From 797bd2bc5689b19f6a1abb14746b59d765f14b7e Mon Sep 17 00:00:00 2001 From: Moni Doerig <82578141+MoniDoerig@users.noreply.github.com> Date: Thu, 13 Jun 2024 10:07:18 +0200 Subject: [PATCH] added spm fmri analysis --- .../first_and_second_level_spm.ipynb | 4674 +++++++++++++++++ 1 file changed, 4674 insertions(+) create mode 100644 books/functional_imaging/first_and_second_level_spm.ipynb diff --git a/books/functional_imaging/first_and_second_level_spm.ipynb b/books/functional_imaging/first_and_second_level_spm.ipynb new file mode 100644 index 000000000..21a431c5d --- /dev/null +++ b/books/functional_imaging/first_and_second_level_spm.ipynb @@ -0,0 +1,4674 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "\"Open \n", + "\"Open " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# First and Second Level fMRI Analysis with SPM\n", + "\n", + "__Author:__ Monika Doerig\n", + "\n", + "__Citation:__ \n", + "\n", + "- Wakeman, DG and Henson, RN (2021). Multisubject, multimodal face processing. OpenNeuro. [Dataset] doi: [10.18112/openneuro.ds000117.v1.0.5](https://openneuro.org/datasets/ds000117/versions/1.0.5)\n", + "\n", + "- Wakeman, D.G. & Henson, R.N. (2015). A multi-subject, multi-modal human neuroimaging dataset. Sci. Data 2:150001 doi: 10.1038/sdata.2015.1\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "__Useful resources:__ \n", + "\n", + "- SPM Tutorial on event-related fMRI: https://www.fil.ion.ucl.ac.uk/spm/docs/tutorials/fmri/event/\n", + "\n", + "- SPM Manual, group face fMRI: https://www.fil.ion.ucl.ac.uk/spm/docs/manual/faces_group/face_group/#introduction\n", + "\n", + "- SPM Wikibooks, group analysis: https://en.wikibooks.org/wiki/SPM/Group_Analysis / https://www.fil.ion.ucl.ac.uk/spm/docs/wikibooks/Group_Analysis/\n", + "\n", + "- Nipype Documentation: fMRI: Famous vs non-famous faces in SPM: https://nipype.readthedocs.io/en/latest/users/examples/fmri_spm_face.html" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup Neurodesk" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [ + "%%capture\n", + "import os\n", + "import sys\n", + "IN_COLAB = 'google.colab' in sys.modules\n", + "\n", + "if IN_COLAB:\n", + " os.environ[\"LD_PRELOAD\"] = \"\";\n", + " os.environ[\"APPTAINER_BINDPATH\"] = \"/content,/tmp,/cvmfs\"\n", + " os.environ[\"MPLCONFIGDIR\"] = \"/content/matplotlib-mpldir\"\n", + " os.environ[\"LMOD_CMD\"] = \"/usr/share/lmod/lmod/libexec/lmod\"\n", + "\n", + " !curl -J -O https://raw.githubusercontent.com/NeuroDesk/neurocommand/main/googlecolab_setup.sh\n", + " !chmod +x googlecolab_setup.sh\n", + " !./googlecolab_setup.sh\n", + "\n", + " os.environ[\"MODULEPATH\"] = ':'.join(map(str, list(map(lambda x: os.path.join(os.path.abspath('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/'), x),os.listdir('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/')))))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vendor_id\t: GenuineIntel\n", + "model name\t: Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz\n" + ] + } + ], + "source": [ + "# Output CPU information:\n", + "!cat /proc/cpuinfo | grep 'vendor' | uniq\n", + "!cat /proc/cpuinfo | grep 'model name' | uniq" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "The fMRI dataset used for this example is part of a multi-subject, multi-modal (sMRI, fMRI, MEG, EEG) neuroimaging dataset on face processing. It contains data in BIDS format on sixteen healthy volunteers. The data was recoreded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory. \n", + "\n", + "The facial stimuli consisted of two groups of 300 greyscale photos, half of which were of famous people and half of which were of non-famous people (unknown to the participants). \n", + "Each scrambled face was created either from the famous face or the non-famous face of the same stimulus number. Additionally, each image was presented twice to the participants. The second presentation occurred either immediately after the first presentation (Immediate Repeats) or after 5–15 intervening stimuli (Delayed Repeats), with 50% of each type of repeat.\n", + "To ensure that each stimulus received equal attention, participants were instructed to use their left or right index finger to press one of two keys (assignment counter-balanced across participants). They determined the symmetry of each image by pressing a key based on whether they perceived it to be 'more' or 'less symmetric' than average.\n", + "\n", + "In the original paper (Wakeman & Henson, 2015), the repetition manipulation was not distinguished, meaning that initial and repeated presentations were treated identically without considering the timing of the repeats.\n", + "\n", + "To illustrate the setup of a 3x2 factorial design analysis (familiar vs. unfamiliar vs. scrambled faces) x (1st vs. 2nd presentation) in an SPM Nipype workflow, the event files will be adapted accordingly. Each stimulus type will be labeled as either the first or second presentation. However, for simplicity, no distinction is made between immediate and delayed repetitions, resulting in 6 stimulus types (conditions): Familiar-Rep1 (F1), Familiar-Rep2 (F2), Unfamiliar-Rep1 (U1), Unfamiliar-Rep2 (U2), Scrambled-Rep1 (S1), and Scrambled-Rep2 (S2)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__Examples of a familiar, unfamiliar and scrambled face:__" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[0maction summary:\n", + " get (notneeded: 6)\n", + "\u001b[0m" + ] + } + ], + "source": [ + "PATTERN_STIMULI = \"stimuli/func/*001.bmp\"\n", + "\n", + "!datalad install https://github.com/OpenNeuroDatasets/ds000117.git\n", + "!cd ds000117 && datalad get $PATTERN_STIMULI" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "from matplotlib.image import imread\n", + "\n", + "# Load the .bmp images\n", + "familiar = imread('ds000117/stimuli/func/f001.bmp')\n", + "unfamiliar = imread('ds000117/stimuli/func/u001.bmp')\n", + "scrambled = imread('ds000117/stimuli/func/s001.bmp')\n", + "\n", + "# Create a Matplotlib figure with subplots\n", + "fig, axes = plt.subplots(1, 3, figsize=(12, 4))\n", + "\n", + "# Plot each image on a subplot\n", + "axes[0].imshow(familiar, cmap='gray')\n", + "axes[0].set_title('Familiar face')\n", + "axes[0].axis('off')\n", + "\n", + "axes[1].imshow(unfamiliar, cmap='gray')\n", + "axes[1].set_title('Unfamiliar face')\n", + "axes[1].axis('off')\n", + "\n", + "axes[2].imshow(scrambled, cmap='gray')\n", + "axes[2].set_title('Scrambled face')\n", + "axes[2].axis('off')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Download Data and install Python modules" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[0maction summary:\n", + " get (notneeded: 9)\n", + "\u001b[0m" + ] + } + ], + "source": [ + "# get func data of the mri session of 9 individuals \n", + "PATTERN = \"sub-0*/ses-mri/func\"\n", + "\n", + "!datalad install https://github.com/OpenNeuroDatasets/ds000117.git\n", + "!cd ds000117 && datalad get $PATTERN" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[0maction summary:\n", + " get (notneeded: 81)\n", + "\u001b[0m" + ] + } + ], + "source": [ + "# get preprocessed normalized func images of 9 individuals \n", + "PATTERN_PREP = \"sub-0*/ses-mri/func/*space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz\"\n", + "\n", + "!datalad install https://github.com/OpenNeuroDerivatives/ds000117-fmriprep.git\n", + "!cd ds000117-fmriprep && datalad get $PATTERN_PREP" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: nilearn in /opt/conda/lib/python3.11/site-packages (0.10.4)\n", + "Requirement already satisfied: pandas in /opt/conda/lib/python3.11/site-packages (2.2.2)\n", + "Requirement already satisfied: joblib>=1.0.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (1.4.2)\n", + "Requirement already satisfied: lxml in /opt/conda/lib/python3.11/site-packages (from nilearn) (5.2.1)\n", + "Requirement already satisfied: nibabel>=4.0.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (5.2.1)\n", + "Requirement already satisfied: numpy>=1.19.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (1.26.4)\n", + "Requirement already satisfied: packaging in /opt/conda/lib/python3.11/site-packages (from nilearn) (23.2)\n", + "Requirement already satisfied: requests>=2.25.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (2.31.0)\n", + "Requirement already satisfied: scikit-learn>=1.0.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (1.5.0)\n", + "Requirement already satisfied: scipy>=1.8.0 in /opt/conda/lib/python3.11/site-packages (from nilearn) (1.13.0)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /opt/conda/lib/python3.11/site-packages (from pandas) (2.8.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /opt/conda/lib/python3.11/site-packages (from pandas) (2023.3)\n", + "Requirement already satisfied: tzdata>=2022.7 in /opt/conda/lib/python3.11/site-packages (from pandas) (2024.1)\n", + "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.11/site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n", + "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.11/site-packages (from requests>=2.25.0->nilearn) (3.3.0)\n", + "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.11/site-packages (from requests>=2.25.0->nilearn) (3.4)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.11/site-packages (from requests>=2.25.0->nilearn) (2.0.7)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.11/site-packages (from requests>=2.25.0->nilearn) (2024.2.2)\n", + "Requirement already satisfied: threadpoolctl>=3.1.0 in /opt/conda/lib/python3.11/site-packages (from scikit-learn>=1.0.0->nilearn) (3.5.0)\n" + ] + } + ], + "source": [ + "# Installations\n", + "!pip install nilearn pandas" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load SPM and import Python and Nipype modules" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['spm12/r7771']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import lmod\n", + "await lmod.purge(force=True)\n", + "await lmod.load('spm12/r7771')\n", + "await lmod.list()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from nilearn import plotting\n", + "import matplotlib.pyplot as plt\n", + "import json\n", + "import os\n", + "from os.path import join as opj\n", + "from scipy.io import loadmat" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "import nipype.algorithms.modelgen as model\n", + "from nipype.interfaces import spm\n", + "from nipype.interfaces.io import DataSink, DataGrabber\n", + "from nipype.interfaces.utility import IdentityInterface, Function\n", + "from nipype import Node, Workflow, MapNode\n", + "from nipype.algorithms.misc import Gunzip" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.8.6\n" + ] + } + ], + "source": [ + "import nipype\n", + "NIPYPE_VERSION = nipype.__version__\n", + "print(NIPYPE_VERSION)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Contrasts need to be defined manually and wont be computed automatically when they are defined in Level1Design using the factor_info parameter\n" + ] + } + ], + "source": [ + "if NIPYPE_VERSION <= '1.8.6':\n", + " print('Contrasts need to be defined manually and wont be computed automatically when they are defined in Level1Design using the factor_info parameter')\n", + " \n", + "# starting in nipype version 1.8.7., when factor_info parameter is used in Level1design T and F contrasts (ess*, con*, spmF* and spmT* images) \n", + "# are created automatically by in EstimateModel by SPM" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1. First Level Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Prepare Data Input" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "#base directories\n", + "data_base_dir = os.getcwd() \n", + "experiment_dir = opj(data_base_dir, 'spm_analysis/') #where to store the working and datasink directories\n", + "\n", + "#list of subject identifiers and runs\n", + "sub_list = ['01', '02', '03', '04', '05', '06', '07', '08', '09']\n", + "\n", + "#only take run 1 and 2 for computational reasons\n", + "run_id = [1,2]" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Repetition Time: 2.0\n" + ] + } + ], + "source": [ + "\n", + "#TR of functional images\n", + "with open(opj(data_base_dir,'ds000117/task-facerecognition_bold.json'), 'rt') as fp:\n", + " task_info = json.load(fp)\n", + "TR = float(task_info['RepetitionTime'])\n", + "print('Repetition Time:', TR)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "source": [ + "#### Start the workflow" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "wf = Workflow(name='level1_spm', base_dir=experiment_dir)\n", + "wf.config[\"execution\"][\"crashfile_format\"] = \"txt\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Input stream" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "infosource = Node(IdentityInterface(fields=[\"subject_id\"]),\n", + " name=\"infosource\")\n", + "infosource.iterables = [(\"subject_id\", sub_list)]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "###### SPM12 can accept NIfTI files as input, but only if they are not compressed ('unzipped'). Use Gunzip node to unzip the files, before feeding them it to the model specification node." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "gunzip_func = MapNode(Gunzip(), name='gunzip_func', iterfield='in_file')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "datagrabber = Node(interface=DataGrabber(\n", + " infields=[\"subject_id\",\"run_id\"], outfields=[\"func\", \"events\"]\n", + " ), name=\"datagrabber\"\n", + ")\n", + "\n", + "# Specify task names and return a sorted filelist to ensure to match files to correct runs\n", + "datagrabber.inputs.run_id = run_id\n", + "datagrabber.inputs.sort_filelist = True\n", + "datagrabber.inputs.template = \"*\"\n", + "datagrabber.inputs.base_directory = data_base_dir\n", + "\n", + "# Define arguments fill the wildcards in the below paths \n", + "datagrabber.inputs.template_args = dict(\n", + " func=[[\"subject_id\",\"subject_id\",\"run_id\"]],\n", + " events=[[\"subject_id\",\"subject_id\", \"run_id\"]]\n", + ")\n", + "\n", + "datagrabber.inputs.field_template = dict(\n", + " func= \"ds000117-fmriprep/sub-%s/ses-mri/func/sub-%s_ses-mri_task-facerecognition_run-%d_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz\",\n", + " events=\"ds000117/sub-%s/ses-mri/func/sub-%s_ses-mri_task-facerecognition_run-0%d_events.tsv\", \n", + ")\n", + "\n", + "wf.connect([\n", + " (infosource, datagrabber, [(\"subject_id\", \"subject_id\")])])\n", + "\n", + "wf.connect([(datagrabber, gunzip_func, [('func', 'in_file')])])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### First-level GLM\n", + "The subsequent task involves obtaining information such as stimuli type, onset, duration, and other regressors for integration into the GLM model. To accomplish this, a helper function needs to be created, which will be referred to as subjectinfo.\n", + "\n", + "A TSV file for each run looks like this: " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "onset\tduration\tcircle_duration\tstim_type\ttrigger\tbutton_pushed\tresponse_time\tstim_file\n", + "0\t.908\t.534\tFAMOUS\t5\t4\t2.158\tfunc/f013.bmp\n", + "3.273\t.962\t.586\tFAMOUS\t6\t4\t1.233\tfunc/f013.bmp\n", + "6.647\t.825\t.546\tUNFAMILIAR\t13\t4\t1.183\tfunc/u014.bmp\n", + "9.838\t.968\t.597\tUNFAMILIAR\t14\t4\t.930\tfunc/u014.bmp\n", + "12.978\t.904\t.415\tUNFAMILIAR\t13\t7\t1.068\tfunc/u016.bmp\n", + "16.219\t.859\t.558\tUNFAMILIAR\t14\t7\t1.207\tfunc/u016.bmp\n", + "19.443\t.804\t.585\tUNFAMILIAR\t13\t4\t1.286\tfunc/u010.bmp\n", + "22.55\t.879\t.526\tUNFAMILIAR\t14\t4\t1.008\tfunc/u010.bmp\n", + "25.606\t.866\t.416\tSCRAMBLED\t17\t7\t1.929\tfunc/s002.bmp\n", + "28.697\t.884\t.461\tSCRAMBLED\t18\t4\t1.300\tfunc/s002.bmp\n", + "31.319\t20.000\t20.000\tn/a\t999\t20000\t20.000\tfunc/i999.bmp\n", + "51.898\t.974\t.543\tFAMOUS\t5\t7\t2.477\tfunc/f004.bmp\n", + "55.173\t.925\t.534\tSCRAMBLED\t17\t7\t1.372\tfunc/s008.bmp\n", + "58.313\t.985\t.439\tUNFAMILIAR\t13\t4\t1.431\tfunc/u012.bmp\n", + "61.587\t.862\t.533\tFAMOUS\t5\t4\t1.086\tfunc/f012.bmp\n", + "64.677\t.869\t.461\tFAMOUS\t6\t4\t1.018\tfunc/f012.bmp\n", + "67.75\t.804\t.446\tSCRAMBLED\t17\t7\t1.267\tfunc/s007.bmp\n", + "70.774\t.873\t.445\tSCRAMBLED\t17\t7\t1.211\tfunc/s011.bmp\n", + "73.881\t.983\t.466\tFAMOUS\t7\t7\t1.203\tfunc/f004.bmp\n", + "77.105\t.998\t.468\tSCRAMBLED\t17\t7\t1.240\tfunc/s015.bmp\n", + "80.445\t.833\t.583\tSCRAMBLED\t19\t7\t1.379\tfunc/s008.bmp\n", + "83.469\t.940\t.434\tFAMOUS\t5\t7\t1.637\tfunc/f006.bmp\n", + "86.676\t.813\t.488\tFAMOUS\t6\t7\t1.209\tfunc/f006.bmp\n", + "89.833\t.994\t.570\tUNFAMILIAR\t15\t4\t1.444\tfunc/u012.bmp\n", + "93.19\t.997\t.594\tFAMOUS\t5\t7\t1.352\tfunc/f009.bmp\n", + "96.448\t.869\t.491\tFAMOUS\t5\t7\t1.012\tfunc/f005.bmp\n", + "99.655\t.821\t.571\tSCRAMBLED\t19\t7\t1.483\tfunc/s007.bmp\n", + "102.695\t.933\t.437\tFAMOUS\t5\t7\t1.228\tfunc/f002.bmp\n", + "105.869\t.818\t.481\tFAMOUS\t6\t7\t1.109\tfunc/f002.bmp\n", + "108.942\t.925\t.487\tSCRAMBLED\t19\t7\t1.205\tfunc/s011.bmp\n", + "111.615\t20.000\t20.000\tn/a\t999\t20000\t20.000\tfunc/i999.bmp\n", + "132.144\t.980\t.498\tFAMOUS\t5\t7\t.898\tfunc/f014.bmp\n", + "135.351\t.833\t.458\tSCRAMBLED\t19\tn/a\t0\tfunc/s015.bmp\n", + "138.541\t.999\t.591\tSCRAMBLED\t17\t4\t1.940\tfunc/s004.bmp\n", + "141.849\t.868\t.548\tFAMOUS\t5\t4\t1.366\tfunc/f001.bmp\n", + "144.906\t.832\t.421\tFAMOUS\t6\t4\t1.433\tfunc/f001.bmp\n", + "147.946\t.897\t.445\tFAMOUS\t7\t7\t.767\tfunc/f009.bmp\n", + "151.186\t.971\t.575\tUNFAMILIAR\t13\t7\t1.604\tfunc/u013.bmp\n", + "154.393\t.978\t.458\tFAMOUS\t7\t7\t1.137\tfunc/f005.bmp\n", + "157.701\t.984\t.564\tFAMOUS\t5\t7\t1.248\tfunc/f015.bmp\n", + "161.008\t.900\t.556\tUNFAMILIAR\t13\t4\t1.239\tfunc/u011.bmp\n", + "164.265\t.828\t.594\tUNFAMILIAR\t14\t4\t1.269\tfunc/u011.bmp\n", + "167.306\t.830\t.447\tFAMOUS\t7\t7\t1.116\tfunc/f014.bmp\n", + "170.312\t.992\t.415\tFAMOUS\t5\t7\t1.806\tfunc/f003.bmp\n", + "173.519\t.942\t.442\tFAMOUS\t6\t7\t1.361\tfunc/f003.bmp\n", + "176.777\t.874\t.539\tSCRAMBLED\t19\t4\t1.363\tfunc/s004.bmp\n", + "179.984\t.845\t.559\tSCRAMBLED\t17\t4\t1.131\tfunc/s012.bmp\n", + "183.058\t.981\t.467\tSCRAMBLED\t17\t7\t.872\tfunc/s001.bmp\n", + "186.365\t.880\t.559\tSCRAMBLED\t18\t7\t1.000\tfunc/s001.bmp\n", + "189.422\t.858\t.414\tUNFAMILIAR\t15\t4\t1.095\tfunc/u013.bmp\n", + "192.027\t20.000\t20.000\tn/a\t999\t20000\t20.000\tfunc/i999.bmp\n", + "212.623\t.873\t.554\tSCRAMBLED\t17\t4\t1.718\tfunc/s006.bmp\n", + "215.83\t.863\t.558\tFAMOUS\t7\t7\t1.115\tfunc/f015.bmp\n", + "218.937\t.984\t.479\tSCRAMBLED\t17\t7\t1.449\tfunc/s014.bmp\n", + "222.178\t.873\t.487\tSCRAMBLED\t18\t7\t.834\tfunc/s014.bmp\n", + "225.452\t.912\t.536\tUNFAMILIAR\t13\t4\t1.099\tfunc/u002.bmp\n", + "228.559\t.952\t.419\tUNFAMILIAR\t14\t4\t.915\tfunc/u002.bmp\n", + "231.733\t.891\t.465\tUNFAMILIAR\t13\t4\t1.023\tfunc/u004.bmp\n", + "234.89\t.947\t.496\tUNFAMILIAR\t14\t4\t.953\tfunc/u004.bmp\n", + "238.164\t.824\t.560\tSCRAMBLED\t19\t7\t1.068\tfunc/s012.bmp\n", + "241.187\t.922\t.425\tFAMOUS\t5\t4\t1.154\tfunc/f011.bmp\n", + "244.478\t.941\t.593\tSCRAMBLED\t17\t7\t1.283\tfunc/s005.bmp\n", + "247.668\t.857\t.482\tSCRAMBLED\t18\t7\t1.023\tfunc/s005.bmp\n", + "250.825\t.813\t.524\tSCRAMBLED\t19\t7\t1.329\tfunc/s006.bmp\n", + "253.849\t.921\t.450\tFAMOUS\t5\t7\t1.221\tfunc/f007.bmp\n", + "257.072\t.903\t.528\tSCRAMBLED\t17\t7\t.788\tfunc/s016.bmp\n", + "260.163\t.969\t.419\tFAMOUS\t5\t4\t1.369\tfunc/f010.bmp\n", + "263.403\t.892\t.516\tFAMOUS\t6\t4\t1.183\tfunc/f010.bmp\n", + "266.627\t.950\t.562\tSCRAMBLED\t17\t7\t1.326\tfunc/s009.bmp\n", + "269.901\t.935\t.561\tSCRAMBLED\t18\t7\t1.010\tfunc/s009.bmp\n", + "273.025\t.896\t.434\tFAMOUS\t7\t7\t1.431\tfunc/f011.bmp\n", + "275.664\t20.000\t20.000\tn/a\t999\t20000\t20.000\tfunc/i999.bmp\n", + "296.109\t.895\t.410\tSCRAMBLED\t17\t4\t1.541\tfunc/s010.bmp\n", + "299.233\t.908\t.452\tSCRAMBLED\t18\t4\t1.010\tfunc/s010.bmp\n", + "302.373\t.866\t.457\tUNFAMILIAR\t13\t4\t1.137\tfunc/u008.bmp\n", + "305.53\t.880\t.519\tFAMOUS\t7\t7\t1.127\tfunc/f007.bmp\n", + "308.588\t.821\t.417\tSCRAMBLED\t17\t7\t1.208\tfunc/s003.bmp\n", + "311.594\t.873\t.403\tSCRAMBLED\t18\t7\t.965\tfunc/s003.bmp\n", + "314.784\t.967\t.543\tSCRAMBLED\t19\t7\t1.126\tfunc/s016.bmp\n", + "318.008\t.913\t.495\tSCRAMBLED\t17\t4\t1.137\tfunc/s013.bmp\n", + "321.165\t.957\t.477\tUNFAMILIAR\t13\t4\t1.073\tfunc/u007.bmp\n", + "324.423\t.826\t.534\tUNFAMILIAR\t14\t4\t.934\tfunc/u007.bmp\n", + "327.479\t.998\t.457\tUNFAMILIAR\t13\t4\t1.293\tfunc/u015.bmp\n", + "330.77\t.981\t.534\tUNFAMILIAR\t13\t4\t1.075\tfunc/u009.bmp\n", + "334.011\t.920\t.491\tUNFAMILIAR\t15\t4\t1.075\tfunc/u008.bmp\n", + "337.134\t.967\t.442\tFAMOUS\t5\t7\t.754\tfunc/f008.bmp\n", + "340.425\t.946\t.552\tFAMOUS\t6\t7\t.917\tfunc/f008.bmp\n", + "343.632\t.870\t.489\tUNFAMILIAR\t13\t4\t1.286\tfunc/u003.bmp\n", + "346.839\t.990\t.552\tUNFAMILIAR\t14\t4\t1.141\tfunc/u003.bmp\n", + "350.146\t.937\t.542\tSCRAMBLED\t19\t4\t1.334\tfunc/s013.bmp\n", + "352.836\t20.000\t20.000\tn/a\t999\t20000\t20.000\tfunc/i999.bmp\n", + "373.298\t.816\t.420\tUNFAMILIAR\t13\t4\t1.415\tfunc/u001.bmp\n", + "376.455\t.837\t.577\tUNFAMILIAR\t14\t4\t1.247\tfunc/u001.bmp\n", + "379.646\t.825\t.572\tUNFAMILIAR\t13\t7\t1.292\tfunc/u006.bmp\n", + "382.786\t.995\t.540\tUNFAMILIAR\t15\t4\t1.003\tfunc/u015.bmp\n", + "385.993\t.976\t.447\tUNFAMILIAR\t13\t7\t1.536\tfunc/u005.bmp\n", + "389.3\t.906\t.558\tUNFAMILIAR\t15\t4\t1.078\tfunc/u009.bmp\n", + "392.508\t.957\t.526\tFAMOUS\t5\t7\t1.223\tfunc/f016.bmp\n", + "395.264\t.012\t0\tn/a\t999\t0\t0\tfunc/Circle.bmp\n" + ] + } + ], + "source": [ + "!cat ds000117/sub-01/ses-mri/func/sub-01_ses-mri_task-facerecognition_run-01_events.tsv" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As mentioned in the introduction, these event files will be adapted in the function 'subjectinfo' to demonstrate the setup of a 3x2 factorial design analysis. The original stimulus types (stim_types) FAMOUS, NONFAMILIAR, SCRAMBLED will be replaced with F1 (first presentation of an image of a famous face)/ F2 (second presentation of image), U1/U2 and S1/S1 due to the first or second occurance of the respective stimulus file (stim_file). In addition, stimuli of stimulus type n/a are deleted." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "# Get the subject information: to create a GLM model, Nipype needs a list of Bunch objects per run (session)\n", + "\n", + "def subjectinfo(events):\n", + "\n", + " # packages need to be imported within the function for node to work (function is executed in a standalone environment)\n", + " from nipype.interfaces.base import Bunch\n", + " import pandas as pd\n", + " from collections import OrderedDict\n", + "\n", + " trialinfo = pd.read_table(events)\n", + "\n", + " # Filter out rows where stim_type does not contain 'FAMOUS', 'UNFAMILIAR', or 'SCRAMBLED' --> n/a\n", + " trialinfo = trialinfo[trialinfo['stim_type'].isin(['FAMOUS', 'UNFAMILIAR', 'SCRAMBLED'])].reset_index(drop=True)\n", + " \n", + " # Create a dictionary to store the count of occurrences for each stim_file\n", + " stim_file_count = {}\n", + " \n", + " \n", + " # Iterate over each row in the dataframe\n", + " for index, row in trialinfo.iterrows():\n", + " # Get the stim_file value for the current row\n", + " stim_file = row['stim_file']\n", + " \n", + " # If the stim_file is not in the stim_file_count dictionary, add it with count 1\n", + " if stim_file not in stim_file_count:\n", + " stim_file_count[stim_file] = 1\n", + " else:\n", + " # Increment the count for the stim_file and update the dictionary\n", + " stim_file_count[stim_file] += 1\n", + " \n", + " # Get the count of occurrences for the current stim_file\n", + " count = stim_file_count[stim_file]\n", + " \n", + " # Determine the new stim_type based on the stim_file and its count\n", + " if 'FAMOUS' in row['stim_type']:\n", + " new_stim_type = f'F{count}'\n", + " elif 'UNFAMILIAR' in row['stim_type']:\n", + " new_stim_type = f'U{count}'\n", + " else:\n", + " # If it's not 'FAMOUS' or 'UNFAMILIAR', it must be 'SCRAMBLED'\n", + " new_stim_type = f'S{count}'\n", + " \n", + " # Update the stim_type in the dataframe\n", + " trialinfo.at[index, 'stim_type'] = new_stim_type\n", + "\n", + " \n", + " # Define the custom sorting order (instead of an alphabetic ordering F1, F2, S1, S2, U1, U2\n", + " sorting_order = OrderedDict([('F1', 1), ('F2', 2), ('U1', 3), ('U2', 4), ('S1', 5), ('S2', 6)])\n", + " \n", + " conditions = []\n", + " onsets = []\n", + " durations = []\n", + " \n", + " # Group trialinfo by 'stim_type' and iterate over groups\n", + " grouped_trials = trialinfo.groupby('stim_type')\n", + " for group_key in sorting_order.keys(): # Use keys() to iterate over keys\n", + " group_data = grouped_trials.get_group(group_key)\n", + " conditions.append(group_key)\n", + " onsets.append(group_data['onset'].tolist())\n", + " durations.append(group_data['duration'].tolist())\n", + "\n", + " subject_info = Bunch(conditions=conditions, \n", + " onsets=onsets, \n", + " durations=durations)\n", + " \n", + " return subject_info\n", + " \n", + "\n", + "\n", + "getsubjectinfo = MapNode(Function(input_names=['events'],\n", + " output_names=['subject_info'],\n", + " function=subjectinfo),\n", + " name='getsubjectinfo', iterfield=['events'])" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "wf.connect(datagrabber, 'events', getsubjectinfo, 'events')" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "modelspec = Node(model.SpecifySPMModel(concatenate_runs=True,\n", + " input_units = 'secs',\n", + " output_units = 'secs',\n", + " time_repetition= TR, \n", + " high_pass_filter_cutoff=128), #in secs, slow signal drifts with a period > 128 will be removed\n", + " name='modelspec')\n", + " \n", + "wf.connect(getsubjectinfo, 'subject_info', modelspec,'subject_info')\n", + "wf.connect(gunzip_func, 'out_file', modelspec, 'functional_runs')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### Level1Design: canonical HRF\n", + "\n", + "The design matrix will be constructed without including derivatives of the hemodynamic response function (HRF) and therefore assumes a constant delay and dispersion for the hemodynamic response." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "##### Starting in nipype version 1.8.7., when factor_info parameter is used in Level1design, T and F contrasts (ess*, con*, spmF* and spmT* images) are created automatically in EstimateModel by SPM. They need to be connected directly to a data output module" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "The following lines automatically inform SPM to create a default set of\n", + "contrats for a factorial design." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + } + ], + "source": [ + "# Level1Design - Generates an SPM design matrix\n", + "level1design = Node(spm.Level1Design(bases={'hrf':{'derivs': [0,0]}}, # no derivatives\n", + " timing_units='secs',\n", + " interscan_interval=TR, \n", + " microtime_onset=8, #The onset/time-bin in seconds for alignment\n", + " microtime_resolution=16, #Number of time-bins per scan in secs\n", + " mask_threshold=0.8,\n", + " global_intensity_normalization='none',\n", + " volterra_expansion_order=1, #do not model interactions\n", + " model_serial_correlations='AR(1)'), # serial correlations --> autoregressive AR(1) model during Classical (ReML) parameter estimation\n", + " name='level1design')\n", + "\n", + "if NIPYPE_VERSION > '1.8.6':\n", + "# Factors need to match conditions: product of levels (here 6) needs to match number of condition names --> F1, F2, U1, U2, S1, S2\n", + " level1design.inputs.factor_info = [dict(name = 'Face', levels = 3),\n", + " dict(name = 'Rep', levels = 2)]\n", + " \n", + "wf.connect(modelspec,'session_info', level1design, 'session_info')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# EstimateModel - estimate the parameters of the model \n", + "level1estimate = Node(spm.EstimateModel(estimation_method={'Classical':1}), #EstimateModel2\n", + " name='level1estimate')\n", + "\n", + "wf.connect(level1design, 'spm_mat_file', level1estimate, 'spm_mat_file')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### Specify GLM contrast for nipype<=1.8.6 \n", + "Contrasts need to be set up manually as they are not created automatically in EstimateModel when factor_info parameter is used in Level1Design.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "condition_names = ['F1', 'F2', 'U1', 'U2', 'S1', 'S2'] #The condition names must match the names listed in the subjectinfo function described above.\n", + "\n", + "cond1 = ('Positive effect of condition', 'T', condition_names, [1, 1, 1, 1, 1, 1])\n", + "\n", + "# positive effect face\n", + "face1 = ('Positive effect of Face_1', 'T', condition_names, [1, 1, -1, -1, 0, 0])\n", + "face2 = ('Positive effect of Face_2', 'T', condition_names, [0, 0, 1, 1, -1, -1])\n", + "\n", + "# rep1 > rep2\n", + "rep1 = ('Positive effect of Rep', 'T', condition_names, [1, -1, 1, -1, 1, -1])\n", + "\n", + "# positive interaction face x rep\n", + "int1 = ('Positive interaction of Face x Rep1', 'T', condition_names, [1, -1, -1, 1, 0, 0])\n", + "int2 = ('Positive interaction of Face x Rep2', 'T', condition_names, [0, 0, 1, -1, -1, 1])\n", + "\n", + "contf1 = ['Average effect condition', 'F', [cond1]]\n", + "contf2 = ['Main effect Face', 'F', [face1, face2]]\n", + "contf3 = ['Main effect Rep', 'F', [rep1]]\n", + "contf4 = ['Interaction: Face x Rep', 'F', [int1, int2]]\n", + "\n", + "contrasts = [contf1, contf2, contf3, contf4, cond1, face1, face2, rep1, int1, int2]" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# EstimateContrast - explicit contrast estimation with nipype version <= 1.8.6 with the defined contrast list\n", + "\n", + "if NIPYPE_VERSION <= '1.8.6':\n", + " level1conest = Node(spm.EstimateContrast(), \n", + " name='level1conest')\n", + " level1conest.inputs.contrasts = contrasts\n", + " \n", + " \n", + " wf.connect([(level1estimate, level1conest, [('spm_mat_file','spm_mat_file'),\n", + " ('beta_images','beta_images'),\n", + " ('residual_image','residual_image')])])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Output stream" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# save all results into one\n", + "datasink = Node(DataSink(), name='sinker')\n", + "datasink.inputs.base_directory=opj(experiment_dir, \"level1_spm_results\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "wf.connect(infosource, 'subject_id', datasink, 'container')\n", + "\n", + "if NIPYPE_VERSION <= '1.8.6':\n", + " wf.connect([(level1conest, datasink, [('spm_mat_file', '1stLevel.@spm_mat'),\n", + " ('spmT_images', '1stLevel.@T'),\n", + " ('con_images', '1stLevel.@con'),\n", + " ('spmF_images', '1stLevel.@F'),\n", + " ('ess_images', '1stLevel.@ess')]),\n", + " ])\n", + "# starting in nipype version 1.8.7., when factor_info parameter is used in Level1Design T and F contrasts (ess*, con*, spmF* and spmT* images) \n", + "# are created automatically by SPM in EstimateModel\n", + "else: \n", + " wf.connect(level1design, 'spm_mat_file', datasink, '1stLevel.@spm_mat')\n", + " wf.connect([(level1estimate, datasink, [\n", + " ('spmT_images', '1stLevel.@T'),\n", + " ('con_images', '1stLevel.@con'),\n", + " ('spmF_images', '1stLevel.@F'),\n", + " ('ess_images', '1stLevel.@ess')]),\n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "subFolders = [('%s/1stLevel' % s, 'sub-%s/' % s) \n", + " for s in sub_list]\n", + "\n", + "subFolders1 = [('_subject_id_%s'%(s), '')\n", + " for s in sub_list]\n", + "\n", + "subFolders.extend(subFolders1)\n", + "datasink.inputs.substitutions = subFolders" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:39:48,46 nipype.workflow INFO:\n", + "\t Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/graph.png (graph2use=colored, simple_form=True).\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Create 1st-level analysis output graph\n", + "wf.write_graph(graph2use='colored', format='png', simple_form=True)\n", + "\n", + "# Visualize the graph\n", + "from IPython.display import Image\n", + "Image(filename=opj(wf.base_dir, wf.name, 'graph.png'))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:39:48,76 nipype.workflow INFO:\n", + "\t Workflow level1_spm settings: ['check', 'execution', 'logging', 'monitoring']\n", + "240613-06:39:48,125 nipype.workflow INFO:\n", + "\t Running in parallel.\n", + "240613-06:39:48,128 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:39:48,700 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/datagrabber\".\n", + "240613-06:39:48,703 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/datagrabber\".\n", + "240613-06:39:48,702 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/datagrabber\".\n", + "240613-06:39:48,704 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/datagrabber\".\n", + "240613-06:39:48,705 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/datagrabber\".\n", + "240613-06:39:48,712 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/datagrabber\".\n", + "240613-06:39:48,717 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,715 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/datagrabber\".\n", + "240613-06:39:48,715 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/datagrabber\".\n", + "240613-06:39:48,715 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.datagrabber\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/datagrabber\".\n", + "240613-06:39:48,719 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,720 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,720 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,722 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,723 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001618s.\n", + "240613-06:39:48,724 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,724 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001625s.\n", + "240613-06:39:48,725 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,725 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001606s.\n", + "240613-06:39:48,724 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,727 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001663s.\n", + "240613-06:39:48,727 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001644s.\n", + "240613-06:39:48,728 nipype.workflow INFO:\n", + "\t [Node] Executing \"datagrabber\" \n", + "240613-06:39:48,729 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001556s.\n", + "240613-06:39:48,730 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001585s.\n", + "240613-06:39:48,732 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.00274s.\n", + "240613-06:39:48,733 nipype.workflow INFO:\n", + "\t [Node] Finished \"datagrabber\", elapsed time 0.001423s.\n", + "240613-06:39:50,130 nipype.workflow INFO:\n", + "\t [Job 0] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,134 nipype.workflow INFO:\n", + "\t [Job 1] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,136 nipype.workflow INFO:\n", + "\t [Job 2] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,137 nipype.workflow INFO:\n", + "\t [Job 3] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,138 nipype.workflow INFO:\n", + "\t [Job 4] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,140 nipype.workflow INFO:\n", + "\t [Job 5] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,141 nipype.workflow INFO:\n", + "\t [Job 6] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,142 nipype.workflow INFO:\n", + "\t [Job 7] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,144 nipype.workflow INFO:\n", + "\t [Job 8] Completed (level1_spm.datagrabber).\n", + "240613-06:39:50,145 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 18 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:39:52,129 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 36 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:39:52,266 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,266 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,267 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,267 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,278 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,279 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,289 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,290 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,290 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,290 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,289 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,304 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,297 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,306 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,306 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,305 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,316 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,307 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,307 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,306 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,354 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,309 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,360 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,361 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,361 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,308 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,348 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,383 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,372 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,383 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,388 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,389 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,361 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,347 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,383 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,390 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,388 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,428 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,427 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,361 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,428 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,410 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,389 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:52,454 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,451 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,363 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:52,482 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,481 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,476 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,499 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,488 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,506 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,507 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,482 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,507 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,545 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,347 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:52,347 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:52,611 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,589 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,628 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:52,646 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:52,666 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:52,666 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:52,900 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 0.581607s.\n", + "240613-06:39:52,917 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 0.595812s.\n", + "240613-06:39:53,117 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 0.740315s.\n", + "240613-06:39:53,238 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 0.830323s.\n", + "240613-06:39:53,211 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 0.717004s.\n", + "240613-06:39:53,647 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.140628s.\n", + "240613-06:39:53,674 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 1.091297s.\n", + "240613-06:39:53,686 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.157195s.\n", + "240613-06:39:53,743 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.22757s.\n", + "240613-06:39:53,915 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.159781s.\n", + "240613-06:39:54,153 nipype.workflow INFO:\n", + "\t [Job 74] Completed (_getsubjectinfo0).\n", + "240613-06:39:54,212 nipype.workflow INFO:\n", + "\t [Job 75] Completed (_getsubjectinfo1).\n", + "240613-06:39:54,213 nipype.workflow INFO:\n", + "\t [Job 79] Completed (_getsubjectinfo1).\n", + "240613-06:39:54,214 nipype.workflow INFO:\n", + "\t [Job 95] Completed (_getsubjectinfo1).\n", + "240613-06:39:54,161 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.517694s.\n", + "240613-06:39:54,215 nipype.workflow INFO:\n", + "\t [Job 98] Completed (_getsubjectinfo0).\n", + "240613-06:39:54,216 nipype.workflow INFO:\n", + "\t [Job 99] Completed (_getsubjectinfo1).\n", + "240613-06:39:54,217 nipype.workflow INFO:\n", + "\t [Job 102] Completed (_getsubjectinfo0).\n", + "240613-06:39:54,218 nipype.workflow INFO:\n", + "\t [Job 103] Completed (_getsubjectinfo1).\n", + "240613-06:39:54,146 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 1.514954s.\n", + "240613-06:39:54,161 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 1.584535s.\n", + "240613-06:39:54,255 nipype.workflow INFO:\n", + "\t [MultiProc] Running 24 tasks, and 7 jobs ready. Free memory (GB): 214.68/219.48, Free processors: 8/32.\n", + " Currently running:\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _getsubjectinfo0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _getsubjectinfo1\n", + " * _getsubjectinfo0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _getsubjectinfo1\n", + " * _getsubjectinfo0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _getsubjectinfo1\n", + " * _getsubjectinfo0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _getsubjectinfo0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + "240613-06:39:54,307 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.6459190000000001s.\n", + "240613-06:39:54,505 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 1.696907s.\n", + "240613-06:39:54,613 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 1.8154249999999998s.\n", + "240613-06:39:55,99 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:39:55,107 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:39:55,110 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:55,107 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:55,126 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo0\" \n", + "240613-06:39:55,134 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func1\" \n", + "240613-06:39:55,149 nipype.workflow INFO:\n", + "\t [Node] Executing \"_gunzip_func0\" \n", + "240613-06:39:55,158 nipype.workflow INFO:\n", + "\t [Node] Executing \"_getsubjectinfo1\" \n", + "240613-06:39:55,143 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:55,153 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:55,162 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:55,204 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:55,204 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:55,211 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:55,212 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:55,226 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:55,230 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:55,231 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:55,251 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:55,271 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo0\", elapsed time 0.111534s.\n", + "240613-06:39:55,247 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:55,284 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:55,285 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:55,276 nipype.workflow INFO:\n", + "\t [Node] Finished \"_getsubjectinfo1\", elapsed time 0.102113s.\n", + "240613-06:39:55,298 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:55,298 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:55,298 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:55,328 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,135 nipype.workflow INFO:\n", + "\t [Job 78] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,141 nipype.workflow INFO:\n", + "\t [Job 82] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,142 nipype.workflow INFO:\n", + "\t [Job 83] Completed (_getsubjectinfo1).\n", + "240613-06:39:56,147 nipype.workflow INFO:\n", + "\t [Job 86] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,148 nipype.workflow INFO:\n", + "\t [Job 87] Completed (_getsubjectinfo1).\n", + "240613-06:39:56,149 nipype.workflow INFO:\n", + "\t [Job 90] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,150 nipype.workflow INFO:\n", + "\t [Job 91] Completed (_getsubjectinfo1).\n", + "240613-06:39:56,150 nipype.workflow INFO:\n", + "\t [Job 94] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,153 nipype.workflow INFO:\n", + "\t [Job 10] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:56,162 nipype.workflow INFO:\n", + "\t [Job 22] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:56,164 nipype.workflow INFO:\n", + "\t [Job 24] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:56,165 nipype.workflow INFO:\n", + "\t [Job 106] Completed (_getsubjectinfo0).\n", + "240613-06:39:56,166 nipype.workflow INFO:\n", + "\t [Job 107] Completed (_getsubjectinfo1).\n", + "240613-06:39:56,167 nipype.workflow INFO:\n", + "\t [MultiProc] Running 18 tasks, and 6 jobs ready. Free memory (GB): 215.88/219.48, Free processors: 14/32.\n", + " Currently running:\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + "240613-06:39:56,626 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,648 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,645 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,652 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,664 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,670 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,684 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,689 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,670 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,683 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,691 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,689 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,700 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,699 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,690 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,703 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,702 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,703 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,707 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,703 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo0\".\n", + "240613-06:39:56,708 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,711 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,710 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,716 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,724 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,724 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,724 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,732 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,727 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,728 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,737 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:56,737 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo0\" - collecting precomputed outputs\n", + "240613-06:39:56,747 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo0\" found cached.\n", + "240613-06:39:56,766 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_getsubjectinfo1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo1\".\n", + "240613-06:39:56,783 nipype.workflow INFO:\n", + "\t [Node] Cached \"_getsubjectinfo1\" - collecting precomputed outputs\n", + "240613-06:39:56,787 nipype.workflow INFO:\n", + "\t [Node] \"_getsubjectinfo1\" found cached.\n", + "240613-06:39:58,137 nipype.workflow INFO:\n", + "\t [Job 12] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,144 nipype.workflow INFO:\n", + "\t [Job 14] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,146 nipype.workflow INFO:\n", + "\t [Job 16] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,147 nipype.workflow INFO:\n", + "\t [Job 18] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,149 nipype.workflow INFO:\n", + "\t [Job 20] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,150 nipype.workflow INFO:\n", + "\t [Job 26] Completed (level1_spm.getsubjectinfo).\n", + "240613-06:39:58,153 nipype.workflow INFO:\n", + "\t [MultiProc] Running 18 tasks, and 0 jobs ready. Free memory (GB): 215.88/219.48, Free processors: 14/32.\n", + " Currently running:\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + "240613-06:40:15,638 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 23.128215s.\n", + "240613-06:40:16,142 nipype.workflow INFO:\n", + "\t [Job 100] Completed (_gunzip_func0).\n", + "240613-06:40:16,160 nipype.workflow INFO:\n", + "\t [MultiProc] Running 17 tasks, and 0 jobs ready. Free memory (GB): 216.08/219.48, Free processors: 15/32.\n", + " Currently running:\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + " * _gunzip_func1\n", + " * _gunzip_func0\n", + "240613-06:40:32,632 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 40.132508s.\n", + "240613-06:40:32,698 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 40.383246s.\n", + "240613-06:40:32,915 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 40.566017s.\n", + "240613-06:40:33,174 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 38.021523s.\n", + "240613-06:40:33,667 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.115592s.\n", + "240613-06:40:33,770 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.066139s.\n", + "240613-06:40:33,800 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.185805s.\n", + "240613-06:40:33,806 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 41.052042s.\n", + "240613-06:40:33,807 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.348077s.\n", + "240613-06:40:33,865 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.102108s.\n", + "240613-06:40:33,915 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 41.452969s.\n", + "240613-06:40:33,928 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 41.216404s.\n", + "240613-06:40:33,947 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.647503s.\n", + "240613-06:40:33,963 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 41.661571s.\n", + "240613-06:40:34,1 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func1\", elapsed time 41.555917s.\n", + "240613-06:40:34,124 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 38.961281s.\n", + "240613-06:40:34,158 nipype.workflow INFO:\n", + "\t [Job 72] Completed (_gunzip_func0).\n", + "240613-06:40:34,159 nipype.workflow INFO:\n", + "\t [Job 73] Completed (_gunzip_func1).\n", + "240613-06:40:34,160 nipype.workflow INFO:\n", + "\t [Job 76] Completed (_gunzip_func0).\n", + "240613-06:40:34,161 nipype.workflow INFO:\n", + "\t [Job 77] Completed (_gunzip_func1).\n", + "240613-06:40:34,162 nipype.workflow INFO:\n", + "\t [Job 80] Completed (_gunzip_func0).\n", + "240613-06:40:34,162 nipype.workflow INFO:\n", + "\t [Job 81] Completed (_gunzip_func1).\n", + "240613-06:40:34,163 nipype.workflow INFO:\n", + "\t [Job 85] Completed (_gunzip_func1).\n", + "240613-06:40:34,164 nipype.workflow INFO:\n", + "\t [Job 88] Completed (_gunzip_func0).\n", + "240613-06:40:34,165 nipype.workflow INFO:\n", + "\t [Job 89] Completed (_gunzip_func1).\n", + "240613-06:40:34,166 nipype.workflow INFO:\n", + "\t [Job 92] Completed (_gunzip_func0).\n", + "240613-06:40:34,167 nipype.workflow INFO:\n", + "\t [Job 93] Completed (_gunzip_func1).\n", + "240613-06:40:34,167 nipype.workflow INFO:\n", + "\t [Job 96] Completed (_gunzip_func0).\n", + "240613-06:40:34,168 nipype.workflow INFO:\n", + "\t [Job 97] Completed (_gunzip_func1).\n", + "240613-06:40:34,168 nipype.workflow INFO:\n", + "\t [Job 101] Completed (_gunzip_func1).\n", + "240613-06:40:34,169 nipype.workflow INFO:\n", + "\t [Job 104] Completed (_gunzip_func0).\n", + "240613-06:40:34,170 nipype.workflow INFO:\n", + "\t [Job 105] Completed (_gunzip_func1).\n", + "240613-06:40:34,172 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 8 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * _gunzip_func0\n", + "240613-06:40:34,266 nipype.workflow INFO:\n", + "\t [Node] Finished \"_gunzip_func0\", elapsed time 41.81803s.\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,493 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,499 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,498 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:34,500 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,501 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,502 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,502 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,501 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,502 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,503 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,504 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,504 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,505 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:34,505 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,506 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,504 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,508 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,509 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,509 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,509 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,508 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:34,510 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,510 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,520 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,521 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,523 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,527 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,521 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,520 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:34,536 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,529 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,537 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,537 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,537 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:34,538 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,538 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,538 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:34,545 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:36,159 nipype.workflow INFO:\n", + "\t [Job 84] Completed (_gunzip_func0).\n", + "240613-06:40:36,160 nipype.workflow INFO:\n", + "\t [Job 9] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,161 nipype.workflow INFO:\n", + "\t [Job 11] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,162 nipype.workflow INFO:\n", + "\t [Job 13] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,163 nipype.workflow INFO:\n", + "\t [Job 17] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,164 nipype.workflow INFO:\n", + "\t [Job 19] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,165 nipype.workflow INFO:\n", + "\t [Job 21] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,166 nipype.workflow INFO:\n", + "\t [Job 23] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,167 nipype.workflow INFO:\n", + "\t [Job 25] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:36,175 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:40:36,334 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/modelspec\".\n", + "240613-06:40:36,334 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/modelspec\".\n", + "240613-06:40:36,334 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/modelspec\".\n", + "240613-06:40:36,349 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/modelspec\".\n", + "240613-06:40:36,349 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/modelspec\".\n", + "240613-06:40:36,349 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/modelspec\".\n", + "240613-06:40:36,348 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/modelspec\".\n", + "240613-06:40:36,348 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/modelspec\".\n", + "240613-06:40:36,368 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func0\".\n", + "240613-06:40:36,370 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,370 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,369 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,370 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,370 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,369 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,371 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func0\" - collecting precomputed outputs\n", + "240613-06:40:36,372 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,373 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func0\" found cached.\n", + "240613-06:40:36,373 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:36,374 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_gunzip_func1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func1\".\n", + "240613-06:40:36,388 nipype.workflow INFO:\n", + "\t [Node] Cached \"_gunzip_func1\" - collecting precomputed outputs\n", + "240613-06:40:36,390 nipype.workflow INFO:\n", + "\t [Node] \"_gunzip_func1\" found cached.\n", + "240613-06:40:36,402 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.029773s.\n", + "240613-06:40:36,403 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.031097s.\n", + "240613-06:40:36,404 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.03211s.\n", + "240613-06:40:36,417 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.031377s.\n", + "240613-06:40:36,404 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.031388s.\n", + "240613-06:40:36,418 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.044186s.\n", + "240613-06:40:36,420 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.046569s.\n", + "240613-06:40:36,428 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.039876s.\n", + "240613-06:40:38,159 nipype.workflow INFO:\n", + "\t [Job 15] Completed (level1_spm.gunzip_func).\n", + "240613-06:40:38,164 nipype.workflow INFO:\n", + "\t [Job 27] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,171 nipype.workflow INFO:\n", + "\t [Job 28] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,172 nipype.workflow INFO:\n", + "\t [Job 29] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,173 nipype.workflow INFO:\n", + "\t [Job 31] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,174 nipype.workflow INFO:\n", + "\t [Job 32] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,175 nipype.workflow INFO:\n", + "\t [Job 33] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,176 nipype.workflow INFO:\n", + "\t [Job 34] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,177 nipype.workflow INFO:\n", + "\t [Job 35] Completed (level1_spm.modelspec).\n", + "240613-06:40:38,179 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:40:38,331 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.modelspec\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/modelspec\".\n", + "240613-06:40:38,332 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1design\".\n", + "240613-06:40:38,333 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1design\".\n", + "240613-06:40:38,333 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1design\".\n", + "240613-06:40:38,341 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1design\".\n", + "240613-06:40:38,340 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1design\".\n", + "240613-06:40:38,358 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1design\".\n", + "240613-06:40:38,358 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1design\".\n", + "240613-06:40:38,360 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1design\".\n", + "240613-06:40:38,385 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,393 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,393 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,393 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,395 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,396 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,397 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,404 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:38,530 nipype.workflow INFO:\n", + "\t [Node] Executing \"modelspec\" \n", + "240613-06:40:38,563 nipype.workflow INFO:\n", + "\t [Node] Finished \"modelspec\", elapsed time 0.028673s.\n", + "240613-06:40:40,159 nipype.workflow INFO:\n", + "\t [Job 30] Completed (level1_spm.modelspec).\n", + "240613-06:40:40,161 nipype.workflow INFO:\n", + "\t [MultiProc] Running 8 tasks, and 1 jobs ready. Free memory (GB): 217.88/219.48, Free processors: 24/32.\n", + " Currently running:\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + "240613-06:40:40,322 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1design\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1design\".\n", + "240613-06:40:40,382 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1design\" \n", + "240613-06:40:42,198 nipype.workflow INFO:\n", + "\t [MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.\n", + " Currently running:\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + " * level1_spm.level1design\n", + "240613-06:41:42,353 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 63.956473s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:41:43,926 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.499334s.\n", + "240613-06:41:43,926 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.532317s.\n", + "240613-06:41:43,990 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 63.605568s.\n", + "240613-06:41:43,991 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.580354s.\n", + "240613-06:41:43,991 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.593839s.\n", + "240613-06:41:44,72 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.676236s.\n", + "240613-06:41:44,91 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.695045s.\n", + "240613-06:41:44,93 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1design\", elapsed time 65.665607s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:41:44,225 nipype.workflow INFO:\n", + "\t [Job 36] Completed (level1_spm.level1design).\n", + "240613-06:41:44,226 nipype.workflow INFO:\n", + "\t [Job 37] Completed (level1_spm.level1design).\n", + "240613-06:41:44,227 nipype.workflow INFO:\n", + "\t [Job 38] Completed (level1_spm.level1design).\n", + "240613-06:41:44,228 nipype.workflow INFO:\n", + "\t [Job 40] Completed (level1_spm.level1design).\n", + "240613-06:41:44,229 nipype.workflow INFO:\n", + "\t [Job 41] Completed (level1_spm.level1design).\n", + "240613-06:41:44,230 nipype.workflow INFO:\n", + "\t [Job 42] Completed (level1_spm.level1design).\n", + "240613-06:41:44,231 nipype.workflow INFO:\n", + "\t [Job 43] Completed (level1_spm.level1design).\n", + "240613-06:41:44,232 nipype.workflow INFO:\n", + "\t [Job 44] Completed (level1_spm.level1design).\n", + "240613-06:41:44,233 nipype.workflow INFO:\n", + "\t [Job 39] Completed (level1_spm.level1design).\n", + "240613-06:41:44,235 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:41:44,402 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1estimate\".\n", + "240613-06:41:44,417 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1estimate\".\n", + "240613-06:41:44,402 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1estimate\".\n", + "240613-06:41:44,425 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1estimate\".\n", + "240613-06:41:44,402 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1estimate\".\n", + "240613-06:41:44,437 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1estimate\".\n", + "240613-06:41:44,441 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1estimate\".\n", + "240613-06:41:44,449 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1estimate\".\n", + "240613-06:41:44,454 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1estimate\".\n", + "240613-06:41:44,500 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,517 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,506 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,507 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,521 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,521 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,521 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,521 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:44,521 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1estimate\" \n", + "240613-06:41:46,225 nipype.workflow INFO:\n", + "\t [MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.\n", + " Currently running:\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + " * level1_spm.level1estimate\n", + "240613-06:43:36,646 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 112.114152s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:43:37,402 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 112.870713s.\n", + "240613-06:43:37,645 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.118144s.\n", + "240613-06:43:37,690 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.146s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:43:37,706 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.169625s.\n", + "240613-06:43:37,739 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.207248s.\n", + "240613-06:43:37,831 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.287801s.\n", + "240613-06:43:37,844 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.307623s.\n", + "240613-06:43:37,845 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1estimate\", elapsed time 113.313924s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:43:38,283 nipype.workflow INFO:\n", + "\t [Job 45] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,285 nipype.workflow INFO:\n", + "\t [Job 46] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,287 nipype.workflow INFO:\n", + "\t [Job 47] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,288 nipype.workflow INFO:\n", + "\t [Job 48] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,289 nipype.workflow INFO:\n", + "\t [Job 49] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,290 nipype.workflow INFO:\n", + "\t [Job 50] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,291 nipype.workflow INFO:\n", + "\t [Job 51] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,293 nipype.workflow INFO:\n", + "\t [Job 52] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,294 nipype.workflow INFO:\n", + "\t [Job 53] Completed (level1_spm.level1estimate).\n", + "240613-06:43:38,296 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:43:38,502 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1conest\".\n", + "240613-06:43:38,504 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1conest\".\n", + "240613-06:43:38,538 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1conest\".\n", + "240613-06:43:38,548 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1conest\".\n", + "240613-06:43:38,540 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1conest\".\n", + "240613-06:43:38,595 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1conest\".\n", + "240613-06:43:38,603 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1conest\".\n", + "240613-06:43:38,577 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1conest\".\n", + "240613-06:43:38,606 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.level1conest\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1conest\".\n", + "240613-06:43:38,675 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,682 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,711 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,711 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,713 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,715 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,715 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,716 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:38,723 nipype.workflow INFO:\n", + "\t [Node] Executing \"level1conest\" \n", + "240613-06:43:40,284 nipype.workflow INFO:\n", + "\t [MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.\n", + " Currently running:\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + " * level1_spm.level1conest\n", + "240613-06:44:06,134 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.402464s.\n", + "240613-06:44:06,139 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.449268s.\n", + "240613-06:44:06,141 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.417092s.\n", + "240613-06:44:06,159 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.435406s.\n", + "240613-06:44:06,161 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.437036s.\n", + "240613-06:44:06,172 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.458638s.\n", + "240613-06:44:06,181 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.467807s.\n", + "240613-06:44:06,182 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.457296s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: stty: 'standard input': Inappropriate ioctl for device\n", + "'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:06,195 nipype.workflow INFO:\n", + "\t [Node] Finished \"level1conest\", elapsed time 27.504365s.\n", + "240613-06:44:06,286 nipype.workflow INFO:\n", + "\t [Job 54] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,288 nipype.workflow INFO:\n", + "\t [Job 55] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,289 nipype.workflow INFO:\n", + "\t [Job 56] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,289 nipype.workflow INFO:\n", + "\t [Job 57] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,290 nipype.workflow INFO:\n", + "\t [Job 58] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,292 nipype.workflow INFO:\n", + "\t [Job 59] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,293 nipype.workflow INFO:\n", + "\t [Job 60] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,293 nipype.workflow INFO:\n", + "\t [Job 61] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,294 nipype.workflow INFO:\n", + "\t [Job 62] Completed (level1_spm.level1conest).\n", + "240613-06:44:06,296 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:44:06,480 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/sinker\".\n", + "240613-06:44:06,505 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/sinker\".\n", + "240613-06:44:06,511 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/sinker\".\n", + "240613-06:44:06,501 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/sinker\".\n", + "240613-06:44:06,528 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/sinker\".\n", + "240613-06:44:06,511 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/sinker\".\n", + "240613-06:44:06,526 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/sinker\".\n", + "240613-06:44:06,539 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/sinker\".\n", + "240613-06:44:06,535 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level1_spm.sinker\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/sinker\".\n", + "240613-06:44:06,577 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,577 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,577 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,578 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,578 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,579 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,579 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,579 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///SPM.mat\n", + "240613-06:44:06,579 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///SPM.mat\n", + "240613-06:44:06,580 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///SPM.mat\n", + "240613-06:44:06,587 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,587 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0001.nii\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0001.nii\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0001.nii\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///SPM.mat\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///SPM.mat\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///SPM.mat\n", + "240613-06:44:06,598 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///SPM.mat\n", + "240613-06:44:06,599 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///SPM.mat\n", + "240613-06:44:06,599 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0002.nii\n", + "240613-06:44:06,600 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0002.nii\n", + "240613-06:44:06,600 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0002.nii\n", + "240613-06:44:06,600 nipype.workflow INFO:\n", + "\t [Node] Executing \"sinker\" \n", + "240613-06:44:06,601 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0001.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0001.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0001.nii\n", + "240613-06:44:06,601 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0001.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0003.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0003.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0003.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0001.nii\n", + "240613-06:44:06,603 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0002.nii\n", + "240613-06:44:06,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0002.nii\n", + "240613-06:44:06,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0002.nii\n", + "240613-06:44:06,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0002.nii\n", + "240613-06:44:06,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0004.nii\n", + "240613-06:44:06,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0003.nii\n", + "240613-06:44:06,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0004.nii\n", + "240613-06:44:06,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///SPM.mat\n", + "240613-06:44:06,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0002.nii\n", + "240613-06:44:06,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0003.nii\n", + "240613-06:44:06,606 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0003.nii\n", + "240613-06:44:06,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0003.nii\n", + "240613-06:44:06,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0005.nii\n", + "240613-06:44:06,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0004.nii\n", + "240613-06:44:06,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0001.nii\n", + "240613-06:44:06,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0004.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0004.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0004.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0003.nii\n", + "240613-06:44:06,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0005.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0005.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0004.nii\n", + "240613-06:44:06,609 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0002.nii\n", + "240613-06:44:06,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0006.nii\n", + "240613-06:44:06,609 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0005.nii\n", + "240613-06:44:06,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0006.nii\n", + "240613-06:44:06,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0003.nii\n", + "240613-06:44:06,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0006.nii\n", + "240613-06:44:06,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0005.nii\n", + "240613-06:44:06,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0005.nii\n", + "240613-06:44:06,611 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0007.nii\n", + "240613-06:44:06,609 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmT_0005.nii\n", + "240613-06:44:06,611 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0007.nii\n", + "240613-06:44:06,611 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0006.nii\n", + "240613-06:44:06,612 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0006.nii\n", + "240613-06:44:06,611 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0004.nii\n", + "240613-06:44:06,611 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0004.nii\n", + "240613-06:44:06,612 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0006.nii\n", + "240613-06:44:06,612 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmT_0006.nii\n", + "240613-06:44:06,612 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0008.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0007.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmT_0005.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0007.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0008.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0007.nii\n", + "240613-06:44:06,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0007.nii\n", + "240613-06:44:06,614 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0009.nii\n", + "240613-06:44:06,614 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0008.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0009.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0008.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmT_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmT_0010.nii\n", + "240613-06:44:06,614 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmT_0005.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0008.nii\n", + "240613-06:44:06,614 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0008.nii\n", + "240613-06:44:06,616 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0009.nii\n", + "240613-06:44:06,616 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0009.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmT_0006.nii\n", + "240613-06:44:06,616 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0001.nii\n", + "240613-06:44:06,616 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmT_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmT_0010.nii\n", + "240613-06:44:06,616 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmT_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmT_0006.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmT_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmT_0010.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0009.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0009.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmT_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmT_0010.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmT_0007.nii\n", + "240613-06:44:06,615 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmT_0007.nii\n", + "240613-06:44:06,618 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///ess_0001.nii\n", + "240613-06:44:06,618 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmT_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmT_0010.nii\n", + "240613-06:44:06,618 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmT_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmT_0007.nii\n", + "240613-06:44:06,619 nipype.interface INFO:\n", + "\t sub: 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmT_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmT_0008.nii\n", + "240613-06:44:06,620 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0002.nii\n", + "240613-06:44:06,620 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0001.nii\n", + "240613-06:44:06,619 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0001.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///ess_0002.nii\n", + "240613-06:44:06,622 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmT_0009.nii\n", + "240613-06:44:06,621 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmT_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmT_0009.nii\n", + "240613-06:44:06,622 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0002.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0002.nii\n", + "240613-06:44:06,623 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0003.nii\n", + "240613-06:44:06,623 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0004.nii\n", + "240613-06:44:06,623 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmT_0010.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///ess_0001.nii\n", + "240613-06:44:06,625 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/con_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///con_0006.nii\n", + "240613-06:44:06,625 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///con_0005.nii\n", + "240613-06:44:06,617 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0002.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/con_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///con_0007.nii\n", + "240613-06:44:06,630 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///con_0005.nii\n", + "240613-06:44:06,627 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0003.nii\n", + "240613-06:44:06,626 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0001.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0003.nii\n", + "240613-06:44:06,625 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///con_0005.nii\n", + "240613-06:44:06,632 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0004.nii\n", + "240613-06:44:06,632 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0004.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0004.nii\n", + "240613-06:44:06,634 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/con_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///con_0006.nii\n", + "240613-06:44:06,633 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/con_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///con_0009.nii\n", + "240613-06:44:06,634 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0003.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/con_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///con_0007.nii\n", + "240613-06:44:06,634 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///con_0005.nii\n", + "240613-06:44:06,635 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/con_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///con_0010.nii\n", + "240613-06:44:06,634 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/con_0005.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///con_0005.nii\n", + "240613-06:44:06,635 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/con_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///con_0009.nii\n", + "240613-06:44:06,636 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0001.nii\n", + "240613-06:44:06,637 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/con_0006.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/con_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///con_0005.nii\n", + "240613-06:44:06,637 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0002.nii\n", + "240613-06:44:06,637 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/con_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///con_0006.nii\n", + "240613-06:44:06,638 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/con_0010.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/con_0006.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///con_0006.nii\n", + "240613-06:44:06,639 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/con_0007.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///con_0007.nii\n", + "240613-06:44:06,638 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/con_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///con_0010.nii\n", + "240613-06:44:06,639 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/con_0009.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0001.nii\n", + "240613-06:44:06,640 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/con_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///con_0010.nii\n", + "240613-06:44:06,641 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/con_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///con_0008.nii\n", + "240613-06:44:06,640 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/con_0008.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0001.nii\n", + "240613-06:44:06,642 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/con_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///con_0009.nii\n", + "240613-06:44:06,642 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///ess_0001.nii\n", + "240613-06:44:06,642 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/con_0009.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0003.nii\n", + "240613-06:44:06,643 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///ess_0002.nii\n", + "240613-06:44:06,644 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/con_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///con_0010.nii\n", + "240613-06:44:06,643 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/con_0010.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0001.nii\n", + "240613-06:44:06,645 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0001.nii\n", + "240613-06:44:06,645 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0001.nii\n", + "240613-06:44:06,644 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/con_0010.nii -> 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INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0003.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0002.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///ess_0003.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0001.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0001.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0002.nii\n", + "240613-06:44:06,651 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/con_0008.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///con_0008.nii\n", + "240613-06:44:06,651 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0003.nii\n", + "240613-06:44:06,651 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0002.nii\n", + "240613-06:44:06,650 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0003.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/con_0009.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///con_0009.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0002.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///ess_0004.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0004.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0002.nii\n", + "240613-06:44:06,651 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0004.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0003.nii\n", + "240613-06:44:06,653 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0004.nii\n", + "240613-06:44:06,652 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0003.nii\n", + "240613-06:44:06,653 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0003.nii\n", + "240613-06:44:06,653 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0001.nii\n", + "240613-06:44:06,653 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/con_0010.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///con_0010.nii\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0004.nii\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///ess_0004.nii\n", + "240613-06:44:06,653 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///ess_0001.nii\n", + "240613-06:44:06,654 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.056046s.\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0004.nii\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///ess_0001.nii\n", + "240613-06:44:06,655 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0001.nii\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0003.nii\n", + "240613-06:44:06,655 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0001.nii\n", + "240613-06:44:06,655 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///ess_0002.nii\n", + "240613-06:44:06,655 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0001.nii\n", + "240613-06:44:06,654 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0002.nii\n", + "240613-06:44:06,656 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0002.nii\n", + "240613-06:44:06,656 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0002.nii\n", + "240613-06:44:06,656 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///ess_0002.nii\n", + "240613-06:44:06,657 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0003.nii\n", + "240613-06:44:06,656 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///ess_0003.nii\n", + "240613-06:44:06,662 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.058342s.\n", + "240613-06:44:06,662 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0002.nii\n", + "240613-06:44:06,663 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///ess_0004.nii\n", + "240613-06:44:06,664 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///ess_0004.nii\n", + "240613-06:44:06,663 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0003.nii\n", + "240613-06:44:06,663 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///ess_0004.nii\n", + "240613-06:44:06,662 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///ess_0003.nii\n", + "240613-06:44:06,664 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0003.nii\n", + "240613-06:44:06,663 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0004.nii\n", + "240613-06:44:06,665 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///ess_0001.nii\n", + "240613-06:44:06,666 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///ess_0002.nii\n", + "240613-06:44:06,663 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0003.nii\n", + "240613-06:44:06,665 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///ess_0004.nii\n", + "240613-06:44:06,669 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0004.nii\n", + "240613-06:44:06,669 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0004.nii\n", + "240613-06:44:06,670 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.066268s.\n", + "240613-06:44:06,669 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///ess_0003.nii\n", + "240613-06:44:06,671 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0001.nii\n", + "240613-06:44:06,671 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.09154s.\n", + "240613-06:44:06,671 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.091656s.\n", + "240613-06:44:06,672 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0002.nii\n", + "240613-06:44:06,672 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///ess_0004.nii\n", + "240613-06:44:06,671 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.065593s.\n", + "240613-06:44:06,673 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.074355s.\n", + "240613-06:44:06,672 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.074125s.\n", + "240613-06:44:06,677 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0003.nii\n", + "240613-06:44:06,678 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0004.nii\n", + "240613-06:44:06,679 nipype.workflow INFO:\n", + "\t [Node] Finished \"sinker\", elapsed time 0.099528s.\n", + "240613-06:44:08,286 nipype.workflow INFO:\n", + "\t [Job 63] Completed (level1_spm.sinker).\n", + "240613-06:44:08,288 nipype.workflow INFO:\n", + "\t [Job 64] Completed (level1_spm.sinker).\n", + "240613-06:44:08,289 nipype.workflow INFO:\n", + "\t [Job 65] Completed (level1_spm.sinker).\n", + "240613-06:44:08,290 nipype.workflow INFO:\n", + "\t [Job 66] Completed (level1_spm.sinker).\n", + "240613-06:44:08,291 nipype.workflow INFO:\n", + "\t [Job 67] Completed (level1_spm.sinker).\n", + "240613-06:44:08,291 nipype.workflow INFO:\n", + "\t [Job 68] Completed (level1_spm.sinker).\n", + "240613-06:44:08,292 nipype.workflow INFO:\n", + "\t [Job 69] Completed (level1_spm.sinker).\n", + "240613-06:44:08,294 nipype.workflow INFO:\n", + "\t [Job 70] Completed (level1_spm.sinker).\n", + "240613-06:44:08,294 nipype.workflow INFO:\n", + "\t [Job 71] Completed (level1_spm.sinker).\n", + "240613-06:44:08,296 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf.run(plugin=\"MultiProc\") #will use all CPUs\n", + "#ca. 10 min" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Visualize design matrix and list contrasts" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "spmmat = loadmat(opj(experiment_dir, 'level1_spm_results/sub-01/SPM.mat'), struct_as_record=False)\n", + "\n", + "designMatrix = spmmat['SPM'][0][0].xX[0][0].X\n", + "names =[i[0] for i in spmmat['SPM'][0][0].xX[0][0].name[0]]\n", + "names_contrast = [spmmat['SPM'][0][0].xCon[0][i].name[0] for i in range(spmmat['SPM'][0][0].xCon.shape[1])]\n", + "\n", + "\n", + "normed_design=designMatrix / np.abs(designMatrix).max(axis=0)\n", + "\n", + "fig,ax = plt.subplots(figsize=(8,8))\n", + "plt.imshow(normed_design, aspect='auto', cmap='gray')\n", + "ax.set_ylabel('Volume id')\n", + "ax.set_xticks(np.arange(len(names)))\n", + "ax.set_xticklabels(names, rotation=90);" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Name STAT c spm_file con_file\n", + " Average effect condition F [1, 1, 1, 1, 1, 1, 0, 0] spmF_0001.nii ess_0001.nii\n", + " Main effect Face F [1, 0, 1, 0, -1, 1, -1, 1, 0, -1, 0, -1, 0, 0, 0, 0] spmF_0002.nii ess_0002.nii\n", + " Main effect Rep F [1, -1, 1, -1, 1, -1, 0, 0] spmF_0003.nii ess_0003.nii\n", + " Interaction: Face x Rep F [1, 0, -1, 0, -1, 1, 1, -1, 0, -1, 0, 1, 0, 0, 0, 0] spmF_0004.nii ess_0004.nii\n", + " Positive effect of condition T [1, 1, 1, 1, 1, 1, 0, 0] spmT_0005.nii con_0005.nii\n", + " Positive effect of Face_1 T [1, 1, -1, -1, 0, 0, 0, 0] spmT_0006.nii con_0006.nii\n", + " Positive effect of Face_2 T [0, 0, 1, 1, -1, -1, 0, 0] spmT_0007.nii con_0007.nii\n", + " Positive effect of Rep T [1, -1, 1, -1, 1, -1, 0, 0] spmT_0008.nii con_0008.nii\n", + "Positive interaction of Face x Rep1 T [1, -1, -1, 1, 0, 0, 0, 0] spmT_0009.nii con_0009.nii\n", + "Positive interaction of Face x Rep2 T [0, 0, 1, -1, -1, 1, 0, 0] spmT_0010.nii con_0010.nii\n" + ] + } + ], + "source": [ + "data = []\n", + "\n", + "xCon_array = spmmat['SPM'][0][0].xCon[0]\n", + "\n", + "# Iterate over each struct in the xCon array, nested loop, iterate over Vspm and Vcon to get filenames\n", + "for struct in xCon_array:\n", + " name = struct.name[0]\n", + " stat = struct.STAT[0]\n", + " c = struct.c.flatten().tolist()\n", + " vspm = struct.Vspm[0]\n", + " vcon = struct.Vcon[0]\n", + " for st in vspm:\n", + " vspm_name = st.fname[0]\n", + " for s in vcon:\n", + " vcon_name = s.fname[0]\n", + " \n", + " data.append({\"Name\": name, \"STAT\": stat, \"c\": c, \"spm_file\": vspm_name, \"con_file\": vcon_name})\n", + "\n", + "df = pd.DataFrame(data)\n", + "df_string = df.to_string(index=False)\n", + "\n", + "print(df_string)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2. Second Level Analysis\n", + "\n", + "For a factorial design with 2 factors there are 4 effects to test for: an overall effect, 2 main effects and one two-way interaction:\n", + "\n", + "- To test (1) the overall effect, use a [1 1 1 1 1 1] contrast for each subject and take the resulting con images of all subjects into a one-sample t-test at the second level. Then specify a [1] F-contrast (at the second level) to test for significantly non-zero BOLD responses related to the paradigm. \n", + "\n", + "- To test for (2) the main effect of Factor Repetition (two levels), use a [1 -1 1 -1 1 -1] contrast for each subject and take the resulting con images into a one-sample t-test at the second level. \n", + "\n", + "- To test for (3) the main effect of Factor Face (three levels), use two contrasts per subject [1 1 -1 -1 0 0] and [0 0 1 1 -1 -1] and take all resulting con images (two per subject) into a two-sample t-test design at the second level. Then, use a [1 0; 0 1] F-contrast to test for this main effect.\n", + "\n", + "- To test for (4) the interaction between Factors Face and Rep, use two contrasts per subject [1 -1 -1 1 0 0] and [0 0 1 -1 -1 1] and take all resulting con images (two per subject) into a two-sample t-test design at the second level. Use then a [1 0; 0 1] F-contrast to test for this interaction effect. \n", + " \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 2.1 One Sample T-Test: Overall effect, main effect of repetition\n", + "\n", + "Test for significantly non-zero BOLD responses over all subjects.\n", + "\n", + "- con_0005: Positive effect\n", + "- \n", + "- con_0006: Positive Effect F>S \n", + "- con_0007: Positive Effect S>U\n", + "- \n", + "- con_0008: Positive Effect of rep1>rep2\n", + "- \n", + "- con_0009: Positive Interaction Face (F/S) x Rep \n", + "- con_0010: Positive Interaction Face (S/U) x Rep" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "wf_2ndlevel_onesample = Workflow(name='level2_spm_1sample', base_dir=experiment_dir)\n", + "wf_2ndlevel_onesample.config[\"execution\"][\"crashfile_format\"] = \"txt\"" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "contrast_id = [5, 6, 7, 8, 9, 10] #contrasts con_0005 to con_0010\n", + "\n", + "l2source = Node(DataGrabber(infields= ['con'], outfields=['contrasts']), name='l2source')\n", + "\n", + "l2source.inputs.sort_filelist = True\n", + "l2source.inputs.base_directory = opj(experiment_dir, 'level1_spm_results')\n", + "l2source.inputs.template = '*'\n", + "l2source.inputs.field_template = dict(\n", + " contrasts = '*/con_%04d.nii'\n", + ")\n", + "\n", + "# iterate over all contrast images\n", + "l2source.iterables = [('con', contrast_id)]" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "# OneSampleTTest Design\n", + "onesamplettestdes = Node(interface=spm.OneSampleTTestDesign(), name=\"onesampttestdes\")\n", + "\n", + "wf_2ndlevel_onesample.connect([(l2source, onesamplettestdes, [('contrasts', 'in_files')])])" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "# EstimateModel - estimates the model\n", + "l2estimate = Node(spm.EstimateModel(estimation_method={'Classical':1}), name='level2estimate')\n", + "\n", + "# EstimateContast - estimates group contrast\n", + "l2conestimate = Node(spm.EstimateContrast(group_contrast=True), name = 'level2conestimate')\n", + "\n", + "con_1= ['Group', 'T', ['mean'], [1]]\n", + "#con_2= ['Group', 'F', [con_1]] # if an F contrast is also wanted\n", + "\n", + "l2conestimate.inputs.contrasts = [con_1] # con_2, include in list if wanted\n", + "\n", + "# Threshold - thresholds contrasts\n", + "level2thresh = Node(spm.Threshold(contrast_index=1,# which contrast in the SPM.mat to use --> here set for con_1: T stat\n", + " use_topo_fdr=True, # whether to use FDR over cluster extent probabilities\n", + " use_fwe_correction=False, # whether to use FWE (Bonferroni) correction for initial threshold \n", + " extent_threshold=0, # minimum cluster size in voxels\n", + " height_threshold=0.005, # value for initial thresholding (defining clusters) - voxelwise\n", + " height_threshold_type='p-value',\n", + " extent_fdr_p_threshold=0.05), # p threshold on FDR corrected cluster size probabilities\n", + " name='level2thresh')\n", + "\n", + "wf_2ndlevel_onesample.connect([(onesamplettestdes, l2estimate, [('spm_mat_file', 'spm_mat_file')]),\n", + " (l2estimate, l2conestimate, [('spm_mat_file', 'spm_mat_file'),\n", + " ('beta_images', 'beta_images'),\n", + " ('residual_image', 'residual_image')]),\n", + " (l2conestimate, level2thresh, [('spm_mat_file', 'spm_mat_file'),\n", + " ('spmT_images', 'stat_image')])\n", + "\n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "datasink_2nd = Node(DataSink(), name='datasink_2nd')\n", + "datasink_2nd.inputs.base_directory=opj(experiment_dir, 'level2_spm_results_1sample')\n", + "\n", + "wf_2ndlevel_onesample.connect([(l2conestimate, datasink_2nd, [('spm_mat_file', '2ndLevel.@spm_mat'),\n", + " ('spmT_images', '2ndLevel.@T'),\n", + " ('con_images', '2ndLevel.@con')]),\n", + " (level2thresh, datasink_2nd, [('thresholded_map',\n", + " '2ndLevel.@threshold')]) \n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "#replace _con_ with con\n", + "subFolders = [('2ndLevel/', '')] \n", + "\n", + "subFolders1 = [('_con_', 'con')] \n", + "subFolders.extend(subFolders1)\n", + "\n", + "datasink_2nd.inputs.substitutions = subFolders" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:11,680 nipype.workflow INFO:\n", + "\t Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/graph.png (graph2use=colored, simple_form=True).\n" + ] + }, + { + "data": { + "image/png": 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9AGVlOgwGAwC1tXp0uqpzW1M6ALTaCurr69HpqqmtraOmpo7Kymqqq2vQ6arRaisoL6+kvLyYnJwq43OdrhqdrpLS0ub7dnFpCJ3/Bc//Hms0Gnx8fPD19cXLyws/Pz/jFpZoG7IlI0Qb0Ol0ZGRkkJGRQWZmJjk5OeTk5JwLlLxzgVLQZEvCysoSLy8NGo0L7u7OaDTOuLs7odG4GOc1zG987IKLiwMODnZmHGlTer3BGE7tQXl5JWVlOoqKtBQXl1FcXEZRkdb4/H/zy43z8/OLjbsKoWFL6n/B442fnx9eXl4EBAQQFBREUFAQwcHBxl1/4oJWSMgI0QparZaTJ08aQyQ9Pf3c44bnRUXFxve6uDjh7++Jt7c7fn4avLzc8fXV4O3tfm6eJ15ebnh5ucl9V9oBg6Ge/Pxi8vNLyM4uJD+/mJycInJzi8jLKyY7u4j8/BLOnMlFp/vfFai9vb3OhU6wMXiCg4Pp1KkTYWFhODg0vzX4DyMhI0Sj2tpazp49S2pqKkeOHOHo0aOkpp4mNfU0aWkZxpt1ubk5ExrqT2ioH76+Gvz8PAkN9SM01B9fXw/8/DzMPBJhKlVVNeTkFJKamk1qahapqVlkZxeSk1NMamoW6enZxq0iNzdXQkNDiYyMIioqitDQUEJDQ+nWrds/KYAkZMQ/T21tLceOHSM5OZnk5GQOHz7E0aNHOXs2C0VRsLS0JCjIh7CwQMLCAggLC6Rr1yDCwgIJCvLGxqb5s6eEqKmpIy0tm5Mnz3DiRCYnT57h5MmznDp1ljNnclEUBQsLC4KDg4iKiiImpjs9evQgOjqa8PDwq/HsOgkZcXUrLCxk//79HD58mKSkJJKTk0hJOUFdXR22tjZERoYSExNKdHQoXbsG0bVrEKGh/tjaSpCItlVVVXMudBqmpKRTJCefJiUlg7o6/bl/jxHExPQgJiaGHj160KdPH1xdXc1d+uWQkBFXj7q6Ok6cOMHu3bvZtWsXv/++n2PHUlAUBV9fT6KiQoiM7ETv3t2IigolOrqzhIkwu7o6PSdOZHL0aBpHjqTx++/HOXo0nbS0rHP/dn0YODCeAQMG0Lt3b/r06YOtra25y24tCRnRcZWWlrJ9+3a2bdtGYuKvHDp0mLq6OjQaV/r1i6Jv3wj69Yumb99I3N2dzV2uEBclL6+YffuOsnfvH+zde5T9+4+h1ZZjZ6cmNjaWf/2rP0OHDmXQoEE4Ojq23KB5SMiIjqOqqordu3ezdetWtm3byu+/H0BRFGJjwxkwIIa+faPo1y+KLl3kEifi6lNfX09KSiZ79x5h374j7NyZxJEjp7GysqJfv74MGzacYcOG0a9fv/Pu92NGEjKifTt79izfffcd3333X3bv3k11dQ1duwYzbFhvhg3rw5AhvWUrRfxj5eUVs3XrfrZt+52tW38jPT0bBwd7Bg8ezG23jebWW2/F09PTnCVKyIj25/Tp06xZs4Zvv13Dvn37cXS058Yb+zNyZBxDh15DYKC3uUsUol06fTqLrVv3s379r2zcuJfa2jri4weSkDCG0aNHm+NCphIyon0oLS3l888/59NPP+Hw4SQ0GldGjRpIQsJghg/vi1rdbjb/hegQdLoq1q//lW+/3c7atXsoL9fRr19f7rnnXiZOnHilvqsjISPMa9++fSxatIhVq1ZiYaFiwoTrmDBhONde26tdXa5EiI6spqaOLVv28eWXm1iz5mfUajV33jmFGTNmEBUVZcquJWTElacoCmvWrOH111/jwIGDxMSEMWPGbUyePAJn53/MN6GFMIvCwlKWLVvL4sXfc/JkJvHxA5kz5z9cf/31puhuhdy0TFxRW7dupV+/vowfP54uXTTs2rWYpKQvePDBMRIwQlwBHh6uPPnkJFJSvmLz5vdxcYEbbriBoUOHsG/fvjbvT0JGXBF//PEH119/HcOHD8fDw4bff1/GV1+9woAB3c1dmjCje+99DSenIahUcRw6dMLk/W3Zsp9nn/3A5P1cyA8/7GTu3C8wGOpbfrMJqVQqhg/vw48/vs2uXYupqyslLi6OMWMSSEtLa7N+JGSESSmKwltvvcU11/RGq81hx44PWbfuXXr27Gru0kQ7sGTJbD7+ePYV6euFFz7mvfe+YvbsaVekv78zalQ8arUNw4Y99Lf3wLnSBgzozs6dH/H9929x/PhhevTozqefftombUvICJOpqqpiwoTxzJnzHC++eC979nzMoEGx5i5L0HAdrf7972txXlv3YS5vvPE5q1Zt5uuvX8PJyd7c5TBr1nh69AjjxhsfR683mLsco1tuGciBA58xY8Zt3HfffTz88MPo9frLalNCRphEXV0dY8YksHnzRjZsmM+//z0FS0v559ZefPLJD+TnF7c4r637aI6p76lz6tRZ/vOfRbz00n3t6lT4F1+8j0OHTjB//ipzl9KEra01b775MKtXv8bSpZ8yderUJjd1u1jyv16YxKxZs9i9exebN7/HkCG9zV1OE4qi8O67K4mIGI+tbTxubtdx221Pc/x4BgAffLAGB4fB2Ntfy/ff/8LIkY/i7DyUgIBbWLlyk7Edg6Ge559fTFDQrdjZDaJ790l89dUW4+s7dhykb9+7sbe/FmfnocTETKKsrOFWwzt3HiIycgIuLsNQq+OJiZnExo2JAMyfvwoHh8FYWPyL3r2n4u09EmvrATg4DKZXrynEx08nMHAUanU8rq7DefrpBcY+33vva9TqeLy8RjBjxlx8fW9CrY6nf//72Lv3CACPPjqPJ554j9Ons1Cp4ujSZUyz8y5njH/XXsPu0+WEh4/D1jYeF5dhPPXU+01+P5ezXpvz3ntfoSgKo0bFN5n/d+20Zh1ezu+okZubE9deG8v8+atojyf5JiQM5vvv32TNmm947bXXLr0hRYg2tmfPHkWlUimrVr2iKEpiu5uef/4excbGWvniixeV0tItSlLSCqVXr3DFw8NVyc1dpyhKovLcc9MUQNm6dYGi1W5V8vM3KPHxPRUHBzultnaXoiiJypNPTlJsba2Vb755XSkp2azMnj1NsbCwUPbvX6pUVPysODs7KHPnPqRUVf2i5OauUxISBisFBRsURUlUVq9+TXnxxXuV4uLNSlHRJiUuLlrRaFyMNb7wwr0KoOzd+6mi021XCgs3KiNGxCmAsnbtu0pBwQZFp9uuzJw5TgGUQ4e+MC47ffpoxcHBTjl6dJVSXb1TOXJkpdKnT6Ti5GSvZGZ+ryhKojJmzBClc2f/JuuluXmXM8bm2nvuuWmKSqVS3nlnllJSslmprNyhLFz4lAIoBw9+ftl9NjeFhvorkZEhTea11E5r1uHl/I4ap2efndpk7O1xmj//McXGxkY5ceJEs//fW7BctmREm1u4cCH9+kUzfvxwc5dynqqqGt5990sSEgYzefIIXFwciYnpzEcfPUNhYSmLF3/X5P39+3fH2dkBT09XJky4Dp2uiszMPKqra/nggzWMHj2YMWOG4OrqxJw5d2FtbcnSpT+Rnp5DWZmOqKhQ1GobvL3dWbPmDTw8Gu4NcvvtQ3nhhXtxc3PC3d2ZUaPiKSrSUlBQ2qT/yMgQ7O3VaDQuTJzY8D2GoCBvPDxcsbdXM3nyCADjVlgjKytLIiI6YWtrTWRkCB988BTl5ZUsXfpTq9fV5Y6xuXU/b94qhg/vw+OPT8TV1Qk7O9sm155r6z51uirS0rLp3Nm/yfzWtNPadXipvyOAsLBAAJKTT7f06zCbRx4ZS2CgNx999NElLS8hI9rczp2/kJBwrbnLaNaRI6lUVFRxzTURTeb36ROJjY21cXdIcxrviFlXpyclJYPKymqiozsbX7ezs8XHR8Px4xmEhvrj5eXG5Mkv8uKLS0hPz7lgXdbWDXdENBj+/iBwY/9/PlDcuFxd3YUPzl5zTQT29upmP+j+TluP8dSps1RWVjNsWJ8r1md+fgmKomBvr24y/2Lbgdatw4v9HTXWlZfXdsfC2pqFhQW33jqQnTt/ubTl27geISguLv7bvyzNrbS0AgBHR7vzXnN1daS8vLJV7eh01QDMmfMRKlWcccrIyKWysho7O1u2bVvIwIE9ePXVpYSGJjBhwhyqqmoAWLt2N4MHP4Cn5whsbeOb3Wff1mxtrSkoKGn1+y93jH919mw+AJ6ef/9vo637rK6uPTf2pgf8L7adRhe7DltiZ2fbpM72ytPTjaKioktaVkJGtLlOnTpx7Fi6uctolqtrw82dmguT0tIKAgK8WtVO4wflvHmPoiiJTaZff10CQFRUKD/++DbZ2Wt55pk7+eqrLbz99goyM3MZPfoZfHw07N37CVrtVubOfaiNRti8ujr9RY0PLm+MzWk8s6umpu6K9dn4Id7cFuLFtAOXtg5bUltb16TO9uro0TRCQkIuaVkJGdHmRo9OYPnyjeh0VeYu5TzR0Z1xdLTjt9+ONZm/d+8Ramvr6N27W6vaCQz0Rq224dChk82+np1dyNGjDd+a9vR05fXXH6RXr3COHk0jOfk0dXV6HnxwDKGh/qjVNiY/jXf79oYbvMXFRbd6mcsZY3OioztjYWHBjh0HrlifXl5uqFQqtNqmZ59dbDtwaeuwJVptw5a1t7d7m7XZ1vLzS/jvf3eQkDDmkpaXkBFt7uGHH6a21sCTT77f8puvMLXahieemMS3325n+fINlJXpSE4+zQMPzMXX14Pp029rdTt33XUzK1du4oMP1lBWpsNgqOfs2XxycgrJzi5gxoy5HD+eQW1tHQcPniAjI5e4uGiCgnyAhkucVFfXcvLkmQseC7oU9fX1lJSUo9cbSEo6xaOPziMoyIdp024GwN3dmezsQtLTcygvr6SuTn/ePEtLi0seY3N9uLo6cvvtQ/jmm2188skPlJXpSEo61eRki8tZr82xt1cTGupn3FXXqDXttLQO20JjXTExnVt4p3nU19czffobeHh4MmXKlEtr5FLOSROiJatXr1YsLCyUV1+doZj7FMy/TvX1vypvvfWIEhYWqFhbWylubk7K6NGDlZSUrxVFSVQWLnxKsbdXK4ASFhaonD69Rlm8+FnF2dlBAZTgYB/lxInVSk3NTuWZZ+5UgoJ8FCsrS8XT01UZM2aIcuTISiU9/Tulf/8Yxc3NSbG0tFD8/DyU556bpuj1exRFSVSeeeZOxd3dWXF1dVLGjh2mLFjwpAIonTv7K088cYex/06dfJWdOxcpb7zxkOLi4qgAire3u7JixUvKqlWvKN7e7gqguLk5KStX/j+l8fRba2srxd/fU7GyslScnR2U2267Vjl9eo1xHRw48LkSHOyj2NnZKgMH9lByc9c1O+9yxthce+XlPyv33XerotG4KI6OdsrAgT2U55+/RwGUgAAv5fDh5ZfVZ3PTzJnjFGtrK6WycodxXkvttLQO589/7LJ+R43TTTcNUPz9PZX6+l/N/v+iuf8nM2eOU2xsbJTt27e38n/+eZbLpf6FySxcuJBHHnmEBx8cw7x5jxrPshGmNWPGXFav3kpR0aaW3/wPcOrUWSIixrN06X+MpxO35Eqsw6IiLQEBt/DKKzN44ok7TNbPpaisrOauu17hv//dwfLlyxk3btylNiWX+hem89BDD7F69WqWLVtHXNy9HDmSau6S/jHMfYXf9qRLlwBefvl+Xn75EyoqWn+c0NTr8MUXl9CzZ1dmzrzkD3CTSEz8g9jYqWzdeoCNGzdeTsAAckxGmNiYMWNISkrGwcGDnj3vZPr0N8jOLjR3WeIf5tlnpzJ27DAmTJhjPNhuTu++u5JDh06wbt28drOFn5mZy/TpbzBw4HSCg8M4dOgwQ4YMuex2JWSEyYWGhrJ9+w6+/HIlmzcfIixsLP/+98J2c5nzq8ns2R+ydOlPaLUVhISM5ptvtpm7pHbj1VdnMHPmOF5//bMLvs/U6/D773+hpqaW7ds/xM3NqU3bvhSFhaX8+98L6dp1HDt2HGXlypVs3LiJgICANmlfjsmIK6q6upqFCxfy+uuvYTDUcQ8lcJQAACAASURBVOedI5gxI4HIyEs7B18IcWl+++0Yixb9l5UrN+Pq6sYLL7zIXXfdhZVVm25ZrZCQEWah1WpZtGgRixcv4vTpVOLjY5k+/TZuv30otrbW5i5PiKtSRUUVK1duYtGi7/j992NER0cxY8YD3HXXXdjbm+Q+OxIywrzq6+vZsmULixZ9xA8//IiLiyO33TaIhITBDB/ex3gtKCHEpamsrGbDhkS+/XY7P/64i9raOm6/fSzTp09n4MCBpu5eQka0H9nZ2XzxxResWfMNv/32O87Ojtx88wASEgYzYkTceRc5FEI0T6utYO3a3Xz77Q7Wr99DdXUtAwb0Z8yY25k8eTIajeZKlSIhI9qnzMxM/vvf//Ltt2vYvXsPtrY2DBrUk2HDrmHo0Gvo2TMMCws5b0UIaLjq82+/HWPr1t/YuvU39uxJor5eYciQwSQkjOG2227D29vbHKVJyIj2Ly8vjx9//JEtW7awbdtWCgoK0WhcGTKkN0OH9mbYsGvo2jXI3GUKccUoisKRI6nGUNmx4yBlZRX4+/sydOhwrr/+em666Sbc3NzMXaqEjOh4UlNT2bJlC1u2bGbz5s2UlmpxcXGiT58IBgzoTu/e3ejfPwaNxsXcpQrRJhqv87Z7dxK7dh0mMfEIhYUlODo6EBcXx/Dh1zF8+HB69epl8outXiQJGdGx6fV69u/fT2JiInv37iUx8VcyMjKxsLAgPLwT/fpF0LdvFLGxXYmKCsXJySRn0AjRZkpLy0lOPs2hQyfZu/cIe/ce5dSpTADCwjrTr9+/6Nu3L/3796dnz55YWlqaueILkpARV5+8vDz27t17bkpk//79lJWVo1KpCAnxp3v3zkRHh9K9exdiYroQFhaIpaUc3xFXVuMdVpOTT5OUdIrk5NMkJ6eSmdlwl053dzf69etH3779zv3seyUP2LcVCRlx9VMUhfT0dJKTk0lOTiYpKYnk5CROnjyFXq9HrbYlMjKUsLAAwsIC6No1iK5dgwgLC2xy/3khLkVBQSknTmRy4kQmJ0+e4eTJM5w4cZbjx9Oora3D2tqaiIhuREfH0L17d2JiYoiJiSEwMNDcpbcFCRnxz1VTU8ORI0dITk7myJEjnDx5khMnUjh9OpWamobb8Go0roSFBdK1ayBhYYF06uRLp06+BAV54+fniZVVu95VIa6A2to6zp7N58yZfDIyckhNzTaGycmTZ4yXT7KzUxMW1oWwsK507RpOdHQ0MTExdOvWDWvrq/b7YBIyQvxVfX09mZmZ50LnhDF8Tp48SWbmGWprG+7HbmlpiZ+fJ8HBPgQFeZ+bfAgM9CIoyAcvLze8vNzkVOsOTK83kJ9fQm5uEVlZBaSn53DmTB6ZmblkZuaTkZFLbm4h9fUNV2xWq20JDg6ma9eGIAkLCzNOAQEB7e2g/JUgISPExVAUhZycHDIyMsjMzCQzM5MzZ86Qnp5mfF5SUmp8v6WlJV5e7nh7u+Pn54GXlyv+/p54ebnj66vBx0eDRuOCRuOCu7tzu7ki79WspqaO4mItxcVlFBVpycoqID+/hJycQnJzi8nLKyYrq5D8/GLy84v580ekp6cHgYGBBAUFExzcMAUFBZ2bF4SPj48ZR9YuScgI0dYqKio4e/Ys+fn5ZGVlkZ+fT05ODrm5ueTl5ZKdnU1+fj75+QXGv4AbOTk54O7eEDgaTcPk7t44ueDkZI+rqyNOTg44OKhxdLTHxcXB+PyfcFUEna6KiooqdLoqSkrKjY8bn5eV6SguLjOGSHFx+bmfZRQXa9Hpmt5TpuEPAU98fLzx9fXDy8sbf39/vLy88PX1xcfHB29vbwIDA7GzszPTqDssCRkhzMVgMJCfn09RURHFxcVNpsZ5DT//93p5eTmlpdq/bdPCwgIXl4YQcnS0w87OFhsbaxwc1OdecwDAxcUBCwsLHBzssLGxwtbWpklAWVtb4ejY/Adq4zJ/VV1dS1VVTbPLlJdXotcbjM8rKiqpq9Mbl9HrDZSXVwJQUlLeZBmdrvpcsFRSUlL2t2NXqVS4urrg7OyMu7sb7u4aNBoP3N3dz5s0Go3xsZeXl+zSNB0JGSE6ovLycnQ6HRUVFWi1WsrKyozPy8rK0Gq16HQ6qqurqa6upqqqCr1eT3l5wwd4SUmxsR29Xk9VVRXV1dXG9isrK40nP/yVVlt23hYYNGwRODs3f38UtVrdZCvA3t4OW1s1NjY2ODg4nAtAVwBcXFzOBaADNjY22NnZ4ejoiJOTE66urjg4OODo6IijoyNubm7G5w4ODpe2MoUprZAdwEJ0QE5OTjg5mfeGV/v27aNfv36kpaXRqVMns9Yi2i/ZRhRCCGEyEjJCCCFMRkJGCCGEyUjICCGEMBkJGSGEECYjISOEEMJkJGSEEEKYjISMEEIIk5GQEUIIYTISMkIIIUxGQkYIIYTJSMgIIYQwGQkZIYQQJiMhI4QQwmQkZIQQQpiMhIwQQgiTkZARQghhMhIyQgghTEZCRgghhMlIyAghhDAZCRkhhBAmIyEjhBDCZCRkhBBCmIyEjBBCCJORkBFCCGEyEjJCCCFMRkJGCCGEyUjICCGEMBkJGSGEECYjISOEEMJkJGSEEEKYjISMEEIIk7EydwFCiPavurqaoUOHUl5e3mSejY0NI0aMwNra2jjfx8eHTZs2oVKpzFGqaGckZIQQLVKr1Xh4eJCYmIiiKE1eS0lJMT5WqVTExcVJwAgj2V0mhGiVSZMmtfgeRVFa9T7xz6FS/vpniRBCNKOyshIPDw+qqqr+9j2enp7k5ORgaWl5BSsT7dgK2ZIRQrSKvb09CQkJTY6//Jm1tTVTpkyRgBFNSMgIIVrtjjvuoK6urtnX6urqmDhx4hWuSLR3srtMCNFqer0eLy8vSkpKznstODiY9PT0K1+UaM9kd5kQovWsrKwYP348NjY2Tebb2Ngwbdo08xQl2jUJGSHERZk4cSK1tbVN5tXW1jJu3DgzVSTaMwkZIcRFiY+Px8/Pz/hcpVIRExNDZGSkGasS7ZWEjBDioqhUKiZNmmTcZWZlZcXUqVPNXJVoryRkhBAX7c+7zPR6PePHjzdzRaK9kpARQly02NhYOnfuDEBcXBwBAQFmrki0V3LtMiH+oUpLS1EUBa1WS319PWVlZRgMBgDKy8vR6/XnLVNfX49WqwWgd+/enD59mujoaFavXg2Am5tbs33Z2Njg4OAANHxp09HRESsrK5ycnLCwsMDFxcUUQxTtgHxPRogOora2lqKiIgoLCykqKqK0tJTy8nLjVFJSQllZ2Z/mlaHVatFqtej1erRaLYqiUFqqNfdQmqVSqXB1bQgbNzc3LC0tcXZ2xtXVFWdnF5ycnIxTwzxnnJ2djc81Gg0ajQYPDw+srOTv53ZihYSMEGaUl5dHXl4eZ8+eJS8vj+zsbIqKis6FSQFFRUUUFBRQUFBAeXnFecur1bY4OTng5GSPm5sTTk72TSZXV0ecnR2wtLTEzc0JABcXRywsVMb5Tk72WFlZ4uhoh7W1lbFdOzvbZmtuWK5hT/vLL3/C88/fA4Beb6C8vLLZZXS6KmprG64UUFNTR2VlNbW1deh01eeW02Ew1FNWpju3taSjrk5PeXklpaXllJXpKC+vpLy8ivLySrTaCrTaCsrLdcZ2/8zV1QVPT09j6Gg0Hnh4NEy+vr74+Pjg7++Pr68vGo3mIn9r4iJIyAhhKtnZ2aSlpZGWlkZGRga5ublkZWWRm5tzLlTym3zfxN5ejZ+fFx4eLnh4uKDRuJx77Iqnp+u55//76erqaAwFc9HrDVhZmfdaZTU1dZSWllNUpKWwsJSiIi0FBaUUFDQ8bpjf8DM/v4Tc3CKqqqqNy6vVtn8KHT/8/Bqm4OBgOnXqREhICN7e3mYcYYcmISPEpaqsrCQlJYXU1FRjmKSlNTxOT0+nuroGABsbawICvPHz88DPT4Ovrwf+/p7Gnz4+GgICvHBysjfziP45SkrKyc4uICeniOzsArKzC8nJKSQrq4CcnGLOns0nOzsfvb7hGJW9vR0hIZ0ICQk9N4UQEhJC586d6dq1K7a2zW/1CQkZIVpUUlJCamoqR44c4ejRo6SmnubIkT84fvwE9fX1ALi5ORMa6k9oqN+5yd/4PDjY17h7SXQsJSXlpKZmnZuyz/3MITU1i/T0bOPv39fXh6ioKCIjo4iKiiI0NJTo6Gh8fHzMPAKzk5ARopFer+fYsWMcPHjw3HSA5ORkiosbLgbp7OxIeHgwERHBdOvWMEVEhBAa6oeNTfOXvxdXr+rqWk6ePMPx4+mkpGRy9GgaKSlnSElJR6druOeOp6cHPXr0IDa2F7GxscTGxhIWFvZPuh2ChIz4Z9Lr9SQlJbF//34OHDhgDJTq6hrUaluio7vQq1cYPXqEER4eRLdunfD39zR32aIDUBSFzMw8UlIyOHYsncOHT3Lw4EmOHDlNXZ0eBwf7JsHTt29foqKisLC4Krd2JWTEP4NOp+PgwYPs3r2bXbt2smvXLkpLtTg5OdC9exeiokKIjAyhd+9u9OkTia2tbJmItlVXp+fEiUx+//34uSmFQ4dOoNNV4ejoQFxcHAMGDKR3794MGjToavnukISMuDpVVlayfft2Nm7cyC+/7CA5+Q8MBgOdOwcyYEAMAwZ0Z8CA7kREdLpa/4IUHYDBUE9y8il27TrMnj3J7NqVxJkzuVhbW9OrV0/i46/lhhtuID4+vqOeXCAhI64ex44dY/369WzYsJ6dO3dSU1NLz57hDB4cawwVHx/5ToRo386cyTOGzrZtv3P0aCoODvYMHTqUESNGMmLECEJDQ81dZmtJyIiOS1EU9u7dy8qVK/n+++/IyMjE3d2F667ry4gRcYwYESehIjq8zMxcNmxIZMOGRLZs2U95uY6wsC4kJIxh4sSJ9OjRw9wlXoiEjOh4kpKSWLVqFatWrSQtLZ1u3UIYO3YIN97Ynz59IuV0YXHVqqvTs3t3EuvX/8rXX28lPT2biIhuTJgwkYkTJxIWFmbuEv9KQkZ0DBUVFXz22Wd8+OEHHDlylKAgXyZMGM7EidfRs2dXc5cnxBWnKAqJiX+wcuUmVq/+mdzcQvr0uYYHH3yIiRMntpdjOBIyon3LzMxkwYIFLFnyMTU1NUyefANTptxI//4xqFQqc5cnRLtgMNTz88+/s2zZWlav3oqbmxsPPPAgM2bMMPclcSRkRPuUmprKnDlzWL16Nd7e7jz00Bjuv/82NJqr4rROIUwmO7uQhQu/YfHi7ykv1zFlylReeuklfH19zVGOhIxoX8rLy3nttdeYN28eoaF+zJkzjbFjh5n9QpBCdDRVVTUsX76BV19dRlFRGbNnP8djjz2GWq2+kmWskCOkot1Yvnw54eFdWbz4Q9588yEOH/6CO+644YoGzNtvr8DLawQqVRwfffSt2ft9+eVPiIycgLPzUGxt4+nSZQxPP72Aiooqk9Wybt0eXFyG8eOPu0zWh6lt2bKfZ5/9wKw1/PDDTubO/QKDod4s/dvZ2XLffbdy7NgqnnlmMq+++v+Iiorkp59+uqJ1SMgIs6uoqGDy5MlMmTKF0aMHcOLE18ycOc4sWy9PPjmJPXuWtJt+t237jYcfHkt6+ncUFm7ktdceZP78VYwd+6zJaunoOzdeeOFj3nvvK2bPnmbWOkaNikettmHYsIcoLS03Wx12drbMmXMXKSlf869/hTNq1ChmzZrV5DYTpiQhI8yqqKiI4cOHsWnTOtavn8fChU/JcZc/cXS0Z/r00bi7O+PkZM+4ccMYPfpaNmxI5MyZvMtuv6qqhv7972sy76abBqDVbuWWWwZedvuXWsOleuONz1m1ajNff/1au7h1wqxZ4+nRI4wbb3zceNsAc/H392T58hdZseIlli79hFGjbkGn05m8XwkZYTaVlZWMGHEDeXln2b17MTfcEGfuktqdn35657zv/Xh4uAJQWVnd3CIX5ZNPfiA/v/iy22kPNZw6dZb//GcRL710H2q1TRtU1jZefPE+Dh06wfz5q8xdCgATJ17Ptm0LOHBgP2PGJKDX603an4SMMJuHH36Y9PRUNm9+j7CwQHOXc0EGQz3PP7+YoKBbsbMbRPfuk/jqqy0ARESMR6WKw8LiX/TuPdX44f/00wtwcRmGWh3PsmVrL9jGxcjKKsDOzpaQEL8WawPYseMgffvejb39tTg7DyUmZhJlZToefXQeTzzxHqdPZ6FSxdGlyxh27TpMUNCtqFRxLFiwGoD581fh4DDYOD5v75FYWw/AwWEwvXpNIT5+OoGBo1Cr43F1Hc7TTy9oUu/OnYeIjJxgXBcxMZPYuDERoNkaWjOm5rz33lcoisKoUfFN5v/d+N9772vU6ni8vEYwY8ZcfH1vQq2Op3//+9i790ibjB3Azc2Ja6+NZf78Ve1mV+Q110Swfv08du3ayQsvvGDSviRkhFns27ePZcuWsWjRM3TpEmDuclr0738v5M03v2DevEfJyVnLLbfEc8cdz/Pbb8f444+VdOrkS2CgN/v2LcXevuHsnTfffJh77hnFG288xLRpN12wjdaqrKxm27bfuO++W433sLlQuzpdFaNGPcnttw+huHgzJ09+Q9eugdTW1jF//mPccstAOnf2R1ESOXVqDQMH9mDPno+b9PnooxN46qnJKIrChx8+Q1raf8nNXcegQT05ePAEzz47lYMHP6e4eDNTp97IW28t5/Dhk8bl8/KKGT9+OOnp35GdvRZHRzsmTWr4YGuuhpbG9HfWrt1DeHiwcf0DFxz/zJnjmDbtZiora5g1azzp6d9x4MDn6PUGrrvuEc6cybvssTeKjQ0nK6ug2dfMpXfvbsyd+xBvv/02p0+fNlk/EjLCLJYsWUJsbDgJCYPNXUqLqqtr+eCDNYwePZgxY4bg6urEnDl3YW1tydKlP2FpacGsWePJzMzl229/Ni5XWVnNmjU/c/fdt7TYRmu99toyfH09eOWVGa2qLT09h7IyHVFRoajVNnh7u7NmzRvGXW4XKzIyBHt7NRqNCxMnXg9AUJA3Hh6u2NurmTx5BADHj2cYl7n99qG88MK9uLk54e7uzKhR8RQVaSkoKG22j0tZVzpdFWlp2XTu7N9kfmvGb2VlSUREJ2xtrYmMDOGDD56ivLzyvL4uZeyNGrfUk5NN92F+KWbMSMDLy41ly5aZrA8JGWEWv/66mxtv/Je5y2iVlJQMKiuriY7ubJxnZ2eLj4/G+IFy77234uLi2GS/+/LlG7jttkE4Ozu0qo2WfPvtdr7+eisbN/6f8aB2S+2Ghvrj5eXG5Mkv8uKLS0hPz7msdfFnjVtSfz6g3XhGYF3d3+/nb3yPwdD8gfBLWVf5+SUoitJkKwa4pPFfc00E9vbqC/5eLnbsjXXl5Zn3+NdfWVpaMHJkHL/+usdkfUjICLMoKSnF3d3Z3GW0ik7XcIxlzpyPUKnijFNGRq7x+Iujox33338be/Yks2/fUQA+/PBbZs4c3+o2LmTVqs288cbnbN/+IZ06/e+b2y21a2dny7ZtCxk4sAevvrqU0NAEJkyYQ1VVTdutoBasXbubwYMfwNNzBLa28c0et/izS1lX1dUNp+Pa2jY94H+p47e1taagoKS1Q2yRnZ1tkzrbE43GhZIS04WfhIwwi8DAQE6ePGPuMlrF07Nh18q8eY+iKIlNpl9//d93Wxq/2zNv3kp++eUggYFext03rW2jOe+/v5rlyzewbdtC/Pw8Lrq2qKhQfvzxbbKz1/LMM3fy1VdbePvtFW2zclqQmZnL6NHP4OOjYe/eT9BqtzJ37kMXXOZS1lXjh3hzW0cXO/66Oj2lpRUEBHi1dpgtqq2ta1Jne5KSkklQULDJ2peQEWZx88238M0329HpTPfN9bYSGOiNWm3DoUMXPmgbEODFuHHD+OabbfznP4t59NEJF93GnymKwjPPLCQ5+RTfffcmjo52F11bdnYhR4+mAQ0f3q+//iC9eoUb55lacnLDfe0ffHAMoaH+qNU2LV7Y9FLWlZeXGyqVCq226fc+LmX827cfQFEU4uKiW91/S7TaCgC8vd3brM22kJdXzIYNidx88y0m60NCRpjFfffdh17fcJpqe6dW23DXXTezcuUmPvhgDWVlOgyGes6ezScnp7DJe594YhJ6vYGSkjKGDr3mktpodPRoGm+++QUff/w91tYDmuw6UqniePvtFS22m51dwIwZczl+PIPa2joOHjxBRkau8QPU3d2Z7OxC0tNzKC+vvOCxlEsRFOQDNFzmpbq6lpMnzxhPD2701xosLS0uel3Z26sJDfXj7Nn8JvNbGj9AfX09JSXl6PUGkpJO8eij8wgK8mHatJvbbD001hUT07mFd15Zjz02H09PTyZMmNDymy+VIoSZLFu2TFGpVMqyZf9RFCWxXUzvvDNL8fZ2VwDFwcFOSUgYrChKolJTs1N55pk7laAgH8XKylLx9HRVxowZohw5svK8NoYM6a0sWTL7vPkXaqO5fpOTVyjA305vvfVIi+2mp3+n9O8fo7i5OSmWlhaKn5+H8txz0xS9fo+iKInKgQOfK8HBPoqdna0ycGAPZc6cuxQfH40CKPb2amXUqHhl/vzHFHt7tQIonTr5Kjt3LlLeeOMhxcXFUQEUb293ZcWKl5RVq14xjsHNzUlZufL/KYqSqDzzzJ2Ku7uz4urqpIwdO0xZsOBJBVA6d/ZXMjO/P6+G3Nx1F7W+G6eZM8cp1tZWSmXlDuO8lsY/ffpoxdraSvH391SsrCwVZ2cH5bbbrlVOn16jKEriZY+9cbrppgGKv7+nUl//q9n/jTdOc+c+pFhaWirr169v1f/XS7RcrsIszGr27NnMnTuXBQue5IEHEsxdjujATp06S0TEeJYu/Y/xdOKWzJgxl9Wrt1JUtMlkdRUVaQkIuIVXXpnBE0/cYbJ+WktRFF566RNefvkT5s+fz8yZM03Z3Qq5frowq9deew0HBwceeug/7Nt3lAULnsDB4fxjD0K0pEuXAF5++X5efvkTbrvt2maPYTXH1FdJfvHFJfTs2ZWZM8eZtJ/WKCrSctddr7B+/a8sWrSI++5rm2vGXYgckxFm99xzz7Fp0ybWr99H167j+Pzzde3m8huiY3n22amMHTuMCRPmGA+2m9O7767k0KETrFs3z6z3RKqvr+fzz9cRGTmRgwdT+fnnn69IwICEjGgnhg8fzpEjR7n99oncffer9Ot3L7/+mmzuskQH9OqrM5g5cxyvv/7ZBd83e/aHLF36E1ptBSEho/nmm21tWsf33/9CTU0t27d/iJubU5u2fTG2bz9Ar17TuPfe15kwYTJ//HGEgQOvzBW2AeSYjGh3Dh48yKxZM9m9ew833zyQWbPGNTlTSwhxYfX19axbt4f5879i69b93HTTjbz77jy6du16pUuRO2OK9ic2NpYdO35hzZo1lJTUM2zYw/TocSeffvpju/zGtBDtRXl5JQsWrKZbtwmMGvUUVlZubNmyhZ9+WmuOgAFkS0Z0AAcOHGD+/Pl89dVXuLg4Mn78MCZMuI7+/WNa/GKfEFc7g6Gen3/+nZUrN7FmzXb0egN33jmFWbNm0a1bN3OXt0JCRnQYOTk5fPrpp6xc+SVHjhwlONiP8eOHMXHidfTsaZ6/0oQwB0VRSEz849xdQLeRm1vINdf05o47JjF16lTc3dvNlQUkZETHlJSUxMqVK1m1aiXp6RmEhQUxcmQcI0f259prY9vlNaKEuBzl5ZVs3bqfDRsSWb8+kczMHCIiujFhwkQmTpxIWFiYuUtsjoSM6Nga/qJL5LvvvmPjxg0cPpyEnZ2aQYNiGTGiHyNH/ovwcNNd/E8IU1EUhaSkU2zYkMjGjXvZtesQBkM9vXv3YsSIkSQkJNCzZ09zl9kSCRlxdcnPz2fHjh38+OOPrF37E8XFJXh7a+jTJ4KBA3swYEB3+vSJxNbW2tylCtGEXm/g8OGT7Np1mN27k9i+/SAFBcV4eGgYMmQow4cP5+abb8bPz8/cpV4MCRlx9TIYDOzbt4+dO3eye/du9uzZTWFhEQ4OdvTtG8XAgd2Ji4smNrYrvr4eLTcoRBvKzMzl4METJCb+wa5dSfz22zGqq2vw8fFmwIABDBwYz6BBg+jZsycWFh32RGAJGfHPoSgKx48fZ/fu3ezatYs9e3Zz8uQpAHx8POjZM4zY2K7npnA6d/aXs9fEZTMY6jl58gwHD6Zw8OAJ41RUVIpKpSIiohsDBgxk4MCBDBgwgM6d29eVmi+ThIz4ZyspKeHgwYMcPHiQQ4cOcfDgAY4fT8FgMODs7EhMTGciIoLp1q0TERGd6NYtmE6dfDvyX5bCRPR6A6mpWRw7ls7x4xmkpGRw9Gg6f/xxGp2uCmtrayIjI4iN7UVsbCyxsbH06NEDZ+eOcYfYSyQhI8RfVVVVkZSUxMGDB0lOTiYl5TjHjh0jO7vh/vBqtS3h4Z0IDw8kIqITXboE0KmTLyEhfvj5ecjWz1XMYKgnKyuftLQc0tOzOXHiDCkpGRw7lsGpU2eora1DpVIRFBRAeHg3IiIiiYmJoWfPnsTExGBjY9NyJ1cXCRkhWkur1ZKSksKxY8c4fvw4x48f59ixo6SlpVNb+797zAcHNwROp04+5376EhzsQ0CAF97e7ma9UKK4sJqaOnJzi8jKKiA9PdsYJg0/c8nMzDHe2E2ttqVz585EREQSHh5OREQE3bp1Izw8HEdHRzOPpN2QkBHictXX15OdnU1aWppxSk9PJy0tlfT0dM6ezTLee16lUuHtrcHX1wN/fw98fTX4+Xni7++Jr68GHx8NXl5uaDQucsuDNlReXklRkZb8/BLy8oo5ezaf3Nyicz+LOXMmn7y8IvLzi43LWFtbExgYQKdOnQgJCSUkJOTc4xBCQkLw9fU144g6DAkZIUytrq6OrKwssrKyyMnJITs72/g4w95iHwAAIABJREFUK+vsuZ9ZlJWVN1lOrbbFw8MVjcYFDw9XPD1d0GhcjM9dXBxwcrLHyckBNzenc48bnrf2XiodSVmZjvLyynOTDq1Wh1ZbQXl5JVptBUVFWgoLSyks1FJQUEpRURlFRVqKikqpqWl6zTs3N1f8/Hzx8/PH19ePgIAAfHx8mvz08/PD0tLSTKO9akjICNFeVFZWkpOTQ2FhIYWFhRQVFRmngoKCc/MLKCoqpKioGK1WS1VVdbNtqVQqXF2dcHZ2xMnJHltbaxwc7LCxscLe3hZbWxvs7GxRq21Qqxse29hYN9l6srdXN/t9Iltba+zt1efNr6ioMu5K+rOqqpomFzatqKikrk6PTldNbW0dlZXV1NTUGd9XXV1rfNwYKCUlZX+73hwc7HFxcUGjcUej8cDDwxNPT080Gg0eHh5oNBrj5OX1/9m787ioyv2B458BBmaGddh3EVA2cQlK3Pc2l1zKpbq51dWbpZbdbM+yumretEVbbmbX9JdLei3UW6bmljuCCQgKgsgm+zosA3N+fyBzJRBBgUF43q/XeTGeOed5vmdGzpfnPOc8jyNOTk4olR0vCbdTIskIwt2sqqqK4uJi8vPzKSoqori4WL8UFhZSUFBAcXExWq2W4uJiqqqqKCkpQavVUlpawvHjJ3Bzc8XMzIzy8rI6SauwsBCdrv6skaWlGn0f1I0UCrMGT94mJiZYWv5vPhWVSomZmYKysjKys7Pp27cvSqUKMzMzVCoVcrkcCwsLzMzMsLS0xMrKChsbG6ysrLC0tNQvNjY2WFtbizv92jeRZAShs0pMTMTX15fjx48TFhbW7P1PnTpF3759SUpKwsvLq9n779y5k4kTJ1JQUNDRb+PtzMR8MoLQWUVFRWFsbExwcLBB6u/duzeSJHH+vJgBtSMTSUYQOqmoqCi6d++Oubm5Qerv0qULarWaqKgog9QvtA2RZAShk4qOjjZYKwZqbk7o0aMHMTExBotBaH0iyQhCJ3Xp0iX8/PwMGkP37t25dOmSQWMQWpdIMoLQCel0OhITEw0+0VW3bt1EkungRJIRhE4oJSWF8vJygyeZ7t27c/XqVcrKygwah9B6RJIRhE7o8uXLAAYfVt7X1xedTkdSUpJB4xBaj0gygtAJXb16FYVCgb29YSdrc3d3ByA1NdWgcQitRyQZQeiE0tLScHMz/KRsarUac3Nz0tLSDBqH0HpEkhGETigtLU3fijA0Nzc30ZLpwESSEYROKD09HVdXV0OHAdQkmfT0dEOHIbQSkWQEoRPKycnBwcHB0GEAYG9vT05OjqHDEFqJSDKC0Anl5uZia2tr6DAAsLOzIy8v79YbCnclkWQEoRPKy8vDzs7O0GEANUkmNzfX0GEIrUQkGUHohPLz81Gr1YYOAwBbW1vRkunARJIRhE5Gq9VSWVmJhYWFoUMBwNzcHI1GY+gwhFYikowgdDK1s1qampoaOJIacrm8wZk2hY5BJBlB6GRqT+hyudzAkdQwNTUVSaYDE0lGEDqZ9taSMTU1RavVGjoMoZWIJCMInUx7SzJyuRydTkdVVZWhQxFagUgygtDJ1LYa2tPlMkBcMuugRJIRhE6mPbZkQCSZjkokGUHoZNpbkqmNQ/TLdEwiyQhCJ1N7MjcxMTFwJDVES6ZjE0lGEDqZ9tYHUlFRAYCZmZmBIxFag0gygtDJ1D7pX1paauBIatQ+7W9ubm7gSITWIJKMIHQytSfz9pJkSktLMTIyQqFQGDoUoRWIJCMInUx7TDIqlcrgU0ELrUMkGUHoZFQqFUZGRu0qyYhLZR2XSDKC0MnIZDKUSqVIMkKbEElGEDohc3NzkWSENtE+bpQXBKFNmZubU1RUREJCAomJifplxowZBAcHt1q9x44dY+fOnfj4+OgXkWQ6NpkkSZKhgxAEofUkJCQQHR2tTyjx8fGcPXuW4uJidDodAEZGRuh0OtLS0nB1da1XRnl5OcOHD6e4uLjOupSUFLp27VpnHDRnZ2f27t3bYEd+VFQUffr00dcHYGxsjLW1NSEhIXTv3l2ffHr16kWXLl1a+uMQ2tYm0ZIRhA4uPDycF198UZ8IGhq+RafTYW9v32CCAVAoFNjb23PixAn+/HdpfHy8/rVMJiMsLOymd4oFBQXVmz+murqavLw8fv31Vw4dOqQfkXnjxo0iyXQAok9GEDq4uXPn4uDgQFVV1U3HBzMyMuK+++5rtJwnnnjilnVJktTodnK5vNHLcZWVleh0Orp168a0adNuWZ/Q/okkIwgdnFKp5O233270ORQTExPCwsIaLWfs2LG3fGDSwcGBQYMGNbpNv379Gh2cU5IkPvjgA4yMxOmpIxDfoiB0As888wyurq43TTSVlZWEhIQ0WoZKpWLixIk3nYdGLpfz1FNPYWxs3Gg5ISEhN52gzNjYGD8/PyZOnNhoGcLdQyQZQegETE1NeeuttxptzYSGht6ynMcff/yml9y0Wm2TLnGFhobqO/3/rLq6muXLl4tWTAci7i4ThE5Cq9Xi6+tLampqvZO8s7MzGRkZtyyjqqoKR0dH8vPz673XpUsXkpOTb1lGdXU1FhYWlJeX11lvbGxMUFAQUVFRYoiZjmOT+HNBEDoJuVzOu+++W+/uMCMjo1v2x9QyMTFhypQp9fpUTE1NmTFjRpPKMDY2plevXvXW17ZiRILpWESSEYRO5Mknn8THx6fO5SgTExPuvffeJpcxbdq0enPRVFZWMnny5CaX8efOf2NjY+69914efPDBJpch3B1EkhGETsTY2JilS5fWac1UVlY2qT+m1qBBg+o8TyOTyQgODiYwMLDJZfy587+6upply5Y1eX/h7iGSjCB0MpMnTyYgIEB/F5hMJrvlnWU3kslkPPHEE/qWiImJCdOnT29WDDd2/tfePj18+PBmlSHcHUSSEYROxsjIiKVLl1JdXQ2Aq6srdnZ2zSrjxktmVVVVTJkypVn7d+/eHZVKpd9/xYoVzdpfuHuIJCMIndCECRPo3bs3UNM/0lx9+vTBx8cHgLCwMNzd3Zu1v5GREX369AFg+PDht3yAU7h7ibHLBKET0Wg0VFRUUFVVxbx58/QPaUZERAA1tzmXlJTcdP/S0lJ9CyYkJITExER69OjBtm3bADAzM9O3UBpiZWWlv0zn4+PD77//zrx588jNzdVPwaxUKlvqcIV2QDwnIwjtUEFBAfn5+eTn55OXl0dxcTEajYbS0lIKCgrQaDRoNBoKCwspKSlBo9FQUlJMYWEhGk0pZWXlVFRUoNFoAMjPLzDwETWPkZER1tZWAFhYWCCXyzE3N0elUmFpaYmVlTUqlQqVSoVarda/trKywtLSUr+dWq1GrVZja2uLlZWVgY+qUxKjMAtCa6qsrCQ7O5usrCwyMzPJzs4mOzubvLw88vLyrieS//3My8snP7+g3rMsAKamcszNldjYWKJUmqFSKbCxscDcXIFKpcDR0RJLSydUKgXm5kpMTIyxtKxpVVhbW2BkJEOhMEOpNMPISIa1tQWnTsUQGhqAnZ21vh4bG8ubPqtiamqCufn/WhrvvruOt96arf93SUkZWm3DQ8bodDoKC//XSkpISCU7uwB//y7k59dMIaDRlFNRUUlVVTXFxTUJsqiolOpqHcXFpZSVVVBSUkZhYRGFhdlkZFRQUFCMRlOBRlNOUVEJxcWlVFVV16vf2NgYtdqmTuJRq23r/NvBwQFHR0ecnZ31r01MxGnyToiWjCDchoKCAlJTU0lJSSE1NZWMjAyys7PJzMwkK+sa2dnZXLt2rV4LQqlU4OCgxtbWCrXaEltbS9RqS9Rqq+s/LbG1tda/VqutsLW1wtJShYlJ42OCGUJVVXW7jKuyUktxsYb8/GLy8orIzy8iP7/4+lJ0fV2xfsnLKyYvr5Ds7HwqKuo+A2Rvb4ejoyMODg44O7voX7u5ueHm5oaHhweenp5YWFgY6GjbtU0iyQjCn1RWVpKUlERSUhJpaWlcvXqVlJQU0tJS9YmlpOR/UxdbWVng5uaIg4MNjo42ODvbXX+tvv5ajaOjGhcXeywsRH9De1dYWEJmZi7Z2QVkZeWTkZFDdnYB2dn5ZGTkXn9dwNWrmWg0/xsax9raCnd3Nzw9u+Du7oG7uzuenp64u7vTtWtXPD09bzq4aAcmkozQOZWXl5Oenk5MTAyxsbFcvnyZy5cTuXz5MleupOhv71UozHB1dcDFxQ5XV3u8vV1xcbG//tpN/1ronMrKKsjIyOHy5XTS07PJyMjl8uU00tNzycjIJSHhKoWF/5tN1MXFmaCgILy9ffD29tYv3bp166h9RiLJCB1bWloasbGx+mQSExNNfHw8ubl5QM11eg8PJ3x83PHxccXHxw1vbzd8fNzx9nbF2lpcAhHuTG5uIUlJ6SQmppGYmHr9Z82Slpal739zcnLE39+fgIBAevToQUBAAD169MDR0dHAR3BHRJIROoaCggIiIiKIjo6+nlBiiImJoaCgEAAHB1t69PAmIKALAQFe15OKG15eLpiadrpLGEI7UV5eSVJSOgkJqSQmpnLhQjKxscnExFwmP78IADs7W3r06EFgYBBBQUEEBwfTp08fLC0tDRx9k4gkI9x9iouLOXfuHBEREdeX08TFXUSn06FWW+Ht7UZgoBchIf4EBXkTFNQVFxdxSUu4u+TnFxMTc5nY2KTrP69w/nwC167lAjWX3kJCQgkJCSEkJIQBAwZga2tr4KjrEUlGaN90Oh0xMTEcPHiQY8eOERFxhoSERCRJwsXFgZAQP0JC/AkJ8Sc01F8kE6HDS0nJJCIijoiIOM6ciSciIo6cnHyMjIzw9/cjJCSUgQMHMnjwYPz9/Q0drkgyQvtSXV3NuXPnOHToEIcOHeTIkSPk5eVjbW3JgAE9CQ2tTSgBosNdEK67ciWTM2cuEBERx+nTFzh+/DylpWU4OzsxePAQBg8ezJAhQwgKCmrr+XpEkhEMLz09nV27drF79y4OHTpEYWERdnY2DBzYi6FD+zB4cB969eqGsbEYak8QmkKrreLMmQscPhzF4cNRHD16jqKiEuzt7Rg2bDhjxozh4Ycfxt6+1f9QE0lGaHuSJBEZGcmuXbsID/+JiIizKJUKRo68l1Gj7mXIkHsICuoq5nkXhBZSXa0jMjKew4ej+OWXExw6FElVVTVhYX0ZO3YcY8eObdZ8QM0gkozQdmJiYvjmm2/YunULqalpuLk5MmbMAMaOHcjw4aEolWaGDlEQOoXiYg17954kPPwoe/YcJzs7Dx8fbx5//AmmT5+uH2G7BYgkI7SugoICNm/ezPr133Dq1Gm6dnXjL395kHHjBnHPPX5iPndBMLDqah0nT8awc+chNm36hYyMHAYPHsSsWbOZNGkS5ubmd1K8SDJC64iMjOSjjz5i+/YfkMlkTJw4lFmzxjB06D0isQhCO1VdrePnn4+zfv1uwsOPYGZmxrRpj/Piiy/i5+d3O0WKJCO0rOPHj7Nkydvs3fsrvXp159lnJzJlykjx5Lwg3GVycgrYtOkX1qzZTmJiKuPHP8KSJe8QHBzcnGI2iZ5VoUVcvnyZSZMm0r9/f8rKcvj559VERv6bv/51vEESzMqVm3B0fBCZLIwvvthh8HrffXcdgYFTsbIajpnZIHx9J/Hyy59RUlLWZrG1lj17jmFtPYLw8KOGDuW27dt3mldfXWvQGH766QjLl39HdbXOoHHUsre3YcGCKcTFbWbr1vdJSoqld+/ezJw5k8zMzCaXI5KMcEd0Oh0fffQRwcE9iIs7x65d/+Tw4c954IEwg14We+mlJzh27Ot2U++BA2d47rnHSE7eSU7OL3zwwbOsXr2Zxx57tc1jbGl3+8WQt9/+F598soXXXpth0DjGjRuEQmHKiBHzKCgovvUObcTIyIhJk4YREfEtGzcu4eDBvQQGBvDtt982bf9WjU7o0AoLCxk//hFeffUVXnnlL0RG/pvRowcYOqx2ycJCxZw5E/Rzw0yePIIJE4bw888nuHr1mqHDa7Kysgr693+mzrrRowdQWLifsWMHGiyG27Vs2QY2b/6VrVs/0E/wZkgLFkyhV69uPPzwiw1OvGZIMpmMadPuJzp6E9OnP8js2bOZMWMG5eXlje4nkoxwWwoLCxk1aiQRESc5eHAtb745Sww02Yhdu/5Z72FSe3sbgDpzkrR369b9RFZWXoeIISEhlTff/JJ33nkGhcK0BSJrGUuWPENU1EVWr95s6FAaZG6uZNWqheze/RE//fQf7r9/FKWlpTfdXiQZodmqq6sZN24smZmpHD36Jf36Nasj0KCqq3W89dZXeHo+glI5mJ49n2DLln0ABARMQSYLw8ioHyEh0/Un/5df/gxr6xEoFIP49tvdjZbRHGlp2SiVZnTt6qpf9913/yU0dAYKxSDMzYfi5TWepUu/AWouS3300fcEBEzBzGwQavUoxo9/mbi4KwCsXbsdc/OhqFRD+PHHwzz00EKsrIbj7j6W77/f26TPAODQoUjuu28WKtUQrKyGExz8BEVFpSxcuIpFiz4hMTENmSwMX99JHD16Dk/PR5DJwvjss20ArF69GXPzofrP0cnpIeTyAZibD+Wee55i0KA5eHiMQ6EYhI3NSF5++bM6n8uRI1EEBk7Vf+bBwU/wyy8nABqMoSnH1JBPPtmCJEmMGzeozvqbHf8nn2xFoRiEo+ODzJ27HBeX0SgUg+jf/xlOnoxpkWMHUKstGTKkD6tXb27XlyIffDCM335bQ2xsNDNnzrjpdiLJCM322WefcfLkSXbtWlnnBHk3eOWVNaxY8R2rVi0kI2M3Y8cO4vHH3+LMmQtER3+Pl5cLHh5OnDq1HpVKAcCKFc8xe/Y4li2bx4wZoxsto6k0mnIOHDjDM888om8Brl69maeeeodHHx1OevpuUlPDee21GcTH1ySRJUu+5tVX1/L66zPJyvovhw9/wdWr1xg0aA7XruXx7LOTeOGFqZSVVWBpqWLLlvdJTNyBt7cbzzzzD7Taqlt+BqWlZYwb9xKPPjqMvLxfuXTpB7p396CyUsvq1S8wduxAfHzckKQTJCRsZ+DAXhw79q86x7Zw4VT+/vcnkSSJzz9fTFLSf8jM3MPgwb2JjLzIq69OJzJyA3l5vzJ9+sN8+OFGzp27pN//2rU8pkwZSXLyTtLTd2NhoeSJJ96+/hnVj+FWx3Qzu3cfw8+vi/57Bho9/vnzJzNjxhg0mgoWLJhCcvJOzp7dQFVVNaNGPc/Vq9fu+Nhr9enjR1padoPvtSe9enVj27b32b59B1u2bGlwG5FkhGaprq5m1aqPeO65R+nZ09fQ4TRLeXkla9duZ8KEoUyaNAwbG0veeGMmcrkx69fvwtjYiAULppCSksmOHb/p99Noytm+/TdmzRp7yzKa6oMPvsXFxZ733psL1Iw19c476xg2LIRXXnkKW1sr1GpLZs8ex733BlJWVsFHH/0fEycO5cknH8Ta2oLgYB+++GIxOTkFfPXVzjrl9+/fEysrcxwcbJg6dRSlpWWkpFy7ZfzJyRkUFZUSFOSNQmGKk5Mt27cv01/aa67AwK6oVArs7KyZNu1+ADw9nbC3t0GlUvDkkw8C6FtjAI8+Opy3334atdoSW1srxo0bRG5uIdnZBQ3WcTvfSWlpGUlJ6fj4uNVZ35TjNzExJiDACzMzOYGBXVm79u8UF2vq1XU7x16rWzcPAM6fT7z5h9tODBsWwrRp97Ny5YcNvi+SjNAsSUlJXLmSwtSpowwdSrPFx19BoymnR4//DZmhVJrh7Gyn/0V/+ulHsLa2qHM9fOPGnxk/fjBWVuZNKuNWduw4yNat+/nll4/1nc1//JFAQUExDzwQVmfb2sQXE3OZkpIyQkMD6rx/772BmJrK9ZdrGlLbUtJqq24Zv7e3G46Oap58cglLlnxNcnJGk46pKWrjuLFDWy430cd2M7Xb1E6J/We3851kZeUjSVKdVgxwW8cfGhqASqVo9Ptv7rHXxnXtmmH7v5pq2rRRnDkTQXFx/bviRJIRmiU3t2bCJEdHtYEjab7S0po+ljfe+AKZLEy/XLmSqe9/sbBQ8te/jufYsfOcOhULwOef72D+/ClNLqMxmzf/yrJlGzh48HO8vFz064uKajpObWwafqaooKBEH9+f2dhYUFysaZHPQKk048CBNQwc2Iv331+Pt/dEpk59g7KyiiaV3xJ27/6doUP/hoPDg5iZDWqw3+JGt/OdlJdXAmBmVrfD/3aP38xMTnZ2flMP8ZZqx/GrjbO9qz0f5OTk1HtPJBmhWbp27YpMJiM6+rKhQ2k2B4eaSx6rVi1Ekk7UWY4f/9+zLfPnT0YuN2HVqu85fDgSDw9H/WWVppbRkE8/3cbGjT9z4MCaenPh1P47J6ewwX1rk09DyaSgoAR396bNA9+U+IOCvAkPX0l6+m4WL/4LW7bsY+XKTU0q/06lpGQyYcJinJ3tOHlyHYWF+1m+fF6j+9zOd1J7Em+oddTc49dqq5r1HTRFZaW2Tpzt3R9/JGBmZoa7u3u990SSEZrF0dGRoUOH8PHHDXfytWceHk4oFKZERTXemeru7sjkySP44YcDvPnmVyxcOLXZZdxIkiQWL17D+fMJ7Ny5osHWiJeXK7a2Vuzde7LBMnr08MHCQlmvI/vkyRgqK7WEhDRtBsRbxZ+enkNsbBJQc/L+xz+e5Z57/PTrWtv584lotVU8++wkvL3dUChMb/lQ7+18J46OamQyGYWFdW+9vZ3jP3jwLJIkERbWo8n130phYU3L1cmp3U2nXE9VVTVr1mxnwoQJyOX1H2MQSUZotqVL32P//jOsWfODoUNpFoXClJkzx/D993tZu3Y7RUWlVFfrSE3NIiOjbjN/0aInqKqqJj+/iOHDQ2+rjFqxsUmsWPEd//rXj8jlA+pc0pHJwli5chNmZnJee20Ghw9HMn/+P0lLy0an01FcrCE2NgmFwpRFi55gx46DbNz4M0VFpZw/n8jf/rYcFxd75swZ3yKfQXp6NnPnLicu7gqVlVoiIy9y5Uqm/gRqa2tFenoOyckZFBdrGu1LuR2ens5AzTAv5eWVXLp0tV5/059jMDY2avZ3olIp8PZ2JTU1q876Wx0/1IxykZ9fTFVVNX/8kcDChavw9HRmxowxLfY51MYVHNxiQ+63miVL/kVc3BXeeuuthjeQBOE2vP/++5KRkZG0fv2bkiSdaHfLP/+5QHJyspUAydxcKU2cOFSSpBNSRcURafHiv0iens6SiYmx5OBgI02aNEyKifm+XhnDhoVIX3/9Wr31jZXRUL3nz2+SgJsuH374vL7szz57SQoO9pEUClNJoTCV+vTpLq1Z83dJkk5IOt1x6cMPn5e6dfOQ5HITSa22lCZMGCrFx2+VJOmEtGbN3yWVSiEBUrduHlJi4nbpq69elayszCVA6tLFWbp4cVuj8Scn75T69w+W1GpLydjYSHJ1tZdef32GVFV1TJKkE9LZsxukLl2cJaXSTBo4sJf0xhszJWdnOwmQVCqFNG7cIGn16hf0cXh5uUhHjnwpLVs2T7K2tpAAycnJVtq06R1p8+b39J+VWm0pff/9UkmSTkiLF/9FsrW1kmxsLKXHHhshffbZSxIg+fi4SSkpP9aLITNzT7O+19pl/vzJklxuImk0h/TrbnX8c+ZMkORyE8nNzUEyMTGWrKzMpfHjh0iJidslSTpxx8deu4wePUByc3OQdLrjBv9damxZvnyeJJPJpK+//vpmp4qNYhRm4ba9+eabvP/++7z44jT+8Y9n9XfLCMLdICEhlYCAKaxf/6b+duJbmTt3Odu27Sc3d++tN75NubmFuLuP5b335rJo0eOtVs+d0GjKefbZD/nuu/+yevVqnn/++ZttKkZhFm7f0qVL+e677/j88/8QGjpTfzeWINwNfH3deffdv/Luu+uaNRp2a4+SvGTJ1/Tu3Z358ye3aj2369dfTxEc/CTh4cfYtWtXYwkGEH0ywh164okniI6OwcmpC2Fhs5k8+XUSE9MMHZYgNMmrr07nscdGMHXqG/rOdkP66KPviYq6yJ49q9rdlYELF5KZPPl17r9/PoGBvTh37g8eeuihW+4nkoxwx7p27covv+xl27ZtnDuXQkDAFGbMWEpMzN13m7PQ+bz//lzmz5/MP/7x70a3e+21z1m/fheFhSV07TqBH3440KJx/PjjYSoqKjl48HPUassWLftOnDlzgccee50ePR4nISGXX375hfDwXQ3ertwQ0ScjtCitVsumTZtYsWI5cXHxDBsWyowZDzNp0rB6T1cLgtA+FRaWsHXrftav383x438QGhrC4sWvMHHiRIyMmtU2EdMvC61Dp9OxZ88e1q37mt2796BSKZg8eQQzZ46+q0ZtFoTOQqfTcfDgWdav382OHb+h00lMnDiJ2bNnM3z48NstViQZofVlZWWxceNG1q//hujoGLp18+SRRwYxZsxABg7sVW+eFUEQ2kZFhZZDh84SHn6Un346SkpKBvfddy8zZ85i6tSp2Njc3sCoNxBJRmhbZ86cYcuWLfz0049cvHgJW1trHnqoH2PHDuTBB8Owtm547C5BEFpGTk4Be/YcIzz8KL/8cpLi4lJ69erJmDFjmTZtGkFBQS1ZnUgyguFcvHiRn376iV27wvn992PIZHDffUEMGdKHwYN7M2BArwaHYBEEoeny84s5evQchw6d5fDhc5w9G4eJiQlDhgxm3LhHGDNmDF26dGmt6kWSEdqHvLw8fv75Z3777TcOHz7ExYuXMDEx5p57Ahg8uBdDhvRh4MBe2Ni0n7tuBKE9ys4u4MiRKH1S+eOPS0iSRGCgP0OGDGP48OHcf//9WFq2ye+SSDJC+3Tt2jVOnTrF77//zr59e4mMPIdOp8PFxZ6QEH/9MmBAT2xtrQwdriAYRFFRKX/8kUBERNz15SIXLlxGJpPh7+9FRzliAAAgAElEQVTHwIGDGDlyJMOGDcPe3v7WBbY8kWSEu0N2djbHjh0jIiKCM2fOEBFxhqysbIyMjOjevQuhof6EhPjRs6cvQUHed8XotYLQHKmpWVy4kExU1EUiIuI5cyaOxMSrALi5uRISEkJo6L2EhobSr1+/lui0bwkiyQh3r6tXr15POBGcOXOaiIgIcnJqJlWzs7MhKMibgIAu9OjhTUCAF0FB3jg72xk4akFo3NWr17hwIZmYmMvExiYRE5NMbGwShYU1s066uDgTEhJCSEgooaGhhISE4OLicotSDUYkGaFjyczMJCYmhtjYWGJiYrhwIZbo6Gjy8mpmLbS1tcbf3wtfXzd8fNzw8XHX/6yd/EoQWltGRg6JiWkkJqZe/1mzxMVd0ScTR0cHevToQUBA4PWfAQQFBRnqstftEklG6ByuXbumTz7x8fEkJiaQmJhIcvIVKitrpri1srLAx8cDHx9XfHxc6drVFXd3Rzw8nHB3dxR9P0KTZWXlk5aWTWpqFikpmSQlpV9PJOkkJl7VTwutUJjRtasXvr7d8PHxxc/Pj8DAQIKCgrCz6xCtbpFkhM6turqaq1evkpiYyOXLl0lMTLy+XCI5+Qr5+QX6bZVKBZ6ezri5OeDu7oCnp9P11464uTni6KjG0VHd7gY2FFpORYWW7Ox8MjNzycjIJSUl84ZkknX99TXKyyv0+9jb2+Hl5YWPjy8+Pj51Fjc3t1vO/HmXE0lGEBpTWlpKSkoKqamppKWl3fA6lZSUK6SmplFQUFhnHzs7GxwdbXF0VOPsXJN4HBzUuLjYX39tg62tFWq1FWq1pUhKBlRZqSU/v5j8/GLy8orIzs4nIyOHrKx8srMLrr8uIDu7gMzMHAoKiuvsb29vh5ubGx4eHnh4eN7w2kP/Wqns1M96iSQjCHeqtLSUtLQ0srKyyM7OJiMjg+zsbLKysq6/ziI7O4uMjEyKiorr7W9paY5CYYarqz1qteWflppEZGGhRKVSYGNjibm5ApVKgaWlCisrc1QqRaccfLSkpAyNppySEg2FhaVoNOVoNOUUFBRTWlqzvjaB5OcXXf9ZcsO/iygtrT+PjFptg5OTEw4ODjg7u+hfOzk54ezsrH/t6ura2RNIU4gkIwhtqby8nOzsbPLy8sjPz+fIkSN88803XLlyhenTp6NSqcjPzyc/P+/6z5qlpKSEsrLyRsu2sbFEpapJRtbW5gBYW1tgZCRDoTBFqTTDyEimH7rHwkKJXG6Cqakcc/O6J8vGhpq3sjJvcLy5qqpqios1De6j0+koLCyts664uJSqqmoqK6v0J/v8/JokrNGUU1GhrVNmQUGJPpHUdo7fjLm5CgsLC9RqG9RqW9Rq9Q0/G15sbW1xcHDA1NS00bKFZtkk2umC0IYUCgUeHh4UFxezdu1atm3bxsiRI9mxYwd9+vRpdF9JkigoKKC0tJS9e/fy7rvvkpmZyd/+9jf69eunf0+j0VBcXHMSzs+vuauutLSUyspKKiuruHy5CICiojSqq6spLy+jrKwcjaaM6uoqFAoFJSUNT+BVkyyKbhqjjY31TfsYrKysKCkpxczMFIVCgbm5OaamppiYmOifPre2tsHIyAhbWwVKpRKZTKZ/3sPa2hqVSoVKpcLGxgZzc3NUKhWWlpb13hPaD5FkBKENpaamsnTpUtatW0fv3r3Zv39/k4dRl8lkaDQaXnvtNb777jvGjBnDb7/9RteuXVsktieffJK8vDz27NnTpO1PnTpF3759SUpKwsvLq0n73HPPPQwfPpyVK1feQaTC3USMsS4IbSA/P59XXnmF7t278/PPP7N27VpOnTrV5ASj1Wr5+OOP8ff35/jx4+zevZvw8PAWSzAAUVFR9O7du8XKa0ifPn2IjIxs1TqE9kW0ZAShFVVWVvLtt9/yxhtvoNPpePvtt1m4cCFmZmZNLmPfvn08//zzpKSk8Pe//51XX321Wfs3RVlZGfHx8be8ZHenevfuzX/+8x8kSerot+4K14mWjCC0Ap1Ox7Zt2/D39+eFF15g1qxZJCYmsnjx4iYniMuXLzN58mRGjRqFr68vsbGxLFmypMUTDMD58+epqqpqkySTn5/P1atXW7Ueof0QSUYQWti+ffsICQlh6tSpDBw4kEuXLrFs2TKsra2btH9ZWRlLliwhKCiIc+fO8fPPPxMeHt6ac34QGRmJlZUV3t7erVYHQK9evTAyMhKXzDoRkWQEoYWcOXOGESNGMGrUKOzt7YmKimLDhg24uro2uYzw8HCCgoJYuXIlixcv5vz58zzwwAOtGHWNc+fO0bNnT4yMWveUUJvIoqKiWrUeof0QSUYQ7lBKSgpz5syhb9++lJaWcujQIX799VeCg4ObXEZCQgKjR49m3LhxBAUFceHCBZYsWdJmz2zExMTQo0ePNqmr9viEzkEkGUG4TTk5OcyfP59u3bpx+PBhtm/fzokTJxg8eHCTy9BoNCxZsoQePXqQlpbG4cOHCQ8Px8PDoxUjry8+Ph4/P782qcvf35/4+Pg2qUswPJFkBKGZysvLWbFiBb6+vvzwww98+umnnD9/nvHjxzernK1bt+Ln58fHH3/MypUriYiIYNCgQa0U9c0VFBRw7do1/P3926Q+Pz8/4uPj0el0bVKfYFgiyQhCE0mSxLZt2wgKCuKdd95h7ty5xMXF8de//hUTk6Y/DRAVFcXQoUOZNm0a999/P/Hx8Tz33HMYGxu3YvQ3FxcXB9BmLRk/Pz/KysrEHWadhEgygtAEJ0+eZNCgQUydOpWQkBBiY2NZtmwZVlZNn2MmLy+PBQsWEBoaSmlpKUePHmXdunU4Ojq2YuS3Fh8fj0KhwNPTs03qq20xiUtmnYNIMoLQiJSUFJ566in69euHQqEgIiKCrVu3Nut24qqqKr766iv8/Pz44YcfWLt2LSdPnqRfv36tGHnTxcfH061btzZrSdna2mJvb69vQQkdm0gygtCAG4eBOXXqFFu2bGHfvn3NHnZl//799OnTh+eff57HH3+cCxcu8Ne//rXVbxVujrbs9K8lOv87j/bzP10Q2gGtVqtvdXz99dcsX76c6OhoHnvssWaVk5CQwOTJkxk5ciReXl5cuHCBjz/+uFmX19rK5cuX8fX1bdM6fXx8SEpKatM6BcMQSUYQrgsPDycwMJDnn3+eadOmkZiYyIIFC5rVqV9aWqq/Jfn8+fPs2bOH8PDwVn+S/k4kJye36mgCDfHy8iI5OblN6xQMQwyQKXR6p0+fZtGiRRw9epRHH32UvXv3Nnt0Y0mS+O6771i8eDEVFRUsX76cefPmNStBGUJhYSEFBQVNHqq/pXTp0oXk5GQxUGYnIFoyQqd19epVnnrqKfr27YtWq+Xo0aNs3bq12Qnm9OnTDBgwgJkzZzJq1Cji4+Ob3QIylNpLVm2dZLy8vCgrKyMrK6tN6xXankgyQqdTUlLCkiVL6N69OydPnmTLli0cP36c/v37N6uc9PR05syZQ1hYGAqFgsjISDZs2ICDg0MrRd7ykpOTkclkbXb7cq3apCYumXV8IskInYZWq+XTTz/Fy8uLNWvWsGLFitvq1K+srNRPIPbf//6X9evXc+DAAXr27NlKkbee5ORkHB0dUalUbVqvh4cHJiYmIsl0Au2/PS8ILWDPnj0sWrSIpKQk5s+fz2uvvXZbc8Hv2LGDl156iaysLF599VUWLVqEQqFohYjbxpUrV9r8UhmAiYkJrq6uIsl0AqIlI3Ro8fHxjB07ltGjR+Pr60tMTAwrVqxodoKJjY3loYce4tFHHyU0NJSYmBhef/31uzrBQE2/VFtfKqvVpUsXUlJSDFK30HZEkhE6pLy8PF555RV69uxJWloaBw8eJDw8HB8fn2aVk5GRwezZswkODqagoIBjx441+4n/9iwtLQ03NzeD1O3q6kpGRoZB6hbajkgyQodS+zClv78/69atY8WKFZw+fZohQ4Y0q5yysjKWL1+Ov78/e/fuZf369Rw7doywsLBWitwwMjIycHFxMUjdIsl0DqJPRugw9u3bxwsvvMDFixeZO3cuS5cubfYT9pIk8cMPP7B48WKysrJ46aWXWLx4MUqlspWiNhxJksjMzGzWzJ0tycXFhfT0dIPULbQd0ZIR7nrx8fGMGTOGUaNG3dEQLqdPn9aPtDxw4EAuXbrEkiVLOmSCAcjNzaWiosJgLRkXFxcyMjLEvDIdnEgywl3rxn6X9PR0fb9Lc4dwSU1N1T+UaWpqSkREBBs2bDDYybet1LYiDNWScXV1RavVkpuba5D6hbYhkoxw17lxEMs76XepHWese/funDhxgi1btnDgwIFmj7R8t6rtDzFkkrkxDqFjEklGuKvs27evztD5tYNYNmcuFJ1Ox4YNG/D19eWTTz7h7bff5vz5881+KPNul5GRgVKpxNra2iD117YURb9MxyaSjHBXuLHfpWvXrrfd73LgwAHuueceZs+ezbhx44iLi2Px4sWYmZm1UuTtV1ZWFk5OTgar39raGoVCIcYv6+BEkhHatdzcXObNm0ePHj3IyMjg0KFDt9XvcvHiRSZPnsyIESNwcHAgMjKSL7/80uBTHxtSdna2wY/f3t6enJwcg8YgtC5xC7PQLul0OjZu3MiiRYsAWLlyJc8991yzpwjOz89n+fLlrF69Gm9vb3bv3s3DDz/cGiHfdXJycrC3tzdoDPb29qLjv4MTSUZod3777TcWLFhAfHw8Cxcu5I033sDS0rJZZVRWVrJmzRree+895HI5n376KbNmzWqzeezvBu0lyYiWTMcmLpcJ7UZaWhpPPfUUI0aMwMnJicjISJYvX96sBCNJElu3biUgIIDXX3+dOXPmcPHiRZ555hmRYP4kOztbJBmh1YkkIxjcjUO4HD9+nJ9++olff/2VwMDAZpVz8uRJBg8ezNSpUwkJCSEmJoYPPvig2TcHdBbtoSVjZ2cnkkwHJ5KMYFDh4eEEBQWxdOlSFi1aRHR0NGPGjGlWGbWd+v369cPU1JQzZ87c1gyXnU17SDKiT6bjE0lGMIj4+HgeeughHnnkEUJDQ4mNjWXJkiXNupU4NzdX/8T/+fPn2bJlC/v37+eee+5pxcg7Bq1WS1FRkcGTjGjJdHwiyQgt5uDBgxQXFze6TUFBgT4xZGVlcfjwYbZu3dqsOU1qZ6b08fFh3bp1LF++vFM+THkn8vPzkSQJW1tbg8ZhZ2dHXl6eQWMQWpdIMkKLiIuLY+zYsbz77rsNvl/7lL2fnx//+te/WLFiBadOnWLgwIFUV1dTVlZ2yzokSWLbtm34+/vz+uuvM3fuXP0T/yYm4kbJ5igsLAS4rdlBW5K1tTVarRaNRmPQOITWI5KMcMfy8vJ48MEH0Wg0rFq1itjY2Drvnz59mgEDBjB79mzGjx9PfHy8figYSZKYO3cuH374YaN17N+/n5CQkDojJC9btkx06t+m2iRjqCFlatUmudp4hI5HJBnhjlRVVTFp0iTS0tLQ6XQYGRnx9NNPI0kSGRkZzJkzh7CwMJRKJWfPnuXLL7+s0w/w5ptv8vXXX7Ns2bIGhxe5cOECkydPZuTIkdjZ2REZGdkpRkhube0lydTWX1BQYNA4hNYjkoxwR55//nmOHDlCVVUVUNOhfOLECWbNmkX37t3Zu3cv27Zt48CBAwQHB9fZd+3atbz//vtATbJ677339O+lp6czZ84cgoODiY2NZffu3fz666/07Nmz7Q6uAyssLEQmkzX7IdeWVptkREum4xJJRrhtn332GV988QXV1dX13tu2bRvPP/88sbGxTJw4sd7733//Pc8995z+31qtlrVr1xIdHa1/ZmbPnj2sXbuWc+fOiaFgWlhhYSHm5uYG78sSSabjE72lwm3Zt28fCxYsaPA9SZKorKxEq9U2OKvk/v37mT59er31RkZGDBs2DK1Wy+uvv86CBQtQKBQtHrtQc1I39KUyAEtLS4yNjUWS6cBES0ZotsuXL/Poo482uo1Wq2XVqlX88ccfddafPn2asWPHUl1djSRJ9fbJyclh+/btLF68WCSYVtRekkztJTuRZDoukWSEZikoKGDUqFFoNJpbzs0uk8mYN2+ePplcunSJBx54AK1We9N95XI5H3zwQYvHLdRVVFTULpIM1NxhJpJMxyWSjNBkVVVVTJw4katXr6LVahvd1sTEBEmSOHr0KJs3byYtLY2hQ4dSXFysv0mgIVqtlgMHDrBv376WDl+4gUajQaVSGToMAJRKpXhOpgMTfTJtrKqqiuLiYioqKtBoNJSVlVFeXg5w0xPwzdbL5XIsLCzqrTc1NcXc3Byo+QVWKBRYWFggl8uxsrK67dGIFy5cyOHDh+t19BsbG2NkZIRWq8XIyIiuXbvSv39/QkJCCAkJwcfHhyFDhpCdnd1ogqklk8l46aWXiIyMRCaT3VasQuPKy8vbzeVIhUKh/x0QOh6RZJqhoKCAa9eukZ2dTV5eHoWFhfWW/Px8CgsLrv+7gMpKLQUFBVRXV1NYWGToQ9BTq20wMjLST4FrbW19fbHB2toatVp9wzprjh8/zpo1a4CaVkpVVRUymQx3d3cGDhzIfffdx7333kufPn3q/IWs0WgYOnQoycnJN239mJqaUl1drU9e1tbWWFpaEh8fj7+/f+t/GJ1QWVlZgzdlGIJSqRRJpgPr9EmmoqKCtLQ00tLSuHLlChkZGWRmZpKdnU12dhaZmRlkZ+eQnZ1DZWVlnX0VCjOsrS1uWMxRqy3x9DTH2toBa2sLzMzk2NhYXj+hm2NiYoylpTmmpiaYmytRKExRKmsGhVQqzVAo6g8QWbPetN76srIKyssr663XaMqpqKhZX1paTmWlluJiDVVV1RQVlVJdXU1BQQk6nY6CghLKyysoLCylsLCEwsIsLl9OIj+/WL8uP7+oTgukqqoKU1M5Dg4OODo6UFhYQFRUFGlpaZw8eRIXFxc8PDxwcXHh2Wef5fTp08hkMuRyOVVVVUiShEwmw9nZmeDgYIKDg/Hz8yMgIICAgADs7Ozu6DsVbq28vNzgz8jUUigUTRpWSLg7dfgkU1paSkJCAgkJCSQmJpKamkpKSgppaamkpqaSmXlNv62pqRxnZ3tcXOxwcLDBxcWG3r174+ioxsFBjaOjGmdnO+ztbbC1tWrwxN+WlEozfYK6kVrdsiePY8fO4+pqj1xuQlZWPpmZuWRn55OTU0hmZi5ZWflkZycQE3OazMxcMjNzqKr63yU1ExMTrKyscHR0pGvXrgQEBNC3b18CAwPx9fVtN5dtOpOysjIcHBwMHQYgWjIdXYdIMpWVlVy4cIGLFy/qE0pCwiUuXbpERkYmUPMMhru7E56eTnh4ODJ0qD8eHkPw8HDE3b1mcXa2E30ADejf/39P6ru53frEVF2t49Klq5w/n4AkSaSn55CSco3U1CzS0tLZsiWCVatW6Vs07u5u+Pr64uvbDV9fX7p164afnx/du3c3+MOCHVV5eXm7uVwmWjId2133G5yenk5sbCwxMTFEREQQGxtNTEws5eUVAKjVVgQGdiUoqCsPP9wTb29XvL3d8Pfvgrl5+/il6uiMjY3w9++Cv3+Xm25TWaklNTWLy5fTuXw5jZiYy8TGnmP//v+SnJyOTqdDLpfTrZsvQUE9CAwMJCgoiMDAQAICAjAyEjdG3omysrJ204JUKBSUlJQYOgyhlbTrJJOYmMipU6euLyc5d+4cpaUaZDIZXl6u9Ojhzf339+SllyYSFOSNn58npqZyQ4ctNIGpqRxvbze8vd2Ae+u8V1ZWQVzcFaKjE4mOvswffyTwzTdHuHq1plVqbW1F7969ue++vvTt25f77rsPDw8PAxzF3as93V2mVCrJzs42dBhCK2k3SaakpITff/+dEydOcOrUSU6dOkVOTi5yuQnBwd3o2zeAGTOG0rOnL4GBXbG0bB/3+AstT6k0o0+f7vTp073O+oKCYqKjL3P+fCIREXH8/PN/+Oijj6iursbFxZn77ruP++7rS79+/ejXr1+7OYm2R+2tJSP6ZDougyWZqqoqzp07x759+9i371eOHDlCRUUlLi4OhIT4MW/eBAYO7EX//sGoVO3jl0EwLBsbSwYO7MXAgb3060pLy4iMvEhERBwREXFs2vQNr7/+OiYmJvTq1ZORI0cxcuRIBg0a1KypnTu69taSEX0yHVebJpkLFy7w448/8ssvP3PixEnKy8vx9fVk2LA+zJr1BsOGheDsLG5fFZrO3FxZL/GkpGTy228RHDgQwf/9379Zvnw55uYqBg4cyIMPPsQjjzxC165dDRi14bW3jn/Rkum4WjXJ6HQ6Tp06xc6dO9m58z/Ex1/E0dGWhx7qx8yZLzNsWAgeHk6tGYLQCXl6OjN9+mimTx8NQEJC6vWkc4Z3332bF154gV69ejJ+/AQeeeQR+vTpY+CI2157u1wmWjIdV6skmXPnzvHNN9+wbdtWMjIy8fHxYMKEwXz99SL69w8WdwYJbcrX1x1fX3eeeeYRtNoqDh2KZOfOQ3zzzZe88847eHl1YerUacycOZPu3bvfusAOQLRkhLbSYkkmPz+f//u//+Obb9Zx9mwk3bp58re/jWPChCH06OHTUtUIwh2Ry00YOfJeRo68l08/XURERBw7dhxk48ZvWb58OQMG9GfWrNk89thjDY4L1xFotVqqq6vbTUtG9Ml0bHfcpIiLi2PGjBm4urqwePHf6dnTjcOHvyA+fgtvvjlLJBih3ZLJZISGBvDBB38jOXkH//3vKlxdlfztb3NxdXXhueee48qVK4YOs8XVntDbS5IRLZmO7baTzB9//MGUKVMICgri1KnDfPrpIjIydrN+/RsMGtRbPDkv3FWMjIx44IEwtmx5j7S0cJYufYZdu3bQrVs3Zs+eTUJCgqFDbDG1J3RxuUxoC81OMsnJyUycOIHevXsTHx/F5s1LiY7exNNPjxPPrggdgp2dNQsWTOHSpW18+eVijhzZh7+/P0899RcyMzMNHd4da28tGaVSSXV1db0BaIWOoclJpqqqio8++ogePYK4ePE8P/74IZGR/+axx0aIjnyhQ5LLTZg5cwwXLmxmw4a3OHLkAIGBAaxbt67e1NF3k9opF+Ty9jE6hqlpzUCzIsl0TE3KDtHR0YSF9eW1115l8eInOXv2W8aOHdgml8RWrtyEo+ODyGRhfPHFjlav71b1vvvuOgIDp2JlNRwzs0H4+k7i5Zc/o6Tk5h2XM2cuRaEYhEwW1uDQ/K2lperdt+80r766tgUja76ffjrC8uXfUV3d+JTPrcHY2IjHH3+A6OhNzJz5EHPmzGH48GEkJye3eSwtoTZBikvaQlu4ZZLZuXMn/fqFYWZWRVTUd7z55qw2HR/spZee4Nixr9usvlvVe+DAGZ577jGSk3eSk/MLH3zwLKtXb+axx169aVnr17/JSy890Zrhtlq9b7/9Lz75ZAuvvTajZYK6TePGDUKhMGXEiHkUFBQbJAZzcyX//OcCTp5cR25uGvfeG8rhw4cNEosg3C0aTTKbN2/m0Ucf5Ykn7ufgwbWNjqrbWVhYqJgzZwK2tlZYWqqYPHkEEyYM4eefT3D1as3cNGVlFfTv/4yBI71zy5ZtYPPmX9m69YN20d+2YMEUevXqxsMPv1hnvpq2FhLiz/Hj/2LIkF48+OAD7Nu3z2CxCEJ7d9Mkc/ToUZ566ikWLJjMF18sRi5vN2NpGtSuXf/E2Ljux2ZvbwPUzEgJsG7dT2Rl5TW4v6EuUTS33oSEVN5880veeecZg0/OdqMlS54hKuoiq1dvNmgc5uZKtmx5j4kThzJ+/CPExMQYNB5BaK8aTDIajYZp06YyenR/Vq6c39YxNUl1tY633voKT89HUCoH07PnE2zZUvMXZUDAFGSyMIyM+hESMl1/8n/55c+wth6BQjGIb7/d3WgZzZGWlo1SaUbXrq4sXLiKRYs+ITExDZksDF/fSfrtjIyM2L37dx56aCHW1iNwcRnNN9+EA7BixXeoVEOwtBxGVlY+ixZ9jJvbGOLjr9wyzkOHIrnvvlmoVEOwshpOcPATFBWVNqnem/nkky1IksS4cYPqrL9ZXZ98shWFYhCOjg8yd+5yXFxGo1AMon//Zzh5suYEvHr1ZszNh+q/Fyenh5DLB2BuPpR77nmKQYPm4OExDoViEDY2I3n55c/qxaVWWzJkSB9Wr95s8M53Y2Mj1q9/g969uzFt2lSqqw3XuhKE9qrBJPPpp59SVFTIV1+92m47B195ZQ0rVnzHqlULycjYzdixg3j88bc4c+YC0dHf4+XlgoeHE6dOrdeP4rxixXPMnj2OZcvmMWPG6EbLaCqNppwDB87wzDOPYGoqZ/XqFxg7diA+Pm5I0gkSErbrt9XpdNjYWLB583skJ+/knnv8ePbZFWg05bz88l948cVplJSU8cEH39K1qythYT2QpMaPtbS0jHHjXuLRR4eRl/crly79QPfuHlRWaptU783s3n0MP78udUbAbqyu+fMnM2PGGDSaChYsmEJy8k7Ont1AVVU1o0Y9z9Wr11i4cCp///uTSJLE558vJinpP2Rm7mHw4N5ERl7k1VenExm5gby8X5k+/WE+/HAj585dqhdbnz5+pKVlN/heW5PLTVi//g3i4uLYuHGjocNplvb6uy10LA0mmQ0b/s3MmaNxcLBp63iapLy8krVrtzNhwlAmTRqGjY0lb7wxE7ncmPXrd2FsbMSCBVNISclkx47f9PtpNOVs3/4bs2aNvWUZTfXBB9/i4mLPe+/NbdL2/fv3xNraArXakqlTR1FRoSUpKb3ONsuWzeO55x5j+/ZleHm5NBpncnIGRUWlBAV5o1CY4uRky/bty/SX8JpTb63S0jKSktLx8XGrs74pdZmYGBMQ4IWZmZzAwK6sXft3ios19T7TwMCuqFQK7OysmTbtfgA8PZ2wt7dBpVLw5APKDFkAACAASURBVJMPAhAXV/+J+27daiYoO38+sSkfeavr1s2DiROHsWHDvw0dSpMYugUodC71koxGoyE29gIjRtzb0PbtQnz8FTSa8jpD1iiVZjg72+lPSk8//QjW1hZ1rt1v3Pgz48cPxsrKvEll3MqOHQfZunU/v/zy8W11jNf2c2m1VTfd5lZxenu74eio5sknl7BkydckJ2fccb1ZWflIklRvHp/bqSs0NACVStHoZ1p7t+KNnfmNxVgb17VrDfd7GcKIEaGcPn3a0GEIQrtTL8kUFRUBYGPTfgcHLC2tuczzxhtfIJOF6ZcrVzL1l4AsLJT89a/jOXbsPKdOxQLw+ec7mD9/SpPLaMzmzb+ybNkGDh78HC8vl9Y4zCbFqVSaceDAGgYO7MX776/H23siU6e+QVlZxW3XWftMjZlZ3Q7/263LzExOdnb+bcfzZ0qlWZ042wO12pKSklLRLyMIf1Ivydjb22NqanrTSyntQe1lvFWrFiJJJ+osx4//79mW+fMnI5ebsGrV9xw+HImHh6P+ElBTy2jIp59uY+PGnzlwYA2urvatdJQ0Oc6gIG/Cw1eSnr6bxYv/wpYt+1i5ctNt11l7Em/ohNncurTaKgoKSnB3d7zteP6str+pNs724PLlNJydnTA2NjZ0KILQrtRLMiYmJgwfPoxt2w4YIp4m8fBwQqEwJSqq8Y5fd3dHJk8ewQ8/HODNN79i4cKpzS7jRpIksXjxGs6fT2DnzhVYWLT+AIO3ijM9PYfY2CSgJiH94x/Pcs89fvp1t8PRUY1MJqOwsLTO+tup6+DBs0iSRFhYj9uO588KC0sAcHKybbEy79QPPxzkgQceNHQYgtDuNNjx/9xzz7N79+8cPXqureNpEoXClJkzx/D993tZu3Y7RUWlVFfrSE3NIiMjp862ixY9QVVVNfn5RQwfHnpbZdSKjU1ixYrv+Ne/fkQuH1Dn8pVMFqb/i97W1or09BySkzMoLtY02udyp8eanp7N3LnLiYu7QmWllsjIi1y5knlHJ3WVSoG3tyupqVl11jelLp1OR35+MVVV1fzxRwILF67C09OZGTPG3HY8f1YbV3Bw+5hGYtu2/Zw5E8u8efMMHUqziLvLhDYh3cSYMaMlT08X6dq1/0qSdMJgyz//uUBycrKVAMncXClNnDhUkqQTUkXFEWnx4r9Inp7OkomJseTgYCNNmjRMion5vl4Zw4aFSF9//Vq99Y2V0VC9589vkoCbLh9++LwkSSeks2c3SF26OEtKpZk0cGAv6cUXp0lKpZkESN26eUiJiduljRvfkdRqSwmQ3N0dpaeeeli/jYeHk/Tdd0uaFGdy8k6pf/9gSa22lIyNjSRXV3vp9ddnSFVVx6Tly+fdst7o6P9r8HOfP3+yJJebSBrNIf26xuqSpBPSnDkTJLncRHJzc5BMTIwlKytzafz4IVJi4nZJkk5Iq1e/IKlUCgmQvLxcpCNHvpSWLZsnWVtbSIDk5GQrbdr0jrR583v6z16ttpS+/35pndhGjx4gubk5SDrdcYP+35SkE1Ji4nbJ1tZaevrpp2/2q9TuxMXFSYAUFRV1R+WcPHlSAqSkpKQ7Kmf37t0SIBUXF99ROUK7tFEmSQ3fz5ibm0vfvvdhbm7M/v2f1rslVujYEhJSCQiYwvr/b+++45o69z+AfxIIIYEsMBBWQAhDhqCoKK4q2mvrdVVRWq3V1t1erdUr2iX6ax3VOjqsWr1trVZcrdZxFS1VbEFxgYhlqawyFcIMI8nz+4OSW2QjcCA879crr0I443sONB+f8zznOd98oBtO3JxFizbj2LFf8ORJWIfV9eRJEWxtJ+CjjxZhxYpXOmw/LZGamo1Ro96EmZklrl79DXw+81PvtERiYiLc3NwQExMDb2/vNm8nOjoafn5+ePToERwcHNq8nXPnzmH8+PEoKSnR26eR9mCHGp1WxtzcHOHhv6K0VA0/v3ld5p4EqnMoFLZYv34B1q/f3+QM00/r6FmSQ0L2wcfHBUuXTu/Q/TTn99/vYvDgeZBILBAWdrHbBAxFdbYmJ8iUy+WIjr4Be3sFBg16HSEh++rcSU7ptzVrXkNgYACCgt7XdbYzadu2w4iJScK5c9sZm0tPpapESMg+jB79Jnx9B+HXXy/D3NyckVooqjtodqp/c3NzhIVdxKZNm7F16w8YMGCubi4qSv99/PEiLF06HRs3Nn03+7vvfoVvvjmDoqJS9O49BcePt+/oxFOnIlBZWYXLl7+CRCJo1223VETEHfTr9xp27DiKTz7ZgtOnz0AkEjFSiz6pHYDQyJV7qptrtE+mISkpKVi4cAGuXIlAUNBYrFkzGx4ejh1ZH0Ux7saN+/j44+/w888RmDx5Er744ktYW1szXVabPXjwAAqFAjdv3oSvr2+bt9NefTI///wzJk2aBJVK1WUeCU21m8b7ZBqiUChw6dIvOHjwIGJjM9C37yxMnboGt28ndlSBFMWYiIg7+Mc/3sagQa8jO7scp0+fxo8//tStAwaA7oO8oqL5mS06Q0VFBVgsFrjcrnNzLdV+WhUyQE3TNigoCLGxd3H8+HGkpRVhwIA5CAj4F3744UKXmuqDolqrpKQc+/b9jMGD52HkyMWorDRCWFgYrl+Pxvjx45kur110xZDhcrn0vh091eqQ0a3IZmPKlCm4efMWzp07B4HACnPmfAQrq/F4880tuHUroT3rpKgOQwjB1asxmDPn/2BlNR7/+tencHLqi6tXr+Ly5SsYO3Ys0yW2Kx6vZqaKrhQy9DKZ/mqXITrjxo3DuHHjkJubi++//x7/+c9+7Np1Ah4eTpg8eTgmTx4JX183+i8VqsvQaLSIiorDyZNX8NNPEXj4MBO+vv2xefMWvPLKK5BIJEyX2GFqP9BVqpYPTe9INGT0W7uOA7W0tMTKlSuxcuVKREZG4ujRozh06CQ+/vhb2NpaYtKkmsAZObIffZwz1elUqkpcunQDp05F4OefryI/vxCuri4IDJyJl19++ZluTOxO2Gw2jIyMaEuG6hQd9knv7+8Pf39/7NixA/Hx8Thz5gxOn/4Zu3YtBY/Hhb9/X4wZMxBDh/aFn58HDR2q3Wk0WsTEJOHSpRu4dOkGfv/9LlSqCri798GSJUsxYcKEZxpd1Z0ZGxt3qZCpvYRH6Z9O+WT38PCAh4cHgoODkZqairCwMISHh2P79mNYvfpLiMUCjBzZH6NH+2LIEE/4+LjQ0KFaTaWqxJ07SYiMvIvw8Fu4ejUGpaXlsLW1wejRAfjqqyV4/vnnYWXVcc//6S54PF6XCZnKykraktFjnf5J7uDggAULFmDBggUghOD+/fv45Zdf8Ouv4QgJ+Q8KC5Xgco3g4+OCQYP6YNAgDwwa5A5nZzvap0PpaDRaJCSkIjr6/l+vPxAXl4zqajUsLKQYNWo0tm6djVGjRsHFxYXpcrucrtaSoSGjvxhtLrBYLF0rZ+nSpSCEIDExEdHR0YiOjsa1a9exZ88pVFVVQSwWwNfXDZ6ejvD0dIKXlxM8PBw75ZkuFLOUyhLcu/cQ9+49QFzcA9y79wh37iSipKQMPJ4x+vfvjxEj/oGVKz/AoEGD4OTUNR4B0JXRkKE6S5e6JsViseDm5gY3NzfMnj0bQE1TOiYmBtHR0YiNjUVkZCz27TuNsrJysFgs9O5t81fwOKJPHwcoFLZwdraDuTmd7qO7yc0tQEpKJpKTM/DHH6mIi3uA+PhHSE/PBgAIhQJ4enrA03MAXn55Pvz8/ODl5QVDwy71Z9wt0JChOkuX/7+Ty+XCz88Pfn5+uve0Wi0ePXqEu3fvIj4+HnFxcfjpp2vYuvUHVFXV3AwqkQihUNhBobCBQmELhcIWTk62sLeXQSYzh6EhfUxuZ6uqqkZW1mOkp+cgJSXzb68/kZKSgZKSmidxGhtz4erqCg8PTyxePAFeXl7w8PB4pqlLqLq6Up8MnU5Gv3X5kGkIm82Gk5MTnJycMGXKFN37Go0G6enpSElJ+dsrGSdOROHBg4eorKwEABgYGEAmM4e9vRVsbaWwsZHC3l4GW1sLWFv3gkxmDgsLCUxM6KW4liotVSEn5wny8gqRmZmHzMw8pKfnICMjD5mZ+cjIyEVOzmPdJIh8Pg8KhQIKhTPGjvXF4sUKODk5QaFQwM6O9r91NNqSoTpLtwyZxhgYGKB3797o3bt3vbu0tVotsrOzkZaWhszMTGRmZiI9PR0ZGRn4/fcUhIb+ipyc3DozwfL5xpBKzSCTmUEqFUMqFcPCQgJLSzNIJEKIRCYQiUwhEplCIhHovu7OraTqajWKikqhVJaiqKgUhYUlKCr639c5OU+Qn69Efr4SeXmFyM0tQF5eASor/zedUE2IW0Iul8PW1g5Dh/rA3t4etra2sLW1hVwupyO8GNbVQkafb37t6fQqZJrCZrNhY2MDGxubRpepqqpCTk4OsrOz8fjxY+Tn5yMvLw+5ubnIz89HTk4+YmLuIj//MQoLC1FWVt7gdkxN+RCJBBCJTMDjcWFqygeHYwCh0AQGBmyIxaZgs2v+a2BQ8/7/1uXVG77NZrMhEpk8vRsolaX1pkevqqpGWVnF35YpgVZLoFSWQKPRori4DGq1BiUl5aiqUqOsTIWysoq/gqQE5eUNf/AIBKaQSCSwtLSEVCqFVKqAu7sUMpkMDx48wP79+yGTybB27VrMnj2b9pN0cV0tZGhLRn/RT4K/MTIyglwuh1wub9HyarUaRUVFKCoqQmFhoe7r2pdSqYRKpUJpaSmqq6tRXFwMjUaD1NRCaDQaFBWlQa1Wo6SkRLfNwsLCevupqqpqMNBMTU3A4XDqvFcTSP8b9CAUCmBgYAiJRPLXz8zA43EglZqCy+WCz+fDxMQEIpFI9xKLxbqvJRIJRCIR2Oymp7l77733sH79esyfPx8HDx7Etm3b4OPj06LzSHU+Ho9Hp5WhOgUNmWdgaGgIc3Nz+mREADY2NtizZw/mzZuH5cuXw9fXFzNnzsQnn3wCmUzGdHnUU4yNjVFUVMR0GQBoyOi7Ns/CTFENGThwIK5evYrQ0FBcvXoVCoUCISEhXebSDFWDx+OhvLzhy72djY4u0280ZKh2x2KxEBgYiPv37+ODDz7Atm3b4OLiggMHDtBH7HYRQqGwzmVaJhUXF0MoFDJdBtVBaMhQHYbH4yE4OBgJCQl44YUXMHfuXAwZMgRRUVFMl9bjCYXCLnO5rKioqE4/IqVfaMhQHc7a2hp79uxBdHQ0jIyMMHToUEyfPh3p6elMl9ZjiUSiLhEyarUa5eXlNGT0GA0ZqtP4+voiIiICp06dwq1bt9CnTx+EhIR0mVFOPUlXCZni4mIQQmjI6DEaMlSnmzBhAv744w9s2LAB27dvp/01DBCJRKiqqmJ8QEZt0NGQ0V80ZChGGBkZYdmyZXjw4AFeeuklvP766/Dz80NkZCTTpfUItR/qTLdmaMjoPxoyFKN69eqFnTt34saNG+Dz+Rg2bBimT5+OtLQ0pkvTa7WjubpKyNDRZfqLhgzVJfTr1w+XL1/GqVOncPv2bbi7u2P16tVdZpitvqltOSiVSkbroCGj/2jIUF3K3/trdu/ejT59+mDv3r3QarVMl6ZXzMzMADQ8jVFnKigoAJ/Ppzdj6jEaMlSXw+FwdP01U6dOxZIlS+Dn54fffvuN6dL0hlAohJGRER4/fsxoHY8fP0avXr0YrYHqWDRkqC7L3NwcO3fuRFxcHKRSKYYPH44JEybg0aNHTJemF8zNzRkPmSdPntCQ0XM0ZKgur0+fPjh37hwuXryIR48ewcPDA6tXr0ZxcTHTpXVrvXr1wpMnTxitgbZk9B8NGarbGDNmDO7cuYMdO3Zg//79cHNzw969e6HRaJgurVvqCi2Zx48f01nM9RwNGapb4XA4WLBgARITExEYGIg333wTgwYNQkREBNOldTtdoSVDL5fpPxoyVLdkZmaGnTt34t69e7CyssLIkSMxYcIEPHz4kOnSuo1evXrRlgzV4WjIUN2aq6srzpw5g4sXLyI1NRV9+vTBsmXLGL/JsDvoKpfLaEtGv9GQofRCbX/N559/jsOHD8PJyQk7d+6k/TVNkEqlyMvLY2z/Go0GBQUFNGT0HA0ZSm8YGhrq+mvmzZuHVatWwcvLC+fPn2e6tC7JysoKeXl5UKvVjOw/NzcXGo0G1tbWjOyf6hw0ZCi9I5FIsGnTJsTFxcHT0xMvvPACJkyYgJSUFKZL61KsrKyg1WoZa81kZ2fr6qD0Fw0ZSm+5uLjg6NGjuHTpEtLT0+Hu7o5ly5YxPl9XV1Hbgqj9sO9sNGR6BhoylN4LCAjAnTt3sG/fPoSGhur6a5i6TNRV1H64MxkyQqEQJiYmjOyf6hw0ZKgegc1mY/bs2UhMTMT8+fMRHBwMLy8vnDt3junSGMPn8yEUCpGVlcXI/rOzs2krpgegIUP1KGKxGJs2bcK9e/fg5eWF8ePHY+zYsYiPj2e6NEZYWVkx2pKhIaP/aMhQPZJCocDRo0cRHh6O/Px89OvXDwsXLkR+fj7TpXUqpkNGJpMxsm+q89CQoXq0UaNG4fbt29i3bx9+/vlnuLm5YfPmzaiqqmK6tE5ha2uLzMxMRvadmZkJW1tbRvZNdR4aMlSPV9tfk5KSgn/9618ICQlB3759cezYMaZL63AODg6MPeo6NTUVDg4OjOyb6jw0ZCjqLyYmJggJCUFSUhIGDRqEGTNmYOzYsYiLi2O6tA5jb2+P1NTUTt9vaWkpnjx5Ant7+07fN9W5aMhQ1FPs7Oxw4MABREZGorS0FP3798fChQsZnYKlo9jb2+s+8DtTbeuJtmT0Hw0ZimrE4MGDERkZif379+P06dO6/prKykqmS2s3tR/ynd2aqd0fbcnoPxoyFNUEFouF2bNnIzk5GUuXLsW6devg5eWlN/019vb2YLPZnR4yaWlpMDMzg0Ag6NT9Up2PhgxFtcDf+2sGDx6MGTNmICAgALGxsUyX9kyMjIwgk8mQlpaG6upqxMfH4+jRo/jwww9x48aNdtlHeHg41q9fjxMnTiAxMRFqtRppaWn0UlkPwSKEEKaLoKjuJjo6GsuXL8e1a9cwc+ZMbNmyBZaWlkyX1SIajQYPHz5EXFwc7t+/j5MnTyIvLw9ZWVl1Ho1w+/Zt9OvXDwBQUVEBhUJR5zk9hBCo1WpwOJw627ezs8O9e/fAZtf8G/bChQsYN26c7uccDgdWVlawtrbGpEmT4O7uDk9PTzg4OOjWofTGIRCKotpEq9WSo0ePEnt7e2JqakrWrl1LVCoV02U1af/+/YTL5RIAhMViES6XS9hsNgFQ58Vms0l5eXmddWfMmNHgsk+vt2zZsjrrZWRkNLisgYEBMTIy0n3P4/HIyZMnO/N0UB3vIP1nA0W1EYvFQmBgIO7fv4/3338fn376KVxdXXHgwAGmS2vU9OnTIRAIwGKxQAhBZWUltFptveVsbW3B4/HqvDdz5swGl/07rVaLV155pd62TE1N6y2r0Wh0N72yWCxYWVnhxRdfbO0hUV0cDRmKekZ8Ph/BwcFISEjAuHHjMHfuXIwaNQoxMTFMl1aPqakpPv74Y7BYrEaXYbFYustkfzdu3DgIhcImt29nZ4eBAwfWe9/Nza3J9Qgh2LZtW71Lb1T3R0OGotqJjY0N9uzZg+vXr0OtVsPX1xezZ89GTk5Ok+tFRkbiyJEjnVQl8MYbb8DZ2RkGBgYN/tzIyAheXl713udwOJgxY0ajQcDhcDBnzpwGA6xfv36NrmdoaAh/f39MmjSpFUdBdRc0ZCiqnQ0YMAAREREIDQ3F1atXoVAoEBISgoqKinrLEkLw1ltv4dVXX8Vvv/3WKfUZGBjg008/rdPJ/3fV1dXw8PBo8GevvPIKqqurG11vxowZDf6sse0BNZfNtm7d2kzVVLfFcKcQRem18vJysmnTJiIQCIidnR357rvviFar1f38wIEDhMViETabTUQiEUlISOi02kaNGkU4HE6DnfJxcXENrqPRaIilpWWD67i7uze6r0uXLjW4DofDIUFBQR11iBTzaMc/RXUkHo+n66954YUX8Prrr2PIkCGIioqCSqVCcHAwWCwWtFotysrKMGbMGOTm5nZKbdu3b2/w6aAGBgZwdnZucB02m41Zs2bByMiozvscDgevvfZao/tqrCVDCMFHH33Uiqqp7oaGDEV1Amtra+zZswfXrl0Dh8PBsGHDEBAQgPz8fN2ILbVajdzcXIwbNw5lZWUdXpO3tzdmzZpVr6/EwcEBXC630fVefvnleo9CUKvVmD59eqPryGQyiESiOu9xOBwsX74cTk5Obaie6i5oyFBUJ6rtr/nyyy9x8+bNei2J6upq3Lt3D4GBgY32mbSnjRs31rkBks1mNziy7O98fX3h6Oio+57FYsHPz6/ZO/jd3d3rfG9sbIzVq1e3vmiqW6EhQ1GdjMViISIiotGfq9VqhIWFYcWKFR1ei42NDd555x0YGhoCqGldeHp6Nrveq6++qmsBGRgYYPbs2c2u4+PjU2ed9evXw8zM7Bmqp7oDGjIU1cmuX7+O0NDQRkdpATUjrj777DPs3Lmzw+tZs2aN7v6XqqqqJkeC1Zo1a5aufkIIpk6d2uw6Hh4eIISAzWbD2toaixcvfrbCqW6BhgxFdSJCCJYuXdroPSpPL7t8+XKcPHmyQ2sSCARYv369bp8tCRmFQoG+ffsCAAICAmBhYdHsOp6enlCr1dBqtfj000+b7Peh9Ich0wVQVE9y/vx53LhxA4QQGBoagsViNdmiAYCgoCBcuXIFfn5+HVJTdXU1AgMD8cknnyArKwvl5eW4desW1Go1SkpK6i1fXl6OyspKeHt74+7du3B2dsaxY8fA4/FgbGxcb3mRSAQ2m627SdPb2xsBAQFQq9W6y3SU/qKzMFNUJyspKUFcXBxiY2MRGxuLW7duIT4+HiqVCiwWC1wuF1VVVbpRZ2w2GyKRCDdv3qzT4V6roKAAubm5yMvLQ0FBAZRKJZRKJQoLC3VfK5WFuv+WlZWjuLgYarUaSmVRve11NolEDA6HA1NTU5iamkIsFkMsFkMiMdN9/feXubk5pFIprK2tm53mhmLcIRoyFNUFaLVaPHz4EDExMbh79y5iYmJw8+ZNZGdn65YxMzPDuHHjUFxchNzcXGRnZyM//3G9J3WamvIhFgsgFgsgkQggFpvqXhKJEHy+MUQiExgYGEAsNgWHYwhTUz54PC7On4/Cq6++AEPDmst5Ekn9D3EjI0OYmNRMnrlr1wksWVLTH1NaqkJ1dd3RclqtFkVFpQCAqio1vvvuLF580R+VldUoKSmDWq1BYWEJ1GoNSkrKUVpaDqWyFEplCQoLS6BUlkGpLIFSWYrCwiKUl9edNcHYmAsLCwtYW1tDKpXC0lIGKysryGQyyOVyODg4QC6X0zBiDg0ZimJKRUUFkpKSkJiYiJSUFKSnpyM9PQ1paalIS0tHaen/7pUxNeXDyIgDgYCP4cO9YWlpBmtrKaRSMWQyc8hk5rCwkMDcXKQLiM5ACGlyss32VlVVjSdPipCfr0RW1mPk5RUgN7cA2dlPkJdXgJycQuTmFiArKx8FBf9rpYnFIsjlcsjlctjb1wSPs7MzXF1doVAo6t1cSrUbGjIU1dFycnIQFxeHpKQkJCQkICkpEUlJSUhPz4BWq4WBgQHkchnkckvY28tgby+DXC6DnZ0F5HIZHByswOPRTvLWKi1VIS0tG2lpOcjIyEV6ei7S03OQmpqD9PRcZGTkgBACAwMDODjI4eLiCje3PnBxcYGLiwu8vb1hbm7O9GF0dzRkKKq9qNVqpKenIz4+Hrdu3cKtWzdx69YtZGfXzMIskQjh6GgDR0druLv3hodHbzg62qBPHwfw+fU7zKmOVVVVjczMPMTHP8L9+4/w8OGfePgwG3FxKcjNfQKgpr/I3d0Dvr6+upebm1uLRgdSAGjIUFTbZWZmIjIyEpGRkYiKikRs7F1UVlbCyIgDd3dHeHsr/no5w9vbGebmouY3SnUJOTlPcPduCmJikhAbm4LY2BQkJqZCrdbAxIQPHx8fDBnij6FDh2LIkCHd5tHbDKAhQ1EtQQhBTEwMIiIiEBUVhcjI35GRkQlDQwN4e7vC398DAwb0gbe3M9zde4PDoUNz9U1FRRXi4x8iJiYJN278gcjIOMTHP4RWq4WjowP8/YdhyJAheO655+pNodOD0ZChqMbk5uYiIiICly5dwtmzZ/Dnn1kQCEzg5+eBoUP7wtfXDcOHe0MsFjBdKsWQ0lIVYmKS8Pvvd/Hbb7GIjIxDQUERLC0tMGLESIwZMwb//Oc/YW1tzXSpTKEhQ1G1CCG4du0aTpw4gfPn/4v4+PswNuZi6FBvPP/8QIwd6wcfH+dOHU1FdS8ajRY3b/6BixejERYWjWvX4qDRaOHj440XXngR06ZNg4+PD9NldiYaMlTPVhssx44dw/Hjx5CRkQkXF3v885/+GDvWDyNG+NBOearNSkrKcfnybYSFXcfp078jLS0Lzs4KTJsWiMDAwGZnvNYDNGSonik1NRV79+7FwYPfIyMjE66uDpg27TkEBgbA27vhB3ZR1LMghODGjT9w7NgvOH78V6SmZkGhcMJrr83BG2+8ASsrK6ZL7Ag0ZKieQ6PR4Ny5c9i9+yucP38BMlkvzJ37IqZPH4O+fRVMl0f1ILWBc+TIRRw4cB5FRaWYNGkiFi1ajNGjR+vTJVkaMpT+q6ysxNdff40tWz5BRkYmxowZhEWLpmDixOGdenc8RTWkoqIKx4+HY/fun/D777FwdXXBmjXvYtasWfpwPw4NGUp/qdVqfPvtt/i//1uPvLw8LFw4GW+9FQiFwpbp0iiqQXFxD7Bz5xF8991ZKBQKhISsQ2BgYJ2nl3YzNGQo/XTu3DksW7YU6enpeOONiXjvvTmwsZEyXRZFzZPxCgAAGTlJREFUtUhKSibWrduPw4fD4OHhji+/3IVhw4YxXVZbHOq28UhRDSkuLsa8efMwfvx4DBzohMTEo9i16980YKhuRaGwxfffr8XduwdhZyfEyJEjsXLlSqhUKqZLazUaMpTeuHLlCry8PHHmzEn89NNm/PDDejg4dP6InXnzNkAgGAUWazBiYpI6ff8AcO5cJESiAJw+/VuL19m48TuIRAHtUvf69fvh7h4EoXA0uNzhUCimYtWqL1Ba+mwfkm05t5cu3cCaNbsAtO28/PzzVWze/D00Gm2ban4W7u69cebMp9i//z3s27cXvr79cfv27U6v41nQkKH0woEDB/D8889jwAAF7t07hMmTRzJWy7597+Lrr99lbP9Azeil1lqz5jXs2bO6XfYfHn4Tb70ViNTUk3j8+AI2bFiCHTtCERi45pm229pzu3bt1/jssyN49905ANp2XiZOHA5jYyMEBLwJpbL+k0I7w5w54xEXdxBWVgKMGDEcZ8+eZaSOtqAhQ3V7hw4dwty5c7Fixcs4fnwDevUSM11Sq6lUlfD3n99u2xs/fiiKin7BhAnMXMc3NeVj4cIpMDMTQiDgY/r0AEyZMhLnz19DRkZup9SwadMBhIZexNGjGyAQ8AG0/bwsWzYD3t7OePHFd6BWazqi3GbZ2VniwoUdCAoag5deegnnz59npI7WoiFDdWvR0dGYO3cu/v3vmdiwYXGXub+gtXXs3/8z8vIKOqiaznfmzKcwMKj78VIb/k8/3bK1WnJuU1Iy8cEHe7Bu3XwYG7fPA8lCQuYjJiYJO3aEtsv22sLQ0ABff70Gr7zyPAIDpyE5OZmxWlqKhgzVbanVarz66iyMHj0AGzcuYawOQgi2bDkIV9fp4HKHQyQKwL///XmdZa5ejYG7exBEogAYGw+Hl9dMXLhwDQDw9tvbsWLFZ3jw4E+wWIOhUExtdh0AuHLlDgYNeh18/kgIhaPh5TUTxcVl+O23WMjlk8BiDcYXXxwDUPOYZBOT58Dnj8SpUxF44YW3IRSOhq3tBBw+HNboseXmFsDBYTIMDf0xbtzbz3Se/vwzHzweF717W7e4npac24Z89tkREEIwceJw3XsNnZfafWzbdhh9+swAlzscEslYTJ68CgkJaXW2KZEIMHJkP+zYEdqmy27thcViYc+eYLi52WPu3DmM1dFSNGSobuuHH35Aamoqdu9exWgL5oMP9iA4+EssXDgFubnnkJNzDqtXz66zTG5uAWbMGIPU1JPIyjoLU1MeZs5cCwDYsWM5JkwYBicnGxByDSkpJ5pdp6xMhYkTV2LatFEoKLiI5OTjcHGxQ1VVNYYN80Zk5Nd19r9kyVQsXx4ElaoSAgEfR458jAcPfoSjow3mz9+I6mp1g8dmZibEgAF98OOPm3H+/I42n6Py8gqEh9/E/PmTYGTEaXE9LTm3DTl7NhKurvZ15p1r6LwAQEjIPqxZswvvvTcXeXn/RUTEbmRk5GL48IXIza3buuzXzxV//pmP2FhmWxBGRhzs3r0KkZFRuHDhAqO1NIeGDNVtHT78AyZMGM7ICLJaKlUltm8PxZgxA/HOOy9DLBaAx+PCzExYZ7lp00Zj7dp5kEgEMDMTYuLE4bpn1TemqXVSU7NRXFwGDw9HGBsbwdLSDCdObGpRf5S/f18IhSaQSsUIChqLsjIV0tPr95Oo1Rq89tp6zJs3qU6LoC02bPgWVla98NFHi1pcT0vP7dPKylR49CgLTk42zdalUlVi27Yf8NJLz2HWrHEQiUzh5eWE3buD8fixEnv3nqyzvLOzHYCamyaZ5uvrhqFDvXH48GGmS2kSDRmq27pz5w5GjmR2FtuUlEyUl1cgIGBgq9arfaiZRtPyTuS/r+PoaAMLCwlmzQpBSMg+pKZmt2r/tYyMOABQryWj0WjxyisfwsJCgnHjBrdp27V+/PEyjh79BRcu7NR1wLeknrae27y8QhBCWjR7dnz8Q5SWqjBgQJ867w8c6A4jIw6uX4+v837tNp9u4TBl5Egf3L59k+kymkRDhuq2iouLIRKZMFpDZmYeAEAqbboFcfbs73juucWQSseByx2OVau+aHbbTa3D43ERHv4lhg3zxscffwNHx5cQFPQ+VKrKZzugv7z11lYkJ2dg9+4fcf/+ozZvJzT0IjZtOoDLl79qdYuzpef2aRUVVQAALrf5Dn+lshQAYGrKq/czsdgUJSXldd7j8bh19sE0sViAoqJipstoEg0ZqtuysrJCWloOozXUjlyqrKxudJn09BxMmRIMmcwc16/vR1HRL9i8+c0mt9uSdTw8HHH69FZkZZ1FcPCrOHLkErZuPfTsBwVg+vQAXLz4GcRiAWbPXtemYbuff34MBw+eR3j4l7C27tXq9VtybhtSGwQtaSWKxaYAUC9MgJoAsrW1qPNeVVV1nX0wLTU1GzY2zV8WZBINGarbGj06AKdOXWW0Bk9PJ7DZbFy50vhd2HFxD1BdrcaSJVPh6GgDY2OjZgcqNLdOVtZjXQtDKhVj48Yl6N/f9ZlaHX83apQvevUSY+/eNbh1KwEfffRNi9clhCA4+EvExaXg5MlPGmwltERLzm1DLCwkYLFYKCoqa9E+TE15uHnzjzrvX78ej6qqavj6utV5v6iopuVjaWnWqpo6glqtwZkzkRg9OoDpUppEQ4bqtubPn49bt/7AmTMtnyKkvUmlYkybNgrHj4dj//6fUVxchrt3U+p0GMvlMgA105tUVFQhOTmj3rV+MzMhsrIeIzU1GyUl5bCy6tXkOllZ+Vi0aDMSEtJQVVWNO3eSkJaWg8GDPdv1+CZOHI45c8bj44+/wa1bCS1a5/79R/jkk+/x9denwOEMBYs1uM6rpa2tlpzbhvD5xnB0tNZdbmuKsbERVqyYiR9/vIyDB8+juLgMcXEPsHjxZlhZ9cLChZPrLF+7TS8vpxYdQ0f69tuzyMrKx+uvv850KU0jFNWNvfxyELG2lpLc3P8SQq4x8iop+ZXMnz+JmJuLiKkpjwwb5k0+/PANAoDY2lqQ2NiDJDj4VWJmJiRisYAEBgaQL75YSQAQJycbkp5+ity+fYDY28sIj8clw4Z5k5ycc02uc/XqHuLv70UkEgExMGATa+te5L335hC1OpJ8/vkKIpOZEwCEzzcmEycOJ19++W/C5xsTAMTZ2Y48eHCC7N27hgiFJgQAsbeXkU2b3iQSiYAAIA4OViQv7zwpLg4ndnaWBAAxNeWRAwfWNns+4uIOEQCNvrZs+VeL6klKOtaic9tQDUuXTiccjiEpL7+ie6+h80LINaLVRpEtW/5FnJ3tCIdjSCQSAZky5TmSmHi03nbHjx9KbGykRKuNYuzvjZBr5MGDE0QkEpDly5e39n+ZznaQTvVPdWtKpRIDBw6ASGSEX375HCKRKdMlUV1ASkom+vSZgW+++QCzZo1rl20+eVIEW9sJ+OijRVix4pV22WZbZGc/xogRiyESSfHbb7/D2Lj5UXQMolP9U92bWCxGWNhF5OQUYcSIxS26RELpP4XCFuvXL8D69fufeebnWiEh++Dj44KlS6e3y/baIiEhDUOHLoShIR/nzv23qwcMANonQ+mB3r174/r1aLDZfHh5zcT33/+X6ZL0UkJCWr3+lYZeQUHvM10qgJpZpQMDAxAU9L6uw76ttm07jJiYJJw7t113v1JnO3DgHAYNeh2Wlra4ciUCFhYWza/UBdDLZZTeUKlUWLduHbZs2YKpU0dh165/d8sZman2FRZ2HeHhN7FpU9PDxhtz6lQE7t9/hFWrXq036WdnyMl5ggULNuHcuUisXLkS69atA5fbNYZQtwB9/DKlf8LCwjBv3huoqCjD6tWzsXjxS13mvgaKaqni4jLs2BGKbdtCIZNZ4dtvv8Pgwc82+wIDaMhQ+qmoqAgbN27EF1/UDAZ4993ZuskZKaorKytT4YsvjmPLlkPQaAhWrFiJFStWgMdr2/1GDKMhQ+m33NxcbNy4EXv27IZUKsHChZPxxhsTIJOZM10aRdWRmpqNvXtPYt++n1FRUY1ly97GihUrIBZ360u+NGSoniEzMxM7d+7EN9/8B8XFxZg8eSQWLZqCUaN8u8yDzqieR6vV4ty5SOze/RP++98oyGSWmD9/Ad566y306tX6qXi6IBoyVM9SUVGB48eP46uvdiEyMgoKhRyBgaMQGBiAfv1cmC6P6gEIIbh27R6OHw/HsWO/IjMzFwEBo7F48RJMnDgRhobMjF7rIDRkqJ7r7t27+P7773H8+DGkpqZBoZBj2rTnEBgYgP79XZkuj9IjWq0W167F49ixX3DixGVkZOTA1dUF06YF4rXXXoOzszPTJXYUGjIUBQDx8fE4duwYDh/+AUlJybC0NMeIET4YM2Ygxo8fChsbKdMlUt1MXl4hrly5jUuXbuDs2Sj8+Wcuevd2wIQJExEYGIhhw4YxXWJnoCFDUU+7desWzp8/j7CwC4iKugaNRgMfH1eMHTsAo0b5YsgQLwiFzD7Hhup6njwpQlRUHMLDbyEsLBrx8Q9gbMzF8OHDMXbs83jxxRfh4eHBdJmdjYYMRTWltLQU4eHhuHjxIsLCLiApKRlsNhseHk4YMsQD/v5eGDLECy4ucqZLpTqRVqvFH3+kIirqHiIj7yIqKh6JiakghMDT0wPPP/8PPP/88xgxYkR3HXrcXmjIUFRr5OTkICoqCpGRkYiKisStW7dQUVEJqdQMvr6u8PFxho+PC7y9neHsbMfIHeJU+6quViMhIQ2xscmIjU1GTEwybt78A0plCUxM+Bg4cCD8/YdiyJAhGDJkCMzN6fD4v6EhQ1HPoqqqCrdv30ZUVBRu376N2NgYJCQkorq6Gnw+D56eTvDxUaBvXwVcXe3h4mIHOztLOmy6C9JotEhLy0Zycgb++CMVd++mIDY2BfHxD1FZWQUjIyN4errD27sf+vfvD39/f/Tt21ffRoO1NxoyFNXeKisrER8fj9jY2L9eMbh79y4KCgoBADyeMVxc5HBxsfvrJYezsx0cHKwgk5nTAOpAGo0W2dk1D4dLSkpHUlI6kpMzkZiYjpSUDFRWVgEALCyk6Nu3L3x8+sHb2xve3t5wc3MDh0NnjGglGjIU1VkeP36MpKQkJCYmIikp6a9XIpKTU1BZWQkA4HKNYGcng1xuCbncAvb2VnBwsIJcbgkrq16wtDSDmZmQ4SPpuvLzlcjLK0BW1mOkpeUgPT0HaWk5SEvLRXp6DjIzc1FdrQYA8Pk8ODs7w8XFFS4uLnB1dYWra83X3fwu+66EhgxFMU2j0SAzMxPp6elITU1FWloa0tPTkZ6epntPparQLW9kxIGFhRlkMnNYWkpgYSGBlVUvWFhIYGYmhFgsgEQigFhsqvvaxKT7dT6XlJRDqSyBUlmKwsJiKJWlUCpLUFBQjJycJ8jJKUB+vhLZ2U+Qm1uA/PwCXYAAgIkJHw4O9rC3d4Bcbg97e3vI5XLY29d8bWNjQ1uNHY+GDEV1B3l5ecjNzUV2djZyc3ORn5+P7Oxs5OXlIS8vF1lZWcjPz0dhYSEqKirrrc/hGEIsFkIiEUAg4IPPNwaXy4FQaAIDAzYkEgEMDQ0gEPBhbMzVzVpd+97TJBJBne+1WtLgM1uKi8ug0WgB1Ez8WFVVjeLiMqjVGiiVpaiuVqO0VAWVqgoVFZUoKir7K1iKoVZr6m2PxzOGRCKBpaUFrKysIZVaQCaTQSaTQSqVwsrKChYWFrCysqId8F0DDRmK0jcqlQpKpRJKpRKFhYW6r2u/LykpgUqlQkVFBUpKSlBdXQ2lshDV1dUoLS3V/QyomYZHpar7ZEmNRoPi4pJ6+xWJhGCz646m4/P5umef8HjGMDbmQSAQgMPhQCyWgMPhwNTUFDweD8bGxhCJRBCLxZBIJBCLxbpX7ffd6DkqVA0aMhRFUVSHOUQH8VMURVEdhoYMRVEU1WFoyFAURVEdhoYMRVEU1WFoyFAURVEdhoYMRVEU1WFoyPRgW7duhYWFBVgsFnbv3s34ftevXw93d3cIhUJwuVwoFAqsWrUKpaX1b/LTB1qtFtu3b4e/vz/TpbQYU38zVPdFQ6YHW7lyJSIjI7vMfsPDw/HWW28hNTUVjx8/xoYNG7Bjxw4EBgZ2eo0dLTk5GSNGjMA777yD8vJypstpMab+Zqjui85RTXUZpqamWLhwIQwMDAAA06dPx4kTJ3D06FFkZGTAzs6O4QrbR2xsLNavX4/FixejrKwM9H5oSp/RlgzVZZw5c0YXMLV69eoFAN3qX/vN8fb2xokTJzBz5kw6TQql92jIUPVoNBp8+OGHkMvl4PF46Nu3L44cOQIA6NOnD1gsFthsNnx9fXUf/qtWrYJIJIKxsTG+/fbbJrfRGn/++Sd4PB569+7d4nWuXLmCQYMGgc/nQygUwsvLC8XFxfjss89gbGwMCwsLLFq0CFZWVjA2Noa/vz+uX78OANixYwdMTEx0x2dpaQkOhwMTExP0798fw4cPh52dHYyNjSEWi7Fq1apWH9OzHAMAXL16Fe7u7rrz7eXlhQsXLjxz/S05P41pr983pYcI1aMlJycTAOSrr77Svbdy5UrC5XLJ8ePHSWFhIXn33XcJm80mN27cIGq1mjg4OBC5XE7UanWdbS1fvpxs37692W00tt+nlZWVEYFAQJYuXdri4yktLSVCoZBs3ryZqFQqkpOTQ1566SWSn59PCCFk4cKFxMTEhNy/f59UVFSQ+Ph4MnDgQCIQCEh6ejohhJC1a9cSAOT69eukrKyMPH78mIwbN44AIGfPniX5+fmkrKyMLF26lAAgMTExLa7vaX5+fsTb27tVx3Ds2DESEhJCCgoKyJMnT8jgwYOJubm5bv1nqb8l56e1fzNUj3aQhkwP9/QHhkqlInw+nwQFBemWKS8vJ1wulyxZsoQQQsj27dsJAHL06FHdMmVlZUQul5OioqIWbaMlIfPee+8RFxcXUlxc3OLjuXfvHgFAzpw50+DPFy5cSEQiUZ33bty4QQCQdevWEUL+9yFdUlKiW+a7774jAEhcXJzuvejoaAKAhIaGtri+pzUUMs0dw9M2bNhAAJC8vLxnrr8l56ctfzNUj3WQXi6j6khMTER5eTk8PT117/F4PMhkMiQkJAAA5s2bB5FIhB07duiWOXjwICZPngyhUNiibTTnxx9/xNGjR3HhwgUIBILmV/iLo6MjLCwsMGvWLISEhCA1NbXZdQYMGAA+n99kbUZGRgAAtfp/D8WqfRRvdXV1i+tridYeQ20dGk3956/Uepb6mzs/7fH7pvQXDRmqjrKyMgDA+++/DxaLpXulpaXp+l9MTU2xYMECREZGIjo6GgDw1VdfYenSpS3eRlNCQ0OxadMmXL58GQ4ODq2qn8fjITw8HMOGDcPHH38MR0dHBAUF1XsmytO4XC7y8/Nbta+O0twxnD17Fs899xykUim4XG6H9Qv9XVPn51l/35R+oyFD1SGVSgEA27dvByGkzisqKkq33NKlS8HhcLB9+3ZERETAzs4OTk5OrdpGQz7//HMcPHgQ4eHhsLa2btMxeHh44PTp08jKykJwcDCOHDmCrVu3Nrp8zUO7lLC1tW3T/jpCY8eQnp6OKVOmQCaT4fr16ygqKsLmzZs7tJbmzs+z/L4p/Ufvk6HqqB15FBMT0+Rytra2mD59Oo4cOYKsrCysXbu21dv4O0IIVq9ejcLCQpw8eRKGhm3708zKyoJSqYS7uzukUik2btyIsLAw3L9/v9F1Ll++DEIIBg8e3KZ9tremjiEuLg7V1dVYsmQJHB0dAaDDn1Pf3Plpy++b6jloS4aqw9jYGHPnzsXhw4exa9cuFBcXQ6PRIDMzE9nZ2XWWXbFiBdRqNQoLCzF69Og2baPW/fv38cknn+Drr78Gh8Opc9mFxWI12RL5u6ysLCxatAgJCQmoqqrCnTt3kJaWVucDUqvVorCwEGq1Gnfv3sXbb78NuVyOOXPmtP6EdYCmjkEulwMALl26hIqKCiQnJzc7vLi1Wnt+2vL7pnoQBkYbUF3Ep59+SiwtLQkAYmJiQl566SVCCCGVlZUkODiYyOVyYmhoSKRSKZk6dSqJj4+vt41Ro0aRffv21Xu/qW00tN+4uDgCoNHXli1bWnRMqampxN/fn0gkEmJgYECsra3Je++9pxtuvXDhQsLhcIiNjQ0xNDQkQqGQTJ48mTx48IAQQsiOHTsIn88nAIiDgwO5evUq2bRpExGJRAQAsbS0JIcOHSKhoaG6Y5BIJOTw4cMtPu9RUVFk6NChxMrKSnd8MpmM+Pv7kytXrjR7DMHBwcTMzIyIxWISGBhIvvjiCwKAODk5kRUrVjxT/c2dn/b4m6F6lIMsQuicFlTPsWjRIhw7dgxPnjxhupQuiZ4fqp0dopfLqB6nqaG+FD0/VPuiIUN1CwkJCfX6aRp6BQUF0fooqguhIUN1C25ubvWGxzb0Cg0NbXQb7777Lr755hsUFRWhd+/eOH78eJeqj2kdeX6onov2yVAURVEdhfbJUBRFUR2HhgxFURTVYWjIUBRFUR2GhgxFURTVYWjIUBRFUR2GhgxFURTVYWjIUBRFUR2GhgxFURTVYWjIUBRFUR2GhgxFURTVYf4f2EkdQQgpk1IAAAAASUVORK5CYII=", + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from IPython.display import Image\n", + "wf_2ndlevel_onesample.write_graph(graph2use='colored', format='png', simple_form=True)\n", + "\n", + "Image(filename=opj(wf_2ndlevel_onesample.base_dir, wf_2ndlevel_onesample.name, 'graph.png'))" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:11,692 nipype.workflow INFO:\n", + "\t Workflow level2_spm_1sample settings: ['check', 'execution', 'logging', 'monitoring']\n", + "240613-06:44:11,713 nipype.workflow INFO:\n", + "\t Running in parallel.\n", + "240613-06:44:11,716 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 6 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:44:12,343 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/l2source\".\n", + "240613-06:44:12,343 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/l2source\".\n", + "240613-06:44:12,344 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/l2source\".\n", + "240613-06:44:12,345 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/l2source\".\n", + "240613-06:44:12,352 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/l2source\".\n", + "240613-06:44:12,353 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/l2source\".\n", + "240613-06:44:12,364 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,364 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,366 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,365 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,379 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,379 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:44:12,382 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.001854s.\n", + "240613-06:44:12,382 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.00206s.\n", + "240613-06:44:12,382 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.002089s.\n", + "240613-06:44:12,384 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.0022s.\n", + "240613-06:44:12,384 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.002058s.\n", + "240613-06:44:12,385 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.002233s.\n", + "240613-06:44:13,727 nipype.workflow INFO:\n", + "\t [Job 0] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,738 nipype.workflow INFO:\n", + "\t [Job 1] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,740 nipype.workflow INFO:\n", + "\t [Job 2] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,741 nipype.workflow INFO:\n", + "\t [Job 3] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,742 nipype.workflow INFO:\n", + "\t [Job 4] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,743 nipype.workflow INFO:\n", + "\t [Job 5] Completed (level2_spm_1sample.l2source).\n", + "240613-06:44:13,745 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 6 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:44:14,242 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/onesampttestdes\".\n", + "240613-06:44:14,242 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/onesampttestdes\".\n", + "240613-06:44:14,244 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/onesampttestdes\".\n", + "240613-06:44:14,245 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/onesampttestdes\".\n", + "240613-06:44:14,246 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/onesampttestdes\".\n", + "240613-06:44:14,247 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.onesampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/onesampttestdes\".\n", + "240613-06:44:14,319 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:14,319 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:14,326 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:14,326 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:14,333 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:14,347 nipype.workflow INFO:\n", + "\t [Node] Executing \"onesampttestdes\" \n", + "240613-06:44:15,716 nipype.workflow INFO:\n", + "\t [MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.\n", + " Currently running:\n", + " * level2_spm_1sample.onesampttestdes\n", + " * level2_spm_1sample.onesampttestdes\n", + " * level2_spm_1sample.onesampttestdes\n", + " * level2_spm_1sample.onesampttestdes\n", + " * level2_spm_1sample.onesampttestdes\n", + " * level2_spm_1sample.onesampttestdes\n", + "240613-06:44:33,591 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.243265s.\n", + "240613-06:44:33,591 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.245873s.\n", + "240613-06:44:33,632 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.273891s.\n", + "240613-06:44:33,654 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.307857s.\n", + "240613-06:44:33,654 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.307692s.\n", + "240613-06:44:33,718 nipype.workflow INFO:\n", + "\t [Job 7] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:33,720 nipype.workflow INFO:\n", + "\t [Job 8] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:33,721 nipype.workflow INFO:\n", + "\t [Job 9] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:33,722 nipype.workflow INFO:\n", + "\t [Job 10] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:33,723 nipype.workflow INFO:\n", + "\t [Job 11] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:33,724 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 5 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_1sample.onesampttestdes\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:33,891 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2estimate\".\n", + "240613-06:44:33,892 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2estimate\".\n", + "240613-06:44:33,892 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2estimate\".\n", + "240613-06:44:33,893 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2estimate\".\n", + "240613-06:44:33,894 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2estimate\".\n", + "240613-06:44:33,902 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:33,902 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:33,903 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:33,903 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:33,907 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:33,916 nipype.workflow INFO:\n", + "\t [Node] Finished \"onesampttestdes\", elapsed time 19.58191s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:35,719 nipype.workflow INFO:\n", + "\t [Job 6] Completed (level2_spm_1sample.onesampttestdes).\n", + "240613-06:44:35,721 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + "240613-06:44:35,922 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2estimate\".\n", + "240613-06:44:35,938 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:44:37,722 nipype.workflow INFO:\n", + "\t [MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + "240613-06:44:53,77 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 19.161336s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:53,723 nipype.workflow INFO:\n", + "\t [Job 17] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:53,725 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + " * level2_spm_1sample.level2estimate\n", + "240613-06:44:53,959 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2conestimate\".\n", + "240613-06:44:53,973 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:44:54,127 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 20.220956s.\n", + "240613-06:44:54,263 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 20.357547s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:54,353 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 20.448029s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:54,574 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 20.667891s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:55,724 nipype.workflow INFO:\n", + "\t [Job 13] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:55,725 nipype.workflow INFO:\n", + "\t [Job 14] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:55,726 nipype.workflow INFO:\n", + "\t [Job 15] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:55,727 nipype.workflow INFO:\n", + "\t [Job 16] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:55,729 nipype.workflow INFO:\n", + "\t [MultiProc] Running 2 tasks, and 4 jobs ready. Free memory (GB): 219.08/219.48, Free processors: 30/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2estimate\n", + "240613-06:44:55,869 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 19.928532s.\n", + "240613-06:44:55,890 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2conestimate\".\n", + "240613-06:44:55,890 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2conestimate\".\n", + "240613-06:44:55,891 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2conestimate\".\n", + "240613-06:44:55,892 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2conestimate\".\n", + "240613-06:44:55,903 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:44:55,903 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:44:55,904 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:44:55,905 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:44:57,730 nipype.workflow INFO:\n", + "\t [Job 12] Completed (level2_spm_1sample.level2estimate).\n", + "240613-06:44:57,732 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + "240613-06:44:57,877 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2conestimate\".\n", + "240613-06:44:57,893 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:44:59,725 nipype.workflow INFO:\n", + "\t [MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + "240613-06:45:17,883 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 23.894972s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:19,725 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 23.819495s.\n", + "240613-06:45:19,728 nipype.workflow INFO:\n", + "\t [Job 23] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:19,730 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + " * level2_spm_1sample.level2conestimate\n", + "240613-06:45:19,835 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 23.929947s.\n", + "240613-06:45:19,863 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 23.956484s.\n", + "240613-06:45:19,913 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 24.005406s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:19,905 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2thresh\".\n", + "240613-06:45:19,944 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n", + "240613-06:45:21,728 nipype.workflow INFO:\n", + "\t [Job 19] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:21,730 nipype.workflow INFO:\n", + "\t [Job 20] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:21,731 nipype.workflow INFO:\n", + "\t [Job 21] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:21,732 nipype.workflow INFO:\n", + "\t [Job 22] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:21,734 nipype.workflow INFO:\n", + "\t [MultiProc] Running 2 tasks, and 4 jobs ready. Free memory (GB): 219.08/219.48, Free processors: 30/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2conestimate\n", + "240613-06:45:21,912 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2thresh\".\n", + "240613-06:45:21,912 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2thresh\".\n", + "240613-06:45:21,912 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2thresh\".\n", + "240613-06:45:21,937 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 24.03745s.\n", + "240613-06:45:21,938 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n", + "240613-06:45:21,937 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n", + "240613-06:45:21,938 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n", + "240613-06:45:21,911 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2thresh\".\n", + "240613-06:45:21,968 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:23,728 nipype.workflow INFO:\n", + "\t [Job 18] Completed (level2_spm_1sample.level2conestimate).\n", + "240613-06:45:23,730 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + "240613-06:45:23,932 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.level2thresh\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2thresh\".\n", + "240613-06:45:23,945 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2thresh\" \n", + "240613-06:45:25,729 nipype.workflow INFO:\n", + "\t [MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + "240613-06:45:33,655 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 13.708427s.\n", + "240613-06:45:33,729 nipype.workflow INFO:\n", + "\t [Job 29] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:33,731 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:33,894 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/datasink_2nd\".\n", + "240613-06:45:33,906 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:33,909 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/SPM.mat\n", + "240613-06:45:33,910 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/spmT_0001.nii\n", + "240613-06:45:33,911 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/con_0001.nii\n", + "240613-06:45:33,912 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/spmT_0001_thr.nii\n", + "240613-06:45:33,914 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.004923s.\n", + "240613-06:45:35,729 nipype.workflow INFO:\n", + "\t [Job 35] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:35,731 nipype.workflow INFO:\n", + "\t [MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + " * level2_spm_1sample.level2thresh\n", + "240613-06:45:35,938 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 13.997871s.\n", + "240613-06:45:35,976 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 14.035477s.\n", + "240613-06:45:35,975 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 14.003737s.\n", + "240613-06:45:36,79 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 14.138397s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:37,729 nipype.workflow INFO:\n", + "\t [Job 25] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:37,731 nipype.workflow INFO:\n", + "\t [Job 26] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:37,732 nipype.workflow INFO:\n", + "\t [Job 27] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:37,734 nipype.workflow INFO:\n", + "\t [Job 28] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:37,736 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 4 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_1sample.level2thresh\n", + "240613-06:45:37,771 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2thresh\", elapsed time 13.824073s.\n", + "240613-06:45:37,904 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/datasink_2nd\".\n", + "240613-06:45:37,904 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/datasink_2nd\".\n", + "240613-06:45:37,905 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/datasink_2nd\".\n", + "240613-06:45:37,905 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/datasink_2nd\".\n", + "240613-06:45:37,918 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:37,918 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:37,918 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:37,920 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/SPM.mat\n", + "240613-06:45:37,920 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/SPM.mat\n", + "240613-06:45:37,921 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/SPM.mat\n", + "240613-06:45:37,921 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/spmT_0001.nii\n", + "240613-06:45:37,921 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:37,922 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/spmT_0001.nii\n", + "240613-06:45:37,922 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/spmT_0001.nii\n", + "240613-06:45:37,922 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/con_0001.nii\n", + "240613-06:45:37,923 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/con_0001.nii\n", + "240613-06:45:37,923 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/con_0001.nii\n", + "240613-06:45:37,924 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/SPM.mat\n", + "240613-06:45:37,924 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/spmT_0001_thr.nii\n", + "240613-06:45:37,924 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/spmT_0001_thr.nii\n", + "240613-06:45:37,925 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/spmT_0001_thr.nii\n", + "240613-06:45:37,925 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/spmT_0001.nii\n", + "240613-06:45:37,925 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.005013s.\n", + "240613-06:45:37,926 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.00601s.\n", + "240613-06:45:37,926 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/con_0001.nii\n", + "240613-06:45:37,926 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.006461s.\n", + "240613-06:45:37,928 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/spmT_0001_thr.nii\n", + "240613-06:45:37,929 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.005159s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:39,729 nipype.workflow INFO:\n", + "\t [Job 24] Completed (level2_spm_1sample.level2thresh).\n", + "240613-06:45:39,731 nipype.workflow INFO:\n", + "\t [Job 31] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:39,732 nipype.workflow INFO:\n", + "\t [Job 32] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:39,733 nipype.workflow INFO:\n", + "\t [Job 33] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:39,734 nipype.workflow INFO:\n", + "\t [Job 34] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:39,735 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:45:39,888 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_1sample.datasink_2nd\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/datasink_2nd\".\n", + "240613-06:45:39,895 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd\" \n", + "240613-06:45:39,921 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/SPM.mat\n", + "240613-06:45:39,923 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/spmT_0001.nii\n", + "240613-06:45:39,924 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/con_0001.nii\n", + "240613-06:45:39,925 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/spmT_0001_thr.nii\n", + "240613-06:45:39,927 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd\", elapsed time 0.005705s.\n", + "240613-06:45:41,730 nipype.workflow INFO:\n", + "\t [Job 30] Completed (level2_spm_1sample.datasink_2nd).\n", + "240613-06:45:41,732 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf_2ndlevel_onesample.run(plugin=\"MultiProc\")\n", + "# 2min" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 2.1 Two Sample T-Test: Main effect of face, Interaction Face x Repetition" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Main effect of face: enter the following 2 contrasts per subject into a two-sample t-test and use 1 0, 0 1 F contrast\n", + "- con_0006: Positive Effect F>S \n", + "\n", + "- con_0007: Positive Effect S>U\n", + "\n", + "\n", + "\n", + "Interaction Face x Rep: enter the following 2 contrasts per subject into a two-sample t-test and use 1 0, 0 1 F contrast\n", + "- con_0009: Positive Interaction Face (F/S) x Rep \n", + "\n", + "- con_0010: Positive Interaction Face (S/U) x Rep" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "wf_2ndlevel_twosample = Workflow(name='level2_spm_2sample', base_dir=experiment_dir)\n", + "wf_2ndlevel_twosample.config[\"execution\"][\"crashfile_format\"] = \"txt\"" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "contrast_id_1 = [6] #con_0006\n", + "contrast_id_2 = [7] #con_0007 \n", + "\n", + "l2source2 = Node(DataGrabber(outfields=[\"group_1\", \"group_2\"]), name='l2source')\n", + "\n", + "l2source2.inputs.sort_filelist = True\n", + "l2source2.inputs.contrast_id_1 = contrast_id_1\n", + "l2source2.inputs.contrast_id_2 = contrast_id_2\n", + "l2source2.inputs.base_directory = opj(experiment_dir, 'level1_spm_results')\n", + "l2source2.inputs.template = '*' \n", + "\n", + "l2source2.inputs.template_args = dict(\n", + " group_1=[[\"contrast_id_1\"]],\n", + " group_2=[[\"contrast_id_2\"]])\n", + "\n", + "l2source2.inputs.field_template = dict(\n", + " group_1 = \"*/con_%04d.nii\",\n", + " group_2 =\"*/con_%04d.nii\", \n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "# SecondLevelDesign - TwoSampleTTestDesign bases Factorial Design\n", + "twosamplettestdes = Node(interface=spm.TwoSampleTTestDesign(), name=\"twosampttestdes\")\n", + "twosamplettestdes.inputs.dependent = False # measurements dependent between levels\n", + "twosamplettestdes.inputs.unequal_variance = True # equal or unequal between groups\n", + "\n", + "wf_2ndlevel_twosample.connect([(l2source2, twosamplettestdes, [('group_1', 'group1_files')]),\n", + " (l2source2, twosamplettestdes, [('group_2', 'group2_files')])])" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "l2estimate2 = Node(spm.EstimateModel(estimation_method={'Classical':1}), name='level2estimate')\n", + "\n", + "# EstimateContast - estimates group contrast\n", + "l2conestimate2 = Node(spm.EstimateContrast(group_contrast=True), name = 'level2conestimate')\n", + "\n", + "con_1 = ('Pos effect level 1','T', ['Group_{1}', 'Group_{2}'],[1, 0])\n", + "con_2 = ('Pos effect level 2','T', ['Group_{1}', 'Group_{2}'],[0, 1])\n", + "\n", + "con_3 = ('Main effect', 'F', [con_1, con_2]) # main effect of face\n", + "\n", + "l2conestimate2.inputs.contrasts = [con_1, con_2, con_3] \n", + "\n", + "\n", + "# Threshold - thresholds contrasts\n", + "level2thresh2 = MapNode(spm.Threshold(contrast_index=3,# which contrast in the SPM.mat to use --> here set for con_3: main effect\n", + " use_topo_fdr=True, # whether to use FDR over cluster extent probabilities\n", + " use_fwe_correction=False, # whether to use FWE (Bonferroni) correction for initial threshold \n", + " extent_threshold=0, # minimum cluster size in voxels\n", + " height_threshold=0.005, # value for initial thresholding (defining clusters) - voxelwise\n", + " height_threshold_type='p-value',\n", + " extent_fdr_p_threshold=0.05), # P threshold on FDR corrected cluster size probabilities\n", + " iterfield=['stat_image'],\n", + " name='level2thresh')\n", + "\n", + "wf_2ndlevel_twosample.connect([(twosamplettestdes, l2estimate2, [('spm_mat_file', 'spm_mat_file')]),\n", + " (l2estimate2, l2conestimate2, [('spm_mat_file', 'spm_mat_file'),\n", + " ('beta_images', 'beta_images'),\n", + " ('residual_image', 'residual_image')]),\n", + " (l2conestimate2, level2thresh2, [('spm_mat_file', 'spm_mat_file'),\n", + " ('spmT_images', 'stat_image')])\n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "datasink_2nd_2 = Node(DataSink(), name='datasink_2nd_2')\n", + "datasink_2nd_2.inputs.base_directory=opj(experiment_dir, 'level2_spm_results_2sample')\n", + "\n", + "wf_2ndlevel_twosample.connect([(l2conestimate2, datasink_2nd_2, [('spm_mat_file', '2ndLevel.@spm_mat'),\n", + " ('spmT_images', '2ndLevel.@T'),\n", + " ('con_images', '2ndLevel.@con')]),\n", + " (level2thresh2, datasink_2nd_2, [('thresholded_map',\n", + " '2ndLevel.@threshold')]) \n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "subFolders = [('2ndLevel/', 'MainEffectFace/')]\n", + "subFolders1 = [('_con_', 'con')] \n", + "subFolders2 = [('_level2thresh0', 'thresh_con1')]\n", + "subFolders3 = [('_level2thresh1', 'thresh_con2')]\n", + "subFolders4 = [('_level2thresh2', 'thresh_con3')]\n", + "\n", + "\n", + "subFolders.extend(subFolders1)\n", + "subFolders.extend(subFolders2)\n", + "subFolders.extend(subFolders3)\n", + "subFolders.extend(subFolders4)\n", + "\n", + "datasink_2nd_2.inputs.substitutions = subFolders" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:44,410 nipype.workflow INFO:\n", + "\t Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/graph.png (graph2use=colored, simple_form=True).\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from IPython.display import Image\n", + "wf_2ndlevel_twosample.write_graph(graph2use='colored', format='png', simple_form=True)\n", + "\n", + "Image(filename=opj(wf_2ndlevel_twosample.base_dir, wf_2ndlevel_twosample.name, 'graph.png'))" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:45:44,421 nipype.workflow INFO:\n", + "\t Workflow level2_spm_2sample settings: ['check', 'execution', 'logging', 'monitoring']\n", + "240613-06:45:44,427 nipype.workflow INFO:\n", + "\t Running in parallel.\n", + "240613-06:45:44,429 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:45:44,938 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/l2source\".\n", + "240613-06:45:44,946 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:45:44,952 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.00239s.\n", + "240613-06:45:46,432 nipype.workflow INFO:\n", + "\t [Job 0] Completed (level2_spm_2sample.l2source).\n", + "240613-06:45:46,436 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:45:46,685 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.twosampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/twosampttestdes\".\n", + "240613-06:45:46,697 nipype.workflow INFO:\n", + "\t [Node] Executing \"twosampttestdes\" \n", + "240613-06:45:48,430 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.twosampttestdes\n", + "240613-06:46:02,47 nipype.workflow INFO:\n", + "\t [Node] Finished \"twosampttestdes\", elapsed time 15.346838s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:46:02,431 nipype.workflow INFO:\n", + "\t [Job 1] Completed (level2_spm_2sample.twosampttestdes).\n", + "240613-06:46:02,433 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:46:02,580 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2estimate\".\n", + "240613-06:46:02,590 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:46:04,432 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.level2estimate\n", + "240613-06:46:22,491 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 19.898428s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:46:24,433 nipype.workflow INFO:\n", + "\t [Job 2] Completed (level2_spm_2sample.level2estimate).\n", + "240613-06:46:24,435 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:46:24,580 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2conestimate\".\n", + "240613-06:46:24,595 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:46:26,434 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.level2conestimate\n", + "240613-06:46:41,400 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 16.802565s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:46:42,435 nipype.workflow INFO:\n", + "\t [Job 3] Completed (level2_spm_2sample.level2conestimate).\n", + "240613-06:46:42,437 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:46:44,435 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 3 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:46:44,580 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0\".\n", + "240613-06:46:44,581 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1\".\n", + "240613-06:46:44,582 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2\".\n", + "240613-06:46:44,592 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh0\" \n", + "240613-06:46:44,592 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh1\" \n", + "240613-06:46:44,592 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh2\" \n", + "240613-06:46:46,440 nipype.workflow INFO:\n", + "\t [MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 218.88/219.48, Free processors: 29/32.\n", + " Currently running:\n", + " * _level2thresh2\n", + " * _level2thresh1\n", + " * _level2thresh0\n", + "240613-06:46:56,734 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh1\", elapsed time 12.139144s.\n", + "240613-06:46:56,789 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh0\", elapsed time 12.19431s.\n", + "240613-06:46:56,825 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh2\", elapsed time 12.230605s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:46:58,442 nipype.workflow INFO:\n", + "\t [Job 6] Completed (_level2thresh0).\n", + "240613-06:46:58,444 nipype.workflow INFO:\n", + "\t [Job 7] Completed (_level2thresh1).\n", + "240613-06:46:58,445 nipype.workflow INFO:\n", + "\t [Job 8] Completed (_level2thresh2).\n", + "240613-06:46:58,446 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:46:58,601 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0\".\n", + "240613-06:46:58,606 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh0\" - collecting precomputed outputs\n", + "240613-06:46:58,608 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh0\" found cached.\n", + "240613-06:46:58,609 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1\".\n", + "240613-06:46:58,611 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh1\" - collecting precomputed outputs\n", + "240613-06:46:58,612 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh1\" found cached.\n", + "240613-06:46:58,614 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2\".\n", + "240613-06:46:58,616 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh2\" - collecting precomputed outputs\n", + "240613-06:46:58,617 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh2\" found cached.\n", + "240613-06:47:00,443 nipype.workflow INFO:\n", + "\t [Job 4] Completed (level2_spm_2sample.level2thresh).\n", + "240613-06:47:00,445 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:47:00,588 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.datasink_2nd_2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/datasink_2nd_2\".\n", + "240613-06:47:00,602 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd_2\" \n", + "240613-06:47:00,604 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/SPM.mat\n", + "240613-06:47:00,605 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmT_0001.nii\n", + "240613-06:47:00,606 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmT_0002.nii\n", + "240613-06:47:00,607 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmF_0003.nii\n", + "240613-06:47:00,608 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/con_0001.nii\n", + "240613-06:47:00,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/con_0002.nii\n", + "240613-06:47:00,610 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/ess_0003.nii\n", + "240613-06:47:00,612 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh0/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con1/spmT_0001_thr.nii\n", + "240613-06:47:00,613 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh1/spmT_0002_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con2/spmT_0002_thr.nii\n", + "240613-06:47:00,614 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh2/spmF_0003_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con3/spmF_0003_thr.nii\n", + "240613-06:47:00,615 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd_2\", elapsed time 0.011128s.\n", + "240613-06:47:02,443 nipype.workflow INFO:\n", + "\t [Job 5] Completed (level2_spm_2sample.datasink_2nd_2).\n", + "240613-06:47:02,445 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf_2ndlevel_twosample.run(plugin=\"MultiProc\")" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:47:04,529 nipype.workflow INFO:\n", + "\t Workflow level2_spm_2sample settings: ['check', 'execution', 'logging', 'monitoring']\n", + "240613-06:47:04,536 nipype.workflow INFO:\n", + "\t Running in parallel.\n", + "240613-06:47:04,538 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:47:04,680 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.l2source\".\n", + "240613-06:47:05,42 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.l2source\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/l2source\".\n", + "240613-06:47:05,46 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.l2source\".\n", + "240613-06:47:05,57 nipype.workflow INFO:\n", + "\t [Node] Executing \"l2source\" \n", + "240613-06:47:05,75 nipype.workflow INFO:\n", + "\t [Node] Finished \"l2source\", elapsed time 0.002216s.\n", + "240613-06:47:06,547 nipype.workflow INFO:\n", + "\t [Job 0] Completed (level2_spm_2sample.l2source).\n", + "240613-06:47:06,552 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:47:06,796 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.twosampttestdes\".\n", + "240613-06:47:06,802 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.twosampttestdes\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/twosampttestdes\".\n", + "240613-06:47:06,806 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.twosampttestdes\".\n", + "240613-06:47:06,813 nipype.workflow INFO:\n", + "\t [Node] Executing \"twosampttestdes\" \n", + "240613-06:47:08,539 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.twosampttestdes\n", + "240613-06:47:22,398 nipype.workflow INFO:\n", + "\t [Node] Finished \"twosampttestdes\", elapsed time 15.58235s.\n", + "240613-06:47:22,539 nipype.workflow INFO:\n", + "\t [Job 1] Completed (level2_spm_2sample.twosampttestdes).\n", + "240613-06:47:22,541 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:47:22,685 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2estimate\".\n", + "240613-06:47:22,690 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.level2estimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2estimate\".\n", + "240613-06:47:22,694 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2estimate\".\n", + "240613-06:47:22,704 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2estimate\" \n", + "240613-06:47:24,541 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.level2estimate\n", + "240613-06:47:42,212 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2estimate\", elapsed time 19.50542s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:47:42,541 nipype.workflow INFO:\n", + "\t [Job 2] Completed (level2_spm_2sample.level2estimate).\n", + "240613-06:47:42,543 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:47:42,685 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2conestimate\".\n", + "240613-06:47:42,691 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.level2conestimate\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2conestimate\".\n", + "240613-06:47:42,696 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2conestimate\".\n", + "240613-06:47:42,705 nipype.workflow INFO:\n", + "\t [Node] Executing \"level2conestimate\" \n", + "240613-06:47:44,542 nipype.workflow INFO:\n", + "\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.\n", + " Currently running:\n", + " * level2_spm_2sample.level2conestimate\n", + "240613-06:47:59,416 nipype.workflow INFO:\n", + "\t [Node] Finished \"level2conestimate\", elapsed time 16.708273s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:48:00,543 nipype.workflow INFO:\n", + "\t [Job 3] Completed (level2_spm_2sample.level2conestimate).\n", + "240613-06:48:00,545 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:48:02,543 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 3 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:48:02,691 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh0\".\n", + "240613-06:48:02,694 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh1\".\n", + "240613-06:48:02,696 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh2\".\n", + "240613-06:48:02,696 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0\".\n", + "240613-06:48:02,701 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh0\".\n", + "240613-06:48:02,698 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1\".\n", + "240613-06:48:02,700 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2\".\n", + "240613-06:48:02,709 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh1\".\n", + "240613-06:48:02,711 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"_level2thresh2\".\n", + "240613-06:48:02,714 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh0\" \n", + "240613-06:48:02,716 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh1\" \n", + "240613-06:48:02,718 nipype.workflow INFO:\n", + "\t [Node] Executing \"_level2thresh2\" \n", + "240613-06:48:04,544 nipype.workflow INFO:\n", + "\t [MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 218.88/219.48, Free processors: 29/32.\n", + " Currently running:\n", + " * _level2thresh2\n", + " * _level2thresh1\n", + " * _level2thresh0\n", + "240613-06:48:14,610 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh1\", elapsed time 11.89035s.\n", + "240613-06:48:14,622 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh0\", elapsed time 11.904817s.\n", + "240613-06:48:14,731 nipype.workflow INFO:\n", + "\t [Node] Finished \"_level2thresh2\", elapsed time 12.0103s.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n", + "stty: 'standard input': Inappropriate ioctl for device\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "240613-06:48:16,544 nipype.workflow INFO:\n", + "\t [Job 6] Completed (_level2thresh0).\n", + "240613-06:48:16,546 nipype.workflow INFO:\n", + "\t [Job 7] Completed (_level2thresh1).\n", + "240613-06:48:16,546 nipype.workflow INFO:\n", + "\t [Job 8] Completed (_level2thresh2).\n", + "240613-06:48:16,547 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:48:16,695 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2thresh\".\n", + "240613-06:48:16,706 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.level2thresh\".\n", + "240613-06:48:16,723 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh0\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0\".\n", + "240613-06:48:16,727 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh0\" - collecting precomputed outputs\n", + "240613-06:48:16,728 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh0\" found cached.\n", + "240613-06:48:16,729 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh1\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1\".\n", + "240613-06:48:16,731 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh1\" - collecting precomputed outputs\n", + "240613-06:48:16,732 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh1\" found cached.\n", + "240613-06:48:16,734 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"_level2thresh2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2\".\n", + "240613-06:48:16,737 nipype.workflow INFO:\n", + "\t [Node] Cached \"_level2thresh2\" - collecting precomputed outputs\n", + "240613-06:48:16,738 nipype.workflow INFO:\n", + "\t [Node] \"_level2thresh2\" found cached.\n", + "240613-06:48:18,544 nipype.workflow INFO:\n", + "\t [Job 4] Completed (level2_spm_2sample.level2thresh).\n", + "240613-06:48:18,547 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n", + "240613-06:48:18,693 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.datasink_2nd_2\".\n", + "240613-06:48:18,698 nipype.workflow INFO:\n", + "\t [Node] Setting-up \"level2_spm_2sample.datasink_2nd_2\" in \"/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/datasink_2nd_2\".\n", + "240613-06:48:18,703 nipype.workflow INFO:\n", + "\t [Node] Outdated cache found for \"level2_spm_2sample.datasink_2nd_2\".\n", + "240613-06:48:18,709 nipype.workflow INFO:\n", + "\t [Node] Executing \"datasink_2nd_2\" \n", + "240613-06:48:18,712 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/SPM.mat\n", + "240613-06:48:18,713 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmT_0001.nii\n", + "240613-06:48:18,714 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmT_0002.nii\n", + "240613-06:48:18,716 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmF_0003.nii\n", + "240613-06:48:18,717 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/con_0001.nii\n", + "240613-06:48:18,718 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/con_0002.nii\n", + "240613-06:48:18,719 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/ess_0003.nii\n", + "240613-06:48:18,720 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh0/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con1/spmT_0001_thr.nii\n", + "240613-06:48:18,721 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh1/spmT_0002_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con2/spmT_0002_thr.nii\n", + "240613-06:48:18,722 nipype.interface INFO:\n", + "\t sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh2/spmF_0003_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con3/spmF_0003_thr.nii\n", + "240613-06:48:18,724 nipype.workflow INFO:\n", + "\t [Node] Finished \"datasink_2nd_2\", elapsed time 0.011743s.\n", + "240613-06:48:20,545 nipype.workflow INFO:\n", + "\t [Job 5] Completed (level2_spm_2sample.datasink_2nd_2).\n", + "240613-06:48:20,547 nipype.workflow INFO:\n", + "\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "contrast_id_1 = [9] #con_0009\n", + "contrast_id_2 = [10] #con_0010 \n", + "\n", + "l2source2.inputs.contrast_id_1 = contrast_id_1\n", + "l2source2.inputs.contrast_id_2 = contrast_id_2\n", + "\n", + "subFolders = [('2ndLevel/', 'InteractionFace_Repetition/')]\n", + "subFolders.extend(subFolders1)\n", + "subFolders.extend(subFolders2)\n", + "subFolders.extend(subFolders3)\n", + "subFolders.extend(subFolders4)\n", + "\n", + "datasink_2nd_2.inputs.substitutions = subFolders\n", + "\n", + "wf_2ndlevel_twosample.run(plugin=\"MultiProc\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Results\n", + "The group analysis was only done on N=9 subjects, a voxel-wise threshold of p<0.005 was chosen and a cluster-wise FDR threshold of p<0.05 to correct for multiple comparisons." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Look at the positive effect using the plot_stat_map plotting method of nilearn" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.11/site-packages/nilearn/plotting/img_plotting.py:1317: UserWarning: Non-finite values detected. These values will be replaced with zeros.\n", + " safe_get_data(stat_map_img, ensure_finite=True),\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotting.plot_stat_map(opj(experiment_dir, 'level2_spm_results_1sample/con5/spmT_0001_thr.nii'), title='Positive Effect', dim=1, display_mode='y', cut_coords=(-45, -30, -15, 0, 15), threshold=2, vmax=8, cmap='viridis');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Look at the results using the glass brain plotting method of nilearn" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.11/site-packages/nilearn/plotting/img_plotting.py:1471: UserWarning: Non-finite values detected. These values will be replaced with zeros.\n", + " safe_get_data(stat_map_img, ensure_finite=True),\n", + "/opt/conda/lib/python3.11/site-packages/nilearn/plotting/displays/_slicers.py:308: UserWarning: empty mask\n", + " ims = self._map_show(img, type=\"imshow\", threshold=threshold, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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", 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jY73ncHNzw40bNxAXFwcAUKlUWL9+Pd58803MmDEDM2bMgLe3N7p27YrRo0fXKMgwxMiRI7FkyRJs3bqVD5KLiorw+++/Qy6X6wSw3Nq/9+7dqzSRT0pKSqWPzZ1v5MiRegOuqpyrMikpKXyiJ6lUWum+wP+TsXl4eBicuKimKlsCijGGadOmYdWqVeVmcs7OztZ7u6OjY5nbuIzKdnZ2EIlE5d5fOiEYl5irdGK40rjbuc94dS1ZsgS3bt3Cn3/+iT///BPm5ubo0KEDBgwYgFGjRkEulxt8rpCQEPj7+6N169aYOnUqEhMTceHCBRQWFuoEyYa8z9zrXt6+Tk5Oem9XKpVIS0szuMwA8MUXX2DWrFkGL8HE0fdeAyXvZ2pqaoWfBX3J32oqMzMTgwYNwrFjx8rdp7zPLWXKJoQQQkh969ixI6ZPn46QkBA4ODjgpZdewp49e3T2WbBgASZMmAAzMzOcOXMG77zzDqKiohqoxOWr93WSq0NfxXrEiBHo0aMH9uzZg0OHDuHEiRNYu3Yt1q5diylTpmDlypU1ftzy+Pn5ITg4GFevXsWdO3fg4+ODAwcOID09HUOHDoVKpeL35Xqw7OzsKu0ldnV1rfSxufP16dMHtra25e5nZWVlyFMx6LFMTEwwePDgCvf19/ev8ePVle3bt+OLL76As7MzVq1ahXbt2sHa2hoSiQRFRUWQyWTlBs8V9cJWpYe2MtVpUNCXVdnZ2RmXL1/GsWPHsG/fPpw4cYIPmJctW4Zz587B0tKywvMyxnDy5Els3rwZv//+O7KysiAQCNCtWzeMGTNG5/MNgF8iLS8vr9xzcveV1xBWW6/l+fPnMXXqVJiammL16tXo0qUL7OzsIJPJAAAODg7l9vpWVobafL8NMXPmTBw7dgydO3fGggULEBAQADMzM4hEIhw6dAi9e/cu93NblcYQQgghhJDaYGxsjBs3bmDjxo34448/ytw/Y8YMTJo0CWPGjEF0dDQWLlyIgwcPws/Pr046HGqizoPkylhaWkIqlSIlJQW5ubl6K9Fc7+nTPTnW1tYYP348xo8fD8YYDh48iGHDhuGLL77AuHHj6jRwGzlyJK5du4atW7fi008/1TvUGvh/D1llvZ2G4s43fvz4SgPXmuKWuxIKhfjxxx8NCuScnZ0BAA8ePABjrN56kyvCfUm/++479OvXT+e+Bw8e1EsZHBwccOfOHcTExOj9XOr7jHO9908v2wQAGo0GT5480ftYYrEYvXr14ocHx8TEYNy4cTh27Bg+//xzLFu2TO9xkZGR2LJlC7Zs2cIv7eXt7Y0ZM2Zg9OjR5fZOOjk5ISIiosLXkruvvB7j2sK914sXL+ZHsXDy8/PLfc0aoz/++AMikQh79+4t0zBRX59bQgghhBBD/f333/j777/LvX/y5MlYtGgR9u7dCwB47bXXkJiYiJdeegnbt2+vr2IapEHWSS5NIpGgbdu2AKB37c+wsDDcuHEDJiYmaN68ebnnEQgE6NOnDx8EhYeHV/rYXBCiVqurXO4RI0ZAKBTi119/RVZWFv78809YWFjghRde0NnPyckJvr6+iIiIwN27d6v8OE/r2bMnAOhtnaltYrEYXbp0QVZWFo4ePWrQMQ4ODmjatCkyMjLw+++/G3SMRCKp1ntgqPT0dAD6A7Tffvutzh63NG6u+K+//lrmPm6ofun9AMDe3h4A9H5u/vnnH4OHE7u6umLmzJkASr5PpSUlJWHNmjVo1aoV/Pz8sGTJEmRlZeHNN9/EmTNncOfOHcyZM6fC4budOnUCULIWtT5arZa/r/TzqwsVvde///57uT2vjVF6ejpUKlWZABmov88tIYQQQkhtcHd3h729PY4cOcLflpWVhQsXLqBdu3YNWDL9GjxIBoD3338fADB//nydHpLs7Gy89957YIzhrbfe4ocQXrt2Dbt27UJRUZHOedLS0nDhwgUA/+/RrAiX7OvOnTtVLrODgwO6du2KqKgozJw5EwUFBRg6dGiZJE8AMHfuXGi1WgwePBjXr18vc39qairWr19v0OMOHjwYfn5+2Lp1KxYuXFhmaAJjDGfOnMGZM2eq/Jz0mTNnDoRCIV5//XUcP368zP05OTnYuHEj8vPz+dtmzZoFAJgyZQpu3ryps39BQQEOHz6sc5uDgwMSExORkZFRK2V+mre3NwBg3bp1OkHSqVOnsHz58jp5zKe98cYbUCgU2LZtm04wqdVqMXv2bMTFxSEkJERnPj0XfG7ZsoXvaQaA6OhoTJo0Se/jrFq1Sm9v6V9//QWg7PfC0dERH3zwAa5du4YXXngB27ZtQ0JCAtauXYv27dsb9NzGjRsHExMT/P3331i7dq3OfRqNBnPmzMGdO3fg5ORU56MfuPd6w4YNOo0IERERfEPBs8Lb2xvp6ellWlZXrVqFf/75p4FKRQghhBBSdXZ2dgCAxMREndsTExP5+wwhk8mgVCoN3rgpd9VRpXTYNV0nuTzcGqYKhYL169ePDR06lFlbWzMArG3btiw3N5ffl1sGydTUlHXv3p2NHDmS9evXjymVSgaAvfjiizrnLm8JqJUrVzIAzNbWlg0fPpy98cYbbObMmZUex9m4caPOa3Pq1Klyn9/s2bMZACYUClmLFi3Y0KFD2ZAhQ1hwcDATiUTM1NTU4Nfq7t27zN3dnQFgNjY2rEePHuzVV19lvXr1YjY2NgwAW7Vqlc4x1V0CijHGvvvuOyYSiRhQstbzoEGD2LBhw1ibNm2YTCZjAFh6errOMe+//z4DwEQiEevQoQMbMWIE69KlCzMzM2PNmjXTu6+7uzsbOXIke+ONN9iyZcsqfR0MXSf5zp07zNjYmAEl690OHz6cdezYkQkEAjZt2jS956jsNanoccv73Pz8889MKBQygUDAvyY+Pj78Z1DfEkuvvfYa/1l/8cUXWffu3ZmxsTEbOnSo3mWGTE1NmVAoZMHBweyVV15hQ4cOZd7e3gwAs7Cw0FmHnDHG/P392bJly1h8fHyFr2Fldu3axX8WfHx82LBhw9iQIUOYi4sLA8DMzMzKrF/OWPWWuWKs/Nc/JSWF2dnZ8Z+nV155hfXo0YNJJJJyXzNuCagxY8ZUqQwVlb82loDasmUL/9vSsWNHNmLECObn58eEQiH78MMP9Za5st+s8tASULTRRhtttNFGW21ujP1/KVkArF27dowxxtfTuG379u1s27ZtBp1TJpNVqX7DGGPx8fF8HbWKW9UOqKsgmbGSIKJ9+/bMxMSEyeVy5u/vzxYvXszy8vJ09ktISGCLFi1i3bp1Y05OTkwqlTJbW1sWGhrKNm7cWGZd2/IqjsXFxezjjz9mnp6eTCKRMEC3AltZhTMzM5PJ5XL+OK1WW+HzO3HiBBs6dChzcHBgEomEWVpasqCgIPbee++xEydOGPw6MVayfuuiRYtYixYt+NfLzc2N9e7dm33zzTdl1lyuSZDMGGPXrl1jY8aMYa6urkwqlTIzMzPm7+/Pxo0bx/bt26f3ue/Zs4f17t2bWVhYMKlUypycnFj//v3Zrl27dPbLyclh7733HnN2dmZisZgBhq0Za2iQzBhjkZGR7MUXX2Q2NjbMyMiIBQcHs3Xr1jHG9AcudREkM8bYmTNn2IsvvsgsLS2ZRCJhLi4u7J133mGxsbF6z1VYWMhmzZrFnJ2dmVQqZZ6enmzRokVMrVbrDcR+/vln9uqrrzIfHx+mVCqZUqlkfn5+bMqUKeU+Rm0JDw9nb7zxBvPw8GAymYwpFArm6+vLPvjgA/bo0SO9x9R2kMxYyVrPr776KnN0dGRyuZw1bdqUffbZZ+W+Zo01SGaMsf3797O2bdsypVLJzMzMWI8ePdjx48fLLTMFybTRRhtttNFGW2PYGNMNkt3d3RljjDVr1kxnv+PHj7Mvv/zSoHMqlcoq1W84XEdqVTbBv38YjMvqTAgh5PnQokULXLt2raGLQQghhJDnBGOszBJQ8fHxWLFiBb744gsAJUt9JiUlYezYsQYl7lIqlcjKygJQUIWSyKFSqcpdNrM8DZ7dmhBCCCGEEELIs83Y2BheXl78/93d3dGsWTOkpaXh8ePH+PLLL/Hxxx/j3r17/BJQ8fHx2L17d8MVuhwUJBNCCCGEEEIIqZGWLVvqJPpdtWoVAOCnn37C66+/jmXLlsHY2Bjr1q2DmZkZTp8+jT59+lRjjeSq9SRXBw23JoSQ/zgabk0IIYSQxu7/w60zqnCUWbWGWzeKJaAIIYQQQgghhJDGgIZbE0IIIYQQQgh5RhTCsMHQgmo/AvUkE0IIIYQQQggh/6KeZEIIIYQQQgghz4gCUE8yIYQQQgghhBBSTyhIJoQQQgghhBBC/lXl4dYpKSnIz8+HQqGoi/IQQgipR/n5+UhJSWnoYhBCCCGEGKgIgNaA/arfH1zlIPnx48fw8fGBlZVVtR+UEEJI45CSkoLHjx83dDEIIYQQQhqNaiXuevz4MVWqCCGEEEIIIYTUswLUdU8yzUkmhBBCCCGEEEL+RUEyIYQQQgghhBDyL1onmRBCCCGEEELIM6IQgMaA/UTVfgTqSSaEEEIIIYQQQv5FPcmEEEIIIYQQQp4RBaCeZEIIIYQQQgghpJ5QkEwIIYQQQgghhPyLhlsTQgghhBBCCHlG0HBrQgghhBBCCCGk3lBPMiGEEEIIIYSQZ0QhALUB+1U/1KWeZEIIIYQQQggh5F8UJBNCCCGEEEIIIf+i4daEEEIIIYQQQp4RBaDh1oQQQgghhBBCSD2hnmRCCCGEEEIIIc+IQgDFBuwnqfYjUE8yIYQQQgghhBDyLwqSCSGEEEIIIYSQf9Fwa0IIIYQQQgghzwhDh1trq/0I1JNMCCGEEEIIIYT8i3qSCSGEEEIIIYQ8IwoBFBmwH/UkE0IIIYQQQgghNUZBMiGEEEIIIYQQ8i8abk0IIYQQQggh5BlRABpuTQghhBBCCCGE1BPqSSaEEEIIIYQQ8oygnmRCCCGEEEIIIaTeUJBMCCGEEEIIIYT8i4ZbE0IIIYQQQgh5RhT+u1WGVfsRqCeZEEIIIYQQQgj5F/UkE0IIIYQQQgh5RhSAepIJIYQQQgghhJB6Qj3JhBBCCCGEEEKeEYUo6U2uO9STTAghhBBCCCGE/IuCZEIIIYQQQggh5F803JoQQgghhBBCyDOiADTcmhBCCCGEEEIIqScUJBNCCCGEkP+sMWPGgDGGkJCQhi4KecZxnyVuKy4uRmxsLH788Uc4ODg0dPGeI0UoSd5V2VZU7Ueg4daEEEIIIYQQUkvmzp2L6OhoyOVytG3bFmPHjkWHDh0QEBCAwkJD1vclDY2CZEIIIYQQQkidcXBwgKWlJWQyGZRKJQQCAbKyspCWlob09HSkp6c3dBFr1YEDB3DlyhUAwIYNG5CSkoJZs2ZhwIAB+P333xu4dMQQFCQTQgghhBDynLOxsUFgYCCCgoJgY2MDMzMzmJqaoqioCKmpqUhJSUFMTAwuX76Mu3fv1uixZDIZWrZsiRYtWqBFixawtLQEACQlJcHGxqbM/rm5ubh79y5u376NyMhIhIWFQa1W16gMjcmpU6cwa9YseHp6NnRRnhOGJu4SVPsRKEgmhBBCCCHkOWRnZ4c+ffqgVatWcHZ2RmxsLJycnMrsZ2FhgSZNmqBdu3YYPnw4MjMzcfHiRRw4cABRUVEGP56ZmRn69++Pvn37wsTEpMz9crlc73HGxsYIDg5GcHAwgJKg+cyZMzhx4gTCwsLAGDO4DI2Rm5sbADx3PebPMwqSCSGEEEIIeY64u7tjyJAh6NChAwQC/b1p+fn5yMzMhFQqhbm5uc5+pqam6NmzJ3r06IFr167h2LFjOHfuHIqLi/Wey9PTE3379kVISAgsLCx07isqKsKtW7fw8OFD5OTkIC8vD0BJQG1ubg5LS0t4eXnB3NycP8bY2Bi9evVCr169kJSUhB07duDw4cPQaDQ1fWnqhampKSwtLSGXy9GmTRvMmzcPBQUF2LdvX0MX7TlBPcmEEEIIIYQQA/j7+2PIkCFlMnUzxnD79m1cunQJN2/eRHR0tE7AKxKJYGVlhaCgIISGhsLPzw9yuRwJCQn8kOmioiLcvHkT165dQ1ZWFgQCAby8vBAaGgpra2totVoAQFxcHOzs7HDy5EkcO3YMERER5QbXpVlbW8PX1xctW7ZEu3bt+F5nGxsb9O3bF0OGDMFPP/2E06dP1+IrVjeOHj2q8//o6GiMGjUKcXFxDVQiUlUUJBNCCCGEEPIMa926NYYOHQofHx+d2zMzM7Fnzx4cPHgQ2dnZFZ7D1NQU9+7dQ2FhIZYsWYLOnTujY8eO/NJFUqkULVu2RNu2bZGfnw+JRAKgZEi3s7MzCgsLcfv2bZw8eRKHDh1CampqlZ5DcnIykpOTcerUKXzzzTdo1aoVevXqheDgYFhYWEClUmHGjBkYOHAgfvjhB9y5c6dK569P7777Lu7evQtTU1OMGzcOnTp1oqzWzxgKkgkhhBBCCHkG+fr6Yty4cfD19dW5PSkpCTt37sSRI0cq7cWVyWQICAiAsbExcnJyYGRkBDs7Oxw+fBiHDx+Gv78/unfvjhdffBG+vr4Qi8W4dOmSzvGZmZnIyMjAtGnTEBYWpnN+oVAIDw8PaDQa5OTkIDk5udLnVVRUhDNnzuDMmTPw9vbGqFGj0Lx5cwCAj48Pli9fjlOnTuGnn34y6Hz17eLFi3x26927d+P06dP45Zdf4OPjg9zc3AYu3fOgEIYNtxZW+xEoSCaEEEIIIeQZYmdnh7Fjx6J9+/Y6t8fExGDHjh04deoUP/y5IhKJBEFBQVAoFAAAgUCAwsJCODk54dGjRwCA8PBwhIeHIyIiAjNnzoRSqcTly5dx9epVpKamol+/fggKCgIAPHz4sMxjuLu7w8HBAfn5+XB0dER+fj5ycnIMfq53797FJ598gpCQEIwbNw7Ozs4AgI4dO6Jt27bYs2cPduzYwc91bmy0Wi0++ugjHD9+HO+99x4+//zzhi4SMQAFyYQQQgghhDwDlEolhg8fjr59+0IkEvG3P378GJs2bcLFixcNPpdQKIS/vz8UCgUYY7h79y6kUimMjY31JshKSUlBfn4+8vPzERUVxSeh6t+/P7+PviHFXJZrlUqF4uJiNG3aFFeuXDEoiOeec15eHq5cuYJr166hd+/eePXVV2FqagqJRIIhQ4agV69e2LJlCw4ePNgoM2GfOHECFy5cwOTJk/Hll1/S0OsaMzRxF/UkE0IIIYQQUm3jxo1Dnz59yty+evXqKvV81gWxWIz+/fsjNDRUZ95xRkYGtm7disOHD+sEnZaWlsjLy0N+fn655/Ty8oKxsTGAksRSiYmJcHV1RUFBAQoKygYgpQNnsfj/IYRMJuP/1je0m+uljo+Ph7W1NRQKBZydnRETE1Pp83Z3d4ezszMKCgoQERGBnJwcHDhwACdOnMCQIUMwcOBASCQSqFQqvPvuu+jevTu+/vprg85d35YvX44dO3Zg7NixWLt2bUMXh1SCgmRCCCGEEPKf9+677+q9/aeffmrQILl9+/Z4/fXXYWtry/fGZmRkYNeuXdi1a1eZXklra2s0bdoUAFBQUICEhAQkJiaiqKgIQEkPso+PD6ytrVFUVIT4+HjExsYCKAl+5XI51Gp1mXKUvq10LzYXJHPnf5pQWNKbl5mZCaAkgLe0tERiYqLeYJxjamrKD63mer0vXLgAAMjLy8PPP/+MAwcOYMyYMejUqROAkvnKX375Jf744w9s27at3DI1hF27diEqKgrTpk3D+vXrDe5JJw2DgmRCCCGEEPKftWnTJmzatKmhi1GGs7Mz3n33Xfj7+/O3mZmZ4dq1a5gyZQrS09P1HmdjY8P/LZfLYWNjAzc3N+Tk5CA/Px8qlYpfXikrKwvR0dH8/lzwq2+4dXk9yVKpFID+odZPi4qKgkqlgomJCZo0aYJbt26Vu6+9vT1fXoFAoLeXOjk5GStWrMBff/2F9957D05OTlAoFBg9ejQ6duyIb775BtevX6+0XLWlos8SYwxNmjSpt7I83wxN3CWqfJdyVH+gNiGEEEIIIaTWDRw4EF9++aVOgHzz5k2sXr0a0dHR5QbIQMmwZg5jDGKxGAKBAEqlEjY2NnyAHBcXh8jISJ1juV5ffUFyZT3J5QXJWq0WWq0WjDEUFxfzvdbm5uawt7fXe4xKpYKNjQ0UCgUSExMrnWccERGBSZMmYevWrfx5bW1t8emnn2Lq1KlQqVQVHk/I0yhIJoRU2ZgxY8AYQ0hISEMXhTzjuM8St3EVqB9//JFfm5MQQv4rrK2tsXjxYrzxxhv8OsTx8fFYuHAhPv74Yxw/fhwBAQF8Mix90tPTkZOTA8YYMjIycO3aNdy7dw+JiYnIzs5GQkICwsLCcP/+/TLBZ3V6kisKko2NjSGVSiEUCpGVlcU/H27NZi8vL5iZmekcIxaL+eHiRUVF/L6VDU9Wq9XYvn07NmzYgCdPnvC3d+7cGd9//32ZTODkWVZQha16aLg1IYSQBjd37lxER0dDLpejbdu2GDt2LDp06ICAgADKAkoI+U/o0qUL3n77bRgZGQEo6QXes2cPNm/ezA81jo6Oxt27d9GvXz9s37693HNFRUXBz88P5ubmsLGxQWxsLBISEiotAxf86gtIq9uT/DTGGMLDw9GiRQtIpVI0bdoUYWFhyM7OhkwmQ0hICMRiMRhjuH37Nuzs7ACgwiRkpaWmpuLQoUO4evUqxo0bBxMTE8hkMkyYMAHt2rXD119/TdcVUinqSSaEENLgDhw4gK1bt2LDhg2YMGECVqxYAS8vLwwYMKChi0YIIXVu+PDhmDJlCh8gJycnY86cOdi4cWOZubg7d+7Eiy++qJNV+mlZWVl8D6yzszMEAoFB5eAeX9+aw/p6kgUCAf93VZJkFRUVITw8HFqtFhKJBH5+fmjRogXatGmDOXPmoGPHjnj06BEyMjIgEomQl5dnUPI0bt3ne/fu4ciRI3j77bdx/PhxZGZmwtLSEp07d8bChQv5IeeElIeCZEIIIY3OqVOnAACenp4NXBJCCKlbw4YNw6uvvsr//+jRo3j//fcRFhamd/9r164hPj5e5xh9Hj9+DKAkcOSWeqqIVCrlh3jn5uaWuV9fTzKXtAswvCeZk52djYiICOTm5kIkEvFDyNetW4fg4GAEBwcDKElWZmRkVGEmbM4rr7wChULBr+GclZWFL774Aj/88APfE+3r64u5c+fqlJ08a7jEXZVt1R8xQEEyIYSQRsfNzQ0AKkxOQwghz7qhQ4eie/fufC/sDz/8gNWrV5fpyS09vBkoWbs5KCgIHh4e5Z47OzubHzZtamqqc5++nuXSgbS+IFlfT3Lp3mx9PckSiQRKpbJM+TlpaWm4du0aHj9+jMTERMTGxuLw4cOYOXMmXn31VXTs2JE/Vl/v9tP69u2LLVu2lOl9P3v2LGbOnMn3RgcGBmL27Nk6c6sJKY2CZEIIIQ3O1NQUlpaWcHR0xKBBgzBv3jwUFBTwvQGEEPK86dOnD0aPHg07Ozvk5uZi7dq12Lt3b5n9XF1dERQUhKZNm8LKygpASWbqsLAwDBw4sNzzM8b4IddPB8nff/89AgMDdW7jenLVarXeXmF9Pcmlg2R9x9jY2CA7OxvFxcUVZr9+/Pgx7ty5gwcPHiAvLw/379/HypUr8eGHH8LR0RFA5cO5uYC89JJWpT18+BCffPIJ36PcokULTJkypcJzksaqsApb9VCQTAghpMEdPXoUKSkpiI2Nxc6dO5Gbm4sBAwYgLi6uoYtGCCG1ztfXF2+99Rb//z/++AP79+/Xu6+1tTWsrKxgZ2eHpk2b8omszpw5U+kqE1xAyA2j5ohEojLJuWxtbQGAz0L9tMp6kp8OgpVKJaytrZGbm4vHjx/rBNmGuHDhArZv347Ro0dDoVBUOq9arVYjOzubD6r1iYqKwvz58/mydujQAb17965Such/AwXJhBBCGty7776LHj16YPDgwdi/fz+srKwo+ygh5LmkUqkwc+ZMvjd29+7d2L17t959pVIpjIyMoFarodFoIBAI4O3tDQcHB2RkZPCJtsrDBbOlA1SxWAwrKyskJibyt3HzfgHddZZL09eTXHoY9dNBsKurK0QiESQSCT8/uqr27t2LuLg4DB48uNJ9GWM4e/Ys+vXrV+F+kZGRWLFiBf//CRMmwMXFpVrlI88vCpIJIYQ0uIsXL+Lo0aPYtWsXBgwYgLCwMPzyyy8GJZshhJBnhUAgwLRp02BpaQkACAsLw08//VTu/lKpFGq1Gmq1Gjdu3EBeXh4YY7C3t4ejo2OlawdLJBKo1Wqd5ZMcHR1RWFiIlJQU/jY7OztotVoUFBQgLS1N77lKr6nM9eoKhf8PJZ4uCxd0JyYmVlrO8mi1WuzcuRPOzs7o06dPpfv/+uuvaN26NZo1a1bhfhcuXOB77qVSKWbMmEGJvKooOjoajLEy29dff613/zFjxpTZ19Blvcqq+3WSKUgmhBDSqGi1Wnz00UdwdHTEe++919DFIYSQWjNixAg0b94cAJCRkYHly5dXGEBKpVK+Nzg3Nxc3btxAeno6jI2NERoaWumySHK5HGKxWGeotL+/v868XWNjY9jY2IAxhpiYmHLPVXq4Mxcwl+5Jfvp5cPeZmJgYvATV0woLC5GTk4Pt27djzJgxcHJyqnD/tLQ0bN68Ge+//z7MzMwq3Hfjxo14+PAhAMDFxQVvvPFGtcr4X9WqVSvY2dnxW48ePQAAv//+e7nHZGZm6hzj6upaX8WtMgqSCSGENDonTpzAhQsXMHny5ArXAiWEkGeFt7c3hg0bBqAkoPz8888rzeBfundTrVajuLgYd+7cQW5uLtq2bYvbt2/DxsZG77EymYz//Sydrbpfv344dOgQ/38uUNFqtUhOTi63LPoC3Yp6kuPj46HVamFkZISAgIBq99RyibxOnDiBGTNmlJlf/bR9+/YhPDwcCxYs0BmOLhAIYGpqChMTE0gkEhQXF2PZsmV8QrAXXngBLVu2rFYZ/4tSUlKQmJjIb/3790dUVBROnDhR7jGMMZ1jkpKSqvnotAQUIaQRGzduHObMmVNm4zJkElITy5cvh52dHcaOHdvQRSGEkBoRiUR4//33+UBz69atCA8Pr/Q4rje09PJHxcXFyM7Ohp2dHW7cuFFu1mcLCwsAJYFJRkYGAKBbt25QKpX8WvRmZmZ8xuzY2FiDh0VzPckVBcmPHj1CfHw8ZDIZzM3NERISAnt7e4POXxqXofvo0aMoKioyqMd3zZo1SElJwbx58yCVSmFtbY1WrVqhWbNm8PHxQcuWLaFUKhEbG4u1a9fyx7399tvUMFsNEokEo0aNwsaNGyvcz8TEBA8fPsSjR4+we/du+Pn51VMJq46CZEJItb377rtYtGhRme3ppSYIqY5du3YhKioK06ZN06mIEULIs2bIkCF8j+39+/exc+dO/j5ra2u4urrC0dFRp5FZIpHwc5dTU1N1zjd06FCcP38eeXl55Q5Z5YLk7OxsqNVqeHl54e2338aqVatQXFwMoVCIJk2aACjJgl3ZagL6hltXFCQzxvDgwQNER0dDq9WiqKgITZo0gbe3d4WP87TCwkIIBALIZDIsW7YMoaGh6N+/f4XHaDQafPbZZwCAVatWITAwEHK5HEBJDztjjK+rHD58GDdu3ABQsmQV19tPDPfSSy/BzMyswvn1d+7cwbhx4zBw4ECMGjUKQqEQZ8+erTAbeUOiWgchpMo2bdoEgUBQ7kbL9hBDcZ+lK1eulLmPMYYmTZqgSZMm1U76QgghDc3JyUlnmPWaNWv43zQuUHV1dYWnpycCAwPRqlUr+Pn5oWXLllCr1WCM6STZGjBgALy8vHDgwAHk5+frHSItEAj4Xui0tDR06NABS5YswebNm3Ht2jUAJcOsFQoFAODevXuV/s5WNty69Lzn0h4/fozLly/zPd52dnZwc3Or8LFK43rRpVIpUlNTsXDhQrz22mto3bp1hceJxWLs27cP5ubmGDt2LAoLCxEWFobi4mJIpVKd4d/fffcdn5375ZdfpmzXVfTGG2/gwIEDSEhIKHef8+fPY/Pmzbhx4wZOnjyJQYMGITk5WWcpNMNR4i5CCCGEEEKeWZMmTeKTb+3atUsnaZa5uTl/HwAUFRVBoVDAysoKEokEYrEYd+7c4RN0+fr6YvTo0Vi7di0EAgHkcrnebNQ2NjYQiUQQi8Xo378/Jk6ciGXLluHPP/8EUJLQi0uClZiYyA/HrkhVe5JLKygoQFhYGD8H28XFBUqlstLHBKCTAVmhUODu3btYtWoVpk2bBi8vL73HWFlZoUWLFsjPz8fGjRuRnp6Orl278gHy0+eNj4/Hb7/9BqBkaPzEiRMNKhspeS979OiBH374oUrHqdVqXLt2rdz3sKGJK9+FEEJIfRIIBPDx8UHr1q1ha2sLxhg0Gg0YY0hLS8OpU6d0KlmEEEIap969e8PX1xdASSD266+/6tzPzbcFgNu3b6O4uBjW1tZ8Yqn09HS+p1ilUmHGjBnYvHkzUlJS4ODggLy8PBQUlO0tc3JygrOzMwYOHIhHjx5h6tSpOusfc8O6uSHRVVXVIJk7JiIiAq1atYJUKkWTJk1w7do1naWl9Cn9/ORyOXJycnDu3DmYmZlh3rx5mD59Op48ecKXx83NjW8AkEgkuHr1Kk6cOIHZs2fj888/x549e5CWlqbTOw8AO3fuRJcuXeDg4ICmTZuiZ8+eOHz4sOEvyn/U66+/jqSkJH5JLUMJhUIEBgbir7/+qvqDajQA9I9ceGpHQFT5XvpQkEwIIeWQSCTw9vZGQEAATExMoFAokJOTg9jYWH6rbPkNQ5mYmGDs2LEwNzeHj48PVCpVufsOGTIEcXFxOH78OE6ePFnh8CZCCCENQy6XY9SoUfz/v/76axQXF+vsU1RUhLy8PBgZGcHS0hKRkZF6M16rVCosXrwY4eHh2Lt3Lx946wuQzczMMHDgQHTq1AmbNm3Cpk2bygSwKpWKX6f26TKVpyY9yRyNRoOoqCj4+fnBxMQEDg4OlU7R0mg0yMnJgVQq1UmqdeDAAbi6uuKtt97CggULYGJiAl9fXz6jdV5eHsLDw/ke48WLF+OLL77AuHHj+HnZpRUXF+Pbb7/FokWLAJQEfxcuXEBWVlalz+u/SiAQ4PXXX8emTZvKDLfftGkT4uLiMHv2bADA3Llzcf78eURFRcHMzAzTp0+Hq6trlXug6wsFyaRGFAoFzMzMdNbA4/4tKipCXFxcuVkXCWmMRCIRgoOD0alTJ7Rt2xYPHz7kKyP6PH78GGfOnMHZs2f59RarwsnJCZMnT8bLL78MIyMjxMbGGhT0Ojo6YuTIkRg5ciSuXLmC7du34/bt21V+fEIagp2dHZ80p3QvUmFhIdLT05GdnV1p7xIhjd3gwYP5z/mZM2cQFhamd7+kpCS4ubnBxMQEYrGYnxvLMTc3x6xZsxATE4NVq1YB+H9wqu97MnHiRLRs2RKrVq3Cnj179D6mRqOBUCiEXC6HUCg0KMCt6hJQ5UlJSUFaWhosLCzg4uKChIQEg+ZDS6VSqFQqnaB6y5YtWL9+PXr16oX8/Hy+jImJiYiKitIJ3DQaDXbs2IE33ngDw4YNw6VLl8oEdjdv3sTx48fRpUsXmJiYYMyYMfjqq68Mel7/RT169ICrq6verNYuLi4676u5uTnWr18POzs7pKen48qVK2jfvj0iIyPrs8gGoyD5P04ul0OhUMDIyAhGRkaQSqVQKpUwMjLib+f+NTExgUql4reioiI4ODhUeH7GGOLj4/Hw4UM8fPgQ9+7dw61btwxutSSkvgQEBKBLly5o3769TnbRyparcHZ2xvDhwzF8+HBERERAJpPhzz//xLFjx8o9RiQSoW3btujSpQuGDRsGa2tr/j5zc3NER0fj6tWruHjxIiIiIsAYg0AggFgshr+/Pzp37oyAgAD+mJCQEISEhODcuXP466+/+CydhDQGbm5uCAgIgKurK9zc3ODm5lbpEiuMMSQkJECj0SArKwtZWVnIzs5GXl4ev+Xn5+v8zf2f+7u8JEKE1AdLS0u8/PLLAErmXm7atKncfZ88eQJ7e3soFArY29vj8ePH/H02NjZYuHAhrl+/jrVr1/JBB1ePKr0OMAC89dZb8PPzww8//ICLFy+W+5gpKSmwtbWFRqOBSqUyaE5yadXtSeZER0fDwsICIpEI1tbWSExMrHD/lJQUGBsbw9raGmlpafz+MpkMt27dwtChQ7F582YUFxfj3r17ZYZSA+BHaG3ZsgWDBg3Ce++9h9WrV5fZb8OGDWjVqhWMjY3Ro0cP7Nu3j6Y4lePw4cN6G08AoGvXrjr/nzJlCqZMmVI7D1yV/jdF9R6CguT/AEtLSzg5OcHR0ZHfnJycYG1tXeaD/fDhQ4MzDhqSwVggEPCPGRoaCqAkUcKlS5dw9uxZXLlyBYWF1V/om5CaUKlU6NatG/r06aO3wSc3NxdXr17FlStXkJiYiMLCQpibm/PfIU9PT/j4+AAAMjIyEBQUhODgYAwfPhxxcXE4fPgwYmJiUFRUxAe57u7u8PLyglwuR5MmTfjMoowxXL9+HRs2bMCePXvK9CRwYmNjcfDgQVhaWqJjx47o378/bGxsAJS02i5cuBBRUVH4/fffcf78eeqNIw2iSZMmaN++Pdq3b1+tdVEFAgE/L7MyWVlZeqcnZGdnIy4uTmfjRmqU9/0ipLaMGjWKTxC1f/9+fs6sPkVFRSgoKIBMJoOxsTF/u7OzMxYuXIgzZ85g/fr1OsekpaXB3t4eAoEArq6uePToEQYNGoQhQ4Zg/fr1uH//foWjknJzc/nyKRSKaifuEon+P+GzKkFybm4ukpKSYGlpCRcXl0qD5Li4ODg5OUEgEMDLywseHh4AShoL4uLi0KFDB6SkpODevXvldsRw2b5zcnIwe/ZsrFixAq+++ip++eUXnf0yMzOxbds2vPHGGxAIBJgwYQI/ZJj8d1CQ/BwyMTFBcHAwWrZsiZCQkArnNj6t9JBpDw8PxMTElKlMcC37CQkJSE1NRUZGBrKysvgfR+6H08TEBK6urnBxcdFJs69QKNCpUyd06tQJRUVFuHLlCs6cOYMLFy5QwEzqRWBgIPr06YN27drpZBUFSuZ3nT9/HidPnsS1a9fK9EY9fPiQXz4DKOn5bdeuHfz9/fleA6BkOPRLL72Ee/fuIT8/nw+GOW5ublCpVMjKykJcXBzmz5+PgwcPGvwcUlNTsXv3bvz555/o3LkzevXqBT8/PwCAl5cXPvroI8TFxWHPnj04fvy43nlrhNQmX19fdOjQAe3bt4eVlVW5+z158gQPHz5EUlISP0oCAJ+p18zMDEqlEhYWFlCpVPzapqW5uLggNTUVubm55Qa8SqUSvr6+ZaZLaDQahIeH4/Lly7h06RItWUdqnbu7O7p16wagJBjcvn17lc/h7e2NefPmYe/evXqPT01NRUJCAuzt7eHq6orevXtj+PDh2LBhA2JjYyudfsMt2ajVaut1TnJpSUlJsLGxgUKhgImJSYU5PtRqNW7dugUHBwc+czdXptu3b0MoFOLRo0cVPhcrKysUFxcjKSkJ6enpmDdvHr744guEh4eXGYG1b98+vPDCC3BwcEBAQADat2+Ps2fPVun5kTpUlQGp1JP83yWTyeDn54fAwEAEBgbqzPUqT35+PhISEpCdna0zRC0tLQ1arRZ5eXkYM2YMTp48iZMnT/JD2rKysvj16gwlFAphb28Pd3d3hISEoE2bNvxwVqlUinbt2qFdu3YoKCjAqVOncOTIkUY7P4E8u1QqFbp3744+ffro7dm6efMmDh48iAsXLlRpHn16ejr++usv/PXXX9i0aRMmTpyIl19+GWZmZjAzM4Ozs3O5n+c7d+4gMTER8+bNq/Z8Yo1Gg2PHjuGff/5B+/btMXToUL6F3dHREe+++y5ef/11/PPPP/jrr7/w6NGjaj0OIfpYWlqiW7du6N69u97RGFqtFmFhYTh//jzu3r2LR48eVbnBRiKRQKlUQqlUQqFQQKVSYfny5Vi/fj0KCgogFothamqqMz3IyMgIVlZWeoN1kUiEoKAgBAUFYdy4cXjw4AGio6Nx8+ZN3Lx5E6mpqdV+PQgBShI+cQHltm3bKk3wKJVK+YbU7OxsBAQEYO7cudi8eTP27dtX7nEPHz6ESqWCj48PRowYgY0bN+Lhw4e4e/dupZ0O5ubmEAgEEIlEBn8naztILl2fLH2e8nBTL5KSkmBkZASxWIzMzEzk5OSgqKiownOU7qXnMorHxsZiw4YNmDx5Mt577z3k5uby+2s0GmzYsAFz584FAPTv3x+XLl2i6YL/IRQkP2OUSiXc3d3h7u4ODw8PuLu7w9nZWWe4S0xMDB8kc+vSPX78GPHx8YiNjUVcXJxBw2psbW2hVCrLTTRhKK1Wyw91O336NEQiEQICAhAaGop27drxZZXL5ejZsyd69uyJsLAwXLt2DUePHtW7/h8hhgoKCkKfPn3Qtm3bMr3GmZmZOHLkCA4dOlQrGaKTkpIwb9487Ny5E59++ilkMhmkUim2bNmC+/fvAyhJTLR06VJ+yY3vvvuuVhJuMcZw5swZnDlzBsHBwRg6dCg/b1mhUKBv374IDg5GRkYG/v77b5w+fZou9qRaxGIx2rZti5YtW6Jr165lpu2o1WrcuHGDHyFUeomb6iguLkZaWhp/LQgICEB0dDS2bdtW6bEymQwODg5wcnLi//X19YWtrS2Akkq6h4cHPDw80L17dwAlcx+jo6P54PnBgwcVDpUlpLSmTZuiefPmAEqSRxmyLI6NjQ2kUiny8vJga2uLWbNm4fvvv68wtwVQ8t149OgRpk+fjt9++w3Hjh1DYmKiQdMJzM3N+ZEYhq7SUFuJu/Ttb0iQzCn9ewCAD34rauC2sLAAAH4pRc7BgwfRunVrvPPOO1ixYoXOMZcuXcK5c+fg6uqKgIAA9OvXD7t37za4nKQOqQEYMptM/3Rpg1CQ3IipVCr4+fmhadOmcHV1haOjI39hr0hKSgquXbuGy5cvIzw8vNrJS8LDwzFu3LhqHVsRjUaDGzdu4MaNG/juu+/g5+eHrl27omPHjnxLqpmZGUaPHo1Ro0bh8uXLOHLkCC5evEiJWIhBTExM0KlTJwwcOFBvr/GNGzfw999/4/z583Xymbp58yY2btyI8ePHo7i4GL6+vvw6gG+++SZ/QT916hSOHz9e649/7do1XLt2De7u7ujbty+6dOkCmUwGrVaLpk2bomnTppgwYQL+/vtv7Nixo8qjQ8h/k6urK3r16oUuXbpAqVSiuLgYGo2Gb3y6efMmjh07hvPnz9fpZ8rPzw8REREG7VtYWIjo6OgySXccHR3RsmVLuLm5oVOnTjpzn7ke6FatWvG3PXjwAGq1GjExMbh79y7Cw8MRGxtbO0+IPFdGjBjB/71t2zaDAlalUgkAaNasGfr06YNvvvnG4GvD+PHjcebMGXz33XdVKqeVlRVkMlmVphvUdk9yeQmfqsrU1BTFxcUV9ohbWloCKOmNfvo9+eqrr7B+/Xq4u7uX+a345ZdfsGbNGgDAsGHDcOTIkVpb+pE0bhQkNyJCoRDNmzfn5zdyC6GXlp2dzf+YAiU/SI8fP0ZkZCRu3ryJW7duITMzs1bKExkZCUdHRxgbG+sMQalNjDGEh4cjPDwc69atQ7t27dC1a1e+B0wgEKBVq1Zo1aoVMjMzcezYMfz999+0LizRy9PTE/3790enTp0gFot1KuqZmZk4fPgwDh06ZHCvkFAohJGRESQSCTQaDTQajcHfhQMHDmDYsGFQKpUIDQ3FunXrUFhYiC5dugAoafGuSqVGLBZDpVJBq9VCq9WioKCg0mHh0dHR+Oabb/Djjz+ic+fOeOGFF/j7TExMMGTIEPTq1Qtbt27FwYMHq1zBIc8/mUyGrl27omfPnmjSpInOfRKJhL/uHDt2DMnJyfVSJh8fH1y/fr1G5+BGNwHAt99+C29vbwQFBSEwMBAeHh5lMgYbGxvD1tYW3t7e6NmzJ4CS63FERASuXr2KU6dOUcWZwMfHh+9FfvLkicGBblJSEkJDQzFy5Ehs2rQJp0+fNug4JycntGzZEhMmTKhSOUuvN6xvTWZD1EaQXDpnTk3qmQ4ODhXWCyUSCczNzQFAb9brjIwMHDp0CEOHDsWyZct07ouJicGxY8fQvXt3GBsb45VXXtG73BF5/lCQ3Ag4Ozuje/fu6NKlCz8cRJ+cnBzcuHED6enp/DCwx48f19mQSe68tdXSV5mioiKcOHECJ06cgLW1NXr27IkePXrwc8pMTU3x8ssv46WXXsLZs2exc+dOREVF1UvZSOPm4+ODV199FcHBwTq3p6am4t69ezh48KBBvcZCoRBKpRLm5uYwNTWFUqnkKwA5OTkwNjZGVFSUQY00xcXFOHr0KF566SVIJBJ069YN6enp/Hz8M2fOGFyplsvlCAwMhEKhQGFhIV+5yc/PR2ZmJjIyMpCRkVFu0JyXl4cDBw7gwIED8PX1RZ8+fdCxY0dIJBKoVCq888476NevHzZs2KCTlIz8dymVSvTv3x/9+/fXaZgFSj7bZ8+exaFDh3Dr1q16L5tQKKzV615xcTHfWPvrr78CKBn+yk1r8vDwgJ2dXZnjlEol2rRpgzZt2mDChAm4ePEijh49iqtXr9Kop/8obmUDhUKB7du3G/w5cHd3x6BBg7Bz5048ePAAwcHBCA8Pr3RExqBBg3D8+PEqT0srPXKiKglT9fUkl76tOkFyfn4+1Gp1jb7Tjo6OiI+PL/d+GxsbCAQCMMaQlJSkd58//vgD69atg4WFRZnXc8uWLejYsSOkUin69++Pffv2lXseUk+KQcOtn1cmJibo3LkzunfvDi8vrzL3azQaREVFISIiAuHh4bh37161W/uqi2tJz8/Pr9fHBYDk5GT88ssv+PXXX9G8eXP07NmTn1MqEAgQGhqK0NBQ3LhxAzt27KB1Yf+jvL298eqrr6JFixY6t+fm5uLIkSOVLrshFAphYmICMzMzmJubQ6lUIj8/X2cJDo5cLodAIECTJk1QVFRkUHIfLkgGSoaIll778vz58wY9R6FQiKCgID7Db+n1ZRUKBRQKBczMzCCXy5Gfn4+MjAykp6cjMzNTb6Xj9u3buH37NrZu3YoxY8agU6dOAEqyBS9YsACXL1/GmjVrqrxmJnk+WFtb46WXXkKvXr3KrGV8//59HDp0CCdPnqyz0UWGyMvLK5MtvrYlJSUhKSkJFy5c4G+TyWRwd3eHr68v/P394efnxzcgiMVifsmrzMxMHD9+HEePHsXDhw/rtJyk8fDy8kJISAiAks/PP//8Y9BxHh4emDlzJhYvXozY2Fi4urpCoVDA29sbjx49KjcAlslk6NKlCyZNmlTlspYOkqsSnOrrNKnuElBASfAqkUhqPHXB3t6+0iAZKOk1L+/5pqSkYP/+/TAyMirzmnOrSbzyyisQi8V47bXXysxfJs8fCpLrmaurKwYNGoSOHTuWSSKkVqtx6dIlHD16FNevX69Sht260K1bNzx69KhBW8QZY/z8SqVSiV69emHgwIH8WnfNmjVDs2bNcP/+fezYsQNnz56ldWH/A7y8vDBy5Ei+QsJJSkrC77//juPHj+ttHZdKpVAqlTAzM4NKpYKxsXGZZCEymQzFxcV8D21WVhYKCwshFAoRGBgIIyMjeHh4ID09vdIKAbcchUQigbOzM27fvo2CggLI5XKDv1eOjo58gHznzh2kpKRAIpHAxMQEpqam/HcB+H/QzM3DLigoQFZWFjIyMpCTk4Pc3Fz++5GcnIwVK1bgzz//xPjx4/n1nlu2bIkvvvgCixcv5pONkeefi4sLBg8ejM6dO5cZPnnixAns2bOHTzbX0B48eIDQ0FDs27evXpPPFRYW8o1MXPIed3d3dOnSBV27duW/i6amphg4cCAGDhyIe/fu4Y8//sDZs2dpOsNzbujQofzfO3bsMOj9lsvlmDFjBn7//XecOXMGQMmoJTc3NyiVSvj7++P+/ft6A8DAwEAkJydXK8AsXf+sbh2vpsOtLS0t+WC9phnlzc3NER4ervc+bspUbm5upWsxb9iwodz7du3ahT59+kClUqFTp0745ZdfKgzMSR0rAvUkPy8CAwMxePDgMj1eABAVFYVjx47hxIkTNc4CWlt69eqFIUOGYNasWQ1dFF52djZ27tyJvXv3olu3bhg0aBAfDHh6emLmzJl4/Pgxvv/++wYZAkjqnkwmw2uvvYb+/fvrtGgnJSVh+/btOHbsWJkLvqmpKaytrWFpaQmZTAbGGBhjOhd2tVrNB8Xp6enlDnGLioqCl5cXpFIpXFxcKu0lYowhLi4Obm5u/GdVX49weeRyOVxcXJCbm4ucnBz+Aq/RaFBQUMDPrRKLxfySU2ZmZvwoELlcDrlcDmNjYxgbG0Or1SIzMxPJyclISUmBWq3GnTt3MH36dHTq1Anjxo2DhYUFrKysMH/+fHz77bc4d+5cpeUkzy5zc3OMHTsWXbt21bm9qKgIBw8exO7du+ttrrGh9uzZA39/f8yaNQvLly9v0DXAuaRgmzZtQosWLdCtWzedTPpNmjTBjBkzkJiYiD179uDw4cNVGt5Kng0uLi5o164dgJLMy0ePHjXouLfeegspKSn4/fff+dtSU1NRUFCAgIAAyGQyeHl5QavVlhkV5eHhoTPSoSq4z6BAIICJiYnBuWxqM3GXi4sLgJKRXzXNpWNsbFzu9CU7Ozu+YbomwXheXh527tyJ119/HQAwYMAAfP/999U+H2n8KEiuQ0KhEKGhoRg0aBA8PT117svOzsaRI0dw9OjRRrVuqUQiwVtvvYW2bdti0aJFiImJaegilVFcXIyDBw/i0KFDaN++PYYMGcK/vs7Ozli8eDFOnjyJjRs30vJRz5FmzZrh/fff54dNAeUHxyYmJrC1tYW1tTWkUqnOeQQCAbKyslBQUIDs7GxkZWXp9LBWJCMjA7m5uTAyMoKzszMyMzMrnQYRHx8PR0dHGBkZ6VSOKxsuKhQK4efnB5FIBLlcXmHDj1qtRkpKCh80S6VSqFQqfuNeA6FQCHNzc5ibm8PLywsZGRlISkpCSkoKTp48iZs3b+Kjjz6Cj48PCgoK8NFHH+Hnn3/Gjh07Kn1tyLNFKBSif//+GDlypM5nMTs7G/v27cO+ffsaTaPt09RqNVauXIlZs2Zh5cqVWLp0aYNnmtZqtbh8+TIuX74MExMTdOzYEb179+bXLLe1tcWbb76JESNGYP/+/di3bx+ysrIatMyk9pTuRd61a5dBIxxMTEzQpUsXvPnmm2WuP7m5ubh69SoCAwNhYmICT09PZGZm6kx/Cw4OxpEjR6pV3pycHKSlpcHMzAwuLi4ICwsz6BpY2RJQhvRKCwQCeHp68lMVaqMObGJiUm6QzOW1SU5OrvFojoMHD2LEiBGQy+Xo3r07tmzZQgn7nmMUJNcBmUyGbt26YfDgwToVeqCkUr979+5G2Zrs4eGBSZMmobi4GB988EGNh7/UtdLrwjZr1gyjR4+Gt7c3AKBTp05o3bo1fv75Z+zbt6+BS0pqwtjYGG+88QZ69OjB31ZUVIQtW7bgzz//1LkoGxkZwd3dnV/qofT+ycnJ/PDpmgzRjIqKgkqlgkwmQ9OmTXHr1q0KgwmZTMZnxzY0SBaJRPD19eWTfEVFRVVp+kVRUZFO0Mz1FpiamsLKygoqlQpCoRAWFhawsLBAYWEhHj58iMTERMyZMwevv/46XnzxRQDAa6+9Bnt7e3z77beUjOg54enpiQ8++ABubm78bTk5Odi2bRsOHjzY6K5N+uTm5uKTTz7BqFGjsHLlSvz444/4+++/G7pYAEpeSy5RXlBQEAYNGsSPIlMqlRg+fDgGDRqEY8eOYdeuXbQG8zPOzs6Oz+2QlZWFgwcPGnScn58f7t27V+5IjeLiYkRERCAkJAQikQgeHh46Q4o9PT2r3ZPJGENWVhYsLCxgbm4OPz8/3Llzx6DlqkqfA6i4J1kqlcLBwYEfVi2TyWBqasrPY87MzNSbbbqqTExM9OZJkEql/Oit2ug0ycvLw5EjR9C/f3/IZDL07t0bO3furPF5STVQ4q5ni4mJCfr164cBAwYgNTVVJ0COiorCrl27GuW8JJlMhlGjRuGFF17Arl278Ntvv1Xph7I+ODo6wt7eHsnJyXp7t7l1l1944QVMmDCBX1bgzTffRGBgIFavXk1rwT6DHB0dMW/ePJ3Msrdu3cJXX32lU7GUSqVwd3fnM1gCJRWM5ORkJCcn19qyaNx5w8PD0bx5c6jVagQFBeHevXvlZrrkglutVqvTCl9ekCyVShEUFMRXQOLi4iqdR1UZxhiys7ORnZ2N2NhYyGQyWFtbw9raGkqlEjKZDD4+PnByckJ0dDTWr1+P9PR0vPbaawCAnj17wsbGBkuXLqXv0TOud+/eeOuttyAWiyGVSiEQCHDo0CGsW7eu3MYec3NzODk5QSQS1XjppdrEGMPmzZtx69YtTJw4Ed26dcPXX3/dqEZn3bx5Ezdv3uTzkXTq1AkikQhSqRTt2rVDz549ce7cOezYsaPRzPkmVdOvXz/+t33Pnj0GNzK5urpWmiG5oKAAcXFxcHFx0VkuSaVSQS6X12hO7KNHj2BiYgIrKytYWlqiVatWePLkCZKSkpCXl6e3Z7l0QFxZkGxmZgYPDw++sZfLz8FJTU1FZGRkreSRKb1ee2mmpqb837VVD9i7dy//nvfv3x+7d++mBuTnFAXJtcDS0hIDBw5Enz59+BYriUQCtVqNGzduYNeuXY12jmyrVq3wzjvvIDExEZMnT27wIWvlsbKygpGRUZmlSMzNzdGlSxf4+fnB1dUVtra2EAgEUCqVfGW+Xbt2cHNzw9KlSynT6DMkICAAc+bM4TNN5+fnY+PGjWVa6Y2MjBAYGMjP8VWr1Xj06BHi4+PrrEEqJycHN2/ehLe3N0QiET88Wd/wydJDsSoLkgUCAfz8/Pg5xQ8fPtTJiF1bCgsLERsbi9jYWKhUKnh4ePCJzAICAhAdHY0dO3bgyZMn+PDDDyGRSNCsWTMsX74cCxcupJ6vZ5BMJsO7776rM/dYKpWisLAQnTt3RosWLRATE4MHDx7g5MmTuHv3Lr9f6TVGpVJpgyeVfNr169cxceJEjBgxAl988QX27NmDbdu21WtSr8rExMRg1apV+PnnnzFgwAC88MILyMzMhKmpKTp06IAOHTrg2rVr+P333xEWFtbQxSUGEgqFfC+yWq3GgQMHDD7Wz88PN2/erHS/goICFBYW6gSTJiYmKCoqqvFnPDIyEi4uLnBxceETTHLTlDIzM/H48WOdlQ6qMifZ0tISJiYmfK91cXExP90pIyOjVqdzJCUlwdrauszt3LW0Nl4rzpMnT3Dx4kW0adMGlpaWaN++PU6dOlUr5yZVoAZgSBVPWPku5aEguQYcHBwwePBgdO3aVacFS6vV4vz589ixY0ejatEuzd7eHm+88Qb8/PywcePGas9rqQ9isZhvQeWGy3At8M2bN0dYWBguX76Mffv24dGjR/wc0ZYtW2Lq1KkwNjaGvb09VqxYgVWrVvEZJEnj1a1bN7z33nv89yo6OhoLFy4sMyzL1NQU/v7+EIvFYIwhNja23jKyZ2Vl4datW2jRogUkEgn8/Pxw5cqVMhfi0kFy6d8JfYm7uGAVKFluJy4uro5K/39ZWVm4fv06LC0t4eHhAYVCAXd3d8hkMpw+fRopKSn4+OOPoVKp4OzsjC+++AKff/45Lbv2DLG0tMT8+fPh6urK37Z37178+OOP0Gg0kMlkcHZ2hqurK3x9fbFgwQJkZGTgyJEj+Pvvv5GWlgbGGAQCASwtLQ1aJ7y+FRUVYdOmTTh+/Djee+89dO7cGRs3bsTZs2cbumg6UlNT8eOPP2L79u144YUX8NJLL/G9XcHBwQgODsadO3ewY8eOaidlIvWnWbNmfAPSpUuXDJ6fampqiubNm+Pbb7+tdF8zMzPIZDKd+cgVzcGtCsYYYmJikJKSAkdHR9jY2ECj0ejkr4iKitLbY11ZkMyNSCwqKqrz60VycnKZ6Y3A/xOUSSQSfp3k2rBnzx60adMGAPDSSy9RkPycoiC5Gry8vDBkyBC0a9dOp1WtqKgIhw8fxh9//NFoFxk3MjLC8OHD0bdvXxw5cgRvv/12o08eYmVlxb/OhYWFmD17Nry9vbF//358++235c5nuXz5Mj744APMmjWLz0g8Y8YMrFmzxuDMk6T+DR8+HK+++ir//8uXL2PZsmVlMthyPchCoRAajQaRkZH1nqitsLAQERERCAoKglQqha+vb5lRI6WHJ5dOIvb00lNWVlZwdHQEACQmJtZLgFxaamoqMjMzERAQAJVKBQcHB2g0Gty+fRvTpk3DJ598AicnJ5iYmODTTz/Fhg0bsHfv3notI6k6Ozs7LFq0iK9AFhQUYPXq1TqNhYWFhYiKikJUVBSOHj2KdevWoW3btnjhhRfQr18/LF++HFlZWXym+MYYJHNiYmIwffp09OjRA2+//Tb69++P9evXIzo6uqGLpoPLlLt371706NEDgwYNgq2tLQDAx8cHc+bMwePHj7Fz506cOHGChnM2Ul26dOH/Pn78eJWOi4yMrDRzvLW1Nf/dLd2ja2xsXKtrlefm5uLu3buIioqCkZERTE1N4eLiAo1Gw3/nuYYyTmVBMnftk8lkkMvldZqF/uHDhwgODi5zO1cGroGvNuY/A0BYWBgePHgADw8PNGnSBI6OjvV+zSZ1rwad0P89rq6umDdvHr744gu0b9+e/7HIzc3Fb7/9hnHjxmHt2rWNMkAWCATo3bs31q1bB3d3d0ydOhXff/99ow+QAfDzUa2srLB8+XIIhUK8//77+P333yv9wUtKSsLMmTP5oFggEOCDDz5A//7967zcpOqGDh2qEyDv27cPixYt0ntxtbGxgVAohFqtxs2bNxssk3lmZiZfATc3Ny+TNKx06395QbJQKOQztOfm5uLevXt1WeRyPf1aWltbQywW48mTJ5g2bRouXboEoOR7NH78eHzwwQc6c8xI4+Lk5ITPPvuMr2QnJCRg8uTJlY6mKS4uxqlTpzB79mz88ccfWLhwId8obGZmxk8rasyOHDmCN998E7dv38by5cvx/vvv68xPbCyKi4tx4MABvPXWW1ixYoXOlCBnZ2dMnjwZ69atQ7du3RqukEQvmUyG9u3bAygZMcT9PlbGz88PI0eOxK5du8rdRyAQwNnZGU2bNgVQch0pPWe9tnqSn6bVapGTk4O4uDjcvXsXcrkcpqam/PQgfdmtuSRc3PGctLQ0aLVaMMb4DNN15fLly7C1tS2zmkV2djbfmNCkSZNavV4dO3aM/7tDhw61dl5ioOIqbNVEQbIBLCwsMGnSJKxZswYhISH87enp6fjpp58wbtw4bNmypdEGnP7+/li9ejUGDRqENWvWYO7cuY1yaSd9jIyMYG5ujl69euH111/Hrl27sGjRoirNZSkuLsbq1at1er3efPNNDBkypC6KTKqpT58+GD16NP//H374AevWrdM7r1gsFsPZ2RnFxcWIjY1t8KVqYmNjkZubi6KiIr43iFM6SC49xLp0kGxtbc0P046KimrQ5H5arRa3b9/mk6xw6zvn5eVh0aJF+O233/h9u3fvjqVLl/LDDUnj4e7ujs8++wwWFhYASpL0zJo1q8qJfv78809Mnz4dzZs3x4QJE2Bubq6TSK8xKygowM8//4yJEyfC2NgY69atw6BBg3Qq9Y2FVqvFyZMnMWnSJCxYsAARERH8fdbW1pg8eTK+/PJLBAUFNWApSWnt2rXjf9NPnz5tUMJTb29vzJ07Fz/88AMuX76sdx+JRIKgoCC4urqisLAQ+fn5CA8P1xlNYGxsXOdJFEs/nr7npm/oculrl0ajwZMnT8AY468jdSU+Ph5isbjM94Mxhjt37oAxxk+LenoUV1WoVCq4ubnBx8cHFy9e5G8PDQ2t9jlJ40VBcgXkcjlGjhyJdevWoUePHnwLWlJSEr755huMHz8eu3bt0qkENyYymQxvv/025s2bh3/++QcTJ07U+VI/C1q0aIF3330X3t7emDRpUo2Wc/rhhx+wfft2/v+vvfYa+vbtWxvFJDXUo0cPvPXWW3wFfuPGjRUO5VWpVBAIBJBIJDXO/FxbHj16BKlUCisrK52etvJ6kku3yNvY2MDExATp6em1mom7utRqNbKzsyESiXQyqjLGsGXLFixbtoxP3uTt7Y1Vq1bxy6+RhmdnZ4eFCxfy711UVBQ++uijStf0Lk90dDQ++OAD3Lt3Dx988AFefPHFGlU061tiYiI+++wzLFy4EF27dsXKlSt1lr9qbK5cuYJZs2Zh5syZuHLlCn+7h4cHFi1ahHnz5sHFxaUBS0gA6CTB++effyrdv3fv3li8eDG2bt2KQ4cO6d1HJBIhMDAQpqamEAqFSE9Px9WrV8sExAKBoM6H4Je+jnFBsr7h1hVJT0+HUCiEQqGo8xEoly9fRsuWLcvcnpOTw3cMKZVK+Pj4VPn3SyqVwt/fH82bN4eLiwtsbW3h5OTEJzh0c3ODg4NDzZ8EMVxRFbZqojnJegiFQvTs2ROjRo3SGZ6Vm5uL7du3Y9++fY1uiaSnBQYG4oMPPkBiYiLef//9eg8kuMq1kZERjI2NYWRkxGdFLSgo4DeNRgOBQAChUAiBQACpVAonJyc4OzujXbt2aN68OU6fPo0tW7bUypyyrVu3oqCgAGPGjAEAvPXWW0hNTaUEKQ2oQ4cOeP/99yEQCGBvb49NmzZh9+7dFR5T+gLXWDLYlu7Nlkql/BDx0pWb0pWE0s+B642ozTlmNcW9rvoqE6dPn0ZcXBw+/vhjWFtbw8LCAp999hm+/vprnSFopP6pVCosWLCAD5AjIyOxYMGCGvc6FRYWYtWqVYiLi8PgwYPRsWNHHD58GI8ePcLDhw+RnZ3ND63kepPkcrnOxhhDbm4u8vLykJubi+zs7HpdkzksLAyTJ0/G8OHDsWLFCuzYsQO///57o53vy713gYGBGDduHD8lIyQkBC1atMChQ4fwyy+/VLvxg1Sfubk5mjdvDqCk4yQyMhJAyWfe398faWlpMDIyQlxcHD+XODY2FnPmzNHJHP80T09Pfsmk6OjoClc30Df0uTYplUpoNBrk5eXx3+nSj6lvxNPTZSrd6KtUKut0XnJkZCQGDBig975Hjx5BLBbDwsKCn0YUHh5u0KgtOzs72Nvb66yuolarIRKJEB4ezjcQt27dutK6C3m2UJD8lJYtW+L111+Hs7Mzf5tarcb+/fuxffv2OpkDUtuGDRuGwYMH46effsJff/1Vb4+rUqnQsmVLhIaGIjAwEHK5HEVFRXylqLCwEDKZDDKZjG9VFAqFfKVKq9VCo9EgNjYWt2/fxj///IO//voL+fn5tboMzs6dO2FkZIShQ4dCIBBg+vTpmDNnDu7cuVNrj0EM06pVK0ydOpW/sO7duxc7d+5s4FJVT+mLbenA0pDh1tzzb0yV9coqYNHR0fjwww8xa9YsBAQEQCwWY/LkyfDw8MDGjRsb3Xrw/wUymQzz5s3jhzbGxMTUSoDM4TKhR0VFwczMDGKxGKGhoRg5ciSMjIz4xk7us80NFeWWsBEIBHyjKbc0S1RUFM6dO4fLly/XS3ItjUaDrVu34ty5c5g8eTJCQkKwYMGCRn1tv3XrFj788EN06dIFr732Gp/Msnfv3ujcuTN27dqFP/74o14bHP7rOnXqxP9Glu5FdnV1hVgshqOjI4RCISwtLZGVlYWHDx8iPDy83PMJBAJ4eXnBzs4O+fn5SElJqbDeo9Vq6zRIFggEsLGxgUgk0kkupm+d5Iqo1eo6DYxLS05OLpMTpLQHDx5AKBTy0/hat26N6OhovZ1IXHZvJycnmJqaQqPRoKioCHFxcYiNjYW/vz8sLCx0chAFBARQkPycoSD5X25ubhg/fnyZ+QynT5/Gzz///MysCzpq1Cj07NkTU6dOrZP1VfVp0aIF+vfvj+bNm+PGjRu4desWNm/ejMePH9eo0h8SEgJjY2Pk5OTUegVm8+bNsLKyQteuXSGVSvHJJ59g+vTpVZ6vR6ovNDQUU6dO5ecHHjp0CBs2bDDo2NpaxqE2iUQi5OXlgTGm07ttSJCcm5tbJnNoY1HRa52VlYW5c+diwoQJ/NSFAQMGwM3NDStXrqQernokFAoxY8YMNGnSBEBJtvL58+fX+rzFJ0+ewMPDA2lpabhy5Qp27NhR7XOZm5ujWbNm8PX1xeeff46UlBQcPHgQhw4dqvNpTA8ePMCUKVMwffp0LF68GLNnz25UIzn0OX78OM6cOYMBAwZg6NChMDIyglwux6uvvoo+ffpgy5YtjXo5x+dJq1at+L9LZ7XmclLk5ORAJBJBoVBApVLB19cXBQUFiImJKfO7aGxsDB8fH74HOTc3t9IGo7q+XiiVSv7aXDqrdnmZrDlPl4nLbA3on9dcm1JTU2FhYQGhUFhuI21UVBQ0Gg2cnZ0hlUrh4+MDT09PZGdnIy8vj5/GZWFhoZO7IDc3F3fu3OF/l548eQILCwtkZ2fj0aNHYIzpXYKK1CE1AENCjBqkoPjPB8kikQivvPIKXnnlFZ0vxO3bt7Fx40bcvn27AUtXNebm5ujcuTNmz55d56noxWIxunTpwq/xuG/fPnz33XeVLmdgKCsrKxgbGwNAna01vWbNGlhYWKBZs2ZQKpVYsGABpk2b1ijmhD7v+vfvjwkTJvAX1BMnTuCbb76p1rkaS2ApkUj43rHSjUOlK/ulh1uXLrdYLIaRkZHetZMbO41Gg++//x4PHjzA22+/zSdP+eqrr7Bq1SqdOZWk7rz99tt8xT0vLw/z589HampqrT9OfHw8nJ2dIZFI4ObmVmHvWGXS09Nx/PhxHD9+HBs3bkSbNm0wYMAAjBgxAgcPHsTevXvr5Dlw1Go1li1bhvnz56Njx474+++/6+yxaktxcTF27tyJw4cPY9iwYejbty9EIhGfYLRLly5YvXp1rV2LSVlisRi+vr4ASoZac/Utbh1egUCAuLg4JCUlwcbGBjY2NjA3N4dUKkVgYCDUajUyMzOhVqv57NGcpKSkCodjcxhjdZoXoPT1qXSjr77h1hU1pFpbW/P71HWCzbS0ND4Df0WrXURHRyMlJQWenp5QqVQQi8X8+8PVOzl5eXmIi4srs+wdl7lbKBQiNzeXz0Lu4uJSZ3VWUv+encwbdcDd3R2rVq3CiBEj+AA5ISEBS5cuxYwZM56pABkoWVYgOzu7zgPkHj16YMOGDXj55Zexe/dujBs3Dtu3b6/VizKXVCUnJ6fW1rV7mkajwdKlS/klN2xtbTFv3rxnMlB5VggEArz22mt48803+YvtkSNH8OWXX4IxBgsLC1hZWenM/XlWcAEyY4xPagUYNieZG47GnaMxsLa2Rv/+/fHiiy9WuJ9IJIKNjQ1u3LiBefPm8ZUTlUqFGTNmYNy4cbRMVB0bOnQo+vTpA6Ak8Fu8eHGdrWCg1Wr5UUqWlpZ871dNFRUV4dSpU5g+fTrmz58PW1tbrF+/Hu+9916tPYY+Go0Gly5d0lm54lmQlZWF9evXY+LEiTh37hx/e1BQEL755hu88MILDVi655u3tzefhPHWrVv87YwxZGRkIC8vDzKZDIwxJCYmIiwsDLdv3+YbTMViMSwtLWFrawtTU1MUFRVBrVbjzp07uH37tkFTVeq6J7l0GcTi//enVTbcunSZ5HI5n2AuLS2tznuSNRoNMjMzDVpuKjs7G9evX8eNGzfw8OFDpKSkICcnB1lZWcjKykJMTAyuXLmCy5cv610XXqvV8te60vf7+fnV3hMiFauHJaD+kz3JIpEIw4YNw9ChQ/ngWKPR4Pfff8dvv/3W6JNylcfV1bVOl3ayt7fHe++9B3t7e3z33Xc4f/58nTyOnZ0dHyzU9VJVXI/LihUrYGVlBS8vL8ycORMLFy5slEN6n2VGRkaYPn06QkJC8OjRI7i4uGD79u3YunUrBAIBvL29YWdnh5ycHJiYmCA8PLzcXiSRSAQrKyukpKRAJBI1irm8XEW+dJITwLDh1tx0AmNjY743oqG4urpi6NCh6N27N+7cuYPTp0+Xu69AIEDLli0hFAohkUhQUFCAWbNmYfz48WjdujUyMjLw0ksvoUWLFli0aNEzM23lWdKlSxedpdO+/PJLnYp7XYiPj4eTkxOkUik8PT1x48aNWj3/7du38dlnn8He3h4TJkzAd999h7Vr11b4WayJmJgY9O/fv07OXdfi4+OxdOlSNGvWDJMmTYK1tTXkcjneeecdhIaGYs2aNTrzJknNBQYG8n+HhYXp3MfNeS3dsMMYQ1JSEpKTk6FSqWBmZgZTU1MIBAIUFBQgOTkZGRkZVcrjwPVi1pXCwkL+OuTk5MTnbNE33Frf9crY2Bj+/v4Qi8XQarX1km+gdJkMlZmZWe3Rg1lZWTA3N9d5bv7+/s/EiBRimP9cT7KrqytWrVqF4cOH8wHyw4cPMWXKFPzyyy91HiCPHDkSb7zxRp2c29bWVm+LV00JhUIMHjwYa9asQUxMDN599906C5BlMhk8PDwAlPwA1eVQO05aWhrmzZvHz0dr2bIlRo0aVeeP+1/i4OCAlStX8r01jo6OWL58ObZu3QoAcHZ25tdeVSgU/G3l8fLywqRJk9CjRw+doWoNhetNBVBmvXS1Ws3/rnDPDdCtbHDHCIXCMuss16eXX34ZK1euRHZ2NlasWIHffvutwoDLxsaGT8YH/L/nYPHixfjqq6/4Fn0XFxesWLGClomqZZ6ennj//ff5/2/atAknT56s88fVarV8A6apqWmdrYGakJCATz/9FOvWrcNbb72FuXPnVpiYp7ri4+Pr7Hvn6emJ9evX18m5S7tx4wbee+89nQp6UFAQvv76a/Tu3bvOH/+/pHSQXPr3USQS6TSWPo0xhszMTMTExODmzZu4ceMG7ty5ww/dbUyKiooQHR2NoqIi2NrawtvbGwKBwKAloOzs7NC8eXM+o/3du3frfE1njlQqrbcVL6RSKUQiETIzM/mkedST/Hz5TwXJvXv3xhdffMEP5dVoNPj111/x4Ycf1lsrV3JyMlxdXevk3AqFotZ/iCQSCWbNmoUePXrg448/xrp16+o0U6G3tzff8lif2aYfP36MJUuW8BeqoUOHon379vX2+M8zT09PrFy5Eo6OjgBKhjnNnTsXp06dAlBSsbC0tERhYSHS0tLw4MEDAODnCulz9uxZfPHFF/D09MSXX36J0NDQ+nky5XB2doZYLAZjTO90B643ubw5yTk5OXxrtouLi05+hPogkUjw4YcfYsCAAZg5cyY2btyI9PR05Ofnlwn6S7OwsABQ0hofEREBjUYDtVoNW1tbHD58GJMnT+aH5qpUKixZsgStW7eul+f0vFOpVJgzZw4/lP3vv/+u18zwCQkJ/GfWw8OjTtdAPXXqFN555x3k5ORg5cqVtX4Nzc/Ph0AgqJOpNq6urnU2Zehp+fn5+PbbbzF37lx++pNcLsfEiRMxa9asRjWd41lVej5ycnKyTi99kyZN+N/uul52s657kgEgLi6Or+/Z2dkhJCREp5Hq6Z5kkUiEJk2awMvLCyKRCGq1GuHh4fU6kkEqldZKlvdu3bph0qRJOg3bHIVCAV9fXzg5OQEoSWzG1Vetra0NGu5NakE9DLf+TwTJcrkc06ZNw8SJE/kKBdd7/Ouvv9brUM3MzMw6m2+pUChqNSOoQqHA/PnzYW5ujunTp9d50Gpvbw9zc3MAJe9PXWc3fdqtW7d0sitPnjy5wt5MUjl7e3vMnz+fT4YRExODDz/8UGeImoWFBZRKJWQyGR48eMBn0lSr1WWSaJR2//59rFu3DqdPn8b48ePxxRdfoFmzZnX6fPSxtLTk512lpKTobajiPsulK6lP/+5wPXNyuZyvhNUHkUiETz/9FA4ODpgyZQru378PS0tLyOVyKBSKCpOtcIFRZmYmP6fLxMSE71V//Pgxpk+fzve2SKVSzJkzp8EbNZ51QqEQM2fO5CtjkZGRWLt2bb2X486dO9BoNBCJRPDx8anTOZI5OTlYtWoVDhw4gM8++6xWvyPc91NfhbimTExM6j0Z5I0bNzBx4kSdXuX27dtjzZo1/FrLpHq8vLyQlZUFrVarcx1zcHDg6y8JCQll6i9cAqvaUteJu7jHuHnzJj9NxsjICF5eXjAzM4OxsTFMTExgamoKU1NTKJVKmJqaQqVSIS8vD1lZWbh27VqFCbTqglQq1ckJUl03btyAlZUVvvzyS3h5eQEoGeno7e2NgIAA/hqXk5ODiIgIRERE8McGBATU+PFJ4/DcB8nu7u5YvXo1X4kFgH379mHq1Kn11ntcWl22/snl8lrr5VWpVFi6dCmKiorw8ccf1/kakpaWlvwPUVZWFmJjY+v08crz559/8mseyuVyfPzxx9T6Xk3m5uZYuHAhPxw6IiIC06dPL9OqXHrIVn5+Pr+JxWKoVKpyz5+SkgLGGMLDwzF79mycPn0as2bNwqeffsp/luqaiYkJX1nPz8/HvXv39O7HBc6lP0tPDwnLyMjgs2JaWlry0w7q2qBBg6BSqTB79mykp6dDJBLxPXVZWVnlVjjEYjGUSiU0Gg3f26zv9ycvLw/z5s3jhwELBAJ8+OGHNPS6Bl5//XV+yGdaWho+++yzBpmXX1BQwF9HTU1N4ePjU+ePuX37dvz888/49NNPay3ZFjcCoi56wytajqYuFRQU4Ntvv8XixYv5qUQSiQRLlix5ZudfNwbNmzeHlZUV1Go1n7lfpVLB09MTQqEQKSkpiIqK4vd3dXXFnDlz8O2331Z4Pauq+srFwQ2XDg8PR25uLoRCIUQiEeRyOezs7BAQEAAHBwdIpVIIBAJoNBrEx8fj+vXr9d7RwXWC1UaQnJqaik8++QQHDx7E0qVLMWHCBLRq1Qp2dnb884yJicGNGzdQVFSEmzdv8se2bNmyxo9PDFBUha2anusguXfv3lixYgXs7e3h6uqKhw8fYunSpVi3bl29zVl4Wl0GyTY2NrWyLqmJiQk+//xzxMbGYtGiRbUydKUipqamaNq0KQQCAQoLCxEZGVmnj1eZb775hh/ya29vj2nTpjVoeZ5FRkZGWLBgAd/a+vDhQ3z66ad6g6jSQTI3VI37zFU03zgpKYmv/Lm5uWHv3r0YP348oqKisHTpUvTo0aPWno8+CoUCQUFBfGUlPDy83JwGXGVBJpPxvW369n348CE/D9/JyanORzK4uLhg2LBh+PLLL/nfRDc3N37YaUUNidx7IxKJ+PeB+217eq6aWq3GihUrcPToUQAlrf1z586t9d6V/4LOnTtj4MCBAEpe188++6xB16OOj4/nh5ba2NjUS0/lgQMHsHr1asyaNavWKqTp6el1ss6pSCRq0PmmFy5cwKRJk/ieLoVCgTfffJOGX1cTN1pJKpXyr6lYLIZarYZCoUBcXBwYY7Czs8OUKVOwcuVKJCUlYcKECRVOXakqiURSr/XY1NRUXLlyBVFRUSgoKIBWq9UZbq1Wq5Gbm4uIiIgGS9DIXbdqs866f/9+/PzzzxgwYADGjx8PIyMjJCcn48KFC4iJieEbKiIjI/nrYIsWLeq8l5/Uj+fyXZRIJPjggw90hldHRUVh0aJFOkslNIS6CpIdHBxgYmJSbk+WoYRCIWbMmIHY2FisWLGizlsqlUol/P39IRQKUVxcjFu3btV5UF6ZoqIiLF68mB9m2rJlSwwbNqxBy/QskUgkmDt3Lj/3PykpCfPmzSt3vnzp1mYu6QkXKHJrF+rDGMOdO3fAGINEIoGXlxdyc3Px888/Y/78+Rg/fjwGDBhQi8/s/xQKBZo3b47CwkJ+2F1F+QC471F5a0+WFhkZiaysLBQWFsLZ2Zmf91QXxo8fj/379/O/G6ampnBwcACgO+dUHy7RWl5eHv8eVpS0BgC+/vprfoiiqakp5s6dS8tDVYGrq6tOoq61a9c2iqUK7969yw+rdHR05L/7denMmTNYvXo1pk2bVivfkbCwsDoZJikUChs8+35ycjLmzJmD48eP87e1b98eq1atqtPfl+eNTCbjRw7FxcXxc80tLCwgkUigVqsRHByMmTNnYu3atSguLsY777yD9evX89OIakt9B8mc7Oxs5ObmIj09HXfv3sWVK1dw7949ZGZmoqCgoEFXh+HqCrXRkwyUXOeDg4ORmZmJNWvWICUlBaNHj4aRkVGZ56nRaHDt2jUAJddBGin1fHjugmRzc3MsWbIE3bt352/7888/MXPmzEaxDEJdBclBQUG4fft2jX80X375ZVhYWOCLL76opZKVz8nJCc2bN4dYLIZGo6k00KhPycnJ+Pzzz8EYQ0JCAgYNGoRWrVo1dLGeCW+99Rb8/f0BlMxV/eSTTyrs6crLy0NxcTGKior4no3ExERotVoIBIIKM+fm5OTwibJsbGz4YcLh4eH4+OOPMWzYMAwfPry2nhqAkspJUFAQJBIJFAoFwsLCKp1zyPWQGxIka7Va3Lp1CwUFBRCLxfDw8OAD0trk6OgIf39/PtmTkZER/P39IRAIUFRUxI+m0EcqlfJJu7heAy7Y1Wq15b4eGo0GS5YsQXx8PICSXuuhQ4fW2nN6npmYmODjjz9GQkICGGM4dOgQDh482NDFAlDSYBUREcH3lLm4uCAgIKDOG0BOnz6N/fv34913361x0q1bt27VSU6Dhhpu/TSNRoMff/wRixYt4nu87O3tsXLlShoeaqCAgAD+t7z0smcPHjzAgwcPYG1tjQ8++AAhISHYunUrTp48CZFIVCd1PrFYXO36nkgkQosWLeDr6wszM7MqHVv6uajVahQUFFS7HBKJBI6OjggODq6VxhqpVAq1Wl0rSyjKZDI0adIEUqkUWq0W4eHhmDZtGn7++WfMmzdPb4Pa5cuX+b+pvlgP1DAsaVcN2m2eqyDZy8sLq1at4udFFRUVYdmyZVi/fn2jWftYq9XWeuZakUiEgQMH8tmCq8vd3R0jRozA8uXL63QuiVgsRkBAADw8PCAQCFBcXIywsLAKEwQ1hJs3b2LdunWwt7eHQqHAlClT6iRYeZ74+vqiV69eAErmxM2fP58PiCqSlZUFqVTKJz5Rq9V8Kz03B6g80dHRfCu9q6srP4Q3KioKH330Efr06YMxY8bU5GnpaNq0KWQyGRhjiIyMNKiHgKtYCIVC/gJe0W8SN3ybq8x6eXlVmMSsOvr06YMzZ87wr33pNS3Dw8Mr7P1ycHCAQCCAVqvlg2SlUgmFQgGhUFjhdzknJwdLlizhn/+QIUMoQZ4Bpk6dCltbW7i6uuLq1av4/vvvG7pIOrgRFVyDmIWFBUJCQqpcCa+qzZs3QyQS1bgx7NKlS3B3d6/1edUNPdz6aRcvXsQHH3zAT6VQKBSYO3cuBg8e3MAla/xKN6KUDpK1Wi3s7OwwbNgwHDp0CF9++SWePHkCsVgMb29vtGnTBq6urrVa96tuT7JEIkGzZs0glUphY2ODoKAgtG7dmm/0rEzpIFlfMGpI8j4uC3bbtm3h6ekJlUoFCwuLGk/VkMlktdKLLBaLERgYCFNTU+Tl5SEyMpKvxxw8eBDff/89PvnkEzRt2lTnOG6OOkBB8vPiuQmSO3fujM8//5z/oqekpGD69Ok4ffp0A5dMV130JL/yyitISEjA4cOHa3SeiRMnYvfu3XyW3domlUrh7u6u84OckZGBy5cv13v2T0Pt378fZ86cAQAYGxtj9uzZdbJMyPNAJBJh4sSJ/P83bdqE+/fvG3QslxiudOZ37qIkk8n4IcD6cL1YeXl5yMvLg4+PD18xf/ToEWbNmoU+ffqgbdu2VX1KZbi5ufHnjo6ONngdb+47b0hPMketViMsLAxqtRpCoRB+fn61Wslq3bo1Tp06BaFQCH9/fzDGoNFoEBkZWWGQy7X+AyUjLrhgl3vviouLK50y8ejRI74HWywW6wwhJmWNGDGCT1KVlZWFr7/+utE0/JamVqtx69YtREdHgzEGqVSKoKAg+Pv712mw/O233+LFF1/USdBZVZmZmdi8eTPGjRtX7hSP6mgsPcmlJSUlYcaMGfy1TSAQYMyYMZg6dSpNf6hA8+bNAfw/6zMnMDAQ77zzDlasWIHvvvsO586dQ0REBP87KJFI4OrqijZt2sDJyalW6oDVDZJlMhlMTExgYmLCfy7lcjkCAgLQpEmTSstW+hpWnc+1SqVCSEgI7O3tIRAIwBiDWCyGmZkZP12numors7WXlxeMjIwgEAjw+PHjMtf5Y8eOYf369Zg2bZpOx0lmZiY/dcnNza1O1nQnpdASUIYZMWKEzo97ZGQkJk+e3CDZqytT20FyixYt8PLLL2PTpk01mvfUqlUrWFtbY/v27bVWNqDkB1WlUsHX1xdt2rTRWU/24cOHuHnzZoMlUTPU6tWr+Wzbbm5uOoEg+b9u3brxDQhRUVH466+/DD6WC5KlUilfQc3KyuLnOVa2drBarcbNmzchFov5gJLreX3y5Am++eYbvP/++3xPdXWYmZnxlfDU1NQqZWBPSUlBfHy8znIYhgQ5hYWF/JxThUJRa/OcpFIpxGIx7t69i6ZNm0KpVMLIyAgPHjyoNPDn3gvGmE6DGlfBMXREyG+//cYPlff19UW3bt2q+WyebyEhIRgxYgSAksr5smXLDG6caSiPHz/GjRs3+CDB0tISQUFBaNGiBWxsbMpd/7y6YmJicOjQoRr3Jv/111/QarW1+hvPBQKNTWFhIT7//HNs3bqVv61z58747LPPahysPI9UKhU/1z4qKoof5ePq6orZs2dj69atOH/+PICS72lKSgrCwsJw5coVJCYm8sGgh4cHWrduXeNM19UNkrljioqKEBYWhlu3bvHT3Ozt7RESElJh2fQFyWq1GllZWRWugiIQCODu7o5mzZrxWeTj4+Nx4cIFfipkTQPc2lgjWaVS6SxhWN5614cPH8bZs2cxZ84cnY6TS5cu8X/TNIZn3zMfJI8dO5avQAAlH9zZs2fXahbB2mRmZlZrZTMxMcHUqVPx7bff8pVVoVAIhUIBU1NTWFtbw8HBAS4uLnB1dYWTkxPs7e1ha2sLKysrmJubQ6VSwdjYGEOHDsVff/1V7d4J7nHNzMxgZ2cHT09P+Pn5ITQ0FM2bN4eNjQ0/PDMhIQFXrlzhl7tp7AoKCrB48WI+M3OXLl2oQv8UIyMjjB07FnZ2dkhISMB3331XpYohV+EAdNcqjY6ORlFREYqLiyuds8Rd9DUaDT+knwusT58+jcuXL2PUqFFVfGb/5+7uDqDk81DVNcPNzc3h4OCgk83Z0ApOWloaHj9+DKBkrc3aqMAqFApYW1vDxsaGb+2OjY1FQkJChcfJ5XJYWloiLy8P8fHxOtnKuffN0LwCxcXF+Oabb/j/Dx8+vNanojzrzM3N8eGHH/L///nnn3V6sBqzrKwsXL58Gffv3+crrtySae3bt0eLFi3g4+MDJycnWFhYwNjYuEa9mH/++Sfat28PV1dXKJVKmJmZwdLSEtbW1rCzs4OjoyN/LXR0dIStrS3Mzc1hYmLCB+0ajQbLli1DcHAwOnfuXGuvQ0VZ+hva9u3bsWTJEv673KRJEyxZsqRWlyt6HrRu3Zr/mxtqbW5ujvnz5+OPP/7AsWPH9B6Xm5uLO3fu4MqVK/wUIqlUisDAwBq9xtUNkrnrKVAyJSI9PR1Xr17lR25xqzaU16Csb7i1UCiESqWCiYmJ3k4ggUCApk2bwtnZmV/F5ObNm4iKioJGo+G/H6XrAdVV08za3JDvwsLCSkdV/vjjj8jMzMQHH3zA31Z6XnKnTp1qVBbS8Gq3ObeeTZgwAS+++CL//40bN2L37t0NVyAD2NraVloRNdTrr7+OmJgYPHjwAP7+/lAqlXwvXG5ursFzGB0dHdGqVSscPXoUHTt2hEaj4deNVKvV0Gg0YIxBIBBAKBRCIBDwm1Ao5HulnpaXl8f/YBYXFyM+Ph7x8fGNvudYn7i4OKxevRozZ84EALz99tsNutRBYzNo0CB+uO2dO3eqnGW9sLCQ/4zJ5XJ++D2XRdPW1hZOTk6Vfn5ycnIQGRkJf39/yGQyuLu782tW/vTTT9iwYQO2b99e5SR+5ubm/POLjo6ucmMStz/3/WGMVel7EBMTAzs7O37YXnh4eJUe/2lcQMsNFUtJSakwURfH1dUVcrkcGo2mTCMX1ztQlXwGYWFhuH79OoKCgpCfn4/27dvXOLfC82Ty5Ml8RfrChQv8EPVnhUajQVxcHOLj42FlZQUnJyf+eyQSiWBra1vmGK1Wi6KiIv66o9VqwRjT2UQiEcRisc6/AoEACQkJePfdd7F//36DypeXl8cnC9RoNMjNzUV2djZ+++03TJgwAZcuXapxMsmEhIRG36h6/vx5TJ8+HZ9++inMzc3h5uaGpUuX4uOPP27Q5cUak44dO/J/cz3GkydPxs2bN/Hbb79VenxeXh4iIiJgZmYGf39/iEQiBAYG4vLly9Xq/WSMVStjNtfLbW9vDxsbGzx48ABarRZRUVFITU2Fr68vJBIJ/P39ERYWVuYxGGN4/PgxGGP8b33pUYxPN3QKBAL4+vrCysoKQMm15u7du/w10dLSkq8nJicnV/n5lFZUVFSjKRe2trb87xP3ulREq9Vi2bJlWLNmDbp3746jR48iKioK8fHxcHBwQGBgIBwcHAzKy0KqwdCkXDUYyPPM9iS/++67OgHyN9980+gDZKBkOEt1AyuJRAI7Ozv4+Phg0KBBGDRoEC5evMjPfSg9j6p0y3hhYSGfgVDfkOyOHTvi8uXL/A+eSCSCVCqFkZERVCoVzM3NYWFhAXNzc5iamkKlUkGpVMLExARGRkZlAmTGGPLy8pCZmYn79+/j6tWrOH/+PGJiYp7JAJlz5swZft63XC7H1KlTqecLJXOcuO+iWq3Gli1bqnwOxhg/1IoLtjgxMTF8xdiQdXXT0tL4i5K9vT1/0UtPT8fNmzfRpk2bKpePy5qdl5dXrQs5VyHgGpdK32YIrVbL9yZbWlrWOImXQqGAWCzmE+fdvXu30mOEQiE/DC0uLk7nuyyVSvmKTlUrfL/88gsKCgrg7u5OS62VMmDAAAQHBwMo+UyvWbOmgUtUfYwxJCcn49q1a7hw4QIiIyORmJiIrKysMtckoVAIuVwOY2NjmJiYQKVSwdTUFGZmZvy1yNTUFMbGxpDL5fznGCgZMdK6desyvyFarZafK88tU8M1ynFEIhFUKhUcHR2RlZUFrVaLjz/+GAEBAXBxcan2dy4xMbHCDP2NRUxMDD766CO+t9PZ2RmfffYZzatESb4FLmlXUlIS7t69ixdeeAHOzs5Yu3Ztlc6VkZGBW7du8Ulcq7tWvIODg85InqrgGomlUqlObzZ3jSwuLoZQKERAQECZXAJSqRTOzs5wcXHRqWdySteJBAIBfHx8+OeYlJSEiIgInWsfFzxnZ2fXOGFsUlISzMzMqr3+N9dol52dbfB1nssRMX78eP678vfff/P39+7du1plIY3DM9mT/Pbbb6NPnz4ASi6+q1evLneoS2ne3t6wtrbmk1U0BA8PjyrN1TQyMoKlpSUsLS2hVCr5SvawYcNw8uRJpKWl8fNBsrOzkZeXpxMUlzfkVSgUQiQSQalUwsnJCdOmTUNKSopO63zpvwHwrfhPt+wXFRWhsLBQ59/GOAerNuzcuROBgYF8Y8WwYcPwyy+/NHSxGlT79u35nsl//vmn2kutZWdnQ6PRlGl4KCgoQE5ODt8wY4iHDx/C2toaUqkUDg4O/PDo27dvo0mTJlUqV+mKRFXmIZfGBZTc6Auu0l4V8fHxfMXE2tq6RkPTSmcyffDggUEBu7GxMR9UPF2BkEql/MiRqlZ0bt++jZiYGDRt2hQuLi4ICQnRyRL6X+Tq6oqxY8fy///xxx8bzfJ4NVVYWMh/frjRCBKJBFKpFDKZDDKZDFKplO8dLj1qifv8lR7tVHrU082bN/kg+fjx49BoNPz1Sh+RSAS5XM5vSqWSz9K+Z88evP/++7h+/TqePHkCNzc3FBYWIjU1FampqcjIyDDoOhcfHw+xWAx7e/taG0VWVU5OTmjatGmlyT3j4+Mxa9YsLFmyBDY2NrC3t8fSpUsxbdq0RjuFrT60b9+ebwQ8ffo07Ozs8Prrr2PhwoXV+l5mZWUhIyMDFhYWsLS0rNZ1xcXFBXv37q3ycUBJgqmEhAQ8efKkTA6J3Nxc3Lx5E82aNYNYLOZ7lLnRXaWHU3PBcXlBso+PD9+wmpSUpHea0u3bt2Fvb18rCbcyMzPx5MkT+Pr64urVq1U6lhsyzpW1Ki5fvozz58/jvffew4IFC3D06FG89tpryMnJgbe3N0QiUYOvlf5cMjQpVw3CkWcuSH7ppZfQt29fACWtwytXrjR4eF5wcDAcHBwaLEhWqVTw9vbG4sWLK9zP2NgYtra2sLS01JmfyfHz8wNjDOvWrUNaWlq1Wt+0Wi20Wi08PDyQkJBgUE/Sf52RkRE8PT1x5MgRjB49GowxDBs2DNeuXUNkZGRDF6/B9OzZk//70KFD1T6PRqOBkZGR3otlXl4en1zK0HMlJyfD0dFRJ2N2VFRUlecalm5Jr27CpKeHWwOGz0nmaLVaZGRkwMrKqsZzHOVyOb80jaEVgtKv/dO/OQqFgr+/OkMHd+7ciY8//hgA0Ldv3/90kCyRSDB9+nS+cfLKlStgjMHJyanOVh5oaMXFxSguLq6VOYnnzp2Dt7e3QQEEN8T66ccVi8VQKpVwc3NDz5498dNPP0EkEvGZ9h0cHKDRaJCWlobk5GSkpqaWGzBzSxyGhIRg3759NX5+1WFlZYXBgwcbtAJGUlISZs6ciSVLlsDe3h52dnaYO3cuZs+e/UyPBKuJ0kOtT58+jQ8//BCHDx/GrVu3qn3O1NRUWFhYQKVSVTm5m1KphK2tLT+VqDoqmhLFBcpBQUF8oHz58mUUFRXpBMH6gmQuiHZxceED5OTkZNy5c0fvc9RqtXwCx9pw+/ZtNG3atMpBskql4stenSkG69evx7fffosePXrgyJEjOHnyJLp16wYzMzO0aNFCJ6EXeXY8U8Ot27Vrh9dff53//+rVq6s0f83e3r7avVy1oUWLFrh//77eeSRisRgODg5o0aIFQkJC4OTkxAfIWq0WqampuHv3Ls6dO4dmzZrh+++/R1xcXI2HpwQGBj4ziWAamru7OwQCAWJjY/mMoAKBAFOnTq328J5nnZ2dHQICAgCU9LJWNaFVaVxw9fRQSeD/c2irMrysoKAA+fn5OkH3vXv34ODgUKX3q3RSkepWEvUNt67OubjfDqVSWaMs+YWFhRAKhcjJyTG4clb6t+bpxjsuu2dxcXG1lgW5ePEiP8yzRYsW/+nsumPHjuXn1UVHR/PzkJ2dnWt1aaLn1a1btxAYGFijc6jVaqSnp+Pbb7+FqakpUlJScOvWLcTHx/O/U9xQWT8/P7Rt2xYeHh7l/q5cvny5QddNTUpKgrW1tcHTg1JTUzF79my+UdDHxwdTpkypyyI2WtyUs+LiYiQkJKBZs2ZQqVTYtGlTjc5b+ve0qgnrmjRpgvj4+FppVCpPTk4OPyxcLBbz64eX/gxxv/VP9ySbmJjwU5TS0tJw+/btehtdGBERUWb9YkNwjeHFxcXVGh2Ql5eHr776ih92XXr52a5du1b5fKRxeGaCZG9vb0ydOpWvYP7yyy/4559/qnSOoKCgGie8qYkuXbrg4sWLOreZmZnB19cXbdu2hZeXF185VKvVePLkCcLDw3H27FmEh4fjyZMnCAwMhJGRUa2t/xwQEFCj1tD/Ci5TKlAyRHD79u38Z8nGxgZvv/12QxavwfTo0YP/u6brdHMXJm6eIYeb76rVaqu0nrZEIoFCodAJujMzM5GTk6M3YVB5uCC5Jmt5l+5J5oLb6mSS54JkoVCo00NenfKU7v01RE5ODjQaDQoKCspkPuXKUpMhwVyDp0gkQmhoaLXP8yxr0aIFP7+/qKgIy5cvx7179/ilA7klaEj57t69C2Nj4wrXVjdUfn4+Dh8+jH79+iE9PR1RUVG4cOECrl69ipiYGD5IkUgkcHJyQsuWLREcHAx7e3udYOLixYsICAhosPm98fHx/BryhkpNTcWnn37KN0yGhobitddeq6siNlqdOnXiszJfvXoVw4cPx6pVq2o8PJjLEcMYq1aQXB+j/7Kzs/Hw4UMAJckrra2tda7NXHBcumFUIpHAw8ODz3dRXg9yXbl9+zZ8fHyqnS+mJuvPX7lyBefOncP777+Pa9eu8XWGNm3a/Gc7UuoUrZNcwtraGnPnzuVb0f/55x9s27atSudwcHCAmZkZIiIi6qKIlWrWrBl8fHywb98+CIVC2NnZoWXLlggKCoKNjQ2EQiEYY0hPT0dkZCTOnz+Pu3fvIjU1VecHqH///vj7779r9EXmSCQSeHl5NWjDwbPCw8MDQEnvZFxcHBhjWLlyJV9J6tKlC5/Y479CIBCge/fuAEouklVttHpa6TlvpQPA0sseVSVpFhfcPr12Y0ZGRpXWS+aC7Jq02tdWT3J+fj5f4dDX426otLQ0CAQCKBQKvVM69NFqtUhJSYFcLuezYnO498vQNZL1OXHiBP/3f3HpDIlEgnfffZf//4YNGxAbG4vCwkJ+OKKtrW2Nk7Y977hEdH5+frVyvv379yM0NFRn2kVOTg5iYmJw5coVfvkc7juuVCrRpEkTtG3bFp6enpDJZHjy5AnOnTtXoyXoaur69eto3rx5lY6Jjo7G559/zv/mDBkyBL169aqD0jVe3PQcsVgMb29vHDhwoNYCVJFIpDMFx1De3t5VXkGiumJjY5Geno78/Hw0adJEZzSLvuHWNjY2UCqVyM/Px927d+t9iH5MTAzy8vL4EW6G4r6/NV3Dff369XB3d0erVq1w8uRJACW/7f/Vht9nXaMPkiUSCebMmcNXeMPCwvDVV19V+TzNmjVDRERErSQHqCqBQIBx48Zhx44dMDc3R+vWreHt7a0zhy8mJgYXL17ErVu3kJycrHfIor29PZo3b44DBw7USrlMTEwgEAhoiYdK2NjY8EFadHQ0X2FISUnB+vXr+f3eeuut/1S262bNmvE9I5cuXarWchSlccnmAOjMueX+zsrKMrhxSC6X80k4nu4BzsjIKJOxszwikQj5+fl8QrzqKp24qyZBMmMMOTk5yM3NrdFnLTk5GYwxSKXSKvWqc8MvS2e1l0qlfMBek+Q+Dx484IPBgIAAneRi/wVDhgzh5/Bdv35d53f+0aNHKC4uhkAg4BvsSPnS0tJqbZ3f+Ph43Lp1i08W+rScnBxERUXh/PnzuH37Nv87KBKJ4OjoiNatW8PX1xc7duxAx44d+fXW61t1gmSgpHfs+++/5///9ttvV6lH+llma2vLP9f09HQ4Ozvj999/r5Vzl+49rkq9lFs6qj47N6KioiCTySAWi3WuF08HyQKBALa2thCJRMjNza12Do+aOnPmTJWDUm74u0QiqdF0n7y8PGzbtg2jR4/W6TgoPa+d1BLqSS5Z6omrFCQkJGDJkiXV6kUNDg7G9evXa7l0hpk4cSKsrKyQnJwMd3d3viUuIyMDYWFhuHDhAmJiYiqthPfo0QPnz5+vtaDWyMgIhYWF1ZpD+F8hFAr5Sk1WVlaZnsxjx47xSbucnJx0liV73rVo0YL/+/jx47VyTq6CWXpYYnWCSjc3NwgEAmg0GiQmJpZ5DEN7kmUyGYyNjWFkZFSjFnF9ibuqOxpEIBDA+H/sfXd8lGX2/ZneW5JJMpn03gMJIEVpIiAKiKJiW3RVFAV1XZcVXUV37StrW8vaUFERUaSsgDTphJZKeu89mZTp7fdHfs/znUkvM0lwPZ9PPoQkM+87M+/7PPfce+65ItGQK8B9Qa/Xw2g0gsPhQK1WD7nX1fGciWycjPew2+2jkqQDoJl3BoPxPxVU+Pj4YOXKlQC6A86eY2WsVis17VIoFMNSQvwvwnH+sSvw888/D1pBJSZ4WVlZOH/+PGpra2Gz2cBgMODt7Y3AwEBcvHgRzz///Lh8fhkZGU7J+eFg//792L17N4DuStvGjRuHnGi8kuGoaBEIBNi7dy9YLBZmzpyJyZMnIzQ0dNhSaQLyOdjt9mHtLfHx8dDpdEOaa+8q6PV6uo96eno6ucw7/kuINNBdUBgvEJI8HN+OtrY26pYfFhY25McKBAI6A5689oMHD4LH48Hf3596bcTGxo66Sv07xh4TmiTPmzePyjmNRiNefvnlXtLJoYDJZCIhIWHMSbJAIMBLL72EqVOnUnk4mReZlpaGrKwstLa2Dvn5pkyZgrNnz7rs/IRC4W9mrIi7oFarqSlRf5vSRx99RKvLd9555/9MAJuYmAig+5rOzMx0yXOS3jmhUEgryGSzGmpfk4+Pj9M8355ktK2tbcgBnmMCaTSVW0e5NXk9IyXd5DxG2+el0WjA4XDAYrEQExMzJMmf4/tB/l6lUsFoNKK+vn7U0jpHyfWMGTNG9VxXEh544AEabO/Zs6dPt9e6ujpa7fi9mjwwdDrdqJJIPZGRkQGJREIN1QaDwWCg/csVFRX0vjhz5gxaW1vx3nvvjXk1tqWlBXV1dcOWoRJs2bIFly9fBtA9Qu7hhx8elXnglYC5c+cC6Fbdcblc7N27FwEBAQBAx2fGx8dDrVYPWzJN5gO3t7cPay2fNm1aL2+bsUBtbS2A/xvXBvQmyXw+H0wmk8qzxwu5ubkwm83DMvCz2WwoLCyE1WqFTCZDSkpKv1MkhEIhgoKCkJKSgqlTpyI2NhZBQUG0FcZqteKbb77BXXfdRT1/uFwuoqOjR//ifsf/4X+5khwWFob169ejpqYGZrMZ77zzDp2pOFyEh4fDbrejpKTExWfZN5hMJuLi4vDpp58iLCwM27dvR1tbG2pra3HhwgXk5eUNm+x7eHggKCgI6enpLjtPPp8/Kgnpbx0cDocGRc3Nzf1KScvKyujweD6f7+TA/luFWCymFfby8vIRJa/6Qnt7O52PSvpeSfAxlCBEoVDQOchdXV19rhnDqSQbDAZKDEdjuuOKEVBA9+ZMgv/RJrh0Oh2tDshkMkRERAz6HjsGxcQ8TCgUgsfjuURaV1tbi/r6egDdfXcjrdJcSUhOTsZVV10FoFsm3J/fht1up4k6kUjUqy/8d/wfjEajS0my2WxGVlYWpkyZMuzHVVRU4Ny5cyguLobBYMDu3btRVlaG999/H7fccotLz3MwZGRkYPLkySN6rM1mw+uvv46WlhZUVVVh2rRp49pj7W74+vpSQszj8bBjxw4wGAwoFArweDxoNBoYDAZIJBKEhYUhJSXFqcpKnuPZZ5/Fiy++iGeffRb33HMP4uPj4eXlRRO1w/HZAMaPJGu1WnR0dIDFYvUiycRYkPRYj9c8cAK73Y7Tp0/j6quvHtbjmpub6Z4oEAiQnJyMFStW4M4778RNN92EuLg4XHXVVZgyZQqCgoLoZ83n8yEQCJx8EI4dOwaTyeSk0vpf8635LWBCkmShUIinn34abDYbarUae/fuHZWb8+TJk5GZmel2hz0S2C9btgxvvPEG2tvb8fHHH6OoqAjnz5+nm+RIkJycjMLCQpeREaC7ova/UvUcCYKCgsBisWC32weVDm3dupWaFs2dOxdxcXFjcYrjhri4OLpBuHqEGAkaSBCh0+lgt9shl8sHDCi9vb0RExMDi8UCi8WC3NzcPlsJOjs7h9VzVF9fTx2x+5MqCoVC+Pn5QSKR9GmoRZJR/VWSmUwmFAoFPD094eHh0W+FJjw8HDqdDnq9nsq4RgqDwQCNRkP7k2UyGWJjYwesDgUEBMBqtcJiscBoNNLPiIzMcQVIrx2bzaYJj98q2Gw21qxZQ/+/ZcuWASswLS0tVNIeHBz8m6/kjRQKhcLlXhsXL15ESkrKiB5rs9lokryoqAg///wzdu/ejXXr1uHxxx9HeHj4mCSE0tPTR0ySge4k5muvvQY/Pz+w2WysXLly2ImDKwWknUgikcBut2PXrl3gcrmULGZlZSE7O5uqAYVCIeLi4jBt2jQEBQXRv83OzsapU6eQmZkJT09PPPvss/jmm2+QnJwMg8EwrLGk/v7+UCgU4za2s729HQwGg6qZHCvJRErMYrFG3XbjCpw6dQozZ84c9n1VXV0NhUKB22+/Hc899xwefPBBLFy4EJMnT4anpydVFlqtVmg0GuTk5KCkpASdnZ1Oa7fdbsfXX3+NSZMm0XX6d5J85WFCCuSfeOIJag5QUFCArVu3jvi5WCwWFi1a5GSw5A4QR8u5c+di6dKlOH78OL7//nuUlZW5RHYyZcoUXLp0yQVn+n9oaGgAj8dzS0BxpUMoFEKlUgHorm4N9hl2dXXhq6++wqOPPgqg28TriSee+M32exOpNQCXjxAjFXsejwcOh4PKykoIhULI5XIkJSUhLy/PaRPm8XgICwuj8rWuri4UFBT0m5BiMBjD+lwqKiowdepUsNlsJCYmorS0lGbOpVIpPTdybC6Xi/Pnzzsdg1w/JNsOOPf3BgYGIjAwEHq9HgKBABaLBe3t7Whra6OmLt7e3vQ4RUVFo3a4NxgM4PP5uHTpEkJDQ6FWqyEQCDB16lQUFxc7VYZZLBaio6OhUChgsVhQWFgIm83m5GrtqiRkTk4ObbOJi4sbt4kEY4Hly5fTUUW5ublOcvP+UFpaismTJ4PL5SIgIID2Kv+O/4NKpXL5iJxLly5hzZo1EAgEI97T7XY76urq0NDQgJqaGjQ1NeG+++5DYGAgfvjhB+Tn51NZqzuQmZkJiUSCpKSkEbfIFBQUYMuWLXjggQcAAE8++SQef/zxYVdEJzoISfbz88MHH3wArVYLqVQKkUgEu90OBoMBvV6Py5cvw8PDg87J5vF4CAoKQmBgIHQ6Hd2L2Gw2amtrkZaWhuDgYNxxxx3w8fFBaWnpkBOeV111FTIzM8fFgBbo3t/IHkY8P4DuvYyQ5OH2WLsLeXl5aG5uxnXXXYd9+/ZBJBLBy8uL7q/EQ6OlpQV2ux1sNhvXXXcdbr/9dnR2duLkyZP49ttv0dDQAB8fH1gsFmqa2dnZiba2NrrH+/v7U3WBI86ePYuVK1ciNjYWNpsNkZGRo1o/fkcPWDA0KfXwOiGcMOFI8rJlyzB9+nQA3YHX66+/7mQvP1zMmTMHRqMRqamprjpFJ7BYLISEhCAkJAQrVqxAWFgYPvzwQ+zfv39U41B6Ijo6Gnv27HHZ8wHdlayWlhaoVKrfSXIPkDl/FotlyEHowYMHsXjxYoSFhSE4OBhz5swZ9VikiQrS62O322mfmqvgqJYQi8W0VUEmk8FutyMxMREdHR3o6uqivcskU6vT6ZCbmzugYoPFYg1rTTGbzSgqKkJkZCRsNluvviLHDc/DwwMmkwk+Pj5OkjNyPn1VkoliBgCkUinMZjNMJhM8PT17SbyJy7Yr5GwGgwE8Ho+2otjtdrrZx8XFOcnrCDkGQAMLALQi70qFi6Nrq6vG+ExEiMVi3HrrrQC676OeZl39obOzE42NjfD29kZAQADq6urGLWieqFCpVFS27yo0NjaitbUV4eHho04M2mw2VFVVUWL8+OOP409/+hO+/fZb5Ofno6ioyKX3FIHRaMSePXuwcuXKUflI7NmzB/Hx8Zg+fTrEYjE2bNiAp59+elSx2kQCi8VCYmIieDwe+Hw+tmzZAuD/xgAyGAyo1WpUV1cD6G6TaG1thUwmg0qlgpeXF5hMJkQiEUQiEbRardPotry8PKxevRq333473n//fXzxxReDTi1hMpm4/vrr6bmMBzo7O2mSl81mU5JoNBp7VZcnAr7//nv88Y9/xNmzZxEYGEh7jIkMWq1Wo7W1FaGhoVi+fDn0ej3+85//9PL+KS4uHvA4RFXXV6J4x44dePPNN9Ha2kpbMS9evOiiV/g73I0JpdWKjIx06ud86623RiUpFAqFuOOOO/Djjz+6RWrt5eWFqVOnYtq0aXjsscfA4/Gwdu1afP/99y4lyCKRCB4eHm6pGNTU1NC+m9/RDblcTsfPVFRUDLliZ7fb8emnn9L/r1q16jcph5RKpQgODgYAlJSUuNz8zWq10veNbLzNzc3IzMyE0WgEg8GATCaDWq2GQqEAk8mEzWZDWVkZLl26NGhLw3BJMtAtAU9PT+/Vs2swGNDa2orLly/j1KlTtJ+JqBAICJF2lKoRkqxUKunPzpw5g0uXLqG2traXoQupQrlq9AepJBOUlpYiIyODBoIikQgqlQre3t7gcDjg8/koKSlBTk4OPS9y3sM1rRkIdXV1NCM/VEOxKxHLli2j8v1Dhw4Nyw22rKyMqhnGa6TQRIVAIIBSqXRLRba8vBxBQUEuez6LxYKMjAysXbsWR48exUMPPYQlS5ZQ52R37B8///wzoqKiRi2Tfvvtt+l6FxUVhXvvvdcFZzcxEBMTAz6fD6VSiezsbKpu6ujooAnCoKCgXm077e3tyM/PR2pqKgoKClBbW4uOjg7o9XpotVo0NTWhoKAAaWlpaGxsxHvvvYdXX30VK1euxMsvv+zkM9Dzs7/qqqvAZDJdat46XBgMBqe9mexhjiR5IuHMmTMwmUy44447IJFIYDQa0dbWRj+TyMhIvPTSS7jvvvuwY8cOrF+/fkTvb3t7O/R6PTw8PHrtV2Q8JiHov0uuXQjTML5GiAlTSWaxWHjsscfojfbDDz+MOtvy1FNPobKyEocPH3bFKVKw2WxERUXB09MT11xzDRYsWIAdO3bgP//5j1uyaIGBgWhtbaXBqyuRnp6Oq666Cr/88ovLn/tKRVhYGIBuYjPcQCsnJweZmZlISkqCSqX6TVaTHSuprpZaA92O4jabDRqNxklW3dHRgcuXL8PX15fK3nQ6HR3NNdR+f0KqhwudTofz58+DyWTCbrf3+Rzt7e0QiUS9Eit9ya0dZycTgzDyd1qtll57jtVnV64vBoOhV493R0cH0tLSoFQqIZPJIJPJYLFY6HvcM/lXW1sLtVoNLy8vVFZWjloCTpCTk4NZs2ZBKBQiODh4XMeJuANisRjLli0D0P2Zbt++fViPNxqNqK6uRmBgIHx8fFBTU+OWyuOViClTpqCysnJYkyOGisrKyiE7XA8HBoMBb731FlJTU7Fx40aEh4fj+++/h1KpRH5+vkt7PLu6uvDee+/hz3/+M/70pz+NuOKu0+nw2muv4Z///CfYbDaWLVuGU6dOoaCgwGXnOl4gUmsvLy+nGdFAd2JYLpfTecUZGRm95LMWiwUNDQ29xg/2hYyMDDz66KO499578f777+PkyZO4cOECWCwWHb1UW1uL5cuXY+/evePewuUoqybrvaOSZajjBMcCdrsd+/btw/3334+cnBzk5+ejubkZkZGRWLhwISZNmoSTJ0/i0qVLaGlpAY/HG5FvUEtLCy02CYVCp1jdarVi165deOGFF6DT6VBeXu6ql/c7xgATpsx1yy230M2nuLgYX3/99aCP4fP5SE5Oxpw5c7BgwQJMmTIFKpUKSUlJeOWVV+Dn54fNmze79DyJNXxQUBDuu+8+TJkyBU8++SQ++OADt8lMgoKCRuzsPRhOnz6NSZMmuXSm5JUMX19fKosqKysbkQJh27Zt9PvfYjXZUXkwmAxpuFAqlXQdsFgsvXqbLBYLqqurkZubiwsXLiAnJwdVVVXD2thGUkkmsNvtsFqtfQYqxPmUy+U6SesA50pyT7k1qdIKBIJej3M8pqvXF6PRSE1Ieh6vsbERRUVFuHjxIjIyMlBaWtqnOqajowNsNht8Pt+lVV8yexz4v6TVbwk9q8gj6eesqqqi19DvI6H+D7NmzcKZM2fc8tyVlZUurST3xNmzZ3H33XejqakJjz/+OOLi4pCYmOjyY548eRKHDh3C66+/jmXLlkGpVCImJgbz58/H3LlzMXPmTDpGbyCUlJTgq6++AtC9tq1bt25CVhSHi5SUFLoPff/9906/MxgMyMnJgc1mo+aCoyWGxMfip59+wqxZs7Bx40Y6bSA4OBhz585FaGgoDh48OKrjjBZMJpMaYTn2HhuNRhor9bWnjCcKCgrAZrMxa9YsyGQyPPfcc3jppZdQUFCA1atX4+OPP4ZWq4VCoYC/v/+IjuEYp/TcA4OCgjB16lSIRCLU1dUhODgYUql0VK/pd4wdJkQl2c/PD6tWrQLQ3avz3nvv9Zst43A4uP766zFt2jTExsaiqakJbW1tMJvN8PDwgKenJ6xWK/bs2YP//ve/LpWCBgYGIigoCBEREbjtttuQlpaGdevWuaXC2/O47jJnqa+vR3V1NaZOnTok05jfMphMJpURt7e3j1jqn5ub61RNnjt3Lo4ePerCMx1fOG4kpCfLFRCLxXR2KDE8cQeYTOaoCSebzXaqmnI4HISFhVFJVVVVldPfExLfl3FXXV0d1Go12Gw2YmNjUVpa6pJxSoNBr9f36cQ9HLS1taGiogJBQUFQKBQIDQ11yag9x/eP9Gv/ViAWi7F8+XIA3VWGHTt2jOh5rFYrysvLERERAblcDk9PzzG5biYyuFwuUlJSnBKVrkRFRYVbKsmO6OjowIYNG7BixQqsW7cOqampOHz4MORyOfLy8lzWf/75558jNzcXt912Gx544AHk5eU5zbsNCQlBfX09Ll26hH379vWrqtqzZw/mzJmDsLAwBAUF4eabbx7xNT0RIJPJ6GspKirqZcYEdI8RzMvLQ2hoKORyOeLj45GZmTmifcXT0xMxMTFgMpmorKzEa6+9hri4OKxcuRJyuRwXLlzAqlWrcOzYMbfHmoOBxWI5VZLJtehIkke7p7gaEokEhw8fxoMPPohp06Zh9+7deOedd5xGemo0GggEAmqMOVw4FlMISWYymbj55ptx++23Y/fu3VAqlQgKCkJ7ezuSkpJw8uTJUb2u34Ghz0C+0o271q1bR2+8Xbt29SutS05OxsMPP4zOzk4cPnwY7733Xp9yltFUivoCh8NBTEwMPD09sWDBAkyfPh3vvvsudu/e7bJjDAQPDw+3OryeOHECixYt+p8nyQEBATQjPNpAf9u2bbT35Pbbb8exY8fGXSblKjiSZFf1/YlEIiQmJoLJZMJisSAnJ8dtyoyRrA/+/v6YPXs2rrnmGkracnNz8dJLL8FutyM+Ph5cLhd6vR4dHR29kgc9e5IdCbbJZEJeXh6io6PBYrEQFxeHsrKyXkSbQCwW45ZbboFMJoPRaERWVhYuXrw4bEfRnj3JI0VFRQV1DlWr1ZS8jQY1NTX0+98aSV6+fDmVuY+0ikxQX18PPz8/iEQihIaGorW11e2jDicy5syZg8bGRrcllZubmyESicDhcNzu4PvTTz8hPT0dL7/8MtasWYNt27ZBKBQiPz/fZUabqampSE1N7ZX0A7rJTlJSEo13fvzxR/zwww+9XjcpbLz11ltgMBhYtWoVTp06Ne6zckeKyZMn032IxWLBy8urz4R5S0sLuFwuIiIiIBaLER4ePuzErkKhQGxsLBgMBjWIbG5uxqVLl3Dy5Ek899xzuPbaa2G320fcthUaGoqgoCC0traioaEBzc3NI26LYbFYNMnbXyV5IpHkKVOm4LHHHkNAQAC2bNmCzz77rM97x2AwUFPMkcButzs9Njw8HA8//DAEAgE2btyI4uJi2O12vPrqq6ipqfmdJF9BGHeSvGDBAsTHxwPoHknUVwZYLBbjkUceweTJk/HVV1/hwIEDAwYCrgyuBQIBEhISoFKpsGrVKlitVtx///1j2lcglUr7NQIjJkYcDgcikYhKOY1Go9OX2Wzu9z3bt28fbrnlFiQkJLilx/RKABmnAnRfh6Pt7/stV5MJSW5sbBzxpuIIQpCJW2Zubq5bRyQMhSQzmUwEBARg8eLFWLBgAby8vKjE++uvv0ZjYyMiIiLA5/MREREBDocDu92OmpqaPhMHjj3JTCazV6DZ1taGjIwMuhYSM6aqqioIBAKoVCrI5XJwOBxcffXVSEhIQFFREeRyOe6//348/vjjOHv2LI4dOzZk11qDwTDizHlP5OfnIzExEVKplFbaRrNGNjU1wWw2g8Ph/KZIsmMvssViGXXFzW63o7S0FAkJCfQ6cecIoYkMFouF22+/ncp/+wObzQaPx6NfXC4XLBaLtjW0t7dDq9X2SSTIviCVSsekal9eXo57770Xf/7zn/HYY4/hp59+ApvNRnFxsUtJaF+v1WAw4Ny5czh37hx+/vlnPPLII5g7dy7efffdXuaBpaWl2LVrF1asWAEOh4NHH30Uf/vb31x2fmMJMg+3ra0Nv/zyC5544ol+X0tdXR0EAgH8/f1H5A3g6+sLBoMBk8mErKwsJ+VjWVkZHnvsMbz11lvw9PQctkR31qxZuPXWWyGTydDQ0AC5XA5vb2+wWCy0trYiJycHJ06cQFpa2pBJM4vFcpJbk0qyxWKhRYDxllszmUxcc801uOWWW+Dt7Y3s7Gx88sknuHjxYr9xhVAohFAoHFUhg8fjwdPTE4sWLUJCQgJ2796N7du3073+hx9+wMsvv0xHWf4OF2CoI6BG0fE4riRZJpPh/vvvp/9///33ewXdCoUCL730Eurq6rB27do+pS/ugkQiQWhoKKZOnYoVK1bg8OHD2Lx585jPgJNIJE4kmYxk8fLygoeHB9hsNrq6uno5LTqCLGh6vR4ajQYajYbONtXpdNi1axfuuusuPP3002PxkiYcwsPDnVySXYHfYjVZoVDQvllXSK0JQeZwOLDZbLh8+bLb73EWizXg58BisXD//fdj4cKF4HK5OHbsGLKysmhAwGKxIJPJ0NbWhpiYGOh0OrBYLOTm5vZrFuQ4AsrRFdQRer0e6enpiI+Ph1AohFqthlqthtFopPOIgW63zAsXLgDorkIT46/JkyfjqaeeQkNDA7755hukp6cP+D70Zdw1UthsNmRnZyMhIYESZbvdPuKKHnHyDgwMhEqlAoPB+E1USB2ryIcPH3bJbNm2tja0trbCw8MDwcHBaG5u/p8cCbVgwQIYjUanCg2fz4dcLodcLodEIgGPxxvUI8JsNoPNZqOjowPNzc1oaWmh96/NZoNWq4VEIhkzabvZbMZrr72GCxcuYMOGDQgLC8OPP/5IZ8iPBYqLi/HnP/8ZN954IzZt2oTNmzfj3LlzTn/z7bffYtasWfD29kZiYiKuvfZaHDlyZEzOz5VITk6Gp6cnampq8PLLL+Ptt9/GsmXL+h3BWV5eDm9vb5pod/RTGAgCgQBeXl4wmUwoKyvrszWwq6sLL7/8Mp5//nk8/vjjWLNmzaAkPCIiAo8++iikUil27NiBQ4cOOZFghUIBlUqFKVOmYM2aNRCJRDh06BDOnDmD/Pz8AZ+7p9za8XmNRiP4fP64keSgoCDMmTMHc+fOhcViwU8//YSCggL4+/vDarX2S5CJF4jdbh9x7EFaaFJSUrB//3489NBDvWIBo9GIjIwMREREwMfHB97e3mhsbBzR8X7H2GFcSfKDDz5IA+5ff/0VGRkZTr/39PTEK6+8gtzc3AH7lN0Bku1ZunQpEhISsHnz5kHn2LkLEokEer0eKpUKnp6ekMvlvTZ6DocDvV4Pm80GBoMBLpdLFzOgOzgnmXO5XA6LxQIGg0EJ87Fjx7BixQqkpKTg0qVLY/0SxxVeXl7w8vIC0G3M4qoA87dYTXaUWvcnBx4qhEKhE0HOyckZkyTYQJXkWbNmYe3atZDJZDhy5AiOHDmClpYW2O12sNlscDgcKBQK+j3Qvcnm5OQMKIEkcrT+KskEFosF2dnZiI+Pp/3NRNrZ2toKvV5Ps/Z8Ph++vr7gcDiwWq344osv8M033+CGG27AU089herqanzzzTfIysrq97xcOV7JarU6EeWgoCDY7fYRB/I1NTUIDAwEm82Gt7f3kJxiJzJcXUV2RGlpKeRyOdhsNsLDw93anjMRweFwcMcdd+Cbb76Bl5cX5HI5FAoFrFZrn2Z4BDabDSaTCRaLBUwmE1wul97XxN09LCwMWq2WEuaOjg6npNVY4ciRI8jPz8fLL7+Mxx9/HNu3bweHw3GJB8BQYLfbsXfvXjQ0NOAvf/kL3n33XaeEhNFoxAcffIAXXngBAHD//ffjwoULTr2fEx0hISHw8vKCSCTCyZMnodVq8a9//Qt///vfUV5e3udaarPZ0NLSApVKNSypMYvForHaQN45TU1N+M9//oN7770Xb731Fp577rk+HcmFQiH+8Ic/4Nprr8WOHTvw008/9bnPtLW1oa2tDbm5ufjqq68QERGBmTNnYtOmTWhubsbBgwdx8uTJPvdiNpvdp9waAC1wDWZixmazERAQgODgYDqpgnzx+Xw0NTWhtLQUjY2NqK6uRnt7Ozo6OuixeDweTSIHBwcjODgYkyZNQldXF6qrq/Hhhx/i4sWLsNvtmDRpEgAMeA2q1WqIxWKwWCyqriLqy8Eq7DweDytWrMD06dPB4/Hw7rvvori4uF83+sOHD2Pq1KlgMBhISEi4IpNI/2sYN5KckpKC2bNnA+geUP7ZZ5/1+pv77rsPubm5eOedd8b03Mhop3vuuQcGgwFr165FaWnpmJ4D0B18e3p6wt/fH5GRkb0y1zqdjm7cfcmxWSwWuFyuk7RMIpFAJpPBZDJBKBTC09MTnp6eALrHQb344ot444030NHRAaPRCJPJRJ11Hb9MJhOVcrsaQqEQer1+TCpHJKgEusfujJb49YRjNfnWW2/9TZHk0VSSe1aQByOZrkRfI6BUKhXWrl2LkJAQXLx4EZmZmWhoaKBkg8FgUGfq0tJSSKVS+Pn5UfI6lHM3GAwDVpIJrFYrcnJy4O/vDz6fj87OTtTV1dFeZsf7QqPRIDExEXw+H97e3qivr8fOnTuxb98+LF26FE8//TQKCgrw0Ucf9SKZ/fXajQaEKCcmJkIikSA4OBgMBmNEFeWefclXOkm+4YYbXF5FJtDpdKisrERwcDBN+rn6s+0PYrHYLeOniGs6j8ejvZCOX46y6ZUrV4LH48FoNCImJoY+B9lHurq66CxTx72rr/uQy+XSfZEkpEUiEUQiEYKCgiCRSBAdHY2qqqpes8zdjZqaGqxZswYbNmzAunXrsHv3buzfvx+FhYVjdh7nz5/Hq6++igceeAAlJSVO8v60tDQcP34cc+bMgVgsxpo1a/Dmm2+OyXm5AsnJyZDL5ejq6qIO6Xl5efjwww/xzDPP4K9//Wufa5lAIKB+FEOFTqeD3W4Hg8GASCTqt6VOq9WCxWJh+/btmDZtGjZv3oxt27bh9OnT0Gq1UKvVSE5OxvLly1FWVob169cPa6xXUVERioqKsG3bNsyePRvz58/HH//4R+Tk5OD48eN0zi/Qu5LseP8YDAaw2Wx4enoiODiYfq9UKum/QUFB8Pf3h9FoRHl5Oerq6tDe3o6SkhIacyqVSsjlclx11VXw8/OjCSmi8CCJ3ebmZpSXl6O8vBwffvghsrKynM5HLBbTBNlAa21HRwd8fHzA4XCcYkGRSASbzYbW1lbU19ejra3N6R5LSkrCn/70JzQ1NeGjjz6CRqNBYGAgLbCVlZX1igtOnDiBv/zlL5BKpb/Pt3cFhmrcdaXJrXk8Hh555BH6/88++6zX4rJ48WJER0fj0UcfHdNz8/DwwF133YUVK1bg9OnT+Oc//+nSGYWDQSgUQqlU0mwmAKcekM7OTkqMB+vbJBKTnn/HYDAgFotptl0qldIh9XFxcVixYgV++umnIZ0vMSwwGAwwGo3QaDRobW0dkSRdKBRi+fLlWLZsGT744IMxMTYICwsDl8uF3W5HQUGBywON3NxcXL58GfHx8VCr1bjqqqt6ydSuJLiCJCuVSkRFRVGympubO2YEGegOvklyh8Ph4JZbbsHKlStx+PBhbNmyhfamO/bUJiUloaurC76+vigvL0dtbe2g0rSe0Ov1g1aSCSwWCz0+i8XC5MmTIRKJoNVqUVFRQQkQmSUtk8ng6+tLgyODwYAdO3Zg3759WL16Nf7973/ju+++w65du2gV3dvbe1BJ9khgtVqRlZVFiXJQUBCEQiEKCgqGpQZyDL79/PyQlpbm8nMdK3C5XCxduhRAd+XJHe6/VVVV8PLyglgsRkREBDQajcvmVvcHoVCI//znP7h8+TK+++67EbWqEF8NDw8PCAQC8Pl88Pn8IY8SCg0NxVVXXYX33nuP/kyn06GtrY0qpYbjU2IymVBXV0cTU2RqhqenJ1gsFphMJpRKJRITE2E2m9HS0oLm5uZeQbS7YDKZ8Morr6CwsBD3338/wsLC8PHHH4+pn0haWhouXbqExx57rFeL1ieffILk5GRIJBLMnj0bR48evWLu3cmTJ9NWGse18ejRo/D09MSLL76Iv/71r04JO7lcDplMRttehgoi3ReLxfDx8RmQ2La3t8PT0xMHDhzAqVOnMGfOHDz44INgMBjQ6/XIysrCRx99NKrRZyaTCYcPH8bhw4fh4eGBq6++GosXL8b69evR2dmJqqoqaLVaREZGAujdx240GiEUCuHv749XX30VVqsVzc3NaGpqQktLC8rKynDixAmUlZUNK0HIZDIhFoshFothMplgMBig1+sHvacDAwOpWnIgWbPBYEBLSwskEglNYpK1h8lk0qSjyWRCRUUF6urqMG/ePDzyyCP4+OOPcejQIfpcAoEAAQEBEIvFSEhIQEdHBxobG6HT6aDX61FeXo62tjbIZDI6SeV3TGyMC0m+5ZZboFQqAQCZmZm9qmsKhQL33nsvXn/9dbdUKvuDh4cHnn/+ecTGxuKLL77Ajh07XDpCqj+IxWJ6I/acV2yz2aDX61FRUYHs7GyX9EMTsk0WPiaTSTPyr7/+Ol577TV4enqiuLiYymscvxwlmgwGgwY1AODj4wO73Y6Ghga0tbUNaTEUiUSUHJPXTxwy3Rl0KBQK+Pj4AOgmfO6ohgDdhg3EkGnlypVXNEkm9y2AYWWrCUJCQigJtVgsyMvLG1OCDHR/7nl5eYiJicETTzwBnU6Hp59+GsXFxbTq39HRQe99mUwGqVQKpVIJk8kEPz8/+Pn5oby8HE1NTUO+RvV6/ZAqyY5gMBgIDQ11IgyxsbEoKCiggVp9fT09R6FQ6LRmabVafPDBBzh69CgeffRRzJs3D//+97+Rn58PpVLptp4oUlGOjY2FXC6HUqmEUChETk7OkANJx0qoQqFwy3mOFRYsWECNd06ePOnSKjKB3W5HYWEhJk+eTKsiw03kDBc33ngjJBIJZsyYgRkzZiA1NRXbtm0bElkWCoXw8vJCQEDAkAgxmU9usVic5oZff/31+OKLL3D8+HGarHVVcsBqtaKpqQlNTU1gMBiQy+XQ6/VOSTZfX1/4+vrCYrGgtbWVjqV0Z3sYSbRUVlbi0UcfxT/+8Q+88cYbbpsP3Re+/vprvP/++1i8eDEOHDhAf97R0YHPPvsMTzzxBADgoYcewtq1aye8HwcZwVdcXIympqZexmg7duyAWCzGv/71L7z22mvIzs6GSCSi8+GNRuOw1S61tbV0qsZAigyNRkPNu86cOYMzZ86Ax+PRNjtXT4JobW3Fnj17sGfPHvB4PAQEBMDf35/GMY6mXQQGgwEdHR3QaDS48847XRa72Ww2dHR0DKtKz2Qy4enpCQaDMWjyyvG5GQwGOBwOOBwOeDweRCIRfHx8IBQKqZP5rbfeilmzZuEf//hHL/l9WVkZtFotAgMDIRQKIZfL4eHhQSdJNDU1oaCgAAKBwK3z1v9nYPr/X4PhShoBJZFIcNNNNwHo3oA++OCDXn/z4IMP4sKFC26pcvSH8PBwvP7669DpdHjrrbdw/PhxtxJkqVRKiXHPPhar1YrW1lY0NzejtbUVGo0GLS0tbjMMI0ScmHq9/fbbuPfee/GnP/2pT8ke6d0i5JjH44HP50MoFEIikYDBYEAqlcLX1xeBgYEoKSnps79FIpFg6dKlTuSYvP78/HzweLxhZWaHAxaLRTOiJAnhLqSlpaG8vBzBwcGIiopCbGzsFdsz6OiGPJz+YS6Xi+joaGrqodPpkJOT41YX6/7g7e0NDoeDu+++G19//TX27NlDZW+EyDgGO2w2G1qtFlarFY2NjVCpVAC6R4aFhISgpKRkSNLWocqtCchYEbFYDAaDQcfPAN3rVVtbG0wmE5qamhAREQEmkwmZTNbnupWfn48nnngCN910E/7+978jMzMTfn5+Lm8vcATprw4NDYVarQaPx0NSUtKQ3y/H68tVLtzjASaTiRUrVtD/79y5023HIn15AQEB1BimPzM5V6C1tZWahgHA9OnTMX36dJw7dw7bt29HcXFxr8dwOByEhobC29sbVquV+muYTCZ0dHTAYDBQsjsY6d2wYQMKCwvx5Zdfuu01EtjtdrS1taGzsxNZWVk00UT2cNI7T16X4x7ujnF2drsd586dg16vx80334yXX34ZH330EbZv3+7yY/UF0oP8l7/8BampqU7369GjR3HdddchLi4OKpUK8+fPx+HDh8fkvEaKgIAAKiV2dO/m8/lgMpkwGAzYsmULqqur8cwzzyAtLQ3p6ekwmUxUETWU5Ayfz3dSTHh4eMBsNsPPzw+FhYV9Pqa1tRVhYWFgMpnw8PBAc3Oz29rdesJoNKK4uBjFxcWorKzEokWLIJVKe+1hjhMc+Hz+uOztBDwejxZzhhOnEPJvMpmg1WrR2tqKqqoqSKVShIaG4s4770RsbCw++OADlJSU0IkcpNBETMCINFwkEtG2R6PRCIVCgZqaGoSHh9PE9pXUs/+/iDEnybfccgslhQcPHuyVrUtOTsbkyZPx8MMPj9k5LV68GE8++SRSU1Nx5MgRZGdnu4Ugy+VySox7mhtYLBYn2ZZj1tUxkBgLHDlyBFFRUdi4cSP+/Oc/9/q9zWajgUxPcDgceHp60rEtIpEICQkJKCwspMQjOjoa119/Pa6++moqJQe6X+eRI0fw/fffu931LywsjBK2wsJCt2e5d+7ciSeffBJA9z1wpZJkYibV1dU15MBPoVAgOjqa9h/X19ejpKRk0MezWCxIJBJIJBJwuVzYbDZYrVY6zoxUkywWC3Q63ZACFE9PT0yZMgWVlZXYsGGDU8VLKBTSjdUxo082O7vdjuLiYjQ2NtLeRBaLhdjY2AHnGhMMJ+HD5XIRFRVFJdYmk4kmjlJSUmAwGCAWi9Ha2gqbzQadTufUg9UXrFYrfvzxR2RkZGDv3r0oKCjo06SOwWBAIBA49YKSDDuRm5I+z87OzgFfl91uR0lJCbq6uqhBSmxsLGpra1FSUjJghv+3QpJnzZpFFStpaWkuc8/vDxUVFfD09IRQKERkZCQuXbrktgTr4cOHcfz4cSxatAgrV66kZPmqq67CVVddhcLCQuzbtw8nT56E2WwGn8+n46oIqqur0djYCK1WO6xjL126FJGRkXRdHSsQ4z+ixiotLe2lBmOxWFAqlVAqlbDZbGhra6NtUq6UwNvtduTk5IDD4aCsrAyrV69GZGQkNm/ePCYqOEIUH3jggV69x1999RVef/11AN3KsF9//dUtyQJXwbFHlNyjMpkM8fHxdESYzWaD0WjETz/9hJtuugmLFi3CxYsXceHCBfj4+KCrq8tpTWMwGJBIJFAoFHQvc4x5gO5e2+bm5n57koFuAqrVasFkMqFQKMbMb6AneDweJYY91xTH600qlY4rSXYsPLkikdDR0QEOh4OYmBh8/PHH0Ol0mDFjRr8mr8T0i7Rqmkwm8Pl8NDQ0oLCwEElJSbDb7QgODh7QWPN3jD/GlCTL5XLceOONALovou+//97p91wuF4888gi++OKLMekDFggEWLduHWbNmoVvv/0WpaWlKC4udmnmnclkwtfXF2q1ute4FdLP1NTUBI1G02/AaLPZhtyf5Sr85z//QVhY2LAfZzabUV9fj/r6enh5eSE8PBxcLhcJCQm47rrrMG3atF69GFarFYcPH8b333/vFhliT3h7e8PX1xdAtxHKWFxrJ0+exD333AOlUolJkyYhICDArVU8d4HIXoeanfXx8UFkZCQYDAYdr+VoyNQTAoEAfn5+UCgUvVoPCIipRk+Q7G9zczMaGhp6JT6mTJmCJ598Ejt27MDHH3/ca/Pk8/mU8Dlu+GSzJ7387e3tyMrKgkwmQ0REBOx2O0JCQiCVSpGbm9vvfewYNPQMlByhVCoRFhYGNpsNnU7n1INMlBoikcjpOTo7O50ctwdCSUkJJk2ahIceegjvvvsu3nrrLRQWFkKlUtG+rJ6u1yaTqV/XUrPZjM7OTtTX11Mn8J4gs8djYmIgFArh5+cHPp+P3NzcfhNURLpnNBondHA9GBYtWkS///HHH91+PJvNRgMxkmy5fPmy245nNpvx3//+F7/88gsWLlyIW2+9lZLlyMhIREZG4oEHHsDJkydRVVVFKydVVVWorKwc8Wd77NgxpKWljXklhslk9jrnrq4udHV1oby8nMrIlUolRCIRlX56enrSJGF1dbXLVFIWiwU5OTngcrl47733cPPNN+O9997Dq6++2mcl39X45JNP8OGHHyIpKclpRnteXh4uXbqElJQUeHt7Y+HCheM2IWQocCTJxKiVEGRSLSRxWH19PT744AOIxWKEhoYiOTkZK1euhMViwdmzZ3Hq1CnU19cjNDQUBoOhzxnHhHAbjUbU19cPWhhobGxESEgIuFwuiouLx2Uk3lBJskQiGVejRVIA6UsWPhIIBAKsXbsW77zzDvLy8sDn86FWq+l14QiDwYDW1lYYDAZ0dXXBYDBQw02r1YqQkBD4+vqirKzMqX3td4wAvzXjrltvvZUGWvv27evl1rxq1So6wN3dCA0NxV//+lfo9Xp8/PHH6OrqQm1trZNZzGjA4XCgVquhUqnoeIrS0lKcPHkSzc3NaG5uHrIz5lhXkskx+5P+DBXNzc1QKBT44x//iKuuugo8Hg96vZ4upp2dnTh8+DD++9//jgk5BroXu4iICADdgY27qzoEVqsVO3fuxPXXXw+lUokVK1bg3XffHZNjuwocDgf19fVgMplDMu0icmSgm2Rdvny5354rhUIBtVpNg2tHWCwWGAwGGqSQ3sSe9wSXywWXy4VCoUBQUBDy8vJoAuT666/Hfffdh/fee69fQzjSQuDY7wh0XydmsxkcDgdBQUGUcLS3tyMtLQ3R0dEQiUTU1bO/a8oxiHAcz+YIoVCI6OhoMBgMSjwJQZbL5YiKiqKu8473jNVqpec+FJhMJrz33nvIy8vD3//+d5w+fbrf98Vut9Ngg7w3xHkY6L4uPDw84OHhAaPRiJqaGtTX1/eqmGm1WqSlpSEyMhLe3t7w8PBAUlISsrOz+6yukeSgj4+PS0dVjSUSEhKQmJiI6upqNDU1jZm5UkdHB8rLyxESEgIPDw/4+/u7ZK75QDCbzfj5559x8OBBzJs3D0uWLEFoaCiA7vv7rrvuAoPBQGFhIXbs2IGKiopRKXhIJXes0Zc7viOI03hlZSWdhUu+nnnmGbzyyitQqVRoaWlBVVWVS16DXq9HTk4OEhMTsXXrVkybNg2vvfYavvrqq37n+7oKbW1t2Lp1Kx555BGsW7fOiTx98803SElJAQDcfvvtOHz4sNtUDaOFh4cHrFYrWCwWysrKwGAwqGqJyOaJbJa0pznGb0wmE7GxsZgxYwZWr16NgIAAfP7553T/6OjooNcsUQcNByQZxGKxxk3OTEiyxWLp9TkaDAa6L4/HiDRHkP2EwWDQ8x0NVq9ejdraWtoywGQy0dLSQo04HRMegx1r2rRp4PF4sNlsVHH5OyYuxowke3h4IDo6msojf/jhB6ffBwYGYtmyZX3Ke12N6dOn48knn8TOnTtRVVUFFosFjUbjknmDfD4fAQEB8PHxcQriiSt1amrqsJ+TBKV9gQSrfD4fdrvdaZ7ceIHNZmPmzJlYsmQJYmNj6egcoJukFhUV4fvvv8epU6fG9FyZTCbCw8Mp0crLyxtTM5HDhw/j7rvvhkAgwNy5c7F169YxN60aDaRSKVUBDBZwe3l5UYKs0+mQnZ3dq3IrEokgl8vh6+tLN1+ge4NrampCe3s7Ojs7+w0GSH8vl8uFUCiESCSCTCaDXC6H2WxGUlIScnNzsXjxYlx//fV4/vnnBzQyIgFPT0Jms9lQUVFBiV1KSgpaW1thMpmoVE4mk0EkEiEgIKBf6ahj5ai/ii8x1SNzu4VCIW0NIPMbmUxmrwosOefhVBdYLBba29vx6aef4qGHHgKbzcbXX38NrVYLnU5HM+D93SNsNptKCEnVjMfj0X7Tzs5ONDU1obOzk5J3m82G/Px8mEwm+Pv7QyKRIDY2tl/JWXt7OyQSSZ+VmCsBN998M4BuV/hvv/12TI9dVVVFJxgEBQXR+8ndMJvNOHjwIA4ePIioqCgsX74cS5YsAYPBgN1uh6+vLx5++GHcdtttOHDgAA4ePOjWvumhgDjo8ng8OiKqv0ovqaQNBXq9HlVVVaiqqkJAQABtDWGxWJQ4d3R0oKqqqlfRYLhob29HcXExIiIicP78eZw7dw733XcfgoOD8f7777tVjbFv3z7Mnz8ft956q9N1XlxcjNTUVEyfPh1msxnz588fkyLISBAdHQ0mk4mmpiZ0dHTQ3lqgO1E6mMTZZrPh8uXLuHz5MmJjY7F+/XqsXr0aDz30kEvUDo77ICk4jCXITGc2m037dh1hNBrp/iMWi8f03HpCp9Ohq6sLTCYTAoFgVOueSqXCdddd5zRpx2azDavXmSA8PBzTpk2jifTfK8mjhAVDqySPQog7ZiR5xYoViIiIgFarxe7du3tJXB955BH8/PPPbjVQAoBly5bh7rvvxubNm9HS0gI/Pz8qTxuNfIXFYiEoKAh+fn6UENrtdjoQPSwsbEhSyL7Q1dXltOj07H/S6XRO0tSmpiYUFhaOuUTR19cXCxcuxHXXXUd7VwHQTGxRUREyMjJQU1ODjIyMMSfzYWFhkMlkdB7yWG8yRqMR+/fvx8qVK8Fms3HjjTdi69atY3oOo4EjURnKptPV1QUPDw+0tbUhODiY3hc8Hg9CodAp8aPVamE2m1FTUwOdTudErPqD3W6HxWKhgaejJJnMSv3b3/4GqVSKDRs2DCjzBkA3fSaT2ctQo6GhAd7e3gBAzTgc+57IKI7a2tp+e6Acr7f+pMtEWmw0GsHn850y8sQMJDMzs1eAQnp2h9N/FR4eDoFAgObmZjz33HNYu3Yt5s+fj08++WRIj7dYLGhra0NbWxsqKyshk8mgVqtpwkAsFkOlUsFut0On08FsNsNms+HGG2/Ef//7X7BYLFqV6Q/t7e10XjSHwxn3BOBwEBAQQKtojY2NY+o8TJCfn4+EhARwuVzExsYiLS1tTN/DwsJCHDp0CFlZWZg8eTIiIiJoAsjDwwN33nknVq1ahdTUVBw4cACZmZljLiP19fVFeHg4XZ/IftufW7VEIhlR0C0QCFBXV4dz585BpVJBrVaDy+VCKpUiLi6OJuqH25vtiLq6Onh7e0Mmk8FsNmPDhg3429/+hk2bNuG1115zW5+y3W7H+++/jzfeeAPHjx93Wmu/+eYbhIaGwsfHB3fccQeOHDni9tFkw4WjGzJZ9202G70WgoODIZVK0dzcjI6OjkGrwDabDdu2bcMTTzyBuLg4nD17dtTnaLfb6YSE8ZBaczgcp8ppz3XEaDRS9c94k2S9Xg+RSDToDOqhYMGCBTh//vyIpnk4gsVi4bHHHsN3332H2267DUC3R8rvmNgYEw2vVCrF9ddfD6D7Rtu3b5/T71NSUqBWq92aaWcwGHjwwQdx66234tlnn0V2djZ1qa2trR1Vf5BKpcK0adPg7+9P+5Wqqqpw7tw5FBQUQKvVoqmpiQbZw0Vrayv8/PzoPMjk5GRqMQ/8n0kBg8GgDnv99XO6GmKxGIsXL8Ybb7yBjz/+GCtXrnQiyFVVVfjPf/6DP/zhD9i0aRMqKyvBZDIRHR09pn3WPj4+UKlUYDKZdHbdeGDv3r00QFiyZAntnbkS4EjYBtt0yOZkMpnoqC2lUkmrgoQg2+12tLa2orS0FJcuXcL8+fPx8ccf01FMI0FnZydycnKwYMEChIaG4o033uiXIBNXdh8fH7S3t9ONPyYmxokEW61WZGRkICcnh84oJ58jkSLX19fT6mtfGEpPss1mQ05ODnJzc6HVaqk8T6PRoKKiApmZmb2C6IiICNqj3dDQAKlUCpFI1Kd0nYDBYNAsdk1NDc6fP4+//vWvmDp1Ku64445+HzcQ2tvbkZubi7S0NFRXV9P3klwLcrkccrkcS5cuhVqtpgqZnl4NPZ+TwHFduRJApjgAwO7du8dlBI7ZbEZpaSkdaRIdHT2mxycGdzqdDlu2bMEf//hHbNq0CefOnaOBPpPJxMyZM/H3v/8dW7ZswerVqxEYGDhm5+jh4QEWi0XXJLIvEbfquLg4zJw5E7GxsbSXfiSVb6VSiaamJlgsFqf4gBBXuVyO5ORkREREjDihDoAq4shYoaeffhpWq5WOdnQXSktLceTIkV7rR0VFBe3x9fDwwLXXXuu2cxgpFAoFmEwm3bMISktLqZTW29sbsbGxmD59OmbOnImkpCSEh4dDpVJBKpU6xTPk+yNHjlBC5AoQV+yxbr8D4KT26o8kk8T2eJNkJpNJ1VWjKRYxGAxce+21TrOQR4pbb70VALBt2zbadkYShv9r2LRpE23jIl95eXnjfVp9Ykwqyddffz2tnBw4cKCX9OTmm2/Gnj173GZnz+Vy8dRTTyEgIABPPfUUGhoaEB8fDwaDAYvFgsrKyhE9r0AgQFRUFK2w2e121NfXo7y8vNcC0tjYOCJphUKhAI/HQ3JystPGTNywW1tb0dXVBYvFgsTEREgkEgiFwhFnavl8PhQKBfh8Pg0cyILf3t6OtrY2GAwGpKSkYP78+Zg2bVovKbjVasWZM2ewb98+p1EKQHdlIyYmBkwmE2FhYaPuex4KRCKRUx+yK2T1I0VbWxuOHz+Oa6+9FiKRCNdee22vpNFEhSNJHkw+1tTURAkyqbySCinQvaGSHi2bzQYOh4Onn34aarUazzzzzKgNZ2JiYjBjxgx8/PHHA94LcXFxAEDnIRYVFSEmJgY8Hg8xMTGoqKhwuu9aWlp6ySKHmtk3GAx01NRAQbDNZuvzOD3B4XAQERFByXBLSwvYbDZiYmLQ1dUFiUSC9PT0PhMaQqGQBlqkt7mxsRGvvvoq/vnPf+LcuXM0sB0ujEYjysrKUFZWBoFAAJlMBqFQSF+z2WyGXq9HXV0durq6BszQO15nMpls3FxdhwupVIp58+YB6FZJuCLIGik0Gg3tTybSa3crtoBu0ufn5we9Xo+Ojg76OaenpyM9PR2enp5YtGgRFi1aRA0BPTw8cMstt+CWW25BaWkpjh49iuPHj0Ov19MkC5fLpW1bxO2eSMlHUmHjcDjUVCc7OxtdXV00qUPUWkwmE15eXoiOjoZYLIZMJhv2fNqec8ntdjsaGhrQ0NAAlUqF4OBgcDgcqFQqKJVK6qQ/XHR1daGhoQE+Pj7w9/dHbW0tXnrpJTz88MPYvHkzXnzxRbd5cezcuRMffvghTQgQfP/995g+fTqA7uTRRJNckwKGh4cHJk2aRNd0jUaD1NRU+Pn5gcFg0OIDm82GTCbrlbgzGAwwm82QSqWw2+04duwYZs+ejfDw8FHvaT1ds8caQyHJJBE4VkWa/uBo7DkaZcbkyZNht9tHPY42MDAQK1euxF//+ldYrVY0NzdTRej/Ki5fvowFCxbQ/4+IswzVuGuiy62vu+46AN03+e7du51+Fx4ejoiICLz66qtuObZUKsXzzz8Ps9mMv/zlLzR4JIFlRUXFiD4cX19fBAcHU/JP+oH6uyGHU0lmMBjUEVsoFMJqtUIqldI5rc3NzU5u2Gw2G4mJiRCJRLDZbKipqRmylJjBYNCB5x4eHgNWdRITE5GcnIyEhAQ6N9ARFRUVOHr0KH799dd++zXa2trQ0NAAtVoNX19f1NXVubVPjozoYTKZsFgsA7rpjhV27dpFs+kLFy68YkjycOXW7e3tQ3IO53A4+Pvf/w4mk4m//vWv/Zp7DQf33XcfvvvuOzQ0NPRrIkJmGvL5fFgsFsjlcjCZTBQWFtJ+2bi4OFy8eHHA+2mogbnjc/TnMTAcREdHQ6FQQKvVwmAwoK2tjc7+VqlU6OrqglKp7POzIu8JGeVEUFZWhl27duGee+7Biy++OOpzJAY3jmhubkZxcfGQTBId15ErqZI8b948+hkfPHjQbfPehwoy69PT0xNBQUHo6Ohwux9CREQENc3piyC0tLTg22+/xfbt2zFt2jTMnz8fU6ZMoUnZ0NBQREZG4oknnkBZWRnS0tKQl5fX735tsVig0WjQ2tqKlpaWIcvKy8rKEB8fDzabjbi4OOTk5KCtrY0mF4hbtbe3N62Kh4WFITg4mDpVDyXBT+ZW94W6ujo6Ws7Pzw9sNhvR0dGQSCQjilGIcy6TyURgYCCKi4vx/vvvY+XKlXjttdfw+uuvIy0tbVjPORQ0NDQgNTUVy5cvx6effkp/XlxcjMuXLyM+Ph5qtRqxsbETagyio6qGw+HgxhtvxN69ewGAFlIqKyvB5XIhEoloO4lIJIJAIKAJR+IP09nZCbFYjNraWqSmpuLqq692KUke62knwP+pn2w2G+x2e78k2W6399tONFYgSTebzTaqtrprrrkGx48fH5W8ncFg4LHHHsOePXtogaalpQXBwcHU12M8DAjHGxaLZVwd0IcKt5PkpKQkSg7T0tJ6uRjffPPNOHTokEsC455QKpV45ZVXUFBQgHfeeYfe1BaLBRUVFRCJRMN2s2az2YiMjISXlxfNJJeUlAzar9DU1EQX1IFuWh8fHwQFBTlJPXNzc2E2m5Gamtorc83n8xEfH08zd+Xl5UOqjLPZbOq+3XNBI70vFosFEokEycnJmDFjBvz9/Z0ymDweDzU1NThy5AiOHj065Ow02cC5XC7UavWAZkqjRVRUFCX++fn54x6sAt3JhMLCQkRGRiI0NBShoaEjrtqNJYYjtx4OlixZApFIhKeeesol4xqEQiHKy8tx/Phx+Pn59Vu1JdJDnU6Huro6qNVqSCQSVFVVIT8/H7NmzYLBYIBQKHRJ//pQK8lDAammyeVyGsAlJyfT19PU1ASlUglPT88+ry3Hqm7PpNHp06cxY8aMUZ3fQDAajUNuM3BMslxJs5IXLlxIv58oVbOCggIkJyeDz+cjOjoaaWlpblNvKRQKuu4WFxcPWHG1Wq04e/Yszp49C6lUimuuuQbXXnstkpKS6D4YHR2N6OhodHV14fz58zh//jwqKyupNwCbzQabzaZeHcQHo6qqatDYoqOjA1lZWUhMTKREubCwkBJaR7dqg8FAkzUsFovuobW1taiqqhqQmHt7eyMjI2PA96G0tBT19fWIioqie7SXlxfy8vKGZf5kMplQUVEBLpfrlGj64Ycf0NjYiI0bN+KDDz7Ar7/+OuTnHCp27tyJV155Bdu2bXMqGvzyyy+Ij48H0H1/TESSbLPZ8PXXX+Oee+5Bampqr3iVGFY5JpjIXHlCnlksFrq6umC1WtHW1obTp09jzZo1+OKLL0Z1jkSJxePxIBaLx2wiCAGRehPC2Jdxl81moxX38fSQIJyjubl5VAR3ypQpeO2110Z1LsuXL4dIJMK2bdvozxzjJ7FY/D9JkiMiIlBTUwODwYCzZ89i48aNwx+Lavr/X4NhIo+AcpwRefDgQaff+fj4YPr06XjooYdcflyBQIBNmzYhPT0dH3zwgdPv9Hr9iORmfD4fiYmJdOM2m83Izs4eEvEi89KUSmWfJJaMj3GUibS1taGmpgYnTpzo8zllMhliY2NpwFtaWjqo6zCHw0FAQAB8fX1ht9vpY41GI1pbW9HW1oaOjg6kpKTgxhtvxOTJkykxbmtro8FIcXExLly4gIyMDBQWFg4ryWGz2VBXV4egoCB4eXm5bTH19/encpaqqqpxd1B1xKFDh2jVb+HChfjoo4/G+YwGx3Dk1kOFQCDAbbfdhs2bN7uEIAPdQe0///lP6q7dn3KABPFarRYlJSUQCASQSCQICgpCbm4udYp3TFiNBo6vb7SVZLvdDpFIhLq6OjAYDPj4+IDP59NRW3K5HEqlst9zJ+9JX71tZWVlTk6erobJZBoySb4SK8lRUVEICAgA0J3gdNVYwdGCKGkmTZoEDoeD2NhYZGRkuMUEyM/PD0D3XjucdbejowP79+9HaWkpQkNDMXPmTCQmJlLXaZvNhqSkJCQlJaGurg4HDx7EkSNHYLVaqRpKLBbTnnuRSASj0Yjy8vIBA9Guri5kZmYiMTERHA4H0dHRNNnmCOJeTOa5E58Lf39/qFQqVFdXo7q6us+kQE+5dX/Q6XTIyMhAYGAgAgMDwePxkJSUhKKiomGZB/UXcJ44cQIajQbPPfccWlpa+nWWHymKi4tRXFyMJUuWYMeOHfTnZ86cwUMPPQSxWIyrr74aH3/8sduMxIYLx1a41NRUyGQyrFu3Dps2bRr0scSYkCQneyI9PR1isdglkuuOjg4olcpxcfsnztZk7xhIbk3GMY4HSRaLxbDb7bDZbKPynomOjkZbW9uoiji+vr648847sWnTJqf3wjFeHu/+7fHAuXPncO+996KgoAAqlQqbNm3CyZMnER8f75aC6Wjg1u5/iURC+1Da29tx/vx5p98vX74cZ8+edXlGjMFgYMOGDWhubnYZ+eDz+TSzbbfbUVlZiczMzGFVJvuSXAsEAiQlJSEuLo4S5I6ODmRmZiI7O7vfAMPHx4cafJCxKgMRZAaDgYCAAGowxmazYTab0dDQgIyMDJw7dw5arRZLly7FZ599ho0bNyI5OdmpcpydnY3Nmzdj+fLleOGFF5CdnQ2xWIzExMRh96DU1dXBbreDyWTCx8dnWI8dCmQyGSVJRDY3kXDixAlaxZkzZ86oK4tjgeHKrYeCa6+9FtXV1W6R/hEC2B9JJgoK8jk0NjaCw+FALBYjKCiIzk12lSTIZDJRQjJauRzpwxQIBFCpVPDw8KAtEAaDgb4mMrajJwYiye4Gi8UasnzUkSRfKZVkxypyz8TweMPRk0EikSAsLMzlx+ByubSdaSQJgri4OCiVSmg0Gnz55ZdYvnw5/vznP+PQoUNO+61KpcLq1avxxRdfYP369fDy8qJ7WXl5ObRaLYRCIRQKBSZPnozY2NgBkzNarRbp6emUuPn7+yMqKqrPe0Sv16OkpATnz59HbW0t7HY7nXAxbdq0Pv1HvL29hxzr2O12VFRUIDs7GyaTCQwGA5GRkfD19R3S4wdDVlYWPvzwQ2zcuJEmNFyJnTt3YunSpU77mtlsppVrLpeLOXPmuPy4IwWR5wLdRqmff/45goODMXv27FE/t9lsxqlTp7B06dJRPxdJTkskkjHvS+ZyuWCxWAOSZLK/EaPA8YCPjw+EQiHMZvOoWkrmz5+PvLy8URl/PfbYYzh8+HAvUypHIjjeM6XHAwcOHMAPP/yA7OxsHDx4EEuWLIFcLnepyZ2r4NYIadasWbRiQrK9BAKBANdddx1++uknlx/32muvhb+/P9544w2X9J/yeDyazSYubOXl5cPOwPc07/L19UVKSgqtkGi1WuTk5CAjI2PAXs7g4GBERUWBx+NBq9UiMzNzwIyZTCZDSkoKQkJCwGKxYLfbUVtbi6ysLJSVlSE5ORmvvvoqPvroI6xYscKpYtPY2IhvvvkGDzzwAJ555hkcPnwYOp0ODQ0NKCoqog610dHRw1q0TSYTXfAdq+euAIfDQUxMDBgMBkwmE/Ly8sZlZMJA0Ov1OHXqFIDu1z9r1qxxPqPB4Q65dUxMDC5evOiS5+oJm81G5/32BbKJE0JJrke73U4Dx7q6OpeNK3GsJLuip6y6uhp2u53KTIH/ew2OMtq+ghUyNms82g+GU2G40tyt+Xw+rrnmGgDd9/jp06fH+Yx6o66ujiZ+/Pz8Rjx1oT8IhUK6FwzXaC0gIIASlvr6ehQWFsJmsyE7OxvvvPMO7rnnHmzevBmZmZn0MUwmE9OnT8emTZvw2WefYeXKldDr9UhLS0NRURG9F7y8vDBlypRebUOOMBgMSE9PR0tLC4xGI3x8fJCUlNRvEtNkMlFVVWNjI1VnxcTEOLlUEznucAsCGo0GaWlptN0jIiLCZZ/X0aNHceTIEbeoRi5evIjOzk56LxA4Jo3mzp3r8uOOFI4J4I6ODuh0Onz88cd48MEHXVLp2759O2bNmgV/f/9RPQ9Z34kT91hCIBDQogzQfyWZ3AOuUmANFyTGbm1tHXHcFxERgXnz5uHAgQMjPo/FixfD29sbX375Za/fOZLksf4cJyLa29tRWFiI8PDw4T2QzEke7GsUIZxbSfKkSZPo94QQEEydOhX19fWjlp/0heuuuw7btm1ziZSHy+VSibXdbkd+fv6IHVYJSeZyuUhISEBkZCSMRiMsFguKiopw6dKlQR1tg4OD6XgMg8GAy5cv90tYOBwOoqKikJSURCu9LS0tuHDhAqxWK+677z58+eWXePLJJ6nLL9AdQJ86dQrPPfccHnjgAWzfvr1PEq7RaFBUVASgWzIy3Iw0IQ2urKIyGAzExsaCy+XCbrfTfu6JCMeAgZjbTWQ4kmRXSWIiIyPd5nDO5XJ7zWN2BKkQkeSdwWCAVquFTCYDj8eDzWYbtH1hOHCsJLvC2ESn06GlpQVMJpMSC1J5dST2fRFyu90OoVDo5HI9VuByuUPuhb3SKslXX301DQ6PHz/utp7f0aKoqIj2i0ZERLjUjdbx2h5OCwWXy0VwcDCA7gC3rykERqMRx48fx3PPPYcHH3wQ33//vZPaysvLC6tWrcKnn36KF154ASEhIUhLS0NZWRmd4RoaGuqUnO4Jq9WKnJwc+rwSiQSJiYkDJrYMBgPy8/ORnp6Orq4u2Gw2SsoVCgWUSiUMBsOI1k2TyURVawwGA1FRUSOalNEXvv32W4SGhkKtVrvk+Rxx5MiRXiS5oqKCjuOLiooaNyLVE+RaIO7UQLc3Q2FhIf74xz+O+vmbmppw+PBh/OEPfxjV82i1Wqd53WMFUhkmRnxA3yQZ6L5/uFzuuFRIpVIpXX9GqlAVCoXYsGEDvv322xG7wHt6euK+++7Dv//97z73AMeY/X+xktwTIpEIYWFhqKurG94Dh0KQh+qA3Q/cGh0lJCQA+L+eP0fMmjXLbVn2v/71ry4xpGAwGIiLi4NAIIDdbkdhYeGopOFNTU1Qq9WYPHkyDWp1Oh0uXrw4pIvD19eXEmSNRoOMjIx+gzCpVIqUlBQqZTYajSgsLIRarcYrr7yCd955BzfccINTFquqqgqfffYZVq9ejTfeeMMpW98fGhsb0dbWRt2BhwMSQLnSCTE4OJhueGVlZS7rnXUH8vLyaMCQkJDgMimdu0Ay6jqdziUKDQ6HAx8fH7dJ4QeTWxM4VpWIG7PBYEB5ebnL+qSB7qCCEHJXBYclJSVUlcFkMunm6/ia+sqmO74nYy3bI60eQwEhHMCVQZIdk10TTWrtCJvNhtzcXFitVjoBwFWOuWQ9N5vNw6rkeHh40McMJXHW0NCAr7/+Gn/84x/x0ksv4fz58/R4DAYDkydPxtNPP43PP/8cCxYsQEVFBU1CC4VCJCYmDjiPuaSkhMYtIpEIsbGxg94rXV1dSE9PR3l5OdhsNjgcDhISEhATEzOq2IEQZaPRCAaDgejoaJdUoHQ6He68885+58iPBmfOnEFSUlKv8yRxBZPJpEZe4w1SSe4ZL3zwwQe4+uqraSw7Gnz33XeIiorCihUrRvwcNpuNJlrcOfO6JwiRcyTJPfdGR2Nc4to81iAqC5PJ1O+ElcGwfv16VFdXj0rlum7dOpw+fbpfo77/9Z7kf/7zn5g9ezaCgoIwY8YM/PTTT7BarU7mZhMFbiPJISEh9CbJyspy2ix5PB5SUlJ6VZddCVfIa4nbLdBtRjHa3kSNRkNnsNrtdpSWliInJ2dIgbhCoaCzfoksu79eCZVKhcTERFpNbW5uRmBgIN544w2sW7fOSdJgMplw5MgRbNiwAY8++ih27949bCltfX09WCwWPD09hxX8ExnocAgXGWnRF7y8vKhhTnNzs0urgO7C4cOH6fcpKSnjeCaDgxhducpshZBYd1X6SUDb31rQ18/Ly8uRmpqKCxcuuPz6MZlMNMBwFUk2Go3IyMjAsWPHcPnyZfpeDkaSHX82lpVkohoZTvKBBDsTXW4tFosRHR0NoDvh6A6VlCuh1+tRUFAAoJs0RkVF9fl3EolkWAE5Wc+JyeNQ4evrCy6Xi5aWlmFdHzabDefPn8dLL72E++67D1u3bnXaq2UyGVasWIH33nsPCxcuRHt7OyWbwcHBiIuL6zdBUFNTQ402FQoFNVscCHa7HdXV1cjIyKDtDImJiaOa1wp03+uZmZkwm820ouyKBJe7WpHq6+tRWVmJadOmOf3cMfmelJTklmMPBwwGg8Z5PdvcWlpa8NVXX2HdunWjNlvUaDR44YUXsGrVKtx6660j/uxIskWhUIxZ3y8hcsQQC+i9b5O9zWKxgMlkQiAQjPmoKtJ2NBK1p0AgwLPPPovQ0FC89dZbIz6HuXPnIjQ0FJ999lm/f9PT3fp/Df7+/ti2bRsKCgrw/fffo6WlBdOnTx/+53YlV5IdF7+e7olTpkxBQ0PDhCYxAoHASfo1bBlAD3C5XMhkMuoqPZjRliMcs9hGoxHZ2dn9EuTIyEhERESAyWSCz+cjLi4Ozz//PO655x6nSkxxcTE++OAD/OEPf8A777wzKgc/x96PofbcOEpEB5OYEwQHB2Pz5s14+OGH+/w9GWflGPxNdDgOqZ8oWfX+QCSZrnYkdVclk2zagwU3jsfX6XTQarWjDmj7gslkovctuT9dAVLZd9xgBiPJju+Jq3quhwIS1A2HBJWUlKCiomLCj8lwrDS6w4jOHSDJRA6HA7lcThNhjpgxYwbef/99J0OygUDWcwaD4WSINBCkUimt5o1mCkFrayt27NiBBx98EM899xxOnjxJr28mk4l58+bhH//4BxYvXkz3Q09PTzoaqy+Ul5dT0u3j4zNg9dkRnZ2dyMjIgF6vh5eXF3XcHg0MBgNNvojF4lH3uLobp06d6uW3kZ2dTdekxMTE8TgtJxA3dKDvqQ0///wzjEYjFi9ePOpjlZWV4dlnn0V8fDzeffdd3HjjjcNuU2toaKCjlsZKfUaSCI4eFj2LG2Rvs1gsYLFYYDAYY0oABQIBVbEMNaYk8PPzw+bNm8HhcPDkk0+OWIEok8nw4IMP4oMPPhgwhujq6kJra+uw3Op/S7jjjjugVqvB5/MREBCAO+64Y8KOQXXbCKjY2Fj6fU/Zrjul1q6Cv78/mEwmrFbrqHsmORwOEhMTodFoIBQK0dTUNGTpFYvFopluq9WKy5cv9xtghoSEwNfXF0qlEklJSUhISHDK5Nntdpw5cwY//vijS6scVqsV9fX1dCRGY2PjoIuMh4cHPbfBgiKZTIabb74ZN9xwA3bt2oXvvvuu198wGAxYrVZwOBw6o/BKQFlZGXQ6HYRC4YQmyQwGgwaRVwpJHqznnWTCx8pZ3FFuTYxX3GWc5fia+iLBJJiwWCxjamrnOJ95OI8JCgoC0J0wdEcCwxVwlGRmZ2eP45kMD83NzYiMjIROp+vzXjx48CCam5uxbt06zJkzB1u3bh0wqWo0GqHVaiESiYbk6Eycm8ljXTXtIjMzE5mZmZBKpViyZAmWLl1Kg/2UlBSkpKQgNzcX5eXlyMvLQ3x8PNLT0/vcOwoLC8Hj8SCXyxEcHEyD3MFgMpmQlZWFRx55BNnZ2YiOjobNZht2EO8IMiXD09MTAQEBqKmpcUn7iztw5swZ3HnnnRAIBNR8jDish4eHIyQkBHw+f1wMBAl6mnb1hN1ux9atW/HYY4/h0KFDo/YZKC4uxt///ncsXLgQM2bMwH333Udl1OSLOEUTIyzyZbPZYDAYwGazYTQaoVKpYLVa0dTU5Db/AxaLRRNKA+39ZE23Wq1UneTp6TmgCa0rQT5Hu90+ZJIrEolw66234sYbb8SePXuwdevWUe2HDz/8MDIzM3Hu3LkB/06n09EJAO6Y7vI7XAe3kWSSHbNYLL36XRISErBnzx53HdolMJvNYLPZ0Gg0o+5LDAsLo5b0RUVFw8quhYWFUXKSm5vbb4Do6+uLOXPm4JprrkFoaCg6OzvR0NAAHx8fWCwWHDlyBD/99JPbZnaWlZXBy8sLXC4XkZGRSEtL63fj5vF4VPKt1+v7fU0KhQK33HILFi9ejMzMTPzlL3/p10jBbrfDbDZDq9VCqVSiubnZ5aPF3AFiLjZlyhTIZDKo1Wq39IeNFo4VJleRFHeTM7Jp99fzrtVqweVyx0xu3LOSLBaLRxUsDwQul0tJT1/BE3lPXNlzPdTzslqtwwrqe85Knqgk2dH8MDc3dxzPZOgg85J1Oh3sdnu/10NaWhoeffRR3Hrrrfj73/+OwsJCbNu2DTk5OX3+fVNTE0QiETw9PeHj4zNgq1JgYCBVqRQXF7s8wdnR0YHvvvsOP/30ExYuXIgVK1bAy8sLdrsd/v7+mDx5MpYsWYKTJ0/CbrcjLS2t19pE1unJkydDIBAgMjISFy9eHJIKw2g0QiQSoby8nMqkz58/PyoFR1VVFQICAlBbWws2mz3m9/FQUVtbi5aWFkRFRTn1Z5aXl9MYQKVSjdggyRVwbOPoj9BduHABdXV1WL58Ob7//vtRH9NqtWL//v3Yv38/uFwulEolxGIx/eLxeGAwGPSLyWTSf4VCIQIDA5GSkgK5XI677roLQLdyoaamBvn5+cjLy0N+fv6oRiAR+Pr60qkoAz2f431L1mhfX19UVFS4pWjB5/MhEolo4jU0NBQeHh7o6uqCXC6HzWaje43NZqMScKFQCLlcjri4ONx4440oLi4eMLYcKmbMmIHExEQ88sgjg/6tY7LBlaaJ/3Mw/f+vwTAK1b/bSDKRgdTX1zttOL6+vhCJRH06V04kEIMCsVjsZFYwXPD5fJrhqqysxOXLlxEaGjqksTceHh70faypqelzgWKxWJg3bx7WrFkDtVoNi8VCs2harRY7d+7E7t27XbJYDgSr1YqioiLExcXRqmhFRUWvTUckEiE6OpouXn3Jor28vLBy5UosWLAAly5dwoYNG4YkxSgpKYFUKoVIJEJkZCS0Wq3Lq57uwOXLlzFlyhQA3ZLriUiSHc1XSEVgtCBVTD6f75YB8oQcisVizJo1CzabDW1tbSgpKYHZbIbZbB7Q/drVcOxJZjAYbt0ciXO1yWSihFStVtMZknw+HyaTaczdl4VC4bCvn54O1+5K9I0GQqGQzhwuLy93y/XsDsTExFDviry8vAH3Ob1ej6+++go7d+7EsmXL8Le//Q3l5eX47rvveqnFqquroVQqwWQyER4eDgaD0UtayOVyERAQQJ2Vm5ub3ZY0ArrXg71792Lfvn2YM2cOrr76akyZMgVGoxECgQA33XQTFi5ciL1792Lr1q299kyLxYL8/HxMmjQJXC4X4eHhQ2pTUiqV4HA4OHz4MJKSksBkMuHt7T2q69jX1xd6vR5CoXBM2yVGgvz8fERHRzuRZMf2NV9f33ElyYNVkgm+/PJLPPfcc9i3b59L72+TyTSiPX/q1KkQCARobm5GVVUVlEolgoKCEB0djTvuuANBQUFoampCbm4uLl26hIsXL44owUjuz9bWViczrp6JJMfrkMRdbDYbPj4+o16zPT09MWnSJISHhyMgIAD+/v60Etva2gqpVAqxWAwOhwOr1dpv3Ge326HT6dDV1YXU1FS8+uqrLlH9iMVirF27Fp988smQKucGgwF2u93tccDvGD3cEh0qFApaqejZyxsVFYXS0tIJO5aHoL6+HiqVCmw2G/7+/rDb7ZgyZQp+/PHHYT2Pn58feDwe9Ho9KisrUVpa2q9BiiPYbDYiIiKg1WrBYDB6bSJCoRCLFy/G0qVLqbbfbrejs7MTTU1N2LNnDw4ePDimJLGlpQUNDQ3w8vKCWCxGUlIS9Ho9db8WCAS0NwvorrY4bkoRERFYvHgx5s6di9TUVPz5z39GRUXFkI9PHFuTk5OpY+tAFe2JgsuXL9PvExIS8Msvv4zj2fQNx4V8oGuKyWTS6qwjKewLNpsNTU1N8PX1HfFYtYGg0WjopmixWMDj8eDt7Q2z2YzS0lJK1sj5uvs66Utu7S6Qyj95jcTUjsvlUskek8l0e/KsJzw8PJxkqkTGz2AwaOKiJ66EWclkLjvgfD9PZAQHB1MZZVlZ2ZBlkV1dXfj222+xa9cu3HDDDdiwYQNqa2uxZ88epKamwmw209nGkyZNAovFQmRkJPz8/KDRaGCz2SCTySCVSsFgMKDT6cBiscbM6MxqteLo0aM4evQoUlJSsGLFCiQmJtLZritWrMDcuXNx/Phx7Nq1y2kP6uzsRFVVFby9vSGXy6FUKgdVLIWFhaGqqgodHR2or6+Hj48PgoKChk0cEhISoFKpcOrUKept0tjYOOH3t4KCgl6mlI4JE5VKNdan5IShkuScnBzk5+djxYoV2Lp161ic2oCor69HSEgIPDw8kJeXh87OTpSWltLJLkTxEB8fjxUrVuCJJ57A2bNnkZ6ejmPHjg0pBnc0Y62pqaHGhH3Bca8nCWmFQgG1Wj3sa53NZmPSpEmYPHkyJk2aBLVajYKCAhQUFODYsWOorq5GdXW1U7JiypQpEAqFqKmpQUlJCZhMJv1isViw2WxuSwrfe++9KC4uxrFjx4b8GJ1OB5FI9Puc5NGAzEkeDKPoqHMLSXY0IuiZPY6Ojh6VSdRYoaurC42NjfDx8YGfnx+qqqpw11134dChQ8Nq6icyGVI5LS0txfXXXz/o4yIiIsDj8cDlcpGenk43Qk9PTyxfvhyLFy+mixefzweLxUJhYSE+//xznDlzZtx6cgsKCtDU1ITw8HCw2WwIBIJeZjCEpDQ3N8PT0xNz587FtddeC09PT5w8eRKPP/74iE3diGlXbGwshEIhIiMjJ/z1RiqbHA6HmsVNNDh+hn2RZBaLBbVaDT8/P5ogI/JNnU4HjUaDurq6XqS5vr4evr6+biEWFosF9fX1sFgskEql0Gg08PDwgFqthslkciKIIpHI7cZQNpuNBiZEbu0ukI1Xp9OBy+UiOjoadrsdWq0WbW1tEIlE1Pl+LOHh4QG9Xo/o6GiIxWLYbDan96G+vh41NTVOFY8rYVay432bl5c3ficyRHh4eFADqpaWlhGttzqdDjt27MDevXuxePFi3HnnnXjkkUdw6tQpHDlyBPn5+bQPVyKRUCmpI2w2GxobG1FTUzMue9alS5dw6dIlhISE4M4778SiRYvA5XLB5/Nx7bXX4tprr0VaWhp+/PFHWnGqqKiAQqGARCJBREQE2tvbB5Q7h4aGUuWcXq8fcUJu+fLlKCkpoRMcLBbLsJLI44X8/HwqCSZwLJ6MN0l2NGwbTOWyY8cO/O1vf8OOHTvGtY8a+L91kSRce1a39Xo97cv/5ptvoFQqkZKSgqVLl+KOO+7AV199NSipI1VksocP5B/ieP+y2WzU1NRAoVBAIBD0So72h/j4eMydOxezZs2CVqvFxYsX8dVXXyE7O3vQgo9Wq4VQKKTVbiKzdjemTp2KSZMmYcOGDcN6nF6vh0gkGjOH8t8xMriFJDs2ovdVSR7N/LGxBMkYEzlmTk4OFi1ahB07dgz5OchCKhaL4enpidLSUvj6+kIoFPZ70/v5+VEXzKqqKnR1dcHf3x8333wz5s6d6yQP5fF4KCgowKlTp7B3795ROYO6Cq2trbhw4QI8PDygUCiowymZ59rQ0IBp06bh0UcfRUJCAjIzM7Ft2zacO3fOJb1Vzc3NqKmpgVqthre3N9rb20ftTu5OWK1WaDQaKJVKp6z2RMJglWS1Wo3g4GDa5wuAVm95PB4UCgWCgoIoCSLBSF1dnVuDpKKiIqf/JyUl0SpWdXU1nRMrl8vHxD2ZrAekt8wdYLPZlCR3dnZCLBbTvuvc3FyXyeWHAyaTCR8fH0yZMoVW9AHna8lqtcLb2xsKhcLJ+MSxwjlRSbLjfetOybArwOPxaEVIr9ePOoloMBiwa9cu7Nq1C5GRkZg/fz6ef/55dHZ20oqt3W6n0wc4HA46OzvR2to67HFP7kJZWRleeeUVXLhwAXPmzHGqfCYnJyM5ORmFhYX48ccfcfbsWRQWFmLy5Mlgs9mIiYlBdnZ2vwF5aGgosrKywOFwaAFhuBUtb29vJCcn4/PPP6ey/tra2ivCoLKsrAwcDsfJb2MikWRHDEaqcnJyUFNTg4ULF467r45Wq6WSXYlEMqgEvKmpCQcOHMCBAwcwZ84c3HvvvZg+fTrefvvtPgm/SCSi621fcvCB5NYsFgutra3UlFStVvcbmwYGBmLevHmYM2cOuFwuTpw4gU2bNg3bMNcxhlIoFGOikpJIJFi/fj22bNky7NibrHu/k+SJDbeQZEdJnOOFw+VyERISMuErewQ6nQ4tLS3w8vKCv78/9u7di0ceeQQ7d+4c8uZEZNsCgQCxsbGor69Ha2srQkJC+jQ98fLyoptgZ2cneDwennnmGUyfPt3p70wmE06cOIHKykq0traira1tQhBkArvdjpaWFqeAMS4uDkuXLsXVV1+NpqYmHDlyBG+99ZZbFrPS0lJIJBJIpVKEhYWhq6trQo+Q6ezshFKpdOr5mUhwlAT1RZJJhUgsFiMzM5MSZJFIRDctJpNJHdALCgrQ2NiI+vp6er2PBTo7OyGTyWh7Qnt7Ozw8PCCXy1FVVeX245NghMFguE1mJZPJaMa/ra2Nzri12WzjQpC5XC4SExMhFAqhVCrR2dkJnU6HtrY2dHZ2wmAwwGazITQ0FHK5HDweDxwOh1bdexp3TUQMVbI53mAymYiNjQWbzabtKa4kWoWFhSgsLMSnn36KadOmYf78+bj99tuRn5+PI0eO4PTp0+NegesPdrudzjb+9ddf4e/vj6uvvpomdCIjI7Fx40bU1NTQCRGBgYGQyWSIjo7u16wtNDQUJ0+exJQpU8DhcGC324fdg7t06VKkpqZCIBBQZdpEHqHpCKvViuLiYkRHR1OypdVqqXpqvBPDjsaNQzGT/PHHH3HDDTdg7969YzoZoCdsNhu0Wm2fCo3BcPz4caSlpeEvf/kLNm/ejJdffrmXJNpRsTCQ8R5Bz0oy0J3ICQ8Ph0KhgFgspkSezWZj5syZWLJkCcLDw3H27Fm8//77yMjIGPF6VF9fD7VaTf0hLl265PbP55FHHkF+fj6VuA8HJFH2O0keBYY6A3kU3b1uIcmOwZ+jbM7Pzw8Gg+GKcB0mqK6uhpeXFzgcDvLy8mA0GjFr1iycOHFiSI+3WCzIyclBYmIiuFwuVCoVLBYLZs2ahZqaGqcA0MvLC9HR0WAwGAgKCkJ8fDxiYmKcnk+r1eLnn3/G3r17ERoaColE4pIxVe6Cn58f5s6di/nz50MgEODYsWPYuHGj243biBtpSkoKOBwO4uLikJ6ePuZGRUMFCaxZLNaAKoPxwmCV5Lq6OggEAohEIgQGBqK0tNQpScLn8ylBZrFYtD+2vr6+1xxNBoMBgUAAmUxGZ0K6Cj03JiLBJsTS3ZsqOb47Z0gS5YZer4fRaKSv1R3kxNPTE1arFV1dXX32n4tEIoSGhlK5PofDwYULF5yMC4lUXyaTwWg0oq2tzalf7kqQW18pJDkyMpIm4oqLi93mFG6xWHDmzBmcOXMGUqkUc+fOxdKlS7F27VqcOXMGv/76K7KysiZcJbSxsRHe3t7w8PBAcXExdu7ciaSkJNx6661UUq9Wq/HYY4+htbUV58+fR2FhIby8vBAZGYni4mK6XvH5fAQHByM8PBw8Ho+O8SkrKxtWQlsgEGDhwoV47rnn4OXlBaB7Vu5EN+xyRFlZWa/50jqdDjKZbNyNiwabKd8T586dw5o1azBlyhRcuHDBnac2KIxGIzWsGi46Ozvxwgsv4J577sHmzZvx0ksv0cKNQCCgasahjhhzvB4JSa6vr0dQUBAd41deXo5ly5ZR07H9+/fjH//4h0vWIbvdjpKSEiQkJEAoFNLjuQuzZ89GfHw8Hn300RE9vqmpqd/Z7L9j4sBttq4tLS3UsIpgKCYXEw0dHR0wGo2w2Wzw9PTEnj17sHz58iGTZKB7M7hw4QKCgoKo5CguLg6JiYkwmUzQ6/XgcDgQCARISkrC7NmzIRQKnRam1tZW7Nq1C7/88gv0ej0CAwNpsFNSUjKhyF9QUBBmzZqFmTNnQqVS4dKlS/jkk09w8eLFMQ2KTCYT8vLykJCQAC6Xi/j4+FFlKt0Jx8BaKpVOOJI8WE8yMWcDuolMcnIyNW1ra2uDRqNBaWkpNf+QSqUIDQ2Fj48PYmJikJCQALvdTjd8o9EIPp8Ps9ns0r5ZsnmTc3Xs65LL5WPiAk/grqoocf0kr428VlfPgybzba1WK/h8PiwWCx0lZLVaqYs20E3YSaW+pKQEYrEYUqkUXl5ekEqltJrD5XJ7SfuuBOMuR5I8UZ2tg4KCaFW0rq6ul1+Iu9DR0YE9e/Zgz549CAoKwvz58/H444+Dy+Xi3LlzOH36NDIyMiYM6SssLKTJ1cjISJw8eRInT55EcnIyVq5cSefZe3h4YPHixbjhhhuQnp6O06dPQyqVwmQygcvlQigUIioqCm1tbTAYDOjo6EBRUdGwCcGCBQtQWVmJuro6yOVymM3mCS/p7wniU+KI1tZW6pMwnrBYLNDr9WCz2WCxBp8VY7PZcODAASxZsmTcSTIh9QP1Cg8Em82GL7/8ErW1tdi0aRPefPNNnD9/HkFBQWAwGLBYLP0qFnomFBz3NvI+2mw2VFVVITQ0FPPnz8fMmTNRUlKCL7/8spcjvivQ1taGlpYWeHp6IjAwEAaDwS3rnEKhwNq1a/H222+POCkqFAppq8FoJuj8T+NKrSQrFAoq8XOsXlyJJBnoztoGBgbC19cXZ8+exd133z1sAzKr1YrS0lLU1taCw+HgL3/5CwDQzTQlJQUzZsyAl5eXU1WGSLuOHTvmdBORm6ulpWXMgp2BEB4ejpkzZ2LWrFnw8PDAxYsXsX37dly4cGFc5XUajQZFRUWIjIyESCRCTEwMcnJyxlUm1Rd6kuSJ8Jk6Yiju1tnZ2VCpVAgMDKRJHwaDAT8/P9jtdmg0GlRVVSEvLw/R0dGQy+Xo6OiAVCqFSqVCa2sr7WcWiUSwWq3w8vJyKUnmcDjQarU0MOvq6oLBYACfz4evr6/bSTLpQ7Lb7U7eDa4CkZIDoO+bTqejLvksFstlSSKJRAIOhwMOhwMmkwk2m01NjxxhNptRVlYGrVaLyMhIKJVKJCcnQ6vVUtWR3W5HU1MTKioqeknCzWYzJR4T1QmUkGStVjsh3YaJozLQHUiOlZN0T1RUVGDLli3YsmULoqOjMXPmTDz88MOQSCS4cOECTp8+jUuXLo1rn7LJZEJRURE1f5TJZGhvb0daWhrS0tIQGRmJlStX0hYom82GmTNnYsaMGcjIyMDJkydppTg8PBwXL15EVlaWkyJiqGAwGFi6dCm++eYbhIaGgs/n0+TjlYSmpibMmDGj18/lcvmEuKdJEnioZPPgwYO4/fbb4evrO657NZ/Ph1arHXVijhjSPvXUU/jyyy9pPNLTUG+w94d4fDj65mg0Gtx9990ICgrC1q1b8fXXX4/qXAcDGdMmEokQEREBk8nk8lbEP/zhD0hLS3PyzhguelbefyfJExNuIcmOFQtH2dyVSpJJrwOLxUJUVBR+/fVXLF++fES91QaDAceOHcOaNWvQ2dkJX19f/PGPf4SXlxeMRiPdSIlJSGpqai9CR/r2gL4NFcYK0dHRmDVrFmbMmAGxWIzz589jy5YtSEtLmxBmLAT19fUQCAQICAiAh4cHwsLCxi1I7A+Om9xECBp6Yigk2WazoaamBnV1ddS0jc/n0xE/xMSts7MTFRUVKC8vh1QqRUdHB60YkzENfn5+kEgkTv1iroBMJoNIJHKqTjY0NCAoKAienp5u36yYTCadD01moLsS5DmJbBnoXnPINSUUCl3Wm0+qBUwmE/n5+WCxWGAymRAIBGCz2bR6ptfroVKpMHv2bHC5XHp8Npvt5KcwUL+0xWIBl8sdUqVnPEDe3/GuivUFmUyGiIgIAN33bm5u7oRIEubn5yM/P5+aUc2cOROrV6/Gk08+iUuXLuH06dO4ePHiuPTRNzc301YFX19fp/WisLAQr7zyipOZZldXF1gsFiZNmoSkpCT897//xY4dOyCVSrFz584REWSg2zmX3CekjWIim1D2h6amJirfJSCxoasVLsOF43o/1HNpa2tDamoqrr/+emzZssVdpzYgfHx8aMtOaWnpqJ/v3LlzePHFF/HGG2/g4sWLDa097gAAs11JREFUOHjw4LD73quqqsBgMGiCVqlUYtOmTejo6MC//vUv6PV6p95kd8BqtSI7OxuTJ08G0G0WnJ+f77LEUnBwMK655hqsXbvWJc8HwOVxzu9wHdxCkh2JseOio1Qqx3Vo/EhhMBiQk5OD+Ph4cDgcVFRUYMmSJSMm/cQw5bHHHoNKpaJmHkwmE9nZ2fjuu+8GHHBOFkaLxTLizXckYDKZiIuLw6xZszB9+nRwOBycO3cOH3300bjL5Tw9PXH//ffj888/77PyWFZWBj6fD6VSCT8/P+j1+nFNMPSE4yI5EStRjuYSg0n7bTYbmpub6edARkD4+flBIBBAIpEgPj4eXV1dKC8vpzNaHfuHpFIpBAKBSzcP0u8NOJOZ+vp6KkP19PQckknJaM7BaDSCyWTC09PTyaBqtGAymZDJZNDpdE7rkk6ng81mA5PJhFQqdRlJJqNszGYzmpqaelWouVwugoOD4ePjAwaDAZVKhYaGBtTW1qK5uRnt7e1DJmvkuScqSZ6I9yzQfe/FxcWByWTCbDYjOzu7XyXBI488gtTUVKSlpY3xWXZL8EtKSrB161YEBQVh5syZuO222/DEE08gIyMDp0+fxrlz58Y0CdHS0gI/P79+k5bV1dV499138c0332DFihW48cYb6TjGJUuWICkpCf7+/gPu5YPhpptuQlpamhNBvlIMuxzR1NQEhULhpGQhseF4V9AclW49x1UOhH379mHjxo34+uuvXbaGDxVCoZDK18lYP1egrKwMX375Je6++254eHggNzd3WM9NRkDa7XaEh4fjueeew9mzZ/Hpp59i6tSptDe5L9NaV8JkMiEzM5POP4+Li0N+fr5LVGn33Xcffv75Z5cU/JqammCxWCasmeGEhxnAUOpxo8jDuSV94VhpcqxAKZXKMZ/L6SpoNBrk5+fDbrdTgnXXXXeNqBdk1qxZuO666zBz5kxIJBLw+XxUV1fjs88+wy+//AKLxTIgOSDnMBYZdhaLheTkZKxbtw5fffUVNmzYAAaDgbfeegt/+MMf8O677+LixYvjutHNnz8f//73v2E0Ggd8TwoKCqiMKCwszC1y15HCUZ403kFDX3AMrIdLXMn9cvHiReTn59P1QSwWIz4+HlqtlvbROoLNZju9L6OFQqFwcn0mMBqNMJlMEAgElCy7CywWCwaDgZJDVx7Pw8MDfD4fQqHQaQMnLt4AaBuMK8Bms8FkMsHhcJxIIoPBgL+/P6ZOnQpfX1/qxktMu4qLi6HRaIZVzSTP78rrwZUg9+xEOj8+n4/ExETqZH358uUBE1yFhYXYsGED1q9fP65mShUVFdi2bRvWr1+P9evXIz8/H0uXLsXWrVvx4osvYtGiRWPiiGwymWAwGAZdj1ksFvLz8/Hhhx8iNTUVLBYLIpEISUlJCA0NxX333TeiamlCQgJSUlLoGLvm5uZeI+2uFJD+Y8d1vq+E5XjA8fjDue4vX74MjUaD2bNnu+O0+gWLxUJsbCxNOPTnqj4S+Pv7o6amBv/6179QWlqKf//735g6dSr9vclkQnl5Oaqqqvq8L0hsIJfL8corr2Dnzp346KOPYLFYUFlZCQAjcuMeCUhxy2w2U1f/iIiIUSXeJ02ahMjIyGGNge0P/v7+UCqVvfyHfsfEglt29IFI8pUotyZobm5GcXExtay/9957kZ6ejrq6OnR2dqKrq2vAnjQPDw889dRTmDVrFphMJpV0/fTTTzh16hTEYjEYDAaUSiX4fD5ycnL6lC2Tfk93mjtFRERg0aJFmDVrFvR6Pc6ePYs333yTOg+LxWLExcWhsbERGo1mXDJhCQkJWL16Nby8vPCvf/1rUBMNm82GnJwcTJo0CQKBAJGRkbDZbBPimnQMrsc6Kz0U9DXeYbiw2+1obGxEY2MjvLy8EBwcDKFQCKlUSoPBqqoqOtoC6O57dZUEmhBErVbb63ptamqCTCaDXC53aXW3J1gsFkwmE+3b9fX1dZmigRBurVbba21oaWmBQqGATCZzWV8yqW4Rsy6gOzgKDw+n6z6R4FdXV+Oaa64Z8fg/8vlPVFnaRJGOEpCxW8RVOS8vb1AFweHDh5GRkYF169bhk08+wffff499+/aN+XrEZDKhUCigVCohl8tRW1uL7du3Q6PRIDo6Gtdeey3Wrl2Ly5cv49ChQzhz5ozbzpG0ivSH4OBg6tqs1+uxe/dunDlzBvfeey9VLK1atQqzZ8/GP//5TydX954g+6pYLIZCocC9996LrKws2oN8pYzO7AtkJKS3tzfdb8kaMd4mlZ2dnSgrKxtRUnbPnj1YunQpjhw54qaz643IyEj63hUUFLisWCKVSuHr60unpRw7dgxz5szBn//8Z+Tk5OCrr74Ck8mkLu99OTMzGAxwuVxMmTIFTz75JA4cOEB/V1dXB09PT7pHZGRkuOS8B4JWq0VmZib1F1CpVJDJZKioqEBLS8ug5JTFYoHP54PH44HP5+OJJ57A6dOnERERATabDQaD0evLaDRSNVd/RUEOh0PjkYnmP3NF4Uo17nLMzDlmjMbCPdbdqKurQ1dXF+rq6rB06VLMmDEDZ86cob2ApMrb1dWFrq4uGI1GcDgcTJs2jRqU2Gw22Gw2XLx4EW+++SYNklksFkJCQmg/5uTJk5GZmdkroCebtqv7yoRCIebNm4dFixbBx8cHx48fdxrqHhUVBW9vb3p8uVwOPp+PyMhINDY29mm64w6EhIRg9erViIqKwo8//og9e/YMuQfabDYjKysLSUlJ4PP5CA8Ph81mG3e3UB6PB7PZDKPROKGcygn6cq4cDZqbm9HS0gK1Wk2Ns0hfcE1NDVpaWhAeHg4GgwEPDw80NjaO6nhE3gygTxOPpqYmhIWF0SRVz5mRrgAheAaDgTrTu6ovmclk0ipNX+8Vec0MBgNeXl6jlpSTzwXo/iyFQiFCQkIgkUio+VpLSwtKSkro+hUREYH9+/eP6HgTXW5NRolNhEoycWUms8ALCgqGvL41NzfjhRdeQHJyMlavXo1ly5bhm2++wa+//ur2PmYmkwm1Wo2AgACw2Wxq1kZ+5+HhgV27dmHXrl3w9PTENddcg1WrVmHNmjX49ddf8csvv7h01vlgzsHR0dE0MUV6vQnhO3ToEO6++27cfffdYLFY8Pf3x9tvv41ffvkFW7duhVarpRVniUQCkUjkdG2LxWIkJSXhxRdfRGlp6RUpse6J1tZWpxFuE4Ukd3V1ISQkBAB69U0PhmPHjuHee+9FXFyc2yXEQPfMbXKO1dXVLlNmMplMKt+2WCyUuB0/fhzp6em47bbbsHnzZlRVVdGe4r7WOiaTidDQUFRVVTkRZKA7YdrQ0AC5XE7NOseiv16n0yEtLQ1hYWFQqVQQCoWIjo4G0P3ZE6JMSC55HTwej75Go9GI5ORkKJVK5Obm0v27LwiFQsjl8gH7rh3jaHe2d/2O0cMtO7rjjUtcmBkMBths9oQkAMNFZ2cnOjs7sWXLFqxevRoHDx6EUCgEk8kEg8GAUCiEUCikG+js2bOxePFiOodVo9HgnXfeweHDh52e12q1ori4GDqdDmFhYeDxeIiPj0d6eroTSSE9Uq7KnsfExGDRokW4+uqrUVZWhj179uDkyZNOn5WHhwed0djU1ITOzk7IZDJaTfL29oaXlxeKiorcdtP7+vrirrvuwowZM/Dzzz/jzTffHJEBhNFoRFZWFuLi4sDlcqnj9XgmcAQCAXUKnoj3iKtJMtAdhFZXV6OoqAgikQharRZisRhRUVHQ6/Ww2+10ZnjP2bnDhUqlohteXyTSbDajs7MTUqkUUqnULSSZvG9Go5EG4K4iyY4mZ30RImKiJZVKERAQMOp7NCQkhFZeFAoFAgICwGAwaBtISUmJUzLCx8cHCoUCeXl5IzreRCfJJKgCMCbztvsDm81GYmIinbVeXV09ogQTcXKePXs27rnnHtx888346quvcP78eTecdXdVKiEhwaknVKvVoqGhAXa7HX5+fmCz2QgNDUV5eTlaWlooYY6Li8PChQvx1ltvobS0FAcOHMCpU6dGbR5JHs/hcHqpWUJCQuj+3trairy8PKc10mQy4fPPP8ehQ4ewceNGJCQkgMlkYvHixQgLC8P27dv7lRkbDAZcddVVOHfuHI4dO/abkWKaTCZ6jyiVSnovj3cLXs/JEsOB0WjEL7/8gqVLl7qdJAcGBsLf3x9Ad7uQK/19oqOjnUzAHK+5jo4OfPrpp9i9ezfWr1+PkJAQZGdn90mSGQwGKioqkJWV1edxGhoaaBEoPDwcer1+THx1bDYbioqK0NraiqCgINhsNkil0gHJLgGfz0dISAgWLFiA1NRUNDY2wmg0wmw209nnpM1JIpGAxWLBbDYPKClXq9X0+98ryRMbbiHJjtlcclOTjPBEcj0eLQ4dOoRVq1aBxWLh9OnTEAqFVC4lFovh4eGBVatWISoqihrcnDx5Em+//faAC0NtbS0sFguio6NpVYD0Q5N5rkDfFbGhQiwWY/78+Vi0aBE8PDxw9OhRPP/889BoNOByuVCr1eDz+XREFZvNhl6vB4vFQmVlJbRaLaqrq8FisWj2H+gOHgQCgcuGuDMYDEyZMoUaoRw7dgwPP/zwqDdWg8GA3NxcTJo0iRqSZWVljXjm3WjhKF0a78x6X3AHSSZwJMuhoaHUtIvL5dIxUpMmTUJ6evqIZNekRxboJpD9BaeERA5l4xwJyIxfo9FIX4crSTLQ/Tn1d/1UVlYiPj4eQqFwVKO1iMSUZNrJa7FYLKirq0NNTU0vkpiQkIDCwsIRr/8kaJuoJNlRQUPG9Iw1WCwW4uPjaRK1trZ21AHYiRMncPr0aVx//fV49NFHcf/992P//v04fPiwyxxqpVIp4uLiaBKsubkZFRUV9D5lMBiQSqVgs9nw9/eHWq2GVquFyWSCTqeDXq/HDz/8gB9++AHJyclYsWIF1qxZg2PHjuGXX34ZMZkgSdOeahYfHx8nVcpAIwWrqqrw6KOPYvny5VizZg2EQiGCgoKwfv16bN26FUVFRVR1Rr4YDAbWr1+PzZs3/2YIMgAnZQCJFwC4tPo/EjhexyPpdf/555/xn//8x63thCqVio5w6+jocOkYy7CwMFoAqamp6fc1NDU14bvvvsOkSZMA9N92pdfrB9ync3NzMXnyZHC5XMTGxiIzM3PM+tJbWlrQ0tICgUAAhUJBiSwhu0B3EUqtViM8PByRkZEIDg5GbW0tvL29sX37dhQXF0MqlUIsFsPT07PXFI6GhgZwOJwB1R9RUVH0+5KSEje92v8BXKly67q6OloFIoshySBOxCrZSGG1WvHzzz9j+fLluHDhAp2/SrJla9asgUqlQkdHB+x2O77++ushN/w3NjaCx+MhICAASqUSJpMJJSUlCAoKojfkSEhyQkICFi1ahBkzZqCgoAD//e9/UVNTA7FYDC8vL7pYms3mXv11HA6n14JmtVpRWVmJ+vp6Ovs2MDAQbDZ7VGOWpFIpFi5ciMWLF4PFYuHAgQN49913XVrt1ev1VHrNZrMRHx+PrKwst44n6A+OvfsT0enQFT3J/UEgEKC2thYdHR3IyMiAXC6Hv78/lfMSV1Ty+QwUOCqVSnR2dsJms1FCRlQZwMABGenZJCOMXG2gRu4tYggEwGXmcYQkD3Tttra20tnEYWFhaG9vh9lspsZOPj4+aGlpGZDIqtVq2tdlsVjQ2dkJg8GA2tpa1NXV9dvrnJiYOCqXX/JZXAkkWSgUjjlJJok+EuSXlZW5TA1htVrx3//+F/v378eMGTOwZMkS3H333Th58iR+/vnnUa3zcrkc8fHxVIWVm5vbK3ljt9tx+fJlxMXFAegmrSS45fF4Tu7Tra2t+OyzzyASiZCSkoI33ngDlZWVOHjwII4fPz6stdVkMqGrqwtisRiBgYFoa2uDUCik5j8tLS00eT0Q7HY7du3ahby8PGzcuJGuaytXrsT777/fq095wYIFdC38LcFoNPZJksdbSm61Wum6OBKS3NTUhPPnz+OOO+7Au+++6/LzU6lUiIiIgE6ng8ViQXZ2tsuSJ2q1mlY1SXvMQOg529cRjkRxoHvCaDTi8uXLTnFXenr6iBOoPB4Pb7zxBgQCAW1NqK6uRk1NDWpqavpMGuv1ekgkEojFYgQEBCAgIAD+/v4ICAiARCJBc3MzsrOzsXPnTmRmZiI4OBjPPvssRCIRZs6cCSaTSdvEHN8bjUaDxsZGtLS0DPgeOJLkK9lr4H8BbiHJpKLg5+cHf39/sFgs6PV6vPrqqxPSlGg02L9/P26//XYEBwfT6mlcXBz+9re/Oc3OfPPNN3Hp0qVhPTfp/1AqlXQxMxqNsNls0Gg0Q644MplMzJ07F7fddhvEYjGOHDmCjRs3wm63Q6VSOfUJkTm1RqMRVqsVJpMJRqMR7e3tlHz0hFKpBI/Ho9VxuVwOPz8/WK3WYWfxo6OjccMNN2DmzJnIycnBp59+ivPnz7sto67VapGdnU1dYBMSEpCZmTnm1VzSE9Xe3j4h1RajcbceDD1JhUajgUajgUgkQlRUFBgMBu3Zi46O7uXmyWQyoVQqERAQAKFQCJPJBDabjfT0dMhkMvj5+QHoTjwNpBRwNDaSSCQul987OkuTbL2rK8mDmTMVFxdTQyfSRxcdHQ2hUAiBQACLxUJnXfckFJ6enggPD4dEIoHJZEJnZydKS0tpUnQgJCYmYvPmzSN+fRPd3dpRvh4aGjqmHgcMBgMxMTF0Ha+qqnJLdc5qteLUqVM4deoUAgMDsWTJErzyyiuoqqrCvn37cPLkyWGtXRKJxGk8VXV1Nfh8PgIDA1FTU+O05thsNmRnZ0MoFNJZ52R0ItCtVONwOLTqDHRXwffu3YuoqCgsXrwY999/Pw4ePIgdO3Y4zT0eCNXV1YiOjobdbseMGTPoz81mM4qLi4dlgFdQUIA//elPePrppxETEwMOh4MnnngCgYGB+OKLL+jfLVu2DLt37x7y814p2LlzJ03iEfMnYPxJMtBdnR0pSQaATz/9FO+88w7mzp2LY8eOuey81Go1wsLC6P9zcnJcYroIdCdtQ0NDAXTvG0NphRmIJDv27g8Wr3V1dSEvLw9xcXG0rTAzM3NEr00ikSAiIgLPPvssgoOD4e/vj4SEBKjVakilUnoujtViJpMJu92Ouro6VFVVobq6GpcvX6YE22g0Qi6X0z1v2bJlqKmpcVKZEfPd9vZ2tLe3D7m4wmAwEBkZCaBbNXOl+zSNK67USjLQvSGQmWlRUVHIzc3F2bNn3XW4cUNXVxeOHj2KZcuW4d1338WMGTPw1FNP0SpsZWUlXnrppRHL3goKCsDn8+nNyePx0NTUhIKCgiE9/pprrsGdd94JJpOJ7777DmlpafD394evry9sNhusViusVivq6+vR1tZGq95DRUBAAEJCQmjGXafTob29HTKZDAEBAbBYLIMGbAqFAldffTWuu+46KJVKHD58GOvXr3dLX2hf6OzsdJqDnZiYiIyMjDGr6AYGBtKEiivHObgS7qwkk/7JntBqtcjIyEBcXBzUajWVCSckJKCpqQlsNpvOviaO1MTgp7GxEddccw0NhrVaLTWg6w9k3AubzYZYLHYrSa6rq6Mjm6RS6ahk/uR9AAYnye3t7SgrK0NoaCgkEglmz55NKzwsFgs2mw1eXl7w9/dHa2srurq6YDAYIBAI4OfnBz6fDyaTCY1Gg+zs7CGRDT8/P0il0lFlzMn6N97jYvpDXl4ebrrpJgDdHg+DOe27EtHR0fTaqq2tdWmvYn+orKzERx99hC+++ALz5s3DTTfdhAceeABHjx7FsWPHBh1VJBKJkJCQABaLBYvFgra2NoSEhFBJrlKp7DOprNPp+k1gCgQCyOVy+Pj4QCqVgsPhICAgAC0tLXj11VchlUpx++2349NPP8XevXudSFt/aGxsBIPBcKr8DGWcVn9oa2vDM888gwcffBBLliwBANx8881QKBR49913ERsbC09PT/z666/Dfu6JDsf1NzExEUB3tX4srtfBoNFooFKpIBaLwefzh733Nzc3Y/PmzXj66adRUlLikiRVWFgYrfIS1ZurikwKhQLR0dFgMBgwGAy4fPnykAoRjiSZx+PR98xms9FEK+nVHQytra0oLi5GREQEnZYykiQAn89HV1cX0tPTkZ6e7vQ7sVhMW7YIiWcwGNSsteexmEwm/Pz8EBAQ4KSk9PPzQ3Z2Npqbm6HRaNDe3j7ivSgwMJDu179XkSc+3EaSMzMzMW/ePABAUlLShA3+XYE9e/bg7bffRkZGBtavX09vrkuXLuG1114blcTcZrMhMzOT3rgNDQ0oLy8fdEGbPn067rrrLgiFQmzbtg3Hjx9HYGAgEhMT6WJhsVhQUVGBhoaGEVdqSVXR09MTRqMRPB4PHR0dYDKZkEgkCAkJgcFg6NXnIhaLMXPmTMyePRtxcXHIzc3Fnj17cOLEiXGppGo0GuTm5lIzL0KUx+JcYmJi6PcjNTZyNxyvYVfPOBxonJnNZkN1dTUUCgWVOCkUCmoY54i2tjZ6LScmJkKr1cJqtUKv1yMvLw82m41WmsioJzKqgQQfRqPR5fOZCRxJclVVFZVd+vv7j2p9dDzXnmZ7ZORTe3s7NBoNrdix2WzI5XL6PtbU1KCsrAxqtRp+fn5gMBjw9PR0Omer1QqbzYbOzk60trYOuRqXnJyM3NzcEQd4js7dE2FcW19w/PxiY2PH7LiRkZHU7bahoWFU0ueRwGAwYP/+/di/fz9iYmKwcOFC/OMf/0BHRwdOnDiBEydO0PmoBBwOBwkJCVTmX1FRQT0DxGIxTCbTiGT1xDSurq4OMpkMwcHBEAgEEAgEiI6ORmdnJ95++234+fnhrrvuwmeffYZdu3Zh9+7dAyqHGhoaYLVaaYtCeXn5qBKoVqsVH330EcrLy7F27VowGAzMmzcPGo0GAQEB2L9//29OcecIX19fes2OZl1wJSoqKug+HBQUNOQihCPS0tKwZ88ebNq0Cc8///yIk/xyuRxBQUHUw6KzsxOXL18e8H1KTk4Gk8lEVVXVoKaM3t7eVKFF5NtD/QxIElkoFCIsLAwREREAutcBqVRK28Z8fHzg6+tLjff6Q11dHfh8PgICAiCXy5GYmDjoawW6kyx8Ph+VlZWQy+X9JplJn/9Q4OPjg+DgYNqaBXTvpy0tLWCxWDh06JBLeAxx1gYwouvsd4wt3EqSCSZNmoRt27a561DjDuIg+uabb+LixYsICAjAkSNH8N5777lEGkOIwlBkScnJybj77rvh6emJ7du34+DBg3ScFMlemc1mVFVVoba2dtQyZlK5am9vh91uB5fLha+vL+rq6sBisahBQnNzM7hcLq666irMmTMHkydPRmlpKU6cOIHNmzdPCMlJa2sr8vPzER0dDT6fj8TERGRmZrp9E3cMqidqMskxM07mgroKfD5/wEQSkfGTqibJWlssFhgMBmi1WtTU1DhthqQKJZPJUFdXBy6Xi9DQUKhUKqcA3GazITQ0FHq9HlarFXK5nFakXQ1HwpmXl4ekpCQA3RWD0Xzu5FyJyZ/VagWfz4fFYqFuwURy3tbWhqqqKpSXl9PxMxqNBiaTCTabDWVlZaiqqoKvry88PT2peZ/VaoVGo6Hv3XAcSefMmdPLyX84IAkSoG/n7omA9vZ21NXV0f5Bd/S090RYWBiV6zc3Nw+qlHA38vLykJeXhw8++ADJycmYM2cO/vWvf6Guro4SZjIChsgdq6qqEBQUBDabja6uLjqXdDBFxGBob29HZmYmFAoFgoODIZFIIJFIkJycjMrKSrz44ouIiYnB3XffjaVLl2Lnzp3Yu3dvv+tQc3Ozy12YDxw4gPb2djz11FNobm7GbbfdBl9fX8yfP9+lx5loIMZPgHOcOJ5wNBoNDg4eMXn5+uuvwWQy8c9//hMvvPDCoIoKJpMJoVAIkUgEkUgEuVzulIRuaWmhCd6BQKarDJZccpRvm0wmZGdnD9k/gRjnSaVSOq3GbrfTUadktCm5tyMjIxEUFISKiooBlZRESUD6gSdNmoTs7OwBE1F8Pp/OL/bz8xu16lChUDipRVpaWlBRUYGuri7weDy0t7f3SvaNFI7H+Z0kjxJmAEOpY3FHfgi3keSWlhbU1NRArVYjOjoaCoViQhAhd4DMHlWpVAgICMC+ffvw4Ycfjuk5qNVqrFu3DgEBAfjhhx+wb98+mEwmREREOI3hMhqNYDKZVCZTVlY2qkp3a2srKisr6QgYs9kMFosFlUpFpXPz58/HrbfeismTJ6O+vh7Hjx/HJ598MiGt75uamsBisRAZGQmhUEiJsjsDXmJIQ8zZJiIqKiro9479ZK4A2VgHAiGx1dXVaG1tHXTMDqkM2Ww2hISEQK1WOx3DYrHQjZ3MKQW6E0h1dXVDrpIOB2RkDACkp6dj1apVAEDnU44URqMRtbW18PLycjKAs1qt9DUSskyq8K2traivr+/zHrRYLE5JOcf3OikpqZeh30Dw8fFBWFgYXnzxxRG/PmJ4BkzcSjLQTRJVKhU4HA4iIiLcqgoJDg6mUkwygmi8xk71hNlsxrlz53Du3Dnw+XxcddVVmD17Nu644w5qrFNUVASNRoPAwEAqfxSJRGAwGOjo6HBJRTwwMBBeXl4QCARU5URGynl5eSE3NxfPPPMMkpKScPfdd2P58uX47LPPXNpTOhjOnj2L1157DRs3boSfnx9YLBaUSuVvNlYC4NTbPRFJMvEHGSm++uor1NbW4uWXX8Z7772HrKwsmmwkxA4AdWzvCwaDAVVVVUOaI8xgMOjeNlBCPyQkhBqm6fX6QYmo4/MTd20PDw9YrVYwmUy0tbUhNTWVHlMoFKKtrY22PgHdkuzIyEj4+vqiuLi436puWVkZTCYTwsLCIBAIKFHuT9JM4jE2mw21Wj0qkuw4I9pgMCA/P9+pMh0QEAAPDw+XxQSkkmyxWCZsvPc7/g9udUE5efIkVq1aBQaDgblz5+Knn35y5+HGDfPmzQOfz0dRURHy8vLw0UcfjdmxmUwmbr75Ztx+++3Yv38/XnzxRbrwESdaAHR8E3GXZLPZ4PF4EAqFqKqqGlXwWVlZSQN0g8EAjUaDadOmYcqUKUhISEBnZyd27NiBrVu3uiwb507U19eDxWIhLCyM9s5lZWW5zDDDEcnJyZQ8FRQUuOUYroBGo0FnZyckEonLK8kkgO0PHA6HkjxCBAYjBMS10svLC3a7nWbiGxoaUFdXRzdr0v/I4/HAYrHAYDBQX18/6kpWT/B4PLoR19fXo7CwkErXiInHSGG1WlFaWgqr1QoulwuLxQKr1Yq2tja6sXO5XHh5eUGtVkMgEIDP5yM2NhY6nY7e//1VKxzfax6PBz6fP2SiPHv2bKSnp4/KMd6RJE/USjIAXL58mVYBr7/+ereR5ICAAHoPtre3Izc3d8IQ5J4wGAw4fvw4jh8/TltsVqxYgZUrV6KyshIXL17EhQsXUFtbSyXXpf+PvfMOa+p83/idQSAhhL2XgGxUBLVaxdG6tx3aautqtXXVjVoH4t5WrVq/jlpX6+iyrVtr696CoLKVvXcC2b8/8Ly/RIYEwtC+n+vKZQLJyQnmnPM+z3M/95OYWC/1jpGREXx9fbVcsJkKGzPmjTEFjIyMREREBCIiItCpUyd8+eWX6Nq1K7Zv395o37U7d+5g7969mDZtGgDgk08+wZIlSxrlvRsbS0tLUknOzMxs9PaA6ni5klwXuFwucUxOS0vDqVOnsGzZMpw4caKSs79YLNYKkNVqNcrKyiAWi4lqobbHtObzqko2s1gseHp6EtVJbeTbDCKRCN7e3lAqlTAwMIBSqYRcLietDZrbYNr45HI5srKy8PDhQzLSUSQSoW3btkhPT0diYmKVny0tLQ1yuRze3t7g8XikTbMq1RLzXswM9fpMTmBGTgIV45helm5rmvLWF2NjY72d5yh4vY27AODSpUukWtKzZ883MkjmcDgYOXIkgAo56P79+xttweLs7IwZM2bAyMgICxcu1JLbGRsbo0WLFkSOKpPJSMCclZUFuVwOKysrCIVC+Pr6wsjIqM5mEyqVCikpKWjdujXeeusttGzZEnZ2doiNjcWaNWuQnp5e7XD55kpaWhrYbDbc3NxgYmKCgIAAvY5eYPjggw/I/T///FOv29Y3z549Q6tWrWBhYQGhUKi3UVma8zOrQvN3NV1UOBwO7OzsYG5uTnpYgf9vV8jMzKzUYy6TyZCWllaPva8d/v7+ZFH08OFD4vzu6elJAtf6jA1ipNLVIZPJyJgmS0tLEmQJBAJ4e3vD1dWVVJdr+n+Vy+WkKlIbunfvjp9++km3D/MSTP8i0LwryVeuXMG4ceOIIdqhQ4fIbF194eDgQCpdzGL3dZmlW1painPnziEiIgJ+fn4IDg5Gu3bt8NZbbyE2NhYPHjxAXFxcvUzsjI2N0bp1axgYGEClUhHzOQcHB2JwFxcXBzc3NxgaGsLV1ZUcNzdu3EBkZCQ+//xzbN++Hbt27Wo0A60zZ85gyJAhsLOzQ2BgIFq1alWvhX9zpUePHiTAuXjxYhPvzf8jkUiQm5sLKysrMo+4tpiYmMDZ2RmWlpZaDs+JiYn48ccf8fHHHyM/Px9JSUkoLy+HVCqFRCJBZmYmpFIpysvLIZFIYGRkBA8PD3Tt2hVOTk4oLS0lXhJZWVl4/PhxtUl0Ro31cpDM5/Ph6+tLkkUFBQU1bkcTc3Nz4j6vVquRk5ODnJwcotKqaQSUSqUiY8xsbW3h7u4OAwMDODo6wsDAAHFxcVXuQ3Z2NuRyOfz8/Mi0keTkZCQnJ1eZDFCpVHB2dsbZs2df+XmqQy6Xo7i4GIaGhlV6E/j5+ektmUOl1q8fDRokZ2ZmIjo6Gv7+/nB2doaPj88b5+bWu3dvUgm8f/9+o/SUslgsDB06FCNHjsTRo0fx22+/VZIDM6O3mMUz0/ealZVFDs6MjAz4+/tDIBDAzc0NKpWqTgGDi4sLBg0ahGHDhiE7OxtHjx7FqVOnwOFwIJVKtS4crxMpKSngcrlwdnaGqakp/Pz8EB0drbckiK+vL+kVTUtLa/bu70yQDFSYm0RHR+tluzKZTGve4MswBiYqlapagx1zc3N4eXnB0NAQCoUCarWajDNKT09v8P7QV8H0HwMg80/j4uKI8Ymnp2ejJJLUajWpVFhYWMDFxQUikQhKpRIODg6wt7dHWlpateaApaWlMDExIf8nNdGiRQvY2Njg9u3b9dpnZkwJUPOc66ZGKpXi5MmTGDVqFGQyGQYOHIh9+/bpbft2dnZEjcCMrmuuypOayMrKQm5uLq5fvw6pVAofHx988cUXmDp1KiIiInDs2DHcunVL5+CfaY9hAuS4uDhiYlRYWEhMK1ksFvLy8mBrawtHR0et5JJYLMaWLVvw77//YvLkyQgJCcG2bdsaXP6sVCpx5MgRzJo1CwDw6aefIjQ0tEHfs7FhsVjo1asXeXzp0qUm3JvKJCUlwcrKCsbGxrCysnplDzqPxyPXHM1Z3QqFghhGPXnyBIWFhejfvz9mz55N1AkGBgZo0aIF2rRpAy8vL3h5ecHR0ZF4C6SkpIDP58PV1RWtW7eGi4sLDA0Ncfv2bVy6dKmSTJ2RQGsqsmxtbdGyZUuiosjKykJsbGyt1i8WFhbw8fEhJnpPnz4lUmqG2o6AysrKQl5eHjw8PGBhYQFzc3O4u7tX269dUFCAyMhIYqLq6uoKMzMzPH36lKwnmSStubk5bG1t67XulkqlZPSXSCTSSlZzuVx06tQJYWFhdd6+Jm3btiX3m6tJK0WbBh86ef78edJzOWLEiHr1pjU3DAwMSKUcAA4ePNjg72lra4uZM2fCzMysUvVYE+YkUlBQACcnJzJmJzExkTynrKwMDx8+ROvWrSEUCuHh4QG1Wl2r/g4Oh4NOnTqhf//+8PLywtWrV7F3716kpaUhNjYWcrmcVP2aqxSwNiQlJYHNZsPR0REWFhbw9fXVW//fqFGjYGFhgfT0dBw5ckQPe9uwaErl3dzc9BYkp6amVpu953A4JJFQXFxc5cJZc1SGWq1GcXExMjIykJ+f32y+e2+99RaAiv1jguG4uDgyXmnSpEmYN29evapoupKfn4/8/HwYGxvD2tqazJp1cnKChYUFoqKiKvWsFRQUwN7enozjqmkh2atXL9y4caNengfA//dsKxSKZt+u8ddffyEoKAienp4YOHAg/vjjD71Uv62trUlCRSKRIDIysskTP/WBGT0IVIwG+vXXX3Hu3DnY29vjs88+w8SJE3HmzBmcO3euVgEqn8/XCpCjoqK0ZJqFhYXIyMiAnZ0dXF1dERcXB1tbW7DZbPB4vEoKkwcPHmDGjBn48ssv8e2332LHjh24du2aXv8GL/PPP//ggw8+gIuLC3x8fNCuXTvcvXu3Qd+zMQkJCSFqtoiIiGanCnn27Bnat28PoCLBV9O5TSgUIiAggKyzmMpwbm5upXPmsWPH4OTkhEWLFiEhIQEtW7aEq6srJBIJYmNjERcXh6tXryIuLq7GvlcvLy906tQJoaGhuH//Pg4ePEiUKgUFBbCxsYGtrS3EYjGsrKyIAkepVCI+Pv6VrteaGBkZgcPhQK1WIyIigiSnNc85L7fcaFaSX77uKhQKxMTEwMfHBzY2NrC2tq7R1KykpAR3796Ft7c3LC0tYWpqiuDgYDx//pyMKwQqEqjR0dE1utO/CoVCQeZkW1lZaf2d2rZtW6vxkbWlQ4cOACqSCC+Pq6LUgUaQW+vfwvUl/vnnH3IgBwcH17v/rjnRqVMnMkLl+vXrDd6E37NnT2zbtg1JSUmYPn16jQcucwKzsrIivSh5eXmV5KrMCADGIIGRSlcHl8slFZJPP/0Ut2/fxtixY/HNN9+Q/dHsIXwTSEhIICdOKysr+Pr61tv9uFOnTmRWJIvFavAFmD7QlBxpVkbrS2xsLAkAGNhsNiwtLdG2bVuw2WzI5fIqkzdOTk5asyQjIiIQFRWFvLy8ZhMgd+jQgQT6UVFRRM58+fJlnD17Fmq1Go6Ojti+fTvef/99vY/YehVisRjPnj3D7du3yfdcIBAQqZ0mBQUFKCsrQ2lpKXx8fNCiRYsqpddCoRC9evXCyZMn67VvhoaGMDQ0hFqtRlJSUrOvnJaWliIyMpKMEfv888/rvU07Ozutmab6nJfaHGBc38ViMY4ePYoJEyZgx44d8PHxwd69ezF9+vQarynMJAIejweVSlVtH2N6ejpYLBYMDAy0ZI/V9deLxWJs3LgRO3bswOTJkzFr1iwtYzx9o1arcejQIfJ4wIABDfZejQ2LxcLHH39MHh87dqwJ96ZqamvexfTLWllZwcTEBFKpFCUlJeDz+XBycoKHhwcxyXJ1dYWLiwsuXbqETp06wdLSEpcuXcLixYsxYcIELF++HEeOHMHdu3dfaQwVGxuLH374AZ999hlKS0uxefNmch1m1tiM9wUTIJeUlOD+/fs6BcgASAU6NTVVKwBVq9Xkuvqyk3Z1lWRNGHl5bUywFAoFoqOjER8fD5VKBS6XCw8PD2I+JpFIEBAQoJdEUmpqKjgcDiwtLWFiYkJ+3q1bN/z777/13j4AotQCKqaY1HXOMqVxafAgWalUap0QR40a1dBv2WhoSofquxisCYFAgNDQUHz66adYvXo1du3a9crqTGpqKkpKSmBhYQG5XA6xWFxtFUYulyMyMpKcDD09PbWceBm6du2KnTt3ok+fPti+fTu++OIL/Pbbb2TRzzjlGhsb1yiffR2JiYkhmW8rKyutkVq64uDggOnTp5PHR44ceS36ChMSEsjFrU2bNnWaJWxkZARLS0vY29vDwcEBjo6OKC4uRqtWreDl5YWWLVsiKCgInTt3Jq0AhoaGSElJqZTZNzMzI4uZoqIi3Lt3r1ErsbWBx+NpnfM0fRmUSiVu3bpF/qampqYYM2YM9u/fj8mTJ6N9+/YNuih/GaVSiZiYGJLsMjY2rpTUVCqVxK2VzWbDxcUFHTt2xFtvvQVfX1+0aNECLi4uGDNmDFlg2dvbw9bWFkKhUOfkkouLC6ytraFUKl85TqW58Ouvv5JzYqdOnTB06NA6bYfFYsHDwwNeXl5gsViQyWSIjIxskjnyDYnmgl4sFkOtVuPOnTsIDw/HlClTwGaz8d1332HcuHGVEkjMTHsmkfLkyRPk5+dX+T7MNbCsrAzm5uZQqVTIzs5+5WL12rVrmDp1KkxNTbFly5YGTfTfvHmTBDxBQUFa3gqvM926dSPJzKioqGbZb62ZBNYcU/UyCoWCSH/Ly8thaGgIW1tbrWuas7MzcYRu0aIFRCIRbt26BVNTUxQWFsLCwgItW7ZEhw4dYGtrq1NLWnl5OXbt2oW9e/di4cKFGDp0KPLz8xEfHw+lUkkMtZKTk/Hw4UOdvS6Y4Le69iZNZ2lNNB9XtZ5hnNuNjIx0SmCnp6fjwYMHpD8bqFCVpaWloXXr1vVu52GxWGTGs2bPtaGhId566y29Bcnt2rUj9+u7z5QXKPD/1eSabvUQXTW43BqoMGgYPnw4bGxs0LZtW3Tu3Pm1qJzVhLW1NakEZmRkNFgvspeXF0JDQ5GSkoJp06bVOgjIzs6GiYkJbt++DXt7e0RFRdVYhWEC5cDAQBgZGRFHw7y8PAQGBmLs2LEwMTHBoUOHcPny5SpPcpmZmWQx7OTk1GycK/UFc2F0cnKCsbEx2rZtS3qOaouhoSG+/vprEvxcuXIF//zzTwPtsf65e/cu3n33XRgZGcHf37/WIzzMzMzg6+tbZdVGLpdDIpFg8ODBlS4eTItAVQvfli1bkrFmjx8/bnaJBqFQiOnTp0MoFEIulyM1NbVS1jsqKgpTpkzBl19+ic6dO5N+q759+6Jv376kgvro0SNERUUhPj6+wV13MzMzYWxsDEdHR9jY2FQaiSWVSnH37l24ubnB1tYWQMX3mgl2eDwehg4diu+//77SeCu1Wo2MjAwkJCTUaqHEVA24XG69Z2E2FhKJBN988w0WLVoEABg7dizi4+MRFRVV621wuVz4+fnBzMwMQEWFOjo6ut7S9eaGiYkJrKysyPHxMhkZGdi8eTN+++03jB49Grt378aJEyfwxx9/QK1Wo02bNmTR/fTp01ceG8+ePQOLxUJOTg74fL5W+1FNFBQUICwsDMOGDcPKlSvx448/4pdffqnTZ34VFy9exMcffwwWi4V33nkHJ06caJD3aSyEQiHGjx9PHv/4449NuDfVk5GRgfT0dDg4OMDf379ac0qVSoXCwkIkJiYS6S8zhknzX8Ybg+mDf/jwIYYMGQKFQkGUUmVlZfDy8oKLiwuePn2q01SFS5cuITk5GUuWLIG5uTm+//57ZGdnE+VVXZVUmhXiqtaMCoUCBgYGla7lmo+rOk+5urrCwMAAYrFYZ28JsViMiIgI0nddVlaG0aNHIyIiol7XBQMDA2ISJpFIIBAIyN/tnXfeQVZWlt6crUNCQiCVSpGZmYlbt27pZZuUhqdRgmSlUol9+/Zh/vz5AIAvv/wSERERenPHbQreffddkv27cOFCg7zH+++/j48//hiHDh3Cb7/9pvPrGfl3becRy2QyREREIDAwkGTROnXqBHd3dxw7dgynTp2qUeanVCpRWFgIoVAIOzs7PHv27LXpmxOJRLCzs4OVlZXWeAHNkUOMA2ZSUhI54bdq1QppaWl4/vx5raSgX331FXEWTklJwdatWxvuQzUAd+7cgZ+fH+RyOdq2bVvrINnd3R08Hg9sNhtKpRIqlYr8feVyOa5evYq33noLly5dglgsRnFxMYqKiqrtNRIKhSTRkJCQ0Kzkp7a2tujduzd69+5NDK6SkpKwcePGKp9fXFyMdevWwc7ODitWrECnTp2QmppKTErc3d3h7u6OIUOGAKioJKSnpyMtLY3c0tPTkZeXh6KiIr1IkhMTE0mfso2NTSV5nEwmQ0xMDBITE8mID5FIBAMDA3To0AE5OTl48uQJ+Hw+WTiy2WxwuVzY2toiNze3VsklzXFjzb0fWZPbt2/j2LFjGD58ONhsNubNm4dZs2bVqg/T2toaHh4eRMael5eH7OxstGjRAqampmQRyyy+GUpLS5GZmVnjOK/mBjMOhTGUq46kpCSEh4ejVatWGDt2LAYOHIgzZ86QObKxsbG17nGtyQX+Vfz666+IiorC3Llz0aZNG2zatEnvM9UvXLhApMm9evV67YPkzz77jCR7bt261SyryAy3bt3CsGHDwGaz0a5du2pnZiuVSp3b6x49eoShQ4eSdgATExOSiGR66h89eqSTGio+Ph6hoaFYsWIFhEIhtm/fXu81F5vNJteeqq4lMpkMfD6/0tjGV02h4PP54HA4UCgUdR6xqFKpUFZWBmNjYwwYMKBehlpcLhetW7cmpmvp6elISkqCSqWCkZERRo4cie3bt9d5+5pYW1uTFg8mUUzRA7IXt9o8r440SpAMVPTs3rhxA506dYKpqSm++OKLaheNrwM9e/YEUPGF17dLo5mZGWbNmgU7OzvMnz+/USuyUqkUjx49wmeffYbBgwfjn3/+wcSJE2vdP8HMu2Qypbr2wjQUjNTH3t4ednZ25MY81lU6XV5eTvpknz9/joSEBERGRiIrK6vaixTjlgpU9M+uXLnytasMPXz4EHPmzAGXywWfz8f+/ftr9TrNrDpzMdK8AEdFReHtt98mwderYNoBFApFk87OZbFYcHBwgIeHBzw8PODt7U2c5BlKSkpw4MCBVwZ5bDYbFhYWePbsGXg8Hs6cOQMvLy+4ublpBUNGRkYkcK6K4uJiFBQU1HgrKSlBaWlptQG1Wq1GdnY2nJycYG1tjYSEhCoDL7lcjry8PPJ/wOFwMHnyZGzbtk3LmMTKygpeXl5knEhtF3KaQXJzdrauisOHD8PT0xNt27aFqakpVqxYgfnz51drRGVhYQFPT0/4+/vDxcUFLi4uMDY2hqGhoU4ydUZGnJmZSW4ZGRnkfn1GjekTpgcQqLhu1Kby9ejRI8yePRsDBgzA1KlTERsbi2+//bZRrzNxcXGYMWMG+Z5v2rSJONbrg5ycHERGRqJ169awt7eHn59fo0zNaAiCgoLw7rvvAqioBu7YsaOJ96hmmCAZqDBbrC5IrguMuZerqysKCwtRUlKCp0+fIisrC35+fuBwOGT0ly6BcmZmJkJDQ7F8+XLMmzcPGzZsqFfSmMvlkgC4qutDWVkZTE1NK62ZNIPkqlpCmOuHPqadvPfee4iPj6/XtJyAgAASICclJWldX9577z2kp6fj5s2b9d5XAOjSpQu5f+XKFb1sk9I4NFqQDADfffcdydx069YNcXFxDdrL21C0atVKa+yTPhfpbdu2xaxZsxAREYHVq1c3+oLGxMQEU6ZMgbe3N06cOIHIyEidDAbKy8tRUlICExOTJguSORwOWrRoQUYreHl5wcnJSa+jqIyMjMDn82FnZ4dOnTqBxWKhuLgYKSkpePToES5evKjlgv3555+jb9++ACouFhs2bHht5KOaMM66QUFBpOJVm4z6s2fPSPBobm4OGxsbPH/+nCyOy8vL8dNPP+HLL7/E9OnTX1kNZUY2NKRBl4GBAYyMjGBqakpGVzAzmJnP4ObmRhYLHA5Ha7+VSiWuX7+OPXv21Mqhd/LkyeByuVAqlThw4ABxyzc2Noa/vz8Zpefo6EiceauCqerWZt5nWVkZSkpKyK24uBilpaXESdzW1hYSiQQSiQRZWVkoLi6u8XzQq1cvSKVSsrgwMTGBh4cHMbJSKpXIyMio9TmFCZLLysqaNBlSF9RqNdavX4/169fD0dER9vb2WLlyJebPn08WwZaWlujZsyc6dOgAZ2dnODg4EKmmWCyuU1WIzWaTJGBVFBYWIi4uDrGxsYiJiUFcXFyTmMiYm5uT77CuTsdPnjzBjh07MHToUEyaNAl79+7Vm9t+bZBIJNiwYQN69uyJr7/+Gn/++ScOHz6sN2O58+fPk3aunj17vpZBsoODA+bOnUse79u3r8FHadUXRvIsl8vJTF99qpSeP38OFxcXLQUWM/KoVatW4HK58PT0xL1793Tabn5+PubNm4ewsDAsXLgQy5cvr/N3UbO3uKrzD+Pe/XKQrCm3ripILigogLm5OfG6kMlkRA3DGHNpPi4rK4NEIkFpaanW/4GPjw8GDx5crxFp1tbWZA3xcoBsbm6OYcOGYeHChXXe/sswRTUAuHr1qt62S2l4GjVILigowPbt28mX+7PPPkNqairu37/fmLtRbzS/8PqSWrPZbHz66acYMGAAdu3ahYsXL+plu7oQGBiIGTNmIDY2Fps3b4aRkVGlcQa1IS8vDyYmJmQR1NDSPw6HAz8/P3h6eqJjx45E2lsdcrkcWVlZWtUVptqSk5MDpVJJAmpNSaNQKIS1tTUsLS1hbW2NFi1awNvbG66uruDz+cQR2N/fHx999BHS0tJw5coVsFgsLeXBxo0bcefOnQb9mzQkN27cQFBQEICKY6E2QXJxcTHu3bsHNzc3mJubE6dKc3NzPHnyBEqlEidPnkTPnj0xePBgLYOrl2GxWOByuTAwMIBIJIKLiwt4PB4MDQ3B4/HITfPxy/eNjIzI7eXHzE2XpIqNjQ2cnJzw9OlTJCQk4Ny5c7hw4UKtpZjt27cni2Jm1jiDWCzG7du3tfq1ORwO7Ozs4OjoCEdHR9jZ2ZEgnrlV59qrCZ/PB5/Pr9Koj81mQyQSQa1WY9iwYWTBJJPJyKzlnJwc5OXlIT09HYWFhRgzZgw2b94MtVoNOzs7eHp6kr9jYWEhUlJSar1QNjQ0JPv1OkmtNSktLcWiRYuwZs0a2NraklEwkZGRePvttxEQEKBllKNSqVBeXo6cnBzExMSQ0S3M37ugoABKpbJSKwhQYfxWnVJG07HVzMwM7du3J+NugIo57Xfu3EFiYiLu3btXZzmkLjBVZIlEonMymOnt27FjBxwcHLB06VKcPHkSR44caVQH9AsXLuDp06cIDQ1Fq1atsG7dOr2MNrpx4wbpkezSpUutzDqbE8bGxli8eDGp1N2+fRvnz59v4r16NSqVCn///TcGDx4MCwsLdOjQQa/+OcnJyVU6Z5eUlCAmJgZ+fn5Qq9W1mtP8MqWlpViyZAlWrVqF2bNnY/369XVKIL+qJ5k5Vnk8HlgsFnmPV8mts7KyyLXawcFBa10oFou1Zk1rolKpkJmZiefPn4PL5WL27Nk4dOhQvdomGC+N0tLSSgqlyZMn486dO3ob++Tr60u8NaKjo6nUWp80wgioRg2SgYosiqurK0aMGAEWi4V58+Zh8eLFevtCNgaMS51EItGLSx2Px8O8efPIDOS0tLR6b1MXDAwMMGbMGPTt2xe//PILHj9+DIFAAB6PV6e+8by8PLRo0QIcDgempqYNkj3mcDgIDg5G165dERwcDGNjY5KpZFAoFEhKSkJcXBzi4+NJUFzXipRUKq3ytUKhEN7e3ggICEDbtm2J26qjoyOmTJkCU1NTnDx5EnZ2dtiyZctrL7e5cuUKJkyYAB6Phx49euD777+vleOuXC5HbGwsBAIBCZAtLCzQpk0bREVFQSaTYceOHVi6dClSUlLAZrPh5uYGS0tL8lwrKyvyGKjbAlufME609vb2SEhIwPPnzzFz5kyd5za+99575P6ePXte+fdUKpWkH7k6BAJBpcDZ3NwcZmZmEIlEEAqFEIlEMDExgYmJSZVJAcaUhpk/q1KpyCKHGWsFVFQCg4ODYWRkRGTzTKZeLpcjMTFRZ1WJ5mLydQ2SgYrz4ddff421a9dCqVSiX79+GDVqFJKTk0lvfmJiIh48eICHDx8iJiamTioTRvZelUGYQCAgDryaKhvGLdrR0RFyuRxDhw4lJljXrl3Dv//+q5MxoS4wzs3VuVHXhFQqBZ/PB1BhuLR161aMGjUKbdu2bXSVTmpqKmbPno3PP/8cGzduRFhYWL0W8EBFIurq1avo3bs3jIyMEBAQoHN1sakwNDTEwoULiZv18+fPsWHDhibeq9pz+/ZtDB48GECFK7c+g+SEhAS89dZbVf6O8ZQwMzODk5OTzkEyUBHAhoWFYe3atZg0aVKd5O1MclWtVlcZJGsWToyMjMj191WVZLVajbt378LJyQm2trYk0ccoyZjkH1CRoBUIBOBwOGCz2XBwcICdnR0GDBiAjIwM/P777zp/Lk0YOfnLSeyRI0fCxcUFs2fPrtf2NWEUhABw5swZvW2X0jg0epAMVPRqOTs74+233wafz8fChQuxadOmWpsANSVubm4kK6+PeZVCoRCLFy+GSqVCaGhovYai1wUnJyfMnz8fhoaGOHDgAAoLCyESiVBaWgoWi1Wni71YLIZUKoWhoSEsLS31GiT7+/ujW7du6NKlS6VxICwWC1euXMGTJ08QGxuLpKSkRjF0Ki0txb1793Dv3j388MMPMDIyQrdu3TBhwgR4eXkhLy8P9vb22LJli97715sCiUSCf//9Fz179iSVDl0+l0QiwaNHj8gsSaFQiMDAQNy7dw8uLi5wdnbG0aNHcfLkSXh4eACouADz+Xwi2eVwOJDJZHpTKSgUCpSVlZGxHsxNKpWiqKiI9PLm5+dr3S8vLweXy8X69evh4eEBa2trzJ07F8uWLat1Ft/Lywv+/v4AKvpu9dUHxcika5t0EwgEJGA2MTGBmZkZ/Pz8SKuCUCgEn88n/xcvG7fIZDJkZ2djwIABaN26Ne7du4ebN28iKiqqTlUwTWfs190pPycnB19//TVWrFiBgoICODg4wNjYGFu2bMHp06cbPKiTSCRISkpCUlISrl+/Tn5uZ2cHLy8veHt7kx53FosFX19f+Pr64rPPPkNERAQuX76MGzdu6C0hZWJiQhbVdUla5ubmIi8vDwKBgBj4HT16FJ07d8a3336LHTt2NJihZlXI5XLs3LkTWVlZWL16NVauXFlvg6p79+6hd+/eACpG7r0OQbKJiQlmzpyJgIAAABUKomXLltVJkdZUPHr0iCTc27VrB1NTU72Zs0VERGDu3Lmws7Or0lA1NzcXZmZmEAqFWlVaXSguLsbixYuxbt06fPLJJ1qztxkYlZCJiQk5fmQyGbhcLhmPVl2BRPMcoBkkv6qSDFRUhZOTk2ud9DQyMoKDgwOcnZ0xcuRIWFpaYtWqVfVWKDLtJZr73LlzZwwePBhz587Vm6mwUCgk/cilpaVa516KHngTK8kMmzZtgrGxMTw9PcFms7F06VLs3LkT586da6pdqhWa8/Pqa9ZhaWmJZcuWIS0tDevXr290h96ePXti8uTJiIqKwt9//00yefn5+cjJyUF+fn6dnRLz8vLg4OAAS0vLei9wnZ2d0aNHD3Tr1o2MmWFIS0vD1atXcfv27WYzR5VxH+Zyubh16xa4XC727t3bJBL6huLMmTNEQt6/f/86Bf9JSUkoLy+Hp6cn7O3tsXnzZhgaGiInJweWlpZkxBOTDOFyuSgpKUFhYSHKy8uRkZGBvLw8yGQySKVSyGSySver+plmIMzcr88FV6FQYM2aNdi0aRNMTEwQHByMsWPH4vvvv6/V6xmjGAA1yswbGs3eY4bLly+TyjBTuSsrKwOHwyGBnZWVFWxtbXH//n2EhITAxMQE3t7ecHNzw5UrV+osE2USJMDrHyQDFQY74eHhWLt2Lfn+GRoaNqk3AdNqwswCtbS0RLt27fD2228jMDAQLBYLgYGBCAwMxOTJk3H79m1cvnwZ9+7dq5esmZFaKxSKOs82j46Ohkgkgo2NDaysrMDj8fDvv/8iIyMDkydPRps2bbBjx45GVZr88ssvKCwsxJIlS7B58+Z6LYofPXpEzA5rmtvbXGBaCRwcHJCWlgYzMzMsXbpUL/LzxkStVuPvv//Ge++9By6XiwEDBuDIkSN62bZEIsHDhw/x9ttvVzlCjAnemFFHdU0u5ObmYvHixVi7di1KS0vJdBRzc3O4uLhAJBJVUg4x8n4DAwOUlpZWGyhq7hOfzydFkFcZd9WF8vJyZGZmYty4cRCJRNi3bx9MTU3h4+NTrz790tJS2NjYQCAQQCQSoVu3bhg9ejTWrl2rV4PIHj16kGTgxYsXm9UUDkrtaLIgWSaTYdmyZZg4cSL69OkDAJg6dSo6dOiAb7/9tsEkXvVFX0Gyk5MTli1bhvv372PHjh2NOrKDz+dj8uTJeOutt3Ds2DFSacrKysLz58/10vuUn58PBwcH0u+p68mey+WiU6dOGDBgQCW34IKCAvz777+4fPmyzmMYGgPGlZzJdh49erTe8qDmRmxsLJ49e0akmx07dqxTBTQjIwPu7u6YOHEiRCIRmUl48OBBxMTEwMjICDKZDEVFRcjNzUVqaiqKiopQVlbWrMbcZGVlYc2aNVi+fDnYbDaGDRuG2NjYV0r17Ozs8Pbbb8PQ0BDZ2dl6dVPVB2q1GteuXYOhoSHpyWf6nV1dXfHkyRMtT4l//vkH06ZNg6mpKcRiMb766itMnTq1Tos9ppKsVCr1NquyqUlJScHSpUuxevVqGBgYoG/fvnj+/Dn++uuvpt41ABXJzbNnz+Ls2bMwNTVFSEgIunfvDi8vL/B4PHTp0gVdunRBfn4+zpw5g7Nnz9ZJKcSMBMrPz6+X8V5xcTGKi4uRmJgIOzs7uLi4IC4uDlu3bsUHH3yAb775BuvXr2/UJMulS5dQXFyM0NBQmJqa4vTp03XaTmlpKeLj4+Hp6YkWLVpAJBLVOaHQkLBYLAwZMgSffvopCQg4HA5CQ0NfO0d6hj///BNDhw4Fm81G//79cfz4cb0FONeuXUP//v2rDJKVSiUpTNTXaDQtLQ1hYWFYsWIFjI2Ncf/+fa0RlwCIQaBarYZMJoNCoQCLxUJaWhppJXqZl+XWDK+SW9cFb29vzJ07F6mpqZg8eTLs7e1ha2sLKysrtGzZss7HdWZmJpycnODq6oovvvgC2dnZWLhwod7bPjWl1mfPntXrtimNQ5MFyUCFJGPHjh2QyWQYNGgQAKBDhw7Yvn07vvvuu2bXu8nlcokskjGrqQteXl4ICwvDqVOncPjwYX3u4ivx8PBAaGgoCgsLsW/fPuIemJiYqNd5j5rGL0KhsNaLZGtra/Tp0wd9+vQhM2aBiurV9evXcfnyZURGRjaYo7E+mDVrFpHk3717t9Zjkl43Dh8+TBwgx40bh7t37+qsPBAKhRg7dixZNKtUKixcuBBRUVFo3bo16WtNTExEamqqXvdfn7BYLBgaGqK0tBSBgYFITEzEuHHjcOvWrRr/JoMHDwaLxSLmb2PHjsXFixfr3dOob6RSKenJZ9y2jYyM4OPjg8jISLJ4F4lEOHLkCEaOHAl7e3vY2Njgk08+wZ49e3R6P4FAQJytk5OT36gMfGxsLLZt24ZZs2YBACZMmICHDx82uhfFqygqKsKff/6JP//8E3Z2dujWrRu6d+8OR0dHWFhYYOTIkfjoo49w48YNnDp1Sid5MaMO0ZdBmEqlQnp6OrKzs+Hl5QVLS0scO3YMrVq1wurVq3Hw4MFGnaRx9+5dLFmyBEuWLIG5uXmdK5ERERHw9PQEUCG5bm5rInt7e8yYMQO+vr7kZ8+fP0d4eHidemqbC7m5ubh69Sq6du0KkUiEd955R29Bzq1btzB16lRYW1tXWWVn3KX1MY0jISEBmzZtwooVKxAQEIBffvkFarUaaWlpKCoqqlN738uVZIbayK1rC4vFwvDhw/HBBx9oHbvFxcXgcDiwsrKCg4MDpFJpnRIxbDYb7du3x/vvv49///0XZ8+e1fv6IigoiBh2PX78uFmvX15XdEnFVG/lWzO1H77YQKjVauzevRsrVqwgQZqJiQnmzp2LVatWaZ18mxofHx9yIqhrFdnT0xMrVqzAjz/+2OgB8uDBg7FmzRpcvHgRv/32GyQSCeRyOWJiYvQaIAMVJ0mmIv1y73BVBAUFYdGiRdizZw+GDx9OAuS4uDhs2bIFn376KbZs2YKIiIhmHSD7+flBqVRCLBYjPT0dGzZsaNb7Wx9u3bpFFsb29vYYOHCgztuYNGkSMfHIy8vDqlWrEBkZCR8fH60RDc31AiMUCvHee+9h9+7dmDp1Kv744w/88ccfACqOgQ4dOlT7WoFAgF69egGo8DeYM2cOjI2NsXbtWmzZsgWDBw8mf4PmhFgsxqNHjyCXy8FmsxEQEED62jgcDtRqNbZt20aO/549e9bKaVuTcePGkUVibeZmv25cvnwZv/76K9RqNRISEtCjR4+m3qUayczMxNGjRzFp0iSEhobi8uXLUCgUYLPZ6Ny5M1auXIkdO3Zg4MCB5LtQHQKBgIx+0lfvH4NCocCTJ0+IGdijR4+wadMmDBkyBIsXL9Zy+W5onj59innz5qFXr14YPXp0nbah6dPSnCTXpqam+Pzzz/Htt9+SNZparcZvv/2GWbNmvdYBMoNm68vQoUP1tt3S0lLcv3+fKCg10TSu0keQbGdnBz6fj++++w7+/v7o3bs37t+/j4yMjDr737zck8ygL7m1m5sbVq1ahe7duyM0NLRScuvp06ckKevq6qo1sqo2+Pr6Ytu2bXBycsKcOXNw/vx5cDgcBAYGkmS9Phg+fDi5z8jdKa8fTR4kM9y+fRuTJ0/WmiEWEBCAtWvXIiwsTMvEpalo06YNuV8XkzE7OzuEhYXh4MGD+PPPP/W5azViYmKCxYsXk4XCv//+Sxat0dHRDWYWlp+fD7FYrJVt1EQoFGLo0KHYtWsXli5dig4dOoDFYkEmk+HChQuYNWsWZs+ejYsXL+pNvtPQhISEwN/fH0KhEL/88kujG7E1Nnv27CEXdqZ6WFvatWuHkJAQABWB1969e1FSUgInJydYWVkBANLT05ulZK9ly5aYPn069u/fj+DgYOzbtw+fffYZjh49iv3796O4uBiOjo5aF8qXadOmDTG/unTpEm7fvk0SQr///jveeust7N+/HwsXLkS7du30Oue7vpSVlSEqKorMt/Tz89Na2GVlZZFzuUAgQMeOHWu97TZt2pAFZHl5OY4fP67/D9AMOHLkCKRSKTw9PTFgwICm3p1a8/TpU2zatAljx47FDz/8QGSZTk5OmDhxIn744QdMmTKlylE3QMV5n1Ew6TtIBioCjSdPnpBzr0QiwfTp06FQKLB161aiBmsMUlJSsHDhQvTp0wf9+vXT+fWPHz8mVTnN9UdTIRQKMXr0aOzZsweDBw8m64iMjAwsWLAA+/bte2NUHwkJCcQp3tHRUWtkWn05ceJElQklqVSKtLQ0sFgs4g5eV+zt7eHl5QWgwoH9iy++gIODAyZOnFiv7dZGbl2X74CzszPmz5+P9evXIzY2FjNmzKhSUaVSqfD06VOo1Wqw2WwyzulV8Hg8fP755wgPD8dff/2F+fPn4+7du4iOjoZSqQSXy0Xr1q3h7e2tc1L3Zfz8/EiboD7NOCnayHW41ZUmlVu/TElJCdatW4crV65gzJgxZMRIcHAwgoODER0djQsXLuDq1atNMjOQmWMK6B4ki0QihIeH4+LFi6TS1Bi0aNECYWFhiI2NxfTp01FaWgpvb28AFX/vhuxxKi8vh729fSUXXGdnZ7z33nvo2rWr1skoIyMDp06dwsWLFxtk8dQY2NnZAahYqN26dauJ96bhSUpKwrlz59CnTx8YGRlh/vz5mDNnzisvkkZGRpg8eTJ5/Mcff6CgoICMzgIqes+bk2GTgYEBQkJCMGDAADg7O+PSpUuYOXNmpSA+JiYGWVlZEIlEcHd3r7Z3SrMypDlKTiqV4tKlS7h06RJsbGzw7rvvYurUqZDJZDh16hTOnz9PDF6akpKSEjx9+hR+fn5a8migQi538eJFvPvuuwCAd955p1ZSUT6fj2nTppHH+/bte+2Mf2qLVCrF06dPERgYCGNjYwiFwtfqvFdcXIyff/4Zv/zyC4KDgzFgwAAEBQXB0NCQtMw8ffoUv//+O65fv06SaYyjrkQiabCZxoz8umXLlmRaw+rVq9GvXz8sXboUhw4dajSfiPT0dCxbtgzLly9HQUGBTgtmuVyOJ0+eoHXr1rCxsYGtra3Oo9T0gb+/P3r27InOnTtrBUYymQwnT57E0aNHX6s5zrXl119/JU7dQ4cOxZ07d/Sy3SdPniAhIQGDBg3C0aNHyc8VCgU4HA7Ky8thYWFRrQv2qxAIBKSwJJFIEBkZCZlMhvnz52u1sdWF6oLk+laSx40bh6ysLEyYMOGVPgfl5eXIz8+HpaUlMYqrCT8/P0yfPh2FhYWYPn261qzi/Px8REREwN/fH4aGhrC1tYWlpSWePXuGjIyMOikBP/zwQ3L/xIkTOr+e0nxoVkEyw40bN3Dr1i306NEDH3/8MWxsbABUnKj9/f3xxRdf4Nq1a7h+/XqDVkJfxtXVFUDFbFRdzEoMDQ0RFhaGuLi4Wjve6oNWrVph4cKF+Pnnn7WqMcyw+IauzjILPi6XCz6fDzs7O4wYMQJvv/02eY5arcbt27fx119/1dstvDnAfFcZs6n/Anv27IG/vz+cnJzg5uaGiRMnYvv27TW+ZtSoUaRaHB0djcjISAAVs1PLyspgZGTUbGanW1tbo3///ujduzcKCwvx119/4e+//67RNffs2bOkl7BHjx5VBslMZUipVCI6OrrK7WRnZ+PHH3/EsWPH0LFjRwwcOBCffPIJ/v77b/z1119NbmiVm5uLnJwciEQiWFtbQyaTgcfjwcTEBFFRUcjOzoaNjQ2CgoJgbm5e43mTx+Nh8eLF5BiKjIx84+dKaprjWFtbv1ZBMgMz//Tu3buws7ND37590atXL5iYmMDHxwc+Pj5ITU3FsWPH8O+//xLJs776kauDub6xWCxionj69GnExcUhLCwMlpaW2LdvX4PuA0NMTAw2btyI2bNnY8mSJXj69GmtX8sEyQDg4uLSKEEym82Gh4cHgoKC8M4771RSCCkUCpw+fRrHjx9vtiar+uDOnTtIS0uDo6MjWrVqVS+zqJc5evQo5s+fj99//10r8IyPjyeuyy1btqyT4sLBwYEkoJgAGag45up73Gle9zRVgvU17lq2bJlOz8/IyIClpSX4fD74fH611+P3338fI0aMwKFDh/DHH39UGfSWlpbizp07cHV1hZOTE7hcLuzt7WFnZ4f4+Hidiklubm4IDg4GUHF+ZyYHUF5PmmWQDFRkgi9evIh//vkHvXr1wqBBg+Dk5ASgInv17rvv4t1330VxcTFKSkrw/PlzpKamori4GKWlpSgpKSH/isVilJaW1ksGJBKJiDRGV8OuadOmoby8HN98802d319XOnfujBkzZmDnzp2VxvMwA9wbWr5ZUlICtVoNJycnDBw4ED4+PuR3paWlOHXqFM6cOfNG9C8xMAv8N7X6VRVSqRSrV6/G5s2bwePx0KdPH0RHR1fr1Mzn84mcViaT4aeffoKxsTE4HA6MjY0BVCwUmroy0aZNGwwePBht27bF7du3sWbNmlqbE129ehVTpkwBi8VCq1atKv2eMR4BKhbQr/qsSqUS165dw7Vr19CiRQsMGDAAGzZsQFxcHP7880/cvHmzwapyryI+Ph7t2rWDoaEhWCwWysrKSG/XpUuX8NFHH4HFYqFDhw7Vmt9wuVwsWLCAVG1KSkqwbdu2xvoITYZmkGxra9vsDNt0JTMzE/v378fhw4fRpUsXDBkyBO7u7nBycsKsWbPwySefIDo6Gg8fPmxwp2Y2m02uc5oL4/j4eDLL3MzMDFu2bGmUY+fWrVv4/vvvsWjRIkybNq3WiXbN9YYu7SxVwWKxiGrBxMQEQqFQ62ZnZ0dMBBnTIU0kEgkuX76MEydOvFHX7Zr4/fffiepp1KhRCA8P18t2IyMj8ezZM4waNQp79+4lP1epVHjy5AmCgoJgYGCAFi1aENl3bRAIBHBwcIBKpUJSUpLeiyG1qSQ3huRecz+Ywo8mbDYbEydORMeOHTFv3rxK51aRSAR7e3twuVywWCyoVCqUl5fj+fPnsLKygqmpKVgsFoKCghATE6NVfa4JzRarn3/+ucmuy/8FGqOxo9kGyQxMxvL06dPw8vJCz5490bVrVxKwFhQUwNXVtVb9GzKZDKWlpVAoFFAqlVCpVFAqlcjPz4eJiQlUKhW5yWQySCQSlJWVIS8vD9bW1rC0tNTZ1bp79+5o06YNpk6dWueZw7oyYMAAjBkzBmvXrsXdu3cr/Z6pvL8sg9Y3LVu2xMcff4w2bdpAoVCgqKgIxcXF+PXXX3Hq1KlGnV/ZGPD5fPI3/a8sIBhSUlKwY8cOzJgxA0BFYigzM7PKikmPHj3IxfXSpUuQy+UwNDQEj8cjvYq1vSDpGw6Hg5CQELz33nuwsLDA6dOnsWPHDuTl5em0HYlEgqSkJLi7u8PV1ZXISxk0+wt1VVA8e/YM27dvx/79+9GrVy+MHTsWEyZMwOnTp3H27NlGr+zI5XIkJSWR/jdzc3OUlZWBy+Xi0aNH+OijjwCAJDmrwtramiTtysrKEBYW1iSy0sZG8zxhYWHRhHuiX+RyOf7++2/8/fffaNeuHUaMGAFvb2+4uLjA19cX7777Lr777jucOXOmwa6Lmkmbl6tHmZmZmDt3LpYuXYolS5Zg9erVdZ5JqwunT5+Gr68vpk+fjqVLl9bqNcx6QyAQYMCAAbC0tASbzSZVNCMjI3A4HLDZbLDZbBQUFMDGxob8jMPhgMPhgM/nkyTkq9A89tRqNSIiInDx4kXcuHHjtfEH0RcXL17E8OHDYWVlheDgYPj5+dVrRq8m3377LbZs2YIrV65oKaekUimSk5Ph4eEBc3Nz8Hi8Wv/dmbUxm82uk1T7VTSU3FpXNEdAMkaADIaGhpg8eTJcXV0xZ84crfOsgYEBfH19weFwqjTyE4vFJGkvEAhILFAbvLy80LlzZwAV0wEuXLhQl49GaUY0+yBZk9jYWMTGxmL37t0ICgpC69atYWpqCnt7e60DtDp4PF6VCxEDA4MaM7RFRUVwcHAgF6DaLuCtra3x5ZdfYuPGjY0mvf3kk0/Qr18/LFq0qFq5qlwuB4vFqtZQq760atUKI0aMQOvWrWFgYAClUgmJRIKffvoJP//8c5NXCBsKzQXI6yibrC+XLl2Cj48P+vbtCwMDAyxevBhz586tlFTq378/uX/q1ClwOByIxWKoVCoUFhYiJiam0R3BBQIBevfujSFDhkAmk+HXX3/FxYsX65URj46Ohru7O1gsFnx8fLTmCdfXBBCouJj/9ttv+P3330lP6PDhw3H9+nX8+eefjeoKnZmZCR6PBzc3N6LeYbPZWr1iNQXJX3zxBYKCgmBnZ4epU6c2q170hkTzPFHbAOZ1g5FiBwYGYubMmXB3dwefz8fEiRPx/vvv4+eff8bZs2f1Xn1irm/VbbeoqAgLFizAwoULsXLlSoSHhzfKHOLvvvsO27Ztw4ABA2o1Hzs9PR3l5eVQKpUICgqCvb09srKyqjUsSk1NrfFYqw1Mxfjx48e4d+/ef0oZ9TJyuRyHDx/G9OnTAQBjxozBvHnz9LLt9PR0HD16FNOnTyfmcgxZWVlwc3MDm82GnZ0dkpOTa7VNJnCVy+UNUsWsbgRUQ8xJronqgmRnZ2fMmTMHJSUl+PrrrysFuG5ubkTpVFZWRtYeTCKJQSaTkQkO7u7uePDgwSv36bPPPiP3f/zxxzfGxK65ogBQm5VifTSzr1WQzCCXy3Hr1i1ijMRisWBnZwd7e3sYGxsTGVFVciJjY2NwuVytLCtzMqnOdp/P58PU1BR8Ph/m5uZ48uTJK/eRxWJh1qxZ+Pfff/Vm9vAqpk6dirZt22LevHk1jsxhKrhsNhtGRkZ6y6C3bdsWH330kdbYroyMDDx69AgRERHIyMh4YwNkQHuR+6a7WlfHrl27YGdnh8DAQBQUFGDp0qWYM2cOWXz6+/sTg6cnT57g2bNnsLKygq2tLfLy8pCQkNColQpLS0sMHjwYffv2xbNnz7Br1y7cunVLL0H648ePyfx3Pz8/rSBZMylX395rzZ5QBwcH9O/fH+Hh4Xj+/DkOHz5M+r0bmuTkZLDZbNjb20MqlUIulyM/Px/l5eUwMjKqVu1jb29PkgYJCQlaJmZvOprniVeNTnrdSU5Oxt69e+Hm5gZ/f3/4+PjA0tISEydOxPDhw/HLL7/g9OnTertGMH/PmhRL5eXlCA8Px4wZM7B+/XosXLiwwVVAEokEmzZtwtKlSxEREfHK8XYlJSUoKCiAv78/rKysajQTUqlUUCgUkEqlUCqVRDGnUqlQVlZG2tCY28uP8/PzkZKS8kZfp+vC33//jffffx9OTk7w9fVFu3btqlTp1YVff/0VnTp1wqRJk7RaTBQKBXJzc2FjYwMbG5taB8nMGlYziNQntRkB1RjBoeb5UiaTgc1m47333sNHH32EP/74A4cOHaqUJDA2NibJpczMzGqvvQYGBqTAwyhOX0WnTp3I2jctLU1vc7UpTctrGSS/jFqtRkZGht4kmhwOBwYGBuDz+RAIBBAKhRg8eDCpgNna2r5yYTt06FCYm5vXWlJVX8aPH49WrVph7ty5ZEZkdTC9wiwWC+bm5vX+u7Vv3x4jRowgckugotfu+PHjuHjxIpycnODo6AgjI6NK/WFvEkZGRigsLASPx/tPVpKBit7Z1atXY86cOWRkRlhYGL7++mtIpdJKVWSgQnKal5fXqN+LFi1aYNiwYejSpQvu3r2LsLAwncx0aoNmMo0ZB8HAyLzEYrFes/3p6enYs2cPDh8+jIEDB2LBggVISkrC4cOHqzUH0yfPnj3D8+fPtf4vU1NT0bJlS9ja2oLL5VaS13766aekp6yxHIebC2KxGGVlZZDL5TrP+3zdEIlEkMlkePLkCX744Qd4e3vjo48+QnBwMMzMzDB+/Hh8+OGH+O233/Dnn3/Wqx2Hy+WSY+xV1WGFQoENGzZg8uTJWLZsGUJDQxv8/B0dHY0//vgDc+bMwaxZs2oMaFgsFjF1u3PnDsLDw1FaWkrawcrLyxutleu/ikqlwsGDB7FgwQIAFecsfQXJSqUSq1atwpw5czBixAgtt+vS0lLY2NjoNJKIUe411HeiuVSSTUxMIJFIwGKxYGVlhenTp8PIyAhff/11tetzW1tbsFgsyOVyJCQkVLttuVyuU6DP4XAwduxY8vj777+nvchvCM1mTnJzQqlUory8HAUFBUhLS0NMTAyuX79OXAFfNZfNxMQEH330EbZt29YoGdkhQ4agR48eCAsLe2WADFQsCpjPUp8+uE6dOuGbb77B4sWLSYCckZGBLVu24IsvvsDZs2ehUCiQl5cHNpsNExOTKntA3hRMTExgZmZWqf/0v0ZZWRl27NhBKjKenp4IDQ2FhYUFOnXqBKBi4Xrt2jXymsYKkNu0aYPw8HBs2LAB5eXlmDp1KlavXq33ABmoGC3B9DJrjkcC0OAOv2VlZTh+/Dg+++wzREREYNGiRVixYoWWeV5D8fL/JSO5ZrFYldpaOnfujC5dugCokL/+9ttvDb5/zQmJRAI+nw+RSARzc/Om3p0GxcbGBjwejxwTMTExCA8Px6xZs4gqzMTEBJ9++in27duHjz/+uM7VdTMzM1JRq61B1s6dO5GSkoLFixfXe05qbTh8+DD4fD7eeeedGp9nYWEBLpcLmUyGiIgIREdH4/nz58jJySEeK5SG58aNG4iLiwNQIdkNCQnR27bz8vKwc+dODB48GAMHDiQ/Z/xxdAk62Ww2BAJBg7XTNZdKsqWlJSwtLdG/f39s2rQJERERmDFjRo0FLLVaDblcrvfxc/379yfXtkePHv2n1FBNiUyHW12hQXIt0TSyYByMq+PDDz9EdHR0o1RuQkJCMHLkSISHh+tk0pCbmwuxWAw+n1/J9OBVeHp6Yv369ViwYAHc3d0BVBg3bdy4EZMmTcLFixe1TkAlJSXkQl7bwe+vI5oLuv9ykAxUXPSXLl1K5vm2b98e69atI9Wyc+fONdrijsPhoHv37tiyZQvmzp2LJ0+eYPz48di5c2eDG4QxQbDmYgIAhEKh1u8bColEgqNHj+Lzzz/H48ePER4ejvDwcC3VR0OjKSfV7JX08vLCrFmzyOPDhw83inlSc0Jz3vWb2pMMVFSRmWPg5aA1Pj4eK1euxFdffYWrV69CrVbD2NgYH3/8MXbv3o1+/frpfI0yMzODWCxGYWFhrb9TarUaGzZsAACEhobq/J66olQqcejQIYwcObLGoFzzmvlfMLNrzhw4cIDc/+STT6p0Va4rycnJCA8Px6efforu3bsDqEgs8ng8nUxWGVVCQ31/m4O7tZGREfr06YO5c+dCKBRixowZOHDgwCvfl8vlwsDAQK+TXUQiETGnBNBoY+UojQMNkmtJZmYmkRLWtJhhMluaJ9OGIiAgAF999RXWrl2rs9FNQUEBjI2NIRAIiInBq7CwsMDMmTOxceNGeHt7A6iQV65duxZTpkzBP//8U61sjLm4m5ubN/jio6nQ/F5oLn7/qyQnJ2PlypUkGA4JCSEX+8aYf8vn8zF06FDs3r0bH3/8MU6fPo3x48fjp59+ahSDHgBEScLj8WBlZQULCwsYGxuTi3RDB8kMYrEYR44cwWeffYa4uDisWLECYWFhaNmyZYO/d1XmXTY2NloVu/Pnz7/xM5GrQjOZ9iYHyZrz46ur7D579gzr1q3DlClTcPnyZajVapiYmGDSpEnYsmWLltldTTDyZGNjY52PL7lcjuXLl8PBwQETJ07U6bV14cqVKygpKUG/fv2qfY6VlRVSU1Px7NkzpKSkNPg+UaonIiKCeDzY29ujV69eet1+bGwsVq5cicmTJ6Nz587k/KhL1ZOp9HI4nAaZYKJQKMg6r6oguaED5KCgIPzvf/9Dp06d8OOPP+Lrr79+ZV8/A1ORFwgEeguUJ06cSJRhf//9d40ybop+ketwqytvdhOUHiktLSUX3ppkLCNHjsTNmzfx7NmzBt0foVCIOXPmYN++fVqGQLWF6YXj8/mwsrKqUaZtYGCAYcOG4cMPPyQn3fz8fBw4cKDSDObqYAa/GxkZwcbGpkFGEzQ1NEiuTFRUFHbu3IlvvvkGz549Q3l5OWJjY7Xmw+obkUiEoUOHon///khOTsb//vc/vZlx6YpUKgWXy4Wbmxv27NkDFouF/Px82NnZISsrq9EVB6WlpTh06BBOnjyJYcOGYfXq1YiIiMDhw4cbbEavZpDs6OgIgUCAsLAwmJqaAqiYF7pjx44Gee/mDjOb08jI6I0NkjkcDuzs7CCTyZCWlvbK4zA1NRWbNm3Czz//jM8//xxt2rSBq6srli9fjlu3bmHv3r01Xj9EIhEJLupiwlVaWoqwsDBs3boVkZGRuH79us7b0IUDBw5g5syZOH/+fJV92M7OziS5pOsoOor+OXDgAFEcfPLJJ7hy5Yper/eRkZFYu3Yt5s+fj1OnTiEhIUGnZI9mP71QKGyQlr+ysrJKa2EmSG6ofmRjY2PMnz8fHh4euHfvHu7fv4/MzEydgvK8vDy4urqCy+XCzMys1q0Y1dGuXTt07doVQMXfnVaR3zzezJJeA8GMsrG2tq7SZMXe3h7dunXDoUOHGnxfpk6diri4OJw+fbrO2ygoKIBKpapxcda5c2fs3LkTn3zyCQwNDSGXy3Hs2DF88cUXtQ6QARBzGsaJ/E2EkdACNEjW5Nq1a0hKSiKzH+fOndsg7yMUCvHJJ59gz549cHNzw9KlSxEaGoqbN282mVmcVCqFk5MTVCoVZsyYgZEjR+LQoUMk8ywSiZpkv4qLi/HDDz/g888/R3p6OtatW4cZM2aQwFWfaI4Ac3Z2xsKFC+Hs7AygIoBevXr1f9rkhDlXaJ4/3iRsbGzAZrPB4/F0GiX0/PlzLF68GCtWrCBtEW+99RZ27NiBcePGVduvbGpqCrlcruW9oSu5ubnYvn07pk6dCktLyzpto7bcu3cPqampGDJkSJW/d3BwIPdfHqdHaXxiY2Nx5coVABXn708//VTv73Hv3j2sX78en376KVq3bq1TMCeXy0mgWt05pb5O+ozkWrOSzMiYaxO01uWYEovFuHXrFubPn487d+5AqVTqfDyUlpaSpEF9j2sjIyNMnjyZPN6zZ0+jjXqlNB60kqwDGRkZ8PT0JIHeyxKP/v374/r16w1eJe3Zsyd8fX0xderUem0nNzcXdnZ2MDExgbGxsVZg5+7ujgkTJsDf35/87Nq1a/j+++/rXAXMzMyESCQimf43bYacZr/lf3mu5MtIJBLExMTA09MTrq6usLKy0uuYFYFAgMGDB2Po0KGIi4vD4sWLG3VGcE2oVCokJydDpVKR+cEXL17Ew4cPtcZRNBVFRUXYt28ffv/9d3z++ef47rvvcPjwYZw6dUpvI0SkUimKiopgamqKLl26kNaL4uJihIeH/+cTSjk5ObC0tIS5ufkbafpnZWUFoOK7Vpee89u3b+P+/fsYPHgwRowYAT6fj2HDhuGdd97BgQMHcOHCBa0kmLW1NQwMDOrtN3Dt2jUEBwdj5syZWLRoUb229SqOHj2KmTNn4vjx45USRowhkFqtpj3JzYS9e/eiffv2MDIyQr9+/XD+/Hm9y2wTExNx+PBhfPLJJ4iMjNTp+1xaWgoLCwuYmZnh+fPnlX6/du1aODg4oLi4GGKxGGKxmIwBY+4zztHMOCTmZmpqivbt25PXMvB4PLi4uMDHxwdLly6FRCKBVCpFeXk5eDwerK2tyY3D4eDTTz9FaWkpOBwOzM3NYWBgAIFAgLS0tGrPE3/++Sfatm0LoGJdUZegNC8vDw4ODrC2tkZiYmKdr3Njxowh57aHDx/qVDSi6AcFgNr879WnGkyDZB3Q7Afy9vbWCpINDAzwzjvvYNWqVQ26D/b29pg4cSJWrVpV737G4uJiqFQqsNlsODs74+nTpzA2Nsa4cePQq1cv0rORmJiI3bt319uIjJF0q9VqmJmZvXGBpJubG4CKqjldzGhz+/ZteHp6Aqgw8aqPAoLB0NAQgwYNwnvvvYfnz59j+fLljWKWpwu2trZkdqlmNSArKwvu7u6wsrICm81usJmWtSUvLw9r165FYGAgvvjiC/Tq1Qs7d+7Um+u3XC5HmzZtwOfzkZWVBalUqrPZ4JtKUlIScR1v0aIFHj9+3MR7pD9YLBZRKtVHKqxQKPDLL7/g4sWLGD16NHr27AlTU1NMmzYNAwYMwI4dOxAbGwtzc3PyfvWVUgLA//73P2zZsgXDhg3Dr7/+Wu/tVceDBw8gk8nQvn173Lx5k/zc0NAQLVq0AFCRpP8vKy6aE/n5+Thy5AjGjx8PFouFSZMmYc6cOXp9DycnJ8TFxeHAgQOYMmUK4uPja105zcvLg4WFBUxNTWFoaFhJcj1r1ixYW1uTAolQKCT/CoVCWFhYwNnZmbhBa96Sk5MREREBMzOzSiOgkpOTUVpaihs3boDP58PIyAiGhoYQi8WIiYlBdnY2cnJykJ2dDWNjY3h7e8PKygocDgdSqRSGhoawtbXFo0ePqlzfOjg4EBVWbedGv0xmZiYcHBxgYGAAa2vrOq3VfHx8yDhLqVSKb7/9tk77Qmn+0CBZByIiIjBq1CgAQHBwMC5evEh+Z21tjcePHzf4In3SpEk4f/48Hj58WO9tqVQqpKWlkepe165dMX78eDIWqqioqMpMfV2RyWTIz8+HmZkZLCws3qgg2djYGNbW1gDQYL2drzO3b98mx05ISEi9gmQDAwMMGDAA77//PjIzM7F27VpEREToa1f1BovFIlLJjIwMrUCYCZI5HA4sLS2bzbHw8OFDTJs2DUOGDMGyZcuIeqS+RmczZ87EwoULwWKx4O7ujrVr15JxKv91EhMTyX03N7c3Kkg2MzMDj8cj5/76UlRUhG3btuGvv/4iSid3d3esX78ev/76KzFVkkgkelGrlJeXY+PGjVi1ahWuXr3aoMfpyZMnK5lotmrVirR26eOaT9Eff/zxB3r16gVnZ2d4eXmhV69eOH/+vF62bWpqSqTSjKpn4cKFmDVrVq16jHNycuDu7g6ZTAZra+tKqke5XF4v6X5gYCBMTEzAZrOJKpDH40GtViMnJwdnz56t9rUsFgtt27atJAVnijJcLhe+vr64d++eVlKIx+ORhFFhYWGdFY2lpaUoLi6GSCQi3iC6IBAIMHv2bLK/Bw8ebFCPFUr1yNHwlWTak6wDsbGxRF4SGBio5dKcnp6OlStXNuj7t27dGp6enjhy5IjetpmWlgaFQoHhw4dj6dKlsLCwgFqtxu+//46JEyfi/Pnzeu3nFIvFYLPZsLCw0KsNf1PDVJEBGiRXRVJSEpGLBQQEIDAwUOdtcLlcDBw4EHv27EG3bt3ISKfmGCADFYkzxsxE07wKgNZFVbPnsDmgUCjw888/Y/LkyeDz+di1axcGDBhQL1d6Y2NjFBcXIy8vD59//jnu3r2rxz1+vdE8XzAj9d4UNPv+9CkjT0xMxIIFC7B27VoUFBSAxWJhxIgRWLJkCaysrOpcZaqK2NhYXLt2DSNHjtTbNqvi5MmTlRzeg4ODyf26GHRSGg6lUomdO3eSx2PHjtWbr4CbmxtUKhXy8/ORnZ2NgwcPoqCgAJMmTarV6xUKBfLy8sDn8xvk+lLVrGTm+vCq0Y4CgQBKpZJUuJOTk3Hnzh3cvHkTkZGRUCgUUKvVRF0DVCTGmYSRSqV6ZYKVw+HU2HedlpYGsVhMKue6MHXqVNImFRMTgz/++EOn11NeL2iQrAMqlYpkc4VCIZGPNhZjxozBiRMn9NrDFxwcjNmzZyM4OBiGhobIysrC3LlzsXfv3iqdNusLk91n+lDeFGiQ/Go0De3Gjh1b69ex2Wz06dMH//vf/9CnTx/s3LkTM2fObPaBlmaP+suZfM3qYfv27Rttn3QhNzcXa9aswbp16zBo0CBs2rRJa+GiCxs3bkSHDh3g6+urFxnsm8Tz589JIpKplLwJsNlsUhltqArstWvXMGXKFPz9998QCASwtrbG9OnTMWjQIK25rfXlyJEjCAkJIYZzjUVQUBCAioCMqZJTmg9RUVH4559/AAAmJiYYPXp0vbfJ5XLB4XAgEomQl5cHtVoNlUqFjRs3omPHjuQ78SqYCqmRkRHpndUXmtVsTfOu2mBpaQlTU1MoFArcuXMHz549I2vNwsJCpKamgs/nw9LSEp6enrCyskJgYCBpo0hMTKx2bSoQCODt7Y1OnTqhXbt28Pf3Jwo/TXJzc8Hj8cDhcHRKIvTu3RtdunQBUFHwWbduXZOZglIaBxok68i9e/fI/XfffbfR3rdTp06wtLTUW9bKwMAAkydPxsKFC8Hj8aBUKnH58mXs37+/QYO8kpISIrtrbhW0+sDMjQZokFwdV65cIeYm7u7uZHRCTXTo0AHffvsthg0bhn379mHatGlaPXvNGU3Tu5eD5Fu3bpGMe+fOnRt1v3TlwYMHmDp1Kq5du4Zly5bhq6++0smV29PTkyxw6LFRGalUSlQWLVq0aJDZpk2BpaUlBAKB1udrCEpLS/Hnn3/i8OHDKC4uRllZGYYMGYLNmzfD0dFRL++RlZWFc+fONYiTcXX4+PgQ067Hjx/XyfSM0vDs27ePBG19+vSBl5dXvbanVCqhVCohlUq1zrMFBQX4/vvvMXr06FqdIwoKCkhBxc3NTa/KPc0gtaaRqFXBJMykUmmVwXtycjIKCwsBVHjwuLu7k/eoqS9bJBIhMDAQtra2YLPZUCqVsLS0hI+PD+ljZlCr1cQPw8bGpsppNS/j7OysNTt969atzaZN6r+KTIdbXaFBso7cuHGDXKx69uzZKNVQNpuN0aNH48cff9TLDDo2m41ly5ahb9++ACpOSjNnzsSZM2fA4XDg6+vboFLowsJCsNlsmJubg8PhNNj7NBbGxsbo2LEjgIrsYkPPyH6d2b9/P7n/5ZdfVisvbdmyJVatWoVp06bhjz/+wJQpU3D16tVG2kv90L17dwAVCpSXq94SiQQPHjwAAHIhb84oFAocP34cU6ZMgUAgwK5du/DOO+/U6rW9evUi91+3/8PG4tGjRwAqkpchISFNvDf6gangyOXyBnXstre3h729PZ4+fYoFCxbg1KlTACoWtZs3b9ZS+dSHo0ePIjAwsN5BUG358MMPyX1N/xNK86KgoACHDx8GUNFXO2PGDDKnuy6o1Wrk5uZCKpXC1tYWLi4u5Hdnz55FaWkpPvnkEwgEArRo0QJ+fn4kmfIyTFK6trJrFosFe3t7eHp6wtbWttrxoJoJG10ryWVlZcjJyamxihsVFUVakrhcLkpKSvD06dNqA2QLCwu0bt0aXC4XSqUSycnJiI+PJ2NH/fz8KrULpaenQ61Wg81mv3LKBI/Hw/z584k65dSpU7hx44ZOn5vyekKDZB0Ri8X466+/AFQcvLrIRutKp06dwOVyceHChXpvy9fXF9999x3S09MREBCAO3fuYMaMGbh37x4J7szMzODh4VHv96oOppKs6Xz6OvPOO++Qk+elS5feuNFW+iQiIoIEjEKhECtXrkRAQAD5vY2NDebMmYPVq1fj8ePHmDhxIk6fPv3aubr6+fmRIOHBgwdVGl9du3aN3GckXM2dnJwcrFmzBps2bcLo0aOxePHiGhOF7du3J8k4hULx2qgAGhtNo5t+/fo14Z7oD6bXryHl9ZrXqpKSEkRGRmLr1q3YuHEjXF1dweVyMW7cOHzyySf1fq+ioiKcPHkSI0aMqPe2XkXbtm1JG0ZOTg6R9FKaJ3/++Sfpk3Vycqq37Do1NZW4O78sF965cycGDRqEwYMHw8LCAlZWVvD09ETr1q0rtRgUFhYSV3lXV9caq75WVlbo0KEDPD09YW9vD0dHRwQHB6Nly5aViiZV9STrQn5+PlgsFkQiUZX7pFKp8PTpU9y5cwcPHz7EgwcPqjXHEolEJAhWKBSIjIzEs2fPkJWVhSdPngAAcc3WRCqV1lrVOGXKFNJq8ezZM+zdu1fnz0zRP3IdbnWFBsl14PfffycniR49eqBHjx4N+n59+/bFmTNn6h0ovP3221i2bBlatGiB6dOnIy0tjZwQgYoRV4x8xMHBocqTrj4oKysjTr9vQpDctWtXpKSkQC6X62W00ZvOunXriIOvsbExVq1aha1bt+LcuXP4448/IJfL8eWXX+LQoUMN0hffGHTv3h3GxsYQCAS4fPlylc8pKiqCm5sbnJ2d0aNHjxqNRpobd+7cwdSpU1FaWoodO3ZUWVX29vbGzJkzyeN9+/ahtLS0MXfztSE+Ph4JCQnIzs6GiYlJo/td6BsOh0MWzw31f+7i4oJWrVqBzWZDLpcjOjoaKpUKBgYGZB63t7c3+vTpg+HDh+PLL7+slayyJs6cOYO2bdtqGZLpG3Nzc8yaNYs8Pnbs2GuXJPyvoVKpsHnzZpIgHzx4sFa7TV1ggkKBQKCluMvKykJkZCR69eoFPp9PVBpmZmYIDg6uJC1mZgFzuVwEBARUeQxYW1vD19eXyLilUilZ+zk4OFRap9WnkgyAmO0xwXJ1lJWV1ahC4fF4JECWy+V4+PCh1uiowsJCFBYWoqysjExt0YRpA+Hz+dVefz/44AOyxpdKpVi3bh0thPyHoEFyHSgsLNSaizZt2jR06tSpQd7L2toa/v7+9a4if/jhh5g/fz6ys7OJ82FxcTGEQiFCQ0NJT21MTAzJrjEnXX2bPqjVahQXF0MikdTpBNucaNeuHby9veHs7IyHDx9W6j2lVKa8vBxhYWFkXBqbzYaNjQ2Aikr8li1b6jVTtakRCoUICQmBk5MTfH19K8m8OBwOpk2bhrCwMJJNNzExaZQKlT4pLS3F5s2bsWnTJowZMwYHDx7EBx98gPfffx+hoaFYv349qSZev34df/75ZxPvcfPm119/hY2NDezs7DB06NCm3p16YWxsDLFYjPLycr0HyXw+H23atEGLFi3AYrEgk8kQFRUFmUwGPp+PRYsWwcPDA+Xl5SgsLER5eTmysrLQt29fLF++vF4OxLm5uYiIiKh1q4GuWFhYYMWKFTA1NQVQkYyqaZwOpfmQmpqKH374AUDFGnHSpEmVAlZdYII9Foul9Z11dHTEzZs34eHhgcLCQty9excJCQkkQdS6dWstdU9ZWRmZd8/n8xEQEKC17rK0tCRVUqlUiocPH+LWrVukHQhApQBSM0jWtScZAJmiYmFhoTUaURcYGTUzeurx48dVBtTp6eng8/lwdXVF586dERwcjPbt26Ndu3ZaHhDMMadJx44dtVQBmzZtomu8/xg0SK4jV65cITPxuFwu5s+fj2HDhtVrTEpV5OTkYNq0aSgqKqrT65kFOWM44uzsjOPHj6N379549OgRcnJy4OLigpUrVyI4OBgqlQpRUVFaJ10/Pz907NgR7u7ueqv8SqVSCASCKk9MrxPDhw8n92kVufZIpVIsWbIEW7duRV5eHtq0aUMWs687H3/8MczMzCASiZCfn48pU6aQyqBAIMDy5ctJn25qaiqpEgwaNOiVvVHNkTt37mDKlCkICAjA6tWrMX78eC35eEJCArZu3dqEe/h6cOPGDXKe79y582ttbCgUCmFsbAwej6cXwykDAwM4ODggMDAQ7du3J9eNvLw83Lt3DyUlJTA1NcWqVavQtm1bmJiYIC0tDZMmTcKcOXPA5/PBZrPh7++PDRs2wM7Ors77smPHDpw8ebLen+llvL29sW7dOhKw5OXlYcuWLXp/H0rDcfLkSVy4cAEikQguLi5aigBd0Qz4mECOzWbDwcEBpaWluHLlCnr27AmgYqTRo0ePoFAowOFwEBAQoCXTzs3NJaaJIpEI7dq1g7u7Ozw8PODr6wuhUIiSkhJERESQ1iDNtZ5mdRaov9zawcEBZWVlyM7OrvP5oWXLlsTYLCEhodo1cl5eHtLS0pCdnQ0OhwNDQ0NSORYKhSgtLUVZWVkll2o3NzfMnj2bPD548CDtQ25mKFA7qXXNQ8lqhgbJ9WD79u3EUIPFYmHcuHHYuHEjWrZsqdf3eXnGam0RCARYunSplnHOgQMH8P3336OoqAhhYWFE0sPj8bB48WL07t2bvOfDhw/JiZrH48HJyQnBwcF4++23ERgYCD8/P7i5udXJvIypLrzOcutOnToRw6WUlJRmP5KouSGXy3HhwgUcP36c9HNFRUU18V7VDycnJwwYMABKpRI5OTlIS0sDj8fD9OnTAQCjRo0iPdgymQybN2/G0qVLAVQk28aMGdNUu14vysrKkJKSgujoaNK+IRaLsWvXLsyePbtBjZveFORyOQm+2Gx2o/hdNBTMeV0ikeg8IsXIyAjOzs7w9vaGr68vOnbsiE6dOmktilUqFeLj4xEdHQ25XA4nJyesW7eO9Cczx1ZkZCTu3LmDpUuXEsdcBwcHbNy4Eb6+vnX6bDk5OVojcOqLQCDApEmTsG7dOqKoyczMxPz586v0MqA0bw4dOkTWN8HBwfVSCDHHDiNJtrOzI6ZgBw4cQNeuXYmMuKioCBEREZDJZCgvL4ePj4/WyLKUlBQkJiZCqVSCzWbDycmJOEHL5XLExsZqBaxMwra8vLxS21N9KslsNhtCoRB8Pp8ck7piZWVFrjNZWVnVGnoBFX/DhIQEpKSk4NmzZ0hJScHz58+RnJyMjIwMFBcXV/qMZmZmWLx4MUlO/PPPPzh+/Hid9pXyekOD5HqgUqmwZcsWnDhxgpzMPDw8sHHjRkyYMKFJ5wDb2Nhg/fr1aNOmDYCKBdi6detw4sQJ8hypVIrw8HDiOMtmszF16lRMmDABbDYbpaWluHv3LiIiIpCRkUFG1nC5XBgaGsLKygrOzs5wd3fXWZLNjCbgcDh1kus0NRwOR2sRq+naTNENzV4hRur/ujJx4kSw2WyoVCqsWrWKyNxcXFwQEhKCAQMGAKg49r7++mucPXsWR48eJVnwLl26EKf01wmlUonExEQYGhqirKwMCxcuxJgxY/DXX3/VWU73X+TkyZPkGOjYsWOdA7mmhpGHMuf52iISieDg4AA3NzfY2tpCIBCQ3ki1Wo2CggLExMTgxo0bZGEcFBSEDRs2kEVzbm4u5s2bh9jYWLLd+Ph4zJ49G8nJyQAqZtquXLmyVmPoGgoOh4N33nkH3333Hfr160cCobi4OISGhr4Rqpr/Ivn5+diwYQNZE44aNQp9+vSp07aYbTAKRUZdkp+fj7i4ODx8+FBrFKlYLMaDBw+gUqnAYrHg5uamVbRJTU3F3bt3kZOTA5lMBplMRtQYL1euzc3NIRaLqyzS1KcnmcViQa1WQ6lU1unawOPxiMO8WCwmCfZXkZWVheTkZBIkP3v2DHFxcYiOjsajR4/INZjP52Px4sVkTRsTE0OVUM0Uatz1mnDgwAGEhoYSd2gWi4VBgwZh3759mD17tt4ry6+iW7du2Lp1K8kiFhcXY+HChVWOX1EoFFi/fj1+//138rNBgwZh8eLFpA+lqKgIcXFxuHnzJpFiZ2dnIz8/HwqFgrgL6tJ/U1paSi4Ar6Pkum/fvmRRFhUVhTt37jTxHr2+JCcnIzExEVlZWQ3qqt7QvPvuuwgMDARQYbry888/a/Xhzp8/nyx2Tpw4QRbxZWVlOHjwIHnerFmz4Orq2ng7rieSk5Mhl8uRl5eH/Px8vYyr+68hlUrJOBkAGD9+fBPuTd3gcDgkSNa1Eurt7Q0nJycYGBiguLgYhYWFePbsGZ4+fYpbt27h0aNHyMrKIkZW/fv3R1hYGLlWJSUlYe7cuVX2Debk5CA0NBQPHz4EUJHsnTNnDqZNm9aos6lFIhFGjBiBffv2YcaMGTAzMwNQEXjs2bMHc+fOrXOFjdI8iIiI0DqnT548mYwE1AWxWAyxWAyVSqVlLsXM+I2IiKg0PlAqlWrJph0cHODv70+uPVKpFE+ePMHNmzdx9+5dREdHVzpXM7OD+Xx+lcma+lSSlUolMeyqi9+Nu7s7SUQ/ffpUr0lYRlHJtEfl5uZi5cqV1KjrPwwNkvVETEwMZs6cif3795MTDofDQbdu3RAaGorNmzejT58+DVo1FQgEmDNnDmbPnk1OpmlpaZgzZw6paFWFWq3G3r17sW3bNlIttrGxwcaNG7X64lQqFfLz85GWloakpCRERUXhxo0b5PMyF/vaoFAoiCSpKSvudcHU1BQjR44kj/ft29eEe/P6ExsbC3d3d9ja2qJPnz6NumDVFz4+PpgyZQp5vG/fPsjlcly9ehVSqZQYpgAVi/VffvlF6/Xnzp0jY16MjIywePHiepm+NAVGRkZkwdKQc9bfdC5evIiUlBQAFUFjQ5lENRRmZmbk/1+XYI/H45HrY2RkJB4+fIiEhAQkJycjOztbayHP4XAwdepUjBo1ikifb9y4gdDQ0BpN/yQSCcLDw3Hu3Dnys169emHr1q0NPv+4devWmDt3LtatW4dRo0ZpXfdu3bqFSZMm4eTJk1R58YZw4sQJcp5n5ifravDK5/NhbGwMLpdLAkpmHQZUrDsZ01VNmFFIubm5ACrMuQIDA2t9bWW+mwUFBWRNqIlmuwGzTeZ7WxsH+fLycrDZbJ3Xw87OzrCxsYFSqURCQoLOSpWa4HA4WLBgAblOl5SUICwsjCas/uPQIFmPKJVK/PLLL5gwYQKOHTumlUX38PDAlClTcODAAcyaNQudO3fWq7NzQEAAvv32Wy352N9//43Zs2eTrOOrOH/+PBYvXoynT5/C2dkZjo6O2LhxI5FsVwXjVA2A9IvVltzcXIjFYvD5/NdqUT1t2jQSwPz777+Ij49v4j16vUlPTyfVHRsbm9fO5dnKygoLFy4ki4NTp07h+vXrACoWA8nJyRCJRODxeGCxWPj999+rzExv3bqVSMdsbGywYMGCeo+saSyEQiHatGkDtVqNiIiIGnvEKDWjUqm05nBOnDixQUcO6RuRSASxWIyioiKdRrhpXj9qWpiamJhg+fLl6N27N0xMTFBUVISffvoJq1evrlWvsFKpxLfffoutW7eSipi9vT3WrVuHESNG6NV809vbG6NHj8auXbuwYsUKhISEwN7eHsXFxVCr1bh+/Trmz5+PlStXvtaO/pSq2b9/P06dOgWgQjI9d+5cBAUF1fr1mj3JTJBcUFBAAtLExEQIBIIqDR9VKhUeP35M5NJCoRBBQUG1WqcxngLVKUE0K8lMkMwc67VZ1zJ91br09ru6usLNzQ1AhRKRGd+kD9hsNubMmYPg4GAAFZ8lLCyMJCspzROZDre6QoPkBqCgoACHDh3CuHHjsGnTJi1nQENDQ3Tv3h3z5s3DkSNHsHTpUvTr16/KGW61wcPDA6GhoVi5ciU5iYrFYqxfvx6bN2/W2TAnOjoaGzZsIL1bxsbGCA8PrzEDWlBQAKlUqvNojaKiIhgbG0MoFL42VbN3330XHTp0AFCx///73/+aeI/eDL777juSsX7//ffRrl27Jt6j2iEQCLB48WLSMhAZGYndu3drPScjI4N8vw0NDfHo0aMqtyWXy7Fy5UoUFBQAqEh8LVu27LUwtxszZgz4fD44HA4yMzNpNaye3L9/H3///TeAiu/YjBkzmnaHdMDGxoaMgNIFkUgEmUyGoqKiauWNpqamWL9+Pan2yOVyHDhwAEeOHNF5Py9cuICvvvoKMTExACoWyqNGjcLWrVvRvXt3rdm0tcXAwADt27fH1KlTceDAAaxfvx4ffPABac0BKgKP3377DZ9//jnWrFlDZsZT3ky+++47YvDK5XLx9ddf13qGMnMe5fF4YLPZkEqlpDoMVHz/09PTtQy6XiYhIQGxsbFkWkmbNm1e6e4ul8shlUqrPQ5rCpKrmzesCfOa2rTkGBkZwd/fn7QgicXiGpWRdWHatGno3Lkz2afw8HBa/KAAAF6PMsVrilwux+XLl3H58mW4ubmhT58+6NatG1n0crlcBAUFISgoCJMmTSLue8+ePSPGAoz7NAObzYarqysCAgLQqVMnslhgePToETZv3qx1ItWV7OxszJ07F3PmzEH79u1JBnTJkiVVug+XlZWRkx6Px6t1L2JxcTHkcjkMDAxgaWnZ7J08ra2tMXHiRPJ427ZtzX6fXxfS09Nx9OhRjBo1CiwWC6GhoViwYAESEhKaeteqxcLCAkuXLkWLFi0AVATDa9asIf2SDJmZmSRIVqvVxLugKvLz87Fy5UqsXLkShoaGCAgIwLp167B06VLk5OQ01EepF23atCHGNGVlZXUKWCiV2bVrF1q1agUrKyu0adMGAwcObPazpgUCAbkW6FoZFQqF4PF41Y5y4fP5CA8PJy1ABQUFWLFiRa2Ne6qCcZEePnw4PvroI7BYLDK6Z/To0bhy5QoePXqE6OjoSlVxY2NjtGjRAq6uruRfDw8PYjSmCaOwOHv2LG7evFnpHEF5s9m2bRsMDQ3RpUsX8Hg8hIWFYcmSJa8M9uRyOTHRMjY2hlqtrnRclZeXv1JGnZmZCYlEAj8/PygUCnh5ecHExISM+nwZLpcLHo9XbcBbldyaOT5eJaFm3K01X1Pd81xcXGBhYUGeX1RUhKioqErHj0AggJGREVgsFsrKympdHGKxWJg8eTIxP1MoFFi1ahVNXL0mKFC78U66zVfQhgbJjURSUhK+++477N69GwEBAejYsSPeeustLeMCZ2dnODs7IyQkhPxMqVRCrVaDxWKBxWIRKVh6erpWv3BRURGOHz+OP/74Q+eRG1VRVlaGFStWYPr06XjnnXfA5XKxaNEizJ8/v9IiX7NSLhKJdArQCwsLYW1t3ezNuwwNDbFgwQJyAbhw4QJu377dxHv1ZnH06FG4urqiS5cuMDIywpIlSzBnzpxmGRw6OzsjPDycHL8lJSVYvnw56bPXRCAQENn08+fPX3l8xsbGYsGCBQgLC4OpqSmcnZ2xYcMGLFu2rNklDVxdXbFgwQLy+ODBg6QSTqkfEokE33zzDVasWAGgwsQrPj5e71UUfcKcx9VqdbXBblWwWCySSKrqGGIqcO7u7gAqWnVCQ0PrlQxmUCqV+PHHH3H//n189tlnxAjJysoKvXv3xrBhwwBUfCaVSgW1Wg21Wk0ko9Uhk8nw4MED3Lx5E3fu3KEJ1f8wKpUKGzduhKGhIdq3bw8jIyOsWLEC69evx61bt6p9HVNwEIlEUCqVKCoqqtQj/Pfff9dKelxcXIz79+8Tx3x7e3sYGxvj0aNHlYLOgoIC2NrawtTUFFwut9J7VuVuzQSmBgYG4HA41SaCzM3NyTWwuuPXyMgIAQEBEAgEUCgUkMvlSE1NRWpqqtb1U/N5UqmUBOwSiQTPnz+vce3AZrMxY8YMYqimVquxfv163L9/v9rXUP57ULl1I6NUKhEREYFdu3Zh/PjxmD59On788UfEx8dXaZDA4XDA5XLB4XCq7JVKS0vDjh07MH78eJw8eVIvATKDWq3Gtm3byPxfgUCA8PBwMsuRQSaToaysDCqVSmcTrvz8fEgkEhgbG1eZgW8uaLqUZ2VlVZLUUvTD5s2b8eTJEwAVF9MVK1a8UhrW2LRq1Qrr1q0jAXJWVla1jrqA9ixwzcVFTcTHx2POnDmkn8zc3Bzr16/HiBEj6iQDbQgsLCy0nIVv3bqFv/76q4n36s0iMjKSTB5gEpVV9R82FywtLVFeXo7c3FydJPdmZmbk+VX1I8+aNYt4Y5SUlGDJkiV6CZA1iYmJQWhoKObPn487d+5ArVZrBR8sFotcj6sLkHNycnD+/HksX74cI0eOxMqVK3Hx4kUaIFOgVCqxZs0a4r/B4/Hw9ddfY+DAgdW+pqysDCwWi1RSq/rO//XXX0hMTKzVPshkMjx69Ij41IhEIrRq1arS2jI5ORkSiQQmJiZwcXGptB25XE7Wmi9XkoGaq8l2dnbgcDjIz8+vspLM4/HQtm1bcl3Jy8vD3bt3kZKSUml96+DgQJ6n+TuBQABfX1+tNgdNuFwupkyZQgJkpVKJ9evX48aNG9XuN6X50RgjoGgluYlJSkpCUlISfvzxR3A4HDg4OGhJuJiFOJO9VqvVyMrKQmRkJKKjoxvcWECpVGLt2rVYsWIFvL29YW5ujmXLliE0NFTrwp+eng43NzfY2NggKSmpyoC/KgoLC+Hp6Qk2mw1PT09ER0c31EepM2PHjiWzayUSCZYtW6aTIQ2l9sjlcpJhd3BwgL29PdavX98seoQMDQ0xZswYrUVNfHw8wsPDa6yaafbq6xI4MMH34sWL4evrCy6Xi1GjRiEkJATbtm0jvZRNgYmJCcLCwsj5KS4uDuvXr9drko5Swf79++Hq6orAwECIRCKEhYVhzpw5OvtNNDRWVlbEW0NX4zY7OzsYGBigsLBQS5kEABMmTECXLl0A/H+/YHUJKX3w+PFjPH78GEKhEH5+fmjbti3c3d3B5XK11FwSiQTJycmkRYoJLCiU6pDL5QgPD8dXX32FHj16gMViYeLEibC2tsb3339f6fnp6emwt7cnvcH6SAypVCrExsZCKpXC1dUVIpEI/v7+iIqKIudvRrKsOaf8ZaRSKYyMjEglWXM9aG5uXqUihM1mw9zcHCwWq9prpomJCcrLy2FgYICnT59WajnUhDEhKy0tRUREBFgsFkQiEQIDA6t8f6Ci+rxo0SK0bt0aKSkpsLe3x5o1a6gykFIlNEhuRiiVSqSkpCAlJQVXrlxp6t0hSKVShIeHY926dXBycoKDgwMWL16M+fPnE0lNXl4emV9nZ2dX60WMVCrF8+fP4ebmBktLS7i4uBDTsObAwIED8d577wGouLisXbuWOh42MCUlJVi4cCGWLVsGZ2dnMhJpz549TXZctGnTBtOmTdNSUdy7dw9r1qyp0aGTzWaTER1M24QulJaWYtGiRfj444/x3nvvkT6tdevW4cyZMzhx4kSjy9FtbGwQHh4OR0dHABXB/LJly+hc5AaCqUBt2LABTk5OcHJywqJFixAeHq6TO2xDYmxsTL7nYrGYKCBqA4/HI8mWl6vIAwcOxKBBgwBUnH/XrFlD5os3NKWlpbh9+zZdPFP0ilKpxObNm5GTk4Phw4cDAIYNGwZra2ts3rxZyyyrrKwMBQUFSEtLQ15enl7Psc+fPweHw4GTkxPMzc1hb2+vldxi1nbVuVUzQTJTSdacp2xra1vlOsnAwIAkmapTVwgEApiYmECpVNYYIDP7oFQqUVZWRvbX2toaCoUCRkZGlVRXIpEIS5cuJapAS0tLhIWFVWumSaFQuTWlVpSWlmLJkiXENMLb2xsff/wx+X15eTmZ3efs7KzTGI3U1FQUFhZCLpfDwcGh2cgJ33//fS2jrl27duHBgwdNuEf/HfLy8hAaGoqIiAjk5eXB3Nwcc+fOxZQpU3QeNVYfWrRogdDQUCxfvpwEyDKZDLt378ayZcteGaS0bt0aIpEICoUCBQUFcHR01HkONOPgO3PmTFJNZ7FY6NevH3bv3o25c+eSi35DwuFw0LdvX2zcuJEEyPn5+Vi6dKlO/acU3WHm+zILS8b5vDZOsg0NYzDHLFifPn2qk6LA1dUVLBYLKpVKS97s5uaG8ePHk8dbt24lrT8UyuvOoUOHsH37dqIu6tKlC5YvX15pSkh0dDSeP39eK8k+h8OBh4cH2rdvD39/fzg4ONSYmE1MTERBQQFkMpnWdZXD4ZCxc9W9b0ZGBtLT04kHRWJiIhISEpCTk0OcqF+GzWajtLQU5eXl1aoNmffjcDivbN+TSCTgcDgQCoXgcDjw9fUl68e8vDytZJ21tTXWrl1LrpVM2wYNkF9fGkNuTYNkSq3Jzc3FypUrScbuww8/1Bpl8Pz5cwAV2UJmEV0b1Go1oqOjUV5eDh6PBy8vryY38vrkk08wZswY8vjo0aM4ffp0E+7Rfw+xWIzw8HAtp8k+ffpg9+7d+OCDD15pnFMffH19sWTJEmzdupVIPYEK9/ipU6fW2iCvW7duACqMUPLz88Hj8Yh0X1eSkpIwZ84c7Nu3jwTnbDYbISEh2LRpE7755huMGTNGZ1+AV+Hs7IyRI0di165dmDx5MoRCIbKzs5Gamoq5c+fqVDWk1J2srCyEh4eT0Uq+vr5YuXJlk47PY7PZCAgIgKGhIfh8PqKionQa/WRkZEQ8B9LT00kVjcfjYc6cOcTw7tdff8WlS5f0/wEolCbk7NmzWL58OTmf+/n5Yf369ZV8X2rbpuPu7g4HBwfw+XxYWlqiZcuWaNOmTY3jOXNzc8Hj8WBjY0Mqr/b29mCxWDXOIzYzMyMtUUBF0Ozh4QFra2tisPcyKpUKQqEQRkZGlT4jQ3FxMWlnY9SJ1cH83UxMTBAUFARra2vymR4/fkyu0V5eXli/fj1Zl+bl5WHevHmNpkqhvL6wUD93bMp/kA8++ACjR48GUGFUMm3aNNKL5evrS+Qut2/frnVvMlBRkWjbti14PB4kEgnu3bvX6D2OHA4HEyZMQP/+/cnPfvjhB/z888+Nuh8Ubfr164dx48ZpSb9ycnLwxx9/4Nq1a3qRHHt6eiIwMBAdO3aEp6en1u+Kiopw5MgRnRIlbdq0wbJly8BiscDj8YjZyd27d7Fs2bJ67atIJEK/fv0wcOBAmJqaQigUwtPTE2KxGLGxsUhISMCdO3dw//59nXsljYyM4OzsjKCgIHTt2rXKGZwHDx7E6dOnq+37ojQcbm5uWL58Oan8pKSkYPny5cSMpzFxcXEhI9BiY2N13gcfHx/Y2NhAqVTi9u3bJEj+4osvMGDAAAAVFao5c+bodC2hUF4nWrZsiSVLlsDMzAxAhXLvm2++0Unqb25ujlatWkEmk0EikYDNZkMkEkEsFkMgECA7Oxvp6emVev4dHBzQsmVLqNVq0s7k7u4OR0dHFBQUVDn2E6hQ1tnb26OkpASjRo0Cm83GsWPHwOPxkJGRgS+++KLK17311ltETaVQKCCRSFBcXAyxWIzc3FwolUpYWVnBz88PQMV1vjp1ipubG1xcXGBoaAiFQoHCwkIUFRUhMTGRPL9nz56YPHkySbilpaVhyZIlzXJqBqV2mJiYoLi4GMdEIihe+j5XBdfEBMOLiyESiSp9/18FDZIpOsNisbBy5UoEBAQgJycHDx8+xLZt2wBUuBq2a9cOLBYLKSkpSEpK0mnbFhYWCAgIQFlZGeLi4qp0Om0oLC0tMX/+fNJbBwD/+9//mv1s0v8KpqamGDVqFPr06VNJQhYXF4fr168jIiIC6enprwwKmd55V1dXtGzZEh07dkT//v2hVquRlJREqmE5OTn45ZdfcP78eZ36waysrLBlyxZS5Tt06BD69u0LKysrqNVqLF68GJGRkTr+BSpjYGCAmTNn4osvvoBAIEBeXl6VTqdFRUVIT09Heno6cnJyKvVHGxsbw9nZGU5OTlpj6TRRq9W4f/8+jhw5Uq/ZtJT64+TkhBUrVhCjLLFYjG+++abGcTL6hs1mw8/PD+bm5sjNzSWu9LXF2NgYQUFBYLFYeP78OVEitWvXDqNHj4arqyvkcjlmzJjRoEZdFEpz4GWvBwD47bff8MMPP9RqrrazszPc3NwAVLTBFBQUwMDAALa2tlotPhKJBFlZWSgsLISBgQE8PT1haGiIkpIS0k7WpUsXcLlcJCQkVOvBsnPnTjg6OkIsFpPWu3Xr1pERamPGjKlyHKBAIIC3tze5NsrlcqIKUygUyMzMRFpaGpydneHg4ACVSgWpVIq8vDySKBMKhRAIBGS8okAgQHl5OR48eEBaAjkcDj7//HOSbAOAqKgorFmzhrrNv+bQIJnS7LGyssK8efPg5eUFFouFTZs24fLlywAqpC12dnZQqVS4ffu2zmYTQUFBEAqFRDLTGLRp0wZz584l1RmFQoFvv/2WSvyaIS4uLhg3bhyCg4OrfQ4TFDLZYs1RalZWVnB0dKwk127ZsiWRKsfFxWHHjh04fvx4rRYomrRq1QpTpkwhc8zv3LmD5cuX48MPP8Snn34KoKJSMGvWrHpV/8zNzTF16lS0b98eQEXQkZmZiZycnGrlbnXh8ePHuHr1Kq5du0ZnIDcj7OzsEBYWprWo/vnnn3Hw4EGdXNTrClPtUavVePDggc6qAn9/f1haWkIul+P27dtQKpUwMzPDtm3bYGpqiqysLJw4cQJnz55toE9AoTQvBAIBvvrqK7z99tvkZ7GxsVi7du0rK59cLhft2rUjbtRM8JmVlQWZTEYc5DVRKpVEYh0ZGUmKEl26dAGbzUZcXFy1cuvDhw/DxMQE2dnZ+PzzzwEAI0eOxEcffQTg1QUGc3NzGBsbw8jICKamplqjElUqFeLi4mBmZkZ+/zKM+zYjx5bL5bh58yaUSiVEIhHmz5+PgIAA8vy//voLe/bs0fl6Tml+0CCZ8lrQuXNnzJs3D0CFC+NXX32FrKwsGBoaon379mCz2cjOzsbTp0912i4j4VMqlbh+/XqDSq6NjY3x6aefol+/fqSylp2djTVr1jT5yCFKzTg4OODtt99Gly5d6h0UqtVq8Pl8mJmZoaCggPQ63blzB1evXsWzZ8+QkpJSreTTyMgIgYGB6N69u9YCJzs7G9OnT4dYLAaLxcKiRYtIUFtYWIjNmzfrbAZnaWmJkJAQjBgxQmthcf78eezYsQNKpRIWFhYIDg6Gj48P7O3t4ejoWKte5ZKSEqSmphIVyM2bN0lmntL8MDIywldffaXVNx8fH48dO3Y0+PmLSYZKJBKdDbUYaSgAJCQkkL72sLAwkvy6ffs2VqxYod+dplBeAwYMGIDPPvuMSITFYjE2b978Svk1Uzk2NzeHSCQiAXBhYSEePXoECwsL2NrawsLCAmw2G2KxGHw+HzExMVpBeOfOncHhcKoNkg0MDEgL2pMnT8g60NnZGdu3b6/089rA5/Ph6OgIOzs7MiIqNTUVarUaTk5O4PF44HA4ZL8LCwshFothaGgIT09PqFQqXL16Fe7u7li4cCHpT1YoFNixYwcuXLhQ632hNG+YIPmISAR5LYJeAxMTjKRBMqUpmD59Ot59910AwNOnT7FgwQIolUq4ubnB2dkZSqUSsbGxOvV/mJiYoG3btgCA+/fvN1jfY48ePTB+/HitLOWdO3ewefNm2mv5mmFnZ4cOHTrA1dUV9vb2cHBwIFLUl1GpVEhLS0NycjK5RUdHo6SkBEOHDsV7771XpRkS87qysjKoVCqoVCoIBAIYGhrC3t6ezIZk+ipjYmKwZcsWLakon8/Hhg0btPp8IyMjcebMGTx+/Jg4xGsiFAphb28PX19fdOnShcjZGAoKCrB9+/ZXLqCMjIzIfgL/P3sdqHDsTk1NpTK015RBgwZh/PjxZFGsVqtx+vRpHDx4UCcjLV1o164dBAIB0tLSkJCQUOvXGRgYoHXr1jA2NkZZWRnu3bsHlUqFgQMHkmkChYWFmDp1Kv0+Uv6zeHh4YN68ecTYDgB+//137N+/v1bVUDabjZYtW5LXawa8BgYGCAgIAJfLhYGBASQSCR4/fkxUf2+//Ta4XC7i4+OrnHlua2uL3bt3AwCuXr2KdevWkd99++23cHFxAQCMGzdO5ySrkZERAgICIBAItFQm1eHn5wcrKyuUlZVBIBBg2rRppJqen5+PVatWUYOuNwwaJFNeG/h8PrZs2UJOxOfOncO3334LNpsNX19fmJqags1m4969e8Sx8FWwWCx07twZbDa72pN0fQgKCsKIESPg6+tLflZeXo7Dhw/j999/1+t7UZoOQ0NDWFhYQKlUat0kEkmNF11DQ0P07t0bw4YNq7Y/VxOZTAY3Nzc4ODiguLgYd+/exf79+3H+/Pkqn29qaooZM2ZUKRcvKipCcXEx1Go12Gw2kaRVx99//43du3fTpA4FXl5emDZtmtb4laKiIvz88884c+YMysvL9fZeXC6XKCaePHmiUxK0devWMDMzQ3FxMRISElBSUoI2bdpg6dKlJMhfunQp7t+/r7f9pVBeRwQCAaZOnaqlFImLi8PmzZtr3affunVrGBgYgMPh4P79+2CxWPDx8YG5uTkJJmUyGeRyOZ48eYLCwkK0a9cOXC4XycnJVa6//Pz8sGbNGgAVgfvevXvJ70aMGIFRo0YBAPbu3VunNZVQKETbtm3BYrGQmppapc8GkwQwMzODra0tQkJCtBLIMTExWLVqFW0RegNhguQfdAiSx9AgmdJUeHl5Yc2aNUQaxLhB8/l8BAUFQa1WIz09Hc+ePav1NgMDAyESieok164KNpuNzp0744MPPiDmFgzXrl3Dnj17qKyUogWHw0GrVq3g5uaGFi1awM3NDU5OTuR7DlRIucRiMdq0aQO1Wo2CggIMHjy4VhWw3r1747333oODgwOEQiGp8Kanp9cYxD9//pz0CFNDI4omHA4HgwYNwsiRI7Wc4MViMf766y+cPHlSL9VZTbn07du3ax2Am5iYwM/PD4aGhkhMTERqaipcXFywbt06MvP5t99+w759++q9jxTKm0K/fv0wYcIEcu1RKBQ4ceIEjh8/TpRL1SEQCBAcHAwWi4X8/HwYGRkRf46MjAyUlZXBw8MDbDYbarUasbGxcHNzA4/HI8foy4SEhGDu3LkAgH379uG3334jv3NwcMB3330HoKKfes6cOXX6zJ6enjAzMwObzUZERITWOcbExATe3t4wNjbGW2+9hXfeeYdMjwAqWo927txJHfHfUBozSOa++ikUSs3Exsbim2++ISfDMWPGIDs7G1euXCEuhY6OjkhLS3vlCZ2h+MUXur4zQJ2cnNC9e3f06NGD9KgwpKWlYffu3bRiQakSpVKJhw8f4uHDh1X+nsPhkGB2woQJGDRoEICKpFFtejTPnTuHc+fOITAwEKNHj8aAAQPA5/ORmpqK8vJyqFQqMqcyIyMD6enpuHv3Lg2MKdWiVCrx22+/4cqVK/jss89IBcrY2BjDhw/H0KFDcfPmTVy+fBkPHjyos4kNY3Aol8t1qlA7OzvD0NAQpaWlSEtLg7m5OZYuXUoC5Nu3b+P777+v0z5RKG8qp0+fRkxMDEJDQ+Hg4AAul4uPPvoIISEh2LlzZ42TEiQSCdLS0uDk5AQHBwdyvGqq9EpLS0nyysPDAwYGBpUmIGii6QHCqEh4PB5MTU3B5XKRmpoKJycn4ltQF4PKpKQkvPXWW+BwOPD29kZiYiIcHR3B5/MhFAphbW2NESNGwMrKirSUFBYWYvfu3WSUFaV5Mn/+fLz33nvw8fFBWVkZrl+/3mznVtMgmaIX/v33X9ja2hL33pkzZyI3NxdJSUlwdnYGh8OBs7NzlbKZlzE2NoaJiQlatGgBFosFuVwOuVxOTtiMFJV5zPwrFAphampKbv7+/jAwMCAuwwxxcXE4ceIEbt682ehzmClvDpoBRnR0NAmSW7ZsqZOR0cOHD+Hi4oKWLVsCANavX08v8pR6kZeXh3Xr1uHIkSN4//330b17d3A4HPB4PHTt2hWenp4QCoW4f/8+cnJyUFRURKT+zPdas2f95X+ZKk9WVhbMzc1RVFT0SkdtkUgES0tLABULax6PhyVLlpCWhvj4eKxfv56ekymUKkhMTMS0adMwYsQIvP/+++BwOLCxscGSJUsQERGB77//vtoEalJSEkQiEQoKCiAUCpGQkIDs7Gzye2b8U6tWrWBkZESOweqSaEyrBYfDgZOTE7Zs2QI3Nzc8efIEvr6+sLOzg4WFBYqKijBhwgQsX75c58+rUCiQkpICMzMzWFpawszMDGq1GsbGxujevTveeustlJeXkwD5zJkz+OGHHxrMg4GiP7p164bt27fjzp074HK5WLVqFc6dOwc/P79Xju/URP7i1pDQIJmiN44fPw47Ozv06tULXC4X4eHh2LFjB549e0bG7mRlZWmdxFgsFt5++23069cPAQEBEIlE4HK5RA5UXl6OkpISrQVYdnY2bGxsarVPCoUCMpkMBgYGuHfvHn799Vc8evRI75+d8t9Gs++JqYrpgmbGvjHG91D+G6SmpmLLli04dOgQhgwZgnfffRcmJiZQKBQwMTFBt27darWdkpISLVWPUCiEkZERWCwWlEolFAoFJBIJUlJScOnSJZw5cwZFRUVa22jZsiWpPKvVaqxZswYeHh4AKs7py5YtI67yFAqlMnK5HIcOHcK///6LqVOnwsDAAB4eHmjfvj3atWuHCxcu4Pfff0dycrLW69RqNaKiomBgYACpVFrlNUYmk+HRo0cIDAwEh8OBWq1Gbm5upee5ubnBw8MD9vb24HA4pP8YADFBzcnJgYODA4yNjfHll19CKBTi559/xp07d3RKgqWkpCA5ORldu3aFu7s7WrVqhdatW0OtVqOkpARqtRrJycn49ttv9dKWR2kc+vXrp/V47NixyMnJQXBwcLMrENAgmaJXduzYAWtrawQGBsLIyAjjx49HXFwcHj9+jJycHLi4uCAxMREdO3ZE586d0blzZ8jlci0ptFKphFqthkKhQGlpab2Chvj4eFy8eBG3bt0iMwApFH2jKTnV7AWtLcysR4AGyRT9k5eXh3379uGHH35AcHAwOnXqBGtr6zp9V4EKeSYze5zFYoHL5RIFj62tLb744gs8evQIV69exZUrVyCTySAUCiEQCODo6Ih27dqR+c5isRjh4eH0/Eyh1JLk5GSEhoaiW7duGDNmDKysrMBisdCrVy/06tULMTExOHv2LK5cuUISTwqF4pU9ujKZDPfv34enpye4XC5xu2ZwdXXFli1b4O/vT/aDITExEcnJyXjy5Ak8PT1hY2MDQ0NDpKenw9TUFIsWLUJGRgYuXbqEK1eu1MqQ1djYGO+88w4GDx4Me3t7KJVKYgArk8nw008/4ddff6Wzj19zmORKVdM9akIOQPbKZ9UPatxF0TuGhob48ssv0aVLF5SXl8PU1BR8Ph8SiQQsFgsmJiYwMDAg1TOFQkEk1ZmZmSgoKEBBQQHy8/OJa69m9lEqlYLH42n9TK1WQyKREMlgUVERcnJy6MKL0ihYWlqSXso7d+7oJC8zNTXFtGnT0LFjR6hUKixatKjGHjMKRR/weDzY29trtaiYmJgQh2ng/xUOKpWK/Jz5mYGBASwsLIgU0srKClZWVigsLISlpSV5nlKpRElJCcrLy8mYNABkNvK6deuQlJTUaJ+bQnmTMDAwwODBg/Hhhx9WUjGVlZXh8uXLOHv2bK1a3TTh8XgkSHZ3d8cHH3yALl26IDMzEyEhIRAIBLh27RrOnz+P8+fPV5J6W1paolOnThgwYAC4XC5sbW21fp+YmIjHjx8jMTERGRkZpI3Ozs4OLVu2hLe3N1q0aKF1PgIqHPsvXLiAU6dO6eSqT2mesFgsnDx5EmZmZggJCanVaxjjrp0iEWS1MOLimZhgEnW3pjQ3goKCMGPGDJiZmYHD4cDU1JScCJnMX3l5OW7evIk///wTDx48qLWxF4XS3Dh+/DgMDQ3h6emJmzdvQiKRQC6Xg8PhaN3YbDa5LxAIwOVy4eLigoKCApSUlODjjz+mfVWU1xJ3d3f07NkTvXv3hpWVFbhcrtY5XyqVoqysDGq1GseOHcOJEyeoxJpC0QNMr26fPn3QokWLSr9PSEjAuXPnEBERUasqrqGhIUJCQtCvXz94enqSnyuVSqSnp+PKlSv4+eefa7VmCw4OxpAhQxAYGPjK577c2sEQFRWF06dP48aNG9S1+g1ix44d6NevH7p06UISp6+CCZJXr15dSe1QFTweDwsWLKBBMqX5wefz0b17d/Tq1Quurq5gs9koLy/HnTt3cPv2bTx8+JDOeKW8EaxYsQKmpqbw8PCo00X82LFjYLFYOHjwYAPsHYXSeLDZbPj4+KBdu3bo2LEjnJycIJVKIZFI8M8//+DcuXPUpZ1CaSA8PT3Rt29fhISEVNlSUVRUhIcPHyIrKwuZmZmQy+VQKBTgcDhwc3ODp6cnvLy8Kr22qKgIx48fx5kzZ2oVnLyMpaUlQkJCEBISohV4a6JSqSCXy8Hj8ZCSkoIHDx7g7Nmz9HzxBrJt2zYMGTIEXbt21WlELA2SKRQK5TVDJBKBz+djyZIlMDY2hkAgIGOilEolVCoVVCoVecxU1nJzc5GTk4NLly5R8xEKhUKh6AU+n4+uXbuid+/elYLSlJQUODs712o7iYmJOH36NC5fvqw35YdQKCQmYGZmZqQ9Izc3F/Hx8Xj27BnpP6a8eWzbtg3Dhg1D9+7dER8fr9NraZBMoVAoFAqFQqFQ6o2bmxuCg4Ph5+cHX19f5Ofn1xgk5+Xl4f79+zh9+rTOQQyFUhPbt2/HyJEjMWTIEMTExJCfFxUVaZmgVkdjBsnU3ZpCoVAoFAqFQnlDSUpK0jLIs7W1hbOzM/EOYPwy0tLSEBcXpzXWkELRJ5MnTwYA/PPPP1o/Hzt2LH744Yem2KVqoUEyhUKhUCgUCoXyHyErKwtZWVlNvRuU/yCMtP51gP3qp1AoFAqFQqFQKBQKhfLfgAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUKhvIAGyRQKhUKhUCgUCoVCobyABskUCoVCoVAoFAqFQqG8gAbJFAqFQqFQKBQKhUJpFCZPnoykpCSUlZXh5s2baN++fVPvUiVokEyhUCgUCoVCoVAolAZn+PDh2LRpE8LDwxEUFISIiAicPXsW1tbWTb1rWtAgmUKhUCgUCoVCoVAoDc6sWbOwe/du7N+/H0+ePMGXX34JiUSC8ePHN/WuaUGDZAqFQqFQKBQKhUKhNCgGBgYIDg7GhQsXyM/UajUuXLiATp06NeGeVYbb1DtAoVAoFAqFQqFQKJQ3GysrK3C5XGRlZWn9PCsrCz4+PrXejqGhoV6fVxU0SKZQKBQKhUKhUCgUSrNGJpMhIyMDs2bNqvVrMjIyIJPJdH4vGiRTKBQKhUKhUCgUCqVByc3NhUKhgK2trdbPbW1tkZmZ+crXS6VSuLm5gfd/7d0hjsJgFIXRW4NBk7CfGpbDGlhAFZ7U4roN0iasgx20iBnzDA4mIR1xzgLef+2n/s3m7TeXZck8zx9vFckAAAB81fP5zDRNads2wzAkSZqmSdu2OZ/Pb92Y5/lP0fspkQwAAMDXdV2Xvu8zjmNut1uOx2O2220ul8va016IZAAAAL7uer1mt9vldDplv9/nfr/ncDjk8XisPe1Fk+Rn7REAAADwH/gnGQAAAIpIBgAAgCKSAQAAoIhkAAAAKCIZAAAAikgGAACAIpIBAACgiGQAAAAoIhkAAACKSAYAAIAikgEAAKCIZAAAACgiGQAAAIpIBgAAgCKSAQAAoIhkAAAAKCIZAAAAikgGAACAIpIBAACgiGQAAAAoIhkAAADKL194Cx58MsnyAAAAAElFTkSuQmCC", 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", 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7KRQKhUKhUChV58yZMzhz5ky530+fPh0rVqzAsWPHAACffPIJ3rx5g8GDB2Pfvn011UytqHWXi0AgQNu2bQGgVI4vAISEhCAoKAgymaxCg4vD4aBv377o378/AODp06eV7pvtUKtUKp3b/fHHH4PL5eLPP/9EVlYWjh8/DnNz81K5kI6OjmjUqBGePXuGFy9e6Lyf2qZXr14AUOZoUHn07NkTALB582atltf3d2BzXP/8888yv9+9e7fGctWJPueJ5fHjxwgPDy81n70f2NJVVeX+/fv4+uuvYW9vjwEDBmDfvn3w8PDA6tWrERsbi9OnT+Ojjz7Sy0AGavYcMAyDTz/9FMeOHYO/vz9OnjxZofeaQqFQKBQKhVJ7uLm5wc7OjmgXAcURjXfu3EG7du1qsWVlU+tGMgB8+eWXAIAlS5bg1atXZH52djamTZsGhmEwadIk0nl/9OgRDh06hIKCAo3tpKWl4c6dOwCKvZmVwXqnwsLCdG6zvb09unXrhoiICMydOxdKpRLDhw+HQCAoteyiRYugVqsxdOhQIj5WktTUVGzZskXnNtQEkyZNgrW1NVavXo3NmzeTkFoW1isZEhJC5k2fPh1isRhbtmwpNSrEMAz++ecfjZAKfX+HDz/8EDY2Nrh+/Xopg3zTpk24f/8+HBwcMHToUJ22qw/6nCcWtVqNL7/8Erm5uWTegwcP8NNPP4HD4WDKlClVbt+ePXvQqlUrbNq0CWq1GtOmTcO9e/cQEhKC2bNnw87Orsr7qMlzMH36dOzevRuNGjXCuXPnYGpqWuX2UygUCoVCoVCqB1tbWwDFYqslefPmDflOG0QiEYyNjbWeRCKRXu2t9XBroDiH8fPPP8fmzZvh4+OD7t27QyKR4PLly0hOTkbbtm2xbNkysnx0dDSGDh0KExMTtGzZEra2tsjIyMDVq1eRnZ2N999/X6sRiYEDB+LKlSvo0aMHunXrBqlUCktLS6xcuVKrdo8aNQoXLlzAr7/+CqB0qDXLyJEj8fTpU3z//fdo0aIF/P394eHhAYZh8PLlSzx58gQymQwTJ07Uar8ss2bNgkwmK/M7iUSCn3/+WaftlYWpqSmOHj2K999/H5MmTcKKFSvg4+MDMzMzJCYm4uHDh8jIyMDhw4eJenfDhg2xY8cOfPLJJ/joo4+wbNky+Pn5ITMzEyEhIYiNjUV6ejq5aAcOHIjff/8dI0eORO/evWFiYgIA2Lp1a4Vtk0ql2LNnD2nb5s2b0bBhQzx//hyPHj2CTCbDn3/+qbdnVBf0OU8sAwYMQFBQEDw8PNC5c2dkZmbi4sWLKCwsxMKFC9GyZUuN5R8+fIipU6eSz2xI8gcffEDOKZuGwMLhcDBo0CCMHTsWAwYMKHMwp76cg6NHj2LTpk0AigfDZs+eXWZ75s2bV+dywCkUCoVCoVAo+iESiaBUKnVaJyEhAW5ubnrlPOtUM0rfOsnasGvXLqZ9+/aMTCZjxGIx06RJE+a7775jcnNzNZZLSEhgVqxYwXTv3p1xdHRkhEIhY2Njw3To0IHZvn07U1BQoLF8eXWSCwsLmYULFzIeHh6MQCBgADAuLi6VrseSmZlJ6rK6uLgwarW6wuO7cuUKM3z4cMbe3p4RCASMhYUF4+fnx0ybNo25cuWK1udJmzrJJiYmGuvoWyeZJSEhgZkzZw7TpEkTRiKRMBKJhPHw8GAGDRrE7Ny5k8nOzi61TlBQEDN69GjGwcGBEQgEjLW1NdOhQwdm3bp1TGFhocaygYGBjLe3NyMSiXS+dkJCQpiPP/6YsbGxYQQCAWNnZ8eMHj26zLq7DFO1Osljx46tcDldzlPJbb5+/ZoZPXo0Y2VlxYhEIqZp06Zl/lYl16toCggI0On4tKGunIMdO3Zo9awq774tCa2TTCc60YlOdKITnehk+IlhGGbQoEHks5ubG8MwDNO0aVON5S5fvsxs2LBBq20aGxtr3W8tibGxsT7HoNsK2hrJFAqlYrQ1Ot9lavscUCOZTnSiE53oRCc60cnwE8NoGskAmPj4eGbGjBnks7GxMZOXl8eMGDFCq23+v5Gcp8Okn5FcJ8KtKRQKhUKhUCgUCoVSf5FKpWjQoAH57ObmhqZNmyItLQ2xsbHYsGEDFi5ciPDwcFICKj4+HkeOHKm9RpcDNZIpFAqFQqFQKBQKhVIlWrZsicuXL5PPgYGBAICdO3fi008/xerVqyGVSrF582aYmpri+vXr6Nu3rx75wrrkJeunTUSNZAqFQqFQKBQKhUKhVIkrV66Aw+FUuExAQAACAgJqqEX6Q41kCqWW6Nq1KxiGqe1m1Cr0HFAoFAqFQqFQ6hrUSKZQKBQKhUKhUCgUSj0hH8X6WpVRsVe7Irh6r0mhUCgUCoVCoVAoFMo7BvUkUygUCoVCoVAoFAqlnqAE9SRTKBQKhUKhUCgUCoVSQ1AjmUKhUCgUCoVCoVAolH/ROdw6JSUFeXl5MDIyqo72UCgUSo2Ql5eHlJSU2m4GhUKhUCgUCkUnCgCotVhOf3+wzkZybGwsvLy8YGlpqfdOKRQKpbZJSUlBbGxsbTeDQqFQKBQKhVLH0Eu4KzY2lnYuKRQKhUKhUCgUCoVSwyhR3Z5kmpNMoVAoFAqFQqFQKBTKv1AjmUKhUCgUCoVCoVAolH+hdZIpFAqFQqFQKBQKhVJPyAdQpMVyPL33QD3JFAqFQqFQKBQKhUKh/Av1JFMoFAqFQqFQKBQKpZ6gBPUkUygUCoVCoVAoFAqFUkNQI5lCoVAoFAqFQqFQKJR/oeHWFAqFQqFQKBQKhUKpJ9BwawqFQqFQKBQKhUKhUGoM6kmmUCgUCoVCoVAoFEo9IR+ASovl9Dd1qSeZQqFQKBQKhUKhUCiUf6FGMoVCoVAoFAqFQqFQKP9Cw60pFAqFQqFQKBQKhVJPUIKGW1MoFAqFQqFQKBQKhVJDUE8yhUKhUCgUCoVCoVDqCfkACrVYTqD3HqgnmUKhUCgUCoVCoVAolH+hRjKFQqFQKBQKhUKhUCj/QsOtKRQKhUKhUCgUCoVST9A23Fqt9x6oJ5lCoVAoFAqFQqFQKJR/oZ5kCoVCoVAoFAqFQqHUE/IBFGixHPUkUygUCoVCoVAoFAqFUmWokUyhUCgUCoVCoVAoFMq/0HBrCoVCoVAoFAqFQqHUE5Sg4dYUCoVCoVAoFAqFQqHUENSTTKFQKBQKhUKhUCiUegL1JFMoFAqFQqFQKBQKhVJjUE8yhUKhUCgUCoVCqVFMTEzg6OgIY2Nj8Hg8yOVyMAyDjIwMpKWlIT09Henp6VCpVLXdVMp/EGokUygUCoVCoVAo/wH4fD68vLzg6+sLFxcXmJiYwMzMDMbGxsjJyUFKSgpSU1Px+vVrPHjwAC9fvjTYvnk8Hry9vdG8eXM0b94cbm5u5LvIyEiNzywqlQqvXr3C8+fP8fz5czx79gxpaWkGaxOlvpL/71QZjN574FRpbQqFQqFQKBQKhVJnkUqlaN++PVq3bo2mTZsiPj4e7u7uWq2bnp6O+/fv4+rVqwgKCtJr/xKJBH369MHAgQNhYWFR5jJxcXFwdHTUanuhoaG4cuUKrl+/jqysLL3aRKmfGBsb//ubL4V2RrIIQADkcjmys7N12hc1kikUCoVCoVAolHcMc3NzDBo0CP369YNYLCbz4+PjYW9vTz7n5eUhOzsbMpkMEomk3O3Fxsbi5MmTuHjxIpRKZaX7t7CwwMCBA9G0adMyjfKIiAg8e/YMGRkZyMrKgkqlApfLhZmZGczMzGBubg5nZ+dyjWe1Wo1Hjx7h8OHDePLkSaXtodR//t9Ing/tjeQfqJFMoVAoFAqFQqH8l7G3t8fQoUPRrVs38PmamZWZmZm4d+8enjx5gufPnyM1NRWFhYXkeyMjI1haWsLb2xutWrWCv78/hEIhAOD169dwcHBAXl4ebty4gQcPHuDx48dQKBRkfTMzM7Rp0wbt2rWDn58feDweUlJSYGlpCYZhcPfuXVy7dg2PHz/W2gssk8ng5eWFxo0bo23btnB2di61zJUrV3D27FmEhIToc8oo9QRqJFMoFAqFQqFQKBSt8fDwwLBhw9C+fXtwOBwyv6CgAOfPn8eFCxcQHh6u1bZEIhH4fD4KCgrQqlUrvPfee7CxsYGNjY3GcgzDIC4uDpmZmbC0tIStrS0EAgFcXV2Rl5eHzMxMpKWl4dSpUzh9+jTi4+OrfJwuLi7o0qULunTpAisrK2RlZUEmk4HL5eLBgwfYuXMnoqOjq7wfSt3j/43kGSguA1UZYgDrqZFMoVAoFAqFQqH8l2jYsCFGjx4Nf39/jfkKhQInT57E8ePHkZmZqdW2TExM4O3tDT6fDw6Hg6tXr5LvXFxc8P7776Nr164Qi8UwMTGBkZERCgsL8fDhQzg5OZFtNGzYEAUFBTh9+jTmzJlTLbnDXC4X7du3R79+/eDr60vmMwyDCxcuYOfOnTRn+R2DGskUCoVCoVAoFAqlXGxtbfHJJ5+gY8eOGvMzMjJw5MgRnDlzBrm5uVpvz8LCAo0bNwaXywXDMLCwsEBSUhIiIiKQlJRElhMIBGjZsiV++eUXmJiYIC8vD0eOHIGLiwuSk5NRVFSEpk2bIjc3F+vXr8fly5dL7YvD4cDLywsikQhGRkZ4/PixVnnOZcHhcNCtWzeMHj0alpaWZL5CocCePXtw6tQpqNVqvbZNqVvUpJFMS0BRKBQKhUKhUCj1BJlMhhEjRqB///4aOceJiYk4dOgQLly4oJFnrA1yuZwYyIWFhQgPD4evr2+pnGYAKCwsxK1bt/D48WOYm5sjMzMT3377Lfn+448/hqenJwCU68G2sLCAtbU18vPzIRQK4e3tjcePH+tlzDIMg4sXL+LatWvo378/RowYAalUCqlUis8//xy9e/fGb7/9hqdPn+q8bUpdRQntjGT94Vbr1ikUCoVCoVAolHrO2LFjwTAMWrRoUWttEAgEGDx4MLZs2YJBgwYRAzYzMxO//PILpkyZgjNnzuhsIIvFYjRp0oQYyEFBQUhPT0dRUREAkL9vw4YyGxkZacwXiUTk/4KCgjLXZVW0ZTIZ+evq6qpTuwFAKBRCIBAAKDbejxw5gkmTJuH8+fNkGVdXV/zwww+YNWsWzM3Ndd6HrrDXCjsVFhYiLi4OO3bs0FAVp9RtqCeZQqFQKBQKhUKpw3Ts2LFU7m1BQQGOHDmCgwcPIi8vT2N5gUAAhmGgUqkq3C6fz4enpycEAgHUajWePn2K3NxcCAQCFBQUVLgN1njm8Xga81k1bADIzy9bgZg1rFNSUpCXlwdbW1s4ODjgzZs3GmrZFSGVSuHr6wuhUIioqCjExMQAKDbeN23ahDNnzmDy5Mlo0KABAKBz585o3bo1/vrrLxw9erRc499QLFq0CJGRkRCLxWjbti3GjRuHjh07wsfHp9zzQtGWAminbq2/P5gayRQKhUKhUCgUSh2kYcOGmDBhAho1agSRSAQOh4O8vDxcuHABe/bsQWpqaql1OBwOfH19IZVKoVAokJKSgsTExFJeXYFAAB8fHxgbGyMnJwexsbHEO8zn84mxW14INGs8v20kl/Qkl5dnzK6jUqnw6tUrWFhYgMfjwdnZGaGhoZWeFw6HA29vbwiFQhQUFMDZ2Rk5OTlIS0sjy7x48QIzZ85E79698cknn8DY2BhisRjjxo1Dr1698Ntvv+Hx48eV7ktfTp8+jQcPHgAAtm3bhpSUFMybNw8DBw7E/v37q22/FMNAjWQKhUKhUCgUCqUOYWlpiXHjxqFz585knr29PYKCgrBw4UJERUWVu66NjY1GGLNMJoOVlRXy8vKQnp6OnJwcSCQSuLq6EoM2KSkJycnJZBtc7v974Mozkkt6Ynk8HvmsTbg1C+upfvnyJRo0aAArKyukpaXhzZs3Fa5nYWFBwqzFYjHUajVMTEw0jGR2+2fPnsWNGzcwevRo9OvXDxwOBw4ODli2bBlu3ryJbdu2aRx7dXHt2jXMmzcPHh4e1b4vStWhRjKFQqFQKBQKhVJH6NOnDyZMmKBhbMbFxeHKlSsQi8UVGsgAkJqaCrVaTQxdlUoFIyMjSKVSDfVnoNiIfPXqFV6/fq0xv6R3uLyw5JJh2OUZyeWFFZes4wwUG+n29vaQy+Vwd3dHWlpahbnVLi4u4HK5SElJgVQqhZGRERim/II9OTk5+PXXX3Hu3DlMnjwZ7du3h7W1NQCgZcuW2Lt3L44cOVKtKthsznV6enq17eO/g7bCXZzKFykHKtxFoVAoFAqFQqHUMmZmZli8eDG++OILYmhmZWXhl19+wZdffomjR4/Cx8enlIH5NoWFhaRkk1qtxpMnTxAdHY2cnBwNQ1KhUCA4OLiUgQxoZySXnF9SBbsyT7JUKoWtrS3EYrGG+nV4eDgYhoFAIECTJk3KPU4HBwdIpVJwuVwkJSWRtmqTY/zq1SvMmTMHx44dI3ncQqEQ48aNw5o1a+Di4lLpNrTFxMQEFhYWcHBwwJAhQxAQEAClUokTJ04YbB+U6oN6kikUCoVCoVAolFqkffv2+OKLL2BsbEzmnTlzBjt37iS1jl+9egUA8Pb2rrScUXR0NCwtLZGfnw97e3u8ePECsbGx4HK5kEgkUCqVFYp66eNJZtEm3LqwsBCFhYXIyMgg8xQKBSIjI+Hu7g65XI6GDRsiLCxMYz1jY2O4u7sDKFb1TktLI2HXuohh3b59G7a2tggNDcWAAQPA4XDg6emJwMBA/Pbbbzh79qzW2yqPCxcuaHyOjIzE6NGjyxyUoOgK9SRTKBQKhUKhUCjvJGKxGN988w3mzZtHDOT09HQsXboUP//8MzGQgWKv8KlTp/Dhhx9Wut38/HzEx8dDKpXCxsYGUqmUbCMnJ6dS1WvW8FSr1VrlJJf0JLOCXyqVSmcF6bi4OCQmJgIozq328PAgBriFhQUGDhwIDoeDwsJChIaGwsjIiHic31b4rggjIyMoFAps2bIFc+bMQWxsLIDiWtNffPEFli1bBrlcrlPb32bq1Kno2bMnhg4dipMnT5JBC0r9gHqSKRQKpZ5haWmJli1bwtzcHDweD3w+H0VFRYiKisLLly/pKDWFQqHUAyQSCZYuXQovLy8y7+bNm/jf//6H7OzsMtc5fPgwtm3bhsaNG1eqAh0bGws7OzsIBAI4OjqW8spWBGtUlzTS36YyT3Jlol3lER4eDolEArlcDhsbG9jY2KCwsBDOzs749NNPce3aNWzcuBEFBQUwNjYmJaMqamtJxGIx2rVrh0ePHgEAwsLCMH36dHz00UcYNGgQAMDf3x/fffcd5s+fj5ycHL2O4+7du0Td+siRI7h+/Tr27t0LLy8vrctcUWoPaiRTKBSKlkgkEtjb20MkEpFcqtevX+s0eq0PPB4PzZs3h5eXF1q3bk3EP8ojISEBFy9exMWLF2tEsZNCoVAouiGRSLB8+XJ4enoCKDbwfv31V1y+fLnC9XJycnDgwAFMnToV33zzTYUe4aKiIrx58waOjo4wNTXVqX2sOnZFxlxlOcn6ek0ZhkFISAgaNGgAsVgMuVwOPp+P5ORkrFq1CmPHjkWPHj1w8OBBSKVSSKVSFBQUaO21HjNmDPh8Pg4fPkzmFRYW4o8//sDjx48xe/ZsmJqawsXFBcuXL8eCBQu0NsDLQ61WY/78+bh8+TKmTZuGVatWVWl7lHxoF25N6yRT6hgymQxyuRxyuRwymQzm5uYwNTWFqakpKSD/tiBDSkoKoqKiEBUVhfj4+GpVGKRQtMXKygqdO3eGl5cX2rRpU6aQSHp6OuLi4hAZGYk7d+7g6dOnBrl+nZycMGfOHPTv3x8FBQV48eKFVuvZ2dlh1KhRGDVqFIKDg3H06FHcvXu3yu2hUPTFysoKbm5ucHFxgb29vcZ9xAoJFRQUICMjAxkZGUhNTYVCoUBmZiaysrKQk5ND3wmUdwaxWIxvv/2WGKJZWVmVlnUqyaFDh9CsWTMMGDAAR44cqXDZzMxMODo6QiQSQSQSaW24sp7kiozk8jzJbLh1RZ5kiURS4fcqlQrPnz+HsbExrK2toVaroVQqkZiYiIiICKxcuRIJCQmk5JMuXuRevXrh22+/LVMNOzg4GHPmzMHKlSthbm4ODw8PLFmyBIsWLapyqPSVK1dw584dTJ8+HRs2bKCh13UcaiRTykQul8PW1hZSqRQSiQRGRkbkL5fLhZmZGSQSicZ37CSTyTQ6QHFxcXB0dNRp/4WFhYiJicGrV69w584dPHr0qMJSABSKITEzM0PHjh2JccySmZkJExOTMpc3MzODr68vBg4ciKysLNy+fRtXrlxBaGhopblfJeFyuWjRogU++eQTDBw4kHQ2xGIxuFwu1Go1wsPDcffuXYSHhxPxE4lEAg8PDzRt2hS+vr7kHvT19YWvry+ioqKwb98+3Lx5s8IyGRRKVeFwOPD29kbbtm3RsGFDuLi4QCKR6LSN2NhYODk5acxTKBTIzc3VmPLy8pCbm4vMzEyoVCrymf2bm5uLpKQkpKamGvIQKf9hPvvsM/Tt27fU/I0bN2oVlisQCLBw4UL4+fmRNJm1a9ciJiamzOXd3NyQl5cHLpeLhIQEMAyDoqIi/P7771ixYgVOnTpVobFZUj1aLpdrRBd16NABzZo1w08//aSxjkgkIkZvRcekrydZLBYTo1YoFFZoiGdnZ5cKPY+MjMSaNWswZ84c/PHHH8jMzNTa4GTTlCIiIspdJjExEQsXLsQPP/wAExMTNGrUCIsXL0ZAQIBO7/OyWLNmDQ4cOIBx48bht99+q9K2/ttoK9xFPckUPeByuXB0dISDgwP5y07s6GZZlNV5qWw/uiIQCODh4QEPDw/06tULSqUS9+/fx82bN3Hv3j06+kYxOHw+H+3atUOfPn00jMySvH79Grdv30ZOTg4KCgpgbm4OR0dHODo6ahjPcrkc7du3R69evdCoUSOEhoZi69atuH//PhEkKYlAIICbmxuaN2+OPn36QC6Xo23btuTeYRgGwcHB2LFjBy5evFhujcWHDx9i//79sLS0RLdu3dC9e3c4ODgAKK7P+NVXX+Hjjz/GkSNHcOnSJZ0FVSiU8uDxePD19UX79u3Rrl27MgeTdKGsa5MNqyyL1NRUWFhYlLu9/Px8vH79utQUHR1NB2ApOjF16tQy5+/cuVMrI3ny5Mnw8/MDUCw0tW7dunINZDaXuKioCHw+H9bW1ggODkZRURHCwsKQlpYGf3//CiOFVCoVlEolxGIxpFKphpHMRvq9Tcl7SR9PckVGMofDgYODA/Lz86FSqTTUrXXh/v37+OOPPzBp0iT8+uuvePPmjVbrFRYWgsfjVepVj4uLw6JFi/DDDz9AKpXC19cXY8eOxbZt2/RqL8uhQ4cQERGBWbNmYcuWLTRCpg5DjeT/GHK5HM2bN0fLli3RvHnzCo3h8ih5Q7u6ukKpVCI2NpaM3mdnZyMrK4tMqampyMvLQ3p6OjIyMpCbm1vqocDlcmFvbw9XV1cyOTg4EENFLBajY8eO6NixIwoLC/Hw4UPcuHEDt27dogYzpUo4ODigT58+6NGjh0bpDZaoqChcvXoV165dq/AlLJPJ0KxZM3To0AEtWrRAeno6rKysIJfL0aZNG7Rq1QpRUVGIjo4m94KxsTF4PB7s7OzIKLyVlRVcXV1RVFSEgoICPHr0CAsWLKi03EdJUlJSsH//fuzfvx+tWrXCiBEj0LBhQyQlJcHFxQVfffUVRo0ahcOHD+Ps2bP0HqLoBZfLRfPmzdGhQwe0adOm3PdJUlISSaWJiopCbGxsKcOUw+HAyMiIpOWIxWJy/7CTsbExiV6ytLSEk5MTnj17BgCVendEIhHc3d1J6RiWgoICBAcH4969e7h//z6pLUuhvM3vv/+O33//vUrb6NGjB3r16gWg+NpbsmQJoqOjy13ewsICHA4HJiYmyMvLg1wuh5+fH4KDg0k4spubW6XpNGxf6u3BJxMTkzKNYHZwNS0trcJBpLI8yTwej+yvrHXt7e1hamoKhmEQFhZWpcim48ePo2PHjvjwww/xww8/aLVOcnIyXr9+jdatW+PatWsVLhsVFYWAgACsXLkSfD4fgwYNwuPHj4kYV3lUdK0wDEPy0Cl1G2okv+OIxWJ4e3vDz88Pvr6+cHd31xjtK4uUlBTExcUhPj4eWVlZGqFreXl5UCgUUCqVyM3NRadOneDv74+FCxdWua1xcXEaD3qBQAA/Pz+0b98ebdu2JQaMQCBAmzZt0KZNGyiVSty4cQPnz5/XyYig/LcRCARo164d+vbtCx8fn1LfJyQk4MqVK7h69Sri4uK02mZOTg6uXbuGa9euQSgUonnz5vj444/h6ekJkUgELpcLd3d3qFQqyGQyiEQiWFtba2zDyMgILi4uyMjIwJs3b3Ds2DFs2rSpSuFd9+7dw71799C0aVMMHjwYLi4uAIo7XxMmTMCIESNw5swZnDlzhop8UbTC2dkZPXr0QLdu3coUAyooKCCRPw8ePKgWFddx48bB0tISv//+OyQSCfGSlUwNkkgkMDY2hq2tLRwcHGBra1sqskkoFKJFixZo0aIFACA0NBRRUVF48uQJgoODkZWVZfC2U/6buLm5YcqUKeTzTz/9VKnOBKvhkpycjOTkZLi4uMDY2Bg+Pj54+vQpCgoKNMKcy0OlUkGlUpUKy3Z2di5lpJuZmZH9VlYpoaSRzN5bJe+xsiJCbGxsAIAMFleVv//+GwEBAejVq1elat8sJ0+exOjRo3H79u1KI0levHiB7du34/PPPwcAfPPNN/jyyy/Ljeii1BTaCndVbPNUBDWS3yFEIhFcXFzg5uZGRsw9PT01HlhJSUmkY65QKBAUFITIyEhiFMfHx+vkVbp37x4+/PBDkitpSAoLC/HgwQM8ePAA//vf/9CkSRN06NAB7dq1g5mZGYDiQYAePXqgR48eSExMxKlTp3Dt2jWaf1aLjB07Fjt37kTLli0rHW2taRwdHdGnTx907969lNdYpVLhxo0bOHPmTJUHXAoKCnD79m3cvn0bS5cuxYIFC9ClSxfIZDI4OTkhIyMD+fn5pMOSlJSEiIgIdOnSBU+ePEFBQQFOnTqFX3/9tUrtKElQUBCCgoLQsGFDDB8+HG3atAEAGBsbY/jw4Rg2bBju37+P06dP48GDB7WSt8xeOywqlQpv3rzBP//8gwULFiA+Pr7G20QpRiKRoGPHjujTp0+ZXpC8vDzcu3cPN27cwMOHD6s9OqFx48Y4e/asTgM7PB6PGMwODg5wdnZGs2bNSLhpfn4+GjdujMaNG6Nfv34AgJiYGISHhyMyMpJM+paDofx3kUgkmDdvHtGYOH36dKUq1kCxwZmbmwuFQoHo6Gio1Wq4uLhAKBTCz88PNjY2FXqigWIPL5um8PaAq4uLC65evaoxz87OjuQL62MIluxzlvUeYUOxyytxpSsKhQJ//vknPvvsM5w+fRrh4eGVrnP69Gn06NEDH374Ifbs2VPp8idOnIC/vz9at24NuVyOmTNnYtGiRVTf4x2HGsn1FGtra7i5ucHV1RUWFhbw9fUtpRhaFi9fvsS1a9dw//59PH/+vMo5idHR0SgqKoK7u3uFIghVRa1WIzg4GMHBwfj111/RuHFjdOvWDZ06dSIPf3Nzc4wePRqffvopHj16hH/++Qd37typssgCpX4jEAjQoUMH9OnTB02aNCn1fVxcHM6cOYOLFy9WS+c3LS0NM2fOxLfffou2bdsCAF69eoVvvvlGY7nx48eDw+GgoKAAUVFR2Lp1q8HbAhSPin/33XdwdnbG0KFD0blzZxIe16pVK7Rq1QovXrzAnTt3cP78+VoZLV+0aBEiIyMhFovRtm1bjBs3Dh07doSPjw8NDa9hfH190bt3b7Rr1w5CoRApKSnkO5VKhTt37uDSpUs1Kq4oEAjg6emJwMBAndYrKioiucglcXV1RatWreDq6or27dtrRFs5OzvD2dlZY/mUlBQ8ffqUhJFHR0cjNjaWdpgp5TJ9+nTY2dkBKK4BvGXLFq3WYwVR2XdTbGwsVCoVPD09yTN73759FW5DLBaT/5XK//e8WVlZwcHBQcOoNDY2hqWlJQBoVU2hrD5nyfunLOcJO8/CwgJxcXFV7ocqFAq8fv0aFy9exOzZs/HVV19pHGdZMAyDn376CatXr0ZoaCgePnxY6X42btyIH3/8Eebm5vDz88PQoUNx4MCBKrWdUhW0Fe6inuR3Gg6HA1dXVzRp0gTe3t7w9vbWEFqIjY0l+SNvExcXR8LGqit07NmzZ/D29q5WI/ltQkNDERoaii1btqBt27bo2bMnLCwsSGemefPmaN68ObKzs3Hx4kWcP3++0tFWyruFnZ0d3nvvPfTo0aNUrmRhYSGuX7+Os2fPkpzG6mbdunVYv349nJyc4OHhgQYNGpB7xsbGBoMGDSJtW7NmTbUP7sTExCAwMBA7d+5Er1690LdvX1haWiI1NRUNGzZEw4YNMXLkSNy5cwfHjh2rsfMEgHizAWDbtm1ISUnBvHnzMHDgQOzfv7/G2vFfxcLCAj169EDPnj1ha2ur8V1eXh4iIiJw4cIFXLlypVa8qg0bNkRWVlaZInj6wOZKA8VeriZNmsDX1xd+fn7w8PAoFaJtaWkJd3d3dOnShcxTKBQIDQ3Fs2fP8PTpU4SHh9MBWgqA4jxkdoA0JycHK1eu1PraKKuUUkJCAjgcDgYNGgS1Wg2JRFJhNB+bEqFWq5GXl0fm9+/fH3fv3tUYCGX7UAUFBTrn57ODRCUN57IM4OjoaHh6eoLP58Pf3x/Pnj3TaJeusF7vq1evQiaTYcqUKVoNoEVGRmLjxo2YN28eFi9ejOfPn2t8LxKJoFaroVKpwDAMsrOzsXbtWnz33XfgcDgYPXo0Hjx4gMjISL3bTqnbUCO5DuPi4oIePXqga9euFRaBFwqFKCwsJC/6yMhIvHr1ClFRUVUufq4NiYmJFaqKVieFhYUkD9TCwgI9e/ZEr169SEi5sbExBg0ahEGDBiEsLAxHjhyhJXDeYbhcLlq3bo0BAwbA29sbKpVKYxQ9NjYWZ8+erTavcUXk5+fj8OHD+OqrrwAAffv2JWU3evbsSZb7+++/ERsbW2PtSk9Px99//40DBw6gZcuWaNeuHbp37w4OhwMej4f27dujffv2uHXrFnbs2GEww0QXrl27hnnz5sHDw6PG9/1fwtvbG0OGDEGrVq1KeYiys7Nx+fJlnDt3rtYHHM3NzbVWstWV/Px8PHz4kHiWBAIBXFxc4OrqSlKZ3NzcSnX+pVIpWrZsiZYtWwIA0cu4cOECQkJCqqWtlLqPqakpJkyYQD4HBgZqnSIgEAhIpNzbfbn4+Hj4+Pjg/v37lRqYrFMlIyODGNJWVlbo06cPli9frrEc25eLjY3VKoWurHrnJQeVytpGYmIiuFwuGjRoAABo0aIFoqOj8fr1a73S9hQKBVQqFfh8PjZv3ozvv/8eXbt21Sqc/fr165DJZAgICMC8efMQHR0NuVwOd3d3yOVy5OTkQCwW49mzZ8jIyEBISAj+/vtvjBgxAlwuF9OmTcOsWbNon/IdhRrJdQy5XI4uXbqgR48epVQ4WfLy8hAaGooXL14gOjoaUVFRSEhIqDUZeT6fXydCIFNTU7Fv3z7s27cPfn5+JERQIBAAALy8vDB37lwkJCTg0KFDuHjxIi398Y4gFArx3nvvYeDAgSRUDCjuSNjZ2eH69es4c+aM1qIeLBwOB1KpFKampjAxMYFIJCKdAoVCgRcvXuh03127dg0TJ06EkZEROnfujG3btkGpVKJHjx4AijsU586d06mNQLHnz83NDQqFAlKpFIWFhcjJyUFmZiYyMjK08lqo1WrcvXsXd+/exd69e9GnTx/06tWL5P+3a9cOrVq1wvHjx7Fv374aGYBjcXV1BaBffhylclq3bo1hw4ahUaNGGvMZhkFQUBDOnTuH27dv1xnPqFqtrlSA0lAUFhYiIiKiVKSUlZUVXFxc4OLiAk9PTzRp0kSj7FVJvYykpCRcvHgRFy9erJVBJkrt8fnnnxND9/Lly7h3757G9xKJhIhqvf0uKfkue1tnxdfXFzY2Njh58iTMzc1hbm6ukQrBwuVyIZfLAfz/81MgEGDevHm4evUqiRDi8XhEayA3NxcJCQlaHZ8+RjJQ/G5WqVRo0KABuFwunJycYGNjg6CgIJ37Zfn5+WSfBQUFWLduHebNm4fExMRS3uGyOHPmDIyNjbFixYpSYfB8Ph98Ph+urq54/PgxAOCvv/5C+/bt4eTkBE9PT/Tt2xenT5/Wqc0UQ6CtcJf+pi41kusAPB4PrVq1Qo8ePdCyZctSL3+VSoUHDx7gyZMnePr0KaKioupUXTUHBwfcunWrtpuhwZMnT/DkyRPIZDJ06dIFffr0IR1tOzs7fPHFFxg5ciSOHTuG06dP12iHn2I4hEIh+vXrh2HDhpWqy5qQkIDTp0/rHBIqk8lgamoKiUQCKyurcjvjUqkUYrEYT5480fp+zM/Px6VLl/Dee+9BLBajVatWSExMJJ2hhw8f6mwIWltbw8vLi3RWJBIJgOLSHmwaRkmDOTMzs1JjJzk5Gbt378aff/6Jbt26YcyYMTAzMwOfz8cHH3yAHj16YM+ePTh79my1PItMTExgYWEBsViMNm3aICAgAEqlEidOnDD4vv6r8Hg8dOnSBUOHDi1V9z4lJQX//PMPzp8/XycVz1NTU2FnZ1ctgpHawqoN379/n8yzt7eHt7c3fH190aZNG3IvWltb46OPPsJHH32EZ8+e4cKFC7h+/XqVQkwpdZ/WrVujY8eOAICsrKxSBpiZmRl8fX0BFBuYqampSE9PR1ZWFqRSKbkvs7OzNQxHExMTzJw5E0eOHEFmZiY4HA7S0tLKbIOZmRkxINPS0mBiYoJ58+ahqKhIoz2urq5EUCs8PFzr+0pfIxkoFqxMT0+Hi4sL7O3twefz4evri6CgIJ3ylBmGgVKpJKr2Dx8+xI4dO7Bo0SLMnDlTq4GpEydOwMfHB/Pnz8fWrVsRFxeHmJgYWFhYQCAQaLwzi4qK8PPPP5OSU2PHjsWtW7cMotRNqVtQI7kWkUgk6NevHwYOHEi8NSUJDw/HhQsXcPXq1Tqrptm0aVO4uLjoLKBSU+Tk5ODkyZM4efIkmjZtiuHDh8PPzw9A8ctj7NixGD58OE6dOoXjx49TT1U9oTzjmGEY3L9/HydOnMCjR48q3Q7rKZbL5cRbzEYe5ObmEgNZrVYjMzMTubm5UKlUMDY2hrm5OeRyOZydnUk+ozbcv38f7733HoDi/K83b94gOjoaAoEAr1690uEsFJ8HVsCloKAAKSkp4HA4EAqFkMvlpIwHn88nir4MwyAnJwcZGRmklnl5I/dFRUU4f/48rl+/jmHDhmHw4MFk21OmTEHv3r3x3XfflenBqAoXLlzQ+BwZGYnRo0dXWo6EUjkikQh9+vTB4MGDNTxVQHGe+oEDB3Dt2rUqi+lUJ2FhYVAoFHjvvffq1MAJWyHi/PnzEAgEaNu2LXr06IFmzZoRY4LVFZk4cSLOnj2LY8eO1cmBCErVkEgkmDp1Kvm8efPmUmrOjo6O5H+2TnjJe5J975R8L3A4HMyePRshISEICQmBsbExkpOTyzVG2e0plUrY29tjwYIFePbsmUZpQSMjI9jb2wMoHlzOzMzU+jjLEu7S1kgG/j9SIy8vDx4eHpDJZGjYsKHOUV+5ublE5Awo1rWwtbXF0qVLMWvWrAqVtM3NzeHi4oILFy6Aw+FgzJgx+Oabb5CQkAALCwuNus8sT58+xfnz59GzZ09IJBJMmDABa9eu1anNlKqS/+9UGQK990CN5FrA0tISgwYNQp8+fTTyJYHikb5Lly7hwoULWtdnrS2aNWuGefPm4aeffqoXJZfYEjgNGjTA0KFD0b59e3A4HEgkEgwbNgyDBg3CwYMHsX//fhqGXUfh8Xh47733MHz4cI08fYZhcOPGDfz111+IiYkpd32BQAC5XA6pVAozMzMYGxuXEuUB/l/g5M2bN8jMzER2dnapnKNGjRrB2toatra2SExMrFRNk6Xkfe3o6Ijbt2+T2sVsWJ62ODs7g8fjQa1WIygoqJRnSigUwtTUFDKZDJaWlhCLxeBwODA2NtYogaVUKpGeng6FQoGsrCwoFAqN41Uqldi9ezfOnj2LsWPHonPnzgAADw8PBAYG4vvvv9e5U1MRU6dOxYsXL2BiYoLPPvsMnTt3rhMpHfWdnj17YuzYsaWiLp49e4YDBw5oeEXrMgzD4IcffsDKlSvB4XBw/Pjx2m5SKUrqZZiZmaFbt27o0aMH8Q6KxWIMGjQI77//Pq5du4ZDhw5RAaB3iHHjxpFc4Pv375cqswT8vzHJMAxevnxJIphYg0ytViMqKkrDwBs5ciQsLCywcuVKMvhSnlErFAphZWUFLpeLVq1aoVu3btizZw8OHz6ssZyLiws4HA5UKpXO12BVPMklef36NYRCIZycnGBlZYXExESdnBbs+7dkn3rHjh2wtLTEtGnTsG7dulI1ooHid6iLiwsYhkFubi5+/PFHtG7dGitWrMDSpUshEomQm5tbpqd+x44daNOmDYyNjdG5c2ecP3+ehGRT3g2okVyDuLq6YsiQIejUqZNGCCfDMLh9+zbOnj2Lx48f16lQ6vIYMWIEhg4dip9//hnXrl2r7eboREREBFatWgV7e3sSOsrn8yEQCPDRRx+hW7du2Lx5c6ncIUrt4ubmhq+//rpUrv7169crNI7ZsGkrKysyysyKfLCo1Wrk5OQgPT2deFgrE+J49eoVxGIxZDIZPD09ERwcrNVxJCUlkf07OjpqGLas51cbTE1NYW9vD6VSiYSEhDJDN1mF0qSkJNJeU1NTMrHKqWKxGHK5nJQoKSoqQlpaGpKTk5GWlkaeScnJyVi7di2OHz+OGTNmwM7ODiYmJpg7dy527dqFixcvat3+irh79y5Rtz5y5AiuX7+OvXv3wsvLCwqFwiD7+C/h7u6OKVOmwMvLS2P+nTt3cPDgQa3y9uoakZGRWLx4MebPn4+GDRvip59+qrMDKenp6Th06BAOHTqEBg0aoHfv3ujevTuEQiG4XC66dOmCLl264PHjxzh06BDtaNdz3N3d0bdvXwDFxtvPP/9c5nLp6ekwMTGBWq1GQkIC4uPjIRAIIBKJUFBQgMLCQo33ULt27TBo0CDMmjVLw7tZXpivvb09bGxsMHz4cKSnp2PevHllViERCATIz88n7yZ9YdtaWQmo8oiKioKFhQUkEgkaNGiABw8eaL2+UqmEWq0uNei9YcMGLF++HDNmzMDKlSvJfKFQiIYNG2rUSA8NDYVCocDJkyfB5XKxatUqHDp0CNHR0WUa7NnZ2di+fTu+/vprAMCUKVMwbdo06mR5h6BGcg3QtGlTDBkyBM2aNdOYX1BQgAsXLuDIkSNaiyTUNhYWFpg2bRrs7e0xZ84cncJM6xrx8fH43//+h71792LIkCEYMGAAeDwebGxssGjRIty7dw+bN2+uNhVVinawgxdDhw7VeAFev34d+/btK1NpVywWw9raGlZWVmV6Z4uKipCSkkI8pzk5OTqrUxYUFCA5ORlyuRxmZmZwdnau0IvNolarkZiYCHt7exgZGellJAuFQjRu3Jh81jYMWalUIjExkeRosaHTcrkcYrEYRkZG4HK54PF4ZGChqKgIqampxGBmGAZhYWGYOXMm5syZAx8fHwDFdUAdHBzwxx9/aNUWbVGr1Zg/fz4uX76MadOmYdWqVQbd/ruMRCLBJ598gn79+ml4fK5fv44///yzRlXUq4OwsDBMnz4dc+bMwbp167Bu3bo6741lRcB2796N/v37Y8CAASSqw9/fH/7+/oiMjMShQ4dw/fr1Oh32Timb8ePHk/93795dbjpKeno6XF1dwePxYG5ujtTUVBQWFpZpZLVt2xYzZszA2rVrERMTo1EGtKzluVwuBgwYgGHDhuHUqVMIDAws13iTyWQQCARlelorw1CeZHb9iIgI+Pn5wcjICE5OTlor6SuVSnC5XIjFYvD5fGLsFxYWEkGupk2bIigoCNbW1mjQoAEZKE9PT0doaKjGAMHx48dhY2ODcePGYdOmTeXq1ly4cAE9e/ZEkyZNYGdnh+HDh2Pv3r1aH3N9JzIykuj9lOR///sfpk2bVmr+2LFjsXPnTo15SqVSJwdBiTVBhbvqKVwuF+3bt0e/fv3g4+Oj8SDJzs7GyZMnceLEiWqpW1wdcDgc9O/fH2PGjMHt27exZs2aeiF2xefz4enpidTUVKSkpJT5wE5PT8e2bdtw9uxZTJ48meQst2rVCj4+PtiwYUOdEyb7r9CoUSN89dVXGrlbUVFR+PHHHxEeHl5qeZFIBFdXV1hbW5eq1ZiamorU1FRkZmbq1Rkoi/j4eJibm8PMzAyurq5QKpVa1ZaUyWTgcrkoKirS2UgWCATw8fGBQCCAWq3G8+fP9Y4+YfOY2U4cl8uFTCaDmZkZ8bzzeDxYW1vD2toaeXl5iIqKQnJyMnJycrBkyRKMHj0aw4YNAwAMHz4cdnZ2FXbI9OHKlSu4c+cOpk+fjg0bNtRZj2FdwsPDA/Pnzyfl8IDiUP9ffvml0qgHthRMYmJihbl8dYGMjAwsXLgQH330EdasWYNTp05hz549df4aycrKwp9//omDBw+iR48e+OCDD0hNajc3N8ycORN9+vTBzZs38c8//9T546EU06pVKyLGlZCQgJMnT5a7bHZ2NnJzcyESiUiN+rJo27Ytpk+fjjVr1uDu3bsANA3RsgZ4P/jgAwwdOhS7du3Cvn37Knweq1QqCAQCvQyVquYkv01GRgaSkpJgbW0NR0dHvH79Wivvdsn7w8TERONc5uTk4MCBAxg3bhy2bNlC8rTZcPbyUhtDQkJw5coVfPLJJ7h582a52gH/+9//8OOPP4LH42HYsGH/KRX7Vq1aaUQO+Pj44Pz589i/f3+562RmZmpENdXl8lnUSDYwAoEAPXv21HjhxcXFwdHREW/evMGRI0dw/vz5evXCc3V1xbRp02BsbIzvv/8eQUFBtd0krTE3NycesTt37pQ67xwOB05OTnB2doazszOys7ORnp6OJk2aID4+HkZGRpg/fz6OHj2KnTt30lF9Hfjss89IyFlJNm7cqJUQ3ciRIzFixAjyElapVNi3bx8OHDhQ6nfg8/lwdnaGvb09eUGr1WqkpaUhKSlJI2TYkDAMg9DQUDRv3hxisRhOTk6QSqWVerPY/CmpVKqTkSyVStGoUSOiQvry5UuDDrSp1Woi5hUdHQ2pVEruHyMjIxgZGaFx48ZwcnLCq1evkJGRgV27diEtLQ0TJ04Eh8NBx44dYWlpiRUrVhi0bWvWrCEdnd9++81g230X6dOnDyZNmkQ8JdbW1oiLi0NCQgJatmwJKysrxMTEIDo6uszOs5eXFwQCAYqKiuq8kQwUX7d79+7F1atX8eWXX+Lnn3/GL7/8Ui9yrAsKCnD69GmcOXMG7du3x5AhQ+Dp6YmMjAz4+PjAx8cHH3/8MU6cOIETJ07Ui9/jvwqPx8Nnn31GPmvTZ4iLi0ODBg1gbW2N6OjoUtoWPXv2xOeff44ffvhBQ4yy5ECvVCrVeNZ27twZI0aMwO7du3H37t1KU1TYa4pNR9KXqnqSWaKjo0llCRsbG60ipRQKBSmB6ObmhuzsbHKOOBwOHjx4gIkTJ5KazDk5OXj+/Hm5zh6pVAqhUIjLly8jJycHS5cuxZw5c8rsu8TFxeHw4cMYNmwY+Hw+Pv30U6J8/a7zdpQEG9J/5cqVctdhGMZAEZraloCiwl21jkQiQf/+/TFw4MBSoijJycnYs2cPbt26VS/yjVnEYjE++ugjDBgwAEeOHKl0NLIuYmFhAaB4JLGkgezo6Iju3buje/fukEqliImJQUxMDF68eIF79+4hNzcXHTt2JAJFgwYNQsOGDbFq1apySy1QNCmp7FmSnTt3VmgkCwQCfP311+TcA8CLFy+wadOmMsOZzczM0LhxY2IQqNVqxMXFITY2tkYGNVQqFZ48eQJPT0+YmZlBKpWCYZgKUxHY45fJZACKjWaxWFxhJ0UsFqNp06bg8/lQKpWIiYmp9jQNtuMRFRUFMzMzuLm5QSaTQSaTwc/PD8nJyQgLC8OJEyeQmJiIOXPmQCwWo1GjRli3bh2WLl1qMAHCQ4cOISIiArNmzcKWLVvq1bO0phCJRJg6dSq6detG5oWFheH777+HWCyGsbExHBwc0KtXLzg7O4PP5+PatWs4f/68Rl5yamoqbG1tYWFhobPiem0SFxeHuXPnonfv3pg5cyYePXqErVu31otnNis+eOPGDTRp0gQ9e/Yk9dONjY3x8ccfY8iQITh37hwOHz5scEV5StXp3bs3KbsXGhqqVQRaSkoKGjZsCKD4dy5pJA8ePBgjRozA0qVL8fTpU4312LJQPB4PTk5O5Ht/f38sXrwYBw8eRGhoKF68eFFpGxITE2FtbQ0jIyNIJBKdogQrC7fW5x2cl5eHxMREksYUHx+vlbcxJiYGjRs3hlgsRsuWLZGeng6VSkXEOlmH1dWrVxETE1PhNtmKM2q1Ghs3bsScOXOwaNEiLFy4sMx+8N9//40ePXrAzMwM7dq1g6+vr9Y6Je8KAoEAo0ePxvr16ytcTiaTISoqClwuFw8fPsS3335L6nXXNaiRXEUkEgkGDhyIQYMGlcp9fPz4MQ4cOIAnT57UUuv0p0ePHvjkk0+QkJCAGTNmaJVrWdfgcDgkb4cNvfH19cUnn3wCd3d33L59G5s2bSpXLO327dt49uwZJkyYAD6fj8aNGyMwMBCLFi2ql+ejpvj999/x+++/67WuXC7HggULSL4twzDYtWsXDh06VOYLzcbGBg0bNgSHwwHDMEhISEBMTIzBwqm1RalU4tmzZ/D29iYv9qysrHI756yRzKqr5+XlkZzgsuByufD29gafz4darUZERESNd/zT09ORnp4OKysruLq6wsjICFZWVhAKhXj69Cnu37+PuXPnIiAgAObm5rCxscGaNWuwZs0aPHz4UKt9VHTtMAwDT09PQx7SO4WxsTGWLVsGDw8PMu/48ePYvn17uR3VBg0aoGfPnggICEBmZib279+PCxcuECNZn05zXeDcuXO4e/cuPvvsM/z66684ePAgDh8+XOPPBX15+vQpnj59iiNHjmDIkCHo0qULuFwuRCIR3n//ffTr14+ENNLyUXUDIyMjjBw5knzetm2bVuuVd2+OGTMGvXv3xoIFC8ocqGIYBq9evYKLiwssLCzQtGlTSCQSLF26FMePH8fTp08RHh6u1TVfVFQEgUCAN2/e6OwIMXS4NUtiYiIRkpTL5VqVpUpOToZUKoWJiQlMTExgZWVFvsvLy0N4eDgYhtEqz9nU1BQKhQLZ2dkoKirC2rVr8d1332HixIllCrEplUrs2rWLiHhNnDgRX3/9dZ0OJTY0gwcPhqmpaamc45KEhYXhs88+w5MnT2BiYoJZs2bh5s2baNKkSZ0s8UiNZD2RSCQYNGgQBg4cqGEcs6PBBw8exMuXL2uxhfrB1m80NjbG5s2bcePGjdpukt6Ym5uTXIn09HSMHj0agwYNwp49e7BkyRKtVHJPnTqF8PBwzJs3D1ZWVjAzM8MPP/yAgICAMlUiKfpjb2+PJUuWkDSF/Px8rF69ulyVcScnJ7i5uQEoDj0LDg6uVeXjoqIiPHv2DM2bN4eRkREaNWqEhw8fllkaqqTRYWRkRHKuSub2lIStHwmgVgzkkiQnJyMlJQUNGjQg6tZNmzZFcHAwIiMjMXPmTCxatAju7u6QSqUICAjAzp07S5UdoRgOMzMzrFixgpQXUiqV2LhxY6XPb1ZEatu2bWjXrh0mTJiA5s2b45dffiFKsdbW1vVSoDEjIwPr16+Hl5cXPv/8c/Tp0wc7duyoV9UYoqOjERgYiN27d2Pw4MHo06cPhEIh+Hw++vbti549e1JjuY4wbNgwEkV49epVrTy4ADQiDwsKCsDhcDB58mS0atUKc+fORXx8fLnrvnnzBhYWFhCLxXB2dsbUqVNx/vx5PHr0CG/evNH6mrCwsEBhYSFMTEx09vyWNJJZg9gQRjLrKRcIBDAxMdG6dnNUVBREIhEcHR2JpkZ+fj5iY2NhYWGBNm3aVLoNPp8PMzMzcDgcEq1VWFiINWvW4Mcff8Tdu3fLTOW4cOEC+vfvjwYNGsDV1RW9e/fG2bNndTvwesz48eNx+vTpCiPcbt++jdu3b5PPN2/eRGhoKCZNmoTFixfruEdthbv0D7cuXSCUUiFSqRQjR47E9u3b8fHHHxMDWa1W459//sGkSZOwevXqemcgW1lZYc6cOViyZAlu3ryJKVOm1GsDGQAZhRSJRFiwYAHatm2LmTNn4siRIzoZU+Hh4Zg+fToRijI2NsZ3330Hb2/vamn3f5EGDRpg7dq1xEBOS0vD3LlzyzWQ2dBfoNjgfPToUZ0oDcQaymq1Gnw+H40aNSpzubfzkMsKU2OxsLAg13JJZerahGEYhIeHE+NJKpUSIY7U1FTMnTuXhBpyOBx8+umnmDlzJgQC/V9WlLKxsrLCypUriYGclpaGmTNn6vT8LiwsJPm8UqkUGzZsIIMyNjY2ZXqL6gusEvuuXbswfvx4rFq1Cg0aNKjtZulEcnIytmzZgk8//RR///03eX6wxvLmzZvxxRdfaHjOKDWHiYkJBg0aBKA4/WbXrl1ar2ttbQ2FQoGcnBxkZWXh66+/hp+fH2bPnl2hgcwSGhqKmJgYjB49GmFhYTh79izCw8MRFhamdRuMjY3BMAxSU1N1NmoNqW79NqxXu6z3YkXk5+fj5cuXCA4OxuPHjxEaGoqcnBwIhUKt9IBYAxmAhgBYcnIyfvvtN3z99deQy+VlrrtlyxYAxe/qfv36adRtfpdxdnZGz549sXXrVp3WU6lUePToUZ19JlMjWUtkMhlGjRqFbdu24aOPPiK5g0VFRcQ4/vHHH+tEB1YXRCIRRo8ejV9++QX5+fmYNGkS9u/fX+9yj99GKBTCzMwMvr6++OKLLxAdHV2lsPHs7GwsXLgQISEhAIoNm2XLlsHf39+Arf5v4uzsjKVLl5JOeVRUFGbOnFlhLqSVlRUYhkFeXh4eP35cp4TwFAoFiTKQy+VESbMkJT3JEomEjN6/bYxwOBxSF7rkdusKMTExRKSMzXkFijspP/zwA/bs2UOW7dKlC1atWkV0AihVx97eHqtWrSKDKElJSZg7d67epZ0yMzOxZMkSnDhxAlOmTEHXrl0hFotJfl595vLly5g0aRKCgoLwww8/YPr06fXuuLKzs7F7926MHz8e+/btI8Yyj8dDnz59sHnzZnz55ZcaiuaU6mfIkCGk5vzJkye1qnDAYmlpCalUiszMTEyfPh2enp749ttvy1W6fhuGYTBmzBgyGBQUFKSTVgV7fzMMo1c0QnWFW5fcjqFCltn605XBvqMUCkWpvsWlS5cQEhKCSZMmlbluaGgo/vnnH9ja2sLd3R1Dhw6tesPrAZ9++imSkpIqVHMvCy6XC19fX/30VYqKtJ/0hBrJlSAUCjFixAhs27YNI0aM0DCOz507R4zj+lhLt0mTJti0aRP8/Pwwb948bNy4scyC6fURT09PDB06FB988AHWrVuHn3/+ucr5aHl5eViyZAnJrxQKhVi0aBH1KFcBW1tbLF++nBhXISEhmDNnToUdBKlUCltbW5JbpE15iJomMTEROTk5UCqVsLGxKfW9tp5kS0tLFBUVkfyzuihWFRcXB4VCASMjIyJaw7Jv3z589913JOS8QYMG2LBhg0aNZ4p+WFpa4vvvvyeDMK9fv8bcuXMN8i46cuQIZs6cCX9/f4wfP56Uxavv5OfnY+/evZg6dSqEQiF+/vlndO3atbabpTM5OTnYs2cPxo8fj7/++osMuvF4PPTq1Qu//fYbpk6dWq63i2I4TExM0L9/fwDF4dIHDx7Uel2BQAA+nw8ul4upU6fCw8MD3377rU79MF9fXzRu3BgrV67USySL1W3hcDjIyMjQef2SsO+xkmlD+r6zOBwOiTwylACnlZVVpYJ3JbVsyktr2rp1K9q2bVvqfcfy999/k37JBx98oFHT+l2EjRb7/fffS/1Wv//+O77//nvyedGiRejVqxfc3NzQrFkz7N69Gy4uLjp7oGsKaiRXQOfOnfHrr79i1KhRRFCnqKgIZ86cweeff46ffvpJpxHDuoJIJMLEiRMREBCAEydOYM6cOXXOQ6UPxsbGaNasGaZMmYIff/wRcrkcixcvNmgOWkFBAVasWEFCSQUCARYuXKhRx5eiHZaWlvjuu+9I+Ynw8HAsX768zBzekrDhS1wut06r1sbExEAsFsPCwqKUIFdJI1kikZCOxNuj8tbW1pDJZKQ0WV2EYRjyG5YVWnbnzh3MmjWLRNmYmJjgu+++Q+/evWu0ne8SUqkUS5cuJZ2vqKgozJ07V2vvkzZERERgzpw5SElJwdKlS7FgwQJ07NjxnYgESE5OxurVqxEYGIhPP/0UixYtqndeZaDYWN67dy8xltmUEx6Ph759+2LLli0YOnQoTXOoRgYNGkS8yGfOnNHJ0CwsLER8fDxGjBgBV1dXbN26VeeyeUOHDsWJEyf0FtdjUwZzcnL0MkarK9xaJpMRY1vbfOTKsLe3r1QcysLCglTKKK9/n5qaisuXL2PYsGFlfv/mzRviURUKhRg1alQVWl336dmzJ1xcXLB9+/ZS3zk7O5NIJ6A4lH3Lli0IDQ3FqVOnIJfL0b59e4SGhtZkk7WGCneVgZeXFyZMmKBR7FqtVuPcuXP1XiDD09MTs2bNQnp6Or7++utqLyFTGa6urmjevDk8PT0hk8kgkUgglUohlUohEomQn58PpVKpMQHFD2Yul0sma2trmJubIygoCFlZWfjtt9+QkJBQLbLyKpUKq1evxuLFi9GsWTPIZDIsXbqUnFdK5ZiammLFihUkh+7+/ftYv369hvFYHmyHRK1W10kvMkvJeqYikUjj2N4W7iprBB74/2PVpq50bcKGpLHtfZuYmBjMmDEDc+bMgb+/P/h8PqZNmwZ3d3ds2bKF1h/XAT6fjwULFpAc5ISEBCxcuNCgNalZoqOjcfjwYVy6dAkNGjRA3759MXv2bOTm5uL169dQqVRQq9VQq9VgGAYMw0AkEkEsFhO1drFYjMLCQigUCuTm5pKyYjExMXj48CHCwsJq7fe/e/cunj17RhRrf/rpp3qpxaFQKLB3714cOXIEAwcOxAcffEDqmo8dOxZ9+/bFjh07cPPmzdpu6juFsbExevfujejoaJiZmenkRQaKn/fDhw+HiYkJtmzZArlcDl9fX4SGhmqV8ubm5oYmTZpUWnKnItgBFH0j7coKty5LzEtXTExMkJeXBz6fb7D3n4ODQ6VGMpuqwD6nyuPgwYP46aefsG3btjLbt2/fPvTs2RNSqRQ9e/bE0aNH39mqKP/880+5uhUlyxECwIwZMzBjxgzD7FiXS7bswiGVQo3kElhZWWHs2LEa9VmB4g789u3bDVbvs7Zo0qQJFi9ejH379uHQoUO11g43Nzd06dIFvr6+cHJywpMnT/Ds2TNkZWVpdKSUSqVGh4udAJBOGfs3OTkZMTExyM3NRZMmTWBhYQGlUlnl8KHyKCoqwg8//ICVK1fC3d0dVlZWCAgIwLx58yr1hP7XkclkWL58Oezt7QEA8fHx2LRpk9YvQnaUty4byAA0Ojlsm1neDrcuLye5vh3r28dZkpycHCxZsgSffvopEbl577334OzsjJUrV1aLkfcu8s0338DHxwdAsYclICCg2s5dYWEhUlNTweFwcOPGDdy7dw98Ph9OTk6ws7MDl8sFj8cDh8MhA5dlDWwKBAJIpVKNQVBPT0/Mnz8fb968QXR0NC5fvoyQkJAaL5mSk5ODwMBAtGnTBjNmzIBMJqu3irS5ubn466+/cPr0aYwaNQp9+vQBh8OBjY0N5s2bh6dPn2Lr1q31Tli0rjJo0CDI5XLI5XIcP35c50HyL774AjY2Npg8eTIcHBxgZWUFU1NTeHt7IyIiolIxygEDBuDChQtVuv9ZI9kQOjSG9CRbWlrCyMgIycnJBnkmiEQiWFhYVCiGxufzSXROZVGi8fHxePjwIaytrcvsu+Tk5GD//v0YN24cCUdeunRp1Q6CUuNQIxn/P5o3bNgwDU9IbGwstm7dikePHtVi6wyDo6MjAgIC8Ntvv+HChQs1vn8Oh4N27drhgw8+gIuLC27fvo09e/YgKCjIoF4EY2NjEg6ojTJkVVAqlVi6dCnWrFkDa2truLu7Y/78+Vi2bBn1jJUDGybq4uICoDjsceHChToNZtSXuoNs6QmgdE5VeTnJbxvJ+fn5Oit71gZsuyv7bdRqNbZt24bIyEhMmzYNfD4fPj4+CAwMxIoVK4gIGKVsPv30U3Tq1AlA8bWxdOnSaheLfP36NSwtLSEWi2Fra4uEhAS8evWqQmE9XfDy8kLnzp0xZ84c5Obm4ujRo7hw4UKNi/HduXMHAQEBWLJkCbKyskhKTX0kMzMTP//8M06ePIkJEyagadOmAIoHygMDA3H+/Hls3769zkeo1GUkEgkGDBgAoHgQU1fHQ9euXdG6dWt8+eWXyMrKQlZWFnJycuDo6AiZTAZ/f3+EhoZWmFLUrFkzbNy4sUrHUdWB2OoIty4pAmmo6DwzMzOoVKoKBxQsLS2Rn58PkUiklbbDihUrKvz++PHjGDBgACwtLdGiRQs0atQIz58/17ntlHLQZVxHT09y3e99VTNubm4IDAzEyJEjiYGcnZ2NX375BV9++eU7YSADQOvWrXHp0qUaN5BFIhEGDBiAzZs3Y/z48bh27RrGjh2L9evX4+HDhwY3Jlnjq6CgoNqNZKD4Ab5kyRLS2WjWrBmmTZtW7futj1haWmL16tXw9PQEUHzuFixYUKmQxtuUZ1DWNfh8PkQiEUQiUakOyNs5yeUJd3E4HIhEonLDmOsK2hrJLBcvXsS8efNIB9DKygpr165Fv379qq2N9Z0BAwbggw8+AFB8nletWlUjWhKZmZlkEMvZ2dng911YWBi2bNmCcePGYc+ePejduze2b9+O0aNHw9TU1KD7qoznz59j9+7dWtVSrQ9ER0dj0aJFWL58uUaYac+ePfG///0PrVu3rsXW1W/69+9PhFwvXryokx6Avb09pk6divXr12sYgbGxsaR0E4/HQ5MmTcoUfgSKS1zK5fIqp5Sxz+yKooAqojrUrZ2cnMDhcFBUVKRz/6A8ZDJZpZ55Ozs7GBkZISMjo8pCr0Cxd75khYfBgwdXeZuUmuU/ayTzeDyMHDkSgYGBcHV1BVDs7Tly5AgmTpyI06dP10klWX3x9/evcS9Nr169sH37dnTv3h27du3CxIkTcezYMa3yTvVBLpeTUJmYmJga+/3i4uKwfPlyEq7Uo0cPjBw5skb2XV9wcXHBmjVrSB5lZmYmFi1apJcXrKKawnWJkobt20by2znJ7GDR28fEXlP1xUjWRSDoxYsX+Oabb0inUCAQYMqUKZg/fz4pB0Yppl27dpg4cSL5/PPPP+P+/fs1tn+2HrZIJNIQYTEkRUVFuHr1KqZPn07SWLZt24bRo0fXqPDU8+fP0apVqxrbX01w7949TJs2DVu3biWGgpmZGRYuXIhvvvmG3m86IhKJiMHDMAwOHDig0/qff/45zp49SypllCQtLY2UNeRwOPD09CTGeEm8vb3x7NmzKodJp6amQqFQQC6X6/VONbQnWSKRkIGB+Ph4g6UaSaXSCiMnjIyMiPfakIK8V65cIQMh7dq1o+XZDIkKxd7kyqYqXEJ1u5dZTbi7uyMwMBAfffQRuZmjoqIwY8YMbN++XW+VwLqMs7Mz6ehUN3Z2dvjuu+/w8ccfY8OGDZgxYwauXbtW7UYrW082Pz+/xutVh4aGYu3ateQl8dFHH6FXr1412oa6SrNmzTBjxgwSBp+QkIDZs2cTEQtjY2M4ODjAxcVFq85wffEksx1PtVpdKk9d2xJQ7LOorndifXx8MHbsWCxcuFCr39DKygr29vYwMjLCt99+i+PHj5Pv2rVrhyVLlsDX17c6m1xvaNSoEWbNmkWu93379tV4zmxWVhbx+ru4uOjtddKW4OBgLFu2DLNmzULz5s2xadMmNGnSpFr3yRIbGwuZTFbjXuzqpqioCMeOHcMXX3yhMcDSrVs36lXWkb59+xKD6sqVKzr1N8RiMezs7HD06NFyl1EoFHj8+DFUKhW4XC4aN25c6t3QoEEDREdH63cAJUhPTyd6AWyUl76wfTx9SkDxeDxYWlrC398fXC4XarXaoDpAMpmsQiOZVbdXq9UG814DxQPkrNI1h8PB+++/b7BtU6qf/5SRzOPxMGrUKKxfv17De/znn3/im2++qXFPq6WlJXbv3l3tHjGBQABzc/NqDz/m8XgYOnQoNm3ahKioKEydOhX37t2r1n2yODg4kJqQ0dHRtRIFcOvWLWzZsoV8njJlCho1alTj7ahLDBo0CEuWLIGLiwsSEhIQHh6O2bNnk06Fra0t/P394ebmBhcXF7Rs2bLS+8HCwgIymYwIBdVVWMNWoVCUCkN+20gu73plX+pCobBOepPbtm2LdevWYfLkyXj9+jVWr15dqWfDyckJjRs3hq2tLRo0aABvb2/s2LEDy5cvR3Z2NqKiotCwYUOsWLECY8aMqaEjqZuYm5vj22+/JQMPFy5c0Ajfq0mioqLAMAwEAgEaNGhQI/uMjIzErFmzcObMGQQEBGDq1KlletUMSX5+PlJTU2Fra1ut+wGAlStXomXLltW+n5KkpaVh2bJl2LBhQymvMitcRikfgUBA0h6A4pq4uuDh4QGBQFCpIZafn4/w8HAAxV7Qt0uUeXh4GESALSsri7yPbWxs4OPjo1PkRlnv4Mo8ycbGxvD29kbTpk3RpEkTtGzZEu3bt4e3tzf4fD7UarVBvOQlkclkFTrATExMABSnWxq6/3j69GkSvt27d+9SJSEpdZe628M0MNbW1li1ahVGjBhBbuDIyEjMmDEDf/75Z60ILaWmpsLIyKjaX8bsDVmdHnKJRILly5ejW7duWLBgAbZs2VJjKs9GRkZwc3MDUDwqWtNe5JKcOHECx44dA1Cc4zN//vx6WX+zqggEAnz99dcYP348MWbDwsLw7bffEuEMuVyOhg0bku85HA4EAkG5OVgsLVq0wIwZM9C2bds626ETCASwtLQEUHaNx/JykgHNDkZWVhb5rrrCXPVBJBLh22+/xeTJk3HlyhUsX74c58+fr3QgjsPhwMHBAcD/h5CbmJjAy8sL9+7dwxdffEE8lhwOB8OHD8ecOXP+k3Ve2ecH69F88uQJfvrpp1prT05ODvHsWFtb11i9ZLVajaNHj2LatGmwsbHBxo0bq/2dmZeXV+3GOFAc/VRbJSUvXryIL774QmMgu2vXrti0adN/fnC3Ilq3bk3Sum7evKmzt9PZ2VnrUkDJycnEuHr7XWdubq6VuJQ2hIeHk+euubk5WrduDU9PT51DsLUJt7azs4OXlxcsLS1hYmICIyMjSCQSEimTn5+PJ0+eVChYpg8KhYLUhC4L9jlrqJrMJcnOzsalS5cAFPdXaZShgdAm1Jqd9OQ/YSS3a9cOGzduRMOGDQEUe4/37t2LGTNm1KqaKsMwSElJIbViqws257G6ysiYmJjg+++/R35+PmbMmIEXL15Uy37Kw8vLC1wuF0VFRTW+77LYvn07njx5AqB4hH7+/PnVHp5Yl5BKpfjuu+/Qo0cPMu+vv/7C+vXrNRRr7ezskJ+fj4KCAty5c4eIA1XW+d61axf27NmDDh06YPXq1WjcuHG1HEdVcHJyAo/HA8MwZdZlLK8EFKAZRl5QUEDyoxwcHOrEdWRtbY01a9ZAIpFg2rRpJFS6sLCwUrVcuVxOjOOnT58iLi4ODMNAKBRCJpMhIyMDS5Yswfbt20nnqmPHjli6dGmFHZx3kc8//xxeXl4AinPkVq1aVeuq+dHR0WSw1dPTs0avx6SkJAQEBODmzZtYvXo1GRitDvLy8ki5wepCIpFALBYbzNDRh7S0NCxfvhyBgYHEq2xpaYmVK1di6NChtdauukzJuq9sGK0uNGnSRCfBPaVSWabSuzZCVNrCMAxCQkIQGRkJhmHA4/FgZ2eHpk2bol27dmjRogUp+fY2uuYkm5mZQSKRQKVSISEhAcnJyYiNjUV4eDju3buHO3fuVEtJu6SkpHLzgXk8HhmINdQ5fZuS4fXvv/9+nU8XoxTzThvJfD4fY8aMwbx580gHi82H/Ouvv2q9wwEUG+zVHTJqZGRUbWJZ1tbWWL16NWJiYrBixQqDKALqgru7OwmzfvnyZY2XDSkLtVqN1atXEw9Bo0aN8Pnnn9dyq2oGsViMJUuWEE9EQUEBVq1ahb1792osx4pziEQiREdHIz8/nxjJbK5XeTAMg7t372LTpk2IiIjAkiVLsGjRIqJsXtuYm5sTb+mbN2/KvSbZSAsjIyMNY+Pt51JMTAwYhgGfz4e3t3etvlwbNmyI9evXIyQkBAEBAcjJyYFcLodEIgGfz6909J/1hhQVFSE7OxuRkZHIz88neeksR44cwfLly8m58/HxwerVq/8zURl9+vRB3759ARTfQ99//z2ys7NruVXFz7awsDAysNG4ceMavx537NiBo0eP4vvvv6+2POW8vLxqD4lk8zbrQj/k0qVLmDZtGp4+fQqg2MgZO3YsvvrqK/J+pRS/m1q0aAGgOBIwJCREp/WNjIzQtm1bXLlyRavleTwepFJpqQoJHA4HEonE4AZdbGws7t27h7i4OKhUKhQWFpI2eHp6omXLlqUGxipTt377+mZDqHNzcxEeHo7o6GhERkYiISGh2vqpQLFX3tTUtMyopKKiItKu6hoci4uLI0JtNjY2aNu2bbXs5z9FgQ6TnryzRjIbXj18+HAibnDt2jVMnz69RspmaItara52I1kikVRL6LOLiwtWr16Ne/fuYf369TX+sndycoKjoyOA4hdWbYZZv01WVha+//578uDt27cvevfuXcutql4EAgEWLlxIvF+ZmZmYM2cObty4UWrZki9a1jjOysqCQqGAWq2uNP82MzMTKpUKt2/fxldffYWEhASsW7cO06dPr/bIjIqQSCTEcFAqlRXWkmU9ciWN5LLuoby8PCK6Z2pqSgTqahojIyPMnTsXhw8fxubNm0lb7e3tARQLlFTWaZNKpcjNzSXGNMMwxPv8dufrwYMHmD9/Pgl/c3JywuLFiyESiQx6XHUNLy8vTJo0iXz+6aefDFaT2BBkZ2eTcFEzM7NaCc09ePAgtm3bhoCAgGoRnFIqldUebs2+9+tKFY3U1FQsWLAAf/31FxiGQVxcHHr27ImNGzfS8Ot/6dSpExncuHz5stYl71jatWuHuLg4xMbGarV8gwYNyP5KDpKx12Z11Llm31u3bt1CcHAwXrx4QdSZ1Wp1herM2niSWUNYKpXWqKZIeno6cnNzyx1MZ9tVnYNCJb3J73p/8F3hnTSSW7dujY0bNxKlPnt7e2zatAlr1qyp1pEqfagJI9nd3V3rHBhtsbCwwIoVK3D69Gls3brVoNvWBltbWxJul5WVhdDQ0BpvQ2W8fPlSI4dw8uTJJOT/XYPH42HevHnw8/MDUPzyXrhwYbmd+7I6hmzOkEgkqtSbnJSURJQ/bW1tsXXrVkyZMgUcDge//PILxo4dW+OiXmKxGL6+vuDxeCgqKsLTp08rTHFgn0USiYSMbpe3fGxsLIlMcHBwIKW0apJPP/0UCQkJOHjwIJlnYWFBBiW0EQY0MTGBRCLRiDipqMZyREQEZs+eTULOPTw8MHPmzCodR13m7fSMY8eO4fLly7XbqDKIjo4mg5JWVlY1JuRVkvPnz2P9+vWYPXs2vL29DbrtmJiYah+MYo2fumIkA8Vt2bt3LxYtWkQGKi0sLLBy5Upa4xWaoda63pdmZmb4+OOP8c8//1S6LI/HQ6NGjYg+R1xcnEYIskwmQ1FRUbVGzjEMA4VCgcTERAQHByMlJQUSiYQ4Jlh0DbdmB0h5PB7J7a4pHj16VK5QHjsQYGFhQfREqmP/rGBb06ZN/3MpRPWRd85IHj16NBYuXKgRXj1r1iycP3++lltWNjVhJPv6+iI4ONhg2xMKhVi4cCFu376Nffv2GWy72mJjY0MGQBQKBUJCQupUR6Mkly5dIjmbfD4fc+bMISqK7xIzZswgtUWVSiUCAgIqLE9R0mPKegYLCgrIS7+yl1RBQQHREzAxMYGdnR2Sk5MRGBiImTNnolWrVpg/f36NKUILhUJ4eXlBJBKBYRg8f/68Uq8qG90hFouJkVyRmmdYWBjxJri6utaokJevry8R9WHh8XjEOMrNza10IE4ikZAQ1pIdPvY3Ki8SJTExEUuXLiWe97Zt22LcuHF6H0tdhcfjYfr06aTjGBISgh07dtRyq8onPDwcqampAIoHot3d3Ws89Pr27dvYtm0b5s+fb9AIkuDg4GovQca+93X1RtYET548wezZs0k4MZfLxWeffYZ58+a985Ec5cEKTgHFoq+6lF+SyWRYtmwZQkJCKs1jNjIygo+PD3kOZGVlldLOkUql1ZY7Wx7l7a+ycOu3r+/c3FxkZGRAoVDUeNTX7du30bRp0zK/i4mJIcfo6elp8L4De07YyDo+n482bdoYdB//Oahwl/YYGRlh4cKF+PDDD8m869evY/r06TVWH1gfqjsnmcvlwsfHx6BG8siRI5Gfn49ff/3VYNvUBi6XCy8vL3h5eYHD4SA/Px/BwcHVJkhmKLZv346nT59CoVCAw+Fg7ty5GnUE6zsDBgxAp06dABQbr0uXLiWlK8ojLy+P/G4lvcasiI2VlVWlokAJCQkkFNfd3Z2EoEVHR2Pu3LkwNjbG8uXLq10BWyAQwM/PD8bGxsjLy0NYWBgxHiqC7Vyo1WpyrBUZyWq1GsHBwcjKyoJSqYSnp2eNlKkBgDFjxuCvv/4iHl2guCPBDgq8ePGi0s4+a9SrVCpyfrhcLvl9KhJriY2NxcqVK8lg2JAhQ9ChQ4cqHVNd47PPPoOnpydSUlKQkpKClStX1ol81fJgGAahoaHkHnR0dISfn1+Nlyo7c+YMbt68iUmTJhnsuRoaGgoLC4tqvb/YWrB1lfT0dCxcuFCjxFH79u2xZs2aWk1pqS26du1K/meVirXBzs4OK1asQGJiIn788ccKlzU1NUXz5s1hYmKCwsJCvH79GkFBQaWerUZGRjVWPYSFvbfe7m+V5UkuSVnz0tLSIJVKYWlpWaPif48fP4a3t3eZIdUMwxC9BfadXtW2cblcODs7w9/fHx06dIC7u7tG+lnHjh2rtH1K9fNOGMm2trZYu3YtyU1iGAZbt27F6tWr61x49duo1epqNZh69OiBnJwcg+VhN23aFH379sXatWtrtAMnlUrRvHlzEn6Uk5ODoKCgGhcK04eioiL88MMPyMjIgJWVFXx8fDB27NjabpZBcHZ2xqeffko+r1q1ioi/VEZmZiaUSqWGQE5CQgIYhgGXy620FBQAvHjxAkVFReDxePD19SUddIVCgUWLFiEzMxOrVq2qNHxbX7hcLnx9fSGRSMDlchEbG6thSFa2LlD8DKgs3JpFpVIhJCSEdDw8PT2rvRSPm5sb3NzccObMGTLP1dWV5KbFx8dXqkZa8vdMSkoixgFbu1KlUlW6jcePH2sMzE2ePLnOlgDTlS5duuD999+HTCaDsbExvv/++2pReDU0arUaISEhJITQxMQELVq0qPEwyi1btsDOzg6DBg0yyPby8/Nx586dag0xrutGMlD8++7evVsjksPV1RWBgYHVJppWV2GNZIZhSglvlRdBYWFhgQ0bNiA4OBirVq2q8PeWyWRo0qQJSdeJjIzEy5cvtTY8qxv2Hfp2iHfJYy/r+Mo6N+zzgsPh1KgwXGZmJl69eoVmzZqV+X3JvjKPx4OPj4/ehrKZmRlatmwJV1dXyOVycDgc2NvbIz09nRy/v79/jZSae2dRQTsvchX8aPXeSPbz88P69etJjp5CocDixYtJrdq6TnWGW5uamqJnz54a5VSqgkAgwJQpU7B7925yk1c3QqEQbm5uaNasGXmYvH79Go8fP67xkdSqkJWVhQ0bNhAjaPDgwfXeE8bn8zFr1ixi4B07dkyj5mZlZGdnQywWaxh5+fn5JDdIm3DivLw8hIaGgmEYiEQi+Pj4kPupsLAQP/zwA2JjYzF//vxqGYzy8PAghtrLly91Eo8rmZOoTbg1i0qlwpMnT6BUKsHhcODl5VWt5Wr69euHy5cvk06yra0tnJ2dARR7m7QRlSoZGZCQkEDmy+VySKVScDgcrcIHWa8hUGyQffbZZzofT13DxcUFX375Jfm8ZcuWOiUuWRlFRUV49uwZIiIiyLXs4+MDLy+vGsu5U6lU+N///oePPvrIYF7OXbt2wcvLq9p0JOqDkczy4MEDzJw5k+gOyOVyrFixgiiwv+t4eXmR91FQUBB5RwHFqQZt2rSBr68vfH19NQaIUlNTMWfOHGzbtq3CAVChUAh3d3fweDyoVCo8fvy4wj6WWq2u0dQGPp8PPp8PlUpVqoJBWUZyZUa8Uqkk77qazst99eqVRiWFt0lISEB4eDj4fD7kcjn8/f11Urrn8/nw8vJCgwYNyHs5NTUVCoUCRUVFcHd3x507d8iyrI4LpW5Sr43k/v37Y9myZaSTGhsbixkzZiAoKKiWW6Y91RVuzePxMGfOHLx584bckFWlT58+yM/P16s2oK5IpVI0atQIbdq0gZOTE7hcLlQqFZ49e4aXL1/Wm85FScLCwrBlyxby+euvvy4lglGfGDx4MFxdXQEUhzj//vvvOq3PKnMKBAKNPDfWiJJIJBUqabKkpaUhIiICDMOAw+FolEliGAaBgYGQSCQaisGGwMbGhnScEhISyqyHXBHsfV9UVKRVuHVJCgoK8PTpUxKq7e3tXW2Dba1bt8bVq1cBFI+Ou7q6Ij8/HwqFAs+ePau0Q8ThcIiiKKtgzsI+u3VRaf3tt9/INnr27FmvOxkSiQTffvstiYD4559/cO7cuVpulX7Ex8fj8ePHJHrLxsYGLVq0gK+vb42U7nr27Blu3LiBUaNGGWR78fHxuHz5MubNm1ct3i4ej1ev3mOvX7/GzJkzSRkbHo+HqVOnYvLkyTUukljTlCfYJZVKYWFhAaFQCEtLS5iZmcHHxwfNmjUjxnJluctCoRA+Pj4wNTUlz9TKBgzZd11NYWZmBqlUWmaZv4ryjytCqVRCqVTW+D2QmppaafRVQkIC+d0kEgmaNWsGOzu7Cs85W1u6VatWsLGxAZ/Ph0KhwJMnT/D06VOEhYVBIBBAIBBo5Jj7+PgY5sAo1UK9fbKNGDECkyZNIjfovXv3MHv2bA0vRX1AJBJp3THWhdGjR8PY2Bj/+9//DLI9LpeLwYMHY//+/dUS6sPj8WBmZgYXFxf4+/ujRYsWsLa2BofDgVqtRkJCAh48eFBjHuzq4vTp07h48SKAYsGmkh3k+oSZmRkGDBgAoPjFuH79ep2v45IlLUqGQ6empmoIVGnTGUhISEBMTAykUinMzc011Hbz8/OxfPlytG3bFj179tSpjeUhkUiIeFxOTg5evnyp8zbi4+MRFRWFhIQErcOtS6JQKEjut0wmg4eHh85tqAxzc3NkZ2cjNDQUUqkU3t7eEAqFJD9am5QLOzs7MqL+tj4E+7vrUgM4PT0dO3fuJJ+/+OKLepvj//XXX5OBloiIiBrXeTA0OTk5ePjwIWJiYsjzwMzMDL6+vmjZsiXc3d1haWlZZq1SQ7B//3506tTJYEb50aNHERYWhlmzZhlkeyUpLCyEQCCo1brnuqJQKLBs2TIcOXKEzHvvvfcwe/bsensPagObyldQUEAiWYBij7qZmRkYhkFkZCSJtjE2NiYRcBWlHpibm6NFixZksDA+Pp6URKwINiWppmCPQaFQlAq31sdI5nA4kEqlEIvFNa67kJKSopV6dVxcHJ49e0YGoj09PdGmTRs0btwYTk5OsLGxgY2NDRwdHdGoUSO0a9cOnp6eEAgEYBgGiYmJePToEfk9c3JyyOBHSkoK3rx5g+jo6HrtKKl1akC4q+Yy5g3ImDFjMHz4cPL54MGD2LVrV51UiawMW1tbg9f3dXNzw/vvv4/p06cjPz8fAoEAEokEYrEYYrEYXC6XlJ3h8/lkRLuoqEhjKjmPDXd++fIlLCwsoFKpoFKpUFRURP6WPP8cDodMXC4XHA4HfD4fQqEQIpGI/BWLxaTsD5tbylJYWIj4+HjEx8dXy0BCbfHzzz+TPE9HR0eMHz8ev/zyS203SyfGjBkDiUSCuLg4PH78uJT6pjYUFhaioKAAQqGwVDjTq1ev0LRpU3A4HNja2mo1+BUdHQ2JRAIrKyvY2dlBqVSSepSpqanYsGED5s6di6CgIFJOSV88PDw0ohv0GQ23tbWFk5MTcnNzyXWv63X+5s0bmJiYwNbWFnZ2dkhISDBo7UxjY2NYWlqS3Gs2X+7Zs2da6QHweDxYWVmBYRikp6drdAA5HA4xnnVVaj179iy6desGb29v2NnZoXv37lqVVqlL9O7dG+3atQNQPEjwww8/vBPPuaKiIkRFRSEmJoZ0Io2MjCCRSEjKDPt+USgUyMvLI8r27N/CwkIwDAOGYaBWq8n/JWHfXSX/qlQqREREYNy4cTh8+DB4PF6picvlkv/Z95dKpUJubi7UajXy8/OhVCqRl5cHpVKJjRs34ueff0a3bt10EmyqjOTkZHC5XFhaWlb5eVSTqNVqbN++HVFRUZg2bRr4fD46dOgAPp+PVatW1XkhTV2xtbUlRtWzZ8800rxKii9GRUUhKioKVlZWcHJyIjoVPj4+yM3NJc+/oqIiSKVSWFtbk0FCtVqNyMhIrZ08Ne1JZt9PZWn86BNubW5uToxrXQZIDYG2RjK77KNHj+Du7g4zMzMIhUJYWVnBysoKubm5ZeYTZ2Zm4uXLl2W+h1NSUiCVSonwmouLC5ydnSGRSMgAC6VuUe+M5PHjx2uIc2zbtk2jQHd9QiKRwNjY2KBGMpfLxddff42rV6/C2NgYrVu3LpWvWN7NXRHDhw/HkydPiPesLNg8GX0f3kqlEkKhEJmZmUhLS9MQ+HmXKCgowKpVq7Bx40aIRCL069cPDx48wN27d2u7aVrh7OyMHj16gMPhwMzMDHv37tV7W+xv/raRnJmZiTdv3sDGxgaurq5ISkrSasQ5LCwMQqEQJiYmcHV1RXp6OnlZPXz4EJcvX8aAAQOqVFqH9R4AxaVA9M2NZzuTJb1q+hhJERERMDc3h1AohIuLi9bCadpgZGSEvLw8eHl5QSgUgmEYrcIBWRwdHYlS69sDKWKxmDwr9BFY3L59O9auXQsAGDp0KC5cuFBvnhf29vaYOHEi+bxx48Z6ZShpAxsBlJCQQGqPmpiYgMfjQSAQgMfjwdTUFKamplpvkzWWK/KiPXv2DGPGjEFwcLBOwo4ikahUfmRhYSGysrJw4sQJTJ48Gffv3zdYp76oqAjJycmwtbWtl7/9xYsXkZGRQaKh2rRpg4ULF+K77757JwZ7WEqGw75dJaRkyDA7SJOcnIzk5GRYWVnBxcWFDA5JJBKNXFj2vcHqaugyuFnTRnJF+6qoJnJZ63I4HKJpkZubW+OlrLQJty6JQqFAcHAw5HI5LCwsIJfLYWRkRI6VHexnvcMV9QdSUlLg4uICHo+HqKgouLi4EF2RR48eVfnY/nMUANDmlV+FoIt6ZSRPnjwZ7733Hvn8yy+/4PTp07XYoqphY2OjEYKhDxwOB6ampjA3N4eJiQk6deqEhg0b4sSJE6UETBiGQUFBAZRKJXJzc1FYWEi8wFwuV2OEveTk4eEBS0tL3L59u8KHs7bhPwzDoLCwkHgOFAoFFAoFsrOz65UYV1WIj4/Hli1bMG3aNADAV199hS+//FJDEKSuMmbMGHIN7N+/v0qeS6VSCblcXqbwVFxcHGxsbCAQCODg4FBpHV6g+CX99OlTtGrVCgKBAJ6enhovn0uXLiEgIAC7du3SO8yLfcHn5+dXaYCLNZJFIhF54erjhVGr1YiLi4O7uzssLCwMWkOTNWRLDgpoe43y+XwSSpaenl6qTSV/c33u+xcvXuD+/fuwsbGBqakpunTpYlBPX3XB4/Ewa9Yskod/5syZejNApi+pqamk7JdQKISxsTGkUimJImKjiyrr+GszCBsREYGkpCT4+vri8uXLUKvVUKlUpaKl2MoSrCgRUPwOE4lE5F0mEAhgYWGBlJQU5OXlYfHixdi3bx+ys7ORlpaGtLS0KoWLJiQkwNbW1qAlGmuShw8fYunSpVi8eDFEIhGaN2+OgIAALF++vFRYbn2lZL3st3+nvLw88hyTSCQaivSssWxpaQkLCwuYmpqSe55hGGRkZCAjIwMpKSk6D+7VtHAXO4hpYmJCBgNYyioBVZEn2dPTk3jQ4+LiqqO5FZKTk6OXonRWVlaVKw6w4eoikYhEuQGAt7c3NZLrKPXGSJ44cSIxkBmGwY8//ojz589rvX67du0gEok0RBdqm0aNGulVw5nP58PCwgIWFhYwMzMjoTBGRkZ47733cOTIEeTl5SEnJwfZ2dnIyspCTk4O8vPz9QpJb9euHf7++2/SAWWNZ7ZzwYa78Xg8MtJfVqhcUVGRRijdf53Hjx/j7t27aN26NeRyOaZPn46AgIDablaFWFlZkfys1NRUHD9+vErbY42jksJdLAqFgoz6mpuba2UkA8WG5suXL9GoUSMYGxvD3t6eqLI+f/4carUaHh4eePHihc7tZXOegWKhwKpcx6y3paTKrb4emPj4eDg5OUEgEMDZ2RmhoaF6t6skMpmM/DY5OTk6iZOxXkOgbPEatnOpVqv1LuX2999/Y/Xq1QCKayfXByN51KhRJGc+Pj4eJ06cAIfD+c88EwsKCjSM5pIIBAIIhUKSq1tW2g6rU1Ey3Yf9n037EYlEGDBggN4dT6FQSMpxsdOxY8fw1Vdf4f79+0hISICNjQ0xdtjj0dUwjIyMhJeXV51KFfD29kaDBg20rhASHByMxYsXY8mSJTAyMoKfnx8WLVqEgICAOl3nW1tYT3JBQQHRgGAp6Rgor1QQW/ccANEfqWofqKZzkpOSkmBnZweVSoWGDRuSihKA9p5kHo+Hxo0bk/fnmzdvDJ5qqA3VpQOkLdnZ2SgqKtKoCuHt7V1r7aFUTL0wkgcMGID3338fwP+r1epq7DZr1syguXqGoGXLlrh//75Wy4pEIlhZWZFwj7dHEfPz89G5c2c8ffoUu3btQm5ursE6Xb6+vti2bRv5zHZG6kON4rqKsbExGjVqhFu3bqFx48YwNjZGs2bNMHDgwDpdvowNswaAU6dOVfllk5eXB4VCUe61mpGRQbyjusC+1E1MTGBlZUWMZAAIDw9HgwYN9DKS2TCtoqKiKr/g2dF4NopDrVbrfT7VajXi4+Ph4uJiUCVhVpQGKD5vujxT2N+ssLCwzHBqVv2zKs+R58+fIzQ0FI0bN4aLiwuaN29O1HfrIr6+vhg6dCiA4mvozJkzcHV1hUql0rhG/6sUFhYapAP76NEjfP3113rn+hUUFBBPMYuRkRHJf9+8eTMpXWZmZgYzMzM0aNCADOwlJydrFc1x//59zJgxQ+f2VSdmZmbo0qWLTu+h0NBQLFq0CEuXLoVUKoWfnx+mTZuGjRs3VmNLqx9ra2sSkRcaGlrK6Le1tQVQ/CzXRnDLUH2mmg63zsnJQWxsLFxdXclAyLNnz1BYWFipkQwUlyNt2LChRkmktwccagqBQFAtfVdtnjUymYzkYyckJCApKQnW1tbw8vIiGgkUHVAB0OaUVUFTsM6rW7du3Vojd+vHH3/UyxtsbW1dp/J+BAIBmjZtWmFdWQ6HA0tLS/j6+qJ169Zwd3eHiYkJeThmZ2cjKioKDx48wNOnT+Hv74+NGzdWaHToipmZGezt7fHs2TODbI9SDKtEnJOTQ/IqAWDcuHGkXE5dhFWHZhiGqHRXhfz8fEilUshksjJVvlnjisfj6awCzo7el1TOBorDMSvKra8IExMTAMXGe1XzX1ljoGQIaVVEb9gwaD6fT9RSqwobKVJQUKBzLiYb0lZevjEbbltVDh06RP4vmY5T15DJZJgxYwb5rXft2kVU0dk8NYphSE9PR3x8vEE9NHl5edi6dSvkcjny8vJw9+5dREREID09nbxvpVIpnJ2d0aJFCzRv3hx2dnYV/q5Pnz6FRCKBm5ubwdpZVZKTk2FjY6Pzei9evEBAQAAxQHr06IERI0YYunk1SkWh1hYWFrC3twcAvUKmq0JNG8lAceRUUlISgOL3YKtWrUh5zpLtKgmXy4WLi4tGzeDo6GhSvrA2EIlEBk8FcHd3x7Zt29ClS5cyvxcIBHB3d4e/vz8ZEE9OTib6IUKhsFqqU1CqTp02kj08PDB79mzyMPj77791CrFm4XK5aNy4McLCwgzdRL1p1qwZMjMzNfISWKRSKTw8PNC2bVt4e3vDzMyMhJilpaUhPDwct2/fxqNHjxATEwOFQoE+ffrg+fPnldbk0xUfHx+8fPmSKu8ZEEtLS1J3MyoqCo8ePcLhw4cBFBslc+bMqbYSKVXBz8+P1C1++PBhmeGSulLyZVVWXnJJNVxdR3/z8/PJVLJD8eLFC72MZA6HQ4zkzMxMndd/G9YgLmkkV8WLlp2dTToeuoghVURBQQG4XK5eOc6scfy2KBsLG8Zd1Q7L3bt3icevefPmBhsgMDRffPEFiUR48uQJDh8+jFevXoFhGBImTzEcwcHBGkaOIcjPz8e5c+cwYMAAKJVKxMfHIzg4GDdv3kRoaCiSkpLIfS2TyeDp6Yl27dqhUaNGZd6TRUVFePToEdq2bWvQdlaFyMhIGBkZaYhMacuLFy+wfv168nnUqFHlGg71ATc3N/JsCQkJIfMlEgmcnJzA4XCgVCrLrO7ACrNWBzWdkwwUG8DPnz8nzyw+n08qdBgbG0MkEkEmk0EsFsPY2BgymQympqYwMTGBWCxGVlYWnjx5YvA+qq4IhUKDe5JfvXqFwMBATJw4ETNnziT9FvYc+fj4wNHREVwuF0VFRQgJCUFGRoaG88nQz6r/BDVQAqrOGsmWlpZEDAIArl69it27d+u1rYYNG0KlUmnkANQ2I0eOxKlTp8hnLpcLW1tbNGvWDC1atICDgwMxlHJychAREYHbt28jJCQECQkJGjc5l8tF//79ceLECYO309fXt96KitRFOBwO8Rrk5OTgzZs3AIA//viDXJ9OTk4YOXJkrbWxPHr16kX+N1QOHasMCqBMryI7mKCPYAaPx4NIJCplpMXExOhVm9DY2JiMmmsTWlcZb4dbA1UzkhmGIcY7a8xXFZVKBYlEUmbOeGWwbeFyuWV2FtnfWx9l65IwDINr164BKO6UsGWV6hIdO3ZEhw4dABTf94GBgQCK8+5Z74yDg4Ne55lSNtVhJAPAyZMn0bZtWw2FXFap+vnz57h9+zZCQ0NJZAeXy4W1tTX8/PyI961k/urJkycxcODAOjO4U1hYiKdPn6JZs2Z6rX/z5k2N6gFff/01mjRpYqjm1Sjt27eHubk5MjMziZOFy+XC29sbcrkcOTk5CAkJ0XhuGxkZ4eOPP8aOHTvQrVu3amkXn8+vtdDcuLg4PHjwgERmcrlcCIVCSCQS+Pn5oXXr1nB1dYVIJCLOndjYWDx58sQg782qUh1GMlA8WPvll19CLpdj06ZN6NSpE1q3bk3KgRUVFSE+Ph737t0j5yEoKIis36JFC4O3iVJ16qSRLBKJsHjxYpJbFxoaWqXclqZNm2pcjLVNt27dIJPJcOzYMfD5fDg5OaF169Zo2LAh6UyyOWoPHz7Ew4cPER8fX24oZps2baBWq6tFIdXBwaHWR/7eJezt7YnRVnLQRqVSYe3ateRlO2jQIL1G8qsLqVSK9u3bAyj2WBrqWmMYhngpWYOYRSQSwdLSEgUFBWQwQRfYTqdSqdQIA0tPTy/XcKsI9ncr2eaqUJYnuao1RlndhfK8t7qSmZkJgUAAIyMjncOBMzIykJ2dDQ6HUyp8UyKREEPBECV1rly5Qv6va54rkUiE8ePHk88//fSTRhRGZGQk1Go1uFwuXF1da6GF7ybR0dEkHNaQJCUl4cGDB+jXr1+Z37OhlMHBwbh79y6io6NJtISRkRHc3NzQpk0beHh4QCQS4cmTJwgNDcVHH31k8LbqS1BQEJo2bar3+ocPH8aZM2cAFBt0CxYs0CuEuzYpWR85MjKSGKVSqZSIy8XHx5MoO4FAgMGDB2Pr1q1o2rQpli5dWm36IgKBoFbFp3JzcxEaGor79+8jJycHKpWKVE9hKSoqQm5uLl68eIHo6Og6U56vOsKtWdLT07F8+XI8evQIy5YtQ+/evcEwDJKTk3H//n1ERERonKPExEQihunt7W2Q9COKYamTRvKXX35JOgsJCQlYsWJFlR4IzZo1qzPy6hKJBJ988gn27t0LJycntGnTBm5ubiTfMjMzk4xGR0REaCU29v777+PkyZPV8hCSSCQ1XsfuXYXP55N847S0tFKjqnFxcTh48CBZdtKkSTXdxHLp3LkziWy4dOlSlY25krBe4reNVtZTIxAINAR0tIUdZHs7NDo/Px9KpVLnkGTWy1dQUGCQnH9Dh1sD/x+6bCiPZHJyMinNo08Id3Z2Nrhcbqm6lOxvzTCMQYzkiIgIJCQkACiOfjGkeFlVGTFiBDn+e/fu4ebNmxrfFxQUkFIoNjY2dcajWN/Jzc012GDR2xw/fhx9+/atNC1GqVQiOjoad+7cQXBwMJKTk8EwDHg8HhwcHNC6dWs0atQI+/btQ9++feHk5FQt7dWVR48ewc/Pr0oKyr/++isePHgAoHjAkq2nXF/w8/Mj/5eMpmPrxQPFKYEuLi7o2bMntmzZgq5du2LdunWYN29eteq4CAQCg76D9SU3Nxc5OTnIzMxESkoKQkJC8PjxY4SFhSEjIwN5eXl1rmZ2dXmSgeIBlJYtWyI4OBi//vorfH190bVrV42BsrdhxXu5XK7e0Rv/Wf6L4dYDBw5E586dARSH4S1btqxKnSixWAwvLy88fvzYQC3UHyMjI3z//ffIyspCYWEhHB0dSdmk5ORkPHz4EEFBQUhKStLa4DUzM4O3t7deudraoK86KKU0zs7O4PP5YBim3ND/AwcOkDAmf3//OpOr1rFjR/K/oa811kiWSCQaecmsoZeXl6dzh8DCwoLkBbECXiVJT0/X2ejj8/koLCw02KBRyRJQhgi3Boo75awRbwghqIyMDNI2fTrw7LP77c4xWwYkNzfXYGGDrDeZw+FoXK+1ib29PQYPHgygeFBky5YtZS4XGxtLfnt3d/eaat47TW5uLjgcTplaB1XlyZMnyMvL08nbmp6ejtDQUNy7dw+vX78meaXW1tawsbHBvXv3sHLlSqKYXJu8evWKlPvRF7VajdWrVxNPmZubG7744gtDNbHaKWkkP3nyhPyfmZmJ5ORkFBQUwMzMDIsXL8asWbNw7tw5LFy4sEbU9dl3UVUxMjKq8kASO8BbVFQEpVKJrKwsjbr3VcmdFovFetU0rojqMpKNjIywspkfhhgJ8b6cwbT42xi07lMss5ZA+dNK5JibIwfA226vkhVuWrVqZfB2UapGnTKSvby8MHr0aPJ5w4YNOtXlLAsfHx8kJSXVurK1o6MjNm/eDA6Hg6NHj5JcDTZHITQ0VK8SVS1atMCLFy8M4o0pC4lEUuWcQUrxw54N/UtMTCx34KGgoABbt24lnydMmFDro+8CgQCNGzcGUFzbUJ/a3hWRlpZGyh+x5TYAECNPVyOKy+WSvG+2JMvbZGRk6OxtFIlEBhVUq45w66KiIgiFQvD5fIO0NT8/H3l5eRAKhZDL5Rq/j7btAUDq3ALFHTyJRAKGYUg+riG4evUq+b+uhFx//vnnJKz80KFD5ZYNKyoqIveVqakpGUSg6A/73jJ0J5vl/v37euURKpVKvHz5Erdv30Z0dDQxdm7duoUXL17gt99+qxP5iVUNuQaKf4PvvvuOGE3dunVD9+7dDdG8aqWkVy83NxcRERHkO5VKhYiICHA4HEyePBm5ubkIDAxEXFwcGjVqBH9/f1haWlarsJYhwq2NjY3h4+ODVq1aoU2bNnB2dtbrncE+1w1VUUUgEJAUxNatW8PX17dUKlZVEIlEBjeShUIhfHx8IFIVgseoMSQ5BB2zosFTZAFrFgGxURCuWwf8K3xakpCQEHJ/1IX7vl5RoMOkJ3XGSJbL5Zg/fz4UCgUyMzNx4MAB3Lp1q8rb9ff3r9VQaz6fj169emHbtm1ISkrCkSNHNEKwIiIiNEbddKVly5YkpKk6EIvFVWofpRg3NzeibFhZjvetW7dI5IO1tTWGDRtWAy0sn0aNGpGOfskRdUPB1hwWCAQaOYT6Gsmenp6kY1yeQZ+RkaGzJ5l9sRoqlLmkJ9lQ4dYl2/Z/7F13eBtV9j2j3m1Jlmy59xqXVFIJCUkILJCQhIROILA/WEKvS2dhgV2WtllaqEtC6CmkQXohPXFsxyXuvduyLcvq0vz+sOdFimVbtuQCy/k+fZJlaTQazbz3zr3nnuuLhYDJZILZbCbbio+PH1Tmwfm3Y35PtVoNsVgMm802pFrzvlBTU0N+b2d/h9HClClTMGHCBADdaobvv/++39c7B8+io6NH3L329waapmG1Woclkwx0k+RJkyYN+f02m63XOmD//v04cuQI/vWvf+G2224btn33BGfPnvWJ/LOmpgbvvvsuzGYz6uvrsXr1asTGxvpgD4cPCQkJZPzIzMzsNQdNnToVq1evxquvvopHH30UhYWFpGewTCZDcnIypkyZAo1GMyzXsS9IcmpqKng8HjG4jIyMxJQpUwatZGC+X1/qx8F8f5VKhcmTJyMqKgoCgYC0IExNTfVK+u8MHo/n05pkNpuN1NRUCIVC6ARCXFOUj2hT24UX2GzAJ+/CcfQouE8+CVxUTsM43APdPMgb9cYf8D3GBEmmKAqPPfYYFAoFlEolSktLsW7dOp9se/z48aNi2sVisRAWFoZ77rkHTz/9NPbu3YtNmzahvLwcJ06ccIkgDxVsNhsZGRnDSpLb2tr+yGp4CalUSjJwNTU1HpGXjz76iEzMS5cuHVXTk75kZ74EI4nm8/kkw8tcH4MhpREREeRY1dXV9dmmaigkmSEwYrHYJ9kp50yyr+TWzHnm7BruDWw2GxwOB76sqsLVdjuuZrPx5rhxqPHwN2F+O5qmyfnMLMI6Ozt9HtF3Doj6skfuYMHlcvHnP/+Z/P3pp58OuDBzLsMQiUT9Llb1Trc/4B5isRhcLnfYHHXPnTsHhULhtTmYs6KsuLgYhw8fxvr163Hbbbfh2WefRUxMzKi0BMzKykJCQoJPiPqRI0ewbds2aDQacDgcPPXUU2PapMhZ9nrq1CmX/2VkZODRRx/Fa6+9hqNHj8JisaCiooIoAxhFIJ/PR1xcHCZNmkQMwHwFX5BkiqLAZrNRV1fnUisfHx+PlJQUj885d5nkwWaVORwOkpKSkJSURErSWlpaUFNTAzabTXoL+wK+ziTvjo7ACokYV1PAfG4x4mK1gAjkRtd13wQff4xn6uvx1hNP9CL8zueYN4G3P+B7jAmSvHz5cmRkZADoJmVvv/22T6QbCQkJUKlUI06SVSoVpk2bhtWrV2Px4sVYt24dNm3ahJMnT6KiosJnNXiJiYmwWq0uUiBfo6GhARqNZti2/78Apkm8xWJx2xfbHWpra4kzJpfLxV133TVs+zcQRoIkt7e3k4mLaV/E1P5yudwBWxpRFIXY2Fio1WrQNA2dTofS0tI+X9/Z2TloCVdzczOMRiMMBsOAmRAmoyASifqMgDPfd6CaZJFIBLFYPOBiVS6XQyaToauri5hY+QImkwn+DgcuKyoCRdOwUxQ2pacPuMhl6i1pmobRaITD4QCHwyHGVMNRApOXl0cej2bbmaVLl5Ke4jk5OThy5IhH79NqtaR1UGRkpE/qyv9XodFo0NnZOWyeGhaLBefOnfPZopamadTX1+PEiRPYvXs33nvvPaSlpeHpp5/GZZddRvryjhSam5tRWVnpszZG69evx/nz5wF0q0keeughn2x3OMCQZJqmXZIQUVFR+Otf/4r33nuvl0KRpmk0NjYSbxkmOCMUCpGcnIzx48f7LNjhC5LMvN9isRCnaqZsT6lUYtKkSR4lSJi5y5nE2mw2NDc3o6WlZcC1vFwux6RJk0iAV6/X48yZM8jPzyclE740//JlTbJQKESmprsLSVpjPdLM7stpGPznP/+BUqnEbbfd5vK88zn2R13yIGCDZ6ZdXlSxjTpJTktLIz1haZrGP//5z15utEPFsmXLsGPHjhEznhIIBEhNTcWMGTPwwAMPIDo6Gq+88gq+/vprFBcX+zxrkpaWNuyGZPX19WPCSOS3ioCAAELGmFYvnuKbb74hrs6XXHKJ1/VhQwGfzyfyn9raWrKAHw4wEzRDolpaWtDU1AQ2m42UlJQ+M79isRjp6emkvVZTUxPOnTs34OQ82Mi0zWZDTU0NRCIR/P39Sd0zA4FAAI1Gg5SUFEyfPh0ZGRlISkpCcnKy28UtswDoL5OsUCgwYcIExMXFYcqUKZg8eTIiIiLg7+/vsk2JRIKEhARwuVywWCziljwU0KKeG7f7tsJqhp9UgMntzbiWdR6OQA6MGgFeuTEDJx4OdfvdmF6i/v7+MJlMRAbt7Nw8lN7XA8HZUXa0SLJCoSAlEna7HR9++OGg3l9WVgaapsHlchEeHj4cu/g/gaCgIJ8Gi9whMzPT5+Oyw+FAVVUVtm3bhmeffRY2mw0PP/ww5s6diwkTJvi0PnMg/Pjjj1i6dKlPpK52ux3/+Mc/yDh/ySWXEFO7sQSVSkW6UBQVFZFxKiAgAC+++CK+++47HDhwoN9tdHR0ICcnB+fOnSOZZalUivT0dJ8QZV+QZGa/GOd9o9GIrKwsVFZWkvFn3LhxA67/3MmtWSwWVCoVAgIC+g30qdVqjBs3jjiGV1VV4ezZs2TNzmTgh+LX0xdMJpPPzDejo6PhUFDg+9swK7ACiET3jXvhRvl135jP/vvf/44rrrgCs2bNIttpa2sjKqKYmJhhaV33B4aGUSXJcrkcjz/+OLnI1q9f75IJ8AZhYWEYP348tmzZ4pPt9QeKohAWFoZJkyZh7ty5eOCBB1BYWIg///nPOHDgwLAZX0VERPSbLfMF6uvr/8gkDxEsFos41er1+kHXXxqNRnzxxRfkbyaYNJJITk4mk5xzG4zhALN4YmrB7HY76urqQNM0OBwO4uLiEB0dDZlMBi6XC7lcjtjYWJeFY0tLC4qLiwdUa7DZ7CEpOurr69HR0QGaphEUFIQZM2Zg6tSpmDlzJqZMmYK4uDiIxWKyqJRKpVAoFCSr6AxmXGCxWOQYOy98KIpCXFwcWCwWyaQLhUIEBgYiLS0NM2fOxPTp0zF16lRMmDABFEWBpmkUFRX5zEQFAGAyAT2y6SRLM67WFYBL22Gl2Tioi8aECRMQFBQEoVAIgUAAtVqN8ePHE9l8Z2cnkdMzJNlutw/LuKjX64lag+lDO9JYtmwZMdvbtm3boAMWXV1daGxsxNUUsDosBG18PhwAHADo57pv4qcu3Gi/7hvzGgcuBDq0uHD7X4NGo+nTKM1XKC8vJ4TK17BarcjJycGDDz6IrVu3YuXKlVi0aBEJmjE+EcOJI0eOwOFwkI4j3qK1tRVvvvkm+XvlypVITEz0ybZ9BWdlgLMM9pFHHsHp06dJm0ZP0NbWhszMTLJOE4lESEtL81ohwmKxvDY9ZN7PKJWA7kRVZWUlzp49S8bnuLi4fsu9mpqaUFlZ6TLOufOiuBgqlQoJCQmgKApmsxnZ2dmoqKggc5dAICBrAV8aPLJYrCG1M7wYcrmcBBimGasgoj0LWtTV1eGtt97C6tWrXWT4zoGXK664wuv9+5/A770F1COPPEIWf2fOnBnQ2MRT8Hg8PPbYY9i+ffuwZr6A7kL7CRMmICEhAcuXL8ef/vQn/Otf/8ILL7ww7J8dERGBqqqqYf2MsrIy4mz8BwaH4OBgIpHtq+XTQDhw4ABZ9CclJY14Njk1NZU8Hi6pNQMmeszlcskCUKfTISsrC21tbRAIBAgNDUVGRgamTZuG1NRUBAcHg6IoWK1WFBYWIj8/36MMMWOiNhTk5uaipqYGXC4XbDYbPB7PpS5Lp9OhrKwMZ86cIaqYkJCQXtthDPH6yiQrlUpC8vLy8pCXl4f6+noSVKQoChwOhxAyk8mEvLw8nylxnHYU4F+Qekdb2rBSewbRgm7qJRaLER8fj8mTJ5O+r2KxGF1dXaipqSESSwDE9Gs4HfOZQCuLxRrxBbhCocDChQsBdP8eQ53TKioqwHXYYadYOHyRYuEPeIakpKRhDyJXVlZCrVYPazDGZDLhgw8+wCOPPIKUlBTcddddSExMdJGoDhccDgfWrVuHu+++22eflZmZie+++w5A9zX6xBNPDFs/66FgypQp5DFDkhctWgSlUom1a9cOaZu1tbWkLE4sFnvt8+KL30Kr1RJfjItJsF6vR3Z2NoxGIyiKQnx8vNtAL9A9t0VERLhknJ3nVncqhICAACQmJhKCnJWV1UtZxOyTw+Ho01tkKNBqtX1+l8GAmdPlDiMmmAbXhefUqVP49ddf8cADD5Dn9u7dS36PefPmjUgQ7A8MjFEjyXPnziUL/tbWVrz11ls+2/b9998Pg8GAL7/80mfbvBgURSEqKgoZGRmIjY3F6tWrIRAIcNttt2HHjh2+zeS4AeMEPJBTsrfIy8sjpgp/wHM4SyVbW1u9Mo/ZsGEDeXzzzTd7u2uDgnM98nBnkmUyGcxmMzo7O11aIen1ehQUFKCpqakXsbVarcT0ZjCZejabPWQjELvdjvLycmRnZ6OsrAxlZWUoLi5GXl4ejh49ivPnz6OmpsalNlgikfSSJTvLrd1lkpnsuNFoREtLC1pbW1FcXIwTJ04gMzMThYWFKC0tRUVFBQoKCpCbm0vk+V6BkYqpem4sEzBbAFwJIL375j/OhCUpuVgUnwe9Xk/Gu6t6brc7DPi+o7JXcKirqwtdXV0ugYW+MFRzqtGsS77++uvJ4mbbtm1DlpRbLBa8XVmNbTRwPlqNugwpqCQA4p5bhNPtxu4bde2FG2Z33+R+F27/SxllkUiEjIwMn3TI6A86nQ46nQ6N4eHk+NIB3TczLtw8RX/n+9mzZ3HrrbeitLQUDzzwANLT00k5x3AuqA8fPozDhw/jmWee8Vk7wg0bNiA3NxdAN2Fybv05muDz+SQw3NraivLycoSGhuKWW27B22+/7ZUrcl1dHZH5emvkFRgY6LWng8PhQHNzM/R6vdv1icViQXZ2NkwmEyiKIh4/F8NdF4r+MskBAQFISkpyySC7O64dHR1EheQrHx8AKCwsREJCglclBBRF4U6VP67mAGnyerDjaCAOF+ZMntONmU8vwqefforQ0FCSNe7s7MTRo0cBdK8X/qhNHhsYlVCFTCbDqlWryN9r1qzxuM+vQCBAWloaAgMDweVyQVEU6urq0NDQAJVKheXLl8Pf3x+PPfaYTy+si/chMTERMpkM06dPx/z587FhwwZ89tlnw06OGYSGhsJoNPo0wuYOdrsdJ06cwPTp01FQUDCsn/V7QkREBHFpHGoWmcGRI0dQXV2NsLAw0odxuGvRgQuBIKA7Eu7zDKUTJBIJgoODwWKx3E7YNpsNhYWFKCoqgkgkglAoRFdX15Azkmw22+uaro6OjgGPCSMrZtqDOI9JznJrd5lkm82Grq4ut/up1+t9WqfVL8wmgNfbNIyigHhZKzIzW8FmsyGVSvERiwWNTgc/f/dOGW1tbcT0LC4uDoWFhT7fXWeSPJIO10qlkix4TCYTNm/e7NX2ampquktdJHwcUMbgpros/NEUyjNMmTIF1dXVwy63BrqzyayICDiKi4f9swwGA1544QVcccUVeOSRR3Du3Dns2LEDUqkUBQUFw1LnDwAff/wx/va3v+G9997DN998g7KyMsjlcoSHh5OxtL29HdnZ2R7NEw6HA++88w7ee+898Pl8XH311Th48CCKioqGZf89xbRp00gg4MSJE2Cz2XjkkUewbds2F0XMUNHS0kIyyUx5zFAQHx+Pn3/+2ev9KS0t7TdYzBDl9PR0su69OLPrjiQ7b9OZJMvlckKQnUm4O7S3t+Ps2bM+a/3EoLKyEg6HAxERESgvLx/SNmQyGWxU935FsNqHtA2DwYA1a9bgqaeeQmZmJpqbm7Fz505ERkZCLpfjT3/607AH+X7z8NSUywtaNiok+a677iK1BocOHUJmZma/rxcIBFi4cCEmTZqE5ORkNDU1oaqqihhhMdncjo4O7N27Fz/99JNP+6A5IyAgAPHx8ZDJZFi2bBnkcjkeeOABn9VSe4rw8HCPnZK9xdGjR3Hvvffi008/HZHP+61DJBKROu66ujqfSEs3bNiAJ598EkB3bfJIkGQmEAVgWBULXC4XKSkpYLFYsNls/ZYQ0DRNspHeYKg1yYP9jJCQEAiFQmJM4gx3cmvnDDqLxSK1YkqlctgDYgSMzyHjHUKZgBghYAHQBw+w2+1ob28Hozeh+/BKNBqNeLShAflBQUBgIC436TG5rtZtpL1tiH6LLS0tpMXXSBpfLVu2zCdZZAYOh6Pb8EyZgDq+DIXiACSixQd7+vvH9OnTSVZmuFFVVQXWCBus/fLLL8jOzsbLL7+Mv/zlL/j666/B4/FQUVExLOsCu92OZ599FnPmzMGiRYugVqtRWFgIk8kEm80GDocDtVqNRx99FKWlpcjMzMTOnTv7HbOamprw1Vdf4c477wRFUVi9ejUefvjhYR+X+8Nll11GHh84cADLly8Hl8vFV1995ZPtMwEEpkxnKOtUmUwGlUrlk64mnqipzGYzcnJykJ6eDj6fj4SEBJw+fdqlOwPgSpKd5zGGJHO5XCKxHoggD3YfBwOaplFYWIikpCSPSTLNNNeI6747LJXjeBAghBXqeD1I9LLronsA6CdmdPbsWRw+fBj3338/nn/+eeTl5YHL5UIqlSItLQ1qtdqn9dh/YPAYcZI8fvx4MhDp9Xp8/PHH/b5+6tSp+POf/4yWlhbs378f//nPf0YkOnwxGBOm4OBgREdHY/ny5Th79iwefPBBnznlDQYKhWJYWqi4Q1ZWFgQCAdLT00el5/RvDVFRUaAoCjabzWfkcjSyyaGhoeSxN27J/YHFYiElJQV8Ph80TaOgoGBY61UZeCO3dretixd2QqEQMTExRDJdVlbW6/MGMu6qrq5GYGAgWZhUVlaitnZwtU8+gdkEcHxXczm7uBhtIhHqZTIcjIyG0mhEtN63QuCamhr4+/vD398fIpFo2Dsc+DqLDPTIdu2NWJccgkajBIfioxG7RQsOHEC+0wuZYEac03OMdYFTO2/56e57rdOQ5F1l5NiEXC7HhAkT8N///ndEPq+lpQXcHoNGACTI5OmqgHYOEDGPPThdGxoacM899+DPf/4z/vKXv2D79u2gKAr+/v44f/68T9vmAN3kYt++fdi3b1+fr2E8WqZNm4b3338fX331FbZt29bnWPvTTz/hsssuQ3R0NCIjI3Hdddfhhx9+8Ol+ewp/f38EBASgrq6OzN9Lly7F448/7kL6vIHFYoHNZiOBhaGQ5Pj4eNTV1Y1Y1xage0zLzc3F+PHjweFwkJCQQMqvPJVbx8fHg8vlgqZp5Obmjsg83xcKCgqQnJyMHTt2DOn9TdxuA8pgSgdvu7J9+umneO+993DFFVfgl19+we7du0mLqDlz5uDbb7/17gN+z/DUlMuLTPKI1iTz+Xzcd9995O9PP/20T2mOSqXCc889h9WrV2P9+vV44oknsHPnzlEhyBwOB2lpaQgNDcW8efNwyy23YO3atXjmmWdGhSAD3a65nmQqKIoCj8eDUCiEWCyGUCgctHzFZrNh8+bNo+Ku/FuDv78/cTysqqry2eQKuNYmj8RvMdwkmSHIzkRyuM3unD97qBmLiIgI3HLLLfjoo4/w008/YdOmTfjwww+JjNjf35+4O5tMJlRXV7ttRTNQTbLdbkdubi5MJhOsVitiYmJIJL4/REVF4e6778Ydd9yBFStWDNjTeUCYTQCn/x7NgwGHpnFVXh4kZjNoUNiSkIxKmb/Ptg90KzgYjEQ7DV9nkRlQAC4L6jaf6rAKkCn6ozXIQFi2bBlOnz496IASRVHg8/lknuTz+R7NlTqdDuhRxo007HY7PvjgAzz11FOYM2cObrjhBmg0GowfPx4ikWjgDfgYOp0OBw4cwGuvvYZXXnkFV155Jd566y3ExcW5fb3D4cCaNWuIyubGG28ctW4aM2fORHh4OIKDg3HkyBE8/PDD+O6774YsyXUHq9UKDocDgUAw5Pru+Pj4UZGld3V1kVZ+/v7+pD55ILk1i8WCUqkkZmVVVVUjVyrUBxiSPFRwad+pHYxGI/7973/jzjvvhEqlwv79+8n/pk6d6rPP+QNDw4hmkm+66SbiKnfu3Dns3bvX7esSExPxwgsv4OjRo7jnnntG9YJijBw0Gg1WrFgBiqJw9913+3TgHApkMlmfhEIgEECpVCIgIAB2u92tk6LVaoXFYoHZbCY3i8WCzs5Ot8R/69atWLx48YjVw/4WQVEUYmJiAHQPfL7O+h05cgRVVVUIDw8fkWxyWFgYeexrksz00WXaBNXW1o5olnQwJFkoFCIsLAwLFy7E9OnToVQqkZOTg127diEvLw9tbW2YNm0a+Hw+FAoFkpOTwWKx4HA4UF5e3qfiY6CaZKB7YZKZmYmUlBQIhUKo1WpwOBwXF28/Pz9IpVJIJBLIZDL87W9/w9mzZ6HX68Hj8bBkyRK0t7fj4MGDOHTo0IC/ZVfPLogZntlkAoIFQCVcpWNu2v+Skbo7EA7aWUjR002FbgFEViuW5+biu1lpMLK42DhxHJY25yLc3A70HC6FF4kS5+8YEhLiE2liX7g4i7xp0ybfbDiy+y785w7EilpRwlHiuC0cycVNkFgtF17HfLU6p/e299w7m6r38GvF8Ho9jiqY3+LRRx91+3+BQACZTAY+n09uPB6P3F8MrVYLPp9PjPMuXotoAbA7O8GbIQPvnp4ne46v3Fl01fPbOL9bzEg4neMezC4MUrB16tQp3HLLLXjxxRexevVqfP311+BwODh37pzHfi++xrlz53D//fdjyZIlePXVV/HBBx+4zUKXlpZi8+bNuO6668DlcnHffffh2WefHfH9nT17NnnMkPbhzGoPFOzsC3FxcThz5oyP98YzMAodsViMuLg4tLe3D5hJ5vF4iI+Ph9VqhcFgGPaOLJ6goKAAEokEkZGRhPhfDNo5xnRjz/293Xf8MzYgDzDKuN3miQyYMdhp7mrzINOZlZWFI0eOYOXKlXjjjTdQWlqKmJgYxMTEjGyp1R/ohREjydHR0aRxvNVqxX/+8x+3r0tLS8Ozzz6Lzz77zCfGBN6A6WkXFxeH2267DYcPH8brr79OajFGE1Kp1GWwkUgkCAgIgFKpJHWMAPokAlwuF1wu1+W1DKxWKzo6OtDW1ob29nYYjUaYTCZs3LgRN9988x8kuQ+EhoaS41leXj4sJm5ff/31iNUmD1cmmSHITPCmrq5u2Fu1XAxPa5LDw8OxdOlSXHXVVWhubsavv/6K8+fPkzFArVYjICAAubm5MJvNiIiIAIvFgtVqxblz5/oN8DFSO+dMsjvlgc1mQ05ODuLj4xEYGAiRSITk5GS0tbVBLpf3CoL985//JNsxm8348ccfIZPJMHPmTLzzzjvIz8/H+vXrPc9GmEwA1zs3VndQdXXh+vpz+E6TBhOHgx9V47C0+RzC+yvi8hDOmWR37bd8iYuzyMNBSmabylAukcPM5mBPeCwWnc//w8TLDa6//nqcPHmSlLnweDz4+/tDJpO5tFTzFBKJBDweD2KxGBERETCbzYQwd3R0ADQNurMTEIxOJtkZHR0dePjhh7Fy5Ur8+c9/xtatW8FisZCfn+8b1/shwGaz4bvvvkNBQQGeffZZ8Pl87Ny5s9frNmzYgBkzZkCtViMtLQ1z587tV9btawQFBSEhIQFAt//G3Llz8fHHH/u8HtY5EDMUqTWHw0FKSsqwdm4ZCKWlpZg4cSJYLBbCw8NJgNf5WDnPrQEBAURmXVpaOmLmtv3BYrHg1KlTmDlzZp8kuT/4i7trqZv0EphsbAg43meWv/rqK3z00UeIiorC8ePHScJl6tSp2L59u9fb/13Cyx7InmBESDKLxcL9999PImfffPONW/lhQkICnn32WXzwwQcukoPRgEQiQUZGBq6++mpMnjwZ7777Ln766adR3SdnyGQyOBwOxMbGup38HQ4H2tvb0d7eDr1eD4fDAbvdDjab3SuC7vw3RVHgcrnw8/MjbQrMZjNxrrzhhhtw5ZVXYv/+/TCbzWNiwBsLEIlEiIjoDim2traipWV4DHZGMpvMkOSWlhaPDDY8AUVRLgS5vr5+WLN8fWEgkszn87FkyRKsXLkSWq0W69evR2ZmJsxmM+lPzLhsm81mF0lvZ2cnCgsLB6wZo2kaZrO530yy82sLCwths9lI/22FQkHIut1uh16vh9lshsPhAJvNhkQiAZfLhb+/P+rr6/H6669DIpFg8eLFeOWVV5Cbm4sNGzb0Ov4S5jOZbh9CC9DO7zbtand6oX/3nfNSj3dlz4Pne+41L17455nux9QnF54KrNPjeioH3yENZoqDjcHjsLQxF2Fd3hFlZ1XCcMqtFQrF8GSRL/4chxFTzVU4gkgU+wegUBGARO0fJl4AyJwVGxuLP/3pT3j55ZcRGxtL6tGBbidZ5znSYrH0UlIxairGiZ7NZkMgEJBAFDN3hoSEICQkBDabDXtbWxHP4WAcXzZ6/TQvwhdffIFz587hxRdfRHJyMr777jucPXt2xDxM3OHcuXN4/vnn8eKLL8Jms2H37t0u/zebzXj//ffx4osvAgBWrVqF06dPD5tb98W49NJLyePOzk7QNI2jR48iKCgIIpEIXV1daGtr8zpBIhBcKFsZyrbGjRsHvV4/qkpGo9GIhoYGBAcHQ6PREJdud5lkiqKIWqypqWnUyhPd4ddff8XB22/Hh+vXu/hG8pg/Jjk9uaznPu1FAEBCuA2Hcg7BSrNw5PsIXG7t6WBysPuO8lAF5bwOaW1txY4dO3Drrbfiv//9L2n3eckll/xBkkcRI0KSr7nmGhIVqaysxMaNG3u9hsvlYtWqVfjyyy9HnSD7+fnh0ksvxS233AKKonD//fcjPz9/4DcOM1gsFhQKBQICAhAdHY2KigqXScRms0Gr1aK1tRVarXbQNZcsFgtSqZTIaZRKJanTYhq7HzhwAI888ggoioJer4fVaoXZbIbdbofNZoPD4YDNZoPdbofD4YDVaoXJZILJZILZbPZpja4zKIpCeHj4sPeN7gvx8fHEnbl4mFuBOGeTly1bNiwkWSaTEQd6X2WR3RHk4T5WfaE/465Zs2bhrrvuAkVR+P7775Gfn48zZ864jfxzuVxoNBqEhoYSI5bi4mKPTVWMRmOfNcnuUFpaCg6HA5VKBRaLha6uLpw/f77PPtxxcXHQaDTQaDRoaGhAZ2cn1q9fj59++glLlizBa6+9hqysLPz3v//t+3eWyAAvSWt/CKL1uL4zB9/LuonyjzHjsKz0HNAy9AVyQ0MDHA4HWCzWsGaSFy1a5JMsMt2zIKNOOz3X85jqKSm/BNUoClShWSjGnWFxONXQ7jqeOv1ENNM5JP3Cc76KuAcHB6O1tXXYOkiwWCwIBAIIBAISvGWz2W5vPB4PPB4PHA4H9957L3JyciAQCHoFRkwmE7RaLTo6OtDe3j6oubGhoYEYYjFlTMxnlocFokHmB4lMg7OXjENcZAtip9wNkYgN5LxItkHf0PPAWbjF7GL7hacshwZxoPrBmTNnsGrVKrz00kt46KGHsGHDBuzdu9dtcmKkUFhYiFdffRV33303cnJyevW1z8zMxMGDBzF79mxIpVLcfffdePPNN0dk3xgzWYqiEB0djXfeeQdSqRRqtRr+/v4ALrjN19XVDTnDzMx9ZrN5SMZqkydPxqlTp4b02b5EXV0dgoODSaLFZDK5Jck8Ho90yBgV08l+cPr0aVAPPwwqKgoYZNDB35+DCdG1qGj2RyYvFGwKmGmp6DZV7AdisRgqlQpyuRxCoRBsNhuZmZkkePDDDz/g448/hkgkQlNTE9RqNVJTU0fEfPI3id9DJlmtVpNG8TRNY82aNW4nqBtvvBEURY16xEQqleKmm27C0qVLcebMGfzzn/8c1XoANptNJmaFQuFiJMJisWCxWIj8q7293avMrsPhcOn9ymaz4efnR+RqAoEAOTk5SElJwdKlS/Hf//6XyLY9hc1mg9lshslkQnt7O7RarVcuhywWC5deeilWrFgBuVyOVatWjXi0MiQkxMV8arjl+EePHiWTVFpaGmJjY32ejfW11JrNZiMpKYksEhoaGkaNIDP7c/E4pNFocO+99yIiIgLr1q0jv2NFRYULIRCJRIRkd3V1oaqqihyjwS6ejEZjn+7WfaGwsBCFhYXgcDiw2Wxgs9mQy+Ww2+29Mi+lpaVQKpXg8XjQaDSExOl0OnzxxRfYtGkTli9fjnfeeQebN2/Gt99+23sfFCqgaXiNYjR2Pa7vPIfvpakwszj4ISYVis6CIctE7XY7GhsbodFoho0ki0QiLFy4EED377Zly5Zh+RwGbNC4oroQX8WPB5fLRUxMzLD0mR4ITzzxBJRKJTZu3IgdO3Z4RZa5XC6USiX8/f0hFAohEAgGNZ8wmDNnDthsNvbs2UMCt3q9npQMeev0TNM02tra0NbWhpKSEkilUiiVSihDA2D094eDBspqFCirUWDX6XqEhfERzw1GXEgLJMLRKc9qamrCww8/jHvvvRerVq1CdHQ0Pvroo17kdCRx7tw5nD9/Hvfddx+ef/75Xv//+OOPMXHiREgkEsyePRv79+8fsEWot4iIiCDzndlsRkNDA44fP47U1FT4+/uDw+HAarXCbrcjMjISISEhKC0t7VMtFhAQAKFQCKvVCp1OR8gNm80m6ryhZvWnTJmCjz76aEjv9SUMBgPa29uhVqvB4/H6JMl8Ph9sNhudnZ2jbtZ1MaxWKxwnT4I9c+agSTIAzEquQM3h7ijkKW4oytgKXCEpQrD+whzM4XAgFoshl8sREBAAmqZJSR6Xy4Ver4darSbKAJ1Oh82bN+O2227DsWPHsGjRIrDZbEyaNAmHDvkogvYHBoVhJ8krV64kMqft27e7rYOLjIzEtddei0cffXRU5bsSiQTPPvssJk6ciO+++w4bNmwYlQubw+EQYiyXy3s5bBoMBnR0dKCkpATHjx8ftv2w2+3QarUuC1WKopCfn49///vfUKlUOHny5ICRfudm8hwOhwwcSqUSMTEx6OrqQm1tLZqbmz2O8DPk+IYbbnDJGixatMjFBXq4IRAIEBkZCQBoa2sbEfd1mqaxadMm4hS/ZMkS/POf//TpZ/iSJItEImI8BXQT5NFw53QGl8slC2cul4tly5Zh6dKl2LVrF15//XUEBQUhNDQUdrvd5TeVSqXIyMiAXq+HVCpFTU0Nqqurh7wIZzLJA8mt3cFms4HL5WLSpEmEWNTV1bn0kHc4HGhsbERYWBhUKhVKS0tdrrGOjg58/PHH2LNnD+677z5ceuml+OCDD3D27Flges+LxqmAr44AXUCXUyxG/Hr3Pc9ZlsZItBnhjerFC/9jyoQv+ONceG4noEEnlpnOYbkxDWw2GykpKV71fa2rq4NGoyFmTb6Wbl555ZXknN67d2+fnRo8Qo+cj3Y232LW0dMvPKXZocfkxhpslYchMDAQzc3NbgMJVM9pRDvHoXygOp8yZQqie9od3XHHHVi6dCk2btyI7du3e0yWKYqCWq0mc1x/cDgcsFgssNvtLmol5m+LxYLg4GCkp6fjqaeeQmFhoc/rSN2hs7MTnZ2dWFVRgaioKNzI60QwW4e6dhloXhGqKoEqXSz2ZsYgWNGJuMXNiBe1wK/d6Rgxv69TO2ffNVrrhslkwnvvvYfy8nLceeediIqKwgsvvDCq5klffPEF3n//fVx22WU4cOCAy/90Oh0+/fRTPPjggwBA2lsN5286YcIEABeUesxcytQPl5aWoqGhAWFhYQgODgafz0dycjI6OjpQW1uL1tZWsm5NSkrC66+/DpPJBC6XCzabjZKSEpw9exZ1dXWw2WygaXpIvW/DwsIgl8vHTBvO5uZmBAUFgcPhgKIot+7WzP9GU+rfH3gVvwJL7wB2rrvwZGTPvfM8xRhhH3/xwnuXAsvZOZggjoVarYZGE4Oqe/+EkJAQrBMKkZ2djZMnT7p8HjOGabVayGQyCIVCyOVyF/n85s2bcfXVV3fPwT2YMmXKHyTZHX7rmeTIyEjMnDkTQPdibN26db1eQ1EU7rvvPmzZsmXUpLJA9wDEDI7vvPMODh8+PKIEmcvlIiAgAAEBAfD39+/lfKjX69HS0oKWlhYYDAYsW7bMZ3WigwFN02htbcWbb76JJ598EidPnhzQdInD4YDP5xMJnUAggEgkgp+fH8mixcfHIyoqCuXl5f0Szb7IMdAdpR5pU7H4+HiSlRzJzOi+fftw8803w9/fHzNmzEBQUJBPCbqzGZQ3zeyVSiUSExNJoKSqqmpIRhm+hkqlQktLC+Lj4/HII4/AYDDgqaeeQklJCSiKIuUFTU1NLgu00NBQ8n+9Xo/AwEAEBQWhuroadXV1gy5xMJlMYLFYoCiK9Ob0FCwWC3FxcbBareByuTCZTAgODoZMJsPZs2fJwq2+vh5hYWFgs9lQqVRuz5Py8nI8/vjjWLhwIZ588kmcPn0a0H8CGNoBmRrQjswiJ9jeiaysLKSkpEAgECAqKgpSqRTnz58f9ELZmTzK5XKfkmQul4tFixYB6B4T3ZUQDRdmNFTCKOjOVsXFxeH06dNDbmc2WNTU1ODQoUOYNWsWKIqCTCbDypUrsWTJEo/Isr+/P2JjY0mdJwOGdDIqI+Y2UNBILBbj6aefxldffYWCggKffc/BwGw2QyHqws1TsqA381CsDkBRcQCq8/xAg0KtVoZarQwHtDEIsncijteCeF4LFBiZPrEWiwU7d+5EW1sbVqxYgQ8//BAvvPDCqMl2DQYD1q5di3vvvRenT5/utc7au3cv5s+fj+TkZAQHB+Oyyy4bVhMvhiSr1WpkZWURYiMSiUDTNCkVKykpQVNTE2JjYyGRSODn5wc/Pz9YrVY0NDSgoaEBhYWFWLJkCbke5XI5Jk6ciHnz5uGuu+7CsWPH8MUXXwxpbTllyhRkZ2f7vP/1UKHT6cjcxeFwehl3MQSZxWJ5F0AcTuSdAW5/EEhIBgoHX1IpVKkxd+pczJo1iwShc3NzYbFYXBQbdrsdra2taG5uRltbGxwOB5KSkmC323sdG6PRiO+//x5z5syB0WiEUChEenr6xR/9B0YIw0qSmcJzAPjuu+/cymoXLlwIf3//UW2Yfdlll+Gpp57C2bNnsWvXLuTn54/IRc3j8aBSqRAQEACZTNaLGOt0OkKMLybEjAnXaCEzMxNbtmzBc889h0ceeaTfQd9ms8Fms/WSQTMyUbVaTWR2jIPv+fPnXRZbfn5+WLBgAa644grSRoxBTk4Ovv76a+Tl5fn2Sw4AjUZD6pXKy8tHNGhhtVrx008/4bbbbgNFUbjuuuvwwQcf+Gz7zPcC0Ge9a3+gKApRUVHE8MZut6OwsHDYDM0GC5VKhUsuuQTz5s3DV199hS1bthBS6Sz5vDgCziya6uvrYTabibunRqNBWFgY6urqUFlZ6bEihskkM9v2FAqFAmFhYfDz6+4jwwQYIyIiSGsLJjptMpnQ2dkJqVQKPz+/PoMpNE1j586dOH78OO6++27gxveBrN0AhEBdHWAFxM5KWOZ0c45VMZnQPT33zoePqcec5/Rcz/+pPU7PobvtVVJSEuRyOWQyGSZMmICCgoJBlVI4n7f+/v4+DcLOmTOHXCNHjx4dEQUJAw7tQGFhITIyMsDn8xETEzNiyoy6ujr861//wjfffIMVK1bg0ksvdSHL119/Pfbs2YOdO3e6OIwzAR0m+ASAjAlarXZIC38Wi4Unn3wStbW1+P77733y/YYCNpsN9PRNlfAtGJ9Rh/EZdTBEcFFSr0RRXQCqWvxhBwsNNikabFIcNkQhwN6FeKoF8YIWBJi6htWt3Gw2IzMzE3a7HVOmTMGrr76KL7/8El999dWIZN4vxtGjRzFv3jysXLnSbaeTL7/8Eq+/3i1Vuemmm3Dw4MFhCQTx+XykpKQQg6m1a9eS/zFEz9mRWqfTITMzE0FBQQgJCYFYLAaXy0VYWBjCwsJIG00m+MkYO+7YsQOHDh3CDTfcgIcffhjvvPMOzp8/P6h9nTp1Kvbs2TPwC0cIXV1dZM7icDguv4/NZiNeDRwOZ8xJrRm0FVjB+34nxH9aAhTmgwaQW6lCpVwO0yYeOHY72DSNgE91iG1uhrpnnAoMDMQNN9yASy+9FOwDB/Dqq6/i/PnzJDsskUhgMpmg1+vR1dXllvv4+fmBx+O5TUJs374dixcvRkdHB4RCIfz8/BARETGqicT/VQwbSY6Li8Mll1wCoNu1zV07J39/f9x222144403RqWtEp/Pxz333IM5c+bghx9+QFFREaqrq4e1ZoeRmmk0GlLHyoCmaeh0OjQ3N6OlpaXfYzLaJBnobtvAmOMMBXa7nQQBmL57MpkMfn5+yMjIQHZ2NmJiYnDVVVdh2rRpZNBlMFrkGOjOYDBmdDqdzmVBOFLYsWMHli9fDoFAgHnz5mHDhg0+C+54Q5IFAgGSkpKI8ZdWq0VZWdmgjCcoioJIJIJAIHCRVzKGcIzscigIDw9HUlIStFotnnzySZSVlbn837kt2sWTO1M3CXRnxZubmxEZGQmxWAwOh4Pw8HDIZDIUFBR4tPAfCkmWSqVkYWcwGEhdNFPvJJfLiauv8/eQSqW9nneHtrY2/POf/8Q/ou4FbvobcOhrwDRw1ssOChYWGxY2G1YWGxYWGzYhGxYWCxyaRiCrE0KHZ5lym82G3NxcREREEIfZ8ePHo6yszONrzflacD6fvQVFUViyZAn5+8cff/R+o0w5s3MMgAlItPd+uU6nQ21tLUJCQhAUFIS2tja3kkbK2czL+70kqKmpwZtvvknI8uzZs0FRFMRiMRYtWoRFixYhOzsbO3bswJkzZ5CcnEzmO5PJhJKSEq/bElEUhfPnz2PTpk2jWqbFZrOBU3bg4Z4nekoORM1WpKEBaWiA6Ro2Sq1KFOlVqKDlsIGFliYxWiDG09ERxDGYzR68GsVTMK77LBYLNTU1WLJkCZKTk/HGG2+MSouoDz74AO+99x727t3bSwWQn5+Ps2fPYvz48VCr1Zg3bx5++eUXn+/DuHHjwOFw4O/vj8bGxm4FTQ/0ej38/f0RGhqK+vp6F5UPkzmWSqXQaDRQqVSkvEypVMJsNru4qdM0jdzcXKxcuRLXXnstXn75ZezatQtffvmlR2UKUVFRiIyMxK+//urbA+AlmDUqi8VymY+Zrg0MxnIXFOvWrcD1n4AODsUJG3DUPxxWDgcsAFybDVYOB3a1Guc0GiTo9Zg3bx7mzp2Lw4cP47777nMJkA7Gv4g5Ju7Wz1arFVu3bsXy5cvJc+np6X+Q5Ithg2dyay8ikMNGkhmzLqC75ZO7BeNdd92Fs2fPDrsxgztERETgiSeegN1uxyeffAKdTofW1tZhs9bncDjERIaRThQUFICmabS3txOy6GlEfSyQZKD7t/UFurq6kJWVheDgYKSkpGDatGl4/PHHIRQKXRYNNE3jzJkz+PHHH0eFHAPdg1pSUhJxsx4tmZ/BYMDOnTtx1VVXob6+HgsXLvSZIsOZVAyGeEulUowbN84lE1tUVDTgwo/FYkGpVEIqlUImk0EikbidPJwXH0zbCaPRSMiiTqfrV1Y7adIkPPzww1i7di0+/PBDtwsUHo8HvV4PmqZ7yZ8ZsskcH6PRiIKCAgiFQkRGRkKlUoHH42HChAnIzc0dMPPprD7w5HrWaDSIiIiAwWAAl8tFcXGxy+/DeAEwGWYGXV1dMBgMg1us7PwAOLUVuO4J4LHXgI/fACqb0cXlolyuQItajBa+CK3+YnSxuLBTLKAn7ufPNaCdLbrQTwoA2IC/zYigTj2COJ2I4moRgL4DJzRNo6KiAp2dnUhISACHwyFSXU+M6tra2sjjiwOS3mDKlCmwWq3Q6/UoKysblRZmQLd6helEEB8fD71e75UJ4lBQW1uLt956C9988w2uv/56zJo1i2Te0tPTkZGRAZqmkZWVhVOnTqGgoABlZWU+yV7a7fYR9Z/oC2w2GxhgfBOw7EjhNyGF3QQLzUIZrUBRuwplMgUANmJiYnDZZZfh6NGjqK+vR21t7bC4hzc3N5NA2SeffILZs2fj3//+N95++22cOXPG55830L58++23uO+++/Dggw/2miPWr1+P8ePHAwBuuOEG7Nu3z+dSY0ZqHRAQgPXr17v8r7S0FBMmTCDtxdxlfpkygdLSUvj5+ZG5y+FwEAfrtrY2Fzf4zZs348SJE7j//vvxn//8B//+979x7ty5fvfz6quvxv79+8dUCyXgAtGjKMrlt3EmyRcnN8Ya6LY24Mh+tC69BYcPH4VAb4HQZEJIZydYDgc6hEI0qNWInT8fH82ahaNHj+KBBx7w2q1bq9XCz88ParXaLfnds2cP7r77blAUBbPZjPT09DHVhvZ/BcNy9iYnJ5PBrbGx0a1EJCMjA5MmTcK99947HLvQLy677DL85S9/wbZt20h9pF6vHxayw+fzERoaiqCgILIIDg8PB03T2Lx5M1pbW4fUFonphfp7QlRUFK666iosWLCAtJ9yOBzQ6XTQarXYvXs3fv75Z69qZH2BuLg4stAoLCwctlYonmDLli1YuHAhIiMjERAQgM2bN/tkf3g8Hux2u0d1gQzkcjmSk5OJ83NJScmAMlQej0eyYZ642joTZ6YWSiqVkqw10B08qKys7JVZW7JkCVasWIH33nuvXxMMsVgMiUTilmy3tbVBo9FAKBSCz+eTY82Q5fb2dsTGxoKiKKSmpiIzM7NfRYgzqRloMREVFYWwsDDo9XqIxWJkZ2e77GNUVBQJKl2cbTWbzeScZVyxB8RRAKgBdj4K3Hs3rC+swfHN3+BUXUs3Ie756G1uYhJGLYUeT6uLIMRV54XIhwpANL5qa+tZbPSdyWptbcWZM2eQlJQEmUxGWo8MVKfc1tYGo9EIPp9PenX6AkuWLCE90X/44QefbJPqadnkrFsQM2VofVgdOBwOFBQUYPz48cQ93rkWvddnDGMFUV1dHd599118+umnmDdvHq688kpSH8/hcHD55Zdj6tSp2L9/P3bs2DFmzId8ATabjS87HLidiZW4iZmYXToZORCNFiShBSwWC3K5HPHx8UhOTsaJEycQGhqKkJAQNDc3o6amxudS1crKSgiFQqjVauzevRt+fn548sknsXXrVre+McOJzZs3Y86cOVi8eHEvRUZxcTFOnDiBSy65BEqlEgsXLsTWrVt9+vkMCfbz88OXX37p8r+uri7U1dUhJCQEarUaFoull+qIgTuT0/5QX1+Pp59+GldddRWee+45HDx4ELt37wZN0xCJRLBYLKirq0NHRwdx+n700Ue9/r6+hnM21Hmd4Px4LK9TGeeV4C834vPPP8fx7CLUdtbi1OnTZI09b9483HHHHajo6sIv779PDNi8RXt7OzQaDYDemXigOzmxb98+3HDDDRAIBCTwMBrlEWMWlp7bMGJYSPJ1112HiooKhISE4Ouvv+4VIeRyubj33nuxbt06l2j/SGDFihVYvHgxXn31VRiNRgQGBsLhcCAvL8+nJ59QKERERARUKpWLnLK1tRX5+fkIDg72StbNONu6A4vFglgshkgkAp/PB5fLhcFggE6nG3ORSC6Xi1mzZuHKK69EQkICeZ6poayqqsK+fftcWvKMJpz7JjLOlqMJrVaLY8eOYe7cuZBIJLj88suxY8cOr7fLBHU8lVqrVCokJiYS86m8vLx+M9AymQwhISEICAhwqcU3Go0kOt/Z2QmDwUD6CLPZbGL0xuFwwGazweVyIRKJIBKJIBaLwWazIRKJEBERAYVCQWo177rrLsycORNPPfWUx2oRd2Sjvb2dyL2TkpJQXFzsck0xtcopKSng8XhITk5GdnZ2n8TFaDS61HX1B8ZBVCgUuvRWZLFYpEaOxWKhubm5V2TaK7mb1YqKzRtQ0m5B2O0PImjL96grOAc/owlKgwFVXV2kBUhfLsRcLpcEM0KkUjRJJLD2eBLI5XIYjUbU1NSgqanJrerAbDYjJycHiYmJxOAwNTUV586d63Pc7uzsJO7TF2fWh4qEhAQkJSUB6CYbI20UeDEMBgNKSkqQkJAAPp/vUos+GtDr9di8eTM2b96MxYsX46qrrkJSUhIx4po2bRqmTZuG+vp67Ny5E3v27Blz9Yp8Pp9k6GmaRldXF6k1dXducrncIS+aHQ4HWltb0draipKSEtTV1SEoKAgsFgtqtRpqtRrt7e2oqKjwqfFcUVERpFIphEIh6urq8PDDD+OFF15AUFAQ3nnnnREzh7Lb7fjPf/6Dv/3tbzh8+HCvAPhXX32FSZMmoba2FvPnz8fPP//ss31TqVQICQmBSqVCWVmZWxf9srIyCIVCKBQKhIaGwmg0+rTX9L59+9De3o4VK1bguuuuw759+3Ds2DGYzWYolUo0NDQgPT0dRUVFY1Jq60yAL/5drFYrWX+OdTQ0NCArKwvXXXcdnn32WQDAvHnzcMMNN6C2thZvvvkmzpw5g7S0NPB4PMTHx6Ojo8MrHxrnZAbTRssZXC6XjOklJSXg8/mIi4sblbZ//8vwOUmOj48ntcjV1dW9LP4BYNmyZdDr9T5ZzHsKNpuN1atXk1YRra2tRGpTU1Pjs2wgm81GREQEgoODSdbL4XCgoaEBNTU1MJlMUKlUSEtL8+pz2tvbXSSxbDYbCoWC9FN27rvqPEiNhfY7QLdL8Pz58zFv3jyXLCDQTRx27NiBU6dOkfrQ8PDwUZM1MmBkjRRFoaWlpc+o8khj8+bNmDt3LgBg8eLF2Llzp1ekiKktBOBxUCUsLIxIrnJycnq9j8PhQCaTQSaTQalUQiwWk3pch8OBpqYm1NbW9vl5ni6MlEolwsPDIRQKiUnQ4sWLERkZiccee8yjVhTMsXM3udtsNhQWFiIxMRE8Hg8TJ05EZ2cnaJqG1WolhiUsFgtcLpe4ufclg3V+fqCIu0wmA5vNBk3TyMjIIAt2Zj+tViu6urpQVFTU6/d3/i4eBwN7YhxtAgE2K1NgzStCF/9zzL9uBSTiMggzDwMAlnqgAGNUCc3NzbgV3cQ+MDAQISEhEIlEEAqFCA8PR3R0NFpbW0m/duc6diZzGhsbS7KUfn5+fQZanUmFr0jyddddRx5v3rzZJ9v0Fo2NjRCLxcQ8Tq/Xj3rLlaCgIGi1Wqxfvx4GgwHx8fFYsGABcc3XaDS48847ceutt+Lw4cP45ZdfRq1sxRkhISGIjo52Cdwxc2hfpVH+/v5DMjd0RkBAAOrr61FSUoKKigoEBwcjJCQEXC4X/v7+yMjIQHNzM8rKynyyVnE4HCgrK0NKSgrEYjHsdjsee+wxPPfcc3j55ZfxyiuvjFjw4vz58zh06BD+7//+Dy+//LLL/yoqKnDkyBFceumlALqJy86dO33yuRMmTEBwcDCio6PxzjvvuH0NTdPIz89HWlp3W7q4uDjY7XafqNnUajUSEhJAURR+/PFHZGVlYeHChYiKiiIZ/fj4eNxwww34+9//7vXnDQecS58uTmKYzWZIJBKX2uyxCrlcjt27d+ORRx7BqlWryNph/fr1OHjwIJlP8/LyMHXqVFAUBaVS6ZXk2jngdvHcHxsbi4cffhgmkwlnzpwhwd709PQ/SPIIw+ckecWKFeTxpk2bei3IRCIRFi9ejBdeeGHEivlFIhGeeuopyGQyPProo2hrayN1wRaLZch9OJ1BURSCgoIQGRlJFqR2u520hnGONDc1NUGlUvW1KY+g1WoRHByMgIAABAYGuu2nTNM0zGYzLBYLZDIZaJomGbiRahniDJlMhksvvRRz585FbGxsr/9XVFRg+/btOHjwIImqxcfHIygoCMHBwaS2ZzTAZrORnJxM6pDLysrGjBlFRUUFsrKykJGRgaCgIEydOhXHjh0b8vYkEglZJHZ2dg74eoqiQNM0KIqCQCDAuHHjYLPZyLESi8V9mlMwBigcDgdJSUle+xO0trZCq9UiKSkJgYGBePbZZ6HVavH44497vOjr6OhAcHAwRCKR2/66zc3NEAgECA0NBZfLJcoNZzAL6tbW1n7rRE0mU7+k3Bl5eXkYN24cHA4H/Pz8XCZWvV4PNpuN4uJit9d2UFAQgO6gx2AVM7ti4mFlscGl7ZhStAmqH84CS58F2Bzg1LZBbYuBw+FAfX096uvricM9szBhMmgMbDYb7HY7nnnmGfzrX/+Cw+EAj8eDTqfr95j5miQHBQVh2rRpALql3AcPHvR6mxfDuYSbZtZfk52e7OnXSTt1K7EUAJaKCsxRKCASiRAfH09q0EcDQqGQjO+dnd0tvU6fPo1vv/0WU6ZMwVVXXUXmXy6Xi7lz52Lu3LloaGjA/v37sX///hF1C3eGQCAATdPg8/lob28HRVFkkc84IMvlcsTGxkKn06GpqQkBAQEDymwHoglqtZpI0G02G6qqqlBTU4PAwECEh4eDz+dDpVJBqVSipqYGVVVVXivfmGCUn58fIiMjcerUKTz99NN49NFH8cYbb+Cll14asd/hiy++wOeff46YmJheLSV//PFHQpKXLVuGXbt2+WT9Mn78eBgMBvD5/H7bNzJKQ+acTUhIgMVi8SowotFoSFmO3W5HbW0tjh49iq+++gqrV6/GqlWrsHPnTsycOXNMKFb6AmNiyQSJncGQ5t8CSVYoFMjIyACHw8H48ePxzjvvYP/+/b2uMavVCoPBALFY7PX3YjplOK8j2Ww2brzxRixevBjffvstfvzxR9x666145plnoNVqkZaWhu+++86rz/1dwdM+yWPFuCs4OBiTJ3fP6C0tLdi/f3+v11xxxRWoqKgYtP39UKFUKvHiiy+ipaUFTz31FEwmE5RKJVk0VVRUeD3gikQiJCQkkIwoTdNoaGhARUWF2wxYc3MzlErlkMkq06R+3LhxSE5OdvlfV1cXWlpa0NraSiz6xWIx0tPTSTbPF7JyRqrF5XLB5XJJCwCLxQKDwYCOjg44HA5wuVxMnjwZc+fOxcSJE3tFzGw2Gw4fPoydO3e6PSdKSkrIcY2Li0NnZ+eoyK4TEhJINK+wsHBUelT3h40bNyIjIwNAd+bUG5LsnNn3ROJH0zS0Wi2kUinsdjv4fD6ZQPR6vQtBtlgsZHHZ2toKmqYxb948rFq1CiUlJT4x8aNpGoWFhbjjjjvA4/Hw3nvv9UuQKYpCaGgokVUyPgEcDgcpKSluM+NM8EuhUIDL5ZJWIGw2GzabDVarFVqtdkBiPphMstVqxdmzZyGRSFx6qdtstl5ZV+fvFhsbS8a7hoYG0rLKaDTCarX2Gwgxcjio7nnvjOYKaKSdQOU54OtngRWvANo6AN79Zm1tbWhra0NlZSVpq+YcqGECewqFgmTtzGaz2x6TzrDb7ejq6oJYLPaJcdc111xD9mnr1q0+qUvzFXg9C/kJEyaQgF5mZuaI169RFIWkpCQYjUbweDxiTgl0/x7Hjh3DsWPHEBwcjCuvvBLz5s0jAaagoCDceOONuPHGG1FQUIB9+/bh119/JdeeTCYji1NmvrFarbBarTCbzdDpdF5/X6FQCBaLBYvFgvLychKUZSS3zu0amT65kyZNgsVigUAgGPK8oFKpemX/mUBSY2MjQkNDSa/z8PBwBAYGoqioyOtyNcacisfjISwsDBUVFfjHP/6BO++8E2+88QZefvnlEVGe6fV67Nq1C0uWLMEbb7zh8r/y8nKcPn0akyZNgkqlwvTp03H48GGvPo/FYiE9PR1yuRwVFRW4+uqrsXPnzj6Jr9Vqxblz5zB+/HjweDwkJCTg1KlTQzrf5HI54uLiAHSP/+fOnXM5b9566y1cffXVeOihhyAWi/Hyyy+TQPRgwWazMWHCBKSmpsLPzw92ux2NjY1obGxEXl6e14qT/kgy853GMkkWi8W46qqrcMstt8Bms2HDhg1Yt27dgOtymqZ9kiRhjh9FUZg0aRJWrlxJVB2MX9LGjRvx0ksvQSAQECXjWEnQ/C/ApyT5iiuuII9/+umnXicam83GokWL8P777/vyY/tEVFQUXnjhBZw8eRIffvghGdCio6MBdBNKbyOlGo0GMTExhAi0t7ejtLS0X5mqVqsFTdNQKBSDGqTEYjExkZBIJMSMpqurC42NjW6zVhKJBGlpaaTZe3Fx8ZAuMC6XC7lcDoVCAblcPmDWKywsDImJiUhMTHQ7SJaUlGDfvn04dOhQv0SMkVhOmDABLBYLMTExIy7LCw0NRUBAAIBucjTadcjukJWVhaqqKtLeKDQ0FDU1NUPaljOh8CSTDIAYZYnFYojFYiKjtlgsxCVar9f3WkTeeOONuOaaa/DGG2/41OV+zpw5SEhIwMcffzxg26PQ0FBERUXBYrGAw+GgoKAA+fn5xKU7ISEBtbW1vTwE7Ha714uMwdQkM9Dr9R5lxXk8HuLi4ojEtaWlBQ0NDWTBZDAYwGazcfr0afeLgligWuQHWkwBKiA+rgVYwPyzGOB/Ajx6P+jy+wBzD0E/2n03FJMok8lE6mlZLBakUin4fD6pPe/o6CAdCBiPhYEWqR0dHRCLxV5nkrlcLubMmQOgO9DjrqWhr9HW01Jc3u705PSe+7suPMXr8cAy/MuI842F2BqZjG3oziiPVDCaQWhoKCSS7nx4QUFBn6Sxrq4On376KdatW4fp06dj7ty5SE9PJ0GIpKQkJCUl4Z577kFJSQkKCgpQXl7e7+LVbrejvb0dbW1t0Gq1QyKsZWVlkEgkxE/g/PnzaG5uhtFoRG1tLWpra8HlchEQEACVSgV/f3/I5XK0tLRg8uTJ0Gq1qKurGzR5VavVfUp4HQ4Hqqqq0NDQgKioKAQGBoLP5yM1NRXV1dWorKwccnBAr9ejqakJarUaoaGhqKurg8ViwaefforGxka88soreOutt3D8+PEhbX8w2LJlCz788EO3x2Ljxo2YNGkSgO51prckOT4+HlKpFAqFAl9++SVaW1tx//3395J7O8NsNqOgoADp6eng8/kICQkZkgpRqVSSuTE7O9tt0H/btm1obm7G66+/jpSUFBw+fNjjuRjoHj8vu+wyrFixAlqtFhUVFaitrSVdViZNmoQHH3wQjY2NyMrKwsmTJ5GVlTXo84hxsu+PJDv3mR4rUCqVWLRoERYuXIiSkhJs2bIFRUVFA44xbDYbQqEQFEX5LFkTFhaGa6+9FkFBQfj222+xY8cOl33o7OxEXl4eQkJCYDKZEB4ePibr00cFnraAGlqXWgA+JMlsNpvURdpsNuzdu7fXa2bPng2j0YiTJ0/66mP7xIQJE/Dkk0/iu+++c3FN5HA4sFgs4HK5Xp1oXC6X9IJlereWlJR4VKvCmHWo1WqPFtkikYi4FzNoa2tDe3s7srKy+iSZfn5+SElJIQQ5Ly9vUJM3i8WCSqVy29OZAZM1s9lsUKvVmDJlCiZPngylUkleYzabSYabkdMNZnIxGAyorq5GREQEAgICvIrYDxZ+fn6IiooCAGKgMlbxyy+/4O677wYAzJ8/H59//vmQtuOcSR7MxGwwGGAwGDwmjvfeey8mT56MJ5980iclDwy4XC5uv/12fPzxx+jo6CDR2r6g0WhAURQkEgksFgtZHOfn5yM6OpooRTgcjtdtHy6G83nMYrF8FiVms9mYOHEiuFwuCU4UFxcjLS0NUqkUFEXB398fFouFLPLdoZPTHeDiUzb4sS6qhWzdDSguBaYtBg74thWPw+HolSXWarVoaGgYVE9yZ+m8x67ebjB16lRC/o4cOTLmzKYYJLa3oLa5Ftv8uoOpI9nDnaIohISEAOiW8noyDlgsFhw4cAAHDhyAQqHAZZddhrlz5yI8PJz0SVer1Zg+fTr0ej2ysrJw7NgxVFZWkuAJh8Mh5n5KpZLMPQaDgZRzePq7GwwGZGdnIy0tDXw+H4mJieBwOC5mTVarlZQKiEQizJ07F83NzaROUalUQqfToaKiwiNJrkAggEQiGfB4WSwWFBYWor6+nhi1BQYGQqlUoqCgYMimnBUVFQgICEBXVxd4PB5Z/G/btg1NTU147LHHsH79+mFvP9PU1IRjx45h0aJF+Pjjj13+l5ubi7q6OgQHByMtLQ1BQUFeJTgmTJhAxr89e/bgxIkT+M9//oP58+dj9+7dfb6vo6MDLS0tCAgIGBJJ5nK5CA4OBk3TqKmp6ZdonTx5EmvXrsWqVavQ3NyML774wqPPSE5Oxl/+8hdwuVx8++23OHDggFvyKxQKkZqaivHjx+OBBx4Am83Gjh07cOjQIY/nOeea5L5IMqOwGo0SP2fw+XxMmTIFs2fPxvjx43Hq1Ck8++yzqK2txcSJE8FisQYc10NDQ4lqxFsVh0qlwi233IK4uDh88803eO655/oszdq7dy8eeughVFVVIT4+/g+SPILwGUmeMmUKidYfP37c7eJ6yZIl2LRpk68+sk8kJSXhr3/9K/7973/3ijjabDav20+IxWKMGzeODBBarRalpaWDiix5UpfMONup1WoSYWcm6OPHj+P777/v871BQUGIi4sjNS+5ubke97tls9kkY31xFk6v15NIvU6nA4/Hw6xZs3D55ZcjJSWFvN9gMEAgEMBmsyE/Px+HDx/G1q1bh1wnV1tbi7CwMCIVHQkHVyYQwkQNnaWDYxH79+/HHXfcAQ6Hg7lz5+LLL78c0sQ0WLn1UDBlyhRMnz4dDz30kM8z89HR0WhubkZmZqaLysMdmIU4Y9ASFhYGPp+P+Ph4nDhxArm5uRg/fjwkEsmwyGudM8mMe7cvFhOM466/vz9KS0tRW1uLmJgY8ttWVlYiICAAIpEISqXSLUmmCoCwMDai+MANQQ6AC+CaLy68oGolIDgKRM0AjjAf3H3HVGgq4DtYLJZBS/ecSYqfn9+QzzVnldSuXbuGtI2RwmV1ZXiM6u43Hh0dTZzihxtKpZJkjYYS9NJqtdi4cSO2bNmCOXPmYP78+cjIyIBYLCbu6UyGubq6Gnv37iXuwGKxGAqFAgqFgsihRSIRoqOjERERgdraWuI8PxCMRiMhygKBAHFxcRAKhW6NGg0GA1588UWw2WzinSEUCiGTyZCWloa2tjaUl5f3u/hWqVQwmUweB150Oh3OnDmDiIgIhIWFgcfjISMjA+fPnx/S+W0ymXDkyBG3c9vJkyfx9NNP46WXXoLZbMYvv/wy6O0PBhs3bsTrr7+Or7/+utfx2LVrF1auXAmg28Dr4r7Gg8GECRMgl8vR1taGs2fPQq/X4+2338YzzzyD6urqfhUYDEnm8XiDbsnDrOMoihow0E/TNDIzM2EymbBq1SpQFIUvvviizzWIVCrFypUrMWvWLHz99ddu1ZzOYBJWDBlPTU3F5Zdfjn//+984f/48fvnlF5w4caLfa8ZZbn3x+pf5fkxdvydrP6VSiaioKCiVSmL0ydy6urpQX1+PiooK1NXVoaampl9DT5VKhYiICERGRiIlJQXBwcGw2Ww4ePAgPvnkExJkCQ0NJd+hv3GSy+UiPDwcXC4XLS0tsNvtQ2rJpFAocPPNNyM6Ohrt7e345z//iaqqqn7Ph127duGRRx6BWCxGYmJiv4GcP+Bb+IwkL1hAdHhuB9KJEyfCz8/PbZ2yLxEYGIhnnnkGn376qdeSHHdQKpVITEwkLrPl5eVDkrX2R5I5HA4iIiKg0WjIAt9ms6G6uhq1tbUDXpTR0dHkwrdYLMjLy/NokcRisRASEoKwsDBwOBwyqOl0OjQ0NECr1ZKBMC4uDrfccgtmz57dK1Nns9lw5swZHDhwADU1NVCr1bBarUhPT3db3+kJbDYbmpqaEBQUhKCgIK8kZp6AoigkJyeDx+MRAjVSbTGGCr1ej+PHj2PmzJnw8/PDlClThlSbPBS59WBAURRuu+02fPPNN8MiXS8sLMQjjzzi0oOwLzgHgRobG9HW1obx48fDZDJBrVYT6SSHw0F4eLhXbdvcwXlhwWSSfQG5XA6BQEDkpywWC35+fjCZTEQRweFwSPusvsAcOzbVx7Vm2g3sGJmet2azedDSPefA4FBJcmBgIOlGUF9fj7y8vEFvYyhgAgx6p0tY7N/zwLll6sIvuu8/WAkAYKN7vGKUBMnJyThz5syw11AzWWS9Xj/k4BqXy0VqaioMBgM2b96MdevWQSqVYtasWbjkkktImU9YWBhWrlyJW2+9FSdPnsSuXbuQmZmJ6upqsHtaiwUGBkKhUMBisSA8PByhoaGor69HVVXVgGO5yWRCVlYWxo0bB4lEgtDQUIhEIhQUFLglHoz5Um1tLdRqNSIjIyEQCIjRV3NzMyoqKtxmitzVIw8Eh8OB8vJy6HQ6onJJTk4e8nqkv+BvSUkJ/v73vxMjr+HscV1aWorCwkJcddVVvQyK9u3bh1tvvZX0rt2wYcOQ1gASiQTx8fHw8/PDvn37iOladnY2Pv/8czz33HN4/PHH+1Rg8Pl8GI1GWCyWQX++xWIhfhcikWhAwzeDwYDW1lasXbsWV111FcLCwrB27VqXLLpMJsOMGTNwyy23oKCgAPfdd9+gzyeappGTk4OcnBx88sknmDdvHlasWIH7778fJ0+exMGDB5GZmekyhjAdHIDu87GvTDLQPc8y60mJRELa+AUEBCAsLAxRUVGIjIyEWCwmpU06nQ46nY70Cmcc/CMiIpCWlgaRSASTyQSdTkc6TAiFQvD5fFIyUVtbS4zPPvnkE7cZcmbc0mq1/f6eDocDzc3NCA0NhVwuJ118Ojs7wWazYbFYoNfr0djY2Oca9/LLL8ddd92Fs2fP4h//+AfYbDY0Gg2USiXS0tJQUFDgNtnG+A/I5XKXVqn/8/DUuGu05dYBAQGknVJTU5PbQXTJkiXYunXrsBINLpeL559/Hvv37x+WmrHAwEBSOG+325Gfnz9kyUVzc7OLgysDtVqNmJgYl8GnpqYGNTU1Ay5yWCwWkpKSXEyT8vLyPIqeK5VKxMTEuEQG9Xq9i4xLIpFgwYIFWLBgASIjI3tto7q6Gvv27cOBAwdcFqNarRaJiYlgsVhITU3FmTNnhnQeMD0kuVxuv61ffIHIyEiijGAWI78F7Nq1CzNnzgTQHbgaCkkeqtzaUzCBlZGo6wT6XwAy1wrjoGw0GtHR0QGlUkl6lKrVatA07VNJOAPnCZGiKJ+R5MbGRtJeKSwsDC0tLUQuzHwPZlzoLzs7sHLC1mPeNfygabrfgIc7OGeSnVvmDQbz5s0jj8d6FpkBo3xJTU0lsuHc3Nxh+zxmTAYw5D6yFEUhJSWFnKcVFRWoqqoCABw7dgwikQgzZ87E3LlziWElm80mvZdbWlqwZ88e7N69G83NzWhpaQGfz4dGo0FoaCgJAgcGBpJsVH+wWCzIysoivbkFAgEyMjKQm5vb75za1NSE5uZmaDQahIeHg8fjEWfqyspK1NTUuFxX/dUjD4TW1lZC5gUCAaKjo8Hn83s5RHuL/Px8vP/++3jqqafw4IMP+qQFUl/YuHEjHn74YWzatMllndDe3o6TJ09i2rRpUCgUmDRp0pBK99LT0+Hn5weHw9GrRenOnTsREBCAv/3tb3j88cd7rTGY/tVCobDfrgX9oaurC35+fggICBgwoMEE+drb2/H888/j5ptvxiuvvIKuri50dHRAJpMhKioK5eXl+Pe//40TJ04MaZ+c0dnZiU2bNmHTpk2IiIjArFmzcPfdd0MikaC4uBjV1dWoqqoi5zjTHu3iNZ3RaIRAIEBERAQ++eQTtLa2ws/PDzweD11dXWhtbUVLSwtqa2uxb98+VFRUoLKy0uO1oXOW2c/PDzRNw2g0wmQykVKLgbbFqDS7uroGnN8dDgd5rbMnD5vNJsFmf39/hIaGorOzEw0NDWhsbITD4YBIJMKjjz6KmJgYvPnmmzh9+jR5P/NePz8/TJ48mbSLdR5jmGTXJZdcgrCwMK/Ovz8wOPiEJDN9wwC4lQGEhIQgMTERr732mi8+rk/86U9/gtVqxWeffebzbQcEBBCCbDKZkJub61WLjebmZpc2SFwul/RXBroXhEzU2xMZN4/HI1FvoNvFtqSkZMBIJ5/PR2xsrEsNcUtLCyoqKsj3GzduHBYsWIAZM2b0MuwymUw4cOAAdu3a1Wcf45aWFtK+hmnEPpRsjF6vJ62GhtMxUalUIiwsDED3vg/VAGs0kJWVhebmZqhUKkyYMAFKpXLQ2bPhlltPnToVO3fuHPYaJUa63F9wiTmPnCektrY2KJVKSCQSch74wqTLHRhjM2Z/B0sC+4LD4UBLSwvCw8OhVqvJsbZYLGRyZb4zl8vtsxaa8Vv49BzwfycB+uDKC/+s6L6j3Jcz+xzO9ZKewluSTFEUIckOhwP79u0b9Da8hXNbqMaeFrHqJKcnVSsBANRFZWrt7e2orKxEZGQkFAoFIiIihq2WzTnDP9QxIzw8nKhYysrKeo27BoMBu3btwq5duxAUFIR58+Zh3rx5xJguICAAN9xwA1asWIGzZ89i165dOHHiBCHEYWFh0Gg04HA4iI2NRVBQEIqLi/sNBDocDuTn5yM8PBwRERGgKArjx49Hbm5uv/JomqZRV1eHhoYGhISEIDw8HGw2G1FRUZBKpaisrCTB56Fkki8+LmfPnkVKSgpkMhlCQkJgs9l8/lvv378fqampuPXWW/Hmm2/6dNvOyMzMhE6nw7Rp03Do0CGX/+3evZu0YZs2bdqQSPKECRNgMplQUVHh1ixy3bp1UCqVePXVV/Hyyy+7BFNiYmKIG/tQVUUNDQ2ELEokkn7Po87OTtjtdrDZbPD5fLz99tvEjJXJpJ47d87jUrrBorKyEpWVlVi/fj1iYmIQExODsLAwTJs2DeHh4cjIyCDlOu4yyWazGWVlZXj//fdRW1tLarp94SnDZJq9QWhoKHg8HslI9weapolpLJ/PJ91dOBwOBAIB+Hw+FAoFOBwOpFIppFIpNBoNqqur8cwzz6CtrQ333XdfryxzcXExDAYDoqOjSaljSEgIaTNms9nQ0NCAX3/9lYxBcXFxyMnJ8eq7/y5g6bkNhNFuAcX0jwPgNpI1Y8YMZGZmDrvZSXp6Or799luf1436+/sjMTERFEXBbDYjOzvbo+xsf3DOJDPbZy5Wq9WKoqIij2XJbDYbqampZPCuqalxWz/lDKbtTUREBFmYGwwGFBcXo6OjA/7+/rjyyiuxYMECIlt1xvnz57Fr1y4cPnzYo2PBtHiJjIyEUqkk9UCDBVOXOJC79lAhEAiInMVoNP4mG7fv2bMHN954IyiKwuWXXz7ovnrDLbeOj4/Htm1D6687GLDZbLDZ7H6jyczi3pl86XQ6mEwmUBSF4OBg2O121NXVDQupd943X5JkoLuOn8mgaTQaGAwGl9+T+c4URYHL5boloA6Hw0VWN5roax/7w8Vy68GCCTQBwOnTp4dVvTIcqKqqgkwmg0KhQHh4OHQ63bB8B2eSPBTXV6beD/AsMNnQ0ID169djw4YNmDRpEhYsWIDJkycTNcaECRMwYcIEdHR0YN++fdi1axdKS0tRV1eH2NhYyOVySCQSZGRkoKGhAeXl5f0G05hgdVxcHHg8HlJTU5GVlTVgNsfhcKC6uhqNjY2IjY0lbtgKhQKlpaWor6+HWq0mGfOhwmq1IicnhzjXR0REwGaz+dxo8Ntvv8Xf//73YTdiOnToEGbMmNGLJGdlZcFisYDH47msOweDhIQEmM1mGAyGPoP17777Lm699VY899xz+PLLL3H69GlERkaStVBDQ8OQAxtNTU0ICQkhMv7+6p9pmkZHRwept6+uroZer8fRo0eH9NneoLS01EWh4Ofnh4ceeggLFixwK7dmWpBarVa0tbWNWJnKYDDUgIfZbHa77mWxWFAqlaSVYWhoKP76178iOzsbr732Wp/XTG1tLbRaLaKiokh2XiwWQyQSgcViITg4mChUgO6Syj9I8sjAa5LMSGgBEEfHizFz5kxs3LjR248aEC+99JLPt8nn85GSkgIWi0UmIm8JMgDSdsHZYIvJHl8sx+oPTO0sc7EzJj39gWlvwZAhh8NBZGDjx4/HFVdcgSlTpvTq29rZ2Yl9+/Zh9+7dQ5rUq6qqSCR/qCTZarWCz+cPS1sBFouF5ORk4gaen58/6o6MQ8GePXtwww03gKIozJ8/f9AkeTjl1nK5HEqlsk/VgS/BEM7+1BSMAsb5NYzLq1wuJ3VGvl5sMnCua6MoCjwez2cyKqvVirq6OoSGhkKpVEKv17vUsjl/577IOfMa5v/UabcvGxGMRiZ5/vz55PFvRWp9Mc6fP4+JEycS2XVmZqZP5jBn9NcKxhMolUpSqzmYscHhcBDzIYVCgcsvvxwLFixAYGAggO6F/HXXXYfrrrsOeXl5JLArl8sRExMDHo8HjUYDhUKBvLy8fgP5DQ0NMJlMpDXcuHHjkJWV5dH3tVgsyM/Ph0qlQlxcHNhsNuLi4iAWi6FWq13kl0OFw+FAbm4u0tPTIZFIEBMTg66uLo8ctj1FY2Mj7rrrroFf6CWOHDmC66+/Hnw+3+VcZYxAMzIyEBAQAI1GMyh5P5fLJX4t1dXV5LejKIq0tmQyoJs2bUJLSwuefvppVFZWYv/+/WhuboZer/f4HKUoCmKxGFKplGQbBQIBFAoFeDwekfD2t95rbW0lhnRcLnfMeKMw/coBkJZWzjAYDET5xygcxxJ4PB6Z/3015zJ1y83NzYiMjMRjjz2G8+fP4+DBg4iMjIRWq4XdbgdN0+ByuRAIBBAIBJDJZKRO3WazEbd+Zt612+0ucnBG4fYHhh9ek+SYmBhi/OIushEcHIzQ0NARafs0HGAmNIfDgZycHJ9dTM3NzZDJZMjIyIDBYIDZbEZ+fv6gSUlcXBzpl1xVVTXgYl4mkxFDKgCk7+iUKVPw5JNPkmi+M3JycvDLL7/g+PHjXg/Q9fX1iIiIQGBgIMrLywed9fe0l6w78Pl8F3nrxYiLiyODeXFx8ZBbaow2mpubkZ2djYyMDAQGBiI8PHxQQQ0m4GKz2Xy+mA4JCUFzc/OItPBiJpj+zjHmf861wIzLJWPOV1RUNGwLE4vFQgIxLBYLYrHYp9K5iooKKBQKOBwOcDgcl21f/J3dwZnA+6o91VAxFJLsTSaZaaPFbMcXRMZbBDIPnJW0A6hqbTYb8vLykJGRQYy8srOz+wweedtibyittgIDA4lr7FD7j2q1Wnz//ff4/vvvkZ6ejiuuuAJTp04lc0ZKSgpSUlJw++23Y8uWLdi9ezcCAwMRHBwMPp+PjIwMFBcX95tVam9vx/nz55GcnAyhUIiUlBTk5OR4bODU3NwMnU6HpKQkyGQyBAcHIyYmxmelHHa7HefOncP48eMhEAgQHx+P06dPD6vJ5XCgpqYGjY2NmDx5Mn799VeX/zFzG9CtHhwMSWY6ZABw6ZARHR1NDJwY9QzQXeK1du1azJkzBw888ADOnz+PnJwcBAYGIjs7u1ddO4vFgkwmg1KphFQqhUQicRuAtFgs0Gq1Hq2BWlpayL4FBAQMuebf12BIMnNuXXzNm81mOBwOsNlssqYYS3A2nPX1Ogfo9oQpLCzEpk2bwOVyERYWhpCQEHR1dbk9Hsx60+FwoL29HVarFRaLBSwWiwToWCwWIiMjER0d7fP9/U3it2Dc5Sx5cWfYNX36dJw9e9ar+t3RglqtJvVOFRUVPiVNCoUCNE2TmtG+msr3h7CwMAQFBQHozkwP1MOXmZCZxW51dTXGjRuHRx55pJfTtlarxZ49e7Bnzx6v+hFeDK1Wi8jISHC5XAQEBAxqccBE3QAMOjqempqK+++/Hxs2bOhl1gF0/9aBgYGgKAp1dXU+dzEeaWRmZpKFxLhx4wZFkoVCIQDfRVedwZjejQQ8ySQzuNgwq7i4GDabDSwWa1gJPdNjHLhAkn0JJrhntVrh5+fnEoTzhCQ7P/9bJMkXt4AaDGJjY0nNelZW1m+OaDhDr9ejtLQUcXFxkEqliIqKcmvuFBYWhn/84x/45JNPBlV/zRxnpv92X3233UEoFJLfxldS8OzsbGRnZ0MqlWLu3LlYsGAByb4oFArccccdWL58ObZv345Dhw4hNDQUHA4HCQkJkEqlKC0t7fNcb2lpQVlZGaKjoyGTyZCYmIj8/HyP981sNiMnJwfJyclETebL654p12JaWEVGRg5YfjUWceTIEcyYMcMtSWaQnp4+KAPIqKgo8pghySKRiJBQoLeqpqmpCWvXroVOp0NiYiIiIiIwbdo03HXXXWhoaMDRo0fJmiIiIgJGo9FFjQV0j8Nmsxkmk4lkqru6ujw63xmy5O/vD6VSOWZJ8sWBZGeSPBYzyc6+Nr4myYmJiZg/fz7uv/9+tLW1QaVSISwsjJicMXA4HKT9W0dHB7q6uqDX6/ucazgcDqlR/wMjA69JMtMaA3BPkmfMmIGtW7d6+zEjDoqiEBMTA6BbcupLuSUjuaqvr4dCoRgSQQ4ICCADfkdHx4C1s6GhoST6xGazERkZif/7v/9zqT8FuqV5GzduxMmTJ4dlUajX66HX6yGRSBAdHY3W1laPP4ch8jRNe0ySRSIRbr/9dsyZMwdffvklDh486PZ1HR0dpPZyJKTADJwbQMh7yj4pN5Ex5yHcE8syZyfbcePGYceOHR7vE7NgG45MOiO/Gk7QPcdxv82GkwD8ORzc08/+AL1J8kgG9Zxrg4cj4s5s/+JrxhOSzGThaJoeVZLI7Mdgx0m9Xk/KVwab3Rw3bhx5PJzO0CMFRsXTXyus6upqvPPOO/jLX/6CWbNm4f333/cokMnUeIpEIqhUqkGRZMbA0maz+dwcr7OzE1u2bMGWLVuQmJiIxYsXY9q0aeRaW758ORYvXoyDBw+S9ivBwcHgcDj91orW1NRAIBAgODiYzMXOmcmB4GwIZjQaIRQKB72N/tDe3o6GhgYEBQUhJCQE9fX1vzk33F9//RVvvvlmL8l1aWkpycY5rz89QWBgIJmDmGPNtO/hcrnIzMyE3W6HQCCA1WqF0Wh0GfecM8cCgQATJ07EtGnT8Pe//x1tbW3YtGkTpFIp8X/o7OyETqcj9blDBeMTM5Yysnw+n6gsgd5jM0OSAfTbZnC04Ly/jB+QL8DhcHD//ffj66+/Jgmmmpoa1NXVEQk1U745mDkpNjYWUVFRxNtnKIqd3x1s8CyT7EVMwWuSzMhzOzo6emUc5XI5oqOjfWJLP9JQKpXE9bWkpMRnGRSRSIT4+HgA3c6BFEUNeuHHOEQDIOYT/e0f06BdJpNh0qRJSExMJPvC4PTp0/jhhx8GFREfKkpKSpCRkQE+n4+IiAiPFgYcDodkApi6jv4gkUiwaNEiXHPNNSgqKsIDDzzQb0ackaSazWaEhYV5baQy2igrKyOLL8YzwFMw58VwEcXhJskMRD3XlaGf+nVmkvFGxu8tmAXgcGSS+4Pzd+7remIMu4YqgfUVmPKQocjeRSIRFArFoBdqziT53Llzg/7csQamDtJoNJL2Zu5w8uRJ5ObmYtWqVfjwww9x4MABfP/99wMqipqamhAZGQmVSoWamhqPSocCAgJIuVBFRcWwLvrOnz+P119/HSEhIViyZAnmzJkDDocDHo+HefPmYdKkSWhsbCSyeqPR2K9DdGlpKfh8PumG0NbWNiiFk8PhAE3TJMsbFhaGzs7OQQUY+kNZWRnUajVYLBaCgoJ8RsBHClVVVdBqtUhNTXUpdaBpmtTZS6VS+Pv7e3zcY2JiYLFYYDabyRzPYrFcauqZbO9AMJlMOHLkCI4cOYK5c+fioYcewhVXXIFXX33V5wFmZn/4fP6oK3oYeJpJBjCmyD0Do9FI1jhCodBnJPmqq66C1WrF5s2bXZ53OBxDDjSz2Ww88MADOH36NFEpKBSKYW3F9ge64ZWVKo/HI3JkdxKQxMREl1YHvyW0t7dDp9NBIBD4VIqRlJREnCF//fXXIRXgJyQkuJhL9bewEIvFmDlzJpYtW4ZHH30UkyZNgkgkQnNzM2iaxsGDB3H//ffjb3/724gQZKDb4I2RMzOmQv2BoijynWma7neyl8lkuP322/HZZ58hISEBL7/8Mp5//vkBF3j19fXQarvzuhEREUPuqTpWwJwbQLfM1FlO1h84HA4hT8NBkkdkcp/dffNTWMASAjYJu09jKk96BQ83mMl5pEky852tVmufk7c35NSX8IasMwvowcitGRM/5v0D9dQd6xAIBCQ4ajQaB+yjazAYsGbNGjzwwAPgcDh477338NBDD5EWhe5QU1NDfp/4+PgBHdFFIhHi4uIAdGf8R0pGWltbizVr1uDuu+/G5s2bYTKZUFtbC7lcjsTERPzlL3/B7bffjksvvbRXGZIzGLLGjCHx8fGDlkFGRETg5MmTZKz15Lh5CrvdDg6HA4vF8pstH8rPzyfnrTOczxWm5MwTqFQq8Pl8iEQiInV2zhbHx8fD399/0IHcrq4ufPbZZ5gwYcKQXPQHwlgs9WC6jPSVSXY2pRyrmWQejweRSOTTefeKK67Apk2bfPqbXX/99QDgUirY39g01vHCCy+ApmmXG9Nea6zBK5LsPDj1RZL7kyyNZXC5XEgkEhiNRiK79hb+/v6EJBQVFaGgoABRUVGDGpCDgoJcIu/9EZnU1FS89tprePzxxzFhwgQYDAbiQpidnY0///nPePPNN4etd2Z/KCsrg9lsJrL2hIQEFyMFBiKRCKmpqVAqldDpdKiqqnL7neVyOVatWoVPP/0UEREReO655/D8888Pqu0As+ChKApJSUnD4qB9MeTBF24MuXPgwo0BL+LCzQxX+XVfuFhy7QmcJ7PhkueNVCZZbL9A7KRSKcmkOcNgMMBisZB2UaMB5jiPNEkWCASw2+29Mn4URUEmk8HPz49ck2Mhk0zT9JDq2RnzLsY91BNER0eT2vzfutTaG9f+2tpavP3227jvvvtgt9uxZs0aPPbYY26Duw6HA8XFxdDr9RAKhcjIyHAbbORwOIiMjERCQgJZZBcVFY14dqy1tRWfffYZ7rzzTuzZs4dcB52dnYiLi8M999yDt99+G5deemmfY4PdbielTgKBwKXm1RNER0ejpKQEBQUFpI2Orxa/ISEhcDgchAj8FnH+/Hm3JNk56O2uRWVfYI6tc7beYrGQ9SuXy0VaWhqmTp2KlJQUoowQiUT9zlsWiwW1tbU4duwYli5d6vH+DAZMJnIsZJGZtoHOcuu+jLuA7mtjLNbRMuOgr5Rk8fHxUCgUPm3RFR4ejmXLluHdd991yRwPlFwa68jNzUVQUBC5zZw5c/AbsQ7iNkR4dWY4k2R3mbqEhATs3r3bm48YNRiNRlRXVyMiIgIqlQpVVVWIjY3FpZdeijVr1gxpm4GBgYR4Nzc3k0E3JCRkwL6QQLckJCYmBgaDASaTye17+Hw+5s6di6uvvhoRERGQSqWgaRpGoxGdnZ3Yvn07fvrpp2FrPu8prFYrzp07h/T0dNA0jcDAQAQGBsJgMKCtrQ00TUMgEECpVJLj1NXV1YvQx8fHY968eZg7dy4yMzPx1FNPDZgl6QtMe4n09HQXF9ixMCkNBc4S0dTUVPzyyy8Dvsd5MTUcmeS2trYRy9IrzAZQoNHJ5mHKlCkk49PW1kaIAhNNBrqvr+Hu5e4OTCZ5uGqS+4JQKOzV71StVhNHf6D7fDAYDKNuvOjn5wedTjek917cBsqT7/J7klrHxMQQ45ySkpIhKbsaGhqwZs0afPPNN1i2bBnefvttZGZm4pdffsHZs2fJYri1tRU8Hg9xcXEQCoVIS0tDe3s7urq64HA44OfnB6lUCoqiiIIhPz9/VK47Bnq9Hhs3bsT27dsxf/58LFmyBGw2GzKZDGFhYfjrX/+KxsZG/Pzzz/j55597SXvb29tRU1MDuVwOjUYDrVZLVEn9gaIoREVFoaysDF1dXWhtbYVKpYJGoxmycuG6666DxWLBzz//TErhWltbfSbhHmkUFhZi1apVvSTGzkkZT0kykzFUqVS9jKTKy8thMBiIUoLL5UKpVLoQEYfDAYPBgK6uLnIzGo2gaRoSiQQURWH79u14+umnsX79ep/3Iydt+MaA3JpR79O85gABAABJREFUIXkqt+ZyueDz+aM+jziDzWaT7+Erteu8efNw6NAhnymvWCwWHnzwQfz0008oLS114Vy/5Uwy0L3e/i0oXLwiyc6D08WZZDabjdjY2CETyrGA6upqBAcHE/v22tpazJkzBxs2bOjT+KQ/XDyYMNLhqKgoj0hyQkICubAvzm5oNBpcddVVmDdvHlloMzUjHR0d+OKLL7Bt27YxNUgZDAacOnUKoaGhCAkJAZvNhkgk6hX1ttlsqKysJOZpSqUSc+fOxdy5cyGXy3H48GE8+uijPsmId3Z2oqysDLGxsZDJZGQRM2xwVtb1jHlUxIWnaMbHpv3Cc54Kg0tLS0nvUXetvdzB+dgPNHGwWCwXomUymQbMUDU1NYHL5UKhUHi0kBwItNOpQjGnds9xFMOKYEEnmlhitDdbIBAIQFEURCIRwsPDUV5eDqPRiKt63vYfoRBpo7BYZ67Jkc4kX+xiLpPJoFarCUFmWtPx+fxRX2QrFIpeY65AICAZZqbO0B2cA4L+/v4eERDn6+W3qoYCuoMezDzd0NDgdaeC5uZmfPDBB/juu+/wpz/9CatXrwabzcaBAwewd+9eVFZWor6+HhaLBTExMRAIBPD39+8VGKNpGlqtFpWVlSPSDs4TmM1mbNu2DTt37sTs2bPxf//3fwgNDSV9bW+66SYsX74cR44cwdatW1FUVETey7RaoyiKtF0aqL5ao9GAoigyrzmvC4YCFouFa665Bh988AE0Gg3Jjv3WapGdwczp4eHhLvP7UEgyQyra2tqgVqsxbdo0HDt2DED32qy+vh719fWQSqVQKpUQi8WQSCSESLFYLEgkkl4Em2mPxygpCgsLMWPGDGzbtm3oX/wiOJ9LXC53TCh7gAtuy0D/xl1jkSQ7z7W+2C8ul4vZs2fjmWee8XpbDK699lqIRCJ8/fXXAOBibBgQEOCzzxkNxMXFoba2FiaTCceOHcNf//pXl17QHsHScxsIo9UCqj+SHBUVBavV6lNX6JGGw+FAbW0tkdxUVFTg7NmzWLhwIb766qtBb49ZxEmlUvj5+aGjowPl5eWIiYnB4cOH+31vZGQkcaIuLS0lC4sJEybgmmuuIf08GbBYLDQ2NuL48eM4cODAmJUM2mw2VFRUoKamhrQ4kMlkRBau1+tRXV0NNpuNOXPmYO7cuUhJSUF2djY2bNjgk97NF6Ouro4QhtDQUOh0ulEnCUOB3W6HTqeDQqHo1ZKiL3iSSWaxWAgODkZgYKDLRKPX68HlcqHX66HVatHY2NirLsdms6GlpYVkXIYbM00V0FE8fGpUo6CgACEhIQgMDERYWBja29vR1tYGicUCPY+HFrEY8LG7ridgjvNIZpKdo+jM58fGxkIikcBkMqGoqAgSiQQ0TYPP5w85i+srKJVK6PV60sucw+EQks+gvr4edXV1vYI7Q+mV7Hy9+DojNFJwNons6uryqWt/a2srvvzyS6xbtw5paWm4/PLL8eabb6Kmpgb79u3DgQMHcOrUKQQHB0Mul4PL5bqMDVqtdtQX+n3Bbrdj3759KC4uxuWXX47p06cjNDSUBBxnz56N2bNno6SkBNu2bcPhw4dhtVpRWFiIjIwM8Hg8JCQkID8/v1/CGxMTg8rKSiKJZkjcUD1QJk+eDAA4e/YsJk2aBKD7dxpLxGSwYPrUM/42DJwzUJ7WJDPH12az4eeff8Y999yDnJycXuMF40rNgCnTkEgkEIvF5MYEE2maRmtrKxknf/31V8yaNcunJPliJ+bRvna4XC45bsw53lcmmSHRvqq19xUYkmmz2XxyjaSmpqKzs9Nn42xQUBBuvvlmPP/88+TYOs9Fw1H7PlI4ceIEVq5cicLCQmg0Grzwwgs4fPgwxo0bN6qqInfwiiQ7R4cvjvInJCQM2Jbot4C6ujqEhYWBzWYjLCwMW7ZswRNPPIHvvvtu0OSsoaEBwcHB4PF4SElJQXl5OUpLSzFjxox+36fRaEhmQ6vVoqWlBQsWLMCSJUt6GalYLBYcPHgQxcXFpAZ5qPLjkQRDni4mo6mpqbjvvvswY8YMNDY2Yu/evXjrrbeGfeFaXFwMiUQCkUiEhIQEIq36rYEhyRe3+uoLntQkBwcHIzo6utfEwmKxwOfzieNrZGQkIS7Ok3p9fT2CgoIGVS/eJ+IuPCRZZUaFFAyE96Tgz9magCDA3l6ED6UKGFhcvDZLiunWNvyk6kChXYW6CH+gwvtdGiycj7Onv5O3cDan0el0JEsCdCto2tvbB92LfLigVCqRkZEBiURCArOM2QfzHSwWC4KCghAQEECyQwycxwpPpf7Ov4MnLs1jDWw2G8nJyWCxWKSMZDjMf2iaJj2J33//fcyYMQOXX345Vq5cibNnz2Lv3r04efLkb7JVSW1tLfLz81FWVgahUAiNRoP58+eTAEpsbCweeugh3Hnnndi6dSu2bduG6upqhIeHQ6lUIjY2FsXFxX1un+lVrVAoEBsbS+qzB51N6cGiRYuwbds2qFQqkun7rXdpALol1wkJCS7lQlarFTqdDjKZjHi0DARneeqBAwcwY8YM3HnnnQOqHW02G3Q6Xa9AITPXURQFo9FI5rijR4/i7rvvhlwu99k65WKSPNoQCoUQi8UuXhEXB4SYYA8T/HXnOTNaoCgKarUaAIiJrbeYNGmSiwu7t3jggQewe/duF0MrZwI5FntPewrn3ubnzp3DiRMnUFlZieXLl+Ozzz4bxT3rDa9Icn/SzJiYmH4niN8KbDYb6uvrERoaCrVajaNHj6KtrQ2zZ8/Gnj17BrUti8WC/Px8pKWlgcPhIC4uDiKRiCxm3C1iAgICSB9Ji8WC2NhYPProo72K9puamrBjxw7s2rULUqmUuIZWVFT85shdcHAw5s6dizlz5oDH4+HgwYN48sknR1Q2ZrfbkZ+fj/Hjx4PNZiMlJQVnz54dknGQx2DiHVc6PceMue1Ozw2inJxZ4DNyp4GyFJ5kkpkIpkgkQnZ2NsxmM9hsNoRCISQSCfz8/ODn5wcul4vw8HCEhoYStQDQHSwajNmKL8EGDbnNCAOPiw6qe9IOZ7Wj0K5CAy3tVaM7EnCe+DzN+HsLhiwy7U6cs7JjpRuBQCDAuHHjIBKJEBQUhI6ODlitVrS2tkKv1xNvBhaLhejoaCgUCnC5XAiFQpcxbyiZZIYkGwyGET8ffIHExERyLRcVFY3IHGAymbB3717s3bsXarUac+bMwe23347Vq1fj8OHD2Lt3r4tEeayDMRRLS0uD0WjEkSNH8NVXX2HWrFm45ppriKGnTCbDzTffjKVLl2L79u0oKCiAQCCARqOB1WpFRUWF2+2PGzcO5eXlLvXvpaWlQ1JtREdHIy4uDq+++ipZL7S3t/8mAzwXo6ioCDfffHOv57u6uiCTyTw2JXMmyc3NzXj//ffx3nvv4cCBA0PyHTCbzW7n0/b2dhQUFPhUcm21WmG1WsHlciGVSkdEhdUfGKLOBCndJYyYY2O328n6Y6xAJpPBZrOBy+X6rC52/Pjx+PDDD32yrYULF0KtVuOll15yeZ5xYncOav8e0NHRgaKiIjJ2eQxP+yR7wXS9IsmMNJAxhnKGWq0esZZCw42mpiaEhoaCzWZDLpdjy5YtWLRo0aBJMtCdtcnMzERsbCz8/f2h0+kQFBSEefPmoby8HC0tLcQMIjg4GCEhIRAKhZg0aRJSU1N7yTFzcnLw008/4dSpU6BpGiKRiEzeOp3uNyN3DwwMxPTp0zF9+nTExMTg5MmT+Oijj3DmzJlRW6QaDAYUFRUhKSmJBDNyc3NH3TRjMHBecMlkMpeaFnfwhCQ3NzdDIBAQB3iGhHR1dRElgFgsRkhICOnTGR0dDZqmUVtbi/r6+kG7wPoSfnYjaiGDjtVDkql2AICDpuDn5zfiCxCLxUKyoiNNkplssXOUfyzUiAqFQiQnJ5PzUSAQ4NixYzhx4kSvYKJAIIBAIEBXVxdsNluvuejimmRPwJDk0ZaZDwXR0dEkiFpTUzMqpSJNTU349ttv8e233yIxMRGXX345/va3v6G9vR2//vorjh079ptQODHtv4KDg6HRaNDW1oZ9+/Zh3759SEhIwDXXXIOZM2eCxWJBIBBg6dKlsFgsKCgowKlTpwB0n8tVVVWwWq3EjFKtViMtLQ05OTkAusfakpKSIas3rr32Wuzduxdms5mMIQON9b8VNDY2ujUpYuYnT0myc8ZZq9WiubkZX375JVavXo3Vq1f7tGxr//79WLx4MbZv3+6z9YJOp4NSqRwTMlvnOm3APUlmst80TYPL5Y6JDDiDoKAgiEQidHV1+WSMnzBhAqRSqU/UcUqlEnfccQdee+01t0EYvV4PmUz2uyLJYrEYMTExWLdu3eDe6Klz9WiR5M7OTlRXV7u9QFQq1e9mkNbr9WhtbYVUKoVarcbBgwexcuVKpKenIzs7e9DbMxgMyMnJQUBAAMLCwlBRUYHk5GSYTCaXDBtN01i4cCEuueQSmM1mF7J4/PhxfP/9972y9VFRUURiV1BQMKYJXWhoKCHG4eHhyM7Oxu7du/HSSy+NmbqE5uZmiEQiREREQC6XDyihGywsTl5jvGU9D5wTeYyr1CcXnqJ7SnssTm3l+orRekOS+8ooMkEjHo+HmJgYaDQaNDY2oq2tjfxuXV1dKCoqQkVFBVJSUsBmsxETEwOFQgGr1Yrw8HBS18Xj8cDn8yEQCCAUCiEUCskCc0A4Vxvc23PPvNX5qzIBytsBZAKoAWg5BVwCyD8xQkqb0Qk+vg+QY26nFtQItgVmrlculzsirVp4PB4JtvUnB3SnOfA2FxAcHIzQ0FB0dHTAaDSSbIzNZoPdbodQKISfnx+Cg4Nht9ths9lQWloKi8WC0tJSQpA5HA7kcjmUSiVUKhXJaLjzXrjY3XogUBRFFiAjRZKZY+3t8dVoNAgNDQXQXQI1rKaDHuL8+fM4f/481q5di8mTJ2P69Ol47bXXoNPpcPToURw9enRMm6OVlZXBz8+PLOSYoENhYSEKCwuxbt06LFmyBPPnzweHwwGPx0NGRgZmzpyJc+fOYfv27b1IXlBQENhsNkpKSlBdXY26urohz9VyuRyzZs3C/fffD7VaDYfDQdyyfw9oaWmBWCzupRBpaGggcl8ulzsgyXUuoWACZ9u3b8ecOXOwYsUKrF+/3mf7vG/fPqxYsQKzZ8926W3rDTo6Oohny2g7XDMk2ZNMssPhAJfLHTNyaxaLReqRfXWN3Hzzzfjxxx99UlayevVqHDlyBFlZWW7/z5DkkQqoDwfeeOMNbN26FZWVlQgODsZLL70Eu91ODMrGErwiyYwE2V30MyAg4HdDkoHuE5OJAGu1WuzYsQPXXnvtkEgyA6YGd+/evYiLiyPtaFgsFqZMmYLLL78cbDYbJpOJ9Mc7ePAgfvjhB7e1RoxrMNBdVzhUA5DhRFRUFGbMmIHp06dDrVYjMzMTmzdvxsmTJ8eswUhlZSWEQiFxijUajR65kY8FOMvtPBlUPe2TnJeXh3HjxkEsFkMkEiEqKgpRUVHQ6XQwmUxoa2sj5jw5OTlEUiiXyyESiZCUlISJEye6tGACugNIQqEQMpls2AhKh6F7svYTMq2XgChKixxag/MBKlxWXgZg5BYgLBYLFosFXC4X/v7+wy75ZmqxaJomY7fzWCEQCIbNGEatVoPP5yMwMJA8ZzAY3AYHKIrC+fPn0dbWhpCQEHR0dCAyMhJSqbRXHaLD4UB5eblbFcBg5dZisZgs/n5LclUmiAd0z1fOtWxjAVarlZBiLpeL9PR0zJgxA88//zwsFguOHTuGo0ePIi8vb1jqp4cKxtcjLS0NfD4f/v7+LmuexsZGfPDBB/jmm2+wePFiXHnllRAIBNDr9UhKSsK4ceNw7NgxHDhwgAS7AwICcPLkSRw/ftzr/bvyyiuRnZ0NnU6H9PR0sNlsWK3WUTd38hX0ej1MJhMCAgJc6rUFAgHp183n8wdFkplgLk3TWLNmDf71r3/h8OHDPumQAXRLjDds2ICbbroJhw8f9sl4zoxjjNR2NMcmJsjaH0m2Wq2kXpnp1d1XWeFIQqFQENM1577DQ8W1114LuVyOHTt2eL2tyy67DNHR0fjLX/7S52uYc5fp3T2WE2F9ITQ0FF9//TWUSiWam5vx66+/YurUqYNXPY31TDLTYuDi6IlMJgOXy/1NOgL3hdraWqjVagiFQiQkJJCm8cHBwUPuacjg+PHjmDt3Lo4fP46pU6di1apVCAsLg9VqJVmWPXv2YOPGjf228GAyKjRNj6n+Y/Hx8ZgxYwamTZsGf39/nDp1Cl999RVOnz49Jom8OxQVFUEgEEAmkyE6Ohomk+k3cX47Bx4udgN2B0/7JJvNZpw5cwZyuZw42LJYLLDZbKjVaqjVatA0jaamJlRVVSE7OxvBwcEICgpCW1sbRCIReDwemVxtNhvMZjMUCgWRDDIkmaE9Cjf7Qe+88Jhkf5nsspOpF/McfUkw2s4oIAkD1Bp9t8lXHZDCbkSOWIMuJQ/lU+TAkZGTXHM4HJjNZrLwUKvVvboF+BIMQdVqteT4G41GGAwGspjR6XTgOfPJnioPs9NQx2Q9na/ggTKhEokELBYLVquVLJ4uXjRZrVa0t7ejvLwcZrMZ48ePh5+fHzQaDTHsstvtYLPZMBgMaG5uRl1dXZ+LZGaxRlGURw6rztfJWA3cXQyxWIzk5GRQFAWz2Yzc3NxRX4z2B6vVitOnT+P06dNgs9kYN24cZsyYgSeeeAIUReHEiRM4cuQIsrOzx0RNeHt7O2mHFhgY6DYx0NbWhs8//xzff/89rr32WlxzzTXkvJs4cSJiYmKwfv167Ny5EwsWLOhlMDcUcLlcXHXVVVizZg1SU1NJgK2vOujfKpqbm6FSqVxI8sVtkQYCEyDr7Ox0uTYqKirw008/YfXq1XjiiSd8RjoOHDiAZcuW4cYbb/RJllqv15Nxz9/ff9RIskgkIiSTQV9jLxP85XK5xMBrtAOPTCLJYDB4Pb6npKTg1ltvxTPPPOP1WtbPzw9333031qxZ068vCHP8mOM5VlSXg8GNN9442rvgMbwiycxJcXFBvlqthk6n+91EMoHuATknJwfjx48Hj8dDSEgITp06hWuvvdbrYn2m3crbb7+NxMREMqCw2Wzs27cPH3/8sUeEjCE4XV1do3rsKYpCSkoKpk+fjmnTpoHP5+PEiRP4+OOPkZWV5fOWTd6CzWZj2bJlEAgE+O9//+v2NQ6HA7m5uRg/fjyEQiESExORnZ3d54DvTLHckTsGzkeC90PPg2lOTy7tYXf5TuzkYO/39gXnycwTKZCnJJlBW1sb2traQFEUZDIZ/Pz8QNM0JBIJKIpCYGAg1Go1mpubiayQxWLh3nvvRUVFBSnXYBYtEydOHNZWEV1dHBgM3dv3k1yovQ2x6+DvMKIdQhQIVXD9BYcXbDbbZYINCgoaNpLMtC8BXNuoMAtDpt3JcMFms8Fms6GsrAxNTU2gKAocDgdcLhdsNpv0O2axWAgKCkJYWBgmTZqElpYW0DQNq9VKVArt7e0ej3N2ux0cDocEdgd6LYOLF4PDBeaMp53KByw9l/xAgQcej4dx48YRgpSbm9vvcZk9ezYyMjLw8ccfj4kggN1uJw7ZH3zwAZKSkjB9+nSsXr0aQqEQJ0+exNGjR5GZmTmqc4dWq4VGoxkw2KjX67FhwwZs3rwZN954I5YuXQoul4uAgACsXr0aV1xxBeLi4rB27Vqv92n27Nku5owOhwN5eXljxnzPV2BIsjOc152eEJT+fAa+/vprzJgxA1deeaVPMoJA95rhtddewz//+U80NTVh165dXm2PUf4olUoEBgYO2QXdWzCKNJqmSU1yX+ON1WqFzWYjr5NKpWOGJHvrPRIeHo4nn3wSn376qU8MCf/v//4P2dnZA6pLnK9tiUTymyTJvyV4RZL7Mk74vUmtGZjNZuTk5CAjIwMcDgelpaW47bbbsG7dOq8mpQULFiAhIQHR0dHkhK+qqiItJSIiIjxqQcT0Fh4tghwXF4fZs2dj5syZYLPZOHbsGN59912cO3duTGQD3CE8PBwPPfQQeDwe3n777X5fa7PZCFHmcDgYN24csrOzx8RCsy84kwJPSLIzQR3MgpSmaXR0dKCjowNVVVXg8XjEeM45u9zS0oLy8nI0NjZCLBb3WtwwNX3DRU5qai6MVWr/C5MLBSDdUo8sWoNiQQDY7JIRO2edSTJN0x73/RwKgoKCYLVaYTKZetVj6fV6iEQij82tBguKooi0niHlDPFlzjWKohASEoKwsDDy2sDAQFRWViInJ2fIxkYMSWYWa/3B+TrxhFSPJjgcDlJTU8Hn80HTNAoKCgaci3JzczFnzhy89957WLNmDTIzM0dobwcGTdPIz89Hfn4+PvnkE8TFxWHatGm488478cgjj+DYsWM4dOgQsrKyRjxTzkiYPflcDoeD6OhoFBcXY+3atVi4cCFSU1MBAFOnToVarcYVV1yB//73v16NM9dffz1yc3Ndfv+x0rrNl2hpaelFkgcT0GWz2eT17kiy1WrF+++/j6effhpHjhxxKdHwBtXV1XjllVfwwgsvIDAwEN99951XGcf6+noolUqIRCL4+fn5bD8HA4YkG41GMk/3tbZgzm1mvB/tOlqJRELmFW9I8vTp0/HQQw/hxx9/dGlnNFRMmzYN6enp/cqsGTgHGX5P5l1DgqXnNhC8WE76hCQz5jsMOVOpVL8JKepQYDAYkJubi9TUVGJWdP/99+Obb76BVqtFV1eXx5NeQEAAnnrqKUydOpUY6Oh0OmzZsgUnTpwgshaxWIzx48cjPz+/3wmQx+ONuINgaGgoLrvsMsyaNQsymQzHjh3D22+/Da1WS2r7wsLC0NbWBp1ONybqJ2gRAD8/YOkK4J4FwPktQNzXuG9Wz0B/T/cd5UYNZzQakZeXh9TUVFJXl5WV1SuAIU93+rweg3HKzSUhXur0R0TPvXNZ1JmedJJzzKmHu3oyPA6WJPsqi2axWEjbJ4YsM9kUhUIBrVbrticw8/nO+02OpZvyf8pZEsyYcyX33Dsfs0ndd6UHaaDDBKXUANlp18VKvLUFB1nRgKP72hypkoWRJMkqlYqUwtA0DZo5ttcCeYY27GhXA9USHAjnATan2afn2PImXXiKZmIozm1G++ng4Pybuhsj/f39ERsb67L41Wq1cDgcOHbsmFeLf+bzPDmnR4MkM4fSefTmXdt9T7/l9GSP0IV6ufu7pKWlEWVASUmJRwu/1tZWvPjii5g/fz6efPJJZGVl4csvvxxTnRDEYjEUCgU4HA5OnjyJw4cPg8PhEIMqDoeDI0eO4ODBgyNae83j8QYcR4VCIcaNG0cyzq2trVi7di3i4uKwbNkyBAcHo6amBnfeeSdmz56N1157zWPjMkZi6e/vj5kzZyIiIgLffvstAKC4uPh3Y9Z1MZqbmxEcHOzyHDNOeNLezHmu6cvrIjs7Gzk5OVi+fDk+/vhjL/bWFXl5eXjkkUdwyy234KOPPsLhw4eRmZmJ/Pz8QRPmtrY2IvvXaDSjSpKdyVpfgSPmWmH+P9okmcki2+32IR07NpuNm266CX/605/wr3/9CydPnvR6nyQSCe69916sXbvWo31qbW1FdXU1Mbr8A8MLn5BkoHtSY0hyQEDA75YkAxfaOMXFxWHPnj244YYbcOLECYSHh4OmaZhMJuj1epebc1aOx+Ph2muvxZ///GeIxWLY7XawWCzs27cPa9asIVl4FosFlUqFuLg4kjEoKSnpU4rJmCgMNxFVqVS49NJLMXv2bAQHB+PkyZP4/PPPcebMGVitVoSFhfVq8aNWq8HhcEiN6mhluwUCAbBiCXD1YuBcNrDzIUBX41q/OgA6OjqQl5eHlJQUQpTPnj07Zuur6+vriYx1IPhaamqz2VBVVYXa2lpoNBqEh4eDw+FArVZj4sSJKCgocBkrurq6hi2b6aCB8sbuSTImqBW4aG3lT5ugMXWiXiCFSqUaMZLM4XBc2i45m1r5En5+fiSI5s6wJErQCgo0aFAokyqR3uZbybfzb+o8d/B4PERHRxNDMaCbHFdUVECv1+O+++7z2lDHXfClL1itVlRWVoLD4YzZkiE2m43U1FSSSSgrKxu0RH/37t04deoUbrjhBrz77rs4ePAgNmzYMGpEi8ViITQ0lPQXvjhL0tzcjM8++wyfffYZUlJSMHv2bDz77LMwmUw4dOgQDh06hPLy8mHbP2ZeZeZZd/D390dycjI5zyorK1FbWwubzYbMzExs27YNt99+O1asWAEWi4WYmBisXbsWP/zwAz799FMXFQATIJdIJJBKpaRUgvn8+fPn49ixY9BqtSgvLx8VwjRSaGlpIZl4Bs7lZQPBE5IMAOvWrcNbb72FzZs3+1QNWVNTg9dffx2TJk3ClClTsHr1aqhUKthsNpd1ItMOkKZpYtbK3NM0jc7OTvKcVquFwWBAfX39iJUhCASCQTn/M+MuQ5JFIhFEItGoqe8YktzW1jbodfLUqVNx++23w+Fw4LHHHvOZeeuqVatQXFyMgwcPevR6m81GDOvcJRr+p+Bpn2QvKvi8IsnOg7JSqSTZUKZn5e8ZRqMROTk5qK6uxtVXX43ExETk5eWBoijSxsZZHmSxWGCz2cDhcLB8+XJccsklALon3paWFrz55ps4cuSIy2c4HA40Njaiq6sL48aNA4/HQ1xcHOx2u9tFLjMxDwdJ5nK5mDlzJhYuXIj4+HhkZWVh48aNOHHihEskl6IoqNVqGAwGIv+WSqVwOBzgcDjEvKmmpgaVlZUjllnmcDhYuHAhVqxYATTWAK88DxSeBx4d2vba2tpQUFCA5ORkWK1WpKWlITs7e8wtqmUyGWkr5sm+OWdJfCl5ttvtqKmpQWNjI6Kjo4k5V3JyMpqbm1FVVUX6LKtUKkgkEggEgm7y2HMZ0QFOG2Tm2GSn5/7acx/e8+Q3Tn3a7wFquX4wyrtHy5jDrUDPv50z/CEhTYiJ6XZP5nA4PmnpMBAYd2tmITFcmWSGhFosFjJ2Uz3ZeToWEMGGYHYnaqNkKE5WIr3RiXQxGWR/pw1W9NxffuEpRsAuZpI+ToqKn0QBKGQBslI9NptMsLJYmBgcjIiICHKumUwml4won89HcHCwz0iyJ+c0E+hjsVgeZalGGjaaRWqQARDFxlDQ3t6ODz/8EJs3b8att96Kjz76CFu3bsUPP/wwonO4RqNBZGQkKfdgzNk6OzvBZrNBURTkcjlp9ZOXl4e8vDx89NFHGD9+PGbPnk1qP3fv3o09e/b4vFbPuf2YO0gkEtLuzuFw4Pz5872SBV1dXXj//fexa9cuPP3004iPjwebzcaKFSswadIkfP755+js7ASLxQKfz++TkCuVSoSHh+O1115DSUmJT7/nWITRaHRpIcSYVwGekTV37Z/coaqqCkeOHMFNN92Ed999d+g73AcYszqgO6sqkUhcbhwOBxRFgcViudwzHjVSqRQajQbp6enw9/fHLbfcQrKiTU1NqKysREFBAQoKCoalA0dwcDAoioLdbvcoiMCQd6adH4fDQUhIiE/baHoK59Z+nqqSZDIZ0tPTcc0110Cj0eCrr77C7t27fVaKNWHCBEybNg333Xefx+9xDjCMRMvI/3V4RZKdL8LQ0FAyWPN4PK+L4n8raGtrw/r163HppZfiv//9LxnsmMgvM6HyeDwolUrccMMNiI6OJrV4u3btwpo1a/qd0PV6PTIzM5GWlgaRSIT4+HiYTKZek4M7GYy30Gg0uPLKK3H55Zejvb0dP//8M/7+97/3+mwej0cIGZ/PB4fDQVFREXHjZnpMazQasFgshIeHg8/no7S0dFiJiFAoxGWXXYalS5diVZwROPUuEHIaeKLnBYykepXTm9o923ZraysKCgqQlJQEiqKQlpaGHdnZEFmthNgBAHpUjLSztJrJXDuT9IAecnfcidz9P3vnHR5F2bXx39Zkd9N7DyEhhQChS5GiKFWwISjYRVGxIyiiIOBnQXhFVFSEV0FUlFdRlC4dAamBAAkQCAnphfS29ftjM8MEEtI2CSj3dc21k8lO2d2Z5znlPvdZXvX6v0ubZA0IwkrpOPUx+KWDf3NQTQ0GA6dOneLs2bPY29tjNptxcXHB09OT7OxsMjIyMJvNyOVyfH19bZoZOqT1B0Bn1uNnqNmwysnJITQ0FJlMhouLS4swYoTvWcgmN5eTLBiVVzNu2plzScOJ8+Wu5KHFHdtE/Itkas7JrVH8wPx8jvn7ExsQQFs7O0pLS9FoNFy4cIELFy5Uo+5FR0eTk5PT5OymcF/XpyYZrM+K0Ju1JSDSraU2z4CqV0mCwWSR8Vt+e1Gp9/z58zW2AxRgGSX5o8ouldXATs7MzOTDDz8kNDSURx55hCVLlrBmzRo2bNhw1V7aTYVMJiM4OJigoCBxW05ODpmZmRQUFIgigF26dMFisdCxY0fS09MpLCykoqICk8kkOh52dnb06tWLoUOH8uCDD/LXX3+xbt06Tp06ZZNrFeZolUp1Rc9eqXiaIPJ5tTk9MTGRJ598koceeojx48ej0WgIDQ3lxRdfZOXKldU6Zgh9j6UZxwcffJB169b9Kxxk4IpWgYIdAdTLGZS2fqvLqf7+++/57LPP+Pnnn5u11WNxcXGjbbWOHTvi6upKaWkpZ86cETU/2rZty8CBA5k4cSIGg0HsUR4XF0d8fHyTkhIKhUKcm7KysqrZbbUdVzruZmZmEhAQgLe3N0lJSTa1+5RKJaGhoQQFBREYGEhgYCB+fn5otVoKCgrw9vZGLpfj6OiIXC4Xaesmkwmz2VxtsbOzQ6vVimP/oUOH2Lt3L+vXr6/G+Goq7O3tmTRpEl9//XWD5rcbTnLLwqZOsgBpffK/AZs3b2b8+PEEBARw+vTpallegZ7SqVMnHn/8cRwdHSkpKaG0tJSFCxfWu9G8Xq8XRaOMRiPt27cnNjZWfGiFzBdcPVJaHygUCnr27Mnw4cOJjo5mz549vPvuu5w/fx5XV1f8/f0JCQkRVWkFNW7ptaamplZrVyVMCBcuXCA0NFR0mh0dHTl27JjN75fg4GCGDx/OLbfcQkpKCt9++y1PdN4JFgv42+48ubm5nDlzhvDwcLRaLWs6duTuo0fRcW0IlUmj7w11kptT2be0tJS8vDxOnz5NaGgogDjRC9kkT09PK0W8tMpgHCc5QFTVqzSTHNSnaqWKkVFw6Z7MvaDljM4DQxlEnUulMLVm1XGBlm5nZ4ejo2OLOMnCbyRk7rRarc1VK5VKpTjp12Qkyn62vioUGXx4UxCVSiV/6wMZnlHlYLxV9UadZKcqFXb9JXterJO3CH64FopQ85simkqVnAI0nKiiigkoLi7mxIkTNRogHTt25NixY/X/oLWgIXRraHknuT4wW2BtQSTnKqx3blpa2lUd5Mbg7NmzzJgxg06dOnHnnXeydOlS9u/fz9q1a4mLi7PpueRyOe3bt8fNzY2ysjKMRiNnzpy5IoNdUlJCYmIi/v7+ODg4EB4eLv7PaDRSWlqKTCYTdRDee+89XFxcGDp0KLNmzSIrK4t169axY8eOJhm5gqaGTCar1rNXLrdm9vV6PUqlkpMnT9br2TWZTHzzzTfs27ePN954Q2wx+cgjj7Bs2TK2bdtGcXEx5eXl1ZwQnU7HLbfcwrRp065y9H8WLneSAyVjSH1UnutLtwarA/jnn3/y4IMP8v777zfiapsfGRkZuLq6otPpMBqNJCYmkpiYyJ49ewDr3N2mTRuioqKIiopi5MiRABw4cIC//vqL2NjYBjup3t7e4viZnp5+1bIDAcI5lEol6enp+Pv7i50LmhqACAwMpEuXLnTp0oUOHTpQUVFBcnIyqampHDhwgLS0NLHU0WKx4OLiQmRkJDKZjGPHjomq20LrSmG9oqJCbA9VUlLSbGV0jz76KBkZGWzcuLFB+11e5vqvRn37JDehGsFmTrJ00Pq3Ocnl5eVs3ryZUaNGMW/evGr/q6io4JZbbuHJJ58Uaw9zcnL4v//7P86dO9eg81RUVHD8+HFiYmLEifnIkSMolUrRcKioqGh0dNLd3Z0hQ4YwePBgjEYj69evZ+HChTg5OYk1pJfDaDRWGyzLy8vJycmptU+jXq8nPj6egIAA2rZti1arpUuXLsTGxjZ5MFIqlfTu3ZsRI0YQFhbGjh07eOONNy5F24XYRZRkp8+tL7ImPESZmZkoFApCQ0NZ7uDApx078nfZMdSWqozYI1VvlGZ1hPne4xnJxkXWFz/J5CNQghvZilsqlFEfJ7m56NaXw97enosXL5KdnU1eXh7+/v6iuJfRaESn06FWq9FoNJyQGYiubHx9mMUCe3ysqmh2RiPt66jdLC4uFp3k5oZMJhPrpKQOuY+Pj02zRNLPcrXxwWQy0TE9nYNBQcQ7e3FTXgru+sZTjktRsUbRnrMyd4osduhkl+aFkIsXOZKcfNXr6dSpE7///nujzy+gIXRruPSstJR6qHgWyU9uEYTq5ljv4Y1/hXMqx0pReS0ri6FnzyLjUuVBjVcq1TqqsqcskrFOX8MtplYB8ceg8Bis8+LuAUPp8NprFBUVsW7dOrZu3drkmkK5XE6nTp1E56WkpIRTp07VmpESGCb+/v7V6nKVSmU1xpaHhwfBwcGYTCZ27tzJ//73P7p168bw4cN5/PHH2bZtG+vXr28Ufd9kMnHx4kXc3d0JDg6msLCQoqIiIiMjxfskISGhwQJzCQkJvPjii0ybNo3IyEgAxo0bh6OjI//973+v+E5uv/12zp49y9mzZxv8Ga5XXO4kS5My9XG2pM9xfeyjn376ia+++go/P79qWf1rBRcvXhQDNk5OTlc8jyaTSbxH/vjjD2QyGVFRUdx0003cddddvPLKK6xZs4bVq1fX2+7y97dmF/Lz8ykrK6uXkywdd4WOCh4eHvj7+5OWltbgzHZERAQDBw6kd+/eODg4EBcXx5EjR/j666/rDBjm5ubi6uoKIDJVWgvR0dFERETwwQcfNHhf6W99LQVx/6lokpOclZUlDl5t27YVty9evNimtITrAb///juff/457u7uInVCJpPx5JNPcscdd4jvO3bsGHPnzq1XHU1NKC4u5vTp00RGRqLVaunVqxdyuZyysjLUajWnT59u8MDj5+fHuHHj6NOnD4cPH+aTTz7h+PHj+Pr6EhERUY2iaDabKSoqorKyUsy6mUwmDAaDKDxRG2QyGT4+PshkMoxGI6dOnSI8PBw7Ozs6duzI0aNHGyVA4enpydChQxk8eDClpaWsW7eOOXPmtGhNXVpamhi9dXJy4lddNPcUnEBJy7YpuRxt2rQBrBNEfb5bKdW1OZ1kqXiHyWQiJSWF1NRUvLy8RAPIyckJjUbDWrso7AtMhNbRuzg9Xcnhw1r69y+itLQU36rtR/N9OeVidS46paWhrqOeqLi4GA8PjxZxkFxcXMTnS2iLBbZ3koXPYjQa6xybO6emctTfHzMKfguI5sGkw6gxYzLLuJDuTH6RBqNRQYws/VIgqAYYZXJ+VUSTjAvZMh3usjJc5BV0yMikW2oq7uXl3HeV69BqtYSFhdkkg9lQunV6errYhqq1DWWLBbbuD+V4opXqGG7OZcjp09RtotoAudnw83Ie+8TaR3b48OE88sgj7Nixg7Vr1zaqHEImk9G+fXvRQU5NTaWgoAA/Pz/kcjnp6ek11vxlZWWRlZUl1maq1WqRyaRSqbCzs8PJyQmlUlmt7VxSUhLTp0/Hz8+P4cOHM3/+fBISEvjuu+8arIx95swZnJ2dMRgMxMTEYDabxXEyNTW1Rq2Q+iA/P5833niDp556iqFDhwIwcuRIAgMDeffdd8VnVi6XM3LkSJYsWdKo81yvSEpKYsaMGeLfUmHQ+mSSpc99fepJL168yM6dO7nrrrtYtGhRA6+2+WE2mykrK0On0+Ho6FiNtVcTpK3VwOqkPfroowwdOpQvv/ySvXtraOUhgZubm+iQNUQFXwi6C/XVaWlpeHh4YGdnh7u7e72YWv7+/gwcOJABAwbg6OjI7t27+c9//sPJkycblA0vLy8X66I9PDxazUnWaDS8/PLLrF69us7frSZIgxot3c3mmsO1nkm2WCycPn2aDh064O3tjaenJzk5Of/IHsl1ISsri4MHDzJixAiWL1+OUqnklVde4eabbxbf8+uvv/LNN980ub9jdnY2Wq2WoKAgcYLWarUN7pHo6enJAw88wIABA9i6dSsTJ06koKCAwMBAevToITrf9vb2ZGZmkpubS1FRUaOvPzo6WqTWabVaCgsLq1GVBUe5PpOYSqWie/fuDBo0iK5du3LgwAHmzZvH0aM19AlqIaSkpKBUKgkICCBZ7crvzlGMKjyJgtZpe+Xv7y9ObPUVymipTHJNCpdms5nMzEyys7PZ8lAb/tIHUiDTkeum4/fOUTzwzAC8vasmhWNvA2DRQ2qeM/tPBXDu70FUVuo5duxTnJyceMhsR06FA1szQsEMPmXFdK6HQSVkGgSKcnOKN7m7u4vr6enptGtnLVa3dV2y4JDUlkWRhh/cjEY8T59mSsco8mRa/nCPYsTkBPaogtnvHkCp2Q5HeSUvBgWSnJzM2XuzsK8qL7AI2cogWFcQQZLFlewyB7zsiwl0LmJEaAJ231qpqAV1XHP79u3JzMy0idqyEDis7z195swZUVyxXbt2reok/xUbzOF4axYnxHKREeZ45C3cSs9gMLB9+3a2b99OSEgIw4YNY+7cuZw/f56NGzeyd+/eegclIyMjRfaEEFwU6MpqtRp/f3/+/vvvq9Y5Xm2ec3BwwN3dXWwZ5Ovri6+vLzk5OXz11VcsXbqUUaNG8fbbbxMfH8+KFSvqHZDS6/UcO3aMTp06iWJKYNWnaCgz7HIYjUYWLVpEYmIiTz/9NEqlks6dO/Pee+/x9ttvU1hYSO/evbFYLOzbt69J57reUFlZWS1jHBNjVQQsLS1tsJNc3yTC6tWr+c9//sN33313TSqHFxcXi05yQ3HixAmmTJlC//79eeGFFwgPD+fbb7+t1bYTsshlZWWi3lBD6NZgHXsLCwspLS1Fp9MREBBQq5MslBTceuutBAcHc+DAAZYuXcqhQ4eaVMucnZ1dTTy2NZJ5EyZMICMjg7Vr1zZq/xtOcsuiyco8R48epUOHDoB14Przzz+bfFHXK3777TemT5/OL7/8wssvv0yPHj0Aq/G/cOFCtm7darNznT9/noKCAtq2bYtcLicxMbHeDrKbmxtjxozhtttuY/fu3UyaNImsrCz8/f3p2bOnOPGbzWby8vJIS0uzCX1eeKAdHR0xmUw4OztTVFTE2bNnCQ0NxcHBgQ4dOnDs2LEaJzK5XE5MTAz9+/end+/eFBYWsmPHDl7//HMG5+Xx7kHJm7u9bX1t9/albYKdKxHLqolmLTT+karG11S/WhMSL5xjk1rBMXtfEnFnvSmC4Y8nIJdRPZollpJMvfIgkiRBaRMeJ8Hhgvo7yS1Vk3w159NsNjNQeQ6TRcZeYxDpFc6UV6r49dc8evRwxMtLRUW6O+l5TpxJdedisRZ3x1KQg0ZjR0mJAZVKxX8O98NbU4TJIkdrNHBn4glM9QjwSB1JBweHZnWSBWcBrO1imstJFjLJ9S3FyMnJoXuWIwe9Azjn5MbH2r4YZAqc5eWYq3KYcrmctm3b8oUyhBBzPm0tF3GyVGC0yIm96MvZSncKZBrslUY87Mu4NyIOF/tK6isDZat6ZKBBSrhQ/XkRSjdsjWqBiZre8APs9w9gr9JaKhCgKuTO4pMoscCwS2/T7alaqcGOl31x5fmk57JU1ZVXo2UL49QDkvcJPuQ84GISfLcI3TffcOutt7L5gWEw5Vk4cQg274RD+5Fl10zhDAsLE7s+ZGVliXRlsI4JJpMJtVrdJIEhQdwqNTUVHx8fgoODxbZznp6eZGRk8NNPP/H7779zzz338O6773L06FFWrFhRLxp2SUkJsbGxhIWFodFoSEpKanQGuSZs2rSJlJQUZsyYgYODA6GhocydO5fJkyczatQo1qxZ02JdIa5FhISEiI5hXFxcvb4LqUNX3yB/SkoKu3fvZvDgwaxatapxF9uMKC4uxsfHRyw/aMw9sXPnThITE5k+fbp4n11eT+/o6CjSlGsLFtYl3AXWoLPBYCA1NZWIiAicnJxwdnauFoAICwtj2LBhDBgwgLNnz7Ju3Tr27Nljs5ZRycnJeHt7o1AoCAsL4/jx4zY5bn3Ro0cP+vTpw3PPPdfoY0idZDs7O1tc1g1cBU12kmNjYxk/fjwAnTt3/lc7ySdOnCAnJ4dFixaRl5eHxWJBr9fz/vvvc+jQIZufr6CggMOHD9d7gHR2dmb06NEMGzaM/fv389JLL5GamopOp6NLly6iIW2xWMjMzCQ5OdmmteUVFRWi01FUVISDg4ModpacnExwcDDOzs54eXlV61Hbvn17+vfvT9++fTGZTOzatYs333xTjP4vttkVNh0y4PazZ9A7KUhw8SLexQvVARODe5xpGXqkBI1xkqUDcHPSjevqlVi6FDorkznY2w9vx2Lskw0UZ51gy/6qjIB7tPW1yueRFcKgYV/QKTSLhIMerI+LRGFWYqxU4K0qZrDhDE5t9JRWBa4NcjknnJ0pV6m4taqO32KxVLWZMnGzyYRCoahV6MkSVrUisakbU9cuzSRLM1FCFqypEH7Nz5RKfuXKNmAFdnZkOziQPliJH4W4UIHlgPV/FSeT0FfIyHRy4pzcDbXRiKOpkokV+7ko1xAT48uxCl8MIXJO48FpPC45WHrwcSoir0CLu3sZMb2zcOm3HQDX93uL57ect77KanDwunbtyo8//tjk70CtVotGdX2z0tLMolQoqiVxxMeXHcHWMiYfZTF3Ox9H1crlG1KUlZXxxx9/QMIf4OUL3fvBPffDxBd4dfff7Ny5k8OHD4uZH51OJ97XeXl5ZGRk0KFDB4xGI0VFRdjZ2eHg4GAzoRyTyURaWhqZmZn4+/sTEBAgtiF0d3fnzJkzLF++nN9++43Ro0czf/58/v77b77//vs6KaVlZWUcO3as0c5JXUhISGDq1KnMnj0bDw8PSktL+fLLL9FoNMyaNcvm57ueIGSRgXozx6ROckN+r927d/Pcc8/xyy+/2Kztj60glE8JLaIaex+mp6czefJkXnrpJebPn89bb71VLegTHGwN0un1+mr04MZkksGazQ0ODsbe3p42bdpw9OhRevXqxbBhw4iMjGT79u1Mnjy5yW3/aoLBYCAlJYWQkBDc3NwICgqyufhhbXB0dOT5559n8eLFTWJHGQwGCgoKkMvl/+pgGWC1N+rjorRWn2SwGt/l5eVoNBo6d+6MXC5vMp34esbFixcZNWoUcXFxZGdnM3fuXE6fPt2s56zrQdFqtYwePZo77riDo0ePMmXKFJKSkpDJZLRp04bAwEBxwCsoKKCgoICysrJ61+/VF2fPnkWtVqPT6cTop0wmIyIigtTUVIqKilCpVLi5uaHT6RgwYAD9+vXDzs6Ov/76iw8++IATJ05c8XlFRV1pi6UH3ra+fiLZJij0SqsBahiHheepvkQWi7PkDxeQA8OTTmFsoyDR2Z1j631RrzUxsO05xHlFyNKcvVRbJbZ5+uHSpqu5qdJ4r67KaZNV2fYymYxevXpZr89iqTedUGocStuy2Br1oTHbG414FxeTo3XCp6IYs1pOpsFRzGTaKY2EOuTRTptHqDYPRYT1vugQmI2TVo/sqJm0Sme6OaahMpgxIuOkjzfx3t5kOjpirrq/O2PNMBYVFbHfXo/KbMbe3h6DwWDzZ+BySJ3ktLQ08vLycHd3r6bxYAuYqqih7u7uIk3UycmJb5yc0EsCAU5U0tYzj24FaThYyrnl7FkyHB3x8/CgfUYGDrdaUGHG21zKYKdEumvTSOjqSWKyB1l5l+5WBzs9rroK3BVlyGTQpk1Bg643ODgYX19fDhw40OTPLv2O61sKVFxcTEZGhqjL4OrqavNWSK5hl9YtPapWqj7ucUdv1odag1zuR0u592gcdkYTCB0/pONaVfyrUhJoqCm/4Fo1TkmFu8RWdL0l2+6sevWVthfZYn15XRLgENrmpQNkwMmf0C/8CYKDyR4wgKeeegqdTseePXvYuXOnSLVUqVTk5eXRqVMn0V5QqVTodDqKi4tt2vYNrIyHkpISUlJScHBwwMvLCzs7Ozp06EB2djaJiYksXbqUX3/9lTFjxrBw4UJ27drFd999V+f90pxGampqKlOmTGH69OmEhYURGhpKfHy8zbJq1yukAqL1dZINBoOoPt6QMV2g9/bs2bPOut2WhvTeq4/DejVUVFTw/vvv8+STT/Lhhx8yY8YMkpOTcXR0FNlOl7fnq+1apJAGFqQ90FNSUggPDyckJITx48fj5eXF6tWref/995u9N/2FCxdwdnbGzc2N4OBgSkpKWqRl7TPPPENCQgLbtm1r0nEMBoPIjGopYcl/M5rsJJvNZg4fPkzfvn1xcnKia9euYrP0fxu0Wi1RUVEYDFa658cff9zsDnJd6N69O5MmTSI9PZ3p06eLGUWhr6/QP9BgMFBcXIyLi4v4AAKioJItetoJdUXt27dHo9GQmpoqtjEQ+ud16tSJqKgozGYze/fu5bPPPiM2Nvaai+LWBYXFwsjzJ1ndtgPn3V05KA9AVWriZgfbR0drQkxMjEhrPHToUL3rBaXRWyGC3JrQ6PU4GcrxrijhVtdz6M0KSsxqNP0M2CuNyGph4wa5F4AGAjVFVJrlHND5c8ghgALtle6D0WjE0dERJycndlRFRowGo9g+ojkhdeDy8vI4c+YM7u7uaLVamwlGWQCnigqKystxdXUVqXMAziUl5Egm2iLsiHXx46izL6Hk0j0lBd/iYjyqaNq6y2whN2U5fbqk0KdLCkajnLJsJRaLDKfSSvJLNWSmOWE2g0LRsOe3f//+7Nu3zyZZRQ8PD3G9IS29du7cydixY5HL5dx66638/PPPTb6W+uCUgwcbvK3ZaxdzOffFxaFpxl7yNkdyMsuXL2f58uVERETQv39/Jk+ejJOTE2fOnOHEiRNi6Y3BYODChQtiUCg/P99mgjoymQxvb2/CwsJEx8hisVBQUICdnR0ajQYvLy+cnZ05fPgweXl5fP755/z888+MHz+ezz77jG+++YZ169bZ5Hoag7y8PN5//30++ugjlEoljo6OhIaG/quUraVwd3enU6dOgJWu35A2QsI91xAn2WKxsH79eoYPH37NOck6nQ69Xo9MJrOZffTVV19RUFDA+++/z5w5c8TvSq/Xk1FHV4iaIJ0/peVbWVlZPPLIIwwdOpTdu3fz7LPPtmjwJyEhga5du2Jvb09UVBTHjh1rdFeY+qBz58506dKFiRMnNvlYUlu8vi0N/7G41oW7BGzZsoW+ffsCMGjQoH+tk3zPPfeg1WpJSEhgy5YtNu8r2RA4ODjw5JNP0rNnT5YuXXoFDd7Pz0+MQuXk5FBYWEhYWFi191gsFnx8fPD09OTEiRM2GcRyc3PJzc3Fw8MDLy8vjh07xoMPPshtt92Gj48Pp06dYtWqVaxevfq6byOmtFi469wJ/hfckVSZM3vLglHJzNykq1topKkYPHiwuL558+Z675eZmSkK6DSnkyz0IoZLlGC4lMUX7rQSe3uKlBosZhmUgRoTbpSDcDtLWclV7bKEtl7lKDms8uewyg+5g4UyuRqFEwRUFhJeloPfkQKcy8t5KMKRWBdf0jVOGPQK9HIF96nMjCpLJEBTJI6vailj4IWq1+WSbY0Y9oRnzmKxkJ2dzZkzZ0QGQHh4eKOdZIvw01VlCidwCK+yKM7Za7CUmFGZTOgqK4mxZNIu7SLKfiZS9c4kVbpxUuWN3qIg0dWT3M46XKngpvALBNgXwkDJSXpVGZvl1uyCEjNOgZfGEHWJgoLPRwOg198HtLH+QxKvqYlmDTBgwAC+/PLLRn32yyEEi6BhTvKff/7J2LFjAevz1BJO8lmdG3/4RGGRyXAyVzK24hgO1/E4eOrUKU6dOsXSpUu55ZZbGDVqFA8//DBlZWXs3r2br7/+Gi8vL8CqPltb68CGQqlU0r59exwdHTGbzaKxL5PJcHFxIT09ndzcXAICAlCr1QQFBYmOZ3Z2Nh999BFbtmzhhRdeoF+/fixcuLBRToItkJ2dzQ8//CCWDDz44IP/Wsr1LbfcImZNt2zZUu/9Lq+NbQg2b97MuHHjxLZF1wJkMhleXl6o1Wqb35erVq2isLCQd955h40bNxIfH09KSkqjGKJ6vZ6SkhKMRqPoJKvVal566SU6derEkiVLuHDhAmq1utmdZOHqywCMRnJOnGB8TAxKpZKwsDBOnz7dbB1RHnvsMX788cdGd7WRQvo7/Oud5BaATb7hI0eOUFBQgIuLCzfddBMODg5XFP//0+Hk5MSoUdZGuEajke+//77VrqVHjx48/vjjpKenM2nSpCuoJDqdjrZt22I0GkVVzp49ewJWtcgTJ05gMpkICAgQ+1937tyZY8eO2eR3TUtLIyoqil69ejFlyhQuXLjAb7/9xsmTJykqKiInJ6dRDrJMkqS1rK9akY67wvhXIHmfkGTyl7xPKN+V+IiCaq/UwBePXZPoTdU2FWbuNh1nlaITmWpHdhpCUKtMdEmucn4+r/3zADU2PRIuRS31YV+49Orj4yMGrQoLC9m/f//VTyKBQIUKCwvD19e32Xqe6/V6kX51NZRXvUdjrH8oMFem5ajKlzilDwaZdWJ2M5fiayjmpvwL+OutE5W+6vfzLy/Cv7xq8iqoOohLvU/XaLi4uIiBiDNnzlBRUVGNFh8WFsb27dttci45Fu5Ks0YR8iXPiWuw+AbC7C8SZn+RfpVJxBr8iDd6kYOOArQkZbrhZ1dE19Q0wnxyUSnrppna218yTBtCoRPa2x0+fLje+1wN0mx9Q5zkrKwsjh49SkxMDL6+vvTu3du22SRPybozpJhcWPNINGajDJ3OwJjwYzg5VGKRJDJlVfesZdmVx1FLjmepGsNkko8rBCQs3SX7CuNGNym9376Gi7UGbpD+7l9UUTwlVG11VYykGqXbE8BM0aFdbM9JR23Q83mHrnTs2JEvvviCjIwM9u3b1yCn52pQq9V06tQJrdZKF8/NzeXcuXMYjUYiIiJE5etjx45hNBrFHu3FxcXVajGPHTvGpEmTePjhh/nPf/7DihUrGq1I21Rs2LCBu+++G09PT7p160b79u3Fdj7/JgwaNEhcb4gQqnQOa6jYUVFREX/99RfDhg27ZlpvtW3bVry/baH+fzk2bdqEp6cnEyZMYNeuXXWOe7XRrWUymZiMkcvluLq68tZbb1FZWcmzzz5LREQE9vb2BAcHt3hLJs/SUo4fP05oaCiOjo506tSJY8eO2dxRvuWWW9DpdFb9BhtAqmhtK/2GG6gdNnGSTSYT27Zt4+6770apVDJo0CB+++03Wxz6usF9992Hvb3VuNiwYUOrtMHSaDRMmDCBPn36sGjRInbt2lXj+4RexWAVqAkMDBT7x504cUKUxU9KShLVR5VKJZ06deLo0aONHkQUCgU33XQTI0aMoFevXhw9epQPPvigQU7c9Qh7TIw2xbFSHUOuXsefOWGoMk108Mmqe+dGYOTIkRQVFeHs7MyaNWsaTMVKTk4mLCwMmUxGYGBgs1D79Hq9aKyooyT/GGB90S0HvVxOpUaNuQLssvQgFRgWAhNVZZNmCxzL9iUu3YeKCCUFeg0UgQwLUcocempS8JSVwSV/6VJm2EVyXKFGU2ILqQUn4DbJ+6oeb1kTSDOdO3cW12NjY4HqAmtS4bUGo8D6IqtBR9Ei/RybN1St3CNusn+njF5coFvfNOJSfThwLpCibDvSjU6kr3fCQV5BW3U+PY9cwNWuAqQElP5DqlZmoFSCvf23VFRUVNXzWj07Sx3l8QMGDGD37t02oxBKRdAaqkK8evVqYmJiqKio4Pbbb282ymWayZFfKqIxGmVoNEbuuy8O17PNW5vX0nDS6xmVaO1LfHP8WVatWkVwcDATJkxg/Pjx9O3bl19//ZVt27Y1ujWLSqWq5iAnJSVVaxEUHx9P9+7dUSqV+Pr6Eh8fj4eHh9gP+/L7o7Kykq+++opdu3bxyiuv0KdPHxYsWNDi87sQeH/xxRcBeOihh5g2bVqLXkNro0OHDmIrIkHzpb6Q2ixCL/qGYN26dcycOZNvv/221R0TT09P8XvIzs5ulnpaR0dHLly4wKeffsrw4cN57733mDdv3hV9fY1Go6gtU59jzpgxg9OnT7Nw4UJMJpNYm+zs7IyLi0uLO8pFRUUkJSXRoUMHVCoVMTExnDlzxmbPt0ql4qGHHuKbb76xSckiWIPrpaWlFBQUNLnt3HWP64VuDVZKyt133w1Yacfr1q1r9nq+awXu7u6MGDECsBr/P/30U4tfQ3R0NC+//DLp6ek899xzV40uCgZEYWEhCoUCf39/ZDIZKSkpVxgneXl5HD9+nI4dO1ZzlBtCjXFzc2PIkCEMGTIEo9HIunXr2LlzJ+Xl5c3Wf1RWpedh8azhn9JtgsMgoc1aqj6aTDqXCoKa0thPm6rXmj7CAMn6KNBg5D7lMVYe7kx+uYYNJ8JRlpmIRJLqaX/l9bkWVF1LDQkwy8OX1mVVGSFfX19GjBiBXC4nISGhUZmPy+uSm8NJLi8vr9NYueDkgrlq8vUvLATvmt+Xb7RnQ3EEqaesXq8L5dgpjLRXZtNdlYqLvAKuwZJ2qUqr4CSXlJSQlZVVrZaytYQQVQozXYPTiQnMIH63F0fy/ag0KMg3aTlW4Uv8KS8G+p0jJjSD2mykgIAAEhMTSU5Opk+fus+pUCi4+eabef/99232OUJDQwFrMLc+PVWlOHz4MHv27KF79+50797dptlkWdVhdDod77p2xCBXYHfcyGi7Y3ieKBGDNzJJ5veiEJSRXoLw//aSbVVjWElNiXMpgUOcou+UbBQGOekgVgM0VT9o8J5L2wQBMmng5H4hSPFfcZOl/VAAXDMK2bx5M9u3b0ej0TB48GAee+wxtm7dytq1axv0eymVSjp27CjOb2fOnLmCimo2m0lKSiIiIgJPT08yMzPJzc3F0dFR3K8mJCQk8Pzzz/PEE0/wySefsHjxYpu2dKwPtm3bxujRo/H39yc6OpouXbpw5MiRFr2G1sT9998vrm/atKlB+0rtlcY4yQkJCWRlZXHLLbewYcOGundoJmi1WlFtv7S0tNk0bwIDAyktLaWiooJnn32Whx9+mAULFlS77y0Wi0j3ravOW6FQMHXqVBISEliwYIGYec7KyiIwMBCLxUJAQECzOsmyqnFPJ9F6s+wFKMDt1RNER0ejVCqJiorC1dWVxMTEJs+9I0eOpLCwkJ07d1qvoSqgIJPJkMvlYnDBYDDUWwTQy8tLFL+9geaHzZzk1NRU9uzZQ58+fXB1dWXo0KH8/vvvtjr8NY2hQ4eKg8Xvv//eotEwIVI1dOhQli1b1iCnyM7OjqioKNEQr622pbCwkBMnrIOIEKmPjY2tM9ofEBDAuHHj6NWrF7GxsXz66accOnQIi8VChw4dcHNzw93dvUHiG9czHOwMjOlylJWHO1NYac/apChQJBBpsl1W4pFHHhEnrIMHDzaqzkdaFxgSElL7G5uA8+fPX1XB2SSTsc/Pqq7toNfjWgtd92SFF5uK22GwWGnVAc6FxMjTCXPOQx137arsq1Qqune3ejd6vZ6EhATxf6dPn0YulxMWFsZTTz3FV1991arCdQq5hQ7OWXRwziI7WcvJSh9iy30xmBVsTm1HosKdkZ3jsVNdeY1BQUEkJiaSmprKuXN2tG3rXMMZLqFnz54YDAZOnDhhk2tXqVSiSntKSkqjArebNm2iT5WH/9BDD3Hw4EGbBYAdHBzo2LEjlXIlKouJe+yO46P495QqCVT40tJStmzZwh9//EG7du0YPnw4H330EadPn+aHH36oU99DoVDQsWNHkdp59uzZWuez3NxcgoOD0Wq1REREiHWCdRmplZWVLFq0iL///psXXniBXr168emnn9qkzrA+MJvNrFixgtdeew2wGuD/Fic5OjpaFOzKyMiolSVXGwoLC8nNzcXe3r7RisBr1qzh3nvvbTUnWaFQ0L59exQKBSaTiZMnTzZLANXd3V0UOzxz5ozIpjhy5AjPPPMMd955J8uWLePw4cNYLBZkMtlVa2NlMhnh4eHExcXx0UcfVXvOLBYLycnJYomNl5eXTXuO1xf5+fkcPnyYqKgodDodPj4+ODs7k5aWRnZ2dr2ywAqFAnt7e+zs7LC3t8fd3Z0nnniCZcuW0bt376uWl1ksFioqKigpKSEhIeGqY5GPj4+43lo6CdcMrqdMMsAPP/wgGhOjR49mw4YN//hsskwmE+tkzGYza9asabFz+/n58dprr2E0GnnppZfqnZXNysoSByS9Xo/RaCQpKemqtaf5+fmcPHmS6Oho1Go1MTExxMbG1kg9cnd3Z9y4cQwcOJDNmzfzzDPPVOt7DNYMtZubG87Oztjb2zeaXne9wclez32dj/HDns6UGtT8bh9Fjl7HzYbzTe6jPGLECPH5Ky4ubvS9KKXwCIaJrXH69GlGjhxp/aOz5B/+kKPX8edNYRSo7NFgoNvpC8gAiyQCLEuDVJ0T6+0iMCNDhYmBqnPEVGQgEzKWj0iOK7T/kuqu1BQ/qKInVxOU2nvZqw1w6623isry+/fvrzYJL1y4kI8++ojCwkKGDx9OZGQk3377bYN6rdcmiAVQKqFg6263ZvSQ+q5tql7nX7mvV5syvOTniLFPZ4M+glSDM0ln3NiQFsEor5PI+nxkfaPSWnoSFaXkwIFs7OzkrPn8GP2CztNZLUMhGAGXTQ/33nsvv/76az0/Zd0ICgoShZsay4g4fPgwCQkJREZGEhAQwLPPPsvHH3/c5Gvz8vIiPDwcuVyOwmLmrpwTBAS2jMN1LUCPXBTtkjKfzpw5w8cff8zSpUsZNmwY06dPJz4+nmXLltUo7CWXy+nYsaMobJWUlHRVgSWhJV7Hjh1RKBS0bduWzMzMerf4OnToEJMmTWLSpEl88sknzJ8/n2PHapHZtzH27NlDTk6OWJvs5ubWIu1rWhsPPPCAuL5y5coGO4elpaWi4+fk5NSoa9i1axePPfYYMTEx9W49ZQuYAYNcTs8OHUS2w6lTp5qlVZJarRYz1WVlZdXo1QcPHuTpp59m+PDhTJ48mZSUFJydnSkuLq6mXH05fHx8kMvlfP755zUGe3NycggICMDBwYGwsDCKiooaZQ9Wa4lZVcIli7+0TdBJkEmZhOcvrZaVlXHkyBHatm2Ln58fGo2Gtm3bEhoail6vR6/XYzAYqmWB5XI5crkctVotBgoEUdJBgwaRk5NDZmZmnforCoUCDw8PsfXq1YLiUif5cvr7DdgeNnWSk5OTq2WTR48ezQ8//FD3jtcxYmJixMH30KFDNu+lWRsGDRrExIkTWbt2LStWrGhQpik7Oxs3NzcsFgv29vZ1GhUCLl68SHx8PFFRUdjZ2YnUa8G51ul03HvvvYwaNYq///6bSZMm1foQZ2dn4+vri1KpJDAwsFot5uWwSFhwsnomRi3CmCT1+4V9paWe/rUfV3peJlS9SsY62RdXuQApfVtIFLtYX1yp4P68o6zWRnPRomWfLIgci44RWxKws5iqOSw10azF/825tB4ZGcmECRPEvz/77LNGBx6Kioo4c+YM7dq1IyQkBHd39yaLg0gnFplMxvnz52nXrh1ubm4kYaEUNTnoSMl0IVvvIGoHdS1KpUsN92aJUs2aNu0xI0Nn0fNAYSyuQddHoEWlUnHPPZdqgH/55Zdq/6+srGT9+vU8/vjjohE/c+ZM0tLS+OOPP9i2bVur90p1VVQw1uEo20pCOWz053SZBwcKA+hJdVaIVqvg3ns9+O67bAwmBVuTQtnbI4jAwkL8iwrxKKsUDZD27dvj5+fHli1bUCgUWCyWJmdK2rZti1wup6CgoN69wmvCp59+yvz580XjJyEhgY0bNzbpugICAgBrXd+cv04yuaAAi7QLiTBOScYhV6E8JEbyPqG/ujTgcDWtPWkXOuHYxo8ubROG4qgCyRsFNeVTlzatrKJZS/WjhHXp9f1QFbxNHypussTDCV9vLM4WysrKagzwlpSUsGrVKtavX8+YMWOYN28ef/31FytWrBBrBuVyOR06dBAdn+Tk5HpRtAsKCsSgb2ZmJhaLpUH9mUtKSvjggw+4/fbbefPNN1mzZg0//PBDszM+LBYLW7Zs4f7770cmk3HLLbe0WGuy1kLPnj2rZZF37NhRxx5XQprtb6yTbDAY2LBhA6NGjWpRJ9kkk7GmfXsxqJqcnNwgAcL6QiaTERERgUqlwmw2Ex8ff0VG02Aw8Ntvv7F582aGDRvGmDFjSEpKqtUJtFgsZGVlkZeXV2vCzGKxiC2ZlEolkZGRHD16tFl7kNcGs9lMYmIieXl5BAQEoFAocHJyws7Ort6Cb4IwbteuXfn5559JT0+noqICvV4vzmdmsxmlUomDg4PYdtVoNOLi4lKnkyzMG8AVyacbsD1srh/+3XffcdNNN6FQKLjvvvv466+/SElJsfVprhncfvvt4vrlbZaaAxqNhmeffZbOnTvz3nvvNZpudfr0adFJbkhEMjc3l1OnThEREYFGoxEd5REjRjBmzBjOnTvH66+/XqdBajKZyM/PJzAwEG9vb86fP/+PZx1I4WYuZ3zJEdYqozhn58ZZO3e+8+7Cnbknca8xxVk7XFxceP3118Vo7urVq9mzZ08de10dBw8eFIWjunfv3iiHICAgAGdnZ3Q6nShqB4gULZPJxKOPPsr/zlypfqXRGehrPE+MWybyGubfTZ3aUWqnRh5sYVT4SVwdKy4Z/4K9Lc38CnaVNIpctS7b2eCP1mjIZDImTpwo9iKPi4ur8Vn5/fffOXnyJC+//LJIF/b392fixIk89dRTnDt3juPHjxMXF8eJEycaJKZXjWxYNWRZHpBsK6h6lZapCt+bRNBM7gK3WM6R21lHSq4LO2UhtFmdj5djKcx/z3rcP8EDeFCrZXvbtiS5ubFKoQI3D3DzqFZG+/jjj3P8+HG6desmbjOZTJSWllJWVsaFCxcanD0JCgpCLpfj4uLS4HpkKVJSUli4cCFTpkwBYOLEiSQlJTW4JlClUhEREYGbmxtwqZvAv4VJI8ACHKpqv1RaWnrV+7ekpIT//ve//P7774wfP57PP/+c9evX8+OPPxIUFCQ+S6mpqdX0FOpCXl4eBw4coLy8HKVS2aiAzObNm4mPj+e1116jU6dOfPjhh80u6iU4yWC1P/7JTrJWq+XZZ58V/16xYkWjfidbOMlgFfBaunQpvr6+LUJ1lclkbAwPJ6lqvEhLS2vQPd4QhIWF4erqCljLoa72TJaVlfHzzz9zzz334OjoeFW6tdlsrrNDRllZGWfPnqVdu3Y4OTkRHh7OqVOnrrpPcyI/P5/8/HzUajWurq7Y29ujUqnEAIIQwLVYLMjlcgIDAwkPDycyMpKQkBAuXryIq6sr//vf/8SOMGq1WnSInZ2d0Wg04vmKiopQqVT1soOlNen/+kyygasHhAWo635LbbC5k3zhwgV+/vlnxowZg1Kp5IUXXmDKlCmtEhVqbuh0OrGnaVFRUbOrNIeFhTFlyhSysrJ4/vnnm1T7LEw0jaHsZGdnI5fLCQ8Pp23btjz//PMUFRXx4YcfNshpT0tLIyAgALlcjo+PT+1GrLTVUXzNbwGwSMViBlz2CvB81avUUYq9ygVKkxtVPmd+DdljBwcH/Pz88PLywtHREQcHBxwcHERxhdexGvtzTSYwGsFoxGTJR5Gby9DMXA5pjfyt0bDMoOUbbTdSL1iNvfoYA3Z2drzxxhui0R0XF8eyZcvq2KtuHDhwgAceeACj0Uj79u0b7CRHRETg7V2z0pYgVrFv3z569uxJypmDyLDgZKokgEKCKCCsMhf7WtS2itVqztlZP29fv/MEOF4fFNXg4GCeffZZoqKiqKys5OTJk3z+ee09wM6ePcvzzz9Pjx49uPPOO7ntttvEeq3Q0FBCQ0O58847xSzYqVOnSEtLIzU1lfT0dLKyspp93JXLLIzsFs/SbT2o0Cs5kemNl+OVipvuZWXce/w4aU5OfObqiqurKzqdTgzs+Pv7ExwczH//+99q+wmRfCcnJzw9PTly5EiDsuhCgAFokpMMVrplREQEo0aNQqlUMm3aNKZOnVovp0gmk+Hr60ubNm1QKpUoFArMZjNGo5FevXrh6emJm5sbL6jVKBQKcZHL5bxHOZSUQGkJDC4BQwkE5kJFOhjyL41T0nboLtYXnTTAJGSNpUaFcPtJAyJCrNdFQuO97W3r6wHJ+2ZbX7IlSS0v6RgsoCrpJm09FurqSscqI7G+mhQ5OTksWLCA1atX8/jjj7N06VK2bNlCQkIC6enpjVJ6Fea/pijPpqam8sorrzBhwgQWLlzIwoULm00FHazZo7i4ODp27Iifnx+RkZHVNA3+SXj00UfFue3QoUMNrkUWYDKZKCsrQ6vVNslJzs/PZ8+ePdx9990sWrSo0cepC5YHrIGkdYRzLsUNrVFPVl5+s4hognWc9PX1BayJkPo+k8JzY4t+vRkZGTg5OeHt7Y23tzd6vb5e7A6xjWeOtFbcytSyeFbNFdGd4J4RcD6B8iHJmFNTIScHfR3zo16vF7O1KpUKf39/sTVqYGAgAQEB+Pv7U1paSmxsLL///jtHjx6lW7du3H777Tg4OODv74+zszN2dnaYzeYrqOmlpaXk5OSQmppap83n6ekpBjKaS7TtBqqjWTpR//jjj/Tp04eAgADCw8O59957+d///lf3jtcZ+vfvL9JMtm3b1qxUq7vuuovx48ezcuXKayJynJ2dzX333ScqmX/yyScNzobo9Xry8vLw8PDAw8OjyUZss0KpBQc/lP18kfn5Iffz40M/P/z8/MRauIZA0IK0A/oAMSoVISUlXLhwgQsXLnD27FmOHDlCVlZWrVFYlUrFW2+9RWRkJGDNjMydO9cmYh6JiYkkJCQQFhZG3759+eyzzxrUL9loNFJRUYGDgwPnz5+npKQEk8mExWIRlzNnztCnTx+eVWShST2NHEv12thakODhhQUZcix08ri2hSvs7Ozo27cvQ4cOFX8nsEaV169fX6cxYrFY2L9/P35+fvTs2VNszSFQ78DqgLVt2/YKITSj0UhGRgZpaWmkp6eTm5tLfn4+BQUFYqTcFnVtWjsDkX7ZxJ73Iz7LiwGhSdbfsgb4FxWRXFQkZkMUCgVqtZqBAweyevVqjh49Wo2Wb29vj4+PD05OThQUFNSpono5hD7vxcXFNhFU/Prrr2nXrh1RUVG4u7vz7rvv8vrrr9dajqBQKPD09CQ6OprIyEiCgoIIDAzE1dW1/swZqaMr/MSCnW+uAFU65KeDSzpkVi3l6VBy7QaPhBKlS+3B6o/k5GRmzpzJI488woMPPsiRI0eYOXNmc1xmvWEwGPj888+JjY3lhRdeoEuXLnz11VfNxo7avHkzHTt2BKzZ5H+ik9y1a1eGDrVS9CsqKvjss8+adLyioqImO8kA33//PR999BH79+/n4MEm9AC8CszAJsI5iTcoITo7k9Onay9Jawp8fHxo06YNYBU4a8i9JDjJV6tJbghOnz4tZm8DAwOprKy0TQeUB58EQy60iUAZPhiZry+YTCjS07GkpfFk1fgt2CYC5HI5vr6+BAYG4uXlRUVFBRcuXCA1NZWzZ8+yY8cOLly4IF6jo6Mj7u7u3HnnnWRkZIhZXwGVlZVYLBYKCwspKCigsLCwQWNERESEuN6amfZrBtebcJcAg8HAwoUL+eCDD5DJZDz00EOcP3++2QaU1kJLUK2dnJx4+eWXCQwMZPr06ddE9Mjb25tXXnkFo9HI4sWLSUtLa7T4luAkOzo6olarG+SINRdUKpXV4RgQDm0jILgd9LBGWe0kWeiIGvbV6/WUlJSIS2lpKRaLBYVCwR1KJSgUoFJhcXdH5uYGVUa/zmBAo9EQExPDTTfdBFhphmlpacTHx7N161aOHDkiOsBKpZLp06eLtVqlpaXMnj2bwsKrKDY1EILqJFh7+jaEKSEoPRqNRry9vSkrKyMnJ6faBFRQUMD69es50mkss3+1pqUsQk2jlP4rZMCqvvv4QC9wgBAuol0myQAJ7WeEbFdNpWsFl1ZlNu4+plaradOmDaGhoYSFhREaGkpQUNAVUfasrCzmz59fb2NEEMIrLy+nrKyMWbNmkZmZSXR0NB06dKBjx46EhIRc0atSqPcXHMWaUFlZSX5+PnOrnOaCggI+N+ZDwUWgEPTF1sW5GIwl0E4SCBQmnliIKs0mtsiPH+PUTP/Mud4OqclkwsXFhZiYGCZOnFjt/tXpdPj6+qLT6TCZTDg4ODQo46fVakVnzFYBOJPJxP/93//x/vvvExAQgLe3N++88w7Tpk0TP7MQtBgyZAidOnXC399fzIYZDAZKS0uvMIwKCgrIzc2loqJCzDALQaWRrlpwcACdAwQ5iKJoAMjtwautdXGTHFAFFOZD7Gk4U7WknYFWrmUHa4ZMULVurNaBQqEgKSmJhQsX0r17dxYuXNigZ6q5sHfvXhITE3n11Vf5z3/+w9y5c5sl+Ltnzx6eeeYZNBoN/fr1Y/Hixa3ev9eW8Pf3F0sbwBqcamodbnFxMT4+Pjg4ODSptV56ejqffvopr7zyCi+++KJN6fWWB8CAnN96RJGYbX1GQvPyGKI7g1lzae6srzZLXXBzcxPLqoTSj4Z8L8J4XFtNcn36J0thsVg4efIkMTExODg4iKJZV/3tOwsrj1/allL1BQldkpQWOL8Wzh1EdQCrHebhjbJNAHj5szjYBaGP4YRzl67ZZDJx8OBBfv31Vy5cuFBjQM/FxYV27drh7u6OWm3l9UZERLBz504sFovY07iwsJDCwsImsVakTnJrj3X/FjSLkwzWH/CHH35g3LhxyGQypk6dypQpU5qtnqKlERQURFiYlVsm9AG1NTp27Mirr77KiRMneOGFF1pdrAesqrwTJ05k69at/Pzzz7Rt27ZeNSe14eLFi2KNqru7e7U6H4sg/nLbpfdbOltfZRI9OHFI97u0TRSQkc5fw6tepUJgP1iN6T59OhMZGUmHDh0ICQmxRkalSasqJt/GqmtOT08nIyOD9PR0ccnIyLjq9zDrsr9lMpnYBisoKIiIiAgiIiIIDQ1Fo9Gg0WjEbXfddRfZ2dns2bOHP//8k/79+9O1a1fAShmcOXNmg4Rn6oN9+/YxZMgQAPr27dsgJ/n06dNUVlaKNaGhoaEEBgZy7ty5aobx999/zxdffEGvXr3Yt29fvY5doLY6CUFSj7cZoVarsbe3x9HREdcqqrCbm1u1dXd3d7HfOFh/W5VKVe1+OH/+PBs2bGDr1q0NCig99dRTYk33+vXrxRrmv//+m7///huw3sOBgYH4+/tXW/z8/K6qrGlnZ4ePj081xUyxfkfa/UswNiLKoLIEKougvAQqisC1BH99EeFOQXRRlqPRaEhKSqK4uJjCwsI6x62HHnqIHTt2iIaQEKTy8vIS9y0tLeXkyZMN+t6kAie21MUoKirizTff5L333sPX1xd/f3+mTZvGt99+y80330y/fv3EzAxcqsmrrKwkJSWFU6dOkZCQwPnz58nJySEvL++qLKR3JOuWyYBcAX28QONnXc74gasfSy5aSz5kMpmVUq10ZUj3m6C7Nei2ESs1+Jnzp+HwQYg/Af+zGn16SRmJIE8j0hjBWlgO6F+4tElw812kFyvcatIWnlVq865Vb8xUOXBXlTH5fiOdZIE+W15ezuLFi+nWrRtz5szh119/ZeXKla3aMi0nJ4dp06Yxbtw45s+fz5IlSxrc17cu6PV6du7cyZAhQ7C3t6dv374t3re5ueDg4MCMGTPEPrD79u1j/fr1TT5uVlYW7dq1QyaT4efn16TWk7t27SI6OprXX3+d119/3WaMgTJU/EIHMrKt7LR2XrnccTEBRS3MHEAUgNLr9ZSXl9e7xMbDw4PIyEhkMhmVlZXExcU12IET3m9nZ0dAQAAeHh5oNBoqKyvRaDS0adMGnU4nKkPXByaTibi4OLp06YK9vT1RUVGcOnWq3q2hzGbIL9BSWqHCQ1GG1mQAew0YJHOHyQRZ6VBSFSmX2IRL61kp4eLiQps2ba5gJgi1xjt27CA7O9umY5GUjXYtJMz+DWg2JxmsUv1BQUHcfPPN2Nvb89Zbb/Haa681WSn3WkCPHj3E9eaYnG677TYmTpzIkiVLmqSiais4ODgwadIkoqOjWbRoERcuXCAoKAh7e3vMZnOjhWcMBgPFxcU4OTnh5ubWcn3fdK4Q1pc5c26iQ4cOKBQKMjMzqzsLej2cOwunT0POachI5b4j6TaL2FssFvLy8sjLy+P06dMiG0Gj0RAWFkZ0dDRdu3alc+fO6HQ6vLy8uOuuu3j22WcpKSlh3759uLi48PbbbzfLgHns2DFKS0vR6XT07duXxYsXN0ggSlDhFDJuGo2G6OhokpOTxaCSIMrz1FNPceTIEWRlVd/t0hoOWJVk7OJYziRnBVo5sOMlQAEo4a8fQKaGDXagVEOeGtRqsLNjhFyNWn1psbOzY5K9PRqNRuxrKPQ41Gg04rqdnV2Do+FqtZrQ0FBUKhUbNmwgLi6OzZs3N+o3ioyMpHfv3taPX1jI8uXLa3xfWVkZp06duoKCJZPJ8PDwwM/PD1dXV1xcXK5w8l1cXKqVDPxe5dePlMb9BHb3RS1Wi8JLdJzIAhnQLcIJ1wirwSUdDyoqKkRnUPqanp6Os7Mz3bp14+mnnwaszn6HDh3EoIBSqeTMmTOiAnFDYMt65Mtx8eJFpk+fzvvvv4+dnR29e/fmwQcfJCUlRczEGAwGjh8/zuHDhzl+/DgJCQm26alrNkFFhnXJPwRbrJuf/MH6fXl7e+Pv70+7du24LTwcRXg4VDkcAQEB4OcNN/cHhRKSz8Dh/bB+N9Sjw4EtcFZjzZCpTaYmMV/MZjMODg4EBASQkJDA//3f/zFhwgS6dOnC/PnzW7WHqNDT+NixY0yZMoXAwECWLq1pUGs8tmzZIgYxu3fv/o9wktVqNW+88YZYH5uUlMT8+TX0omsEkpKSuPnmmwFo06ZNk5xkgCVLlvDOO+8wZ84c3nnnHVGgqTFQKpX4+/vzX/wor4o0dQtOY2DUWeTfX31fR0dHkXq/d+/eejmjvr6+hIWFIZPJMBgMxMXFNSrRIZPJcHJyEtkzAkwmEwqFQpxL7e3tCQ0NxWKx1IsRIFxTTEwMarWayMhIVCpVvbqwGI1y/vtrdwDu1J4kvPSiVSiyyDYZf7lcTkREBJ6el2iFlZWV5ObmkpeXR1BQEOfOnbP5+KNUKgkNDQWsej5Nud/+Mbhe6dZSLFiwAG9vb9q1a4eXlxcffPABM2bMsE2dQSuic+fO4rqtaeSjR49m9OjRzJo1i+PHj9v02I1BdHQ0r776KhkZGSxduhSLxUJAQICY5Tl37lyT6mDz8vJwcnLC1dUVvVyOUjiWEN2TZoirfDRLlGSbkN14+plL2/pYFWlkklbBWq2WXr16MXDgQGJiYpDJZNU6leTm5nL8+HFOnTrF6dOnuTslpVUyEuXl5cTFxREXF8fKlStRqVT06dOHwYMHc++99+Lk5CSKXMyePZv4+KuomTUBBoOBrVu3MnLkSLFudO3atQ06RmlpKadOnSIrK4uwsDC0Wi3BwcHY29uLCutbt25l8ODBjBs3jh9++AFvb2+8vLzEDK2bm5u4eHp6EhAQgJ9WgTclVLs5wvtaX4Us1iWRZJ5uepn2VWEwGEhNTSUxMZEePXqgVqspKysjOTm5SbV00lZRy5YtazCbxGKxkJOTUyclUKlUig60sIxs4wQOTuDgCOGOoHGEfEfr346OcFlnb6NcgVIuvyIbYW9vXyPtOykpiZEjR4pCJ4cPHyYyMhKlUonFYiE1NZWUJjyDUqOtOZg+ubm5TJ8+nRkzZoi9Mf39/cUWKVu3brW5ISOr8hcsktteWjZgNBpJS0sjLS2N/fv3813Vdj8/P8LDwwkPD+dYUBAdO3ZEZgIC2lmXUeM5e/Ys27dvx3XnTvLz86u1n7NUVRPV1QTlYtVQ5Cqd3qtuWaFP6dmu7shDIdR8EbNSQiFtoCFz9uxZOnbsiNFoFIObK1eu5KabbmLhwoV8+eWXLdJx4moQnOTZs2fj4uLCggULbDannDp1SgxixsTE1L3DNQ6NRsOMGTOIjo4GrEHBOXPm2CwoLe2x3aZNG3bv3t2k4xmNRmbMmMGrr77KzJkzmTt3br2p1/b29qK45wInHeddXDHIFZRrQIaFgf3P0T26yiEUftqTNR9LoPhaLJZ6OcjBwcEEB1vVUCsqKoiLi2uwNoVCoaBNmza4uLigUqlEtef8/HyRUiyXy8XyEbA68+3bt6esrIxz587V2d+7vLycI0eO0KlTJzQaDaGhoajVapKSkqh2Rwhx+5XWQUdlAWVGG4wWOaW+KtB5gcYC5TlWpou0pUL6Za/1QHR0tCieVV5eTkpKCtnZ2WIQ96abbmoWu71t27Zi6daNeuSWQ7M7yXq9nnfeeYf33nsPPz8/DAYDH3zwAbNnz75qb9xrGSqVivbtrU9adna2TWXYJ0yYQP/+/Zk2bZrN6bMNhUwm4/7772fMmDFs27aN2NhY8X8Gg0HsPdpUQZy8vDxCQkKQy+Uku7gQWsfg2RAolUq6devGwIED6dmzZzXqqdlsJi4ujv3793PgwIFrVk7fYDCwY8cOXF1diYmJIS8vj9zcXObOnUtcXFyznnvTpk2MHDkSgCFDhjTYSRZQUFDAkSNHiI6OxsXFBW9vb1QqFcePH0ehUIjiO48++ihHjhyp5uAImV/BebKzs0Mh0yNvBuFmvV5PRUUFFRUVYkZUWEpLS8nPz+fixYui8JWwLnVePTw8WLhwIQ4ODvTu3ZuxY8fy448/Nvha/Pz8xPr0ixcvsm3bNpt9zsthNBrJzc2tHuWXBqe6V71K67xHaK2O8x6r43yqc1f+8vFDo9FgMpnQarXib+fm5iYacwJcXV3F9juTJ0/m9OnTIkUtPj6+yYwjoRwGaDZV2KysLN59910++OADTp06RWFhIcnJyaxZs6bunVsQQknI9u3bAavWRffu3enZsyfdunXDzs5OVEx//PHHiYuLY/v27ezZs8emZT7FajVZDtYmZKGmpo3zhYWFHDlyBHd3d+RyORqNBrlczoEDB8jJyeGpp54iJiamST3jbYHMzEymTJnCrFmzeOutt3jvvfds4vhZLBaOHTtG7969cXR0pG3bto1S+L4W4O7uzsyZM8UxoqysjDlz5ti0H7DUSQ4JCan9jQ2AXq/nvffe49FHH2XevHnMnj2b5OTkakwkYV2lUqHRaFCr1dXYSWeqVmVYiLTLoaf2Al7R9WdsCaJZ9Qm+hIWF4ednHdhLS0sblUH29fUlODgYtVqNyWTCbDZTVlbGvn37rgiQFhUVia2USkpKUKlUIlsoLy+PxMTEqz4LlZWVxMbG0qFDBxwdHQkMDLS2YTpzBnktzCKZDOzlRkpMaiplSvDwhItZYGl6pNzDw0N0kNPT0zl79uwVDKfQ0FCbiERejhuiXTXASP2yxI0vA29+JxmssvnTpk3j2WefpWfPnshkMt577z2+/vrrRhvdrYmoqCjR2bJVU3mFQsFLL71EeHi42OapNeHm5sarr76Kt7c3K1asECOkJSUlJCcn25QyX1ZWRkVFBfb29iS5udnGSfYLgV7DWP78zTg4VOsMy6lTp9i+fTu7du2yDf2xBdC9e3cee+wxzGYzeXl5fPjhhxw6dKjZz5ucnExCQgKRkZG0adOG8PDwRlO7hVqj8PBwvL29cXNzo0ePHgwePJibbrqJ/Px8QkNDxQlApVKJhoawf0FBAQaDgajSNHQVJWC/F8wGMOtBWWl93awHQyUc01sp85WVfFSmF+tChVepI1xeXm6zjEVubi7/+c9/eOutt5DJZIwfP56UlJQGt4W56667RGNqzZo1Lc5qkGYoLQJTVOL7yZ4ow5omrBqrDhyhc+fOODk5iXQ7QBQuyc3NxdXVVVSz9/HxobCwkODgYMxmM127diU6OppJkyY1eXyRy+VioCUzM7NBZQINRVpaGm+99RYffPAB9vb29O/fn+TkZFatWtVs52wqioqK2Lp1K1u3bsXOzo6bbrqJgQMH0rVrV+RyOZ06daJTp04888wzVi0C4wY43/S5Tuj3KsNCiLnpc4jQYzklJQVHR0eCg4Nxc3Pj/PnzfP3119x+++18/PHHzJ07t9kCJfVBYWEh06ZNY/r06bz77rvMmjXLJnPP0aNHxXKMmJiY69JJ7t69O88//7zofBw7doxvvvmmxv7xTUFOTo7YBkqqGdAUqNVqHBwc2Lp1K46OjixevJj//ve/NZZ36PV67tFcChT+YbJua2MpxbusmE55mbhYqoI570l2FMbhWpwBwUm7mvK/TCYjMjJSpAgXFhZy/PjxBs0pTk5OhIWFIZfLxWBGSUkJBQUFoq7M5RAyn3q9nv379+Pi4kJISAharRZ3d3dcXV1JTk4mNTW11nIag8HAsWPHaN++PQ8FuEKoD+s8VYxMi0dlMYtMFSS3iynHei2K82Zw9YMT6ZcEPaXzWlW1R0E9vwNpBrm2+7NNmzasW7eunkesP26IdrUOWsRJBqujvGDBAqZPn06HDh1Qq9VMnDiR3r178/HHH9tUIbC5IaVaS7OrjYXQ69bJyYmpU6faVKG4MejevTsvv/wyJ06cYMuWLRQUFIj02Ob6nQoKCvDx8SHT2RGZkOwVaEbtJG+sSZBLGKt+WgIefcF3ODz9MQAOVSyitLQ0tm/fzo4dO67ZjHFtCAgIYMqUKeIk9P333zeZKtYQbNiwQRSMGDNmDO+8804de9QOi8XCqVOnxCzrvffeS2pqKiaTiby8PJKSkjh06JCojl1YWEhRURFZWVmkpKRQXFxMeXk5hcHlgAWk3bcEmrVQwi/Jem5rnk4steLgwYMsX76cRx55BIBXXnmFKVOmVMtmXA1OTk7ceuutgHVC3rBhQx17XBs4efIkWq1WbLXi4eEh1tu5ubkRGxtb7Tv45ptv6Nu3Ly+//DIuLi4YDAaeeuoppk6d2qSgQGBgoGjI2drYrglJSUnMmzeP6dOnix0dkpOTGyR21xDYUpm9srKSnTt3snPnTpycnLj55psZOHCgWAfYt29ffqcv6e3SGWVYx5YtW2oNOogC2zVMYSXABUdHTIDvoFK09xqrjeMlVTRIhyt3rReKi4s5fvw4Tk5OREZGUl5ezurVq+nYsSPvv/8+y5cv5/fff2/k0ZuO8vJy3n77bSZPniyWnTV1PpXaH507d2b16tVNvMqWg1arZcKECdx22yVlzszMTBYtWtRs5XjJyclERUXh6emJVqttFEvCxcUFX19fnJ2dq7FjYmNj0el0PPzww3z66acUFhZiMpmqBWL7yo046itxrKxgep5V5f4+D6zZzsAgCNOAyg58iqE4G8rykUiT1giBzlybdoYgfiXoTuTl5REfH9+gEjlvb2/Cw8ORyWTo9XoKCgpISkpi0KBB+Pv7A1aH+HK6t5BMslgs4hx/8eJFAgICCA4ORi6XExISgouLy1WVtU0mE8ePHyfSOZIER0/OOrjzXZsujEyLx50rf0Njleqq0mwGHz/IsM39JOjv1HbfKJVK2rRp0ywsUMEG0+v1/xgB5CZDX7XU532NRIs5yWCN+s6YMYMnnniCESNGANCpUyc+++wzli5dek0IVNUH0vqfY8eONelYTk5OzJw5k7KyMt544w2b9C1tLBQKBY8++iiDBw9m2bJlFBUVIZfLUalUHDlypFnVtYX2DDk6HSaZDEVDRHocvCByKPQcDKoqpcE0oLSY337fyvbt21s1i9BUPPbYY6Ji4l9//cXKlStb9Py7d+/moYcewt3dnZ49e9KpU6cm3/cuLi6MGTNG7CO7f/9+vv/+exISEvD29hajpkLENj8/v5qpIBNsS6no6Zyq14Kq97SwY3w5fv75Z9q3b89tt91GYWEhkydP5oUXXqiXANWIESNQq9UEBQWxefPmVqmNt0hFsYU5+fzV99Hr9aIRlZ6ejkqlIjg4GD8/Kw27Q4cOHD16tJoxpNfr+fLLL3nqqaews7OjXbt2jB49ulEUdQGCwAm0jJMMsH//flasWMFDDz0EwNNPP82hQ4daVWm5oSgqKmLdunWsW7cOb29vBgwYwODBg/Hy8sLPz48JEybw8MMPs2PHDtatW9fgcTW7itXj7dF8ojNFRUViaYdGo+H48ePExcXx2GOPERMTw4IFC1pN9MZoNDJ37lwmTpzIhx9+yMyZM5tk8Ar9zz08PIiOjkapVDapxUxLISYmhhdffFFs0QZw6NAhPvroo2ZldyUlJREVZRU0CQ4ObpCeh5ubG15eXnh5eV3xP0GA9IcffsBsNjNs2DCmTJlyRTCpjxZrO7fojjzYJtI6TkW1BY0WigrAvhyMevBzAp2bVaQv/jjE74VD+6CGFkRSJ/ny1lZeXl60a9dOZPVkZGSQmJjYIBFEX19ffH19RQc5MTFRpMFL77XLWx3CJSdZ6jxbLBYuXLhAdnY2YWFhYuukDh06XNWusFgs3JEZj9ak57CTPzl2OpaHdOXWkkQ6lWaKChkmiwyT4CRbLNAhBv5Xh/pZPWE2m7G3t681ING1a1ex5MaW8PT0FO+7M2fONEkD6AYahhZ1ksH6UH355Zfs3buXF198EU9PT+zt7Zk0aRLDhw9nxYoVHDhwoO4DtRJ0Op1Y63b+/PkmZX3t7e2ZPXs2mZmZzJs3r1UnNx8fH6ZOnYpMJhP7MtvZ2WEwGIiNjW32mi7BaDH5y8m7V4sXpZd65baRvHGJ9cWSJ4OuXWH4cOjaHWQyLFXluZbTpxm8bh27du2yWWuG1kJISAj+/v5kZGSgVCpZsGBBi1+DXq9n+fLlvPzyy4C1bv7FF19ssNqwgLCwMJ555pLI2r59+5gzZw4mkwlXV1fCw8MBKw0/Njb2ujD6LkfXrl0ZMWIEXbt2FZ2k4OBg+vXrx86dO6+6r1qtFoOIFRUVuLi48O233/LXX3+xZcuWa0LMr74wGAwkJiZSXl5OaGioKN5y4sQJsX+40DJk3rx5TJs2Dblczv3338/69esbbTD37NlTXG8pJxlg1apVREdHExwcTHFxMQMHDmTLli0tdn5bIisri59++olVq1bRtWtXhg8fTvfu3VGr1dx+++3cfvvtnD59mnX1HGsdZTL66nTIgSHmEmvgRZLgaWwGuSZI1XGFcpspU6YwceJEPvnkEz788ENOnqxFCamZYbFY+OKLLygoKOCdd95hypQpTWI3HT16lEGDBokqwNfy+BAWFsb48ePp1u2SqmJ5eTlfffVVi4isXS7eVR8nWSaT0a5dO3x8fMTe5Xq9nqysLIqLiykuLq5W1ztv3jxmzZpFyYtPwWcfgZ0ddAyH9jHQvwv4h0F2Cv/ddhL278TyzTeQnAwGAzJBkDQRay9fb28qYroj790f9dKJcHA/rFwBpy61tJM64m5ubuTm5qJQKESxXLBmYhMTExtcxie041MoFBQWFpKQkFCtLKkxTrKAyspKTpw4QUhICAEBAchkMlxcXK5azyszwKD0s/ilFrEpJBy9QsELynByDW4c+vQ09iYj551cMbexOrF3mjX8x8OP8buOkF2V45HGftVVshWubSQba7gNLVWaHGcDCvlFFQjYsarQicDyIkol/vDb/fvXOb83BtL57PDhwzY//g3UjhZ3kgUcO3aM5557jieeeILBgwcDVofgrbfe4vTp03z77bc2q/e1JTp16iRGkZpyfQqFgtdff52ioiI+/PDDVs029OvXj0mTJvHnn3/yzTff4OLiItaBJiQktIjoSWlpKSUlJTihJAsHq5NcEzSO0Pl2GDkMvL0vbdfrMe/YgXn9ekhM5PpvhmFFz549RaGNxYsX26xutqHYtm0bd9xxB+3ataNNmzbcfvvtjer9qVAoePnll1Gr1aLwzIoVKzCZTDg4ONC+fXsxYt2Yvo2tCQcHB2677TaGDRuGRqNhw4YNLFq0CH9/f9555x3S0tLo27dvnZNov379xN6Lq1atYv78+YSEhDBo0CBef/11KioqxHrS66V0IC0tTeyl6ebmRrt27Th9+rSY4QCrVsDvv//OnXfeiUKhYMCAAY2ix/bs2ZM+fazNeUtKSlpcIPLHH3/kgw8+wN3dnV69el23TrIAi8XCoUOHOHToEF5eXgwdOpTBgwfj5OQkKmY/8cQT/Pnnn6xfv77We1Kr1WIwGDAajXg7Fzf7dQsUzZ49eyKXy3F0dOTdd99l+PDhzJo1i//973/89NNPjQ72NRUrV65Ep9Mxa9YspkyZ0uiAkOAkg5VyfS06ycHBwYwfP55evXpV23706FEWLlzYYuV2DRXvUiqVREdH4+xs7YFXWVkptjas7b4xmUx89NFHTP/pO+jRG+ztofginDwK+36Hc0ehOB/2VO1QG0HPZIL0dEzJazCtWYM6wA1G3QMvTeHODX/y22+/WXcvKxNVzkNDQ3F3d69mw5WUlBAfH98olqIgtqtUKomPj79C5Ku+TvLV5vGkpCR8fX2Ry+Votdp6iV5F5eXgW1LMH2FRoHHEw8ODrz2dCCzOJ93B+lu5VJYTFRXFyZMnbcaCDDHn420uxiCTc9jVn8ByyTNbpe3w6quv2uRcUkhbzjZXCc91iX9CC6iroby8nE8//ZSdO3fyyCOP0K6dtfg0PDycOXPmcOrUKTZu3Mju3btbVZ1SCinVuin1yM899xwuLi5Mmzat1RxkuVzOxIkTufnmm/nPf/4jPnyCgV5eXk5+DfSe5oDZbEYmk1GEPRk40ZHLIp7KMNCMhJf6gVwpagWRng7r1sHWrZj/gX3jpH2bm1vJui4sXbqU999/H7BSwGNjY8nOzm7QMUaPHi22AkpJSeGnn34SaWJRUVEoFApMJhO/XozD26cqICDUpO+5dByhPc1FSdtgVyEx1MKxtbZt2zJixAgGDBhAYmIiK1asYM+ePeJzLdSARUVF4e/vT2Rk5FWFN6RZFkHYMCkpiSVLlvD111/TrVs3brvtNhYtWkRCQoI4Rtp6HLFIJ5aqSHrt0jB149y5c9jZ2eHp6YmPjw/5+fkUF19ylkwmExs3buTOO+8EYNCgQQ12koV+7gIWL17c4iUs8fHxGI1GsWfxPwnZ2dksX76cH374gb59+zJ8+HAiIyNxdHTk7rvv5u677+bw4cP88ccfV7RGdHJyws7ODrVajZdL8wmpSaHX68nLy8PT01N0dNatW0d8fDxTp06lY8eOvPvuu81aSnQ1LF26FHd3d2bMmMH06dMbFQSVButjYmJYsWKFLS+x0VAoFHTr1o3bb79dFGwVkJ2dzffff9/ivZ2lNFhpSUZtCAoKwsvLC51OR3l5OeXl5QQHBxMYGIjFYhFbH5nNZtFpFrafiDuCxt2Dc5+8jzm6GLnMQoR9Dh7tS9HIQVaVsbRIu3c9XfX61qVNOkFro/1FSFoC+nB+vX8adG6H/fufUFlZSXp6Ou3atcPOzg5nZ2fRQU5NTSUpKanRgSCdToe9vT25ubk1qmDX5SQL267GMtFoNCiVSsxmc41lEJZgyR9VtoAsGSirQHYwVvw9VqKmQumMPfZghLPn05kwYbjITK2RqVJFMrJIssGWYdXPBcDD1hd5t96E7NKxdauOwpBcynsp0d1f9R306Ul2drbNqdb29vZ06tQJsIqC3qhHblm0qpMs4NixY0yePJmePXvy4IMPisqDERERREREMHHiRHbv3s2ff/7JiRMnWvVahf5yQKP70z744IN06tSJV199tdVqkNVqNVOnTsXb25sXX3yxWqsFqSJhS8EMbCwqIq5AR0alI6QAZ4CQKEwd7kfWpQsAcgVgsSDL/Rv+Xgtnj1rf5w52/zwfuVrD+tYWtzt58iQ7duxgwIAB6HQ6XnvttQYJLAUEBDB27FjAGhRZuXIlJpMJuVxOUFCQWHcdHx+Pt2PLGNGNhVKppG/fvtxxxx20adOGbdu28eqrr9YqzLVhwwaxFm7IkCFXdZKFQJzQY1oKk8nE/v372b9/P05OTgwcOJAHHniAJ554gg0bNrBhw4Y6+0+2JhISEtBoNDg4OBAWFlZtPJfJZKSmpnLmzBnatWtH27ZtCQ4ObpBRMGHCBFGB9MCBA2LLo5ZGTk4Ovr6+1Z7ffxIMBgPbt29n+/bthISEMHz4cAYOHIidnR1du3ala9euJCUl8eOPP7JnjzW6JQgHlZaWUnmTmUpAKzmmUGXXlEBMTRAcTylrISkpiZdeeokpU6bwwQcfMHPmzFZ7bj766CNmzZrF1KlT+b//+78G1xvm5+eTkZEhtuZpbQQFBXHbbbdxyy23iIEJARcvXuTHH39k06ZNrZIcEPraBgUFERYWhrOz81VL5s6dO4fZbKZt27YYjUZxjrocZrP5CnXp7Xv2MvilKZxw9kJfZnXRzla4UW5W0dsxGYUio3HfQdppmP4SvPAaH374IbNmzSIjI4OysjJCQ0MpLS2lqKiIzMzMJrciEj5TbdfZFLq1gICAAHG9ocEqi8XC+fPnuXjxIn5+fpjNZhwdHTl37pyo0v/ll1826JhXQ3a2ghMn7LFYZHQPuIBGJcmQ92seqnXnzp2prKxEqVTeyCJfjn96JvlyCMZfv379GDt2LEFBQYBV/XnQoEEMGjSIoqIijh8/zunTpzl37hzJycktlu0EROprQUFBo6LPgwYNYvjw4UydOrVFr1sKBwcHZsyYgclk4rXXXrvicwgR35amofkWFxOHL7lqHeVRXdHcfS+EdURWYP2/pbAQtq6HPzdChO1aUF3LEDJRpaWlrZbtkOLzzz8nPDwcX19f2rVrx+OPP85XX31Vr32fe+45cSJdvXo1hYWFyOVyDAYDbm5u1vvRL4+RnherR3GriohkNdQKuUoKjGTVE1dYbpP8z0blbh4eHgwdOpQhQ4ZQUlLCunXrROG9q2H37t089dRT6HQ6+vXrxxdffFFj1igkJER0Jo4fP37VZ7CoqIg1a9awZs0aOnfuzMiRI1myZAn79u3jjz/+aHLNpa2dFbCOKadPn6ZLly4YDAa8vLzEdlFOTk5iayKBVXTrrbfy9ddf1+vY99xzj6gIXlpaymeffdYMn6B+yM7OxtfXF51O12gV3esFSUlJfPbZZ3z99dfceuutjBgxAn9/f0JCQnj99de5cOECP/74o8gGk7IHWhKXi+1UVlby7rvvMmnSJObNm8eMGTNITU1t8esyGAy88847zJ07lwkTJrB48eIGHyM9PR1fX1/s7e1xdXVtMdvCwcGBoKAggoKCaN++Pe3bt69R2OrixYusXr2adevWtbpOyN9//01QUBAymYwePXrUWQudlZVFeXk5arUauVyOXC5HJpOJDKia1mUyGV7mfGSZaUR5upOryKTYpKbAZI9ObmBXUQg9ewZWCd81jI0FQFEhvPcWp+97hrlz5/LWW2+Rnp5u83pVYb6uj5MsOMRS1EW3FpTCy8rKyMzMbHR5VVFR0RXlCk8++ST79++3WUnSiRQvtvzlilJpRqczY6+UfCc+PtC5CzsWL639AI3EzTffjE6nIzs7u0W7mtyAFdeUkyxg165d7Nq1i3bt2nHbbbfRv39/dFWcEycnJ3r16iXWnIE141lSUlJtKS4uvmJbSUkJRqMRs9ksNkE3mUwYjcZqtBlhm0CvEQYIYQICGtWiwM/Pj4kTJ/J///d/rTIZg9XInzVrFqmpqcybN6/GCUuocalNwa85IAfUFy/ykF87Bg0axG4PD6tRVWClq/78889s3LhRvF6L1EeebH2xSHwC2c9XnkN0miStgVpbAbkuCOqfDaU1NxfKysp4//33mTdvHiqVipEjR3LixAkxW1QboqOjad/e2uMlIyODtWvXEhISgtlsxt3dXRRvusXcciJLDUFMTAwjRoyge/fuHDp0iHnz5jVIk8BgMLB7926GDBmCWq0mIiKiRiXPxpZzxMbGEhsbi7e3N8OHD+fNN98kNzeXP/74gx07drRaLXtNKCkpISUlheDgYLRaLUVFRSgUCjE4sGPHDp544gmUSiX9+/evl5M8bNgwHn30UfHvxYsXt2pGXfq8enp6/isocmVlZfzxxx/88ccf9OnTh/vvv582bdoQGBjI66+/jsFgYNu2baxYscKmIl11QaFQUFZWVqNzbjab+eSTTxg/fjwffPABs2fPvoK90RIoKytj1qxZLFy4kCNHjjRYvDQ9PV0s0/Dz8xOdZJlMhkajQaPRVHPyFArFFesKhUJctFotDg4OODo64uDgUG2RbrO3txevIT8/X7SPwOoY7du3jz///JPY2NhrRpH377//5r777gPgpptuqtNJFuzAhuK+e4G8nYTFqOFwLAD5D9lzKDGA2CRf7laqoFMksXkKOlsyrDs9XSVo2e7zSwf6X9WrlEjWGcDEp59+ysMPPyy2FLN16yGLxYLRaKzVeZXOK9J2WALqolsL949Wq63dpi64tFrfYHelkxPKIUOQvzGF96t8d33VJUivRCcQHe6UbKwqLZIG6o8qp7ApMR8IR6t15fbbB9CuXWDVcTXIxz0CW7bZXCNErVaLol0ajabR7NUbaDyuSSdZwJkzZzhz5gxLliyhV69e9O/fnw4dOlBQUCD2ZgPrjeTm5oabm9tVjlY7Lly4INZJ1oScnBzxYQ8LCyMxMZGMjIwGnUOhUDB58mQ2btzYaoJkQUFBzJo1iwMHDvD555/XmqUyGo3odLoWndR69OjB2LFj6datGwqFArPZTEpKCqtWrWLLli3XlYCTraDRaESKYGv3zpYiKSmJxYsXi7WfL774Iunp6VftATx8+HBx/bvvvsPBwQGNRoO9vb2YYUpOTsYh4Nr5nZVKJQMGDODuu+/GxcWFTZs28dVXXzWa9n78+HGGDBkCQPv27et0khszTmRlZfH111/z3XffMWDAAO644w4ee+wxNm3adFVRpZbGhQsX8Pb2xt7eHjc3N8xmMxqNBplMJgrNdOzYEXd3dxwcHK7assfV1ZUnnnhC/Hv58uVs27atJT5GrZA+r4Lz/2/Cnj172LNnDz179uT+++8XVabvvfdeOnTowE8//cSWLVtahHIrZPOvJoz13XffkZ+fz5w5c5g7d+4V9dQtgZycHL744gteeOEFnnvuuQaN+YKDERAQwJw5cygoKKCwsPCqdbd5eXm4u7s3+bqlx3NwcCA+Pp59+/axffv2Vmu1dTWcPn1adOi7dOmCWq1uvtKyzLMQ2Vf809Whgts6JxITksFvv7Qn36hhs6IdRpOc7pa0Rp1i+fLllJSU8O677zJnzhybqrar1WqxXrgmSLWCaqKi16cmGWzPWpTffTeWuDiwQdAgPsuTTXHWoJObmxv33nsvLi4uQNVnj4hA3q0bxokTm3yuy9G9e3cxkLB3797rqp1gS6AhT+2VIZz64Zp2kgUYDAYxuyyTyQgICKBdu3YEBwcTHByMm5ubGN0UBAtsCblcjqurKxqNhqysLOLj4xs8EN1///2o1WqWL19e95ubAVFRUbz11lv89ttvdfYfFaKmcrkcOzu7Zs1C9e7dm7Fjx9K2bVvAOugKGYdvv/22Wq30vw1a7aWKvWuNrrlx40Y6dOjAgAED0Gg0zJw5k8mTJ9eYvXNxcRGZH4WFhezZs4eAgAAx8FFcXCzSrcT2C+0lB7iKT6qXzL1iX18hOiyhW4viH5LHrzYWgVarZdiwYYwcOZLy8nJ++eUXtm/f3mSaoHTMELLqUigUCjp06ABY6YlNYZvo9Xo2b97M5s2biYqK4o477mDRokUcOXKEtWvXtnobCbPZTHx8POHh4Tg4OKBSqSgsLESlUqHX60lNTaVjx46A1fC/Wg336NGjOXv2LP369ePLL7/kf//7X63vbSlIM0/S5/jfhv379xMbG8tDDz3EoEGDxH6fzz33HPfffz//+9//2Lx5c7NScAXjva5s4Lp16ygoKOC1117jyy+/bJGWRJdjx44d9OjRgxdffJHZs2fXe7+EhATOnj2LwWDA3d0dpVLZbHonRqNRZOoVFhaSkpJCcnIyZ86cITk5udXp1PXB/v37GTJkCCqVii5duvD333/b/ByynyHyRDITJw7lxSoWrszF+upJKfe/P5Sffsol768TbCMUX9di/MdVZZClpeVll71CNTYcwC+//EJxcTFvv/0277//vs3G97ro1lInWcoqgOr069ruCSm7w9PTk6ysrGqUdZlMhrrs0rq9vQyDwVDj9Yjzf7t2MGUkbJoiCm4BqF2qXqUyEUIceoBkmzA1d4fKSgVbvw4DQnB1dWHs2LFiSzmwfl7164/DkV9RB+WDjascbrnlFnF9165dtj34DdQL14WTLIXQiPzChQs1/l+pVNZKD9LpdNUoRQLdSOjXJt2mUqlEmpJAx27fvj1ubm5ERUWxevXqel9zZGQkd911F6+++mqrTCBdunRh2rRpLF26lI0bN9b5funk6uDgYHMnWSaTcfPNN1erOwdrdumnn36ioqICOzs7PDw8aneSXWrYJmE0CnFPWXfJ/wWnSRp+sr3Ogs2gE2Utrz0nGeCTTz7Bx8eHiIgI3N3defnll3n33XevMM4GDx4sZsQ3bdqE0WgUI9QVFRUYjUZOnz7dGh+hGjw9PRk1ahRDhgwhMTGRzz77zKY923NycsjNzcXDw4PIyEjkcnm1CH1oaKgY5LMl2yQ+Pp74+HhcXV0ZNmwYL730EuXl5axdu5aNGze2GhW7uLiY8+fP0759e/R6fbX7XRog8Pf3r9VJVqlU9O/fH2dnZzIzM1m2bFmzX3d9IO1dKv1c/0Z4enpy5swZTp06RVlZGffeey8dO3bEw8ODp59+mjFjxvDLL7+wYcMGm2f01Gq1aKzXZwzds2cPRUVFTJ8+HZ1OJ7bZaUl8/vnnfPLJJwwbNoz169fXa5+ioiJCQ0MJDAxErVZz/vx5cnNzKS0tFenClZWV1UrKKioqRNaWtATNbDaLLRlrKmFrSUHP5sLu3buJjIzEz8+Pm2++uVmcZLDaNKGhoeDgAJdl1R0cFNx/vwfL91ZSbLZjX2kQ93Ccxha5bd68mYqKCl5//XVmzpxpE2quMG/XxuSTzvWXZ5KlQl617V9aWkp2djaenp507979ipKI8vLyGjPUer2esrIyioqKSEtLu2RX29nBy69C3A+Q3/Qs8pGjfpSVqZDJZYwcOVjiIEvg4QuLZjT5XJfDzc1NpFrn5eW1eneTaxEN8ab+0ZnkhsBoNFJQUNBkVb+aMHDgQCZPthbA1iROURPUajWTJ0/m22+/bZW6tLCwMKZNmya22qoPKisrqaioEGuw8/JsI5Ill8sZMGAAY8aMqUaXP3/+vKiCarFYCAkJwcfH54rI5L8N9vb2ItX/WqJbC9Dr9cyZM4f58+djMpmIjo5m2rRpzJo1S4z0yuVyhg4dClgDXBs2bAAgMTGRiooKSkpKyM/Pv0S3cqk6uKQkS3YVMoFamqQTWjcIkWJpNF6IFEtZlFV+aNu2bbnnnnvo06cP+/bt480332w2p/3kyZP0798fe3t7QkJCqoRbrLBSuKxoDs2C/Px8vv/+e3788Uf69OnDXXfdxX333cfPP//MunXrWsX4zcvL48CBA3h7e5OXlydeQ1raJeqhdKy4HMOHDxcVdA8dOtS8F9sAlJSUUFBQgMFgqFHQ5t8ER0dHKisrKS0t5fjx4xw+fJj27dtz//3307lzZ9zc3JgwYQL33Xcfv/76K2vXrrVZy0ehBMtisdR7DD1+/Dhvvvkm7777LoWFhS2ukF5aWspHH33EW2+9xZEjR+pVIiHYI6mpqfz6668sXWp7AaF/Eo4fP467uzsqlYpevXo1G2OutLTUWp4TEgI1ODlarYK+2vPsLw8kWe/MBZwJovFz/a5du9BqtcyYMYNp06ZdtQSqLggJI6hfJvlyFmd9Mslg1SgpKSkR2YT1gVqtRq1W4+LiQkBAAKmpqRjTU1A+ORHycuHCL/U+1tWQk2MNcAYE+OHt7VHzm35eDHrb3zu33367qAu0efPma6am/9+Gf5yT3JzIysoSjfn69r+84447KC4uZs2aNc15aTXC19eXmTNnsmLFigZL0wuS+o2t85ZCoVBw6623ct9991Xr+3v27FlWrlx5RRQ3Ly+PwMBAVCoVjo6ONauhSjsECY6PJGssEygzUhpNcA3bejfss7QkHB0dxRYy15LwkhRFRUXMmDGDuXPnolQq6dy5M88//zwLFiwArDU1gvjYwYMHxXpeoea8NdG1a1fuueceIiIi2Lx5M88++2yz1+wKTjJYKddSJ1lau9qctXwmk0ksX+nevTvjxo3jnnvuYdWqVWzYsKHF2S4VFRVXBBClQQJpixAptFotY8aMAaxO0Hfffdd8F9lAlJeXi0EPafDj3wa5XI6Hhwdyubwa++vkyZPMmDGD8PBwxo4dS48ePXB2duaRRx7hnnvu4bfffuOPP/5oMoNGmL+Ki4sbpGtx9uxZ3n33Xd58800KCws5cuRIk66joYiLi2Pnzp089NBDfPjhh3W+X7BHLBYLWVlZzX151z1MJhO7d+9m6NCh2NnZ0bNnz2ajs546dYoHO3bk+7g4zPMvbZep3gYgeoiMPXvbYKpUkODkRVBwIUgJBEKVzguSbVXBYcteybaq4LBs40YcHByYPXs2U6dObfScJhXiqi2AerWa5Po6yYWFhZSUlGAwGEQBXeCKdWGxs7NDq9Wi0+lwc3MTW0i+OXYsnTp14oUXXiD3rqqgu3T4cKl6lQbWhYC6lLgl2IRKP8or3UBmj1b7FTCbS8ajHTDQuuPftleclslkDB48GLB+9k2bNtn8HDdQP9xwkhsA6eRTn0yyVqtl9OjRfPDBB815WTXC2dmZ2bNns3Xr1kY56BcvXqwmqNPY+qbevXvz+OOPVwsqnDp1ipUrV9aa+REMGqVSiZeXV6u1DGltXMs1yVJkZGTwf//3f7zzzjuo1WpuvfVWcnNzWbFiBSNGjBDft3bt2la8yiooFNBtANx6Ny8bXfj99995//33W0xgJjHxknr35RlSqZPcUvf8wYMHOXjwID179mT8+PHce++9rFq1io0bN7aqWF5OTo6Yha0tkzxp0iTxO9u+fXuTsia2hvR5/TfTrT09PcVsVE1tiU6fPs2cOXNo27YtY8eOpXfv3jg6OvLggw9y991388MPP7B27dpGCdZYaxitwoCNYUMdPXqUTz75hNdff5033nijWkCrJfDDDz/w5ZdfEhISUqdqsdQeuVY6IVzr2LFjh8hyGjJkSLM5yXv37mXs2LF8//33Nf5fLrcQ5FrA8Uxvsstso/v+888/4+TkxDvvvMPUqVNr1AqRy+U4ODjg5OSEo6OjSI+urKxEpVJhZ2eHXC6nsLCwVvtPur0xNckCTCZTo4I7dnZ2hISEiGPHl19+aVPmTmBgKWVlCrKy7DGbwTqUyYGhwAWgeZJfXbp0ERMkhw4d+ldr81wNLRHOv+EkNwAXL14kPz8fvV5frwfxnnvu4dy5cy2uZm1vb8/bb79NfHx8vXuMXo6CggKxZYSHh0etNeC1ISQkhCeffFIUIgIrxenHH3+s8/uwWCxkZ2fj5+eHt7c3SUlJ/0qqibT+5VpUCZUiISGB+fPn8/rrryOTyRgzZgwmk4kuXboA1gBTfcREZPWsSBC/DWnrBoEpIIiaSKnVPlroPpRlL4yivLyc1V+vZtu2bS2eNZXWql5OT5P+3i0dGBJ61Pfu3Ztx48Zx77338tNPP7F58+ZWUdS0WCykp6cTHByMr6/vFfXbDz74IP369QOs2YwVK1a0+DVeDdLn9d/sJPv6+gJWxsnVAq3nzp3jvffeIzg4mDFjxoi9QSdMmMCwYcNYsmRJg+n0Li4u4jPV2L7BO3fuxM3NjbfffpspU6a0qDp8Xl4ea9eu5eGHH2bWrFlXfa+joyOZmZnY29tfMwr21zpOnDhBRkYGvr6+dOrUqV7BiMbgwIED7HzlJSa18Yd8iYK1oC+YDO5V1LhF5+156L3q+wsjiU6aAa3qFIVUP1bKrgO+/vprMaP8+uuvi2OSk5MTwcHBuLi41Njms7S0FJ1Oh1wux2g0UllZ2ahMcn1qkpsKg8FA7969ad++PZ9//jn5+fmEh4cTd8xCx5IsGC55s2CyS0XPhGS5tDSrjbDigr+/gt27HSGrhCOLK+i2bz3c+QookuC5N6C8/KrlYI3FsGHDxHWhRO0GWgfy1r6A6w1lZWV4e3sTHR191fe5uLgwatSoVlGznjRpEqWlpXz88ceNPobZbBajjwJdtj5wcnJi0qRJLFiwQHSQz58/z5tvvskbb7xR74BBRkYGFRUVVFZW1timQlZ4adGvty4kSha/qmWhZLnfupT2vrRcy7heMskC9u7dy1dffSX+/corr4gOQn0FaGwOFw+48wmY8g1E9OCzzz7jmWeeYdOmTa0ioielzV/uJLdGJvly7N27l+eff56lS5cycuRIFi9ezO233y4KuLQkhLpkpVJZjYly6623VqNZf/jhh41uy9VckAZD/q3q1lqtFpVKRVlZWb1bJiYnJ/Phhx8yadIk0Sn29/dn5syZzJw5s1bqfU0Q5q3KysomBRl//fVXduzYwRtvvFHN8G8JrFq1iqioqDrtjbCwMHx8fHBxcblBt24Afv31V3H9rrvuapZzVFRUwJHD0LtPre9RYNsWSAI+++wzUlNTeffdd/Hz8yMsLIzOnTvj6uoqOsgmk4nCwkKys7PJzs6msLCQ3NxccnJyuHDhwlU7udgqk9wYuLq68s4779C9e3defvllNmzYINpJmzzDOadxreMIdSMwsIKgoApkcgWZDo9T+dQiSIqFZVOhmdTjXV1d6dGjB2BNzLVGO7rrBUas2eS6lqaEaG5kkhuI9PR0/P39sbOzw83NrUYaC8DYsWOJjY1tcdXeAQMG0KVLF55//vkmZ4Dy8vLw8PAQqThXiwYqFApGjhzJ/fffLxqFRUVFfPvtt2zatKnBffBKS0sxGAw4Ojri6+t7zRnBLQFpBkpqdF/L+OOPP/Dw8GDSpEkUFxdjZ2dHaWkpu3fbtm5HzLn+UPP/Q0JCuOeee+jbty9///03q59sPjGuhkCIvMtkMqKiopg/fz5ms5nY2NhqSu+tXWLw119/sWfPHm6++WbGjRvHmDFj+OGHH9i+fXuLsTouV7jOyMigQ4cOPPfcc+L2JUuW2FSB3FaQBrVqVET9F8DHxweNRoPJZGrw+J2amsqsWbPo2rUrTz75JP7+/nTr1o0uXbqwdu1avv/++zrHRFdXq5FsC6ri119/zdy5c3nooYcazc5qDEpKSli9ejWPPPIIU6dOrfV9fn5+gNWovlb1K65FbNmyhQcffBBHR0f69+/PsmXLarXpmoQ9f8Gou2Ddqhr/balykmvK7DYFZrOZuXPnMmPGDL744guWLl1KdnY2ZrOZ1NRUCgoKKCsra3Sf4vrWJNtaFLJz585MnjyZQ4cOMWvWLPGej4uLo0uXLphRs8a7PWONR/FVNj5AJpPBsGEOnAt8GLNFxqqffuLW82vxszRfgP2OO+4QS1Q2bdr0r2RRXku44SQ3EOnp6eK6n59fjQOqq6srgwcP5qWXXmrBK7PWfz3zzDP85z//aTS9TIqCggJKSkpQKBS4uLjUamz07NmTJ554QqTWmUwmfv/9d1auXNmkDGhmZiaOjo64uLhcVX1SzMdJ21q2fItLm0NQ7YVrn24txTfffMOjjz5KSUkJaWlp/Pe//22xOrng4GAefPBBOnfuzJ9//tkiYlwNQWVlJTKZjHbt2uHv78+bb75JRUUFXbt2ZcSIEaIa6rWgiGyxWNi1axe7d+9mwIABPPDAA4wdO5Zvv/3W5kGPmnC5eFdGRka1bN7atWv5/fffm/06GoOysjLMZjNyubzac/xvgpD9F4zyxuDw4cM899xzDB8+nHHjxqHT6Rg5ciQDBw7ku+++Y8OGDTUe287ODplMRklJiU2cHpPJxPz581mwYAGHDx9u0RKqX3/9lTvuuIPOnTsTGxt7xf81Go14j0ntkxuoG3q9nvXr1zNmzBgUCgV33HFHk9l/lrCqlR6SjS77oe/zFLoEY64SKXQTRKwTwc8PwsJqdpKFEFs1N1aIn0v62shq6fgUEBDA1q1b0Wq1TJw4kZkzZ3Lw4MFGO8ZStHQm2d3dnSeeeIKuXbuyZMmSK3qZV1ZWEhcXhzwmBqVSiaMhksfdDyKTAf2Fi5HscKbqVZqsFWKu/YcD3XFyisTH7iNW/nEewxELP5k6cfuZM3TItb1No9VqRR0Xo9F4g2p9DeAG3bqBkNLGahOUue2224iLi2twHW9TIJPJmDx5Mjt37mT//v02OWZlZSVyuRyNRlOjmndQUBCzZ8/mzTffFB3kAwcOMGnSJP773/82mSKcnZ0tDuS2UNm+3hAYGCiu15eueK1A6NHo5+dnk36NdSEgIICpU6cyf/58srKyePLJJ/nyyy+vKQcZrMaC2WympKSEXbt2sW7dOrZu3cq8efNYtGiRGNyqb4u5loDFYmH79u0888wz/PTTTzz55JO88847DaK+NgbSNlBhYWHMmjVLzMoeOnSoGrX/WoTwzPr7+9s8Q3Stw9HRUTSSmxogE4KuTz31FOvWrcNiseDo6MjTTz/NwoULiYmJuWIfb29vUQW3qKioSecXkJ6ezpIlS3j55ZdblB1QWVnJpk2bRJGpyyG1Q663eeJawB9//CGy5IYNG3ZFGYxNoC+Dk5tR3Xdfjf82GAxi202pqnRT0aZNG9q0aQNYheC+++47Xn75ZcLDw21yfGni4nInWfo5muokq1Qq7rvvPj7//HP0ej1PP/30FQ6ygNLSUpE1dtGgJaXSpeEn1LYH7sEqf/0rPizj3l6xqI1GDAoF6yIjad++vc2D2SNGjBCZmFu2bGkeVsM/CPoGLI3FDSe5gZAqqNZWJzR48GA2btzYQldkxejRo3F2drZ5f0TByXB3dxcfXnt7e5588kkWLlxI586dAbhw4QIzZsxgzpw5Notmm0wmiouLsVgsODk52eSY1xMEJzknJ8dmfUNbCkKgRiaT0bVr12Y7j6+vL6+88goLFiygqKiIiRMnsmTJkmbpk24LqNVqZDIZ6enpV1DQkpKSRGOtvi3mWhJms5ktW7bw9NNPk5SUxIIFC3j00UebrZ+5QDlXKpXceeedYuDg3LlzfPDBB9c8DU1ocaZWq6+poEdLwNnZGbPZjMlkspmTWlxczBdffMELL7wgZnKDgoKYM2cO06dPF7Ur5HK56Djm5ubaVHhu06ZNnDlzhueff95mx6wPNm/eTM+ePWtkJUjtkMtbqd1A3SgoKBB7Yet0Om6//famHbBH1dJesuwBvviZDb1708HPj8tD/rm5uZjNZgwGA2FhYSLdthr2SpZ1VUuaZLkMAQEBYglPUVERx44d47vvvmPFihXcfPPNTfuMVaisrBQTGc2VSb755ptZsmQJvXr1YsaMGSxYsKDO+T03N5eKigr+OAXDV/shewu4t2o5KlkOVi07qpa9ajg5AQyzIPEDOHQbHHobVBDoW8iY2Fg8SkowY9U86N69u83GdrVazZ13WpVILRYLP//8s02OewNNww0nuYE4deqUSDERlHulcHV1JTMz02bZ3PrA29ubsWPHMm/ePJvXI2VkZIiGe2BgIDExMXz66aeMHDkSuVxOcXExX375Jc8//3yNVLCmIicnB7PZjIeHx78qG+Pq6irWJLd2P+HGQFon2rNnT5sf39PTkxdeeIFPP/0Ug8HAM888wxdffNGoVi8tCWnWR0onhuoZt2vZqSovL2fp0qVMnjyZiIgIPv/8c5sZXVIYDAaMRiPdunUTmSrZ2dnMmjXruggaSZlE0nrzfwPc3d2RyWTk5OTYhNYpRXJyMm+99RbvvPOOmDm96aabWLRoEYMHD8bPz0800JuDzbVw4ULat2/fLONabcjMzGTHjh3icyCFNAhZnw4CN3AlpAJed955Z/PYGhdz2L59uyg6KIXFYiE1NZWysjI8PDwICwur4QD1h729vZhBLioqIi4uTgwWrVu3zqbJFMHmbK6a5Pz8fD799FMmT55MQkJCvfcTkjXu7u71y85HRcGCT8CnHXz9IhT+xmUkd9zLyrj/yBFuSk7GYrGgUqmIjIykY8eOTe5iMHjwYDEZtGvXrmuOBXctoj6iXcLSWNxwkhsIk8kkRrGdnZ0JDQ2t9v/8/HzeeuutFm2bMn78eHbu3NksfRxNJhMpKSkYjUYmTpzIu+++Kxrw69evZ+LEiaxdu7bZsjpFRUUoFAoUCsW/qrZPalS3JG3fVoiPjxeFdbp3737FBNpYuLu78+yzz/L555+jUCiYNGkSn3zyyXUj7CZ1kqV0Yqjeh/1azCRfjuTkZKZNm8ayZct46qmnbE7BzsvLY/To0ezbt4+vv/6a/Px83n77bZvoLbQEpMGtf5OTrFQqcXJyQiaTNasA3f79+5k0aRLLli1Dr9ej0Wh4/vnnmT17Nmq1mqysrGYRPCwuLmblypU8/PDDLRq4/fjjj69wEtRqtdhFIicn54rA2w3UDykpKWKAwdvbmz59aleibgpWrVpFv3798PHxueJ/mZmZFBZaC5V9fHyaNAf4+/tTUVGByWTi5MmTzWqPCkmj5soknzhxolHijELQWSaT1V0eMeg2mDkbNqyD716Hi7WzIRUWC32Skzly5Ig4vqnVarp27UpYWFijFPAVCgX33HOP+PeqVTULvN1Ay+OGcFcjcPjwYXr16gVYo7jN4ZzWF23atKFPnz48/fTTzXYOX19f3njjDVxdXdHr9SQmJrJw4ULi4uKa7ZwCiouL0ev1qNVqfHx8rlkara0REhIirl+PmWSTycTevXu57bbb0Gq1jBo1ih9//LHRx3N1dWX06NEMGTKEv//+m5deeum6NAilTuTl1y919Gsyoq5VbN++nf379/PAAw+wYMECUbSvqawWmUyGs7Mzp06dIiEhoVmYMs0JaXCrbdu2rXglLQsfHx9kMhkWi6XZmR1Go5Gff/6ZvXv38uKLL9KtWzciIiJ44403WLhwIadOnWqW827YsIG7776bW265ha1btzbLOeqDDh06iM7IjSxy07B69WoxKz9+/Hj27t3bqOC/rKrjgnRPWVUXuMyyTLFk5e23375i37Nnz+Lg4ICjoyNt2rSppsvCEskb91a9rpFsq9JVVSqV+Pn5IZPJSE5Otrmy9OUQWD1Xq0lu7muoCdJuLHK5HASJnNhL75HlwgMPPMCoUaN49+3ZxMXFIcww6io/+aLcniMl/hSp7TH1l2GWydCaDLhfKCc1NRUHBwf8/PxQKBQEBgbi7u7OoUOHGtQb+pZbbhFb1u3fv/9G2cQ1hBuZ5EZAOhkJznJr4eGHH2b9+vU2aXNxOdRqNc899xxvvfWWOOAdPHiQOXPmtIiDLCA9PZ2ysjKxFdW/AdL7qiEUo2sJP/30k2hk3H333Y0Su3FycuKxxx5j8eLFeHh4MHnyZD788MPr0kGGqzvJBoNBpIi1a9fuuqrDLysrEynYUVFRfPHFF/Tt27dJx/Tz82PZsmVERkYSGhp6XTnIYA1uCZnMrl27tkqv6daAu7u7qNLeUsZxeno6//d//8eff/4pZq0ef/xx3nnnHbEVlC1hMplYsWIF48ePb9U5STpP3HCSm4ajR4+KPYEDAgK49dZbm+U833zzDW3atKnx+GazWUy62NnZiY5TQ6DVakWGQ0swrIRM8tXo1g1xGG0FaYCjxhpvhYKnn36afv368dprr11h05qBLQ6h/OLSgUOe/iQ6u5OkcyNZ60q8oxfBwcEEBwcTGBiIUqnE3t4eBwcHjEZjg2wdtVrN+PHjxb9vZJHrj5bok3zDSW4EsrOzSUpKAqzGrEB3amlER0cTHR3dLA+Vr68v8+bNY/DgwYBVsEzIEgUFBeHo6Gjzc9aGrKwstFotGo1GFGf5J8PFxYWoqCjA6khdrw5hZmamqECp1Wq5rxZlz5qgVqsZM2YMX331FYGBgbz22mu89957132EVSjPMJvNNSrR7tmzB7BmUXv37t2i12YLJCcn8/rrr7Ns2TImTpzI7Nmza+0CUBciIyPF9Wu91rwmmEwmkSao0+lqVGH+p0Gn0+Hs7IxOp2vREgiVSkVUVBR79uxh/vz5HDxo7enSqVMnFi5c2Cxz9I4dOygtLWXYsGE2P3Z94OzsLDpaFRUVLdqW6p+KZcuWievjxo1rknqxXLJkl1mXi0BqWRl3L1rEhAkTcHFxuWK/oqIinigu5g7gP/7+lAAlgKzs0sLTVcsZyVIFwVm1WCzVWjQ1F4RMslKprBYIbM4+yfWF4CgrFAr0ZVaRcdoBXV3hg1lERkYyffr0amw9u6plXW47DlT6k1usZVVBGcsy8oh0yCbKIZsgxwLG+VfyZDsZQ4DBFgv9ysroUVnKOCdNgwLcd911l2jX7t+/v9nYLzfQONxwkhsJqfJcTUIMLYGHH36YX375xWbqoQL8/f2ZNGmS2CZg/fr1PPfcc6xZswaDwYBcLic6OrrFerlWVlaKtR/NkRW41nDzzTeLkWDBabpesXLlSjGKfNddd9VprMpkMgYNGsTixYvp2bMns2bNYvbs2Zw7d64lLrdZERISIjqMp06dqrFOTNp/uF+/fi12bbbG9u3befrpp0lJSeHjjz/m4YcfbvB4IRUD27Vrl60vsUWwd+9ecf16/j3rC2F8NplMLVY7LpPJiI6Oxs7OTuztPXXqVJYuXYrJZMLT05NXX31VFDKyFSwWC8uXL2fs2LHNpvB+Ndx1110iw2vDhg1Nbrl4A1YtDSHA4uHh0WwBENP+/Rw+fJiXX365xixnxyrRpkxHR0wNrHsXbAeLxWJz0byaUFuv5Obok9wQqFQq8butlsnudgtMWQSFebz22ms1jlMODg4crxLJC8nL48iRI5w4cYKR5gTuMCcw1nSMifzNExxk3P793BUby91HjjAhbj+TYvfWu0TOxcWF0aNHA1aH/uuvv27ip/534YZw1zWM3bt3i+pznTt3ZuDAgS16/rCwMEJCQvjtt99setw77riDRYsWUVlZSWRkJNu3bxd701VWVhIfH4/FYkGtVreooywEAlqyP2VrQTox79y5sxWvpOnIzc3lu+++A6yT96uvvlprZrFLly58/PHH3H///SxZsoRXX31VpL/9EyAdI7Zt21bje86dOyeOKx07dryuKNeXo6ysTPwdO3bsyMKFC6tlh6+GDh06iPWBOTk5Yt/L6w2HDh0SKdf9+vX7x49fwucrLS1tkRZdcrmc8PBw8Tk5d+6cqFvx22+/8dVXX9GuXTvy8/OZN28ekyZNqpl62UgcPHiQ3NxcBgwYYLNj1gchISFiuxij0VhNnfkGmoZvv/1WXB8zZkyzBUA+++wzXFxceOihh674n0fVmGGRyShq4PnNZjNlZWUt1gGgtl7JrV2TLJ07i4qKwNUV+VtvwfBHYeVHsPKjWkt4PD09AbA3GBickFCr8JkCC84VFfgWFeFTXIxvWQl25vqLpI0bN078zjZs2HCFmOcNtD5uOMmNhNlsZvny5eLfzz77LH5+fi12/iFDhrBjxw6bDYQymYzx48fz1FNPodPpeOaZZzh79iwDBw5k+PDh4vsKCgrErJ6TkxPdunWrkTJkawiGpkajsamRc60hJiYGJycnUlJSiI2NvS5Fuy7Hzz//LFIB3dzcmDt3Lv3790elUqFWqwkNDWX27NlMmTKFP//8k2eeeaZaRvWfAJlMJhrSJpPpqp9P+J9MJms2ldWWxPnz55k6dSqbNm1izpw5PPbYY1cNrjk7OzNlyhQxI7Ju3bqWulSbQ6/Xs3nzZlJTUykoKGDIkCGtfUnNCqENSklJSbOfS6vV0rlzZ1EFOCsrq5qR2alTJx577DFOnTrF6NGj8fPzY8iQIbzwwgs2dXw2bNjQor+rvb09r732mlgLvWbNGi5evNhi5/+nIykpSQxOOzk5icGIpkBXtbj6XVpyyst5Ys4cbrnlFsaNGweAJcy6OHXVgxvgBpYuanTdweJxadHvtS6WskuLAJlMJpantQTqk0lujZpkFxcX7jKZmFRYSNktt6D+chFKfQmsmgRl+6ENWLRVi+rSUgLMqQr2+RcWojaZsPiBxQ+r+JewOFsXFy4tskLrUh8EBQWJ40Z5eTnff/+9DT/9DdgK/1xvowWwe/dusebS3t6eOXPmtIijbGdnx4ABA9i4caPNjjdt2jTGjh1LcnIyZWVlrFu3TnRM77jjjmqU8rS0NJKSksSMcqdOnQgJCWlW57WkpISKigrKysrQarXNdp7Wxl133YWzszNBQUGsX7++tS/HZvjwww/F4IqjoyOvvvoqP/30Exs2bOCPP/4gKSmJJ598kjVr1rTKhNrc6NChA17/3959h0dVZg8c/85MpmTSk0nvCaH33lVQQBGw4Iora11d1gUFfqgooqBgoShKsbKAurZVUFxFpIhKlw6hBggEEtIz6WXK74/JXDOShCQQAng+zzPPJJOZO3eSzJ173vO+5wQFERQUxN69e2sMIry9vfHx8aF9+/aEhoZy++23XxMFn+x2OytWrGD8+PG0bt26xqxySEgIU6ZMUabt7tmzh+XLl1/u3b2kvvvuO8LDwwkKCmLYsGHXxN+zOs6K1iUlJY3a+gkc/yedO3dWMtfp6ekcO/b7wsyePXvy6KOPotfrsVgsrFu3joyMDNLT07n++ut57bXXLll9i59//pnIyEiXjgSNxWg0Mn36dOU8IykpySXzKS6Njz/+WMke3nHHHY1XgyUri+eee46hQ4cyfPjw32+32/CzlhBoLURlr9+MDOcU68vVnqxqoqZqYN7Ua5L9/f3xa96cHv/3f6huvx3emgvz34DSCw/gGcvK8C8qwqMRi0U++OCDyt/oiy++uOTLJv8Myutxaag/R6ngRvTuu+/SokULIiMjCQwMZNasWbz00kuNuvi+rKyMyZMnX5J1mr6+vkydOpWEhATAsR75jTfe4KeffmL06NH06NGD6OhoRo8eja+vL++99x7gaG9iNptp2bIlBoOByMhIQkNDyczMJCMjQ+n3d6kUFxej1+uVnneXI1NxucXGxtKlSxfAURxu27ZtTbxHl05+fj7PPPMMU6ZMoX379oAj61RcXMy2bduu+bU4Q4cOxd/fn+joaFq0aIFOpzvvxKFNmzY8++yzeHl5UV5ejsFgIDQ0lKFDh7Jy5coatnx1OXv2LE899RS33XYbM2fOJCUlhW+//RY3NzdiY2O56aablJOr3Nxc5s6de1nW1TWm9PR0tm3bRs+ePfH39+f6669n3bp1Tb1bl5zRaFSC1sZYH2s0GgkODiYoKAi9Xg84ZmUcPXrUpUjYoEGD+Ne//oVKpSI5OZn09HRee+01WrRowaRJk1Cr1cTGxjJ37lymT5+uFOFsqJKSEp588slGn/VjMpl4/vnnlbXVRUVFzJo1q1F74P5ZnTt3jjVr1jBkyBDc3d256667+Pe//93g7TkXWVQ9knl0dVynBJ6B9S/w10kz4YMi2LwOy3UactMcAadmeOUGYn5/rG6q41q19vznqvr/oNVqG3098JW4Jjk+Pp5HH32UnvFxaD9biurLT8BgdaR7o6vc0bmyrUrNOw8PqAjUY8aDUIrwMIHK2Ta55vbJ9dKtWzflXC8zM/Oa+Xy/Fkkm+SKVlZUxZcoU5YPW29ubWbNm8cgjjzTqdJdLESBHRUUxd+5cJUAuLi5m+vTpynrJjz/+2OVk7tZbb+XJJ59UDn75+fns3LlTOUFxc3MjNDSUDh060KNHD1q0aEF0dDQmk+mi2zfZbDblYHytZpIffPBB5euvv/76sqzpu5xKSkp47rnneOaZZ9i+fTsRERGoVKrLVuCnqbRt25bevXtjMpmwWCx4eXkxYcIEl/sMHDiQl156SclYnDp1SgkOR40adU2tZXVmlV955RVuvfVWZs+ezb/+9S9uueUW5diSk5PDK6+8cskH25pK1Wz4vffee9lqOVxOzqnW8PvymIZQq9V4enpiMpmIjIwkISGBLl260LVrVyIjI5UAuaCgwOXzB+Duu+9m7NixSobm5MmTvPzyy1gsFhITE5kyZYqy5t/f35/XXnuNrl27NnhfnZKTkxvteK1WqxkxYgSLFi1SAmSz2cyzzz6rvBZx6X322WfKQObQoUMbt7NGahJ8OgNG/QO6X0ehVa/8SKep38yqqu+9qu/JxlI1k1xTkHy5MslGo5EHH3yQhQsXUlBQwM9zXiXoi/9APQeSAiocg3xnPH251EO0RqORxx57TPl+6dKlTVLY7FoghbuuEnl5eTzzzDMkJiYCjmkuw4YN4+23375i27h06NCBWbNmKQUKMjMzeeqpp85rI/H1118zb9485QSgX79+vPzyyy5VTA8dOsTOnTs5c+aMcjDU6/UEBwcTHR1Ns2bN6NSpE7169SI6OrrB04CcB/9rKWBw6tixIx07dgQcWeQffvihaXeoESUmJvLdd9+RlJSE1Wpl3759Tb1LjUalUvHoo48CjnZeJ06cwGaz0adPH2U9UvPmzXniiSeUQaRdu3bx17/+lcWLFwOO//dRo0Y1zQtoRCUlJRw8eJDTp08rxyGr1cqKFSsYM2bMVdsfvDqHDx9W2kGZTCbXqZXXCOdxuaSkpEEBo0qlwmQy0bt3bzp37kyrVq2Ijo4mNDRUOdm3Wq2kp6ezb98+du/erZyga7VaJk2a5NJvdMWKFbzxxhsuMxFSU1OZNGmS8r9lMBiYOnUqQ4cObfDrbkzNmjXj9ddf5+GHH1YCkIyMDJ566qmLzoCL2uXk5PC///0PcPx/Pfzww437hMn74e2ZMPpf5IU7UpxGTQX+hvq1cSotLVWyyZfjXKmm6dZVC3ddjiBw4MCBvP/++zRr1oz333+fr7/+mhanjuNWz+nqAPEljpaDhVod54yX9nd4//33KwMuO3fuvGo7N/xZyHTrS6S4uJjnnnuO4cOHc++996LT6fD39+eZZ57hwIEDfPPNN2zfvv2KmDo4fPhwHnroIWUN8bFjx5gxY0aNGb3169eTn5/P008/jV6vp0WLFsydO5cZM2YoGe2ioiJOnDjBiRMn8PX1JTAwEKPRiMFgUEYUNRoNAQEBeHp6KgMK9VFYWEhgYCBeXl7K+rdrgUql4qGHHlK+X7Zs2TW5LreqqqPy6enpTbgnjWvQoEFK9mfXrl188sknPP/888rPVq9ezSOPPKLcf9WqVbz77rvYbDY++ugj+vXrh06nY+jQoaxZs+aq7xNdlTNb7unpSUZGBtOmTeP48ePX7NqsJUuW0LVrV1QqFXfddRdr1qy5pl6rs5psQ7PI0dHR+Pv7o9VqsVqtqFQqSkpKsFgslJaWkp2dTXZ29nkBuJ+fH1OmTFFaFoLjd71ixYpqnyc/P58pU6YwYcIEpd3eP/7xD6Kiovjggw+uiKxOy5YtGT58OH369HFp6bNq1So+/PBDafd0mfz3v/9l4MCB+Pj40LdvX1avXn1x/ajzqnztU3mdXOU2815InYHP/LlEZX6Hx94fUDkbXPxeJxZ7NdOsqyosLMTHx+eyBMlXynRrs9nM3LlzOXfuHM2aNQMg5ngquZUxvJ+zXFDVhhl5zh2scltXiLSb0ZstlKncON7RhD3LsbxPdZFvu9atWyvdS0pLS1m0aNHFbVA0OgmSLyFnFmTjxo3885//VKZxtW3blrZt25Kens7KlStZv379RU1Hayg/Pz/Gjx9Pp06dlNu2bdvGnDlzaiyF77Rjxw6eeuoppk6dislkwmQy8eKLL7JgwQK2bt3qct+8vDylDQc4posZDAbi4+Px8/PD09MTvV5/wef8I+c2NRoNXl5e18wJ5g033KAEUseOHftTjCw6BwFsNts12/va09PTpb3He++9x+HDhzl+/Djx8fEkJCRw991306JFC8Cxzv+9995TgoCcnByWL1/OqFGj0Gg0TJkyhYkTJ14z6/ELCwtJS0sjLCyM0tJSdu/e3dS71KjOnDnDjz/+yODBgzEajdx99928//77Tb1bl4TzmAw0ePlEaGgoWq2WgoICDh8+TElJyQXX28bHxzNu3Dji4uIAx4nn3LlzL1jPoaKiglmzZpGWlsZdd90FOFrvtW3bljlz5jRJllar1dKzZ09uu+02ZQmUU3JyMgsWLLhqW6FdrYqKili6dClPPPEEAGPGjGHs2LGNug686NAhNnz1H3rdeT+6itOQVf8ZNc4gubYWgo899hiRkZHk5uZSWFhIYWEhRUVFynXVrysqKtBqtcrFzc0NrVaLh4cHffr0ITo6mlOnTp0XJPv5+REYGMjtt9/O2bNnKSsro7S0lNLSUvR6PUFBQQQGBhIYGEhQUBDp6enMnj3bZT+dz1VRUVFr8mDHjh2oVCrlvDsnJwefBnZ/0ajsxFpzOOwWxCG3QPqQzMWWQdNqtYwbN075/sMPP3RZKiLqzwLU5Z14MaUyJUhuBJmZmbz44ov06dOH0aNHK31hg4ODGTJkCPfffz+bNm1i9erVl60PbM+ePRk3bpxLlcbly5ezbNmyOmdkT548yYQJE5gyZQotW7akuLiYZ599lv/85z98/vnnNT7O2bfv8OHDyvRzLy+vegfJhYWFWCwW3Nzc8PPzuyaCZG9vb5e1yNd6ASunvXv3curUKaKioujWrZvSS/laodFomDx5snKS8ssvvyhTPNesWUN8fDxqtZqxY8cqQcUHH3xw3snXl19+Sbdu3YiPjyckJITJkyfzwgsvXDPFepxVkN3d3astZnat+eSTT7j++uvR6/UMHTqUDRs2uFRlvlr5+PgoGc+qA6R1VXXG0fHjx+s0ENSnTx8mTJhASUkJpaWlFBQU8NJLL5GcnFzn5/3oo49IS0tjzJgx6HQ6IiMjmTt3Lh999FGNmehLLSIigsGDBzNgwACKi4uVllbgyI599dVXfPvtt9fMe/5qs27dOgYNGkSrVq0IDw/ntttu46uvvmrQtlwykYfO/7k9GhL9g8k8eoItn37I6NvuxfzPA9iOHsW/Hs+Tm5tLeHg4BoMBLy+vaqvN//DDD0RHRysZZ09PT4KCgvDw8MDT0xMPDw/la2eQ+sdLSUkJdrtdmXL9xyC5qKgIrVZLQEAA0dHRGAwGDAYDer2eiooKpdDrsWPH2Lx5M0lJScDvRfoCAwMxGAyUlpaiVqtJTEystXJ+RESEMuX77Nmzv2ePARL+cA0wZ6nj+vQDv99WGce2Madz2DeIPNxJjvAjtjDX0fqpge6++24lFjhy5AjfffddwzcmLhsJkhvRpk2b2LRpE507d2b48OG0b9+egIAAdDodN9xwAzfccANnz55ly5YtbNu2rVEqYhsMBh555BFuuukm5bacnBzeeOONBk0bchYMuf/++5X+gffeey/R0dHMmzev1pNc50HV3d0dT09PsrKy6vXcdrudjIwMfH198fX1vSamno4bNw4fH8e8qy1btnDgwIEm3qPLIzc3V5lSGRcXxw033KAUjLsWPPLII0oVb7PZ7FIZdePGjYwZM0Y5KcnNzWXHjh3VZlLLy8uZMWMG8+bNU1pDPfzww0qV+auZRqPB19eXlJQUSkpKrvkAGRz/9//9738ZPXo0arWaiRMn8sQTT1z1r93f35/S0lJKSkpcpl/WlZeXF3a7HZVKVaf2UaNGjVJ6y+p0OrZu3crChQsbVOht7dq1HD58mEmTJhEXF4ebmxsPPvggXbt25fXXXyc7O7ve27yQiIgIevToQc+ePZWZJOD4PeTm5pKbm8vKlSv55ZdfrvmlN1eDd955h3nz5qFSqRg1ahQ///xzvc9f6qJCpea3gEgAfA9vw+37HAyTJ1M8fjzUIymQm5urZH+DgoKqfU85l8ddrHbt2hEfHw+cvya5vLycjIwM5syZU6dthYaG0qlTp/Nabmk0GrRaLe3bt2fXrl3VHmMMBgPR0Y7S1VlZWY7B54uonRtbnouvtYQ8jTu7A8IcQXIDxcXFceeddwKOWXRvvfXWNbNcsClVULdM8sWUVJTCXZfBrl27mDZtGv/6179Yu3atyyh5eHg4I0eOZPbs2Xz44YeMHTuWrl27XnT1U71ez7Bhw1i0aJFLgLx582bGjh17UetqLBYLixcvZsmSJcobvW/fvsyYMUOpPFqT3NxcbDYbvr6+DXruwsJCjEYj3t7eV32F2AEDBtCjRw/AsU7uz7Y+5cMPf19k9dBDD10zBdluvvlmbrnlFsDxXpk5cyY5OTnKz/Pz8ykqKsLT01MZef/ll1+q3RZAdnY2M2fOVE6Wb731VmX7V7PrrruO4OBgIiMjSU29RL01rgJfffWVkj0ODw/n/vvvb+I9ungBAQEYDIYGBcjw+3pms9l8waBw3LhxSoAMjkzfrFmzLqoS+pkzZ5g0aRJfffWV8pnWrl07Fi5cyH333dfgzysnlUpF69atefDBB3nnnXdYtGgR999/v0uAXFFRwYYNG5g5cybjx49n/fr1EiBfIU6ePKkU8dLr9fz9739vlOfZ4xuCwVKBGju9Ck/Dz99gPXIEw6RJ9Sp4arfbSU1Npbi4mKCgIKX+TGOoaU2ysxBlXYv4mUwmEhISlADZarVy7tw5Dh48yIkTJ7BarWg0GuLi4s57PSqViubNm6NWq7FarUpG+mKogE7FqdiBbJ07uVrDhR5SLYPBwNNPP41G45j0++WXX5KSknLR+ycuD8kkX0ZpaWl88MEHLFu2jN69ezNo0CDatm2rHPx8fX0ZNGgQgwYNoqysjH379nH8+HFOnTpFcnIyaWlptR5wnAeKnj17MmjQIJfRuNLSUt59991L2p9zxYoVnDlzhieffBKDwUDLli15+umnmTlzZo1Tw0pKSlCr1Q1uTeAc1VepVPj7+1+1RZ8CAwOVqscACxYsuGba3dTVrl272LRpE3369MHHx+eamErcoUMH/vGPfyjfL1iwoNoqzWlpaXTp0gWdTodKpbpgIbvDhw+zaNEiHn/8cQAlE/3FF19c2hdwmXh4eLgsM1i79gKVaK4hVquV119/nTfffBOdTsewYcPYtm3bVVvl3cPDQxkcbWjW1VmM8UJLcP72t78pg752u50lS5bw9ddfN+g5/8hisbBs2TJ27tzJxIkTMZlMGI1GRo4cyYgRI9iwYQMbN24kMTHxgpn/wMBAoqOjiYmJISYmho4dO9a4PjQ5OZk1a9bw008/XTP1Bq5F//nPf+jfvz8+Pj707t2bTp06XdI6ChqNhm2maEo0WlqVpxNMIWjBuOJNeP4Nbr/9dpdWcheSlZWlZFYDAgIabf1rTdWtnee19QmStVotxcXFHD9+nKysLJfH2mw2oqKiCAgIID4+XhloVKvVtGrVShnISk5OpuzOyvdn1enWrSuvHY0UyCz0wJw4kciIPPRVVz06v34G2ljOsetIOHkHjOwNCINT9c+8/+tf/yI0NBRw1JypbWmiuPJIkNwEKioq+Pnnn/n555/x9vame/fu9OjRg06dOill8/V6Pd26daNbt24uj0tJSSE1NRWbzaaMpjn7SjZv3pzCwkJMJpPL8/3222+8//77jdJT8bfffuPpp5/mlVdewWg00rVrV8aOHcubb75Z7f2dJwEajQaj0VjvKp0VFRUUFhbi6emJj4/PVRkkO9uVOPs9r1u37rziZ38WH3zwAe3atcPb25v27dvz+OOP88YbbzT1bjVInz59+L//+z/lfblixQrWr19f7X0zMjKUzHlBQUGdTmDWrl1LeHi4Mm1r9OjRBAUF8fbbb191Awt///vflWUGmzZtumoDxIY6e/YsS5cuVQbKJk6cyIQJE67KnuHOv6PNZmvQQJ9KpVIGTWuban3rrbcqRbbsdjuzZ89m48aNDdjj2h04cICxY8fywAMPcOONNyqFg2666Sauu+461Go1x48fJzs7G7vd7nIJDAwkJibGJVj4I7vdTmJiIlu3bmX79u3S6/gqUVxczL///W+lx/0//vEPxo4de8my/W5ubviVl3DSz59ROXt+/0FZKfz7Te7550ts3ry5zv8vRUVFFBQU4OXlRVRUVKMFyTVlkuvL09OTiooKzGYzGRkZ5/08MzMTPz8/PDw8CA0NxWazkZubS2RkpHIMSk9P5+zZs7U+z+FMEzvPRJCa7w2nISzETFh+Adc3O8Efk/XublaivXPZRyj7/UJQq+vXD33gwIFcd911gOP/Z9asWVfdZ/WVrBwp3HXNy8/PZ+3ataxduxadTkfHjh3p0aMH3bt3V974Tlqtlri4OKWSZ3XS0tIwmUxYrVZ++eUXvvrqK06fPt2or+HkyZPMmDGDF198ETc3NwYOHEhubq7LdFqngoICJcD38/NrUCuLnJwcVCpVrSciV7LHH3+cVq1aAY7R3mulwm1DZGdn89JLLzFz5kxlrf65c+f49NNPm3rX6mX48OEuU/C2bdvG0qVLa7y/r6+vMtJen1oEy5Ytw2w2Ky3DBg0aREBAAK+99prLiP6V7M4772TgwIGAIwvxwQcfNPEeNY3//e9/9OjRgw4dOuDv78/zzz/P5MmT613QsKl5eHhQVFREaWlpg/oje3t7K1MRawqy+/Xr59Iq7d13322UANmpuLiYRYsW8emnnzJixAhuvvlm3N3dSUtLIzo62mWadF2Ulpaya9cutm7dyo4dOyRjfJX66aefGDx4MK1btyYsLIw77rijXrN5qv7V/7i4yGKxkKt2J7iogD36MMJL8n9fD3n8MHeuW8ed990Hs2bVeZ3k6dOnadOmDR4eHoSEhDTKgEzVz52LCZLT09OJjY3F09MTNze3agcfkpKSlCJj4eHhBAYGKomlKeo0bjIcQ9UBaFb5gCqnEfZk2KKOYpNvjHKb1azibJIPqRofvNLK6OpTJcCuLODVyZjKy61DATcCAwPrnJiJiIhgzJgxyvcLFiy4KpM6f3YSJF9BysvL2b59O9u3bwcgJCREmbLlvA4PD69xbUpOTg6HDh3i22+/5bfffrus03cPHDjA7NmzmTx5MiqVipEjR5KXl8fKlStd7mez2Th37hy+vr6EhIRccNSvOgUFBURFRQGOiuFX04Hn7rvvVkYWy8rKmDlz5p++5+WRI0eYO3eu8r9zzz33YDab+f7775t61+rk4YcfVorYgaN69cKFC2stzFF1uUF913F+/fXXZGVlMXHiRNzc3OjSpQtz5sxh3rx5l2QtVmPq16+fyxrc+fPnN0phpKvFnDlzmDt3LkFBQcTHx/N///d/vPzyy029W3Xm6elJSEgIKpWqwX/HkJAQysrKKC4urjZ47NChAxMmTFA+9z7//PPLdmzIzc1l6dKlfPbZZ3Tq1In4+Hjc3NyUKrXVycjIUJZIJScnc+rUKc6ePSsZpGvE22+/zZtvvolarWbUqFFs27btkhQRtVqtdM1IYXtQJIe9ggirKKBLUZXzo6VLYdEiGDgQ1q1TCpiWlJSQkZFR7edNdnY2ZrMZHx8fYmNjyczMrPP/odFoxN3dHZvNRkFBQY0Z80sZJIeEhODu7k5ISAhnzpw57z42m429e/fSokULZXq22WwmOzubmwLO1NimyQ6sV8ezS+143/pri+npnUKAWyHrchNItXjzc04c4QYzobgeg4KKi8jPz8fb27vO55tarZannnpKWYayevXqRh3U+7OyVF4u5GJKpEmQfAU7d+4c586dc+n56Ow95zwgOqd5VVRUNHlLpC1btvD222/z2GOPAY4plbm5uef1/c3LyyMszLFYxNvbu977nZ2drRy04uPjMZvNV0UWrX///tx7772A4+82Z84cjh8/3sR7dWXYsmUL//73v3n44YcBx5pbPz+/K7o1lMlkYty4cS59xz/99NM6ZcGdQXLVZRP1sXHjRnJycnjuuefw9PQkKiqKuXPnsnLlSj7++OMrMhvZpk0bZaoiOAq3/Rl6gtfGbDYzffp0Zs+ejdFopGfPnjzwwAO1zkK4Umg0Glq0aIFKpaKioqLak9oLcXNzZGfUanW1Uyzj4uKYMmWKUgToxx9/bJJjQmlpKVu2bGHLli18/PHHeHh4KAGB8/3rrMzd0OJl4upw6tQpli9fzsiRI3Fzc2PixIlMnDjxkgyC9Mg4w2kvP055+bHJK5p2xWnonLV5S0vhnXewT5hAn8pew87PkbCwMI4cOVLtgPvx48fp1KkTWq2W6OjoC1a01ul0xMXFERQUBDgG8/V6PRkZGSQlJZ0XLFutVqU158XM7isvL6eoqKjWINn5fAcPHsRoNKJSqSgqKgJAFVDzttcGNmOP2nHOGaE3c3vgAQxqx99rROBBlqV3odimZUteNHdwfn2Q9PR0vL298fX1Ra/XX/Dz9dFHHyUmJgZwZPP/zLMFr3ZS3foqU1FRQUZGBpmZmWRmZpKVlaUEjVeCH374gc8++0z5fsKECcTGxrrcJzs7Wyl8EhER0aDnOXr0KDabDTc3N1q1anXFV7ru3r0748ePV75fsmSJy+CHgG+++Yb//ve/yvd33303Y8aMUU6QryRDhgxh0aJFSoBss9mYP39+nQJkZ+sjcEyxc04Xq6+DBw/y5JNPcvLkScBxkj5ixAgWLlxI586dG7TNxtKuXTumTp2q/C1Xr17Nl19+2cR7dWVISUnh1VdfVaYq33HHHcra2yuVSqUiISFBOUk/duxYg9ZmhoaGolarlWq8VXl6ejJ16lQlGN22bdsV0wGgqKiI7OxssrOzlc/ijIwMCZD/JD755BMlexwbG8s999xTp8d53Pj7xd7McSnk94sqAfrpksELyrzdyGrpAR2ADqCKBtK3c8R8jjvuuAMPDw/lPMrLy4vOnTu79Nh2KiwsVAagIiIilOC3OgaDgc6dO7vcx3lcCgoKonXr1tU+rro+yQ2Rk5ODWq2mrKzsgoPHxcXFSoAMQHKVS0Xl5e+w7+4Q9rQPAw3EueUw8tH9GO6ywp3AfeD5YDndw1LADTLsnuR9qYMfHD2tnZfMzEyX30Ntbr31VgYPHgw4Av/XXnvtqm/xd6WqqMeloSRIFpfcJ598wurVqwFHpmDSpEkugYDdblemWZtMpga1/ikuLubIkSOUlZVhMBho06ZNo7Y5uBj9+vXj2WefdQkQLlVF1mvNRx99xHvvvYfdbufcuXPcfPPNvPLKK/j5+TX1rgGOqaEzZ87kscceU04IsrOzmTZtGmvWrKnTNqoW6CsoKFAKuDXE2bNnmThxIsuWLVM+iIOCgpg2bRpTp06lTZs2Dd72pdKvXz+mT5+uvM6dO3fy9ttvN/FeXVn27Nnj8jv529/+xt/+9rcm3KPaNWvWDJPJRGlpKSkpKQ3qGevm5kZkpKMnbFZW1nnZmbFjxxIQ4EgPHTp0iFmzZjVozbMQl5rFYuH1119Xsse33347LVu2vCTbDrQUoq6cIJptd+0Ckuzhx69bttKlSxcKCgrYunUrR44cwWq1olaradGihfKequr48eNKlrl58+bn1bsBR7HYNm3aoNPpsNvtnDp1ii1btrBv3z5l6V5N52qXKkjWaDQX1SL0j1JLvVib5VigHKwqZIT6IFq3848hbX3P4asrIa/MwPrfmnHirB8+Pj74+vri4+ODwWAgLy8PqD1I7ty5s0vthAULFki7p6vclZeiEdeEd999l4SEBOLi4oiMjOTBBx/k3XffVX5+9uxZIiIi0Gq1xMbGsn///no/R2ZmJjqdjvj4eLRaLc2bN6+23U5TuvHGGxk3bpyynm7Dhg0SIFzA//73PzIzM3nsscdQqVS0aNGCBQsW8J///IfVq1c3ydq+4OBg7rzzTqXardPq1atZsmRJvdaV9+vXD5vNRnl5OTk5OTRv3rxBld6drFYrX331FZs2bWLs2LG0b98eQKmOf+zYMVasWMHmzZsva5ARFRXFX//6V7p166b8zrZv3y7BTg1Wr16N0WhUWmPdddddGAyGK26qXnh4uNLSJD8/X5nJUF+RkZG4ubkpJ+RVDRw4kN69ewOOTNhrr71GRcXF5AOEuLROnjzJp59+yqBBgzAYDDz55JM88cQT1a6rV26pOuGtslyLx9wqt3mAG3Z8PUvIKTGSHW4EZ5wcBttLIzFb0/A+k8SOAS3R7N5Neno6eXl5tGvXDqPRyJjYWNrq9fRJSsLZ58RisXDgwAFl2nXbtm2VtfJ2ux2dTkf79u3RaDRUVFRw7Ngxl4Gv/Px8fHx8aqyz4ZxBcbHFVP39/bHZbOTl5dX7M0JVpQSP/W0o1Or45qY2WFHjTgW3kYibzQarqjyo8iPX/UYLYeoCsk8b+W11JMdXmWjZskxZUwyOpY4Wi6XG/YqIiOCpp55SzvW++OILNmzYUK/XIK48V2bqTVz1LBYLc+bMUbJbQ4cOpWvXrsrPbTabcmLk5+dX7chmXZw9e5a0tDTAMcJ3pWQcAW677TYef/xx5aD5ww8/8Prrr0uAUAfbtm1j+vTpyge1l5cXY8aMYf78+S7/R40tKiqKiRMn8t577zFkyBAl2MvIyGDq1KksXLiwXsGtXq+nV69egGOdk9lsVopvXaxz587x3HPP8eabb7qc4CQkJPDUU0/x/vvv8+STT9a7Mm99GI1GBgwYwAsvvMD8+fPp3bs3KpWK5ORkVq9ezcsvvyxTz2qxYsUKl0G0YcOG8cQTT1wxSw70er2yfCY/P5+jR482aDtarVYpfpWRkeHyHgoNDXXpNT5//nxycnIuYq+FaBxffvklaWlpeHt7ExgYyMSJEy/Jdg1ujqULFdbfT9HTrF6ctvoC4PHDZ6ivH6rMSCorK2PPnj3KsrsDYWH82qyZy+y60tJSDhw4gNVqRaPREBcXR9euXWnRogVdu3bF3d0drVZLUlLSeTND/P39AWpsUXcpMsm+vr5KvZ2GFHStyoaKlXGtKUSHGjvDOYg3ta8j7t/qBKN678HfVv2SieLiYux2O15eXufNWvT09OT5559XZks5axeIxnU5pltfGZ+84pp05swZFi9ezD//+U8A/vKXv5CUlKRMW0lLSyMiIgKDwUBsbCx79uxp0PMkJSXh4+OD0WgkODi4yXuNGgwGHn/8cfr27avc9s0337B48eIm3Kurz4kTJxg/fjyPPvoo/fv3Bxyjtc8//zz79u1j5cqV7N69+5JnmHx8fOjZsye9e/d2KcoFjhHz7777js8//7xBxbEeeeQR5URi3bp1ynTogQMHXrIiVuvWrWPDhg307duX22+/nbi4ODQaDX379uWWW25h4MCBnDt3jh07dvDbb7+xZ8+eiyr05eHhQbdu3ejbty+dO3c+L6ArKChg6dKl7Nq162Jf2p/CqlWrKCsr44knnkClUjFw4ECioqJ49dVXG63XaV0FBQWhVqux2WwcPHiwwQN+0dHRynaSk5OV2zUaDQ888ICSwfnxxx/ZsmXLpdh1IS45m83GG2+8wVtvvYW3tzddu3bl7rvv5vPPP7+o7TobmNjsv9dr3l7hmEbtoSonbudGGDyMgQMHsmqVIzVqsVjYt28fT7ZqhdlgIDEsjHYeHiQmJir1AgoKCti5cyfx8fEEBAQo1avd3Nyw2WwkJSWdd4zx8vJSag/UtKzCmUlWqVTodLoGDYQ6s9Bqtfqiz+G2hEVx1tMbgOs4QRQX7vTi5V6OUV/B2ILN2IEpu1SoVI6LRqPB3d1dmXZd9bin0Wh49tlnCQkJARznLa+//vpF7b+4ckiQLBrVqlWraN++PVFRUbRs2ZInnniC6dOnAyjT7Fq0aIG3tzf+/v4NyhjY7XZSUlKIjY0lMDCQ06dPN1lbpcjISJ599lmXFiF1rXgszpefn8+cOXNYuXIlDz/8sNJfun379rRv357S0lK2b9/Opk2b2LlzZ4M+nDUaDWFhYXTp0oWhQ4cyePBg0tLSXFo9FBQU8M033/Ddd9+5Fguphz59+jBo0CDAMfK/cOFCXnzxRUwmE507d6ZTp07s3r27Qdv+I6vVys8//8zPP//Mddddx2uvvYa3t+OkwWKx4O/vz6BBgxg0aBB2u53MzExSU1NdLkVFRcosCOe1MwMYGRlJREQEkZGRNc7eyMrKYuXKlXz//feSPa6n9evXU1ZWxsSJE9FqtSQkJDBv3jzmzp3bZIMNKpWKqKgopXhkQ/+mBoNBOaFMS0tzGaC555576NWrFxkZGeTl5V1xU82F+KOcnBzmzJnD9OnTUalU3HvvveTn5yvBK/zeE9m+tsoDP6y8frzKbXmOK/VGG7iBTauGYii2aDlW7lif30V9FrcONjj9Ld/fczOkrqryWBvWgwdZGx9PoYcHPj4+dOzYkf379yvvs9LSUhITEwkICCAwMBCLxUJpaSnJycnVfrZFRERQUVFBcXFxjW3e/tgGqiHHBucyqvLycrRabYMHv729vfnFFIXdAq3SsumSXpmVdp6SVf0bPF953dORGdYA7tsrs/h/ePqazikff/xx2rZtCzgy7S+99NIV2V3iWlRO3VpAXczcTQmSRaN7++23WbBgAYASiHz33XeAY8ppZGQkRqOR2NhYcnNza+0vW5PMzEwSEhJQqVQEBAQ0SZB844038o9//EPJghQXF/PGG29IFetL4OjRozz99NP07t2bBx54QDnJNhgM9O/fn/79+1NRUUFaWhppaWlKoJeeno7dbkej0aDRaHBzc8PNzY2wsDCioqKIiooiPDxcyX7qdDq0Wi1RUVEEBASwd+9eli5dyo8//nhRH3zXXXcdTzzxhPL9O++8w5kzZ/jwww+VKXpPPPEEkyZNalARpJpcf/31jBkzRgk6PD09lT6Tzql6KpWKoKAggoKC6Nix40U9X05ODhs3bmTjxo1XXH2Aq82mTZtITU3lmWeeISQkBC8vL1544QX++9//8tlnnzWomvTF8PHxUd5HF9ObPiYmBrVajdVq5fTp08rtbdq0Uap6BwQE8Oqrr8rJprgq7Nmzhw8//FDpAf/Pf/6TsrIy1q9f36DteerK8XMvRquxghWOFwVgr+wC3EZV+d5L2Q+9/gVuWrD8HtGp7XZuSkrCq7yc/8XEYDQa6dSpE/v373cJgp3V2Wuj0WgwmUyoVKpaz82qBsnu7u4N6raSk5NDRUUFer0ef3//Bh1jNBoNMTEx2FUqjOXlDC44UmPv5EthzJgx3HDDDYAjuJ8xY0aD+8WLK5MEyaLR5efnM2/ePKZNmwbAQw89xL59+5SqfydPnqRNmzZ4eHgQFRV1XhGXunAWe/D398fX1/eyVhSMiorin//8p0sl4ZMnT/LKK69w7ty5y7YffwabN29m27ZtdOjQgb59+9KzZ0+l4qYzuI2Kimrw9p2j6rm5ueTm5qLVaunfvz+ZmZls3bq13tsLCQnh/vvvp0+fPsptGzZsYN26dcrXgwcPpk2bNvj7+/Piiy8yY8aM89rh1Fd4eDh/+9vflOJH4OjXOG3aNFJTU9HpdLRr145u3bqRkJBAWFiYMqWuPsxmMykpKZw8eZJNmzZx8ODBi9pv4erkyZOMHz+eCRMm0KNHD1QqFX/5y1/o27cvb7/9Nnv37r1s++KcMVBeXl5tcaK6CAgIUKrDnj17VskWGY1GJk6cqMxY+Pjjj0lKSroEey3E5fHVV1/h4eHByJEjAcegZ1lZGZs2bVLuo6qSnbS9Wnlb1WJeIxxXZT5u5BYZCfYpAgMcKwiAYgiz5OOZX165yDIdbiuChHg4dRgq41+VD6iA3ubTHDlSRvPmzdHpdHTs2JHDhw/XK4jz9fVV3pPV9TF3qjqY5UwSOKckazSaOj2XxWKhoqICrVbboM8iG7CqWTMSfX0JCC/iBo5j9KkykOhctVHlI6q8Mgmve7VKrtHZzeud2p/vvvvu45ZbbnE8t83G7NmzOXbsWL33W1zZJEgWl8WuXbtYuXIlw4cPR6vV8uSTT/Lkk09SVlamjGj6+fkRGBiI2WxW1i3Xh9lsxt/fHy8vr0v/Aqqh1+u55557GDFihMsHwZo1a3jnnXekGmsjsVqt7Nq1i127drFw4ULatWtH3759adWqFaGhofUqcmSxWEhNTeX06dMkJSWxdetW/Pz8GDt2rDJlvkWLFjz77LPk5ORw4sQJkpOTOXnyJCkpKZSVlWGz2bDZbGg0Gvz8/AgICCAyMpJu3brRrFkzl+f74YcfeOcd10/fV155hdmzZxMaGkpERATz5s3jww8/ZM2aNfXKpGm1Wtq3b8/AgQPp06ePcnID8NNPP/Huu+8qMyzKy8vZuXMnO3fuVO7j5eVFWFgYYWFhhIaGKic7zuyB3W7HZrORnp5OSkoKKSkpDQ6WRN0VFxczc+ZM7rjjDu677z7UajVhYWG89NJLbNy4kQ8++OCyFLZyHled7WDqS6/XExMTg8Vioby83CWLPHbsWAIDAwE4cOAAy5cvv/gdFuIy+/DDD9Hr9QwbNgyVSsWkSZMoKytjx44d9dqOWu045tpsKsosGpLNjgGqhPI/zDI6fQSimjuC5Gqkp6dTXl5O69at0Wg0tGnThuTkZJf3Xm2cS3TKyspcssV/9Mfp1lVvq886Zednd0POnTbExZFY2Sc6llxinXPXG8HIkSOVwRCAefPmyYzBJmDh4opy1YUEyeKyWbZsGR06dCA6OpqYmBiefPJJZs6cid1u5+jRo7Ru3RofHx9atWrFtm3b6l0UpqCgAHAcaC+mpc6FGAwGBg8ezO23365UfQTH+rp33nnnkq0rFRdmtVrZs2ePUvRNpVJhMpmUYM9kMmG327FYLFitVqxWKxaLhezsbE6dOkVaWtp5LaVSU1MZO3Ys/fr144477iAmJgZwVPj09/e/YHXtM2fO0Lx5c+Lj4zl69ChlZWWYzWaWLVvG2rVrz7t/fn4+zz//PNOmTSM8PByDwcCjjz7Kvffey6+//sqRI0dISkpSpqOp1Wq0Wi3BwcGEhIQQGhpKfHw8nTp1cmlZAY73xKJFi1yyGTUpKCjgyJEjHDly5IL3FZff8uXL2blzJ4899piyNr9v37507dqV77//nm+++abRihaqVColSHYeZ+urZcuWeHh4UFZWxqFDh5Tj+1//+lelyGFRURGvv/56g5bcCHEleP/99zEYDNx0001oNBqeeeYZpk2bVq82lxq1471htalINvthsalRUU2QnHIUIhJq3VZubi67d++mTZs2uLu7ExMTg4eHB0eOHLngOZbNZqOoqKjWABmqzyQ7i3mBYwr2hYJklUqFVutIq9dnTbNaraZ58+bsqJyhEpqfT7/w5Do/vr5uueUW7rvvPuX7t99+W1o9XcMkSBaXTUVFBa+99hqzZ8/Gw8OD7t2788gjj/Dee+9RUVHBiRMn6NSpE1arFZPJVOv0nuoUFBRgt9uVE7pLHSR7e3szbNgwhg4dqkzxdb6uL774guXLl0v2uIk5i1BlZmZe1FRUq9XKhg0b2LBhA126dGH48OE0b968TtPAjEYjLVu2RKPRKH1u//e//9V6opGens748eN55JFHlOJeHh4eDBkyhCFDhij3y8zMVDJutTGbzSxfvpxVq1Zd8ARHXD1OnTrF008/zYABA3jooYfw9vbGYDBwxx13MHz4cNavX8/y5csverr+HxmNRmW2TEPWG3p6eqLVapUii861kQMGDGDUqFGA4707b968S7omX4imsGDBAvR6Pf3790er1TJ16lSef/55lzoNziZC9g+rPLCD40obMgWyjlPuGczR4EQM1lLCMrbg5155LHdOGS7Ig+iWlQ+qvC3s983ZnfHzwWJKjuzm22atWOjph8lkws3NjWPHjtX6+aDT6fDw8LhgMF1dkFz1/Mvd3f2CM1AMBoMy+6muM6gCAwOJj49Hp9PxPxzrmg8ePMjowsr9rfpRWVm0W1XdKdrkOj0dAwYMYMyYMcr3S5cudSnQJi6vi23vVBcSJIvL6syZM7zyyitMnz4djUbDrbfeyrlz51i5ciUFBQVkZWVhMpmIiooiMzOzXhkFq9VKcXExHh4eeHt7X1RxGSeVSkX79u25/vrr6devn1LsyGnLli0sWbJE1h5fw6pOSzaZTMTExBAbG0toaKhSyEilUmG328nNzSUnJ4fQ0FDsdjslJSV88803dRo8KSsrY8GCBXz//fcMHTqU6667joCAAKKiorDb7aSnp9faP9JsNvPbb7+xfft2du7cKQM217D169ezfft27r33XgYNGoRWq8XNzY1BgwZx00038dtvv/HTTz+xffv2S/J/4Jx2abfbGzTFPiIiAqPRSElJidLXvn379owbN065z+LFi2XKorgm2O123njjDfR6PT169MBgMDBt2jSmTZtWp4KGHh6OdkgFBUWkp5dRXm4nhGredxVloNWff3s13C0WRh4+wDMhsfj5+eHn50fnzp05dOhQjTNQnINZzkGumo4lVQPt6jLJzv7BtTGZTIAje32h2SoeHh4kJCTg5uamnJOlpaWRlJR03jmjDRXJOl/y/N3J0RuJ1JRRXFxMbm5uvWYr3nTTTYwdO1b53pkYEdc2CZLFZbdv3z7mz5/P+PHjAXj44YfJyMhg69atpKenYzKZMBqNhISEKCdUdZWfn68EyfWl1+vx8fHB19cXX19fOnToQMuWLUlIcJ3O5MwyfvXVV5w5c6bezyOuXllZWWRlZV1wjVlkZCQ33ngjGo2G+Pj4elV6PnHiBPPnz2fx4sWMHDmSsWPHYjQaOXXqFIcPHyY9PR2r1UpWVhZpaWmcO3eOtLQ0Tp8+LdNU/0QKCwt59913+fzzzxk+fDi33HILRqMRlUpF9+7d6d69O8ePH+f06dP89ttvZGVlkZ+fT15eXr1n2TiPp4WFhfVeBuPp6akU68rIyMButxMVFcWzzz6rZKe//fZbVq5cWa/tCnEls1qtzJo1i6lTp9KxY0eMRiMzZsxg7ty5Lr2/VVXqlNrfclx7vD4b8Cc9XY1O1w+VSkVCt8/AvfKOzqzx/XtBexZex9EPB35vLQXgW3ldOalKjZ0TJ04QHBysBJlt27bl2LFj1Q705+TkYLfbKS8vJzw83KWneVVVM7/ONcl/nG59Id7e3pSXl5Ofn3/eEqiqTCYTLVu2RK125OKzs7M5ffq0S2Ctqqz5pz6hpmvXrhjsBor0RXh4eBAb6/hZRUUFp06dqtOsm2HDhvHII48o33/77bd8/PHHF3ycqN7kyZO54447aNmyJSUlJWzevJmnn36ao0ePNvWunUeCZNEk1q9fT0hICKNGjVIKXMyZM4etW7eSm5uLTqcjMjKSzMzMGludJCQk0KdPH0wmE76+vkrfP29vbywWi8t0bZVKRXZ2ttLOoOrtKpUKvV5/XpYYHKOaZWVl6PV6iouLWbNmDV9//bWU+Re1Onr0KDfeeCMAsbGxDWqHVFxczIkTJ5STl88++0wCCXGevLw8PvzwQ7788kuGDBnCsGHDCAhw9FQNCAggPj5eaVPiZLFYKCkpwW63uwys2O12UlNTCQ0NVb4HR2Vrg8FAaWkpGRkZZGdnk5eXR25uLjt37qx10KhZs2YUFRWhVqtJSUkhLi6O5557Tskubdu2jQ8++OCS/k6EuBJUVFQwc+ZMpkyZQseOHdHpdEyePJnFixfXeiwPDHREvKWlaioqiggLCyPIVk0m2ZrruNRTeno6RUVFtGnTBr1eT0JCAlarlczMTJf7lZaWcubMGSIjI4mMjOTcuXPVTs+uLpNcdSDuQplkd3d35Zj1x32oymQy0bp1a8BxDDt+/HitMwYDAwOVoF2lUlFYWIhOp1NaPTZr1gy1Wl1rsuP222/ngQceUL5fsWIFS5YsqfX1iNpdd911LFy4kN9++w03NzdefvllfvzxR1q3bl2vAVyZbi2uaZ988gnBwcHccMMN6HQ6nn32Wb777ju+/PJLWrdujUqlIjIykpMnTyqPiYiIYMiQIXTp0oX27dsrt1utViUrYbPZlErXVZWVleHr61uvfbTZbPz000/s3bv3kk1dFNe+qtXZ6zLVrCZVB3Tqm8ETfy7FxcUsX76cFStW0K5dO3r06MGAAQOqva+bm1uNXQDMZrPS7slJrVaj1+vx9PTEZDJhsViUSrT33XcfJ06cYNeuXaxevdqlDZjJZFKy0EePHuW2225j9OjRymOPHTvGnDlzZAaEuGaVlZUxffp0xo0bx4ABA1CpVPz9738nMDCQxYsXV/uYyMhSYmOL2bjRn4AAN1q2bInq0KXdr8LCQnbv3k3Hjh0xGAy0bNkSq9V6XqX8lJQUoqKisFgseHh4VBskV5dJrprZ/ePx5I+qTrWuLQHhfH6NRsOePXtcstXVqVqdu+pAnqenJ126dFG6U9Tk4YcfZsSIEaSkpBAZGcmnn37Kp59+Wutzigu7+eabXb5/4IEHyMzMpEuXLvz6669NtFfVkyBZNKm33noLrVZL3759KSsrY8CAAfTp00fpo+zt7U1oaCjdu3enW7duREdHA7isi3O2prFarVRUVGA2m10O0M4TsLy8PGWKTtUMit1up6Kigry8PPLz8zGbzZjNZlJTU9mxY0ejVckW167qRtYbwvn/CkggIerEbrezb98+9u3bx5IlS+jYsSOxsbH4+PgoF29vb9zd3ZVBGOeMGnAEyRkZGS63geOY6+Pjo5wEO4skguOk84477mDkyJGkp6eza9cupUOBr68vkZGR3H333URGRpKXl4evry/Hjh3jpZdeqlebMyGuRlarlXnz5pGRkaEUqhsxYgSBgYHMnTv398H3ytpWqscO0saSyZmy5oy8dw7enjNgZ5UNOsddi6rclld5XTURW7nZaotV4agivW/fPiXL7ewsUnX2njOIVKvVLp9HVVVXuKvq9O2QkJDqd6CS85hyoeUc/v7+GAwGMjIyLhggV92vqscxcGSY7XY7Op2u2paRGo2Gxx9/XJmBExkZyaJFi/jhhx8u+Jyi/nx8fADq3cqwgt9XGTQWCZJFk3Ku29m9ezcDBw6kdevWuLu7M2DAAKVYhM1mc8lc2O12tFotv/76K1u2bOHQoUNKcFuXA6cQja3qwMrF9O2uuparpmUHQtTEYrGwY8eOevdprY1Op1OC7ejoaAYOHEjHjh2VnwcHBzNo0CBuvvlm3NzclB6rzoGjoqIi1q5dy3/+859a1x4Kca355JNPyMjIYOzYsajVanr37o2fnx8zZsw4r1hVS00m4e5mvIPrFwZkq4wcUwfgby8hxJ6Pt6r2x5eWlrJ//346d+4MOALRqkvVgoKCsNvtqNVqpZDXH5WVlZGSkqIkKsDRSjElJQWVSqVMpa6J1WqtU6up/Px8vLy88PHxUYpl1qakpISysjK0Wi1qtRqbzUZcXBwRERHK9v5YDFOn0/H000/TrVs3wHG++dZbb7Fu3bpan0s0jEqlYt68eWzcuJHExMSm3p3zSJAsrghr1qxhz549PPzww/Tq1QuLxaJUB9br9djtdkpLSzl+/Di//PIL69evv+RtToS4VKqOonfu3Jno6GiKi4uVQRxnVWznRa1WK1+7ubnh6+tLYGAgo0ePRqfTUV5eTkpKSlO9HCEU5eXlSpu1pKQk1q1bh4+PD/3792fAgAG0adMGrVaLRqOhpKQElUql9D09dOgQixcvviILtAhxOaxdu5acnBwmT56MwWCgVatWzJ49mxdeeAHCKtfX3gIqwJty+FvlA2+qspFuldcDq/R7OpTK7mOhrKtohp3KzGmynU5nz6JWJ9eaoS0qKiI7O5uAgABCQ0PPC5KLioooLy+vcVad1WolMjISQGm9mJGRQVBQEHq9Xul/XBO9Xo+Hh8cFl7Pl5OQQHh6OXq8nODj4gl1FSktLlcy2n58fYWFhytRvs9nM/v37XX4vnp6eTJ06VelDX1FRwaxZs6TqfiNauHAhbdu2pW/fvvV+bN4zz9Spp3Z19YbqSoJkccXIzMzk1Vdfxc/Pj4EDBxIZGYlKpcJqtbJ//352795dY6sCIa4k+fn5FBU5qmn27NmT+fPnN2g7vr6+ZGVlYbPZOH78+CXeSyEuDbPZzLfffsu3336L0WikQ4cOSkVfq9VKXl4e69atk4EeIYBdu3YxefJkXnjhBSV4mzNnDvz6MqQ0bPHx2SwvtiRGYbRWUKRxBAU2lYodERG09/bmzJkztfYgr6ioQKVSuUyp9vPzU+q41FTZGlzrZVRd0nbixAlatWpFcHAwnp6eNbaPKywsJDAwEF9fX+Lj48nJyaGwsPC8oDk3Nxez2YyPjw9xcXHk5+fXuhyu6uNbt26tDFLn5uaSmJjost8xMTE899xzSiX+kpISXnrpJQ4cOFDj9sXFmT9/Prfeeiv9+/evtb1lU5IgWVxxcnNz+fLLL5t6N4S4KD/++CN+fn5cf/31Dd5GXl4eixcv5sSJE7J2U1wViouL2bJli0ubGyGEqxMnTjBp0iSmTZtGZGSkY13mA6/A+o+Ar+q9vaMpgRSV6rFqVDx2egtq4OfyGFK9vfH29qZ169bk5+eTnp5ebdcQ57Kgqpk5rVZLYWEhBoOh1oJa1QXJAElJSUpWNj4+Xsky/1FWVhYRERFotVrCw8MJDw9XZg+WlJSQmZmptI9LSkqiU6dOSvuqQ4cOVdtXWafTKVX6PT09KSkpwdvbmwMHDrhkygH69OnD+PHjlaxzXl4eL7zwgkvRWHFpzZ8/n9tvv53rr7++1gGYpiZBshBCNIIlS5bg5uZGXl4eRqMRo9GIu7u7UmTOarXW+HV+fr4ypTU5ORmz2dzUL0cIIcQllJmZyVNPPcUzzzxD+/bt+TZLDe3vZ1huW/jqDSjO/73XcdUuac5Z1pm/LzmrOJgAVtCU2vnErxPNcrMYU1xMcVYWsbGxeHh44F0ZMDuztVlZWVitVgIDA/H09ARwCSB9fX3x9PR06dZQnT8WxnI6duyY8nWnTp1qDJJLSkrYuXMncXFx+Pr6otPpsFqtuLu74+7ujr+/P7GxsaSmppKamsqhQ4do3bo1Wq2WDh06kJ+fT0VFBVarFa1Wq9SzcQbszhmJZ86cOa816OjRo7nrrrtc9vnll1+WNp+NaOHChfz1r39lxIgRFBQUEBwcDDhmJF1oXfrlJkGyEEI0EovFwr///e+m3g0hhBBXoKKiIp5//nlGjRrF3Xff7Qg4E7rAv96C/86GjLoVM+rvdoIzdh+yMVKg1ZPkG0Ccv4GysjISExPx8PAgODgYX19f1Go1JpMJk8lEeXm5smbTbDa79Cl2FsaqKQh2qtriqWpAvXPnTmw2G2q1mr59+7J06dIat1FeXs7hw4cBR7Vro9GIl5cXfn5+eHt7o9PpiImJISwsjP3793Pw4EFCQ0Px9/evtrVnSUkJBoOBvLw8JYCuGoAZjUYmTZpE165dldvWr1/PwoULpdVnI3vssccA+Pnnn11uf+CBB1i2bFlT7FKNJEgWQgghhBCiCdhsNj755BMSExOZNGkS3+ID+GMf9jLDN3wMP/yX8lO/319f+bW9SmLWoLXyIDs4ZfTjhI8fmUYP7B569Ho9HTt25MCBA+zbtw+9Xk9QUBDBwcEYjUZKSkrQ6XScPXv2vOnFdQ2Sq1avrpqBLSgoYM+ePXTu3JmgoCCaN29ep6J9zmr4OTk5nDp1Ci8vLyIiIjCZTKhUKuLj4zl8+DB5eXmEh4djNBqVopdWq5XCwkLMZjOFhYVYrVb69u2LVqtVgt+IiAiee+45wsLClN//4sWL+fbbby+4b+LiXej/6UpSfdMzIYQQQgghxGWxd+9eHn/8cfbt2wdUBhPD/gbjXgRv7ws+XgXEmHMZcPoEdx/ez4EDB7BYLKjVahISElCr1Uq7ph07drB3717c3d1JTU0lODjYJSMMDQuS/9jr9tdff1W+7tev3wVfQ3UKCgo4dOgQiYmJaDQafH19admyJVarldOnT3P48GESExPZu3cvBw4cIDk5mdzcXCoqKvCu8nsrKyuje/fuzJ07VwmQCwoKmDp1qgTIoloSJAshhBBCCNHEcnNzmTp1Kp988snvfYBbdkTz1luo2rWr97YOHjyI3W7HZrMRHh6u/Mzf35927dqh0+lo1qwZbm5utGnThtjYWCUotlgsFBcXX3D6cU2ZZICtW7cqRcIa0uanqpycHCXb7evri8lkqvX+Hh4exMXFAY5Af9SoUTz33HO4u7sDjordEyZMYP/+/Re1X+LaJdOthRBCCCGEuALY7XY+++wzEhMTyZs0yZHh9feHmTNZtWoVxmXLKC4uJrdK9yNnJ1iP6CrbSQWK8vg+P4PEgGDcvKN5KCqDFJ0vW5tHkmcBndpCP6897CyKJOOQO0RGEu7lxd8PHkSj0WA0Gn8P1mtQW5BcVFTE7t276datGwEBAbRu3ZqDBw82+Hdz9uxZQkJCcHd3JzQ0lOzs7Gr3LyQkhGbNmmG322nevDk33ngjRqNR+fnGjRt58803pWuEqJVkkoUQQgghhLiC7N+/n8cff5w9e/Yot918880sWrSI3r1713k7fVKTcbPbsKjUvGPqyffeLci1GAnTFfDXgD108jjHaNMuYioD3LO+vrRv317JKF9ounVgYCDg6EtcXS/kqlOuLzabDI7WUna7HT8/P+Li4vDw8FD209vbm1atWtG8eXP8/f154IEHuPPOO5UAuaysjA8++IBZs2ZJgCwuSDLJQgghhBBCXGHMZjMvvPACw4YNY/To0RgMBvz9/Zk8eTKvbtzIxx9/TGrq762gqFLgy145G9nHWMaAnOP8GJKAJtuKVa3GlFnMrccO411eBi+BASv3uCeySRPNFs9o3ErdiIiIuGAWOSgoSJnG7ex365zm7O7urkyJVqvV2Gw2+vfvz7Jlyy4qQDWbzZjNZvz9/WndujXh4eFkZmYqwbparaZLly4MGTKE8vJyZbr4jh07ePvtt10qeAtRGwmShRBCCCGEuALZ7XZWrlzJ5s2bGTNmDN27d8dqtdK+fXsWLVrEDz/8wCeffEJ+fn6N22ifl0aW3og+rZxCvZ7rcpJxt1pc7qMC+hacQmezsFIXqwTIJSUlNW63V69eytdpaWlMmjSJXr16odVqOXHihLImOCYmBk9PT8xmM4888ggLFiy4iN8InDx5ErPZTGxs7O/7r1KRkJDATTfdhJ+fn7LfOTk5vPfee2zevPminlP8+UiQLIQQQgghxBUsKyuLGTNm0KtXLwYPHkznzp0BuOWWWxgwYABff/01q1atIjc397zHqoCB6ccpT3F8r/Op+Xm6F53lVLqamJgYVCoV6enpNd73uuuuIyQkhODgYAwGg0svYn9/f+Xr1NRU2rVrR1BQEBMmTCAmJoavv/6aLVu2YLVa6/eLwLHWuaioiJycHHx8fLjxxhsZPHgwfn5+WCwWSktLsdvtfP/993z00UcUFxdfeKNC/IEEyUIIIYQQQlwFtmzZwq5du7jtttu48847MRgMGAwGRo0axV/+8he2bt3KqlWrUO2tbKScVc1GzFW+fry6Z0khPz+fZs2andfWCUCr1TJu3Djuuusu3NzclN7GAPn5+WzcuJFz585hNpsxmUx06tSJgIAAKioqyMzMxNPTk6eeeors7GzWrFnDL7/8wpkzZ+r1e2jXrh0333wzvXr1QqPRACiVtJOTk1mwYEGd+jILURMVUPuCAyGEEEIIIcQVxcfHh3vuuYchQ4agVrvW4k1NTeWHH35g7dq11RbUqguVSuWyLlmr1TJ48GBGjhyJ3W6nQ4cOhIaGcuzYMdatW8eaNWvYtm1btdlhg8FA7969ue222zAYDISEhLj8PDk5mc2bN5OUlMTx48ddMuJarZbIyEgSEhJo0aIFbdu2Pe/xdrudXbt2sWrVKnbs2IHNZmvQaxZXNi8vL/Lz83nllVcoLy+/4P11Oh3PPPMM3t7eFBQU1Ou5JEgWQgghhBDiKmUymRg8eDCDBg1ytIyqoqKigm3btrFlyxZ27tzZoKnHYWFhDBkyhIEDB+Ll5aXcfvbsWbKzs3n33XdJSUmp8/batm3LiBEj6N69e43Vs0tLS7HZbNjtdoxGI+np6ecFxuAo5PXjjz+yevVqMjIy6v3axNVFgmQhhBBCCCFEnWk0Gnr06MHNN99Mhw4dzvu5xWJh37597Ny5k2PHjpGcnOyyjthJrVYTFRVF8+bN6d+/P+3btz/vPps3b+bTTz/l1KlT5/2srvz8/Ojbty/9+/enRYsWtd43OTmZmJgYAKxWK4mJiaxatYqtW7c2aF2zuDpJkCyEEEIIIYRokJqyv065ubn4+fmRk5NDfn4+FRUVWK1WNBoN0dHR6HS68x5TUVHBpk2bWLFiBSdPnryk+xsYGEjLli2Jj48nLi6OgIAAwDHlu6SkhMTERLKysjh69CjHjx9XWjuJPxcJkoUQQgghhBAXRaPR0Lp1a3r27EnPnj2VfsKnTp0iOjq6TttIS0tj1apVrFu3rt6BhhCX0uUMkqW6tRBCCCGEENcgq9XK/v372b9/P++//z6xsbG0bNkSk8lEcXExYWFhuLu74+bmphT/SktLIykpiWPHjnH48GEOHz7cxK9CiMtPgmQhhBBCCCH+BE6ePFnrVGmNRiNrfIUA1Be+ixBCCCGEEOJaJwGyEA4SJAshhBBCCCGEEJUkSBZCCCGEEEIIISpJkCyEEEIIIYQQQlSSIFkIIYQQQgghhKgkQbIQQgghhBBCCFFJgmQhhBBCCCGEEKKSBMlCCCGEEEIIIUQlCZKFEEIIIYQQQohKEiQLIYQQQgghhBCVJEgWQgghhBBCCCEqSZAshBBCCCGEEEJUkiBZCCGEEEIIIYSoJEGyEEIIIYQQQghRSYJkIYQQQgghhBCikgTJQgghhBBCCCFEJQmShRBCCCGEEEKIShIkCyGEEEIIIYQQlSRIFkIIIYQQQgghKkmQLIQQQgghhBBCVJIgWQghhBBCCCGEqCRBshBCCCGEEEIIUUmCZCGEEEIIIYQQopIEyUIIIYQQQgghRCUJkoUQQgghhBBCiEoSJAshhBBCCCGEEJUkSBZCCCGEEEIIISpJkCyEEEIIIYQQQlSSIFkIIYQQQgghhKgkQbIQQgghhBBCCFFJgmQhhBBCCCGEEKKSBMlCCCGEEEIIIUQlCZKFEEIIIYQQQohKEiQLIYQQQgghhBCVJEgWQgghhBBCCCEqSZAshBBCCCGEEEJUkiBZCCGEEEIIIYSoJEGyEEIIIYQQQojL4rHHHuPkyZOUlJSwdetWunXr1tS7dB4JkoUQQgghhBBCNLq//OUvvP7660yfPp3OnTuzd+9eVq9eTWBgYFazzd4AAAJsSURBVFPvmgsJkoUQQgghhBBCNLqJEyfy/vvvs3TpUg4dOsSYMWMoLi7moYceaupdcyFBshBCCCGEEEKIRqXVaunSpQtr165VbrPb7axdu5ZevXo14Z6dz62pd0AIIYQQQgghxLXNZDLh5uZGenq6y+3p6em0bNmyztvR6/WX9H7VkSBZCCGEEEIIIcQVrby8nLS0NCZOnFjnx6SlpVFeXl7v55IgWQghhBBCCCFEo8rKysJisRAcHOxye3BwMOfOnbvg48vKyoiNjUWn09X5OcvLyykrK6v3vkqQLIQQQgghhBCiUVVUVLBz504GDhzIN998A4BKpWLgwIEsWLCgTtsoKytrUNBbXxIkCyGEEEIIIYRodK+//jrLli1jx44dbN++nfHjx+Ph4cGSJUuaetdcSJAshBBCCCGEEKLRffHFFwQGBvLiiy8SEhLCnj17GDJkCBkZGU29ay5UgL2pd0IIIYQQQgghhLgSSJ9kIYQQQgghhBCikgTJQgghhBBCCCFEJQmShRBCCCGEEEKIShIkCyGEEEIIIYQQlSRIFkIIIYQQQgghKkmQLIQQQgghhBBCVJIgWQghhBBCCCGEqCRBshBCCCGEEEIIUUmCZCGEEEIIIYQQopIEyUIIIYQQQgghRCUJkoUQQgghhBBCiEoSJAshhBBCCCGEEJUkSBZCCCGEEEIIISpJkCyEEEIIIYQQQlSSIFkIIYQQQgghhKgkQbIQQgghhBBCCFFJgmQhhBBCCCGEEKKSBMlCCCGEEEIIIUQlCZKFEEIIIYQQQohKEiQLIYQQQgghhBCVJEgWQgghhBBCCCEq/T+lW02bn02mPwAAAABJRU5ErkJggg==", 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Gtl4ClQ+SuUq6btIjXaGhoQyAXtDIBREqlcpgkh0uCDM2yZpuJdrQ8nRroyFr165lANjq1av5xwoLC/kbJefOnatwHytXrmRA6WCPw900WLFihVHH9fbbbzOgdNDAqa3jZuzf3/HIkSNLbbNq1Sr+80tLS9N7LiMjgwkEglLfo8qerxirfJCcmJjIAOODA8YYW7x4MQNKJ8uqiSC5st/v8o63PO3bt2cCgUDvhhxj/57bDh8+XGobLjAq7/N9+thrKkguy7179xgANnDgQL3Hue+5ra1thQkhue/ze++9Z/TrMsbY119/zZ/Hbt26xUxNTZmJiQm7c+dOpfbz9HVGq9WymJgYNm/ePCYQCFjr1q1Zdna23jZVudZxn0W7du1KbVNUVMT3+Dh58mSFZaYgmRZaaKGFlppaan0KKEPjuJRKJTZu3Ahvb28UFxfj3LlzAIARI0aUWjckJAQhISG4fv06rl27hjZt2sDf3x+mpqbYt28fvvjiC4wYMQJOTk61fSgASo7n1VdfxeLFi/Hrr7/yCUyAkvlJgZKkK5ykpCRcv34djRo1QlBQkMH9tW/fHteuXcPly5fRu3fvapVPIpGga9eupR739fUFACQkJBi9r2PHjqG4uBh9+vSBQqEo9byDgwMaNWqEmzdvIj8/v9Q6FSUPunbtGg4ePIiYmBjk5eWBMYbs7GwAwL179/j14uPjERkZCQsLC4Pj7WrKyZMnARj+HgIln+vly5dx8uTJUuuEhobC2tq61Da+vr4IDw9HQkJCqbHe5SlrKqSnkwedOnUKx44dQ1xcHAoKCsAY4z9j3ffw0qVLyMjIQJMmTdC6desKX//gwYMAgIEDBxp8vmPHjgCACxcuGHU83NhFS0vLcter6ePW1atXr1KPcYmlWrRoUaps5ubmsLKy0vvNVOV8VRV2dnZwcXHBtWvXMGvWLLz55psVJsHavXs3Pxd9Tavp73dOTg727NmDa9euIS0tDcXFxQBKzk+MMdy/f79UXgeJRGJwrmUvLy9cvXq13M+3Mue9yrp37x7+/PNPREVFITc3F1qtlp9Sr6zvYo8ePSpMGmZlZQUASE5OrlR5Jk6ciD///BP79u1DmzZtkJubi++//56/BlSWp6dnqcdeeOEF7Nq1Sy/xYXWvdcOGDSu1jUQiweDBg/Hll1/i5MmTZU4PRwghhNS0OpsnWSgUQqVSITg4GAMHDuQrpKmpqSgqKoKNjQ1MTU0N7sPDwwPXr19HXFwcAEClUmHt2rV48803MWPGDMyYMQO+vr7o2rUrXnvtNbRv375Wj2nEiBFYvHgxtmzZwgfJRUVF+P333yGXy/UCCy5Rz7179wzeMNCVkpJS7bI5ODhAJBKVepyby9JQMpmycGVfu3ZthQlk0tLS4OzsrPeYm5ubwXWLioowZsyYcufJ5oJl4N8Eb15eXhW+h9URHx8PAGVW9rnHue+hLhcXF4PbVOV9B4AOHTpgw4YNZT6fmZmJgQMH4ujRo2WuY+g99Pb2Nur1uc++ot+Ssd9ZLjlWRXOq1vRx63r6+wkAZmZmZT7HPa+bbKgq56uq2rhxI4YNG4bPP/8cn3/+Odzd3dG5c2cMGzYML7zwgt66SUlJuHDhAl555ZVSGduN+c1wQV1ZavL7ffToUQwbNqzc4M/QZ1jWua28z5B7rrK/P2MwxjBt2jSsXLmyzPevrO9iWedGXSqVCgDKTBJZnnXr1sHDwwNZWVl44YUX8Oabb1Z6HxxunuSioiLcuXMHV65cwf79+7F48WK9+c6re61zd3c3uC533uXOz4QQQhqujh07Yvr06QgNDYWTkxMGDBiAXbt26a2zYMECjB8/HhYWFjh9+jTefvttREVF1VOJy1brQXJ5FV5jGbrgDh8+HD169MCuXbtw8OBBHD9+HN9//z2+//57TJkyBcuXL6/265YlICAAzZo1w5UrV3Dnzh34+flh//79SE9Px5AhQ/jKDQA+U7ODg0OFrcRlVRIqQyisuYTlXNmbNm2KJk2alLuuTCYr9ZhcLje47ooVK/DLL78gODgYS5cuRfPmzWFpaQmJRIK7d+/Cz8+vwkp7fSiv4leT77sxZs6ciaNHj6Jz585YsGABgoKCYGFhAZFIhIMHD6J3797Veg+5z37w4MFlBoNA6RbespibmwMoO2gwVnWOu7zPqCY/v8reyCkrm3u3bt0QFRWFvXv34q+//sKxY8ewadMmbNq0CYMGDcK2bdv4dffu3QutVmswqzXXYpmXl1dmGbjnyvqsa+r9ycnJwSuvvIK0tDR8/PHHGDZsGNzd3aFQKPheOr/88ovBz7CiMtT1b3Dr1q1YsWIFXF1dsXLlSrRt2xa2traQSCQoKiqCTCYr87tY1rlRF3djycLCotJl2717N59l/c6dO8jJyeFvGFTWsmXL9G4cbt26FcOHD8cnn3yCPn368D1T6vpaRwghpOExNTXF9evXsX79evzxxx+lnp8xYwbee+89jB49GtHR0Vi4cCEOHDiAgICAWrmhXR21HiRXxNraGlKpFCkpKcjNzTVYSePuUD/dUmBra4tx48Zh3LhxYIzhwIEDGDp0KFasWIGxY8fy01TUhhEjRuDq1avYsmULPvnkE4NdrYF/W2BsbGxq5IZBXeLK3qFDB/zvf/+rsf1yP5pffvml1Gf04MGDUuu7urryzzHGaq01meuyz02L9bSyvof14Y8//oBIJMLu3bv1bsoA5b+H9+/fN2r/Li4uuHPnDmbNmoXQ0NBql9fOzg5ASY+D6qjscde0qp6vpFIpgJIg8WlPT4WnS6VS4dVXX8Wrr74KADh37hyGDBmC7du3488//0Tfvn0BAHv27IFYLOb/1sX9jst7f7jnymoxriknT55EamoqBg8ejAULFpRZjmcBdx779ttvS01rVhPHkZ6eDqDkOlcZ9+7dwwcffAATExP06dMHO3bswHvvvVdj09ENHToUR48exZo1a/Dhhx/yvTqqe60r67zLPV5XQ6oIIYRU3V9//YW//vqrzOcnT56MTz/9lJ+yctSoUUhMTMSAAQOwdevWuiqmUeplnmRdEomEH7dnaJ7T8PBwXL9+HWZmZvw8u4YIBAL06dOHr6xERERU+NpcxdXQXL8VGT58OIRCIX755RdkZWVhz549sLKyKtUN0sXFBf7+/rh161aZc4DWp/Leg65du0IkEmHv3r38mMGawFX+DFXIf/vtt1KPOTk5oXHjxsjIyMDvv/9u1GtIJJJKf67cWM6yuoFv3rxZb736lJ6eDpVKVSpQBAy/h6GhobCwsMD169eNGkfcs2dPADB4F7AquJ4IhuaarozKHndNq+r5ytHREQAMngMOHTpk9Ou3adMGr732Gv9aQMnc0YcOHUKHDh0Mtjp26tQJAPD3338jPz/f4H65i1Vtf7fL++1HRUXhypUrtfr6Namy57HKioyMBIByr3tPU6vVGDlyJHJzc7FixQps3rwZ/v7++PHHH/m55GvC/PnzIZfL8ffff/Nzplf3WmfoPVOr1Xy5aTwyIYQ82zw9PeHo6IjDhw/zj2VlZeH8+fNo27ZtPZbMsHoPkgHg3XffBVBy4dW9A5+dnY1JkyaBMYYJEybwXdSuXr2KHTt2oKioSG8/aWlpOH/+PIB/W87Kw92ZrkrF3cnJCV27dkVUVBRmzpyJgoICDBkypNR4QACYO3cutFotBg0ahGvXrpV6PjU1tcIxv7WlvPfA2dkZY8eOxcOHDzF8+HAkJiaWWicqKqrSlS8ugcx3332n9/i2bduwadMmg9vMmjULADBlyhTcuHFD7zkuSNDl5OSExMTESo3ne+WVV2Bvb49Tp05hzZo1es+tXr0aly5dgrOzMwYNGmT0PmuLr68v0tPTS911W7lyJf7+++9S68tkMnzwwQcAgDfeeKNUq01mZiaOHz/O/z1hwgTY2dlh6dKlWLNmTakuwWq1GgcOHOADtYpwwdfFixeNWr8slT3u2lDZ8xUAdO7cGQCwfPlyvW7PR48exZdfflnqNR49eoQNGzaU6iJdUFDAHyd3jjt69Chyc3PLTJTXvn17tGjRAmlpaZg4cWKp7ky7du3Chg0bIBKJMGnSJGPfhirhfvs7duzQG5OckZGBN954o0ZvxtU27ljWrFmj16365MmT+OKLL6q9f+5mFvfdMcYnn3yCCxcu4KWXXsKECROgUCiwefNmSCQSvPnmmzU2rtfR0RFvvfUWAGDRokX849W51p06dapUa/e8efPw6NEjhISENIibk4QQQqrOwcEBAErFE4mJifxzxpDJZFAqlUYvhoaEGqtS6bCrO09yWd58800GgCkUCvbiiy+yIUOGMFtbWwaAtWnTRm+6DG5+TnNzc9a9e3c2YsQI9uKLLzKlUskAsJdeeklv32VN97F8+XIGgNnb27Nhw4axN954g82cObPC7TjclEHcUt4UFbNnz2ZAyVytzZs3Z0OGDGGDBw9mzZo1YyKRiJmbmxv9XpU3BVRZ0x5xU488PRVKRe9BXl4e69mzJwPATE1NWfv27dnw4cNZv379mI+PDwPA+vfvb7B8ZTl+/DgTiUQMAAsNDWXDhw/n50eeNm0aAwxP+fPuu+8yAEwkErEOHTqw4cOHsy5dujALCwvWpEkTg+t6enqyESNGsDfeeIMtXbqUf76sqV4OHz7MFAqFXtm4aUXMzMxKzU/LTZFT1vy+FX2HnmbsfMGbN2/mv3cdO3Zkw4cPZwEBAUwoFLIPPvjA4D6Ki4vZgAEDGAAmlUpZ9+7d2fDhw1mHDh2YiYlJqc/x7NmzzMbGhgFgrq6u7IUXXmCvvvoq69atGz+d1B9//GHUcWm1Wubp6cmUSqXe1Eh1cdzlfQYVfX5lfZcrc75irOR35Ofnx4CSeYUHDRrEWrduzYRCocHv/NWrVxkAZmJiwjp16sReffVV1r9/f/41WrRowc9ZPGHCBAZAb17ap925c4efSsfOzo4NGDCADR8+nDVt2pQ/Lz09N7gx709lp1JijPHnEwsLCzZgwAA2YMAAZmFhwXx8fFj//v0N7q+8c1tVPt+amALqzp07zNTUlAEl82wPGzaMdezYkQkEAv4zfbrMZZ2Hn5adnc3kcjnz9/cvdz1dZ86cYSKRiNnb25eav3zRokUMAOvZs2epOcbLUt48yYyVTAHInSt1566v7LWO+yzefvttJhAIWKtWrdjw4cP5Oa5VKhW7cuWKUWWmKaBooYUWWhrOwhjjr+vAv1OsOjg46K23detW9uuvvxq1T5lMZtT1QFd8fDyTyWRVOYbKbVBbQTJjjG3atIm1a9eOmZmZMblczgIDA9miRYtKzdGbkJDAPv30U9atWzfm4uLCpFIps7e3Z+3bt2fr169nRUVFeuuXVSEqLi5mH330EfP29mYSiYQB+pWaigKczMxMJpfL+e0qqnwcP36cDRkyhDk5OTGJRMKsra1ZSEgImzRpEjt+/LjR71NNBskVvQeMlcxxvXHjRtatWzdmZWXFJBIJc3JyYm3btmULFiwoNf+mMXOKnj17lnXr1o1ZWloypVLJ2rVrx7Zv325wzlhdu3btYr1792ZWVlZMKpUyFxcXFhYWxnbs2KG3Xk5ODps0aRJzdXVlYrG41D7Lq8SHh4ez4cOHM3t7eyaRSJijoyMbOXIku337dql16ytIZoyxffv2sTZt2jClUsksLCxYjx492LFjx8otk0ajYRs2bGCdOnVi5ubmTCaTMQ8PD/bKK68YLGNCQgKbMWMGCwwMZCYmJszExIR5e3uz/v37sw0bNpSaJ7U8XEX9t99+q9Pjro0gmTHjz1ec2NhYNnz4cGZpackUCgVr0aIF+/333w1+57Oystjy5ctZ3759mYeHB5PL5cza2pq1aNGCrVy5Ui8Id3Z2Zo0bNy73PWOMsZSUFDZnzhwWEhLCTE1NmVQqZa6urmzYsGFlzp1dG0FyXl4emzNnDmvUqBGTyWTM1dWVvfXWWywlJaXM/ZV3bquvIJkxxiIjI9lLL73E7OzsmImJCWvWrBlbs2ZNmWU2NkjetGkTA8CWL19e7nqc7Oxs5uXlxQCwffv2lXpeo9GwDh06MMD4uc0rCpIZY2zKlCkMABsyZIje45W51ul+Fnv27GFt27ZlJiYmzNzcnPXv359FREQYVV7GKEimhRZaaGlIC2P6QbKnpydjjLEmTZrorXfs2DH25ZdfGrVPpVJp9DVBF9eQWsmlchsYGyQTQoiuhIQEJpfLWVhYWH0X5blx6dIlBoDNmDGjvotCalCvXr2YiYkJS0lJqe+i1LrK3kgsDwXJtNBCCy0NZ2FMP0gGwOLj4/kbrAD4HoZDhw41ap//Bsn5lViqFiQ3iDHJhJDnn4ODA959913s27cPN2/erO/iPBc0Gg3mzZuHsWPH1ndRSA25cuUKDh48iKlTp8La2rq+i0MIIYQYzdTUFE2aNOETtnp6eqJJkyZ8HpUvv/wSH330EV566SUEBQVh06ZNiI+Px86dO+ux1IbV+xRQhJD/jtmzZ2PdunVYsGCB3jy/pGpatWqFVq1a1XcxSA365JNPYGdnhxkzZtR3UQghhJBKadGiBY4dO8b/vXLlSgDAhg0b8Prrr2Pp0qUwNTXFmjVrYGFhgVOnTqFPnz5VmCO5oBLryitexQAKkgkhdcbCwgKpqan1XQxCGqyGeDedEEIIMcbx48chEAjKXWfevHmYN29eHZWo6qi7NSGEEELqxYYNG8AYQ5cuXeq7KIQQQgiPWpIJIYQQQgghhDwjClGSX6si5bdql4dakgkhhBBCCCGEkH9QSzIhhBBCCCGEkGdEAaglmRBCCCGEEEIIqSMUJBNCCCGEEEIIIf+odHfrlJQU5OfnQ6FQ1EZ5CCGEEEIqJT8/HykpKfVdDEIIIXWiCIDWiPWq3h5c6SD58ePH8PPzg42NTZVflBBCCCGkpqSkpODx48f1XQxCCCHPiSol7nr8+DFdjAghhBBCCCGE1LEC1HZLMo1JJoQQQgghhBBC/kFBMiGEEEIIIYQQ8g+aJ5kQQgghhBBCyDOiEIDGiPVEVX4FakkmhBBCCCGEEEL+QS3JhBBCCCGEEEKeEQWglmRCCCGEEEIIIaSOUJBMCCGEEEIIIYT8g7pbE0IIIYQQQgh5RlB3a0IIIYQQQgghpM5QSzIhhBBCCCGEkGdEIQC1EetVPdSllmRCCCGEEEIIIeQfFCQTQgghhBBCCCH/oO7WhBBCCCGEEEKeEQWg7taEEEIIIYQQQkgdoZZkQgghhBBCCCHPiEIAxUasJ6nyK1BLMiGEEEIIIYQQ8g8KkgkhhBBCCCGEkH9Qd2tCCCGEEEIIIc8IY7tba6v8CtSSTAghhBBCCCGE/INakgkhhBBCCCGEPCMKARQZsR61JBNCCCGEEEIIIdVGQTIhhBBCCCGEEPIP6m5NCCGEEEIIIeQZUQDqbk0IIYQQQgghhNQRakkmhBBCCCGEEPKMoJZkQgghhBBCCCGkzlCQTAghhBBCCCGE/IO6WxNCCCGEEEIIeUYU/rNUhFX5FaglmRBCCCGEEEII+Qe1JBNCCCGEEEIIeUYUgFqSCSGEEEIIIYSQOkItyYQQQgghhBBCnhGFKGlNrj3UkkwIIYQQQgghhPyDgmRCCCGEEEIIIeQf1N2aEEIIIYQQQsgzogDU3ZoQQgghhBBCCKkjFCQTQgghhJD/rNGjR4MxhtDQ0PouCnnGcd8lbikuLkZsbCx+/PFHODk51XfxniNFKEneVdFSVOVXoO7WhBBCCCGEEFJD5s6di+joaMjlcrRp0wZjxoxBhw4dEBQUhMJCY+b3JfWNgmRCCCGEEEJIrXFycoK1tTVkMhmUSiUEAgGysrKQlpaG9PR0pKen13cRa9T+/ftx+fJlAMC6deuQkpKCWbNmoV+/fvj999/ruXTEGBQkE0IIIYQQ8pyzs7NDcHAwQkJCYGdnBwsLC5ibm6OoqAipqalISUlBTEwMLl26hLt371brtWQyGVq0aIHmzZujefPmsLa2BgAkJSXBzs6u1Pq5ubm4e/cubt++jcjISISHh0OtVlerDA3JyZMnMWvWLHh7e9d3UZ4TxibuElT5FShIJoQQQggh5Dnk4OCAPn36oGXLlnB1dUVsbCxcXFxKrWdlZYVGjRqhbdu2GDZsGDIzM3HhwgXs378fUVFRRr+ehYUFwsLC0LdvX5iZmZV6Xi6XG9zO1NQUzZo1Q7NmzQCUBM2nT5/G8ePHER4eDsaY0WVoiDw8PADguWsxf55RkEwIIYQQQshzxNPTE4MHD0aHDh0gEBhuTcvPz0dmZiakUiksLS311jM3N0fPnj3Ro0cPXL16FUePHsXZs2dRXFxscF/e3t7o27cvQkNDYWVlpfdcUVERbt68iYcPHyInJwd5eXkASgJqS0tLWFtbw8fHB5aWlvw2pqam6NWrF3r16oWkpCRs27YNhw4dgkajqe5bUyfMzc1hbW0NuVyO1q1bY968eSgoKMDevXvru2jPCWpJJoQQQgghhBghMDAQgwcPLpWpmzGG27dv4+LFi7hx4waio6P1Al6RSAQbGxuEhISgffv2CAgIgFwuR0JCAt9luqioCDdu3MDVq1eRlZUFgUAAHx8ftG/fHra2ttBqtQCAuLg4ODg44MSJEzh69Chu3bpVZnCty9bWFv7+/mjRogXatm3Ltzrb2dmhb9++GDx4MDZs2IBTp07V4DtWO44cOaL3d3R0NEaOHIm4uLh6KhGpLAqSCSGEEEIIeYa1atUKQ4YMgZ+fn97jmZmZ2LVrFw4cOIDs7Oxy92Fubo579+6hsLAQixcvRufOndGxY0d+6iKpVIoWLVqgTZs2yM/Ph0QiAVDSpdvV1RWFhYW4ffs2Tpw4gYMHDyI1NbVSx5CcnIzk5GScPHkSX3/9NVq2bIlevXqhWbNmsLKygkqlwowZM9C/f3/88MMPuHPnTqX2X5cmTpyIu3fvwtzcHGPHjkWnTp0oq/UzhoJkQgghhBBCnkH+/v4YO3Ys/P399R5PSkrC9u3bcfjw4QpbcWUyGYKCgmBqaoqcnByYmJjAwcEBhw4dwqFDhxAYGIju3bvjpZdegr+/P8RiMS5evKi3fWZmJjIyMjBt2jSEh4fr7V8oFMLLywsajQY5OTlITk6u8LiKiopw+vRpnD59Gr6+vhg5ciSaNm0KAPDz88MXX3yBkydPYsOGDUbtr65duHCBz269c+dOnDp1Cj///DP8/PyQm5tbz6V7HhTCuO7Wwiq/AgXJhBBCCCGEPEMcHBwwZswYtGvXTu/xmJgYbNu2DSdPnuS7P5dHIpEgJCQECoUCACAQCFBYWAgXFxc8evQIABAREYGIiAjcunULM2fOhFKpxKVLl3DlyhWkpqbixRdfREhICADg4cOHpV7D09MTTk5OyM/Ph7OzM/Lz85GTk2P0sd69excff/wxQkNDMXbsWLi6ugIAOnbsiDZt2mDXrl3Ytm0bP9a5odFqtfjwww9x7NgxTJo0CZ9//nl9F4kYgYJkQgghhBBCngFKpRLDhg1D3759IRKJ+McfP36MjRs34sKFC0bvSygUIjAwEAqFAowx3L17F1KpFKampgYTZKWkpCA/Px/5+fmIiorik1CFhYXx6xjqUsxluVapVCguLkbjxo1x+fJlo4J47pjz8vJw+fJlXL16Fb1798arr74Kc3NzSCQSDB48GL169cLmzZtx4MCBBpkJ+/jx4zh//jwmT56ML7/8krpeV5uxibuoJZkQQgghhJAqGzt2LPr06VPq8VWrVlWq5bM2iMVihIWFoX379nrjjjMyMrBlyxYcOnRIL+i0trZGXl4e8vPzy9ynj48PTE1NAZQklkpMTIS7uzsKCgpQUFA6ANENnMXif0MImUzG/99Q126ulTo+Ph62trZQKBRwdXVFTExMhcft6ekJV1dXFBQU4NatW8jJycH+/ftx/PhxDB48GP3794dEIoFKpcLEiRPRvXt3fPXVV0btu6598cUX2LZtG8aMGYPvv/++votDKkBBMiGEEEII+c+bOHGiwcc3bNhQr0Fyu3bt8Prrr8Pe3p5vjc3IyMCOHTuwY8eOUq2Stra2aNy4MQCgoKAACQkJSExMRFFREYCSFmQ/Pz/Y2tqiqKgI8fHxiI2NBVAS/MrlcqjV6lLl0H1MtxWbC5K5/T9NKCxpzcvMzARQEsBbW1sjMTHRYDDOMTc357tWc63e58+fBwDk5eVh06ZN2L9/P0aPHo1OnToBKBmv/OWXX+KPP/7Ar7/+WmaZ6sOOHTsQFRWFadOmYe3atUa3pJP6QUEyIYQQQgj5z9q4cSM2btxY38UoxdXVFRMnTkRgYCD/mIWFBa5evYopU6YgPT3d4HZ2dnb8/+VyOezs7ODh4YGcnBzk5+dDpVLx0ytlZWUhOjqaX58Lfg11ty6rJVkqlQIw3NX6aVFRUVCpVDAzM0OjRo1w8+bNMtd1dHTkyysQCAy2UicnJ2PZsmX4888/MWnSJLi4uEChUOC1115Dx44d8fXXX+PatWsVlqumlPddYoyhUaNGdVaW55uxibtEFa9Shqp31CaEEEIIIYTUuP79++PLL7/UC5Bv3LiBVatWITo6uswAGSjp1sxhjEEsFkMgEECpVMLOzo4PkOPi4hAZGam3LdfqayhIrqgluawgWavVQqvVgjGG4uJivtXa0tISjo6OBrdRqVSws7ODQqFAYmJiheOMb926hffeew9btmzh92tvb49PPvkEU6dOhUqlKnd7Qp5GQTIhpNJGjx4NxhhCQ0PruyjkGcd9l7iFq0D9+OOP/NychBDyX2Fra4tFixbhjTfe4Ochjo+Px8KFC/HRRx/h2LFjCAoK4pNhGZKeno6cnBwwxpCRkYGrV6/i3r17SExMRHZ2NhISEhAeHo779++XCj6r0pJcXpBsamoKqVQKoVCIrKws/ni4OZt9fHxgYWGht41YLOa7ixcVFfHrVtQ9Wa1WY+vWrVi3bh2ePHnCP965c2d89913pTKBk2dZQSWWqqHu1oQQQurd3LlzER0dDblcjjZt2mDMmDHo0KEDgoKCKAsoIeQ/oUuXLnjrrbdgYmICoKQVeNeuXfjpp5/4rsbR0dG4e/cuXnzxRWzdurXMfUVFRSEgIACWlpaws7NDbGwsEhISKiwDF/waCkir2pL8NMYYIiIi0Lx5c0ilUjRu3Bjh4eHIzs6GTCZDaGgoxGIxGGO4ffs2HBwcAKDcJGS6UlNTcfDgQVy5cgVjx46FmZkZZDIZxo8fj7Zt2+Krr76i6wqpELUkE0IIqXf79+/Hli1bsG7dOowfPx7Lli2Dj48P+vXrV99FI4SQWjds2DBMmTKFD5CTk5MxZ84crF+/vtRY3O3bt+Oll17Syyr9tKysLL4F1tXVFQKBwKhycK9vaM5hQy3JAoGA/39lkmQVFRUhIiICWq0WEokEAQEBaN68OVq3bo05c+agY8eOePToETIyMiASiZCXl2dU8jRu3ud79+7h8OHDeOutt3Ds2DFkZmbC2toanTt3xsKFC/ku54SUhYJkQgghDc7JkycBAN7e3vVcEkIIqV1Dhw7Fq6++yv995MgRvPvuuwgPDze4/tWrVxEfH6+3jSGPHz8GUBI4clM9lUcqlfJdvHNzc0s9b6glmUvaBRjfkszJzs7GrVu3kJubC5FIxHchX7NmDZo1a4ZmzZoBKElWZmJiUm4mbM4rr7wChULBz+GclZWFFStW4IcffuBbov39/TF37ly9spNnDZe4q6Kl6j0GKEgmhBDS4Hh4eABAuclpCCHkWTdkyBB0796db4X94YcfsGrVqlItubrdm4GSuZtDQkLg5eVV5r6zs7P5btPm5uZ6zxlqWdYNpA0FyYZaknVbsw21JEskEiiVylLl56SlpeHq1at4/PgxEhMTERsbi0OHDmHmzJl49dVX0bFjR35bQ63bT+vbty82b95cqvX9zJkzmDlzJt8aHRwcjNmzZ+uNrSZEFwXJhBBC6p25uTmsra3h7OyMgQMHYt68eSgoKOBbAwgh5HnTp08fvPbaa3BwcEBubi6+//577N69u9R67u7uCAkJQePGjWFjYwOgJDN1eHg4+vfvX+b+GWN8l+ung+TvvvsOwcHBeo9xLblqtdpgq7ChlmTdINnQNnZ2dsjOzkZxcXG52a8fP36MO3fu4MGDB8jLy8P9+/exfPlyfPDBB3B2dgZQcXduLiDXndJK18OHD/Hxxx/zLcrNmzfHlClTyt0naagKK7FUDQXJhBBC6t2RI0eQkpKC2NhYbN++Hbm5uejXrx/i4uLqu2iEEFLj/P39MWHCBP7vP/74A/v27TO4rq2tLWxsbODg4IDGjRvziaxOnz5d4SwTXEDIdaPmiESiUsm57O3tAYDPQv20ilqSnw6ClUolbG1tkZubi8ePH+sF2cY4f/48tm7ditdeew0KhaLCcdVqtRrZ2dl8UG1IVFQU5s+fz5e1Q4cO6N27d6XKRf4bKEgmhBBS7yZOnIgePXpg0KBB2LdvH2xsbCj7KCHkuaRSqTBz5ky+NXbnzp3YuXOnwXWlUilMTEygVquh0WggEAjg6+sLJycnZGRk8Im2ysIFs7oBqlgsho2NDRITE/nHuHG/gP48y7oMtSTrdqN+Ogh2d3eHSCSCRCLhx0dX1u7duxEXF4dBgwZVuC5jDGfOnMGLL75Y7nqRkZFYtmwZ//f48ePh5uZWpfKR5xcFyYQQQurdhQsXcOTIEezYsQP9+vVDeHg4fv75Z6OSzRBCyLNCIBBg2rRpsLa2BgCEh4djw4YNZa4vlUqhVquhVqtx/fp15OXlgTEGR0dHODs7Vzh3sEQigVqt1ps+ydnZGYWFhUhJSeEfc3BwgFarRUFBAdLS0gzuS3dOZa5VVyj8N5R4uixc0J2YmFhhOcui1Wqxfft2uLq6ok+fPhWu/8svv6BVq1Zo0qRJueudP3+eb7mXSqWYMWMGJfKqpOjoaDDGSi1fffWVwfVHjx5dal1jp/UqrfbnSaYgmRBCSIOi1Wrx4YcfwtnZGZMmTarv4hBCSI0ZPnw4mjZtCgDIyMjAF198UW4AKZVK+dbg3NxcXL9+Henp6TA1NUX79u0rnBZJLpdDLBbrdZUODAzUG7dramoKOzs7MMYQExNT5r50uztzAbNuS/LTx8E9Z2ZmZvQUVE8rLCxETk4Otm7ditGjR8PFxaXc9dPS0vDTTz/h3XffhYWFRbnrrl+/Hg8fPgQAuLm54Y033qhSGf+rWrZsCQcHB37p0aMHAOD3338vc5vMzEy9bdzd3euquJVGQTIhhJAG5/jx4zh//jwmT55c7lyghBDyrPD19cXQoUMBlASUn3/+eYUZ/HVbN9VqNYqLi3Hnzh3k5uaiTZs2uH37Nuzs7AxuK5PJ+POnbrbqF198EQcPHuT/5gIVrVaL5OTkMstiKNAtryU5Pj4eWq0WJiYmCAoKqnJLLZfI6/jx45gxY0ap8dVP27t3LyIiIrBgwQK97ugCgQDm5uYwMzODRCJBcXExli5dyicEe+GFF9CiRYsqlfG/KCUlBYmJifwSFhaGqKgoHD9+vMxtGGN62yQlJVXx1WkKKEJIAzZ27FjMmTOn1MJlyCSkOr744gs4ODhgzJgx9V0UQgipFpFIhHfffZcPNLds2YKIiIgKt+NaQ3WnPyouLkZ2djYcHBxw/fr1MrM+W1lZASgJTDIyMgAA3bp1g1Kp5Oeit7Cw4DNmx8bGGt0tmmtJLi9IfvToEeLj4yGTyWBpaYnQ0FA4OjoatX9dXIbuI0eOoKioyKgW39WrVyMlJQXz5s2DVCqFra0tWrZsiSZNmsDPzw8tWrSAUqlEbGwsvv/+e367t956i27MVoFEIsHIkSOxfv36ctczMzPDw4cP8ejRI+zcuRMBAQF1VMLKoyCZEFJlEydOxKefflpqeXqqCUKqYseOHYiKisK0adP0KmKEEPKsGTx4MN9ie//+fWzfvp1/ztbWFu7u7nB2dta7ySyRSPixy6mpqXr7GzJkCM6dO4e8vLwyu6xyQXJ2djbUajV8fHzw1ltvYeXKlSguLoZQKESjRo0AlGTBrmg2AUPdrcsLkhljePDgAaKjo6HValFUVIRGjRrB19e33Nd5WmFhIQQCAWQyGZYuXYr27dsjLCys3G00Gg0+++wzAMDKlSsRHBwMuVwOoKSFnTHG11UOHTqE69evAyiZsopr7SfGGzBgACwsLModX3/nzh2MHTsW/fv3x8iRIyEUCnHmzJlys5HXJ6p1EEIqbePGjRAIBGUuNG0PMRb3Xbp8+XKp5xhjaNSoERo1alTlpC+EEFLfXFxc9LpZr169mj+ncYGqu7s7vL29ERwcjJYtWyIgIAAtWrSAWq0GY0wvyVa/fv3g4+OD/fv3Iz8/32AXaYFAwLdCp6WloUOHDli8eDF++uknXL16FUBJN2uFQgEAuHfvXoXn2Yq6W+uOe9b1+PFjXLp0iW/xdnBwgIeHR7mvpYtrRZdKpUhNTcXChQsxatQotGrVqtztxGIx9u7dC0tLS4wZMwaFhYUIDw9HcXExpFKpXvfvb7/9ls/O/fLLL1O260p64403sH//fiQkJJS5zrlz5/DTTz/h+vXrOHHiBAYOHIjk5GS9qdCMR4m7CCGEEEIIeWa99957fPKtHTt26CXNsrS05J8DgKKiIigUCtjY2EAikUAsFuPOnTt8gi5/f3+89tpr+P777yEQCCCXyw1mo7azs4NIJIJYLEZYWBjeeecdLF26FHv27AFQktCLS4KVmJjId8cuT2VbknUVFBQgPDycH4Pt5uYGpVJZ4WsC0MuArFAocPfuXaxcuRLTpk2Dj4+PwW1sbGzQvHlz5OfnY/369UhPT0fXrl35APnp/cbHx+O3334DUNI1/p133jGqbKTks+zRowd++OGHSm2nVqtx9erVMj/D+iaueBVCCCF1SSAQwM/PD61atYK9vT0YY9BoNGCMIS0tDSdPntSrZBFCCGmYevfuDX9/fwAlgdgvv/yi9zw33hYAbt++jeLiYtja2vKJpdLT0/mWYpVKhRkzZuCnn35CSkoKnJyckJeXh4KC0q1lLi4ucHV1Rf/+/fHo0SNMnTpVb/5jrls31yW6siobJHPb3Lp1Cy1btoRUKkWjRo1w9epVvamlDNE9PrlcjpycHJw9exYWFhaYN28epk+fjidPnvDl8fDw4G8ASCQSXLlyBcePH8fs2bPx+eefY9euXUhLS9NrnQeA7du3o0uXLnByckLjxo3Rs2dPHDp0yPg35T/q9ddfR1JSEj+llrGEQiGCg4Px559/Vv5FNRoAhnsuPLUiIKp4LUMoSCaEkDJIJBL4+voiKCgIZmZmUCgUyMnJQWxsLL9UNP2GsczMzDBmzBhYWlrCz88PKpWqzHUHDx6MuLg4HDt2DCdOnCi3exMhhJD6IZfLMXLkSP7vr776CsXFxXrrFBUVIS8vDyYmJrC2tkZkZKTBjNcqlQqLFi1CREQEdu/ezQfehgJkCwsL9O/fH506dcLGjRuxcePGUgGsSqXi56l9ukxlqU5LMkej0SAqKgoBAQEwMzODk5NThUO0NBoNcnJyIJVK9ZJq7d+/H+7u7pgwYQIWLFgAMzMz+Pv78xmt8/LyEBERwbcYL1q0CCtWrMDYsWP5cdm6iouL8c033+DTTz8FUBL8nT9/HllZWRUe13+VQCDA66+/jo0bN5bqbr9x40bExcVh9uzZAIC5c+fi3LlziIqKgoWFBaZPnw53d/dKt0DXFQqSSbUoFApYWFjozYHH/VtUVIS4uLgysy4S0hCJRCI0a9YMnTp1Qps2bfDw4UO+MmLI48ePcfr0aZw5c4afb7EyXFxcMHnyZLz88sswMTFBbGysUUGvs7MzRowYgREjRuDy5cvYunUrbt++XenXJ6Q+ODg48ElzdFuRCgsLkZ6ejuzs7Apblwhp6AYNGsR/z0+fPo3w8HCD6yUlJcHDwwNmZmYQi8X82FiOpaUlZs2ahZiYGKxcuRLAv8Gpod/JO++8gxYtWmDlypXYtWuXwdfUaDQQCoWQy+UQCoVGBbiVnQKqLCkpKUhLS4OVlRXc3NyQkJBg1HhoqVQKlUqlF1Rv3rwZa9euRa9evZCfn8+XMTExEVFRUXqBm0ajwbZt2/DGG29g6NChuHjxYqnA7saNGzh27Bi6dOkCMzMzjB49Gv/73/+MOq7/oh49esDd3d1gVms3Nze9z9XS0hJr166Fg4MD0tPTcfnyZbRr1w6RkZF1WWSjUZD8HyeXy6FQKGBiYgITExNIpVIolUqYmJjwj3P/mpmZQaVS8UtRURGcnJzK3T9jDPHx8Xj48CEePnyIe/fu4ebNm0bftSSkrgQFBaFLly5o166dXnbRiqarcHV1xbBhwzBs2DDcunULMpkMe/bswdGjR8vcRiQSoU2bNujSpQuGDh0KW1tb/jlLS0tER0fjypUruHDhAm7dugXGGAQCAcRiMQIDA9G5c2cEBQXx24SGhiI0NBRnz57Fn3/+yWfpJKQh8PDwQFBQENzd3eHh4QEPD48Kp1hhjCEhIQEajQZZWVnIyspCdnY28vLy+CU/P1/v/9zf3P/LSiJESF2wtrbGyy+/DKBk7OXGjRvLXPfJkydwdHSEQqGAo6MjHj9+zD9nZ2eHhQsX4tq1a/j+++/5oIOrR+nOAwwAEyZMQEBAAH744QdcuHChzNdMSUmBvb09NBoNVCqVUWOSdVW1JZkTHR0NKysriEQi2NraIjExsdz1U1JSYGpqCltbW6SlpfHry2Qy3Lx5E0OGDMFPP/2E4uJi3Lt3r1RXagB8D63Nmzdj4MCBmDRpElatWlVqvXXr1qFly5YwNTVFjx49sHfvXhriVIZDhw4ZvHkCAF27dtX7e8qUKZgyZUrNvHBl2t8UVXsJCpL/A6ytreHi4gJnZ2d+cXFxga2tbakv9sOHD43OOGhMBmOBQMC/Zvv27QGUJEq4ePEizpw5g8uXL6OwsOoTfRNSHSqVCt26dUOfPn0M3vDJzc3FlStXcPnyZSQmJqKwsBCWlpb8b8jb2xt+fn4AgIyMDISEhKBZs2YYNmwY4uLicOjQIcTExKCoqIgPcj09PeHj4wO5XI5GjRrxmUUZY7h27RrWrVuHXbt2lWpJ4MTGxuLAgQOwtrZGx44dERYWBjs7OwAld20XLlyIqKgo/P777zh37hy1xpF60ahRI7Rr1w7t2rWr0ryoAoGAH5dZkaysLIPDE7KzsxEXF6e3cD01yvp9EVJTRo4cySeI2rdvHz9m1pCioiIUFBRAJpPB1NSUf9zV1RULFy7E6dOnsXbtWr1t0tLS4OjoCIFAAHd3dzx69AgDBw7E4MGDsXbtWty/f7/cXkm5ubl8+RQKRZUTd4lE/w74rEyQnJubi6SkJFhbW8PNza3CIDkuLg4uLi4QCATw8fGBl5cXgJKbBXFxcejQoQNSUlJw7969MhtiuGzfOTk5mD17NpYtW4ZXX30VP//8s956mZmZ+PXXX/HGG29AIBBg/PjxfJdh8t9BQfJzyMzMDM2aNUOLFi0QGhpa7tjGp+l2mfby8kJMTEypygR3Zz8hIQGpqanIyMhAVlYWf3LkTpxmZmZwd3eHm5ubXpp9hUKBTp06oVOnTigqKsLly5dx+vRpnD9/ngJmUieCg4PRp08ftG3bVi+rKFAyvuvcuXM4ceIErl69Wqo16uHDh/z0GUBJy2/btm0RGBjItxoAJd2hBwwYgHv37iE/P58PhjkeHh5QqVTIyspCXFwc5s+fjwMHDhh9DKmpqdi5cyf27NmDzp07o1evXggICAAA+Pj44MMPP0RcXBx27dqFY8eOGRy3RkhN8vf3R4cOHdCuXTvY2NiUud6TJ0/w8OFDJCUl8b0kAPCZei0sLKBUKmFlZQWVSsXPbarLzc0NqampyM3NLTPgVSqV8Pf3LzVcQqPRICIiApcuXcLFixdpyjpS4zw9PdGtWzcAJcHg1q1bK70PX19fzJs3D7t37za4fWpqKhISEuDo6Ah3d3f07t0bw4YNw7p16xAbG1vh8BtuykatVlunY5J1JSUlwc7ODgqFAmZmZuXm+FCr1bh58yacnJz4zN1cmW7fvg2hUIhHjx6Veyw2NjYoLi5GUlIS0tPTMW/ePKxYsQIRERGlemDt3bsXL7zwApycnBAUFIR27drhzJkzlTo+Uosq0yGVWpL/u2QyGQICAhAcHIzg4GC9sV5lyc/PR0JCArKzs/W6qKWlpUGr1SIvLw+jR4/GiRMncOLECb5LW1ZWFj9fnbGEQiEcHR3h6emJ0NBQtG7dmu/OKpVK0bZtW7Rt2xYFBQU4efIkDh8+3GDHJ5Bnl0qlQvfu3dGnTx+DLVs3btzAgQMHcP78+UqNo09PT8eff/6JP//8Exs3bsQ777yDl19+GRYWFrCwsICrq2uZ3+c7d+4gMTER8+bNq/J4Yo1Gg6NHj+Lvv/9Gu3btMGTIEP4Ou7OzMyZOnIjXX38df//9N/788088evSoSq9DiCHW1tbo1q0bunfvbrA3hlarRXh4OM6dO4e7d+/i0aNHlb5hI5FIoFQqoVQqoVAooFKp8MUXX2Dt2rUoKCiAWCyGubm53vAgExMT2NjYGAzWRSIRQkJCEBISgrFjx+LBgweIjo7GjRs3cOPGDaSmplb5/SAEKEn4xAWUv/76a4UJHqVSKX8jNTs7G0FBQZg7dy5++ukn7N27t8ztHj58CJVKBT8/PwwfPhzr16/Hw4cPcffu3QobHSwtLSEQCCASiYz+TdZ0kKxbn9TdT1m4oRdJSUkwMTGBWCxGZmYmcnJyUFRUVO4+dFvpuYzisbGxWLduHSZPnoxJkyYhNzeXX1+j0WDdunWYO3cuACAsLAwXL16k4YL/IRQkP2OUSiU8PT3h6ekJLy8veHp6wtXVVa+7S0xMDB8kc/PSPX78GPHx8YiNjUVcXJxR3Wrs7e2hVCrLTDRhLK1Wy3d1O3XqFEQiEYKCgtC+fXu0bduWL6tcLkfPnj3Rs2dPhIeH4+rVqzhy5IjB+f8IMVZISAj69OmDNm3alGo1zszMxOHDh3Hw4MEayRCdlJSEefPmYfv27fjkk08gk8kglUqxefNm3L9/H0BJYqIlS5bwU258++23NZJwizGG06dP4/Tp02jWrBmGDBnCj1tWKBTo27cvmjVrhoyMDPz11184deoUXexJlYjFYrRp0wYtWrRA165dSw3bUavVuH79Ot9DSHeKm6ooLi5GWloafy0ICgpCdHQ0fv311wq3lclkcHJygouLC/+vv78/7O3tAZRU0r28vODl5YXu3bsDKBn7GB0dzQfPDx48KLerLCG6GjdujKZNmwIoSR5lzLQ4dnZ2kEqlyMvLg729PWbNmoXvvvuu3NwWQMlv49GjR5g+fTp+++03HD16FImJiUYNJ7C0tOR7Yhg7S0NNJe4ytL4xQTJH93wAgA9+y7vBbWVlBQD8VIqcAwcOoFWrVnj77bexbNkyvW0uXryIs2fPwt3dHUFBQXjxxRexc+dOo8tJapEagDGjyQwPlzYKBckNmEqlQkBAABo3bgx3d3c4OzvzF/bypKSk4OrVq7h06RIiIiKqnLwkIiICY8eOrdK25dFoNLh+/TquX7+Ob7/9FgEBAejatSs6duzI30m1sLDAa6+9hpEjR+LSpUs4fPgwLly4QIlYiFHMzMzQqVMn9O/f32Cr8fXr1/HXX3/h3LlztfKdunHjBtavX49x48ahuLgY/v7+/DyAb775Jn9BP3nyJI4dO1bjr3/16lVcvXoVnp6e6Nu3L7p06QKZTAatVovGjRujcePGGD9+PP766y9s27at0r1DyH+Tu7s7evXqhS5dukCpVKK4uBgajYa/+XTjxg0cPXoU586dq9XvVEBAAG7dumXUuoWFhYiOji6VdMfZ2RktWrSAh4cHOnXqpDf2mWuBbtmyJf/YgwcPoFarERMTg7t37yIiIgKxsbE1c0DkuTJ8+HD+/7/++qtRAatSqQQANGnSBH369MHXX39t9LVh3LhxOH36NL799ttKldPGxgYymaxSww1quiW5rIRPlWVubo7i4uJyW8Stra0BlLRGP/2Z/O9//8PatWvh6elZ6lzx888/Y/Xq1QCAoUOH4vDhwzU29SNp2ChIbkCEQiGaNm3Kj2/kJkLXlZ2dzZ9MgZIT0uPHjxEZGYkbN27g5s2byMzMrJHyREZGwtnZGaampnpdUGoSYwwRERGIiIjAmjVr0LZtW3Tt2pVvARMIBGjZsiVatmyJzMxMHD16FH/99RfNC0sM8vb2RlhYGDp16gSxWKxXUc/MzMShQ4dw8OBBo1uFhEIhTExMIJFIoNFooNFojP4t7N+/H0OHDoVSqUT79u2xZs0aFBYWokuXLgBK7nhXplIjFouhUqmg1Wqh1WpRUFBQYbfw6OhofP311/jxxx/RuXNnvPDCC/xzZmZmGDx4MHr16oUtW7bgwIEDla7gkOefTCZD165d0bNnTzRq1EjvOYlEwl93jh49iuTk5Dopk5+fH65du1atfXC9mwDgm2++ga+vL0JCQhAcHAwvL69SGYNNTU1hb28PX19f9OzZE0DJ9fjWrVu4cuUKTp48SRVnAj8/P74V+cmTJ0YHuklJSWjfvj1GjBiBjRs34tSpU0Zt5+LighYtWmD8+PGVKqfufMOG5mQ2Rk0Eybo5c6pTz3Ryciq3XiiRSGBpaQkABrNeZ2Rk4ODBgxgyZAiWLl2q91xMTAyOHj2K7t27w9TUFK+88orB6Y7I84eC5AbA1dUV3bt3R5cuXfjuIIbk5OTg+vXrSE9P57uBPX78uNa6THL7rak7fRUpKirC8ePHcfz4cdja2qJnz57o0aMHP6bM3NwcL7/8MgYMGIAzZ85g+/btiIqKqpOykYbNz88Pr776Kpo1a6b3eGpqKu7du4cDBw4Y1WosFAqhVCphaWkJc3NzKJVKvgKQk5MDU1NTREVFGXWTpri4GEeOHMGAAQMgkUjQrVs3pKen8+PxT58+bXSlWi6XIzg4GAqFAoWFhXzlJj8/H5mZmcjIyEBGRkaZQXNeXh7279+P/fv3w9/fH3369EHHjh0hkUigUqnw9ttv48UXX8S6dev0kpKR/y6lUomwsDCEhYXp3ZgFSr7bZ86cwcGDB3Hz5s06L5tQKKzR615xcTF/s/aXX34BUNL9lRvW5OXlBQcHh1LbKZVKtG7dGq1bt8b48eNx4cIFHDlyBFeuXKFeT/9R3MwGCoUCW7duNfp74OnpiYEDB2L79u148OABmjVrhoiIiAp7ZAwcOBDHjh2r9LA03Z4TlUmYaqglWfexqgTJ+fn5UKvV1fpNOzs7Iz4+vszn7ezsIBAIwBhDUlKSwXX++OMPrFmzBlZWVqXez82bN6Njx46QSqUICwvD3r17y9wPqSPFoO7WzyszMzN07twZ3bt3h4+PT6nnNRoNoqKicOvWLURERODevXtVvttXVdyd9Pz8/Dp9XQBITk7Gzz//jF9++QVNmzZFz549+TGlAoEA7du3R/v27XH9+nVs27aN5oX9j/L19cWrr76K5s2b6z2em5uLw4cPVzjthlAohJmZGSwsLGBpaQmlUon8/Hy9KTg4crkcAoEAjRo1QlFRkVHJfbggGSjpIqo79+W5c+eMOkahUIiQkBA+w6/u/LIKhQIKhQIWFhaQy+XIz89HRkYG0tPTkZmZabDScfv2bdy+fRtbtmzB6NGj0alTJwAl2YIXLFiAS5cuYfXq1ZWeM5M8H2xtbTFgwAD06tWr1FzG9+/fx8GDB3HixIla611kjLy8vFLZ4mtaUlISkpKScP78ef4xmUwGT09P+Pv7IzAwEAEBAfwNBLFYzE95lZmZiWPHjuHIkSN4+PBhrZaTNBw+Pj4IDQ0FUPL9+fvvv43azsvLCzNnzsSiRYsQGxsLd3d3KBQK+Pr64tGjR2UGwDKZDF26dMF7771X6bLqBsmVCU4NNZpUdQoooCR4lUgk1R664OjoWGGQDJS0mpd1vCkpKdi3bx9MTExKvefcbBKvvPIKxGIxRo0aVWr8Mnn+UJBcx9zd3TFw4EB07NixVBIhtVqNixcv4siRI7h27VqlMuzWhm7duuHRo0f1ekecMcaPr1QqlejVqxf69+/Pz3XXpEkTNGnSBPfv38e2bdtw5swZmhf2P8DHxwcjRozgKyScpKQk/P777zh27JjBu+NSqRRKpRIWFhZQqVQwNTUtlSxEJpOhuLiYb6HNyspCYWEhhEIhgoODYWJiAi8vL6Snp1dYIeCmo5BIJHB1dcXt27dRUFAAuVxu9O/K2dmZD5Dv3LmDlJQUSCQSmJmZwdzcnP8tAP8Gzdw47IKCAmRlZSEjIwM5OTnIzc3lfx/JyclYtmwZ9uzZg3HjxvHzPbdo0QIrVqzAokWL+GRj5Pnn5uaGQYMGoXPnzqW6Tx4/fhy7du3ik83VtwcPHqB9+/bYu3dvnSafKyws5G8yccl7PD090aVLF3Tt2pX/LZqbm6N///7o378/7t27hz/++ANnzpyh4QzPuSFDhvD/37Ztm1Gft1wux4wZM/D777/j9OnTAEp6LXl4eECpVCIwMBD37983GAAGBwcjOTm5SgGmbv2zqnW86na3tra25oP16maUt7S0REREhMHnuCFTubm5Fc7FvG7dujKf27FjB/r06QOVSoVOnTrh559/LjcwJ7WsCNSS/LwIDg7GoEGDSrV4AUBUVBSOHj2K48ePVzsLaE3p1asXBg8ejFmzZtV3UXjZ2dnYvn07du/ejW7dumHgwIF8MODt7Y2ZM2fi8ePH+O677+qlCyCpfTKZDKNGjUJYWJjeHe2kpCRs3boVR48eLXXBNzc3h62tLaytrSGTycAYA2NM78KuVqv5oDg9Pb3MLm5RUVHw8fGBVCqFm5tbha1EjDHExcXBw8OD/64aahEui1wuh5ubG3Jzc5GTk8Nf4DUaDQoKCvixVWKxmJ9yysLCgu8FIpfLIZfLYWpqClNTU2i1WmRmZiI5ORkpKSlQq9W4c+cOpk+fjk6dOmHs2LGwsrKCjY0N5s+fj2+++QZnz56tsJzk2WVpaYkxY8aga9eueo8XFRXhwIED2LlzZ52NNTbWrl27EBgYiFmzZuGLL76o1znAuaRgGzduRPPmzdGtWze9TPqNGjXCjBkzkJiYiF27duHQoUOV6t5Kng1ubm5o27YtgJLMy0eOHDFquwkTJiAlJQW///47/1hqaioKCgoQFBQEmUwGHx8faLXaUr2ivLy89Ho6VAb3HRQIBDAzMzM6l01NJu5yc3MDUNLzq7q5dExNTcscvuTg4MDfmK5OMJ6Xl4ft27fj9ddfBwD069cP3333XZX3Rxo+CpJrkVAoRPv27TFw4EB4e3vrPZednY3Dhw/jyJEjDWreUolEggkTJqBNmzb49NNPERMTU99FKqW4uBgHDhzAwYMH0a5dOwwePJh/f11dXbFo0SKcOHEC69evp+mjniNNmjTBu+++y3ebAsoOjs3MzGBvbw9bW1tIpVK9/QgEAmRlZaGgoADZ2dnIysrSa2EtT0ZGBnJzc2FiYgJXV1dkZmZWOAwiPj4ezs7OMDEx0ascV9RdVCgUIiAgACKRCHK5vNwbP2q1GikpKXzQLJVKoVKp+IV7D4RCISwtLWFpaQkfHx9kZGQgKSkJKSkpOHHiBG7cuIEPP/wQfn5+KCgowIcffohNmzZh27ZtFb435NkiFAoRFhaGESNG6H0Xs7OzsXfvXuzdu7fB3LR9mlqtxvLlyzFr1iwsX74cS5YsqfdM01qtFpcuXcKlS5dgZmaGjh07onfv3vyc5fb29njzzTcxfPhw7Nu3D3v37kVWVla9lpnUHN1W5B07dhjVw8HMzAxdunTBm2++Wer6k5ubiytXriA4OBhmZmbw9vZGZmam3vC3Zs2a4fDhw1Uqb05ODtLS0mBhYQE3NzeEh4cbdQ2saAooY1qlBQIBvL29+aEKNVEHNjMzKzNI5vLaJCcnV7s3x4EDBzB8+HDI5XJ0794dmzdvpoR9zzEKkmuBTCZDt27dMGjQIL0KPVBSqd+5c2eDvJvs5eWF9957D8XFxXj//fer3f2ltunOC9ukSRO89tpr8PX1BQB06tQJrVq1wqZNm7B37956LimpDlNTU7zxxhvo0aMH/1hRURE2b96MPXv26F2UTUxM4OnpyU/1oLt+cnIy3326Ol00o6KioFKpIJPJ0LhxY9y8ebPcYEImk/HZsY0NkkUiEfz9/fkkX1FRUZUaflFUVKQXNHOtBebm5rCxsYFKpYJQKISVlRWsrKxQWFiIhw8fIjExEXPmzMHrr7+Ol156CQAwatQoODo64ptvvqFkRM8Jb29vvP/++/Dw8OAfy8nJwa+//ooDBw40uGuTIbm5ufj4448xcuRILF++HD/++CP++uuv+i4WgJL3kkuUFxISgoEDB/K9yJRKJYYNG4aBAwfi6NGj2LFjB83B/IxzcHDgcztkZWXhwIEDRm0XEBCAe/fuldlTo7i4GLdu3UJoaChEIhG8vLz0uhR7e3tXuSWTMYasrCxYWVnB0tISAQEBuHPnjlHTVenuAyi/JVkqlcLJyYnvVi2TyWBubs6PY87MzDSYbbqyzMzMDOZJkEqlfO+tmmg0ycvLw+HDhxEWFgaZTIbevXtj+/bt1d4vqQJK3PVsMTMzw4svvoh+/fohNTVVL0COiorCjh07GuS4JJlMhpEjR+KFF17Ajh078Ntvv1XqRFkXnJ2d4ejoiOTkZIOt29y8yy+88ALGjx/PTyvw5ptvIjg4GKtWraK5YJ9Bzs7OmDdvnl5m2Zs3b+J///ufXsVSKpXC09OTz2AJlFQwkpOTkZycXGPTonH7jYiIQNOmTaFWqxESEoJ79+6VmemSC261Wq3eXfiygmSpVIqQkBC+AhIXF1fhOKqKMMaQnZ2N7OxsxMbGQiaTwdbWFra2tlAqlZDJZPDz84OLiwuio6Oxdu1apKenY9SoUQCAnj17ws7ODkuWLKHf0TOud+/emDBhAsRiMaRSKQQCAQ4ePIg1a9aUebPH0tISLi4uEIlE1Z56qSYxxvDTTz/h5s2beOedd9CtWzd89dVXDap31o0bN3Djxg0+H0mnTp0gEokglUrRtm1b9OzZE2fPnsW2bdsazJhvUjkvvvgif27ftWuX0TeZ3N3dK8yQXFBQgLi4OLi5uelNl6RSqSCXy6s1JvbRo0cwMzODjY0NrK2t0bJlSzx58gRJSUnIy8sz2LKsGxBXFCRbWFjAy8uLv9nL5efgpKamIjIyskbyyOjO167L3Nyc/39N1QN2797Nf+ZhYWHYuXMn3UB+TlGQXAOsra3Rv39/9OnTh79jJZFIoFarcf36dezYsaPBjpFt2bIl3n77bSQmJmLy5Mn13mWtLDY2NjAxMSk1FYmlpSW6dOmCgIAAuLu7w97eHgKBAEqlkq/Mt23bFh4eHliyZAllGn2GBAUFYc6cOXym6fz8fKxfv77UXXoTExMEBwfzY3zVajUePXqE+Pj4WrshlZOTgxs3bsDX1xcikYjvnmyo+6RuV6yKgmSBQICAgAB+TPHDhw/1MmLXlMLCQsTGxiI2NhYqlQpeXl58IrOgoCBER0dj27ZtePLkCT744ANIJBI0adIEX3zxBRYuXEgtX88gmUyGiRMn6o09lkqlKCwsROfOndG8eXPExMTgwYMHOHHiBO7evcuvpzvHqFQqrfekkk+7du0a3nnnHQwfPhwrVqzArl278Ouvv9ZpUq+KxMTEYOXKldi0aRP69euHF154AZmZmTA3N0eHDh3QoUMHXL16Fb///jvCw8Pru7jESEKhkG9FVqvV2L9/v9HbBgQE4MaNGxWuV1BQgMLCQr1g0szMDEVFRdX+jkdGRsLNzQ1ubm58gklumFJmZiYeP36sN9NBZcYkW1tbw8zMjG+1Li4u5oc7ZWRk1OhwjqSkJNja2pZ6nLuW1sR7xXny5AkuXLiA1q1bw9raGu3atcPJkydrZN+kEtQAjKniCStepSwUJFeDk5MTBg0ahK5du+rdwdJqtTh37hy2bdvWoO5o63J0dMQbb7yBgIAArF+/vsrjWuqCWCzm76By3WW4O/BNmzZFeHg4Ll26hL179+LRo0f8GNEWLVpg6tSpMDU1haOjI5YtW4aVK1fyGSRJw9WtWzdMmjSJ/11FR0dj4cKFpbplmZubIzAwEGKxGIwxxMbG1llG9qysLNy8eRPNmzeHRCJBQEAALl++XOpCrBsk654nDCXu4oJVoGS6nbi4uFoq/b+ysrJw7do1WFtbw8vLCwqFAp6enpDJZDh16hRSUlLw0UcfQaVSwdXVFStWrMDnn39O0649Q6ytrTF//ny4u7vzj+3evRs//vgjNBoNZDIZXF1d4e7uDn9/fyxYsAAZGRk4fPgw/vrrL6SlpYExBoFAAGtra6PmCa9rRUVF2LhxI44dO4ZJkyahc+fOWL9+Pc6cOVPfRdOTmpqKH3/8EVu3bsULL7yAAQMG8K1dzZo1Q7NmzXDnzh1s27atykmZSN1p0qQJfwPp4sWLRo9PNTc3R9OmTfHNN99UuK6FhQVkMpneeOTyxuBWBmMMMTExSElJgbOzM+zs7KDRaPTyV0RFRRlssa4oSOZ6JBYVFdX69SI5ObnU8Ebg3wRlEomEnye5JuzatQutW7cGAAwYMICC5OcUBclV4OPjg8GDB6Nt27Z6d9WKiopw6NAh/PHHHw12knETExMMGzYMffv2xeHDh/HWW281+OQhNjY2/PtcWFiI2bNnw9fXF/v27cM333xT5niWS5cu4f3338esWbP4jMQzZszA6tWrjc48SeresGHD8Oqrr/J/X7p0CUuXLi2VwZZrQRYKhdBoNIiMjKzzRG2FhYW4desWQkJCIJVK4e/vX6rXiG73ZN0kYk9PPWVjYwNnZ2cAQGJiYp0EyLpSU1ORmZmJoKAgqFQqODk5QaPR4Pbt25g2bRo+/vhjuLi4wMzMDJ988gnWrVuH3bt312kZSeU5ODjg008/5SuQBQUFWLVqld7NwsLCQkRFRSEqKgpHjhzBmjVr0KZNG7zwwgt48cUX8cUXXyArK4vPFN8Qg2ROTEwMpk+fjh49euCtt95CWFgY1q5di+jo6Poumh4uU+7u3bvRo0cPDBw4EPb29gAAPz8/zJkzB48fP8b27dtx/Phx6s7ZQHXp0oX//7Fjxyq1XWRkZIWZ421tbfnfrm6LrqmpaY3OVZ6bm4u7d+8iKioKJiYmMDc3h5ubGzQaDf+b526UcSoKkrlrn0wmg1wur9Us9A8fPkSzZs1KPc6VgbvBVxPjnwEgPDwcDx48gJeXFxo1agRnZ+c6v2aT2leNRuj/Hnd3d8ybNw8rVqxAu3bt+JNFbm4ufvvtN4wdOxbff/99gwyQBQIBevfujTVr1sDT0xNTp07Fd9991+ADZAD8eFQbGxt88cUXEAqFePfdd/H7779XeMJLSkrCzJkz+aBYIBDg/fffR1hYWK2Xm1TekCFD9ALkvXv34tNPPzV4cbWzs4NQKIRarcaNGzfqLZN5ZmYmXwG3tLQslTRM9+5/WUGyUCjkM7Tn5ubi3r17tVnkMj39Xtra2kIsFuPJkyeYNm0aLl68CKDkdzRu3Di8//77emPMSMPi4uKCzz77jK9kJyQkYPLkyRX2pikuLsbJkycxe/Zs/PHHH1i4cCF/U9jCwoIfVtSQHT58GG+++SZu376NL774Au+++67e+MSGori4GPv378eECROwbNkyvSFBrq6umDx5MtasWYNu3brVXyGJQTKZDO3atQNQ0mOIOz9WJCAgACNGjMCOHTvKXEcgEMDV1RWNGzcGUHId0R2zXlMtyU/TarXIyclBXFwc7t69C7lcDnNzc354kKHs1lwSLm57TlpaGrRaLRhjfIbp2nLp0iXY29uXms0iOzubv5nQqFGjGr1eHT16lP9/hw4damy/xEjFlViqiIJkI1hZWeG9997D6tWrERoayj+enp6ODRs2YOzYsdi8eXODDTgDAwOxatUqDBw4EKtXr8bcuXMb5NROhpiYmMDS0hK9evXC66+/jh07duDTTz+t1FiW4uJirFq1Sq/V680338TgwYNro8ikivr06YPXXnuN//uHH37AmjVrDI4rFovFcHV1RXFxMWJjY+t9qprY2Fjk5uaiqKiIbw3i6AbJul2sdYNkW1tbvpt2VFRUvSb302q1uH37Np9khZvfOS8vD59++il+++03ft3u3btjyZIlfHdD0nB4enris88+g5WVFYCSJD2zZs2qdKKfPXv2YPr06WjatCnGjx8PS0tLvUR6DVlBQQE2bdqEd955B6amplizZg0GDhyoV6lvKLRaLU6cOIH33nsPCxYswK1bt/jnbG1tMXnyZHz55ZcICQmpx1ISXW3btuXP6adOnTIq4amvry/mzp2LH374AZcuXTK4jkQiQUhICNzd3VFYWIj8/HxERETo9SYwNTWt9SSKuq9n6NgMdV3WvXZpNBo8efIEjDH+OlJb4uPjIRaLS/0+GGO4c+cOGGP8sKine3FVhkqlgoeHB/z8/HDhwgX+8fbt21d5n6ThoiC5HHK5HCNGjMCaNWvQo0cP/g5aUlISvv76a4wbNw47duzQqwQ3JDKZDG+99RbmzZuHv//+G++8847ej/pZ0Lx5c0ycOBG+vr547733qjWd0w8//ICtW7fyf48aNQp9+/atiWKSaurRowcmTJjAV+DXr19fbldelUoFgUAAiURS7czPNeXRo0eQSqWwsbHRa2krqyVZ9468nZ0dzMzMkJ6eXqOZuKtKrVYjOzsbIpFIL6MqYwybN2/G0qVL+eRNvr6+WLlyJT/9Gql/Dg4OWLhwIf/ZRUVF4cMPP6xwTu+yREdH4/3338e9e/fw/vvv46WXXqpWRbOuJSYm4rPPPsPChQvRtWtXLF++XG/6q4bm8uXLmDVrFmbOnInLly/zj3t5eeHTTz/FvHnz4ObmVo8lJAD0kuD9/fffFa7fu3dvLFq0CFu2bMHBgwcNriMSiRAcHAxzc3MIhUKkp6fjypUrpQJigUBQ613wda9jXJBsqLt1edLT0yEUCqFQKGq9B8qlS5fQokWLUo/n5OTwDUNKpRJ+fn6VPn9JpVIEBgaiadOmcHNzg729PVxcXPgEhx4eHnBycqr+QRDjFVViqSIak2yAUChEz549MXLkSL3uWbm5udi6dSv27t3b4KZIelpwcDDef/99JCYm4t13363zQIKrXJuYmMDU1BQmJiZ8VtSCggJ+0Wg0EAgEEAqFEAgEkEqlcHFxgaurK9q2bYumTZvi1KlT2Lx5c42MKduyZQsKCgowevRoAMCECROQmppKCVLqUYcOHfDuu+9CIBDA0dERGzduxM6dO8vdRvcC11Ay2Oq2ZkulUr6LuG7lRreSoHsMXGtETY4xqy7ufTVUmTh16hTi4uLw0UcfwdbWFlZWVvjss8/w1Vdf6XVBI3VPpVJhwYIFfIAcGRmJBQsWVLvVqbCwECtXrkRcXBwGDRqEjh074tChQ3j06BEePnyI7Oxsvmsl15okl8v1FsYYcnNzkZeXh9zcXGRnZ9fpnMzh4eGYPHkyhg0bhmXLlmHbtm34/fffG+x4X+6zCw4OxtixY/khGaGhoWjevDkOHjyIn3/+uco3P0jVWVpaomnTpgBKGk4iIyMBlHznAwMDkZaWBhMTE8TFxfFjiWNjYzFnzhy9zPFP8/b25qdMio6OLnd2A0Ndn2uSUqmERqNBXl4e/5vWfU1DPZ6eLpPuTV+lUlmr45IjIyPRr18/g889evQIYrEYVlZW/DCiiIgIo3ptOTg4wNHRUW92FbVaDZFIhIiICP4GcatWrSqsu5BnCwXJT2nRogVef/11uLq68o+p1Wrs27cPW7durZUxIDVt6NChGDRoEDZs2IA///yzzl5XpVKhRYsWaN++PYKDgyGXy1FUVMRXigoLCyGTySCTyfi7ikKhkK9UabVaaDQaxMbG4vbt2/j777/x559/Ij8/v0anwdm+fTtMTEwwZMgQCAQCTJ8+HXPmzMGdO3dq7DWIcVq2bImpU6fyF9bdu3dj+/bt9VyqqtG92OoGlsZ0t+aOvyFV1iuqgEVHR+ODDz7ArFmzEBQUBLFYjMmTJ8PLywvr169vcPPB/xfIZDLMmzeP79oYExNTIwEyh8uEHhUVBQsLC4jFYrRv3x4jRoyAiYkJf7OT+25zXUW5KWwEAgF/05SbmiUqKgpnz57FpUuX6iS5lkajwZYtW3D27FlMnjwZoaGhWLBgQYO+tt+8eRMffPABunTpglGjRvHJLHv37o3OnTtjx44d+OOPP+r0hsN/XadOnfhzpG4rsru7O8RiMZydnSEUCmFtbY2srCw8fPgQERERZe5PIBDAx8cHDg4OyM/PR0pKSrn1Hq1WW6tBskAggJ2dHUQikV5yMUPzJJdHrVbXamCsKzk5uVROEF0PHjyAUCjkh/G1atUK0dHRBhuRuOzeLi4uMDc3h0ajQVFREeLi4hAbG4vAwEBYWVnp5SAKCgqiIPk5Q0HyPzw8PDBu3LhS4xlOnTqFTZs2PTPzgo4cORI9e/bE1KlTa2V+VUOaN2+OsLAwNG3aFNevX8fNmzfx008/4fHjx9Wq9IeGhsLU1BQ5OTk1XoH56aefYGNjg65du0IqleLjjz/G9OnTKz1ej1Rd+/btMXXqVH584MGDB7Fu3Tqjtq2paRxqkkgkQl5eHhhjeq3bxgTJubm5pTKHNhTlvddZWVmYO3cuxo8fzw9d6NevHzw8PLB8+XJq4apDQqEQM2bMQKNGjQCUZCufP39+jY9bfPLkCby8vJCWlobLly9j27ZtVd6XpaUlmjRpAn9/f3z++edISUnBgQMHcPDgwVofxvTgwQNMmTIF06dPx6JFizB79uwG1ZPDkGPHjuH06dPo168fhgwZAhMTE8jlcrz66qvo06cPNm/e3KCnc3yetGzZkv+/blZrLidFTk4ORCIRFAoFVCoV/P39UVBQgJiYmFLnRVNTU/j5+fEtyLm5uRXeMKrt64VSqeSvzbpZtcvKZM15ukxcZmvA8LjmmpSamgorKysIhcIyb9JGRUVBo9HA1dUVUqkUfn5+8Pb2RnZ2NvLy8vhhXFZWVnq5C3Jzc3Hnzh3+vPTkyRNYWVkhOzsbjx49AmPM4BRUpBapARgTYlQjBcV/PkgWiUR45ZVX8Morr+j9IG7fvo3169fj9u3b9Vi6yrG0tETnzp0xe/bsWk9FLxaL0aVLF36Ox7179+Lbb7+tcDoDY9nY2MDU1BQAam2u6dWrV8PKygpNmjSBUqnEggULMG3atAYxJvR5FxYWhvHjx/MX1OPHj+Prr7+u0r4aSmApkUj41jHdm0O6lX3d7ta65RaLxTAxMTE4d3JDp9Fo8N133+HBgwd46623+OQp//vf/7By5Uq9MZWk9rz11lt8xT0vLw/z589Hampqjb9OfHw8XF1dIZFI4OHhUW7rWEXS09Nx7NgxHDt2DOvXr0fr1q3Rr18/DB8+HAcOHMDu3btr5Rg4arUaS5cuxfz589GxY0f89ddftfZaNaW4uBjbt2/HoUOHMHToUPTt2xcikYhPMNqlSxesWrWqxq7FpDSxWAx/f38AJV2tufoWNw+vQCBAXFwckpKSYGdnBzs7O1haWkIqlSI4OBhqtRqZmZlQq9V89mhOUlJSud2xOYyxWs0LoHt90r3pa6i7dXk3Um1tbfl1ajvBZlpaGp+Bv7zZLqKjo5GSkgJvb2+oVCqIxWL+8+HqnZy8vDzExcWVmvaOy9wtFAqRm5vLZyF3c3OrtTorqXvPTuaNWuDp6YmVK1di+PDhfICckJCAJUuWYMaMGc9UgAyUTCuQnZ1d6wFyjx49sG7dOrz88svYuXMnxo4di61bt9boRZlLqpKTk1Nj89o9TaPRYMmSJfyUG/b29pg3b94zGag8KwQCAUaNGoU333yTv9gePnwYX375JRhjsLKygo2Njd7Yn2cFFyAzxvikVoBxY5K57mjcPhoCW1tbhIWF4aWXXip3PZFIBDs7O1y/fh3z5s3jKycqlQozZszA2LFjaZqoWjZkyBD06dMHQEngt2jRolqbwUCr1fK9lKytrfnWr+oqKirCyZMnMX36dMyfPx/29vZYu3YtJk2aVGOvYYhGo8HFixf1Zq54FmRlZWHt2rV45513cPbsWf7xkJAQfP3113jhhRfqsXTPN19fXz4J482bN/nHGWPIyMhAXl4eZDIZGGNITExEeHg4bt++zd8wFYvFsLa2hr29PczNzVFUVAS1Wo07d+7g9u3bRg1Vqe2WZN0yiMX/tqdV1N1at0xyuZxPMJeWllbrLckajQaZmZlGTTeVnZ2Na9eu4fr163j48CFSUlKQk5ODrKwsZGVlISYmBpcvX8alS5cMzguv1Wr5a53u8wEBATV3QKR8dTAF1H+yJVkkEmHo0KEYMmQIHxxrNBr8/vvv+O233xp8Uq6yuLu71+rUTo6Ojpg0aRIcHR3x7bff4ty5c7XyOg4ODnywUNtTVXEtLsuWLYONjQ18fHwwc+ZMLFy4sEF26X2WmZiYYPr06QgNDcWjR4/g5uaGrVu3YsuWLRAIBPD19YWDgwNycnJgZmaGiIiIMluRRCIRbGxskJKSApFI1CDG8nIVed0kJ4Bx3a254QSmpqZ8a0R9cXd3x5AhQ9C7d2/cuXMHp06dKnNdgUCAFi1aQCgUQiKRoKCgALNmzcK4cePQqlUrZGRkYMCAAWjevDk+/fTTZ2bYyrOkS5cuelOnffnll3oV99oQHx8PFxcXSKVSeHt74/r16zW6/9u3b+Ozzz6Do6Mjxo8fj2+//Rbff/99ud/F6oiJiUFYWFit7Lu2xcfHY8mSJWjSpAnee+892NraQi6X4+2330b79u2xevVqvXGTpPqCg4P5/4eHh+s9x4151b2xwxhDUlISkpOToVKpYGFhAXNzcwgEAhQUFCA5ORkZGRmVyuPAtWLWlsLCQv465OLiwudsMdTd2tD1ytTUFIGBgRCLxdBqtXWSb0C3TMbKzMyscu/BrKwsWFpa6h1bYGDgM9EjhRjnP9eS7O7ujpUrV2LYsGF8gPzw4UNMmTIFP//8c60HyCNGjMAbb7xRK/u2t7c3eMeruoRCIQYNGoTVq1cjJiYGEydOrLUAWSaTwcvLC0DJCag2u9px0tLSMG/ePH48WosWLTBy5Mhaf93/EicnJyxfvpxvrXF2dsYXX3yBLVu2AABcXV35uVcVCgX/WFl8fHzw3nvvoUePHnpd1eoL15oKoNR86Wq1mj+vcMcG6Fc2uG2EQmGpeZbr0ssvv4zly5cjOzsby5Ytw2+//VZuwGVnZ8cn4wP+bTlYtGgR/ve///F39N3c3LBs2TKaJqqGeXt749133+X/3rhxI06cOFHrr6vVavkbmObm5rU2B2pCQgI++eQTrFmzBhMmTMDcuXPLTcxTVfHx8bX2u/P29sbatWtrZd+6rl+/jkmTJulV0ENCQvDVV1+hd+/etf76/yW6QbLu+VEkEundLH0aYwyZmZmIiYnBjRs3cP36ddy5c4fvutuQFBUVITo6GkVFRbC3t4evry8EAoFRU0A5ODigadOmfEb7u3fv1vqczhypVFpnM15IpVKIRCJkZmbySfOoJfn58p8Kknv37o0VK1bwXXk1Gg1++eUXfPDBB3V2lys5ORnu7u61sm+FQlHjJyKJRIJZs2ahR48e+Oijj7BmzZpazVTo6+vL33msy2zTjx8/xuLFi/kL1ZAhQ9CuXbs6e/3nmbe3N5YvXw5nZ2cAJd2c5s6di5MnTwIoqVhYW1ujsLAQaWlpePDgAQDwY4UMOXPmDFasWAFvb298+eWXaN++fd0cTBlcXV0hFovBGDM43IFrTS5rTHJOTg5/N9vNzU0vP0JdkEgk+OCDD9CvXz/MnDkT69evR3p6OvLz80sF/bqsrKwAlNyNv3XrFjQaDdRqNezt7XHo0CFMnjyZ75qrUqmwePFitGrVqk6O6XmnUqkwZ84cviv7X3/9VaeZ4RMSEvjvrJeXV63OgXry5Em8/fbbyMnJwfLly2v8Gpqfnw+BQFArQ23c3d1rbcjQ0/Lz8/HNN99g7ty5/PAnuVyOd955B7NmzWpQwzmeVbrjkZOTk/Va6Rs1asSfu2t72s3abkkGgLi4OL6+5+DggNDQUL2bVE+3JItEIjRq1Ag+Pj4QiURQq9WIiIio054MUqm0RrK8d+vWDe+9957ejW2OQqGAv78/XFxcAJQkNuPqq7a2tkZ19yY1oA66W/8ngmS5XI5p06bhnXfe4SsUXOvxL7/8UqddNTMzM2ttvKVCoajRjKAKhQLz58+HpaUlpk+fXutBq6OjIywtLQGUfD61nd30aTdv3tTLrjx58uRyWzNJxRwdHTF//nw+GUZMTAw++OADvS5qVlZWUCqVkMlkePDgAZ9JU61Wl0qioev+/ftYs2YNTp06hXHjxmHFihVo0qRJrR6PIdbW1vy4q5SUFIM3qrjvsm4l9enzDtcyJ5fL+UpYXRCJRPjkk0/g5OSEKVOm4P79+7C2toZcLodCoSg32QoXGGVmZvJjuszMzPhW9cePH2P69Ol8a4tUKsWcOXPq/abGs04oFGLmzJl8ZSwyMhLff/99nZfjzp070Gg0EIlE8PPzq9Uxkjk5OVi5ciX279+Pzz77rEZ/I9zv01CFuLrMzMzqPBnk9evX8c477+i1Krdr1w6rV6/m51omVePj44OsrCxotVq965iTkxNff0lISChVf+ESWNWU2k7cxb3GjRs3+GEyJiYm8PHxgYWFBUxNTWFmZgZzc3OYm5tDqVTC3NwcKpUKeXl5yMrKwtWrV8tNoFUbpFKpXk6Qqrp+/TpsbGzw5ZdfwsfHB0BJT0dfX18EBQXx17icnBzcunULt27d4rcNCgqq9uuThuG5D5I9PT2xatUqvhILAHv37sXUqVPrrPVYV23e/ZPL5TXWyqtSqbBkyRIUFRXho48+qvU5JK2trfkTUVZWFmJjY2v19cqyZ88efs5DuVyOjz76iO6+V5GlpSUWLlzId4e+desWpk+fXuqusm6Xrfz8fH4Ri8VQqVRl7j8lJQWMMURERGD27Nk4deoUZs2ahU8++YT/LtU2MzMzvrKen5+Pe/fuGVyPC5x1v0tPdwnLyMjgs2JaW1vzww5q28CBA6FSqTB79mykp6dDJBLxLXVZWVllVjjEYjGUSiU0Gg3f2mzo/JOXl4d58+bx3YAFAgE++OAD6npdDa+//jrf5TMtLQ2fffZZvYzLLygo4K+j5ubm8PPzq/XX3Lp1KzZt2oRPPvmkxpJtcT0gaqM1vLzpaGpTQUEBvvnmGyxatIgfSiSRSLB48eJndvx1Q9C0aVPY2NhArVbzmftVKhW8vb0hFAqRkpKCqKgofn13d3fMmTMH33zzTbnXs8qqq1wcXHfpiIgI5ObmQigUQiQSQS6Xw8HBAUFBQXBycoJUKoVAIIBGo0F8fDyuXbtW5w0dXCNYTQTJqamp+Pjjj3HgwAEsWbIE48ePR8uWLeHg4MAfZ0xMDK5fv46ioiLcuHGD37ZFixbVfn1ihKJKLFX0XAfJvXv3xrJly+Do6Ah3d3c8fPgQS5YswZo1a+pszMLTajNItrOzq5F5Sc3MzPD5558jNjYWn376aY10XSmPubk5GjduDIFAgMLCQkRGRtbq61Xk66+/5rv8Ojo6Ytq0afVanmeRiYkJFixYwN9tffjwIT755BODQZRukMx1VeO+c+WNN05KSuIrfx4eHti9ezfGjRuHqKgoLFmyBD169Kix4zFEoVAgJCSEr6xERESUmdOAqyzIZDK+tc3Qug8fPuTH4bu4uNR6TwY3NzcMHToUX375JX9O9PDw4LudlncjkftsRCIR/zlw57anx6qp1WosW7YMR44cAVByt3/u3Lk13rryX9C5c2f0798fQMn7+tlnn9XrfNTx8fF811I7O7s6aancv38/Vq1ahVmzZtVYhTQ9Pb1W5jkViUT1Ot70/PnzeO+99/iWLoVCgTfffJO6X1cR11tJKpXy76lYLIZarYZCoUBcXBwYY3BwcMCUKVOwfPlyJCUlYfz48eUOXaksiURSp/XY1NRUXL58GVFRUSgoKIBWq9Xrbq1Wq5Gbm4tbt27VW4JG7rpVk3XWffv2YdOmTejXrx/GjRsHExMTJCcn4/z584iJieFvVERGRvLXwebNm9d6Kz+pG8/lpyiRSPD+++/rda+OiorCp59+qjdVQn2orSDZyckJZmZmZbZkGUsoFGLGjBmIjY3FsmXLav1OpVKpRGBgIIRCIYqLi3Hz5s1aD8orUlRUhEWLFvHdTFu0aIGhQ4fWa5meJRKJBHPnzuXH/iclJWHevHlljpfXvdvMJT3hAkVu7kJDGGO4c+cOGGOQSCTw8fFBbm4uNm3ahPnz52PcuHHo169fDR7ZvxQKBZo2bYrCwkK+2115+QC431FZc0/qioyMRFZWFgoLC+Hq6sqPe6oN48aNw759+/jzhrm5OZycnADojzk1hEu0lpeXx3+G5SWtAYCvvvqK76Jobm6OuXPn0vRQleDu7q6XqOv7779vEFMV3r17l+9W6ezszP/2a9Pp06exatUqTJs2rUZ+I+Hh4bXSTVIoFNZ79v3k5GTMmTMHx44d4x9r164dVq5cWavnl+eNTCbjew7FxcXxY82trKwgkUigVqvRrFkzzJw5E99//z2Ki4vx9ttvY+3atfwwoppS10EyJzs7G7m5uUhPT8fdu3dx+fJl3Lt3D5mZmSgoKKjX2WG4ukJNtCQDJdf5Zs2aITMzE6tXr0ZKSgpee+01mJiYlDpOjUaDq1evAii5DlJPqefDcxckW1paYvHixejevTv/2J49ezBz5swGMQ1CbQXJISEhuH37drVPmi+//DKsrKywYsWKGipZ2VxcXNC0aVOIxWJoNJoKA426lJycjM8//xyMMSQkJGDgwIFo2bJlfRfrmTBhwgQEBgYCKBmr+vHHH5fb0pWXl4fi4mIUFRXxLRuJiYnQarUQCATlZs7NycnhE2XZ2dnx3YQjIiLw0UcfYejQoRg2bFhNHRqAkspJSEgIJBIJFAoFwsPDKxxzyLWQGxMka7Va3Lx5EwUFBRCLxfDy8uID0prk7OyMwMBAPtmTiYkJAgMDIRAIUFRUxPemMEQqlfJJu7hWAy7Y1Wq1Zb4fGo0GixcvRnx8PICSVushQ4bU2DE9z8zMzPDRRx8hISEBjDEcPHgQBw4cqO9iASi5YXXr1i2+pczNzQ1BQUG1fgPk1KlT2LdvHyZOnFjtpFs3b96slZwG9dXd+mkajQY//vgjPv30U77Fy9HREcuXL6fuoUYKCgriz+W60549ePAADx48gK2tLd5//32EhoZiy5YtOHHiBEQiUa3U+cRicZXreyKRCM2bN4e/vz8sLCwqta3usajVahQUFFS5HBKJBM7OzmjWrFmN3KyRSqVQq9U1MoWiTCZDo0aNIJVKodVqERERgWnTpmHTpk2YN2+ewRtqly5d4v9P9cU6oIZxSbuqcd/muQqSfXx8sHLlSn5cVFFREZYuXYq1a9c2mLmPtVptjWeuFYlE6N+/P58tuKo8PT0xfPhwfPHFF7U6lkQsFiMoKAheXl4QCAQoLi5GeHh4uQmC6sONGzewZs0aODo6QqFQYMqUKbUSrDxP/P390atXLwAlY+Lmz5/PB0TlycrKglQq5ROfqNVq/i49NwaoLNHR0fxdend3d74Lb1RUFD788EP06dMHo0ePrs5h6WncuDFkMhkYY4iMjDSqhYCrWAiFQv4CXt45ieu+zVVmfXx8yk1iVhV9+vTB6dOn+fded07LiIiIclu/nJycIBAIoNVq+SBZqVRCoVBAKBSW+1vOycnB4sWL+eMfPHgwJcgzwtSpU2Fvbw93d3dcuXIF3333XX0XSQ/Xo4K7IWZlZYXQ0NBKV8Ir66effoJIJKr2zbCLFy/C09OzxsdV13d366dduHAB77//Pj+UQqFQYO7cuRg0aFA9l6zh072Johska7VaODg4YOjQoTh48CC+/PJLPHnyBGKxGL6+vmjdujXc3d1rtO5X1ZZkiUSCJk2aQCqVws7ODiEhIWjVqhV/07MiukGyoWDUmOR9XBbsNm3awNvbGyqVClZWVtUeqiGTyWqkFVksFiM4OBjm5ubIy8tDZGQkX485cOAAvvvuO3z88cdo3Lix3nbcGHWAguTnxXMTJHfu3Bmff/45/0NPSUnB9OnTcerUqXoumb7aaEl+5ZVXkJCQgEOHDlVrP++88w527tzJZ9mtaVKpFJ6ennon5IyMDFy6dKnOs38aa9++fTh9+jQAwNTUFLNnz66VaUKeByKRCO+88w7/98aNG3H//n2jtuUSw+lmfucuSjKZjO8CbAjXipWXl4e8vDz4+fnxFfNHjx5h1qxZ6NOnD9q0aVPZQyrFw8OD33d0dLTR83hzv3ljWpI5arUa4eHhUKvVEAqFCAgIqNFKVqtWrXDy5EkIhUIEBgaCMQaNRoPIyMhyg1zu7j9Q0uOCC3a5z664uLjCIROPHj3iW7DFYrFeF2JS2vDhw/kkVVlZWfjqq68azI1fXWq1Gjdv3kR0dDQYY5BKpQgJCUFgYGCtBsvffPMNXnrpJb0EnZWVmZmJn376CWPHji1ziEdVNJSWZF1JSUmYMWMGf20TCAQYPXo0pk6dSsMfytG0aVMA/2Z95gQHB+Ptt9/GsmXL8O233+Ls2bO4desWfx6USCRwd3dH69at4eLiUiN1wKoGyTKZDGZmZjAzM+O/l3K5HEFBQWjUqFGFZdO9hlXle61SqRAaGgpHR0cIBAIwxiAWi2FhYcEP16mqmsps7ePjAxMTEwgEAjx+/LjUdf7o0aNYu3Ytpk2bptdwkpmZyQ9d8vDwqJU53YkOmgLKOMOHD9c7uUdGRmLy5Mn1kr26IjUdJDdv3hwvv/wyNm7cWK1xTy1btoStrS22bt1aY2UDSk6oKpUK/v7+aN26td58sg8fPsSNGzfqLYmasVatWsVn2/bw8NALBMm/unXrxt9AiIqKwp9//mn0tlyQLJVK+QpqVlYWP86xormD1Wo1bty4AbFYzAeUXMvrkydP8PXXX+Pdd9/lW6qrwsLCgq+Ep6amVioDe0pKCuLj4/WmwzAmyCksLOTHnCoUihob5ySVSiEWi3H37l00btwYSqUSJiYmePDgQYWBP/dZMMb0bqhxFRxje4T89ttvfFd5f39/dOvWrYpH83wLDQ3F8OHDAZRUzpcuXWr0zZn68vjxY1y/fp0PEqytrRESEoLmzZvDzs6uzPnPqyomJgYHDx6sdmvyn3/+Ca1WW6PneC4QaGgKCwvx+eefY8uWLfxjnTt3xmeffVbtYOV5pFKp+LH2UVFRfC8fd3d3zJ49G1u2bMG5c+cAlPxOU1JSEB4ejsuXLyMxMZEPBr28vNCqVatqZ7quapDMbVNUVITw8HDcvHmTH+bm6OiI0NDQcstmKEhWq9XIysoqdxYUgUAAT09PNGnShM8iHx8fj/Pnz/NDIasb4NbEHMkqlUpvCsOy5rs+dOgQzpw5gzlz5ug1nFy8eJH/Pw1jePY980HymDFj+AoEUPLFnT17do1mEaxJFhYWNVY2MzMzTJ06Fd988w1fWRUKhVAoFDA3N4etrS2cnJzg5uYGd3d3uLi4wNHREfb29rCxsYGlpSVUKhVMTU0xZMgQ/Pnnn1VuneBe18LCAg4ODvD29kZAQADat2+Ppk2bws7Oju+emZCQgMuXL/PT3TR0BQUFWLRoEZ+ZuUuXLlShf4qJiQnGjBkDBwcHJCQk4Ntvv61UxZCrcAD6c5VGR0ejqKgIxcXFFY5Z4i76Go2G79LPBdanTp3CpUuXMHLkyEoe2b88PT0BlHwfKjtnuKWlJZycnPSyORtbwUlLS8Pjx48BlMy1WRMVWIVCAVtbW9jZ2fF3u2NjY5GQkFDudnK5HNbW1sjLy0N8fLxetnLuczM2r0BxcTG+/vpr/u9hw4bV+FCUZ52lpSU++OAD/u9NmzbptWA1ZFlZWbh06RLu37/PV1y5KdPatWuH5s2bw8/PDy4uLrCysoKpqWm1WjH37NmDdu3awd3dHUqlEhYWFrC2toatrS0cHBzg7OzMXwudnZ1hb28PS0tLmJmZ8UG7RqPB0qVL0axZM3Tu3LnG3ofysvTXt61bt2Lx4sX8b7lRo0ZYvHhxjU5X9Dxo1aoV/3+uq7WlpSXmz5+PP/74A0ePHjW4XW5uLu7cuYPLly/zQ4ikUimCg4Or9R5XNUjmrqdAyZCI9PR0XLlyhe+5xc3aUNYNZUPdrYVCIVQqFczMzAw2AgkEAjRu3Biurq78LCY3btxAVFQUNBoN//vQrQdUVXUza3NdvgsLCyvsVfnjjz8iMzMT77//Pv+Y7rjkTp06VasspP7V7O3cOjZ+/Hi89NJL/N/r16/Hzp07669ARrC3t6+wImqs119/HTExMXjw4AECAwOhVCr5Vrjc3FyjxzA6OzujZcuWOHLkCDp27AiNRsPPG6lWq6HRaMAYg0AggFAohEAg4BehUMi3Sj0tLy+PP2EWFxcjPj4e8fHxDb7l2JC4uDisWrUKM2fOBAC89dZb9TrVQUMzcOBAvrvtnTt3Kp1lvbCwkP+OyeVyvvs9l0XT3t4eLi4uFX5/cnJyEBkZicDAQMhkMnh6evJzVm7YsAHr1q3D1q1bK53Ez9LSkj++6OjoSt9M4tbnfj+MsUr9DmJiYuDg4MB324uIiKjU6z+NC2i5rmIpKSnlJuriuLu7Qy6XQ6PRlLrJxbUOVCafQXh4OK5du4aQkBDk5+ejXbt21c6t8DyZPHkyX5E+f/4830X9WaHRaBAXF4f4+HjY2NjAxcWF/x2JRCLY29uX2kar1aKoqIi/7mi1WjDG9BaRSASxWKz3r0AgQEJCAiZOnIh9+/YZVb68vDw+WaBGo0Fubi6ys7Px22+/Yfz48bh48WK1k0kmJCQ0+Juq586dw/Tp0/HJJ5/A0tISHh4eWLJkCT766KN6nV6sIenYsSP/f67FePLkybhx4wZ+++23CrfPy8vDrVu3YGFhgcDAQIhEIgQHB+PSpUtVav1kjFUpYzbXyu3o6Ag7Ozs8ePAAWq0WUVFRSE1Nhb+/PyQSCQIDAxEeHl7qNRhjePz4MRhj/Lletxfj0zc6BQIB/P39YWNjA6DkWnP37l3+mmhtbc3XE5OTkyt9PLqKioqqNeTC3t6ePz9x70t5tFotli5ditWrV6N79+44cuQIoqKiEB8fDycnJwQHB8PJycmovCykCoxNylWNjjzPbEvyxIkT9QLkr7/+usEHyEBJd5aqBlYSiQQODg7w8/PDwIEDMXDgQFy4cIEf+6A7jkr3znhhYSGfgdBQl+yOHTvi0qVL/AlPJBJBKpXCxMQEKpUKlpaWsLKygqWlJczNzaFSqaBUKmFmZgYTE5NSATJjDHl5ecjMzMT9+/dx5coVnDt3DjExMc9kgMw5ffo0P+5bLpdj6tSp1PKFkjFO3G9RrVZj8+bNld4HY4zvasUFW5yYmBi+YmzMvLppaWn8RcnR0ZG/6KWnp+PGjRto3bp1pcvHZc3Oy8ur0oWcqxBwN5d0HzOGVqvlW5Otra2rncRLoVBALBbzifPu3r1b4TZCoZDvhhYXF6f3W5ZKpXxFp7IVvp9//hkFBQXw9PSkqdZ09OvXD82aNQNQ8p1evXp1PZeo6hhjSE5OxtWrV3H+/HlERkYiMTERWVlZpa5JQqEQcrkcpqamMDMzg0qlgrm5OSwsLPhrkbm5OUxNTSGXy/nvMVDSY6RVq1alziFarZYfK89NU8PdlOOIRCKoVCo4OzsjKysLWq0WH330EYKCguDm5lbl31xiYmK5GfobipiYGHz44Yd8a6erqys+++wzGleJknwLXNKupKQk3L17Fy+88AJcXV3x/fffV2pfGRkZuHnzJp/EtapzxTs5Oen15KkM7iaxVCrVa83mrpHFxcUQCoUICgoqlUtAKpXC1dUVbm5uevVMjm6dSCAQwM/Pjz/GpKQk3Lp1S+/axwXP2dnZ1U4Ym5SUBAsLiyrP/83dtMvOzjb6Os/liBg3bhz/W/nrr7/453v37l2lspCG4ZlsSX7rrbfQp08fACUX31WrVpXZ1UWXr68vbG1t+WQV9cHLy6tSYzVNTExgbW0Na2trKJVKvpI9dOhQnDhxAmlpafx4kOzsbOTl5ekFxWV1eRUKhRCJRFAqlXBxccG0adOQkpKid3de9/8A+Lv4T9/ZLyoqQmFhod6/DXEMVk3Yvn07goOD+ZsVQ4cOxc8//1zfxapX7dq141sm//777ypPtZadnQ2NRlPqxkNBQQFycnL4GzPGePjwIWxtbSGVSuHk5MR3j759+zYaNWpUqXLpViQqMw5ZFxdQcr0vuEp7ZcTHx/MVE1tb22p1TdPNZPrgwQOjAnZTU1M+qHi6AiGVSvmeI5Wt6Ny+fRsxMTFo3Lgx3NzcEBoaqpcl9L/I3d0dY8aM4f/+8ccfG8z0eNVVWFjIf3+43ggSiQRSqRQymQwymQxSqZRvHdbttcR9/3R7O+n2erpx4wYfJB87dgwajYa/XhkiEokgl8v5RalU8lnad+3ahXfffRfXrl3DkydP4OHhgcLCQqSmpiI1NRUZGRlGXefi4+MhFovh6OhYY73IKsvFxQWNGzeuMLlnfHw8Zs2ahcWLF8POzg6Ojo5YsmQJpk2b1mCHsNWFdu3a8TcBT506BQcHB7z++utYuHBhlX6XWVlZyMjIgJWVFaytrat0XXFzc8Pu3bsrvR1QkmAqISEBT548KZVDIjc3Fzdu3ECTJk0gFov5FmWud5dud2ouOC4rSPbz8+NvrCYlJRkcpnT79m04OjrWSMKtzMxMPHnyBP7+/rhy5UqltuW6jHNlrYxLly7h3LlzmDRpEhYsWIAjR45g1KhRyMnJga+vL0QiUb3Plf5cMjYpVzXCkWcuSB4wYAD69u0LoOTu8PLly43untesWTM4OTnVW5CsUqng6+uLRYsWlbueqakp7O3tYW1trTc+kxMQEADGGNasWYO0tLQq3X3TarXQarXw8vJCQkKCUS1J/3UmJibw9vbG4cOH8dprr4ExhqFDh+Lq1auIjIys7+LVm549e/L/P3jwYJX3o9FoYGJiYvBimZeXxyeXMnZfycnJcHZ21suYHRUVVemxhrp30quaMOnp7taA8WOSOVqtFhkZGbCxsan2GEe5XM5PTWNshUD3vX/6nKNQKPjnq9J1cPv27fjoo48AAH379v1PB8kSiQTTp0/nb05evnwZjDG4uLjU2swD9a24uBjFxcU1Mibx7Nmz8PX1NSqA4LpYP/26YrEYSqUSHh4e6NmzJzZs2ACRSMRn2ndycoJGo0FaWhqSk5ORmppaZsDMTXEYGhqKvXv3Vvv4qsLGxgaDBg0yagaMpKQkzJw5E4sXL4ajoyMcHBwwd+5czJ49+5nuCVYdul2tT506hQ8++ACHDh3CzZs3q7zP1NRUWFlZQaVSVTq5m1KphL29PT+UqCrKGxLFBcohISF8oHzp0iUUFRXpBcGGgmQuiHZzc+MD5OTkZNy5c8fgMWq1Wj6BY024ffs2GjduXOkgWaVS8WWvyhCDtWvX4ptvvkGPHj1w+PBhnDhxAt26dYOFhQWaN2+ul9CLPDueqe7Wbdu2xeuvv87/vWrVqkqNX3N0dKxyK1dNaN68Oe7fv29wHIlYLIaTkxOaN2+O0NBQuLi48AGyVqtFamoq7t69i7Nnz6JJkyb47rvvEBcXV+3uKcHBwc9MIpj65unpCYFAgNjYWD4jqEAgwNSpU6vcvedZ5+DggKCgIAAlrayVTWiliwuunu4qCfw7hrYy3csKCgqQn5+vF3Tfu3cPTk5Olfq8dJOKVLWSaKi7dVX2xZ07lEpltbLkFxYWQigUIicnx+jKme655umbd1x2z+Li4ipNC3LhwgW+m2fz5s3/09l1x4wZw4+ri46O5schu7q61ujURM+rmzdvIjg4uFr7UP+fve8Oj6rcvl7Te0syaZPeeyABpChdQBQQxa4XK4qCei0oepWr137l2q7l2lBREVGkKCBNOqGlkN57b5Nkev3+yHfe30zqTGYmCcp6njyEJHPmzMw577vX3muvbTKhs7MTH330ESQSCdra2pCbm4uGhgayTlFS2YSEBEydOhURERGDrivnz58f07mpLS0tkMvlDrcHtbe347nnniNJwdjYWDzxxBOePMVxC6rlzGg0orGxEampqRCLxfj6669dOq7teuqsYV10dDQaGhrcklQaDCqVisjCmUwmmR9uew1Ra33fSrJQKCQtSh0dHSgqKho1dWFBQUG/+cWOgEqGG43GEakDNBoNPvjgAyK7th0/O2fOHKePdxnjA5cMSY6JicGTTz5JAszvv/8ef/zxh1PHSElJcdnwxhXMnj0bZ8+etfuZVCpFXFwcpk6diqioKBIcmkwmNDU1IT8/H6dOnUJ+fj6ampqQnJwMPp/vtvnPSUlJLmVD/yqgnFKBXong1q1bybXk6+uLhx56aCxPb8wwf/588r2rc7qpjYnqM6RA9btaLBan5mmzWCzweDw70t3V1QWVSjWgYdBgoEiyK7O8bSvJFLkdiZM8RZLpdLpdhXwk52Nb/XUEKpUKZrMZOp2un/MpdS6uSIKphCeDwcCMGTNGfJxLGWlpaaS/32Aw4N///jdKS0vJ6EBqBM1lDI6SkhIIBIIhZ6s7Cq1WiwMHDuDaa69FZ2cnysrKcObMGWRmZqK6upqQFBaLhaCgIEyaNAkTJ05EQECAHZk4e/YskpKSxqy/t6GhgcyQdxTt7e14+eWXSWJyxowZ+Nvf/uapUxy3mDlzJnFlzszMxK233op33nnHZXkw5RFjtVpHRJJHQ/3X09ODqqoqAL3mlXK53G5vpsixbWKUxWIhIiKC+F0MVkH2FIqKihAbGztivxhX5s9fuHABp0+fxtq1a5GVlUVihiuuuOIvW0jxKC7PSe6FXC7HCy+8QLLof/zxB3744QenjhEYGAipVIqCggJPnOKwSE1NRWxsLH799VfQ6XT4+/tj0qRJSElJga+vL+h0OqxWKzo7O1FYWIiMjAyUlJSgvb3dbgG67rrrsG/fPpduZAosFgtRUVFjmji4VBAREQGgtzpZX18Pq9WKjRs3kiBp9uzZxNjjrwIajYZ58+YB6N0knU1a9YVtz5stAbQde+SMaRZFbvvOblQqlU7NS6ZItitZe3dVkrVaLQk4Bqq4O4qOjg7QaDTweLwBWzoGgsViQVtbG7hcLnHFpkB9Xo7OSB4IR48eJd//FUdnsFgsPPzww+T/X3zxBerq6qDX64kc0c/Pz2XTtj87KCO6hIQEtxzvt99+w4wZM+zaLlQqFaqrq3HhwgUyPoe6x0UiEaKjozF16lRERkaCw+GgqakJp0+fdmkEnavIzs7GhAkTnHpMZWUl3nzzTbLmrFixAgsWLPDA2Y1fUO05TCYTMTEx2Lt3r9sIKoPBsGvBcRQxMTFOT5AYKerq6tDZ2QmtVovo6Gg7NctAcmtfX1+IRCJotVqUlJSMukS/uroaGo2GKNwcBXX/ujrD/bPPPkN4eDgmT56MY8eOAehd2/+qid9LHeOeJLNYLDz//PMk4M3Ly8MHH3zg9HFSU1NRUFDgFnMAZ0Gj0XDvvffip59+gkwmw5QpUxATE2PXw1ddXY2zZ88iNzcXra2tA0oWAwICMGHCBOzdu9ct5yUUCkGj0S6PeBgGvr6+hKRVVlaSgKGtrQ2fffYZ+bsHH3zwL+V2nZqaSioj586dG9E4CltQZnMA7Hpuqe+7u7sdTg5xuVxiwtG3AqxUKvs5dg4GBoMBrVZLDPFGClvjLldIstVqhUqlglqtdulaa21thdVqBZvNdqqqTskvbV3t2Ww2IeyumPtUVFQQMpiUlGRnLvZXwIoVK0gPX3Z2tt06X1NTA6PRCBqNRhJ2lzE4Ojo63Dbnt6GhAbm5ucQstC9UKhXKysqQkZGBoqIisg4yGAwoFApMmTIFcXFx+Omnn3DVVVeReeujjZGQZKC3OvbJJ5+Q/z/00ENOVaQvZfj5+ZHX2tnZieDgYGzbts0tx7atHjsTl1Kjo0azuFFWVgYOhwMmk2m3X/QlyTQaDX5+fmAwGFCr1SP28HAVJ0+edJqUUvJ3FovlUruPRqPBDz/8gLvuusuucGDb134ZbsLlSnLvqCcqKGhsbMRrr702oirqxIkTkZ2d7eazcwyPPPIIfHx80NraivDwcJKJUyqVyMvLw5kzZ1BdXT1sED5//nxkZGS4jdTy+Xzo9foR9RD+VUCn00lQ093d3a+SefjwYWLaFRQUZDeW7M+OtLQ08v2RI0fcckwqwLSVJY6EVIaFhYFGo8FsNqO5ubnfczhaSeZwOBAIBODz+S5lxAcy7hqpGoRGo0EgEDhcAR4IWq0Wer0eLBYLCoXC4V5X23OmZOPUeA+r1eqSJB0AybzTaLS/VFDh5+eHFStWAOgNOPuOlTGbzcS0SyaTOaWE+CvCdv6xO/Dbb78NW0GlTPAuXryIs2fPoqGhARaLBTQaDb6+vggJCcH58+fx4osvjsnnl52dbZecdwZ79+7Fzp07AfRW2tavX+9wovFShq2ihcfjYffu3WAwGJg+fTomTpyIiIgIp6XSFKjPwWq1OrW3JCUlQaPRODTX3l3QarVkH/X29rZzmbf9lyLSQG9BYaxAkWRnfDs6OzuJW35kZKTDj+XxeGQGPPXa9+/fDw6Hg6CgIOK1kZCQ4HKV+jJGH+OaJM+ZM4fIOfV6PV599dV+0klHQKfTkZycPOokmcfj4ZVXXsHkyZOJPJyaF5mZmYmLFy+io6PD4eNNmjQJp0+fdtv58fn8P81YEU9BoVAQU6LBNqVPPvmEVJdvv/32v0wAm5KSAqD3ms7JyXHLManeOT6fTyrI1GblaF+Tn5+f3TzfvmS0s7PT4QDPNoHkSuXWVm5NvZ6Rkm7qPFzt81IqlWCxWGAwGIiPj3dI8mf7flB/HxAQAL1ej6amJpeldbaS62nTprl0rEsJ999/Pwm2d+3aNaDba2NjI6l2XK4mDw2NRuNSEqkvsrOzIRKJiKHacNDpdKR/ubq6mtwXp06dQkdHBz744INRr8a2t7ejsbHRaRkqhU2bNiEvLw9A7wi5hx56yCXzwEsBs2fPBtCrumOz2di9ezeCg4MBgIzPTEpKgkKhcFoyTc0H7urqcmotnzJlSj9vm9FAQ0MDgP8b1wb0J8lcLhd0Op3Is8cKBQUFMBqNThn4WSwWlJSUwGw2QyKRID09fdApEnw+H6GhoUhPT8fkyZORkJCA0NBQ0gpjNpvx3Xff4Y477iCeP2w2G3Fxca6/uMv4P/yVK8mRkZFYu3Yt6uvrYTQa8d5775GZis4iKioKVqsV5eXlbj7LgUGn05GYmIjPP/8ckZGR2Lp1Kzo7O9HQ0IBz586hsLDQabLv5eWF0NBQZGVlue08uVyuSxLSPztYLBYJitra2gaVklZWVpLh8Vwu186B/c8KoVBIKuxVVVUjSl4NhK6uLjIflep7pYIPR4IQmUxG5iCrVKoB1wxnKsk6nY4QQ1dMd9wxAgro3Zyp4N/VBJdGoyHVAYlEgujo6GHfY9ugmDIP4/P54HA4bpHWNTQ0oKmpCUBv391IqzSXEtLS0nDFFVcA6JUJD+a3YbVaSaJOIBD06wu/jP+DXq93K0k2Go24ePEiJk2a5PTjqqurcebMGZSVlUGn02Hnzp2orKzEhx9+iBtvvNGt5zkcsrOzMXHixBE91mKx4M0330R7eztqa2sxZcqUMe2x9jT8/f0JIeZwONi2bRtoNBpkMhk4HA6USiV0Oh1EIhEiIyORnp5uV2WljvH888/jpZdewvPPP4+77roLSUlJ8PHxIYlaZ3w2gLEjyWq1Gt3d3WAwGP1IMmUsSPVYj9U8cApWqxUnT57ElVde6dTj2trayJ7I4/GQlpaG5cuX4/bbb8f111+PxMREXHHFFZg0aRJCQ0PJZ83lcsHj8ex8EI4cOQKDwWCn0vqr+db8GTAuSTKfz8ezzz4LJpMJhUKB3bt3u+TmPHHiROTk5HjcYY8K7JcuXYq33noLXV1d+PTTT1FaWoqzZ8+STXIkSEtLQ0lJidvICNBbUfurVD1HgtDQUDAYDFit1mGlQ5s3byamRbNnz0ZiYuJonOKYITExkWwQ7h4hRgUNVBCh0WhgtVohlUqHDCh9fX0RHx8Pk8kEk8mEgoKCAVsJenp6nOo5ampqIo7Yg0kV+Xw+AgMDIRKJBjTUopJRg1WS6XQ6ZDIZvL294eXlNWiFJioqChqNBlqtlsi4RgqdTgelUkn6kyUSCRISEoasDgUHB8NsNsNkMkGv15PPiBqZ4w5QvXZMJpMkPP6sYDKZWLVqFfn/pk2bhqzAtLe3E0l7WFjYn76SN1LIZDK3e22cP38e6enpI3qsxWIhSfLS0lL89ttv2LlzJ9asWYPHHnsMUVFRo5IQysrKGjFJBnqTmG+88QYCAwPBZDKxYsUKpxMHlwqodiKRSASr1YodO3aAzWYTsnjx4kXk5uYSNSCfz0diYiKmTJmC0NBQ8re5ubk4ceIEcnJy4O3tjeeffx7fffcd0tLSoNPpnBpLGhQUBJlMNmZjO7u6ukCj0YiaybaSTEmJGQyGy2037sCJEycwffp0p++ruro6yGQy3HLLLXjhhRfwwAMPYMGCBZg4cSK8vb2JstBsNkOpVCI/Px/l5eXo6emxW7utViu+/fZbTJgwgazTl0nypYdxKZB//PHHiTlAcXExNm/ePOJjMRgMLFy40M5gyROgHC1nz56NJUuW4OjRo/jxxx9RWVnpFtnJpEmTcOHCBTec6f+hubkZHA7HIwHFpQ4+n4+AgAAAvdWt4T5DlUqFb775Bo888giAXhOvxx9//E/b701JrQG4fYQYVbHncDhgsVioqakBn8+HVCpFamoqCgsL7TZhDoeDyMhIIl9TqVQoLi4eNCFFo9Gc+lyqq6sxefJkMJlMpKSkoKKigmTOxWIxOTfqudlsNs6ePWv3HNT1Q2XbAfv+3pCQEISEhECr1YLH48FkMqGrqwudnZ3E1MXX15c8T2lpqcsO9zqdDlwuFxcuXEBERAQUCgV4PB4mT56MsrIyu8owg8FAXFwcZDIZTCYTSkpKYLFY7Fyt3ZWEzM/PJ202iYmJYzaRYDSwbNkyMqqooKDATm4+GCoqKjBx4kSw2WwEBweTXuXL+D8EBAS4fUTOhQsXsGrVKvB4vBHv6VarFY2NjWhubkZ9fT1aW1txzz33ICQkBD/99BOKioqIrNUTyMnJgUgkQmpq6ohbZIqLi7Fp0ybcf//9AIAnnngCjz32mNMV0fEOiiQHBgbio48+glqthlgshkAggNVqBY1Gg1arRV5eHry8vMicbA6Hg9DQUISEhECj0ZC9iMlkoqGhAZmZmQgLC8Ntt90GPz8/VFRUOJzwvOKKK5CTkzMmBrRA7/5G7WGU5wfQu5dRJNnZHmtPobCwEG1tbbj66quxZ88eCAQC+Pj4kP2V8tBob2+H1WoFk8nE1VdfjVtuuQU9PT04fvw4vv/+ezQ3N8PPzw8mk4mYZvb09KCzs5Ps8UFBQURdYIvTp09jxYoVSEhIgMViQUxMjEvrx2X0gQmOSamd64Sww7gjyUuXLsXUqVMB9AZeb775pp29vLOYNWsW9Ho9MjIy3HWKdmAwGAgPD0d4eDiWL1+OyMhIfPzxx9i7d69L41D6Ii4uDrt27XLb8YDeSlZ7ezsCAgIuk+Q+oOb8mUwmh4PQ/fv3Y9GiRYiMjERYWBhmzZrl8lik8Qqq18dqtZI+NXfBVi0hFApJq4JEIoHVakVKSgq6u7uhUqlI7zKVqdVoNCgoKBhSscFgMJxaU4xGI0pLSxETEwOLxdKvr8h2w/Py8oLBYICfn5+d5Iw6n4EqyZRiBgDEYjGMRiMMBgO8vb37Sbwpl213yNl0Oh04HA5pRbFarWSzT0xMtJPXUeQYAAksAJCKvDsVLraure4a4zMeIRQKcdNNNwHovY/6mnUNhp6eHrS0tMDX1xfBwcFobGwcs6B5vCIgIIDI9t2FlpYWdHR0ICoqyuXEoMViQW1tLSHGjz32GP7+97/j+++/R1FREUpLS916T1HQ6/XYtWsXVqxY4ZKPxK5du5CUlISpU6dCKBRi3bp1ePbZZ12K1cYTGAwGUlJSwOFwwOVysWnTJgD/NwaQRqNBoVCgrq4OQG+bREdHByQSCQICAuDj4wM6nQ6BQACBQAC1Wm03uq2wsBArV67ELbfcgg8//BBfffXVsFNL6HQ6rrnmGnIuY4Genh6S5GUymYQk6vX6ftXl8YAff/wR9957L06fPo2QkBDSY0zJoBUKBTo6OhAREYFly5ZBq9Xif//7Xz/vn7KysiGfh1LVDZQo3rZtG95++210dHSQVszz58+76RVehqcxrrRaMTExdv2c77zzjkuSQj6fj9tuuw0///yzR6TWPj4+mDx5MqZMmYJHH30UHA4Hq1evxo8//uhWgiwQCODl5eWRikF9fT3pu7mMXkilUjJ+prq62uGKndVqxeeff07+f+utt/4p5ZBisRhhYWEAgPLycrebv5nNZvK+URtvW1sbcnJyoNfrQaPRIJFIoFAoIJPJQKfTYbFYUFlZiQsXLgzb0uAsSQZ6JeBZWVn9enZ1Oh06OjqQl5eHEydOkH4mSoVAgSLStlI1iiTL5XLys1OnTuHChQtoaGjoZ+hCVaHcNfqDqiRTqKioQHZ2NgkEBQIBAgIC4OvrCxaLBS6Xi/LycuTn55Pzos7bWdOaodDY2Egy8o4ail2KWLp0KZHvHzhwwCk32MrKSqJmGKuRQuMVPB4PcrncIxXZqqoqhIaGuu14JpMJ2dnZWL16NQ4fPowHH3wQixcvJs7Jntg/fvvtN8TGxrosk3733XfJehcbG4u7777bDWc3PhAfHw8ulwu5XI7c3Fyiburu7iYJwtDQ0H5tO11dXSgqKkJGRgaKi4vR0NCA7u5uaLVaqNVqtLa2ori4GJmZmWhpacEHH3yA119/HStWrMCrr75q5zPQ97O/4oorQKfT3Wre6ix0Op3d3kztYbYkeTzh1KlTMBgMuO222yASiaDX69HZ2Uk+k5iYGLzyyiu45557sG3bNqxdu3ZE729XVxe0Wi28vLz67VfUeEyKoF+WXLsRBie+RohxU0lmMBh49NFHyY32008/uZxteeqpp1BTU4ODBw+64xQJmEwmYmNj4e3tjauuugrz58/Htm3b8L///c8jWbSQkBB0dHSQ4NWdyMrKwhVXXIHff//d7ce+VBEZGQmgl9g4G2jl5+cjJycHqampCAgI+FNWk20rqe6WWgO9juIWiwVKpdJOVt3d3Y28vDz4+/sT2ZtGoyGjuRzt96dItbPQaDQ4e/Ys6HQ6rFbrgMfo6uqCQCDol1gZSG5tOzuZMgij/k6tVpNrz7b67M71RafT9evx7u7uRmZmJuRyOSQSCSQSCUwmE3mP+yb/GhoaoFAo4OPjg5qaGpcl4BTy8/MxY8YM8Pl8hIWFjek4EU9AKBRi6dKlAHo/061btzr1eL1ej7q6OoSEhMDPzw/19fUeqTxeipg0aRJqamqcmhzhKGpqahx2uHYGOp0O77zzDjIyMrB+/XpERUXhxx9/hFwuR1FRkVt7PFUqFT744AM8+eST+Pvf/z7iirtGo8Ebb7yBf//732AymVi6dClOnDiB4uJit53rWIGSWvv4+NjNiAZ6E8NSqZTMK87Ozu4nnzWZTGhubu43fnAgZGdn45FHHsHdd9+NDz/8EMePH8e5c+fAYDDI6KWGhgYsW7YMu3fvHvMWLltZNbXe2ypZHB0nOBqwWq3Ys2cP7rvvPuTn56OoqAhtbW2IiYnBggULMGHCBBw/fhwXLlxAe3s7OBzOiHyD2tvbSbGJz+fbxepmsxk7duzAP//5T2g0GlRVVbnr5V3GKGDclLluvPFGsvmUlZXh22+/HfYxXC4XaWlpmDVrFubPn49JkyYhICAAqampeO211xAYGIiNGze69Twpa/jQ0FDcc889mDRpEp544gl89NFHHpOZhIaGjtjZezicPHkSEyZMcOtMyUsZ/v7+RBZVWVk5IgXCli1byPd/xmqyrfJgOBmSs5DL5WQdMJlM/XqbTCYT6urqUFBQgHPnziE/Px+1tbVObWwjqSRTsFqtMJvNAwYqlPMpm822k9YB9pXkvnJrqkrL4/H6Pc72Od29vuj1emJC0vf5WlpaUFpaivPnzyM7OxsVFRUDqmO6u7vBZDLB5XLdWvWlZo8D/5e0+jOhbxV5JP2ctbW15Bq6PBLq/zBjxgycOnXKI8euqalxayW5L06fPo0777wTra2teOyxx5CYmIiUlBS3P+fx48dx4MABvPnmm1i6dCnkcjni4+Mxd+5czJ49G9OnTydj9IZCeXk5vvnmGwC9a9uaNWvGZUXRWaSnp5N96Mcff7T7nU6nQ35+PiwWCzEXdJUYUj4Wv/zyC2bMmIH169eTaQNhYWGYPXs2IiIisH//fpeex1XQ6XRihGXbe6zX60msNNCeMpYoLi4Gk8nEjBkzIJFI8MILL+CVV15BcXExVq5ciU8//RRqtRoymQxBQUEjeg7bOKXvHhgaGorJkydDIBCgsbERYWFhEIvFLr2myxg9jItKcmBgIG699VYAvb06H3zwwaDZMhaLhWuuuQZTpkxBQkICWltb0dnZCaPRCC8vL3h7e8NsNmPXrl349ddf3SoFDQkJQWhoKKKjo3HzzTcjMzMTa9as8UiFt+/zesqcpampCXV1dZg8ebJDpjF/ZtDpdCIj7urqGrHUv6CgwK6aPHv2bBw+fNiNZzq2sN1IqJ4sd0AoFJLZoZThiSdAp9NdJpxMJtOuaspisRAZGUkkVbW1tXZ/T5H4gYy7GhsboVAowGQykZCQgIqKCreMUxoOWq12QCduZ9DZ2Ynq6mqEhoZCJpMhIiLCLaP2bN8/ql/7zwKhUIhly5YB6K0ybNu2bUTHMZvNqKqqQnR0NKRSKby9vUfluhnPYLPZSE9Pt0tUuhPV1dUeqSTboru7G+vWrcPy5cuxZs0aZGRk4ODBg5BKpSgsLHRb//mXX36JgoIC3Hzzzbj//vtRWFhoN+82PDwcTU1NuHDhAvbs2TOoqmrXrl2YNWsWIiMjERoaihtuuGHE1/R4gEQiIa+ltLS0nxkT0DtGsLCwEBEREZBKpUhKSkJOTs6I9hVvb2/Ex8eDTqejpqYGb7zxBhITE7FixQpIpVKcO3cOt956K44cOeLxWHM4MBgMu0oydS3akmRX9xR3QyQS4eDBg3jggQcwZcoU7Ny5E++9957dSE+lUgkej0eMMZ2FbTGFIsl0Oh033HADbrnlFuzcuRNyuRyhoaHo6upCamoqjh8/7tLrugw4PgP5UjfuWrNmDbnxduzYMai0Li0tDQ899BB6enpw8OBBfPDBBwPKWVypFA0EFouF+Ph4eHt7Y/78+Zg6dSref/997Ny5023PMRS8vLw86vB67NgxLFy48C9PkoODg0lG2NVAf8uWLaT35JZbbsGRI0fGXCblLtiSZHf1/QkEAqSkpIBOp8NkMiE/P99jyoyRrA9BQUGYOXMmrrrqKkLaCgoK8Morr8BqtSIpKQlsNhtarRbd3d39kgd9e5JtCbbBYEBhYSHi4uLAYDCQmJiIysrKfkSbglAoxI033giJRAK9Xo+LFy/i/PnzTjuK9u1JHimqq6uJc6hCoSDkzRXU19eT7/9sJHnZsmVE5j7SKjKFpqYmBAYGQiAQICIiAh0dHR4fdTieMWvWLLS0tHgsqdzW1gaBQAAWi+VxB99ffvkFWVlZePXVV7Fq1Sps2bIFfD4fRUVFbjPazMjIQEZGRr+kH9BLdlJTU0m88/PPP+Onn37q97qpwsY777wDGo2GW2+9FSdOnBjzWbkjxcSJE8k+xGAw4OPjM2DCvL29HWw2G9HR0RAKhYiKinI6sSuTyZCQkAAajUYMItva2nDhwgUcP34cL7zwAubNmwer1Tritq2IiAiEhoaio6MDzc3NaGtrG3FbDIPBIEnewSrJ44kkT5o0CY8++iiCg4OxadMmfPHFFwPeOzqdjphijgRWq9XusVFRUXjooYfA4/Gwfv16lJWVwWq14vXXX0d9ff1lknwJYcxJ8vz585GUlASgdyTRQBlgoVCIhx9+GBMnTsQ333yDffv2DRkIuDO45vF4SE5ORkBAAG699VaYzWbcd999o9pXIBaLBzUCo0yMWCwWBAIBkXLq9Xq7L6PROOh7tmfPHtx4441ITk72SI/ppQBqnArQex262t/3Z64mUyS5paVlxJuKLSiCTLllFhQUeHREgiMkmU6nIzg4GIsWLcL8+fPh4+NDJN7ffvstWlpaEB0dDS6Xi+joaLBYLFitVtTX1w+YOLDtSabT6f0Czc7OTmRnZ5O1kDJjqq2tBY/HQ0BAAKRSKVgsFq688kokJyejtLQUUqkU9913Hx577DGcPn0aR44ccdi1VqfTjThz3hdFRUVISUmBWCwmlTZX1sjW1lYYjUawWKw/FUm27UU2mUwuV9ysVisqKiqQnJxMrhNPjhAaz2AwGLjllluI/HcwMJlMcDgc8sVms8FgMEhbQ1dXF9Rq9YBEgtoXxGLxqFTtq6qqcPfdd+PJJ5/Eo48+il9++QVMJhNlZWVuJaEDvVadToczZ87gzJkz+O233/Dwww9j9uzZeP/99/uZB1ZUVGDHjh1Yvnw5WCwWHnnkEfzjH/9w2/mNJqh5uJ2dnfj999/x+OOPD/paGhsbwePxEBQUNCJvAH9/f9BoNBgMBly8eNFO+VhZWYlHH30U77zzDry9vZ2W6M6YMQM33XQTJBIJmpubIZVK4evrCwaDgY6ODuTn5+PYsWPIzMx0mDQzGAw7uTVVSTaZTKQIMNZyazqdjquuugo33ngjfH19kZubi88++wznz58fNK7g8/ng8/kuFTI4HA68vb2xcOFCJCcnY+fOndi6dSvZ63/66Se8+uqrZJTlZbgBjo6AcqHjcUxJskQiwX333Uf+/+GHH/YLumUyGV555RU0NjZi9erVA0pfPAWRSISIiAhMnjwZy5cvx8GDB7Fx48ZRnwEnEonsSDI1ksXHxwdeXl5gMplQqVT9nBZtQS1oWq0WSqUSSqWSzDbVaDTYsWMH7rjjDjz77LOj8ZLGHaKiouxckt2BP2M1WSaTkb5Zd0itKYLMYrFgsViQl5fn8XucwWAM+TkwGAzcd999WLBgAdhsNo4cOYKLFy+SgIDBYEAikaCzsxPx8fHQaDRgMBgoKCgY1CzIdgSUrSuoLbRaLbKyspCUlAQ+nw+FQgGFQgG9Xk/mEQO9bpnnzp0D0FuFpoy/Jk6ciKeeegrNzc347rvvkJWVNeT7MJBx10hhsViQm5uL5ORkQpStVuuIK3qUk3dISAgCAgJAo9H+FBVS2yrywYMH3TJbtrOzEx0dHfDy8kJYWBja2tr+kiOh5s+fD71eb1eh4XK5kEqlkEqlEIlE4HA4w3pEGI1GMJlMdHd3o62tDe3t7eT+tVgsUKvVEIlEoyZtNxqNeOONN3Du3DmsW7cOkZGR+Pnnn8kM+dFAWVkZnnzySVx33XXYsGEDNm7ciDNnztj9zffff48ZM2bA19cXKSkpmDdvHg4dOjQq5+dOpKWlwdvbG/X19Xj11Vfx7rvvYunSpYOO4KyqqoKvry9JtNv6KQwFHo8HHx8fGAwGVFZWDtgaqFKp8Oqrr+LFF1/EY489hlWrVg1LwqOjo/HII49ALBZj27ZtOHDggB0JlslkCAgIwKRJk7Bq1SoIBAIcOHAAp06dQlFR0ZDH7iu3tj2uXq8Hl8sdM5IcGhqKWbNmYfbs2TCZTPjll19QXFyMoKAgmM3mQQky5QVitVpHHHtQLTTp6enYu3cvHnzwwX6xgF6vR3Z2NqKjo+Hn5wdfX1+0tLSM6PkuY/QwpiT5gQceIAH3H3/8gezsbLvfe3t747XXXkNBQcGQfcqeAJXtWbJkCZKTk7Fx48Zh59h5CiKRCFqtFgEBAfD29oZUKu230bNYLGi1WlgsFtBoNLDZbLKYAb3BOZU5l0qlMJlMoNFohDAfOXIEy5cvR3p6Oi5cuDDaL3FM4ePjAx8fHwC9xizuCjD/jNVkW6n1YHJgR8Hn8+0Icn5+/qgkwYaqJM+YMQOrV6+GRCLBoUOHcOjQIbS3t8NqtYLJZILFYkEmk5Hvgd5NNj8/f0gJJCVHG6ySTMFkMiE3NxdJSUmkv5mSdnZ0dECr1ZKsPZfLhb+/P1gsFsxmM7766it89913uPbaa/HUU0+hrq4O3333HS5evDjoeblzvJLZbLYjyqGhobBarSMO5Ovr6xESEgImkwlfX1+HnGLHM9xdRbZFRUUFpFIpmEwmoqKiPNqeMx7BYrFw22234bvvvoOPjw+kUilkMhnMZvOAZngULBYLDAYDTCYT6HQ62Gw2ua8pd/fIyEio1WpCmLu7u+2SVqOFQ4cOoaioCK+++ioee+wxbN26FSwWyy0eAI7AarVi9+7daG5uxtNPP43333/fLiGh1+vx0Ucf4Z///CcA4L777sO5c+fsej/HO8LDw+Hj4wOBQIDjx49DrVbjP//5D15++WVUVVUNuJZaLBa0t7cjICDAKakxg8EgsdpQ3jmtra343//+h7vvvhvvvPMOXnjhhQEdyfl8Pv72t79h3rx52LZtG3755ZcB95nOzk50dnaioKAA33zzDaKjozF9+nRs2LABbW1t2L9/P44fPz7gXsxkMgeUWwMgBa7hTMyYTCaCg4MRFhZGJlVQX1wuF62traioqEBLSwvq6urQ1dWF7u5u8lwcDockkcPCwhAWFoYJEyZApVKhrq4OH3/8Mc6fPw+r1YoJEyYAwJDXoEKhgFAoBIPBIOoqSn05XIWdw+Fg+fLlmDp1KjgcDt5//32UlZUN6kZ/8OBBTJ48GTQaDcnJyZdkEumvhjEjyenp6Zg5cyaA3gHlX3zxRb+/ueeee1BQUID33ntvVM+NGu101113QafTYfXq1aioqBjVcwB6g29vb28EBQUhJiamX+Zao9GQjXsgOTaDwQCbzbaTlolEIkgkEhgMBvD5fHh7e8Pb2xtA7ziol156CW+99Ra6u7uh1+thMBiIs67tl8FgIFJud4PP50Or1Y5K5YgKKoHesTuuEr++sK0m33TTTX8qkuxKJblvBXk4kulODDQCKiAgAKtXr0Z4eDjOnz+PnJwcNDc3E7JBo9GIM3VFRQXEYjECAwMJeXXk3HU63ZCVZApmsxn5+fkICgoCl8tFT08PGhsbSS+z7X2hVCqRkpICLpcLX19fNDU1Yfv27dizZw+WLFmCZ599FsXFxfjkk0/6kczBeu1cAUWUU1JSIBKJEBYWBhqNNqKKct++5EudJF977bVuryJT0Gg0qKmpQVhYGEn6ufuzHQxCodAj46co13QOh0N6IW2/bGXTK1asAIfDgV6vR3x8PDkGtY+oVCoyy9R27xroPmSz2WRfpBLSAoEAAoEAoaGhEIlEiIuLQ21tbb9Z5p5GfX09Vq1ahXXr1mHNmjXYuXMn9u7di5KSklE7j7Nnz+L111/H/fffj/Lycjt5f2ZmJo4ePYpZs2ZBKBRi1apVePvtt0flvNyBtLQ0SKVSqFQq4pBeWFiIjz/+GM899xyeeeaZAdcyHo9H/CgchUajgdVqBY1Gg0AgGLSlTq1Wg8FgYOvWrZgyZQo2btyILVu24OTJk1Cr1VAoFEhLS8OyZctQWVmJtWvXOjXWq7S0FKWlpdiyZQtmzpyJuXPn4t5770V+fj6OHj1K5vwC/SvJtvePTqcDk8mEt7c3wsLCyPdyuZz8GxoaiqCgIOj1elRVVaGxsRFdXV0oLy8nMadcLodUKsUVV1yBwMBAkpCiFB5UYretrQ1VVVWoqqrCxx9/jIsXL9qdj1AoJAmyodba7u5u+Pn5gcVi2cWCAoEAFosFHR0daGpqQmdnp909lpqair///e9obW3FJ598AqVSiZCQEFJgq6ys7BcXHDt2DE8//TTEYvHl+fbugKPGXZea3JrD4eDhhx8m///iiy/6LS6LFi1CXFwcHnnkkVE9Ny8vL9xxxx1Yvnw5Tp48iX//+99unVE4HPh8PuRyOclmArDrAenp6SHEeLi+TUpi0vfvaDQahEIhybaLxWIypD4xMRHLly/HL7/84tD5UoYFOp0Oer0eSqUSHR0dI5Kk8/l8LFu2DEuXLsVHH300KsYGkZGRYLPZsFqtKC4udnugUVBQgLy8PCQlJUGhUOCKK67oJ1O7lOAOkiyXyxEbG0vIakFBwagRZKA3+KaSOywWCzfeeCNWrFiBgwcPYtOmTaQ33banNjU1FSqVCv7+/qiqqkJDQ8Ow0rS+0Gq1w1aSKZhMJvL8DAYDEydOhEAggFqtRnV1NSFA1CxpiUQCf39/EhzpdDps27YNe/bswcqVK/Hf//4XP/zwA3bs2EGq6L6+vsNKskcCs9mMixcvEqIcGhoKPp+P4uJip9RAtsF3YGAgMjMz3X6uowU2m40lS5YA6K08ecL9t7a2Fj4+PhAKhYiOjoZSqXTb3OrBwOfz8b///Q95eXn44YcfRtSqQvlqeHl5gcfjgcvlgsvlOjxKKCIiAldccQU++OAD8jONRoPOzk6ilHLGp8RgMKCxsZEkpqipGd7e3mAwGKDT6ZDL5UhJSYHRaER7ezva2tr6BdGegsFgwGuvvYaSkhLcd999iIyMxKeffjqqfiKZmZm4cOECHn300X4tWp999hnS0tIgEokwc+ZMHD58+JK5dydOnEhaaWzXxsOHD8Pb2xsvvfQSnnnmGbuEnVQqhUQiIW0vjoKS7guFQvj5+Q1JbLu6uuDt7Y19+/bhxIkTmDVrFh544AHQaDRotVpcvHgRn3zyiUujzwwGAw4ePIiDBw/Cy8sLV155JRYtWoS1a9eip6cHtbW1UKvViImJAdC/j12v14PP5yMoKAivv/46zGYz2tra0Nraivb2dlRWVuLYsWOorKx0KkFIp9MhFAohFAphMBig0+mg1WqHvadDQkKIWnIoWbNOp0N7eztEIhFJYlJrD51OJ0lHg8GA6upqNDY2Ys6cOXj44Yfx6aef4sCBA+RYPB4PwcHBEAqFSE5ORnd3N1paWqDRaKDValFVVYXOzk5IJBIySeUyxjfGhCTfeOONkMvlAICcnJx+1TWZTIa7774bb775pkcqlYPBy8sLL774IhISEvDVV19h27Ztbh0hNRiEQiG5EfvOK7ZYLNBqtaiurkZubq5b+qEpsk0tfHQ6nWTk33zzTbzxxhvw9vZGWVkZkdfYftlKNGk0GglqAMDPzw9WqxXNzc3o7Ox0aDEUCASEHFOvn3LI9GTQIZPJ4OfnB6CX8HmiGgL0GjZQhkwrVqy4pEkydd8CcCpbTSE8PJyQUJPJhMLCwlElyEDv515YWIj4+Hg8/vjj0Gg0ePbZZ1FWVkaq/t3d3eTel0gkEIvFkMvlMBgMCAwMRGBgIKqqqtDa2urwNarVah2qJNuCRqMhIiLCjjAkJCSguLiYBGpNTU3kHPl8vt2apVar8dFHH+Hw4cN45JFHMGfOHPz3v/9FUVER5HK5x3qiqIpyQkICpFIp5HI5+Hw+8vPzHQ4kbSuhMpnMI+c5Wpg/fz4x3jl+/Lhbq8gUrFYrSkpKMHHiRFIVcTaR4yyuu+46iEQiTJs2DdOmTUNGRga2bNniEFnm8/nw8fFBcHCwQ4SYmk9uMpns5oZfc801+Oqrr3D06FGSrHVXcsBsNqO1tRWtra2g0WiQSqXQarV2STZ/f3/4+/vDZDKho6ODjKX0ZHsYlWipqanBI488gn/961946623PDYfeiB8++23+PDDD7Fo0SLs27eP/Ly7uxtffPEFHn/8cQDAgw8+iNWrV497Pw5qBF9ZWRlaW1v7GaNt27YNQqEQ//nPf/DGG28gNzcXAoGAzIfX6/VOq10aGhrIVI2hFBlKpZKYd506dQqnTp0Ch8MhbXbungTR0dGBXbt2YdeuXeBwOAgODkZQUBCJY2xNuyjodDp0d3dDqVTi9ttvd1vsZrFY0N3d7VSVnk6nw9vbGzQabdjkle2xaTQaWCwWWCwWOBwOBAIB/Pz8wOfziZP5TTfdhBkzZuBf//pXP/l9ZWUl1Go1QkJCwOfzIZVK4eXlRSZJtLa2ori4GDwez6Pz1v8yMPz/r+FwKY2AEolEuP766wH0bkAfffRRv7954IEHcO7cOY9UOQZDVFQU3nzzTWg0Grzzzjs4evSoRwmyWCwmxLhvH4vZbEZHRwfa2trQ0dEBpVKJ9vZ2jxmGUUScMvV69913cffdd+Pvf//7gJI9qneLIsccDgdcLhd8Ph8ikQg0Gg1isRj+/v4ICQlBeXn5gP0tIpEIS5YssSPH1OsvKioCh8NxKjPrDBgMBsmIUkkITyEzMxNVVVUICwtDbGwsEhISLtmeQVs3ZGf6h9lsNuLi4oiph0ajQX5+vkddrAeDr68vWCwW7rzzTnz77bfYtWsXkb1RRMY22GEymVCr1TCbzWhpaUFAQACA3pFh4eHhKC8vd0ja6qjcmgI1VkQoFIJGo5HxM0DvetXZ2QmDwYDW1lZER0eDTqdDIpEMuG4VFRXh8ccfx/XXX4+XX34ZOTk5CAwMdHt7gS2o/uqIiAgoFApwOBykpqY6/H7ZXl/ucuEeC9DpdCxfvpz8f/v27R57LqovLzg4mBjDDGYm5w50dHQQ0zAAmDp1KqZOnYozZ85g69atKCsr6/cYFouFiIgI+Pr6wmw2E38Ng8GA7u5u6HQ6QnaHI73r1q1DSUkJvv76a4+9RgpWqxWdnZ3o6enBxYsXSaKJ2sOp3nnqddnu4Z4YZ2e1WnHmzBlotVrccMMNePXVV/HJJ59g69atbn+ugUD1ID/99NPIyMiwu18PHz6Mq6++GomJiQgICMDcuXNx8ODBUTmvkSI4OJhIiW3du7lcLuh0OnQ6HTZt2oS6ujo899xzyMzMRFZWFgwGA1FEOZKc4XK5dooJLy8vGI1GBAYGoqSkZMDHdHR0IDIyEnQ6HV5eXmhra/NYu1tf6PV6lJWVoaysDDU1NVi4cCHEYnG/Pcx2ggOXyx2TvZ0Ch8MhxRxn4hSK/BsMBqjVanR0dKC2thZisRgRERG4/fbbkZCQgI8++gjl5eVkIgdVaKJMwChpuEAgIG2Per0eMpkM9fX1iIqKIontS6ln/6+IUSfJN954IyGF+/fv75etS0tLw8SJE/HQQw+N2jktWrQITzzxBDIyMnDo0CHk5uZ6hCBLpVJCjPuaG5hMJjvZlm3W1TaQGA0cOnQIsbGxWL9+PZ588sl+v7dYLCSQ6QsWiwVvb28ytkUgECA5ORklJSWEeMTFxeGaa67BlVdeSaTkQO/rPHToEH788UePu/5FRkYSwlZSUuLxLPf27dvxxBNPAOi9By5VkkyZSalUKocDP5lMhri4ONJ/3NTUhPLy8mEfz2AwIBKJIBKJwGazYbFYYDabyTgzqppkMpmg0WgcClC8vb0xadIk1NTUYN26dXYVLz6fTzZW24w+tdlZrVaUlZWhpaWF9CYyGAwkJCQMOdeYgjMJHzabjdjYWCKxNhgMJHGUnp4OnU4HoVCIjo4OWCwWaDQaux6sgWA2m/Hzzz8jOzsbu3fvRnFx8YAmdTQaDTwez64XlMqwU3JTqs+zp6dnyNdltVpRXl4OlUpFDFISEhLQ0NCA8vLyITP8fxaSPGPGDKJYyczMdJt7/mCorq6Gt7c3+Hw+YmJicOHCBY8lWA8ePIijR49i4cKFWLFiBSHLV1xxBa644gqUlJRgz549OH78OIxGI7hcLhlXRaGurg4tLS1Qq9VOPfeSJUsQExND1tXRAmX8R6mxKioq+qnBGAwG5HI55HI5LBYLOjs7SZuUOyXwVqsV+fn5YLFYqKysxMqVKxETE4ONGzeOigqOIor3339/v97jb775Bm+++SaAXmXYH3/84ZFkgbtg2yNK3aMSiQRJSUlkRJjFYoFer8cvv/yC66+/HgsXLsT58+dx7tw5+Pn5QaVS2a1pNBoNIpEIMpmM7GW2MQ/Q22vb1tY2aE8y0EtA1Wo16HQ6ZDLZqPkN9AWHwyHEsO+aYnu9icXiMSXJtoUndyQSuru7wWKxEB8fj08//RQajQbTpk0b1OSVMv2iWjUNBgO4XC6am5tRUlKC1NRUWK1WhIWFDWmseRljj1ElyVKpFNdddx2A3ovoxx9/tPs9m83Gww8/jK+++mpU+oB5PB7WrFmDGTNm4Pvvv0dFRQXKysrcmnmn0+nw9/eHQqHoN26F6mdqbW2FUqkcNGC0WCwO92e5C//73/8QGRnp9OOMRiOamprQ1NQEHx8fREVFgc1mIzk5GVdffTWmTJnSrxfDbDbj4MGD+PHHHz0iQ+wLX19f+Pv7A+g1QhmNa+348eO46667IJfLMWHCBAQHB3u0iucpULJXR7Ozfn5+iImJAY1GI+O1bA2Z+oLH4yEwMBAymaxf6wEFylSjL6jsb1tbG5qbm/slPiZNmoQnnngC27Ztw6efftpv8+RyuYTw2W741GZP9fJ3dXXh4sWLkEgkiI6OhtVqRXh4OMRiMQoKCga9j22Dhr6Bki3kcjkiIyPBZDKh0WjsepAppYZAILA7Rk9Pj53j9lAoLy/HhAkT8OCDD+L999/HO++8g5KSEgQEBJC+rL6u1waDYVDXUqPRiJ6eHjQ1NREn8L6gZo/Hx8eDz+cjMDAQXC4XBQUFgyaoKOmeXq8f18H1cFi4cCH5/ueff/b481ksFhKIUcmWvLw8jz2f0WjEr7/+it9//x0LFizATTfdRMhyTEwMYmJicP/99+P48eOora0llZPa2lrU1NSM+LM9cuQIMjMzR70SQ6fT+52zSqWCSqVCVVUVkZHL5XIIBAIi/fT29iZJwrq6OreppEwmE/Lz88Fms/HBBx/ghhtuwAcffIDXX399wEq+u/HZZ5/h448/Rmpqqt2M9sLCQly4cAHp6enw9fXFggULxmxCiCOwJcmUUStFkKlqIRWHNTU14aOPPoJQKERERATS0tKwYsUKmEwmnD59GidOnEBTUxMiIiKg0+kGnHFMEW69Xo+mpqZhCwMtLS0IDw8Hm81GWVnZmIzEc5Qki0SiMTVapAogA8nCRwIej4fVq1fjvffeQ2FhIbhcLhQKBbkubKHT6dDR0QGdTgeVSgWdTkcMN81mM8LDw+Hv74/Kykq79rXLGAH+bMZdN910Ewm09uzZ08+t+dZbbyUD3D2NiIgIPPPMM9Bqtfj000+hUqnQ0NBgZxbjClgsFhQKBQICAsh4ioqKChw/fhxtbW1oa2tz2BlztCvJ1HMOJv1xFG1tbZDJZLj33ntxxRVXgMPhQKvVksW0p6cHBw8exK+//joq5BjoXeyio6MB9AY2nq7qUDCbzdi+fTuuueYayOVyLF++HO+///6oPLe7wGKx0NTUBDqd7pBpFyVHBnpJVl5e3qA9VzKZDAqFggTXtjCZTNDpdCRIoXoT+94TbDYbbDYbMpkMoaGhKCwsJAmQa665Bvfccw8++OCDQQ3hqBYC235HoPc6MRqNYLFYCA0NJYSjq6sLmZmZiIuLg0AgIK6eg11TtkGE7Xg2W/D5fMTFxYFGoxHiSRFkqVSK2NhY4jpve8+YzWZy7o7AYDDggw8+QGFhIV5++WWcPHly0PfFarWSYIN6byjnYaD3uvDy8oKXlxf0ej3q6+vR1NTUr2KmVquRmZmJmJgY+Pr6wsvLC6mpqcjNzR2wukYlB/38/Nw6qmo0kZycjJSUFNTV1aG1tXXUzJW6u7tRVVWF8PBweHl5ISgoyC1zzYeC0WjEb7/9hv3792POnDlYvHgxIiIiAPTe33fccQdoNBpKSkqwbds2VFdXu6TgoSq5o42B3PFtQTmN19TUkFm41Ndzzz2H1157DQEBAWhvb0dtba1bXoNWq0V+fj5SUlKwefNmTJkyBW+88Qa++eabQef7ugudnZ3YvHkzHn74YaxZs8aOPH333XdIT08HANxyyy04ePCgx1QNrsLLywtmsxkMBgOVlZWg0WhEtUTJ5inZLNWeZhu/0el0JCQkYNq0aVi5ciWCg4Px5Zdfkv2ju7ubXLOUOsgZUMkgBoMxZnJmiiSbTKZ+n6NOpyP78liMSLMFtZ/QaDRyvq5g5cqVaGhoIC0DdDod7e3txIjTNuEx3HNNmTIFHA4HFouFKC4vY/xi1Eiyl5cX4uLiiDzyp59+svt9SEgIli5dOqC8192YOnUqnnjiCWzfvh21tbVgMBhQKpVumTfI5XIRHBwMPz8/uyCecqXOyMhw+phUUDoQqGCVy+XCarXazZMbKzCZTEyfPh2LFy9GQkICGZ0D9JLU0tJS/Pjjjzhx4sSoniudTkdUVBQhWoWFhaNqJnLw4EHceeed4PF4mD17NjZv3jzqplWuQCwWExXAcAG3j48PIcgajQa5ubn9KrcCgQBSqRT+/v5k8wV6N7jW1lZ0dXWhp6dn0GCA6u9ls9ng8/kQCASQSCSQSqUwGo1ITU1FQUEBFi1ahGuuuQYvvvjikEZGVMDTl5BZLBZUV1cTYpeeno6Ojg4YDAYilZNIJBAIBAgODh5UOmpbORqs4kuZ6lFzu/l8PmkNoOY30un0fhVY6pydqS4wGAx0dXXh888/x4MPPggmk4lvv/0WarUaGo2GZMAHu0eYTCaREFJVMw6HQ/pNe3p60Nraip6eHkLeLRYLioqKYDAYEBQUBJFIhISEhEElZ11dXRCJRANWYi4F3HDDDQB6XeG///77UX3u2tpaMsEgNDSU3E+ehtFoxP79+7F//37ExsZi2bJlWLx4MWg0GqxWK/z9/fHQQw/h5ptvxr59+7B//36P9k07AspBl8PhkBFRg1V6qUqaI9BqtaitrUVtbS2Cg4NJawiDwSDEubu7G7W1tf2KBs6iq6sLZWVliI6OxtmzZ3HmzBncc889CAsLw4cffuhRNcaePXswd+5c3HTTTXbXeVlZGTIyMjB16lQYjUbMnTt3VIogI0FcXBzodDpaW1vR3d1NemuB3kTpcBJni8WCvLw85OXlISEhAWvXrsXKlSvx4IMPukXtYLsPUgWH0QQ105nJZJK+XVvo9Xqy/wiFwlE9t77QaDRQqVSg0+ng8XgurXsBAQG4+uqr7SbtWCwWp3qdKURFRWHKlCkkkX65kuwiTHCskuyCEHfUSPLy5csRHR0NtVqNnTt39pO4Pvzww/jtt988aqAEAEuXLsWdd96JjRs3or29HYGBgUSe5op8hcFgIDQ0FIGBgYQQWq1WMhA9MjLSISnkQFCpVHaLTt/+J41GYydNbW1tRUlJyahLFP39/bFgwQJcffXVpHcVAMnElpaWIjs7G/X19cjOzh51Mh8ZGQmJRELmIY/2JqPX67F3716sWLECTCYT1113HTZv3jyq5+AKbImKI5uOSqWCl5cXOjs7ERYWRu4LDocDPp9vl/hRq9UwGo2or6+HRqOxI1aDwWq1wmQykcDTVpJMzUr9xz/+AbFYjHXr1g0p8wZANn06nd7PUKO5uRm+vr4AQMw4bPueqFEcDQ0Ng/ZA2V5vg0mXKWmxXq8Hl8u1y8hTZiA5OTn9AhSqZ9eZ/quoqCjweDy0tbXhhRdewOrVqzF37lx89tlnDj3eZDKhs7MTnZ2dqKmpgUQigUKhIAkDoVCIgIAAWK1WaDQaGI1GWCwWXHfddfj111/BYDBIVWYwdHV1kXnRLBZrzBOAziA4OJhU0VpaWkbVeZhCUVERkpOTwWazkZCQgMzMzFF9D0tKSnDgwAFcvHgREydORHR0NEkAeXl54fbbb8ett96KjIwM7Nu3Dzk5OaMuI/X390dUVBRZn6j9djC3apFINKKgm8fjobGxEWfOnEFAQAAUCgXYbDbEYjESExNJot7Z3mxbNDY2wtfXFxKJBEajEevWrcM//vEPbNiwAW+88YbH+pStVis+/PBDvPXWWzh69KjdWvvdd98hIiICfn5+uO2223Do0CGPjyZzFrZuyNS6b7FYyLUQFhYGsViMtrY2dHd3D1sFtlgs2LJlCx5//HEkJibi9OnTLp+j1WolExLGQmrNYrHsKqd91xG9Xk/UP2NNkrVaLQQCwbAzqB3B/Pnzcfbs2RFN87AFg8HAo48+ih9++AE333wzgF6PlMsY3xgVDa9YLMY111wDoPdG27Nnj93v09PToVAoPJppp9FoeOCBB3DTTTfh+eefR25uLnGpbWhocKk/KCAgAFOmTEFQUBDpV6qtrcWZM2dQXFwMtVqN1tZWEmQ7i46ODgQGBpJ5kGlpacRiHvg/kwIajUYc9gbr53Q3hEIhFi1ahLfeeguffvopVqxYYUeQa2tr8b///Q9/+9vfsGHDBtTU1IBOpyMuLm5U+6z9/PwQEBAAOp1OZteNBXbv3k0ChMWLF5PemUsBtoRtuE2H2pwMBgMZtSWXy0lVkCLIVqsVHR0dqKiowIULFzB37lx8+umnZBTTSNDT04P8/HzMnz8fEREReOuttwYlyJQru5+fH7q6usjGHx8fb0eCzWYzsrOzkZ+fT2aUU58jJUVuamoi1deB4EhPssViQX5+PgoKCqBWq4k8T6lUorq6Gjk5Of2C6OjoaNKj3dzcDLFYDIFAMKB0nQKNRiNZ7Pr6epw9exbPPPMMJk+ejNtuu23Qxw2Frq4uFBQUIDMzE3V1deS9pK4FqVQKqVSKJUuWQKFQEIVMX6+GvsekYLuuXAqgpjgAwM6dO8dkBI7RaERFRQUZaRIXFzeqz08Z3Gk0GmzatAn33nsvNmzYgDNnzpBAn06nY/r06Xj55ZexadMmrFy5EiEhIaN2jl5eXmAwGGRNovYlyq06MTER06dPR0JCAumlH0nlWy6Xo7W1FSaTyS4+oIirVCpFWloaoqOjR5xQB0AUcdRYoWeffRZms5mMdvQUKioqcOjQoX7rR3V1Nenx9fLywrx58zx2DiOFTCYDnU4nexaFiooKIqX19fVFQkICpk6diunTpyM1NRVRUVEICAiAWCy2i2eo7w8dOkQIkTtAuWKPdvsdADu112AkmUpsjzVJptPpRF3lSrGIRqNh3rx5drOQR4qbbroJALBlyxbSdkYlDP9q2LBhA2njor4KCwvH+rQGxKhUkq+55hpSOdm3b18/6ckNN9yAXbt2eczOns1m46mnnkJwcDCeeuopNDc3IykpCTQaDSaTCTU1NSM6Lo/HQ2xsLKmwWa1WNDU1oaqqqt8C0tLSMiJphUwmA4fDQVpamt3GTLlhd3R0QKVSwWQyISUlBSKRCHw+f8SZWi6XC5lMBi6XSwIHasHv6upCZ2cndDod0tPTMXfuXEyZMqWfFNxsNuPUqVPYs2eP3SgFoLeyER8fDzqdjsjISJf7nh2BQCCw60N2h6x+pOjs7MTRo0cxb948CAQCzJs3r1/SaLzCliQPJx9rbW0lBJmqvFIVUqB3Q6V6tCwWC1gsFp599lkoFAo899xzLhvOxMfHY9q0afj000+HvBcSExMBgMxDLC0tRXx8PDgcDuLj41FdXW1337W3t/eTRTqa2dfpdGTU1FBBsMViGfB5+oLFYiE6OpqQ4fb2djCZTMTHx0OlUkEkEiErK2vAhAafzyeBFtXb3NLSgtdffx3//ve/cebMGRLYOgu9Xo/KykpUVlaCx+NBIpGAz+eT12w0GqHVatHY2AiVSjVkht72OpNIJGPm6uosxGIx5syZA6BXJeGOIGukUCqVpD+Zkl57WrEF9JK+wMBAaLVadHd3k885KysLWVlZ8Pb2xsKFC7Fw4UJiCOjl5YUbb7wRN954IyoqKnD48GEcPXoUWq2WJFnYbDZp26Lc7ikp+UgqbCwWi5jq5ObmQqVSkaQOpdai0+nw8fFBXFwchEIhJBKJ0/Np+84lt1qtaG5uRnNzMwICAhAWFgYWi4WAgADI5XLipO8sVCoVmpub4efnh6CgIDQ0NOCVV17BQw89hI0bN+Kll17ymBfH9u3b8fHHH5OEAIUff/wRU6dOBdCbPBpvkmuqgOHl5YUJEyaQNV2pVCIjIwOBgYGg0Wik+MBkMiGRSPol7nQ6HYxGI8RiMaxWK44cOYKZM2ciKirK5T2tr2v2aMMRkkwlAkerSDMYbI09XVFmTJw4EVar1eVxtCEhIVixYgWeeeYZmM1mtLW1EUXoXxV5eXmYP38++f+IOIujxl3jXW599dVXA+i9yXfu3Gn3u6ioKERHR+P111/3yHOLxWK8+OKLMBqNePrpp0nwSAWW1dXVI/pw/P39ERYWRsg/1Q802A3pTCWZRqMRR2w+nw+z2QyxWEzmtLa1tdm5YTOZTKSkpEAgEMBisaC+vt5hKTGNRiMDz728vIas6qSkpCAtLQ3JyclkbqAtqqurcfjwYfzxxx+D9mt0dnaiubkZCoUC/v7+aGxs9GifHDWih06nw2QyDemmO1rYsWMHyaYvWLDgkiHJzsqtu7q6HHIOZ7FYePnll0Gn0/HMM88Mau7lDO655x788MMPaG5uHtREhJppyOVyYTKZIJVKQafTUVJSQvplExMTcf78+SHvJ0cDc9tjDOYx4Azi4uIgk8mgVquh0+nQ2dlJZn8HBARApVJBLpcP+FlR7wk1yolCZWUlduzYgbvuugsvvfSSy+dIGdzYoq2tDWVlZQ6ZJNquI5dSJXnOnDnkM96/f7/H5r07CmrWp7e3N0JDQ9Hd3e1xP4To6GhimjMQQWhvb8f333+PrVu3YsqUKZg7dy4mTZpEkrIRERGIiYnB448/jsrKSmRmZqKwsHDQ/dpkMkGpVKKjowPt7e0Oy8orKyuRlJQEJpOJxMRE5Ofno7OzkyQXKLdqX19fUhWPjIxEWFgYcap2JMFPza0eCI2NjWS0XGBgIJhMJuLi4iASiUYUo1DOuXQ6HSEhISgrK8OHH36IFStW4I033sCbb76JzMxMp47pCJqbm5GRkYFly5bh888/Jz8vKytDXl4ekpKSoFAokJCQMK7GINqqalgsFq677jrs3r0bAEghpaamBmw2GwKBgLSTCAQC8Hg8knCk/GF6enogFArR0NCAjIwMXHnllW4lyaM97QT4P/WTxWKB1WodlCRbrdZB24lGC1TSzWKxuNRWd9VVV+Ho0aMuydtpNBoeffRR7Nq1ixRo2tvbERYWRnw9xsKAcKxhMpnG1AHdUXicJKemphJymJmZ2c/F+IYbbsCBAwfcEhj3hVwux2uvvYbi4mK899575KY2mUyorq6GQCBw2s2ayWQiJiYGPj4+JJNcXl4+bL9Ca2srWVCHumn9/PwQGhpqJ/UsKCiA0WhERkZGv8w1l8tFUlISydxVVVU5VBlnMpnEfbvvgkb1vphMJohEIqSlpWHatGkICgqyy2ByOBzU19fj0KFDOHz4sMPZaWoDZ7PZUCgUQ5opuYrY2FhC/IuKisY8WAV6kwklJSWIiYlBREQEIiIiRly1G004I7d2BosXL4ZAIMBTTz3llnENfD4fVVVVOHr0KAIDAwet2lLSQ41Gg8bGRigUCohEItTW1qKoqAgzZsyATqcDn893S/+6o5VkR0BV06RSKQng0tLSyOtpbW2FXC6Ht7f3gNeWbVW3b9Lo5MmTmDZtmkvnNxT0er3DbQa2SZZLaVbyggULyPfjpWpWXFyMtLQ0cLlcxMXFITMz02PqLZlMRtbdsrKyISuuZrMZp0+fxunTpyEWi3HVVVdh3rx5SE1NJftgXFwc4uLioFKpcPbsWZw9exY1NTXEG4DJZILJZBKvDsoHo7a2dtjYoru7GxcvXkRKSgohyiUlJYTQ2rpV63Q6kqxhMBhkD21oaEBtbe2QxNzX1xfZ2dlDvg8VFRVoampCbGws2aN9fHxQWFjolPmTwWBAdXU12Gy2XaLpp59+QktLC9avX4+PPvoIf/zxh8PHdBTbt2/Ha6+9hi1bttgVDX7//XckJSUB6L0/xiNJtlgs+Pbbb3HXXXchIyOjX7xKGVbZJpioufIUeWYwGFCpVDCbzejs7MTJkyexatUqfPXVVy6dI6XE4nA4EAqFozYRhAIl9aYI40DGXRaLhVTcx9JDguIcbW1tLhHcSZMm4Y033nDpXJYtWwaBQIAtW7aQn9nGT0Kh8C9JkqOjo1FfXw+dTofTp09j/fr1zo9FNfz/r+EwnkdA2c6I3L9/v93v/Pz8MHXqVDz44INuf14ej4cNGzYgKysLH330kd3vtFrtiORmXC4XKSkpZOM2Go3Izc11iHhR89LkcvmAJJYaH2MrE+ns7ER9fT2OHTs24DElEgkSEhJIwFtRUTGs6zCLxUJwcDD8/f1htVrJY/V6PTo6OtDZ2Ynu7m6kp6fjuuuuw8SJEwkx7uzsJMFIWVkZzp07h+zsbJSUlDiV5LBYLGhsbERoaCh8fHw8tpgGBQUROUttbe2YO6ja4sCBA6Tqt2DBAnzyySdjfEbDwxm5taPg8Xi4+eabsXHjRrcQZKA3qP33v/9N3LUHUw5QQbxarUZ5eTl4PB5EIhFCQ0NRUFBAnOJtE1auwPb1uVpJtlqtEAgEaGxsBI1Gg5+fH7hcLhm1JZVKIZfLBz136j0ZqLetsrLSzsnT3TAYDA6T5EuxkhwbG4vg4GAAvQlOd40VdBWUkmbChAlgsVhISEhAdna2R0yAAgMDAfTutc6su93d3di7dy8qKioQERGB6dOnIyUlhbhOWywWpKamIjU1FY2Njdi/fz8OHToEs9lM1FBCoZD03AsEAuj1elRVVQ0ZiKpUKuTk5CAlJQUsFgtxcXEk2WYLyr2YmudO+VwEBQUhICAAdXV1qKurGzAp0FduPRg0Gg2ys7MREhKCkJAQcDgcpKamorS01CnzoMECzmPHjkGpVOKFF15Ae3v7oM7yI0VZWRnKysqwePFibNu2jfz81KlTePDBByEUCnHllVfi008/9ZiRmLOwbYXLyMiARCLBmjVrsGHDhmEfSxkTUsnJvsjKyoJQKHSL5Lq7uxtyuXxM3P4pZ2tq7xhKbk2NYxwLkiwUCmG1WmGxWFzynomLi0NnZ6dLRRx/f3/cfvvt2LBhg917YRsvj3X/9ljgzJkzuPvuu1FcXIyAgABs2LABx48fR1JSkkcKpq7Ao93/IpGI9KF0dXXh7Nmzdr9ftmwZTp8+7faMGI1Gw7p169DW1uY28sHlcklm22q1oqamBjk5OU5VJgeSXPN4PKSmpiIxMZEQ5O7ubuTk5CA3N3fQAMPPz48YfFBjVYYiyDQaDcHBwcRgjMlkwmg0orm5GdnZ2Thz5gzUajWWLFmCL774AuvXr0daWppd5Tg3NxcbN27EsmXL8M9//hO5ubkQCoVISUlxugelsbERVqsVdDodfn5+Tj3WEUgkEkKSKNnceMKxY8dIFWfWrFkuVxZHA87KrR3BvHnzUFdX5xHpH0UAByPJlIKC+hxaWlrAYrEgFAoRGhpK5ia7SxJkMBgIIXFVLkf1YfJ4PAQEBMDLy4u0QOh0OvKaqLEdfTEUSfY0GAyGw/JRW5J8qVSSbavIfRPDYw1bTwaRSITIyEi3PwebzSbtTCNJECQmJkIul0OpVOLrr7/GsmXL8OSTT+LAgQN2+21AQABWrlyJr776CmvXroWPjw/Zy6qqqqBWq8Hn8yGTyTBx4kQkJCQMmZxRq9XIysoixC0oKAixsbED3iNarRbl5eU4e/YsGhoaYLVayYSLKVOmDOg/4uvr63CsY7VaUV1djdzcXBgMBtBoNMTExMDf39+hxw+Hixcv4uOPP8b69etJQsOd2L59O5YsWWK3rxmNRlK5ZrPZmDVrltufd6Sg5LlAr1Hql19+ibCwMMycOdPlYxuNRpw4cQJLlixx+VhUclokEo16XzKbzQaDwRiSJFP7G2UUOBbw8/MDn8+H0Wh0qaVk7ty5KCwsdMn469FHH8XBgwf7mVLZEsGxnik9Fti3bx9++ukn5ObmYv/+/Vi8eDGkUqlbTe7cBY9GSDNmzCAVEyrbS4HH4+Hqq6/GL7/84vbnnTdvHoKCgvDWW2+5pf+Uw+GQbDblwlZVVeV0Br6veZe/vz/S09NJhUStViM/Px/Z2dlD9nKGhYUhNjYWHA4HarUaOTk5Q2bMJBIJ0tPTER4eDgaDAavVioaGBly8eBGVlZVIS0vD66+/jk8++QTLly+3q9i0tLTgu+++w/3334/nnnsOBw8ehEajQXNzM0pLS4lDbVxcnFOLtsFgIAu+bfXcHWCxWIiPjweNRoPBYEBhYeGYjEwYClqtFidOnADQ+/pnzJgxxmc0PDwht46Pj8f58+fdcqy+sFgsZN7vQKA2cYpQUtej1WolgWNjY6PbxpXYVpLd0VNWV1cHq9VKZKbA/70GWxntQMEKNTZrLNoPnKkwXGru1lwuF1dddRWA3nv85MmTY3xG/dHY2EgSP4GBgSOeujAY+Hw+2QucNVoLDg4mhKWpqQklJSWwWCzIzc3Fe++9h7vuugsbN25ETk4OeQydTsfUqVOxYcMGfPHFF1ixYgW0Wi0yMzNRWlpK7gUfHx9MmjSpX9uQLXQ6HbKystDe3g69Xg8/Pz+kpqYOmsQ0GAxEVdXS0kLUWfHx8XYu1ZQc19mCgFKpRGZmJmn3iI6OdtvndfjwYRw6dMgjqpHz58+jp6eH3AsUbJNGs2fPdvvzjhS2CeDu7m5oNBp8+umneOCBB9xS6du6dStmzJiBoKAgl45Dre+UE/dogsfjkaIMMHglmboH3KXAchZUjN3R0THiuC86Ohpz5szBvn37RnweixYtgq+vL77++ut+v7MlyaP9OY5HdHV1oaSkBFFRUc49kJqTPNyXCyGcR0nyhAkTyPcUIaAwefJkNDU1uSw/GQhXX301tmzZ4hYpD5vNJhJrq9WKoqKiETusUiSZzWYjOTkZMTEx0Ov1MJlMKC0txYULF4Z1tA0LCyPjMXQ6HfLy8gYlLCwWC7GxsUhNTSWV3vb2dpw7dw5msxn33HMPvv76azzxxBPE5RfoDaBPnDiBF154Affffz+2bt06IAlXKpUoLS0F0CsZcTYjTZEGd1ZRaTQaEhISwGazYbVaST/3eIRtwECZ241n2JJkd0liYmJiPOZwzmaz+81jtgVVIaKSdzqdDmq1GhKJBBwOBxaLZdj2BWdgW0l2h7GJRqNBe3s76HQ6IRZU5dWW2A9EyK1WK/h8vp3L9WiBzWY73At7qVWSr7zyShIcHj161GM9v66itLSU9ItGR0e71Y3W9tp2poWCzWYjLCwMQG+AO9AUAr1ej6NHj+KFF17AAw88gB9//NFObeXj44Nbb70Vn3/+Of75z38iPDwcmZmZqKysJDNcIyIi7JLTfWE2m5Gfn0+OKxKJkJKSMmRiS6fToaioCFlZWVCpVLBYLISUy2QyyOVy6HS6Ea2bBoOBqNZoNBpiY2NHNCljIHz//feIiIiAQqFwy/FscejQoX4kubq6mozji42NHTMi1RfUtUC5UwO93gwlJSW49957XT5+a2srDh48iL/97W8uHUetVtvN6x4tUJVhyogPGJgkA733D5vNHpMKqVgsJuvPSBWqfD4f69atw/fffz9iF3hvb2/cc889+O9//zvgHmAbs/8VK8l9IRAIEBkZicbGRuce6AhBdtQBexB4NDpKTk4G8H89f7aYMWOGx7LszzzzjFsMKWg0GhITE8Hj8WC1WlFSUuKSNLy1tRUKhQITJ04kQa1Go8H58+cdujj8/f0JQVYqlcjOzh40CBOLxUhPTydSZr1ej5KSEigUCrz22mt47733cO2119plsWpra/HFF19g5cqVeOutt+yy9YOhpaUFnZ2dxB3YGVABlDudEMPCwsiGV1lZ6bbeWU+gsLCQBAzJycluk9J5ClRGXaPRuEWhwWKx4Ofn5zEp/HByawq2VSXKjVmn06GqqsptfdJAb1BBEXJ3BYfl5eVElUGn08nma/uaBsqm274noy3bo1o9HAFFOIBLgyTbJrvGm9TaFhaLBQUFBTCbzWQCgLscc6n13Gg0OlXJ8fLyIo9xJHHW3NyMb7/9Fvfeey9eeeUVnD17ljwfjUbDxIkT8eyzz+LLL7/E/PnzUV1dTZLQfD4fKSkpQ85jLi8vJ3GLQCBAQkLCsPeKSqVCVlYWqqqqwGQywWKxkJycjPj4eJdiB4oo6/V60Gg0xMXFuaUCpdFocPvttw86R94VnDp1Cqmpqf3Ok4or6HQ6MfIaa1CV5L7xwkcffYQrr7ySxLKu4IcffkBsbCyWL18+4mNYLBaSaPHkzOu+oIicLUnuuzfaGuNSrs2jDUplYTAYBp2wMhzWrl2Luro6l1Sua9aswcmTJwc16vur9yT/+9//xsyZMxEaGopp06bhl19+gdlstjM3Gy/wGEkODw8nN8nFixftNksOh4P09PR+1WV3wh3yWsrtFug1o3C1N1GpVJIZrFarFRUVFcjPz3coEJfJZGTWLyXLHqxXIiAgACkpKaSa2tbWhpCQELz11ltYs2aNnaTBYDDg0KFDWLduHR555BHs3LnTaSltU1MTGAwGvL29nQr+KRmoM4SLGmkxEHx8fIhhTltbm1urgJ7CwYMHyffp6eljeCbDgzK6cpfZCkViPVXppwLawdaCgX5eVVWFjIwMnDt3zu3Xj8FgIAGGu0iyXq9HdnY2jhw5gry8PPJeDkeSbX82mpVkSjXiTPKBCnbGu9xaKBQiLi4OQG/C0RMqKXdCq9WiuLgYQC9pjI2NHfDvRCKRUwE5tZ5TJo+Owt/fH2w2G+3t7U5dHxaLBWfPnsUrr7yCe+65B5s3b7bbqyUSCZYvX44PPvgACxYsQFdXFyGbYWFhSExMHDRBUF9fT4w2ZTIZMVscClarFXV1dcjOzibtDCkpKS7NawV67/WcnBwYjUZSUXZHgstTrUhNTU2oqanBlClT7H5um3xPTU31yHM7AxqNRuK8vm1u7e3t+Oabb7BmzRqXzRaVSiX++c9/4tZbb8VNN9004s+OSrbIZLJR6/uliBxliAX037epvc1kMoFOp4PH4436qCqq7Wgkak8ej4fnn38eEREReOedd0Z8DrNnz0ZERAS++OKLQf+mr7v1Xw1BQUHYsmULiouL8eOPP6K9vR1Tp051/nO7lCvJtotfX/fESZMmobm5eVyTGB6PZyf9cloG0AdsNhsSiYS4Sg9ntGUL2yy2Xq9Hbm7uoAQ5JiYG0dHRoNPp4HK5SExMxIsvvoi77rrLrhJTVlaGjz76CH/729/w3nvvueTgZ9v74WjPja1EdDiJOYWwsDBs3LgRDz300IC/p8ZZ2QZ/4x22Q+rHS1Z9MFCSTHc7knqqkklt2sMFN7bPr9FooFarXQ5oB4LBYCD3LXV/ugNUZd92gxmOJNu+J+7quXYEVFDnDAkqLy9HdXX1uB+TYVtp9IQRnSdAJRNZLBakUilJhNli2rRp+PDDD+0MyYYCtZ7TaDQ7Q6ShIBaLSTXPlSkEHR0d2LZtGx544AG88MILOH78OLm+6XQ65syZg3/9619YtGgR2Q+9vb3JaKyBUFVVRUi3n5/fkNVnW/T09CA7OxtarRY+Pj7EcdsV6HQ6knwRCoUu97h6GidOnOjnt5Gbm0vWpJSUlLE4LTtQbujAwFMbfvvtN+j1eixatMjl56qsrMTzzz+PpKQkvP/++7juuuucblNrbm4mo5ZGS31GJRFsPSz6Fjeovc1kMoHBYIBGo40qAeTxeETF4mhMSSEwMBAbN24Ei8XCE088MWIFokQiwQMPPICPPvpoyBhCpVKho6PDKbf6PxNuu+02KBQKcLlcBAcH47bbbhu3Y1A9NgIqISGBfN9XtutJqbW7EBQUBDqdDrPZ7HLPJIvFQkpKCpRKJfh8PlpbWx2WXjEYDJLpNpvNyMvLGzTADA8Ph7+/P+RyOVJTU5GcnGyXybNarTh16hR+/vlnt1Y5zGYzmpqayEiMlpaWYRcZLy8vcm7DBUUSiQQ33HADrr32WuzYsQM//PBDv7+h0Wgwm81gsVhkRuGlgMrKSmg0GvD5/HFNkmk0GgkiLxWSPFzPO5UJHy1ncVu5NWW84injLNvXNBAJpoIJk8k0qqZ2tvOZnXlMaGgogN6EoScSGO6ArSQzNzd3DM/EObS1tSEmJgYajWbAe3H//v1oa2vDmjVrMGvWLGzevHnIpKper4darYZAIHDI0ZlybqYe665pFzk5OcjJyYFYLMbixYuxZMkSEuynp6cjPT0dBQUFqKqqQmFhIZKSkpCVlTXg3lFSUgIOhwOpVIqwsDAS5A4Hg8GAixcv4uGHH0Zubi7i4uJgsVicDuJtQU3J8Pb2RnBwMOrr693S/uIJnDp1Crfffjt4PB4xH6Mc1qOiohAeHg4ulzsmBoIU+pp29YXVasXmzZvx6KOP4sCBAy77DJSVleHll1/GggULMG3aNNxzzz1ERk19UU7RlBEW9WWxWKDT6cBkMqHX6xEQEACz2YzW1laP+R8wGAySUBpq76fWdLPZTNRJ3t7eQ5rQuhPU52i1Wh0muQKBADfddBOuu+467Nq1C5s3b3ZpP3zooYeQk5ODM2fODPl3Go2GTADwxHSXy3AfPEaSqeyYyWTq1++SnJyMXbt2eeqp3QKj0QgmkwmlUulyX2JkZCSxpC8tLXUquxYZGUnISUFBwaABor+/P2bNmoWrrroKERER6OnpQXNzM/z8/GAymXDo0CH88ssvHpvZWVlZCR8fH7DZbMTExCAzM3PQjZvD4RDJt1arHfQ1yWQy3HjjjVi0aBFycnLw9NNPD2qkYLVaYTQaoVarIZfL0dbW5vbRYp4AZS42adIkSCQSKBQKj/SHuQrbCpO7SIqnyRm1aQ/W865Wq8Fms0dNbty3kiwUCl0KlocCm80mpGeg4Il6T9zZc+3oeZnNZqeC+r6zkscrSbY1PywoKBjDM3Ec1LxkjUYDq9U66PWQmZmJRx55BDfddBNefvlllJSUYMuWLcjPzx/w71tbWyEQCODt7Q0/P78hW5VCQkKISqWsrMztCc7u7m788MMP+OWXX7BgwQIsX74cPj4+sFqtCAoKwsSJE7F48WIcP34cVqsVmZmZ/dYmap2eOHEieDweYmJicP78eYdUGHq9HgKBAFVVVUQmffbsWZcUHLW1tQgODkZDQwOYTOao38eOoqGhAe3t7YiNjbXrz6yqqiIxQEBAwIgNktwB2zaOwQjduXPn0NjYiGXLluHHH390+TnNZjP27t2LvXv3gs1mQy6XQygUki8OhwMajUa+6HQ6+ZfP5yMkJATp6emQSqW44447APQqF+rr61FUVITCwkIUFRW5NAKJgr+/P5mKMtTxbO9bao329/dHdXW1R4oWXC4XAoGAJF4jIiLg5eUFlUoFqVQKi8VC9hqLxUIk4Hw+H1KpFImJibjuuutQVlY2ZGzpKKZNm4aUlBQ8/PDDw/6tbbLBnaaJfzkY/v/XcHBB9e8xkkzJQJqamuw2HH9/fwgEggGdK8cTKIMCoVBoZ1bgLLhcLslw1dTUIC8vDxEREQ6NvfHy8iLvY319/YALFIPBwJw5c7Bq1SooFAqYTCaSRVOr1di+fTt27tzplsVyKJjNZpSWliIxMZFURaurq/ttOgKBAHFxcWTxGkgW7ePjgxUrVmD+/Pm4cOEC1q1b55AUo7y8HGKxGAKBADExMVCr1W6venoCeXl5mDRpEoBeyfV4JMm25itURcBVUFVMLpfrkQHyFDkUCoWYMWMGLBYLOjs7UV5eDqPRCKPROKT7tbth25NMo9E8ujlSztUGg4EQUoVCQWZIcrlcGAyGUXdf5vP5Tl8/fR2uPZXocwV8Pp/MHK6qqvLI9ewJxMfHE++KwsLCIfc5rVaLb775Btu3b8fSpUvxj3/8A1VVVfjhhx/6qcXq6uogl8tBp9MRFRUFGo3WT1rIZrMRHBxMnJXb2to8ljQCeteD3bt3Y8+ePZg1axauvPJKTJo0CXq9HjweD9dffz0WLFiA3bt3Y/Pmzf32TJPJhKKiIkyYMAFsNhtRUVEOtSnJ5XKwWCwcPHgQqampoNPp8PX1dek69vf3h1arBZ/PH9V2iZGgqKgIcXFxdiTZtn3N399/TEnycJVkCl9//TVeeOEF7Nmzx633t8FgGNGeP3nyZPB4PLS1taG2thZyuRyhoaGIi4vDbbfdhtDQULS2tqKgoAAXLlzA+fPnR5RgpO7Pjo4OOzOuvokk2+uQiruYTCb8/PxcXrO9vb0xYcIEREVFITg4GEFBQaQS29HRAbFYDKFQCBaLBbPZPGjcZ7VaodFooFKpkJGRgddff90tqh+hUIjVq1fjs88+c6hyrtPpYLVaPR4HXIbr8Eh0KJPJSKWiby9vbGwsKioqxu1YHgpNTU0ICAgAk8lEUFAQrFYrJk2ahJ9//tmp4wQGBoLD4UCr1aKmpgYVFRWDGqTYgslkIjo6Gmq1GjQard8mwufzsWjRIixZsoRo+61WK3p6etDa2opdu3Zh//79o0oS29vb0dzcDB8fHwiFQqSmpkKr1RL3ax6PR3qzgN5qi+2mFB0djUWLFmH27NnIyMjAk08+ierqaoefn3JsTUtLI46tQ1W0xwvy8vLI98nJyfj999/H8GwGhu1CPtQ1RafTSXXWlhQOBIvFgtbWVvj7+494rNpQUCqVZFM0mUzgcDjw9fWF0WhERUUFIWvU+Xr6OhlIbu0pUJV/6jVSpnZsNptI9uh0useTZ33h5eVlJ1OlZPw0Go0kLvriUpiVTM1lB+zv5/GMsLAwIqOsrKx0WBapUqnw/fffY8eOHbj22muxbt06NDQ0YNeuXcjIyIDRaCSzjSdMmAAGg4GYmBgEBgZCqVTCYrFAIpFALBaDRqNBo9GAwWCMmtGZ2WzG4cOHcfjwYaSnp2P58uVISUkhs12XL1+O2bNn4+jRo9ixY4fdHtTT04Pa2lr4+vpCKpVCLpcPq1iKjIxEbW0turu70dTUBD8/P4SGhjpNHJKTkxEQEIATJ04Qb5OWlpZxv78VFxf3M6W0TZgEBASM9inZwVGSnJ+fj6KiIixfvhybN28ejVMbEk1NTQgPD4eXlxcKCwvR09ODiooKMtmFUjwkJSVh+fLlePzxx3H69GlkZWXhyJEjDsXgtmas9fX1xJhwINju9VRCWiaTQaFQOH2tM5lMTJgwARMnTsSECROgUChQXFyM4uJiHDlyBHV1dairq7NLVkyaNAl8Ph/19fUoLy8HnU4nXwwGAxaLxWNJ4bvvvhtlZWU4cuSIw4/RaDQQCASX5yS7AmpO8nBwoaPOIyTZ1oigb/Y4Li7OJZOo0YJKpUJLSwv8/PwQGBiI2tpa3HHHHThw4IBTTf2UTIaqnFZUVOCaa64Z9nHR0dHgcDhgs9nIysoiG6G3tzeWLVuGRYsWkcWLy+WCwWCgpKQEX375JU6dOjVmPbnFxcVobW1FVFQUmEwmeDxePzMYiqS0tbXB29sbs2fPxrx58+Dt7Y3jx4/jscceG7GpG2XalZCQAD6fj5iYmHF/vVGVTRaLRczixhtsP8OBSDKDwYBCoUBgYCBJkFHyTY1GA6VSicbGxn6kuampCf7+/h4hFiaTCU1NTTCZTBCLxVAqlfDy8oJCoYDBYLAjiAKBwOPGUBaLhQQmlNzaU6A2Xo1GAzabjbi4OFitVqjVanR2dkIgEBDn+9GEl5cXtFot4uLiIBQKYbFY7N6HpqYm1NfX21U8LoVZybb3bWFh4didiIPw8vIiBlTt7e0jWm81Gg22bduG3bt3Y9GiRbj99tvx8MMP48SJEzh06BCKiopIH65IJCJSUltYLBa0tLSgvr5+TPasCxcu4MKFCwgPD8ftt9+OhQsXgs1mg8vlYt68eZg3bx4yMzPx888/k4pTdXU1ZDIZRCIRoqOj0dXVNaTcOSIigijntFrtiBNyy5YtQ3l5OZngYDKZnEoijxWKioqIJJiCbfFkrEmyrWHbcCqXbdu24R//+Ae2bds2pn3UwP+ti1TCtW91W6vVkr787777DnK5HOnp6ViyZAluu+02fPPNN8OSOqqKTO3hQ/mH2N6/TCYT9fX1kMlk4PF4/ZKjgyEpKQmzZ8/GjBkzoFarcf78eXzzzTfIzc0dtuCjVqvB5/NJtZuSWXsakydPxoQJE7Bu3TqnHqfVaiEQCEbNofwyRgaPkGTbRvSBKsmuzB8bTVAZY0qOmZ+fj4ULF2Lbtm0OH4NaSIVCIby9vVFRUQF/f3/w+fxBb/rAwEDigllbWwuVSoWgoCDccMMNmD17tp08lMPhoLi4GCdOnMDu3btdcgZ1Fzo6OnDu3Dl4eXlBJpMRh1NqnmtzczOmTJmCRx55BMnJycjJycGWLVtw5swZt/RWtbW1ob6+HgqFAr6+vujq6nLZndyTMJvNUCqVkMvldlnt8YThKskKhQJhYWGkzxcAqd5yOBzIZDKEhoYSEkQFI42NjR4NkkpLS+3+n5qaSqpYdXV1ZE6sVCodFfdkaj2gess8ASaTSUhyT08PhEIh6bsuKChwm1zeGdDpdPj5+WHSpEmkog/YX0tmsxm+vr6QyWR2xie2Fc7xSpJt71tPSobdAQ6HQypCWq3W5SSiTqfDjh07sGPHDsTExGDu3Ll48cUX0dPTQyq2VquVTB9gsVjo6elBR0eH0+OePIXKykq89tprOHfuHGbNmmVX+UxLS0NaWhpKSkrw888/4/Tp0ygpKcHEiRPBZDIRHx+P3NzcQQPyiIgIXLx4ESwWixQQnK1o+fr6Ii0tDV9++SWR9Tc0NFwSBpWVlZVgsVh2fhvjiSTbYjhSlZ+fj/r6eixYsGDMfXXUajWR7IpEomEl4K2trdi3bx/27duHWbNm4e6778bUqVPx7rvvDkj4BQIBWW8HkoMPJbdmMBjo6OggpqQKhWLQ2DQkJARz5szBrFmzwGazcezYMWzYsMFpw1zbGEomk42KSkokEmHt2rXYtGmT07E3te5dJsnjGx4hybaSONsLh81mIzw8fNxX9ihoNBq0t7fDx8cHQUFB2L17Nx5++GFs377d4c2Jkm3zeDwkJCSgqakJHR0dCA8PH9D0xMfHh2yCPT094HA4eO655zB16lS7vzMYDDh27BhqamrQ0dGBzs7OcUGQKVitVrS3t9sFjImJiViyZAmuvPJKtLa24tChQ3jnnXc8sphVVFRAJBJBLBYjMjISKpVqXI+Q6enpgVwut+v5GU+wlQQNRJKpCpFQKEROTg4hyAKBgGxadDqdOKAXFxejpaUFTU1N5HofDfT09EAikZD2hK6uLnh5eUEqlaK2ttbjz08FIzQazWMyK4lEQjL+nZ2dZMatxWIZE4LMZrORkpICPp8PuVyOnp4eaDQadHZ2oqenBzqdDhaLBREREZBKpeBwOGCxWKTq3te4azzCUcnmWINOpyMhIQFMJpO0p7iTaJWUlKCkpASff/45pkyZgrlz5+KWW25BUVERDh06hJMnT455BW4wWK1WMtv4jz/+QFBQEK688kqS0ImJicH69etRX19PJkSEhIRAIpEgLi5uULO2iIgIHD9+HJMmTQKLxYLVanW6B3fJkiXIyMgAj8cjyrTxPELTFmazGWVlZYiLiyNkS61WE/XUWCeGbY0bHTGT/Pnnn3Httddi9+7dozoZoC8sFgvUavWACo3hcPToUWRmZuLpp5/Gxo0b8eqrr/aTRNsqFoYy3qPQt5IM9CZyoqKiIJPJIBQKCZFnMpmYPn06Fi9ejKioKJw+fRoffvghsrOzR7weNTU1QaFQEH+ICxcuePzzefjhh1FUVEQk7s6ASpRdJskuwNEZyC5093qEJNsGf7ayucDAQOh0ukvCdZhCXV0dfHx8wGKxUFhYCL1ejxkzZuDYsWMOPd5kMiE/Px8pKSlgs9kICAiAyWTCjBkzUF9fbxcA+vj4IC4uDjQaDaGhoUhKSkJ8fLzd8dRqNX777Tfs3r0bEREREIlEbhlT5SkEBgZi9uzZmDt3Lng8Ho4cOYL169d73LiNciNNT08Hi8VCYmIisrKyRt2oyFFQgTWDwRhSZTBWGK6S3NjYCB6PB4FAgJCQEFRUVNglSbhcLiHIDAaD9Mc2NTX1m6NJo9HA4/EgkUjITEh3oe/GREmwKWLp6U2Ven5PzpCklBtarRZ6vZ68Vk+QE29vb5jNZqhUqgH7zwUCASIiIohcn8Vi4dy5c3bGhZRUXyKRQK/Xo7Oz065f7lKQW18qJDkmJoYk4srKyjzmFG4ymXDq1CmcOnUKYrEYs2fPxpIlS7B69WqcOnUKf/zxBy5evDjuKqEtLS3w9fWFl5cXysrKsH37dqSmpuKmm24iknqFQoFHH30UHR0dOHv2LEpKSuDj44OYmBiUlZWR9YrL5SIsLAxRUVHgcDhkjE9lZaVTCW0ej4cFCxbghRdegI+PD4DeWbnj3bDLFpWVlf3mS2s0GkgkkjE3LhpupnxfnDlzBqtWrcKkSZNw7tw5T57asNDr9cSwyln09PTgbss1xwAAuBRJREFUn//8J+666y5s3LgRr7zyCinc8Hg8omZ0dMSY7fVIkeSmpiaEhoaSMX5VVVVYunQpMR3bu3cv/vWvf7llHbJarSgvL0dycjL4fD55Pk9h5syZSEpKwiOPPDKix7e2tg46m/0yxg88Zuva3t5ODKsoOGJyMd7Q3d0NvV4Pi8UCb29v7Nq1C8uWLXOYJAO9m8G5c+cQGhpKJEeJiYlISUmBwWCAVqsFi8UCj8dDamoqZs6cCT6fb7cwdXR0YMeOHfj999+h1WoREhJCgp3y8vJxRf5CQ0MxY8YMTJ8+HQEBAbhw4QI+++wznD9/flSDIoPBgMLCQiQnJ4PNZiMpKcmlTKUnYRtYi8XicUeSh+tJpszZgF4ik5aWRkzbOjs7oVQqUVFRQcw/xGIxIiIi4Ofnh/j4eCQnJ8NqtZINX6/Xg8vlwmg0urVvltq8qXO17euSSqWj4gJPwVNVUcr1k3pt1Gt19zxoar6t2WwGl8uFyWQio4TMZjNx0QZ6CTtVqS8vL4dQKIRYLIaPjw/EYjGp5rDZ7H7SvkvBuMuWJI9XZ+vQ0FBSFW1sbOznF+IpdHd3Y9euXdi1axdCQ0Mxd+5cPPbYY2Cz2Thz5gxOnjyJ7OzscUP6SkpKSHI1JiYGx48fx/Hjx5GWloYVK1aQefZeXl5YtGgRrr32WmRlZeHkyZMQi8UwGAxgs9ng8/mIjY1FZ2cndDoduru7UVpa6jQhmD9/PmpqatDY2AipVAqj0TjuJf19QfmU2KKjo4P4JIwlTCYTtFotmEwmGIzhZ8VYLBbs27cPixcvHnOSTJH6oXqFh4LFYsHXX3+NhoYGbNiwAW+//TbOnj2L0NBQ0Gg0mEymQRULfRMKtnsb9T5aLBbU1tYiIiICc+fOxfTp01FeXo6vv/66nyO+O9DZ2Yn29nZ4e3sjJCQEOp3OI+ucTCbD6tWr8e677444Kcrn80mrgSsTdP7SuFQryTKZjEj8bKsXlyJJBnqztiEhIfD398fp06dx5513Om1AZjabUVFRgYaGBrBYLDz99NMAQDbT9PR0TJs2DT4+PnZVGUradeTIEbubiLq52tvbRy3YGQpRUVGYPn06ZsyYAS8vL5w/fx5bt27FuXPnxlRep1QqUVpaipiYGAgEAsTHxyM/P39MZVIDoS9JHg+fqS0ccbfOzc1FQEAAQkJCSNKHRqMhMDAQVqsVSqUStbW1KCwsRFxcHKRSKbq7uyEWixEQEICOjg7SzywQCGA2m+Hj4+NWksxisaBWq0lgplKpoNPpwOVy4e/v73GSTPUhWa1WO+8Gd4GSkgMg75tGoyEu+QwGw21JIpFIBBaLBRaLBTqdDiaTSUyPbGE0GlFZWQm1Wo2YmBjI5XKkpaVBrVYT1ZHVakVrayuqq6v7ScKNRiMhHuPVCZQiyWq1ely6DVOOykBvIDlaTtJ9UV1djU2bNmHTpk2Ii4vD9OnT8dBDD0EkEuHcuXM4efIkLly4MKZ9ygaDAaWlpcT8USKRoKurC5mZmcjMzERMTAxWrFhBWqAsFgumT5+OadOmITs7G8ePHyeV4qioKJw/fx4XL160U0Q4ChqNhiVLluC7775DREQEuFwuST5eSmhtbcW0adP6/VwqlY6Le5pKAjtKNvfv349bbrkF/v7+Y7pXc7lcqNVqlxNzlCHtU089ha+//prEI30N9YZ7fyiPD1vfHKVSiTvvvBOhoaHYvHkzvv32W5fOdThQY9oEAgGio6NhMBjc3or4t7/9DZmZmXbeGc6ib+X9Mkken/AISbatWNjK5i5Vkkz1OjAYDMTGxuKPP/7AsmXLRtRbrdPpcOTIEaxatQo9PT3w9/fHvffeCx8fH+j1erKRUiYhGRkZ/Qgd1bcHDGyoMFqIi4vDjBkzMG3aNAiFQpw9exabNm1CZmbmuDBjodDU1AQej4fg4GB4eXkhMjJyzILEwWC7yY2HoKEvHCHJFosF9fX1aGxsJKZtXC6XjPihTNx6enpQXV2NqqoqiMVidHd3k4oxNaYhMDAQIpHIrl/MHZBIJBAIBHbVyebmZoSGhsLb29vjmxWdTifzoakZ6O4EdUxKtgz0rjnUNcXn893Wm09VC+h0OoqKisBgMECn08Hj8cBkMkn1TKvVIiAgADNnzgSbzSbPz2Qy7fwUhuqXNplMYLPZDlV6xgLU+zvWVbGBIJFIEB0dDaD33i0oKBgXScKioiIUFRURM6rp06dj5cqVeOKJJ3DhwgWcPHkS58+fH5M++ra2NtKq4O/vb7delJSU4LXXXrMz01SpVGAwGJgwYQJSU1Px66+/Ytu2bRCLxdi+ffuICDLQ65xL3SdUG8V4NqEcDK2trUS+S4GKDd2tcHEWtuu9o+fS2dmJjIwMXHPNNdi0aZOnTm1I+Pn5kZadiooKl4935swZvPTSS3jrrbdw/vx57N+/3+m+99raWtBoNJKglcvl2LBhA7q7u/Gf//wHWq3WrjfZEzCbzcjNzcXEiRMB9JoFFxUVuS2xFBYWhquuugqrV692y/EAuD3OuQz3wSMk2ZYY2y46crl8TIfGjxQ6nQ75+flISkoCi8VCdXU1Fi9ePGLSTxmmPProowgICCBmHnQ6Hbm5ufjhhx+GHHBOLYwmk2nEm+9IQKfTkZiYiBkzZmDq1KlgsVg4c+YMPvnkkzGXy3l7e+O+++7Dl19+OWDlsbKyElwuF3K5HIGBgdBqtWOaYOgL20VyPFaibM0lhpP2WywWtLW1kc+BGgERGBgIHo8HkUiEpKQkqFQqVFVVkRmttv1DYrEYPB7PrZsH1e8N2JOZpqYmIkP19vZ2yKTElXPQ6/Wg0+nw9va2M6hyFXQ6HRKJBBqNxm5d0mg0sFgsoNPpEIvFbiPJ1Cgbo9GI1tbWfhVqNpuNsLAw+Pn5gUajISAgAM3NzWhoaEBbWxu6urocJmvUsccrSR6P9yzQe+8lJiaCTqfDaDQiNzd3UCXBww8/jIyMDGRmZo7yWfZK8MvLy7F582aEhoZi+vTpuPnmm/H4448jOzsbJ0+exJkzZ0Y1CdHe3o7AwMBBk5Z1dXV4//338d1332H58uW47rrryDjGxYsXIzU1FUFBQUPu5cPh+uuvR2Zmph1BvlQMu2zR2toKmUxmp2ShYsOxrqDZKt36jqscCnv27MH69evx7bffum0NdxR8Pp/I16mxfu5AZWUlvv76a9x5553w8vJCQUGBU8emRkBarVZERUXhhRdewOnTp/H5559j8uTJpDd5INNad8JgMCAnJ4fMP09MTERRUZFbVGn33HMPfvvtN7cU/FpbW2EymcatmeG4hxGAI/U4F/JwHklf2FaabCtQcrl81OdyugtKpRJFRUWwWq2EYN1xxx0j6gWZMWMGrr76akyfPh0ikQhcLhd1dXX44osv8Pvvv8NkMg1JDqhzGI0MO4PBQFpaGtasWYNvvvkG69atA41GwzvvvIO//e1veP/993H+/Pkx3ejmzp2L//73v9Dr9UO+J8XFxURGFBkZ6RG560hhK08a66BhINgG1s4SV+p+OX/+PIqKisj6IBQKkZSUBLVaTfpobcFkMu3eF1chk8nsXJ8p6PV6GAwG8Hg8QpY9BQaDAZ1OR8ihO5/Py8sLXC4XfD7fbgOnXLwBkDYYd4DJZIJOp4PFYtmRRBqNhqCgIEyePBn+/v7EjZcy7SorK4NSqXSqmkkd353XgztB3bPj6fy4XC5SUlKIk3VeXt6QCa6SkhKsW7cOa9euHVMzperqamzZsgVr167F2rVrUVRUhCVLlmDz5s146aWXsHDhwlFxRDYYDNDpdMOuxwwGA0VFRfj444+RkZEBBoMBgUCA1NRURERE4J577hlRtTQ5ORnp6elkjF1bW1u/kXaXCqj+Y9t1fqCE5VjA9vmdue7z8vKgVCoxc+ZMT5zWoGAwGEhISCAJh8Fc1UeCoKAg1NfX4z//+Q8qKirw3//+F5MnTya/NxgMqKqqQm1t7YD3BRUbSKVSvPbaa9i+fTs++eQTmEwm1NTUAMCI3LhHAqq4ZTQaiat/dHS0S4n3CRMmICYmxqkxsIMhKCgIcrm8n//QZYwveGRHH4okX4pyawptbW0oKysjlvV33303srKy0NjYiJ6eHqhUqiF70ry8vPDUU09hxowZoNPpRNL1yy+/4MSJExAKhaDRaJDL5eByucjPzx9Qtkz1e3rS3Ck6OhoLFy7EjBkzoNVqcfr0abz99tvEeVgoFCIxMREtLS1QKpVjkglLTk7GypUr4ePjg//85z/DmmhYLBbk5+djwoQJ4PF4iImJgcViGRfXpG1wPdpZaUcw0HgHZ2G1WtHS0oKWlhb4+PggLCwMfD4fYrGYBIO1tbVktAXQ2/fqLgk0RRDVanW/67W1tRUSiQRSqdSt1d2+YDAYMBgMpG/X39/fbYoGinCr1ep+a0N7eztkMhkkEonb+pKp6hZl1gX0BkdRUVFk3ack+HV1dbjqqqtGPP6P+vzHqyxtvEhHKVBjtyhX5cLCwmEVBAcPHkR2djbWrFmDzz77DD/++CP27Nkz6usRnU6HTCaDXC6HVCpFQ0MDtm7dCqVSibi4OMybNw+rV69GXl4eDhw4gFOnTnnsHKlWkcEQFhZGXJu1Wi127tyJU6dO4e677yaKpVtvvRUzZ87Ev//9bztX976g9lWhUAiZTIa7774bFy9eJD3Il8rozIFAjYT09fUl+y21Roy1SWVPTw8qKytHlJTdtWsXlixZgkOHDnno7PojJiaGvHfFxcVuK5aIxWL4+/uTaSlHjhzBrFmz8OSTTyI/Px/ffPMN6HQ6cXkfyJmZRqOBzWZj0qRJeOKJJ7Bv3z7yu8bGRnh7e5M9Ijs72y3nPRTUajVycnKIv0BAQAAkEgmqq6vR3t4+LDllMBjgcrngcDjgcrl4/PHHcfLkSURHR4PJZIJGo/X70uv1RM01WFGQxWKReGS8+c9cUrhUjbtsM3O2GaPRcI/1NBobG6FSqdDY2IglS5Zg2rRpOHXqFOkFpKq8KpUKKpUKer0eLBYLU6ZMIQYlFosFFosF58+fx9tvv02CZAaDgfDwcNKPOXHiROTk5PQL6KlN2919ZXw+H3PmzMHChQvh5+eHo0eP2g11j42Nha+vL3l+qVQKLpeLmJgYtLS0DGi64wmEh4dj5cqViI2Nxc8//4xdu3Y53ANtNBpx8eJFpKamgsvlIioqChaLZczdQjkcDoxGI/R6/bhyKqcwkHOlK2hra0N7ezsUCgUxzqL6guvr69He3o6oqCjQaDR4eXmhpaXFpeej5M0ABjTxaG1tRWRkJElS9Z0Z6Q5QBE+n0xFnenf1JdPpdFKlGei9ol4zjUaDj4+Py5Jy6nMBej9LPp+P8PBwiEQiYr7W3t6O8vJysn5FR0dj7969I3q+8S63pkaJjYdKMuXKTM0CLy4udnh9a2trwz//+U+kpaVh5cqVWLp0Kb777jv88ccfHu9jptPpUCgUCA4OBpPJJGZt1O+8vLywY8cO7NixA97e3rjqqqtw6623YtWqVfjjjz/w+++/u3XW+XDOwXFxcSQxRfV6U4TvwIEDuPPOO3HnnXeCwWAgKCgI7777Ln7//Xds3rwZarWaVJxFIhEEAoHdtS0UCpGamoqXXnoJFRUVl6TEui86OjrsRriNF5KsUqkQHh4OAP36pofDkSNHcPfddyMxMdHjEmKgd+Y2dY51dXVuU2bS6XQi3zaZTIS4HT16FFlZWbj55puxceNG1NbWkp7igdY6Op2OiIgI1NbW2hFkoDdh2tzcDKlUSsw6R6O/XqPRIDMzE5GRkQgICACfz0dcXByA3s+eIsoUyaVeB4fDIa9Rr9cjLS0NcrkcBQUFZP8eCHw+H1KpdMi+a9s42pPtXZfhOjyyo9veuJQLM41GA5PJHJcEwFn09PSgp6cHmzZtwsqVK7F//37w+XzQ6XTQaDTw+Xzw+Xyygc6cOROLFi0ic1iVSiXee+89HDx40O64ZrMZZWVl0Gg0iIyMBIfDQVJSErKysuxICtUj5a7seXx8PBYuXIgrr7wSlZWV2LVrF44fP273WXl5eZEZja2trejp6YFEIiHVJF9fX/j4+KC0tNRjN72/vz/uuOMOTJs2Db/99hvefvvtERlA6PV6XLx4EYmJiWCz2cTxeiwTODwejzgFj8d7xN0kGegNQuvq6lBaWgqBQAC1Wg2hUIjY2FhotVpYrVYyM7zv7FxnERAQQDa8gUik0WhET08PxGIxxGKxR0gy9b7p9XoSgLuLJNuanA1EiCgTLbFYjODgYJfv0fDwcFJ5kclkCA4OBo1GI20g5eXldskIPz8/yGQyFBYWjuj5xjtJpoIqAKMyb3swMJlMpKSkkFnrdXV1I0owUU7OM2fOxF133YUbbrgB33zzDc6ePeuBs+6tSiUnJ9v1hKrVajQ3N8NqtSIwMBBMJhMRERGoqqpCe3s7IcyJiYlYsGAB3nnnHVRUVGDfvn04ceKEy+aR1ONZLFY/NUt4eDjZ3zs6OlBYWGi3RhoMBnz55Zc4cOAA1q9fj+TkZNDpdCxatAiRkZHYunXroDJjnU6HK664AmfOnMGRI0f+NFJMg8FA7hG5XE7u5bFuwes7WcIZ6PV6/P7771iyZInHSXJISAiCgoIA9LYLudPfJy4uzs4EzPaa6+7uxueff46dO3di7dq1CA8PR25u7oAkmUajobq6GhcvXhzweZqbm0kRKCoqClqtdlR8dSwWC0pLS9HR0YHQ0FBYLBaIxeIhyS4FLpeL8PBwzJ8/HxkZGWhpaYFer4fRaCSzz6k2J5FIBAaDAaPROKSkXKFQkO8vV5LHNzxCkm2zudRNTWWEx5Prsas4cOAAbr31VjAYDJw8eRJ8Pp/IpYRCIby8vHDrrbciNjaWGNwcP34c77777pALQ0NDA0wmE+Li4khVgOqHpua5AgNXxByFUCjE3LlzsXDhQnh5eeHw4cN48cUXoVQqwWazoVAowOVyyYgqJpMJrVYLBoOBmpoaqNVq1NXVgcFgkOw/0Bs88Hg8tw1xp9FomDRpEjFCOXLkCB566CGXN1adToeCggJMmDCBGJJdvHhxxDPvXIWtdGmsM+sDwRMkmYItWY6IiCCmXWw2m4yRmjBhArKyskYku6Z6ZIFeAjlYcEqRSEc2zpGAmvGr1+vJ63AnSQZ6P6fBrp+amhokJSWBz+e7NFqLkphSmXbqtZhMJjQ2NqK+vr4fSUxOTkZJScmI138qaBuvJNlWQUON6RltMBgMJCUlkSRqQ0ODywHYsWPHcPLkSVxzzTV45JFHcN9992Hv3r04ePCg2xxqxWIxEhMTSRKsra0N1dXV5D6l0WgQi8VgMpkICgqCQqGAWq2GwWCARqOBVqvFTz/9hJ9++glpaWlYvnw5Vq1ahSNHjuD3338fMZmgkqZ91Sx+fn52qpShRgrW1tbikUcewbJly7Bq1Srw+XyEhoZi7dq12Lx5M0pLS4nqjPqi0WhYu3YtNm7c+KchyADslAFUvADArdX/kcD2Oh5Jr/tvv/2G//3vfx5tJwwICCAj3Lq7u906xjIyMpIUQOrr6wd9Da2trfjhhx8wYcIEAIO3XWm12iH36YKCAkycOBFsNhsJCQnIyckZtb709vZ2tLe3g8fjQSaTESJLkV2gtwilUCgQFRWFmJgYhIWFoaGhAb6+vti6dSvKysogFoshFArh7e3dbwpHc3MzWCzWkOqP2NhY8n15ebmHXu1fAJeq3LqxsZFUgajFkMogjscq2UhhNpvx22+/YdmyZTh37hyZv0ply1atWoWAgAB0d3fDarXi22+/dbjhv6WlBRwOB8HBwZDL5TAYDCgvL0doaCi5IUdCkpOTk7Fw4UJMmzYNxcXF+PXXX1FfXw+hUAgfHx+yWBqNxn79dSwWq9+CZjabUVNTg6amJjL7NiQkBEwm06UxS2KxGAsWLMCiRYvAYDCwb98+vP/++26t9mq1WiK9ZjKZSEpKwsWLFz06nmAw2Pbuj0enQ3f0JA8GHo+HhoYGdHd3Izs7G1KpFEFBQUTOS7miUp/PUIGjXC5HT08PLBYLIWSUKgMYOiCjejapEUbuNlCj7i3KEAiA28zjKJI81LXb0dFBZhNHRkaiq6sLRqORGDv5+fmhvb19SCKrUChIX5fJZEJPTw90Oh0aGhrQ2Ng4aK9zSkqKSy6/1GdxKZBkPp8/6iSZSvRRQX5lZaXb1BBmsxm//vor9u7di2nTpmHx4sW48847cfz4cfz2228urfNSqRRJSUlEhVVQUNAveWO1WpGXl4fExEQAvaSVCm45HI6d+3RHRwe++OILCAQCpKen46233kJNTQ3279+Po0ePOrW2GgwGqFQqCIVChISEoLOzE3w+n5j/tLe3k+T1ULBardixYwcKCwuxfv16sq6tWLECH374Yb8+5fnz55O18M8EvV4/IEkeaym52Wwm6+JISHJrayvOnj2L2267De+//77bzy8gIADR0dHQaDQwmUzIzc11W/JEoVCQqibVHjMU+s72tYUtURzqntDr9cjLy7OLu7KyskacQOVwOHjrrbfA4/FIa0JdXR3q6+tRX18/YNJYq9VCJBJBKBQiODgYwcHBCAoKQnBwMEQiEdra2pCbm4vt27cjJycHYWFheP755yEQCDB9+nTQ6XTSJmb73iiVSrS0tKC9vX3I98CWJF/KXgN/BXiEJFMVhcDAQAQFBYHBYECr1eL1118fl6ZErmDv3r245ZZbEBYWRqqniYmJ+Mc//mE3O/Ptt9/GhQsXnDo21f8hl8vJYqbX62GxWKBUKh2uONLpdMyePRs333wzhEIhDh06hPXr18NqtSIgIMCuT4iaU6vX62E2m2EwGKDX69HV1UXIR1/I5XJwOBxSHZdKpQgMDITZbHY6ix8XF4drr70W06dPR35+Pj7//HOcPXvWYxl1tVqN3Nxc4gKbnJyMnJycUa/mUj1RXV1d41Jt4Yq79XDoSyqUSiWUSiUEAgFiY2NBo9FIz15cXFw/N086nQ65XI7g4GDw+XwYDAYwmUxkZWVBIpEgMDAQQG/iaSilgK2xkUgkcrv83tZZmsrWu7uSPJw5U1lZGTF0ovro4uLiwOfzwePxYDKZyKzrvoTC29sbUVFREIlEMBgM6OnpQUVFBUmKDoWUlBRs3LhxxK9vvLtb28rXIyIiRtXjgEajIT4+nqzjtbW1HqnOmc1mnDhxAidOnEBISAgWL16M1157DbW1tdizZw+OHz/u1NolEonsxlPV1dWBy+UiJCQE9fX1dmuOxWJBbm4u+Hw+mXVOjU4EepVqLBaLVJ2B3ir47t27ERsbi0WLFuG+++7D/v37sW3bNru5x0Ohrq4OcXFxsFqtmDZtGvm50WhEWVmZUwZ4xcXF+Pvf/45nn30W8fHxYLFYePzxxxESEoKvvvqK/N3SpUuxc+dOh497qWD79u0kiUeZPwFjT5KB3ursSEkyAHz++ed47733MHv2bBw5csRt56VQKBAZGUn+n5+f7xbTRaA3aRsREQGgd99wpBVmKJJs27s/XLymUqlQWFiIxMRE0laYk5MzotcmEokQHR2N559/HmFhYQgKCkJycjIUCgXEYjE5F9tqMZ1Oh9VqRWNjI2pra1FXV4e8vDxCsPV6PaRSKdnzli5divr6ejuVGWW+29XVha6uLoeLKzQaDTExMQB6VTOXuk/TmOJSrSQDvRsCNTMtNjYWBQUFOH36tKeebsygUqlw+PBhLF26FO+//z6mTZuGp556ilRha2pq8Morr4xY9lZcXAwul0tuTg6Hg9bWVhQXFzv0+Kuuugq333476HQ6fvjhB2RmZiIoKAj+/v6wWCwwm80wm81oampCZ2cnqXo7iuDgYISHh5OMu0ajQVdXFyQSCYKDg2EymYYN2GQyGa688kpcffXVkMvlOHjwINauXeuRvtCB0NPTYzcHOyUlBdnZ2aNW0Q0JCSEJFXeOc3AnPFlJpvon+0KtViM7OxuJiYlQKBREJpycnIzW1lYwmUwy+5pypKYMflpaWnDVVVeRYFitVhMDusFAjXthMpkQCoUeJcmNjY1kZJNYLHZJ5k+9D8DwJLmrqwuVlZWIiIiASCTCzJkzSYWHwWDAYrHAx8cHQUFB6OjogEqlgk6nA4/HQ2BgILhcLuh0OpRKJXJzcx0iG4GBgRCLxS5lzKn1b6zHxQyGwsJCXH/99QB6PR6Gc9p3J+Li4si11dDQ4NZexcFQU1ODTz75BF999RXmzJmD66+/Hvfffz8OHz6MI0eODDuqSCAQIDk5GQwGAyaTCZ2dnQgPDyeSXLlcPmBSWaPRDJrA5PF4kEql8PPzg1gsBovFQnBwMNrb2/H6669DLBbjlltuweeff47du3fbkbbB0NLSAhqNZlf5cWSc1mDo7OzEc889hwceeACLFy8GANxwww2QyWR4//33kZCQAG9vb/zxxx9OH3u8w3b9TUlJAdBbrR+N63U4KJVKBAQEQCgUgsvlOr33t7W1YePGjXj22WdRXl7uliRVZGQkqfJSqjd3FZlkMhni4uJAo9Gg0+mQl5fnUCHCliRzOBzynlksFpJopXp1h0NHRwfKysoQHR1NpqWMJAnA5XKhUqmQlZWFrKwsu98JhULSskWReBqNRsxa+z4XnU5HYGAggoOD7ZSUgYGByM3NRVtbG5RKJbq6uka8F4WEhJD9+nIVefzDYyQ5JycHc+bMAQCkpqaO2+DfHdi1axfeffddZGdnY+3ateTmunDhAt544w2XJOYWiwU5OTnkxm1ubkZVVdWwC9rUqVNxxx13gM/nY8uWLTh69ChCQkKQkpJCFguTyYTq6mo0NzePuFJLVRW9vb2h1+vB4XDQ3d0NOp0OkUiE8PBw6HS6fn0uQqEQ06dPx8yZM5GYmIiCggLs2rULx44dG5NKqlKpREFBATHzoojyaJxLfHw8+X6kxkaehu017O4Zh0ONM7NYLKirq4NMJiMSJ5lMRgzjbNHZ2Umu5ZSUFKjVapjNZmi1WhQWFsJisZBKEzXqiRrVQAUfer3e7fOZKdiS5NraWiK7DAoKcml9tD3XvmZ71Minrq4uKJVKUrFjMpmQSqXkfayvr0dlZSUUCgUCAwNBo9Hg7e1td85msxkWiwU9PT3o6OhwuBqXlpaGgoKCEQd4ts7d42Fc20Cw/fwSEhJG7XljYmKI221zc7NL0ueRQKfTYe/evdi7dy/i4+OxYMEC/Otf/0J3dzeOHTuGY8eOkfmoFFgsFpKTk4nMv7q6mngGCIVCGAyGEcnqKdO4xsZGSCQShIWFgcfjgcfjIS4uDj09PXj33XcRGBiIO+64A1988QV27NiBnTt3Dqkcam5uhtlsJi0KVVVVLiVQzWYzPvnkE1RVVWH16tWg0WiYM2cOlEolgoODsXfv3j+d4s4W/v7+5Jp1ZV1wJ6qrq8k+HBoa6nARwhaZmZnYtWsXNmzYgBdffHHESX6pVIrQ0FDiYdHT04O8vLwh36e0tDTQ6XTU1tYOa8ro6+tLFFqUfNvRz4BKIvP5fERGRiI6OhpA7zogFotJ25ifnx/8/f2J8d5gaGxsBJfLRXBwMKRSKVJSUoZ9rUBvkoXL5aKmpgZSqXTQJDPV5+8I/Pz8EBYWRlqzgN79tL29HQwGAwcOHHALj6GctQGM6Dq7jNGFR0kyhQkTJmDLli2eeqoxB+Ug+vbbb+P8+fMIDg7GoUOH8MEHH7hFGkMRBUdkSWlpabjzzjvh7e2NrVu3Yv/+/WScFJW9MhqNqK2tRUNDg8syZqpy1dXVBavVCjabDX9/fzQ2NoLBYBCDhLa2NrDZbFxxxRWYNWsWJk6ciIqKChw79v/YO++4pu7v/78yyE7Ye4NsFARnFVfdW9tqq1ZrW21ddaPWgbi3VavWj6PW1TpaW23dWlu3uFgqICB7bwJk//7gd9/fRGYgDG2ej0ceJpDc3GDuve9zzuu8zr/YunVrq5Cc5Ofn4+XLl/D09ASHw0G7du0QHh7e5Bdx9UV1a00mqWfGqbmguoLD4dSaSKJk/FRVk8pay+VyVFRUQCwWIy0tTeNiSFWhDA0NkZGRARaLBRcXF1hbW2sswJVKJVxcXFBeXg6FQgEjIyNSkdY16gHnixcv4OfnB6CyYtCY/3dqXymTP4VCAQ6HA7lcTtyCKcl5QUEBUlJS8Pr1azJ+prCwEFKpFEqlEomJiUhJSYGVlRVMTU2JeZ9CoUBhYSH522njSNqzZ88qTv7aQCVIgOqdu1sDRUVFyMjIIP2DTdHT/iaurq5Erp+bm1unUqKpefHiBV68eIE9e/YgICAAPXv2xLZt25CRkUECZmoEDCV3TElJgaOjI5hMJkpLS8lc0roUEXVRVFSE8PBwGBsbw8nJCUKhEEKhEAEBAUhOTkZoaCi8vLwwYcIEDBs2DL/99hvOnz9f43koNzdX5y7Mly5dQlFRERYsWIDc3FyMGTMGVlZW6NOnj07fp7VBGT8BmuvElkTdaNTJyanBwcuxY8dAp9OxefNmrFy5sk5FBZ1OB4/HA5/PB5/Ph5GRkUYSOi8vjyR4a4OarlJXckldvi2VShEZGVlv/wTKOE8kEpFpNSqViow6pUabUse2u7s7HB0dkZSUVKuSklISUP3A/v7+iIyMrDURxeFwyPxiGxubRqsOjY2NNdQieXl5SEpKQmlpKdhsNoqKiqok+xqK+vvog+RGIgNQnzoWq+Fv0WRBcl5eHtLS0mBrawtPT08YGxu3ikCoKaBmj1pbW8Pe3h4XLlzA3r17m3UfbG1tMXPmTNjb2+PMmTO4cOECpFIp3NzcNMZwSSQS0Ol0IpNJTExsVKU7Pz8fycnJZASMTCYDg8GAtbU1kc716dMHH330Edq3b4/MzEz8888/2L9/f6u0vs/JyQGDwYC7uzt4PB4JlJtywUsZ0lDmbK2RpKQkcl+9n0wXUBfW2qCC2NTUVOTn59c5ZoeqDCmVSjg7O8PW1lbjPeRyObmwU3NKgcoEUkZGRr2rpNpAjYwBgKdPn+Ljjz8GADKfsqFIJBKkp6fDzMxMwwBOoVCQz0gFy1QVPj8/H5mZmdUeg3K5XCMpp/639vPzq2LoVxuWlpZwdXVFaGhogz8fZXgGtN5KMlAZJFpbW8PAwABubm5NqgpxcnIiUkxqBFFLjZ16E5lMhgcPHuDBgwfgcDjo3LkzevTogU8++YQY68TFxaGwsBAODg5E/sjn80Gj0VBcXKyTiriDgwPMzMzA5XKJyokaKWdmZobnz5/j22+/hZ+fHyZMmIARI0bg4MGDOu0prYt79+5hw4YNWLJkCWxsbMBgMGBubv7OrpUAaPR2t8YgmfIHaShHjhxBeno61q5di127diEiIoIkG6nADgBxbK+OiooKpKSk1GuOMI1GI9e22hL6zs7OxDCtvLy8zkBUffuUu7aJiQkUCgXodDoKCgpw//598p48Hg8FBQWk9QmolGS7u7vDysoKr169qrGqm5iYCKlUCldXV3C5XBIo1yRpptZjTCYTtra2jQqS1WdEV1RU4OXLlxqVaXt7e5iYmOhsTUBVkuVyeatd7+n5P5rUBeXWrVv4+OOPQaPR0KtXL5w9e7Yp367F6N27NzgcDuLi4vDixQv88MMPzfbedDodo0ePxtixY3Hx4kWEhoaSEx/lRAuAjG+i3CWZTCbYbDZ4PB5SUlIatfhMTk4mC/SKigoUFhaiU6dO6NChA9q2bYuSkhKcPn0aR48e1Vk2rinJzMwEg8GAq6sr6Z2LiIjQmWGGOgEBASR4iomJaZL30AWFhYUoKSmBUCjUeSWZWsDWhIGBAQnyqECgroCAcq00MzODSqUimfisrCxkZGSQizXV/8hms8FgMECj0ZCZmdnoStabsNlsciHOzMxEbGwska5RJh4NRaFQICEhAQqFAiwWC3K5HAqFAgUFBeTCzmKxYGZmBltbW3C5XHA4HHh7e6OsrIwc/zVVK9T/1mw2GxwOp96Bco8ePfD06dNGOcarB8mttZIMAFFRUaQKOGjQoCYLku3t7ckxWFRUhOfPn7eaAPlNKioq8M8//+Cff/4hLTajRo3Chx9+iOTkZDx69AhhYWFIT08nkuuEhIRGqXc4HA68vLw0XLCpChs15o0yBYyIiEB4eDjCw8PRtWtXfP311+jRowd2797dbN+1sLAwHDx4ELNmzQIATJgwAStWrGiW925uTE1NSSU5MzOz2dsDauLNSnJDYDKZxDE5LS0NFy5cwKpVq3DmzJkqzv5isVgjQFapVCgvL4dYLCaqhfoe0+rPqy7ZTKPR4ObmRlQn9ZFvU4hEInh4eEChUMDAwAAKhQIymYy0Nqhvg2rjk8lkyMrKwrNnz8hIR5FIhPbt2yM9PR0JCQnVfra0tDTIZDJ4eHiAxWKRNs3qVEvUe1Ez1BszOYEaOQlUjmN6U7qtbsrbWPh8vs7Oc3rwdht3AcCNGzdItaRv377vZJDMYDAwbtw4AJVy0MOHDzfbgsXe3h5z5swBh8PB0qVLNeR2fD4fTk5ORI4qlUpJwJyVlQWZTAYzMzMIBAJ4eXmBw+E02GxCqVQiJSUF7dq1Q+fOndGmTRtYWVkhNjYWGzZsQHp6eo3D5VsraWlpoNPpcHZ2hlAohK+vr05HL1B8+OGH5P6ff/6p023rmtevX6Nt27YwMTGBQCDQ2ags9fmZ1aH+u9ouKgwGA1ZWVjA2NiY9rMD/tStkZmZW6TGXSqVIS0trxN7XDx8fH7IoevbsGXF+d3NzI4FrY8YGUVLpmpBKpWRMk6mpKQmyeDwePDw84OjoSKrLtf2/ymQyUhWpD7169cIvv/yi3Yd5A6p/EWjdleRbt25h8uTJxBDt2LFjZLaurrCxsSGVLmqx+7bM0i0tLcWVK1cQHh4Ob29vBAYGokOHDujcuTNiY2Px9OlTxMXFNcrEjs/no127djAwMIBSqSTmczY2NsTgLi4uDs7OzmCz2XB0dCTHzb179xAREYEvv/wSu3fvxr59+5rNQOvSpUsYMWIErKys4O/vj7Zt2zZq4d9a6d27Nwlwrl+/3sJ783+UlZUhNzcXZmZmZB5xfREKhbC3t4epqamGw3NCQgJ+/vlnfPLJJ8jPz0diYiIqKiogkUhQVlaGzMxMSCQSVFRUoKysDBwOB66urujRowfs7OxQWlpKvCSysrLw/PnzGpPolBrrzSCZy+XCy8uLJIsKCgpq3Y46xsbGxH1epVIhJycHOTk5RKVV2wgopVJJxphZWlrCxcUFBgYGsLW1hYGBAeLi4qrdh+zsbMhkMnh7e5NpI8nJyUhOTq42GaBUKmFvb4/Lly/X+XlqQiaTobi4GGw2u1pvAm9vb50lc/RS67ePJg2SMzMzER0dDR8fH9jb28PT0/Odc3Pr378/qQQ+efKkWXpKaTQaRo4ciXHjxuHkyZP4/fffq8iBqdFb1OKZ6nvNysoiB2dGRgZ8fHzA4/Hg7OwMpVLZoIDBwcEBw4YNw6hRo5CdnY2TJ0/iwoULYDAYkEgkGheOt4mUlBQwmUzY29vD0NAQ3t7eiI6O1lkSxMvLi/SKpqWltXr3dypIBirNTaKjo3WyXalUqjFv8E0oAxOlUlmjwY6xsTHc3d3BZrMhl8uhUqnIOKP09PQm7w+tC6r/GACZfxoXF0eMT9zc3JolkaRSqUilwsTEBA4ODhCJRFAoFLCxsYG1tTXS0tJqNAcsLS2FUCgk/ye14eTkBAsLCzx8+LBR+0yNKQFqn3Pd0kgkEpw7dw7jx4+HVCrF0KFDcejQIZ1t38rKiqgRqNF1rVV5UhtZWVnIzc3F3bt3IZFI4Onpia+++gozZ85EeHg4Tp06hQcPHmgd/FPtMVSAHBcXR0yMCgsLiWkljUZDXl4eLC0tYWtrq5FcEovF2LFjB/79919Mnz4dQUFB2LVrV5PLnxUKBU6cOIF58+YBAD799FMEBwc36Xs2NzQaDf369SOPb9y40YJ7U5XExESYmZmBz+fDzMyszh50FotFrjnqs7rlcjkxjHrx4gUKCwsxePBgzJ8/n6gTDAwM4OTkBD8/P7i7u8Pd3R22trbEWyAlJQVcLheOjo5o164dHBwcwGaz8fDhQ9y4caOKTJ2SQKsrsiwtLdGmTRuiosjKykJsbGy91i8mJibw9PQkJnovX74kUmqK+o6AysrKQl5eHlxdXWFiYgJjY2O4uLjU2K9dUFCAiIgIYqLq6OgIIyMjvHz5kqwnqSStsbExLC0tG7XulkgkZPSXSCTSSFYzmUx07doVISEhDd6+Ou3btyf3W6tJqx5Nmnzo5NWrV0nP5dixYxvVm9baMDAwIJVyADh69GiTv6elpSXmzp0LIyOjKtVjdaiTSEFBAezs7MiYnYSEBPKc8vJyPHv2DO3atYNAIICrqytUKlW9+jsYDAa6du2KwYMHw93dHbdv38bBgweRlpaG2NhYyGQyUvVrrVLA+pCYmAg6nQ5bW1uYmJjAy8tLZ/1/48ePh4mJCdLT03HixAkd7G3Toi6Vd3Z21lmQnJqaWmP2nsFgkERCcXFxtQtn9VEZKpUKxcXFyMjIQH5+fqv57nXu3BlA5f5RwXBcXBwZrzRt2jQsWrSoUVU0bcnPz0d+fj74fD7Mzc3JrFk7OzuYmJggKiqqSs9aQUEBrK2tyTiu2haS/fr1w7179xrleQD8X8+2XC5v9e0af/31FwICAuDm5oahQ4fi/PnzOql+m5ubk4RKWVkZIiIiWjzx0xio0YNA5Wigs2fP4sqVK7C2tsYXX3yBqVOn4tKlS7hy5Uq9AlQul6sRIEdFRWnINAsLC5GRkQErKys4OjoiLi4OlpaWoNPpYLFYVRQmT58+xZw5c/D111/j+++/x549e3Dnzh2d/g3e5J9//sGHH34IBwcHeHp6okOHDnj06FGTvmdzEhQURNRs4eHhrU4V8vr1a3Ts2BFAZYKvtnObQCCAr68vWWdRleHc3Nwq58xTp07Bzs4Oy5YtQ3x8PNq0aQNHR0eUlZUhNjYWcXFxuH37NuLi4mrte3V3d0fXrl0RHByMJ0+e4OjRo0SpUlBQAAsLC1haWkIsFsPMzIwocBQKBV69elWn67U6HA4HDAYDKpUK4eHhJDmtfs55s+VGvZL85nVXLpcjJiYGnp6esLCwgLm5ea2mZiUlJXj06BE8PDxgamoKQ0NDBAYGIikpiYwrBCoTqNHR0bW609eFXC4nc7LNzMw0/k7t27ev1/jI+tKpUycAlUmEN8dV6WkAzSC31r2F6xv8888/5EAODAxsdP9da6Jr165khMrdu3ebvAm/b9++2LVrFxITEzF79uxaD1zqBGZmZkZ6UfLy8qrIVakRAJRBAiWVrgkmk0kqJJ9++ikePnyIzz77DN999x3ZH/UewneB+Ph4cuI0MzODl5dXo92Pu3btSmZF0mi0Jl+A6QJ1yZF6ZbSxxMbGkgCAgk6nw9TUFO3btwedTodMJqs2eWNnZ6cxSzI8PBxRUVHIy8trNQFyp06dSKAfFRVF5Mw3b97E5cuXoVKpYGtri927d+ODDz7Q+YituhCLxXj9+jUePnxIvuc8Ho9I7dQpKChAeXk5SktL4enpCScnp2ql1wKBAP369cO5c+catW9sNhtsNhsqlQqJiYmtvnJaWlqKiIgIMkbsyy+/bPQ2raysNGaa6nJeamuAcn0Xi8U4efIkpkyZgj179sDT0xMHDx7E7Nmza72mUJMIWCwWlEpljX2M6enpoNFoMDAw0JA91tRfLxaLsXXrVuzZswfTp0/HvHnzNIzxdI1KpcKxY8fI4yFDhjTZezU3NBoNn3zyCXl86tSpFtyb6qmveRfVL2tmZgahUAiJRIKSkhJwuVzY2dnB1dWVmGQ5OjrCwcEBN27cQNeuXWFqaoobN25g+fLlmDJlClavXo0TJ07g0aNHdRpDxcbG4qeffsIXX3yB0tJSbN++nVyHqTU25X1BBcglJSV48uSJVgEyAFKBTk1N1QhAVSoVua6+6aRdUyVZHUpeXh8TLLlcjujoaLx69QpKpRJMJhOurq7EfKysrAy+vr46SSSlpqaCwWDA1NQUQqGQ/Lxnz574999/G719AESpBVROMWnonGU9zUuTB8kKhULjhDh+/PimfstmQ1061NjFYG3weDwEBwfj008/xfr167Fv3746qzOpqakoKSmBiYkJZDIZxGJxjVUYmUyGiIgIcjJ0c3PTcOKl6NGjB/bu3YsBAwZg9+7d+Oqrr/D777+TRT/llMvn82uVz76NxMTEkMy3mZmZxkgtbbGxscHs2bPJ4xMnTrwVfYXx8fHk4ubn59egWcIcDgempqawtraGjY0NbG1tUVxcjLZt28Ld3R1t2rRBQEAAunXrRloB2Gw2UlJSqmT2jYyMyGKmqKgIjx8/btZKbH1gsVga5zx1XwaFQoEHDx6Qv6mhoSEmTZqEw4cPY/r06ejYsWOTLsrfRKFQICYmhiS7+Hx+laSmQqEgbq10Oh0ODg7o0qULOnfuDC8vLzg5OcHBwQGTJk0iCyxra2tYWlpCIBBonVxycHCAubk5FApFneNUWgtnz54l58SuXbti5MiRDdoOjUaDq6sr3N3dQaPRIJVKERER0SJz5JsS9QW9WCyGSqVCWFgYQkNDMWPGDNDpdPzwww+YPHlylQQSNdOeSqS8ePEC+fn51b4PdQ0sLy+HsbExlEolsrOz61ys3rlzBzNnzoShoSF27NjRpIn++/fvk4AnICBAw1vhbaZnz54kmRkVFdUq+63Vk8DqY6reRC6XE+lvRUUF2Gw2LC0tNa5p9vb2xBHayckJIpEIDx48gKGhIQoLC2FiYoI2bdqgU6dOsLS01KolraKiAvv27cPBgwexdOlSjBw5Evn5+Xj16hUUCgUx1EpOTsazZ8+09rqggt+a2pvUnaXVUX9c3XqGcm7ncDhaJbDT09Px9OlT0p8NVKrK0tLS0K5du0a389BoNDLjWb3nms1mo3PnzjoLkjt06EDuN3af9fx/5Pi/anJtt0aIrppcbg1UGjSMGTMGFhYWaN++Pbp16/ZWVM5qw9zcnFQCMzIymqwX2d3dHcHBwUhJScGsWbPqHQRkZ2dDKBTi4cOHsLa2RlRUVK1VGCpQ9vf3B4fDIY6GeXl58Pf3x2effQahUIhjx47h5s2b1Z7kMjMzyWLYzs6u1ThX6grqwmhnZwc+n4/27duTnqP6wmaz8e2335Lg59atW/jnn3+aaI91z6NHj/D++++Dw+HAx8en3iM8jIyM4OXlVW3VRiaToaysDMOHD69y8aBaBKpb+LZp04aMNXv+/HmrSzQIBALMnj0bAoEAMpkMqampVbLeUVFRmDFjBr7++mt069aN9FsNHDgQAwcOJBXUyMhIREVF4dWrV03uupuZmQk+nw9bW1tYWFhUGYklkUjw6NEjODs7w9LSEkDl95oKdlgsFkaOHIkff/yxyngrlUqFjIwMxMfH12uhRFUNmExmo2dhNhdlZWX47rvvsGzZMgDAZ599hlevXiEqKqre22AymfD29oaRkRGAygp1dHR0o6XrrQ2hUAgzMzNyfLxJRkYGtm/fjt9//x0TJ07E/v37cebMGZw/fx4qlQp+fn5k0f3y5cs6j43Xr1+DRqMhJycHXC5Xo/2oNgoKChASEoJRo0Zh7dq1+Pnnn/Hbb7816DPXxfXr1/HJJ5+ARqOhT58+OHPmTJO8T3MhEAjw+eefk8c///xzC+5NzWRkZCA9PR02Njbw8fGp0ZxSqVSisLAQCQkJRPpLjWFS/5fyxqD64J89e4YRI0ZALpcTpVR5eTnc3d3h4OCAly9fajVV4caNG0hOTsaKFStgbGyMH3/8EdnZ2UR51VAllXqFuLo1o1wuh4GBQZVrufrj6s5Tjo6OMDAwgFgs1tpbQiwWIzw8nPRdl5eXY+LEiQgPD2/UdcHAwICYhJWVlYHH45G/W58+fZCVlaUzZ+ugoCBIJBJkZmbiwYMHOtmmnqanWYJkhUKBQ4cOYfHixQCAr7/+GuHh4Tpzx20J3n//fZL9u3btWpO8xwcffIBPPvkEx44dw++//6716yn5d33nEUulUoSHh8Pf359k0bp27QoXFxecOnUKFy5cqFXmp1AoUFhYCIFAACsrK7x+/fqt6ZsTiUSwsrKCmZmZxngB9ZFDlANmYmIiOeG3bdsWaWlpSEpKqpcU9JtvviHOwikpKdi5c2fTfagmICwsDN7e3pDJZGjfvn29g2QXFxewWCzQ6XQoFAoolUry95XJZLh9+zY6d+6MGzduQCwWo7i4GEVFRTX2GgkEApJoiI+Pb1XyU0tLS/Tv3x/9+/cnBleJiYnYunVrtc8vLi7Gpk2bYGVlhTVr1qBr165ITU0lJiUuLi5wcXHBiBEjAFRWEtLT05GWlkZu6enpyMvLQ1FRkU4kyQkJCaRP2cLCooo8TiqVIiYmBgkJCWTEh0gkgoGBATp16oScnBy8ePECXC6XLBzpdDqYTCYsLS2Rm5tbr+SS+rix1t6PrM7Dhw9x6tQpjBkzBnQ6HYsWLcK8efPq1Ydpbm4OV1dXImPPy8tDdnY2nJycYGhoSBax1OKborS0FJmZmbWO82ptUONQKEO5mkhMTERoaCjatm2Lzz77DEOHDsWlS5fIHNnY2Nh697jW5gJfF2fPnkVUVBQWLlwIPz8/bNu2Tecz1a9du0akyf369Xvrg+QvvviCJHsePHjQKqvIFA8ePMCoUaNAp9PRoUOHGmdmKxQKrdvrIiMjMXLkSNIOIBQKSSKS6qmPjIzUSg316tUrBAcHY82aNRAIBNi9e3ej11x0Op1ce6q7lkilUnC53CpjG+uaQsHlcsFgMCCXyxs8YlGpVKK8vBx8Ph9DhgxplKEWk8lEu3btiOlaeno6EhMToVQqweFwMG7cOOzevbvB21fH3NyctHhQiWI9OkD6/2/1eV4DaZYgGajs2b137x66du0KQ0NDfPXVVzUuGt8G+vbtC6DyC69rl0YjIyPMmzcPVlZWWLx4cbNWZCUSCSIjI/HFF19g+PDh+OeffzB16tR6909Q8y6pTKm2vTBNBSX1sba2hpWVFblRj7WVTldUVJA+2aSkJMTHxyMiIgJZWVk1XqQot1Sgsn927dq1b11l6NmzZ1iwYAGYTCa4XC4OHz5cr9epZ9Wpi5H6BTgqKgrvvfceCb7qgmoHkMvlLTo7l0ajwcbGBq6urnB1dYWHhwdxkqcoKSnBkSNH6gzy6HQ6TExM8Pr1a7BYLFy6dAnu7u5wdnbWCIY4HA4JnKujuLgYBQUFtd5KSkpQWlpaY0CtUqmQnZ0NOzs7mJubIz4+vtrASyaTIS8vj/wfMBgMTJ8+Hbt27dIwJjEzM4O7uzsZJ1LfhZx6kNyana2r4/jx43Bzc0P79u1haGiINWvWYPHixTUaUZmYmMDNzQ0+Pj5wcHCAg4MD+Hw+2Gy2VjJ1SkacmZlJbhkZGeR+Y0aN6RKqBxCovG7Up/IVGRmJ+fPnY8iQIZg5cyZiY2Px/fffN+t1Ji4uDnPmzCHf823bthHHel2Qk5ODiIgItGvXDtbW1vD29m6WqRlNQUBAAN5//30AldXAPXv2tPAe1Q4VJAOVZos1BckNgTL3cnR0RGFhIUpKSvDy5UtkZWXB29sbDAaDjP7SJlDOzMxEcHAwVq9ejUWLFmHLli2NShozmUwSAFd3fSgvL4ehoWGVNZN6kFxdSwh1/dDFtJPRo0fj1atXjZqW4+vrSwLkxMREjevL6NGjkZ6ejvv37zd6XwGge/fu5P6tW7d0sk09zUOzBckA8MMPP5DMTc+ePREXF9ekvbxNRdu2bTXGPulykd6+fXvMmzcP4eHhWL9+fbMvaIRCIWbMmAEPDw+cOXMGERERWhkMVFRUoKSkBEKhsMWCZAaDAScnJzJawd3dHXZ2djodRcXhcMDlcmFlZYWuXbuCRqOhuLgYKSkpiIyMxPXr1zVcsL/88ksMHDgQQOXFYsuWLW+NfFQdylk3ICCAVLzqk1F//fo1CR6NjY1hYWGBpKQksjiuqKjAL7/8gq+//hqzZ8+usxpKjWxoSoMuAwMDcDgcGBoaktEV1Axm6jM4OzuTxQKDwdDYb4VCgbt37+LAgQP1cuidPn06mEwmFAoFjhw5Qtzy+Xw+fHx8yCg9W1tb4sxbHVRVtz7zPsvLy1FSUkJuxcXFKC0tJU7ilpaWKCsrQ1lZGbKyslBcXFzr+aBfv36QSCRkcSEUCuHq6kqMrBQKBTIyMup9TqGC5PLy8hZNhjQElUqFzZs3Y/PmzbC1tYW1tTXWrl2LxYsXk0Wwqakp+vbti06dOsHe3h42NjZEqikWixtUFaLT6SQJWB2FhYWIi4tDbGwsYmJiEBcX1yImMsbGxuQ7rK3T8YsXL7Bnzx6MHDkS06ZNw8GDB3Xmtl8fysrKsGXLFvTt2xfffvst/vzzTxw/flxnxnJXr14l7Vx9+/Z9K4NkGxsbLFy4kDw+dOhQk4/SaiyU5Fkmk5GZvrpUKSUlJcHBwUFDgUWNPGrbti2YTCbc3Nzw+PFjrbabn5+PRYsWISQkBEuXLsXq1asb/F1U7y2u7vxDuXe/GSSry62rC5ILCgpgbGxMvC6kUilRw1DGXOqPy8vLUVZWhtLSUo3/A09PTwwfPrxRI9LMzc3JGuLNANnY2BijRo3C0qVLG7z9N6GKagBw+/ZtnW1XT9PTrEFyQUEBdu/eTb7cX3zxBVJTU/HkyZPm3I1Go/6F15XUmk6n49NPP8WQIUOwb98+XL9+XSfb1QZ/f3/MmTMHsbGx2L59OzgcTpVxBvUhLy8PQqGQLIKaWvrHYDDg7e0NNzc3dOnShUh7a0ImkyErK0ujukJVW3JycqBQKEhArS5pFAgEMDc3h6mpKczNzeHk5AQPDw84OjqCy+USR2AfHx98/PHHSEtLw61bt0Cj0TSUB1u3bkVYWFiT/k2aknv37iEgIABA5bFQnyC5uLgYjx8/hrOzM4yNjYlTpbGxMV68eAGFQoFz586hb9++GD58uIbB1ZvQaDQwmUwYGBhAJBLBwcEBLBYLbDYbLBaL3NQfv3mfw+GQ25uPqZs2SRULCwvY2dnh5cuXiI+Px5UrV3Dt2rV6SzE7duxIFsXUrHEKsViMhw8favRrMxgMWFlZwdbWFra2trCysiJBPHWrybVXHS6XCy6XW61RH51Oh0gkgkqlwqhRo8iCSSqVklnLOTk5yMvLQ3p6OgoLCzFp0iRs374dKpUKVlZWcHNzI3/HwsJCpKSk1HuhzGazyX69TVJrdUpLS7Fs2TJs2LABlpaWZBRMREQE3nvvPfj6+moY5SiVSlRUVCAnJwcxMTFkdAv19y4oKIBCoajSCgJUGr/VpJRRd2w1MjJCx44dybgboHJOe1hYGBISEvD48eMGyyG1gaoil5WVaZ0Mpnr79uzZAxsbG6xcuRLnzp3DiRMnmtUB/dq1a3j58iWCg4PRtm1bbNq0SSejje7du0d6JLt3714vs87WBJ/Px/Lly0ml7uHDh7h69WoL71XdKJVK/P333xg+fDhMTEzQqVMnnfrnJCcnV+ucXVJSgpiYGHh7e0OlUtVrTvOblJaWYsWKFVi3bh3mz5+PzZs3NyiBXFdPMnWsslgs0Gg08h51ya2zsrLItdrGxkZjXSgWizVmTaujVCqRmZmJpKQkMJlMzJ8/H8eOHWtU2wTlpVFaWlpFoTR9+nSEhYXpbOyTl5cX8daIjo7WS611STOMgGrWIBmozKI4Ojpi7NixoNFoWLRoEZYvX66zL2RzQLnUlZWV6cSljsViYdGiRWQGclpaWqO3qQ0GBgaYNGkSBg4ciN9++w3Pnz8Hj8cDi8VqUN94Xl4enJycwGAwYGho2CTZYwaDgcDAQPTo0QOBgYHg8/kkU0khl8uRmJiIuLg4vHr1igTFDa1ISSSSal8rEAjg4eEBX19ftG/fnrit2traYsaMGTA0NMS5c+dgZWWFHTt2vPVym1u3bmHKlClgsVjo3bs3fvzxx3o57spkMsTGxoLH45EA2cTEBH5+foiKioJUKsWePXuwcuVKpKSkgE6nw9nZGaampuS5ZmZm5DHQsAW2LqGcaK2trREfH4+kpCTMnTtX67mNo0ePJvcPHDhQ599ToVCQfuSa4PF4VQJnY2NjGBkZQSQSQSAQQCQSQSgUQigUVpsUoExpqPmzSqWSLHKosVZAZSUwMDAQHA6HyOapTL1MJkNCQoLWqhL1xeTbGiQDlefDb7/9Fhs3boRCocCgQYMwfvx4JCcnk978hIQEPH36FM+ePUNMTEyDVCaU7L06gzAej0cceNVVNpRbtK2tLWQyGUaOHElMsO7cuYN///1XK2NCbaCcm2tyo64NiUQCLpcLoNJwaefOnRg/fjzat2/f7Cqd1NRUzJ8/H19++SW2bt2KkJCQRi3ggcpE1O3bt9G/f39wOBz4+vpqXV1sKdhsNpYuXUrcrJOSkrBly5YW3qv68/DhQwwfPhxApSu3LoPk+Ph4dO7cudrfUZ4SRkZGsLOz0zpIBioD2JCQEGzcuBHTpk1rkLydSq6qVKpqg2T1wgmHwyHX37oqySqVCo8ePYKdnR0sLS1Joo9SklHJP6AyQcvj8cBgMECn02FjYwMrKysMGTIEGRkZ+OOPP7T+XOpQcvI3k9jjxo2Dg4MD5s+f36jtq0MpCAHg0qVLOtuunuah2YNkoLJXy97eHu+99x64XC6WLl2Kbdu21dsEqCVxdnYmWXldzKsUCARYvnw5lEolgoODGzUUvSHY2dlh8eLFYLPZOHLkCAoLCyESiVBaWgoajdagi71YLIZEIgGbzYapqalOg2QfHx/07NkT3bt3rzIOhEaj4datW3jx4gViY2ORmJjYLIZOpaWlePz4MR4/foyffvoJHA4HPXv2xJQpU+Du7o68vDxYW1tjx44dOu9fbwnKysrw77//om/fvqTSoc3nKisrQ2RkJJklKRAI4O/vj8ePH8PBwQH29vY4efIkzp07B1dXVwCVF2Aul0skuwwGA1KpVGcqBblcjvLycjLWg7pJJBIUFRWRXt78/HyN+xUVFWAymdi8eTNcXV1hbm6OhQsXYtWqVfXO4ru7u8PHxwdAZd+trvqgKJl0fZNuPB6PBMxCoRBGRkbw9vYmrQoCgQBcLpf8X7xp3CKVSpGdnY0hQ4agXbt2ePz4Me7fv4+oqKgGVcHUnbHfdqf8nJwcfPvtt1izZg0KCgpgY2MDPp+PHTt24OLFi00e1JWVlSExMRGJiYm4e/cu+bmVlRXc3d3h4eFBetxpNBq8vLzg5eWFL774AuHh4bh58ybu3buns4SUUCgki+qGJC1zc3ORl5cHHo9HDPxOnjyJbt264fvvv8eePXuazFCzOmQyGfbu3YusrCysX78ea9eubbRB1ePHj9G/f38AlSP33oYgWSgUYu7cufD19QVQqSBatWpVgxRpLUVkZCRJuHfo0AGGhoY6M2cLDw/HwoULYWVlVa2ham5uLoyMjCAQCDSqtNpQXFyM5cuXY9OmTZgwYYLG7G0KSiUkFArJ8SOVSsFkMsl4tJoKJOrnAPUgua5KMlBZFU5OTq530pPD4cDGxgb29vYYN24cTE1NsW7dukYrFKn2EvV97tatG4YPH46FCxfqzFRYIBCQfuTS0lKNc68eHfAuVpIptm3bBj6fDzc3N9DpdKxcuRJ79+7FlStXWmqX6oX6/LzGmnWYmppi1apVSEtLw+bNm5vdobdv376YPn06oqKi8Pfff5NMXn5+PnJycpCfn99gp8S8vDzY2NjA1NS00Qtce3t79O7dGz179iRjZijS0tJw+/ZtPHz4sNXMUaXch5lMJh48eAAmk4mDBw+2iIS+qbh06RKRkA8ePLhBwX9iYiIqKirg5uYGa2trbN++HWw2Gzk5OTA1NSUjnqhkCJPJRElJCQoLC1FRUYGMjAzk5eVBKpVCIpFAKpVWuV/dz9QDYep+Yy64crkcGzZswLZt2yAUChEYGIjPPvsMP/74Y71eTxnFAKhVZt7UqPceU9y8eZNUhqnKXXl5ORgMBgnszMzMYGlpiSdPniAoKAhCoRAeHh5wdnbGrVu3GiwTpRIkwNsfJAOVBjuhoaHYuHEj+f6x2ewW9SagWk2oWaCmpqbo0KED3nvvPfj7+4NGo8Hf3x/+/v6YPn06Hj58iJs3b+Lx48eNkjVTUmu5XN7g2ebR0dEQiUSwsLCAmZkZWCwW/v33X2RkZGD69Onw8/PDnj17mlVp8ttvv6GwsBArVqzA9u3bG7UojoyMJGaHtc3tbS1QrQQ2NjZIS0uDkZERVq5cqRP5eXOiUqnw999/Y/To0WAymRgyZAhOnDihk22XlZXh2bNneO+996odIUYFb9Soo4YmF3Jzc7F8+XJs3LgRpaWlZDqKsbExHBwcIBKJqiiHKHm/gYEBSktLawwU1feJy+WSIkhdxl0NoaKiApmZmZg8eTJEIhEOHToEQ0NDeHp6NqpPv7S0FBYWFuDxeBCJROjZsycmTpyIjRs36tQgsnfv3iQZeP369VY1hUNP/WixIFkqlWLVqlWYOnUqBgwYAACYOXMmOnXqhO+//77JJF6NRVdBsp2dHVatWoUnT55gz549zTqyg8vlYvr06ejcuTNOnTpFKk1ZWVlISkrSSe9Tfn4+bGxsSL+ntid7JpOJrl27YsiQIVXcggsKCvDvv//i5s2bWo9haA4oV3Iq23ny5MlGy4NaG7GxsXj9+jWRbnbp0qVBFdCMjAy4uLhg6tSpEIlEZCbh0aNHERMTAw6HA6lUiqKiIuTm5iI1NRVFRUUoLy9vVWNusrKysGHDBqxevRp0Oh2jRo1CbGxsnVI9KysrvPfee2Cz2cjOztapm6ouUKlUuHPnDthsNunJp/qdHR0d8eLFCw1PiX/++QezZs2CoaEhxGIxvvnmG8ycObNBiz2qkqxQKHQ2q7KlSUlJwcqVK7F+/XoYGBhg4MCBSEpKwl9//dXSuwagMrl5+fJlXL58GYaGhggKCkKvXr3g7u4OFouF7t27o3v37sjPz8elS5dw+fLlBimFqJFA+fn5jTLeKy4uRnFxMRISEmBlZQUHBwfExcVh586d+PDDD/Hdd99h8+bNzZpkuXHjBoqLixEcHAxDQ0NcvHixQdspLS3Fq1ev4ObmBicnJ4hEogYnFJoSGo2GESNG4NNPPyUBAYPBQHBw8FvnSE/x559/YuTIkaDT6Rg8eDBOnz6tswDnzp07GDx4cLVBskKhIIWJxhqNpqWlISQkBGvWrAGfz8eTJ080RlwCIAaBKpUKUqkUcrkcNBoNaWlppJXoTd6UW1PUJbduCB4eHli4cCFSU1Mxffp0WFtbw9LSEmZmZmjTpk2Dj+vMzEzY2dnB0dERX331FbKzs7F06VKdt32qS60vX76s023raR5aLEgGKiUZe/bsgVQqxbBhwwAAnTp1wu7du/HDDz+0ut5NJpNJZJGUWU1DcHd3R0hICC5cuIDjx4/rchfrxNXVFcHBwSgsLMShQ4eIe2BCQoJO5z2qG78IBIJ6L5LNzc0xYMAADBgwgMyYBSqrV3fv3sXNmzcRERHRZI7GumDevHlEkv/o0aN6j0l62zh+/DhxgJw8eTIePXqktfJAIBDgs88+I4tmpVKJpUuXIioqCu3atSN9rQkJCUhNTdXp/usSGo0GNpuN0tJS+Pv7IyEhAZMnT8aDBw9q/ZsMHz4cNBqNmL999tlnuH79eqN7GnWNRCIhPfmU2zaHw4GnpyciIiLI4l0kEuHEiRMYN24crK2tYWFhgQkTJuDAgQNavR+PxyPO1snJye9UBj42Nha7du3CvHnzAABTpkzBs2fPmt2Loi6Kiorw559/4s8//4SVlRV69uyJXr16wdbWFiYmJhg3bhw+/vhj3Lt3DxcuXNBKXkypQ3RlEKZUKpGeno7s7Gy4u7vD1NQUp06dQtu2bbF+/XocPXq0WSdpPHr0CCtWrMCKFStgbGzc4EpkeHg43NzcAFRKrlvbmsja2hpz5syBl5cX+VlSUhJCQ0Mb1FPbWsjNzcXt27fRo0cPiEQi9OnTR2dBzoMHDzBz5kyYm5tXW2Wn3KV1MY0jPj4e27Ztw5o1a+Dr64vffvsNKpUKaWlpKCoqalB735uVZIr6yK3rC41Gw5gxY/Dhhx9qHLvFxcVgMBgwMzODjY0NJBJJgxIxdDodHTt2xAcffIB///0Xly9f1vn6IiAggBh2PX/+vFWvX95WtEnF1GzlWzv1H77YRKhUKuzfvx9r1qwhQZpQKMTChQuxbt06jZNvS+Pp6UlOBA2tIru5uWHNmjX4+eefmz1AHj58ODZs2IDr16/j999/R1lZGWQyGWJiYnQaIAOVJ0mqIv1m73B1BAQEYNmyZThw4ADGjBlDAuS4uDjs2LEDn376KXbs2IHw8PBWHSB7e3tDoVBALBYjPT0dW7ZsadX72xgePHhAFsbW1tYYOnSo1tuYNm0aMfHIy8vDunXrEBERAU9PT40RDa31AiMQCDB69Gjs378fM2fOxPnz53H+/HkAlcdAp06danwtj8dDv379AFT6GyxYsAB8Ph8bN27Ejh07MHz4cPI3aE2IxWJERkZCJpOBTqfD19eX9LUxGAyoVCrs2rWLHP99+/atl9O2OpMnTyaLxPrMzX7buHnzJs6ePQuVSoX4+Hj07t27pXepVjIzM3Hy5ElMmzYNwcHBuHnzJuRyOeh0Orp164a1a9diz549GDp0KPku1ASPxyOjn3TV+0chl8vx4sULYgYWGRmJbdu2YcSIEVi+fLmGy3dT8/LlSyxatAj9+vXDxIkTG7QNdZ+W1iS5NjQ0xJdffonvv/+erNFUKhV+//13zJs3760OkCnUW19Gjhyps+2WlpbiyZMnREGpjrpxlS6CZCsrK3C5XPzwww/w8fFB//798eTJE2RkZDTY/+bNnmQKXcmtnZ2dsW7dOvTq1QvBwcFVklsvX74kSVlHR0eNkVX1wcvLC7t27YKdnR0WLFiAq1evgsFgwN/fnyTrdcGYMWPIfUrurufto8WDZIqHDx9i+vTpGjPEfH19sXHjRoSEhGiYuLQUfn5+5H5DTMasrKwQEhKCo0eP4s8//9TlrtWKUCjE8uXLyULh33//JYvW6OjoJjMLy8/Ph1gs1sg2qiMQCDBy5Ejs27cPK1euRKdOnUCj0SCVSnHt2jXMmzcP8+fPx/Xr13Um32lqgoKC4OPjA4FAgN9++63ZjdiamwMHDpALO1U9rC8dOnRAUFAQgMrA6+DBgygpKYGdnR3MzMwAAOnp6a1SstemTRvMnj0bhw8fRmBgIA4dOoQvvvgCJ0+exOHDh1FcXAxbW1uNC+Wb+Pn5EfOrGzdu4OHDhyQh9Mcff6Bz5844fPgwli5dig4dOuh0zndjKS8vR1RUFJlv6e3trbGwy8rKIudyHo+HLl261Hvbfn5+ZAFZUVGB06dP6/4DtAJOnDgBiUQCNzc3DBkypKV3p968fPkS27Ztw2effYaffvqJyDLt7OwwdepU/PTTT5gxY0a1o26AyvM+pWDSdZAMVAYaL168IOfesrIyzJ49G3K5HDt37iRqsOYgJSUFS5cuxYABAzBo0CCtX//8+XNSlVNff7QUAoEAEydOxIEDBzB8+HCyjsjIyMCSJUtw6NChd0b1ER8fT5zibW1tNUamNZYzZ85Um1CSSCRIS0sDjUYj7uANxdraGu7u7gAqHdi/+uor2NjYYOrUqY3abn3k1g35Dtjb22Px4sXYvHkzYmNjMWfOnGoVVUqlEi9fvoRKpQKdTifjnOqCxWLhyy+/RGhoKP766y8sXrwYjx49QnR0NBQKBZhMJtq1awcPDw+tk7pv4u3tTdoEdWnGqUcTmRa3htKicus3KSkpwaZNm3Dr1i1MmjSJjBgJDAxEYGAgoqOjce3aNdy+fbtFZgZSc0wB7YNkkUiE0NBQXL9+nVSamgMnJyeEhIQgNjYWs2fPRmlpKTw8PABU/r2bssepoqIC1tbWVVxw7e3tMXr0aPTo0UPjZJSRkYELFy7g+vXrTbJ4ag6srKwAVC7UHjx40MJ70/QkJibiypUrGDBgADgcDhYvXowFCxbUeZHkcDiYPn06eXz+/HkUFBSQ0VlAZe95azJsMjAwQFBQEIYMGQJ7e3vcuHEDc+fOrRLEx8TEICsrCyKRCC4uLjX2TqlXhtRHyUkkEty4cQM3btyAhYUF3n//fcycORNSqRQXLlzA1atXicFLS1JSUoKXL1/C29tbQx4NVMrlrl+/jvfffx8A0KdPn3pJRblcLmbNmkUeHzp06K0z/qkvEokEL1++hL+/P/h8PgQCwVt13isuLsavv/6K3377DYGBgRgyZAgCAgLAZrNJy8zLly/xxx9/4O7duySZRjnqlpWVNdlMY0p+3aZNGzKtYf369Rg0aBBWrlyJY8eONZtPRHp6OlatWoXVq1ejoKBAqwWzTCbDixcv0K5dO1hYWMDS0lLrUWq6wMfHB3379kW3bt00AiOpVIpz587h5MmTb9Uc5/py9uxZ4tQ9cuRIhIWF6WS7L168QHx8PIYNG4aTJ0+Sn8vlcjAYDFRUVMDExKRGF+y64PF4pLBUVlaGiIgISKVSLF68WKONrSHUFCQ3tpI8efJkZGVlYcqUKXX6HFRUVCA/Px+mpqbEKK42vL29MXv2bBQWFmL27Nkas4rz8/MRHh4OHx8fsNlsWFpawtTUFK9fv0ZGRkaDlIAfffQRuX/mzBmtX6+n9dCqgmSKe/fu4cGDB+jduzc++eQTWFhYAKg8Ufv4+OCrr77CnTt3cPfu3SathL6Jo6MjgMrZqNqYlbDZbISEhCAuLq7ejre6oG3btli6dCl+/fVXjWoMNSy+qauz1IKPyWSCy+XCysoKY8eOxXvvvUeeo1Kp8PDhQ/z111+NdgtvDVDfVcps6r/AgQMH4OPjAzs7Ozg7O2Pq1KnYvXt3ra8ZP348qRZHR0cjIiICQOXs1PLycnA4nFYzO93c3ByDBw9G//79UVhYiL/++gt///13ra65ly9fJr2EvXv3rjZIpipDCoUC0dHR1W4nOzsbP//8M06dOoUuXbpg6NChmDBhAv7++2/89ddfLW5olZubi5ycHIhEIpibm0MqlYLFYkEoFCIqKgrZ2dmwsLBAQEAAjI2Naz1vslgsLF++nBxDERER7/xcSXVzHHNz87cqSKag5p8+evQIVlZWGDhwIPr16wehUAhPT094enoiNTUVp06dwr///kskz7rqR64J6vpGo9GIieLFixcRFxeHkJAQmJqa4tChQ026DxQxMTHYunUr5s+fjxUrVuDly5f1fi0VJAOAg4NDswTJdDodrq6uCAgIQJ8+faoohORyOS5evIjTp0+3WpNVXRAWFoa0tDTY2tqibdu2jTKLepOTJ09i8eLF+OOPPzQCz1evXhHX5TZt2jRIcWFjY0MSUFSADFQec4097tSve+oqwcYad61atUqr52dkZMDU1BRcLhdcLrfG6/EHH3yAsWPH4tixYzh//ny1QW9paSnCwsLg6OgIOzs7MJlMWFtbw8rKCq9evdKqmOTs7IzAwEAAled3anKAnreTVhkkA5WZ4OvXr+Off/5Bv379MGzYMNjZ2QGozF69//77eP/991FcXIySkhIkJSUhNTUVxcXFKC0tRUlJCflXLBajtLS0UTIgkUhEpDHaGnbNmjULFRUV+O677xr8/trSrVs3zJkzB3v37q0ynoca4N7U8s2SkhKoVCrY2dlh6NCh8PT0JL8rLS3FhQsXcOnSpXeif4mCWuC/q9Wv6pBIJFi/fj22b98OFouFAQMGIDo6ukanZi6XS+S0UqkUv/zyC/h8PhgMBvh8PoDKhUJLVyb8/PwwfPhwtG/fHg8fPsSGDRvqbU50+/ZtzJgxAzQaDW3btq3ye8p4BKhcQNf1WRUKBe7cuYM7d+7AyckJQ4YMwZYtWxAXF4c///wT9+/fb7KqXF28evUKHTp0AJvNBo1GQ3l5OentunHjBj7++GPQaDR06tSpRvMbJpOJJUuWkKpNSUkJdu3a1VwfocVQD5ItLS1bnWGbtmRmZuLw4cM4fvw4unfvjhEjRsDFxQV2dnaYN28eJkyYgOjoaDx79qzJnZrpdDq5zqkvjF+9ekVmmRsZGWHHjh3Ncuw8ePAAP/74I5YtW4ZZs2bVO9Guvt7Qpp2lOmg0GlEtCIVCCAQCjZuVlRUxEaRMh9QpKyvDzZs3cebMmXfqul0bf/zxB1E9jR8/HqGhoTrZbkREBF6/fo3x48fj4MGD5OdKpRIvXrxAQEAADAwM4OTkRGTf9YHH48HGxgZKpRKJiYk6L4bUp5LcHJJ79f2gCj/q0Ol0TJ06FV26dMGiRYuqnFtFIhGsra3BZDJBo9GgVCpRUVGBpKQkmJmZwdDQEDQaDQEBAYiJidGoPteGeovVr7/+2mLX5f8CzdHY0WqDZAoqY3nx4kW4u7ujb9++6NGjBwlYCwoK4OjoWK/+DalUitLSUsjlcigUCiiVSigUCuTn50MoFEKpVJKbVCpFWVkZysvLkZeXB3Nzc5iammrtat2rVy/4+flh5syZDZ45rC1DhgzBpEmTsHHjRjx69KjK76nK+5syaF3Tpk0bfPLJJ/Dz84NcLkdRURGKi4tx9uxZXLhwoVnnVzYHXC6X/E3/KwsIipSUFOzZswdz5swBUJkYyszMrLZi0rt3b3JxvXHjBmQyGdhsNlgsFulVrO8FSdcwGAwEBQVh9OjRMDExwcWLF7Fnzx7k5eVptZ2ysjIkJibCxcUFjo6ORF5Kod5fqK2C4vXr19i9ezcOHz6Mfv364bPPPsOUKVNw8eJFXL58udkrOzKZDImJiaT/zdjYGOXl5WAymYiMjMTHH38MACTJWR3m5uYkaVdeXo6QkJAWkZU2N+rnCRMTkxbcE90ik8nw999/4++//0aHDh0wduxYeHh4wMHBAV5eXnj//ffxww8/4NKlS012XVRP2rxZPcrMzMTChQuxcuVKrFixAuvXr2/wTFptuHjxIry8vDB79mysXLmyXq+h1hs8Hg9DhgyBqakp6HQ6qaJxOBwwGAzQ6XTQ6XQUFBTAwsKC/IzBYIDBYIDL5ZIkZF2oH3sqlQrh4eG4fv067t2799b4g+iK69evY8yYMTAzM0NgYCC8vb0bNaNXne+//x47duzArVu3NJRTEokEycnJcHV1hbGxMVgsVr3/7tTamE6nN0iqXRdNJbfWFvURkJQRIAWbzcb06dPh6OiIBQsWaJxnDQwM4OXlBQaDUa2Rn1gsJkl7Ho9HYoH64O7ujm7dugGonA5w7dq1hnw0Pa2IVh8kqxMbG4vY2Fjs378fAQEBaNeuHQwNDWFtba1xgNYEi8WqdiFiYGBQa4a2qKgINjY25AJU3wW8ubk5vv76a2zdurXZpLcTJkzAoEGDsGzZshrlqjKZDDQarUZDrcbStm1bjB07Fu3atYOBgQEUCgXKysrwyy+/4Ndff23xCmFTob4AeRtlk43lxo0b8PT0xMCBA2FgYIDly5dj4cKFVZJKgwcPJvcvXLgABoMBsVgMpVKJwsJCxMTENLsjOI/HQ//+/TFixAhIpVKcPXsW169fb1RGPDo6Gi4uLqDRaPD09NSYJ9xYE0Cg8mL++++/448//iA9oWPGjMHdu3fx559/NqsrdGZmJlgsFpydnYl6h06na/SK1RYkf/XVVwgICICVlRVmzpzZqnrRmxL180R9A5i3DUqK7e/vj7lz58LFxQVcLhdTp07FBx98gF9//RWXL1/WefWJur7VtN2ioiIsWbIES5cuxdq1axEaGtosc4h/+OEH7Nq1C0OGDKnXfOz09HRUVFRAoVAgICAA1tbWyMrKqtGwKDU1tdZjrT5QFePnz5/j8ePH/yll1JvIZDIcP34cs2fPBgBMmjQJixYt0sm209PTcfLkScyePZuYy1FkZWXB2dkZdDodVlZWSE5Ortc2qcBVJpM1SRWzphFQTTEnuTZqCpLt7e2xYMEClJSU4Ntvv60S4Do7OxOlU3l5OVl7UIkkCqlUSiY4uLi44OnTp3Xu0xdffEHu//zzz++MiV1rRQ6gPivFxmhm36ogmUImk+HBgwfEGIlGo8HKygrW1tbg8/lERlSdnIjP54PJZGpkWamTSU22+1wuF4aGhuByuTA2NsaLFy/q3EcajYZ58+bh33//1ZnZQ13MnDkT7du3x6JFi2odmUNVcOl0Ojgcjs4y6O3bt8fHH3+sMbYrIyMDkZGRCA8PR0ZGxjsbIAOai9x33dW6Jvbt2wcrKyv4+/ujoKAAK1euxIIFC8ji08fHhxg8vXjxAq9fv4aZmRksLS2Rl5eH+Pj4Zq1UmJqaYvjw4Rg4cCBev36Nffv24cGDBzoJ0p8/f07mv3t7e2sEyepJucb2Xqv3hNrY2GDw4MEIDQ1FUlISjh8/Tvq9m5rk5GTQ6XRYW1tDIpFAJpMhPz8fFRUV4HA4Nap9rK2tSdIgPj5ew8TsXUf9PFHX6KS3neTkZBw8eBDOzs7w8fGBp6cnTE1NMXXqVIwZMwa//fYbLl68qLNrBPX3rE2xVFFRgdDQUMyZMwebN2/G0qVLm1wFVFZWhm3btmHlypUIDw+vc7xdSUkJCgoK4OPjAzMzs1rNhJRKJeRyOSQSCRQKBVHMKZVKlJeXkzY06vbm4/z8fKSkpLzT1+mG8Pfff+ODDz6AnZ0dvLy80KFDh2pVeg3h7Nmz6Nq1K6ZNm6bRYiKXy5GbmwsLCwtYWFjUO0im1rDqQaQuqc8IqOYIDtXPl1KpFHQ6HaNHj8bHH3+M8+fP49ixY1WSBHw+nySXMjMza7z2GhgYkAIPpTiti65du5K1b1pams7mautpWd7KIPlNVCoVMjIydCbRZDAYMDAwAJfLBY/Hg0AgwPDhw0kFzNLSss6F7ciRI2FsbFxvSVVj+fzzz9G2bVssXLiQzIisCapXmEajwdjYuNF/t44dO2Ls2LFEbglU9tqdPn0a169fh52dHWxtbcHhcKr0h71LcDgcFBYWgsVi/ScryUBl7+z69euxYMECMjIjJCQE3377LSQSSZUqMlApOc3Ly2vW74WTkxNGjRqF7t2749GjRwgJCdHKTKc+qCfTqHEQFJTMSywW6zTbn56ejgMHDuD48eMYOnQolixZgsTERBw/frxGczBd8vr1ayQlJWn8X6ampqJNmzawtLQEk8msIq/99NNPSU9ZczkOtxbEYjHKy8shk8m0nvf5tiESiSCVSvHixQv89NNP8PDwwMcff4zAwEAYGRnh888/x0cffYTff/8df/75Z6PacZhMJjnG6qoOy+VybNmyBdOnT8eqVasQHBzc5Ofv6OhonD9/HgsWLMC8efNqDWhoNBoxdQsLC0NoaChKS0tJO1hFRUWztXL9V1EqlTh69CiWLFkCoPKcpasgWaFQYN26dViwYAHGjh2r4XZdWloKCwsLrUYSUcq9pvpOtJZKslAoRFlZGWg0GszMzDB79mxwOBx8++23Na7PLS0tQaPRIJPJEB8fX+O2ZTKZVoE+g8HAZ599Rh7/+OOP+l7kd4RWMye5NaFQKFBRUYGCggKkpaUhJiYGd+/eJa6Adc1lEwqF+Pjjj7Fr165myciOGDECvXv3RkhISJ0BMlC5KKA+S2P64Lp27YrvvvsOy5cvJwFyRkYGduzYga+++gqXL1+GXC5HXl4e6HQ6hEJhtT0g7wpCoRBGRkZV+k//a5SXl2PPnj2kIuPm5obg4GCYmJiga9euACoXrnfu3CGvaa4A2c/PD6GhodiyZQsqKiowc+ZMrF+/XucBMlA5WoLqZVYfjwSgyR1+y8vLcfr0aXzxxRcIDw/HsmXLsGbNGg3zvKbizf9LSnJNo9GqtLV069YN3bt3B1Apf/3999+bfP9aE2VlZeByuRCJRDA2Nm7p3WlSLCwswGKxyDERExOD0NBQzJs3j6jChEIhPv30Uxw6dAiffPJJg6vrRkZGpKJWX4OsvXv3IiUlBcuXL2/0nNT6cPz4cXC5XPTp06fW55mYmIDJZEIqlSI8PBzR0dFISkpCTk4O8VjR0/Tcu3cPcXFxAColu0FBQTrbdl5eHvbu3Yvhw4dj6NCh5OeUP442QSedTgePx2uydrrWUkk2NTWFqakpBg8ejG3btiE8PBxz5syptYClUqkgk8l0Pn5u8ODB5NoWGRn5n1JDtSRSLW4NRR8k1xN1IwvKwbgmPvroI0RHRzdL5SYoKAjjxo1DaGioViYNubm5EIvF4HK5VUwP6sLNzQ2bN2/GkiVL4OLiAqDSuGnr1q2YNm0arl+/rnECKikpIRfy+g5+fxtRX9D9l4NkoPKiv3LlSjLPt2PHjti0aROpll25cqXZFncMBgO9evXCjh07sHDhQrx48QKff/459u7d2+QGYVQQrL6YAACBQKDx+6airKwMJ0+exJdffonnz58jNDQUoaGhGqqPpkZdTqreK+nu7o558+aRx8ePH28W86TWhPq863e1JxmorCJTx8CbQeurV6+wdu1afPPNN7h9+zZUKhX4fD4++eQT7N+/H4MGDdL6GmVkZASxWIzCwsJ6f6dUKhW2bNkCAAgODtb6PbVFoVDg2LFjGDduXK1Bufo1879gZteaOXLkCLk/YcKEal2VG0pycjJCQ0Px6aefolevXgAqE4ssFksrk1VKldBU39/W4G7N4XAwYMAALFy4EAKBAHPmzMGRI0fqfF8mkwkDAwOdTnYRiUTEnBJAs42V09M86IPkepKZmUmkhLUtZqjMlvrJtKnw9fXFN998g40bN2ptdFNQUAA+nw8ej0dMDOrCxMQEc+fOxdatW+Hh4QGgUl65ceNGzJgxA//880+NsjHq4m5sbNzki4+WQv17ob74/a+SnJyMtWvXkmA4KCiIXOybY/4tl8vFyJEjsX//fnzyySe4ePEiPv/8c/zyyy/NYtADgChJWCwWzMzMYGJiAj6fTy7STR0kU4jFYpw4cQJffPEF4uLisGbNGoSEhKBNmzZN/t7VmXdZWFhoVOyuXr36zs9Erg71ZNq7HCSrz4+vqbL7+vVrbNq0CTNmzMDNmzehUqkgFAoxbdo07NixQ8PsrjYoeTKfz9f6+JLJZFi9ejVsbGwwdepUrV7bEG7duoWSkhIMGjSoxueYmZkhNTUVr1+/RkpKSpPvk56aCQ8PJx4P1tbW6Nevn063Hxsbi7Vr12L69Ono1q0bOT9qU/WkKr0MBqNJJpjI5XKyzqsuSG7qADkgIAD/+9//0LVrV/z888/49ttv6+zrp6Aq8jweT2eB8tSpU4ky7O+//65Vxq1Ht8i0uDWUd7sJSoeUlpaSC29tMpZx48bh/v37eP36dZPuj0AgwIIFC3Do0CENQ6D6QvXCcblcmJmZ1SrTNjAwwKhRo/DRRx+Rk25+fj6OHDlSZQZzTVCD3zkcDiwsLJpkNEFLow+SqxIVFYW9e/fiu+++w+vXr1FRUYHY2FiN+bC6RiQSYeTIkRg8eDCSk5Pxv//9T2dmXNoikUjAZDLh7OyMAwcOgEajIT8/H1ZWVsjKymp2xUFpaSmOHTuGc+fOYdSoUVi/fj3Cw8Nx/PjxJpvRqx4k29ragsfjISQkBIaGhgAq54Xu2bOnSd67tUPN5uRwOO9skMxgMGBlZQWpVIq0tLQ6j8PU1FRs27YNv/76K7788kv4+fnB0dERq1evxoMHD3Dw4MFarx8ikYgEFw0x4SotLUVISAh27tyJiIgI3L17V+ttaMORI0cwd+5cXL16tdo+bHt7e5Jc0nYUnR7dc+TIEaI4mDBhAm7duqXT631ERAQ2btyIxYsX48KFC4iPj9cq2aPeTy8QCJqk5a+8vLzKWpgKkpuqH5nP52Px4sVwdXXF48eP8eTJE2RmZmoVlOfl5cHR0RFMJhNGRkb1bsWoiQ4dOqBHjx4AKv/u+iryu8e7WdJrIqhRNubm5tWarFhbW6Nnz544duxYk+/LzJkzERcXh4sXLzZ4GwUFBVAqlbUuzrp164a9e/diwoQJYLPZkMlkOHXqFL766qt6B8gAiDkN5UT+LkJJaAF9kKzOnTt3kJiYSGY/Lly4sEneRyAQYMKECThw4ACcnZ2xcuVKBAcH4/79+y1mFieRSGBnZwelUok5c+Zg3LhxOHbsGMk8i0SiFtmv4uJi/PTTT/jyyy+Rnp6OTZs2Yc6cOSRw1SXqI8Ds7e2xdOlS2NvbA6gMoNevX/+fNjmhzhXq5493CQsLC9DpdLBYLK1GCSUlJWH58uVYs2YNaYvo3Lkz9uzZg8mTJ9fYr2xoaAiZTKbhvaEtubm52L17N2bOnAlTU9MGbaO+PH78GKmpqRgxYkS1v7exsSH33xynp6f5iY2Nxa1btwBUnr8//fRTnb/H48ePsXnzZnz66ado166dVsGcTCYjgWpN55TGOulTkmv1SjIlY65P0NqQY0osFuPBgwdYvHgxwsLCoFAotD4eSktLSdKgscc1h8PB9OnTyeMDBw4026hXPc2HvpKsBRkZGXBzcyOB3psSj8GDB+Pu3btNXiXt27cvvLy8MHPmzEZtJzc3F1ZWVhAKheDz+RqBnYuLC6ZMmQIfHx/yszt37uDHH39scBUwMzMTIpGIZPrftRly6v2W/+W5km9SVlaGmJgYuLm5wdHREWZmZjods8Lj8TB8+HCMHDkScXFxWL58ebPOCK4NpVKJ5ORkKJVKMj/4+vXrePbsmcY4ipaiqKgIhw4dwh9//IEvv/wSP/zwA44fP44LFy7obISIRCJBUVERDA0N0b17d9J6UVxcjNDQ0P98QiknJwempqYwNjZ+J03/zMzMAFR+1xrSc/7w4UM8efIEw4cPx9ixY8HlcjFq1Cj06dMHR44cwbVr1zSSYObm5jAwMGi038CdO3cQGBiIuXPnYtmyZY3aVl2cPHkSc+fOxenTp6skjChDIJVKpe9JbiUcPHgQHTt2BIfDwaBBg3D16lWdy2wTEhJw/PhxTJgwAREREVp9n0tLS2FiYgIjIyMkJSVV+f3GjRthY2OD4uJiiMViiMViMgaMuk85R1PjkKiboaEhOnbsSF5LwWKx4ODgAE9PT6xcuRJlZWWQSCSoqKgAi8WCubk5uTEYDHz66acoLS0Fg8GAsbExDAwMwOPxkJaWVuN54s8//0T79u0BVK4rGhKU5uXlwcbGBubm5khISGjwdW7SpEnk3Pbs2TOtikZ6dIMcQH3+9xpTDdYHyVqg3g/k4eGhESQbGBigT58+WLduXZPug7W1NaZOnYp169Y1up+xuLgYSqUSdDod9vb2ePnyJfh8PiZPnox+/fqRno2EhATs37+/0UZklKRbpVLByMjonQsknZ2dAVRWzfWLGU0ePnwINzc3AJUmXo1RQFCw2WwMGzYMo0ePRlJSElavXt0sZnnaYGlpSWaXqlcDsrKy4OLiAjMzM9Dp9CabaVlf8vLysHHjRvj7++Orr75Cv379sHfvXp25fstkMvj5+YHL5SIrKwsSiURrs8F3lcTEROI67uTkhOfPn7fwHukOGo1GlEqNkQrL5XL89ttvuH79OiZOnIi+ffvC0NAQs2bNwpAhQ7Bnzx7ExsbC2NiYvF9jpZQA8L///Q87duzAqFGjcPbs2UZvryaePn0KqVSKjh074v79++TnbDYbTk5OACqT9P9lxUVrIj8/HydOnMDnn38OGo2GadOmYcGCBTp9Dzs7O8TFxeHIkSOYMWMGXr16Ve/KaV5eHkxMTGBoaAg2m11Fcj1v3jyYm5uTAolAICD/CgQCmJiYwN7enrhBq9+Sk5MRHh4OIyOjKiOgkpOTUVpainv37oHL5YLD4YDNZkMsFiMmJgbZ2dnIyclBdnY2+Hw+PDw8YGZmBgaDAYlEAjabDUtLS0RGRla7vrWxsSEqrPrOjX6TzMxM2NjYwMDAAObm5g1aq3l6epJxlhKJBN9//32D9kVP60cfJGtBeHg4xo8fDwAIDAzE9evXye/Mzc3x/PnzJl+kT5s2DVevXsWzZ88avS2lUom0tDRS3evRowc+//xzMhaqqKio2kx9Q5FKpcjPz4eRkRFMTEzeqSCZz+fD3NwcAJqst/Nt5uHDh+TYCQoKalSQbGBggCFDhuCDDz5AZmYmNm7ciPDwcF3tqs6g0WhEKpmRkaERCFNBMoPBgKmpaas5Fp49e4ZZs2ZhxIgRWLVqFVGPNNbobO7cuVi6dCloNBpcXFywceNGMk7lv05CQgK57+zs/E4FyUZGRmCxWOTc31iKioqwa9cu/PXXX0Tp5OLigs2bN+Ps2bPEVKmsrEwnapWKigps3boV69atw+3bt5v0OD137lwVE822bduS1i5dXPP16I7z58+jX79+sLe3h7u7O/r164erV6/qZNuGhoZEKk2pepYuXYp58+bVq8c4JycHLi4ukEqlMDc3r6J6lMlkjZLu+/v7QygUgk6nE1Ugi8WCSqVCTk4OLl++XONraTQa2rdvX0UKThVlmEwmvLy88PjxY42kEIvFIgmjwsLCBisaS0tLUVxcDJFIRLxBtIHH42H+/Plkf48ePdqkHit6akaGpq8k63uStSA2NpbIS/z9/TVcmtPT07F27domff927drBzc0NJ06c0Nk209LSIJfLMWbMGKxcuRImJiZQqVT4448/MHXqVFy9elWn/ZxisRh0Oh0mJiY6teFvaagqMqAPkqsjMTGRyMV8fX3h7++v9TaYTCaGDh2KAwcOoGfPnmSkU2sMkIHKxBllZqJuXgVA46Kq3nPYGpDL5fj1118xffp0cLlc7Nu3D0OGDGmUKz2fz0dxcTHy8vLw5Zdf4tGjRzrc47cb9fMFNVLvXUG970+XMvKEhAQsWbIEGzduREFBAWg0GsaOHYsVK1bAzMyswVWm6oiNjcWdO3cwbtw4nW2zOs6dO1fF4T0wMJDcb4hBp56mQ6FQYO/eveTxZ599pjNfAWdnZyiVSuTn5yM7OxtHjx5FQUEBpk2bVq/Xy+Vy5OXlgcvlNsn1pbpZydT1oa7RjjweDwqFglS4k5OTERYWhvv37yMiIgJyuRwqlYqoa4DKxDiVMFIqlXUmWBkMRq1912lpaRCLxaRyrg0zZ84kbVIxMTE4f/68Vq/X83ahD5K1QKlUkmyuQCAg8tHmYtKkSThz5oxOe/gCAwMxf/58BAYGgs1mIysrCwsXLsTBgwerddpsLFR2n+pDeVfQB8l1o25o99lnn9X7dXQ6HQMGDMD//vc/DBgwAHv37sXcuXNbfaCl3qP+ZiZfvXrYsWPHZtsnbcjNzcWGDRuwadMmDBs2DNu2bdNYuGjD1q1b0alTJ3h5eelEBvsukZSURBKRVKXkXYBOp5PKaFNVYO/cuYMZM2bg77//Bo/Hg7m5OWbPno1hw4ZpzG1tLCdOnEBQUBAxnGsuAgICAFQGZFSVXE/rISoqCv/88w8AQCgUYuLEiY3eJpPJBIPBgEgkQl5eHlQqFZRKJbZu3YouXbqQ70RdUBVSDodDemd1hXo1W928qz6YmprC0NAQcrkcYWFheP36NVlrFhYWIjU1FVwuF6ampnBzc4OZmRn8/f1JG0VCQkKNa1MejwcPDw907doVHTp0gI+PD1H4qZObmwsWiwUGg6FVEqF///7o3r07gMqCz6ZNm1rMFFRP86APkrXk8ePH5P7777/fbO/btWtXmJqa6ixrZWBggOnTp2Pp0qVgsVhQKBS4efMmDh8+3KRBXklJCZHdtbYKWmOg5kYD+iC5Jm7dukXMTVxcXMjohNro1KkTvv/+e4waNQqHDh3CrFmzNHr2WjPqpndvBskPHjwgGfdu3bo1635py9OnTzFz5kzcuXMHq1atwjfffKOVK7ebmxtZ4OiPjapIJBKisnBycmqS2aYtgampKXg8nsbnawpKS0vx559/4vjx4yguLkZ5eTlGjBiB7du3w9bWVifvkZWVhStXrjSJk3FNeHp6EtOu58+fN8j0TE/Tc+jQIRK0DRgwAO7u7o3ankKhgEKhgEQi0TjPFhQU4Mcff8TEiRPrdY4oKCggBRVnZ2edKvfUg9TaRqJWB5Uwk0gk1QbvycnJKCwsBFDpwePi4kLeo7a+bJFIBH9/f1haWoJOp0OhUMDU1BSenp6kj5lCpVIRPwwLC4tqp9W8ib29vcbs9J07d7aaNqn/KlItbg1FHyRryb1798jFqm/fvs1SDaXT6Zg4cSJ+/vlnncygo9PpWLVqFQYOHAig8qQ0d+5cXLp0CQwGA15eXk0qhS4sLASdToexsTEYDEaTvU9zwefz0aVLFwCV2cWmnpH9NnP48GFy/+uvv65RXtqmTRusW7cOs2bNwvnz5zFjxgzcvn27mfZSN/Tq1QtApQLlzap3WVkZnj59CgDkQt6akcvlOH36NGbMmAEej4d9+/ahT58+9Xptv379yP237f+wuYiMjARQmbwMCgpq4b3RDVQFRyaTNaljt7W1NaytrfHy5UssWbIEFy5cAFC5qN2+fbuGyqcxnDx5Ev7+/o0OgurLRx99RO6r+5/oaV0UFBTg+PHjACr7aufMmUPmdDcElUqF3NxcSCQSWFpawsHBgfzu8uXLKC0txYQJE8Dj8eDk5ARvb2+STHkTKildX9k1jUaDtbU13NzcYGlpWeN4UPWEjbaV5PLycuTk5NRaxY2KiiItSUwmEyUlJXj58mWNAbKJiQnatWsHJpMJhUKB5ORkvHr1iowd9fb2rtIulJ6eDpVKBTqdXueUCRaLhcWLFxN1yoULF3Dv3j2tPreetxN9kKwlYrEYf/31F4DKg1cb2WhD6dq1K5hMJq5du9bobXl5eeGHH35Aeno6fH19ERYWhjlz5uDx48ckuDMyMoKrq2uj36smqEqyuvPp20yfPn3IyfPGjRvv3GgrXRIeHk4CRoFAgLVr18LX15f83sLCAgsWLMD69evx/PlzTJ06FRcvXnzrXF29vb1JkPD06dNqja/u3LlD7lMSrtZOTk4ONmzYgG3btmHixIlYvnx5rYnCjh07kmScXC5/a1QAzY260c2gQYNacE90B9Xr15TyevVrVUlJCSIiIrBz505s3boVjo6OYDKZmDx5MiZMmNDo9yoqKsK5c+cwduzYRm+rLtq3b0/aMHJycoikV0/r5M8//yR9snZ2do2WXaemphJ35zflwnv37sWwYcMwfPhwmJiYwMzMDG5ubmjXrl2VFoPCwkLiKu/o6Fhr1dfMzAydOnWCm5sbrK2tYWtri8DAQLRp06ZK0aS6nmRtyM/PB41Gg0gkqnaflEolXr58ibCwMDx79gxPnz6t0RxLJBKRIFgulyMiIgKvX79GVlYWXrx4AQDENVsdiURSb1XjjBkzSKvF69evcfDgQa0/sx7dI9Pi1lD0QXID+OOPP8hJonfv3ujdu3eTvt/AgQNx6dKlRgcK7733HlatWgUnJyfMnj0baWlp5IQIVI64ouQjNjY21Z50dUF5eTlx+n0XguQePXogJSUFMplMJ6ON3nU2bdpEHHz5fD7WrVuHnTt34sqVKzh//jxkMhm+/vprHDt2rEn64puDXr16gc/ng8fj4ebNm9U+p6ioCM7OzrC3t0fv3r1rNRppbYSFhWHmzJkoLS3Fnj17qq0qe3h4YO7cueTxoUOHUFpa2py7+dbw6tUrxMfHIzs7G0KhsNn9LnQNg8Egi+em+j93cHBA27ZtQafTIZPJEB0dDaVSCQMDAzKP28PDAwMGDMCYMWPw9ddf10tWWRuXLl1C+/btNQzJdI2xsTHmzZtHHp86deqtSxL+11Aqldi+fTtJkA8fPlyj3aYhUEEhj8fTUNxlZWUhIiIC/fr1A5fLJSoNIyMjBAYGVpEWU7OAmUwmfH19qz0GzM3N4eXlRWTcEomErP1sbGyqrNMaU0kGQMz2qGC5JsrLy2tVobBYLBIgy2QyPHv2TGN0VGFhIQoLC1FeXk6mtqhDtYFwudwar78ffvghWeNLJBJs2rRJXwj5D6EPkhtAYWGhxly0WbNmoWvXrk3yXubm5vDx8Wl0Ffmjjz7C4sWLkZ2dTZwPi4uLIRAIEBwcTHpqY2JiSHaNOunq2vRBpVKhuLgYZWVlDTrBtiY6dOgADw8P2Nvb49mzZ1V6T/VUpaKiAiEhIWRcGp1Oh4WFBYDKSvyOHTsaNVO1pREIBAgKCoKdnR28vLyqyLwYDAZmzZqFkJAQkk0XCoXNUqHSJaWlpdi+fTu2bduGSZMm4ejRo/jwww/xwQcfIDg4GJs3bybVxLt37+LPP/9s4T1u3Zw9exYWFhawsrLCyJEjW3p3GgWfz4dYLEZFRYXOg2Qulws/Pz84OTmBRqNBKpUiKioKUqkUXC4Xy5Ytg6urKyoqKlBYWIiKigpkZWVh4MCBWL16daMciHNzcxEeHl7vVgNtMTExwZo1a2BoaAigMhlV2zgdPa2H1NRU/PTTTwAq14jTpk2rErBqAxXs0Wg0je+sra0t7t+/D1dXVxQWFuLRo0eIj48nCaJ27dppqHvKy8vJvHsulwtfX1+NdZepqSmpkkokEjx79gwPHjwg7UAAqgSQ6kGytj3JAMgUFRMTE43RiNpAyaip0VPPnz+vNqBOT08Hl8uFo6MjunXrhsDAQHTs2BEdOnTQ8ICgjjl1unTpoqEK2LZtm36N9x9DHyQ3kFu3bpGZeEwmE4sXL8aoUaMaNSalOnJycjBr1iwUFRU16PXUgpwyHLG3t8fp06fRv39/REZGIicnBw4ODli7di0CAwOhVCoRFRWlcdL19vZGly5d4OLiorPKr0QiAY/Hq/bE9DYxZswYcl9fRa4/EokEK1aswM6dO5GXlwc/Pz+ymH3b+eSTT2BkZASRSIT8/HzMmDGDVAZ5PB5Wr15N+nRTU1NJlWDYsGF19ka1RsLCwjBjxgz4+vpi/fr1+PzzzzXk4/Hx8di5c2cL7uHbwb1798h5vlu3bm+1saFAIACfzweLxdKJ4ZSBgQFsbGzg7++Pjh07kutGXl4eHj9+jJKSEhgaGmLdunVo3749hEIh0tLSMG3aNCxYsABcLhd0Oh0+Pj7YsmULrKysGrwve/bswblz5xr9md7Ew8MDmzZtIgFLXl4eduzYofP30dN0nDt3DteuXYNIJIKDg4OGIkBb1AM+KpCj0+mwsbFBaWkpbt26hb59+wKoHGkUGRkJuVwOBoMBX19fDZl2bm4uMU0UiUTo0KEDXFxc4OrqCi8vLwgEApSUlCA8PJy0Bqmv9dSrs0Dj5dY2NjYoLy9HdnZ2g88Pbdq0IcZm8fHxNa6R8/LykJaWhuzsbDAYDLDZbFI5FggEKC0tRXl5eRWXamdnZ8yfP588Pnr0qL4PuZUhR/2k1rUPJasdfZDcCHbv3k0MNWg0GiZPnoytW7eiTZs2On2fN2es1hcej4eVK1dqGOccOXIEP/74I4qKihASEkIkPSwWC8uXL0f//v3Jez579oycqFksFuzs7BAYGIj33nsP/v7+8Pb2hrOzc4PMy6jqwtsst+7atSsxXEpJSWn1I4laGzKZDNeuXcPp06dJP1dUVFQL71XjsLOzw5AhQ6BQKJCTk4O0tDSwWCzMnj0bADB+/HjSgy2VSrF9+3asXLkSQGWybdKkSS21642ivLwcKSkpiI6OJu0bYrEY+/btw/z585vUuOldQSaTkeCLTqc3i99FU0Gd18vKyrQekcLhcGBvbw8PDw94eXmhS5cu6Nq1q8aiWKlU4tWrV4iOjoZMJoOdnR02bdpE+pOpYysiIgJhYWFYuXIlccy1sbHB1q1b4eXl1aDPlpOTozECp7HweDxMmzYNmzZtIoqazMxMLF68uFovAz2tm2PHjpH1TWBgYKMUQtSxQ0mSraysiCnYkSNH0KNHDyIjLioqQnh4OKRSKSoqKuDp6akxsiwlJQUJCQlQKBSg0+mws7MjTtAymQyxsbEaASuVsK2oqKjS9tSYSjKdTodAIACXyyXHpLaYmZmR60xWVlaNhl5A5d8wPj4eKSkpeP36NVJSUpCUlITk5GRkZGSguLi4ymc0MjLC8uXLSXLin3/+wenTpxu0r3rebvRBciNQKpXYsWMHzpw5Q05mrq6u2Lp1K6ZMmdKic4AtLCywefNm+Pn5AahcgG3atAlnzpwhz5FIJAgNDSWOs3Q6HTNnzsSUKVNAp9NRWlqKR48eITw8HBkZGWRkDZPJBJvNhpmZGezt7eHi4qK1JJsaTcBgMBok12lpGAyGxiJW3bVZj3ao9wpRUv+3lalTp4JOp0OpVGLdunVE5ubg4ICgoCAMGTIEQOWx9+233+Ly5cs4efIkyYJ3796dOKW/TSgUCiQkJIDNZqO8vBxLly7FpEmT8NdffzVYTvdf5Ny5c+QY6NKlS4MDuZaGkodS5/n6IhKJYGNjA2dnZ1haWoLH45HeSJVKhYKCAsTExODevXtkYRwQEIAtW7aQRXNubi4WLVqE2NhYst1Xr15h/vz5SE5OBlA503bt2rX1GkPXVDAYDPTp0wc//PADBg0aRAKhuLg4BAcHvxOqmv8i+fn52LJlC1kTjh8/HgMGDGjQtqhtUApFSl2Sn5+PuLg4PHv2TGMUqVgsxtOnT6FUKkGj0eDs7KxRtElNTcWjR4+Qk5MDqVQKqVRK1BhvVq6NjY0hFourLdI0pieZRqNBpVJBoVA06NrAYrGIw7xYLCYJ9rrIyspCcnIyCZJfv36NuLg4REdHIzIyklyDuVwuli9fTta0MTExeiVUK0Vv3PWWcOTIEQQHBxN3aBqNhmHDhuHQoUOYP3++zivLddGzZ0/s3LmTZBGLi4uxdOnSasevyOVybN68GX/88Qf52bBhw7B8+XLSh1JUVIS4uDjcv3+fSLGzs7ORn58PuVxO3AW16b8pLS0lF4C3UXI9cOBAsiiLiopCWFhYC+/R20tycjISEhKQlZXVpK7qTc37778Pf39/AJWmK7/++qtGH+7ixYvJYufMmTNkEV9eXo6jR4+S582bNw+Ojo7Nt+M6Ijk5GTKZDHl5ecjPz9fJuLr/GhKJhIyTAYDPP/+8BfemYTAYDBIka1sJ9fDwgJ2dHQwMDFBcXIzCwkK8fv0aL1++xIMHDxAZGYmsrCxiZDV48GCEhISQa1ViYiIWLlxYbd9gTk4OgoOD8ezZMwCVyd4FCxZg1qxZzTqbWiQSYezYsTh06BDmzJkDIyMjAJWBx4EDB7Bw4cIGV9j0tA7Cw8M1zunTp08nIwG1QSwWQywWQ6lUaphLUTN+w8PDq4wPlEgkGrJpGxsb+Pj4kGuPRCLBixcvcP/+fTx69AjR0dFVztXU7GAul1ttsqYxlWSFQkEMuxrid+Pi4kIS0S9fvtRpEpZSVFLtUbm5uVi7dq3eqOs/jD5I1hExMTGYO3cuDh8+TE44DAYDPXv2RHBwMLZv344BAwY0adWUx+NhwYIFmD9/PjmZpqWlYcGCBaSiVR0qlQoHDx7Erl27SLXYwsICW7du1eiLUyqVyM/PR1paGhITExEVFYV79+6Rz0td7OuDXC4nkqSWrLg3BENDQ4wbN448PnToUAvuzdtPbGwsXFxcYGlpiQEDBjTrglVXeHp6YsaMGeTxoUOHIJPJcPv2bUgkEmKYAlQu1n/77TeN11+5coWMeeFwOFi+fHmjTF9aAg6HQxYsTTln/V3n+vXrSElJAVAZNDaVSVRTYWRkRP7/tQn2WCwWuT5GRETg2bNniI+PR3JyMrKzszUW8gwGAzNnzsT48eOJ9PnevXsIDg6u1fSvrKwMoaGhuHLlCvlZv379sHPnziaff9yuXTssXLgQmzZtwvjx4zWuew8ePMC0adNw7tw5vfLiHeHMmTPkPE/NT9bW4JXL5YLP54PJZJKAklqHAZXrTsp0VR1qFFJubi6ASnMuf3//el9bqe9mQUEBWROqo95uQG2T+t7Wx0G+oqICdDpd6/Wwvb09LCwsoFAoEB8fr7VSpTYYDAaWLFlCrtMlJSUICQnRJ6z+4+iDZB2iUCjw22+/YcqUKTh16pRGFt3V1RUzZszAkSNHMG/ePHTr1k2nzs6+vr74/vvvNeRjf//9N+bPn0+yjnVx9epVLF++HC9fvoS9vT1sbW2xdetWItmuDsqpGgDpF6svubm5EIvF4HK5b9WietasWSSA+ffff/Hq1asW3qO3m/T0dFLdsbCweOtcns3MzLB06VKyOLhw4QLu3r0LoHIxkJycDJFIBBaLBRqNhj/++KPazPTOnTuJdMzCwgJLlixp9Mia5kIgEMDPzw8qlQrh4eG19ojpqR2lUqkxh3Pq1KlNOnJI14hEIojFYhQVFWk1wk39+lHbwlQoFGL16tXo378/hEIhioqK8Msvv2D9+vX16hVWKBT4/vvvsXPnTlIRs7a2xqZNmzB27Fidmm96eHhg4sSJ2LdvH9asWYOgoCBYW1ujuLgYKpUKd+/exeLFi7F27dq32tFfT/UcPnwYFy5cAFApmV64cCECAgLq/Xr1nmQqSC4oKCABaUJCAng8XrWGj0qlEs+fPydyaYFAgICAgHqt0yhPgZqUIOqVZCpIpo71+qxrqb5qbXr7HR0d4ezsDKBSiUiNb9IFdDodCxYsQGBgIIDKzxISEkKSlXpaJ1Itbg1FHyQ3AQUFBTh27BgmT56Mbdu2aTgDstls9OrVC4sWLcKJEyewcuVKDBo0qNoZbvXB1dUVwcHBWLt2LTmJisVibN68Gdu3b9faMCc6OhpbtmwhvVt8Ph+hoaG1ZkALCgogkUi0Hq1RVFQEPp8PgUDw1lTN3n//fXTq1AlA5f7/73//a+E9ejf44YcfSMb6gw8+QIcOHVp4j+oHj8fD8uXLSctAREQE9u/fr/GcjIwM8v1ms9mIjIysdlsymQxr165FQUEBgMrE16pVq94Kc7tJkyaBy+WCwWAgMzNTXw1rJE+ePMHff/8NoPI7NmfOnJbdIS2wsLAgI6C0QSQSQSqVoqioqEZ5o6GhITZv3kyqPTKZDEeOHMGJEye03s9r167hm2++QUxMDIDKhfL48eOxc+dO9OrVS2M2bX0xMDBAx44dMXPmTBw5cgSbN2/Ghx9+SFpzgMrA4/fff8eXX36JDRs2kJnxet5NfvjhB2LwymQy8e2339Z7hjJ1HmWxWKDT6ZBIJKQ6DFR+/9PT0zUMut4kPj4esbGxZFqJn59fne7uMpkMEomkxuOwtiC5pnnD6lCvqU9LDofDgY+PD2lBEovFtSojG8KsWbPQrVs3sk+hoaH64oceAMDbUaZ4S5HJZLh58yZu3rwJZ2dnDBgwAD179iSLXiaTiYCAAAQEBGDatGnEfe/169fEWIByn6ag0+lwdHSEr68vunbtShYLFJGRkdi+fbvGiVRbsrOzsXDhQixYsAAdO3YkGdAVK1ZU6z5cXl5OTnosFqvevYjFxcWQyWQwMDCAqalpq3fyNDc3x9SpU8njXbt2tfp9fltIT0/HyZMnMX78eNBoNAQHB2PJkiWIj49v6V2rERMTE6xcuRJOTk4AKoPhDRs2kH5JiszMTBIkq1Qq4l1QHfn5+Vi7di3Wrl0LNpsNX19fbNq0CStXrkROTk5TfZRG4efnR4xpysvLGxSw6KnKvn370LZtW5iZmcHPzw9Dhw5t9bOmeTweuRZoWxkVCARgsVg1jnLhcrkIDQ0lLUAFBQVYs2ZNvY17qoNykR4zZgw+/vhj0Gg0Mrpn4sSJuHXrFiIjIxEdHV2lKs7n8+Hk5ARHR0fyr6urKzEaU4dSWFy+fBn379+vco7Q826za9cusNlsdO/eHSwWCyEhIVixYkWdwZ5MJiMmWnw+HyqVqspxVVFRUaeMOjMzE2VlZfD29oZcLoe7uzuEQiEZ9fkmTCYTLBarxoC3Ork1dXzUJaGm3K3VX1PT8xwcHGBiYkKeX1RUhKioqCrHD4/HA4fDAY1GQ3l5eb2LQzQaDdOnTyfmZ3K5HOvWrdMnrt4S5KjfeCft5itoog+Sm4nExET88MMP2L9/P3x9fdGlSxd07txZw7jA3t4e9vb2CAoKIj9TKBRQqVSg0Wig0WhECpaenq7RL1xUVITTp0/j/PnzWo/cqI7y8nKsWbMGs2fPRp8+fcBkMrFs2TIsXry4yiJfvVIuEom0CtALCwthbm7e6s272Gw2lixZQi4A165dw8OHD1t4r94tTp48CUdHR3Tv3h0cDgcrVqzAggULWmVwaG9vj9DQUHL8lpSUYPXq1aTPXh0ej0dk00lJSXUen7GxsViyZAlCQkJgaGgIe3t7bNmyBatWrWp1SQNHR0csWbKEPD569CiphOtpHGVlZfjuu++wZs0aAJUmXq9evdJ5FUWXUOdxlUpVY7BbHTQajSSSqjuGqAqci4sLgMpWneDg4EYlgykUCgV+/vlnPHnyBF988QUxQjIzM0P//v0xatQoAJWfSalUQqVSQaVSEcloTUilUjx9+hT3799HWFiYPqH6H0apVGLr1q1gs9no2LEjOBwO1qxZg82bN+PBgwc1vo4qOIhEIigUChQVFVXpEf7777/rJT0uLi7GkydPiGO+tbU1+Hw+IiMjqwSdBQUFsLS0hKGhIZhMZpX3rM7dmgpMDQwMwGAwakwEGRsbk2tgTccvh8OBr68veDwe5HI5ZDIZUlNTkZqaqnH9VH+eRCIhAXtZWRmSkpJqXTvQ6XTMmTOHGKqpVCps3rwZT548qfE1ev576OXWzYxCoUB4eDj27duHzz//HLNnz8bPP/+MV69eVWuQwGAwwGQywWAwqu2VSktLw549e/D555/j3LlzOgmQKVQqFXbt2kXm//J4PISGhpJZjhRSqRTl5eVQKpVam3Dl5+ejrKwMfD6/2gx8a0HdpTwrK6uKpFaPbti+fTtevHgBoPJiumbNmjqlYc1N27ZtsWnTJhIgZ2Vl1eioC2jOAldfXNTGq1evsGDBAtJPZmxsjM2bN2Ps2LENkoE2BSYmJhrOwg8ePMBff/3Vwnv1bhEREUEmD1CJyur6D1sLpqamqKioQG5urlaSeyMjI/L86vqR582bR7wxSkpKsGLFCp0EyOrExMQgODgYixcvRlhYGFQqlUbwQaPRyPW4pgA5JycHV69exerVqzFu3DisXbsW169f1wfIeqBQKLBhwwbiv8FisfDtt99i6NChNb6mvLwcNBqNVFKr+87/9ddfSEhIqNc+SKVSREZGEp8akUiEtm3bVllbJicno6ysDEKhEA4ODlW2I5PJyFrzzUoyUHs12crKCgwGA/n5+dVWklksFtq3b0+uK3l5eXj06BFSUlKqrG9tbGzI89R/x+Px4OXlpdHmoA6TycSMGTNIgKxQKLB582bcu3evxv3W0/pojhFQ+kpyC5OYmIjExET8/PPPYDAYsLGx0ZBwUQtxKnutUqmQlZWFiIgIREdHN7mxgEKhwMaNG7FmzRp4eHjA2NgYq1atQnBwsMaFPz09Hc7OzrCwsEBiYmK1AX91FBYWws3NDXQ6HW5uboiOjm6qj9JgPvvsMzK7tqysDKtWrdLKkEZP/ZHJZCTDbmNjA2tra2zevLlV9Aix2WxMmjRJY1Hz6tUrhIaG1lo1U+/V1yZwoILv5cuXw8vLC0wmE+PHj0dQUBB27dpFeilbAqFQiJCQEHJ+iouLw+bNm3WapNNTyeHDh+Ho6Ah/f3+IRCKEhIRgwYIFWvtNNDVmZmbEW0Nb4zYrKysYGBigsLBQQ5kEAFOmTEH37t0B/F+/YE0JKV3w/PlzPH/+HAKBAN7e3mjfvj1cXFzAZDI11FxlZWVITk4mLVJUYKFHT03IZDKEhobim2++Qe/evUGj0TB16lSYm5vjxx9/rPL89PR0WFtbk95gXSSGlEolYmNjIZFI4OjoCJFIBB8fH0RFRZHzNyVZVp9T/iYSiQQcDodUktXXg8bGxtUqQuh0OoyNjUGj0Wq8ZgqFQlRUVMDAwAAvX76s0nKoDmVCVlpaivDwcNBoNIhEIvj7+1f7/kBl9XnZsmVo164dUlJSYG1tjQ0bNuiVgXqqRR8ktyIUCgVSUlKQkpKCW7dutfTuECQSCUJDQ7Fp0ybY2dnBxsYGy5cvx+LFi4mkJi8vj8yvs7KyqvciRiKRICkpCc7OzjA1NYWDgwMxDWsNDB06FKNHjwZQeXHZuHGj3vGwiSkpKcHSpUuxatUq2Nvbk5FIBw4caLHjws/PD7NmzdJQUTx+/BgbNmyo1aGTTqeTER1U24Q2lJaWYtmyZfjkk08wevRo0qe1adMmXLp0CWfOnGl2ObqFhQVCQ0Nha2sLoDKYX7VqlX4uchNBVaC2bNkCOzs72NnZYdmyZQgNDdXKHbYp4fP55HsuFouJAqI+sFgskmx5s4o8dOhQDBs2DEDl+XfDhg1kvnhTU1paiocPH+oXz3p0ikKhwPbt25GTk4MxY8YAAEaNGgVzc3Ns375dwyyrvLwcBQUFSEtLQ15enk7PsUlJSWAwGLCzs4OxsTGsra01klvU2q4mt2oqSKYqyerzlC0tLatdJxkYGJAkU03qCh6PB6FQCIVCUWuATO2DQqFAeXk52V9zc3PI5XJwOJwqqiuRSISVK1cSVaCpqSlCQkJqNNPUo0cvt9ZTL0pLS7FixQpiGuHh4YFPPvmE/L6iooLM7rO3t9dqjEZqaioKCwshk8lgY2PTauSEH3zwgYZR1759+/D06dMW3KP/Dnl5eQgODkZ4eDjy8vJgbGyMhQsXYsaMGVqPGmsMTk5OCA4OxurVq0mALJVKsX//fqxatarOIKVdu3YQiUSQy+UoKCiAra2t1nOgKQffuXPnkmo6jUbDoEGDsH//fixcuJBc9JsSBoOBgQMHYuvWrSRAzs/Px8qVK7XqP9WjPdR8X2phSTmf18dJtqmhDOaoBevLly+1UhQ4OjqCRqNBqVRqyJudnZ3x+eefk8c7d+4krT969LztHDt2DLt37ybqou7du2P16tVVpoRER0cjKSmpXpJ9BoMBV1dXdOzYET4+PrCxsak1MZuQkICCggJIpVKN6yqDwSBj52p634yMDKSnpxMPioSEBMTHxyMnJ4c4Ub8JnU5HaWkpKioqalQbUu/HYDDqbN8rKysDg8GAQCAAg8GAl5cXWT/m5eVpJOvMzc2xceNGcq2k2jb0AfLbS3PIrfVBsp56k5ubi7Vr15KM3UcffaQxyiApKQlAZbaQWkTXB5VKhejoaFRUVIDFYsHd3b3FjbwmTJiASZMmkccnT57ExYsXW3CP/nuIxWKEhoZqOE0OGDAA+/fvx4cfflincU5j8PLywooVK7Bz504i9QQq3eNnzpxZb4O8nj17Aqg0QsnPzweLxSLSfW1JTEzEggULcOjQIRKc0+l0BAUFYdu2bfjuu+8wadIkrX0B6sLe3h7jxo3Dvn37MH36dAgEAmRnZyM1NRULFy7Uqmqop+FkZWUhNDSUjFby8vLC2rVrW3R8Hp1Oh6+vL9hsNrhcLqKiorQa/cThcIjnQHp6OqmisVgsLFiwgBjenT17Fjdu3ND9B9CjpwW5fPkyVq9eTc7n3t7e2Lx5cxXfl/q26bi4uMDGxgZcLhempqZo06YN/Pz8ah3PmZubCxaLBQsLC1J5tba2Bo1Gq3UesZGREWmJAiqDZldXV5ibmxODvTdRKpUQCATgcDhVPiNFcXExaWej1Ik1Qf3dhEIhAgICYG5uTj7T8+fPyTXa3d0dmzdvJuvSvLw8LFq0qNlUKXreXmhonDu2nv8gH374ISZOnAig0qhk1qxZpBfLy8uLyF0ePnxY795koLIi0b59e7BYLJSVleHx48fN3uPIYDAwZcoUDB48mPzsp59+wq+//tqs+6FHk0GDBmHy5Mka0q+cnBycP38ed+7c0Ynk2M3NDf7+/ujSpQvc3Nw0fldUVIQTJ05olSjx8/PDqlWrQKPRwGKxiNnJo0ePsGrVqkbtq0gkwqBBgzB06FAYGhpCIBDAzc0NYrEYsbGxiI+PR1hYGJ48eaJ1rySHw4G9vT0CAgLQo0ePamdwHj16FBcvXqyx70tP0+Hs7IzVq1eTyk9KSgpWr15NzHiaEwcHBzICLTY2Vut98PT0hIWFBRQKBR4+fEiC5K+++gpDhgwBUFmhWrBggVbXEj163ibatGmDFStWwMjICEClcu+7777TSupvbGyMtm3bQiqVoqysDHQ6HSKRCGKxGDweD9nZ2UhPT6/S829jY4M2bdpApVKRdiYXFxfY2tqioKCg2rGfQKWyztraGiUlJRg/fjzodDpOnToFFouFjIwMfPXVV9W+rnPnzkRNJZfLUVZWhuLiYojFYuTm5kKhUMDMzAze3t4AKq/zNalTnJ2d4eDgADabDblcjsLCQhQVFSEhIYE8v2/fvpg+fTpJuKWlpWHFihWtcmqGnvohFApRXFyMUyIR5G98n6uDKRRiTHExRCJRle9/XeiDZD1aQ6PRsHbtWvj6+iInJwfPnj3Drl27AFS6Gnbo0AE0Gg0pKSlITEzUatsmJibw9fVFeXk54uLiqnU6bSpMTU2xePFi0lsHAP/73/9a/WzS/wqGhoYYP348BgwYUEVCFhcXh7t37yI8PBzp6el1BoVU77yjoyPatGmDLl26YPDgwVCpVEhMTCTVsJycHPz222+4evWqVv1gZmZm2LFjB6nyHTt2DAMHDoSZmRlUKhWWL1+OiIgILf8CVTEwMMDcuXPx1VdfgcfjIS8vr1qn06KiIqSnpyM9PR05OTlV+qP5fD7s7e1hZ2enMZZOHZVKhSdPnuDEiRONmk2rp/HY2dlhzZo1xChLLBbju+++q3WcjK6h0+nw9vaGsbExcnNziSt9feHz+QgICACNRkNSUhJRInXo0AETJ06Eo6MjZDIZ5syZ06RGXXr0tAbe9HoAgN9//x0//fRTveZq29vbw9nZGUBlG0xBQQEMDAxgaWmp0eJTVlaGrKwsFBYWwsDAAG5ubmCz2SgpKSHtZN27dweTyUR8fHyNHix79+6Fra0txGIxab3btGkTGaE2adKkascB8ng8eHh4kGujTCYjqjC5XI7MzEykpaXB3t4eNjY2UCqVkEgkyMvLI4kygUAAHo9HxivyeDxUVFTg6dOnpCWQwWDgyy+/JMk2AIiKisKGDRv0bvNvOfogWU+rx8zMDIsWLYK7uztoNBq2bduGmzdvAqiUtlhZWUGpVOLhw4dam00EBARAIBAQyUxz4Ofnh4ULF5LqjFwux/fff6+X+LVCHBwcMHnyZAQGBtb4HCoopLLF6qPUzMzMYGtrW0Wu3aZNGyJVjouLw549e3D69Ol6LVDUadu2LWbMmEHmmIeFhWH16tX46KOP8OmnnwKorBTMmzevUdU/Y2NjzJw5Ex07dgRQGXRkZmYiJyenRrlbQ3j+/Dlu376NO3fu6GcgtyKsrKwQEhKisaj+9ddfcfToUa1c1BsKVe1RqVR4+vSp1qoCHx8fmJqaQiaT4eHDh1AoFDAyMsKuXbtgaGiIrKwsnDlzBpcvX26iT6BHT+uCx+Phm2++wXvvvUd+Fhsbi40bN9ZZ+WQymejQoQNxo6aCz6ysLEilUuIgr45CoSAS64iICFKU6N69O+h0OuLi4mqUWx8/fhxCoRDZ2dn48ssvAQDjxo3Dxx9/DKDuAoOxsTH4fD44HA4MDQ01RiUqlUrExcXByMiI/P5NKPdtSo4tk8lw//59KBQKiEQiLF68GL6+vuT5f/31Fw4cOKD19VxP60MfJOt5K+jWrRsWLVoEoNKF8ZtvvkFWVhbYbDY6duwIOp2O7OxsvHz5UqvtUhI+hUKBu3fvNqnkms/n49NPP8WgQYNIZS07OxsbNmxo8ZFDemrHxsYG7733Hrp3797ooFClUoHL5cLIyAgFBQWk1yksLAy3b9/G69evkZKSUqPkk8PhwN/fH7169dJY4GRnZ2P27NkQi8Wg0WhYtmwZCWoLCwuxfft2rc3gTE1NERQUhLFjx2osLK5evYo9e/ZAoVDAxMQEgYGB8PT0hLW1NWxtbevVq1xSUoLU1FSiArl//z7JzOtpfXA4HHzzzTcaffOvXr3Cnj17mvz8RSVDy8rKtDbUoqShABAfH0/62kNCQkjy6+HDh1izZo1ud1qPnreAIUOG4IsvviASYbFYjO3bt9cpv6Yqx8bGxhCJRCQALiwsRGRkJExMTGBpaQkTExPQ6XSIxWJwuVzExMRoBOHdunUDg8GoMUg2MDAgLWgvXrwg60B7e3vs3r27ys/rA5fLha2tLaysrMiIqNTUVKhUKtjZ2YHFYoHBYJD9LiwshFgsBpvNhpubG5RKJW7fvg0XFxcsXbqU9CfL5XLs2bMH165dq/e+6GndUEHyCZEIsnoEvQZCIcbpg2Q9LcHs2bPx/vvvAwBevnyJJUuWQKFQwNnZGfb29lAoFIiNjdWq/0MoFKJ9+/YAgCdPnjRZ32Pv3r3x+eefa2Qpw8LCsH37dn2v5VuGlZUVOnXqBEdHR1hbW8PGxoZIUd9EqVQiLS0NycnJ5BYdHY2SkhKMHDkSo0ePrtYMiXpdeXk5lEollEoleDwe2Gw2rK2tyWxIqq8yJiYGO3bs0JCKcrlcbNmyRaPPNyIiApcuXcLz58+JQ7w6AoEA1tbW8PLyQvfu3YmcjaKgoAC7d++ucwHF4XDIfgL/N3sdqHTsTk1N1cvQ3lKGDRuGzz//nCyKVSoVLl68iKNHj2plpKUNHTp0AI/HQ1paGuLj4+v9OgMDA7Rr1w58Ph/l5eV4/PgxlEolhg4dSqYJFBYWYubMmfrvo57/LK6urli0aBExtgOAP/74A4cPH65XNZROp6NNmzbk9eoBr4GBAXx9fcFkMmFgYICysjI8f/6cqP7ee+89MJlMvHr1qtqZ55aWlti/fz8A4Pbt29i0aRP53ffffw8HBwcAwOTJk7VOsnI4HPj6+oLH42moTGrC29sbZmZmKC8vB4/Hw6xZs0g1PT8/H+vWrdMbdL1j6INkPW8NXC4XO3bsICfiK1eu4PvvvwedToeXlxcMDQ1Bp9Px+PFj4lhYFzQaDd26dQOdTq/xJN0YAgICMHbsWHh5eZGfVVRU4Pjx4/jjjz90+l56Wg42mw0TExMoFAqNW1lZWa0XXTabjf79+2PUqFE19ueqI5VK4ezsDBsbGxQXF+PRo0c4fPgwrl69Wu3zDQ0NMWfOnGrl4kVFRSguLoZKpQKdTieStJr4+++/sX//fn1SRw/c3d0xa9YsjfErRUVF+PXXX3Hp0iVUVFTo7L2YTCZRTLx48UKrJGi7du1gZGSE4uJixMfHo6SkBH5+fli5ciUJ8leuXIknT57obH/16Hkb4fF4mDlzpoZSJC4uDtu3b693n367du1gYGAABoOBJ0+egEajwdPTE8bGxiSYlEqlkMlkePHiBQoLC9GhQwcwmUwkJydXu/7y9vbGhg0bAFQG7gcPHiS/Gzt2LMaPHw8AOHjwYIPWVAKBAO3btweNRkNqamq1PhtUEsDIyAiWlpYICgrSSCDHxMRg3bp1+hahdxAqSP5JiyB5kj5I1tNSuLu7Y8OGDUQaRLlBc7lcBAQEQKVSIT09Ha9fv673Nv39/SESiRok164OOp2Obt264cMPPyTmFhR37tzBgQMH9LJSPRowGAy0bdsWzs7OcHJygrOzM+zs7Mj3HKiUconFYvj5+UGlUqGgoADDhw+vVwWsf//+GD16NGxsbCAQCEiFNz09vdYgPikpifQI6w2N9KjDYDAwbNgwjBs3TsMJXiwW46+//sK5c+d0Up1Vl0s/fPiw3gG4UCiEt7c32Gw2EhISkJqaCgcHB2zatInMfP79999x6NChRu+jHj3vCoMGDcKUKVPItUcul+PMmTM4ffo0US7VBI/HQ2BgIGg0GvLz88HhcIg/R0ZGBsrLy+Hq6go6nQ6VSoXY2Fg4OzuDxWKRY/RNgoKCsHDhQgDAoUOH8Pvvv5Pf2djY4IcffgBQ2U+9YMGCBn1mNzc3GBkZgU6nIzw8XOMcIxQK4eHhAT6fj86dO6NPnz5kegRQ2Xq0d+9evSP+O0pzBsnMup+iR0/txMbG4rvvviMnw0mTJiE7Oxu3bt0iLoW2trZIS0ur84ROUfz/v9CNnQFqZ2eHXr16oXfv3qRHhSItLQ379+/XVyz0VItCocCzZ8/w7Nmzan/PYDBIMDtlyhQMGzYMQGXSqD49mleuXMGVK1fg7++PiRMnYsiQIeByuUhNTUVFRQWUSiWZU5mRkYH09HQ8evRIHxjrqRGFQoHff/8dt27dwhdffEEqUHw+H2PGjMHIkSNx//593Lx5E0+fPm2wiQ1lcCiTybSqUNvb24PNZqO0tBRpaWkwNjbGypUrSYD88OFD/Pjjjw3aJz163lUuXryImJgYBAcHw8bGBkwmEx9//DGCgoKwd+/eWicllJWVIS0tDXZ2drCxsSHHq7pKr7S0lCSvXF1dYWBgUGUCgjrqHiCUioTFYsHQ0BBMJhOpqamws7MjvgUNMahMTExE586dwWAw4OHhgYSEBNja2oLL5UIgEMDc3Bxjx46FmZkZaSkpLCzE/v37ySgrPa2TxYsXY/To0fD09ER5eTnu3r3baudW64NkPTrh33//haWlJXHvnTt3LnJzc5GYmAh7e3swGAzY29tXK5t5Ez6fD6FQCCcnJ9BoNMhkMshkMnLCpqSo1GPqX4FAAENDQ3Lz8fGBgYEBcRmmiIuLw5kzZ3D//v1mn8Os591BPcCIjo4mQXKbNm20MjJ69uwZHBwc0KZNGwDA5s2b9Rd5PY0iLy8PmzZtwokTJ/DBBx+gV69eYDAYYLFY6NGjB9zc3CAQCPDkyRPk5OSgqKiISP2p77V6z/qb/1JVnqysLBgbG6OoqKhOR22RSARTU1MAlQtrFouFFStWkJaGV69eYfPmzfpzsh491ZCQkIBZs2Zh7Nix+OCDD8BgMGBhYYEVK1YgPDwcP/74Y40J1MTERIhEIhQUFEAgECA+Ph7Z2dnk99T4p7Zt24LD4ZBjsKYkGtVqwWAwYGdnhx07dsDZ2RkvXryAl5cXrKysYGJigqKiIkyZMgWrV6/W+vPK5XKkpKTAyMgIpqamMDIygkqlAp/PR69evdC5c2dUVFSQAPnSpUv46aefmsyDQY/u6NmzJ3bv3o2wsDAwmUysW7cOV65cgbe3d53jO9WR/f9bU6IPkvXojNOnT8PKygr9+vUDk8lEaGgo9uzZg9evX5OxO1lZWRonMRqNhvfeew+DBg2Cr68vRCIRmEwmkQNVVFSgpKREYwGWnZ0NCwuLeu2TXC6HVCqFgYEBHj9+jLNnzyIyMlLnn13Pfxv1vieqKqYN6hn75hjfo+e/QWpqKnbs2IFjx45hxIgReP/99yEUCiGXyyEUCtGzZ896baekpERD1SMQCMDhcECj0aBQKCCXy1FWVoaUlBTcuHEDly5dQlFRkcY22rRpQyrPKpUKGzZsgKurK4DKc/qqVauIq7wePXqqIpPJcOzYMfz777+YOXMmDAwM4Orqio4dO6JDhw64du0a/vjjDyQnJ2u8TqVSISoqCgYGBpBIJNVeY6RSKSIjI+Hv7w8GgwGVSoXc3Nwqz3N2doarqyusra3BYDBI/zEAYoKak5MDGxsb8Pl8fP311xAIBPj1118RFhamVRIsJSUFycnJ6NGjB1xcXNC2bVu0a9cOKpUKJSUlUKlUSE5Oxvfff6+Ttjw9zcOgQYM0Hn/22WfIyclBYGBgqysQ6INkPTplz549MDc3h7+/PzgcDj7//HPExcXh+fPnyMnJgYODAxISEtClSxd069YN3bp1g0wm05BCKxQKqFQqyOVylJaWNipoePXqFa5fv44HDx6QGYB69Ogadcmpei9ofaFmPQL6IFmP7snLy8OhQ4fw008/ITAwEF27doW5uXmDvqtApTyTmj1Oo9HAZDKJgsfS0hJfffUVIiMjcfv2bdy6dQtSqRQCgQA8Hg+2trbo0KEDme8sFosRGhqqPz/r0VNPkpOTERwcjJ49e2LSpEkwMzMDjUZDv3790K9fP8TExODy5cu4desWSTzJ5fI6e3SlUimePHkCNzc3MJlM4nZN4ejoiB07dsDHx4fsB0VCQgKSk5Px4sULuLm5wcLCAmw2G+np6TA0NMSyZcuQkZGBGzdu4NatW/UyZOXz+ejTpw+GDx8Oa2trKBQKYgArlUrxyy+/4OzZs/rZx285VHKluuketSEDIK3zWY1Db9ylR+ew2Wx8/fXX6N69OyoqKmBoaAgul4uysjLQaDQIhUIYGBiQ6plcLieS6szMTBQUFKCgoAD5+fnEtVc9+yiRSMBisTR+plKpUFZWRiSDRUVFyMnJ0S+89DQLpqampJcyLCxMK3mZoaEhZs2ahS5dukCpVGLZsmW19pjp0aMLWCwWrK2tNVpUhEIhcZgG/k/hoFQqyc+pnxkYGMDExIRIIc3MzGBmZobCwkKYmpqS5ykUCpSUlKCiooKMSQNAZiNv2rQJiYmJzfa59eh5lzAwMMDw4cPx0UcfVVExlZeX4+bNm7h8+XK9Wt3UYbFYJEh2cXHBhx9+iO7duyMzMxNBQUHg8Xi4c+cOrl69iqtXr1aRepuamqJr164YMmQImEwmLC0tNX6fkJCA58+fIyEhARkZGaSNzsrKCm3atIGHhwecnJw0zkdApWP/tWvXcOHCBa1c9fW0Tmg0Gs6dOwcjIyMEBQXV6zWUcddekQjSehhxsYRCTNO7W+tpbQQEBGDOnDkwMjICg8GAoaEhORFSmb+Kigrcv38ff/75J54+fVpvYy89elobp0+fBpvNhpubG+7fv4+ysjLIZDIwGAyNG51OJ/d5PB6YTCYcHBxQUFCAkpISfPLJJ/q+Kj1vJS4uLujbty/69+8PMzMzMJlMjXO+RCJBeXk5VCoVTp06hTNnzugl1nr06ACqV3fAgAFwcnKq8vv4+HhcuXIF4eHh9aristlsBAUFYdCgQXBzcyM/VygUSE9Px61bt/Drr7/Wa80WGBiIESNGwN/fv87nvtnaQREVFYWLFy/i3r17etfqd4g9e/Zg0KBB6N69O0mc1gUVJK9fv76K2qE6WCwWlixZog+S9bQ+uFwuevXqhX79+sHR0RF0Oh0VFRUICwvDw4cP8ezZM/2MVz3vBGvWrIGhoSFcXV0bdBE/deoUaDQajh492gR7p0dP80Gn0+Hp6YkOHTqgS5cusLOzg0QiQVlZGf755x9cuXJF79KuR08T4ebmhoEDByIoKKjaloqioiI8e/YMWVlZyMzMhEwmg1wuB4PBgLOzM9zc3ODu7l7ltUVFRTh9+jQuXbpUr+DkTUxNTREUFISgoCCNwFsdpVIJmUwGFouFlJQUPH36FJcvX9afL95Bdu3ahREjRqBHjx5ajYjVB8l69OjR85YhEonA5XKx4v+1d/8uVe5xAMc/XtTwx+CgnBYHN21UHFwiEKItWhqaxCmcwj8gqD/AJZ0c0tWtSQSJ2iJKchJRUoiwk0fBxTin0rt8PHDoVnqvp9O112s7X54fn/XNeZ7vc/9+dHR0RHt7e/UzUV+/fo2jo6M4Ojqq/j75Z61UKsXu7m48ffrU5iMAnIu2tra4evVqXL9+/ZsofffuXfT29p7qOm/fvo3FxcV49uzZuT350dnZWd0ErKurq/p6RqlUis3Nzdje3q6+f8zF8+jRo7h161Zcu3YtNjc3z3SuSAYAAP6zvr6+GBoaiitXrsTAwEDs7+//MJL39vZiZWUlFhcXzxwx8CMzMzNx586duHnzZqyvr1fXDw4OajZB/Z5fGcl2twYAgAtqa2urZoO8QqEQvb291b0DTvbLeP/+fWxsbNR81hDO08TEREREPH/+vGZ9bGws5ufnGzHSd4lkAAD4QxSLxSgWi40egz/QyaP1/wd//fwQAAAA+DOIZAAAAEgiGQAAAJJIBgAAgCSSAQAAIIlkAAAASCIZAAAAkkgGAACAJJIBAAAgiWQAAABIIhkAAACSSAYAAIAkkgEAACCJZAAAAEgiGQAAAJJIBgAAgCSSAQAAIIlkAAAASCIZAAAAkkgGAACAJJIBAAAgiWQAAABIIhkAAACSSAYAAIAkkgEAACCJZAAAAEgiGQAAAJJIBgAAgCSSAQAAIIlkAAAASCIZAAAAkkgGAACAJJIBAAAgiWQAAABIIhkAAACSSAYAAIAkkgEAACCJZAAAAEgiGQAAAJJIBgAAgCSSAQAAIIlkAAAASCIZAAAAkkgGAACAJJIBAAAgiWQAAABIIhkAAACSSAYAAIAkkgEAACCJZAAAAEgiGQAAAJJIBgAAgCSSAQAA+CUmJiZia2srPn36FC9evIjh4eFGj/QNkQwAAEDd3b59O6ampuLBgwcxODgYq6ursbS0FD09PY0erYZIBgAAoO4mJydjdnY25ubmYm1tLe7evRuHh4cxPj7e6NFqiGQAAADqqqWlJYaGhmJ5ebm6dnx8HMvLyzEyMtLAyb7V3OgBAAAAuNi6u7ujubk5isVizXqxWIz+/v5TX+fSpUvnetw/EckAAAD81iqVSuzs7MTk5OSpz9nZ2YlKpXLme4lkAAAA6qpUKsWXL1+iUCjUrBcKhfjw4cNPzy+Xy9HX1xetra2nvmelUolyuXzmWUUyAAAAdfX58+d4/fp1jI6OxpMnTyIioqmpKUZHR2N6evpU1yiXy/8qes9KJAMAAFB3U1NTMT8/H69evYqXL1/GvXv3oqOjIx4/ftzo0WqIZAAAAOpuYWEhenp64uHDh3H58uV48+ZN3LhxIz5+/Njo0Wo0RcRxo4cAAACA34HvJAMAAEASyQAAAJBEMgAAACSRDAAAAEkkAwAAQBLJAAAAkEQyAAAAJJEMAAAASSQDAABAEskAAACQRDIAAAAkkQwAAABJJAMAAEASyQAAAJBEMgAAACSRDAAAAEkkAwAAQBLJAAAAkEQyAAAAJJEMAAAASSQDAABA+hufggMpgfJo7QAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con5/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect');\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con6/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect Famous>Unfamiliar');\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con7/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect Unfamiliar>Scambled');\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con8/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Effect of rep1>rep2');\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con9/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Interaction Face (Famous/Unfamiliar) x Rep');\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con10/spmT_0001_thr.nii'), \n", + " colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Interaction Face (Unfamiliar/Scrambled) x Rep');" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Visualize main effects face and interaction face x repetition" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_2sample/MainEffectFace/thresh_con3/spmF_0003_thr.nii'), \n", + " colorbar=True, display_mode='lyrz', black_bg=True, vmax=10, title='Main effect face');\n", + "\n", + "\n", + "plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_2sample/InteractionFace_Repetition/thresh_con3/spmF_0003_thr.nii'), \n", + " colorbar=True, display_mode='lyrz', black_bg=True, vmax=10, title='Interaction face x repetition');" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}