTxkX2wdnVzJHl6lAgx07tmP9+sdx0EGHyBzVJjIhT+5TgQ6+7+MTn/gnPPTQAzBNE319/ekYsGzZznDdGsrlMgzDwNKlOzW8t79/ZjH11752OU4//Z/x7W//J/7rv/4vDjzwDVi+fP+G11x66UXYuHEDdtppGb7whQvTdc7xx/8dLr30Udx++634+Mc/jb6+/pa/44YbrgMA/PVf74UDDngdgMQ4tGzZzpO2K4oi7NixfUb/h2YqlQrOOut0rFv3ePrYwMAAqtUqRkZG8Mwzf8Fdd62eVMiLogif+9y/4de/vhumaaJYLKJSqeCRRx7GI488jOeee3bWwqKmXC7jn/7pVKxfvw6O48AwDAwPb8Ndd63GffetxX/+53ew66674V/+5eN4/PE/pa8ZHx/Db3/7a9x//x/wrW99F3vvvc+cfr+QwUrI6ySDg4NYuXIlfvzjH+Omm27CU089Bd/38dd//dc4/PDDcfrpp2PZsmWdbuai0+xi0oIedSeT6zYKeVwceaZlw7YceB7tGoQAEIUhzPp63VD0RY0gCBpOIivDRBTVU8dKYKNjcBFqWhHHtPs8Z7QYxiXFZv5QgDjyaMB5XOcyLjbWyON2vXlcY4EePEWP+sE7Uxx57YLznMOzTwsUuOGGn2Ldusfwyle+Cjvt1HuxssVAx1jCUPadAh1++tP/ARDjnHPOw7vedSSKxSLGxsYQBD5uuOGXuPnmG3HJJRdg1113w7XX3jjn33PSSf8Hf/jDfVi79ndYseJcfO97P06z811//bW46647oJTCeeddgJ13flH6vne/+wh885tfx9jYKG699RYcf/zfTfhs13Xxi18khqHjjjsxfXy//Q7ADTf8ctI2ff3rX8E116yEbdt44xsPmdX/55prVmLdusfhOAX8y7/8O975ziNQKpUQxzF27NiOhx56EKtX3zrp+6+77hqEYYjPfvYLeNe73oNCoYgtWzbjK1+5FL/5za/xgx9cjfe85yj81V+9bFbtAoCrr/4O+vr6cPnlX8PBB78ZhmHgkUf+FxdccC42bnweX//6VzA4OIjt24dx2WVfwyGHJK959NFHsGLF57Bx4/P42teuwDe/+d1Z/26hEVZC3urVqxf8M0888USceOKJ078QifJ+yimn4JRTTlnwdnBFByfT1Jr+9935AAAgAElEQVSmCWUo8o6xWq2KYtFi5chzXRe2ZSNg4sgLoxB2PYhnKEV+ExiGQerGA5B+H4Yh6803d7gErFshKU7ahxbDuLhm8y48Lm3udjiP61xOteevMb/rzeMa5+HSL7odzsFUfvcpHzi7kqkfxhTosnnzJgAiBrcTfXCU855Z6D6q1QouueQK/M3fHJY+tpDlrzRKKXz+8xfgwx/+B2zatBFf/vJFuPjiy/DEE3/GN77xHwCAf/iHD+KQQ97c8L5CoYijjjoG//M/K3HDDataCnl33XUHRkdHUCwWccQRx8yoPdde+xNcc81KAMDZZ5+H/fd/3az+P//7vw8BAI488mi8973HN/w/d9ppGd7+9sPx9rcfPun7x8ZG8R//8c0GAXHXXXfDRRd9GX//98fhhRe2YvXq23DKKafNql1AYiy56qrv42Uve3n62PLl++Hss8/Dpz51Jh544I9wnAK+//0fN7zmta9djs985lx8+tMfw4MP3o+tW7dgl112nfXvFzJktS7MizS1Zu4Ep2HRT0noujWUSjZKJT5CnnbkJak1OTjyIuheYQKIiC8ug6BZyEuGR9l4dBbOwQNx5LUP30+EPC5pKhsdeTza3O1IwLr95N09cr3bjwTxaMA5vZncp+2Ds9AueyFhvnDez1FHHxyVfadAiT333KtBxGsnO+20DJ///EUwDAN33bUaK1f+P5x//mfheS723Xc5zjjjYy3fd/zx74NSCuvWPYbHHnt0wvM/+1mSVvMd73j3jETIe+75Fb7xja8CSGrjHXnkzMS/PDqt6PDwtlm/FwD222//li5Ax3Fw8MFvAgA88cSf5/TZhx32jgaBTnPggW+A4zgAgMMPb/2a17/+oPQ1f/7zujn9fiFDVuvCvNDBSdUQrDHJByprtWqTkFftcIumx/NcWKYFk4kjLwpDGDlHXkR8E5gIedmQmDnyJA1eJ+EcPJBNa/vQc0xA/NCIJi/kUT/o0ivkUylzgZtQkxcFJGWf0CtwXLfooUXu0/bBWcjjLE4LnUWvW0Rkah/iyBMosv/+Byzq7zvooINx8slJ5rxvfvNrePrppzAwMIAVK74Iy2qdiPBlL3s5Xv/6NwLIRDvN008/hYceegAAcNxxE916zTz22J9wwQXnIooiHHHEUXOuQ/fWtx4KIBEF//VfP4HbbrsFL7ywdcbv33ff5ZM+96IX7QIAGB0dmVPb9t33tS0fN00TQ0NLAQCvec30rxkbG5vT7xcyWKXWFOihRQ5dGw8AlGWSrwFUq9VQLC6BbZswDMXGkbd0iQPf8ngIeVEII1cjLwZI15sLw7Blak3qfbnb4ZyiSoS89qHFMC6imBYelUnfsd4rmCbNuWhm8AgI58VSqnO/ICw0HEUPrTFxPODAD37Bdo7itEAL2RO1Dy3gyTUWKNGJmpinnfZR3H33ajzzzF8AAJ/61L/jpS/dfcr3nHji+/CHP6zF7bffio9//NPo6+sHkAl7r3zlq/Da104ujgHApk2bcPbZn0a1WsUBBxyIc875woTXbN68Caef3rpE1wc+8EGcdNKHAADvfveRePzxx3DNNSuxZs1vsWbNbwEk6TEPOuhgHHnkMXj96w+atC26/a3Qh7XmGt+cyWe38/cLGbKrFuZFECQLe9VUB4X6gr9WS1JrKqVQLDpwXR5CnmXZsEwmqTWjKB1gjHrQkfICM4qihtOy+nvKbe4FOAbENNTHQc7otM4+g0MNQCY4mnZBhDwicHZHcIF3jTx+yGl8GvA8gJSMh1wcebz7Or+5R9azwlzJ9tOc71naSGpNgSKdWPfff/99ePbZZ9KfH3jgj9O+561v/RvsssuuqFYruPXWWwAAruvillt+DgA47rgTp3x/uTyOz3zmk9i27QXsscfL8KUvXQHbtie8LooiDA9va/mvWq00vPassz6FlSuvwz//88fxlrcciqGhIWzZshk333wjPvGJf8J5550tYliPI448YV6kjrzcxk+ZtB15QRAgCII0rWapZKNapZ9a0/c9mJaV1Mgbox+8juM4XbzreCnljXccR1lDgfR7ym3uBTgLqZzbTh1ujrxUyHOKbNrc7fAWlnjMS2ZT2nVe8LjGeWS9QgN9AInj34PLuCjrq8VFhDxhrmRuMelD7SJNrSliqdDDbN8+jIsvPh9xHOMVr9gbTzyxHjfd9DO88Y2H4J3vfM+k77MsC8ceezz++7+vwg03rMLxx/8dVq++DWNjoyiV+nDEEUdN+t4gCHDeeWfjySefwNDQEK644utYsmSo5Wtf8pKX4p577pvx/+elL90dJ598Ck4++RTEcYx16x7Htdf+BL/4xU246647sGrVgXj/+z8w488Tugseq3WBLFqwU7kUVco0SNcV0/XwisVMyKNeIy8IAkRRlDjyLJtFIDiKo/TMqe4dlE+KRVHcIOQpBi7CXoBz8IBz26nj113JPvF6rBo9Zht2AZ5P/yBGL8DRkcetzbxr5PG61gBP4agb4enIS+Byn8rafHGR6y3MFb1u4TwuUkdP/bIGEDihFvDQfBzHuOii87Ft2za8+MUvwZVXXoW//dsTAACXXfZFPP/8hinf/7d/ewJM08S6dY/hsccexQ03rAIAvOtdR0yZKvKKK76Ee+9dA8dxcMklX8Eee/zVvP8vrVBKYZ99Xo1zz12R1qC79941bfldAg9EyBPmRSbk5WuLGfB9ykJekkazVHLqX23yNfJ0Gjkt5PGokRenA4zKPUaVRGQURx41KB8KmA45fdo+dEpNv37IgTq6Rp7pFBAwOIjRCyglS+B20+jIk+vdbjiMhb1A6sjrcDvmAhchTw5KLS5yvYX5InsiQRDyDAwMAADGx8fm/VkrV/4Ia9f+DqZpYsWKL2JwcBCf/OS/Ys8990K5XMb5539uyoxxL3rRLjj00LcDAK688mt4+OEHAUydVvOHP/xv3HTTzwAA55zzeRxwwOvm/f8AMG2ct1gsAgAMg9+BQ2HhkF21MC900KDhlLhhkHZeafddPrWm69J25Gk3h2VasEwLQeCTD9jEcVZzzmAgikVRBOQCuzrIKxuPzkI5Te9k6H4ugY/2kV/kBgxceZ6XOfK4uAi7HW7uNo6IkLe4UF5j9RJ6fR4TX6e3gksKXOp7oG5D9kLCfJF7VhCEPHvt9UoAQLlcTmvTzYU//ekRXHXVtwAAp532USxfvj8AoFAo4sILL4HjFOqv+eaUn3PCCe8HkNXV22ef1+DVr35Ny9euXn07vvvdb6e/8z3vmTz95mw544wP46tf/TLuu28tKpVy+vj27dtx9dXfwf33/wEA8Ja3HLpgv1Pgh9TIE+ZFKuTlAjTKUKQXa5kjLxHyikUbtdr8T4K0Ex20tiwbppXctkEQwHGcTjZrSuIoTnUxHS6lLPACjSXykNb160hThDochTwN57ZTJ5+e0vM8OE6hg62ZniDwAaVgWA4Cwo71XkJ0vPaTFwVEOG0/IuTRQO+BIoZ/D9PkIbjzFpb49Qs5mCbMF+lDgiDk2X33PXDwwW/C2rW/x4UXnofLL78EQ0NJfbnDDnsnzjrrU9N+Rrk8nrrt3vCGN+KDH/xww/N77fVKfOITn8YVV1yKlSv/H97whoNxyCFvbvlZb3jDG/Hyl++Jv/zlaQDA8cf/3aS/93e/uyddc69adS1Wrbp20td+4AMfxEknfWja/4tmfHwM1113Da677hoopdDf348oihtEvXe8491473uPm/FnCt2HCHnCvMiEvFxtMWUgJLzByhx5Tvq1WqWdWjNNy2ZasEw7fYy0kBfH0N1CqewxQZgNuu9z7DqyaW0fnueh3zRQDiMWqYZ934dhWjAMC1EUIooicSgJc4bLXCp9fHGhfIiulxBHXvvJr6/4zac8DjXk5xkuc45AD913eIvvgpCwZGAAOx64tdPNmDdL6mktO81FF12KH/zgavz2t/dg48bnsWnTRgDAyMiOGb3/8su/hOef34ClS5fi85+/qOVa4Pjj34d7712Du+++ExdffD6+//0fY+edX9Ty8w4//F34/vf/C/39/XjXu46YURuGh7dN+Xy1WpnR52hWrLgE9923Bg8+eD+ef34Dhoe3IQgC7Lrrbthnn9fg6KPfi0MPPWxWnyl0HyLkCfMiXZSpRkce5QC2duQVi1lqTc/zEIYh2doQOrWmaVowzeS29TwffX2dbNXURHEEVc/eq+qbVgkyCbMlCOiOJZOhnSfiyGsPURTBDwIsK9hshLwg8GGYZlpP1vd9FAq0XYQCXbi427i4exqhnwp8MqhnPegV9N+BkyNP93eq+6BmeAt5PMjv2WT/JswXyrEhQZgp/3jKaZ1uAnmuvPKqGb+2v38AZ575SZx55ifn9LtWrPgiVqz44rSv++IXL5/R59177xoAwLvffRRKpdKkrzv33BU499wVM/rM2bJ8+X5Yvny/Wb9vJtf9tNM+itNO++is33/ttTdO+9kL9RphZsiqV5gXYTjRkQdlkF7wN9fI04Ke67oda9N0NKTWrAt5vk87eB3HMQzoGnnZY4IwG7SIHbNKRaRr5ImQ1w50nxioiwSeR3fs1vi+D2VYUHW3A4e6foIwX7i4e1rBRCttgPLau5dIU2sycqCkNa2ZCGL5vs5PIOCxns3v2aKIR5sFuvC7TznC5z599tm/4M47b+90MwQh5U9/egSPPPIwAOCEE97X4dbQIAxDbN26hUWspdfgsVoXyKJPneZPh3OokacU4DiJIKYFPS3wUSRLrWnCSmvk0Q4Ex3GcBsJ07+CwERzdsB6jG9Z3uhlCHS1Yc0xRJY689qD7xICViAQcHHm+70OZJlR6EIP2+C0ICwEXUaBboLz27iWy1Jr017zNcLlnGx15XAQCXqcD8tdV3L7CfBEhr33oOJxiMn4DwE9+8iPcccctaaYsQegk27dvx1e/+mUAwMEHvxmveMUrO9wiGnieC89zMT4+3ummCE1Iak1hXqSn9fJHl5Ui7bxy3RoKBRtG3SbGwZGnBQHTtNIT7tRFgjiO0y2rSh8jvhGMgdHn1gEAlr583+xBoWNokYaj8OH7tO9Rruixuj915NEX8oIggDL4jN+CsBBwEQUa4TXnN7pmiK+xegxemQQSuNyzeZFJBIL2kD98KWOLMFe0yCT3aftIhTxGqQR0DTTysSGhqzn//M/i4YcfwrZtLyAMQxQKBZx11qc63SxyUI7t9yoi5AnzQt/UDY480L7Za7UaSiUn/ZmHI68u5BlmLrUmbWGjQchTDGvOpBo1n0VxN6JFGo94Ktk8erNK3TXLFe3I62fkyAsCH8rIauRJ3xAEYSFoTDEoATEKpGtdRkteDRchr7lGHif4bIXYNFQgjS43IEJeu9CH05XiMX7n4TZ+C93Ftm3bsGXLZvT392OffV6DM874GPba6xWdbpYgTIsIecK8iON4YiER4o68Wq2GYjHr+pkjj661Xwt5hmmlheipL4ijKM5qbqSP0V2sJW3N+q0+SS1CXmfRoo3PQKzR6PuVutjOFS3c6Rp51OuFAtqRZ+Zq5IkjT5g7lNdYwuKSX1fxSTHYG4gjr33wrJGn9xUdbsYMyU8zMucI80Xmp/bB0ZGnoRwbErqfK6+8qtNNEIQ5wWO1LpAlXwdNo8gLedVUvAMyIY9yju4stWbmyKPu6IjjKB1gdB+h3C+Sfpt7IHWbyjDZSXRx3SiK2IgfWsCjfo9yRQt5mSOPblpkje/XHXkGD0e1QBuOwRqhPXB2JnUrnB15XNa8jQK29Pv2wLADC2ThI7jzQ4Q8QRCE3oLHal0gS7JZbVbyaAs2rltL02kCSN15HBx5pmHCZOLoiOK8I0+n1qS7WEuCFxP7LcdFcTeRr13JIYViFEXpZlXEmvaQCnmMauT5QQBl5lNr0h6/BUHggQgadBFHXvuQfr+4UN7XCzyQ1M/tQx/A4BizkPFbEARh9vBYrQtkieNo4qJBKcSEJ2XXraFQmJhas1aj6+oIw3pqTcOCkQp5dE+2xXGMOI4zR179a75wOjWSzJoNeWQ61hYhI++UpVzHUpN34YmQ1x60cFc0DJhKsRDy0hp5TA5iCILAIyCWT1cmqctowNkdwaXNIuQJAheS/bTMT+1D18jTMSJOyPgtCIIwe0TIE+ZFqxp5Cor0GVTXdRtSa9q2CcNQpNOzaYePYRjpIk2LexSJ48Y6EEaaWpPuYq3ZkadPUnM5ndyt1NwaVN15lXfnUSUv3nGo3cYRfV0dQ8E2DBbXublGHuXxWxAEPjTWCqO7xupFFBMxOI8IeYIgLCT6EK+k1mwfOlZhmvxiFpTGb3EeC4LQDtoxtvAb7QVSxLn0iSnEa+S5rtvgyFNKoVCwSafWDMMQSqlEyKsv0igviPWiTKfU1MEM2o481dKRxyWo0a24tRrs/n4APBx5eXcYB6cYR7RwZxsKjqHgefSdj81Cnu+LkCfMHcprLO5k15bHNW6skUd3XdhLcHbkcTm81jgG8rhXuZHvvxz7skADHROQdUv70Ie8uYzfeajEs5QySImKgiB0D1EULXgNan6jvUCKxJHX9KCi67yKogi+7zc48oAkvSZlt08YBrlFmnZ00Fj4tEIv1g1GjjzDMBo2GZmrUIbJTuK6Lpz+vvR76uTFO0mt2R70dbWVAdtQDelMqRIGARQTR7Ug9DLcgo3iTKIHx3pF3Pp9q/U6H7j0CxHyhPmj5yVO89Odd96GNWt+0+lmzJjs8Ai/mAWVA0iOU4Tr0j8wLAiLCbvlFVFctwrHKS7oZ1rTv0QQJieO4wmpYxRhR54WAvKOPP0zdUdemjaBQSBYL8r0ctJQ2pFHdxGfLIInOvJ03nlh8QnDEEHgw64LeRwcedotZpoGfJ++8MgR3/ehAFgKsJRiIZgGoXbkJaMiB/FREHqRLD0lj7lfhDx6cHTkcWor0CzkdbAhXQyzLiEQRd+rlA/zNnPHHb8EABxyyFs73JKZoWNE3MZxgM7B9FKpH+PjO1AslljWGhSE9iALrPkSRSEqlVEMDCxd0M8VIU+YFy0deVCIiaZQ1HXwisVWQh7dNHiJkJcsKvRpKyoLn1akqTXrC0ot6FFus6TWpEe1WgEAOIMDAHgIedqRNzhYYCEwcSQIfFiGAaUUbNAXxeI4rjvystSaQUD3IIZAH6qHpbqB7HQ4j2ssQh49OAp5Gi5tbhTypN+3A0mtKSwEek6V+al9ZMITj3VLHiq1fQuFEjzPxfDwZvT1LUGhUIJR32sKQq8i2825EccxoiiC61ZRqYzCcUooFEoL+jtEyBPmRat8r8qg68jTQXbHaRbyTNRqdN0zeUee/kpZFMuEPDR8pbyIn5BaE3H6uNAZqtVEuHMG+xt+pox25A0MFLB9O90xhTO+78OqDyocHHl6rFaGkRPy6I7fAn2orrG6AW4iez4tFeV1YS/RvF4X2gHn1Jo8yO/vJZgtzJWofribcgyAO6ap71V+9ymVDFNKKQwOLoXrFlCtljE2tl0OiQg9j+u6qFQqqFZt+H65081hhVIGHKeIgYGlKBRKC76OEiFPmBdRFEE1px5UiuxiTQt5zak1HcfC6CjdoHsYhjByNTcU4WsMZIv1DVUP9xtl7GxbDY9TJNmwtnLkSSCmU2gHnl0qwrAsFkKeHmMGBorYskUWPO3A9wPY9cWQbShUPLpuaiDbpCrDAtKDGDQ2rgJPJHDdPrjdm/l1lfQLGoiQt7iIyNQeGh150pcFgSqc5xpKB5CUUigW+1As9nW6KYJAgjVrfoMbb1yFffddjpNO+nCnmyPk4DvqCySIoigNTGqUYZAVbHRqzYmOPCsNwFMkiiIEYYAnn3oUQJJCgUpx4FboNAnPVD38YUc558ij2+YJtR0ltWbH0ak1TceBVXDSnymTpdYswvN8smMhZ8IwSB15tlLkU2tq952qp2hRhkm+zQJtZFxpH/wcefnUmnTXWL1EWq+IcXCVPpzX5jwEd0mtSZNarSqHNoQGONd0k3WLINCFSupbYSKywxDmRZJas3FxT9ktNllqTcehLeSFYYgg8PHEk48ASK4x5YFVL8pUmlpT1R+n22bDaKyRpzdJRrPjVFg0tAPPLDgwCw6TGnnJYYHBwQIA+vXbOBIEAax6EM9UtE5ztiJz5CUbbcMwJbWmMC8k3U/74Cbk5deClNdYvYRp6prW/NaPXAQChpc2B4/GNwp5HWyIkDI2NoqLL/48fvWr1Z1uikAIceQJgtAOMqFdFgHU4DvqCyRIUmtOrJFH9XSNDrI3p9ak78hrvJ70HXl1Ia/+s9H0OEUMw2iq6CqpNTtNKuQ5DgzHZpVac8mSYsPPwsIRhiHM+uBiKkU+FZ4WBrSQp0yDfJsF2ohg0z70/crlGufXglza3O2kjrwOt2MucBQfObaZG3KNaVCpJJlJHnjgDx1uiUCJTMjjcRAjD+XYkECbTZs24tZbb5a1bxuhbBzpdSRCLcyLMAwnHtNTBuI4Jjmo+n7ijnGcxhQEjmPC932yJ1HDMGzYRBmGQXrh0ywymvW2U54MJLUmPRoceU4BFSapNQ1Doa8vceS5Lt3amxqKY/VUhGHQKOQRd7dpV6bSLg3DSuciQZgL3O5ZTmghz/d5iO35vkB5XdhLpEFVRutHqvufyWhcm/O5zpyQ1Jr0EDe+0Apx5Am9yA03/BS/+tVqDA9v63RTupYspstrjdgL8B31BRKEYQBlNnYjo/4zxYnZ91un1rRtC3Eck2wzMDFolwh5dBfzur2pI081Pk6R5k1qDBHyOk2tVoFhmTBME2bBYePIcxwrdf3qMYcylO/LVoRhCJNRas18jTz9lXqbBdpwu2c5ocfsgMHYDeQ22YpufepeI02t2eF2dDP5bBmSAr89iJBHjyiSYKowkaxGHr/7VPZDwlzZsWM7ANkTtRN9bZmd9eoJRMgT5oXvBzBME8Prn8Tw+icBZK4DinVGpnLkJc/TDNyEYQiFvCOPR2pNTVYjj26bE0debiEgjryOU61WYTmJs80qOKixEPJcFAp2eliAQ2pNbmkew6DJkUd4XAFyjjzDqn81Sc6PAh8oH+Thjh6zdSp26qQHpwxTAmJEyIKqQrvIO1AkBX77kWtMA46OPC20Sx9qH9lhBn7Rdlm3CPOF47jIhUzI43ONK5UKNmx4rtPNaDsyowrzInHkmdj2+BPY9vgTAACjLuRRDA7rAI1tTybk0Ux3lqQwzX42FG1HR7MjT7tnKLdZqaYaefXvOaer4E61WoVZcAAkdfJ83yPdh4BkjCkUMkceh9SaAfHUlM0kNfK0I0+Rb39WI0878sxU3BOE2aDT31FcX3UL3IQ8LeoapkV+fuwVtCOPJzwOrzWWG+DR5gx+wXY500gDjs4TLeBx2U9zvMZcrm0rKB/yFnjA8Z7lgt5XcNpfXHvtj/Htb3+NzT5urvAd9QUS+L4/IbWmsuiKYr7vw7LMCQse26btnkkGz8YaeZQXPmngWmXp7wDak8DE1JqtHxcWj2q1AsOxASAV9KrE6+R5ngvHMVml1syLShwWw1EUposXQ9E/JZYJefXgrmGSFx97A75jO4f7lCt6zKa6HmxGrwWVaUq/IALnoCoXkYm3I4/j3MOxzd0Ht1qWQHavchHcOc6jnOccyrEhgQeScrh96PGQ07i4bt1jAGhmB1xI+I76AgmCwE8deBqDeGrNZjceQD+1ZhSFDachDeIplHTbdJMtpR159PqERqmmDVIcQzaunaVWq8F0tCPPTh+jjOu6TY48mmNKnvyhC4rjdjNRGKXpeg0o8otLPe7pdGviyBPmilL03e3c0S5qLkKeduRJak06cHTkcTu01ujIk3BGu2HWPboWjmO8vle5CO6UD0pPDq8bNL9vk1Txwnzhec/yQF9bjnMP9fjQfOExowpkSRx5jRtW/TNNR56X1q7Kox15FNsMJKnvVJMjj/KAqgPXaWrN+iKetgtl4iJYNq6dpVarpgKeFvRcl7aQ1+zI8zza7QUaxTsOAlMUhdAHew2V+AcoL9aaHXnKMFgIpr0CxxPulOd/7vj1VCy+77PoG3qTbZg2+XqhvQJHIY8b+Wss11voFTjO/Zkjj0fYkbOwxGDJAqBxz0Z5/ybwgOO4yIXUkcfwGnf72MJjRhXI4nouDLtRGDMtHcCml5d2ekcezSB2GAYNqlLi6KAbCG6eULPUmnTbLNDDdd2ckMfDkZfUyLPTAwMcXB158Y7qGJgniuMstWZdgKcccE+FPFMLeRZ8BoJp95P0GU5OFKmR1368uiMvimPS6yxNmgHBtFhutLsRLgFrzuTFO7neiwGfebKb4RiYNE1eQh7Ha6zhspzNX2Pq5REE+oiQ1z70vUo5zjIZ3Z5ylceMKpDFcz2Ytt3wmK5ppdMTUcL3/VS0y0M9tWYYNjryTMMkHcjLauSh/lXBVIrZRNvdgz914jiG69bS8cSw9bhCXchLUmvatgmleAh5efGOhZAXhllqzfoYQ3njLY48YaGQ1JrtJ39YhPp8A2R9wbAsBNIvSKDTKAvtIy8K8HHkMYmyt0T2RBTgmUIu6fdc7tP8NeYTvObSzgRx5AkLieyJ2ocWwzjepzzny5kjQp4wZ6Iogu97aYBdo4U9mo48r6Ujj35qzaBh/2cYBuk0lVmNvJz4qBTD4DXnTTdvgiBAFEXsauQljjwLhqHgOBbJcbCZvNhI9TBDniiK0jvTSB+jOx5OFPJoO6oFuuigkvSf9lHzXCyxknuV+nwD5NZbhoWIcUqwbkI7UDjBJ2CdkBdLuTh9BGG+cAymargIeXlRgPP1pkzehSfXWJgvlGMA3NH3KkfnbLcLvLLyFeaMDv5OcOTVRTGOjjyq7pkwDJsKu9MOBGtBNC+DWYZiUH+rOZDBK7DRTWgnhB5PTIe+Iy+OY3iel44niZBHc0zJkxfvqB5myBPHcerI0+Mi5SBkWjO0HmxUhomQ8PjdK1DuM9NBef7nTBAECMMQQxt+5LAAACAASURBVPUDX5TnG01aI8+ySGdq6CV4O/J4HGBrTK3J7Xrzm3sYT5ddBcfApO47XO5TcYu1n3zKO44CgUADHQOQPVH7SGvkMRwLu13gFSFPmDPaaWI4jTXyshR49IQ8z3NZ1sgLAr/R3WZapEUx3bZ8rnZbGWSvL5AsJJXKD4mKdaCXO+lBAaueWjOtvUm3D4VhiCiKUCgkbeUi5OXbyKG9cRyno6HKPUaVVqk1OQZjug2OufP1nEp5/udMrVYFACxl5MjT44th2gi7fNPKBXGItR+OqTWzgDUPsbQRfvNlN8Jx7ajXLVycyo2OPH7Xmwd5Ia+DzRBYk9UN5ycycUFf45ilkMevzbOBx4wqkEQHOJodeWbdQaMDIpTwfS8NsudxHCt9nhpxHMP3gwZVzDIt0qKYFlvyA4xt0BVKgXpQN3eNtajX7ZMAVXRfMeoBVVUP1FAOYOvDDXo8KRQskgcamuEm5EVxNEHIoyzKpCcFVc6RxzAY021wDtBQTq3NGb2uHUrXsfSFvDS1pmnJuEIELs4TzjQ68niEMzjfn5QPS/USPPuQrpE3Mf5CEc6OPC63aX48kbFFmCtZ3XBx5LULfX9GDO9TnvPlzOGx8hVIUq1WAABmodDwuDIMmI5DUshzXbelkGfbJpSi6SJMBqG4IbWmadF25Pm+V099l7XZVoqkUKqZ4MirX29ui/huQfcVpYU8pWBYJuk+pMePzJFnsqiRl7+mHIS8JLVm8r3+Sjk1SxgGUIaZjuGJkCebjk7DcYGv5yPK8z9ndCrNodSRR28d20w6vhgmwiCUoBgBDIOj44oXIuQtLjKu0IBzH+Jyn+YPeXG53vr+VEymnsbxRMYWYX5wuU85wnnu7/YYLo8ZVSCJFvKsgjPhOavgoFKpLHaTpiWpkTdRyFNKkU2Dl9abywt5hpm49IgSBD7spkCGrag78qKGa6xEyOsomSMvu18Ni7YTVQtihYJd/0pzTGkmf4CBg/CYpNasi2LgUCMvTOvjAclhlziOZePRYThef+3uFCGvPVSriXC3k8PHkRcEIQzDrI8xsaxZCMAlYM0Zjq5HbnOOuGbooUUmTn8O3XfEkdc+svgFEyUvh4wtwtzRqTXpxkSFztHttRNlpyHMGS3UmS2EPLPgpEIfFeI4hue1duQBdOtZpfXmWtTIo7r48TwflmocXmyl4BO8vpooihqPshmSWrOTaFGsWcijeI9qdNt0zc1CwYLv0xfGGlNr0m9vQ408lT1GlQlCnqTtJQHH66/HRcoHGjiTr5GnAHLr2FYkjjwjrcHZ7RtXDnAUmTLozqV5uNTbyiNCnjBfdC0oLs6rPFzu2UYhT/p9+2HYmQVSyLq3ndTHQIZrAG5rrtnCY0YVSKJPLjen1kwec1AhFgAJwxBRFLd05AFayKMXxNZB9rxbzKrXJaQazPM8F4UmR55jGPBcuqfbgyBIA2EA0u+7fRKgiq4BlRdADNMkvVibmFqTtvCo8TwXxWIfAJrphZuJ4zgNYnCokReGIZTKBXbrfVrGls7C7fpHUZSOi1Tnfu7odW3JNFAwTRapNYMggDLN3JqF7hzZK/BOrcmj7RzF0mzOobteySNCHj1SR16H2zEbdPyCpyOP1zpREHoRfcBBEPJw2+fPFhHyhDlTrVYApWA69oTnzEIBlXK5A62anOYgezNJGjx6QWzdpgYhz3IanqNGrVZFsSmQUTQU6TRVvu9DNdTcMOuP0xdiuhG9ecoLeVCKdC003Vf0YYFCwWIhjHmeB9t2YFk2C+GxwZGXPka3X0zuyOvuBSZ1KB8KaEW+vdzazgXtwCuZBkqmQTJFfDP6EJI48uigONplmMExfSm3AxjiTKIH58AkT0ce3b2FIAgJcoBNaEW39wseM6pAkkqlDKvgtNywUnTk6ZPVxeJE4REASiWbpNCkhQCVS1VpW3bDc9So1WoTHHlF00CNsCPP9z0oIxN5Vf3kILeNd7egN08q14+UoUhvqlxX18jLhDwOwpjr1mBbDmzLJjum5MnXs9RfKZ8WT9rbWCMP4B2Q6Qa4je35unjc2s6FarUKUynYSqFkKD6OPBHyiMFZyKM7l+bhKOTpMZzyeiVPoyOP7tq7l9DrRi59KA8XFy1vIY9fv5BzL8Jc0fcnv/uUH/xGliy7V7fCbxUskKFcLsMqFls+ZxWLqFWrpAKVbl1EKpWmEvLoBW1SR57RypFHUyRwqxUUmzbZBcOA53lkJ9vEkSdCHhVSIU81Opmo9h8gu1fzqTWDICA1DrbC8zxYlg3Lcsi6fPPEcZwuXvRXyv1iQv1NpYU8um3uBfLCGAfyc5E4xdtDtVpF0TShlELRUKgycOSFYQAoQw4IEIJjYJKbi5Bbe4FszuGyr5DUmvRIA9cMx3ku4jvvfs9vXBSEuaLXu93uvOosjQenOdHt/YLHjCqQpFweh1l0Wj5nFZO6eVVCrjzttpvMkVcs2qnYR4msRt5ERx7VoHvNdVum1oxBV3z0fb+hRp6RCnk029vtpMJMvh8Rd+Tpvp135AH0+5DrunUhj1FqTV0jT2WPUSXvIATyLkK6fbkX0MFUwl2ngUYhj0cgmBu1WgUlM7k/S6aBGqE17GRMdORJ3xDmDuW5lDt63Obims2vUSivvXsJnZI9YnifmiYPR17jGMjvOnOgURTgJxAINMiEPD4HG+6445f43e9+3elmzBh9AMNgKeTx6RdzQYQ8Yc6Ml8encOQlQl6ZUJ087babypFXrdJz5GkBsqFGnm03PEcN162h2JQLX/9Mt80uDCvrG9qRxyHVYDeSOfIaBRDKk7I+CJCvkQfQFa81npcX8uj39yiOoeobPwP0RbE4jgBlYHTDeoxuWJ+qjxIY6yzcBI+8eMet7VyoVqso1Q+PlAyD5JqwGV8Leaak1hQEyuh70ye+JtTwdiZ1J7pWYcxo/aj7DkchT/p9+2GoDwhE4Cjk3Xnnbfj5z3/W6WbMmKyUCT/ZSBx5gjAJlXI5FeyasUqJwFcujy9mk6ZkZo48l9yiTQuQRm4AdZxi/Tl6olgYhqi5LkpNQl5f/edqlY64m6dSqcC0s/6sv6fkKu0l0vuQ0Qo/SVFppgXdCwXatSw1ruvCth1YNv0aeXEcN6TW1L1DBzcoolNrjj63DqPPrUtFSGpzTa+hBfaYyYlr7ewtFm3yLl+uVCsVlOqnT0umgapbI3+fSo08YSGh3t85ow9jcBm/RdCgB8eaUDoQzCW1Zt6FJ92+PYgjT1gI9CFemZ/aRyrkGfzuU04C71zgMqMKxIiiCNVqZXIhr5A8XqnQEW30yeq+viQd6Nq1T2Pt2qfT5/v6HMRxTC69ZrVahVKqYdHj1EWmWo2eyKT/5v1NJ+/66j+Pj9MRd/NUaxUYIuSRQWU5E9PHku/oLiQ8z01deEDekUdbHNM18mzLITf+NaODF3o9aTJwtzWn1hRHHg30fcklTaVuZ3+/w6bN3KhWK2n2gKJpIAxD8tc6EfIMEfKEBUECYu1DC3gi5AlzRQeuI8JZKJrRfYeLo6Ox3/O5zrzIZ9vpYDME1uh9tNScbx+ZI4/HjZqPrYiQJwgtqNWqiON48tSaqSOPjpBXqZShlEodeWvWPIU1a55Kn9cCX6VCS7ip1apwnEbBVP9crdILumsX5kCTI2/AMurP0+kTGt/3EQZBgyNPi3rU+kNPE9Ne8LtuayGPusvN9xMhzzIt8kHrTMirn/BV+nG6i7UkKDBRyJPAWGep1ZL7krp4rdHB3/7+Avn7lCu1WjVz5BlG+hhlMkde0t5uTyUjtAc9H8m81D70WpB6unWN1Aqjh14Dx4SzUEwGH0deHsKbzpbw6BeNe3lu11igQJKhR38vQl670AcwuAh5efFOhDxBaIEWYyZ15KU18ui4ryqVMvr7CzAmsQYPDNBzEQKJI8+xG6+zaVowTYukI0877vqtRkeeduhR6hMa7brLO/KUYcC0HBY1crqRVo48ICa9kODoyAuCAFEUwTJtmJZNPsCkF2V6dNGCHqfFmko3rTw23N2Kvi89gim1W5F35FG/TzkSRRFqtVqaFryUpgOnt87KE0pqTWEBUOIUbzu6Nh6X8VscefTgKLhnqTXp7t+6By7XOO/I49JmgRL5tYqsW9qHPoBhMKlxmj/YzSk2NBdEyBPmhBZjJnPkKcOA5TikRLFKpZK67lqROfLotBlIToPbzkTB1HEKJEUm3Tf6mxx5RUPBVIqkkKeFabNZMHUKJNvbS/DZqvJ05GmXj2VZsCybvNNngiOv6XGKxHHccm/NKA7TlWgnXhzH5Ps9kAV/+/sLCAKfVSCPA57nIgZaCHm0HZthGDak1uz2javQXmRcaR9efc7x6weoqCNCnrCQcEmtKWkf249cV2G+5OckDvMpV8z6XsgweAh5+TSr3b4f4jKjCsTQYpc5iSMPSFx5lNIoJo68yYW8/n6aqRTL5TIKTmnC44VCiZzoCOSEPKtxeFFKoc8ySdbIGx0dAQCYxb6Gx41CH0bHRjvRpJ6n5Qm9mLYjz3VraepeAOn3tIW8RMDQqTWDwCe9INYnrZ6vebh/pJzWyKO8WJsQ/0q7sATGOkmtlgk0HNJrBkHmyItj2n2eI7o/FOqugWL9q+vSOzCVJwjrjrx6kFQcecJc0EExyvM/d7xcbTwOh0cahbwONkRISVPJMVw/ckmtKWkfBYEXlGND3EkdeUzG77wjr9vXszz+IgI50tSapdaOPCAR+Si5maYX8mg68srlMgqFFkKeUyQllGrGxkZhKpXWl8kzaBoYJyiMaSHPKvY3PG4V+zAysqMTTep50gVDvg5ETHsh4bouisXMkae/pywSaJfPtuEtMK1EeNSCAUW0ePFs1cMfdpRhMqiRl6AmfC+Bsc6ST5lI0d3eTJZas1D/mUd6Ni5oIa9Yn2MKaY08uuM3AERhCIgjT1gguj3w0Uk8Ny/k0R+/G9cosmAR5gefYLs48tqPpNYUBA5kQh4PR15+DdvttRPpRkQF0qRCXmFyR55ZLJIS8srl8bQOXitKJQeGociJY5XKOIqthLxCidT11YyMjGCJbbVcmC2xDIyMbO9Aq6ZmZGQHoBSsQqMjzyr2Y3R0RFLKdAC9cMhPwnEcERfyaigUMkee41hQiocjb+vWDbBMq+Eximi3iR5erPo3QcAxeC3jSiepVCuw+5Mxn3odNCC7L3UacMr3KUdqtUTMLdbTyOiv+nGqpI68+twYhuLIE2aPXrN3e+Cjk7ieh8F6thLK68IMceQJCwcXwSbfTi5tFgRBaAc67maadONveaIobvl9N8LjLyKQo1qtwLBMGNbk6rxZcMicco+iCJVKGYODkzsIDUOhv7+I8fGxRWzZ1Pi+D8/zWjvyiKbWHB0dwZJJBvshy0rdb5QYHR2FXSilgTCNVehHGARk+nEvkQp5uUk4jmLiQp7bkFpTKYVCwSbtyEvdd0rBrAt5lFOzpUJe/edMyGMkakhcgATVahWFJYP173kIeYah0jFGu2mFhSFz5DWm1qTsyIvjGFEYQikjJ+RxPNQgUEEcee0hDEMEYYDB+r6Zh5CXp7sDYuxg+OfgIorl95lcXCgZXDoGl3YKwsLB0Rigx0Au43ezAaCboRsRFUhTrVZhOZO72wDAKjioEjnJXK1WEUXxlI48ABgcpJcOFACKxYlCXrFQQrVaJRe0GR3ZjiG79cJ3iW2iWquRC0COjGyHUeif8LhOtSnpNRcfvXBomITjmOymKooieJ6HUslueLxYtEkHgjOHm4Jpmg2PUWRyIY9umwV6+L6PMAhSIY9abdxW+L4Px7Fg2/o+ZSReMyCrkZdsjSylYCpFevzWoosyDCglqTWF+SP9pz14XiLcLUmFPLrjiqaxRh6/AGQ3YtQPmCiDR1CVI7wdedzaKwi9A8eDUpkjj2b8rZnG1JrdvW4RIU+YE7VaBWZh8npzAGA6DnzPI7EpLJcTl91Ujrzk+QLGx+kIeVpUbOXIKxaTlGCUXHlxHGN0dDTdqDajH6fmyts2vA1238CEx62+JMg7PLxtsZvU87SqkRdHdFNr6qBM3pEHAKUSEyEPeUceXYFApxPUm2u7HsyQNIPCbNAOPGfJQMPPlAkCH5ZlwqqnZhPxemFx3cbUmkopFEyDdMBdr6+VMgBx5AkLAMdAEwe0A0878rSwJwizQa99+QlMfGh05NHccwpCr8NRcOe4Ps8O0PO4xnkktaYgtKBarcJw7Clfo4U+CkFsLc5NL+QVU9GPAmNjSVtKxYluMS3kUUoFWq1WEIQhKyEvCAKM7NgOu29ownNO3xIAwLZtWxe7WT2PPnXafCKY6mItTctWtLB27dNYu/bp+s88UmsqpdLFGmWBIG1v/Wdx5AlzQdfCLSwZhFKKjSPPts3UkSfi9cKiMwUUck6HgmGQToEXRfWggGEkc6NSLAMF3QfNdcpMkP7THpqFPMrjikAXpZLQnaH4hfC4uCPy4h3VPSd38l2BS78QaMExBW66ZmcEl9p4ml4aT3j9ZQQyVKtVmM50jjy7/trOB8i02DU4OHVqzYGBAsbHx8gMArrdWrTLU6yLe5QchDt2JCkohyYR8nTKTUqpKrdvH0Ycx7D7l0x4zrAdWIUStm17oQMt623S1Jr50+ER3dSaWqwrlRysWfMU1qx5CkAi7NWIpBhuRSqA5VJr+j5dUWyy1Jq0RQ0a84mQod3uVrEAq1gklVJ7MoJAhLx2ooU8Kxe4cwwF36eVCjxP6shLa1gYIsQI84JjoIkD2oHHSciT1Jr04OzI49LmvEDAJZ0cP2Q8oYbr1vCd7/wn1q17rNNNmRHJAeRkTDGYpBoOQ34ZD3i7krt7nOH8lxE6SLVWhVmYxpHnaEde54PYs3Hk+X5AJuVJJuRNdOSV6uLe2NjoorZpKkZGtgMAltpWy+eHrORxLfhRQIt0TgtHHgBYfUvwwgsi5C026YavIZAQkV2sVavJONdcI69UckiMgZORBoKRnfClHMjTQXXdDUyVLGQoB9vjGEBDAENljwsdQTvyrGIRVrGQ/kyZIAhg20auRh5dwZ0jnufCMQwYeSFPKbgu3bGlIbUmklp5lMdvgT6SWrM9SGpNYSFIa+QxEcU4kj8wyjuITZdGR57MORTYsWM7nn32L7jttps73ZQZo+9PLvdpfn3O5XAM58MMTC7xnOHR6wVy+L4Hw2ot1miMuphD4dT4+PgYDEOhVJraRaiFPiout/HxMdi2A6vFtaaYWnPHDi3ktR70bUNhwLLS11FAC3mtHHkAYPctwQuSWnPR0Yuy5hPBVBdrWqxrHmP6+uxU5KNI5t5QqauDsqNDB8MUsmCGY5qpm4YizZtUlT7e5StMwlQqdUdeqQCzWGDhyPP9pEaeOPLag+d5cJpSyDgK8AkH3DNHXibkUR6/BfpI/2kP4sgTFoI0cM04uEodjin7Mrjcp/mxpYPNEFL0IR5OhwTTVMNEY0PN5NdXXA5NZWMgxxuVY5tnDo9eL5DD9/3phTxLC3mdD7COj49jYKA4rZtHp96kEtQbGxtrmVYTQF3gs4kJeTtgGQp9U+RTHrKN1LlHga1bN8N0ijCd1m5Np38I5fEx0mJMN5IuyvKFaiO6Qp7uH319rRx5NbILtszRAZj1a0s5kKcFu/xQ7hiK2en2VMrraCt6mXK5nKSTLRRgFQsYJzLnT0UQBHAcE5al71M+m20OeJ4Hu8nl4BgG6bFlgiNPGSxT93Qf/MZ2LdRQnv85o4W7omHAZrJmESGPHjqoahLdC3UDeQcKt/pQXOqzNo4nMrZQgGqcYir0vUo1NtQMTyFPX1seY0sjHNs8c3j0eoEUcRwj8H0Yk9RB0xgmnVPj5fLYtPXxgLwjj4Y4NjY2ilKLtJqaUqkfY2M02gokqTWX2taUKT+WWiZGtg8vYqumZvPmTXD6l076vDO4E4BE8BMWj8yRly104jhOA5bUyFJrNjvyHMRxTDZok6V5UKmrg3JqNh0My/cCx1CkT7cnG9bcmKjyjwudoFweh10oQCkFq1REhUlqTdM0YFk6tWbn11bdhOd5KBjNQh7tsSUdq1NHnikCrzAn9LpdhLz2oNeABUPVDwh0/pDrdIiQRw8j577mBpc+xNuRxw8m3aLr4SIs5dFCnmlObS6hQn59xWWtxUUkbUW3Z6Dm+5cROkYYhkmKuxk78jofbBofH5u2Ph5AVMgrTS7kFYv9pGrk7di+HUPTnF4bskzsGNlBYkEfxzG2bNkMe3AKIW8gEfI2b960WM0SMEn9hzgmWxeiVqtCKaBYbHbkJT9TdXRq94ZS2YaV8uLS81xYSiEvjBUU7dPt8YR+q9LHhc5QqZRhlZLDPVaxgFqtSrrfA0AY+rDtzJEXBLTbyw3f92A1TS+WUggIrGEno5Ujj2MwRqAD9XGQK1q4c+pCHuUDAhoR8uihA9dU90JTwaXNjUKehErbgTjy6MFx7ajvz1YliCiSPyhN+dB0Hm6HGVrFW7oVmZ2EWaOFOTWtkEfHkZcIedM78gYGCvXX00izNTY2NrUjr9iH0VE6Qt7IyHYM2VP3i6W2BT8IUK1WFqlVkzM6OgLXraFQF+taYZUGYJgWtmwRR14naCiI3blmTEu1WkWx6ExI39vX56TPUyRzPCoY9cVPFNG90p7nTqxjZSh4hINiYRg2HAvLnI/8Nk3dQrlchlHQQl5ygIfCnDQVQRDAsjJHnjivFpYgCGA1bfpspRAQvs6ta+TRba9AmWTe5xJc4obrulBIxpQCm9Sa2RpF1is0SNM+irDaNvKpNUXIE3oFjod49P1pMqkZmk99z+V6cx4DmZwdmTN8/zJCx9DpnKa7sZVJJ/1TpVJORbqpME0DpZKDSqXzabZctwbf91CcwpFXKvVjfJyGkBeGIcbHx7FkmpSr+vnR0ZHFaNaUaHHOmULIU0rBGdgJmzdvXKxmCQ00ntqjOilXKuVUtMuTCXk0RYJ8cEa7OigHbFzXhdM09xQMhVqNplAKJNezIQ2SpDDrOOPlcVjFZE1gFmnVxp2MRMjLHHkUDkl1E2EQwGo6iGEaivR9GgSJaKf0iVnDEKemMC8o93fOeJ4HxzSSPYUCC0defi1IeV3YS2TuCKKboS4gLwpwcRFyRjRpGnAe47kIefmDUlzqWXOrE9pLYzavv4xAgtQOb0xzoyga6cM8z4PvB+jvn17IAxJXXplAvRxd+266Gnme55HYEI6NjSEGMGRPI+TVnx8Z6byQp8U5XQdvMuyBpZJac5HhNhFXq2X0908U8vS4Q+FwQCtS953Krnn+FDY1arUqSk1zT9EwUKvVOtSi6QnDsKG2IwfBtNspl8dTJ56VCnk071GNduSZpgGDuMDEkSDwW6TWzMQyijQLeUpJjTxhfsi40h48z4NdP9BjKwXfp18jL98XxKlJA25BVY5wSyXXCEdVjGObuw/Oa0c+Ql6276cca8mTxeP43afcYomzRVYDwqzRwpya5jSYIiLk6QD6TIW8/n4ajjxd+26qGnla5KNQ029sLBHmODnyNm/eBKvQB9OZun6iM7gTyuVx8oHermRCGn2ak3KlUpnSkVep0HTk6YWkgkrHbMoCU7VaRbFZyDMN0o68MAqBvJCXptaUwFgniKIItWo1FfC0oEfdkReGYerGsyyTtMDEkSAI6vU3MyylEMUxWXFDB14yR54pTk1hXnA5Jc4N3/dg18cXxzDge/SFvPxaUPoFDUwzKV/BMT7Z6XjQTOGcSo4nDDtzF8JxjNdDih4XqcPb5c7jPs2LdyLkCUIT6UJsuptDNb2+Q8xeyCugUul8QE+Lc6Vi36SvoSTkjYzsADC9kDdomVCgI+TZA0unfZ2uoSfpNSlAcyNYqUzmyKMt5DWk1mRQu82tVlFs2mQXDQOu55FtdxiGDak1tSOPqjjQ7bhuDXEcwywk96b+SrWOpUY78oDkVD6H07NU78lWBIEPs4WQB9A9qazTaOZr5InAK8wNqZHXTnzfg1M/hGQbioWQJ448enAWmbgEVbm4ewRhIdHr3E7HbecCl3s2P6dKDECYL3xXA0LHyIS86V5Jw5GnXVQzqZGnX0fBeTU+noiJxSmEPP0cBSFvdDRxEE6XWtNUCgO21fHUmlEUYcuWzdOm1QSy1Jtbtkh6zcVCB4DHN27G8PonASRByjQVJDEqlUrLwwKWZaJQsFCtdn5MaUV+fKbiop6Kaq2FI89QiOMYHtHAmO/5MHKnBVX9e88T50wn0IKdFvCs+lfKrk4g2WRb9YMyXBx5HNqoCYNwgpBnEq9nqWtQp6k1TUscecKc0KfxqfZ17vi+D7s+vNhKwWOWWlNqb9KAi/OEM5zFUi6umTxM9N2uR68BuAjuebiMixwdeVlMiG5sKE9jKRN+fXk2cJ6phA4x89Saja/vFNVq4oRplfauFX19Dgn3zPj4GJRSKBRKk76mWEqEPF1Pr5OMj4/BUAqlGSyAB0wD5XJn27x9+zCCwEdhYNm0rzULfTCdAjZtEiFvsdALnLENm7Dt8ScAJBMyxYVPGIZwXXfSMaavr0BiTGlFgyMvPXxB7xprarUqik01QvTPVIUYP/BS8Q7IhDwONXK6EV1P0XSS+1WZJhTxOotRFCGK4rQ+jmXxcF5xEgWiOJqwKdKrXKoHSPThBcOyk6+mxUIgEOih71VxXrUHz3VzqTUVC8Fdt9GwHPgB/fb2AlIjr/3wFvIEYW5QzTwxE6xpsoFRgaOQx428didCniBMQjxDZb7T5g7XdQEApZI9o9eXSjaCIOh4AOr/Z+9cY2XJyrr/X6uufdmXc5kzMBdeQCAjMRDUjIkyUZT4ooNkBggKCQQvhCiCMSoiXzAQlcsXA2RihGgcFQQjjphJiBGBDxIcBHTAQeYA79zO3M6+9b26ru+H6qe6und3V/U+u3s91Xv9ksk53V199praVavWev7P/3k6nQ5qbmPhJOTYNQghWDjy+v0+6oZRiD4U2QAAIABJREFUatKsS6G8D+FTT6WinL1VXFpTCAG7cU6X1lwj2QIn/0CWkmWQia7lea5fLn03Z5EX7SiLiWvQOo5jDH3/WGlNSh7gWhox8IMJIU8a6bOIq4Nw06HkHnLiCSFgOnb2PkdItBv3yJPK1yhlqFJgIIkTTJl9s9dckxtoDhGjOUWalp5XNCeC1lxV7JNTBfI98ixRDSGPHL/SsnXiEROqUkJOo1nEWepjVRXGpTUVD+QEVGVezJtbVBtdyjK+P/V9yg0t5GmWRo5K+KAg2JuMPledPTYcpln2rlvOdu045uh7w5WNqQy9XgeOO9+NB6RZY65TYyHkDQY91Ev+ruuGxEBx+dK9vacBAHajWMgDAKu5g729q6sckibHOEidWzhIno68IiEvLdervu/mLNKFZHqOuZfWJMddbY4jj6MQE0UR4jiaKq2ZPkN1YEwN0448+jtnRx5tsK1R6WrLqkZpzXywmrvwmCA5VmlCMCkRPw/fT9epNL8Iw6xE7y0NPyhJimOy1CYQhmHWc9MQAlEcs1zP5qH527CcSgiPZwHtFtPMhtYuPNcq05yl8ndVgdboVfx1VFPI4/38P0415pazhF4NaJaGhLmiCSgZbVBUT66e50EIwLbLCXmum2Y2kwCoil6vB8deLOQBgOPUWJTt6/V6qE2ns8+hbhjoKXYo7e1dhenUIa1yJVetxg4Ggz5bZ9WmQQEOccyRx2/hQz01Z/XIS9/n68iL4yQ7x2Mhj985BsaOu2khr8a4tObYMZMT8qQBCKE8WeSsQs92aeVckpap/Jm/iLEjj3rkycwtwZm8WM1duI7j+FgAg15zfO4AqZAnZFoaFkjdvr7vsxUezwpVPP90jXO91qtOGAQwR3sk+pN7ckNWWlMLeWzIkqkrSBXnxepRDRVGyrwjT4ejOUD7jCrep1WZF6voyBtTjbllMjGgGmM+KXrm1CwNTZZJkSNvNEGpzh7z/SEcxyqd8cPHkddb2B+PsG2XhUgw6JV35NWMtB+RyoDB3t5VWPXt0sfbjZ3se5rVMyvAISTPvlB0/zUas0XhZrMiPfJGmymupbXIcTfdh5NzaU0as2GNRV4hBEzLYSk8ngWycmHmpEuSc6CSxkaOvKr0yMufU+4lH5MkObYpotdcxY3hcAjDHJeNT3vlJezP9abDtTz1ImjMVRx7FQijsSOPSmxyn8PJ8Ws6NT2nMEF1crSGJ1wTMOehS2vyI4u7VPD3UZ15scpCnoYbWsjTLA0Jc0lBYIM+V50l4XnDzGVXBi6OvH6/B7eEkOc4NRZl+/r98kJew5BIoNZBc/Xq07CaO6WPt7SQt1Yy90ZuQSkNg6ULpdiR52A4HLIM2qRltNJzTBmSXIPWRY48jqU1acx5IQ9IM9w5Co9nAboPRW7jJ03epSqne+SlpTX5zYXT5IO/nIVSIN1UT4cvuJcbHgwGkLm5hf6u5xa1cH2GziOO4+wa16U1V0NaWjP9u5EJebznREpoNZxaJupp1KI6Ofpa4Poc3QTCsFrzti6tyQ8S8qp0n9K1ozrWXJb8udVJU6th8vrd7HNc3dWARhlZac2ijWom5Km9zILAL11WExiX4FSZfRhFEYZDD47jFh7LpbTm0B/CKVla0x4dp8r1OBj0MRj0M3GuDFZtC0JILeStCQr6TmTtmTxdM0U98kjg4+CcnSZfTo42VlwDeZkjb0rIc6SABM/gNY1ZHhPybJbC41kgKxeWE/K4O/Kme+SZzIVHIl9Os5KODuZ7wMGgP1Ee3Bj93fP03KISrs/QeUwGl6olQlaFfI88EvS4z+G+P4Q0LUjTRhSG7EuBngVUx1SuhSoJBFWD1ohVIX8dV8dNtdnQ/F7Fed4oaSTghNavV0P+MbPpj5zqXfUa5ZQurcmkR14URTCM8rMlHatyI04Bf7uUI89Fv99XvkCOoijbpBZhKi4rc3R0BACwas3S3xFSwqw10GodrWpYmhxZUD0v5DENtvf7PbiuNXchSQIfRyEvXbCn51gIASEE20DePEeeEAKuabAUxuYLeXzLrW46WZJA7jqSTOcWgsY2duRJ1uMl8uJdFRwd06uoZPQO14zxfr8/05Gn5xa1cC1PPY/8M5/r87/q5PdIqvdAZfG8tHSvNNJKNVWYwzedKgt5em5ZHVUTX/LXcZWv6U2CxOCqXUuA+lizRqOCuTalxx9/fC0DuOGGG9byczSnB02WScFEH48+N83ybrhVEMfRUosECsar3Ih7XlrW07ZmO3zy2JaDJInh+z4cp/j4VRDHMaI4zsrFFEGbWFUZZO12Kx2H01jqe4ZTz76rWS3k5MgHUKVpsnR19Hq9uWU1gXHvPCrByYnpjbWUkq2bgIQ8d8Z8XjMkS0ceibezSmv2+gcqhnTmiaIQ0jAm3b6GgZBxRjOJdlQxwLZNhKH6ktpF0FoGUF+uvIhFYh1bIW/Qh1E7l702dGlNFlTNHZHvr6Q6KXATSZJkYo803gPxXGsRvu9BmNao92Y6n9dqdcWjOttUWfSoWh+3KjGeS6oxf2shjx+UWBIxTzCZRb5Ua1Xguq+YTzXmlslxVmXMJ2OuwvLTP/3TK7/AhBB44IEHVvozNKePEAKGaRYKeclICFMt5C3ryBv3iVK3waKAl5UrmTQPOiYtxalGyKMFpFmytKYh1WajdjrtdBzuchtS06mj3W6vYkiaKWY58qRpwO/xywju93uZWDcLzqU1oyiaajou2boJPG8AUwhYM+YZVwilPTfn0e2mYothT5ZJNp0aule7aV+uyi3mNxDmvwJKYBgLeQbLpIZp8g4OVaW0yyKEmOHIyz5d72BK0u/3UNt+RvbasNJ5hkPf5LNM1YS8fK8WHWw/fWiPREKeUREhbzAYQJp2Vr6XezLGWaCKAWtC94RaHdz7bU4zkaRbkf5mmw7t/SOmybyLkCXjj6qp9n6/GmPPJ6NtemLaQoWF0//8YDDAV7/6VTzwwAN44IEH8O1vfxuPPvookiTBnXfeife///1zv9vr9fClL30JX/7yl/Gtb30Ljz76KDzPw/b2Nl7wghfgZ3/2Z/Ha1762UARJkgT/9E//hH/4h3/Agw8+iH6/j+uvvx633XYbfvVXfxU33XTTaf9vs8U0zMISCeTIMwzVjrx4qQm+ao48a3RMek2X7/l2mlDQoiqlNceOvOLSpXkMp472wZVVDEkzxXA4hJxKAjAsC/6Qn5Da7/ewuzv/XuVcWjMMQ4jc4swwTLYbQs8bwDVnb/hcKeAxdKF0Om2YTg1iKuPUsOsIgwDD4RCuW9wLVXO2IYeybRujP82J/nNcmXTk8RbygFmlNVM47r1934c/HGLLGSckGaO+yt1uR9WwNOBfMnGavHing+2nT5bsOJpHKLeUu+DreV4q5Jna6cuFKrqXKJ6oS2uujiqUWp9HFfubbSJ0f1bxPq2OGJxPnGa4sdBUioUKixACv/Vbv4Xrr7/+VH/oU089hT/90z9d6jv3338/3vKWt5zo59155514+OGHs9eWZaFWq+Hg4ABf+cpX8JWvfAV33303Pvaxj+FZz3rWzH/D9328/e1vxxe/+EUAqcvMcRw8+uij+MQnPoF77rkHH/nIR/DSl770RGOsGoZpFDvyYk6OvOVLa6p15KUBr2UdeaqgoEVZ4yMdp9KRZzouxJIPftOtI/D9kftRB99Xied5MG1r4j1pW/AYZgT3+z3ccMN8Eb1e51taM4rCiSQrwzAQhjyz8TxvgNqcIEbNkGgz7JHX7XZgzEgYoCSCbrejhTxNIdOOPMsyEAThKFGJbxAkL95xd3MIIeZWYeG44SaxLj+/CGnAtF0t5CmmakKeduStlso68rwBpL2VOfLyiRkaNXB8FpWFa9n+TYCEvKo9e4BqitObCN2fVRTyqjIvVmWcVUY78nK8/OUvx/Oe97xT/aGXL19eWsgDgJ2dHdxyyy144QtfiB/8wR/Exz/+cTz44IOF3wvDEM997nPx6le/Gj/5kz+J5z//+RBC4OjoCJ/61Kdw11134aGHHsJb3vIW/PM//zNs+7h48sEPfhBf/OIXYZomfu/3fg+vf/3r4TgOLl++jHe/+924//778fa3vx333nvvmej7Z5oW4gLHWsKkR95JUXnzU4m4ZYQ8lRssOleipO2ajlN1jvv9XlaCahmoPF6v19NC3orxvAHk1Fxs2Db84ZBd8Lrf76PRuG7u54Yh4boWy2zmIAgmFpaGNNg68gaDAdw57mqXaY+8drsNwz4u5BkjF02n08bFi/OvHY0GyPfIS5NPHMfM3ldVUrsMnufBdevwvD77IPDM0prJ+DNujIW8yRLhhlPTQp5iqhZMnXTkVS+Ixx1y3k0LedyvE28wgFm/CMOkfSa/NdZZg+GjqDSbHlRVCa0Rq+jMq46barOh+zOp4BqA4xp9FvkKcfq6Xw1ayGPIj/7oj+K+++6beO/v/u7vSn33T/7kT3Drrbceu8l3d3fx1re+FTfccAN+93d/Fw899BA+97nP4VWvetXEcQ899BA+8YlPAADe9ra34c1vfnP22fOf/3z8+Z//OW6//Xbs7+/jwx/+8MIyn5uCYRhICjKrSOhTXVrTMMylymSGoXonIZXMMk2r4MjxMSr75RhG+jCKS06YdBx9b90EQQBxguuSvsNV6NgkPG8AaU1e/8bIoTccDlGrLVcWdVWEYQjf9zPX3TzqdRsDho6x2aU1eQaXvEEfjTlCXk1KDIb8zm+704axfbyqAblodM9NJjBf65ObjQQ8+tP3h8yFvAEcp4Y4itgHgYUQiKcuBHrNMUjQ6aRi3XSJcGnX9LyiGHqGViWIcJYCHyqYrlpShdKaSZLAG3rYNq2cI4/3HK7hDXcHapUZC3n8S65PoyoWpJmk2qU1+SR3LyLf47Qqff2qzKavZ+de9XfccQfuuOMObG9vn/oP3d7ezv79slzLJP9jP/ZjCzfhP//zP49GowEA+OY3v3ns889+9rOIogj1eh1vetObjn1+7tw5/OIv/iIA4HOf+xxLV8BpY5omkiJHXlZaU+0D2jAkoqj8jUwPMJULi2zTV0JsMhmIS5RVEpWcMGkpryobJQgC4AQ/m8YbBHw335uC53mZcEfQa07BBBpLVYW8IPAnUnylwbf3lucN4MxZrDtSIooiViJkFEXodTsw3caxz+i9dvto3cM680hpII7jyeB1HMNgvBEcDj2YppGtp1yX5kLeLrfBoA/LsmHZDvu1sRQS0+3B6BLhGCTodNJev9Ole02nroU8xfg+lZStRqAmH7jTPfJOn+nSmmZWWpNvwDQMQ8RRBMNyIEeOPO5zuIY3VRQIqgLFgAKFSd0nheP66iySvz83XQBRRf5ar951X41r4ixdu3NVglW6yq6//npWrjXDMGCNnB+zsoW+/OUvA0hdgc1mc+a/8VM/9VO46667MBgM8PWvfx0/8RM/sboBM8AwjGIhjzYuFXXkqRTySCgqc+5kJuSpC2DTuSqbazd25Kl5iAVBsHR/PGDsyKti6YqqMfAGMLbriAfjq8qw1ZeRnabfT8W5en2xK6Zet7NjOTEc+hOJLpZpKXX3LmI4HMKx5pXWFNkxXMo5dzptJEkyU8gzLBvStNBqtRSM7Gxjmlaq0CRJJmInUQTTKnbAq2I4HGbiHTAW8rj3nfO8AWzLQRSGrObtWQgpkBxz5I0+E/w23K3WEYSUx0r3mm4DR098n10J6rMEPUOnryeuTAbwdLD9tKHYgnmsRx6fxKNpKElNWg6ElJCmxX4O1/BGO/JWBz1zqijkaUceFyad+RwrUVSd/Jqc475iMfp64EbVrqCV8O1vfxtHR2lW/C233HLs88uXLwNIy2jOI/8ZHb/JmKZZWEM5ibmU1jQyca4MEYOSoGGY9q0qE4ShBZBaR146zrKlNSMGpTXlSUprSvXn+qzQ7/dgupPiGL3u93sqhjQTctmVc+TxGTfh+0PI3GLSsmy24sBwOIS7wJGXHsNn7K1Wuq4wa8eFPACw3EZ2jGZ9WFY698e5oFIcxaVKWasi7TV3XMjjHlgdDAawbQe27bB0JOdJHXkJvtHq4RutdK6mzE6OJXBarRYst3Es2GK6DSRJrPvkKYSCqmFFkr7yGczaNXP6TDvyxkIeX2GD5msqq2lYPKtKaKoD5+u96tDeZ5i5watD9QQNDTeqIjpW25FXPTbdnKevIAAf+tCHAKQ9817xildMfNbtdtHtdgEAz3jGM+b+G/V6PStD+tRTT61opHwwjRJCXsSltKZxIkeeygk2DIPSQqLJwJE3FvLKHR9n5arUXBtRFJ3MkZcJeXyzaDeBKIrgDQYwXHfifXP0utfrqhjWTKjUUL2+WASo1y2WZYl8fzixADZNC8Mhv4zOKIoQhCHsOQF1R5Ijj4+wkQl5Mxx5AGC4TRy1Dtc5JA3GSTpJLqiURBEsJk7OWQyHHlx3PL5abdwvlDOpkOfCsviX1hRSIgHwtaMevnaUCnmcHXlHrSMYzoyyvaPEAZ0koA4qT+0zLVM9jS6ptVrIeXe8Rx5fYYOSRKispjRt9okjGt7EMd/rver4o7Ug14oqi9CCBg+q/Oivyrolf61rJ6rmWjnzM+ddd92Ff//3fwcA/P7v//6xnoC93thBUatNlq+Zxs2CzPxcF6dNWlpz8YKMhD5VYg1h2zZ8v7zwQsc6zuJSeaskDMPSE/y4b5u6zF8hBCzTRFDyQUrHWYpKmRmGgeQEGwr6DpfSfZsKZf2aNf6OPBKO8m6ZWbiuxUpkApD1lJsU8uxcfx8+0JiKHHmcAk1jIW92SW6z1siqAWjWB83fcS7BJ4ki1vP6YDDIxDsg78jjK47FcQzP82DbLhzbZe/mkFIcS0aKGffIOzo6hDHD7UuJA1rIUwcJ7D7DpJhZTPbI08H202Z+jzy+SYG0ljJGQp4w+VZr0FQDzsJ11aF7MwjDyp1njusrTbWoiiMvH9vV1/06qIbAe1L4Ri3WwD333IMPf/jDAIDXve51ePWrX61sLBcuzA70ccVxLKCgag9lR1y6tF0ogq6S8+d3MBiUF7no2BtuuIjrrtta1bAW4jhm6QxwOq5Ws5SNFwBcx8GwZEkeOu6GGy5ge3v9Y67XXbTby4sVyWjTfd11O0rP9aYTBOnkYk6J6YaTBhSSJGBz/kmLLiPkhWGE3V1XmYA9DSWdiNxi0h6V1uRyfomDg3RedgocebWawWbsvt+HYdkwrNllV023gXa/h50dB7a9uDSr5vQ4fz69PpKcszqJItTrLptrZxrf93Du3PgaoVK+UkZsx5z2BE1g2w6iMIDn8ZtX8limiSSY3PRRj7NLl7ZZZc/GcYxup43tC8869hklDoThgPX53mSSJJ1boihk9cyfx3A47tUqBCp33XAf797eaL7OHHnpX1zXZDv2hx9OxyhHJaelaSEMfbbjPStk+yOTz1q3CMNI9xj1uto4xUmoynjDnPt7Z8dRGndblt3demXO8ybjOGNZ4LrrtiohNFHZ+wsXmtnejjODwXiMly7tKImBLsv2djqXOA7f9UqeOB4njdZqdiXGfFJWLuS96U1vyv4uhMBf/dVfrfpHluKzn/0s3v3udyNJEtx+++34wz/8w5nHNRrjbNeiskCUvZb/Tln297uIy9YlZEAYxoWlNcmjvb/fg+OoyzqMY4kwjBAEESyrOBAzGKSLoX4/wtWranqM9HrD0tkldFy36ykbLzDqrRWXE8eGo2u92w0xHKoYszyRI48ylbvdQOm53nQee+xpAIBZmyytKaSE6TrY2ztkc/739lLXQxkhDwCuXNlDo8EjcWN/fw8AJnrk2Y6LMAzx+OMHrIKPTz21DwCwCxx5Tz/N59p48smn55bVBACzll4H3/veY7h48bp1DevMMxyma5coJ+TFYQTAYHPtTNPpdPCc51yfvXYcE1IKXL3K53qf5uBgdM9aDiI7RBD4eOKJQ7bOxzhOjuVu0uu9vS6roEa73UIcx7Bqx58l0rIhTQtXrjzF9trYdFqt8Xl/7LGraDZ5BxL29tLxCiHg+37lrhvu493fbwMArClH3tFRj+3Yn346Lfs9Lq1podttsx3vWeHwME3AC0N1MYplofYmnK/3eVRlvAPPgyUEgiTBlSt72NnZVT2k0nQ6w8qc500mCMZxsb29biVcbhQ739/vIor4xCzm0WqNXe2HhwMMh/zPcbud6h/DYTVin4eHYyHP88JKjHkeUoqFZq+V76bvu+8+CCGQJAmbCeGee+7BH/zBHyCOY9x+++340Ic+NDfTttlsotlsotvtLux91+/30W6nC/Xrr79+7nGbghCi0K1KjjzVwQ/XTTMJBgMfllWcoeR5I+eH4xYcuTqSJF5KyBNCKG9Q77gu/G65Ml9+HEMKoSygZ1kWcJLSmiNHnmXxDERuCt3uKOPUPX4Pmq6bfc6B4XAIKQVse3GSwLgUnsdGyKNSd5OOPDf7zLJ2lIxrFtRzaF6PPGv0Pqf+EIeHhzAWCXkj50yrdaSFvDVi26nTNw5yQl4QZO9zI0kSDAYDNBpjR54QAo2GM3K98YSS32zbzUrIDQZ9bG1tL/qaMtK9yuR79JrL/oU4OkqD7LPK9gohYLlNtHT/TWXky8gOBgP2Qh4lqVmWoXwvsYlQ6wMS8KhHXhiqa4lQBJXqGzvybHgnqGSi0RBVK/lYFZIkge/72DUNHARh5UrgcltfnVWowhfFFTWnT15vIKdydajeNbHpl/FariBODSj//u//PhPxXvnKVy4U8YjnP//5AIAHH3xw7jGXL18+dvwmI6Us/r2OPlf9MBgLeeU2TINBANM0lbpR4jiecMkUQWK5ShzHhReVG8MwSuA4jrJrw7LsTJRbBuoLaZr8s36qTKeTCnVW/bjwbtZdtDvtdQ9pLsOhB8exCq9lEvI4bbCo12B+rqEEBk59CIGxQGfNOc8k8AUBHyHvqHU0tz8eAFij/lYUlNesBypjGucceVEYsi1vOhwOEcdxVk6TqNdtDAa87tM81L/Ptp1MJOXUw3IaIeRcR57qdew0Wf/NGT3yAMBwdf9NlQw8L+vpy7mPJUGOGcsydLB9BYSjZ405WqcIIWBKwVzIS0U7MUq4lKYFf6iFPM3y0ONT999cDUHgI04S7IyqTg0rdp9yW1+dVch4UcXfh+oYaFny5hYp+ZTr3yTy128Vr+VlWLmt5POf//yqf0RpPvWpT+E973kPkiTBL/zCL+ADH/hAqZ4XP/7jP45vfOMb+M///E/0er2ZpTO/9KUvAQBqtRp++Id/+NTHzo3Ukbd40kyYCHm1GgWmywV4B4MA7gwn0DqJ4/KOPCANQKnOonVcF52SD9JhHCt1P9TrdUTB8gFF+s5JyudqytPptCGkzHri5bFqNXT2WzO+pYbhcDhRV34edAwnx1i/nwYY8wtL26b5kpfTp9CRJ8iRxyMw5vtDeIM+6jNK3xFUdpOC8pr1kAl5I0dekiSIAr5CHrl7Zgl53O7TPGMhb9KRxxUhBaaLayZQv4adBc0Z1pxEAbPWwNH+Y+sckiaH5w1gbzcResPCtgwcoPvTcUwt5K2ATMjLzSWmkNn7HAmCAEIaY5eGNBGGAasKS5pqQQkDmtOFEqR2TWPitUazDDSvC0Zl5MtSlWfSpCOvGkJeVURS4iwJeSu/U2+88caJ/1TxiU98IhPx7rzzTnzwgx8sfQO96lWvgmEY6Pf7+Ou//utjnx8dHeFTn/oUAOAVr3hFpRrMnpwSNwaTkkT1ehos7fXKZSh1OkxK31Vs8nEcF17JPo/DOIHrqBPyms0thEOvuM/jFOGwD9Oy2JZg2xQ6nTasem3m3GHWa+h0O2wWFmEYwraLhTwqvUklljhAbh6Rd+TZzB15czYYphAQ4OPIo1Lbplufe4yQBkynhnabjzB9FrCsKSEvioEkYSvk9XpdAECzOZlg1Gw66Pe7KoZUChIwnnzyEdgWf3fSzNKaSFgWkzk6OoJh2pDW7GvWdJvo93usnjdnhSiK4A+HsLfSfUQVhDwSlOp1i7W4VFXIeZevKGBKgSDge66DwIeRqz4iDXP0vp5TNCcjOkElHE0x5MDbGbX94LzO0vCF4uKqWyJtMnntoSrnmUu8rSxnyfVYjStoRKvVwsHBQfYfZQ36vj/xPpVlI/72b/8W733ve5EkCV772tfij//4j5e6eZ797GfjDW94AwDgox/9KO6+++4sqPjd734Xb33rW7G3t4d6vY53vOMdp/R/y5skiYuFptHnqp1izWbaj6XTKZeh1OkMefSzqNjE6bouvJK/60Ecw63ND3CvGurRE/nLLXajYdrrRLU4vel0Om2YcxIirHoNURiyyTgMAh+WVfw8sSx+Ql63mzazzj8P3ZHwROIBF+i8zSutKYSAJSUbxyOJc+aCHnkAYDh1LeStmenSmvQnXyEvFdWbTQf33fcQ7rvvoew1fcYRCiY9+th3YY2SXwYDHvP2LFKnyeR7XJ/07XZr4dxCCQQdRmWozwrkOnV20nUmt6SYWZB4V6vZWshbAdOlNYE0+YhzaU3f9yGMcZKa0EKe5hpRHQ/aVGitRaU1ueyPy1I1oWBTIZGpKk6xKlJFYSnOTBrVuE8nhbxKSV1Ls/LSmqfJnXfeiStXrhx7/95778W9996bvb711lsnnHPve9/7sofEF77wBdx2221zf8ZLXvISfPSjHz32/jvf+U48+uij+OIXv4g/+qM/wgc+8AG4rotuNw121ut1fOQjH8ENN9xw4v+/KhHHMcScEmcEfa76Ad1splmxnU55R97NN6sV8oQQS0+XqrUl161hGMWlyq4M4wRbCp2rW1vp7zccDgoD7Xmi4QDnRyKgZnW0O21Y9dnlbalvXqfTYuF+9v0gE+kWMRbyeAhNQCrkuVOOMcepZZ9xggS6eaU1gdStx+X8ZkKeszhhwXDqaLW0kLdO5gl51hx3k2rGjjwH//zP9wMAbr0XtKskAAAgAElEQVT12SNHXi/tqctws0LBJCFEzpHHt7RmkiRIfb3j1ZeA+v7Ds2i1W5DO/OcfzTvtdgvnz19Y17A0GAt3zs7WxGvOkKBUq1msxaWqQuuXfGlNSwjWolgQBBB594BB5eGHur2AZknSZ6gu27saaK21Y1KPvGoJeRoeVFHIo/U5x3X6LAyD316tiHFvU66pjZPkxVJZoFVUnUoJeSclf3Pv7+8vPHZeQM22bfzZn/0Z7rnnHnzmM5/Bgw8+iH6/j5tuugm33XYbfu3Xfg033XTTqY6bM3Fc7MgTmSMvAmAtPHaVmKaJWq2Gdrt4YZMkCTodj4cjbynUP8Acx0WUJAiSBHbBtTGIE1x01PUhpN9vNFwuqBj7A2xtXVzFkDQ5Ou02mhdvnvkZCXntdhuXLj1jncOaSRj6cN0ypTX5ZTP3eh24U0KTlBKOU2PnyKPgorlgbjGlYOMmICdMUaKA6TbQ3ntkHUPSjMhKa5KQF1RHyMvTbDqI4wSeN8hKiHNiOPSydSCdWyoBxZFUyJtkUtbjQ7vVgrl9ae7nxmje0W7f9UMuWavmwnTsigh56RzouhbCMNJ90E6ZIAhgCAFjQsjjldg1TRiGEPK4I0+LMaqp3n1Jjg7tyFsNJNxtmwYEtCNPczIyIa9CrrGqrVOq6Mir2jM/L95V8Xwvw9JC3j333HNNP/COO+448Xf/7d/+7UTf+853vnPin5lHCIE777wTd95556n8e1Umjkts8kYZ4nHJvmmrpNlsliqtORyGCIIoc2yp4mQPJrUPs1otFeaGcQK7IOFkGMdK3VTb2zsAgHAJd0CSJAi8Hra2dlY1LA3SbF/PG+BcfU5pzcbYacCBIPCxtVXN0pqdTgeuWzu2SKu5dXS7nTnfUkMYpmM0FznyBNgIee12C9K0IM3FSSymW0d70EcYhjDNM5FbpRwpJQzDzAQ8/qU1uzBNA44zeX1Qz7xer8dUyBtmaxkjc3PwDVzPLK0p8p/xCBjEcYxut4PdS8/O3mtfuQwA2L7x+QDGpTW5PCfPElRa03AdmK6Lfp+vC5WgdUmtls6BYRjCstQlYG4aQRAc6+/L3ZEXRSFEbszUS1n3OdMsC+0xxs4OzWlCCVKuIWEbknXC1Cy0wMsDWqdXyZFXNap4bqsn5FWvD+FJWTpq9K53vevEm1khxDUJeRo+xHG0hCNP/QO62dwuFdAg116jod6Rt0yGEodkJirJN4hibJnzH1RJksALIzgKHXlbW9uQUiIclHcdxYGPOAxw7ty5FY5M026nTiYS7Kax6un7XMoRRlEEwygOeBmGGB3PJwjS7XZw/twz0etN9lFynDq6HW5CXgABYNESOO05w+P89no9mAtK3xGGnR7T7/eyBAPN6rFsqzI98rrdLppN59jae2vLGX3ewXXXzXdnqSIV8tJNlBAClmWzDjAtWnNxEvL6/R6SJIaRc1O3H3sQwFjIk6YNaZi6R54CyJFnOg4Mx2bnbp8FOcPI9Zv2/tVC3mkRBD6sqSQkWwoMGCc2hGEIiJyQNwqIUVKVRlMWigNFkfp40CZCjjxHSjhSVq60phZ4eUAik6yg2FQVV2cVhaWq3Z95sbSKwukynOhqSpLkxP9pNoMoiiAK6vzSop9D4Hpra7tUac1WK20YvL2ttg9aGjBaRshT3yPHcdIAgF8g3IZJgjh3vAqklNje2UWwhJAXDlJhY3f3/KqGpcHYQTBPyJOmAdN10elwEvKK7z06hstGNkkSdLsd1Nzj57lWa6DNTsgLYUq5MJhuCrDp79PrdSGt4jnOsJ3R8fzLr20SlmkhHt2L9CfXwHWv18XW1vHEFwq6cxUKfH84cb9aJm8hD3NKa6Yf8dm/0O/bsOcnQwkhYNiunlcUQKU0TdeB4TqVcOSRU7bZtCdea06HIAiO9fe1hEDg850PoyiacORhlOXOYU+vqRbj5yef5+gmQaU0HSngVlDIq5rjZ1Mh0YNHytpycDCNlIFLQuAyjO/Paszf+Xj4pgt5SzvyPv/5zxceMxgM8NBDD+Hee+/F5z73ObzkJS/B+973PriuOgeO5nTxAx/SWnz5SJNPKaXt7R088MCgMKt6LOSpdUYIIZd05KnPFic3g19QSjUY/X+pdj+c2z2HJ47KixUk+u3uakfeKiGn3TwhD0j75LVaR+sa0kLiOF5KyOOy2BwMBoiiCLXa8ZJ8tVoDj11ps5hXiDAMJ/rLzMIAL0eetIrXPBSM5yrGbCqGYSAZ3YvJKNuQ64K/1+tid/e4KEziXrfL89rJl9YEANOy4DMOXMdxDDk1x8hcZQku1weJc4uEPACQllOJ/mybRq/XgzRNSNOE6TroHe6pHlIhqQPPgOOkyQwc9m2bhO/7sKbmFksK+Jx75EURhBjPeWNHHo81lqY6UDyDU0LMJjEcDmFLCSkEHCngeXzXWbPQQh4PxmtcHvv+ZdBzy+qg+7Mqp1gLeQu48cYbSx33vOc9Dy9/+cvxcz/3c/jt3/5tvPe978Vf/uVfLj1ADU9834ecEQDOI00+PaG2t7cRhhH6fR+NxnyXBCdHXtmHEh2nOuBOwlxQMG4S+ixLsZB37jwee+KJ0sdTGU5dWnO1tNupQEclNGdhNWpsSmvGcTTRWHcedAyXEgVUcs2dJeS5DYRhCM/zlPayzBOGAcyCOc4UgM/geQOkwVxju7jcoTES+3TAfb0YhomIhLyRI4/rgr/X6+Cmm447wet1G0LwFYHDMMhKawLpOefimJ1FGEUwpqYYmnOiKGLj2KS5wihIFJDakaeEfr8Hy033GabjoNXvs0qKmYXv+7BtE7adhgUCxgJTFQmCOUIeY8E0jiJAjsNENJfrgKlqqnf+k2RU/YBJIuOm4XkenFGyqCMFvOFA8YiWQycH8KDKfdppjtGcPnR/Ml7CziXfL28TWXktvp/92Z/Fa17zGtx333345Cc/ueofp1kTQRBkjrt5kGOPw4aQHHYk1M2j1RrAcRyl/duAUdC/YkIeBbmKHHlchLzd3XMIvD6SkplgwaALy7JRq80XmDTXTrvdgmnbMBY4fq1GvVTPy3UQReUceUIISCnYZB6SkFdzZzny6qNjeJxjYFTCtEAwNYVgU/apP+gVOmaAsatGC3nrxTCNbO4nZx41eudEWgK3N7O0pmFINBouWyEvCMKJvF5DGggCHvfnLKIohDGViSyzz3jM20BOyCuYXwzLRU/PK2un3+/BICGv5iKKQtaCDTAW8hwnnQNZl8CtIL4/hD21fLGFYJHoOo84jif3lYz63muqhXbkrRbfH2alex0p4HvVKq2phTwe0B6oioKNfi6tDtr/cNoHlYVrgu5psZamWv/3//5fJEmCf/zHf1zHj9OsgSDwM8fdPLiV1gSAo6NiIW9rS60bD0iD/nHpBS8JeWp75JEwF1SktCaVyAyH5QJdodfFzu6ucsF002m32wvLagKpW6/f77FY/Kcl18pdE1JKNovNTMib48hLj+HTJy+KIpgFp9kQPITSKIoQhSGkWezgkWY6D+rA6XqZKK3J2JHneR6iKMLW1uxKAs2mg26Xz32aJwyDiYgAd0deFEXHyvcamSNP/bOG6PfTdawsSIYybAeDCvRn2zS63W4m5NGfXMV2wveHcN2xkMdh37ZJBEMf9lQfc1tKBEHAVtyIk3hi/qY9Jpc1rKY60DUeF8QHNCcjTRRI71VL8Hb6zoJzQsNZgvZAXJ9Ji9DPpdVB+zbOiZjz4LivP03WEvk/fz4tCfTQQw+t48dp1kDgl3DkmXwceSTOlXHkcRHyykIP3DLl/VZJ1iOvwN7ujx62qoW8nZ1dAOPed0WEXg/ndH+8ldNqt2A2FpdzJKGPxCiVpPdfuXsvva15LJAXO/KaE8dwIIoiyILzLAWPjDHaREujRCk+KYEKbryrzoSQN3pmSak2GWYWJAA0m7PdV82mzbZHXhiGE2sZwzBZB2ziOD5WWpNec5hXCN8fQggJUVAyRhgmi/X3WaM/6MN0xqU1gbQnLWeGwyEcRzvyVoXvD2HJ46U1E/B1o2hHnua00Xmwq8H3/czxazPvvUnk11Sc14VnCRI9qpiwrp9Lq4PWKBHjRMx5cKy0c5qsJWrx8MMPA+C1EdacnCAI0hJE9uIgpTEqtegxsPg3m1sAgE5n8Vg6nSETIU8u0SOPvqP2wUuTZVQwbPpcdZZE5sgblHPkRV4XOztayFs17dbRwv54QNojDwCbPnllbz3V92ieTqcDy7Jnlrgllx43Ia/I+GgwKa3p+2kQVJToNyCEgGFa2Xc0ayIBgv4AB5e/r3okCyEhb15v32bTQb/PWMjLie9SGmyD1kCRI4/P/iWtiGEWPk+kYSKOY9bnfBMZDPownPS5Sn8OBrydkdNCnn4enS5+4GeOGYJec03iieMYyFV6EVrI05yY9NrhtAfaJAJ/7Pglpy938klGOuGIB6rjcteCfi6tjjCMRn9Wby9hFlQPrDorF/K63S7uuusuCCHw3Oc+d9U/TrMGaENqOLMDS4Th8tnAWpYF13UXCnlJkqDT8bC1tbXGkc1GiPI98salNdUukJf/8WrHS+VWQ684CBpHIcKhh93d3VUP60wTRRF6vW4m1M2DhD5OPdzKwqViRafTnunGA9IyuaZpsSqtGcdlhTz1AfelHHlIA+5cg3mbSpIkCHoD7H/ne6BnEcdyMr1emmjSbM4X8ugYbqSB4PFrTqWFp0mSZKaQZzIsren7PmSJLFOaf3SQbH3EcYyh52X7o6oIeb7vwXUtuG56zQyH6hMwi+A4X88jCIKshxVBr7mKpnEUT7ZsyEprql9jaTSaMb4/hJUrrRmEIdu1FpHf8+g1Cg+q7F7isPffVGj/w7k1wjxkQeWSqrP0HfvVr3618Jg4jtHpdPCtb30Ln/nMZ3D16lUAwJ133rn8CDXsoA2p6RT150g/7zPp0bG1tYV2e/7mdDgM4fth5t5TiRACSckSfLSZVS3kLSvMqR6uZVmoN5oIS5TWDL00UErlODWrodfrIkkSWLUiIS/9nINjbPlgEo/gU6fThuvOdz7Wag0W55cIwwhFyzGDWWlNUXJTJAxLC3lrZuIuVP3oXMC4tOZsIa/RcDAYDFIRilk2bVqydHwPCCGyMqbciKIICcbCHUHCHmWkcsD3fYgSSQIi16e6VlvsctecDlSBxG93cHD5+9i68ZkA+At5qSOvDtuuTmlNDs/6sgRBAEtOzuHkoOEaxI7jGDLfI0/qHnmak0GXkfo4xWYSBH6WGEB/hmEA216ccK+S/DOmCs+bswC3PcQyVGk9UDVIwIsq6MgzDH4tM06TpYW8N77xjSfq3/Wyl70Mb3jDG5b9cRqGkDBX5MgTQsB0HDYb2GZzG+32fAcPufWaTQ6lNcUSpTVJyOMxWRWNm4eMkdJsNNELiheQkU/XhnqRd5PpdlMHmFlfLOQZjg0hJRvHWNln4lJG2xXT6bSx1bww93PX5SXkxXFxjzwDgkW2OI1BlOy5JqTUm5B1M+NG5OjwKHLkbW2lvfP6/R6LsuB54jhGvqqJEAJxzO8cA+OMU3NqiqHXnBx5YRgU9scDACmpT3X1smirCu13+nsH8Ht97D7n/4zer0aPPCkFbNusRGC1Ks/MKIoQJwmsqT0aJQ0EAZ+5JU8UR5C6tKbmVNAC3ioJ/ADWqEke9eIMAu5Cnjfz7xp1VFnI47D331RoD1HFvYR25M1gmWDHC17wArz+9a/HL/3SL+lMnA1hXFpzsSMPSF17XBx5zeYWnnji6bmfk1uPR2nNZe4zEvJWN54ylP75bByEQKPRQPuoRGnNkZBXL+jdprk2SJizCoQ8IQSsei0T/lSynOjO47oHUtH00sVnzf285tbR6RytcUSLieP4WJB9GiF4BJloDKJ08KL8NaQ5HRIkWWxJMC6t2e/3YNsmLGv2ZoQEvl6Po5CXTCwM0t6/6u/PWZDjbl6PPE69IZIkKbfgEnyv602FHHliFEyVpgFpGPA8vkJekiQYDoeo1VKXp+talRDyON2TiyDHnTVVWnMccOfryJtIRhqJelURUDV8oH0Pl4TjTSOMQpginb9NhmuWWWhHHj9kyeRTjujn0uqguYT7nDKLKl/TZVhayLv77rsLj5FSotFo4MYbb8T2Nq/AgubaIWGuqLQmAEjHRr/Po39Lo9FEtzs/66fbHY6Om903ar3wCPYvR/XGXK83kFzdLzwuGvWwqNc5XBubS+bIq7mFx5o1l4VjbBkhL44TSKn+PvF9H77vw3HnC6auW8fTVx9d46gWk0yVeZqFXOJ3sUqyMZQNWjAuObippBuSUXDJoAAlv03KYNBHozE/q7pe59uDa/peTB15PK9zKh1jzgm2c+oNkSTJiSqjaFZP1u8s9/uRJu8eqEHgI0mSrD9eKuTxd0jks8PjOGYbsKFxWlP3rCXExOfciKNoQngZl9bUAVOVVHE6p3uTw/5nE0n7+6ZrQY7JR7OgZ6W0bC3kMaGKjjxa32ohb3VQslHAaB9Ulipe08uwtJB36623rmIcmgoxDrYvds3QMRxcMwDgui6Gw3BuEMTz0gnKcYpFBM1xsnJyJYLtAI+HbqPRQBQUByzoGC3krRaaK6ySQl63W+ymXDXLlItL5x71wSbqu1Vz51/PrlOH53kIwxCmqb4BdlpaczESvBx5ZXMblhGDNadDEARZrF2aVIKQX+BjMOijXp/fD20s5PF1/OTh4kiehoJeVeiRl84V5R15vAqabzZZf9S8kGfxFvIoiPrEE23cd99DcF2zEkJeXlwPwxC2XZxcqgIS6qqQJJAnDEOIXBCMyvlyFwg2HaaP0IWMHXkVHHwFSIW89NyaWYyF931K7nXTbWLg8X/enAW4JsOUgdMafdMIR2uYkEHcdlmqfE2XYbP/7zQrodNpw3RsSLNY5bbqLtoMXDMA4DgOkiSB78+eiEjIc10t5J2E4TANVDgFGXfUiJlDYKNWqyP0h4VB9Mj3IA2DbaBgU+h2OzBsKwusL8Kq1dDpqp9bpJSlM2TjeDknxaogwdR155eKpc9I9FNNHMcoSuaVAogZCGLJ0uWD+TqVNpUwCLKImBwFKzk6I/r9fibWzaJW4+vIqxLjHnmT9yzHoFhaWrP4OM4lYzeVrExihRx5FFB95JF9/Md//L+KCnn85m6Crgl7jiPP9/mNPYoiJEkMIY4LeRwTXjS8oWAqh0TGTSOOY8RJkrUeMLK+vryD7lRu2qpvwatIItqmU2XRg9MafdMgIS+OY/bzyjRVvqbLsNn/d5qV0G63YZXsFWbV6xj0+ywy+MhpR4LdNMNhOHGcZjmoTIJdMGnS51kJIoVYlp3WKSkoa5fEESzLYiHCbDL9fh9mSSHdcG0M+n3lQcqyjrwkSZAkCYtFBTkZywh5HFyPwKhfS0H0WjARxGieKH9p8hB4zxJBTsgTJgUo+QXbPW+xkNdoaCHvNIiidN4wpm5DjkGxJEmWMtlpHW99zHTkmQbLuYUg0Y7K3jmOlYl7nMknXnBMwiDmOfJMxo48CorOcuTpgKlaqjif03zIYf+zaVB8jRx5VSmtSVUkTLcBb6iFPA5U+f7ktEbfNPLrK47rlUVsemylunesRhmdThtGidJ3AGDV0/KbHMprFgl5nhfAskwm9XSXX6mrXtyPhbzqOPIocFEoBjEpibjpDAZ9GPb8MnJ5TMdBHMfKryMpZWkhD+CxqCCXneMs6pFXmzhWNUlJRx6gvrymHAW8ihIEiCSJmTx3zg5hGIyDSyMHMMcNSpEjz3FMSCkqU1qTK1QaXE4lC9BrTkECwzBKJbBQ3009t6yPWY48wdyRR6U1KYjnuhaLRLsi8ueU8/mlucOogNuXIBFA5AK7QggIKVmLpmcB1cmLJ2HsyFO//9k0pueXqgh5nudBmhYM20Xg+6zWWGeVKsa5BMNku00j3xuvas//Kl7Ty7Dyxjf33HPPxOs77rhj1T9Ss2La7Ras68+XOtYcCXmdThu7u+dWOaxCXNcBMHbeTeN5ARs3XhyXd+7QJJWUDBqvCtpIT5ePmcbJhDz1gYLsHBc58pg4qTadfr8Pw3FKHWs4YyeKU/I7qyAV8orvvShKN98cgqr9fg8A4C4Q8kjko2NVU6XQhWGM5uSyguIS873m2gnDEFEUZf1apZUuhT1P/TNpGs/z4LrzkxuEEHBduxqOPMYBSAoCTCcLGEySA/IYhgEkxUELWhPquWV9kLMzj5ASUcw3yETuO0psc12zEo68SSGP39xNZIH2qffHbl8+cwuRibvGZBKJNKsh8m4ynJ5FZaG5RT+LTh+6HujM0p/cBd/BoA/DsiHNdI7xPA+Nxvy+7ZrVU2WdnWNCzKYQhiEcKTCMkwoKeRW+qEuwciHvXe9610STWy3kVZs4jtHtdnDxOTeWOp4cee12a5XDKoVppsGwIJi9oQ6CGGaJ3lzrII7j0lkEdJzqxT1t7hyjXGlN6qmnEtpUFDvyYsgNz+rgQK/fg7HbLHUsCX79fl9pkoBhGKUCMVnpNiZCnmGY2Zw4C25CHpKksC0Ufa56A5v9jpdw5GUuPs3KIdGL3AamQ4EEXmJYGIYIwxC12mKXsutaWeCVE9P7J85hpXmuGSn4OfKkNMolbsV8njlnBfq95IMHQggkJVz7qpgurZnOJx6ShHfJ57ygxHH+I+bOLeDryMuEvKk1omHarM/1WUB10u7JGMcBNadLlrBDiWmjP1XHhIrwvAGk6cCw0r38YNDXQp7mxIQhnzX6phGEIbYNiWEcsXf6TrPpj5y1RKapN5Dq4Jrm2ul2O4jjGHbJh63dTI87Ojpa5bBKUVTaTgj1AWAijqPSC17afKtetFFpL7eg/p0pBCwpWDgIMrG04PeeJAlEUV0/zTUzGPSzoHoRpsOjN5SURua2WwQJeRwEm16vt9CNBwC25UAIgV6Ph5DHY2YuxzhBoOScnMQ6U3mN0LOK5nTDtife50KWHOMsTjByXZOpS0Jg+s7lGsjLstqnhselXG8ewzCAMuWctZC3dmZeJ4JH79Z5TDvyajULScLb5QZMinecx0ple4/33yQhj9+1QedTTAl5wuCZNHKW4JRUsiybXuZMBdNrF45VBGbR7/chLBvS4rGX11SVdC3MMSFmE4iiCHEcoz4yaVTNkcckrL8yVm4/+s3f/M1V/wjNGjk6OgQA2FvlhDzDsWFYVvY9lYyFvNmfSykYCXnLl9ZUvWijPohNszho1DRNFn0Ts3NWEFwUQiBiviiuOkmSYOh52LHLCXnj4LvaxX9ZRx710TMKHKvroN/vLeyPB6TXvOPU2Ah55Rx5JXterhhyOiYlAy5xHC10R2pOF88bCXmjZ6eQEoZtsRPyKMC+qLRm+jnPUnhMNbuZ0FrAmJpl6HXMqDSiYZhISownGZXfNAwelSbOArP65QohEDN20Uw78hzHGr0/ZNNuYBZVd+SNS2vyC0Bm4u60kGda2fWiUUOVhTypE2JPnaws+Og1nWHVMaEi+oM+DMuFzBx5vNbfmmpA8Zcqz4ucod7xtVFMmmMv+cXwiOuvCi3kaZbi8PAAAGA3y5W/E0LAbjZwdHSwymGVYlbJmzxCcBLy4tKZ60KIVGhS/BDrdDqwpYRTQoBsGpKFkEcB3enN6jTStNHXm9eVEoZh2ovQKvdYouPyfVJUkDryigMx3Bx5tl0coHOcGpvSmgkSoFDK4wGJcmWD/0kUwbK0kLcu+n0qrTm+nkybX585Ck4XC3kWjo44Pp9m3a887+Hx+nDyfcEwu92yTMRx8TOHEgn03LI+sj1E/jqSgnU5PM/zYNsmaNBUyncwGGB7e0fhyBaTT17gLC6N+28eL9srwDMAmYm75vEeeTrgrhaO10tZdOWJ04eeOdOlNTk/c4D0+SJ3diZKa2o0y0LzIadku02CHHjakccT/UTVLAU566xm+TrWVrOOw0M+jrx5GWGcSmtGUQhDltfZUzFB7UOs2+1gyyonUmwZEt12e8UjKmY49CBNq7DchzRthEGg/BxvMiTIyZJBRznqZxkEaoW8avbI65fKtLcth9Xmqii3gT5XPY9T4DwpmWkfRyGskgK25tohcVrkgkrScdiI1gQFU1138bXhOCbTQPas+5DHGqssHGVHy7IRl+hTEY/mHy69n88szC95zxtMJAvUaql4w3NOGeN5XuY2HQz4jjXbe874jGupYarEYEwlfBm2ix6z5+RZg6ODU6MOSjKimUROvc8VbzCAYTnakae5Jug651iiehMg4a5WUSGP/QL8GtFCnmYpDg8PYboujCWCjnazgUMWjrzFN7Ng1MciCPylAv6maSoXNDqdNpols+2apkSnq17I8zwPhllcypHEJe6BjSpDZZJkyaAjF0eeYZgIw+J5g47hUOZsMOiXdOS5mXtJNQKiMLMqM0MoDo5lQl6p8ncJkjiCZZUrKau5dnq9LoBJIc+suegwcInnoTkxdcvMx3FM5fPgLNIyg+N7kdMaq8pYloUkjgrXtMmoZK/q+fAskZXOzv1qkjiGwcCJPw/PG2TiHTDpyOOM5w1Qc+uQ0siqa2hOB0pqIbcMYVguq+Sus4hOKNXkycqCTznyOK+1giBAGAaQlp1z5Ok5XLM82pG3WsJR0mBtFJOuWmnNWeXuNwkt5GmW4ujoAHazvtR37K0mhp6nfKNFZaocZ3ZQzLbTYJhqNweQLnKWCfgbhokgUJul12230DTLCnkG+oNB9oBQhed5x0rHzIKO4diHaFPIHHkleiymx/EQ8kzTKCXkUbaYandEHMfwvAGcEkKebbt8XEpCjMprzoc+Vx24pt9xXCJzmsQ+Xf5ufXQ67XT+yF0nVt1Fp6M+uSQPzW3z1iwErV04kSTJsdJOnMqXV5myiQJJFMLU88paoXV7/jpP4hhGyXWNCgaDAWq18RxDQp7qPVsRnjeAbbtwbIf1WIsTkPjNif1+H4blTCS7AIC0HQS+X+BwmiYAACAASURBVMGs/M1B9b5Zw4tpR14VeuTRfE1zTFqyVycIaJaHBDztyFsNVS+tuekCrxbyNEtxcLAPe6tcfzyCjqf+eqqgUiHNpjPz82bTQRiGLAJiJxHyVGZJJEmCVruF7ZLBCjpOdeC0P+hDlHDCUOkHNqLGBkKO0rI98oQQkKb6ALZpmqUWkGNHntqA3nDoIUmSUqU1HafGJkuySp4SKSUM0yxVWpOO0ULe+uh0OrDrtYn3rFoNvW6XVfCD5rYyjrwg4JGERNBY8vetduSdDuTeLZpf4iiEVdD/V3O6ZI68HFVw5NXr43Uw/Z2zOAakAqRl2bBsh806ZVm4rmv6/d4xNx6QOvLoc40aqhZI1awWSpiirjEy6+vLZz04DVV6odiKwayNg6YaJEmSXeebLtiogmJzNSknXleFTRd4T2wN8H0fn/3sZ/Gv//qv+M53voOjo6NCt4oQAg888MBJf6RGMXEc4+joEBdvun6p75GQd3BwgGc+88ZVDK0UvV4XUoqJEjJ5SODr9bpwnNli37oIggDGEs6d1JGnbnLt9/vwgwDnrHK9E8+NxJrDwwOcO3d+lUNbyNHRIUx3t/A4003/v1qtFm66adWjOpvQ5lQuIWBLw1Bu81+2tKZqRx5toMqU1rRtB2EYIAgC5UKTEKKw0jl9rtqRBwCWaZUqrRlnQp4urbkuut0OjNrk9W/Wa0iSBINBH43GcslKq4Ke6ba9WASwbQNxnCCKIuXzC5EJdiJfWlOyEhurCs3FcRRi0ZWRRCFsW88r60TOEuziWHkCzyLSHnlNDIejEkoVKa3Z6/VQc7cRRZEWlk6ZTqcN6dSOvW+M3ut2u9jZKd47aU4fWhfoR6kGGAt2YpQWQH9OV0TgBD1bqLWJtGz2zxsNPyYqH+gJcSUc75FXLUf4pgu8J9rxf+9738Pb3vY2PPzww/rGOUO0223EcQx7+6SOvP1VDKs0vV4P9boDKWcHefNC3vnzF9Y5tGP4/hCus136eNNQ60yi3+25km4qOu7gYB/Pfe7zVjauRcRxjHarhe1zxcqcVUuv4aOjw1UP68ySlQeZkdE+D2FI5dk2hlGutGYYRtnxKqGAlzMjSDONY9ey7ygP2ojq9MgDUmEuLiEya0fe+ml32jC3aggH4+QzayTsdTptNkJeWUcefe77PhshLxpd1yLnOTGkUbmyYBx3OCTOlXHkOVrIWyvZ8326tCZjIa/f76PROI9WKw2kmqYB2zbZOyQGgz52dy4hjiM2vXw3hXanDcM5nphpOmlrDdXVVM4yY0cex6fTYrQj//SZ78jje67J7U2OPGHaGDB3gGv4oYW81TPukSdHr6vlCN/0nrJL7/i73S7e8pa34PHHH4dhGPiZn/kZ7O7u4tOf/jSEEPj1X/91tNttfOtb38J//dd/QQiBF7/4xXjpS1+6ivFr1giJNc6SpTVNx4bp2Dg4UCvk9ftdNBrzgxqNBgl56jM7Pc/D9tZ1pY9XXVqGyqaes8oFK3YsAxJqy612ux3EcQTLLb6epeVAGqYW8lZIFviVSwh5UmbfU4VpVsuRR8G5Mj3yqPxmv99XLuSVceTlj1WNZVvw4+JrUzvy1kuSJGi3Wth9xoVJIa+RBihbrRae8YwbVA1vAgrYFTvyxkJevb5cD+NVQSJk/l40TCsrAcrhHs0jRPrcmY4F0Gu5xHNp1dBcUdSDM4lCWPXieV5zemQia5JkEnYSRWzn9yiK4HneRGlNIC2vyVkcI/e0Y9cQRxH2DtS2blgEJY/OWr9wnAuBVKirPeP4HpQceVrIUwc9W6sYtt70oKoKSLCjFYocPXk4O1Gmhby0tKYW8tTD71m0CC3krR4S7tzROqZqpZ1VxwhXzdIRxU9+8pN4/PHHYZom/uIv/gK33norLl++jE9/+tMAgHe84x3Zsf/7v/+Ld77znbj//vvxile8Am9+85tPbeCa9UNC3LI98ug7HHrkzeuPBwBbW2NHnmoGg0Gp0neEbblod/ZWOKLFHByQkFduSjGEwLZtKb0mSJQza8XXsxACVq2phbwVQs66ZYU81VmHqZBXvGEa98hjUlqzTI88m08/lDLBrqTkcevAtmx4JdxH2pG3XjxvgCDwU+Fub/z8sZpUPvlI1dCOEQQ+TNMoFJFI6OPUu2CWkGeZFpIkQRiG7K53OsfRVHg0nvqcA3Tuihx5SRzCZnaeN53sus4FleKA3/VOUEsMSmQkGg2btSNvOPQQxzEcx0UUR6zHSnNHPBVoTJIEMXjNLUBaEcYfDrHlHE8K0Y489VAgNaxQQJUEPC3knT7kmDFGay1jtORSXa1mEVlpzVGCizRtDDp81t6aaqCFvNVDpTQtKWBKUbmqKlUb77IsvXr8whe+ACEEXvnKV+LWW29deOwtt9yCu+++G9dddx0+9KEP4b//+79PPFCNeo6ODgEhYDfL9UHLY201sa/YkXdwsIcLF+aPfWenBimFcudgGIYIwwD2jEbj87BtR2lj+sPDA9RNA84SZRHPmVJpudXDw/JCHgAYNfVi9CYzduSVF2I4OPIMwyy1YSKxzzRVl9YkR15xaU17lH3NIUiWOvIWL9QTJGzyCS2rXI88CsbrXlbr4egoDRZMr2OsmgshBDMhLygsqwmMHXmcMiVnCXmmaU18xgka53QsgILv5NjjAM0VxY48vk6wTYXOdz6oFIcR2/mdknRmO/LUJ/DMI9/r13FcBEHAav7Lkwl5U++PkwR4lV3tdDoAAGOGkCekhGm7aLdb6x6WZoTvDwEAw9GfVWAs5G12UFUFdG7N0RqG/uR8rjNHXq5HnsoYlmaSKopiVRxzFSBHniUELCErV1pTC3lTfP/73wcAvOxlL8vey2/Up7Ntdnd38cu//MuIogh/8zd/c9JxahhweHgAu1FfyjFD2M0GWq0jZROt53nodDq4dGlr7jGmaeDChSb29q6ucWTHocWMbS8r5HnKzu/BwR7OLylQnLdMHOyrcxHu7T0NCAGrPv+ayGM1drC3f1W5A2xTOZkjTyjP8DRNE0FQ3pFHwWxV9Ps9CCFKzS9UWpNDuWEhZHGPPPBx5JmmWU7Ii6l3Io/eZpsOCXVUSpMQUsJq1FkJeb7vF5bVBMaOPE4CGbkDZwt5/AKQFEyffron2ed8hDw6j0XzSxJHbJ1gm0om2OUeVlEYshVUKUlnuu1Ao8G7tCZVTnHdOtxRwhGHdcossrllagFDr40lEiDXAT0DTXd24qvhNtBqaSFPFeSi9YfDygSvq+bIq8p5BcbndOzIS/8sUylGFZ7nQRpmtt83TBuB7+v4ChO47KOXoYpjrgIk3JkjRx459KoC1wSv02Lp1WO3my6eb7hh3EMkn2k4a+H/kpe8BADwta99bekBavhweHR4IjceANhbDURhiG63c8qjKsfe3tMAsFDISz9vZseqgkoOLCfkuUiSGMOhmgDZ/t7TuFDCOZDnom2i1+8ry8J6+umnYNe3IUsG0O3mLsIgYBXo3SRoAb+M80EIHqU1kyQpdOWNHXmqS2v24DhuqUUvufY4ZOYLUdwTJEn4LOYtywJKCHnUx0L1dXFWaLVSJ/astYzVqLMqnxwEAawSfWctixx5fIQ8CqqLnNvEtsc9N7lBfazmBdt5CXnp77tYyAv1vLJmsrKno+smSRLEDEvJEnSfHi+t6bB47s+Dxr23/yQch9Yp6tsizCIr2zu1gKHXnOYWAJlIZ9Zm7/dNt6H3QQoZDlMhL47jyrgNaJxVCQKr3lcuw1jIw8SfvB15HmQuuYWceRyTvM4W1RGwgcn9Ppe9/6ZBQpgpBEwhKujIq9Z4l2Xp1WOtli6Y89kq29vb2d+vXLly7Dv0AN/bU+e+0Vw7h4cHsLZOKOQ10/KFqoJk5LIrFvK2sL+/p3QRR2KnO6OsyTwoI1WFUBoEAVrtNi4uKeSR8LevyJX39NNPwWrslD7ebuwCAK5efWpVQzrTJMnonluitCaE+sxJCpSS424eXHrkdbvd0nOLYRiwbYdF31AhZLGQBz6L+WUdeTrgvh6Ojo7S8mC14z0i7WYDh6yEvOUceZyEPFqL5IPUNbc+8RknaJzTcwzN6lzmFSAn5BW4G5Io0vPKmsmcdyTkjX5HXEtr0rN9un94o+FgMOizDWjTuJ944mE4o/UMX0celdac7r9JSQK8SmtOO/LaVy6jfeVy9rnpNtBqayFPFfmEXRL1OBOGYTaPVEWo4SyCTTPdI08IAUOor1aziOHQg8xVp6G/k9tUoymDFvJWD80vYyGP/9yYn/s4VapZBUsLeTfffDMA4Mknn8ze293dxfnz5wEA//Ef/3HsO1//+tcBAK57PHCiqQZRFKHTbmWC3LLYIwFQpZAnhMDFi4vHf+nSFsIwVJptSE3Ea3OyIWdBx6oIkJEQd8FeLuOYjldRyjSKIuzv78Fq7pb+jj069umntZC3CsaOvGWEPPWOPBLmihx59LnqHnm9XjfLYC+D49RYBMjSHnmL4ZRLaJpWYaAdGAd6uTo2No2jo0M4zcbMecZuNtBpt5TPKURaWrNYiHEcc3Q8n8xDqt6RF/JcxkIeOcGn80IShq6ZzPUVL95Qx3GkvJTzWcNxUkGMEoyigHqglq+wsU7IdTct5DWbDpKER3/cWdC4pZS50prqE45mka0R5zjyuJXWbLePYNhuVq2k/diDaD/2YPa56TYw9DxlFWDOOnmxowrCR/46qY6Qx2MNWAYSHY3cmtZgHnAfDj1I47gjrwrCtIYPWshbPVEUQQKQQsAU1UhyyCe1aiFvihe/+MUAgG9+85sT77/0pS9FkiT42Mc+hocffjh7//7778fHP/5xCCHwQz/0Q9c4XI0qqL+dfWJHXvq9g4OD0xxWaa5efQrnzzcKg+iXLm1nx6uCGo27c/oTzIKOJRFwnezvp0Lcso6885YJATVC3sHBPuI4ysS5Mhi2C9Op4emn1ZZe3VQo8LXMYkxIgThWK98YRjqnFJfW5OPIW1bIYxF4L+m+5LKYl1KOXaYLoGM4CQWbzOHhAcw5JcKtrQbiOEa7vf7n6Cx8f5iJdIsgsY9TkKzbbcO2XQiM70dap7CYT6ageeO4a2bycw5oRx5fph15cUhCHldHXg+WZRxLGCBhj6s4RuMSQsBxeffIo9LH4dT6hV5zE9uPjo7m9scDxk49XV5TDYNBH4aTzieqWlMsQ16cqYLwCIxL3lcBClrbuWo2luRdAs/zPIjcvEd/18kBmmXgtC7fVMIwgEG9LEU1yiPnxTtOlWpWwdKRo9tuuw1JkuBf/uVfJt7/lV/5FRiGgf39fdx+++14zWteg9tvvx2vf/3rs3rrb3zjG09n1Jq1Qwt2u1G+3GMew7JgOjbaispxPP74Y7jppmLR5oYb0lKLs0rErotOp52VtCsLOfJIBFwnVDL3grVcwMiSAju2paS05lNPPQEAsJvnlvqe1dzNvqs5XbKN01KOPKF8w0VCXlFpTRL6VAs2/f5yQp7r1NHrqg/mJUlSuGgXUF9qlUh/zyXGwrAH1yZzeHQwt9fvuAS4moSjacoKeWNHHp8gSLfbyUppEqZpwrJslkIe9cibvmMTUIIJn/uTSvEtShRIkgRJEmfPJ816GLslR0LeqL8IXyGvi2bzeLWcsZDHUxzr9XrZfWBbDoQQbEVHSt4Kp5LO6DU3sf2oVSDk1dLnpBby1DDwBnC20zYhg0EVhLwqOvLG+0oue4p5UA8ra0LIk6ydKMPhcGZpTS3kqaZawpgQIlu767XuagjDEOYo9mJCVMKRl5/7OM+Dp8GJhLw77rgDL3rRi/Doo49m799yyy14z3veA8MwEIYh/ud//gff+973sofhb/zGb+BlL3vZ6Y1cs1ba7VSMtU4o5NF36d9ZJ71eD4eHh3jWs84XHlur2bh0aRuPP/5o4bGrotNpw3Vnl/6ah2O7kFIqc+Q1LRPOCcrDXDAl9vfW73B78sknACGWcuQBgL11Hk89/SSb0mubBDnrxBI98oQQyn8XWZAmXCwohmEEKaVSwSYMQwwGA9SWcvvW0eUQIEvKbTG47LmFkOUCAAk/oWBTCYIAvW53bmUBev/wkEefvLKlNalHHqcNy8HBPuqN4z2JG41tHBzsKxjRYmi9Na+0JqfM36yf36L5RScIKEEIkSbhkSOvAqU1G43jImOjwd+RR9e2EAIukxLgs8j6KFfEkdcuEvK0I08ZURTBHw5hb6Viar/Ps/RtHhJnGg2nMqUT80Ie515zwHjdZ+XWKLYQrJ0ovj/MSvcCgDSs0ft8x6zhCa0D9Fp3NYRhBHMUlzOZO32JfMLIpicHLJ0GZlkW3v/+98/87HWvex1+5Ed+BPfccw8uX76MMAzx7Gc/G6961avwohe96JoHq1FHJuTVTy7kmfVa5s5cJ48//hgA4Oaby7mvbr55Fw8++Mgqh7SQdru1VH88IN3I1mpNJULp/t5VXLROlglz0bbw3/t7pdw2p8mTTz4Op7EzsZAsg7N1Hq0gwMHBPi5evG5FozubZD3ylliMCSkRlyhfuEqoXG+ZHnmqM8YoKFerlZ/Ha24d/X4fURQpHX+psprpkaseSimkFKVUxSQLuPMRCjaVrLLAPEdeg3r58nDkDYflHHlSSliWwSYIkiQJ9vf38Zz/84M4PJosnb3V3FXiwi8iE/Km3qfXnO7PbB5ekMQyLtmrs5TXjWVZGI76F1JpTa49UHu9Lra2jouM5MijXnTc6PV6kLnkF8epod/nKTqSUBcmCb7RSs/nS3YaiBJ+jrzhcAjPG6ChhTyWUClNZzsV8rj2sMxDY7x4sYGrV/k7CIHjQh6ne3Qa3/dhSgEp8o483qLY0PdhbeUdefyqSmiqQbrGVRuf2GSiKMz6b5oCiBj33iSq6AI/Kaf+ZPqBH/gB/M7v/M5p/7MaxbTbLRi2BcM++WbUatTRurL+3nNXrqTuuvJC3nl87WuPoN1uYXt7Z5VDm8nBwT7O7T5j6e81FWW67+1dxS1LltUkLtgmvKPuqLzP8ez9VfHEk0/A2ip2aE5jj77z5JOPayHvlBmX1lxGyBPKsyXLl9ZMlC80qaSd65YX8tJjE/R6XSXz4ZiknCNv5eMoh5SypD1QO/LWxeFhKtBRNvs00jRg1Ws4OuLkyCs3ZziOxWbD0ut14ftDbG3tHhfytnbx+BP/D3Ecs8qgpftvukfeuLQmHyEvPW9icQ/OmHqy8jnHZwXTsjD0RkLeaH3CVcjr93t45jO3j71PLj2uLrderzuR9OU4NbbuwXyPvP9qpaLGS3YaCBgKeSTOUfnMWQgpYbp1LeQpgEpp2hUqrUnJAJcubeGRRw7YPftnkS8fp3qPWUQQ+LCmzqcFkZXc5EgQ+HDyPfIyRx6PNaymOlBcRSetrYY4jmGMtj8SIlvTcoaEPGFYG+/I4/0k1bCh1WpdkxsPSN18vW537YuiK1cexaVL26jVyvWooBKcV648tsphzSSKIrTbLTQbxzfWRTQa21mgcl14nodev4eLJcp/zYK+t84Mfc8boHV0mIlyy2A3dwEh0tKcmlOFHG3LlNaElMpLa1IAuMgxxmHzSj003SVKa5I7WHVfqyQpFvJEeuAaRrMKqjru6kAC3TxHHgBYjQYLIS8MQ0RRhFqtnADgOCabDQv1zW02jwv/W81dRFHE4hzPZE5pTW5IKQt75KXH6eDGurEsKxOAk5C3kNfrdbMymnlM04DrWmyFvH6/N3FtO04N3S7PsWalNSvQI4+qupgFyV6G01BSAeasQ6KYVXNhWBYGA57XfJ6xkLeNJKmG+DjpyOPtQPF9f6KsJgDYUsBnWsY0jmOEQQAxUVqTHHl8XYQanlBcRXWi9KYSxxHkKPoiBZTH3MpAJZxNtw7P4zkPnhZayNOUot1uwazXrunfsEf99dbZxy1JEjz22CO4+ebyvdBuvHEXUgo89tj6y2u2WkdIkmRmAKyIZmMH3W5nrVlYJMBdOKGQd0GBkPfUU08CAJytcg7NPNIwYTd28OSTj5/2sM485MhbqrSmUO/Io0VkFC2O+EZRolzIO7kjbywCqiItv7v4GCEEYiaR9yiKy7lLR/9Tccxj3JvM0dEhhBSwFqxl7K0GDtacEDML2oi4bjkBwHUtNv1n9vdTF972jGfs1tbu6Bhe5TWzUpRTk4zMeufxuj+LHYL8nIRnBcu0xj3yRusTbn3QgLRnqO8HWRnNaRoNh2VpzTAM4fv+xHrKcWpsywzS7z441iMv/ZOTyJsJec7iZK/UkaeFvHVDPfEMx4Hp2JXokdfr9WCaBs6dS/cSHOeUacJc+biQeSk53x/CndpbOlLAZ5LYNQ2dz3xrExL1OLsINTwZO/K0pLEK4jgG5ddLISoi5KVzn+nU4THZF68KfdVrStHutGE1rk3IIyFwnULe0dEhOp0Onv3sC6W/4zgmbrhhF48++vAKRzYbctQ1TuDIazbT76wz031vLw3YnVTI27VMSCGyf2cdkJvuJI689HvntCNvBWQ98pYIPAopldv8afFYFOhNEj5CXm0JIa/m8nDkBUEAs+DaMEV6nlWLu0B6PZdxl2a9uRT3ejwLHB0dwm40FiYL2M0G2q0j5ZsVyiJ0nLJCnskm8/DJJ5+AaVoz1zG7OxdGx/BKhiEhffqOFdnnzO5PgcV2wYSEvPUMRzPGtMxsPcC5tCa57ZrN2dVKmk2HZblKEgImeuTZLjxvwO8+RRpolEIgnLpfx6U1+Vwb7Xa6PzcK1oimU1/rXl6TQte+6TowXJ5C+zT9fg/NppMlDHB1+ebJ7yE4zil5PG8Ie2pJa0vJNoAdBKnrLu/IE0JASCP7TKMpC+2hDYOPs32TiOM4E4skgIj5fAjkHHm1BoZM9sWrYm4045ZbbsELX/hCfPe73z31H3r58uXs39fwJ0kS9LodWLVrE/KsugtgvQHhRx5JxbjnPOfiUt97znMu4LHHHll7QJh63J2ktCa5+NbZJ49+1vkT9sgzhMA528TBwTodeU/AsJysYfv/Z+/NYl3J7rLvZ9Vsl8c9nLFPzulOdwh5wwfky4S+0IKkUUCQSQTllkYBIYWEIAFK7kAICBESg+AiF1EGLoiElOEFIhQl5OJNvwqdoTunkz7dfXo4fYa9t7fnctkuD1Xruyivsre3h7Jdw/I+9ZNaOfa2a1e8y1Wr/s//ef6romR20GjUuSmanhWGwwEEabVoBCKKGHIi5C1zVPHgyGu1DCiKttKClxdH3tCHkMfiZYbD+Ls6XYepjyo6m821BYvjbader0HSFxcolYwO27ZjF65ZR6HfaM1Uih9H3tHRAQr53ZnnO1VNIZ3OcNcMw75/09q74Dlm+fp+Lmt4oT5flxA8sqR4QiqL1uQpPpHBHGzp9DxHnsKly425kE7OyNNAKeV2XS5JEgZTa8TB6JzCk8jbajUhyuoJt8wsRC0Ny+omDpqIYd9HSVMhquqWOPJM6LoyIeTx1xwwzVZFa/YsqFPXeU0g3MZUsv0ShJPnGEGSkvNJwtpIK9aPEvxx2pEXf6P0MizLAgiBqKTQO+NzNxdWFcOOkuEtqiZhNt1uF7ZtbxytyYTAKLv47ty5BUWRcPHialGV167tod/vezGMUVGplCGKEtLp7MrvzY5irKJ0t9XrVWRl6dSg5VXYkUTUIxQfDw8PoGSKaxe41JGT7/g42mPjrDMYDCCsWOwSpPg7+MbRmosLvW40ZLxFVdNsreTGA9xucVlWYhc2BsMB5CUON2n0cx5uBimlvmJiCadCwVmk0ahDyS5u4JBH8/OazUYUuzSXdaI1LSv+2TOUUhwe3kOhsD/3NcXCPg4P7kW4V8vxojWnxHf2Debt+0lAlgzw86S8KHYnYQJRHJ/3qcPvrMKxkDfbkZdO8ynksX2abBRQFPf+kleHkizJpxx57DFfQp4BSV1+ry+p7joymZMXLe12G0QgEGQZoqZshShmmi3kchqy2eibudflZLQm34XrntWFJk5Fa4oC+oMBd+sWYHx/RqZmmgmihH4//nu3hO2CXVaTGXnhYNsTjjwCOEtqXTzQ61kQJQWCrMKxbS5qQmGRRGsmLMU0XeFNTmkzf04pxaDTgdVoonLjhbkCrTR6f5TOjtu3b+Hq1Z0TN9Z+ePDBXe/9UVKpHCObLazl3NHUFFRVQ6VyHMKezaZWq6K4YRdMURYjcxFSSlEqHUFZYz4eQ8m57+XNUbDtDAYDCCsuxARRxHDAd7ckgwchr9VqQVvDiZpK6d51IC6Gw+EKjrz4j4nhcAjiY0YeIaL3+oTwcBzHdaQuc+SNfh63kMecJZrmr7lB0yTPxRcnzK1eLC4W8sqVMlc3V+No55PPs8fcNR4SgGL5PiWGvOghhIx1VDAhj78/RLfrCv/zhLxUSvZewxPMhXQiWlN17y95FB4BQJLlGY48/qI1TdOEoCwX8kTOhdOzSqfTgSBKqL/4CiRVRYfT430S0zSQzWrIZFQQsh1C3jY58qxeD8rU9UUd1ZB4WBNOwxJTyJTrlwgSF2kq9zecrXNXIInWDAdKqdcOSODvviNuLMuCIMkQRmsrXtJqwmDpUf/JT34SqQ0jFafh8cYgYT5MeJPnOPKqN26ib7hdYXef+B5Agb03vO7U64ggQE5pkQl5vV4PR0cHeOyx16/83mIxjVwuhdu3b+Htb///Qti72ZTLx8itObsNcF155XJ0Ql69VsWD8qZCnoRuow3L6kLTgj3XTNNo1NHv95Df4DOWtAxESUGplAh5QbKeI0/CYNCPVSSj3iyixb+fEBJ7MbjVaiGXXS1mGAA0NR1/tOZwCJnMjgBj8OTIGwz6p25UZ0EkNuSdzxics0KrZYBSCnmJkCdzJ+St4sizYm8YYLPvioX555licR+UOiiVDvHAA6+JatcWMo7WPPnZiaPHPMzdPAEdufKWvYz/e+4zx+T3b7w+4K9vduzIm32OSacVWJblRivFHAs+CXMeUS7MMwAAIABJREFUkxOOPHX0Mz4LNrIsYzAVdTccfTd5il012yZEZXkijKgydxX/jrCzRLfbgeM4qD7/EjIXz6PH4fdzEreBykQudwmiKEDXo6sBbcJJRx7fQl6/34M6dQ5XR/dCvZ4VeA13U9jnKQgijHs3AQC5y4+MZuTFf++WsJ0kjrywoGDJHoQ95Jxez4IgKRAlt0nNsixkMqsn3W0DS1ePzzzzTBT7kcAxLApTmrMYaN6+d+rxLCGPbSMqZ8e9e3fgOBTXrq1euCaE4MEHdyN15A2HQ9TrdVy68Nq1t5HLFnFcvhPgXs1nOBzCMJoo7q4+z28SNl+vXq/h4sXLQezaXI6PSwCwkSOPEAI5k0dptK2EYBgM+iArujvZTL3hcBhbPBEr1C3ruOdByDPNFs6fW71wrmlptFr1EPbIH7Ztw3YcT6ibB3Pk8XAz2O/3AWF5gY7NieBhn88yTJiT9cWOVFFVIEhS7EJer+cWq/3OyNM0GY7jYDAYQFFmO2yi4O7dOyCEoLggWnOneA4AcO/eXW6EPDa3RZkS8sbnFL6EduoqeQsg3isTomWyqM6iNeN248/CT7Qm4Apn6fR6M6XDgAl5k448RVZP/Iw3JEmCPWWOGY463XkqQLbbJrRz88/dDFHRvNcnREe32/EEbEnl8/s5SbfbheM4XqxmLqdtiSNvOPFvzpp4JqCUotfvQ82cbHLk2ZE3Ga1p3H0BwFjISxx5CevCazPDWWBy9botjjxywpHH33kwKOZWmd7ylrdEuR8JHMOEvHmOPGeqW2n68SRSOoVmM5pM/bt3bwMArl5dz3119eoOfvSjuzDNViRKfq1WAaUOcrn1RaZcbgcvv/Isut1u6F1YjUYdFEBR2ayblL2/VgtfyCuXR0KeXthoO3KmiOMSXzN+tp1+v796tOaEmyluIW9ZnY6QeOPZ+v0eBoM+tBVn5AFAStNROo6mQWAWrDiXWrJQT40ilHmI13KPZ/+OPF4H058VmDC3LFqTEAJFT8cu5K3qyGOCX69nxSrk3bt3B4X83sK4OF3PQVVTuHcvvnPKNJ6QN9UswB5z9/2kQDL/jk9c9x271rNGH/6KTJZlQRAIlDlr+FTKPY90u3wJBezcOCmOyiMhj9fEH2nOjDxJkrgReW3bRs+yoK8QrZkIedHS6XRARtckUVW953j6fk7CGreZkJfNqrHH9PthW6I1WSKNOnfdwl8B24vWnG50TBx5CRvAU0PMWcKtW43qXFtyz+FGayoQRo68+zJa81/+5V+i3I8EjjGMJkRZhqhsXiiX0ykY96JxMt258yr29jLQ9cVxbPO4etWdk3f37m28/vX/K8hdmwlzi+Vy68c+5kfvLZdLeM1rrgWxW3NpNFyHTnHDaM3C6P2NRm3jfVrG8XEJkpqGqKx3TDCUTAHVuy+g3W5DX+LwSPBHt9uFqK5WgBaV+AtN2xKtySKQNHV1IU/VUuj1LAwGg1gE03bbncOSlhYXQ9MjIY+HuS39QR9EXP5ZM7GPN8fPWcMw3AaiZdGaACDp6cgajuZhWV1IkgjJp0tZ08bnwmx2M5f8ulBKce/eHVy6uDhVgBCC3Z3zuHuXRyHv5DlGIASyIHAn5Pntik2iNePg9Icetxt/Fr1eD6oqz127sPmcvBWDLavrOfAYLFqT14KNJM8X8niBNUAJPu6PBFECEUQumqbuJzqTjjzvms/v34Ddd+RyY0deqRTv2soPJ6M1+XXkMaeJOrVu2RZH3iSCmAh5CavD1i88NkudHU7HxfOM1bMgqHnPkcdr5HoQJEd9wlIMo+mr+OUHWU+j3TZDjyqglOLOnVdx7dru2tu4cqUIQSC4c+d2gHs2Hybk5TcR8vK7J7YVJqwwmtvwRjQlCJAF4m0vTEqlI8iZ/MbbUTKua5I5/BI2p2t1PWHOL+JEtExcUOrOVlou5MW7AGKd0+s58tKjbcQjkHU6owiwJR137Ofs9XHS6/W8ReQiiHj2ox94wDAMCKLoq1lA1lORXI8WYVk937GawElHXlzUalV0u13s7pxf+trdnfMol0vciARsP6YdeQAgC4Sb/fRYcilh16NtuOk+a7j3N6OZIqPiEo/xbL2etdDxq6p8Xpssy4I8tVYURQmECNw68kRRmink8eQiYH9nP+sWABBlhbtj46zT7Xa8c/ukI49X2Dy8sSPPjdbk/bo06cLjeUbeWMg7uW4Zz8jj7/s5GLAZeSdrR0SUEiEvYW14upYugvdz3yzI1P/yTo858uT4a4Rhkwh5CUtpGk1Ic2I1V0XW3e2EPey42WzANM21YzUBQFEkXLxY8CI6w+b4uIRMJr8wkmoZGT0HSZJxfHwU4J7NZizkzb54UkphDG2U+wM8WTfnXrwIIcjJUugOCEopyuXjhbGalFIMrQ76ZgPN2zfm7rOScbcRhWB6v2Ct48hTxy6UuGA3edISt5gsi7HeEHqOvDWEPFVlQl48sy2Yw04X/UVr8uDIs6yut4hchCjHfwzfD7RaBmQ97SvGTE6nYZotOI4TwZ7Npt/veYV0P6iqWxSJs3DDojJ9CXm7F0ApxcEBHxHVi4Q8hUdHHqVL8pyTGXlxYdu29/EzIc9xeBTyet55YxbMkceby63XsyBLJ6+thBDIssLdvjJkWcJw6qs4dOhG93tBs6qQJ0gyl0LBWcVxHAz6fWB0ThHl+Jt3lnE6WlPDcGhz75CYvFfjOVqTrVvmO/L4+5y9aM0p4YUIIgbJjLyENdkWRx6PTV3LmAyK5yUKfBG9vttILYwapblrxAyQ7TjqE2LFMAxPgNsUOe0WhFutcEWb8Xy89R15AHDt2g7u3r0dSUHvuHSEfG6z/SWEIJcrolSKRshLSyLkGYUvAHiy0UZtMETbdvC/S3U82ZhfXM+JAoyQZxKZZgv9fg9yZr6QZ9x+DsOOAadvofyT/wvj9nMzXydpOgRRQrVaDmt37yscx4G1jiNvFPcbZ7QM6yCcN2eGIctirPGJniNPXf1crmnxzkNhwlx6iZAnEQJVFGIX8mzbxqDfhyj5iKjifLbPWcFtSNJ8vVZOp+A4TqzHUa9nLSyyT8NeG+cNy8HBXQiC6CUDLGKneM57Dw8woU6ecZOq8ujIA118Qz360TZ2/247Jxx5It+OvEXnGF4deb1eD9KMJhmZY4eY68g7+ZxNKSQfc3SjghX9BdHfOpyIMpdCwVmFXYO8KDmFz+/nJKZpQpJELzGARWyaZjxNgX6ZbOAeciwusb/9dAOSyvGMPC9ac9qRl8zIS9gAdzYx//DY1LUIQsiEkEe5n5Nn2zbs4dAV8iTmyOPvPBgU23HUJ8SGbdswWwaUdDDRmsooopPNVwuLe/fuQBQFXLq0WYzia16zg16vh1qtGtCezca2bVSqFeTz6zsIGfncbiROsWazMdeNBwDPm92FjyfJSWLoQl6l4opuSnr+/KB2+fbCxwxCCOR0zttmwmawm43VHXmuCBJndye78ZCXzIp0HXl2bC4fFoupriPkqfFGa3oz8pYIee5rxNj2k8GORz+OPCKIIIIAy+I3HuksYBhNr5FoGSxK3DCMMHdpIb1ez3PE+IFF5MXryLuLYmHPV8RNKqUjncrg3j0+hLxutwNNFCHMEMc0QriLL3MFuvk31OxmOxHyomdoD70/jSC43wUehbx+f/E5ZuzI46sIYlmnHXkAIEsyl4VrwI39cqbcsTYFRJ8zUKNgVUeeK+Tx+XmfRVgxkoxEmu1w5LWQzWr43vdexZNP3vKcea1WfGsrP0wmBfA8I89rJJ0S8liDNY/C2DxHniBKGHK4vwnbwTY4xQDAtuNLelmHyc91Gxx5k+sYIrr1FV7XhUGQCHkJC2k06nAcB0o+G8j2lFwGAFCtVgLZ3jyOjg5x/nwO0oY3SZcuFUbbOwhit+ZSrVbgOPbGjjwAyOd30GoZoTs8jGYD+QWF9b5DFz6eJC+JMEKOMmPHnKzPF3edqQiN6ceTSOkcyomQFwhMeJHU5Q6mSaSR8BencDN25C0+1zDHXlzdnZ2OCUmS14pyUlVttI14PudWqwlVFGa6ZabJikLs882YQ1SUlx/PhBCIspo48kKEUupGa/qMCGevi/M4cqM1t8eRx2Iyd3bO+X5PsXjOi+OMm3a7DX1OPLIuCuhw5iBYGq2ZzMiLjeFw6BU7mCOPxzlL/X5/4TmGrVniTBKYRa/XgzyjSUaS+HXkCYIAe+qr6IByFQfGIgSJ4O++mYgiBhwe12cVT7BjjjyZT6F9knbbRCaj4n/+5xX8z/+8gkyGzfWLP/5+EZPXTZ4deWzfpKm1AHvMo5A3duRNRWuKEpfXyYTtgHeBibFtjjyAgI6akJb0D3LBdLKAGwHOb7PLpvCzgkzgEhYdqOaCEfJEWYaSTkcg5B1s7MYDgAsXchAEgqOjwwD2aj5spl3BRyTVMpgYWC6H68prGQayAXWTZiUx9CizSqUMIgiQUnog25P1HBr1Gped1tsGi2z0G33HECQJoiLHNrsNGBe5/Djy3NfHc6PSbrfXcuMBgCyrIESITTBtNOooyJKvhXpBFtGo1yLYq/kwIU/wIeQBgChr3Dl+zhK9noXhYODfkZdms3zj6xpfV8iLq6hXq1XR61nYKS6fj8fY3TmHSqXCxU1Wu21Cn1NU1yUBbY4Kj77EudG5Ms45j/crPcuaKLbz65rp93sLI8HH5xS+hLx+vzezIUmWFW5nbwmCCGfqe+vQsWOTB9i9DPEpLhIiwEnufyKDnUNYhBwhBKLCd5Gy02lD18eiu64zIY/v9S6lY5GdRzGMwe4np4U8gRCIhHApjPX7fQji6fs5V8gbJGuWhLXYFiFvsma4DY12gkC2akbedLKAKPG7LgyCRMhLWAgT3NT8/DjCVZFzGVRCnC3WbptotVq4fHn+LDS/yLKI/f1s6I48FoWZyxU33habTxNmvKbjOGh3O8gEJOSx7YQ5g6tarUBJ5wPL0Vb0PBzHCT0m9n6g1XKFODm1utAkp1Le++Og3++DECx1/46LYvEsKDqdtuesWxVCCDQtFZuQV69VUZzjlpmmKIswjGasArtpuucx0adwKigazJjmD94PsIhM2WejgJSKP/6p3+8vbQ6YhL2WzXqLmsNDN4qKzb7zQ7F4DgDF4WG4jVJ+6LRNpMXZN6hpUUS32+WmwMRu/v3cUG9BneDMYVmWt84cz/Hlz3Hd7/cXJgmIogBRFDh05FlQZjTJ8DwjTxAETIeS2JRC8BEXHhVe5JfPeyQiCEkjY4R4gtLEeV+QJPT7/ApN3W5nSshz/70djjwCURS5FMMYniNPOL0WkAQ+hbzBwBXypmHP8eyATEjYlMlrJi/3FMs4IeRxbsnzZsmOhDwiStytYYOEnxVkApdUKmWIigxJWy3ybhFqPotqJTxHHnPPsVjMTbl8uRC6kFcuHyOTya8VezdNRs9BFKVQhbxutwtKKfSAbkLZdlgBPAyq1QrEdDDOUgCQR7P2wnaX3g+YplswZwX0VRBTaqyD07vdDlIpFcKMG6lJ0mll9Pp4CnqbOPIAd7ZepxO92EQpdR15kj93UkGW4IyiFOOCNSSIir/jWVS0WI/hsw47FiSfjjxBFCFrWqzHkG3bK0WDE0IgivEVVkulIxBCVprzW/Cajo7C2i3ftE0T+pzZfroowKEUlsWHGDPu4l0wIy+J1oyNXs8az7FSFO853hgM+gsdeYAbrxlXc8AsKKXo9fqQZkRrypLC5ecMuKLo9Iw8B3w58ljkF1mylmUQIsDeupiw7YWJMpP9G4IgepGoPNJutz0XHuA2PKqqtBWOPEIIREHiWlhi+yYTgqeabTzVHAukEiFc7vtgMACZIeSx53h2QCbwx7atcSfv0bahEYYQghNLF751PG+9KnhCnsxdqkSQJEJewkKq1QrUXDZQK62ay6LTaYdWFGGi26JoTUopms0uSiUDTzzx4sILwaVLeTQajVAL8KXSEfI5/wWwRRBCkM/thFocY0XnbXHkUUpRr9cgByrkuduqxxzjdxZotVoAIWs1DMipFFoxiiCdzsmO03kwIS+uTlTTbEFT/QkZs1CVFNohCu3zsKwuev0+Cj7dSYXRuSTO76XnyPMr5KmpUN3I9ztMkJN1/0K2lE7FKuQNh0NIPl2oDEmKr6h3fHyETCYPcUaBZh66noMkyaE2HfmBUopOtzO3MYk9H+cs1km89erCdXki5MXBYDCAbdvePRNz5PEW7UMpxWAw2Dohz90XOnNGHt+OPBH2qWhNvmbkMXeA79QSQrbGUXAW8K7tE+d9Igpcuq4At0jd6/W8ex9GOq1ugSPPASEEkiRz7Xhkf3uJEPyg0cYPGhNCniBwKYr1+72Fjjxez+EJfLMt16JtFPLGjjwaWKpZWLDzR7d6AOPeTRBR4rbBKwj4/mskxAqlFEdHh1ALm8+am0QrutsLa+5cuXwMXVeRzc4voj7xxEuoVEyYZg//9m8/xBNPvDT3tRcuuPtbqRwHvq+AeyKvVMqBCXkAkMvthFocY0XnoBx5GYkVysIpZrfbJgaDPuRUcEKeqKZBBDER8gLANFuQNdX3bI5JpFS8BfdOp33qRnUWTOxj89Oixo3WXN+Rp2mpWOIfWXRtQfbvyHPf1whtn5bRbpsQJWXmzeosREVDz7K4LchsO56Qt0J0r5TW0DSaYe3SUmx7HSEvvqKe24y02oxf5uCL25HX7XZgO87cxiT2fJzXmUm8aM1FL/IcedtR3DgreA2KAovWVE4+zwmDQR+UYukcTlWVvKgiHmAFGVmaLeT1+z0uC3qzNHcKwlVRbHUXL+V+Xs5ZYta1nYgCt448ds47LeQpsd0H+cVx6EjI4+v8Nw0TAmaZaAXwKW70ej0Q8XT6lDB6jufPO4E/2DWIx2N9FieFPD7P3dN4Qh7l3pDnnT/ax3dg3H0BgiSjx1EzWtCsvIIMM/ougS+azSZMs4X0/mrFmWWk99zt3b17O9DtMmq1Kvb2Mgtf85OfHCx8PAnbVrVa3XznZtBo1OE4NnIBCnn53A4MoxnagogJbkE58jRBgIDwzi9MbAvSkUcIgZzOoF4P57i4n2g2m75j76aR9RT6vV5sXXzTMyDmEeeQ936/h8FgAG0TIU9Nx+JIqdXc71dxiXOAUZAlEAC1WnyRt6bZ8j0fDxjP0kviNcPBMAyIsuy5Y/wgp9NoGfEIN5RSDIerRWsCriNvOIy+w3M4HKJarXrzeVchn9tFqRSvkNdsuqJ/fs7nnR+5gZvN+ITdSTxxzteMvMSRFyXsGjmO1pQBQrhxczKYy277hDx3X2T59LmcufR42l/G/K8hP99PT5Tzec6glELgSIg864yjNScceQK/jjz2XdW0k99VTZO4d10xR54oyVzPV/LM+TN+RsDn9b/X63nzqyZhz/F+bCTwybY0rU2Kd9viyJt6Ip4d8Ym3/hvtpyDK6J/hc8rKK7B3vOMd+NM//VN897vfDWN/Ejji7t1XASBwIU9Op6Bk9BCFvAr29xcLef2+vfDxJLu7OggJrzBcqZQBALlcMbBtZrPufMCw5rcF7cgTCEFakkJz5NVqrpAnBejIAwBJy3rbTlifptGArK8r5LnvM2Jyz3Q6be6jNVkRcdMZeb1e9K6xctl1Qu/5FPJkgaCgyN55NQ6azQbEFWJMJVUHEN8xfNYx1ji/yHoaptmK5UaLdZau48iLo8OzVquAUmetVIF8fhftthnb7FBgQsibE9+bk8QTr4sbx1kerZnMyIsH5toko9lnRBAgp+KdtzkLVixdLuSJXEVrMiePMiO2mj0X57lkEWSq3M5bOcyL+fR7zqDU9zy9hM2Z5TghQnxzcZcx7xzDW3PALFxHngBJlLk6/51m/rxcXuvtVs/y5ldNIiRCXsIGeOtizrFtZ+LffJ67TzIZrcnveYXBztfsHoiIEvocN2NsyspVeMuy8O///u94/PHH8a53vQv//M//jIOD+W6mhO3l7t07IIKA1G5wAhMjvb+LO3eCF/IGgwGazcZSR94qyLKIQkH3nCFBwwrO2ez8z9md4WKiadTwwovXlxZncqNthVXMZq4iLSAhDwDSohBa3IbnyEsFd1wArsOvlkRrbkyz2YCSWU/IU0YF+jiKrJRSmGYLmczyWWiiKCCdVmNxXTGBXNPWn5GnaakT24qKcvkYeVmCukLs6r4sohxjXF/TaEJc4bOWtHjF6LOO6/hdTcRm55U4CvBedCLnN0wMdn3NZHIrvzeju+9pNOK7jo6FvNmihiIISEsiDIMPIW8crbn4ACFESIS8iGHnC2FibRx3/Pcs/At5fM0XYfce6kwhz0094D22j1dYzCf16xJMHHnxcGphwOdCgZ03NO20kMfTOWUW4xl5fLsHFzny3J/zd/3v9XpejOYkTMjjXeQ9y3B4uPiGV2fyNNvmyNs2xo0XI0eeJHHtqt6UlVdgv/mbv4l0Og1KKe7du4d/+qd/wmOPPYbHH38c//mf/8l550rCKty5exup3SIEMZj4xEnS+3toNhuBF7Xr9RooRaBCHgDs7emhuduq1TIURZt5Y8q4+eJ1mGYTvV4X3/v+f+Pmi9cXbpM58iqVcPa50+lAE0WIAVYaUwIJLXaw0ahDUrWZXWCbIKUy6Fld7m9KeKbX66FnWes78jKumykOIa/TaWM4tFEo+BMJCoVULGKNMYoITKX0tbeRGongURcky8cl7Pt04zH2VRmVSiWWzHxKKVotA9IqjjyNOfL4KvaeFZpG0xPm/CLr7nc6TnF1W26q63V3jmVGX32esj4S8uKcNdtsNiESsjBhIC+JaMY4d3MS39GaZHvmhpwV2D3N5LxfOa2h1eIrNpkVS1V18ZpYVWWuCqss0WCWI09VUqPX8CjkzTqZU64K7eLo/Ecdf8VFSh2IIdQHEpYwcczwc/ScZtwsMB2tKXMtjgHudZMQAllWOb+/n6/k8SnvAj3LgiCfTrERJDZPlufP+2zD0/XIL2yft0WsOTkjj38hj1LHE4vcuZt8HyP9fh+CKHknQCLKGA4GZ/ZeaGUh7y//8i/xxBNP4FOf+hTe9ra3AXAveN/97nfxx3/8x3jHO96BP//zP8f164uFhgS+sW0bB/fuIr2/F8r20+fcuM6gXXnMNRe8kJdBtRqOu61cPkYuW1g4NPzewSsLH08jSTL0dBaVynEg+zhNp9NGKkA3HuA68johuX0ajRpELdhjAnCFPHf79cC3fb/ABLhVC+0MeeS0iUPIYzOTikV/+14opGLZz1bL3c/0Bo5UJgJGKeQ5joNK5Xh1IU+RMLSHsXwvO502HNv2xDk/CLIKIoiJIy8EbNuG2TLWitYE4hHyFq0FFhHXPXi9XoMoSms5fpn4x8TAOGg2G8jKEoQFn3teEtBs8nGd925IlxwnriPvbN688kqr1YIoyyf+Nnw68txiqT9HHj9Fd+a2U9UZQp6qnXgN//BVamdzB30LebY9c1ZhQoRQfp3742aB7YrWdBzHm/+oyCrXwtLiGXmEO2HGcRzXkSerp34myomjOm62eb24nUIe/y5Ct6nB/TchBJRzQWwwGAl5I9i/B4NBXLsUKmtV4jVNw/vf/3584QtfwDe/+U185CMfweXLl0EphWEY+NKXvoQPfehDeM973oPPf/7zyQypLeTOndsYDPrIXNgPZfvpvR0IooiXXroZ6HZZoWVnZ/0IuVns7KTR6XRCORHUalVkMoWFrxkOBwsfzyKTKYTmIux2O0iLwd49pEQhtE7aeqMOKQQhTx5tM84i5LbDhC3mrFsVQRQhp1NoxOCWYPteKPgV8tKxCHmGYYAQstGMPCYCRukaMwwD/cEA+8pqxSL2ejZfL0rY33cVIY8QAlnTuZnBdZYwzRYopWsLeXE2aaxehKFri4CbUK/XkNFza/1uRVEhy0qsjrxGo478ksakvCRx07Azjl5d5sgj3HfPnjUMo+k1FzFkPYV22+Sq+7rbdYvTqdTia2sqJcOy+Jk51+l0PKfMNMylF8cc4mVMFsMYAmeOWWmUWEJ9HqfUGSZCXoTMO9/Hcc33A6uXyFOzZ2VZ5DoGjzU5EEGArKhcnf+mGc/CPf0zGtN6cBHuZ0shSqcdeUSUAEK4nXF6P8DTGsUv7BDv97dDqNm2aE3HoScdeZyLvf1+3z2XjCCekLcdQu+qbGypuXz5Mj760Y/im9/8Jr7whS/gve99LzRNA6UUN2/exN/8zd/g0UcfxR/8wR/gv//7v7latCbM54UXboAQgszli6FsX5AkZC6dx3PPPxtox1Cz2YQgEF8zq1Yhnw+nO9+2bRhGE5nM6pFUy8hkcqEVnjrtNtIrzKzygzsjL/gFHKUUzUYD0gaxgvNIHHmbU6+7Llolu77QqmR0bztRwmYm5fP+ozXDaghYRKtlIJXSIWzwnVXVFAghkToLyuUSAGB/iWtgGvZ69v4oYecCaUX3o5jSk/NICLAmCyW72vlfVBSIihxLgwBvxZdlNJsNL3p3VQghSKezsYrYtWoFO8riiLgdRYLV63ER28du/smS+VSECHB8umsSgqFWr0KeOtcomYy7DuWoUYMVp9Pp0wXVSdJpBcOhzU03c6tlQNPSM8+R4zUKXzGmADAc2pCm9lkkhKuO/LGQ52+fEkceD/DbqMHEullCnuNQbovYrA5BRo684XDIzflvGklyP1t7xnEwpOAu+pZ9trOiNQkhkGS+hdOzznDI53dyEUxX2BahxradiX/z/3m70ZqjeXMEoJw3B7qOvPG6hDnyzurot0Ar8W9729vw6U9/Gt/5znfwF3/xF3jTm94ESimGwyG+9a1v4SMf+QgeffRR/O3f/i1u3w42UjEhWJ5/4Qb08/uQ1MU3eZuQu3IZjXotUNeYYTSRz6chCMEWwtgMrKCFvGazAUopMqM5MUGi6zmYZiuUBWgY0ZopUcDQHgZ+su10OhgOB5A3iBWch6imQAQxKcBvQL1eczusFAY8AAAgAElEQVQf0+u7xZRsBrUYHB2scSCb9dc4wJx7URf0DKOJ1AoOsVkIgoBUKlrXWKl0CAA4v2SOzzRpUURWlnB0dBjGbi2ECUdyKrvS+6RUNpZj+KzDnF6rNgoQQqBkMrE0CDBWdVM5Tjwd2KbZ2mz+ppYOfF6yX/r9HlpmC7tLCtI7snszWKuFk3KwCt7N/5LGDCIIW1EoOEvU6zUomZPnGtZEEKfrdBpWUPXjyAPATXHVMJpzmwYEQUBK07mMqLbt4amZ4hIBbI6cSUyU8yv+U8f2xL+E8JkpyjiUO7GGsUjIc3/OpzjGznUCIVAU9cRzvCEIIyFvRkO8Tfk7NsZC3mlHNXueh2ap+xWeGkv8wqK/eYoAX8T2OfIcL7pXANk6Rx4T9bZF6F2VYCvxI3Rdx6OPPopHH30Ue3t7bqYqdYc6VyoVfPazn8Wv/uqv4o/+6I9wcHAQxi4kbIBhNFE6OkT2yqVQfw/b/gsv3Ahsm81mA/l8sG48YOy4YTOxgoLd2OshCHls9kwYIpMbrRm8I49tO0hY3GoY0ZpJJN7muIUvfaMCtJLRYTQbkS+KqtUKdnczvhsH9vbcgh6b5RkVtVotkHOMng7P5TuLo6NDZGUJ6TVuRs8rEkoxCHmNRg2CJM/sOF2EnMqgHVLjxf1MozES8vTVhSY5q8dSfBcEAYIgnOjc9INtOxDF1dyrm0IpdYW8NebjMTRNj81Fw6L/d5fM4WQ/DyuufBVYB7IfR96qx1DC+lhWF1a3CzV3cq2pZlkEOz9CnmV1oSiS5+iYRyrlXsd4mVtkGAbSC5oGUilehbw5jjyOhDxFcf/W/h15Q+89CeHDRJnJFCPqONyJNQwm1EnSyesUe8xrvGa77UbzCoLojSNgz/EG+9vP6vlyOHTksdhjUZldp3OFPD4/6/sBXr+T8xgOx83/23LcTCYTbkNihtuE5P5bIPyLj6ejNUXv+bNIoJX4fr+Pr3/96/jwhz+Md77znfiHf/gHVCoVUEpx7do1fOxjH8O73/1uSJIEx3HwX//1X/jABz6Al19+OcjdSNiQF154DoDrmAsTNZuBVsjj+eeDE/IMo+F7XtUqjB15wQo27MY+LEee+zuCFQ0cx4HV6yEVdLSmEJaQN5pZFUK0JgCIiZC3EbVabeXYu2mUbDzRVdVqGfv7/gXi/f3s6H3RFYMdx0GzWQ/kHKPruUhFyNLRIc4vKbDP47wqo1wuRb7orNfrkFPZlYVpFsWZnEuCpV6vQ06nICwpWM9CyeioN+qBxn/7RZJEDIeriTDDoQNJilbIsywLtm1D28Dxq2lptNutWD5n5rDbWXKeKcoSCPgQ8nxHawpJtGaUzHP/ynoaRCCRN/AsotvtQtOWu6nGQh4fjpRFjjwASKUykc7x9ctwOC6GMURCuCqcMlHOsf01Ezn2wHMsJYTPrCYdV8iL9prvF9aUNt0swBx5gwE/x/4kLB1AEARoowaldtuMc5fmwoS64ZY48tjnOE/IExUNJqei6f3AtjnyJsW7bRHyJj/jbYgyHfT6UEb1WUUQMBgMYrlX80t/MC3kuevcsyrkBXL1v379Or7yla/g61//ureAppQilUrh3e9+Nz74wQ/izW9+s/f6er2OL3zhC/jsZz8LwzDw93//9/jHf/zHIHYlIQCee+5ZKBkdWjH4uW3TZK9cwq1nX4BlWdC0zZx0lFIYhoF8fjegvRujqjI0TQ6807PRqHszYoIm4wl5wTpovNkaIURrAgg8VoHNOArDkeduV0e9UQ5l2/cD9XoN6aubuX+ViY73nZ3gv/+zoJSiVqvida+76vs9mYwKVZUjLQa3WgZs24YewBzOTCaPV28/D9u2Q79BtG0b5XIJD+XXa8w4r8oY2jZqtSr2988FvHfzqdaqENeI8WVRnPV6DXt7+0Hv1n1LvV6FkllPZFKyGQz6fXQ6HehrOPo2QRSlld1Uw6G91GETNKzopW3gyEtpaQwGA/T7Pahq8IkKi2DnYhadOQ9ZIMjJEhdijN9oTZAkWjNKxkLeyXMFEYTRHF9+HHndbhu6vtxNxV7DQ9xZv9+HZXWRXijk6ahU70W4V/6w7eGpgotECIYcFU6ZKEd9iIuUUtjDQeLIixBvzT3pyLP5deS59wnCqcQSb64bR8f+JGMhT/TWNXFFfy+D/e3tGXV1m/J3bHiOPHmOI0/R0IlhLnWCCxPXeRZqJtlOIW+7HHn9fg/y6BwuCwQUbmMSr/Nx+/0+BCnjNSSxGXlnNe1obSGvWq3ia1/7Gr785S/jpZdeAjD+4r/xjW/EBz/4QfzGb/wGMpnTC+5isYiPf/zj2NnZwV/91V/hhz/84bq7kRAw3W4XN28+h+LrH45k1krh2hWUn7mBGzd+gp//+f93o231ehYGg4HnnguafD6FVivYTs9ms4FUSocQsLsNgDcQPmjxkd3QhzEjDwi+87fZbIAI4twOsE2RUjoahy/DcZxQ/o5nGcvqotvtoLDi/KpplFGUVa1WxWtf+0gQu7YU02yh3++v5MgjhGBvLxPpnCVWeA7CkZfRc6CUotGoY3d3b+PtLaJWq2Jo2yvPx2NcGL2vVDqMTMhzHAe1WgXZB16/8nvl0d+nWi3jkUd+Kuhdu2+pVitQzhXXei+LxKvVKjEIees58qLuzh8Leeuvu8bFMjMGIa+KtCT6Ws/syCKqlfibdtgNqbDkb01E8czevPJIZXRsqLnT11oll/V+zgPtdhuZzHI3FXsND0Uyli6Sycxfy2QyeViWhW63g1Qq+HSWdRkMBqeiNSXCV5TZKo486tgApYmQFyHjaM3xc9SxvTlpvGHbQ4gzrqvsOX6FPNc1RgiBpqZPPMcbLIFhekYepRRDh3Ln1my32wAhc0cPiIoGo9MGpfHMe77f6ffZnLnt+OxZ5G2xmOZijeKHbZuR1x/0IUvu8aCMvpP9fp9fIa/XB1EnZ+S5/x4f22eLlc/w3/jGN/DlL38Z3/nOd2Dbtife5fN5vOc978EHP/hBvP71/opYv/ALvwDAvZFO4INnn30Gtm2j+Nprkfy+9Lk9qNkMfnT9hxsLecwNmsuFJeRpgUe2uDEx4RQIBUEIZV4Ei74MT8gLPlpTTm02g20RkpYBpQ5aLQP5fCGU33FW8Qpf+c1EJkVPQxBFVKvRFcrYvu/tream3d/P4M6d6PZzHN8bgCPPc/nWQhfySiV3vt26Qt6+4kbhHR0d4o1v/NkA92w+hmHAHg4hp1c/nkUlBUGK1q151hkMBjCMJi487N81O4mad7/blUoFV66st411kSRppdgV23ZAKY08WpM19rBZMuvA3tvptEM/r0xTqRxjb4kbj7GnSPhx5Tj2IhMb2k6WCXmCdGYHvPNIuXwMOZ2CqJy+Zqn5HMov8NPw1emY2NlZ/p3VdX6EPFYryGbmr7PZz6rVCh544DWR7Jcf+j0LukDQnxhmpQoC+n0rxr06iSiKEEUJztCHkDcqRiZCXnSMr+3jY8ixHcg+r19Rwxx504yFPD6L2KbZ8sRRRVEhCAK3jjx2TExHazpwjxJJ4qvYbpomJEWbu34SFQ2OY8OyLKRS4dTyEuazbfGDLKr1/PkcXnqpGvva3A937tzx/s3rOXCSwWDsvGfOvH6/F3lzq1/6gz60ifMekZiQt13Htl9Wvvp/7GMfAyHE+7K8/e1vx2/91m/hV37lV1Ze0Klqkq3OG9evPwU1l0V6P5p4OkII8g+9Bi9dv4F224Sur+/MYW65fD6cju5cLoXj42BFMcNoIp0KPlaTEYaQxwp3QUdrsu0FPVS62WxCVMO74EgjN4FhNBMhb0UqFVe00DYU8oggQI24450JLqs48gDg3LkMrl+/i+FwGEnRvVqtgBDizczchGx2XCR7+OHXbby9RZRKRyAAzq05I08WBOyqMo6PS8Hu2AKYkCyv8VkTQiCnc953ImFzmPOVCXKromQzACGRNggwJEnCYODfkcdEv+iFPPd6rW0k5GknthUllXIJr/N5jtlXZHQbbXQ67Y3WqpviOfKWODGIKJ3Zm1ceKZeP5zYlaYUchoMBDMNAoRD/OrHT6SDjI25bUURIkhj4unwd2HmYrUNmMblG4UnI6/V6KE4JeYpAMLTtSKLK/SIriifSLYKJfcmMvOjwru10UsizI7/m+2Ve1LckCaOf8+nIM4ymd20lhIzmbgZbRwkKJtQNnJNCHnvMm8jbbpsQlflrRWn0s3bbTIS8GOj13MYSiu2I1mTfy6tXd/Dcc0ewrC5XTvxZHBxsj5BHKXWFPMG9zrNZeTw3CA4GfaTESUee7D1/FlmrEn/u3Dn8/u//Pr7xjW/g85//PH791399ra6sy5cv41vf+ha++c1vrrMbCQHTahl4+eUXUXjoaqQdDcXXXgOlFD/+8Y822s5YyAs3WjPI7GjDMBYObt+UdAgLUFZsSwd846kIAmSBoNsNWMgzGp7YFgaS5oqEzWaS674qlcoxQIgXjbkJSj6LcoRC3vHxEWRZxM7OaiLx+fN5OA6NTByoVivQ9VwghaJUKgNRlCJxjR0fH2FHlSFv4F44J0s4PjoIcK8Wwz6XdYQ8AK6QF4NodFZhfw81t56QJ4gi1Iwei0tSkuSVHHlM9Iu6A5utB5QFxZllqF7xJlqxoNvtwGy3se9TyNsbva5cPg5zt5bi25EnSkm0ZkRQSlGuHEMtzD73q3lXNKtU4j12ADcCutvteG67RRBCkMmoXud7nFSrVahqCsqCmPzsSJzkzdne61lQp9Yy7HGvx0/kk6IocPwIeaP4zaQhOzrYtX2yBOEKeXy5rhi2PfREu0nYc7wWsRuN+on7pXQ6i0ajHuMezYfF20078thj3uLvTLMFYcH5m41A4TXK9KzDGr+GW7JubDTq0DQZly4VvMe8M1lD5vUcyBgMBnAo9dYq6siRx9OaZRLbtuHY9omxA+w+qddLhDwAwGc+8xl8+9vfxsc//nFcuXJlo18uiiIuX76My5cvb7SdhGD48Y+vg1IaWawmI7VTRKpYwI9+9NRG22FCXi4XliNPg207gQ197/d76PWshYPbN8XtJAs2DpTd0OsBO/IAIC1KgRbzHMeNvBS1MB157raD/pzvB6rVCtSsDmGOyEQpxaDTgdVoonLjhYUiuprPol6rRrYwKpWOcP587tQg92VcuOAW+qJyilWr5YUd7KtACEEuW4hEhCwdHeL8ht2k51UZ1XotsmJ2tVoGEURI2nrndFnPoVGvc9upvG14Qt6ajjxgNNsqBnFVlmUMBv7PZUz0i7pw0+m0IUnyRq6AyWjNKGEO7v0ZUYizYK+LW8hjxZZlQp4gSuid0bkQvNFum+hZ1tx0AW0k8MV97ADu94xS+BLyAEDXFU6iNcueUDcPUZSgp7McCnk9rwjGGBfF+InXVBXVX7TmMInWjJppRx51HCCGOG2/zIvW5NmR5ziOm+IzcU+qcyzksb/9YOremD3mTeRtmS2IC9Ib2M/abT6jTM86bI4Yr0LNNI1GA8ViGsVievSYz+/pJJN1LMfhW8gbGzeEE//Lw3pwFuy4ZS48ACCCCEKEMzsjb+VK/COPPIKjo6OViqWO4+Dg4AAHB9F1xiesztM/+iFSO0Voxc1nKa1K4bVXcfv2LW+e0zoYRhOqKkNdc6bSMpjTLyiHW6vlLlTCmpHHtt3rWYHGK3U6HYiEnLopDYK0SAK9QHQ6bbdjMUQhT5BVEEGEYSSOvFUpl4+hLHDLVG/cRN8wYVs93H3ie6jeuDn3tWo+B8dxNjqHrEK5XPJEuVU4dy4LQghKpaMQ9uoklFJUqxXkMsXAtpnJFEKPfxwMBqjWqji34bn8vCq7TomIiqfHx8dQMoW1He1KpghKHe6KkNtKpVKGnNIgblBsVPNuZG+QTnw/SJKMfn8VR1480ZrtdtuLxlwXWVYgCELkjjx2XthX/X1meVmELJDYXVWW1QUAiPJiIUaQFVjdbhS7dN/DGnPUwuz7JymlQVIUlMvRRT3Pg33PMhl/Qh4vjrzj4xLyueVjH3K5nUjWV35xHAf9wWA7HHmqCmovF/KYIy+J1oyOsSjjrkUcO55rvl+GwwFkeZaQJ45+zp+QZ5otOI4NURh/prqec+dfc+ie8Rx5U9Ga7DFvQl6n3fZcd7NgsZu8ziQ867D6m2V14Tj+o/3jotmsTQl521CH2x5H3vQoJZbExkPU+ixYU5QwOSOPEAiSzFXDVJCsLOS9853vxGOPPYZXXnnF93vu3r3rvS+BT8rlY9y7exvFhx+M5fczF+DTT/9g7W00GnXs7IQXoRh0x4cn5IUoMrFtB7koarfbSEtiKPGruigEWjBgoqukhndcEEIgazqaTT4z9HnFtm2UyyVoxflusebtewsfT5IabSeKAk6324VhGGsJebIsYm8vE4kjzzRb6Pf7gTnyAHcGTb0ervORCSfnNxTymBB4fBxNUa90fARZX/+zVjLue3ko9p4FyuVjKBu48QC3QWDQ73uO/6iQZRnDof8baSbkRe3IM80WtA2vr4QQaFo6crGgXD6GSAgKPp2/AiHYU+TYXVWdTgdEEJY68kRZhWVZkYvQ9yPsGpOa0whJCIFazHMhMLHvWTbrT4DnQcgzzRbabRP5wnIhr5DfRbl8zE2RjDVSnnLkiUzI46fApPqO1kwceVHDBDB2Pqe2uz4Ql1wH4sKdA75oRh5/8X2svjOZEpPRs6DUiXwN6AdvRt7caE1+jo1+v4fBoO/NwZsFE/l4FQrOOpOJY6xhjGeYIy+TUSFJ4pY48uDVT1cZnxAH06OUmKDX7QaTTBc0zHVHphoYXCGPn4apIFkrG2/dm8LkZpJfnnrq+yCEoPjwtVh+v5LNIHPxPJ566vtrHyeNRi1UIY/NwgrqQmGa7qJQC3EwqzaaDRekkNfpmN7JPGjSooB2gNnonpAXolgKAIKa5nYYNq9UKm6hJbU73y3mTHVsTj+eRCvmAUJweDhf7AsKJrRcvLiee/nChVwk4lKtVgUAZJbEUa1CNlOA4zihHu+s2LmpI29XkSASglLpMIjdWkiv14PRbHhi3DrIuvt34qHYexYoV46h5Tc79lkkXiXC+ZuA22W/WrRmPEU90zS9dcYmqGo68i7sSvkYu4oMcYWmpD1ZQjmixoB5dLtdiLK6tJlKkFVQ6pzZG1ieKJWOIKkKpPT8IqU2EvLivhdmopx/R54We2GVXRML+b2lry0U9mDbQ2/9Ezes6JWaum9KjYQ9nopiiqKA+hDy2GtkORHyosK7to9OH9Rhc3H5EWsmcYW807UCWWaOPP6K2LWam+gyuY7SR+tyXs4nk7C/vT1HyOPp2GBz7xZFaxJBgKRoiSMvJtoTiVhBjREKi06ng263i91dHYQQ7O7qqNX4T7OhlIIQAkIIbB/X2jiZjtbUBAIB/B4bXrTmDCEvidbcAGbPFYRIfl3CijiOg6ee/gGyD1yEvOAmNGx2HnkItVoVt2/fWuv99XodxWJ4gk0mo0KWRTQawUT3sYVKEEWwebDYzkAdeaaJdAixmkDwjjzmely0cAwCSUvB4LBbj2cOD92o5UVC3ioIkgStkPO2GyasqLSOIw8ALl7MoVarhD67jcWMBinksW2FGWFaLpcgwBXiNkEkBLsROWiYuLuJkCeIEpR0LnHkBUCn00G304E6Z2aVX9j7o45TFEUJtu3fkTcW8mbPGw2Ldtvc2JEHAJqW8go9UVE+PsK+strnta9KaDQakc3dnEW321kaqwmMozd5EgrOKqXSEdRifqG4qhULsKxu7M6OdaI1+/1+oBH9qzIW8vw48vZG7wm/gccP43iqk+ca9pinopgs+xPyWLRmIuRFx/jazhx59tTzfDE/WpNfR161WgYh5MRnmhslmkTdzOUH5sgbzhXy+InWZLWdRdGa7OdxO8DvVzqdjteMxOscNAa7Jzt3Ljf63yyX39Fp3EYuAkEQt0DIOxmtSQhBSpK4PTZmzcgDACLKsCx+kg+CJBJl7fDQXUxnMpkofl3Cirz88otoGc3YYjUZ+QevQJAkPPXU91d+r2V1YVlWqI48QgiKRT1AR57pxu0siBnYlDCiNVstA9kZcRlBkJFE9AeDwAoGrGAihSzkiWoaZivpIFuFw8MDCKIIbcNC+ySpnWIkjrxS6RCqKnsu3VW5eLEAxwl/dpvnyNOD+4zZtsLsTq1UyiiqMqQA4nv3ZBGVCIQ8FpWqZDcTpuVMAUdHiSNvU9hNnlrYLFpT1tMQJCnyG0RBEGDb/p07th29kEcpRbttQtU2v75qETvyhsMhavUa9pTVCl37igwKt+AXF+1OG2QFIY/Xm+6zAqUUpdLRwphwAN7P43Zct9smCAF03Z8Ik82q3vviolQ6gqqmfDU+5nI7IITg6IgXIc/9/k078lhxjKfvpyvkLRdY6DCJ1owadm2nU448foW8edGazJHHn5BXqZSh6zkQjO890uksRFGK9Zo/D++znDsjjx9H3ljIW7xeJIqGVsRNXQnuOqbTaUPNufdMPF2XZsHuyc6dy3r/W6tVuInUngdz5ImiyOWc0EnabRMEJ9cuQRsugoTFwQpT90eCrKC7BVGx67BUyDs4ODjxH6NcLp/62fR/r776Kr7zne/g7/7u70AIwcMPPxzq/5mE9Xjqqe9DVBTkr16JdT9EWUb+2hVcf+bplbudmbi2bmHdLzs76cCcKK1WC5qaCtWpqo4ErFaAIlO7bSITUrQm225QBb1Wy4CkaiBCuDc6kprGYNDnatYF7xwe3oNWzIMEePyndoswjGboC9CjowNcvJib2X1PKUWz2UWpZOCJJ16cGaN16VLe206Y1Os1pFOZQOP20uksCCGhOvIq5RL2AmoW2FMl1Oq10Bf3R0cHEEQJcnq2cEQpxdDqoG820Lx9Y268mpLdQbUavlvzrMNu8jZtFCCEQM1nUS5HW8QRRXGlYfPj5IvoinrttgnHcZBObd6kl0rpME1zpf/Pm1CrVeFQiv0VXb/s9XHOyTOaDUg+BA1x1MiVxH6Hi2E00etZ3pzeeaR2WHRyvAJTp9NGKqX6vvfQdSYIx+ccOzo6QLGw52s2tyRJyGWL3Ah5zBE7PZJAFQgEQtDt8lNgUvzOyHMSIS9qxt9Xd+3ocC7k9ft9KDOur+w5Hte4lcrxqZnihBDksoXI14B+GDvyTj7PHvMl5Ln35UsdeXLiyIuDXs+CPRx6KUlB1g3DoFIpQxDcSE0A2N/PwLYd7ufkUeqMhDyJy3PgJK2WAV2STowfyIoELYPPBDK2lhKnkgIESTmzjrylZ/h3vetdp56jlOJ3fud3Vv5l733ve1d+T0K49Ps9/OTZZ1B46CqEkFxWq7DzyEOov/gKnn/+WbzxjT/r+33MHRK2kLe7q+PWrXteR8UmmKYBLezZbYIwiqwK5oLc6/XQHwyQlcJxPjKnn2m2sLOzPEJnGa1WC6ISnkuTIY2ixVqtFlR18SI1wb0BPTi4h/TVS4Fuly1A7927i0ce+alAt82glOLo6BBvetPsfX/iiZdQqbg3If/2bz8EpcA73nGyiWVvLwNJEkMv6NXrNegBuvEA95yi67nQHHmO46BareLh/PyuTUopjKGNnuPgybqJtxT0uefjPUWG4zio12vY29sPZZ8B12GqZIogZHZx1Lj9HIYdd/Fb/sn/BSiQv/rTp16nZndAqYPj4xIuX34gtP0961QqZRCBQMluLjKp+Vzk0Zpu7Ip/UYu598SQmmxm0Wy6AlE6vflnnE5n4Tg22m0T2Wyw56xZMCFuf8U5nLuKBIL4hDxKKQzDQObKxaWvZbOB2d8pIRxYQ462s1jIkzQNcjoVu8DUbpu+YzWBcQRnXMVV27ZRKh3ikdf+P77fUyjsRZLO4IfpeCoGIQQpUeTK+SDLsi8hj9rDUxGECeFCCHHFPObIs6Nv3lmFwaAPRTld42Az8uKM6p0FpRSVSgUPPfgG1OsnRbtsthj5GtAPgiCAELIgWpMfIY81NCyLBRcVFV0O3Y9nHSbcjYU8PsUaRqVSxu5uxrvnYRGb7vPLZ+nGBaUUBNsh5JlmC5mpOacZScSrnB4bixx5VoOfhqkgWXrHTyk98d+85xf9pygKfvu3fxsf+tCHQv0/k7A6zz9/A8PBAIXXXot7VwAAmYvnIKdSuH796ZXeVyq5sWbnz28Wo7WM8+dzsCwrkAucaZrQAoikWoYbWRXMDTgTBDMhRmtO/p5NMVpG6PPxADdaE+B/4cMLx8dHsKwuMhfOBbrd9L7bsX3r1suBbncSw2jCsixcujS7aPeTnxwsfAy4xfYLF3KhF/QMwwikyD5NKpUJ7VhvNhsY2kPsLXDKPNloozYYom07+N+lOp5szC+EMQdNmNGIlFIcHh1Aye3MfU27fHvhYwbbRthuzbNOtVqGms0G4vhV81k0GvVIY1BEkf9ozWazAcAV4TZFH52n2DbDhglxi84zs5AFAYWI5m7OotvtYjgcQFKXN4GJigYiCIkjL2TYdTy1RMgDXLHvMOZze7vd9h2rCUw68uIRnKrVMobDIYpF/404xeI+ms0GF/Mh50VrAq64x5uQRx0HlC5uInHsISRZ3rihNWE1TjaK0dFzfP4N5jnyBIFAlkUMBnwJec1mA4NBH7kZ8fi53A7q9Rp3hXdCCERBnCvkBZnGsimdTgeECCBL5vaJsgbL6s5NLUkIB3ZPr2R0SJoWadT9OlQqx16sJjCO2OR9Tp7jUGBbHHlGE9mpdUtWEmGaLS6/n91uF0QQTqWwibIKy7K43OdNWXqG/+u//usTjz/5yU+CEII//MM/xPnz5+e+jxACRVGwv7+PN7zhDdD1cJ1HCevxzDNPQ06nkLkQnlNhFYggIP/gFTz/wg30epZvd1O5XEKxqENdsbt6VS5ccDs+jo9LyOXyG23LNFvYKS7vqt4UTQtu9own5IUWrRmskGe2WhCz4XfmiKPjlPeFDy8woRt9+LMAACAASURBVE0PWMgTFRmpvZ1QhTxWtLt4cfb3v9+3Fz5mXLqUnynyBUmnY2Jv9/LC11BK0emaGAz6eOHF63jktT+ztDCgqSm02+EIeWwRvqjA/rzZPfX4bcXZguWuJ+QdA3hDMDs5hWE0YXW7yGTnC3nTXe7zut7ldBaCKMXu2th2ypUylHwwjT1qLgdKKer1Gvb3gz1nbTNMdNMDEPKYGNhsNvFABEbUSuUYOVmCuobQuy+LqJRLIezVcpgoJ/lIcyCEQFLTiZAXMkdHh1CzGYg+YgZTO0WUf/zcaH5UPEXWTsfE+fPrOPLiEZwOD911UrGwgpA3eu3h4QEeeijesR7ttomUJJ6Ip2LoAgms0TIIWFQmtW0Qaf65kdo25CUF+YTgObE2pzOe44jBYABFmd1YJMv8FbFZQkqhsIdXb79w4meF/C4odeeaX7q0+J4qagSBnCpQs4dhjm5ZlU6nDVFRlx6vgqLCcRz0elYkze4JLkzIk1MpyGmN68Z027ZRrZbxxjc+4j2XyajQdRXlmNbmfnET3YTRjDy+zoHTtFoGzkmnhbyhbcOyLKRSfH0/O50ORFk7dY4RZBWUns1zytK7iA984AMnHn/yk58EADz22GORzrzrdrv43ve+h2effRbPPvssbty4gTt37oBSig984AP41Kc+tXQbg8EA//qv/4r/+I//wCuvvILBYICLFy/il3/5l/HhD38YOzvzi3BBvJ83LMvC88/fQPGnHg50TtWmFB66isqzL+DGjWfxcz/3Jl/vOT4+xMWL4ccxseL98XEJDz/8urW3QymFaZq4dDH82EdNS6PRDKZDhV3Yw3Lk6ZIAAtdJtCmUUjemazf82Y/SaHgzTzfkPPPKKy9DyehQA4i9m0a/cA53n30Bg8EAshx8oYE5pdicu3W5dKmAJ5+85UYXZIJ3EtujhZa2xJF688XrME230Pu97/83QCle98jiWGNVTaFaC0doqlYrANxIzHn0pwa7Tz+eJC2KSEuit90wYIVGdYGQ5xdCBCjZHW5iwbYRN561gp2ffmT5i32g5sednlEJeZRSCIL/Ah17bVQz5gBXyBME0ZvFuwlszl5UjrxqtYxdeb11zK4i4Va1EkjE+qqw+R9+hDzAnZMX5jzTBODg8B5UH248wHXtOY6DSuUYFy4EGy3uF9eR5/88lkrJEAQSW7Tm4eEBBEFELnfaKTMP5t47OopfyDPNltekOE1GEnDEUcGUzdyi9hBYINRRx3XkJUTMpI5HmSMvpn1ZgOM4GA6HXozmNKoqcReteXR0BMAV7aYp5N2G4FLpkEMhT8D0qs8Zqbw8CXndbmdprCYwjt7sdDpnrujOM6y+J6VTkFKpQOpwYVGv12DbDs6fP1n3PXcuuwVCngNBECFLCnq9Xty7MxfHcWC228gWTt5rMCNHq2VwKOSZM2dwsufa7faZO6es3A74xS9+EQDwQBQtsxNcv34dv/u7v7v2+1utFh5//HE888wzANz4CFmW8fLLL+Pll1/GV77yFXzuc5/D61//+lDezyPPPfcT2LaNwkOviXtXTqCf34eip/HMM0/7EvJs20a5XMYb3hD+zRrr+Dg+PtpoO72eBdseIqVFI+SZ91qBFJ1YZ3d+zQLYMkRCkJGlQBYQ7DOOIlpTUDSAkMSR5wNKKV659RL0i+G4gDMXzqH8zA3cvXsbDz742sC3f3R0iGJRRyrlP5pqFkwIPDw8CGWeH4trWlZkv3fwyqnHy4Q8TU2h2+3AcZzAbxQbjRokgQTq+i1KIhohFrOZ6KYuiNZcBSW3g4PDV0L5fO8HDKMJeziEmgvIkZdnsxeOAfyvQLa5DMdxVrpes9dGGR1Sr9eQ0XOBiFmqmoIkyZGJTrVqBT8tr+eI2pEl9AfmaNZYuHHu07A5PbLur5FE1vMoV5KY3rAYDAaoVSs4d+WNvl6vjebPHB4exiLkUUrR6XRWitYkhCCdVr1Zb1FzdHSAfH53pVlgKU2HpqW5cLabrRYy4uxzZFYS8WJMAuksWPOb4wyx6NN27CG0RMiLHAIytltNPMsbTKTTtNnHiKJI6Pf5KmKXSofQ01koMwrB2WwBohj+XPN1EAQB072MDoeOPMuyQKTl1x1h9BqeRY6ziGE0IUgSREWGrKfQPOQ3opJF208LeRcu5PCjH21Wnw0bx3EgSwJkWUGvx+/ctm63C8dxThk3JkcgnTs3P5kxDkzTPDUfD5gU8kyu5yeuw8pn+Le+9a1461vfCk3zF3kYJPl8Hm9729vw+OOP49Of/jRe9zr/jqg/+ZM/wTPPPIN0Oo1Pf/rTePrpp/HUU0/hS1/6Eq5du4ZarYbf+73fm+uo2fT9PPLMM09DyejQz/MRq8kghCD/4Gtw8+ZzvuYb1GpV2LaNCxc2c8j43bcLF3IbC3lsqKzms6t6E1KajuFwEMiiyDCakAhBKsTFYU4U0DI278pn38VZ3RlBQwiBpGhb9f2Pi0qljE67jcyFcBYA+igm+JVXXgpl+0dHB7h8efNzzeXLbgd/WDeGrHt+mZA3He3gJ+pBVVOglKLbDX4RWq/XUZClQJ0uBVkMVSC4d+8uFD3v3YBuipbbQ7/XS5w0a8Lcl2pA0ZqSqkDSVNRq1UC25wfHoRDnFH9nEYcjr1qtIJMJZt1FCEE2kw/VOcuwrC7anY4Xu7sq47je8Pd1mnK5DEnRICr+ohEVPY9O2wzlXJ3gXr8ppb7m4wGAls9BEEUcHcXjuO71LDiO482984uuK+h244nWPDo6RHGGS2YZhfweF7NmzZYx15GniyKsXo+bmMGxI292JDwjidaMh1nrYh4deUykmzUjDwBUVeTOkVcqHSI/5zwjCAJyuR0uGgOmEQQBNk4qeWNHXnQzk5dh9XpL5+MBgDB6Ta9nhb1LCRM0m00oehqEEMh6Gm3ThL3kOhAXrKFtckYee9zpdGKLAfeD4zggAoEkKbAsfsVq03QNFdkpIY89ZnVsnmh32gsdeTzNIw4Kflo1lvDmN78ZTz75JL74xS/iE5/4BN73vvchk/EXy/bd734X3/72twEAf/Znf4b3ve993myCn//5n8dnPvMZKIqCUqmEz33uc4G/n0cGgwFefPEmclcf4DJfvfDga+A4Dl588YWlr2VuiE2j7vxy6VIeR0eHGxXMmLMtlYpAyBtFVgWRd91sNpELuMg+TU4SA4nXYu44FnsZNqKSQrvN34WNN27efA4AkLkUjpAnqSrSe7u4efP5wLc9GAxQqZRx6ZK/ot0idF1FPp/2YhmDhgn3io8ok1WRZdYxGfyNVqNeRTHg6N6iLKHRaITmVjo4uAslt3qhcR7qaFsHB3cD2+b9BBPcgozuVbKZiIU8e6XrbNRCHqUUtVo1MCEPADKZPGq18MWxatX9O24q5EWxr9NUKseQfLrxAFfIY+9LCJ6DA/f+I7Xnz41NBAHaTsF7X9QwV106vVrTSTqtxOLIa7dNmGYLhRXm4zEKhT0cH5cibW6Yhdk2kZkzb449z0uaB3PkUWeJkOfYoUTXJyzGoc4p5S5KF75f2P2Hps2+xmqaxJVQMxwOUS6XUSjMd2u4jQEcCnlkkSOPn/per2d5It0iEkdePBhGE5LupoTJeno0AoiP69I05XIZ2ax2ah3DHHrMsccbrGGHEAGKonLtyGPGhOm1C3vMY72z3V4crXkWzRZz72K/+tWvev9+//vfP/P5dZjc1iqIc7rZ/PCVr3wFgBsH+p73vOfUz69du4Zf+7Vfw9e+9jV89atfxUc/+tFA388jt2/fgm0Pkb18Me5dmUl6fxeiIuOll17Ez/zMzy187Z07r0JRJG9+XdhcvbqL//N/XkSpdISLF9eLxmGdDOlIhDx99DuNjef7GEYTuQUD0IMgJ4l4ZSR0bgJzJEURrQm48Zpn8SIRNM8++2OkioXAYu9mkbt6GXd+cB2tloFsNrjZmcfHR6CUBtY0cOlSLrSOcVa8CkN0J8Q9B4RRQKjXa7ikBivkFWQRQ3sI02wFejwA7nnGMJrYvRRcPKqSLYIIAg4O7i69/iWcplargggCZD246Goll4nELcZwY1X5FfI6nTb6/R6ymc2bGhiZTAEHh7dCj5RlAtzOmtGaBVmCAER6PDCOy8dQdvzP6JE9Ia+MK1euhrVb9y2Hh/cgqQqUjP+1fGq3iINbd2OZscg6ktdx5JXL0Xczs8L5ogL7PIqFPQyHQ1Srlchmm04zGAzQ6/eRyc++D5mMqSoWg4nm3gTWpOzYw4Wvc4W88EdDJJyEOo4XpElG18i4hepZMLedqs6P1jQMfoSacrkEx7G92ZqzKBb28cqtG6HNNV8XIgig9KTwzu7MeGrU71k9CPnl68XEkRcPzWYD8nm3iVQZ3TsZRhN5H3+zqKnXq9jddddcTz55CwDw1rde856r12u4du3BuHZvLuyYJkSAPHLkxbEO9AOrU0+nCaQEASIh3DnyBoMBepYFXT29LpEU9zne9jkI5t7FfuITnwAhBISQE+Ibe34dprcVFU888QQA4Bd/8RfnFgd+6Zd+CV/72tdw9+5d3Lp1C9euXQvs/Tzy0ks3QQQBmQvx3NwsgwgC9Avn8OJLyx15d+68iitXihADnKm0iGvXdr3fu76Qxxx5wTkG5sGEvCDmzhnNOq4E7JaZJieLsBom+v0eFJ/xUbPwhLwIHXlmux7J79pW2u02Xn31FZz72XDnTOWvPoCjH1zHc889i7e85e2BbZe551gs5qZculTA88+/gOFw6BVQgoKJbOEIeeGIBr1eD51uF4UAXT6A68gDgEajHriQx5wVaoCOPCKIUDJF3LuXOPLWoVarQs1mvEJXEKjZLI5fvg3btjdqLPNLv9+b280+C1Ywi6qLmbkTg3TkZTN52LaNZrMRalGbCXA7azryREJQUOTIhbx220S300b6iv/rj5zOgQjCxnHwCbO5d3AP2k5xpetsareI6nMvotGoRy7eMFfdKjPy/n/23ixGkuws/35ij4zIPbOW7q7ep5dZPGPjwYsG/5HNIH0YLrAQjORFBku+MbcICW64QdzADRfcgMwFCCHzRxgZLJtPYowx/QmPPTM9M71Ud3V3VWVVVmblvu8R8V1Enqg1l8g8sXR3/qSRXZUZkaezMiPOOc/7PK/5fAnb2+4L1yR6PBqdIVpzKP7t72c8E/JI+kpoxD3DbzFVUzvytMHCkecBuq5bUVqMB3Ha00I2rCVpVLQmj27XH5954GAeH4+Ovk4Qkc+pvuYzYxjWZ8HP9PpdyNzkORczfI7folefZXRdR71ew/LlNQCAoJjCR7Va8WUBWLlcxAsvmGuPn/50E4Ap5MXjqvW4HyER9yzDQJRkGIaOXq8LSXK/XdkkiOPueI88hmGg8pzv3JokdY6XTwp5DMeBF2Vr7/1ZYuwuh2EYp1bck9/P8p/bVCoV5PNmw85r166NfN7hxzY2Nqgd71cePd6AkjRdb34ldHYVlXJpbJ+gfr+PTCZtiWtukEioCAYl7Oxsz3yOer0GnhesiDonUSxH3nwXMF3XUavXEXZayBuev1qdb7xu9sgDAE6SLfFwwek8eHAPhmEgcnHN0deRY1FIoSDu379D9bzZbAaiyCORoCPAnzsXha7rjsRAHDjy6Bc4kEWjYdDdQKhUTCE8KtB35AFwpOccEdukMN0GylIkifTeri9jk/xOsVSAEKLrdhfDQRiGYX1GnabT6UCWp5+fBQLuVjGT/nDhEL1q3VAoBgCOR5iWy2WoPA9xDqE3yrOoVNztYWlda2z0C2NYFlIovigKcABN07C/n0EgEbN1XCBhinekLYCbzBqtqapmtKbb96NcLgdJkhGYoZ94OBQfnmOf9rCmhmwuhUfMacKWkOePDSZSUGZMcORB16kXny0Yj67r5vdvWDRA5vZ+7GN14MgbJeQJvhJqMpk98LyA0Jj5TCxKhDxvYpFHcdo1mRnzmFcMBgMwU/TsY4dC3jT92hfQodlswDAMK8VEUM0CeBoteWgzGAxQrVYt0e4wgsAhElF821+eiF8sy0EepoX5NcmrXq+DYxjILIP3q028Xz1IZAhyrG+FPO4URx75vR8/z/Mychb2n//5n7Z+71f29w8m8KurqyOfd/ixXO5gU3Xe4/1Iu91GZm8Xyx931hUzL8Gz5nv6+PEGXn/906c+J5NJQ9N0V4U8hmFw8WJiLiGvVqu60h8PAHheBM8LVmXorDSbZuNb2pvsxyHnr1TKc1XRmlnJElVXxjg4MYB+r4derwdRdF6gfRq5f/8ORFWZup/MrDAMg/DFNTy+v4Fut0Ot2imbTePMmQi1vgOk1142uzezu3cUliPPgUpNliGRPnQXidamF+VigfBww8mJSVw6vQNRjYCjXJQhRZKo7TxAqVREIkFXJHyWMQwD5VIJoasXqJ6XRAG79ffodtuIx6cX8oh7r9NxR8grFvNmZaaNfm2TIKJgoZDH1aujC+fmpVYtIzpnRHhU4LFRmb+Xrx1Iz0y7RQNiOIH03rZvI3yeVvL5HLTBwBLmpiUQj4JhGOztpfHSSx9zaHSn024TR569tAtFEaFpGvr93lxJGXYpFHKWwG8XnuehqmEUCnnKo5oey5E3Yk6jcixY0ElMoQHPE0fe+CItQ9es5y5wB6s4b/izv6M1zWSAcY488hw/kNlLIxpNjr0/SpIMVQ071td8VgwYGDVqv+h4hmFAGwwst904iNhH+oktcB7iCOcVU1ziJHPvzC9O8cNUq2a/exKjeZx43L9CHin2Z1kW0lDIazYbvlzjt1otKDwHhmHwbsUU8T4RMd9zlWPRaroftT6OcY48wGyzVPXJPIsmI6+o586d3oNh1O/9SvPQBy0QGB2xJ8sHG72H1fF5j/cjm5uPYRgGQmdHC5N+QI5FIAQCY4W8VGoLAFwV8szXi+Pu3TtotZpQFPuCXLlchqrQjXgbhbnZFka1Ot+m04FbxtkqzOihGLx5aDYb4F2K1QQAfuj8azYbEEXve134jV6vi41HDxF94ZIrm4mRi2vI31nHw4frVPqMGYaBbDaDX/gFeoLb0lIQPM850iePvMdOVGQexHbSPa9TQp7MMuBZxjkhj2KsJkEebtbv7e36cpLvV9rtNrrdDhIhurHV4vB8bkW2dDodBALTzxGIe889R14ewWCEasxoIBAEzzsfWVmtlJGc8xoT4Tk0qjXXolYB05E3S9HAoijAGdLpHQBmT287sDwPORbF7m7KiWGNhfTIIw7eaSHCX6vVdlnIy2N56fzMx4dDURQK3hXXTprTsAyDoMDPXWhJC8uRNylaU6cfB79gPBpxSRJH3rCdyGAwwT3pASTie5yQ1+8PXL1/jkLXdWSye7h08ebE58aiS1ZBjW8wcELIYw4/6APIZ5SdwpFHhDw/fq6fVYgjXBgKeQzDQFACvrkvHYaIdKc58gAzNW1jw5/RmkRTYFkO8lBw8muSV6fTQmCEEUJmWZSGRWF+gaS48aMcebKKaiXj5pBcYTEL8wm0otqmoVYzN0nsLj7dhmEYBJYTyOWzWFo6vbFwOr2NZDKEUMjdfOErV8yIhVIpg4sXP2H7+FqtOtfi1C6qEkK9Xh35Pk7D1paZ7Rx1IVqTZYBerznXeLvdNhjBvQ0H0otPEPS5xv2s8r//exeDfh/Rq5dceT11ZQmiquDe/Q/xhS98bu7zFYtFdDody0VHA45jceZMBMXiPvXPTK1mjtOJeBJyzjNnEkgk6I1b183F/6jq9VlhGAYhnkev16b6PtdqNdRqVSTO0u+XIYZiYFgW5XJucT2xwfa2ucgTKQt5ghIAw7HodBqu/D3MHnnTb7bzPAdB4MCy7tx/qtUSQkF610Jg+D0NRlCvlx37NxiGgWqtiqs2e4QdJyJwMADw/ADJJN33YRSZTHqmogHi4KvXC7h58zLtYT23FItZcKIAKWL/sxpIxrG3u4tkMuiyS3KAQEC03VOcRHHKMly7H7XbbTQadbxwdTZHHmDGa26l7nvwPpv0+20ILAt5TDJCmGfR6cy33qEFy5pxh5OFPB2hkOKLMT8vVKtD593wc8wOhVRJYn33dxBFZvi/o4U8AIhEpLFF8m6Qy+XQ63Wt6MxxxGNL+OjuE4RCwpECfk9hcELJI5e6eFxFKOT9Z4NEOk8TrcmwLBiGhSAwvvtcP6usr5vX/eZ+Ht1qDfFrVyAoAd/clw6zuWnem8Lh079/4bCMVqvlu3EDgGGY7zPLspCHghPDDHw5Vk3rIzBi3hLgGHS7HV+Nu9drguUFsCP2fQVZRalRRzQqP1P9fZ95IU9VDxR70mTyNA7HEQWDBxtA8x4/LcVig3pM2ShSqTSkUNCaBPoZORJG/s469verYI9VBmiahocPH+KTn3TfJXrxYhyiyOP99z/E2toLto7t9/uo12u4fNG9C6CihLCXeYJ8fnab/M7OsOm8w448jmEQEgRkMrm5xlssVcBL7gnk3NAmv7u7j2BwUfV+nP/+7/+BFApCXZm8WKIBw7KIXrmIu3fuYHNzD8HgfN+3+/fN3qfnztHdtD13LoIPP9xBLlejutHUbpuT3X6ffh+Kft8U3BqNAXSdXvRGNpuHxLFz9a4aRYhjkc8X57qmHOfBg3UAB+45mjAsBymUwMbGY6pjftZ58sR0yUiUhTyGYSAFg0ins47/PTRNQ6vVhmpTbFIUCfl8yfHxGYaB/f19XL70EvVzh0Ix7O1lHPs3tNttdHs9RCLzbR5GhvOgzc00DMP5gqF6vYZKpYzEqv3IUSkUA8NyuHfvIS5dmuw6WDAdjx49QSARn+m+rSwlUHr4GA8fbiMed6+oslSq2u6PB8C6FqXTeciyO8I1cSyGZ4zWBIBQOIZut4snT9IIh+nFAE/L/n4BYYEb+xkJcxwK+YIv7vP1urmXMalHnq4N0O/rvhjz80KpZKbUMJaQxw1/X/fd36FYNN0R4xx5AJBOFxCJuHM9GcXduw8BALHY5LVpLLYEwzBw9+4GLly45PDIpkPXdLD80esL+alQqMOltPWxWP20plzbMSyLRqPtu8/1s0omY8ZPV7d3ADCIX7sCPhBAsVT23d9gf98s1hw1j1EUEf1+H3t7Jd8JNvv7Bau3KXHk7e3Nt9fpFLVqDeERQp7MsWh1mtT3reYhk9mHIKsjx8MHzD2Bx4+frpQjlmXGmr1m2i3rDftAjeLv//7v8eUvfxm/9mu/hm9+85v40Y9+NMvLUGFlZcX6/4f73R0nm81a/395+aAv17zH+5F8Pgcx7B8VfRxSJARd10/NO06nd9DtdnH9+sopRzoLz3O4ciWJx483bB9LrOqq6k60JmA68lqt5lzNpSuVMmSOhWyzkncWohyLypwZ181G3RLX3IC8lh8zxb2mVqviyZNHrsVqEmLXrkDXdXz00e25z5XN7oFhgDNn6G4GnTsXRavVoh77SPoCOiPk9YevQXcDu1arWf3saBPmWdQpx4Qc9KxyZiNWDCewt5f2VcN6v1MqmZEqtB15ACCEVOv8TlKv12EYBqJRe/evaFR2JQqn2Wyg1+shGKS/MR5Uw6hUyo71/alW6USEk2SCikt98ra2ngAAAjH7kfgMy0GOLmFz6zHtYT23DAYDZLN7MyebKEtm/DqJ53SLdrsFRbG/uUU2zdouximRdV9wDudvaHiNKpW86ZlTq1YQmrB5HeY51ByI/Z4FbtjDyjAm9MgzdOu5C9zBWr9b0Zqklxj9Of689Ho98Dw30vkrSSQK3Ps+eZnMHhiGRTQy+Voei5r7e3t7aaeHNTWaroE7tq4mPw8G4521bmH1d2SmFPIYFprmv96PzyqtVgucKOKwtZOXJbRb/opPBA7mIOOEvMPP8xOVStmKEuY4DoGA6toawi7tdnvkfm+AZaHr+lx7yrQpl8vg5NHrfiLkzdu2yW/Y3pH/0Y9+hNdeew2f/exnT+0F90d/9Ef4sz/7M7z//vvY3NzE//zP/+Bb3/oW/uZv/obKgO0SjUaxtGRW2Tx8+HDk8zY2DgSZa9cOKl7nPd5vGIaBQjEPKeKeiDQPZJzF4slm5Y8fb4BhgGvXvBFOb9xYQaGQt917jixOFcU9MZWIhvNcwCrlsuNuPEJU4ObqRdTv99HtdsCNyEp2AtKPz6o8W2DxwQfvwTAMxF9wN9YrEI8ikIjj/fffnftcmUwayWTIVtzdNBCHXyZDd2FIRLbBwAEhb9ADz/PUe1vU6zUEOWeE3hDPURdLSc8q1mbPqmmRIkl0ux1XxKNnhXK5BF6SwIn0KzHFUBAlF3rk1WrmnCIatXf/ikYV61gnsTbYVfpCnhqMQNM0R/pZAgeFVPP24QwL3PB87izCNzcfg+WFmYsG5PgZZDN7R9JDFsxONrsHXdehJGfrhyzHomBYFru77gp5rVbL6ndnB3LMuGQa2pD1ijrHWokcSwR8t6lWyogI4681EYFDp9t1rb/pOMiczhiTEGQYBgxd97y32fMGEeyIZsMwDFie99VmKqHX64504wEHjjw/iJB7e2lEIvGphGlFCUKSAtTXa/OgaaOFPG2Cs9YtNM0UFBkbjjx9QrzvAnq02y3w0tF1LCeJaLfbviskbbdbkCRhZJGAn4W8crkM7lC8rKqEPJubTKLTaY/ukTd8792cD06iUilbYt1pCPJCyAMA/OQnP4FhGPj85z9/IkLy5z//Ob773e8CAGRZxksvvQRJkmAYBv7yL//yiNjlJm+88QaAg7Gfxo9//GMAwLlz53Dp0iWqx/uJRqOOfq83U08HLyBCXqFQOPHY48cPce5cbKZFKQ2IgGjXlUc2ZWn3lxnHQVXq7JuQpVIBcYf74xHiAo9arTZzs2MiphFxzQ0YjgMnSgsh7xiGYeD9938OdTnpSQFB7IVL2NvbRS6XnfzkMWQyaeqxmgCsnnuZzB7V84qieV3sORStSRx/NGnWawg6tDmkchy6vZ7lJqRBOr07U8+qaZGHmCiAaQAAIABJREFU5ybOvwWTKRYLjiUOSOEQup2O1e/DKUhxkH0hL4Bqter4wvtAyKN/PSfnPC2FgQbEMR+ccy4jsSwElj21oNEJnmw+hhxdnnoj7DiB2CoMw0AqtUl5ZM8nOzvbAABlebaIHpbjoCTj1nncot1uzhStGQiYhRFOX/sOU61WIAqSNZeZBRpFjLOi6zpqjfpEIY8UBdgtCnUCS8gzxmyiD+8v7BT9rhbQw3KvHRJtOEFAr+e9q+04vV5vKiHPDyJkJpOeqj8eYIqnseiSvxx5pwh5vCXk+UMMs4S8KR15YFjfjP15oN1ugTtFyNO0AdU1Mw1ardbYOQx5zM25yjQYhoFqtQL2UMGAooRQLvtTWOr3+xBHRGuKw+uLHwoxAPPe2G63IIwR8viA2SrtuRfybt++DYZh8JnPfObEY//0T/8EwIyW/MEPfoB/+Zd/wQ9+8AOcOXMGmqbhO9/5zvwjnoEvfelLAIDd3V38+7//+4nHU6kUfvCDHxx5Ls3j/UShYDrbaAp5Wq8PSZLwhS98AZIkQevRu+jzsgROFE848nq9LnZ2tnH9uncxpmfPRqGqkm0hr1gsgON4KIp7/duCoaj12rNgxpuWER/RuJo2cZGHgdkvuKSa381oTQDgJcUxJ8HTSiaTRi63j5jLbjxC7KoZ5/n++z+f+RztdhvlctkRIU+WBSQSQepCHsdxkOUAul36FVPdbhuKok5+ok2arSZU3pnoXnLeZrNJ5XyNRh31ehVSxLmsdTEUA8OySKcXQt60FIsFSGFn7q3SUCAslWa7j04LcY3Z7eMWjSro9XqOu65ITJ0j0ZoUio7GQYS3IIXrTJDnXCncaTYbKORzkONnZj6HHDNFwK2thZBHg1RqG6KqQAzOfh9UlpNIp3dnLlibhXa7PVO0pijy4HnO1Sr3SqUMVZ1vrcrzAiQp4IlI1mjUoes6IhPiwsnj1arzsciTsHrRj4k2JrGboxwRC5yh0zHn8oeLOYhrxm/0ej2IY/YLRJEbPs9bEbLZbKDRqE8t5AFALJpELrfvWPy3HXRdh24YOB5kQn72ixhmvVdTO/IYX7y/zwutdguseFQc44epPuS64xcGgwGEMcUx5DE351XT0G630O/3jjjZVTWMarXiO9ejYRjQdP1EgQCB81mhACn85MekNzAsByEQdKxI1Ctsz8LIAv7y5ZObsj/5yU/AMAy++tWvYnXV7ONw5swZfPWrX4VhGHjnnXfmGmy1WkWpVLL+Ix+gXq935PfHe1R95jOfwec//3kAwJ/8yZ/g3/7t36xjb9++jW9+85vodrtYWVnB7/3e75143XmP9xMkuoOn2NtI6/Xwxhtv4K233sIbb7wBjWKFFcMw4CXxxMbU5uZjaJqOGzfc749HYFkGN26s4PHjh7YmHKVSAcFgxNVeYZIoQxSlmTcgG406BtoAMZeiNcnrzLqZRxbtpALDLTjJv3nXXvHuu++A5ThEr17y5PUFJYDQ+XN4772fzzzpyGZNkc0JIQ8A1taiyGbpV3iqqopOh/7GW6fTPuHIn5fBYIBOtwvVoc0h4vRrNuk4aEhFrhR2TshjWA5SKI70wpE3FYPBwHRxOOjIA2YviJmWSqUCUeQtF8y0EOHP6aiWSqUMWQ6A5+nHl5IoPKeqJhuNOkSWhTijs+0wQY51Rcjb3DR72wXi9vvjEViOhxRZmqmv84KTpFJbM7vxCOrKEjRtYM0vnEbX9aGQN1sUtKKIrgt5NFoQeFX1TtYh00RrHn6+l7AsC4ZhxvfIG653WQrX0AXTQxwmR4Q8UfBlhJwZrTn6c+8XR97+vpnUMk1/PEIkkoCmDXwReU/WtH6P1iTXEwbT7nsthDw3abfbpzryAP8528z707jo54Pn+QlyvTgcrRlUw9C0ge8MAKOuKwTeZ9cX0opJCIyfL/KBoC+u2zSZWchT1aMb5I8ePbImyr/yK79y5LFXXnkFAJBOz7dR+aUvfQmf/exnrf8++OADAMD3v//9I7//1re+deLYP//zP8fHPvYxNJtN/MEf/AFee+01fOITn8Bbb72Fra0txONx/PVf//XIzcl5j/cLpHnsrPE8p8GJIm7duoXvfOc7uHXr1rBhKj2YYVPNw2xsPIAgcLhyZfoqKie4eXMVjUYD2Wxm6mMKhYIVdekWDMMgFIxajky7kAtffMKClBbxoZA3a588S8gb0/jUCfiA+szZtueh3+/j9gfvIXLp/In8dTdJ3LiCZrOBhw/XZzqeuOWcEvLOnYuiWCxSd9KoatAZR16vfWIOMC+tlumUUx2L1iSOPDpCHvlMSOHZeiRNixhOIJNJ+65iz4+Q+5TkkJAnhsz7idNCXj6/j+XlkO2F6PJyaHh8zolhWTSbdciyM0UyHMdDkmRq39PjNBp1hCjNY0Ici4YLC/CNjQfgBBFyZL75rpI4h3R6x7rWLpiNWq2KarUyt5BHjk+l3InX7Ha7MAxjZiFPVd0V8mq1GgJjopKmRQmonmyUWc7qCTG+YZ4DA38IeSbj7zsGzLnI1DF5C6hAvnuH5wWcJPluox0whbxxjjwi5FlxoR5hCXnR6a/l5Ln7+9Pv+zgFcR3xI4Q8v8Qi6rqlrkz1fIZlF2seF+n3+2CP3acYjjjb/PEZmh5/fm7I/it3qAAyFIodecwvEIGOH/F15Vh/OfKINiVMKPziAyHruc8KtmdhxBJ6PALi3XffBQDE43FcuXLlyGORiClaeHnDDoVC+Md//Ef88R//MV599VXIsgxd13H58mV84xvfwPe//33cvHnTseP9AmkeS1fIE9DtdvH222+j2+2CE+lWaTPsyazsjY11XLu2PNZe7QbEEbixMZ1AoOs6SqWiq/3xCMFgdOYNSEvIcylaM8Sz4Flm5gtupVIBx4vgBHfFI15W0Wo1fTN59pp79z5Ct9NB/MZVT8cRPn8OQkDGu+/O5grf29tFKBSwHXU3LWtr5mSOdgP1YDCIjgNCXqfThqrSFclpRt6dxkG0Ji0hLw1RCYETnO3RKoUS6LTbPtrk8y/Ece5UD2CW5yAGVceFvFwui9VV+/3nVlbCYBjG2pxyikajAdnB2GpZUhzrPddo1BGkNP8N8s478gzDwMOH65ATZ+eetytLawCAR48e0hjacwvpa6euzCeskmjOVGqLwqgmQ4SAQGC2eXEgILgmGui6jlarBVm21yf0NGRJcawwYBwknWOSI49jGAQF3jf3eIbBVHuhPjM8PPO02y2wHHe0R54souVDR16324Esj94LkiTzMa+jNff3s5Ak2dZ1JjIs3nN6njUNpEeVcOzLSHpY+SVekBTjT1+ctnDkuYk2GJzoecoOi18HA3+INQTTkTf6cb868gqFPBiGORKtGbaEPGeLL+1C/uYjozWt5/nj+lIul8DyAtgJ+zGCEkKjUXum9mht78ovLy8jlUrh/v37+PSnP239/r/+67/AMAw++clPnjiGRF3GYrE5hgq8/fbbcx0vCAK+/vWv4+tf/7onx/sBq+HsiAaWvoRlLAESMKvhi8UifvmXP+HhoEwikQDOnYtiY+MBfvmXf2Xi8yuVMjRtYFVhuEk4HMN26iH6/T4EwZ7YWioVwQKIuBStyTAM4oJwojfitFSrFddjNYEDB2CtVkUi4Vzk3tPCz999B1IoiOAZ7yJwAbMYIHbtCh58dA/1eg2hkL1N8kxmF+fPOye+nz9vXg/29tK4fJme6Kko9B15uq6j1+tQF/LIRpvimCOPcrRmJg0h5KwbDwDE4aZBJrOHaNT9+8bTBHGiOeXIAwAxHEIuv+/Y+TudNmq1GlZXL9o+VhA4JJNB5B0cH2B+h0JB5+5vkhRwzpFXr2GJUnxvkOfQqjShadqRxTlNcrks6vUali++Ove5pEgCnChjY+MBXn3V+/nz08r29hZYjkMgMf/1WFlOYnt7E4ZhOL7xRBz/swt5IkolZ/tvEkzXqEFHyJNNIU/XdVfjICuVMkSWRWCK14zynI/SPBjLdXcqxsHzFrhHq9U60RaFlyQ0fOjI63a7kCR55OP+ceRlEAknbF17eV5AKBT1hSOPRJOKx/b0hOHPXkeXEqyo3mkdecxCyHOTgTaAfGxeTBx5folPPMzT6NbM53NmW6VD901FCYLnBeTz/nTkjYzWZP1VKFAqFSEok1NsSPRmpVLG0tKyG0NzHNsz2tdffx2GYeAf/uEfLLfMnTt38JOf/AQA8LnPfe7EMY8fm/0dlpa8jUFccMgG+xRl2x935D169AAA8OKLs/cLocnNm6tIpbamisUjG2wRG3nstDCryIyZKj8KhRxionAivsFJkgKH4owRYeVyCZzkgZA3FA/9syD3jlKpiM0njxC7fsUXlVHx61dgGAZu337X1nG9Xg+5XM5yzTlBKCQjHA5gj3IvNEVR0O12qE56u722dW6akI17p3rkSSwDjmGoCATdbhelYgFSyPnruBQiQh79HorPGvv7WYiKAl6e7JI0DAP9VgudShWF+w+n/o4E4lHkcznHNhlyOXOOsLo6W/z26moYuZyzleLNZgOy7KAjT3bOkddsNqi5fsm1ysmoyo0Nc76rJNfmPhfDsAgkzuLhw/XFJtkcbG09gbKUMN0xc6KuLqFer6Fcdj7up9Mx7912e28SAgHBOofTkO9/gJKQp+u6a2MnVCplRAV+qvlvlGdRmbGVAHUmDpdEazo+kgWHqNWq4JWj4pigBNDv96jH8s9Lt9uFLI8u/OU4FjzPeS7kFQp5hGeIxw+H4r6IwyOOvONCnugzIc+ab0wbxzupT+cCqmgD7UTiA/nZL2INgeM4q03UaQwGuvU8P1Eo5CwHHoFhGIRCMd858gij7vF+u/WXSkXwE/rjAQA/jN58lvrk2V7NfvnLXwbLstjd3cWbb76J3/qt38JXvvIVDAYDhMNhfPGLXzxxzP/+7/+CYRhcveptvNqCgyoGP2ysT82xypyNjQeIx1Ukk/7oR/jii6vQdR1Pnjya+FyySRdxuK/SaRDxkIzBDoV8DkmXY0yTIo9SuWQ7g9kwDLM6Q7UfTTYvgmK+ptPRa08DH374PgAg/sJlj0diIkcjUJeTuH37PVvH7e9nYBiGo0IeYLrynBDyDEO3Fns06HVJVb9DPfIcitZkGAYKz6HZnL96mVTiii5cx1legKhGFkLeFOzvZyHFprvuF+9voFdrQOt0sXvrZyje35jqODkawWDQd2zj/UDIm+3+tboaRrFYcGzxrWmaWW0vjq62nxdJkh0Rx3RdR7vdpub6pe3yPY0HD+5DCsWoJQwoS2toNhtWj88F9uh2u8hk0lBX6VTzBofn2d7epHK+cRw48mYT8mRZcE0wIN8piUKELyk6cDoG9ziVcgnRKeczUYFHtVbzh8A+qaZluH/wNLoinmaqtSoE9aiwTX6u1fwRywqYnwvTkTf+OiPLArpd7wTIdruFdruFcMh+2kooFEGxWPT8O0Ai4oRjIow4/Lnf91YoJdjee2QYz9/b5wlNG4A54chjrcf8RCAQQLs9ek+DPBYIOFdsaBdN01AoFE4IeYAZrznLvqyTMNY9/vTH/RRfqus6ypXSxP54wMEe7XMt5L388sv4wz/8QzAMg1arhbt376Lb7YLnefzpn/4pVPXoYrNer+PHP/4xAOBTn/oUnVEvmBlFMf8+A59Vb41D63StGDdN07C5+Rg3bqz44gICAJcuJSAI3NRCXiCgjo2ccIpQMAqGYWzfMHRdR7FYQMKl/niEhMhD03XbG6bNZgO9XneqizpteFkFw3LPvZBnGAZuf/Ae1NVliCF/CO4AEL16Cfv7GVuRKOm0Ka6R+EunOH/erMqiWaFKrvfdHr3rPVl4H7/Xz0uz2QQLQHbQLa5yLFqt+TfdSW8MyYVoTQAQQjFkfdCPw8/ouo58Pgc5Nt2mTDWVHvvzKOS4eX6nFl6ZTBqSxCMen+37dfZsFLpuOBb7ZEWucM7NB1iWc6SJeqvVhAF6fTgP+m4648hrt1vY2tpEYOk8tXOqQ2ff+vpdaud8ntjZ2YZhGNSEPDkWBS+J2NpyQ8ij4cij6/AfBRHyaQh5kmieo91215FXrZYRnbIAMiqY1zwvevkdxjAM6LoGhh09boYhG7z+6p30rFOrjhbyqtWqF0M6lcFgAF3XxzryADNe00tHHtnMDQbtpx+EglEMBn3U6zXaw7IFcdwd75FHfvadI29qL89CyHOTU/dTfSTWHEaWA+h2ByNdea0WEfLopgbNQ7GYh6YNEI2eTCaMRZOoViuuz0/GYQl5Ix7Xjz3PSxqNOrTBwIrNHAcnymA5HmW/pB9QYKbV7O/+7u/iu9/9Lr71rW/hd37nd/D7v//7+N73vodf/dVfPfHcn/70p3jllVfw+uuv4/Of//zcA14wH+GwqUb3m/65YIzDMAz0my1r3Ht7u+h2u7h2zT/ZtjzP4cqVJJ48mVzRn8vtI+zS5u9xOI5DKBS13T+nVquiPxggKc62+J+VpeHr2Y2vICKaoMwWTTYPDMNAVEIolZ5vIS+bzaCQzyF21X6fJyeJXr4AhmHw4Ye3pz5mb28XqiohGnW2uuv8+RgMg26EIhHyehT75DkZranwPFgHJ4Yqy6BJIbJvfz8LlhfAB9wRqaVgDOVSyTeLcj9SLpcwGPSnFvL0Y4614z+PQo6a9xWn4itTqS1cvJgAe0ofY8MwUK22sb9fw61bj07d6Lh0KTE8z7Yj4yObt+yYjV6CYRhotRuo1kp4+OjDqTdmnBLyiOCmPiWOvIcPH8AwdKjLF8Y+zzAMDDot9BoVVFP3x77PnBSAHFvB+vo92sN9LtjaegIwDNRlOj0iGYaBsryEza3HVM43DlKEI8uzC3mGYaDXc37znTj/RGFyTPIkRFEantO9dW+v10Wr3Z66r3h0+DyvY/nJdfd4zNphiMi3EPLco9vtoNvtjHHk+UfIOygYGN+L082o3tMgewWh4AyOvOExXhftPj098ixVaKrnL3rkuQzDAPqxeaNPE9yIQDfKlUeEPFl23zAxikzGLKyMxU7OG6NR83fZrH9SMg6EvNPXEgb889kgbd74KcwbDMNAUELWMc8CM5fU3rhxAzdu3Jj4vDfffBNvvvnmrC+zgDLhsLkJ1fdhc+TT0Lo96JqGUMgcN3G9+UnIA4Dr11fwb//2IRqNOoLB0y8mhmEgn8/h0sWbLo/ugEg4brlJpoUIaUmXHXnJYTPsYnFGIc+DaE0A4JUw8j7IzveSDz98DwzLInp5/Aak2whKAMGzq7j9wXt4883/Z6pJyO7uNi5ejDs+YblwwRT40+kdXLp0hco5idhG05FHNvFoV7s1m03HYjUJKs+hTCFea38/A3HocHYDMRQDYN4/zp2bv1fWswhxoMkxZws4OFGAGFSRzdJ3vHW7HWSzGbz66ounPn7r1mMUCqZo9H//73swDOCXfumFI8+JxRREowpSqS189rO/RH2MB0Le5O/qxqMP0WiYG4w/+/nbgGHg+rXXJh7nnJBnvnfKmD6chmGgNtDQ1XW8U27gF6PqyO856ZHnlCNvff0ueFGGfEoV72FqqXUMWqYzIH/3/wMMIHLx9M8QAKhL55F5+HNUqxVEIvY3MZ9ntraeQEnEwFEsbAueWcbeO++PXT/QgGzqStJsc3lxuAbo9/uOp4qQDX4iws2DMDxHu+1eEg0R5Ow48gCzIOX8ee8K4Cwhjxkz7uH1cCHkuUetZl7fxeNCnmIWGFar/onWbA33lxRlvJCnqiKVqPtZKRZnd+QFh3GcpVIRly971zaIXCePJ5lwDAOBZT2NLj3MQbTmtEcsHHluwjLsiff74G/m7LrcLiQys9XqIxg8OQ9pt/vgOBaCMP764ybZbBosy55q5IjHlofP2fP0WnKYpylas1IxRblpHHkAwMlBlFzoSe0W/vp2LnAcVQ2CYZinxpFHBEfiyHvy5BHOnIkgFPJPpQVwICyOi9esVMro9bqIDnvVeUEkkkSpVLRy1achnzebsC5NyLunjcJxUHgOuZy9JrDFYgFgmKkv6rQR1AjKpdJzW02m6zo++OB9hM6tgvdRRRQhdvUSqpUydnYmO1Y6nQ7y+ZwlsjlJKCQjFlOxu7tD7ZyiaE5kafbLGgz6w3PPv8F2mGazAeUUFxJNVI5Fc87eW4ZhIJvNQAw6G7V6GHE4+XcqLvFZYHd3BwzLIBB3/u8SSMaxu5uift7d3R0YhoFLl053+9y9uzf2Z8KlSwns7GzRHh4AYDCY3pGX3tsc+/MoOJaFYejU76FWH84xQt47lSZK/QGamo7v7ZfxTmX09SLAsWDgjCNP0zQ8fLiOwNL5iRspzXxq7M/HUVdMoWDhyrPHYDDAzm6KWqwmQXWpT16/3wfDMODGfP7HIQzFJjdcHu12GwzDUonwJa6+Tsc90YC0BIjZdOSVy1478sy54lhHHsOAYVnH+rAuOAkpaD3eqoDlOIhB1XNn2GHabfN7pqrjN9IVRUS77UwRzDRUKiUEZAU8b39vQx26P7x20BLnssydXDvJHOtaT9NJHIhE0/bIW/TgdBOGPUU4Hf48TdGem5AiYuK8O06r1YMsB3whMhEymT1Ewglwp6SByLICWQ74qm/1pGhN49jzvITMmaZNSBKUECqV0jNzffHXt3OB43AcBzUYfGoceURwDIcjGAwG2N7e9J0bDwDW1qKQZWGskEeiuCIROpE8sxCNJGAYBgqF6cWxXC6LAMchOOPifx6WRR65nL3N63w+B1EJj12IOomoRqBpA88n+F6xu5tCrVZF9Molr4dyKpFL58FyHD766IOJz93b24VhABcvuiO+X7wYw+4uvUg8skCl2ayanIvn6Tp0m4362A12Gqgch26vZ6uQ4TjNZgPtdstVIU9QQmBYzrab+nkind5BIB4Dy9OJTRyHspRAuVyyKs9pkUptgWGAixdPLxzo9bSxPxMuX06gUqk4UqVvGKa4Ns0Cjoj+o34eDakGpbvQagxjdYNjPiMPGu2xPx+GZRgoPOeIkLe9vYlutzMxVhMA9GPX9+M/H0dQIxCVMO4v+uTZIp3egTYYUBfyAokYWJ43YzsdpN/vQRS5mTdfDjvynKbTaUMUJSobRaIHjjyyuTStkCexLBSes6rLvYL0LGMniBssL7gSsbrAhPTkPS1xQIqGHevZOwsHjrzxxX6qKlGfQ9mhXq9BDszWi5hlWciy4nmPPOLIk07Z75BZ1tPo0sPYjdY0HXmODWfBMViGPWG/MnwarRkMmoJNo3H6/bxe7yAU8qaQ/zQMw0Ams2dFaB6HYRhEI0tU26rMCynU1Ed8CcnvTxMm3aZSKYGXFLBTFn3xgSB63a5vro3zMtdOnKZpePToEXZ3d9FsNqeqnv3N3/zNeV5yAQWikRgqde+qoOzQq5sbJJFIFLu7OxgMBr4U8liWxQsvLGFzc7SQRzZhoxFveuSZr52wxnLmzLmpjsntZ7Es8p7czJdFHh/sZ2EYxtSvv5/LQpgh854W5LVzuX3E4965L73i0aOHAIDw+bMej+R0OFGAurqER48fTnzuzo7pbLhwwR3R5sKFOG7f3qUWsUXENl2nF4FE4pRoC3n1eg3Xg3RdfscJDqM7G406YrHZrsPEoWzGXboDw7AQgxHrtRccxTAM7KZ3ELzkTuyokjSv6+n0Dq5dmxwxPy2p1CZWViITI6kmcdAnbwsf+9jHaQzNQhDMDd4BxeKA42jaACzLUl8kNhp1MBgfrdk71ifk+M/HCfKcJRDSZH39LhiWg5Kcbp5mB4ZhEFg+jydP1tHtdiFJzl53nxW2tkzHXHB1fNSpXViOg7KcwKbjQl4fwpTC0mmIovl9nF6Qn51ut0stGotlOXAcjx7FiPFJlMsl8CxjqwAyxnOWk88riIOH5ce/9xwv+cbt8zyQy+1DVBVw4sm/ixyNIL/+GLqu+8I9Qxx5k+YxiiKi02l7Nu56vY6APJuQBwABWUWDQlT/PHQ6HYgsC+6U/RGZZZ7q7+iz4ph5GuA4DsaxPXxD063H/ATZG6nVRgt5quqfvbdarYpms4HEjZWRz4nHl7H+4L3hHM3d9LPTIH/zwYivoGYcfZ6XlMsl8DYKMkhaW7lcot4ixgtmmtG322381V/9Ff75n/8Z1er0DXYZhlkIeT7g3Lk1ZN77mS1xxCtahRICioJIJIp79+4AGF2t7jUXL8Zx584ddDqdU5us5nL7UJQgRNG7uMFQKAqWZad2dhiGgVwui1dkd/vjEZYlAd1KE7VadapeLoPBAKViEdEr3olIoiXkZXHz5kuejcMrnjx5BCUZBy/7d3MweHYVmZ/dniiYpdMpJJNBqKo7/xbi/Nvd3aHy2SFiG1VHnj4YRl7Rm8B1u130+n2EeGcnVaGhE6der80h5JmVz4LqbC+24whqBLm8f6qu/USxWEC308Fy0p3FWyB50M+SlpA3GAywtfUEn/nMpbnPtbYWgywLePx4g7qQdxDX69xm/kBzZjHbaDSg8DxYivNelWXQaNCtyjcMA/fu30UgcWaiM2ZW1OWLqG7dxaNHD/Hyyx9z5DWeNba2nkCORRyJDA+uLiP73kfodNqQ5QD18wNEyJv9vu1mtGav150p8m4UPC+4Mm5CpVJCTBBsrbFjAodsqejgqCZDqtTZCSIqwwvPTEX708B+LgspenrfdzkawWDQR6VS9kXxKHGoB4OTe+QZhrmnqKqzC2qzUq/XsLI0ex93OaBYvQu9otPpQB5RLCCzDFptf3xHbYtyDGOlPyxwHo7jLOGOYOjOFO3Oi6qajrxRQl6t1sXFi6dfK70gnTbbpSTio4W8RHwVuq4jm93ztEcugRRWaCO+t5qvHHll8PL0f28i+lWrFZw9607xr5PYLoFpt9v42te+hm9/+9uoVCowDMPWfwu859y589D6fXQr3k5ApqGdL2Lt3AUwDIO9vV2EwwGEw84scudlbc10aIyyR+/vZxCrr+nWAAAgAElEQVQJezvJZlkO4XB86l5L9XoN7U4HKy73xyOQ1502NqRYzMMwdFdj747DCRIEWfFV1Ilb9Ho97OxsQz0zesLiB0JnVwGM72lpGAZSqS1XCwfW1mJgWYZa/y0nojV1TQNPOb6QxNOEHI5FPBDyZq+izefzYDke/ByVvLMgqFFUymVXYs2eNshCSVly5/7KSyLkSJhqn7zt7U30+wPcuLE697k4jsW1a8t49OgB9Xm3dU1xUsgbDBxpVN9o1C1XLi2CPIcG5XitfH4flXIJ6rJzC/pAbAWcIGJ9Ea85FbquYzu1CXWFrhuPcNAnb8uR8wPm94qf4/NPjiWufCfp9XrgObpCHomNdINyqYiozfc6KvAoVyue9tee1pHH8iLaT7Hb52lC13Xk8zlI0dOLx0jcpl/WnPV6HZIkQJqwbxCJBIbPd38vStd1NJuNmaM1AdOR54doTXmEm1FmWXTa/mqjw0zbIw/+i3R8luF4/kRyj2458vwl5PE8j0AgcGq0pmEYqNc7VBKNaLG7uwOGYRGLjZ47EpGPrGW9hmVZsCwLfUSXPPJJ8fqzYRgGqrWqLUceL5tCsB0jmp+x/Rf49re/jTt3TGfUjRs38JWvfAUvvfQSIpGILyz9CyaztnYeANDKF0/NW/cLWq+PdrmCtY//IgAgk9nF2pp3kYmTOCzkXb589chj5kQ8jxeuvuLF0I4QCcenjmgjC4Nl0Rshj7xuLpedyvlAxit6GK0JALwa9c2iyk1SqS1omobQWX8LeYFEDLwo4vHjR3j11U+c+pxKpYxGo4HLl6+7Ni5J4nH2bBSp1BalM9rtSzAFDiyu3BfyZl985/P7ENSI64tMUY0AMFAsFrC6esbV1/Y7qdQWOEFwdT6jLCexndqilmzw6NGDoQBHRyi4eXMFH330HgqFPJaW6MWRsywLnhecdeQN+pbzjyaNRg1Blu73NsSxaFCOqr9//x4AQF0+T/W8h2FYFoHkeaw/uOebSDY/k8tl0et2oa44E+2vLCXBMAxSqS3cuPGiI68x77WKHOtGUW6vS9+R1++758grl0tYk+3NZ2ICD03T0GjUEQ57szZvtcxrGSeMT6FgBcmR3qALTlIsFjDo9xGIn76uJfOeTCbtixSYer1qiXTjIEXZ9XrN9Tltu92GYRgIyLOngMiygmbT2zY1rVYTyog5jcKxaPlMyDNGCAMLvIXnefSOO/KsNhreu66OEwyGTnXkdTp9DAaa1UfPD6TTO4hGk2NFL0UJQpYV7O76Q8gDAI5lrQjN4/jFkddut6ANBuCl6YU8TpTBsCxqtedUyPvhD38IhmHw+uuv42//9m99keW6wB7J5DJEUUIrX0D8+hWvhzOSdtHsFbC2dgG9Xg+5XA6vvebMApcGoZCMSETB3t5JR161WsFg0Ec45H0saDgUw3ZqY6osZhLBueyRI0/lOQR5HtnsdA5CIp65HXt3HDEYRX7v0XO3QfbkySMwLGNVl/sVhmWhnlnG4ycbI59DxDTSb8otLl9O4Kc/TUHTtLknSYOB6cTjWHqTLY7lMBgMqEYzkz4TIcpumeOoHAsG8wp5OQge5O+T4oR8fn8h5B1jc+sJlOUkGBevterqEkobT6gJZRsbD3D5cnJiFfu03LxpOvsePXpIVcgDAEmS0HNwU7zfd6ZvW6NeR4LypkSQ59Af9Kn2mnvw4B7kSNJx16+6fB77mcfY3U3hwoVLjr7W004qtQ0AUFeSjpyfE3gEEjGkdrYdOT8AGIYOdg4hm9zv3XCM9Xo9CAK9qG2e511z5LXbbbQ7HcRC9tYhsWF0aalU8kzII1GBvDT+vedlBfUp12UL5oOsRdTl04t8OFFEIBbF9vami6MaTa1WQzg8OX44EpGHz3d/Q7XbNUWAeZz/Ai9C17Wh09kbZ0qr2UByRLSmwrHodDq+2IewvVY0DMCGe2/BfPAcj+4xpz3pmee16+o0VDWIZvNksk6z2bMe9wO6riOd3sHauRfGPo9hGCTiK/4S8jgOgwnRmizFvaVZIK46O2slhmEgyCqq1YpTw3IV21f2nR3zQ/aNb3xjIeI9pbAsi3Pn1tAqeNtUexKtvNkrYG3tPPb3MzAMw3K9zUun04ckSfjCF74ASZLQ6dCpLl9bi2Jvb/fE7wuFPAAgHPYu8pEQDsdBnB2TyGb3EBR4BD2syFkROexPuWDM53MQlTBYjyceYjCGfr/3zFR8TMvubgqBRBzcU3BvUFeXUSmXRlZUplJbkCQeZ864u6Fy6VISvV5v6vjbcZAYRpoTcZbjYBgG1c08txx5LMMgKPAzC3n9fh/VanXojnMXQTEz4Ke5bj9PtNst5PazUFedibwbBXHm0Ng8q9dryGYzuDGmGbpdEokgkskgHj16QO2chGAwhE7HuUrvTreFUIhujwvDMNBoNKhfY4IUXL6H6XTa2NlJIZA8R+V841CGr7GxQf8z8qyxs7MNQZYhhpzbIFKWk9jdTTkmlOm6MZehnoiAbvQu6vX7dB15nOBaLHW5bK6t44K9eVdc5IfHe9cnr1argJdkMBOKyHhZRa/btaI4FzjH9vYmeFka2SMPAJSVJaRS257GshIajZol0o3jsCPPbagIecNjybm8oNVqQhkj5BkwCwueOhhHwl8WjIBh2RNOe8MSa/xXjK4oiiXaHabZ7FqP+4FisYBOp4NkYnLxbSKxikIh75vesxzLQZ8g5Hnt1qzVTDGOs+msZiXl+RXy5GGT79XV+ft4LPCOCxcuoV0sQ3Ox+bddGpkcYvEEVDVoOa3OnqWzgdpu9/HGG2/grbfewhtvvIF2m84C7+zZCPL53IkeEiTKMhL2gSNvKCYWCpPjNfeze1gVvRXFVmURudz+VH059nP74OfYZNf7vSMCrz6j60AM+qtngVuUyiWIYX9UQk2CbMhVKuVTH0+ltnDhQhzciEWSU1y+nLBef14sRx7F+AMiCpJz06BcLkNkWQRcWDBEeRaV8ul/80mUSkUABgTV/UbaLC9AkJWFkHeMA6eMu0KeFAmBl2UqQh4RUoiLjhYvvriKJ08eUd/ADgaD6HSdi5TqdFrUK2pbrRYG2gARygtPcj5aRTuPHz+CYehQks43YedEGXJ0aSHkTcF2aguB5aSjkcrKchL9Xs9KwqDNvI48cqyuOx+PNhj0wbF0C5BozlnGQYS8mM21U5TnwRw63guq1Sq4KWKqSAX881as6AVb20+gLC+Nvfaoq0vo9bpUCgDnwTCMoSNvcrSmIHBQFMkjR5654c9P6AU5jgMhz73em4cxDAOtdnuskAccxOV6ifXZnTaWeZHA6Sosy5z82wzv8wzjPyEvEFAt0e4wRNxTFHd72I9iZ5iwkEhMXtslE6sADN+48tgx0ZpkCui1yFuvm67MSQkCx+GkAOqNk47OpxHbf4Hr181+QdmsMwuNBe7wwgvXYeg66nv+FBp0TUMjs4/rw75opGJrmtz1aQgEBNy6dQvf+c53cOvWLQQCdCo/I5GAObk6NnEqFHKQJBmSNNv4SdQUEZj6/dknjuGQKeRN6pOnaRpyuX2sehSrSViVBAy0wXATfTSapqFYzM/VH08f9I4IvPpgRiFPJTF40/UifBbQdR21agVi0B8TqEmIIXOclcrJTZNut4tsNmOJam4SiykIhwPY3t6a+1wHQh69DTES00mzR1a5XEJM4F3pOxcTeJTLs4lhxaLprPYqupdXIpa7e4HJ9vYmGJaFsuRM5N0oGIaBupLE5taTuc+1vn4XkUiAeg/gl18+i36/jydjIoRnIRQKO1Y1ahgGOh36jjxSfRkW6Ap55Hy0qjs3Nh6A5QXIUXfiqQOJc0ind9D2WS8dP9FsNlEqFhyL1SSoy+b56fXIPYoxZ1yZmz3yBoM+OIpxdTzHY+CaI89cq8RsOvJ4lkFI4CeudZykWq2Am2JTjB9WwD8rVe1+pdGoo1QsIjghcSA4LGSisW6Yh2azgcFggHh8uo3VWCzgyWeIiG9PsyOv2+1C1/XRQt6wyMhXQt60Cp1heC4SPE+wzDhHnv+skapqCnnHx0zEvUDAH4683d0UBEGcysSRiK9ax/gBlpvsyPM6WpP06eVs7q3zYgDNxrPR49f2VfKtt96CYRj43ve+58R4FrjEhQuXIEoS6jt7Xg/lVJrZHPTBANev3wRgCnmBgAiB0iaMLAvodrt4++230e12Ict0xKpRURHFYgHBYGTmjepe/6jANE9/Gp4XoCjBiYvFYrGAgaZhxQdCHmDGfI6jXC5B17S5hDyWF48IvOyM1XqcFAAvysjn/SmUO0G9XoOu60+PkBckQt5Jd9bubgqGYeDyZXddPoC54LlyJYGdna25z0U2Z4U5qk6PQxavNONaKuUiYoI7i7aYwKFaq03l8D0OccOJivuOPAAQ1PBCyDvG5ubjYZyv+85xEs87T0V5v9/HxsYDvPLKWepC9gsvLEGSBNy/f4/qec1ozaYjG/q9ntnTJRgMUT0v2Sx0ypFHYzPSMAxsbKwjkDjrWr9HZWkNhmHg8WO6Yu+zRDptbqwoS84W9oihIARZdmwjx6ysn/076+bGXr8/oBsJzvLoUyw+Gke5XILMcQjMkOYQ4znPHHm6rqNUKkJQJl97hYA5ByqVFgkBTrI1LBSalDggBFWIqoLNzcduDGskZD0Vi023DozHVU8+770eceTNvr9Bju12vUm2IgKdMiJxhQh8o9pHuMlBEci0R9Drwb5gMizLwjjutPd5tKauG+h2j7rs/ejIS8RXpvosi6KESDhuufi8hmNZjNolIb+nmfY0C81mAywv2G6nxIkBdDrtmfaB/Ibtb+dv/MZv4Itf/CJ++MMf4tvf/rYTY1rgAhzH4YWr11BPZ1yprrRLbTcDjuNw+fJVAKZ9dpqoBq8hDZ6PC3mVSgXqHJu/onBUYBLnqCIDAEUJTdx4IhEdszryOpp+tA+hNlt2/5IogAWQndAnj0SFEjfcLLCCeETgZed4n3k18lw58sgCTgw+HdGanCiCE4RThbzt7U0wDOOJIw8ALl9OolKpjIz9nBYSOxAI0JvUBgLB4bnp9LUwDMNy5LlBTOBN9+gM4kuhkAcvBea6LsyDoITRbrcW7pkhvV4P6fQOgmfccS8dh7zuPJtnJPrylVfO0hqWBc9zePHFFayv36HaOycUCkPTNPR69CvRW+3m8DXoCnmkl0KE8nVGYFkoPEclHqxUKqJarUBJ0P8sjEKOLIHjRTx6tBDyRpHJmEVkStLZaHyGYSAnY9brOXH+eZZ7ZK3o9AarYRgYDAaW+58GHMe51iOvVCoiNmPRaVzgUPIoPrtaraDf70EMTu7lzskKOF587toHuM36+j3wkjixiIBhGATXzmBj44FrEbKnYfWHnNKRF48rqFTKru9DacP9iHlECnYYOajr3mwGN4bRcCp/+r9BtYQ8750ndqM1DWMh5LmJ+V6f7sjz499Bksy91k7n6D291xsMH5dcH9Nxer0estnsVLGahERiFTs7KV/sy3NjHHm6T0TeRqMBXrSvDXDDz48fro3zYntF+7Of/Qy//du/jb29PfzFX/wF/uM//gO//uu/jsuXLyMQmPxm/uIv/uJMA11An+vXX8S9e3fQqVQRiNGNdJqX+s4eLl26AlE0L8aNRg3hsPcX5kkcCHkH2btmZnwFS3P0PBEECd1KAW+//TYAIBKeL+JHCQRPjRQ8TDabAQtTSJuFjq7jjf/zObz11lsAgPf++8cznYdnGSQlEfsThLzysO8VP0U1qRsISgil8vPjniHvP01HntbrQ5IkvPHGG7h16xa0Hr2NGIZhIAZVa9yH2d7exNmzEWpOXbtcvXoQkxONTt5UGUWjYYptdIU881y0hLx2u4Vur4do1J0ojOhwI79cLiEWs7cxWywVPb2+CAqpgi/i3Dl/RId4yc7Otune8kjIC8Rj4EQBm5tP8NprvzDTOdbX70KSeFy75sy/4ZVXzuH27V3s7e1ibe0ClXNGo+Z8sdmqzxwXPopWqz58jdmve6dRrVbBMYy1uUWTCM9RceSRfo9yzL0e5AzLQowuORbn+CyQyexBCgXBic4XcATiMeTurGMwGICnGC0JmHOeefrb6bo7G3tmlbRBNxKc412rvi4VC1idUciLiTzqhRr6/T4Ewd35Zy5ntkyZJtWEYRgIwahj/RwXmA7JBw/uI3R+Ood25MIaSg8eY2vrCV544boLIzwJKT6Mx6d35PV6PbRaLaiqey4awxgKeXP0/yJ/E5pFUnYgm9DBESkDwaFbpuGDCDlrw9+Y8r1aRGu6iqZpYFgOxqHPMjOcK/vRtUScYNoxg8BgoIFhvBeYACCTScMwdCsycxoSiVU82byHSqVse3+CNizLYtR00S898prNBljRvjbADcW/ZrOBcNibVim0sD1L/trXvnZkEv/RRx/ho48+mupYhmFw7x7diJ8Fs3ON9J/b2fOVkNdrNNGpVHH9s//H+l29XsPSkj8EmnGcJuS12y30+32oPhGYAEBVw9jLbI6tetrPZpCURPAzxujILItbt24BAG7duoXYHBf8FZHDzoRozUqlBJbjwYnyzK9DEz4QQmXvsSMbMn5E08xKKJZidJnW6+Fzw0hZAPjJOz+ldm4AYHjOGrf1mpqGnZ1tfPrTdDa9Z+HMmQgkSUAqtYnXXvvEzOep12vgOB6CQK8I4kDIo9MomFTwzlrBbpfYISHPLsVCAULI/bhVgqCaQl6xWMC5c+c9G4df2Nx8DDAM1BVvhDyGZaGuLGFzazZHnq7rWF+/i5s3V8FTjnwkvPjiKliWwf37d6kJeZGIOV9stRqIx+i+982hkEdegxbVagUhgQfrgAgR4Vkq8WA7O1tgeQFiyN35uBxdRu7R++h0OpBlf8yf/MReJg05TldYHkUgEYOu68jnczhzhq4zk2WZuSq9yaHMHJvf02DNJSnGNnEs54pTSdd1VCplvBSdTZSIW/OTIpaX3RP0AVjuOjE03WddDEaRy6WdHNJzTSq1jXa7hZUL0xUBh86tguU5rK/f80zIK5dLUBRp6iJIIviVy0VXhTwivs1TlHDgyPNGyCMC3ajiJJ5lIHMsmk06a7V5IBv+0999DMfvMwsO6A/6YDkW2qHPMrn/eunwHQVnje24kKeD4zhfuAh3d3cAAEk7jrz4yvDYlOdCHqZ4D71+n9udzkwtkMgxnY43/U1pMtNV0jCMmf9b4B8ikShWVs6gmvLXRLy6vQvAdAwSOp0OAgFve7VNA89zEAQO3e5B/yhSqa34SMhTlCAGg8HYJsj7+3tYEWdfSMsce7QP4RyV8CuSiEq1MrapdLlcghAIeX5jIQiBIAzDeG6awZPqYZ1i9RYnHo2UpV0Rb2jaiarnbDaDXq+Hy5fnc73OA8exuHQpju3tJ3Odp1arIRBQqX4nREECx3Go1+ePkgOAfN50rSZmdP7aJSpw4BjGdq+5fr+Per02Vf8YpxAC5mtP6m/6vLC59RhKwnTFeYW6uoxiIT+TQzWTSaNer+Pll52LUlRVCVeuLGF9/S61cxKRjYhuNGk162BZlnqPvFKxgPiICKp5iQk8yuXS3GucVGobUmTJ9Q0sOWqKsU71Znua6Xa7KBULCCTcE/IA89pAG4Zh53LkuRW1RRwANKu9We5k0ZYTVKsVaLqOuDhb8V5ieJwX9/j9/Sx4WQE3ZeGXGIyh1WpaEX8L6LK+fhcMyyK0Nt38gOV5BM+u4v79O57tt5XLxaljNYHDQp67ffIsIW+Oa4zXjjzyvQuOKXgI8pwvvp8H0Zp2HHn+2Mt5HhgMBmCOfY7I53vgUm9ZO4xy5GmaTtXJPw/p9A4UJWgrESkaSYLjOKTTOw6O7NmhM6uQJ5D+pk+/kGf70/53f/d3ToxjgUe8/PLH8Pbb/y/6rTYExR896KpbO1haWsbS0kGlN8dx0LSnQwjWNB3sod4OpHeKovind5gy3BCu1apQ1ZPj6nY7KFcq+GTSH5bjlWGfvlxuH+fPXzz1OaVSCRzFCMF54Ye9xCqVMhIJ70QhtxCGfcP0AU0hT0Cz1LUiZdUY3c+jPtCscRO2tzcBAFeuePs3u3w5if/4j7tot9tTxVafRrlcghKge91hGAaKEjo1knQW8vl9sAxjbWA5DccwSEoC8jZ7u5gbDYYVb+kFLC+Al5SFkAdz4bm7k0L8xWuejiN4xqyg3Np6go997OO2jr1//y4YhsHLL59xYmgWr7xyBv/6rx+gVCoiHp+/76eqBsFxHJpNOvG6h2m26giHI9QjW0qlAl50qA9nXODR6zfQbDZmFiC73S729zOIXrX3GaKBHDVdxjs72545OfwK6RUdSLjjkpTCIbA872ifPL9DHABUe+SxHDRNc7z3Erk3x2e81pDjvLjHb6e2INlo2yANrxup1DZeeukVp4b1XGIYBu7dv4PgmWVbhUqRC2vY+Z+fIpvdw5kz5xwc4emUSkWcPz/9OjyRUIfHuS3kmevUea4F5FgvhTyZ48amJqksiwal9JR5sIqTbPXIWzjy3GLQ74Plju4zkHQlPzrySMrV6UKeO+k+k9jZSdmK1QTMve5YdAm7Owshbxq6nTY4xb5z8Vly5NmeaX7qU59yYhwLPOKll0whr5raRfKmtxtiADDodNDI5vD6L//Kkd+bQp43kyU7GIYBXTeO3EjIhUKkGG83L6T34KiLGIlYIQKa15BxZLOZkUJepVKGuHz6Y15A3DNuVxp6heXI8+GkbxTGYHDCkZdKbSEWU1zr2TaKK1eSMAzTJUFikO1gGAZyuX1cOE9/YzYSjlPrjZLLZZEQBfAubjAuCRz2cvbGTzbWvO7BySshFBdCHtLpHWiaBnXVm1hNgpKMg+U5pFJbtoW89fU7uHIlCVV1dm7wyivn8K//+gEePLiHz372c3Ofj2VZhMMRq58dTZqtOvVYzU6ng2arhfiSM4VJpAihWCzMLORlMnswDANyxP3oXk6QIAajVhTQggPy+RwAQHap/QDDspCjYeTz9gpNniXIxiFLUcgj59I0zdGoe0vIm7EwSeFYSBzrupBXr9dQLhWRuHF16mPkcBIMy2F7e3Mh5FEmk0mjVCxg7Q17e27hi2tgbr2DDz+87bqQR2JlP/7x6e9hsiwgGJRRLrs9p6Ww3rCihuc/1Sw0mw0EJ6QMBHkW+z5w5BF3nTF1uKazBRcLjtIf9CEed+QNf+73/efII9/f47qwrvujWKnVaqFcLuLi+Zu2j43HV7C5dR+6rnveg87vdHtdBOeI1nwWHHmLT8hzzsrKKmLxOKpb/ljAV1NpwDBOLAo4jpsrEsYtiNh4WMgjFwqafarmhbiQRl3EyCa9X4S8qMBBZFmrGftxdF1Hp9O2Gpj6AdKrr91ueTwSdzgQ8vzXGHkU2uBktObOzhYuXZrftTIvFy7EwTAMUqmtmY6v12vodjuIROj/WyKRBEqlApVKvfx+FstzRPjOwrIkoFwu2VqgkI0GLx155uuHUCouhLytLdM5G1zxrmchYG68K0tJbG7Zi8Etl0vIZrN45RXnYjUJyWQQKyth3L9PN16z1WpQOx+h7YCQRzbFE0458ijE4RUKpmAkBr3pVy2oUdtxw88DhUIeDMtCDLqX9iBGQs/134JEa9KsrOdc6vdTKhXAMQwiM/Y8ZRgGcYF3/R5P5pmyjZ6nDMdBjiSxNUyxWECPDz54DwzLInrZXl9bISAjtHYGH3zwnutOsWq1Ak3TkUzau1YmEqrrwjXZ7J+rZyhI1LA3W6n1Wg3BCRv9Qc5v0ZpTvt8OO6cXHGAYBtrtNjjpqCDCS+aepR/3sPr9HgBAEI7eZ0WRsx7zEhKNHo/bLzSNx5bR7/dQLBZoD+uZwjAMDPp9MDNEqbLDY3o97z8r87IQ8p5zGIbByy+9isbePgZd7z/Q1c0dRCLRE5VkHMedaGrqR0j851EhrwsA4Hl/iGIAIPAkH7h76uO5XBYCyyIq+MOizjIMlkV+pAuICJKcQLeH2jwwHA+GYdFutyc/+RmAuDz1p+TGaOg69EH/SLRmpVJBtVr1PFYTMCtVz56NzCzkke9KNEy/YXIknICu6ygW59tsHAwGKJZLWHK5x9myKMDAweb5NJTLJbAcbwn0XsEHQqjXa76MO3GT7e1NyJEw+IC3fw8AUFeXsJ/N2IrpWF+/BwCuCHnkdba2nlC7H0UiUbTadDeIDMNAq91wQMgzF8SzumQmERV4MMBcC29TMOLAexQPLqoRlMtFS0RZYFIs5iGFQ3P1UrKLFA6jUik/t9f4A0ceve/rgSPP2fe0WCwiJvJg59iETgjc3HMru2xvb4FhOcg2ojUBQIqtILOXfiY2xPyCruu4/cH7CJ0/C162XwAcu3oJtVrVahPgFiR9JpGwF+efTKquO/JsC0un4FbP0FE06jWEJjjyQjyHTrfrI1fVQpzzG71eD9rg/2fvzWLkSNOy7Tv2yH2vfXN5t9u9zXT3dNfwf6g54dMMHCDBICFAQiOGE04QB8wgwREcIIEAMQIJiQMGJHoG0eJH+gWjj+ZjwMP0uO3u9m5XufYtK/c9MjIj4j+IetN2VW6xZYRddUk+qKrMyNdVmRFvPPdz30/72LmGOfy6Vqu5say+kOuNIDy/RxAEFrLcci3ulrC/r0ejx6LGG01jsdRzx3CNIc6Nbs1iBZ42fJlppCD7+ZfhfsfSnUmlUsH3vvc9/O7v/i6+8Y1v4Fd+5Vews/P8gO50Oo2VlRVsnea9eparV69BU1WUt+wfrm4ERW6hsrOHq1dfPbYxoukXI1qzuyPPg0LeoTuwlyMvl8siYfFm1G4SPIt8j5tbUpykWe+4HimKAsPxkKSTIeQlEklQFIVGoeT2UoZCKpWhqRrGxsY739vc1G98FxbcF/IA4MyZBLa2NkxtNoh71QlHXvTwmAcG58wdJZvNQNM0jI3Y+Zt6ZubmsBQKBXC+oOtdopwvCIK/8X0AACAASURBVEBDqVR0dR1uoqoqNjbX4J9w141HCI6PQdM0bG1tDP2cR4/uY2wshFRqNFGtr7wyBVVVsbLyyJbjEUeenTfMklSHqqq2C3m5nLW5VYNgKQoRnrPsyOMDYde6+7lABKqqnpgo8GHJZDPgI6ONUxYPX48I0CcNIra9iI68XOYASYsNkAleTwwYZZHpyZNliNFUJ05tWHyxCaiqMnLR6GVmdXUFtWoF8XNnTD0/PD8LmmXx2We3bF5ZfzrO94RxR16xWBzp+51E1lly5Gn63sete4JKtYLQAOcvEfoqFfvnGRvBxXr/KQOo1fRkjaNNkawoPvdzL0GEPP5Icx75ut12V7je39+DzxeAKBof0RIJx0FRNPb39xxY2fAoqgqmx6mNcXk+qP7ah0KemSY76lTIw9/93d/hJ3/yJ/F7v/d7+Kd/+if853/+J27cuHGs2/fHP/4xvvrVr+KrX/0qisWTW3jyMtPTswiGwq7Ha5a3d6GpatesfZ/Pj1qtu3vMS5A1iuLTiMdmswmO410vAD8LO8CRl89mEDcZDeMUcY5FqVTqeiNOnBC0hxx5gL6el2GY6jDwPI9kagyN7ItRCCTrnJp66v7d3NwAz7OYmnJmlpJRzpxJQpZlU/Po9vZ2IYp+UxvJQYTDMVAUjb09ax1jZKM65pBTphcJngVDUYY63vL5HBifu/PxgJM3e7MbmUwaTUlCcNzd+XgE/1gSoKihi5mtVgvr66u4fNnYIHQrzM/H4fPxWFl5bMvxIpEoNE2DJNkXu0Nm7tkt5GUyaYQ4FgLjnEiW4hhkLDQ2ZDIZsH73rjt8QH/tkxzpeBRVVZHP5SCGjZ33NU1Dq16HVCwh++Cx4WKxENHjm7NZe4U8RWl3ZhWZgTyXFFCcwskZeU4KeaqqIpfPImExYSDBs1A1bWTX+EIhj3R6D/7UrOHn+hKToGgGjx49cGBlJ5PPPrsJhucQnjU3447hWEQWZnH37ucjdWIVCnnQNGV4vngiEYSmaSgWCw6t7Di2RGt2ZuSNvrbTbEqQW60hhDz95+7Haxr9PXunXvay0xHyjjryOBY0y3pcyDserfnsz91ib2+30/BsFIZhEQnHLNdXrKIo7Y5gdxQi8DmdcNAPYpwx5cijKICiXHdu2oGpu9o///M/xx/8wR+gVquB4zhcvXq152O/8pWvIJnUi5Hf//73TS/0FOegaRpXLl9FZXsPqotRLqX1Lfj9AczNLRz7WSwWRzbrPXv3UbJZ/YIXjz919Kiq4rmBpWQ93U5iqqoiXywgMeLi+iASPAsN3efQENcbY2LoqZPQ7Mlx5AHA9NQMpNzobsas0MgVwLIcksmnYsD29iZmZ2NgHCz4GmF+Xt8I7uwYb7LY2FhDKjlp95IA6BvNRHzMchf23t42WJrqOORGBUtRGBc47O4O70IvFPPg/O4Leaz/VMjb3tY/D/4x92dZAgDDc/DFotje3hzq8Rsba2i327h4cXRCHk3TuHBhDCsrj2yJQwmHdbGhIdm3LyPHCoXs/ZwdpPcx5nBM+BjPIpM5MHVjqGma6+cXLqD/PUcdceZlyuUSFKXdEdaGJfdgGXK5CkVqYvv6DeQeLBt6vuCQI6/ZlI9FURmBPLdXA6BdELGNsVPIY5yP1iyVimgrCpIW753I80clqhMRLjBmbB4boM+a8SWm8ODhPVdjtl4Wms0m7t27g8jCHGgLzbSxc2fQbEp4+NC+ubiDKBTyiMUChu+f4vFA5/mjghR/7XDkuVHfqVR0YS44pJBHHu86w+pzpzreyCDRmcSB9yycKKBa9Z6Q12xKoGnq2Iw8QehvUhgFiqIgk0kjaiJWkxCNplyP1lTaSs9UNiLwuelo6zSUmTz/UhR9Mh15d+/exV/+5V8CAH72Z38W169fxz/+4z/2fgGaxk//9E9D0zRcv37d/EpPcZQrV65BbbdR2THu/LADVVFQ2drF5cuvdN0UxeNJlMsNyLK3Z0bkcvoFMR5/OpeKphloqrducMjmtdvvWh9YrXhSyAO6FzeIjZ6y8cbfFmjGQ9n0zjM1NQ25Xker7n3xspHNY2JisvMZUBQF+/u7mJ2NubyypyQSAfh8PHZ2tg09r1Ipo1DII5U019E7DMnkFLa3tyx1uO/ubGNC4Hp2fTnJpMBhb3d7qBt5SZIgN5tgRXfmVz0LK/oBijrR0Zq7u9tgOM5wgd1JfMk4doZ8P62sPAbD0Dh7drTRoBcvjqNUKtlSIA4E9Dk4djrySNNLMGifoKWqKjKZNMYdbhYYEzi0lbapYmSz2YSqKGB43+AHOwTNCQBFeXIeilsQhwgXNHbeL23u9P16EAzPg+F52x0qsixBFK0IeaMpknWEPDujNWkSueXcPSSZkZmwGOFLhLxRzcl7+PAe+EAYXMCcIzgwNodSsdCJcz/FPLqLTkb8wqKl44SmxsEH/Lh564ZNKxtMPp9DImE8ASSZHL2QR8RGVTPvyNDU46NURgWJyhzWked2tCZpcKKGLTtT1EtRZH8RIPsMvss+hw34UfTgvWalUkY47Dvmho1ExM7P3SKf12dNm3XkAfr4knK51HP80ShQVAVsz2jNw8e4+Bm1Y86pl5LyzGJYyPv7v/97aJqG119/HX/0R380VOfsG2+8AQB4/NieSJ9T7OfMmbMQRNFUvCbNsn2/Hobq7j6UVqtrrCbwVBjL571dZMhmq2BZFqHQ0wIjTVOWNotOQDZV3YQ8cjPq1DwZsyQ6N7fHO8Y73XWG4xscRtM858Z0kslJXThq5LztFtI0DY1cAdPTM53vZTIHaLfbnhLyKIrCzEwUe3vGhDzilEulppxYFgBgLDUFRWljd9fY2giqqmJ3dxtTI3bjEaZEHvVGY6hiabms38h4QcijKBqc6D/RQt729hZ8ybinNuH+ZByNen2o99PKyiOcOZO05I4xw8WL44evb30vTsQ2e4U8/VhEJLSDQiGPVrvt+BxOIhSaiUGu1/V9LcO7N+OXoiiwnIBGw76/54tOvwJXP44mm5hJOuGDAduFvGaz2fOco2kaSqUG0ukyrl9f6dqQQJ4ry04LeXrzG83Yd34cxYw80iCRtBit6WcY+FhmJI68ZlPC6toT+FKzpq+ngTE9kvPBg/t2Lu1EcuvWDYiRMALj1pp8KJpG7PwZPFl5jHJ5NHPLC4UcEgnj1+5IxAeGoUcq5PVLJRoW1VVHni5UhAcIeX6GBg33hbxWSz/vDjuDk6IYV2P7ThLFYh40wxybkQcAfCjoyfSXUqmISOR441sk4u/83C2I2SAUMj8igDzXytxtqyiK0idaU/9+u+2ekEfi0jWT9XVNVVxpwrAbw1efGzdugKIo/NIv/dLQz5me1ou76bT5+RGnOAvDMLh08QrKWzudLqNhicxN9/16GErr2+B5AWfPnu/683hc72wgjjevksvVEI8/X2CkadpzkSP9HHnkoh3zmCPPR9MQGLpr9FPn/+ExwfSkCXlTU9OgaRrVXW+f6xvZPJRWCzMzT6OEiCA1M+MdIQ8AZmdj2N/fM1SA2thYB8OwiMecc/wkD2M7zcZrFgp5NGUZU6I7cbhTol5s29sb7JYolfRCiBUhT23JEAQB77//PgRBgNoyn+HPCIGRFWe8Rrvd1geJJ+ODHzxC/Cl9jzJI2K5WK9jf38OlS+OjWNZzJBJBJJNBrKw8snysjiOvaZ/7WmrWIQgCOM4+0e3gcG6d0448Eg9sxpVCxDOGc0/IA3RXXr1+KuQRngp59s+ZHQQX8KNQsNuR11vIu379CbLZKqrVJr73vVu4fv3JsceMKlqTFH1ZW4U89vDYziVkZLMH4GkaIdb6nj/J6VG9TnP//j2oioLg+ILpY7BiAGJ0DHfufGbfwk4guVwWGxtriF1YtKVJKX7+LDRNw6effmLD6vojy03UarVOTKYRaJpGLBYYadGaFHDNFoGBpyKgG8Vgsv8f5MijKQpBjnX9foGIctSQ9RCKZhxtujjlKYVCHnww0PWcw4cCqJRLnnNHlstFxGLHhbxo1Hf4c/fe7+Q8Fgyan3lNnut1Ic9Nsb1z3jU1zsC9c7fdGN5tZjJ6h9ji4vC2f0HQb07dHj55Sn+uXLmGttREdd9YF2Di8nnw4RAYUcDM0ltIXO4uxvVC0zSUN3dw4cIlsD3cfETIy2S8l9X8LNlsFbHY83ZqiqI9N1CTnMS6DQkl0UpBj53gKIpCkGW6Rj/ZMbjaGTRPuUacRhBEnD17HqX1LQ/+LZ5SXN8ETdO4ePFK53u7uzsQBBaplPtz0J5lZibWyVwflrW1J0gmJjodS07gEwMIhaJYW1s19XwioLkl5E0IHGhgqDl55KbAkpDXlrG0tISvfe1rWFpagtq2IOSJ3ow7GQUHB2koSht+jwl5YjwKiqYHxuAS4fvcubG+j3OK8+f12ZZW9yREcLPbkWenGw946pBLWXTJDEKgaUR5zqQjT/8d0vzxjuhRQnMCajVv77FHSbFYBCeKplJGrMKHAiiW7BXyJEmCKHb/HNy7t9v3a0CPo+N51vG5z8SRxzgg5JFjO0E6vY8xnrVlzz/GszhI79mwqv589vlNcP4QxJi1xpLg1Fmk03uuz/V5kbl16wZAUYifO2PL8YRICMGJMdy8dcPx+zHS9JBImNsjx+N+2x3I/bDDkefmjLxyuQyOpiHSg881YZZ2XcgjohxFD3lOp+lTIW9E5PN5cKHun1s+FISmaSP9bA5CTw8oddx3zyKKHESR6zTfukEulwPLchAF8w1goUMhjySkjRpVVdFqt8H12MuQ77csNCRbpdOMYUbIc7EJw24MX31Ip2y5PLxNO5vV34jhsHfmmZxynHPnzoOmaVS2jW3EKYoC5/dBjEaQvHzB8E1MI5dHq9HApUtXej7G7w8gGAxie9s7F5OjNJttpNNljI9PPvd9hmGgaaqnxDwyJLTbSaxer4GnaXBDbBBHjZ+mOzFUz/LUkect8Ug7YY48ALh69VU0K1U08t78rGqahtL6Fs6cOQu//+lGa3d3G1NTUdAW3/eS1HrOeSVJ1gpHJOpzGMEJ0CNU9vd3MTExN/jBFpmcmMfa2oqpG66dnW0wFIUxhwvsveBoGimBx+4Q8wdJTAcrmt+Y0yyP69ev44MPPsD169dBs+YFTFY8uY48Uij0miOPZhiI0Qj29vrvn7a2NsEwNGZmzMeuWGF+Pg5Jkmy5QRQE0dYbuVZLhijaOycund5DlOcgMs5fhyd4BvtDOHyPQoQRK+cEO6A5Hg2HRZoXiWIxD84FNx6gO/KakgRJsmdGSr1ehyRJPR0zsqz0/ZoQi9nvFDwKcc05IeQ56cg7SO/bFuE7JnCoNxqoViu2HK8blUoZq0+WEZy07gALTS6Comh89tktm1Z3slBVFZ9++glC05PgAvadc2IXFpHPZbG1tWHbMbtBzgmxmLm160LeKKM1rTvy+iUbOU2lUkaYZYb63IYZBhWXG/+eCnnDO/KcPFef8pRCIQ8+1L2Bjg8GO4/xCo1GA61Wq+O+O0os5kfJ5iYoI+TzWYSCUUvXVI4TIAg+1xx55LPH96iHke+7adCiaRoURUHTjLtFnwp53kqeM4Phq8/kJInTGn5T8KMf/QgAcOaMPV1GpziDIIiYX1g0LORZpbylv9758xd7PoaiKMzNLWBtzT2b8SC2tvJQVQ3z8wvPfd/n0ze2rZazcTRGaB7OuPD5jl8I6/Ua/APiGtwiwFCod+kYJ05OTfWW/R8vSQazES5fvgqKolBaMz5vcxRIhSKapQquXn31ue9nsweYmLDebNJotJ5zXjUa1m5GEokAGIZGNjtczBKZfzU1uWDpdYdhcmIerVbLVLzm9vYmJgQOrIsNA9Mih+3tzYHdytVqBQwvgLLgcKQ5Hs1mEx999BGazSZozoKQx/vQkuUTmXKQzWZA0TSEHjeebiJEw8gM+Jxub29gZiYK1qVr7Py8nhhgR2GP5wVbHS7tdgs8b6+Ytb21gekRzSKcEnlksxnDA+oV5TAhweWmH4qioSreaThzm2KpaGtR3QhkLp9ds17I3BYzM6yeJZkMIp93dnYbaQ6ws8jCOizk1Wo11Oo1jNk0kmCsE9XrXEz97dufQdM0hKbOWT4Ww4vwpWbw+ee3PNW0+qKwsbGGcrmE+Hl762TRhTnQLIPPP3dWYCUinJloTfK8arU6MvHGjhQftZNsNPp7mHKpiNCQzUlhjkHZ5Rl5ZE80bLMSzfKQDO6jTjFOrVaFJDUgRLrXPsSInlA0inmtw0JqIb3Sk5LJ4ND1EicoFAoIBKzXkoKBsGtOSLIH62Xo4Dwg5AEALwhQTdyDkkQkkhj5ImP4rvHdd9+Fpmn44IMPhnp8Op3Gd7/7XVAUhaWlJcMLPGW0XDh/EY18EXJtdHMyKtt7mJqaGRipNDe3gFyuikrFmxd3IjLOzs4/930i5Dk9IN4Isqz/DsnanqVWqyLgQTceoA+Br1WPC3nk/6F4SCwF9PX4/ebj+F5EAoEgFhYWUVr3ppBXPBQYr1x5pfM9SWqgXq8jmbQuDvh83HPOK5/PWoc2TdNIJIJDd2YtLz+CKPoRizo3H48wPjYDmmawvPzQ0PNUVcXuzhame8R8jYppkUe9UR/YbViv18Fw7sbePQvN65vPkzjPKpM5gBAOuS56dEOIhFEs5HsWoxRFwc7OdkdMc4Px8TDEQwHbKjzP2yvkKS1bb6zq9RoKxQKmRxTfOy3y0DC8e5pAEhK6RZ2PFA/GwLtJuVwCF3Bn/0YERLuc12T/kErZIeTlHI3qI8Whfk1wmqah3qiiVM7j8crtgethWe65Y9sNmY1plyNv/FAQNDNzcxg0TcOtWzcgRpLgg/a4w0NTZ3WX3+qKLcc7SXz++S3QLIvw3Iytx2V4DuG5Gdy+85mjc66KxQJYlkEoZG6fTATAURWu7RDyNFU7PJYb0ZpFhLnhmsHCLAOp2XS1BtVJHRiygZHheEgNb9b6XiZIo4jYQ8hj/T4wHGdotIfTkDX3aryemAgjl8u6Fs1ar9dsSRYRRL9rUfdkn8T3OLfxh/ffbkZrAoAo+KCaWAMR8kTRO3Udsxi++vzyL/8yWJbFgwcP8O1vf7vvY1dXV/H1r38dlUoFoijiF3/xF00v9JTRcOHCJQAYmSuv3WyidpDtvG4/5uYWAMCzrrz19SxSqdQx4Ya43pqydzYl/YS8eq2KwAhiqMwQYGjUG/Vjm2/yO1c89DvWNA1tWTpxQh6gx2tKxRIaeW/N8dI0DaW1TcwvnEEw+LSbixS57BDyRJF7znnVayaNEZLJwFBReKqqYnn5ESYn5kfSJcpxPMZSU3j8+JGh52WzGTRlGTOiu91QMz79pnJnp7/oXK/XQHPe6dwiomKjcTxm+GUnkz0AH/HWHEsC6V4l7pejHBzso9VquSrk0TSF2dmYLY48QbDfkcdZcKoehcwrHKWQp7+usSaWjnjm8jxdiqI6LoOTjiRJkJtNcAF7o16HhQh5djnycjl9j2N2hhUhmQyg1Wqj4qDDo9WSwbJc3z3M8sptVKslNJsN3PjkIyyv3O57TJLa4VThyW4hL8QyEBnaMUfezs4W0uk9hKYv2HbMwNgcGE7AjRs/su2YJ4F2u407dz9HZGEGDGe/ezx2dgGNeh0rK8b26UYoFAqIxfymRxOQSM5RCXkkDtOSkOdStKaqqihXKggPmepAHufm3DASEU2zw50faZY3nGxwinEyGd25Jka7i2IURelJIxn3HG5HOTjYB8+zPd2/ExMRqKrmiotQ0zTU63UIgvV9o8iLqNXcucfvCHm9ojUpbzjyRFHsiHJGIOKf3aMc3MDw1Wd2dha/9Vu/BU3T8Bd/8Rf4hV/4Bfz1X/915+f/+q//ir/6q7/Cr//6r+NnfuZnsLKyAoqi8K1vfQvxuLdmmpxynLGxCYRC4U7cpdNUdvYBTRtKyJuamgHDMFhfd2f4Zz80TcP6eh6zs8djMcgcLtlDIpPcJ1pTajRGMk/GDCJDo60oxzptRFHUY6E85HpU2zKgaQi41NHtJq+88ipomkb+8RO3l/Ic9YMspGIJr7365nPft6tb3SmG7YLf3d1Go1HH5MR838fZyeTkAg4O9lEsDl9wJIXuaZ+7M6HGBQ4MRWF7e5CQV/eWkHdCHXmKoiCfy/bsHnUbIaoPKO91A0neZ/Pz7u6FFxYSSKf3LMdY8TyPtmLfjZwu5Nnn0iXnmakRCXlBlkGEZzsC4rAQIe/UkecdymX9ekYiLkcN59f35nZGa4bDPvAWox+TSb1ZwY4Zm72QZRncgILvzu5a36+PwjDOOvLS6X0IDI2ITZHJ1OH84P39PVuOd5QbNz4GzbAITp3t+zhN09CW6pCrRZQ2H/Tdg9IMi+D0OTx4cNfR2X4vG48fP0BTkhA758z4mdDMJFhRcHR+YbFYMD0fD9Bn5JHjjAJyrbU2I8+daM1arQpFURAd0pEXPRSH7bqWmEGSGqBZbug9Ds3xaLVkR12kp+gxlTTLguuzzxGiERx4yJGXTu9jbCzUs2lgclK/P3TKzd4PSWpA01SINgh5guh37R5/ULSmF2bkAXoNWzl15Bnn137t1/Dbv/3bYBgGt2/fxp/8yZ90LmTf/va38Wd/9mf4r//6LyiKApqm8Tu/8zv4+Z//eVsXfoozUBSFCxcuobabdjQ6hVDZ2YMgipienh34WJZlMT09g9VV7wl5BwcV1GpNzM0dL6AT15uXuouafRx58Gaq5nMc3ThTFAWf3w+l5Z3fMXEHnkRHXjAYwpUr11B4vArVpXiDbmQfLoPnBbz22vNCHilKWZ0f4xTJZBCyLA+MWXj06AEoisLU5OiEvOlJvfjw+PGDoZ+zvb0JnqaRsmmejFlYisKkyGFnQMxgrV4Dw3tnw0cfOvLq9ZPlyCsWC1BVtec8B7cRBsyTyGTSfTtJR8XkpN6xarUYT1EUYPM20c7u9p3tLSQFDr4RNibNCBy2DbodO8VELzjyToU8AE/dC27NyKMZBpzfZ5uLYnt7E9PTEcvHIccw6jo1gizLYAYIeUedwIOcwTRNg2EYxwpPuzvbmBT6uwiNMiVw2N/bsf0zKUkSbt/+FMHJRTADHNDlzYdo18tQZQmZez9EebN/jHpk9hJUVcWtWzfsXPJLzeeffwrOJyI0NeHI8WmGQeTMHB48uIdm05lm12Ixb0nIC4d9oGlqhI4869GahFELeUSQi7LD3T9FDgU/t+ZtAWQ8wfDNkKRxstE4Wc2Ko+bgIA0hEu77HhajYVQrlU48qtscHOx3xLpuEJHPyfmyvSAOOjsceYIgot1uuRKJSxy0Yo/7MeHw+27XtX0+P7S28d8PGcN0Ih15hK9//ev453/+Z/zcz/0cYrEYNE177l8wGMRXvvIVfPjhh/jVX/1VO9d8isMsLCyiLcuQCs7b8OvpLObnzvSdhfAsi4vnsbGRR73ubhfAUR4+1Ds/FhePDw0nEX6S5J2ia6NRA8tyXefRUBQ9EhHXDGRZ3TYdgUAQStMbGw3gZAt5APDOO++hLcsorFqPcLODttREaXUTb7zxhWPv+2KxgGBQhCC4Kyz1gsRhDZrl9vDhfSQTk7ZsIoclHI4hGIzg0aP7Qz9nZ3sLUyIH2uQNsKSoEAQB77//PgRBgKSYL3TNCDx2d7f7FstkuTl0JMwoIGtxqijjVUiXv1txd4NgOA4Mz/V0I2QyB0ileneSjoqxMSI4WovL0TTN1iIWBcq2vYemadje3sCUTVF3wzIl8igUC4YicZ7+Dt3dd2mw9+/5IkOKnm4JeeS1SyXrxddqtYJM5gBnz1qfmxsO+5BKhbC25lzaAonWtBuW5R2J1lQUBfv7e7afayZFDnKrZbv78fbtW2i1ZIRnByfh1DKbfb8+Ch+MwhefwI0bH582BQxBu93G4+WHCM/PODr3N3pmDu12C0+eLNt+7Ha7jWq1aknIYxgakYh/ZK4xtTPfzvr1btT1EnJtihiYkUfBXUdetVoBzQ+/b2cPH1utujMj7KSwn96DGOvf4EN+nk6P3uF2lGq1gkqlgqmp3nNdWZZBKhXC3p6xWdV2QIRn3obGX4EnDbujr2sSgU7o48ij8FTwcwu/PwDFhNBJ6rOBgDeb941gaddw9uxZ/OEf/iF++MMf4qOPPsL3vvc9fPDBB/i3f/s3fPzxx/jjP/5jXLhgX/76KaOBzKKrpZ3NF25LTUjFEubnF4Z+zoULl6BpGh498o7NGwAePNhHMplCPH589o0oiuA4DvWGdzYkjUYV4XD3LhyKolwuJ/VGQ+/NdzQSRdtDYmn78O8djdozSP5FY2FhEcnUGPIPvTH4Pr+8ClVR8NZb7x77mSRJ8Pm8I9Qchaytn3BTLpewt7eD6Sln4nl6QVEUpifP4MmT5aG63UnRa9pC0UtSVSwtLeFrX/salpaWIFkoGE2J/MBimaIojhZZjELR+g38SYudITf1rIfjMDhR7Fl8yGYPMD7u/nw/IuRZnXuhqpq9LjLKPiEvn8+hUq1i3jfaSFzyehsb/aP+nqUTN+V2A5WmmW6ueNkoFgugKAq8i0IeHwwMbN4ZhvX1VQDAuXNjlo+lHyeFjY01x4SaZrPpkJDHOdL8ks1m0Fbatkf4kuPZWZDUNA0ff/w/EMJxCJHkwMerSrvv190Iz15CoZDD6qo39v5eZm3tCVqyjPDcjKOvE5wYA8NzhhruhoUIRFaEPP35vhG6xsi11vz1zq2ml44jb8h5igxFIcSxrjryqtWqoVQTRhAPn3ca0esU9XoN1UoFvnj/GpUvpv88nXYm5tkIJAlgbq7/eIL5+Ti2tzdHLrIrh03FDG09Yps+PIaqjv4+v+PI65FmQlMUeIZ23ZEXCATQlhuG/86KLIGmmZMbrdmNqakpXLt2Da+99hrm5+dHPvz1FPuIxxMIBIKopZ0dblo70IVCIhwOw8zMHHw+Hx48cP+CQpDlRBvTbQAAIABJREFUNlZWMj3n/FEUhVAognrdO0JevV5FONy9C8fbQp5Otw10PB7viGdeoNXQN6DR6MmcDUpRFN55+13UDrKoZ60Xo6ygaRpyD5cxN7eAiYnJYz+X5aZn3XgAIAiDhbxHj/Roy1ELeeQ12+021tYGF25I0WvCQtFLpGlcv34dH3zwAa5fv94z/mEYJkX9d9uvWKYqSkc88wJEVFSGKKq9TNRqh448n3c334xP7Fp8kGUZxWKhI6K5Cc+ziMUCloU8TdNA2ZjFTdko5BHx4ox/tELejMiDpSmsrw/vWOrsZ1zfeGmA23P6PEKxWAAf8LvawMEHAyiVipYFs/X1VfA8i9nZmC3rOns2BUmSHJvfNsyMPDNwLOdItOburr53sFvIGzuc4UuObwdbWxtIp/cQnr3smBARHF8Ay4v4+OMfOnL8l4lHj+6DZhmEpsYdfR2KphGansTDh/dtF+CJQGRdyLPHgTwMZJ9h7TNgXzynEYrFIgSGhmgg2SHKMq4KeZVqBayBpBjm1JHnOOT6LQ4Q8rhgAIyD81qNsL29BYqiMDPTfy8zNxdHrVYb+XueiG527BtJg58bznYSo9qvtiLSjOuOvGAwCGgaVINJC4oswe8PvBQJJIbfad/85jfxrW99CwcHwxcA8vl853mneB+KojA/v4B62tlZdLX9DGiaxszM3NDPoWka585dwIMH+51oBLdZXj5Au63g/PneMSWRSASNhnfcYrojr4+Q541f7TH6RWtGozEorWYn+9ht2o0q/P4AeN7em/sXiddf/yJYjkP2/mNX11Hd2UezVMHbb7/X9eeSJEEUvSzk6Wvr1/306NEDBAJhRCLHXcFOMzY2DZblOmJiP/b2dgEAU6L5Qp3I0Gg2m/joo4/QbDZ7do0NQ+qwWEbWdRRVVaGq6tBD2kfBiXfkeVjIY0URlS5CXi6XhaYB4+PemO83Ph6yIVpTtdWRZ+eMtrW1J/CzzMjncLI0hVmRx9qqcSFPg8tRdBpOHXmHFAp5sEF3Y9H5UBCKolh2JaytrWBhIQHGplmR586lDo/rTLym7sizf9/Mspwj82b29rbB0RSSNp9rGIrChMBhd3fbtmN+/PEPQbMcQlNnbTvmUSiGQXD6PB4+vIdy2fkRHS8qmqbhwcP7CE5NgB5y3pkVwnMzqNWqtr6fAPscefF4AKVSaSSFaztn441ayCsUcohyrKEidJRjUMjnHFxVb1RVRaNe64hzw8Acin6kee8U+yFRmcRx1wuKoiDGotj3gCNve3sTk5ORgY3XxLHn5CzfbpBzlx31ArrTsOuOI4+CHqHZC5GhXBfy/H49GlORjcWPKrKEQODlGHtk+J324Ycf4sMPP0S5XB76OdVqtfO8U14M5ufPoFmpouVgNm8tncHU1Aw4zlhB9/z5S6hUJOzums/75nmm79dGePBgHxzHYWFhsedjwuEIGh5xi2mahnqj1lPIYxgWbY8qeW1NA9OjQyQW0y/cXnHlteqVzppOKj6fD2+8/gUUn6yj7eIFP3PvIQKBIF555dWuP5dlqeN68yKi2N+RpygK1tZWMDkx50qHEcOwGB+bwcrK4Pkb+/s7YCkKSd4bv2+WojAmcNjv4cjrbKK95Mg7vElot0+aI68KVhA8FXN6FNYnotalizif1xujUilvZPKnUkHLs5ckqQGOs6/gzrG8bVEt62tPsCDyrpwPF3wC9vd3O12tg/CKI09zewEeolAsgA+5+1nlQ3qhwUpXealURDqdxoUL9sRqAkA06kcqFcLy8kPbjvksstx0xJHHsrwj0Zo7O9uYEPiBIrimaSi3FWTkFn5cqA4lAEyKHHZ3tm0RC+r1Gu7evY3Q1DnHZ/5G5vQxGDdu/MjR13mROTjYR6lYQHhueiSvF56dAigKDx/aG69plyMvGvVDVVVUKsPXF81ihyPPLSEvn8sizhq7H4lzLErlkiuiQL1eg6qqYMTh3x80y4OiGUO15lOMsb+/B1YQwPoHC6xiPIr9/b2Rv9efRZ97vYm5ucHJAlNTETAMje3t/jNd7YZ8vuxIJSTHcMOR12xK4Bm6755GoKih73GcgohxZObdsKhyQ3fzvQR4txpyiqvMzs4DAOoZZzp4NFVFI5fvvI4RSITl/fvmu0OuXp3q+/WwaJqG+/f3sLh4rq8gGYlEUW9UPTH8W2rWoaoKIpHuXTihcBgVxf11dqPSVhAKdo8mI6IZibR0G6VRRSxmT5TRi8y7734ZqqIg59KsPKlURnlrF++88x7YHl2vzWbT0448srZeRajd3W00m01MjA/vbrabifFZ5PNZFIv9Gyx2d3cwfuiC8wqTAofd3R1Xb1IMQer+L8p6bUKWZdBDzgUZhCK3IAgC3n//fQiCAEVu2XJcmmPRah0/VmeuSdS9mVvPEo360Ww2LXVUNhoN8Jx90ZUcJ3SGxVuhWCygWCqOPFaTcMYvQMPwc/K0p1EDzi1qCChQp2Ie9AaJSrkE3m1H3mGhIZ83H01+9+7nAIDXXrN3Btdrr01jdXUZtZr9jXOyLINxRMhjIdss5CmKgt2dLcwMkTDw42IN+VYbNUXF/5su4MfFwSktMyIPqSkhm7U+s/7WrRtQlDbCc73TY+yC84fhT87gxicfn7jkgGEhMwTD08fj/p2AFQX4kwnbZxcWi0WEQj6wBsWloxAhkOyVnIQ0wTGM+TWT546yoU7TNBQKecQ540KepmmuxGsSVy5rQMijKAqcL3Dq6HWQvb0diInYUGK2LxGD3GzaMrPXLLlcFo1GA/PzgxvkWZbBzEwUm5sbI1jZUzSNOPKs7+XJMdyoG9frdfgGnBv9DIVG3d2kOdNCXquJQOBUyBuaRkNXbE9yxNyLxvj4BACgkXdmQyVXqlDbStd5VYMIBkOYnZ3DnTvdo9CGYWnpLJLJIIJBAT//829iaclczMjeXgn5fA2XLl3t+7hYLK7HC3ggXrNW1TucernFIpEoSm1v3niV2grC0e7iWDyuD25v1dzv4NJUBXKjgkQi5fZSXGdsbALnzl1A9v4yVBdu6LP3HoFhGLz99rs9H6Npmqezsp92fnbf0D15ot+Yj4/ZW6wzwvj4LABgdbW3K0/TNOzv7WDCY+7HSYFDrV7r2glMxF/NhYHTvdAOP0dG3ewvOvpMNntQZBlLS0v42te+hqWlJSg2zU6i0N3ZVCoVwbIMAgFv7IOJoGilaNZoNCAI9sWc8ryAug0pEGtr+ny8BZeEvBkfD4aiOusYRCeOx8Z5g6agKGgeaDZzG+KeFSLuzrMkjsBczryIc/v2p5iZiSGVsvf/8uabc1BVDffu3bb1uADQajkzI49lecgGZ6kMIp3eQ6vdxqxv8LnmUbXR9+tukONubVkrSGqahhuffAwxOgYhNJqkkPDcRVQrZSwvPxrJ671obGysgw/4R+r8DYwnsbOzbav4VCzmEY8PH5vYi3hc35MUCs6LTR0hjzbfGEbTRMizpwlsGCqVMlrtNuIGY3zJ4/MuxGuWSkTIM9YYQwv+znNPsRdFUZBO78GfGK7Z3J/Qrxn9Zsk7DWmMO3NmuLra4mISOztbXRsrnYJh9M+ZakO9gDTAWG2QMEOjUYd/wAxOH03b0nhphU60ZsuYkEdm5L0MjETI++///m8AwNiYfdEepziLIIiIxuKQ8s5sqIhAaEbIA4DLl1/B1lYehYK5kwhFUYhEfBgfD2Np6ZzpIv7t2zugKODSpSt9H0dEs2rN/U1JpaqvoZeQFw5HUG8raHlkBuGzlBW1p5PQ5/PBHwhC9sDvuFWvAJqGZPL0nAcA7733E2jV6yitjTbmoN2UkX+8ildffQPBHk5OQD/fSdLoNntGIWsTxe5F89XVZcSiSYgGOh7tJhpJQhR9fbt96/U66o0Gxjwm5JH1dOt6pygKDMNCU7wTY0lExZMm5AGwzbXE8DyuX7+ODz74ANevXwdjV6MZRXWNSCyVSojF/J5pGIjF9MKb2Y5nVVX1+BUbHXk8L9oS1fLkyWP4GAbjLp1neJrGrI/Hk5XhZsN6xZEHioJ6wly+3SCRs0LYXSGPZhkIwYDpCNxcLoudnW28+easzSsDJicjGB8P4/btz2w9rqqqaLfbYB0R8jjINjVsEIjANusbfP2Qj9xTHf26GymehWBDRNjW1gZy2QzCMxcsHccIgdQcWMGHmzd/PLLXfJHY2FyHf3y0zZ6B8RQUpW3rnLxSqWA5VhN41pE3QiHPkiOPfe5Yo4AIcTGDyRRxjgh51uLUzdBx5AnGCuesEEC57Lw78yRycJCGoijwJYdr6hBjUVA0hd1dd4W8QEDA+Phw+7LFxRQURcHOjr0zQftB7skVG84JymHNwYm90CAajTp8g4Q8hu4YtdzCjCNPUxUoLfmlmZE38ErwzW9+s+v3//RP/xShUP8PU6vVwvb2Nm7fvg2KovDWW2+ZW+UprjAxPon1fWdOgETIS6XGTT3/8uVX8P3v/3+4e3cHP/ET5+1cmiHu3NnF7Ow8QqFw38d1hLxqyVXXDADUasSR170Th8zOK7cVJGwe3m4FTdNQbrVxqcdsPwAYS41h3wMdXHKNvL9PHXkAcO7cRSSSKWTuPULs3JmRvW7+0ROo7Tbee+8n+j5OEEQ0m+67ZXshSfqGrpv7pdVqYWNjHefPXRv1sp6DoiiMj83iyZPlng7HQkG/CY3bFI9oF+SmuFdsCMuynnTkubHBdxNN02wU8jjU8k189NFHAIBArPd1xRAU0E3JK5WKiEatd63bhVVHXidpw0ZHnsALqNfrUFXV9IwJTdOwsvwI5/yDZ1Y5yTm/iP+zv4tqtdK3iQR4xmltcr1qS4YgCFhaWsL169ehmnQdUaCgebCBa9SQhg63HXkAwEdCpmMV79zRYzXfeMN+IY+iKLzxxiz+7d/uoVwu9Zy5bRQitL04Qt4mghyLqENd8zRFYUbgsLW5buk4N2/+GDTDIjg5uv03RdMITp3Do0f3hjoPniSKxQIq5RKmr462fhE4FA43N9cxN7dg+XiqqqJUKuLVVxOWjyUIHPx+fiTxj8RFRzPm70XciNYkQp5RR16IpcHRlCuOvHK5BIqiwRjcK7KiH+WDdUv7wVO6Q4T8YYU8mmUgRqO2NgAYZWNjFWfOJIZuhjxzJnn4vDUsLIzmukeEvLYNjb/kGG407DbqdUSZ/p85P8NAbrUOG6/cqelwHAeO4w0JeYqsx6u/LI68gb/5Dz/88NiHRtM0/Pu///tQL0A6TcPhMH7jN37DxBJPcYuJiUk8enQfalsBbfNNipQvIp5Imo5bTaXGkEqlcPu2e0JePl/Dzk4BP/3TSwMfq7vIqI6I5ibVWgmBQBA8372T/qmQ1/aUkNdQVbRUrW/BIJkcw9auvR3CZmgduh5PHXk6NE3jvXe/jH/5lw9Rz+TgT1m/6RuEpmnIPXiM+YUzmJzsP0xeFEXUat7t/COOvG5CXiaThqK0kUyMZs5GP5LJSWxsPkatVu1atCFCWczgfAeniXAMaLw4Qp6qkk4975yfR8GLMROQ6rrOcrmAiYnRRJoNQyTiA0WZF/KKRf2zEvDbV5z1B8JQVQXVasW0MJBO76Faq+LchLvzac8HRPyfbAkrK8t4/fU3+z5WUazN1VDbMv6fw5hYAPjB/5h0wNA0FA+d59wim82CE0WwgjvRrM8iRMLIPtkwHP+taRpu376FhYUEYjFnChZvvDGLf/3Xe7hz5zMsLf0vW44pHxZZnBDyOJZDq9WyNUp9a3MdswLnqNN61ifgP9P7kOVmz/u2fjSbTdy+8xkCE2dAs6ONdg7PXEBx7Q4+++wmvvzlnxzpa3uZjY11AE+FtVHB+X0QwiFsbKzZ8veo1apotxXE4/acY+LxwEiFPDsceaOM7stmM6ApClGDzZAURSHOc7bM2jRKsVgAK/pBUcbEONYXhKooqNWqA5vlTzHG7u42GI4zlDrgS8aws73tyiiSSqWMXC6HpaVXh35OMChgfDyMjY1VAO87t7hnIPsWxQYhT3FZyPMJ/T+vvkOhr9Gou/r55AUBmoF4Y7WtN3P1Srh60Rh4Vp2amsLk5GTnH6BfEFKp1HPfP/pvamoKZ86cwdtvv41vfOMb+Jd/+RfMzc05/h86xT4mJiahaRqkov0OJ6lQxKTJWE3C5cvX8ORJBvW6vR2Ww3Lnjm4xHzQfD9ALrpFIpBNr6SbVarlnrCYARA9n0OVl70TJAUBB1gtM0Wj3aE1AF3gVWTI8+NRu5FoJgWDopblQ2MFrr30BHMcj+2C4uDGrVLb30KxU8aV3BgvterSmt97vz/JUyDtexEmn9wEA0WjS1LFbrSYEQcD7778PQRDQajVNrzMaST63pqPk84dCnocaBACAoSiEea5nt6ogCJ3NnxdQ273fDy8zNE17foaXpqrHChaqqqJSqSIS8c71gGFoBINi17mQw0BE72DAJicjgGBAvxm0Usgj85jOB9z9XU+KHPwsg5WVwfOhmk19v2K2yE6zz8fEmj8OB7lp/vz/spDNZcB7wI0H6PGecrOJarVi6Hnb25s4OEjjrbcWnFkYgPHxMObn47h582PbmixIUZxh7C9eMSwLQLOt8F6r1ZDL5zAzRKymFWZ9PDRNw/b2lqnn379/By1ZHmmsJoEPRiFGx3Dz1icjf20vs7OzCZpl4Iv3vp91Cv9YAltb9ow5INdq+4Q8f6dJyEkkSb/mcqz5PTR3eJ0l1+9RkM0eIMGzYE0IKSmOQfYg7cCq+lMsFcEYnI8HAJyoz7+yMsf5lO5sbW3Cl4wbEuT8qQTq9VrPhlcnIfPxFheNNT4sLiaxubnemUPtNB1Hng1zM0k856iTd1RVRUNqwDegycF/KOTV6+6mWQmCAFUxIOQpJOHq5aifDKymkdghwqVLlwAAf/M3f4Nz5845s6pTPAGJvWyWyvAPab8eBlVR0KxUTcdqEi5fvoof/OAj3Lu36+jNai/u3NnF2Ng4ksnhLiyJRBJlD2xIKtUCLly42PPn8XgCAs9jV2rhCyNc1yB2JL2Q3s9dlUrpDji5WoAv7p5DqVUtYjJ16sZ7FlEU8frrb+Lmpzcw9c6bjne7Zx8sIxAI4vLlVwY+VhAENBreEWqO0m9GXjq9D5pmEAqaKwjILRlLz7g5Pv7YfMElGkl01nT27HGndKGQh59lIHgwJiXO0p3oz6MEgyFkqu42BzyLIuuxhoFA0OWVjJZAIIh2Q3KlI3RY2pJ0LHu/0WhAVVWEQt4R8gAgFBINCwSEjpAXtK8Tk4iC+XzedOzXyvJjjAkcwi7H99IUhbM+ASvLDwe+XyWpAZphQZk8L9IcD6mS79yviQFzbkSa5SHLzRMfZZXJpCFOT7i9DACAENU/X9lsxlDX840bPwLPs/jCF5xtoH333UX8wz98gs3NdczPW4+varVItKb9n9+nM61aptNgnmXzMO5y3ufsXpbM39vcXMfiovG6y527n4PzBSHGrN1zmyU4uYjMgx/h4CCNsTF31uA19vf3DudOjf4864vHUFhZR71esxwvRvYBdgl5sVgADx6sOb7HkyQJNM1YcuRxh+5YIgqOgkx6H0mTe5sUz+FevoBWqzVSl0+pWADrN15DZH36e6pUKmJm5tQIYheyLGN/fxepa5cNPS8wRmJ5NxCPO5+q9Czr62vgeRYzM8bqHGfPpvA//7OKdHofk5NTDq3uKaRG07Kh8bfVaoJhmJEn70hSA6qmITggWjNw+PNazWUhjxcgGYg3Jo3QZtINvIjhHcRbb72FL37xi/D5vDPr4xRnICfqZtlcoacXcrUGaJrlC8H09CxCoVDHGTdKqtUmnjzJ4MqV4edSJZMplCsFV+PB2u0W6vUqEone4iNN05iamsF201vCxrYkw+/z9XUTjo/rxRe5Yq6j/2hevpn8fE3TIFcLmLDoOH0Zefvt96C2FeSX14Z6PH1kA3P0617I1RrKWzv44hffGWoTFI3GUas1PSvmZTJVAOj63k+n9xEJx00XXnnueTcHz5kvcImiH6Lo6+nIKxRyiDk0S8YqMY5FoYcjLxgMQm15SMg77AA+aTNngkE9akdtedc9225Ix/4u1arueguHvbVvDoetOfIEQQTH2XczFDh05Jnt+JVlGRsbqzjv98YN2vmAiGqthv39vb6PkyQJjIXzrl0wLjgMvEa9XkO9VoMYtc9pagWyjgMDTgpJauDOnc/w5puzEEVnC7ZvvDEHQeBw48aPbDneU0ee/cUr1uYovI2NNTAUhWnR2c+un2EwJnDYWB9u3/wsktTAyspjBMYXXGt+CU4sAADu3bvtyut7kf30HkS75vIaRIzpxfBe+3QjEEdeLOa3fCxAd+S1Wi3HXR6S1ADP85Y+E+ReSZIadi2rL4qiIFfIIyWYFPIETh85kcvavLLeqKqKcrkM1oQjjz105I0iavUksbOzBVVV4TcY6yvGImA4Dltb684srA8bG6uYn4+DNVg/WFwkc/JWnVjWMURRv8cjEeFWkOUmRNE38ut2tarXmwIDftfk57Va1fE19cOoI09TXq5EI8OVv+985zv4zne+g+np/jOHTnnx4TgOwVAIctneD6l8KAzG4+ai4Ag0TePKlWt48GAf8ohjIO/e3YGmabhyZbDbh5BMpiDLTTSbo9n0daN8KHClUv0v4NMzc9iXWmh7aCbRTrOF6Zm5vhe1cDgCQRDRNCnkBVJzfb8ehnajAlVpY2zMGx3dXmJycgqzs/PIP1geStCOzE33/boXuYcrgKbhi198Z6jHky7hdNrepgW7SKfL8Pv9XR1Y6fQeIhHzTREcJ6DZbOKjjz5Cs9m0XJiPhBNIp7sXrivlEiIeFfLCLINqrdY1giMQCEJx8bx9lJPqyCMCWbvhnb/FUdoNCaHQ80JepaKfV8Jha448SWo9F4NLnLpmCYfNO/JyuSwCNsZqAroLx+cLIJczN8dlff0J2oqCcy7HahLIOgbFa0pSY+Szq7pBHxYmGx7+fDnNwcEBAECMeWMmDxfwg+E4ZDIHQz/n888/RavVwnvvnXVwZTqCoLv+7t79HI1G3fLxnBTySFynbULe+iqmRR4c7Xyhbd7HY3NzzXBE2MOH96EqCoIT1t2SZmHFAHyxcdy9eyrkAUC1WtGbBWKjj9UEADFur5Dn9wu2NQwkErrg43R8nyRJ4C3e69A0A5blRubIy+dzUFUVKd7c7zp1ONIgmx3+WmKVarUCVVXA+Yzfq9AcD5rlUCy6n2T1MrG5uQEACIwZq8FSNA1fKoGNQyf6qJCkBvb3dzuinBHi8QCiUT/WTTTBmIGmaQiCANmG8T5yq+mKaYoIc4EBjjzi2CPCn1vwPA8YmElIojVHHVnqFCc3O+WUoUjEk2hW7C1uNw+FwUTCujX7ypVraLUUPHxofUNqhNu3dxCNRvvGPB6FRHCWTYpMdkBeu58jDwCmp2egaBrSFgqF/JGb26NfG0FWVRxIMqanZ/s+jqIojI9PQq6a+x2H5y6B9YdB8yJSV99DeO6S8bUe/o5PHXndefvt9yCVyqjuDe4wT1w+Dz4cAiMKmFl6C4nLx+Maj6KpKvKPn+Dixct93ZvPQoS8/X33Z1h2Y2+v1FUY1jQN5XK5M1vKCwQDkZ4zDVqt1kiKXmYg56d2l4iGYDCEtix5Zj6bIjfAspwt8WAvEkTIazW86xjq5sizS8hrNFqdGNylpSU0GtYK0iRa02hKgKZp2NvbRSxirRmrG9FIEvv7u6aeu7z8GCxNYcEjjrwwx2Bc5LH8+GHfx9XqdVCeEPL035sdgsyLSiaj70sEjzjyKIqCEA131jUITdPwySc/wvR0FLOz5iJWjfLee4tot9v47LNblo9FZsuwjgh5T6M1rdJqtbC7u415h+fjEeZ9ApqybFh8uXv3c3BiAELUmPvCbgITC0in95DNmmvSeJkgf0OfS0Ie5/eB5fmeDXdGKBRyHfHNDkhEp/NCXgOsDWkCPCeMzJFHrgEpkzPGEzwLCsbc3VYhf0fWZzw9hKIocL7gSGYmniQ2N9chRsJgRePv/8BYEun9vZGmNmxurkPT9JhMM5w9m8TGxurI0tBE0WeTI0+Cz2eP09kIRMgLsv0lIh9Dg4L7jjwd43Ulj07nMIwtQl61WkU6ncbu7u7Af6e8WMTjCbTK9kYcyJUqWI6zJRZsYWERPp8Pt2+PLl5Tklp4/PgAly9fM2R5JuJZueyekFcpFw/X0r8ARwSzbcl81ODFoK/v10bYk1rQnllXPyYmJtCqFk1dtCmKAiv6wQejiMxdNmVpbx6KiKezILrzyiuvguN5FJ9sDHwsRVHg/D6I0QiSly8M9feo7qXRqjfw5ptvD72mWCwOlmWxv28uZs5JNE1DOl3p+n7S58loYD0Qy0ZgOa7nJrbdapka0j4KyLq6FfmIw8orrry2VEcwFPLsnDinIH+HVt0bf4ejaKraN1rT6ow8n497LgbX57PWURgOi1AUFfW6MeGmUimjXq8hFrO/OByLpXBwcNBVUB/E8uMHOOMTwHlovtt5v4CNjTU0m71v7IvFAlgTHet2Q+KvejVinAQymQPQLAs+aF9x2ipCNDx08XV3dwd7e7t4993FkV0fZmZimJmJ4ebNjy0Xy8jnnrYwu6oXZB6WHY687e1NKKqK+RE1DZDX2dgY3lnQarWwsrIM//i863uFwPgCAODhw3uursMLkM+yW9GaFEVBiEVsceTl884Iefm8s+JNtVqFKFh3uwiCOLJCdjpNhDxz+z6ephHluZEKeSQW04wjDwAYMYhC4TRa0y4URcHa+hMEJsZMPT84OQZN07C+PpqoSkCfj0fTFObnzZk/FheTqFQqyPcYnWE3Pp/ftmhNNxx5JKUlMGAPRlMU/CzruiPP6J6TOhT93BxzZSemW95+8IMf4B/+4R9w8+ZNlMvDFT8pisL9+/fNvuQpLhCPJyHX61Db7aHnUw2iWa4gHk/YcmNW5GN/AAAgAElEQVTBMAwuXryCe/fuQFFUMAOswHbw4ME+2m3FUKwm8FQsKJXd6y4qlXOIRmMDnRyxWBwBvx+bjSbeiZnbgL0dDeB6voKmquKnkhG8FTW/2d9s6BfFmZnBQt74+ASUVhNtqWZ682gFuZJHJBqDIHgj3strcByHy5eu4v7j+5hZesv2Ye/F1U1wPI8LF4Z3U9I0jVRqzJNCXrksodGQuzryZFkX2jkPRQSwLA9ZlrsOq28rbXAmB7U7DdvHkReL6TcQrUalM4DdTdqNCsZtcLS/aMTjSVAUBangTeesVCpD0zSkUs/fJFcqFfA8azl+ShQ5NJtFfPTRR4dfW3Pikpl91WoZgcDw7+u9Pb0pzykhT1UVZDJpQ4kHhUIe2VwWb4+543LoxfmAiP/OV7C2toJLl64e+7mqqiiXSgjHZlxY3fOQ/dJJnkmTyRxAiHirSUKMRrC3vIZmUxq4r7x582OwLIM33zQeC2+Fd989g+997xZ2d7eHarjrBbn+MrQDjjyaee41rLCxsQ4AmBuRIy/KMghzLDY21vClLy0N9ZytrQ202y34E+6PQuF8QfCBCFZXV/DlL/+k28txlVwuA4bjwPrdm5krRMLI7lgT8lRVRbFYwOuv27cPEEUOwaCIQsHZonutVkXShs+FIPhHVshOp/cQ4zkIFupc4zyDtMnEAzMQEc5soxLnC6JwMJpYxJPAzs4W5GYToRlziVGB8THQDIOVlWVcvHjF5tV1Z2trHdPTMQgmZ0OeOZM8PM7GQBODHfh8PlQr1ptN9WjN0TvyKpUKKAD+Ic4zQZY2PZ7BLjRNM2avo8jznFnPqDF1Nfj93/99fOMb38B//Md/oFQqQdO0of+d8mJBounkin2uvFalhnjMviLk1avX0GjIWFkZTWTHnTs78Pv9mJ83NnOApmmMjU2gWDQ+aPholq/ZbN9iMYuJiamBj6MoCufOXcRKvQnV5OeWoiiEWQYpnsPbsaClwsjjmoTxsXGEQoMLl6T4J5dH031zFLmcx5SBAuRJ5Nq119CWmqjs2huJq6kqSutbuHzpKjjO2GdkfHwSOzvmnJxOsrOjuyO6OfKIy8NLWd8cqw9U71Ysa7XaHcHMaxBHXrdufXIdbNW9MUOx3ah0xMWTBM/zSCRTaOS8GbXTyOpFi8nJ56+xlUq5I5p5CRL1WTEYn763pycgxKL23xTHDyPgdneNpSwsL+tz6M57ZD4eYf7QIUjWd5TODBnR/QYBmhNAM+yJnkmTzWUghK2nhdgJWU8u139PK8syPv/8Fl5/fQZ+/2hd+m++OQeOY/DJJx9bOo6TjjxyTEVRLB9rY30VYwIHvwPr7AZFUZgXeWysPxl6j/rkyTJAUfDFvTGv25eYwtr6qi2//xeZXC4LPuxus4AQCaFeq1ma71Yul6AoKpJJe69diYTfUfeMpmmo1exx5Imif2SF7PT+LsZ5a+ebcYFHLpe1bU7oIIrFPFjBB9pkVDLrC6IpSSd6bq+dkH1ocNJcYhTNMghMjGF5wNxnu1BVFTs725ifH25MSjcmJsIQBBbb25s2rqw3Pp8PrZZd0Zqjv28sl0sIcSzoIa5PEYZG2eUED+M1uxPuyPvwww/xwQcfAABEUcRP/dRP4erVq4hEIqA9FGdzij3EYvqMBblasyUGQtM0yNUaYpfsm91w9uwFcByLu3d3cPGis3GGiqLi/v09XLnyuqn3+8TEFO7fv2v4edNTZ7C7t/7c10ZRlDbKlQLemHhzqMefv3AZn9/+FLuSjBmfezNnJEXFRkPG0heG6/4hs+mkcg6B8Xknl3YMtS1DrpUwNfWlkb7ui8a5cxfBCwKKq5sIzwwWloelsruPdrOJa9deN/zchYVFfPbZTaTTZUxMeGM+DgAsL6fBMAxmZ4+/l4kjj/XAfCUCERVlufmcmKppGtpK27PRmlyfaM1oNAaAQqvhvpCntltoNyXE4+ZvbF5kpian8XD1sdvL6EojXwDDsEgmjzryygiFvDG37VmeCnnGnMg7O1sIhaLgbJgxc5RgMAqW5bCzs4UvfGH4eOTl5YeIciySJufHOAVLU1j09Z6TR2IsvRCtSWbSlEon05GnKAqKhTzGZr0hfBCeCnkZTE31bhK7d+8Oms0mvvQl4/cHVvH5eLz++gxu3/4U//t//wx43ty5oePIcyRak8zIs+bIU1UVm5treHXEYum8n8eddBGFQh7x+OBGnidPliFGUqA9Er3uS0yhtPkA29ubhhthXyayuSyEiLvne3JOyedzfc8p/SBiWzxu7/8lkQhibc05IU+SGlAUBaINzTM+0Y/tnWrXBBI7abVayOWyuBq31mQyIXBQNQ2ZzIHpv7sRcvlcz/l4mqahLdWhtmWUNh8gPHvp2O+Q8+vN24VCDj6f+6kFLzorK4/hTyVMzccjhKYnsfvjWyiViohEnE3AODhIQ5ZlS0IeTdOYnY1ha2vwOBc7EEXr0ZqapkGWmxBFd4S88ID5eIQQy2DXZSGv1W6DooffL5IUMDtmJXsBw3e83/3udwEAU1NT+Nu//VvMzJyeWF9m9AImINsUHaA0ZSitVue4dsDzPM6evYA7d9bxcz/3hqObqZWVDCSphcuXj0ckDcPExARu3foxGlINPgObyPPnXsXDR59CbjXx6rV3cf7sNcOvXSrnoWlaR+ga+JrnL4KC7oZzU8hbrUtQNW3oqESeF5BIpiC54MhrHsamjmKD/CJD4jXvPbgLdekt27qvi6sb4AUB589fNPzcxcVzAIDHjw88JeQ9fnyAubn5rg5DVVUBwFMxYGQtZG0E8jXjnaU+B3O47m7d4izLIhyOoO0BRx4RE4lL8KQxOTmF27c/RVtqWroZdYJGroDx8YljRehqtYyZGW85xQBzQp4+H2MNkxMLjqyJpmkkE5OGZkEpioLVJ8u4FhA8dS4knA+KeJTOI5fLHov2IbOAvCDkAfpMmkHOr5eVYrEATdPAR7zlyOOHdOTdvPkjJJNBnD1rf+TtMHzpS4u4cWMDd+/exptvvmXqGIpCojUdcOR1ojWtFXD29/fQlGXMJ0b7mV3wPZ2TN0jIazYl7OxsI7po/F7RKXxx/d5zdXXlxAp5iqKgVCwg5XKzwFMhL2tZyLPfkRfAp59uod1ug7VppMuzkChMO4rkguhHu92CLDcdHaeRyRxA1TSMC9bSV8jz0+m90Qh5uSzYQPdzVXnzIdp1fe+ZufdDQAMi85efewznf1ZwPq03W6HRaGB7exNjr1mLxAxN6+eulZXHhprtzEBcdGbn4xHm5xP4v//3MVqtluG0JqP4fD40ZfNOZ0CP1dSPNfpozXKpiDF2uP1XhGNQLZUdO1cPQ6NeB80Nfy6nDxtQXxaXr2FL0fLyMiiKwm/+5m+eingngFAoDJqmIVftidYkx7FTyAOAy5dfQbFY78TQOcXduzvgOBZnz14w9fzxcf1Gxmi8JkVR8PkCiITjuHDuVVPFKvKaZA2DCAQCmJ6exeOatQuSVR5XJQi8gLm5haGfMz01A7ky+vi15qF4aGS2z0nl2rXX0JZl1PYPbDmepmkob+7g8qWrpjYU8XgCsVgMjx+PbhD4IKrVJnZ2ilhc7H6+8fv1TV6z6Z0NCVmL3//8zT3DMOA5Dg1F7fY016kfCni9bu4TiQRadfdns7Vq+o1vPO581r8XIefWRs5briFN0yDlC12LI5VKxZPRmoLAgedZQ9GamUwajUYdYynnrnFjqWmk0/rrDMP+/i6asoxFv/fEUgA4c7iu9fXVYz/LZvXrH+k8dxsuEEE2lznWiHESyOX0eH6vRWsyHAvO7+usrxv5fA7r62t4550zronZi4tJpFIhfPrpDdPH6ERrOiDk2TUjb2ND/xwv+EfbSDImcBAZBuvrg5scdnd3oGkqxJizKTVGYHgBQig2sogzL1IsFqCqqulmAU3T0KrXIRVLyD54bDoejA/rInQ2a3zUByGXy4BhaMRi9habU6kQNE1DoeDMPXy5rO/jfTY0z/gPj1EuOztfPZ3eAwDLQl6CZ8FSVOd4TtJut1Epl3rubWqZzb5fA0+FvJPaXGQnjx7dh6ZpCM9a27uL8Sj4YMBUuphRtrY24fPxSKWsfVbn5+NQFLUzFsBJfD4fFKXdaUoyA3H0uRWtGR5SyCOPM5rqYif1Rh2MgdQBpiPkDXd/6XUMC3mkW/3iReOOh1NePGiaRjgSdUDIs9dNcPHiZVCUPr/OKTRNw507uzh79gJ43lxUCZmdky/YI14YIV84AMtyhoa9Xrh4GTsNGbW2OzMNNO3/Z+/NYtza03LvZ83LY7lcLpdrsGueU5Vk797wHcJ0NnxA0zoIpANb+iQECImr5gaE1JeISwSXXAISEkitI9R8HNF089Gb5nSHHnayk+xMlaTm8jzPXstew3fhWk5SqfKwBtuVqp+0teXE/vufKnsN7/M+z6viZVXE0tJKT1E7U1PTaNTKkPsscIjFDOwOR1ez/K468/OLIAgCZZOEPCFXgCSIWFxc1r3GwsIKdneHp4i5u9v82SwuLp379w5H8+J2mIQ8QayB5/lzv68OhxPlIRXytH05necXWPz+CTTKhYHnqtfLTQFrfNzf4ZnvJ9PTM6YeN8xCyDePPzMzobf+vF6vQxTFlvtt2HC7bT3NeNGKyJYKef5pACqOjg572tOczXiEnCAr4DgOH3/8MTiOg2DC8WqcpWGjqHNdhul0CqzdrXuGjNmwzhFIjYblhclhRCsWDpuQBzRdeZk2c6OePXsMAPjgg2C/tvQOBEHg9u0ZHB4eoFLRl+LyOlrT/O+Ddk1iWMg7PMAIQ8PD9Pc7SxIEZnkGx4d7HZ8bi0UBAJx7uGbpsi4vIj3OP32f0MQp1qmvMJ15/gr1YhmyICJ89zNknr/StQ7FMGBsvCGxLJ1Ow+dzmj5Wx+/XxBv9ImM7NCHPbjdByDtdo2BxvFw8HgNNEBgzGB1OEQTGOQbxuPVCXi7XTIHSxLizKGeEjrOPAYCkWdCcDdmsNZ+Fq8STJ4/AOuyw+401gRIEgZG5IHZ3X0AQrK09xGJhhEKjhpuTQqFmzTkaDZuxrbZoztxGo657Den0tVa6fM9DEASI9XrPQl6hMLgmZ0GotVx23XDlhbxQqFmk6KWD95rLzahnFI3ScDvynE4XgsE5PHkSNXXdN4lE8sjnq1hfv6F7DbvdgdHRMWQycRN31h2ZTBwz08GeLrpXV9ehAgNz5cXEBooNCctdxmpqTE83ixlC4eIOZisQCykEZ0JDGe81bHAcj8nJaVRi5hTkNWff3NyC7jUWFpYgCA2Ew4PN/NZ4+TIJjuNan+ezsCwLhmEgDJGQJ4q1C2+QnS4XygNqCuhERZLBMsyFTRp+fwCyVIcsDPbir17Ow+MZ1d1Mctmx2eyYng6iFLG+ENELpXBzP0tLbze5aSKZyzWcQp7LxfXUTXl0dACbzQGn07r44TFvACRJnutgO3dPh/sYZRm4TSisC4qCO3fu4JNPPsGdO3cgmNDUQRIEZm0Mjg7eLcAnkwnQjuFp/GEczZknmlPwKlEul0AQBGjb8H1XGbsN5Tbf06dPH2N6ehRjfY57PMv29gxUVcXz5091vV6SJBAEYbo4AKAV4W6kU74ZLbyPWROaBvQQsnNIZdIdhdJYLAKas4Pm+h/N1Q7WPYZyqahb6L3saMIZ59IXR1k4jrR93AuM04F8Xr+Ql8mkDDtlzkNbs50D2Qha0dl+wey2XnjtyLO2kB2PReHnmNYIACMEOBrxPjiT0unm7491GLtWpO1upFL9reW8bwiCgFevXsA9FzSlPuWZD0GWZezsPDdhd+ejKAqSyQQmJ43fa4yM2GCzsUgmrU9c0qI7jVxnaK+1Ogb0LPl8s1F4pMt7Ka2ZSXtdv2k0GpAlqSchT3tutXpFhbyvfOUrUFUV//mf/2nFfq4ZQkZHx8xz5JXKYFi2FQlnJuvrmy2xzQqePo2CIJrilhFCoVmkM/G+OjtkWUI2l0IwFOr85DeYmprBiHsET4qDOeA9KVVBEkTP4mnTtUFCyPevGCXXRdTLeQSDc317z8vO/PwCqqkMlHPmkvVKOZ6Eyz1iaHbY0tIyCIKwtCGgWxRFxbNnMSwsLLV1o9rtjuFy5Ak1OBznFymcThcqymAdbRdRlpWWw/E8/P5mRJVYHmykY6Ocx8TEYOerDJrl5VVUUxlIgrGB4mZSCsfgG/fD43l7+Lsm5A1jtCYAjIzwXTvyVFXF/v4uxn1Tljar0DSNsbEA9vd3u9rT0dE+Znlzbnh5ksTdu3fx9a9/HXfv3gVvkqAwZ+OQyWXfEk0VRUE6kwLr8LR5ZX9hTwXaVOrqCXmVSgU0P5xzFmmeQ6V6/n1YsVjAyckRbt4cfKT79LQHXq+j5RDsFVmWLHHjAW9Ga+q/3sxmMyhXypgd0Nzw13PyDts+LxqNgHUN3xxdzSEYvaKuvHw+B4IkwDj01UCUM27Ss497gXU5kdXpyFMUBdlsGuPj5ruXHQ4OdjtroSMvD46zmTLT6bUjzzohT1VVxGJhTBqM1dSY5FiUKxXL4/A00YQxeH3DOj1IpvpbM3vfePHiOWRZhme+txrgRdj9PrAOO54+fWTKeueRzWYgSZIpQh5BEAgE3H2JlGVOYx6NCHnSgIQ8be5pt87fUYYGAQzMMas5oWm++/MpQZKgOZvlzRf9ouc71N/5nd/B8vIy/v7v/x6ff/65FXu6Zsjwer1oVGuGLhg16sUyvKNjltwor6w0BbZnz6w5UD97FsP0dPDC6LVuCQZDqNUqqFb715GYy6WgKDKCwdmeXkcQBG5s3cJuVez7bCtVVfGkJGBhYflCYeAiWJZDIDDZVyFPKDTfKxTq7Wd8lZmbW4Aiy6imjOXfq6qKSjyJ+bkFQ8cWh8OJ2dl5PHpkffxCJ46Ps8jnq9jY2G77PJfL3ddjSScEoQKX6/xjpMPhQlka0mhNSYbzgn0DTUce8DrachCoioJ6Jd8SFa8qy8urgKoOjStPkSRU4kmsLL8bOa8VS4Y1WtPl4rsu6KRSCZRKRUwGrD/HBSZCiEYjqF4gXmik0ylUqlXT5lXxFAlRFPHpp59CFEXwlDlC3qxdK8C/jtcsFPKQJQmMwY51M6FYGyiGvZKOvGq1KeQNIzTPQRSE1niLN3n+vDmrZnt78HPrCYLAzZvT2Nt7qSt2S5KknmL0e0ETCCWpoXuN4+NDABiYI2+KZ0ERBI6PL56TJ8syUqkEWPcQCnmuppAXjw++WW4Q5HJZsA4HCAscp73COh0o5PO6Rgnk8zlIkgy/v7MjT1VVFAo1JBJF3L2725UgMz7usqyZpFDIt5x056GqKqq1MgrFLF7uftF2vxRFg+dtlkZrlkpFVGs1TJrUrKSto8XvWkUqlQDDO3qaX3UerNMDoVa7si5eM3jy5BEYuw2OiXFT1iMIAu65IF6+3IEgWJPYlUw2k8vMEPK0dRIJ6wVhTXyTjAh5p9co/RfymoKct0tHHkMScDN0SwDsN5rDnelx3inNOy2bwdpver6S4DgOf/M3f4P19XX87u/+Lv7iL/4COzs7EMXh6Yy+xlxGR5sX3mLJ+Em0US7D67Ums9/vn4DH47FEyCuXBRwfZ1tioRE0MS2d6V8RUnuvs/N7umFr6yZkVcXzcn9dPzGxgWy9gRtbN3W9PhSahVhIQ1X7IxwI+RQIgrgwBvGad5mdnQcAlA3Ga9aLZTSqNUOxmho3bmwjkSgikdDXrciyVNvH3fLFF2FQFIm1tY22z/P7A8gX0kPRrShJEoqlXEv0OovT6URVkiAPwV7PUpbVtk0aDocDdocD9dLghLxGpQBVUS78+V4VpqeD4Hh+aIS8ciwJRZbfidUEXsfQD6uQ53bbIIoi6vXO8xx2d18CAAIBc7p62zEZCAFQO7rytPjNQTlkumWKZ8GciQvVHAfMEEVrEgQB2u62zA0xzFQqZZDccH6OaL55/DhP2H769DH8fjcCgeH4HG1vz0CWFbx40XvsVqPRAEVa48gjTx15jYZ+Ie/o6AA8RcJvkjumVxiSwDTP4ujwYiGvUGiKM0Yj7ayAYjnQrLHZbJeZXD4LxqkvVtNsWJcDiiL3NCNXQ3NbTUx0/ozdvbuHdLqMclnE//pfn+Pu3c4zHgMBd6uQbzaFQr7tfLxXu1+gXC5AFGv47N6neLX7Rdv17DaXpUKeJrgFOHOaB7R1rBbTm7Hhxo9BWmJBP2IR30cqlTJevHgGz8KsqSaK0cU5yLKMJ0+sceUlEs3v/8SEOdc1k5NuCIJguRPV3GjN/jYMZTJp2GkKth4aGL0MZVkMcie0SE+6x5hk2q7fjT5s9Czkra+v42d/9mfx6NEj1Ot1/PVf/zV+4zd+A7du3cL6+nrb/zY22hckrxlOvN5mV1+9aEzIU1UVYqncWs9sCILA6uoGXr5MGopOOY9nz+JQVWB11fhneGJiEjRNI53uXxEylY7B7R6B2937RdX0dBCeEU/f4zUfF5uxmhsb+mYSBoNzUKRG3wrvQi4Bvz8AbkgLQcOI3e6Ad2wMtYyxE2r19PXBoPEC88bGFgDoduVtbk61fdwNqqri0aMIFhaWYbO1j+SbnJyEKNZQE8yJPzZCoZiBqqqYnDz/3zw+7ocKICnqL6RZQUNRka43MD7e3uk2NTmNemkwnWcAIBab7z05OfgItUFCURSWFldQOolBNWGGmVGKJxFQNH1uI4E2d8vhGM6Zhi5X83zVTTFvd/cl3K5ROPsgPI15A2AZDq9evWz7vEQiBo4i4esyCmZQUASBSY5BPP76uk8Ty1j7cBXcGbu7Nd/mKlEZYkcexWtzPd4+z0uShOPjA6yvD09zx+zsGGw2FgfnzITsRL1eB2VC5N15EAQBmmbQaHRuWriI48MDhHgW5ADjV2dtLKLR8IWCpNYdz5gwA8wKaJtrYB38gyafzw+PkHe6Dz3zjVKppqjSTfPA06fRto/PIxBwo1KpoFIx/74mn8/Dbr/4uxGJHrR9fBa7vV9CnjnNAzaKhIdlLHXkKYqCVCoJ1mk8Npx1jQKAZcLu+87Dh/ehKAq8K4umrmsfHwPvGcG9ez8ydV2NZDIBr9cBjjPneiAQGGmtayVaooCRkTGaS9qqdIKLyKTT8DK9vecYQyM7oMa/XC7bjMrsIVoTaF6D6HWjDxs9C3mqqrb+O/u4m/+uuXxoDrq6QUeeVBOgSHLL4WcFKyvrqNcl7O6aW4R49iwGp9N5YYG6F2iaRjA4i0SyP/F9qqoimQxjfl7fSbwZr3mzr/GaqqriSVnA4uIy7HZ9Nz2zs3MAgFrW+os/VZEh5pOYm5u3/L3eN8Z9ftSLvXeEvolYaHZYjY35DO/H7R5BKDSrW8i7c2cRPp8TTieH3/zND3DnTu/fu0gkj0ymjM3N9rGaABAINI9JudzgC6/aHrQ9nUVzBIcF/YU0K4iLdSiqipmZ9m7aqakZ1Et5qCbMdNSDWMqAomiMj/sH8v7DxNbWTTRqNZTjg40AVBUFhYNjrK1ugGXfFetqtSpsNhbkEERpnYf9NPKxUwyeJEk4ONjvixsPAEiShN8/g93dF23vHdLpFMYYeijnmp1ljKWQeSOyMpNJg6RoUD3ehFoNY3ejUMhDMiFO/zLRaDRAWiQiGUXb11nxJhaLQJJkzM9bd1/VKyRJYG7O24qh7IVGow6Gtq7pgaaZrtzH51GtVpFMJxEasPt31sZBVhSEw8fn/r3mdqPbiBWDhLY5kbmCQp4syyiXimB1zsczG21On55ZQYlEHG63DXZ75+9qvS63fXwer4vu5t6/i6JwOsf74u/G2ejdTlG8DocLhYJ1DcPxeASjLGNazDcATLI0YlHralDpdBKNRh3ciPF7coqzg+ZsiEQGP/LisqGqKu7d+xHs42Owec2dxUwQBLwriwiHj1vuOTPJ5TLw+XqLTGyHtpbVTSSt+xUD9yTaS/utm2QyzfupXhhjaVSqVV1R6kbJZjNgeCcIordjI2NzQVFkSxsw+kXPdyxf/epXrdjHNUOM3e4Aw7IQDTryxNNivVWOPACYn18ETdN49iyGtTVzOlRlWcHOThwbG7dMK8YtLi7j3//9WxCEKniLizj5QhqCWMPi4rLuNW7cuInvf/8/8axUxYce806sFxER6sjVG/i5G/piNQFgdNQLz6gXtWwMnrlNE3f3LkIhDUWWsLCg/2d8VfH5xvFq7yVUVdVdjBWLJbjcI2BZcwosm5vb+Nd//d9IpUo9D3MnCAIjIzaMjNhw586Srvd/9CgMkiSwvt7ZjRoITAIA8vk0pqcGKyTn82mwLIvR0fOP8V7vGGw8j3Ctjo/MvacwRLjWLOx1ih6enJyCqioQyznwJtyg9opYzGAiMNn3Lr1hZGVlHQzDIr9/BNfU4Nwo5VgSjZqArQsioGu1Gmy2wcSwdYPd3txbrdb+Juz4+BCNRh2Bif4IeUAzXjN8fw+ZTBo+3/mzPTLpJIJD7sbT8LEMHqQKEEURHMchk0mBsbuHToRkHG6oqopcLnulmgYoihraDl2teUSb86ZxcnIEAJif7//5qB1zc2PY2XkKQaiB59unCrxJvV5/599oJkaEvNZ8vC7ECysJnb7/8fHhuQ2a2WxGV5d6v6DtLhSSR1AUZWgbXKygUilDVdWWgDZotH0UCr0LeclkHJOT1jnztbWTyYTuJuTz0Aq3DhNFbofdBVEUez7WdUs0EsaUSa4kjUmewU463boWMRtNdOPdxs9LBEGAdY8hfC3k9Uw4fIxUKongT/+kJeuPLs8jdu8h7t//MX71V3/N1LVzuSyCQfPmwY+M8KAo0vJYZ01861VcehPttf0aDQQA9bqIYrGAMV9vx/Wx0/uvVCrZGh3VLxKJuK74XtbZfE0qlbiwXnVZuBbyrukIQRAY9/lRzPd+sfcmYr7pmvH5rCsMsCyL+flF7OyYF1t5fJyFIDSwsoodQHgAACAASURBVLJm2pqakJdIhjEbWjFt3fOIJ04AwJDIND0dhHfUiy/6JOR9UayCIklsbm4ZWmdxYRkPv3gIVVUMnVQ7Ucs0Iyrm543PaLtqjI35oEgyGpVqK+qlV+qFEvwmuPE0Njdv4l//9X/jwYMT/NIv9TcSWlVV3L9/jPn5JTgcnX8eNpsdIyMeZHODdSYBQDaXxMTE5IXFGYIgMDMzi0i4fVRNvwkLdbicro7Rw1qkpVjM9F3IU1UV9WIGU/Mf9PV9hxWWZbG2toHnr55j5qc+AjGggmB+/wgMy144P1cQal11rQ8KbW+1Wvvo7N3dlyAIEoGJmX5sCwAwGZg9fe8X5wp5kiQhXyjglnc4nSdn0TpdM5k0pqamkc3lQPc4pL0faJF8V03IoykKYp9SJ3pFvSBq6fj4CKOjdoyMmF9ANsL8vA+qCpycHGN5+d3ZoRchiiJo2rrGB5qiDQl5JNGcUTdI7BSFcY7B8dHhuX9fKOR1dan3C8bmhKIoKJdLusY9XFY0EWlYhDyKZUHSNIrF3lwJWmzi8vKcNRsDMDJiA88zpjvy8vnmv9VuN0+E1GI68/k8AgFzj8OCUEM2l8UHvvbfE1VVUZRkiIqCH+fK+MjjaNsgNMWxUNGck6fNqjeTaDQMkqLBOM35fnNuH9L7zZFO5yVfXHM+9+79GCRNw7NgjcDC2Hi4Q9N48PAefumXfhW0SYkGoiigUqlgbMy8GGKSJOH1OpDL9ceRZ6Q/T/vu9tORl0jEoaL3CN+J05mbiUS8r0KeLMvIZNJw6zBqsE4trjdx4b37ZWE4r/KuGTr8/gnUC8YGhAr5AmiagcczatKuzmdpaRXJZBG5nDkz3XZ24iAIY0LYWaamZsBxHOKJ86NRzCSeOIHX64PHo98CQxAEtm9+gP2KgJLJ8wfPoqgqHpcFrKysw2YzdsOzsLAEuSG2ZktZRS0TQyAwpTsG9CozNtYs0IoG4jXFYulCx4YePB4P5ubmce/ecd+jDQ4PM8hmK7h5s3vBJhSaQyodG2h8tSxLyOYSCIXm2j5vJhhCUqijPkTOh4jYwEwX8xW93jGwHAex0P88eKlWgtyoY2rqas/He5Pt7duQBBGlyGBmZyiyjMLhCdbXNi8sLlSr1ZbrbRix2TQhr70jb3f3BcZ9k2CY/sXKuVweuJwjF87Jy2abMznHLo0jTxPymhHE1WoFFMsPckvnou2pWu3vXORBQ9E0VGUwscmdUE8FxrOFspOTQ8zNDU+spkYo5AVBED3Ha4qiCIaxMFqTYSGKgq7XHh8dYIpnwA6BiyzEszg+PjzXQVoul0AO4XFFg2KbYkc3c1nfJ7QIy2GJ1iQIAqzD3rMjL5NJo9FoYGrKulgNgiAwOTli+hw37Xdgt5vXQKOtZUVMm/bvn+LbX0P+OF9BtiGhIiv450QOP863ny2orReLRczZ6BnC4RNw7jHTmgm4ER9UVbVsv+8jtVoVj774HJ6FWVCsdfcgY2vLqFWrePLkkWlraq65sTFzG928XrvljjztnGwsaYM4Xau/Qh7wWpjrllGGAkuSSCTMM9B0QyaTgqLI4Jy9awoUy4Pm7JZEwvabwV+NXnMpGB/3o16pQq63zwpvh5AvwucbtzxKY2mp6XB78cKcL+iLFwlMTwdht5t38U1RFObmFpE4dctZhaLISCbDWFoyLkJub9+GCuBJ0drizmFVRKkhYfvmbcNrLSw0IzlqGetOMIosQcgnTPkZX0VaQl5B3029JIqQBNGU+XhvcvPmh0gmiwiH+5uhff/+MWiaxsZG927UubkF1GpllMvGXNNGyGQSkGW545zImZkgFABRQf+5xExqsoK02OgYqwk0O/pmpoMQC/2fRyjkm+8Z7EJwvCosL6+C43jk9g8H8v6lSBySKGJ7++JzlSBUW2LZMKKJjO3mG1QqZUSj0ZZDrlsajWZs08cffwyO49BoiD3vLxCYxcHB7rnz2jRBzHdJhDzv6T7T6TRUVYVQq4HsozDaLdTpnjq5NN83aIqGYoIjT6433vrcG7lv0jjPkVeplFEoFBAKDV80EM8zmJhw91x4rdWqYC0UoTiW1/W5lmUZ4fAJQgN242mEbCxqQg2ZzLtNRaVSCRQ3XA7NN9H2dlWFPMYxPL8b2m5DoUdHnvadnp62Nh9/ZsaDeDxqatyx9juw8eY13dpPXfWlkrFm9/OIRps/66kOx50X5Vrbx2dx0RQcNNVa30wajQai0Qg4j3lufv50LT1zV68q9+//GFKjAd+mtalfrukA+BE3fvCD75u25mshz9zm+LExp+Uz8pTTZjCS0D8CQ6uTy3L/5lTH4zGwJIlRprd9kwQBP0cjbnLTRSeSyQQAgHXqOw8xTg8Sp2tcZq6FvGu6Yny8mVMsGnDl1QtF+P3m5R1fhN8/AZfLhRcvjH9Bq9U6jo+zWFrqPhqmW5aWVlAqF1AsWTckOZWOQZIaWFw0fiL3+ycQmAjgUcna4s6jYhUsw2B11Xikocvlxvj4BKpp67LVa9k4VEXBwoK+eWhXHZerGUsi1fR1SWuvc7nMndewubkNiiJx//6Rqeu2Q5YVPHhwgrW1TfB898UsTTxLpgbXrai9d6eYlmBwFgRBYLei7/cNACxJtH3cC3un++g2XiYYnIVYykKReivOkmfm/px93AkhnwTNMPD7BzcPbtigaRo3btxE4eAEcqP/wnDu1T5sNnureeg8JEkCwwzvpTZzetN2nlCmsbv7CoCKyUBvInK9UcedO3fwySef4M6dO6g3eo+0mwyEUK/Xzy3gaE4CT4/D2QcFS5Jw0DQKhTwajTpkWWqJZsMEeUWFPIZhoLT5HnSLXH/7cy/rjHJ8a83TfTHM6856rSDV6xzffjE+3lvRTFVV1Go102YdnwfL8rqcprFYBJIsIWQbju+rto+jo3djysvlUsv1NozQLUdeecA76S+VSgUgCFAWzCTTC23jm/vqgVgsAooiEQhYNyMPAGZmRlGv100tvBeLBfC83dQ50zabo7W22USjYbgYGk66/X7rZ5w7Zx+fhSAITHEMohHzm8lPTo4gyxJsXvPuVWjOBtbpwf7+nmlrvs8oioIf/uguHBPjsI9Z2+hDEATGNlYQiZwgHDYnZSyfb9ZFvV5z3cterx21Wg2i2HtTYbcIQnNtI8kC2mut3OdZEvEo/BwNUoeTMMAySCT6mwoVj8cAggCjU8hjXaNIJuJDOxe7W9re/X722Wemv+FHH31k+prXWI82J0PIF2Af7z3GRZEkiKVyX+ZtEASBpaVVvHz5GIqigjRQ5N3dTUJRVCwumu+2Wl1dx7/8yz8hGj2Ae9WauNFI9AAURZnmFrt560N8+9v/gmxdanWXm4mkqnhWFrC+uW1aDvra2jq+//3/A6VRB2lBZE81dQKaZjA/fy3k6YGiKLAcB0nnBYt0etFkdqyp3W7H8vIaPv/8AL/2a9uWO4mBpvu3UhFxs0c36vj4BHjehlQqisWF3vPCzSCZisDvn+j4e7DbHZidncPzeAS/OK5vfsKq04aXbwiBq079Ratn5RrsNnvHSFCNYHAWUFWIxTRs3smu38cxHkI1FX7rcS+IhRRmpoOmFiDeBz744Eu4f/9HKBycwLvSvxmlkiiicBTG//WTP9V2LgRBEBhg4m1HtL21i4E5ONgFy3IYHe3t+o1lWNy9excAcPfuXdhtvQsOE/4gCILAwcHeO80y2g0YZSjCpr9QRHOAfbXa7Jgfxgg8giRBMeyVi9b0eLw4MSG6i2Lf/txTJkTp1YtlMCz7Vtx8NmtN17pZeL0O7OzsQ1XVrmKm6vV6MyrJckdee7fKeRwfNxu6hkXI87E0bBSF4+MjfOlLP9n6c1mWUavVwF878oaOarUChuMMRq6ZC81zKMd6m68djUYQCIyA7iAuGUVz/MViEdNGJ5RKxZbwZhYkSYHn7SgWLXDkRU4wZVHiwCTPYC+VRKPReKtBxCgHB3sAQYAfNbfpkPcGcHi0D1mWr++DOvDy5Q7yuRxmP/7pvryfd3kB8XuP8IMffB+/+Zv/j+H18vkcGIaCw2Hu+XZ01NFaf2LCmqZYUWxeX5gh5AmC/obnXlBVFfF4FJs9zsfTmOAY3CvkUSoV+zb3NhaLgHN6em6K1uBcYyhIDWQy6Us9C7ztv/63f/u3Tb3gIAgCz549M229a/qH1zsGiqIgZPXFzAm5ZqdSPxx5QNPt9uDBPUQiOQSD+rtRXrxIgGVZSwZ4er1j8PsnEI4cYG21+3lYvRCJ7mN+fhEcZ86N8dbWLXz72/+CL4pV/LzP/G683YqAmiybEqupsbKyju9977uoZiJwBswd6qyqKqqpEywuLpt6IXzVsNvskHUKebLY7HY3M/pW4+bND7Cz8wy7uymsrFh/7Lp//wg2mw3Ly2s9vY4kSczNzSMSGYwjT1EUpDMx3L79YVfPX1/fwr8eHuhuCPgJjwN3syWIioJf8I3gI4++G3NZVfGyImDj5oddC7VatKWQT/Uk5LlDa8gdPoEi1TG2/AHcwe5/x6osQyxmENwajEg7zIRCc/B6x5B9td9XIS+/fwRVUXD79pfaPq8p5A2vkvd6MHs7IW8P477pnpsZGIaDmE/j008/BQCMuHuPP2ZZDqOecRwe7r/zd6p6Ooui51UHBwECiqKgXm/eoOu9CbUaktY/S+yy4vP50KjVINcbhmbKUCyDSlZsfe4do8YLG2KxCN/Y+FvfU6vip8zC53Og0ZBQLpe6SkzQHKBWRmuyLI96Xey5GHx8fAgPS8PdY+yUVRAEgRDP4OTo7eNi8zurgrJwzqBRCIoGQZK6BNXLTKVSBsUPhxCsQXEchFqt6++DNqdsa8v6+6FAwA2KIhGNRrC1dcuUNQuFAmw2c+duAc14zVLJXEeeIAhIp1PYsqDWAgAzPAtFKSEej5pa4zo42APvHjP9GGTzTqJ4vINYLNLVKISrzA9++H2wDjs8c8G+vB/FMhhdnseTJ4/w5S//DzidxlIC8vkcRkcdpjc9aA6/QsE6IU8T34zME2dPX9tu5IGZ5PM51AQBkyP63G2Tp9G/0Wikb0JeJBoB69Lf4MG5m6akaDRyqYW8jnflqqqa+t81lxOKouCfCKCa0RcDWTt93eTktJnbuhCtc/vVq946zc6yu5vC3NxC2457I6yubiCZiqBeN98+XSzlUCzmTImo1PB4RhGcCeFph/x1vTwpVsFzvClRoBqh0Bw4nkclaX6ERKOcR6NawurquulrXyXsdgckQV/8lObke7NT3SzW1jbBsiw+/9ycuIh2iKKEx4+j2Ny8qet4Mz+/iFIpj2q1/3FFuVwSjUYd8/OLXT1/fb0pSD3XeRwhCAJumsI4y+AnRp26L/YPqiIEWcH6+o2uX+NwOOEZ9ULI93ZuIQgCNG8H6/RgJLTe056FYhqqoljSUHLZIQgCt29/hHIsAbHUv89+9tUB/BOBjtc0w+7I04apX/R5LJWKyGTS8Pv7c+12Hv7xaZycHL0T//lahBzErvRBEM19ax236uk8jWFDlSXTUhEuC615vRY4K4xSL5becaXkchm4XDzYIZ0R6fU2BUZNcOyE5tDiLHSTcXxz7Uqlt3PF8dEBgtxwfR9Cdg6pTBrV6utoRK2ISNLDtdc3IQgC1BVsFKhUKqCGZMaiBs33FqOcz+dQrVYxM2PtfDwAoGkKk5MjiJgY/1gul0ydj6dhhSMvGg1DRVNws4KZ09+9WXGIAFCvizg+OQLfQ5Njt2iNk3t7r0xf+30imUxgb/clvGtLIPqQJKTh21iFLMv47LMfGl6rKeSZfx0wOmpvrW8VoiiAomhDrlFNBOxXtKZ2DJjRmTgwxTMg0YzV7QeVShnlUhGsu/eEQA3W6QFBkj3PcR422l79f/WrX+3XPq65BExNzuDR04ddx6S8STWTBcfxGB3tz1B2l8sNn28ce3spfPxxb+4WjVJJQCJRxK1bP2Py7l6zurqB733vPxCLH2E2ZO5A2kj04PQ9zBWZtrZv4Zvf/Gek6w34DHQtn0VSVDyvCNi8+aGpwilFUVhZXsPzly90fXbbUUk1bzCuhTxj2O125Av65iDIgnWOPIZhsLGxhYcPv8D//J8fWBol8/RpFPW61HOspoYmoiWSYczP6Tvm6SWRbEZGzs1154jyescQmAjgeSmHO97BzffZKdXA0HTbGWfnMT+3gC+ePjH9eHIRQjYOoPs5fleN27c/xHe+8y3kXu0j8MG25e8n5AqoJtP4uS//j46//+F35DX/f9G/Q5vB5B8foJDnn8bOyweIRsNvReBq0ZqXSMcDgaaQx53OSep11ma/kKW6pbPKhhGfr+kYFQsl2H36CwRmo8gyxFIFY2NvO1pzuWxLLBtGNKdgNpvtKrq6VGoWwu128x0zGvbTWL1eIqAKhTyKpSJCfuvFi14Inhb4w+FjrKw070Eug5AHACTD9i02bFioVCughySaVUMT8iqVSlcuGq3gOzvbn+Pj7KwX9+6dQFEUw+MNVFVFtVoxLaHoTTjOhmxOX2LVRbwurlvzXXYzFNwMjXDYPKF0d/cVFFmGfXzGtDU1aM4GfsSHnRfP8XM/9wumr/++8KMf3QVJUfCtmT8SqB28xw3XzCR++KP/ws/8zH83VMfL53MIhcx3/brdPEiSQD5v7nf1TcyY86s1+vVrTvXJyTFokkBAZ7QmS5KY4FmET6xvegeaLjrgtatODwRJgnWOInot5F1zVZiamsL9+z9Co1IF6+zt5lHI5DA5OdXXbPi5uUU8eXJf9wXg3l7qdB3r4rpCoVnYbHaEI/vmC3mRfYyPT8DrNfeCe3NzG9/85j/jSbGGn/eZJ+TtVgSIsoIbN26atqbG2toGHj9+CDGfAt/jnJ92VJPHmJiYxIhOO/o1TWw2O5RUXNdr5XodBEFYcnMGNOM1Hz68j2fP4tjetq6Yff/+MUZGRnSLNYHAFHieH5iQ5/ONdxWfpbG2fgP/+d1/R0WS4bB41sZ5qKqKZxUBS8urPcfizs0t4MGDe2iU82Bd1sw3fZNaLg6fzw+Hw7oC52XG4xnF/MISoq8OMHF7y/LrjOzuPgiCwPZ2Z9GdJCnI8vAO09b2dtE10uHhPmiagXfUnBk1ehj3TQFoRja9KQhoAil5iaQ88tSRp93oK/LwCXmqIkNVlCsn5Hm9mpA3XI68erEMqGrLMahRqZTh9w/fjEUNl6u5t25TAorFZjSd3YLoOw0tVq9YLGB6urvYMa2gHrSooK6XaRsLAs0i3Gsh73T25hBHawIAQTFXzpFXF0WQI+Y3HBqBPL32bTS6S0Q5OTkGTVOYmupPfNrs7Bju3t1DKpU0HIUniiIURbHE8ctxvOlF93D4GF6Wgd3CeXAzHIOwiS6anZ1noBgWNpPn42nYxoMI7z1EpVKBwzG8TSyDolar4fPP78GzMAva1v9rg/HNVex/+7t4+vQL3Lypb2SQKAqoVCqWRIaTJAmv14lsNm362hrlctnwjFqSJMFxtp6TA/QSPjnCFMcamjce5Bk8Ch+Z0nTRCc1Fx7mM1bc59xhi0XDfmrKtoH+e22suPVqEVC3TXUyKhqooqGVzmJrqb0f3/PwCBKGBSERfbvnubhIsy2JqyvzOIg2SJLG2toFo7ACKiRFLolhDMhXBxkb3kXHdMjLiQSg4iycmx2s+LlVh43ksLprfRbSysg6SJFFOHJq2piTWUMslsLm5ZdqaVxWGYaDI+j7/iiyDphnLTsILC0twOBy4f9+6yIBKRcTz5zFsbd3WfQHUnJO3gGQqbPLu2qMoClLpaCvOuFs2NragAnhmUUxvJ06EOooNqadYTQ2tuaOW0yc+94KqKhBzSUsbSt4HPrj9JYilMiqJlKXvoyoK8ruHWF5e60q4drncyOeHdxZQodDc20X/lkgkDO+oHyQ5uNlQPG+Hy+VBNPr2sU1zEw6v3/Ec1KaQR9M0SJIaSkeechphqrkGrwoMw8A37kclqS8dwCoqqWbRaXJy6q0/r1YrsNuHV7Cx2VgQBFCtdlfgLhaLp01Z1kVr2t8Q8rrl5OQINEEgMGSxiNxpF/zJ8etrUy2Ki6SHe2Y3SV89R15DaoC0UJTRA3naRNdodHceCoePMDPjsTSd5E1mZ72n72vc6aFF0HIWzODkWBvq9fo78d9GCJ8cY4a39ns8bWORyWa6Pka3Q1EUvHjxDDbftGWRjg5/CKqq4uXL55asf9n5/PMfo9Gow7e5OpD3d81MgR9x47/+63u610inm9c7fr81aT1+vxPptLGxS+0ol0vgeeMNGzbe3oobtxJJkhCNhhE0eKyZ4TmI9bqlP1uNaDQMxu4CZbDZkHP7UKtVUShY59C0mmsh75quCQSa+dTVdG/ZwmKhBEWS+zYfT0OLmtvd1XdQ2d1NY3Z2zlDOcTdsbNxAvS624unMIBzZh6qqlgh5AHBj6ybiQh3pujlFqIaiYqciYH1j25Kft81mw8LCEqrJI9NiziqJ5s3zxsa1kGcUmqahSvqEPFWWLZthCTSjWbe2buHp0xhqNX1z/Drx8GEYiqLqjtXUmJ9fOp2TZ/3Fn0a2x/l4GpOTU/CP+/Gg0J/oiLM8KFTA0LQuId7rHYPT6UIta72QVy9mIUv1ayGvAxsbW6AZBrndA0vfpxxLol6p4vbtD7t6/uioF9nsYD7j3ZDNNotb58Weq6qKRCIOj8f3zt/1G8/IGOLx2Ft/5nY3xcd8w7zimZUoqopCQ2pF+vE8D6U+fMVsud4Ud3l+eN1eVrEwv4hqIgVVGR4XbSWWhM1mh9//dtRUrVaDwzFc4tKbkCQBm43r2qlSLBZgszks7ebmOBsIguhpntXJ8REmeRb0EHZsz/AMwqdd8AAgnTYGkKQ518RKow6O4/Dxxx+D4zgoXTq3OkFQVNfi0fuCJEkghk3IO91PNwKULMuIRiN9i9UEgPFxF2w2FicmRLa1hDwLGgVYTnMfVzo8szuKxQKKpaJl8/E0Zt6I5zVKNBpGpVKGYzxkeK2L4NxjoDk7dnaeWfYelxVFUfCDH34fzoAfdl9/xhidhSAIjG2sIBI50T0vTROCxsetEfLGx13IZNKtc6bZlEpF8CbM4eR5O0ol62s5iUQMkiwjaDD2WUssMONY3YlIJAzWoBsPALiR5hpaVOdl5FrIu6ZrWJbD+LgftXRv3arV0+db6Ww7D7d7BGNjY62IzF6oVETE4wXMzfVWnNbD0lIz2u0kvGfamuHIHtzuEct+5pubzTlET0vmOA32qlqspnXzjTY3t1GvFFEvmTPktpI4xKh3zHDcxzUATRtw5EnWCnkAsL19G5Ik4+nTWOcn6+DBgxOMj48jEJjq/OQ2aGJPMtW/i5LU6Xv1KjQRBIHbH3yE45poWkNAtzQUFY9LAjY2t3VFshIEgbm5BQi5uOXzzzSxcG7uej5eOziOw+bGFvL7x1B0NgV0Q3Z3HxzHY21ts6vnezyjKJcF1OvDKTZpQp7H825EbD6fQ70uwjMyDEKeD9ls5q3i7/h4MyY7PaQ/27PkGzIkVW3teyIwadr1iJloe9Ka964Sc3MLkBsN1DLD83upxJuO7DcFrkajAUmSTHPkCULjLcFGEMw5J9vtLGq17u4T8vmcpbGaQDO5wG53Ip/v7vcryzIiEePd6lYR5FkIooh0unmfqx0fzRKMFKmOO3fu4JNPPsGdO3egSCYJeSSNxhC6ka1EajRaDrhhQfucdCOqxuNRSJLUcsn1A5IkEAqN4uTk0PBa2nGItcSRx5++hzlNW4eH+wCAWbu1rvigjQVJEK1ZyEZ48uQLEAQJ+3h3kcV6IAgCdn8IL1/uoF63prH2srK7+xL5XA5jG+aO6ekV7/ICKIbBj3/8A12vT6dTIAjA57PmWsDvd6HRkHpy5XeLqqrNaE0THHk87+iLkKd9941Gh4+xNGwUhaOjQxN2dTG1Wg25XBacCfelrMsLEMQ7aS+XiWsh75qeCAZnUU1leipeVpLplgjYb4LBORweZnsuth4eNsXHbga0G4VhGCwvryIc2TOlKCxJDcTix9jYsG5W0MiIB1OT09gpm9NNvlOugWXYnuP5emF9vVl4NSNeU26IqGViuLFp/Tymq0AzWlNfMVaVZdA9zjjrlZmZENxuNx4+NG8ouEapJGBvL4XNzZuGP0uBwCRYlkUyFTVpd51JpqIYHR3raT6exs2bH4AgCDzssytvp1yDIMu4fftLutdYWFiCJFTRqJh/M/Am1Uzz53ue0HLN29y+/SXI9TqKx9ZclMuNBgoHJ9jautn1XEXt95bLDacrL5ergqKoc+cvJhLNxgWPp38d+Bfh8figqiqSyUTrz3w+Tci7HAVhbZ8+X3PW2dTkFMRSdqjcXwAgFjMgSRJ+/9VrUtKc5eVYosMz+0O9XIFYKr/jeNcKxmYJebVa4y3BplYzS8hjUKt151LJZjNwOq2fN+10jCCb7a4hNR6PQZIlw93qVqHtS3M/aM4qwqQoZJJmcffuXXz961/H3bt3QdLmfN4I8mo58hRFac4OoqxtOuwVTViUuhBVtYLvwkJ/G3sWFnxIJuNdNwRcRL3ejJ3tdSZ2N9CnUbZmiUuHh/vgKBIBztp7W5YkMc2zODww1kiuqioeP34Im2/KcNxdJ5yT82g06tfxmme4d++HYHgeI7P9NU2chWIZeBZm8fjxo9bM1l5Ip1MYHXWCYaxpetAiO7XmFzMRBAGyLMFmWrRm0fJm4YP9PXhZBiOMsXMTSRCYs7E42H9l0s7OpzUfz33xfamqqpCEKurlPArHzy/8GZIUDc757tiGy8S1kHdNTwSDs5AEEfVS9wM4a6kMZmaClg+/PI9QaBblstDqOu+Wo6MMSJLA9HR/TogbG1uo1SrIZIxHtUVjR5BlybJYTY219U2EayLKBt0PiqriRUXE8vKqpc4qp9OF2dl5VE0Q8irJY6iqch2raRI0TUNVVF0Ffhzr2wAAIABJREFUTcXiaE2g2cW9ubmNnZ2EaZ3qGo8fR6CqqiluVIqiEAzOIp3uj5CnqipS6ahut5jbPYKlxWU8KFahWHyx+iYPChW4XW5DjQPaLM9axrqftaooEHJxS+aGvo8sLCzB5XIja1G8ZuEoDEWScOtWd7GawGshb1jjNbPZKjwez7nXZ4lE83rEMzIEQt7pHjRxEWhGZjvsjkvjyNP2qQl5k5PTUBUZ9cpwzWcQixmMj09Yfl4dRlwuN7xjPpRj1s/56AZNUJyff9vxrhW1eZOcYjYb85ZgY7OZs263jjxJanbIu5wjprxvO5zO7oU8rcAzPWTz8TR8LA2WJFvFrZaQZ5JgRDIsRFHEp59+ClEUQTLm/BxIijJ1ntiw04pxG7LGT615sJuYuaOjA3i9Dng8xovUvbCwMA5VhWFXniay0dQlEPL29xDiWVB9+LzM2ViEwyeGhPVw+BiFQh7OgPUjAGzeAGjOhi++eGj5e10WSqUidnaeYXR5fijmcI6tLUGSGnj06EHPr00mYwgErInVBIBAoNl0rN3fmInm8rOZkCxgszkhSZIuMbRbFEXB4eEe5gy68TTm7Rxy+RzyeevuaboR8orHO5CqRSh1Aamn/4Xi8c6Fz2VdY4hcR2tec1WYmWlmX1eT6a6er0gSatk8gsFZK7d1Idr7Hh5me3rd4WEWExOTYC3uLNJYXV0HQZA4iRiP1wxH9sDzNszOWhvFtra2CRXAi7Kxk0xMaKDUkLC23l1UmRE2N7chlnKol42dZCrxQ7jcI5ieti5C4iqhFQwVuXchT5Vl0H3oct3cvAlJkvHsmbnxmg8fhjE2NoaJCXNizGZn55HLp1Hvw+ylYikHUawZOtbcuv0RCg0Jh1XRxJ1dTEmSsVsVcOv2lww1l3i9Y3CPeFDNWBO3CgBCIQVFamBx0Tqn8vsESZK4ceMmypE45A4uLfKMSHH28XkUDo7hdLl7cuprSQSRyPBE9b1JJJJvOdvOUiwWwHE2MMzg3SgOR/Pm++xsK9+4/xIJeQ3wHNdyP2pzo8Vib3H1VlMvZTA11d+Z1sPEwvwSKvGk7rhvMylF4+B52zvXB5q7hOPMufbheeYtwcYsgZBlqa6K2/l8DqqqwtknIa9SKUMUO18jxWIR8BSJUYvcAUYhCQIBjmkJjvJpsgVBDHl5hyAhD8H3q19os9+HzX2tKs0Guk6z6VVVxdHRQd/deAAQCnlBkgQOD401aLWEPHq4hbxKpYxkOok5i2M1NebsHGRF1j3TDAAeP34EgiThmLC+1kcQJByBebx4+byrY/hV4PPP70FRFHjXhuNe0ebzwjY2is8++2FPjrJ6XUQymUQwaF0CjcvFw+OxIxIxP2FJE/LsdhOEPLvjrTWtIJGIoyYImDfpWKOtc3ho3qios0SjETC8A3SbWaeV1HHbx2/CucdQKZdQKnU/N3mYGPIrvWuGDb9/AjTDoJLsrvBQTTdjgzQBsN/4/QEwDIOjo+4LJYqi4Ogo21fx0WazY35+AZHIvqF1FEVBNHqAtbWNjhfmRpmcnILb5cYLg/GaO+UaCILAysq6STu7GM1BZyReU2nUUU1HcGNzeyAu0/cRIze5qqL0xTkQCs3C5XLh0SPzLPjlsojd3aQpsZoa2qy6VNo6gUkjdRrhaUTIW1/fBMeyeFAwZ0h8Jx4VKlBUGIrVBJqdzEuLyxCyMcuiL2qnIqGVkcPvG5ubW1BkGcWT9h12I6Hpto/PIjcklMLNOOVejvsOhxN+vx+7u+bHuBilUKghlSq9E9unUalUWrNfBg1F0aBpBtXq28eJ8XE/Ug3J8vgZM0jXJYyPT7SO9T7fOBiGhZAz5v46G9dmJL6tUS1CEmt9n2k9TKyurkFuNFBJDPY7qyoKyicxrKysvXPM0QrGZgl5VsFxNBqNzsXtbLbZHNqPaE3X6Xtks50bPKORMCY5Zqgj9Kd4BvFYtCtX1dBAALgEx2yzIAgCJEkOnZCnKE0xtVO9IJvNoFwuY36+/0Iex9GYmRk1PMdNOw5Zcb+oufzMEPK0f+d8n+J8QzYOBF7P5esVRVHw+PFD2H0zoExy7HbCGZiHLEl4/vxZX95vmFFVFffu/xDOgB/8SO8jLqyAIAiMrS4hHo/2FFsYjTYTikIha+dwhkKjiEQuFnf00hLyTHDk2W1NV2KhYJ2QpwluZgl5ExwDnqJwcGCslt2OSDQMxtX+83F2VE+70T2as09z+l02rqvQ1/QERVGYmQ6imurOkVc9FfyCwcEIeRRFYXo62Jp51w2JRAmi2Oi7i3B9fROFYhbFkv7O/VQqArEutObBWQlBEFhb38RuVURD0X9DtlMREAyG4HA4TNzd+Xg8HszMhFCJH+peo5I6garI2Nw0HoV4TRMjQp4iK5aL1kDT7bOxsYVnz2Kom+QAefIkAkUxJ1ZTY2YmCIIgkDYhprcT6UwMNputFRWnB5ZlsbX9AZ6UBQg6HJm9oKoqPi9WEZwJmTKzdWFhGXJDtMxRU8tEMTExee78smvOJxSag93hQOGwfbfl2PoyWLcLFM9h5s5HGFtvH19aCkehyLKuOOX5+SXs76chW/z57pVXr5oC0kVCcbVaATskQh4AcJztHSFvamoGVUlGashdeQ1FwYnQwNQbce0URWFlZQ3V5LEhIdIxHmr7uBfKiWZX/uqq9Y1Vw8rCwjIoikLxeLA39tV0Fg1BwOrqxjt/d5mEPFHs7LZPp5v3lC6X9Y48l6sp5GUy7YVaWZYRj8cwZfGcKqNMcSzqjQYymfTr48gQC48AQIDA1ZHxmpAUNXRCHrp05A1qPp7GwoIPkcixoThW7ZhJWRKt2TwOd9O00In9/T0wJIkpk+LuOmGjSAR4Fgf7u7pef3Cwh1KpCOfU+Q1hVsCPToCxOfHw0f2+veewEomcIJfNwrvSv59/N3gW50CQZE8RqJpLzmohLxj0IpPJtGYNm8XraE3j9Uy7zXpH3sH+HkZZBh6D8/E0mnPyGMvm5NXrdWTSqbaxmr3Cnq4VjfZnJI3ZXAt51/RMMDiLWiYHpYvZaJVkCiOeUTid1uUddyIYDCESyUPqcpab5t7rt4twba0pvoUNuPLCkX1QFI2lpVWzttWW1dUN1BUFhzV9sXjFhoyYUMfqqvXCo8aNG9sQixk0Kvps1OX4IZxOF0KhwcTFvo+QpIHYGaU/Qh4ArK/fQKMhtwrgRnn6NIaRkZFWxJoZsCwHvz9gyrzNTmSyCczMhAx3q3/44UdoKAqelKydIxYW6kiKDXz4pZ80ZT0t8rKWNr/gq0gNCPkElpf7cyx/XyBJEpsbWyieRKG0KfoQBAHGbgPvGYFvfaXjZzh/cAyb3a7LfTo/v4h6XcLxcW8R31azu5sEz/MIBKbO/ftqtQKuTXxJv+E4/h0hb22tKXI8NxjxbTV7VRENRWld52lsbGxBEqsQ8vrPKe7QGmi7GyTLY3zzp+AOreleq5I4RCAwBa938HMRBwXHcVhYWOro6rWa4nEYBEGcew7QojVZdriFPJalu3KppNNJsCwPnrN+/pbb1YztSqXaf+fS6SQkWcLkkM7H05g8jUHV3AyXAoK4PHs1CWoIhTwtPpjq4OI+ONiDw8FhYmIwjp+FhXFIkoxwWL+LRpblljPSbLR7WDPiYndfPse8jQXdRzF+yc7h+PhQV1Tlw4f3QdEsHP7+1cwIgoBzahF7uy8vbSSeWTx9+hgEScI9O1xx6DTHwjUdwNOnX3R9rA+HTzA66oDLZW0D4exsUyiMRMxLWAKaohvP2zoeT7tBm7NnlZCnKAr293cxb3LDwIKdRzaXRS5n/v1uItFMQDJTyKMYFozdde3Iu+bqEAzOQlUU1DKdv6S1VAazPcyTsYKpqRnIsoJ4vLuTfSSSB8uyGBvrb+fZ6KgXgcAkwjrn5KmqinB0H4uLS+C4/kQyzM8vgCJJ7FX0xWvuVZuv62exWnPSleO9x3QoUgO1dBibPcarXdOeliNPx02Q2kchb25uASzL4ulT47GVkiTjxYsEVlc3TI9tmpkJIZNNWFooaTTqKBQypjQ8zMyE4Pf5cb9grZB3v1ABQ9O4ceOmKeu5XG5MTEyiaoGQV8vGoSoKlpZWTF/7fWdzcxuKJKEYNideVpFllE6i2Fjf0nWsmZ9vCr67u+Y0AJjFq1cpzM0tXHguq1ar4Po0J7gbOJZHtfr2McLtHsH01DR2DEZ8W81OqQaOZd+JMV1dXQNJUqgk9M+nIQgCNG8H6/RgJLSu+3wiCVUIuSQ2N3t3nb5vrK5uQCyUIBQGVyQsHkcRmp2D3f6uuKWJY5dByJMkqWPsYzKZgNs92pcIS5pm4HC4Owp5Woe2WUKeICvgOA4ff/wxOI4zLYHAzzGgCQKxmLlFSeu5WkIeTdG67nGsRD39DHa6rjk83MPiog8kORin5+Jisx5jJLJNUWTL7tu1dbWoUr1ksxmksxksO/qbhLDs4CErCvb3e6s/1et1PHn6BeyBOUOR3npwTS1BVdWeHF/vG6qq4unTL+CcnADdp7pfL4zMBZHP5xCLded2CoePEApZNx9PY2ZmFAQBHB8fmrpuqVRsCXBGoSgKPG+zTKiORE4giAKWTD7WLJ6ut7dnvitPE9vMFPIAgHWN9RQBO0xcV6Kv6RnNiVRJtI/XrJcrqFeqfY+oPIvWbR6NdtfVEI0WEAhMDkSoWV+/gVQqqqsrqljMolwuvNPxbSUsyyEYmsNeVZ8jb68iwG6zIRCYNHlnFzM66sXk1DQqyd4LZ9V0GIosXcdqmozWvaTqKGz0U8ijaRpLSyt49sz4XLS9vRTqdcmS2ZAzM0HU6wJK5XzH554d/N7tIPhsLglVVU0R8giCwAdf+gmc1EQkxYbh9c6jrih4XKrhxtZN8Lx5F67LyysQ8gkokrn7rmYioGja0PzBq8r8/CIYhkU5ao4rtZpMQ240dMcNOhwOTEwE8OJFwtA+WJZq+7gXMpkyMpnypZq/qKrN0UpnWVvfQrgmotRl6kK/UVQVOxURyyvr78zn4XkbFheXUUkcDtyhoomJeuJj3ze07/qg4jXrlSpq2RzWzonVBADp9Hxj5BjQD7T9SR3Oj6lUEiNua+O03sTtHkUy2f54nE4nQQLwmSSWCoqCO3fu4JNPPsGdO3cgmOTOoggCYxyDdDr9+lp4yN1uqqKAIof7s2s2NrsdkqDvXtkqpNPYW7v94ii4fD6HXC6HxUX9EfpGcTg4TE15WjOd9CDLCgjCWiHPqCPv1asXAIBlZ3+FvJCdA0uSePVqp6fXPX/+FI16Ha6p/l9Hsk4P+BEfHjy41/f3HhYSiRiy2QxG5oOG11JVFY1qFUK+gPTzl6Zcj47MzoAgCDx9+kXH52azGeRyOSwtWX+csdtZTE15cHCg/3hyHsViATbevDFBNt5hmZC3u9sU2hZMmo+n4WdpuBgau7svTV0XaDZXUQwH2iSxVINzjyGXy0IQhjvZ5TyunJD3gx/8AH/0R3+Ejz/+GNvb29ja2sLP//zP4w//8A/xne98p+1rG40G/u7v/g6/9Vu/hY8++gi3bt3Cl7/8Zfz5n/95V0Oz3xecThc8nlFUku3nC1SSTaFv0BGEY2M+MAyNSKTz7DlVVRGJ5E2NuusFzZkWT/QeHxGNN4swKyv6Y5X0sLi4jLhQR6XHIpqqqtiv1bGwsNx30XRzYwtCPgVJqHR+8htUEkfgbbbr4rrJMExTPFL0OPIkGUyfBmwDwMrKOvL5KmIxY3EHT5/GQNO0JYV0TVzLZDoLB9NT820fX4QW3TkzY/wGAgBu3foQJEni80Jv38lueVqqQZQVfPDBT5i67tLSatOhnjU3ylRIRzA3t9D6blzTPRRFIRSaRSVmjgOuHG+uMze3oHuNjY0t7O2lkM/rd51ubk61fdwL9+83rzHW129c+ByGYSG1GRLeb2RZAsO+e6xfX9+ACuDFkMZrRoQ6ypJ0YZPV5uYWGtUSxEL7a2qrKcf24B3zwe+fGOg+hoHRUS/G/RMongxmbkbp9H0vah7QZkXR9HCLIdr+2s22qlarqFTKfRXyRtxepNOptk7BXC6LEZYBZZJLkCdJ3L17F1//+tdx9+5d8Cbe94zSJHKZdKtRQDXoDLIaVZG7bhp7X3A4nEMn5Mmn+2k3o15zwS0tGZ8rbYTFRR+Ojw91i2VNR541x0uC0KI1jYnzr17tYJRlMGbSzKpuoQkCC3YWL18870nAefjwPhibAzZvwMLdXYxzagnxeBSJhPWjJIaRp08fAwSBkVnj9+GZ569QL5YhCyLCdz9D5rlxRxXN83BM+vGkCyFPE9WWl/tznFle9uPk5BCNhnlNuKVSqe18PFVVUa2VUShm8XK3c+Qob3OgWLRGyNvbfYFJnoXT5GtIgiCwaGOxv/eyYxJDr0RjEbAur+nJDZrDr1vn6DBx4Znin/7pnyx5w1//9V+3ZN1OqKqKP/uzP8M//MM/tP6MZVlQFIVYLIZYLIZ/+7d/w6/8yq/gL//yL9/pmi2VSvi93/s9PH78GECz8MwwDPb397G/v49vfOMb+Nu//VusrfVXRBkUodAcdnZfQFXVC79Q1WQaFE1jYqJ/bqvzIEkSExNTiEQ6u1Oy2QoEoXHhzBirmZ4Ogud5xGJHmA31FqkWix3B5xuHx2O9Lf1NFheX8Z3vfBsHVRE33N3Pt0jXJRQbEhYHEB23vn4D//7v30IleYyRUHcuC1VRUE2dYPvGdt8cYFcFTazQEzujyHJfxQ6tsPbsWQxTUx7d6zx7FsPCwhLYcwrTRvH7J0DTDDLZOObn2p+Tlpe2sfPiAeoNEdtb/w3Li925MTLZBDyeUTgc5nRGOZ0urK6u48GrHfzf4yOmFc80Pi9UMDbqNSTGnMfs7DwomkY1HYHDb46oKQkViOU8lpd+2pT1riLz80vY23sFSRBAG3RglmNJTAQmz42465Zbtz7Ef/zH/4d7947wi7+oz9l3584ivvvdlxCEBr785U381E/pG26vqio+++wIc3PzGB29uHjOsgzkYRPyzjnWT0xMwjPiwU65hi95jB2P2DPRYWcf62GnXANJEFhdPf9YvLV1E//yzf8XheMd8J7BFEvFUg61XAI/+8tf6Uu84WVgdWUdd//r/0BuNED1uaGieBLByIgH4+Pni6pa8Ylhhrsfl2Ga18rtimWaM87dZyFPkhrI53MXzoPMZtLw0ub9fHmKhFgT8emnnzYf28zrhPcyNPZy2Va6hSJLGOa7FFWRwPRZrBg0DrsDycJwNX1rwqLNdvG1zeHhHmw2FpOTI/3a1rksLfnxve/tIhI5QUjHyBZFUSyLBjUjWlOSJOzvvcJtBzeQc/CKw4adRA7pdArj452vQ0qlInZ3X8Azvz2wawbn5ALSOz/Cw4f38cu//JWB7GGQ7O29gt03BsZm3MFZOJM+UDiOwLdhvD7nDk4j+qPPUSwW4HZffAzZ39+Fy8X3bQ7n8rIf3/3uSxwfH2JxcdnweoqioFwuYTZ08T3Iq90vUC43m8A/u/cpoKpYWb541IeddyKZPjG8t7OIooiTkyP8N4957sE3WXLweBjLIhaLYnp6xpQ1ZVlGIhGDa8Z8neVNIe/s+INh58KrqK997WumH5gJghiYkPeNb3yjJeL9wi/8Av74j/8YCwsLIAgCkUgEf/VXf4V//Md/xLe+9S1sb2/j93//9996/Z/8yZ/g8ePHsNvt+NM//VN85StfAU3TePDgAb72ta/h8PAQf/AHf4BvfvObcDrNtXwOI8HgLL744gEalSpY5/kHgmoyjenpmXdE0UEwOTmFJ08+bys8AmiJfZOTgxHyKIrCwsIyDg8POu71/2fvTWMbSc9r/1NFsrgvokhJJLUv3VKr1+l1Wl7GTrwCvo6TvzFBHCRIEH9JYicfDBhxAidBYAOOgQSBgwvHARJvSDzXgON4iX2Rm/F4Zno87lm7Z3rXLpGSuO+1V/0/FIstdYsUSVWxSt36AQMMJS5vU2TVW895znm2IwgCkqk4Lly4pPMKHyYWG4KdorBQZdoS8tT5eEZEe/X19SMYDKGytdKykEdnNyHyHI4da+xgOKQzVEed1KRruxGSIHTVkef1+hCJRHHr1mbHBfl0uox0uoxLl/Rp/LBYLBgYiCCX29vhQRAEnE43nE43jky2Hhmby6cwNKSNcKXyxBPncevWDSxUGBzxODV73jwvYKnK4leefErzfY3NZsPoyBjWt7SLYFNn7h3Ox+ucsTFFsC1vJBEY6zz+VRJFVJMpnDj/5L7W09sbwvDwCF55ZQW/8ivTHX0OCYKA3++E3+/E3Fzn582VlSxSqRLm5j7Y9H42GwWWMZuQ9/CxniAIHJs9gV/+4kVUBBHufXSYHvU4cXfbzN+j+zwOSbKM6yUGo2MTDYuldrsDp089gddefxXizEVYbN2fdVJcuw3SYsETT5zv+mublSNHpvHii8+hnNjUpOO9VSRRRDmxhbNnzjU8TgiCAIuFNP2sZlXIa+bIS6UUIc/v13buSTPU10omtxoLedk0Zu3GX7+2QpCyghfKdbeS6R15ogjbY+bIc7ncEBhzzXIVGAZ2h6Npc+ry8gLGx42bj6eyfU5eJ0KeKEogCb0cecp7sx8HysrKEjiex6TbGMFUnct39+7tloS869ffhCzL8MaMi2e32p1whQbx5puv4X3v+5Dpz4daIggC4vF1BGe0ef8frL90Uo/ZDXe/EpW5trbScCyNLMtYXLyHqam+ronCExNhkCSBxcV5TYS8SqUMWZbhdDSug8YTSw/dbibkOZxulMulWhOCdp/t5eUFiJKk+Xw8FXVO3vz8Xc2EvFQqCVEQNJ+PBwBWhwtWu/NAzslr+qmQZVnz/4xCdRgODw/jH/7hHzAxMVE/WMRiMXzhC1/A2bNnAQD/9V//teOxL7/8Mn72s58BAP7qr/4KH/3oR+vi1JkzZ/BP//RPoCgKW1tb+Nd//ddu/ZMMRY1Tq6Yyu/5eliTQmRyGNJifpAUDAxHQNId8vnn0UiJRAEEAfX3GxAQASrxmtVpGsdh6514qHYcoCpicPKrjynbHYrFgbGwSi1WurcctVlgE/P6GF9F6QhAEjh07Djq7AZFvbd2VrWVYrTZMTBwW17WGomrRmh3MOJKE7jryAGB8fAorK1nwfGfFkvn5ZO159LsAisUGkcundDnvchyLUimPaFSbDZrK1NQ0nA4H3ix2Hj+4G9drz3fq1BOaPq/K1NRRsOV821G9jaim43C7PYa72Q8ysdgQrFZbPRazU6qpDCRB1KRL7/Tps9jaKmJ9fe90AD159dUVWK1WHD/eXLinKAqC0N55XU94gWt4rD979iJEWd53NO+FgBtBmxVuC4n/1d+DC/vsWJ2vMMhxPM6fb95kdeHCk5BEAaW49gPi90ISeJTj8zg+e1Izh/WjwPDwKCjK3vV4zcpWCiLPN43JFwTe9LGaAGCtOdqaO/I2YbXa4HZ5u7WseoxnMrl7JBvDMKjSNIIHxDWmrlOd8SKbyEm9G1IDd/WjjNvthsCwkDWOG9sPAsM2nY9XLBaQyWS6MrdqLzwexa2zsrLY0eMlSQShkxhJEAQIgtiXkHf79k1YSQIT7u438gBAD2VFn92G27dvtHT/N954FQ5/CJSn82QaLfDGJlEqFTWfd2Z2NjcTEEWhLpSZFWdvD0iLBauryw3vk06nUCqVMDXVvX+Lw2HD0FAQi4va7LlLpRIANI3WfHBW8F6zg50OlxLHWdV25Mj8/F1YSQIjTn2a4L1WCwYcFObn72j2nKrIZveHNHvO7VC+XsTjB0/Ia7hD3Wte3EEjmVSKOdPT07tuHgmCwIkTJ/Daa6+hWt1ZRPyP//gPAMDg4CA+8pGPPPTY0dFRfOhDH8J//ud/4vvf/z4+9alP6fAvMBcDA1GQJIlqOrNrtzudzUMSRcRi3etibYYaT5NMltDT07hbIpksIRDo0SXurlXUOXkbmystd6hubK7WBDVtY+NaZWR0DLfv3ERZEFvKW5ZlGSsMh6njxwyLZJiZmcWLLz6Hanod3kjz902WZVRTa5icPGLoZ+NRpVNHnixJXY/WBICxsQlcufJzLC9nOspzn59Pwe12N4zN0oJodBC//OVLKJXy8Pm0jdvN5ZK119B2lqjVasXs8dO49vpVsJIEu0YdaNeKNIYGh3VrGlDF/Wo6Dt/g/oR+WZbBZBKYnTHu2PgoYLVaMTg0jGRy92ajVlGblTrpAH+Q48dP48c//k+88soyhoa6G4GtIggiXn99FTMzs3A4mrvN/P4erK1pH+vSCaIooFotN4wO7+8fwOjoGK4m1jEX9ILs8LtDEAR8VgsACy707F/U+mWuDI/b3XQWIQBEIjEMDg4juXYH/pHZrn73yxuLEAUOFy5c7tprHgSsVismJqawsNZeQsZ+Ka4laukcjRt9JEk23CHTCmoXuSw3LnBvbW3C79N+7kkzKMoBl9NTj/V8kFxOOe4fGCGPUtbJcUrjhcibaxbbg0g8B3fI2KjGbhMI9ECWZfBVumGSUbfhShUMNBnHsbKiOEgmJswhFkxMhPHaa0sdOVQkSQJB6OfYIkmy42hNWZZx+9bbmHDaQRnoKpv2OPDi8iJouto0bjWZ3MTmZgKhme6nQD2Iu28YFiuFN998VRNn1UFhdXUFAODq00fY0ArSYoGzN1hf727Mz98FABw50l5NRJZlFAo0GIbHlSvzuHx5oq19xJEjffif/7kNmqbhdO4vfaNSKQMA7PbORzA8iKPm7qtUyvB4tGt0unf3Nsacdth0PNZMuuz4xcoSWJaF3b7/5oREIg7SYoXNrU/0qt0XQnrxGjiOO1B13oZ/wVgspst/RqFGgN2+fbthZ6A6/+748Z0X3FeuXAEAvPOd72y4cXjqqacAAOvr61heXtZgxebGZrOhvz+Camp31xidVn5uHiFPKbYnk82Hhm5tlXTgoz2FAAAgAElEQVQtrrdCINCDQCCIZKr1LuBUKo5YbBgUZUwn18jIGABglW7t4jHLC6gIoibF0U4ZHByGw+FENbV3BwZfKYCny/X5aIdoS13I49sT8lQHX7dPuiMjYyAIYGFh7+jKB5FlGfPzKYyOtrfhbBdVZMvm9udI2o1sLbJTayEPAE6ffgK8JOFWqbl7ulU2GQ5bLIfTZ85q8ny70d8/ALfbg2p6/84NrpiBwDGGuKsfNfr7+sEVivtypbKFIpwulyYXUS6XCzMzs3j11RVwnDGOievX46hWOZw5c27P+4bDYbAsDZY1Pg6sVJsrEQo1bpy4eHEOOY7HvYrx6wWAHCfgboXBufNPthQxf+HCk+DKedCZjS6sTkGWZRRWbyEc7sfIyGjXXvegMDV1FFy5Aq5Y6tprlhObGB4ZM2w/322Sya2uxmqq+HzBho68clkpyrXSmGgGvLVoRDVaU+TMcQxshMQzTZ1gjyJqIxnbxWPJXnClEoLBxkLA0tIC7HYrYjFjXVcqExNhsCyLjY3299qSJIHUUcgjCLJjR14yuYlcPodpr3YjBTphxuOEJMu4e/d20/tdv/4mQBDw7NEE3Q1IixWu/hHcuPl20wjnR421tRVQHjcot3bCkV64+kNIJNYb/n3m5+8gFPKgt7e95rkrVxaQTpdRLrP47ndfx5Ur7bkyp6cHIEkylpbm23rcbqh7hmbRmu2iCnnqc2tBLpdFOpPWLVZTZdLtgChJmjllE4l1UL5e3Zox7P4QZFnG5mZ3Ezj2y2MTJvyJT3wCALC6uoo/+ZM/wcLCQr24E4/H8bnPfQ6vvfYaAoEAPv3pT9cfl8/nkUopRcupqcadHtt/d+9e96NxjCAWGwKTzu5aJKumMnA4nIbEJu6Gx+OF3W7H1lbjDbQkyUilSgiFjO88GxkZRTqz0VIBUhQFZHNJjIyMdGFluxONDsJqsWCFbi2GS72fkYUji8WCyckjoDPxPd9nVew7nFmlD87aoGaRay/GTb3/Xs4SrXE6nYhEYvWIzHbIZivI56u6D9Tt6xuAxWLRSchLwuv1adohpjI8PAq/z49rGsVrXitWQZIkjh8/rcnz7QZJkpicPAKmhWPJXlQzyiZycvLx6SzVi1AoDIHjINCdFzXZfBHhJuJRu1y8OIdqlcNrr61q9pzt8POf30Nvb29LQnFvr7IXKpVyei9rT4pFZQ3N9mczM8fhcXtwNafdRe9+eCVfBggC58611rV+4sRpuFxu5Fdai7bSAia3CbaYweXL7zx0AO+Cep7eb0RvqwgsBzqTw9io8QXSbkDTNMrlEny1qMtu4vcHkUoldy2+qw2/tgPgegQAa22dqkvT7EKeyDFwux9PIY8rmuP8JHIcBIZFb2/jOs3y8iLGxkKwWMxRLlTn5C0vtx+vqURr6ujII0iIYmdC3q1bNwEA0xrOBu+EmIOC22rB7ds3G95HlmVcv/4mnMEBWO3GrlfFExkHx7K4d6+5APkosbW1AUfQHAL7Xjh7eyCKIrLZhxNSBEHA0tICpqfbN1HcuJFoensvRkaCsNutdUfgfqhUlPqylvUoh117IU/9t07pLOSNOO2wkYQm8ZqSJGFjI6HLfDwVh085txy0eE1znJm7wFNPPYXPf/7zoCgK//M//4MPf/jDOHXqFE6fPo33vve9+MlPfoKPfvSj+N73vld37wHA1tb92I2BgcZz07b/To3xfNQZHByCwHG7bkqr6SxisUHTFAYIgkAoFG7qyCsUquA4oWnHd7cYHh4FTVdQqTR3EAJAJqtciBrpbrNarYjGBrHaopC3WmXhsNsNdz9OTR2FwFTBlZsXKqvpdYRCfejp6X6x4XGAouwgCAIi26aQV7t/swgQvRgdncDycvtz8ubnlcYQvWNwLRYL+voGkMu17xrci1w+qYsbD1BEsVOnz2KhyqDcwczE7UiyjGslGlOTR3UvGk1MTEHgGHD7FD3odBzhcD+8Xn3iIx4n1HM5W9j7PNoItlCsO/q1YHR0HAMDETz//L2uz41eWclgZSWDS5cap0tsRxXNiiYQ8lQxMRRq7B6wWq04f+FJ3K0wyBrkeFQRJBmvFquYmZ5FINBascVms+HixcuoJlfBtbD304L88k04nE7d5ocedEKhMFwud9eEvMqWcr4efUyEvHRaeV/9Gsd/t4LP2wOe51EsPvxdqwt5JrmG3QsLQeyIEzazkCcJPCRReOwceX5/ACRJmsaRx9ZqN40ceTRdRTK5hfFx80T3BQIu9PZ6OpqTJwgCLKR+DlvSYoHY4WzK27fexqCTgtdgBzBJEJh2O3Dv7q2G7qmNjQSy2TQ8A+Y5R7l6o7BQDsUp+JhQKBZME9G7F6prsFgsPPS7tbUVcByHo0cb19gbwXFi09t7YbVaMDnZp4nYVC6XYbFYYLVqlxClioKqSKgF8/fuwGezIky1FhsuyzKKgogUx+NqrtzydauNJDDmtGN+D3dvKySTm+B5Dg6/fkYbi8MFq92F9XVjmmw75WCEv2vEJz7xCQwPD+PP/uzPkEqlwLL3YwB5nke1WkWxWNwRAVqp3B8w2Sw/1+G4r2x3opy3ayc2A8ePH8X3vw9U0zs7LCRRBJPLY+r8BYTD3RtevhdDQ4O4fft6w98nk8qBcmpq1PB1nzp1DD/84feQSm/A42k+RyBdi3M7fXoWPp9x656Zmcb/W1sFL0l75i6vMjwmJqfQ32/sjISLF5/Af/zH/0E1tQ67d3eRThIFMLlNPPnUU4Z/Lh5lXC4XhDYdeUJNyItEerv+tzl58hheeul5xON5jI623iW0vJyB0+nEsWOTbc94aJfx8VG8+urrms73EQQexWIO73jHk7q950899Q48//yzuFmi9zWnap3hUOQF/H86rlXl/PnT+N73ngGdScDeobtAFkUw+SQuvftdh8caDSBJJfKZKRThibTfNCKwLHiawcjIoKZ/j/e//3345je/iXv3km3PhNgPzz9/Dw6HHe9731MtzYMIBl0gSRKFwv7mDGpBoZiF3+/H4GDzC7kPfOBX8PPn/h+u5sv4YJ9x3cpvlaqoCiLe/4Ffbeuz86EPvQ8/f/5ZFFZuIHzsSR1XCPDVEirJFXzwAx9ALGaO9AwzcvToEdyc707SSmUzCdJiwZkzs00jw51OGw6IxgQA6Olx7/o9mJ9Xrrt8DfbfeqK6AAWhjHB45xgIp1MpqB8URx4A2EgSFGWBx+OByFT2foBBCKySthCN9j12+5zeUGhfQp7I8bDb7Zibm8OVK1cgcruPimkFdR0TE0O7/h1u3FAKmu1c33SD0dEgFhbW2v7sEIQM0qKfUGa1WGGxoO11FYtFrMfX8CshczTvTXuceK2QRj6/iZmZh8eJvPDCTRAEAc/AaPcX1wCCJOHuH8GdOzfh99sP1IyrTmAYBizDIHgAYjUBwFYTHCWJeej7ceXKMkiSwNSUMSaK6el+3LjxBgAG4XDnQpEosrDbnZoaWCjKAYIgIMu8JudKURSxuHgPx1z2ltd5NV9Btjb25gdbOcgALrZYl5l0O/BfyQwIgm3ahLkXt28rDV/2gH5CHkEQsPtDSCTaP7cYyb6EvJWVFTz77LO4ffs28vk8GIZpqtQSBIFvfOMb+3nJjmEYBn/+53+OH/3oRzh27Bi++MUvYnZ2FjabDXfu3ME//uM/4r//+7/x4osv4n//7/+Ny5e7O/Q9kylDkrrbnb1frFYPCIIAk9vZYcEWipAlCT5fL1Ipc3SeAYDb7Uc+r7juqF06EVIpRYC1WFyGr5uifKAoCunMBsZGp5veN5XeQDDYC5YlDF13OByFKMuIMzxGXY1ne9CihCTL4cTAkOHvM2BFX98ASuk4esZP7noPOrsJSRQRi42ZYL2PLna7o31HXk34Y1m5638bj0fZlKytZdu60F1byyEaHUQmo3+hJRjsA8vSqFbLcLu12ZjkC2nIsgy/P6zbe26zedET6MHt8v6EvNslGiRJIhLpxnfXhmAwhGomgcDY8b3vvgt0PglJFBCJjBweazRAkqywWm1g8525m9iC8jdwOv2a/j3Gxmbgcrnw/PP3uibkFQo03nxzHRcuzKFcFlAut/bviURiSHVxZlsjUukEhoZa2TNYMTt7Eq/cegtP9frgMCASTJZlXMmV0RfuQzAYbfOzQ+LE8VN468ZbCE6dhcWmX0GqsHoTBIATJ84dHm+aEIkM4Y033gBXqeo+j6aymUQsOohCgQXQeOY0ywoQRfNfM6qxlfk8DYfj4c/Y4uIqCIKEx9NeEZvn2R2CBs+3Np97O/6akDc/v4xQaHDH77JZ5ZxxUBx5gCI6FgoV9PT0Iq1hB7/W8DW3MUV5HrvjTm8wjOXNzqO7RI7DO+fm8PTTTwMAXrj6y46fi8kVQBAESHL3msfbb98GQQDDw+ZKohkeDuK111axsLAOn6/1ZuBqlYaF1M+/YLFYUS5X2/5Mv/HGawCMj9VUmXDbYSEIvPrqGw8dFwHglVdfgzMYgYXSN5qvXTwDYyiu3cHLL7+OmZlZo5ejK8mkkhZnOyhCnkv5bK+vbz70/XjrrRsYHg7C4bAZsbT6Ndgrr7yJ8+dbi8HfjVyuALvGUbMEQcBudyCTyWtyrlxbWwHNMJhsY+zVnTL90O12hDwAuHr1jX29t7du3YWFssPm0rfZwRHoQ+ruq1hZ2YLLZY7vFkkSTc1eHV3hVioVfPazn8WHPvQh/O3f/i1+8IMf4Pnnn8fVq1dx9epVvPLKKzv+U39+9erVjv8h++XLX/4yfvSjH2FmZgbPPPMM3vWud6G3txc+nw/nz5/H17/+dbzrXe8CTdP4/Oc/D65WIN4ex0XTdKOnB8Pcj7HweA6eu64TrFYrgr0hMLn8jp+rwl5fX/s2aT1RYxFzud1nL2WzFVitFl3mPrULSZKIxYaQye4+iH072dwWBgeHu7Cq5sRiSkdrgmkuxqi/Hxoyfs0AMD4+CTafhNxgSDWT2wRBkBgZGevyyh4vnE5XB9GaSvGm2zPyAMDv98PtdmNtrfXYOUEQsbFRQDT68MWRHkQiirtcyzl52Wyy9txRzZ7zQQiCwMyx41issmA7HB4PALcqDEZHx1tyH2nB5OQUmNxmw2PJXtCZBAiC0D129XGBJEm43G4IbPtFXgAQGOVxWu/pbDYbzp9/EjduJJBOd2dezpUrC5AkCZcuzbX1uNHRcWQyWx1HRmlBlS6jXC60HDf4jnc+BVaU8FrBGFfKQpXFJsNh7h1PdeS6npt7FySBRymunwtMEgWU1u9idvYk/P6DMWfFKEZGlM9dRed4TUkUUU1nW9prOhxOsCzf8UymblGpKHu6RkWRdDoJr9cPss3IO47nMFcTNObm5sDx7e0dAcDhcMFmo5BOPxw/rkZrWg+QI89KEBAEHr29IQh0d6J5O4GvKmsLtlFMfFSIRmNg8oWOnXQWisKVK1fwzDPP4MqVK7Dsw3lEpzMIhfsaupfW11fR1+czrMDeiJER5XOzttZeBBrP87BY9RXy1ONGO9y9exseqxUDdnO8zxRJYtRlx907tx76XSaTRjaThqvPHPWb7TiDAyCtNtzZZd2PGmpEpd6NRVpBWiywOZ0oFB4wfrAMEok1w9x4ANDX54XX68DS0sK+nqdSqcCug7htp5w70gH3w/z8PRAAxpuYLR6Ee8Bk9ODtZoQpK7w2KxYW9ncts7q6Ars/rPu4LtXxd5DiNdu+wpQkCX/0R3+EH/zgB5AkCT09PZienq478c6dO4fJyUlYLJb6z8bGxnD+/HmcO3dO29W3SKVSwXe+8x0ASrzmbpsWgiDwe7/3ewCAtbU13L6tZLr299/vlt4+L+9BNjfvCy59fcbPWOsWA/2Rhxx5TDYPkiTr81XMQiCgCHnZ7O4HxGy2gkCgR/e4u1bp74+gUMg2dblyHINqtYyBgUgXV7Y7Xq8PPq8P8T2EPPX33RIz9mJkZBSSKIAt7R4fxuSSiESisNtbP/Ed0j5ut7teOG8V9f56zz/bDYIgEI0OYn09v/edayQSBYiihFisO5995bhAIKehkJfLpeBwOBEI6DvTZnp6FoIsY77S2ayXNMcjxfKYmenMHdcJ4+OTkAQeTKGzuYR0NoFobMgQYfpRxel0tt0goKLnDM6LFy+DJEk8/7z+kX08L+KllxZw9Ogx9Pa2F28yOjoGSRKRyTbe/+pNMhWvr6UVYrEhjI6O4aVcGWKX5xACwJVsCR63p+O5c9HoIGKDwyiu3dZtjmI5sQiR59oWdh9H+vsHQJIk6Iy+syKZXAGyJGFwcGjP+6p7nmq1s2Nbt6hWlT1ao2NoJpOG19O+kEzZdgoaVAfOVYIg4PUEkMmk236sWZFlGb29IfB0BZKBzRfN4KtFUJQdbvfj0fS8HfW6l852diyxUDawLItnn30WLMvCQnUu/tCZHGINrsNlWcb6+ipGRszlxgOAwcEALBYS6+srbT2O53lYLfoJeaTFAp5v7zsnSRLm793BlIvSvUjdDlMuO5KpJPL5nde3d+8qIpm7b+9zVLchSAucvTHcuXur6/Onuw1NK4YEi+Pg1KWsDgoMs9NIsbKyBEmSDRXyCEKJ9Vxc3N/c8kqlorkjD1DiNatVbYS8hfk7iDgouLs0i5MgCEw6KSwu3K2nM7QLw9BIpbZ0nY+n4vCHAILA2lp75xYjaVux+PGPf4yXX34ZAPDpT38aL774Ir70pS/Vf//tb38bP/zhD3H16lV87nOfg8vlQj6fx6c+9Sl861vf0m7lbbC0tFQf2hqNNnYRbP/d+roSfRAIBOqZuXfv3m342Hv37hdjpqam9rXeg0R//4CSs77t4EfnCwj2hmDVsfOpE4LBvYS8al3sMwP9/QMQBB6VamM7daGYrd/XDMRiQ4izzTvS4gyHnkCPaWzLavczs0uhUpZEsIXUoRuvC3i9PghNXM+7wVdpUJQdFGXMZjYaHcTmZgEc19rFm+re65aITVF2hEIh5PKdCUu7kc2nEI3GdL/oHBkZg9PhwK1Se58Jldu1x01PH9NyWU0ZG5sAoMTxtosk8GDzaUyMT2q9rMcaVwdOXxU1ulcPR6fP58fx46fxy18ugab1Lca/9toKymUWly+/q+3Hquc+VUwzglQqAYqiMDDQugv4He94Dwq8gLdLuycw6MUmw+FehcGTl9+5rz3wxQtPgivnOzqWtEJx7RbC4f7DvU0LWK1WhPv6Oy6+t4oqFLbyOXe5FCGvXO7MbdwtymUOFGWDzba74JDP5+F2tx+XZLPZdwgaNltne0C324t8/uG/qyoyVQRzOx5VZFlGRRDh8XgQDCrNGqrzzWzwlSKCwV5TCRfdQm3io9NZQ9fBV2nwVbrhtUg+n0O1WjWlkGe1WhCLBdp2TXAcB6tVP9ebzWoDy7bXeBiPr4FmaBwxSaymirqe+fk7O35++84tUJ6A7hF3neIOD6FULGBry/g4+G5A4CAdQwk8qJMtLi7AYiENn8M5NRVGuVze1Z3fKjStj5BntztR1cCRx7Is1tZWMNGGG08LJtwOVGkam5uJjh6/uroMAHD06F/nJq0U7N4glleWdH8trehIyAMU590f/uEfgiTJXTdjLpcLv/M7v4NvfvObYBgGn/rUp7CxYcyB1bJtuG0q1fhLut1xt93hMTendKy+8MILDdX6n//85wCAWCyG0dHR/Sz3QNHXpzgWJUGs/4zNFTBgEmFpOx6PFxaLBdlso2jNaj1+0wyo4lyhsLtTDADyeeV3ZokxjcaGkGZ5ME3ifuKsgJgJokBVfD4//IEe0LmHhTy2mIEkChgZGe3+wh4zvF4f+CrdViwhX6Xh9Rl3QRGLDUKSZCQShb3vDGB9PQeHw9HV40w0OohcThshT5JEFAppRKMxTZ6vGRaLBUeOHsPdKtuRq+ZWhcFA/0BX32u324NwuB9Mtv29DpNPQpalluMDD2kNp9MJqcMYK1XI08shOTf3LrCsgJdf1u+iQZZlPPfcPQwMROpCczu4XG709fUjmex8rs9+2UquY2hoZMdefi+OHJlGuDeMK9lyV7uzr+RKoGrRqfvhxInTcDicKK5qHxPF5FNgCmlcvHj5sSymd0I0EgOTbd193wl0NgebjWopclB1uB0ER54qOj4Iw9BgWQZul3HjDNwuH/L5/EPHCHXEQnnbta2Z4SQZvCTB4/HWE1rYYuNrR6OQZRlcKaNrNLuZ8Xp9cHs8qOrs7t0LOqMIiY328uoMrkjEnLHLkYgfqVR7SSM0XQWl41w3inI0HcGzG3fv3gYBZS6dmQhTVvht1roDD1CE0KWlBbh2mZtnFlxhZW137tw2eCX6cnAdhzvXvbQ0j5GRXlCUscaPycm++no6QZIk0DSjT7Sm3YGKBo685eVFiJKECXd3Z1uqrzc/39gM1YyVlWUQBAlHoDspf46efqytrUAUD8ber20h78aNGyAIAr/xG7/R0v1nZ2fxW7/1WygUCvjmN7/Z9gK1YHz8/oycZ555puEf59/+7d8AKAXEkydP1n/+sY99DIDi0vvRj3700ONWV1fxk5/8ZMd9HxfuC3mKI0USRbDFEsLh/mYPMwSSJBEIBJDJPHxAZFkB5TJjKkee+t7mC41jXwqFDCiK0j3mrlXUbsNGc/Iqgog8x3ctWrBVRkfGlDl5D2yOVHHvsGtdf7xeRZAT6NY7GoUqDZ/XOCGvv18pmGxttdb5vLlZRH9/pKvF02g0hkq1BIbtzNm2nUIxC1EU67P39GZ6+hiqgoh4m44lWpSwWmUx3cVYTZXx8Qkwua225+TRWXUW56g+C3tMcTicdUGuXUSWg81GtSUgtUM0OojR0TE8//y8brOu7t7dwuZmAZcvv6vj487U1FEkU3EIQmeC6H6oVIooFDI4cmS6rceRJInL73g3EgyHxWp3XEtFXsT1Io0nzl7cd+KAzWbD2bPnUdlagcBq6yosrN6CzUbh9Omzmj7vo0wkEq27WPSCyeQwMBBpKd5fbTY1vyOPbRirWSgowmgnjjytcLm94HnuoQJ8Xcg7IMUcdZ0ejxfhcB9sFAW2ybWjUQhMBQJLtxQf+6gyGBsCnTJWZK0kMyAIoqGgqjpT+vqME9mb0dfnRblcBsO0djwWBAE8z+tSaFdRhLz2ztXz9+4g5qTg0mmP2SkEQWDKZcfC/P1IvHh8DZIowtlr/CiXRlgdLlCeAFYOkKOmE+qlqoPUh0XsCG8Dy7JIJOKYnDR+DFMo5IHP58TycmefG+V7L+vnyKtW9y3eLizcg5UgMOLsfK5qJ3itFvTbKSzMdzZGYnl5EXZ/L0gd3dTbcfYMQOB5JBLGNa+2Q9tCnpqXPDR0fxO2PT5mt26Ud7/73QDuu9a6jd1ux8c//nEAwOuvv45PfvKTuHXrFkRRhCzLWFpawp/+6Z/ipz/9KQBFjOvpuS+MXLp0Ce95z3sAAH/5l3+JH/7wh3Ux8M0338QnP/lJsCyL/v7++py9xwVVQJJr7wdfVjYxZnK2bcfv70E+//BGS/2Z32+e7jOHwwmfz49CoXEER6GYQTjcb5qu6r2EvEQtdtMs8/FUBgeHIbBViA+IHWwxA6/XXxeZDtEP9T3m2+hoFGjG0L9NINADi4VEMtk4/nY7qVQZoVB3s+BV0U2LOXmqs69b39/xcSWmut1C/EqVhQxgYqL7MddjYxPKzM1ie0U0JruBaDQGu7273XKPOhRF1RuN2kUSxIaRcFpx+fK7kctV8NZb+kRXPvfcXXg8Hpw8eabj55iamoYoitjcWtNwZa2R2Fiur6FdTp8+C7fLhZdzZW0X1YCr+TIkWcbly+/U5PnOn38SsiyhFO+sS3g3JIFHZXMJp06dgcNxeKxpFTXuUq85ebIsg87mW3YqKdGEwOZma2kARrG5WWq451EjLY115Hl3rEXF41GiNcsHJFpTXafH4wVJkohFh8B2OKtXT9hazPugiVJZus3o6DiYfEHXpoC9qGxsYSASbbjfTKeTcLkoeDzmcoqpqAJjq1F4qsCm5xgGO+UAw9Atz4ISBAGJRByjTnO+xyMuO1iOqzsfV1eVuVGOgHHzzFrBHujD2trKAXattYM5an+tsXOt8fgaZFk2PFYTUITrsbFerK0td/T4alU5vuhx/W63OyFJIlh2f01by0sLGHJSsLXQKKY1Yy4Kq6vLbbvcBEHA+voaHIHumYMcQeW1DkozQNt/TVW02z4zRN3wAkAy+XCxUL1Y3NzUZ9ZDK3zmM5+pC4pXrlzBr/3ar+HUqVM4deoUPvjBD9YddZcvX8Zf/MVfPPT4L3/5yzhx4gQqlQo+85nP4NSpUzhz5gyefvppLC8vIxgM4mtf+9qO9+JxgKLscLnckGpfTq6suN3M4hB7EEUYe9jxUyjQtd+bS7AJBntRrjR2+5QrRfT2hrq4oua43R54PR5sNpiTt1UT+MwWq1KPointFE35Us50a31UUb97fKW1i1tZlsFXq/B6jSsCWSwWBIO9SKX2FvKqVQ7lMlOfudotVCEvq0G8ZjaXhM1m69oxx+12o7+vH0t0exvYpSoDq8ViSLFIjcakM63Ha0qiAKaQ6ij68JC9IB5Mc2kDWfcmmenpYwgGg3jhBe3EGpVUqoRbtzZx4cLlfc1rGx0dh81G1UW1bpLYWEYg0INwuP3ikc1mw7nzT+J2mUauxTmmnSJIMl4pVHD06ExL0YitEAqFEYsNobyxqMnzAUAluQpJFHDq1BOaPefjgOq+Z/L6CGd8lYbIcS3Pu7bbHQgGexGP6xv3uR+qVQ65XKXhHrpUUvZNTqdx182u2muXSjv/ruqMvIPnyFPWPTQ0BLaYqTfZmgWmkAJpsdS/T48j6h6xsrn/5rpOkAQR1VQG4032m+l0yrRuPKBzIU8Px4wKZXdAluWWC+7J5CZESUTM0V2HTKuo64rHlQautbUVUG4/LDq6GrXAEQiDpqvIZMznSNYKdT/faZOiEciiuC86IlQAACAASURBVOM6ZG1NmXFpljmco6O9yOVyKJdba8zeTqU2w04XR17t+1bdR7wmwzDY2EwY1jQw6rSDF9p3ua2vr0IUhbq41g2sdhcotx9LSwtde8390LaQF4kom690+v4BMhwO14W9a9euPfSYhQXlzTCyO8Jut+NrX/savvKVr+D9738/IhEl3kySJPT19eE973kP/v7v/x7/8i//skOkVPF6vfj3f/93fO5zn8PJkyfhcDggSRLGxsbw+7//+/jxj3+M6en2O4YfBQI9Qci1WCiurHQ+m9WR5/X6UCzSD30W7wt5fiOW1ZBAoAfVBgPLZVlGtVoynWjaPxDFVoOi2SbLw+vxNJyZYRTqRSW3TciTJRFcOV8X+Q7RF9UNqzYD7IXAsJAE0fDPfyjUh62tvTd+qmuvt7e7Qp7L5YLfH9DEkZfNpTAwEG0p+ksrxsansEpzENrYPyzSHIaGRnR3U+2Gx+NFb28YdL7195stpCFLEkZHDyN8tYbYn46ne8MrSZI4d+4SFhZSLUf0tsovfrEIkiRw7tzFfT2P1WrFxMQUEhvLXd3Hi6KAza01HD0607Ggev78kyAIAlfz+rry3i5VURFEXLz0Dk2f9+TJ02CLGXAVbQSk8sYiPF7fYVx4m7jdbjidLrAFbb+jKmxeed52HPuRyCDW180r5KkiY6MobjUWT0+XzF6or80wOxs8LRYLPG438ry5hLBGqOtUEyoGB0cgSxKYNpMB9IbJbyESie2rseSgE40OwkZRKBsk5FVTaUiiiNHRZkJe0tRCXm+vGyRJtCzk1QvtOopQ6nNXKq3tNdbXFYHMrEJeiLKCIsm6c2p1bRn2Ls2p2g+qY3BtbcXgleiH2sDczigSo+Fpuh5ZDQDr6ysIh71wm2Q+5MiI0oDXyedGFdn0itbc/hqdsLqqXLuNuAwS8mqvu7zcXlOiKqY5e7pbh3UEB7C8vNSyu9pI2q7GzczMAABu3945SPTs2bOQZRnf+MY3wG2bR1IqlfDP//zPNduq8ReO73//+/GVr3wFzz33HN566y28/fbbeOGFF/DVr34VH/7wh5sWC2w2G373d38X3/3ud/Hqq6/i2rVr+OlPf4rPfvazCAbNKVx1g55Azw5HHkEQphPEVHw+P0RRQqWys2NKFfLMFqGoCHnlXQ8mNF2BJEkIBMwTBwoooliK5SHuUvDb4gT0D5jP4eZyueD1+ncIeVy5AFmWDoW8LuHxeGG12sCVWrsIUu9ndNNAKBRGOr37d3Q7qpAXCnX/QigSiSGf319BR5Zl5PMpRKPdmY+nMj4+AV6SWp6TR4sSNhkOY+OTOq+sMSMNZm42gqnN4hweHtVxVY8rBDqV8mTIILoQXfPEE+dBkiReflk755UgiLh6dRlHjx7TZD929OhMfV5dt1Dn8nUSq6kSCAQwM3Mcrxaq4HW8KHs5X0aoN6R5nO/x46cAQBNXnsizqKbXcfLE6a42YzwqhMLhuuCmNUxBEWrbcZ5GIjFksxVUq53NANWb9XUlrrKRI4+maRAEAWuXZp/shq0u5D2cBBGNDWGd6f5c0E5Ypzn4fb56oXRsbAIEQaCa1ieyuRNEngWTT2Fq8ojRSzEUi8WCkeFRVDaMEfLKtddt1DgmSRLK5RICgf3NedUTq9UCr9eJYrG143Ghdnx1ufRz/7pqMb3FYmtNN/H4OpwWC3ps5pqPp0ISBKIOG+LrayiViqhWKrD7zS/kUZ4ASIsViYR5jn1aozrGD4qQJwkCRI6vO8ZlWcbq6jJGR81TOx8cDIAkibpTsB3qQp4OjQKOmpDXaoPAbiwvL4IkCAx3eT6eisdqQchua1vIW1xcgN3XC0uXm72cwQhYlsHmZqKrr9sJbV/JXb58GbIs47nnntvx89/8zd8EANy8eRMf+chH8KUvfQl//dd/jY985CNYXFT+cB/96Ef3v+JDTEdPT089voMrVeD1+WEx2eBeFTW+78F4zUKBht1uh91ujs4QlUCgp+68exA1ctNoR9KD9PcPQJBlZB9w5YmyjBTLmzZSJRKJgCvdn5OhinqHQl53IAgCgZ6elh15ZhHyenvDEEUJ2WzzIefpdAkkSWgWu9YOkUgUhWIWgtB5UapcLoDnufqsoG6hxhAtVlu7YFmuzcczMqZyZGQUIseAb9FFQ+e2EAr1mc6p/ChAdK7jdcWRByhNDDMzx3H16goEQRsHyNtvJ1Auszh//pImz3f0qNLEF090b27AenwRVqtt3+LYxUtzoEUR14vNj9Gdsk6zWKc5XLz0Ds0FMr8/gJGRMVQ29/++V7ZWIEsSTp48rcHKHj/CoX6whfZjl1qBzZdgo6i2mgnVphqzxmvG43l4vd4dXfjbYRgaFOUwdMY3ZVOu+ehdCqJDQyNIsRwY0fxd2Wssj6Gh0fptl8uFwcFh0Kn2oqz0hE4nAFnGkSOPZ3rRdsbGJkHn8uANKMSXN7bQPxCB07m7UMdxLGQZcDq1EdgZhofdbsd73/te2O12MBqJ4w6HDSzb2iiGYlE5RuoZ46vG9Kqi4V4k4quIOWyGHv/2IuagsLmZqDsfKZd2ze4Sz+34XEi8Ng0pBEHC5vIhm+1e01m3Uc+pPG3cnM12UI9z6rrz+RwqlUrdBWcGKMqKWKynozl55VoancOhffODvfacqqu4E1aWFxG120AZ2MA34qCw0obLTRAErK4twxFsLW5eS5y11zwI8Zpt/0Xf9773IRqNYmNjA2tr9wff/+qv/io+9rGPQZZlrKys4Otf/zq+853v1OfiPfnkk/jt3/5t7VZ+iGlQu71lSQJfpeE3qRsPuL9W1YGnUijQppuPB9wX6Sq7CHkVkwp5qvC19cCcvCwnQJDllmeAdJu+vgFwlXy96MtV8iAIsutRiI8zPYEguFKLQl59HqexQp76/cvnmxeJc7kqvF6fIU0OasEvl+98Tp762G478lwuNwb6B7DcoiPPyPl4Kqqzjq457ZohyzLYfPIw6u4x5/z5S6hUWFy/rk0X8UsvLSIQCGBy8qgmz+fz+RGNxrCe0M412AxZlhFPLGFiYmrfEbljYxPo7+vHy/mKLtGgL+fKoGwUzpw5p/lzA8CJE6fAlnL7jtesbK3A7w8gFhvSaGWPF+FwGDxNQ2C1d8CxhQJCoXBbRd1YbBAEQeDePWOcPc2QZRnz8ykMDY00vA9N06BsxsbKWSxWWCzWXR15Q0MjkAGsM+Z0PKqUBBF5jsfQ8M73+siRaTCFFMQWxQ69qaTXYXc4Do8/ACYmlMSIcmKzq68rCQIqWylMTjR2Raoxs1oJeTTNY25uDk8//TTm5uZA09oIeU6n9aFI3EYUiwVQlB02HY83qttPFQ2bIQgCtpJbiDqMcyO3QsxBQRDFupPGqqWQJ3A7PheSoN1x1uryIpM1V6ywltjtymf5oDjyhAeEPHVW2vCweRx5ADA01INEIt52pGKlUoLNRsFi0T4yer+OPJ7nsb6+Zlispsqoyw6GZZBMtnbOW19fhSgIcAa7b6awOtyg3H4sLj6CQp7P58Ozzz6Ln/3sZxga2rkZ++IXv4i/+Zu/walTp+B0OmGz2TA1NYXPfOYz+Kd/+ifTurQO2R9OZ81FIMsQWRYul3njGFQ7eqm08+RXKrHweMwn5KniIk0/LG4wjPIzr9dcwmk43A+CIB4S8tTbZnW49fT0QJYkyLLiiOCrZfj85nWXPooEg0Hw5dajNZ0ul+EuWnW2Xz7fvFiSz9P1+3YbdUZNLte5kJfNpUAQJPr6ui/EDw2PIs5wkFoowscZXplBYsB8PJVQKAyny1WPzGwGX85D5FmMjIzqv7DHEEmSO+54JkgCstSdmXDj45Po6enBSy/tXyhLp8u4e3cLZ89e1NQhNj09i3R6Awyjj7NtO/lCBpVKEdPTx/b9XARB4OKlOWwwHOIaF+VpUcLbJRpnnjgHh0Of+TuqGEtnNjp+DlmSwGQ3MTV11NQOADOjxmLrMSePK5QQbmM+HqA0uYyMjOGtt8wXIba2lkM+X8XMzPGG9+F5ztBYTRWr1QZ+FzfI4OAQCABrNPvwg0zEeq3J6UHRVHW+mSFeU5Zl0Ol1TE0ePbymgjInz+F0ohTv/JjeCeWNJGRJwmSTeFNV1HZoJDI5nTZcuXIFzzzzDK5cuaKZQOh02nYV4HejUMjXHXN6YbXaYLc7UCjsLeSVSkVIkoRem7lnRQZrsZ+pVBIgCNic2qWGkFZqx+eCtGonstqcXuRy2a7OdO42Pr+/5VEkRqOu0+9X6pWJRBwkSSASMVf9cmgoAJZlkctl977zNsrlsi5uPACw2ShYrba6669dtrY2IEoihgyexTlUi/WMx1tLCVhaUq6FnT3GmD8cwQEsryyafk6eph5LgiDw8Y9/HM888wxef/11XL9+HT/84Q/xB3/wB4YW1Q7RF7dbOXjJkgSR5UwdD6bmMz8o5JXLbMP4FyNRhcfd4iMYlgZJWnQrHnWKzWZDwO9H+oFoTfW2WR1uqrNLjYkVmJLhsY2PGz09QQgsB4Hdu3DCFsvo6TE+lkHdmO7lyMvnafh8xgh5fn8AdrsD+ULnHYr5fBqhUNiQc3ksNgRGlJDlhab3k2QZCZZHbNDYjm+CIDA8NAK2sLdwytScjs2cC4d0jixLIDoUswiCgCR3ZxNPkiTOnDmPhYXkQ4kB7fLGG0pahtYOMVVU60a8Zjy+uOM198uJE2dgIS2ax2veLFUhyLJubjwA6O0Nwev1gc50Pq+BLWYgChzGDZwdetBR965ax2tKggi2XOlofu6xYyewsVFAKqVP5GenXLu2DpIkcfRo4+8vQRAdpx5ry+7NHg6HE+FwH9ZaTAMwilWahYUk6w1bKpFIDG6PF+WtFYNWdh82n4LAVOsRzY87JEliYnwK5fhmV8WGUnwDFou1Hlm/G1o78pQITBbPPvssWJbVTCB0OFoX8vL5HJw6zsdTcTm9yOf3FvKqVWUf4jK5qK2uL5/PweZwgyC1Wy9po3Z8LkgN3ZJWlxeiIKBcNtd5UUv6+wZ0m9mrNUyuAIIgEKo1KyUS6xgY8MNmsvmQg4NKzW9jo73ml0qlDHvNOacHDruzY0ee6n6MGizkBW1W2C1kfT17sby8ALs32PX5eCrOngGwDIOtre665tvlcNr5IftGFe5kSYLAMKYW8ijKDoqiUC7vFApKJaYumpkJJcOeALOLkMcyNNxutym7q0OhPmQeKLpneB5ej9dwB1UjenqUiERZUoQ8kS6jx2SxpY867RTK+GIJ4Q4KX1pDUXY4nc6mjjxZlpHPVw1z5BEEgYGBCPL5zmcGFAppw9y0ahTTXm6aFMeDlyRTRDcNDo6AK+ch7jH3gSmkYHc40Nsb6tLKHi9EUaoNyusAguxqN97s7EnIMvbtsLl2bR2Dg0Oax25HIjF4vb7uCHkbS4hGB9uaGdYMp9OJo0dncL3EtOTsbZVrxSp6e4K6HnMIgsDExBSY7EbHRV86qzg/DoW8zgkGe0EQBNiitsVBtqQ8XyfngGPHFMebVpG8WiDLMq5fj2NsbGKPhBYCMIFjQvlO7X6OGBoexRrDQzTBOhuxQnOIRKIPNVmRJImTJ06hmlrbcx+iN6WNBVgs1qYOzceNqamj4CrVrhbjy/FNjI6ONW3I43klPcdsRfYHoShrfa3NkGUZ2WwGXo/+118ejx/ZFiId1aK822LuMqy6PpquwkKZq2m8GepaaVr/9Aij6OvrB1MsQdJorraeMLkCgr0hWK1WyLKMRGIdg4PG1EOaEYn4YLGQSCTa20+VSiU47Pql0dkdTpRKnZ0n4vF1OC0W9Bh8PCcJAhG7DfH1tT3vK4oiVldXDJmPp6K+thorbFbMfQY55ECgDkyWRAmSIJo6WhMA3G73DkeeIIhgGN6UQh5JknC5XGDZhzcjDKsIeWakNxSuCXn3L34znIheEwgvjVCLnrIkArIMnqkeOvK6zP3oquaFMkkQwJYrphE/fD5/U0detcqB58W6e88IBgYiyBfSHRWCeZ5DuVJEf78xQl5fXz+sFisSe3TGx2uzN8wg5A0NKTP69nLlsYUUBmNDmkYgHnIfxZFn/mhNQPmch8NhXLvWWsfibmQyZayv5zA7e1LDlSkQBIEjR2awubUKSdq7ePBgbF6rMXosSyOd3tDcvXHq9BMoCwIWq9pE5RV5AUtVFidPn9W9oWp8fBICx4Ar5zp6PJ1JIBTuM2XyxEHBarXC5w+ALWpbeFf3O53sZwKBHkSjMVy/3vkxAwAoytL0djtsbRWRSpVw7NiJpvczjSNPRsPv75EjM6BFEcsaHTO0piyIWKNZHGngfDx58gxkSUSlQ1ce+cDMnwdvt4IsS6hsLuPo0WnTJcgYycTEFACg2KV4Tb5SBZ3LY2qq+dxcilKcGxxnboGA44T6WptRrVbAsmxXhDyvx49cLrtnA1i1qoxGcVm12fczogS73Y73vve9sNvtYERtGtAokoCFIBTBVEM3nt6QtbXye6S4HGT6+wcAWdYl6ltr2HwB/bWxHKVSEZVKBUND5muUt1otGBjwIx7fW2zaTrlcvD9mSgecDjfKpc4ayBLxNUTtVlOYPmJ2GzY3ExDF5ueWjY04eJ4zLFYTAGxOD2xOz6GQd8ijT92RJwg7bpsVt9u7w5Gn/r8au2k2XC73rvERDFs1pfgIKAUJVpQgbrtKz/CCaWM1AcVZ5XC6IEsi5Nom3CgH1eNKT0+w1vHefGPKFpVuxk6iqPRAEfIaO/LUqDyt3CWd0N8/AJ7nUKm2vxlUIzkHBozZVFksFkQiUawzzbtv4wwHykaZQuBVxUQ1OnM3JFEAW8oexmrqiCTtx5FHdNWRRxAEjh07ifn5FMrlzobYqyKgHkIeABw9Og2e55BK7118jEXHmt5uxMamUnRWZzxpxZEjM7BTdlwrPDxzuBOuF6uQAZw69YQmz9eMsbEJAACTbT/mRZZlMPkkxmvPcUjnhHpD4DSO1uSKqpDX2X7m2LGTWFnJIp3ufF7O7Gy06e12eP31NRAEMDMz2/R+BGESR16DaE0AmJo6ApvVipul/cUd68XNEg0ZaCiaDg4Owx/oQXmjs2KUOzzc9HYr0NlNCGwVJ0+e6WgNjyo9PUEEe3tRTnQnuquUUGY2j49PNb0fVYsyY1lziyAsK9TX2oxMRrl+8Xq7IOR5AxBFEcVioen96kKeRo48RpIwNzeHp59+GnNzc2A02rcSBAGX1QJeEDSN1dQbotZw0Ipj86DS19cPAGBye0e5GokkiGCKpfp6VbdbLGbO+los5sfmZqLlpmee50HTNJwOHYU8pxvFDhx5PM9jK7mFmMGxmipRBwVBFJFMbjW9nyqeOYL93VhWQxw9A1haXjD1rM2OzyD37t3DF77wBfz6r/86Lly4gNnZWczMzDT979gxbWZdHGIu1KhEteBl1uhEFY/Hg1LpvpCn/r9ZRTGPx7PrjDyOM2+MqVqQ4GsHP1qUUBFEhELGF9ib4Xa7IUsy5NpcJLN+Jh5VrFYrAoGePR15ageaWYQ8t9uDSqWxW+x+s4BxbgjVTZfPtz8nT43kNMqRBwCxwSFssHzTWLw4yyEaGzSFu83pdKI3FAbTxJHHFtKALGNwsP3i2CFdostNjMePn4Qsy3jrrc7moV27FkckEkUwqM/80PHxKZCkBYmN5T3vOzV5El5PAHa7E+fPvRdTk62Ji/HEMlwut+bOWpvNhtnjJ3GzwoDXoNB1rUQjFo115TwUCPTA7nCALbXvyBOqJUgCj2h0UIeVPV6EQmGwxbKmF/ZsoQSnywWns7MZK2fOnAVJEnjppYWO1zA3N4FQyAOPx46Pf/wJzM11JvoKgohf/GIRU1PT8PmaJxBYrVYIorFigSzLEEUBlgazqijKjqkj07hZ0TaSVytulmn0BnsVd8YuEASBUyfPoJqJQ9jlOnIvfMPTsLp8ICkHwrOX4Rtuv7minFiAjaKazkt8XBkfm0JlM1lvHtWT8sYmHE7nnhH5ag3n0RHylOsXr0f/RBRPzfWnioeNqFQqIAA4NLpWcZAkrly5gmeeeQZXrlzR7HkBJV5TFISO3LhGoYqOgvDoCnm9vWFYLBZUM52lNHQLJpcHZLl+3NncVK5tolGzCnkBVCqVlucrqvfT25FH01UIQnvH5GRyE5IkGT4fT0Vdx15z8tbWVmFzeWHVMa60FRyBPlQrFeTz5v2OdXSk/9rXvoaPfexj+Pa3v42bN2+iWCxCFEXIsrznf4c8etSLprUIqlbjk4zC6XShWr1fdK/WIlPMKoo5HI5dNyM8z5k2pkR1xAi1z0SWE3b83Ky4nC5AloDaRZXZY2IfRUKhvr2FvGLnUVR64PF4UC4zDc9xqpBnpDDcV4u1KBSzbT+2UMzAZqM0n7nVDpFIDJwkIdcgKkWSZWyxAqLRWJdX1pjB2BD4YuO5hGxRudiPxQ4L7HpBkmR9b9I2sgyS6K4oPDAQRTAY7GhOXrFIY2Ulg2PH9HHjAcp+ZGRktCUhjyAIOJ1u+H1BHJk82VK0iyzL2NhcwdTUUV0E+VOnngArSrjToeNRJcXy2GA4nDp9VqOVNYcgCAz0R8CV2z9+s7XHNCr2H9I6vb1hiBwHkdEuapEtlvYlBvv9AczMnMAvfrEEjuus+E4QBPx+J/r7fZibm+w4hun69ThKJQaXLs3teV+Xy71rk2I34XkOkiQ1HVNw7NhJlHgB63vM6O02tChhscri2GzzY+vp02cBWUYpMd/2axAEAavDBcoTgH94pu3PhSTwKG8u4cTxU03nsj2uTExMQuR40F0oxlc2FFf2XudVNa6SZc0tgrCs0FLjeCaTAkEQcLv1T0Txtijkqd8jrfrEHBYSLMvi2WefBcuycGg8e0+GDHR5L7wfiNpnfK8Iv4OM1WpFJBJDNdV+c243qSSV9Q0OKskzm5sJ9PZ64HCY83ygOgU3NlprplRn1+kq5NWeu1VxUSWZTAIA+uzmeK+DlBUWgkAqlWx6v/X1Vdh9xtf37AFlDe1GrXaTttsrnn32Wfzd3/0dAOVEdPr0aczOzsLv95uiC/4QYyAIou5islrN3bXjcilCXm+vcmBUnTQuV2fdsHpjtzvA8exDAinPc7DbzSnkqZGUQk3YKNS6SIwUAlrB5XJBlqX6Z1md/3hI9wiFwlhYmocsN447YgtFeDxe03z+3W4PeF4Exwmw77JhUmdyGhnf63Q64XZ7UCq2XzAolnIIhcKGZqyrsRxJVkAv9fB7nOdF8JJUFyzNQDQaw7Vrr0NkaVjsD59f2GIGbrfX0MjVRx2CIJUiRAfIstzxfL1OIQgCExNH8NZbr0EUJVjaKMjMzyvuz6mpI3otD4ASefl//++PQdMVzS9es7kkWJbec45Pp4yOjsPpcOBuhcFxX+fn97sV5Zg+M3Ncq6XtycBABGvxV5qeG3eDq7n4zHRsPKiozUNMoQiPU5v9B1coIXR0f+7Tixcv48aN63j99VVcujSuybo64YUX5hEMBjE5uff31+12QxB4CAJvWAOoKiQ2a7Kanp6BhSRxo0Rj2GmexJnbZRqSLGN2tvkswr6+fgwOjSC5fheB0eNd3ceVN5YgCTzOnr3Qtdc8SKiRyaXEJlxhfVz0AMCWymBL5T1jNQHUr6uYPaLsjYamefT0tBat6Xb7YOmCo8zl8sBisSKTaT4b2+FwQAbASTLsFuNnVzWDkWRYrTZIgrkaGZoh8cpaO3W5HxSGh0eQuPoSZEmqi5dmo5pMw+P1wu9XHLEbG3HEYvq7YztFdQpubiZaivcvlfR35DlqsZ2lUrGtOmo6nQQJRUAzAxaCQC9lQzrdWMgrl0soFPLojeh7HdsKdm8QBElifX0Nx4+fMno5u9L2X/Zb3/oWACAQCOCrX/0qTp8+rfmiDjl4EAQBue7IM8cBoxFOpwscJ9SLIao7z6yijd1uB89zwLb9iCiKEEXBNELGg1itVrhdLgisUuwq8EpX1F5RO0bjcrkBWao7qw4ded0nFApDEgTwVRqUe/f3n80XEQ73dXlljVGLQKUSu6uQVy6zIEkCDoexFxXhcB+KHUSzlUp5jI8bVxwEgHBYEfK2WB4z3offxySnFB1Uwc8MRCKKO5AtZuAKP+y644pZDJvIQfgoQpLEvhx5RojXY2MTeOWVlxGP5zE8HGz5cfPzKVAUVf/c6cXEhFIM3Nxaw9iotnPstrbWdryG1lgsFkxMHsW9OzfaFsS2c6/CIBwKo6en9b/Pfunvj0ASeAh0GTZX6zHNbCmLnp6g6WPvDwKqkMcWS/AM7L4HIR+4Bnrw9nZEXgBXre47XWBsbAJ9ff144YUFXLw4Zshxa309h6WlND70of/VUmOvum9iWBoeg4Q8hq3W1tK4COdwODExMYUbKwv4QNgPssP3lnqgKeTB2+1yo1SF3+drKYL43NkL+P73vwsmn4Szp3t7pGL8Dnp7wxgeHu3aax4kPB4vwn39KG9sof9U85mS+6Fcn4+3d2SuzWaD2+1GJqPNLFk9EEUJuVwFs7N7n3/T6VRX5uMBSi3M6w0gnd5LyFOuYWhJgl1j95zWMKIEh4sCzR8cIU/kFce80dfcejM0NIKXXnoBdDYPV6h7e9F2qKYymBgaAUEQ4DgW2WwG58/rd6zbLy4XhZ4eNzY3954DDqA+D9Pl1K9R2+Xy1F6rvTl56XQSPXYbrAY2YT9ImLJgq8mMPNX95vAbPzqHIC2w+3qxvr5q9FIa0vbZ48aNGyAIAn/8x398KOIdUkdx5CnFMrPHZ6jijFQr7plfyHMoQt42hFpnlMNh3sKM3x+AWPtMFAURFovFtPGlKk6nUxGka9Gaj/om0IyoEVNsvvGGhS2UEDbJfDxgu5C3e1xbuczC6XQZ7loPhcJtC3mCIKBcLhg+j9DhcMDv8yHF7d4lnKzFAKmCnxmIRKIAFCHvQSRRAFvOmSoK9FFk+96kXWSp+9GawP0usTyppQAAIABJREFU/fn55vEjD7KwkMLo6HjDeU9aMTAQhcPhrItuWrK5tYZwqE9Xl+rU1FGUeAFbHUaHcZKE5SqLqSMzGq+sOWo0JlfOt/U4oZw3dL7po0RPT1ApSDWJ//YPx5re3g6nUUw4QRC4dGkO8XgOy8uN45z15MUX52GzWfHEE+daur+6bzIyXpNhVEdec2H85KknkOcErNCdR6oe9Tib3m6HsiDiboXFiZNPtCTanjhxCjYbheL63Y5fs124ch5MLolz5y4YmuZgdsbHJlDdSus6fqaylYLT5Wp5fxwKhbG11V6MWzfJZiuQJHnP6xJZlpHJpODzdi8NyOftaUHIq7keRf1nI+4HSZbBiiLsdgdkQbs4ab2ReHVkjjnrelqhzlevJs0ZrynQDNhiCUNDSqxmMrkFWQaiUXM39UejPmxttR6tSZIk7Luk7miFKhKqomGrpJNJhG36Xg+2S4iyIpvPNYy9TSSUsRJ2n34O9Xaw+0JIbMRNOx6u7QoFxykCwpkzZzRfzCEHF4Ig6uJHN+IL9oMq2Im1DVSlwoGiKNM6Ce12ByRJ3BEPpgp7rQx6/v/Ze5MfSc7z3PeJIafIuabMmufurp7YA5um1LQs01c4R7Z1bVqQeTbmQgv7XzBkQwt7wYUXArywfQUbkiDIhiwC1sK2gCOJGnDaEilR8mGzu9lkj2QPVVmVc8zjXUR+UVPOGZn5VXX+AA6VlRn1VVRmDO/zPs87LBLJNMzaksumhUQ8PnQhoxWBQBBuGrwDluP6XhAdcRjitNPK9YU8U1VhahomJmhy5LkC9d7Zm3uRJG2o8/EIk5NT0DSlo8JZtVY0psEBOZWZRq7BDKCcZiARi1MVpRKJCEim0nWFPF0sAo4zEvL6DM/zsLuck+FYFrghXBfE4wlMTEx6UZntUK2q2NqqeCJgP2FZFisrq9jMfezrzY1lWdjeeYLVtf648QgktvNDqbs5eQ9kDabj9C3+sxHE/Wcq7RdYHceBoYgYG6OzW/uowXEcUukxb05vPcY31hFMxMGFQ5i7egXjG43fz7vzfntvlHnuucuIRCJ4883bPW+rU8plBb/4xUNcvHil7abIeNwVz2R5eIKBrIj71tKI06fPIRQM4Z1S9y6lF1JRjAV4RDkW/28mjRdS3Tc2/ndZgu04bUdWhkJhnDt3AdLTe17sXL+pPLoNlmVx8WJ7wu6zyszMHCzD8ET9fqDkC5idmWtbUJ2YmML2tti39fRKLufuq1ZCXrVaga7rAxXy4vEUisVC0/lspElY7TYtYkDotlt5CofDMPXe5goPkmfFkZdKpRGLxSFttX+vMEjIfLy9Qh4AZLN0C3nZbBI7O9ttzVisVMqIRGJ9bVYJhSJgWbYjIc+2beQLO5ioM4pkmEwEA7BtG4VC/Yaz7e0cApEY2CGlNBwkEEtB17SO5xMOio6r6jMzboe5qh6dA/qIwUJ74x25ySSOPEXREfFp1kU/8ByOewpmluUWs8lQahpJJpP7HHnJJN3z8QDsCo2OA44diXjDIB5PIBAMQm3gyCOPD9shthdyTCHzNg8iSToVblTS9V8V278YFGtCXq+OAT+YmspiWzdg1xEPcrqJqSx9rpNsZhqGdNhBo1fdx0ZOmf4SDkdgmyYcu/POZ0s3EAkP59pgeXkV9+7teA1HrSCi3yCEPABYWVmHJFUgdnAsaUW+sAnTNLCysubbNuuRSCSRzWS9OXed8oGkIsDzWFoabNxwLBYHy3EwlPYLrLahwbZM6ucTHyUmxiehVRr/DRiGQUCIIJxKYmLjRNMCz66Q13v3cSgUwosvvoTr1x9jc7OzCKZe+clPPoBtO7h69bfafg25husm7tsvqpUigsFgSwdwMBjEufMXcUNUunbRMAyDBM9hMhjAC+nuC3+O4+BXFRnzcwsdNVhdufIbsC0T1af3uvq5neBYFqqP7+DUqTOIxdqPAX4WIc1c8k6hL9u3LQtqsYSZmcPx7o2YmJiEKKoNmxOHTbtCHnHGDSpaE3AdebZto1hs/Pc8Ko48pXbdHIvFYZsGLP1ouPJMRUQkIlDboO8XDMNgaWkF0maOSseQ+HQLHMd7zsFcbgscx2J8fPj1kGZkMglYVmOxaS+ukNff34dhGEQisY6EvFKpCNOyMEHJfDzCZG09jebkbe/kwEfpEXqDtbVsb3eWkDMoOhbyPvOZzwAA3nrrLd8XM+J4QOG5ZB9kTggR8lTVoHbWHLA7c3DvfiVdIjRfpCQSSdhw/W1l00ac8vl4APY48BywlOfWH1cYhsHExGRDRx55nCYhj4h0klT/JscV8oYf8UEcHaLUiZBX2ffaYTI1lYFpOygZ+7vkHMfBjm5SFatJmJrKQJfKh4QkXSyC5Tgq9utxhnTkWnrnBSlL1xEeUuT2wsIyVNXwClatePgwD57n+z4fj0Bm7eS2H/u2zVzO3dbSUv/FyPUTG3io6NC6KKR9KGlYXl4beIw8y7JIJJIw1faFPCL6jYQ8/xgfH4derfpSONMqVQjRqG/3IC+++BICAR4//OH7vmyvHWRZx7Vr93D27HMdNfyEwxHEYnFUKsMT8irVAiYmJtsS1S5fvgLDdnC9Kg9gZY15pOrIaQYuP/8bHb1ubm4BU1NZVB/137Ep5h7C0lVcufJi33/WUWdyMgOO46Dk+/M5UIslOHZn6Q8k8aTd649Bk8tVIQhCywZJIqbFY4MT8mK1n9VMBEgm3ecUjfoJI7RQrCWgZGtNkro4vGN1J+hiCRkKGzv7wfLyCnRJhi72NtPS0g2EQiG8/PLLCIVCsBqMsegEaTOH+fkFr1aZy20ik0mAo7y+ls26jT25JrPcCOVyua/z8QiRSLRjIQ8A0gG66sRkPWR9e3EcBzs72554RgOB2loaCY/DpuNP0he/+EVks1l8/etfx4MHD/qwpBFHFu8+iG4lb1fIcws4mmYeDSFvz361bLP2PTqsx/UgF9iWAyiWTUW0YCs8Ic9xwI4ceUNjYnwSerV+sVKrVMGyLFWFyXA4DJZlmkRr6n3v2GqHVMoVjSSx/W59SaogFApREVEyNua6FgoHbn5Fy4Zu21S4Bg8yOTkFx7ZhHIjD06UyxscmRvG9fcYT8rqYh2YP0ZFH0i8eP25vHtrjxyVkMtmBvZ8mJqYQDkewvdPeHIl22N55gsnJzECaHtbWTsB2nI5nXlUME3ndwOraiT6trDlj6TGYHTjyzJGQ5zvp9Dgs3YCl9e5W0asixtL+zQKJRqN4/vkX8c47D1Es9lbYa5dr1+5A0wx86lMvd/zabub2+kmlWmo7pn1ubgFTk1P4VXm4Qt47ZQkBPoCzZ5/r6HUMw+CFF16EWt6BWu7vTKXKx+8jmUxhdbW/McnHAZ7nMTWV7ZsjT9lxP1+dNPkQ4ebjj/uzpl756KMCstmZls8rFgtgGAaCMDhXaCyW8H524+fEIUQEbHY5p3dQkPWRGPFO5/MOA8dxYIglZKboa+zsByQZQnzaWnRqhqXruHr1Kl599VVcvXq1q+bH/dszIOeL+5Irtre3PJGMZjIZIuRtNn2e4zioVAYj5AldOPIAIEXZjDyBYxFgmbpCXrVagaHrCEYH13jRCj4cBcvxx8eRl0wm8Y//+I9Ip9N49dVX8S//8i+oVAYb4TGCPlyJyVXy6HfkuYW5XUeeiWCQfiFvf7Sm60ihuQhMinG240C1LKpmVzWC7E9nFK05VMbHJ6BVxbqzrbSKiFR6jKr3vht7INR15DmOA1nWqHDkhUIhCEIUotT+OVuUykinx/qa/94uRKjLH5iTR74mQh9NTNVuJg92sppSCZnMs3GjOUxIbHbXjrwhCdgTE1Pgea4tIc9xHDx+XBqYGw9w3WELC0vY3nnqy/Ycx8FO/ikWF5d82V4r5uYWwDIMPlI6e188rD1/UOs8SDKZgqW2LyQQ995RiDY/KpDzTLM5ee1iVETfG1A++clPAWDwox994Ot266HrJn7ykw9x4sQpTE+3LqwfZHJyCtUhCXmmaUCSKm3HUzIMg0uXX8DHiobckArwum3jelXB2XPnvXi+TnjuucvgeB6Vj/vnytOlCpT8U1y58iL1c9FpYXp6FlqhPyKJUigiGAx1dH2cSqWRTCZx715/Bd9uUBQdT56Usbi43PK5hUIeUSHe0fvQMLR9ziTD6KzZJxKOguM4FIuNHXkMwyCbncGmD66nfrKpGYgKAqanZxEIBI+EI89UJVimjqmp7LCXMhAmJzNu/WGzN6GBCwZx7do1fPvb38a1a9fA9Ti6R9raBhzHi/s3DAPFYhFTU/RHLYdCPNLpaEvxRtNUGIYOQRiAkCe4Ql67SRBEKEtSltzGMAxSgUBdIY88xg+w8aIVblR+HKUSnU0MHf91f+d3fgeAOyOvXC7jr/7qr/DXf/3XSKfTLS8qGYbBD37wg+5WOoJunIZfUMfBaE1NMxGLhYa5pKbsRmsenpE36GinTiBzw4zaummYETbiaDA2Ng44Dow6URF6pYr5cfoEEEEQ6s7I0zQTlmVTIeQB7g261EG0piRVMD1Dxw1RLBZHgOcPOfLI17Q68gBA3zNLzLEs6HKVyijQ40Y47H7uTK3z2R6mpg+tAYXjOGQy020JeaWSDFnWByrkAa6Y9cEHt6BpCkKh3vZTuZyHrmtYWFjyZ3EtCIVCyGan8bDcegbGXj5SNAQGGGF6kHg8AVNT4DhOW80VpqaAZbkj0Uh1VCAFcb0qIjrV/TnHtixokux7A0o6PYbz5y/i5z//v/gf/+M0otH+3d+8/fYDiKKG3/zN3+7q9VNTGWiaClkRB9LVvpdyxXXMdDJn7sKFy/j+//5PvFMS8dnM4MXx9yoKNMvGpUsvdPX6SCSCs2fO470b78He+A2wnP9FvurjD1zR89IV37d9XEmnx2CoKmzTAsv726SoizJS6XRHzXgMw2BxcQV3777f9rlmUDx4UIDjOG0JecViAdFoZw4g3dh1JgHAW2/9sqPXMwyDaDTR1JEHANnpGfzi4T3YjgOWov27ly3dQHZ6ERzHYWoqg0KFTofmXvSqu8apZ8SRx7IslpaWce/Rw562wwUDkAoa3nzzTQBANN1bvKG4uQWWZTE/787HI26ysbGjUQscGxNQLje//yK/U2Qgjrw4DMOAqqptXc+XSiXEAzx4lr5jS5JnUapzfKxW3eY4vsf7Sb9hgxFUq3Sa1jpulXr8+DEeP36MfN69+XUcB7ZtI5/Pe99r9s+I48quyETjwNW9BIOHZ+SRx2iERDzu3atkH9Pc7UiEC7O21siQZg11gmm6ggDDsDAturPrjzNEkDnY8e44DvQ+dLD7QSQSrRutScQ9WoTsdDoNSW7fSSDJVWpi2ViWRTo9hsIBR15BN8EyDDXr3EsoFIYQjcGUdy8CDVUEHAdjY/S9j48biYRbxDGkzuLQLN2ApetIDHG2azY7i8ePSy2vqYjY140jpheI6OaHK49so53inF8sLK7gkWrA6uCa9aGiY25uYWiO8FgsDsexYbfpErA0BdFojOprxaMGmWuqVdqPOK2HIUqA4/RlTupLL30aum7i2rW7vm+bYNs2fvzjDzA3N78vPqsTZmfnAQD5fG+xYN2Qz7uxWXNzC22/JhaLY2PjLH5dVWDYg7/X/UVZwuT4ZNf7GwAuXboCy9QhbfVW+K2H4zgQn9zB6tqJoZ47jxrJpLuvDNn/2FZTlpFMdB5Vtri4hEpFQaEwmIjedrl/fxssy2B+frHlc4vFAmIdzlsKBvY7k4KBzp1J0WgChUILIS87DcO2DzUm0oLtOMhpBrLTbszq4uIy1PI2bMprI0phEyzHeeeWZ4Hl5VVoVbHnOXl+Ij3NYXZ23quvElEsnaa/FggAqVQElUpzIa9cdoW8gczIq9WQWq2JUCoVkOTpvO5P8VxdR55YG/vCUSbkcaEIqiKd82I7bsV65ZVX+rGOEUccx3HAsAwcy4Fh0B0VwLIsAgHeK47puoVgjxby/rI3uPTo4DnybOLIo+vAXA8i5IFhPNfjiMHjCXnl/SdOU1FhGQaVQl40Gq17YULiNmkR8hKJJGT5/baeaxg6DGO4YsZBxicmkb9XgrCnyyyvm0gmU1TFre4llUqjqO7eYO3OraInB/64kky6+1gXOyuQ6ZL79xqmODw9PY133nkLlYqKZLLx+ZMIeZnM9KCWBsAtwjMMi3x+E3Oz3ReWAbeoHokIA43HXVxcws9//n+wqRqYjbS+BtRsG5uqjt8coNh4kHjcjZwxNQVcG5Hwlq4gFacnpuY4EAwGEYkIHTcHHESvvZ4co/wkm53G+vpJ/PSnd/Dbv30SgT7MSbl+/Ql2dkT8r//1SteOnenpWbCsewyZn1v1eYXNyec3EY3GOt7/z195Ee/deBc3RRnPJQZ3Xbep6vhY0fDZT3+iJ4fU8vIqEskUqo8/RHzG332u5J/CUCRcuvi8r9s97pBrbEOSEUr4e7w2JAWJxc6v4UlTzb17Oxgfp2fG/b17O5ienvXSlRph2zZEUcTSYmdrDwRC0Eo7njMpmej8flOIxLCV+6jpc8gcwk3VwESQvnSlgmHCsB3vunJ5eRX/9V8/hVbaRmR8sNeanaAWNjE/t0B5Xc9flpbc47j4NIex9eFdnxIsw4S8U8Dll857j3kz21L01wIBV3Aslx/Btu2GjXCeI28Q0ZoR97xQLpfbutcrl4qY9tnd7RfJAAepXIFhGPuS5arVKsAwbd3bDBI+FEE1V6XOnQ50IeS9/vrr/VjHiCOOK+RxcGDviiEUw3G7Qp5pWuB5+i6iCM2axWl2PxLrN4nWHNasoU4gswfBMLCMw/PZRgyGaDSGQCAIrbq/412vfd2PDvZeiUSiePy4mSOPji60RCIJ0zRgGDoCLTpN5ZrgFI/TI+SNjY3jzu2bEEIBkPaGomFibGo4UXftkE6lsfPwIdigewzcFfLocxAeNziOQzyeqBvT2wzy/GH+jUj06tZWpamQl8tVkUqlWha2/CYYDGJqKoN8sXc3TaG4hbm5+YHeJBFH4UNFa0vIe6TosDG8+XiA6wgCXKcd4q3fm5amID7WfnTgiPZIJBJQenTPGJJS21Z/zq8vvfRpfO1r/x9+8YsH+OQn/RVsHMfBm2++j7GxMZw+fa7r7QQCAWQy08gXNn1cXXvkC1uYm1vo+JizsrKGdCqNX5akgQp5vyxL4FgOFy5c7mk7LMvi0sXn8eOf/BCmKoEP+/c7VB9/iFAojI2Ns75t81lgr5DnJ7ZlwVAUz/HXCVNTWUQiEXzwQQ5Xriz5uq5u0XUTDx4U8MILV1s+V1FkAA7CQ3B3hEIRyLLctPA7OZkBz3H4WNFwNkHH/eFePqolzMzMzAEAlpZcgUgpPKVWyLMNHWplB8sXnxv2UgZKNjuNUDgMcXOLCiFP3tqGY9vefDxg172WStH3Xq9HKiXUmgGqDa/RiJAnRPp/HUDm8JGf2QzHcVCtVnCS0rFRiZrAWK1W9jVviqIIPhgGw9DlJOSCAizThKap1NWy6dpTI44srpDnvp1Mk25HHuAW94gGZpoWtU6ORtDWEVAPIo6S9Jmj0B1FXHgMGNi2RbVQepxhGAbJVOrQTa1OQXG9EYIgQJb1Q+8ZWabLkUdEOSLSNUOR3eeQeEIaSCbTMGwHe1OtSpZN5XuCkEqlYCqSl49sKCIYhqHK6XicSaXSnsOuXYiDrx9umXaZmJgEAGxvN4/02N4WMT4+OYglHWJ2dh6FQq6nc6VpGiiV8wOPQkomU0gmkvhIaS+m8mPFLWzNzy/1cVXN2RXy2iv4WrrivWaEfyQSKZiy0tM2SIxev86vKytrmJmZxY9+9IE3SsAv7t3bwcOHBVy9+ls9x7bOzy8gX9ga6PW2rmsoVwodxWoSWJbF81dexH1Zw44+mPtdw7bx3xUFZ86cQzTa+7XkxYvPA46D6hP/oldt04C09QDnzl2gen47jRChTfdZyDPk7psFWJbF2tpJvP/+pu/Hj2758MMcTNPCiROnWj5Xql3zhUKDd3eEQxHYtgVNUxs+JxAIYH5+EfeUww2gNHBPViFEBG/WXCQiYHp6Fkqh9yj1fqEUtwDH2ScgPQuwLIulxRVIm9vDXgoAdz4ewzBYWNiNv61USohGQ31JB+gHJAK0mXBWLpcRDgvg+jBr9iCRMInWbC3kaZoG3TA8wYw29gp5e9E0FSxPX62YrV3PaFp794qDZCTkjegZ27bd/6lFndEerQkAPL/ryLNtBzzf/4Nw99BxAd0p5Oberu3nQZzoesUwDIBhvBzTo/BePq6kkoeFPKOPUVS9IggCTNOCru93ctLnyHOLhkSkawYR+2gSnMjfnszeNB0HkmFS+Z4gpFJpd66E454rTVVCLJY4cg0kR5VUKg2j02hNUQLLsojHhydix+MJBAIB5HKNP6uO4yCXq3qi36CZnZ2Dpikdzd08SLG0DcdxhjLTZG5uAU+09lIkHqs6JsbG2xo03y9iMbcr19IbFwgJjuPA0tSRkNcHEomkVyTvFkNWEAyG+lZoZhgGL730aWxvV3Hz5hNft/2jH92GIAi4ePFKz9uam1uAYegol/M+rKw9dufjdXfMuXTpCliWxS9Lg5lJ9F5VgWpZeP7Ki75sb3x8AjMzc5A2H/iyPQCQtx/BtkycP3/Bt20+KwSDITAMA9vne067JjR3e846cWID1aqKx48Pjw0YBrduPUUwGGxrRqQkuddNodDg771CNReg1KKBbHllDZuqDsWyB7GstnEcB/cVHcsra/saNdbW1qEWc7DanNE7aOTtj8HzAS9t4VlieXkFWrnS83WJH4ib25iZmdt3baPrOsJhfxs8VNVAKBTCyy+/jFAoBFX17/gZCrk1S11vLLRXKqWBzMcDXANKJCx4zsZmEIEsTqmQF28g5BmGDobCWjHLtn4vDIuRkDeiZ4gDjzjyjoL4QRx5jicy0XmwA5rHZ9LuGGMYBuTylG6x1EVRFDAM69m6VXX4F0TPKsk6Qp4uyQgGQ9RZ24Fdxx2ZiUcgX9OyZiLKyUrrApRSe84wxYyDkM5lIuRVDAsO6BR3CaSQ7tSaXixNQSxOz8yR487Y2Dh0UfT2fzvolSqSqXTPbpNeYFkW4+MTTR15oqhBVY2hCnkAUCh0H6+Zr72WbGuQzMzOoaAbbRXSHmsGZrpw8PhJOBwBy3Iw9dbXJrahwXFsRKOjY43fJBIJGLLS0THlIIYkI95nt/uZM+cRj8dx7do937ZZKsm4ceMpnn/+RV+SNkhRfmv7cc/bapet7UdgGLbrgm88nsCpk6fx64oMawD3Ye+UJYynx3x1mpw5cx5qeRtGG+kM7SBu3YcgRNsSWUbsh2EYcDwP22dBx66Ni+j2/nt9/QQYBrhxY/guLMdxcOPGJlZX19v6feSa43kYjjwi5Mly8/uslZU1OAAeyHQJY0XDQtkwsbKy/3izsXEWjmND3n40pJU1xnEcyLmPsL5+4pl0BJPjrriZG+o6bNOCnNs5dB6wLBM87+/9lKIYuHr1Kl599VVcvXoViuJf/ZmviU3NxkWVy2Uv8nIQRIQYKpVSy+cR1x6tQl6i5sqsVPYLebqug2F7X7Nt6PsEXtvoTYBjaucbGvWNjs/s3/3ud7v6QaFQCPF4HIuLi5ifH3zX7Yj+Qd7YJO7R6PEDMwh4noemOZ4QRrPIpOv79y+wG1tJY3fAXhiG8Rx5NO9jgqLIAMO6/8C9EaDJjfQskUym3I71RAzEImmIEpIpOgUbEndUT8iLRCLUNAsQUUlrI5pN1WQEAsGBz95qxkFHXrl2kU2zkBeJuB3BjmODgVtgj1IcBXrcmJycgmM70MpVhNPtHc+1UgULUzN9XllrJiamsLnZuAify1W95w2DbHYGDMOiUNzGwvx6V9soFrcRjcaGcq4lLsAnqo7VaOOCn2haqBjmUMTGvTAMAyEabcuRR54zEvL8h5xHTVVDQOiuScdUNaT77JbkOA6XLr2An/70TRSLEtLp3mMZ3377ARzHweXLL/iwQnfmcSKRRC73CCfXBzPbKJd7hNnZuZ6ubS5dvoKbt97DB6KKjXj/GrXyuokHsob/55Mv+zpW4cyZc/j+9/8T0uYDpJZ7m2lnWybk7Ue4dOHSUJtfjjIBPgCnSdG4GxxPyOtO2IjF4pidncetW0/xP//nGT+X1jFbWxUUixI+9amNtp5PYi0DgcHfv5D5462i2ObmFhDgedyT+3sM6ZR7srvvlpfX9j0+N7eAaDQGKfcQ8Rm64iu1Sh6GKj2z8zmnp2fBBwKQNnNIryy2fkGfkHfycGzbm6lIME3/hbxIJIBr164BAK5du4aJCf8+Q2StzYS8SqWEudnBNVEKkVhHjrwEpTGmEZYFxzCoVvf/LrrujyPPNnV8qibwAsBPf/Z2T9tjOXpr7h3vrT//8z/v+UIynU7jD/7gD/Cnf/qnSKdHxayjjqq6J3y2VqhWVbo6i+rBsiz2NlHSNlhzL0YtwmDvGslFOe2iaT3xkWYkWQbDMJ671B2WPWIYEGHGsWwwtWOLIcmYSg/HedIKUiwVxf3HP1HUqCqkhkIhcBwPRW1DyFNlqtYOuPuZY1lYteN32XALFTQLeSRW1alFa9qm7ol7I/rP5KQrcqnlSltCnmPbUMsVTJ4ZfkTY+PgEbt58F5Zlg+MOX6fs7Lhuir0DwwcJz/OYnJxEqdT9bI5iaQfT08MRTWdmZgG4sZnNhLwnql57/nCFPACIRWOoaK0deVbtOSSOc4R/EIe9petdC3m2riOS7n/x9vLlF/DTn/4QP//5fXz2sz0KNraDn/3sPlZW1jA+PuHL+hiGwfLyKm7fft+dt97nGeCmaSBf2MLVq7/V03bW108hFo3hV2Wpr0X4X5clMAyDixcv+7rdiYlJZDLTqGz1LuQpO49hmwbOnDnv0+qePfg+OvJ6cSidOLGBH/3of6NaVRGPD97dRrjcCw5KAAAgAElEQVR582ltPa3n4wG7iUVsn48n9SDHsFapSTzPY35hCfeffDSIZbXNfVlDLBr1rp0JLMtiY+MMfvXfv4JjWd69OQ1IWw/BMAxOnTo97KUMBY7jsDC/iKdDnpMn1RyBi4v9F/LC4QA0rYQ333yz9rV/CQdkrZZVX8jTdR2KogwsWhMABCGOnY9bx6R70ZoUfT73wjAM4gH+kCPPMAxPNOsFlg/uE3jZYG8NbMQlSGPNvatPlOM4Pf1TKBTw9a9/HZ/73Odw8+ZNv3+nEQOGCHkMx4JhWWhtFBiGjXuzuP9rWiEdAHtvbgM8GbxJ30FlLwx210yLI6kZsiwBLOvt65GQNzzi8f1xhIDbwU7rvJ/daM39n0lJ0r3v0QDDMIjFYlDbFPJoKwKzLItEIrHHkUeEPHqds16sKpnLamhDnbP1rEFiJ7VS605GwJ2P59j2oSLGMEinx2DbDkql+p/XfF4EwzBIDdHhmc3OoFTa6eq1tm2hXM4jmx2OkCcIUaRTKTxWm19LPVZ1MHC7nodNLBaD3YYjj8Rv0taMcRyIRNyCttXDNbil6QOJ3B4bG8fq6gm89daD3ZnmXXL79haKRQlXfJrVRlheXoWqyqhU+j+La3vnKWzb7jmmkuM4XLj4PG5LKkTTav2CLrAdB7+uyFhbPdGXZqUzZ85BKW615fBthpT7CKFQGCsra62fPKIufCDgzlL2EdvszZEHABsbZ+A4wI0b/s7Z7JR3332MmZnZtj8H5FjX78aAepCf2c7xdnV1HZuq3rdjSKc4joO7so7llfW6+25j4yxs04CcH+774SDS1gMsLq5Qdb89aJaWVqAUijCHWBsUN3OYnJw69HdwhTz664CEVtGaJL5SEAZXkxIiMaiq2tLpK4pVBFgWoTrNn7QQ4xiI4v6xEZZteYlovcAGgtA0DW+++SY0TQMb6C0Cnpg7er1+7gcd760f/vCH+Ld/+zecP+92XZ09exZf+tKX8K1vfQvf+9738L3vfQ/f+ta38KUvfQlnz7odXufPn8cbb7yB7373u/ibv/kbfPrTn4bjONjZ2cGf/dmftRwGO4JuvDliDAM+GPSEPZrZFe5I1xR9H04COWDXj9ak3/14lFBk2XU+7onWHDEcyEXgfiFP9SIsaYOsSxT3H/9oc+QBblyO2la0puIJqjQRjye9uTSiaSEUDCIYpCf+8yCeI8+2AQcwDW3kyBsgoVAY8XgCarnS+skA1JL7PFqEPADI5+tfJ+fzEpLJ5FAbZaanZyDJVS/KqhMqlSJs2xqakAcAM7MLeKI1L6A+UQ2Mj08gHB6eI4EQi8VhtTEjb+TI6x/k+G31ELVj6cbAGjquXHkRpZKMW7c2e9rOz39+D4Ig+B5fRkS1rdzHvm63Hlu5j8EwLBYXl3re1qVLV2A7Dv5vpT/3CvdkDWXDxKXLV/qy/bW1EwAAJd/9DDTHcaDkn2BlZe1INGzSCsdxcGyfm4pr90/13Pztks3OIJVK4fr1wc2wPEilouDhw3xHxx1S5xlG4hL5me00ia+tnQQA3JHoqJ1tagZE08T6+sm6319dXUcoHIb41L+5q72iVQvQxRLOnXu2HcHEBSfnumus6xV3TmEei4uH56TyPA/DoEOsbgey1kZjgcpld1bdIGfkkZ9FRMRGVKtVxCgXTeMcB7G6/57cth0w7OAbL1riHc/p0wo6PrtNTk7iL//yL3H9+nX8xV/8Bd544w289tpruHz5MpaXl7G8vIzLly/jtddewxtvvIEvfelLuH79Or785S9jeXkZn/vc5/AP//APeP3118EwDHZ2dvDP//zP/fjdRgwIUrxhGBZcMHCEhDzGc+XR7sg72E13VGbkOdjdrzTvY8Ddl5qmgmFZr/ui1clyRP84KOTZpgnbtKjttguFwmBZpk60Jl2OPMAt7Gpq60KwRmG0JgDE4nEvWlM0bcQoXONeAl43mOP+4zh7HhsxCKamMtCK7R3PiXNvWHPn9kKEvEKhsZCXTg8nVpNARLhu4jWLNSdfNjvt65o6YXp6FkXdgNok1uypbmKaglhNwBXyTE1peU1l6Yo7U4+y889xwIvW7LLz3bFtWIYxEEceAJw6dQaCIOBXv+o+wk1VDbz33hNcuHDZ95nXY2PjSCZT2NwagJC39THm5uYRCvUuyk9NZTA3O493ylJf7nHeKUmIhMM4dao/88lmZ+cRDIZ6cteYchWGImJtrbsZqSMGQffFUYZhsLFxDrdv56Bpho9rap8bN57AcdChkFc7nw+hLsx00CQ+PT2DqCDgQ0qEPLIOIvIfhOd5nDl9HlLuoe8O0m4Rn94DwzDPfLTv3NwCGIaBNCQhTy2VYek6FhYOz+gThOihxCKakWV3rY2abncdeQMU8iLtCXmiWEWMYjceAER59pAjz/bJkec3nTisB03He+ub3/wmbty4gVdeeQV/8id/0vL5r732Gv7wD/8Qt27dwje+8Q3v8VdeeQWf+cxn4DgOfvzjH3e6jBEUQYS71Ooi2GCgq67sQXOUojUVRT7kNuH5IBiGcaMgjwg0djLshZwYGZZz3aWhyKH85hGDgzjcSIeqWZu9SWtRkmVZRCLCvgtVx3EgSfS5CAUhCq2Fo8NxHKiaSuX+jsXiu448y0I07l8ufj9ga40Be/oaeuqQHtE5U1MZqKVKW+d6tVhGNBbznJTDJJlMgWWZJo48eehCXiaTBQCUKoWOX1su58GyrBd/OgyIiLjVoEipWjZKujFUsXEvsVgMjm3BNpsXRSxNgSBEd48/I3yDODMtvbvCNnndoIQ8juNw6tQZ3LjxFFaXc7hu3dqEZdk4fdr/YinDMFhdXcdW7lFfiyW6riFf2MLqqn+i06XLLyCnGXjqs8ihWjZuSQrOP3eppxlnzeA4zo017UHIIyLgyspIyOsZn2sRfm1tY+MMTNPC++9v+bTFznj33SdIp9PetUY7tDunrh+QJuZ2Yj1ZlsXq2knckTXYFNSiPpRUZKYySCQajys4f/6CG6+53f/Gi1Y4jgPx6T2srK5TO3pjUIRCIUxlspBzw5mTJ2+5AuLCwtKh77lC3tFJESNN2Y3qN+VyTcgb8Iw892eXmj5PrFYQp7zGEOc4yLIMy9p1adq2PRQHdUuYYxSt+e///u9gGAa///u/3/ZrPve5z8FxHPzHf/zHvsc/+9nPAgDu3aPHnj2ic8gcsfGTa+BCwSMRR3jww2j7HWfhI9VqBeHw/hMJy7IIh4VD3QzUsWe30iyWAgeEPABcSECl0vxkOaJ/BIMhsCznOfJoF/IA94Jv74WqqhqwbYcKQWAvgiC0bLgwDB2OY1O3dsCd+eS+KxxIlkN9dBzDMLUbesc7Jo6K64NlaioL2zShi62bX9RSGZmp9gtG/YTjOCSTqbqOPF03Ua0qnmtvWMTjCYRCYZTL+Y5fW67kMTY24bvDpxOIo3CzQSGeCHzDjP/cCylWWS3mUZu6+swXtvoFEVZsq7uoKPK6fgk09djYOAtVNXDnTndFvuvXHyMajdbttveDlZV16LqKYhfO3nbJbT+C4zi+znI7e/Y8WJbFuz7Ha94SFZi2g+eeu+Trdg+ytrYOXa7AkLu7n1TyTxBPJIfajHEc6Ocst143vbi4jEgkMpR4TVU18MEHW9jYONfRPiJNEsYQRpDotZmT7TZqrK+fhGRaDa9BBoVm2/hI0bF+4lTT5y0vr0KIRlF9Mvz6rVbehiFXcf7chWEvhQoWF5Yg5/L7xpIMCim3jUhEwPj4xKHvCYIAVTW6biQaNLLsHjcikfo1p0qlhFAo3NP80U4h7j8iIjZCFKuI8XTXGGI8CwfYZ0ixbbv3k1UfIOcdq8vr/X7S8V/5o4/cWI5Uqv2hy8mk29Xx6NGjfY/Pz88DcLNcRxxdJEkCw7qxmnw4DFESh72klliWCYbZ++GkIx6gHtVqFZHw4WJ6OBylXsjbG61Js1gK7BXy3MMiF462PFmO6B8MwyAiRLyLUUsjF1WD6WDvBkGI7XPkkf+nTXyMRKIwTaPpcU+r3YjStnZgd+aT5biOvKNQrGZYtnY0dP89EvIGy9RUBoDrtmuG4zhQi+WOOr/7TSo1hkLhcJG4WHQfS6fTg17SPhiGwdRUBpVuHHmVAjKZTB9W1T7JZBLhUAhbDWISN2uP0+PIqwl5LVzVNqUzTo8DpHjjdHlj75hk/srgikCrq+sIBPiuivGmaeHmzac4depM385dq6uuuNbPeM3NrY/B84G6joFuEYQo1tdO4HpV8dVRc70iI5VMYX6+P8IpYWnJnU+olnJdvV4tbWFlebWvQtSI4cJxHE6ePN2To7dbbt/egmXZ2NjoLF6WROJpQxHyOrtfJTGWw47XvC9rsBzHm9vXCI7jcP7cBcjbH8M2hhuXWH1yDyzH4fTpc0NdBy3Mzy/BMgyopcHXr+RcHgsLi3XPBaSWQCIraWe3ftM4WjMyQDceAHAcj1AojGq18d/WsizIioIo5fNqY7X1ieKuZuA68ii8jvAcefTVsTu+GicX8Hfv3m37NcRxd/CPQxw6oxvNo40kieDDITAMAy4cgizRH/eoaTrY2kDNYJCnetacKFYPOfIAIBIWUK0enehH26avk2EvBx15fFhoaV8f0V+CwZB3nrBNV3TyY65JvxCE6L4Zea2iGYaFILg3l81ceXrN7UGrIw8ALMeBYlpUzvE7CEuGJde+pjI+4hizK+Q1P6brogTbNDFFiSMPcOM1iWi3l1JJ8b4/bKamMih3KORZlglRLGNycrhCHsMwyGZnsKnVb2zY1AxEwuGmUVODxGtkaOGqto2RI69fcLUihG1268hz32uBwOCcqMFgEGtrJ3H9+uOOEzLu3NmGqhodzajqlHg8gcnJDLbaEPIazQ1vxdbWx1hcXPLdAXzu/EWUDRMfK/7cS8qWhTuyhnPnL/S9sDU1lQHPB6CWO3dCmqoEU5UxOzvfh5U9g/hdJ/Q+572/hzY2zkJRdNy7N9j5W9evP0YkEulYfCciGnHHDRLyMxvN1zpIPJ5ANpPFnSELeXckFQGex+Licsvnnj9/EY5tQdx62NXPYjm+6dft4Dg2pM17OHlig+om30FCHPNyrvOEjF4wNR1qqdyw8SReG4FRKtGf2ga491ehUAjBYP159uVyuaFbr58IkVjTGXlk3JXgU7SmatkIhUJ4+eWXEQqFms4S74RIbX0k1Q+gN1pzd0YefXXsjvfW2toaHMfB1772NRhGawu4ruv4p3/6JzAMg7W1/VEWxKE3NjbcWKARvSFJEvjavAg+HIauazBNeh1ugBsbRz6YrpBHZ26zbduQJLGuIy8SjlLvZnUcxzvItHO8GCbFYgFcMOzZugPhGFRVORIzH48rgUDAuxElBbNBRlF1iiBE93Wbkf+nzdVG1tNsTh7NjjyyJsNxPb80rvEgpHDKeF8fjXiR40IkIiAWi7fsUtVq3x+2uLSXVCqNclk51AlfLEre94fN1FQGqipDbRH3uJdKtQjHcTyRdZhkp2ewpRt1HTWbmolMdoaaTlGvkaGFI8/UlCPR5HAUYRgGPB/oOlrTqX2WB+nIA9xifLms4PHjzprUbtx4gkAg4OtsuXqsrKxie+dJy4LJ7Mxy06/roaoySuW8r7GahI2NM+A53rd4zfcqrrvv/PmLvmyvGRzHYXp6Blq5c4FGrb1mbm4k5PUKz/G+x+GR7XE+uDPW1k6A4zi891738xQ7xbJs3Lz5FCdPnu74dyCxlsOo75CfSWaptsPa+kl8pOjQhziH6a6sYWlppa377Pn5RaRSYxCf3OnqZ0UnF5p+3Q5K/ilMTcGFC/2NHz5KjI2NIxyOQN4erJCn7Lg/b26u/t9xcnIKALC5eTQMCJub5ab3JpVKeaDz8QiRSKxpWhgRxiJ+CXm2jatXr+LVV1/F1atXofp0fKon5DkOrdGatUZsCkdEdfxX/qM/+iMAwK1bt/DFL34R9+/fb/jce/fu4Ytf/CLef/99AMDnP//5fd//2c9+BoZhcPJkcwv3CLqRJBFcOAQA4CMh7zFaMU0TlmV7jrxQiF5HnihW4ThO3a6PcCQKURSpzOwFXBHScRxwtYMyrfuYUCjkwUd2u9cDQqL2eOdxYSP8IRgIeh2qR0HIOzgjjzjyaBOaiKvRaBKJQr5HowOSdF6atYuqdudQDAvbtt04ZzDeRaqu093YcByZmspAKzVvflFLldpzpwaxpLZIJlNwHAeVyn7hpliUwTCgwilG5iNVq8W2X1OtlmqvHf6+zmSmoVk2ygccVo7jIKcbVEWtkvOJ2cRpYJsGbMukfn7oUYYP8F1Ha5KEgUHPhiQi1t27nbmv7t7dwcLCUt+vv1ZW1mCaBvKFrabPW187j3gshVAogivPv4z1tfMtt53bfuz9DL8JhcI4eeo03hMVWD4Ue65XZUyMTwxsLufc3AL0SudzlbTyNhiGpWZ+6FGG4ziqhbxQKITV1XXcuPGko4JmMMg1/boZDx7kIcs6Tp063fZrCO00LPYLTVPAcTwCgfpunnqsrp6A5Th4IA+nsbxsmNjWDKzWYj5bwTAMnnvuIuTCU5ha5w0MiYVT4IUE2GAYk2c+icRC87l89ag+uYtgKIQTJzY6fu1xhWEYzM3NQ94ZrJBHhMNG7uzx8QlwHHuEhLxKw2QWy7IgSdLQhLxmjjy/hbwwy+LatWv49re/jWvXriHsU7T6rpC3e3ymdUYe2GM0I+8LX/gCXnrpJTiOg1/+8pf43d/9XXz+85/Hl7/8ZXzlK1/BV77yFXz5y1/G5z//efze7/0e3nnnHQDAJz/5SXzhC1/wtiOKIr73ve/BcRx86lOf8u83GjFwxFq0JgDPmSdRHK9JBKVdRx5HrchUKLgnxljscKEuHkvCcWxq4x+JEMDVjsm0uh4J+UIeAWFXyONr/0/+BiMGTyAQOBSt2cmN0aCJRCKwbcdbs1KLWWo3XmVQhELu8bo9IS80kDV1AhEXTZsIefSJjXvx9jPDgHjymu37Ef1hcnIKernStAillSuICAJV4jtx3B2M1ywWZcRicV+KdL0yPk6EvPavRyo10W98fLwva+oEIkTu6PvTJETLhmbZVDk0OY5DJCI0deSR740cef2D5/keojXdAvugG5NSqTSSySTu32//ulZVDTx9WvZ1rlwjyLy2ra1HTZ/HMAwikSiSiTGcWDvfllt2c+tjBAJBzMzM+bLWg5w/fxGSafVciK/WtnHu/MWBuYBnZ+dhWyZ0qbP7Sa2cx9RUpmH82Ij26YuQZ/kn5AHAqVOnsbMjYmur/WL8mTMzTb9uxnvvPQbHcVhf77zhPxKJIBgMQZIGLxyIUgWpVLqjz+/S0gp4jhtavObdWhPqWptCHgA899xFwHEgPr3X8c9jGAZ8WEAwlkJyYaPjY51tmZC3HuLM6XNUN/gOg9nZeaiFklc3GQTydh5j4+MNI045jsPExOSREPJEUYUoag2FPDcNrb7Jot8IkSgkSWooKhEhz69ozTDHQtM0vPnmm9A0DWGftivUceRZluWNN6IJxpuRdwyEPAD4u7/7O7zyyitwHLdgefPmTXznO9/BV7/6VXz1q1/Fd77zHdy8edP7/iuvvIK///u/37cNwzDwt3/7t/ja176Gz3zmM778MiOGgyhWwUfcQmqg9l9RpPdATQSl/Y48OkWmZkIeeYxWoYmIo8SRp2l07mPAPXmUS6V9Qt6uI2+w8wBG7BIMBvdEaxIhj94LduIMIxF4iuK6rmgTwzwhzGzsCjPNo+TIo2+NeyGxwgzDAIw7C4L2qOHjyMTEJExdh6k0LpRopQomKXCI7SWZdM/1B4W8UklBMjn8WE0ASKfHwDAsKh0IedVqCbFYnIpjDIn92dH2fy63a1+T79NCNBprOiPPqrn1aJvPepxwo/C6jdZ0XzdoRx4ALCws4/79fNuumgcP3Oe2MzepV6LRKDKZLLZyzYW8bsjlHmFpablvjQ/r6yfAczxuib05gN4XFTgAzpw558/C2oA4jnWxMyHPkErIZqf7saRnDo7r3uHbiF1Hnj/HmVOnzgAAbtx42vZrrl5dxcREDLFYCF/4wiVcvbra9mtv3HiK5eXVrq4RGIbB2NgYRLF5nHo/EKUKxsY6a1AKBAJYWFzGXXk4TX53ZBWxaBSZTPuf56mpLDKZaYibjdPZ+oW8/QiWqQ8kfvioMTe3AMdxoOTbT8joFWWngPm5+vPxCJOT2SMh5D19SpJZ6jfwSZKb7BIOD/76OhwWADiQ5fqGGeJw88uR1y8CDAOOYSDL7n2tbduwaRXyamuicWxYV3/lYDCI119/HW+88Qb++I//GPPz855oR/6Zm5vDF77wBfzrv/4rXn/99UPdWul0Gp/4xCfwiU98YnSjeYTRNBWGriMguIVVvvZfmme3kYMcVzvICUJwX0cATRQKeTAMg2hNVNpLLEq3kEeEu6MQrVkqFeE4tifeAQAXCIILhqndv88CbsHFLTb5GRHTL4igZNvEkWcgFApRt+b2HHluAZvGTmtPiKzVIWmP1vSOfbVjIcvzI0feECARjlq58Y2kVq5QJ9qQ6MxKZb9wUy4rSCQOXxsMA47jkEqlO47WJE64YRONxhAJh7F9IPJ2u+bQo+09IQgCbLNxc5Rl0BnrfJzgAwHPWdcpwxTyFheXUC7LhxoDGnH//g4YhsH8fOczjLphZWUNO/mnvnY/q6qMcqXgOf76QTAYwtraCbwvqj3NUnm/qiCVTHVUUO+V8fEJAAyMDkQP2zRgKCJ1x8ajCs/778gjMzz9ugdJJJLIZLJ4//3Ntl/DMAySyQgymQSuXl1r23mVz0vI5ao4caLzyEXC2Ng4xAE78hzHgSiWMDY21vFr19ZOYEvTUe3S6d0tjuPgrqxhde1kx864c+cuQC3mYCiDHakjbt5DRBD6EpV81CEzSwc1J8+QFeiSjNnZ5m73TCaLQkGEqtLdyPrkidvQ0ihSXxTd93okPPi0pXDtZ5I1HERV3fvEkE8RmP2CYRiEOBZarSGROAxHQl5n9HQHcfbsWZw9exaAW6iqVNyTZSKRoLL4N8J/iGAXEITaf92CKnkv0AjpYiCOvGg0iCdPBt+x1Q6FQh5RoX50liDEwHEctUITcTmSaE2tSff4sCH7cK8jDwACkTjy+ZEjb3jsuaGo1UUGFTXUDURQ2hXydCrdYp6QZzYR8kwdPB+gToQEAJZlwTDMkXHkkQvrXSEvuC8XfsRgIKKRWqogNn2409LUdBiKSo24RAiFwggE+EMz8ioVFUtLdAh5ADAxMYGdnfaFPFEqY36hPzF3ncIwDCYmp7Cd3z+ba0c3EAwEEI/Ts5+BmpDXZN6jXbv+or3J4SjDczz0bmfkWf46ZTphYcF11t2/v4OxsdZC7/37eWSz0wNzzi4sLOFnP/s/KJZ2MD7mT6TtTt51EC0uLvmyvUac2jiD92/fxKZmYDrceR1Et23cVTRc+Y3nB3qtGwwGkUylOorWNCT3vnkk5PlDOByB5fPsZEs3wDCMrzW59fVT+NnPfgpNMxAK9S8hhYiF6+vdC3np9Dhu334fjuMM7POk6xoMQ+/YkQe4c/KA/8RdScWF5OCacHK6Acm0sLq63vFrz517Dj/4wfcgbt5HenkwLmLbNCDnPsblS89TeY86bOLxBKKxGOQBOfKUfAEAWsZWz88vwnGAhw/zOHmSnrnTB3nwII9kMtlw/rgoEkfeMIW8+tf/Nml6p7dU5sExjJdgZVmuSMZQKEAyLAswDJVCnm97KxgMYmJiAhMTEyMR7xmCDNwMRN1iActx4MMhVKt0CmPArpBHHHnRaIjamX6FQh7RaP0TCcMwiEWT1Ap5xC4dqF0801y4zue3AQCBA/s6EE1gZ2ck5A2L/fdd3Xc4DwoS+UgupFTVoLKQyvPuzXezjnfbtsDz9N4gsQzrvSNoiOZrhiS5nXMkZ50Nhr3HRgyOZDIFjuOhV+rfAOm1xiQy740WGIZBPJ5AubzbDKPrJhRFRzxe//pgGKTTY5Dl9pq4LMuEokhIpzvvWu8XExNT2DH2HxO3dRMTE1PUNZCEwxHYRhNHXq1JQxDoms96nOB53ptB1SkkknMYjrxMJguO4/D4cXuizePHJczMzPd5VbvMzy8BAHZ22o/va8X2zlOwLIvZ2f7+HqdOnQYDNx6zG+5IKkzb8SIMB8nU5JQnzrWDXnvuBGVR1EcVQYjCUv0dQWFpGgQh6uv5a339JCzLxp07275tsx63b28ilUr11Fg1NjbmXWsMimotnjad7lzIm56eQTgU6nnOZqfcr/285eXOHcvj4xOYnp6F9HRw8ZrS9sewLRPnzl0Y2M88asxMz0EdkJAn1xr4stnm8y/n5hbAMExHM3qHwf37+aYzgYkbbrhCXv0aguO416QM6LpnqQeD3fUSkYxGRx4AsCx3vIW8Ec8mniNvz3DTQCRCdbQmEe32CnmGYVAZ/ZjPbyORSDX8fiyW8kQo2iD7OcAyYAGqC9c7Oztg+QC44H7RJRBNolIpjeZZDQ2GjMjz/ktbQXUvRFAijjxVNaibjwfs7kPHbiyO2rYNltILKmD/+4DmuYnAbuccuUDlghFUG1yEj+gfLMu6rgOxflFHr7qP0yQuEeLxxD5HHonZjMfjjV4ycJLJtBu33kZsLJkxkUrRMeMPcAvSVcOEs6dpZMewMEGh40QQBC8+sx4jR17/CQQC3uzeTrFr0WnDOHdxHIeJiQlsbbW+TxNFDZKkNZwV0w9SqRTi8QS2fRTydnaeYnp6tu/7OxaLY25uAbfE7hJIbokKwqEQlpZWfF5ZayYmJmFI5bZjQQ2pAoCpxXKO6BVBEGDquq/xmqaqIeJzM8fi4jICgQBu3Wo/XrNTLMvG7ds5rK2d6umeb2rKdf2UyoNryC2XXZGiUSxfM1iWxeLSCh6og61H3Zc1pJLJrq99z5+/ALW8DUMZTO1P2r0kDqcAACAASURBVHyAaDQ2lOPkUWFmZhZqseRda/QTJV9Aemy8ZTpOOBxGJpPFvXv0NsgXizJKJbmpkCfLIng+4DVFD5JwKOKtoR6kkfwoCDwsw3jrJXVWlh18c1s7MBwH06SvFnwU/s4jKIY478hsPPL/xKlHI7uOPPfiMBYL1h6na06eJElQFAXxeONCVyKeQj6/4x0IacLbz2Ag8HzDwaw0sLOTQzCaPHTDQBx6o3jN4VDv/o1mIY901xMhzzBs8Dx9DnW2Fl1AOqHqMcgomm5g2N210R6tctCRxwXDkBrEYozoL2PpsSZCnvt3oklcIsTjyX2OvF0hj57IR7LfJLn1e1uqOfdSqcaNSoOGzLQxasdvy3FQ0Y2uIrL6TTgcgW0aDY/hlqkhEAhSf2w8yoRCYdhGl0JerWgxLDf55GSmLSFva6tSe/5gxeyFhSUvDrNXbNtCvrDV91hNwqmNs3ii6qh0+N6wHQe3JQ0nTmwM5XObTKZgWybsJpHrezFVEdFodCiu0uMImWdqNnHlsQf29cGvD2KqGmLRWO+L2wPP81hZWetoTl6nPHyYh6YZWF8/2dN2yJzJUmlw9/DF0jYCgUDXotjy8ip2NAMVo30BJsgyTb9uhu04uK/oWF7pPFaTcPq0G6kpbT3sehvtYlsm5J1H2Ng4693LjjjMzMwsHMeBWmw/Lrlb1HwRszOzbT13cXEZDx8WqKxbAm7kOLAbQV4PVdUQDAynSTtQ+7neyI4DkP1KcfnGw3XkufdbniOP0nsWluVhdHm9308aXgG89tprANyi6Te+8Y1Dj3fDwW2NOPpUKmWwPA8uuNuVEIhGUH5Kp0sMcIuqkUgQZP5WNBr2HqepqEScdolmQl4iDdM0US6XqHMReLMIGSDKs5QLedvghcP7OSi4RdJ8fhvZ7OAGz48gHIErkT2Qbm/S0GwYFqJR+ooc7s0PA7tJ57Xj2FTfJBGRkeM4qtcJuBEYDMt5V9ZcMIKqItdcj3Sv/biRSo3hwaOP6n5Pr4oIhcNeRC5NxGIx3LunI5Fwr1dEUas9To8jL52uCXlSBalkc/GLRkceuYYyHQdBABXTgg261kjwzjWWBYY/fAxxLAs85U7lo044HPYEuU6xdAMcxw9NBJmczODGjeswDAuBQOPCyebm8IS8GzfehaJIiER6mxVVKuVhWSbm5xd9Wl1zTpw4he9//z9xR9JwKdX+3/epZkA2Layf2Ojj6hqTTLr3v6YqgWujSGmqElJJeu6ZjzrRaE3I0zQEhPrXIMmFWVQfPdn3dTNsTYfQxhzMTllZWcft27dQKslIpfyPl/vwwxwYpruox70IgoBEIoniAIW8UmkHmcx019f2y8trAID7iornAu397U7GIvhAUvd93S7bunvc6WVfj49PYHIqC3HrIVJLZ7veTjso+SewTQOnT/f35xx1pqfdY4OSL0KY7F8zmqXr0Koistn2hLyFhSW89dZ/4cmTMubm6Lu2vn9/B4FAoGnNT9NUBALDadJmGAaBQBCaVr/hgzSSs0dAyeMYHHLk0Srk0erIa3iF+fbbbwM47H54++23wTBM29ELZBu0d/eP6I5KpYxgVNgfcxYVUBRFWJZFZTdwtVpFIrF7kbNbGGtvtsug2N7OAWgu5BG33s7ONpVCnnsZy0BgQe0cQiKEpiaWDn2POPJ2dugVpo8ztm17XUXEgUWz+EGKcuT86Dry6CymsizTNMLHoXg/A7vXJjyF55iDVCpl8GHB06X5UASO40AUqw2HaY/oD+n0GExVhVWnAK+LdM1s20skIkBRNLizQhnItZkmNImOpBDcjiNPlqsAGKre/0SwM2vH71Kt+5JuIc8E6pxjHNtEgNJzz3EhFArB0rsX8oYZuz05OQXHcbC9XcXMTGMxZmurgmAw6H22B8X0tDtrp1ja7lnIK5a2a9tsr9DYK5lMFlEhijuyikup9td+p1aIX1vr3hnTC56Qp0gIxVufBy1VRmpqMPv0WYA05RiSgki6/udtfGMduffeh6XrmL58HuOnmr9XdEnuS/w2EX3u3NnG88/7L5DfubONbHbGlxmv2ew0crnBCHmO46BU3sG5c891vY3p6RmEgiHclzU8l2jv+PFCKoprhSo028bvTCRxpYPjTi/z8fZy5vRZ/PgnP4Slq+CC/XOaS1sPEQyFsLKy1refcRxIpdLgAwEofXbkqUU3ga3dZnfyPvvwwxyVQt4HH+SwuLjctH6taWpXjXKGoSEUCuHq1au4du0ajCbx+M1whbz6jjxSG7Edh3pbnu3srpeIZAyt0ZosT+WYpYZ768qVKx09PuLZpFwug4/uv9AKRAWvSDnom792qFbLSCbDsGpD6pPJcO1xuqLO8vkdMAyLaLRxdBYR+fL57Z4jKPxGkkSvI0TgWOQojZIrFgtwHMdz3+2F5QPgQwLyeboH8x5XLMsEUT+YmqhkmiaCQfriKgF4ot1uVIBFZeyQ4zjuGptd5HXYsDNoSEwljfv3IKVSEVx498aaj8S8x2kSMp4FiChjiIejtA1RRrrNrtJBE4kIcBy325JlGciyG3/mR6HLL0ghUlNbx5QrqoRoNEpVs1c0GgPP8Z6QV6xFW9Eo7pJzjW1bqLcHHctCcOTI6yuhUBiWoXfVqGobwxXyJiZch10u11zI29kRMT4+MfCmnr1C3sz0Uk/bKha3EQgEBxaRy7IsVtdO4O7Nd2E7Ttud8XclFZmpzNDiksk8dlNtr+nSUMWmM9xHdEY67b4/ScR3PRiGQUCIICBEMLFxoun2TE2Dpet9OX9ls9MIh8O4cyfnu5Bnmhbu38/jhRc+6cv2stkZfPjhB7AsExzX3/sFRRGhaWpPCT4sy2JpaQUPHt5p+zUMwyDBcwA4vJDuLEr1vqwhmeh+Ph7h9Omz+PGPfwAp9xESc83fm93iODbk3EfYOLlxJO79hgnLspiayqJS7O+oIyLktTtHN5FIYnJyEh98sIXf/m266pblsoKtrQouXPjNps/TVBWBLsam6IaOq1ev4tVXXwUAvPXWL7taZ4BvLOQRZ7ds2QhS3IwNAJJlIVqLfvaiNVl67gn3wrBHzJH3zW9+s6PHRzyblMslBDL7b46CNWGvUilTKuRVkM0mUSi4xaZ43BXyaJvrl8/vIBZLNL2BDocF8HyAyhlu1UoFfO3+Nc5zuEupkEf2XaCOkAcAvBCncv8+C5im5bmYiJBnWf0f3NwtLMvWHOju14ZBp5BnWRYcxwHf5KaW4+jsPiKQ2hhNQkAjCsUCAomMNwiej7iCR7FYbDpQe4T/kO50Q1EOfc9QFKpmzu0lEnGvqyzLAcsCsqyDZVkEg8MTAw7CcRwikQiUNoQ8VVW8GzhaYBgG6VQKUqkAwHXkMQCV17H7HHl1sC3Te86I/hAKheHYTi3etLPzvKXrEMLDmY8H7L6ny+XDx8G9lEoKksnBNzdEIgKSyRSKxd7TMAolNxp/kGLk2toJvPvur5HTDGTDrQt+um3joaLjxYvDK2ySc6OlN39PAKjN0jOoinY+6iQS7v1+MyGvE/SqK8gSgdBPiNh05079mPJeePiwALPHqMe9uLPCbJTKeYyPtSc2dEu+kKv9zLmetrO4tIzbH9yCZFqI8v27x3EcBw9VA6une4/znZ6eRTyRhJT7uG9CnlbagamrOHXqTF+2f9zITGWwfftGX3+GUiwhEAh2lFyxsrKOX//67VqzMz338B9+6H5+V1ebO501TUOgzdjbvQQDQVy7dg0AcO3aNQiR7s6ffCDQMFqT3FdJpo0UxbcApu1As2xPePRm+9EqPjKMF1tKE5TurRFHAdu2Ua1WEIzuj3YK1DrEy+X+D1jtFMdxUK1W9kVr8jyHWCyMapWuaM1iMY9YtLlbg2EYxGJJFIvFAa2qfSqVErhatT3Bc1A1DbrenY28nxQKNSGvgfMxICRGQt6Q2OvIY2uCjdWgcEkDDMPs68x3TW/0nWZJVxHXpPjIczyV3Ue71JyaFO7fvZimCbFa9Vx4ABDY48gbMViIUGfI+4uVtmXBVDVqC5NCbWYOudmRZR2CIFAXWR+NxqFprQvBqiojFqNLyAOA1Ng4TJs48kzEYnEqmzE897ddv7HFselsIjlOkPevodTvjG6GqaiID/FYIwgCeJ5DqdRayEskhtPcMDMz68VidovjOCiVtjEzM1gxcm3NLWTfkdp7bzxUdFiOg9XV/hTA24HjOASCQVhtxH3ZtecIDWa5jegclmWRTKV9FPLc7fTLUb68vIadHRGlUuvGnU64c8edj7e4uOLL9mZn5wEA+fymL9trRr6wBYZhkc3O9LSdpSX3d3+o9LdmUjBMiIaJxcXlnrfFMAxOnjgFNf+k6diGXpB2HoFhGKyvD+84eZTIZLIwZAWm2r/3kVosY2oq01GjzOrqOnTdxMOHhb6tqxtu395CJBJp+fm1uhw9EgiEoGka3nzzzZoY2F0jJstw3r3gQYgwJlHc9A7sro8Ij3btXoa2e1oPhvHWSBN0V8BGUI0oVuE4jifcEQJRIuTR5XADAFmWYVm2NxePkEjQKOQVm8ZqEqJCAsUiXSdDVzCtekJevNZxU6nQtY8B15HHBYJgG5xQA0IColihUoQ87piWuWdGHonWpO9EuhfH2b24YhhQGU9JnHbNYmZcR55J5fqPEq7T2/HEO6AW2RsMo1weCXmDhrgOTHl/gdWsFeOPgiMPAGTZQHiIjp5GxGKx9hx5mkylaBqPJ2HB3ceiaY+ib0c0hBwrTLm1cH0QU1GHeqxhGHc+ZTNHnq6bkGVtaJ+BbHYGlUqxp+YtSarAMPSeC+udkkgkMTkxibtye/cNdyUVHMt5BfxhEQkLnkjXDCL2kfPSCH8YS49BF/2ZJ99vIW9pyRV/7t/3d/TE/ft5TE1lfIsNT6XSEIQo8oUtX7bXjEJhC5lMpufxDzMzc+A5Dg/aPH50C9m+H0IeAJw4cQqWqUMt9mdfK9uPMDu3AEHobW7qswKJu1RL/avHaqVy27GahOXlVTAMgw8+6P9nsl0cx8GHH+awsrLeUqTrJk7dVximiZDn1hpEqz9iul9ItfXtCnm19VLanM0wbMN9Pkz6sreKxSJKJfrcWCP8hQhfgQMz8rhQECzHUSeMAbvxmcnk/i7CZDJMVbSmpqlQFBmxNoS8WDSBUqlAVcFdUWSYluVFayY8IY+efUzI53fAR+INT8rEqVco0CWWPguYpullKDIcEfLodYm5s+d2v2ZZZp+wRwtEyGsVrQk4VEeZHgVIk8VeRx4AcJEYCoXR7M1BEwqFwfH8oWjNXSGPPnEJODx/0zAsBAL0zQqNRmPQ23DkaRp90ZqAK0S6WqkD0bIRo/T9gJrY2HDOKcOAnivC40kjd28rHNuGIQ8/xjeRSDV10xCRb1hCHpnjV612X08gr52YmPRlTZ2wsrruOe1a8UDRMDe/MPT5z4IgwDL0ls/7/9l7sxhJsrP8+4k9cs+qrL2qq6r3ZXpmmLGnB88MEiALyRL+LNvihjtLFoJLgwzmAgmBkBASXHCBhASyJSQwEsgLiL9kYSyEzIf84W+GmXbPGI9nunuq11pyiYx9Of+LyBNZS0auERmnqvN31ZVLdHR2VOQ57/M+zxt0XjMT8pJlfr4Gp5WMI8/W2lDVHHK5dFyTKytrkCQRH36YXGJNEBDcvbuPzc1khCUgbFpYXz+Hg5SFPEIIDg6eRA7ASRBFERsbm7hnDf5dnIR7poOcmsPi4lIix6MiiL63k8jxDuPZJqzmLq5euZb4sc8q8/MLAJDYPeU4gefBNUzUagsjvS+Xy2N9fQM//jE7Qt6TJxoaDWNgrCZA92HZCXkc4pvE6b7KYLzpXfeoI+9YtCbTjjz26nmJCXl7e3v4vd/7Pbz66qt47bXX8IlPfAKvvPIKvvKVr+Dhw4dJ/TUzGIK6q6Rj0Rp0GPPpEvJyTIlMNCqzUBzCkVcsw7ZtmD1m/mQFvTYOR2sCYPKaaDQa0cyqXkhq+KU4c89MH8e2o0Il35n34w5RZMiK4wurcF4ee+VUmq1OxYFeUJEgLod9xnDEzeCUZrM3MyGMoy6dcNHQYjyLLjEAUUwivZ+EsyXYG4CgKApcr/89mhAC13WgKOzM96PQ//8AYUcrq9fDoO8VLnzRVM7lWYVGTo4q5HmWDUIIA0JeBc1mfPRj9kJeKL61JhDyWlr9yLGmydbWeThBgCd2/+YzJwjw0HIzd+MBQC6XG8qRF0SOvFm0ZpIsLCzCs+1EovDsZivV614QBKyvb+Lu3eQa0p48acGy3MRnR29snEOzdZDq/rGtt2A7ViJCHgBsbV/AI9OBnWLx+J7pYGv7fGLzQ1VVxebmeZgpCHnmflhLvnw5uzmip41qdQ4cx8HWtFSOb3cEwvn50edwXr58DffuHUDX2agxvPfeIwDDXV9ZO/L61ZYURYEiyzhw2R1DAwB1NxTy6PqSjklhsWYGAMjahRlD3zv348eP8cYbb+CNN97A3/7t38a+7qOPPsLnPvc5/MM//AOazWbHlRBG633rW9/CZz/7Wbz77ruJn/yMbNG0UPg6LuQBgJhnSxij0HOqVk8KebreZsZ9QkWjYn64aE2ArXlL9HMWT0RrsnlNiGp8V6moht0iLEbFnnUcx4m+OOk8N9tmX8ij3/WhI4+9RYmuh4tvRYkvwiiKeuS1M8bj4GAPHC9E9xGKlC+j0Wgw853zLJHP5+Edu494Np35w2ZkT1fIC392XTZnoMmyMtA1Ta/5rN0nvaBzz3xCoHdm5LFI93slbmM5c+SlTS6XB8/zIwt51A2ctZBXKBT6FtF03em8Lhvn7MJC2OWvaePvbTStAVlWMvk9pq6iewPi8XZMBwEhiYsX4yBJEjDEHBg6K0aS2GsmOc1Q4c1uTt706jS11AXszc1t7OzU4TjJFI2puy8NIY8Qgnp9spmb/aAz+DY2EhLyts4jAPCRmc6et+352HfcxGI1KRcvXobdOoDvjD47th/m/kMoqoq1tY1Ej3uWEUUR5Uo1NUee0xEIxxHyrly5BkIIM668O3ceY3FxaagoYhbqOnHnwHEc1tbP4eGABqKseWA5yOdyqFbnAHTXEmSCKPU0IYHH5J61r5D3H//xH9jb20Oz2cSnPvWp2Nd96UtfwtOnT6OLanV1FS+++CIKhQIIIWg2m/jN3/zNMCZtxpmBuq7E3Mk5LWI+hxaD7qtWqwmOA8rlowXsajUHQthxjBlGGHfTr9BOoQV300x24PQkNJthBy115KkCD0XgmRPDLMuC49gQ1fhChaDkAI5jUoQ869iOHQl5vBx+yTsJbw6SpGu775wzz6YVX9fDGRyqEi9gK53n2BXyOotYBhbU/djf34ecL5/o5JLyZRASMNWA8ayQz+XhO0eLI75No8LYdBhEm5zIkRcwKuTJA4U8r+PYY3FTRAv+TkAQoCvssUa3aaRPtCaD3z1nCZ7nUSpX4I4408pth2v1SiXb+YuqmoNtuwiC3t+hZqeAnNUsTkVRUSyWIlfdOLS0AywsLGTSSV2tVlEpV3DP7C/k3TNtcAA2N7emc2J9EARxqPsG6Qh5/eYszxgdGidrTSjk+a4LRzei46XF5uY2goDgo4+SWcd++OE+CoXCWMJAP6hLbu/gcaLHPcz+wWOIoojl5dVEjre5uQ2O4wY2AowLPW7STuCLFy8BAMyDR4ke1zx4hAvnLybmHnxWqM3XIudc0nQdeaNFawLh72Qul8N776X3Ozkstu3hpz/dxeXLw8W2iqIQNbNkgR/0b+RcXz+HR5YLj+H6yAPbxfr6uWhtRveDAatCns/mOIu+d8M333wTAPDqq69ibm6u52u+973v4fbt2+A4DpVKBX/1V3+F733ve/j7v/97fP/738fnPvc5AMDdu3fxne98J+HTn5ElmtaClM+B6/GlKuVz0FpsiGKHabWaKBZzEISj51yp5KPnWcCywo5dWR4cPUVfQ9/DAs1mAxwQzcgDgIooMhdP2WqFgmM/Rx7H85DUfCROzpgOQRDAdRzkFmqoXb0IXgoXLY7DriOPnhvP04WJwOT5GkZYeKRNAL1QO00EtKmANej61M9wMT0Me/t7EPMn3QA0anMWrzl9crkcAueo2OR3fu73O5ElJ6M1AyajNWVZRhAEfZ2mVOgbZn0zbahw53TEDVYdeXTOKScIPZ/nBCF6zYz0GKdIZrdoF/voxa8kUdWwgdGyel8nphk+nmVzw8LC4mQz8tpN1GrTj9WkbG1fwD3L7dvBf990sLS0zMS8OUEQQMgQa6qO2CfE3H9mjEe1Ogee52E3Jquf2M3wHrO4mLYjLxSfk5qTd+/eAc6d20pceC8WS6hW5yLXXBrs7z/B2tpGYr8TqqpiZXllYCPAuNwzbYiCiNXV9USPu75+DpIkw9xPTshzDQ2uoeHChUuJHfNZYX6+NnKz0bA4mg5ZUZDPj/7dxfM8Ll26gnfffZy5w+2nP92F7we4MuT8RUmS4WUoOPm+19cNv76+AZ8QPGXUlecEAZ5aDtY3NqPHqEg2c+SNRl8h73//93/BcRxef/312Nf80z/9U/Tnr3zlK3jjjTein1VVxR/90R/hypUrAIDvfve7k57vDIZotzVIMRs8KZ+D49hwHDayjymtVhOVyslCHZ2Zx4qQR+fdSdIQQp5EHXlsCXklScTh2KeqyKPJmPuEOgTFXP+ue0GZCXnThhYhiyuLmL984VC0Jlv3lMPYdugWpEKeoojRYyxBXXayHC9aKGruyGtZg5CwkMSy058QgvrBfm8hrxAKeQcHMyFv2qhqLnLgUXzbgaKozHb7ducHhD8HAZt5/XRz6ffZjFGRj0VHIY1WdTsfNKtRq/T7ked7f4a8IMJheJ7sWaFWW4jipYbFbmlQ1dxYxa8koQKdGRPdZpphtHmWgnu1OgfDHG8NQgiBYWhRdFMWbG1tQ3O9aB7McQJCcN9ysMXAfDygI8wN5cibCXlpIAgC5msLE0dr0venLWLn8wXMz88n4sgzDAdPn7awcai4myQbG5vYP0gnxi8IfBzUnyZ+7lvbF/GR5cJPQei4azrYOLeZ+DpMEARsbZ+HlaAjj7r7ZkLe6BSLJbiWlUpCg2eaE0WEX758DZpm4cGDbOtrd+48giSJQ8fMyrIMf0DySJp4ntt3XUYdyA8sNvcAj20XAULBkUL3joHPpvgYeP3F06zoW7F48OABAODatXiF+gc/+AEAoFQq4Zd/+ZdPPM9xHD7/+c+DEIL33ntvknOdwRi6rkNQe6vTohLeYFhzc2haMxLtDsOakGdZJiRJHqqoyKIjr9GooyIe3eCVJYG5GDkqUgh9BI3w+RzaejodTTN6E4linS9OvtMJY1nsCWMUKjJSIU9VJSaFvHa7DUXJ9b2/KHKu89p0hmRPCu3gcxkW8jStFS64e8w6FeQceEHEwcF+Bmf2bJPL5aKZeBTfsaEyGqsJdGN7j87fZC86cWDkIxD197CY+qJ2Ghho4SyrWMFBuB2RjouJtuMEcebImwLz8zV4ln1i5mY/nFY78ei4caDXumH0vk4Mw4WqZtvcUKlUYRjaWBHllmUgCAJUq9UUzmw4zp3bBgDsxBTUdh0Pth/g3LnsYzWB0CUxjDuCdKLNWW18Oc3U5hfgaJM10FHXb62Wvut3fX0T9+9Pvrff2QmPkZaQd+7cJnS9BdNKfi/faO7D973E5uNRtra24QYBHiVckLf98JhJx2pSzm9fgN1uwE+omd+sP4Gay2FxcTmR4z1LlEolgBB4VvJN0K5poTRBagV1wN25k2wM6ygQQnDnziNcvHhlaKFGlmV4GQpOoSMv3h02NzePnKpiJ6X5mpPyoHNeVHAEOtcpAN9mp5ZNIUEAzzGZTGjpuwJrt8OFRFys5s7ODvb29sBxHD7+8Y/H/gLcuHEDAPD06dNJznUGY+h6G4LauyOAPk4j3FhB0zSUyycLM/m8DJ7noms+a0zThDyEGw8ARFECx3FMOfJajTqq4tHbS1UUYZgmU8UlKn4KYn+7NC/JsBj6fJ8F6MxHUQn/b4TOjDyWZkEe57iQx6ojT9OayA9yoQoCVDUXzUJlDVps8n2fyTmEACKRTuwh5HEcBylfxv7+TMibNoqidrpTuwVL3/WgKuxFPVK68xjYnr85TBGYi5z67Cl5tDvd60Rrshq12o3WjHfkeQyttc4qtFA+iivP0dpTKbAPQlFoE2Dv68S23eg1WVGtzoEQAmuM4rtuhGuXSiU7R97S0jIEQcDDmEI8fXxtbaPn89PG9/2e4zKOQx3iLH4HnXZqtTCud5K4ObvVRrFUmoqDYGNjE/W6jlZrsj3yvXsHAI66NJKEFo0PDpKvRe7vPznydyQFdQjdS7gg/5HlgBw6ftLQxgSrkcxnbTeeYvPc1qxxYAyo+OCZydcifNOaSNwoFkvY2DiHH/3oYYJnNRpPnrRwcKDj6tUbQ79HkmT4GTYRh468+Hs7x3HY3NzGB6aTeWxpL35qWKiUKyiXu3OiFUWFoubgjZnAkCaerQOEZJruEEffOyLtqI2b8fP2229Hf75582bscajKypLQMGNyDNOInHfHEVX2HHlBEMAwjJ5CHs9zKJVyzLhPgiAYajMFhL+nPJ/t4NXDEELQbDVRkY4WmCpS6NBjKaKSurv4AQNMeVFmUpA5y9B7h9C5x3AcB1FRmBbyHCe8Ruh3Z+jIYy8KtNlsIpcbHBmXyxWhaWy4lI9Dgu7ilNV4TSrkST2EPCCM9N2fRWtOnSiL/9D+hngeJAbz7ym9HHksF1GHc+Sxt8EEQpcJXU2x6shzHBu8IMZ+zpwgwXUdpq+RswCdc0dnUg0i8H04GhuOPFrk97ze14jrBpnH31YqYaFHN0bfm+l6+J4sHXmiKGJleSVWyHtkOZBEEYuLS1M+s974vh+JdP2g+1NW116nmfn5BQSeN1Hh3WlpU5sNScWrSV159+8fdqGfvwAAIABJREFUoFarpTYrMpwFx+EghXjNg/oTqGou8ft6uVzBXHUOd41k95H3DBscx6XmBN7YOAeO4xMR8nzXhtNuRO7mGaNBhTY3hRq8a5pRjX9crl69gfv3D6Bp2dTYfvSj0A047Hw8IEx1yWp0VBAEcBw7SlSI49r1m6g7Lh4zNifPCQK8b9i4fuP5E89VK1W4LAp5nXM6dUIeXfzevXu35/Nvvvlm9Ofnnz/5H0LRO5F0LA4JnDEevu/DtqxIsDsOFfh0huIIdT3scCuVehdmSiWFGSFPEISR8qyDwIcQ05k9bXS9Dc/3T0Rr0p/ZEvLMsBjG95/zEAp59qwoNkVo44egdL83REVmuiHENI/OyMvlJFiWyVzButVqIp/v78gDgHyuGM2RZI3DsYJehln1/djf3wM4DlKM+1HKl1E/OJjdV6aMRJtMDv1eBp4PSWQv/54SBEfvIawKefQ8+wl51JHH2n2Rcrjrm1VHnmVZ4PskCfCda5m1OdVnDeqsG3amldNx2rAg3NA9A51ZeRzP8xkQ8sI6xDhCnmG0jxwjK1bXzuGR7fW83z20XaysrjHjNAkCHxjBkRd37cwYHyoG0XjMcXC0NmpTahZYW1sHz3O4f/9gouN89FEd6+vpxGoCoQN5YWEB+yk48g7qT7G2tp7K3OLt8xdxz0rWWXPXtLG6sppao5IsK1heWUlEyLMauwCAzU024odPG4VCuP9M2pEX+D58xx2qltCPq1evgxDg3XcfJ3Rmo/GjHz3CysrqSOuEQqEIyzYy2cPQhnH6/xrH9evPgQNwR2OrZvaTtgUvILhx46QBbG5uDn4K0ceT4pnhOWW9luxF39UanY33ne9858RzhBD827/9G4BQdHj55Zdjj/PwYWiZXVjIPkpkRjJQV4wQ48ij0Zqmyc4vJBXp4oS8clmFprERIycIwzvsgiAAIYSZoeN0ziB14FFYdeT1K4ZRQscemRXFpsjxaE0A4BWZaUcenbkodmJli0UFnuczdd14ngfD0AdGawKhI4+VuaHHCQiJAvpYdD0C4axQKVeMdVeL+RJ832OmgeRZIZotcGgTRnyf6WYzuh6ghSJB4Jksovp+6NDo5+rgO40zLJ4/APCdc+d5PnMhIw7LsqL5sb2gceEsz5Q9C0iShGp1DlZjuL2D1RH8WBDy6LXtur0bAjwvgJhxc0OpFDryrDH2kqalQxTFgZ3rabO2tg7T99Fwj97vAkLwyHaZidUEhnfkUbGP3u9nJEfUHDCmkBd4HlzDnJrrV5ZlLCws4cGD8R157baFRsNILVaTsr5+DvV6skKe73toNPYSj9WkbG9fgOH52HWS+V3zCMFHloOt7YuJHC+Orc1t2M3dicUOuyPkJT1/8FmBxmMHbrL3ano8NcbQMSyrq+solUqZxGvquo27d/dGitUEgEKhgCAI4LrTrz1YnRlyxWL/Gk6xWMLm5jbe1dnaA9xpm8jncj1jfefm5uEaLeaaPB2jBYA7fY68X/zFXwQhBN/97nfxzW9+88hzf/3Xf40HDx6A4zi89tprKBTiY7reeustAMD58+lkMc+YPrQ4IMQUvmjxnSX3jNaZYdErWpM+zkpBVRAE+EN229OufH6Aq2xaUKGucqwAVu78zJLDx3Ec8EMU6niBdrezOTj2LNKrWUBQZOgMxfUeR9fb4Hku6q4uFsN7DSuzNwFEzQq5IYS8fK4Iw9CZi0/yfR+EEEgdUYPOumSNZrMBQYmPCZLUcN3Eqlh6VqGRcuSYIy/ronU/es3fZKlBgGJZJkRR6uswkWUlei2LUOFdkeVUOuyTwLYt8EI/R95MyJsWi4vLQ0drUufewsJ0Yu/6Ec2D9Po58rK9J+ZyOQiCANMafd1nmjqKxVLmv8Nra+sAgIf20f3DgevB9gOmhDzbcQB+mD0RFYHZTEM4zdCuf1cfb6/jdN5Xrc4ndk6DWF1dx87O+OvYnZ2wbrCyspbUKfVkfX0DhtlOtMm80dxHEASpiZDdOXnJrPceWg68gGB7+0Iix4tjdXUdgefCHcNNfRhb20ettshsOgLr0PV2kPA+nh6PHn9cOI7DtWvP4d13H8N1p9vc9+67jxEEBNevPzfS+6gLkYpq08TurIXy+cHjUW489zweWw4OEmoCmBSPEPxYt3D12nM9zSerq+sIfA+uzlZNxG7uYWFxcSozZ0elr5D3mc98BqurqwCA3/3d38Wv/Mqv4Ld+67fw2c9+Fn/6p38ave4LX/hC7DEIIfjXf/1XcByHF198MaHTnpE1rhtuSHip94Kf43lwPMfUIt8wwoVbsdj7S6dQUKDrOhOdAKM58sLXiSJbQl75mCNP4jnkRYEpR94MdtF1HRzPH7nHiKoCQ2dHFDtOu92OxDsgjOsFuk49FqDNCsPNyMt33sPO+QPd4rTYETVYmsV6mEazAVGN/5yFmZCXCVFx+pgjj8VFOoWKXlTIU1WJSSHMNE0ocv+CiyhK4DiOqUavw9DPmFU3HgAYpgmuj8hC5/6yeI2cNRYXl2A3h+sithotlEplJoqSg4W8IPOkD47jUCyWxiq8W5YezQfKkuXlVXAch8fW0f0w/Xl1NV3xYhQs0xw4MxyYNQqkiSiKyOXycI3x7t2uHr5v0tlVo7C6uoZm00C7Pd71sLNT7xxnPcnTOgE9/kGCrrx6fffIsZOmVltAsVBMbE4ePc72drrmCvp5OK39iY7jaAdRM8SM0aH7Gj8lR14SSSbXrj0Hx/Hw/vvJx9724/btByiVSiM301A3XBbr62EdeQBw/XoYX3lHY6NG8qFhw/ID3OgxHw9A1AxhN/emeVp9IYTAae1jIyXH9aT0FfJyuRz+7M/+DPl8HoQQ3L59G//yL/+C9957L9qwfP7zn8cnPvGJ2GP8+7//O548CQfLvvbaawme+owsoQId30c84kWRqdlF9Iaby/X+0snn5Y5VOvtzFkUJvu8NNQPH893oPSzQbDYhcBwKwsnbS0UU0GrNhLwZg9H1NqSceqSbWlRVpuZuHkfX20caBeifWRTyVHXwQHn6mnabjchhCnVrsuzII4RAa7X6Cnn0OZZcys8CvdxihBBm5hT1wraPzt9UVYnJSFnLsiAN6NDlOA6yrDD5extC40vZFfIsq3/BfVZonx6Li0thnN0QDhq70WIiVhPoxvTG6Y+s3BOLxRKsMeamWJaBcrmcwhmNhiRJmKtWsecc3VvudbrkWXBnUizLgjDEXrJ7f2H1Hn66KZXLYwt5XqexrVyuJHlKfaGiDXXWjcqDBw1Uq1Xk84P3JZOwvByaE5rNycSlwzSae+Hv+Fw6DkiO47C9fQF3rWQSge4ZNhZrCwNnbE3K0tIyOI6HrY3/WfuuDdfQUndqnmV4nockyYk78vxOrXRSRx4AXLhwCbIs4513phev6Xk+3n33Ma5efW7kdQ5tEBpnXTIptKmpWBy8tpmfr2F9bR1vaSYTJpW3mjpURcGlS1d6Pr+wsARRkmBNKOTxx/Zux38eBd824NlGatHJkzLwyn3ppZfwj//4j/ilX/olKIoCQggIIVhbW8Pv/M7v4A//8A/7vv8v/uIvAITz8X7mZ34mmbOekTmRkNenW5MXRDhO9qIYxewMes3lem9S6OMsbEzK5TIIIbCHsG3TmzoLG1YgdJeUJBF8jzibisij2Rg/Rz9pho/cISO+fsak6HobYu5o17qYU+G6DpORcgCg69oxIY+9aE16Lrk+AhNF7byGpfMHDs1P5Nh15BmGAd/3IPYRTAVZBcfzs+aGKdOzgB0Qpu/vVJChG85cTmJSpLEsE5I0eGMvSyqT5w90rw+RkbnDvQgL7v2EPCl63Yx0iWZaNQc3vDitFlPCDdBPyJvuecRRLpfHi9a0DCYceQCwsLiM3WOxYbuOi0q5nEghNCkse9i54bP7S5qUS2V44zryDOrIm15NgDqmqLNuVHZ2Gqm78QAgn8+jVCqjkaCQ12zuY2lpJdWmh+3zF9B0PNQndFUFhOCe5WDrfLrz8YCwgWFhcQn2BI48p3UAgC3X8mlEkqTkZ+R1hMEkkkwkScKlS1dw+/bDqQlOP/nJLmzbGzlWEwCq1TD+WNenP45JNzSIojR008PHPv4qHlsOHlrZ1uNNP8CP2iZe/JmPxV4zgiBgbXUddmt3or+rsLjZ9+dRsJrhuaQ9v3VchpIot7e38ed//ucIggAHBweQJAmVynCdPl/72tfCv4jhiJoZoxNFa/b5f+VFIXodC1iWAVkWIXScYq++ejRWgDr1TNOcaidbL8rl8EvCMNsDI/AMo915T7bnTNG0Fso93HgAUBIFfMTIHMIIRooVM46itdsQjg1RpsKerutMFT8o7baGpaUSGg26kVaix1mBzshT1dzA1+YiRx475w8ccuR13En0Z5agn3O/GXkcx0FU8tH81hnToVtwORStSQg4Lnv3SRxdIY868kT4vg/XdZmKBG23NajK4OK5orAzk/g4VMgTGN632LaFYj8hr+PWG6YZbMZkUGHObmoora/Gvs6zbHi2g1qNDSGP5caFw+TzRdj23ZHeEwQBbNtM3XUyLAsLS/jw/R9jXZFAHb97rocFhiLjCCFwbAv5EaI1qVN8RrKUyxXcf7Qz1ntdw4QkyVCU6e2Rcrk8KpUKHj8ePb3DcTzs7bVx8+Z0xJrl5RXs78eLS8fTjQalHTWa+7hxY3QxYBS2tsJ5dvcMG3OV8dclT2wXlh+kPh+PsrK8gvd++tOx3++0Q2F4eXklqVN6JuEFHoQMTvgaiSDcPyUVv339+k3cuXMbH31Ux+bmcO5WWRb6/tyP27cfQJZlXLhwaaTzBML6iSzL0I3ppxUZhoZKpTr0+u2FF17C//mXb+O/m22s50Z3Dcs81/fnYfmflg4vIPjYx17t+7pz57bw0f/7Hwh8b2wnXXnzGup3byPwHNQuv4zyuWtjHQcArIMn4AVhKo0m4zBS1YLneSwsLAwt4gFh90s+n08kQ3cGO1BHHjcgWpOFmEqKaVpHYjVv3drGrVvb0c8sOfLo75hxaEjwxQvP4eKFk4tFw2RLyGtrLRRjhLyiIHScKtMdaBsHx3HDLW7IzJE3bXS9DVE95shT2YuqpBBC0Gq1UKl0BTJRFFAoKJGowwK63oaiqOD5wQtelVEhjzrwBC505bHoyKPfI8IAdxIvyUx85zxL9LyPExKJZCxC58nRc+w2HrFz7RNC0Gw2kM8PFvLy+RIaDTadqPTyYDVa0/d9eK7b1zkzi9acHqVSGaIkwW71/56kz1MHHzuw3c1WKBRgWaNFQ9mO2XkvG0Le4uIS3IDA6/wTCCHYczxmYlaB8F5BCAE/hKOaF2WA0bXXWaBYLME1x4tD80wLhUJh6vvVxcXlsYS83d02CCFYWlpO4axOsry8ilZrP3Z0yfra+b4/H8ayDFiWEUV2psXy8gpURcFdc7I0mnud929tpTsfj7KwsAjX0BD447nBHL0FSZKZqW+dVniOj4S3pKC1s6ScqFevXgfHcbh9+8HQ73nuubW+P8cRBAS3bz/CpUtXxmqE5DgOlUr1SI12WhiGFjkCh0FVc7j5/It4WzPhDDGu6ThXi7m+Pw8DIQT/3TSwtro2cN7lxYuXQYIA5sHjkf8eCsdxENU85GIVlc3rE30XmvsPsbV5nqmG2cOw2348g2noAqhvB/uwIsmUsCwzNlYT6Ap5tGCWJXTRQt12AHDh/A1cOH/jxGsNQwPP88xsWNttDUUxRsgTBRAAhsHGnDNFURAMMcfR77xGUdQBr5yRBIQQ6O0e0ZoqjapkS1gCwoK67/tHhDwAqFRyaLXYEfJs24Y0RHQSEBayeZ6H47DjrAa6bjeR41CURKaEUkrkoBrwWXOiPCu2T5lei/rQkceukKfrGnI5OTrHUom6k9lparAsE47joDCkkNdsNpiY23CcriOPzWjNaF5in40lxwvgOH52b5kCHMehNl+D3Rwg5HWiN9kT8uJh4Z5YKBRBSADHHb6IbVtUyBscIT4NqGvT7dzv2n4A2w+Yilml+zJBHrzP4TgOoqwws5c7a6iqChIQkDGaXn3HQS6X7qy5XiwtLePpUw3BiIIBFf8WF6cj5C0tLcP3fbT13rOpL196AaViFYqSwysf/0VcvvRC7LGanejHtEVInuexuXUe98zJ9mJ3DRuVcjm1eX7HWVgIGxXcMZ1Lrt5ErbbAxPfQaYbj+cTX2iThBvd8voCtrfMjzcl7/fWLWFgoolhU8Cu/8jJef324yNidnTqaTQPXrz8/7umiWp2Dbkx//6UbGqrVuZHe87GP/SxsP8Dt1uj17VvVAuYlEQWBx/+zPIdb1dHXVA9tF48tBx/7+M8OfO329gXwggBzf3hBNy0824CtHeDy5d4z/VhgJuTNGIvujbvfFwNbhTHXdfrarmVZjF6XNfl8AYIgDNXtYRhtlEplJobS+74PwzRRjCmAUYGPFSEml8vDd+2BC5zAtSGIIrMdGWcNx7HheS6kY0Ie/Zm1mW0AIrHuuJBXLqvQtN4bxixwXQfCgKiYw4iCxMQ98TCapoEDwIFDSeDYFvIGxFQJosxE88izRM/7PccxKSpR2m0tEu+ArpDH0r2w2QwddsM48gr5EjzPZcpR2CVct7IatTpMkwDHcRAkeRZ9NyVqtUU4QzjyOI6bWhF1EN37Xfw+jYV7Im1StEeYk2fZbDnyIiGv0wS774QOFVZiVoFDQp40XMOiIKkzR15KUCHOt0dfe/uOi1xudNfEpCwtrcBxPNTro4m7T540wfPc1ERt2kjRbvfel3Ech1yugEp5HlcuvdC3jkWPMY3mjO3tC9i1XejeeIlGhBDcNV1snx89SnBcFhc79z19vD2aZ7SYci2fVnieT37obed4w6T7DMv16zfx6FETe3vD7WtCZ1wOy8tlvP76paFrzu+88wA8z+Hq1etjn2u1Ogc9phkgLXzfg2nqqFSGd+QBwNbWNhZqC/jv5uiNNxzHoSwKWJQl3JorjlXX/2GjDUkU8cILLw18rSzL2Nrchrk3vKCbFvQcLl2aCXkzzhjRL3J/HQ/9NojTxvf9aD5eL+hzvp+9i5DneczP19DSBg+Obml1Zro6qTugGJOZXeo8zspMKLrZCbz+m6XAtYeaKTYjGWhx+oQjr/P/xVLxmtJqhQu63o48loQ8F+IIkXGiKMFx2IlIBkJHnkCdSYKANkOfL4XGZQ5y5PGiDHMWrTlVupFK3fUJz3NMfPfH0W63USx2ryUW52/SqMxhHXmH38MWUf5dtqcRQxRtP+A+zglsxdufZWq1Gmyt3Vf4clptlMsVZmbG0/ugIPTepwkCz8Q9kbrqrBHmPdo2W468QqEIgefhdy6PphsKeaN21qdJ15E33Gw1TlKgzxx5qaB20kf8MdbeQWZCXuhKGzVe8/HjFubnF6Z2X5yfrwGIF/JGQWs3wXH8yIX1caBz7e6NGa954Hpoe97UYjWBrsDpjiF4kMCHY2qnysHOKjzHg4wRq9gPEiQ/cub69XB80DvvpOvGeuedh9jauoB8fnzncq22ANu2YDvTa5bTosaB0Wq+HMfh46/8LO6bNh5b023Mtv0Ab7VM3Hz+xaG/ly5dugJbO4BnZ9soZOw9QC6Xx8rKdOa3jsNMyJsxFvTGTU6RI8/3fYgxkY/AYSFvvCzvpFleXkGzGT+QGaBzuQ6YGQRMi4px0ZqFjlOPleIj7XoMBkT2+K6TycboWYVeH8eFPF4UIMgSdJ2N6+cw1BVWLh8950pFRbvdjp3HMG0cxxlp9pMgiuw58lpN0NpjSRTQYtCR5zjhPWXQsGZelJiLLj3r0BmtR5YnPI8gYGN2ay90Pc6Rx869sF4P1yuFYnnga4ud19D3sAQ5NMeKRbxO1DfPDxLyhJmQNyUqlSpIEMAz44s6jm4wJdzQNUlcmgfPc0zcE/P5UIwbxV1KhTz63qzheR6lYgle557S6rhqyuXB98ppQd11/LCOPFllKtr5LEEbR/0x1oa+42TSeEpjFJ8+HW1N8vRpO3rvNCgWSxBFMREhr91uolqtQohpXk6StbUNiIKIu8Z4Qh593/b29IQ8RVGh5vJwrdHvE55lAIQw42A/1aRYik2yzjs/X8Py8spI8ZqjsrfXxuPHTVy/fnOi41CBWdOm14yodcwdCwuji9svv/wKREHA/9eYbvPN/7QMOEGAW7deG/o9V65cAwAYT3fSOq2BEBLA3NvB5ctXmUi8i4PdM5txOuhT6CDkWKEsYwY78sKTZaXgvrS0Aq3djIo2vWjrLXiei6UlNoQ8GhGXi/mc853HLUYcKFSc8wcIeYFrI5/BzIFnlThHHgBIuRyTjjzqMi2Xj26gSyUVhBBmZom4rgthhM5XUWBTyBOpI08UYNk2uwVrlr4EZwDAoeJ09/+G4/lI4GORdrt9RMhTFBGSJDB1L9zb24UsKVCVwd+VpWLYwb67u5v2aY1N/0a17Og68voXDzle7Lt+nJEc5XJ4Pbt9ogY9w5yKc2NYBjvyOCb2Q7Rr3hmh852KflnMCoujXJ2Df0jIU2SZqbnbNOZ4WEceLymzWPCU6DryRl97e7YTvX+a5HI5KIqCg4Ph9zqEEBwc6Jifn55Yw/M8qtX52Bl5o9DWG5HDL21EUcTGxjncH9NRc990kFNzUxVNAaBaqcIzR9//ema4tmXpO/O0wnFc8qvZaEZesoe9fv0mPvxwD7o+nmA9iNu3Q5Hw2rUbEx1nfj4DIa/TfED/7lHI5wu4+fzP4C3NgD2lpAVCCH7Q1LG6soaNjc2h37eysoZSuQJ9936KZ9cfq7ELz7Emvk7SZibkzRiLaHZIX0MeAVvRml5fIY+69dhx5K0C6A5T7kWzudd5LRtCHp3dosZ0L8g8d+R1WVMqhd2w/gBh0XcMpjpnzzrUZSL1cEEKqsKUC4XSbmvI5WRI0tHiKhX2WJnjxvN8FIkxDAEhiWbgTwohBFpbO+TIC+81rHy+lG78dP/PmoAw9C35bBAVpw998BzHRtG6F67rwjTNI25fjuNQLueYuu739nZRKlWH6tCVJBn5fBH7++wKeYzqeMNHa/IzR960oMVGV+8t5BFC4LR1VCqVaZ5WX2jjQrwjjw2XMhXy7FGiNR0TsqwwE2MKAOVyBV7nntLyfJTL7FwLwCFH3oA4cIogKbBmQl4qyHL4fxCMOA+NEILA8yANmM2cBnT+5/7+8KJNu23Dcbypu67m52totydfO+l6C3Nz0xHyAGBz6zweWm40a3MU7lsONje3p+4uqVbn4FujC3nUxceSi/1Uk3DCRPdoye5gr169DkII3nvvSaLHpdy58whLS0sTC/Dh+zlo7ek68vL5wtgJYa+++hpsP8D/tKYTWXnfdPDYcnDr1ddGcm5yHIfr127A3HuAIKOavP70PjiOx+XL1zL5+4dlJuTNGAtJCjdHQZ8O9sD3IUnStE5pIKEjL/5GQhc3rHTl07z5fvGajc5zi4vLUzmnQdAuWCVmoShwHGSeHykiJ02i4kuf2AdCCDxTR6UyW0xOCxrXI6onO4PFnIo2g3E+mtY64pih0OI7K3MhJUkaqVnB91ym7uOWZcJx3ciRV+l8FzWbLM7aGgKCmWtvyngevf4POfIE4dDjbBE/f1Nlav7m7u5TlErDf0+WilXs7j5N8YwmgxA2hV16nXIDGiw4XoDL6DV91qACndPuXSDxLBskCCLnHgt0ozXjHXks7IdkWQHPCyPNonEce6L5N2lQqVQ6jjyCpuejzJjTxLJMCLIydMGNlxR4njtrFkgBKsQFI96/ScdpkYWQBwBzc7WRhDz62mkLeeVyBeYY4tJhgsCHZZlTbfLd3NxCQAgeWKP9zhm+j13bxbnN7XROrA/VahXeGJ81fc/MkTc5qYw5SsmRt75+DoVCAXfuJB+vaVkufvrTXVy5MrnLSpIkVCoVtFr1BM5sODStMdHMyI2NTayurOIHTX0qowN+0GhDkRW8+OJLI7/36tUbCHwP5sHjFM5sMObuR9jaOs/8WKWZkDdjLORO9Ebgxi8yA9eDogwX0TENhv0iY2Wu3/x8DaIool6P71hvNPZQrc5lEqPRi8iR10cwVQSeGUdeoVCEIIhRhEMvfMdC4HuzrrApYpoGBFkG10MQFhWFmZjKw7TbLZTLJ+93VNxjxTkzspDne0wJeY1GKNgJVMjrzN1kTcgbqfssxfOYcRI6k5A7VMDmRSGaa8gaVKyrVo8LeTloGhtCnuM4aLWaKI8g5JXLc9jbY8+RRze4rDo0h2Z2Y5ka+XwBPM/HOvLo4yy5sOg6IG52uCCwETfMcRxyuRycUWbkORZTsZpA+H9PAAQANI8wdS0AoSNPkIbfs9PX0kjOGclB19z9aiy9oMKfLGezZp+bm0e9bgxdJKYxnNMW8orFImzbnOg7no4IKRZLSZ3WQM6d2wYA3DdHW6t+ZIZr3s3NraRPaSClUgW+ayMYMebbtwyoao6p/edpheO4xB15h46e6NF4PnRBvfvu48TX4D/+8RP4foCrV68ncrylpRW0+qSmJU2ztT/RKCWO43Dr1dfx2HKie0Ja6J6P25qJl17+eKQZjMKFC5cgShKMp9OP13QNDbZWx/XrbMdqAjMhb8aYREJeny9m33XH+uVNC0EQ4HnxXwq+H0SvYwFBELCysoaDenzH+kH9KdbW1qd4Vv2hC9s4Rx4Qxm6yIuTxPI9KpdJXyPOieIdZV9i00HW9pxsPCKM1TWP4jeK0aLe1E/PxgK4jj5U4UEmS4fnDb6g8P5uYnjiazbD7revIC+/XVOBjBerwHujqIUFPwXpGelDB7rDYyktSJPCxBm0COOnIy6HVajJxL9zfD2O+SyM4jsqlOViWCV1nqzGDfp6n3mmS/WXxzMDzPHL5PDy7d4HVt8LHC4XCNE+rL9TZKYq99zyiKDAzakBVc3AGzLI+jOvYzHVSU2ExIIDp+8jn2bkWgPC9+SE6AAAgAElEQVR7kROGL5rzYvhaO+aanzE+XUfeaEI6FfKyc+TNwXG8oedbUSGvWp2ukFcqlUAIGSmu9ziWZUTHmhaFQgEL87WRhbz7pgOe47CxcS6lM4unWCwCCJuiR8FzTBQ6750xGaOO1BgGEqRXM7127QYMw8Hdu8mKZHfuPIKqqthMyJm6tLSMlnYwlaY/yzJgWWaU1jYuL7zwEmRJwn830913/U/LgE8IXnnlZ8d6vyRJuHjhEoy9nanvcY3dHQDAlSvJCL5pMqsezRgLmt/ux3SLBb4PEgTR61hAEIRIrOtFV8hjZ6bC2to66o3dnjcx17WhaQ2srW1kcGa9sW0bEs9FbpleKDw7M/KAMH+9X+wDFflmjrzpYRg6BKX3vUNUFARBwEw8K6XdbqNYPCk+yrIIRZHQbrMRBypJErwhOyMJIfAYi9akgh0V8mSeR14UIoGPFVQ1LCIGbn9xyHcd5gqOZ52o8HhEyBNhM+7IO94oUKnk4LoeE9+ne3thw1GlPHxBrtx5LWvxmlR8dxkVdkcJjZiZ8qZHLpeHb/e+ZqjAx5JLjLrt4hx5osiGIw8AVFWFO4KQ57g2M0klFLom8AmBEwTMnZ/jOAPnbh6GvvbUNzwwSOTIGzFakwp/opjNmp260zRtuN9VTbMgy/LU05voeVIxbhxoNOc0HXkAcG7rPO5b7kjF7fumjZWV1Uya68cV8gLbQmnKn+1ZReCFxKPiqTCYxszFS5eugOc5vPfeo8SOSefuXbp0JTHxcWlpGb7vo62nn4xCxyxNKuQpioKbz7+E25oJOyUBkhCCH7YMrK9tYHl5dezjXLlyHa6hwZ3C53sYfW8H1eo8FhYWp/r3jsNMyJsxFnTRFRf70I13YMmRJ/YV8qhbb9qDgPuxtrYB13XQbp+8iR10IjdZcuT5vg+B6//5CeAQBGwUB4Aw098z4mMPXSN0Uk27Y/BZRjfiHXn0ccNgJ87H933Yto1Cobf4mM/LzMQPFQoF2LY51CbQcSwQQphyETSbdQgch8PpvVVRQJMxRx4t2PoDio+BazPXmX/WcRwH/LGNHC+JcBh1FmhaC7IsIpc7WpyjDj0W5uRRMa5UHCFasxPDSUVAVogceSNGQbEIK1HxzwL5PkKe3xGFWWra6Dry4qM1WZkbqqo5uAOaYg7jujYUhS2hjAp3fuf+QoU9VnBdd+DczcPwkZDHZsPDaUYQBPA8j2BER2y39pJNE3VXyBtOtGm37UjomSb0PCeZk0dFwEJhuue/sbEJw/NRd4erowSE4KHtYuPc9GM1ge7n4zujuR8D18rk2jiLCIIQOeiSIk1HnqrmsLa2gZ/8JLno/d3dNppNAxcuXE7smMvLYcwlFdnSpNGJ8KR/5yS8/PIrcIIAP2qN70jux0PbxRPLwcsfuzXRca5cuQag65CbBoHvwdp/iKtXr52K/RM7isWMUwVdJAYxnXhU4GPJkcfzw0ZrsuTIC912veI16WMsOfKCwAc/4L7Hc2zNnllcXITnWFHBvbxxBeWNK9Hzrt5EPl9gqgBz1jEMA0JMh6agyp3XsBPHRiNl83n2hbxqdQ6+78OyB5+PrlMRmx03aqPRQEUScdhrUhEFNOrpL6RHIYrRGiTkeTbyDLk0ngUcxwYvHf2eF0SWHXktlMu5E5sKKuSxMH9zd/cpisUKRHH49VOhUIYgiMw58oKA7WjN6DoY0IzBQuTqs0Qul4sEu+NQgY8tR164TxOEeEceO0KeOqKQ5zAnlNHzcSMhjy2hMWxwmTnyWEGUpJGjNUnHQZtVigYVbYZ35NlTF8KA7n14krnITsdhNu1GPBqP+dAa7n6473iw/QDr69OP1QQOCXkjxph6jpnJtXEWGUbI44+t3Y//fJw0hTwAOH/+Eu7fP4BtJ7MG+clPwn3GhQuXEjkeACwuhu64xhSEvGZzD4qiolQqT3ysra1t1OZr+GErnTra/9/QIQoCXnjhpYmOMzc3j4WFJRi7HyV0ZoOx6k8Q+F4kIrLOTMibMRayrIDneXgDYmTyeXY2raI4nJAXNy8iC5aWlsHzQm8h7+ApSqXy1GMd+hEEBPyAMCceYMqRV6uF1mlq3S6vX0Z5vdux4+hNLCwsZXJuzyqObUOIGdYuSOzN5aDuwDghr1CQmBHyKpVQlKMiXT90g87mYkfIazbqqBxzEFQlAY1mg6nCdT7fidEa6MibRWtOG9M0IR5rMhJkGbZlMXUNUTSthUrlZNGXzt9kRcgrlUabI8txHMqlKnNCHo0g8jyPyeshmp80yK0ReEw10511+kdrOhBEkamY6m60Zr8ZeWys1VVVHXpGHiGkI+SxJZTR8/EYFfJcd8RozY57b+bISwdJlCJhbli60ZrZNCSP6sjTNCuTGgb93Rslrvc44XXPTf07dnl5FQLPY2dIIe9B53VZCXm0DuiPcJ8ghMB3bKYaX04zoiiC+P3XspXN9b4/HydtIe/ChUvw/QB37+4lcrz333+KUqmEWm0hkeMBYTrd3FwNjUYy59iPemMPqytribjEOI7Dyx+7hXuGjT0n2UYcNyD4H83EjRvPJ1LbuHLlKsz6k5G/C8fF2HsAnhdw/nxygm+azIS8GWPBcRxy+Xw0wP049HGWIsNkWenb2WFZ7MWBiqKIpaUl1Bsn7eWN5h5WV9cyOKt4CAkGzm/hOS7xobuTQDOQnZgMZs9oYXGR/Zzks4TjOLHdYNRJ4zA0v4iKdKfFkQcAhjGEkMekI6+OyrHCY0UU4LguE7PCKPS7r99ciHCzajHV8PIsYFkm+GMzOAVFASGEqQYBiqY1I9HuMHRmXquVvZBXr++jVBxNyAOAYrGKgwO23LRUvCNg021Co+2J3//cAt9laj171lFVtU9KiQuFsf+LQdGa4Yw8Nhx5kiQPfS70dSyJpkDXked19j+sRX+OCvuhU6cbaQxHHm3uyKqBQ1VV8Dw/UrRmFq4r+rs3iQjtuDYURZ76OBZRFLGyshoJdIN4YDmQRAmLi9k0JMuyAo7jEXjDr60Dj70o6tOMLCsgA6Lia9cvQy6XIKgKNl5/BbXr/SMo6VonrTXm5uY2eJ6PnHSTQAjB++/v4sKFy4nHJa6urvas0SYJIQSNxh5WEqz5vvTSx8FxHN5sJlubeq9twvL9iWM1KdvbF0ACH1YrfbEUCB156+sbp6YJcibkzRibfL4QOe+O41nsOfJUNQfLiv8iM002Fw6rq+snuj1830OzeYDVVXbm4wFhZOYgRx4HtqI15+bmwXF8z2GqvmvDs81TMfD0rOD7PnzfOxF9R+E7Q9xZFPJyuXghj5WZftVqWGzX9cHFf93QIIoSM/dx3/ehtbVOtGYX+nOzyc6cvHy+AEEQ4Znt2NcEjoXA95gSSp8Fwuje40Je+DMrgjuFEAJN0yLR7jCKIkJVpcwdeaZpdmaEjh75UiiU0GzWmXK+BYc6P2lsMkvQwkkwoDBDPG8m5E0RQRARxMzhJn6QmUsmjmFm5AUBYWK9Lori0O7ArtOQLSGPCov002SuUMTxCNsXhoO+8jTMkTmNhNGao87Iy/ba53keqqrCtodrgDFNN5MIXFmWwXEcnAmEPNd1MhPj1zc28dB2EQyxbnpguVhdW0vNOTUIjuOgqCqCET5r+lrW4pFPK4qiwh/gvOI4DlI+B7VawcL1KwPv677jQpLTE7IVRcH6+jm8//7kItnTpxo0zcL58xcTOLOjrK6uQ9MaqTrT2+0mPM/FyspqYscslyu4cP4ibmtmovuv25qBYqGYWITp1tZ5AIB18DiR4/Uj8D3YrT1sb19I/e9KipmQN2NsCvlCJNgdpxutyY4jL5dTYZrxX2RU5GNt4bCysgbT1I8MZW62DkBIkOhNPQkIIUM48rrRVSwgiiLm5ubhtE8KeW5H7KDxmzPShy6GBjvy2HHOUFFRVXtvnhVFYiZ+SFVzyOVyaGn1ga9taXXMz9eYKdRoWguEEFSlY468zs/N5uB/07TgeR6VSvWIkHdi/mbnuZmQN10Ms5+Qx5ZwY9s2HMfpGa0JhK48TevtJp8WjUY4hL04lpBXhuu6zMw8DYIAASGQOrc81oRdYPhozcB3oSiMiQVnGFEUj4jAhwl8nzkhryt4xTvyDr8uSyRJgu8PF3XLqiOPFjzpP2HaTp5B8Bw3io4X/UNYWR+eNWRZHkPIy/7aVxQlSjjqh+8H8Dw/cphPE47joCjKxNGamQl56+dg+wH2nf6fs08IHtkO1tc3p3RmvcnlcgPHDByGzhafRWsmg6oqA4W8UfEdN/Xf3XPnNvHgQWPiZqKPPgprAxsbyf8erKyELrlGMz3HGHX8JZ3CduO5F7DvuHg64D4yLE4Q4H91Gzeeez6x9U2hUERtYRFmPX0hz2o8BQkCbG+fT/3vSgq2VpEzThWFQgFBjCOPRmuy9CWsKDl4ng/X7b0ppSIfa3MLqFjXqHe/JOr13c5zbEVr8rwwsEPMJ+HrWGJxcQmecbIY6rQb0fMzpgMVxWKFPJG9uRw0fk2Sen+lShIP12Vj3hLHcVhZWRsq073Z2GOqWYA67o5Ha1ZF4cjzrDA3NwfPOiTkHZu/6UVC3vzUz+1ZxjQNiIqC2tWLqF0NOzTFjuDBiqBE0fXwGimVeq9LSiUF7Xa863MaNBrhJnkcRx4V/+gxssa2w0gwsVOcZsVJfRhaPKHxU70ghMD3ZtGa00QURYCQaHbMYYgfQGBOyAuLN4LQX8jzRhQT0oCKoMPM16b/LtaEUyp40VUga0Iex3Egoyl50ftmJI8iKwjcEYW8zuuzjG2VZRnOEIVhOuokq+8oWVbgDXC198Pz3MxctbSg/3iA8/HA8eAGJPMxLDk113e9chzfo82xbNXjTiuKosJ33Z5rk3Hx3fTdtKur63BdH0+fDh4F0o+dnTpEUUyllkdrJPUU5+TV67vgOA5LSyuJHvfGjZvgANzRktnnvK9bcIMAN248n8jxKOe3L8BuPE29hmbVnwAIY11PC2ytImecKvL5AjwzPlpTUdXMrPy9yOXCBUFcvCaN1mRtbgFdgB3OYK43diFJUqJDW5NAkkS4A260bkAgMRYps7i4BEdvnljkOHoDPC9gfr6W0Zk9e1BRjBd73zuowOck3F02Cd2IqvCcX331PF59tdvRI4oCCGEjogoIh6U3mvt9F0WOY0E3NKaEvEajI+Qdi9YsigJ4joueZ4W5ufm+0Zquyd4MwrNOEASwTBOCImP+8gXMXw4jNISOOMKaA4sKeYVC72JXsajAMBgR8vKlkd9byIdCXr1+kOg5jQsV7iQ+LE6z5tAE6Bwioe/8zcC1AUIymT/0rBKJTT3iNUnAniPP68TwxQl59HEW5uTRqMBhzoWKfax93pEjryOAsSbkCYIwUqGXvpa1xsyzgqKoozvyOvunLFxuFFlWh3LkUSEvq3MVRWmie5vve5kJeYuLy+A4Dk8GCHn0+az3cYqiDIwCPwyd5zYT8pKBCm5+gjOffduBmnK9dG0tHB+0szPZ3n5np4GVldVUatLV6hxUVUUjxTl59cYeFhaWEndal0plnDu3hTvt4WaaDuKOZiKnqolHmG5sbMJ3HbjGZILuIOzWPmq1RaZMSINgaxU541RRLJbgWlbPhb9rWiiVRu/OThP6RWYYvbuCDMOFKIrMxbHk8wUUiyU0W91CV7N5gMXFZeY2gpIkwRuwEfQIYe4zXlxcAgmCKOqO4upNzM/XmBKknx1OT5evF8XZhNfJrVvbuHVrO3qePj5J92eSrKyswvNctHvEyVIajf3otaxAIwTLx0RenuNQEgW0WtlGDB6nWp2HZ5uxG1jX0KCoKnNzWc8yVKgTjxUIRDUsJuk6W4486hAsFnsXuwoFJfNzpuKXLI++qVeU8NpnRTCLrg+OO/IzS3Ach3yhAN+O/8zoczMhb3oIQigckR5RlAGDM/JoY9EgIY+VBqRhyT73oD/daE229hWqqo7kmglmrplUkWV5ZEee73rgeT7TPassK5FI14+uIy8bMYzG9Y6L73uZ1TIkSUJtvjZQyHtsu+A4DouLy1M6s96oqhqJc8NA90yzRIFkKBbDdaBnJCPYAIBvWiiVRm/eG4WFhSWIohhFY44DIQQ7O3WsrW0keGZdOI7D6up6lJSWBo3Gbmqu2hvPPY9HloODCeM1fULwnm7j2vWbiX//0DqU00634dPV6kzVvIaBLRVgxqmC3sB7zcnzDBOlYro3+FGhBY12u7eLsN22oi871lhcXDoy00pr15mMexRFCV5A+jp9PLDXKUs/S7d9tOvHbTewtJTtAvhZY3jrPDvlGirQDZo1w0JEFXAorreT6X7xwnO4eOG5I6+pd55bXmZnUdNutyFwHFT+pMhbFPjIvcQKi4vhbE1H7y0wunoTCwvs3cfPMvQaocIdpSvksXUNUZEu3pEnwzSNTIvttm1DFKWxGovovDcaaZk1VFCUomhNtoRdSqlYgu/EC3lex63H6pr2LNI/YpCA59jaclPnGt/j+/Tw42wJeYMbvFhuAePAbrTmyMV2l80Um7OCoowXrSnLSqZxp7IsxY4wOYzr0gbI0yvkUadwFqysruHxgOL7E9vFwnwt8+ZpWVZA/FGEvFmTQJJQY4WbYMOca5qpGzYEQcDKyhp2dsYX8g4OdFiWi9XV9QTP7CgrK2toNPdTWSvZtgnd0NIT8joxmO+2J7s2PjRsWL6PGzduJnFaR6B1WEdLbwRD4LlwjBaWl5ONL00btqrpU8IwDHz961/Hd7/7XXzwwQfQNA3VahUbGxt45ZVX8Ku/+qtYXT1ZvHRdF3/3d3+Hf/7nf8aHH34I13WxurqKX/iFX8AXv/hFzM8/W3NuisXOF4NhQsofdRR4poXScjrdD+NS7AiLmta7YKRpNrPdy7XaIh4+fAtAKBrousZcrCYQCnkE4Rw8MWYf4RKS6eK3F1TIc/QGCgiH4ZIggGtoTAqmzwQx1w+L8ziOR2seR4zm+rEh5C0trYDjOBzUd3Fu4xIunL9x4jX1+i5yuRzK5UoGZ9ibdltDURR6XgMFgYempRu7MCpUpHP1JtTKyfu1azSxtHXys5+RHlQYOy7kcTwPUZGZE26GceQREgpQhUJhmqcWYVnW2J3TdC1gWWwIee12eA+ReA4izzEn7FJKpRLqT+JnclCRr8hYQ90MdgiCADzPxa6pqNDEhpDHTuNWUrAwM/kwiqKCzBx5zKAoCvwRZ4EHbnZz2yg8L8D3B1/b9DVxjuC0kSRpogaiLB15QNhkefv227CDAEpMU8ATx8Padrbz8YDwHuGPdG+ZOfKSJBLyjGSEvMD34Vn2VJLXlpaW8f77t8d+P52vl6YrdXV1rZNy1EC5nKwWQGfvrayk83s8P1/DQm0BH+htvD4//n7hA90Cz/O4ePFygmcXIssK5ubmUxXynI6R47Q58p45Ie+HP/whvvSlL+HJk3CgoSiKKBQK2Nvbw+7uLt588028+OKLJ4Q8TdPwhS98Ae+88w6AcAEgSRI++OADfPDBB/jGN76Br371q7h27drU/01ZETnyenR4uIbJXAGBdibHC3kWikU2f4EXFxdh2xZs24TRiX9kUWCSOrOrXEIgxigxbkCYc+Tlcnnkcnm4Rit6zDU1EBIwKZjO6MYTsUScxsia9ijLMhYXl3Fw8CT2NQf1J1hfP8eUcKrrbRRiNv1FUcDjNltCXq22AI7jowXiYXzXgWcZTN7HzzJUGDserUkfyzqm8jiGoUMUBchy7yYB6tQzDD0zIc+2LUjieMVDjuMgSTJsu3dSwrRptcI1gMBxKIli9DNrFApF+PZHsc/7dhgJyto6/Nmgx+KEwfVKEPh9XWGCwI4jj4pewy1HuCPvYQkCQOCAgLDxuR4ml8uNJBz50RyrWTR4GqhqDoHnI/B98ENGlfmOk3lUO8/zQ13bQcYzFkNH3viNOr6f7dxTmpby1HZxLndS8HKCAHXHxUsMpKrIsjzSjLzAdztrQ7aavk8rVHDzEhLyPNM6ctw0mZ+vodUy4TgeZHn037f9/XBPV6vVkj61COqWqzf2UhDydo/8HWmwff4S3nnzBwgIAT9mzedD08H6+kZq4vvy8io+3HmQyrEBwGmHIuHS0uly5LGV65Ayb7/9Nr74xS/iyZMnuHXrFv7mb/4Gb7/9Nn7wgx/g7bffxre//W186UtfwtLSycLal7/8ZbzzzjvI5/P4kz/5E7z11lt488038fWvfx3b29s4ODjAr/3ar6HdZrN7Nw1ogcA9lrnsuy4Cz0s9O3lU8vkCOI4b4Mhj65wpCwthRFtLq6PVqh95jCXohs704xfxlh9kvtHoxcLCIlz9kJDXicNj8XN+FmBHPhoMFbviCkf08bgIqyxYX9/AQf1pz3P2PA+Nxj7W189lcGbxtDUNxRghryDw0A2dqeKdKIphF5l+Usij95eZkDddqMNKUE9uNgRVYc6BZds2VFWKFdRVVeq8LjtHm+PYE7nsWRLy2u0WOAAcOJQEHprGppBXrc7BtY1oRnV54wrKG1ei5z1ThyhKyOdPz9D20w5DPS9DQR15cdB7Do3gzJLu9/oQ0Zrc8fewARUuuM6/YZJYvzTI5wvwXbvnjMde+LYJSZZnxfaUoPtp3xleAPFsB7lctvd8QRDg96kBUKgjL6uIWUEQJ7q3+UG2Qh7dO+zGxGvuOR4I2NhjyLIKEgQgQ37egZd9ROxZQlEUSJKcmCOPHmcadd65uVCAo4LcqOzttSGKYqpNbQsLS+A4Ds3mfuLHbjb3kc8XUj3/8+cvwvYDPBowczMOJwjwwHJw/vylhM+sS622AMfQUlvXuYYGjuMwN3e60hWfGSHPtm18+ctfhmEY+OQnP4mvfe1ruHXrVjSQUZZlXL16Fb/+67+OF1544ch7/+u//gvf+973AAC///u/j8985jPRl/dLL72Ev/zLv4Qsy3jy5Am++tWvTvcfliFdq7Zx5HHa8UGjN1mB53kUCgVo2smCURAQpmfk1WqhmKRpDWgdd8f8PHtOMVo0ihPyvIDACQLkctk4B/pRqy3AO+zI64h6M0fedKGbOhLEiGJRFydLX19UyOv9LGON1wCA9fVzsCwDhnFSuGg0d0FIgPV1tuKR9baGQswcwqIowA8CWFZyMwCSYHFxCV6PGXnUpTebkTdddD1crxyP1gQ6Qh5j0Zq2bUNR4otF9DnHGS2CK0l4np9ocxUEQWbxWsfRtBaETvGoJPJot3rPt8yaSqUKEALPCq/X8vpllNe7kTau1UalUp0VwrKALf2oL/0uD5auHdcNC0yCMLhwLgjSkfewQuRA6vzsDymYTYtKpQoA8GxjwCtDPEtnKnr9rNEV8kaIJHTczB2Sw0drhr8PwpBuw6QRRRHBBL+Dge9lKuTNzc2D4zjsxwh59HFaP8oSRQkTG4IhmxeI70LKOCL2LMFxHCrVKhwtmUZFepxqNX3Rg46tGlfI29/XMT8/n+p6RpIkzM3No9k6SPzYzdZBNCMuLc6fvwAAuGuM11B533QQEILz5y8meVpHqFbnQAIfvpNO06pntlEslTP7PhoXNnbOU+Db3/427t69C0mS8Ad/8Acj/Ud94xvfAABsbGzg05/+9Innt7e38alPfQoA8M1vfjOZEz4FiKLYiSM8Wjh19PDncpktIQ8IXYSt1smbgGE4CALCbAwR3SwZRhuG0Yaq5qAo7GWH5/OhQGfELI6NzsK9UGCvS7xWW4Rr6dFC0zVaUBQ1+jfNmA50vkPg9V7w08ezngNxmEGOPFrZY6kwRkW6g/rJeM39g6cAgLU1thx5ummgEPPdTSM3WYtGXFpahqM3IwGa4ugN8LyA+fn04j5mnMQwdAiS1DOqSlQUGIxdP44znJCXpaNNkmR4/vhFc89zIUls3M9brVY037csCmgx7MgDws1nL3xTx9zc3DRP6Zkn+v7v9T3PsecQO004jgNBEIdq4KLu4CybG3pBhTt6ebAm5NF9Jm0OGIRv66h2xL8ZyZPLhfHfvj2qkJftzMLhozWzdeSJogg/GN8V6/n+UI0FaSGKIqqVKg5iHJtdIS/7PQaN2xs2XjPw3Nl8vISZn6vB0ZLZ31AhbxprTLpH3t8fT4Tc39cjV1+aLC0to9lK1pFHCEFrCkJeuVxBbW4eHxrjiWQfGhZ4jsPm5lbCZ9aFXmtxe55J8cw25k+ZGw94hoQ8Ksa98cYbI3+pff/73wcA/NzP/VzsguPnf/7nAQA7Ozu4e/fu2Od52iiVyyeEPK/j0GOxU69crqDZPOnYoI+xKD4CoWiRy+VgmG2YZhsVBj9b4LCQ13sRTwU+FsWxhYXQeUedeI7e7My4Ykd8eRagMT3xQp5/5HUs0BXyej/fre+xcy2trKyB43js95iTd3DwBPl8AZUKO/cZ3/fh+z6UmCgwufO447AR0UdZXFwCCYIj8zeB0JFXW1g8dd1fpx3D0CHmehe6xJwCg7F41uEdeVkKedLYMXGEEPi+x8z9XGs1I0deURRgOw5z9xSgK+S5Vu9NrWe1UanMhLxpQgvTXI/vKI7jERD2rPkM3er64rrO0PG91CXDqpDHR9Gap13IM5jc558VaETmKI48z7EzH13BccPdV7pzL7PZFwnC+I48QggICTJ15AHh6I99t/e/Yd9xUSqWmBDEaOP50EKe70YuvhnJMD9fg6O1E9nf2K02CoXiVK6tfL4ASRJRrw/nFD9OvW5E6+U0WVpagaY1Eo0itywDjmOnLuQBwPaFS7hrugjGuD7uGg7W1tahKOk1kVD3p2tqqRzfs9qnLlYTeEaEPMdx8M477wAAbt68iXq9jj/+4z/GJz/5Sdy8eROvvvoqvvCFL+Bb3/rWiS6iRqOB3d1w0OTly5dPHJty+Lmf/OQnKfwr2KRcKp8YntrNTmZPFCuVKmg2T3YcdIU8djcl5XIFptmGYbZRZqjAfhgarRkv5IWPZ53h3wt6A/c6X5IH8QQAACAASURBVBK+pUeW/hnTgzozYoU8lz1HHo2Fi5sLQR9nKQ5UkiQsLS2hXt898Vy9vou1tXWmhEfXDYsZcsxnSB93RpgnMg3oAvz4nDxPb2C5xzzeGemi620IMQUCUVERBEGm8+aOcxocebIsw4u5Xw8iCAIQQpgQ8ggh0DQtEvLKYiiyt1rsufKiGLwe3amB78GzTVSrM7fMNIkKOD0deRyCIeZGTRd2vt8H4TjO0EVznhfAcVy0ZmAFr1PEpjova9GftHFrGCGPBAFcaybkpUkUrTmkI48EAXzHzXx/zdK+oR+SJI4tptP3ZenIA4DawiL2Xa+nOLPv+qgtZB+rCXT362TI5IbAc6GmKAo8i8zNzcN33ZEcvnE47emJHhzHoVgsod0efY/jeT5M05lK2tri4hKCIICmJRfHT6M6FxfTF/I2NjZh+T4aMY0BcQSE4JHtYuPcdjon1mFQCskkEBLAtfRoX3WaYKeqmCI7OztRZ1673canP/1pfPWrX8WjR4+Qz+fRbDbxn//5n/jt3/5t/MZv/MaRLr4nT7puhZWVldi/4/BzT58+TeFfwSblcqWnkCdJMpPRj+VyGe22eaLgToU8FsVHSrlchWG0YZo6ymU2bzZ04xEn5NHZeSw68rod7qEjwzXbU+nimXEUnufDTkmv92KCRp+yEsUGdN2BbswCiD7O0jkDwOrqOuqNo0Ke73toNPextsbWfDz6vSzFFAno46wV7+igeToTDwivYcfQprI4n3EU/f+y926xkmxpfec/bhkRGRl52ZfadTvn1Kmq092mRVvtZvqYiwEzgLExBhqN+sGWAIseGR5mJNsPFgIhISxL9oOfeMGyLAssW37FyI80QvOARmMYP4wsEBqmOd1d55yq2jsz4x4r1pqHyBWZO3dG3nbujC9zr99L1c7LPutkZUau9f2///8Lw4Xz8YDp3DxK8ayM5TBr5kICgGUZk8dtHxF1WyyrBcayrTp9GZsI9AQaM6IoBCtYFa3Zmwh5w+HVkmc1g2VZ6HS6yKOb3alscpuK7d0vlSNPu/l51XSNpCPvUMiyFKaxntivaRoss0XOSSubLWSjALX1OY47GZexuuM9jwNACHWNuUNkY+y6hXfp3GtayDsUDMNEsaV7RkZyNt2AdHp6hrTgCBfUXN7kjMR8PGA2WnPdGXmMxJ7wmJCN6buYk5ePw71e+z3Px3i8eYOlFP/2IeSdnpapXkG4OyEvCMrftY/X+uHDRwCAj9PNGoyu8gIZ59Xz7wrHcWC1WmDJds7MZRRpDAhBKoVqXZptJdkTs920//7f//tqTt5P/uRPwnEcvH37Fr/5m7+J3/md38HXv/51/Mt/+S/xK7/yKwCuF3SWxRXMZpIHweYXydPTzsbPocDFxRn++I9jCM6hTRwReRSj3+/hwQN6otjjxw8gBDAaJRgMpptdKeQ9f/6k8aiEOi4uzvCNb/x/SNMYjx6d4/yc5jy/judhXNPlJm9/9uwRul1a6z899WCYJlgcgGcJBC/w5MlDsq/zMdOyW+A13crSkXd+3iPzb3NyUl7rsmzx+z7LGDRNw6NHA1Ldqh988Bx/8if/F+I4hOuW4vrV8A2E4Pjc516SeX0BQIjyGm3VRGvK213XILVuwEe/P7gm5OXhEBACL168R2ytx0+aJTC8xa+5dOo5jkbm30XXtcrxuwh5X7ttNbbmJ08uUBQFkiSqriPrEkyirN9551Hjr3kUld2v5uQa3ZuIpJwnja9tEQ8fPsBHb266BWUh/sWLd0mu+1hx3fLssDhaU4OmCVL/Hp5nV+LjIuR9p6d+4+tmLEOrtb5Do2Xb4DxvfN2zBMFrANPri2WB1PoA4OHDC7wari5E5lH5mJcv1R7mrjg5KWsUbE23PUtKIe/hw9NG/01ct7VWU498yGDgNbLeXs9DUZRutk3PZTKSczDoNPpaP3tWNlxe5tcFsoxzhKzA06c0ahhxXIpIvFjTXVrk6HabfW2PjSx7FwCQjsZon28vDPGiQBqEePp0f3v2k5M+Xr/+xsbPk+Lf48d3XzM1zfKzGK3RCLMuUTSGpml48eLpnY/h8P2X0AB8O83wV/z145lfTRpNPve5F3f+Gg/6A4Tp7httpThI5Xq5CTQVix0zu6HgnOMf/+N/jK9+9avVbScnJ/jVX/1VfPOb38Tv//7v4z/9p/+EX/zFX9zrgNg3b4KlByqqmKYDIQRYksJqlx/8PIrQ93x8+und5NjeBl0vu4KGw/iGkOd5Hi4vb87Po4Kut5Cmcn0WydcXKF2N4/HlwvtGeQFd1xHHAmlKb/3dbg95EiCfRMsYhkv2dT5mbNtBURORKLtO0xRk/m2SpDzUZdnibsMsK2BZFl6/vpshvdvS7ZYdZG8vP8ET930AqKI2Pe+EzOsLAK9eldeUVs2BW87Ie/16SGrdQNmp99HrWSGvLL7bdpfcWo+dKIzQuVi8t5NC3re//QaeR8NpkGU5dL1+q65P3vfjcdzYe6nVKhvRxsFwcyFv0nFqml7jn4W/+ItvlWupojXL1/2jj141vrZF+H4fxUffunG7nMepaWr/sk+CYNIxvug7SteR5xmpf48s47Vx4MA0Enw4TGAYza57OBzBttcvLrVaDi4vae0FXr0qGwWMyduD4l6l1zvBR6/+x8rHyT2MYbTJ/T8cE62Wvb4jbyL45bnW6L9JkuRrzt4sH3R11czeJU3L6xvnxcYRmXImcByzht//5Z51NJcGM5ok2pgmjc9nGJav19oz8hgD5zqJtR8PZf0zHd2uDpEHISAEHGd/dV7LcjEeb+5gl88pCuPO18q5Dk3TEUb1r+/8nN9Vc3/DaIxOx8fbt7t3oS3iZHCCj9PN6uCv0hwagFbr7t8PnY6P0dvdjzqYxom3yF1zdF1bava6F9GanjctLLiui7//9//+wsf9wi/8AoAyt/6P/uiPbjw3juvf3Ekytfx2OofprtsG3y9tqPlMvCaLErK5+XK90oEnGQ5jsmuWyJgNgHZ0ht/tYTQpAHyp7+FL/elnaMQK+J0OqVlhswz6A7A4rDKY1YyZZvDaXm0Xquw6nf08NI2MAKmL1swy1ngEyyIePXoCANfm5F1efYpWyyY39FdGZpoT4WL+2jKN1qQ1dwYoB9KzaFQ1FWWTbvZ9NgspykauJIlrZ+QZk89xktBp6OGcL3XkSSFvWUH+rpGxL1KU24RpdEzz1xsZoSmj7yxdg2caJKM1AeDk5Ax5ElVx05I8HqNl26S+I+8DRVFMnHcLHHm6Vrk4qKDrOoQQN2bDS6ZzoO62E3wdoijayJFntxxSEcnANFpTNgpQmsUqOT09Qx6HN64p8+TRCK2WDc+7P/WOJnBdFyxZ05GX0jsbLUOKfU2FlFhWKd7xLeI1ZSRn0+c6OdNpODeKYjg5i1KJipOjdsSa0ZqcZXBqIvAV29Fq2fA6HWTj2wkVUgjcZ7Rmp9NBGCYbx/fLaM19fE/pug7f95c68p48fn/pz/NE0Xivc9suHj3Gq3SzMQ2vkhwnJ6dVfO5d0u32UKS7FzXZ5HdS1wEWQbOavmMuLqZzaN55553aL96XL19Wf//mN79547mz8/LmefXqVfX3Bw8ebL3WQ8P3SwtqHpUfAiEE8iiqbqeG3NRcXV2/EFxd0RfyZsW7ZTGvTdPt9jBiZWHgiz0PX+xdF/KozvcDpl8Sh3xRPwba7XZtF6rsOqV0WJWz79KaDVCWFSTz/h3HQbfbqwYqA8Bw+BYPHlyQFdvlmX/+2kInsPQmp6dnKPIUPCsLd3k4Qsfv7mXjq5giZxIZNZ9FKfAta9raN5zzpbFP8nO6TTFqV5Siv4Yg2FzwGgdDtNsebHv9Iv1dMRxewdS0yjEDlHPy6Ap5ZSFlfqZVHo1wMjglFeN8H+C8qEYMzKNpOooawawppAulKBYXx9hkH09FyLM3idZsuYii/XSxr4sU7nRNQ0vXSQp5Z2flTK18xZyfLLjC6dmZusbcMa5bfxaaR56N5Kz6ptA0baNozaZ273KMClshWi9COvI2dfLtGtdtwzTMm0Iek0IejXqL3N9xtvq9LAQHLxiJPeGxcXpydmtHXjre/wxm13XBuaitsdQRx/udG9rvD5YKeR+8/AL8Th+27eJ/+q4fwgcvv7D094XRGP3+YNfLrOXhw8d4m+XINtirfpwzXDx8fIermtLr9ZEnIcSO99IsDmAYJtrtzRJlKECzUrdjer0eHj58uPJxsxsPuTnt9/s4Py83tn/6p39a+9w/+7M/q/7+wQcfbLvUg0M63FhUHkh4noOzAr5Pbz4eALTbHgzDOEhH3qx4R0nEmMf3uwgZQ7FgIz8uBHzCr3On44OlMYo0hqZpB3lRPwaWHV5ZmkLXdVIiiOw2TGuGBCdJTmq9s5yfP8BoPBXyRuO3OD+n14xSCRY19xdzj6OEHDifTSLv8nBYFcwU+0MKdIfmyNNnZm59+OH7+PDDaRenvK/OVbMPTNNEv9/HqCZSexmj8WU1JL5phsMr+JaJ2cJizzQwvNr8/2sfSEcvi65HzbBoTOY1vU/wmVnh82i6Ts6RZ5qlQFfn5pUCX9PF6jzPwViO1gaFXdt2EMe0HHkyuUfXANvQEcf0hLwHD8rm5WxFUwYLr3DxYHVdRXE7XNetxgmsQp6Zmk/sWVeYK68vTWnBMtau2OK6LIW8ph15mqah1+tiODcjT/5Mpa5lWRY0TQMvViem8IlrT56rFbvj5OQU+fh2Ql42CmCa1l7rvLI5QQpz6xLH+eT5+xGFOx0fyZJoSk3T4Loeet0TfOblF1Y2wqRpjE5nf8aY09MzCABXNelS83AhcJmxvdUzTk5OASFmojB3Qx6N0R8MSNaPVnF4K96S7/u+7wMA/OVf/mVt9Naf//mfV39/+vRp9ffv/d7vBQD84R/+YW2X0R/8wR8AAJ48eYJnz57tYskHwbwjLw/jye00Ng/zaJqGbrd7TchjrEAYpmQ2PHXMbs6b7rhbhnwdx+zmF8GIMXS7NEVeoLTvC14gj8Zw3fZBXtSPgXbbQ1ETJ1OkGVy3TaoTWH4eo2jxd0sc5wQO14s5P7/AaHQJIQSyLEUch0SFvLLoyGu+g+WIWYqf2fkudxaNcKYK7XtHRpsZNcUX3TQATbsWld40Mv5O8uUvP8OXv/ys+lnOVm76ff/48VO8eVufWrEIzjkuLz/Bkyfv3NGqNmM0vEJvLsa0axoYjTaPDN0Hixx5QnDk8Xiv3dKKkqLg0PTF+xJN16o4NipIpx1bsFefvb1pR14YloVHx15/D+XYLpIk2apIf1dEUVl80gG0DR1xTMsxCJRNR5qmIwvqmxeKPEWeRLi4UELeXeO6bfB1hbzJ4/ZVtK5D03BQjrxVMbKLkNcV+TuapNsbVClIkhEr0HbdxoVGiaZpaNn2WjPypGtPOfJ2T78/QBbFt3I05WGEXq+/1xqMNDJIYW5doiiDbdt7Ox/Ztg2WbyY21iGEQJ5nexW05UiVy3y9a+KIFeBC7G0Ui/zv5PFu59ixeIyTwWGemehVvO6In/mZnwFQdmT/h//wHxY+5t/8m38DoLxgfPd3f3d1+0//9E8DAD766CP8l//yX2487xvf+Ab+63/9r9cee18wDAPttlfNyJN/Uo3WBEqRcVbIk3+nLuSdnz9Ap+NjMDghE5ewCBlfOpzr6EgKjrTgpNcuc7Sz4BLeHrtgFNdpt9tgWbZws8mSFC4xR6oU6eq6xaIoIxuHe37+AIzliKKgcuadn1+seNb+qRx5NfUBARqCxiLKa54GFofgLAfLEnIzCO8Dcs6ibi4uTGuaBsMwwNYoNuwLXdeXzr+TTjwpdDfFO++8iyAYIknWL04Ph2/AWI6nT9+9w5Wtz2h0ha51/XXsWgaSNK1iWSnhum3YtoN8xpHHJrEzSsjbP5wX0LRljjxa0ZoyErxutq+8velitZx1Z9vr76HkY6V4RoEoCidFFw1tXUMU3s4ZcReYpomT01NkS9zV0q1HcZ94bLiuW82+WwVLM7RaduPC+6bCXHMz8kqR6zbRmhSEMt/vYjz33RIwDr9Dq2nabjlrCXli8hjlyNs9vV4fEKKq1W5DFkZ7n704deRtdjYrm6j3V3txHKc6Z96WomAQQjQi5F2tKeRJ596+4j8rIW9JfOk2sDggMad9G+hVvO6Iv/bX/hp+/Md/HADwr//1v8Z//s//uerOfvv2LX7jN34DX//61wEAX/va165dpP76X//r+Jt/828CAH7t134Nv/u7v1t14/zJn/wJvva1ryFNU1xcXODnf/7n9/h/RYOO7yOfRGvmsRTyaG0gZul2exgOpx33hyLkdTo+/tk/+zX8k3/yyyQ2j3X0euUFnXpm+yI8r4zSzMaX6HgqVrMppKDKFkQPsTiBT0xklR2wUbR4AxfHOVkXrXTfjcZvMRpdXruNEquiNSk78kzThNfpgCVBFQkhr5OK/SHTGLQlUXG6adamNjSBruuV624R8j7DaPZ9L8W4129eXbv9xfPP48Xzzy98zus33wZQioBNI4TAeDxGd07klT+PRqNFT2sUTdPKqKSZQ638uxLy9k/pyFsi5BGbkSfPEVm2WMjLsgKWZTb+nVo58jbYQ0khLyQklkVRBH2iWrQNnZTIOMvDi4fIw/poTenWkzGcirvDdd31Z+RlGRwCDYOr9iwS+Zi65oe7ZurI2z5as+kmB6CsW0Rz/w9hwdHudBpa0WIcx1lrRl7BpLO0+ffysSFr23m4vRucTRx5+0SKcXU1ljriONurQ9m2HeQsW8uRvAopCO7Tmep5HZiGgcs1ozWlc29fjcm9Xh+6rl9rXrwtRZ6iyNODba6mV/G6Q/75P//n+O7v/m4kSYJf/dVfxZe+9CV8+OGH+J7v+R789m//NgDgq1/9Kn7pl37pxnP/1b/6V/jO7/xOhGGIf/pP/yn+6l/9q/jiF7+Ir371q/iLv/gLnJyc4Ld+67fQIfbFuQ/8jl8V3OWflF+H+WhNKepRFh8PCfkFX5fZvs/BrZsiBSRAzPxdsW9kJnheI+TtMzN8HXRdh+M4td1ipSOPlotQIjcvYThGEJabI4qf0akjry5aUzrymu5GXky/P0AeB2BxMPmZbkPDsSIFujpHXnkfNSHPWFoUk269povtT548habpeDMn5D1//zvw/P3vWPic129eod32SIhOURSBFUWtkDccLp8Z1RSnp6dg8ayQV17DKbym9w3Oi/poTY1etKZ05GXZ4u7rPGfVY5pkG0eeUwl5dMSyKAphTN4enqEjIrS2WR48eIgsHNVGDmbjS1hWi+Q+8dhwnDZ4UawlNhVZDrfhWE2gTGpaliIgkY9pSgyTM/Ju48iTv6NJ2m0PacGrVBIAiLmoGpOp4Lou+BpuJc5oRMQeI7I+l20p5AnOkUXx3oU8KWYlyWZnsyTJN9o33BbbtiGEqK4PtyGvImb358jTdR39Xn8DR175uH29H3Rdx+np+coZvpsg0wcOtTHpXgl5ruvi3/27f4d/8S/+BT788EN4nocwDHF2doYf+ZEfwb/9t/8Wv/7rv74w99f3ffzH//gf8cu//Mv4whe+UHaWcI73338f//Af/kP83u/9Hj73uc818H/VPJ2OjyKZCnmGYZDupPH9LrKMIU3LL4TRiL6L8JBwHAeObd8Ylip/puzIm33fUn4PHzuyEYAtmFXFkoRko4Drugu7xYqCI8sY2WjN0omsIYrGiKIxOh2fRJfpPNI9kNcIefJ2y6K3dgDo9/oo0hB55cijex08VqbRmvXvEc00dhaNsgtWR2vSiJRttWxcXDzEp6+/tfZzXr/5Np4+fZfEvFM5B683J+T1LLqOPADo90+Qx+OqA5jFATRNJ58wcYwURbHUkXebuTR3wTqOvFareSEvisrml42iNZ325Ll0xLIoDGBAOvIMRElMzqUJoJp9J4tl3aefQffpZ6r7s/ElHjy4aPw75z4gi7h8jeYinuWwCZxbpZC3ypUiZ3A29T6S179tiu7TGXkUhLzyWjfb7xUWBdptWkLeuo48KfapGszu6XbLc+e2jrw8TgAh9r6/lNfBzYU8tldBuIrr3cF4hqbie/snp7ismZs8z2VeoON5e13jo0ePkU/GwOyCdPQGAPDw4eOd/c59QrPidYdomoavfOUr+MpXvrLxcy3Lws/+7M/iZ3/2Z+9gZYdLp+Mjj+NyMGecwPM6JAozdXQmueGjUYLzcwujUQLD0KvNkOL29Hp9DKPhtduGjEHXNNKC6ewXvuoGa466aE3OChRZTtIt2W57CIKbc5TkbdQOVRLDMOD7PsJojDgOyApMUghNakSNeHI7Vedjv98H+x//z8SRp6lCewPkk+5BfckMGd0wSDnyypl99YUmxvjkcc1v558/f4k/+qP/A4yxlc0AURRgNLrE93zP9+5pdcsZjSZF6/kZeVW0Jk1H3mAwgOAcRRrDdNrI4wDdXo/AnKT7B+cFUFeUnkRrCiHInI+kSFfnyMsyRiLGP56MbGhZ63emt1r25LnbR4jtmigMIQ2bbUOHEAJJkpA7e15cPAIAZOO3cHpn6D75oLpPCIE8uMTD97/Q1PLuFbKAXeQM5oojKc8ZHL/5uWLyu6coOMwl6QdUHHnFLaI1KVwf5dmSQ8CABi4EYkZRyHMhNhLyVA1m1ziOU6YDpNvNfC6S8nn7rsFMHXmbie5JwnBysr/3UdW7sNM93n73i77fxafFetGgISvQ7e43kvLRo8f47//9j1FkKYzW7b/vsvFbuG6bdG16GaqdSnFrOp0OOCvAcwYWx+Ri7+bx/XJ9o1FS/dnp+GQO18dAv3+CK3a94H6VF/B9n3QX52wWtdpENoe8hswLeWxS0KF4jfG8zlIhj1rMySy9Xn/iyAvIRj5aVgu6riOu6WBPJu2oVLs4Ox0fvGDIozHcdlsV2htAiMl7pyb+DgCgaTuZb7ArWi27ttAOTIvwFJwzL168RFEU1ey7Zbz6+C8nz/lgxSP3QxCUrh/PMPClvocv9cvrdUvX0dJ1UrO2Zun3J8PfJ/GaLA4OdtbDoVPOyKuJ1pzcTsmBNRXyljnymhcGkiRGq+VsdEZrWeX+PV4Qz94EQgiEUQhj8v/gTWaaUryunJycwjDMahbeLEWWgGVJJfYp7hZ5JuXZGo68PN/rPKU6ZoW8ZUybkJrZC0sBcTtHHp0ZeVKwk7X3hHMI0Gsedd02iny1gCQfQ/Usd8homgbHcVGscT1ZRJE1I7KapgnD0LeK1myilrfbavJ+z6Oe5yFkbK1zcMD53kVd6ZxLx2928vvS8Vs8evT4YDUAuhV1xcEwLbrHYHFaCWVUkeuTc/JGo/hglXiq9Pp9DOes2cO8QK9Pu8A0uymncCC6r9i2DcM0b8zIywnP4Fwt5NFbs6Tf7yOMxgijMVlHnqZpcGx7pSOPqgAv//2z4BIdwu+FY0YeTJZu1zUQE/JatYV2AEhTOkLee+89h6bpePXxN1Y+9uOPvwHXbZMpCEvnjmfo+GLPwxd70yJY2zQQRXScPbMMBuWcKjl7s4gDDNTsqkbgvICm1UdrAtu5P+4KKdLJa8g8acpICHlxHG+8DsMwoOsGkiRe/eA9kCQxCs6rGXmdiVMpCMZLntUMhmHg/MEDpOObQl42ibSS8ZuKu2XqyFtdwC7ynMTnVZ6j83y5kCeFvqaEvNtFa9IR8mRaiZwTnhSyqZHWWajdbqPIs5UR00WewLJaJNyOx4jjOCjS7cYHSAFw36NCNE2DbTuI421m5O3zmrjLs2MzwpLndcC4QLZkNrskLAS8PTfWP3o0EfJGtxfyBC+QjS/x6NGTW/+uplBCnuLWyK4flmYo0pRcF9A8UrS77shTQt4u6Xb7iFmBbGbDNiw4WZFgEfv98lfMomkaOh2/cuBJWCXk0WsW8LwyWnNeBDgEIa/T8RGGYzCWw/PovbYS13Er5908CZdCHs0uzqmQd0VSiL4PVJ/NJZ13GjFHnmVZS4W8fDJ71rKaF/Icx8HTp+/g44nbrg4hBD7+5CM8f/6SjEM/DEu3TGuBo6qta6Rmbc3Sn4h2eRxA8AJ5Ela3KfYL57zW7SsFvsoVTAAp/st54fOUQl7z15UkiTeK1QTK63irZZMR8qTj9xAceQDw8OIRWHAzTli69JSQtx82mZFXZPsuWi9mVYOARMbkNbV3uZ0jr4Cu6ySSNeTrJ3etsu5C4do9i4wQXuXK43lKdkTCMeC4buWs25SpI2//52zbtmv3KotgrABjRUNN+Yfp7gKmtYpwhaMaKKM1913b6nR8DAanSC4/vvXvSoavIXiB9957dvuFNQSNE7TioJFfzixJwZKUXN7/PI7jQtc1BEEpCgRBqgqrO0YKdsNJkZELgVHOlJCnWBvf95FH89GaUsijJ7x7XgeMFTcOr/I6Q1nIc912Od8HIH39dly31pGXFBymYZDt4qyiVcX+oygUJesIedceRwDLaq0VrUlByAPKOXlv3n6MLKsv1oyDK4TRGM+fv9zjypYTRRHaprEwXqVt6IhCmkJeq2XDth0UaQSWlqKFmr/ZDJzz+ngegtGassBF3ZGXJMlW1zfLaiFJaERrSuedFPKmjjyaQt6DBxfIk/BG0T0LruC6bbWH2RPyfc/ZcievEAKc0RDe5dl5VdE9TXO0Wq3GmnnkWUGefTah4Kyasdc08t9c9jjmk/0rhffCLK47meW3QsgrMvp1xEPGvU20Ztrc/ELbdlY2B8wiH7tPIW96xrz975J7yX3vGadC3vLrYsY5cs4bGRvz7Nn7SC4/vvVZPXn7CgDw3nvv72JZjaCEPMWtkQ68PIrAGau+rKmi6zra7dI9w7lAGKbqULJjer2ykCTjNaOCoxDioIQ8CpEZ9xm/00VxI1pTzsij93mV15D5eM0gSKFp2t6jKDZhdiNGeZaf2/YQ1Qh5UcHJRcnMMvsdQ/k1PmbWi9bUiBXbnQ7yPQAAIABJREFU7aWH1zQtv2OpFG1evPgAQgh88ulHtY+hNh8PAKIoRNtYfCRqGzqiiGbBHShTJlgSoUjK+M9ul16jy31guSNPFmXoNAmYpglN08gLeYwx6PrmzhdDN8DY5m6bu0A67+QVpm3o0EDXkffgQem4y+ZceVlwiQcPHh7sPJlDoxKbVryPxWRfTKGRbV1HXpqyRhtmDUM68rYQ8oqCTI1g6sgrv1tkJB6V5i6JPPcU2fLmCp4n6ox0hxiGsTLetA75vCacqLbtbDQjTz52n9eYPC+veYZ++2uDMdnzsBVNHLtGfvZCtvw9Iu9von7+7NlzFFmCfEFqwCbEl69wdvbgoDUAJeQpbo3snEmH42s/U0bG4MVxBs6F2jTsGCnYjSaOPCnoHZaQ1/yB6D7j+/6NGXksiuG4LpkD1Cwy7nM8vr7m8ThBp9MhEyG3iNnmC8qRJp2Oj6CmEBqwgvSs01khl2r857EjP4PLuviEEFsVje8KeXitEwDiuLkO2UW8++4zmKZViXWLePXqG+h2ezg9PdvjypYThQHaNSKMZ+hkZ+QBZeNUkYZgaekaVI68ZigdeXUz8qSQR2dGXhk/2Voh5DVfDJYxdpui6waZ13s+WlPXNLRNk+SMPKB05AFANjMnTwiBfHyFhw9VrOa+qNxWK4Q8eT8F8UYWzmV0Zh1J0rSQZwDQtp6RR+UcesORx2k68mQDbpEujzsusoTk+IxjQdd1YEsnU9UMWbPPuUts2155TZmlCUceY6V4uAuhU/4O+Tv3haxPJCvE3ibHmTx79hxAKcRtixAc6eUneP/957taViPQrSwqDgbbdsquzgMS8trtDsIwQxhm1c+K3VFFa04OF8NJl8ohCXkUOhvvM52OD5Yk1zrH8pjuBt/3y3XJ2ZuScgYnzTVLZq/ZlGecdjodBDlbKMQEBSf9Os86G6iILvcN2YEtlmX/cw7TpCPkua4LIURtTJUU8qg4fk3TxHvvPasV8oQQ+OSTj/DixQekXB1JHMOpEQscXUeSpqScmrP4fhdFGoNNHHmUGxqOGc55bWyvLHwVa8wd2SeWZVVzNmcRQiDPD1vI03RtK7fNXRCGATQAxszbwzN0so68fn8A07KQhdOO9yKNULAM5+cXDa7sfjF15C1/H/NCzspt/ty6SbRmM/OrSjRNg2maKLYQ+zmn48gzjDISXJ6KZLQmhffCLPJ8xrJ6IU8IAZZE1XlasXs0TZsOVLzN79gzm0ZrNuHIk+kBu3h99Ml5dd+pArI+ka5Ij5D3N9GMcXJyCt/vIn7z7a1/Rzp8g4JlePbsxQ5Xtn+UkKe4Nbquw3FcpMMRANqODonndRAEaRWDpxx5u8U0TbRdF+PJ4UP+eUiRT9Q2wfcN2b3HZlx5LE7gExVr6hx5o1FCvrA6KyxRFpk6HR9MiIUbzKDg6BB+nWcLkRTiyu4jUqBbFisjCl4JfhSQ3Y5xXCfk5dC0/XadruLly89gOHyDOL45V+7y8lOkWYIXLz7TwMrqYSyHVePIMye3UxEF5ul2e2BJBJZGVXS8Yv8UnFfOuxtMbheClpDXai2ewVkUHJwLEvvgZU7HZeiaQUZ8D8MArlk6gCSeoSEkOiNP13WcnZ4jD4fVbVlYnvHPzs6bWta9QybDrIzWrBx5zX9eZQ0oirKlj4uirPF6kWmaWzryCjL7RE3TYJlmFa0phTxqqULttgdN01Gk9ekGnOUQvCDdlHnoaJq29WwxwaUjb/9CXqu1nSNvn81IjLGdxY5OozX368iropFX7J3k/U0IeZqm4eXLzyB+862t99TR628CAF6+pDPiYRuUkKfYCbbjIA/LL+dDiA2T0ZpKyLs7fL+L0UTAGzEOTdMOIof4x37s7+Lxk3cwGJw2vZR7jdzIz8ZrFoQdeZ7XgaZpNxx543FKds2S2Y0uhQ78OuTrGMwV1IUQCFhBcnbiIiiJLvcJWXjhSwQZwTmZTmtgdVEsijLYtkMquvf585cAgI8XzMmTtz1/TqsLkjEGs6Y4IW/fpuC3DzzPgxAcLBrDdduk3gv3CcF5bYFrOiOPhrAksawWsuzm9VDeRmE/wDnfzpFHaN5pGAbw5gp8nqEjJBqtCZSCHZuIdwAqUU8JefujclutaCKRjj0KQp5sJAnDdOnjgiBrvOnENM2l+8E6ioLBsujsE2eZxh/SSTwAyuaAtuctjdaUIl+nQ7cp89DRtO2jNaWVrxlHno0sW1/UmkZr7tORl+9OyGvIkWdZFnRNW+nIyxp05AHAy5efRZGnSIdvtnp+/OabePToyUHUpZehTnuKneA4TtUxRtnRIXHdNpIkQxSl1c+K3eJ3exhPhqGOWYFO2zuIAtP3fd8P4pd+8X8/iPfxMVPFcMwIeZSjNXVdh+d51xx5QggEAd01S2bnalCYsVFH5XqcixlKuEAhBPnDn5y95jjKkdcE8oC12pFHK1oTWO7IoxKrKXn48DEsq4XXn96MPfn002+h3z8hN8etFPIW3yeFvH0fqNdF7l+zcNh4YfQ+wwUH6pxjmnTk3TLTaseUQt7N97W8jcJ+wDSNrdywnNNxzQRBAG/OrdkxDAREozWBUrDL4jHEJHowD4cwTYvctfuY0TQNhmmCr4jklXsaCk1IlmWh1WohCJY78sIwbbyJ2jCMg4/WBOiJdnV0u12w5GZSg4RNhLxDSm86NDgvqoSATWmyIUmmB9TNC59n6sjbb7Smoe/muqDrOjRN2/u5Q9M02La90pGXVI68ZmqlL1+WqS7R65sNo6vgLENy+Qk++OCzu17W3qFfVVccBM7MB7nJ4cXrUs6dAS4vD8dFeGj4fhfjyeEjYAV8tTFTbMC8kMcZQ5HnpEWxTse/5sgLwwwF8dltwPWue0qH03nk3ISAXd9gSmGPuiPvq1/9B/gbf+MHDz6T/VCZzpupPxjxgpH6DEiRpq67nUI81TyGYeCdd97FJ6+/de12IQQ+ff0tPHv2fkMrq4cVyxx55Z95vt+Im3WRxdA8HDZeGL3P8IN05FkLHXlybh4Fh49ltbaMv2NotZpfPwBEwRieqeNLfQ9f6pef0bZZzt6k2iBwdnYOCIE8Kl2DWTjEyenZQTRkHhOmaa525E3upxKn6HneUkdeUXAkSd5444lpWltHa1J5reeRMgdFcW/QH6BI6qM1WVw2NvR6/X0t6d5RFAU0fbtmRW3S5NhEzLxt2xACC2f6LqIJIW/beb516Pp2TUy3pdVaLeRJR15To0I8z8Ojx08QTyIyNyF+820IwSsx8JBRuzHFTpgVwg5BFJNrfPs2msyXoS8+Hhq+30XACnAhMC44fNXFqdgAKcrkcTz5M7l2O0V838doNI0NkX+nPrj7UGa2ScfdvCNP/kx9FuHnP/+d+Ft/6+8qt29DyM5BvkSQKbKc1L+PvN7JGPB5xuOEZDTIe++9j6urT5Hn0678IBgiSSK8++6z5hZWwzrRmlQL7rIYKnihhLwGEULUdrpTFfLKGVE318QYHYdPq9Xaak4MKxgJRyEABGGAjmHgiz0PX+yVn9HOpCgaRfUOlSY5PT0DgErIK+IAZ5PbFPvDNEyIVY68SbGXigO13fZq9yzAtDGpeSHPLB1KG1IcgCOPopDX6w2QJ0GtM51N5iorIe/uYIxBM7Z05E1EqmbEpfK7fFGCwCKamJFXFAz6Dq/Bhm40EulvmSbYiq1qPhHymmz2+uDlZxFffQKeL3d/zxO9/iZMyyJ5Ft0UJeQpdoIUwgzDILW5qUNGUb19G5KbL3Ms+L4PLgTigmPM6LuSFLRotWxYVqty5LEDEPI6nS7G4+nhVcZsUheYLMvCs2fP8fnPf6HppSyl3W7D0PWDFfIUzSIFuqJmzgIvCvCigG3TaUaSha66olgQZCSFvHfffQYhBF6/mcZrfjpx6L333rOGVrUYIQQKzmEcuJAHAK6rhLymWObIoxqtaRhmJdrNIm+jIAy0Wls68hgj4SjknCNJErjG9XNme/JzFNU7VJqk3x8AAFg8hhACeTyublPsj3XmuMn7qcxt87zOUiFPnpOabjwxTXPraE0K10aJpmnV2DPKjrx+vw/OcnC2uPDOkgCe1zmIOuKhwgp2C0eeFPL2vxeWDcdSoFtFljFomrbX91JRFDC2fG0XoRvNOPIM0wRbsVeV9zc5iuLly88AQiB6e3OMwzLiN9/C8/dfHsV15vD/DxQkkAWyQ3F2SEfemzchufkyx4IsLgYFR8SYEvIUG9P2PLDkupBHsWgt8f0uRqMYnAvouobh8DCEPE3T8Au/8EtNL2Mlmqah0+lgPFdQDyohT11jFPWsEvLk7ZQceYZhwHXdhUWx6QxOetfEd955FwDw9u0nePTwPQDAm7cfo9Vq4fz8osml1VJ3bJUyh77lXJG7ZjZRgtJ7974hlkVr6lLIo+XIMwxjoSNP3kZhXqhlWds58lhOwpGXpgkEcEPIcyY/xzFNIc/zOjAME3kcgGcJeMEwGCghb98YprmymCsKOsI7UL53Pv74G7X3yybHpudam6aJONrMzQGUQgb1IjC1phFg6rRjcQDDulkvzOMAA9UscKcUrKicdZsi57w30dQmm3LWdeRlGUOr1dqroF3Glu7uv6freiOvtWlaKFZcPwohYBpmow0D7777DJbVQvz6m+hcvLfWc/JojCwc4oMPfvBuF7cnlA1JsRPkBdbao4X5Nkgh7+oqamxQ57Eju8QvMwaO0k2jUGxCx+uAJWUBW/5JW8jzwblAFJVrldGaSsTeHb7fW+jIs0xTXcsVS5Hvj1pH3uR2au+jsrs9uXF7ljHkeUHymug4Lnq9Pi6vPq1uu7p6jYuLR+QSEDRNg6HrtQdXebu+w07bXWIf2IzqY4ULUTnvbkA0WrMU8m6+7ykJeZ7XQZLGqx84Q1EwZHlK4toYT+Lh3bnrnhT2kuTmtZ0Cuq6j1++DxQHyyeyqfv+k4VXdP0pH3vLrxnRGHg1xyfe7GI/LpsZFyFniTTffWZa1VbQmLwoSbl8JY6wqqMtkgSacPKsYDE4BTON65yniAKcnp/tc0r2jjH/cbg8+deTt/70lP2/rzsjLc1rxt9uzf6HMNE3kazjyTLPZ/aFpmnj+/AXiN+vPyYsmM/VevvzsXS1rr9A6TSsOFjn091AumrPFDmpFu2NBCnmvJ8XRprPwFYdHp9NBUQl59B15UrCTh9TxOEGr1VLF1R3id7sI5ooD46KM7qUYJaOgg2maMAwTPFvcgV1MbqfmavK8zrXIXsk0normNfHRo8e4Gr4GUHaHX129xqNHjxte1WJ0XUddqVTeTkHUWMTsvlvtZ5tjqSOPbLTmYkcepWhN3+8iTeONiofxZNZS00IBACTJRMibK55KYY+qIw8ABv0BWByAVUKecsvsG8u0IFaITdKRR6UG0+l0wLlAHC/ea8nGpKbTBEzT2kqUYMQceQXnVbnfJCzknZxIIW904z7BObJ4XD1GcTewYntHXpMz8mSdeRMhb5/z8YDrEbe7QAjRSBKIaVlY0N91DTZx5DXNy5efRRaOapsD5onefBPdbg9nZ+d3vLL9oIQ8xU6Q8SX6gRRSZy/uqsh+N0jh7tOJDV4JeYpN8bzOtRl5ltXa+8ZsE6SQJ2NjRqOERCHpmPD97kJHnt/tNbQixSHR9jywdPHslqnrl9Z3le/7NUIe7ejehw8fYzS6RFEwRNEYWZ7i4uJR08taiGEYpaNqAZy4I29WPFL72eYQSx15+vQxhND1VdGazZcJ5PUtScK1nxMnUshr/tooHXmOcf29MXXkbeY23Cfdbg9FFoOl0eTn5l/P+4ZpmuBslZBHy5E339Q4z2iUwLKsxsexlDPytpi/WbBKWGgaznk5n3Xys7zMUJzp67ouXLddFd27Tz+D7tPPACjjNiGEEvLumKIoKmfdpjQp5G3nyNvvZ1TTNOxYyWukQdlcc0YehebG589fAADiNebkCSGQvn2FFy8+OJrG7+Z36IqjoNWSF8vD+GDMbh4pCwOHjIzSfF0JeSpaU7EZnueBJSmEEGBJijaxAvs8UyGvLLoHQQrPU0LeLul0fESsuBaDFxZCCaaKtejMNAfMQ9X16/s9DIc3i73yNgrF6kU8fPgIQggMh29xeVU680g78mrOrfJ2CqLGKpSQ1xxcLHPkTR5DLFpT17WF4qK8jUKxQ363x5sIeROXG4Vro1zLfLSmrWvQMBX6KOL7XbA0Aksj6LoO11XnuH1jGCbEiuuGjNak4KAFbjY1zjMel7N9m76+mGvMH1xEUdCJ7ZPrly/l1JFHT8gDSleedOR1n3yA7pMPAExdekrIu1vKOW7bCTDTaM0mZ+St93nNsv3H3+q6vtM5yLwhIU/T6hNKJFxg64jWXXJ+fgHHdRG/fbXysXlwBZYlePbs+R5Wth+a/xdQHAXSkUfgzLcWsxf3pjvCjpVWqwXLNFW0pmJr2m0PvCjAGQNLUnjE30M3HXmpmo+3Y6TIEs24CIKC5pwwBT06nenczXmkwNd03NM83W4XaZojSa7P9qMu5J2dPQAAjIJLjMdX126jhn7AM/JmoTS3594hUN/LSDRasy4KSt6mac2XCXy/dNtH0SZCXjB5bvP7r3TiALfnil66pqFl6EhTmjPygHJPKzhHHlyh7XXIzTe9D1iWWTnu6pBCHxVxSe6hgmDxXisIaJyNLMtCUSyemVwH5wWE4GS+a6WoMnXklX9jK1ycTXF6ega2IFpTCnmnp2f7XtK9oigYtC3jGilEa8rY71Uwxvd+PSz3U7vb44mGhDxd17Dq/0IA0AnsD3Vdx/vPniO5XC3kxZPHKCFPoZhDXiypHVLr0HW9chEqIe/ucGwH4aTg7rpuw6tRHBpS/C2SFEWaknd1Oo4D0zQqIU92nSp2h3w9w8khtRACMVNCnmI9PK+Dos6RFycwTJPcnkAKdfMxVaNRAsPQyV4XB4MTAEAYjBCEQ9i2TXYfYFmt2uHu8nYqhbtlUIn7uo8sjdYEXSGPTyynH374Pj788H0AtBx58joSBFdrPycIhrAsi4RYkOelUGAteC1NTa/up4gUQtPRGxKi6H3ENM1qBl4dMnqTipAnk0jqhLzxmEZaSavV2jiCkrG8ei4F5tdvVkIezevK2dk58jgAn3N1ZeEIltUi25h2LGgHkpw2j4xxXFegZqzYu0PZslpgO3QrFkXeyHVmnVl/TYmMi3j27AXyaAwWL2/2it++QsfvHpXrVwl5ip0gL7BUPtTrIF2EVDZjx4jtONXfqRVHFfSRMT4szVCkGXlXp6Zp6HR8jEYJioIjimh0nR4TUrALJoWNuOAQoBeHqKBJp9NBHicLC+p5ksLzmo97mkcWNubjNYfDGL7fJbdeiW3baLc9BOEIYTjCYHBCdq2O4yCpKZYmnEPXtAMR8mgUcu8jQohVhjyCQp5erenLX36GL3/5GQBU4h6Fz6vrumi3vcrVuw6j4Aqnp2ck1i8L6ouEPEvXSAt5cl/FkhC+2ss2gmlaqx15RVm0pvB+B8rPrKZpCILFTVPl2IHm9+yW1QJj+UbXZSmcyRpS00jHrz75t29N3FZZljW2pmWcnp4DQDUnT5JHQzLX7GNG0zWIuhz5VXCZTrF/+UDubRfN9F1EUezfkec4DvJ8N5+7omAoigK2vf/mxzJac/l7hGPq0Gwa6bCLrz5e+rj06hO8/+z5UV1jaPwLKA6eQyweyDUf4toPBdsuhTzTMNXrrNgY6TQpkhRFQt+RB5SFj/E4qTpRKRxWjwn5eoaTwob8UzkfFevQ6fhlXO+C4imLYpLFym63jJZbLOT1mljS2vT7A4QzQh5VbMdFWlPcSAsB27YP4vB3CGLjsSKwxJFH9L0z68ibhZIjDyjj1sYbOPLG48uqYNw0UqgzF8SZWZpG1jkD4NpMPDUfrxlM06xm4NXBCc1sA8pCv+d51bzwWTgXCAIaaSWykXuTmV/UHHlSsJMF3amQt9gN2TRnZxMhLxxeu52FI5yf04xePyZ0TcdKu1UNcv5bE0KedNdtEq25b0eebTvIsnQnDVtSEHSc/ZsgdF1fHa0pps0DTXNx8RC6YSAdvq59TJHGyOMAT5483ePK7h4l5Cl2gnTkHSKq8HF3SEeebdPY8CoOCync5XEClmUHUUjwvA7CMEMYSiGPtovw0KiEvMlmPpj8qQRTxTpIUSwLoxv3sShCr0dPGOt26xx5Ccn1zjIYnCAMRwjCEfp9ukKe47hIag7fCedVUxJVZEcqddf6MVMWb5YXNjhfrwi1L0qhrr5kQ0XIOzs7X1vI45wjCEZVwbhp8jyHrmnV7KpZTA2kHXmzUchUY5GPHcuyIFbEyYmigGnREfKAck++KFozjjNwLkicjaQYt4mYzgpqQl75GstrtT0RWagKeXIG3qyQJ3iBLB6r+Xh7QNf1rYUmIZp05JV15nUdeYyJ6jn7wrYdCMF3MkNQCnnNOPI0rDJtivKB+1jOSkzTxMXFQ6SjN7WPSSb3PX58XEIerW99xcGy766HXSC/x9RMkbtDFr9sFaup2AJZlMzG48nP9IW8dtvDp59m1QFWFVZ3i4zsiSabefnnIbw3FM3T7fYBAHkYwR30r92XhVF1PyVs24HjOLi6moqPQghcXUV4+ZLeemfpdrsYB1cQQlSCJEVs20ZS58jjHI5HW8j7B//g5zEajdDvD5peimIJVIQxSd0sFErRmkBZ/I2iAHmerYy0C8IhhOBkisKM5bAWuPEAwNKAPN/dTJ1dMyveOY4S8ppgLUceK2ASq8O4bhvRXHwiAMRxXt3fNHLkR85yrPsNX0XlEonWrHfk0YzWdBwHba+DLBpVt+XRGBCCjIv6mNF0HWLbhqLKqd+kI289kawoOHR9v0KedM/leXprh3STjrxlMfFUefL4HXzyf/9x7ey+dFS69R4/frLvpd0pypGn2AnyAnuIrghKcRTHhm2XX0Czs/IUinWRQnA2LgfYOk7zB79VeJ6HMEwRhtnk58O7JlJG0zQ4to14ZkYeQKMooKCPFJPy8Lq7rchyFFlOVmzqdnu4upquOY5zZBkj78hrtztVFy/lpgbHcZDWFDeSQsAmXsR2HBcPHlw0vYx7jYbl7jaKlELeomjN6f0UkO/t0ejtyscOh2+uPadpGGML3XgAYBKP1pydba72WM1gmhZ4USx10fCigEXEISZxXbcS7WaJIlmgbv47VZ4x83x999q0wE6jrlE58iY/y1mccnYeRc5Oz6858uTfz85oNF8cM3bLBt+yeaTIyuc14UaVLsCiWG+PVRR872lx8oyTpvGKR64mSaNrv3PfrNr6acDWEa13wePHT1DkKVh8s3kEANLhGwxOTkl87+wSJeQpdsKTJ0/x/d//Q/jxH/+pppeyMSpa8+6QX/aWcuQptsCyLBiGiSyQQh6Ng9My2m0PWcYq9wyF+Jhjw3VcxJOiu/zz2DZnirtBRmvmc9GaeRRN7qfpcOv1etccefLv8v+HKp7Xnvk73Wuh47hIWAG+4GCaCKFi5RSrWUPzoiKMSeoceVKQpLLei4tHAICrYX10kuTqipaQB0iR9/CY/feXjZmK/SLP0WKJK08wRq6W4ThuJdrNMnXkNf+dKs+UUpxbBymcUTlzSMFOzqvSNQ0tXact5J2dg8048qQ7Tzny7h7XdVFs6daUz2uiqUPXdWiatna0ZhNCXmcyYz1Obo5u2JRk8js6DcxtXzd6lY6MBzx69BgAkI0XR7DnwSUePXy8zyXtBSXkKXaCZVn40R/9O9UH6ZBQjry7Q8aWUjtgKA4Hx3EOTsgDgI8/Lg8mqot597jtNpLJZj6ZbNbVNUaxDqZpou15yMLw2u1S2KPryOtfc+TJv/d6NIVHyawjmbIjz/M8CADpgnjNqOCk1644AAh1Ls+iadrCuX3UljsYnMA0LVwNX6987NXwNQaDk2tuMsXtoTIT7L4hz9Gc1btoOCvQIhL1KKlz5MUxHUeeXMNmjjwp5NE4j6ZpAgCYTe+1DdpC3unpGVgag08E1DwcwXFdNSJhD7iuC55t5wKXQl5T733DMEgLeb5fnh/jOFzxyNXI3+H7+xfygNV9aUR6vCpkE0AWDW/cJzhHHo3JzE3eJUrIU9x79n2hv0/I4roqsiu2xXHcSsij0MG5CnkQefMmhG3b6vpyBzhue+rIKzhc2yHjHFDQp98b3HDkZUH5M9UZY91uD0GQVIfY4bBcrzw4UmVWAKMcMyzXGc65HoQQiFihhDzFSjRo9BSwFei6DiHEjQ5seZ2hsn/RdR0PHjyo3HbLGI7e4OLi4R5Wdb9QQl4zyPMzXzIbShQFuXO247hI0/xG4V2KezSEvMn4hmx90SvLaTnykuR6tCYAOLpeCXwUOT09BQDkEydeHo1weqJiNfeB49zCkZeWM2qb2hdsKuTte0aeFN2SZAdCXhKi1bJpNyQR2u+22224bvtaZK8kj8cQgishT6E4RvZ9ob9PyE5C9RortsVxnGqzIOcZUEau8e3b8CCEx0PEdV3EE+dMzLl6nRUb0e8PkAfzQl558KIaVdnt9iAEMBqVTryrqxiaRl/Ie+ed9/DDP/xj+Nt/+ydwcnLa9HJqkUJdNFckyIQAE4J0LKiCBpq+eN4cMI0qotZwYhgGhAA4py3kAWW85nC0XMgrCobR6KqK4lTsDouY4+u+IF/3ZUIeZwW5fx8ZxZpl152EaZpP7m9+vVKMyzackafrBpk0pzRNYOratfheWwdpIW8wmAh5cQAAKOKA9P7wmHBdFyzdXshr0omq6/qGjrz9yhytlg3LshDvQMhLkqiRWE1gvWhNbc3H7ZPz8weLhbxqBqcS8hSKo4PSQfXYsCy50aV1sVccDrNdj1SiTJYhRaXLy+gg1nuIOI6LeDLwOik4HBVfqtiAfn+ALAivHULyIITvd8kUZ+aRAqOM1BwOY3heh+x6JaZp4gd/8Ifxvd/7A+REjFmkUBex60X7TyFSAAAgAElEQVQCKewpR55iFYZhQiyIZgXKaB+AXpS/PP/MF8coCnkPHz5CHIfV7JhFDEdvIQTHw4dKyNsVjx8/BdDMrB4F0GqtjtakOCNPNvLm+XUBUv5MQXgsz2gasg1ErzRN0G63yexn0jSBPdcsbWsa0oSykHcCYOqUyeOguk1xt3Q6PjhjKLaI18zjGJ2Goh4B6chbr55YCnn73W9pmgbf7+4kWjOKgsZGPQghoK8I19RAr7J7dnZeuXxnycPjncFJ60ShUDQApYPqsSE38sSaNhQHxGzXJumIgQlSeORcwLaVU+wusG0b2aQwmgpxEE5NBR36/X55kE1TmDJaKQgxIBqrCUyFvOFwKuRRdQ8eInXRmlLIU448xSoMw4AoFrtmRCWM0Tp2H5aQV85gv7x6jUcP3134mKur19ceS4clhyDiB6Sf+7n/deJyVHGlTTB15C2fkUdBGJtFCotZdv2amGUFNE0jcW0xDAOu6yDNNhHyYniEGnuSJIFjXC+627qOcRLXPKN5XNdFy7bBojFYEkIIroS8PeH75bkhjyIYrc3OECyK0Xvw5C6WtRamaa7lyONcgHPRyDWm1+sjGAe3/j1xHODxk2a+c4XgK2fgaZpWNahRod8fgCURBJ9rHkkCWFbrKGdwKkee4t5DYTN5rMjuYyqda4rDQ4p3hmEexGd11oWnIh/vhlbLRs45uBDI+DTCR6FYh16vFOxknCYA5GGEXq/f1JJW0utdd+RdXcXodumu99Coi9YMJ3FmypGnWIVhGLWFDXk7tT1MnZDHGD3hUbrsrq4+rX3M5dVrmKZJKqbNMAzUmQgKIWAQc2nO0263CQqj94d1ZuQVjFXOPSrIdS9y5FmWRaYu0G57SNP1Ra80jdEm1NiTpglsbV7Io+3I0zQNg/4J8ngMFpWihxLy9oM8S8zPCV+H8pzUXAPhujPyeIP7rV6vjyge3+p3CCEQxUFjZ1IhxAo/XunI48SakGRzK0uvv7eLJILf7ZL5ztklSshT3Ht0XX0M7gr12ipuS6vVuvYndWbdYcopdjdUsze4QCrEwbw3FDTo98vDUTaZkyeEQBaE6BN25LluG6ZpzjjyksZiV46RVqsF0zAQzgt5KlpTsSamYVQFpHmkU4+ekFeKSHleJ+TRWa/nddDp+LicuO4WcXX1Gg8ePCS1bsMwwcTi9wUDvbhVBS3k/na5Iy8n6Mgr1zMv5GVZQSoG1PM8JBu417IsIeXQz7IMrRtCno4s324O2r7o9/so0ghsMk+MciPdMSHFjjzczLHJGQNLs8rR1wS6blR7k2U0uX/pdnuIorB2L7gOSRKBc95Y6sq6Qh61GXmVkDcXv86SEP0jvb6oKrvi3qPrdA58x8b0S5TWxV5xOEhH3qGINaY5dQ4qp9jdIN8TGRfIOFevs2IjZMFAdqSyOIHgvBL4KFLOXvAxHidgrEAUpfB9JeTtCk3T4LW9yoEnmUZrdppYluKAMAyzNlqzyQ7xZVTfpdl1kSBNGSzLJNeM9+jR4yo+cxFXw0/JucdM00TBxcKiVyGUkKdYzqpoTcE5BBfkhDz5vp4X8hgrSL3n2+0O0mx9USNJY1KNPVmawNavl91buoYsoy3k+X6vFPIm7hnVmLYfpNiRbejIk8Jfk/9O6zry5GOaqO/2en0IwZGkmzseJVE0rn5XE3DOVwt5GshFa06FvOszCos0OtpRFLR26ApFA+j68VltqUCtaKE4PKSAZxLq4FyFXDO1g/WxIIuPKefICn4QsxMVdPC8DgzDrKI1paBHvSPY80ohLwhSAOXQesXu8Dqdm448VsDQ9WuRyQrFImzbBs8XF9vl7dRc+rIJJk1vCnkUv1cvLh5hOHq7sNs9TkIkSYyHD2nNcjMMEwLAIomXCUEqvlRBj2m05uJrSzG5tlCL1lw2f5NSbaDT6SBJ1iu6c14gTWNSe680TdGaa7ho6ToKzsGWuDibptvtgqUJWByg1bLJfTceK5Zlod32kIfh6gfPIM9LTSaXmKa5kSOviYYBKRhF0fZz8qI4uPa79o0QYuWMPB0aeE3SQFPI16uYuZ4LIcCS6GgbX5WQp7j3aJr6GNwV0zxiJZYqtkMeYg8p21qu+VBchIeGLD7GnKMQgmTBUUEXTdPQ7fUqAU8eUOXsPKr4vo/RKMFoVM4+oVRMOgY8r4NwTiAICo522zuo7x9FM9i2s0TIyyePofVdVS/k5eTWCpRCHucFxuOrG/cNr95Uj6GEZZXFxILfdOQx5chTrKCK1qy7tkzEGmqNg8uFPDrved/vVlF2q5CCH6WicJamaOk3Z+QBQJalTSxpLWTRPRm9RofQ63kf6PcHyMabCnlB9dymMAwTbMmsUIl8TJNCXhzfRsgLJ7+rmc/FutGa1MLWHMeBpmko8ul8UM5yCMFJxSHvEqVgKO491KJjjglZ/FKChmJbTHMi5DW8jk1Q7/u7RQql0aTrTr3Oik0Z9AfIJwKejJihHK0JlMLdeJxiPC4PKb6vhLxd4nV8hMX1k2lUFEd7AFTsltKRVwp2p599gdPPvqjuK7IchmGQE20qd3uaX7u9dOTR+169uCjddlfDm/Ga8jb5GCpI0YItiNZkQpB7TyhosSpaU95OraFNvu+Lue/UohAwDDp1F7mPWseVF08K7JT2XlmeLYzWBEq3HlXka5iN3qJL6PW8DwwGJ9X5Z12yIISmaY0ml2zqyGuiYUCKb/JasQ1xHEDT9MYi/YUAtFVVN43ejDxd1+E4LoqZBgY+EfUoxSHvEjrfpArFnpGbCNVpfXc8e/YC3/VdH+L7v/+Hml6K4kA5xCKH3NtQ65A9FmSBUc6vsg4odlVBg263hzwqZz7kYQTDNOG67YZXtZxOx0cYJri6iqqfFbvD8zxEc92+YcHhqddZsQaOM3XknXzwHCcfPK/u43mOFkGHm3TdJcmiaE16UWfn5w+gaRqGwzc37rsavkG77ZG7Lsr9Srag6JVzTlIwVdDBNMtZlbVCXhWtSet9JMW6RY68JmZX1SHddXGyuvAuH0PFkSeEQJZlC6M1AdqOPFlYF1w1S+2bwWCALAg3EmKycQi/22s0FvcQojU9rwNN0ytX3TbEcQjf9xszmqzjyNNBT8gDgLbnXXPkSVHvWIW8w6uQKhQ74id+4iv4b//t/8RgcNL0Uo6WdruNn/qp/6XpZSgOGOnIOyRkc4ASmO4G+Z6IirLorl5nxab4fhd5FJf5+VEMv+OTb+rxvA6EAD75ZFz9rNgd7baHjHPknMOaHKAjLtA/0gOgYre0WjZYli28r8hz2MQcMwCq5oUour7uMMzQ7Z41saSlWJaFk5OzhY684fANOTceMBVY8rloTSGEmvGrWAur1QLPF0fKTR151IQ86chbFK1JZ89eCXlrFN6njjwaQl5RFBAAzLm9qzX5mfKMvNnGOepNdMdGvz8ALwqwOIHVdtd6ThYEOGswVhNYX8jLcxmtuX/RUdd1+L5/u2jNKGhsPh4ACMGhrcjN1KBBgNaMPADw2h6iYNrAUFSOvOO8xihHnuLe8vTpu/h7f+9nSA1dVigU15HzRQ6RQxQhD4EqWpMrR55iO7rdLgTnKJIUeRQ3emhaF3kQ+fTTAJZlqvf9jpEdm9FM4TFkxztbQbFbXNctrykLZlkVaQbHXa9gtk9c14WmAWF43bkRRRnZ4uqDBxcYjS6v3SaEwHD0Fg8eXDS0qnqkUJfNzeBiQkCAngCjoEfLaoGzfOF9VB150k0yL+QxRm9GHgBEaxTeoyiApmlkmqjY5D1hzUVrmpOf85q5ihSYLawfq1uGKnLOXbZBvCYLokbn4wFlTWUdIU9ec5qqwfh+91ZCXpKEjTcLrIrW1EDUkddug7PZaM2ySY3qfva2KCFPoVAoFGShdOBbF7m5OcRY0EOgEvJUtKZiS+QhKY9isChubKj4JsiDyKefBkd7KGmSeSGvEAJJUagik2It5PuEJcmN+1iSokOk+DuLnCkShtcdeUGQkhWwz87OMQ6urt2WJBHyPMPZ2YOGVlWPFFjSOUdeNvlZOfIUq2jZdiXYzXOYjjw6DdS+3y2j8KLxysdG0Ridjk9m/dJxN+/IMytH3mLxlwKOM21scQk2uRwzvV4pyOXh6rmQACA4RxZSEPJMMLbYmTyLdOQ1VRvodDpI0pv7wHVJ0rjRZoG1BDqCM/IAwLYdiJnrnhTyHIdeVPwuUEKeQqFQKMhCaSj6pjQR63AfkLMH44a77hSHy6yQl0dx492P6yA7mF+/Hh9tTEiTyNdUCnny+qJea8U6yMJLkdycS1QkKRkXxzztdvuaIy/LGBgr4Lo0hbzz8wfgnKMopsLGaPS2uo8acg5hNifkpZWQR0uAUdDDbtlrzMijJQjLs9u8g6YoBBkhDCibGbrdLqJotYMmjAL0ev09rGo98rwsWJtz5plDiNacnf81K+op7h75Hl7XkZfHCYQQ6PWaTS4xTRNZtlrIk2JfU83UntdBmq4nks4jhECaxmQbqSoESI6jcBwHBZs2pnEmhbzjvMYcboVUoVAoFEcPpaHom3KIbsJDQMatykK7KoQpNkUKd9k4QJHn6HToC3nShScEyBbZD5l5R15UCXnqtVasRhZe6hx5VAsz7XbnmiNPinpU1yvFurOzx3jx/PMAgNH4cnIbPSGvLlpT/qz2L4pV2La9MLIXAIqJ+0AKxlQ4FEceUAobazny4jH6fTpCXuXIuxGtKe+n68ibRV0D94vrurCs1tqOvHwi+EknX1OU0ZrrOPJkk29TQp6HJIm3cqxlWSmaNtn4pWmrJuQBAjSFPNt2wPMc8n+Asxy6rh9tQtZx/l8pFAqF4iigduBbBxnncKwbh6aRBYKEN7tZVxwuskidXI2u/UyZ2ThNFUW0e6aOvGLypxLyFOsjCy9szpHHWYEiz8k68jyvg9FoWP0cBOX6qb7vz87OAQBt18Pz978DADAaXcKyLJIRyauiNW37OCOfFLuj1WpBjA7NkVee3YqC48MP369uLwpOrkGz1+vjL97+v0sfI4RARMyRVxetaWj0Z+TNQu29e+xomoZev7+2Iy+bCH5Nv/c3jdZsKq3H8zrgvABjGSxrs/d2ksTV72iW5VKeWCn1NYNtOxCCYyI1grMMLdshKTruAuXIUygUCgVZDlHI+9Ef/Tt4/vwlHjy4aHopR4lhGNB1XUVrKram1bJhGAbSYVnAPgQhb7bjXhV/d8+8I09Fayo2oRLy4uuOPOnQa74ws5hOx8d4PF3zaFT+3ff9ppa0FNdtw3VdBOGM+BgOMRicXotro8I0WvO6Mymd/EzNSaWgR6tlly6DBfA8h6Zp5Bra5HoY4/jyl5/hy19+BqB0y1Cba93v9xFGwVIHTZrGKArWuCtpFs5LwcLAnJA3+VneTx3lyNs/vW4PLIrXemw+eVzz0ZoWOBc3XL7zTIW8Zq6J8iwhRblNSFMp5DV3Ji0deauFL22Nx+wbxyn3U/JazlkO+4gbBWh96ysUCoVCMYMszBySoPf5z38Bn//8F5pexlFjGgaSotnNuuJw0TQNrtuuHHmHEFWp6zosy0Ke50rIuwMMw0DLspBMnDLxpNB+rLMVFLvFtm2YllUVvSTyZ6rCmO/7CIIUnHPoul6Jep0OzfUCwGBwgiAYVT8HwRAPH9FsnJIzfecdedMZecdbZFLsBtt2UNTMOytyhpZtk3McyIa7LLu+7jxn5Jrv+v0TcF4gTkK03cUNF2FYXm8GA0pCXrlHmf+nlz9vE+23Tx4/fopvfesj0t81x0qn44N98u21HsuiGIZhNL4XlmM18ryoZnAuQgp58rt338jmvyy7GbO+inTynNkElv2jYbUjb/IwYlT7KSnkFTncI26WUtUvhUKhUJDl9PQMT5++ix/4gf+56aUoCGGaJmI56F0JeYotaHsego9fATgMRx5Qdi7nea46mO8I23aQTLp95Z9NFy8Uh4GmafD97hIhr9lu9jo6HR9CCARBim7XrRx5lIurg8Ep/vIbfwmgLFYH4QiDwXc0vKrF6LqOlmVVDjyJcuQp1sVxbBRZtvC+IqPb2GNZFrLsuissywq0WtSEvFKcC8NRvZA3maEnH0sBKdTNSxp65chb7lxqmp/7ua9hOBzi4uJh00u5d/i+jzwq57itagLI4xhex2+8WUA6efO8gOPUX0OmQl4z1xnHkUJeuuKRN8kqIa+5c4eua1h15eAC0DW6CQgQHIBROvLax7vHovcvoFAoFArFBNdt4x/9o/8Nf+WvfL7ppSgIYZpW1S9GrbtXcRh4MzOgDiU+UYrWqvh7N7iOU83eTFShXbEh3QVCHjsARx4wjdQcjxM4jkMu/m6Wk5MTBOEIQgikaQzGcgwGJ00vqxa7ZS+ZkaeuL4rl2LYLzgqIBcIMzzI4Dl0hTxbVJRQdedJlJ113i5D39ft0rjNTR951gUWvHHm0hbx228OjR4+bXsa9pNPxwYuiNrJ3FhYl8Ak09kiH3XxzwDx5zqBpzSU5SREuzTd35GV5eu13NIFhGOArzLxcCJJJWdKRJ5scRJGT/X7cBUrIUygUCoVCcVBYMy485chTbMPsQelQXFcyKUkVf+8Gx21Xs/HigsNutUgeVhU06XZ7KOZm5OVRBE3TSM/IA6ZC3miUoNOhuVbJYDCJwosDBFXkHZ0C+zy2bS+YkaeiNRXrIef+FNnNonuR53AIO/Jmhbyi4OBcNBZ5V8fUkTeufUwQjmDbdqMF9nmkkDdfzNWq+2lHayqao9PpAsCNxqNFsDiG73fvekkrmXXkLSPPC5im1ZiDcBqtuY0jLwWgNeqyNgwTq6ZrFgAMk97ZaOrImwh5jB11go0S8hQKhUKhUBwUxox4pwrtim2QBVTDNA/uPUStEHYsOK5bzchLCn7UnZyK3eP7PrIwunZbHiXwOp1q3i81pJAnZ+ONRgnZGFBJr9cHAERxgCgKrt1GkZbtLHDkcRiGoRqRFCuRRd1F8Zo8o+s4aLVa12bkpSmb3E7Lkddq2Wi3PQThsPYxYTgmFasJTF0n83qFPrmBuiNP0RyyWYclq8UmlqQkGpGkkDc/d3OeLCsaTRSQjaHbzMjLsgSOYze6XzQMA8WK+ZqFEDAMensX+V0pr328yMhGT+8CmqcKhUKhUCgUihpkNI9hGGQLpArayOLXIbrbqEVTHQuO4yKWQh4XcGw63fcK+vh+F5yxa86ZPIrQJSyMzTvyxuOU9Hw8YDpvMI5DxHEp5HW7zTsG6rAdp4rSlKRcwFYNGYo1kIXhRY68Usij+T1l2w6SZLrmNM2r26nR7w+WOvLCaITB4HSPK1Io7g45F3yVkCeEAEsSEnPEZfPlKiEvTVmj5zrLsmAYJvItHXlyxl5TGIYBtsLMWxCN1px35HGWH+QZf11U9UuhUCgUCsVBIbvYTYIbScVhIItJ9gFFm8moGOXiuBvKCLzyAJhyDpuo00FBExk/NRtXxaKEtMjUarVg2/aMI49GjNYy5OsZRQGiOICuG2i3my801tFqtZCJm468Y458UuwOGedYpDcdeSzNSMU9zlIKedOiu/w7RQfhYDBAFC0W8oQQCMMROUdeXXSggFh6v0Ihvy+LFUIez3MILkgIeVKQkc7eOtKUNR5Z7brudtGaedr49dwwzDUcedeTkagg3yNCCEAABcsbfy/cJUrIUygUCoVCcVDIDSTFjjDFYVBFax7Qe0hGKSkh725otaazrDIh0DriTk7F7lks5NEXxnzfx2gUI01zZBmD79N25LXbHnTdmDjyQvi+T9qZ32rZN4W8/5+9O4+Sq6zzP/6pvbqqek+AhMWAKIkgAlEWQZCj4zIOKDA6uAsEFBXjhsryQ8Gjh6MwCEhAZg6bHkTBART3YVBQUDAGjZF9MSQIhJClu2u7Vff+/qh6blev6b2ep+v9Oiena+vqp9O3bt16Pvf7fdi/YILMmkvV0tCJ4SAIVCmV1NbW3AqOsQwP8goFmyvyetQ/sD08xmpULpfkeWV1d9sV5BlBIC3vymp5Vza8XkOQh9GZIK9SHL/9o6nYs+FEGfOZrXGfMhobgrx0Oq2yN5WKvGLTg7xEIq7KDtbX9PzAys4w5u+ebO9W++KXS0FARR4AAIAtTP97Ag1MVSplqiHcm+xgu58dyWRSnu/LDwKVfTV9MgBu6eiotXys5Gvr5PnVqrxi0fogL5fr0LZtxbC9pu2tNaPRqNrb25Uv9NeDPLv/f5PJ1Ig18ko+QR4mxgR1lWEVeWbNPBP02WZ4a01z2caJ1e7ublWrFRVL+RH3DQxsl1QL+2xiKu4CSQd2ZnVgZ3bU+4HhEomEEonkDltr2hTkmf1GeZQWw42a3VpTqrVDnkpFnuc1v8I6kUiGJzSOpRwEVnYUiEajSiSSSmTald15D0l2vt/MFII8AADgFLPIctzCxZbhBnM2oUtzHZ2dXZLU1IXc57NwosAPVJrnZ3Ji5g2vyKsUasGYCfhslcvl1N9fUl9fqX7d7iBPkrLZnEqlgkqlvPUVhLWWvUMnxsq+b2VlEuxjgrzhFXmm1aatFXnp9FhBnn3bvWmbaUK7RgP57UMeY4vGIK9REN4/p8OBYzKZjCqliQZ5zd/HmODIhYq8TCYz5Yq8Zq95mkymVA2CcdtreoGsDPIkKZlKKah48r3a+2NqHq91TpAHAACcEq6RR2USpsjGtiA78s53nqA3vemtWrx4t2YPZV4yH/7LfsAaVpi0VCqleCIRBnnmq+3BWDZbC/L6+0v1680/+35HstmsSuWCSuWiFdUC40kmkypX/SFt+8oWT4TBLolEQvF4YkRFnplkb3YFx1hqVSkVVau1ELtQMMGjfePt7KyFdPl8/4j7BgZqa+d1dXXN6Zh2ZEdBnovdJjB3MpnsDtfIq1pVkZdWNBpRPj9yrdBGAwPlpp/c0NaWUbk8ftvS4YIgUKnU/OMZc1xSHqe9Zsn3mx6WjiWdTsuvePIrXnh9viLIAwAATjHrmtm42DLckEi4t+3ssstiHX30vxBgzxLzwbTk+ypX7f2gCjtFIhFls7lwgt2sP5PL5Zo5rB3KZnMqFMravr0WPGYydo9Xqk0slkpFlUoFK6oFxpNIJBVIqjQGeX6gRIIgDxOTyWZHrGdl9jPZrJ2vVxPYmYn3fN6r327f69WEdCa0a5TP9ykejzd9gn04sy7o8HX9/Pp1m9cNRfNls1lViuOHYqZiz4aTeyKRiNraMhoYGDt8DIJA+Xyp6ePNZrMqlQo7fmCDSsWT71ebPnYT5HnjtNf0fDtba0pSOpVWtVKWXzEVefP3cxx7eAAA4BTTWpMgD1NFGIbhkslalWbZr7WVoYUpJiuXzYUT7pWC3RPthpk4ev757UOu2yyTyWpgYLuq1ap1E+zDjXaGu61rzMBOuWwubNVrmP2MrfsX0yLOBHmFQlnxeMzK99V0uk2JRFL5/MggbyDfp46OLuvWnItGayc0VocVzpjr5oRHYDSZTHZEu97hKsWSotGoNe1wa+/7Y4ePpVKtArjZJ/dkMll5XlnV6vhtQBuZ4K/ZxzPmuGT4ur6Nyr5v7YlI6XRaQaXcUJFnXwX4TCHIAwAATonHY/Wv9k0IwA3mrPCdd96lySOBLcz+pFA/E9XGCUfYLZfLqVoYWpFn60S7Ycb33HPblUwmndjuM5lsWInS7ImvHQmDvIbKGY/WvZiEXC43og2eCfZs3b+YirxCwQu/2jqpGolE1NnZpYFRgrx8vs+6tpqSFIvVpnH94RV5MhV5BHkYWyaTDat6x1ItldTWlrEmxK4FeWOP2dzX7GMC8/NLk2ivaUuQZ0Lb0hgVeV79REdbK93S6bbaGnn1ijxaawIAAFjCVFOZyjxgsnbbbQ995COn6dhj/73ZQ4ElTIBRqBLkYWqyQyryikokktYHNmbi6IUX+pyoxpOktrZ0w2U7wwFjsFVVbYI9CAKVq/ae0Q77NLbsNSrFkuLxhLX7l8Egz7TWbP7aVePp6uoatSIvX+hXZ6d9QZ4J6oZPt/thRR7TvBhbJpNRtVyWX62O+ZhKoaSMRccEO6rIM/c1uyLPHEeVihNvr1msB3nNPgYzJ1sUx6jIK9YDPluPu2pr5JXlewR5AAAAVjEBnqnMAyYrGo1q771f2fQPfLDH8CCPil9MVjabk1coKggCVQpFqybBxmImZLZtK1hbMTNc4/qVtq9laQK7cn0CrBJIgWRtAAP7ZEdrrVnfv9hSLTOcCe3M2niFgmft5K8ktbd3qFAcGHKb7/sqFAbU0dHZpFGNzayBVx1WkVcNqMjDjpm1e4dX+jaqFIvKWVTx297eru3bx65yM+v85nLtczWkUWWztZ8/fH8ynmIxX//e5v5/m5OkitXRK/LM7bYeK6bTaVW9sqrhGnkEeQAAAFYwaz+wBgSAmUJrTUxXJpNR4PvyK1VVy2UnThRonJCxdXJmuMazrG0/43r4Gnle4A+5HdiRXC5Xq5xpCG0qhaLamzxhPR7zujQVeTa31pTqQV4hP+S2UrmgIAjU3t7RpFGNzXz+GR7kUZGHiTCB0XjtNavFUtODpUYdHV0aGCipXB597bktW2qv32ZX0HZ01PYXhcLEg7x8ob/+vc09acDsowtjtNY0FXm27stTqbT8akW+V1IymQpPeJiP5u9vBgAA5qXBAM/OM5EBuMe07KUiD1NlJjeq5bKqpbLaLJ3saNQ4IWNzxUyjxrOsbT/jOmytWZ9wN4EerTUxUblcbWLYb6iSqBSKVgZMRjghXF8jL58vWzv5K9WCvCDw5TdMYJuJeBv/nweDvKG3m2CPpQcwnjDIK4xd4VYpFMPKPRuYgG7r1tFbVm7dWlAsFm16+GjCOBPOTUSh0K9MJht+DmkWcww4VkWe+Xxk67GieY+pFPqtPzacLvbwAADAKVTiAZhpI1tr8jEJk2MmN6qlsqplz+o1oYxUKqVIpFbsY/NEe6NUKjXqZRuZ/YpZI6zpIawAACAASURBVM8jyMMktbfXKu/aF++sdHdtkriSL4S32yiRSCgejw2pyLN18lcarKLx/WpYxWGCPHOfTczxyfCKvEoY5PE5CWMzYZc3RpDnV6uqlMtND8UadXbW9n1bt+a1004j931bt+bV0dHZ9CqseDyutraMCpMI8vL5AStOGEgkkopGo2FF3vKuoe3hC5ZX5JlK8EpxQB2Wd2uYLj6hAgAAp7D2A4CZZia+TMUMQR4ma0hFXrls9cS1EY1GlUqlVSwWrW9TaTSGYLYHYmZ8piLPfE0mqfjFxJjArq23W90vX6LA9+UVi01fC2pH0uk2FQqegiBQsWh/RZ4kVf2q4qqf1FMP8mz8fzYVd5UxgjyOXzAes02PVZFnbrcryBu/Im/Llrw6O7vnckhj6ujoVD4/8daahUK/ehf0zOKIJiYSiagtlQ4r8g7sHBrkFa2vyKsdw3qFAaU7d27yaGYXrTUBAIBTONMUwEwzE2Pl+hmn7GcwWaYCr1qqt9a0dLJjOFM1lkzaXd1mNK5faftallTkYbpMa01TPWMm2W2uyJNqk6qFQlnlclW+H1h9ooAJLIKG1prFUm3NLRuDPBPUDQ/yTKtNgjyMJ51OKxaPyyuMHop5+drtNlWjdnZ2KRKRNm+uVbodcsieOuSQPcP7X3opr64uO4K8zs4u5fN9E378QL6v6Wv7GW2ZTNiZZLhCfQdja7cJ007T99w5MW2q2MMDAACnMMEOYKaFFXm0psIUDbb1KcmvVp1Zo8O0onIlXGoM72x/nZr/U3OCgNm/2B5Awh5tbW2KxWKq1CfXTaBnAj5b1Sp9KyoWvfp1e08UyGZrlSeNa+SVSgUlEkkrX6vRaFQRSZVha+RVWCMPExCJRNSeaw/3KcNV6gGfDe0ejXg8rs7OLr34Yi3IO/jgJeF95XJFW7fm1dPT26TRDdXT06unnnpCQRAoEomM+1jPK6tUKqinp/kVeVItpMsXRg8hC9WqkomEtScKNIZ3rhx/TxUVeQAAwCmD/e+DcR8HABM12FrTVOTZ+UEV9koma6GNmQRzpcLNFHWY8dsuHh+cWN/RJFmzmRDABHheff9iYzgAO0UiEWVz7Q0VeWaS3b5KsUapVFqlUkWlUiW8bqtUKq1oNCY/qIa3lUpFZTJ2Vp5EIhHFYvEx18izdaId9mjv6Agr74Yzt9sU5ElST8+CMMhr9NJLtTaWvb0L5npIo+ru7pHnlVUuj966tFH/wLbwe2zQlsmo4I8+v5L3fas7TTS+x9j8fjMTCPIAAIBTBtfIs3sCD4A7zBnuZo082yt9YB8ThJkJd1eCMROGuTJel0KwWCymWDSqCq01MQ3tufYwwPPypiLP9iAvpWLRc6IiLxKJKJPJDKnIK5byVq0RNlw8Hgv3KwZBHiaqo71zzIo8s4+xbfvv7V2gF18cufacCfdsCfJMdV1//7YdPra/f3v9e+yoJmxrGzvIK1R9a9tqSkPfY2x+v5kJBHkAAMApgxV5ADAzame4x1QiyMMUmXDGrGHlykRCUJ/8dSXIc+21mUgk5JmKvIAgD5PX3t6hSn5oRZ79QZ47FXlSLbQY2lqzqFzOriCjUSI+uF8xKj6tezExHeNV5A3UQmzb3mt7exdoYKCkfL485PZNm+wK8kx1Xd/ABII8yyryMpmM8tXqqPcVqoHaMtk5HtHENR7DunI8O1XMhAEAAKfEYhy+AJh50Wg0rJixbQID9otGo4rHE+HkmCthjanIc6WKw/Z2msMl4olwv2K+JpNMtGPicrn28AQBL19UKp22PqypVeS5sUaeVJvADoLBIK9cLlpdfRJPJMIKPMMLK/Ls3jbQfB0dnap6nqplb8R9Xj6vzs6uJoxqfCao27Rp6Bpumzb1q62tzZrXa3d3rbquv28iFXnblEqlrBl7Ot2mUtWXH4ysyisEgTXjHE3jMbft7zfTxUwYAABwimuTeADcEIvF5AV+eBmYrGQyGU64u3JGsKnIY13I2UFFHqYrl8vJKxQU+L4qhYJyWbur8aTaNl4uV1QuV8LrNmtraxtSkVcul6xeDyqRGDxBwDDXXTkpA83T0VEL6ryB/Ij7KgMFy4O8oevkbdrUpwULFjZjSKNKpVJqb+9QX9+WHT52+/YtWrBgJ2vmNsw+rzRKe81i1Vc6be8+sbFjkyvH31NFkAcAAACg5UWjUVWCwcvAZMUTCVVLtbZPtlfMDEd4PTsSyeSIijwm2jEZZq2qarmsSrGkrMUtH41kMqlKpRpW5Nk+sZpOt4UVeUEQyPNKVk9aJ0apyKsEgeKxGMcv2KHOzk5Jowd53kA+vN8mPT0LFImMXpHX22tPkCdJCxYs1Pb+rTt8XF//VqtCSLPPK1T9EfcVq77a2uxukWzYfuLIdLGHBwAAjhp9MWYAmIpYdDDIINTAVCTiCVVKpdplR4I811pruiaRTKrcUJGXiMetOfsebsjU1yWqFEuqlkrKWrxOkWGCu/7+0pDrtqpV5NVfp15ZQRAonbZ30jqeSI5cIy8I2I9jQjo6akFdeViQV/UqqpTLam+3L8iLx+Pq6uoeUpFXLle0dWveyiCvr2/8IK9SqWhgYLs1a/tJgxV5RX9okFcNApV9X+m0va01G7ly/D1V7OUBAICjmAgDMHMaz2LnjHZMRTwRlxxbp2iwtaY74fUJJ5xo9SR7o0RiaEXefJ9gwszLZhuCvGIpDPZsZioiTJBne4VErRKl9jote6WG2+yUTCZVGKW1ZsKR9x00lwnyvPzQIM9U6NlYkSdJvb0L9cILm8LrL75YC/UWLLAnDJNqQV6pVFCpVFAqNfp+pK9esedCRV6xft2dirz5vR/kEyoAAACAltcYZESj7oQasEfj5IErQd7ee+8jSWprc+NMa0k68MDXatmy/Zo9jAlJJgcrZ8qBb32gAfuEFXmForxiKQz2bGYq8Pr6SopGI9afKGAmsP3AlxcGefZOWicSCXnDbvOCwPrKR9ghHo8rk83K6x8e5A1IkpVr5Em10GvTpv7wBCRTnWdbRZ4Zz/Zx1skza+jZGOQVhwV5hXqF3lihpG3m+3EWFXkAAAAAWl40RmtNTE9jNYQrZwQfc8xxOvzwI61q7zSfxOMJefXCGc8PlEi6sV3AHia4K/f1K/B9ZTL2h+5m/5fPl5VIJK1vJ5tKpSRJgR/I82rrnNpckZcYpbVm2Q+USM/vCWzMnM6OLvUPa61pWm2aij3bdHf3qlTylM+Xlc2mtHlzLcjr6elp8siGMuHc9u1btHDB4lEfs317LcizKYQ0+8HSsGpfcz2dTs35mKbClePvqaIiDwAAOCUIP7iyRh6AmWPWyIuI1pqYmqEVeW6cM5tIJLTzzrs0exjzViKRCCfcKwGtNTF5JlAq16tnXKiebQzyXNgXplK16rsg8MMgz0xq2yiRSIQtew0vCJSgIg8T1NXVpcrA6K017Q3yuiVJL700EH5ta2uzLnTv7u5RNBodtyJve98Wtbd3WLWfMRW95WBoRV65XpGXTNoz1vHEYva/50wHn1ABAAAAtLxorPbRiBAPU9U4Ye3C5DVmXzI5uEZe2Q+UcGQiDPYwk6um7Z1NE79jMa2FaxV59ofXYUVeEDgS5CVHBnk+QR4mrqOjMwzuDG8gr0wma+1rtqurVnn30kv58GtXV3czhzSqWCym7u7esH3maPr6tljVVlMaDOrK/shq39r9buxf5ntXFT6lAgAAp+Ry7ZKkRYt2a/JIAMwnprUmQR6mypwFHInYvyYU5kY8npBXP5vdC+Z/yyfMvEgkolQqHba9M9VjNhvaWtP+bd6sh+cHvioVE+TZ+/9cO0FgaNUMa+RhMjo6ulQpl6WGFq3eQF4dnXZW40kjK/I2bx5Qd7ddbTWNhQsXjlmRFwSBtvdt0cKFO83xqMaXSCQU0XhBnr0nNzSa78fffEoFAABOednL9tSKFZ/QG97wxmYPBcA8Eo0S5GF6TBVejGo81NVa4Pm1Sh9aa2KKUqlUWD1jQiebme28WPTC6jybmQlqdyryEqoGgaoNIUw5qFXqARNh2mcGDYGwly+o09K2mlKtrXA6ndbmzQMKgkBbtuTDKj3bLFiwk/r6tskfFrhLUqlUULlcsq4iLxKJKJlMhq00jcHWmm7sXwjyAAAALBKJRLRkyZ60LQMwo0yAR5CHqTLvS/F5vj4HJi6RSCiQVJVZI8+NiTDYJZVOq1Io1i5bXClmNIZ3LgR5g601fXkVT5Ld1SfhWlYNlTNl32f/ggnr6OiQJPnVanhbZaCg9nZ7gzypNu7t2wsqFj2Vy5Xw97BNb+8C+X5V+UL/iPv6+reGj7FNIpFQydGKvL322luSG++R08EnDAAAAAAtL0ZrTUzTYEXe/D4bGBNnKpMqfiDPZ+1ETE2qYQLVharOxu3chfE2VuRVvLLi8YTVxwImsCv7vtrq6/uWfVprYuLCirxqrdrKr1blFYvWBmNGNtuuvr5t6u8vhddt1NPTK0nq79824j5zW0+PnUFexS8Pua1Sr/xNJOw+fjnxxA/qpZc2K5vNNnsos8ruvwIAAAAAzAEzaReLEsJgaswaeVTkwTDVSF4QyAt8J0IN2Me1YKxxjC6M1wRgge/Lq5StbqspjV6R5/k+QR4mzAR2prVmJV+o3253RV42m9Pzz7+gvr5akJfL5Zo8otGZIK+vb+uI+2q3Raxc3y8Wi6taLQ25zQR5McuPbTOZrDKZ+R3iSbTWBAAAAIDBirx5vrYCZg9r5GE4E2J4fqCKzxp5mJrGIM+Fqs6hrTXtH28sFlM0GlVHZ68qFc/6FnImsPPqE+xmvTxaa2KiUqm0EomkUh3t6t3n5fLqrXvb2+2uyMvlcurvL6m/vzbebNbOIK+zs0uxWEz9/aMEef3b1NnZaeW+MR6Lqzq0s6aqgRQRHUtsYd9WM8dWrVqlSy+9NLz+yCOPjPnYfD6v6667Tr/85S+1fv16SdIee+yht7zlLTrppJOUyWRmfbwAAAAAZl60XokXi/FBFVNDe1YMF7bWDAJ5vu/EemGwT+OEr+1VEdLw4NGNbT6dblMu265CYUCplN2B2GBrzWDIVyryMBnZXE5KJ9Xzir209elnJEm5nJ2tKo1sNqdCoaxt22oVhLZW5EWjUXV19ahv1NaaW61cH0+qtYavBkOTvGoQKBaLKRKJNGlUaGT/EcAseuyxx7Rq1aoJPfaf//ynPvShD4UBXjqdVhAEevjhh/Xwww/rtttu0w033KBFixbN5pABAAAAzAITwtBaE1Nl49nVaC4TYhR9X4HcCTVgF9cq8mqTvlIQuDFeqbZOXqVSked5Srelmz2ccQ221qy1RfTqXwnyMBnt7e3aUq/Eq9S/2hqMGaaAZtOmfklSW5u9BTXd3d3a8tK2ESdf5PP92uNluzdpVOOLxRNhK02jUg/yYIeWPVWwWq3qrLPOkud5OvDAA3f42NNPP13r16/XggULdPXVV+vBBx/UX/7yF1199dXq7e3V+vXrdfrpp8uvv4ECAAAAcIepoqK1JqYqnKwJxn8cWocJMYrV2jxBIuFGqAG7mH1LNBp1oioiEomE274rQV4qmVSlUlalWrY+EBu+Rl6p/pXWmpiM9ly7qoXaemgmyLO1VaVh2t729RUVjUas3r90dnYrn+8bclu1WlW+0K/Ozq4mjWp88XhclRGtNQnybNKyQd4111yjtWvX6thjj9Xhhx8+7mNvu+02PfTQQ5KkSy+9VEcddZQikYgikYiOOuooXXbZZZKkhx56SLfddtusjx0AAADAzAor8viwiiky244D8+yYI2aSsVA/4ZeKPEyFCe8iDrXtNdu6K9t8MpWS53mqVCoOrJFXG1+5Xjlj1sqzvSUo7JLLtYdr41UKBaXTbVYHY9JgiN3fX1IikbT6xIauri4VinkFDWd3FQr99fu6mzWscUUi0SHjlSQ/oGW8TVryL/Hkk0/q8ssvV3d3t84666wdPv7WW2+VJB188MF67WtfO+L+1772teHt5rEAAAAA3GHWyKMiD1NFCIzhzBp5xWptYsz2SVLYKQzyLJ60Hs7sD13Z5pPJlCpVT5WKOxV5pqVmmYo8TEE2m1OlWFQQBKoUS8pks80e0g6Zbbyvr2j969RU3fnVanjbQL1Cz9aKvGg0ouF9Bn1J0UhLxkdWarm/hO/7Ovvss1UqlXT22Werp6dn3McXi0WtXr1aknTkkUeO+bijjjpKkrR69WoVi8WZGzAAAACAWReLRetf3Zh0hH0I8jBc2FqTijxMQ6Q+iUqQN3tSqaQqXlmVimd9QGDCDBPglVkjD1PQ1tYmSaqWy6qUyuH6czYbbK1Zsn57N2Fd1R8M8vLWB3lRDVsiT0EQOFUNPt+13F/ihhtu0Jo1a3TkkUfq2GOP3eHjn3jiiXDdu1e+8pVjPs7cV61W9eSTT87MYAEAAADMCTPpaCrzgMkiyMNwJrhjjTxMh4sVeYYrQV6tIq8iz/Osb61pKn0Hg7zaV9vHDbu0tdWCu2qpLL9cVqbNhSCvtu0PDJSsr0Btb++QNLQir1AYGHKfbSKR6OgVeVH33nvmq5YK8tavX69vfetbymQyOv/88yf0Pc8//3x4eeeddx7zcbvsskt4+YUXXpj6IAEAAADMORPgmco8YLKo5sRwI9fIYxvB5IVBntyZTDVVHa5s88lkUuVyUb5ftb7SJxqNKhGPh5V4Zq0828cNu4QVeaWyqqVyGOzZrPFkO9tPnsrl2iVJfjAYjRVLBcXjcaVSdobu0Whk2Ap5UiBaa9rEjXfUGRAEgc455xwVCgWdc845Wrx48YS+b2BgILxsdnKjSafT4eX+/v5Jj6+3Nzfp7wEAAAAwM9rba8f6bW0pLVzY3uTRwEXd3bX1ZWKxKNsQJEmpVG1KrFRfI6+3t4NtA5OWTtem7iIRObP9xGK10LGrK+fEmDs7cyqXS5Kknh77X6epVEpePcAza+UtWtSjjg67xw17bNu2QJJUqQd5vb1d1m/3lcrgfHsymbB6vEGQUywWk9/QWrNYzKujvUM77WRnRV46nZQ/LMnzg0DxRMzq/+tW0jJB3o033qj7779fBxxwgD7wgQ80ezgjbN7cL3/4qwUAAADAnCgWK5KkSsXXpk19TR4NXNTfX5sErlbZhlBTKBQlSaX6RHt/f5ltA5NWLHqSalVurmw/1Xp4nc97Toy5Uhm8XC4H1o85Hk+o7JclDbbW3L69rFLJ7nHDHsVibbuplkqqlMvy/aj12/3WrYXwsu/bvz/MZLLyvMGdS7E4oLZM1tpxe54/akVe4MD/9XwRjUbGLfZqidrIjRs36qKLLlIikdBXv/pVRSexSGM2mw0vFwqFMR9XLBbDy7kc1XUAAACAS2xv0QP7sb4ihjNtBYu01sQ0mDaVwYgpVvu5ss03tqW0fe0tqd4KdNgaeWbtPGAizDZfKdVOQrK13WOjxvn8ycztN0su1z6sIq+g9nZ7K9sikciI95kgcHN91vnK/q1+Bnz9619XPp/XBz/4Qe26664aGBgY8s/zvPCx5rZyuXZmS+O6eI3r5Q333HPPhZd32mmnWfgtAAAAAMyWwSCPD6uYGhcmlTC3zH6lVJ9odyXUgG2CIV9c4so23xjeubDWXDLZ0FozCJSIx3kPwqQkk7XgrlKvHHdhu288YSriwLpt2WxWvj+4Rl6pXLB6LcJakDdUIDf+r1uFG++o07RhwwZJ0jXXXKNrrrlm3McedNBBkqTjjjtOF154oV7+8pcrGo3K9309+uijOuqoo0b9vkcffVRS7UB9r732msHRAwAAAJhtTIBhuqjIw3DRaFSxaFSlam0iLxZriSkYzDCXK/JcqXZvrGZzobItkUyqXA8Iyr7vxJhhl7AiL18L8lyoRI1GI6NetlVbW0ZBMBjklcslZTKWB3nD3mYCBYo48H/dKvi0ugPpdFrLly+XJN19991jPs7ct3z5cqXT6TkZGwAAAICZMRjCuDdRCjvEYny8xkixWIzWmmhZrpzg4GRrzfrhiucHTowZdonH44pEIvLqy0i50FqzkQvtHtva2uTXK/Kr1aoqFU/ptOVB3rDbaK1pl5Y4irz99tvHvf/yyy/Xt7/9bUnSI488MuL+4447Tg888IDuv/9+rV69Ogz2jNWrV+uBBx4IHwsAAADALVTkYbqY6MBo4vG4ivXlPAjyMDXuttZ0sSIvmbS/ui2RSKpigrwgUDJFkIfJiUQiiicSqhZra+TF4/Zv964dZzVW5JW9WuVjJtPWzCGNKxKJyB9WkhfIvf/3+YxPqxPwrne9S8uWLZMkrVy5UnfffbeCIFAQBLr77ru1cuVKSdKyZcv0zne+s5lDBQAAADAFrJGH6SIMxmhi0ZhMYy1XQg3YJahPrLrUWtNM/LqyX2ysaHOhui2RSKhs1sijIg9TFIvFVK1UJbl3ookL4VJbWy20C4JA5XItMLW5Ii8ajY54l/HlTmV1K3DrVdoksVhMV155pT70oQ9p/fr1OvXUU8P2mcViLVHfY489dOWVV3JgDgAAADhocLLRnYlS2CUScWPCGnMr1jA5yhp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\n" }, - "metadata": {} + "metadata": { + "needs_background": "light" + } } ] }, { "cell_type": "markdown", - "source": [ - "##Visualisation: TE6 of the group-averaged, PAM50 registered MGRE scans" - ], "metadata": { "id": "MVa2uPXnSaLF" - } + }, + "source": [ + "##Visualisation: TE6 of the group-averaged, PAM50 registered MGRE scans" + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 771 + }, + "id": "pF9Pv6kXTVCe", + "outputId": "08b67786-b1bc-461f-d5bd-f5fa69991ec8" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], "source": [ - "\n", - "# Signal along the spinal cord for PAM50 registered TE6\n", - "csvfile_NOSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/noshim_PAM50_sc.csv'\n", - "csvfile_staticSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/staticshim_PAM50_sc.csv'\n", - "csvfile_staticzSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/staticzshim_PAM50_sc.csv'\n", - "csvfile_rtSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/rtshim_PAM50_sc.csv'\n", - "csvfile_rtzSHIM_mutual_coreg='/content/SC_rt_shim/PAM50_means/rtzshim_PAM50_sc.csv'\n", - "\n", - "noshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_NOSHIM_mutual_coreg)\n", - "staticshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_staticSHIM_mutual_coreg)\n", - "staticzshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_staticzSHIM_mutual_coreg)\n", - "rtshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_rtSHIM_mutual_coreg)\n", - "rtzshim_coreg_alongcord=signal_extractor_for_PAM50(csvfile_rtzSHIM_mutual_coreg)\n", - "\n", "plt.clf()\n", "plt.cla()\n", "plt.close()\n", @@ -2628,40 +3421,24 @@ "#plt.rcParams[\"font.size\"] = \"20\"\n", "\n", "plt.show()" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 769 - }, - "id": "pF9Pv6kXTVCe", - "outputId": "c616b793-62fb-44cd-f4f5-2b97411b4ed4" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": {} - } ] }, { "cell_type": "markdown", - "source": [ - "##Visualisation: Distribution of the STD of compensation gradients" - ], "metadata": { "id": "Wi_Ex0bOSg66" - } + }, + "source": [ + "##Visualisation: Distribution of the STD of compensation gradients" + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vegX7xcnJbO_" + }, + "outputs": [], "source": [ "#Extracting the required data \n", "Subjectdirs=sorted(glob.glob('/content/SC_rt_shim/'+'*acdc*')) \n", @@ -2699,20 +3476,32 @@ "STD_XRIRO_reshaped=np.reshape(STD_XRIRO_for_all,np.shape(STD_XRIRO_for_all)[0]*np.shape(STD_XSTATIC_for_all)[1])\n", "STD_YRIRO_reshaped=np.reshape(STD_YRIRO_for_all,np.shape(STD_XSTATIC_for_all)[0]*np.shape(STD_XSTATIC_for_all)[1])\n", "STD_ZRIRO_reshaped=np.reshape(STD_ZRIRO_for_all,np.shape(STD_XSTATIC_for_all)[0]*np.shape(STD_XSTATIC_for_all)[1])\n" - ], - "metadata": { - "id": "vegX7xcnJbO_" - }, - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 649 + }, + "id": "sAcVYpZzpl5W", + "outputId": "d67375e8-ab99-448e-a20e-408a451abb2e" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ], "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", "plt.clf()\n", "plt.cla()\n", "plt.close()\n", @@ -2743,27 +3532,6 @@ "\n", "plt.rcParams.update({'font.size': 30})\n", "#g.despine(bottom=True, left=True)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 640 - }, - "id": "sAcVYpZzpl5W", - "outputId": "8028a09b-e50c-4aa6-c7dd-c29e1eb82423" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": {} - } ] }, { @@ -2772,10 +3540,10 @@ "metadata": { "colab": { "base_uri": "https://localhost:8080/", - "height": 632 + "height": 640 }, "id": "oycVry6mTo0Y", - "outputId": "1fcdf1be-2bae-4564-b316-7b1b64d2efe2" + "outputId": "938825cb-8116-4f7b-f344-acd196a98e38" }, "outputs": [ { @@ -2784,16 +3552,12 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {} } ], "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", "plt.clf()\n", "plt.cla()\n", "plt.close()\n", @@ -2820,5 +3584,22 @@ "plt.rcParams.update({'font.size': 30})\n" ] } - ] + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "provenance": [], + "toc_visible": true, + "include_colab_link": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 0 } \ No newline at end of file