{ "cells": [ { "cell_type": "markdown", "id": "e872038e", "metadata": {}, "source": [ "# Pre-processing (Re-annotation)\n", "\n", "## Foreword\n", "\n", "`dandelion` is written in `Python 3` and is a single-cell BCR/TCR V(D)J-seq analysis package. For the pre-processing section, it integrates a standard pipeline for V(D)J gene reannotation with `IgBLAST`, similar to the fantastic [immcantation suite](https://immcantation.readthedocs.io/) [[Gupta2015]](https://academic.oup.com/bioinformatics/article/31/20/3356/195677). This work streamlines the pre-processing and exploratory stages for analyzing single-cell BCR/TCR V(D)J-seq data from 10X Genomics (and other technologies as long as they can be formatted or read into `dandelion` accordingly). Post-processed data from `dandelion` can be smoothly transferred to [scirpy](https://scirpy.scverse.org/)[Sturm2020](https://academic.oup.com/bioinformatics/article/36/18/4817/5866543) and [Scanpy](https://scanpy.readthedocs.io/)/[AnnData](https://anndata.readthedocs.io/) [[Wolf2018]](https://doi.org/10.1186/s13059-017-1382-0) object for integration and exploration of scV(D)J-seq data and scRNA-seq data. \n", "\n", "For some of the more advanced scV(D)J-seq analysis, specifically V(D)J trajectory analysis, there's also an `R` package `dandelionR` [Yu2024](https://doi.org/10.1016/j.csbj.2025.06.047) available on [GitHub](https://github.com/tuonglab/dandelionR) and [BioConductor](https://bioconductor.org/packages/release/bioc/html/dandelionR.html). If you are an `R` user and you want to perform pre-processing and re-annotation of your single-cell V(D)J-seq data, please refer to the `immcantation` suite and its documentation. Alternatively, there is a [singularity container](https://sc-dandelion.readthedocs.io/en/latest/notebooks/Q1-singularity-preprocessing.html) that can automate the steps outlined below.\n", "\n", "
\n", "\n", "Note\n", " \n", "This section will cover the initial pre-processing of files after 10X's `CellRanger vdj` immune profiling data analysis (BCR) pipeline manually.\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "id": "0a34653c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dandelion==1.0.0a1.dev36 pandas==2.3.3 numpy==2.3.5 matplotlib==3.10.6 networkx==3.6.1 scipy==1.15.2\n" ] } ], "source": [ "# Import modules\n", "import dandelion as ddl\n", "\n", "ddl.logging.print_versions()" ] }, { "cell_type": "markdown", "id": "b161e253", "metadata": {}, "source": [ "We will download the 10X data sets to process for this tutorial. The following function will download the tutorial files and place them in a folder called `dandelion_tutorial` in your current working directory.\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "0171992c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading filtered_feature_bc_matrix.h5 → dandelion_tutorial/vdj_v1_hs_pbmc3_b/filtered_feature_bc_matrix.h5\n", "Downloading filtered_contig_annotations.csv → dandelion_tutorial/vdj_v1_hs_pbmc3_b/filtered_contig_annotations.csv\n", "Downloading filtered_contig.fasta → dandelion_tutorial/vdj_v1_hs_pbmc3_b/filtered_contig.fasta\n", "Downloading filtered_feature_bc_matrix.h5 → dandelion_tutorial/vdj_nextgem_hs_pbmc3_b/filtered_feature_bc_matrix.h5\n", "Downloading filtered_contig_annotations.csv → dandelion_tutorial/vdj_nextgem_hs_pbmc3_b/filtered_contig_annotations.csv\n", "Downloading filtered_contig.fasta → dandelion_tutorial/vdj_nextgem_hs_pbmc3_b/filtered_contig.fasta\n", "Downloading filtered_feature_bc_matrix.h5 → dandelion_tutorial/sc5p_v2_hs_PBMC_10k_b/filtered_feature_bc_matrix.h5\n", "Downloading filtered_contig_annotations.csv → dandelion_tutorial/sc5p_v2_hs_PBMC_10k_b/filtered_contig_annotations.csv\n", "Downloading filtered_contig.fasta → dandelion_tutorial/sc5p_v2_hs_PBMC_10k_b/filtered_contig.fasta\n", "Downloading airr_rearrangement.tsv → dandelion_tutorial/sc5p_v2_hs_PBMC_10k_b/airr_rearrangement.tsv\n", "Downloading filtered_feature_bc_matrix.h5 → dandelion_tutorial/sc5p_v2_hs_PBMC_1k_b/filtered_feature_bc_matrix.h5\n", "Downloading filtered_contig_annotations.csv → dandelion_tutorial/sc5p_v2_hs_PBMC_1k_b/filtered_contig_annotations.csv\n", "Downloading filtered_contig.fasta → dandelion_tutorial/sc5p_v2_hs_PBMC_1k_b/filtered_contig.fasta\n", "/Users/uqztuong/Documents/GitHub/dandelion/docs/notebooks/polars/dandelion_tutorial\n" ] } ], "source": [ "# new function to setup tutorial data\n", "from dandelion.tutorial import setup_dandelion_tutorial_bcr\n", "\n", "setup_dandelion_tutorial_bcr()\n", "\n", "# change to the tutorial data directory\n", "import os\n", "\n", "os.chdir(\"dandelion_tutorial\")\n", "print(os.getcwd())" ] }, { "cell_type": "markdown", "id": "180c606e", "metadata": {}, "source": [ "`Dandelion`'s reannotation workflow requires `CellRanger` formatted-files to start, particularly either `all_contig.fasta` or `filtered_contig.fasta` and corresponding `all_contig_annotations.csv` and `filtered_contig_annotations.csv`. If you only have an `AIRR` rearrangement file, you can still load it into `dandelion` and write the files out with `.write_10x` function later.\n", "\n", "I'm running everything with the `filtered` files to speed up the tutorial but I would recommend starting with the `all` files as they contain more information, and it is easier to filter the contigs than to try and add them back in later.\n", "\n", "If you followed the installation instructions, you should have the requisite auxillary softwares installed already. Otherwise, you can download them manually: [blast+](https://ftp.ncbi.nih.gov/blast/executables/igblast/release/LATEST/) and [igblast](https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/).\n", "\n", "For convenience, in `shell`, export the path to the database folders like as follows:\n", "\n", "```bash\n", "# ~/.bash_profile or ~/.bashrc if using bash or ~/.zshrc if you are using zsh\n", "echo \"export GERMLINE=./dandelion/container/database/germlines/\" >> ~/.bash_profile\n", "echo \"export IGDATA=./dandelion/container/database/igblast/\" >> ~/.bash_profile\n", "echo \"export BLASTDB=./dandelion/container/database/blast/\" >> ~/.bash_profile\n", "source ~/.bash_profile\n", "```\n", "\n", "The databases for igblast are basically setup using [changeo's instructions](https://changeo.readthedocs.io/en/stable/examples/igblast.html). \n", "\n", "If you are using a jupyter notebook initialized via jupyterhub instance, you might want to try the fix to a known issue where pathing requires some adjustments https://github.com/zktuong/dandelion/discussions/146.\n", "\n", "For reannotation of constant genes, reference fasta files were downloaded from IMGT and only sequences corresponding to *CH1* region for each constant gene/allele were retained. The headers were trimmed to only keep the gene and allele information. Links to find the sequences can be found here : [human](http://www.imgt.org/genedb/GENElect?query=7.2+IGHC&species=Homo+sapiens) and [mouse](http://www.imgt.org/genedb/GENElect?query=7.2+IGHC&species=Mus).\n", "\n", "The utility function `ddl.utl.makeblastdb` is a wrapper for:\n", "\n", "```bash\n", "# bash/shell\n", "makeblastdb -dbtype nucl -parse_seqids -in $BLASTDB/human/human_BCR_C.fasta\n", "```\n", "\n", "This does the same thing:\n", "```python\n", "# python\n", "ddl.utl.makeblastdb(os.path.expanduser(\"~/Documents/Github/dandelion/container/database/blast/human/human_BCR_C.fasta\")\n", "```\n", "\n", "This section will now demonstrate how I batch process multiple samples/files from the same donor, as it will become important later on.\n", "\n", "Finally, because you are running the preprocessing manually, you will need to install some R packages so that they work later:\n", "\n", "```R\n", "install.packages(c(\"optparse\", \"airr\", \"shazam\", \"alakazam\", \"tigger\"))\n", "```" ] }, { "cell_type": "markdown", "id": "c5bffc3c", "metadata": {}, "source": [ "## Step 1: Formatting the headers of the Cell Ranger fasta file\n", "Here, I'm adding a prefix to the headers of each contig in the fasta files, via the function `pp.format_fastas`. The prefix is basically just the folder name, so in this case it's:\n", "`sc5p_v2_hs_PBMC_1k`, `sc5p_v2_hs_PBMC_10k`, `vdj_v1_hs_pbmc3` and `vdj_nextgem_hs_pbmc3`.\n", "\n", "The function will also create sub-folders where a new fasta file and all subsequent files will be located. The function will also add the prefix to the corresponding annotation file automatically and create a copy in the same folder as the formatted fasta file. \n", "\n", "This is to ensure that the barcodes are consistent throughout so as not to interfere with subsequent integration with the gene expression data, which will be covered in subsequent sections. \n", "\n", "The file structure should look something like this later on if the settings are left as default. The tmp directory can be deleted once the initial preprocessing has completed.\n", "```\n", "sc5p_v2_hs_PBMC_1k\n", "├── dandelion\n", "│   ├── filtered_contig.fasta\n", "│   ├── filtered_contig_annotations.csv\n", "│   ├── filtered_contig_igblast_db-pass_genotyped.tsv\n", "│   └── tmp\n", "│   ├── filtered_contig_igblast.fmt7\n", "│   ├── filtered_contig_igblast.tsv\n", "│   ├── filtered_contig_igblast_db-pass.blastsummary.txt\n", "│   ├── filtered_contig_igblast_db-pass.tsv\n", "│   ├── filtered_contig_igblast_db-pass.xml\n", "│   ├── filtered_contig_igblast_db-pass_genotyped.tsv\n", "│   ├── filtered_contig_igblast_db-pass_heavy_parse-select.tsv\n", "│   └── filtered_contig_igblast_db-pass_light_parse-select.tsv\n", "├── filtered_contig.fasta\n", "├── filtered_contig_annotations.csv\n", "└── filtered_feature_bc_matrix.h5\n", "```\n", "\n", "The first option of `pp.format_fastas` accepts a list of the fasta file paths to reformat, or list of names of folders containing the fasta files; each folder should only contain 1 fasta file, and 1 contig_annotation.csv. Make sure there's no hidden files and delete those if present.\n", "\n", "You can provide `prefixes` and/or `suffixes` to add the the cell/contig barcodes as a list and they will be formatted accordingly. The prefixes/suffixes will be separated by an underscore (`_`) if left as default but that can be adjusted with the `sep` option. \n", "\n", "If you choose not to provide a prefix/suffix, then the function will simply make a copy of the original files and place it in the `dandelion` sub-folders.\n", "\n", "For more complex experimental setups, such as with data from multiplexed experiments, please contact me (z.tuong@uq.edu.au) and I can walk you through a slightly more advanced set up." ] }, { "cell_type": "code", "execution_count": 3, "id": "6a6c9dbb", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Formatting fasta(s) : 0%| | 0/4 [00:00` for any files that are named `_contig.fasta`. \n", "\n", "If you are running more than 1 sample and if each filename prefix needs to be specified, `filename_prefix` in `ddl.pp.format_fastas` will accept a list of prefixes i.e. `filename_prefix=['all', 'filtered', ...]`.\n" ] }, { "cell_type": "markdown", "id": "1cf28d7e", "metadata": {}, "source": [ "## Step 2: Reannotate the V/D/J genes with *igblastn*\n", "\n", "Like immcantation, we will reannotate the V(D)J genes with igblastn using the latest IMGT reference databases. Dandelion's `pp.reannotate_genes` will use `flavour=\"strict\"` to run `igblastn`, imposing lower e-value and higher D-penalty cut offs. The original behaviour i.e. with [changeo](https://changeo.readthedocs.io/en/stable/examples/10x.html)'s `AssignGenes.py`, is toggled with `flavour=\"original\"`. Additionally, there is now an additional `assign_dj` option (default is `True`), which will use blastn to assign a stricter call for the D and J genes because [igblastn can return random assignments if it cannot detect a V gene](https://www.ncbi.nlm.nih.gov/igblast/faq.html). In the `tmp` folder, there will also be a table where all alignments generated in this step will be shown. All the column headers are now adhering to the [AIRR](http://docs.airr-community.org/) standard." ] }, { "cell_type": "code", "execution_count": 4, "id": "d54d87ef", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Assigning genes : 0%| | 0/4 [00:00 MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:54:23 |Done | 0.0 min\n", "\n", "PROGRESS> 14:54:24 |####################| 100% (202) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 185\n", " FAIL> 17\n", " END> MakeDb\n", "\n", " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:54:24 |Done | 0.0 min\n", "\n", "PROGRESS> 14:54:25 |####################| 100% (202) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 185\n", " FAIL> 17\n", " END> MakeDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Assigning genes : 25%|██▌ | 1/4 [00:13<00:41, 13.76s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:55:35 |Done | 0.0 min\n", "\n", "PROGRESS> 14:55:36 |####################| 100% (2,601) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 2409\n", " FAIL> 192\n", " END> MakeDb\n", "\n", " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:55:37 |Done | 0.0 min\n", "\n", "PROGRESS> 14:55:38 |####################| 100% (2,601) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 2409\n", " FAIL> 192\n", " END> MakeDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Assigning genes : 50%|█████ | 2/4 [01:28<01:39, 49.80s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:56:36 |Done | 0.0 min\n", "\n", "PROGRESS> 14:56:38 |####################| 100% (2,059) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 1841\n", " FAIL> 218\n", " END> MakeDb\n", "\n", " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:56:38 |Done | 0.0 min\n", "\n", "PROGRESS> 14:56:40 |####################| 100% (2,059) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 1841\n", " FAIL> 218\n", " END> MakeDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Assigning genes : 75%|███████▌ | 3/4 [02:29<00:54, 54.64s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:58:08 |Done | 0.0 min\n", "\n", "PROGRESS> 14:58:10 |####################| 100% (3,222) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 2976\n", " FAIL> 246\n", " END> MakeDb\n", "\n", " START> MakeDB\n", " COMMAND> igblast\n", " ALIGNER_FILE> filtered_contig_igblast.fmt7\n", " SEQ_FILE> filtered_contig.fasta\n", " NPROC> 8\n", " ASIS_ID> False\n", " ASIS_CALLS> False\n", " VALIDATE> strict\n", " EXTENDED> True\n", "INFER_JUNCTION> False\n", "\n", "PROGRESS> 14:58:11 |Done | 0.0 min\n", "\n", "PROGRESS> 14:58:13 |####################| 100% (3,222) 0.0 min\n", "\n", "OUTPUT> filtered_contig_igblast_db-pass.tsv\n", " PASS> 2976\n", " FAIL> 246\n", " END> MakeDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Assigning genes : 100%|██████████| 4/4 [04:04<00:00, 61.22s/it]\n" ] } ], "source": [ "ddl.pp.reannotate_genes(samples, filename_prefix=\"filtered\")" ] }, { "cell_type": "markdown", "id": "4e0b82a7", "metadata": {}, "source": [ "
\n", "\n", "Note\n", "\n", "If you did not set a path to the igblast or germline paths in the environment above, you need to specify the path to the folders containing the fasta files directly.\n", "\n", "```python\n", "ddl.pp.reannotate_genes(samples, \n", " igblast_db=\"database/igblast/\",\n", " germline=\"database/germlines/imgt/human/vdj/\")\n", "```\n", "
" ] }, { "cell_type": "markdown", "id": "a06ec016", "metadata": {}, "source": [ "## Step 3 : Reassigning heavy chain V gene alleles *(optional but recommended)*\n", "\n", "Next, we use `immcantation`'s `TIgGER` [[Gadala-Maria2015]](https://www.pnas.org/content/112/8/E862) method to reassign allelic calls for heavy chain V genes with `pp.reassign_alleles`. As stated in TIgGER's [website](https://tigger.readthedocs.io/en/stable/) and [manuscript](https://www.pnas.org/content/112/8/E862), *'TIgGER is a computational method that significantly improves V(D)J allele assignments by first determining the complete set of gene segments carried by an individual (including novel alleles) from V(D)J-rearrange sequences. TIgGER can then infer a subject’s genotype from these sequences, and use this genotype to correct the initial V(D)J allele assignments.'*\n", "\n", "This may impact on how contigs are chosen for finding clones later. It is also important when considering to do mutational analysis. For convenience, germline sequences are reconstructed at this step using the corrected V-gene alleles. Therefore, it is highly recommended to run it. \n", "\n", "However, this will only work properly if there is sufficient contigs. An ideal scenario would be to run it on multiple samples from the same subject to allow for more information to be used to confidently assign a genotyped *v_call*. In this tutorial, I'm assuming the four samples can be split into two sets where sets of two corresponds to a different/single individual. So while important, this step can be skipped if you don't have enough data to do this. \n", "\n", "`pp.reassign_alleles` requires the `combined_folder` option to be specified so that a merged/concatenated file can be produced for running TIgGER." ] }, { "cell_type": "code", "execution_count": 5, "id": "5e0432c6", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 0%| | 0/2 [00:00 ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IGH\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:20 |####################| 100% (185) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_heavy_parse-select.tsv\n", " RECORDS> 185\n", " SELECTED> 89\n", "DISCARDED> 96\n", " END> ParseDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 50%|█████ | 1/2 [00:00<00:00, 1.19it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IG[LK]\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:20 |####################| 100% (185) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_light_parse-select.tsv\n", " RECORDS> 185\n", " SELECTED> 96\n", "DISCARDED> 89\n", " END> ParseDb\n", "\n", " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IGH\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:21 |####################| 100% (2,409) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_heavy_parse-select.tsv\n", " RECORDS> 2409\n", " SELECTED> 1135\n", "DISCARDED> 1274\n", " END> ParseDb\n", "\n", " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IG[LK]\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:22 |######### | 45% (1,089) 0.0 min" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 100%|██████████| 2/2 [00:02<00:00, 1.03s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "PROGRESS> 14:58:22 |####################| 100% (2,409) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_light_parse-select.tsv\n", " RECORDS> 2409\n", " SELECTED> 1274\n", "DISCARDED> 1135\n", " END> ParseDb\n", "\n", " Reassigning alleles\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n", "Error in findNovelAlleles(db, germline_db = igv, v_call = v_call, j_call = j_call, : \n", " Not enough sample sequences were assigned to any germline:\n", " (1) germline_min is too large or\n", " (2) sequences names don't match germlines.\n", "Execution halted\n", "ERROR> Database file tutorial_scgp1/tutorial_scgp1_heavy_igblast_db-pass_genotyped.tsv does not exist.\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " Reassigning alleles\n", "null device \n", " 1 \n", " START> CreateGermlines\n", " FILE> tutorial_scgp1_heavy_igblast_db-pass_genotyped.tsv\n", "GERM_TYPES> dmask\n", " SEQ_FIELD> sequence_alignment\n", " V_FIELD> v_call_genotyped\n", " D_FIELD> d_call\n", " J_FIELD> j_call\n", " CLONED> False\n", "\n", "PROGRESS> 14:58:39 |####################| 100% (1,224) 0.0 min\n", "\n", " OUTPUT> tutorial_scgp1_heavy_igblast_db-pass_genotyped_germ-pass.tsv\n", "RECORDS> 1224\n", " PASS> 1205\n", " FAIL> 19\n", " END> CreateGermlines\n", "\n", " START> CreateGermlines\n", " FILE> tutorial_scgp1_light_igblast_db-pass.tsv\n", "GERM_TYPES> dmask\n", " SEQ_FIELD> sequence_alignment\n", " V_FIELD> v_call\n", " D_FIELD> d_call\n", " J_FIELD> j_call\n", " CLONED> False\n", "\n", "PROGRESS> 14:58:40 |####################| 100% (1,370) 0.0 min\n", "\n", " OUTPUT> tutorial_scgp1_light_igblast_db-pass_germ-pass.tsv\n", "RECORDS> 1370\n", " PASS> 1370\n", " FAIL> 0\n", " END> CreateGermlines\n", "\n" ] }, { "data": { "image/png": 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XL19i165duHPnDoC8z2jSpEniNKBA3u+Y2NhYvH37VvzuAECdOnVgaGgIAIXqZlS1alU0bNgQd+/eBQBcuHBB6SJy165dQ1pamtx758+fxyeffKKQNisrS67OvXv31qguRTm2s2fPYteuXQCA6tWrY8SIEWjQoAEyMzNx9epV7Nq1S/wsN2zYgCFDhmg0Mcu77JtvvsFPP/0kvrazs8OYMWNQt25d8XrfvXs33rx5g+HDh6vtXnzp0iVkZ2eLr1u2bFmidS9LTpw4IT8TaPHGSERlX2JiolykP3/+fJ2UK9tCYW9vr7LbV3x8vNCnTx8xrampqfDixQuFdMqegq1atUppc/D27dvl0i1evFghze3bt+W6bHh4eAjR0dFK63jo0CG5p3ydO3dWmu6LL74o8KlN165dxTSNGjVSmkbqxo0bap94yT65AiDo6+urbI3YvXu3oK+vL6Zt3bq10nSyn0XdunVVttK8ePFCrmm+cuXKSruoaUr2qSWQ1xVn+/btKtMnJCTIdS/o27evkJCQoDTtlStXBBsbGzFtv379lKYbOXKkmMbFxUWIiYlRmi4+Pl5o3ry5mLZevXpK62doaKjyaa9UVlaWMGrUKDFdzZo1FdJ89NFH4vbmzZsLKSkpSvM6deqUXCvJ+fPnFdLInmNlLSCy31sDAwNhz549Sss6ceKEwpPvglpApP/atm2r9Nw+f/5cqFSpkpiuevXqSsvOn1+NGjWEu3fvKqTbuHGjQtrq1asLoaGhCmlDQkLkPq/NmzcrpCnua05Z66m9vb1w48YNhbRv375V6DqmrEUjKCiowDSakm19dXFxUZpm2bJlCsfg4OCgNO3FixfFNNWqVVPYXtC1qemx5f9dgv9/cp+ZmamQ9urVq3LdDD/99FM1Z6RoZOtTUi0gV69elfsdMHDgQKUtia9evZL7/a3qnOb/Dmnahbeo3vUWkKdPn8r9LmjYsCG7YBHl9/jxY7kv2po1a3RSpvSXoIGBgXDz5k216dPS0oSaNWuKdVTWFSV/ADJv3jy1ecp2ZejVq5fC9sGDB8v9wVTX51wQBGHHjh1y5V+8eFEhjSYByK5du+TyUTf2Zd68eWK6KlWqKARb+QOQgrqbffvtt2qPQbY/v6WlpfDs2TO1+UVHR8t1Rdm6dava9Orkv2mYNWuW2vSLFy8W07Zu3VrpzYWs06dPy+WvLLCqUaOGuP3vv/9Wm9+JEyfEtNL++7L++ecfcbu+vr7a4CwxMVHuZj7/NSE7fuTnn39WWy/ZIErZd0TdTV50dLTczZi6PtqCoHgtaxKAODs7qwygBEEQVq5cKZde2UMB2e16enpCcHCw0rzS0tLkuo8AEAIDA1WW3aNHDzHduHHjFLYX9zWX/ybIyMhICAkJUZnf5cuX5dIfOHBAIU1xBiAXLlwQ85FIJEqDRun4D319fblxfvm7qgqC/PmbMmWKwnZ112Zhji3/75IJEyaoPc7Ro0eLaQt6KFQUsnUqqQBk4MCB4vY6deqovUZjYmIEW1tbted00aJFBX4fS4Im3e40+aeqm5o2AUhycrJw48YNYfHixYKVlZW4r7m5uXD37l2B0/AS5RMXFyf3WpMZp1q3bg2JRKLRv44dOyrsv2XLFrHrw0cffYSmTZuqLc/U1FTsIgEAJ0+eVJu+QoUKWLx4sdo0Xbp0EX9+8eKF3LaXL1/i6NGj4uv58+fD2tpabX4TJkyQm4J43759atOrMmjQIJQrV058LdvFKj/ZbSNGjFC7cqyVlRVmzpyptuzZs2fD3NxcfH3kyBG57Zs3bxZ//vzzzwucNatSpUoYP368+Lqgz01TJiYmWLBggcrt2dnZcl0MvvvuO7Erhirdu3eHq6ur+FpZXR0cHODq6oqmTZvC09NTbX7VqlUTf5Z24ZCVmJgo/pyTk4OEhASVeVlaWmLr1q1YtWoVVq1aJXd95M8rNjZWbb1mzpwp5tOhQwe1afPbu3evXNci2e6JyowZM0Zp10Z1VqxYATMzM5XbZb+3gOJ3N79u3brJfa6yTE1N5b6zTZs2RatWrVTmVb16dfFn2Vl/gJK75mRNnDgRjRs3Vrm9devWcjN6FXRuiqpt27awsrICAAiCINd9CsjrUnXlyhUAQIsWLdCnTx9xm5+fn0J+vr6+4s+adr8qDsq6R8qS7VYk7XpaFsXFxeH48ePi68WLF6u9Rm1sbDB9+vQC85RV0P1DWFiYxvcOEonknVkNfvz48QXW1dzcHM2bN8d3330n/k6uWbMm/v33X7i4uHAdEKL8ZPtvAhADg5J0+vRp8Wd3d3eN9pFNFxoaijdv3qhM6+npWeB0mbLjBfIveHT+/HlxHIaBgQFGjBhRYP309PTkVueVXRG2MMqXL4/+/fuLr1UFILdu3cKjR4/E16NGjVKbb8eOHZVON5q/bNnpl6U3D0DeTbLseAVtPrfAwECN9ilI69at1S5wdfPmTcTExIivNb3RLqiuly5dQnBwMG7evKkQBOQXFBSkdnvt2rXlXn/88cfi9JPKjBs3DvPmzcO8efMUAj/ZvL7//nscO3ZMZT7NmzcX8+nVq5faOuYnHScE5N3YF3QOAMhdy5ro2bOn2u35x/kUtFiZsgcgsmSDnYL6r8vO6f/27Vu5bSV1zckq6NxIJBK56Y9LeiE3AwMDdOvWTXyd/3fe1atXxfEfnTp1kgsez58/L5c2NTUVV69eBZAXGGozDbw2nJ2dUaNGDbVpbGxsxJ9TUlJKuEYlJzAwUPy7pqenp9GYPHXTmgOlc/+QX7ly5eDi4qLVP3UPO4rDkCFDxKmxOQidKJ/8T/bV3dhL1apVS+0vYtnB1vklJiYiLCxMfL1ixQps2bKlwDKlvzilIiMjVa4vIvukUhXZecrz/xK9du2a+HOjRo0KbP2QatCggfiz7GDIwho1apTYghIcHIxHjx7JrRILQG6V+UaNGhU4/3+7du00KrtVq1biDazsDfHdu3eRnJwsvv7iiy80mutdOnAXAOLj45GWlqbRjas6VapUUbtdNnCSSCQaT6wg23pQmKfHaWlpePr0qfjv5s2b2L17t9p9mjdvDg8PD/Gm7fLly6hduza6du2Kbt26wd3dHY0bN9ZofZmvv/5abGlKSUnBgAED0KBBA/Tt2xcdO3ZE27ZtNV6LR53g4GDxZ1WtCvmpe2KfX4UKFeRa4JTJf83l/+7mlz/Qy0+21bBixYoF1PB/BNnBpdDNNVfU32sloVevXjhw4AAAxQBE9rWnpydatGgBPT095ObmKgQgFy5cQFZWlphWF2sIAdBovR7ZwDP/36GyRPb7W6tWrQK/awBQr149GBkZITMzU+l2ZfcP6h7+GRsbi5OyqBIaGqrw/VLHzc1N4Xoqbo6OjmJrnyrp6emIioqSm3Rh7dq1OHnyJHx8fBiAEOWX/4/uy5cvC9znr7/+Urt93Lhx4swi+b169Urul8uLFy+06iqgLlAq6lONV69eiT8XZkE5Ozs78ee3b98iPT1dqz+k3bp1g62trTjjz6FDhzBv3jy5NLIBSEGtHwCUztijTKVKlcSfZYPI/NeFdGamwkpOTi5yAFLQTblsXYX/n/WpsNRdXzdv3sS+ffsQGBiIBw8eyD35LoyDBw/io48+Em/UsrKycOrUKZw6dQpAXncGd3d39OrVCwMGDFB4+i81btw4vHr1CosWLRJvkEJDQxEaGorVq1dDT08PzZo1Q9euXTFgwACtZ6qR7W4h23VJncLc1JfE08jCBF4FdZlSp6SvOaBkzk9R9ezZExKJBIIg4Pbt20hISBBbJ6U3hUZGRmjfvj1MTU3RrFkzXL9+Ha9evcKDBw/E36+l1f2qqIvcliXafH/19PRgZWUl/i3KT9n9g7pFSGvWrCnOnKZMbm4uDA0NCxWA6MLy5csxbty4AtPl5uYiKCgIU6dOxfXr1wHk/S7+/PPP2QWLKD9ra2u5JyGyT0m0pa4/u7pthaGsX71UUVcll+1TX5g/UPlvrLV9WmZgYIBhw4aJr/N3w5K2igB5T1uHDx9eYJ7quizJku2mJft0WBefW3Epjroqq2dsbCwGDx6M5s2b44cffkBAQIBC8GFgYIDWrVtrNP1spUqV4Ofnh0OHDqFHjx4KU4UmJSXhxIkTmDJlCqpWrYphw4YpjD2Qmj9/Pu7evYsvvvhCLhAG8v4oXr9+HatWrUKrVq3QsGFDuW6QmpK9QS6JJ9RF/d4qI/v0uiSV1DUnqyTOT1HZ2tqiRYsWAPICL+mU7llZWeL05K1btxavF9luWLLjQGS7dxa2a2BRFCXoLGtK4vubv1WuqPcPSUlJpdKNq7jo6emhVatW8PHxkXvod/LkSQYgRPnp6enJdc+5ceOGXLcZbch2scrP2NhY7vWZM2cgCEKh/2k6BkEbsjctqpqelZG9CTEwMChwzIU6sq0aN27cQHh4uPhatvXD3d29wMHgANQOUJcl281Ktnk9/+f24MEDrT432cHZJUW2rpUrV9aqnvlbeFJSUtCpUyd4e3uL7zk4OGDUqFFYu3YtDh48iBs3biAlJQVXrlxRuiaCMhKJBIMHD8Y///yD+Ph4nD59GnPnzkXr1q3lrsPs7Gzs378fbdq0UXmzW69ePWzZsgWvXr1CSEgINmzYgP79+yt0k7h37x569+6Nw4cPa1RHKdkAW9NA8vXr14Uqo6wqiWuurJANGKStebLrf8iO51A2DiQmJkZcw8TFxaXAMRmkHW2+v7m5uWontsj/d1h2TTFtqLt3KEusrKzk1mvKzs5mAEKkjOxAzZSUFJw4cULrvKKjo+UWKcsvf5NtQbP2lAbZOmrSJU1KutAfUPA4hYK4ubnJdf+SbQUpbPcrABp3E5Kd5UX2PJSFz01Ktq4JCQnF8kRt3bp14k2Snp4etm3bhmfPnmH37t2YNWsWhgwZgmbNmikEaoVhZmaG7t274/vvv8eVK1eQkJCAI0eOyM0eFBERgR9++EFtPhKJBI0bN8aMGTNw9OhRxMTE4Pr165g7d64YFOfm5mLGjBmF6uog24qmqiUmP3W/C94nJXHNlRXKAhDZPvmyAYi0K5ZsGl9fX/E61GX3qw+NNt/fR48eqb2W7ezs5Bas9fb2LtRDu/yKGsC8S/KPf2MAQqTE0KFD5Z62bty4Ueu8duzYoXZ71apV5bp8hYSEaJTv69evsWfPHuzZs0cc9FhSZH+hXr9+XeOuVLKDLotjRdiRI0eKP0sDkJCQEPz3338A8p66fvTRRxrlpa7frSzZ2ZtkBxrLDrCX1kMTjx8/Fj+34pqGtyCydX379q1cYKjO5cuXxbpK++9KyQZ9n3zyCSZPnqy2S0xBf+Dv37+P4OBgBAcHq5ytqHz58hgwYABOnDiByZMni+/L9pd//fq1mM/z58+V5qOnp4fmzZvj+++/l+vq8uLFC43PDQC5KXVlJ2pQR92MXO+Tkrjmygo3Nzex339wcDDevHkjBhflypWTm9rY2NhYbHF//fo17t+/X2rjPz40st/fBw8eaDThjCbfX9mHYImJidi5c6dW9cvNzcXvv/+u1b7vovwP7RiAEClRo0YNuXEEV65cKXCguTIvXrzAhg0b1KbR19dH+/btxdey622os3HjRowePRqjR48uUoCkCdn6xcXF4d9//y1wn1evXsnNgy87PaW2ZH+xX7t2Dc+ePZMLvvr166fxGJW///67wDTR0dE4d+6c+Fp2rQtbW1vUr19ffJ1/jRBVvvnmG/Fz0+aa0oaHh4dclzNN6pqTk4OhQ4eKdb1586bcdtnuMZpMsVrQrCxDhw5F06ZN0bRpU43qJzudrewYpb/++kvMR3bNFVVatWolN0ZENq+CtGnTRvz51KlTKme6kzp37hxCQ0M1zr8sK4lrrqyQSCTo0aMHgLxj8vPzE8d/tGvXTmFsU/5xINIAxMrKCm3bttVRrT88st/fnJycAteqysjIKPCBIpA3I6LsQ8Vvv/22wN8Nyvzyyy+FeiDyrss/yxgDECIVvvnmG7mBaZ9++qn4R0QTr1+/Rt++fRUWJlJmwoQJ4s8PHz7E3r171aZ/9OgRfvzxR6X7l4T27dvDyclJfP3NN98UOKXlqlWrxGkkzc3NMXToULXpNemiUbNmTbk/yIcOHZLrijV69OgC85AKDQ3F/v371aaZP3++eAwmJiYK6w7InncfHx9cunRJbX6XLl2SC5hK+nOTsrOzk+sWsmnTpgJvtNesWSPOxla+fHmFMRyyrR0FdT+7fv26ylngpGSnh9XkZlV2zRfZGWxk87l8+XKBYy4SEhLkbg40nQ0HAIYPHy7eZKelpcktDppfVFQUPvvsM43zLutK4prTheLqKiZ77GvXrlU6/kNKNgDZuXOnOL6te/fuxTppwIfUDU4TTk5Ocq1R3377LSIjI5WmFQQBs2bNElvb1bGyssKcOXPE19HR0ejTp4/cdLQF+fvvv9X+PimLGIAQaahOnTr45ZdfxNfp6eno0qULVq5cqXbAWk5ODvbu3QtXV1dxBgzZqVyVGTRokNy6FZMnT1ZYRVfq/v376NGjh9hNpW7dunKDu0qCnp6e3LS3N2/exJgxY1R2ldmxY4fcWibz5s1TOgBdtrXi3r17Gg3QlW0FWbdundin3tbWtsCFyfJTdZ5zc3OxdOlSuebvyZMnK0z7+tlnn8m99/HHH6ucbvTSpUsYMGCAeBPg6empsIp1SVq0aJEYNERHR2PQoEEqB29v27ZNbjXk2bNnK8z5Ltufd9OmTUq7WAmCgN27d6N79+4KC9VJAzsp2UXAvL29sW3bNpXHEhwcjGXLlomvZceEdOzYUfxDl56ejtGjR6vsWpGamoqJEyeKdWncuLFGExhI1a9fH4MGDRJf//XXXxg6dKjcBAlZWVnYt28fWrduLRc0fQiK+5orCflbTGW7PxWFbPAg+2BCWQDStGlTsXuKbLezona/Kqlje58sXLhQ/Dk6OhodOnTAP//8IxesBQcHY9CgQRqtzyW1YMECdO3aVXx95coVtGjRQumK97Jev36NGTNmoF+/fsjKyoJEIinU1N3vsvwBCNcBIVJj1KhRePDgAZYvXw4g74Zm4cKF+P7779GjRw80a9YMtra2MDExQWxsLEJCQvDvv//KrePRp08fLF26FM2aNVNZjp6eHg4ePAg3NzckJycjOTkZHTt2RN++fdGlSxfY2NggISEB/v7+OHz4sNj6YGJigl27dik06ZeETz/9FEePHhXXZNi3bx/8/f0xdOhQuLi4wMjICM+fP8exY8fEFXwBoEWLFpg9e7bSPGUHlcfHx8PJyQnVqlWDm5sb/vzzT6X7DB06FDNmzEBmZqbcgPiRI0cW6mmhmZkZEhMT4enpid69e8PT0xO2traIjIzEvn375KZPdHZ2xjfffKOQh7m5Ofbv34/OnTsjOzsbL1++RLNmzTB48GB06NBBnC/ex8cHp06dEgeW2tjY4Ndff9W4rsWhVatWWLp0qfgH18/PD3Xq1MGIESPg6uoKY2NjRERE4PDhw7h165a4X+vWrRXWXAGASZMmiS2CERERqFevHiZOnIjGjRsjLS0NDx48gLe3tzgOY8iQIfD29hb/sC9evBh16tTBwIEDYWlpiREjRmDFihXiTfrnn3+OX375BX379oWTkxMMDAwQGRkJHx8fnDt3TjyXNWvWlBsPYm5ujpkzZ2Lp0qUA8lqmatasiSFDhqBp06awtLREXFwcbt++jQMHDiApKUncd/Xq1YU+rzt27MCdO3fEQPjAgQM4cOAAqlSpItZZGuAYGxtj4sSJ+OmnnwpdTllU3NdcSahevTpMTEzEAHnSpElYtWoVTExM4OPjU6gWMVlWVlZo06aN3CBiS0tLNG/eXCGtnp4ePD095Vpz9fT0xG5c2iqpY3uf9O3bF7Nnz8batWsBAOHh4ejVqxcsLS1ha2uLqKgouZkQZ86cWWC3aiDv89u3bx+6du0qXtv3799Hp06d4OzsjF69eqFmzZqoVKkSMjMz8erVK1y6dAnnzp0TPy8DAwPs2LED9+/fx5o1azQ+pqCgIDRs2LAwp0FO586dsWnTJq33V0Whe7RARAU6duyYUKlSJQGAxv/09PSE2bNnC9nZ2YIgCIKdnZ0AQPDw8FBZTlBQkGBvb69R/pUqVRLOnj2rMi8PDw8x7eLFiws8xrVr14rpq1evrjRNSkqK0L17d43PQbNmzYS4uDiVZaampgo2NjYK+6k7R4IgCP3791fY586dOwUeY/Xq1cX069evFxo2bFjgMVStWlUIDw9Xm++pU6cEc3Nzjc6Jk5OTcOvWrQLrWpCxY8eKeY4dO1bj/ZYuXSpIJBKN6tq1a1chNjZWaT65ubnC4MGDNcpn0qRJQnZ2ttC8eXOFbbLnNjg4WLC2ttb4+rK3txdCQ0MV6paVlVWo61QikQjr1q1Tepyy6Q4ePKg0TWxsrNCrVy+1ZZibmwve3t7C9u3bxfc6deqkkNfOnTsL/B7KiomJkSvHz89P7TEo2y7LxcVF498bX3zxhUbf2eK65sLDw1VeO0U5nilTpiitiyb5q7Nq1Sq5/Pr27asy7c8//yyXtnXr1gXmr8m1qcmxFfZ3ycGDB+XyKimyZRTmd5yU7HepoGt//fr1gomJidprc9y4cUJqaqrce8+ePVNbh7dv3wpffPGFoKenp/HvIwCCnZ2d4OPjIwhC3t8X6fs7d+5UWo7s3/ui/uvfv79C/vm/e6rqoU5ubq5gaGgo5sEuWEQa6NevH8LDw7F27Vq5PubKmJmZYfjw4QgKCsKaNWvELgiyU/uq0qJFC4SEhGDKlCkqpy81MzPDhAkTEBwcjM6dOxf6WIrCzMwMJ0+exLZt29Q+PXN0dMQPP/yAwMBAhTUXZJUrVw6nT59G165dYWFhAQMDA1SqVElhur788k+1K11MrjAqVKiAgIAATJgwQWkLkpGRET755BMEBwcXOA9/z549ERISgmHDhqlshbG2tsaMGTNw8+ZNNGnSpFB1LU6LFi3C+fPn5QZg5le7dm1s3LgRp0+fVtn8L5FI4OXlhQULFihdxEsikaBDhw7w8fHB9u3boa+vj6VLl6ptpXJ1dcX169fx8ccfq01namqKiRMnIiQkRG4iACkDAwOcPHkSK1euVFiEML82bdrAx8cHX331ldp06lSsWBEnT57Ev//+ixEjRqBatWowNjZGhQoV0LBhQ8yePRshISEYOHCg3DiIkli88F1UXNdcSVm7di2mTp0KR0dHcb2ixo0bKyykWlj5u1Ap634lJdtdByi+xQdL6tjeNzNnzsR///2HefPmwdXVFebm5jA1NUWNGjUwZMgQnDx5Ejt37kRKSorcfgV9h42NjbFlyxbcu3cPY8aMgYWFhdr0NWrUwNKlSxEWFiZ20e3QoYPOFhAtSRKJBE2bNv3fa0F4x9Z3JyoDIiIiEBQUhNevXyMxMREmJiaoVKkS6tati2bNmhVLl6jU1FT4+fkhPDwcb968Qfny5eHs7AwPD48iLehXXARBwM2bNxEcHIyYmBgYGRmJwYPsdLUl4e3bt7CwsBC7tvz2228aDeiuUaMGnj59CiBvsOe4ceMA5A0QDggIwNOnTyEIApycnODh4aHVjVBCQgLOnTuH58+fIzU1FZaWlqhXrx46dOhQpDUxSkJ4eDgCAgLw6tUr5OTkoFKlSnB1dYWbm1uh8omPj8e5c+fw5MkTGBgYoGrVqmjRogVq1qypkPbevXv4559/kJWVhfr166N3795KV19OTEzEtWvX8OjRIyQlJUEikcDKygp169aFm5ubxt+B7Oxs3L59GyEhIYiPj0d6ejrMzc1RpUoVuLm56WQhSFkzZswQuzeMGTOmwMH575viuuaISkNwcLB4E62vr4+3b98WKjjIzs5GUFAQHj58iJiYGGRkZKB8+fKoWrUqGjVqVOADzvcJAxAiKnP8/f3h4eEBIK+vdWRkpEZP9FQFIES60rlzZ3Fq56VLl8oNvCaid9vu3bvFSV+cnJzw+PHjUq5R2cUuWERU5mzdulX8efz48exOQKXin3/+gbOzM5ydneHi4qIw01d+0dHRCAgIEF+r65JERCWvcePG4ndYdhIAVQ4fPiz+zO9v0TAAIaIy5eXLl+I6Efr6+pg6dWop14g+VNInoI8fP0ZoaKjKmduAvKmdp06diszMTAB500a7u7vrqqpEpISZmZn4Hd64caPatVJOnDghtxL6Rx99pIsqvrcYgBDROy0lJUWcBjElJUVu3YbBgwfLLZBIpEt169ZFy5YtxdczZszA1q1bFdbHuXz5Mnr27ImDBw+K7y1dulQn02cTkWqya2hdunQJw4cPV1iv5+XLl1i6dCkGDx4svteuXTu59Yeo8DgGhIjeaefPn0fnzp1RqVIlJCQkiE+Q9fX1ERISAhcXF43z4hgQKm7Xr19Hhw4d5LpfSQfi6+npISoqSiEgGTRokFxXDiIqHdnZ2ejQoQMCAwPl3re1tUWFChUQFxeHuLg4yN4qW1tb4+bNm6hevbquq/teYQsIEb3zcnNz8fr1azH4AIBvv/22UMEHUUlo0aIFfH195VrisrOzER4ejsePH8sFH3p6eli4cCH2799fGlUlonwMDAxw5swZDBkyRO796OhoPHjwALGxsXLBR5s2bRh8FJOyP7EwEb3XpCvSxsTEwMLCAo0aNcKUKVMwYsSI0q4aEQCgbdu2CA0NxYEDB3D06FHcuHEDr1+/BgDY29ujSpUq6NmzJ4YNG8Yug0TvGAsLCxw8eBDXrl3D7t27ERAQgCdPniAtLQ0VK1aEvb093NzcMGzYMHh6ekJPj8/uiwO7YBERERERkc4wjCMiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzXAeEiKgUtWjRAlFRUaVdDSqj7O3tcf36dYX3eV2RtlRdU0TFiQEIEVEpioqKQmRkZGlXg94zvK6I6F3GAISI6B2gp6eHypUrl3Y1qIx49eoVcnNzC0zH64o0pek1RVQcGIAQEb0DKleujBcvXpR2NaiMqFKlikYtHLyuSFOaXlNExYGD0ImIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiEgrM2bMgKOjI9atW1eo/Vq1agVHR0ccO3ashGpGmjh9+jTWrVsHHx+fYslv3bp1cHR0xMiRI4slP5JX3J8XUWliAEJERDpVvXp11KpVC+XLly/tqnzQTp8+jfXr1+Ps2bPFkp+1tTVq1aoFBweHYsmP5BX350VUmgxKuwJERPRhOXDgQGlXgUrA+PHjMX78+NKuBhGVAWwBISIiIiIinWEAQkRURl27dg1ffPEF2rVrh1q1aqFJkybo1asXNm/ejJiYGIX0Q4YMgaOjI/bv348nT57gyy+/RJMmTVC7dm307NlTHJMRFxeHBQsWoEWLFqhZsyZatmyJJUuWIC0tTWVdwsPDxfycnJzQrl07LF26FPHx8Qpp1Y0BuXHjBsaOHQsXFxfUqVMHffr0wf79+wEAjo6OcHR01Dgv2WPesmWLwraUlBRs2LABXbt2RZ06deDs7Ixu3bph48aNSE5OVkgvHfMyd+5cpWWpGwPh6+uLUaNGoWHDhqhevToaN26M0aNHK/Tn379/PxwdHTF06FDk5ubijz/+QM+ePeHs7Iz69etj8ODB8PX1VVr+1atX8emnn6Jp06YQBAF2dnYQBAFXr15VWsbBgwcBAHv27IGjoyNmzJihNF9NqTp+6ef28uVLBAcHY+LEiWjUqBGcnJzQvn17/PDDD8jMzCxS2fkdPnwYffr0gbOzMxo1aoTRo0cjMDAQly9fhqOjI4YMGaJ0v+PHj2PYsGFwcXFBrVq14O7ujmXLluH169cKaYvyWQHyn1eNGjXQtGlTfPrpp4X6vLy9veHo6Ihq1aohLi5OaTn79u2Do6Mj6tevj7dv3+L58+fiZ5KdnY1Tp05h4MCBEAQB9vb2EAQB/v7+KuudlJSENWvWoHPnznB2doaLiwsGDx4MLy8v5OTkqNyPSBYDECKiMmjz5s0YOHAgjh49ihcvXsDGxgaZmZkICQnB6tWr0blzZzx9+lTpvrdu3UKvXr3g7e0NfX19ZGRk4Pbt2/j888+xbds2dO/eHbt27UJKSgosLS0RGRmJHTt24NNPP1Wa382bN9GtWzd4e3tDIpGgQoUKiIiIwPbt29GjRw+V9chv3759GDBgAM6ePYv09HRYW1vj/v37+OqrrzB79mytz5UyERER6NatG3744QeEhobCwsICFhYWuHfvHtauXYtu3brh0aNHxVLWjz/+iDFjxsDPzw+5ublwdHREeno6zp07h3HjxmHz5s0K+2RmZmLs2LFYuHAhIiIiYGtri/T0dAQGBmLs2LEQBEEu/Q8//IBBgwbh1KlTSElJAQBIJBIAwKBBg7Bq1SoxrYWFBWrVqgVzc3MAgKWlJWrVqgU7O7tiOV5V9u/fj759++Ls2bMoX748TE1NER4ejg0bNmDq1KnFUoYgCJg5cyamTZuGW7duwcDAAGZmZjh//jw++ugjHDp0SOl+mZmZmDx5MqZMmYKLFy8iMzMTNjY2ePr0KX7++Wd4eHjgwoULKvdV91kpGzSe//OqXLkykpOTcerUqUJ9Xj179oSZmRlycnLwzz//KK3fyZMnAQB9+vSBiYmJ3La1a9fi008/RUhICID/XTPDhw/Htm3bFPJ68OABOnXqhE2bNiEsLAwWFhYwMDBAYGAgvv76a/Tv3x9v3rxRWg8iOQIREZUaR0dHAYDg6Oio8T5xcXFCtWrVBAcHB2Hz5s1CZmamuO3q1auCq6ur4ODgICxcuFBuv8GDBwsODg6Cg4ODMHz4cOHFixeCIAhCYmKi0KtXL3Gbi4uLcObMGSE3N1cQBEE4evSo4OjoKDg4OAihoaFiftOnTxf38fT0FG7duiVuu3nzptC8eXPBwcFB6Nu3r1w9WrZsKTg4OAhHjx4V3wsJCRGPae3atUJaWpogCIKQlpYmrFy5UizHwcGhwLyUHfOPP/4ovvf27VuhU6dOgoODgzBgwAAhPDxc3PbkyRNh0KBBgoODg9C2bVshPT1d4XjnzJmjtKwffvhBcHBwEEaMGCG+9/z5c6Fq1aqCo6OjcPjwYfGc5uTkCN7e3kLVqlWF6tWrCxEREYIgCIKXl5d4nDVr1hT27dsnZGdnC4IgCNHR0UKXLl3E7dLrxtvbW3BwcBCqVasm7NmzR8jMzBSvKwcHB6FGjRqCg4ODsGfPHrn6FnQ8haXs+AVBkPvsJk+eLMTExAiCIAjZ2dnC999/L2578uRJkeuwY8cOwcHBQXB2dhaOHz8unu9Xr14Jo0aNEssaPHiw3H7ffvut4ODgILRo0ULw8/MT90tMTBQWLlwoODg4CLVr1xaioqLEfTT9rPr37y9XlrLPSxAEISMjQ9izZ0+hP6+pU6cKDg4OwrBhwxTOR0JCglC9enXBwcFBuHLliiAIgvDs2TO5z2TFihVCWlqa4OjoKEgkEvF9R0dHcR9BEISkpCShVatWgoODgzBhwgQhMjJS3Hbnzh3xO/XJJ58U/EHRB48tIEREZcydO3eQnZ2NJk2a4Msvv4ShoaG4rWXLlhg+fDgAqGx5qFq1Knbu3Cl2Z7K0tMSECRPE7UuXLkW3bt3Ep6H9+/eHs7MzAOD27dsK+ZUvXx779u1DkyZNxPeaNm2K1atXA8jrVnXjxg21x7Rp0yZkZ2djwIABmDVrFkxNTQEApqammD9/PgYMGKB2/8Lw9vZGWFgYzMzM8Pvvv6NGjRritpo1a2Lnzp2oWLEiIiIiijxg/ubNm8jJyUHFihUxaNAg8Zzq6elh4MCBGDp0KOzs7HDnzh2FfZcsWYJhw4ZBX18fAFCpUiWFblKCIIjnecqUKRg5cqTc9SCRSDBz5kwAeV2kcnNzi3Q8RdG8eXNs3boVNjY2AAB9fX18/fXXsLS0BIACr5GCZGZm4scffwQALF68GH379hXPt729PXbs2IHq1asr7Pfs2TPs3LkT+vr6+O2339CxY0dxP0tLSyxfvhxt27ZFamoqdu3apbRsdZ/VrVu3xBarnJwclZ+XkZERRo4cWejPa/DgwQCAy5cvIyEhQW7bmTNnkJWVhSpVqqBVq1YK+3bq1AkLFiwQv2+CIEAikaB9+/YQBEGuFeS3337D8+fP4erqiu3bt8vNdtawYUP89ttv0NfXx6lTpxAREVFgvenDxgCEiKiMadmyJYKCgrBnzx6l26XjP1TdvPTq1QvGxsZy79na2oo/d+nSRWEf6U1j/hscAOjdu7fS7judOnUSb+4DAwOV1gXIu3E8f/48AIjBU35jxoxRuX9h/f333wDyxodUqFBBYbuFhQX69u0LAGK9tGVtbQ0AiI2NxbZt25CVlSW3fe3atbh69Sr69Okj976xsTGGDRumkF+dOnXEn6U3yc+fP4eBgYHKGahGjBgBiUSC169fIzQ0tEjHUxSjR4+Gnp78bYeBgQGcnJwAKL+2CuPmzZuIjY2FsbGxeFMuy8TEBB999JHC+8ePH0dOTg7q1auHxo0bK81bGgBfunRJYVtBn1V2drbYLSk4OLjYP68OHTrA1tYW2dnZOHPmjNw26bU+cOBA8XrJX5Yy0u/hlStXxN8jR44cAZDXpc/AQHESVek4FkD5eSKSxWl4iYjKGFNTU5iamiI9PR0BAQG4d+8eIiMjERkZicePH+O///5Tu7+yp8DSJ7eGhoawsLBQuW92drbCe/Xq1VOaViKRoHbt2oiIiMCrV69U5hkREYG3b98CgMobwPr166vcv7Du3bsHAGjRooXKNLVr1waQ93S8KNq2bYtu3brh33//xfLly7Flyxa0bt0abm5uaNu2LRo1aqT0xtDW1hZGRkYK78v24Zfdr0qVKirHcNjY2KBChQqIj4/Hs2fP0LBhwyIdk7aqVKmi9H3pMWVkZBQp/7CwMACAs7Oz+EQ/vwYNGii8J219Cg8Ph7u7u9L9pBMwREZGKmzT5LOSHpv02ivOz0tfXx/9+vXDr7/+ipMnT4rBUFJSEi5evAgASgMyQPX3TXqeUlNTkZiYCFNTUzx+/BgAsG3bNvz5559K95MO1ld2nohkMQAhIipjBEHAL7/8gvXr14sDjoG8GxdXV1c4OjqqfXKffyCqrPxPqDWhLj8rKysAUDvLUVJSkli2dKBtfqpuKAuSv8UBABITEwHkdctRRVqeNDDStiw9PT389ttvOHHiBA4dOoTLly/j9OnTOH36NADAzs4O48ePxxdffCF37pXd0KpTuXJltdulx1PUm/yiKOwxFZb0OpJ26VJG2XUk3S8tLU28yVYlPT1d4b3CHJf02ivuz2vQoEH49ddfcfHiRSQlJcHS0hKnT59GVlYWGjVqJAbU+Ulb6PKTXSQ0KytLrh5RUVEF1kfdjHlEAAMQIqIy58cff8Tq1athbGyMOXPmwMPDQ26WnHXr1hW561BhSG/glJE+EVXW1UlKegOXm5uLtLQ0mJmZKaRRNcWoNnUzMjJCVlaWeDOojLTFRtUNmqZlAXlBSP/+/dG/f39kZmbi9u3bCAwMhI+PD65fv47vv/8eubm5mD59usZl5afuWARBQHR0NIDCHU9ZI+1WmJqaqjKNsutIerPfo0cP/PbbbyVTuf8nvdaL+/NydXWFs7MzHj16hDNnzuDjjz+W636lSkZGhtqgDMh7iCAbeP3+++/o3r27RvUiUoVjQIiIyhhp94cFCxZg+vTpaNKkiVzLQVH70heWsoHpQN6A24cPHwJQ3vVFSrYlQtXA+fxrI0hJWw2UrT+QlpamdDCsdFzK/fv3VdYpKCgIAOS6v0jLUjW2Rtq9Jn+9Dx8+jPDwcAB5N6AtWrTA1KlTcezYMUybNg3A//rqaysiIkLlU+ebN2+KrTMuLi5FKuddJr2Onj17pjBNsZSy66hWrVoAIH5Gyjx+/BiHDx9GQEBAkepYs2ZNACXzeUkDjZMnTyIpKQkBAQHQ19dXO4GDqu6a0u90tWrVYGxsDCsrK3EcmLrz5Ofnh8OHD+PFixca15s+TAxAiIjKmNjYWAD/u3GS9ebNG5XrAZSU8+fPK+2WcebMGURFRcHU1BSdOnVSub+dnZ04LuWvv/5S2C4IAnbu3Kl0X2nLirKboiNHjijtFiWty549e5R2sXrx4oXYd753794alfXff/8hODhY4X1vb29MmzZN5ZN16fgZVTfMmpCOB1J27oC89VUAoHXr1uJN5PvIzc0NEokECQkJ4toXsmJiYnD8+HGF97t27Qogb40LaeApSxAEzJs3D9OmTVMZCGuqdevWJfZ5SWdZu3jxIg4fPozMzEx06NBB7fouymZ5EwRBfMjh4eEhvi+dnGLv3r1Kg/DHjx9j/PjxmDFjBhckpAIxACEiKmOks+ts3bpVXGk8JycH/v7+GDRokNh9ozDjF4oiLS0N48ePl1u4LygoCN988w0AYNKkSSrHdkiNGzcOQF4Asn//fvEGJzY2FtOmTVN6YwjkdT0BgD/++AN3794FkNdCceLECXz33XdKZ+sZP348rKysEB0djc8++0xugPyjR48wadIk5OTkoF27dmjXrp1CWYGBgTh8+LAYNNy5cwcTJ05UOphcenO7b98+HD58WG4Q/61bt/DDDz8AADp37qz2/KgikUgwceJEAMCaNWvEGZ2kBEGAl5cXJBIJvv76a7l9pWN31E0QUJY4OjqK53vx4sVy0/qGhYVh9OjRSrvJtWrVSrzRnjFjhlyLXlxcHGbOnInLly/DxsZGbrpqbVhaWqr8vDIyMvD7779r/XlVq1YNLVq0QEZGBtasWQMA+Pjjj9XWx8vLCz///LM4xkN6DQcHB8PQ0BBTpkwR037xxRcoV64cHj9+jNmzZ8t1IwsKCsKYMWOQlZWFoUOHKp3ogkgWAxAiojJm7ty50NPTw5UrV9CsWTO0bt0a9erVw/Dhw5GdnY3169cDyOtu0qpVqxJfmXjYsGH477//0LFjRzRr1gxNmzbFgAED8Pr1a7i7uyusXaHMJ598gj59+iArKwtfffUVGjVqhJYtW6JZs2bw9vbGyJEjAUDhJv+TTz6BmZkZ4uPj0b17dzRp0gR16tTB5MmT0bhxY4XpbYG8Fpdt27bBzMwMZ8+ehZubG1q2bInmzZvDw8MDISEhcHZ2FteUkOrevTvq168PQRAwbdo0uLi4wMXFBT169EBycrLS4+zSpQv69u2Lt2/fYtq0aahXrx7atWsHFxcX9OnTB0+ePEGjRo3w5Zdfan7C85k1axa6du2KtLQ0TJkyBS4uLhAEQa5r26JFi9C2bVu5/aTde3x9feHm5oaVK1dqXYd3xdq1a1G7dm1ERUWhX79+aN68OZo0aYLOnTvj/v374gxR+a+jLVu2oEmTJoiIiEDPnj3RpEkTtG7dGk2aNMHBgwdhY2OD33//Xe1YJk0p+7zatm0LFxcXLFq0CID2n9egQYMAAMnJybCysipwrEbXrl2xbNkyhWtGX18fGzdulAsknJyc8PPPP6NcuXLw8vKCq6sr2rRpg0aNGmHAgAGIiIhAx44dsWzZMu1PDn0wGIAQEZUxnTt3xr59+9CmTRsYGBggISEBzs7O+Pbbb3HmzBkMGTIEI0aMgImJCTIyMsQpdktK8+bNcezYMXTt2hWZmZl48+YNGjRogMWLF2P37t0azRKkp6eHn3/+GRs2bECzZs2QkZGBhIQEuLi4YP369eKT2PwzbtWqVQvHjx9Hz549YW1tjeTkZFSvXh3z58/Hnj175Bblk+Xu7g4fHx+MHDkSjo6OiImJQVpaGpo0aYL58+fj9OnTCl1XjI2NcfDgQYwbNw6Ojo5IT0+HhYUFRo0ahdOnT8stzCbrp59+wqpVq9CyZUsYGxvj+fPnyM7OhqurK+bPn48jR47IzTpUWIaGhvj999+xfv16ucXmpC00x44dw2effaaw35AhQzBo0CBYWVkhLi6uSN3A3hU2NjY4efIkvv76azg7OyM+Ph5ZWVnw8PDAoUOH0Lx5cwCK15G1tTW8vb2xZMkSNGrUCCkpKUhISECdOnUwdepUnD17Vty3qJR9Xq9evYKVlRX69+9fpM+rb9++4jU/aNAgtTPUAcCqVauwcuVKcVyUNM+jR48qHTvSuXNn+Pr6YuTIkbC1tUVUVBQMDAzQrl07bNiwAXv27NF6xjr6sEiE9+E3DhFRGVWlShVERkbC0dGRAzfVuHjxIoYNG4ZatWrB39+/tKtT6gq6bnhdKbdmzRps2rQJo0aNElckf59kZmaiadOmSExMhK+vr9I1ep4/f47WrVsDyOsGKF2ElNcM6RJbQIiIqNQtXrwYY8aMUTp4GIC4boa6xQPpw/b27VuMHTsWY8aMUbqeR25uLv79918A7+919PfffyMxMRFt2rRRuUAo0buA64AQEVGpEwQBvr6+uH//Puzt7cXuLtLZgnbv3g19fX1xsDqVjI8//hiBgYGF2qdq1aq4dOlSsdWhXbt2eP78eaH2ad26NQ4cOICXL18iNDQUb9++xYYNG+Do6AggbzKDFStWiNeX7OxmZV1WVhYMDQ2RkpKCn376CQCUduEiepcwACEiolI3ffp0+Pr6IiIiAv369YOVlRXMzc0RExODt2/fQk9PD4sXL0bjxo1Lu6rvtR9++KHQq1irGmejrT///FPp9MnqlCtXDgCwYsUKjBw5EpcuXUKrVq1QqVIl6OvrIzo6Gjk5ObC0tMS2bdvE9O8Db29vrFixAunp6UhLS0PTpk3FKXOJ3lUMQIiIqNRVrFgRp0+fxr59+3D8+HE8ffoU0dHRsLGxQcuWLTF27Fi4ubmVdjXfe9WqVSvtKihd30ZTLVu2xLlz57Bz506cP38ekZGRyM3NRY0aNeDp6YlJkyaJrSLvi/LlyyM5ORmGhobo2rUrVqxYoXRKaKJ3CQehExGVIg78JG1wEDoVN14zpEschE5ERERERDrDAISIiIiIiHSGAQgREREREekMB6ETEZWi6OhoAEBkZCSqVKlSyrWhsuLVq1dqt/O6osIq6JoiKk4MQIiISlFOTo74c2RkZCnWhN4nvK6I6F3GAISIqBTp6+sjNzcXenp6qFy5cmlXh8oYe3t7pe/zuiJtqbqmiIoTAxAiolJka2uLyMhIVK5cmVNfUrHhdUVE7zIOQiciIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0hgEIERERERHpDAMQIiIiIiLSGQYgRERERESkMwxAiIiIiIhIZxiAEBERERGRzjAAISIiIiIinWEAQkREREREOsMAhIiIiIiIdIYBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHTGoLQrQEREqiVvaFjaVdDKlsZrS7sK74X5nXsWe56rfP8p8TKIiNRhCwgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0hgEIERERERHpDAMQIiIiIiLSGQYgRERERESkMwxAiIiIiIhIZxiAEBERERGRzjAAISIiIiIinWEAQkREREREOsMAhIiIiIiIdIYBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0hgEIERERERHpDAMQIiIiIiLSGQYgRERERESkMwxAiIiIiIhIZxiAEBERERGRzjAAISIiIiIinWEAQkREREREOsMAhIiIiIiIdIYBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0hgEIERERERHpDAMQIiIiIiLSGQYgRERERESkMwxAiIiIiIhIZxiAEBERERGRzjAAISIiIiIinWEAQkREREREOsMAhIiIiIiIdIYBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdMSjtCryvli5dilevXhWYplKlSjqqUfG4cOECfH19ERERgZSUFJQrVw5OTk7o3Lkz3N3dIZFIilzGxo0bce7cOfTo0QOff/55MdS6eEnrp4qBgQEqVKgAV1dXDB48GI6OjoXa39TUFLa2tnBzc8OgQYNQvnx5ue2+vr7YtGmTXH5OTk5q6/zy5UtMnjxZfD19+nR07txZadoXL17Ax8cHISEhiImJQXp6OkxNTeHg4ABXV1d07969xK/badOmITIyEocPH1a6fe/evfDy8kKnTp0wY8aMEqvHggULcPfuXbXni4iIiAqHAUgJEAQBt2/fRmZmptp0WVlZOqpR0QmCgLVr1yIgIAAAYGJiggoVKiAuLg7BwcHiv+nTp5dyTXXHyMhI4UZcEAQkJycjJiYGZ8+excWLF7FgwQI0bdpUo/2zsrKQmJiIp0+f4unTpwgICMCqVatQsWJFlfXw9/cvMADx9/cv8HhycnLwxx9/4MSJE8jNzQUAmJubw9raGgkJCXjw4AEePHiAo0ePYtKkSejWrVuBeWrj4cOHiIiIgKGhYYnkT0RERKWLAUgJiI2NRWZmJlxcXLBq1arSrk6x+PvvvxEQEAAjIyNMnjwZnp6e0NfXR2ZmJg4dOgQvLy/4+vqiQYMG6Nq1a2lXVyfq1KmDlStXKt0WHh6OTZs24cmTJ1i/fj1++eUXmJqaarR/Tk4Orl69io0bNyIqKgp79uxRGtgZGBggOzsbFy9exNixY9W2Pl28eFFun/wEQcAPP/yAS5cuQU9PD71790bfvn3h4OAgbn/y5Am8vLxw9epVbNmyBfr6+sXaKpCVlYXg4GBs37692PIkIiKidw/HgJQAadcr6c3b++DUqVMAgI8//hhdunSBvr4+gLyn+CNGjIC7uzsA4MiRI6VWx3dJzZo1MWvWLABAUlISbt26pfG++vr6aNu2LXr37g0AuHnzptJ0dnZ2sLe3R0xMDO7fv68yvydPnuD58+ewt7eHnZ2d0jQnTpwQg485c+bgs88+k7t+JRIJatWqhQULFsDT0xMAsH37drx580bj41IlPDwcX375JYYOHYply5YhOjq6yHkSERHRu+uDbQFJTk7GoUOHcO3aNURHR0NPTw+2trZo0aIFBg8eDAsLC7n0KSkp8Pb2xpUrVxATEwMzMzNUrlwZ3bt3h7u7u3hDDvwvAKlcubLG9ZH2affw8MCUKVPg7e2NixcvIjY2FhYWFnBzc8PQoUPVdsXRxNGjR/H777/DwMAAu3fvhpmZmUKawMBArFy5EkZGRvjzzz+RkZGByMhIABADjfzc3Nzg7++PFy9eICUlRWHcgrYSEhKwf/9+BAUFISEhARYWFmjevDlGjRqFChUqKKQ/f/48/v33X4SHhyMjIwMWFhaoW7cu+vfvjwYNGhRLnTRVpUoVWFpaIikpqcDxQMpIgwV1XfXc3d1x4MAB+Pv7qzw+afcrd3d3XLp0SWF7RkYG9u/fDwDo06cP2rZtq7I8iUSCiRMnIiAgAG/fvkVAQAB69eql8TEp8/btWyQlJYnXTHZ2NlJSUrTO79y5c9i8eTMAYOrUqejSpUuR6if16NEjHDhwAPfu3UNGRgbs7e3Rvn17DBgwACYmJsVSBhER0YfggwxA4uPjMWfOHERHR0NfXx/W1tbIzc3F8+fP8fz5c1y6dAmrV68Wb/ZfvnyJb7/9VgxUrK2tkZqaitDQUISGhuLChQv49ttvoaenJ6YHtGsBSU1Nxdy5c/H06VOYm5vD3Nwc8fHxOH36NAIDA7Fs2TJUr15d62P38PDAH3/8gezsbAQFBaFjx44KaaTjPNq0aYNy5cqJN88SiUTl4GPZAExZFx9txMfHY/bs2YiOjoaZmRksLS0RFxcHHx8f3L17Fxs3bpTr1rR161acOXMGAGBhYQEbGxvEx8fjypUruHr1KqZPny4+vdeVnJwcAPLnR1NhYWEAgNq1a6tMIw1ALl26hE8//VShHEEQxM9TVQASFBSE5ORkSCQS9O/fv8B6WVhYYM2aNUhLS4ONjU1hDkmp+vXr488//xRf37lzBwsXLtQqr5IKPgIDA7Flyxbk5OTAxsYGenp6ePbsGfbu3YsrV65g+fLlMDc3L5ayiIiI3ncfZACyd+9eREdHo0GDBpg7d674JD0uLg7r16/HnTt38Ndff2HatGnIysrCihUrEB0djSZNmmD69OliYBIQEID169fj5s2b8Pf3F2/mpTfsqampWLlyJe7fv4/U1FRYWFjAxcUF/fr1Q926dZXW7fr16zA3N8d3330nDlx+8eIF1qxZg4iICHz//fdi/3ttSGdnunXrFq5cuaIQgGRkZCAoKAgA0KlTJwB53Yn2798PiUSistzLly8DACwtLWFpaalV3fK7du0a7O3tsXz5cjRu3BgAEBoaiiVLluDVq1fw9/dH9+7dxffPnDkDIyMjfPPNN2jSpAmAvNaDv//+Gzt37sSOHTvQqlUrlCtXrljqV5D79++LT/LVBRGyMjMzER0djXPnzsHPzw/GxsYYO3asyvTVqlVDjRo1EBERgeDgYDRv3lyhDtHR0ahevTqqVaumNI+7d+8CyAuYNZ3dqlatWhql0yXZ4OPLL78s1vEpV69eRYMGDTB16lRUqVIFQF7XuDVr1iA8PBzbt28Xu9wRERGReh9kACLtL+/u7i7XjadixYr47LPPsHTpUrHLkZ+fH54/fw4rKyvMmzdP7ua1ffv2+O+//3DkyBFcunRJIQD58ccfAQDW1tYoV64c4uPjcfHiRVy6dAkjR47ERx99pLR+U6ZMkZs1qUqVKliwYAE+//xzREZG4urVq2q7yRTE09MTt27dws2bN5GRkQFjY2Nx240bN5Ceng5ra2u4uroCAPT09BQGUMs6duyY+JS9e/fuxTIVr7TcJUuWyLUkNWjQAG3atIGfnx9CQ0PFAET6mdaoUUMMPgDA0NAQAwcOREhICF68eIFnz56hXr16xVI/ZXJychAfH4/r16/Dy8sLQN7NurLuUXfv3kW/fv1U5mVmZobvvvuuwBmu3N3dERERAX9/f4UARNr9qkOHDir3j4uLAwCF6YLLkpIMPgDA1tYWS5Ysketq1axZM4wZMwY///wzAgICMH78eJVdJPfs2YO9e/cq3RYbG1usdSUiInrXfZABiLSrxKlTp+Dq6ip341WtWjX8+uuv4mvpk/0OHToofXLes2dPWFlZyY0Zef36NYC8Lkzjx4+Hvb09gLyuWb/++iuuX7+O3bt3w97eXuHG0MzMTGlwYW9vj0aNGuHWrVu4fft2kQKQNm3awNTUFOnp6bhx44ZcXtLZkjp27Ch2KVMlJiYG27dvx7Vr1wAALi4uGDp0qNb1yq9OnTpKu7FJx0YkJiaK70nP/+PHj3Hu3Dl4enrKBUJLliwptnpJFRRAAHnB59dff600KFM2DW9ubi5SUlKQnJyM1NRULFu2DFOmTFH7eXfo0AG7d+9GYGAgMjMzYWRkBCAvGJJ2uVI1dgfIG4MBQG2Q+S6TBh+5ubkltl5Hly5dlI7z6Ny5M/744w+8ffsWoaGhKgO91NRUlYPrpVMeExERfSg+yABk1KhRWLp0KZ49e4bPP/8cNWvWhIuLCxo0aIBGjRrJBRPh4eEA8vqpK2Nvb4+BAweKr3NycjB16lQYGhqidevWcjeeDg4O+Oabb7BgwQKEhobCy8tL4YalVq1aKm/8a9SogVu3biEmJkbrYwcAY2NjtG7dGn5+frhy5Yp4c/v27Vtcv34dwP+6XymTkZGBI0eO4PDhw8jIyIBEIkH37t0xceLEYl27QdUgfukNtuzgbHd3d5w5cwYPHz7Exo0bsWvXLjRs2BD169dH48aNVXY/KgplAQSQN9WtlZUVGjVqhJ49e6ocG6BuGt+XL19iz549CAgIwJo1a7Bq1SqV16CdnR3q1q2LsLAwBAUFoV27dgCA27dvIykpCXXq1BGDYGWkg7/L0ro0Unfv3sX58+fFm3hBEEqkHFXjroyNjWFnZ4enT5+qbckwMzODra2t0m0FBfpERETvmw8yAGnYsCG2bNmCv//+G1evXsWTJ0/w5MkTnDhxAnp6enB1dcWECRNQvXp1JCcnAwCsrKw0yltfX1/t02Y9PT1069YNoaGheP78OVJTU+VmolI3kFXaAlMcg7w9PT3h5+eH69evIysrC4aGhggKCkJGRgacnZ1V3rDfuHED27ZtE5/mOjk54dNPP4WLi0uR65SfbNcwTdKuWrUKvr6+8Pf3R1hYGC5evCi26Njb22Pw4MFil63ioC6AKCoHBwfMmjULkZGRCA8Px7Fjx1QGIEBeABYWFgZ/f38xANGk+xWQ10oDAFFRURrX78mTJ4iOjoaVlVWJdmkriHRiiAYNGiA0NBQ7d+5EixYtNP6+akoa9Coj/c6qC+BGjRqFUaNGKd1WpUoVscsnERHRh+CDDECAvD7dEyZMwIQJExAXF4f79+8jODgYly9fxq1bt7Bw4UJs375dXLgtPT292MqWHaSdmZkpF4Cou4mRDmgujtl2GjdujIoVKyIuLg4hISFo0aKFeLOuqvXDy8tL7MdeoUIFjBkzBp6enu/ME1xDQ0P06NEDPXr0QEZGBh48eIC7d+8iMDAQERER2Lp1K4yNjZXO/PUukgbD4eHhePbsmdq07du3x6+//oobN24gLS0NhoaGCAwMhJ6eHtq3b692XxcXF5w4cQJPnz5FUlKSRpMIbNy4EREREejVq1epBiAGBgaYNWsWmjZtis8//xxxcXHYsWMHZs+eXazlqJsWOD4+HgAUpu4mIiIi5d6NO0cdSk1NhZ+fnzi2A8gbfN6+fXtMnToVW7duhbm5Od68eYM7d+6I3YCeP3+uNL+QkBAsWLAAP/30EwDgzJkz+PHHH+Hn56eyDtK8TE1NFW72Xrx4oXK/x48fA4A4C09R6OnpiS01V65cQVpaGm7evAkDAwOlLThnzpwRgw8PDw9s27YNnTt3fmeCjxs3bsDPzw8JCQkA8lpEGjdujBEjRmDz5s1i0KFsGtp3WWZmJoCCp/G1srJC48aNkZmZiStXruD69etITU2Fi4tLgWvHuLq6wtTUFDk5Ofj7778LrFNYWBgiIiIAAK1atdLsQEpIhw4d0LZtW5iammLixIkA8sYxSbsSFhfpdy+/lJQUsUtkzZo1i7VMIiKi99W7cfeoQ5mZmdiwYQPWrFmDpKQkhe0VKlQQn2Tm5uaiRYsWAAAfHx+l/cuPHz+Ou3fvijeIiYmJ8PHxwb59+5R2lcrKyhJXFW/ZsqXCDfzLly8RGhqqsF94eLj4vuwMWUUhXRPj6tWr4gDmFi1aKDzJzcnJwZ49ewDk3fB99dVXOpvKVlPHjx/Hhg0bcP78eaXbpV3KSmqMQEnIysoSB/ir634l5eHhASCv65Wm3a+AvPEJ0vU/Dh8+LE7Lq0xaWpoYbNepU0duxrHSIDvGqn379uJ3Y9u2bcXaannx4kVkZGQovH/27FlkZWWhUqVKGk+1TERE9KH74AKQChUqwNnZGbm5uVi/fr3czDRpaWn466+/EBkZCRMTEzRs2BB9+vRB+fLlERkZKXdTk5WVhT179iAoKAh6enro0aMHgLzuS8bGxoiKisLq1avlBozHxcVh7dq1iIqKgpGRkcoZo9avXy8uQgcADx8+xIoVK5Cbm4vGjRurXEOksGrUqIGaNWvizZs3YoChrPuVdDCziYkJpkyZUmzT7Banli1bAgAOHTqEGzduiIGGIAi4desWjh8/DgBiQPmui4qKwqpVqxAbGwsjIyONFghs3bo1DA0NERISgqCgIBgYGGg8W9qQIUPQqFEjZGdnY8mSJfDy8hKn5wXygtBbt25h7ty5iIiIgLm5Ob766qt37lr47LPPYGhoiJiYGPGaLg5xcXFYtWqV3Pc5KCgI+/btAwAMHTr0nWkNJCIietd9kGNApkyZgoULF+LWrVv45JNPYG1tDQMDA8THxyM7Oxt6enqYMmWK2BIwa9YsrFy5EqdPn4avry8qVKggppVIJBg/frw4S06lSpUwc+ZMrF+/HlevXsW1a9fELjBxcXEQBAEGBgaYOXOm0q5UNWvWRGpqKubMmQNLS0sYGBiIN4L29vaYOXNmsZ6Ljh07Ijw8HLGxsTA3N1d6g/7ff/8ByGsR0qRv/bZt24q1jpro1q0b/P39cf/+fXz33XcoV64cLCws8ObNG6SlpQEAmjdvjq5du+q8bqo8fPgQU6ZMUXg/PT1dHFdgZGSEuXPnarRGh5mZGZo3b662NUsVIyMjLFy4EFu2bEFAQAD27t2LvXv3wtLSEiYmJkhMTBRbAKpXr4758+crnSK5tDk4OGDQoEHYv38/Tp48CQ8PD9SpU6fI+fbs2RNnzpzBp59+Cmtra2RkZIgTVHTu3Pmduq6IiIjedR9kAFK7dm2sX78e3t7euHv3LuLj45GbmwsrKyvUr19fYaXyZs2aYcOGDThw4ABu376NuLg4lC9fHvXr10f//v0VZoBq27YtnJyccPToUdy8eROxsbEwMDCAo6MjGjdujH79+qm8ebOyssKSJUuwd+9eBAUFISkpCba2tmjbti0+/vhjccrU4uLh4YFdu3YhNzcX7u7uMDBQvCSkN8OZmZnv7Gw9hoaGWLZsGY4fP44rV64gMjIS0dHRMDU1Rf369eHh4YHu3btrvYJ8SVB1Pk1NTVGtWjU0adIE/fv313h1ciBvNqzAwEAAmnW/klWuXDnMmTMHffr0gY+PD+7fv4+4uDikpaXB0tISTZs2Rdu2bdGhQ4d36jzm99FHH+HChQuIiorCli1bsGHDhiLXt02bNujQoQO8vLzw+PFj5OTkoE6dOujZs2eJrDtCRET0PpMIZalT/Hts79698PLyQtOmTfHdd9+VdnWISEek0/A6OjoqnYQieUPDUqhV0W1pvLa0q/BemN+5p1b7qbuuVvn+UyxlEBFpi52WiYiIiIhIZz7ILljvg3PnzmHz5s2F3m/58uVo2LDkn6hOmjRJboC/Jho2bIjly5eXUI3+510/d2XN3bt38c033xR6v2nTpqlcc6Y4ffPNN2pn9lLG1tYWv/zySwnViIiI6MPGAKSMatmyJTZt2lTo/ezs7EqgNooWL15c6BXbC7PyeVG86+eurHF2dtbqfBa0PklxmTp1qtIpdNVRNhaKiIiIigf/ypZR5cuXL/YB6cVJk1mbSsu7fu7KGhMTE3EWuHeRvb19aVeBiIiIZDAAeUeMGDECI0aMKO1qEBERERGVKA5CJyIiIiIinWEAQkREREREOsMAhIiIiIiIdIYBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdMSgogb+/f4kV7u7uXmJ5ExERERHRu6fAAKRjx46QSCTFXrBEIkF2dnax50tERERERO+uAgMQABAEoaTrQUREREREH4ACA5CdO3eq3JaWloZFixYhISEB+vr66NatGzw8PFCrVi2UL18e6enpePXqFYKCgnDs2DHEx8fD0tISW7ZsQb169Yr1QIiIiIiI6N1XYAAyduxYpe9nZWWha9euiI+PR7169XDo0CE0aNBAadrJkyfjxx9/xIIFC7B582Z88cUXuHz5ctFqTkREREREZY7Ws2D99ttv8Pf3h5WVFc6ePasy+JAqV64cNm7ciKlTp+LNmzcYOXKktkUTEREREVEZpXUAsnPnTkgkEowcORIODg4a7/ftt99CIpHg9u3buHbtmrbFExERERFRGaR1APLo0SMAQJ06dQq1n42NDaysrAAAt27d0rZ4IiIiIiIqg7QOQLKysgAAr169KtR+mZmZePPmDQAgKSlJ2+KJiIiIiKgM0joAcXJygiAI2L9/PzIzMzXez9vbGzk5OQCA6tWra1s8ERERERGVQVoHIAMHDgQAREREYPz48RotKnj37l3MnDkTAGBqaoqePXtqWzwREREREZVBWgcgM2bMQNWqVQEAXl5eaNSoEXbs2IGIiAi5dGlpabhw4QImT54MNzc3REdHQyKRYPHixbCwsChS5YmIiIiIqGzRaCV0ZSwtLXHy5En06dMHz549w8OHDzF58mQAgJGREczNzZGdnY03b96IK6lL/580aRJmz55dDNUnIiIiIqKyROsWEABo2LAhbt26halTp8LQ0BCCIEAQBGRkZCA2NhaJiYnIzc0V37exscGvv/6Kn3/+ubjqT0REREREZYjWLSBSFSpUwObNm7F06VIcPnwYAQEBCAsLQ2JiIiQSCaytreHi4gJPT08MHDgQxsbGxVFvIiIiIiIqg4ocgEhZWVlh4sSJmDhxYnFlSURERERE75kidcEiIiIiIiIqjAJbQB4+fCj+LLvquez72irsKupERERERFS2FRiA1KtXDxKJBBKJRG6tD+n72sqfHxERERERvf80GgMinT5X0/eJiIiIiFRZ5ftPaVehUOZ35uLZxanAAGTs2LGFep+IiIiIiEiVAgOQnTt3Fup9IiIiIiIiVd6JWbCOHTuGP//8s7SrQUREREREJeydCEDmzZuH8ePHl3Y1iIiIiIiohL0TAQgREREREX0YGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0hgEIERERERHpDAMQIiIiIqJCGjduHCQSCZYsWVLiZUVFRWHYsGGwtbWFvr4+li5dWuJllqQCV0InIiIiIqLSs3jxYuzfvx8AUK1aNVhbW5dyjYqGAQgRERER0Tvs0aNHAIDPPvsMP//8cynXpujYBYuIiIiI6B2Wk5MDIK/1433AAISIiIiIqAgePXqE0aNHw97eHiYmJqhduzZmzZqFuLg4pel9fHzQv39/2NnZwcTEBE5OTvj888/x8OFDuXRLliyBRCLBhQsXAAALFy5UOu7k9u3bGDNmDKpVqwZjY2PY2NigV69eOH78uNLya9SoAYlEgoCAAFy8eBHt27eHqakpjh49KpcuKCgIw4cPh6OjI4yNjVG1alWMHTsW169f1+5E/T8GIEREREREWgoMDESTJk2wZ88eSCQSVKxYEY8ePcK6devQrFkzPHnyRC79zJkz0a1bNxw/fhxJSUmwt7fHy5cvsW3bNjRu3Bi7du0S09rY2KBu3bowNTUFAFSqVAl169aFjY2NmObXX39Fs2bNsHv3bsTExMDR0RGZmZn4559/0L9/f4wePVpsQcnP29sbnTp1wrVr1+Dg4IBy5cqJ2zZs2IBWrVrBy8sLMTExqFy5MuLj4/Hnn3+iVatWWLlypdbnjAEIEREREZGWzpw5gxo1auDatWt49eoVIiMjcfXqVVSpUgXPnj3DqFGjxLSbNm3Cxo0bUaFCBezduxepqamIiIhAfHw8VqxYgYyMDEycOBHBwcEAgKlTpyIsLAwtW7YEAHz11VcICwvD1KlTAQABAQH47LPPkJOTg6VLlyIuLg5PnjxBYmIiDh8+DCsrK+zZswfffvut0rpv2LABI0aMQExMDB4/foxu3boBAI4dO4avvvoKxsbG2LRpk1jPhIQE/Prrr9DX18fChQtx4sQJrc4ZAxAiIiIiIi2Zm5vDx8cHbm5u4nstW7bE9u3bAQBXrlxBYGAgkpOTsXjxYgDAzp07MXz4cOjr6wMAypUrhwULFmDcuHHIycnBunXrNCp7/vz5yM3NxYgRI7Bo0SKxBUNPTw+DBg3C1q1bAeQFGgkJCQr7165dG7/99hssLS3F93JzczFr1iwAwPfff49p06bB0NAQAGBkZISJEydi4cKFAIA1a9ZofqJkMAAhIiIiItLSkCFDULlyZYX3e/bsiVq1agEALly4gJMnTyIpKQlWVlbo37+/0rxGjBgBADh37lyB5UZFRSEgIAAAMGPGDKVpPvroI1hZWSE9PV0cRyJr9OjRMDCQnxT32rVr4qxbY8eOVVvPK1euID09vcC65vdOTMM7YMAAREVFlXY1iIiIiIgKpVGjRkrfl0gkaNCgAR4/fowXL16IA9LT0tJQr149pftkZmYCAF6+fIns7GyF4ECWtJuWkZERmjdvrjSNoaEhnJ2dcf36dYWxKADg5OSk8N7NmzfF+rdu3VppvoIgAMibnevly5dioKWpEglABEFAeno6jIyM1J44qVWrVpVENYiIiIiISpR0gLgy0gUDMzIy8PbtWwB5QcaDBw8KzDctLQ0WFhYqt8fHxwMAKleuDD091Z2apN2ypOXLknYBkyXtqiUIgkb1TE1NLTBNfsXSBSsuLg6rV69Gly5dYGtrCwMDA5ibm+P3338HkDfV2Pjx43H16tXiKI6IiIiI6J2gbGyF1MuXLwEAFStWFAOBJk2aQBCEAv+pCz4AwNjYGMD/AhFVIiMjAUBu5ix1pPW0srLSqJ6NGzfWKF9ZRQ5Adu/eDScnJyxYsAB+fn6IjY0Vm2Wk4uPjsWvXLrRt2xYjRoxASkpKUYslIiIiIip1N27cUPp+Tk4O7t27ByAv6Khbty4A4MmTJyqnxX358iX27Nmj0exSzs7OAIDk5GREREQoTRMZGYnw8HAAQNOmTQvME4BYz8TERMTGxipNk5SUhD179mDfvn0a5ZlfkQKQXbt2Ydy4cUhJSYEgCDAxMUGLFi0U0pUvXx4SiQSCIGD//v3o3r07srOzi1I0EREREVGpO336tNjSIevYsWN4+fIlypUrh549e6JXr17Q19fHmzdv4OXlpTSvBQsWYPTo0Th8+HCB5TZq1AhVqlQBAGzcuFFpmp07dyI3Nxc1atRQOU4kP3d3d7H1RTqTV34bNmzA6NGjVW4viNYBSFRUFKZPnw5BEGBubo7t27cjLi4O165dU0jbu3dvPHjwAJ6enhAEAYGBgVi0aJG2RRMRERERvRNSU1PRr18/hIWFie9dvnxZXKvjq6++goWFBWrUqIGJEycCyFuM0NfXV0yfnJyMefPmYdeuXTAxMRGnuVVHT08P33zzDQBgy5Yt2Lp1qziIPScnB15eXlixYgUA4LvvvlM7TkRW+fLlMW/ePADAypUrceDAAeTm5gLIG0eyfv16rFixAhKJBMuWLdMoz/y0HoT+66+/4s2bNzA0NMS///4rLpCiirOzM86cOYMuXbrA398fP//8MxYvXgwTExNtq0BEREREVKomTJgALy8vNGjQAPb29hAEQZzdtWvXrnIP3Tdt2oQXL17g1KlT6NKlCypWrAgLCwu8ePECWVlZKF++PP766y/Url1bo7I/++wzBAcH4+eff8bUqVMxZ84c2NvbIyYmBsnJyQCAadOmYcyYMYU6pnnz5uHx48f47bffMHToUFhaWqJixYp4+fIl3r59C0NDQ/z000/o0KFDofKV0roF5MiRI5BIJOjdu3eBwYeUgYEBvv/+ewDAmzdv4O/vr23xRERERESlrk2bNrh8+TL69u2LzMxMJCUlwdXVFevXr8epU6dgZGQkpjUxMcGJEyewc+dOtGvXDhkZGXj9+jVq1qyJqVOnIiQkBP369StU+du2bcORI0fQrVs3mJiY4Pnz5zAzM0P//v3xzz//YNOmTYU+JolEgl9//RVHjx5F165dAeSNT3FwcMC4ceNw7do1TJ48udD5SmndAiKdS1jT4EOqdevWMDExQUZGBp4+fapt8UREREREpeaPP/7AH3/8Ib4+duyYRvvp6elh3LhxGDdunMZlnT9/Xu32AQMGYMCAARrnp2rQen79+/dXuWhiUWjdAiLtCyadqqswpN2uCpo2jIiIiIiI3i9aByDVqlUDANy+fbtQ+8XExCAxMREAYGtrq23xRERERERUBmkdgPTs2ROCIMDLywvPnz/XeL+tW7eKP3t4eGhbPBERERERlUFaByBTp05FuXLlkJ6ejp49e+Lx48dq0+fm5mLdunVYvnw5JBIJunXrBicnJ22LJyIiIiKiMkjrQejVqlXDxo0bMWnSJNy/fx8uLi7o27cvXF1dxTSXLl1Ceno6QkNDcfLkSbx69QqCIMDa2hpbtmwplgMgIiIiIqKyQ+sABAA++eQTAMD06dORnp4Ob29veHt7QyKRAAD27NmDPXv2AAAEQQAAVK5cGUeOHEGtWrWKUjQREREREZVBWnfBkvrkk08QEhKCsWPHwtjYGIIgKP1nbm6OadOmISQkpNBT9xIRERER0fuhSC0gUs7Ozti5cye2bduGa9eu4cGDB4iPj4dEIoG1tTVcXFzQvHlzuYVYiIiIiIjow1MsAYiUiYkJ3N3d4e7uXpzZEhF9sMxn3i3tKmhlfmlXgFSa37lnaVeBiD5wRe6CRUREREREpKkCW0D+/PPPEit8zJgxJZY3ERERERG9ewoMQMaNGyfOalWcJBIJAxAiIiIiog+MRmNApFPoEhERERERFUWBAYifn58u6kFERERERB+AAgMQDw8PXdSDiIiIiIg+AMU6DS8RERERUUE4HfSHrdgCkDdv3uDixYu4desWYmNj8fbtW1hZWcHa2hqurq5o164dypcvX1zFERERERFRGVTkACQ5ORnz58/Hrl27kJaWpjKdvr4+hgwZgkWLFqF+/fpFLZaIiIiIiMqgIi1EGB4eDldXV2zbtg2pqakQBEHlv+zsbOzfvx/NmjXD/v37i6v+RERERERUhmjdAvL27Vv06NEDERERAIBy5cph6NCh6NSpE2rUqAErKyukp6fj5cuXCAoKgpeXFx4/foyMjAyMHDkSFhYW6NmT/f+IiIiIiD4kWgcgmzdvxn///QeJRAJ3d3d4eXnBzs5Oadp+/fphyZIlWLlyJRYvXozc3Fx8+eWXePjwIfT0itQIQ0REREREZYjWAYi0G5WtrS1OnjyJcuXKqU2vr6+PRYsW4c2bN1i3bh3Cw8Ph7++Pjh07alsFIiIiIiqDkjc0LO0qFIr5zLulXYX3itbND9LWjxEjRhQYfMiaO3cuJBIJACAkJETb4omIiIiIqAzSOgAxNjYGAFSrVq1Q+9nY2MDS0hIAkJWVpW3xRERERERUBmkdgNSpUwcA8PLly0Ltl5GRgaSkJABA9erVtS2eiIiIiIjKIK0DkAkTJkAQBHh5eRWqJePw4cMQBAFmZmbo1q2btsUTEREREVEZpHUAMmbMGLRo0QLPnz/HRx99hJSUlAL3uXfvHmbMmAGJRIL58+eLXbGIiIiIiOjDoPUsWFlZWfDy8sLAgQNx4sQJ1KxZExMmTICnpycaNGgAKysrGBkZIS4uDnfv3sXRo0exc+dOZGVlYfjw4RgxYgSePXumMv/Cji0hIiIiIqJ3n0QQBEGbHfX19eVeC4Igzm6liiZpAEAikSA7O1ubahERlSlVqlRBZGQkHB0d8eLFC4XtZW2qyi2N15Z2Fd4r8ztrt2Cvuutqle8/xVYOkbbK2u82TsNbvLRuAVEWt2gSy2gZ7xARERER0XtA6wBk8eLFxVkPIiIiIiL6ADAAISIiIiIindF6FiwiIiIiIiq8Xbt2wdXVFaampnLjqo8ePYolS5bg77//LsXalTwGIEREREREOvLixQtMmDABt2/fhoGBAWrVqiVuO3r0KL777rv3PgDRuguWVEREBLy9vRESEoLY2Fikp6drtJ9EIoGvr29RiyciIiIiKjPCw8ORm5sLAPjvv/9gb29fyjXSvSIFIGvWrMGiRYsKPWWuptPxEhERERG9T3JycgAAhoaGH2TwARShC9axY8cwb948ZGVlQRCEQv0jIiIiInofBAQEYMSIEXB2doapqSns7e3h5uaGlStX4vXr13JpJRIJPD09AeQt6i2RSCCRSPDHH39AIpFg165dAIDt27dDIpFg3Lhxcvvn5OTgl19+Qfv27VGhQgWYmZnB1dUVS5cuRVJSkkLdlixZAolEgk8++QRxcXGYNGkS7OzsMHDgwJI5GRrSugXkxx9/BJB3IlesWIFRo0bBxsaGLRtERERE9EFYuXIlFi5cCAAwMDCAo6MjkpKScP36dVy/fh0bN25EYGAgnJycAAB169ZFWloanj9/DolEgjp16gAALC0tUbduXbx69Qpv3ryBlZUV7OzsULlyZbGspKQk9OvXD/7+/uI+FStWxN27d3H79m389NNPOHPmDFxdXRXqGRcXh7Zt2+Lhw4eoXLky7OzsSvrUqKV1C0hISAgkEgn69euHefPmoUqVKjAxMYGxsbHG/4iIiIiIyqLY2FhxWYqVK1ciLS0NERERSEhIwMWLF2FnZ4eYmBhs2LBB3CcsLAx//vknAMDIyAhhYWEICwvDwIEDxf8BYOjQoQgLC8OqVavEfceNGwd/f380bNgQgYGBSExMxLNnzxAZGYkhQ4bg9evX6NOnj9Lx2EePHkVWVhZu3LiBly9f4ueffy7JU1MgrQOQ1NRUAECHDh2KrTJERERERGXBzZs3kZ2dDTc3N8yfPx+Ghobitvbt2+OTTz4BADx58qTIZfn7++Po0aOwsLDAyZMn0apVK3Gbvb099u3bh9q1a+PFixfYu3ev0jx27tyJZs2aFbkuxUHrAKRq1aoA/heIEBERERF9KDp06IDnz5/j9OnTSrdHRUUB+N+g86KQBhWdOnVCtWrVFLYbGBjgo48+AgCcO3dOYbuTkxM8PDyKXI/iovUYkN69e2Pjxo04dOgQFi1aVJx1IiIiIiJ6p5mamqJKlSpIT0/HuXPnEBwcjKdPn+LZs2d48OAB7t+/X2xl3bx5EwBw/vx51KtXT2maxMREAMCzZ88UtknHoLwrtA5A5syZg127duHu3buYOnUqfvzxRw5AJyIiIqIPgiAI2LBhA5YsWYLk5GTxfVtbW7i5uaFatWo4c+ZMsZSVkJAAIC/IkAYaqijrnSS72vq7QOsAxN7eHidOnED//v2xbds2nD59GgMGDICzszPKlSunUR5jxozRtngiIiIiolKzatUqLFy4EMbGxli+fDm6deuGunXrwsLCAkDeFLjFFYBI761nzJghN6i9rCrSQoRpaWkwNjaGIAgIDw8v1AmRSCQMQIiIiIioTNq2bRsAYPXq1Zg+fbrC9ri4uGIrq27durh9+zb+++8/lWlu3bqFe/fuoU6dOmjZsmWxlV0StB6Efvv2bfTu3RuvXr2CRCIp9GKEXJCQiIiIiMoq6SKDdevWVdiWlJQEb2/vYiurb9++AIAzZ84gIiJCYXtGRgaGDx+O0aNHIzQ0tNjKLSlat4AsX74cWVlZAIDatWujf//+qFy5ssbdr4iIiIiIyioXFxcEBwdj9erVaNGiBWxsbJCTk4Nz585h1qxZ4ixYytblUMXU1BQA8OLFC7n3hw0bhjVr1uDu3bsYNmwYdu/ejdq1awMAIiIi8Pnnn+PBgwdo0KABRowYUUxHWHK0DkCuXbsGiUSCxo0bIzAwkAsLEhEREdEHY8WKFejbty/Onz8PBwcHODo6IiYmBqmpqahfvz527tyJsWPH4uLFi6hRowZCQkJgaWmpNs8mTZoAAE6ePIlq1aphxIgR+P7772FoaIhjx46he/fuuHr1KurUqYMqVapAIpHg+fPnAIBatWrh6NGjMDIyKulDLzKtu2DFxMQAyIvIGHwQERER0YekV69e8PHxgYeHBwwNDREXF4d69eph3bp1uHXrFkaPHo1PPvkEpqamePv2rUYzUY0ZMwajRo2CtbU1oqOj5YYsODk54caNG1iyZAkaNGiA2NhYpKSkoFmzZlixYgVu3boltoq86ySCloMxGjRogAcPHmDt2rX46quvirteREQfhCpVqiAyMhKOjo4KTe4AkLyhYSnUSntbGq8t7Sq8V+Z37qnVfuquq1W+/xRbOUTaKmu/28xn3i3tKrxXtG4BGTBgAARBgI+PT3HWh4iIiIiI3mNaByBfffUV7Ozs8O+//+LQoUPFWSciIiIiInpPaR2A2NjY4J9//oGNjQ1GjBiB2bNn4969e5xel4iIiIiIVNJ6FqwGDRqIP2dnZ2P9+vVYv349jIyMUKFCBZiYmKjdXyKR4PHjx9oWT0REREREZZDWAUhYWJi4ACEA8f+MjAxx3mN1JBKJtkUTEREREVEZpXUA4u7uziCCiIiIiIgKResA5Pz588VYDSIiIiIi+hBoPQidiIiIiIiosHQegAiCgEmTJmHChAm4d++erosnIiIiIqJSpHUXrKI4cOAAkpOT0ahRI7i4uJRGFYiIiIiIqBQUOQDx9/fHnj178PTpU2RlZRWYPioqCm/evIFEIkF2dnZRiyciIiIiojKkSAHIunXrMGfOnELtI52u18jICH369ClK8UREREREVMZoPQbk4cOHmDdvHgRBgCAIsLGxQd26dcXt5cuXR7Vq1VC1alWYmJiI6czNzTFt2jRcu3YN9evXL5aDICIiIiKiskHrAOSXX35BTk4OJBIJfvvtN7x+/RqhoaHYuXMnBEFAjRo1EB4ejoiICKSmpsLPzw/16tVDSkoKbGxs0KhRo+I8DiIiIiIiKgO0DkDOnz8PiUQCd3d3jB8/Xnx/+PDh0NfXx927dxERESG+7+HhgYsXL8LW1haLFy+Gr69vkSpORERERERlj9ZjQB4/fgwA6NChg9z7hoaGqFKlCp49e4br16+jRo0a4raKFSti/vz5mDFjBr7++msEBwdrWzwRERERlVHmM++WdhWoFGndApKSkgIAsLW1Vdjm5OQEAHjw4IHCtqFDhwIA7ty5g5s3b2pbPBERERERlUFaByAWFhYAgISEBIVtNWvWhCAIePjwocI2Ozs7lC9fHgAQEhKibfFERERERFQGaR2AuLi4QBAE/PPPPwrbpLNhXbt2TWFbVlYW3r59CwCIjo7WtngiIiIiIiqDtA5ABgwYAAC4evUqZs2ahbS0NHGbu7s7gLypei9cuCC3359//ikuQGhjY6Nt8UREREREVAZpHYBMmjRJHP+xYcMGVKxYEdu3bwcAtGjRApUrVwYADBo0CGvXrsWxY8ewaNEiTJ06Na9gPT107dq1qPUnIiIiIqIyROtZsMqXL49jx45hwIABeP36NTIyMhAXFwcA0NfXx8aNGzF06FAkJiZi3rx54n7SldC/+OILVKtWrYjVJyIiIiKiskTrAAQAWrVqhYcPH+Lw4cO4ceOG3OKCH330Ee7fv4/ly5eLXa6AvJaPyZMnY/369UUpmoiIiIiIyqAiBSAAYG5ujnHjxmHcuHEK27799ltMmDABPj4+iIqKQoUKFdC1a1fUqlWrqMUSEREREVEZVOQApCBVqlSRWymdiIiIiIg+XFoPQi+MN2/eIDY2VhdFERERERHRO6xYAhA/Pz8sW7YMUVFRcu//+++/aNiwISpUqAA7OzvY29tj0aJFSE9PL45iiYiIiIiojClSABIbGwtPT0906dIFS5YsQXx8vLjt6tWr6Nu3L+7fvw9BECAIAqKjo7Fy5Up4eHggNTW1yJUnIiIiIqKyResAJDs7G507d4a/v78YYOjr64vblyxZgqysLABA69atMXv2bLRp0waCIODGjRv46quvil57IiIiIiIqU7QOQHbs2IE7d+4AAMaPH4/Xr1+jbt26APJaRnx8fCCRSNC+fXtcvHgRq1evxqVLl9C3b18IgoBdu3bJtZgQEREREdH7T+sAxNvbGwDg4uKC3377DZUqVRK3nT59Grm5uQDyFhyUbRlZuHAhACArKwsBAQHaFk9ERERERGWQ1gHI3bt3IZFI0LdvX4VtZ8+eBZC3InrPnj3ltrVo0QIGBnmz/4aHh2tbPBERERERlUFaByDS7lOVK1dW2Obn5weJRIKmTZvC3NxcvkA9PVhYWAAAB6ITEREREX1gtA5AzMzMAABJSUly79+/fx/Pnz8HAHh6eirsl5GRIe5Tvnx5bYsnIiIiIqIySOsApEGDBgDyWjtk7dixQ/y5a9euCvudPn0aOTk5AICaNWtqWzwREREREZVBWgcgAwYMgCAI8PPzw/z583Hr1i38+OOP+PHHHwEAFStWRMeOHeX2efbsGb7++msAgKGhIdq3b699zYmIiIiIqMzROgCZMmUKatasCUEQsGbNGrRo0QIzZsxATk4OJBKJ3OxXISEh6N+/P+rVq4fw8HBIJBKMHz8eFSpUKLYDISIiIiKid1+RxoCcOXMGderUERciFAQBANCxY0csWLBATPvo0SOcOHECb9++hSAI8PT0xIYNG4peeyIiIiIiKlMMirKzs7Mz7t69C29vbwQGBiIjIwOtWrXCyJEj5db+kEgksLKyQtOmTTF27FiMHj0aEomkyJUnIiIiIqKypUgBCAAYGBjg448/xscff6wyzaBBgzBo0KCiFkVERERERGWc1l2wiIiIiIiICosBCBERERER6QwDECIiIiIi0hkGIEREREREpDMMQIiIiIiISGcYgBARERERkc4wACEiIiIiIp1hAEJERERERDrDAISIiIiIiHSGAQgREREREekMAxAiIiIiItIZBiBERERERKQzDECIiIiIiEhnGIAQEREREZHOMAAhIiIiIiKdYQBCREREREQ6wwCEiIiIiIh0xqC0K1AWLF26FK9evSowTaVKlXRUo+Jx4cIF+Pr6IiIiAikpKShXrhycnJzQuXNnuLu7QyKRFLmMjRs34ty5c+jRowc+//zzYqh18ZLWTxUDAwNUqFABrq6uGDx4MBwdHQu1v6mpKWxtbeHm5oZBgwahfPnyctt9fX2xadMmufycnJzU1vnly5eYPHmy+Hr69Ono3Lmz0rQvXryAj48PQkJCEBMTg/T0dJiamsLBwQGurq7o3r17iV+306ZNQ2RkJA4fPqw2XUJCAo4cOYLr168jOjoa5cqVQ61atdCrVy+4ubkppP/kk08QHR2NFStWoFGjRiVS99evX+PTTz8FABw/frxEyiAiIvrQMAApgCAIuH37NjIzM9Wmy8rK0lGNik4QBKxduxYBAQEAABMTE1SoUAFxcXEIDg4W/02fPr2Ua6o7RkZGCjfigiAgOTkZMTExOHv2LC5evIgFCxagadOmGu2flZWFxMREPH36FE+fPkVAQABWrVqFihUrqqyHv79/gQGIv79/gceTk5ODP/74AydOnEBubi4AwNzcHNbW1khISMCDBw/w4MEDHD16FJMmTUK3bt0KzFMbDx8+REREBAwNDdWme/nyJRYsWID4+Hjo6enB2toa6enpuHHjBm7cuIGBAwdi/PjxJVJHIiIi0i0GIAWIjY1FZmYmXFxcsGrVqtKuTrH4+++/ERAQACMjI0yePBmenp7Q19dHZmYmDh06BC8vL/j6+qJBgwbo2rVraVdXJ+rUqYOVK1cq3RYeHo5NmzbhyZMnWL9+PX755ReYmppqtH9OTg6uXr2KjRs3IioqCnv27FEa2BkYGCA7OxsXL17E2LFj1bY+Xbx4UW6f/ARBwA8//IBLly5BT08PvXv3Rt++feHg4CBuf/LkCby8vHD16lVs2bIF+vr6KltRtJGVlYXg4GBs3769wLSCIGDVqlWIj49H7dq1MXv2bNjb2yM3Nxd+fn7YunUrjhw5gtq1a6N9+/bFVkciIiIqHRwDUgBp1yvpzdv74NSpUwCAjz/+GF26dIG+vj6AvKf4I0aMgLu7OwDgyJEjpVbHd0nNmjUxa9YsAEBSUhJu3bql8b76+vpo27YtevfuDQC4efOm0nR2dnawt7dHTEwM7t+/rzK/J0+e4Pnz57C3t4ednZ3SNCdOnBCDjzlz5uCzzz6Tu34lEglq1aqFBQsWwNPTEwCwfft2vHnzRuPjUiU8PBxffvklhg4dimXLliE6OrrAfQICAvD06VMYGRlh/vz5sLe3BwDo6emhc+fOYuvM3r17i1w/IiIiKn3vRQtIcnIyDh06hGvXriE6Ohp6enqwtbVFixYtMHjwYFhYWMilT0lJgbe3N65cuYKYmBiYmZmhcuXK6N69O9zd3cUbcuB/AUjlypU1rs/evXvh5eUFDw8PTJkyBd7e3rh48SJiY2NhYWEBNzc3DB06VG1XHE0cPXoUv//+OwwMDLB7926YmZkppAkMDMTKlSthZGSEP//8ExkZGYiMjAQAMdDIz83NDf7+/njx4gVSUlIUxi1oKyEhAfv370dQUBASEhJgYWGB5s2bY9SoUahQoYJC+vPnz+Pff/9FeHg4MjIyYGFhgbp166J///5o0KBBsdRJU1WqVIGlpSWSkpIKHA+kjDRYUNdVz93dHQcOHIC/v7/K45N2v3J3d8elS5cUtmdkZGD//v0AgD59+qBt27Yqy5NIJJg4cSICAgLw9u1bBAQEoFevXhofkzJv375FUlKSeM1kZ2cjJSVF7T7SroCtWrWCjY2Nwva2bdvi1KlTePHiBZ4+fYrq1aurzS8rKwurVq3C9evXYWtri5UrV8LW1lbLI/qf3NxcnDlzBv/++y+eP38OQ0NDODs7o1+/fkrHqBAREZFyZT4AiY+Px5w5cxAdHQ19fX1YW1sjNzcXz58/x/Pnz3Hp0iWsXr1avNl/+fIlvv32WzFQsba2RmpqKkJDQxEaGooLFy7g22+/hZ6enpge0K4FJDU1FXPnzsXTp09hbm4Oc3NzxMfH4/Tp0wgMDMSyZcsKvJlSx8PDA3/88Qeys7MRFBSEjh07KqSR3ty1adMG5cqVE2+eJRKJysHHsgGYsi4+2oiPj8fs2bMRHR0NMzMzWFpaIi4uDj4+Prh79y42btwo161p69atOHPmDADAwsICNjY2iI+Px5UrV3D16lVMnz5dfHqvKzk5OQDkz4+mwsLCAAC1a9dWmUYagFy6dAmffvqpQjmCIIifp6oAJCgoCMnJyZBIJOjfv3+B9bKwsMCaNWuQlpam9Oa/sOrXr48///xTfH3nzh0sXLhQZXpBEHD37l0AUDmQvH79+jA0NERWVhYePHig9jtTUsEHAKxZswaXL1+GoaGhOJYmJCQEISEh+PjjjzFq1KhiKYeIiOh9V+YDkL179yI6OhoNGjTA3LlzxSfpcXFxWL9+Pe7cuYO//voL06ZNQ1ZWFlasWIHo6Gg0adIE06dPFwOTgIAArF+/Hjdv3oS/v794My+9YU9NTcXKlStx//59pKamwsLCAi4uLujXrx/q1q2rtG7Xr1+Hubk5vvvuO3Hg8osXL7BmzRpERETg+++/F/vfa0M6O9OtW7dw5coVhQAkIyMDQUFBAIBOnToByOtOtH//fkgkEpXlXr58GQBgaWkJS0tLreqW37Vr12Bvb4/ly5ejcePGAIDQ0FAsWbIEr169gr+/P7p37y6+f+bMGRgZGeGbb75BkyZNAOTdXP7999/YuXMnduzYgVatWqFcuXLFUr+C3L9/X3ySry6IkJWZmYno6GicO3cOfn5+MDY2xtixY1Wmr1atGmrUqIGIiAgEBwejefPmCnWIjo5G9erVUa1aNaV5SG/mHRwcNJ7dqlatWhqlKwkJCQlITk4GAIUZxqQMDQ1hZWWFmJgYta1PssGHnZ0dVqxYUWzBBwBcuXIF/9fevcfZVPb/H3/P+WwOTuMQ43waZzmUQ1KS3NxSxO1bX9GBXymFKGWiOx3ur1TirpuUUyKSqOQwOZNBcqaMoUFjZphhxpzX74957HXbZs+YYc+aTa/n4+HxMHutvdZnr7nU9d7ruq71yCOP6MEHH5Svr68yMzM1b948rVixQosXL1aTJk0cLlAAAADs3fRzQGzj5Tt37mw3jKd8+fJ66qmnVKlSJXPIUXR0tE6dOqWQkBCNGzfObghUx44d9be//U2S7L5ZtnV4PvzwQ23fvl0eHh7y9/dXcnKyNm3apJdeeklLliwptL7hw4fbdUqqV6+ul19+WZ6enoqPj9eOHTtu6PPb7gLs3r1bmZmZdtt27dqly5cvKywsTM2bN5eUP67ez89Pvr6+Do/3zTffmN+y33fffU5Zitd23qioKDN8SFLjxo3VoUMHSfmhw8b2O42IiDDDh5TfEe3bt69atWolf39/nTx50im1FSY3N1fnzp3T999/r7feektSfmfd0fCo/fv3q3fv3nZ/HnroIY0YMUJfffWV/P399c9//vOaK1zZhsU5WunK9lqnTp0KfX9SUpKkwjvzrubK4VlFhV3bkK60tDSH268OH86882Hz97//XYMGDTL/7fj4+GjYsGGqX7++pPwhkQAA4Npu+jsgQUFBkvInVjdv3tyu41WjRg3NmjXL/Nn2zX6nTp0cfnN+//33KyQkxG7OyJ9//ikpfwjTkCFDzAmyp0+f1qxZsxQTE6N58+YpPDy8QMcwICDA4Rj88PBwNW3aVHv27NGvv/5a5Dj9a+nQoYP8/PzMJUuvPJZttaS77rrLHFJWmHPnzunjjz/Wzz//LElq0qSJBgwYcN11Xa1+/foOh7HZ5kZcuHDBfM12/X///XetX79eXbt2tQtCUVFRTqvLxhYgihIWFqYXX3zRYShztAxvXl6eLl26pIsXLyotLU2TJ0/W8OHDi/x9d+rUSfPmzdP27duVlZUlb29vSflhyBaMC5u7I+XPwZBUYJUuV3VlALF9Vkdsn8c2DO5KV4aPihUr6s033yyVZ5v06tXL4es9e/bU0aNHdejQIeXl5Tn8tzZ//vxCJ9EnJiY6tU4AAFzdTR9ABg8erEmTJunkyZMaMWKEatWqpSZNmqhx48Zq2rSpXZiIjY2VlD+m3JHw8HD17dvX/Dk3N1fPPPOMvLy81L59e7uOZ9WqVTVhwgS9/PLLOnjwoBYtWlQggNSpU6fQjn9ERIT27Nmjc+fOXfdnl/K/hW3fvr2io6O1bds2s3ObkZGhmJgYSf8dfuVIZmamvv76ay1dulSZmZlyc3PTfffdp6FDh17z2Q0lUdgkflun88rJ2Z07d9bq1at19OhRTZs2TZ9//rkiIyPVqFEjNWvWrNDhRzfCUYCQ8pe6DQkJUdOmTXX//febgfdqRS3je/r0ac2fP1+bN2/WO++8oylTphTaBitXrqwGDRro8OHD2rlzp+68805J0q+//qqUlBTVr1/fDMGO2O4U3CzPpfH0/O9/gmzPK3HE9nl8fHwKbJs5c6b5RUFGRkaRQeZ6+fv7FxpqbHNSMjIydOnSpQKLXkj5d24KWxGsqM8NAMCt6KYPIJGRkZo+fbpWrlypHTt26Pjx4zp+/Li+/fZbubu7q3nz5nr88cdVs2ZNc6x5SEhIsY7t4eFR5LfN7u7u6t69uw4ePKhTp04pLS3NbiWqwjqrksw7MM6Y5N21a1dFR0crJiZG2dnZ8vLy0s6dO5WZmam6desW2mHftWuXZs6caXaMateurSeeeEJNmjS54Zqu5qjjWNS+U6ZM0bp167Rx40YdPnxYmzZtMu/ohIeHq1+/fuacEWcoKkDcqKpVq2r06NGKj49XbGysvvnmm0IDiJQfwA4fPqyNGzeaAaQ4w6+k/Ls0knT27Nli13f8+HElJCQoJCREDRs2LPb7nOHKFdZs/z4dsd0pcbRa2p9//qnw8HDl5OQoMTFRs2bN0osvvujUOosKNVd+hsKCX0BAQKFDwq51dxIAgFvNTR9AJKlSpUp6/PHH9fjjjyspKUmHDh3SL7/8oq1bt2rPnj165ZVX9PHHH5sPbrt8+bLTzn3luPWsrCy7AFLUt9C2DlVRIaW4mjVrpvLlyyspKUl79+5VmzZtzM56YXc/Fi1aZA4JCQ0N1aOPPqquXbu6TGfIy8tLPXr0UI8ePZSZmakjR45o//792r59u06cOKGPPvpIPj4+Dlf+ckW2MBwbG3vNuSsdO3bUrFmztGvXLqWnp8vLy0vbt2+Xu7v7NR/E16RJE3377beKi4tTSkpKsRYRmDZtmk6cOKGePXtaHkAqV65s/rs8c+aMwwUdcnNzzWFK1atXL7C9Zs2aev3113XkyBFNmTJFGzZsUNeuXdWqVSun1VnUUsLJycmS8leWK+zf8+DBgwtdJat69ermPDUAAP4KXKO3eZ3S0tIUHR1tzu2Q8iefd+zYUc8884w++ugjBQUFKTU1Vfv27TOHAZ06dcrh8fbu3auXX35ZM2bMkCStXr1aH374oaKjowutwXYsPz+/Ap29P/74o9D3/f7775Icd6hKyt3d3bxTs23bNqWnp2v37t3y9PR0eAdn9erVZvjo0qWLZs6cqW7durlM+Ni1a5eio6N1/vx5Sfl3RJo1a6ZBgwbpgw8+MEOHo2VoXVlWVpakay/jGxISombNmikrK0vbtm1TTEyM0tLS1KRJk2s+O6Z58+by8/NTbm6uVq5cec2aDh8+rBMnTkjKfw6H1Tw8PMzQYVvB62rHjh1Tdna23N3dHd6dGzZsmMLCwtShQwe1adNGkjRjxgxzPowz5OTkKC4uzuE229DOatWqlcrwLwAAbjWu0eO8TllZWXrvvff0zjvvKCUlpcD20NBQczx2Xl6e2TlZs2aNDMMosP+KFSu0f/9+s4N44cIFrVmzRl988YXDoVLZ2dnmU8Xbtm1boAN/+vRpu9WdbGJjY83XnbVsp201rB07dpgTmNu0aVNgPHpubq7mz58vKX84zwsvvGDZUrbFtWLFCr333nv66aefHG63DSlz9Dt0VdnZ2eYE/6KGX9l06dJFUv7Qq+IOv5Lyh/rYnv+xdOnSQjv1kpSenm6G7fr169utOGYl2+fauHGj3WIENqtWrZIktWrVyuH8iiv/3T355JPy9vZWQkKCFixY4NQ616xZU+A1wzD0ww8/SNINLSYBAMBfyU0dQEJDQ1W3bl3l5eVp6tSpdpM809PTtWDBAsXHx8vX11eRkZHq1auXAgMDFR8fr5kzZ5pDsbKzszV//nzt3LlT7u7u6tGjh6T84Us+Pj46e/as3n77bbsJ40lJSXr33Xd19uxZeXt7F7pi1NSpU82H0EnS0aNH9c9//lN5eXlq1qxZoc8QKamIiAjVqlVLqampZsBwNPzKNpnZ19dXw4cPd9oyu87Utm1bSdJXX32lXbt2mUHDMAzt2bNHK1askCQzULq6s2fPasqUKUpMTJS3t3exHhDYvn17eXl5ae/evdq5c6c8PT2L3cF96KGH1LRpU+Xk5CgqKkqLFi0yl+eV8kPonj179NJLL+nEiRMKCgrSCy+8UGZt4Z577lGVKlWUkZFhXicp/wuGhQsXasOGDfL09NSjjz56zWOFh4froYcekiR9++23+u2335xW58qVK/XNN9+YQysvX76sjz/+WCdOnFBgYGChq2QBAAB7N/0ckOHDh+uVV17Rnj17zKEYnp6eSk5OVk5Ojtzd3TV8+HDzm9PRo0frzTff1A8//KB169YpNDTU3NfNzU1DhgwxV7WpWLGiRo0apalTp2rHjh36+eefzSEwSUlJMgxDnp6eGjVqlMOhVLVq1VJaWprGjh2r4OBgeXp6mh3B8PBwjRo1yqnX4q677lJsbKwSExMVFBTksIN+7NgxSfl3hMaMGXPNY86cOdOpNRZH9+7dtXHjRh06dEivv/66/P39Va5cOaWmpio9PV2S1Lp1a917772W11aYo0ePavjw4QVev3z5sjlHwNvbWy+99FKxntEREBCg1q1bF3k3qzDe3t565ZVXNH36dG3evFkLFy7UwoULFRwcLF9fX124cMF8ZkzNmjU1fvx4h0skW8V2XSZOnKhDhw5p2LBhKl++vFJTU5WZmSl3d3c9/fTTioiIKNbx+vXrp59++kmnT5/Whx9+qKlTp173wz5twsLC1KBBA82ePVvz589XSEiIzp8/r6ysLHl6eurFF18s9uIWAAD81d30AaRevXqaOnWqli1bpv379ys5OVl5eXkKCQlRo0aNCjypvFWrVnrvvfe0ePFi/frrr0pKSlJgYKAaNWqkPn36FBhjfscdd6h27dpavny5du/ercTERHl6eqpatWpq1qyZevfuXWjnLSQkRFFRUVq4cKF27typlJQUVapUSXfccYf69+9vt3qOM3Tp0kWff/658vLy1LlzZ7slTm1sneGsrCyXnfjq5eWlyZMna8WKFdq2bZvi4+OVkJAgPz8/NWrUSF26dNF99913w51KZyrsevr5+alGjRpq0aKF+vTpU6LnU3Tu3Fnbt2+XVLzhV1fy9/fX2LFj1atXL61Zs0aHDh1SUlKS0tPTFRwcrJYtW+qOO+5Qp06dXOI61q5dW9OmTdOSJUsUExOj8+fPKygoSK1atVLfvn1LNDney8tLTz31lCZOnKjY2FgtX75c/fr1u6H63NzcNHbsWC1fvlxr165VQkKC/P391a5dOw0YMKBUloYGAOBW5WbcTAPpbxILFy7UokWL1LJlS73++utlXQ4AF2ZbBatatWoOF664+F5kGVR1/aY3e7esS7iljO92/3W9r6h2NWXd9047DwBcj5t6DggAAACAm8tNPwTrVrB+/Xp98MEHJX7fG2+8ocjI0v929Mknnyz0Kc6FiYyM1BtvvFFKFf2Xq1+7m83+/fs1YcKEEr9v5MiRhT5zpqwlJCToySefLPH7HnnkET3yyCOlUBEAAH9tBBAX0LZtW73//vslfl/lypVLoZqCJk6cWOIntpfkyec3wtWv3c2mbt2613U9r/V8krIUFhZ2XZ+pOA9xBAAAJUcAcQGBgYFOn5DuTMVZtamsuPq1u9n4+vqaq8DdKjw9PW+5zwQAwM2MAFIKBg0apEGDBpV1GQAAAIDLYRI6AAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAAAAMsQQAAAAABYxrOsCwAAFC5o1P6yLqFExpd1Abim8d3uL+sSAPzFcQcEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAAAAMsQQAAAAABYhgACAAAAwDIEEAAAAACWIYAAAAAAsAwBBAAAAIBlCCAAAAAALEMAAQAAAGAZAggAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBk3wzCMsi4CAP6qvL29lZ2dLXd3d1WpUqWsy8FNJjw8XDExMQVep13hehXWpgBn8izrAgDgryw3N1eSlJeXp/j4+DKuBrcK2hUAV0YAAYAy5Ovrq4yMDHl4eKhSpUp22xITE5WXlyd3d3dVqFChjCp0jTpcoQZXqsMmPDzc4euFtStXqZ86XLMOqfA2BTgTQ7AAwEX17NlTCQkJqlSpkr777ru/dB2uUIMr1XG9XKV+6nDNOgCrMAkdAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIZleAHARQ0aNEhpaWkKCAj4y9fhCjW4Uh3Xy1Xqpw7XrAOwCsvwAgAAALAMQ7AAAAAAWIYAAgAAAMAyBBAAAAAAlmESOgC4mPPnz+vrr79WTEyMEhIS5O/vrzp16qhnz566/fbbS+Wcv//+u0aNGqUePXpoxIgRhe534MABLVu2TMePH9fFixcVFham1q1b6+9//7sqV6583ec/d+6cli9frt27dyspKUmGYahChQpq2bKl+vbtq4oVK5Z6LRs2bNDatWt14sQJXbp0Sf7+/oqIiFCnTp107733ysPDo9RrKC1l0aaksm1XrtCmpFu7XQHXi0noAOBCTp8+rZdfflnJyclyd3dXWFiYLl++rLS0NElS3759NWTIEKefd+bMmfr++++L7Ch+9913+ve//y1J8vHxUXBwsJKTk5WTk6PAwEBNmDBBjRs3LvG5Dx48qMmTJystLU1ubm4KCwtTZmamLl26JEkKCgrSpEmTVKdOnVKrZfr06frxxx/tjnfhwgVlZWVJkiIjIxUVFSVvb+9Svx7OVlZtSiq7duUKbUq6tdsVcCMIIADgIgzD0MiRIxUXF6d69eppzJgxCg8PV15enqKjo/XRRx8pJydHY8eOVceOHZ1yzvPnz+vHH3/UF198oby8vEI7iseOHdPo0aNlGIb69++v/v37y9vbWxcvXtSMGTO0ZcsWhYWFafr06QoMDCz2+bOysvTkk08qOTlZzZo107PPPmt+w/vbb7/pvffe06lTpxQeHq6PPvpIXl5eTq9l27ZtmjJlijw8PPTUU0+pW7du8vLyUm5urlavXq1PPvlEeXl5euyxx9SvX79SvR7OVhZtSirbduUKbUq6tdsVcKOYAwIALmLz5s2Ki4uTt7e3xo8fr/DwcEmSu7u7unXrpu7du0uSFi5ceMPnWrx4sR5//HE99thjWrBggfLy8orcf8GCBTIMQ7fffrsGDx5sfmMbFBSk559/3vyW9ocffihRHdu2bVNycrKCgoI0fvx4u+EldevW1bhx4+Tu7q6zZ89q+/btpVKLbb+ePXuqR48e8vLykiR5eHioZ8+euu+++yRJMTExpX49nM3KNiW5RrtyhTYl3drtCrhRBBAAcBGbN2+WJLVr104VKlQosP2OO+6QJP3xxx+Ki4u7oXOlpKQoJydHISEhCgkJsRsCcrW0tDT98ssvkqQHHnigwHYfHx+1atVKkrR169YS1XHgwAFJUps2bRw+hO22225TlSpVJEmHDx8ulVpOnDghSWrRooXD7TVr1pQkZWRkSCrd6+FsVrYpyTXalSu0KenWblfAjSKAAIALMAxD+/fvlyQ1bdrU4T6NGjUyv0U9cuTIDZ3viSee0Ny5c80/RQ2/2b9/v/Ly8uTu7q4mTZo43KdZs2aSpOPHjys7O7vYdSQnJ0uSKlWqVOg+7u75/6vKyckplVqeeOIJjR49Wg0aNHC4/dixY5LyO65S6V4PZ7K6TUmu0a5coU1Jt267ApyBVbAAwAWcP39eFy9elCRVq1bN4T5eXl4KCQnRuXPndObMGctqO3nypCSpQoUK8vHxcbiPbUWhvLw8/fnnn6pevXqxjj127Fjl5uaanWBH546Pj5ck1ahRo1RqubqTnJubKyl/FaW1a9dq/fr18vLyMsfpl+b1cCZXblNS6V1HV2hT0q3brgBnIIAAgAuwrc4jScHBwYXuFxgYqHPnzpkrGFnBVltRdQUFBZl/L0ltRQ3RSUxM1DvvvKO8vDwFBASoU6dOWrp0aanVYjNp0iTt2bPH/DkgIECvvvqqOWSmNK+HM7lym5JK7zq6YpuSbp12BTgDQ7AAwAVc2VksqgPl5+cn6b/fplrB1tEp7BtlSfL19TX/fqO1GYahtWvX6rnnntPJkyfl6emp559/XuXKlbOklooVK6pChQrm8xnS0tL01ltv6ejRo+bPpV2DM7hym5KsvY5l3aakW6ddAc7AHRAAcAGenv/9z3FRKwfZxn0XNkSjNNg6TMWpS7qx2o4dO6ZPPvnEnI9QsWJFjRo1SpGRkZbV8swzz0jK7+Dt3LlTn332mU6fPq3Jkydr1qxZll6PG+HKbUqyrl25QpuSbp12BTgDAQQAXMCVa/rbxu07YvtWOzQ0tNRrsrEN+7jyG/WrXbntempLS0vTnDlztGbNGhmGIS8vL/Xu3Vv9+/c3v6G3qhYbDw8PtW/fXuHh4Ro5cqRSUlL0888/W1rDjXDlNiWV/u/SFduUdPO3K8AZCCAA4AIqV64sT09P5eTk6MyZMw5XzsnNzVViYqIkWTr5tGrVqpKkhIQE5ebmmt/UXunPP/+UlD+uvaQdo7Nnz2rixInmJOiOHTvqscces3t+Q2nVcujQIW3btk2+vr4aNGiQw30iIiIUHByslJQUJSQklPr1cBZXblNS6barsmxT0q3drgBnYA4IALgADw8Ps4NoWzr1aseOHVN2dnaRy3SWhsaNG0vKf8J0YUu1Hjp0SJLUpEkTubm5FfvYmZmZioqK0pkzZ1SuXDlNnDhRY8eOddhRLI1azp07p+XLl+vLL7/U5cuXHe5jGIZycnIk5c+XKM3r4Uyu3Kak0mtXZd2mpFu7XQHOQAABABfRqVMnSdLGjRt14cKFAttXrVolSWrVqpXKlStnWV3h4eGqX7++JOnbb78tsD01NVWbNm2SJHXt2rVEx169erVOnz4tX19fRUVFqXXr1pbW0qhRI7m5uckwDPOp2FeLiYkxJwhHRkaW6vVwNldtU1LptauyblPSrd+ugBtFAAEAF3HPPfeoSpUqysjI0JQpU8yhMVlZWVq4cKE2bNggT09PPfroo5bX9o9//ENubm7asmWLvvzyS3MFnrNnz2ry5MlKS0tTw4YN1aFDhxId1/ak7r/97W+qW7eu5bVUrFjRfBr47NmztWvXLhmGISl/eNKaNWs0depUSVL79u1Vo0YNp9dQmly5TUmlcx3Luk1Jt367Am6Um2H7FwEAKHPHjx/XxIkTlZKSInd3d5UvX16pqanKzMyUu7u7RowYoe7duzv9vNOmTdP69evVo0cPjRgxwuE+ixcv1vz58yXlLwcaFBSkxMREGYah8PBwTZo0SeHh4cU+p2EY6tevn3Jycop8+JrNAw88oF69ejm9lgsXLuiVV17RqVOnJOWPrw8ICFBSUpLZAWzUqJFee+01BQQElNr1KC1l1aYk69uVq7Qp6dZvV8CNYBI6ALiQ2rVra9q0aVqyZIliYmJ0/vx5BQUFqVWrVurbt68aNmxYZrX1799fdevW1YoVK/Tbb78pJSVFVatW1R133KE+ffqUeAjPxYsXzTHwtm/mi5KamloqtYSEhOjdd9/VypUrtX37dsXHxyspKUmBgYGqVauWOnfurK5duxaYFOzs61FaXLlNSc69jq7SpqRbv10BN4I7IAAAAAAswxwQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAliGAAAAAALAMAQQAAACAZQggAAAAACxDAAEAAABgGQIIAAA34LPPPpObm5vc3Nz0008/2W2766675ObmpoiICKef98SJE+Z5o6KinH78m0Fh15drA7g2AggAoEzEx8dr8eLF+vzzz/Xzzz/LMIxive+pp55SYGCg/vzzz1KuEABQGjzLugAAwF9LRkaGnnvuOc2aNUt5eXnm682bN9e8efPUtGnTQt977Ngxffrppxo3bpwqV65sRbkAACfjDggAwDJ5eXnq27evPvnkE7vwIUl79+5Vp06ddPjw4ULfP2HCBAUHB2vMmDGlXSoAoJQQQAAAlpk9e7Z++OEHSdKoUaMUGxur5ORkLVy4UBUqVFBKSoqGDRvm8L179uzRkiVLNH78eJUrV87KsgEATsQQLACAZWbPni1JGj58uKZOnWq+PnDgQFWvXl1dunTRli1bdOTIETVo0MDuvePGjVO1atX0//7f/7O0ZgCAc3EHBABgmX379kmSHn300QLbOnXqpHr16kmS9u/fb7ftp59+0o8//qioqCj5+vqWSm3ff/+9BgwYoBo1asjb21v+/v6qXbu2BgwYoOXLlxd7knxJGYahL774Qr169VK1atXk6+urmjVr6qGHHtJ33313w8dPTExUVFSUWrdurdDQUAUGBioyMlIvvfSSfv/9dyd8AiktLU1vv/222rZtq9DQUPn4+KhmzZoaMGCA1q5dW+R7L168qKlTp6pTp04KCwuTp6enQkJC1Lp1a7344os6cuSIU2q82vbt2/U///M/ioiIkK+vr8qVK6cGDRro6aefLtD+ADiZAQCARfz9/Q1JxrZt2xxur1evniHJWLJkid3r7du3Nxo0aGDk5OQ4vaZLly4ZvXr1MiQV+adLly7G+fPnC7x/zpw55j7R0dF227p06WJIMmrWrOnw3AkJCcadd95Z5Hnvu+8+48yZMwXeGxsba+4zceJEh8f/9ttvjbCwsEKP7ePjY7z11lslvGL2du/ebdx2221FfoYhQ4YYubm5Bd67fft2o3LlykW+18PDw3j33Xcdnruw63utazNhwgTDzc2t0HN6enoaH3744Q1dFwCFYwgWAMAyTZo00c6dOzV37ly1b9/ebtuWLVv022+/mfvZfP3119q+fbu++uoreXh4OL2m0aNHa+XKlZKkihUrauDAgapTp44uXbqkI0eOaOnSpUpLS9OGDRs0atQozZkzxynnvXjxorp06aJDhw5Jklq2bKnevXsrNDRUJ0+e1LJly3TixAmtXr1aPXr00KZNmxQUFFTs43///fd68MEHlZ2dLU9PTz344INq166dcnJy9Msvv2j58uW6fPmyxo0bp8zMTL322msl/gxHjhxRt27ddP78eUlS27Zt1bNnT4WEhOjAgQNasGCB0tPTNWfOHNWuXVsTJkww35uamqo+ffqYyym3a9dO999/v0JDQ5WQkKBNmzZp48aNys3N1ZgxY9SmTRvdddddJa7xanPnztUbb7whSQoLC9M//vEP1a5dW1lZWfrll1+0bNkyZWZmauTIkWrcuLHuvvvuGz4ngKuUdQICAPx1zJw505BkuLm5GS+88IIRGxtrnD9/3li0aJFRqVIlQ5LRvn17c//c3FyjcePGxu23314q9aSnpxu+vr6GJKNu3brGuXPnCuxz8uRJo2rVqoYkw9fX18jKyrLbfr13QIYOHWq+7+233zby8vLstmdkZBiDBw829xk7dqzd9qK+5U9MTDTvLFSpUsXYs2dPgfMfPnzYvHPh7u5u7N+/v/AL5UBeXp7Rrl07s4bXX3+9wD779u0z/Pz8DElGUFCQcfnyZXPbp59+ar73+eefd3iO2bNnm/sMHTq0wPbruQPSsGFDQ5IRGhpqnDp1qsAx9+/fbwQEBBiSjI4dOxbjSgAoKeaAAAAs88QTT+jee++VYRiaOnWqatWqpdDQUD3yyCNKSEhQUFCQZs2aZe7/+eef6+DBg5oyZUqp1HPgwAFlZGRIksaMGaMKFSoU2Oe2227ToEGDJOU/wyQhIeGGzxsbG2veSXnsscc0duxYubm52e3j4+Oj2bNnm0/5njFjhrKysop1/OnTp5t3FhYuXKgWLVoU2KdBgwbmtc7Ly9MHH3xQos+wZs0a7dixQ5LUpUsXh3dQIiMjNXr0aEn5d3zWrVtnbtu1a5ckydvbW5MnT3Z4jscff1wVK1aUJMXFxZWoPkdSUlLMZZ7vvPNOVa9evcA+TZo00WOPPSZJ2rFjh7Kzs2/4vADsEUAAAJbx8PDQN998o6FDh8rd3f5/QU2bNtXGjRvN4VeZmZmKiorSPffco27dupVKPRUqVNDkyZM1efJkPfDAA0XuZ+OMDulnn31mPgflhRdeKHQ/b29v/e///q8k6dKlS9q+fXuxjv/pp59Kyh/WVdSwpe7du6tWrVqS8gNFScybN8/8+8iRIwvd7+GHH5aPj498fHx04MAB8/V7771XkydP1rRp0xQYGFjo+8uXLy/JOdc9MzPT/PvevXt16dIlh/tNmjRJ+/bt0+7duwsEQwA3jjkgAABL+fn5adasWYqKitKWLVuUkZGhhg0bqm3btnadvRkzZujkyZNaunSp+Vpubq4++eQTzZo1S4cOHZKvr686d+6sCRMmqE2bNiWuJSIiwm5egiMHDx502rwPm40bN0rKD2RFPfldkt3n+vXXX9W5c+ci94+Li9PJkyclyeGdj6u1bt1asbGxio2N1cWLF4s9z2Tr1q2SJE9PT91zzz2F7te0aVPzLtOV+vTpoz59+hT6vqysLC1atMipq2BVrFhRtWrVUmxsrE6dOqX27dvrtdde0wMPPKCAgABzv/Lly5vBB4DzEUAAAGWievXqGjBggMNtFy9e1JQpU/TQQw+ZHfCcnBz169dPK1asMPe7fPmyvvnmG61atUpz587VwIEDr7ueuLg4rV+/Xnv37tXx48fNTnlaWtp1H7Mwtk51bm5ugTtBRSnO8K8rO+xz5swpUXg6d+5csQJIdna2jh8/LkmqWrXqDT0YMicnRzExMdq4caOOHDmi2NhYHT9+XH/88Ydyc3Ov+7iOuLm56aOPPlKfPn2UnZ2tAwcOaMCAAfL29la7du3UrVs3de/eXe3atSvR7wVAyRBAAAAu51//+peSk5PN1YokKSoqSitWrJC7u7uef/55PfDAA7pw4YL+9a9/adu2bRoyZIiaN2+uxo0bl+hcx48f1/Dhw/Xjjz863B4cHKzq1avbDR+6UcnJydf1vvT09FI7dnGPL0kXLlww/+5o3kxxLVmyRM8995zOnDnjcHtkZKTi4uJ08eLF6z7H1e6//35t3rxZ48aNU3R0tKT8uy2bNm3Spk2bFBUVpSpVqujpp5/WmDFj5Ofn57RzA8hHAAEAuJRz587pvffe05AhQ8ynodseVidJM2fO1JNPPmnu37t3b3Xu3Fnbtm3TW2+9pblz5xb7XPv379edd96p1NRUSVJISIg6dOigpk2bqnbt2mrRooVatmypN99806kBxDbULCQkpEQT7Js1a1bsY0v5ne3evXsX+/hVqlQp1n5Xzse43g76pEmTNHHiRPPn+vXrq23btqpfv74aNGigNm3aqHbt2oqIiHBqAJHylwtev369Tp48qVWrVmn9+vXauHGjeYfpzJkzmjhxotavX69169aVyvLPwF8ZAQQA4FLeeOMNZWdn23VOt23bpsuXL6tSpUp64okn7Pb39PTUK6+8ol69etmtslQco0ePNsPHmDFjNGnSJIdPWjec/BT0sLAwnT59Wnl5eXr66aedfmybevXqOf34Un5wsklKSirx+0+dOmWufBUSEqKlS5cW+rwNZ1/7K9WoUUPDhw/X8OHDJUm//PKLFi9erA8++MB89suyZcv08MMPl1oNwF8RAxwBAC4jLi5O//73v/XMM8/YLZGamJgoKb/D6GhVopo1a0rKv3tSXJmZmVq/fr0kqWHDhnrnnXcchg+peHMvSsK20ldqaqri4+OL3PfEiRNatGiRFi1apNOnTxf72FL+BPpriY6O1qJFi/T1119fc18bf39/1ahRQ5L022+/FTlP5uDBg4qIiFBERIRmzJghKX/FrZycHEnSSy+9VOTD/kryO72WQ4cO6auvvtJXX33lcEnjFi1a6M0339SXX35pvrZlyxannR9APgIIAMBlvPbaa/Lz89P48ePtXrc9C+LIkSO6fPlygfft3r1bklSpUqVinyspKckcSlS/fv1C98vLyyt0fsj16tq1q/n35cuXF7nvq6++qoEDB2rgwIEOV5O6WtWqVc3Ps2nTpiLnhKSkpKh3794aOHCgpk2bVqzabWyhIScnx25hgKstWbJEcXFxiouLU+3atSVJZ8+eNbfbhtk5smHDBoe/7+v1448/6uGHH9bDDz+sffv2Fbrflb+f4j57BUDxEUAAAC7hwIEDmj9/vsaMGWM3jEiSOnToIH9/f128eFFjxoyxG5Zz9uxZvfrqq5JUoueFBAcHmysd7d27t9DnTIwfP95c8clZhgwZIm9vb0nSW2+9VWhIWLt2rRYsWCAp/7kZtg78tdiGXWVmZprXxpGRI0eaz8J46qmnil2/JA0bNsz8+xtvvOEwKJw6dcqcuxMSEmKGltDQUHOfmJgYh8dPSkoyh0Y5S8uWLc2//+c//yl0P9syyZL9HSUATlK2D2IHACBf7969jcqVKxuXLl1yuH3ChAmGJEOS0bFjR+PNN980xowZY1SsWNGQZPj4+BgHDhwo0Tk7depkHrN///5GfHy8YRiGkZGRYaxatcq4++67DUlGYGCgud/mzZuN3Nxc8xhz5swxt0VHR9sdv0uXLoYko2bNmgXOPXnyZPN9zZo1M6Kjo83jJiUlGf/3f/9n+Pn5GZIMLy8vY+/evXbvj42NNd8/ceJEu23p6elGZGSkuX348OFGXFycuX3fvn3Ggw8+aG5v3769kZeXV6JrZxiG0a9fP/MYXbt2Nfbt22du27p1q10NkydPNrcdO3bMcHd3NyQZ3t7exn/+8x8jMzPTMAzDOHPmjPH+++8blStXtrv2DRo0MHJzc+2ufWHXt7Brk5OTY9SpU8fc9swzzxi///67uT0pKcmYPn26ERYWZkgyypUrZyQkJJT4ugAoGgEEAFDmtm3bZkgypk+fXug+2dnZRu/evc3O45V/PD09jQULFpT4vFu2bDG8vLzsjhUcHGy4ubmZP7du3dpYs2aN+bO3t7cREBBgHuN6A0hubq4xePBgu3N7e3sboaGhduf38vIy5s2bV+D9RQUQwzCMo0ePGjVq1LA7frly5YyAgAC71+rVq2f88ccfJb52hmEYiYmJRtOmTe2OFxAQUOAc3bp1MwOGzYgRIwr8Dq8MepKM119/3Xj22Wft6h86dOg1r29R12bt2rWGh4eH3Xn8/f2N4OBgu9fc3NyMhQsXXtd1AVA0hmABAMrcuHHjVLt2bbvlda/m6empZcuWacaMGWrRooV8fX0VEhKi3r17a+vWrRo0aFCJz3vHHXdo+fLldnNHUlJSZBiGgoODNWHCBG3dulX33HOP2rdvLyl/ToAzHk7o7u6uuXPn6v333zeHJGVlZen8+fPmELPbb79dGzdu1ODBg0t8/Hr16mnHjh165JFHzIn7qampZu2+vr4aOnSoYmJiVK1atev6DOXLl1d0dLQGDx5sniMtLc08R0BAgMaNG6dVq1aZQ85s3n//fT377LPmMLicnBxzOFhkZKRWr16t1157TcOGDTPfm5qaak5ev17dunXT999/bzf3JD09XSkpKebP9erV08qVK2/owZYACudmGKW4vh0AANeQlJSkDz/8UHfffbc6d+5cJjWkp6dr9erVOnr0qHx9fVWnTh1169bN7hkXly5d0oIFC5SYmKj69es7dWnWzMxMrVu3TkePHlVOTo6qV6+uZs2alfihioWJj4/XunXrdPr0aZUrV041atRQx44d7ZbTdeY5vLy8VK9ePXXp0kXBwcFFvu/EiRNas2aNEhMTValSJTVv3lxt2rSx2+fAgQNauXKlPD091b17dzVt2vSG6zUMQ3v27NHu3bvNVdbKly+vVq1aqVWrVg5XWwPgHAQQAAAAAJZhCBYAAAAAyxBAAAAAAFiGAAIAAADAMgQQAAAAAJYhgAAAAACwDAEEAAAAgGUIIAAAAAAsQwABAAAAYBkCCAAAAADLEEAAAAAAWIYAAgAAAMAyBBAAAAAAlvn/ixeefwi7Lm8AAAAASUVORK5CYII=" }, "metadata": { "image/png": { "height": 300, "width": 400 } }, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Writing out to individual folders : 100%|██████████| 2/2 [00:00<00:00, 15.26it/s]\n" ] } ], "source": [ "# reassigning alleles on the first set of samples\n", "ddl.pp.reassign_alleles(\n", " samples[:2], combined_folder=\"tutorial_scgp1\", filename_prefix=\"filtered\"\n", ")" ] }, { "cell_type": "code", "execution_count": 6, "id": "760adb6c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 0%| | 0/2 [00:00 ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IGH\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:41 |####################| 100% (1,841) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_heavy_parse-select.tsv\n", " RECORDS> 1841\n", " SELECTED> 833\n", "DISCARDED> 1008\n", " END> ParseDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 50%|█████ | 1/2 [00:00<00:00, 1.52it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IG[LK]\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:41 |####################| 100% (1,841) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_light_parse-select.tsv\n", " RECORDS> 1841\n", " SELECTED> 1008\n", "DISCARDED> 833\n", " END> ParseDb\n", "\n", " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IGH\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:42 |####################| 100% (2,976) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_heavy_parse-select.tsv\n", " RECORDS> 2976\n", " SELECTED> 1330\n", "DISCARDED> 1646\n", " END> ParseDb\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing data file(s) : 100%|██████████| 2/2 [00:01<00:00, 1.41it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ " START> ParseDb\n", "COMMAND> select\n", " FILE> filtered_contig_igblast_db-pass.tsv\n", " FIELDS> locus\n", " VALUES> IG[LK]\n", " REGEX> True\n", "\n", "PROGRESS> 14:58:42 |####################| 100% (2,976) 0.0 min\n", "\n", " OUTPUT> filtered_contig_igblast_db-pass_light_parse-select.tsv\n", " RECORDS> 2976\n", " SELECTED> 1646\n", "DISCARDED> 1330\n", " END> ParseDb\n", "\n", " Reassigning alleles\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "null device \n", " 1 \n", " START> CreateGermlines\n", " FILE> tutorial_scgp2_heavy_igblast_db-pass_genotyped.tsv\n", "GERM_TYPES> dmask\n", " SEQ_FIELD> sequence_alignment\n", " V_FIELD> v_call_genotyped\n", " D_FIELD> d_call\n", " J_FIELD> j_call\n", " CLONED> False\n", "\n", "PROGRESS> 14:59:09 |####################| 100% (2,163) 0.0 min\n", "\n", " OUTPUT> tutorial_scgp2_heavy_igblast_db-pass_genotyped_germ-pass.tsv\n", "RECORDS> 2163\n", " PASS> 2126\n", " FAIL> 37\n", " END> CreateGermlines\n", "\n", " START> CreateGermlines\n", " FILE> tutorial_scgp2_light_igblast_db-pass.tsv\n", "GERM_TYPES> dmask\n", " SEQ_FIELD> sequence_alignment\n", " V_FIELD> v_call\n", " D_FIELD> d_call\n", " J_FIELD> j_call\n", " CLONED> False\n", "\n", "PROGRESS> 14:59:12 |####################| 100% (2,654) 0.0 min\n", "\n", " OUTPUT> tutorial_scgp2_light_igblast_db-pass_germ-pass.tsv\n", "RECORDS> 2654\n", " PASS> 2654\n", " FAIL> 0\n", " END> CreateGermlines\n", "\n" ] }, { "data": { "image/png": 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" }, "metadata": { "image/png": { "height": 300, "width": 400 } }, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Writing out to individual folders : 100%|██████████| 2/2 [00:00<00:00, 6.90it/s]\n" ] } ], "source": [ "# reassigning alleles on the second set of samples\n", "ddl.pp.reassign_alleles(\n", " samples[2:], combined_folder=\"tutorial_scgp2\", filename_prefix=\"filtered\"\n", ")" ] }, { "cell_type": "markdown", "id": "b7587731", "metadata": {}, "source": [ "We can see that most of the original ambiguous V calls have now been corrected and only a few remain.\n", "\n", "
\n", " \n", "Note\n", " \n", "Similar to above, if you you can specify the path to the folder containing the fasta files accordingly:\n", "\n", "```python\n", "ddl.pp.reassign_alleles(samples[2:], combined_folder='tutorial_scgp2', germline=\"database/germlines/imgt/human/vdj\", filename_prefix=\"filtered\")\n", "```\n", "
" ] }, { "cell_type": "markdown", "id": "4c546938", "metadata": {}, "source": [ "## Step 4: Assigning constant region calls\n", "\n", "Cell Ranger's annotation files provides a *c_gene* column, but rather than simply relying on Cell Ranger's annotation, it is common to use *[immcantation-presto's MaskPrimers.py](https://presto.readthedocs.io/en/version-0.5.3---license-change/tools/MaskPrimers.html)* with a custom primer list. \n", "\n", "As an alternative, `dandelion` includes a pre-processing function, `pp.assign_isotypes`, to use *blastn* to annotate constant region calls for all contigs and retrieves the call, merging it with the tsv files. This function will overwrite the output from previous steps and add a *c_call* column at the end, or replace the existing column if it already exists. The Cell Ranger calls are returned as `c_call_10x`.\n", "\n", "Further, to deal with incorrect constant gene calls due to insufficient length, a pairwise alignment will be run against [curated sequences](https://immunology.sciencemag.org/content/6/56/eabe6291) that were deemed to be highly specific in distinguishing `IGHA1` vs `IGHA2`, and `IGHG1` to `IGHG4`. I have also curated sets of sequences that should help deal with `IGLC3/6/7` as these are problematic too. If there is insufficient info, the `c_call` will be returned as a combination of the most aligned sets of sequences. Because of how similar the lambda light chains are, extremely ambiguous calls (only able to map to a common sequence across the light chains) will be returned as `IGLC`. This typically occurs when the constant sequence is very short. Those that have equal alignment scores between `IGLC3/6/7` sequences and the common sequence will be returned as a concatenated call; for example, a contig initially annotated as `IGLC3` will be returned as `IGLC,IGLC3`. \n", "\n", "
\n", "\n", "Note\n", "\n", "The curated sequences can be updated/replaced with a dict-of-dict-of-dict style dictionary via the option `correction_dict`. The provided dictionary should be a nested dictionary like the following:\n", "```python\n", "primer_dict = {\n", " 'IGHG':{\n", " 'IGHG1':'GCCTCCACCAAGGGCCCATCGGTCTTCCCCCTGGCACCCTCCTCCAAGAGCACCTCTGGGGGCACAGCGGCCCTGGGC',\n", " 'IGHG2':'GCCTCCACCAAGGGCCCATCGGTCTTCCCCCTGGCGCCCTGCTCCAGGAGCACCTCCGAGAGCACAGCGGCCCTGGGC',\n", " 'IGHG3':'GCTTCCACCAAGGGCCCATCGGTCTTCCCCCTGGCGCCCTGCTCCAGGAGCACCTCTGGGGGCACAGCGGCCCTGGGC',\n", " 'IGHG4':'GCTTCCACCAAGGGCCCATCCGTCTTCCCCCTGGCGCCCTGCTCCAGGAGCACCTCCGAGAGCACAGCCGCCCTGGGC'}}\n", "```\n", "\n", "The key for the first level of the dictionary is used for searching whether the string pattern exists in the `c_call`, and the second level holds the dictionary for the the reference sequences to align to. The keys in the second level are used for replacing the existing `c_call` annotation if it is returned with the highest alignment score. The function currently only accepts 2-4 reference sequences for the pairwise alignment.\n", "
" ] }, { "cell_type": "code", "execution_count": 7, "id": "acfceb09", "metadata": {}, "outputs": [ { "data": { "image/png": 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" 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" 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" }, "metadata": { "image/png": { "height": 400, "width": 400 } }, "output_type": "display_data" } ], "source": [ "ddl.pp.assign_isotypes(samples, filename_prefix=\"filtered\")" ] }, { "cell_type": "markdown", "id": "c570ec3a", "metadata": {}, "source": [ "
\n", "\n", "Note\n", " \n", "Should you want to use a different reference fasta file for this step, run with the following option:\n", "\n", "```python\n", "ddl.pp.assign_isotypes(samples, blastdb=\"path/to/custom_BCR_constant.fasta\")\n", "```\n", "\n", "The default option will return a summary plot that can be disabled with `plot=False`.\n", "
\n", " \n", "Finally, it's worthwhile to manually check the the sequences for constant calls returned as IGHA1-2, IGHG1-4 and the light chains and manually correct them if necessary.\n", "\n", "## Step 5: Quantify mutations *(optional)*.\n", "\n", "At this stage, with all the necessary columns in the files, you can quantify the basic mutational load with `pp.quantify_mutations`, a wrapper of `SHaZaM`'s basic mutational analysis in R [[Gupta2015]](https://academic.oup.com/bioinformatics/article/31/20/3356/195677), before subsequent analyses. This will be covered again later in the `Calculating diversity and mutation` section." ] }, { "cell_type": "code", "execution_count": 8, "id": "e95fe10d", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Basic mutational load analysis : 100%|██████████| 4/4 [00:17<00:00, 4.29s/it]\n" ] } ], "source": [ "from tqdm import tqdm\n", "\n", "# quantify mutations\n", "for s in tqdm(samples, desc=\"Basic mutational load analysis \"):\n", " filePath = s + \"/dandelion/filtered_contig_dandelion.tsv\"\n", " ddl.pp.quantify_mutations(filePath)" ] } ], "metadata": { "kernelspec": { "display_name": "dandelion", "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": "3.12.9" } }, "nbformat": 4, "nbformat_minor": 5 }