{ "cells": [ { "cell_type": "markdown", "id": "concrete-bruce", "metadata": {}, "source": [ "# Annotating cell types in human single-cell RNA-seq data with CellO\n", "\n", "This Jupyter notebook implements the STAR Protocol for using CellO to annotate human single-cell RNA-seq data." ] }, { "cell_type": "markdown", "id": "restricted-neighbor", "metadata": {}, "source": [ "### Before we begin\n", "\n", "We will download a single-cell RNA lung tissue dataset from GEO produced by Laughney et al. (2020)." ] }, { "cell_type": "code", "execution_count": 1, "id": "yellow-ministry", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "CompletedProcess(args='curl -O ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3516nnn/GSM3516673/suppl/GSM3516673_MSK_LX682_NORMAL_dense.csv.gz', returncode=0)" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import subprocess\n", "\n", "GEO_DATASET_URL = 'ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM3516nnn/GSM3516673/suppl/GSM3516673_MSK_LX682_NORMAL_dense.csv.gz'\n", "\n", "subprocess.run(f'curl -O {GEO_DATASET_URL}', shell=True)" ] }, { "cell_type": "markdown", "id": "exotic-cheese", "metadata": {}, "source": [ "### Steps 1-2: Install CellO and its dependencies\n", "\n", "Steps 1-2 entail installing CellO, its dependencies and verifying that they are installed correctly. We will install CellO within an Anaconda environment. Make sure that Anaconda is installed, and then run the following commands:\n", "\n", "```\n", "conda activate\n", "conda create -y -n cello_env python=3.7 graphviz\n", "conda activate cello_env\n", "pip install pygraphviz leidenalg cello-classify\n", "```" ] }, { "cell_type": "markdown", "id": "interesting-raise", "metadata": {}, "source": [ "### Step 3. Import necessary Python packages" ] }, { "cell_type": "code", "execution_count": 3, "id": "female-sense", "metadata": {}, "outputs": [], "source": [ "import os\n", "import pandas as pd\n", "import scanpy as sc\n", "from anndata import AnnData\n", "import cello" ] }, { "cell_type": "markdown", "id": "expensive-sessions", "metadata": {}, "source": [ "### Step 4: Load the expression matrix using Pandas and Scanpy" ] }, { "cell_type": "code", "execution_count": 4, "id": "heated-court", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/anndata/_core/anndata.py:120: ImplicitModificationWarning: Transforming to str index.\n", " warnings.warn(\"Transforming to str index.\", ImplicitModificationWarning)\n" ] }, { "data": { "text/html": [ "
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Normalize the data by estimating log transcripts per million (TPM)" ] }, { "cell_type": "code", "execution_count": 5, "id": "engaged-potential", "metadata": {}, "outputs": [], "source": [ "sc.pp.normalize_total(adata, target_sum=1e6)\n", "sc.pp.log1p(adata)" ] }, { "cell_type": "markdown", "id": "brave-measurement", "metadata": {}, "source": [ "#### 5.b. Select most highly variable genes\n", "\n", "Key parameters:\n", "\n", "`n_top_genes`: The number of top highly variable genes to select. These genes will be used to compute the clusters. Selecting many highly variable genes tends to decrease the separation between very different cell types (e.g., myeloid vs. lymphoid cells). Alternatively, selecting few highly variable genes may exclude genes that are important for distinguishing granular cell types. We suggest erring on the side of selecting higher numbers genes." ] }, { "cell_type": "code", "execution_count": 6, "id": "sought-object", "metadata": {}, "outputs": [], "source": [ "sc.pp.highly_variable_genes(adata, n_top_genes=10000)" ] }, { "cell_type": "markdown", "id": "removable-cargo", "metadata": {}, "source": [ "#### 5.c. Perform principal components analysis (PCA)\n", "\n", "Key parameters:\n", "\n", "`n_comps`: The number of principal components to compute prior to clustering. The dimensionality of the data is reduced to this value. Computing more principal components preserves more of the data, but may also include noise. Generally, a default value of 50 tends to produce good results." ] }, { "cell_type": "code", "execution_count": 7, "id": "choice-arrival", "metadata": {}, "outputs": [], "source": [ "sc.pp.pca(adata, n_comps=50, use_highly_variable=True)" ] }, { "cell_type": "markdown", "id": "champion-groove", "metadata": {}, "source": [ "#### 5.d. Compute nearest-neighbors graph\n", "\n", "Key parameters:\n", "\n", "`n_neighbors`: The number of neighbors to use when constructing the nearest neighbors graph. The neighbors graph is required for both clustering and for computing UMAP coordinates. Large values tend to capture more general clusters in the data, whereas small values tend to capture more granular clusters. 15 neighbors usually works well for balancing both global and local structure. For very small datasets, the number of neighbors should be decreased. " ] }, { "cell_type": "code", "execution_count": 8, "id": "naughty-holocaust", "metadata": {}, "outputs": [], "source": [ "sc.pp.neighbors(adata, n_neighbors=15)" ] }, { "cell_type": "markdown", "id": "ordinary-scratch", "metadata": {}, "source": [ "#### 5.e. Cluster the cells with Leiden\n", "\n", "Key parameters:\n", "\n", "`resolution`: The resolution sets the granularity of computed clusters. High values for this parameter result in smaller, more granular clusters. Larger values for this parameter result in larger, more coarse clusters.\n", " If clustering is too coarse, then cells of multiple cell types may be erroneously combined into a larger cluster. If this occurs, then CellO may classify the cluster as one of the constituent cell types. \n", " Scanpy uses a default value of 1.0 for the resolution; however, because CellO was found to work well when clustering was fine-grained, we set the resolution to a higher value. We suggest erring on the side of over-clustering rather than under-clustering. " ] }, { "cell_type": "code", "execution_count": 9, "id": "printable-jimmy", "metadata": {}, "outputs": [], "source": [ "sc.tl.leiden(adata, resolution=2.0)" ] }, { "cell_type": "markdown", "id": "atlantic-edwards", "metadata": {}, "source": [ "### Step 6: Specify CellO’s resource location\n", "\n", "If you do not want to place CellO's resources at the current directory, change the following variable to the location where these resources will be stored. Note, these resources require approximately 5GB of disk space." ] }, { "cell_type": "code", "execution_count": 10, "id": "aquatic-girlfriend", "metadata": {}, "outputs": [], "source": [ "cello_resource_loc = os.getcwd()" ] }, { "cell_type": "markdown", "id": "following-privilege", "metadata": {}, "source": [ "### Step 7: Variant 1 for running CellO\n", " \n", "Because CellO's pre-trained models expect different genes than those in the current expression matrix, we will need to train a new CellO classifier using CellO's built-in training set." ] }, { "cell_type": "code", "execution_count": 11, "id": "suitable-bidding", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found CellO resources at '../../test_cello/resources'.\n", "Checking if any pre-trained model is compatible with this input dataset...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator PCA from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n", "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator LogisticRegression from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Could not find compatible pre-trained model.\n", "Found CellO resources at '../../test_cello/resources'.\n", "Loading ontology...\n", "Loading expression data from ../../test_cello/resources/training_set/log_tpm.h5...\n", "Loaded matrix of shape (4293, 58243)\n", "done.\n", "Inferred that input file uses HGNC gene symbols.\n", "Of 18804 genes in the input file, 15754 were found in the training set of 58243 genes.\n", "Training model...\n", "Fitting PCA with 3000 components...\n", "done.\n", "Transforming with PCA...\n", "done.\n", "(1/317)\n", "Training classifier for label CL:0000576...\n", "Number of positive items: 314\n", "Number of negative items: 3950\n", "(2/317)\n", "Training classifier for label CL:0002087...\n", "Number of positive items: 2010\n", "Number of negative items: 2267\n", "(3/317)\n", "Training classifier for label CL:2000001...\n", "Number of positive items: 1575\n", "Number of negative items: 2242\n", "(4/317)\n", "Training classifier for label CL:0000842...\n", "Number of positive items: 2010\n", "Number of negative items: 2267\n", "(5/317)\n", "Training classifier for label CL:0000763...\n", "Number of positive items: 1094\n", "Number of negative items: 3188\n", "(6/317)\n", "Training classifier for label CL:0000226...\n", "Number of positive items: 2010\n", "Number of negative items: 2283\n", "(7/317)\n", "Training classifier for label CL:0002242...\n", "Number of positive items: 2083\n", "Number of negative items: 2210\n", "Skipped training classifier for label CL:0000000. 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"Training classifier for label CL:2000078...\n", "Number of positive items: 3\n", "Number of negative items: 4282\n", "(251/317)\n", "Training classifier for label CL:0000814...\n", "Number of positive items: 2\n", "Number of negative items: 4177\n", "(252/317)\n", "Training classifier for label CL:0002127...\n", "Number of positive items: 6\n", "Number of negative items: 4173\n", "(253/317)\n", "Training classifier for label CL:0002620...\n", "Number of positive items: 54\n", "Number of negative items: 4211\n", "(254/317)\n", "Training classifier for label CL:0002551...\n", "Number of positive items: 54\n", "Number of negative items: 4211\n", "(255/317)\n", "Training classifier for label CL:0000723...\n", "Number of positive items: 38\n", "Number of negative items: 4253\n", "(256/317)\n", "Training classifier for label CL:0000034...\n", "Number of positive items: 57\n", "Number of negative items: 4236\n", "(257/317)\n", "Training classifier for label CL:0000037...\n", "Number of positive items: 13\n", "Number of negative items: 4186\n", "(258/317)\n", "Training classifier for label CL:0000007...\n", "Number of positive items: 9\n", "Number of negative items: 4275\n", "(259/317)\n", "Training classifier for label CL:0000360...\n", "Number of positive items: 2\n", "Number of negative items: 4275\n", "(260/317)\n", "Training classifier for label CL:1000274...\n", "Number of positive items: 3\n", "Number of negative items: 4282\n", "(261/317)\n", "Training classifier for label CL:0002489...\n", "Number of positive items: 6\n", "Number of negative items: 4173\n", "(262/317)\n", "Training classifier for label CL:0000893...\n", "Number of positive items: 12\n", "Number of negative items: 4167\n", "(263/317)\n", "Training classifier for label CL:0002420...\n", "Number of positive items: 12\n", "Number of negative items: 4167\n", "(264/317)\n", "Training classifier for label CL:0001071...\n", "Number of positive items: 20\n", "Number of negative items: 4222\n", "(265/317)\n", "Training classifier for label CL:0002341...\n", "Number of positive items: 8\n", "Number of negative items: 4261\n", "(266/317)\n", "Training classifier for label CL:0001069...\n", "Number of positive items: 23\n", "Number of negative items: 4219\n", "(267/317)\n", "Training classifier for label CL:0000790...\n", "Number of positive items: 6\n", "Number of negative items: 4173\n", "(268/317)\n", "Training classifier for label CL:0000809...\n", "Number of positive items: 2\n", "Number of negative items: 4177\n", "(269/317)\n", "Training classifier for label CL:0000713...\n", "Number of positive items: 1\n", "Number of negative items: 4235\n", "(270/317)\n", "Training classifier for label CL:0000817...\n", "Number of positive items: 4\n", "Number of negative items: 4113\n", "(271/317)\n", "Training classifier for label CL:0002010...\n", "Number of positive items: 8\n", "Number of negative items: 4184\n", "(272/317)\n", "Training classifier for label CL:0000020...\n", "Number of positive items: 2\n", "Number of negative items: 4285\n", "(273/317)\n", "Training classifier for label CL:0000681...\n", "Number of positive items: 8\n", "Number of negative items: 4277\n", "(274/317)\n", "Training classifier for label CL:0000048...\n", "Number of positive items: 1\n", "Number of negative items: 4290\n", "(275/317)\n", "Training classifier for label CL:0000566...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(276/317)\n", "Training classifier for label CL:0002619...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(277/317)\n", "Training classifier for label CL:0000134...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(278/317)\n", "Training classifier for label CL:0000646...\n", "Number of positive items: 25\n", "Number of negative items: 4266\n", "(279/317)\n", "Training classifier for label CL:0000035...\n", "Number of positive items: 25\n", "Number of negative items: 4266\n", "(280/317)\n", "Training classifier for label CL:0000036...\n", "Number of positive items: 25\n", "Number of negative items: 4266\n", "(281/317)\n", "Training classifier for label CL:0000327...\n", "Number of positive items: 1\n", "Number of negative items: 4276\n", "(282/317)\n", "Training classifier for label CL:0000667...\n", "Number of positive items: 1\n", "Number of negative items: 4276\n", "(283/317)\n", "Training classifier for label CL:0000499...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(284/317)\n", "Training classifier for label CL:0000153...\n", "Number of positive items: 1\n", "Number of negative items: 4276\n", "(285/317)\n", "Training classifier for label CL:0000138...\n", "Number of positive items: 1\n", "Number of negative items: 4276\n", "(286/317)\n", "Training classifier for label CL:0000447...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(287/317)\n", "Training classifier for label CL:0002352...\n", "Number of positive items: 2\n", "Number of negative items: 4186\n", "(288/317)\n", "Training classifier for label CL:0002246...\n", "Number of positive items: 2\n", "Number of negative items: 3772\n", "(289/317)\n", "Training classifier for label CL:2000095...\n", "Number of positive items: 2\n", "Number of negative items: 3772\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "(290/317)\n", "Training classifier for label CL:1001599...\n", "Number of positive items: 2\n", "Number of negative items: 4259\n", "(291/317)\n", "Training classifier for label CL:0000152...\n", "Number of positive items: 2\n", "Number of negative items: 4283\n", "(292/317)\n", "Training classifier for label CL:1001433...\n", "Number of positive items: 2\n", "Number of negative items: 4267\n", "(293/317)\n", "Training classifier for label CL:0000123...\n", "Number of positive items: 1\n", "Number of negative items: 4284\n", "(294/317)\n", "Training classifier for label CL:0000242...\n", "Number of positive items: 1\n", "Number of negative items: 4264\n", "(295/317)\n", "Training classifier for label CL:0000810...\n", "Number of positive items: 2\n", "Number of negative items: 4177\n", "(296/317)\n", "Training classifier for label CL:0000811...\n", "Number of positive items: 2\n", "Number of negative items: 4177\n", "(297/317)\n", "Training classifier for label CL:0000128...\n", "Number of positive items: 5\n", "Number of negative items: 4280\n", "(298/317)\n", "Training classifier for label CL:0001059...\n", "Number of positive items: 1\n", "Number of negative items: 4188\n", "(299/317)\n", "Training classifier for label CL:0000016...\n", "Number of positive items: 18\n", "Number of negative items: 4269\n", "(300/317)\n", "Training classifier for label CL:0000014...\n", "Number of positive items: 18\n", "Number of negative items: 4269\n", "(301/317)\n", "Training classifier for label CL:0000085...\n", "Number of positive items: 18\n", "Number of negative items: 4269\n", "(302/317)\n", "Training classifier for label CL:0000089...\n", "Number of positive items: 18\n", "Number of negative items: 4269\n", "(303/317)\n", "Training classifier for label CL:0011001...\n", "Number of positive items: 27\n", "Number of negative items: 4257\n", "(304/317)\n", "Training classifier for label CL:0000100...\n", "Number of positive items: 28\n", "Number of negative items: 4257\n", "(305/317)\n", "Training classifier for label CL:0000527...\n", "Number of positive items: 28\n", "Number of negative items: 4257\n", "(306/317)\n", "Training classifier for label CL:0002633...\n", "Number of positive items: 22\n", "Number of negative items: 4021\n", "(307/317)\n", "Training classifier for label CL:0002614...\n", "Number of positive items: 24\n", "Number of negative items: 4234\n", "(308/317)\n", "Training classifier for label CL:0000700...\n", "Number of positive items: 28\n", "Number of negative items: 4249\n", "(309/317)\n", "Training classifier for label CL:0000940...\n", "Number of positive items: 4\n", "Number of negative items: 4175\n", "(310/317)\n", "Training classifier for label CL:0000798...\n", "Number of positive items: 8\n", "Number of negative items: 4171\n", "(311/317)\n", "Training classifier for label CL:0000545...\n", "Number of positive items: 4\n", "Number of negative items: 4026\n", "(312/317)\n", "Training classifier for label CL:0000899...\n", "Number of positive items: 4\n", "Number of negative items: 4026\n", "(313/317)\n", "Training classifier for label CL:0000970...\n", "Number of positive items: 4\n", "Number of negative items: 4112\n", "(314/317)\n", "Training classifier for label CL:0002393...\n", "Number of positive items: 4\n", "Number of negative items: 4260\n", "(315/317)\n", "Training classifier for label CL:0001058...\n", "Number of positive items: 4\n", "Number of negative items: 4249\n", "(316/317)\n", "Training classifier for label CL:0000767...\n", "Number of positive items: 4\n", "Number of negative items: 3696\n", "(317/317)\n", "Training classifier for label CL:0001044...\n", "Number of positive items: 2\n", "Number of negative items: 4032\n", "done.\n", "Writing trained model to GSM3516673_MSK_LX682_NORMAL.model.dill\n", "Found CellO resources at '../../test_cello/resources'.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Transforming with PCA...\n", "done.\n", "Making predictions for each classifier...\n", "Running solver on item 1/31...\n", "Running solver on item 2/31...\n", "Running solver on item 3/31...\n", "Running solver on item 4/31...\n", "Running solver on item 5/31...\n", "Running solver on item 6/31...\n", "Running solver on item 7/31...\n", "Running solver on item 8/31...\n", "Running solver on item 9/31...\n", "Running solver on item 10/31...\n", "Running solver on item 11/31...\n", "Running solver on item 12/31...\n", "Running solver on item 13/31...\n", "Running solver on item 14/31...\n", "Running solver on item 15/31...\n", "Running solver on item 16/31...\n", "Running solver on item 17/31...\n", "Running solver on item 18/31...\n", "Running solver on item 19/31...\n", "Running solver on item 20/31...\n", "Running solver on item 21/31...\n", "Running solver on item 22/31...\n", "Running solver on item 23/31...\n", "Running solver on item 24/31...\n", "Running solver on item 25/31...\n", "Running solver on item 26/31...\n", "Running solver on item 27/31...\n", "Running solver on item 28/31...\n", "Running solver on item 29/31...\n", "Running solver on item 30/31...\n", "Running solver on item 31/31...\n", "Checking if any pre-trained model is compatible with this input dataset...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator PCA from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n", "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator LogisticRegression from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Of 18804 genes in the input file, 15754 were found in the training set of 58243 genes.\n", "Of 18804 genes in the input file, 15402 were found in the training set of 31283 genes.\n", "Using thresholds stored in ../../test_cello/resources/trained_models/ir.10x_genes_thresholds.tsv\n", "Binarizing classifications...\n", "Mapping each sample to its predicted labels...\n", "Computing the most-specific predicted labels...\n", "Loading ontology...\n", "Item 0 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 1 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 10 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 11 predicted to be \"CD14-positive, CD16-positive monocyte (CL:0002397)\"\n", "Item 12 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 13 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 14 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 15 predicted to be \"CD14-positive, CD16-positive monocyte (CL:0002397)\"\n", "Item 16 predicted to be \"epithelial cell of upper respiratory tract (CL:0002631)\"\n", "Item 17 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 18 predicted to be \"endothelial cell (CL:0000115)\"\n", "Item 19 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 2 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 20 predicted to be \"endo-epithelial cell (CL:0002076)\"\n", "Item 21 predicted to be \"myeloid dendritic cell, human (CL:0001057)\"\n", "Item 22 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 23 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 24 predicted to be \"naive B cell (CL:0000788)\"\n", "Item 25 predicted to be \"plasmacytoid dendritic cell (CL:0000784)\"\n", "Item 26 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 27 predicted to be \"myeloid cell (CL:0000763)\"\n", "Item 28 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 29 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 3 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 30 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 4 predicted to be \"professional antigen presenting cell (CL:0000145)\"\n", "Item 5 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 6 predicted to be \"natural killer cell (CL:0000623)\"\n", "Item 7 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 8 predicted to be \"natural killer cell (CL:0000623)\"\n", "Item 9 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n" ] } ], "source": [ "model_prefix = \"GSM3516673_MSK_LX682_NORMAL\" # <-- The trained model will be stored in a file called GSM3516666_LX682_NORMAL.model.dill \n", "\n", "cello.scanpy_cello(\n", " adata, \n", " clust_key='leiden',\n", " rsrc_loc=cello_resource_loc, \n", " out_prefix=model_prefix,\n", " log_dir=os.getcwd()\n", ")" ] }, { "cell_type": "markdown", "id": "treated-tackle", "metadata": {}, "source": [ "### Step 7: Variant 2 for running CellO\n", " \n", "If you have a pre-trained model that is compatible with the genes in the target expression matrix, then we can run CellO without training a new model. For example, once we run the first variant of Step 7 (above), we don't need to run it again. We simply use the trained model from that step.\n", "\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "overall-application", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loading model from GSM3516673_MSK_LX682_NORMAL.model.dill...\n", "Found CellO resources at '../../test_cello/resources'.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Variable names are not unique. To make them unique, call `.var_names_make_unique`.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Transforming with PCA...\n", "done.\n", "Making predictions for each classifier...\n", "Running solver on item 1/31...\n", "Running solver on item 2/31...\n", "Running solver on item 3/31...\n", "Running solver on item 4/31...\n", "Running solver on item 5/31...\n", "Running solver on item 6/31...\n", "Running solver on item 7/31...\n", "Running solver on item 8/31...\n", "Running solver on item 9/31...\n", "Running solver on item 10/31...\n", "Running solver on item 11/31...\n", "Running solver on item 12/31...\n", "Running solver on item 13/31...\n", "Running solver on item 14/31...\n", "Running solver on item 15/31...\n", "Running solver on item 16/31...\n", "Running solver on item 17/31...\n", "Running solver on item 18/31...\n", "Running solver on item 19/31...\n", "Running solver on item 20/31...\n", "Running solver on item 21/31...\n", "Running solver on item 22/31...\n", "Running solver on item 23/31...\n", "Running solver on item 24/31...\n", "Running solver on item 25/31...\n", "Running solver on item 26/31...\n", "Running solver on item 27/31...\n", "Running solver on item 28/31...\n", "Running solver on item 29/31...\n", "Running solver on item 30/31...\n", "Running solver on item 31/31...\n", "Checking if any pre-trained model is compatible with this input dataset...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator PCA from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n", "/opt/anaconda3/envs/cello_env/lib/python3.7/site-packages/sklearn/base.py:315: UserWarning: Trying to unpickle estimator LogisticRegression from version 0.22.2.post1 when using version 0.24.2. This might lead to breaking code or invalid results. Use at your own risk.\n", " UserWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Of 18804 genes in the input file, 15754 were found in the training set of 58243 genes.\n", "Of 18804 genes in the input file, 15402 were found in the training set of 31283 genes.\n", "Using thresholds stored in ../../test_cello/resources/trained_models/ir.10x_genes_thresholds.tsv\n", "Binarizing classifications...\n", "Mapping each sample to its predicted labels...\n", "Computing the most-specific predicted labels...\n", "Item 0 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 1 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 10 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 11 predicted to be \"CD14-positive, CD16-positive monocyte (CL:0002397)\"\n", "Item 12 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 13 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 14 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 15 predicted to be \"CD14-positive, CD16-positive monocyte (CL:0002397)\"\n", "Item 16 predicted to be \"epithelial cell of upper respiratory tract (CL:0002631)\"\n", "Item 17 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 18 predicted to be \"endothelial cell (CL:0000115)\"\n", "Item 19 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 2 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 20 predicted to be \"endo-epithelial cell (CL:0002076)\"\n", "Item 21 predicted to be \"myeloid dendritic cell, human (CL:0001057)\"\n", "Item 22 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 23 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 24 predicted to be \"naive B cell (CL:0000788)\"\n", "Item 25 predicted to be \"plasmacytoid dendritic cell (CL:0000784)\"\n", "Item 26 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 27 predicted to be \"myeloid cell (CL:0000763)\"\n", "Item 28 predicted to be \"type II pneumocyte (CL:0002063)\"\n", "Item 29 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 3 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 30 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 4 predicted to be \"professional antigen presenting cell (CL:0000145)\"\n", "Item 5 predicted to be \"alveolar macrophage (CL:0000583)\"\n", "Item 6 predicted to be \"natural killer cell (CL:0000623)\"\n", "Item 7 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n", "Item 8 predicted to be \"natural killer cell (CL:0000623)\"\n", "Item 9 predicted to be \"effector memory CD4-positive, alpha-beta T cell (CL:0000905)\"\n" ] } ], "source": [ "model_prefix = \"GSM3516673_MSK_LX682_NORMAL\"\n", "\n", "cello.scanpy_cello(\n", " adata, \n", " clust_key='leiden',\n", " rsrc_loc=cello_resource_loc, \n", " model_file=f'{model_prefix}.model.dill'\n", ")" ] }, { "cell_type": "markdown", "id": "interested-register", "metadata": {}, "source": [ "### Step 8: Run UMAP" ] }, { "cell_type": "code", "execution_count": 13, "id": "incorporate-formula", "metadata": {}, "outputs": [], "source": [ "sc.tl.umap(adata)" ] }, { "cell_type": "markdown", "id": "qualified-missouri", "metadata": {}, "source": [ "### Step 9: Create UMAP plot with cells colored by cluster" ] }, { "cell_type": "code", "execution_count": 14, "id": "alert-model", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "... storing 'Most specific cell type' as categorical\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = sc.pl.umap(adata, color='leiden', title='Clusters', return_fig=True)" ] }, { "cell_type": "markdown", "id": "furnished-married", "metadata": {}, "source": [ "#### Save the figure to a file" ] }, { "cell_type": "code", "execution_count": 15, "id": "contained-hello", "metadata": {}, "outputs": [], "source": [ "out_file = 'clusters_under_clustered.pdf' # <-- Name of the output file\n", "\n", "fig.savefig(out_file, bbox_inches='tight', format='pdf')" ] }, { "cell_type": "markdown", "id": "generic-fiction", "metadata": {}, "source": [ "### Step 10: Create UMAP plot with cells colored by most-specific predicted cell type" ] }, { "cell_type": "code", "execution_count": 16, "id": "under-migration", "metadata": {}, "outputs": [ { "data": { "image/png": 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u19/8xvpb7bxlF+aaawO4EJht1tDR3Pf7gFx04oo/Dd4vpdRmtBj7Fz4BvR5IEZHhZv4QEenZxLU1RND3uYljgl4nMA0dh+mNNY0z2ycBx6OtkV7BV/eaJwPXGXc4ojPso/bxmg5aLAuhhYXFocPGqZCzWj//brkuRr5rERQZA9jCN+G0Fw7c+g4wmY+d9FHGXT/AfswyVkopETkDeEZE/gFUAZnobF2AjiKyFG3pKwWeU0q9A7pcDTpbNRbwmAD+Hs2NrzMsRMfCdQKmA5NMlu1d5rUAPyilvjHWwbeNeAS4O8h8rwE/i8juunGESqnVxmK3SymVZbZNEZHuwO8iAjrj9iIRyTNrKghyjnuBh4A1IlIFlKMtnl6mi57MhhYkD3p3iMhstFs6WkR2Alcay9RjwIeiE2XKAH8BWJcEEVmBtrqdb7bdaO7NHWjhd7nZ/oSJRxS0aFpOYEb0d8AXInKamaMun6Izo9ub+1UjImcDzxnR5UDHMa5uZL1BUUplBXufmzisoeu8GXhNRK5Ei9jrgN/NeqcDRSYsAWAF4BaR5cA7wLNoK+4S877l0nDm/CGL+Cyu+49BgwapRYsWNT3QwsLCYm+Yeh/89mzD+4/5Nxx1m+/1nKdh+iMw/O8w/t9//vr+ICKy2MSIWaCzXYHblVInH+Cl1ENEegFXKKVua3LwX4iIZAKDlFJ5B3othwLmy8MS4Byl1MYDvZ4DieUytrCwODSY9gD81pAnUkDssPR9eK4/vDoG5r8G81/VZYjWftvAcRYW+4ZSatXBJgYt9g4R6YGO+Zx2pItBsFzGFhYWhwLOKpjzDDrWXHTdSbFBVYnelpABhVuhYIvvmJw1Wgw6wuCE/wad1uLgRik1A5hxgJdxSGHiMi2agVJqDdDhQK/jYMGyEFpYWBz82BwQbmLAEzJgwCXgrNTCMCoVQuqU3nNEQEJH/dxVDXkNfPlf+QW8OEzHHjZFRT543E2Ps7CwsDgEsQShhYXFwYvbpR/tDohM0s8Lt8LvL4C7GqqLoTxHJ5pEJvuOazcc8tb5XpeZpg4lu8E/bnreS5C7FubWcUXnb4ZvboC13+nXL4+ExzvA071g11IoD1aqzMLCwuLQxRKEFhYWBx8L34SH0uDBJPj9RZj3CpRk1R9n9+tb3WcitfV9N/9KQPm1Of+DN46F/3WHL0xZuuJd4KrSLQ9H3hQ4768PwdIP4MurtIUx2yRIlu6G14+Gl4dDddl+ulgLCwuLA48VQ2hhYXHwsfxjLdYANkyBHfN8r/1xV0NqTzj2AWjZF5wVsPjt+uNAl6cBWP2VLlfTqr9P6LUerB+Ld8F7p0J1KSDQcZyOQex6Iqz/wTdXRYEWimHR++VyLSwsLA40loXQwsLi4GPsPZDcVccO5qyBfhdARKLfAL9OXzmrtRXxtdENi0EA5dcyd803EBanz9HpWP0IsHk65G+Csmw4930435TvG3ip79j4DOgywVcP8QhGRDJNMej9OedhZ3oVkftF5PYDvQ4Li8awBKGFhcXBR8dxMOZO8Lh0jGDXE+GOzRDT0gyoUz91y3Qoy927c0y9Fwo2w475UFUEhdtg8t26fE33U6HLcb6xSZ18z0t2wroftDv5YOT+uAu4Py6T++M85vGCA72kPwvR/KWfYyJiedYsDkssQWhhYXFg2b0MJv8TctYFbreH+p6v+gJE4IqftUXPFmJ2eP+FKUgz3bFi03VJmqaoKdeCs7pEn794p36u3ND1BHCY85flwOumoUVUij4GID1YV7QDjBZ/r6P7GYt5fP2PikIR+VpEFovIav8Wdn77HxORG/xe11rEROQOEVkoIitE5D9+Y24TkVXm55Ygc0ab1nBLRGSl6ZSBiGSIyHoReQ9YRZ1Wa8Zq+aiILBORRSIyQEQmi8hmEbm2sbnNvkvMWpeLyPtm2zsi8oqIzAceF5F+IjLPjJskIglm3AwRedace5WIDPFbWg+zf4uI3OR3vqD3VkSuFJENIrJARF4XkRfM9hQR+dLc04UiMrJZb6KFRRNY33QsLCwODCu/gNn/g5y1gEdb6i75Bt4/Q7t3R9zsG7v8E1j3E8SkgSMcPKbnveAzFrpq4OaV8FzfQPdws9byGRz/KMSkQ+ku2PiLdlODjiesMp3W2gyFdd/r50Ov28cL/1N5BKhTg4dIs32f29ehO3IUiEgEsFBEvlRK+adaf4puT/aieX0ucJyITAA6A0PQ79a3IjIa3crtcmCo2T5fRGYqpfybUVcBZyilSoxbep6IeCuMdwYuVUrNa2C925VS/UTkaXTrsZHo1nqrgFcambsHuu3cCKVUnoj4xym0Ntvdpi3cjUqpmSLyAPBvfK38Is25RwNvAb3M9m7oXsQxwHoReVkp5Qx2b4EwdH/gAeh2gL+iW8qBbqP2tFJqjoi0RffZ7d7AfbCwaDaWILSopdrlZFnuVvqkZBDhCG36AAuLP8KUf0LpHt9rmwNeGeUrLv3jbdDrbNj2uxZp1cX6x4vYtVt3/Y/6de4a+PzSvROD9jCdmALwv24Q304/9//9T+oIF36uLYgt+sDGKXqtsa32/pr/fNru5fbmcpPofsagLXKdgVpBqJRaKiKpItIKSAEKlVI7RORmYALgFXrR5thodE/icgAR+Qo4ym8caKH4iBFWHiAdSDP7tjUiBgG8wnElEK2UKgVKRaRaROLRgjTY3OOAz71t35RS/n2KPzdiMA6IV0rNNNvfBT73G/exOXaWiMSa84Huw1sNVItIjjnfzgbubQtgpvf8IvI50MWMGY+2NnrPFysi0Uqpwy720uKvxRKEFrX8Y/Y7/Jy5hDGte/GfERfw2fo5jG3bh97J7Q700iwOR3qdresJghZY238P3F+WA6u+hIu+gEnXaUudq9K3X7lNbUIb+jMd2L3EN19CB8jfSL14w1ps2u1buE2Xk3E7of9FkNIdOhwdOLTzsfoxdz0Muw56nAnJnerNeBCwHe0mDrZ9nzD9hMcDw5VSFSIyA21tq8vnwNloMfOp93DgUaXUq3XmvJmmuRAtLgcqpZymR6/3vOVNHGtUPh6/597Xjibmboimzuml7i+c97X/OtyAYy/urT82YJhSKkjavYXFvmPFEB4kVBUoirc29MH111BUrf/f5VYWc+Ovr/HS8h+56ddXmzjKwqKZqDq/38c9DNfNhfM+AntI4L6MMd6D4IOzdGKJvxgESOsDnSfAP7bCRZNA/ObwuCB/Aw2LQaDdCC1CS3f7tg3+G3Q9HkKCfCaX7oH3z4TfnoVp9zdxsQeMe4CKOtsqzPZ9JQ5t8asQkW7AsAbGfQqchxaFXovZZOAKEYkGEJF0EUkFZgOni0ikiEQBZ5htdc+bYwTbWIIL3T9yTcHm/hU4R0SSzHoT6x6olCoGCkXkKLPpYmCm35CJ5thRQLEZ39g6gt3bhcAYEUkQncRylt8xU4AbvS9EpF9zLtjCoiksC+FBQHWx4udLPTjLIDQOxr0AMa3tf9n5cyuKueDHJ9lRmkeLyHh2luRR4tQfvp3iWzZxtIVFM5j+CMx6AkbdCsfcp93C9jBdFHrNt7pXsT9VxRASBU4/o4zNoYVeWIx+zF4Bn10MnSbApil+B/sHFkKABdGfom34yteY8S+P1G7oEx7X5W6m3KsznkfcCO+cpDOMARIP0van9xd/xP1xoGMG26Itg/dwf/EfiR/8GbhWRNYC64Ggrlql1GoRiQF2KaWyzLYpItId+N24OMuAi5RSS0TkHWCBOfyNOvGDAB8C34nISmARUCfr6A8RdG5zDQ8DM0XEjXZhXxbk+EuBV0QkEtiCjof0UiUiS4EQ4Iom1hH03iqldonII+j7U2DW5xWWNwEvmjhGBzALuHYvrt3CIiii6n5r3w8MGjRILVq0aL/Pe7hSkaP44TyP7zNM4KzJNmwh0uhx+0xZDvx0JyR2pHrMXRzzxb3kVZbUG9Y6Ool+Ke05peNQxrTpFWQiC4tm8upoyFqui0if/D94+0Rd8LlVP9g210/sxek4wU7HQs8zYfM0WPO13hcSocvBrPicoALPS1JnaDtMz1uwed/WO/5+yPwNNk3Vr+/NhZeG6fl6nA5nvw22/e9gEZHFSqlB+31ii78E4/K9XSn1hz8AvXGBxkI4CXhLKTXpj85rYdEQloXwICAyVeh0Bmz6ymxQMPc+DwldhJ6X/wle/SXvwmr9f6Wgw3hKq+t6mDQ7y/LZWZbP91sX0T2hNZNO/+f+X4vFkcHxj+l2dAMv065X5dZdRSJT9P72Y7RQfOsELQiVgu9vMQkf5ouRs1rHHa78vGFPsNh13GDJLrhhITw/QM/R5zzdaaS6tP4x8e2MtRAIj9OFp3+5X4vU6DToNF4nmVz2A+xcqC2If4IYtLCow/0iMh4dUzgF+PrALsficMeyEB5EfHmcG08N2MPBbTxoJ35kI6rlfrYU7l4GH5/HauXg/MQROEIiqXBVBzjaQmx2nB53wGHDW3bD5XEjIjw79ioSwq22XRb7gFK6NV1YDHQ9CXLXaqueIxQ+Og82/AQjb4VFbwVmFad0165k/5g/gKg0HWMYEqFFZjDqup+9hMVBTRmEREKL3rojSeZs3cfYEQY9z9JCNSRi/11/I1gWQgsLiwOFZSE8iOh/k7D9F0WbccKa9xRxGRAapyhcD/GdQOx/XBh+uWEu20tz6XHWx9w5621q3E5qXDr57Zi2fVmeu5XcyhIiHWG0iExgfdGu2mN/z/KF8MzZtYZTOg6pN7+FRT2UgvU/QUKGLgnz0UT9/KIvtaXNW1Aa4LwPtQVx6r8DxWBUmrbY1RWDAOXZcO1cyF4Fk+rVTNYEE4PhCVBVqJ/XlML2ufrHi6saln+kH095WlsPLSwsLA5TLEF4ENHhJBsdTtLPO56iH2ff5WbPfEWbY2DYvX8s0eSOmW/z3ZYFta8dYseG4EGRHBFLl4R0ftmua5+W1VTSMrVDrSB0iA2Xqe82vGU3jmrds/4JLCyCseB1+OkOXVC61QCdmFGyU8fjecVgSRbsWakTOOwhkDkrcI7ybP3TEK+PhZOfgahUbS2sl1gShGDuY5sdPG59fGxLva7VX4KrAuLawsibIK5186/dwsLC4hDBEoQHORU5+nHHNGg51EO7Y5sXu1RaU8l1v7zEluI9lNVUcdOAUwLEIIBLuYkPiyYxLJqUyBheXv5j7b6MuDQKqspwYMOFp1YMxoRE8NZxN+FXFNXConFs5ouM26ktcCGRMOQqSO3hG/PmsVC8QydsVJdCWSPiD7Qrd88KyN8EKB0n+M11MPxG+P15gorBjsdAYaYv0US5AvenD9Q9jfM3axfxxd/Ax+fp8Rt/0d1RqorgzNf25S5YWFhYHNRYkdEHOUPultp3qch8jpXvUfx4oZspV7qpLg5uBVmeu5VF2ZsoqCqjxuPiu80L6BjXot64ouoy8iqLmL9nY8BH6ObiPazIy8RVJ5uz3FnFf37/mPwgWckWRzh5G+Hzy2HZx4HbB18JF0/ytYKzh+qyLTVlMPMJ2DRNi0WAtd/pzOKQKN/xYXEQWidetbo0eNHpJe8GX1t4nP7x749ci/lyU1XiO6+zAl4cAqXZcOn3umYh6NZ1FhYWFochliA8yEnobGPUQza6Xyx0v0h/cOWtUJTvhuItULi+/jGZxTksy9nCMW370DIqAYANhbvom9o+6DnKXTXNXo8HxSfrZ3PF5Of2/mIsDl/cLl1KZvVX8M0NOm7QWQVluXp/x3Fw2gs6a7eqCL67Bb75O0x/CD44E055Fsbe64vT88b8xbSEcfdq8ehPQN1BP4K5gUEno6z+Siew1MMIwvyN2upYiwJnGVTk6ezlMXdpcZuzDioKYOp9Oh6yeGfT9+cwRUTOEZG1IjLdvP5YRFaIyK17OU+8iFz/56zy4EZEThCRRSKyRkSWishTZvv9IrJLRJaJyEYR+UpEegQ5/jkR+VPb1onIqSJyl3l+uv86ROQBkw39pyMil4nIC390TBPHHy0i3+/lMbeYmpTNHf+ieV/XiEileb5MRM7e+xUHzJtpenOzL78Tlsv4EKDlcKHlcJ+LNv0oIWOpruubOqD++DtmvcXKvG30Sc7gtgGnc8fstwm3h1BWU0WkI4wKV3XA+MYyzZPCokmNimdtQeCHXrXbyfFf3EfHhFb8d/RlRAfr7GBx5LB1pondQ1v/3DWmL/FmXbOv5+l6X/pA3XtY7Dqm0EtNBaz8DCoLAjOCS7N0/KEXcdR39QagdJq+3VFfRDZIIzUNOx8Pm6fDll/1j8cNs5+AiES9VtD9jccdPCWZur193QXUKUy97vKX/0hh6sa4ErhKKTVHRFoAg5VS+9LTLx64HnipuQeIiEOpRn8ZDhjNXZuI9AJeAE5SSq0TETvgnxn1tFLqSTN2IvCriPRWSuWabYOAhP1/BYEopb7F1x/6dOB7YI3Zd9+fff5DgFuAD6jfJSgoSqkbAEQkA/heKdXvz1rY3mBZCA9iatxObvr1NS788Un2lBfWbndECIP/YWPALTZsDqGgqpRLfnqaa6a+SLmzinaxqQCsyd/O/fM+wmGzU+l2MmXbUqqCWAOVcbvF1imt0TepHTFhkayrIwZDbA4yS3LILM1l2vbl3Dvn/f196RaHEntWwofmi23GaLj0W6gu02JQefT+GY/Bu6fAMf/WsYPKBYkZ0HooIPDd3yG+rZ7DKwa7HF//XI1+xpovTe6qBsRgE3GvYfEw4qbA89rs0OtMbansMxHmvai3Vxbqfsex6brTynun62s+wBgx+Dq6FZuYx9fN9n1GRC4SkQXGivGqiNhF5D5gFPCmiDyBrpWXbsYcJSIdReRnEVksIrNNazZEJE1EJonIcvMzAngM6GiOfUI0T4jIKhFZacSQ13ozW0S+xQiSOussM8etFpFfRGSIiMwQkS0icqoZYzdjFhpr5jV+c88UkW/M+MdE5EJz3StFpKMZlyEiv5pjp4lIW7P9HRF5RUTmA48bq16K2WcTkU3e137cCTyslPJ2SnErpV4O9h4opT419/gC73UAT5g5GnvvykTkaXNPpvmtqZ+IzDPXMUlEEsz2m4zlaoWIfGK2XSYiL5j36lTgCfNedTTXfbaIHC8in/udt9bSJiITROR3EVkiIp+LaWXYyJpPEZH5oi2mv4hIWpAx3vu9SEQ2iMjJfrtbmd+9jSLyuN8xL5vxq0XkP40sIVZEfhCR9eYctoauQ0RuAloB08VnKW/ueRqlgb+VoH+P+3oOfyxBeJChlKKgSru9VuVtZ8q2pSzO3syHa2dQWFVGjdvF9pLcgGNm7VzNgj0bmLlzFUuyN/PYUZdyXLsBuJSHcmc1Lr96gp4gwfbeLd52dV6W528jsySn3hFOT+CHcrAuJxZHEB6Xr0/xUbdCbCvddzi1J7TsBwMuhRmPwtZZMP8VHWsIWiTunA8oqCmH3PVw7vvaegj6cfx/IDSm8fPXxheaNdjq9EWu/TfXRNZxu+Ew4UFdiBq0CX7Cg1r4/d86OP0Vfa0Aab3g4q8hKhny1sGW6bB7SePz/zU8AtR1XUWa7fuE6NZzE4GRxpLhBi5USj2Abvt2oVLqDrRQ2KyU6qeUmg28BtyolBoI3I7P+vccMFMp1RcYAKwG7vI79g7gTKAf0BcYjxYg3j6aA4CblVJdgiw3CvhVKdUTKAUeAo5F90p+wIy5Et1jeDAwGLhKRLzxNH3RbeC6o3sUd1FKDQHewNc/+HngXaVUH3QLPP/4mdbACKXUbWiL0YVm+3hgudey50cvYHGQ62iIJUA38/zvwLfeNoGNEAUsMvdkJvBvs/094B/mOlb6bb8L6G+2B7TEU0rNRVsK7zDvlX8roF+AoaJ7U4P+nflEtAvzXmC8UmoA+nfmtibWPAcYppTqD3xCw6I3AxgCnIRuJeh1O/Qz5+8NTBSRNmb7P02dzz7oXtF9Gph3CPr97gF0BM5s6DqUUs8Bu4GxSqmxe3mepqj3t9LQ3+M+zh+A5TI+yPi/mW/x49ZFXN/vRK7tczzHZQxgbf4OXl85he82LyQjLpV5Weu5vu+J3DRA16YZ07oXw1t2JdwRysC0TmwvzWXyNv3h1C42lcLK0npib1+IDglHKUW5q5oWkfGE2hyEOUK4f8QfMj5YHOq06g9X/Kzj9DqO09uWfwLZK/XzmjLoewFs+w02TtXZumLT1kOgtkRMTEvTpcR8gaksglG3wNzndZ3AYES3hKFXwzS/L+EeZ+CY2HQo2dH0dWz4CT67DNaY7mBnvQFJHX37lQccEdodHhoJDyT51hrXBpKD6ZO/nLZ7ub05HAMMBBaKri4QAeQ0doCxAI0APhdfRYIw8zgOuAS0RQwo9lqn/BgFfGz2Z4vITLR4KwEWKKW2NnDqGnR/YNAip1op5RTdszjDbJ8A9BFfvFYc0Nkcu9ArsERkM9oi553L+2E/HC1YAd4Hai1QwOdmzQBvAd8Az6B7Gr/dwJr3BjFrawWcAxzdjGM8wKfm+QfAVyISB8QrpWaa7e8CXuveCuBDEfmaveiOopRyicjPwCki8gVapN0JjEELq9/M70Io8HsT07UGPjVfAkKBht7vz5RSHmCjiGzBJ5anKaWKAURkDdpSvgM4V0SuRmuflmZdK+pPywKl1BZz/Mfo38eqvbiO5p6nKYL9rVzMXv49NhfLQniQoJTigzUz+G2X9oLM2rGaUHsIz469ipM7DAYgv6qU1XnbAdhY5CvQmxAezdvH38LL468nMiQMj1KEmlIf20pyEBFsTbnLmkGZs4pyVzWd41uSHpPE9rI8NhZlsWjPxj88t8UhSnmefsxaDh+dC59erF93OxlSukGXE7T1sKoIhv9du1oBEBj2dzj2YZ1IInbYuUAnm4AWjCc8prN8q0yB6oQO9c9flgW/Pdv4Gr1iMK4NxDZRQ9ArBgHW/6wtl1P/rdvu2R1w5RQ4/WVtzfR+7nc6FiKT4KmuMOna4PP+dWzfy+3NQdAWsX7mp6tS6v4mjrEBRX7H9FNKdf8Da/AnSJXxWpzKFxTtAaoBjGjwGkAEbbn0rqu9Usor/PwDrD1+r/2Pb9balFI70GJ2HNri9FOQ8avRH+7NpT+w1jx2AjaJSCYQaVzSdvElKDzQwBxNtSc7CXgRbZFaKLqXcnP5BDgXLWQWKaVK0fd7qt/97qGUurKJeZ4HXlBK9QauQbfvC0bda/G+9n8f3YDDWIFvB44x1s8fgHARGep3z05tZN5mXUdD52nieveGffl7bBaWIDxImL1rNQ/N/5TiGh2Tuip/G6+vmAzANX2O51/DziXU7qDUWUmn+JZc3fu4Bue6feZb1Pi5iePDooK6iveV6NAINhT4BOnrKybz1camvvBZHHb8eCc80RHePxN+M16zDcY4k9oNbpivCzlPvkcnkvx0B5z+ErToq0XivBfhl39rsegVV16XbEo3na38VFdt8UvqDIVbgq+jqkg/hjXRSWTiB9DjtOZdW0gUDLkaFr0Nvz0DP9ymRWBqN10+Z+i1ulZht5O1SzlrmT5u+cew5IDG1N5D/cD2CrN9X5kGnC0iqQAikigi7Ro7QClVAmwVkXPMMSIiff3mu85stxtrVSngHxswG+3qs4uOeRsNBBZS3XcmA9eJSIhZQxc/N2dzmAucZ55faNbaEG+grXL+lkN/ngDuEZEuZi02EQn6rUJEzkJbNz9WSv2glGqhlMpQSmUAFUqpTiYG0SsUvMkeNsBrDb0AmGOsZ4UicpTZfjEw08TKtVFKTQf+gbae1o33q/te+TMTLSSvQotDgHnASBHpZK4jyu96HxWRM4LMEwd422Rd2sC5AM4x96wj0AEIUnejlli0YC82MYknACil5vvdM2/izBARaW/ux0S0C7vB6yDwngQ9zz4S7G9lr/8em4slCA8CtpfkEmYPIdIRFmDJW5OvLRthjhDO7zaGuFAdGrSpKItzvv8vLywNzIwvrankmcXfEGoL/EJ3Va/jiA/z/b8LszsIqxdnFZzk8Fhi6mQQL83ZQqmzsvY8u8oLuGfOexRWHvigeou/kJ3m83nzNJ8o87fAZa/RpWi2zoDQKEgfBJ9fpsu44AGUThKJawOth8Ax90OrfhDfDnLWmBIw5otMYUMeIz+qiyGhPUGTR2wh8NoY2LVYt8Dzr0eYFCQp1lUFn5yv9znCISIB1k/27R97N/xzj86anlInw7jWFf7XY7KJrwK2oW/eNuCqP5JlrJRag46dmiIiK4CpaDdYU1wIXCkiy9GWMK8avxkYa9y4i4EeSql8tCtulegElUloF9ty4FfgTqXUnn29hjq8gU5IWSIiq4BX2bvwqRuBy829uNhcT0N8ixZUQd3FSqkV6AzVj0VkLbAKLWy83GosVxuBi4BxQeIQm6IcLXBWoS13XsvhpejYzBXomLsHADvwgXlvlgLPKaWK6sz3CXCH6ISPjv47jOj9Hi2CvjfbcoHLzDWuQLtZva7d3kCw9/V+dLjBYiCvkWvbjv6i8BNwrVKqqqGBSqnl5prWAR8BvzUy70J09vdatLt6UhPX8Rrws4hM38vzNEWwv5V9/XtsElGNlBzZVwYNGqQWLVq03+c9HFmeu5Xzv38CD4qb+p0ConjOCL0HRlzIuV1HAbCleA/h9hCeXvIt323WH8T9U9vz8Um+WNunFn3N6ysnB8wfrMwMQM+kNqwv2I0r6JfWQAa36MyWoj1UumoC5ooJiaDUxCYKsPSiZwkPCVb41+KwZM9K3cmjeCe0GQYZI6H3udqKBrrjx0vDdMzd+R/rItS7l2j3cI/TdUs4fy79HtofBau/hi8ub0BYOdAeoAb+b7UeCqERsGVG4Hb/mMXoNF8nFHsouN1mziBMeFhbN7eZ/+mX/6QtgKsn6dqJC9/wCWOAlv3hmhlBp2oOIrLYBKNbHAaILgvztFLqqCYH/3lrKFNKNZrVe6AQkclKqYbdXY0f+w66ZMsX+3dVRy5WUskB5Pml3zN75+pad+4Ly77D37oxb/c6zu06ipeX/cizS7+jb0p73j/hVvIqismtLOGeIRMBeGrRJH7auoTjMwZgEyHE5qDadH4IJgYB1ubvbLYbeWEDMYKlfokqPZPaWWLwSCOlO1zyPexZrt2mEfGB+5M6wph/wPbfIWulLwt38JWw4jMtxjpPgKwV4Aj1WRnn/C9QDNocOpPY7YSeZ8CyDxpeU2QSdJkQKAjTh0JYNGyZpoWhvwXR3UBR9tZDdeLIlHsBpcvPhMdr6+War3UW9brv/GIiDZ3Gaytk+t6EhVkcjogu5Hwd+ykD9HBkX8WgxZ+D5TL+i8gszuHCH5/k/rkfoZRic1EWLy77gRV5maSExwLaieYv0n7MXMzmoiwyS3QCUWZJDo8v/Irfs9azqSiLrPIC3B4Pr6+cws6yPL7ZPI9/DzuvVgw2RkNiMCokjNSIOOzSvF+NFpHxnNxhMM+Ou6pZ4y0OA/I3Q/EueGsCPN9Pt54LidSdScrz4M0J+qdwG/z6EGz6RYtBb5jCone0+HPXQJ9z4fIfoGArfHoRTH9Mu5dBl6xJ6w0jbtbjneX1xaCjTqz2hh/h+1v0c7tJai3fo8UgaKFZ5uehcoQFtsnzMvQaXUrGG0t+4lNwy0qIS9eWwe6n6rqERdsCj5v9hHaT1xWKFkccSqnHlFLtlFJzDvA6Dkrr4B9FKXWZZR3cvxz2FkKny0NxhYvEmBBsEiS26C/im83zWJy9mcXZm7mi17H8tNVXeqqoOjBpLtweQpURdVUuJ3cNOZu0yHhW5m3jl23La8c9vfgbHp7/GTYEDwq72Hhq0df7vMbO8a3YU15ATmVxvX3DWnRlee4WKs26IhyhVLpq2FNRRL+U9mwvySXU5iAlsonAfotDmyXvw7d/D3TBLn1Pi6eS3SDiSwzZMh06H6utdf0u1NbAH24DT4225HncsPILKNrpSyqZ9yJUl0BUqi9RI3ulLvfiClI6yVUFaT0hMll3S/Envg3kbwoUbaHRgUWrXdX6v2B0C23hzF2nk0U6jIGoNKgq0JnQgy73HdPnXP0z5V/BLYyOiCC1EC0sLCwObg4bQVhR7cblUcRGOKh2eli4qQi3W1Hj9lBW6aFDWgR928cesPUd27YfX2z4jTYxyaRHJ9EnOQO72Ai1O6is0z3EKwYjHWHEhUVy7vf/pbCqjDKnjpcd0qITeZVlbCkOjMXdU1G0z+sbnNaJB0ZeyMmTHqy3z4aQHBFLtdtXkNq7ZhvC8tytPDT/M1pGJTDtnIewNdO6aHGIUFGgRd3uZTDXlHjxikGxazFXvBOdJGKOsYVA1xNh4GU6o1hEP5ZmwawnoCJfj1v7Law1yVE2h07eqC7Rljt/golBL9mrIaZV/e1VpmC6V7zaQ+H6edqCuGWmr16hqwbaDtMu6dx1WtC9OhqcFXrbnKdg2DWBc+dthPmvmhemjqL3+RU/axe1hYWFxSHEIS8It+VWsmFXOWVV2sIQHW6n2unB6Q50iW7NrqSi2s3QLnFkFdYQG+kgJkJfvsvtobDcRVykg1DH/hczTo+brzfNJ7eyhNzKEnaU5rEqfztu5aHSVYMgte3jACLsoVS6a6h0VXPZz8+ws0x/eNpE8CjF6rwdhDv2nwUiyhHOwuxNnPb1w/xr6ETun/dxwH4Piu+3LgxaydCDoqBKW1wqXTW6YcWBM8Ra/Bl8dglk+lfWEG1BC4+DPauhYBMktof2YyA8VscEHvsARKea4eJ7HHINzHqSWgHV7yJY9RW4KrRlsWgbtBoIuxdrS11zC6qX7q6/zdtbWXkgJl2XwQmPgTNfg8f9EzmVjgu0hcAVU+Gt40xPZdPwo6ZC1yMM9XMtl2aB28Tnth2m4yQBTn7al1RjYWFhcQhxSApCpRT5pU6iwuws2RzYNs0rDOsdA+wpqmHBxmKyCmtw2IUTBqRgt8G05flU1Hiw2+DYfslEhOqizpXVbkTAZhN2F1STGhdKZNjetww8+9tHWV+oSypFOsKIDY1kbb6vc0JaZDyD0jry/VadmV3prkGAMHtIrRj0XjdAuauacr9kEYfYcAXJyAy3hVBVt2tDEMpd2vJY43Hx5uqp9QRq7fn9nntFq11sXN5rPKd0HEKflAzsNss6eNhQUQDf36pjBgNQkL8Fbl2pawUWbIIOY+Hk/zU+3493wILXQBy+nsQbpvqElZfdJpzCVUOg9e0PULoLHmut4wUjE33b7WG+83c4GtoOgeMehsXvQGp33W6vskAXnJ7oV18wMhm6naTF60aT2Z/WW1tELSwsLA5BDslP7xXbSpm9ppBfV+Y3PbgOucXG1SnGiwVUOrWYcnugqkY/LyxzMnlZHlOW5TNvfSFLt5QwZVkehWXBBda6nWX8tDiXbTmBFo3dZQW1YhB01u/9v3/ILQNPpU1MMl0TWvHWcTdx++AzGZLWGTHmNQUBrtceiW0a/FjsltialIhYwuvELfmLQYfU71VyTJv67RV3lOYR2sCvRXxYFKmRcZzSYQhtYpMB8CgPV015ns83zKFDXIsGVmhxyLF9Hrx3qracle7W5WT8iYjXpVdOfQFuXQMnPdX0nBun6kflovZfT0W2L36wZX8zULTLWJnyMnvVKMFgjwi+3VkOxX5t7NqP9j2vKtK1Buc8A3nr9bWHm5jYuolaX1wB637QY3bM19uSu/isoRYBiMifXqRUROaaxwwRucBv+2Ui8sJezjXDlIxBRH4UkfgmxmeK7nW7z4jI0SLyvXm+12u2sPijHJKC0OnS0qjGVV8iOWxgb+R/sssY0nq0icZuE2wijOoeT1p8KP0yYkiI1qKqtNKFUuD2KPJLtTVDKdiZH7zuZWZOJVVOD9tyAwVhXpAEjSnblvHjlkXkVZRQ4azhumkv89n6OWwvy6ttORcfGslDIy/i38PO4/NT7uKTk+8kNUjCRkxIOKvyt5NbWUKVx9lgizqXCswr7pXUlhk7V9W+Fr/jqv1qsjn8RGlxdTk5FcXMy1rPhkLtolPmZ3nOVmqakd18OPPWzlz6zFnJqHlryK6uYWFxOQ9t3s3OqgZKmxzMTPmXrjNoC9E1BrNMG860Xjrjds8KXWR691KdeduQEMpaDtMf1TGG/S/xba87Pj4Djr7LvFA62cOLcoEjUou34x8LLCpdl9BokFBwN8PVnNBedxzxsnMhfHwulGf7th33CJz1Jpz5auCxKV31Y4s+1MZIhB+4GGV/1nbrfsHabt0z13br7jGPR0SzcaXUCPM0A92RY3/Ne2KQ4swWFocdh6Qg7N0umsiw4Ev3KDimX1KTYWyrtpXWPk+ODWNEtwTat4is3bZhV/B2mXYUq7eXkl1UhcvtwenWCrNHm2iSY0Polh5YwmJtwc7a5+F+H2SvrPiZSncNO8ry2FaSwyvLf2JPeSHVJkOzqKaC22a+yTurpxETEkFRdTlj2/QhROwBXUZ6p2QEiDYPimPb9uPMTsMbvQfVbhduPzdzMBcxEOCK9o7INSLXJsIF3cdwftfRPHX0lYTaj9zMyhKXm3s27iLH6WZTZQ19567hlCUbeWF7Dvdt3NX0BAcLbpe2hnU/WYvB9IHachZqLG6t+kOLXr7agJFJOvP45VGw7GPtYv7pHz6L2qcXwczH4IfbIdmvI4hy6+LUiSaWryhTC8y25jO9ywmBMXuuCuh1Ngy7rvFOIDVloBoQ4I46VsPCrfDh2cHHAsS3h24nQu+zfZZCL2e9CTcugcF/07GGjgjd6u4AY8Tf60A7tFJtB7z+R0WhiFwkIgtM14xXRcRutpeJyMMislxE5plWXZi2X7+LyEoRechvHhGRJ0xHkpUiMrGB80WJyFvmnEtF5DSz/TIR+cZY8DaKyL/9jvFaIR8DjjJrvdVsayUiP5tjHvc7ZoJZ5xIR+VxE6mUD+Vv/RORrEVksIqtFpMk3XESON3MvF5FpjV2bhcWB5pCMIVyzo5yKag820QLQH4+CtTvKm4w6cntg855ytuVUkRQbQt8M37f73QVVlAaJRbQJrM/SlocNu8FudNhRPRJpmxJB25T6bqpO8a1qy8JU+ZWo8NTpENNQXcBtpbmc+vWD9E1pz8LsjYTbQzit41A+3aBLW83dva7eMb9sX8bo1r14ZNQlRDnCuG3mW/U6kjRVgse75obomdSWOwadwbBWVgA9QJTdRmqInRxn/d+bXjENuC8PNkr3wGtH6+zaK6fCyJvhoRY6wzcsVrdxO/pubRG8aamOv4tJgw+e0eVdZjzqK/HS8RhdIDq5KxRth5rSwB6/9lA4/WX46U4oMD2Ko1Lg0m+12BSBlV/CN9fr0jKgs4nnvaLL1TQb0T2Ox94DP98ZZL/3d9wB+LLo6Xk2nPCofr7oLSjNhqNu067sNd/CN3+H+La6JI6Xom2Q1mMv1van8AgQWWdbpNm+T+3rRKQ7up/rSKWUU0ReQhdbfg+IAuYppf5phNZVwEPAs8DLSqn3ROQGv+nORLdJ6wskAwtFZJZSKqvOaf8J/KqUusK4axeIyC9m3xCgF7pH80IR+UEp5d8a6y7gdqXUyWb9l5lz9geqgfUi8jxQiW4BNl4pVS4i/wBuw9faLRhXKKUKRCTCnPtL03Yv2H1LQYvz0UqprSLiDV5t7NosLA4Yh6QgLCrX1oe6YtDLzrwG2xnWooBV28rwKCiucFFS7sTlgaFd4tmUVbc3PESEavVXWeOzThjjIIVlNSREh7CnsJqFm4pJjg1lWBdtUfjblOcDhJVXaPlb5GJCwvl7/5P5bddaFmZvrC3p0iIynj0VRdR4XKzK1x+0VW4nn26Yw3ldj+KLjXOJcYRRWBO4XgXM3LmKmTtXMa5Nn6Bx+f5xjcFoSAyOa9OH87qOYnSb3o0ef6SRX+MKKgbTQxzclnGIxFbmrtfZswBfXgX5G6HHqTqesGibLgezdaZOtBC7L25w+A1aqA28VD/aQ3RPYtAFnjdNhcw5kGG6d4kdTntZdwI54XHtCo5IgNaD9LEASz/QSSguv7/lBXXcts1C6Qzoyfdot7Or/t+2/gPxE4PxGXDOm/p51gpt9QSdNT34Sl0qp7oYsk3IRVgsjLwJOh8UTRfa7uX25nAMMBAtgAAiAJPCTQ2mZy261+qx5vlI4Czz/H3gv+b5KOBj0/M2W0RmAoPRPX/9mQCcKiK3m9fhftcw1SvCROQrM2dTvVKnKaWKzTFr0JbTeKAHuocyQCi6P21j3CQiZ5jnbYDOQEPB7MOAWUqprQBKqYJmXJuFxQHjkBSE7VIiKCovrbfdhu720dycRH9BmWfiBPcUVtM+LYKqGg8ZqeFsya6kssZD2+RwnG5FSaWLtinhlFW62bBbf7iICEopsgqrcbkVewqrmbYiH5vA6amnkBSayCe7viTPmU9CWCz51YFxhaXOKrLLC5m1azUAqRGx5FSW0C+1AzN2rKTK7QyoVSgI87LW4/K4KaypCGrNiwuNpLimgsySbFxNWFS8GcPB8M9gFqB3Sjs6xAep+XaEkxjioF14KNuqaghFf0oCeA6VoAxnJbQeAmPv1S7i3008uyNMl2v57mZd12/HAlhuyhJ1O0m7VAddoX9Ai0N/kjtrd6vbpQUlaHfxnmXQ52wtCvv4JawUbNHdTVbV6XMcDG8NxKbIWqofXa4GBpi/Ha9gLMqE6jJdSzA2Xdc4rCyAFuZL0KjbdBmalv2gIk+7vjNGNr2Ov4btaLETbPu+IsC7Sqm7g+xzKlXr7nAT+JnS7PRwY0X0tjs60ZzzLKXU+jrjhgaZtznn8U9l965T0OLy/Gau8WhgPDBcKVUhIjPQYm5vaeja0vZhLguL/cYhKQg7tIgkNERYv7OckkrfB0IjkUVN0iohFJcHWiWGER5qp02ydvN1ahlFldPDnsJq1mdqEdq/fSypccLW7EpcHsX23CqWZ5bSOimM6HA7ZVVuSs26+sT1AiDMHgZO6BzRhQFpTsa06cnW4hzeXKUzLz9d7+tulFOpPziX525lcFpnTugwiMcXfklZTaVJDlG4Pb6rDWbN6xTfksU5m9lSnM3AlE4szt3U4LXXFYOndRzK77vXkVNZHBBD2CIynmeXfMfkzKV8fdo/m39zjwAcNmH+8B5kVztJDnXwS14Ji0rKOatFQtDxBU4Xk/OKGZsYS4uwPz/2srKqgN17fictdSDRkXUslnkb4Y1jtMC6egYktNNCbstMGHWrrgfY7wId41dZqF3Fsa2gzZAgJyqCkl26A0n7MfDj/0Fsazj1eXhjnG/c9nnaRR1j1uLxaPfxys99PY1BWw4rCyEiEaKSIW+Db59/LGFEohZt/jRoEQxCp/G6xR7o8jHe+MWoJO0ed1f74gjTesD5Hwef58BzD9pN6e82rjDb95VpwDci8rRSKse4PmOUUtsaOeY34DzgAwJ7+c4GrhGRd4FEYDRwh1LqW+BF7yARmQzcKCI3KqWUiPRXShllz7FmDZXA6cAVdc5dCsQ047rmAS+KSCel1CYRiQLSlVIbGhgfBxQaMdgNbQFsav6XRKS912VsrISNXZuFxQHjkBSEAK2TImiVEM7PS3Opdv7xOmUtE8OJjXTwy4p8IkPtjO6ZgMNuw2YTIsPstfUHQx1CebWb/FInR/VIINQhTF6ajwJ25FXjsEHblHDCQ2zERzlYt7Mcu03IqdYelipPFeHlcby/Yi79W7YjJTyW3KoS3EqRHBFLXqWvrmJeRQlZ5YUogbnnP877q6fz6MIvEKCgqpTTOw3jh80LcdaxkoSInaU5W2pfNyYG/RHjW/5m8/yg+7NMJ5SEsCC9Xy0ASDPi7riUOI5LabiN301rt/NLfgkDYiP5cWCXZs1dWraT7Lxl7M6eT0R4Er26XkJoqP7cszfRKm3F2rfIL1zD7pz5HDWkTohUzhqoMlbr7fN0/N7Ay3S7uQ/Php2LAtu9uauhPBem3KtrFU54CFK66ALTX16p4wNdVTD/FR2PCPD5Jdq1ag/RXUp2L4Nn+sCVk3WiSt56WPi67xxih7AYLQZtIdD1BB27B35t7Pz+7pVbJ7hU+HnvWg2AnQt0qzwvjijArbOY41r7StBsnqlrC1aXwpg7tYs8IUPvCwnXlsBlH+kexnHpjd7rA0n3dWs/WtutO+iYwbZoy+A93det3af4QQCl1BoRuReYIiI2wAncADQmCG8GPjJxed/4bZ8EDAeWo9/AO5VSe4Ic/yDwDLDCnHMrcLLZtwD4EmgNfFAnfhBgBeAWkeXAO0DQxtJKqVwTX/ixiHhb49wLNCQIfwauFZG1wHq04GsQM//VwFfmGnLQLvXGrs3C4oAhSv1xMVWXQYMGqUWLmgrp+GMUlTvZsKucuEg7FTUesgqqqQ5ShgYgLS6U7OLGS38M7RJHaaWbNTv0B9/Y3onERwV+yJZXuQlxCL+uyKeyxkPLhDCGdY1nR14lG3dXUFzhIizExvH9k7HZApM2pmxdxuuLZ5MWlkqhs4jFxcsAePu4m1mcvYlJm+axqyw/oCi0tzPJ4LROnNV5JP+e+xHVHieRjjAqXNW0jk6qLVzt3dYc6grPvWFcmz78Y/BZtItL3afjLTTXrM7km5wijkqI5vN+nZocv3Hrt2zc+nXAtqSEnhQWrUfhYWDvm0lJ6oU0kCy0ct077Ng9i7Tk/gzsc2PgTo8bZv9PW+YWvqlbul0xRVvHnu0bfEHRaVBmyrN0OxnO+xAm/9PnavbSegg4wiFzln7dbiT0vQC+Na7lc96FnqfrItQvD9fJKQBXzdBitCIvcD7/HspNEdNCWyEDJ6BWSCZ20kW1AbDBjYvh7ROhLEsntnQ/DVoPhJiWMO9lLS7bjoALPoVJ1+i5znxVC9f9hIgsVkoN2m8THmYYATdIKfX3A70WC4vDjUPSQuh0eZi5qgCPgl0FkBwTwvEDU/h+YS7uOpkmoTbIqSMGbQKp8aHsKdTbB3aMJT4qhK17tDVDW/fqW1yiwrWVMDbCQWWNbn8H0CY5gtZJ4eQW1xAT4agnBgFaxSSwqnQtK0vXEGWLIMoeSeeEVvRP7cDwVt0oqi7ng7UzUChaRSXSLbE103foDMaF2ZtYmO2z8tltNkan9+TcrqP4dvMCHDY7j4y6mC82zuWpRZNq4w0TwqIprK5fD7bC2bBwDLM5CHeEcWH3o3lp+Q8B++LDovh1xwqq3DW8ddzNDc5h0TTPdmvLBS2TGBhbNyG0Pkp56olBgPzC1bXPV6x7C5eznD49/kartCFUVhWwZsOHpCT3pW2r0fTqegntWh9DdGTLwEkqi3RruuIdWgB5ewaX7YH0AdBxnLYQVvt9gWgzXLuDZz2mX3uTRfpfpIWTcmtroCNct4krz4U3Ta5BeKzOTI5M0jUNe5iKG45QqDCGHBEdW+i19qUP0u7azdOaLwYBWo+EtXVjEf3+PxRsgaTOUJipy8cUbNFiEHQbvdVf6h+AFkYYx6TB5l9h/Y/69ebpOvHGwsLC4hDnkBSEYrqMeP+355U6QSkcdl/mL+jMYP+sYC9KUSsGvfNNXZZXm2QS4hCcLg8hDfQ1HtY1nsoaT61A1HMIqfFhQccDrMnfUWv5K/dU0i4mhU9O+T8AdpTmsrloD+GOUKpcNfROyeDZsVcxbdty7pv7IflVvgSauNBIEsOj2VVWwGcb5vDgiItIi4pnQ+Eujm3Xjw6xaVw99QVcyoPNtJFrE5MCSrGjTFtb/BNU6lLtceFxqnpiEHRHlHlZ60mJaNgVatE8wu02xiQ2z7IkYiM1qR85+cuC7g8NiaGmpgRQ5OYvp6Iyly3bf8LlqiA7byktUwbhcEQQG92m/sFbZ+nMYYDfnobjHtVdSKKSdbu2zb/qfWGxMP4/2oI36ApdU3Djz5C1DLbPhWHXanHkDV+oLtE/n10MXb3eMIFhN8DCN7TY2zY3sEB1UkfYma//QL++AVA6XrHzBH2uvaWeGKyLR9ci9Lig3Qjduq7Pefp+pHSFLTN8Q+Pb6tZ8Lfpo93m7kfp6Mkbt/bos9hml1DtoN7CFhcV+5pAUhA57YD+OVolhVDo9uN2+b/8OG3RuGcGKbb4C09FhNnq0jcHjUSzPLMVmE/pmRBMeaq8Vg4nRDgrKXMxaU8gxfZKCnt9mkwAx2ByGtOhMSkQsTo+bMJuDid18LbM+3/Abv2f56glOyVzCSZP+Q0pELCNadee7LQsAOL/raL7Y+BvFJdqSubk4iwfnfcJJHQZz64w3ECAuLKo2ESTfuIU7xKWxtcjnOlMoQm0OIuyhFDvrB93XjUmMdoTzjyFncWrHoawv3EX3pCDCwuJPZVDfmygo2si8JY8GbBex4/bUAArBRnHpDnbt8VXOsImDtZs+YdeeufTofAHtVIxOvqguhcSO2jKY1kvX+ItKBrsDvr1RiyR/qkt0JnLf8/W+nYu1ZQ10BjHA7iVmUX7Zv9lrdFIJ6Ni/6Ba6XIs9BIZcG3AKJjwI75ykRWCOsX66q3V9Q5SOJWxGb+5mk9QFCkyf5jlP6zqLZdm69I7Y4PYN8GRXfe5130HHo3VpHEciXP7j/luHhYWFxUHAISkIlVK0TAxnh1+9wfU7y2vb0oFuUbdht699lU2gY8so0pN0lYD05HAE3f7OZoMhXeKocXrYXaDnrKrZm+K3jbOnvJDrfnmZXCPQ7hx0Jpf3PAaAdQU7KawsIz06iZSIOFbnbyfUZmdz0R42+4m4sW368K/hE6lyO/l203zcJqf6l+3LKa3R16mAomotgAUhzO7gtoGnc0bn4azMy+T5Jd+xNHcrADV1PvDDbI7aLil1KXNVsb00lzBHCH1SMvbbfbHYOxLjO9Ojy4XkF6wlO0+LL6XcuN36d1Xhoax8J74CTBAf15mcvOUo5aF0yxSY/qrP7eoI08kVrQbAbWt1NvHjHYKXchEHzHocpphk1fh2vmxgbweesf/UbuIux8H0xyBnle5q4k1YcVXAi37hcTF+7muPB9oO090/HGG68POmqYFriG4BJTv4w4RE6mSXfL/cgd1L4K3jfa9d1TpO8tgH4Zd/63viDv73YWFhYXE4cMgJwq3ZFSzbql2o7dMiCLHb6NAigopqNzvyqhAgIsxGWZWvrRzomoM1forRJkJ+aQ1z1hTisAvH9EliwcZi8kudxEc56JoeRUGZk8TofS8JUumq4YWl37O5KIutJdm153180VdEhIRyfrcx3DL9dTJLchjZqjt/6z2Bspoq3lg5heV5W2vnEeCszsOpcFbz0MiLuLH/yczZvYYXln5PTkUxHeNb0jIqganbllHuqua6PicwsdtRfLlhLo8t+IJtpblc1P3ogDZ6ECgKGxKDXvqndtzn+2Cx/8hofQyt0oaSP3ctrgb69UZFpFJeuQcRG53bn4LLVcnunAVkRHUBXvMNtIUA1bq0S2xLnTEcTAwe82/ddeQVn1WbGr/Wjuu+g12LdZu700xSSfog2PCzrlX4VZAOX2Ex8Mt9um9wSCTMelKf++y3dZLJxA/hYW/ikjHf15TVtxLuTZIJaCtofDu93rr41wetNPGMI2+ETsdo13JEIky6DgZdHrzkjoWFhcUhzCElCMuqXKzb6fsgKq10kZEaQXmVi1CHjU4tIykqd5lHJymxoTjswsxVBbg8UFLhJL+0hqSYUHO82whFRWWNpzYhJdRhY+HGYjwKhneNp0VCw7GBjfHI/M/4fMNvALSNSaFtbAqL92yi0l1DtdvF3bPfq43niwqN4PLJzwIwqpWv/ZUd4eKe45izaw03TX+N3skZZJUXkmNKwFzX9wTO6DScubvX8X+DzkBECLHZya8s5bstC/Cg+Hz9HBLCoqhyN8/dFoINsdnweDy48BBuC6Fj/CHSbeMIIDQkmv69rmPRiueIjEhhxMB7mTn/bmpqSrDbw2nVYhgbt35NYlwXkhJ0a8G0lP764Ktn6KLLzgodJ1e03ddVJDJRW/c2TdOCbdj1OsZv0OXw9fW6MHPb4Xpc8U5Y8q5PoL13BtztV/s4tqU+DmDMP3zxeGGxeu7yXO16/u3ZwItb+bkWhCFh9cVfVZ3qIWHx2upYr6h6kNY8XpK7wh6/dnMp3bXY8++IAr6SM6DrDqb1gJdHand3zmq4Zlbw+S0sLCwOUQ4pQbh2RxlVTm0NSI4NobDMSV6J/sDw/whwexSjeybWHjemVxLbcivYlFXJroIaxvRMIDEmlLbJ4dQ4PYSG2EiIDmFY13hyi2uIjrAzc5X+kHE11B+vEZbnbqWwqoxZO3UclF1sfHzSHSRFxLClaA+7yvLJKi9k0iZfrFeI2Aix2XF5PBzXvh/lriqUUrSOTuKd1dNqx63I3UpqZHzt67TIeP5v5puszNvGtO3LeGDkhUz44j4qXNXEhOji2jUeF/OzNtA7OYM1+dtxG4uKDSHU7qgnFJ14GJjcgQ2Fuyh1VlLlcbImfwftYq1SMwcLKUm9mDD6BWw2ByI2Bva+kS3bfiKjzXiSErqR3mIY4WGJ9Q9s2SfwdbxfPOjqr2HDZP28slALxh6nwYYpvqzaYddD34nafdrzdN2SbvZTuph1Q7QbDj3PgPU/aStgyU4tDBMzdLs80FbCiAQYc5cuQbP+Bxh6Ncx7FZSxXtftTFJd1MAJG/mb3f57oEUxb0PgnKExuu+yPciXwNjWWhB2GFd/n0WjiEiZUiq6kf0ZwAil1Efm9WXsZXkZ0znkdqXUIhH5EbhAKVXUyPhMc468hsY045xHm3OebJXEsTjUOaQEYUpcGDvzq2mREMagjrH8tCS3dp//R0BJRaD7MzbSQavEcDZlBbrYbDahS7qvyHJEqJ22KVpEje6ZQLXTQ2p8CJ9vmEN6dBIjWnVvco1XT3mhtgXdUek9yK4owq08/LR1MRf1OJoO8S3oEN+CzOIcWkYmkF9VSo3HRfekNtzQ7yTWFezkH7PfAeCzk//Bud//N2B+BRSbOMEJ7fpzdpeR/LJ9OQDRIRE8PO+z2nqELj838Or87VS7nXRJSCenooj8qlI8qAathotzfGVuzuo0gvHt+jV57RZ/LXZv7B6QENeRgX18n0OREfsg3rOWmyei+xJ3PVG/DImE0GjtsvXW9bM7dEmajuOg9zk6C7chZj4Bq78K3FZdAq1O8glCEd3h5IfbwGbXwi06TbuOl3+ks5mLGqmDnNwdup8Es58MstN8XRS7EYM26Hysvr4f/i9waPpA2DEPep+p4xp/vF1nVg+83JfpXKf15MHG52PdF1CnMPU50+37XJj6LyIDuADYL+tUSp24P+axsDiSOKQEYUZqBG2Tw6lyepiyNLe2xEyb5HDaJoezNaeS3QXVQWsIJsWEMrpnAgIkxvg+SEsqXGTmVNImOZwEv3hBr1v5w7UzeHDep9jFxuSzHqB1TPDM48KqMj5bP6dWDAIszt5c+zw+PLC7R0ZcKtMnPkKZs4pdpfl0TdTdD/ZUFOI0vYeLqsvpGN+SdQU7sSO4jez1irhdZfk4bHaeG3s1q/K38a85H7Ct1CeSK/3Enlckri3YwdCWXcjPqt8Lui4Om51zu4zkX8POa7DgscVhQkUB/PaMfj7wUjjFuHILtsL7p/myjvesqH9sagNflNwubYGb/pBvW0QipHTTiSjj7tU1Ddd8BdXlsGsh7F7q5yYW+GRi89ZfvkeLQXs4uKt0covXDZzaDXLW+lkCFWycDFtn+KyPAOEJcOx/fC703PWw6E39PHuVb5yfED/YMGLQv3VdO+D1z8e6+SOiUEQuAm4CQoH5wPVKKbeIlAHPojttVAKnKaWyRaQ9WtxF49epRPQ/kseBE9Dfbx9SSn0KPAZ0F5FlwLvo7iKtRORnoCMwSSl1p5ljAvAfIAzYDFyulAoouOpv/RORr4E26L7DzyqlXqMRROR4tKC2A3lKqWNMW7vngV5ACHC/UuqbRqaxsDjkOKQEIWirXmZOJf5JwKEhwoKNxSTGhHBMn0Siwh043R6Ky10kxYTUipmkmPr/yJduKaGgzElOcTXj+yYD4PZ4qHTXEB0SXltzLzoknKiQ+m4kpRTzs9Zz1+z32FPhi3FyiK1WhF3d+zhO7jA46PUopUiN9NX1G9GqO8+M1T3e1xfuYmjLrvxr2ESu+PlZ3H4WvxCx838DTwfgvTW/siZ/B9uNGIwJiSAmLILdZQXYxUZCWBR5ppZhTEgE87Ma6szk46j0Hjw06mLS/NzTFocxodE62aIwEzZOhQdTtGXwrDe1ZQ2X7vFblq3b23ncuvdwl+PgmPvqz1dRAK+O1iVuYltrNzHotnDtR8Oyj+HDc7TgdFXCoL/pLOdMv9i8iERdILsuwRJJvEkgbiMCvWJQbNBQV566nX2qCuH7W3Vv57AouPxn3YVl/U+6bmJqD118e/gNjd3JA80jBPYxxrx+hH20volId2AiMFIp5RSRl9D9id8DooB5Sql/isjjwFXAQ2iR+LJS6j0R8b9hZwL9gL5AMrBQRGYBd2Fcr+acl5lx/YFqYL2IPI8WnfcC45VS5aY13m1AnX6MAVyhlCoQkQhzvi+VUvnBBopIClpQj/b2Hza7/gn8qpS6QkTigQUi8kuzbqCFxSHCISMIPR6FRykKy1ys31UesM/pVDjdiuyiGgZ1smO3CbNXFVJY5qRDWgR928c2OG9CdEhANrHb4+G8Hx5nTf4Oxrfty/HtB/LyMdexKm8bLo+bapeTareT2DD9P/eFZT/w4rIfausiOsSGS3lqawFe3/dEruvn8154lIeNhbtpH5dGfmUpp3/zMFVuJx+e+H/0StZxWMdnDGB9wU5uma57u6ZHJfLS+Ou5cspztfO0iErgP/M+4f7h5/PMEt3jNdTmoMbjotRZiSg4pf1g7h56DhO+1B/YNqDcWSd43o8eiW3IqSgir6qUMmeVJQaPJH5/QSdXgHbdgk7WWPAqXDlFt22b+QRkr4TpD2t3bvYqXb9w7L1gq1PEvXCrr0/w8BthpulqMuXewBqH3li9uHRY9UXgHLlrgq+1RR/tQm4OygOlu5o3Fny1FGtKtTX0vA9hzjOw9H2dHNPz9ObPdWBoyHffiE+/SY4BBqLFFEAEui8vQA3wvXm+GN2rF2AkcJZ5/j7gjX0ZBXyslHID2SIyExgMBFPt05RSxQAisgZt7YwHegC/mbWEAr8HOdafm0TkDPO8DdAZCCoIgWHALKXUVgClVIHZPgE4VURuN6/D+WP31MLioOOQEIQ1Lg/TV+ZTZfoH+5NgSsS4PIqkmBBCTXeRGpN8UuPy4HJ7KCp3kRgTgs3P9VlaU0mbFkLX9BRCHXp7haua1fnb8SjF5G1LmbxtKenRiewqK2Be1nrWFe6kyuXkzQk3MqxVN8qMwFJAWkQ8P575b3aU5XHvbx/QNSGdv/c/CZv4PiwfmvcpH62bxej0nlzb9wSKa3Rh6MySnFpBCNAqOol2MSnkVpbQN7U9+ZU+F29MSERt15FvNy+gTUwSO0rzA8rIlLgq+W7rQiZnLqHGuMpsNjsuj8+0mhGbSmZJTu3rNQU7eGPC35m0aR6X9LAC548oMuf4nnvdrmKDshz44CzdUzipsy4U3etsSO6iXapdjqsvBgF2L9PztOgFo27RNQa3z4eZfoW1Q2Ogz7namtjzDF2X8Jf7g1sFARBdPDprma+W4J9FqwHQZigs+wj6XaCv4dBgO1o4Bdu+rwjwrlLq7iD7nEqp2nw+Aj9T9j4jLxB/E653bgGmKqXOb84EJuljPDBcKVVhEk/C92EtApyllFpfZ/60fZjLwuKg5KAXhDnF1RSWOamo1gIvPNRGeKiNiBAbheUuCstd5JfW0Dcjhl35VUxZmkeLhFBGdNcZw+lJ4UxfWUBZlZu2yeEM7KTds7vK8jnjm4epdrv4+KQ76GG6b8SERvDk6Ct48PdPKDS11vaUFwFatJWbPsBvrJzK6vwdXNPnODYW7GJu1jryq0oQEboltuaLU+4Kej27ygpqz19g3LgCdI5vFTAuJjSCn866H5fHTag9hH/99gGg4/peHn8d9875gB1lebWZygLYxFabQeylxi+DMkTsuPC93l6Sy5jWvRjTuhefrp/N0W16Myq9J6PSezb/DbI4PEho73seHgvlVbqTh78lLjoVrpur+w4DXDs7cI7infDjnbpEy7a5WlSWZmlXcMex+qdlH90dRCnthvXGLWYtBbdTl6SpKdcWOptDi8bacjPKZ3X0isGIJKhsyNgDpPaE/hfD5OB/jwCk9NDr8jh1WZoZj2hL4XunQ+5aLQyvnNL4/Tt4uIfAGEKACrN9X5kGfCMiTyulcowbNUYp1UiWD78B5wEfoN3LXmYD14jIu0AiMBq4A0gHmtPLcR7wooh0UkptMrF96UqphuJg4oBCIwa7oS2ATc3/koi097qMjZVwMnCjiNyolFIi0l8ptbQZ67WwOGQ4qAVhaaWL39YWATpxJCLURnm1m6oaDzbR3Uc8CtbuKmfJFp8FbfOeStokR9A+LZKKajdlVVoEFZT5kiyyygooMR0+rvvlJboktGJ0654syt7MTf1PxulnbXMrDyE2OxPa9efj9TrGac7uNczZvYaCqlKeOvpK3lo1lf6pHSmoKuOOWW/TK6ltgKvYywMjL+TbTfMZ17YPu8r0B5nDZifUXv+tsImNULuNzOKc2nqGo1v1YPbO1WSW5gSMbRuTwten/ZOhH99OjemoYBMh3B5Khasau9j48tS7+fu0V9hiimR7UMzcuYrzu47mm9Pv3Yt3xuKwY8TfoSgTolJ8JWZiWoCz3CfCdi6Ch1vCeR9A1xPqz7HobV0uZv0PcM47EBoFHcbCa2N17cKz34Jufn8T39zoe+52+lzVab20Ozp9EBz/GLx9go4zhPr1AhsUgyazOGd142IQdE3ELhOg11mw4A3fdu//gJC6IXkHL+dMt3/0+Vg37McsY6XUGhG5F5giIjbACdwANCYIbwY+MjF+/skXk4DhwHK0BfFOpdQeEckH3CKyHN2ruE7Rydq15Jr4wo9FxOsuuhdoSBD+DFwrImuB9WjB19i15orI1cBX5lpz0G7wB4FngBVm+1Z0Io2FxWGD+Kz9+49BgwapRYsW/eF5Kmvc/LI8H5db1RaInrEqn8Iy/Y/abgMUuINcQmJMCI74bNIiE9m81UZFjYfBneJonezzFny6fjbTt69gxs5V9SdogAh7KFVuJ8p4Q+4ffgHndTuKxdmbWLhnI7mVxXy4diYAvZLa8Y/BZ9EyOrFednK5s4qNhbtZX7CLd1dP45h2ffm/QWfUOx9AtcvJJT//j1V5uobg4LTObCzajYhQWKWT66af8zAtoxNZtGcj/134JSvzAv9Xp0TEUlxdUa9lHcCbE25kZHqPetst9g2lVL2sbJfbg8MexLV6sOBxw8zHdayfN2lj0JWw7MP6IqzbKRCZACNuguTOvu07F8OnF0FaTzj/E12a5tNLYK3RA0fdDsf8yzd+8j+1ABPRgs8eqn/G3qN7Lc96UrexG3I1zPmfthi2HqxL0uwLEQm6/mFZHkQl6gQZ/6LWJz4Bg6+CKf+Emgo47mF9rjZDteXyL0BEFiulBjU90sLCwmL/clALQoDc4mpyS2pIiw8jr7gGj1Ks2xU8digy1Ea1y4PbA0qc3LPmYSIdYfxy9kNEh0TWxhf6k1NRzL9++4DkiFhW5W5jfVH9APQIRyhdEtJZbvoAC9A3pQMePLwy/nriQqMY9OGtVLpqGNemD0tztlBYrYWaXWzYRHj66L8R5ghlQ8EuthbvYV3BLlblb6NjXAs2F+uYqRWXPEeoveFWeRf9+BSLsjeRGhlHtcvJxT3G8s7qafRP7cCrx95QG6u4OHsT1//yMiU1Fc0K4gmzhfDW8TcxMK1TM0ZbNMbvm/O58t2FdEmL4ZOrhjFvSz7P/rqRlTuLeeGC/hzfq2XTkwBVTjc1bg+x4fveOnGvePVo7bYFsEfAcQ9C3/PhxSE+y127kdq1vOITbT3rMBYu+Vrvc9XA/Jchrg30OtM376ov4cu/aRfxeR/qVnZeHknXtQ3r0nqI6Y5ynX6d1lsns4gNOo2HjcZ9G5msYxubREzfZj9hGxIFEXFQsjtw6OCrtBB07Ft3oj+KJQgtLCwOFAety9jjUeSV1rBoUzHVTsV6PxGYGO0gPtJBdKSDLXsqKK/yoICKGg9p8aEkxYSyuHAFg+L6E2J3IEJQMQiQGhnHq8fewNAP/682wcOfhNAopp7zIJuKdnPBj//DozyAsCx3CwAzd6zijM7DaRebyrqCnQxt2YXnx13D3XPeZWXeNrYWZ+NWcMest2vb1NU9f4jdwYhW3Sh3VrO1OKe2JmFdnht3NbN3ruau2e+igOW5mSy88H/cOuMNxn72T54ccwWDW3RmYFon5l/4FPfOeZ8vNs6tN0/dxl7VHicLsjZYgvAPMH1dDlPXZuOwCRU1bpbtKOKcV+eycpcvefKnVXuaJQjzy6o54dnZFFc6+eTqYfRvm/BnLl1bw7L8wqHG3Q1DdOkjjvo/XSwadJu75K4+V2qkXyeUJe/CVFN+JjJJWxsT2+t6ht1O0cLPfzzA+Pth1VfaArfhJ0jqqBNM+l0Es//nG5djanuGRPvEIJhezAZ7KCA66aUuIpDY0TcPaFe4s7z+2IWv63UMu67+PgsLC4vDmINWEC7PLCUzpxJbkHrIBWUuXB7o2yEOp0ux1q+/ceukcNqmRBAX2Z+Isg4A1FSF1MsrU0rV1iCUmLygYhCg1FlJZkkOn6yfY8Qgte7iwWmdGdOmFwCfnHQH2RVFte3dHh+t+7g+t/Q78ipK+G7LQkC3mss2fYijHOE8PfYq4sOiqHBWc9yX95FbWcKjoy7hjM7DAZi9czWvr5zCeV2P4sQOgzit0zBeXzGFTcVZrM3bTlF1OT9n6lIZkzOXMLiFz4XXPbFNbSmagGuvc42d41tyfvcxQa/fonlc/+FiKp0eRnT0iZ7VuwMraSzZVsjqXcW0TowkLsInZh75cQ2vz9pK39bxfHn9CLKKq8gp1cJm5a7iP18QBljZRNfe85LY0fe8eAcsfgs6H6etdSc95duX1FHXK4xMgq2zYNsc/TP8Bl242hGkjd6Qq3zC89j79WNZDnx8PuRv9I3zJkrV1KlMUpble+51/UalQnlgfC3Ko8XguPvgV1Ouzh7mE4/H/Bvaj4FPzofyPJ1BbWFhYXGEcdAKQqdLfwiEhdiorPHU219S4eKHRYH/+EMdQnqSVn6RYQ68IVsRofZ6x9e4FNtyjQupMp7zWp3JJ7u/qjfOpTwsyd5M35QMvt7ki0fultiad0+4pdZNG+4Irdfrd3NRFi8v+wmFwia6b/CN/U7h/t8/wqXclLuq+GLDb/yt9wSq3U6KTEu6dQU7cXrchNjsvLDse5bnZpJVXsCJHbQnaVirrmwqziKvupTV+du5uf8pLM3ZwkXdx+L0uLly8nOszt9WmxEdYnMEJMkARDrCeHbcVVQ6qxnbti8htvr3yKJ5/LJmD5WmzJF/BIa3DbbXIrujsJKTnp9DakwYU28bQ1xECEUVNXyzdDcKWLaziIWZBQzrkMRDp/fiqyU7ue+b1SzfUcS4bmmc2LvF/u0Yk71Gl5vpO9HX2aPHGVrcedk8LfCYuLZwxiu6jdysJ2HgZbpeX8lu3eWjcLsuPL1xCiR20GVimsv3t8KKT3WWsb8dOzJJz5OzVre88xLTEqrLdEayl/IcX5s9gPB4qCrSz399CAZfrTOIB18F0/4DUUkw+EoIj4MbF2traYxVScTCwuLI46AVhC0TwtlVUB1UDIJOKKlxBdq6alyKacvz6JIeRVp8GB3SIkiLCyM2MvAy1+bv4KVlP9Ijujtt7N1wuqBNZHA3LcBTi7/m29Pu5akxV5AUHkOH+JZ4lIfi6goSwhvs1064I5Qwu4MqtxOPUtS4Xdw79/2AMc8t+ZYZ21fy/DHX8NZxN/PC0u95d82vbCvN5ZXx13NKx6FkFudwasehtcdc0G0MH6ydAcDO0vyAbOZ1+TtZsCcw4U4pD2kRcWRX6h6sbaOT6Z/WkacWTuKRoy61xOAf4LNFO7jzixW18qWosoaIEBtupWtgQn2LbF5ZNaVVTl6avolXZ21hQJt4csuqiQpz0C1NJy9cNKwd7/+uE4O+WrKLL5fs4uEzenHh0GAl5vYBpeCNY3T5ll2L4JJvYMsMGPy3wHHDroc132gBKA64cZGOr3vreMhbD5lzIWtJ4DELX4MuJ8C57zZ/Pa5qWPSW73X6YOh8DKz5DnqcqjOAl30IC98AZxW0P0q7mou26z7J/jUJ/eMS49r4BCEenUhylRG5/c4LXENYzF+WPGJhYWFxsHHQpj2u2NZAuymDO7hOpLzaw9ItpSzaWMzGrEqWbg3s2bthVzn/mT2JqduX8cbGSYzukUjrpDAmdGvPxK5HER2iLYxndRrOgFTtcq52O1lXuJMT2w8i2pnOU3MnM/azexjz2d1sK8mptwYv6dFJfHfGv/jqlLt5cOSFnNnJVwIr0hFm3LluFuVs4rEFXzK4Refa8jMbCnQg/+I9myiuqWBpzpbaY5fk6B7J7WPTOLvLCACyK4q4e/a7vLmqfr00l/LUikGA7WV5fLN5PusKd/F/M96oN96i+ewp1lZmu03omx7L2qwyKp2eWjFoFyHR9NYW4JZjOvHqxYNonRDJjPW61eC2ggo8CkqrXOSW+WLgHj6jFyf3aUlYiP4zjQ7bj9/fVnzqE1Hlebpw9NF3QVRy4LjYlr4Ei9BIcJryL63668f0/jq5w+bQ4svLhp9ga506hR43lDZQdNoRpjuepA/UtQfz1+uM4vJcXRfwjXGw5D1tIWzVV8cPzngEln2g3dcB+H3BKdgG+FlVt8yAJ7ro7iMWFhYWFrUclIJQKUVzk58bugDv4aEhvg8Dj0exekcZnSO6cXbL07kx4xp25VfSsUUkbVIiuGvQRKIcuuZYcU0F53Y5Ss9hd1DldJJXWs3GrApmZi1BATVuFyd8eT+X/Pg/ZmxfSYVx0f62ay2nfv0QTy2chEPs9EhuyzldRtE1sXXtWipd1dj9OjxsL8nhoXmfcs/Qc0kMj2Z3eQGvrZhc22quuLqc22a8yZMLJ7HA9CLeXprLk4smUeGs5oWlPzBp0zy+27KQEFvTwsFmPiRjQw+dGmsHI8d0SyU6zIHLo9heWFm7XYBHz+jNyv9MIC5CF3JW6LjCsV1TmLJ6D+uzS7EJXDaiHV3TojmhVwsykqPIKa3C5fYwKCORFy4YwNRbx/DV9SM4rV/DVuy9ImctTLrWLNQRvDevxwNfX6/7EReYLyPVJfBkJ9j2O5z+Mty2Dk7+H9y0BG5ZBRd8qvsWe6mbqfvhOfBUV1/CSPFO+P42mPui7qE85g44+h7tAq4q1mVpynXNTBQ68zgkCnYtho0/++at25PYr/g6zhJ9sFesVhfrORe9pd3lJVnwxRXwTG/dScVivyAiD4jIePP8FhGJ9NsXJLW80bkuE5EXzPNrReSSJsbf79dibp8RkUwRSTbP93bNN4nIWhH58I+u41CgOe9LkGOOFpERf9J69uvcdX+HD1cOSpexiDCqRwJ5JTWs2VHWoDVQD6aeTy4iBDq1iCC/1ElhmYvc4hpS4kKx2YT0xDCEvrWHrNtVwYbdFZwwMIUVmaWc12IiGys3ctfw8fy0VZfOqXG7+Mecd7isxzEMixrLqa2OY2reNLIq8vGgWJC9kQXZG+md3I7PT7mLD9fOYEPhLjYU7uLt1b/w3gm3MSCtI21jUxEEZdJS/LOOl+ZuYWnuFrompNcWlt5dls9/R1/Gr9tXsKssn5eW64LBrx17A06Pi58yl/DO6mnM3bU2oAVdqM2O0+NicFpnLupxNFuK9vDNpvm1xay7Jaazzlggnx937T6/T0c6OSVVnPz8nNrfpcIKX+Hz0Z2TSIwOJTOvgq15vqSnqWtzuPnTZUzooePUPAqemrqRjKRIHjurD+//vo0Hvl9DVKidGreHhMhQrjqqA1eMas9+we3Ugsq7auWCuc9Dp2MCxxXv0C5agKg0nzBzO2HPSmg3XFsPQcffhcfB4rehZKfeNvFDaDMkcM7dJpPZ2/1k+iO+c0x/CG5YoBNAQqJ0UevctXqfCFwzE2Y9ETwz2GPue4v+en++X8hEm6G6/uDQa3RGc+E2yJylYw3fOSkwCWX1JGg7tP78hxhPTTz5AuoUpv6/T7/f58LU+4JS6j6/l7egO5b84V6DSqlX/ugcfxHXA+OVUjsP5CJExKGUql98Vu8TdOm5xj5hm0VD70tj5weOBsqA+qUwGqCJ+Zo1917M4c8t7Kff4YOZg8pC6HR5yC2uoazKRUW1m6hwO54mflU9dcSgAJVOmL/R53L2r7XodKvaD3BvfL7dprueRIbZaBGexmltxpIaGceF3Y/m0VGXEB8aBYDLo+jWwUZJ6Hau63c87eMCg8/zKvU5L+x+NO1iUvQxysPKrCyKyp2MbdObX855kBfHXUtaZHzAsTEhEcSFRdE/rSNvH3czdw4+i/8bdAYJ4dGc1WUEx2UMoEVkAv1TOzC4RRceGHkRduMq21C0OyCT2Cs0Nxdl8fD8z1iRmxnQ2eSSbuMIsdmJC42kxuPEYt947/dtQes8CjBzYz7XfbCYksqaepnyEQ4bYQ4bA9vF127LzK9ge34Fq3Zp1355jRunW5FTWs3DP67ls0U7Gl9MYSas+Mzn0m2I72+Bb+pYBMNi6lvZ4tvCwMt1solXDCIw4mYYcHHwuftMhDbDYMAlul7gZ5fqWMNi85l43oe6mPVxj+jX7fy+wLuqtNCc8YgWdf6Zwsc+pEvY+Fu+bSG6V7KXkEjYsyxQDIJOUBn8N+g4Dk57wZcw471eV5V2TdtC9Dk/mgg7FgS/vkMAIwZfR/czFvP4utm+z4jIRSKyQESWicirImI328tE5GkRWS0i00QkxWx/R0TOFpGbgFbAdBGZ7jffwyKyXETmefsBi0iKiHwpIgvNz8gg66i1/onIVWbccnNcoxYcEUkTkUlm/HKvBamha2vmfblNRFaZn1vMtleADsBPInJrnfG11k7z+nvTb7mxezlDRJ4161slIkPM9igRecusfamInOZ3jm9F5Fd020H/82eIyHoReQ9YBbQRkTvMfVwhIv/xm/sHc59WichEsz1TRB4XkZXmvJ2CvC8zROQZEVkE3Cwip4jIfLPGX8z7kAFcC9xqrusos7ZfzTqmiUhbM987IvKKiMwHHheRjX73xiYim7yvvdcYZO66cwwRkd/NmuaKSFdzrF1EnjTXvEJEbmzod/hw5KCyEM5dV6TLwKDtFzbZ++7o/uMdNhjWNYGUuNDabYkxIeQU19A6KZzwUBubsiqICnfgsNsoqdCuJpdpfeKw2Tmj83Aia1qyYNdWhkT04M2VU/l60zy+2TSf3yb+l90lZSzLX8fG4t1c2lNbWUamd2fy2Q/w09bFbMguJLqyI7NWF3DCgBTSo5NIj07i8YVf1q4pISyKSaf+k5iwCD5cO5NO8S25otf4gOvqmpjOjImPBGxrERnPrvKCevfAgyLcHkKBKY6dU7Gydl/r6CSm7VyB0+OmuKaC6TtWcnGPsXt5ly0ABrSLRwC7XWp/ZyJD7USF2sktq8GjoF/bBL6+YSTT1+Xy9C9arKTFhnPtBzoR45rRHcgqrqJbyxh6t47j5vGdmb0xl7yymoDf5ZToJgolv32iLiA96Ao4+emGx+VtDHwtdlj7LXxyIVz0hd92gVOegeUf+w02vYRDIoLPndQRrpysn+9cBGu+1s/Xfqfr+rUbESgC+18EPU6HDZMhOkULyMoCbdFr2Q+2TNfxgc4KbZkcchUs+QBwa6ug+LmGXdUE/W+RvQo+PFuL0C7HwTJzPd1Ph4yR0KofvHmstkyunqQfnZVw6bcN38ODm0cI7GOMef0IsE9WQhHpDkwERiqlnCLyEro/8XtAFLBIKXWriNwH/Bv4u/dYpdRzInIbMFYp5a1vFAXMU0r9U0QeB64CHgKeBZ5WSs0xYmAy0L2RpX2llHrdrPEh4Erg+UbGPwfMVEqdYURfdBPX1tR9GQhcDgxFi+/5IjJTKXWtiBxf55qbQ2P3MlIp1U9ERgNvAb2AfwK/KqWuEJF4YIGI/GLGDwD6mD7MdekMXKqUmiciE8zrIeYavjXnSAF2K6VOMtca53d8sVKqt2gX8TMEb+EX6i2wLiIJwDDTA/pv6HaF/2eEc5lS6kkz7jvgXaXUuyJyBfr9Ot3M1xoYoZRyi0gx+j16BhgPLFdK5XpPrJTKDDL3lXXmiAWOUkq5RIc2PAKcBVwNZAD9zL5EpVRBkN/hw5KDShA63YFZmXWtf80hIdpBdY2bihpFqEMCxCBA99bRdGwRSYhdWLhJW2NqTMmQiFBtcYsICzScJoUl0Cs2ApvYGZnenU83zKZXUjs+XLya1iHt6RDfj4tG1BdVJ7QfSJeIClZklmK3SUDJkFeP/Ttzd69lbNveJIbF8MC8T9hanMOSnE3YRJhx7qOkRsbVm9Ofj0++k9V521iWu4U3Vk7F7Wf5r3YHWv7CbSFUeZwMbtGZdfnaYiPAqFZWy7p9ZVy3NBbeO549xVVc8PrvlFS5qahxU1njEyqj/vsr47unkV9WTajdRlpsGEM6JPLyzM04bDbOGdSaTqm+zNbvV2SRW6YtvC1iw7hsRAbHdE+jc1oT2a8OYy1zNCDWQIvBHSZOLqmLtqYps9acNcGPOeFx+PF2X52/osba1/qx4jOISIL41tD9lIbHhUVD77P0c2+Si80B4+7VglB5YPrDuvTM4Cvhutnw3mk62cQf5aZRJt8Di9/ViTGVVbDhR1j7NZz9trYOuqshOk0nvdRLUjmkaLuX25vDMcBAYKH5HxaB7vEL4AE+Nc8/AOrX7qpPDfC9eb4Y3SsY9Id7D7//k7Ei0nAZB+hlhGA8EI0WkI0xDrgEQCnlBopF5GIavramGAVMUkqVA4jIV8BRwNJGj2qYxu7lx2bds0Qk1gjACcCp4ouXDMf3Pk9tQAwCbFNKeWuoTTA/3jVHowXibOApEfkv8L1Syj9D7GO/x4a+fX7q97w18KmItARC0X2ggzEc8LY5eh943G/f5+Y9Ay2Iv0ELwiuAtxuYry7+c8QB74pIZ7Tk8BaGHQ+84nUpN3IPD0uaFIRGSacopTbX2d5HKbVify5mRLcEcoprWJFZ0njcYANEhtqoqnHjMm95qMPOht3ltEgIIybczpbsCnKLnbRNCadVYjh9M2JJjK4iNV6Lxv4dYmmfFllbpsbp9rBxdwUpcaGkxYeSHBtKRGgyyy5+li82zGX7TiAEsouq2ZhdxJMrPsSjPDw15kpiw/SX9I4tIomLdBAVbsdhF7LLi/jP7x/TPi6NOwafyXebF3DnrLcDbBstIhNqs50bIzUyjtS2ffjX3A9rxWCYPYRqt5NQewjt49IYlNoJu83Gu2t+BWCSXy1FBRRWl9Eeq+7avlDldJNTUo1dAksg+b+XeWU1fLLQ5+7NL69hTJdUfr5lNC63h08X7qBNYiQXDW3HFe8sZMYGLXTCHDb2lFTz9txMrj26GbX8rpgMe5ZD+6MbHhMWoy2Cyg1luyE2Hcr2aEF06gvBjxl4qbbgrf9Bvx5wmU7GKN4Fvc8BWxDxVLIbFryqn/c7H3LX6+dxreuPBZjztK5pGBEPFYUw/O91spHFV88wracuOwO+gtUA9khoN1SLSC/xbaDEzONx6uv2lqTxtrH7/QW48DNY+JZed2mWL8bx0GQ72k0cbPu+ImjLzd3NGNucr/FO5YvjceP7HLKhLUkBzbOl4dqb7wCnK6WWi8hl6LixvWVvrm1/4CIwVKuxf/Sqgefe1wKcpZRa779DRIYCQYJta/HfJ8CjSqlX6w4SkQHAicBDIjJNKfVAM9YV7BzPA/9TSn0r2j1+fyNra3LNSqkdIpItIuPQls0L93YO4EFgurEWZwAz9mFNhx2NfhUWkXOBdcCXouMaBvvtfmd/LyYyzE5GagTj+yTRIbVpQVSXiFAblTUKp3HfFVW4WL29jLlrC9mwq5wVmWVkFVazYIO2DIaF2OjUMpKYcDvbcyvJLqohIToEuwn62pRVwfpd5SzZXGLEoA4tsYmNo9J7sKxifm0ru6lbVjNz5ypm71rD3Kx1AevyP/aLjb/x644VvLlqKluK9/DxulkBf1F3DTmb7874F5EhDbsI3R4PN0x7hbGf3cOynC2kRMTW7hvesisATo+bFlEJjG7ds1YM+tM3JYO/9ZpAv9T9lKxwBHLRG/M58bnZnPf6PKpczfsGc/lIfb+7pMUwd3M+r8/eyn3frGbUf3+tFYMA1S4PApw/pC0rdxYzaenOWgt6cJQWNJWFDQ+JaQHnfwwZYyC1p3YxK+CuHdBpXCPH+X1hiEmFd0+FSVfD0ga8atEtdB/klO7asvjBmfDqmCDZwOgs31/+o4Va6R44520dg/i9Cb2yhcL5n0AH00nnu1sCC1GDblvnrtBicPhNEGnWW7QDTn4GblsL57yrrz08PvDY5K6w+B1Y+w3kb9Kxht4Yx0OTe6gf+F5htu8r04CzRSQVQEQSRcQrOm3A2eb5BcCcIMeXAs0p8DgFuNH7QkT6NTE+BsgSkRCaJwqmAdeZue3GDdrYtTXFbOB0EYkUkSjgDLOtMTKBfib2rQ1a0Hhp7F56Y/hGoV22xWiL6I1iFLOI9G/muv2ZDFzhtcSKSLqIpIpIK6BCKfUB8ATaBR2wFvP4ezPOEQeYhuhc6re97u/FXMBbHPRCGr+Xb6CtqP5WP3+a+p3zX9NlftunAteIiAP070Mz5zssaMo3cg8wUCnVDx0r8b6InGH27ceWCYFEhjtokbj3gjC/LHjiUIhDyMz1BdtHhtkoLndSWa1/j3blV7N4cwm/ry+iuNznao2PdCBAVLi9Xi/kltGJfHDKzQzoEEdafCindOvFiFbdGd6ya60oC8a4Nn1Ij05iVHoPWkcnc9ug04kPiyLKEc4t/U/lsp7HEBXEOqiU4q7Z73LKpAeZu3st07YvJ6u8kF+2Lefl8dcTagLuNxTupk10Mh7lYcaOlTy+qL4Hp11MCp+e/A9uH3xGbacVi71nTZb+YlFcqX/vEiJD+OLa4dw+Qbc+axEbzuUjMwix+/5URnVKZnt+BUUVNfRrE094iI2IEBu7i31GEe94BUxetYdTXpjDrZ8u58XpmxpezOeXwbc3wpdXNL7oFn1g4nsw8maIStHiy2HCKuY8DQ+3hBn/DTxm8N90OZk2wyC5m07gAIgI0o4OtNXwjFfghnm+MZWFsG1e4LiqEl0PMDLJt+2H27VQ9SaVHHu/TlCZ/xqs/lpnMtfD71/R789BRbbvdc5qHZ+YvQpeGKzn8o6PSNQu5OgW5t70gosnQb8/lH9xQDHZxFcB29C/QtuAq/5IlrFSag1wLzBFRFagPzS9TbnLgSEisgrtkn0gyBSvAT83IyD/JmCQCeZfg04MaIx/AfOB39CGi6a4GRgrIivRruoeTVxboyillqANIwvMOt5QSjXlLv4N7TJdg46R86/q3ti9rBKRpcAr6FhJ0FauEGCFiKw2r/cKpdQUdGzp7+a+fIEWPr3RMYnL0LGMD/kdlmDu1c3ArTTN/cDnIrIY8I/B+w44Q0ziB/rLwOVm7ovN/A3xLdq93ZC7uO7cdXkceNTcU39P6Rtoa/oKEVmOFubQ/N/hQxpRjRT8E5GVSqnefq9bomM/3gUuU0oNCHbcoEGD1KJFi/7QwkoqXPy6Mr/Z9QjrVp/xvo6PdNAyKYy1O3zWYm1J9OCwCxP6JbN4czHZRTobdHzfZKLCfUlm1U49zu6XKur0uHluyXeE2Oz8vf9J+0VULc7exO6yfL7eNJ/NRVkoFP8cOpEJGf15ZflPTN++guV5mQBc0Ws84fZQ1hTs4N6hE0mNjGP8F/eSU+ErPm3HhhufRSnc5mBcu76c320MvZLbEeEVARZ7RZXTzeacMl6btYUfVu7G5YGIEDtL/jWeD+dv59Ef19K7dTxPntOXlnHhRIU5cLo9TF29B5vNhsMmXPX+IhIjQzlnkHah9kmP4/HJ60EgM6+i9nc3LtxBSbWr9m/gXyf34MqGys98NBE2/Kz7EJ/XQOmzrbN0/J0tBC7/CVoPDNz/ylG6DV1KN7jBrybford1Ysgx/9IFqYt3QkUBtOwTePyGKVp8tfIzVLhd8FCKdu/2PAPOece3b9YTup0cQGInKNgEqT0gubPujpI+UK9zztMw41E9zuvy9hKZpM9RbX73I5N1b2Z7qO65fOrzOnN5+cdQXQpJnaFgqy6344gEVwX0OE33M45r4xPHBwgRWewNxj8UEJEypVRjcX4WzaSheykiM4DblVJ/7EN1PyAimcCgA51cISKD0AlIwcSexT7SVAxhqYh09MYPKqWyTAzA10DPP3NhsZEOju+fzG9rCympbCJgHJ0U6S8ej+6dQGGZi1aJ4fpDPKuiNs7L2+PY5VbkldaQXaQD5tPiwwLEYFmliw27y2mZGE7LBJ8Ld9q2Zby+Uscv90ttz+jWvf7QtW4p3sPFP/0PTx31+9Wm3+mb2p5nluiMRwF6JrXlrM4jaB+XxmMLvuCUSQ/QM7ktdw0+G6UUb66aSm5lMbmmBE6X+HSKneU8P/Ya+qRk/KF1HukUVzo54ZlZAdY8gFGdk3lh+iZenK7DbJftKMLt8RBlOouE2G2c2KcVFTUunvllA0pBQUUNr8zUBZ9funAAb18+mFs+WQb4vti4FXRKiWZTThkK6NaiEY/F2W/DzgXQekjDY/I2aGHmrobZT8H5dYxGEx7UlrhBdayMP/1DHxMaCRM/0GJt3ssw+g4dYwg6ieSrq7TYHP9vPWbUbdDtRG2NXPeDtkbmboCKfB2TWLIH7aTwaDEY21qLsnUmXrEsT2ceb5qqX9scYLNTGyTc7yItDv0zoSvy4Mw3dWu7mDTYPAMWvKb3hcXpNnZpPSBvE6R21bUR0wcG9m+2sLA4aBGRu9Cu/+bGDlo0k6YE4XXUcQ0rpUpNSv25f9qqDOGhdgZ2imNLdgW78qpoLEzLPyM5MsyG3WajfVokpRVOZq8uwOmnKcuqfBMt2FCMiC4X0q11VO12t0cxa3UB1S7FzvwqTh3ii6PqntSGhLBoHDY7XRJ83SM2FO7i/TXTObH9IIa36tbs6wy1hRBic1DtdtInOYPsiiKSwmP4W69jSQ6PpXtia9YW7EREeGLMFaRExHLBD0+xLFcLikXZm1ias4Wnj76SDvEtqPG4agXh1pI9KAXfbZ5Ph7g0okMbyUK1aJQ5G3MDxGBchIPrj+7ElaPa848vVwaM/XVdLl1bxAZsO//1+SzfUcSoTkmc1i+d//68HrfHQ5XTzbinZtazhpdVu9iYUxbwukFCI6HD0bq3747N+nndYPwBl2rBl78Jep9df44OR+ufugy4RJdk6XqSjgNc+IYuP7P4bS0Ipz8C27z1XwV+e17XLvzmBui0Dsbfr3+2zoaXhgVa+MTmU8BpPWGjX6Kos0y3wPPicemfyGRdmmbN14F9i73kb9TiOKkjTPmXXlN4rO5+Uo0vQ7lFH7jgc23VtNgnLOvg/qOhe6mUOvovXkqDKKUyDoI1PAY8dqDXcTjSqMsYQEROBzoBK5VSTaX1A/vHZexPRbWbyUt9FmoBHHZwunWtQo/SFsXOLSJZsa0Up1uRGhfK0C5xfL8ot9lu55MGpdTGCpZUuJi2Ih+AmAg74/sG9nh1edwIEtB+7orJzzF391paRCbUqxnYFJnFOZTWVDA5cylvrJpCSkQcMyc+UuuOnpK5hPyqMqbvWMnsnavqpXaF2hzEhkaSV1VCi8h4MuLS2FaSQ1a5L8ng+IwBPDP2qr1al4VmZ2EF456cQY1JWIoKtZMcE0a4w0ZSdBi3TejC0m1FTFubTVGlk5cuHEBGUhQ2v1CDIQ//Qk5pNaf3a8Uz5/XH5faggM8X7eSeSSsbOLOud3jt6I5M6Nmi8UXWlMPTPXW83nGPBG9JB7otnX92sNuphVVEQsNzZ86B/2/vvMOrqrL+/1n35qZXIAmd0HuR3iwo6tgbNmzYRsdxnKa/cXz1VWccXx2n6qijWLCODbEPggUBEaVI772HJKT3e+/6/bHPTW6SGxJIIAnZn+fJk3P22Xufdc6FZGXtvdb3tUvMfrtT7oYVb5rIX0InI28HZrn34DqqbOCY9imkTTTHr10KW4Pr5Dr9wmNN5LHLaLMXcu9yE+kDs88vIh5ydhz+2YMJLCu7wowDGdwWoNt4uOhpaNOj/vMeB1rakrHFYjlxOGyE0CnSORCT/fNHERmtqke8cbWhREe4Gd8vkfxiL26XEOlxsdjJFO6WHEWX5Ejaxpm9P+m5pezJKqVtnIeiUn8NZ9BZxaPMa35lucUszcVGmv1dAeKi3PTqEE1BsZdhPapGesAUra7O2A59WbRvPWM7hk4qKSwv4a9LZ5EUGcedw86rUk4hLSEFgM93VO5JlqDg7Mtrv+THg9tqfUdlfi+ZJSYqeKAohwNFOYxM7VXFIYy0+waPmt+8s6LCGQSjJFKY5SRzphfQbdke/u/SIdx6inEwbnllCfM2ZvDXK4ZWaBC/evNoFm7OZMoIs3cwzO3iQG4Jb/2wk+7tYhjXvQ1vBpWoCbB8Zw6ZBSEydKujfrOfDirLqoQi2Bn0lsHfB5io2RkPwcm17BHfv9JkDOfugq7jKpeKS/Oh/WCT4Vyxl9Z5TxFxZj/h1q+Mc9b3nGoOodOvrAA+vBN+sxaueRceDvrjq7zYRCUjEir3CYJJbOk43Nx79bvOvsEIs7Qd+H8TFgmDppiI4c5vK8eKCy7+NyTVN5nUYrFYTnzqWjI+BRjqVPaOxqSBH3eHEMz+vtTEyn18w3sqOQXl9OscS4Sn8hfcyF4JDO2uFZG+Lu0i2X+ocrm5b+c4eraPRlXJLfISGxmGz6+EuaVKNEdEGNwt9J4tVeXtjQuIDAvn4l5jK9p/OuRsrhswqdaEjY+3/sCbG+YDcHKnAQxLqRmd+NWICzkppQf923ap4jBmFOXV6BsKF4Lf+UWbGp3I3Mv+wIK9ayn1eblh4GFKi1gOS/u4qpnfnRIj2ZtjnK728ZFcMLRjxTWfX5m3MQOvX/lmY0aFQ9ivfTz9gpaRNx7I57fvrGDNPmd5P7PQqPNozeJe+3LqkKQD44Dd8gVkbDh8MWgwdf9+fM1E+QJLqKvert0hHHGjiTwmdoXkPlXvebtTHSNjo1E8yXLUUE77vVEsec0pTDDhlzD0WnMfLa9MAAGjgTzvz6YuYnCGmLfac7ftZWT6yotg50LoMsrM+83jMPQqKEiHnL2wf7mJmC6fYZa6o9uZSOX4X5jyO7XVRLRYLJZWSl0OYVmgxo+qFonUXiH0eNMtOYpuyTX3w4kI4WGVZo7slYDXF8+mfYXERrrp6owRERJjTHHyMPeRPdacnT/y0HdmI3uXuHaMSK0sHFzdGTxYlMuCPWs5vesQhqf2JCEihsSImBo6yAHCXG7O6Da0RntqdAJ7Cswvz8SIGHJKq9YdDRMXXvXjFqlITvlh/yZ+v/BVOse2408Tr7MlZhpAdrEpRxTlcTGmR1t+f05/5m86yKwf96JO8kcAt0v46xVD+WZjBr+c3LvWOf/55aYKZzBAKHWeTomR3Dmp9nmqkNLPfNVGSR4sfsZ8leSavYG9zoQ9S+CM/619XHi0UQ85HMl94RdLjRP40k+MOkivIAnGb/9pvgekYosyq47/4bmabcFEtYUbZ8P0SWYPI5iM58kPwYS74KVzYNciiEh0BjgvM3VgzQQai8VisVShLg+hn1MTapVToyhwvtqpFdQiCHMLA7rEVjiDDaVTbFs8rjCiwyLqlJe766vn+Z9vX+P/zX+ZPkmdWHz1E3x+2cMkRMQcdlx1RravdAiCncHUKHN/r6PakBydWHEtu7SQpelb+GDrYu755qUjup+lKucM6kCUx82Vo7oy48bR9G0fR0xEGOv257P+QD6Pz65aBu2iYZ3425XD6Na29s/57IHtifS4SI49/FL+1aO7Ehlec4vCUREo4VKSZ5ZzJ/zSaBhf/GzVAtQNISKuUkVku4mIIy5HbURMlDG+S2X/QVPMPsGELjWmqkJxFvz3/5koaMogaNMTznRKtaWvrZTviwr6PxnVBiY1pCaz5VghItNEpBaJnIo+t4vRzK3enubU62uoDQ8FpN9EZIaIhMi2slhaB3VFCA8nLN5qGdSuG19e/ghhLhdtIiuXlbfk7OfeBa/QN6kT9425nHc2LqTc70SWwsxy99EGWUNFFGM9kTx+yjSmfW4iLylR8Tw4/moe+PZ1EiNiaBeZwKL96wH4bMcyHim/7rAKKJbamTqmK1PHVJWDPalrUsUS75kDj9yZumhYJy4a1ondh4qYOn0xe7KLaywVu10wqNPh/+ioF2WF8MEdJgsZTAbuTZ9DWASs+A98cLspGfOLZQ3fW9euj4koluZXaiCrH8pLAYXs7SaRJMCa9wG/kYzzxDqaxrWUFNix0Cz53vEtFGTAho+h+yQTkSzNg9E/hckPw9NjzfLxuX+pmW19grPn3gVTgUcxura7gPs6P3ZyiwyRquq/m9oGi6W1cFiHUFVDKtk78jlXA7WkMZ74hIoMfrz1B9Zk7mRN5k4iwzy8sf6bisSQ6jUGj5Td+ZVLaYF9gm0iYlmwdx13DD2HMr+Xc7uP5HcLXqkoYxNwBgG6xiUT4faEmtpylPTvEM+S/5mMXyE57ugc7byScgrLvEybkMYfP6n8vAIujM8PN7+ylLUPn02kpwFRwq1fmzItAOf9zahxOH+kVHx3hYHbYzzchjhRIhCbahxCl8foCAPk76vsM/G3sG6WKYFTHlBaU1NqJhS9fgIHV8PYOyrbZt1mklQ6DjcOZmkexHUwzuivW8wCRqPiOIPTAUdOhm7A9D33LuBonUJH63U2sBgYDyzBKEQ8DKRg6sEtBTYC41U1Q0RcwCZgnDPNvzEOKsCvVDUoy6fiHi8B7YAM4EZV3SUiDwEFqvoXERnh9AEjc1ebvb8DrsX8VfFfVb1XRHoCTwPJGCm/W1W1PuomFkuroa4IYQWOTuJU4HKM9E5NTbRWzoU9R7N4/wb6JHWmfxuz/BXmclHu93GoJB+/+rlv4WtszdnP4ydPo0di7WVE5u5cwZvr5zFt4GRO7TIIV1DGsQBj2vfBq35eXDOXcFcYy6/7B7O2fMfmbPNLd0/Q79VLe43lofFTq5TIaUz8PqXkEEQnt65IDEBSdDjPzNuCKtwxqVcVRZtgcovLmblsD+N6tqV/h3jySsrZdCCfa6YvptRX84+F4Az46HA3HncDP7tu4430nPqMMocnaPvEoEuNIxXd1tQO3PGtURTpd+7R3++WL2DmrU5RaTHqJxmOw3vDp9BpOKx6K8gZrIOtc+D+g8ZhBSjOgQNOqZ6IOJj6tnEuu40/eptPDB6l0hkMEO20NyRK2Avzs/8mjEM4FZgIXAjcp6oXi8jrGOfwH8BkYKXjHL6JUZVYKCJdMfq51VefngJeUdVXROQmjKzbxdX6vAzcqarzReSJUEaKyDnARcAYZ997QF/xeeB2Vd0sImOAZzDycBaLxaGusjN9MJHAqzEahG9jahdOOg62tTh6Jnbg7fN/B0B2SQF/XTqLnNJCusWnsPzgVh7+7i0+2GL0XD/ZtoS7hteeCfq3ZR+wPTed3LIiTu0yiKv7n8JH275nZ14GydEJTOg0oEItJS48ijCXm/0Fh0LOlVmcT/gxjA4uut/P/sXQ/3rofamLiIQTzzH0+5UPVuwlNT6SCb0qy6J8vfEgf5mzCYC+7eNqrRX4yCfreHfZHtrFhvPazWO47NlFeP1apZRNda4e05Uyr5+fndqzVkezvjyVUc76cc/zUM+OpESE+LfQbRyUFphIIgpbvqifQ1heYiKAEdUy8qOS4KxHTNQxbQJ86RQniE6GV86DPmdD5sb6P4BqVSmi7d9U6h2fdC3EppgvS9cjbK8v21V1NYCjm/ulqqqztzzN6fMS8CHGIbyJSp3ZycCAoO0y8SJSvQjzOOBS5/g1jNZsBSKSCCSq6vygPueEsHMy8LKqFgGo6iHnXuMxerqBfnbvjMVSjboihBswpWbOV9UtACJSHzHrVk9OaSHZTvJHXqmJguzKy+Cy3uPZkrOP83uOOuz4y3qP56U1cyvK2uwrOETvxI7szMvgQFEOf1v2AXFOlOfcHiNZcmAzn+9YEXKu4OXmhqJ+Ze0MxVcKg24W3OFC9hZzbfunsP5VP55YOOkuoduZJ05W87vLdvO7matxCXz129NIa2eSRXqnxJEY7UHVOIS10T7BJDykxkeydEc2RWW1yzGGu110axvNrSf3OGxSSn3ZXVLGn7btB6BbZDi/69EhdMeIWLjgn0Z1ZOKvjObvh3cY/d9Rt5qSML3PrOxfmAVPjzFycEOvggEXwpePmHqBN3xisp0v+TcsesqpDwgUOSVudi42EcmirPo9RMeTquoM9zitMoO5z9n1fRWtgV2YZeJQ7Q0huBCmP+jcj/N7RFV3i0i6iJwOjKZSWswFjFXVKsUxj2PRCheQo6rDjtcNLZaWSF0O4aXAVcDXIjIbeItqUnaW0HRPSOXvp93CvoIshqX04IudK5nSZwI9D7NMHMwtg8/ilsFnVZz/fsGrbM7ZV6XPtf1P46TUHozv2J8b/vt3tubuDzlXr8QOXPrRo1zcayzXD2jYKsnBH2H9a+ocK6kjhPEPu9i7UNkx27SXF8CGN5VuZx5uppZF2xgTUIgODyM6KOO3a9toFv/+DHZmFfL2kt2cN6QDAzua/aV//GQd8zdl8KdLBvObM/tw9sD2fL7mAA98uIZ2seHkFJbhrRYgvGViGvef3zgy4TMPHOKjjBzu6prK2IQYNhSWMKnNYfSQwRScDhSdnn2fcQ53LoLlrwIKY35m1EiS+xv94YCD9+NrsPq9yrqBn/zaZC9/drcpHF3xY8N54PJiKC2r/8NUL0cTmQDXzqz/+NbDfVTdQwhmz9zxSrV+AXgdeC1Qsgyz3+8XwBMAIjJMVVdUG7cI87vmNYwjuSD4oqrmiEiOiExU1YXUrmM7F/hfEXkjsGTsRAm3i8jlqvquUz5tiKqubITntVhOGOpKKvkA+EBEYjD7Mn4FpIjIs8AsVa11Y68Fzuk+ouJ4f2E2F33wRyZ0GsB9Yy6nc2y7I9rTNyQ5jc05+xie0pPlB7cCcHLngQxP7QnAWWnDWea0R7g9lPrMRv6RKb0oKC9hXdZu9hUcarBDmNAdolKgLBdyNkPOZmXLB0p0KpRWiqJQsLdBt2l2TB6QyuxfnUxClIeU+KpFqiM9bh76aB3fbctizrp0vvjNqZR5/by4cDsA7yzdzejubRjUKYHfvLMCgMyCms7Qg+f358aJjSel9rtNeyjwGbWeD4Yfpo6h3w9zHzAFqs/5M0QlQtGhasvAjiO34k0TAdz+Tc15gv9UjE02e/xWv2fOw2OMwsmWueY8LAK8/kppuboYeXP9+rVyOj928pt77l0ATZdl/BFmqfjloLa7gKedUmVhwHzg9mrjfgG8LCL34CSVhJj7RuAlEVFqSSpR1dkiMgxYKiJlwGcYZ/ga4FkRuR/wYIIb1iG0WIKoU8u4xgCRJMzm4itV9YxQfRpby/hE4N4Fr1TsHwQ4pfNAnj/zznqPV1WySvKJcHt4ZPHbFHlLWZu5i0ldh3D/mCuYu3MFs3cs57PtNd/7Jb3GsiJjO5f0GsdPhzRsee3QemXFs6YkSPZG8NcS5InpCOe+0Ui181oAD3+8lpe/3cEFQzvy1NUnAfDXORuZvymDmyZ2p2dyLH/6dD3r9ueR6xS5rs6y+yfTNrbxtjb9v427mZmezWN9OnN5+za1d9z1PbzkRKNPvRf2LjMlYAozjMKH3wcl2bUMDpYVceh7Llz2Amz8L8ys5si16WGk6PLq+RfD2DvNHsS+57SK8jEtXctYREZiEkhObmpbLBbLkXFYhzAoQyskqhoyi8E6hDXZnZ/Bn5e8z9ydKwCIDovggbFXcm73kXjc7nqpiGQU5XLXV89T5i9n46G9FcWoPS435X4fLhF6J3SkS3w7xnXoxx+/fxuAHgnt+ezSBxvlORb/0c/ur0L8m3EBfojpBCPvFtr0FcKiTvxf4MHsyS4iKTqcf3+zlYz8UlbszqFPShwfrdoXym3CLfDoJYOZsWgHU8d247qxTaStW5IHr14IhZlG3m3lf6peH3UrdBxm9IY9kUb/GGDIlbDta8g/AEOvhjbdjXzd2Y8a5+2fQ4OyiMXUJ7z1S9i73MjZBVYU3ZHgq6697LyxSffDqfccu2dvZrRkh1BE7gV+BlzjLOtaLJYWRF0OoR/YAwTWdYJ/w6uqhlzfsg5haLx+Hz+d+y9WHtxOobdyj7ZbXPx+9BSuHXD45O2LP/gTG7L3HLaPICjKbUPO5tNtS9lTkMXlfSbwxwnXNtj+onRlwb1+8nYENbqh03gYeY9QuE9I7HNcN4s3O17+djsPf7yu4jxQOiYUp/Zpxys3jTlOltWTnd/BzFtMQkj+AfN1xSvGUczcbJZ+Y1LA7ew2Kc4xGsdtuledJz8d/jkEvCUm+3fib2Fs0Cph9g5Y8gL0/gl0HgHTTzd7E+Pam3sOuRJ6ng6DLqssNdMKaMkOocViadnU5RD+A5gEfAv8B1io9Vhjtg7h4dmas59LP/o/yv3eKgWrH5lwLVP6TKh13NRPnmB5xrYqbd3jU4gNjyKjKI+u8e344cBmADrFtOW9C+9lXdZuxnToQ5ir4cu36171s/bloI/fBSN/K3Q/98TJJm4IpV4fy3ZkM23GEmLC3ZR6fRSVVVXcaBfjYUiXRErL/Tx44UD6pNaR5NGSSV8LuXuhz1l191U10US/Fw6uh86j4RjVzWzOWIfQYrE0FXUllfzKycg6DbgOeEpE5gDPqur242DfCUnPxA7MmfIHMovyuWH23ygoN8tl+2qpIxjgX2fcxm1zn6HM52VTzl4UODNtOL8ZcREAJd5yznn/QXJKC3l04nUkRcZyUkoPPt22hDaRcZzc+ciyVw9t9JO7VQmPc9HpZKHTycKur5TYDtDjIkgZ5iIssvVGAwOs25fLFc99R0Gpj2iPiytGdiYu0sOz87bW6Bse5ualaaObwMomIHWg+aoPIib6CNB17LGzyWKxWCwhqXdSiVMY9Crgj5jK9NNr62sjhPXHr34eWvQf3tm0kI6xbfjskgeJDK635vDMis948sePQ85xSqeBKHDToMnsKcgkr7SIGwaeQZjLzRUfP86qzB0A/O3Umzm3R93Bh4xVys7P/Wz/rLJt4qMuOow7MZ2/ojIvM5ftYXi3pIqSMUfCuf+cz7r9+fXqO7xrIu/fUXsU2NK6sRFCi8XSVNSlVBIoN3MlRgPyfWCEqja0yKnFwSUukh1d5PTCHIq8pSEdwqXpm2udY/7etYBJXNmRZ9Qb2kUlcFGvMRwqqXRUXPXY25exQpn3a3+N9rCG10duttzxxnLmbcwgNsLNygfPDqkKkltUznvLdvPDjkN8symDpOhwYiLc5BZ5ySgoDTFrTaaNT+OB8wc0tvnNi7WzIHsnjP1ZpUayxWKxWJo9dRWmPghsxtRs2oxJlBzplBZAVa2ecSNwy+CziHB7cIuL3857kXN7jOTyPhOr9Lln5CVc/elfKfFV1nnxiIvyoEzjs7qdxDubFlLsZIFuydnPC2fdxXubvmVwcjfOThteMXZvQRbRYREkRRoFqcIDflZPV8LjHGdIIOUkiGoHfS4XEnudGNHBFxZsY3tmIT+f1JPdh4qJ9LiZt9EUV3aJ8MP2LMb1rJSme3fpbh7+eB0FpVXr5e3PrZ4VaxDgtL7JXD6iM//4cjOb0gv43dl9+cngDnRvd4J61YWZ8MoFxhEsN+o8hEVWTSKxWKohItOAkapaa/0tEbkdKFLVV6u1pwGfqOqgOu4xw+n3XiPYOw+4W1VrLH+JyAvA31R1nYjcp6qPBl1bpKrHRGRbRHZg3mGmiBSoanVJwOr96+xjab3U5RC+43zv43xBVckB6xA2AlFh4fx0yNncNvdpvtu/kSXpW8goyuOOYZVasmkJ7WtIxJSrn0iXh24Jybx53j3EeCL56ZCz+X7/Ju786jncInxw8f0kR8ez5MBmJnTsT2x4FIv3beDmOU8RExbJP/0PkDErjtKcwKzK+D8KUW2FNv1PDCcwwNaMAh75dD0Ab36/CwXGdk8iNiKMwlIveSVerp7+PecMTKXUp/yw/RCdEqNqOIPhYS7KvH7CXMKpfZKJ9LiI8rg5tU8KE/u0JSnaRMZO759KZkEpnZOiq5tyYpC5BTZ8YiToDlZmViNuaNer6exq5Xz21U1TqVaY+tzTXzpehakbFVX9d1PbUBci4lbVW4Ka7sO8fwCOlTNosTQ2daXxrQFWA2udrzXAV8AfVPWmY2xbq+OinmOI8UTi9ft48sePWZ25s+JaVFg44zv1rzEmzO3mg4vuJ8Zj1DNiw6Nwu1woik+Vrdn7+b8f3uP19fN4e6NRg9pTkIXP7+fU+Rew++XYIGcQ2vSHDuNOPGdwzd5cLn92UcV5YOfs4u3ZuF1VawSu2J3DVxsOUlDqpUubKIZ1SaCDo0UcF+HmpglpAAzunMCL00bx9DUj+MsVw7hgWMcKZxCMgskJ6wwCvHsDfPEgrHqnavvt31bqDFuOK44zOB2jZyzO9+lO+1EhImkiskFEZojIJhF5Q0Qmi8i3IrJZREaLiMs5TnbGuERki4gkO18zRWSJ81VjE61zj69EZJWIfCkiXZ32h0Tkbud4hIisFJGVwM9rsVVE5F8islFEvgBSgq6NEJFvRGSZiHwuIh2c9nki8riI/OA838lOe5SIvCUi60VkFhAVNFeBiPzVsWWcM8dIEXkMiBKRFSLyRqBv0Ljfichq5zkeC2F/qojMCjyniIx32q917FshIs+JyFGXjRCRPzlzLxaRVKdthohMCX4+5/tpzjv7UES2ichjInKNY8tqEenp9LtARL4XkR9F5IugeR8SkZec97NNRO46Wrstx566IoShQsvdgP8RkYdU9a1jYFOr5dweI+mekMoNs/9O26h40uKdn2V+P7hcjG7fmy93VVVbKigv4bt9GxjfqT+78zJ4cNGbnNZlMFf1PYX1h3aztyCrou+MtV/gVT/XdDyTkuRIIjYPq7jmCoNOp8DYB05MdZFnv9nKoaLQCiG5xSYCGO52cXq/ZG6c0J0NB/L5Ycch7v1JP7q0icbvV+ZtOkjvlDi6tInm4pM60a3NCboEXF8SukD6GmiTZuoGfvEgjJgGqTX/cLEcNx6lqo4xzvmjQEOihL0wClU3AUuAqcBE4EJMkuHFIvI6RiLuH8BkYKWqZojImxj1koWOo/c5UP0fyVPAK6r6iojcBDwJXFytz8vAnao6X0SeqMXOS4C+wAAgFViHkbvzOPe4yLHpSuBPzvMAhKnqaBE5F3jQsf9nmOXq/iIyBFgedJ8Y4HtV/S1U1l5V1XtF5E5VHVbdMBE5B7Mnf0xAZzmE/U8C36jqJY7TFysi/TH7+CeoarmIPIN5z6+GGF8XMcBiVf0fEfkzcCvwSB1jhmI+r0PANuAF5139EiM5+CtgITBWVVVEbgH+H/BbZ3w/TPm6OGCjiDyrqqF/GFualLrKzjwcqt35h/wFZm+hpRHp37YLi6f+pVK5ZN7XsHEDTJjIDYPO4KSUntw4+x9VClv7nPjWnV89x8bsvSzav6GiQHVCRDRh4sKrfjKK81k0M5M28yE5bRh0g8ID0GsKyMXbydQtbMjvRL+4wU3w5MeWS4Z14qv16ZR6zZ5Lv0JStIeocDeXDu+Ex+VmfK+2jEozP6PH9GjLDePTKsa7XMLp/VIrzvu1jz+u9jdLrnjFKJOkDgSXG4Y3vPi5pcF0PcL2+rJdVVcDiMha4Evnl/9qIM3p8xLwIcYhvIlKPePJwACpTGqLF5HqwYZxwKXO8WvAn4Mviqlykaiq84P6nBPCzlOA/6iqD9gnIl857X2BQcBcxw43sD9oXGD707Kg5zkF46ChqqvEaDEH8AEzQ9z/cEwGXlbVImfOUHXGTgeud677gFwRuQ4YASxxbI/C7O8/GsqAT5zjZcCZ9RizRFX3A4jIVip1pFdjHD2AzsDbTtQ1HAguS/epqpYCpSJyEOOoH15hwdIk1BUhDImqHhJpxXIUx5gqMna7nGXjXbugQ0eGeCP4csSNeAsK2N65HaXqY2Ink7kaSBDxiJt+bTuzMy+Dq/qewkPjpnLFx4+RWZJPWJKRC8vfDRd/7CIsSrhr3r+Y8/FaeifHcP6gVPK9uQxPHIf76Fclmh2TB6Sy/o/m90e5z8/CzZkM7pxAu0bUDm51hEVAhyFNbYWlKrswqzih2htCcCq9P+jcj/N7RFV3i0i6iJwOjMZEscBsTRqrqlUysY7zrxAB1qrquFquB57HR/1+L5Y4DtvxQDDR0983wlzlQeISwc/qxdlCJiIujFMXoM7PHhN9/ZuqfiQipwEP1TK+vu/X0gQclRSAiEwCalO7tzQiCwZ15Y/xuezJ2gfvvQMffUDigkW0+3EVo/L8jEztxa48kyX7r9Nv46FxVzM4OY3VmTtJjIghPjyKDjFJ+J0oYkqP8Iq0oKJ0831D9g5z4PycWJ77HR/se4NiXxEnIh63i0n9UqwzaDkRuQ+o/h+3yGk/HrwAvA68G+QwzcEsLQIgIsNCjFuEqXMLxpFcEHxRVXOAHBGZGNQnFPOBK0XE7USrAhGsjUCyiIxzbPCISF1V0+djlsYRkUFAff/6KXeWqKszF7hRRKKdOUMtGX+JWarGeYYEp22KiKQExonIYYXPRWRDPW0NsAMThQSzDeBI9SITgL3O8Q1HONbSTDisQ+hsGl1V7WsP8Dhwx/ExsXXzy7Uf8UbJTv5WWql64XW78QsURUdx1adPcNbM/+XVtV8RGx7FVf1OoVNsWwB25Wdww3//wdIPc/hn19/y8PiruLDTENRTjvqoSCb5xahJTOzRlvP79cLl/JPILE9nY8Ga4/24FoulATjZxLcCOzG5UjuBW49jlvFHmL3nLwe13YUpV7ZKRNYBoeoR/QLjLK3CqGL9MkSfG4GnRWQF1Ci6EGAWpkTaOsweu+8AVLUMmAI87iSCrADqyv59FrOHbz3wB8wSa314HlgVSCoJoKqzMe9nqfMMd4cY+0tgkrMUvwwYoKrrgPuBOc77mQt0qO3mItKO2t9PbUwHTnXezTig8AjHPwS8KyLLgMwjHGtpJtSlZVz9rxAFslT1sP9YrFJJA9i2FdasgSFDIS2NW+c8xYK967g/si/XdhxKQZdOnD3/acL8yun9xvHxlsVcW5ZI/+Q0zr7oRgDKfF5eXfcVf1k6i9HbJnDBwqvBBWFPfMLB6O20L+rF8Lzz6HKa+Zmxs2grsw/WrCB0QcqVxHriiXJH43HVLJZdX/LKc8gqO0i36F5Vl8MtFksVpIUrlYipUft3VT25qW1prYjI+UAPVX2yqW2xtCzqSirZebjrlkbgwAEoL4MuXaGkBBYugOJi05aWxnNn/pyCshLiI0zi4KsrPiNLy0AgxhPJ2wOm0HPZGjhQAnv3QqdOhLvDmNbrTNL+OxpXmIcszHYvf3oMSf+4nfJoH8kvQqmvhB9zF7M6L/Qfvh8ffBuAeHciV3S+6aj2FPrUx6z9r1PiL2Z4wjhGJU2se5DFYmlxiMi9mOXO2pZzLccBVf2k7l4WS03s5s6mwOeD7xbBurUV+/Y4+yewdYtxBkWgn6nK4BJXhTMIMDg5jTBxkRqTxM9POo+ovHxY7syzYzt06gTAlg+U7P/GATDqXkgZ7mL39xNZVeZByzzMWfsl7t6H2FNSt8+f58vhQMkefOqja3QPAA6U7KXUX0K36J51jhdn9UKOeBXDYrG0FFT1MaBGbT2LxdIysA7h8WT5MljxI7jdJhoYjMsNUY7jl5wCA0MrMp3caQCLr/krkW4PewuyWLt/A5PVRzgu2FuZyV+WV7kVILKNEJ0sZIz5lrynNhO+sTOHuqzHXVL58UdIJGVahuKvKFkTYGjcaD5NfxdFGZ4wnt6x/fnowH9QlMnJF9Azpl8NO1UVEcEtbi7peC2HyjLpEtWdUl8JYS7PCZXBbLFYLBZLS8c6hMeLvXthyQ/muNypyel2g8cDY8ZB167QpQv07AVtQiWfVRLricTn93PVJ0+QXVrALe5k7vZ1gFgTEdz8vp8DP1T2D48Dv/pZW7gcYsE7wsi3+aiUZHO73IjPbBKNkCiGJ44lqyyDg2X7ifPEV7iHy3MXsb94V4XD6MI4dvtL9rAqbwkdI7ryfc43+NTPBalX0jGqC3FhCcSFJbCzaCtzDn5AXFgCUzreQJjrSBPZLBaLxWKxHAusQ3i8+OSjqudt2sKUy83ycAARSE2lPoiAx22csfCkduDpAKefgX/TNlb8qyvq8uPrkU7Y3hTCosJxiTAkfiSr8kIn+xT5KvOEwiSMwQkjmLnvVbLLM/kuex6jEieyJMdUgjhQZqoLxLjjmJPxAYnZbSj2FVGqJewo2lIxz8KsuVzRuVLhMLMsHT9+cr3ZlPhLiLUOocVisVgszQLrEDYFad1h8plVncEjxCUu3j3/Xjbl7GNCx35sKFhLxt6PGbkwg67dTmfDeZspGbmBjtqDhZHKgZ176BDZuV5zF/rzAWgXnkpmWTo+9ZJReoCe0f0o8hXQLrw9W4s2EMhQz/GGKrgPcWGJFcfppfvYW7yLaFcMxf4iPk9/n8EJIynxFTMofrjNPrZYLBaLpQmxDuHx4rRJJonklNOgbdtGmTI1JpHUmESKfIV8kzUb3ODvHUbvhK/IGJvI3nIoDS8gq9ioHO0t3g2YZd62nhRSIzsSFxbHj7nfU+IvJsoVTbG/iE6RRuWqfUQnNhQYtabEsCTGtD0VgGJfEesLVuLVciIkilItrrApzp1Avi8XgEJffkX7Fwc/psCXV3GeWX6QrzM/A8DjCqd/nFW8sFhOFETkdowO8NHo7QbP8xCmrmIGEAl8DfxcVf0NnHcHMFJVM0WkQFWrS+lZLK0O6xAeL/r2M1+NideLfjmX4sL9hA1z4XMpm7r42dClkCivEuWK4dR2Z3OgZC9Lc76lTEtJDGtD75gBnJQ4lnIt54P9r1PqNwku3WP64FMfka4oVLWKQzcw4STK/WV8lv4eBd48FPPz+KTE0eSX57GuYAWK0iGyCwWFeShK16geqCoLsuZUcQbBOKVh4sarXhI8SY37XiyWVkz7r1dMBR7F6BfvAu47MGnY8SpMDYCq/rsRp/u7qv7FkVSbD5yKcQwtFksjYtfpWjIHDyI7dtA2o5Ree01mcCDZo1iLKPYX8kP2AjpFdcOrJpElx3uIJbkL2Vy4lnxvLtnlWSjKwNhhtPOksrFgNSvzfmB/6R4GxY9gWMIYJrU7l9iweLLLszhQupcCXz5dI3vwk5RLaRueyrqCFbjFw6C44aREdKiwYUXe98zP+pz1BauqmO2RCPz4KNMyTmt3Lh0juxzf92axnKA4zuB0jJ6xON+nO+1HhYikich6EZkuImtFZI6IRDnXbhWRJSKyUkRmBsmyPSQid4tIPxH5odpcq53jESLyjYgsE5HPHam5wxGOiRLWkE0VkVQRmeXYsVJExjvt14rIDyKyQkSeE7HlDSyW2rAOYUsmJQVN686hth52pZiIXXC5GIA9JTtYnvsdZ6dcQq+YARXtxb5i2oYnMyhuBG3DU+gbN5gOUZ2JdseQGNaGNp52uMXNyMQJ9IkdyI6iLWzOX1dRS3BH8Ra6RHVnW+FGFMWrZXSN7kH7yI6EiQfBhaLsK9lDj+i+xLnjK+49NH5kxTwRrshj/ZYsltbEo0B0tbZop70h9AaeVtWBQA5wmdP+vqqOUtWhwHrg5uBBqroBCBeR7k7TlcDbjtbvU8AUVR0BvAT8qZZ7/9qRetsPbFLVFSH6PAl849gxHFgrIv2d+01Q1WGAD1s022KpFbtk3JIJC0PO/gltAN+up8BfErJbuESwsWANnaPS2FK4DjAqJbP2vU6Rr5ACXx6LDn3N2KRTiXBF0SGyM14t553dL+HHzzkplzHn4AdVnM02nmRc4qJTVFfWF6wEINYdR1J4O67r8jPSS/ezIX8V/eIG0zGyKxvyV7Lw0JfGHncEF3WYitfvJd+by5LshZyUMMaWobFYGk7XI2yvL9uDHLFlQJpzPEhEHgESMRrGn4cY+w7GMXvM+X4l0BcYBMwVk1znxjh8oQgsGXuA90TkKlV9q1qf04HrAVTVB+SKyHXACGCJc48o4GD9H9liaV1Yh7Clogper6ljCIS7Iir2AgYIFJgOOGzZ5VkkhCWR581ldf5SvOqtiNSV+otZl7+C7PJMsssz2ViwBp+aOoV53hziwhLI8+bQJaoHbTztGBA7lHf2voxPvUxscyZtw5NJCm9XYUuXqDS6RKUB8N/099lVvLWiZmFKeAdSIzqSXZbFJ+lGHi/CFcmQhBYr4WqxNBd2YZaJQ7U3hNKgYx/GuQKYAVysqitFZBpwWoixbwPvisj7gKrqZhEZDKxV1XH1NUBVy0VkNnAKUN0hDIUAr6jq7+t7D4ulNWOXjFsifj/MmgkvvwjbtgJwSYdraOtJrtKt+vJxdnkmud5sFD9hYhzJCIl0rmWxpXA9bsdp8wU5i/nePKZ0nMa1nW/n3NTLGNvmVNYU/Eh2eSZ53hw2FqziowP/4ZvM2SHNzffmANA+oiNTO/+U1MiOAES7Y4h1x+PCTbvwlLqfuyQXPrwTvvxjpeSfxWIJ5j6gqFpbkdN+LIgD9jvRu5DLsaq6FeNEPoBxDgE2AskiMg5ARDwiMvBwNxIT5psAbA1x+UuMjjIi4haRBKdtioikOO1tRCSUs2yxWLARwpZJeTlkZhqn6MAB6NETF26yyjPqHCoIHlcEMe44olwx9I0bzLKcbynXMvz4cVf5JyGAUq5leFwePC4Pxb4icsoP0T2qN+vyfjTd1EQidxRt5VRn5Mb8NSw4NJfeMf05M/kidhRtoWdMP9JL9xLljaZdeHsi3JFc2elmfOolwl2PvYQr34YfXzPHfc+FziOO5K1ZLCc8ByYNe7P91yvg+GUZPwB8jykL8z3GQQzF28ATQHcAVS0TkSnAk47zFgb8A1gbYuyvReRawAOsAp4J0eeXwPMicjPG+fyZqn4nIvcDc5wM5XLg50DdAu4WSytE9BhEWkaOHKlLl4ZWxLA0Els2Q3o6DB8BUaZMzOyD77OneAceVwTl/lL8VJbqcuHGj6/GNJGuKNwSVlFipk/MQLYVbcKr5bhwEe6KYGj8aMr8pRT7C9lTvJMCXx4dIjqT681hbNKptAlvxzeZn5NTnkW0O5Zcb7aTVOLHhYsodwwdI7uQ5GnLD47aSYwrjis630S4K7zClrL9hfgLywnvHIs3o5iwjjF4DxThSYlCPG5IXwevXggxKXDTbIiMr/E8FktLRkSWqardO2GxWI47NkLYEjl4EDIyYOAgiDJbeUSEc1JN4l+pv5QZu56sMqSNpx1Z5QdrLCN3ierB9qKNFefR7piKpWI/fkr8xSzJWVDhXAaWlA+W7seHj68zPyMlvAOZZekoSq7XVIRQ/MS44yj05VPoy2dz4TpGJIyvuE+hP59SX3GFQ+g9VMLBf/0IPsUVH44/r8w4hPsKwS0kXNwTX1YU/rTPSDy/B65I+0/XYrFYLJbGwu4hbIl89QWsWgkL54e8HOGKYEjcqIrzMDxklqfXcAYB8stz8TrJIx3CO7O3ZBflWlalT3CkcXC8Wab1OdFGRUkv2xdybq+/vMp59+g+DI4zwY9odwzRYZXiAL5SL/jNHP4Cc39frrOP3afkztxCwbw9FC1Lp3B5esjntlgsFovFcnTYMEtLJCYWcnOhXXKtXca2OZVwdziqyo6iLWSV16y2ECnRpJftrTg/VJ5F2GHqtiaFJdM2KPmjnSe1StQxJbwjoxInsqdkOyvzllCqJSS62+LHR4Evj9kH36dbdE8ASnzFeNWLCxeF3+0n7+tdVPiUtYlSeVy4ItxE9kys1UaLxWKxWCxHjnUIWxJbtsC8r8Dn7AXsWnvCnIgwItEs0XaJ6s7HB97Gh5e2nuSK5JMSDU5GFHxaXkWXuDrZ3gwKyivl7Ap9BVUigwfL9vHpwXeIdEUTSEjJ8WVVXC/w5ZFZmsHwhHGkRnQkwhVB8YZD5HwUKmkQcEnANBCh7dT+RPVvU6t9FovFYrFYjg7rELYUVOHrL03JmQCu+q/4+zDLwkW+whrX2oWlkulNx+v0CRBIDAlmbcHyiuNif825AEr8RSSFtSXbm1XjWnrZHkYmjaOzU6MwrG0kEu4GlMgBbdFSHyWbs4lIS6DN1X0p2ZBNZO8kXHEenOKyFovFYrFYGhnrELYEvF74Yk5VZ7BTJ+MgRsfAueeB2w3zvoa8XJh0BiQkVHQN3gM4InE88Z5E9hXvYkWekRjN9Nbckzc26TRSwjvwcfpbVaKABb78Gn0DhBNBmVO/NtubxbD4MazJX45Xy3HjxoePcIkgObx9xRhPcjQd7jX7HV3RNZVKYkak1vFyLBaLxWKxNBSbVNLc2bAeXnoBdjqls9zOHr+oaMjLgwP7IfsQ5OTA5k2mFM3WLVWm6BDZmQtSr+SC1CsZGH8SXaK6M6bNqfSNGRTyli7cDE0Yxf7S3RXOYIwrjh7RfYmSSpnUaFdMxfG4pElM7fJThsSPrCh6vSLve8LE/M3hw8fguJFc2+VnNWoOuqI9IZ1Bi8XSMhGRi0VkQN09j2jOghBtaSKyJkT7SBF50jmeJiL/co4fEpG7G9OuwyEiM5x6i4jIPBGxJYUszRYbIWzO7N4Fa9dUVeUI7B90u6FHDxMhTE4xfXr1NhHCnr1qTNUxqqaUqccVUeU8ydOW7PKsiuXcvrGDSC/dR4IniXFJkxARdhVtY/bB91GUIn8hse44escOpF14Kt9kfc7AuJNIjejI0uxFZHsz8aufGHcshb4CVucvJc4TX5GpbLFYGp9Zi9OnUq0w9SVjU49VYerauBj4BFhX3wEiEqaq3rp71o2qLgUaXAy3MW2yWJo71iFsrhw6BJ99WrXN44HefcBbDiNHQWxl2RZE4IzJR3SLkUkTyCnPosCbz8jE8XSL7kVG2YGKJd2YsLiK2oYBukb34JIO1/HJgbcp01KGJYxhQNwwXtr1T7xazs6iLRVL1Mnh7RmeOJYOEV14c8/zlGkpHgmvYYfFYmkcHGdwOhAI5XcDps9anM7ROoUikgb8F1gIjAf2AheparGI3Ar8FAgHtgDXAcOAC4FTHaWQy4AXgbtVdamItAOWqmqao398KRALuEXkPOBDIAmjTHK/qn5YTzt7ADMde2Kc+51/mP49gaeBZIy8362qukFEZgAlwEnAt8Bvgsa4gceBn2DqIUxX1adEZATwN+c5MoFpqrq/PnZbLM0F6xA2V/Jya7aVlxvt4tMnV3UGj5IIVwTntb+8SluHyM51jkuOSGVKpxvI9+bRMbILZf4yvGpqDgbvVyzzl5EW3RuAKZ1uoNBbQPvITg2222Kx1MqjVDqDAaKd9oZECXsDV6vqrSLyDsbJex14X1WnA4jII8DNjoP0EfCJqr7nXDvc3MOBIap6SETCgEtUNc9xHBeLyEdah6SWiPQF3sI4YitF5LR6PNPzwO2qullExmAk8U53rnUGxqtqdXmnnwJpwDBV9Tr6yB7gKYyTnCEiVwJ/Am6qhw0WS7PBOoTNlQ4djQpJcbUyMCUl8Pl/4cabK/cTNgFxYQnEhZnElXBXOGe0O58DpXtpG57M/Ky5gNIjpnfI/haL5ZhRc2/I4dvry3ZVXeEcL8M4RQCDHEcwERMd+/wo5p6rqoecYwEeFZFTMBG4TkAqcOAw45MxUcVLVbVeS9QiEouJdr4b5KwG76F5N4QzCDAZ+HdgGdlxYgcBg4C5zlxuwEYHLS0O6xA2VyIi4Ppp8N67kJVZ9Vp8/BGVnDke9IrtT6/Y/gD0iO5Lka+ApPB2TWyVxdLq2IVZJg7V3hBKg459QJRzPAO42InKTQNOq2W8l8okxshq14LrV12DcfBGqGq5iOwI0b86uZjnm0j99yy6gBxVHVbL9dA1tUIjwFpVHXcEYyyWZkfz8iosNbnkUrN3MBhPuNkz2EyJcEdaZ9BiaRruw+yHC6bIaT8WxAH7nWXTa4La851rAXYAgWyyKYeZLwE46DiDkwjt3FanDLgEuF5EptbHaFXNA7aLyOUAYhhaj6FzgducpW1EpA2wEUgWkXFOm0dEBtbHDoulOWEdwuaOiKlDGExiIhy0er4Wi6UqTuLIrcBOjBjkTuDWY5hl/ADwPSb5YkNQ+1vAPSLyo5O88RfgZyLyI3C4vxbfAEaKyGrg+mpz1oqqFgLnA78WkQvrafs1wM0ishJYC1xUjzEvYKKRq5xxU1W1DOPkPu60rcAsR1ssLQqpY6/uUTFy5EhdurTBGf+WADt3wldfQpmzauN2m/IzI0aabGOLxXJCICLLVNXWqrNYLMcdGyFsCXTrBpdfUXkeqEVYXH1lyGKxWCwWi+XIsQ5hS6H6PkKAoScdfzssFovFYrGccFiHsKUQEQETTq6aTDLz3UpJO4vFYrFYLJajxDqELYlBg2DS6ZVOYVkZbNty+DEWi8VisVgsdWAdwpZG7z5w623Qtq0537sXsrKa1iaLxWKxWCwtGusQtkREINKp1VpYCB+8D8cgW9xisVgsFkvrwDqELZUzJlcmmni98N2iprXHYrG0OkRknog06zI5InKaiNRZF1BEbheR60O0p4nImnqMnyEihyu6XW8O915F5AURGeAc31ft2jH7RSAiOxx9aUSk4Fjdx9J0WOm6lkpUtNlPOMeRDl29CpKTIa176Ixki8XSOvji91OBRzH6xbuA+5j8f8eqMHVL4DSgADiss6Sq/z4u1jQAEXGr6i1BTfdhPmsAVNUWxLYcNTZC2JLp3gPOPKsyyeSrL+HlFyEnp0nNslgsTYRxBqdjJN/E+T7daT8qnAjZBhF5Q0TWi8h7IhIdot+zIrJURNaKyMNB7Y+JyDoRWSUif3HaZjj9F4vINieK95Iz/4x6zDlKRBaJyEoR+UFE4kRkvogMC+qz0JGjux2jYLJCRE52nucrx54vRaSr0/8hEbnbOR7hzL0S+Hkt70VE5F8islFEvgBSgq6NEJFvRGSZiHwuIh2c9nki8rhj8yYROdlpjxKRt5znn0WlVjQiUiAif3VsGReIHorIY0CU81xvBPoGjfudiKx2nuOxEPanisiswHMGoqgicq1j3woReU5E3KGe33LiYR3Clk6PnnD9tMpzVZj1PpSUNJlJFoulyXgUqO6sRRMURTpK+gLPqGp/IA+4I0Sf/3FUVoYAp4rIEBFpi9EZHqiqQ4BHgvonAeOAXwMfAX8HBgKDgxy7UHOGA28Dv1TVocBkoBh4EZgGICJ9gEhVXQn8G/i7qg5T1QXAU8Arjj1vAE+GeJaXgV8489fGJc57GYCR2Qs4VB7nHlNUdQTwEvCnoHFhqjoa+BXwoNP2M6DIeb8PUqn7DBADfK+qQ1V1YaBRVe8Fip3nCtaRRkTOwUjxjXGe4c8h7H8S+Ma5PhxYKyL9gSuBCao6DPBRVaPacgJjHcITgchIGDio8rysFF57BQrtNg+LpZXR9Qjb68tuVf3WOX4dmBiizxUishz4EePYDQBygRLgRRG5FAiWV/pYjXbqaiBdVVerqh+jK5x2mDn7AvtVdQmAquapqhd4FzjfcchuAmbU8izjgMAS+mvVn0VEEoFEVZ0f1CcUpwD/UVWfqu4DvnLa+wKDgLkisgK4H+gcNO595/uyoOc8BfNeUdVVwKqg/j5gZi021MZk4GVVLXLmPBSiz+nAs851n6rmAmdgnNElju1nAD2O8N6WFordQ3iiMPFk6NIVvvkaiovB74dD2RAT29SWWSyW48cuzDJxqPaGUL2MQZVzEekO3A2MUtVsZ9k3UlW9IjIa41hMAe7EOCIAjjg7/qDjwHlYbXPWaqBqkYjMxUTGrqBqlO14IsBaVR1Xy/XAs/qo3+/gElX1NYpldSOY6Onvj9P9LM0IGyFsxuzZsJZF775JUV5u/QZ06wZTroDOXWDQYOjcue4xFovlROI+qkbhcM7vC9H3SOgqIgEHZyqwsNr1eKAQyBWRVOAcABGJBRJU9TPM0vDhlmCrE3JOYCPQQURGOfeIE5GAY/UCZil0iapmO235QFzQvIuAq5zja4AFwTdV1RwgR0QmBvUJxXzgShFxO3sEJwXZlxx4XyLiEZGBdTzrfMx7RUQGYZbI60O5ExGtzlzgRnH2eopImxB9vsQsVeM8Q4LTNkVEUgLjRCTUHxiWExDrEDZTVJVZjz3Ed++9yfw3Xq7/wOhoOO98mDCxMtlEFb5fDF/ONdFDi8VyYmKyiW8FdmKieDuBWxshy3gj8HMRWY/Z+/ds8EVnr96PwAbMcmxgeTkO+EREVmGcyN/U94a1zamqZZh9bk85iRZzcSKHqroMs8cx+Ifmx8AlgaQS4BcYZ2kVcB3wyxC3vxF42lk2lRDXAWYBm4F1wKvAd0H2TQEed+xbgbO/8DA8C8Q67/cPmOXk+vA8sCqQVBJAVWdj9mUudZ7h7hBjfwlMEpHVzv0GqOo6zBL3HOf9zAU61NMWSwtH9BgUNB45cqQuXbq00edtbbxx3685sHUzp1x7E6MuuPToJ8rKhPfeNccul3EazzgT2rdvHEMtFkujICLLnCSKZoOIpAGfqOqguvo2NSLSEZgH9HP2I1oslnpiI4TNlH2bNpBzMJ0Ovfoy/JwLGjZZfAKkpppjvx8KCuCTjyD9QMMNtVgslmaAmKLS32Myk60zaLEcIdYhbKZsX7GMkvw89m/ZSH5DtYo9Hrj40qrLyD4ffPwRvPYq5OfVf67ycjhwwDiWFovlhEdVd7SE6KCqvqqqXVT13aa2xWJpidgs42bK0DPPIXvfHtp26UpiaiMt7Q4aDAMGwoJvYNs2KCuDokI4eBDi4us3x38/hf37YcAAOPnUxrHLYrFYLBZLk2IdwmZKTGIS5911D+Jq5CCuywWnTjLO3PeLTaQvrXvl9QP74fPZEB8PKe3N/sPhIyAhHgoLK5NSbHKKxWKxWCwnDNYhbIZk7dnFq7+7C/X7ufyBP9FlwODGv4nLBeNCJL7t2mVUTkpKTOQQ4NN9ZqlZFUaPAU849OzZ+DZZLBaLxWJpEuwewmbI5iXf4fd6Ub+fjYsW1D2gMRk4yEQMpVqlhUA2elgYDBoEUVE1x1osFovFYmmRWIewGTLi3ItJ7taDpI6dmXDltcf35jExcPZP4MKLzHEww4aZfYgWi8VyBIjI5SKyXkS+bqT5/iAikxtjrqA5TxORTxpprl8FikI75585kngnNCKSKCJ3BJ13FJH3msiWeSIy0jneISLtmsKOloRdMm6GlBUXceWDj+IKC8MTUatS07GlfQe49nrYuAHycqFvf7Ov0GKxNGue2/HEVOBRjH7xLuC+29LuaWhh6joREfdhJNZuBm5V1eoKJ0eFqv5vY8xzDPkVRps4oCV8bpNa41DHZ9QYJAJ3AM8AOBrPU47h/SyNiI0QNjMWvv0a/77tOp6+ZSrP//wm8jIzmtagvv1g1BjrDFosLQDHGZyO0TMW5/t0p/2oEJE0EdkgIm84Ub73giTRdojI4yKyHLhcRK4WkdUiskZEHnf6/C8wEXhRRJ5wZNKeEJElIrJKRG5z+nUQkfmOosgaETnZ6TvDOV8tIr92+s4QkSnO8Rki8qNz/SURiQiy7WERWe5c6+e0jxaR75wxi0Skbz2ef4Ezz3IRGe+0n+ZEod4Lej8iIncBHYGvAxHR4AiViDwgIhtFZKGI/EdE7nbae4rIbBFZ5twvYO8MEXnSsXVb4Lkb8Bmd5Tz/chF5V4y8ICLymIiscz6TvzhtySIy0/mslojIBKf9Ieddz3Nsussx5TGgp/MZPuHYtcYZM01E3neecbOI/DnI/ptFZJOI/CAi00XkXyGeMVZEXnY+y1UicpnTHvJ5LEeOdQibGcs++QAA9fspyc8j58D+pjXIYrG0JB4Foqu1RTvtDaEv8Iyq9sdIw90RdC1LVYdj9HgfB04HhgGjRORiVf0DsBS4RlXvwUQLc1V1FDAKuFVEumO0fD9X1WEYzeMVzjydVHWQqg6mqiQdIhIJzACudK6H4ejzOmQ6tj1LpXzbBuBkVT0J+F/qfjcHgTOdea7EaCUHOAkTDRwA9AAmqOqTwD5gkqpOCp5IjP7yZc7znQMEq9I8D/xCVUc4tj4TdK0Dxqk+H+N0haI+n9EXGGm6yc75UuA3ItIWuAQYqKpDgEeccf8E/u58VpdhtKID9APOBkYDD4rRVL4X2Kqqw5zPujrDMO9wMEYHuosYdZkHgLHABGfeUDyA+Xcz2LHxK8fJrvE8tYy31IFdMm5meMtKK44HTTqLroPqq3FusVgsdD3C9vqyW1UD+sSvA3cBf3HO33a+jwLmqWoGgBh93VOAD6rNdRYwJCjSlQD0BpYALzmOxQequkJEtgE9ROQp4FNgTrW5+gLbVXWTc/4K8HPgH875+873ZUBA/zMBeEVEemP0nj11PLsH+JeIDAN8QJ+gaz+o6h7neVcAaRjN5tqYAHyoqiVAiYh87IyNxegdvyuVCX0RQeM+cNRX1olIai1z1+czGotxXr917hOO0WDOBUowUdxPgMBeysnAgCCb4oMicJ+qailQKiIHgdrsCuZLVc11nnkdJoLdDvhGVQ857e9S9R0HmAxcFThR1WwROb+W57EcBdYhbEZU15XO3r+niSyxWCwtlF2YX7Kh2htCddH74PPCI5xLMJGwz2tcEDkFOA+YISJ/U9VXRWQoJhJ1O3AFcNMR3CvwF7aPyt93fwS+VtVLxOg0z6tjjl8D6ZiongvjOFWfv/o9jhQXkONER0MRfB+ppU99PiMB5qrq1dUHi8ho4AzMnr87MZFeFzDWcWCD+1a3qb7P3ljvq8IUankey5Fjl4ybESJCas/eFedZu3c3oTVHT9mePWw973w2TZjI+oGDOPDY46Q/8QSFixejZWXkf/EF5enpeA8dQr3einGlmzeTM/N9SjZuRMvKmvAJLJYWy304iQxBFDntDaGriIxzjqcSOgr2A3CqiLQTETdwNfBNiH6fAz9zIoGISB8RiRGRbkC6qk7HLE0Od5YEXao6E7M0OLzaXBuBNBHp5ZxfV8s9g0kA9jrH0+roG+i/34nQXQe46zEmH4gL0f4tcIGIRDqRtvMBVDUP2C4ilwM4exGH1uM+wdTnM1oMTAi8L+e993FsSVDVzzAOcODec4BfBAY7UdLDUdtzH44lmH83SSIShlmaDsVcTPQ3YEtSbc9zhPe3ONgIYTPC5/WSm165Z7Bj39q2UjRv9j/0EGVbt1acZ7/2Gvh8HHrxJaOrXF6OREWhxcVEDByAOy4eX3Y2pZs2VdY79HiIHj6c8J49aH/vvUh4eBM9jcXScrgt7Z43n9vxBDR+lvFG4Oci8hKwDrMnrwqqul9E7gW+xkRuPlXVD0PM9QJmaXW5mFBTBnAxcBpwj4iUAwXA9UAn4GURCQQvfl/tniUiciNmqTUM41z8u45n+TNmyfh+zDJ0XTwDzBSR64HZ1C8i+jwwW0T2Be8jVNUlIvIRsAoTdVyNWa4FuAZ41rHLA7wFrKzHvQLU5zPKEJFpwH/ESb7BONr5wIfOnkyhch/eXcDTIrIK4y/Mx0RqQ6KqWSLyrZNI8l/g6bqMVtW9IvIo5g+KQ5g9nrkhuj7i2LIGE118WFXfr+V5NoUYb6kDqb5M2RiMHDlSly5d2ujznuhsWryQj/9u9guHR0Uz7S9PE9cuuYmtOnLSH3+cQy/PqF9ntxt8h6+CIBERpD7wAElTavvD0WI5MRCRZao6su6exw9nWfUTVR3U1LacCIhIrKoWiMkCng/8VFWXN3DONFrwZxT0TsKAWcBLqjqrqe1qbdgl42ZEcloPIqJNgmBZcRGrv57bxBYdHW2m3Wik8arjbEx2p5q9x+62ben0xJ+JHjXqsPNpaSkHHniAjCefPGw/i8ViaQE87ySgLAdmNtQZPEF4yHkna4Dt1ExEshwH7JJxM6LgUBblpWW4wsKIio2l54jRTW3SUeFJTaH757PZccGFaEkJ7e76BW1vvhlXRATe/ALcsTGUrF1HeFoa7tgY4s89l9ItWyhau5bc92bi6diR0i2bKV27rnJSVTKfeZbEK6/Ck5rSdA9nsbQyVHUH0CIjT80RVT3qmpCHmXMHLfgzUtW76+5lOdZYh7AZsXfjOvw+k2TRddAwUnv0qmNE8yWySxf6rfgRLS9HPJVVHcLiTMWCqEEDq/SP6NWLiF69SLroooq2oiVLKMvMomTVSvI+/ZTooUMJa9f2+DyAxWKxWCytCLuHsBlxcMd2XvudSehyh3n41Rt2C4XF0ppojnsILRZL68DuIWxGpG/fUnHs9tRVK9VisVgsFoulcbAOYTNiznOVSRNlxUXsWruqCa2xWCwWi8XSWrAOYXOi2vL9d++91USGWCwWi0FEEkXkjrp7Nvg+80RkpHO8wylKfUIjIr9yys9YLE2OdQibkIVvvcY/r7+MpZ+YvYKeyKgq1/esW8WGRXUV3bdYLJYgnnt2Ks89u4PnnvU73xua1ZoIHHOHsJXyK8A6hJZmgXUImwhvWRlr5s3FW1rKpsVGYSghtX2NfnOee+p4m2axWFoqxvmbjtEzFuf79AY6hY8BPUVkhYg8ISKvisjFgYsi8oaIXCQi00TkQyfSt1lEHgzqc62I/ODM8ZwjbXfEiEiBiPxdRNaKyJcikuy0zxORx517bBKRk512t2PzEhFZJSK3Oe2nicgnQfP+y1G8CEQn/8+xdamIDBeRz0Vkq4jc7vQRZ941IrJaRK4Mmut3TttKEXlMRHqKyPKg671FZLmI3AV0BL4Wka+da2eJyHfO9XcdSTmL5bhgHcImYu70f1GYfYiImBhOnjqNvRvXkblze8V1t8dItbXv1bepTLRYLC2PR6kZcYp22o+We4GtqjpMVe8BXsTRABaRBGA8lRJwozFatEOAy0VkpIj0B64EJqjqMIzs2DVHaUsMsFRVB2I0ix8MuhamqqMxUbdA+81ArqqOAkYBt4pI93rcZ5dj6wJgBjAFGAs87Fy/FBiG0fydDDwhIh1E5BzgImCMqg4F/qyqW4HcIB3gG4GXVfVJYB8wSVUnOUvk9wOTVXU4sJRKCTmL5Zhj6xA2AbvXrmLjdyYqGJ2QRJcBg1ny8ftV+gw4eRJjL7uK2KQ2TWGixWJpmXQ9wvYjRlW/EZFnnOjcZRi1Da+RJWauqmYBiMj7wETAC4wAljh9ooCDR3l7P/C2c/w6EPyDM3C8DKOVDHAWMEREpjjnCUBvoKyO+3zkfF8NxKpqPpAvIqUikoh5rv+oqg9IF5FvMA7nqRhnrwhAVQ8587wA3Cgiv8E4x6FUB8YCA4BvnfcUDnxXh50WS6NhHcImYPMP3+ErNz+Psvft4dt3XicqPqlKn+4njSC+BeoYWyyWJmUXZpk4VHtj8ipwLXAVJuIVoHphW8UsXb+iqr9vZBuq36/U+e6j8nebAL9Q1c+DB4nIRKqukEVWmzcwlz/oOHB+NL83Z2Kill8BywJOczUE41BffRTzWywNxi4ZNwEnnXMBnfpXKnUsnvkWC954seI8Ki6OL154hhfuuoWi3JwmsNBisbRQ7gOKqrUVOe1HSz4QV61tBmZpFlUN0pjkTBFpIyJRwMXAt8CXwBQRSQFwrodyWuuDC7N8CzAVWFhH/8+Bn4mIx7l3HxGJAXYCA0Qkwon4nXGEdiwArnT2KCYDpwA/AHMxkcBo535tAFS1xLHlWeDloHmC3+1iYIKI9HLGxohInyO0y2I5aqxD2AQkte/I5JurJu35vF4mTfspbTp1QVxuinJzyE0/QMbOHU1jpMViaXnc9rM3gVsxDo8632912o8KJ5r1rZNA8YTTlg6sp6pzA8YpmgmswiwlL3UcxvuBOSKyCuM0dThKcwqB0SKyBjgd+EMd/V8A1gHLnTHPYfYa7gbeAdY43388QjtmYZ5xJSbq9/9U9YCqzsYsNy8VkRVAsEbvG5gI45ygtueB2SLytapmYPZm/sd5T98B/Y7QLovlqLHSdU3I6q/msOSjmWTv3wvAXa+8x9sP30v6ti2ER0czYOIkTr/xNsRl/XaLpTXQUqTrnAjYamC4quY6bdOAkap65zG8b4GqtsjMWxG5G0hQ1Qea2haLJRTW02hCBp9+FhHRlQmBBdlZnPSTC0hs3wF3mIcVcz9j43cLmtBCi8ViqYqITMZEB58KOIOWwyMis4DrgX82tS0WS23YpJImJlBeBmDGb+6g+0kjadOpK9uW/wCqZO7e2YTWWSwWS1VU9QtCJK6o6gzM3sJjee8WGR1U1Uua2gaLpS5shLCJufTehxg06SzcYWH4/T62Lvuebcu+B1WSu/Vg1IVT6p7EYrFYLBaLpQFYh7CJCY+K4uzb70LcoQv3By8pWywWi8VisRwLrEPYTLjo7v8hMja+4rzbkOGcfftdTWiRxWKxWCyW1oLdQ9hMSBsynJ+/+Ca5B9MpKykmuWtaU5tksVgsFoullWAdwmZGQkpqU5tgsVgsFoullWGXjC0Wi8VisVhaOdYhtFgsFovFYmnlWIfQYrFYLBaLpZVjHUKLxWKxWCyWVo51CC0Wi8VisVhaOdYhtFgsFovFYmnlWIfQYrFYLBaLpZUjqtr4k4pkADsbfWKLxWI5semmqslNbYTFYml9HBOH0GKxWCwWi8XScrBLxhaLxWKxWCytHOsQWiwWi8VisbRyrENosVgsFovF0sqxDqGlRSEiaSKyplrbQyJyt4jMEJEiEYkLuvYPEVERaRfUdrHT1q/avMUiskJE1onIv0XE5VybLSI5IvLJ8XhGi8VisViON9YhtJxobAEuAnAcutOBvdX6XA0sdL4Hs1VVhwFDgAHAxU77E8B1x8Zci8VisViaHusQWk403gKudI5PA74FvIGLIhILTARuBq4KNYGqeoFFQC/n/Esg/5hZbLFYLBZLE2MdQsuJxiYgWUSSMBHAt6pdvwiYraqbgCwRGVF9AhGJBs4AVh9rYy0Wi8ViaQ5Yh9DS0qitcGZw+/uY6N8YYEG1fsFO4ltUXTbuKSIrMFHFT1X1vw221mKxWCyWFkBYUxtgsRwhWUBStbY2wPag87eBZcArquoXEQBEpA1mT+FgEVHADaiI3OOMC+whtFgsFoulVWEjhJYWhaoWAPtF5HSocPJ+gkkSCfTZCfwP8Ey14VOA11S1m6qmqWoXjCN58nEx3mKxWCyWZop1CC0tkeuBB5zl3a+Ah1V1a3AHVX2uehtmeXhWtbaZ1Mw2roKILADeBc4QkT0icnZDjLdYLBaLpblhtYwtFovFYrFYWjk2QmixWCwWi8XSyrEOocVisVgsFksrxzqEFovFYrFYLK0c6xBaLBaLxWKxtHKsQ2ixWCwWi8XSyrEOocVisVgsFksrxzqEFovFYrFYLK2c/w9XZyz9pv5RJAAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = sc.pl.umap(adata, color='Most specific cell type', return_fig=True)" ] }, { "cell_type": "markdown", "id": "excellent-recorder", "metadata": {}, "source": [ "#### Save the figure to a file" ] }, { "cell_type": "code", "execution_count": 17, "id": "transsexual-sarah", "metadata": {}, "outputs": [], "source": [ "out_file = 'specific_cell_types.pdf' # <-- Name of the output file\n", "\n", "fig.savefig(out_file, bbox_inches='tight', format='pdf')" ] }, { "cell_type": "markdown", "id": "brilliant-magazine", "metadata": {}, "source": [ "### Step 11: Create UMAP plot with cells colored according their probability of being T cells\n", "\n", "Key parameters:\n", "\n", "`color`: The variable for which to color each point. To color points by the probability that they are a given cell type (e.g., 'T cell'), we provide a string with the name of the cell type, such as 'T cell', followed by the string, '(probability)'. \n", "`vmin`: The lower limit of the colorbar. We set this to 0.0 because 0.0 is the lowest possible value for a probability. \n", "`vmax`: The upper limit of the colorbar. We set this to 1.0 because 1.0 is the highest possible value for a probability." ] }, { "cell_type": "code", "execution_count": 18, "id": "relevant-andrews", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = sc.pl.umap(adata, color='T cell (probability)', vmin=0.0, vmax=1.0, return_fig=True)" ] }, { "cell_type": "markdown", "id": "forbidden-honduras", "metadata": {}, "source": [ "#### Save the figure to a file" ] }, { "cell_type": "code", "execution_count": 19, "id": "humanitarian-visiting", "metadata": {}, "outputs": [], "source": [ "out_file = 'T_cell_probability.pdf' # <-- Name of the output file\n", "\n", "fig.savefig(out_file, bbox_inches='tight', format='pdf')" ] }, { "cell_type": "markdown", "id": "decreased-shareware", "metadata": {}, "source": [ "### Step 12: Create UMAP plot with cells colored according whether they are classified as being T cells\n", "\n", "Key parameters:\n", "\n", "`color`: The variable for which to color each point. To color points by an indicator of whether each point was classified as a given cell type (e.g., 'T cell'), we provide a string with the name of the cell type, such as 'T cell', followed by the string, '(binary)'." ] }, { "cell_type": "code", "execution_count": 20, "id": "discrete-stage", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = sc.pl.umap(adata, color='T cell (binary)', return_fig=True)" ] }, { "cell_type": "markdown", "id": "accompanied-garden", "metadata": {}, "source": [ "#### Save the figure to a file" ] }, { "cell_type": "code", "execution_count": 21, "id": "reflected-stress", "metadata": {}, "outputs": [], "source": [ "out_file = 'T_cell_binary.pdf' # <-- Name of the output file\n", "\n", "fig.savefig(out_file, bbox_inches='tight', format='pdf')" ] }, { "cell_type": "markdown", "id": "stable-statistics", "metadata": {}, "source": [ "### Step 13: Visualize cell type probabilities assigned to a specific cluster overlaid on the Cell Ontology graph" ] }, { "cell_type": "code", "execution_count": 22, "id": "oriented-ballet", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = cello.cello_probs(adata, '21', cello_resource_loc, 0.5, clust_key='leiden');" ] }, { "cell_type": "markdown", "id": "happy-treat", "metadata": {}, "source": [ "#### Save the figure to a file" ] }, { "cell_type": "code", "execution_count": 23, "id": "thermal-timber", "metadata": {}, "outputs": [], "source": [ "out_file = 'probs_on_graph.png' # <--- Name of the output file\n", "\n", "fig.savefig(out_file, format='png', dpi=300)" ] }, { "cell_type": "markdown", "id": "burning-communist", "metadata": {}, "source": [ "### Step 14: Write CellO's output to a TSV file" ] }, { "cell_type": "code", "execution_count": 24, "id": "afraid-above", "metadata": {}, "outputs": [], "source": [ "cello.write_to_tsv(adata, 'GSM3516673_MSK_LX682_NORMAL.CellO_output.tsv')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 5 }